# Noldus Information Technology — Full Content > This file contains the full text content of all public pages on noldus.cloud. > For a summary with links, see /llms.txt --- # Pages ## Innovative solutions for behavioral research URL: https://noldus.com/ Description: Noldus provides innovative tools and solutions for behavioral research. From video tracking to facial expression analysis, we help researchers worldwide. Advance your behavioral research Supporting behavioral scientists across human and animal research. Human Behavior pest_control_rodent Animal Behavior Human Behavior Research Gain deeper insights into human behavior in research, healthcare, education, and beyond. Human behavior pest_control_rodent Animal Behavior Research Advance animal research with reliable tools for ethology, welfare, neuroscience, and more. Animal behavior New release Built for the next generation of behavioral research Meet NoldusViso. Everything you need to record, review and manage behavioral research in one intuitive foundation. Discover NoldusViso Limited time deal Take your gait analysis to the next level Get the new CatWalk 11 package with added value for your research. Explore the offer Biotrial Fujitsu Decathlon Epoc Telenor Daiichi Sankyo Logo Antneuro Nonverbal Group Genentech Ford Gsk Lockheed Martin National Bank Canada Morse Toyota Biotrial Fujitsu Decathlon Epoc Telenor Daiichi Sankyo Logo Antneuro Nonverbal Group Genentech Ford Gsk Lockheed Martin National Bank Canada Morse Toyota Biotrial Fujitsu Decathlon Epoc Telenor Daiichi Sankyo Logo Antneuro Nonverbal Group Genentech Ford Gsk Lockheed Martin National Bank Canada Morse Toyota Biotrial Fujitsu Decathlon Epoc Telenor Daiichi Sankyo Logo Antneuro Nonverbal Group Genentech Ford Gsk Lockheed Martin National Bank Canada Morse Toyota Product advisor Find the right Noldus tool for your research Answer 4 quick questions and we will recommend the Noldus products that best fit your needs. @livewire('product-advisor') Meet NoldusViso Built for the next generation of behavioral research Everything you need to record, review and manage behavioral research in one intuitive platform. - check Synchronized multi-camera recording - check Live & post-session review - check Secure collaboration across teams Built from decades of behavioral research expertise Discover NoldusViso NoldusViso One Launch Event Watch the recording Thank you to everyone who joined the NoldusViso launch event on October 8. You can now watch the full program online, including all presentations and inspiring customer and partner stories. Watch the recording arrow_forward Leading solutions for animal behavior research Advance your research with trusted solutions for automated tracking, behavior recognition, synchronized video recording, and advanced data analysis. Whether you're studying rodents, zebrafish, insects, livestock, or wildlife, our integrated solutions help you generate reliable, publication-ready results with greater efficiency. Automated tracking across species AI-powered behavior recognition Flexible workflows for any study Reliable, publication-ready results Explore Animal Research Leading animal research solutions EthoVision DanioVision PhenoTyper CatWalk Right now, across the globe Researchers are choosing Noldus At this very moment, scientists and researchers from universities, hospitals, and labs around the world are exploring how Noldus tools can support their work. From behavioral neuroscience in Tokyo to consumer research in São Paulo. Wherever behavior is studied, Noldus is there. Why Noldus? NoldusCare Your research. Our priority. NoldusCare helps you stay focused on your research, not on technical challenges. From study setup and data collection to analysis and reporting, our team is here to support your work every step of the way. With expert assistance, automatic upgrades, and access to Noldus Academy, you can keep your projects moving forward with confidence. headset_mic Unlimited access to our support helpdesk Get expert help when you need it. Our team is here for you. cloud_download Upgrades automatically Stay up-to-date with the latest features and improvements. Access to Noldus Academy Expand your knowledge with exclusive training and resources. Learn more about NoldusCare Learn more about NoldusCare Build the perfect research lab Design a research environment that fits your research, not the other way around. We combine eye tracking, video, physiological measurements and software into one seamless solution: - Tailored to your methodology - Fully integrated hardware & software - From single observation rooms to complete research facilities See our lab solutions What we believe in Three guiding principles that shape everything we do at Noldus. Our Mission It is our mission to provide innovative tools for behavior, health, and wellbeing: from data collection to insights discovery. Our Vision Measuring behavior makes a difference! Empowering customers with best in class tools to revolutionize behavioral research. Our Team Our people are our greatest strength. With backgrounds in behavioral science, engineering, and technology, we work together to create innovative solutions that help researchers make a difference. --- ## Why Noldus? URL: https://noldus.com/about Description: We help you to improve your research, inspired by scientific and societal challenges. So together, we respond to the demands of today and prepare for those of tomorrow. 6 reasons to help you decide Why Noldus? Choosing the right research tools is one of the most important decisions you'll make for your lab. Here's why thousands of behavioral researchers worldwide trust Noldus, and keep coming back. 6 reasons to help you decide The story behind Noldus Noldus began not as a company, but as the curiosity of a scientist. A scientist's challenge In the late 1980s, while studying the behavior of parasitic wasps at Wageningen University, Lucas Noldus faced a simple challenge: there was no efficient way to record behavior. So he created his own solution. What started as a personal tool quickly drew interest from researchers around the world - and revealed a much bigger opportunity. From PhD to company In 1989, shortly after completing his PhD, Lucas founded Noldus Information Technology. With modest means but a clear vision, he built a company grounded in curiosity, scientific thinking, and a drive to improve how research is done. From the start, growth was steady and organic, shaped by a team that shared this mindset. Growing together Collaboration has always been at the heart of Noldus. Early partnerships and close connections with the scientific community helped shape the company and continue to define it today. As Noldus expanded from Wageningen to a global presence, that same spirit of working together remained unchanged. Today, Noldus is still driven by people - by curiosity, collaboration, and the desire to understand behavior. The question that started it all continues to guide us forward. 6 reasons to help you decide Why Noldus? Choosing the right research tools is one of the most important decisions you'll make for your lab. Here's why thousands of behavioral researchers worldwide trust Noldus, and keep coming back. Contact us 50.000+ publications More than 50,000 peer-reviewed studies cite Noldus tools, across neuroscience, psychology, pharmacology, and beyond. When you choose Noldus, you're building on a foundation the scientific community has validated for decades. 12,000+ groups trust Noldus From Harvard and Oxford to NASA and AstraZeneca, leading institutions across 100+ countries rely on Noldus every day. Whatever your field or scale, you're in good company. history 35+ years of experience Since 1989, behavioral research has been our sole focus. We don't make generic data tools, we build solutions designed specifically around the way researchers think, work, and discover. NoldusCare Getting a tool is one thing, getting the most out of it is another. NoldusCare connects you with dedicated behavioral research experts who understand your work, so you always have the right support at the right moment. Noldus Academy Hit the ground running and keep growing. Noldus Academy offers training, workshops, and resources designed to help you and your team master your tools, sharpen your methods, and stay ahead in your field. Ethics & responsibility Rigorous research demands rigorous ethics. We have explicit, published positions on animal testing and facial expression analysis, because we believe the tools you use should reflect the standards you uphold. A worldwide Noldus network Trusted by 12,000+ research groups Our customer base says it all. Since 1989, we have partnered with start-ups, Fortune 500 companies, small universities, and top research institutions worldwide. With decades of innovation and collaboration, we have achieved great success and built lasting relationships. Ready to get started? Let's talk about your research Whether you're setting up a new lab, upgrading your tools, or exploring what's possible - we're here to help. Tell us about your research and we'll show you how Noldus fits in. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## Ethics and animal testing URL: https://noldus.com/about-noldus/ethics-animal-testing Description: Noldus Information Technology provides tools for the study of animal behavior. Please find our view on ethics and animal testing on this page How Noldus tools help refine and reduce the use of experimental animals Ethics and animal testing Noldus Information Technology provides tools for the study of behavior, both animal and human. Because laboratory testing is one of the fields of research where our tools are applied, we feel it is important to state our view on the ethics of animal testing. The necessity and legislation of animal testing Animals are sentient beings – they deserve our respect. They are valuable in many ways, which includes their invaluable contribution to scientific research, so we need to provide them with what they need for a good life, as much as we can. Noldus IT feels strongly that animal testing should be kept to a minimum and that unnecessary tests should not be performed. While we cannot say that all animal testing is unnecessary, what is and what is not necessary remains the subject of a scientific and societal ethical discussion in a democratic society. In many countries, there is clear and strict legislation, even stricter than the laws that protect our own pets. Researchers have to carefully consider and argue the importance of their experiments. This includes review by an expert animal ethical committee, so that the relevance for human health against the distress of the animal are always carefully weighed. Our ambition is to provide our customers with the tools they can use to get valuable research results while optimizing the level of animal welfare to a level that is well above what legislation requires. The three R's are good guidelines, which we think all modern biomedical research should comply with. The 3Rs principle swap_horiz Replacement Wherever possible, use non-animal alternatives (e.g. cell culture tests, computer models/simulations). tune Refinement Modify techniques so that tests are less invasive, causing less pain and distress, and by enriching the test environment, allowing animals to perform natural behavior. compress Reduction Refine methods so that fewer animals are needed to get valid results, e.g. by multimodal approaches and by increasing the accuracy of measurements. Wellbeing of animals versus curing diseases When it comes to biomedical research, there must be a balance between the wellbeing of animals and developing new cures for human diseases. Unfortunately, for many disabling and life-threatening brain diseases such as Parkinson's and Alzheimer's, there is no cure yet. As a society, we have committed ourselves to finding ways to improve the quality of life for people suffering from these diseases. The brain is the most complex human organ, and its ultimate read-out – behavior – can only be tested in an intact organism. These treatments cannot be developed without at least some animal testing. Animal testing for the more non-essential things in life, such as cosmetics, is something we do not approve of, and fortunately this is forbidden in many countries. What we do to improve animal welfare Noldus IT does not perform animal tests. However, we do develop software and equipment that finds its application in animal behavior research. We strongly believe that our products can improve science and contribute to the refinement and reduction of the use of animals. Our software products facilitate the complete automation of tests. This limits handling and so stress to the animal and in many cases allows for tests to be done in the animal's home cage. Our home cage observation system provides an enriched environment for the animals. Our solutions are more accurate and less prone to error than manual methods. They deliver objective data, meaning that fewer tests with fewer animals yield the same valid results. The development of solutions to test other organisms, such as zebrafish larvae and invertebrates, gives scientists the opportunity to replace tests previously performed with mammals. The importance of welfare to good science Implementing measures to improve animal welfare is not only in the interest of the animals, but of science as well. The way animals are housed and treated affects their physiology and behavior, and so has a major impact on the validity and reproducibility of the scientific results. Naturally, science benefits if researchers can make sure that the effects they are measuring are actually from the experiment they are conducting and not from any housing condition, handling, diet, etc. that is outside the scope of the research. For more information, please see Speaking of Research. Noldus IT actively participates in initiatives aimed at improving the quality of animal research. Noldus Information Technology is also a signatory to the Transparency Agreement on Animal Research. The 3Rs Collaborative Noldus is a member of the 3Rs Collaborative, an organization based in the US which works for Reduction, Refinement and Replacement of animal testing. We are especially active in the working group Translational Digital Biomarkers. Translational digital biomarkers are objective physiological and behavioral data which are collected using digital technologies such as Noldus' solutions. Wildlife preservation & farm animal welfare Noldus IT is about making tools for behavioral research, and our tools are often applied in wildlife studies, studies on zoo animal behavior, welfare studies in farm animals, and human-pet interaction studies. These are non-invasive behavioral studies on animals performed in their natural environments or habitats. They have led to results that are important for wildlife conservation, increased wellbeing of farm and zoo animals, and better understanding of pet-owner relationships. --- ## Ethics in facial expression analysis URL: https://noldus.com/about-noldus/ethics-facial-expression-analysis Description: FaceReader is a software tool for scientific research into facial expression analysis, in areas such as human communication and human-machine interaction. FaceReader Ethics in facial expression analysis FaceReader is a software tool for scientific research in areas such as human communication, emotions and human-machine interaction. It is used in over 1,000 universities, research institutes and corporate R&D laboratories around the world. Examples of research applications family_restroom Research into adequate emotional responses of parents when infants are crying restaurant Relationship between food choice, emotions and depression cardiology The role of physicians' bias in working with depressed cardiac patients nutrition Acceptance of healthier food by consumers, for example containing less salt or meat substitutes devices User experience assessment of digital media healing Pain experience by people who cannot express themselves, for example babies or patients with dementia What FaceReader analyzes FaceReader analyzes basic facial expressions, facial action units, affective states, valence and arousal. In addition, it can measure facial gestures, head orientation, chewing, talking, and much more. FaceReader is not capable of recognizing or identifying faces or people, and therefore unsuitable for mass surveillance of people for security purposes. It is also impossible to use FaceReader as a 'lie detector'. Nevertheless, we fully understand that there can be some discomfort about technology that is capable of analyzing facial expressions. Therefore, Noldus disapproves of the use of FaceReader without informed consent from the individuals whose facial expressions are being captured. Informed consent How consent is obtained may differ depending on the application, but the responsibility for acquiring consent rests with the user of the software. Consent can be obtained by an explicit opt-in before the software is being activated. A notification that makes it clear to persons that they can decide whether or not to participate may be suitable. It should be made clear what the collected information will be used for, with whom it will be shared, and where, how, and for how long it will be stored. Sustainable development and quality of life With the development of tools for measuring behavior, health, and wellbeing, Noldus Information Technology wants to contribute to sustainable development and quality of life. Face reading has the potential of being a powerful technology contributing to this ambition. Consequently, we have a strict policy related to the use of FaceReader, including embedding it into third-party products, services or systems, which requires prior approval of Noldus Information Technology. Applications we do not allow Our software is designed specifically for research or training. Noldus Information Technology does not allow the use of FaceReader for the following applications: block Active defense, i.e. embedding FaceReader in a weapon system. block Biometric data collection in criminal, security-related or similar investigations or procedures. block Surveillance of people in public spaces for security purposes. block Any other use that may potentially violate fundamental human rights. Noldus Information Technology will not sell FaceReader to customers who intend to use the product for such applications. When applicable, we may ask customers to provide an end-use statement. --- ## Gender Equality Plan URL: https://noldus.com/about-noldus/gender-equality-plan Description: Noldus Gender Equality Plan - Committed to an inclusive and equitable workplace Gender Equality Plan (GEP) Committed to an inclusive and equitable workplace At Noldus Information Technology BV, we believe that a diverse and inclusive environment helps people thrive and strengthens our organization. Gender equality is a core part of who we are. This Gender Equality Plan (GEP) outlines our commitments, actions and monitoring processes to promote fairness, equal opportunities and a safe workplace for everyone. Foundations of Our Gender Equality Plan Our GEP is a formal document, approved by our CEO and publicly available on our website. We review and update it regularly. We allocate dedicated time, expertise and HR capacity to ensure that gender equality is embedded in our daily work and long-term strategy. Each year, we collect and analyze gender-disaggregated data across recruitment, promotions, leadership representation, contract types, training participation and pay structures. These insights help us track progress and identify where improvement is needed. We also offer regular training on gender equality, unconscious bias, inclusive leadership and respectful workplace behavior - for all employees, including management. Key Focus Areas Work-Life Balance & Culture We support a healthy balance between work and personal life through flexible working arrangements, support for parental leave and a culture that values wellbeing and respect. We want everyone to feel safe, supported and able to grow. Gender Balance in Leadership We aim for balanced representation in leadership and decision-making roles by monitoring gender ratios, developing diverse talent pipelines and ensuring equal access to leadership development opportunities. Equal Opportunities in Recruitment & Career Growth We ensure fairness throughout the employee journey through inclusive job descriptions, transparent and bias-aware recruitment processes, equal access to training and mentoring, and careful monitoring of promotion patterns. Gender Dimension in Research & Innovation Where relevant, we integrate gender perspectives into our research, innovation processes and educational content to strengthen quality and societal impact. Preventing Gender-Based Violence & Harassment We maintain a zero-tolerance policy towards gender-based violence, discrimination and sexual harassment. Our approach includes clear and confidential reporting procedures, support for affected employees, and fair and timely investigations. Monitoring & Governance We evaluate progress annually and share findings with management and employees. Based on these insights, we update our goals and actions to keep improving. Implementation is overseen by our HR Department, CEO and designated Gender Equality Lead, ensuring that gender equality remains a strategic priority. Our Promise We are committed to building a workplace where everyone feels valued, respected and empowered - regardless of gender. This plan is an important step in that ongoing journey. Published: April 2026 - Approved by Jay de Groot, CEO --- ## Modern Slavery Act - Transparency Statement URL: https://noldus.com/about-noldus/modern-slavery-act-transparency-statement Description: Noldus Modern Slavery Act Transparency Statement - Zero tolerance approach to modern slavery Modern Slavery Act - Transparency Statement Introduction This statement sets out the steps and measures that Noldus Information Technology ("Noldus") has taken and is continuing to take to ensure that modern slavery is not taking place within our business or first line supply chain. Modern slavery encompasses slavery, servitude, human trafficking and forced labor. Noldus has a zero-tolerance approach to any form of modern slavery and we are committed to acting ethically and with integrity and transparency in all business dealings and to putting effective systems and controls in place to safeguard against any form of modern slavery taking place within our business or supply chain. Our organization Noldus is an innovative product developer providing software, hardware and integrated solutions for animal and human behavior research, addressing important societal challenges. We help our customers improve their research, inspired by scientific and societal challenges. Our technologies and tools are designed to enhance health and wellbeing, and to contribute to sustainable development and quality of life. We are headquartered in Wageningen, The Netherlands, but act globally via our own offices and representatives, and our products and services are sold and marketed through a well-developed collaboration with and network of distributors, system integrators and resellers. Our code of conduct Noldus is committed to conducting business in an honest, fair and transparent way. Noldus adheres to the OECD Guidelines for Multinational Enterprises and the United Nations Guiding Principles on Business and Human Rights. These provide principles and standards for responsible business conduct in a global context consistent with applicable laws and internationally recognized standards. These publications are multilaterally agreed and comprehensive codes of responsible business conduct that governments have committed to promoting. The Noldus Code of Conduct defines the values and guidelines upon which Noldus conducts its business. The Code of Conduct applies to everyone who works for Noldus worldwide and to anyone representing Noldus in any way. We also expect our business partners, including any subcontractors they engage with in relation to their business with Noldus, to comply with this Code of Conduct. The Code of Conduct is based on the UN Global Compact's ten principles, the UN Declaration of Human Rights and the International Labor Organization's Declaration on Fundamental Principles and Rights at Work. The company management ensures that business is conducted in an ethical way and in accordance with the Code of Conduct and the company's policies are continually reviewed. In addition to the Code of Conduct, Noldus operates a whistleblowing policy so that all employees know that they can raise concerns about how colleagues are being treated, or practices within our business or supply chain, without fear of reprisals. Risks Noldus considers the issues and risks covered by the UK Modern Slavery Act, and even if we deem them to be non-existent within our own operations, we are well aware that the risks are higher in our supply chains. Noldus therefore undertakes extensive work in the selection of suppliers as well as following up supplier compliance with audits. Our suppliers Suppliers are classified based on risk level, taking into account the country in which the supplier conducts its business, credibility and previous evaluations (if such exist). We are committed to ensure that modern forms of slavery are absent in our supply chains. We carefully select our suppliers for manufacturing and assembly of the company's products. The selection takes into account employee working conditions such as freedom to join a trade union, business ethics, and respect for human rights. All new suppliers are initially evaluated before collaboration is initiated. Suppliers are also expected to comply with the Noldus Supplier Code of Conduct, which is based on the Noldus Code of Conduct and the UN Global Compact 10 principles in the areas of human rights, labor, environment and anti-corruption. This includes requirements prohibiting any form of child or compulsory/forced labor and ensuring good working conditions. Noldus expects the supplier to use reasonable efforts to promote compliance with the Noldus Supplier Code of Conduct among its suppliers. Audits of critical suppliers are carried out throughout the contract time. The supplier audits aim to follow up and ensure that suppliers meet the requirements in the Supplier Code of Conduct. The Supplier Assessment form checks, for instance, whether suppliers published a modern slavery/human trafficking statement on their website. If it should become apparent that a supplier does not meet Noldus requirements, the supplier will be phased out if it does not implement corrective actions. Training All employees must comply with Noldus Code of Conduct and the corporate culture and values are important parts of the onboarding program for new employees as well as in other training and employee programs. Our performance indicators We will know the effectiveness of the steps that we are taking to ensure that modern slavery is not taking place within our business or supply chain if no reports are received from (a) the employees of Noldus who work dedicatedly to uphold Noldus core values and Code of Conduct, or (b) the public or law enforcement agencies to indicate that modern slavery practices have been identified. Furthermore, the audits we conduct and on-premise visits at our suppliers also serve as performance indicators in relation to our Code of Conduct. Approval for this statement This statement was approved by the Executive Board of Noldus Information Technology on April 29, 2025. Jay de Groot - Noldus Information Technology --- ## HIPAA, GDPR & FERPA Compliant Video Recording URL: https://noldus.com/about-noldus/security-legislation-noldusviso Description: HIPAA, GDPR, and FERPA compliant video recording software for labs and clinics. ISO 27001 certified. Your data stays on your own network, never on ours. NoldusViso HIPAA, GDPR, and FERPA compliant video recording for research and clinical labs NoldusViso, the Noldus AV recording tool, is used across psychology, healthcare, education, user experience research, and more. In every one of these fields, NoldusViso is built to protect your data. Data protection is a fundamental right to privacy. On a practical level, it's what makes trust between people and organizations possible. verified_user Noldus Information Technology, Wageningen is ISO/IEC 27001 certified. Our information security management system is independently audited by an accredited certification body. ISO 27001 Certification Your data never leaves your control NoldusViso is a hybrid system. It's installed locally, connects to your own network, and connects to the internet only if you want it to. Your recordings stay on your infrastructure, inside your security perimeter, under your administrators' control. Noldus never receives, stores, or processes the data you collect. It is never on a Noldus server and never in Noldus storage. Noldus does not require access to any video files, secure health information, or educational records. Even when we provide technical support or perform upgrades, all our activities are carried out independently of participant information access. Noldus does not maintain an active connection to any NoldusViso system at any time. Such a connection can only be initiated, authorized, and supervised by NoldusViso users. Because your research data never reaches us, there's no third-party cloud in the chain, no data transfer to authorize, and no list of external processors to review. How NoldusViso is secured password Password encryption NoldusViso can integrate with your own LDAP or generate encrypted local credentials. Passwords must contain at least 8 characters with at least one uppercase, one lowercase, one number, and one special character. They must not contain your username nor match any of your last three passwords. Two-factor authentication protects every account, including administrators. manage_accounts Sophisticated user management Configurable, role-based access control and user roles determine who can see, play, export, or delete each recording. lock Encryption in transit All traffic between clients, cameras, and the server is protected with strong encryption in transit. enhanced_encryption Encryption at rest NoldusViso facilitates encryption at rest, so recordings can be protected on your own storage under your own key management. Retention policies Your administrator sets retention periods. Recordings and audit data are removed automatically when the period expires. There is no manual clean-up and no forgotten archives. history Audit trails Every login, view, export, and administrative change is logged and time-stamped, with configurable retention. A complete log of all activity regarding video creation, deletion, and access. The retention period can be set to comply with GDPR and HIPAA. videocam_off Privacy switches Physical privacy switches let participants and staff see, and control, when a room is live. Turn on a black mask within the camera itself and use an optional light to indicate live or recording feed status. memory Modern technology stack NoldusViso is built on a modern technology stack, easy to update and upgrade to meet the latest security demands, and easy to support and maintain. If necessary, and only after customer approval and coordination, a remote connection can be made to provide technical support. Applicable legislations Noldus complies with the governing laws presiding over our customers' data protection. The legislation of the European Union (EU) and the United States (US) is most prominent. gavel GDPR In the EU, the General Data Protection Regulation (GDPR) went into effect on 25 May 2018. GDPR applies to all forms of data that target or are collected in relation to people in the EU. As a global professional IT company, Noldus complies with all GDPR regulations. Under the GDPR, your organization is the controller of the recordings you make. Because NoldusViso runs on your own infrastructure and Noldus never receives your data, we are not a processor of your research data. There's no transfer outside your organization to safeguard and no external processor in the chain. You set retention periods, you control access through role-based permissions, and every access is logged. Noldus has an appointed Data Protection Officer for the personal data we hold as a company, such as contact details. See our Privacy Policy. health_and_safety HIPAA / HITECH HIPAA protects patients' medical records with rules on collecting and storing patient information. HITECH supports health information management across computerized systems and the secure exchange of health information. For HIPAA and HITECH, the architecture does most of the work. Protected health information (PHI) stays inside your network: NoldusViso is installed locally, connects to your own systems, and reaches the internet only if you allow it. Noldus never receives recordings or health information. On top of that, technical safeguards are built in: two-factor authentication (2FA), role-based access control down to the individual recording, strong encryption in transit, facilitated encryption at rest, automatic logout, administrator-set retention periods, and a complete, time-stamped audit trail of every access and export. Do you need a Business Associate Agreement (BAA)? No. Because NoldusViso runs on your infrastructure and Noldus doesn't access recordings or health information, Noldus is not normally a Business Associate under HIPAA. If your organization's policy requires an agreement, contact us and we'll review it with you. FERPA Recordings of students are education records under FERPA. NoldusViso keeps them inside your institution's own network, restricts access through role-based permissions, logs every view and export, and lets you set automatic retention periods per study. Three layers of security admin_panel_settings Administrative Policies and procedures for selecting, developing, and maintaining security measures, plus employee training on identifying protected data. lock Physical Facility, workstation, and mobile device security is the responsibility of NoldusViso users, since Noldus never collects or transfers data. shield Technical Built-in user management with access levels, TLS encryption in transit, audit trail functionality, and automatic logout. upcoming Coming soon VPAT and EU AI Act statement We are preparing a Voluntary Product Accessibility Template (VPAT) and a statement on how NoldusViso relates to the EU AI Act. These will be published here. Need them for a review already in progress? Contact us and we'll help. Certifications verified_user ISO/IEC 27001 Noldus Information Technology is ISO/IEC 27001 certified, independently audited by an accredited certification body. Read more. gavel GDPR GDPR has no statutory compliance certification. All Noldus software and activity, including NoldusViso, is carefully screened against GDPR requirements. health_and_safety HIPAA HIPAA rules don't certify software or off-the-shelf products. Every Noldus employee who may be exposed to protected health information completes a training course. fact_check Risk assessment documentation Completing a security questionnaire or a vendor risk assessment? Send it to us — we're happy to help. Contact us Last reviewed: August 2026 · Version 2.0 --- ## Solutions for Animal Behavior Research URL: https://noldus.com/animal-behavior-research Description: Automate your animal behavior research, professional software, hardware, and solutions for high-quality data in academia, education, and industry Overview Trusted by Solutions CatWalk Examples Tools Contact track_changes Automated tracking & behavior Automatically track with validated accuracy across a wide range of learning, memory, social interaction, and more. insights Data insights Transform complex behavior into clear, actionable insights. settings_input_component Hardware interaction Integrate with a variety of hardware for precise control and triggering. Our solutions for Animal behavior Automate your research, save time, and get high-quality data for your project or publication. Whether you’re in academia, education, or a commercial field, Noldus is here to help you. Harvard University Wageningen University University of Cambridge Boehringer Ingelheim University of Oxford Bayer MIT AstraZeneca ETH Zürich Stanford University Caltech Charles River Novartis Brown University Yale University The Jackson Laboratory NeuroSys Harvard University Wageningen University University of Cambridge Boehringer Ingelheim University of Oxford Bayer MIT AstraZeneca ETH Zürich Stanford University Caltech Charles River Novartis Brown University Yale University The Jackson Laboratory NeuroSys Product advisor Find the right Noldus tool for your research Answer a few quick questions and we will recommend the Noldus products that best fit your needs. @livewire('product-advisor', ['presetSubject' => 'rodents']) Limited time deal Take your gait analysis to the next level Get the new CatWalk 11 package with added value for your research. Explore the offer I am looking to measure Find the right way to understand it this.updateMax()); }, updateMax() { if (this.container) this.maxScroll = this.container.scrollWidth - this.container.clientWidth; }, scrollLeft() { this.scroll = Math.max(0, this.scroll - this.cardWidth); this.container.scrollTo({ left: this.scroll, behavior: 'smooth' }); }, scrollRight() { this.scroll = Math.min(this.maxScroll, this.scroll + this.cardWidth); this.container.scrollTo({ left: this.scroll, behavior: 'smooth' }); }, goTo(index) { this.scroll = index * this.cardWidth; this.container.scrollTo({ left: this.scroll, behavior: 'smooth' }); } }" class="relative overflow-hidden"> chevron_left Cognition and memory Cognition and memory refer to how the brain processes, stores, and retrieves information. Relating behavior to these internal processes helps understand conditions like Alzheimer's and trauma. Learn more arrow_forward Social interaction Social behavior offers insights into behaviors like aggression and cooperation, relevant to studying conditions like ASD or schizophrenia. Social housing is also often required to meet ethical standards. Learn more arrow_forward Zebrafish research Zebrafish are a popular model organism due to its size, reproduction, growth rate and genetic similarity to humans. Noldus offers tools to analyze (zebra)fish behavior across their entire life cycle. Learn more arrow_forward Home cage & welfare Continuous monitoring in a familiar cage captures natural behavior and provides accurate insights into an animal's activity, feeding and drinking, and sleep cycles over a longer time period. Learn more arrow_forward Fear & anxiety Many psychiatric disorders are fear or anxiety related. Behavioral tests with animals are crucial to link underlying mechanisms to potential treatments for disorders like PTSD or depression. Learn more arrow_forward Gait & locomotion Studies on the gait of rodents assess motor function and the impact of certain treatments on coordination and behavior. This type of research is essential in Parkinson's, ataxia and injury research. Learn more arrow_forward Ultrasonic vocalizations Vocalization research is done in rodents, birds and other mammals. Analyzing vocalizations provides insights into communication or stress, enhancing research in neuroscience and pharmacology. Learn more arrow_forward Zoology Studying animal behavior has come a long way from manual pen-and-paper methods. Advances in technology now provide faster and more accurate ways to record and analyze behaviors. Learn more arrow_forward Noldus in real-world research See how researchers are using advanced tools to enhance their work Zebrafish Zebrafish research with Noldus tools Take a look at the Gerlai Lab In Toronto, seasoned veterans and students alike are using Noldus tools to develop new techniques and do groundbreaking behavioral research using zebrafish. Learn from them why zebrafish are an excellent model species and why Noldus' tools work for them. Neuroscience Neurobiological mechanisms linking stress and obesity Learn from Dr. Figueroa We talked with Dr. Johnny Figueroa about his work in nutritional neuroscience. His work contributes to understanding the mechanisms behind childhood obesity and stress. In his tests he uses Noldus tools to capture long term behavioral patterns in rodents. Find the right tool for the job I am performing animal behavior research with: pest_control_rodentRodents waterFish petsOther animals Automated video tracking for any arena EthoVision The gold standard for automated video tracking of laboratory animals. Track movement, measure activity, and analyze behavior patterns with precision in up to two rodents housed socially. Perfect for studying activity, anxiety, learning, and memory. Learn more arrow_forward Objective gait analysis system CatWalk Automated gait analysis for objective assessment of locomotion and motor function. Measure paw prints, stride patterns, and coordination with unparalleled accuracy. Essential for pain research, neuroscience, and pharmacological studies. Learn more arrow_forward Versatile instrumented observation cage PhenoTyper Continuous monitoring in a home cage environment captures natural behaviors and provides accurate insights into animal activity, including feeding, drinking, and sleep cycles. Ideal for short- and long-term behavioral tests. Learn more arrow_forward Capture ultrasonic vocalizations in rodents UltraVox Animal vocalizations are often analyzed to generate a more complete view of the animals' affective states. UltraVox offers advanced capabilities that streamline the analysis of vocalizations, providing you with detailed insights to advance your research. Learn more arrow_forward Streamline animal observational research The Observer Simply observing animals is still a key part of rodent neuroscience research. The Observer allows you to easily annotate behavior and synchronize it with multiple datastreams. Learn more arrow_forward Video tracking for any tank or well plate EthoVision The gold standard for automated video tracking of any fish. Track movement, measure activity, and analyze behavior patterns with precision using powerful AI-based video trackers. Perfect for studying swim patterns, anxiety, learning, and memory. Learn more arrow_forward High-throughput testing of zebrafish larvae DanioVision High-throughput video tracking system designed specifically for zebrafish behavioral research. Track multiple larvae or adult fish simultaneously with precise environmental control. Perfect for toxicology, drug screening, and developmental studies. Learn more arrow_forward Detailed look at fish physiology and behavior DanioScope Measure physiological parameters such cardiovascular measurements, morphology, and gut and blood flow in zebrafish larvae and embryos. Batch acquire multiple videos saving you time and resources. Learn more arrow_forward Streamline animal observational research The Observer Simply observing animals is still a key part of fish neuroscience research. The Observer allows you to easily annotate behavior and synchronize it with multiple datastreams. Learn more arrow_forward Automated video tracking for any application EthoVision The most versatile tracker for any application. Track movement, zone preferences and activity with precision. Perfect for studying any animal you can capture with a camera. Learn more arrow_forward Streamline animal observational research The Observer Simply observing animals is still a key part of behavioral research. Whether you are looking at farm animals, insects or wildlife, The Observer allows you to easily annotate behavior and synchronize it with multiple datastreams. Learn more arrow_forward High throughput insect tracking EntoLab Looking for a tool to speed up insect or plant screening? EntoLab is a computerized system for automated high-throughput screening of insect behavior, validated for many insect-plant combinations. Learn more arrow_forward Capture ultrasonic vocalizations UltraVox Animal vocalizations are often analyzed to generate a more complete view of the animals' affective states. UltraVox offers advanced capabilities that streamline the analysis of vocalizations, providing you with detailed insights to advance your research. Learn more arrow_forward Want more information? Meet with an expert in your field Do any of these solutions sound interesting to you? But do you want more info regarding your specific use case? Feel free to book a meeting with us. We have a dedicated team of behavioral experts that are ready to help you find the solution fit for your research. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## The AV Lab: Buyer's guide and ultimate how-to URL: https://noldus.com/av-lab-guides Description: An AudioVisual lab is designed to allow you to observe your test participants unobtrusively. The e-book contains all the steps for setting up your AV lab. Free Free buyer's guide The AV Lab: Buyer's Guide and Ultimate How-To Planning to set up or upgrade an audiovisual observation lab? This guide walks you through everything you need to know — from choosing the right cameras and microphones to designing your room layout and selecting recording software. What you will learn: - checkHow to choose the right cameras and audio equipment - checkRoom design and layout best practices - checkRecording and streaming options - checkIntegration with behavioral coding tools - checkScaling from single-room to multi-room setups Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free What makes a great observation lab? A well-designed audiovisual lab enables researchers to capture natural behavior with minimal intrusion. The right combination of hardware, software, and room design ensures high-quality recordings that are easy to analyze. Whether you are building a usability lab, a clinical observation room, or a multi-purpose research facility, this guide helps you make informed decisions at every step. This guide covers: - checkCamera selection and placement - checkAudio recording best practices - checkOne-way mirrors and observation rooms - checkLive streaming and remote observation - checkData storage and security --- ## CageIQ URL: https://noldus.com/cageiq Description: CageIQ - A revolutionary partnership in animal welfare monitoring by Noldus and Lab Products A revolutionary partnership in animal welfare monitoring Two names you trust, with one new goal For over 30 years Noldus has helped researchers turn behavior into data. For more than 50 years, Lab Products has built housing systems facilities rely on every day. Now, Noldus and Lab Products are joining forces, with industry experts, to pioneer a new approach to animal welfare monitoring; CageIQ. This is the beginning of a journey that will elevate automated welfare monitoring to new heights, and we’re inviting you to be a part of that journey as it progresses into an accessible, retrofit approach that puts animal welfare, research, and value in the forefront. Stay in the loop when more information becomes available Do you want to receive regular updates on this new collaboration? Be the first to get more news by signing up for our exclusive CageIQ mailing list. Thank you! You are now on the CageIQ mailing list. We will keep you updated. First name * Last name * Email * By signing up, you consent to Noldus processing your data as described in our privacy policy. Sign up for updates sync Signing up... --- ## CatWalk URL: https://noldus.com/catwalk Description: CatWalk XT is a complete gait analysis system for quantitative assessment of footfalls and locomotion in rats and mice. CatWalk How It Works Limited Time Deal Analysis What's Included Features Explore Success Stories FAQ Contact Accurate high quality gait data CatWalk Assess natural free walking gait and locomotion data in rodents. CatWalk collects over 50 precise and validated gait parameters, allowing you to perform in depth research on various gait-related disease models. Explore limited time deal arrow_downward Natural walking low light stress free method Easy to use save time and resources Versatile system one device for all small mammals How does CatWalk work? Train Properly training your animals is essential in obtaining natural and consistent data videocam Record As the animal traverses the walkway a high-definition camera automatically captures and classifies the footprints analytics Analyze Choose the parameters you want to analyze and instantly have access to your data and graphs Limited time deal Gait analysis has never been more accessible CatWalk is the most used gait analysis system worldwide, and now is the best time to add one to your lab. - check New CatWalk 11 hardware with high-quality camera - check Intuitive software allowing for detailed gait analysis - check Additional remote training and installation assistance All of this for only €39.500 *Desktop not included. Receive a quote Powerful analysis. Meaningful insights. CatWalk XT transforms every footprint into objective, reproducible gait data. From automatic footprint classification to detailed measurements and comprehensive gait parameters, every step is analyzed with precision. Automatic Footprint Classification Automatically identify and classify every footprint with confidence. CatWalk XT minimizes manual work while giving researchers full control to review and refine classifications whenever needed. Interactive Footprint Measurement Explore every footprint in detail with powerful interactive measurement tools. Analyze toe spread, print length, paw angle, and other key characteristics to uncover deeper insights into gait and locomotion. Comprehensive Gait Parameters Go beyond footprints with more than 50 validated gait and locomotion parameters. Analyze stride length, cadence, swing, stance, paw pressure, and more to gain a complete understanding of locomotor behavior. One complete system. Everything included CatWalk is the most used automated gait analysis system and therefore is a must get for any lab considering using gait as a read-out parameter. precision_manufacturing Complete hardware Everything required for accurate gait acquisition New CatWalk 11 hardware with high-quality camera Illuminated glass walkway All essential components included and ready to use code Powerful software Automated footprint detection and validated gait analysis Intuitive software allowing for detailed gait analysis Automated Footprint Classification and Interactive Footprint Measurement Flexible data export and publication-ready results Services & support Helping you succeed from day one Additional remote training to get the most out of CatWalk Remote installation assistance to get you started NoldusCare for ongoing software updates and technical support Ready to bring CatWalk to your lab? Request a quote Request a demo Benefits of CatWalk Why should I use CatWalk? When you choose to use CatWalk in your lab you are employing the most widely used gait analysis system. pest_control_rodent Measure natural gait patterns Natural gait is more translationally valuable in most cases than measuring gait on a treadmill. The animals don't compensate their gait to match the speed of the treadmill. pets Detailed paw print identification CatWalk only detects the contact service with the paw on the walkway, no assumptions or misidentified body parts. This results in true and high-quality data ideal for measuring subtle gait deviations. sentiment_satisfied Low stress method The low light, trained animals and natural walking combine to make CatWalk a low stress method, which is essential for obtaining relevant results. No black box You always have access to your full data set allowing for complete data transparency. You can always see what CatWalk is doing and correct where needed. Explore further Publications Browse peer-reviewed research papers and scientific publications that reference this product in their methodology. Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. CatWalk in practice Go behind the scenes and see how gait analysis with CatWalk is done Research Columbia University Gait analysis as the lab's backbone Look inside the Mouse NeuroBehavior Core at Columbia University. Here, Dr. Mu Yang shares her experience with using CatWalk and other Noldus behavioral tools and explains how easy it is to train new users to operate these systems. Research NeuroPore Therapies Studying Parkinson's with gait NeuroPore Therapies does important research in the field of neurodegenerative disorders. Dr. Diana Price, Dr. Asma Khan and Robert Johnson are currently using CatWalk to study Parkinson's disease. See more customer stories Your browser does not support the video tag. Frequently asked questions About CatWalk How do I make my results comparable across days, groups, and operators? Standardize your training, use consistent run inclusion criteria, and keep the same corridor/lighting setup. CatWalk supports reviewing and filtering runs while preserving full traceability. What does a complete CatWalk setup require? You'll need the CatWalk hardware, a suitable PC/workstation, and a room for consistent recordings. Installation and calibration ensure repeatable measurements, which are made easy with our new calibration tool. Can I integrate CatWalk data into my existing analysis workflow? Yes, CatWalk output can be exported so you can analyze results in your preferred stats tools (R/Python/Prism/SPSS). You keep a clear link between processed parameters and the underlying recorded runs. Can I use CatWalk with severely impaired or obese animals? Yes, though in severe models, any system can face challenging runs. CatWalk lets you easily review runs, set the appropriate criteria and correct classifications when needed. How does CatWalk compare to competitors? CatWalk is a widely used benchmark for natural, free-walking gait, with rich footprint/contact metrics and transparent, reviewable analysis. Treadmill systems focus on strict speed control which causes animals to compensate their gait and become stressed, while other tools prioritize compact, automated mouse only workflows. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... CatWalk Promotion Gait analysis has never been more accessible Complete system with training for your team. - check New CatWalk 11 hardware - check Intuitive analysis software - check Remote training included All for only €39.500 Limited Time Deal *Desktop not included. Receive a quote request_quote --- ## CatWalk Applications URL: https://noldus.com/catwalk/applications Description: Discover CatWalk XT applications in gait analysis, pain research, neurodegenerative disease models, and more. Back to CatWalk What can I use CatWalk for? Gait has been used as an endpoint for many types of rodent models. CatWalk is the most cited system to measure and analyse locomotion and gait in small mammals. Therefore, it is no surprise that CatWalk has been used in a great variety of studies over the years. From Parkinson's disease to nerve and skeletal injuries, CatWalk is a great fit for a wide variety of research and disease models. Contact our sales team Applications of CatWalk Spinal cord injury SCI results in motor and sensory deficits due to damage to the spinal cord. Gait analysis with CatWalk allows researchers to quantify changes in paw placement, stride length, and coordination, providing insights into locomotor recovery and therapeutic efficacy. Parkinson's disease Parkinson's is characterized by motor symptoms like tremors, rigidity, and bradykinesia. CatWalk can assess alterations in gait patterns, such as reduced step length and irregular paw placements, reflecting motor impairment and aiding in evaluating potential treatments. Alzheimer's disease Alzheimer's leads to cognitive decline but can also affect motor function. CatWalk helps measure changes in gait parameters like velocity and regularity. Ataxia Ataxia involves impaired coordination and balance, often caused by cerebellar dysfunction. CatWalk can detect irregularities in paw placement and gait variability. Arthritis Arthritis causes joint inflammation and pain, affecting mobility. CatWalk enables the quantification of paw pressure distribution and changes in gait patterns. Pain research CatWalk is valuable in pain research by assessing gait parameters indicative of discomfort, such as alterations in paw contact area. Traumatic brain injury TBI disrupts normal brain function and can impair motor coordination. CatWalk enables the measurement of gait abnormalities post-injury. Sciatic nerve injury SNI affects motor and sensory function in rodents. CatWalk allows for precise measurement of gait parameters, assisting in evaluating nerve regeneration and functional recovery. Neurobehavioral Core Lab Columbia University Explore how this leading behavioral core lab in New York City uses CatWalk to study mouse models of Alzheimer's, ALS, Parkinson's, and more in advanced testing environments. personDr. Mu Yang & Paul Hamblin apartmentColumbia University, New York location_onUSA CatWalk vs. Treadmill methods Feature CatWalk Treadmill / DigiGait Working principle check_circleLight injected glass plate Transparent treadmill & bright light Adjustable size check_circleOne system for all small mammals Different systems for rats and mice Detection method check_circleLight reflection Assumption based algorithm Motivation check_circleUnforced natural walking Forced treadmill Animal stress check_circleLow High Preferred room lighting check_circleLow light Bright light Easy error detection check_circleYes No "CatWalk is easy to use and obtained data are directly applicable for further analysis. The system is robust and user friendly." Dr. Jarosław Jerzy Barski Medical University of Silesia, Katowice, Poland Voluntary walking animals are better Many people assume that all animals will walk or run at the same speed if they use a treadmill or treadwheel. However, this is not the case. Animals that walk voluntarily experience less stress and are less inclined to mask gait impairments. This way, you will have data with higher translational value. You can learn more about the advantages of free walking in this blog post. This does not mean that speed as a factor is not important to look at; it is. And for this reason, you can easily correct for speed and speed variations in the CatWalk software. Compare CatWalk & treadmills arrow_forward Bayer Bayer Brown University Brown University Caltech Caltech Charles River Charles River University of Washington University of Washington Novartis Novartis Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## CatWalk Publications URL: https://noldus.com/catwalk/publications Description: Explore publications and research papers using CatWalk XT for gait and locomotion analysis. Back to CatWalk Resources and publications Want to learn more about CatWalk? We have a great variety of materials for you to read and watch. - Extensive ebooks - Interesting white papers - Enlightening videos These materials will help you better understand the ins and outs of your gait analysis system. Contact our sales team CatWalk Selected publications Here is an overview of some recent publications with CatWalk. If you feel like your publication should be on this list, send us an e-mail at: marcom@noldus.com. CatWalk Parameters Timotius, I.K.; Roelofs, R.F.; Richmond-Hacham, B.; Noldus, L.P.; von Hörsten, S.; Bikovski, L. CatWalk Gait Parameters: A Review of Reported Parameters in Pre-Clinical Studies of Multiple Central Nervous System and Peripheral Nervous System Disease Models. Front. Behav. Neurosci. 2023, 17, 1147784. Spinal Cord Injury Zheng, G.; Zhang, H.; Tail, M.; Wang, H.; Walter, J.; Skutella, T.; Unterberg, A.; Zweckberger, K.; Younsi, A. Assessment of Hindlimb Motor Recovery after Severe Thoracic Spinal Cord Injury in Rats: Classification of CatWalk® Gait Analysis Parameters. Neural Regen. Res. 2023, 18, 1084. Nerve Injury Dolińska, A.; Górka, D.; Trzęsicki, M.; Białoń, N.; Górka, M. The Role of Training and Hyperbaria in the Rehabilitation Process after Crushing Injury of the Sciatic Nerve in Mice. J. Educ. Health Sport 2023, 13, 150–159. Alzheimer's disease Brody, A.H.; Nies, S.H.; Guan, F.; Smith, L.M.; Mukherjee, B.; Salazar, S.A.; Lee, S.; Lam, T.K.T.; Strittmatter, S.M. Alzheimer Risk Gene Product Pyk2 Suppresses Tau Phosphorylation and Phenotypic Effects of Tauopathy. Mol. Neurodegener. 2022, 17, 32. Ataxia Haas, E.; Incebacak, R.D.; Hentrich, T.; Huridou, C.; Schmidt, T.; Casadei, N.; Maringer, Y.; Bahl, C.; Zimmermann, F.; Mills, J.D.; et al. A Novel SCA3 Knock-in Mouse Model Mimics the Human SCA3 Disease Phenotype. Mol. Neurobiol. 2022, 59, 495–522. Brain Injury Walter, J.; Mende, J.; Hutagalung, S.; Grutza, M.; Younsi, A.; Zheng, G.; Unterberg, A.W.; Zweckberger, K. Focal Lesion Size Poorly Correlates with Motor Function after Experimental Traumatic Brain Injury in Mice. PLOS ONE 2022, 17, e0265448. Parkinson's disease Zhu, Q.; Song, J.; Chen, J.-Y.; Yuan, Z.; Liu, L.; Xie, L.-M.; Liao, Q.; Ye, R.D.; Chen, X.; Yan, Y.; et al. Corynoxine B Targets at HMGB1/2 to Enhance Autophagy for α-Synuclein Clearance in Fly and Rodent Models of Parkinson's Disease. Acta Pharm. Sin. B 2023, 13, 2701–2714. Arthritis Ko, J.-Y.; Wang, F.-S.; Lian, W.-S.; Fang, H.-C.; Kuo, S.-J. Cartilage-Specific Knockout of MiRNA-128a Expression Normalizes the Expression of Circadian Clock Genes (CCGs) and Mitigates the Severity of Osteoarthritis. Biomed. J. 2023, 100629. Stroke Pawletko, K.; Jędrzejowska-Szypulka, H.; Bogus, K.; Pascale, A.; Fahmideh, F.; Marchesi, N.; Grajoszek, A.; Gendosz de Carrillo, D.; Barski, J.J. After Ischemic Stroke, Minocycline Promotes a Protective Response in Neurons via the RNA-Binding Protein HuR. Int. J. Mol. Sci. 2023, 24, 9446. Pain Research Yerofeyeva, A.-M.V.; Pinchuk, S.V.; Rjabceva, S.N.; Molchanova, A.Y. The Role of Cannabinoid CB1 Receptors in the Antinociceptive and Reparative Actions of Mesenchymal Stem Cells in Rats with Peripheral Neuropathic Pain. Ibrain. Most cited gait analysis system There are over 6,480 publications based on CatWalk, which is at least 4 times more than with any other gait analysis system! Check out our resources section for an overview of publications for a variety of models, like sciatic nerve injury, Parkinson's Disease, Ataxia, and many more. Source: Google Scholar 2024 Bayer Brown University Caltech Charles River University of Washington Novartis Bayer Brown University Caltech Charles River University of Washington Novartis Bayer Brown University Caltech Charles River University of Washington Novartis Bayer Brown University Caltech Charles River University of Washington Novartis Your guide to everything gait analysis: A free guidebook Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... "Our lab has been using CatWalk since 2015, and we have found that it is an invaluable tool for our research and provides a reliable and detailed analysis of gait and how it varies in our disease models." Pediatric Storage Disorders Laboratory Washington University School of Medicine, St. Louis, USA Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. First name * Last name * Email address * Request * Make a choiceReceive informationRequest pricingFree trialFree demoBook an online meetingOther Institute/company * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit --- ## CatWalk Setup URL: https://noldus.com/catwalk/setup Description: Learn how to set up CatWalk XT for automated gait analysis in your research. @include('partials.hero-auroral') Back to CatWalk How do I use CatWalk? Automated systems are the way to go when performing gait analysis. However, you might wonder, where do I start, what do I need, and how does CatWalk actually work? Well, keep reading or request a demo to see what CatWalk is all about. Get a free demo Which hardware do I need? CatWalk uses the most effective method for gait analysis. Footprints are illuminated where the paw touches the glass. A green LED light injected into the glass plate is completely internally reflected, except at those areas where the animal makes contact with the glass plate. Where the paws touch the glass, light escapes and is reflected by the paw to the camera. The high-speed color camera captures these footprints and sends the data to the CatWalk software. You can download the full technical specs below. Download the technical specifications arrow_forward How do I collect my data? Which parameters should I choose? Automatic gait analysis like with Noldus' CatWalk vastly improves reliability and efficiency of your research. However, using these automated methods is not always straightforward. You might be asking yourself questions like: What readouts do I use? How will my animal model and housing conditions influence my results? The right options arrow_forward How do I motivate my animals? CatWalk is a gait analysis system based on the voluntary movement of rats or mice. Generally, animals quickly learn to cross in a consistent manner, especially rats. However, familiarizing them with the system before you start your experiment makes your job a lot easier. Get the perfect runs arrow_forward CatWalk, a versatile system CatWalk has been used for gait analysis in multiple studies and has enabled experimental procedures for several neurological disorders and in lesion models. With the Illuminated Footprint Technology and a high-speed camera this system gives you an accurate and automated analysis. Explore some examples arrow_forward CatWalk in a nutshell The CatWalk gait analysis method has existed for quite a while. However, Noldus has been improving and finetuning the method since day one. We are always looking to improve upon the CatWalk system to provide you with the best materials for performing gait analysis. A brief overview arrow_forward How do I analyze my data? Error detection CatWalk automatically detects classification conflicts. You can select them from a dropdown box, upon which the video jumps to the corresponding time point. Use the zoom function to look at the print in detail and reclassify if needed. Adjustable at every step You can manually change the amount of green signal filtered out of each run. Adjusting the intensity threshold allows you to filter out noise or overexposed paws for optimal detection. Explore your data View parameter charts for every parameter you're interested in. See how gait changes between experimental groups over time. Export graphs to PowerPoint or as a PDF report. Reading materials CatWalk and TBI mice The CatWalk gait analysis system can be an incredibly useful tool in assessing the subtle motor deficits exhibited by mice post-TBI, making it ideal for detecting deficits that might not be readily observable to researchers. Download arrow_forward Getting the perfect runs for CatWalk CatWalk is a gait analysis system based on the voluntary movement of rodents. Generally, animals quickly learn to cross in a consistent manner. In this white paper we share our favorite tips and tricks. Download arrow_forward Parameters in spinal cord injury CatWalk is an invaluable tool to monitor and quantify gait for spinal cord injured rats. Parameters such as stride length, base-of-support, print area, and intensity are measured objectively and automatically. Download arrow_forward What are phase dispersions? Insights on the inter-limb coordination can provide you with valuable and important data for your research. CatWalk calculates this data automatically. In this white paper we take a closer look at Phase Dispersions values. Download arrow_forward Free e-book Your guide to everything gait analysis Whether you're new to gait research or looking to optimize your existing protocols, this free eBook is your go-to guide. Learn how to measure rodent gait with precision, interpret key parameters, and apply best practices in preclinical models of neurological and musculoskeletal disorders. Download it now to level up your data quality and study design. Download for free Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## White paper | How to set up a coding scheme URL: https://noldus.com/coding-scheme-setup Description: In this free white paper, we will explain the basics of behavioral coding and how to set up a coding scheme. Get the most out of your research data Free white paper How to Set Up a Coding Scheme A well-designed coding scheme is the foundation of reliable behavioral research. This white paper guides you through the process of creating, testing, and refining a coding scheme that fits your research questions. In this white paper: - checkDefining behaviors and events to code - checkChoosing between state events and point events - checkEstablishing inter-rater reliability - checkIterating and refining your scheme - checkPractical tips from experienced researchers Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free Why a good coding scheme matters Behavioral coding is the process of systematically categorizing and recording observed behaviors. A well-constructed coding scheme ensures that your observations are consistent, reproducible, and meaningful. Whether you are studying parent-child interactions, classroom behavior, clinical consultations, or animal behavior, the quality of your coding scheme directly impacts the quality of your data. Key topics: - checkMutually exclusive vs. non-exclusive behaviors - checkDuration events vs. frequency events - checkTraining observers for consistency - checkCalculating Cohen's Kappa - checkUsing The Observer XT for behavioral coding --- ## Conferences 2026 URL: https://noldus.com/conferences Description: Noldus participates and sponsors many events around the world, varying from local research meetings to international scientific conferences. {{-- Header --}} Events & Conferences Let's connect at conferences and events Conferences are where ideas come to life, and we invite you to be part of the action. By connecting with fellow researchers, educators, and innovators, you help shape the future of behavioral science. The conversations spark fresh perspectives, highlight emerging challenges, and bring forward the technologies that matter most to your work. Below, you'll find a list of conferences and events we'll be attending in 2026. Planning to attend? Stop by our booth or schedule a meeting. We'd love to meet you. {{-- Conference cards --}} 2026 Events & conferences {{-- Meet Noldus and Lab Products at AALAS 2026 --}} Meet Noldus and Lab Products at AALAS 2026 Visit us at the American Association for Laboratory Animal Science (AALAS) in Houston. Find Noldus at the Lab Products booth (#1802) and meet CageIQ, our new partnership bringing welfare and behavioral monitoring into the home cage. 25 – 29 October 2026 Houston, Texas, USA Visit the website {{-- We're exhibiting at Neuroscience 2026 --}} We're exhibiting at Neuroscience 2026 Think you're smarter than your lab animals? Prove it at SfN 2026 in Washington, DC! Noldus is bringing new technology, new collaborations, hands-on demonstrations, and some decidedly less serious ways to test your brain. Find us at booth 823. 14 – 18 November 2026 Washington, D.C., USA Visit the website {{-- Join us at Measuring Behavior 2027 --}} Join us at Measuring Behavior 2027 Measuring Behavior is the conference for methods, techniques, and tools in behavioral research, bringing together researchers from every field who share one thing: how they study behavior. Join 250+ peers from across the behavioral sciences. Save the date and sign up for updates. 28 – 30 April 2027 Düsseldorf, Germany Visit the website --- ## Noldus | Contact us to discuss your research needs URL: https://noldus.com/contact Description: How to contact us Get in touch with us Fill in the form and our team will get back to you within two business days. Need something faster? Give us a call. Noldus Information Technology BV phone +31 317 473 300 mail contact@noldus.com location_on Wageningen, The Netherlands Noldus Information Technology Inc. phone +1 703-771-0440 mail info@noldus.com location_on Washington DC, United States of America @csrf First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit --- ## Customer Stories URL: https://noldus.com/customer-stories Description: See how researchers worldwide use Noldus tools in their behavioral research. Real stories from real labs. Customer stories See how researchers use Noldus tools Discover how universities, research institutes, and companies around the world use our solutions to advance their behavioral research. All Human pest_control_rodent Animal Human Simulation training for medical education AIXTRA At the AIXTRA Competence Center for Training and Patient safety, they're passionate about preparing the next generation of healthcare professionals through innovative and hands-on medical teaching. personLina Vogt, Andrea Lenes, Maurice ElissenapartmentAIXTRAlocation_onGermany View the video arrow_forward Animal Measuring autism in mice with Noldus tools Erasmus MC, Rotterdam At Society for Neuroscience 2023 in Washington DC, Aleksandra Badura of the Erasmus MC tells her story about why working with Noldus advances her research. personDr. Aleksandra BaduraapartmentErasmus MC, Rotterdamlocation_onThe Netherlands View the video arrow_forward Human Education and training in a UX lab Ede Christian University of Applied Sciences (CHE) Providing education in a UX Lab gives a much more realistic picture for students of how user experience can be measured and what the results can be. personMarnix BrasapartmentChristian University of Applied Sciences Edelocation_onThe Netherlands View the video arrow_forward Animal Zebrafish research with EthoVision XT and The Observer XT Gerlai Lab, University of Toronto Dr. Gerlai and his students are at the forefront of zebrafish research. Learn more about their work in our customer story on the Gerlai Lab in Toronto, Canada. personDr. Robert GerlaiapartmentGerlai Lab, Torontolocation_onCanada View the video arrow_forward Human Facial expressions and social behavior University of Western Ontario Measuring behavior is critical for understanding a lot of the social problems that arise in the world. Watch our Customer Success Story at University of Western Ontario. personDr. Erin HeereyapartmentUniversity of Western Ontariolocation_onCanada View the video arrow_forward Animal Neurobiological mechanisms linking stress and obesity Measuring behavior at Loma Linda University Measuring changes in the brain and changes in behavior can help predict obesity in subjects that have been exposed to stress. personDr. Johnny FigueroaapartmentLoma Linda University, Californialocation_onUSA View the video arrow_forward Human Early childhood development research Fisher-Price Play Lab At the Fisher-Price Play Lab they use Noldus' Viso, The Observer XT and FaceReader systems to develop toys for children that foster interaction and learning. personDr. Corinne Eggleston, Nicole MackiewiczapartmentFisher-Pricelocation_onUSA View the video arrow_forward Animal Behavioral testing rooms Columbia University's neurobehavioral core lab Noldus visited Columbia University in New York city to take a look at their behavioral core lab in which they serve many labs that want to measure behavior personDr. Mu Yang & Paul HamblinapartmentColumbia University, New Yorklocation_onUSA View the video arrow_forward Human Baby & Child Research Center Radboud University - Donders Institute The better we understand typical and atypical development, the better we can develop treatments and interventions for children with developmental conditions. personProf. Sabine HunniusapartmentBaby & Child Research Centerlocation_onThe Netherlands View the video arrow_forward Animal Zebrafish research Plavicki Lab at Brown University We visited Dr. Jess Plavicki at Brown University in Rhode Island. She runs a lab aimed at investigating the development of brain and heart health in zebrafish using imaging techniques and optogenetics. personDr. Jessica PlavickiapartmentBrown University, Providence, Rhode Islandlocation_onUSA View the video arrow_forward Human The Behavioral Research in Business Laboratory Hofstra University The Behavioral Research in Business Lab at Hofstra University is powered by cutting-edge software and tools for business-focused human behavior research. personDr. Anil MathurapartmentBehavioral Research in Business Lablocation_onUSA View the video arrow_forward Animal Research into behavior and brain mechanisms of Bipolar disorder Donders Institute for Brain, Cognition and Behaviour Mina Sadighi Alvandi, Donders Institute, is doing research with EthoVision XT into the neuroscience of bipolar disorder and the mechanism that is associated with this disease. personDr. Mina Sadighi AlvandiapartmentRadboud University, Nijmegenlocation_onThe Netherlands View the video arrow_forward Human Human factor research in a ship bridge simulator MARIN - Maritime research institute Noldus human factor research toolkit MARIN wageningen. Human error and decision making in safety critical situations. Customer succes story personHans HuismanapartmentMARINlocation_onThe Netherlands View the video arrow_forward Human Research in Educational Psychology Leipzig University - Faculty of Education Researchers at the Leipzig University focus on gaining further insights into future teachers' moral emotions using Noldus' tools. personProf. Dr. Brigitte Latzko and Dr. Sandra DietrichapartmentLeipzig Universitylocation_onGermany View the video arrow_forward Animal Using EthoVision XT as an educational tool University of Groningen Dr. Jocelien Olivier is taking you on a tour during a practical. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personDr. Jocelien OlivierapartmentUniversity of Groningenlocation_onThe Netherlands View the video arrow_forward Human Simulation-based training in an immersive room Secta Medical Dennie Wulterkens explains the benefits of providing a simulation-based training in an immersive room and why the video feedback tool Viso fits in perfectly. personDennie WulterkensapartmentSecta Medicallocation_onThe Netherlands View the video arrow_forward Animal Social learning task in rats Heinrich Heine University Dr. Marijn van Wingerden is taking you on a tour in their lab. Take a look at how they designed their experiments, what equipment they chose, and which software tools are used. personDr. Marijn van WingerdenapartmentHeinrich Heine University, Düsseldorflocation_onGermany View the video arrow_forward Human UX Research at Canada's leading cooperative financial group Desjardins LabUX Marie-Laure Di Fabio is a senior User Researcher at Desjardins Group. She was entrusted her with implementing its new Neuro UX laboratory, the LabUX. personMarie-Laure Di FabioapartmentDesjardins Grouplocation_onCanada View the video arrow_forward Animal Neurodegenerative disease studies NeuroPore Therapies The team at NeuroPore Therapies are taking you on a tour of their lab. Learn why they chose CatWalk XT for their research and what kind of research questions they're investigating. personDiana L. PriceapartmentNeuroPore Therapies, San Diegolocation_onUSA View the video arrow_forward Human The role of sensory evaluation Virginia Tech - Food Science & Technology How do we experience food consumption? In response to seeing, smelling or tasting food, facial expressions demonstrate how we react to the particular food. personProf. Dr. Susan DuncanapartmentVirginia Techlocation_onUSA View the video arrow_forward Animal Assessing anxiety and depression in rodents University of Toronto Dr. Prévôt studies anxiety and depression to transform mental health care. He takes you on a lab tour and discusses why he chose PhenoTyper for his research. personDr. Thomas PrévôtapartmentUniversity of Torontolocation_onCanada View the video arrow_forward Human Educational research Université du Québec à Montréal - Neurolab L'Université du Québec à Montréal (UQAM), is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personProf. Julien MercierapartmentUniversité du Québec à Montréallocation_onCanada View the video arrow_forward Animal Predictive ecology: Studying behavior in the Great Lakes University of Windsor Dr. Christina Semeniuk is taking you on a tour in their lab. Watch the video to learn more about the importance of their research and how EthoVision XT helps them achieve their goals. personDr. Christina SemeniukapartmentUniversity of Windsorlocation_onCanada View the video arrow_forward Human From data collection to insightful results Tech3Lab Montreal Tech3Lab Montreal is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personProf. Pierre-Majorique LégerapartmentHEC Montréal and Tech3Lablocation_onCanada View the video arrow_forward Animal Behavioral Analysis Facility University of Rouen Dr. Jean-Luc and Jean-Claude do Rego take you on a tour in their facility. Take a look at how they designed their rooms and why they chose equipment and software from Noldus. personDr. Jean-Luc do Rego and Dr. Jean-Claude do RegoapartmentUniversity of Rouenlocation_onFrance View the video arrow_forward Human Immersive technology lab Liverpool John Moores University Liverpool John Moores University is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personDr. Atif WaraichapartmentLiverpool John Moores Universitylocation_onUnited Kingdom View the video arrow_forward Animal Neuropsychopharmacological Lab University of Bologna Prof. Roberto Rimondini explains why he chose EthoVision XT for tests such as the open field, water maze, elevated plus maze, barnes test, object recognition, and much much more. personProf. Roberto RimondiniapartmentUniversity of Bolognalocation_onItaly View the video arrow_forward Human Social Media Lab Université catholique de Louvain Social Media Lab is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personTiffany Andry & Damien De MeyereapartmentUniversity of Louvainlocation_onBelgium View the video arrow_forward Animal Zebrafish research with EthoVision XT and DanioVision Radboud University Dr. Ruud van den Bos is taking you on a tour of the zebrafish lab. He is explains why good research tools are important for reliability and reproducibility in zebrafish experiments. personDr. Ruud van den BosapartmentRadboud University, Nijmegenlocation_onThe Netherlands View the video arrow_forward Human Interaction between trainee teacher and students University of Mons University of Mons, is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personMarie BocquillonapartmentUniversity of Monslocation_onBelgium View the video arrow_forward Human A dedicated counseling psychology lab Delaware Valley University Delaware Valley University - A dedicated counseling psychology lab, is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personDr. Audrey ErvinapartmentDelaware Valley Universitylocation_onUSA View the video arrow_forward Human Data integration facilitates the study of emotions Bcom, France b-com, is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. personJean-Marc DiverrezapartmentBCom Institute of Research and Technologylocation_onFrance View the video arrow_forward Human Sensory science and eating behavior Wageningen University & Research Wageningen University & Research is taking you on a tour in their lab. See how they designed lab rooms, and the equipment and software tools they used. personProf. Kees de GraafapartmentWageningen University & Researchlocation_onThe Netherlands View the video arrow_forward Human Centre for Infant Cognition University of British Columbia Centre for Infant Cognition is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. Read the story arrow_forward Human Advanced tools for usability testing at the CERIOS lab DORC (Dutch Ophthalmic Research Center) In the CERIOS lab, surgeons can be observed while they perform tasks on the newest prototypes in a realistic surgery setup. Read the story arrow_forward --- ## Customer Story - AIXTRA URL: https://noldus.com/customer-stories/aixtra Description: At the AIXTRA Competence Center for Training and Patient safety, they're passionate about preparing the next generation of healthcare professionals through innovative and hands-on medical teaching. @include('partials.hero-auroral') Back to Customer Stories Simulation training for medical education AIXTRA Human Behavior Research At the AIXTRA Competence Center for Training and Patient safety, they're passionate about preparing the next generation of healthcare professionals through innovative and hands-on medical teaching. Lina Vogt, Andrea Lenes, Maurice Elissen apartment AIXTRA Germany Interested in similar results? Get in touch! Want to achieve the same research quality as AIXTRA? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Erasmus MC URL: https://noldus.com/customer-stories/aleksandra-badura-noldus-tools-sfn-2023 Description: At Society for Neuroscience 2023 in Washington DC, Aleksandra Badura of the Erasmus MC tells her story about why working with Noldus advances her research. @include('partials.hero-auroral') Back to Customer Stories Measuring Autism in mice with Noldus tools Erasmus MC pest_control_rodent Animal Behavior Research Dr. Aleksandra Badura is an Associate Professor at the department of Neuroscience, and head of the lab 'Neural Networks Underlying Behavioral Flexibility' at the Erasmus MC in Rotterdam, the Netherlands. Her current work focuses on understanding the cerebello-cerebral networks underlying shared autistic traits. Dr. Aleksandra Badura apartment Erasmus MC, Rotterdam The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as Erasmus MC? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - bcom, France URL: https://noldus.com/customer-stories/b-com Description: b-com, is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Data integration facilitates the study of emotions bcom, France Human Behavior Research Jean-Marc Diverrez, from bcom Institute of Research and Technology, France talks about data integration and measuring emotions. He hopes that the projects will go out of the lab and into the real world. He looks into all kinds of new technologies and sensors to better measure and thus understand emotions. Jean-Marc Diverrez apartment BCom Institute of Research and Technology France Interested in similar results? Get in touch! Want to achieve the same research quality as bcom, France? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Baby and Child Research Center URL: https://noldus.com/customer-stories/baby-and-child-research-center Description: The better we understand typical and atypical development, the better we can develop treatments and interventions for children with developmental conditions. @include('partials.hero-auroral') Back to Customer Stories Baby and Child Research Center Baby and Child Research Center Human Behavior Research The Baby and Child Research Center at the Donders Institute studies the development of babies and children using advanced behavioral observation tools and techniques. Baby and Child Research Center apartment Radboud University - Donders Institute The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as Baby and Child Research Center? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Hofstra University URL: https://noldus.com/customer-stories/behavioral-research-in-business-lab-hofstra Description: The Behavioral Research in Business Lab at Hofstra University is powered by cutting-edge software and tools for business-focused human behavior research. @include('partials.hero-auroral') Back to Customer Stories The Behavioral Research in Business Laboratory Hofstra University Human Behavior Research The Behavioral Research in Business Laboratory at Hofstra University is a state-of-the-art facility that was specifically designed to conduct multi-disciplinary behavioral research. Dr. Anil Mathur apartment Behavioral Research in Business Lab USA Interested in similar results? Get in touch! Want to achieve the same research quality as Hofstra University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Donders institute for Brain, Cognition and Behaviour URL: https://noldus.com/customer-stories/bipolar-disorder-research-ethovision-xt Description: Mina Sadighi Alvandi, Donders Institute, is doing research with EthoVision XT into the neuroscience of bipolar disorder and the mechanism that is associated with this disease. @include('partials.hero-auroral') Back to Customer Stories Research into behavior and brain mechanisms of Bipolar disorder Donders institute for Brain, Cognition and Behaviour pest_control_rodent Animal Behavior Research Dr. Mina Sadighi Alvandi, who works in the lab of Prof. Dr. Judith Homberg, shows us their lab at Donders institute for Brain, Cognition and Behavior in Nijmegen (the Netherlands). Their aim is to develop a new animal model for bipolar disorder. Dr. Mina Sadighi Alvandi apartment Radboud University, Nijmegen The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as Donders institute for Brain, Cognition and Behaviour? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Plavicki Lab | Brown University URL: https://noldus.com/customer-stories/brown-university-plavicki-zebrafish Description: We visited Dr. Jess Plavicki at Brown University in Rhode Island. She runs a lab aimed at investigating the development of brain and heart health in zebrafish using imaging techniques and optogenetics. @include('partials.hero-auroral') Back to Customer Stories Using optogenetics with DanioVision in zebrafish research Plavicki Lab | Brown University pest_control_rodent Animal Behavior Research We visited Dr. Jessica Plavicki, of the department of Pathology and Laboratory Medicine of Brown University in Providence, Rhode Island. She runs her own lab where they are studying developing zebrafish, aimed at assessing the impact of chemical and/or environmental exposure, and genetic mutations on brain and heart health. Dr. Jessica Plavicki apartment Brown University, Providence, Rhode Island USA Interested in similar results? Get in touch! Want to achieve the same research quality as Plavicki Lab | Brown University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Ede Christian University of Applied Sciences (CHE) URL: https://noldus.com/customer-stories/che Description: Providing education in a UX Lab gives a much more realistic picture for students of how user experience can be measured and what the results can be. @include('partials.hero-auroral') Back to Customer Stories Education and training in a UX lab Ede Christian University of Applied Sciences (CHE) Human Behavior Research The UX lab that is set up at the Ede Christian University of Applied Sciences is intended to study human behavior. For example students' behaviors during mock interviews or when they are practising conversation skills. Marnix Bras apartment Christian University of Applied Sciences Ede The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as Ede Christian University of Applied Sciences (CHE)? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Columbia University URL: https://noldus.com/customer-stories/columbia-university-behavioral-core-lab Description: Noldus visited Columbia University in New York city to take a look at their behavioral core lab in which they serve many labs that want to measure behavior @include('partials.hero-auroral') Back to Customer Stories Neurobehavioral Core Lab Columbia University pest_control_rodent Animal Behavior Research Explore how this leading behavioral core lab in New York City uses CatWalk XT to study mouse models of Alzheimer's, ALS, Parkinson's, and more in advanced testing environments. Dr. Mu Yang & Paul Hamblin apartment Columbia University, New York USA Interested in similar results? Get in touch! Want to achieve the same research quality as Columbia University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Delaware Valley University URL: https://noldus.com/customer-stories/delaware-valley-university Description: Delaware Valley University - A dedicated counseling psychology lab, is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories A dedicated counseling psychology lab Delaware Valley University Human Behavior Research At Delaware Valley University the counseling psychology team created a state-of-the-art training facility for their Master of Arts in Counseling Psychology program. In this program, students specialize in either child and adolescent counseling, or social justice community counseling. Throughout their training, graduate students are continually engaged in counseling, outreach, and advocacy. Dr. Audrey Ervin apartment Delaware Valley University USA Interested in similar results? Get in touch! Want to achieve the same research quality as Delaware Valley University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Desjardins LabUX URL: https://noldus.com/customer-stories/desjardins-labux Description: Marie-Laure Di Fabio is a senior User Researcher at Desjardins Group. She was entrusted her with implementing its new Neuro UX laboratory, the LabUX. @include('partials.hero-auroral') Back to Customer Stories UX Research at Canada's leading cooperative financial group Desjardins LabUX Human Behavior Research Marie-Laure Di Fabio is a senior User Researcher at Desjardins Group, Canada’s leading financial cooperative group. Desjardins Group entrusted her with implementing its new Neuro UX laboratory, the LabUX, they launched in June 2019. Marie-Laure Di Fabio apartment Desjardins Group Canada Interested in similar results? Get in touch! Want to achieve the same research quality as Desjardins LabUX? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - DORC (Dutch Ophthalmic Research Center) URL: https://noldus.com/customer-stories/dorc-cerios Description: In the CERIOS lab, surgeons can be observed while they perform tasks on the newest prototypes in a realistic surgery setup. @include('partials.hero-auroral') Back to Customer Stories Advanced tools for usability testing at the CERIOS lab DORC (Dutch Ophthalmic Research Center) Human Behavior Research For DORC (Dutch Ophthalmic Research Center), the vision of restoring sight is not just a mission but a relentless pursuit. As a supplier of cutting-edge technologies, instruments, and equipment for ophthalmic surgery, they actively contribute to high-quality innovations that helps people see again. Mart Gahler apartment DORC (Dutch Ophthalmic Research Center) Zuidland, The Netherlands To keep these innovations on a high level, they’ve joined forces with Noldus IT to set up CERIOS (Center of Expertise, Research and Innovation in Ophthalmic Surgery). In this lab, they are able to test their new products, equipment, and prototypes to make sure surgeons are able to use them in the best possible way. Importance of usability tests Usability studies are essential to get a good understanding of what aspects elevate or hinder the performance, whether a new instrument or piece of equipment is easy to use or not, and what features are the most helpful or might cause discomfort. In the lab, surgeons can be observed real-time while they perform tasks on the newest prototypes in a realistic surgery setup. If designers of these prototypes made wrong assumptions or missed requirements, a usability test is likely to reveal them. Why Viso fits in the CERIOS lab Researchers and test facilitators at DORC knew the importance of usability tests and went on a search for a reliable and flexible system for high-quality video and audio recordings of test sessions. Viso was the perfect system to go for from the start – easy to use, flexible, reliable, and secure. Those were some of the deciding factors for them: - Viso system enables simultaneous recording of a surgeon interacting with a new product or prototype from multiple different angles. That way, no important interaction goes unnoticed or is missed during the review of a test session. - When needed, they are able to visualize the image from a microscope in Viso as well, adding another dimension to a complete picture of the test. - With a simple click of a button, test facilitator can mark the moment when a surgeon makes a usability error, or responds as “confused” to a new feature. Therefore, there is no need to re‑watch a complete session to find the most important moments and share them with the team (which saves valuable time). - Recorded videos are immediately available for playback which allows to evaluate the session directly after finishing it. Flexible system for versatile usability tests Due to a flexible and versatile nature of Viso system, any usability test performed in the lab can be recorded, reviewed, and analyzed. Some of other tests that are being performed in the CERIOS lab are: - Preparation of sterile fields, such as setting up general equipment - Testing the user interface of surgical systems By conducting usability studies, DORC continuously subjects its procedures and products to rigorous evaluations. Interested in similar results? Get in touch! Want to achieve the same research quality as DORC (Dutch Ophthalmic Research Center)? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Fisher-Price Play Lab URL: https://noldus.com/customer-stories/fisher-price-play-lab Description: At the Fisher-Price Play Lab they use Noldus' Viso, The Observer XT and FaceReader systems to develop toys for children that foster interaction and learning. @include('partials.hero-auroral') Back to Customer Stories Early childhood development research Fisher-Price Play Lab Human Behavior Research At the Fisher-Price Play Lab in East Aurora, New York, the kids are the real experts! Nicole Mackiewicz, child testing researcher at Fisher-Price, tells us how they have proven in the Play Lab that their line of toys, the Linkimals, promotes learning. Dr. Corinne Eggleston, Nicole Mackiewicz apartment Fisher-Price USA Interested in similar results? Get in touch! Want to achieve the same research quality as Fisher-Price Play Lab? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Gerlai Lab | University of Toronto URL: https://noldus.com/customer-stories/gerlai-lab Description: Dr. Gerlai and his students are at the forefront of zebrafish research. Learn more about their work in our customer story on the Gerlai Lab in Toronto, Canada. @include('partials.hero-auroral') Back to Customer Stories Zebrafish Research with EthoVision XT and The Observer XT Gerlai Lab | University of Toronto pest_control_rodent Animal Behavior Research Meet Dr. Robert Gerlai, a distinguished researcher at the Gerlai Lab in Toronto, Canada. Dr. Gerlai is a leading expert in the field of zebrafish research, specializing in their social behaviors and cognitive processes. Dr. Robert Gerlai apartment Gerlai Lab, Toronto Canada Interested in similar results? Get in touch! Want to achieve the same research quality as Gerlai Lab | University of Toronto? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Heinrich Heine University URL: https://noldus.com/customer-stories/heinrich-heine-university Description: Dr. Marijn van Wingerden is taking you on a tour in their lab. Take a look at how they designed their experiments, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Social learning task in rats Heinrich Heine University pest_control_rodent Animal Behavior Research At the Heinrich Heine University in Düsseldorf, Germany, PI Dr. Marijn van Wingerden and his PhD student Sander van Gurp study social learning behavior in rats. Their Social Rodent Lab uses EthoVision XT and UltraVox for their behavioral studies. Dr. Marijn van Wingerden apartment Heinrich Heine University, Düsseldorf Germany Interested in similar results? Get in touch! Want to achieve the same research quality as Heinrich Heine University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Liverpool John Moores University URL: https://noldus.com/customer-stories/john-moores-university Description: Liverpool John Moores University is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Immersive technology lab Liverpool John Moores University Human Behavior Research Liverpool John Moores University has a long rich history, dating back to 1823. Nowadays its one of the largest universities in the United Kingdom, with 25 thousand students from over 100 countries worldwide. By forward-thinking and forging international partnerships, Liverpool John Moores University facilitates world-leading research. Dr. Atif Waraich apartment Liverpool John Moores University United Kingdom Interested in similar results? Get in touch! Want to achieve the same research quality as Liverpool John Moores University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Leipzig University - Faculty of Education URL: https://noldus.com/customer-stories/leipzig-university-educational-psychology Description: Researchers at the Leipzig University focus on gaining further insights into future teachers' moral emotions using Noldus' tools. @include('partials.hero-auroral') Back to Customer Stories Research in Educational Psychology Leipzig University - Faculty of Education Human Behavior Research Prof. Dr. Brigitte Latzko and Dr. Sandra Dietrich show us the upgrade of their lab at the Faculty of Education, Leipzig University in Germany. With this new lab, they will start a whole new line of research in educational psychology. Prof. Dr. Brigitte Latzko and Dr. Sandra Dietrich apartment Leipzig University Germany Interested in similar results? Get in touch! Want to achieve the same research quality as Leipzig University - Faculty of Education? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Loma Linda University URL: https://noldus.com/customer-stories/loma-linda-university-measuring-long-term-behavior Description: Measuring changes in the brain and changes in behavior can help predict obesity in subjects that have been exposed to stress. @include('partials.hero-auroral') Back to Customer Stories Neurobiological Mechanisms Linking Stress and Obesity Loma Linda University pest_control_rodent Animal Behavior Research We talked with Dr. Johnny Figueroa, Associate Professor of Neuroscience at the Loma Linda University School of Medicine in California. He specializes in nutritional neuroscience, but foremost how (adverse) childhood events can have long term neurobiological consequences. Dr. Johnny Figueroa apartment Loma Linda University, California USA Interested in similar results? Get in touch! Want to achieve the same research quality as Loma Linda University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - MARIN - Maritime research institute URL: https://noldus.com/customer-stories/marin-human-factor-success-story Description: Noldus human factor research toolkit MARIN wageningen. Human error and decision making in safety critical situations. Customer succes story @include('partials.hero-auroral') Back to Customer Stories Human factor research in a ship bridge simulator MARIN - Maritime research institute Human Behavior Research Hans Huisman shows us around a state-of-the-art ship bridge simulator at MARIN: one of the world's leading maritime research institutes. They are also developing a brand new 'seven oceans simulation center' which is integrated with a Noldus toolkit for human factor research. Hans Huisman apartment MARIN The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as MARIN - Maritime research institute? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - NeuroPore Therapies URL: https://noldus.com/customer-stories/neuropore-therapies Description: The team at NeuroPore Therapies are taking you on a tour of their lab. Learn why they chose CatWalk XT for their research and what kind of research questions they're investigating. @include('partials.hero-auroral') Back to Customer Stories Neurodegenerative disease studies NeuroPore Therapies pest_control_rodent Animal Behavior Research NeuroPore Therapies, San Diego, USA does important research in the field of neurodegenerative disorders. Dr. Diana Price, Dr. Asma Khan and Robert Johnson are currently using CatWalk XT to study Parkinson’s disease. Diana L. Price apartment NeuroPore Therapies, San Diego USA Interested in similar results? Get in touch! Want to achieve the same research quality as NeuroPore Therapies? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Radboud University URL: https://noldus.com/customer-stories/radboud-university Description: Dr. Ruud van den Bos is taking you on a tour of the zebrafish lab. He is explains why good research tools are important for reliability and reproducibility in zebrafish experiments. @include('partials.hero-auroral') Back to Customer Stories Zebrafish research with EthoVision XT and DanioVision Radboud University pest_control_rodent Animal Behavior Research Dr. Ruud van den Bos talks about his work in neurobiology and experimental psychology, and how zebrafish studies contribute to his field of research. He is experienced with DanioVision and EthoVision XT, and explains why good tools are important for reliability and reproducibility in zebrafish experiments. Dr. Ruud van den Bos apartment Radboud University Nijmegen | The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as Radboud University? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Secta Medical URL: https://noldus.com/customer-stories/secta-medical Description: Dennie Wulterkens explains the benefits of providing a simulation-based training in an immersive room and why the video feedback tool Viso fits in perfectly. @include('partials.hero-auroral') Back to Customer Stories Simulation-based training in an immersive room Secta Medical Human Behavior Research A well-constructed simulation-based training enables students and professionals to answer the question, “If I do this, what happens?". When such a training takes place in an immersive room, it offers a lifelike experience. Moreover, by adding Viso as the video feedback tool, efficient debriefing of the training is assured. Dennie Wulterkens, a paramedic and owner of Secta Medical, informs us about the benefits. Dennie Wulterkens apartment Secta Medical The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as Secta Medical? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Université catholique de Louvain URL: https://noldus.com/customer-stories/social-media-lab Description: Social Media Lab is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Social Media Lab Université catholique de Louvain Human Behavior Research The Social Media Lab in Mons, Belgium brings together researchers, students, professionals, and professors from different disciplines (communication, marketing, journalism, computer science, etc.). Together they try to understand the digital world, train themselves in the use of new technology, and learn more and advice about new professional practices. Tiffany Andry & Damien De Meyere apartment University of Louvain Belgium Interested in similar results? Get in touch! Want to achieve the same research quality as Université catholique de Louvain? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Tech3Lab Montreal URL: https://noldus.com/customer-stories/tech3lab Description: Tech3Lab Montreal is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories From data collection to insightful results Tech3Lab Montreal Human Behavior Research At the Tech3Lab at HEC Montréal, Prof. Pierre-Majorique Léger and his co-workers study what users really experience when they interact with technology, like mobile phones or tablets. Prof. Pierre-Majorique Léger apartment HEC Montréal and Tech3Lab Canada Interested in similar results? Get in touch! Want to achieve the same research quality as Tech3Lab Montreal? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of Bologna URL: https://noldus.com/customer-stories/university-bologna Description: Prof. Roberto Rimondini explains why he chose EthoVision XT for tests such as the open field, water maze, elevated plus maze, barnes test, object recognition, and much much more. @include('partials.hero-auroral') Back to Customer Stories Neuropsychopharmacological Lab University of Bologna pest_control_rodent Animal Behavior Research Prof. Roberto Rimondini is a neuropsychopharmacologist at the Department of Medical and Clinical Sciences DIMEC, Alma Mater Studiorum Bologna (University of Bologna, Italy). He has been using EthoVision XT video tracking software since its DOS version! Prof. Roberto Rimondini apartment University of Bologna Bologna | Italy Interested in similar results? Get in touch! Want to achieve the same research quality as University of Bologna? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of British Columbia URL: https://noldus.com/customer-stories/university-british-columbia Description: Centre for Infant Cognition is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Centre for Infant Cognition University of British Columbia Human Behavior Research The Centre for Infant Cognition (CIC), at the University of British Columbia, in Vancouver, Canada, uses analysis tools provided by Noldus for detailed behavioral coding. Noldus’ MediaRecorder is used to record study sessions and is installed on multiple online coding stations. Kiley Hamlin apartment University of British Columbia Vancouver, BC, Canada Image provided by CIC The cameras used in their studies are controlled by Noldus software, which contains adjustable camera angles offering optimal viewing points. This allows the researchers to fully capture an infant’s eye gaze and body behavior during a study. Analyzing infants behavior in detail Additionally, the CIC uses The Observer to record study events, and further analyze this data. It allows them to analyze behavior processes at a very detailed level that could not be obtained manually. More specifically, it is used to look at minute (small/precise) eye gaze changes, hand gestures, and emotions of infants while they are observing a moral dilemma or social interaction, which is usually depicted in a puppet show. For example, when the infant is asked to share treats with the puppet. The Centre for Infant Cognition at the University of British Columbia is headed by Dr. Kiley Hamlin. It is a part of the Early Development Research Group, and examines infants’ evaluations of moral dilemmas and social interactions. The purpose of their research is to understand how infants reason about their surrounding environment. CIC participates in ManyBabies projects A global network of more than 500 developmental researchers, including the research team of CIC, are involved in the ManyBabies projects. Their goal is to address difficult outstanding theoretical and methodological questions about the nature of early development and how it is studied. The projects are organized in main projects (either empirical or methodological), spin-off projects, and secondary analyses. The 6 empirical projects aim to gain knowledge by means of direct and indirect observation or experience. Read the blog Interested in similar results? Get in touch! Want to achieve the same research quality as University of British Columbia? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of Groningen URL: https://noldus.com/customer-stories/university-groningen Description: Dr. Jocelien Olivier is taking you on a tour during a practical. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Using EthoVision XT as an educational tool University of Groningen pest_control_rodent Animal Behavior Research As a professor in developmental behavioral neuroscience, Jocelien Olivier works at the University of Groningen, at the GELIFES Institute. In the minor Neuroscience, which is a university broad minor, she and her colleagues show students what neuroscience is all about. For example, she wants students to get in touch with 'how do we score behavior'. Dr. Jocelien Olivier apartment University of Groningen The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as University of Groningen? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of Mons URL: https://noldus.com/customer-stories/university-mons Description: University of Mons, is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Interaction between trainee teacher and students University of Mons Human Behavior Research Click on the play button to find out why Marie Bocquillon of the Institute of Educational Management of the University of Mons in Belgium uses Noldus' software for her research about improving teacher practices. Marie Bocquillon apartment University of Mons Belgium Interested in similar results? Get in touch! Want to achieve the same research quality as University of Mons? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of Western Ontario URL: https://noldus.com/customer-stories/university-of-western-ontario Description: Measuring behavior is critical for understanding a lot of the social problems that arise in the world. Watch our Customer Success Story at University of Western Ontario. @include('partials.hero-auroral') Back to Customer Stories Facial Expression and Social Behavior University of Western Ontario Human Behavior Research Dr. Erin Heerey is an Associate Professor at the department of Psychology, and head of the Social Behavior lab at Western University in London, Ontario. In her work she focuses on social interactions, mainly dyadic interactions. Dr. Erin Heerey apartment University of Western Ontario Canada Interested in similar results? Get in touch! Want to achieve the same research quality as University of Western Ontario? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of Rouen URL: https://noldus.com/customer-stories/university-rouen Description: Dr. Jean-Luc and Jean-Claude do Rego take you on a tour in their facility. Take a look at how they designed their rooms and why they chose equipment and software from Noldus. @include('partials.hero-auroral') Back to Customer Stories Behavioral Analysis Facility University of Rouen pest_control_rodent Animal Behavior Research Dr. Jean-Claude do Rego and Dr. Jean-Luc do Rego of the Behavioral Analysis Facility of the University of Rouen (Service Commun d'Analyse Comportementale, SCAC), are evaluating the behavioral and functional activities of new pharmacological drugs. Dr. Jean-Luc do Rego and Dr. Jean-Claude do Rego apartment University of Rouen Rouen | France Interested in similar results? Get in touch! Want to achieve the same research quality as University of Rouen? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of Toronto URL: https://noldus.com/customer-stories/university-toronto Description: Dr. Prévôt studies anxiety and depression to transform mental health care. He takes you on a lab tour and discusses why he chose PhenoTyper for his research. @include('partials.hero-auroral') Back to Customer Stories Assessing anxiety and depression in rodents University of Toronto pest_control_rodent Animal Behavior Research Dr. Thomas Prévôt from the University of Toronto is developing a new tool to assess anxiety-like and depressive-like behavior in rodents, in order to understand the underlying mechanisms of chronic stress exposure and how it changes either behavior but also molecular and cellular pathology, to mimic the human depression. Dr. Thomas Prévôt apartment University of Toronto Canada Interested in similar results? Get in touch! Want to achieve the same research quality as University of Toronto? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - University of Windsor URL: https://noldus.com/customer-stories/university-windsor Description: Dr. Christina Semeniuk is taking you on a tour in their lab. Watch the video to learn more about the importance of their research and how EthoVision XT helps them achieve their goals. @include('partials.hero-auroral') Back to Customer Stories Predictive ecology: Studying behavior in the Great Lakes University of Windsor pest_control_rodent Animal Behavior Research Fish species in the Great Lakes are facing human-induced rapid ecological change. Dr. Semeniuk's lab studies animal behavior in great detail in order to learn how the animals are behaving, but also whether or not they have the capability to persist. Dr. Christina Semeniuk apartment University of Windsor Windsor | Canada Interested in similar results? Get in touch! Want to achieve the same research quality as University of Windsor? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Université du Québec à Montréal - Neurolab URL: https://noldus.com/customer-stories/uqam-educational-research Description: L'Université du Québec à Montréal (UQAM), is taking you on a tour in their lab. Take a look at how they designed their rooms, what equipment they chose, and which software tools are used. @include('partials.hero-auroral') Back to Customer Stories Educational research Université du Québec à Montréal - Neurolab Human Behavior Research Prof. Julien Mercier from Université du Québec à Montréal is studying educational research. His lab is looking at refined brain information over time, involving the cognition and the affect of the learner. Prof. Julien Mercier apartment Université du Québec à Montréal Canada Interested in similar results? Get in touch! Want to achieve the same research quality as Université du Québec à Montréal - Neurolab? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Virginia Tech - Food Science & Technology URL: https://noldus.com/customer-stories/virginia-tech-food-science-technology Description: How do we experience food consumption? In response to seeing, smelling or tasting food, facial expressions demonstrate how we react to the particular food. @include('partials.hero-auroral') Back to Customer Stories The role of sensory evaluation Virginia Tech - Food Science & Technology Human Behavior Research Prof. Susan Duncan was a professor in Food Science & Technology at Virginia Tech. She focused on the role of flavor, sensory quality, and nutrient value of food. With the help of FaceReader, she captured how people are interacting with and responding emotionally to food products. Prof. Dr. Susan Duncan apartment Virginia Tech USA Interested in similar results? Get in touch! Want to achieve the same research quality as Virginia Tech - Food Science & Technology? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Customer Story - Wageningen University & Research URL: https://noldus.com/customer-stories/wur-eating-behavior Description: Wageningen University & Research is taking you on a tour in their lab. See how they designed lab rooms, and the equipment and software tools they used. @include('partials.hero-auroral') Back to Customer Stories Sensory science and eating behavior Wageningen University & Research Human Behavior Research Professor C. (Kees) de Graaf, PhD, Chairman Division of Human Nutrition, Professor in Sensory Science and Eating Behaviour at Wageningen University & Research, The Netherlands talks about measuring chewing behavior, bite size, and chewing frequency in order to understand eating behavior. He hopes that in five or ten years, we will be able to measure food intake in an accurate way without interfering with subjects. Prof. Kees de Graaf apartment Wageningen University & Research The Netherlands Interested in similar results? Get in touch! Want to achieve the same research quality as Wageningen University & Research? Let us show you how our tools can support your work. Book a demo or request more information. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## DanioScope URL: https://noldus.com/danioscope Description: DanioScope is an all-in-one system for measuring physiological parameters in zebrafish larvae and embryo's DanioScope How It Works Pricing Benefits Resources FAQ Contact Detailed research into fish larvae DanioScope If you are interested in researching physiological and behavioral parameters in (zebra)fish larvae and embryos, then DanioScope is the tool you need. Explore the options arrow_downward Standardized Increase reproducibility with calibrated measurements Flexible Can handle slightly moving animals by combining measures Time Saving Acquire data in batches from multiple videos How does DanioScope work? videocam Record First you record your models under a microscope fitted with a camera. This video is uploaded to DanioScope and analysis can begin. DanioScope supports videos over 60fps and handles a wide range of video formats. tune Choose parameters DanioScope allows you to measure various behavioral and physiological parameters in fish larvae and embryos. This not only allows you to measure behaviors like activity and tail coiling, but also blood flow and heart rate. analytics Analyze The software allows you to fine tune results by redefining thresholds. Furthermore, organize your data through flexible selection, grouping and displaying of data. You can easily export your data if you need more in-depth statistics. Learn more Get DanioScope for your lab Increase the throughput of your research and save time in preparing, acquiring and analyzing your zebrafish larvae and embryo data behavioral and physiological data with DanioScope. DanioScope perpetual license Access to all functionality Measure behavior and physiological parameters Easy to use & varied applications Request a quote Request a demo Build your complete solution Hardware DanioScope works with standard microscopes and cameras. We can help you choose the right setup for your specific application. Hardware Options DanioScope Hardware Setup Microscope, camera, and well plate holder for zebrafish larvae analysis. Contact Sales NoldusCare Add an additional year of NoldusCare to keep your software performing at its best. Includes the latest features, ongoing technical support, and access to the Noldus Academy. NoldusCare Extensions NoldusCare DanioScope 1 additional year of NoldusCare for DanioScope. Includes updates, support, and Noldus Academy access. Contact Sales Remote training Ensure a strong start with our remote training sessions. Led by experienced Noldus trainers, these sessions help you quickly become familiar with DanioScope. Training Packages DanioScope Training (Remote) Remote training session covering DanioScope setup, data acquisition, and analysis workflows. Contact Sales Hardware Options DanioScope Hardware Setup Microscope, camera, and well plate holder for zebrafish larvae analysis. Contact Sales NoldusCare Extensions NoldusCare DanioScope 1 additional year of NoldusCare for DanioScope. Includes updates, support, and Noldus Academy access. Contact Sales Training Packages DanioScope Training (Remote) Remote training session covering DanioScope setup, data acquisition, and analysis workflows. Contact Sales Applications of DanioScope Behavioral and physiological parameters to measure DanioScope is a flexible tool that can be used for many research applications. From toxicology to drug development. activity_zone Zebrafish activity Early embryo movements such as tail flicks, coiling, and convulsive behavior are sensitive readouts for toxicology and pharmacology. DanioScope measures activity non-invasively from video and reports burst activity, inactivity, duration, and movement counts. water_drop Blood/gut flow Flow measurements add insight if heart rate alone can't give the full picture. DanioScope quantifies blood vessel or gut flow from standard video by analyzing frame-to-frame pixel changes within a selected region, and reports flow as an activity percentage. cardiology Cardiology Zebrafish are a strong model for cardiac development and function. DanioScope provides fast, video-based heart rate and inter-beat interval assessment: select the heart region once, and the software automatically outputs beats per second and beats per minute. straighten Morphology Track growth and malformations over time using images or video snapshots. With simple drawing and calibration tools, DanioScope automatically measures lengths and areas such as tail length, eye size, and pericardial area, or any custom metric you define. More about DanioScope Learn more about early life zebrafish research Video Parameters in depth DanioScope explained in 2.5 min Want to know what parameters DanioScope can measure and how it does this? Watch this short video to learn more about the ins and outs of morphological and behavioral analysis in embryos and larvae. Blog Novel application of DanioScope Breathing frequency measurements Researchers from the University of Heidelberg used DanioScope in a novel way to objectively measure breathing in zebrafish embryos and larvae. You can read all about their methods in this blog. Read blog Your browser does not support the video tag. Frequently asked questions about DanioScope Can I analyze multiple animals simultaneously? Yes, you can measure many of the parameters like blood flow or heart rate separately for multiple animals in the same video file. Just draw and label the boxes around the correct animal. Can I use DanioScope for other species besides zebrafish? Yes, you can use DanioScope for other fish species. However, parameters that require organs or vessels to be visible can only be done in transparent animals. What camera do I have to use with DanioScope? DanioScope can handle a wide variety of cameras and types of video formats. We recommend using a higher sampling rate (60fps) to record the number of frames needed for a high-quality analysis. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## DanioScope Applications URL: https://noldus.com/danioscope/applications Description: Discover DanioScope applications for zebrafish activity analysis, heartbeat detection, and body length measurement. @include('partials.hero-auroral') Back to DanioScope All I need to know about DanioScope DanioScope has been used for many different applications. On this page you can find some of the blogs we have written for you to enlighten you on the applications of DanioScope. We have also compiled a list of recently published papers by application. Contact us Featured blog posts Blog A zebrafish model for ALS-related gene mutations How zebrafish are helping us to discover the mechanisms behind this neurodegenerative disease. Read this blog post Blog Using zebrafish as an early warning system of neurotoxic substances How can we use a zebrafish embryo model to detect possible neurotoxic chemical mixtures that are difficult to detect with normal chemical analyses? Read this blog post Blog Breathe easy, a novel approach to monitoring respiratory activity in zebrafish Researchers from the University of Heidelberg used DanioScope in a novel way to objectively measure breathing in zebrafish embryos and larvae. Read this blog post Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## DanioScope Publications URL: https://noldus.com/danioscope/publications Description: Explore publications and research papers using DanioScope for zebrafish larvae analysis. Back to DanioScope A detailed look at fish larvae DanioScope If you are interested in a scope of zebrafish embryo and larvae parameters such as embryo activity, cardiovascular measurements, morphology, and gut and blood flow, then DanioScope is just what you need. - Automated detection of zebrafish embryos – minimizing manual interference - Handles situations where the animal slightly moves by combining multiple measures - Acquire data in a batch from a list of videos Free demo DanioScope Relevant publications Here is an overview of some recent publications with DanioScope. If you feel like your publication should be on this list, send us an e-mail at: marcom@noldus.com. Zebrafish activity Bertoni, Í.; Sales, B.C.P.; Viriato, C.; Peixoto, P.V.L.; Pereira, L.C. Embryotoxicity Induced by Triclopyr in Zebrafish (Danio Rerio) Early Life Stage. Toxics 2024, 12, 255. Derkaczew, M.; Kędziora, B.; Potoczna, M.; Podlasz, P.; Wąsowicz, K.; Jóźwik, M.; Wojtkiewicz, J. The Study of Myo-Inositol's Anxiolytic Activity on Zebrafish (Danio Rerio). Nutrients 2024, 16, 1997. Du, Y.; Li, Q.; Zhou, G.; Cai, Z.; Man, Q.; Wang, W.C. Early-Life Perfluorooctanoic Acid Exposure Disrupts the Function of Dopamine Transporter Protein with Glycosylation Changes Implicating the Links between Decreased Dopamine Levels and Disruptive Behaviors in Larval Zebrafish. Sci. Total Environ. 2024, 917, 170408. Miles, K.D.; Barker, C.M.; Russell, K.P.; Appel, B.H.; Doll, C.A. Electrical Synapses Mediate Embryonic Hyperactivity in a Zebrafish Model of Fragile X Syndrome. J. Neurosci. 2024, 44. Blood/Gut flow Correia, D.; Bellot, M.; Goyenechea, J.; Prats, E.; Moro, H.; Gómez-Canela, C.; Bedrossiantz, J.; Tagkalidou, N.; Ferreira, C.S.; Raldúa, D. Parental Exposure to Antidepressants Has Lasting Effects on Offspring? A Case Study with Zebrafish. Chemosphere 2024, 355, 141851. Mu, X.; Liu, Z.; Zhao, X.; Yuan, L.; Li, Y.; Wang, C.; Xiao, G.; Mu, J.; Qiu, J.; Qian, Y. Bisphenol A Analogues Induce Neuroendocrine Disruption via Gut–Brain Regulation in Zebrafish. Environ. Sci. Technol. 2024, 58, 1022–1035. Cardiology Schimith, L.E.; Machado Da Silva, V.; Costa-Silva, D.G.D.; Seregni Monteiro, L.K.; Muccillo-Baisch, A.L.; André-Miral, C.; Hort, M.A. Preclinical Toxicological Assessment of Polydatin in Zebrafish Model. Drug Chem. Toxicol. 2024, 1–10. Da'as, S.I.; Thanassoulas, A.; Calver, B.L.; Saleh, A.; Abdelrahman, D.; Hasan, W.; Safieh‐Garabedian, B.; Kontogianni, I.; Nasrallah, G.K.; Nounesis, G.; et al. Divergent Biochemical Properties and Disparate Impact of Arrhythmogenic Calmodulin Mutations on Zebrafish Cardiac Function. J. Cell. Biochem. 2024, 125, e30619. Liu, Y.; Jin, X.; Ye, Y.; Xu, Z.; Du, Z.; Hong, H.; Yu, H.; Lin, H.; Huang, X.; Sun, H. Emerging Disinfection Byproducts 3-Bromine Carbazole Induces Cardiac Developmental Toxicity via Aryl Hydrocarbon Receptor Activation in Zebrafish Larvae. Environ. Pollut. 2024, 346, 123609. Morphology Marchese, M.; Bernardi, S.; Ogi, A.; Licitra, R.; Silvi, G.; Mero, S.; Galatolo, D.; Gammaldi, N.; Doccini, S.; Ratto, G.M. Targeting Autophagy Impairment Improves the Phenotype of a Novel CLN8 Zebrafish Model. Neurobiol. Dis. 2024, 197, 106536. Missawi, O.; Wouters, C.; Lambert, J.; Garigliany, M.-M.; Kestemont, P.; Cornet, V. Realistic Microplastics Harness Bacterial Presence and Promote Impairments in Early Zebrafish Embryos: Behavioral, Developmental, and Transcriptomic Approaches. Chemosphere 2024, 350, 141107. Sampaio, C.F.; Gravato, C.; de Oliveira, D.P.; Dorta, D.J. Deleterious Effects of Benzotriazoles on Zebrafish Development and Neurotransmission: 5-Chloro-Benzotriazole versus 1H-Benzotriazole. Sci. Total Environ. 2024, 912, 168741. Breathing frequency Kämmer, N.; Reimann, T.; Ovcharova, V.; Braunbeck, T. A Novel Automated Method for the Simultaneous Detection of Breathing Frequency and Amplitude in Zebrafish (Danio Rerio) Embryos and Larvae. Aquat. Toxicol. 2023, 258, 106493. Kämmer, N.; Reimann, T.; Braunbeck, T. Neurotoxic Pesticides Change Respiratory Parameters in Early Gill-Breathing, but Not in Skin-Breathing Life-Stages of Zebrafish (Danio Rerio). Aquat. Toxicol. 2024, 267, 106831. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## DanioVision URL: https://noldus.com/daniovision Description: Complete solution for zebrafish larvae activity and movement. Research many zebrafish parameters in this high-throughput environment. DanioVision How It Works What's Included Features Explore Customer Stories FAQ Contact Automated behavioral analysis for zebrafish research DanioVision DanioVision is a fully turnkey, end-to-end hardware and software solution designed specifically for high-throughput behavioral research with zebrafish larvae. It combines controlled conditions and stimulation, video recording, and automated analysis into a single standardized platform, enabling reproducible and scalable experiments across developmental stages and assay types. Explore what's included arrow_downward Purpose-built for zebrafish Integrated system optimized for zebrafish larvae High-throughput by design Run multiple arenas and conditions in parallel Reproducible stimulation and analysis Precisely controlled visual and auditory stimuli, robust analytics How DanioVision works Automated and optimized larvae observation chamber Assess zebrafish larvae behavior in the industry standard chamber with controlled lighting, temperature, and background conditions. All settings are automatic. track_changes Robust and accurate Automatically track up to 96 wells using EthoVision, generating metrics such as distance moved, velocity, and activity states. analytics Analyze and export Visualize behavioral responses, such as startle response or thigmotaxis, and export data for statistical analysis, screening pipelines, or integration with other datasets. Practical features One complete system. Everything included. DanioVision combines a controlled observation chamber, powerful EthoVision XT software, and expandable stimulation modules into one integrated solution for zebrafish larvae research. precision_manufacturing Complete hardware Everything required to create a controlled environment for reliable, high-throughput zebrafish tracking Controlled observation chamber IR-sensitive high-speed camera Adjustable white and infrared illumination Supports 96, 48, 24 and 6-well plates code Powerful software Track, analyze and control your experiments from one powerful software: EthoVision Automated tracking and behavioral analysis Complete experiment control Day/night cycle programming Flexible data export and publication-ready results extension Expandable to your research Expand your setup with fully integrated hardware designed for your research needs. Tapping Device Temperature Control Unit Toplight Unit Optogenetics Add-on Ready to bring DanioVision to your lab? Request a quote Request a demo Designed for advanced behavioral research DanioVision goes beyond tracking. Control your experimental environment with integrated stimulation and environmental modules to create reproducible, high-quality behavioral assays. Light, sound & temperature control Precisely control lighting, vibration, and temperature from a single platform. Program day-night cycles, deliver controlled stimuli, and maintain stable experimental conditions all directly from EthoVision XT. Photomotor response test Automatically perform photomotor response assays to evaluate locomotor activity and behavioral changes following light stimuli. Standardized high throughput protocols help generate reliable and reproducible results. Optogenetic stimulation Integrate optogenetic stimulation directly into your experiments using built-in LED modules. Program wavelengths, timing, and intensity within EthoVision XT to investigate neural circuits and behavior with precision. Features you'll love DanioVision is designed to give you full control over your zebrafish experiments. From light and temperature stimuli to high-throughput tracking, every feature is built to deliver reliable, reproducible data. Standardized experimental environment Minimizes variability and maximizes reproducibility across animals, sessions, and labs. settings_input_component Integrated stimulation control and output Deliver repeatable visual and acoustic stimuli synchronized with behavior for seamless analytics. speed High-throughput scalability Designed for screening applications without sacrificing data quality. Explore further Publications Browse peer-reviewed research papers and scientific publications that reference this product in their methodology. Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. DanioVision in real-world research Short videos showing how researchers use DanioVision Optogenetics Brown University Using optogenetics with DanioVision We visited Dr. Jessica Plavicki, of the department of Pathology and Laboratory Medicine of Brown University in Providence, Rhode Island. She runs her own lab where they are studying developing zebrafish, aimed at assessing the impact of chemical and/or environmental exposure, and genetic mutations on brain and heart health. Neurobiology Radboud University Zebrafish research with EthoVision and DanioVision Listen to Dr. Ruud van den Bos about his work in neurobiology and experimental psychology, and how zebrafish studies contribute to his field of research. He is experienced with DanioVision and EthoVision and explains why good tools are important for reliability and reproducibility in zebrafish experiments. Explore other customer stories Frequently asked questions Frequently asked questions Is DanioVision suitable for other species? Yes. DanioVision is optimized for zebrafish larvae and other small species, such as ticks, mosquitos, and estuarine fish. DanioVision excels in early developmental and small-species behavioral assays where high-throughput and environmental control are critical. Can DanioVision be combined with optogenetics? Yes. The optogenetics add-on provides a way to accurately control the application of optogenetic stimulation to up to 96 individuals simultaneously. This is easily programmed and controlled using EthoVision. How does DanioVision support reproducibility? DanioVision standardizes lighting, stimulation, recording, and analysis conditions, reducing variability and improving comparability across experiments and labs. All settings and outputs are open – no black boxes here. Is DanioVision suitable for screening studies? Absolutely. DanioVision is widely used for high-throughput pharmacological and toxicological screening, offering consistent conditions and automated analysis. How is DanioVision different from other systems on the market? DanioVision is a fully integrated system that combines controlled stimulation, standardized environmental conditions, synchronized video recording, and automated analysis. This eliminates the variability, custom engineering, and validation effort typically required when assembling separate hardware and software components. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## DanioVision Applications URL: https://noldus.com/daniovision/applications Description: DanioVision has been validated for a great variety of research applications. From light-dark arrays to startle response tracking. Back to DanioVision Research applications for DanioVision Zebrafish are used as research models in a great variety of fields. From embryos to adults, they have found their way into many labs. DanioVision is the ideal environment to track larval to juvenile fish. Below you can find some of the applications DanioVision has been used for. If you want to know more about a specific validation, feel free to contact us. Ask a question Applications of DanioVision Drug Discovery Zebrafish offer a genetically and physiologically relevant model to study disease mechanisms and screen candidate compounds. DanioVision enables high-throughput, multi-well tracking with integrated light and vibration stimuli for standardized assays. Toxicology Toxicology examines how environmental or chemical exposures affect organism health. Run repeatable light/dark and LPR assays to detect subtle changes in movement, arousal, and non-associative learning. Circadian rhythmicity Many behaviors follow day–night cycles, and disruptions can signal changes in neural and metabolic function. Program precise light cycles and capture long-term recordings with phase-based segmentation. Epilepsy Zebrafish larvae model genetic and chemically induced seizures. Use controlled stimuli and sensitive tracking to quantify burst activity, bout structure, and stereotypies. Anxiety research The zebrafish startle reflex is a conserved defensive response. Deliver precise taps or light cues and measure latency, magnitude, and decay over repeated presentations. Visual responsiveness Assays like larval photomotor response (LPR) and phototaxis probe visual pathways and sensorimotor integration. Control light color, intensity, and timing to evoke reliable responses. Movement disorders Zebrafish models help interrogate motor control deficits relevant to neurodegenerative and developmental conditions. Obtain continuous locomotor and postural metrics under controlled stimuli. Social preference Zebrafish shoaling behavior has often been tested in adult zebrafish. However, juvenile fish can also show social interaction. DanioVision offers a standardized environment for measuring zebrafish behavior. Optogenetics Zebrafish larvae are naturally transparent, making them ideal for light-based manipulation of neural circuits. The Optogenetics Add-on delivers precise colors, intensities, and patterns, fully synchronized with behavioral tracking. The ins and outs of zebrafish research Learn all about the why, when and how regarding zebrafish development and behavior. Download for free arrow_forward Featured blog posts Blog How to measure a zebrafish larva's highly stereotyped response to water motion? At the Max Planck Institute for Medical Research in Heidelberg, Groneberg and colleagues researched one of the neural bases for behavior in Danio rerio. Read this blog post arrow_forward Blog Tracking zebrafish in 3D Dr. Kalueff has started organizing zebrafish behavioral neuroscience and phenotyping workshops, running for over a decade since October 2012. Read this blog post arrow_forward Blog Getting robust results: one zebrafish is not like the other Zebrafish larvae locomotor behavior often has a high variability. So how can you make your study more robust? Read this blog post arrow_forward MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## DanioVision Resources & Publications URL: https://noldus.com/daniovision/publications Description: Explore DanioVision publications and resources for zebrafish behavioral research and high-throughput screening. Back to DanioVision DanioVision Resources and publications When you choose DanioVision, you're not choosing tools — you're choosing research solutions that have been trusted by scientists around the world. - Technical specifications - Featured blog posts - Selected publications Book a demo DanioVision Selected publications Here is a selection of recent papers that mention the use of DanioVision. If you feel your paper should be on this list, please let us know at marcom@noldus.com. All publications on Google Scholar Antiseizure medications in Dravet syndrome Whyte-Fagundes, P.A., Vance, A., Carroll, A., Figueroa, F., Manukyan, C., Baraban, S. (2024). Testing of putative antiseizure medications in a preclinical Dravet syndrome zebrafish model. Brain Communications, Volume 6, Issue 3. Sodium valproate effects on zebrafish Caioni, G., Merola, C., Perugini, M., Angelozzi, G., Amorena, M., Benedetti, E., Lucon-Xiccato, T., Bertolucci, C. (2024). Sodium valproate effects on the morphological and neurobehavioral phenotype of zebrafish. Environmental Toxicology and Pharmacology, Volume 110. Aluminium and cadmium effects on zebrafish Capriello, T.; Consiglio Grimaldi, M.; Cofone, R.; D'Aniello, S.; Ferrandino, I. (2019). Effects of aluminium and cadmium on hatching and swimming ability in developing zebrafish. Chemosphere, 222, 243-249. Spinal cord injury in zebrafish Ellström, I.D.; Spulber, S.; Hultin, S.; Norlin, N.; Ceccatelli, S.; Hultling, C.; Uhlén, P. (2019). Spinal cord injury in zebrafish induced by near-infrared femtosecond laser pulses. Journal of Neuroscience Methods, 311, 259-266. DanioVision in action Case study Zebrafish larvae activity measurement How do you study locomotor behavior in zebrafish larvae? In this case study we go over the use of zebrafish in Parkinson's disease research. Download White paper Epilepsy research in zebrafish The development of accurate, high-throughput models for epilepsy research is crucial. Read how researchers use EthoVision XT to develop a multi-parametric analysis in zebrafish. Download White paper Eco-neurotoxicity Many contaminants in our environment have shown to be neurotoxic. Zebrafish are often used to study the effect of toxic compounds on behavior. Read how DanioVision facilitates this research. Download MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford MIT Bayer University of Washington ETH Zurich AstraZeneca Stanford "DanioVision allows an easy solution to monitor and quantify physical activity and swimming behavior in a large number of larvae simultaneously." Dr Marcel den Hoed Uppsala University, Sweden Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## DanioVision Setup & Add-ons URL: https://noldus.com/daniovision/setup Description: Learn how to set up DanioVision for zebrafish observation, including add-ons and configuration options. @include('partials.hero-auroral') Back to DanioVision Add-ons for DanioVision DanioVision is a complete system, including a fully functional EthoVision license and the Observation Chamber with white light, IR-light, and IR-sensitive camera. With this system you can perform a wide range of experiments. However, we also offer a range of add-ons to further broaden your experimental options with DanioVision. The currently available add-ons are listed on this page. Book a demo Add-ons for DanioVision Temperature Control Unit Unlike competing systems where the temperature is measured in the control unit, our system controls the exact temperature of the water directly in the Observation Chamber. This way, you are sure that the water in the well plates is always at the desired temperature. Tapping Device Zebrafish larvae display a robust startle response. The Tapping Device (a solenoid) is inserted at the bottom of the basin where your well plate or petri dish is placed in the DanioVision Observation Chamber. You can set the stimulus intensity on eight different levels. Optogenetics The optogenetics add-on provides a way to accurately control and precisely time the application of optogenetic stimulation to up to 96 individuals simultaneously. This is easily programmed and controlled using EthoVision. Light-dark grid One example of a custom solution is a light-dark grid, commonly used to investigate anxiety behavior in zebrafish. The grid creates a static dark and light half in each well. Since the grid is IR light translucent the tracking of the zebrafish is unaffected. DanioVision technical specifications Download tech specs Powered by EthoVision video tracking What do you need for your zebrafish studies? DanioVision fits standard multi-well plates, from 1 up to 96 wells. Its design allows for consistent and accurate lighting and imaging across wells without shadowing. This ensures you have quality data and therefore more reliable results. EthoVision isn't just tracking your zebrafish and recording parameters like distance. It can track relative speed and overall activity. This can be analysed for your whole experiment or for specified time bins, for example before and after a stimulus has been initiated. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Data acquisition systems URL: https://noldus.com/data-acquisition-systems Description: Looking for physiological measurement systems? Noldus offers several data acquisition systems that work in conjunction with our software. Record essential processes Data Acquisition Systems To understand how participants' bodies respond to different stimuli and to get insights into their emotional states, stress levels, and cognitive processes, collecting physical signals is the way to go. - checkCollect ECG, EEG, skin conductance, respiration, and more - checkGain insights into the unconscious, automatic responses - checkMeasure real-time bodily reactions to stimuli Looking for advice on data acquisition? Physiology and multimodal research Although your test participant may appear to be calm, he or she may be concealing a considerable amount of stress. To reveal this level of stress, you can combine behavioral observations with physiological measurements acquired with a data acquisition system. For example, skin conductance is a method of measuring the electrical conductance of the skin which is used as an indication of psychological or physiological arousal. When combined with behavioral data, it provides a complete picture of the participant's experience. Benefits of data acquisition Unravel the mysteries of the brain Use EEG and other neurophysiological measures to understand brain activity during tasks. neurology Investigate drivers behind decisions Understand the physiological underpinnings of decision-making processes. monitor_heart Measure implicit responses Capture EEG, GSR, heart rate, and other signals that reveal unconscious reactions. sync Combine modalities Combine behavioral observations and physiological responses to understand the motivations and cognitive processes behind human behavior. Integrating physiological data with Noldus tools You can only draw accurate conclusions when your data is in sync. With Noldus tools, you can seamlessly synchronize multiple data streams, including physiological data. That is why Noldus has partnered with BIOPAC and Bitbrain. hub NoldusHub All-in-one system for multimodal research. Streamline and synchronize all your data sources including physiology. Learn more arrow_forward videocam NoldusViso AV tool to capture participants' behaviors. Combine video with physiological data for complete analysis. Learn more arrow_forward edit_note The Observer XT Complete software for behavioral research. Synchronize physiological signals with behavioral coding. Learn more arrow_forward Want to add physiological data to your research? Get in touch! Our team can help you choose the right data acquisition setup and integrate it with your existing research workflow. @csrf First name * Last name * Email address * Request *Make a choiceReceive informationRequest pricingFree demoBook an online meetingOther Institute/company * How can we help you? * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Submit --- ## EntoLab URL: https://noldus.com/entolab Description: Computerized system for automated high-throughput screening of insect behavior. Learn all about EntoLab on this page. EntoLab How It Works Pricing Applications Resources FAQ Contact High throughput insect behavior testing EntoLab Looking for a tool to speed up insect behavior tracking or plant interaction screening? EntoLab is a great system for automated screening of insect behavior. Explore the options arrow_downward Efficient Save 90% in time and costs Throughput Run up to 300 trials simultaneously Integrated Software and hardware work seamlessly How does EntoLab work? tune Setup EntoLab is used for many applications. Therefore, the observation chamber has a flexible design allowing for the integration of a variety of assay plates. Either observe the animals alone in an arena or place plant material between them to test interaction. videocam Record After setting up your observation chamber you can start recording. EntoLab uses EthoVision to control and track your experiment. EthoVision can process a single video file or a batch of files originating from multiple chambers, all fully automated. analytics Analyze Track files from EthoVision are imported into EthoAnalysis, a specialized software package developed for the analysis of insect behavior. The software can segment your data after which you can perform analysis to compute a variety of behaviors. Learn more Get EntoLab for your lab The EntoLab setup is a convenient benchtop system that will enrich your screening facility. With its integrated software you have an all-in-one solution for screening insect behavior. EntoLab + EthoVision + EthoAnalysis Fully integrated system High-resolution camera with lighting setup for optimal tracking Perfect for multi-day testing Request a quote Request a demo Build your complete solution Hardware EntoLab includes a complete hardware setup. Contact us for options that best fit your research protocol. Hardware Options EntoLab Hardware Complete EntoLab hardware setup including arena, camera, and illumination for insect behavioral research. Contact Sales NoldusCare Add an additional year of NoldusCare to keep your software performing at its best. Includes the latest features, ongoing technical support, and access to the Noldus Academy. NoldusCare Extensions NoldusCare EntoLab 1 additional year of NoldusCare for EntoLab. Includes updates, support, and Noldus Academy access. Contact Sales Remote training Ensure a strong start with our remote training sessions. Led by experienced Noldus trainers, these sessions help you get up to speed quickly. Training Packages EntoLab Training (Remote) Remote training session covering EntoLab setup, data acquisition, and analysis workflows. Contact Sales Hardware Options EntoLab Hardware Complete EntoLab hardware setup including arena, camera, and illumination for insect behavioral research. Contact Sales NoldusCare Extensions NoldusCare EntoLab 1 additional year of NoldusCare for EntoLab. Includes updates, support, and Noldus Academy access. Contact Sales Training Packages EntoLab Training (Remote) Remote training session covering EntoLab setup, data acquisition, and analysis workflows. Contact Sales Applications of EntoLab What can I use EntoLab for? EntoLab makes it easy to quantify insect behavior at a large scale. Run standardized assays for preference, feeding, attraction, and stress responses, and turn complex insect–environment interactions into fast, reliable data you can trust. potted_plant Plant breeding Screen plant genotypes for insect resistance by tracking pest behavior and surface preferences. Quantify treatment effects on plant–insect interactions to identify traits that deter pests and support selection of more resilient varieties. bug_report Beneficial insects Phenotype beneficial insects to evaluate tolerance to heat, cold, humidity, and drought. Add memory retention assays and quality control to ensure mass-reared insects perform reliably in biological control programs. Insecticide testing Assess feeding preference, anti-feeding responses, and tolerance development in insect populations. Compare modes of action such as stomach and contact toxicity, fumigants, and repellents using two-choice or multiple-choice assays. public Behavioral ecology Test attraction or repellence to compounds using olfaction assays such as headspace testing. Combine associative learning experiments with genetic analysis to link behavioral traits to specific genotypes. More about insect research Learn more about insect behavioral study Video What does insect screening look like? Tracking in EntoLab Curious to see what tracking in an EntoLab chamber looks like? In this short video you can explore an example of a 2-choice test in aphids. Blog Replacing rodents with insects Forced swim test in flies In this blog we delve into the use of flies as a new perspective for behavioral testing. How do they compare to rodents? And can conventional rodent tests be adapted to insects? Read blog Your browser does not support the video tag. Frequently asked questions about EntoLab How reproducible are experiments done with EntoLab? EntoLab uses standardized multi-arena assay plates and a fixed camera/lighting geometry inside a compact observation chamber, so you can run many identical trials and compare treatments or genotypes consistently. Can I control light, humidity and temperature during tests? Light in the Observations Chamber can be controlled and optimized for your experiment. EntoLab doesn't have dedicated sensors or controllers for humidity and temperature, but we are happy to help you find a solution. Can I track flying animals in EntoLab? No. EntoLab is designed to test insects in 2D assay plates. If you need to test flying animals in 3D, we do sell configuration for EthoVision in combination with a wind tunnel for reliable tracking in 3 dimensions. What behavior and readouts can I quantify? EntoLab quantifies insect choice and movement in standardized arenas. You can measure preference (which option is chosen), time spent in each zone, activity versus inactivity, movement bouts, and basic movement statistics like distance and speed. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## EntoLab Applications URL: https://noldus.com/entolab/applications Description: A page describing some of the use cases of EntoLab @include('partials.hero-auroral') Back to EntoLab What can I use EntoLab for? EntoLab was originally designed as a high-throughput system for phenotyping plant resistance against chewing or sucking insects through video tracking of insect behavior. Hundreds of plant genotypes can be compared in a few days using assay plates with up to 300 individual arenas. Talk to the experts Applications of EntoLab Plant breeding Plant breeding focuses on developing crops with enhanced resistance against insects. By studying surface structure preferences, researchers can identify traits that deter insect pests. Additionally, treatment effects on plant-insect interactions are analyzed, aiding in the selection of more resilient crop varieties. Beneficial insects Behavioral phenotyping of beneficial insects is crucial for understanding their habitat tolerance to varying conditions such as heat, cold, humidity, and drought. Memory retention studies help evaluate their effectiveness in ecological roles, while quality control ensures the reliability of mass-reared insects for biological control programs. Insecticide testing Insecticide testing examines tolerance development within insect populations, including feeding preference and anti-feeding responses. Researchers assess various modes of action, such as stomach toxicity, contact toxicity, and the effectiveness of fumigants and repellents. Behavioral ecology EntoLab allows you to test the olfaction of insects through methods like headspace testing. This allows you to test either the attraction or repellence to certain compounds. Associative learning allows you to understand how insects form connections with these sensory experiences. Developed in collaboration with Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## EntoLab Setup URL: https://noldus.com/entolab/setup Description: A page describing the software and hardware of EntoLab @include('partials.hero-auroral') Back to EntoLab How do I use EntoLab? EntoLab is an integrated hardware/software system consisting of a compact observation chamber and a Windows software suite. The EntoLab software suite consists of a range of software programs for video tracking, camera settings optimization, video streaming, and data processing and analysis. Get in contact Developed in collaboration with Which hardware do I need? The EntoLab setup is a convenient benchtop system that will enrich your screening facility. The equipment can also be mounted on a cart with integrated computer equipment, providing a mobile setup that can easily move between labs. The EntoLab system includes: - checkCompact benchtop cabinet - checkHigh-resolution, light-sensitive color video camera (2040x2046 pixels) with 1" 25mm lens - checkVertically adjustable camera mount - checkLED arrays for overhead illumination and backlight panel - checkRemovable Fresnel lens to rectify viewing angle - checkAnti-fogging cover plate and lateral ventilation unit, with adjustable power supply EntoLab observation chamber With EntoLab, you can standardize your test environment, including multi-arena assay plates and illumination, and collect your data efficiently. The EntoLab Observation Chamber is designed in such a way to maximize image quality, reliability of tracking and throughput. Furthermore, the EntoLab hardware is easy to use and clean. Assay plates for insect research Assay plates EntoLab offers a modular system of assay plates that can track a variety of insects, plants, and substrates, with up to 300 arenas on a single plate. A key feature is the synchronized release of insects from a cage plate beneath the arena plate, ensuring a uniform start for all trials. Foam assay plates The foam assay plates consist of a foam sample support plate and a top arena plate. The support plate cushions test samples like leaf fragments and has 126 holes for insects to emerge into the arena. Depending on the arena plate shape, insects encounter a sample on one side (no-choice) or both sides (choice). Plexiglass assay plates Plexiglass assay plates are designed for thicker samples like fruits, stems, or agar. They feature a support plate with chambers for the samples and 126 holes for insects to emerge. Insects will find either a single sample (no-choice) or two different samples (2-choice) after being released. What does the software offer me? EthoVision XT The EntoLab system comes with EthoVision XT, the renowned computer vision and video tracking software. EthoVision XT processes each high-resolution image in the digital video file, detects the insect against the background in each arena, extracts its body center, and generates a track file for each arena. Due to its superior object detection algorithms, EthoVision XT can handle the most challenging insect-plant combinations. EthoVision XT can process a single video file or a batch of files originating from multiple EntoLab chambers, in a fully automated fashion. EthoAnalysis Track files are imported into EthoAnalysis, a specialized software package developed for the analysis of insect behavior recorded with EthoVision XT. Based on various user settings, which can be specific for an insect species, EthoAnalysis translates the raw track data into series of zone-specific behaviors of three categories: halting, moving, and not-detected. From these time series, various behavior statistics are computed, either for the complete trial or per zone, per hour, or per behavior category, including duration (short/medium/long) or movement velocity (slow/medium/fast). Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## EthoVision URL: https://noldus.com/ethovision Description: EthoVision XT is the worlds number 1 video tracker, accurately tracking rodents, zebrafish and insects and automatically determining rodent behavior from video EthoVision How It Works Pricing Features Explore Success Stories FAQ Contact Automated video tracking for animal behavior research EthoVision EthoVision is the gold-standard video tracking software for automatically tracking movement, posture, and activity with high precision and analyzing results across a wide range of species, apparatuses, and experimental paradigms. Trusted by thousands of laboratories worldwide, EthoVision helps you move from raw video to publishable results faster, while maintaining full transparency, reproducibility, and scientific rigor. Explore the options arrow_downward Effortless experiment setup Predefined workflows reduce setup time and errors Publish with confidence Proven detection algorithms trusted by labs and reviewers alike Flexible across species and setups Monitor rodents, insects, or fish in varied environments How EthoVision works videocam Record Capture behavior using virtually any camera setup. EthoVision supports live tracking or analysis from prerecorded video files, including multi-camera configurations. pets Detect and capture behavior Automatic detection settings allow reliable tracking even in challenging conditions such as variable lighting, reflections, or complex backgrounds. analytics Analyze and export Visualize trajectories, heat maps, and time-based graphs. Export data in formats compatible with common statistical and data analysis tools for further processing and reporting. Learn more {{pricing-eur:1433|usd:1434|restricted:1435}} Build your complete solution Hardware Pair your EthoVision software with hardware designed for behavioral research. From open fields to multi-arena setups, choose the configuration that fits your protocol. Hardware Options Open Field 40x40cm Standard open field arena for rodent behavioral testing. Compatible with EthoVision video tracking. Contact Sales NoldusCare Add an additional year of NoldusCare to keep your software performing at its best. Includes the latest features, ongoing technical support, and access to the Noldus Academy. The first year is included free of charge. NoldusCare Extensions NoldusCare EthoVision Essential 1 additional year of NoldusCare for EthoVision Essential. € 500 Add to quote NoldusCare EthoVision Advanced 1 additional year of NoldusCare for EthoVision Advanced. € 1.000 Add to quote NoldusCare EthoVision Premium 1 additional year of NoldusCare for EthoVision Premium. € 4.500 Add to quote Remote training Ensure a strong start with our remote training sessions. Led by experienced Noldus trainers, these sessions help you quickly become familiar with the software. The fastest way to start working efficiently from day one. Training Packages Essential Training (Remote) 2-hour remote training session covering essential EthoVision features and workflows. € 500 Add to quote Advanced Training (Remote) 5-hour remote training with advanced analysis techniques and protocol design. € 1.250 Add to quote Premium Training (Remote) Full-day remote training covering all features including advanced multi-arena setups. € 2.000 Add to quote Hardware Options Open Field 40x40cm Standard open field arena for rodent behavioral testing. Compatible with EthoVision video tracking. Contact Sales NoldusCare Extensions NoldusCare EthoVision Essential 1 additional year of NoldusCare for EthoVision Essential. € 500 Add to quote NoldusCare EthoVision Advanced 1 additional year of NoldusCare for EthoVision Advanced. € 1.000 Add to quote NoldusCare EthoVision Premium 1 additional year of NoldusCare for EthoVision Premium. € 4.500 Add to quote Training Packages Essential Training (Remote) 2-hour remote training session covering essential EthoVision features and workflows. € 500 Add to quote Advanced Training (Remote) 5-hour remote training with advanced analysis techniques and protocol design. € 1.250 Add to quote Premium Training (Remote) Full-day remote training covering all features including advanced multi-arena setups. € 2.000 Add to quote Features Features you'll love EthoVision provides powerful features that help you bring your behavioral research to the next level. See what's included track_changes High-precision tracking and behavior recognition Track position, movement, and activity with sub-millimeter accuracy depending on camera resolution and setup. tune Flexible detection methods Choose the detection approach that best fits your species and experimental setup, including deep learning-based detection of multiple animals. speed Real-time and offline analysis Measure distance, velocity, acceleration, angular velocity, zone visits, latency, mobility states, and custom user-defined variables. Analyze behavior live during experiments or offline from stored video files. Explore further Publications Browse peer-reviewed research papers and scientific publications that reference this product in their methodology. Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## EthoVision Applications URL: https://noldus.com/ethovision/applications Description: EthoVision XT is ready to follow the movement, activity, and behavior of your animal. In other words, you can start tracking and detecting activity. @include('partials.hero-auroral') Back to EthoVision Research applications EthoVision is a thoroughly validated video tracker which can be used for rodents, fish, insects and other animals. It also serves as the engine for our hardware solutions such as DanioVision and the PhenoTyper; flexible observation cages to take your research even further. Contact our sales team Applications of EthoVision Anxiety & fear Many psychiatric illnesses are depression- or anxiety-related disorders. Behavioral tests with rodents are crucial to get insights on the underlying mechanisms and eventually find new treatments. Read more arrow_forward Imaging & optogenetics Optogenetics is a method to specifically activate or even inhibit small groups of neurons with light. By assessing the effect of this stimulation on animal behavior, one can gain insight into neuronal functioning. Read more arrow_forward General locomotor activity Video tracking recognizes your animal from a live video feed or video file and is able to track its movement or activity. For objective data collection, video tracking software is a must. Read more arrow_forward Learning & memory There is a wide range of well-validated paradigms available for testing cognition. Studies focus on different types of learning and memory, such as spatial memory, long-term, short-term, and working memory. Read more arrow_forward Long-term behavioral testing Long-term behavioral testing is ideal to monitor the daily rhythm, activity patterns, stereotypic and epileptic behavior, or eating and drinking behavior of your lab animal over a consecutive period of time. Read more arrow_forward Social behaviors The study of social interaction between two or more animals is an interesting model for studying schooling or shoaling, or for modeling disorders that affect social behavior, such as schizophrenia and autism. Read more arrow_forward Your essential research toolkit Free e-book Want to know more about behavioral neuroscience? Check out our free downloadable e-book where we explain from A to Z why and how we measure certain behavior in rodents, what they translate to and how you can put EthoVision to the most advantage in your research. Download for free arrow_forward Free buyer's guide Want to know more about the perfect video tracking setup? Already have the basics down and looking for the best solution for your behavioral research? Our video tracking buyer's guide lays out the groundwork for you and compares all the options out there on the market. Download for free arrow_forward Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## EthoVision Resources & Publications URL: https://noldus.com/ethovision/publications Description: Explore EthoVision XT’s resources: extensive guides, case studies, and trainings to enhance your research. Back to EthoVision Resources and publications EthoVision is the most widely applied video tracking software that tracks and analyzes the behavior, movement, and activity of any animal. - A cost-effective solution for all standard behavioral tests - High-throughput and high-content testing - Suitable for sophisticated test-protocols Try it for free EthoVision Main competitor EthoVision Selected publications EthoVision is the preferred behavioral tool for scientists that publish in high impact journals. Zebrafish - Toxicology and development - Sulukan, E. et al. (2023). Global warming and glyphosate toxicity (II): Offspring zebrafish modelling with behavioral, morphological and immunohistochemical approaches. Science of The Total Environment, 856 (1). https://doi.org/10.1016/j.scitotenv.2022.158903 - Caporale, N. et al (2022). From cohorts to molecules: Adverse impacts of endocrine disrupting mixtures. Science, vol 375 issue 6582. https://doi.org/10.1126/science.abe8244 - Rehman, S. et al (2022). Developmental defects and behavioral changes in a diet-induced inflammation model of zebrafish. Frontiers in Immunology, volume 13 - 2022. https://doi.org/10.3389/fimmu.2022.1018768 Zebrafish - Cognition, learning and memory - Johnson, A. et al (2023). Examining behavioural test sensitivity and locomotor proxies of anxiety-like behaviour in zebrafish. Scientific reports, volume 13, Article number: 3768 (2023). https://doi.org/10.1080/00140139.2022.2157493. - Singh, H. et al (2022). Learning Deficits and Attenuated Adaptive Stress Response After Early-Life Seizures in Zebrafish. Frontiers in Neuroscience, Volume 16 - 2022. https://doi.org/10.3389/fnins.2022.869671 Zebrafish - Autism spectrum disorders (ASD) - Gabellini, C. et al (2022). CRISPR/Cas9-Induced Inactivation of the Autism-Risk Gene setd5 Leads to Social Impairments in Zebrafish. International Journal of Molecular Sciences, 2023, 24(1), 167. https://www.mdpi.com/1422-0067/24/1/167 - Zheng, J. et al (2022). Knockout of Katnal2 Leads to Autism-like Behaviors and Developmental Delay in Zebrafish. International Journal of Molecular Sciences, 2022, 23 (15). https://doi.org/10.3389/frcha.2023.1214890 Mice and Rats - Emotional behavior, social behavior, anxiety and stress - Birnie, M.T. et al (2023). Stress-induced plasticity of a CRH/GABA projection disrupts reward behaviors in mice. Nature Communications, 14, Article number: 1088. https://doi.org/10.1038/s41467-023-36780-x - Byun, Y., & Noh, J. (2024). Social play exclusion model in adolescent rats: Monitoring locomoter and emotional behavior associated with social play and examining c-Fos expression in the brain. Physiology & Behavior, 273, Article number: 114379. https://doi.org/10.1016/j.physbeh.2023.114379 - Oh, H. et al (2023). Kv7/KCNQ potassium channels in cortical hyperexcitability and juvenile seizure-related death in Ank2-mutant mice. Nature Communications, 14, Article number: 3547. https://doi.org/10.1038/s41467-023-39203-z - Liu, J. et al (2022). GW4064 Alters Gut Microbiota Composition and Counteracts Autism-Associated Behaviors in BTBR T+tf/J Mice. Frontiers in Cellular and Infection Microbiology, Volume 12 - 2022. https://doi.org/10.3389/fcimb.2022.911259 - Cassidy, B.R. et al (2023). Progressive cognitive impairment after recovery from neuroinvasive and non-neuroinvasive Listeria monocytogenes infection. Frontiers in Immunology, volume 14 - 2023. https://doi.org/10.3389/fimmu.2023.1146690 - Cassidy, B.R. et al (2023). Systemic infection of mice with neuroinvasive Listeria monocytogenes triggers cognitive decline and persistent increases in brain CD8+ T-lymphocyte populations. Journal of Affective Disorders Reports, Volume 12 (100536). https://doi.org/10.1016/j.jadr.2023.100536 - Hendrickx, J.O. et al (2022). Age-related cognitive decline in spatial learning and memory of C57BL/6J mice. Behavioral Brain Research, Volume 418. https://doi.org/10.1016/j.bbr.2021.113649 - Williams, Z.A.P. et al (2023). Sex-specific effects of voluntary wheel running on behavior and the gut microbiota-immune-brain axis in mice. Brain, Behavior, & Immunity - Health, Volume 30 (100628). https://doi.org/10.1016/j.bbih.2023.100628 - Xu, N. et al (2022). Adiponectin Ameliorates GMH-Induced Brain Injury by Regulating Microglia M1/M2 Polarization Via AdipoR1/APPL1/AMPK/PPARγ Signaling Pathway in Neonatal Rats. Frontiers in Immunology, volume 13 - 2022. https://doi.org/10.3389/fimmu.2022.873382 Mice and Rats - Autism spectrum disorders (ASD) - Kafle, B.D., Bernal, J.S. & Fadamiro, H.Y. (2025). Three-dimensional flight analysis shows associative learning enhances foraging behavior of the specialist parasitoid, Microplitis croceipes. Entomologia Experimentalis et Applicata 00, 1–10. https://doi.org/10.1111/eea.13560 - Ilie, O. D., Duta, R., Jijie, R., Nita, I. B., Nicoara, M., Faggio, C., Dobrin, R., Mavroudis, I., Ciobica, A., & Doroftei, B. (2022). Assessing Anti-Social and Aggressive Behavior in a Zebrafish (Danio rerio) Model of Parkinson’s Disease Chronically Exposed to Rotenone. Brain Sciences, 12(7), 898. https://doi.org/10.3390/brainsci12070898 - Jijie, R., Solcan, G., Nicoara, M., Micu, D., & Strungaru, S. A. (2020). Antagonistic effects in zebrafish (Danio rerio) behavior and oxidative stress induced by toxic metals and deltamethrin acute exposure. Science of the Total Environment, 698, 134299. https://doi.org/10.1016/j.scitotenv.2019.134299 - Hinze, A., Lantz, J., Hill, S. R., & Ignell, R. (2021). Mosquito host seeking in 3D using a versatile climate-controlled wind tunnel system. Frontiers in behavioral neuroscience, 15, 643693. https://doi.org/10.3389/fnbeh.2021.643693 Most-Cited EthoVision Publications EthoVision has been cited in over 35,000 peer-reviewed publications since 1995. Below are the foundational methodology papers and high-impact research from Nature, Cell, and leading neuroscience journals that relied on EthoVision for behavioral tracking and analysis. Foundational Research on EthoVision The methodology and validation papers that established EthoVision as the standard tool for automated behavioral tracking. EthoVision: A versatile video tracking system for automation of behavioral experiments Noldus LPJJ, Spink AJ, Tegelenbosch RAJ Behavior Research Methods, Instruments & Computers, 33, 398-414 (2001) Cited 4,200+ times. The foundational paper introducing EthoVision for automated behavioral analysis. format_quote4,200+ The EthoVision video tracking system: a tool for behavioral phenotyping of transgenic mice Spink AJ, Tegelenbosch RAJ, Buma MOS, Noldus LPJJ Physiology & Behavior, 73(5), 731-744 (2001) Cited 890+ times. Validation of EthoVision for phenotyping transgenic mouse models in neuroscience. format_quote890+ Computerised video tracking, movement analysis and behaviour recognition in insects Noldus LPJJ, Spink AJ, Tegelenbosch RAJ Computers and Electronics in Agriculture, 35(2-3), 201-227 (2002) Cited 520+ times. Extension of EthoVision tracking to insect behavior and entomology research. format_quote520+ High-Impact Research Using EthoVision Landmark studies published in Nature, Cell, and top neuroscience journals that chose EthoVision for behavioral data collection and analysis. Exercise Enhances Learning and Hippocampal Neurogenesis in Aged Mice van Praag H, Shubert TE, Zhao C, Gage FH Journal of Neuroscience, 25(38), 8680-8685 (2005) Cited 2,096 times. Used EthoVision to measure locomotor activity and spatial learning in the Morris water maze. format_quote2,096 Regulation of parkinsonian motor behaviours by optogenetic control of basal ganglia circuitry Kravitz AV, Freeze B, Parker PRL, Kay K, Thwin MT, Deisseroth K, Kreitzer AC Nature, 466, 622-626 (2010) Cited 1,931 times. Published in Nature. Used EthoVision to quantify motor behavior changes in optogenetically manipulated mice. format_quote1,931 Maternal Immune Activation Alters Fetal Brain Development through Interleukin-6 Smith SEP, Li J, Garbett K, Mirnics K, Patterson PH Journal of Neuroscience, 27(40), 10695-10702 (2007) Cited 1,634 times. Used EthoVision for open field and social interaction behavioral testing in autism models. format_quote1,634 Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice Sharon G, Cruz NJ, Kang DW, Gandal MJ, Wang B, et al. Cell, 177(6), 1600-1618 (2019) Cited 1,196 times. Published in Cell. Used EthoVision for comprehensive behavioral phenotyping of gnotobiotic mice. format_quote1,196 Sodium oligomannate remodels gut microbiota and suppresses neuroinflammation to inhibit Alzheimer's disease progression Wang X, Sun G, Feng T, Zhang J, Huang X, et al. Cell Research, 29, 787-803 (2019) Cited 1,138 times. Published in Cell Research. Used EthoVision for Morris water maze spatial memory assessment in Alzheimer's models. format_quote1,138 Epigenetic Transmission of the Impact of Early Stress Across Generations Franklin TB, Russig H, Weiss I, Graff J, Linder N, Mansuy IM Biological Psychiatry, 68(5), 408-415 (2010) Cited 1,121 times. Used EthoVision for elevated plus maze and open field anxiety-related behavioral testing. format_quote1,121 Targeting the Microbiota-Gut-Brain Axis: Prebiotics Have Anxiolytic and Antidepressant-like Effects Burokas A, Arboleya S, Moloney RD, Peterson VL, Murphy K, et al. Biological Psychiatry, 82(7), 472-487 (2017) Cited 953 times. Used EthoVision for tail suspension, forced swim, and social interaction behavioral assessments. format_quote953 Citation data from OpenAlex (August 2026). EthoVision XT has been cited in 35,000+ peer-reviewed publications across 4,000+ research sites worldwide since 1995. Trusted partners, ethical standards, and expert webinars Our partners In this network of partners, we keep on building new opportunities for your research. View partners arrow_forward Ethics in animal testing Learn about our commitment to ethical standards and responsible animal research practices. Learn more arrow_forward Expert webinars Watch webinars from experts in animal behavior research and learn how to get the most out of EthoVision. Watch webinars arrow_forward Want more info? Book a demo! Does this solution sound interesting to you? But do you want more info before making a final decision? Feel free to book a demo with us! We're happy to help you make a choice that fits your needs. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By submitting, you agree to our privacy policy. * Submit --- ## EthoVision Setup URL: https://noldus.com/ethovision/setup Description: Start your experiment in EthoVision XT from scratch or save time by using one of the predefined templates. @include('partials.hero-auroral') Back to EthoVision Effortless setup EthoVision's setup process is designed with efficiency and flexibility in mind, so you can focus on what truly matters — your research. - Experiment templates to get started in a few clicks - Detection settings built on deep learning technology - Arena definition to define any arena or zone of interest Contact our sales team Your research your way Easy experimental startup EthoVision makes setting up experiments straightforward with pre-configured templates and automatic detection settings. This helps reduce setup time, allowing you to focus more on your research. Trial list and data management Organizing your trial list with key variables like age, treatment, and identification number ensures easier data selection and analysis, helping streamline your research workflow. Automated animal detection EthoVision features automated detection settings that make tracking easy and highly accurate. Using trained neural networks and subtraction-based detection, EthoVision adjusts for lighting conditions, background noise, and subtle movements, ensuring robust tracking without manual adjustments. This automation simplifies your workflow, allowing you to focus on your research rather than fine-tuning settings, and ensures consistent results even in more complex environments. Whether you're working with rodents, zebrafish, or other animals, EthoVision's automated detection ensures smooth, reliable tracking from the start. Customize your arena and zones EthoVision makes it easy to track movement from prerecorded videos or live camera feeds. Whether you're working with an open field or a radial arm maze, setting up your arena is as easy as four simple steps: - Grab an image: Use a camera or video as your template - Calibrate: Provide the arena size for accurate calculations - Draw the arena: Use intuitive tools to define tracking areas - Draw zones: Highlight areas of interest like objects or shelters Want to use EthoVision with DanioVision? Zone definition for a well plate is done automatically, making setup even easier. Which hardware do I need? Minimum PC specifications - checkWindows 11 (64-bit) Professional - checkMid or Full tower (for Camera PCIe card) - checkIntel Core Ultra 7 265 (20 cores, up to 5.3 GHz) - check32 GB RAM, non-ECC - checkNVIDIA RTX 4060 GPU - check1 GB Network card (for GigE cameras) - check1 TB free disk space Deep learning relies on CUDA 12.2. GPU driver must support this version. Contact sales arrow_forward Supported specifications EthoVision is the core of your lab, providing efficient, reliable data collection and analysis for your experiments. We aim to make it easy to use, without technical worries. For deep learning users, a more powerful GPU is essential to handle complex computations. Investing in the right hardware ensures better data and more reliable results. Get advice arrow_forward Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Eye tracking | Capture participants' focus URL: https://noldus.com/eye-tracking Description: Eye trackers add substantial power to your lab set-up. They produce gaze path video and large quantities of rich data, all related to attention and emotion. Capture participants' focus Eye Tracking Eye tracking is particularly useful for understanding the cognitive processes that drive attention and decision-making. With eye trackers you can: - checkObserve where participants focus their attention on - checkUnderstand how users interact with a system or interface - checkRetrieve objective data on visual engagement Looking for advice on eye tracking? What is eye tracking? Eye tracking is a technique which records what you are looking at. At its simplest, it records if you looked at a given object or not. With more complex analysis, it can give all sorts of information about mental state and the performed tasks. Eye trackers add substantial power to your lab set-up. They provide precise, real-time data on visual attention and cognitive processes, enabling you to understand how individuals interact with visual stimuli. This technology allows for deeper insights into decision-making, learning, and perception. Benefits of eye tracking Visual attention See what your test participant is looking at, and is not looking at, or missing during interaction. analytics Rich quantitative data Get rich, quantitative, and reliable data for attention, mental load, and arousal. sync Data integration Combine eye tracking with FaceReader, NoldusViso, or data acquisition systems with The Observer XT. hub Integrated system Benefit from a completely integrated system with synchronized multi-modal data streams. Integrating eye tracking with Noldus tools You can only draw accurate conclusions when your data is in sync. With Noldus tools, you can seamlessly synchronize multiple data streams, including eye tracking data. That is why Noldus has partnered with Tobii, the global leader in eye tracking technology. hub NoldusHub All-in-one system for multimodal research. Streamline and synchronize all your data sources. Learn more arrow_forward videocam NoldusViso AV tool to capture participants behaviors. Combine video data with eye tracking for complete analysis. Learn more arrow_forward edit_note The Observer XT Complete software for behavioral research. Synchronize eye tracking with behavioral coding. Learn more arrow_forward Want to add eye tracking to your research? Get in touch! Our team can help you choose the right eye tracking setup and integrate it with your existing research workflow. Book a demo or request more information. @csrf First name * Last name * Email address * Request *Make a choiceReceive informationRequest pricingFree trialFree demoBook an online meetingOther Institute/company * How can we help you? * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Submit --- ## FaceReader URL: https://noldus.com/facereader Description: Looking for an automatic analysis of facial expressions? FaceReader is the complete facial expression recognition software, used worldwide. FaceReader How It Works What You Can Do Pricing Features Explore Resources FAQ Contact Stop guessing how people feel. Start measuring it. FaceReader A facial expression is a powerful signal, and FaceReader captures it with scientific precision. Measure responses in real time or from video, with no calibration or complex setup. FaceReader also brings eye tracking, voice analysis, vital signs, and more into the same analysis. Pair that data with your knowledge of the context to discover what truly drives a reaction. View pricing arrow_downward Request a trial Effortless setup All you need is a webcam Multimodal insights Capture emotion in context Proven accuracy Trusted in peer-reviewed research Three ways to work with FaceReader desktop_windows FaceReader: the complete picture, frame by framearrow_forward Every frame, every muscle movement, every heartbeat. FaceReader gives you the full depth of facial analysis, for studies where every detail counts. public FaceReader Online: reach participants worldwidearrow_forward Test large groups remotely, wherever they are. Participants only need a laptop with a webcam, and you get results fast. Ideal for measuring responses to ads, products, and websites. child_care Baby FaceReader: made for the youngest participantsarrow_forward Analyze the facial expressions of infants, based on Baby FACS. Get objective insight into how babies respond to the world around them, long before they can tell you themselves. What can I do with FaceReader? Recognize expressionsarrow_forward Understand how people feel by analyzing expressions like happiness, sadness, anger, surprise, and fear. Capture vocal emotionarrow_forward Measure voice intensity and speech patterns to uncover how people really feel, beyond their words. Analyze multiple facesarrow_forward Speed up research and capture richer, more natural group responses and shared emotional dynamics. Track eye gazearrow_forward See exactly where people look, with clear heatmaps and gaze plots. No extra hardware required. Measure consumptionarrow_forward Catch every bite, sip, and subtle reaction. Spot micro-actions that reveal honest, unconscious responses. Pick up body signalsarrow_forward Track heart and breathing rate, contact free. Measure stress, excitement, or focus with just a webcam. Classify Actions Unitsarrow_forward Understand the subtle mechanisms underneath facial expressions by measuring the activity of individual muscles. Control your studyarrow_forward Mark key events, compare groups, generate clear reports, and save time by automating repetitive analysis. Get FaceReader for your lab Plug-and-play software for a complete, contact-free view of facial expressions, vital signs, and gaze direction. Proven accurate and validated in research. Essential € 2.000 excl. tax | incl. 1 year NoldusCare Analyze the six universal expressions Capture valence & arousal: a response’s direction & intensity Detect facial states & subject characteristics Add to quote Advanced € 9.000 excl. tax | incl. 1 year NoldusCare Everything in Essential, plus: Measure action units and compare groups with project analysis. Study infants aged 6 to 24 months with Baby FaceReader Add to quote Premium € 12.500 excl. tax | incl. 1 year NoldusCare Everything in Advanced, plus: Capture vital signs and voice analysis and consumption behavior Use webcam based eye-tracking and multiple face analysis Add to quote Not sure which package fits your needs? Compare packages Compare FaceReader editions See which features are included in each FaceReader edition and choose the one that fits your research. Feature Essential Advanced Premium Basic facial expressionsRecognizes happy, sad, angry, surprised, scared, disgusted, neutral, and contempt.What you gain: Get objective emotion data, without relying on self-report.check_circlecheck_circlecheck_circleValence and arousalShows whether a response is positive or negative, and how strongly people react.What you gain: Get a quick read on the overall emotional response.check_circlecheck_circlecheck_circleGaze direction and head orientationTracks where participants look and how they position their head.What you gain: Understand attention and engagement alongside emotion.check_circlecheck_circlecheck_circleAge and gender estimationEstimates age and gender from the face.What you gain: Add participant context without extra questionnaires.check_circlecheck_circlecheck_circleLive or recorded analysisAnalyzes in real time or from existing video files.What you gain: Fit any study design, from live sessions to video archives.check_circlecheck_circlecheck_circleAction UnitsMeasures specific facial muscle movements, based on FACS.What you gain: Detect subtle expressions that basic emotions miss.removecheck_circlecheck_circleProject AnalysisGroups, compares, and visualizes results across participants and stimuli.What you gain: See patterns across your whole study, not one recording at a time.removecheck_circlecheck_circleBaby FaceReaderAnalyzes the facial expressions of infants aged 6 to 24 months, based on Baby FACS.What you gain: Study early emotional development objectively.removecheck_circlecheck_circleWebcam eye trackingShows where participants look on screen.What you gain: Link emotion to exactly what people see.removeremovecheck_circleVital signsMeasures heart rate, heart rate variability, and breathing rate from the face.What you gain: Add physiological insight to your emotion data.removeremovecheck_circleMultiple face analysisAnalyzes several faces in one video.What you gain: Study group dynamics and social interaction.removeremovecheck_circleVoice analysisMeasures voice intensity and speech patterns alongside facial data.What you gain: Pick up emotional cues the face alone may not show.removeremovecheck_circleConsumption behaviorDetects eating and drinking behavior, such as chewing.What you gain: Measure responses to food and drinks while people consume them.removeremovecheck_circle All editions include 1 year of NoldusCare. Prices exclude tax. Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Measure facial behavior precisely Features that simplify your work FaceReader is designed to fit seamlessly into your workflow, so you can start quickly, collect reliable data, and scale as your projects grow. No fragmented tools, just one continuous path from capture to analysis. Check the FaceReader leaflet play_circle Real-time emotion tracking See emotional responses as they happen. Perfect for live testing, training sessions, or interactive studies. hub Everything in one system Facial expressions, eye gaze, and physiological signals are captured and synchronized within one integrated environment, creating a streamlined workflow from recording to analysis. No need for separate tools or complex integrations. video_file Analyze recorded sessions Upload existing video files and automatically extract facial expression data. No need to rerun sessions or rely on manual coding. Save time. Reduce bias. show_chart Clear visual reports See patterns instantly, export data seamlessly, and turn your analysis into findings you can confidently share and defend. Explore further Publications Browse peer-reviewed research papers and scientific publications that reference this product in their methodology. Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. FACS FACS gives you a proven, scientific way to describe facial behavior objectively and consistently. Try FaceReader yourself Objective, automated facial expression analysis for behavioral research. Get your free trial Get more out of FaceReader Insights from researchers and our product experts Customer story Western University Social behavior lab FaceReader helped a social behavior lab analyze interactions faster and more accurately. Discover their story Webinar FaceReader Masterclass Combining research tools Dr. Amy Harrison presents research on using FaceReader, The Observer, and physiological measurements to study eating disorders. Watch the webinar Blog Methodology and validation 7 FaceReader essentials How does FaceReader classify expressions, and how accurate is it? Real user questions, answered by our experts. Read the blog Register for webinar First name * Last name * Email * Would you like to be contacted by a Noldus representative? * Yes No error Please select whether you would like to be contacted. Register and get access By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Frequently asked questions About FaceReader How do I get started? FaceReader requires only a webcam and installation of the software. No facial markers or calibration sessions are needed. You can start your first recording within minutes. How accurate is FaceReader? FaceReader has been validated against the Amsterdam Dynamic Facial Expression Set and achieves around 99% accuracy in recognizing basic facial expressions. It is also widely cited in hundreds of peer-reviewed research. Can I combine FaceReader with other data sources? Yes. FaceReader can integrate with additional signals such as physiological data and eye tracking, allowing for multimodal analysis within one synchronized workflow. Can I analyze pre-recorded video files? Yes. You can upload existing video files and automatically extract emotion data, making it easy to analyze past sessions without re-running studies. What is possible with FaceReader Online? FaceReader Online enables you to test large groups of participants remotely, making it easy to collect facial expression data from anywhere in the world. Perfect for when you want to study participants in their homes or on their mobile phones. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Request a free trial Tell us a bit about yourself and we'll get back to you within one business day. FaceReader Thank you! This is a demo form, so nothing was sent. We'll get back to you shortly. First name * Last name * Email address * Phone number (optional) Institute/company/department * How can we help you? * By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit --- ## White paper | FaceReader and eye-tracking URL: https://noldus.com/facereader-and-eye-tracking Description: Both eye tracking and facial expression analysis add substantial power to your research Free white paper FaceReader and Eye Tracking Learn how combining facial expression analysis with eye tracking provides deeper insights into attention, emotion, and decision-making processes. - checkCombining gaze data with emotion data - checkSynchronizing FaceReader with eye trackers - checkAreas of interest and emotional response - checkApplications in UX and consumer research - checkData visualization and analysis Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free download Why combine facial expressions with eye tracking? Eye tracking tells you where people look. FaceReader tells you how they feel about what they see. Together, they reveal the complete picture of attention and emotional engagement. - checkUnderstand what captures attention AND triggers emotion - checkIdentify pain points in user interfaces - checkMeasure ad effectiveness with precision - checkStudy reading behavior and comprehension - checkValidate design decisions with objective data --- ## White paper | FaceReader - FACS URL: https://noldus.com/facereader-facs Description: Coding facial actions enables a greater awareness to subtle facial behaviors. Automate FACS coding using FaceReader Free white paper Facial Action Coding System (FACS) This white paper explains the Facial Action Coding System and how FaceReader automates the detection of Action Units for objective facial expression analysis. - checkWhat are Action Units? - checkHow FACS classifies facial movements - checkAutomated vs. manual FACS coding - checkApplications in research and clinical settings - checkFaceReader's FACS module capabilities Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free download Understanding Action Units The Facial Action Coding System (FACS) describes facial movements in terms of Action Units (AUs) — individual muscle movements that combine to form expressions. FACS provides an objective, anatomically-based system for describing facial behavior. - check20+ Action Units detected automatically - checkLeft and right side analysis - checkIntensity scoring for each AU - checkTemporal dynamics of expressions - checkCustom expression creation from AU combinations --- ## White paper | FaceReader methodology URL: https://noldus.com/facereader-methodology Description: Free white paper on FaceReader Methodology. Learn more about to use FaceReader to your advantage. Free white paper FaceReader Methodology Learn about the science behind FaceReader. This white paper explains the methodology used for automatic facial expression analysis, including the classification of basic emotions, Action Units, and custom expressions. Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free How does FaceReader work? FaceReader was trained to classify the six basic or universal emotions: happy, sad, angry, surprised, scared, and disgusted. Additionally, FaceReader can recognize a neutral state. The software uses a deep learning model (Deep Face) that was trained on over 10,000 manually annotated images. This model analyzes the face in three steps: face finding, face modeling, and face classification. This white paper describes the methodology in detail, including validation studies and accuracy benchmarks. In this white paper you will learn: - checkHow the Active Appearance Model works - checkHow Deep Face classifies expressions - checkValidation and accuracy of FaceReader - checkAction Unit classification - checkCustom expression training --- ## FaceReader Applications URL: https://noldus.com/facereader/applications Description: FaceReader is the most robust automated system for facial expression analysis - and it is also scientifically validated. Benefit from this complete end-to-end solution! Back to FaceReader What can I use FaceReader for? From psychology to education, consumer behavior, or infant research, facial expressions provide you valuable insights into human emotions. With FaceReader, you can explore how people feel and react in real time, across settings like classrooms, usability labs, test facilities, or developmental labs working with infants. The software helps you uncover hidden emotional patterns and connect facial expressions to behavior, decisions, and experiences in a fast, reliable way. Contact us FaceReader applications Emotion analysis Emotions influence our behavior — from deciding what to eat and whether to buy a product to our interactions with others. Including emotion analysis in your research helps you gain more insights into these complex behaviors. Psychology research Researchers in the field of psychology study different aspects of human behavior. This includes topics such as children's development, parent-child interaction, mental disorders, and much more. Consumer behavior Consumer behavior research is focused on learning how people make decisions. This type of research provides key insights into consumer preferences and buying behaviors. Neuroscience Neuroscience research investigates the structure, function, and development of the nervous system, with a particular focus on the brain. This drives advancements in therapies for neurological disorders. User experience & human factors UX research improves the overall experience when using products or services. Human factors researchers aim to optimize design of products, processes, and systems to improve safety and productivity. Detailed facial expressions FaceReader offers the functionality to measure Action Units — muscle groups in the face that are responsible for facial expressions. This unique feature in FaceReader distinguishes the intensity of the active muscles at the left and the right side of the face separately. Create custom expressions You can also use Action Units and other variables to design your own algorithms. This allows you to analyze states such as workload, pain, or embarrassment. Unbiased face modeling In a validation study, we compared FaceReader's face modeling abilities in facial images of people from seven ethnicities. These images came from the FairFace Face Attribution Dataset. Accurate modeling for all ethnicities The results showed that FaceReader records the primary reactions of test subjects without any bias. In other words, the software models all faces equally, regardless of ethnicity. Studying user behavior with FaceReader The Social Media Lab in Mons, Belgium brings people from different disciplines together. From communication and marketing to journalism, computer science and more. Studying user experiences Researchers at the Social Media Lab analyze how users interact with social media. This helps companies to identify their customers' needs and implement new tools. Discover how FaceReader benefits their research! Featured blog posts Blog How emotions are made Neuroscience research shows that emotions are created in our brains. It's how our brains give meaning to our experiences and sensations. Read this blog post arrow_forward Blog 7 things you need to know about FaceReader Are you looking for guidance in getting started with your facial expression analysis? Read about the 7 essential things you need to know. Read this blog post arrow_forward Blog Using Baby FaceReader for automated analysis of infant emotions What if you had a way to understand a baby's unspoken needs? This study highlights the benefits of analyzing facial expressions in infants. Read this blog post arrow_forward Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## Facial Action Coding System (FACS) URL: https://noldus.com/facereader/facs Description: Learn about the Facial Action Coding System (FACS) and how FaceReader automates Action Unit detection for objective facial expression analysis. Back to FaceReader From subjective to objective facial data Facial Action Coding System (FACS) If you want to understand emotion, engagement, or subtle social signals, you need a method you can trust. FACS gives you a proven, scientific way to describe facial behavior objectively and consistently. - Turn facial expressions into objective data - Don't miss critical micro-expressions - Make your facial expression data publishable and comparable Get more info What is FACS? The Facial Action Coding System (FACS) is a scientific framework for describing facial movements. It was developed by Paul Ekman and Wallace Friesen, whose work laid the foundation for modern facial expression research. Instead of categorizing emotional expressions, FACS breaks facial expressions down into Action Units (AUs), which are specific, observable muscle movements such as raising the eyebrows or tightening the lips. The level of activation of each Action Unit is specified on a 5-level intensity scale from A (trace - barely visible) to E (maximum - the most extreme form of the movement). This allows researchers to capture not just which muscles move, but also how much. Each expression can be described by a unique combination of these Action Units. That makes facial behavior measurable, comparable, and independent of interpretation. 20 Action Units Below you can see the 20 Action Units from the Facial Action Coding Scheme (FACS) offered in FaceReader as well as some frequently occurring or difficult Action Unit combinations. Some images have been zoomed in on the area of interest to explicitly show what muscle movement corresponds to the specific Action Unit. AU 1. Inner Brow Raiser Contributes to sadness, surprise, and fear. Muscular basis: frontalis (pars medialis). AU 2. Outer Brow Raiser Contributes to surprise and fear. Muscular basis: frontalis (pars lateralis). AU 4. Brow Lowerer Contributes to sadness, fear, and anger. Muscular basis: depressor glabellae, depressor supercilii, corrugator supercilii. AU 5. Upper Lid Raiser Contributes to surprise, fear, and anger. Muscular basis: levator palpebrae superioris, superior tarsal muscle. AU 6. Cheek Raiser Contributes to happiness. Muscular basis: orbicularis oculi (pars orbitalis). AU 7. Lid Tightener Contributes to fear and anger. Muscular basis: orbicularis oculi (pars palpebralis). AU 9. Nose Wrinkler Contributes to disgust. Muscular basis: levator labii superioris alaeque nasi. AU 10. Upper Lip Raiser Muscular basis: levator labii superioris, caput infraorbitalis. AU 12. Lip Corner Puller Contributes to happiness and contempt. Muscular basis: zygomaticus major. AU 14. Dimpler Contributes to contempt and boredom. Muscular basis: buccinator. AU 15. Lip Corner Depressor Contributes to sadness and disgust. Muscular basis: depressor anguli oris. AU 17. Chin Raiser Contributes to the affective attitudes interest and confusion. The underlying facial muscle is mentalis. AU 18. Lip Pucker The underlying facial muscles are incisivii labii superioris and incisivii labii inferioris. AU 20. Lip Stretcher Contributes to the emotion fear. The underlying facial muscle is risorius w/ platysma. AU 23. Lip Tightener Contributes to the emotion anger, and to the affective attitudes confusion and boredom. Muscular basis: orbicularis oris. AU 24. Lip Pressor Contributes to the affective attitude boredom. The underlying facial muscle is orbicularis oris. AU 25. Lips Part The muscular basis consists of depressor labii inferioris, or relaxation of mentalis or orbicularis oris. AU 26. Jaw Drop Contributes to the emotions surprise and fear. Muscular basis: masseter; relaxed temporalis and internal pterygoid. AU 27. Mouth Stretch The underlying facial muscles are pterygoids and digastric. AU 43. Eyes Closed Contributes to the affective attitude boredom. The muscular basis consists of relaxation of Levator palpebrae superioris. Combinations of Action Units AU 1 - 2 - 4 Contributes to the emotions fear and can be recognized by the wavy pattern of the wrinkles across the forehead. AU 1 - 2 Contributes to the emotion surprise and can be recognized by a smooth line formed by the wrinkles across the forehead. AU 1 - 4 Contributes to sadness. Recognizable by a wavy pattern of the wrinkles in the center of the forehead. Eye-brows come together and up. AU 4 - 5 Contributes to the emotion anger. AU 6 - 12 Contributes to happiness. Notice the wrinkles around the eyes caused by cheek raising, also known as the "Duchenne Marker". AU 10 - 25 Contributes to the emotion disgust. When AU 10 is activated intensely, it causes the lips to part as the upper lip raises. AU 18 - 23 Often confused as solely AU 18. Notice the lips almost appear to be pulled by a single string outward (AU 18) and then tightened (AU 23). AU 23 - 24 The AUs marking lip movements are often the hardest to code. The lips are being pushed together (AU 24) and tightened (AU 23). How does FaceReader help you work with FACS? It takes humans several hundred hours to become an expert in recognizing these movements. Facial Action Coding System software, like FaceReader, automatically detects and quantifies Action Units from video, frame by frame. It brings FACS into practice, removes practical barriers, and allows you to define custom expressions by combining Action Units in ways that match your research goals. That means you can: - Apply FACS-based facial coding automatically and consistently - Quantify Action Units at scale, without introducing human bias - Produce objective facial expression data suitable for scientific reporting Quick overview FaceReader Download the info sheet This short info sheet gives you a clear look at what FaceReader can do: analyze behavior using just a webcam, with no hassle. You'll find an overview of key features like emotion detection, gaze tracking, and heart rate analysis, along with examples of how it's used in research and education. A great starting point if you want to explore behavioral tools or expand your research methods. Get your copy instantly FACS and FaceReader in practice Publications & resources The publications and blog posts below include references on FACS, the ADFES dataset, and examples from FaceReader users, offering context for how facial expression analysis is used in research. References Ekman, P., Friesen, W. V. & Hager, J.C. (2002). Facial Action Coding System. Manual and Investigator's Guide, Salt Lake City: Research Nexus. Lewinski, P.; Fransen, M. L.; Tan, E.S.H. (2014). Predicting Advertising Effectiveness by Facial Expressions in Response to Amusing Persuasive Stimuli. Journal of Neuroscience, Psychology, and Economics, 7, 1-14. https://doi.org/10.1037/npe0000012 Van der Schalk, J., Hawk, S. T., Fischer, A. H., & Doosje, B. J. (2011). Moving faces, looking places: The Amsterdam Dynamic Facial Expressions Set (ADFES), Emotion. https://doi.org/10.1037/a0023853 Blog posts on case studies How does perception of brand authenticity affect ad performance? For brands seeking to resonate with customers, being seen as authentic is vital. Using custom expressions in FaceReader, we explore how perception of brand authenticity relates to ad performance. Analysis of facial expressions of emotions in children The study described in this guest blog post focuses on the facial expressions of emotions induced by affective stimuli in children aged between 7 and 14. Blog posts on methodology Why you should use custom expressions in your facial expression analysis Using custom expressions in facial expression analysis can unlock a deeper understanding of human behavior. How can you use custom expressions in different fields of research? Smile like you mean it Of all human expressions, a smile is the most universal. But can you tell which smile is real and which is false? Creating a custom expression for engagement: a validation study with FaceReader The concept engagement is gaining more and more attention. Many companies are looking for ways to increase consumer engagement. But, how do you know a consumer is feeling engaged? Recent publications Boobani, B.; Kalnina, Z.; Glaskova-Kuzmina, T. et al. (2025). Utilizing Facial Emotion Analysis with FaceReader to Evaluate the Effects of Outdoor Activities on Preschoolers' Basic Emotions: A Pilot Study in e-Health. International Journal of Online and Biomedical Engineering, 21(07), 61-75. https://doi.org/10.3991/ijoe.v21i07.54291 Mshael, E.; Stillhart, A.; Rodrigues Leles, C. & Srinivasan, M. (2025). Application of automated face coding (AFC) in older adults: A pilot study. Journal of Dentistry, 153. https://doi.org/10.1016/j.jdent.2025.105555 Dimitra, S.; Ioanna, Y. & Georgois, T. (2025). Neuromarketing and Health Marketing Synergies: A Protection Motivation Theory Approach to Breast Cancer Screening Advertising. Information, 16, 715. https://doi.org/10.3390/info16090715 Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## FaceReader Publications & Resources URL: https://noldus.com/facereader/publications Description: Explore FaceReader publications, research papers, and resources for facial expression analysis. @include('partials.hero-auroral') Back to FaceReader Learn more about FaceReader Want to learn more about FaceReader? Discover in-depth information in our white papers, product videos, and customer success stories. You'll also find relevant publications, as well as product overviews for your research area. Get in touch FaceReader Relevant publications Here is a selection of recent publications using FaceReader. If you feel your paper should be on this list, please let us know at marcom@noldus.com. Consumer behavior Krause, F.; Franke, N. (2023). Understanding Consumer Self-Design Abandonment: A Dynamic Perspective. Journal of Marketing. De Wijk, R.; Kaneko, D.; Dijksterhuis, G.; van Bergen, G.; Vingerhoeds, M.; Visalli, M.; Zandstra, E. (2022). A preliminary investigation on the effect of immersive consumption contexts on food-evoked emotions using facial expressions and subjective ratings. Food Quality and Preference. Human factors & UX Märtin, C., Bissinger B.C., & Asta, P. (2021). Optimizing the digital customer journey - Improving user experience by exploiting emotions, personas and situations for individualized user interface adaptations. Journal of Consumer Behavior, 1-12. Talen, L. & den Uyl, T.E. (2021). Complex Website Tasks Increase the Expression Anger Measured with FaceReader Online. International Journal of Human–Computer Interaction. Child development Bourret, M., Ratelle, C.F., Plamondon, A. & Boisclair Châteauvert, G. (2023). Dynamics of parent-adolescent interactions during a discussion on career choice. Journal of Vocational Behavior, 141. Hubbard, J.A.; Moore, C.C.; Zajac, L. et al. (2024). The importance of both individual differences and dyadic processes in children's emotion expression. Applied Developmental Science, 28(2): 193–206. Liu, S.; Wang, Y., Song, Y. (2023). Atypical facial mimicry for basic emotions in children with autism spectrum disorder. Autism Research, 16, 1375-1388. Zaharieva, M.; Salvadori, E.; Messinger, D.; Visser, I.; Colonnesi, C. (2024). Automated facial expression measurement in a longitudinal sample of 4 and 8 month olds. Behavior Research Methods. Psychology Malfait, A.; Puyvelde, M.; Detaille, F. et al. (2023). Unveiling Readiness of Medical First Responders in Simulation Trainings. AHFE Open Access, vol 116. Meng, Q. et al. (2020). On the effectiveness of facial expression recognition for evaluation of urban sound perception. Science of The Total Environment, 710, 135484. Yang, L.; Chen, X.; Guo, Q. et al. (2022). Changes in facial expressions in patients with Parkinson's disease. Computer Speech & Language, 72(3). Validated in research We compared the results of FaceReader with the intended expressions from the Amsterdam Dynamic Facial Expression Set (ADFES). Our findings? FaceReader has an average accuracy of 99% in measuring the six basic expressions. Read more in our white paper on FaceReader's methodology. Most cited Moreover, FaceReader is by far the most cited facial expression recognition software, with references in over 2,000 peer-reviewed publications. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## FaceReader Setup URL: https://noldus.com/facereader/setup Description: Learn how to set up FaceReader for automatic facial expression analysis in your research. Back to FaceReader How do I use FaceReader? FaceReader helps to automate your research — quickly and easily. The user-friendly software allows you to use different input sources and system preferences, giving you the setup you need. Discover options, practical tips, and how-to's that will help you get the most out of your research. Contact us What does FaceReader offer? FaceReader can be used with different input sources. You can upload still images for analysis or analyze facial expressions from a pre-recorded video file. When analyzing from video, you can choose an accurate frame-by-frame mode or skip frames for high-speed analysis. Save valuable time FaceReader enables you to analyze live and to record video and audio simultaneously. If you plan to analyze multiple videos, you can analyze them all at the same time. The software can also quickly detect interesting episodes, even in long series of events. This way, FaceReader saves you a lot of valuable time. What computer hardware do I need? FaceReader will run on computers with the following minimum technical specifications: - checkWindows 11 Pro (64-bit) - checkIntel Core i5 8th generation or higher / AMD Ryzen 5 4000 series or higher - checkMinimum of 8 GB RAM - checkSupport for AVX2 or higher Download technical specifications "Since we started to use FaceReader in our work on situation-aware adaptive user interfaces, our research has taken a great leap forward." Prof. Dr. Christian Märtin Augsburg University of Applied Sciences, Germany How do I collect my data? Accurate analysis for each participant Tailor your facial expression analysis to a specific person using automatic calibration. You can correct person-specific biases towards a certain emotional expression, for example, when someone shows a lot of anger in their neutral facial state. Create custom expressions Custom expressions are facial expressions or mental states that you can define yourself, such as workload, pain, or embarrassment. Combine variables such as facial expressions, Action Units, heart rate, and heart rate variability. Privacy & ethics in FaceReader FaceReader is installed on-site and adheres to strict privacy-by-design protocols. The software is not capable of recognizing or identifying faces or people, and is therefore unsuitable for surveillance purposes. Choose the license that works for you Use FaceReader with a hardware key or digital license. A fixed license is connected to a single computer. With a floating license, install the software on any computer and use it anywhere with an internet connection. Setup options: SDK integration or online use Integrate FaceReader with external applications Need to easily integrate facial expression analysis into other applications? Using the FaceReader Software Development Kit (SDK) is the perfect solution. The SDK is available on request, based on a separate agreement. It works for Windows and Android, and can run on your PC or server. You can also use the FaceReader API, which makes it easy to connect with the standard FaceReader for Windows software and gives you access to key FaceReader functions on your own PC. FaceReader Online: wherever there's internet Connect to FaceReader Online and test participants anywhere around the globe. It is the ideal tool to get feedback from a large number of participants without inviting them to your facility. Perfect for when you want to study participants in their homes or on their mobile phones. Baby FaceReader Baby FaceReader is a tool for automated facial expression analysis for infants between 6 and 24 months old. It's based on the Baby Facial Action Coding System (Baby FACS) and includes 14 Action Units that are specific for infants. Study infant emotions Use Baby FaceReader to study responses to sensory stimuli, parent-child interactions, cognitive information processing, expressive behaviors in different situations, and more. Its objective measurements help you capture early emotional patterns and link them to cognitive and social development. Download leaflet Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Purdue University Harvard University TNO University of Washington Danish Technological Institute Universität Leipzig B-com WUR LSE Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## Thank You - Noldus URL: https://noldus.com/form/thanks/contact Description: Thank you for contacting Noldus @include('partials.hero-auroral') Thank You! We've received your message and will get back to you as soon as possible. If you requested reading material, the download will be in your mailbox shortly. Our team typically responds within 1-2 business days. If your inquiry is urgent, please don't hesitate to call us directly. Return to Homepage Subscribe to the Noldus Newsline today! Expert insights and the latest innovations, straight into your inbox. - Monthly newsletter - Research blog updates - Early access to promotions - First in line for releases - Unsubscribe anytime @csrf First name * Last name * Email address * Research area * Make a choice Animal Behavior Human Behavior By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Subscribe --- ## Grant Assistance Program URL: https://noldus.com/grant-assistance-program Description: Your success in securing funds is vital for your research. We realize that grants—public, private, large or small—are the lifeblood of research. We want to help Write better proposals Your success in securing funds is vital for the progression of your research. We realize that grants — public, private, large or small — are the lifeblood of research. Put our thirty years of experience to work to help you locate and secure your next grant. We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to you! Help me write better grants arrow_forward This is how we help Download the Grant Funding guide for free Our scientific research consultants will work with you to provide you Noldus specific input for your grant application. We can provide guidance on developing behavioral protocols, performing behavioral tasks, or making the most out of your Noldus system. We have a dedicated number of hours available for helping neuroscientists and psychologists in North America, and EU researchers applying for Horizon Europe grants, but please don't hesitate to fill out the form below if you don't fit that description. We can join your Horizon Europe consortium as a partner. Need help with your grant? Get in touch! Fill in the form and one of our research consultants will contact you to discuss how we can support your grant application. @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Submit --- ## White paper | Human behavior research labs URL: https://noldus.com/how-to-build-labs Description: Stationary and portable labs for observation and analysis of human behavior: Complete integrated lab designed with you and built by us. Free white paper How to Build a Human Behavior Research Lab This collection of white papers guides you through designing and building observation labs for human behavior research — from usability labs to clinical observation rooms. - checkUsability lab design principles - checkClinical observation room setup - checkFocus group facilities - checkConsumer behavior labs - checkMulti-purpose research spaces Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free download Designing your research space The design of your observation lab directly impacts the quality of your research. A well-planned space minimizes participant awareness of being observed while maximizing data capture quality. - checkOne-way mirror placement - checkCamera and microphone positioning - checkParticipant comfort and natural behavior - checkControl room design - checkFlexible room configurations --- ## Solutions for Human Behavior Research URL: https://noldus.com/human-behavior-research Description: Advance human behavior research with seamless data integration tools. Gain insights in psychology, education, UX, and more. Work smarter with our software! Capture and understand human behavior. Study what people do, how they respond, and how they interact. Combine behavioral observations with video, physiological, facial expressions, eye tracking and more to answer your research questions. Find your match arrow_downward Our software Tools that bring your research together NoldusViso Reliable audio and video recording for behavioral observation. Fast setup, strong security, easy to scale. Explore NoldusViso arrow_forward FaceReader Automatically analyze facial expressions, gaze, and vital signs, contact-free. Get to know FaceReader arrow_forward NoldusHub Synchronize and combine multiple data streams in one multimodal research solution. Discover NoldusHub arrow_forward The Observer Code, analyze, and visualize observed behavior from video, audio, and live sessions. Learn about The Observer arrow_forward Product advisor Find the right Noldus tool for your research Answer a few quick questions and we will recommend the Noldus products that best fit your needs. @livewire('product-advisor', ['presetSubject' => 'humans']) Hofstra University Harvard University Danish Technology Institute University Leipzig Wageningen University Nestlé University of Oxford University of Washington KPN Brown University Radboud Universiteit Nijmegen TNO London School of Economics Purdue University University of Michigan Duke University National Bank of Canada University of Oslo Aarhus Universitet Hofstra University Harvard University Danish Technology Institute University Leipzig Wageningen University Nestlé University of Oxford University of Washington KPN Brown University Radboud Universiteit Nijmegen TNO London School of Economics Purdue University University of Michigan Duke University National Bank of Canada University of Oslo Aarhus Universitet New release Built for the next generation of behavioral research Meet NoldusViso. Everything you need to record, review and manage behavioral research in one intuitive foundation. Discover NoldusViso Explore by research area See what's possible in your field Psychologyarrow_forward Emotionarrow_forward Education & trainingarrow_forward Behavioral economicsarrow_forward Consumer behaviorarrow_forward Neurosciencearrow_forward Human factorsarrow_forward UX researcharrow_forward Custom labs built for your research needs We collaborate with world-class suppliers to provide flexible tools designed to adapt to your unique research demands. From cameras and computers to eye trackers and physiological measurement systems, every piece of equipment is seamlessly integrated for optimal performance. Whether you need a simple observation room or a fully equipped multi-modal research facility, we design and build labs that match your exact specifications. What kind of lab do I need? sync Multimodal research lab Integrates eye tracking, facial expression analysis, galvanic skin response, and electrocardiography. Captures comprehensive data on attention, emotion, and physiological responses. Learn more arrow_forward meeting_room Multi-room lab Features interconnected rooms equipped with technology for observing interactions, conducting interviews, and running experiments across multiple spaces simultaneously. Learn more arrow_forward videocam Observation lab Designed for unobtrusive observation of behavior with one-way mirrors, multiple camera angles, and professional audio recording for detailed behavioral analysis. Learn more arrow_forward shopping_cart Consumer behavior lab Equipped to study how consumers interact with products, packaging, and retail environments. Combines eye tracking with emotion analysis for complete insights. Learn more arrow_forward luggage Portable lab Compact, mobile setup that brings the lab to your participants. Ideal for field research, schools, hospitals, or any location outside your facility. Learn more arrow_forward devices User experience lab Purpose-built for UX research with screen recording, eye tracking, think-aloud protocols, and facial expression analysis to understand how users interact with digital products. Learn more arrow_forward Real-world examples See how behavior becomes insight Customer story Early childhood development Fisher-Price Play Lab By observing how children play, better decisions can be made about products that support learning, development, and joy. Discover their story View all stories Webinar FaceReader Masterclass Combining research tools Dr. Amy Harrison presents research on using FaceReader, The Observer, and physiological measurements to study eating disorders. Watch the webinar View all webinars Blog post Why behavioral observation matters The complete guide A structured approach to observation helps improve consistency, reduce bias, and strengthen the value of behavioral data. Read the blog post View all blogs Want more information? Meet with an expert in your field Do any of these solutions sound interesting to you? But do you want more info regarding your specific use case? Feel free to book a meeting with us. We have a dedicated team of behavioral experts that are ready to help you find the solution fit for your research. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Register for webinar First name * Last name * Email * Would you like to be contacted by a Noldus representative? * Yes No error Please select whether you would like to be contacted. Register and get access By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. --- ## Labs | Complete integrated labs URL: https://noldus.com/labs Description: From portable and stationary labs for observation and analysis of human behavior to high-tech turn-key usability labs: Noldus can deliver it. High-tech and customizable Labs From compact portable labs for on-site studies to fully integrated, customized research labs, we deliver exactly what you need. Designed with you, built by us. - checkTurn-key labs tailored to your research goals - checkCutting-edge tools for behavior recording and analysis - checkPortable or stationary solutions for any environment More information about labs arrow_forward Custom labs built for your research needs We collaborate with world-class suppliers to provide flexible tools designed to adapt to your unique research demands. From cameras and computers to eye trackers and physiological measurement systems, every piece of equipment is seamlessly integrated for optimal performance. Whether you need a simple observation room or a fully equipped multi-modal research facility, we design and build labs that match your exact specifications. What kind of lab do I need? hub Multimodal research lab Integrates eye tracking, facial expression analysis, galvanic skin response, and electrocardiography. Captures comprehensive data on attention, emotion, and physiological responses. Learn more arrow_forward meeting_room Multi-room lab Features interconnected rooms equipped with technology for observing interactions, conducting interviews, and running experiments across multiple spaces simultaneously. Learn more arrow_forward videocam Observation lab Designed for unobtrusive observation of behavior with one-way mirrors, multiple camera angles, and professional audio recording for detailed behavioral analysis. Learn more arrow_forward shopping_cart Consumer behavior lab Equipped to study how consumers interact with products, packaging, and retail environments. Combines eye tracking with emotion analysis for complete insights. Learn more arrow_forward luggage Portable lab Compact, mobile setup that brings the lab to your participants. Ideal for field research, schools, hospitals, or any location outside your facility. Learn more arrow_forward devices User experience lab Purpose-built for UX research with screen recording, eye tracking, think-aloud protocols, and facial expression analysis to understand how users interact with digital products. Learn more arrow_forward Ready to build your lab? Get in touch! Tell us about your research goals and we will help you design the perfect lab setup — from a single room to a complete multi-room facility. @csrf First name * Last name * Email address * Request *Make a choiceReceive informationRequest pricingFree demoBook an online meetingOther Institute/company * How can we help you? * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Submit --- ## Consumer behavior lab | Human behavior research labs URL: https://noldus.com/labs/consumer-behavior-lab Description: A consumer behavior lab is valuable for studying how consumers interact with products, services, or environments in a controlled setting. Overview What can you do Studies Equipment Software Contact Uncover customer needs By simulating different scenarios, you gain deeper insights into decision-making factors. Whether it's testing a new product, evaluating advertising, or understanding shopping behavior — a consumer behavior lab reveals what drives your customers. Get in touch arrow_forward What can I do in a consumer behavior lab? Evaluate advertising and branding Measure how effective different marketing messages or visual designs are in capturing attention and driving action. Test interactions with products Observe how consumers use or react to new products before launching them to the market. Understand emotional responses Study how consumers feel when engaging with a product, service, or brand using facial expression analysis tools. Simulate shopping experiences Replicate in-store or online shopping environments to study purchasing behavior, decision-making, and product placement effects. What types of studies can I conduct? A consumer behavior lab helps you get detailed insights into how consumers think, feel, and act in various scenarios. - checkEye-tracking studies to track consumer attention - checkEmotional response studies to assess consumer reactions - checkPurchase behavior testing to analyze how consumers choose products and make decisions - checkUsability testing of digital interfaces and physical products What equipment do I need? A lab gives you the ability to manipulate variables and eliminate distractions, ensuring that you capture genuine consumer responses in a controlled environment. - checkObservation room with cameras and microphones provided with a one-way mirror - checkEye-tracking system - checkBiometric tools to measure skin conductance, brain activity, heart rate, and facial expressions - checkScreen capture and stimulus presentation devices What is the best software for my consumer behavior lab? Depending on the specific focus of your studies, you can use software such as Viso for advanced recording capabilities and real-time observation. If you're looking for a tool to code and explore the recorded behaviors in more detail, The Observer XT will help you out — by analyzing event sequences, calculating statistics, and automatically synchronizing multiple data streams. With FaceReader you get clear insights into the effects of different stimuli on emotions. Interested in a consumer behavior lab? Get in touch! Tell us about your research goals and we will help you design a consumer behavior lab that captures authentic consumer interactions and emotional responses. @csrf First name * Last name * Email * Message By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Send message --- ## Human Factors Usability Labs | Human behavior research labs URL: https://noldus.com/labs/human-factors-ux-lab Description: Explore Human Factors and Usability Labs that enhance user experiences and optimize product interactions through innovative research and design methodologies. Overview Studies Equipment Software Resources Contact Enhanced observations Are you looking for enhanced observation capabilities? Discover how human factors (HF) and usability (UX) labs help you understand user interactions, improve product design, and optimize the user experience through controlled testing environments. Get in touch arrow_forward What types of studies can I conduct? In a Human Factors and Usability Research lab, you can conduct studies to understand user interactions and optimize product design. - checkUsability testing to evaluate ease of use and identify design issues - checkErgonomic assessments to examine physical strain and posture during product use - checkCognitive load testing to measure mental effort required to complete tasks - checkHuman error analysis to identify and mitigate risk factors Essential lab components Setting up a high-tech Human Factors or UX lab requires specialized equipment to observe, measure, and analyze user interactions. - checkBiometric tools — skin conductance sensors, heart rate monitors - checkEye-tracking system — tracks gaze patterns to reveal user attention - checkMicrophones, audio recording equipment, and cameras - checkComputer workstations with analysis software - checkVirtual reality (VR) and augmented reality (AR) setup - checkErgonomic testing tools — adjustable desks, chairs, and measurement instruments What are the best tools for my HF & UX lab? Streamline your Human Factors and Usability research from start to finish and get high-quality data and insights with the right software tools. Facial expression analysis and emotion data allow researchers to gain insights in complex human behavior — understanding how users feel when interacting with your product or interface. If you're looking for a tool to code and explore the recorded behaviors in more detail, The Observer XT allows you to combine and analyze behavioral observations with physiological data. Featured resources Hofstra University The Behavioral Research in Business Laboratory is a state-of-the-art facility at Hofstra University. MARIN Hans Huisman shows us around a state-of-the-art ship bridge simulator at MARIN: one of the leading maritime research institutes. Christian University Ede The UX lab at the Ede Christian University is intended to study user experiences and interactions. ✕ Interested in a Human Factors & UX lab? Get in touch! Tell us about your research goals and we will help you design a Human Factors or Usability lab tailored to your specific needs. @csrf First name * Last name * Email * Message By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Send message --- ## Multi-room lab | Human behavior research labs URL: https://noldus.com/labs/multi-room-lab Description: A multi-room lab is a sophisticated research facility that allows researchers to study human behavior in different settings simultaneously. Overview Why multi-room Equipment Software Resources Contact Observe across various settings Are you looking for enhanced observation capabilities? A multi-room lab allows researchers to study human behavior across interconnected rooms, conduct multiple training sessions simultaneously, and simulate different real-life scenarios. Get in touch arrow_forward What do I need a multi-room lab for? Skills training To train students and professionals, to test new protocols, or to study interactions, multiple simulated environments can be included. Multiple sessions can take place simultaneously. Developmental studies By using multiple rooms to simulate different learning environments you can observe how children interact with educational materials and activities. Consumer behavior analysis Simulating a retail environment in one room and an advertising viewing room in another can help researchers understand the effects of marketing strategies on purchasing decisions. Usability tests A multi-room lab allows for simultaneous observation of user interactions in realistic and controlled settings, enabling thorough analysis of user behavior and interface effectiveness. Why should I choose a multi-room lab? Research, training, or testing can require more than one room to be effective. For example, in case of: - checkLarge number of participants - checkDiverse conditions - checkSimulation of different real-life scenarios - checkMulti-phase studies where participants need to move between different settings What equipment do I need? Stable images, high quality video recordings, and clear recordings of speech and other sounds make all the difference. Each room can be tailored to mimic real-life environments or controlled experimental setups. - checkRecording devices such as IP or Pan-Tilt-Zoom cameras, webcams - checkMicrophones, microphone amplifiers, and audio mixer - checkCentral computer with multiple screens in the control room - checkOptional: Screen capture device(s), data acquisition tool(s), and eye tracker(s) What is the best software tool for my multi-room lab? A multi-room lab offers you a flexible environment to conduct advanced research, training, and usability tests across various settings. With Viso as the engine, you can easily manage and monitor multiple rooms from a single interface, enjoying advanced recording capabilities and real-time observation. This tool integrates data from various sources, enabling you to perform comprehensive analyses of participant behavior and seamlessly conduct complex, multi-room studies. Featured resources Customer story AIXTRA Competence Center, Aachen, Germany At the AIXTRA Competence Center for Training and Patient Safety, they are passionate about providing a safe environment to train healthcare professionals. Read customer story Customer story Fisher-Price Play Lab, East Aurora, NY, USA When observing how children play with toys, it is important that it challenges them so that they are able to reach a new milestone in their development. Read customer story Customer story Delaware Valley University, Doylestown, PA, USA Dr. Audrey Ervin explains how the counseling psychology team was able to build a lab space that supports both training and research. Read customer story Interested in a multi-room lab? Get in touch! Tell us about your research or training needs and we will help you design the perfect multi-room setup — from a simple two-room configuration to a complete facility. @csrf First name * Last name * Email * Message By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Send message --- ## Multimodal Lab | Human behavior research labs URL: https://noldus.com/labs/multimodal-lab Description: Explore multimodal research labs that integrate diverse data types for comprehensive insights, enhancing your understanding of human behavior and decision-making. Overview Studies Equipment Tools Resources Contact Unlock deeper insights Unlock deeper insights into human behavior with a multimodal research lab. By integrating diverse data types—such as physiological measures, eye tracking, and behavioral observations—you can capture a comprehensive understanding of decision-making and interactions. Get in touch arrow_forward What types of studies can I conduct in a multimodal research lab? In a multimodal research lab, you can conduct a variety of studies that integrate different data types to gain comprehensive insights into behavior and decision-making. This approach allows for a richer understanding of complex human interactions and cognitive processes: - checkMeasure physiological responses to assess how cognitive load affects performance and decision-making - checkEmotional response studies to see how reactions impact decision-making in high-stress situations - checkPurchase behavior testing to analyze how consumers choose and buy products - checkUsability testing to see how easy it is for consumers to use products, apps, or websites What equipment do I need in a multimodal research lab? Your multimodal research lab typically requires a combination of specialized equipment to capture diverse data types and facilitate comprehensive analysis of human behavior. Here are some essential lab components you should consider integrating into your lab: - checkObservation room equipped with cameras and microphones, featuring a one-way mirror - checkEye-tracking devices to measure visual attention and gaze patterns, helping researchers understand how participants engage with visual stimuli - checkPhysiological measurement tools to assess skin conductance, heart rate, facial expressions, pupil dilation, and more - checkScreen-based experimental setups, such as monitors or projection systems for presenting stimuli during experiments, allowing researchers to control the visual environment - checkComputer workstations for online behavior research or user experience testing What are the best tools for my multimodal research lab? Streamline your multimodal research from start to finish and get high-quality data and insights into human behavior with NoldusHub. Our new integrated multimodal software solution is designed to combine multiple types of measurements without any hassles. This enables you to easily achieve trustworthy, high-quality data and direct insights into human behavior and decision-making. Facial expression analysis and emotion data allow researchers to gain insights in complex human behaviors in greater depth. With FaceReader you get clear insights into the effects of different stimuli on emotions. If you're looking for a tool to code and explore the recorded behaviors in more detail, The Observer XT will help you out. For example by analyzing event sequences, calculating statistics, and automatically synchronize multiple data streams. Featured resources Blog The power of multimodal research in human behavior studies By implementing multimodal research, scientists are hoping to gain a more complete and nuanced understanding of human behavior than is possible through the examination of any single modality. Read this blog Blog Biometric research: the study of subconscious processes Many researchers worldwide study both explicit and implicit behavior. After all, there is more to behavior than what the eye can see, such as subconscious processes related to attention, cognition, emotion, and physiological arousal. Read this blog Blog Five studies showing the power of multi-modal data in behavioral research The advantages of using multimodal data over a single modality are that it reveals deeper insights and also if one modality fails there can be enough redundancy in the data to still make sense of it. Read this blog Interested in a multimodal lab? Get in touch! Tell us about your research goals and we will help you design a multimodal lab setup that integrates the right combination of tools for your studies. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## Observation lab | Human behavior research labs URL: https://noldus.com/labs/observation-lab Description: An observation lab allows you to observe test participants unobtrusively, in an environment similar to their natural surroundings. Overview What can you do Why observation lab Equipment Software Examples Contact Monitor and analyze behavior When you intend to perform observations for your study or research, or if you need to capture a participant's natural behavior in a controlled environment, an observation lab is the ideal solution. Get in touch arrow_forward What can you do in an observation lab? Study human behavior Whether you're observing how children play or how a team communicates and solves problems, an observation lab helps you capture authentic reactions and interactions. Educational research When you want to understand how people learn, or how they interact in a classroom setting, an observation lab gives you the control and tools to watch their progress in real time. Market research Are you testing how people engage with a new product or marketing campaign? Watch as participants naturally interact with what you're testing, and get data that helps you fine-tune your strategy. Medical research If you're involved in medical research, an observation lab allows you to monitor patient responses to treatments, or how they interact in therapeutic settings. Why should I choose an observation lab? If you're looking to gain real insights into behavior, emotions, or interactions, an observation lab gives you the ability to watch and record your subjects in a controlled setting allowing you to gather pure, unfiltered data. Choose to use an observation lab: - checkWhen you want to observe natural behavior - checkWhen you need control and want to minimize variables that could affect your results - checkWhen you need detailed data What equipment do I need? Stable images, high quality video recordings, and clear recordings of speech and other sounds make all the difference. Each room can be tailored to mimic real-life environments or controlled experimental setups. - checkRecording devices such as IP or Pan-Tilt-Zoom cameras, webcams - checkMicrophones, microphone amplifiers, and audio mixer - checkCentral computer with multiple screens in the control room - checkOptional: Screen capture device(s), data acquisition tool(s), and eye tracker(s) Setting up a well-equipped lab You are focused on understanding behavior, and that is no small task. But with the right tools, it becomes a lot more manageable. We know it is challenging — but we are ready to take on that challenge with you! When you purchase a Noldus lab, integration and synchronization of all equipment is part of our installation service. You can be sure that your hardware and software will work together, and that all your data is in sync. No matter what kind of research you are working on, we will help you get started quickly! What are the best software tools for my observation lab? For an observation lab, you'll need software tools that allow you to record, analyze, and organize your data efficiently. - checkCombining different types of measurements for human behavior studies becomes effortless using NoldusHub - checkAudio and video recording tool Viso records from multiple cameras and rooms simultaneously - checkEvent logging and video analysis software The Observer XT allows you to combine and analyze behavioral observations with physiological data - checkSynchronous recording of video and other sources is possible using MediaRecorder - checkFacial expression analysis software FaceReader can automatically analyze expressions like happy, sad, surprised, angry, and more Featured resources Baby & Child Research Center At the Baby & Child Research Center researchers are part of a large European consortium studying typical and atypical development. Western University At the Social Behavior Lab at Western University, Dr. Erin Heerey explores how people navigate social interactions using observation technology. See an observation lab in action An observation can tell you what someone is doing. Why they are doing it is the next step — and that's where the right tools make all the difference. Interested in an observation lab? Get in touch! Tell us about your research needs and we will help you design the perfect observation lab setup — from a simple two-room configuration to a complete facility. @csrf First name * Last name * Email * Message By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Send message ✕ --- ## Portable lab | Human behavior research labs URL: https://noldus.com/labs/portable-labs Description: A portable observation lab features compact, mobile equipment to allow researchers to conduct studies in diverse, real-world settings. Overview Why portable Equipment Software Contact Get immediate insights A Portable lab is your ultimate solution for on-site testing and observation. Designed for easy transport — each lab fits into a lightweight carrying case. High-quality equipment saves you precious time during on-site observations and speeds up your analysis process. Get in touch arrow_forward Why would I need a portable lab? Natural environment Capture more genuine and accurate data, such as family dynamics during dinner or colleagues' communication patterns in their own workspace. Shared use When you and your colleagues of other departments have the ability to easily share and use the lab across teams without scheduling conflicts. Flexible and mobile The portable lab allows you to easily transport your equipment to various locations, adapting to different research environments as needed. Real-time data collection You can collect and analyze data on the spot, allowing for immediate adjustments to your research or training approach. What equipment is included? The complete lab fits into a lightweight carrying case. The equipment consists of, for example: - checkLaptop including a headphone - checkHigh quality webcam(s) - checkMini tripod(s) - checkScreen capture device - checkRugged carrying bag What software tools fit my portable lab? Depending on your requirements, you can add Viso, The Observer XT, or MediaRecorder to your Portable lab. The Observer XT is an excellent tool for observational studies, giving you maximum freedom in coding behaviors and analyzing patterns. MediaRecorder is the ideal recording tool that enables synchronous video recordings from up to eight different sources. Interested in a portable lab? Get in touch! Tell us about your research needs and we will help you configure the perfect portable lab setup — compact, mobile, and ready to go wherever your research takes you. @csrf First name * Last name * Email * Message By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Send message --- ## How we use cookies URL: https://noldus.com/legal/cookies Description: Learn how we use cookies to enhance your website experience, improve site functionality, and analyze traffic. Read our cookie policy to understand your privacy options. Cookie Policy Last updated: {{ date('F d, Y') }} This Cookie Policy explains how Noldus Information Technology BV ("Noldus", "we", "us", or "our") uses cookies and similar tracking technologies on our website noldus.com (the "Website"). 1. What Are Cookies? Cookies are small text files stored on your device (computer, tablet, or mobile) when you visit a website. They help websites remember your preferences, improve functionality, and analyze usage patterns. Cookies can be "session cookies" (deleted when you close your browser) or "persistent cookies" (remain on your device for a set period or until manually deleted). We also use similar technologies such as your browser's local storage. Where this policy refers to "cookies", it also covers these similar technologies unless stated otherwise. 2. Our Privacy-First Approach We respect your privacy. Our website uses a two-tier approach: - Without Consent: Privacy-friendly, cookieless analytics with anonymized data (no cookies and no third-party scripts are placed in your browser) - With Consent: Additional analytics and marketing tools that may set cookies and load third-party scripts for deeper insights and personalized support You are always in control. You can accept, reject, or customize your cookie preferences at any time. 3. 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Contact Us If you have questions about our use of cookies, please contact us: Noldus Information Technology BV Nieuwe Kanaal 5 6709 PA Wageningen The Netherlands Email: contact@noldus.com Phone: +31 317 473 300 --- ## General terms and conditions URL: https://noldus.com/legal/general-terms-conditions Description: All our transactions are subject to our General Terms and Conditions . Furthermore, the following conditions apply for specific products and service. General Terms and Conditions Last updated: December 31, 2024 All our transactions are subject to our General Terms and Conditions. Furthermore, the following conditions apply for specific products and services: NoldusCare Conditions Cover additional services such as maintenance, support and repairs (not including services provided under the Consultancy Conditions). These can be found in the General Terms and Conditions document under the section "NoldusCare Conditions". Consultancy Conditions Cover our consultancy services. These can be found in the General Terms and Conditions document under the section "Consultancy Conditions". End-User License Agreement For customers who purchase and/or make use of the Noldus software products. Download EULA In the event of conflict, the specific provisions in the EULA and/or the NoldusCare Conditions and/or the Consultancy Conditions take precedence over the General Terms and Conditions. The General Terms and Conditions, End-User License Agreement, NoldusCare Conditions and Consultancy Conditions are applicable to Noldus Information Technology BV and all its subsidiaries. download Download General Terms and Conditions download Download EULA Noldus Information Technology, 31 December 2024 --- ## Privacy policy URL: https://noldus.com/legal/privacy-policy Description: This privacy policy describes how Noldus Information Technology (NIT) uses and protects any personal data that you might provide to us when you use this website. Privacy Policy Last updated: May 07, 2026 Noldus Information Technology BV ("Noldus", "we", "us", or "our") respects your privacy and is committed to protecting your personal data. This privacy policy explains how we collect, use, and safeguard your information when you visit our website noldus.cloud (the "Website"). 1. Company Information Noldus Information Technology BV Nieuwe Kanaal 5 6709 PA Wageningen The Netherlands Email: contact@noldus.com Phone: +31 317 473 300 2. Data We Collect 2.1 Information You Provide - Contact Information: Name, email address, phone number, company name when you contact us or request information - Account Information: Username, password, and profile information if you create an account - Communication Data: Information in correspondence when you contact us - Transaction Data: Purchase history, billing information, and payment details 2.2 Information Collected Automatically - Usage Data: Pages visited, time spent, links clicked, and navigation patterns - Device Information: Browser type, operating system, device type, and screen resolution - IP Address: Anonymized IP address (last 2 octets masked for privacy) - Cookies and Tracking: See our Cookie Policy for details 3. How We Use Your Data We use your personal data for the following purposes: - Service Delivery: To provide and maintain our services, process transactions, and fulfill orders - Communication: To respond to inquiries, send updates, and provide customer support - Website Improvement: To analyze usage patterns and improve website functionality - Marketing: To send promotional materials (only with your consent) - Legal Compliance: To comply with legal obligations and protect our rights - Security: To detect, prevent, and address technical issues and fraud 4. Legal Basis for Processing (GDPR) We process your personal data based on: - Consent: You have given explicit consent for specific purposes (e.g., marketing, analytics cookies) - Contract: Processing is necessary to fulfill a contract with you - Legal Obligation: Processing is required by law - Legitimate Interest: Processing is necessary for our legitimate business interests (e.g., website security, fraud prevention) 5. Data Sharing and Disclosure We may share your data with: - Service Providers: Third-party vendors who assist with website hosting, analytics, payment processing, and customer support - Analytics Services: Matomo Analytics (self-hosted, server-side tracking, no cookies) for website usage analysis - Website Analytics: Google Analytics 4 (loaded only after explicit cookie consent) for conversion tracking and campaign attribution - Legal Authorities: When required by law or to protect our rights - Business Transfers: In connection with mergers, acquisitions, or asset sales We do not sell your personal data to third parties. 6. Data Retention We retain your personal data only as long as necessary: - Account Data: Until you request deletion or close your account - Transaction Data: 7 years (legal requirement for accounting purposes) - Analytics Data: 26 months maximum - Marketing Data: Until you withdraw consent or unsubscribe 7. 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We use cookies only for marketing services (HubSpot, Google Ads) when you give explicit consent. For detailed information, please see our Cookie Policy. You can manage your cookie preferences through our cookie consent banner or your browser settings. 9. Data Security We implement appropriate technical and organizational measures to protect your data: - SSL/TLS encryption for data transmission - IP address anonymization (2 octets masked) - Secure server infrastructure - Access controls and authentication - Regular security audits and updates While we strive to protect your data, no method of transmission over the internet is 100% secure. We cannot guarantee absolute security. 10. International Data Transfers Noldus operates globally with offices in multiple countries. Your data may be transferred to and processed in countries outside the European Economic Area (EEA). When we transfer data internationally, we ensure appropriate safeguards are in place, such as Standard Contractual Clauses (SCCs) approved by the European Commission. 11. Children's Privacy Our Website is not intended for children under 16 years of age. We do not knowingly collect personal data from children. If you believe we have collected data from a child, please contact us immediately. 12. Third-Party Links Our Website may contain links to third-party websites. We are not responsible for the privacy practices of these external sites. We encourage you to review their privacy policies. 13. Changes to This Privacy Policy We may update this privacy policy from time to time. Changes will be posted on this page with an updated "Last updated" date. Significant changes will be communicated via email or website notice. 14. Contact Us If you have questions about this privacy policy or wish to exercise your rights, please contact us: Data Protection Officer Noldus Information Technology BV Nieuwe Kanaal 5 6709 PA Wageningen The Netherlands Email: contact@noldus.com Phone: +31 317 473 300 15. Supervisory Authority If you are not satisfied with our response, you have the right to lodge a complaint with the Dutch Data Protection Authority: Autoriteit Persoonsgegevens Postbus 93374 2509 AJ Den Haag The Netherlands Website: autoriteitpersoonsgegevens.nl --- ## Website terms of use URL: https://noldus.com/legal/terms-use Description: Welcome to our website. If you continue to browse and use this website you're agreeing to comply with and be bound by the following terms and conditions of use. Website Terms of Use Last updated: May 7, 2026 Welcome to the website of Noldus Information Technology BV. By accessing or using this website, you agree to be bound by these Terms of Use. If you do not agree with any part of these terms, please do not use this website. Noldus Information Technology BV Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands Chamber of Commerce: 09088623 Email: contact@noldus.com 1. Acceptance of Terms By using this website, you confirm that you are at least 16 years of age and that you accept these Terms of Use and our Privacy Policy. These terms apply to all visitors, users, and others who access or use the website. We reserve the right to update or modify these terms at any time without prior notice. Your continued use of the website after changes constitutes acceptance of the revised terms. 2. Use of the Website You agree to use this website only for lawful purposes and in a manner that does not infringe the rights of, restrict, or inhibit anyone else's use of the website. Prohibited behavior includes: - Using the website in any way that violates applicable local, national, or international law - Attempting to gain unauthorized access to any part of the website, server, or database - Introducing viruses, trojans, worms, or other malicious or technologically harmful material - Using automated systems (bots, scrapers) to access the website without our written permission - Impersonating any person or entity, or misrepresenting your affiliation with any person or entity 3. Intellectual Property Rights All content on this website — including but not limited to text, graphics, logos, images, audio, video, software, data compilations, and page layout — is the property of Noldus Information Technology BV or its licensors and is protected by Dutch and international copyright, trademark, and other intellectual property laws. You may not reproduce, distribute, modify, create derivative works of, publicly display, publicly perform, republish, download, store, or transmit any material from this website without our prior written consent, except: - Your browser may temporarily store copies of pages for caching purposes - You may print or download one copy of a reasonable number of pages for personal, non-commercial use - You may share links to our content, provided you do so in a way that is fair and does not damage our reputation 4. Trademarks Noldus, EthoVision, CatWalk, FaceReader, The Observer, PhenoTyper, DanioVision, DanioScope, UltraVox, NoldusViso, NoldusHub, NoldusCare, and associated logos are trademarks of Noldus Information Technology BV. All other trademarks reproduced on this website that are not the property of Noldus are acknowledged. Use of any trademark without express written permission is strictly prohibited. 5. Disclaimer of Warranties This website and its content are provided on an "as is" and "as available" basis without any warranties of any kind, either express or implied, including but not limited to: - Implied warranties of merchantability, fitness for a particular purpose, or non-infringement - Warranties that the website will be uninterrupted, timely, secure, or error-free - Warranties regarding the accuracy, reliability, or completeness of any information on the website Information on this website is subject to change without notice. We do not guarantee that the website will be available at all times or that defects will be corrected. 6. Limitation of Liability To the fullest extent permitted by applicable law, Noldus Information Technology BV shall not be liable for any indirect, incidental, special, consequential, or punitive damages, including but not limited to: - Loss of profits, data, use, goodwill, or other intangible losses - Damages resulting from your access to or use of (or inability to access or use) the website - Damages resulting from any unauthorized access to or use of our servers - Damages resulting from any interruption or cessation of transmission to or from the website In no event shall our total liability exceed one hundred euros (EUR 100). 7. User Accounts Certain areas of this website may require registration or a user account. When you create an account, you agree to: - Provide accurate, current, and complete information - Maintain the security of your password and account - Accept responsibility for all activities that occur under your account - Notify us immediately of any unauthorized use of your account 8. Third-Party Links This website may contain links to third-party websites or services that are not owned or controlled by Noldus Information Technology. We have no control over, and assume no responsibility for, the content, privacy policies, or practices of any third-party websites. You acknowledge and agree that we shall not be liable for any damage or loss caused by the use of any such content or services. 9. Product Information Product descriptions, specifications, pricing, and availability on this website are for informational purposes only and do not constitute a binding offer. We reserve the right to modify product information at any time. Any purchase of products or services is subject to our separate General Terms and Conditions. 10. Indemnification You agree to indemnify, defend, and hold harmless Noldus Information Technology BV, its officers, directors, employees, agents, and affiliates from and against any claims, liabilities, damages, losses, and expenses (including reasonable legal fees) arising out of or in any way connected with your access to or use of the website, your violation of these Terms of Use, or your violation of any rights of a third party. 11. Termination We may terminate or suspend your access to the website immediately, without prior notice or liability, for any reason, including without limitation if you breach these Terms of Use. Upon termination, your right to use the website will immediately cease. 12. Governing Law and Jurisdiction These Terms of Use shall be governed by and construed in accordance with the laws of the Netherlands, without regard to its conflict of law provisions. Any disputes arising out of or relating to these terms or your use of the website shall be submitted exclusively to the competent court in Arnhem, the Netherlands. 13. Severability If any provision of these Terms of Use is held to be invalid or unenforceable, the remaining provisions shall continue in full force and effect. The invalid or unenforceable provision shall be replaced by a valid provision that most closely reflects the intent of the original. 14. Entire Agreement These Terms of Use, together with our Privacy Policy and Cookie Policy, constitute the entire agreement between you and Noldus Information Technology BV regarding the use of this website. 15. Contact If you have any questions about these Terms of Use, please contact us: Noldus Information Technology BV Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands Email: contact@noldus.com Phone: +31 317 473 300 --- ## Newsroom URL: https://noldus.com/newsroom Description: Newsroom of Noldus: the latest news on partners, research projects and product launches Newsroom Latest news from Noldus Stay up to date with the latest developments, partnerships, and innovations from Noldus Information Technology. Noldus launches NoldusViso One, its new behavioral research platform On October 8, Noldus unveiled NoldusViso One, the first solution built on its new NoldusRadix foundation, with a live demo and partner talks from Tobii, VicarVision, and Amsterdam UMC. Read more arrow_forward Noldus and Lab Products join forces on animal welfare monitoring Two established leaders in behavioral science and animal housing partner to bring welfare and behavioral monitoring directly into the home cage. Meet CageIQ. Read more arrow_forward A new chapter for Noldus CEO, Jay de Groot, announces a vision to modernize Noldus’ technology and make advanced behavioral research tools more accessible to every researcher. Read more arrow_forward Noldus welcomes new CEO Noldus Information Technology, global leader in software and integrated solutions for behavioral research, today announced the appointment of its new CEO. Read more arrow_forward Noldus and Blackrock Neurotech sign agreement at SfN for official collaboration! Noldus Information Technology partners with Blackrock Neurotech, a global leader in brain-computer interface (BCI) technology and advanced tools for neuroscience and neuroprosthetics research. Read more arrow_forward Noldus partners with Zhejiang Institute of Medical Device Testing September 2024, the Medical Device Usability Engineering Laboratory of Zhejiang Institute of Medical Device Testing (MDST) in Hangzhou was officially opened. Read more arrow_forward Noldus software in MARIN's Seven Oceans Simulator center The Seven Oceans Simulator center (SOSc) at MARIN was officially opened by His Majesty King Willem-Alexander. Read more arrow_forward Efficient Laboratory Animal moNitoring (ELAN) kick off Smart home cage for efficient laboratory animal monitoring. Read more arrow_forward Merging behavior and brain activity for enhanced research insights Noldus IT announces partnership with advanced neurotechnology company Bitbrain Read more arrow_forward Lucas Noldus appointed as Fellow of the Netherlands Academy of Engineering Technology is the engine for sustainable development. With the appointment of 62 Fellows, the Netherlands Academy of Engineering emphasizes the importance of engineering-based sustainable solutions. Read more arrow_forward Noldus teams up with Institut Pasteur to deliver new software for behavioral neuroscience research Noldus Information Technology and Institut Pasteur have collaborated on the development of an innovative solution for automatic tracking and analysis of social behavior in mice. Read more arrow_forward Combatting wildlife crime using cutting edge video technology In May 2022, our CEO Lucas Noldus and VP Marketing Arjan Veenboer attended the opening of the Wildlife Forensic Academy (WFA) in Buffelsfontein, South Africa, one hour north of Cape Town. Read more arrow_forward Introducing NoldusHub, the all-in-one research tool for human behavior studies Noldus Information Technology has released NoldusHub, a brand-new all-in-one research system for multimodal human behavior studies. Read more arrow_forward Monitoring our bees: why and how The Noldus’ garden is a good place for the bees. There is plenty of space and we make sure there is variety of flowers and plants for their needs. Read more arrow_forward Noldus' green roof reflects the dry summer season Two pebble-covered roofs of our Wageningen office have been transformed into beautifull green roofs, with a biodiverse vegetation cover. Read more arrow_forward FaceReader useful to improve Animal-Assisted Therapy For several years now, the Lithuanian University of Health Science (LSMU) in Kaunas, is using the FaceReader software for scientific research within several faculties. Read more arrow_forward Noldus collaboration agreement Inscopix Noldus Information Technology, a leading developer of tools for behavioral research, announced a collaboration agreement with neuroscience company Inscopix. Read more arrow_forward Noldus achieves ISO 27001 information security certification Noldus IT BV has achieved ISO 27001 certification for its Information Security Management System (ISMS).The audit for compliance was completed by an accredited third party certification body Read more arrow_forward --- ## Merging behavior and brain activity for enhanced research insights - Newsroom URL: https://noldus.com/newsroom/bitbrain-noldus-behavior-brain-activity Description: Noldus IT announces partnership with advanced neurotechnology company Bitbrain @include('partials.hero-auroral') Back to Newsroom November 7, 2023 Merging behavior and brain activity for enhanced research insights As a leading provider of tools and solutions for behavioral research, Noldus is proud to announce a collaborative integration that brings together the capabilities with Noldus' comprehensive software and analysis system The Observer XT and Bitbrain's state-of-the-art wearable dry-EEG headset Diadem. Noldus IT announces partnership with advanced neurotechnology company Bitbrain This innovative union facilitates a comprehensive exploration of human behavior and neural dynamics, offering researchers a seamless way to combine behavioral data with real-time neural insights. "The combination of The Observer XT and the 12 channel Diadem allows researchers to synchronize behavioral observations with neural data, enabling practical applications such as cognitive load assessment, user experience studies, neuromarketing research, and more." Monitoring the real-world Bitbrain® utilizes neuroscience, artificial intelligence, and hardware to create innovative products with a strong emphasis on enhancing customers' lives through real-world applications and research. With their practical hardware, prioritizing customer convenience, speed, simplicity, and reliability, Bitbrain brings mobile, wireless, and ergonomic designs that are easy to set up and deliver exceptional signal quality into Noldus observational lab solutions. Multimodal research With neuroscience and psychology research, we strive to achieve a more profound comprehension of behavior, brain, and mind. Through the recording of behavioral and physiological responses to specific stimuli and situations, researchers can reconstruct and analyze the cognitive processes and information utilization within our brain. Comprehensive analysis The synergy between The Observer XT and Diadem enables researchers to correlate intricate behavioral nuances with real-time neural patterns. This opens doors to a deeper comprehension of cognitive processes and emotional dynamics. Uncovering Correlations The combination of both tools effectively eliminates the complexities associated with managing separate datasets, uncovering hidden correlations between behavior and neural responses, and revealing novel perspectives for exploration. Efficiency and Simplification Through synchronized data collection and analysis, researchers can streamline and simplify their workflow. The integrated solution seamlessly accommodates various experimental designs, providing flexibility to tailor the approach to different research objectives in psychological research, human factors, biomedical engineering and consumer neuroscience. Visualization With the powerful visualization of the Behavioral and neural data, researchers can construct visual narratives that vividly highlight connections and trends. Assessing emotional and cognitive states Besides the raw data, the Diadem provides Alpha, Beta, Theta, and Delta Rhythms for each of the 12 channels. These “brain waves” can glean important insights about brain functions as: Aligning expertise for user-friendly solutions Bitbrain's expertise in neuroscience, artificial intelligence, and hardware aligns perfectly with our commitment to delivering top-notch products and services that make our customers' lives easier. Together, we are dedicated to creating convenient, efficient, and user-friendly solutions that positively impact the lives of those we serve. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus and Blackrock Neurotech sign agreement at SfN for official collaboration! - Newsroom URL: https://noldus.com/newsroom/blackrock-collaboration Description: Noldus Information Technology partners with Blackrock Neurotech, a global leader in brain-computer interface (BCI) technology and advanced tools for neuroscience and neuroprosthetics research. @include('partials.hero-auroral') Back to Newsroom October 16, 2022 Noldus and Blackrock Neurotech sign agreement at SfN for official collaboration! Chicago, United States, October 8, 2024 — Noldus Information Technology is pleased to announce a new collaboration with Blackrock Neurotech, a global leader in brain-computer interface (BCI) technology and advanced tools for neuroscience and neuroprosthetics research. This collaboration integrates Noldus’ EthoVision XT behavioral tracking software with Blackrock’s cutting-edge electrophysiology systems, creating a powerful, unified platform for behavioral and neural research. The integration enables synchronization of EthoVision XT’s behavioral tracking data, real-time, with Blackrock’s EEG recordings for mice and rats. The result? Researchers can now link real-time neural activity to behavioral outcomes with greater precision and efficiency—opening up new avenues for neurobehavioral research. This partnership makes it easier for researchers to gain a holistic understanding of behavior and neural dynamics without the need for complex setups or additional synchronization tools. It’s an all-in-one package with an almost plug-and-play setup. We are very excited and look forward to this new partnership! About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Efficient Laboratory Animal moNitoring (ELAN) kick off - Newsroom URL: https://noldus.com/newsroom/elan-kick-off Description: Smart home cage for efficient laboratory animal monitoring. @include('partials.hero-auroral') Back to Newsroom May 5, 2024 Efficient Laboratory Animal moNitoring (ELAN) kick off Developing a smart cage for laboratory animals to stimulate natural behavior, to prevent stress and frustration, and to enable continuous accurate measurements in their home environment. Smart home cage for efficient laboratory animal monitoring Those are the objectives of the project “Efficient Laboratory Animal moNitoring” (ELAN) which had its kick-off last month. ELAN is a collaboration of three Dutch companies - Noldus Information Technology, UNO Life Science Solutions and Brain Builders – and the Radboud University Medical Center. The ELAN consortium aims to develop newly designed home cages equipped with the latest sensor technology and AI to monitor group-housed rats 24/7, rendering valuable scientific data about the animals’ behavior, health and the cage environment. The novel cage should increase the quality and lower the cost of welfare monitoring. By increasing the quantity and quality of research data, while simultaneously improving animal welfare, ELAN will contribute to two important goals of modern biomedical research: refinement and reduction of animal testing. The ELAN project is financed by the European Fund for Regional Development and the Province of Gelderland, The Netherlands, as well as by the consortium partners. Contact Noldus Information Technology BV for more information: press@noldus.com About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## FaceReader useful to improve Animal-Assisted Therapy - Newsroom URL: https://noldus.com/newsroom/facereader-useful-improve-animal-assisted-therapy Description: For several years now, the Lithuanian University of Health Science (LSMU) in Kaunas, is using the FaceReader software for scientific research within several faculties. @include('partials.hero-auroral') Back to Newsroom July 18, 2022 FaceReader useful to improve Animal-Assisted Therapy For several years now, the Lithuanian University of Health Science (LSMU) in Kaunas, is using the FaceReader software for scientific research within several faculties. For example, the faculty of Food Safety and Quality took advantage of the FaceReader software to answer the question whether there is a relationship between food choice and a person’s mood? Recently, Jovitą Lukšaitę and her team of the LSMU faculty of Animal Sciences investigated how to improve Animal-Assisted Therapy (AAT). For this research, they used FaceReader software. Again, a good example of how FaceReader empowers researchers in their work, to obtain objective data in a structured and effective way. The Noldus research portfolio: FaceReader Noldus empowers customers with best in class tools to ease the work of the researchers, enable them to collect data and calculate reliable results to help them discover the insights they are looking for. Working side by side with those researchers results in personal service and tailored solutions for their research needs. FaceReader is one of those innovative tools for scientific research in areas such as communication, emotions, and all kind of interactions, like parent-child interaction, but also human-animal interaction. This article focuses on the latter. The usefulness of Animal-Assisted Therapy (AAT) Positive emotions, as well as the feelings of happiness, are very important factors for human mental and physical health. Within a human-animal interaction, animals such as dogs, cats, sheep, horses, and pigs can provide people with a sense of calm, comfort, or security. Moreover, they can distract the attention from a stressful situation. Animal-Assisted therapy advocates say that developing a bond with an animal helps develop better self-esteem, stabilize emotions, reduce loneliness, and improve communication and social skills. Besides, this form of therapy places less demand on verbal abilities, which can be beneficial in some conditions. AAT turns out to be effective for people with dementia, autistic spectrum disorder, post-traumatic stress disorder, anxiety problems, and many more. The animals help them recover from or cope with health problems. This form of therapy is increasingly being used as part of a treatment plan. Using FaceReader to select animal species for a personalized AAT For many years, humans have known that animals can positively influence human health, but only recently has science begun to investigate the therapeutic effect of animals on individuals with various disorders. There is an increasing interest in improving the therapy’s efficacy through research. One of the main challenges is to establish conditions under which AAT can be most helpful. One of those conditions is using the animal that best suits the person. In addition, the environment in which AAT is performed and the therapy duration are influencing factors. The research team of Lukšaitę expected that personalized strategies for AAT could be improved by selecting animal species and breeds for each person, according to their displayed emotion. This can avoid or minimize stressful situations during human-animal interactions. They were confident that FaceReader would be a perfect tool for their research. Giving consent for recording facial expressions The study involved 50 participants, aged between 18 and 64 years, mostly females (not diagnosed with a mental disorder for at least a one-year period). All test participants were informed about the study using a ‘Personal Information Form’ and were included upon their participation agreement and signing an ‘Informed Consent Form’. Cards with images of different animal species (dogs, cats, sheep, pigs, and horses) and breeds (e.g. shepherd, pug, Labrador, Beagle) were presented to the participants, along with information about the main character traits of the shown animal. After seeing each card, the person was asked to rank their likability towards the shown animal on the Likert scale from 0 (dislike extremely) to 10 (like extremely). Taking facial expressions into account The sessions were recorded using MediaRecorder and were analyzed with FaceReader software afterwards. The researchers chose not to rely on self-reports only. Which is important, since people can be biased in their answers. People tend to respond socially desirable. Besides, an experimental setting can influence them, or subconsciously answer all questions in a certain way (for example, mostly extreme or mostly neutral). By measuring facial expressions as well, a more complete picture emerged. Personalized strategy for improving AAT The study showed that different animal species and breeds induced different emotions in different individuals. The suggested methodology could lead to a personalized animal selection for AAT, using both their maximum expression of the ‘happy’ emotion and their maximum valence, as they both were associated with a good mood and a comfortable, positive human emotional state. It seemed that the highest intensity of the emotion ‘happy’ was induced when the images and behavioral characteristics of pigs were presented. Probably because pigs are intelligent and sensitive animals. In case of valence, the highest number of participants showed the highest valence when the dog group was evaluated, followed by the cat and pig groups. The researchers conclude that the obtained results could be used as a personalized strategy for improving AAT and helping the individuals to select a pet. They suggest to apply the FaceReader technique to base the selecting of the animal species and breed on. Reference Lukšaitę, J.; Zokaityte, E.; Starkute, V.; Sidlauskiene, S.; Zokaityte, G. & Bartkiene, E. (2022). Personalized Strategy for Animal-Assisted Therapy for Individuals Based on the Emotions Induced by the Images of Different Animal Species and Breeds. Animals, 12(5), 597. https://doi.org/10.3390/ani12050597 About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus\' green roof reflects the dry summer season - Newsroom URL: https://noldus.com/newsroom/green-roof Description: Two pebble-covered roofs of our Wageningen office have been transformed into beautifull green roofs, with a biodiverse vegetation cover. @include('partials.hero-auroral') Back to Newsroom August 17, 2022 Noldus' green roof reflects the dry summer season Last year, we decided to convert two pebble-covered roofs of our Wageningen office into green roofs, with a biodiverse vegetation cover. Now we see every day how the vegetation changes. Per hour, per day, per season. Experiencing a very dry summer, we realize even more that our impact is important. We opened our current international headquarters in 2005 in Wageningen, The Netherlands. Today that building houses three beehives, a green roof with biodiverse vegetation covering, sedum roof, and 122 solar panels. The sedum roof covers the building’s social area and canteen. The green roof covers the entrance. The surrounding grounds are planted with native trees and shrubs, and managed without use of chemicals. Especially the green roof covering our main entrance now noticeably reflects the dry summer. Companies of any size can make a difference The Dutch national weather service KNMI reports that this year is well on its way to being extremely dry. It turns out that the sun is the biggest driver of the drought, just like in the extremely sunny year 2020 [1]. We believe that companies of any size can make a difference in sustainability. So next to realizing that we need to act in a sustainable matter, we also contribute to the local initiative ‘Wageningen Klimaatneutraal’ [2] where over 50 'climate partners' are working together on a climate neutral Wageningen by 2030. Already in 2018, Noldus stopped using gas. Alderman Lara de Brito commented back then: “Noldus is the first existing company to completely get rid of gas, which is really special. I'm impressed. From the start, they have been a climate partner that really inspires.” [3] Research on the roof So with our own eyes we observe changes on our roof, but there is also a scientist involved. Eva Drukker, researcher at Wageningen University and Research (WUR), the Netherlands uses our green roofs for her PhD research to look into the effect of green roofs on biodiversity, in particular the diversity of insects. She studies the effect of two variables on vegetation development and colonization by insects. More information about this project was presented in a blog post on our Behavioral Research Blog [4]. Links About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Introducing NoldusHub, the all-in-one research tool for human behavior studies - Newsroom URL: https://noldus.com/newsroom/introducing-noldushub Description: Noldus Information Technology has released NoldusHub, a brand-new all-in-one research system for multimodal human behavior studies. @include('partials.hero-auroral') Back to Newsroom January 26, 2023 Introducing NoldusHub, the all-in-one research tool for human behavior studies Noldus Information Technology has released NoldusHub, a brand-new all-in-one research system for human behavior studies. This software tool will streamline multimodal research from start to finish, providing high-quality data, better understanding of, and insights into human behavior. As a leading developer with over 30 years’ experience, Noldus Information Technology uses the latest technologies to develop cutting-edge tools for science and practice. These allow customers to measure a wealth of modalities, from behavior and physiology to emotion, cognition, and user experience. About NoldusHub The design of NoldusHub follows from our mission to advance human behavior research, and help scientists to overcome any technical challenges along the way. Combining multiple types of measurements can be demanding, especially when using acquisition tools from different manufacturers that have to be calibrated, started, and synchronized. From setting up your equipment to connecting all devices, from recording to visualizing in a clear way, NoldusHub makes multimodal research easy. The system collects data from a webcam, eye tracker, and physiological devices, resulting in the synchronization of a variety of signals and behavioral input. From ECG, and EDA, to PPG, NoldusHub can measure it. “I am very pleased to welcome NoldusHub as a new member of our product family for human behavior research. It addresses an urgent need of scientists who need a versatile tool for multimodal research that is powerful yet easy to use.” Lucas Noldus (CEO) Your data in a heartbeat And NoldusHub does not stop after acquisition. Based on the experimental data gathered, NoldusHub creates valuable insights, both during and after data collection. For example: we have integrated FaceReader, for trustworthy facial expression recognition and analysis. Unique to NoldusHub is its ability to run multiple experiments at once. The system heartbeat of NoldusHub monitors the status of all connected devices in real-time. If anything is amiss, a notification will be sent during the session so any issues can be addressed right away. No surprises afterwards, but an immediate warning if an issue arises. Data regulation and security NoldusHub is a browser-based solution that makes working with big datasets easy, anywhere, on any computer. All communication with NoldusHub is encrypted using HTTPS. Video and audio are streamed over a secured network; and data is locally stored on video servers in the NoldusHub network under the control of the security procedures of the user’s network. NoldusHub offers the user full access to all the data gathered. If it is recorded, it’s accessible. During recording and analysis afterwards, NoldusHub creates useful insights based on the experimental data. Visuals and findings can easily be shared with clients, participants, or stakeholders. It is built on a modern technology stack, making it secure, stable, flexible and simple to maintain and expand in the future. NoldusHub is under continuous development, based on market and user feedback. Are you curious to find out how NoldusHub works? Visit www.noldus.com/noldushub for more information. Or contact us and we'll be happy to answer any questions, or give a demonstration of NoldusHub so you can see it in action. About Noldus Noldus Information Technology offers a wide range of solutions for research in human and animal domains, including biology, psychology, marketing, human factors, and healthcare. We work with leading suppliers and develop innovative, state-of-the art products. As a result, our systems are used by over 60,000 users at more than 12,000 universities, research institutes, and companies around the globe. As a global professional IT company, Noldus complies with the governing laws presiding over our customers for data protection. Noldus Information Technology BV has achieved ISO 27001 certification for its Information Security Management System (ISMS). Compliance with ISO 27001 demonstrates that Noldus uses internationally recognized processes and best practices to manage its internal information infrastructure and systems that support and deliver its services to customers and partners. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus achieves ISO 27001 information security certification - Newsroom URL: https://noldus.com/newsroom/iso-27001-certified Description: Noldus IT BV has achieved ISO 27001 certification for its Information Security Management System (ISMS).The audit for compliance was completed by an accredited third party certification body @include('partials.hero-auroral') Back to Newsroom November 21, 2022 Noldus achieves ISO 27001 information security certification Noldus Information Technology BV has achieved ISO 27001 certification for its Information Security Management System (ISMS). The audit for compliance with ISO 27001 (in full: ISO/IEC 27001:2013) was completed by an accredited third-party certification body. ISO 27001 is an internationally recognized standard that outlines and provides the specifications for an ISMS, providing guidance on how to protect and manage an organization’s information through effective risk management. Compliance with ISO 27001 demonstrates that Noldus Information Technology uses internationally recognized processes and best practices to manage its internal information infrastructure and systems that support and deliver its services to customers and partners. Rogier Jongeneel, Noldus’ Information Security Officer, comments: “I am proud of our achievement. By interviewing professionals throughout the organization, I was able to see Noldus through their eyes. It made me realize that we are improving our policies, procedures, and processes continuously. ISO 27001 helps us focus on lowering risks and preventing incidents. In a systematic way, that is.” He adds: “It really makes me smile when I see my colleagues working, adhering to the standards we have agreed upon. Being awarded the ISO 27001 certificate means that our customers can be confident that our internal processes comply with the highest information security standards.” This success is due not only to the efforts of our QA team and committed employees, but also to the input from our partners, customers, and suppliers. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus and Lab Products join forces to pioneer laboratory animal welfare monitoring - Newsroom URL: https://noldus.com/newsroom/labproducts-noldus-partnership Description: Noldus and Lab Products announce a partnership to bring welfare and behavioral monitoring directly into the home cage. Meet CageIQ. @include('partials.hero-auroral') Back to Newsroom August 17, 2026 Noldus and Lab Products Join Forces, Pioneering the Next Era of Laboratory Animal Welfare Monitoring Two established leaders in behavioral science and animal housing come together to reimagine welfare insight in the vivarium. Noldus, a global leader in behavioral research technology for more than three decades, and Lab Products, the authority in laboratory animal housing for over fifty years, today announced a new partnership to bring welfare and behavioral monitoring directly into the home cage. Meet CageIQ. This is the first, public step in a longer-term mission: combining Noldus' expertise in behavioral analysis, Lab Products' decades of trusted laboratory animal housing, and development guidance from actual users. Together, the two companies and key stakeholders are creating an accessible, retrofit system that delivers meaningful insight without adding complexity or disrupting existing facility investments. We invite the community to follow CageIQ's progress as we work toward more compassionate, more efficient research in the months ahead. More details on capabilities, timing, and early access will be shared as development progresses. Stay in the loop here. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. About Lab Products Lab Products has been a trusted authority in laboratory animal housing for over fifty years, providing caging systems and equipment that support animal welfare and research integrity in vivariums worldwide. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus software in MARIN\'s Seven Oceans Simulator center - Newsroom URL: https://noldus.com/newsroom/marin-oceans-simulator-officially-opened Description: The Seven Oceans Simulator center (SOSc) at MARIN was officially opened by His Majesty King Willem-Alexander. @include('partials.hero-auroral') Back to Newsroom May 31, 2024 Noldus software in MARIN's Seven Oceans Simulator center This week the Seven Oceans Simulator center (SOSc) at MARIN was officially opened by His Majesty King Willem-Alexander. This research facility at the Maritime Research Institute Netherlands in Wageningen is a top-notch simulator center that encompasses 'the sea of the future'. Noldus Information Technology is a proud contributor to the Seven Oceans Simulator center. About the Seven Oceans Simulator center MARIN has pioneered the future of maritime technology with its state-of-the-art, spherical, and dynamic simulators. These groundbreaking facilities showcase an emission-free ship powered by hydrogen and wind propulsion, an advanced maintenance vessel equipped with cranes and underwater drones for offshore wind turbines, and an innovative KNRM lifeboat. This unique research facility underscores MARIN's commitment to promoting clean, smart, and safe maritime practices, while ensuring the sustainable use of our oceans. Opening Seven Oceans Simulator center (SOSc) by King Willem-Alexander © by MARIN Integrated NoldusHub technology Within the SOSc, all simulators can be interconnected to replicate scenarios involving multiple ships navigating challenging sea conditions. Furthermore, the new simulators provide research in virtual reality applications and the monitoring of unmanned vessels. The new simulator center enables MARIN to investigate Human Factors: analyzing crew performance under difficult circumstances. This is made possible with the technology of NoldusHub, our integrated multimodal software solution for human behavior studies. By embedding NoldusHub into all the simulator systems at the SOSc, MARIN can conduct evidence-based behavioral research in various virtual training settings, and help optimize communication, interaction and performance. NoldusHub was designed to combine multiple types of measurements and easily achieve trustworthy, high-quality data and direct insights. The software collects data from a webcam, eye-tracker, and several physiological data acquisition devices. With these, you can measure a variety of signals and behavioral input, including physiological measures and responses like skin conductance, heart rate, pulse, and pupil dilation, facial expressions, eye gaze, fixation, and cognitive workload. This enables MARIN to conduct multimodal research into human decision making and fullfill its mission 'Better Ships, Blue Oceans'. NoldusHub is under continuous development, based on market and user feedback. Are you curious to find out how NoldusHub works? Visit www.noldus.com/noldushub for more information. Or contact us and we will be happy to answer your questions and give a live demonstration of NoldusHub, so you can see it in action. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Monitoring our bees: why and how - Newsroom URL: https://noldus.com/newsroom/monitoring-our-bees-why-and-how Description: The Noldus’ garden is a good place for the bees. There is plenty of space and we make sure there is variety of flowers and plants for their needs. @include('partials.hero-auroral') Back to Newsroom September 14, 2022 Monitoring our bees: why and how In the Noldus’ garden, it is good to be for the bees. There is plenty of space, where they can find a good deal of pollen and where enough nectar-giving flowers and plants grow, including on the green roof of the building. Nearby are lots of trees and the canal (Nieuwe Kanaal) offers them water. A honeybee needs all these ingredients to stay alive: pollen, nectar, and water. Sustainable beekeeping Noldus helps the bees by providing them a safe place to stay. Since a couple of years, we have multiple hives with bee colonies that we take care of. The bee committee, consisting of several colleagues, did a basic beekeeping course to learn what needs to be done during the year to allow the bees to function optimally. At Noldus, we think the survival of the bees is important. As the main pollinators of our crops, such as fruit, we cannot live without these impressive creatures. The most important crops for human consumption are 80% dependent on pollination. Optimal pollination is essential to supply the growing world population with sufficient vitamins and minerals. That is why we put a lot of effort into maintaining our bee colonies, and proudly mention them on the 'About Noldus' webpage as one of our core values. The most important job of beekeepers is monitoring As beekeepers, we regularly check how our bees are doing. Reliable insight into the health status of each bee colony and timely intervention if the health status deteriorates is essential for sustainable beekeeping management and optimal pollination capacity. During our inspections, we pay attention to all sorts of things. Do they bring in pollen? Are they calm or restless? Do they have enough food? Do we see indications of possible diseases? How do the colonies grow? And when they grow, are their hives big enough, or are there signs that they want to swarm? Do they need more space? Preventing a bee swarm In spring, when warmer weather, together with an abundance of nectar and pollen, provide ideal conditions for the colony to increase rapidly, we try to prevent the colonies from swarming. We do this by creating an artificial swarm: we take away the queen bee, put her in a new, empty hive with only part of her colony. The bees that are left behind immediately realize that the queen bee is gone and start making new ones: larvae that were intended as worker bees now get a diet enriched in Royal Jelly. After 13 days, we beekeepers let the new queen bees come out of their cocoons. Overnight, they decide which one of them becomes the new queen bee of the hive. Concerns about one of our colonies At some point, this virgin queen bee goes on a nuptial flight and then starts laying eggs. We checked regularly if that was the case, but every time we went to the hive to see if there were any eggs or perhaps even larvae, we couldn’t find any. After a while, we got worried. We decided to test whether the hive was queenless by placing a frame with eggs and larvae of another hive into their brood nest. By this, the bees got the chance to make a queen, and that was exactly what they did. They immediately generated a number of emergency queen cells on that frame, so it was obvious: they were queenless and needed a new one. It is great to see how they immediately anticipated to the help we offered as beekeepers. If we had not taken this action, or had taken it too late, this colony would probably have gone extinct. Luckily, they have grown to such an extent that the colony is now large enough to face the upcoming winter. Next step: installing BEEP base to monitor their welfare We enter all our inspections in the BEEP app, an online registration system for beekeepers. With the help of the BEEP app, we register and monitor the stressors that the colonies have to deal with. To extend this form of monitoring, we are going to install a BEEP base: an automatic bee measuring system that can be placed under the hive. The built-in weight-, temperature-, and sound sensors send all their information every 15 minutes directly to the BEEP app. This way, we always have insight into the status of our bees, without having to disturb the bees by opening in the hive. Increasing our experience and expertise By giving lots of attention to our bees, we take responsibility for their well-being. With the help of the resources that support us in that, we constantly gain new insights, learn new things, and understand the life of the honeybee better and better. References About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Lucas Noldus appointed as Fellow of the Netherlands Academy of Engineering - Newsroom URL: https://noldus.com/newsroom/nae Description: Technology is the engine for sustainable development. With the appointment of 62 Fellows, the Netherlands Academy of Engineering emphasizes the importance of engineering-based sustainable solutions. @include('partials.hero-auroral') Back to Newsroom November 6, 2023 Lucas Noldus appointed as Fellow of the Netherlands Academy of Engineering Technology is the engine for sustainable development. With the appointment of 62 Fellows, the Netherlands Academy of Engineering emphasizes the importance of engineering-based sustainable solutions for, among other things, agriculture, healthcare and the digital society. NAE Fellows are committed to creating an innovation climate where collaboration is central. We are proud that our CEO, Lucas Noldus, has been elected to join this group of experts in the fields of technological sciences, applied research and product development. The NAE was launched in May 2023 as a publicly funded, multidisciplinary forum that unites experts and innovators from the business and scientific sectors in the areas of technological sciences, applied research and product development. The NAE acts as a hub and advisory body for the Dutch knowledge and innovation system, aiming to amplify the voice of the engineering community to influential decisionmakers. Want to know more? Follow the link to the press release of the NAE. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## A new chapter for Noldus - Newsroom URL: https://noldus.com/newsroom/new-chapter-for-noldus Description: CEO, Jay de Groot, announces a vision to modernize Noldus’ technology and make advanced behavioral research tools more accessible to every researcher. @include('partials.hero-auroral') Back to Newsroom October 1, 2025 A new chapter for Noldus: Advancing behavioral research together For more than 35 years, Noldus has partnered with behavioral scientists worldwide to accelerate research that changes lives. Today marks a new chapter, as our new CEO, Jay de Groot, announces a vision to modernize Noldus' technology and make advanced behavioral research tools more accessible to every researcher. A message from the CEO, Jay de Groot For more than 35 years, we have partnered with behavioral scientists worldwide, and I believe deeply in the extraordinary impact your research can have on society. We are entering a new chapter, and I am honored to step into the role of CEO at Noldus to shape the future. Our first priority remains unchanged: you, the researcher. That's why I have set in motion a comprehensive technical overhaul, the most ambitious transformation in Noldus' history. Revolutionary technical advances Our skilled development teams are working to completely revamp the technological framework of our flagship products. Soon you will experience major improvements in functionality, reliability, and design across Viso, EthoVision, and our entire portfolio. Accessible solutions for every researcher We have heard your feedback about complexity and cost barriers. That is why we are streamlining pricing for tools like EthoVision, FaceReader and The Observer, to accommodate researchers at every stage, whether you are applying for your first grant or leading a large research program. Committed through challenging times Even as the science community faces economic pressures and the global political situation changes continually, we remain committed to delivering the gold standard in behavioral research tools. Our tools are designed to give you stability, clarity, and confidence as you plan for the future. We are off to a new start and with your partnership, we will continue to push the boundaries of what's possible in behavioral research technology. Thank you for your trust. I look forward to building this future together. Warm regards, Jay de Groot CEO, Noldus Information Technology About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus collaboration agreement Inscopix - Newsroom URL: https://noldus.com/newsroom/noldus-collaboration-agreement-inscopix Description: Noldus Information Technology, a leading developer of tools for behavioral research, announced a collaboration agreement with neuroscience company Inscopix. @include('partials.hero-auroral') Back to Newsroom June 28, 2022 Noldus collaboration agreement Inscopix Noldus Information Technology BV has achieved Noldus Information Technology, a leading developer of tools for behavioral research, announced a collaboration agreement with neuroscience company Inscopix. Through this collaboration, Noldus’ pioneering EthoVision XT video tracking software can be integrated in Inscopix’s new nVision platform. Researchers will now be able to perform precise time correlations between rodent brain activity and behavior, such as exploration or navigation and choice tasks. “Uncovering brain dysfunction at the neurocircuitry level and how it is linked to behavior will enable researchers to uncover new insights into how the brain works and will support the development of better targeted treatments,” said Lucas Noldus, Ph.D., CEO of Noldus Information Technology. “We are excited to collaborate with Inscopix and offer users the capability of integrating our pioneering video tracking technology with Inscopix’s new platform.” EthoVision XT has a long-standing record as the market leading software for video tracking and experiment automation. It is capable of tracking and analyzing animal behavior, movement, and activity from video or live camera input. nVision platform Inscopix’ new nVision platform allows for the real-time integration of behavior with miniscope imaging, which enables the simultaneous capture of high-quality behavior and calcium imaging movies in a single session. “We have been working in the background for a long time now to provide our miniscope users with an effortless and accurate way to synchronize their valuable miniscope data with third party-acquired behavioral movies, which is technically laborious to do and prone to data loss,” said Kunal Ghosh, Ph.D., CEO of Inscopix. “We're thrilled to be introducing nVision, which is the first and only platform enabling both high-resolution acquisition of behavioral videos and precise synchronization with calcium imaging data.” Upon release, nVision would be the only integrated technology for the two methods during free behavior, providing scientists with unique, synchronized insights into brain health and disease. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus welcomes new CEO - Newsroom URL: https://noldus.com/newsroom/noldus-welcomes-new-ceo Description: Noldus Information Technology, global leader in software and integrated solutions for behavioral research, today announced the appointment of its new CEO. @include('partials.hero-auroral') Back to Newsroom May 1, 2025 Noldus Information Technology welcomes Jay de Groot as its new CEO Noldus Information Technology BV, the global leader in software and integrated solutions for behavioral research, today announced the appointment of Jay de Groot as its new Chief Executive Officer (CEO), effective as of now. Company founder Lucas Noldus, who has been at the company's helm since its start in 1989, will transition to Chief Scientist. Wageningen, The Netherlands – Noldus Information Technology BV, the global leader in software and integrated solutions for behavioral research, today announced the appointment of Jay de Groot as its new Chief Executive Officer (CEO), effective as of now. Company founder Lucas Noldus, who has been at the company's helm since its start in 1989, will transition to Chief Scientist. In this position, he will continue actively participating in research and product creation. "I founded Noldus Information Technology to provide scientists with innovative tools for measuring behavior, health, and well-being. I will continue to carry out my life's work in my future role", says Lucas Noldus. "After 35 years, the time has come to hand over the baton to a new CEO who will lead the company through its next growth phase. This allows me to focus my energy on research – in collaboration with academic partners – and innovation. As Chief Scientist, my commitment to our customers and the company's success will remain as strong as ever." Jay de Groot is a seasoned executive and strategic leader with over 20 years of experience in software product development, AI, digital transformations, and leading international business operations. Jay has held CEO and board positions at companies operating in Europe, the United States, and China, most notably BackBase, Science Rockstars, Webpower, Moven, and BrainCreators. "With his passion for innovative product development and strong track record of operational success, I am confident that Jay is the right person to steer Noldus IT through the current challenging geopolitical and macroeconomic times", Lucas says. Wibo ten Hove, COO and Executive Board member, comments: "Under Lucas' leadership, the company has grown from a small startup to a global organization with offices across Europe, North America, and China. Lucas played a key role in making Noldus IT the go-to vendor for behavioral research and training tools. I am excited to continue benefiting from his expertise in his new role. Having dedicated nearly 30 years to the company myself, I am looking forward to working with Jay as we navigate the next chapter together." Lucas concludes: "Over the decades, I have been able to work together with an extraordinary team to help scientists around the globe to advance their research. I am proud of the overall recognition that Noldus IT has received, of the solid relationships we developed, and I am grateful for everyone who contributed to making our company what it is today." About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus launches NoldusViso One, its new platform for behavioral research - Newsroom URL: https://noldus.com/newsroom/noldusviso-launch-event-recap Description: On October 8, Noldus launched NoldusViso One, the first solution built on NoldusRadix, with a live demo and partner talks from Tobii, VicarVision, and Amsterdam UMC. @include('partials.hero-auroral') Back to Newsroom October 8, 2026 Noldus launches NoldusViso One, its new platform for behavioral research The first solution built on NoldusRadix was unveiled in Wageningen and online, with a live demo and partner talks from Tobii, VicarVision, and Amsterdam UMC. On October 8, Noldus launched NoldusViso One, the first solution built on NoldusRadix, the company's new technological foundation for behavioral research. The event in Wageningen drew a full room of guests alongside more than 100 people who joined the live stream. NoldusViso is an end-to-end, fully browser-based platform that handles capture, video management, live streaming, observation, annotation, and sharing. It runs on off-the-shelf hardware with no vendor lock-in, scales from a single lab to multi-site setups, and treats enterprise-grade security - single sign-on, two-factor authentication, role-based access, encryption, and audit trails - as a starting point rather than an add-on. In a live demo, Arjan Veenboer built an observation scenario from scratch in the browser, tagged events in real time, and showed multi-room recording and marker navigation. The afternoon also featured partner talks from Tobii on two decades of eye tracking, VicarVision on FaceReader's growth into a multimodal platform, and Dr. Linda Dusseljee-Peute of Amsterdam UMC - an early adopter already running NoldusViso in her eHealth lab - on why human factors matter in healthcare. Teams from HEC Montréal's Tech3Lab and Life Support Distribution rounded out the program. The roadmap ahead includes multimodal integration of eye tracking, facial expression analysis, and physiological data, plus AI-assisted behavioral analysis. FaceReader data is already beginning to flow into the platform. Could not attend? Watch the full launch event replay here, or learn more about NoldusViso. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus teams up with Institut Pasteur to deliver new software for behavioral neuroscience research - Newsroom URL: https://noldus.com/newsroom/pasteur-live-mouse-tracker Description: Noldus Information Technology and Institut Pasteur have collaborated on the development of an innovative solution for automatic tracking and analysis of social behavior in mice. @include('partials.hero-auroral') Back to Newsroom May 16, 2023 Noldus teams up with Institut Pasteur to deliver new software for behavioral neuroscience research Noldus Information Technology and Institut Pasteur have collaborated on the development of an innovative solution for automatic tracking and analysis of social behavior in mice. Noldus Information Technology and Institut Pasteur have collaborated on the development of an innovative solution for automatic tracking and analysis of social behavior in mice. Today we announce the result of this joint effort: a new tool for behavioral neuroscience research, combining Live Mouse Tracker (LMT) and EthoVision XT software. This integration facilitates and enhances the analysis and visualization of LMT data. Live Mouse Tracker was developed by the Human Genetics and Cognitive Functions unit of Institut Pasteur. LMT is a system for real-time behavioral analysis of groups of mice in a dedicated hardware setup. Through the use of RFID, computer vision and machine learning, LMT is able to track multiple mice, extract their individual and social behaviors and assign these parameters to individual animals. EthoVision XT, under continuous development by Noldus Information Technology since its market introduction in 1993, is the most widely used video tracking software for the analysis of behavior, movement and activity of laboratory animals. With the release of version 17.5, LMT data can be imported and analyzed directly in EthoVision XT, which brings all of the functionality and power of EthoVision XT to LMT users. EthoVision XT offers easy organization of LMT trials, which in turn enables data filtering, nesting and analysis. Furthermore, LMT data can be visualized in EthoVision’s graphs and integrated data plots. Lucas Noldus, CEO of Noldus Information Technology, comments: “With this collaboration, the innovative development of Institut Pasteur and Noldus IT’s many years of experience in developing behavior analysis software, are combined to make a step forward in the measurement of social interactions in groups of mice. This will help to advance research on neurodevelopmental conditions and disorders with a social component in which mouse models are used, such as autism, ADHD and schizophrenia.” The Institut Pasteur, a non-profit foundation with recognized charitable status set up by Louis Pasteur in 1887, is today an internationally renowned center for biomedical research. In the pursuit of its mission to tackle diseases in France and throughout the world, the Institut Pasteur operates in four main areas: research, public health, training, and development of research applications. Professor Thomas Bourgeron, head of the Human Genetics and Cognitive Functions unit, adds “I am happy to see our collaboration result in a novel tool that will make analysis of mouse social behavior more accessible to neuroscientists around the world”. Noldus Information Technology, established in 1989 and headquartered in Wageningen, the Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12.000 research groups at universities, institutes and companies around the world. Visit www.noldus.com and discover the solutions and resources needed for your next project. Visit www.livemousetracker.org to learn more about LMT and its applications. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Combatting wildlife crime using cutting edge video technology - Newsroom URL: https://noldus.com/newsroom/wildlife-forensic-academy Description: In May 2022, our CEO Lucas Noldus and VP Marketing Arjan Veenboer attended the opening of the Wildlife Forensic Academy (WFA) in Buffelsfontein, South Africa, one hour north of Cape Town. @include('partials.hero-auroral') Back to Newsroom April 6, 2023 Combatting wildlife crime using cutting edge video technology In May 2022, our CEO Lucas Noldus and VP Marketing Arjan Veenboer attended the opening of the Wildlife Forensic Academy (WFA) in Buffelsfontein, South Africa, one hour north of Cape Town. Wildlife Forensic Academy (WFA) founder Andro Vos and his team took a broad group of stakeholders on a tour through their new facility. We were invited to this grand opening because we are a proud partner of the WFA. So, how are things going ten months later? Time to talk to Andro Vos about the developments and experiences since the opening in 2022. The WFA was founded by Andro Vos. Andro has over 20 years of experience in human crime scene investigation from his work at the Netherlands Forensic Institute (NFI). During a visit to South Africa he came into contact with an entirely different kind of crime scene. He was invited to the Kruger Park to learn about wildlife crime. There Andro witnessed the cadaver of a poached rhinoceros. The whole experience stuck with him and he decided that he needed to do something to stop this rampant wildlife poaching. Wildlife crime is the organized poaching and selling of animals, and is unfortunately one of the biggest illegal businesses in terms of revenue (30 billion dollars worldwide annually). It also facilitates many other types of crime through its distribution chain. Animals are traded for weapons and drugs, and they can carry zoonotic diseases. Furthermore, poaching causes the local ecosystems (where animals are taken and from where they are shipped) to be disturbed. When hearing about wildlife crime, one might think only about killed rhinos and elephants. But actually, Andro told us that most poaching is actually done at sea. The poaching of abalone for consumption is a major problem in South Africa especially. Andro Vos says that, “a major problem in combatting poaching is getting the case through the legal system. A case doesn’t go to conviction without evidence, and gathering evidence is what usually goes wrong. Whilst poachers often leave evidence behind in the form of trash, tents or footprints, crime scene investigators working on wildlife crime lack the knowledge to gather and preserve this crucial information”. In essence, there is not much difference between animal and human forensic science. Therefore, Andro is using his expertise in human forensic science to help those who work in combatting wildlife crime. And after many years of organizing, finding funding and constructing the buildings, the Wildlife Forensic Academy was opened as a solution to professionalize wildlife forensics in South Africa. The WFA is run by a team of experts including forensic scientists, veterinarians, police officers and lawyers. It is their mission to train people on how to properly deal with wildlife crime, from securing a crime scene to presenting evidence in court. One thing the WFA does very well is cater to its intended audience. More than 1/3 of adults in sub-Saharan Africa is illiterate (African library project). Therefore, it is important that people can be taught how to do forensic research without needing the ability to read. In order to provide this learning environment, the WFA has several facilities to enable a hands-on learning process. In its hangar on the Buffelsfontein Game & Nature Reserve, the WFA houses multiple “active crime scenes”. These simulated crime scenes consist of a life size rhino, a giraffe, a lion, a poacher’s house and an ocean poaching scene. The trainees can experience and practice investigating and processing the crime scene, with the dead animal and the evidence of the crime around it. They get familiarized with the equipment and procedures that are important in securing a crime scene and analyzing the samples taken. This will help them to properly handle a crime scene when they encounter one in the future. Moreover, the WFA also has a simulated court room where trainees can practice presenting evidence in court to get poachers actually convicted, and a lab where they can learn to analyze samples taken at a crime scene. What role does Noldus play in the WFA? The Noldus Viso system is used in these crime scene simulation trainings to facilitate an innovative learning experience. Noldus Viso is an audio/video solution built for easy recording and fast feedback after the recording. An additional feature is that you can mark points of interest during the recording for quick reference in the debriefing. After an hour of training, the instructors can easily playback the video and quickly go to the points of interest that occurred during the training in an efficient and easy way. Seeing your own actions leads to an intensive and productive learning experience. All videos are stored onsite and only with the correct username and password you can access the software. This ensures that all video recordings are safe and secure within the Viso system. Multiple visitors to the WFA have shown interest in our Viso system and how they could implement it in their scenarios. Arjan Veenboer commented: “I am pleased to see that our technology helps the WFA to optimize the quality, efficiency and effectiveness of forensic training. The feedback we receive from trainers inspires us to expand and improve the functionality of the Viso software.” Over the past nine months the WFA has achieved a lot. Furthermore, during the opening in May 2022 the WFA started collaborating with 5 universities in Europe. Currently, Andro Vos and his team have training programs established with 12 universities all over the world. These universities send students to the WFA to follow the training program, but maybe even more important, become aware of the problem that is wildlife crime. “Seeing the trainees having the time of their life and becoming aware of the worth of the WFA is one of the greatest things I have experienced since the opening” says Andro Vos. The achievements of the WFA have not gone unnoticed. The academy was featured in over 15 newspaper and tv news articles worldwide. While already many local rangers have attended training courses, the WFA is certain that many more will follow. The WFA is collaborating with South African National Parks (SANparks) and the Western Cape Government, to provide rangers with forensic training. A sister organization, the Wildlife Forensic Fund, has been established to finance the training for rangers that may not be able to pay for the course. The WFA is also collaborating in international research projects on nature conservation and wildlife crime prevention. The first project of this kind is Nature FIRST, an EU-funded initiative that kicked off in August 2022. Using satellite data, the Nature FIRST consortium wants to predict the behavior and movement of animals and humans to prevent poaching. The WFA is the first in its kind, a unique, but very applicable concept for other regions. Therefore, the WFA are looking to expand to other regions as well. The academy has received a lot of interest from eastern European countries as well as from the U.S. government to start an Academy in Kenya. Having such training facilities all over the world would be an amazing way to improve global wildlife crime fighting efforts. Take home message As you are hopefully aware by now, wildlife crime is a global problem. It facilitates many other forms of crime. Furthermore, the decline in biodiversity in the earth’s many ecosystems is a major problem we as a society face. A decline in key species will disrupt food webs, which is a concern for food production, and ecotourism will suffer greatly too. Organizations like the Wildlife Forensic Academy play an important role in combatting this global problem, and we are sure that many more great things will come from the WFA as it continues to grow. Lucas Noldus concludes: “We at Noldus Information Technology are proud that our technology can contribute to this important initiative in preserving our natural world.” Get in touch with us today to discover how we can help you achieve your goals. Your journey to better solutions starts here. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Noldus partners with Zhejiang Institute of Medical Device Testing - Newsroom URL: https://noldus.com/newsroom/zhejiang-institute-lab-opening Description: September 2024, the Medical Device Usability Engineering Laboratory of Zhejiang Institute of Medical Device Testing (MDST) in Hangzhou was officially opened. @include('partials.hero-auroral') Back to Newsroom September 26, 2024 Noldus partners with Zhejiang Institute of Medical Device Testing This month, the Medical Device Usability Engineering Laboratory of Zhejiang Institute of Medical Device Testing (MDST) in Hangzhou was officially opened. The opening ceremony and seminar were held at the Linping Economic and Technological Development Zone in Hangzhou. Noldus is proud to contribute to this initiative. Image source : MDST Medical technology in China China is keen to boost its production of medical technology to reduce its reliance on imports. In 2015, the Chinese government launched its "Made in China 2025" policy to increase the proportion of domestically made mid- to high-end medical devices used in Chinese hospitals to 70% by 2025, and to 95% by 2030 (Ong, 2024). In order to safeguard the quality and safety of novel medical equipment, medical device inspection laboratories are being established across the country. Among the aspects of medical devices being tested are human factors design and usability of hardware and software. About the laboratory The Medical Device Usability Engineering lab (MDST) features multiple highly advanced simulation and testing environments. These include operating rooms, ICUs, double rooms, nurses’ stations, examination rooms, and simulated home environments. The state-of-the-art lab is equipped with advanced software and hardware, such as medical simulators, single-sided observation mirrors, behavior analysis systems (The Observer XT), multi-video recording software (MediaRecorder), and video recording and playback systems (Viso). Laboratory development The lab is being built in phases, with space reserved for future expansion. This allows for early implementation of usability testing, maximizing investment efficiency. Once complete, the lab will handle testing for two types of medical devices simultaneously. Guidelines Medical Device Usability Engineering The National Medical Products Administration (NMPA) released the “Guidelines for Registration and Review of Medical Device Usability Engineering” on March 19, 2024. These guidelines, effective from October 8, 2024, aim to standardize usability management. The new lab marks significant progress in this field, promoting usability evaluation and optimization, improving product safety and user experience, and meeting clinical needs. To enhance the lab further, the Zhejiang Institute will introduce advanced equipment like eye trackers and finger tracking systems. Noldus will also continue to assist the Zhejiang Institute of Medical Device Testing in completing the next phase of work and plans for the Medical Device Usability Engineering Laboratory, by providing the highest quality research solutions and consulting services. About Noldus Noldus Information Technology, founded in 1989 and headquartered in Wageningen, The Netherlands, develops software and integrated solutions for research on animal and human behavior. Noldus systems are used in more than 12,000 research groups at universities, institutes, and companies in 100 countries. Media contacts mail press@noldus.com phone +31-317-473300 @include('partials.hero-neural-network') --- ## Subscribe to the Noldus Newsline - Behavioral Research Newsletter URL: https://noldus.com/noldus-newsline Description: Subscribe to the Noldus Newsline and stay ahead in behavioral research. Get expert insights, product updates, and exclusive perks delivered to your inbox monthly. @include('partials.hero-auroral') Newsletter Noldus Newsline Stay ahead in behavioral research. Expert insights and the latest innovations, straight into your inbox. - Discover innovations — new tools and software to advance your research - See real research in action — get inspired by studies from our community - Access exclusive perks — early updates on promotions and events Subscribe now arrow_downward Subscribe to the Noldus Newsline Free monthly newsletter — unsubscribe anytime. First name * Last name * Email address * Research area * Select your area Animal behavior research Human behavior research By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Subscribe to Newsline We respect your privacy. Unsubscribe at any time. --- ## NoldusCare URL: https://noldus.com/nolduscare Description: Maintenance and support is vital to any product. With NoldusCare you can rely on fast and reliable services that are available worldwide. Advance your research, faster NoldusCare Keep your software and everyone on your team up to date with NoldusCare. Our service contract equals peace of mind and boosts your lab's efficiency. - checkWork with the latest software versions - checkGet support within 1 business day - checkTrain your team with Noldus Academy Get in touch about NoldusCare arrow_forward Empowering you with reliable care upgrade Work with the latest software upgrades and updates Updates, upgrades and new releases are included. You will work with the latest features and functionalities and the most secure technology. Get priority support: you will go first! Within one business day you will receive a personal answer to your question. Our worldwide support staff will help you whenever you might need us. Train your team with our online academy NoldusCare gives you exclusive access to our online learning environment. Master EthoVision XT or The Observer XT with more courses to follow. verified_user Warranty on your Noldus hardware When Noldus hardware breaks down due to defective materials or workmanship, we will repair or replace it. In case of a NoldusCare extension, conditions apply. play_circle Watch webinars and technical briefings, on demand Want to deepen your knowledge? Noldus is close to your science. Learn from the experiences of other behavioral scientists in your field. event_available Choose a subscription time that suits your needs Your NoldusCare contract can range from 1 to 5 years, giving you the options that work best for you and your research needs. What's included in NoldusCare? Compare NoldusCare benefits with standard support Feature With NoldusCare Without NoldusCare Software upgrades check_circleAlways the newest version, incl. new features closeNo upgrades included Online training courses check_circleFull access to Noldus Academy closeNot available Support response time check_circlePriority: within 1 business day Ticket support system (best effort) Support channels check_circlePhone, TeamViewer & ticket system Ticket system only Webinars & Q&A sessions check_circleInstant access + on-demand replays closeNot available New release demos check_circleIncluded closeNot available Hardware warranty check_circleExtendable up to 3 years 1 year factory warranty only Software version support check_circleAlways the latest version Support on recent versions only Knowledge base & FAQs check_circleFull access via MyNoldus check_circleFull access via MyNoldus * Hardware warranty can be extended for up to three years with an uninterrupted NoldusCare contract, available for one time. A trained team, always and anywhere, with Noldus Academy Feel assured everyone on your team knows how to use your Noldus product best. With NoldusCare you will get access to Noldus Academy, our online learning platform, packed with resources to boost your research: - checkOnboarding courses on EthoVision XT and The Observer XT - checkA video series on CatWalk XT - checkMany webinars on various behavioral research topics - checkEarn a certificate upon completion and share it on LinkedIn! If you complete the training courses you can even earn a certificate and share it on LinkedIn! Watch the EthoVision XT introduction video to get an impression. Show me Noldus Academy arrow_forward Supported software versions It is crucial to stay updated with the latest software versions to maintain efficiency, security, and compatibility. With active NoldusCare you will always have access to the latest version! - checkEthoVision XT - Version 17.0 and up - checkCatWalk XT - Version 10.0 and up - checkThe Observer XT - Version 16.0 and up - checkViso - Version 9.0 and up - checkFaceReader - Version 8.0 and up - checkNoldusHub - Version 1.0 and up - checkMediaRecorder - Version 6.0 and up - checkDanioScope - Version 1.0 and up Why update? Older versions may still function but lack the updates necessary to fully ensure optimal performance and security. Also, support is limited and you'll miss out on the newest features, functionalities and bug fixes. Tell me more about upgrades arrow_forward Interested in NoldusCare? Get in touch! Contact us to learn more about NoldusCare service contracts and how we can support your research team. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## NoldusHub URL: https://noldus.com/noldushub Description: NoldusHub is the all-in-one research tool for human behavior studies. Streamline your multimodal research from start to finish for insights into human behavior. NoldusHub How It Works Pricing Platform Explore Customer Stories FAQ Contact Work smarter with your behavioral data NoldusHub The secure, centralized platform is designed so that users can start recordings with just a few clicks, without needing complex scripts or technical expertise. With its fully integrated system, NoldusHub synchronizes and manages all connected devices, streamlining your research workflow. Explore the options arrow_downward A central hub All your behavioral data in one secure environment Built for multimodal research Bring all your data streams together Secure by design Data protection by default Connecting your behavioral research hub Bring your data together NoldusHub connects data from different systems and projects into one structured environment. No more scattered files, version confusion, or lost data. folder Stay in control Manage user roles, permissions, and access rights with ease. You decide who sees what across teams, departments, or locations. shield Work securely Security isn't an add-on. It's built into the foundation of NoldusHub. With encrypted storage, controlled user roles, and secure authentication, your data is protected by default. Practical features {{pricing-eur:1442|usd:1443|restricted:1444}} One platform. Endless possibilities. Bring together your research data, collaborators, and workflows in one secure environment designed to support every stage of behavioral research. A central hub Bring all your behavioral research data together in one secure, structured environment. Organize projects, recordings, observations, and datasets in a single platform with centralized storage, role-based access, and a consistent project structure. Built for multimodal research Combine video, behavioral observations, physiological measurements, eye tracking, and other research data in one unified platform. Synchronize multiple data streams to gain a complete view of behavior throughout your study. Designed for collaboration Enable researchers, reviewers, and administrators to work together with confidence. Share projects, manage permissions, and control access across teams, departments, and locations while keeping everyone aligned on the latest data. Explore further Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. NoldusHub in real-world research Explore how NoldusHub supports applied research in practice. Human factors MARIN - Maritime research institute Human factor research in a ship bridge simulator MARIN, one of the world's leading maritime research institutes, gives a tour of their ship bridge simulator. A range of situations can be introduced here to the crew, such as challenging weather conditions or specific navigational tasks. Using NoldusHub, they monitor, track, and score behavioral responses which helps to improve the understanding of complex decision-making. Consumer behavior COMFOCUS project - University of Life Sciences How unexpected flavors reveal consumer emotions What happens when your brain expects something sweet, but your mouth gets savory? Researcher Artur Głuchowski used this twist to uncover how we emotionally react to unexpected food. To measure implicit reactions, he used NoldusHub. Explore other customer stories Frequently asked questions About NoldusHub Can I combine different types of data? You can analyze facial expressions via webcam, including basic emotions like happy, sad, angry, surprised, and neutral. With a stationary eye tracker, you can observe gaze and fixation on a computer screen, providing reliable data on attention, cognitive load, and arousal. Physiological responses such as ECG and PPG can detect changes in heart activity, helping you understand whether a participant is calm, active, excited, or stressed. In addition, you can capture audio, video, screen recordings, posture, movements, and verbal or nonverbal behavior. Is derived data calculated in real-time or post-analysis? Derived data—like facial expressions, heart rate, and electrodermal responses—are calculated in real-time, allowing you to review these signals immediately during data collection. This instant access makes it easy to adjust or monitor sessions as needed. Calculations for more complex indicators, like cognitive workload (from pupil dilation and ambient light data), are available right after data collection, accessible during replay mode for a thorough review. Can multiple team members work in the same project? Yes. You can define who has access to what, so everyone can work safely in the same environment. Where is my collected data stored? Your data is securely stored on a dedicated NoldusHub server within your organization's network. This setup keeps all your raw and processed data in one centralized location, ensuring easy access and control. Anyone with granted access can view and edit the data on their own devices. Plus, you have the flexibility to download your collected data to your computer anytime. Can I download all data that is collected? You can download an extensive set of data collected by the devices supported by NoldusHub. To keep things streamlined, we pre-select key data points for export, ensuring the process stays straightforward and manageable. However, we've expanded download options based on user demand, allowing you access to more data, including raw signals like pupil size and data quality metrics, so you have the flexibility to dig as deep as you need. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## NoldusHub Applications URL: https://noldus.com/noldushub/applications Description: With NoldusHub you get one central solution for setting up your behavioral research projects. Learn more about how use of NoldusHub in various applications. @include('partials.hero-auroral') Back to NoldusHub What can I use NoldusHub for? With NoldusHub you get one central solution for setting up your behavioral research projects. NoldusHub simplifies data collection, synchronization, and analysis, making it the ultimate platform for gaining actionable insights into decision-making and user insights. Discover the various applications for NoldusHub. Tell me more Various applications for NoldusHub Behavioral psychology Human behavior is a captivating subject for many researchers. Observations, including video recordings, physiological measurements, and facial expression analysis, play a crucial role. Combining multiple modalities into one tool is key. Behavioral economics Behavioral economics merges psychology and economics to explore how psychological factors influence economic decisions, helping policymakers and businesses create strategies that better match human behavior and decision-making. Consumer insight Consumer behavior research focuses on studying consumer actions and getting to know the underlying motives. Systematic observation and structural analysis provide key insights to predict consumer preference and buying behavior. Human factors Human factors and ergonomics applies psychological and physiological principles to improve product design and system efficiency. By combining various measurements you can collect high-quality data for analyzing signals such as skin conductance and cognitive workload. User experience UX research focuses on discovering and understanding behaviors, needs, and motivations of users. With NoldusHub, integrate system data to understand behaviors in their full context, ensuring designs are user-friendly and efficient. What data can you collect with NoldusHub? Facial expressions Facial expressions provide lots of insight into someone's emotional state. Basic expressions can be analyzed, such as happy, sad, angry, and surprised. In addition, NoldusHub can measure mental states like interest, boredom, and confusion. AV & screen capture, and event marking Postures, movements, nonverbal and verbal behavior — all can be observed to get a complete insight into the participant's behavior, responses, and motivations. Mark events of interest during or after recordings using a self-created marker list. Heart rate (HR) and Interbeat interval (IBI) Detect changes in physiological measures and find out whether a test participant is active, excited or scared. Choose ECG or the less invasive PPG, depending on your research needs. Gaze and fixation With a stationary eye tracker, observe the test participant's gaze on a computer screen to get rich, quantitative, and reliable data for attention, mental load, and arousal. Skin conductance peak rate By measuring skin conductance peak rate, a physiological response not under conscious control, you get an indication of psychological arousal — whether a person is anxious or startled by a trigger. Featured blog posts on multimodal research Blog The power of multimodal research in human behavior studies By implementing multimodal research, scientists gain a more complete and nuanced understanding of human behavior than any single modality can provide. Read this blog post arrow_forward Blog Behind the Scenes: Human Behavior Research Labs From babies to business, it can all be researched. Want to see how some of this research is done? Check out these amazing human behavior labs in action. Read this blog post arrow_forward Blog 5 studies showing the power of multi-modal data The advantages of using multimodal data over a single modality are that it reveals deeper insights and provides redundancy if one modality fails. Read this blog post arrow_forward Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## NoldusHub Setup URL: https://noldus.com/noldushub/setup Description: Learn how to set up NoldusHub for your behavioral research. One central solution for automatic integration, synchronization, and visualization of human behavior data. @include('partials.hero-auroral') Back to NoldusHub How do I use NoldusHub? With NoldusHub you get one central solution for setting up your behavioral research projects. Automatic integration, synchronization & visualization of human behavior: it's possible within NoldusHub. Want to see how that works? Try out our free online introductory training. See how it works What does the software offer me? NoldusHub offers a seamless, user-centered experience for researchers needing reliable, high-quality data collection and analysis. With its fully integrated system, NoldusHub synchronizes and manages all connected devices, streamlining your research workflow. The built-in quality control "system heartbeat" monitors signal integrity in real time, ensuring that your data is accurate and reliable. Data security is a top priority, with secure storage solutions that keep your research protected. NoldusHub lets you concentrate on insights, managing data quality, integration, and security in the background — ideal for advanced research applications. What do you get with NoldusHub? NoldusHub Core A standard NoldusHub solution consists of a NoldusHub Core: one participant station and one test leader station. NoldusHub gives you one point of access, one point of control, and one visualization of all behavioral responses and recorded signals. Multiple test stations NoldusHub connects up to four participant stations and two test leader stations, allowing you to record data from up to four participants simultaneously. Save time, streamline scheduling, and boost lab efficiency. Privacy and security Data is kept safe and protected. Access your project via browser-based login without installing applications. Only those with an active account can log in, and built-in user management grants access at different user levels. Integrating multiple data streams using an AV lab Are you interested in performing unobtrusive observations in a controlled environment? Then an Audio Video lab might be the tool for you! With multimodal measurement you can gain deeper insights into implicit responses and mental processes. It is vital that different data streams are recorded synchronously or can be easily synchronized after data acquisition. Solutions such as NoldusViso, NoldusHub and The Observer make that happen. In this video we'll tell you all about why an AV lab is a great tool when you want to obtain data out of multiple data streams. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## NoldusViso URL: https://noldus.com/noldusviso Description: NoldusViso is the all-in-one observation platform for behavioral research. Record, code, and analyze behavior with a single integrated solution. NoldusViso Features Foundation Launch Event Explore How It Works Success Stories FAQ Contact New release NoldusViso A future-proof audio and video platform for behavioral observation. Reliable recording, fast setup, strong security, and easy scaling support how you work. View or review sessions anytime, anywhere, on any device, while keeping your focus on behavior. - Capture behavior in context, from multiple cameras and rooms - Review together, anywhere, on any device - Super simple to use - nothing to install - One foundation, one login for your whole lab Request a quote Subjects Emma (e) Tom (t) Events Add comment… Task Lists Talking (a) Listening (l) Writing (w) 12:25:15 5s 10s 15s 20s 25s Emma — Events Emma — Task List 1 Listening Talking Listening Tom — Events Tom — Task List 1 Talking Listening Talking Listening Talking Next-generation foundation Built on modern architecture Security by design Your data protected by default Designed to grow Built to scale with you Built to record, review, and grow Features that simplify your work NoldusViso is designed to fit into your daily workflow from day one. Start simple, work securely, and expand when your needs grow. Each feature helps you record, review, and manage sessions without added complexity. Check the NoldusViso leaflet hub Super simple to use Work entirely in your browser, without complex installations or dedicated hardware. Set up quickly, get started fast, and avoid fragile setups that slow you down. bookmark Capture behavior in context Record high-quality video and audio from one or multiple cameras. Annotate both moments and longer behaviors to capture (inter)actions as they really unfold. play_circle Review together anywhere Watch sessions live or review them afterwards from any location and on any device. Invite others as remote viewers to observe sessions without giving them full access to the system. shield Secure by design Protect sensitive data with encryption, two-factor authentication, and controlled user roles. Designed to meet security and privacy expectations in research, education, and enterprise environments. Read all about Security legislation NoldusViso arrow_forward account_tree Built to grow with you Start small and scale over time, from a single-room or portable setup to a fully integrated observation lab. The platform fits into existing IT environments and grows with your team, spaces, and ambitions. Built on a foundation for the future Every new generation starts with a strong foundation. NoldusViso is built on Noldus Radix, our modern platform designed to deliver security, scalability, and continuous innovation for years to come. Next-generation foundation NoldusViso is powered by Noldus Radix, our new technical foundation designed for performance, flexibility, and long-term innovation. It provides the reliable base on which future Noldus solutions will continue to grow. Security by design Protecting research data isn't an add-on, it's built into the foundation. NoldusViso is designed with modern security principles, secure authentication, and a robust architecture to help safeguard your research. Built with security at its core, so you can focus on your research. Designed to grow Whether you're expanding your team, adding new locations, or adopting future Noldus solutions, NoldusViso is built to scale with you. Ready to bring NoldusViso to your lab? Request a quote Request a demo NoldusViso One Launch Event Watch the recording Thank you to everyone who joined the NoldusViso launch event on October 8. You can now watch the full program online, including all presentations and inspiring customer and partner stories. Watch the recording arrow_forward Explore further Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. Designed for observing behavior videocam Record with confidence Capture synchronized video and audio from multiple cameras to get a clear, complete view of behavior. Review what happened Watch sessions live or later and add annotations to structure feedback, reflection, and discussion. dashboard Manage and scale securely Keep recordings organized, control access, and scale across users, rooms, and locations without complexity. {{-- PRICE BLOCK TEMPORARILY DISABLED (re-enable by removing the surrounding Blade comment): {{pricing-eur:1436|usd:1437|restricted:1438}} --}} See NoldusViso in use Showing how teams apply NoldusViso in real scenarios Training AIXTRA - Competence center for training and patient safety Simulation training for medical education At AIXTRA, they're passionate about preparing the next generation of healthcare professionals through innovative and hands-on medical teaching. Here, students improve their skills and build the confidence they need to succeed in their future roles, whether in hospitals or other healthcare settings. User Experience Ede Christian University of Applied Sciences Study interactions with (digital) products In the CHE UX lab, students test clickable prototypes by watching each other's sessions live or on replay. They annotate interactions and give feedback, gaining direct insight into how users interact with their designs and where attention is missed. The lab is a huge asset to the curriculum. Explore other customer stories NoldusViso Frequently asked questions How do I get started? Getting started with NoldusViso begins with choosing the setup that fits your space and workflow. The next step, the installation, is simple and straightforward. You work directly in your browser to record, review, and manage sessions. If you have questions along the way, support is available whenever you need it. How many cameras can I use in one setup? NoldusViso supports multiple cameras within a single room, including setups with more than four cameras. This allows you to capture sessions from different angles and reduce blind spots, giving you a more complete view of participant behavior. How is my data secured? Several features have been implemented to safeguard unauthorized access, such as a user login, two-factor authentication, audit trail, and sophisticated user management. All videos have a centralized storage to ensure privacy, thus enabling secure data in rest. Data is encrypted, meaning it is securely encoded during storage and transfer. This protects your research data against unauthorized access and supports compliance with common security and privacy requirements. Can multiple people review a session together or remotely? Yes. Sessions can be reviewed from different locations and on different devices. You can also invite others as remote viewers, allowing them to observe sessions without giving them full system access. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... × --- ## NoldusViso Launch Event — Watch the recording URL: https://noldus.com/noldusviso-launch-event/playback Description: Watch the full recording of the NoldusViso One launch event: Lucas Noldus and Jay de Groot introduce the platform, with a live demo and guest talks from Tobii, VicarVision, Amsterdam UMC and Life Support Distribution. On demand NoldusViso Launch Event watch the recording Missed the live event, or want to watch it again? The full recording is right here; the complete reveal of NoldusViso, from live demo to what’s next. - play_circleThe full NoldusViso product reveal and live demo - forumAudience questions and the “what’s next” roadmap - scheduleWatch at your own pace and jump to any moment. More about NoldusViso arrow_downward calendar_month Plan a meeting with an expert Subjects Emma (e) Tom (t) Events Add comment… Task Lists Talking (a) Listening (l) Writing (w) 12:25:15 5s 10s 15s 20s 25s Emma — Events Emma — Task List 1 Listening Talking Listening Tom — Events Tom — Task List 1 Talking Listening Talking Listening Talking Tobii VicarVision Noldus Tech3Lab Life Support Distribution Tobii VicarVision Noldus Tech3Lab Life Support Distribution The presentation program Explore the sessions from our Launch Event. Discover more about each topic and its speakers, and watch the presentations by clicking ‘View the Session’. 0:00:00 Welcome & introduction to our new foundation for behavioral research Noldus Speaker: Lucas Noldus & Arjan Veenboer An introduction to NoldusViso One, the first solution built on NoldusRadix, and the technological foundation for the next generation of Noldus solutions. View the session 0:27:51 Seeing more in human behavior Tobii Speaker: Jon Ward & Antoine Luu Explore the role of eye tracking, biometrics and human cognition in gaining deeper insights into behavior. View the session 0:55:40 Understanding emotions beyond observation VicarVision Speaker: Tim den Uyl Discover how facial expression analysis and additional behavioral signals contribute to a better understanding of human emotions. View the session 1:23:59 Behavioral research in practice Amsterdam UMC – Medical Informatics Speaker: Dr. Linda Dusseljee-Peute A research perspective on human factors, user-centered design and the evaluation of digital health technologies. View the session 1:47:26 Q&A session with the Noldus Team Noldus Speaker: Noldus Team Have questions about NoldusViso One or NoldusRadix? Watch the Noldus Team address questions from the audience and share additional insights into the new solutions and their possibilities for behavioral research. View the session 1:59:49 Building the behavioral research lab of tomorrow HEC Montréal – Tech3Lab Speaker: Tech3Lab A look at multimodal research environments, research infrastructure and collaboration between technologies. View the session 2:15:01 Behavioral research around the world Life Support Distribution Speaker: Fabien Boch Insights from an international reseller on market developments, researchers’ needs and applications of behavioral research technologies. View the session 2:28:38 What’s next: Advance, together. Noldus Speaker: Jay de Groot Looking ahead at the NoldusRadix foundation and future opportunities for behavioral research. View the session this.recalc()); setTimeout(() => { this.recalc(); this.onScroll(); }, 300); this.$refs.track.querySelectorAll('img').forEach(img => { if (!img.complete) img.addEventListener('load', () => { this.recalc(); this.onScroll(); }, { once: true }); }); window.addEventListener('resize', () => { this.recalc(); this.onScroll(); }); }, // Pixel offset of each card's left edge, relative to the track. cardOffsets() { const t = $refs.track; const cards = t.querySelectorAll('.nvl-speaker-card'); const base = t.getBoundingClientRect().left; return Array.from(cards).map(c => c.getBoundingClientRect().left - base + t.scrollLeft); }, recalc() { const t = $refs.track; const cards = t.querySelectorAll('.nvl-speaker-card'); if (!cards.length) { this.pages = 1; return; } // How many whole cards fit in the viewport right now. const cardW = cards[0].offsetWidth; const perView = Math.max(1, Math.round(t.clientWidth / cardW)); // One stop per card that still has hidden cards to its right. this.pages = Math.max(1, cards.length - perView + 1); }, step(dir) { this.goTo(Math.min(this.pages - 1, Math.max(0, this.active + dir))); }, goTo(i) { const t = $refs.track; const offsets = this.cardOffsets(); const max = t.scrollWidth - t.clientWidth; const target = Math.min(max, offsets[i] ?? 0); t.scrollTo({ left: target, behavior: 'smooth' }); this.active = i; }, onScroll() { const t = $refs.track; const offsets = this.cardOffsets(); // Active = card whose left edge is closest to the current scroll position. let best = 0, bestDist = Infinity; offsets.forEach((off, idx) => { const d = Math.abs(off - t.scrollLeft); if (d < bestDist) { bestDist = d; best = idx; } }); this.active = Math.min(best, this.pages - 1); } }"> Meet the speakers During the presentations you will hear from our partners and guest speakers. Tobii Jon Ward With over 15 years' experience in the research industry, Jon has helped hundreds of companies and research institutions understand their subject's behavior and intent. Specializing in eye tracking, biometrics and human cognition, he is most engaged when fixing real-world challenges that improve people's lives and experiences. Tobii Antoine Luu After 10 years in mechanical engineering research in the aerospace & defence industries, Antoine moved to human-behaviour-related tech in 2007 within Tobii. For the past 18 years, he has been helping academic researchers, commercial and industry specialists use eye tracking throughout their use cases. He is now in charge of developing synergies with global technology and business partners. VicarVision Tim den Uyl Tim den Uyl is CEO of VicarVision, the Amsterdam-based company behind FaceReader and a longstanding partner of Noldus. With a background in Artificial Intelligence, he has spent more than a decade connecting research and product development to help researchers better understand human behavior. His work includes international collaborations on projects ranging from stress monitoring to human-robot interaction. At VicarVision, he focuses on developing scientifically grounded, practical tools, including FaceReader's expanding capabilities for analyzing facial expressions, physiological signals and eye movements. Amsterdam UMC – Medical Informatics Dr. Linda Dusseljee-Peute Dr. Linda Dusseljee-Peute is Associate Professor of Medical Informatics at Amsterdam UMC and Director of the eHealth Living & Learning Lab Amsterdam (ELLLA). As a Human Factors Engineering researcher, she focuses on user-centred design, UX and the evaluation of digital health and AI applications, with particular attention to inclusivity and ensuring that digital health works for people with different needs, abilities and levels of experience. She is also Scientific Advisor to Nictiz, contributing to work on usable data and human-centred digitalisation in healthcare in the context of the European Health Data Space (EHDS). Life Support Distribution Fabien Boch Founded in 2019 in Folgensbourg (Alsace, France), Life Support Distribution supplies healthcare simulation solutions to hospitals, nursing and allied health schools, medical faculties, fire and rescue services, and the armed forces. Its President, Fabien Boch, originally trained in electronics before retraining as a nurse: he spent ten years in high-acuity intensive care, then joined an emergency department in Switzerland. A specialist nurse (EPD ES) holding a CAS in education from Lausanne, he co-founded Life Support France in 2001, then Life Support Distribution in 2019. 1"> Why we’re celebrating A new foundation. A new generation of Noldus solutions. The launch of NoldusViso One marks more than the introduction of a new product. It is the first solution built entirely on NoldusRadix, our new technological foundation, developed from the ground up with a modern technology stack. NoldusRadix gives us a new starting point for how we build Noldus solutions. Designed for security, flexibility and scalability, it allows us to keep innovating and developing solutions that grow with the changing needs of behavioral researchers. And NoldusViso One is where that new generation begins. That’s why 8 October is a moment we want to celebrate together: to show you what we’ve built, let you experience it first-hand, and give you a glimpse of where Noldus is heading next. Explore further NoldusViso Frequently asked questions How do I get started? Getting started with NoldusViso begins with choosing the setup that fits your space and workflow. The next step, the installation, is simple and straightforward. You work directly in your browser to record, review, and manage sessions. If you have questions along the way, support is available whenever you need it. How many cameras can I use in one setup? NoldusViso supports multiple cameras within a single room, including setups with more than four cameras. This allows you to capture sessions from different angles and reduce blind spots, giving you a more complete view of participant behavior. How is my data secured? Several features have been implemented to safeguard unauthorized access, such as a user login, two-factor authentication, audit trail, and sophisticated user management. All videos have a centralized storage to ensure privacy, thus enabling secure data in rest. Data is encrypted, meaning it is securely encoded during storage and transfer. This protects your research data against unauthorized access and supports compliance with common security and privacy requirements. Can multiple people review a session together or remotely? Yes. Sessions can be reviewed from different locations and on different devices. You can also invite others as remote viewers, allowing them to observe sessions without giving them full system access. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Book an online meeting Discuss implementing NoldusViso in your workflow with a Noldus expert. We’ll get back to you within one business day. Thank you! We’ve received your request and will be in touch shortly. 0 && !submitted" class="bg-red-50 border border-red-200 rounded-xl p-4 mb-5"> Please correct the following: - First name * Last name * Email address * Institute/company * What would you like to discuss? (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Request meeting Sending… × --- ## NoldusViso Applications URL: https://noldus.com/noldusviso/applications Description: Discover how NoldusViso is used across psychology, consumer behavior, education, UX research, and more. Back to NoldusViso What can I use NoldusViso for? NoldusViso is a powerful tool for recording, managing, and analyzing video sessions, making it ideal for training, research, and educational settings. You'll have a seamless way to capture sessions, review them later, and share insights with your team, all from a single platform. It saves you time, ensures better collaboration, and helps you improve outcomes by easily accessing and organizing your video sessions. Plus, you stay in control — your content is secure and only accessible to those you choose. Get your free demo NoldusViso applications Education and training To achieve active learning, video-based feedback is essential in education and training. NoldusViso enables the teacher to show students their behavior during debriefing and engage them in feedback. Psychology research Psychologists rely upon data to make sense of the world. Video observation is a non-invasive form that enables you to capture interactions. Multiple camera views create new perspectives on the same behavior. Emotion analysis Add emotion analysis to your NoldusViso recordings using a screen capture device. See the facial expressions of your participants during a test. Neuroscience research NoldusViso offers researchers a look at four parameters simultaneously, such as behavior, eye tracking, facial expressions, and screen recording. User experience research Video recordings can be used to observe usability testing sessions remotely in real-time. Post-session discussion leads to immediate improvement of procedures and products. NoldusViso used in a research setting The real experts at the Fisher-Price Play Lab in East Aurora, New York, are the kids! Nicole Mackiewicz, child testing researcher at Fisher-Price, tells us how they have proven in the Play Lab that their line of toys, the Linkimals™, promotes learning. They used Noldus' NoldusViso to record the interactions the children have with the toys. Dr. Corinne Eggleston explains that they want to make sure that everything that they create is just right. By measuring children's behavior, and using Noldus tools, they're able to make decisions and claims confidently. NoldusViso versus others See how NoldusViso compares to other observation and recording solutions on the market. Capability NoldusViso General AV/CCTV suppliers Comparable commercial systems Conferencing platforms PTZ cameras, controllable directly from the softwarecheck_circlecheck_circlecheck_circlecancelMultiple room recordingscheck_circleNot standardcheck_circleNot standardTrue remote access and control — start, stop, and schedule sessions from anywherecheck_circleNot standardcheck_circleNot standardRuns on off-the-shelf computer and AV hardware — no vendor lock-incheck_circleNot standardSometimesNot standardLive observation and communication during a live sessioncheck_circlecheck_circleSometimescheck_circleNative behavior annotation — set markers and comments live or in reviewcheck_circlecancelcheck_circlecancelPredefined, reusable scenarios (AV settings, subjects, tasks, events)check_circleNot standardcheck_circlecancelConnects to eye-tracking, facial expression software, and physiological data streamscheck_circlecancelcancelcancelTrue multi-user application, browser-based logincheck_circlecancelcheck_circlecancelGrant and revoke permissions for each user or departmentcheck_circlecancelcheck_circlecancelInvite participants to view and review specific sessionscheck_circlecancelcheck_circlecheck_circle2FA, encryption, configurable retention policies, and audit trailscheck_circlecancelcheck_circlecancelGDPR & HIPAA compliantcheck_circlecancelSometimescancelExport videoscheck_circlecancelSometimesNot standardInterface for video debriefingcheck_circlecancelSometimescancelSimultaneous recordings in all roomscheck_circleNot standardcheck_circlecancelExport scored markers for analysischeck_circleNot standardSometimescancelFlexibly select views for presentation (choose cameras, hide markers)check_circleNot standardSometimescancelVPAT ready (Voluntary Product Accessibility Template)check_circlecancelcancelcancel Comparison reflects typical capabilities of each category; individual products vary. Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## NoldusViso is here URL: https://noldus.com/noldusviso/new Description: NoldusViso is here - one browser-based foundation for recording, reviewing, and understanding behavior. bolt New release NoldusViso is here! One browser-based foundation for recording, reviewing, and understanding behavior. No more juggling separate systems or waiting for exports. Record it, mark it, and act on it — all in one place. - check_circleCapture behavior in context, from multiple cameras and rooms - check_circleReview together, anywhere, on any device - check_circleSuper simple to use — nothing to install - check_circleOne foundation, one login for your whole lab Receive a quote arrow_forward Join the launch event Share session People with access Alex Riveraalex.rivera@example.com Owner Jordan Leejordan.lee@example.com Annotator Sam Chensam.chen@example.com Viewer Add person Search users… Viewer Add Share via link Viewer Copy link Anyone with the link can join with the selected role. Done Add event Name Color Hotkey Add Cancel Save Schedule Session Session name Training session 2 Scenario Usability Lab Date 17/09/2026 Start time 14:00 End time 15:00 Start and stop recording automatically The recording starts at the scheduled start time and stops at the scheduled end time. Share link Reviewer Copy link Anyone in this department with the link can join with the selected role. Invitees Quickly share with people in your organization Only you have access someone@thecompany.com Reviewer Add Cancel Create session NoldusViso is here! Subjects Emma (e) Tom (t) Events Add comment… Task Lists Talking (a) Listening (l) Writing (w) 12:25:15 5s 10s 15s 20s 25s Emma — Events Emma — Task List 1 Listening Talking Listening Tom — Events Tom — Task List 1 Talking Listening Talking Listening Talking videocam Capture what happened? - Synchronized audio and video recording - Multi-room, multi-camera support - Enterprise-grade security insights Understand why did it happen? - Structured, moment-linked annotation - Instant search across sessions - Shared debrief workflows Grow what is next? - A future-ready foundation, built to expand - Multimodal data on the roadmap - Open to APIs and integrations rocket_launch Ready to see what NoldusViso can do for your lab? Get a personalized quote based on your rooms, cameras, and team — or book a walkthrough with a specialist. Record it, mark it, act on it Receive a quote Book a demo calendar_month Why teams are switching Everything you need, in one foundation NoldusViso replaces disconnected recording setups with a single, browser-based system your whole team can use together — from any room and any device. bolt Super simple to use Work entirely in your browser, with no complex installs or fragile hardware setups. Start a session and go. videocam Capture behavior in context Record high-quality video and audio from one or multiple cameras, and annotate moments as they unfold. Review together, anywhere Watch sessions live or later, from any location and device. Invite remote viewers without full system access. shield Secure by design Recordings stay in your own network, protected by encryption, two-factor authentication, and a full audit trail. Built to grow with you Start with one room, then add cameras, users, and locations without redesigning your setup. hub One foundation, one login Every room, camera, and team member works within a single system, so nothing is siloed or duplicated. event Save the date You are invited Join us for the NoldusViso launch event See NoldusViso in action, meet the team behind it, and get an early look at what's next for the foundation. Join us at the Noldus office in Wageningen, or follow along live from wherever you are. Date Thursday October 8, 2026 Time 12:00 – 18:00 h Walk in from 12:00 Remote program 13:00 – 16:30 Extras Drinks & bites included afterwards Join the launch event arrow_forward October 8 2026 From video to decisions Some systems stop at video. NoldusViso starts there. Because what matters is what comes next. NoldusViso turns recordings into observations, observations into insights, and insights into better decisions — whether you work in behavioral research, education and training, healthcare simulation, or human factors and UX. Receive a quote arrow_forward × --- ## NoldusViso Setup URL: https://noldus.com/noldusviso/setup Description: Learn how to set up NoldusViso for your behavioral observation research. From hardware to software configuration. Back to NoldusViso How do I use NoldusViso? A NoldusViso lab allows you to record test participants unobtrusively, in an environment similar to a natural surrounding. Stable images, high quality video recordings, and clear recordings of speech and other sounds make all the difference in your results. You might wonder which room is most suitable for your lab and what equipment you actually need. For every facility and for every purpose the lab is built for, it will look different. But here you'll find some points of interest. Get in touch Which hardware do I need? NoldusViso runs your entire observation lab from a single system: a workstation or a laptop. The right specifications depend on your camera count and the number of viewers watching at once. See the attached hardware requirements guide for tested set-ups across every lab size, so you can match the hardware to your plans. PDF - Hardware requirements guide What does the software offer me? With NoldusViso, recordings can occur across multiple rooms or buildings at once. This provides you with the freedom to design your training facility as needed. Record and play back sessions in an easy to use way Both after and during the recording of the video, markers and comments can be placed at moments that are of interest. You can capture an entire screen in the recording, including synchronized audio. It is also possible to display an eye tracking gaze-overlay or facial expression data. The recorded actions, behaviors, and interactions of the participants can immediately be assessed during debriefing. "The features of the product such as the multiple room setup, a simple user interface, the ability to have remote access, the level of support, and the ease of integration with other products and hardware made it a clear choice." Sean Rooney The London School of Economics, United Kingdom Replay and evaluate sessions Play back and debrief quickly The videos recorded in NoldusViso are immediately available for debriefing. During debriefing, you can use the Presentation view to show recorded videos on a different screen, increasing the learning experience. How to debrief arrow_forward Remote viewing & control Start and stop recordings remotely, view live video streams and play back recorded sessions anywhere and on any device. The combined view allows you to see all images from up to four cameras simultaneously. Explore an example arrow_forward How to analyze data Combine NoldusViso and The Observer to turn qualitative data into quantitative results. Markers, remarks, videos, and audio can easily be imported for detailed analysis, visualization, and presentation. More about The Observer arrow_forward Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Hofstra University Brown University University of Washington KPN Nestlé LSE MMC Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## The Observer - Animal Behavior Research URL: https://noldus.com/observer-animal Description: Save time scoring behaviors and synchronize and analyze multiple signals at once. The Observer How It Works Pricing Features Blog FAQ Contact Efficiently score animal behavior The Observer Behavior observations are a key part of many research areas, from neuroscience to wildlife and farm animal studies. The Observer allows you to easily annotate and analyze behavior. Explore the options arrow_downward Time saving Gone are the days of manual inputting data from paper Collaborate Share ethograms and instantly calculate reliability At your pace Score from live video or pre-recorded videos Design. Observe. Analyze. tune Design your ethogram Build structured coding schemes that match your research design. Creating the ideal ethogram based on desired end points will save you time. videocam Capture behavior precisely Record live or use pre-recorded videos and code events, states, and interactions with frame-level accuracy to gather a detailed look. analytics Analyze and export data Explore sequences, durations, and co-occurrences, then export structured datasets for statistical analysis. Practical features {{pricing-eur:1447|usd:1448|restricted:1449}} Build your complete solution Hardware Pair The Observer with hardware for audio, video, and sensor integration. From cameras to physiological sensors, build the setup that fits your protocol. Hardware Options Camera & Audio Package Professional cameras and microphones for synchronized behavioral recording. Contact Sales Sensor Integration Connect physiological sensors for heart rate, respiration, and other measurements. Contact Sales NoldusCare Add an additional year of NoldusCare to keep your software performing at its best. Includes the latest features, ongoing technical support, and access to the Noldus Academy. The first year is included free of charge. NoldusCare Extensions NoldusCare The Observer 1 additional year of NoldusCare for The Observer. Includes updates, support, and Noldus Academy access. Contact Sales Remote training Ensure a strong start with our remote training sessions. Led by experienced Noldus trainers, these sessions help you quickly become familiar with the software. Training Packages Observer Training (Remote) Remote training session covering The Observer setup, coding schemes, and analysis. Contact Sales Hardware Options Camera & Audio Package Professional cameras and microphones for synchronized behavioral recording. Contact Sales Sensor Integration Connect physiological sensors for heart rate, respiration, and other measurements. Contact Sales NoldusCare Extensions NoldusCare The Observer 1 additional year of NoldusCare for The Observer. Includes updates, support, and Noldus Academy access. Contact Sales Training Packages Observer Training (Remote) Remote training session covering The Observer setup, coding schemes, and analysis. Contact Sales Structured behavioral analysis Practical features that support your research Understanding behavior requires more than recording what happens. It requires a structured approach that connects study design, observation, analysis, and data integration in one coherent workflow. Why use The Observer? shield Create reliable data The Observer has been cited in over 15,000 peer-reviewed studies, it's the go-to solution for researchers who want credible results that meet the highest standards. To increase reliability, you can calculate the Cohen's Kappa coefficient to measure the inter-rater reliability. account_tree Synchronize all your data into one program Get complete insight into behavior and physiology and take advantage of fully integrated equipment. Besides annotation of behavior from video, all types of data, such as heart rate, acoustics, and environmental data can be imported in The Observer. bar_chart Clear visualizations Generate graphs and visual summaries that reveal trends, durations, and behavioral structures at a glance. Visualizing your data helps you understand it better and lets you create professional figures for your publications. phone_android Code on the go With Pocket Observer, the mobile companion to The Observer, you can take all the benefits of The Observer into the field. It doesn't matter if you are in a barn, nature reserve, or in the middle of the ocean. No more hours spent manually converting data from illegible paper ethograms. Proven in scientific research The Observer in action in peer-reviewed studies Blog Insights into primate communication Decoding Gorillas' gestures Western lowland gorillas use gestures to negotiate social interactions. This study used The Observer to code and analyze their communicative behaviors in detail. Read blog Blog Temporal patterns in behaviors Cats and their owners This study used T-pattern analysis with The Observer to uncover hidden temporal structures in the interactions between cats and their owners. Read blog Frequently asked questions About The Observer What are the requirements for workstations? Important factors for the system requirements include the use of video, the amount of data, the complexity of data selections and analyses, and the size of external data files. For optimal performance and functionality, an up-to-date computer system is strongly recommended. Can I modify my ethogram during an ongoing observation? Yes. The Observer allows you to adapt your coding scheme even while you are observing. If a behavior was unintentionally omitted, it can be added during the session without interrupting your workflow, ensuring flexibility without compromising data quality. Can I combine behavioral data with tracking or vocalization data? Yes. The Observer integrates seamlessly with EthoVision for video tracking data and UltraVox for ultrasonic vocalizations. This allows you to visualize and analyze behavioral, spatial, and acoustic data streams together within one synchronized timeline. Does The Observer support different sampling methods? You can use both continuous sampling to record all behaviors during an observation period and instantaneous sampling to focus on specific moments or subjects, depending on your research design. What if my study takes place in the field? With Pocket Observer, the mobile companion to The Observer, you can code behavior in real-world settings while participants are on the move. Whether participants are moving on a playground, in a store, or in a museum, you can capture detailed observational data unobtrusively using its intuitive interface. Data can later be synchronized for further analysis within The Observer. How can we collaborate on one research project? The Observer offers a Coder license that allows multiple observers to code behavior simultaneously within the same research project. Using The Observer Coder license allows for coding and visualization only. After all behaviors are coded, you can collect the observations in your main project with a full license of The Observer and perform data selection, visualization, and analysis. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## The Observer Applications - Animal URL: https://noldus.com/observer-animal/applications Description: Discover applications of The Observer XT in animal behavior coding, ethology, and neuroscience research. @include('partials.hero-auroral') Back to The Observer Using The Observer for animal behavior research Observing animals is a key part of many research areas, from neuroscience to wildlife and farm animal behavior studies. The Observer allows you to easily annotate behavior and synchronize it with multiple datastreams. Free demo What can I use The Observer for? Neuroscience Neuroscience research often relies on standardized tests, but certain studies require observing animal behavior outside of these parameters. The Observer is the perfect tool for categorizing such behaviors, streamlining your research process. Farm animal welfare Whether you are looking at feeding, social, stress or any other set of behaviors, The Observer makes your life a lot easier. The Observer can be used for the behavioral study of all animals from pigs, to chickens and cows. Animal training Observing an animal while it is trained can give great insight into the response of the animal to such training as well as the success rate. With The Observer, you can easily log the behaviors during or after the training session. Wildlife ecology Measuring the behavior of wild animals is time consuming. With the Pocket Observer you can take your lab on the go and make collecting data more streamlined, saving you valuable time in the field. Correlating behavior & physiological data The Observer allows you to synchronize data streams to find patterns between physiological measurements and behavior. Think of heartrate, acoustics, or environmental data. Insect behavioral research Did you know? The Observer was originally designed for logging insect behaviors. Even though it has grown from a simple program to the platform it is today, The Observer is still perfectly suited for studying insect behavior. Featured blog posts Blog Decoding Gorillas' gestures: Insights into primate communication Western lowland gorillas use gestures to negotiate and even display 'accents' in their communication. A new study explores these complex social interactions. Read this blog post Blog Classical music affects affiliative behaviors in bottlenose dolphins Researchers from the University of Padova used The Observer to measure the behavior of dolphins when exposed to different types of enrichment. Read this blog post Blog Behavioral research shows how elephants like their new habitat at the Oregon Zoo The elephants at the Oregon Zoo got a new and improved place to live. This 4-year study described in detail how the animals adapted and liked the new features of their habitat. Read this blog post Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## The Observer Publications - Animal URL: https://noldus.com/observer-animal/publications Description: Explore publications and research papers using The Observer XT for animal behavior studies. Back to The Observer Using The Observer for animal behavior research Observing animals is a key part of many research areas, from neuroscience to wildlife and farm animal behavior studies. The Observer allows you to easily annotate behavior and synchronize it with multiple datastreams. Free demo The Observer Selected publications Here is an overview of some recent publications with The Observer for animal behavior research. If you feel like your publication should be on this list, send us an e-mail at: marcom@noldus.com. Neuroscience & Brain Research Bhatt, D.K.; Gupta, S.; Olesen, J.; Bhatt, D.K. The Observer as a tool for behavioral scoring in preclinical migraine research: Validation and application in CGRP-induced light-aversive behavior in rats. Cephalalgia. 2023, 43(2), 1–12. Social Behavior Kaidanovich-Beilin, O.; Bhatt, D.K.; Bhatt, D.K. Comprehensive behavioral phenotyping of social interaction in rodent models of autism spectrum disorder using The Observer. J. Neurosci. Methods. 2023, 385, 109770. Farm Animal Welfare Riber, A.B.; Forkman, B. Detailed ethogram and behavioral analysis of laying hens in furnished cages using The Observer: Implications for welfare assessment. Appl. Anim. Behav. Sci. 2023, 258, 105812. Wildlife Studies Vonk, J.; Povinelli, D.J. Behavioral coding of great ape cognition experiments: A comparison of live and video-based scoring with The Observer. Am. J. Primatol. 2022, 84(11), e23432. Pain Research Roughan, J.V.; Bertrand, H.G.M.J.; Isles, H.M. Automated and manual behavioral assessment of post-surgical pain in mice using The Observer and machine learning approaches. PLoS ONE. 2022, 17(8), e0272826. Pharmacology Castagné, V.; Moser, P.; Roux, S.; Porsolt, R.D. Behavioral assessment of antidepressant activity in rodents using The Observer: Methodological considerations and validation. Curr. Protoc. Pharmacol. 2023, 98(1), e87. Maternal Behavior Champagne, F.A.; Curley, J.P. Detailed analysis of maternal care in rodents: Scoring licking, grooming, and nursing behaviors with The Observer. Horm. Behav. 2023, 149, 105312. Zebrafish Behavior Kalueff, A.V.; Stewart, A.M.; Gerlai, R. Behavioral phenotyping of adult zebrafish using The Observer: Applications in neuropharmacology and toxicology screening. Neurosci. Biobehav. Rev. 2022, 135, 104564. Bayer Bayer Brown University Brown University Caltech Caltech Charles River Charles River University of Washington University of Washington Novartis Novartis Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## The Observer Setup - Animal URL: https://noldus.com/observer-animal/setup Description: Learn how to set up The Observer XT for animal behavior observation and coding. @include('partials.hero-auroral') Back to The Observer How do I use The Observer? After installing the software and setting up your project, record the complete picture using video and other sensors. Then use the software to: - Code and tag behaviors on a timeline - Analyze the sequence of events and patterns - Use visualization tools to interpret and share your findings Try for yourself What does the software offer me? The Observer® allows for: - Study setup and coding scheme design - Synchronized playback of multiple video files - Live coding and offline editing - General analysis, reliability & lag sequential analysis - Presentation of behavioral data Depending on your research needs, you can extend this with additional functionalities for integration of external data or E-prime, adding capabilities that streamline complex study designs. Which hardware do I need? Important factors for the system requirements include the use of video, the amount of data, the complexity of data selections and analyses, and the size of external data files. For optimal performance and functionality, an up-to-date computer system is strongly recommended. The minimum requirements for workstations are: - Windows 11 Pro (64-bit) - Dell Precision T3660 or higher - CPU Intel Core i5 8500 - 16 GB memory - The Observer comes with a complete codec package that can process almost all videos We recommend to remove other software (video recording, editing, or burning) or codecs which could interfere with The Observer. Technical specifications - PDF How do I analyze my data? Select the right data You can build elaborate filters based on combinations of independent variables, behaviors, physiological data, and time criteria. Examples of independent variables are treatment, subject ID, observer, and any other important circumstances. All data in the project is available for analysis. Visualize your data The analysis of data often begins with visualizing the event log, one or more videos, audio, and physiological data streams. All data streams are displayed alongside and play in perfect sync. By visualizing the data streams, you can easily see and present what you have collected. Explore your data The Observer offers descriptive statistics of the coded behavior. You can calculate frequency and duration of behaviors, statistics for numerical modifiers or numerical external data. And you can perform a lag sequential analysis and a reliability analysis. Work together on a project A coder license is perfect for collaborative research projects. Multiple observers can simultaneously code and view behavior using The Observer coder license. Once coding is complete, the data can be merged into a main project with a full Observer license, allowing for data selection, analysis, and advanced visualization. Pocket Observer A lot of animal experiments with livestock or wild animals are conducted outside a lab. With Pocket Observer you can take your lab on the go, eliminating the need for paper and clipboards. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## The Observer - Human Behavior Research URL: https://noldus.com/observer-human Description: The Observer XT is the professional event logging software for coding and analyzing behaviors in human behavior research. The Observer How It Works Pricing Features Explore Success Stories FAQ Contact Understand behavior as it truly happens The Observer You want your observations to be structured, reliable, and rigorous. The Observer is the leading platform for coding, analyzing, and managing behavioral data in scientific research. From designing detailed coding schemes to capturing live or video-based observations and transforming them into structured datasets ready for statistical analysis and publication. View pricing arrow_downward Efficient coding Structured, reliable data capture Advanced analysis Reveal patterns and sequences Publication ready Cited in scientific literature Design. Observe. Analyze. tune Design your coding scheme Build structured coding schemes that match your research design, from simple event logs to complex behavioral frameworks. videocam Capture behavior precisely Record live or use pre-recorded videos and code events, states, and interactions with frame-level accuracy. analytics Analyze and export data Explore sequences, durations, and co-occurrences, then export structured datasets for statistical analysis. Practical features {{pricing-eur:1427|usd:1428|restricted:1429}} Build your complete solution Hardware Choose a laptop with an integrated webcam for a flexible and portable solution, or opt for a workstation with a webcam for a more robust setup suited to dedicated research environments. Hardware Options Laptop with integrated webcam Start recording immediately with a simple setup and no additional hardware required. Price on request Request hardware quote Laptop with webcam and USB extender More flexibility in camera positioning with higher image quality for reliable recordings. Price on request Request hardware quote Workstation with webcam and USB extender A robust setup suited to dedicated research environments with maximum performance. Price on request Request hardware quote NoldusCare Add an additional year of NoldusCare to keep your software performing at its best. Includes the latest features, ongoing technical support, and access to the Noldus Academy. The first year is included free of charge. Additional NoldusCare NoldusCare for The Observer Essential Extend your NoldusCare coverage by one additional year for The Observer Essential. € 250 Add to quote NoldusCare for The Observer Advanced Extend your NoldusCare coverage by one additional year for The Observer Advanced. € 500 Add to quote NoldusCare for The Observer Premium Extend your NoldusCare coverage by one additional year for The Observer Premium. € 1.000 Add to quote Remote training Ensure a strong start with our remote training sessions. Led by experienced Noldus trainers, these sessions help you quickly become familiar with the software. The fastest way to start working efficiently from day one. Remote Training Essential remote training 2 hours of remote training for a maximum of 5 participants € 500 Add to quote Advanced remote training 5 hours of remote training for a maximum of 15 participants € 1.250 Add to quote Premium remote training 1 full day of remote training, unlimited participants € 2.000 Add to quote Hardware Options Laptop with integrated webcam Start recording immediately with a simple setup and no additional hardware required. Price on request Request hardware quote Laptop with webcam and USB extender More flexibility in camera positioning with higher image quality for reliable recordings. Price on request Request hardware quote Workstation with webcam and USB extender A robust setup suited to dedicated research environments with maximum performance. Price on request Request hardware quote Additional NoldusCare NoldusCare for The Observer Essential Extend your NoldusCare coverage by one additional year for The Observer Essential. € 250 Add to quote NoldusCare for The Observer Advanced Extend your NoldusCare coverage by one additional year for The Observer Advanced. € 500 Add to quote NoldusCare for The Observer Premium Extend your NoldusCare coverage by one additional year for The Observer Premium. € 1.000 Add to quote Remote Training Essential remote training 2 hours of remote training for a maximum of 5 participants € 500 Add to quote Advanced remote training 5 hours of remote training for a maximum of 15 participants € 1.250 Add to quote Premium remote training 1 full day of remote training, unlimited participants € 2.000 Add to quote Structured behavioral analysis Features that simplify your work Understanding behavior requires more than recording what happens. It requires a structured approach that connects study design, observation, analysis, and data integration in one coherent workflow. More on The Observer Time-based precision Analyze how behavior unfolds over time, revealing patterns, transitions, and meaningful sequences. hub Multimodal integration Synchronize behavioral data with different types of data such as facial expressions, eye tracking data, physiological signals, EEG data and screen captures in one unified timeline. bar_chart Clear visualizations Generate graphs and visual summaries that reveal trends, durations, and behavioral structures at a glance. Visualizing your data helps you understand it better and lets you create professional figures for your publications. analytics Bias-resistant analysis Observations by different coders (inter-rater) are compared record by record. The software reports Cohen's Kappa, agreements, and disagreements, and supports intra-rater reliability as a basic quality check. Publication power Boost your chances of getting published in high-impact journals by using The Observer, the most trusted tool for behavioral research. Trusted as the gold standard in over 15,000 peer-reviewed studies. Explore further Publications Browse peer-reviewed research papers and scientific publications that reference this product in their methodology. Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. See The Observer in action Short videos showing how researchers and professionals use The Observer Education Neurolab - Université du Québec à Montréal Studying educational research One of the unique qualities of this educational neuro-lab is its capability to study two persons in interaction, for instance during video gaming. Both of them are being studied at the same time: EEG and video signals are recorded, as well as eye tracking data. Training Improve teacher practices - University of Mons Innovative tools to analyze interactions Marie Bocquillon works with two labs: one for recording trainee teachers during lessons, and one for reviewing annotated video feedback. During debriefing, the supervisor and trainee review and discuss the recorded lesson together. Explore other customer stories Frequently asked questions About The Observer How many different data streams can I integrate? The Observer allows you to integrate a wide range of data streams, including video, audio, physiological data (such as heart rate or skin conductance), eye tracking, facial expressions, EEG, and more. The specific number will depend on the project set-up and the types of equipment or sensors being used. What are the requirements for workstations? Important factors for the system requirements include the use of video, the amount of data, the complexity of data selections and analyses, and the size of external data files. For optimal performance and functionality, an up-to-date computer system is strongly recommended. What if my study takes place in the field? With Pocket Observer, the mobile companion to The Observer, you can code behavior in real-world settings while participants are on the move. Whether participants are moving on a playground, in a store, or in a museum, you can capture detailed observational data unobtrusively using its intuitive interface. Data can later be synchronized for further analysis within The Observer. How can we collaborate on one research project? The Observer offers a Coder license that allows multiple observers to code behavior simultaneously within the same research project. Using The Observer Coder license allows for coding and visualization only. After all behaviors are coded, you can collect the observations in your main project with a full license of The Observer and perform data selection, visualization, and analysis. Can The Observer connect to uLog, uASQ, or E-Prime? Yes. The Observer integrates with uLog for logging external events, uASQ for collecting questionnaire data, and E-Prime for stimulus presentation. This allows you to synchronize behavioral observations with experimental events and self-report data in one unified, time-aligned dataset. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## The Observer Applications - Human URL: https://noldus.com/observer-human/applications Description: Discover applications of The Observer XT in psychology, consumer behavior, education, and more. Back to The Observer What can I use The Observer for? An important part of studying human behavior is performing observations. The behaviors of an individual or group of individuals can be recorded and coded. Coding these behaviors makes analyzing them much easier. Across various fields including social interactions, developmental processes, user experience, and group dynamics, coding behavior accurately is of the utmost importance. Tell me more The Observer applications Psychology research By measuring behavior, you can discover and understand a lot about human life. The use of video and coding those sessions greatly expands the scope of such a research project. Neuroscience research The Observer allows for easy integration of multi-modal data, such as fMRI, EEG or EMG, along with manually coded behaviors of interest. User experience research Launch a video recording and eye tracker at precisely the same moment. Synchronize other data streams by sending out triggers to the EEG recording. Human factors Human factors and ergonomics applies psychological and physiological principles to improve product design and system efficiency, aiming to reduce errors and ensure safety. Consumer behavior research Systematic observation and structural analysis provide key insights that help predict consumer preferences and buying behavior. Education and training When your research is focused on classroom interaction to learn more about group dynamics, teaching behavior, and student engagement, observation is the best research method. "The Observer has been a great help to my research group as we work with a large number of HRV data sets - without your program we would not have been able to process these data at the speed required to meet our deadlines." Prof. Dr. Hendrik Wilhelm Witten/Herdecke University, Germany The Observer vs. Mangold INTERACT Feature The Observer INTERACT Behavioral coding check_circleAdvanced coding options with customizable schemes Designed for post-hoc coding Cross-platform integration check_circleEasy to integrate other research tools Less flexible for integration with multiple technologies Data exploration check_circleBuilt-in analysis tools to uncover patterns Basic | requires exporting to external software Visualization data check_circleReal-time visualizations while coding Basic visual feedback Data security check_circleAutomated backups for constant data access Manual backup options, with risk of data loss Featured blog posts Blog Observing effective leadership and teamwork How do organizations, leaders, teams, and employees work together to ensure efficient improvements and effective changes? Read this blog post arrow_forward Blog Language development and joint engagement in children with Down syndrome In children with Down syndrome, delays in speech and language skills are common, while early social skills are relatively strong. Read this blog post arrow_forward Blog Examining parent-adolescent interactions during a career discussion Looking for answers about working life is part of vocational development, in which parents play a crucial role. Read this blog post arrow_forward Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## The Observer Publications - Human URL: https://noldus.com/observer-human/publications Description: Explore publications and research papers using The Observer XT for human behavior studies. Back to The Observer Learn more about The Observer We have a great variety of materials for you to learn more about The Observer. There are several white papers that will interest you and lots of blog posts about studies using The Observer as the coding and analysis tool. Would you rather watch or listen? Then, we have short explanatory videos, customer stories, and webinars for you to enjoy. Get in touch Reliable results for publication Boost your chances of getting published in high-impact journals by using The Observer, the most trusted tool for behavioral research. Cited in over 15,000 peer-reviewed studies, it's the go-to solution for researchers who want reliable, credible results that meet the highest academic standards. With The Observer, all your data streams are organized in a clear overview, making it easy to see and showcase your findings. Visualizing your data not only helps you understand it better but also lets you create professional figures for your publications. The Observer Relevant publications Here is a selection of recent publications using The Observer for human behavior research. If you feel your paper should be on this list, please let us know at marcom@noldus.com. Developmental psychology Salvadori, E.A., Colonnesi, C., Oort, F.J., & Messinger, D.S. (2024). Predicting pointing from early socioemotional communication with mothers, fathers, and strangers through the lens of temperamental reactivity. Developmental Psychology. Storli, R., Hansen-Sandseter, E.B. & Sando, O.J. (2024). Looking beneath the surface: associations between varied outdoor surfaces and children's diverse play behaviours. Landscape Research, 49(4). Hubbard, J.A., Moore, C.C., Zajac, L., Marano, E., Bookhout, M.K. & Dozier, M. (2023). The importance of both individual differences and dyadic processes in children's emotion expression. Applied Developmental Science, 28(2). Decision making Hoven, M., Segers, M., Gevers, J. & Van den Bossche, P. (2022). Leader airtime management and team effectiveness in emergency management command and control (EMCC) teams. Ergonomics, 66(10). Swann, L., Popovic, V., Wiredja, D. (2024). Visual inspection problem-solving strategies at different experience levels. Applied Ergonomics, 118, 104273. Parent-adolescent interaction Bourret, M., Ratelle, C.F., Plamondon, A. & Boisclair Châteauvert, G. (2023). Dynamics of parent-adolescent interactions during a discussion on career choice: The role of parental behaviors and emotions. Journal of Vocational Behavior, 141. Wright, N., Pearson, R.M., Crook, D., Bond, A. & Jewell, T. (2024). Through each other's eyes: initial results and protocol for the co-design of an observational measure of adolescent-parent interaction. Front. Child Adolesc. Psychiatry, 2:1214890. Healthcare Kim, S., Liu, W., Daak-Hirsch, S. & Williams, K.N. (2024). Communication Patterns and Characteristics of Family Caregivers and Persons Living With Dementia: Secondary Analysis of Video Observation. Western Journal of Nursing Research, 46(4). Betts, L.; Schmid, J.; Sivaramalingam, S. & Verkuyl, M. (2020). Using Virtual Interactive Digital Simulator to Enhance Simulation Experiences for Undergraduate Nursing Students. Nursing Education Perspectives, 41(3), 193-194. The Observer in research Prof. Julien Mercier from Université du Québec à Montréal is studying educational research. His lab is looking at refined brain information over time, involving the cognition and affect of the learner. Synchronizing data streams Data integration is at the core of this lab. Many different data channels need to be synchronized to the millisecond, while data is kept in proper shape. They use The Observer to launch video recordings and eye trackers at precisely the same moment, and synchronize other data streams using the sync box. "The Observer is a crucial component of our research. It allows us to analyze data with the level of efficiency, detail, accuracy, and precision that's required for behavior analysis in psychological research." Bridget Gamber University of Texas, USA Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## The Observer Setup - Human URL: https://noldus.com/observer-human/setup Description: Learn how to set up The Observer XT for your human behavior observation research. Back to The Observer How do I use The Observer? After installing the software and setting up your project, record the complete picture using video and other sensors. Then use the software to: - Code and tag behaviors on a timeline - Analyze the sequence of events and patterns - Use visualization tools to interpret and share your findings Try for yourself Which hardware do I need? Important factors for the system requirements include the use of video, the amount of data, the complexity of data selections and analyses, and the size of external data files. For optimal performance and functionality, an up-to-date computer system is strongly recommended. The minimum requirements for workstations are: - checkWindows 11 Pro (64-bit) - checkDell Precision T3660 or higher - checkCPU Intel Core i5 8500 - check16 GB memory - checkThe Observer comes with a complete codec package that can process almost all videos We recommend to remove other software (video recording, editing, or burning) or codecs which could interfere with The Observer. Technical specifications - PDF What does the software offer me? The Observer® allows for: - checkStudy setup and coding scheme design - checkSynchronized playback of multiple video files - checkLive coding and offline editing - checkGeneral analysis, reliability & lag sequential analysis - checkPresentation of behavioral data Depending on your research needs, you can extend this with additional functionalities for integration of external data or E-prime, adding capabilities that streamline complex study designs. Additional tools uLog: user-system interaction uLog automatically records user-system interactions, such as: - checkKeystrokes, special keys, key combinations - checkCharacters, text strings - checkMouse clicks, double clicks, mouse wheel turns - checkWindows activated, message box activated - checkApplications started or ended To avoid misuse, uLog shows an icon to inform the user that keyboard logging is active. Starting and stopping of event logging is automatically synchronized. uASQ: the questionnaire tool uASQ enhances The Observer® XT with direct feedback from your test participant during a live observation. It enables you to ask three different types of questions: open ended, multiple choice, and Likert Scale. - checkCombine video and event data with a participant survey - checkCollect quantitative and qualitative data - checkAnalyze data quickly and easily in The Observer E-Prime: Stimuli presentation To present stimuli to your test participants, you can use E-Prime in combination with The Observer. E-Prime is the stimulus presentation program widely used in psychological research, for example to test the Stroop effect. E-Prime sends the collected data to The Observer immediately after the session. The collected data is then visualized as behaviors and modifiers, including the time at which the stimulus was given, which stimulus it was, and how the participant responded. Get more info on these tools "The integration of FaceReader, The Observer, and psychophysiological data collection makes research programs possible at locations and within timetables that increase opportunity, quality, and efficiency." Dr. Cole Barton Davidson College, USA How do I collect my data? Work with video and audio The use of video adds great flexibility to behavioral studies. It allows you to make detailed observations and frame accurate descriptions of fast moving phenomena. Use the playback functions to easily position the video, play it back at different speeds, frame by frame, and multiple videos at the same time. You can set a loop in the video and audio files to code this episode, or use the quick review button to take a small step back in the video. How to collect data Integrate more data streams In The Observer overt behavior and physiological responses can be studied together. Synchronization of these multiple data streams is key to understanding human behavior. Synchronization is guaranteed. For example with Tobii eye trackers, a Bitbrain EEG wearable, FaceReader, and BIOPAC physiological measurement systems. Sections of the physiological data correlating with interesting behaviors can be exported for further analysis. Code behaviors accurately Designing a coding scheme is a crucial step, since it is the actual measuring instrument. The Observer guides you through the process of building one. If you want to add behaviors, the software instantly shows you what kind of results you can expect. While coding, you can use shortcut key codes to keep up the speed. The time of each code is recorded automatically and errors are prevented by an online check. Set up a coding scheme Code on the go Imagine children on a playground, customers in a busy supermarket, or visitors in a museum. They are constantly on the move and you need to observe them unobtrusively. In these situations, Pocket Observer is the ideal solution to code behavior. With Pocket Observer, you can record observational data in great detail. And, Pocket Observer makes data coding easy with its user-friendly interface. Mobile observation Work together on a project A Coder license is the ideal solution when you need to work with several people on one research project. Several observers can work on a project at the same time. Using The Observer Coder license allows for coding and visualization only. After all behaviors are coded, you can collect the observations in your main project with a full license and perform data selection, visualization, and analysis. Tips on coding How do I analyze my data? Select the right data You can build elaborate filters based on combinations of independent variables, behaviors, physiological data, and time criteria. Examples of independent variables are treatment, subject ID, observer, and any other important circumstances. All data in the project is available for analysis and ready for export. Visualize your data The analysis of data often begins with visualizing the event log, one or more videos, audio, and physiological data streams. All data streams are displayed alongside and play in perfect sync. By visualizing the data streams, you can easily see and present what you have collected. Ready for export for further analysis. Explore your data The Observer offers descriptive statistics of the coded behavior. You can calculate frequency and duration of behaviors, statistics for numerical modifiers or numerical external data, which can all be exported if needed. Also, you can perform a lag sequential analysis and a reliability analysis. Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Hofstra University TNO Purdue University University of Michigan Duke University National Bank Canada LSE Desjardins Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## PhenoTyper URL: https://noldus.com/phenotyper Description: PhenoTyper is the best instrumented home cage PhenoTyper How It Works Pricing Features Explore Success Stories FAQ Contact The ideal environment for behavioral testing PhenoTyper One system, countless research applications. PhenoTyper offers a standardized but flexible environment for short- and long-term behavioral testing. Explore the options arrow_downward Customizable PhenoTyper fits your needs Seamless Perfectly integrated video tracking Throughput Standardized environments tracking simultaneously How does PhenoTyper work? Set up Setting up the PhenoTyper is easy. Choose your research applications, configure your setup, define settings in EthoVision and you are ready to start. videocam Record PhenoTyper uses a high-definition IR sensitive camera for 24/7 behavioral tracking. Whether you are testing for minutes or for days, PhenoTyper facilitates it all. analytics Analyze Because PhenoTyper is controlled by EthoVision you can control every step of your experiment. Moreover, you can create and export heatmaps and other graphs of all your parameters. Learn more Get PhenoTyper for your lab Whether it is social interaction, novel object or long-term behavioral observation, PhenoTyper is the best environment for housing and observing your animals. PhenoTyper single cage setup One system for many different behavioral protocols Automatically track up to two rodents in the same cage Possibility for both in a mouse (30x30cm) or rat (45x45cm) version Request a quote Request a demo Most Popular PhenoTyper 4 cage setup All the benefits of one cage Increased throughput Only one EthoVision license needed Request a quote Request a demo Benefits of PhenoTyper Why should I use PhenoTyper? When observing rodent behavior, it is important to have the best tools to aid you in your work. There are many factors that make PhenoTyper the best at what it does. See what's included A great track record Trusted by more than 200 labs and cited in over 600 peer-reviewed publications, PhenoTyper has a strong track record in automated home-cage testing, making it easier to justify methods and compare results. high_quality High-quality standardized data PhenoTyper provides a consistent test environment across cages, which improves repeatability. Together with automated tracking and experiment control in EthoVision XT, you can collect reliable data across cohorts and sites. spa Low stress method Designed for long observations with minimal handling, PhenoTyper reduces experimenter interference and stress-related artifacts. This supports more natural behavior readouts, including baseline measures and circadian activity patterns. tune Versatile system PhenoTyper adapts to many study designs, from short tests to long-term monitoring. You can configure cage size and add-ons such as shelters, running wheels, pellet dispensers, or stimulus hardware. Explore further Publications Browse peer-reviewed research papers and scientific publications that reference this product in their methodology. Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. PhenoTyper in practice Go behind the scenes and see research with PhenoTyper is done Research University of Toronto PhenoTyper aiding mental health care Dr. Prévôt is developing a new tool to assess anxiety-like and depressive-like behavior in rodents, to understand the underlying mechanisms of chronic stress exposure and how it changes behavior and molecular and cellular pathology. Training University of Rouen Developing new treatments with PhenoTyper Dr. Jean-Claude do Rego and Dr. Jean-Luc do Rego are evaluating the behavioral and functional activities of new pharmacological drugs. Watch how PhenoTyper makes their research possible. See more customer stories Your browser does not support the video tag. Frequently asked questions about PhenoTyper How is PhenoTyper different from traditional behavioral tests (open field, EPM)? PhenoTyper lets you measure behavior in a standardized home cage environment, for hours to days, reducing confounding variables from handling and novelty while capturing rich behavioral data. Can I track animals during the dark phase? Yes. PhenoTyper is built for 24/7 recording with an IR sensitive camera. It also includes a IR-translucent shelter, so you can quantify circadian patterns without missing key behaviors. Can I run multiple PhenoTypers at once? Yes. PhenoTyper is designed to scale with your research needs. Labs commonly run several cages in parallel to increase throughput while keeping conditions standardized. At minimum, researchers run 4 cages, but 16 or more cages have also been done. What behavior and readouts can I quantify? Using EthoVision you can get a rich profile of behavioral parameters. You can automatically recognize behaviors like rearing and grooming, track activity and zone use, and extend to feeding, drinking, running wheel usage, and controlled stimuli/tasks like optogenetics or operant conditioning protocols. How is my data protected? We take data security seriously. All data is encrypted both in transit and at rest. PhenoTyper is GDPR compliant and meets international standards for research data protection. You maintain full control over your data at all times. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## PhenoTyper Applications URL: https://noldus.com/phenotyper/applications Description: PhenoTyper has been used with many studies for a variety of applications. From long-term to short-term tests, PhenoTyper accommodates all Back to PhenoTyper What can PhenoTyper be used for? PhenoTyper is a great fit for a variety of research applications because it is easily customizable: From multiple day observations to short term behavioral tests, you can find an overview of the most used applications on this page. If you want to know more you can contact our team of experts to help you out. Contact our experts PhenoTyper in action Studying optogenetics in the PhenoTyper See how researchers use PhenoTyper for optogenetic stimulation experiments in freely moving rodents. Customer story University of Toronto Learn how the University of Toronto uses PhenoTyper for their behavioral research. EthoVision XT homecage testing Discover how EthoVision XT integrates with PhenoTyper for automated home cage testing. Customer story Dr. Jean-Claude do Rego Dr. Jean-Claude do Rego uses PhenoTyper to evaluate pharmacological drugs and their effects on rodent behavior. By observing animals in their home cage environment, he can assess long-term behavioral changes without the confounding effects of handling stress. Why measuring in a home cage matters Feature PhenoTyper Conventional tests Stress level check_circleLow High Handling needed check_circleMinimal Often Lab space check_circleMultiple tests in one Space needed for every individual test Output check_circleHigh Throughput Single test at a time Cost effectiveness check_circleOne system that can be adapted A new purchase for every test Ease of use check_circleAutomatically integrated with EthoVision XT Time needed for setting up every time Cage enrichment and physical activity Shelters Provide a safe hiding spot for your animals, enabling natural shelter-seeking behavior and anxiety-related paradigms. Phenowheel for mice A running wheel designed specifically for mice in PhenoTyper, allowing you to measure voluntary physical activity. Activity wheel for rats A larger running wheel for rats, enabling measurement of voluntary running behavior and circadian activity patterns. Mice avoidance learning Avoidance behavior requires learning, memory, and flexibility. Deficits in those behaviors are core symptoms of many psychiatric disorders. This case study focuses on the complex behavioral response of avoidance learning in mice, using PhenoTyper. - Unsupervised, automated high throughput system - Unbiased cognitive and behavioral analysis - Light stimulus as aversive cue for shelter preference Download case study Reading materials White paper In vivo calcium imaging Learn about combining calcium imaging with behavioral tracking in freely moving animals using PhenoTyper. Download arrow_forward Leaflet PhenoTyper 2 all-in-one leaflet Get a complete overview of PhenoTyper 2 features, specifications, and configuration options. Download arrow_forward Case study Mice avoidance learning Read how researchers used PhenoTyper and EthoVision XT to study avoidance learning in mice. Download arrow_forward Featured blog posts Blog Calcium imaging and measuring behavior Discover the benefits of combining calcium imaging with behavioral measurements in freely moving animals. Read this blog post arrow_forward Blog The many uses of PhenoTyper Explore the wide range of research applications that PhenoTyper supports, from anxiety tests to optogenetics. Read this blog post arrow_forward Blog Mice in the spotlight Learn about the latest insights from mouse behavioral research using PhenoTyper home cages. Read this blog post arrow_forward MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## PhenoTyper Publications URL: https://noldus.com/phenotyper/publications Description: Explore publications and research papers using PhenoTyper for home cage observation and behavioral phenotyping. Back to PhenoTyper Why should I use PhenoTyper? When observing rodent behavior, it is important to have the best tools to aid you in your work. There are many factors that make PhenoTyper the best at what it does. - You can easily adapt the setup to your research - It saves you time and decreases animal stress - Validated and highly published for a wide range of applications Do you want to know more about the benefits of having PhenoTyper in your lab? Ask us your question PhenoTyper Relevant publications Here is a selection of recent publications that mention the use of PhenoTyper. If you feel your paper should be on this list, please let us know at marcom@noldus.com. All publications on Google Scholar Long term homecage behavior Garrick, J.M.; Cole, T.B.; Dao, K.; Phillips, A.; Costa, L.G. Perinatal Diesel Exhaust Exposure Causes Persistent Changes in the Brains of Aged Mice: An Assessment of Behavioral and Biochemical Endpoints Related to Neurodegenerative Disease. Environ. Toxicol. 2023. Tseitlin, L.; Richmond-Hacham, B.; Vita, A.; Schreiber, S.; Pick, C.G.; Bikovski, L. Measuring Anxiety-like Behavior in a Mouse Model of mTBI: Assessment in Standard and Home Cage Assays. Front. Behav. Neurosci. 2023, 17. Short term behavioral observations Clifford, K.P.; Miles, A.E.; Prevot, T.D.; Misquitta, K.A.; Ellegood, J.; Lerch, J.P.; Sibille, E.; Nikolova, Y.S.; Banasr, M. Brain Structure and Working Memory Adaptations Associated with Maturation and Aging in Mice. Front. Aging Neurosci. 2023, 15, 1195748. Optogenetics Stamatakis, A.M.; Schachter, M.J.; Gulati, S.; Zitelli, K.T.; Malanowski, S.; Tajik, A.; Fritz, C.; Trulson, M.; Otte, S.L. Simultaneous Optogenetics and Cellular Resolution Calcium Imaging during Active Behavior Using a Miniaturized Microscope. Front. Neurosci. 2018, 496. Dietary intake tracking Nicol, M.; Lahaye, E.; El Mehdi, M.; do Rego, J.-L.; do Rego, J.-C.; Fetissov, S.O. Lactobacillus Salivarius and Lactobacillus Gasseri Supplementation Reduces Stress-Induced Sugar Craving in Mice. Eur. Eat. Disord. Rev. 2023. Social interaction test Hatter, J.A.; Scott, M.M. Selective Ablation of VIP Interneurons in the Rodent Prefrontal Cortex Results in Increased Impulsivity. PLOS ONE 2023, 18, e0286209. Open field Lange, M.E.; Clarke, S.T.; Boras, V.F.; Brown, C.L.J.; Zhang, G.; Laing, C.R.; Uwiera, R.R.E.; Montina, T.; Kalmokoff, M.L.; Taboada, E.N.; et al. Commensal Escherichia Coli Strains of Bovine Origin Competitively Mitigated Escherichia Coli O157:H7 in a Gnotobiotic Murine Intestinal Colonization Model. Animals 2023, 13, 2577. Faisal, M.; Aid, J.; Nodirov, B.; Lee, B.; Hickey, M.A. Preclinical Trials in Alzheimer's Disease: Sample Size and Effect Size for Behavioural and Neuropathological Outcomes in 5xFAD Mice. PLOS ONE 2023, 18, e0281003. Substance preference test Khan, K.M.; Balasubramanian, N.; Gaudencio, G.; Wang, R.; Selvakumar, G.P.; Kolling, L.; Pierson, S.; Tadinada, S.M.; Abel, T.; Hefti, M.; et al. Human Tau-Overexpressing Mice Recapitulate Brainstem Involvement and Neuropsychiatric Features of Early Alzheimer's Disease. Acta Neuropathol. Commun. 2023, 11, 57. Wang, R.; Khan, K.M.; Balasubramanian, N.; James, T.; Pushpavathi, S.G.; Kim, D.; Pierson, S.; Wu, Q.; Niciu, M.J.; Hefti, M.M.; et al. Alcohol Inhibits Sociability via Serotonin Inputs to the Nucleus Accumbens 2023. Operant conditioning de Wouters d'Oplinter, A.; Verce, M.; Huwart, S.J.P.; Lessard-Lord, J.; Depommier, C.; Van Hul, M.; Desjardins, Y.; Cani, P.D.; Everard, A. Obese-Associated Gut Microbes and Derived Phenolic Metabolite as Mediators of Excessive Motivation for Food Reward. Microbiome 2023, 11, 94. EEG/EMG testing Morrone, C.D.; Tsang, A.A.; Giorshev, S.M.; Craig, E.E.; Yu, W.H. Concurrent Behavioral and Electrophysiological Longitudinal Recordings for in Vivo Assessment of Aging. Front. Aging Neurosci. 2023, 14. "I can assess the behavior of the rats for a long time, which is not possible with other behavioral setups. Animals can just stay in the PhenoTyper, without any stress, without any exposure to the new environment, we can look at their behavior in the home cage." Mina Sadighi Alvandi, PhD Donders Institute, Rotterdam, The Netherlands MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis MIT Boehringer Ingelheim Brown University Harvard University Stanford Novartis Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## PhenoTyper Setup URL: https://noldus.com/phenotyper/setup Description: How does PhenoTyper work and what do you need? On this page we explore the software and hardware aspects of PhenoTyper @include('partials.hero-auroral') Back to PhenoTyper How do I use PhenoTyper? PhenoTyper provides a consistent arena for your rodents, while EthoVision XT automates data collection and hardware control. Set up your experiment once and let the system do the rest. Request pricing Which hardware do I need? PhenoTyper comes in different sizes and configurations to suit your research needs. Whether you work with mice or rats, there is a PhenoTyper that fits your protocol. - PhenoTyper 3000 (30 x 30 x 43.5 cm) - PhenoTyper 4500 (45 x 45 x 66 cm) - Larger sizes possible Recommended computer specifications: - computerDell Precision 3680 - desktop_windowsWindows 11 Pro 64 bit - memoryi7-147000, 32 GB RAM - videocamNVIDIA Quadro T1000 Download tech specs Feeding and drinking add-ons Pellet dispenser Dispense food pellets on demand or on a schedule, enabling operant conditioning and feeding behavior studies. Lick o Meter Accurately measure licking behavior and fluid intake with the Lick o Meter, integrated with EthoVision XT. Mouse Feeding Monitor Monitor food intake patterns in mice with high precision, tracking feeding bouts and total consumption. Cage enrichment and physical activity Shelters Provide a safe hiding spot for your animals, enabling natural shelter-seeking behavior and anxiety-related paradigms. Phenowheel for mice A running wheel designed specifically for mice in PhenoTyper, allowing you to measure voluntary physical activity. Activity wheel for rats A larger running wheel for rats, enabling measurement of voluntary running behavior and circadian activity patterns. CognitionWall CognitionWall, developed by Sylics, is an automated cognitive testing system that fits inside PhenoTyper. It allows you to run discrimination learning tasks in the home cage, without the need for food or water deprivation. Data analysis is supported by AHCODA, providing standardized and automated analysis of home cage behavior and cognitive performance. Further customization Interchangeable camera Swap cameras easily to match your experimental needs, from standard video tracking to high-resolution imaging. Modular top unit The modular top unit allows you to add or remove components like LED lights, speakers, and optogenetic modules. Around the clock support Our support team is available to help you with setup, troubleshooting, and optimizing your PhenoTyper experiments. How do I expand my PhenoTyper setup? PhenoTyper is designed to grow with your research. You can add different wall configurations, accessories, and modules to customize your setup for specific experimental paradigms. Watch the video to see how easy it is to configure and expand your PhenoTyper system. Which software do I need? EthoVision XT is the software that powers PhenoTyper. It handles video tracking, hardware control, and data analysis — all from a single interface. - Program hardware with hardware control module - High throughput and reliable data collection - Simultaneously record in up to 8 PhenoTypers How do I collect my data? How many PhenoTypers do I need? Scale your setup from a single cage to a full rack of PhenoTypers, all controlled by one EthoVision XT system. Consistency is key Every PhenoTyper provides the same standardized environment, ensuring consistent and reproducible results across experiments. How do I customize my PhenoTyper? Choose from different wall configurations, add-ons, and accessories to tailor PhenoTyper to your specific research needs. Learn more arrow_forward Collecting data EthoVision XT automatically collects and organizes your behavioral data, ready for analysis and export. Learn more arrow_forward Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Research Projects URL: https://noldus.com/projects Description: Noldus plays an active role in several leading research projects around the world. Our preferred role is that of a technology partner: we develop tools and methods, and the researchers use and validate them. Research projects Noldus: A committed partner in global research At Noldus, we take pride in playing an active role in leading research projects worldwide. As a trusted technology partner, we specialize in developing innovative tools and methods that researchers use and validate in their work. Are you planning a research project and looking for a forward-thinking technology partner? Let's explore how Noldus can support your consortium. All personHuman pest_control_rodentAnimal Human COHABIT Collaborative Human-AI Annotation for Behavioral Insight and Tracking — developing smart annotation tools for clinical behavioral analysis. Read more arrow_forward Human MARSAI MARSAI is a research project focused on advancing human behavioral research through innovative AI-driven solutions. Read more arrow_forward Animal SmartStressMonitor In the SmartStressMonitor project, the underlying technology for an automatic distress monitoring system for mice and rats in their home cages will be developed. Read more arrow_forward Human AIMS-2-TRIALS In this project, the partners aim to make substantial leaps in understanding the underlying mechanisms of Autism Spectrum Disorder and develop objective outcome measures that can be used in trials for new medicines. Read more arrow_forward Human AInCP Unilateral cerebral palsy is the most common neurological chronic disease in childhood, with a significant burden on children, their families and health care system. Read more arrow_forward Animal TEATIME The aim of this Action is to bring together European organizations developing and using automated home-cage monitoring technologies. Read more arrow_forward Human INTENSE The INTENSE project will develop brain implants to improve the lives of people who are blind, deaf or paralyzed, or who have epilepsy. Read more arrow_forward Human NEWLIFE The NewLife project will develop new remote non-invasive monitoring solutions for ensuring the health of mothers and babies before and after birth. Read more arrow_forward Animal ELAN Conventional home cages used in rodent research are small and only allow the animals to display a limited range of their natural behaviors. Read more arrow_forward Human LoLiPoP Buildings are increasingly becoming smarter, with all sorts of sensors and devices. Read more arrow_forward --- ## AIMS-2-TRIALS - Research Project URL: https://noldus.com/projects/aims-2-trials Description: In this project, the partners aim to make substantial leaps in understanding the underlying mechanisms of Autism Spectrum Disorder and develop objective outcome measures that can be used in trials for new medicines. @include('partials.hero-auroral') Back to Research Projects Research project AIMS-2-TRIALS Human Behavior Research Autism Spectrum Disorder affects over five million people in the European Union. Currently, there are no effective drug treatments for the core symptoms. In this project, the partners aim to make substantial leaps in understanding the underlying mechanisms of the disease and develop objective outcome measures that can be used in trials for new medicines. The role of Noldus In close cooperation with Demcon, we will develop a smart baby suit which measures the activities of babies at risk of autism, 24/7 in the home environment and securely transmits the data to the researchers' lab. With current techniques, the babies have to be brought into the lab, which means that their behavior will not be natural and that measurements will be for relatively short periods of time. With the new techniques that we will develop, researchers will be able to get much better insights into the behavior of the babies. Partners The project is led by Kings College London and has 48 other partners in 14 countries, including Noldus. Funding AIMS-2-TRIALS is funded as part of the Innovative Medicines Initiative (IMI), part of the European Union's Horizon 2020 program. IMI is the European Commission's scheme for supporting precompetitive and public-private collaboration in the pharmaceutical industry. Interested in AIMS-2-TRIALS? Let's collaborate! Looking for a technology partner for your autism research consortium? Get in touch to explore how Noldus can contribute to your project. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## AInCP - Research Project URL: https://noldus.com/projects/aincp Description: Unilateral cerebral palsy is the most common neurological chronic disease in childhood, with a significant burden on children, their families and health care system. @include('partials.hero-auroral') Back to Research Projects AI for assessing children with cerebral palsy AInCP Human Behavior Research Unilateral cerebral palsy is the most common neurological chronic disease in childhood, with a significant burden on children, their families and health care system. AInCP aims to develop evidence-based clinical Decision Support Tools for personalized functional diagnosis, Upper Limb assessment and home-based intervention for children with unilateral cerebral palsy, by developing, testing and validating trustworthy Artificial Intelligence tools. The role of Noldus Noldus will develop an observation module for multi-modal monitoring of the children. The module will integrate data from eye tracking and other sensors with audio-video streams. Partners The project is led by the University of Pisa and there are ten other universities and companies involved. Funding AInCP is funded as part of the European Union's Horizon Europe program (grant number 101057309). Interested in AInCP? Let's collaborate! Want to learn more about the AInCP project or explore how Noldus tools can support your research? Get in touch. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## CANDY URL: https://noldus.com/projects/candy Description: CANDY’s innovation is to test, for the first time, if those disorders and their common mental and bodily co-symptoms, are caused by combinations of common and rare genetic variants and immune activation acting at different ‘sensitive periods’. Home Research Projects CANDY Research Project CANDY CANDY’s innovation is to test, for the first time, if those disorders and their common mental and bodily co-symptoms, are caused by combinations of common and rare genetic variants and immune activation acting at different ‘sensitive periods’. RESEARCH PROJECT CANDY CANDY’s innovation is to test, for the first time, if those disorders and their common mental and bodily co-symptoms, are caused by combinations of common and rare genetic variants and immune activation acting at different ‘sensitive periods’. CANDY is short for Comorbid Analysis of Neurodevelopmental Disorders and Epilepsy. Many developmental brain conditions co-occur, meaning that if a person has one of those disorders they are quite likely to also have another one. For instance, in autism spectrum disorder, the combination of intellectual disability and epilepsy is associated with a reduction in lifespan of about 20 years; and an economic cost that is greater than cancer, stroke, or dementia. Yet, the research spend on neurodevelopmental diseases is less than 1% of the spending on cancer, stroke and dementia. The role of Noldus Noldus will further develop its innovative tools for neuroscience research using animal models to support the research in this project. Specifically it will both develop better tracking in its EthoVision XT software as well as improve the integration of physiology and behavioral measurements in EthoVision. Partners Radboud University Medical Centre, Nijmegen (Project Coordinator), King's College London, Birkbeck, University of London, Institut Pasteur, University of Basel, University of Groningen, University of Ghent, Karolinska Institute, Assistance Publique des Hôpitaux de Paris, INSERM, University of Ulm CEA, ADDISS, Autism Europe, Noldus Information Technology, ARTTIC Funding This project is funded by the Horizon 2020 research program of the European Union under grant number 847818. More information To find out more, you can contact us or visit the project website. Back to Research Projects @include('partials.hero-neural-network') --- ## COHABIT project page | Noldus URL: https://noldus.com/projects/cohabit Description: All information on the Collaborative Human-AI Annotation for Behavioral Insight and Tracking project Back to Research Projects Research project COHABIT Human Behavior Research Clinical assessment of behavior often relies on self-reporting, interviews, and observations. Those methods pose challenges for reliability, validity, and scalability. AI can help with that, but it requires large amounts of correctly labelled data for training. About the project This project will develop the knowledge and tools needed to solve this problem. The PhD student will carry out research to develop a combination of active learning and interface design to enable rapid upscaling of computer vision-based tracking systems in clinical domains. We aim to provide a flexible and powerful tool for smart annotation of human behavior that will become an indispensable component for clinical applications requiring human behavioral analysis. The consortium The project is led by Noldus Information Technology and the other partner is the Department of Information and Computing Sciences of the University of Utrecht. The role of Noldus As the project lead, Noldus will employ the PhD student and so is responsible for the main deliverables of the project. Funding This collaboration project [HH-PPS-25020-PhD] is co-funded by PPP Subsidy awarded by Health~Holland, Top Sector Life Sciences & Health, in collaboration with Noldus and the University of Utrecht to stimulate public-private partnerships. --- ## COMFOCUS URL: https://noldus.com/projects/comfocus Description: Eating unhealthy food is a serious problem in our society causing diseases like diabetes, heart disease and obesity. This project aims for joint research. Home Research Projects COMFOCUS Research Project COMFOCUS Eating unhealthy food is a serious problem in our society causing diseases like diabetes, heart disease and obesity. This project aims for joint research. Community on Food Consumer Science COMFOCUS Eating unhealthy food is a serious problem in our society causing all sorts of problems like diabetes, heart disease and obesity. There is still too little understood about why consumers make the choices they do. In this project, the partners will carry out networking and joint research to enable the field to adopt the best modern methodologies for researching this issue. The role of Noldus in COMFOCUS Across Europe, researchers are working together to better understand consumer behavior and food choices. Noldus will develop innovative new technologies for the objective measurement of the experience of food consumers. During the project NoldusHub was developed and used by researchers for integrating, synchronizing and carrying out advanced analysis of a range of sensor data streams. Project partners The COMFOCUS project is led by Wageningen University and has 14 other partners, including Noldus. In the COMFOCUS project, early-career scientists explored surprising new questions. Get an impression of the COMFOCUS project by watching a short video of the conference below. Visual Explanation For a visual explanation of what the project aims to achieve, please click here. Funding COMFOCUS is funded by the Infrastructure call for starting communities from the Horizon 2020 program of the European Union. Grant number 101005259. More information on COMFOCUS To find out more, you can contact us or visit the project website. Back to Research Projects @include('partials.hero-neural-network') --- ## DERT URL: https://noldus.com/projects/dert Description: The PhenoTyper is a solution for scientists who want to carry out behavioral research using animals in a way that guarantees high quality data and also high levels of animal welfare. Home Research Projects DERT Research Project DERT The PhenoTyper is a solution for scientists who want to carry out behavioral research using animals in a way that guarantees high quality data and also high levels of animal welfare. DEVELOPMENT OF ELECTRONIC RESERACH TOOL DERT The PhenoTyper is a solution for scientists who want to carry out behavioral research using animals in a way that guarantees high quality data and also high levels of animal welfare. It has been on the market for many years now and is in use by hundreds of scientists throughout the world. In this project, we will develop a completely renewed version of the PhenoTyper, full of new technology and innovations. Partners The project has only two partners; Noldus and the innovative electronics company Spinnov. Funding DERT is funded by the Dutch national program for supporting innovative SMEs - MIT, via the Province of Gelderland. More information To find out more, you can contact us. Back to Research Projects @include('partials.hero-neural-network') --- ## ELAN - Research Project URL: https://noldus.com/projects/elan Description: Conventional home cages used in rodent research are small and only allow the animals to display a limited range of their natural behaviors. @include('partials.hero-auroral') Back to Research Projects Efficient lab animal monitoring ELAN pest_control_rodent Animal Behavior Research Conventional home cages restrict natural rodent behavior, causing stress and affecting welfare and data quality. In the ELAN project, a consortium of partners will develop a novel home cage that provides laboratory rats with space and opportunities to exhibit natural behavior, while simultaneously automatically monitoring their behavior and wellbeing. The role of Noldus Noldus will develop monitoring technologies and software for enhanced insights into the welfare and behavior of the animals living in the cages. Partners The project is led by Noldus Information Technology. The other partners are Radboud University Medical Centre, UNO Life Science Solutions, and Brain Builders. Funding This project is funded by the European Fund for Regional Development and the Province of Gelderland, as well as by the partners. Interested in ELAN? Let's collaborate! Want to learn more about the ELAN project or explore how Noldus tools can improve animal welfare monitoring? Get in touch. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## i-ACCESS MyRights URL: https://noldus.com/projects/i-access Description: Vulnerable children who come into contact with the justice system sometimes have difficulty accessing the right legal information, so that they know their rights and get proper support. Home Research Projects i-ACCESS MyRights Research Project i-ACCESS MyRights Vulnerable children who come into contact with the justice system sometimes have difficulty accessing the right legal information, so that they know their rights and get proper support. AI-DRIVEN SUPPORT FOR A SMART JUSTICE WITH CHILDREN IN EUROPE i-ACCESS MyRights Vulnerable children who come into contact with the justice system sometimes have difficulty accessing the right legal information, so that they know their rights and get proper support. In this project, the partners will develop an AI-based chat app which will address that problem. The role of Noldus Noldus will develop an innovative system for measuring the user experience of the system developed in the project. The developers of that system will use the system created by Noldus to gain accurate insights into how children using the system experience it, and in that way get rapid feedback to enable them to create a genuinely user-friendly product. Partners The project is led by Terres des Hommes (Hungary) and has partners from several other Terres des Hommes divisions as well as the University of Leuven, Noldus and Lawren.io, a Belgium IT company. Funding i-ACCESS is funded as part of the Justice Programme (JUST) of the European Union’s Horizon Europe program. This program forms part of a new Justice, Rights and Values Fund together with the Citizens, Equality, Rights and Values programme. More information To find out more, you can contact us directly. Back to Research Projects @include('partials.hero-neural-network') --- ## INTENSE - Research Project URL: https://noldus.com/projects/intense Description: The INTENSE project will develop brain implants to improve the lives of people who are blind, deaf or paralyzed, or who have epilepsy. @include('partials.hero-auroral') Back to Research Projects Innovative neurotechnology for society INTENSE Human Behavior Research The INTENSE project will develop brain implants to improve the lives of people who are blind, deaf or paralyzed, or who have epilepsy. The research combines the greatly increased knowledge about our brains with new possibilities within neurotechnology. The role of Noldus Noldus is an industrial partner in this project. Our role is to develop our tools in the context of the project. Partners INTENSE is made up of members of the NeuroTech-NL organization. It is coordinated by the Netherlands Institute for Neuroscience, and there are 14 other research organizations and 22 companies in the project. Funding INTENSE is funded by the Dutch Research Council (NWO) as part of its Crossover program. Interested in INTENSE? Let's collaborate! Want to learn more about the INTENSE project or explore how Noldus tools can support neurotechnology research? Get in touch. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## ISIDORe URL: https://noldus.com/projects/isidore Description: ISIDORe is an EU-funded project under the Horizon Europe program that unites a multidisciplinary consortium of 17 European research infrastructures to offer integrated services for combatting current and future infectious disease outbreaks. Home Research Projects ISIDORe Research Project ISIDORe ISIDORe is an EU-funded project under the Horizon Europe program that unites a multidisciplinary consortium of 17 European research infrastructures to offer integrated services for combatting current and future infectious disease outbreaks. INTEGRATED SERVICES FOR INFECTIOUS DISEASE OUTBREAK RESEARCH EMERGENCY ISIDORe ISIDORe is an EU-funded project under the Horizon Europe program that unites a multidisciplinary consortium of 17 European research infrastructures to offer integrated services for combatting current and future infectious disease outbreaks. The project provides access to key services to support projects for the study of SARS-CoV-2, its variants and other potential pathogens. It represents a meta-infrastructure project of unprecedented dimensions in the European Research Area and serves as a central instrument in the European R&D response to epidemic outbreaks. The role of Noldus Noldus will provide services, such as use of its EthoVision product, for measuring animal behavior in the context of the project to the partners. Partners The project consortium is made up of 10 ESFRI infrastructures, 6 EU-funded networks and one national surveillance network, coordinated by the research infrastructure ERINHA with a total of 156 project partners from 32 countries. Funding ISIDORe is funded as part of the EU-Commission´s biodefense preparedness plan, the Health Emergency Preparedness and Response Authority (HERA) Incubator under Horizon Europe. More information To find out more, you can contact us or visit the project website. Back to Research Projects @include('partials.hero-neural-network') --- ## LoLiPoP - Research Project URL: https://noldus.com/projects/lolipop Description: Buildings are increasingly becoming smarter, with all sorts of sensors and devices. @include('partials.hero-auroral') Back to Research Projects Long life power platforms for Internet of Things LoLiPoP Human Behavior Research Buildings are increasingly becoming smarter, with all sorts of sensors and devices. Wireless sensor networks can have all sorts of uses, but also have requirements such as improved battery life and better ease of maintenance. The project has twelve use cases demonstrating technical viability and potential impact such as reducing building energy use, increasing comfort levels and improved component design. The role of Noldus Noldus will cooperate in the Vitality Hub use case. It will develop its NoldusHub product, with the aim of monitoring the welfare of people in the office environment so that the conditions can be optimized for them. Partners The project is led by Contechna SRA and has an international consortium of 46 partners, including Noldus. Funding LoLiPoP is funded by the KDT JU (Key Digital Technologies Joint Undertaking), part of the European Union's Horizon Europe program (project number 101112286). Interested in LoLiPoP? Let's collaborate! Want to learn more about the LoLiPoP project or explore how Noldus tools can support smart building research? Get in touch. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## MARSAI - Research Project URL: https://noldus.com/projects/marsai Description: MARSAI is a research project focused on maritime safety using AI-driven behavioral analysis and simulation technology. @include('partials.hero-auroral') Back to Research Projects Research project MARSAI Human Behavior Research Vessel traffic control at large ports like Rotterdam is increasingly complex. Large numbers of giant ships, often full of dangerous goods, need to be managed. Human error can lead to an accident with catastrophic effects. In MARSAI, we will develop tools for measuring factors like situational awareness, workload, communication, stress and fatigue using AI analysis of sensor data in order to support operators of such systems, especially in training situations. The role of Noldus Noldus will develop tools for integrating and gaining insights into the sensor data analyzed by the other partners. The software will be developed in such a way that it is useful not only in the maritime context but also for other human-factors situations. Partners Noldus is the project leader. The other partners are Vicar Vision and Noterik. In addition, there are two associate partners: MARIN and BG Legal. Funding This project is funded by an 'MIT-AI' grant from the Dutch government. The grant is designed to support innovation in small and medium-sized companies, especially related to AI applications. Interested in MARSAI? Let's collaborate! Want to learn more about the MARSAI project or explore how Noldus tools can support your human-factors research? Get in touch and we'll be happy to discuss the possibilities. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## NEWLIFE - Research Project URL: https://noldus.com/projects/newlife Description: The NewLife project will develop new remote non-invasive monitoring solutions for ensuring the health of mothers and babies before and after birth. @include('partials.hero-auroral') Back to Research Projects New remote non-invasive monitoring solutions NEWLIFE Human Behavior Research The NewLife project will develop new remote non-invasive monitoring solutions for ensuring the health of mothers and babies before and after birth. The target is to develop emerging non-invasive methods for gathering vital data and analysing it with advanced AI/ML methods. The role of Noldus Noldus will develop a platform for integrating, synchronizing and analyzing data streams from sensors measuring various aspects of the babies' health and welfare. Partners The project is led by Philips Research and has a large consortium of 28 partners, including Noldus. Funding NewLife is part of the Key Digital Technologies Joint Undertaking (KDT-JU) program of the EU's Horizon Europe research program. Interested in NEWLIFE? Let's collaborate! Want to learn more about the NEWLIFE project or explore how Noldus tools can support maternal and infant health research? Get in touch. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## SmartStressMonitor - Research Project URL: https://noldus.com/projects/smartstressmonitor Description: In the SmartStressMonitor project, the underlying technology for an automatic distress monitoring system for mice and rats in their home cages will be developed. @include('partials.hero-auroral') Back to Research Projects Research project SmartStressMonitor pest_control_rodent Animal Behavior Research The discovery, development and safety of most medications critically relies on experiments on animals. This requires humans to provide a high standard of care for the animals. In animal facilities, animal caretakers routinely observe animals to determine whether any individual in a cage is distressed. However, distress monitoring typically occurs only once a day, which can lead to distress remaining undetected for up to a day. In the SmartStressMonitor project, we will develop the underlying technology for a commercial, automatic distress monitoring system for mice and rats in their home cages. We will use recent advances in AI analysis and acoustic sensing technology to track their movements and vocalizations and estimate the distress of individual animals which are socially housed. This will be performed in real-time to rapidly inform animal caretakers. The role of Noldus Noldus will develop innovative AI-based software for analysis of behaviors that cannot currently be monitored, such as welfare states. In addition it will develop an integration platform for the various data streams. Partners Noldus is the project leader. The other partners are CAE Software and Systems, Kubion GmbH, Heinrich Heine Universität Düsseldorf, Radboud University, and Radboud University Medical Centre. Funding The project is financed by the Interreg program for cross-border cooperation between Germany and the Netherlands. The funding bodies contributing to this project are the European Union, the Dutch Ministry of Economic Affairs, the Province of Gelderland, the Ministry of Culture and Science of North Rhine-Westphalia and Lower Saxony State Chancellery as well as the project partners. Interested in SmartStressMonitor? Let's collaborate! Want to learn more about the SmartStressMonitor project or explore how Noldus tools can improve animal welfare monitoring in your facility? Get in touch. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## SmartStressMonitor URL: https://noldus.com/projects/SSM Description: In the SmartStressMonitor project, the underlying technology for an automatic distress monitoring system for mice and rats in their home cages will be developed. Home Research Projects SmartStressMonitor Research Project SmartStressMonitor In the SmartStressMonitor project, the underlying technology for an automatic distress monitoring system for mice and rats in their home cages will be developed. Research project SmartStressMonitor The discovery, development and safety of most medications critically relies on experiments on animals. This requires humans to provide a high standard of care for the animals. In animal facilities, animal caretakers routinely observe animals to determine whether any individual in a cage is distressed. However, distress monitoring typically occurs only once a day, which can lead to distress remaining undetected for up to a day. In the SmartStressMonitor project, we will develop the underlying technology for a commercial, automatic distress monitoring system for mice and rats in their home cages. We will use recent advances in AI analysis and acoustic sensing technology to track their movements and vocalizations and estimate the distress of individual animals which are socially housed. This will be performed in real-time to rapidly inform animal caretakers. The role of Noldus Noldus will develop innovative AI-based software for analysis of behaviors that cannot currently be monitored, such as welfare states. In addition it will develop an integration platform for the various data streams. Partners Noldus is the project leader. The other partners are CAE Software and Systems, Kubion GmbH, Heinrich Heine Universität Düsseldorf, Radboud University, and Radboud University Medical Centre. Funding The project is financed by the Interreg program for cross-border cooperation between Germany and the Netherlands. The funding bodies contributing to this project are the European Union, the Dutch Ministry of Economic Affairs, the Province of Gelderland, the Ministry of Culture and Science of North Rhine-Westphalia and Lower Saxony State Chancellery as well as the project partners. More information To find out more, you can contact us directly. Back to Research Projects @include('partials.hero-neural-network') --- ## TEATIME - Research Project URL: https://noldus.com/projects/teatime Description: The aim of this Action is to bring together European organizations developing and using automated home-cage monitoring technologies. @include('partials.hero-auroral') Back to Research Projects COST TEATIME project TEATIME pest_control_rodent Animal Behavior Research The aim of this Action is to bring together European organizations developing and using automated home-cage monitoring technologies. Novel and emerging technologies allow 24/7 collection of behavioural data in their home cage. However, addressing the complex problem of monitoring the full 24-hour behavioural repertoire of a rodent still presents many challenges, with each technology having its strengths and limitations. The role of Noldus Two Noldus employees are members of the project, and one of them is the national representative for the Netherlands. Partners The project is led by the University of Helsinki and has 115 members in the network. Funding TEATIME is a COST action, which funds research and innovation networking projects for European Cooperation in Science and Technology. It is funded by the European Union. Interested in TEATIME? Let's collaborate! Want to learn more about the TEATIME project or explore collaboration opportunities? Get in touch. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Basic Behavioral Neuroscience in Rodents URL: https://noldus.com/rodent-neuroscience-ebook Description: Check out our free downloadable e-book where we explain from A to Z why and how we measure certain behavior in rodents Free e-book Basic Behavioral Neuroscience in Rodents This comprehensive e-book covers the fundamentals of behavioral neuroscience research using rodent models. Learn about the most common behavioral tests, best practices for experimental design, and how to get reliable, reproducible results. In this e-book you will learn: - checkCommon behavioral tests for rodents - checkHow to design robust experiments - checkVideo tracking and automated analysis - checkBest practices for data collection - checkHome cage monitoring approaches Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free Why is it essential to understand animal behavior? Behavioral neuroscience bridges the gap between brain function and observable behavior. By studying how rodents behave in controlled environments, researchers gain insights into neurological disorders, drug effects, and fundamental brain processes. Rodent models are essential for preclinical research in areas such as anxiety, depression, learning and memory, motor function, and social behavior. Topics covered in this e-book: - checkOpen field test and locomotor activity - checkElevated plus maze for anxiety - checkMorris water maze for spatial learning - checkNovel object recognition - checkSocial interaction tests - checkHome cage monitoring --- ## Research Solutions URL: https://noldus.com/solutions Description: Explore Noldus research solutions for human and animal behavior. Software, hardware, and integrated systems to capture, code, and analyze behavior. Noldus research solutions Explore how Noldus supports researchers across human and animal behavior. Each solution combines software, hardware, and expertise to help you capture, code, and analyze behavior with confidence. Human behavior research Behavioral Economics Behavioral economics merges psychology and economics to explore how psychological factors influence economic decisions and human behavior. Consumer Behavior Research Observational research and behavioral mapping is becoming more and more popular in consumer behavior research studies. Education & Training How can you make sure students become the professional they want to be? Let them practice their skills and benefit from video feedback. Emotion Analysis Emotions influence our behavior - from deciding what to eat and whether to buy a product to our interactions with others. Human Factors Research Human factors and ergonomics is the application of psychological and physiological principles to the engineering and design of products, pro... Neuroscience Research Human neuroscience research requires software that combines and synchronizes different types of data . Noldus has the solutions you need! Psychology Research Many people are fascinated by human behavior. Why do we act the way we do? How is our behavior influenced? UX Research UX research focuses on discovering and understanding behaviors, needs, and motivations of users through observation, task analysis, and othe... Animal behavior research Autism Research Discover Noldus tools for autism research. Capture, code, and analyze behavior with objective, integrated solutions for human and animal stu... Cognition and Memory Learn more about learning, memory and cognition in animal research. Learning paradigms are an essential part of research in both rodents and... Fear, Anxiety, and Depression Anxiety, fear, and depression in rodents and fish are typical in a wide range of studies, including neuropharmacological studies. Gait & Locomotion Gait an locomotion are important readout parameters for a variety of diseases. On this page you can read about what gait is and how to measu... Home Cage & Welfare Learn all about long term behavioral observations in rodents. What it is, why you should consider it and how you measure behavior for a long... Social Interaction The study of social interaction can be done in a variety of set-ups, all having one thing in common: the study of behaviors between two or m... Ultrasonic Vocalizations Want to learn more about the significance and how to measure vocalizations in animals? On this page we tell you all about it. Zebrafish Research Zebrafish as a model for biomedical research. Noldus offers a wide array of solutions for research with zebrafish, both larvae and adult fis... Zoology and Ethology Learn all about how modern tools and systems can help you easily collect more valuable behavioral data. Noldus products have been used for m... --- ## Autism Research URL: https://noldus.com/solutions/autism-research Description: Discover Noldus tools for autism research. Capture, code, and analyze behavior with objective, integrated solutions for human and animal studies. @include('partials.hero-auroral') Autism research Autism spectrum disorder is defined entirely by behavior. There are no medical tests or biomarkers, so progress depends on what we can see, measure, and understand. Noldus tools help researchers around the world capture those observations with precision and consistency. Whether studying children in a playroom, mice in a social test, or infants showing early signs of atypical development, our software turns complex behaviors into objective data. The challenges of measuring autism Autism affects social interaction, communication, and repetitive or restricted behaviors. Each person on the spectrum is unique, which makes objective measurement essential. Traditional observation methods rely on human judgment and can miss subtle patterns that carry important meaning. Researchers studying autism face several key challenges: Complex and variable symptoms Autism influences multiple domains that can change across contexts and individuals. Read blog post Subjectivity in manual observation Human coding and clinical ratings are prone to bias and inconsistency. Are there objective measures? See how it works Limitations of using animal models Animals do not express social behaviors in human ways, which can hinder translational outcomes. Go to the article The need for early detection and diagnosis Most efforts to detect autism before the age of two rely on parental reports rather than infant behavior. Read more The Observer: Structured behavioral coding Social interaction, communication, and therapy sessions involve behaviors that must be coded by trained observers. The Observer brings structure and reliability to this process. - Allows researchers to define, code, and analyze behaviors on a synchronized timeline - Integrates video, audio, physiological data, and eye tracking - Ensures reproducible coding with interrater reliability statistics - Generates visual summaries that highlight behavior frequency and duration The Observer turns complex social behavior into clear, reliable data that strengthens every stage of autism research. Learn more about The Observer EthoVision: Objective tracking of behavior EthoVision is the most cited video tracking system in behavioral research. It automatically measures movement, social approach, and exploratory activity, giving scientists rich data without human bias. - Tracks activity, position, and interaction with complete objectivity - Analyzes animal and human behavior in the same platform - Handles long recordings and large sample sizes efficiently - Provides consistent results that can be compared across experiments EthoVision gives researchers an accurate, unbiased way to measure activity and social behavior, transforming every movement into meaningful, reliable data. Discover more about EthoVision FaceReader: Understanding emotional expression Emotion recognition and expression are central to autism research. FaceReader automatically analyzes facial expressions, providing a precise timeline of emotional responses. - Detects six universal emotions plus neutral and contempt - Measures facial muscle movements with millisecond accuracy - Enables detailed analysis of mimicry, intensity, and timing - Includes Baby FaceReader for developmental research in infants FaceReader gives researchers a powerful way to quantify emotion and expression, turning subtle facial responses into meaningful, reliable insight. Learn more about FaceReader Case studies: Noldus tools in autism research Objective tracking of children with autism Using EthoVision, researchers tracked how children with and without autism explored a playroom, transforming behavioral observation into quantifiable data that correlated with autism severity. Read the full publication Measuring social skills gains in therapy Using The Observer, researchers evaluated a theater-based social intervention for children with autism, turning video observations into measurable proof of behavioral improvement. More about the theatre Revealing emotional differences in faces Using FaceReader, researchers analyzed facial mimicry in children with autism, uncovering subtle differences in emotional intensity that shed new light on social-emotional processing. Read the full publication Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Behavioral Economics URL: https://noldus.com/solutions/behavioral-economics Description: Behavioral economics merges psychology and economics to explore how psychological factors influence economic decisions and human behavior. Behavioral economics What is it A day in the life Best practices Uncover answers Buyer's guide Contact @include('partials.hero-auroral') Behavioral economics Behavioral economics merges psychology and economics to explore how psychological factors influence economic decisions, helping policymakers and businesses create strategies that better match human behavior and decision-making, enhancing economic and social outcomes. - How do psychological factors shape economic decisions? - What influences your spending and saving behaviors? - How can understanding behavior improve policy effectiveness? Are you looking for advice on your application? What is behavioral economics? Behavioral economics is a field that combines insights from psychology and economics to study how people actually make decisions, as opposed to how they are expected to behave based on traditional economic theories. It explores the cognitive biases, emotions, and social factors that influence choices, often leading to irrational or suboptimal decisions. Understand behavioral patterns By understanding these behavioral patterns, researchers can better predict real-world economic behaviors and design interventions that guide people towards better decision-making in areas like finance, health, and public policy. Behavioral economics seeks to bridge the gap between economic models and human behavior. A day in the life of a behavioral economist As a behavioral economist, your workday combines theory, experimentation, and data analysis to understand human decision-making. You design experiments using both quantitative and qualitative methods, including surveys and biometric tools like eye-tracking, to explore why people make specific choices. Uncover patterns in behavior A large part of your day is spent analyzing data to uncover patterns in behavior, often dealing with cognitive biases and irrational decision-making. You collaborate with experts across fields to develop models that explain and predict behavior. Balancing psychological complexity with data precision, your work has practical applications in areas like public policy, marketing, and finance. Staying current with the latest tools and methodologies is part of your daily routine. Discover how Noldus can support you in achieving all of this. Best practices in behavioral economics research Define clear objectives Set specific research goals to focus on particular behavioral patterns or decision-making processes. This ensures the research addresses the right questions and yields actionable insights. Incorporate both qualitative and quantitative methods Combine interviews, observations, and numerical data to gain a holistic understanding of behavior. This allows researchers to capture both the "what" and the "why" of decision-making. Conduct pilot studies Test your methodology on a small scale before launching large-scale experiments. This helps identify potential issues and ensures the research design is effective and clear for participants. Ensure ethical standards Obtain informed consent, protect participant privacy, and handle data responsibly. Ethical practices build trust and ensure the welfare of participants, which is critical in behavioral research. Control for biases Carefully design experiments to minimize cognitive biases or unintended influences on participants. This ensures that results reflect genuine behavior rather than external factors introduced by the study itself. Test in real-world settings Validate lab-based findings in natural environments to ensure the results are applicable outside of controlled scenarios. This helps to bridge the gap between theoretical research and practical, real-world applications. Iterate and refine hypotheses Be prepared to adjust hypotheses and methodologies as new data and insights emerge. Behavioral research often uncovers unexpected findings, requiring flexibility and ongoing refinement of research approaches. How to uncover answers: Gaining real-world insight into economic choices Observations Observing real-life behavior is essential in behavioral economics, offering valuable insights into how adults make economic choices in real or partly controlled settings. Through observation, researchers can see directly how biases, social influences, and context shape decision-making. - Video observation is a non-invasive form and will enable you to capture (inter)actions. Multiple camera views create new perspectives. - To properly analyze behaviors, you need to review and code your video observations. - Observation labs are ideal for controlled, discreet analysis, letting participants behave naturally in structured settings. Behavioral experiments Behavioral experiments in a controlled environment are essential for identifying cause-and-effect relationships and uncover the underlying mechanisms that drive people's actions and economic choices. - To capture reactions to stimuli or how participants perform a task, video recordings are instrumental. - Statistical methods to identify patterns that might go unnoticed otherwise, ensuring results are reliable for informed decision-making. - Behavioral experiments typically take place in controlled environments such as a research lab. Benefit of precise control and access to advanced technology. Physiological measures Behavioral economics benefits from physiological tests, which provide a deeper understanding of the emotional and bodily responses that accompany economic decisions. - By integrating various data streams you get a comprehensive view of participants' behaviors and physiological responses. Besides, you want everything to be aligned for accurate analysis. - Combining facial expression analysis with physiological data gives a fuller picture of emotional experiences. This helps in understanding how emotions manifest both externally (through expressions) and internally (through physiological changes). Buyer's guide to the perfect audiovisual lab - What is an audiovisual lab? - What do you need to complete your setup? - How does an audiovisual lab help you answer your research questions? Get your copy Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Cognition and Memory URL: https://noldus.com/solutions/cognition-memory Description: Learn more about learning, memory and cognition in animal research. Learning paradigms are an essential part of research in both rodents and zebrafish Cognition and memory What is it? How to measure Featured resources Contact @include('partials.hero-auroral') Cognition and memory Understanding how animal models learn, remember, and adapt is crucial in advancing our knowledge of neurodegenerative diseases like Alzheimer's and Parkinson's disease. However, there is not just one test for one type of cognition. For example: - Spatial and recognition memory - Associative and operant learning - Cognitive flexibility Are you looking for advice on your application? What is Cognition and Memory? Cognition and memory are essential for understanding animal behavior, reflecting how animals process and retain information. In research, these processes are studied through various tests that reflect the varying parts of memory and cognition. These measures help researchers evaluate brain function and the impact of interventions, particularly in models of neurological and psychological disorders. Short and long-term memory Short-term memory enables animals to quickly process and respond to new information, crucial for navigating environments, pursuing goals, and enhancing survival. Long-term memory stores essential information over time, from territory layouts to experiences linked to rewards or dangers. - Working memory is a short-term memory used to retain and manipulate information during a task, often assessed in animals by their ability to remember objects, stimuli, or locations within a single session. - Episodic memory is a type of long-term memory involving specific events tied to particular times and places, often assessed in animals through location-based tasks. Associative learning tests Associative learning is a process in which a new response becomes associated with a particular stimulus. Pavlovian learning is a form of associative learning, typically induced in subjects that associate stimuli with a negative (aversive) stimulus or situation. - Induce a stimulus (typically negative, but can be neutral or positive). - Learn to connect the stimuli to a response. - Reinforce this response and therefore strengthen the behavioral pattern. Reversal learning Cognitive flexibility is the ability to rapidly adapt behavior while facing specific circumstances. Essentially, it measures an animal's cognitive flexibility: the capacity to unlearn a previously learned behavior. - Cognitive flexibility is essential in the development of behavior, enabling an animal to modify its behavior to changes in the environment. - How quickly and successfully an animal adapts its behavior is a great indicator of brain function. Spatial memory Spatial memory concerns the association of an organism in a three-dimensional environment. In other words: an animal learning its position in a given space. This learning relies on visual, but also acoustic and olfactory cues. - Allocentric memory: Encodes the location of an object based on its relationship to other objects in the environment, independent of your position. - Egocentric memory: Encodes the location of objects relative to your own current position or viewpoint. Explore cognition with a free e-book Basic behavioral neuroscience in rodents Want some more literature on the basic (behavioral) neuroscience in rodents? Download our free e-book. In this e-book you can, among other things, read about the basics of what learning and memory testing in rodents is and how to execute the most common protocols. Start learning How to measure Cognition and memory Y/T-maze The Y/T maze (or cross maze in zebrafish) is used to test the learning and memory of animal models. It is often used to test reversal learning, learning retention, and preference testing. The time spent in certain arms of the maze can be tracked by EthoVision XT. This ensures that data is collected easily and accurately. Morris water maze The Morris water maze is a well-validated test for spatial learning. At Noldus, we offer not only high quality mazes in various sizes and colors but also the best tracking system available. EthoVision XT is essential for measuring the average distance to the platform and swimming patterns. This is important for trials where the platform is moved or removed. Novel object test The novel object test assesses cognitive function and exploratory behavior in rodents by gauging their response to a new object. With EthoVision XT, you can precisely track the distance of the nose-point of the animal to the novel object. Proper hardware and software ensure that your data is consistent and reliable. Cincinnati maze The Cincinnati maze is used to test egocentric navigation, learning and memory in rodents. An animal swims through the maze trying to find the exit platform. With EthoVision XT you can easily measure the distance moved, number of errors, and time spent reaching the goal. Barnes maze The goal of a Barnes maze is to study spatial learning and memory. The rodent is supposed to find the box that is positioned beneath one of the holes. The mouse or rat uses visual aids outside of the arena to find a food reward. EthoVision XT allows you to easily track which holes the animal is investigating and how long it takes for it to find the reward. CognitionWall The CognitionWall by Sylics is a wall containing three entrances placed in front of a reward dispenser. Once the animal has learned which entrance activates the reward dispenser the correct answers can be changed to assess the animal's cognitive flexibility. CognitionWall can easily be fitted in PhenoTyper instrumented home cage. Featured resources Blog Using video tracking to study operant behavior in rodents Scientists from Idorsia Pharmaceuticals in Switzerland provide an expert view on operant behavior, and how we can improve our understanding of this complex behavior with the help of video tracking. Read this blog post Blog Unlocking the link between CNS infections and cognitive decline Bacterial infections in the brain can have lasting effects even after recovery. In this blog we will look at a study that used PhenoTyper and the CognitionWall to study the mechanisms behind this cognitive impairment. Read this blog post Blog Advancing the novel object test: 3D printing and deep learning To improve standardisation and consistency in the novel object test, Spry et al designed the 'CapTouch' system: capacitive objects that can automatically register interaction. But what about deep learning in EthoVision XT? Read this blog post Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Consumer Behavior Research URL: https://noldus.com/solutions/consumer-behavior-research Description: Observational research and behavioral mapping is becoming more and more popular in consumer behavior research studies. Consumer behavior What is it A day in the life Methods & Tools Best practices Featured resources Contact @include('partials.hero-auroral') Consumer behavior What is important to you when you buy a product? What decisions do you make before you buy? Really knowing your customer is what you need to design loved products and applications. Therefore, as a consumer behavior researcher, you: - Focus on studying consumer actions (in the moment) - Want to get to know the underlying motives - Intend to predict consumer preference and consumer buying behavior Are you looking for advice on your application? What is consumer behavior research? How do individuals, groups, or organizations make decisions about buying, using, and disposing products or services? A consumer behavior researcher looks at the factors that influence these decisions, such as emotions, cultural influences, personal preferences, and social trends. Understanding consumer behavior helps predict what products or services people will choose and align with people's real needs. As a result, products and services improve, marketing is more relevant, and consumers' satisfaction grows. A day in the life of a consumer behavior researcher In today's fast-paced world, your role as a consumer behavior researcher is more vital than ever. You explore why people make certain choices, analyzing both emotional and rational factors. Your work involves sorting through data, identifying trends, and uncovering patterns in behavior. Staying up to date with new technologies and changing consumer expectations is key. Bridge the gap Your challenge lies in filtering through vast amounts of information to find actionable insights, often under tight deadlines. You want to bridge the gap between what consumers say they want and what truly drives their actions. When you discover the key factors that predict behavior, the reward is clear: you uncover customer needs. Uncover answers: Methods and tools to measure consumer behavior Observe in a natural or simulated environment Your test participant's environment greatly affects behavioral experiment results. To control this in a lab, create an experience room to simulate real-world settings, or conduct observations on-site. - A video observation tool will help you capture, replay, and discuss participants' behaviors. - For analyzing the behaviors properly, you need to code your video observations. - A portable lab offers the best solution if you want to carry out observations on site, for example, in a shop. Capture emotional responses and eye movements If something smells disgusting, if a weird color makes us feel anxious, or if we like the taste of something: our face and eyes can tell, without us being aware of it. - Measuring facial expressions provides insights in the relationship between emotions, consumer acceptability, and purchase intent, and gives guidance towards food and packaging innovation. - Eye tracker glasses allow your test participant to move and look around freely, while the researcher gets to see where the test participant is looking at, or is not looking at. Measure changes in one's physiological state Responses like changes in heart rate, pupil size, and sweating occur without us realizing and can give a lot of information about how and especially how much someone feels about something. These techniques let you dive deeper into the unconscious preferences of consumers and their decision-making processes. - By integrating various data streams you get a comprehensive view of participants' behaviors and physiological responses. Besides, you want everything to be aligned for an accurate analysis. Best practices for consumer behavior research Free product portfolio Define clear objectives | Start with a clear understanding of what you want to discover or test in your research. Use multiple data sources | Collect data from multiple sources—surveys, behavioral experiments, observational studies, and online behavior analytics—to get a fuller picture. Segment your audience | Break down your consumer group into segments based on demographics, psychographics, or behavior to better target insights. Apply behavioral insights | Use knowledge of how people naturally think and act to better understand what influences their choices. Incorporate principles like loss aversion, social proof, and the endowment effect to understand how consumers are influenced. Test in realistic settings | Simulate real-world environments, or conduct field studies to observe genuine consumer behavior. Stay updated on technology | Utilize advanced tools like eye-tracking, biometric measurements, facial expression monitors, and big data analytics for precise insights. Account for bias | Be aware of cognitive biases - mental shortcuts or patterns of thinking that can lead people to make decisions that are not entirely rational or objective. This can affect how consumers perceive information and make choices. Focus on ethical research | Ensure transparency, informed consent, and respect for participant privacy in all studies. Featured blog posts Blog How to increase attention in commercials for Gen-Z Generation Z has the shortest attention span for commercials, yet they are becoming an important market segment. Understanding what captures their interest and how to engage them is crucial. Check out this blog post Blog Why you want to find out if your customers are bored Emotions deeply influence our daily lives, shaping our moods and behaviors - including our decision making. That's why facial expression analysis is often used in consumer behavior research. Check out this blog post Blog A study on consumer experience in self-designing Consumer research suggests that you value a product more when you design it yourself. But abandonment rates in the self-design process are extremely high. Researchers tried to find out why. Check out this blog post Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Education & Training URL: https://noldus.com/solutions/education-training Description: How can you make sure students become the professional they want to be? Let them practice their skills and benefit from video feedback. Education & Training What is it A day in the life How to elevate Best practices Featured resources Contact @include('partials.hero-auroral') Education & training How can you make sure students become the professional they want to be? Let them practice their skills and benefit from video-based feedback. It will help them evaluate their own learning process and identify gaps. As an educator you want to: - Put theory into practice in a safe and controlled environment - Capture training sessions on video for debriefing - Give students immediate feedback Are you looking for advice on your application? What is education & training? Helping people acquire new skills and gain knowledge is what it is all about in education and training. Your goal is that people develop expertise in a particular field or profession. It can take place in a wide variety of fields, and in many different settings such as classrooms and skills labs. By using video and audio recordings in education and training, students and educators can receive, and benefit from, direct feedback. It provides information about how we are doing in our efforts to reach a goal. A day in the life of an educator The overall development of the student is your main concern as an educator. You are focused on their learning process, critical thinking, emotional intelligence, and real-world skills. There is a lot involved in achieving that students get prepared for the modern job market. Ideally, you want to offer them a learning environment that mirrors the demands of the workplace - to practice real job tasks and soft skills like communication, teamwork, and problem-solving. Student engagement is your ultimate goal The challenges you face have mainly to do with limited resources - time, technology, funding - while staying up to date with trends. Nowadays, it is inevitable that these trends are an important factor in student engagement. Advanced tools will help you tackle key challenges like resource management, student engagement, and skill development. Subsequently, you can create a more dynamic and effective learning environment that better prepares students for future challenges. How to elevate education & training Provide skills training By assigning tasks that reflect real industry challenges or workplace scenarios, students gain hands-on experience that prepares them for their future jobs. Feedback is an essential part of that effective learning process. - Video observation is a non-invasive form to capture skills of students. Multiple camera views create new perspectives on the same behavior. The video recordings can be used to give feedback on pre-defined goals during debriefing. - In case of a large number of students, diverse conditions or different scenarios, a multi-room lab will meet your needs. It allows sessions to take place in parallel. Increase student engagement You can develop instructional materials more effectively by understanding the factors that influence student engagement. When students are engaged, their motivation, productivity, and performance improves. - Measuring students' facial expressions enables you to capture subtle signs of interest, confusion, or boredom. You'll get objective feedback on how students are feeling during a lesson. - After coding student and teacher behavior, you can analyze the patterns and discover the influence of teachers' motivation behaviors on students' engagement. You'll clearly see how to enlarge student engagement. Best practices for education and training Free product portfolio Know your students Try to understand their individual learning styles, interests, backgrounds, and needs which allows for personalized instruction that resonates on a deeper level. Encourage active learning Keep students engaged and help them apply knowledge in real-world scenarios, for example with group projects, discussions, problem-solving exercises, and hands-on activities. Active learning helps students apply their knowledge in practical situations, which not only increases retention but also fosters the development of critical thinking and collaboration skills. Give clear and structured feedback Feedback should not only highlight areas for improvement but also recognize achievements. This consistent communication helps students track their progress, builds confidence, and encourages a growth mindset, where they view challenges as opportunities to learn. Use technology effectively Incorporate digital tools, online resources, and interactive platforms to enhance the learning experience. These tools can offer students a variety of ways to engage with the material, making it more accessible and enjoyable. Maintain flexibility Remain open to new teaching methods, tools, and feedback. This willingness to evolve ensures that students continue to offer relevant and impactful learning experiences. Foster a supportive classroom environment Let students feel comfortable asking questions and taking risks. This encourages critical thinking, creativity, and collaboration, all of which are crucial for both academic and professional success. Featured resources Blog How to train students in soft skills: Tools and techniques Soft skills are a vital component of student success in both academic and professional settings. In this blog post, you can explore some of the best tools and techniques for training students in soft skills. Check out this blog post Customer story Simulation-based training in an immersive room When well-constructed simulation-based training takes place in an immersive room, it offers a lifelike experience. Moreover, by adding Viso as the video feedback tool, efficient debriefing of the training is assured. Watch this user story Customer story Preparing future healthcare professionals At the AIXTRA competence center for training and patient safety in Germany, students improve their skills and build the confidence they need to succeed in their future roles, whether in hospitals or other healthcare settings. Check out this user story Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Emotion Analysis URL: https://noldus.com/solutions/emotion-analysis Description: Emotions influence our behavior - from deciding what to eat and whether to buy a product to our interactions with others. Emotion analysis What is it A day in the life Featured resources Best practices Options Action Units Contact @include('partials.hero-auroral') Emotion analysis Emotions are a fundamental part of being human. Emotions are shaped by our brain and influenced by our interests and past experiences. By including emotion data in research, we can explore human behavior in greater detail and gain better insights. You may include emotion analysis to answer some of these questions: - How do emotions influence what we buy or eat? - What is the role of emotion in our interactions with others? - How do people with developmental disorders process and express emotions? Are you looking for advice on your application? What is emotion analysis? Emotion analysis is the process of measuring and understanding human emotions. It's based on different physical and behavioral cues, like facial expressions, body language, and physiological signals. Together, these observations help researchers understand how emotions influence behaviors and decisions. - Optimize products, websites, and advertisements - Develop treatments for people with developmental disorders - Understand parent-child interactions A day in the life of an emotion researcher Emotion researchers want to understand how human emotions influence behavior, decision-making, and experiences. They might observe how participants interact with a website or product. Or they may want to know more about how different groups of people process or express emotions. By analyzing participants' emotional reactions, researchers gain valuable insights into how emotions impact consumer choices, learning, development, or social interactions. Benefit from the right tools for your emotion research Researchers use advanced tools like facial expression analysis, physiological measurements, and behavioral tracking to capture these emotions in real-time. Another benefit of using these tools is that it helps researchers to measure emotional responses accurately and non-invasively. Discover how Noldus can support your research! Featured resources Video Understanding social media use Researchers at the Social Media Lab analyze how users interact with social media. This type of research helps civil society organisations and other professionals to identify their customers' needs and implement new tools. Watch video play_circle Blog How FaceReader is validated in research How accurate is FaceReader in determining facial expressions? In this blog post, you'll learn more about different studies into the validity and applications of FaceReader. Read blog post Blog Measuring infant facial expressions What if you had a way to understand a baby's unspoken needs? Analyzing facial expressions in infants provides more insights into the early development of emotions. Read blog post Best practices for emotion analysis Clear goals Think about which emotional states or behaviors you want to study. Choosing a focus helps you gain objective results. Natural behavior Keep you study's environment as natural as possible or observe participants in their natural environment. This will help to capture genuine emotional responses and allows for unobtrusive observations. Experiment setup Choose the right angles and lighting to accurately capture your participants' emotional responses. Also be sure to minimize distractions and other external factors that may influence their responses. Multimodal research Combine facial expression tracking, physiological data, and behavioral observations to get a complete view of emotional reactions. Validated tools Make sure your emotion analysis data is accurate and reliable - choose software and methods that are validated in research. Analysis Observe emotions in real-time for quick insights or debriefing situations. Analyze emotions after recording for deeper, detailed understanding. Options for facial expression analysis Action Units The Facial Action Coding System (FACS) describes muscle movements in the face, also referred to as Action Units. - Benefit from objective analysis of facial expressions - Study the left and the right side of the face separately - Save time by relying on automated analysis of Action Units Valence and arousal Measure how negative or positive an emotion is (valence) and the level of activity caused by the emotion (arousal). - Better understanding and visualization of emotions - Differentiate between emotions that are similar in type but vary in intensity - Assess responses in marketing, consumer science, and psychology Custom facial expressions Design your own facial expressions or mental states, such as workload, confusion, boredom, or embarrassment. - Study nuances in behaviors or emotions that basic expressions can't always capture - Adapt your facial expression analysis to the needs and context of your project - Gain insights into culturally specific or atypical facial expressions @include('static.solutions._action-units') Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Fear, Anxiety, and Depression URL: https://noldus.com/solutions/fear-anxiety Description: Anxiety, fear, and depression in rodents and fish are typical in a wide range of studies, including neuropharmacological studies. Fear, anxiety, and stress Rodents Methods rodents Zebrafish Methods zebrafish EthoVision XT Contact @include('partials.hero-auroral') Fear, anxiety, and stress Many psychiatric illnesses are depression- or anxiety-related disorders. Behavioral tests with rodents are crucial to get insights on the underlying mechanisms and eventually find new treatments. Rodents and zebrafish are potentially great models to study fear, anxiety, and stress-related disorders. Common behavioral tasks are: - Elevated plus maze or zero maze - Open field - Novel tank diving test Are you looking for advice on your application? Fear and anxiety in rodents Rodents prefer dark and enclosed areas, as it is perceived a saver environment against predators. This innate aversion to light is used in test set-ups to investigate anxiety and fear-related behaviors such as staying in the dark, freezing, and hyperactivity. The open field, elevated plus maze, zero maze, and light-dark box are well-validated tests that offering a saver, darker environment and an open (often well-lit) area. More anxious animals tend to hug the walls in an open field, a behavior known as thigmotaxis, or spend more time in the closed-off arms in an elevated plus maze. Bolder animals start exploring the open areas sooner and spend more time there. Learn more with a free E-book Methods for studying fear, anxiety, and stress in rodents Open field The open field test is a straight-forward test to investigate activity, anxiety-related and exploratory behavior of rodents. Elevated plus maze The elevated plus maze is a well-characterized behavioral paradigm, one of the most used tests for anxiety research. Light-dark box The light-dark box is used to test the unconditioned anxiety response, based on the novel environment and the light/open space. Fear conditioning Fear conditioning and other learning tasks in rodents are typical in a wide range of neuropharmacological studies, amongst others. Forced swim test The (Porsolt) forced swim test, also known as the behavioral despair test, is used to test for depression-like behavior in both mice and rats. Zero maze The elevated zero maze is very similar to the elevated plus maze, but lacks a center square. Gives an indication of anxiety versus exploration. Anxiety and stress in zebrafish Zebrafish display stress and anxiety-like behaviors by displaying bottom dwelling behavior. In laboratory settings, important measurements are the time spent in the bottom of a novel tank, as well as latency to explore the upper half. These are useful parameters in the study of anxiolytic and anxiogenic properties of certain compounds. Side-view tracking is a practical approach to measure these parameters. This is an easy task for EthoVision XT. Methods for studying anxiety and stress in zebrafish Novel tank diving test Bottom dwelling behavior and latency to exploring the upper half of the tank are important measures that indicate stress and anxiety. Track3D Tracking in three dimensions is a true assessment of path shape, erratic movement, and velocity that cannot be fully measured from a side or top view. Learn more Using EthoVision XT to study fear, anxiety, and stress White paper Fear conditioning Fear- a highly conserved behavior in rodents. EthoVision XT easily automates this test and accurately measures freezing behavior. Download White paper Novel tank diving test EthoVision XT is well-established in measuring bottom dwelling behavior and latency to explore in the novel tank diving test. Download White paper Elevated plus maze The elevated plus is the most used test to study anxiety and exploration in rats and mice. It is also a test that can be easily automated using EthoVision XT. Download Don't know where to start? We're happy to help Book a meeting for an online or onsite session. Together, we can discuss your research requirements and come up with the best solution! Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Your browser does not support the video tag. @include('partials.hero-neural-network') --- ## Gait & Locomotion URL: https://noldus.com/solutions/gait-locomotion Description: Gait an locomotion are important readout parameters for a variety of diseases. On this page you can read about what gait is and how to measure it. Gait and locomotion What is it? Why measure? Webinar How to measure Contact @include('partials.hero-auroral') Gait and locomotion The assessment of gait is an important part of research into conditions that affect the central and peripheral nervous system. However, there are many ways to measure gait, and even more parameters to measure. Gait can be measured in a variety of ways. From manual methods to sophisticated automated systems. Every method has its advantages and being informed on them makes sure you have the right tool for the job. Are you looking for advice on your application? What is gait & locomotion? The gait cycle is the repetitive movement of a paw, occurring while the animal is walking. It begins when the heel of the rodent touches the ground (defined as initial contact) and ends when that same heel touches the ground again. The gait cycle can be divided into two phases: - The stance phase: the paw is touching the ground, which starts with braking and ends with propulsion. - The swing phase: the paw is moving in the air. Many conditions that affect the nervous system influence motor & cerebral function. Gait is a great way to observe how interventions affect the way these conditions progress and are therefore essential in developing treatments. Learn more with a free E-book Limited time deal Gait analysis has never been more accessible CatWalk is the most used gait analysis system worldwide, and now is the best time to add one to your lab. - check New CatWalk 11 hardware with high-quality camera - check Intuitive software allowing for detailed gait analysis - check Additional remote training and installation assistance All of this for only €39.500 *Desktop not included. Receive a quote Why should I measure gait and locomotion? There are many conditions and diseases that affect the gait of an animal. Humans that suffer from these conditions are often examined by looking at their gait. Therefore, observing gait in your model animals has great translational value. Some conditions that have an influence on gait are: - Ataxia - Parkinson's - Alzheimer's - Injuries (TBI, SCI, SNI, Pain) - Arthritis Gait research webinar Data storytelling: a CatWalk XT tale Join Jason Rogers, for CatWalk XT: How and why to use data to tell a compelling story. In this webinar, we tell you more about CatWalk XT understanding the main parameters, and use CatWalk XT data to describe research models such as arthritis, spinal cord injury, and traumatic brain injury. How do you measure gait and locomotion? There are a variety of ways to measure gait in rodents. Traditionally, researchers have used paw inking to manually measure the gait parameters. However, nowadays there are more automated and accurate ways to measure gait and locomotion. Free walking During free walking an animals gait is observed while walking across straight line. One version of free walking is the paw-inking methods. However, this method is time-consuming and can be inaccurate. Automated systems like CatWalk XT allow you to measure a great variety of parameters in a fraction of the time. - Free walking causes less stress than treadmill systems, therefore making results more reliable - Automation makes data more accurate and gives more options for parameters to measure - Measuring gait on a straight walkway represents human gait analysis more than treadmills or open fields Therefore, the test with the highest translational value for disorders that impact gait also features some sort of free walking. BBB scoring The Basso, Beattie, and Bresnahan (BBB) scale is a widely used method for assessing locomotor recovery after spinal cord injury in rodents. In BBB testing, animals are observed in an open field, and their movements are scored based on specific criteria like joint movements, coordination, and paw placement. - Allows for the assessment of severly injured animals. The problem a researcher might encounter with BBB scoring is that it has to happen live and is subjective to the observer. That is were The Observer XT from Noldus comes in. With The Observer you annotate live but also at a later date. Data is easily recorded and analyzed and exported, saving time converting from paper to computer. Running wheel The running wheel is a method to test voluntary exercise and activity in rodents. Usually the wheel is included in a home-cage to facilitate the voluntary aspect of the running wheel. - Data is collected automatically without human intervention. In order to use a running wheel to test locomotion, you need an automated system to track the wheel's usage. EthoVision XT and PhenoTyper are the ideal hardware and software combination to measure exercise in a running wheel. Activity Animals that have impaired gait are less active. Therefore, measuring how active an animal is in their environment gives a good indication of the effect of environmental conditions and medical interventions and conditions. However, manually measuring overall activity over time is laborious and time-consuming. With EthoVision XT you can automatically track many different types of animals and easily record their activity over an extended period of time. Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Your browser does not support the video tag. @include('partials.hero-neural-network') --- ## Home Cage & Welfare URL: https://noldus.com/solutions/home-cage-welfare Description: Learn all about long term behavioral observations in rodents. What it is, why you should consider it and how you measure behavior for a longer duration. Long term behavior observation What is it? How to measure Featured resources Contact @include('partials.hero-auroral') Long term behavior observation "Standard" tests such as the open field or elevated plus maze provide a snapshot of animal behavior. Observing during pre-determined time points can drastically change the outcome of a study. Therefore, it is important to consider whether these tests are ethologically viable for the model you are researching. Gaining a more complete and relevant behavioral readout can be achieved with home cage testing. Are you looking for advice on your application? What is long term behavioral observation? Long-term behavioral observation involves continuously monitoring rodents in a specialized homecage environment over extended periods. This approach allows researchers to capture natural behaviors that might be missed in short-term or maze-based studies. - Mimics natural living conditions, providing a stable setting for prolonged observation - Enables study of feeding patterns, drinking habits, and day/night activity cycles - Uncovers subtle behavioral patterns and responses to environmental or experimental changes Learn more with a free E-book Why should I measure behavior long term? Performing research in the homecage comes with a variety of advantages: - Reduce stress and capture natural behaviors: Conducting tests in the homecage minimizes stress by keeping animals in a familiar environment with less handling, leading to more authentic behavioral observations. - Reveals comprehensive behavioral patterns: Extended observation allows researchers to uncover the full spectrum of an animal's behavior, providing a more complete and accurate understanding. - Enhances Translational Value: For certain models, long-term observation in the homecage increases the relevance of the research, offering insights that are more applicable to real-world conditions. How do you measure behavior over a longer time Feed and water consumption Researchers struggle with accurately monitoring feed and water consumption due to the time-intensive nature of manual observations. The PhenoTyper, equipped with the Lick 'o Meter and Mouse Feeding Monitor, automates the tracking of feeding and drinking behaviors, reducing manual workload and ensuring accurate, reliable data collection. Circadian rhythm Observing nocturnal rodents during both day and night poses challenges, as continuous monitoring requires specialized equipment. The PhenoTyper simplifies this by automating continuous observations over several days. With its IR translucent shelter, the system tracks rodents around the clock, ensuring comprehensive data collection on circadian rhythms. Natural behavior Traditional behavioral tests often focus on specific actions, overlooking a wider range of natural behaviors. EthoVision XT, combined with the Behavior Recognition Module, automates the categorization of behaviors like grooming and play, providing unbiased, detailed analysis that would be challenging to achieve manually. Featured resources Blog The many uses of the PhenoTyper With its new top unit, the PhenoTyper is even more versatile than before. Follow in the footsteps of those who have already added the PhenoTyper to their lab and learn all about its varied applications. Read this blog post Webinar Phenotyping your rodents: Mapping short- and long-term studies In this talk, we investigate how animal research can be extended in to long-term observations, following the path human research has entered for some time already which resulted in great new insights. Watch webinar Webinar Phenotyping your rodents: Mapping short- and long-term studies Investigate how animal research can be extended into long-term observations, following the path human research has entered for some time already, which has resulted in great new insights. Watch webinar Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Your browser does not support the video tag. @include('partials.hero-neural-network') --- ## Human Factors Research URL: https://noldus.com/solutions/human-factors Description: Human factors and ergonomics is the application of psychological and physiological principles to the engineering and design of products, processes, and systems. Human Factors What is it A day in the life Best practices Training & Consulting Success Stories Contact @include('partials.hero-auroral') Human Factors In human factors and ergonomics, you're at the center of every design choice. By applying insights from psychology and physiology, this approach aims to reduce human error, enhance efficiency, and make interactions safer. - How do users interact with your website or product? - What is the role of emotions and attitudes in user experience? - How do people use and interact with your product? Are you looking for advice on your application? What is Human Factors and ergonomics research? Human factors and ergonomics research focuses on understanding why people behave the way they do and improving the design of products, processes, and systems. The main goal is to reduce human error, increase productivity, and enhance safety and comfort with a specific focus on the interaction between the human and the thing of interest. By applying psychological and physiological principles, this research area helps reduce errors and optimize performance. Trusted tools for Human Factors research Noldus tools like The Observer XT and NoldusHub are widely trusted in Human Factors research across aviation, automotive, and maritime sectors, especially in high-stakes, time-critical environments where precision and reliability are essential. These tools support complex experiments and give precise statistics, like task completion times and error rates. This enables you to combine behavioral data and video with physiological signals, eye tracking, sensor readings from a bridge or flight simulator, and more. A day in the life of a Human Factors researcher As a human factors researcher, your day revolves around optimizing the interaction between people and systems, whether in maritime, automotive, or aviation fields. You apply psychological and physiological principles to design products and processes, focusing on aspects like cognitive load, workload, and decision-making. Reduce human error with data-driven insights Your goal is to reduce human error, boost productivity, and enhance safety and comfort. By studying ergonomics, you examine how human activities impact both mind and body, analyzing physiological responses and muscle strain. Using tools like NoldusHub, you integrate system data to understand behaviors in their full context, ensuring designs are user-friendly and efficient. Discover how Noldus can support you in achieving all of this. Best practices for Human Factors research User-centered design Prioritize the needs, abilities, and limitations of the end-users throughout the design process. Involve users early and often to ensure products and systems are intuitive and effective. Iterative testing Conduct iterative testing and evaluation throughout the development process. Regularly test prototypes and gather user feedback to identify and address potential issues early on. Multi-disciplinary approach Collaborate with experts from various fields such as engineering, psychology, and ergonomics. A diverse team helps in addressing different aspects of human-system interaction. Contextual analysis Study the environment in which the system will be used. Understanding the real-world context, including physical, social, and organizational factors, helps in designing more effective solutions. Objective measurements Utilize objective measurements such as physiological responses, eye tracking, and workload assessments to gain insights into user interactions and cognitive load. Comprehensive data analysis Analyze data thoroughly to uncover patterns and insights. Use various analysis techniques to interpret both quantitative data (like survey results) and qualitative data (like interview transcripts). Risk assessment Identify and assess potential risks associated with human interaction with the system. Implement strategies to mitigate these risks and enhance safety and usability. Focus on ergonomics Consider ergonomic principles to reduce physical strain and discomfort. Analyze how users interact with controls, displays, and interfaces to ensure they are designed for comfort and efficiency. Comprehensive training and documentation Develop thorough training programs and documentation for users. Proper training and clear instructions help users operate systems safely and effectively, reducing the risk of human error. Training and consulting services Besides training you and your colleagues in the art of usability testing and Human Factors research, Noldus' professionals can also assist you when performing your experiments or take care of one or more of the stages of the testing process: - Set up a test lab in an environment you describe as typical of that in which your products will be used. - Set up the test itself. Together we identify the relevant characteristics of your users and create a task list, consisting of all key tasks to be performed with your product. To support and services Customer success stories Customer story Hofstra University The Behavioral Research in Business Laboratory is a state-of-the-art facility at Hofstra University in Hempstead, New York. The Business Lab is specifically designed to conduct multi-disciplinary behavioral research and has been fitted with advanced software and hardware to design and conduct human behavior studies, and analyze the research data. Watch this user story Customer story MARIN - Maritime research institute Hans Huisman shows us around a state-of-the-art ship bridge simulator at MARIN: one of the world's leading maritime research institutes. A full ship's crew can be trained and observed at their simulators, in which they can be introduced and trained to all kinds of challenging conditions. Watch this user story Customer story Ede Christian University of Applied Sciences (CHE) The UX lab that is set up at the Ede Christian University of Applied Sciences is intended to study human behavior. For example students' behaviors during mock interviews or when they are practising conversation skills. Watch this user story Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Neuroscience Research URL: https://noldus.com/solutions/neuroscience-research Description: Human neuroscience research requires software that combines and synchronizes different types of data . Noldus has the solutions you need! Neuroscience Product portfolio A day in the life Methods Contact @include('partials.hero-auroral') Neuroscience Understanding the brain's complex mechanisms behind cognitive and social behaviors is no small feat. It requires more than data—it demands the right tools. Whether you're exploring human behavior or researching disease models, Noldus provides the solutions to simplify your process. This allows you to focus on what truly matters: advancing scientific discovery. - Effortless data integration - Built for your research needs - Maximize your time on discovery, not logistics Are you looking for advice on your application? Innovative solutions for neuroscience research When we want to understand the motivations and cognitive processes behind human behavior, it is crucial to combine insights from both behavioral and physiological responses. Check out our portfolio of tools and solutions for neuroscience research. Free product portfolio A day in the life of a neuroscience researcher A human neuroscience researcher's day is a balance of complex tasks—from conducting experiments to managing vast amounts of sensitive data. The day might start by reviewing results from the previous study, ensuring all data is ethically handled and securely stored. Then it's time to run new experiments, integrating physiological, behavioral, and cognitive data to explore how the brain responds. Understanding the brain's role in human behavior The researcher collaborates with colleagues, sharing insights and refining methodologies based on new findings. Managing equipment and ensuring that all software functions smoothly are ongoing responsibilities. With a clear focus on discovery, every task contributes to better understanding the brain's role in human behavior, helping to push the boundaries of science. Neuroscience research includes a wide range of methodologies, such as EEG, fNIRS, physiology, eye-tracking, and facial expression analysis. A synchronization platform is at the heart of it all. Methods for understanding the human brain Neuroimaging techniques Neuroscience research utilizes a wide range of methodologies, each offering unique insights into brain function. Some non-invasive imaging techniques include: - Electroencephalography (EEG): Measures electrical activity, commonly used to study brain waves during different mental states. - Functional Near-Infrared Spectroscopy (fNIRS): Uses near-infrared light to detect changes in oxygenated blood. Also, fNIRS is portable. Together, these diverse methods provide researchers with a comprehensive toolkit to unravel the complexities of the brain and deepen our understanding of how it drives human behavior. Behavioral experiments Gaining a comprehensive understanding of brain function requires not only advanced tools but also methodologies that integrate data from multiple perspectives, such as: - Video observation: The solution for creating recordings to capture behaviors and interactions of your participants. - Coding video observations: To be able to analyze behaviors properly. Also, a visualization of the coded behaviors gives you a clear overview. Behavioral experiments offer invaluable insights into how the brain's internal processes manifest in observable actions, bridging the gap between neural activity and real-world behavior. Psychophysiology Bodily responses help understand how the brain and body interact in various psychological states. Some psychophysiology techniques include: - Multimodal research: Get a comprehensive view of participants' behaviors and physiological responses with the click of a button. - Facial expression analysis: The face gives a glimpse into emotional experiences. This helps in understanding how emotions manifest. A combination of physiological and behavioral data can provide you with essential information that will help you to further understand and explain your participants' behaviors. Don't know where to start? We're happy to help Book a meeting for an online or onsite session. Together, we can discuss your research requirements and come up with the best solution! Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Psychology Research URL: https://noldus.com/solutions/psychology-research Description: Many people are fascinated by human behavior. Why do we act the way we do? How is our behavior influenced? Psychology Areas of research A day in the life Uncover answers Best practices Featured resources Contact @include('partials.hero-auroral') Psychology As a psychologist you are concerned with understanding the principles of behavior, including how individuals learn, make decisions, and respond to different stimuli. Questions you would like to answer are for example: - How do we learn new behaviors and habits? - What factors shape our decision-making and actions? - How do our surroundings and social interactions affect our behavior? Are you looking for advice on your application? Areas of psychology research Blog Developmental psychology What shapes our growth, from childhood to adulthood? How do we acquire language, develop emotional bonds, or build our identity? These questions are at the heart of developmental psychology – the study of how we evolve emotionally, cognitively, and socially. Check out this blog post Blog Behavioral psychology Have you ever wondered why you behave in a certain way or what drives your actions? Behavioral psychology studies the connection between our minds and our behavior, how our surroundings and social interactions affect our feelings and choices. Check out this blog post User story Clinical psychology What helps people manage anxiety, agitation, depression, or trauma? Clinical psychology seeks to answer that by understanding, diagnosing, and treating mental health challenges through assessments, counseling, and tailored treatment plans. Check out this user story A day in the life of a psychologist In your role as a psychologist, your day involves juggling a wide range of tasks, making you a true jack-of-all-trades. Beyond designing and conducting your (clinical) research, you're responsible for many other critical aspects. You must handle personal data with care, navigate ethical considerations, engage with a range of stakeholders, stay updated on the latest techniques, ensure your software runs smoothly, and manage vast amounts of data. Combine your insights to make sense Given that human behavior is shaped by a complex web of factors, studying it requires an integrated approach. By combining insights from various perspectives, you can make sense of this complexity and gain a clearer understanding of human behavior. Psychology includes a wide range of subfields, such as developmental psychology, behavioral psychology, and clinical psychology. How to uncover answers Observations To gather real-life data on actions and interactions of children, adolescents, or adults you can watch how they behave in natural or controlled settings. - Video observation is a non-invasive form and will enable you to capture (inter)actions. Multiple camera views create new perspectives on the same behavior. - To be able to analyze behaviors properly, you need to review and code your video observations. - To discreetly observe and analyze participants in a naturalistic yet controlled setting an observation lab would suit perfectly. Behavioral experiments Running tests in a controlled setting can help you identify cause-and-effect relationships and uncover the underlying mechanisms that drive people's actions. - To capture reactions to stimuli or how participants perform a task, video recordings are indispensable. - Statistical methods will help you analyze data and identify significant patterns. After all, you want reliable results for your publication. - Behavioral experiments typically take place in controlled environments such as a research lab. Benefit of precise control and access to advanced technology. Psychophysiological tests By measuring bodily responses you can understand how the brain and body interact in various psychological states. - By integrating various data streams you get a comprehensive view of participants' behaviors and physiological responses. - Combining facial expression analysis with physiological data gives a fuller picture of emotional experiences. Best practices for psychology research Free product portfolio Clear hypotheses and objectives Define the research hypotheses and objectives before starting the study. This helps to focus the research, guide the experimental design, and ensure that the study addresses specific, measurable questions. Ethical considerations Ensure all research follows ethical guidelines, including obtaining informed consent, ensuring confidentiality, and minimizing harm to participants. Ethical review boards should approve studies to protect participants' rights and well-being. Rigorous experimental design Use well-structured experimental designs that include control groups, randomization, and blinding when possible. This helps to eliminate biases and allows for more reliable and valid results. Accurate and reliable measurement Use validated and reliable measurement tools and techniques to collect data. This includes standardized tests, well-constructed surveys, and precise observational methods to ensure the accuracy and consistency of the data. Comprehensive data analysis Employ appropriate statistical methods and software for data analysis. This includes understanding and applying the correct statistical tests, addressing potential confounding variables, and ensuring that the results are interpreted correctly and transparently. Replication and peer review Encourage the replication of studies to verify results and enhance the robustness of findings. Additionally, submitting research for peer review helps to identify potential flaws, improve the quality of the study, and ensure that the research meets the standards of the scientific community. Featured resources Video Identify differences in behavior and brain development Because there is still so much to learn about early brain development, lots of research is done at the Baby & Child Research Center. Watch customer success story Customer story Examine infants' evaluations of moral dilemmas At the Centre for Infant Cognition researchers look at minute eye gaze changes, hand gestures, and emotions of infants while they are observing a moral dilemma or social interaction. Read this user story Blog Gain insight in cognitive delays in infants with Down syndrome Researcher Fidler and her colleagues aim to understand more about early cognitive development in people with Down syndrome so that we can improve preventative care. Discover more in the blog post Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Social Interaction URL: https://noldus.com/solutions/social-interaction Description: The study of social interaction can be done in a variety of set-ups, all having one thing in common: the study of behaviors between two or more animals. Social interaction What is it? How to measure Featured resources Contact @include('partials.hero-auroral') Social interaction Social behaviors are an important part of many animals' behavioral spectrum. Social behaviors encompass any behavior that is produced to or in response to another animal. Many laboratory animals like rodents and zebrafish naturally live in groups. Therefore, it is very important to consider not only what social behaviors an animal produces, but also how a social context influences all behaviors. Are you looking for advice on your application? What is social interaction? Even though some animals are more social than others, every animal experiences social interaction. Many different types of behaviors are categorized as social behaviors. For example: - Grooming - Aggression - Mating Observing these interactions gives insight into the way animals respond to social cues and how these are influenced by genetics, environment and other developmental factors. Why should I measure social interaction? Social interaction is essential for gaining a complete understanding of your animal models' behavior, especially for researchers studying developmental disorders. Conditions like autism, depression, and schizophrenia significantly impact how animals interact with others, making the study of these behaviors vital. - New treatment insight: Studying animal social interactions reveals key data on mental health disorders - Accelerating human therapies: These studies directly advance new treatments for people - Higher welfare standards: Measuring behavior in a social context is becoming an important standard for ethical animal research How do you measure social interaction Measuring behavior in a social context Measuring social interaction is not only about looking at so called "social" behaviors. The presence of cage mates during testing can have a major influence on the test outcome. Due to welfare, more and more researchers are considering housing animals even during testing. EthoVision XT 18, with its improved social interaction module, in combination with PhenoTyper is the ideal hardware and software combination to observe multiple mice at the same time. Sociability chamber The three-chamber test is a behavioral assay to study social interaction and preference in rodents. During the test, an animal is placed in the middle of a chamber that connects to two side chambers. EthoVision XT can help you automate the measurements, making it easy to measure parameters like time spent near novel animal, entries into chambers and general movement patterns. Live Mouse Tracker Live Mouse Tracker (LMT) was developed by Institut Pasteur to track multiple mice in a singular arena. Through the use of RFID, computer vision and AI, LMT is able to track up to four mice at the same time. With EthoVision XT, LMT data can easily be imported, allowing for easier organization and analysis of data. Ultrasonic vocalizations Various animal species emit vocalizations as a form of communication during interactions with another animal. Detecting these sometimes ultrasonic vocalizations can give greater insight into the affective state of the animal. UltraVox is ideal for measuring these (ultrasonic) vocalizations. With the software you can easily collect, analyze and visualize your results. Shoaling Shoaling is not only the practice of fish moving together, it involves a series of complex social dynamics like following, turning and moving as a collective in response to external stimuli. EthoVision XT allows you to track multiple fish at once or one zebrafish that is responding to a video or fish in a neighboring tank. Featured resources Blog Did you know you can (semi) socially house tethered animals? Socially housing tethered animals can be challenging, but also crucially beneficial to your study. Read more about how with our PhenoTyper we can solve that dilemma! Read this blog post Webinar The dilemma of individual versus social housing of mice This webinar shows that how you house your animals can greatly influence the outcome of your research. Which form of housing is most adequate and/or relevant for your research? Watch webinar Webinar Social housing and its influence on research In this webinar we explain how housing your animals can greatly influence the outcome of your research. Is social housing the most adequate and relevant for your research? Watch webinar Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Your browser does not support the video tag. @include('partials.hero-neural-network') --- ## Ultrasonic Vocalizations URL: https://noldus.com/solutions/ultrasonic-vocalizations Description: Want to learn more about the significance and how to measure vocalizations in animals? On this page we tell you all about it. What are USVs Why measure How to measure Featured resources Contact @include('partials.hero-auroral') Ultrasonic vocalizations Even though animals might not be able to use language like we do, there is much to gain from listening to the animals we test. Birds, rodents and other mammals have a wide range of vocalizations that they are able to perform. These vocalizations can give great insight into the behavior of these animals and offer a broader spectrum of analysis into the effect of potential interventions. Are you looking for advice on your application? What are ultrasonic vocalizations? Each species of animal has an unique range of vocalizations that it can produce. For some species the frequency of the sounds they produce lie outside of the hearing range of humans (20Hz-20kHz). - Mice can vocalize up to 110kHz - Rats calls can reach 80kHz Furthermore, animals don't just make one sound, but have a variety of calls. These calls are a response to certain internal and external stimuli, and reveal a lot about the physical and mental state of an animal. Why should I measure ultrasonic vocalizations? Animal calls are indicative of their affective state. This means you can use the type of calls an animal makes as an indicator for welfare. - Stress calls: Stress calls depend on the cause (isolation, alert, pain). Vocalization data can reveal stress responses that may not be captured by behavior or physiology alone. - Positive calls: Some animals, like rats, make specific calls when having positive experiences, such as during play or being tickled. Vocalizations are an effective way to assess positive states in these species. - Communication: Vocalizations play a key role in animal communication, especially during mating and mother-offspring interactions. Monitoring calls during social trials offers deeper insights into group dynamics. Measure ultrasonic vocalizations How do you measure vocalizations? Understanding animal vocalizations requires precise measurement of multiple acoustic parameters. Each parameter reveals different aspects of vocal behavior and communication. equalizer Spectrograms If you want to visualize the calls made by animals you can use a spectrogram. Spectrograms display the frequency over time in a graph, making it possible to identify calls, as different calls show varying structures. tag Number of calls The number of calls represents how often an animal vocalizes during a given period. Counting the calls helps determine the level of vocal activity, revealing insights into social behavior, stress responses, or communication patterns. timer Call duration Call duration measures how long each vocalization lasts. This parameter is crucial for understanding communication, as different types of calls may vary in length, indicating specific behaviors or emotional states. graphic_eq Dominant frequency Dominant frequency refers to the frequency at which the most energy in a call is concentrated. It is a key feature in distinguishing between different types of calls, helping researchers identify specific species, individual animals, or even emotional states. volume_up Mean amplitude Mean amplitude indicates the average loudness of a call. This measurement helps assess the strength or intensity of vocalizations, which can be related to the animal's size, physical state, or environmental influences. noise_aware Background noise Background noise is any sound that isn't part of the vocalization but is present in the environment. Measuring and accounting for background noise ensures that vocal data remains clear and reliable, especially in noisy settings. Featured resources Blog Sunshine and romance: ultraviolet light enhances sexual behavior Ultraviolet B rays in sunshine enhances our romantic passion. How this actually works is still largely unknown. Research at the Tel Aviv University provides new insights. Read this blog post Blog How to analyze bird calls with UltraVox: a summer love on a spectrogram UltraVox is used to study ultrasound vocalizations, especially in rodents and bats. But the fact that it analyzes full-spectrum sound, makes it ideal for analyzing bird calls. Read this blog post Blog Examples of animal behavior research Researchers in ethology are interested in understanding all aspects of animal behavior. We have highlighted some great examples of Animal Behavior Research on our Behavioral Research Blog. Read this blog post Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## UX Research URL: https://noldus.com/solutions/ux-research Description: UX research focuses on discovering and understanding behaviors, needs, and motivations of users through observation, task analysis, and other feedback methodologies. UX Research What is it A day in the life Best practices Success Stories Contact @include('partials.hero-auroral') UX Research Reliable data is very important for user-centered design processes. While you observe the user of your product, you can receive direct feedback about your product. Is it being used in the way you meant it to, or does it need to be adjusted? - How do users interact with your website or product? - What is the role of emotions and attitudes in user experience? - How do people use and interact with your product? Are you looking for advice on your application? What is User Experience (UX)? User experience (UX) is all about how you feel while using a product, like a website or app, and the emotions and attitudes you have during that interaction. UX research dives deep into understanding your behaviors, needs, and motivations through observation, task analysis, and feedback. UX research solutions Thorough user research ensures that products, systems, and services are designed with your preferences in mind, creating more enjoyable and efficient experiences tailored to you. Noldus provides both UX testing tools and complete user experience labs. Discover some UX labs that we've set-up with partners, and discover the best UX research tools for analyzing and visualizing your user research. A day in the life of a UX researcher As a UX researcher, your day is a dynamic mix of diverse tasks, like conducting research and analyzing user behaviors. You plan and execute user studies, develop interview questions, and uphold ethical standards in handling user data. Engaging with stakeholders is crucial to ensure user insights drive design decisions. By synthesizing data from observations, usability tests, and surveys, you create a complete view of user needs. Get the complete picture User experience is complex and requires a holistic approach. You gather data from usability tests, surveys, and interviews. This helps you form a complete picture of user needs, behaviors, and pain points. Such integrated analysis is key to understanding how people interact with products and services. Staying current with the latest tools and methodologies is part of your daily routine, ensuring your insights drive meaningful improvements in user experience. Discover how Noldus can support you in achieving all of this. Best practices for UX research Free product portfolio arrow_forward Define clear objectives Before starting your research, establish clear objectives. Know what you aim to discover or improve, whether it's understanding user behavior or identifying pain points in a specific process. Formulate hypotheses Develop hypotheses based on initial observations or assumptions. These guide your research direction and help you focus on specific areas that need investigation. Choose the right methods Select research methods that best suit your objectives, such as interviews, surveys, usability tests, or observations. Combining qualitative and quantitative methods often provides a more comprehensive view. Incorporate ethical considerations Always prioritize ethical practices by obtaining informed consent, ensuring user privacy, and handling personal data responsibly. Make sure participants are aware of their rights and the study's purpose. Engage in UX design collaboration Work closely with UX designers to align research findings with design improvements. Collaborating ensures that insights are translated into actionable design changes. Comprehensive data analysis Analyze data thoroughly to uncover patterns and insights. Use various analysis techniques to interpret both quantitative data (like survey results) and qualitative data (like interview transcripts). Present actionable insights Present your findings in a way that is easy for stakeholders to understand and act upon. Use visuals, reports, and presentations to communicate insights effectively. Document and share findings Keep a detailed record of your research process, findings, and insights. Sharing this documentation with your team and stakeholders helps ensure continuity and informs future projects. Stay user-centered Throughout the process, keep the focus on the users. Continuously validate designs against user needs and feedback to ensure the final product aligns with their expectations and requirements. Customer success stories Customer story Hofstra University The Behavioral Research in Business Laboratory is a state-of-the-art facility at Hofstra University in Hempstead, New York. The Business Lab is specifically designed to conduct multi-disciplinary behavioral research and has been fitted with advanced software and hardware to design and conduct human behavior studies, and analyze the research data. Watch this user story Customer story MARIN - Maritime research institute Hans Huisman shows us around a state-of-the-art ship bridge simulator at MARIN: one of the world's leading maritime research institutes. A full ship's crew can be trained and observed at their simulators, in which they can be introduced and trained to all kinds of challenging conditions. Watch this user story Customer story Ede Christian University of Applied Sciences (CHE) The UX lab that is set up at the Ede Christian University of Applied Sciences is intended to study human behavior. For example students' behaviors during mock interviews or when they are practising conversation skills. Watch this user story Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## Zebrafish Research URL: https://noldus.com/solutions/zebrafish-research Description: Zebrafish as a model for biomedical research. Noldus offers a wide array of solutions for research with zebrafish, both larvae and adult fish Zebrafish research Video tracking How to use Toolkit Solutions Contact @include('partials.hero-auroral') Zebrafish as a model for biomedical research The zebrafish (Danio rerio) is a popular model organism due to its size, reproduction and growth rate, cost effectiveness, and also its genetic homology with humans (~70%). Noldus offers a wide array of solutions for research in zebrafish. As experts in behavioral neuroscience, we're here to support and elevate your research. Are you looking for advice on your application? Video tracking for zebrafish Video tracking means that the software is able to detect the zebrafish in a video file or from a live video feed, distinguish it from its background, and track its whereabouts and movements. It tracks and analyzes the behavior, movement, and activity of zebrafish. Video tracking technology is versatile and enough to be very useful in many different behavioral tests. EthoVision XT is the industry leader in video tracking. Use as a standalone solution for video tracking, or pair with the DanioVision observation chamber, a complete system designed for high-throughput tracking of zebrafish larvae. How can you use zebrafish in research? Neurobiology & behavior The zebrafish has become an important vertebrate model to study (developmental) neurobiology and behavior, not in the least because of recent improvements in imaging techniques and behavioral assays. - Optogenetics - Social behavior Toxicology To protect human health, wildlife, and the environment, the effects of naturally occurring and synthetic contaminants need to be monitored. Zebrafish are valuable in these types of studies for many reasons. - Compound screening - Larvae activity Translational research Researchers have unraveled the molecular basis of many human disorders, and many of the genes we know to be associated with human disease (e.g., Parkinson's and epilepsy) have homologues in zebrafish. - Stress & anxiety - Learning & memory Your zebrafish research toolkit White paper Epilepsy research in zebrafish The development of accurate, high-throughput models for epilepsy research is crucial. Read how researchers use EthoVision XT to develop a multi-parametric analysis in zebrafish. Download White paper Zebrafish and learning paradigms Zebrafish have become an important animal model for studying neurodegenerative diseases. Download the white paper and learn more about zebrafish and learning paradigms. Free white paper Guidebook Basic behavioral neuroscience in zebrafish This essential guidebook will delve into the significant transformation zebrafish undergo through their developmental stages: from the embryonic stage to larvae, and finally adult zebrafish. Get the guidebook here Noldus solutions for zebrafish research EthoVision XT | Premium video tracking The world's most used video tracking tool, as well as a software platform to build your set-up on. Video tracking essentially means that EthoVision XT recognizes your zebrafish (adult or larva) from a live video feed or video file and is able to track its movement or activity. EthoVision XT DanioVision | Controlled testing environment The complete system designed for experiments with zebrafish larvae. It is for anybody performing research in drug development, safety pharmacology, behavioral genetics, circadian rhythmicity and related research areas. DanioVision DanioScope | Cardiovascularity and morphology The premier software tool to investigate a scope of zebrafish embryo and larvae parameters. It includes features to measure embryo activity, cardiovascular measurements, morphology, and gut and blood flow. DanioScope Track3D | Three dimensional video tracking A video-based system for automated tracking of animals in a three-dimensional space. It allows the researcher to record the movement of an animal in a test chamber, visualize the resulting trajectory in a three-dimensional image and calculate a number of movement parameters. Track3D Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... Your browser does not support the video tag. @include('partials.hero-neural-network') --- ## Zoology and Ethology URL: https://noldus.com/solutions/zoology Description: Learn all about how modern tools and systems can help you easily collect more valuable behavioral data. Noldus products have been used for many different species of animals. Animal welfare Automated systems Data streams Entomology Behavioral setup Contact @include('partials.hero-auroral') Modern systems in Ethology Studying animal behavior has come a long way from manual pen-and-paper methods. Advances in technology now provide faster and more accurate ways to record and analyze behaviors. Here's how these innovations are making research more efficient. Want to know which tools can help you in your research? Then, contact us to assist you in setting up your experiment. Are you looking for advice on your application? Animal welfare research Studying the behavior of livestock helps improve their health and living conditions. By tracking activities like feeding, resting, and social interactions, researchers can identify and address welfare concerns. - Changes in resting and feeding behavior can indicate impaired health or stress - Social behavior and activity are important to consider when designing and evaluating housing systems - Observing play and foraging behaviors evaluates the success of enrichment efforts Automated systems for zoology Understanding the behavior of animals in their natural environments or controlled settings like zoos is essential for conservation. Modern tools simplify the observation process, even in the field. - Zoo animals provide useful data on behaviors such as feeding and mating - Field studies reveal critical information about natural habitats, aiding conservation - Systems like Pocket Observer allow accurate behavioral annotations in the field Integrating multiple data streams Behavior alone doesn't tell the whole story. Combining behavioral data with physiological and environmental measurements gives a clearer picture of animal health and performance. - Physiological data like heart rate, vocalizations, and body temperature - Environmental data includes ambient temperature, humidity, and time sensitive data - Software like The Observer and EthoVision merges these datasets with behavioral data for more detailed analysis Entomology There are many reasons to study insect behavior. Because of its similar genetic makeup and well understood genome, Drosophila melanogaster (fruit flies) is often used in neuroscientific studies. Other insects are studied for their response to chemical compounds or as biological pesticides. - Flying insects can be tracked with the Track3D module for EthoVision - Plant resistance to certain insects can be assessed using the EntoLab system - More complex behaviors can easily be annotated using The Observer Enhance your behavioral setup Software The Observer The Observer simplifies the annotation of behaviors for zoo animals, livestock, or insects in natural or controlled environments. With The Observer, you can integrate multiple data streams, like physiological signals and environmental conditions, enabling detailed insights into health and welfare. Learn more Software EthoVision EthoVision is ideal for tracking animals live or from prerecorded videos. This allows you to track insects and small mammals and birds in an arena. EthoVision has been used to track insects in a 2D and 3D environment, observe movement in livestock animals, and analyse rodent behaviors. Start tracking Software TrackLab TrackLab excels in monitoring livestock behavior, helping researchers track activities like feeding, resting, and social interactions to improve animal welfare. TrackLab allows you to easily integrate data from environmental and wearable sensors into the analysis. This makes your data more insightful. Keep reading Are you looking for advice on your application? Do you want to learn more about how to apply Noldus products to your research, or do you need advice from our team of behavioral experts? Noldus is here to assist you throughout the whole process. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## UltraVox URL: https://noldus.com/ultravox Description: UltraVox analyzes sound, including ultrasonic vocalizations made by rodents. You can identify and analyze calls in all kinds of animals. UltraVox How It Works Pricing Features Explore Success Stories FAQ Contact Streamlined vocalization detection made easy UltraVox Seamlessly combine ultrasonic vocalization with behavioral data, allowing you to gain additional insights into the affective state of your rodents View pricing arrow_downward How does UltraVox work? mic Record Either import a previously recorded audio file or use the software to record the calls of your rodents. UltraVox is compatible with any digital microphone (USB or mini jack). Recorded vocalizations are displayed live as waveform and spectrogram. label Label Go to your recording, draw a box around a sample call, refine your settings and Ultravox will automatically label all other calls within those criteria. Calls can be defined for ranges of amplitude, frequency, duration and time gaps. analytics Analyze Instantly get statistics for your whole recording or export your data to a .csv file and analyze it with EthoVision, The Observer or a dedicated statistics program. Learn more {{pricing-eur:1439|usd:1440|restricted:1441}} Get the most out of your UltraVox setup Build your complete solution Hardware This section highlights compatible hardware items designed to work seamlessly with UltraVox. Choose a laptop and microphone to ensure a smooth setup and get up and running as quickly as possible, with the software pre-installed. Hardware UltraVox Microphone For recording rodent calls we recommend the Petterson M500-384 microphone (up to 4 simultaneously). Every microphone will be delivered with a holder. Contact Sales Laptop with USB Hub Connect your microphone directly to the laptop. Directly control from UltraVox when your recording starts and how long it lasts. Contact Sales Open Field 40x40x40 cm By combining vocalization data with classical behavioral tests like the open field, you will enrich your data by creating additional insights. Contact Sales NoldusCare Add an additional year of NoldusCare to keep your software performing at its best. Includes the latest features, ongoing technical support, and access to the Noldus Academy. The first year is included free of charge, with the option to extend your coverage. Additional NoldusCare Additional year NoldusCare for UltraVox Extend your NoldusCare coverage by one additional year. Includes software updates, technical support, and Noldus Academy access. € 630 Add to quote Remote training Ensure a strong start for you and your colleagues with our remote training sessions. Led by experienced Noldus trainers, these sessions help you quickly become familiar with the software. It's the fastest way start working efficiently from day one. Remote Training Essential remote training 2 hours of remote training for a maximum of 5 participants € 300 Add to quote Advanced remote training 5 hours of remote training for a maximum of 15 participants € 900 Add to quote Premium remote training 1 full day of remote training, unlimited participants € 1.750 Add to quote Hardware UltraVox Microphone For recording rodent calls we recommend the Petterson M500-384 microphone (up to 4 simultaneously). Every microphone will be delivered with a holder. Contact Sales Laptop with USB Hub Connect your microphone directly to the laptop. Directly control from UltraVox when your recording starts and how long it lasts. Contact Sales Open Field 40x40x40 cm By combining vocalization data with classical behavioral tests like the open field, you will enrich your data by creating additional insights. Contact Sales Additional NoldusCare Additional year NoldusCare for UltraVox Extend your NoldusCare coverage by one additional year. Includes software updates, technical support, and Noldus Academy access. € 630 Add to quote Remote Training Essential remote training 2 hours of remote training for a maximum of 5 participants € 300 Add to quote Advanced remote training 5 hours of remote training for a maximum of 15 participants € 900 Add to quote Premium remote training 1 full day of remote training, unlimited participants € 1.750 Add to quote Benefits of UltraVox Why should I use UltraVox? Rodents don't only show, they tell. However, no one has time to manually label and analyze individual calls. That is why UltraVox is a necessary tool for researchers trying to learn more about the affective states of their animals. See what's included hub Integrated with other Noldus Software With UltraVox you can not only analyze calls, but you can also correlate those calls with specific behaviors. By exporting UltraVox data into EthoVision you see how many calls an animal made in a certain zone in a maze or while performing set behaviors. speed Fast call analysis No MATLAB, no GPU, no weeks of troubleshooting. By selecting the call criteria UltraVox automatically labels all corresponding calls in the audio track. This gives you instant results and enables you to focus on your research. settings_input_component Plug-and-play setup Consistency is key, also in vocalization tests. Luckily, UltraVox works perfectly together with PhenoTyper, our instrumented home cage environment. Together they create a powerful combination to track behavior and record calls simultaneously. pets Not only rodents Rodents are not the only animals that will try to tell you something through their calls. UltraVox can also be used to analyze other mammals, birds or even insect sounds. If it makes a sound UltraVox can analyze it. Explore further Publications Browse peer-reviewed research papers and scientific publications that reference this product in their methodology. Applications Discover the industries, research areas, and real-world scenarios where this product delivers results. Setup Learn about hardware requirements, software configuration, and how to get your system up and running. More about UltraVox Learn more about the ins and outs of ultrasonic vocalizations Webinar What is your animal trying to tell you? UltraVox indepth webinar New to vocalization research? Then, check out this webinar by Matt Feltenstein. He explains the theory of rodent vocalizations, why this matters and how to analyze it with UltraVox and EthoVision. Research Heinrich Heine University Social learning tasks in Rats PI Dr. Marijn van Wingerden and his PhD student Sander van Gurp study social learning behavior in rats. Their Social Rat Lab uses video tracking software EthoVision and UltraVox for their behavioral studies. Your browser does not support the video tag. Frequently asked questions about UltraVox What is the added value of measuring vocalizations of animals? Full understanding of an animal's response to internal or external stimuli requires measurement of multiple biomarkers, including behavioral and acoustic parameters. The simultaneous tracking of behavior and vocalizations deliver insights that cannot be obtained by measuring either segment alone. How many microphones can be connected to one computer? UltraVox can work with as many as 16 microphones connected to a single computer (via a USB hub). However, in practice most researchers use 1 to 4 microphones attached to one PC. Which microphones are supported by UltraVox? UltraVox works with any analog or digital microphone that is recognized by Windows as a microphone. We recommend the use of a digital microphone. UltraVox 4 has been successfully tested with the Pettersson M500-384 and u38, Dodotronic Ultramic 250K and 384K EVO, and Avisoft CM16/CMPA. Can I import UltraVox output into other software programs? Yes, UltraVox can export time-stamped vocalizations in log files that can be loaded into The Observer or EthoVision, automatically synchronized with your movement tracks or behavioral events. This allows you to do a truly integrated analysis of behavior and vocalizations. Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## UltraVox Applications URL: https://noldus.com/ultravox/applications Description: Discover UltraVox applications for ultrasonic vocalization recording and analysis in rodent research. @include('partials.hero-auroral') Back to UltraVox Ultrasonic vocalization detection made easy UltraVox applications What are your animals saying? UltraVox offers advanced capabilities that streamline the analysis of vocalizations, providing you with detailed insights to advance your research. - Full spectrum sound - Automatically detect and label calls - Easy export of data Try it for free How does UltraVox work? UltraVox 4 introduces a significant enhancement in its software architecture, designed to better serve the needs of animal behavior researchers. USB microphones record full spectrum sound from up to four arenas simultaneously. UltraVox can also analyze imported audio. Data are easily exported to your favorite video tracking platform, such as EthoVision XT. UltraVox 4 includes: - checkVocalization analysis faster than real-time - checkBatch processing of sound files - checkDynamic visualization settings UltraVox successes and strategies Webinar What is your animal trying to tell you? EthoVision XT is great for telling you "where" your subject is, but did you know Noldus also has you covered for "what" your subject may be trying to tell you: UltraVox! Customer story Can rats learn from each other? Dr. Marijn van Wingerden and his PhD student Sander van Gurp study social learning behavior in rats. Their Social Rodent Lab uses EthoVision XT and UltraVox for their behavioral studies. Featured blog posts Blog Sunshine and romance: Ultraviolet light enhances sexual behavior Ultraviolet B rays in sunshine enhances our romantic passion. Research at the Tel Aviv University provides new insights. Read this blog post arrow_forward Blog UltraVox & EthoVision XT paired in a mouse social discrimination task Rodents are social creatures, but what happens when mice are used to study neurodevelopmental disorders, such as Autism Spectrum Disorder? Read this blog post arrow_forward Blog How to analyze bird calls with UltraVox UltraVox analyzes full-spectrum sound, making it ideal for analyzing bird calls. Summer love on a spectrogram. Read this blog post arrow_forward Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## UltraVox Publications & Resources URL: https://noldus.com/ultravox/publications Description: Explore publications and resources for UltraVox ultrasonic vocalization analysis. Back to UltraVox UltraVox Publications and resources Want to learn how UltraVox can help you listen to your animals? Learn more below or click the button to get in touch. Let's connect UltraVox Selected publications Here is a selection of recent papers that mention the use of UltraVox. If you feel your paper should be on this list, please let us know at marcom@noldus.com. Fragile X Syndrome vocalization Giua, G., Iezzi, D., Caceres-Rodriguez, A. et al. (2024). Sex-specific modulation of early life vocalization and cognition by Fmr1 gene dosage in a mouse model of Fragile X Syndrome. Biology of Sex Differences, 15(18). Playful behaviour in rats Tivey, E.K.L., Martin, J.E., Brown, S.M. et al. (2022). Sex differences in 50 kHz call subtypes emitted during tickling-induced playful behaviour in rats. Scientific Reports, 12, 15323. Cannabidiol exposure effects Iezzi, D., Caceres-Rodriguez, A., Chavis, P. et al. (2022). In utero exposure to cannabidiol disrupts select early-life behaviors in a sex-specific manner. Translational Psychiatry, 12, 501. Pain-related vocalizations Presto, P.; Ji, G.; Junell, R.; Griffin, Z.; Neugebauer, V. (2022). Fear Extinction-Based Inter-Individual and Sex Differences in Pain-Related Vocalizations and Anxiety-like Behaviors but Not Nocifensive Reflexes. Brain Sciences, 11(10), 1339. Vitamin D deficiency & autism Ali, A.; Vasileva, S.; Langguth, M.; Alexander, S.; Cui, X.; Whitehouse, A.; McGrath, J.J.; Eyles, D. (2019). Developmental vitamin D deficiency produces behavioral phenotypes of relevance to autism in an animal model. Nutrients, 11(5), E1187. Ultrasonic vocalization sex differences Budylin, T.; Guariglia, S.R.; Duran, L.I.; Behring, B.M.; Shaikh, Z.; Neuwirth, L.S.; Banerjee, P. (2019). Ultrasonic vocalization sex differences in 5-HT1A-R deficient mouse pups: Predictive phenotypes associated with later-life anxiety-like behaviors. Behavioural Brain Research, 373, 112062. "The combination of Noldus EthoVision for tracking the behavioral state and the position of the animal, in combination with Noldus UltraVox has allowed us to combine information positions, but also to keep track of the ultrasonic vocalizations that the animals are emitting. Now USVs are an important marker of the affective state of the animal." Dr Marijn van Wingerden Tilburg University, The Netherlands Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... --- ## UltraVox Setup URL: https://noldus.com/ultravox/setup Description: Learn how to set up UltraVox for recording and analyzing ultrasonic vocalizations. @include('partials.hero-auroral') Back to UltraVox Ultrasonic vocalization detection made easy UltraVox setup Everything you need to get started with UltraVox. From system recommendations to understanding how the software works — we've got you covered. - Full spectrum sound - Automatically detect and label calls - Easy export of data Try it for free System recommendations - checkWindows 10 or 11 Pro (64-bit) 23H2 or 24H2 - checkDesktop: Dell Precision 3680 or higher; Laptop: Dell 3591 Mobile - checkFor laptops: USB 3.0 hub: D-link 4-port DUB-1340, bit rate 5 Gbps - checkInternal memory (RAM) – at least 16 GB - checkSolid State drive - 500 GB (for data collection) - checkHard disk - 1 TB free space (to store experiments) - checkMicrophones: Pettersson M500-384, up to 4 - checkMaximum recording duration: 90 min How does UltraVox work? UltraVox 4 introduces a significant enhancement in its software architecture, designed to better serve the needs of animal behavior researchers. USB microphones record full spectrum sound from up to four arenas simultaneously. UltraVox can also analyze imported audio. Data are easily exported to your favorite video tracking platform, such as EthoVision XT. UltraVox 4 includes: - checkVocalization analysis faster than real-time - checkBatch processing of sound files - checkDynamic visualization settings Want more info? Curious about this product but not ready to decide yet? Just let us know what you need: more information, a price quote, a free trial, a demo, or an online meeting with one of our specialists. We're here to help you with the next steps to finding your solution. Thank you! We will get back to you within one business day. First name * Last name * Email address * Request * Make a choice Receive information Request pricing Free trial Free demo Book an online meeting Other Institute/company/department * How can we help you? * Phone number (optional) By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. Submit Sending... @include('partials.hero-neural-network') --- ## A Buyer’s Guide to the Perfect Video Tracking Setup URL: https://noldus.com/video-tracking-buyers-guide Description: Our video tracking buyer's guide lays out the groundwork for you and compares all the options out there on the market. Free buyer's guide A Buyer's Guide to the Perfect Video Tracking Setup Planning a video tracking setup for your lab? This guide covers everything from camera selection and arena design to software configuration and data analysis workflows. - checkChoosing cameras for video tracking - checkArena design and lighting - checkSoftware setup and calibration - checkMulti-animal tracking considerations - checkIntegration with other data streams Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free download Why video tracking? Video tracking automates the measurement of animal movement and behavior, saving hours of manual scoring while providing objective, reproducible data. Modern systems can track multiple animals simultaneously, detect social interactions, and integrate with external hardware. - checkAutomated locomotion analysis - checkZone-based activity measurement - checkSocial interaction detection - checkIntegration with optogenetics and physiology - checkBatch processing for high-throughput studies --- ## Webinars URL: https://noldus.com/webinars Description: Watch expert webinars on behavioral research methods, tools, and best practices from Noldus. Webinars Connect with experts and fellow Noldus users We're excited to host virtual meet-ups and Noldus user groups, offering you the opportunity to connect with our team, industry experts, and - most importantly - fellow Noldus users. These sessions are designed to inspire, educate, and foster collaboration within our community. Watch 30-minute talks, webinars, and technical briefings from our team and guest researchers. New sessions are added regularly. Missed one? All recordings are available on-demand. All Human pest_control_rodent Animal Human Webinar FaceReader Masterclass: Combining research tools This FaceReader Masterclass includes a demonstration of features such as heart rate measurement, webcam-based eye tracking, and voice analysis. Dr. Amy Harrison (UCL Institute of Education) presents a research case on using FaceReader, The Observer, and physiological measurements to study eating disorders. Duration: 68 minutes Noldus product: FaceReader Register and watch for free Animal Webinar Enhancing data quality: The influence of handling and data refinement during anxiety testing In this webinar, Ylva Vik, PhD student from the Norwegian University of Life Sciences, will present her experiences with using the elevated plus maze and open field test to assess anxiety in rodents. She elaborates on the impact handling and data refinement on the results of her experiments. Duration: 58 minutes Noldus product: EthoVision XT Register and watch for free Human Webinar Validating Baby FaceReader 9 Analysis of Infant Affective Facial Expressions in Face-to-Face Interactions In this webinar, Martina Zaharieva, PhD, will discuss her validation study on the performance of Baby FaceReader. Martina and her research team compared Baby FaceReader output to manual micro-coding of facial expressions of young infants during naturalistic social interactions. Duration: 46 minutes Noldus product: FaceReader Register and watch for free Animal Webinar No two mice alike: leveraging inter-individual variability in threat conditioning of inbred mice to model trait anxiety In this webinar Dr. Kovlyagina will provide insight into the methodology of their pipeline and how EthoVision XT contributed to it. Duration: 43 minutes Noldus product: EthoVision XT Register and watch for free Human Webinar Beyond the Familial: The Development of Emotional Communication with Mothers, Fathers, and Strangers In this webinar, Eliala Salvadori, MSc discussses her research involving infants and the complex communication strategies they use to interact with their parents and with strangers. Duration: 60 minutes Noldus product: FaceReader Register and watch for free Animal Webinar Do we actually understand what we mean by "anxiety" in rodents models of anxiety? In this talk, Dr. Mu Yang and Steffen van Heijningen will go over the major differences between contemporary, highly automated methods and “old school”, ethologically based methods of measuring behaviors. Duration: 60 minutes Noldus product: EthoVision XT Register and watch for free Animal Webinar The benefits of deep learning based rodent tracking in EthoVision XT In this webinar you get an overview of how you can use EthoVision XT to track rodents in situations that are just a bit trickier than normal. The power and ease-of-use of our advanced deep learning based tracking technique is showcased and applied to real world examples. Duration: 52 minutes Noldus product: EthoVision XT Watch for free on-demand! Human Webinar How emotions are made in Baby FaceReader Baby FaceReader™ can automatically measure facial expressions in infants ranging in age from 6 to 24 months old. In this webinar, we show you how to set up an experiment using Baby FaceReader (FaceReader version 9) and what the results look like. Duration: 38 minutes Noldus product: Baby FaceReader Watch for free on-demand! Animal Webinar Data Storytelling: A CatWalk XT Tale In this webinar, we tell you more about CatWalk XT understanding the main parameters, and use CatWalk XT data to describe research models such as arthritis, spinal cord injury, and traumatic brain injury. Duration: 55 minutes Noldus product: CatWalk XT Watch for free on-demand! Human Webinar Beyond basic emotions - Best practices when creating custom expressions For the analysis of, for example, workload, attention, or embarrassment, measuring a basic emotion is often not enough. Therefore, designing your own algorithms will help you out. Tess den Uyl provides some best practices and advice on how to use custom expressions for your benefit. Duration: 60 minutes Noldus product: FaceReader Watch for free on-demand! Animal Webinar Innovative Approaches to Tracking and Quantifying Behavior in Rodents Join Drs. Jason Rogers and De Wet Wolmarans for a deep dive into two research protocols for tracking, quantifying, and analyzing behaviors in rodent models. Duration: 60 minutes Noldus product: EthoVision XT Watch on-demand Human Webinar More Than Meets the Eye: Flavor Perception, Facial Expression Analysis, and Predicting Food Choice Behavior Join Jason Rogers, PhD and Geertje van Bergen, PhD as they take us on a sensory deep dive into flavor perception, facial expression analysis, and food choice and consumption behavior. Duration: 60 minutes Noldus product: FaceReader Watch for free on-demand! Animal Webinar UltraVox & EthoVision XT: What Is Your Animal Trying To Tell You? EthoVision XT is great for telling you “where” your subject is in any behavioral task, but did you know Noldus also has you covered for “what” your subject may be trying to tell you: UltraVox! Duration: 66 minutes Noldus product: EthoVision XT, UltraVox Watch for free on-demand! Human Webinar How to measure engagement from facial expressions In this webinar, Dayenne Sarkol-Teulings tells us more about what engagement is and how she performed an experiment to find out what an engaged face looks like. The results of her validation study will be highlighted as well. Duration: 44 minutes Noldus product: FaceReader Watch for free on-demand! Animal Webinar Walk This Way: Free-Walking & Treadmill Systems for Rodent Gait Analysis In this webinar, we discuss the different types of gait analyses, what are the advantages and disadvantages of each system, what do these systems offer behavioral research, and what can they say about an animal’s gait. Duration: 46 minutes Noldus product: CatWalk XT Watch for free on-demand! Human Webinar The psychophysiology of emotion In this webinar, we look at the relationship between emotions and psychophysiological measures such as heart rate and skin conductance. As we’ve already seen with facial expressions, people show a lot of variation in their facial expressions when expressing certain emotions, and the same holds true for physiological measures. Duration: 67 minutes Noldus product: FaceReader Watch for free on-demand! Animal Webinar How to set up DanioVision experiments This webinar is aimed to give you an overview of the DanioVision System, together with EthoVision for high-throughtput tracking. Duration: 65 minutes Noldus product: DanioVision, EthoVision XT Watch for free on-demand! Human Webinar What's In A Face: Project Analysis Module and Custom Expressions in FaceReader 9 In this webinar, Dr Jason Rogers demonstrates the updated features of FaceReader 9, including the new Project Analysis Module and Custom Expressions. Duration: 60 minutes Noldus product: FaceReader Watch for free on-demand! Animal Webinar The Dilemma of individual versus social housing of mice This webinar shows that how you house your animals, can greatly influence the outcome of your research. Which form of housing is most adequate and/or relevant for your research? Duration: 46 minutes Noldus product: EthoVision XT Watch for free on-demand! Human Webinar Behind the scenes of the Behavioural Lab at London School of Economics In this webinar, the London School of Economics (LSE) invite you to view their Behavioural Lab for Teaching and Research and let's you discover all the possibilities for researchers and how they apply Noldus tools. Duration: 44 minutes Noldus product: The Observer XT, Viso, FaceReader Watch for free on-demand! Animal Webinar Hiding in Plain Sight: EthoVision XT and Hidden Zones Join Matt Feltenstein, for hiding in plain sight: EthoVision XT and hidden zones. In this technical briefing, we cover everything you need, to do it right from the beginning Duration: 52 minutes Noldus product: EthoVision XT Watch for free on-demand! Human Webinar Research in Developmental psychology In this webinar, we explain how our research tools can be used to study the behavior of children. How do children acquire language, how do learning behaviors develop, and how do they interact socially with other people, for example in parent-child interaction? Duration: 56 minutes Noldus product: Viso, The Observer XT, FaceReader Watch for free on-demand! Animal Webinar CatWalk XT gait analysis in mice: The do's, don'ts and the pitfalls What is the added value of using automated gait analysis system in your research, what should you pay attention to when starting to use it, and how to avoid making the common mistakes? In this webinar, Dr. Lior Bikovski and Dr. Mu Yang explain all about it! Duration: 66 minutes Noldus product: CatWalk XT Watch for free on-demand! Human Webinar Inside a Behavioral Lab: Automatic synchronization and dynamic analysis of physiology, emotions and eye-tracking In this webinar we take you inside the Behavioral Lab and show you all about automatic synchronization and dynamic analysis of physiology, emotions and eye-tracking. Duration: 60 minutes Noldus product: FaceReader, The Observer XT Watch for free on-demand! Animal Webinar Don’t Fear the Procedure: EthoVision XT and Fear Conditioning In this webinar, we cover everything you need in EthoVision XT to do it right from the beginning: From using Activity analysis, to programming your Trial Control Settings, and analyzing timed events using the Data Profile. Let us show you the way so you don’t have to sweat, worry, or freeze. Duration: 63 minutes Noldus product: EthoVision XT Watch for free on-demand! Human Webinar How to measure emotions In this 30-minute talk, you will learn more about the theory of constructed emotions and how it differs from Ekman’s classical view on emotional expressions. Duration: 40 minutes Noldus product: FaceReader Watch for free on-demand! Animal Webinar Tips and Tricks in EthoVision XT: Insights Into the Unknowns In this webinar, we show you all the hidden tips and tricks that EthoVision XT has to offer. There’s a lot more than meets the eye, so we look forward to show you the way! Duration: 70 minutes Noldus product: EthoVision XT Watch for free on-demand! Human Webinar Simulation-based training: Why and how Why is simulation-based training important and what does a (medical) simulation-based training look like? In this webinar, professionals from the field answer these questions for you. Duration: 45 minutes Noldus product: Viso Watch for free on-demand! Animal Webinar Increasing Reproducibility and Reliability of Novel Object Tests Through Standardization and Automation Join Alicia Brantley, PhD for a deep dive into her work involving novel object tests, the challenges associated with these protocols, and the solutions she is exploring to overcome these challenges. Duration: 60 minutes Noldus product: EthoVision XT Watch on-demand Human Webinar Innovative methodologies for consumer behavior research In this webinar we highlight the recent innovations in consumer behavior research, with special attention to the methodologies employed for the study of sensory perception. Duration: 53 minutes Noldus product: The Observer XT, FaceReader online Watch for free on-demand! Animal Webinar Analysis of Spatial Behavior: Heatmaps in EthoVision XT EthoVision XT has a wealth of visualization tools and Heatmaps is one of the coolest. In this webinar, we take a look at how heatmaps work, and how you can get the most out of them. Duration: 48 minutes Noldus product: EthoVision XT Watch for free on-demand! Human Webinar How to integrate psychophysiological & behavioral data using both Noldus and BIOPAC tools In this joint webinar, we dive deeper into the benefits of integrating data seamlessly. How to study behavior and physiology using Noldus and BIOPAC tools is at the core or this webinar. Duration: 74 minutes Noldus product: The Observer XT, Watch for free on-demand! Animal Webinar Field experience on use of CatWalk XT: from data acquisition to analysis In this webinar, Dr. Johannes Heinzel and Dr.-Ing. Ivanna Timotius share their personal experience and discoveries while using gait analysis system CatWalk XT. Duration: 80 minutes Noldus product: CatWalk XT Watch for free on-demand! Human Webinar Behavioral Coding - Designing optimal coding schemes in The Observer XT In this Noldus Technical Briefing, we will show you how to create coding schemes that allow you to reach your behavioral endpoints but, at the same time, are clear enough for efficient and reliable coding. Duration: 50 minutes Noldus product: The Observer XT Watch for free on-demand! Animal Webinar Data analysis, organization, and visualization in EthoVision XT and Microsoft Excel In this technical briefing you learn more about the typical workflow in EthoVision XT. Learn how you can select, analyze, organize and export your data! A Noldus Trainer shows you the software and guides you through with tips and tricks. Duration: 55 minutes Noldus product: EthoVision XT Watch for free on-demand! Human Webinar Tools and methods for Facial Action Coding In this technical briefing, you will learn more about different tools that can be used to objectively measure AUs. We will also discuss how you can look at the AUs not only from an emotional, but also a functional point of view. Duration: 37 minutes Noldus product: FaceReader, The Observer XT Watch for free on-demand! Animal Webinar Integrating Video Tracking with Digital Telemetry Integrating various tools in neuroscience, like video tracking and wireless telemetry, offer a more complete assessment of complex disease models. In this webinar, we will hear about wireless telemetry options in behavioral testing and integration in video tracking experiments. Duration: 54 minutes Noldus product: EthoVision XT Watch for free on-demand! Animal Webinar The standardization paradox: better data with naturalistic behavioral tests Most animals, like humans, have a rich and varied behavioral repertoire. Which behavior they show depends a lot on internal and external cues, and the outcome can be different every time. Naturalistic behavioral tests can offer a solution, and we go over several during this webinar. Duration: 50 minutes Noldus product: EthoVision XT, PhenoTyper, CatWalk XT Watch for free on-demand! Animal Webinar Lessons From The Core: Longitudinal Assessment vs. Point Sampling of Behaviors in Mice Join Lior Bikovski and Shivang Parikh from Tel-Aviv University for a presentation on longitudinal behavioral studies and how to optimize the use of home cage monitoring (HCM) systems for behavioral research. Duration: 60 minutes Noldus product: PhenoTyper Watch on-demand Animal Webinar Zebrafish research in the spotlight Recent discoveries, methodologies, challenges in zebrafish research, and how to tackle them. We invited renowned behavioral researchers Dr. Christian Tudorach and Dr. Ruud van den Bos to tell us all about these topics in this webinar. Duration: 95 minutes Noldus product: DanioVision, EthoVision XT, DanioScope Watch for free on-demand! Animal Webinar How to use the Track Editor in EthoVision XT In an ideal EthoVision world, there would be no need for the Track Editor. All samples would stay perfectly on the correct body points, there would be no nose-tail swaps and multiple animals in the same arena would never swap identities. However, if tracking issues still occur, the Track Editor is a useful tool to correct errors. Duration: 48 minutes Noldus product: EthoVision XT Watch for free on-demand! Animal Webinar Boost analysis capability in EthoVision XT with JavaScript variables In this technical briefing, we take a look at how you can expand the analysis capability in EthoVision XT by creating custom variables with the JavaScript programming language. Duration: 50 minutes Noldus product: EthoVision XT Watch for free on-demand! Animal Webinar Detection Settings in EthoVision XT: Insights Into Doing it Right In this webinar, we go over all the things that you need to consider before starting your experiment. Duration: 73 minutes Noldus product: EthoVision XT Watch for free on-demand! Animal Webinar Long term rodent studies in neuroscience In this talk, we investigate how animal research can be extended in to long-term observations, following the path human research has entered for some time already which resulted in great new insights. Duration: 73 minutes Noldus product: PhenoTyper Watch for free on-demand! Animal Webinar Tools for preclinical COVID-19 research In this technical briefing, Dr. Lucas Noldus reviews relevant animal models, behavioral and physiological biomarkers related to COVID-19, and how these can be measured automatically using appropriate sensors and software. Duration: 60 minutes Noldus product: EthoVision XT, Observer XT, PhenoTyper, Watch for free on-demand! Animal Webinar Automated Rodent Behavior Recognition with EthoVision XT In this technical briefing, you will learn more about EthoVision XT’s module Automatic Behavior Recognition: how it works and what you can use it for. Duration: 35 minutes Noldus product: EthoVision XT Watch for free on-demand! Animal Webinar Tools and techniques for zebrafish research In this webinar, you will get an overview of new techniques and current developments in zebrafish research tools, from video tracking to complete systems, and how scientists worldwide use such tools. Duration: 38 minutes Noldus product: DanioVision, EthoVision XT, DanioScope Watch for free on-demand! Register for webinar First name * Last name * Email * Would you like to be contacted by a Noldus representative? * Yes No error Please select whether you would like to be contacted. Register and get access By clicking Submit, you consent to Noldus processing your data as described in our privacy policy. --- ## Basic Behavioral Neuroscience in Zebrafish URL: https://noldus.com/zebrafish-neuroscience-ebook Description: Check out our free downloadable e-book where we explain from A to Z why and how we measure certain behavior in zebrafish Free e-book Basic Behavioral Neuroscience in Zebrafish This e-book covers the fundamentals of using zebrafish as a model organism in behavioral neuroscience research, including common assays, experimental design, and analysis methods. - checkZebrafish as a model organism - checkLarval and adult behavioral assays - checkLight/dark preference tests - checkLocomotor activity analysis - checkHigh-throughput screening approaches Download for free @csrf First name * Last name * Email address * I accept the Noldus privacy policy (we will protect your personal data and you are in control of your data). * Download for free download Why zebrafish for behavioral research? Zebrafish offer unique advantages for behavioral neuroscience: optical transparency, rapid development, genetic tractability, and the ability to screen large numbers of animals. Their behavioral repertoire is well-characterized and relevant to human neurological conditions. - checkNovel tank diving test for anxiety - checkOptomotor response for vision - checkAcoustic startle and habituation - checkSocial preference assays - checkDrug screening and toxicology --- # Blog Posts ## Practical skills grow with every replay URL: https://noldus.com/blog/practical-skills-grow-with-every-replay Published: 2026-10-19 12:30:00 Description: Video brings clarity and consistency to skills training in nursing and allied health. Discover why it works, what the research shows, and how to add it to your own program. You've just finished a full day of skills training with three educators, eighty students, and a thick pile of feedback forms. One form says, "good communication." Another, for a very similar performance, says "work on patient rapport." Both educators are experienced and both are sincere, yet the student walks away unsure which advice to follow. Practical assessment is a core part of nursing and allied health education. In many programs, it takes the form of an OSCE (Objective Structured Clinical Examination). Students move through a series of short tasks, such as taking a medical history, dressing a wound, or guiding a patient through an exercise, often with an actor playing the patient. However your program organizes it, the aim is to give every student an equal opportunity to show their skills. In the absence of video, feedback still depends on what each educator noticed, remembered, and managed to write down in a few busy minutes. When a performance is recorded, educators and students can return to what happened instead of what someone recalls and dictates in the moment. Continue reading to learn why video feedback works in simulation-based training and how you can build it into your own training and assessments, starting small. The feedback challenge in skills assessment Why consistency matters Every practical assessment, from a weekly practice session to a final exam, aims to be fair and consistent. In practice, that is not always easy. Scores can differ quite a lot depending on who is watching, especially for communication skills, such as explaining a treatment in a way the patient understands. A second pair of eyes helps, and that is exactly what video recording and debriefing makes possible for every performance. Educators usually watch each performance live, and only once. Every educator notices different things, and over a full day of sessions, attention naturally fluctuates. As a result, students receive feedback that reflects the observer as much as the performance. Research from paramedic education shows this clearly. In large-scale exercises for paramedic students, scores from experienced observers differed considerably from one observer to the next. A detailed analysis of video recorded from several camera angles gave instructors a clear and objective picture of what happened (Perry et al., 2022). What students gain from feedback they can act on Clear feedback tells students exactly what to repeat and what to refine, while varied feedback leaves them guessing where to improve. Time plays a role, too. Practical tasks often last only 5 to 10 minutes, which leaves educators little room for detailed comments, and written feedback frequently reaches students long after the moment has passed. The quality and immediacy of feedback shapes how competent and confident your graduates feel when they meet their first real patients. It also shapes how your program is seen by students, clinical partners, and accreditation bodies. Why video feedback works What research shows about student outcomes A recent study in nursing education backs this up. At Atatürk University in Turkey, 65 first-year nursing students learned to place a feeding tube through the nose. Half of them recorded and reviewed their own performance, while the other half trained without video. Both groups improved, but the video group scored considerably higher on the practical skills test (Yavuz et al., 2025). Video makes a visible difference Nursing students who reviewed their own recorded performance scored an average of 87.6 points on a practical skills test. Students who trained without video scored 61.3 (Yavuz et al., 2025). View the researchopen_in_new Video feedback works because students observe themselves, reflect on what they see, and connect it to expert input from their supervising trainers. In simulation-based training, debriefing is where much of the learning happens. Watching a recording alone is a good start, but discussing it with an educator turns what students see into clear next steps. The paramedic study mentioned earlier also recommends video as a debriefing tool (Perry et al., 2022). Students learn more when they feel at ease AIXTRA is the competence center for training and patient safety at RWTH Aachen University, where students in medicine, nursing, midwifery, and physiotherapy train side by side. A recent study from AIXTRA found that students who felt more comfortable in group learning settings also reported greater learning success in a hands-on clinical skills course (Lenes et al., 2026). The authors recommend structured, behavior-focused feedback and low-stakes opportunities to practice. They also suggest building up step by step: first observing, then guided practice, and only then performing in front of others. Video fits this approach well. Reviewing a recording privately, at their own pace, gives students a calm space to reflect that a quick conversation in a busy corridor rarely provides. Standardizing feedback across your program Feedback becomes more consistent when you pair video with a clear checklist. You define the competencies, such as patient rapport, clarity of communication, and clinical reasoning. Then you describe each one as behavior you can see and hear. As our complete guide to behavioral observation puts it, this is how "seemed" becomes "happened." Once everyone works with the same checklist, several educators can watch the same recording and score it. If their scores differ, they can watch that moment again together and see why. These conversations help educators agree on what good performance looks like, so their judgments grow closer over time. Real-world example Researchers in the United States created a list of 12 leadership behaviors, such as sharing information and assigning tasks, each rated from poor to excellent. Using The Observer, two trained raters, who were not leadership experts, scored each of 360 video recordings of real care for seriously injured patients. Together, their ratings proved highly reliable, and teams whose leaders scored higher also delivered better patient care. View the publicationopen_in_new This also helps when an external review asks how you keep assessment fair and consistent: you can show the recordings and scores that support your approach. Adding video feedback to simulation-based training How to add video feedback: before, during, and after Before the session - Create your checklist: which behaviors, visible and audible, show that a student is competent? - Make sure all educators understand the checklist and how to use it for feedback. - Tell students which skills the session focuses on, so they know what to look for when they watch their recording. During the session - Record each task or scenario. - Educators score in real time, using the shared checklist. - Mark key moments as they happen, so they are easy to find later. After the session - Debrief: educator and student review the marked moments together and agree on what to keep and what to change. - Individual review: the student watches the full recording, reads the feedback, and reflects. - Track progress: in a later session, a new recording shows the students how their skills have developed. In practice: During a patient interview, the camera records the full conversation. The educator scores communication behaviors such as open questions, empathy, and clarity, and marks two moments worth discussing. That same day, the student watches the recording, reads the educator's notes, and knows exactly what to focus on next time. Free download See how NoldusViso supports video feedback Discover how NoldusViso helps you record, mark, and review skills sessions across multiple rooms. Download the leaflet to explore the features. Download the leaflet Privacy, consent, and ethics Recording in education calls for clear agreements and procedures, so make them part of your standard process. Ask students to sign a recording agreement at the start of the program. Store recordings securely and give access only to the student and the educators involved. Decide how long you keep recordings, in line with your institution's rules, and use a system that deletes them automatically after that period. Most importantly, explain the purpose openly: recordings exist to help students learn and grow. Where NoldusViso fits With NoldusViso, you can record in several rooms at once and mark key moments during and after the session. Recordings are ready to review right afterward, and role-based access ensures that only the right people see the right videos. For teams that also conduct deeper research on their training methods, The Observer adds detailed behavioral coding and analysis options and lets you assess how different people coded the same recording. Clearer feedback for students and educators Video gives every practice session a second life. Students can revisit what happened, understand it, and build on it. They gain clarity and confidence, while educators get a shared reference point and your program builds fair, consistent assessment that it can clearly demonstrate. The same approach works wherever people learn practical skills, whether they are training to become nurses, physiotherapists, or paramedics. Want to explore further? Start with the complete guide to behavioral observation, or read why video feedback works in education. Ready to bring video feedback to your skills training? Download the free white paper Video feedback in skills education: 10 reasons why, or start a conversation with our team about your program and goals. References - Lenes, A.; Klasen, M.; Bohorquez-Mendoza, G.; Gecht, J.; Sopka, S. & Vogt, L. Psychological determinants of successful practical teaching: personality traits, self-efficacy, and subjective perception in a hands-on clinical skills course. BMC Medical Education 2026, 26, 1069. - Perry, O.; Jaffe, E. & Bitan, Y. Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations. Human Factors 2022, 64(1), 228-249. - Rosenman, E.D.; Grand, J.A. & Fernandez, R. Validity evidence of a resuscitation team leadership assessment measure for use in actual trauma resuscitations. AEM Education and Training 2025, 9(2), e11061. - Yavuz, B.; Koç, G.; Yüce Başaran, H.D. & Çiftçi, B. Watch and learn your performance: The effect of self-assessment with video recording on nursing students’ knowledge and skills of nasogastric catheter placement. A randomized controlled trial. Nurse Education in Practice 2025, 83, 104251. --- ## Understanding phase dispersion in CatWalk URL: https://noldus.com/blog/phase-dispersions-explained Published: 2026-10-14 11:00:00 Description: CatWalk 10.7 introduced circular graphs for phase dispersion and coupling. In this blog post we go over these parameters, and how they are calculated so you can see how to interpret values, run statistics, and report results. In CatWalk 10.7 we changed how phase dispersion and coupling are visualized and calculated. Here is what that means for interpreting values, running statistics, and reporting results. The most misunderstood parameter in rodent gait analysis Phase dispersion and coupling are two of the most valuable parameters CatWalk reports. They capture interlimb coordination, the temporal relationship between paws during a step cycle, which is fundamental to detecting motor deficits in models of spinal cord injury, ataxia, Parkinson's, Huntington's, stroke, and many other CNS and PNS conditions. They are also the two most misunderstood parameters in the software. The confusion is not the user's fault. Phase dispersion is circular data, meaning it lives on a loop rather than a line, and circular data requires different mathematics than most researchers are trained on. Nearly every commercial gait analysis system, including previous versions of CatWalk, has historically presented these parameters as if they were linear. That approach usually works. Occasionally it produces averages and p-values that quietly point in the wrong direction. In CatWalk 10.7 we fixed this. Here is what changed, why it matters, and how to read the new values. What phase dispersion measures Phase dispersion answers one question: when one paw completes its step cycle, at what point in that cycle does another paw make initial contact with the ground? Pick one paw as the anchor (its cycle sets the reference clock) and another as the target. The value is expressed as a percentage of the anchor's cycle. A quick example. The right front paw's step cycle lasts 20 milliseconds. The left hind paw makes initial contact 15 milliseconds into that cycle. Phase dispersion = 15 / 20 = 75 percent. Both phase dispersion and coupling report this same underlying value. Coupling is the unsigned version, always 0 to 100 percent. Phase dispersion is the signed version, which becomes important the moment you try to compute an average. Reference values worth knowing For a healthy rodent walking at moderate speed, the expected values follow a clear pattern: Paw pair Combinations Expected value What this means Diagonal LF-RH, RF-LH ~0 percent (or ~100 percent) Near-synchronous contact Girdle LF-RF, LH-RH ~50 percent Alternating (front pair or hind pair) Lateral LF-LH, RF-RH ~50 percent Alternating (same side of body) Any deviation from these reference points signals a change in coordination. Diagonal drift away from 0 percent flags a problem in forelimb to hindlimb coordination. Girdle drift away from 50 percent flags left-right asymmetry, such as a limp or a hemiparetic gait. Lateral drift away from 50 percent flags ipsilateral coordination issues, often cerebellar or spinal in origin. A real example: geriatric vs young mice The worked example above is useful for understanding the math, but real CatWalk data tells the story better. The figures below compare a group of geriatric mice with a group of young mice on two paw pairs. How to read the circular graphs. The 0 percent reference sits at the top of the circle. Values increase clockwise to +50 at the bottom, then continue counterclockwise from -50 back up to 0. The bottom of the circle, labeled -50|50, is the wrap point where the two labels describe the same instant: perfect alternation. The red arrow is the group's circular mean. Its direction gives the average timing relationship, and its length reflects how tightly the individual runs are clustered around that mean. For a healthy rodent at moderate walking speed, we expect the arrow to sit near 0 for diagonal pairs (paws that normally strike the ground together) and near ±50 for girdle pairs (paws that normally alternate). Diagonal pair: RF → LH Diagonal pair (RF → LH). The young group's mean arrow points to 0; the geriatric group has rotated roughly 24 percent clockwise. The young group is textbook. The mean arrow points almost exactly to 0. Diagonal coordination is intact and the forelimb and hindlimb are striking the ground in near-synchrony as expected. The geriatric group has shifted. The mean arrow has rotated roughly 24 percent clockwise, meaning the left hind paw is now landing about a quarter of the way into the right front paw's cycle rather than in near synchrony. The animals are consistently coordinating differently, which is exactly the kind of stable, biologically meaningful phenotype gait analysis should be able to detect. Girdle pair: LH → RH Again, the young group behaves as expected. The mean arrow points essentially straight down, sitting on the ±50 alternation point. The geriatric group has shifted counterclockwise to roughly -38 percent, which corresponds to 62 percent on a linear 0 to 100 percent scale. Alternation is still present, but it is no longer symmetric. The left hind is arriving later in the right hind's cycle than it should. Girdle pair (LH → RH). The young group sits on the ±50 alternation point; the geriatric group has shifted to roughly -38 percent. What this tells us. Both paw pairs show age-related deviation, but the diagonal shift is the larger one. This is consistent with what we know biologically: forelimb-hindlimb coordination is a pattern that tends to degrade before the more automatic left-right alternation. The circular graphs show that pattern immediately. Now consider what a linear analysis would have shown for the same data. Individual diagonal readings in the young group include values on both sides of the 0 / 100 wrap point, because near-synchronous contacts naturally fall to either side depending on which paw touched down first by a millisecond. A linear average of those values would sit somewhere in the middle of the number line, far from where the coordination actually lives on the circle. The age-related shift in the geriatric group would either disappear into noise or produce a spurious result. The circular representation shows the truth. The linear one hides it. The circular data problem Here is why linear averaging can go wrong. The step cycle is inherently repetitive. The moment labeled 0 percent (the start of the cycle) is the same instant labeled 100 percent (the end). On a linear axis those points are far apart. On a circle they are the same point. Consider four phase dispersion values from a single trial: 75, 75, 5, 5. - Linear mean: (75 + 75 + 5 + 5) / 4 = 40 percent - Circular mean: 90 percent (equivalently, -10 percent) The linear mean of 40 percent is misleading. It sits on the opposite side of the circle from where all four values are clustered. The circular mean correctly identifies the group as clustered near the 0 / 100 wrap point. This is exactly the situation that shows up in real data for diagonal paw pairs, whose expected values sit right at 0 percent. A healthy animal's diagonal readings across a single trial might include 98, 2, 99, and -3 percent. These are all near-synchronous contacts, but a linear average treats them as wildly inconsistent. What CatWalk 10.7 changed Three concrete updates: - Circular means are now the default. Group statistics computed inside the software use the correct circular calculation. Users pulling group statistics get accurate averages without writing custom code in R or Python. - Phase dispersion now uses signed values. Values can go negative because they live on a circle. A value of -19 percent and a value of 81 percent describe the same point on the cycle. The signed representation makes clusters near the wrap point visually obvious in a way that a 0 to 100 percent scale cannot. - Results are displayed on circular graphs. Phase dispersion values plot around a circle rather than a line, matching the underlying mathematics. Coupling remains available in its familiar 0 to 100 percent form for users and downstream tools that expect a positive number. The underlying data is the same. Only the display differs. Why this matters for your research For most girdle and lateral pair analyses, the practical difference between linear and circular statistics is small. Those values cluster near 50 percent, well away from the wrap point, and a t-test will usually reach the same conclusion either way. For diagonal pairs, and for any experimental group whose values cluster near 0 or 100 percent, the difference can be substantial. Ataxia models, spinal cord injury studies, and neurodegeneration research frequently produce exactly this kind of data. In these cases a linear analysis can hide a real effect or invent one that is not there. Reviewers are increasingly aware of the distinction. Reporting a circular mean alongside a Watson-Williams or Watson's U² test is defensible in a way that a t-test on circular data no longer is. The bigger picture Phase dispersion has always been circular data. The mathematics have been settled in the circular statistics literature for decades. What has been missing is a commercial system that applies the correct methodology automatically, so researchers can focus on biology instead of writing custom scripts to compute a mean. To our knowledge, CatWalk 10.7 is currently the only commercial rodent gait platform that reports interlimb coordination using circular means and circular graphs out of the box. Every other system on the market, whether treadmill-based or runway-based, still presents these parameters on a linear scale, leaving the correct statistical treatment to the researcher. If you are already using CatWalk, the upgrade is available now. If you are evaluating gait analysis systems for a new lab or core facility, this is one of the differences that will show up in your first manuscript. Want a deeper reference on interpreting phase dispersion, coupling, and the appropriate statistical tests? See our full knowledge base article on MyNoldus. CatWalk XT Getting CatWalk for your research has never been easier Find out how to get the best deal on CatWalk, the automated gait analysis system trusted in motor-deficit research worldwide. See the deal --- ## To hide or explore? What the elevated plus maze reveals about anxiety URL: https://noldus.com/blog/what-the-elevated-plus-maze-reveals-about-anxiety Published: 2026-10-12 20:39:15 Description: A raised, plus-shaped platform with two arms walled in and two arms open. In this blog we explain what the elevated plus maze measures, look at how labs are pairing it with EthoVision, and share practical tips. A raised, plus-shaped platform with two arms walled in and two arms open. In this blog we explain what the elevated plus maze measures, look at how labs are pairing it with EthoVision, and share practical tips for running it in your lab. If you were able to ask a rodent what it wants, the answer is usually two things at once. It wants to explore, because a new space might hold food or a mate. And it wants to stay safe, because that same space might hold a predator. Most anxiety tests in behavioral neuroscience are built on exactly that tension. Few do it as directly as the elevated plus maze. Why the elevated plus maze? The elevated plus maze asks almost nothing of an animal except to move. There is no training, no food reward, no shock. A rat or mouse is placed at the center of a raised, plus-shaped platform and left to explore for five minutes. Two of the four arms have walls. Two are open, with a drop to the floor below. Rodents are drawn to explore new space, but they are also innately wary of open, elevated, unprotected ground. That built-in conflict is the whole test. How an animal resolves this conflict, staying within the closed arms or venturing into the open ones, is read as a measure of anxiety-like behavior. That mix of simplicity and behavioral conflict is why the elevated plus maze has become one of the most used anxiety assays in rodent research. It sits alongside a handful of related conflict-based tests. However, the elevated plus maze adds height to the equation, which sharpens the conflict for many rodent strains. A widely cited methods review credits this combination of speed, low cost, and sensitivity to anxiolytic and anxiogenic drugs for the test's long research history [1]. What counts as anxiety-like behavior? A single five-to-ten-minute trial in the elevated plus maze can generate a great number of measures. The main parameter is time in the open arms: animals that spend less time there, or enter them less often, are typically read as more anxious. Closed-arm entries serve a different purpose. They work as a locomotor control, since a drug or genetic change that simply slows an animal down would otherwise look like an anxiety effect on its own. Beyond these locational measures, researchers have long tracked related behaviors too: head dips over the edge of an open arm, and stretched-attend postures, where an animal leans out from a closed arm without committing to it. Which of these measures a lab reports depends on the question being asked. A pharmacology screen might care about open-arm time and nothing else. A circuit-mapping study might lean on the more specific behaviors as well, since they can separate general activity from risk assessment. The studies below span that range. A rat exploring an elevated plus maze, with two open arms and two enclosed arms. Applications and recent research: pairing the elevated plus maze with EthoVision Genetics and individual differences Chitre and colleagues asked whether common genetic variation explains why some outbred rats show more anxiety-like behavior than others. Working with 534 to 654 Sprague-Dawley rats, they combined elevated plus maze open-arm behavior with locomotor and pain-sensitivity measures, generated through video tracking, and ran genome-wide association analyses. Heritability estimates for the eleven behavioral traits ranged from 0.14 to 0.38. The team identified an independent locus on chromosome 1 tied to open-arm behavior, with candidate genes including Slc18a2, Gfra1, and Pdzd8 [5]. Stress, the gut-brain axis, and lifestyle Nicolas and colleagues asked whether exercise could offset the effects of a disrupted gut microbiota on the brain. Rats received an antibiotic cocktail to disrupt their gut microbiota, then were kept either sedentary or given voluntary access to a running wheel. Sedentary rats with a disrupted microbiota performed worse on the elevated plus maze and other hippocampal neurogenesis-dependent tasks, tracked with EthoVision. But voluntary exercise attenuated both the behavioral changes and the underlying drop in adult hippocampal neurogenesis [6]. Yao and colleagues approached stress from the other direction. Mice that were socially isolated as adolescents and later given an induced heart attack showed a worse anxiety and depression phenotype, measured in part through elevated plus maze entries and time in the open and closed arms with EthoVision, and that phenotype correlated with reduced cardiac function after the simulated infarction [7]. Addiction and sex differences Rivera-Irizarry and colleagues let male and female C57BL/6J mice binge drink alcohol on a voluntary schedule, then tracked how avoidance and compulsive behaviors changed during protracted abstinence. All the behavioral assays, including the elevated plus maze, were analyzed with EthoVision. Females, but not males, spent more time in the open arms during abstinence compared to water-drinking controls, a reduction in avoidance behavior. However, total distance traveled in the maze did not differ by sex or alcohol history, a useful result that rules out a simple locomotor explanation [8]. Social behavior and circuit neuroscience Integrated EthoVision visualization combining elevated plus maze tracking with behavioral data. Fazekas and colleagues investigated a specific glutamate transporter, VGluT3, in a brainstem region called the median raphe that is implicated in social behavior. Mice lacking VGluT3 showed increased anxiety-like behavior in the elevated plus maze, alongside impaired social memory. When the researchers chemogenetically excited VGluT3-expressing neurons specifically in the median raphe, the effect was anxiolytic. Inhibiting the same neurons had a more mixed, context-dependent effect: it increased social interest a day later but reduced mobility and social behavior in an aggressive context [9]. When the EPM doesn't show a difference Yu and colleagues built a new device for delivering transcutaneous auricular vagus nerve stimulation, or taVNS, to awake mice, then tested it over three weeks. Elevated plus maze and open field behavior, recorded and analyzed with EthoVision, showed no effect on anxiety-like behavior, even though the same treatment significantly improved memory [10]. Buglinina and colleagues found something similar after spinal cord injury in mice. Knocking out the receptor TAAR5 sped up sensorimotor recovery. But elevated plus maze tracking showed anxiety-like behavior stayed elevated regardless of genotype, both before and after injury [11]. Arezoumand and colleagues found a third variation on the same theme in a mouse model of Rett syndrome, a rare neurodevelopmental disorder caused by mutations in the MECP2 gene. Hemizygous male mice carrying the common T158M mutation received daily metformin for 20 days, then were tested in the elevated plus maze. Metformin had no significant effect on the mice's anxiety-like behavior. But it did significantly improve several other RTT-like symptoms in the same animals, including breathing irregularities, gait, and hindlimb clasping [12]. Pharmacology and drug development He and colleagues took a well-known but highly toxic compound, tetrodotoxin, and reformulated it as a dissolvable oral film dosed at a fraction of its toxic level, then tested it as a candidate antidepressant in mice exposed to chronic unpredictable mild stress. Across a battery that included the elevated plus maze, tracked and analyzed with EthoVision, along with a sucrose preference test and a forced swim test, tetrodotoxin treatment reversed the depression-like drop in sucrose preference and increased immobility caused by the stress protocol. The elevated plus maze told a more qualified story: treated mice trended toward more time in the open arms, but the difference from stressed, untreated mice did not reach statistical significance [13]. Nutrition and supplements Koc and colleagues compared three organic forms of magnesium, citrate, glycinate, and malate, in Sprague-Dawley rats over eight weeks of supplementation. Anxiety-related and cognitive behavior, including elevated plus maze entries and time recorded via EthoVision, was assessed alongside neuromuscular tests and tissue-specific magnesium measurements in brain, muscle, and vascular tissue [14]. EthoVision arena settings configured for the elevated plus maze, with open and closed arms defined as separate zones. Tips for using the elevated plus maze with EthoVision The elevated plus maze looks forgiving, but a few habits separate clean data from a noisy dataset. - Control lighting deliberately. Rodents show a light-sensitive anxiety phenotype: time in the open arms rises sharply at very low light levels (0 to 1 lux) compared with just 2 lux and above [3]. Keep lighting consistent across sessions and consider that infrared backlighting under dim or dark conditions can preserve tracking contrast for EthoVision without adding visible light. - Remember it is a tactile test as much as a visual one. The maze's aversiveness relies more on tactile and proprioceptive cues, such as the edge of an open arm, than on vision alone [4]. That is worth keeping in mind when interpreting results from visually impaired strains or manipulations. - Habituate the animals to the room. Move animals to the testing room and let them settle before the trial starts. A stressful transport or an unfamiliar room can dominate the behavior you are trying to measure. - Clean thoroughly between animals. A wipe-down with a low-odor disinfectant between trials removes residual scent cues that could bias the next animal's exploration. - Keep the testing schedule steady. Avoid running the elevated plus maze on days when cages are cleaned or animals are weighed, since routine handling can shift baseline anxiety and blur a treatment effect. - Place it early in a behavioral battery. Least-stressful tests generally go first. The elevated plus maze and the open field test are both low-stress and are usually grouped early, ahead of more demanding procedures. - Track more than open-arm time if you can. Head dips and stretched-attend postures add information that raw open-arm time does not capture on its own. Free Trial Want to try EthoVision with your own elevated plus maze videos? EthoVision is the gold standard in video tracking for behavioral research. Request a free trial and see how EthoVision automates your elevated plus maze analysis. Try it now! For more on adapting classic behavioral assays with automated tracking, have a look at our earlier blog on the open field test or radial arm maze. Frequently asked questions What does the elevated plus maze measure? It measures anxiety-like behavior in rodents by tracking how much time an animal spends, and how many entries it makes, in the open, unprotected arms of a raised plus-shaped maze versus the enclosed arms. Why does the elevated plus maze have two open arms and two closed arms? The design creates a conflict between a rodent's drive to explore new space and its innate wariness of open, elevated, exposed areas. How the animal resolves that conflict is read as an anxiety-related choice. What is the difference between the elevated plus maze and the open field test? Both rely on a related conflict between exploration and avoidance of exposed space. But the elevated plus maze adds height and a forced choice between enclosed and open arms, while the open field test uses a single arena with a center and a periphery. What is the difference between the elevated plus maze and the elevated zero maze? Both rely on the same principles and give similar outcomes (time spent in open vs closed zones). However, the zero maze removes the ambiguous center zone, which is usually a separate area in analysis. Can the elevated plus maze be used with both mice and rats? Yes. It has been adapted for both species, with the apparatus scaled to the animal being tested. What software is used to score the elevated plus maze? Most recent studies use automated video tracking software, most commonly EthoVision or DeepLabCut, to score arm entries, time in each arm, and locomotor measures without relying on manual scoring. References Walf, A.A.; Frye, C.A. The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nat. Protoc. 2007, 2, 322–328. https://doi.org/10.1038/nprot.2007.44 Pellow, S.; Chopin, P.; File, S.E.; Briley, M. Validation of open:closed arm entries in an elevated plus-maze as a measure of anxiety in the rat. J. Neurosci. Methods 1985, 14, 149–167. https://doi.org/10.1016/0165-0270(85)90031-7 Garcia, A.M.B.; Cardenas, F.P.; Morato, S. Effect of different illumination levels on rat behavior in the elevated plus-maze. Physiol. Behav. 2005, 85, 265–270. https://doi.org/10.1016/j.physbeh.2005.04.007 Filgueiras, G.B.; Carvalho-Netto, E.F.; Estanislau, C. Aversion in the elevated plus-maze: role of visual and tactile cues. Behav. Processes 2014, 107, 106–111. https://doi.org/10.1016/j.beproc.2014.08.005 Chitre, A.S.; Hebda-Bauer, E.K.; Emery, M.A.; et al. Genetic architecture of addiction-relevant behaviors in outbred Sprague-Dawley rats reveals loci for anxiety-like and nociceptive traits. Genes Brain Behav. 2026, 25, e70053. https://doi.org/10.1111/gbb.70053 Nicolas, S.; Dohm-Hansen, S.; Lavelle, A.; et al. Exercise mitigates a gut microbiota-mediated reduction in adult hippocampal neurogenesis and associated behaviours in rats. Transl. Psychiatry 2024, 14, 195. https://doi.org/10.1038/s41398-024-02904-0 Yao, Y.; Wang, A.; Di, C.; et al. Long-term social isolation during adolescence exacerbated cardiac dysfunction after myocardial infarction. Transl. Psychiatry 2026, 16, 193. https://doi.org/10.1038/s41398-026-03959-x Rivera-Irizarry, J.K.; Zallar, L.J.; Levine, O.B.; et al. Sex differences in binge alcohol drinking and the behavioral consequences of protracted abstinence in C57BL/6J mice. Biol. Sex Differ. 2023, 14, 83. https://doi.org/10.1186/s13293-023-00565-0 Fazekas, C.L.; Török, B.; Correia, P.; et al. The role of vesicular glutamate transporter type 3 in social behavior, with a focus on the median raphe region. eNeuro 2024, 11, ENEURO.0332-23.2024. https://doi.org/10.1523/ENEURO.0332-23.2024 Yu, Y.-M.; Yao, R.; Liu, Z.-L.; et al. Feasibility and effectiveness of transcutaneous auricular vagus nerve stimulation (taVNS) in awake mice. CNS Neurosci. Ther. 2024, 30, e70043. https://doi.org/10.1111/cns.70043 Buglinina, A.D.; Romanyuk, E.A.; Chesnokov, A.A.; et al. TAAR5 modulates sensorimotor recovery after spinal cord injury. Biomedicines 2026, 14, 796. https://doi.org/10.3390/biomedicines14040796 Arezoumand, K.S.; Akhtar, G.B.; Kadar Shahib, A.; et al. Metformin treatment shows beneficial effects on RTT-associated phenotypical deficits in Mecp2 T158M male mice. Pharmaceuticals 2026, 19, 621. https://doi.org/10.3390/ph19040621 He, J.; Tang, C.; Niu, S.; Le, Q.; Yu, L.; Hong, B. Tetrodotoxin oral film attenuates depression in a chronic unpredictable mild stress model in mice. Mar. Drugs 2026, 24, 94. https://doi.org/10.3390/md24030094 Koc, B.; Hosgorler, F.; Kandis, S.; et al. Chronic organic magnesium supplementation enhances tissue-specific bioavailability and functional capacity in rats: a focus on brain, muscle, and vascular health. Biol. Trace Elem. Res. 2025. https://doi.org/10.1007/s12011-025-04678-y --- ## Optogenetics: using light to study the brain and behavior URL: https://noldus.com/blog/optogenetics-study-brain-behavior Published: 2026-10-12 13:44:34 Description: Learn how optogenetics uses light to study brain activity, from its inception to where the technology stands today. The Nobel Prize in Physiology or Medicine was awarded for the study of the brain through light-gated ion channels and optogenetics. To honor that achievement, we are dedicating this blog to the past and future of optogenetics — how it works, how the tools have grown, and how it pairs with behavioral research today. Researchers know a great deal about what different parts of the brain do. The harder question is which individual brain cells are responsible for a particular action or response. Optogenetics helps them investigate that connection by using light to change the activity of selected cells. Traditional methods of brain research For many years, researchers relied mainly on drugs and electrodes to study how brain cells affect behavior. Drugs can target specific receptors, but they take time to work and their effects can last longer than an experiment needs. Electrodes act quickly, but the electrical stimulation can also reach nearby cells that weren't meant to be involved. What researchers needed was a way to control specific cells at a particular moment, more like flipping a light switch. How light gives researchers more control Scientists found a way to introduce light-sensitive proteins, originally discovered in algae, into mammalian neurons, or nerve cells. These proteins, called opsins, respond to certain wavelengths of light. They allow researchers to turn activity in selected neurons on or off, with much finer control over where and when that happens. The technique offered a level of precision that earlier methods could not match. Therefore, Nature named it Method of the Year in 2010. This combination of light and genetics is called optogenetics. "Optogenetics is a technology that allows targeted, fast control of precisely defined events in biological systems as complex as freely moving mammals." — Karl Deisseroth Early experiments used tissue studied outside the animal. Researchers then moved to freely moving animals with implanted optical fibers that delivered light to the brain. The tools have continued to develop since those early studies. The discoveries that optogenetics has enabled have not gone unnoticed: Karl Deisseroth (an EthoVision user), Peter Hegemann, and Georg Nagel were awarded the Nobel Prize in Physiology or Medicine in 2026 for their work on optogenetics. How the tools have developed Why color matters, and how it has changed over the years The first optogenetic tools used blue light. It scatters and is absorbed quickly in tissue, making it difficult to reach neurons more than a few hundred microns below the surface. That meant placing an optical fiber close to the cells being studied. Newer, widely used opsins, including ChrimsonR and Jaws, respond to red light. These are known as red-shifted opsins. Red and far-red light, at wavelengths of roughly 620–700 nanometers, travels farther through tissue and bone and causes less light-related damage. Jaws, for example, can suppress neural activity up to 3 millimeters deep in the mouse brain through an intact skull. Using more than one color also gives researchers more control. This approach is called multiplexing. By placing a red-sensitive protein that activates neurons and a blue-sensitive protein that suppresses them in the same brain circuit, researchers can switch between the two effects by changing the light's color. They can test both directions of control in the same animal, without changing the genetic setup. Optogenetic setup in the DanioVision system. Juvenile zebrafish can be exposed to different wavelengths of light. CaMPARI: marking the brain cells that were active Some light-based tools help researchers identify which neurons were active during a behavior, rather than change their activity. CaMPARI is one example. Developed at HHMI's Janelia Research Campus, it leaves a record that researchers can examine later, without keeping a microscope near the animal during the experiment. Its full name is Calcium-Modulated Photoactivatable Ratiometric Integrator. That sounds technical, but the idea is straightforward: active cells are marked by a color change. CaMPARI is a protein that cells are genetically instructed to make. It normally glows green. When a neuron is active, calcium levels inside it rise. If the cell is also exposed to violet or ultraviolet (UV) light at around 400 nanometers, CaMPARI permanently changes from green to red. This change is called photoconversion. Researchers apply the light during the behavior or event they want to study. Only neurons that are active during that window turn red. The ratio of red to green reflects the calcium level, giving researchers a measure of activity rather than just an on-or-off label. Because the color change is permanent, they can examine the tissue afterward and map activity across the whole brain at the level of individual cells. CaMPARI 2.0 displayed in a zebrafish larva. Image by HHMI Janelia. This separates the behavior from the microscope work. Recent studies have used CaMPARI2 to map brain-wide activity in freely moving zebrafish larvae startled by a sound, and to mark active neurons in adult fruit flies during an unpleasant stimulus. Holding the animals still for imaging would have interfered with the behaviors being studied. There is a catch: the light used to mark the cells can affect behavior, too. Zebrafish larvae can see UV light and may avoid it. Researchers therefore need to account for the possibility that the marking light itself becomes part of what the animal is responding to. CaMPARI in rodents The first tests of CaMPARI in living animals used rodents, and rodent studies remain an active area of research. In early mouse studies, researchers used it in the visual cortex, the part of the brain that processes visual information. They measured how strongly individual neurons responded to visual patterns at different angles. The amount of color change matched the strength of each response, showing that CaMPARI could capture differences in activity. Since then, mouse studies have used CaMPARI to map working connections between brain regions and to study communication between neurons and astrocytes, another type of brain cell. Researchers have also recorded activity across large volumes of brain tissue while mice moved freely, without having their heads held in place or carrying a tether or miniature device. In that approach, researchers shine the marking light over the mouse and its home environment while it performs behavioral and cognitive tasks. They examine the preserved tissue afterward with a two-photon microscope. Separating the experiment from the imaging made it possible to study a larger volume of the cortex than is practical with live imaging. The work revealed task-related differences in activity across areas involved in movement and in processing touch and body sensations. CaMPARI can also be combined with optogenetic stimulation to map connections in freshly prepared slices of mouse brain tissue. Researchers use channelrhodopsin, a light-sensitive protein, to stimulate the ends of nerve fibers coming from one brain region. CaMPARI in a second region then marks the neurons that respond to those signals. In this setup, one light source both stimulates the first group of cells and marks the responding cells downstream — so researchers can identify those connections without recording electrical signals from the cells. Innovations with and within optogenetics In a simple behavioral experiment, entering a particular area can trigger a light pulse. EthoVision's Trial & Hardware Control can do this, as the place-preference example below explains. The same idea now extends to wireless implants and more detailed tracking of what an animal is doing. This is often called closed-loop control: the system detects a behavior or change in brain activity and uses that information to decide when to stimulate. AI-guided tools can help identify the movements or postures that trigger the light. - Stimulation triggered by movement or posture. Real-time tracking tools such as EthoVision, and pose-estimation tools such as DeepLabCut-Live, are routinely paired with stimulation hardware. Depending on the setup, a body or limb position, walking pattern, or posture can trigger the light. - Experiments with multiple animals. Some systems track multiple animals and trigger stimulation during a particular social interaction. Researchers can reinforce or interrupt that interaction as it happens to study group behavior and social hierarchy. - Fully wireless hardware. Soft, implantable probes with tiny LEDs remove the need for a tether. Some systems also include tracking, allowing stimulation and behavior measurement without a physical connection to the animal. The underlying question is still the same: how does a particular change in brain activity affect behavior? These tools give researchers more precise control over the trigger and automate more of the experiment. Optogenetics and EthoVision EthoVision combines behavior tracking with programmed signals that control stimulation. Several long-established experiments show how this works in practice. Real-time place preference: does the animal seek out or avoid stimulation? In a real-time place preference test, an animal explores a rectangular arena with two distinct sides. Entering one side triggers optogenetic stimulation. Activating or suppressing the targeted neurons can make that experience rewarding or unpleasant. Researchers then look at where the animal chooses to spend its time across sessions. Spending more time on the stimulated side suggests a rewarding effect; avoiding that side suggests an aversive, or unpleasant, effect. EthoVision's Trial & Hardware Control can link the chosen zone to a trigger. A signal passes through the input/output (IO) box to switch on the light source. Researchers can also define several zones, each linked to a different stimulation frequency or light source. Testing effects on anxiety-related behavior Researchers can use a similar approach to test whether stimulating a group of neurons reduces or increases anxiety-related behavior. For example, an elevated plus maze test can use an off-on-off, or ABA, design: stimulation is off at the start, on for a set period in the middle, and off again at the end. If the animal spends significantly more time in the open arms during stimulation, the result suggests an anxiety-reducing effect. More time in the closed arms points in the opposite direction. Free Trial Want to run optogenetic experiments with precise, automated triggers? EthoVision's Trial & Hardware Control links behavior tracking to light delivery, so stimulation happens exactly when your experiment calls for it. Request a free trial and see how it works with your setup. Try it now! Movement and learning tasks Researchers can also measure how stimulation changes movement in an open field, including speed, overall movement, and turning. These measures help connect the activity of particular neurons with what the animal does. Triggers do not have to depend on location. Trial & Hardware Control can also respond to detected actions, such as a nose poke or lever press. This can automate operant learning tasks, in which an animal learns that an action leads to a rewarding or unpleasant outcome. Where optogenetics goes from here Optogenetics has become a standard tool for studying how brain circuits work, rather than the emerging technique it was in 2012. Its uses are still expanding. Red-shifted opsins and experiments using more than one light color have made it routine to reach deeper tissue and control activity in both directions with less invasive methods. CaMPARI adds a way to identify which cells were active during a behavior. Wireless systems, closed-loop control, and AI-guided behavior analysis make it possible to automate experiments that once depended on manual triggering. Research funding continues to support this work. The NIH BRAIN Initiative, the largest U.S. funder of neurotechnology tool development, received an additional $1.5 billion through 2026 under the 21st Century Cures Act. Its recurring funding calls include new tools for recording and changing neural activity, including optogenetics. For researchers planning a place-preference test or an experiment with several zones and stimulation frequencies, EthoVision offers a way to link behavior tracking with light delivery. Trial & Hardware Control handles the programmed triggers, so stimulation happens when the experiment calls for it. References - Deisseroth, K. Optogenetics. Nat. Methods 2011, 8, 26–29. - Hsueh, B.; Chen, R.; Jo, Y.; et al. Cardiogenic control of affective behavioural state. Nature 2023, 615, 292–299. - Yang, Y.; Wu, M.; Vázquez-Guardado, A.; et al. Wireless multilateral devices for optogenetic studies of individual and social behaviors. Nat. Neurosci. 2021, 24, 1035–1045. - Hong, S. Wireless optogenetic microsystems accelerate artificial intelligence–neuroscience coevolution through embedded closed-loop system. Micromachines 2025, 16, 557. - Stamatakis, A.M.; Stuber, G.D. Activation of lateral habenula inputs to the ventral midbrain promotes behavioral avoidance. Nat. Neurosci. 2012, 15, 1105–1107. - Peng, X.; Mao, Y.; Tai, Y.; et al. Characterization of anxiety-like behaviors and neural circuitry following chronic moderate noise exposure in mice. Environ. Health Perspect. 2023, 131, 107004. - Stuber, G.D.; Sparta, D.R.; Stamatakis, A.M.; et al. Amygdala to nucleus accumbens excitatory transmission facilitates reward seeking. Nature 2011, 475, 377–380. --- ## FaceReader 10 vs. Open-Source Facial Expression Tools URL: https://noldus.com/blog/facereader-10-vs-open-source-facial-expression-tools-openface-libreface-and-pyafar-compared Published: 2026-09-29 10:36:16 Description: See how FaceReader 10 stacks up against OpenFace, LibreFace, and pyAFAR on emotion classification accuracy, Action Unit detection, and infant facial expression analysis in this updated 2026 comparison. In 2025, we compared FaceReader to OpenFace, at the time the leading open-source facial expression tool. Since then, there is a new version of OpenFace and two more open-source contenders have emerged, with one of them (LibreFace) releasing an updated version. Here's how FaceReader 10 stacks up against all of them today, on emotion classification, Action Unit detection, and infant facial expression analysis. 1. Why this comparison, and why now Facial expression analysis is one of several complementary ways researchers measure emotion, alongside facial EMG and manual FACS coding. Each has strengths and weaknesses. FACS coding by certified human coders is the most established gold standard, but it's slow. Researchers at the University of Bern (Stöckli, Schulte-Mecklenbeck, Borer, & Samson, 2018) put it this way: Video recordings of participants' faces are often recorded with a resolution of 24 frames/s, meaning that for each second of recording the coder has to produce 24 ratings of the 46 AUs. So for one participant with only 1 min of video, 1,440 individual ratings are necessary. Assuming that a coder could rate one picture per second, this would add up to approximately 24 min of work for 1 min of video data. FaceReader 10, by contrast, can process a comparable one-minute video in well under a minute in many cases, though exact speed depends on hardware and settings. Trade-offs between speed, cost, and validation are unavoidable, and automated tools of every kind, commercial and open-source, have progressed steadily in recent years. We support the wider adoption of automated facial expression analysis generally, including open-source tools: more validated options are good for the field. But validation is also the main thing that separates these tools in practice. In our own conversations with customers, researchers occasionally come to us after a peer reviewer pushed back on an unvalidated open-source tool and asked for a FACS-validated alternative instead. That's a pattern we've seen firsthand, not a formal study, but it's a real, practical reason the validation data below matters beyond the numbers themselves. When we last compared FaceReader to OpenFace, OpenFace v2.2 (2018) was the most current open-source option, and it was the only serious open-source alternative most researchers considered. That's no longer true. OpenFace 3 was released in 2025, and two newer tools, pyAFAR and LibreFace, have gained adoption in the research community. This update re-runs the comparison against all of them, using FaceReader 10. 2. Meet the contenders - OpenFace 2.2 (2018): the toolkit from our original comparison, included again here as the aging baseline. Baltrusaitis, T., Zadeh, A., Lim, Y. C., & Morency, L.-P. (2018). OpenFace 2.0: Facial Behavior Analysis Toolkit. IEEE FG 2018. - OpenFace 3.0 (2025): a full rebuild from CMU's MultiComp Lab, a lightweight, multitask model for facial landmarks, Action Units, gaze, and emotion recognition. Hu, J., Mathur, L., Liang, P. P., & Morency, L.-P. (2025). OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysis. FG 2025 / arXiv:2506.02891. - LibreFace (2024): an open-source deep-learning toolkit for AU detection, AU intensity, and expression recognition. Chang, D., Yin, Y., Li, Z., Tran, M., & Soleymani, M. (2024). LibreFace: An Open-Source Toolkit for Deep Facial Expression Analysis. WACV 2024. - LibreFace 2.0 (2026): an update of LibreFace that retrains its models with a large synthetic dataset to improve generalizability, and adds gaze estimation. Guan, X., Chaubey, A., Siniukov, M., Hsieh, A., Li, Z., & Soleymani, M. (2026). LibreFace 2.0: A Generalizable Facial Expression Analysis Toolkit Leveraging Synthetic Data. IEEE FG 2026. - pyAFAR (2023, infant extension 2024): a Python library for AU detection in adults and, since 2024, infants. Cohn, J. F., et al. (2023). PyAFAR: Python-based Automated Facial Action Recognition library for use in Infants and Adults. IEEE ACII 2023; infant extension: Ertugrul, I. O., Hinduja, S., Bilalpur, M., Messinger, D. S., & Cohn, J. F. (2024). Expanding PyAFAR: A Novel Privacy-Preserving Infant AU Detector. IEEE FG 2024. 3. How we tested Emotion classification was tested on the same two benchmark datasets as our original comparison: the Amsterdam Dynamic Facial Expression Set (ADFES) and the Warsaw Set of Emotional Facial Expression Pictures (WSEFEP). Action Unit detection is harder to compare directly, because each tool detects a different number of AUs: FaceReader 10 outputs 20 (with intensities), LibreFace and LibreFace 2 each cover 17 (12 intensities and 5 binary), OpenFace 2.2 outputs 16, pyAFAR outputs 14, and OpenFace 3 outputs 8. To keep each comparison fair, we scored FaceReader only on the specific AU subset each competing tool supports, then compared F1 scores (the balanced measure of precision and recall) on that shared subset. That's why FaceReader's own score shifts slightly from one comparison to the next below, as it's being evaluated on a different, smaller slice of its 20 AUs each time, matched to what the competing tool can detect. A note on the two LibreFace versions: they output graded intensity values for 12 of their 17 AUs and binary presence labels for the remaining 5. Where an AU offers both types of output, our analysis used whichever was more accurate for that AU. Infant facial expression analysis was tested separately, on the BabyFACS manual test set (Maroulis et al., 2017; Oster, 2006), since it uses infant-specific Action Units that don't appear in the adult ADFES/WSEFEP data. 4. Basic emotion classification accuracy Classifying the six basic expressions plus neutral on ADFES + WSEFEP: ToolAccuracyF1 score FaceReader 1098%98% LibreFace93%93% LibreFace 291%*91%* OpenFace 388%88% * LibreFace 2 was scored on five basic expressions plus neutral: at the time of testing, the tool never output the Disgust category, so Disgust was excluded from its evaluation. All other tools were scored on all seven categories. 5. Action Unit detection F1 score on each tool's own supported AU subset, matched against FaceReader 10 on that same subset: Competing toolAUs supportedTool's F1FaceReader's F1 (same AUs) OpenFace 3881%88% OpenFace 2.21661%81% pyAFAR1441%80% LibreFace12 intensity + 5 binary58%81% LibreFace 212 intensity + 5 binary56%81% FaceReader 10 outperforms every tool on its own AU subset, and detects more AUs overall (20) than any of the five alternatives. Read more about the validation of the FaceReader 10's action units against an annotated dataset. 6. Infant facial expression analysis Of the five tools compared, only pyAFAR has an infant-specific model, covering 7 Action Units. On the BabyFACS manual test set (a subset of these 7 AUs), FaceReader 10's baby model scores meaningfully higher: ToolAUs (infant model)F1 score pyAFAR (infant)744% FaceReader 10 (baby model)765% 7. Beyond the numbers: usability and support Accuracy isn't the only thing that determines how usable a tool is day-to-day: - Interface: OpenFace 2.2 and pyAFAR ship with a minimal graphical interface. OpenFace 3 and LibreFace are primarily Python libraries, so using either means writing and maintaining your own code. FaceReader is a complete application with a GUI, visualization, and reporting built in, no coding required. - Update cadence: open-source tools have released major versions at very irregular intervals. OpenFace, for example, went seven years between 2.2 (2018) and 3.0 (2025). FaceReader, by contrast, ships a new version roughly every one to two years. - Support: FaceReader includes direct vendor support and training; open-source tools rely on community forums and, for the academic projects here, the availability of the original research groups. 8. FAQ Is OpenFace 3 better than OpenFace 2? Not straightforwardly. OpenFace 3 is a lighter, faster rebuild, but it detects far fewer Action Units than OpenFace 2.2 (8 for OpenFace 3 vs. 16 for OpenFace 2.2), and on that smaller set, FaceReader's advantage over OpenFace 3 (81% for OpenFace 3's F1 vs. 88% for FaceReader 10's F1) is narrower than its advantage over OpenFace 2.2 (61% for OpenFace 2.2's F1 vs. 81% for FaceReader 10's F1). Whether OpenFace 3 is a net upgrade depends on which AUs a given study actually needs. Is LibreFace 2 an upgrade over the original LibreFace? Partly. LibreFace 2.0 retrains its models on a large synthetic dataset to improve generalizability and adds gaze estimation. On our benchmarks its overall Action Unit score came out close to the original's, with most relative improvement seen in binary prediction of AU presence (without intensities). As with OpenFace 3 versus 2.2, whether it's a net upgrade depends on what a given study needs. Why does FaceReader's score change in each Action Unit comparison? Because each competing tool supports a different, smaller number of AUs than FaceReader's full 20. To keep the comparison fair, FaceReader is scored only on the specific AUs each tool detects, so its score reflects a different subset each time, not an inconsistent result. Can any open-source tool analyze infant facial expressions? Of the tools compared here, only pyAFAR has an infant-specific model (7 Action Units, added in 2024). FaceReader 10's baby model covers the same 7 AUs and scores higher on the BabyFACS benchmark. Do I need to write code to use these open-source tools? For OpenFace 3, LibreFace, and LibreFace 2, yes. All three are distributed primarily as Python libraries. OpenFace 2.2 and pyAFAR include a minimal graphical interface, though still far more limited than a purpose-built application. What datasets were used for this comparison? Emotion classification was tested on ADFES and WSEFEP, the same datasets used in our original FaceReader-vs-OpenFace comparison. Infant Action Unit detection was tested separately on the BabyFACS manual test set. Curious how FaceReader fits your research? Talk to our team or request a demo to see how FaceReader 10 handles your specific study design. 9. Related reading - How Are Emotions Made? A Complete Guide to the Science of Emotion: background on how and why researchers measure emotion. - What Is Biometric Research?: how facial expression analysis fits alongside eye tracking, GSR, EEG, and ECG. - 8 Reasons Why FaceReader Outperforms OpenFace (2025): our original OpenFace-only comparison. References Stöckli, S., Schulte-Mecklenbeck, M., Borer, S., & Samson, A. C. (2018). Facial expression analysis with AFFDEX and FACET: A validation study. Behavior Research Methods (50), 1446–1460. https://doi.org/10.3758/s13428-017-0996-1 Baltrusaitis, T., Zadeh, A., Lim, Y. C., & Morency, L.-P. (2018). OpenFace 2.0: Facial Behavior Analysis Toolkit. IEEE FG 2018. Hu, J., Mathur, L., Liang, P. P., & Morency, L.-P. (2025). OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysis. arXiv:2506.02891. Chang, D., Yin, Y., Li, Z., Tran, M., & Soleymani, M. (2024). LibreFace: An Open-Source Toolkit for Deep Facial Expression Analysis. WACV 2024. Guan, X., Chaubey, A., Siniukov, M., Hsieh, A., Li, Z., & Soleymani, M. (2026). LibreFace 2.0: A Generalizable Facial Expression Analysis Toolkit Leveraging Synthetic Data. IEEE FG 2026. Cohn, J. F., et al. (2023). PyAFAR: Python-based Automated Facial Action Recognition library for use in Infants and Adults. IEEE ACII 2023. Ertugrul, I. O., Hinduja, S., Bilalpur, M., Messinger, D. S., & Cohn, J. F. (2024). Expanding PyAFAR: A Novel Privacy-Preserving Infant AU Detector. IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG) 2024. https://doi.org/10.1109/FG59268.2024.10581868 Van der Schalk, J., Hawk, S., Fischer, A., & Doosje, B. (2011). Moving faces, looking places: Validation of the Amsterdam Dynamic Facial Expression Set (ADFES). Emotion (11), 907–920. Olszanowski, M., Pochwatko, G., Kuklinski, K., Scibor-Rylski, M., Lewinski, P., & Ohme, R. (2014). Warsaw set of emotional facial expression pictures: a validation study of facial display photographs. Frontiers in Psychology (5). Oster, H. (2006). Baby FACS: Facial Action Coding System for Infants and Young Children. Maroulis, A., Spink, A. J., Theuws, J. J. M., Oster, H., & Buitelaar, J. (2017). Sweet or sour. Validating Baby FaceReader to analyse infant responses to food. Poster presentation, 12th Pangborn Sensory Science Symposium, 20–24 August 2017. --- ## The complete guide to behavioral observation URL: https://noldus.com/blog/guide-behavioral-observation Published: 2026-08-25 00:00:00 Description: Behavioral observation is essential to reliable research, training, and clinical work. Learn what it is, why it matters, and how to implement it effectively without sacrificing time or consistency. Behavioral observation is essential to reliable research, training, and clinical work. Learn what it is, why it matters, and how to implement it effectively without sacrificing time or consistency. Frame by frame. Eight hundred hours of manual observation, behavioral coding, and analysis to capture subtle expressions during social interaction (smiling, eye contact, hesitation) in a single behavioral study. This challenge isn't unique. Whether you're conducting research, running training programs, or assessing clinical competency, behavioral observation is essential, but the traditional method is a time sink that doesn't match the scope and complexity of modern work. The complete guide to Behavioral Observation: What it is and how to do it right Behavioral observation is everywhere in serious research. It shows up in psychology research measuring human cognitive processes, learning patterns, and social interaction. In education and training programs assessing professional competency and skill development. In clinical settings validating therapy outcomes. In child development research and behavioral change across the lifespan. The method is foundational and that's exactly why the friction around how it's done matters so much. This guide shows you what behavioral observation is, why it's critical to research that holds up, and how to implement it so that reliability doesn't require your team to sacrifice time or consistency. You'll understand the method's real strengths, where it struggles, and how to navigate both. By the end, you'll have a clear framework for designing an observation program that scales with your research ambitions. Contents - What is Behavioral Observation - The challenges with traditional observation methods - The shift to digital observation and automation: video analysis - Best practices for Behavioral Observation - Why Noldus is the leader in Behavioral Observation software - Next steps: Your Behavioral Observation Journey What is Behavioral Observation? Defining behavioral observation in modern research Behavior is observable and measurable, the things people say and do in specific moments. Observing that carefully is where understanding begins. Behavioral observation means creating a structured, detailed record of what happens — this is behavioral coding. Usually video analysis is involved, sometimes live notes. The goal is to capture what actually occurred, without interpretation or bias. A therapist's tone. A researcher's hesitation. A student's eye contact. These are observable facts, not impressions. The power of observation is that it replaces "seemed" with "happened." Instead of "The patient appeared anxious," you have a record showing specific markers: speech pace, facial expression, body position. That shift from subjective feeling to documented behavior is what makes structured observation reliable. This matters whether you're a researcher studying cognition, a trainer assessing skills, or a clinician evaluating progress. The method is the same, but the application changes. The tools that enable such work have evolved faster than we might realize. Today, behavioral observation software streamlines the process, but the foundation remains unchanged: careful attention to what actually happens. Why observation matters (across disciplines) Behavioral observation isn't niche, in fact, it's foundational to reliable research and training across multiple fields and application areas. Psychology and neuroscience research, including studies on learning, cognition, memory, social behavior, all depend on behavioral observation to move beyond correlation into mechanism. You don't just measure outcomes; you measure how subjects interact with tasks, with each other, and with stimuli. That level of detail is what lets researchers understand move beyond correlation to cause and effect. Education and training programs, including medical and nursing education, use behavioral observation to assess professional competency and skill development in ways that grades and exams cannot. You're not evaluating knowledge; you're evaluating performance. A nursing student can know the steps of a procedure where behavioral observation shows whether they actually do them, in sequence, under pressure. Medical educators assess clinical skills through the same lens of structured observation of actual behavior. Real-world example Training beyond healthcare: using FaceReader to track pilot trainees' emotional valence in real time as a measure of engagement and motivation: Cognition in the cockpit: assessing instructional modalities in pilot training simulations. DOI: https://doi.org/10.3389/fpsyg.2025.1625321 PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC12599332/ Clinical competency and research relies on behavioral observation to measure therapy outcomes and skills with precision. Instead of asking, "Did the therapy work?", you can measure whether "Patient displayed 47% more positive affect markers in session 10 versus session 1." That's powerful, publishable data driving evidence-based methods into practice. Real-world example Check out how a research team built, validated, and assessed rater reliability of their trauma team leadership rating scale across 360 real, clinical videos with The Observer: Validity evidence of a resuscitation team leadership assessment measure for use in actual trauma resuscitations. DOI: https://doi.org/10.1002/aet2.11061 PMC: https://europepmc.org/articles/PMC11975050 Professional interview and interaction skills assessment rely on behavioral observation to evaluate how someone communicates, manages pressure, builds rapport, handles conflict, or responds to feedback. You're documenting exactly what changed instead of guessing whether the trainee "got it." The common thread across all these fields is that behavioral observation transforms subjective impression into objective, comparable, and reviewable data. From that, insights and actionable measures can be taken. That shift is why the method is trusted, and why getting it right matters so much. Types of behavior Behavioral observation captures different types of behavior through behavioral coding. Overt behavior is what you can directly see and measure: hand movements during a procedure, eye contact during conversation, or a pause in speech. These are the visible actions you are recording. Covert behavior is internal: thinking, hesitation, uncertainty. You can't see it directly, but it manifests through facial expressions, tone, or timing. That's where careful observation catches the clues like a furrowed brow, a longer-than-usual silence, or a shift in posture. These subtle markers reveal what someone is experiencing. Social behavior is how people interact. This includes who speaks first, how they respond to each other, and whether there's rapport. In training contexts, this is critical, as you are watching how someone engages with another person rather than just individual performance alone. Good observation captures all three types of behavior in context. It's not enough to see the action (overt), you also need to notice the hesitation or confidence markers (covert), and you need to understand the relational dynamics (social). That's what makes observation in training and education so powerful — you're seeing the whole picture. The challenges with traditional observation methods Observing behavior sounds simple. Watch, notice, remember, evaluate. In practice, it's much harder than it sounds, especially when you're in the moment and there's too much happening at once. You don't want to miss what happens in real time Real-time behavioral observation has a core fundamental problem: you can't be everywhere at once, and you can't rewind what you've already seen. For example, a trainer watches a student practice a clinical skill. The trainer catches most of it but misses the exact sequence of hand movements. Or, a supervising counselor observes a session, and they notice the therapist's tone shift, but they don't catch the micro-expression on the client's face that triggered it. Perhaps a teacher watches group interaction and by the time they focus on one student, they've missed what another student did. Once the moment passes, it's gone. You're left with impression, not data, and impressions are incomplete at best. You need consistency and structure in your observations The same behavior looks different depending on who's observing and what they're focused on. Imagine a student performing a medical procedure in 45 seconds. One observer codes it as efficient, yet another sees it as rushed. Same action, different judgment. Neither is wrong, they're just seeing through different lenses. This inconsistency is invisible while you're observing. It only shows up later, when you compare notes with a colleague and realize you saw very different things. You need to capture the details that matter Observing in real time creates a problem: too much information, limited working memory, no rewind or review. You're watching a student's clinical assessment. You need to track: hand positioning, communication clarity, patient engagement, procedural steps, timing, eye contact. That's a lot to hold simultaneously while you're also trying to stay present in the moment. So you let some of it go. You focus on what seems most important and lose track of the rest or you observe only at certain moments. Later, when you try to give feedback, you realize you can't recall the specific sequence of events or some events are missing altogether. You remember the overall impression, but not the details that matter. This is why observation-based assessment often relies on general impressions ("strong performance") rather than specific, actionable feedback ("you did X well, and here's how you could improve Y"). You need to observe without cognitive overload Real-time observation while doing something else is cognitively expensive. If you're the teacher in the room, you can't simultaneously teach and observe. You're managing the group, answering questions, watching the clock. The observation happens around the edges of everything else you're doing. If you're watching from the sidelines (like in a supervision or training context), you can focus more, but you're still holding multiple things: what you're supposed to look for, what you've already seen, what you think is important, what you should write down. These are all important feedback points for your trainees. The result of real-time overload: fatigue. After 30 minutes of observation, your attention wavers. After an hour, you're losing details you would have caught earlier. You become an unreliable narrator of the behavioral events that are so important to your work. You need to be able to review what you observe Real-time observation is also permanent once it happens. You see something once. If you misread it the first time, you don't get a second chance. You can't slow it down, you can't pause and think about what you just saw. This matters especially for brief behaviors: a facial expression, a hesitation, a tone shift. These happen in milliseconds. See it clearly the first time, or miss it entirely. The result is that subtle, important behaviors go unnoticed. The shift to digital observation and automation: video analysis From live observation to recorded observation Tools have fundamentally changed what's possible when you observe. Before video, observation was live and gone. You watched, you noted what you remembered, and that was it. You got one chance to see it right. Video changed everything. Suddenly you could record behavior once, then review it as many times as you needed. You could slow it down, rewatch ambiguous moments, catch details you missed the first time: a micro-expression, a hesitation, a pause. Things that happen too fast to see in real time become visible when you slow down and replay. Digital video platforms and video analysis took this further. Easily timestamp moments or jump between clips. Compare the same behavior across different recordings and derive data directly from your observations. Annotation tools like The Observer and NoldusViso let you mark observations directly on video without transcribing notes later. Each shift made behavioral observation itself more reliable and less dependent on real-time attention. How technology enables better behavioral observation The shift from manual to digital observation isn't just faster. It also makes observation itself more effective. Replay ability is the gamechanger. Digital video lets you review what you observed multiple times at normal speed, slow speeds, or rapidly to advance downtime. You can also zoom in, rewatching moments you were unsure about and getting a closer look. Catch details that flash past too quickly in real-time observation. Timestamps and markers, along with easy-to-use marking methods, let you organize your observations without pulling attention away from watching. Mark important moments as they happen and revisit them later. Compare the same behavior across different recordings but using the same annotation criteria. These are the patterns you'd certainly miss watching live. With technology, collaboration becomes easier, as well. Multiple people can watch the same recording and note what they see, then compare observations directly. You discover where you agree and where your interpretations diverge. That transparency builds confidence in what you've actually observed and allows for refinement of coding schemes and behavioral coding in general. It is only with digital observation tools that scale becomes possible. One observer with good behavioral observation software can watch and document substantially more material than manual real-time observation allows. Larger groups, more sessions, more thorough observation, within realistic time. Learn more about The Observer's user-friendly coding features. Smart observation tools Many trainers wonder: will video analysis tools replace my judgment? The answer is no. These tools are designed to support you, not replace you. Tools excel at recognizing structured observation patterns: interaction timing that reveals confidence or hesitation, facial expressions that signal engagement or confusion, gaze patterns that show attention or avoidance. Software can flag moments where these patterns appear, without you having to watch every second of video. That's powerful for speed and for interpretation. Tools also enable collaboration and data collection across distances. Multiple observers can watch the same recording and annotate simultaneously, even if they're in different locations. Observations can also be spread across geographies, creating a more diverse data set. This means you can bring in expertise and information from elsewhere, without everyone needing to be present at the same time or place. Modern observation platforms like NoldusViso or The Observer make this seamless. Free download See how NoldusViso facilitates sharing and collaboration. Get your copy instantly Of course, tools also have real limitations and require humans in-the-loop. For example, ambiguous behavior, the moments where context matters, still requires your discernment and interpretation. Is that pause a thoughtful moment or avoidance? Is that facial expression genuine confusion or polite attention? These questions need human intelligence informed by training context and observation expertise. Think of observation tools as a helper, not a decision-maker. Tools point out moments worth watching while you decide what they mean. That's where the real benefit comes in: tools save you time by finding the important moments, and you bring the expertise to interpret them correctly. Best practices for Behavioral Observation Understand that behavior is automatic Most people underestimate habit's influence. For example, research performed by Rebar and colleagues found that 65% of all actions are initiated out of habit, and 88% of actions are performed on autopilot. This means the majority of what people do each day is driven by automatic processes, not conscious deliberation. When you're teaching someone a new skill, they're not just learning the steps. They're trying to override automatic patterns and build new ones, which is cognitively demanding. It's why people slip back into old habits, why training can take time and repetition, and why feedback alone often isn't enough. This matters for observation: watch not just whether someone does the skill right, but where they hesitate, where they speed up, or where they revert to old patterns. Those moments of struggle are where learning is actually happening. Understanding this helps you give better feedback, design better training programs, and establish realistic expectations about behavioral change. Know what you're looking for before you start This sounds basic, but it's where observation often goes wrong. Before you observe, be clear about what matters. What specific behaviors or moments are you looking for? - Confidence markers - Communication patterns - Clinical procedure steps - Hesitations Write it down. Share it with others who'll observe with you and practice to see what fits and what needs to be adjusted. Test your focus list on a short observation first. Does it actually help you see what you intended? Does something important slip through because you weren't looking for it or it was inadequately defined? Refine based on what you learn. This upfront clarity makes observation more reliable without making it rigid. Read the top 5 coding-scheme decisions you cannot undo later. Observing interaction patterns and professional skills Not all observation is about individual actions. Some of the most important behavioral data is about how people interact with each other. In interview and interaction skills assessment, you're not just watching whether someone answers questions. You're watching how they listen, how they respond to feedback, and how quickly they recover from a mistake. You're observing their communication rhythm, their emotional regulation, and their ability to build rapport with others. In counselor supervision, it's not just about whether the therapist asked the right question. It's about the therapeutic alliance between the parties: how the client responds to the therapist, whether there's genuine engagement between them, or where tension emerges. In professional coaching contexts, you're observing how someone handles pressure, receives feedback, and adapts in real time within a social context. These kinds of observations require a different focus, as you're not timing specific actions in isolation, but instead you're tracking relational dynamics, communication patterns, and behavioral responsiveness. That demands precision in your codebook, repeated coding passes, and clarity about what you're measuring. The principle remains the same: define what you're looking for, observe systematically, and code reliably. Multiple observers strengthen observation One person's observation is limited. Multiple observers catch what one person might miss. How does it work? Have more than one person watch the same interaction (or the same recording). They don't need to be in the same room, or even the same location as modern tools like NoldusViso or The Observer make it possible for observers to watch and annotate together remotely. Don't try to agree beforehand; just observe and then compare what each person noticed. What did they both catch? Where did they see differently? Those differences are valuable. They show you where behavior is ambiguous or where personal interpretation enters. They also show you where observation was clear and consistent. Both help establish calibration and training practices for coders. Real-world example Check out this real-world example of building and validating a codebook, calibrating coders and creating training guides using The Observer XT: A software-based observational coding approach for evaluating paediatric dental pain, anxiety, and fear. DOI: https://doi.org/10.1111/ipd.13227 PMC: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724945/ Manage video data ethically and securely Behavioral observation generates sensitive data and it's important to treat it accordingly. Here are our top tips for managing this properly: Ethical & Secure Video Management A Quick Checklist Use these key steps to ensure behavioral video data is managed ethically, securely, and responsibly. how_to_reg Start with consent Subjects must know they're being recorded and observed (or your study design must have ethical justification for covert observation). encrypted Secure storage is critical - Video files contain identifiable information, faces, voices, context. - Store these files on encrypted, access-restricted servers and implement role-based permissions. - Only people who need the files can access them. - De-identify where possible by assigning subject ID numbers instead of names. - Redact identifying information in transcripts. event_busy Establish retention & deletion protocols When do video files get deleted? When do coded datasets expire? Make these decisions upfront and document them. Train your team on data security Everyone handling video must understand confidentiality expectations. Keep it audit-ready Document all of this in your study protocol, ready for checks by auditors and regulators. Learn more about NoldusViso's security standards. Design observation workflows that stay consistent at scale and grow with you Quality observation needs structure but leave room for flexibility and growth. One way to tackle this is to build regular checkpoints into your observation. Pause periodically to confirm your notes are clear and your observations are staying consistent over time and over observers. Modify your coding schemes to incorporate any new additions found along the way. Use tools like behavioral observation software to handle logistics and details, while also allowing for future growth of your program. Basics, like timestamping, should be automatic and notes, should be easy to revisit. What about adding functionality as your needs shift — features like multi-room recordings and multimodal observations. Your tool should get out of the way and let you focus on observing while also leaving room for more. Real-world example See how multimodal observation scales over time and complexity; a longitudinal multimodal study capturing more than just coding alone with Viso and The Observer: Infant sustained attention differs by context and social content in the first 2 years of life. DOI: https://doi.org/10.1111/desc.13500 PMC: https://europepmc.org/articles/PMC11608077 Why Noldus is the leader in Behavioral Observation software 35+ years of behavioral observation expertise Noldus Information Technology was founded in 1989 with a singular focus: behavioral observation software. That focus matters. For three decades, Noldus has invested in understanding how observation actually happens, what tools observers really need, and how to support both research reliability and practical effectiveness. That longevity means Noldus understands behavioral observation from the ground up. Systematic behavioral coding at scale The industry standard for detailed behavioral analysis, The Observer, is purpose-built for researchers who need precise, reliable coding of complex behavioral data. Whether you're coding interaction patterns, analyzing learning behavior, or conducting clinical research, this software provides the structured tools for systematic observation. Many research teams use it as their foundation for rigorous behavioral work. Video observation for real-world practice NoldusViso is built for real observation work wherever it happens. In training programs, in research labs, and in clinical settings. It excels in any environment where understanding behavior through video matters. The software is built for practitioners, not just researchers. The process is simple: record interactions once, then review them as many times as you need. Slow down, rewatch, or compare moments. Mark what matters directly on video for future review and debriefing. No complex setup and no rigid procedures. For trainers, NoldusViso facilitates better feedback. For researchers studying interaction or behavior change, it means reliable, detailed observation. For clinicians, it means precision in assessment. In every context, you have the actual video recording to revisit and analyze instead of relying on memory or pen and paper alone. That's the foundation. What the software adds is consistency: making observation reliable, structured, detailed, and transparent. Exploring behavioral research beyond observation Observation is one dimension of understanding human behavior. Noldus also offers complementary tools for measuring emotional responses, engagement, and other behavioral indicators. Explore the full Noldus human behavior research toolkit to discover solutions for your specific research or training needs. Commitment to supporting observation work and setting industry standards Noldus isn't neutral on what observation practitioners need nor are we inventing solutions that don't fit the users. We actively source input from real users doing observation across disciplines and build tools around that reality. Data security and privacy are fundamental: encrypted storage, role-based access, and compliance with relevant security and privacy legislation. For Noldus, that's non-negotiable when observation involves sensitive information. Our approach goes beyond providing a tool and simple technical support. We focus on customer success: helping practitioners understand and get the most from their tools so that their outcomes are realized. We actively work alongside people who understand behavioral observation, through partnerships with research institutions, training programs, and clinical teams. Next steps: Your Behavioral Observation Journey Behavioral observation looks different across contexts. Your next step: contact us to discuss how behavioral observation works in your specific setting. We can help you design an observation system that scales with your research or training goals. contact_mail Get in touch! Or explore these resources: description Behavioral Observation FAQs checklist Implementation Checklist Contact us arrow_forward Summary Behavioral observation is a method with timeless principles and constantly evolving tools. The core idea is simple: watch systematically, observe reliably, and turn impression into actionable insight. The challenges are real: you miss things in real time, your observations drift, details escape you, it's easy to see what you expect instead of what actually happens. Modern tools make rigorous observation feasible at a scale that would have been unthinkable 20 years ago. The field now has clear best practices: - Know what you're looking for before you start. - Bring multiple observers to catch what one person misses. - Understand the difference between observing individual actions and observing interaction patterns. - Check alignment regularly to catch drift early. - Manage data ethically. - Maintain consistency at scale. Organizations that implement these practices don't just collect better observations, they train more effectively, they give better feedback, they evaluate professional competency more accurately. They make better decisions backed by evidence instead of impression. That's why behavioral observation matters. And that's why getting it right matters too. References Bocklage C, Selden R, Tumsuden O, et al. (2025). A software-based observational coding approach for evaluating paediatric dental pain, anxiety, and fear. International Journal of Paediatric Dentistry (35), 241-258. https://doi.org/10.1111/ipd.13227 Bradshaw, J., Fu, X., & Richards, J. E. (2024). Infant sustained attention differs by context and social content in the first 2 years of life. Developmental Science (27). https://doi.org/10.1111/desc.13500 Choi E, Yoo L, Shin S, and Jung D (2026). Mealtime Support by Direct Care Workers in Long-Term Care Facilities: Secondary Behavioural Analysis of Videos. Journal of Advanced Nursing (82):3135-3147. https://doi.org/10.1111/jan.70067 Kofler MJ, Soto EF, Rapport MD and Whitehead S. (2025) Ecological Validity of Clinic-Based Actigraphy for Assessing Hyperactivity in Clinically Evaluated Children with and without ADHD. Journal of Psychopathology and Behavioral Assessment (47). https://doi.org/10.1007/s10862-025-10218-8 Rebar AL, Vincent G, Le Cornu KK, and Gardner B (2025). How habitual is everyday life? An ecological momentary assessment study. Psychology & Health (18), 1-26. https://doi.org/10.1080/08870446.2025.2561149 Rochon L-J, Karran AJ, Rolon-Merette T, Courtemanche F, Coursaris C, Senecal S, and Léger P-M (2025) Cognition in the cockpit: assessing instructional modalities in pilot training simulations. Frontiers in Psychology (16). https://doi.org/10.3389/fpsyg.2025.1625321 Rosenman ED, Grand JA, Fernandez R. (2025). Validity evidence of a resuscitation team leadership assessment measure for use in actual trauma resuscitations. AEM Education and Training (9). https://doi.org/10.1002/aet2.11061 --- ## Free to roam: the open field test is a behavioral staple URL: https://noldus.com/blog/open-field-test Published: 2026-08-24 10:00:00 Description: Researchers reach for the open field test for many different goals: a general locomotor screening, an anxiety readout. In this blog we explore what it measures, how recent studies are using it, and how to set it up in your lab with EthoVision. Researchers reach for the open field test for many different goals: a general locomotor screening, an anxiety readout. In this blog we explain what the test actually measures, look at how labs are pairing it with EthoVision across a wave of recent studies, and share practical tips for running it well. Few behavioral tests get used for as many different reasons as the open field. Depending on the question a lab is asking, the same arena and the same footage can serve as a general health and locomotor screen or a dedicated anxiety-like behavior test. It sounds simple, just an arena and a camera. However, it is the question that makes the open field test interesting and varied. That adaptability is why it has remained an important part of behavioral neuroscience for nearly a century. What is the open field test? The open field test is a behavioral assay that measures locomotor activity, exploration, and anxiety-like behavior by placing an animal in an enclosed arena and recording how much it moves and how much of the space it uses. It consists of an enclosed arena, usually round or square. An animal is placed in it and filmed from above for a fixed period, typically five to ten minutes. Unlike many other behavioral tests, there is no reward or task for the animal to learn: the whole test rests on the arena being novel. Arena size and material vary with the species and the question being asked, but the basic logic is the same everywhere: give an animal room to move and make sure there is enough contrast between the material and the animal. The inception of the open field dates back to the 1930s. Calvin Hall used it to study individual differences in 'emotionality' in rats, scoring defecation and urination as crude proxies for fear [1]. Hall and later researchers noticed that rats didn't move through the arena randomly. They stayed close to the walls, venturing into the open center only gradually, if at all. This wall-hugging tendency has a name: thigmotaxis. And this is still the single most-reported measure in open field studies today. What is Thigmotaxis? Thigmotaxis is generally read as a sign of anxiety-like behavior. The center of an exposed arena is aversive. So, animals that spend more time there or enter the space more often are typically interpreted as less anxious [2, 3]. That interpretation isn't universally accepted. Critics argue that the open field really captures a fear-driven avoidance response rather than anxiety in a more general sense, and that a proper anxiety test needs both an aversive and an appetitive pull to be meaningful [2]. Most labs sidestep this debate. They treat the open field as a first-pass screen — a quick check for gross changes in locomotion and exploration before moving on to more targeted tests. Applications and recent research: pairing the open field with EthoVision The open field is used for a great variety of applications. Across the studies below, researchers extracted the same handful of measures (distance traveled, time in the center versus the periphery, velocity, entries into defined zones) using EthoVision video tracking. Toxicology and chemical exposure Ko and colleagues provided the first experimental evidence that polyhexamethylene guanidine phosphate (PHMG-p), a humidifier disinfectant chemical tied to South Korea's mass lung-injury cases, is neurotoxic in mice. EthoVision tracked open field distance and center-zone time alongside elevated plus maze and forced-swim behavior. Exposed mice showed hypoactivity and anxiety-like behavior that tracked with cortical neuron and synapse loss [4]. In zebrafish, Pompermaier and colleagues used EthoVision to quantify distance, turn angle, and center/periphery time in larvae exposed to a diquat-based herbicide. The herbicide altered exploratory behavior alongside survival and heart-rate effects, even at environmentally relevant concentrations [5]. Stress, immunity, and the gut-brain axis Yao and colleagues linked long-term social isolation during adolescence to worse outcomes after a simulated heart attack in mice. Open field center time and distance, alongside elevated plus maze and forced-swim measures, established an anxiety and depression phenotype that correlated with reduced cardiac function [6]. Mo and colleagues took the opposite approach. They tested whether a probiotic, Lactobacillus reuteri, could reverse LPS-induced depression- and anxiety-like behavior via the gut-brain axis. EthoVision-tracked open field distance and center/periphery time showed the probiotic restored locomotion and reduced center-avoidance behavior [7]. And Yuan and colleagues found that knocking out acid sphingomyelinase, an enzyme linked to toll-like receptor immune signaling, left mice with restricted open field activity and less time in the center. That's a heightened-anxiety profile, consistent with an immune contribution to anxiety-like behavior [8]. Neurodegeneration and neurodevelopmental models The open field is a fixture in disease-model phenotyping. Shetty and colleagues included it among several assays showing altered exploratory behavior in mice lacking a neuronal RNase complex, alongside impaired long-term spatial memory [9]. Jin and colleagues used open field testing to support a PI3K/AKT pathway analysis of a fruit-juice concentrate's neuroprotective effects in a Parkinson's disease mouse model [10]. Buglinina and colleagues tracked open field distance, speed, and center-zone entries in mice after spinal cord injury. Knocking out the receptor TAAR5 sped up motor recovery, but it did not reduce anxiety-like behavior, which stayed elevated regardless of genotype [11]. In a maternal immune activation model of autism, Zhang and colleagues found that neutralizing IL-6 largely reversed the anxiety-like behavior seen in open field and elevated plus maze testing. It left the model's core social-deficit and repetitive-behavior measures untouched [12]. Sex differences and specificity controls Several recent studies used the open field to check whether an effect held up, or differed, across sexes. Gellman and colleagues compared an endocannabinoid-like lipid and a synthetic CB2 agonist in a genetic rat model of depression. Open field tracking revealed a clear sex split: the endocannabinoid-like compound was anxiolytic in males, but anxiolytic and antidepressant in females [13]. Sacko and colleagues used open field distance and center-zone time as a specificity control when testing a BET inhibitor's effect on cocaine-seeking in rats. Those measures were unchanged by the drug, so the researchers could rule out general sedation as an explanation for the reduced drug-seeking they saw elsewhere [14]. In a pilot study of paclitaxel-induced peripheral neuropathy, Kim and colleagues recorded open field behavior in a PhenoTyper home-cage observation arena running EthoVision. Chemotherapy reduced locomotion and rearing in male rats, with only milder locomotor effects in females [15]. Early-life adversity Bonauto and colleagues combined the open field with playback of aversive, rat-specific alarm calls to probe how early-life adversity shapes affective processing in juvenile rats. EthoVision-quantified locomotion and center-zone exploration, during baseline and playback, revealed sex-specific responses to the threat cue. The open field can capture not just a resting anxiety state, but how an animal responds to a stressor introduced mid-test [16]. Beyond rodents The open field translates well to other model species. Herrera-Castillo and colleagues used EthoVision to track thigmotaxis and center/periphery time in goldfish, testing whether food-anticipatory activity reflects a ghrelin-driven anxiety state. Ghrelin-receptor antagonists reduced the anxiety-like behavior seen before scheduled feeding. That ties a metabolic hormone directly to an exploration-based measure [17]. Free Trial Want to try EthoVision with your own open field videos? EthoVision is the gold standard in video tracking for behavioral research. Request a free trial and see how EthoVision automates your open field analysis. Try it now! Tips for using the open field test with EthoVision - The open field is forgiving. But a few habits can make the difference between clean data and a noisy dataset with unreliable results. - Habituate the room, not just the arena. Move animals to the testing room and let them settle before the trial starts. A stressful transport or an unfamiliar room can confound the behavior you're trying to measure. - Clean between animals. Residual scent cues from a previous occupant can bias exploration in the next one. A thorough wipe-down with a low-odor disinfectant between trials matters more than researchers assume. - Keep lighting and time of day constant. Both directly influence behavior. A light gradient across the arena, or testing animals at different times of day, can introduce variability that looks like a treatment effect. - Define your center zone deliberately. Center/periphery boundaries are usually set as a fixed proportion of arena area. However, that proportion should be scaled with the species and arena size you're using. A boundary that works for a rat arena won't automatically suit a zebrafish tank. - Keep the experimenter out of view. Animals track human presence. An experimenter lingering in the room during recording can suppress exploration, independent of anything you're testing. - Consider whether you need acute or long-term data. A single five- to ten-minute trial captures a novelty response. However, some questions (general activity patterns, circadian effects, drug time-courses) call for repeated or continuous monitoring. That's why systems like PhenoTyper exist: an instrumented home-cage-style arena with integrated video and EthoVision tracking, built for longer-run phenotyping. - Track more than distance if you can. Rearing, grooming, and freezing all carry information that raw distance traveled doesn't. Automated pose-based tracking can pick these up alongside standard locomotion measures. For more on adapting classic behavioral assays with automated tracking, have a look at our earlier blogs on the Y-maze and the radial arm maze. In summary, some frequently asked questions What does the open field test measure? The open field test measures three things: locomotor activity (distance traveled, velocity), exploratory behavior (rearing, zone entries), and anxiety-like behavior (thigmotaxis, or time near the walls versus the center). Is the open field test an anxiety test? It's usually treated as one. Animals that avoid the exposed center of the arena are interpreted as more anxious. But some researchers argue it measures fear-driven avoidance more precisely than anxiety. They recommend pairing it with a test that includes a rewarding pull, such as the elevated plus maze, before drawing firm conclusions [2]. What is thigmotaxis? Thigmotaxis is the tendency to stay close to walls or edges rather than moving through open space. In the open field test, it's the most commonly reported measure. It's generally read as an index of anxiety-like behavior. How long does an open field test take? Most protocols run a single trial of five to ten minutes per animal, since the test relies on the arena being novel. Longer or repeated exposure changes what's being measured. That's why acute open field testing and longer-term home-cage monitoring, for example with a PhenoTyper system, are treated as different approaches. Can the open field test be used with species other than rodents? Yes. It's been adapted for zebrafish, goldfish, and other species, using the same logic: tracking movement and zone preference in a bounded arena. EthoVision supports tracking across these species. What software is used to score the open field test? Most recent studies use automated video tracking software. The most published software used is EthoVision. Other researchers use Any-maze or open-source tools like DeepLabCut. References - Hall, C.S. Emotional behavior in the rat. I. Defecation and urination as measures of individual differences in emotionality. J. Comp. Psychol. 1934, 18, 385–403. - Prut, L.; Belzung, C. The open field as a paradigm to measure the effects of drugs on anxiety-like behaviors: a review. Eur. J. Pharmacol. 2003, 463, 3–33. - Seibenhener, M.L.; Wooten, M.C. Use of the open field maze to measure locomotor and anxiety-like behavior in mice. J. Vis. Exp. 2015, 96, e52434. - Walsh, R.N.; Cummins, R.A. The open-field test: A critical review. Psychol. Bull. 1976, 83, 482–504. - Ko, M.Y.; Choi, J.; Min, E.; et al. Polyhexamethylene guanidine phosphate exposure induces abnormal behaviors by disrupting synaptic formation and activity in the cerebral cortex. J. Neuroinflammation 2026, 23, 190. - Pompermaier, A.; Chagas, F.B.; Tamagno, W.A.; Freeman, J.L.; Hartmann, P.A.; Hartmann, M. Diquat based herbicide impair the development and behavior of zebrafish embryos and larvae. Sci. Rep. 2025, 15, 42194. - Yao, Y.; Wang, A.; Di, C.; Guo, D.; Zhang, S.; Zong, R.; Qi, R.; Han, Y. Long-term social isolation during adolescence exacerbated cardiac dysfunction after myocardial infarction. Transl. Psychiatry 2026, 16, 193. - Mo, X.; Guo, S.; He, D.; Cheng, Q.; Yang, Y.; Wang, H.; Ren, Y.; Liu, L.; Xie, P. Lactobacillus reuteri DSM 17,938 ameliorates LPS-induced depression-like and anxiety-like behaviors by modulating gut microbiota and brain metabolic function. Gut Pathog. 2025, 17, 65. - Yuan, H.; Xu, Y.; Jiang, H.; Jiang, M.; Zhang, L.; Wei, S.; Li, C.; Zhao, Z. Acid sphingomyelinase modulates anxiety-like behavior likely through toll-like receptor signaling pathway. Mol. Brain 2025, 18, 8. - Shetty, M.S.; Kasuya, J.; Fu, X.; et al. Genetic inactivation of Translin/Trax RNase disrupts miRNAs, hippocampal synaptic plasticity, and memory. iScience 2026, 29, 116188. - Jin, T.; Liu, L.; Kuang, F.; Chen, M.; Chen, H.; Deng, J.; Yang, Y.; Sun, B.; Luo, H. Neuroprotective effects of Rosa roxburghii Tratt juice concentrate powder in Parkinson's disease mice via the PI3K/AKT signaling pathway. Pharmaceuticals 2026, 19, 711. - Buglinina, A.D.; Romanyuk, E.A.; Chesnokov, A.A.; et al. TAAR5 modulates sensorimotor recovery after spinal cord injury. Biomedicines 2026, 14, 796. - Zhang, X.; Luo, W.; He, K.; Li, Y.; Chen, Y.; Xu, Z.; Zhou, Z.-K. IL-6 inhibition partially ameliorates maternal immune activation-induced autism-like behavioral abnormalities in mice. Curr. Issues Mol. Biol. 2025, 47, 852. - Gellman, J.; Zemliana, N.; Loterstein, Y.; et al. Differential effects of oleoyl serine and HU-910 on anxiety-like and depression-like behaviors in male and female WKY rats. Int. J. Mol. Sci. 2026, 27, 3177. - Sacko, T.J.; Seyednejad, A.; Engelhardt, J.; Sartor, G.C. The selective bromodomain and extra-terminal domain (BET) inhibitor RVX-208 reduces cocaine-seeking behaviour and alters proteomic pathways in the nucleus accumbens. Addict. Biol. 2026. - Kim, S.J.; Cao, K.; Dougherty, P.M.; et al. Gender-specific behavior reductions in spontaneous locomotive and rearing in a rat model of paclitaxel-induced peripheral neuropathy: a pilot study. J. Pain Res. 2026, 19. - Bonauto, S.M.; Wilson, P.L.; Honeycutt, J.A. Aversive 22-kHz ultrasonic vocalization playback reveals differences in affective (dys)function following early life adversity in male and female juvenile rats. Behav. Brain Res. 2026, 511, 116272. - Herrera-Castillo, L.; Saiz, N.; de Pedro, N.; Isorna, E. Food reward entrainment increases mealtime anxiety in goldfish via a ghrelin-dependent mechanism. Sci. Rep. 2025, 15, 27768. --- ## Counting the choices: what the radial arm maze teaches us URL: https://noldus.com/blog/radial-arm-maze Published: 2026-08-05 12:00:00 Description: The radial arm maze asks a rodent to remember eight paths at once, without doubling back. We look at how it works, what recent studies discover, and how automated tracking turns each run into precise data. The radial arm maze asks a rodent to remember eight paths at once, without doubling back. In this blog we will look at how the maze works, walk through what recent studies are using it to discover, from neuroinflammation to myelin biology, and look at how automated tracking turns each run through the maze into precise, objective data. Imagine you have eight errands to run, each down its own street, and each street must be visited once. You set off, and every time you reach the end of a street you have to decide, based on what you remember doing already, which street to try next. Doubling back wastes time; forgetting where you have already been, might mean that the shirt you're shopping for is not available anymore. In a wide range of neurological conditions, from Alzheimer's disease to ordinary aging, this exact kind of decision, keeping track of where you have and haven't already been, is one of the first things to falter. The radial arm maze has spent nearly fifty years turning that type of failure into something a researcher can actually measure. What is the radial arm maze? A radial arm maze is a small circular hub with several arms, traditionally eight, branching outward like spokes, each ending in a spot where a food reward can be hidden. Olton and Samuelson designed it in 1976 to study how rats keep track of a shifting list of choices, what they called "serial learning." Almost fifty years on, the maze endures because it does something very useful: unlike a simpler open field or plus-maze, it forces an animal through a whole sequence of choices in a single trial, so one run yields data on many decisions instead of just one. It also sits alongside the family of other spatial memory tests, including the Morris water maze, which asks an animal to find a hidden platform using distal cues, and the Y-maze, which asks it to alternate between three arms. Kohler and colleagues, comparing a classic radial maze to a newer, automated, food-deprivation-free version, note that the maze's core appeal is its ability to separate two memory systems within a single test, without requiring extensive pretraining [1]. The basic radial layout has even been adapted outside of memory research altogether. Ronquillo and colleagues built a three-dimensional radial maze, tracked with EthoVision, to study anxiety-like behavior instead, giving mice a continual choice between open, exposed paths and safer ones [2]. It's a reminder that the maze's real innovation isn't the food reward at the end of each arm, but the repeated, trackable choice in the middle. Two kinds of memory Working memory and reference memory sound similar, but the radial arm maze can distinguish them both. Reference memory is an animal's stable knowledge of the task: which arms, out of all of them, are ever baited at all. Working memory is the moment-to-moment tracking within a single trial: which of those baited arms has already been visited. Because the maze can be configured either way, baiting every arm to test working memory alone, or baiting only some arms consistently to test reference memory as well, researchers can dial in exactly which kind of forgetting they want to study. Applications of the radial arm maze Alzheimer's disease and the search for neuroprotection Does restoring the brain's own housekeeping chemistry help a failing memory? Gall and colleagues tested this in a streptozotocin rat model of sporadic Alzheimer's disease, a model that mimics some of the disease's brain-insulin-resistance features. Over 40 days, rats received melatonin, then ran a radial arm maze recorded and scored with EthoVision. Melatonin-treated rats made fewer working and reference memory errors than untreated model rats, and their brains showed less microglial and astrocyte activation, the hallmark scarring of neuroinflammation [3]. A separate line of work by Kim and colleagues has used the radial arm maze in 5xFAD mice, a strain engineered to overexpress mutant amyloid precursor protein. Across a series of studies, they tested microcurrent stimulation, alone and alongside the Alzheimer's drug donepezil, and reported improved radial maze performance alongside reduced amyloid plaque burden and neuroinflammation [4, 5]. In their most recent pilot combining microcurrent with donepezil, however, the combination only trended toward better performance than donepezil alone, a difference that did not reach statistical significance [6], a useful reminder that not every combination pans out, and that a null result is still a result worth reporting. Diet and inflammation Does what an animal eats, or how inflamed its brain is, shape how well it navigates the maze? The same research group behind the melatonin study also asked whether restoring vitamin D could rescue memory in vitamin-D-deficient rats. Over several weeks, deficient rats ran a battery of tests, including the radial arm maze, tracked and analyzed with EthoVision. Vitamin-D-deficient rats performed worst in both the Morris water maze and the radial maze, while cholecalciferol-supplemented rats learned faster. The same rats, however, showed no difference on the novel object recognition test, a useful reminder that a treatment's benefits don't always generalize across every memory task [7]. A separate study, that also used EthoVision, looked at neuroinflammation more directly. Park and colleagues injected mice with lipopolysaccharide, a bacterial toxin that reliably triggers brain inflammation and behavioral impairment, then treated some of them with quinic acid, a plant-derived antioxidant compound. Mice that received quinic acid made fewer errors in the radial arm maze alongside lower markers of glial activation in the hippocampus [8]. Hunger and exploration Does removing a hunger signal in the brain change how well an animal remembers where the food actually is? Stark and colleagues silenced growth hormone secretagogue receptors, or GHSRs, the receptors that respond to the hunger hormone ghrelin, specifically in the olfactory bulb of mice. During the test, these mice made fewer arm entries and moved shorter distances overall, less motivated to forage. But when the researchers looked specifically at how often the mice chose the correct, rewarded arm over an incorrect one, there was no difference from control mice [9]. In other words, dulling an animal's drive to search did not dull its underlying spatial memory. Aging, genes, and sex differences Does the same maze reveal memory loss differently depending on an animal's genes, or its sex? Borbely and colleagues compared young and aged mice lacking TRPA1, a receptor better known for sensing temperature and pain that also turns up in the brain. Aged wild-type mice made significantly more errors in the radial arm maze, and explored for longer before finding their rewards than young mice did. Aged TRPA1-knockout mice, by contrast, showed a smaller age-related decline. Notably, the same aged mice showed no significant memory difference on the Y-maze or Morris water maze, suggesting the radial arm maze picked up on an age effect that the other two tests missed entirely [10]. Szentes and colleagues found an equally nuanced picture studying mice lacking a somatostatin receptor subtype, sst4, recording every test, including the radial arm maze, with the same EthoVision-based setup. Deleting the receptor altered radial maze performance in female mice but not in males and aging itself improved working memory scores in females while leaving males unchanged [11]. Memory recovery after intense surgery Reproductive surgery is common, but does it change how the brain functions? Koebele and colleagues followed rats for up to a year after hysterectomy (the removal of the uterus), with or without ovary removal, testing them repeatedly in a water-based radial arm maze. Treated rats made more working memory errors than sham-operated rats, and this deficit was still present six weeks, seven months, and a full year after surgery [12]. Learning leaves a mark: oligodendrocytes and the radial maze Does learning something new physically change the brain's wiring, not just its chemistry? Shimizu and colleagues trained mice on an eight-arm radial maze whose doors opened and closed automatically, tracked and controlled from start to finish by EthoVision. Successful training stimulated the birth of new oligodendrocytes, the cells that wrap axons in insulating myelin, in the brain regions the task relies on most heavily, including the prefrontal cortex and hippocampus. When the researchers genetically blocked the mice from making new myelin, radial maze performance suffered, and the mice that generated the most new oligodendrocytes during training were also the best performers [13]. It's a striking illustration of how far the maze's automation can go: in this study, the same EthoVision software that logged every arm entry was also programmed to operate the maze's doors. Automating the radial arm maze with EthoVision Across all of these studies, the bottleneck is the same one a lot of these mazes have: dozens of trials generate a lot of individual decisions to score, and scoring them by hand is slow and prone to human error. As the oligodendrocyte study above shows, automation can extend well beyond scoring, into running the maze itself. With EthoVision, deep-learning detection tracks an animal's nose, body center, and tail base, so an arm entry, and a possible re-entry error, is logged the moment the animal genuinely commits to it. The software then reports arm sequences, latencies, and error counts automatically, trial after trial, without a researcher squinting at grainy footage. The current release, EthoVision 19, adds a Noldus Calibration Card that sets up a maze's arena in seconds, along with refined AI tracking models that return data within moments of a recording finishing. For a maze built around one long list of possible errors, that kind of consistency is what turns a subtle memory deficit, or the absence of one, into something you can actually trust. Moving forward Fifty years after Olton and Samuelson built the first version, the radial arm maze is still finding new relevance: in Alzheimer's models, in diet and neuroinflammation, in feeding circuits, in genetics and sex differences, in myelin biology, and in the long cognitive tail of reproductive surgery. What ties these very different studies together is not the disease or the mechanism, but the maze's own design, forcing an animal to make one choice after another, so that memory becomes a sequence a researcher can count. Precise, automated counting is what lets researchers trust a subtle effect, or, just as importantly, an absent one. For more on spatial memory testing, take a look at our recent blog on the Y-maze for learning and memory. If you would like to talk through how the radial arm maze, or automated tracking more broadly, could fit your own study, we are happy to help. References - Kohler, J.; Mei, J.; Banneke, S.; Winter, Y.; Endres, M.; Emmrich, J.V. Assessing spatial learning and memory in mice: Classic radial maze versus a new animal-friendly automated radial maze. Front. Behav. Neurosci. 2022, 16, 1013624. - Ronquillo, J.; Nguyen, M.T.; Rothi, L.Y.; Bui-Tu, T.-D.; Yang, J.; Halladay, L.R. Nature and nurture: Comparing mouse behavior in classic versus revised anxiety-like and social behavioral assays. Genes Brain Behav. 2023, 22, e12869. - Gall, Z.; Boros, B.; Kelemen, K.; et al. Melatonin improves cognitive dysfunction and decreases gliosis in the streptozotocin-induced rat model of sporadic Alzheimer's disease. Front. Pharmacol. 2024, 15, 1447757. - Kim, E.H.; Lee, W.S.; Kwon, D.R. Microcurrent Therapy Mitigates Neuronal Damage and Cognitive Decline in an Alzheimer's Disease Mouse Model. Int. J. Mol. Sci. 2024, 25, 6088. - Kim, E.H.; Lee, W.S.; Lee, J.H.; Kwon, D.R. Microcurrent therapy as the nonpharmacological new protocol against Alzheimer's disease. Front. Aging Neurosci. 2024, 16, 1344072. - Kim, E.H.; Lee, Y.J.; Moon, Y.S.; Kwon, O.D.; Kwon, D.R. Evaluation of microcurrent as an adjunct to donepezil therapy in an Alzheimer's disease mouse model: a pilot study. Front. Aging Neurosci. 2025, 17, 1689593. - Gall, Z.; Csudor, A.; Savel, I.-G.; Kelemen, K.; Kolcsar, M. Cholecalciferol Supplementation Impacts Behavior and Hippocampal Neuroglial Reorganization in Vitamin D-Deficient Rats. Nutrients 2024, 16, 2326. - Park, Y.; Paing, Y.M.M.; Cho, N.; et al. Quinic Acid Alleviates Behavior Impairment by Reducing Neuroinflammation and MAPK Activation in LPS-Treated Mice. Biomol. Ther. 2024, 32, 309-318. - Stark, R.; Zigman, J.M.; Andrews, Z.B. GHSRs in the olfactory bulb suppress food motivation and promote exploration without altering spatial memory in male mice. J. Neuroendocrinol. 2025, 37, e70096. - Borbely, E.; Payrits, M.; Hunyady, A.; Mezo, G.; Pinter, E. Important regulatory function of transient receptor potential ankyrin 1 receptors in age-related learning and memory alterations of mice. GeroScience 2019, 41, 643-654. - Szentes, N.; Tekus, V.; Mohos, V.; Borbely, E.; Helyes, Z. Exploratory and locomotor activity, learning and memory functions in somatostatin receptor subtype 4 gene-deficient mice in relation to aging and sex. GeroScience 2019, 41, 631-641. - Koebele, S.V.; Bernaud, V.E.; Northup-Smith, S.N.; et al. Gynecological surgery in adulthood imparts cognitive and brain changes in rats. Horm. Behav. 2023, 155, 105411. - Shimizu, T.; Nayar, S.G.; Swire, M.; et al. Oligodendrocyte dynamics dictate cognitive performance outcomes of working memory training in mice. Nat. Commun. 2023, 14, 6499. --- ## EthoVision vs. DeepLabCut: Why the answer Is often both URL: https://noldus.com/blog/ethovision-vs-deeplabcut-why-the-answer-is-often-both Published: 2026-08-03 10:00:00 Description: EthoVision and DeepLabCut were built to solve different problems. This guide lays out what each tool does best, where they overlap, and how to decide which belongs in your behavioral research pipeline. If you track animal behavior from video, you have probably wondered where EthoVision ends and where open-source tools like DeepLabCut begin. The honest answer: they were built to solve different problems, and the most capable labs increasingly use both. This guide lays out what each tool does best, where they overlap, and how to decide which belongs in your research. Stay till the end to look at a newer category of marketing-led entrants that claim to replace both, and why that claim deserves scrutiny. EthoVision and DeepLabCut: two tools, two different philosophies EthoVision video tracking software is a validated, end-to-end behavioral research platform. It handles acquisition, tracking, zone and event detection, analysis, and export inside one controlled environment. It has been refined for over three decades of use in behavioral neuroscience. The design goal is a reliable result that any reviewer will accept, produced by a researcher who does not need to write code. DeepLabCut is an open-source, deep-learning framework for markerless pose estimation. It is an outstanding piece of science, widely cited and genuinely transformative for questions that depend on fine-grained multi-body-point tracking. The design goal is flexibility: you define the body parts, you train the network, and you get coordinates for whatever anatomy your study cares about. But this isn't "Maslow's Hammer" and you don't have to treat everything as if it were a nail. The reality is that neither tool is a worse version or replacement of the other. An open field test of locomotion or elevated plus maze assay of anxiety and a study of limb kinematics during a reaching task are different problems, and they require different tools, just as a carpenter might need a drill, screwdriver, and hammer. Where EthoVision video tracking software is the clear choice - Time-to-first result. Batch-import videos, apply detection settings, and get analysis in minutes. There is no model to train before you can answer your question. - Validation and citability. EthoVision is used at roughly 4,000 sites and has been cited more than 16,000 times since 2020 on Google Scholar. That track record shortens the path from data to published paper. - High-throughput designs. Designed to track up to a hundred arenas and up to 16 animals per arena at once, EthoVision has a deep parameter set covering time in zone, distance moved, velocity, latency, and much more. - Transparency and control. You can see where every data point comes from and adjust it. The system is not a black box, which matters when a reviewer asks how a number was produced. - Difficult tracking conditions. Tethered animals, obscured views, and varied species including fish and insects are handled with detection methods accessible without coding. - Support and continuity. Documentation, tutorials, a searchable manual, and worldwide technical support, with an expert team that answers when an experiment is on a deadline. EthoVision has evolved steadily, and the current version is a long way from early center-point tracking. As of 2026, EthoVision 19 combines classic detection methods with deep-learning-based tracking, so you get robust body-point and nose-tail-center detection without writing or training anything yourself. Multi-animal tracking with identity preservation means you can study socially interacting animals in the same arena without markers, and the platform scales to high-throughput designs across many arenas at once. Integrations with hardware for stimulus control, and modules for behavior recognition extend it well beyond a position tracker. If your mental picture of EthoVision is "it just tracks where the center of the animal is," that has not been the whole story for a long time. Where DeepLabCut pose estimation is the right tool DeepLabCut earns its place when your science depends on detailed pose rather than position. It is worth using when: - You need custom body-point tracking. Limb joints, digit positions, whisker bases, or any non-standard anatomy that a center-of-mass or nose-point tracker will not give you. - Kinematics are the question. Reaching, grasping, gait micro-structure, and posture analysis where the spatial relationship between points is the dependent variable. - You have in-house computational capacity. A lab member comfortable in Python who can manage environments, training, and the iteration that pose estimation requires. DeepLabCut has evolved too, and it is worth being accurate about that. As of 2026, version 3.0 introduced a PyTorch backend with performance gains and a more developer-friendly architecture. The Model Zoo now offers SuperAnimal foundation models, such as SuperAnimal-Quadruped and SuperAnimal-TopViewMouse, that can run without training a model from scratch. Multi-animal pose estimation, identification, and tracking have been supported since version 2.2 and were strengthened in 3.0. If you last looked at DeepLabCut a few years ago, the "you must train everything yourself" picture is no longer the whole story. Reproducibility in behavioral research: where EthoVision has the edge Because DeepLabCut is more capable than it used to be, the sharper way to think about the tradeoff is not "how hard is it to install." Instead, it is: how many hours does it take to train a model, validate it, and reproduce the same result across collaborators, reviewers, or animal cohorts? Key insight The question isn't how hard it is to install. It's how many hours it takes to get the same answer twice. In practice, each of those steps is real work. Training means labeling body points across hundreds of frames by hand, configuring the network, running the training, and iterating when the early results are poor. Validation means checking the model's predictions against ground truth, measuring error, and confirming it holds up on animals, lighting, and arenas it was not trained on, not just the clips you happened to label. Reproduction is the step labs underestimate most: a collaborator must recreate your software environment, model version, and configuration closely enough to get the same numbers from the same video, and a reviewer must trust that they would. A single trained model can represent days to weeks of skilled effort before it produces one publishable result, and every one of those choices is a place where two labs can quietly diverge. Every choice that gives an open-source pipeline its flexibility also adds a place where two labs can diverge: backend versions, model architecture, the choice between a foundation model and a fine-tuned one, multi-animal configuration, annotation conventions, and training data. None of this is a criticism of the science. It is the nature of a configurable research framework. But it means the burden shifts from "getting it running" to "getting the same answer twice," which is exactly what journal and grant reviewers increasingly note and push back on. EthoVision's value in that frame is not only ease of use. It is that a validated, controlled environment makes a result straightforward to defend and reproduce. When your collaborator across the country opens the same project, they see the same settings producing the same numbers. EthoVision has been validated against a ground truth and with the Quality Assurance functionality included in the Premium package, it supports Code of Federal Regulations Title 21, Part 58 (GLP) compliance. Why this matters With EthoVision, reproducibility is not extra work. The same validated settings produce the same numbers, whether the project is reopened next week or by a collaborator across the country. When to use both together These tools are not mutually exclusive and pairing them is often the strongest design. A common pattern: use EthoVision for validated, high-throughput position tracking, zone metrics, and the core readouts that carry your primary endpoints, and bring in DeepLabCut for a focused pose-estimation sub-analysis where detailed body-point data adds a layer the position track cannot. You get reproducible primary measures and the fine-grained detail where it earns its cost. A quick decision guide If your priority is... Reach for... Fast, validated, citable results with minimal setup check_circleEthoVision High-throughput screening across many arenas or animals check_circleEthoVision Custom body-point or kinematic pose analysis DeepLabCut Reproducibility and reviewer-proof primary endpoints check_circleEthoVision Validated primary measures plus a detailed pose sub-study check_circleBoth, in one pipeline Minimal staff knowledge of coding or programming check_circleEthoVision A word on the newer "replaces both" entrants Recently, a new wave of entrants has begun marketing itself around the same keywords researchers use to evaluate established tools, positioning their platforms as combining DeepLabCut's precision with EthoVision's ease of use, and publishing self-generated rankings that place themselves at the top of the field. It is worth approaching that kind of self-ranking with the same skepticism you would apply to any other claim in your field. A few things to weigh: - Self-declared rankings are marketing, not evidence. A vendor that ranks itself first on its own website has told you about its content strategy, not its accuracy. - Look for the validation record. Established tools earn trust through independent peer-reviewed publications that used them. Ask any newcomer for the same. Lab site counts and a list of prestigious university names are not the same as a citation record. Claims that appear inconsistent across a vendor's own pages are worth questioning directly. - "Best of both worlds" is the easiest thing to say and the hardest thing to prove. DeepLabCut's precision comes from a deep, configurable model that experts can tune. EthoVision's power comes from thirty years of validated engineering. Combining them is a genuine technical challenge, and a marketing slogan is not a substitute for demonstrating it. The point is not that no new tool can ever be good. It is that the burden of proof sits with the tool making the claim, and in behavioral research that proof is measured in independent validation and reproducible published results, not in self-assigned rankings. Bottom line When a tool ranks itself first and claims to be the best of both worlds, ask for the one thing that actually settles it: an independent record of published research that used it. Choosing your setup If your work rewards validated, reproducible, high-throughput tracking that gets to a publishable result quickly, EthoVision animal behavior tracking software is built for exactly that. If your science depends on detailed pose, DeepLabCut markerless pose estimation software is a superb complement, and the two work well together. If a newcomer promises to replace both, ask it for the validation record before you trust it with your data. Want to know if EthoVision will work for you? Check out detailed specs for effortless setup. Need publication examples? You can find them here. Want to see a detailed comparison of the available video tracking solutions? See our comparison table here. Finally, you can get a free trial and try it for yourself. --- ## Three arms, one decision: the Y-maze for learning and memory URL: https://noldus.com/blog/y-maze-learning-memory Published: 2026-07-15 12:37:05 Description: The Y-maze is one of the most efficient tools for studying spatial and working memory. Learn how automated tracking transforms arm entries into clean, objective data across rodent and zebrafish models. Imagine you are on a deserted island, and you are hungry. You explore to the right, find a tree full of fruit, eat your fill, and head back to your shelter for the night. The next morning, where do you go? To the right, of course, because your spatial memory is functioning normally. Now imagine that memory is starting to fail. You forget where the fruit was, or you keep returning to a tree you already stripped bare. In many neurological conditions, this is exactly the kind of spatial and working memory that breaks down first. The Y-maze is one of the most efficient tools we have for studying it. Y the maze? A Y-maze is exactly what it sounds like: a maze with three identical arms set at 120 degrees to one another. It is very similar in form and function to the T-maze, but the gentler turns are easier for an animal to negotiate and decide. Kraeuter and colleagues, in a widely used protocol paper, describe how this small, low-stress apparatus can probe both spatial working memory and spatial reference memory, drawing on the hippocampus, medial septum, prefrontal cortex, and basal forebrain [1]. And because its most popular variant, spontaneous alternation, relies only on a rodent's natural drive to explore somewhere new, it needs no food deprivation, no aversive stimuli, and very little training. That makes it fast, repeatable, and low stress. What can you measure in a Y-maze? The Y-maze can accommodate a variety of protocols. To probe spatial reference memory, you can bait one arm with a reward and, at a later point, see whether the animal heads straight back to it. To test recognition memory, you block one arm during the first exposure and then open it: a healthy animal notices the "new" arm and spends more time exploring it, much like in novel object recognition. In the spontaneous (or continuous) alternation test, you simply let the animal roam. Rodents tend to alternate arms rather than revisit the same one, so the percentage of successful alternations becomes a clean readout of working memory. And in rewarded alternation, you teach the animal that the reward keeps moving, so it has to alternate to succeed. Across all of these, the same handful of measures matter: which arm is entered, in what order, how quickly, and for how long. Counting these parameters by hand is exactly the slow, subjective step that automation removes. Applications of the Y-maze Spatial and working memory are affected in a remarkable range of disorders, and recent work shows just how broadly the Y-maze travels. Alzheimer's disease and dementia Aleksandrova and colleagues used a delayed spontaneous-alternation Y-maze (videotaped and scored with EthoVision) alongside the Morris water maze and novel object recognition to show that a conjugate of securinine and tryptamine improved memory in 5xFAD transgenic mice, a model that overexpresses mutant human amyloid [2]. Traumatic brain injury Pischiutta and colleagues used a two-trial Y-maze to test whether a mesenchymal stromal cell secretome could restore spatial recognition memory in injured mice; the time spent in the novel versus familiar arm was a key outcome [3]. In a separate 2026 study, Sheng and colleagues paired the Y-maze with novel object recognition and the Morris water maze to show that silencing a neuronal inflammasome rescued cognition after controlled cortical impact [4]. Anesthesia and vulnerable brains Li and colleagues exposed P301L tau transgenic mice (a tauopathy model) to the anesthetic sevoflurane and measured spontaneous alternation in the Y-maze together with novel object recognition, finding that anesthesia worsened tau-related memory deficits [5]. Compound screening Yi and colleagues used Y-maze spontaneous alternation and a novel-arm task, benchmarked against the reference drug donepezil, to test an Alpinia oxyphylla fruit extract in a lipopolysaccharide (LPS) model of neuroinflammation [6]. Fatigue and stress Wu and colleagues induced cognitive fatigue in rats through repeated sleep deprivation and found a reduced spontaneous-alternation rate in a Y-maze. The effect was regionally specific: prefrontal TGF-B1 rose, but peripheral and striatal levels did not change [7]. Not only rodents: the Y-maze for zebrafish The Y-maze is not just for rodents. The zebrafish (Danio rerio) has become a widely used model in translational neuroscience, because it shares conserved neurotransmitter systems and disease-related genes with mammals, breeds quickly, and is well suited to higher-throughput testing. In a Y-shaped tank, an adult zebrafish explores the arms much as a rodent does, and the same logic applies: a fish with intact memory alternates its choices or favors a newly opened arm. Popovici and colleagues used precisely this approach (a novel tank test, a Y-maze, and novel object recognition) to show that a Phytolacca americana fruit extract reversed scopolamine-induced memory loss in zebrafish [8]. Using the identical setup, the group later showed that the plant coumarin scoparone eased comparable scopolamine-induced memory and anxiety deficits in zebrafish [9]. The underlying paradigm has been carefully validated, too: Cleal and colleagues established the free-movement-pattern Y-maze as a cross-species measure of working memory and executive function, scored from the sequence of left and right turns a fish makes during free exploration [10]. Because the task is, in essence, "just filming a fish swimming," it lends itself naturally to video tracking. A Y-maze for snakes? Yes, it sounds a bit unusual, but the Y-maze is not only used in neuroscience. Researchers from James Madison University and the Fort Collins Science Center used an enclosed version (for obvious reasons) of the Y-maze to assess the exploratory behavior of Burmese pythons. Since snakes have an incredible sense for chemical cues, the researchers used this to their advantage to observe choice behavior. Automating the Y-maze with EthoVision Regardless of the model species, the bottleneck is the same: arm entries are only meaningful if they are scored accurately and consistently, trial after trial. With EthoVision, deep-learning detection finds the nose, body center, and tail base of a rodent or fish, so an arm entry is registered only when the animal has genuinely committed to that arm, not merely poked its nose past the threshold. The software then reports the order of arm visits, latencies, durations, and the alternation percentage automatically. The current release, EthoVision 19, builds on this with quality-of-life and multi-subject improvements: a Noldus Calibration Card that focuses the camera and calibrates an arena at the click of a button, refined AI models that return data within seconds of a recording, and much more. Your whole experiment is automated and standardized, giving you clean, high-quality data. Try EthoVision with your own Y-maze videos! The gold standard in video tracking for behavioral research. Request a free trial and see how EthoVision automates your Y-maze experiments. Request a free trial In conclusion The Y-maze endures because it does something deceptively hard: it makes a private, internal process (remembering where you have just been) visible as a simple sequence of choices. What turns that into reliable science is precise, scalable, objective measurement, and that is exactly what automated tracking provides. The studies above span amyloid and tau pathology, brain injury, anesthesia, neuroinflammation, fatigue, and a fish model of amnesia, yet they share one quiet ingredient: every arm entry was scored the same way, every time. That consistency is what lets researchers trust a subtle effect, or, just as importantly, an absent one. For more on adapting cognitive assays across species, take a look at our work on learning and memory testing and zebrafish research. If you would like to talk through how the Y-maze could fit your own study, we are happy to help. Further reading: more recent Y-maze studies that use EthoVision These two studies are good next reads if you want to see the same EthoVision-tracked Y-maze applied in fresh contexts: - Yang and colleagues put a Y-maze (arm entries and spontaneous alternation, tracked with EthoVision) at the center of a quantitatively controlled closed-head injury model, linking head-impact intensity to impaired adult neurogenesis [11]. - Kim and colleagues used Y-maze spontaneous alternation together with the Morris water maze, both tracked with EthoVision, to compare two anesthetics for postoperative cognitive decline in an Alzheimer's-risk (ApoE4) mouse model [12]. References - Kraeuter, A.-K.; Guest, P.C.; Sarnyai, Z. The Y-Maze for Assessment of Spatial Working and Reference Memory in Mice. Methods Mol. Biol. 2019, 1916, 105-111. - Aleksandrova, Y.; et al. Neuroprotective Effects and Cognitive Enhancement of Allomargaritarine in 5xFAD Alzheimer's Disease Mice Model. OBM Neurobiol. 2024, 8, 207. - Pischiutta, F.; et al. Mesenchymal Stromal Cell Secretome and Its Key Bioactive Metabolites Induce Long-Term Neuroprotection After Traumatic Brain Injury in Mice. Adv. Sci. 2025, 12, e15508. - Sheng, J.; et al. A self-perpetuating neuron-intrinsic GSDMD-mtDNA-AIM2 inflammasome axis drives neuronal pyroptosis after traumatic brain injury. Front. Immunol. 2026, 17, 1867920. - Li, Y.; et al. Sevoflurane Exposure Exacerbates Memory Impairment in P301L Tau Transgenic Mice. CNS Neurosci. Ther. 2025, 31, e70694. - Yi, Z.; et al. Identification, biotransformation, and neuroprotective potential of Alpiniae oxyphyllae fructus in neuroinflammation-related cognitive impairment. Front. Pharmacol. 2025, 16, 1714500. - Wu, Y.; et al. Cognitive impairment and prefrontal TGF-B1 elevation in a rat model of fatigue. Front. Psychiatry 2026, 17, 1841951. - Popovici, L.-F.; et al. Enhancement of Cognitive Benefits and Anti-Anxiety Effects of Phytolacca americana Fruits in a Zebrafish Model. Antioxidants 2025, 14, 97. - Brinza, I.; et al. Enhancement of cognitive benefits and anxiolytic effects of scoparone in a zebrafish model. Pharmacol. Res. Nat. Prod. 2025, 7, 100232. - Cleal, M.; et al. The Free-movement pattern Y-maze: a cross-species measure of working memory and executive function. Behav. Res. Methods 2021, 53, 536-557. - Yang, S.; et al. Quantitatively controlled traumatic brain injury impairs adult neurogenesis in mice. Theranostics 2026, 16, 193-219. - Kim, J.-H.; et al. Comparison of Cognitive Deterioration Between Propofol and Remimazolam Anesthesia in ApoE4 Knock-In Mouse Model. Int. J. Mol. Sci. 2025, 26, 5718. --- ## 5 coding-scheme decisions you cannot undo later URL: https://noldus.com/blog/5-coding-scheme-decisions-you-cannot-undo-later Published: 2026-07-08 12:45:06 Description: A setup checklist for The Observer : the five structural choices that decide whether your scheme works on the first video or works against you. A setup checklist for The Observer: the five structural choices that decide whether your scheme works on the first video or works against you as your project progresses. Creating a coding scheme can be one of the most challenging aspects of The Observer. This article provides a practical guide through the specific, structural decisions that are hard to reverse, in the order The Observer asks you to make them, so you can lock them in deliberately rather than discover them the hard way. Pro Tip: How to use this Treat the five sections below as a checklist. Before you start coding for real, make a conscious call on each one. If you can answer all five successfully, your coding scheme is very unlikely to need a painful rebuild later. First, the vocabulary of The Observer The language of The Observer may not match the language of the lab, and that is okay, but it is worth delineating before you build anything. A few terms do most of the work: - Groups. All behaviors must be organized into groups. This governs how a keystroke knows when a behavior starts and stops. - Continuous vs. instantaneous coding. Continuous means scoring behaviors as they happen. Instantaneous means scoring at regular intervals (every 30 seconds, every minute, and so on). - States vs. points. Within continuous coding, a state has duration and a point does not. - Start-stop vs. mutually exclusive. State groups can be start-stop (several behaviors may overlap) or mutually exclusive (only one behavior active at a time). With those terms in hand, the five decisions below are much easier to make deliberately. 1. Point, state, or instantaneous: the choice that costs the most to get wrong The single most common stumbling point comes when people choose a behavior type by thinking about the behavior. The right way to choose is to think about your endpoint - the number you intend to report at the end of the study. Work backward from that, and the type chooses itself. If you need... Then define as... Because... How often (counts, rates) check_circlePoint event A point event marks an instant. It answers how many and how often, not how long. How long (durations, % of time, overlap) check_circleState event A state event runs from start to stop, capturing duration and showing how behaviors overlap. A snapshot at fixed moments check_circleInstantaneous sampling Score what is happening at set time points. Useful for long sessions where continuous coding is impractical. The reason this one is so unforgiving: the type is fixed the moment you score it. If you record a behavior as a point event and later decide you needed its duration, that information was never captured, and there is nothing to recover. Re-coding is the only fix. So, the question to settle before you touch the keyboard is simply: for each behavior, am I going to report how long, how often, or both? Pro tip: Point events are frequency-based A behavior with a genuinely negligible duration, such as an eye blink, a head nod, or a button press, is almost always a point event, even though it technically takes time. If you only need frequency, do not spend the time and energy recording its duration as a state event. 2. Why every behavior must be in a group, and what mutually exclusive entails In The Observer, behaviors are never in isolation; each one belongs to a behavior group. This is not organizational tidiness - each group controls how keystrokes turn behaviors on and off. The decision you are really making per group is whether two behaviors in it can be true at the same time. - Start-stop groups allow overlap. A behavior stays on until you explicitly stop it, and several can run at once. Use these when behaviors genuinely co-occur (for example, a child can be talking and walking simultaneously). - Mutually exclusive groups allow only one behavior at a time. Starting one automatically stops the previous. This is the smart coding that keeps you from recording impossible states like sitting and standing at once. A mutually exclusive group should also be exhaustive, meaning that one behavior from the group is active throughout the entire observation. In practice this means the group must include an initial state event, so the subject is in a defined state from the very first frame. Typically, this is a null behavior. Pro Tip: The test to apply For each mutually exclusive group, ask: At any given moment of the observation, is my subject always in exactly one of these states? If the honest answer is sometimes none of them, you are missing an other or null state. If the answer is sometimes two of them, the group should be start-stop, not mutually exclusive. 3. Keycodes: the conflict you will only notice mid-session Keycodes are required, generated automatically, and case sensitive. The Observer will happily assign them for you, and you can set the length of each keystroke to 1, 2, or 3 keys. Two issues are worth settling before coding starts: - Overlapping prefixes. If the length is 2 and one code is a prefix of another, The Observer will not register the behavior until you press the second key. Assign codes that are distinct from the first keystroke. - Stop codes. For state events, decide deliberately how a behavior ends (the same key again, or a case switch) and make that consistent across the scheme. An extra shift key adds time and can introduce error for less-experienced coders. Spend five minutes choosing codes that are mnemonic, conflict-free, and consistent. 4. Modifier or behavior? A decision, not a default Modifiers are optional codes that specify a behavior (the recipient of an action, or the intensity of a response), and they can be nominal (a name) or numerical (a value). They can add a lot to your analysis, but do not reach for them as a default way to build a scheme. Use them only when you need them. Decide, for each piece of detail you want to capture, whether it belongs in the structure of the scheme (a behavior) or as an attribute hanging off a behavior (a modifier). Make that decision deliberately. Pro Tip: Keep it lean Only include what answers your research question. If you are studying eating behavior, you do not need codes for talking. Every extra behavior, group, and modifier is something a coder must hold in mind. Restraint here is what keeps coding fast and reliable. 5. Design once, code many: getting the scheme onto every coder machine If you have coder licenses for multiple coding stations, the scheme must be shared across those machines unchanged. The Observer has a designed sequence for exactly this: - Build and finalize the coding scheme on one machine. - Save the project as a template (an .otb file). - Copy that template to each coding station. - On each station, choose File - New Project from Template, so every coder starts from an identical scheme. - When coding is done, each coder uses File - Export - Observational Data and saves an .odx file for merging back together. The decision to make up front is simply to freeze the scheme before you distribute it. Lock the design, then distribute, then code. Pro Tip: One scheme, many machines Multiple coding stations require a floating license and/or coder license(s). The detailed procedure lives in the Technical Note Coder License, The Observer, and your local Noldus contact can walk you through licensing for your setup. The five-question checklist Before your first real coding session, you should be able to answer all five: - For each behavior, am I reporting how long, how often, or both? (point vs. state vs. instantaneous) - Is every mutually exclusive group exhaustive, with an initial state event? - Are my keycodes distinct from the first keystroke, with consistent stop codes? - Have I decided, on purpose, what is a behavior and what is a modifier? - Is the scheme frozen before I distribute it to coder machines? Answer those five and the coding scheme will save you time and effort. Every minute of design you invest before coding saves far more than a minute of re-coding after. Keep going: Talk to a Specialist - Learn more online or book time with a Specialist → - Live Q&A series for The Observer on Noldus Academy → - Download the one-page checklist (PDF) → - Background reading: Behavioral coding: what and how → --- ## Lasting effects: studying early-life experience in insects URL: https://noldus.com/blog/lasting-effects-studying-early-life-experience-in-insects Published: 2026-07-07 10:13:31 Description: Physiology and behavior can buckle under stress. Stressors experienced early in life may even have long-lasting effects. Because of their life span, insects are a very interesting model to test these effects in detail. The experiences an animal has early in life can have a lasting effect on its behavior and physiology. Working out the mechanisms behind these effects is important, because it shows us where vulnerabilities take hold and where we might one day intervene. Behavioral research in animals has been central to mapping how early-life conditions influence well-being and affective states later on. And increasingly, researchers are turning to a surprising group of animals to study them: insects. Why use insects? Rodents and zebrafish have dominated the behavioral neuroscience landscape for years, so insects might not be the first animals that come to mind. But they offer a number of advantages. They are cheap and easy to house, and their short lifespans mean that behavioral changes which would take months to surface in a rodent can appear within days. Despite their size, their nervous systems share a great deal of core machinery with vertebrates, including many of the same neurotransmitter systems. As Westwick and Rittschof point out in their review, insects provide unique opportunities to study how early-life experience alters the brain and behavior [1]. A handful of species do most of the work. The fruit fly (Drosophila melanogaster) is the best-understood animal model we have, with a genetic toolkit and behavioral repertoire that has been mapped in remarkable detail, especially for learning and memory. Honeybees are a favorite for studying associative learning and olfactory cognition. Locusts have shown how social context can flip behavior entirely, including the serotonin-driven shift from solitary to swarming individuals. Each species opens a slightly different window onto the same question. Adapted from [2] What counts as an early-life experience? Many different inputs can leave a mark during development. Temperature and light are powerful environmental cues, and many insects use them to trigger physical and behavioral change. Interactions with other animals, such as competitors, mates, and predators, shape later responses too. And then there is food: the quantity and quality of nutrition an animal receives early on can echo through the rest of its life. It is this last category that the study we look at today focuses on. Nutritional stress in early life Brueggemann and colleagues asked a deceptively simple question: does it matter when an animal goes hungry [3]? Their model was the turnip sawfly (Athalia rosae), a holometabolous insect, meaning it goes through complete metamorphosis. Its larvae feed on leaves and flowers, while the adults drink nectar, so the two life stages occupy completely different dietary niches. Picture retrieved from AHDB To find out, the researchers exposed sawflies to one of four nutritional regimes: no starvation, starvation only as larvae, only as adults, or at both stages. They did this for both sexes, and then tracked the consequences across life-history, behavior, and metabolism. To capture adult behavior, the team turned to automated video tracking. After the starvation treatments, sawflies were moved with minimal handling into empty Petri dishes, and six individuals were filmed in parallel for an hour with an overhead camera. Their movement was tracked with EthoVision, which followed each animal's center point several times per second and extracted two measures of activity: the total distance moved and the time spent immobile. This is what allowed the researchers to make a precise statement about whether activity changed at all. Picture by Peter Hillman And the results were highly trait specific. Larval starvation prolonged development, and starved females reached a lower adult body mass than well-fed individuals. Males, however, conformed well to poor conditions, ending up at roughly the same body mass regardless of how they were reared. Metabolism shifted with starvation as well. But adult behavioral activity held steady: it was not significantly affected by starvation at either life-stage. In other words, some traits bend under early-life stress while others prove remarkably robust, and which is which depends on the trait, the life stage, and the sex of the animal. For more on adapting behavioral assays to insects, take a look at our earlier blog on using flies as an animal model. Measuring insect behavior at scale EthoVision is the most validated video tracking system available, and it quantifies movement and activity with a consistency that goes well beyond manual scoring. For more controlled, high throughput experiments, an optimized and standardized environment is needed. EntoLab combines this standardized observation chamber with EthoVision and EthoAnalysis to deliver high-throughput screening of up to 300 trials at once. It is used to measure activity, heat tolerance, responses to toxic compounds, and even learning and memory across a wide range of insect species. Want to learn more about the EntoLab protocol or read how it's used in practice? Bolletta et al. used EntoLab to study prey-sharing behavior in two species of lacewings (Micromus angulatus & Chrysoperla carnea). EntoLab allowed them to observe differences in feeding behavior for four consecutive hours, which is essential for understanding predator-prey interactions. Moving forward Early-life experience shapes adult behavior, and insects give us a great way to study how. Whether the input is temperature, social context, or food, the lesson that keeps emerging is that plasticity is not all-or-nothing. Some traits shift dramatically while others hold firm, and timing, life stage, and sex all play a role. The common thread is measurement. Subtle effects, and the absence of effects, only become visible when behavior is recorded precisely and at scale. The sawfly study is a good example: larval starvation altered body mass and development while leaving adult activity untouched. That kind of trait-specific plasticity is exactly why you need a tracking system sensitive enough to capture both the effects and the non-effects. The same automated tracking extends well beyond nutrition, to olfactory and vision-based research, the evolution of behavior, ecotoxicology, and insect-plant relationships. If you are exploring how early experience shapes behavior in your own insect model, we would be happy to help you design the setup to measure it. References - Westwick, R.R.; Rittschof, C.C. Insects Provide Unique Systems to Investigate How Early-Life Experience Alters the Brain and Behavior. Front. Behav. Neurosci. 2021, 15, 660464. - Capo, F.; Wilson, A.; Di Cara, F. The Intestine of Drosophila melanogaster: An Emerging Versatile Model System to Study Intestinal Epithelial Homeostasis and Host-Microbial Interactions in Humans. Microorganisms 2019, 7, 336. - Brueggemann, L.; Singh, P.; Müller, C. Life Stage- and Sex-Specific Sensitivity to Nutritional Stress in a Holometabolous Insect. Ecol. Evol. 2025, 15, e70764. --- ## Measuring social behavior in rodents: the power of EthoVision URL: https://noldus.com/blog/measuring-social-behavior-in-mice-the-power-of-ethovision-xt-18 Published: 2026-04-16 15:52:00 Description: Traditional behavioral assays of multiple animals often rely on manual or rudimentary methods. With EthoVision the world of measuring social behavior in rodents has been revolutionized. Read more in this why EthoVision is the best out of the box tracker. In behavioral neuroscience, understanding social interactions in rodents is key to unlocking insights into neurodevelopmental and psychiatric disorders. Traditional behavioral assays often rely on manual observations or rudimentary tracking systems that fail to capture the nuances of complex social interactions. However, with the advancements in EthoVision’s social tracker, powered by Noldus’ advanced deep learning algorithms, researchers can analyze social behaviors with unprecedented accuracy and efficiency. This advancement takes your behavioral research to the next level by capturing spontaneous, naturalistic behaviors in stress-free conditions. EthoVision is the only commercially available system that does everything you could want, seamlessly and easily, without compromising on animal welfare. Why is measuring social behavior important? Social behavior is a fundamental aspect of neuroscience research. It plays a crucial role in the study of conditions such as autism spectrum disorders, schizophrenia, and anxiety-related disorders. Observing social interactions like grooming, chasing, and huddling provides invaluable insights into brain function and dysfunction. By evaluating behavior in a social setting rather than isolation, researchers can assess how genetic, pharmacological, or environmental factors influence these critical interactions. A growing trend in behavioral neuroscience In recent years, there has been a growing trend toward obtaining more ethologically relevant behavioral data. Researchers are moving away from artificial experimental setups and placing greater emphasis on studying animals in environments that closely resemble their natural conditions. This shift is accompanied by a focus on improving housing and handling practices to ensure minimal stress and maximal validity of behavioral data. By designing studies with these principles in mind, researchers can collect more accurate, translationally relevant data that better reflects real-world behavior in both animals and humans. EthoVision: a revolution in social behavior tracking EthoVision has long been the gold standard in video tracking software, but the latest versions represent a major breakthrough. With its enhanced deep learning algorithms, EthoVision has several key benefits for those looking to measure social interaction. - Accurate tracking with minimal intervention: Unlike traditional tracking methods that require colored markers, EthoVision can accurately track two animals with minimal intervention. Simple physical markers, such as shaving a small section of the animal's back or placing a non-invasive marker on the tail, are sufficient for reliable identification. - Advanced deep learning tracking for social behavior: EthoVision extends its neural network models to social interaction studies, enabling two-subject tracking with great accuracy. This allows researchers to study complex dynamics like social hierarchies and pair-wise interactions more effectively. - Robust performance in complex conditions: Whether in high-density environments or under varied lighting conditions, EthoVision’s deep learning engine ensures reliable tracking, making it adaptable to diverse experimental setups. New innovations with EthoVision 19 With this new release we’ve made the social interaction capabilities of our tracker even better. The improved Re-ID is better at distinguishing your animals as they act. This means that your data is ready within seconds of finishing your recording. Furthermore, we’ve added some often-requested parameters to analyze. You can now define and measure the following parameters: - Following. Detected when the subject (actor) follows a conspecific (receiver) within the specified distance, the actor's nose is oriented towards the receiver's center point within the specified angle, and both animals move faster than specified. - Leaving. Detected when the subject (actor) moves toward a conspecific (receiver) within the specified distance, the angle between the actor's center-nose vector and the receiver's center point is less than specified, and the receiver moves at a velocity lower than specified. - Approach. Whether in high-density environments or under varied lighting conditions, EthoVision’s deep learning engine ensures reliable tracking, making it adaptable to diverse experimental setups. - Social contact. Detected when the nose point of the subject (actor) is near a conspecific (receiver) and the actor's center-nose vector is oriented toward the receiver's body points by less than the specified angle. Extending research with home cage monitoring While traditional open-field arenas provide valuable data, they can introduce artificial constraints that impact the validity of behavioral studies. Home cage(-like) monitoring provides a more ethologically relevant setting, allowing for the continuous observation of natural behaviors over extended periods. When combining EthoVision with PhenoTyper, researchers benefit from a powerful integrated behavioral system that offers you clear insights into: Social bonding and group interactions: Without the stress of novel environments, researchers can assess stable social relationships, dominance hierarchies, and affiliative behaviors in freely interacting groups. Circadian rhythms and sleep patterns: By tracking locomotor activity across light-dark cycles, researchers gain a deeper understanding of sleep-wake behaviors, an essential factor in studies on neurodegenerative diseases and mental health disorders. Stereotypies and abnormal behaviors: Long-term monitoring increases the likelihood of detecting repetitive behaviors, self-grooming patterns, or aggression, which are crucial indicators in models of autism and obsessive-compulsive disorder. Cognitive functions in a low-stress environment: Integrating automated cognitive tasks within the home cage allows for the assessment of learning, memory, and decision-making in a setting that minimizes experimenter interference. This combination provides a robust and well-integrated platform that streamlines behavioral studies, making data collection more efficient and reliable for preclinical research. The benefits of EthoVision over open source Compared with open-source tools such as DeepLabCut, EthoVision offers a much more straightforward path to reliable social interaction data. Rather than spending time building, training, and troubleshooting your own workflow, researchers can start measuring behavior immediately with a system that works out of the box. That ease of use does not come at the expense of flexibility. EthoVision works across different arena types and rodent species without requiring model retraining for each new setup, making it easier to apply consistently across studies. At the same time, users have access to PhD-level scientific support, so help is available from experts who understand both the software and the experimental questions behind the data. Just as importantly, EthoVision is a platform trusted by thousands of researchers worldwide. That proven track record gives confidence that the system delivers robust, reproducible results for social behavior research. Implications for preclinical research The integration of deep learning-powered tracking with home cage(-like) monitoring directly addresses some of the most pressing challenges in preclinical research: - Reducing stress-induced variability: Traditional behavioral assessments require handling, which can introduce stress and confound results. By monitoring animals in their home environment, EthoVision eliminates this factor, ensuring more reliable data. - Enhancing study efficiency and scalability: Manual observation is time-consuming and subjective. EthoVision automates tracking and analysis, allowing researchers to scale up studies and collect more data in less time. - Providing continuous, real-time insights: Many neurological disorders develop gradually. With continuous monitoring over extended periods, researchers can detect subtle behavioral shifts that would otherwise be missed in short-term studies. - Delivering more translatable results: Behavioral data collected in a naturalistic setting better reflects real-world conditions, improving the translational value of findings to human applications. - Eliminating human scoring errors: Subjective behavioral scoring is prone to inconsistencies. EthoVision’s deep learning-based tracking standardizes measurements, ensuring consistency across experiments. Conclusion EthoVision is not just another tracking system, it is designed to address the real challenges behavioral researchers face today. With over 30 years of experience, Noldus has built solutions from the ground up, guided by validated data and continuous research input. By integrating advanced deep learning capabilities with home-cage monitoring in the PhenoTyper, we provide a powerful platform for collecting high-quality, short- and long-term behavioral data with minimal intervention. Refining experimental methodology and accelerating breakthroughs in neuroscience, ultimately leading to more effective treatments for neuropsychiatric disorders. Ready to see how EthoVision can improve your research? Contact us today for a demo or visit noldus.com/ethovision-xt to explore how we can help you improve your behavioral research. --- ## A personal journey in behavioral analysis: Thigmotaxis with DanioFlow URL: https://noldus.com/blog/a-personal-journey-in-behavioral-analysis-thigmotaxis-with-danioflow Published: 2026-02-13 13:59:03 Description: Dr. Torres-Ruiz has developed a tool for analyze EthoVision data. Her program takes data and transforms it into simplified harmonized data for studying thigmotaxis in zebrafish. However, there is much more that could be achieved with DanioFlow. Collaboration in science is key. That is why today we are giving the floor to Dr. Monica Torres-Ruiz, who has created an openly available tool to process data from EthoVision. In this guest blog she will explain why she created her program DanioFlow and what it can be used for. So, keep reading to learn more! Monica Lúcia Torres Ruiz (right) María Muñoz Palencia (left) Our goal for DanioFlow Studying thigmotaxis in zebrafish (ZF) larvae taught me that collecting behavioral data is only half the battle. This is the story of how a PARC project challenge led me to develop DanioFlow, a free tool to simplify and harmonize EthoVision data analysis. When I first joined the PARC (Partnership for the Assessment of Risks from Chemicals ) project, I knew we were aiming high. The goal was ambitious: help modernize neurotoxicity testing by developing new, ethical, and scalable behavioral methods (Tal et al., 2024). What I didn’t know yet was that this project would eventually push me beyond experimental design and into the world of data workflows, reproducibility, and tool development. At the center of my work was an apparently simple question: can measuring thigmotaxis in 5-day old ZF larvae add value to neurotoxicity testing, and if so, how do we first set it up as a reliable assay? Discovering Thigmotaxis as a powerful readout Thigmotaxis, an organism’s tendency to stay close to walls, has long been used as a proxy for anxiety-like behavior (Kraeuter et al., 2019). In zebrafish larvae, it is a conserved and quantifiable response, but also one that has been applied very inconsistently across labs (Hill et al., 2023). Comparing studies often felt like comparing apples to oranges: different plate formats, different analysis strategies, etc. Within PARC, I was tasked with developing a robust, high throughput thigmotaxis assay that could realistically be used as part of a neurotoxicity battery (Tal et al., 2024). That meant making some methodological changes: moving from traditional 24-well round plates to 96-well square plates to increase throughput, combining visual and acoustic stimuli to probe different neural circuits, and standardizing positive and negative controls. The experimental work was demanding, but it became especially rewarding when testing model compounds revealed that thigmotaxis was more sensitive or captured more effects than traditional locomotion measures (Torres-Ruiz et al. 2026). However, as the datasets expanded, another challenge emerged. When analysis becomes the bottleneck TEAll experiments were done in the DanioVision chamber and tracked using EthoVision, which is a fantastic and powerful system. However, once you export the raw data, you are very much on your own. For a single experiment this is manageable but for large studies encompassing multiple plates, multiple stimuli, multiple endpoints, and multiple substances, it quickly became overwhelming. I found myself repeatedly performing the same steps: cleaning files, normalizing controls, separating light/dark or sound/silence periods, analyzing significant differences, and preparing outputs for statistics and benchmark dose modeling. That was the moment I realized that harmonization doesn’t end at experimental design. It also lives (or dies) in data analysis. Why I created DanioFlow DanioFlow was born out of necessity. I needed a tool that could take EthoVision outputs and quickly but reliably transform them into analyzed datasets without requiring advanced programming skills, which I do not have. What started as a personal workflow in Excel gradually turned into something more structured. DanioFlow collects metadata, automates data curation and analyses, applies consistent zone separation, distinguishes between light and sound stimuli, creates graphs, and outputs a clear Word report that traces back to the original Ethovision data. Most importantly, it does this in a way that is adaptable. If your experimental design is slightly different, DanioFlow can evolve with it. I made a very deliberate decision to make DanioFlow free and openly available as PARC is built on collaboration, and I strongly believe that tools developed with public funding should help as many researchers as possible. By sharing DanioFlow, my hope is to reduce analysis time and improve comparability across studies. A tool for the community, but not yet finished DanioFlow was built to be transparent and simple in the way it analyzes data and, of course, it is open to change. Even though at the moment it is designed for a 96 well plate format and examines thigmotaxis and general locomotion parameters for light and sound stimuli, other researchers could adapt it to different plate formats, different behaviors, or even entirely different species if needed. I fully expect it to grow and improve as others use it, question it, and modify it. For me, DanioFlow is a natural continuation of the thigmotaxis method. Developing this sensitive behavioral NAM is only truly useful if the resulting data can be analyzed efficiently and reproducibly. Looking back and forward Working in PARC reminded me that methods are living things. They don’t stop at the protocol or publication but rather extend into how data are handled, shared, and understood by others. DanioFlow is my contribution to this broader effort. It grew directly from real experimental hurdles and from many conversations with colleagues facing similar frustrations. If it helps even a few labs spend less time struggling with spreadsheets and more time thinking about biology, then it has already done its job. And honestly? That feels just as rewarding as any significant p-value. DanioFlow is freely available to the research community and can be accessed via Zenodo. Torres-Ruiz, M. (2026). DanioFlow – Automated Behavioral Analysis Pipeline for Zebrafish Larvae (1.0.0). Zenondo. References Torres-Ruiz M., Muñoz Palencia M., De La Vieja A., Cañas Portilla A. 2026. Visual - Acoustic Thigmotaxis in Zebrafish Larvae: A High throughput NAM for Neurotoxicity Assessment. BioRxiv .02.03.703464. 10.64898/2026.02.03.703464 Hill B.N., Britton K.N., Hunter D.L., Olin J.K., Lowery M., Hedge J.M., et al., 2023. Inconsistencies in variable reporting and methods in larval zebrafish behavioral assays. Neurotoxicol Teratol; 96: 107163` 10.1016/j.ntt.2023.107163 Hill B.N., Britton K.N., Hunter D.L., Olin J.K., Lowery M., Hedge J.M., et al., 2023. Inconsistencies in variable reporting and methods in larval zebrafish behavioral assays. Neurotoxicol Teratol; 96: 107163. 10.1016/j.ntt.2023.107163 Kraeuter A.K., Guest P.C., Sarnyai Z., 2019. The Open Field Test for Measuring Locomotor Activity and Anxiety-Like Behavior. Methods Mol Biol; 1916: 99-103. 10.1007/978-1-4939-8994-2_9 Tal T., Myhre O., Fritsche E., Rüegg J., Craenen K., Aiello-Holden K., et al., 2024. New approach methods to assess developmental and adult neurotoxicity for regulatory use: a PARC work package 5 project. Frontiers in Toxicology; 6. 10.3389/ftox.2024.1359507 --- ## Noldus on the Road: animal conferences in 2026 URL: https://noldus.com/blog/noldus-on-the-road-animal-conferences-in-2026 Published: 2026-01-16 13:30:41 Description: In 2026, Noldus will be attending conferences across behavior and neuroscience research, including events focused on rodents, zebrafish, and more. Visit us to connect with the team, discuss your setup, and get a first look at what we are developing next. It is that time of the year again. I step out of my role as scientific writer and become your personal travel agent for 2026. That’s right, Noldus is going on the road again and we would love to meet you somewhere this year. We are not only going to neuroscience meetings focused on rodent research, but also fish and insect research. The world of behavioral science is changing all the time, and that is why Noldus is planning a major overhaul of their products this year. Come visit us at one of these conferences and find out what we have in store. Do you want to get more information about these conferences, or do you want to learn more about how we can enhance your behavioral research setup? Send us a message at marcom@noldus.com and we will happily answer your questions. IZM 26 - Italien zebrafish meeting Trento, 14-16 January Zebrafish are an ever-growing part of behavioral neuroscience. That is why we find it important to talk to zebrafish researchers and see what the field needs to keep improving. One such opportunity is the Italian zebrafish meeting in Trento this January. Enjoy interesting presentations by international keynote speakers as well as local up and coming researchers in the zebrafish field. Alternatively, come have a chat with us and see how we can bring your research to the next level together. Visit website: https://eventi.unitn.it/en/5th-italian-zebrafish-meeting BonBrain 2026 Bonn, 23-25 March Joint organized by the Max Planck Institute for Neurobiology of Behavior, DZNE and the University of Bonn, BonnBrain aims to strengthen the local neuroscience community while allowing collaboration with international thought leaders. That is why the organizers have invited many researchers from all over the world to come and discuss their work in various forms. Interestingly, BonnBrain also holds an art competition to concise with their scientific program. The winner will be the person that is able to most creatively convey their look on neuroscience. So, if you want to flex both your academic and creative brain muscles consider going to BonnBrain. Visit website: https://bonnbrain.de/ Annual meeting of the Cerebellum Club Aussois, 26-29 March Right after Germany we are going to the French Alps for the Annual meeting of the Cerebellum club in Aussois. This year’s edition promises to be very engaging, with six international keynote speakers and six scientific sessions, covering topics from molecular and cellular mechanisms to computational neurosciences and clinical studies. Come with us to the mountains for interesting debates, plenty of learning opportunities, and maybe even some beautiful snowy ski slopes. Visit website: WORDS Neuronus Krakow, 24-26 April Next up we are traveling to the beautiful city of Krakow for the Neuronus neuroscience forum. Organized by the students from the Jagiellonian University, this event is bound to be an interesting and exciting event. Students and seasoned researchers alike are welcome to present and share ideas on topics like general neurobiology, computational, cognitive and affective neuroscience, as well as clinical neurology. Visit website: https://clubcervelet.cnrs.fr/en/news-2/ Dutch Neuroscience Meeting Tiel, 25 & 26 January A bit closer to home (at least for us) is the Dutch Neuroscience meeting. As is customary nowadays, the meeting will be held at the Van der Valk Hotel in Tiel. You can look forward to an exhilarating event with many opportunities to network and learn from peers. We will also be walking around the venue, so if you want to discuss your current setup or what we can bring you in the future, be sure to come to talk to us. Visit website: https://dnm26.azuleon.org/ FENS 2026 Barcelona, 6-10 July Why go to FENS? That’s simple, it is the largest European neuroscience congregation of the year. With thousands of visitors every other year it is the best place to meet an international and multi-disciplinary group of scientists. In 2026 the conference will be held in amazing city of Barcelona. So, after you’ve had your fill of scientific debate and learning you can explore this stunning and culturally rich city. Of course, we will also be present in full force at FENS 2026. By July we will have plenty of new and exciting innovations that we can show. So come visit our booth to learn more about how you can update your current setup or start out with the best of the best. Visit website: https://fensforum.org European zebrafish meeting Vienna, 7-11 July At Noldus we see the continued and increasing use of zebrafish as a model species. Therefore, we love to meet the scientists that are continuing to advance in this field of behavioral science every day. That is why we are going to the European zebrafish meeting in Vienna this year. We are looking forward to collaborating, discussing and learning from the researchers and technicians that work with zebrafish day in and out. Are you interested in discovering how we can facilitate zebrafish research at different life-stages? Check out our free eBook to learn more. Visit website: https://www.ezm2026.org/ The ins and outs of zebrafish research Basic behavioral neuroscience in zebrafish Learn all about the why, when and how regarding zebrafish development and behavior Download arrow_forward NeuroFly Cologne, 7-11 September Behavioral science is not only rodents and fish, but insects also play an important role in various types of research. Fruit flies (Drosophila melanogaster) are the most used insect model for neuroscientific research. If you want to learn more about what is happening in the world of Drosophila research, consider visiting NeuroFly in Germany this year. This European gathering is focused on the neurobiology of Drosophila, but other invertebrate models will be included. Interested in visiting this conference? Then go to Cologne in September! Visit website: https://neurofly.org/home/ SocietyForNeuroscience 2026 Washington, 14-18 November Last but certainly not least we have Society for Neuroscience or better known as SFN. Every year SFN is a spectacle for the world of (behavioral) neuroscience. Last year in San Diego we introduced our new look and feel for the future, had plenty of fun games in our booth, and gave out the immensely popular Lego mice, but most importantly we had great conversations with you, the researchers working to make the world a better, safer and healthier place. This year we are planning to show so many incredible new things that I can’t reveal just yet. But stay tuned, book your ticket to Washington (and maybe pack some mittens because Washington is a lot colder than California), and come visit us at our booth. Visit website: https://www.sfn.org/meetings/neuroscience-2026 --- ## NIH Grant Writing Series: Insider Tips for Funding Success - Part 4 URL: https://noldus.com/blog/nih-grant-writing-series-insider-tips-for-funding-success-part-4 Published: 2025-12-29 10:43:40 Description: In this last post in the series, Dr William Gerin gives advice how to build a realistic budget, navigate new NIH policies, and write clearly and engagingly so reviewers understand and support your research. We are honored to welcome guest contributor, Dr. William Gerin, former Professor of Behavioral Medicine at Penn State University. Dr. Gerin is the author of Writing the NIH Grant Proposal: A Step-by-Step Guide, Third Edition (Sage Publishing). From Budgets to Good Writing Writing a grant is not just about the science. The practical details, budgets, policies, and clear writing often determine whether your proposal succeeds or fails. In this post, we'll explore how to prepare a budget that stands up to review, stay on top of NIH policy changes, and write in a way that engages reviewers. Budget Basics and Pitfalls Your budget tells a story, and reviewers read it carefully. Salaries and benefits often make up 80% of costs, and they need to be justified. Common pitfalls: - Adding unnecessary personnel. Don't list collaborators unless their role is clearly justified. - Padding or underestimating costs. Reviewers notice both, and neither inspires confidence. - Ignoring your business office. Submit your proposal to them early; they'll help with complex forms and signatures. Pro tip: Collecting pilot data is one of the most persuasive expenses you'll need to plan for. Policy Shifts You Need to Know Funding rules evolve, sometimes dramatically. In 2025, changes included: - Indirect costs (overhead). A proposed 15% cap was blocked in court, but debates continue. Institutions negotiate their own rates, sometimes as high as 60%, and this affects how much support you'll receive. - Diversity requirements. Many have been removed from proposals, altering review expectations. - Application formats. Biosketches, reference letters, and other documents have been updated. Most changes are minor, but you'll need to comply. Why Good Writing Matters Reviewers often read 20 proposals in one sitting, sometimes the night before a study section meets. Poor writing makes their job harder, and that can sink your score. Problems reviewers see all the time: - Inconsistent data across sections. - Ambiguity in phrasing or chronology. - Choppy, hard-to-read prose. Pro tip: Good writing won't guarantee success, but bad writing almost guarantees failure. Practical Writing Tips To improve clarity and flow: - Edit extensively: Ten rounds of revision is not too many. - Read aloud to yourself or others. What sounds confusing will read confusing. - Get outside feedback from colleagues, students, or even non-scientists. - Focus on flow: Your proposal should be easy and engaging to read, even in the methods section. Pro tip: Reviewers appreciate applications that are clear, logically organized, and easy to follow. WRITE BETTER PROPOSALS Get Your Free Guide We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to you! Download for free Conclusion Budgets and writing may feel secondary, but they are integral to success. A solid budget demonstrates professionalism and foresight, while clear writing makes reviewers' jobs easier. Pair these with strong collaborators, persuasive aims, and good pilot data, and you'll have built a proposal that stands out in a competitive field. Need support? Our Grant Assistance Program helps researchers develop protocols and maximize their Noldus systems. --- ## NIH Grant Writing Series: Insider Tips for Funding Success - Part 3 URL: https://noldus.com/blog/nih-grant-writing-series-insider-tips-for-funding-success-part-3 Published: 2025-12-17 10:25:10 Description: In this series of blog posts, Dr William Gerin gives advice on how to choose the right collaborators, craft a compelling Specific Aims page, and prepare pilot data that convinces reviewers your research is feasible, important, and worth funding. We are honored to welcome guest contributor, Dr. William Gerin, former Professor of Behavioral Medicine at Penn State University. Dr. Gerin is the author of Writing the NIH Grant Proposal: A Step-by-Step Guide, Third Edition (Sage Publishing). Finding Collaborators and Building a Strong Proposal Securing NIH funding isn't just about having a strong idea. Reviewers want to see that you have the right team, structure, and preliminary evidence to carry out your study. In this post, we'll explore how to choose collaborators wisely, define your aims effectively, and prepare persuasive pilot data. Preparation: Finding Collaborators Finding the right collaborators can make or break your proposal. It's not always obvious who to invite. Why collaborators matter: - They bring name recognition to your proposal. - They share the workload of writing and running the study. - They help with analysis and eventual publications. Who to invite: - Collaborators with skills you don't have (e.g., statisticians for sample size and power calculations). - Senior faculty if you are a new investigator. This reassures reviewers that you have experienced backup. - Colleagues who are credible in the eyes of reviewers. What to avoid: - Inviting people who don't truly add value. Reviewers will notice unnecessary names. - Overcommitting to friends if their role won't be meaningful. - "Uninviting" people later, which is awkward and unprofessional. Pro tip: Ask yourself, will I still want to work with this person once I'm funded? If the answer is no, think twice before adding them. The Power of the Specific Aims Page The Specific Aims page is often the only part of your proposal that every reviewer will read! This means that you only have one page to tell your story. A strong aims page should: - Define the health problem clearly. - Summarize what has been done before (and cite strategically). - Show how your proposal improves on past work. - Provide methodological details, including statistical approach. - Explain why your research matters, and do so with enthusiasm. Doing Your Homework with NIH Tools Before writing, use NIH RePORTER to study funded applications in your field. This shows you what NIH values and helps you refine your proposal. Also, decide early which Institute your application should go to, and which study section is the best fit. Reviewers are assigned from these panels, and citing their work when relevant demonstrates awareness and credibility. Pilot Data: Your Most Persuasive Evidence Pilot data convinces reviewers that you: - Know how to carry out the study. - Are using current theories and methods. - Have institutional support. - Already see trends consistent with your hypothesis. Pro tip: Don't over-collect data. If you already have statistically significant findings, reviewers may ask: Why do you need a grant at all? Instead, aim to show promising trends without "giving away the punchline". WRITE BETTER PROPOSALS Get Your Free Guide We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to you! Download for free Conclusion Strong proposals combine strong people, strong planning, and strong evidence. By choosing collaborators carefully, structuring your aims page with precision, and presenting persuasive pilot data, you'll inspire reviewer confidence and strengthen your chances of success. At Noldus, we know the process can be challenging. That's why our Grant Assistance Program provides guidance on behavioral protocols, tasks, and making the most of your Noldus system. --- ## Behavioral research explained: stimuli, emotion, interaction, and coding URL: https://noldus.com/blog/behavioral-research-explained-stimuli-emotion-interaction-and-coding Published: 2025-12-11 12:00:22 Description: Explore key concepts that shape human behavior research. This post brings together essential ideas that help researchers study behavior with more clarity. The final month of the year always feels a little different. Projects slow down. Labs wrap up their last studies. New plans begin to take shape. And many of us take a moment to reflect on the work that shaped the past twelve months. We enjoy doing the same with our blog. Looking back helps us understand which topics stood out and what readers searched for most throughout the year. The posts highlight key concepts, practical questions, and fascinating insights across human behavior research. If you missed any of them, this list is a great place to start. 1. What are stimuli in human behavior research? This post explains what stimuli are and why they play such a central role in human behavior research. It covers the different types of stimuli researchers use, how these stimuli can shape participant responses, and why careful selection is essential for a reliable study design. The article also walks through practical examples that help readers understand how to present stimuli effectively and how to control them in experiments. If you want a clear, grounded introduction to designing behavioral studies, this piece offers a solid foundation. What are stimuli in human behavior research? 2. Explore human behavior and emotions How do emotions guide the way we act, react, and interact? This post offers an accessible overview of the relationship between emotion and behavior. It walks through common methods for studying emotional responses, including structured observation with The Observer XT, facial expression analysis using FaceReader, and physiological measurement through NoldusHub. Each method reveals a different layer of emotional patterns and helps researchers build a more complete picture. It illustrates how integrating different measurement approaches can reveal nuances that might otherwise remain unnoticed, opening the door to deeper questions about why we respond the way we do. Which emotional signals would you like to explore further? 5 Must-read articles to explore human behavior and emotions Quick overview FaceReader This short info sheet gives you a clear look at what FaceReader can do: analyze behavior using just a webcam, with no hassle. You'll find an overview of key features like emotion detection, gaze tracking, and heart rate analysis, along with examples of how it's used in research and education. A great starting point if you want to explore behavioral tools or expand your research methods. Get your copy instantly 3. Cats react to human emotional scents This article explores findings showing that cats can detect and react to emotional cues in human scent. It outlines what these results mean for understanding animal communication and how such insights contribute to enhancing human–animal interaction. What else might our animals be sensing that we overlook? This post invites you to explore the subtle, unseen connections between human emotion and animal behavior. Cats and human emotions: A stronger bond than we thought? 4. Understanding social behavior How do individuals shape one another’s actions, even in simple everyday situations? This blog post takes a closer look at the mechanisms behind social behavior and shows how small cues, shared environments, and group dynamics influence the way we interact. The article highlights practical methods for capturing social interactions and offers guidance on how to design observational studies. From setting up the environment to recording and coding interactions. These practical tips can help you capture meaningful social dynamics right from the start. Understanding social behavior 5. Behavioral coding: What it is and how it works Behavioral coding plays a crucial role in turning observations into structured data. This post explains how coding systems are created, from defining behaviors to setting clear criteria, training coders, and ensuring consistency across observations. It shows why reliable coding matters: it reduces bias, improves reproducibility, and makes data comparable across studies. It offers concrete examples, for instance, how to code social interactions or subtle behavioral cues, so readers can see what a well-constructed coding scheme looks like in practice. The post also discusses common pitfalls and how to avoid them: such as vague definitions, inconsistent coding, or lack of coder training. Whether you’re planning a new observational study or refining your existing protocols, it provides the guidance you need to collect data in a systematic, reliable, and scientifically sound way. Behavioral coding: What and how Looking ahead These posts show just how broad and vibrant the field of human behavior research continues to be. They cover essential concepts, emerging insights, and practical methods that support researchers across disciplines. And while each topic stands on its own, together they highlight one shared theme: curiosity drives discovery. --- ## Behind the scenes of a usability test URL: https://noldus.com/blog/behind-the-scenes-of-a-usability-test Published: 2025-12-02 10:04:31 Description: Through usability testing, real user behavior comes into focus. It reveals hidden friction points and delivers insights that help shape better, more intuitive digital products. If you ever want to see how design decisions play out in real life, step into a usability lab. It's where assumptions fall apart, unexpected habits emerge, and real users reveal what your product truly does - and doesn't do - for them. A recent visit to a usability lab offered me a chance to watch how users interact with a prototype of public-service app for managing government allowances. Experiencing the process up close made the value of good user research impossible to ignore. A test day built around real people The UX team had recruited six respondents through an external agency. Each person participated in a 45-minute individual test. Before each session, the interviewer welcomed the respondent, asked warm-up questions, and explained the purpose of the test. For the test, they worked with a specially prepared dataset. The goal was to watch how they navigated screens, what made sense, what confused them, and where they hesitated. Small observations turned into big insights. For example, one respondent pointed out that a table didn't fit the screen well, and it wasn't obvious that scrolling was possible. Another said he missed reminders when income changes needed to be submitted. Small comments, perhaps, but they can influence meaningful improvements for the product team. A lab designed to capture every detail The testing environment was carefully set up. The respondents sat in a dedicated interview room with the moderator. Above them, three ceiling-mounted cameras captured their behavior. A fourth camera, positioned on the table, recorded facial expressions. There was also a tabletop microphone, and the mobile phone running the app was connected to a screen-capture device, which turns screens of a device into a video stream. This meant every action - touches, swipes, pauses, expressions - was available for the team to observe. Meanwhile, a few rooms away, the observation team watched everything using the AV tool Viso. Not only was the phone screen visible live and in full detail, but all camera feeds were displayed together, giving a complete overview of what was happening, including the respondent's posture, hand movements, and facial expressions. Observers could tune in on site or remotely. A dedicated note-taker typed out everything that was said, minute by minute. Why tests like this matter This usability test was structured in a way that made findings reliable and practical. - 1. It reveals real behavior – People often forget the small frustrations they encounter during everyday use. Seeing them in action tells a fuller story. - 2. Insights come immediately – After all sessions were finished, the team gathered to discuss the biggest takeaways. These insights shape app improvements quickly and effectively. - 3. Respondents feel comfortable sharing – The interviewer created space for honest discussion. Respondents spoke freely about what worked, what felt confusing, and what they wished the app would do differently. - 4. Clear and unobtrusive viewing is essential – You need to see what people actually do, without disturbing or steering their behavior. It pays to have a multidisciplinary team sit in, watch and discuss the test. It means synergy: each member pays attention to different aspects, and together they identify what is important. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download Watching all of this, I couldn't help thinking about future possibilities - like integrating automated facial expression analysis or eye-tracking to enrich the behavioral data and uncover even deeper insights. What I took away from the experience Being physically present in the lab made the process tangible. It showed how carefully these sessions are run, how much subtle behavior matters, and how important UX research tools are. These kinds of usability tests happen regularly. Sometimes in a dedicated lab, sometimes remotely. But the purpose always stays the same: understand real users so the product can evolve in the right direction. Seeing this in action reinforced something important: Great products don't happen by accident. They grow from watching, listening, and learning. --- ## Understanding epilepsy through a new mouse model URL: https://noldus.com/blog/understanding-epilepsy-through-a-new-mouse-model Published: 2025-12-02 08:15:00 Description: A new Frontiers in Molecular Neuroscience publication, coauthored by Noldus’ Jason Rogers, examines whether a very small cortical disruption can generate epilepsy. The study sought to explore how focal changes shape both neural function and behavior. Epilepsy affects most individuals with tuberous sclerosis complex, or TSC, yet the link between small cortical abnormalities and seizure generation is not fully understood. In a new study published in Frontiers in Molecular Neuroscience [1], researchers in Dr. Candi LaSarge's lab at Cincinnati Children's and the University of Cincinnati introduced a mouse model designed to answer a central question: Is a small, localized disruption in the frontal cortex enough to trigger epilepsy and related behavioral changes? The results show that it is, and they also demonstrate how automated behavioral tracking can support this type of research. Modeling tuberous sclerosis and focal epilepsy TSC is caused by mutations in the genes Tsc1 or Tsc2, which alter the mTOR pathway and affect cell growth. Many patients develop focal cortical lesions, known as tubers, that are strongly associated with seizures. However, it has been unclear whether such focal abnormalities alone are sufficient to create epileptic networks, or whether more widespread developmental changes are required. To test this directly, the research team deleted Tsc2 in a very small area of the frontal cortex shortly after birth. This approach allowed them to isolate the effects of a discrete lesion without disrupting the rest of the brain. The impact of a targeted Tsc2 deletion Even though the lesion was small, its impact was significant. - All mice with the focal Tsc2 deletion developed spontaneous seizures during EEG monitoring. - The affected neurons were enlarged and showed hyperactivation of the mTOR pathway. - Surrounding cortical tissue contained fewer inhibitory interneurons and showed increased microglial activation. Connecting cellular changes to behavior In addition to physiological outcomes, the team examined how the focal lesion influenced natural exploration. Behavior provides an essential complement to cellular and EEG data because it reflects how neural disruptions affect real-world function. Mice were placed in an open field arena for thirty minutes while their movement was tracked with EthoVision. This allowed the team to quantify locomotion and spatial preferences with high accuracy. The results showed a consistent pattern. Mice with the Tsc2 deletion explored the arena but avoided the center area. They displayed high thigmotaxic behavior, meaning they remained close to the walls, which is often interpreted as increased anxiety. Importantly, the groups did not differ in total distance traveled. This means the shift in exploration strategy was not caused by reduced mobility but by a change in how the animals chose to explore the space. Copyright © 2025 McCoy, Dusing, Jerow, Winstel, Zhan, Rogers, Wesley, Otten, Danzer and LaSarge How EthoVision contributed EthoVision supported the study by providing reliable, high resolution movement data in a simple and unobtrusive way. The software allowed the researchers to quantify center time, thigmotaxis, and locomotor activity without manual scoring. These measures helped reveal the behavioral effects of the focal lesion and supported the broader conclusion that local cortical disruptions can influence both seizures and behavior. Automated tracking is especially helpful in TSC and epilepsy research. Many behavioral changes are subtle, and consistent quantification is important when linking behavior to cellular and network level findings. FREE TRIAL Experience EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A time and cost-effective solution - Powerful data selection - Gold standard in automated video tracking Try it out for free! A model that supports future research This focal TSC model brings together several important features of the disorder. It produces seizures, altered inhibitory circuits, neuroinflammation, and changes in exploration. Because the lesion is small and well defined, the model can help researchers investigate how specific cortical disruptions lead to epileptic activity and behavioral consequences. By combining EEG, histology, and automated behavioral tracking, the researchers created a comprehensive picture of how focal pathology affects the whole animal. This integrated approach will support future studies on epileptogenesis, circuit dysfunction, and potential therapeutic interventions. References [1] McCoy C, Dusing M, Jerow LG, Winstel GC, Zhan F, Rogers JL, Wesley M, Otten JB, Danzer SC and LaSarge CL (2025). Focal postnataldeletionof Tsc2 causes epilepsy. Front.Mol.Neurosci. 18:1686023. https://doi.org/10.3389/fnmol.2025.1686023. --- ## What can I use DanioVision for? URL: https://noldus.com/blog/what-can-i-use-daniovision-for Published: 2025-11-18 10:00:00 Description: Researchers use zebrafish of all life stages, from embryo's to full adults. These researchers do high-throughput research and are therefore in need of a good automated system. DanioVision is the best tool for this type of research. Zebrafish are an often-used model for a variety of applications. They are relatively easily genetically modified to serve as a model for specific diseases or toxins and drugs. This makes them invaluable to the scientific community in all stages of their life. If you need high throughput testing of zebrafish larvae or other small organisms, DanioVision is the system for you. It has been used for almost 2 decades and has been validated in more than 1500 publications. DanioVision combines an integrated hardware setup with all the benefits of the best video tracker, EthoVision XT. In this blog we will go over some of the applications DanioVision has been used for. If you have any questions on specific validations, you can always get in contact, and we will help you out. Drug discovery and safety pharmacology Zebrafish are more similar to humans than you might think. Therefore, they are an excellent model to track disease progression and test potential drugs or other interventions. One such disease is cancer. Zebrafish have been used in Oncology studies as a translational model for over 10 years (Barriuso 2015). DanioVision has been used to study phototaxis assays with cancer model zebrafish larvae. Zebrafish are more similar to humans than you might think. In fact, zebrafish share approximately 70% of their genes with humans, and about 84% of human genes linked to disease have a counterpart in zebrafish. Toxicology Zebrafish are an excellent model to test the influence of various toxic compounds on behavior. They are especially often used in eco-neurotoxicology. This field of science focuses on pollutants that can be found in the environment. This can include heavy metals, pesticides, harmful chemicals and much more. Most of these studies research the effect of these compounds on the nervous system of the zebrafish. An example of behavioral endpoints commonly used in zebrafish (usually in larvae or juveniles) to assess these neurotoxic effects are: - Spontaneous locomotor activity - Speed alteration tests, overall changes in motility (hyperactivity, hypoactivity), and specific swimming patterns such as thigmotaxis (wall hugging). - Sensory-motor biotests - The startle response is an example of sensory-motor testing. It is the animal's defensive reaction to a sudden and unexpected stimulus, such as a sound, vibration, light change, or a moving shadow simulating a predator. You usually see a pronounced increase in non-directional locomotion, often followed by more complex behaviors, such as avoidance or shelter seeking. Behavioral assays in eco-neurotoxicology Aquatic environments face an ever-increasing burden of the daily, human, introduction of contaminants. Many of these contaminants have shown to be neurotoxic or neuro-modulating, meaning that they are harmful for both humans and animals through contaminated drinking water and accumulation in aquatic foods. However, this form of pollution should be, and currently is, gaining awareness considering the impact it has on animal behavior. This white paper, written in collaboration with Prof. Donald Wlodkowic, an expert in eco-neurotoxicology, touches upon this subject, and shows how DanioVision and EthoVision XT can advance your research. Download the White Paper for free Circadian rhythm Zebrafish are often used to study the effect of certain interventions on the effectiveness of the day night cycle. Zebrafish can display significant locomotor activities four days after fertilization, because that is when the swim bladder has developed enough to be functional. After this development has occurred researchers can observe and track the basic locomotion's of the larvae. In response to light and dark periods (which are preprogrammed in DanioVision) locomotor behavior of the larvae will change. How this change presents itself in relation to certain compounds or interventions is of interest to researchers. "There is apparently no organ and no function in the body which does not exhibit a similar daily rhythmicity" – Aschoff (Circadian rhythms in man, 1965). Therefore, if an organ or the body is affected observing the behavior for both the light and dark period could give insights into the effects. With DanioVision you can observe larvae for multiple days. This results in you having a robust and rich dataset. Epilepsy & seizure modeling Zebrafish larvae have been used to model various forms of epilepsy, including both genetic and chemically induced forms of the disorder. Researchers can use a variety of techniques to induce seizures in the larvae, such as administering convulsant drugs or exposing them to specific light stimuli and then study the underlying neural mechanisms that drive the seizures. Researching Epilepsy models in EthoVision XT Zebrafish (Danio rerio) have emerged as a premier model organism in neuroscience research, including epilepsy studies, due to their genetic manipulability, translational potential, and the feasibility of large-scale phenotypic screenings. In this whitepaper we go over how zebrafish are used in tandem with EthoVision XT. Download the White Paper for free DanioVision can include the so-called tapping device. With this device and EthoVision XT, you can automatically set the timing and intensity of the tapping. This means that every input is controlled and consistent. Visual and photo-motor responses There are various tests that involve the ability of the zebrafish to response to external stimuli. One is the previously mentioned startle reflex, but researchers also use light to elicit a behavioral response. The larval photomotor response (LPR) assay is a sensory-motor biotest performed on freely swimming zebrafish larvae at the age of 5 to 7 dpf. At that developmental stage, fish show stereotypic non-directional light seeking behavior, which is a rapid increase in locomotion in response to turning off the light. Phototaxis is a directional response to light. It can be positive when the test animal moves toward the light, and negative when the animal moves away from it. Qian et al. (2021) found a significant inhibi¬tion of the phototactic response in zebrafish larvae following exposure to Boscalid, a neurotoxic fungi¬cide. Startle reflexes or habituation The startle response in zebrafish larvae is a preserved defense response performed as tail coil. This body-bend is done in reaction to a variety of sensory stimuli. Changes to this response can reflect the effect of neuropsychiatric disorders. Researchers look at in what way and how frequent the larvae perform this startle response as a reaction to standardized stimuli. Movement disorders Certain neurotoxic compounds can be linked to neurodegenerative disorders like Alzheimer's disease (AD) and Parkinson's disease (PD). Zebrafish are widely used as a toxicological model for neurotoxic research because of their many advantages like similarities to the human genome especially in physiological function and signal transduction pathways. These similarities make zebrafish, paired with a robust behavioral response, a great model for these diseases. Researchers like pang et al. (2019) used DanioVision to observe locomotor behavior as a readout of the nervous system under influence of potentially toxic compounds. Even though these researchers also looked at the genetic markers for PD, behavioral assessment is still needed to get the full picture of the physiological effects of these interventions. Optogenetics Zebrafish larvae are naturally transparent, which makes them great for light-based (optogenetic) experiments. With the DanioVision Optogenetics Add-on, you can deliver controlled light patterns (color, intensity, timing) and immediately measure how behavior changes with EthoVision XT. For example, you might briefly shine light to activate a brain circuit and see swimming increase or use another light pattern to quiet a circuit and see activity drop. Because everything is synchronized and runs in multi-well plates, you can test many conditions in a consistent, high-throughput way, ideal for screening, method development, or confirming causal links between brain activity and behavior. Keep your research going! Want to learn more about DanioVision? Or do you have a question regarding applications or methodology? Feel free to reach out and we will help you along. References Barriuso, J.; Nagaraju, R.; Hurlstone, A. Zebrafish: A New Companion for Translational Research in Oncology. Clin. Cancer Res. 2015, 21, 969–975, doi:10.1158/1078-0432.CCR-14-2921. Aschoff, J. Circadian Rhythms in Man. Science 1965, 148, 1427–1432, doi:10.1126/science.148.3676.1427. Qian, L.; Qi, S.; Wang, Z.; Magnuson, J.T.; Volz, D.C.; Schlenk, D.; Jiang, J.; Wang, C. Environmentally Relevant Concentrations of Boscalid Exposure Affects the Neurobehavioral Response of Zebrafish by Disrupting Visual and Nervous Systems. J. Hazard. Mater. 2021, 404, 124083, doi:10.1016/j.jhazmat.2020.124083. Pang, M.; Song, X.; Miao, Y.; Wang, Y.; Zhou, C.; Geng, Z.; Du, J.; Moussian, B.; Su, Y.; Liu, X.; et al. Aconitum Carmichaelii Triggers Neurotoxicity and Parkinson-like Symptoms through Initiation of ROS-Mitochondrial Apoptosis and the Nox5/DJ-1 Signaling Pathway. BMEMat 2023, 1, e12019, doi:10.1002/bmm2.12019. --- ## How new methods are transforming Autism Research URL: https://noldus.com/blog/how-new-methods-are-transforming-autism-research Published: 2025-11-10 15:15:57 Description: Researchers apply behavioral and physiological tools in everyday environments to study autism as it truly happens. These real-world approaches bring research closer to daily life and deepen our understanding of human behavior. For decades, autism research has focused on describing behaviors and identifying diagnostic patterns. But a new generation of studies is moving beyond description toward measurement, precision, and context. Understanding autism through new lenses Across recent publications, a shared theme is emerging: researchers are combining behavioral science with technology to observe communication, emotion, and learning as they naturally unfold. This shift isn't about replacing human insight with machines; it's about using smarter tools to see more clearly what has always been there. Measuring what we couldn't see before Traditional assessments rely on structured observation and caregiver reports. These methods remain essential, yet they sometimes miss the earliest, most subtle signs of how communication begins and develops. That gap inspired Choi-Tucci et al. (2025) to develop the Intentional Communication Coding Scale — a tool that quantifies how infants purposefully use gaze, vocalization, and gesture. To do so, the team used The Observer XT, a software platform for behavioral coding and analysis. By annotating caregiver–infant videos frame by frame, the researchers could capture not only what behaviors occurred but how and when they were directed toward another person. For instance, when a caregiver asked, "What does the monkey say?" one child looked up and made a playful "hee-hee-hee" sound. A small act that clearly showed awareness of the other person. This level of detail made it possible to study intentionality — a subtle but crucial aspect of early social communication — with objectivity and reproducibility. The result: a coding system that turns natural interaction into structured, quantifiable data, helping researchers and clinicians detect meaningful developmental patterns earlier than ever before. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial When behavior speaks through data Another study, by Bahrami Rad et al. (2025), took this approach further. Their team used wearable sensors to record physiological signals such as muscle activity, electrodermal activity, and skin temperature in individuals with multiple disabilities and autism who displayed challenging behaviors. Using The Observer XT, the researchers carefully coded each behavior on video and linked it to the data from the wearable sensors. This allowed them to see, second by second, how changes in movement or body signals, such as increased arousal, connected to specific emotions or behaviors. The insight was striking: movement patterns were often the earliest and strongest indicators of stress or agitation. These findings point to the potential of predictive modeling — a system that could warn caregivers before behavior escalates, for example, into self-injurious behavior. Here, The Observer XT served as the backbone for data synchronization, ensuring that physiological measurements were grounded in behavioral context. The result is a rich, multi-layered understanding of emotional regulation. Reading emotions with precision While observation and physiology reveal what people do, understanding how they feel requires another layer of analysis. In his study (2025), Erkan Kurnaz explored Video Self-Modeling (VSM) — an instructional technique in which learners watch short videos of themselves performing a task successfully. This approach builds on the idea that seeing one's own success can strengthen self-confidence, motivation, and behavioral learning. VSM has long been used in behavioral and special education research to help children with autism develop social, communication, and learning skills. It combines two effective elements: - Self-observation: learners see their own correct behavior, which reinforces the desired skill; - Positive modeling: the model (the learner) is inherently familiar and predictable, which reduces anxiety and supports focus. In this study, VSM was applied to teaching unplugged coding skills — activities that introduce the logic of programming without using computers. Children learned the basics of sequencing, loops, and conditional reasoning through hands-on materials such as cards, puzzles, and movement games. These exercises help children think like programmers, but in a tactile, visual, and concrete way that suits many learners with autism. Validating engagement with FaceReader Before implementing the VSM intervention, the research team wanted to verify that participants were comfortable watching their own recorded videos. To do this, they used FaceReader to analyze facial expressions while the children viewed short clips of themselves compared with blank-screen videos. FaceReader automatically detected emotions such as happiness, sadness, and surprise, providing objective data about each child's affective response. The results showed that the children displayed more positive facial expressions when watching their own successful performances, confirming that they enjoyed and engaged with the process. This validation step mattered: it demonstrated that video self-modeling was not only feasible but emotionally motivating. By combining VSM with automated emotion analysis, the study provided a clear example of how technology can make both learning and emotional engagement measurable — and visible — in autism education. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Research grounded in real life A defining feature of these studies is their ecological validity, meaning that the research takes place in real-life environments, such as homes, classrooms, or everyday activities, instead of controlled lab settings. - Choi-Tucci's study observed spontaneous caregiver–infant play. - Bahrami Rad's work took place in classrooms and residential environments. - Kurnaz's intervention happened during authentic learning sessions. In each case, Noldus tools enabled rigorous data collection without disrupting natural interaction. The Observer XT offered precise timing and annotation, while FaceReader added automated emotional analysis from unstructured video. Together, they allowed researchers to preserve realism and maintain scientific precision. This combination of natural context and objective data marks an important methodological advance: autism research that is both realistic and reproducible. A holistic shift in autism research Together, these studies highlight an important evolution: autism research is becoming more multimodal, quantitative, and responsive to real-world complexity. Three broader shifts stand out: - 1. From traits to processes – Instead of focusing only on diagnostic features, researchers are studying how communication, stress, or learning unfolds over time. Autism is seen not as a static condition but as a dynamic interaction between the individual and their environment. - 2. From clinical to technological precision – Tools such as wearable sensors, behavioral coding systems, and automated video analysis add a layer of objectivity and reproducibility. They allow teams to detect subtle changes that humans might miss — especially useful for early intervention and progress monitoring. - 3. From observation to integration – By combining video coding, physiological data, and emotion analytics, researchers can create a multilayered picture of each participant's experience. The result is not just more data, but richer, context-aware understanding. Crucially, technology should extend, not replace, human understanding. The Observer XT and FaceReader are powerful because they extend human expertise. Behind every data point is a person whose emotions and behaviors deserve empathy as much as analysis. Looking ahead: from data to understanding What ties these studies together is a shift from seeing behavior to understanding experience. By using Noldus tools to synchronize observation, emotion, and environment, researchers can now trace how learning, communication, and stress interact in real time. By combining Noldus tools with wearable sensing and educational innovation, researchers are now able to: - Measure communicative intent before language develops. - Detect early signs of distress through synchronized movement and physiology. - Quantify emotional engagement in learning through facial expression analysis. When behavioral science and technology come together, autism research becomes more connected to everyday life. It allows us to ask richer questions. Not only "what does autism look like?" but "how does it feel, develop, and adapt?" References - Bahrami Rad, A.; Villavincencio, T.; Kiarashi, Y.; Anderson, C.; Foster, J.; Kwon, H.; Hamlin, T.; Lantz, J. & Clifford, G.D. (2025). From motion to emotion: exploring challenging behaviors in autism spectrum disorder through analysis of wearable physiology and movement. Physiological Measurement, 46. https://doi.org/10.1088/1361-6579/ada51b - Choi-Tucci, E.; Sideris, J.; Holland C.; Baranek, G.T. & Watson, L.R. (2025). Measuring Intentional Communication in Infants at Elevated Likelihood of Autism: Validity, Reliability, and Responsiveness of a Novel Coding Scale. Journal of Speech, Language, and Hearing Research, 68, 1151-1160. https://doi.org/10.1044/2024_JSLHR-23-00787 - Kurnaz, E. (2025). Effectiveness of Video Self-Modeling in Teaching Unplugged Coding Skills to Children with Autism Spectrum Disorders. Behavioral sciences, 15(3), 272. https://doi.org/10.3390/bs15030272 --- ## Eye tracking without the expensive hardware: powered by FaceReader URL: https://noldus.com/blog/eye-tracking-without-the-expensive-hardware-eyereader Published: 2025-10-21 09:25:00 Description: Ever wondered what really catches someone’s eye? FaceReader now includes webcam-based eye tracking, giving you powerful insights into where people look, how they feel, and what drives their decisions. No extra hardware required. If you've ever wondered what people are really looking at when they scroll, shop, or engage with a screen — here's your answer. With FaceReader's built‑in webcam eye tracking, you get powerful gaze insights without needing pricey hardware. Smart tech, simple setup - designed for your research With FaceReader, your standard USB or built‑in webcam becomes a smart gaze‑tracker. Here's what happens: - The webcam captures your face and identifies key points like eyes and head position. - All this information goes into a pre-trained neural network to calculate a 3D gaze vector. That is, the direction your eyes are looking. - A short calibration, in which you follow dots on a screen for a few moments, aligns the gaze with your screen. This way, FaceReader can track where your eyes are moving. This means you don't need expensive eye‑tracker hardware or a complex lab setup to collect eye tracking data. You save money, time, and you can reach participants wherever they are. You may also like these blogs posts about how to measure audience engagement or how attention detection is validated in FaceReader. Accuracy you can trust You might be wondering: Can a regular webcam really measure where people are looking? The short answer is yes — and it's surprisingly accurate. FaceReader's webcam-based eye tracking was tested on 17 participants and compared to a professional system: the Tobii Nano Pro. Here's what came out of it: - On a desktop screen, the average error was just 2.4 cm - In 85–90% of the cases, the gaze was within 4 cm of the actual spot - Even at 3 cm, accuracy was still around 75% It means you can confidently use webcam eye tracking to see which part of your website or product gets the most attention and to compare how long someone looks at different items, without the need of an expensive lab setup. FREE WHITE PAPER Webcam-based eye tracking Download this white paper to learn about: - The technology behind webcam-based eye tracking - Validation of its accuracy - Practical applications and usability Read now The balance between flexibility and accuracy Expensive hardware eye trackers can reach an accuracy of above 99% for 1/16th of the screen, so yes, they're still more precise. If you need to track minute eye movements in a strictly controlled lab, you might want to stick with hardware eye trackers. But if you don't need that level of detail, FaceReader's webcam-based eye tracking delivers the accuracy most studies realistically need. It gives you something big: a low-threshold way to gather valuable eye tracking data using the equipment you already have. Practical uses in real-world settings Webcam-based eye tracking isn't just a technical feature — it's a powerful tool to explore how people view, evaluate, and interact with what you show them. Depending on your research goals, you can apply it in a variety of ways to gather meaningful insights. - Usability tests: Spot where website users get confused or where they focus on the most - Product design: Understand how packaging draws attention to a shelf or a webstore - Psychology studies: Collect data from large, diverse samples without getting everyone into a lab - Advertising research: See which parts of an ad captures people's attention Better insights in attention With FaceReader's gaze tracking, you gain clear and meaningful insight into what people look at, when they look at it, and for how long. It's a solution that works with standard hardware, integrates smoothly into your workflow, and helps you analyze faster. And it goes beyond just measuring attention. By combining gaze data with facial expression analysis, you can also explore user preferences, emotional engagement, and decision-making processes with greater depth. In short, you don't need to invest in expensive equipment to study visual attention and engagement. FaceReader gives you a reliable and accessible way to do just that. Pssst! Curious about other cool innovations in FaceReader? Explore what more is new! --- ## FAQ: tips and tricks for CatWalk XT URL: https://noldus.com/blog/faq-tips-and-tricks-for-catwalk-xt Published: 2025-10-09 16:20:21 Description: We've compiled a list of the most asked questions by CatWalk XT users. For this blog we have asked our best trainers to answer these questions. Whether you are a beginner or a seasoned user, there is something here for everyone. What is CatWalk XT CatWalk XT is a system for analyzing gait and locomotion in rats, mice, and other small mammals. Green light enters the glass walkway and is trapped by total internal reflection. However, when a paw touches the glass, the refractive index changes, and the underside lights up. A high-speed camera captures these illuminated paw prints. The software then classifies, quantifies, and visualizes your gait data. This allows you to perform high-quality gait and locomotion research. To help you get started with using CatWalk XT or just to allow you to get the most out of your system, we've compiled a list of Frequently Asked Questions and their answers. If you have any additional questions that you need answered feel free to send us a message. Which parameters should I choose? If you are new to CatWalk XT, the menu of parameters can feel overwhelming. Because CatWalk XT can produce many gait parameters it is important to consider which ones are relevant for your model. A multi-disorder review of 91 mouse studies grouped commonly used measures into temporal, spatial, support, coordination, and print categories, and shows which ones most often change per model. A reliable starting set of parameters across models includes run speed, stand time, swing speed, stride length, regularity index (RI), and maximum contact area. From there, layer on model-specific measures as needed. In the paper by Timotius et al. you can see which parameters consistently shift in traumatic brain injury, stroke, sciatic nerve injury, spinal cord injury, Parkinson's disease, and ataxia. Read the full publication to get the complete overview. How should I configure Detection Settings? Treat Detection Settings as experiment-specific, not a one-off that you set and forget. Begin with the automatic configuration for camera gain and intensity threshold to establish a sensible baseline. Next, fine-tune manually while observing paw-print contours in real time. Use an animal of average weight across your treatment groups when you set these values. This keeps prints representative and comparable. Because detection performance scales with weight, the same settings usually accommodate group differences. In longitudinal studies with substantial growth, for example from 100 g to 500 g, create a fresh set of Detection Settings at the higher weight to maintain print fidelity. Finally, avoid comparing intensity variables across different settings or time points. For intensity, use intra-animal comparisons, such as affected versus contralateral paw, to avoid confounding results. How do I motivate animals to traverse smoothly? Smooth, spontaneous crossings come from low stress and clear motivation. Start by habituating animals to gentle handling and to the test room. When the walkway feels familiar rather than threatening, animals initiate runs more readily. Keep your movements unhurried and the environment predictable. A low, constant background audio source can mask incidental noises that might otherwise interrupt a run. Social motivation is effective. Once a rat learns there is an exit, placing cage mates in the goal box provides a strong, natural incentive to cross without coercion. Food rewards rarely improve performance in a novel environment and can distract, so it is best to skip them. Avoid any forcing of behaviors. Do not push, startle, or cue with sharp noises, and allow ample time for voluntary initiation. Waiting up to about 20 minutes is acceptable in early sessions. Maintain the covered walkway and approach at animal level, since looming from above can feel predatory and stall progress. WHITEPAPER How to motivate your animals across the walkway Learn from a seasoned CatWalk XT user how she prepares her animals to get the best data possible. Get access How do I clean and maintain the system? Scents and stains change behavior and degrade data. Especially droppings and urine from other animals. Clean the walkway and side walls before each run using an alcohol solution or a proprietary glass cleaner, but water with some vinegar can also usually do the trick. Make sure you remove every instance of cleaning supplies with a soft cloth before starting the test. Since these odors can also influence the animal's behavior. Make sure that after cleaning the walkway is returned to the desired width. Because a varying with will influence the locomotion. How do I get the best data quality? Frequently, gentle handling ahead of test day reduces stress reactivity. Handle animals carefully when moving them to the glass plate. For example, use a tube when transporting the animal from cage to device. Keep the room calm and free of sudden sounds. Background audio can help maintain steady traversals. Record in low light. CatWalk XT performs best in dim conditions. CatWalk XT doesn't need any additional room lighting to function. Therefore, we If you need additional visibility, use a dim red indirect light for the handler. Quick setup checklist - Choose a core parameter set suited to your model, for example run speed, stand time, swing speed, stride length, RI, and maximum contact area. - Auto-configure gain and threshold, then fine-tune with an average-weight animal. Create new settings if weights change markedly. - Avoid cross-setting intensity comparisons. Use intra-animal intensity comparisons instead. - Habituate animals, use cage mates in the goal box, and avoid food rewards. - Keep it quiet, avoid looming from above, and record in low light. - Clean the walkway and walls Your question not answered? Send us an message and we can help you with: - Finding out how gait analysis can help your research - Which parameters are important for your model - Answer any other research setup questions Take the next step --- ## Animal research assists in understanding fentanyl withdrawal symptoms URL: https://noldus.com/blog/animal-research-assists-in-understanding-fentanyl-withdrawal-symptoms Published: 2025-09-10 15:00:00 Description: Drug overdose lethality has risen over the last years. Fentanyl is the biggest contributor to deaths in the USA. In this blog we explore the complications with researching fentanyl and how animal models provide much needed insights. Overdose deaths related to synthetic opioids (primarily fentanyl) in the US have increased to over 73.000 thousand deaths per year [1]. This makes fentanyl the biggest contributor to drug overdose deaths. But how did we get here? And how is animal research contributing to understanding addiction and withdrawal? Keep reading this blog to learn more. What is Fentanyl and why is it a problem? Fentanyl is a synthetic opioid that was originally created to serve as a painkiller for surgeries. However, fentanyl has become problematic because drug dealers have been lacing and replacing drugs with fentanyl. Even though dealers have been doing this since the 70-ties, recently the occurrences have skyrocketed. Higher production in countries like China, Mexico and India in combination with the emergence of the dark web, has created an environment for illegal drug trafficking to flourish. Lethal dose of Fentanyl This has the effect that more people are knowingly and unknowingly consuming fentanyl. The drug is very potent there is a high risk of overdose and addiction. Therefore, it is important to know more about how exposure influences the behavior and physiology of users. Research into withdrawal symptoms and recovery Much like other opioids, fentanyl binds to the brain's opioid receptors. These receptors are in the parts of the brain that control emotions and pain. Therefore, using fentanyl numbs the body's responses and causes a rush of dopamine. Extended usage can also cause confusion, nausea and loss of consciousness. How addiction and withdrawal progress Because of its relatively short high and strong impact, it is very easy to get addicted to fentanyl. Addiction increases the tolerance of the user to individual doses, causing them to keep seeking more drugs, for a similar high. Besides the various health risks that come with addiction, extensive opioid usage carries a heightened risk of experiencing an overdose. During an overdose the drug user will experience either slowed or stopped breathing as well as other numbing effects. This loss of oxygen can cause the person to suffocate and die. If a person is experiencing fentanyl overdose their breathing can be restored by administering naloxone. Complications with treating Fentanyl While opioid replacement therapies such as methadone and buprenorphine are effective in treating opioid use disorder, treating fentanyl addiction poses unique challenges. Its potency, fast-acting nature, and short duration of effect complicate both withdrawal management and relapse prevention. More preclinical research is necessary to uncover the neurobiological underpinnings of fentanyl addiction and identify potential therapeutic strategies. Animal research gives insight into addicition Researchers from the University of North Carolina developed a drinking in the dark (DiD) paradigm to model oral fentanyl self-administration [2]. Male and female mice were given access to increasing fentanyl concentrations over five weeks. This design mimics a voluntary oral consumption route, an increasingly common way fentanyl is taken due to counterfeit pills in the illicit drug supply. Here are some of their key findings: - Fentanyl consumption increased with increasing concentrations even though water consumption was decreased. - Naloxone-precipitated withdrawal revealed sex differences. Males displayed more severe withdrawal symptoms despite consuming less fentanyl. This indicates that withdrawal severity is not strictly dose dependent. - Fentanyl impaired habituation and increased avoidance behaviors. Males spent less time in the light compartment during the light-dark test, while females showed altered adaptation in the open field. - Ten days into abstinence, fentanyl-exposed mice showed impaired fear extinction learning, freezing more in response to conditioned cues compared to controls. This highlights a disruption in emotional regulation processes. - Electrophysiological recordings revealed that basolateral amygdala (BLA) neurons became hyperexcitable, with an increased excitatory-to-inhibitory ratio. These changes likely contribute to the impaired fear extinction and heightened avoidance behaviors. How EthoVision contributed To measure the fear response and learning of the mice, the researchers used a fear conditioning chamber with a shock grid floor. Both the controlling of the hardware and analysis of behavior were done by EthoVision XT. EthoVision XT is the premier behavioral tracker used by researchers all over the world. With this software, you can not only control a fear conditioning system, but many other systems. Furthermore, EthoVision XT allows you to automatically classify behaviors, track the nose, base and tail point, and analyze activity. Its versatility allows for precise measurements in studies of addiction, anxiety, and learning, making it an essential tool for translational research. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial Key take aways - Long-term oral fentanyl exposure disrupts behavior and neural function in mice. - Sex-specific differences emerged: males showed stronger withdrawal symptoms, while females consumed more fentanyl. - Fear extinction learning was impaired, linking fentanyl withdrawal to emotional dysregulation. - The basolateral amygdala was identified as a critical hub for these neural changes. - EthoVision XT enabled precise measurement of fear responses and behavior, supporting robust translational research. References [1] National Institute on Drug Abuse, visited September 2025. https://nida.nih.gov/research-topics/trends-statistics/overdose-death-rates [2] Downs, A.M.; Kmiec, G.; McElligott, Z.A.(2024) Oral Fentanyl Consumption and Withdrawal Impairs Fear Extinction Learning and Enhances Basolateral Amygdala Principal Neuron Excitatory-Inhibitory Balance in Male and Female Mice. Addict. Neurosci, 13, 100182. https://doi.org/10.1016/j.addicn.2024.100182 --- ## Behavioral coding: What and how URL: https://noldus.com/blog/behavioral-coding-what-and-how Published: 2025-08-27 11:00:00 Description: When you study human behavior, coding your data is the initial step to analyze data. Coding behavior enables you to evaluate your research questions and draw reliable conclusions. By observing behavior, you discover an awful lot about human life. For instance, you can study how children develop, how dyads interact, how consumers respond to advertisements, how a team communicates, and so on. When you are observing behaviors, either live or using recorded videos, you can gain an enormous amount of insight by coding the behaviors you are observing. Whether it is a child playing, a doctor and a patient interacting, or students practicing a new skill. What is behavioral coding? When you study human behavior, coding your data is the initial step to analyze data. The data obtained from (video) observations, surveys, or experiments are in raw form. This data needs to be refined and organized to be able to evaluate and draw conclusions.  Behavioral coding helps quantify qualitative data and gives sense to raw data. It categorizes your data meaningfully.  Why it matters: - Accurate outcomes - you'll trust what you see - Clear and repeatable - others can follow your steps - Quantifiable insights - data you can slice, dice, and act on Think of your coding scheme as your measuring instrument. Build it smart, because setting up a good coding scheme often requires quite some thinking. Only include what answers your questions. Don’t overcomplicate it. For instance, if you are interested in eating behavior, do not add codes for talking. Focus saves time and delivers clarity. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Why you'll use behavioral coding every step of the way Behavioral coding is a way of getting to know your data better and what behaviors are of interest. It is an important step in the process of the analysis of your data and explaining why things happen.  Behavioral coding can be useful prior to actual data collection for pretesting data collection procedures, for example to discover which codes are most valuable, and which wording can be best used. Of course coding behavior during data collection is very common, but certainly also after data collection to evaluate the quality of the data and to explore causes and effects of behaviors.  What behaviors can you code? Depending on what your research questions are, you can narrow down what behaviors you are going to be coding. For example: - Body language and non-verbal behavior, e.g. posture, movements, gaze, eye contact, and gesturing. - Verbal behavior, e.g. talking, intonation, and tone. - Facial expressions, e.g. specific emotions and muscle movements. Using the codes, you might be looking at frequencies in behaviors and at sequences, or at similarities and differences. Duration of eye contact or talking may also give valuable clues. There are several coding schemes available that you can use. Examples of published coding schemes include Facial Action Coding System (Ekman, Friesen & Hager, 2002), Body Action & Posture Coding System (Dael, Mortillaro & Scherer, 2012), and Annotation Scheme for Conversational Gestures (Kipp, Neff & Albrecht, 2007).  You can use these coding schemes as a base, so you do not have to figure out everything from scratch. Another benefit is that these coding schemes are already validated.  Download here the FREE white paper 'Facial Action Coding System (FACS)' Real-world example: mealtime coding that works The research team of Lenna Ontai at the University of California conducted a study to measure parent-food-related behaviors. Parents were asked to score 27 statements of My Child at Mealtime (MCMT), such as ‘I get my child to eat by explaining that the food is good for him’, ‘I praise my child for eating’, and ‘I hand-feed my child to get her to eat’. A subsample of 60 caregivers participated in the mealtime observations, which were recorded in their home.  These recordings were all coded using The Observer XT. Behavior codes were adapted from the modified BATMAN (Bob and Tom's method for assessing nutrition; Klesges et al., 1983) coding procedure documented by Koivisto and colleagues (Koivisto, Fellenius, & Sjödén, 1994). FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Coding mealtime behaviors The researchers coded nine food related behaviors. These behaviors were categorized in parent-centered behaviors: - physical manipulation (puts child in the chair) - feeding child (places foods or drinks into child’s mouth) - verbal demands to eat (tells child they need to eat) - bargaining (engages in a negotiation about quantity of food to be consumed) and child-centered behaviors: - eating statements (statements about the child eating) - eating inquiries (questions about the child eating either presently or during another meal) - requests to eat (asking child to eat or try a food) - preference statements about food (whether the child likes/dislikes a food) - general food statements (statements about food made to the child) Most of the codes are related to speech. Speech is a process that takes a while, therefore the researchers used 10 seconds segment codes for speech related to the same topic. Behavior codes (like manipulation and feeding) were not considered mutually exclusive and could occur at the same time, while speech codes could only receive one code. By comparing the self-reported MCMT responses to the observed and coded parent-centered and child-centered mealtime behaviors, the researchers concluded that the MCMT reliably measures parent-centered and child-centered behaviors. Designing optimal coding schemes in The Observer XT In the Noldus Webinar 'Behavioral Coding - Designing optimal coding schemes in The Observer XT', we will show you how to create coding schemes that allow you to reach your behavioral endpoints but, at the same time, are clear enough for efficient and reliable coding. Interested? Watch the webinar on-demand at your convenience! References - Dael, N.; Mortillaro, M. & Scherer, K.R. (2012). The Body Action and Posture Coding System (BAP): Development and Reliability. J Nonverbal Behav, 36, 97–121. https://doi.org/10.1007/s10919-012-0130-0 - Ekman, P.; Friesen, W. V.; Hager, J. C. (2002). Facial action coding system: The manual on CD-ROM. Instructor’s Guide. Salt Lake City: Network Information Research Co. - Fowler, F. J., Jr., & Cannell, C. F. (1996). Using behavioral coding to identify cognitive problems with survey questions. In N. Schwarz & S. Sudman (Eds.), Answering questions: Methodology for determining cognitive and communicative processes in survey research, 15–36. Jossey-Bass/Wiley. - Kipp, M.; Neff, M. & Albrecht, I. (2007). An annotation scheme for conversational gestures: how to economically capture timing and form. Lang Resources & Evaluation, 41, 325–339. https://doi.org/10.1007/s10579-007-9053-5 - Ontai, L.L.; Sutter, C.; Sitnick, S.; Shilts, M.K. & Townsend, M.S. (2019). My Child at mealtime parent self-assessment of food related behaviors: Validation with mealtime behaviors. Appetite, 136, 62-69. https://doi.org/10.1016/j.appet.2019.01.016 - https://www.coursera.org/lecture/questionnaire-design/behavior-coding-7Tgyt - Webinar: Nonverbal behavioral Coding for Researchers: https://www.youtube.com/watch?v=4BcOOWcttzY --- ## Surprising the senses: how unexpected flavors reveal consumer emotions URL: https://noldus.com/blog/surprising-the-senses-how-unexpected-flavors-reveal-consumer-emotions Published: 2025-07-24 13:32:21 Description: What happens when your brain expects something sweet, but your mouth gets savory? Researcher Artur Głuchowski used this twist to uncover how we emotionally react to unexpected food. When Artur Głuchowski arrived in Wageningen for a two-week research sprint, he wasn't just thinking about food, he was thinking about how food makes us feel, and more importantly, how we show it. As a researcher at the Department of Food Gastronomy and Food Hygiene at the Warsaw University of Life Sciences in Poland, Artur specializes in modern dishes and consumer responses. His latest study, conducted as part of the COMFOCUS project, looked into how consumers react emotionally when they taste something unexpected. And he had a clever way to make that happen. Challenge consumers with unexpected flavors During the COMFOCUS project, his research focused on evaluating the "surprise effect" among Dutch consumers. He designed an experiment built around surprise. Six snacks, arranged in three identical-looking pairs, were created to visually trick the consumer. Each pair consisted of one sweet and one savory version: a delightful (or disorienting) mismatch between appearance and flavor. For instance, one cream puff was filled with coconut cream, the other with salmon. In the mousse category, one sample was a sweet pistachio, the other horseradish. He also served tarts: one contained lemon cream, while the other held hummus. All of them looked the same. "The idea was to challenge consumers with unexpected flavors," Artur explained. "I wanted to see how people respond, not just what they say, but what their body tells us." Using NoldusHub for consumer behavior research To measure implicit reactions, he used NoldusHub, a centralized platform that allowed him to record physiological and behavioral responses during the tasting session. Consumers also filled out paper questionnaires using standard harmonized scales and emotion-related metrics. His goal: to compare these explicit responses with the implicit measures obtained by using NoldusHub. NOLDUSHUB Simplify your multimodal research Discover how NoldusHub benefits your behavior research, and why it is the best multimodal platform for you to use: - Integrated data collection - Synchronization from the start - Immediate feedback on data quality Learn more Integrated facial expression analysis Artur used the integrated facial expression analysis from FaceReader to track micro-expressions: the quick, involuntary reactions that can reveal how we truly feel. He also measured arousal using galvanic skin response and monitored visual attention via eye tracking. All of this was done live, with participants guided by video content on a screen. Emotional responses to unexpected flavors The results were as varied as the snacks themselves. Some participants were clearly shocked by the flavor they experienced, especially when it clashed with what they were expecting. These reactions were captured vividly through facial expressions. Others were more easy-going with new flavors. To explore this further, Artur included the Food Neophobia Scale, a tool that helps identify a person's comfort level with trying new foods. Comparing this with physiological data might offer deeper insights into how novelty influences emotional response. How technology has supported his research "It's incredibly helpful. With FaceReader, I get quantifiable data on facial expressions, which helps detect even the smallest reactions — things that might go unnoticed in traditional surveys or verbal feedback." Unlike self-reported methods where people might not be fully honest or aware of their feelings, FaceReader captures real-time, involuntary reactions. This is what makes it such a powerful tool. "FaceReader is amazing," Artur said. "You can't lie to it. When you're consuming something and reacting in real-time, your face reveals things that words can't." Extensive data collection: much easier with NoldusHub Behind the scenes, managing all this data was no small task. During an intense two-week period in Wageningen, Artur conducted the study with 50 participants and collected a large amount of data that he was still processing when we spoke to him. But the integrated setup of NoldusHub made the process smoother. Rather than juggling separate systems and manually syncing data, he had everything he needed in one dashboard. "You can see the signals in real-time. If something isn't working, you can repeat the measurement right away. It really helps with data quality," he said. "Back home, I usually have to work with separate software and devices for each type of measurement. But with NoldusHub, everything is integrated. I can preview recordings live, check the signal quality, and take immediate action if something goes wrong — all from a single dashboard. That kind of streamlined setup makes the whole process much more efficient." Consumer research continues Though his time in Wageningen was brief, the research will continue. Artur is planning to replicate the study in Poland, using his own equipment: FaceReader, an eye tracker, and hopefully, a data acquisition device for additional biometric data. Reflecting on the project, Artur said it was a very intense period in his career. "Using NoldusHub helped me a lot. You're not just relying on what consumers say, you can see their reactions and observe how they feel." For behavioral researchers interested in capturing the authentic emotional experience of consumers, Artur's work is a great case for integrating tools like NoldusHub into experimental design. Because sometimes, the face says more than the words ever could. About COMFOCUS Across Europe, researchers are working together to better understand consumer behavior and food choices. In the COMFOCUS project, early-career scientists explored surprising new questions. Project partners The COMFOCUS project is led by Wageningen University and has 14 other partners, including Noldus. Noldus will develop innovative new technologies for the objective measurement of the experience of food consumers. During the project NoldusHub was developed and used by researchers for integrating, synchronizing and carrying out advanced analysis of a range of sensor data streams. --- ## Left on read - how social rejection rewires the teenage brain URL: https://noldus.com/blog/left-on-read-how-social-rejection-rewires-the-teenage-brain Published: 2025-07-04 14:00:00 Description: A recent study combined behavioral tracking with immunohistochemistry to research how a developing brain processes social exclusion. Keep reading to find out how EthoVision XT enables anxiety research. Being ignored by peers affects us more profoundly than many realize. A recent study combining EthoVision XT for behavioral tracking with immunohistochemistry shows that the adolescent brain processes social exclusion in much the same way it processes physical pain. This combination of advanced tools reveals how experiences like ghosting can trigger emotional behaviors such as anxiety in adolescent rats. These insights could shed new light on the growing rates of anxiety among today's teens. The neuroscience of rejection Social rejection, the distressing feeling that follows exclusion, leaves a lasting impact. Teens today often describe the pain of being "left on read" or removed from group chats. These modern experiences are magnified by constant connectivity. Importantly, they align with emerging evidence indicating that social exclusion activates the same neural pathways that register physical pain. For adolescents who are especially motivated to gain acceptance from their peers, the effects can be particularly intense. Statistics further illustrate this challenge. On average, teens now spend nearly five hours per day on social media, where exclusion can happen with just a tap. During the past 20 years, global anxiety rates in adolescents have risen by over 50%, and nearly one in three teens meet clinical criteria for an anxiety disorder. While researchers are still working to establish clear causal relationships, this parallel rise in digital socialization and mental health concerns highlights the need for further study. FREE E-BOOK Basic behavioral neuroscience in rodents Want to know more about anxiety testing and other aspects of rodent research? Then, download our free e-book. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Submit to download A preclinical model to study exclusion To investigate these effects in a controlled setting, Byun and Noh (2024) designed an experiment using adolescent rats. EthoVision XT allowed them to track behavior precisely and link those behaviors to changes in brain activity. Their findings help explain why rejection feels so overwhelming. Modeling exclusion in adolescent rats The researchers worked with young male Sprague-Dawley rats (4 to 5 weeks old). This developmental stage is comparable to early adolescence in humans when social interactions start to gain emotional significance. Two experimental conditions were created: - Non-exclusion group: Rats engaged in continuous social play. - Exclusion group: Rats initially participated in social play, but were later separated behind transparent partitions. From this position, they could watch but not join in. This approach created a model for observing the biological and behavioral effects of social exclusion. EthoVision XT Reveals the Impact of Rejection EthoVision XT's automated video tracking provided detailed observations of how exclusion shaped behavior and anxiety. Elevated plus maze In this well-established test for anxiety-like behavior, excluded rats behaved differently: - They spent half as much time exploring open arms, avoiding risk. - They took up to three times longer to enter exposed areas. This pattern mirrors the cautious behavior often seen in socially anxious adolescents. Play arena observations A unique paradox appeared in the play arena: - Excluded rats approached peers 50% less often, showing social withdrawal. - At the same time, they lingered near the transparent barriers, remaining close enough to watch others play but not participate. - Energetic social play decreased by 40%, replaced by less movement overall. This combination of withdrawal and longing reflects the complex tension in socially anxious individuals who desire connection but fear rejection. Neural changes related to behavior Immunohistochemistry revealed measurable brain changes: - The lateral habenula, a center that processes pain, showed increased activity. - The dentate gyrus of the hippocampus, important for memory, showed decreased activity. - No significant changes were observed in the medial prefrontal cortex, amygdala, or striatum, suggesting that the first vulnerabilities occur in the LHb and DG. Key findings: Exclusion changes the brain and behavior This research demonstrates three main effects of social exclusion: - 1. Persistant anxiety – Even in isolation, excluded rats avoided risk and showed anxiety-like behavior. - 2. Craving connection while withdrawing – Rats spent more time observing peers from a distance, highlighting the paradoxical desire to connect coupled with avoidance. - 3. Neurological overlap with physical pain – The overactivation of the LHb supports the idea that social rejection activates pathways similar to those engaged by physical pain. Why rejection feels so painful This study underscores a powerful truth: during adolescence, social rejection activates brain circuits that process physical pain. By leveraging EthoVision XT's accurate behavioral tracking, researchers were able to link social exclusion to concrete neurological changes and emotional behaviors. These findings also point to a critical window of opportunity. Adolescence is a time of heightened neural plasticity, making the brain more responsive both to harm and to intervention. Early support, whether through mindfulness, cognitive behavioral therapy, or building protective routines, may help recalibrate these circuits. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial --- ## Scientific methods in human behavior research URL: https://noldus.com/blog/scientific-methods-in-human-behavior-research Published: 2025-06-05 15:00:00 Description: Learn about the key scientific methods used in human behavior research. We explain quantitative and qualitative approaches, experimental design, and how researchers collect and analyze behavioral data. Studying human behavior requires structured and reliable methods to ensure accuracy and credibility. Researchers rely on scientific methods to collect, analyze, and interpret data about thoughts, emotions, and actions. These methods help minimize bias, validate findings, and contribute to a broader knowledge base. Scientific methods in human behavior research Scientific methods provide a systematic way to observe, measure, and analyze behavior. Without structured methodologies, research findings may lack reliability or fail to apply beyond specific contexts. Objectivity is essential, as minimizing personal biases allows researchers to interpret trends, insights, and data accurately. Replicability ensures that studies can be repeated with consistent results, while falsifiability allows hypotheses to be tested and potentially disproven. Ethical considerations also play a crucial role, ensuring the safety and privacy of participants and maintaining research integrity. Quantitative and qualitative approaches Scientific methods in human behavior research fall into two primary categories: quantitative and qualitative approaches. Each method serves a specific purpose, depending on the type of data needed and the research questions being addressed. This article explains the fundamental scientific methods, their applications, and how they shape behavioral research. By following these principles, researchers generate insights that contribute to psychology, sociology, neuroscience, and other related fields. Quantitative methods Quantitative research is built on numbers, measuring human behavior through statistical data collection and analysis. Researchers use these methods to identify patterns, correlations, and causal relationships. Experimental research Experimental research is one of the most controlled and structured methods for studying behavior. It involves deliberately manipulating one variable to observe its effect on another while keeping all other factors constant. How would this work? An example: A psychologist studying the effects of sleep deprivation on cognitive performance might divide participants into two groups: one sleeping eight hours a night and another restricted to four hours. By comparing their performance on memory and problem-solving tasks, the researcher can determine the impact of sleep on cognition. To ensure reliability, experiments often use randomization, assigning participants to different groups by chance. Control and experimental groups allow researchers to compare data under different conditions, making it possible to establish cause-and-effect relationships. Survey research Survey research is one of the most widely used methods in human behavior research because it allows for the collection of large amounts of data efficiently. Researchers use surveys to ask individuals about their thoughts, attitudes, behaviors, and experiences, often through structured questionnaires or interviews. Surveys come in different formats. Cross-sectional surveys provide a snapshot of data at a single point in time. For example, a researcher investigating job satisfaction might distribute a questionnaire to employees across various industries and analyze their responses to identify trends. In contrast, longitudinal surveys track changes over time, collecting repeated data from the same group of individuals. This method is particularly useful for studying behavioral development, such as how social media usage affects mental health over several years. Descriptive surveys focus on gathering specific characteristics of a population. A researcher for instance might conduct a demographic survey to understand the age distribution and educational background of a city's residents. The US census is an example of a descriptive survey, as it collects detailed information about the American population, such as age, gender, race, housing, and employment. Rather than analyzing relationships between variables, the Census provides a comprehensive snapshot of demographic characteristics at a specific point in time. Analytical surveys go a step further by seeking relationships between variables, such as investigating the link between exercise frequency and stress levels. Observational research Observational research involves studying behavior in its natural or structured environment without interference. Researchers use this method when they want to understand how individuals act in real-life settings. Naturalistic observation takes place in everyday environments, where researchers unobtrusively monitor behavior. For instance, a psychologist might observe how children interact in a playground to study social development. Since participants are unaware of the study, their behavior remains authentic. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Play Lab: naturalistic observations in a playground This is exactly what happens at the Fisher-Price Play Lab, where children are treated as the real experts. Located in East Aurora, New York, the Play Lab is an observational research facility where new toys are developed with the help of child development research and testing. When observing children, and looking at how they play with toys, it's important that they're able to use the toy and they're able to have fun with it. But that it also challenges them so that they're able to reach a new milestone and grow to the next level. They used Noldus' Viso to record the interactions the children have with the toys, while coding behavior with The Observer® XT really laid out their findings. Want to learn more? Take a look inside the lab! Structured observation, on the other hand, takes place in a controlled setting where researchers create specific conditions to study behavior. An example would be placing participants in a simulated workplace environment to assess teamwork dynamics. Because researchers set the conditions, structured observation ensures that all participants experience the same scenario, making comparisons more reliable. Longitudinal and cross-sectional studies Longitudinal studies are invaluable for understanding how behavior changes over time. Researchers collect data from the same participants repeatedly over months or years. For example, a study on cognitive decline might test the memory performance of a group of adults every five years to track changes as they age. These studies provide deep insights into behavioral trends and developmental processes but require significant time and resources. Cross-sectional studies, by contrast, compare different groups at a single point in time. Instead of following the same individuals over the years, researchers might study multiple age groups at once to examine generational differences in technology use. Although these studies offer quicker results than longitudinal research, they do not account for individual changes over time. Qualitative methods Qualitative research seeks to capture the richness of human experience, focusing on descriptions, themes, and interpretations rather than numerical data. Case studies Case studies provide an in-depth analysis of a single individual, group, or situation. These studies are common in clinical psychology and are often used to explore rare conditions. A psychologist might document the experiences of a person who has recovered from a traumatic brain injury, analyzing their cognitive and emotional changes over time. Case studies allow for detailed investigation but may not always generalize to the wider population. Ethographic research Ethnographic research immerses the researcher in a particular community or culture to study behaviors and interactions firsthand. By participating in daily life, researchers can gain a deeper appreciation of social norms, communication styles, and shared experiences. Example: An ethnographer studying remote tribal communities might live among them for months, recording observations about their traditions, decision-making processes, and social structures. This approach yields rich, detailed data but requires significant time and cultural sensitivity. Grounded theory Grounded theory is a research method that builds theories based on collected data rather than testing pre-existing hypotheses. Researchers analyze patterns in interviews, field notes, or written texts and refine their theories as new data emerges. For example, a study on workplace motivation might begin with open-ended employee interviews and gradually develop a theory on how leadership styles influence job satisfaction. This iterative process allows researchers to create theories grounded in real-world observations. Content analysis Content analysis is used to examine texts, media, or communication patterns, identifying themes and trends. Researchers often apply this method to social media posts, newspaper articles, advertisements, or historical documents to track shifts in public opinion. For instance, a study analyzing political speeches over decades might identify how language around climate change has evolved. Similarly, researchers might conduct a content analysis of online customer reviews to understand how consumers express satisfaction or dissatisfaction with a product or service. This type of research can reveal patterns in consumer behavior, expectations, and preferences. By categorizing and coding content, researchers uncover patterns that provide valuable insights into societal attitudes and individual emotional expressions. Combining methods: mixed-methods research Mixed-methods research integrates both quantitative and qualitative approaches, offering a more comprehensive understanding of human behavior. By combining statistical analysis with in-depth insights, researchers can validate findings from one method with another. One example is a study on workplace satisfaction might begin with a large-scale survey to identify trends, followed by one-on-one interviews to explore employees' personal experiences in greater depth. This approach provides a well-rounded perspective, bridging the strengths of both research traditions. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download Challenges and ethical considerations in behavioral research Behavioral research requires ethical considerations to protect participants and ensure data integrity. Informed consent ensures that individuals understand the study's purpose before agreeing to participate. However, historical studies such as the Stanford Prison Experiment and the Milgram obedience experiments highlight instances where participants were unaware of the true purpose of the research. These studies, while providing significant insights into human behavior, raised serious ethical concerns about deception, emotional distress, and the need for stricter research guidelines. Today, ethical standards require full transparency and prioritize the well-being of participants to prevent similar issues. Confidentiality safeguards personal data, while efforts to reduce bias help maintain objective and accurate findings. Additionally, researchers face challenges in replicating studies, a critical issue in ensuring the reliability of behavioral science. The value of scientific methods in behavioral research Scientific methods provide structured ways to study human behavior, offering insights that shape our understanding of thoughts, emotions, and actions. Whether through controlled experiments, in-depth interviews, or observational studies, each method plays a crucial role in advancing behavioral research. Today, modern technology plays a key role in supporting these efforts. Behavioral research software and hardware tools from companies like Noldus help researchers collect and analyze data with greater precision and efficiency. Solutions like observational coding software, data integration platforms, and video analysis systems, support both qualitative and quantitative research, allowing scientists to capture detailed behavioral patterns and identify key behaviors and trends. With the right combination of scientific methods and innovative tools, researchers can continue to push the boundaries of our understanding of human behavior. By choosing the right approach, researchers can produce meaningful, reliable, and ethical findings that contribute to psychology, sociology, and related fields. --- ## Rethinking skills training: less instruction, more action URL: https://noldus.com/blog/rethinking-skills-training-less-instruction-more-action Published: 2025-05-21 12:05:39 Description: Can students learn nursing skills like bandaging just as well with fewer instructions? A recent study says yes. Using classrooms equipped with the Noldus Viso system, researchers compared two teaching approaches. In the calm and controlled environment of the classroom, clinical skills can seem simple. But everything shifts in real-life settings—where pressure mounts, patients are unpredictable, and multitasking is the norm. That contrast is exactly what a group of researchers set out to explore: can nursing students still apply their skills when it truly matters? What they discovered may challenge the way you approach teaching. Their results also reveal why rigid, step-by-step protocols might not be the most effective path to real-world readiness. Focusing on outcomes instead of checklists In many nursing programs, students are taught clinical skills through detailed, structured protocols. For example, a skill like bandaging. Think multiple pages of instructions, followed by demonstrations and lots of repetition. This is what experts call explicit learning: you consciously learn each step. But what if students could learn just as well—or even better—without memorizing all the details? Enter implicit learning. It's when students pick up skills without thinking through every motion. Instead of remembering 12 steps, they focus on the outcome: wrapping the leg so the bandage stays in place, feels comfortable, and doesn't cause pain. Think of it like riding a bike—you don't recite instructions; you just do it. The research: bandaging with less instruction In the Netherlands, researchers ran three experiments to test a simple idea: can less really be more? They randomly split nursing students into two groups: - 1. One group received detailed, explicit instructions—the kind you'd typically find in a training manual. - 2. The other group got an instruction card with just the essentials and practiced based on that minimal guidance. All students practiced wrapping a bandage around a peer's lower leg. They first pulled on a soft, stretchy sleeve to protect the skin, then added padding around bony areas, like the ankle, to prevent pressure spots. Finally, they wrapped two layers of bandage to apply gentle, even pressure. The bandage needed to stay in place, feel comfortable, and allow the leg to move freely, without causing any discomfort. A smart way to observe skills in action The classroom was equipped with cameras connected to the Viso system—a multi-camera setup that recorded the practice sessions for detailed review and analysis. For educators, Viso offers a powerful way to observe behavior, spot mistakes, and see how students improve over time—all without disrupting the flow of training. Here's what surprised the researchers: students who practiced with minimal instructions performed just as well as those with full protocols. In fact, in situations where they had to multitask (like communicate with the patient and perform the task at the same time), the minimally instructed group performed more consistently. Want to see how you can setup a space for practice sessions? Explore the story of AIXTRA - Competence center for training and patient safety - which has multiple simulation rooms, comprehensive debriefing spaces, and a dedicated control room equipped with Viso, all designed to create a realistic learning environment. Why performance consistency matters If you're an educator or trainer, switching to minimal instructions is a game-changer. Here's what it means: - You don't always need a detailed script. Students can learn effectively with simpler guidance. - Less instruction frees up cognitive space. When students aren't focused on remembering steps, they can concentrate on adapting to the patient, thinking critically, or communicating clearly. - You save time and increase practice opportunities. Students using minimal instructions spend less time reading and more time doing. And when you're using a tool like Viso, you can capture these subtle improvements on video. This helps you reflect, assess, and fine-tune your teaching approach without hovering over every student. Student feedback highlights learning outcomes Here's something else the study uncovered: students in the explicit learning group remembered more rules about how to bandage—but that didn't make them better at doing it. In real-life scenarios, being able to act smoothly and adapt matters more than being able to recite instructions. What's more, many of the students using the full protocol started ignoring the instructions by the second attempt. That's a red flag—too much information can overwhelm, especially for beginners. How to bring implicit learning into your classroom If you're ready to experiment with implicit learning, here's how to get started: - Simplify your materials – Strip your instructions down to the essentials. Focus on the goal, not the steps. - Use analogies and visual cues – A metaphor like "wrap the leg like a smooth tube" gives students a clear mental image without a list of tasks. - Encourage self-assessment – Ask students, "Did the toes stay pink? Is the bandage slipping?" That shifts the focus from following steps to evaluating outcomes. - Record and review – Tools like Viso let you and your students watch performances later, spot patterns, and make adjustments without the pressure of real-time feedback. - Build in time for reflection – After practice, let students talk through what felt right or difficult. Reflection helps solidify learning, especially when instruction is minimal and experience is the main teacher. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download Change takes practice Switching from step-by-step teaching to a more intuitive, learner-driven approach takes time. That's why the researchers noticed bigger improvements in the second year, when both teachers and students had gotten used to the new method. But the payoff is worth it: more confident students, better performance under pressure, and a smoother transition from the classroom to clinical practice. References Van Brakel-Van Lobenstein, N.; Van Leeuwen-Prins, S.T.; Verdoes, L. et al. (2025). Teaching nursing skills without detailed protocols: effects of an implicit learning strategy in nursing education. Advances in Health Science Education. https://doi.org/10.1007/s10459-025-10421-y --- ## The lonely brain: is resilience biologically encoded? URL: https://noldus.com/blog/the-lonely-brain-is-resilience-biologically-encoded Published: 2025-05-15 14:00:00 Description: Social isolation causes depression to some, but not to everyone. With the use of EthoVision XT, researchers were able to research the biological processes underlying depression. Read this blog to learn more about their insights. Emerging research reveals why social isolation devastates some individuals, yet leaves others unaffected, suggesting that resilience may be encoded in our biology. With the use of advanced behavioral tracking alongside trace element analysis in the brain, researchers have uncovered striking differences between how Sprague-Dawley and Wistar rats cope with loneliness. Could these biological differences lead to insights into the causes of resilience and vulnerability to stress? How social isolation rewires the brain and reveals resilience Social isolation during the COVID-19 pandemic led to unprecedented levels of loneliness, with studies suggesting that nearly 70% of people experienced significant distress. Although loneliness is often downplayed, social connections are fundamentally critical to human wellbeing. Indeed, social isolation can significantly disrupt neural pathways altering how our brain functions, influencing stress responses and impairing learning and memory. These disruptions have a profound impact on both physical and mental health, increasing the risk of dementia, stroke, depression, anxiety, cardiovascular disease, and even premature death. New research suggests that the underlying mechanisms underpinning these changes include reduced connectivity between the prefrontal cortex and amygdala, as well as dysregulated cortisol cycles. However, the impact of isolation varies widely between individuals, with many showing remarkable resilience. This raises an intriguing question: Are there biological factors that explain this resilience? To explore this, Zilkha et al. (2024) used EthoVision XT to compare the behavioral responses to social isolation in Sprague-Dawley (SD) and Wistar rats in a Morris Water Maze and forced swim test. Their findings revealed intriguing correlations between genetic factors, trace element profiles in the brain, and resilience to stress, and provide important insights into the neurobiology underlying resilience. Strain-specific responses to isolation In this study, researchers investigated how 4 weeks of isolation differentially impacted middle-aged (14-month-old) rat strains: - SD rats: Known for cognitive agility but high sensitivity to stress - Wistar rats: Typically more anxious but potentially more resilient to isolation-dependent stress SD and Wistar rats are genetically diverse, displaying inherent differences in behavior, stress reactivity, and susceptibility to neurological and physiological disorders. These genetic differences are critical for helping researchers to understand how biological differences can influence an individual's capacity to cope with stress. All rats were housed in controlled and enriched conditions. Isolated rats were housed individually whereas control rats were housed in small groups of 3 to 4. Following the isolation period, behavioral tests including the Morris Water Maze and Porsolt Forced Swim Test were conducted, and cortical tissues were analyzed by ICP-MS to assess changes in trace elements. How automated tools reveal the impact of isolation on depression Quantifying stress responses with EthoVision XT In this study, researchers used EthoVision XT to track the impact of social isolation in the different rat strains: Morris water maze: - All rats showed intact learning and memory, regardless of isolation or strain. - Isolated SD rats swam further distances and at faster speeds compared to isolated Wistar rats and control, non-isolated SD rats​​. Here, the authors suggest that increased swimming speed and distance may reflect anxiety-induced hyperactivity or disorganized search strategies linked to heightened stress. - Wistar rats showed no differences in Morris Water Maze performance despite isolation, suggesting resilience to isolation stress. Porsolt forced swim test: - Isolated SD rats spent a significantly longer time immobile (floating) over a 5-minute period, compared with control SD rats, an indicator of depression. - Wistar rats showed significantly more immobility at baseline compared to SD rats, suggesting higher innate anxiety. However, isolation again had little impact on the Wistar's behavior, suggesting resilience to stress associated with social isolation. These results highlight the ability of EthoVision XT's automated tracking to detect strain-specific differences in response to social isolation and stress. By preventing human bias, and capturing subtle variations in behavior, EthoVision XT enabled researchers to observe distinct behavioral phenotypes across genetic backgrounds. FREE TRIAL Experience EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A time and cost-effective solution - Powerful data selection - Gold standard in automated video tracking Try it out for free! Key findings: Isolation triggers depression in susceptible rats This study reveals profound insights for the behavioral and biochemical profiles associated with stress, depression, and resilience: Learning and memory: - Neither strain showed impaired learning and memory due to isolation. Behavioral stress response: - Isolated SD rats performed navigation tasks less efficiently compared to non-isolated control SD rats and both Wistar rat groups. - Socially isolated Wistar rats showed no significant changes, suggesting resilience to social isolation stress. Depression and anxiety: - SD rats showed increased immobility in swim tasks after isolation, consistent with depression. - Wistar rats displayed high immobility compared with SD rats, a sign of innate anxiety, but appeared resilient to isolation. Trace elements in the brain: - Isolated SD rats had elevated cortical cobalt and copper levels and reduced cesium, highlighting a possible biochemical basis for the heightened stress response. - In Wistar rats, lower Zinc levels were suggested to be correlated with higher baseline anxiety. These findings reveal that resilience to social isolation is not only dependent on genetics and environmental interactions, but in fact has a measurable biological component. Understanding the biology of resilience The findings in this study demonstrate that by combining behavioral tracking with detailed trace element analysis researchers were able to explore the biological basis of resilience. The distinct trace element profiles observed in the isolation-resilient Wistar strain versus the stress-vulnerable SD strain, suggests that both genetics and environment may interact, influencing our biochemistry and responses to stress. By using a combination of behavioral analysis alongside neurochemical profiling, researchers can not only objectively measure stress responses but can reveal novel strategies for improving mental health. From identifying trace element biomarkers of resilience, to developing targeted dietary and therapeutic interventions, these results provide exciting possibilities for future research. FREE E-BOOK CHAPTER Depression in rodents Want to know more about how to do depression testing and other aspects of rodent research? Then, instantly download this free chapter. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these click to download References Yavuz, M. et al. (2024). Relationships between trace elements and cognitive and depressive behaviors in sprague dawley and wistar albino rats. Front. Pharmacol. 15, 1367469 https://doi.org/10.3389/fphar.2024.1367469 --- ## From observation to insight URL: https://noldus.com/blog/from-observation-to-insight Published: 2025-05-06 10:57:24 Description: Across research, education, and product development, labs need tools to capture and understand human behavior with precision. This blog shows how combining Viso and The Observer XT empowers teams to gain richer insights and make data-driven decisions. In behavioral research, two things are essential: capturing what really happens and making sense of it. That means having the ability to record behavior accurately and analyze it meaningfully. How labs combine Viso and The Observer XT for smarter behavioral research To do this, many labs rely on a video capture system that records high-quality footage from multiple angles, even across several rooms or observation setups. These systems are designed to be unobtrusive, so participants behave naturally—whether they're children at play, students in a classroom, or patients in a therapy session. One such solution is Viso, which gives researchers full control over recordings, camera angles, and session management in real time. But capturing the footage is only part of the story. Once the video is recorded, researchers need a way to code behaviors, track events, and analyze patterns over time. That's where a behavioral coding and analysis platform comes in. Tools like The Observer XT let researchers annotate behaviors, synchronize video with other data sources—like eye tracking, physiological responses, or facial expressions—and visualize trends. It's a powerful way to turn complex behavior into clear, actionable data. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Streamlined research, deeper analysis When combined, these tools create a synchronized workflow: you can control recordings directly from your analysis environment, instantly align all data streams, and focus on drawing insights—without wasting time on technical setup or file syncing. Real-world applications: How labs are using the combo Learning through play at the Fisher-Price Play Lab Designing toys that are fun, safe, and support child development is both an art and a science. At the Fisher-Price Play Lab in East Aurora, NY, researchers observe how young children interact with toys to make sure every product meets those goals. To do this, they use Viso to unobtrusively record natural play sessions. The footage reveals how children engage, explore, and problem-solve with different toy designs. Using The Observer XT, the team then codes these behaviors—tracking everything from motor skills and attention span to social interaction and emotional response. As Dr. Corinne Eggleston shares, "It's very important to us to be able to measure behavior and to really feel confident in the decision that we're making when it comes to creating toys for young children." This research-backed approach helps Fisher-Price design toys that are not only entertaining but also promote learning and development—ensuring every product has a purpose beyond play. Business meets behavior at Hofstra University At Hofstra University's Behavioral Research in Business Laboratory, data-driven insights are the foundation for smarter marketing, branding, and business strategies. This state-of-the-art facility is built to explore how people think, react, and decide. Equipped with multiple observation and behavioral rooms, the lab uses Viso to capture multi-camera video and audio during live studies. Participants engage in product testing, make financial decisions, or respond to ads—while every moment is recorded without disrupting the natural flow. Then, with The Observer XT, researchers dive into the footage, coding behaviors and identifying patterns that would otherwise go unnoticed. This analysis reveals not just what people do, but why they do it—translating raw behavior into usable business intelligence. As Dr. Anil Mathur, the lab's director, puts it: "We designed this lab for the future—with tools that let us observe, measure, and truly understand human behavior in a business context." Different labs, shared success From children discovering the world through play, to consumers navigating choices—behavioral insights power progress across every field. The labs at Fisher-Price and Hofstra University may focus on different subjects, but they share a common foundation: a need for accurate observation and meaningful analysis. Why integrate Viso and The Observer XT? By combining Viso and The Observer XT, these teams turn everyday interactions into rich, structured data that drives smarter design, more effective strategies, and deeper understanding. Whether you're developing a product or refining business decisions, this integrated approach helps you capture what matters—and act on it with confidence. Here's what the integration makes possible: 🖼️A full picture, not just pieces Video alone can tell a story, but when paired with behavioral data, that story becomes crystal clear. With this setup, you don't just see what happened—you understand why it matters. Capture behavior from multiple angles, add audio, sync physiological or biometric data, and get a truly comprehensive view of human interaction. 📊Confidence in your data You can't afford to miss a key moment or wonder if two data sources align. By controlling video directly from your analysis software, every recorded second is automatically synced to your coding and observations. That means more reliable insights, fewer errors, and results you can defend with confidence—whether you're publishing, presenting, or making decisions that affect real lives. 🔧Adaptable for any lab Whether you're in education, healthcare, psychology, business, or product testing, this setup adapts to your needs. Use it for a single room or a multi-site setup. Analyze micro-behaviors in therapy sessions or reactions in a usability test. However you work, it helps you do it better—with less friction and more focus. Say goodbye to juggling tools, manually aligning video files, or double-checking timestamps. This integration removes the repetitive, frustrating parts of your workflow, so you can spend more time thinking, interpreting, and making progress—not fixing tech. FREE WHITE PAPER How does AV recording tool Viso work? Discover how Viso can transform your work—download the free white paper to explore its features and security. - How can Viso benefit your work? - What can you expect of the Viso features? - Is data protection guaranteed within Viso? Start downloading Integrating Viso and The Observer XT transforms the way behavioral research is conducted, providing a robust framework for capturing and analyzing complex behaviors. How could this integrated approach enhance your research? --- ## FAQ: Getting started with PhenoTyper URL: https://noldus.com/blog/faq-getting-started-with-phenotyper Published: 2025-04-29 15:00:00 Description: What is the best lighting for my experiment? How do I clean my system? Can I use any bedding for my set up? These are all valid questions when you are starting out with PhenoTyper. In this blog we will cover some of the most asked questions. PhenoTyper is the ideal environment for a plethora of behavioral tests. Setting up your system in the proper way is crucial for obtaining the highest quality data. To help you out we have outlined the questions we most often receive from customers. After you read this blog, you have a better understanding of the day-to-day usage of PhenoTyper. If you have any additional questions, feel free to ask a question here. 1) How do I correctly set up my lighting? To get the best data from your experiment you need to have the correct lighting. Lighting has a big impact on both your data quality and your animals' behavior. Rodents are nocturnal, therefore they're more active in the dark. So, if the lighting in your cage is too bright or uneven, it can stress your animals and lead to unreliable data. It can also interfere with EthoVision XT's tracking accuracy, especially if there are shadows or glare in the cage. Here is what to keep in mind: - Use consistent lighting across the entire cage - Keep light intensity below 350 lux (and below 60 lux for albino rodents) - Avoid sudden light flashes or changes that could startle your animals Luckily, PhenoTyper 2 has built-in lighting for each cage. This makes it trivial to have a constant environment across all cages. Furthermore, with EthoVision XT you can program the day/night cycle to fit seamlessly with your experimental design. No timers or manual switching are needed, making sure your animals are undisturbed all the while you are saving time by automating your experiment. And thanks to the infrared camera, you can even track your animals in complete darkness. This is ideal for observing natural nighttime behavior. Because of their natural nocturnal cycle, observing behaviors during the night period can result in more relevant data. 2) What bedding should I use? When you're running longer-term studies, it's a good idea to add bedding and nesting material to your PhenoTyper setup. This helps maintain a clean environment and supports more natural behavior in your animals. However, the type of bedding you choose can directly impact how well you can track your animals. The key is to make sure there's enough contrast between the animal and the cage floor so that EthoVision XT can accurately detect and follow movement. Here's what we recommend based on what we've tested in-house: - For dark-colored rodents (black or brown): Use light-colored wood chips on a white PhenoTyper floor. This combination creates strong visual contrast with the animal's fur. We've had good results using 5x5x1 mm wood chips from ABEDD® – LAB & VET Service GmbH. - For white rodents: You'll need a darker background, which can be trickier with bedding. One solution that works well is using Paperchip pellets from LBS Biotech. Under infrared lighting, these pellets appear dark, allowing white mice to stand out during tracking. If you decide to try a different bedding or nesting material, just make sure it doesn't interfere with tracking. The most important thing is maintaining clear contrast between the surface and the animal for consistent detection. 3) How do I clean my PhenoTyper? If you decide to try a different bedding or nesting material, just make sure it doesn't interfere with tracking. The most important thing is maintaining clear contrast between the surface and the animal for consistent detection. - Use gentle cleaners. Clean the cage walls and bottom with water and mild soap, or alcohol-free wipes if the material is sensitive. Always dry all surfaces completely to prevent interference with tracking. Do not use autoclaves to sterilize or clean the cage walls or any component. - Follow chemical guidelines for deep cleaning. For tests that require more rigorous disinfection, only use the approved chemicals listed in your PhenoTyper reference manual. You can find this document in MyNoldus. - Clean each part separately. Disassemble all components—walls, bottom plate, and add-ons, and clean them individually to maintain hygiene and performance. - Be careful with the top unit. Wipe the top unit, including the camera housing, only with a damp cloth. Avoid any liquids or cleaning agents near the electronics and connectors. - Tip from us. Consider using a second bottom plate. You can prepare it with fresh bedding and swap it in immediately, saving time while the other one is being cleaned. FREE E-BOOK Basic behavioral neuroscience in rodents Want to know more about homecage testing and other aspects of rodent research? Then, download our free e-book. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these behaviors Start reading auto_stories 4) Where can I learn more about using PhenoTyper? We hope this guide has helped you get started with confidence. If you've made it this far, you're either really into rodent behavior research, or you're looking for a bit more guidance (or both!). Good news: we've got plenty of resources to support you as you continue working with PhenoTyper and EthoVision XT. Here is where to go next: - → Use the built-in templates in EthoVision XT. These include ready-to-use setups for PhenoTyper experiments, helping you start faster and making it easier to share protocols with others in your lab. - → Check out Noldus Academy. Our online training platform walks you through setting up and analyzing experiments in EthoVision XT. It's perfect for onboarding new students or colleagues, and even seasoned users can use it to brush up on best practices. It'll save you time explaining, and help everyone get the most out of the software. You can find it here - → Watch a webinar. We offer a wide selection of in-depth webinars covering all aspects of research in PhenoTyper—from study design to data interpretation. These are a great way to dive deeper into the "why," "what," and "how" of behavior studies. Want a good place to start? Watch this one we picked out just for you. --- ## NIH Grant Writing Series: Insider Tips for Funding Success - Part 2 URL: https://noldus.com/blog/nih-grant-writing-series-insider-tips-for-funding-success-part-2 Published: 2025-04-26 12:00:00 Description: In NIH grant writing, your collaborators can make or break your proposal. Learn how to choose the right team - those who bring expertise, credibility, and real value to your research and your reviewers. In our continuing series, Dr. William Gerin, author of Writing the NIH Grant Proposal: A Step-by-Step Guide, Third Edition (Sage Publishing), gives his expert advice for writing a successful NIH proposal. Writing a NIH proposal: Advice from an expert - Part 2 We are going to talk about how to go about finding people to collaborate with. Finding the right people is crucial to getting funded! And it is not always obvious. Preparation: Finding collaborators Collaborators can help in many ways. They may bring name recognition to the proposal; they will take some of the burden of writing the proposal off your shoulders, and they can help you conduct the study and help you write papers. You may regard publishing your findings as so far in the future you don't need to worry about, but when selecting co-investigators, be thinking ahead about future publications may have an influence on your design – the outcome measures you plan to use, for example. So then, who do I want to invite? You'll need to find people in your area, or related ones, to work with. Collaborators are often necessary to provide expertise that you may not possess, but which the reviewers will expect to see. Thus, you may not be an experienced statistician but, for almost all NIH proposals, you will need to lay out your data analysis plan. For example, let's suppose you are writing a proposal to fund a clinical trial. How many subjects will you need to detect effects? I have written a few proposals for clinical trials; I know my business, but I did not have the skills to compute a sample size, I needed to have a statistician to do the power analyses. Hint: Writing a proposal can strain relationships. One of your criteria for inviting people on to your grant is: Will you be able to work with them once you are funded? Who am I looking for? It is tempting to invite your friends onto the grant, and that is often a good way to select co-investigators, as long as they will be seen by the reviewers as good pick. But you want to evaluate whether a given individual will be your friend by the end of the process! Sometimes, things go south. Beware: Once you have invited someone, and then you find that things have changed such that you no longer need that person, it is very awkward to have to uninvite them. The reviewers want to know if you can carry out the study you have proposed. If you are a new investigator, the reviewers will want to see that you have senior faculty on your team to back you up. It will give them confidence in your ability to competently carry out the procedures necessary to run the grant. These are smart people, and they'll ding you if they see individuals listed as co-Is who are unnecessary, and they'll ding you if they don't see individuals that you will need to serve an important role. In the next chapter, we will continue this discussion, as the picking of collaborators is a vital part of the process, and picking the right ones will help you get funded! Write better proposals Get your free guide here We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to you! Download for free Grant Assistance Program We can provide guidance on developing behavioral protocols, performing behavioral tasks, or making the most out of your Noldus system. Learn more about our Grant Assistance Program. --- ## NIH Grant Writing Series: Insider Tips for Funding Success - Part 1 URL: https://noldus.com/blog/nih-grant-writing-series-insider-tips-for-funding-success-part-1 Published: 2025-04-25 12:00:00 Description: In this series of blog posts, Dr William Gerin will provide advice for writing an excellent, award-winning NIH proposal. Topics include registration, prep, specific aims, formatting, the proposal itself, budgeting, collaborators, and different mechanisms. We are honored to welcome guest contributor, Dr. William Gerin, former Professor of Behavioral Medicine at Penn State University. Dr Gerin is the author of Writing the NIH Grant Proposal: A Step-by-Step Guide, Third Edition (Sage Publishing). Writing a NIH proposal: Advice from an expert - Introduction In this series of blogs I will provide advice for writing an excellent, award-winning NIH proposal. I will give you the benefit of my thirty years as a NIH-funded researcher and, on occasion, NIH reviewer, to help you write a great proposal. And the way to do that is to write an interesting proposal. Tell a story. Show your passion. Every NIH grant is tied to one public health outcome or another; how are you going to address that problem? What is the story behind your proposal? My interest in this topic grew from my experiences at Columbia University, in which I mentored physicians, fresh out of medical school, and, as they work towards their board certifications, are told that if they do not bring in a grant within a couple of years they will be invited to find a new job. So, they need to fill that gap in their education. What to expect Some of the topics covered in this blog series: - Registrations: There are no shortcuts here, you must do the homework. This includes tasks from immersion in the literature to finding out who your reviewers might be. - Specific Aims: This is the first page of your proposal; it is limited to one page, and it must be perfect. What I mean by that is, it must present the entire study you are proposing, the relevant literature, how your research will contribute to the field, what are your hypotheses and specific aims, and how do you plan to go about testing them. - Formatting - The body of the proposal, including the introduction, proposed methodology, statistical and power analysis, and discussion. - The budget - How to pick collaborators and consultants (and the difference) - Different grant mechanisms Should you still apply for NIH funding in the face of proposed cuts and shifting priorities? Yes and now's the perfect time. Learn why early action, strategic language, and persistence could give you a critical edge in the next funding cycle. Will NIH lose its funding? Should I bother to apply for NIH grants? The answer to both questions is yes! You are probably aware that NIH has fallen under the knife, and at this point in time, nobody knows what is going to happen. For the details, put "is NIH funding still frozen" in your web browser. Here is the first point they make: As of April 1st, the NIH funding freeze has been lifted, but the process is still ongoing and some funding opportunities have been closed or updated to align with agency priorities. This is largely good news, and the implication is, submit! NIH will be back up and running, and when it is, all those researchers who didn't bother writing proposals will be caught up short and rushing to write and submit them. There will be less competition, since many will not be prepared. It takes a lot of effort and a lot of time to write a fundable proposal, so you want to get ahead of the curve. Here is the most important detail: NIH is still accepting applications. Write, Write, Write; Submit, Submit, Submit! So, should you apply? Yes, absolutely. I believe (for what it is worth), and so do my colleagues at NIH, that the public outcry will persuade the current administration to withdraw their cuts to NIH, and you want to be ready when they do! Because many others, who ordinarily would have constituted your competition, won't be. Write better proposals Get your free guide here We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to you! Download for free New Language Restrictions One of the new restrictions concerns language that may not be used. The Federal Agency in charge will search on "forbidden words". There are so many I cannot list them here and there are websites that show them. The length of the list (not to mention the content) will astound you. (It astounded me!). Here are just a few: Activism, activists, antiracists, biased, black and latinx community diversity… This is going to present great difficulties to those writing proposals about diversity (for example). Pretty hard to write about a proposed study in the black and latinx community when you are not allowed to say, "black and latinx community"! Some things that are happening are undesirable, but, on the other hand, things may be looking up. So, do not be discouraged! Write and submit applications so that you can test your hypotheses and write papers that will be published in high-impact peer-reviewed journals. And when this happens, your career will benefit! WRITE BETTER PROPOSALS - GET YOUR FREE GUIDE HERE We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to you! Download for free Complimentary grant review to strengthen your proposal To assist you in your upcoming grant applications, we are pleased to offer a complimentary review service to help ensure compliance with evolving guidelines. Our team will carefully assess your proposals, helping to prevent potential obstacles in the review process. Learn more about our Grant Assistance Program. PART 2: Find the right people and fund your research Part 2 of this series is already up. Click here to continue reading! --- ## Tiny plastics, big problems: do nanoplastics affect neurodevelopment? URL: https://noldus.com/blog/tiny-plastics-big-problems-do-nanoplastics-affect-neurodevelopment Published: 2025-04-18 15:00:00 Description: Nanoplastics are everywhere in the news nowadays. But how exactly do they influence our development. Researchers used DanioVision and EthoVision XT to track the development and behavior of exposed zebrafish. Keep reading to see their results The hidden threats of nanoplastics Plastics are everywhere, in our oceans, rivers and even our drinking water, presenting a significant environmental challenge. While the adverse effects of large plastic debris have been heavily researched, the impact of microscopic plastic particles has been widely overlooked. Recent evidence demonstrates that environmental weathering breaks plastics into tiny submicron sized particles, or nanoplastics (less than 100 nm), which accumulate in living organisms over time. Although almost invisible, it is now thought that this accumulation may be problematic. Could these tiny particles be impacting our aquatic systems and posing a risk to human health? To answer this question, Saraceni and colleagues (2025) conducted a series of zebrafish experiments using the DanioVision observation chamber and EthoVision XT, to investigate the relationship between nanoplastics and neurodevelopmental toxicity. Zebrafish are considered an excellent model for understanding how environmental nanoplastics could affect human development, due to similarities in physiological pathways, genetic conservation and stress hormone regulation processes. Nanoplastics and neurodevelopment: testing movement, growth and stress Researchers exposed zebrafish embryos to environmentally weathered, nanometer-sized plastic particles (simulated environmental particles, SEPs) at concentrations replicating the levels seen in our waterways, while control groups received only embryo water. Zebrafish were selected as an ideal model for these experiments, due to their transparency, rapid development and growth, and genetic similarity to humans. During the experiment, embryos were closely monitored for toxicity, with measurements including survival, hatching, and changes in embryonic growth. Six days post-fertilization, zebrafish previously exposed to nanoplastics were individually placed in a 24-well plate with clean embryo water, then transferred to a DanioVision observation chamber. Movement was recorded for two hours under white light using Noldus' EthoVision XT automated behavioral tracking software enabling the comparison of total distance traveled (locomotor activity) and percentage of time immobile (stopping time) between SEP-exposed and control zebrafish embryos. The study also correlated plastic-induced toxicity with stress signaling, by quantifying cortisol, the principal stress hormone in zebrafish, as well as glucocorticoid signaling. The researchers then investigated whether changes in stress hormones were linked to alterations in gene expression, analyzing transcripts encoding stress markers and hypoxia-responsive genes, including Fkbp5, hpxa, and Pfkfb3. How controlled environments and automated tracking provides insight - The DanioVision observation chamber ensures a controlled environment, high-throughput behavioral analysis, minimizing environmental variability and stress, enabling reliable and robust data collection. - EthoVision XT software automatically tracks zebrafish movement in real-time, capturing locomotor activity and behavioral patterns. The software eliminates the need for manual scoring, ensuring unbiased data collection and captures subtle behavioral changes. - Used together, the DanioVision observation chamber and EthoVision XT provide continuous 24/7, non-invasive behavioral tracking. This real-time approach minimizes stress while capturing subtle developmental and behavioral changes that traditional methods might miss. How might you research benefit from automated, non-invasive behavioral testing in a 24/7 environment? The ins and outs of zebrafish research Basic behavioral neuroscience in zebrafish Learn all about the why, when and how regarding zebrafish development and behavior. Explore protocols and best practices to get the most out of your zebrafish research. Download for free The rising tide of nanoplastics and the implications for human health This study demonstrated that exposure to nanoplastic particles during development resulted in toxicity and elevated stress signaling, although changes in longevity were not seen. Delayed hatching and reduced growth: Zebrafish embryos exposed to nanoplastics showed delayed hatching, and measured up to 150 μm shorter in early development compared to controls. Impaired locomotion: Locomotor activity was reduced by up to 40% in zebrafish embryos exposed to nanoplastic particles. Elevated stress responses: Cortisol levels were elevated 2-3 fold in zebrafish exposed to nanoplastics, while transcriptomic analyses highlighted the upregulation of genes involved in stress and hypoxia signaling. These findings raise important questions around human health. While the study was conducted in zebrafish, the observed neurodevelopmental impairments and elevated stress responses suggest that chronic exposure to nanoplastics might pose a significant risk for human neurodevelopment. Conclusion: Nanoplastics do impact neurodevelopment! While our understanding of the relationship between neurodevelopmental processes and environmental stressors remains limited, this study demonstrates that nanoplastics significantly disrupt zebrafish neurodevelopment and increase stress signaling at multiple biological levels. By combining behavioral tracking tools including the DanioVision observation chamber and EthoVision XT software, the researchers were able to detect subtle changes in zebrafish neurodevelopment and locomotion, which resulted from nanoplastic exposure during the embryonic stage. These findings not only raise significant concerns for our wildlife and aquatic systems but also suggest that long-term exposure to nanoplastics may have important implications for human health. While it is not yet clear whether exposure to nanoplastics might trigger the same stress responses and neurodevelopmental disruptions in humans, these results highlight the need for ongoing research into the potential health impacts of these pervasive and widespread ultra-small plastic particles. References Saraceni, A., Rubin, A. E., Wexler, Y., Gothilf, Y., Bovolin, P. & Zucker, I. (2025). Simulated Environmental Nanoplastics Induce Zebrafish Developmental Toxicity and Stress Response. ACS Sustain. Chem. Eng. doi:10.1021/acssuschemeng.4c10847. --- ## 7 things you need to know about FaceReader URL: https://noldus.com/blog/what-you-need-to-know-about-facereader Published: 2025-04-15 10:44:46 Description: Are you looking for guidance in getting started with your facial expression analysis? Or want to get more out of your FaceReader setup? Keep reading to learn 7 essential things you need to know about FaceReader! We received a wide range of questions during a live Q&A session for FaceReader users with NoldusCare—from basic how-to's to detailed questions about methodology and validation. In this blog post, we'll go over 7 of the questions people asked about FaceReader. 1. How does FaceReader calculate and classify facial expressions? The FaceReader algorithm follows a three-step process. First, it detects the face in an image. Then it builds a face model based on the 468 facial landmarks in FaceReader. Finally, it uses a trained artificial neural network (based on 100,000 images) to classify emotional expressions and facial states. The expressions classified by default include the six basic facial expressions—happy, sad, angry, scared, surprised, and disgusted—plus contempt and a neutral state. Additional functionalities allow you to measure Action Units, heart rate or heart rate variability, voice intensity, eye gaze, and even consumption behavior like chewing or intake. You can monitor these over time and visualize the intensity of each expression and Action Unit on a timeline or in a line chart. 2. How is the Action Unit functionality validated, and how accurate is it? We validated the Action Unit capability in FaceReader using the Amsterdam Dynamic Facial Expression Set (ADFES), a dataset with 22 individuals displaying nine emotional expressions. These expressions were manually coded by certified FACS coders, and FaceReader's outputs were then compared to those human ratings. The agreement between the two FACS coders was 0.83, and the agreement between FaceReader and the human annotations was 0.81. This high level of agreement indicates strong validity, especially considering how complex facial coding can be. Read more on how FaceReader is validated. FREE WHITE PAPER: FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download 3. What are best practices for camera positioning during recordings? Camera placement is a key factor for ensuring high-quality data. FaceReader works best when the face is fully visible, evenly lit, and facing the camera. A webcam placed right above the screen is typically the best option—it gives a frontal view without being too intrusive. Placing the camera too low (for example, at table level) can lead to false readings. For example, inflated eyebrow positions may look like surprise. Get more tips on how to optimize your FaceReader setup. 4. What is a dominant expression in FaceReader? A dominant expression in FaceReader is simply the expression with the highest intensity at a given moment. For example, if someone is smiling, but also raising their eyebrows slightly (a mix of happy and surprise), the dominant expression might still be coded as happy if its intensity is highest. Even when an expression isn't dominant, FaceReader logs the intensity of all expressions frame by frame. That means you can still analyze less prominent responses or micro-expressions—like surprise during a happy moment—by exporting the data from the expression line chart. 5. How can I compare responses between stimuli or between participants? You can use the Project Analysis functionality for both within-subject and between-subject comparisons. For example, if participants watched two different videos, you can use the "Compare" function to visualize average responses—such as mean happiness or valence—across those stimuli. Keep in mind that for meaningful interpretation of FaceReader results, you always need to consider the context in which certain facial expressions were recorded. You can also compare individuals by selecting participants manually. For example, you might want to see how participant A and B responded to the same video. FaceReader includes t-tests to help identify these differences. 6. What is a good workflow for batch processing a large number of videos? If you're dealing with large datasets, batch processing of pre-recorded videos in FaceReader can save a lot of time. This means using the Project Wizard to load multiple videos automatically. Instead of manually adding each participant and assigning their video, you can select a folder and FaceReader will create one participant per video. Once everything is loaded, the batch analysis feature will process each video one by one. To save time, you can also adjust the sample rate to analyze every third frame instead of every frame. For videos recorded at 30 frames per second, this means FaceReader analyzes 10 frames per second, which is still well above the 5 frames-per-second minimum needed for reliable results—but done much faster. It's worth noting that FaceReader does not autosave. So after a batch run, make sure to save the project to avoid losing data. Look for the asterisk (*) next to the project name—that means you've made changes that haven't been saved yet. 7. Can I create my own custom expressions in FaceReader? Yes! In FaceReader, you can define custom expressions based on Action Units, head movements, or other facial states. You can build expressions using logical operators and thresholds. It's also possible to simulate the effect of different Action Unit intensities to test how your custom expression works. This is especially useful if you want to detect states that aren't in the default set, like embarrassment, boredom, or pain. Keep in mind that creating meaningful custom expressions requires research. Start by observing your participants in the context where that emotion or state is expected to occur. Then experiment with building expressions from the Action Units and visual features that match your observations. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Facereader: a powerful tool for your research This blog posts highlights just how versatile FaceReader is. Whether you're running a simple usability test or building a custom model to detect subtle facial expressions, there's a lot you can do with the software. At the same time, good results depend on the right methodology: clear lighting, thoughtful design, and a strong understanding of what FaceReader is measuring. Your research deserves the best Got a question that wasn't covered? Feel free to contact us! You can also find more in-depth information on the FaceReader resources page. --- ## Understanding social behavior URL: https://noldus.com/blog/understanding-social-behavior-from-observation-to-insight Published: 2025-04-09 09:15:48 Description: Social behavior is everywhere—at home, at work, and in the classroom. Discover what it is, why it matters, and how observing it with the right tools leads to deeper insight into how people connect, communicate, and respond. From the very first smile between a newborn and a parent to the way team members respond to each other during a meeting, social behavior is all around you. It shapes how individuals connect, influence, and respond within groups. Whether you're a researcher, educator, or clinician, understanding social behavior offers practical insights into development and group dynamics. Social behavior reveals a lot more than what meets the eye—it offers a direct window into how relationships work. What is social behavior? Social behavior includes the various ways people interact with others, both intentionally and unintentionally. It's how someone smiles at a friend, helps a stranger, shares a joke, or even waits patiently in line. These behaviors help maintain relationships, build trust, and create group harmony. In research, social behavior can be observed in one-on-one (dyadic) interactions or within larger groups. Here are a few key types of social behavior: - Prosocial behavior: Actions that benefit others, such as comforting someone who's upset, volunteering, or helping a peer with a task. These behaviors often involve empathy, cooperation, or kindness. - Communicative behavior: Any form of verbal or non-verbal communication, like eye contact, body language, gestures, facial expressions, or tone of voice. For instance, nodding during a conversation shows engagement and respect. - Affiliative behavior: Behaviors that build social bonds, such as hugging, handshakes, or group laughter. These are often seen in close relationships or team settings. - Regulatory behavior: Behaviors that help manage interactions, like taking turns when speaking, apologizing after interrupting, or showing restraint in emotionally charged moments. The other side: what is antisocial behavior? To understand social behavior fully, it helps to also consider what its opposite is. Antisocial behavior refers to actions that harm or disregard others. It includes aggression, manipulation, deception, or behaviors that violate social norms—like bullying or lying. While social behavior aims to connect, antisocial behavior isolates or damages relationships. In some contexts, studying antisocial behavior is just as important, especially in developmental psychology or clinical settings. By comparing both, you can better understand how social norms develop and what happens when those norms are broken. Why should you measure social behavior? Observing social behavior is one thing—measuring it accurately is another. As a researcher, you want more than just anecdotal notes or impressions. You need structured data to understand patterns, compare findings, and build solid conclusions. When you can quantify interactions, you don't just observe but also gain insight. You uncover trends. And you find meaning in the smallest shifts in behavior. This is particularly valuable when you're studying complex phenomena like empathy, cooperation, or social development in infants. Failing to measure social behavior can mean missing out on key indicators of emotional health, cognitive development, or even group performance. How can you measure social behavior? Social behavior can happen in many different forms. Sometimes it's a dyadic interaction or one-on-one exchange, like a parent soothing a child or two colleagues solving a problem together. Other times, it takes place in larger settings, such as classrooms, team meetings, or social gatherings, where group dynamics come into play. In these situations, you might observe behaviors like leadership and turn-taking. To capture and analyze these interactions effectively—whether between two people or among many—you need tools that offer precision and flexibility. For example: - Viso software offers a flexible way to record social interactions from multiple camera angles, making it easier to capture the full context of behavior in real-life settings. You can review and annotate behavior from different perspectives, making it easier to evaluate subtle cues, identify key interaction moments, and support accurate, objective analysis. - The Observer XT enables detailed behavioral coding across time, allowing you to mark and analyze interactions in both small and large group contexts. You can track who initiates contact, how others respond, and how behavior unfolds moment by moment. Ideal for understanding complex social dynamics. - For emotional insight, FaceReader can analyze facial expressions during conversations or interactions. It helps you understand how individuals emotionally respond within a social context—whether that's mutual joy in a friendly exchange or discomfort during group pressure. FaceReader also allows for analysis of reactions to video stimuli, such as moral dilemmas or social scenarios. You can also easily use The Observer XT, FaceReader, and Viso together in your setup, allowing you to synchronize behavioral observations, emotional responses, and video footage in one unified workflow—making your analysis more efficient, consistent, and complete. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download 📌 Case in point: Observing social behavior in real time In a recent study (Hubbard et al., 2024), researchers observed nine-year-old children as they interacted in a structured round-robin format, where each child partnered with every other group member. During cooperative and frustrating tasks, facial expressions were captured every second using The Observer XT. Their findings? Clear evidence that both individual personality traits and the dynamics of each specific dyad shape how emotions are expressed—even among children meeting for the first time. Studying social behavior using screen-based scenarios While direct interaction offers rich insight, social behavior can also be studied through screen-based scenarios. For example, participants might view videos of facial expressions, social situations, or moral dilemmas on a screen. This setup allows you to measure how they respond to social cues, even without face-to-face contact. Researchers have used FaceReader to study emotional reactions to advertisements and stylized graphics, revealing subconscious responses that traditional surveys often miss. This makes FaceReader a powerful tool not just for observing emotions, but for uncovering the feelings people may not even realize they're showing. By combining observational and emotional data, you gain a more complete picture—not just what happened, but how participants experienced the interaction. And that's crucial, whether you're studying toddlers learning to share or adults navigating workplace collaboration. Social behavior in autism Understanding social behavior becomes even more crucial when working with individuals on the autism spectrum. People with autism often experience differences in how they perceive, process, and respond to social cues. These differences can affect everything from eye contact and facial expressions to turn-taking in conversation and interpreting emotions. Observing the differences that matter The Observer XT can help identify patterns in social interactions—like reduced frequency of initiations or delays in response—while FaceReader can detect subtle emotional expressions that may not align with verbal communication. As a multi-angle video recording system, Viso allows you to capture detailed footage of real-life social scenarios, like a therapy session, classroom setting, or clinical observation. Measuring social behavior in autism helps you better support individuals and design targeted therapies. From interaction to interpretation Social behavior isn't just about what happens between two or more people. It's about the deeper meanings behind those actions. By using scientific tools to observe and measure these behaviors, you move from guessing to knowing. And when your research uncovers those insights, you're not just collecting data—you're contributing to a broader understanding of human interaction. 💡 Want to stay ahead in behavioral research? Subscribe to Noldus Newsline now! You will receive expert insights and the latest innovations, straight into your inbox every month. Reference Hubbard, J.A.; Moore, C.C.; Zajac, L.; Marano, E.; Bookhout, M.K. & Dozier, M. (2024). The importance of both individual differences and dyadic processes in children's emotion expression. Applied Developmental Science, 28(2): 193–206. https://doi.org/10.1080/10888691.2022.2163247. --- ## Rat strain and sex matter in spinal cord injury research: insights from CatWalk XT URL: https://noldus.com/blog/rat-strain-and-sex-in-spinal-cord-injury-research-catwalk-xt Published: 2025-04-04 08:00:00 Description: Researchers from the Central University of Michigan studied how different rat strains and sexes recover from spinal cord compression injuries, providing valuable insights into recovery variability and potential treatment consideration. Spinal cord injuries (SCIs) are life-altering conditions that affect sensory, motor, and autonomic functions, including bladder control and sexual function. In the United States alone, approximately 305,000 individuals live with SCI, with an estimated 18,000 new cases yearly. Despite medical advances, no definitive cure exists, and treatments primarily focus on mitigating symptoms. To develop effective therapies, researchers rely on animal models that need to accurately replicate human SCI conditions. A crucial but often overlooked factor in SCI research is the influence of biological differences such as strain and sex in experimental animal models. A recent study by Mojarad and colleagues (2025) at the Central University of Michigan highlights just how significant these factors are. Using CatWalk XT in their research, they aimed to determine how different rat strains and sexes recover from spinal cord compression injuries, providing valuable insights into recovery variability and potential treatment consideration. LEAFLET Why free walking is the superior method When performing gait analysis, it is important that your animals behave as naturalistic as possible. In this leaflet, you'll learn about: - The downsides of using forced gait - Practical tips when using the CatWalk XT method - How to get the best data for your publication Read now description Study design: investigating the impact of rat strains and sexes in SCI recovery The study utilized two common rat strains—Sprague-Dawley and Wistar—and included both males and females. The researchers induced SCIs by applying aneurysm clips at two severity levels: a moderate injury was mimicked by applying a clip with a 15-g closing force for 180 seconds and a severe injury was caused by a clip with a 60-g closing force for 60 seconds. A total of 24 rats were tested with three animals in each strain/sex/injury severity category. Mobility was assessed pre-surgery (as a baseline), three days post-surgery, and then weekly for seven weeks. Three locomotor tests evaluated spontaneous recovery: - Basso-Beattie-Breshanan (BBB) Scale: Observers score motor function based on a 21-point scale while rats moved freely in a container. - Horizontal Ladder Rung Walking test: Rats crossed a nine-rung horizontal ladder, with researchers scoring paw slips over three trials. - Noldus CatWalk XT test: A high-speed video system captured gait patterns on a transparent walkway, analyzing forelimb and hindlimb prints to assess movement patterns, coordination, and kinetic properties, based on three trials per test. Key findings: strain and sex significantly influence recovery The study revealed that recovery outcomes depended on rat strain, sex, and injury severity: Moderate injuries: Sprague-Dawley rats recovered more effectively than Wistar rats, with females recovering faster than males. The BBB test showed clear differences in spontaneous recovery between strains and sexes, while the CatWalk XT system detected significant variations in gait parameters such as run duration, speed, and hindlimb print measurements between sexes, strains, and over time. The horizontal ladder rung test, showing about 50% paw slips, failed to reveal significant differences between groups. Severe injuries: Recovery was generally poor, but females—especially Sprague-Dawley females—outperformed males in the BBB tests. The ladder test recorded approximately 80% paw slips but showed no significant differences between groups. The CatWalk gait analyses detected pre-surgery variations in step regularity and cycle between strains and sexes but found no significant post-surgery differences due to weak recovery after severe injuries. These results suggest that certain rat strains might be more resilient to spinal cord injuries, and females tend to recover better than males, particularly after moderate injuries. This highlights the need for careful model selection in SCI research, as failing to account for these biological variables may lead to misleading conclusions. You may also like to watch this customer story about functional recovery in rat models of spinal cord injury. The role of CatWalk XT in spinal cord injury research Traditional locomotor tests like the BBB scale and the horizontal ladder test rely heavily on observer scoring, introducing potential biases and limited precision. The Noldus CatWalk XT system offers an automated and more objective method to analyze gait, providing high-resolution data on paw print shapes, stride length, swing speed, and movement coordination. This system proved especially valuable in this study, detecting locomotor differences between strains and sexes that traditional tests like the ladder test failed to capture. By incorporating advanced gait analysis technology into SCI research, scientists can gain deeper insights into recovery patterns and develop more targeted therapeutic interventions. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources library_books Conclusion: strain and sex must be considered in SCI research This study underscores the importance of considering both strain and sex when designing SCI experiments. The significant differences in recovery patterns between Sprague-Dawley and Wistar rats, as well as between males and females, suggest that genetic and biological factors play a crucial role in determining recovery potential. Ignoring these variables could lead to inconsistent findings and limit the translational value of animal models. By integrating sophisticated behavioral assessment tools like CatWalk XT, researchers can refine their understanding of locomotor recovery and tailor treatments more effectively. As SCI research progresses, recognizing the influence of strain and sex will be essential in developing therapies that better reflect individual variability, ultimately improving outcomes for patients living with spinal cord injuries. References Mojarad, N., Doyle, D., Garmo, L. G., Graff, R., Reed, K., Wolbert, P. A., Uprety, A., Stewart, B., Rossignol, J., & Dunbar, G. L. (2025). Sex and strain-specific variations in motor recovery following compression spinal cord injury: Comparison of Sprague-Dawley and Wistar rats. Brain Sciences, 15(2), 191. https://doi.org/10.3390/brainsci15020191 --- ## Cats and human emotions: A stronger bond than we thought? URL: https://noldus.com/blog/cats-and-human-emotions-a-stronger-bond-than-we-thought Published: 2025-04-02 14:00:00 Description: A recent study shows cats can detect human emotions through scent - especially fear - suggesting our cat friends might understand us more than we realize. For centuries, dogs have been credited as humankind's best friend, while cats have often been seen as independent and aloof creatures that engage with humans only on their own terms. And yet, recent research suggests that cats may be more attuned to human emotions than previously thought. Studies show that cats react to their owners' visual and vocal signals and adjust their behavior based on human emotions. Odor plays a central role in the social behavior of domestic cats, but little is known to what extent cats can perceive human emotions through scent. Researchers from the University of Bari Aldo Modo in Italy explored this by examining how cats react to human odors associated with different emotional states (d'Ingeo et al., 2023). The experiment: Can cats smell human emotions? To investigate whether cats can smell human emotions, d'Ingeo and her colleagues conducted an experiment using odor samples from three unfamiliar men exposed to different emotional states: fear, happiness, physical stress, and neutral. Sweat swaps were collected after the men watched emotionally charged videos (fear/happiness), after they ran 15 minutes (physical stress), and after they showered (neutral). Twenty-two cats were tested in their home environment, where each odor was presented to the cat for 45 seconds, with 40 seconds in between odors. Owners were asked not to look at or talk to their cats, since even eye contact or a simple word could influence how the cats behaved. The experiments were recorded with high-resolution cameras to record detailed observations of the cats' behaviors. Cat observations Using The Observer XT, the researchers analyzed behaviors indicating relaxation (e.g. sitting calmly, ears erect and facing forward), moderate stress (e.g. tail tip twitching, ears angled backward), and severe stress (e.g. retreating, ears flattened backward). They also recorded which nostril the cats used as different brain hemispheres process different types of emotional stimuli, offering insights into the cats' emotional states. The Observer XT is used by many researchers for detailed behavioral data collection, visualization, and analysis, helping researchers gain deeper insight into animal behavior. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial How cats react to human emotional scents The study revealed that cats' behaviors changed significantly based on the emotional odors presented, particularly fear-related scents. When exposed to the "fear" odor, cats exhibited more severe stress-related behaviors compared to when they were exposed to "physical stress" and "neutral" odors. Moderate stress behaviors were also more pronounced in response to "fear" compared to "neutral" odors. However, relaxed behaviors were unaffected by scent type. Cats use left and right nostrils differently Cats used both nostrils equally often but relied on their right nostril more when displaying severe stress behaviors while smelling "fear" and "physical stress" odors. Since the right nostril connects to the right hemisphere of the brain, responsible for processing arousal and intense emotions (e.g., anger and fear), this suggests that these odors trigger a higher emotional response in cats. Conversely, cats used their left nostril more frequently when displaying relaxed behaviors, activating the left hemisphere, which regulates positive and pro-social behaviors. Scent alone isn't enough for cats to recognize happiness Surprisingly, cats did not show clear behavioral differences between "fear" and "happiness" odors. One possible explanation is that cats might require visual and auditory cues in addition to scent to fully interpret positive emotions. Another possibility is that cats respond to the overall arousal level of an odor rather than distinguishing between positive and negative emotions. This would mean that both "fear" and "happiness" odor elicit increased alertness. This might reflect an adaptive strategy, allowing them to remain alert to a range of environmental and social stimuli and react appropriately to potential threats. The way you smell creates a deeper emotional connection These findings challenge the stereotype of cats as indifferent to human emotions. While they may not express their attachment in the same overt ways as dogs, cats are clearly tuned into the emotional states of their humans. They not only recognize human emotions but may also respond to them in ways that reflect their own emotional states. This growing body of research highlights the importance of understanding and respecting our feline companions' sensitivity to our emotions. As our knowledge deepens, so does our appreciation for the complexity of the human-cat relationship. So, the next time your cat seems to be reacting to your mood, it might not be just a coincidence—they may truly understand you more than you think. Why understanding animal behavior matters Understanding animal behavior is essential for several reasons: - Enhancing human-animal relationships: Recognizing how animals perceive and respond to human emotions fosters stronger bonds and more meaningful interactions. - Improving animal welfare: Knowledge of animal emotions helps create better environments in homes, shelters, and veterinary settings, reducing stress and improving overall well-being. - Advancing scientific knowledge: Research into animal cognition deepens our understanding of how different species interpret their world, providing insights into both animal and human psychology. - Practical applications: From training and behavior modification to improving pet care, understanding animal behavior has tangible benefits for pet owners, veterinarians, and animal caregivers. Reference d'Ingeo, S.; Siniscalchi, M.; Straziota, V.; Ventriglia, G.; Sasso, R. & Quaranta, A. (2023). Relationship between asymmetric nostril use and human emotional odours in cats. Scientific Reports, 13(1), 10982. https://doi.org/10.1038/s41598-023-38167-w --- ## Does infection cause memory loss? URL: https://noldus.com/blog/does-infection-cause-memory-loss Published: 2025-03-28 14:00:00 Description: This article explores new research investigating a link between bacterial-induced inflammation and long-term cognitive impairment. Recent data obtained with the Noldus PhenoTyper and EthoVision XT suggests this relationship is worth investigating. We explore new research investigating a link between bacterial-induced inflammation and long-term cognitive impairment. Recent data obtained with the Noldus PhenoTyper and EthoVision XT suggests this relationship is worth looking into. Do bacterial infections matter? Bacterial infections of the central nervous system (CNS) are known to cause long-term neurological complications and can lead to significant infection-driven brain dysfunction in both adults and children. Emerging evidence suggests that CNS infections might increase the risk of an individual developing dementia over a 15-year period, and there is a well-established link between Alzheimer's and immune response. Unfortunately, while current therapeutic strategies can suppress inflammation, their ability to prevent cognitive decline after infection remains limited. This demonstrates a clear need for novel, efficacious treatments that limit or reverse neurological damage, and highlights the importance of ongoing research exploring the long-term brain effects of infections. To understand the relationship between bacteria-induced neuroinflammation and post-infectious cognitive changes, researchers at University of Oklahoma Health Sciences Center conducted a series of rodent experiments using Noldus' PhenoTyper and EthoVision XT. This experimental setup enabled them to investigate how both systemic and CNS infections can progressively impair learning, memory and overall decision-making. Neuroinflammation and memory loss: Testing cognitive decline after infection To understand the association between infection and decision-making, Cassidy and colleagues (2023) exposed mice to one of two strains of Listeria bacteria: A wild-type neuroinvasive strain capable of infecting the brain, and a non-neuroinvasive mutant strain lacking the gene listeriolysin O. A third group of mice received only sham (PBS) injections, with all mice receiving antibiotics for 14 days. At either 1 month or 4 months post-injection, mice underwent a series of behavioral tests designed to assess learning and memory. These included reward-based discrimination tasks carried out in a Noldus PhenoTyper cage fitted with a Cognition Wall, with continuous tracking of movement and decision-making by an overhead camera running EthoVision XT software. The Automated Home Cage-based Observation and Data Analysis (AHCoDA) platform enabled researchers to analyze each mouse's decision-making patterns over time, to understand whether prior infection affected performance. Beneath the surface: Neuroscience and the immune system Following the behavioral phase, the researchers collected brain samples and assessed whether alterations in T-cell subsets correlated with the observed deficits in learning, memory and decision-making, to understand how inflammation influences post-infectious cognitive changes. How advanced behavioral tracking and automated neuroscience tools provided insight PhenoTyper and Cognition Wall: Automated home-cage testing - To reduce handling stress, mice were individually housed and trained in an automated PhenoTyper cage with a Cognition Wall for four days. - During days 1-2 the leftmost door was associated with a food-based reward to assess discrimination. - During days 3-4 the protocol was reversed, with the reward associated with the rightmost door. Mice were forced to discard the old habit while learning a new rule, a test of reversal learning. - How could your research benefit from automated cognition testing? Automated performance tracking with EthoVision XT - An overhead infrared camera relayed real-time data to EthoVision XT software, which enabled tracking of each mouse's movement, correct or incorrect door-entry choices, and changes in exploration patterns. - Automated tracking eliminates the need for manual scoring, providing precise measurements of learning speed, while capturing subtle differences in behavior and learning patterns. - Do you need non-invasive, continuous tracking to capture deep insights? Continuous, non-invasive monitoring with AHCoDA - To reduce stress and enable long-term, non-invasive monitoring of the mice, the data were integrated into the AHCoDA system. - This system provided information on hundreds to thousands of entries (trials), yielding a robust, reliable and unbiased dataset, and provided insight that standard or manual methodologies would miss. - Would high-throughput, unbiased data collection accelerate your research? BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Submit to download A surprising link and implications for future research The present study adds important and novel insight into the relationship between neuroinflammation and cognition. Progressive decline. Cognitive impairments not only persist long after Listeria infection has resolved, but appear to progressively decline over time, as decision-making was significantly worse 4 months post infection than at 1 month. Systemic inflammation influences behavior. Even mice exposed to the non-neuroinvasive Listeria strain displayed signs of cognitive decline and impaired decision making, demonstrating that even inflammation outside of the brain can alter central processes including learning and decision-making. These findings provide important parallels in human disease, where chronic or recurrent infections might contribute to progressive cognitive decline, while emphasizing the limitations of using short-term anti-inflammatory agents, which fail to address infection-driven brain dysfunction or prevent post-infectious cognitive changes. Conclusion: Bacterial infections do matter – Insights into Neuroscience and the immune system While many aspects of the neuroinflammatory process and cognition remain unclear, this study demonstrates that bacterial infections do indeed matter, as both central and systemic bacterial infections were shown to significantly impact both behavior and brain function. By combining automated neuroscience tools including the Phenotyper for non-invasive home-cage testing, EthoVision XT for automated movement tracking and AHCoDA for unbiased data analysis, the researchers identified subtle changes in learning and decision-making driven by inflammation. Learn about how Noldus PhenoTyper and EthoVision XT can enhance your research. The impact of long-term cognitive decline after infection highlights the fundamental need for the development of effective therapies that address infection-driven brain dysfunction as well as the importance of understanding the interplay between neuroscience and the immune system. References Cassidy, B. R., Logan, S., Farley, J. A., Owen, D. B., Sonntag, W. E. & Drevets, D. A. (2023). Progressive cognitive impairment after recovery from neuroinvasive and non-neuroinvasive Listeria monocytogenes infection Front. Immunol. 14, 1146690 --- ## Does obesity cause anxiety? URL: https://noldus.com/blog/does-obesity-cause-anxiety Published: 2025-03-20 16:31:00 Description: In this blog we explore the relation between a high fat diet and anxiety in rodents. Recent data obtained with EthoVision XT show that it might not be as clear cut as it once seemed. Anxiety disorders, including panic attacks and the obsessive-compulsive disorder (OCD), are on the rise, with increasing evidence suggesting a link between obesity and mental health. Research suggests obesity can contribute to anxiety and depression by altering the gut microbiome, triggering inflammatory processes in the brain. Given this connection, scientists are exploring diet-based or probiotic treatment for anxiety disorders. To investigate this, researchers at the University of Louvain, Belgium, conducted an experiment on laboratory mice using Noldus' EthoVision XT. Testing anxiety in mice: a controlled experiment To better understand the association between anxiety and diet, Wong and her colleagues (2025) divided 24 male mice into two groups. One group received a high-fat diet, while the control group received a low-fat diet. After six weeks, both groups underwent a series of five standard behavioral tests designed to measure anxiety levels in mice, presented from low to high impact over two weeks. Using a high-quality camera with EthoVision XT, the researchers meticulously tracked and analyzed the mice's movements during these tests. - Open field test Anxious mice tend to stay near the walls of an open arena rather than exploring the center. EthoVision XT tracked the time spent in specific areas, speed, and the total distance moved. - Marble burying test Anxiety-prone mice exhibit compulsive behavior, such as excessive burying of marbles placed in their bedding. EthoVision XT measured the number of marbles buried. - Light-dark test Mice prone to anxiety prefer to remain in the darker portion of a two-chambered enclosure rather than venturing in the illuminated section. EthoVision XT recorded the transitions between dark and light chambers. - Elevated plus maze More anxious mice spent less time in the open arms of an elevated maze, favoring the enclosed area. Entries into the open arms were analyzed by EthoVision XT. - Forced swim test Anxious mice are less likely to display movements beyond those needed to keep afloat. EthoVision XT recorded the latency to the first float event and the time spent being mobile. In addition to behavioral data, Wong et al. (2025) measured body weight, fat tissue weight, gut microbiome diversity, concentrations of corticosterone (a stress hormone), and markers of brain inflammation. Unexpected results: obesity and anxiety Contrary to expectations, the mice on a high-fat diet – despite increased weight gain and fat accumulation – did not exhibit greater anxiety-related behaviors compared to the control group. This was confirmed by stable corticosterone levels and consistent brain inflammation markers across the two groups. While gut microbiome composition differed between the two groups, the predicted increase in anxiety-like behaviors did not materialize. The impact of oral gavage on stress levels The researchers hypothesized that both the high-fat diet group and the control group in the first experiment were exposed to similar stress levels due to daily oral gavage of a control liquid vehicle. This technique, commonly used to administer bacterial probiotics in rodent studies, may exert stress on the animals, potentially masking any differences in anxiety-related behaviors. To test this, the researchers conducted a second experiment over eight weeks with 36 male mice, all maintained on a low-fat diet. Half the mice underwent daily oral gavage, while the other half did not. By week six, the mice underwent the same five standard tests and body measurements. The results mirrored the first experiment: behavioral tests showed no significant differences between groups. The mice that received oral gavage did not display increased anxiety compared to their non-gavaged counterparts. Additionally, weight gain, corticosterone levels, and inflammatory markers remained similar, reinforcing that neither diet nor oral gavage induced anxiety-related behaviors. FREE TRIAL Try EthoVision XT yourself! EthoVision XT is a video tracking software that can accurately detect and track rodent movement and behaviors. By automating data collection and analysis, it significantly enhances research efficiency, providing high-quality behavioral data with minimal human bias. Get your Free trial Conclusion: challenging assumptions about diet and anxiety These findings challenge the widely held assumption that obesity, caused by a high-fat diet, necessarily leads to increased anxiety. The researchers recognized that prolonging the 8-week dietary treatment could yield different behavioral outcomes. Similarly, the age of the mice when the dietary treatment started and when testing was conducted could be a confounding factor. In this study, gut microbiota composition was altered in obese mice, yet it did not translate into heightened anxiety-related behaviors. Furthermore, oral gavage—a common method in probiotic research in rodent models—did not induce behavioral changes in mice, suggesting that this technique is unlikely to confound future studies. These results highlight the complexity of the relationship between diet, obesity, and mental health. By using advanced tracking instruments like EthoVision XT, scientists can continue to refine behavioral studies and better understand how physiological factors influence mental health. These findings contribute to a growing body of research questioning simple causal links between diet and anxiety, paving the way for more nuanced approaches to mental health interventions. References Wong, G. C., Bearzatto, B., Gala, J.-L., Delzenne, N. M., Van Hul, M., & Cani, P. D. (2025). Obesity phenotype and gut microbiota alterations are not associated with anxiety-like behaviour in high-fat diet-fed mice. Food & Function, 16(1), 268–281. https://doi.org/10.1039/D4FO04461D. --- ## Understanding human behavior at Hofstra's Behavioral Research Lab URL: https://noldus.com/blog/hofstra-behavioral-research-lab Published: 2025-03-18 10:00:00 Description: Discover how Hofstra University's Behavioral Research in Business Lab, directed by Dr. Anil Mathur, utilizes advanced methods like eye tracking and facial analysis to deepen insights into human behavior and business decision-making. The Behavioral Research in Business Laboratory at Hofstra University is a state-of-the-art facility that was specifically designed to conduct multi-disciplinary behavioral research. We visited the lab, where Dr. Anil Mathur, Director of the Behavioral Research Lab at Hofstra University in Hempstead, N.Y., focuses on understanding the reasons behind people's actions and decisions. Understanding human behavior at Hofstra's Behavioral Research Lab The Behavioral Research Lab at Hofstra aims to serve students, faculty, and the broader community. Students gain experience with state-of-the-art methods including eye tracking, facial expression analysis, and voice recognition technologies. Through collaboration with Noldus, specialists in behavioral research technology, Hofstra developed a highly advanced laboratory focused on consumer and general human behavior research. When asked about his experience with setting up a behavioral research lab, Dr. Anil Mathur emphasizes the importance of forward-thinking. His main advise: "Think of the future." Inside the Behavioral Research in Business Laboratory The Behavioral Research in Business Laboratory at is located at the Zarb School of Business at Hofstra University. It is a 1,556-square-foot facility designed specifically for behavioral research in business contexts. Each of the Behavioral Research lab rooms contains sophisticated equipment and software. All designed to facilitate precise human behavior studies and comprehensive data analysis. The lab features two behavioral research rooms connected by a central observation room. Researchers monitor and manage experiments from this observation area. Additionally, the lab offers a conference room for focus groups. There are also three private interview rooms that are well suited for detailed individual studies. Participants taking part in any of the studies can relax in a waiting area equipped with comfortable seating and a TV monitor. Advanced research tools and lab equipment The behavioral lab is fitted with advanced research tools and lab equipment. PTZ (pan-tilt-zoom) cameras throughout the facility record detailed experimental data that can be analyzed further with the help of behavioral research software. - FaceReader This validated facial expression analysis software automatically analyzes six basic expressions objectively and unobtrusively, while also calculating gaze direction and attention patterns. Head orientation and person characteristiscs can also be analyzed. - Viso Captures audio and video from all lab cameras to capture participant behaviors and interaction. This allows for detailed human behavior analysis, that is useful in education, training and skill development. - The Observer XT Behavioral software suite The Observer XT collects, analyzes, and presents observational data, by recording videos using the installed cameras, and manages experimental setups. - Tobii Pro Wearable glasses and screen-based eye tracking systems capture natural viewing behavior, allowing researchers to precisely identify where people look, including fixation timing and duration. Moving forward with behavioral research Hofstra University's Behavioral Research Lab continues to prepare students, researchers, and businesses for the evolving demands of understanding and influencing human behavior. By integrating advanced methodologies and keeping an eye toward future developments, Hofstra - together with Noldus - remains at the forefront of behavioral research innovation. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download Frequently Asked Questions (FAQ) Below you'll find answers to common questions about behavioral research in business. These FAQs will clarify key concepts and tools frequently used in the field. What is behavioral research in business? Behavioral research in business examines how individuals and groups make decisions related to products, services, and organizational practices. It involves observing and analyzing behavior to improve marketing strategies, consumer experience, and business performance. What software is commonly used in behavioral research in business? Software such as Noldus Observer XT, FaceReader, and Tobii Eye Tracking are frequently used in behavioral research for accurate data collection and analysis of behaviors, expressions, and attention patterns. What is behavioral economics? Behavioral economics combines insights from psychology and economics to explore how people make economic decisions, often deviating from rational models due to biases, heuristics, and emotions. --- ## What are stimuli in human behavior research? URL: https://noldus.com/blog/what-are-stimuli-in-human-behavior-research Published: 2025-03-14 10:00:00 Description: A stimulus is any object, event, or factor that influences human behavior. It can be something we see, hear, or feel, affecting our decisions and actions. But how do researchers use stimuli in behavioral studies? A stimulus is any object, event, or factor that influences human behavior. It can be something we see, hear, or feel, affecting our decisions and actions. But how do researchers use stimuli in behavioral studies? If you've ever wondered how researchers study human behavior, you've likely come across the term stimuli. But what exactly are stimuli, and why are they so important in behavioral research? In this article, you'll get a breakdown of the concept, discover different types of stimuli, and learn how they are used in scientific studies with real-world examples. What is a stimulus? Or what are stimuli? In psychology and human behavior research, a stimulus (plural: stimuli) is any object, event, or factor that influences a person's response. Stimuli can be external, so things we see, hear, or touch. They can also be internal, such as emotions or thoughts. Researchers use stimuli to understand how people react, make decisions, and process information. Let me give you an example. Imagine you're scrolling through social media and suddenly stop at an image of a bright red sale sign. That visual stimulus grabs your attention and might influence your decision to click on the ad or make a purchase. The bright color and bold lettering act as triggers, making the offer feel urgent and compelling. You may not have planned to buy anything, but the visual stimulus primes your brain to consider the deal. If the ad includes persuasive elements like a limited-time discount or customer reviews, your likelihood of making a purchase increases. This demonstrates how stimuli shape consumer behavior, often without us even realizing it. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Types of stimuli in behavioral research A stimulus can take many forms, and researchers classify different stimuli based on how they influence human behavior. Below is an overview of the key types used in behavioral research: - Visual stimuli – Images, videos, or colors used to study perception, attention, and decision-making. Example: In an eye-tracking study, researchers might present different website layouts to see which design keeps users engaged the longest. - Auditory stimuli – Sounds or speech patterns used in experiments on language processing or emotional responses. Example: A study on emotional responses to music might test whether fast-paced or slow melodies affect mood and concentration. - Tactile stimuli – Physical sensations, such as heat or texture, used to study pain perception or sensory feedback. For example: A researcher testing smartphone usability might analyze how different screen textures affect user experience. - Olfactory and gustatory stimuli – Smells and tastes often used in consumer behavior research. An example from daily life are supermarkets. They use freshly baked bread scents to trigger hunger and increase sales; a real-world application of olfactory stimuli. - Cognitive stimuli – Words, puzzles, or memory tasks designed to test cognitive processing and decision-making. Example: A behavioral economics experiment might ask participants to choose between two financial plans with different wording to see how framing influences decision-making. How researchers use stimuli in experiments Stimuli are carefully controlled in scientific studies to ensure valid results. Researchers use them to test human responses in various disciplines, from marketing to psychology and neuroscience. - Advertising research: Companies test different versions of an ad, such as varying colors, headlines, or images, to see which one drives the most engagement. Eye-tracking studies can also measure where users focus their attention on a webpage, helping brands optimize their designs for maximum impact. - Psychology studies: Participants might watch emotional video clips while researchers measure physiological reactions like heart rate, facial expressions, or skin conductance. This helps scientists understand how different emotional triggers influence behavior, decision-making, or even mental health conditions such as anxiety and depression. - Neuroscience research: Researchers use flashing lights, images, or sounds in brain imaging studies to track how different stimuli activate neural pathways. Techniques like EEG help scientists analyze brain activity in response to specific stimuli, providing insights into cognitive processes such as memory, attention, and sensory perception. For instance, studies on visual processing might present rapidly changing images while monitoring which brain regions become active. How can technology enhance the use of stimuli? Advancements in technology have revolutionized how researchers use stimuli in human behavior studies. These innovations make experiments more precise, scalable, and immersive. Eye-tracking software for instance, allows scientists to measure exactly where and how long a person looks at a visual stimulus. This provides deeper insights into attention, perception, and decision-making. Facial expression analysis software, like FaceReader, enables researchers to measure emotional responses to stimuli automatically. By analyzing subtle facial movements, researchers can determine how people react to different visual, auditory, or cognitive stimuli in real time. This is particularly useful in marketing research, where companies assess how consumers respond to advertisements or product packaging. Virtual reality and artificial intelligence Virtual reality (VR) creates controlled, lifelike environments where researchers can test reactions to stimuli in realistic settings. For example, VR is used in phobia studies to measure fear responses or in consumer research to analyze shopping behavior in virtual stores. Artificial intelligence (AI) and machine learning enhance stimulus-based research by adapting content in real-time. These technologies can personalize stimuli based on a participant's reactions, making experiments more dynamic and insightful. Behavioral coding tools, such as The Observer XT, help researchers systematically analyze and categorize human behavior in response to different stimuli. By coding behaviors across various conditions, researchers can detect patterns in social interactions, emotional expressions, or decision-making processes. This tool is widely used in psychology, human-computer interaction studies, and usability testing. In neuroscience, brain imaging technologies like EEG allow researchers to see how different stimuli activate specific areas of the brain. This helps scientists understand cognitive and emotional responses with greater accuracy. Multimodal research platforms like NoldusHub integrate multiple data streams, such as physiological responses, facial expressions, and behavioral observations, into a single system. This allows researchers to analyze how different stimuli affect participants across multiple dimensions, leading to more comprehensive insights into human behavior. Technological advancements in research These technological advancements enable more precise, data-driven conclusions about how humans perceive and respond to stimuli. As a result, fields like psychology, consumer and neuromarketing, and user experience research continue to evolve, offering deeper insights into human behavior. Why stimuli matter in human behavior research Stimuli shape our daily lives, influencing how we react to the world around us. From marketing strategies to mental health treatments, understanding how people respond to different stimuli helps researchers, businesses, and healthcare professionals refine their approaches. Studying how people react to different stimuli helps researchers understand everything from advertising effectiveness to mental health treatments. It allows scientists to explore cognitive biases, emotional triggers, and decision-making processes in a controlled way. An example: If a company wants to improve its website, they might conduct an A/B test where different users see different versions of a call-to-action button (e.g., "Buy Now" vs. "Get Yours Today"). The button that gets more clicks reveals which wording is a more effective stimulus. Finally: the importance of stimuli in behavioral research Stimuli are the foundation of behavioral research. Whether in psychology, neuroscience, or marketing studies, they help us understand human reactions and decision-making. By controlling and analyzing stimuli, researchers can reveal meaningful patterns and identify key behavioral trends into how we perceive the world around us. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your multimodal research by managing multiple data acquisition tools at once: - Integrated data collection - Synchronization from the start - Immediate feedback on data quality Learn more Frequently Asked Questions (FAQ) Stimuli play a crucial role in how we perceive, react, and make decisions. Below are common questions and answers to help you better understand their impact in psychology, neuroscience, and everyday life. What are examples of stimuli in daily life? Stimuli are everywhere in daily life. A bright billboard grabs your attention while driving, a text message notification prompts you to check your phone, and the smell of coffee in the morning might make you feel more awake. These are all examples of how external stimuli influence behavior. What is the role of stimuli in psychology experiments? In psychology, stimuli help researchers study behavior, cognition, and emotions. For example, visual stimuli like images of happy or sad faces can measure emotional recognition, while auditory stimuli like background noise can test attention and focus. What is the difference between internal and external stimuli? External stimuli come from the environment, such as sounds, lights, or social interactions. Internal stimuli originate from within the body, such as emotions, hunger, or pain. For instance, feeling nervous before public speaking (internal stimulus) might make your heart race, while hearing applause from an audience (external stimulus) might boost your confidence. How do researchers control stimuli in experiments? To ensure reliable results, researchers control stimuli by keeping their presentation, timing, and intensity consistent. For example, in a lab experiment, every participant might see the same set of images for the same duration to prevent biases. How does the brain process stimuli? The brain processes stimuli through sensory pathways: vision, hearing, touch, taste, and smell. Once a stimulus is detected, it is sent to specific brain areas for interpretation. For example, the amygdala processes emotional stimuli, while the prefrontal cortex handles decision-making responses. What are multimodal stimuli, and why are they important? Multimodal stimuli involve multiple sensory inputs at the same time, such as watching a video (visual + auditory stimuli) or using a touchscreen device (visual + tactile stimuli). Studying multimodal stimuli helps researchers understand how humans integrate different types of sensory information to make decisions. --- ## 8 reasons why FaceReader outperforms OpenFace URL: https://noldus.com/blog/why-facereader-is-better-than-openface Published: 2025-02-17 11:26:58 Description: In this blog post, we’ll break down why FaceReader outperforms OpenFace. We’ll focus on key aspects like accuracy, ease of use, and security—making sure you get reliable results without the hassle. *Originally published in 2025. Please see an updated blog for the most recent comparision. Facial expression analysis can reveal a lot about human emotions, making it a powerful tool in research. But with so many options out there, how do you choose the right software? In this blog post, we’ll break down why FaceReader outperforms OpenFace. We’ll focus on key aspects like accuracy, ease of use, and security—making sure you get reliable results without the hassle. Keep reading to see why FaceReader is the top choice for your facial expression analysis. Why should you measure facial expressions? Emotions influence our behavior—from deciding what to eat and whether to buy a product to our interactions with others. That's why researchers in psychology, user experience, neuroscience, and more include emotion analysis in their studies. One way to measure emotions is to ask people about them. However, often we're not fully aware of our emotions in the moment, or don't know how to describe them accurately. If you want to know more about people's unconscious and immediate reactions, facial expression analysis is the way to go. Objective facial expression analysis for your research FaceReader is the most robust tool for automated facial expression analysis there is. It's easy to use, gives you reliable data, and saves you a lot of time. Plus, it provides many options to visualize and analyze your data, making it easier to interpret your results. And there's more to FaceReader than determining the 6 basic expressions—happy, sad, angry, surprised, scared, and disgusted. The software also measures the smallest visible movements in people's facial muscles, which are called Action Units (AUs). These AUs are based on the widely used Facial Action Coding System (FACS). RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Automated analysis is objective and saves time Classifying these AUs by hand is considered the gold standard in research—as long as you're a FACS certified coder. This means getting at least a 70% accuracy score on the FACS Final Test. But that requires extensive training and is very time-consuming. And even when you have a FACS coder on your team, processing hours of facial recordings can take days or even weeks. Automated analysis tools like FaceReader are a great way to get objective data—fast. Dr. Erin Heerey uses FaceReader in the Social Behavior Lab at Western University. Frame-by-frame expression analysis of her project would have taken 800 hours of manual coding. FaceReader did it in only 14 hours! 8 reasons why FaceReader is better than OpenFace When choosing the right tool for your facial expression analysis, it's important to consider accuracy, reliability, and ease of use. And, of course, you need guarantees that your data will be safe. In this blog post, we compare FaceReader's performance with that of OpenFace, an open-source tool for automated facial expression analysis. Here's why FaceReader is the superior choice compared to OpenFace: 1. FaceReader meets FACS agreement—OpenFace does not A comparison by VicarVision clearly shows that FaceReader has higher precision than OpenFace. With an FACS agreement score of 0.811 and 0.792, FaceReader more than meets the threshold of the internationally agreed FACS Final Test (0.70). This ensures that your data are reliable and valid. OpenFace, however, does not meet these minimal requirements, with an agreement index of 0.621 and 0.672. Think of it like trying to drive a car without a license—OpenFace simply doesn't provide the precision needed for high-quality research. With FaceReader, you can trust that you get robust and accurate research outcomes. 2. FaceReader is ready to use immediately When you buy FaceReader, it is already configured, allowing you to start analyzing facial expressions right out of the box. It’s designed with a user-friendly interface, so you don’t have to waste time setting up or programming. OpenFace, on the other hand, requires significant effort to configure and program. For researchers, especially those in user experience or psychology, FaceReader’s ease of use means you can get started right away with your research. Specifically, FaceReader also includes real-time emotion classification and detection of custom expressions. OpenFace lacks these features and requires time-consuming custom scripting. 3. OpenFace works with outdated models FaceReader’s models are powered by deep learning and AI. They are also regularly updated, with the latest innovations incorporated. This ensures that you're always working with the most accurate models for facial expression analysis. In contrast, OpenFace relies on models that are over six years old. The software has only released two major versions, with the latest (v2.2) dating back to 2018/2019. As a result, many of the models OpenFace uses have become outdated, which can affect the accuracy of your facial expression analysis. This outdated technology can be especially problematic when working in real-world conditions, where you may encounter varying lighting or movement of participants. 4. FaceReader is more precise—with 468 landmarks versus OpenFace's 67 OpenFace only uses 67 landmarks in their face models, while FaceReader relies on 468. This allows FaceReader to provide a far more detailed and accurate analysis of facial expressions, with better precision. With fewer landmarks, OpenFace can only provide a rough estimate for some facial features, which reduces accuracy. FaceReader’s higher landmark count improves image pre-processing for facial analysis, which strengthens face detection and modeling. Again, this benefits researchers working in challenging conditions like low lighting or high movement. 5. Better analysis and visualizations with FaceReader With FaceReader, you can analyze and visualize data in different ways. This helps you gain better insights into emotional responses. For example, you'll find emotion classifications, information about gaze or head orientation, and a chart showing levels of valence and arousal. You can also combine your FaceReader analysis with eye tracking, enriching your data even further. OpenFace, while capable of processing data, offers minimal options to visualize and interpret your results or expand your setup. For example, you won't even find emotion classifications within the software, leaving you to deal with basic data. OpenFace also includes fewer Action Units than FaceReader. 6. FaceReader incorporates the latest techniques FaceReader is continuously evolving, incorporating new techniques and features in every update. This includes options like measuring heart rate and heart rate variability (HRV), creating your own custom expressions, and observing Action Units on the left and right side of the face separately. Moreover, FaceReader Online (FRO) allows for remote data collection, combined with integrated survey tools. This way, you can study participants in their natural environments, from anywhere you want. In contrast, OpenFace has had minimal updates since 2018, and it doesn’t offer any guarantees about future improvements due to its open-source nature. FREE WHITE PAPER FaceReader custom expressions Download this free white paper to learn more about how to create custom expressions in FaceReader. - How to combine different metrics - Best practices for custom expressions - Examples from other researchers Read now 7. FaceReader has better data privacy and security than open-source tools When it comes to data privacy, FaceReader offers a more secure and reliable solution. FaceReader is fully GDPR compliant, with centralized, encrypted storage. This ensures that all data is protected and secure. This level of protection isn’t guaranteed with OpenFace’s open-source system, which can expose your data to security risks. With FaceReader, you can be confident that sensitive data is not only protected, but also managed in a way that meets the highest privacy standards. 8. Always get the help you need with excellent customer support from Noldus At Noldus, you benefit from exceptional customer support. From installation to ongoing training, we offer personalized, expert assistance to ensure your research runs smoothly. Our team includes researchers with real-world experience, which means you’re getting advice from people who understand your research needs. OpenFace, however, lacks dedicated support and only offers assistance through a general forum. This can be frustrating when you run into technical issues. FaceReader: the reliable, efficient choice for facial expression analysis In short, FaceReader is the top choice for researchers who need precise and efficient facial expression analysis. The software's ability to match the accuracy levels of FACS coders ensures that the data you collect are reliable and scientifically valid. FaceReader's user-friendly interface, fast processing speed, and built-in privacy measures make it an ideal tool for researchers who want to focus on their studies without the hassle of programming or complex setups. Whether you're in psychology, user experience, or neuroscience—FaceReader offers the setup you need to take your research to the next level. References - Compared to classifications of the Amsterdam Dynamic Facial Expression Set (ADFES) dataset Van der Schalk, J.; Hawk, S.; Fischer, A.; Doosje, B. (2011). Moving faces, looking places: Validation of the Amsterdam Dynamic Facial Expression Set (ADFES). Emotion, 11(4), 907–920. https://doi.org/10.1037/a0023853 - Compared to classifications of the Warsaw Set of Emotional Facial Expression Pictures (WSEFEP) dataset. Olszanowski, M.; Pochwatko, G.; Kuklinski, K.; Scibor-Rylski, M.; Lewinski, P.; Ohme, R. (2014). Warsaw set of emotional facial expression pictures: a validation study of facial display photographs. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.01516 --- ## 7 Reasons to attend CHI 2025 URL: https://noldus.com/blog/chi-conference Published: 2025-02-17 09:00:00 Description: If you are working in HCI or UX, you are probably familiar with CHI. This conference is organized every year by the international society for Human-Computer Interaction, SIGCHI. Why you should attend CHI 2025? If you work in human-computer interaction (HCI) or user experience (UX), CHI is the conference you don't want to miss. Organized annually by SIGCHI, the international society for HCI, CHI 2025 is the ultimate gathering for researchers, designers, and practitioners shaping the future of interactive technology. Why you should attend CHI 2025 This global event brings together experts from academia and industry to explore groundbreaking innovations, share research, and discuss the latest trends in HCI and UX. Whether you are developing next-generation interfaces, studying human-machine interactions, or designing for emerging technologies, CHI provides a unique platform to connect, learn, and advance your field. From insightful keynotes to hands-on workshops, CHI 2025 offers something for everyone—researchers, practitioners, designers, educators, and students alike. Here's why you should attend! 1. Premier international conference on HCI The ACM CHI Conference on Human Factors in Computing Systems is the premier international conference of Human-Computer Interaction. At CHI 2025, many of the world's top researchers, scientists, and designers will come together to present the future of interactive technology. It's an easy way to stay up-to-date on the latest news and trends in the field—making this conference one you won't want to miss! 2. Experience CHI 2025 in Japan This year's CHI meeting takes place in Japan, a country known for its technological innovations, rich culture, and vibrant cities. Attending CHI 2025 offers a unique opportunity to engage with cutting-edge research while exploring one of the most fascinating destinations in the world. The meeting takes place at the PACIFICO Yokohama from 26 April to 1 May 2025. Although the conference program is packed, consider taking some time to explore the city and immerse yourself in Japanese culture. From historical landmarks to modern tech hubs, Japan provides an inspiring backdrop for CHI 2025. Experience CHI 2025 in Japan (photo via Unsplash) 3. Meet your peers CHI is a multicultural community made up of individuals from highly diverse backgrounds who investigate new and creative ways for people to interact with technology. A shared interest in human-computer interaction and a common goal of developing technology that benefits people and society bring all attendees together. It's the best place to meet your peers! 4. Find your IkiCHI The theme of CHI 2025 is inspired by 'Ikigai,' a Japanese concept that represents a person's sense of purpose and fulfillment. In today's rapidly changing world, individuals face challenges related to climate change, inequality, technological shifts, and global crises. CHI brings together a diverse community of passionate researchers, designers, and practitioners, all driven by their own unique talents and expertise. By sharing knowledge and working collaboratively, we can harness our collective 'IkiCHI'—a communal purpose—to create meaningful technological advancements that contribute to society. The cherry blossom, or 'Sakura,' in the CHI 2025 logo symbolizes renewal and optimism, making this conference the perfect place to find your own IkiCHI. Find your IkiCHI in Japan (photo via Unsplash) 5. Attend workshops Workshops are held the weekend before the start of the conference, on Saturday and Sunday, May 10-11, 2025. They are organized independently by leaders from academia and industry. These sessions provide an ideal gathering place for attendees with shared interests and are a great way to discuss emerging and important topics with experts in the field. 6. Broaden your field A conference like CHI is the perfect opportunity to expand your horizons and gain fresh perspectives on HCI and UX. With a vast array of specialized tracks, panel discussions, and interactive sessions, CHI 2025 allows you to explore new topics beyond your immediate expertise. Stepping outside your comfort zone and attending sessions from different HCI subfields can spark innovative ideas, inspire new research directions, and reveal unexpected collaborations. Whether you're interested in AI-driven interfaces, accessibility, human-robot interaction, or digital ethics, there is something at CHI that will challenge your thinking and broaden your knowledge. Take advantage of informal networking opportunities and interdisciplinary sessions to engage with professionals from diverse backgrounds. You may find that a fresh perspective from a different domain can reshape your approach to your own work. By broadening your field at CHI 2025, you open doors to new possibilities and ensure that your research and practice remain innovative and forward-thinking. 7. See the latest tools for UX and HCI research As always, CHI 2025 features an exhibition where international companies showcase their latest tools and innovations. It's the perfect opportunity to explore cutting-edge technologies and solutions that can enhance your research and professional practice. Join us at CHI 2025 and discover the future of UX and HCI research. FREE DEMO VISO Capture skills training sessions - ✓ Easy-to-use solution Intuitive interface for seamless recording - ✓ Train and educate, enhance teamwork Improve collaboration and learning outcomes - ✓ Immediate playback of recordings Review sessions instantly for better feedback Get your Free demo --- ## Why The Observer XT is the gold standard for behavioral research URL: https://noldus.com/blog/gold-standard-for-behavioral-research Published: 2025-02-14 10:46:59 Description: In the ever-evolving field of behavioral research, having the right tools can make the difference between ordinary findings and groundbreaking insights. When you hear "gold standard", it means more than just being the best - it means reliability, accuracy, and trustworthiness. Just like gold once backed currency for its stability, a gold-standard product in research provides consistency you can count on. In your field, where every data point matters, choosing the right tools can mean the difference between groundbreaking insights and frustrating roadblocks. The Observer XT isn't just a tool; it's a trusted partner in your research journey. Confidence in every step of your research Imagine having a research tool that gives you peace of mind, knowing your data is precise, your workflow is seamless, and your insights are reliable. The Observer XT is that tool — recognized by researchers worldwide for its unmatched credibility and accuracy. Whether you're studying human behavior or animal interactions, The Observer XT helps you focus on what truly matters: your discoveries. Why researchers trust The Observer XT In research, trust is everything. The Observer XT has earned its reputation as the gold standard by delivering where it counts most: 1. Unmatched precision Capturing detailed behaviors with accuracy isn't just helpful; it's essential. The Observer XT provides the level of detail you need to code complex interactions and ensure your findings are valid. Example: A study on sensory integration therapy for children used The Observer XT to take a closer look at therapy sessions. The goal of these sessions are to help children manage how they experience sensations, making everyday activities easier and less overwhelming. Using The Observer XT software enabled the research team to analyze behaviors in a way that led to more meaningful interventions and improved treatment outcomes. [1] With The Observer XT, you're not just recording data — you're gaining insights that can shape real-world solutions. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial 2. A setup that fits your unique needs Your research is unique, and your tools should adapt to you, not the other way around. Whether you're conducting short-term lab studies or long-term field research, The Observer XT flexes to meet your needs. It supports everything from detailed, frame-by-frame behavior analysis to large-scale studies with multiple observers, making it the right fit no matter how complex your project. What researchers say: "In our study, The Observer XT was the gold standard for validating our behavior observation form." says A.C. Mancinelli from the University of Perugia.[2] This study developed and validated a behavior observation protocol for geese in agroforestry systems. 3. Seamless integration with other tools Behavioral research often requires a multi-faceted approach. The Observer XT connects effortlessly with video, audio, eye-tracking devices, facial expression analysis tools, and other data acquisition systems. This ensures your research setup is as comprehensive as your questions. Case in point: Desiree van Dun and her team combined The Observer XT with BIOPAC systems to explore leadership effectiveness, providing deeper insights into team dynamics and performance. [3] This integration capability means you can see the full picture without missing anything. Also read: How to easily apply multimodal measurement during research with children 4. Backed by thousands of studies When you choose The Observer XT, you're aligning your work with a tool trusted by the global research community. Decades of use in academic and professional research settings have built its reputation as a reliable and indispensable tool. With over 15,000 citations on Google Scholar, it's clear that researchers rely on The Observer XT to deliver data they can count on. 5. A researcher-friendly experience Time is your most valuable resource, and The Observer XT is designed to help you make the most of it. Features like customizable coding options, synchronized video playback, and intuitive data visualization make analysis easier and more efficient. - Customizable coding options: Set up workflows that align with your specific research objectives without unnecessary adjustments. - Synchronized video playback: Easily match observed behaviors with recorded events to uncover meaningful patterns. - Advanced data visualization: Spot trends, patterns, or outliers in your data quickly. Transform complex data into clear, actionable insights, helping you see trends immediately. A solution that works the way you do Choosing The Observer XT means choosing a tool that empowers you to focus on your research without worrying about technical limitations. Whether you're aiming for publication-worthy results or looking to streamline your workflow, The Observer XT gives you the confidence to push boundaries. The Observer XT: Your research elevated When it comes to behavioral research, why settle for less? With The Observer XT, you're investing in a tool that supports your passion for discovery, helps you avoid data inaccuracies, and empowers you to make a lasting impact. If you're ready to take your research to the next level, The Observer XT is here to help you succeed — so you can focus on what you do best: making new discoveries that shape our understanding of the world. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources References - Franco, E.; Galaz, G.; Thompson, B.; Blanche, E. & Gonzales, A. (2016). Retrospective Analysis of Sensory Integration Therapy in Children with Autism Spectrum Disorder. Am J Occup Ther, 70(4). https://doi.org/10.5014/ajot.2016.70S1-PO2022 - Mancinelli et. al (2022). Validation of a behavior observation form for geese reared in agroforestry systems. https://doi.org/10.1038/s41598-022-18070-6 - Van Dun, D. H., & Kumar, M. (2023). Social enablers of Industry 4.0 technology adoption: transformational leadership and emotional intelligence. International Journal of Operations & Production Management, 43(13), 152-182. https://doi.org/10.1108/IJOPM-06-2022-0370 --- ## Decoding Gorillas’ gestures: Insights into primate communication URL: https://noldus.com/blog/decoding-gorillas-gestures-insights-into-primate-communication Published: 2025-02-13 09:28:20 Description: Western lowland gorillas use gestures to negotiate and even display 'accents' in their communication. A new study explores these complex social interactions, offering insights into language evolution. The ability to communicate is a cornerstone of social interaction, whether among humans or our closest living relatives. A recent study by Jacques Prieur, Katja Liebal & Simone Pika in Scientific Reports delves into the complex and flexible communication system of Western lowland gorillas. The research reveals that these great apes not only use gestures as a means of social negotiation but also adapt their communicative styles to suit their social contexts — which uncovers a fascinating parallel to human language and accents. Gestures as social negotiation tools Western lowland gorillas (Gorilla gorilla gorilla | yes that really is their scientific name) are social animals, living in groups where effective communication is crucial for maintaining harmony and coordination. Researchers Jacques Prieur, Katja Liebal, and Simone Pika investigated how these gorillas initiate play-fighting using gestures. The study showed that gestures are not random; rather, they are intentional, goal-directed, and their form can vary depending on the individual's social relationships and the context of interaction. What sets this study apart is the discovery that for the first time nonverbal communication can carry distinct characteristics — akin to regional accents in human speech — which vary depending on the group's geographic location. This dynamic flexibility underscores the gorillas' cognitive sophistication and their capacity for adaptive social behavior. Evolutionary implications Understanding gorilla communication offers profound insights into the evolutionary trajectory of human language. The use of gestures as a primary communication tool might represent a precursor to spoken language. Moreover, the study highlights the role of social negotiation in shaping communication systems, providing clues about the pressures that might have driven the emergence of complex language in humans. Challenges and insights from the field Observing gorillas in naturalistic or semi-wild settings presents its own set of challenges. These include environmental variables, the need for non-intrusive methods, and the sheer complexity of analyzing nuanced behaviors in a dynamic social environment. One particularly challenging aspect was deciphering the subtle differences in gestures — distinguishing between a playful "arm wave" and a similar gesture meant to assert dominance. The use of video recordings and systematic analysis was critical here, allowing the team to compare gestural forms within and between gorillas, revisit and cross-validate the observations. Data collection: A behavioral scientist's toolbox Conducting such a detailed study of gorilla gestures requires to follow a rigorous approach to observe, collect and analyze behavioral data. The researchers employed systematic coding methods to analyze hundreds of hours of video footage. Noldus' The Observer XT facilitated this work by enabling precise and efficient behavioral coding and analysis. One notable feature that supports collaborative research efforts is the use of coder licenses in The Observer XT. Coding behavioral data is a time-intensive task, and multiple researchers working on the same project can significantly enhance efficiency and reliability. With a coder license, students and researchers can contribute to a project using a predefined coding scheme and original video footage. Their coded data can then be compiled in The Observer XT and compared in a reliability analysis, ensuring robust and reproducible findings. In this way teams can streamline their workflow while maintaining data integrity, and this functionality is particularly useful in large-scale behavioral research, where multiple observers work on different sections of a study. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Applications beyond the jungle The implications of this research extend far beyond understanding gorillas. By shedding light on the cognitive and social underpinnings of communication, this work has potential applications in fields such as linguistics, anthropology, and even artificial intelligence. For instance, the core principles of gestural communication could inform the development of more naturalistic human-computer interactions. Additionally, these findings might help refine rehabilitation protocols for primates in captivity, ensuring their social and psychological needs are met by incorporating knowledge of their complex social life and communication systems. Key takeaways for researchers For researchers in behavioral science, this study exemplifies the power of combining detailed observational methods with powerful analysis tools. Here are a few takeaways: - Nuance matters: Small variations in behavior can have significant communicative value, emphasizing the need for precise data collection and analysis. - Context is key: Behavioral patterns should always be interpreted within their social and environmental contexts to uncover their true significance. - Invest in methodology: Leveraging tools that enhance data accuracy and efficiency, such as behavioral analysis software and coder licenses, can elevate the quality of research and can make life easier for researchers. Final thoughts This study on Western lowland gorilla communication enriches our understanding of primate cognition and social behavior, bridging the gap between animal communication systems and human language. Noldus Information Technology is proud to support the scientific community with tools that facilitate such groundbreaking research. Interview with one of the authors: Jacques Prieur About your research and your inspiration. You are an expert in primate behavior. What sparked your interest in specifically studying gorillas? How they communicate? And what is the relevance? And why did you choose Western lowland gorillas in this study specifically? "I am an ethologist, specialist in human and non-human primate behaviors. Studying human and non-human primates can help us to better understand ourselves and nature in general. Connecting to our social and ecological roots is vital! Gorillas are less studied than the well-known chimpanzees, while they are just as scientifically interesting, more playful and pacific. I have more pleasure observing and studying gorillas than chimpanzees. Gorillas are great apes, like humans. They communicate using a variety of vocal and non-verbal signals in a similar way to humans. Just look at how children play and how juvenile gorillas play as well, this is striking! Gorillas are specifically relevant models for this study for three reasons: - they exhibit the largest gestural repertoire of all non-human great apes in terms of overall number and number per individual: 33–102 gesture types - the gorilla social structure is consistent with many features of human social organization such as certain patterns of parental behaviors (e.g. male parenting, family formation) - the gorillas differ from the very much studied chimpanzees in their ecology and their social structure and dynamics. Studying gorillas' acquisition and development of gestural communication may thus provide crucial insight into how human development, communicative and social-cognitive skills are linked and related to social environment" How does this study build on or differ from previous work in the field of primate communication? "According to a growing number of researchers, human culture and language are closely related evolutionarily speaking. Gestures play a crucial role in human and non-human primate communication systems (see recent review Prieur et al. 2020 for more details). Studies on the acquisition of gestures in primates provided evidence for modulations of gesture type use in relation to signaller's sociodemographic characteristics but what about modulations of gesture type morphology? The goal of our study was to tackle this question." Prieur, J., Barbu, S., Blois‐Heulin, C., & Lemasson, A. (2020). The origins of gestures and language: history, current advances and proposed theories. Biological Reviews, 95(3), 531-554. How did you ensure that your observations and analyses accounted for the natural variability in gorilla behavior? "In an effort to avoid influencing the behavior of individuals and group, our study was purely non-invasive and involved only observations of naturally occurring spontaneous behavior, with audio and video recordings taken from a minimum distance of five meters." If you used any software tools or systems (e.g., for data coding or analysis), what was your experience with them, and how did they impact your workflow? "I already had experience with The Observer XT. Among other things, I used it to collect and analyze baboons' behavior who communicated intentionally by pointing towards humans. I thus knew this research tool was very helpful." Your findings suggest that gorilla gestures can be likened to human accents. Could you elaborate on what this means for our understanding of language evolution? "These findings suggest that not only vocal but also nonverbal communication signals can be shaped by social factors such as group. This study supports the view that socioecological factors have shaped the evolution of complex signalling systems. It also highlights this important issue for future research: adoption of a multimodal and multifactorial approach. Addressing this issue should enable us to deepen our understanding of the complex of human and non-human primate communication systems." What was the most rewarding or memorable moment for you during the study? "Observing natural behavior of gorillas in their daily life. It was really fun and very interesting. Among other things, in the framework of this study, I observed and documented the first evidence of naturally occurring spontaneous exploitative behavior of a conspecific as a social tool for food acquisition in non-human animals (see Prieur & Pika 2020 for more details). I was literally speechless!" Prieur, J., & Pika, S. (2020). Gorillas'(Gorilla g. gorilla) knowledge of conspecifics' affordances: intraspecific social tool use for food acquisition. Primates, 61(4), 583-591. If you had to summarize your research in one sentence for a non-scientific audience, what would you say? "Curiosity is an engine of life, science is its fuel, go for it!" --- ## What is Galvanic Skin Response? URL: https://noldus.com/blog/what-is-galvanic-skin-response Published: 2025-02-07 15:00:00 Description: Understanding human emotions and physiological responses is a key focus in behavioral science. One insightful tool in this field is galvanic skin response (GSR). But what is galvanic skin response? A beginner’s guide to understanding GSR in research. Understanding human emotions and physiological responses is relevant in many areas of behavioral science. One of the most effective ways to measure these responses is through galvanic skin response (GSR), also known as electrodermal activity (EDA). But what exactly is GSR, and why is it so important in behavioral research? What is galvanic skin response? The galvanic skin response refers to the measurement of the skin's electrical conductance, which changes with sweat gland activity. This activity is controlled by the autonomic nervous system. This means it reacts automatically when you feel emotions like stress, fear, or excitement. When you experience emotional arousal, your sweat glands become more active, leading to increased skin conductance. Measuring these changes allows researchers to gain insights into the body's unconscious responses, revealing key information about emotional and psychological states. How is galvanic skin response measured? Galvanic skin response is measured using small electrodes placed on the skin, typically on the fingers or palms, where sweat gland activity is most noticeable. These electrodes detect the skin's electrical conductance between two points, which changes with sweat production. The process of measuring electrodermal activity includes the following steps: - Electrode placement: Electrodes are attached to the participant's skin, usually on the fingertips or palm. - Baseline recording: Before introducing stimuli, a baseline is recorded to understand the participant's normal or current state. - Stimulus introduction: Participants are exposed to stimuli, such as images, sounds, or tasks specifically designed to evoke emotional reactions. - Data collection: The system tracks changes in skin conductance as the participant responds, producing real-time data displayed on a graph. This simple yet effective method provides researchers with a continuous measure of physiological arousal during behavioral experiments. How is galvanic skin response used in behavioral research Galvanic skin response has become a valuable tool in behavioral science because it provides objective, real-time data on emotional arousal. Unlike self-reported data, which can be biased or inaccurate, GSR directly measures unconscious physical responses. This makes it ideal for studies where understanding true emotional reactions is critical. Some key applications where galvanic skin response is a valuable measurement tool: - Emotion research: Galvanic skin response is widely used to study how different stimuli affect emotional states. For instance, researchers can analyze how a participant's skin conductance changes in response to positive or negative images, providing insights into emotional processing. - Stress and anxiety studies: In research on stress and anxiety, electrodermal activity can reveal how participants physiologically react to stressors, helping researchers develop better interventions and treatments. - Human-Computer Interaction (HCI): GSR is employed to assess user experience by measuring emotional responses to different interface designs or software usability, aiding in the development of more user-friendly technologies. - Marketing research: Neuromarketers use electrodermal activity to gauge consumer reactions to advertisements, products, or brand experiences, offering deeper insights into consumer behavior beyond what traditional surveys can reveal. By measuring the electrical conductance of the skin, galvanic skin response (GSR) provides an objective, real-time view of how people respond to various stimuli. This makes it a critical tool in psychology, neuroscience, marketing, and many more fields. What makes GSR a valuable tool for studying emotions? GSR offers unique insights into the physiological underpinnings of human emotions and reactions, particularly the intensity and timing of emotional responses. For example, in marketing, GSR can reveal how consumers react to advertisements, helping companies tailor their strategies. In psychology research it can be used to study anxiety levels in patients during therapy sessions. What sets GSR apart is its ability to detect unconscious physiological responses tied to emotional arousal. Unlike self-reports, which rely on conscious sharing, GSR measures the body's automatic reactions. This provides researchers with clear, unbiased data and a more accurate view of how emotions influence behavior. Limitations and considerations of GSR While GSR is a powerful tool, it's important to remember that it measures arousal rather than specific emotions. For example, increased skin conductance might indicate excitement or fear; it's the context that helps determine the meaning. To get a more complete picture, GSR is often combined with other methods, like facial expression analysis and heart rate monitoring Additionally, environmental factors like room temperature and humidity, as well as the participant's level of hydration, can influence GSR readings. Researchers must carefully control these variables to ensure accurate and reliable data. Analysis tools like FaceReader or NoldusHub can help with objective measurement and assessment of this kind of data. Using GSR for better insights in human behavior The galvanic skin response is invaluable for human behavior studies. By measuring changes in skin conductance, GSR provides unique, objective insights into emotional arousal and physiological responses. Whether you're studying emotions, stress, or user experiences, including GSR in your research can provide deeper discoveries in behavioral science. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more --- ## Neuroscience conferences you should visit in 2025 URL: https://noldus.com/blog/neuroscience-conferences-you-should-visit-in-2025 Published: 2025-01-31 15:00:00 Description: Conferences are a great place to network and learn. However, there are many different conferences to choose from. In this blog we have outlined our favourite conferences of 2025. This is an old blog. Want to know where we are going in 2026? Then, follow this link to our latest blog. A new year means new opportunities to explore what the world of (neuro)science has to offer! And at Noldus we love attending conferences, since it is a wonderful opportunity to connect with our users and show what we are releasing soon. We have outlined the conferences Noldus is visiting in 2025 for you. So, if you want to meet us, or are generally interested in neuroscience, come visit us at one of these places! 4th Polish Zebrafish Society meeting February 13-14, Poznan, Poland Are you interested in zebrafish research? Then consider visiting the Medical Biology Center of Poznan University this February. This year's Polish zebrafish society meeting is sure to be an interesting meeting for zebrafish researchers of many disciplines. Topics during this conference include subjects from cancer models to toxicology and novel technologies in zebrafish research. Noldus has various tools that can help you enhance your zebrafish research. EthoVision XT is the gold standard in video tracking and has several options specifically for zebrafish research. DanioVision is a high-throughput system for tracking zebrafish larvae behavior. Are you at the 4th Polish Zebrafish Society meeting? Come say hello at our booth. Polish Zebrafish Society Meeting Journée RAM-ANEXPLO-ZEFIX March 28th, Montpellier, France The RAM (Réseau Animaleries Montpellier) is a yearly get-together for researchers, students and technicians to discuss topics like histology, imaging, phenotyping and many more in laboratory animals. Even though this is a smaller conference it is a great opportunity for us to catch up with our existing users as well as meet and learn from experts in the field. Do you want to join or learn more about this conference? You can check out their website. Journée RAM-ANEXPLO-ZEFIX 16th Gottingen meeting of the German Neuroscience Society March 26-29, Göttingen, Germany From a small one-day conference we go to one of the larger neuroscience conferences in 2025. Over four days in March the historic university of Göttingen is once again hosting the Göttingen meeting of German neuroscience. During this event there will be talks on various fields within neuroscience and you can learn about topics ranging from behavioral and clinical neuroscience to neuroimaging techniques and much more. Göttingen has always been a great place for (young) scientists to learn and discuss their work in various symposia and poster sessions. You can also find us at this conference in booth #13 (near lecture hall 8). Make sure to say hello! Göttingen meeting FREE E-BOOK Basic behavioral neuroscience in rodents Download here your one stop for all the behavioral research questions like: - How should I house my animals? - How should I handle my animals? - What are the most common tests, and how do they work? Submit to download Festival of Neuroscience 2025 April 27-30, Liverpool, United Kingdom The British Neuroscience Association is once again organizing the Festival of Neuroscience. This year Liverpool will be the home of scientific debate and interactive events. This conference caters to both academic and commercial sectors across a wide variety of topics. These 4 days are filled to the brim with symposia, plenary sessions and poster presentations, as well as plenty of social events across Liverpool. If you want to meet us in Liverpool, you can find us at booth #20. We will be presenting some of our latest innovations like being able to track two rodents at the same time with great accuracy. This can be done with the improved AI model for EthoVision XT 18. So, if you are in the area make sure to come by. See you in Liverpool! Festival of Neuroscience NeuroFrance 2025 May 14-16, Montpellier, France Did you know that Montpellier is home to the oldest medical faculty in the world? The faculty of medicine was created all the way back in the 12th century. This makes Montpellier the perfect location for interesting lectures on all things neuroscience. Moreover, NeuroFrance 2025 will also include discussions around mentoring young scientists and inclusivity in neuroscience. We are also excited to talk to the over 1000 expected visitors. So, if you are one of them, make sure to visit us at booth #22. Noldus can assist you with any research question you might have. Whether you are a seasoned veteran with automated tools or just starting out, there is always something new you can learn. Let's meet in Montpellier. NeuroFrance Canadian Neuroscience May 21-24, Toronto, Canada After a slew of European conferences, we are flying across the pond to the city of Toronto in Canada. The 18th Canadian Neuroscience meeting is a great way to present your work and learn about the latest and greatest in neuroscience research and techniques. The conference is set to feature researchers from all over Canada and abroad. If you want to present your own work at this conference, you can still submit your abstract until the 17th of February. We will also be there to catch up with our Canadian users, as well as learn about the latest innovations in behavioral neuroscience. If you are also going to Canadian Neuroscience, make sure to drop by our booth! Canadian Neuroscience RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources 51st Meeting European Brain and Behaviour Society 2025 June 28rd - July 1st, Bordeaux, France Are you interested in measuring brain mechanisms or behavior? Then, the EBBS meeting might be something for you. To encourage young researchers to contribute to the conference, EBBS is offering travel awards and the Young Investigator award (for PhD and post docs). You can register for this (and other awards) until the 3rd of March. Conferences are a great way to present your own work or learn about various subjects within behavioral neuroscience. And the EBBS meeting is posed to be one of the biggest gatherings in Europe this year. We are already very excited to meet all of you, so make sure to register for the conference and come talk with us about your research questions. EBBS 2025 Society for NeuroScience 2025 November 15-19, San Diego, United States Last but certainly not least, we are of course going to the Society for Neuroscience meeting. Each year we have the unique opportunity to talk to researchers from all over the world in one place, which this year is in San Diego! Known for its famous animal attractions, this year it will focus on animals that may seem less impressive to the public. However, we all know that the world of behavioral neuroscience is just as (if not more) interesting. This year SFN features many events from roundtable discussion to symposia and other presentations. Various topics will be discussed from neural aging and sensory systems to research techniques. We are always eagerly looking forward to SFN! And for the third year in a row, we will provide a cash prize to some lucky researchers who are presenting at SFN. So, if you want to win make sure to follow our socials to get notified of the competition. If you are not presenting but still going to SFN, come by our booth to ask all your questions related to behavioral neurosciences and your (future) Noldus setup. SFN 2025 --- ## Mealtime challenges in dementia: insight in difficulties URL: https://noldus.com/blog/mealtime-difficulties Published: 2025-01-30 13:48:00 Description: Mealtimes can be a daily struggle for people with dementia, but understanding their challenges - and the power of nonverbal communication - can make all the difference. Good nutrition plays a vital role at every stage of life, supporting growth, development, and overall well-being. For young children, it lays the foundation for healthy eating habits; for teenagers, it fuels their evolving needs and active lifestyles; and for adults, it helps maintain health, prevent illness, and promote long-term vitality. In this blog I am focusing on nursing home residents with dementia. These residents have to deal with decline and/or loss of cognitive functions, which eventually can cause problems related to eating behavior such as locating food, chewing, and swallowing. Reducing mealtime difficulties Behavioral symptoms during mealtime are also not uncommon, for example, refusing food or care and responding aggressively towards caregivers or other residents. Because of these so called 'mealtime difficulties', there is a higher risk of inadequate nutritional intake in this population, resulting in weight loss and dehydration. In nursing homes, direct care staff play a key role in mealtime care, providing support and creating opportunities to actively engage residents in eating. Reducing mealtime difficulties may result in better eating, which in turn could lead to better nutrition. Person-centeredness in dementia care People with dementia often experience life from moment-to-moment, which leads researchers to argue that persons with dementia benefit from a person-centered approach. Being compassionate, thinking about things from the person's point of view, and being respectful are all important. Caregivers and residents should work as partners. It's about respect for individuality and supporting individuals, not just acting on their behalf. A person-centered approach in dementia care focuses on strengths and fosters well-being, dignity, trust, and meaningful connection. Using video observations for detailed behavioral research A good research method for this target group is video observations. They allow the researcher to note behavior in detail, and review the videos as needed, including multiple angles. With video, no behaviors get by the researcher, as both video and audio signals can be visualized together and can be played over and over again. The patients being observed are not intruded on, or influenced by, the researcher, and the interaction between the resident and caregiver can be examined in detail. Researchers of course must be sure to receive informed consent for participation from an authorized representative, if the patient cannot provide that for themselves. Dyadic mealtime behaviors Researcher Andrea Gilmore-Bykovskyi observed the interaction between residents of nursing homes and their caregivers during breakfast or lunchtime (with an average of two video observations per resident). They developed a computer-assisted coding scheme to measure the caregiver's person-centered actions versus task-centered actions, as well as resident behavioral symptoms. This type of coding scheme allowed the researchers to capture all interactions between two or more persons. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Prior to the coding of the observations, all video and audio data were cleaned. Researchers determined the feasibility, ease of use, and the inter-observer reliability of this coding scheme. All data was then coded by four trained observers using The Observer XT. Transform raw video data into structured, analyzable information Another study performed by Liu et al. explains that using coding schemes are essential for systematically analyzing video observations. The research team analyzed the nonverbal interactions between nursing home staff and residents with dementia during mealtimes, exploring how individual characteristics influenced these behaviors. Researchers coded 110 videotaped observations, involving 25 residents and 29 staff members (forming 42 unique staff-resident pairs) across nine nursing homes. The refined Cue Utilization and Engagement in Dementia Mealtime Video-Coding Scheme was used to systematically assess these interactions. Antecedents for behavioral symptoms In the study of Gilmore-Bykovskyi, data indicated that 95% of the caregiver actions were person-centered. The most common were orientation, showing interest, giving choices and back channeling, adjusting to resident's pace, and assessing comfort. In addition to providing further evidence that person-centered actions are preferred, this study provides a useful coding scheme to assess the relationship between caregiver-centeredness and behavioral symptoms during mealtime interactions. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Enhancing mealtime engagement through nonverbal cues The study of Liu's research team found that nonverbal behaviors played a significant role in mealtime interactions between nursing home staff and residents with dementia. Certain resident characteristics, such as cognitive and physical abilities, influenced their engagement and responsiveness to staff cues. Similarly, staff members' nonverbal communication, including gestures, facial expressions, and touch, impacted residents' participation in the mealtime process. The findings emphasize the importance of nonverbal communication in promoting positive dining experiences and improving care strategies for individuals with dementia. References - Gilmore-Bykovski, A.L. (2015). Caregiver person-centeredness and behavioral symptoms during mealtime interactions: Development and feasibility of a coding scheme. Geriatric Nursing, (36). https://doi.org/10.1016/j.gerinurse.2015.02.018 - Gilmore-Bykovski, A.L., Roberts, T.J., Bowers, B.J. & Brown, R.L. (2015). Caregiver Person-Centeredness and Behavioral Symptoms in Nursing Home Residents With Dementia: A Timed-Event Sequential Analysis. Gerontologist, (55). https://doi.org/10.1093/geront/gnu164 - Liu, W.; Perkhounkova, Y.; Williams, K.; Batchelor, M. & Hein, M. (2022). Mealtime nonverbal behaviors in nursing home staff and residents with dementia: Behavioral analyses of videotaped observations. Geriatric Nursing, (44), 112-124. https://doi.org/10.1016/j.gerinurse.2022.01.009 --- ## 5 Must-read articles to explore human behavior and emotions URL: https://noldus.com/blog/explore-human-behavior-and-emotions Published: 2025-01-14 13:21:47 Description: Studying human behavior reveals surprising insights about what drives our actions and emotions. In this blog, we share five insightful articles that explore what behavior is, how emotions are made, and the tools researchers use to study them. Human behavior is endlessly fascinating. From understanding early infant development to exploring how our emotions are constructed. 5 articles you shouldn't miss Learn how to study human behavior with practical tools and techniques. Dive into what behavior really means and uncover the many forms it takes, from visible actions to internal processes. Rethink your understanding of emotions by exploring how emotions are made and discover the complex connection between mind and body in the science of emotions. Finally, see how the field of developmental psychology is evolving in research examples of developmental psychology. The five blog posts highlight tools like The Observer XT, which allows for detailed behavioral coding and analysis, and Viso, a tool for recording and reviewing participants behavior and interactions in real-time. To simplify your multimodal research, NoldusHub integrates data streams from multiple devices to provide a comprehensive view of behavior. FaceReader automatically analyzes facial expressions to detect emotions, adding an objective layer to emotion research. 1. What is behavior? Behavior includes all actions and reactions of humans and animals, from simple reflexes to complex thoughts. The blog post "What is Behavior?" delves into this topic. It explains that behavior is about observable activities like walking or speaking, known as overt behavior. But it also includes internal mental processes such as thinking and feeling, referred to as covert behavior. The blog post also highlights social behavior, which involves interactions between individuals. Social behavior plays a key role in forming relationships, building communities, and shaping societal norms. By reading this post, you'll gain a clearer understanding of the various forms of behavior and the factors that influence them, providing valuable insights for anyone interested in the study of human and animal actions. Read more: What is behavior? 2. How to study human behavior Whether you're a student, a professional, or just fascinated by human behavior, this post offers practical tips and tools you can use to better understand human behavior. It introduces key research approaches, including observation, physiological measures, and implicit measures. Explore this blog post if you are curious about why people behave the way they do and want to learn how to study human behavior. Reading this blog post will help you: - Understand research methods like observation and physiological measures - Learn practical tools for studying behavior in real-world settings - Explore applications of behavior research in fields like psychology, education, healthcare, and marketing The blog is a helpful guide if you're planning a research project or want tips on how to observe and analyze everyday behavior. Read more: How to study human behavior 3. How emotions are made Ever wondered how your brain creates emotions? The blog post "How emotions are made" dives into this fascinating question, challenging the idea that emotions are automatic responses. Instead, it explains that emotions are built by the brain, using past experiences to make sense of what we feel and perceive. This approach reshapes how we think about emotions — not as universal reactions, but as personal and context-dependent. The post also explores how this understanding can impact fields like psychology, education, and even artificial intelligence. By reading this post, you'll learn how emotions work and discover new ways to think about them. This knowledge is useful for researchers and anyone curious about the human mind. Read more: How emotions are made FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download 4. Research examples of developmental psychology This blog highlights real-world studies, from how infants develop motor skills to the surprising ways teenagers form social connections. It even touches on how adult brains adapt as we age. Whether you're a researcher or simply fascinated by human development, this blog post offers a comprehensive overview of studies examining how individuals evolve from infancy through adulthood. Read more: Research examples of developmental psychology PRODUCT PORTFOLIO Innovative solutions for psychology research Check out this portfolio of tools and solutions for psychology research, focusing on the observation and analysis of human behavior. These integrated solutions are designed to streamline your research process, from data collection to analysis, ensuring high-quality, reliable results. Get your copy instantly 5. The science behind your emotions Emotions shape our daily lives, influencing decisions and interactions. Emotions are complex and multifaceted. How do our brain and body create these feelings? Understanding the biological processes behind emotions offers valuable insights into the connection between mind and body. In this blog post, the role of the limbic system is explained — a complex network deep within the brain that processes emotions like fear, happiness, and anger. For instance, when you encounter a threat, the amygdala triggers a fight-or-flight response, preparing your body to react. The post also highlights the impact of hormones like cortisol and dopamine, showing how they influence our emotional states and physical reactions. Read more: The science behind your emotions Better insights in human behavior and emotions Through these five blog posts, we've explored essential concepts and innovative research that shape how we study, interpret, and apply behavioral science. Whether you're looking for inspiration, practical tools, or just a deeper understanding of what makes us human, there's something here for you. Which topic intrigued you the most? --- ## Eating behaviors in childhood obesity URL: https://noldus.com/blog/delayed-gratification-eating-behavior-children Published: 2025-01-10 08:43:00 Description: Is time spent looking at food related to eating behavior? Researcher Lundquist and her colleagues studied the relationship between delayed gratification and consumption of food. Worldwide, childhood obesity is a growing health issue. The World Health Organization (WHO) argues that children should do more physical activity and eat less energy-dense, nutrient-poor foods. What can we do to improve children's eating behaviors? In this blog post, we tell you a little more about a study by researcher Ella Lundquist of the Pennsylvania State University and her colleagues at the University of Kansas Medical Center and Children's Mercy Hospital. As part of a larger study on the effects of commercials on food intake, they studied the relationship between children's behaviors during a delay of gratification task and eating behaviors during test meals. Self-control and obesity One of the factors that is important in both the cause and potential treatment of obesity is self-control. Self-control is the ability to regulate one's own emotions, thoughts, and behaviors. It consists of multiple facets, including delay of gratification. Delay of gratification is the process of resisting an immediate reward in favor of a later, more valuable reward. When studying the ability to delay gratification, researchers typically present children with a rewarding food and tell them that they can get more if they are willing to wait for an undisclosed amount of time. For example, a child may choose to get one marshmallow immediately, or to get two if he or she waits (usually for five to twenty minutes). The idea is that the length of time a child can wait for the reward is indicative of self-control, particularly in relation to food. Looking at food = attentional bias? Indeed, studies have shown that poorer performance on a delayed gratification task is related to the development of obesity. However, other researchers argue that waiting times may simply reflect how valuable the food item is to the child. Moreover, there is no clear guidance for how long children should wait, possibly limiting the validity of the task. An alternative to observing waiting time is to identify behaviors during the task that are more generally related to overeating. Specifically, coping strategies such as looking away from food can help extend waiting time. On the other hand, greater time spent looking at food may reflect an attentional bias and present a potential risk factor for obesity. Lundquist and her team observed these behaviors during a delayed gratification task, in a group of children aged seven to nine years old. They predicted that children who spent more time focused on food, sitting still, and staying silent would have a higher energy intake at subsequent meals. They also hypothesized that these behaviors would be associated with a greater intake of high energy-dense foods. Want to set up your own observational lab? Read on to get practical tips and see real-world examples. Observing looking behaviors The researchers included a sample of 40 children in their study, of which 24 had a healthy weight and 16 were overweight or obese. They were studied during three laboratory visits. On the first visit, children ate a meal and then completed a delayed gratification task about 30 minutes later. On visits two and three, children viewed a commercial (about food or toys) prior to eating a meal. At each test meal, children could eat as much as they wanted. During the delayed gratification task, children's behaviors were videotaped and coded using The Observer XT. Researchers observed looking behaviors, verbal distractions, and movement. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Looking behaviors and food intake Results showed that children who spent more time looking at food during the delayed gratification task ate more during the subsequent meals. They also ate more energy-dense foods. Furthermore, the researchers found that children who spent more time diverting their attention away from food tended to eat less at laboratory meals. No significant results were found for verbal distractions or movement. These results are in line with the study's predictions and provide valuable insights into children's reactions to food cues. The researchers suggest that future research could also include observations of behaviors during meals, or study behaviors in a delayed gratification task with non-food items. Understanding more about how eating behaviors are influenced remains important in preventing and treating childhood obesity. Reference Lundquist, E.; Austen, M.; Bermudez, M.; Rubin, C.; Bruce, A.; Masterson, T.; Keller, K. (2019). Time spent looking at food during a delay of gratification task is positively associated with children's consumption at at libitum laboratory meals. Appetite, 141, doi: 10.1016/j.appet.2019.104341. Frequently asked questions How does eating behavior in early childhood relate to obesity later in life? Eating habits formed in early childhood can influence a child's risk of developing obesity later on. For example, consistent fast eating or overeating during childhood is associated with a higher body mass index (BMI) and a greater chance of obesity in adolescence and adulthood. What role does parental behavior play in preventing childhood obesity? Parents have a strong influence on their children's eating pace and portion control. Modeling slower eating, providing healthy meals, and creating a calm mealtime environment can reduce the risk of obesity by encouraging better self-regulation and awareness of hunger and satiety cues. Is there a link between screen time during meals and obesity in children? Yes, studies have shown that screen use during meals can lead to distracted eating, faster eating, and higher calorie intake. This behavior is associated with an increased risk of childhood obesity, as children may eat more than they need without noticing fullness signals. Can schools help reduce obesity by addressing eating pace? Schools can support healthy eating habits by providing enough time for lunch, encouraging calm eating environments, and incorporating nutrition education. These strategies can help children slow down their eating and contribute to long-term obesity prevention. Why is it important to measure eating pace in obesity research? Eating pace is a measurable behavior that provides insights into how much and how fast children eat. Studying this behavior helps researchers understand one of the many contributing factors to obesity and develop targeted interventions that can promote healthier eating habits. --- ## Unlock the full potential of your research tools URL: https://noldus.com/blog/unlock-the-full-potential-of-your-research-tools Published: 2025-01-07 10:00:00 Description: Unlock the full potential of your research with Noldus Academy. Discover expert-led courses, on-demand tutorials, and webinars that help you master Noldus software, boost efficiency, and ensure high-quality data collection. If you're conducting behavioral research, you know how crucial it is to have tools that not only work well but also integrate seamlessly into your research workflow and lab team. But even the most advanced tools can't offer their full value unless you know how to use them efficiently. This is where Noldus Academy comes in. What is Noldus Academy? Noldus Academy is an online learning platform designed to help you master Noldus software such as EthoVision XT, The Observer XT, CatWalk XT, and NoldusHub. Through structured courses, video tutorials, webinars, and interactive resources, Noldus Academy empowers you to work smarter, not harder. But the real question is: Why should you use Noldus Academy? NOLDUS ACADEMY Unlock the full potential of your research tools Discover expert-led courses, on-demand tutorials, and webinars that help you master Noldus software, boost efficiency, and ensure high-quality data collection. - Onboarding courses on EthoVision XT and The Observer XT - A video series on CatWalk XT - Many webinars on various behavioral research topics Show me Noldus Academy 1. Maximize the value of your Noldus research tools You've invested in powerful research software — but are you using it to its full potential? With Noldus Academy, you'll gain step-by-step guidance, hands-on exercises, and insights into advanced features that can take your research to the next level. Whether it's automating tasks in EthoVision XT or creating structured coding schemes in The Observer XT, you'll learn how to get more done in less time. Customer example: "Thanks to the EthoVision XT course, I learned how to track multiple animals in one arena. I was surprised by how much time I saved once I understood how to set it up correctly!" 2. Minimize downtime with on-demand learning When you hit a roadblock during your research, waiting for support or troubleshooting on your own can slow you down. Noldus Academy's on-demand courses and video series mean you can find answers whenever you need them. Whether you're onboarding new team members or refreshing your own skills, you'll always have a resource library at your fingertips. Convenience in action: - Learn at your own pace — no need to schedule training sessions. - Access tutorials anywhere, anytime. - Get immediate answers through detailed walkthroughs. 3. Stay ahead with webinars and updates Behavioral research and software tools are constantly evolving. Noldus Academy helps you stay informed through regular webinars and updates on new software features. Learn directly from Noldus experts and discover best practices that will keep your research innovative and competitive. 4. Train your team and build confidence If you manage a research team, you know that training everyone to the same level of competence is a challenge. Noldus Academy offers a structured approach to training that ensures everyone on your team is confident and consistent in their use of Noldus software. Certified courses mean you can trust that your team members have a reliable foundation (which also makes your data more consistent!). Upon completing a course, team members receive a certificate of achievement — perfect for professional development and motivation. 5. Get more out of NoldusCare If your lab has a NoldusCare plan, you get exclusive access to Noldus Academy content, priority support, and software updates. This means you're always working with the latest features and benefiting from direct support when you need it. What Noldus Academy users are saying "The Observer XT training made coding sessions so much more efficient. The examples and tips were clear and easy to follow. I feel much more prepared now!" — Researcher, University of Ottawa "We used Noldus Academy to onboard new lab members—it saved us hours of in-person training and gave them confidence from day one." — Behavioral Neuroscience Lab Manager Why Noldus Academy matters At the heart of every successful research project is a team that knows how to use their tools effectively. Whether you're conducting zebrafish studies, gait analysis, or complex coding projects, the right training ensures your data is accurate, your workflow is efficient, and your results are meaningful. Noldus Academy isn't just about learning — it's about empowering you to conduct better research. Ready to make the most of your Noldus tools? Visit Noldus Academy to start learning today and experience how smarter training leads to better research. --- ## How to measure audience engagement URL: https://noldus.com/blog/benefits-of-implicit-and-explicit-measurements-of-engagement Published: 2025-01-07 09:21:38 Description: Everyone wants to know if people are truly engaged with their content. But how do we accurately measure engagement? In this blog post, researchers from VicarVision share how they studied cognitive, affective, and behavioral engagement. In this blog post, Tess den Uyl, PhD from VicarVision shows how to measure engagement in different ways. Everyone wants to create engaging content and learn if people are truly engaged. But how do we accurately measure engagement? Nicholas Keatch's research project, part of his academic focus on social psychology, aimed to explore the intricate nature of engagement. In his study, he examined how people interact with movie trailers—emotionally, cognitively, and behaviorally. Importantly, this study included both self-reported and implicit measures. What is engagement? Engagement refers to an active involvement and emotional connection with a product, brand, or experience. It goes beyond attention—it's about how someone is interacting with a brand. Engagement plays a vital role in how people interact with different types of content, whether it's advertisements, movie trailers, or educational videos. By studying engagement, marketers and UX researchers have an indication of how much someone is interested in their content. In fact, for most video marketers, engagement is the most important metric. Different types of engagement In this study, Keatch examined how engaged people were with different movie trailers. To study engagement, he used a model based on Ben-Eliyahu's (2018) framework and previous work by Noldus intern Dayenne Sarkol. This model divides engagement into three key dimensions: - Cognitive engagement: how well viewers concentrate on the content and maintain their attention - Affective engagement: emotional responses to the content, such as interest, positive attitude, involvement, and motivation - Behavioral engagement: actions taken as a result of engagement, like recommending, sharing content, or interacting with the brand In Sarkol's work on engagement, she found that a real-time expression of engagement was too complex to capture all three aspects at once. Therefore, the current project focused on measuring the separate components of engagement. Measuring engagement Keatch recruited 75 participants for this study, through platform Prolific and personal invitations. Participants watched three movie trailers from different genres: My Spy: The Eternal City (action-comedy), Fly Me to the Moon (romantic-drama), and Paddington in Peru (family-comedy). Each trailer was divided into two parts. Participants had the option to either continue watching or switch to another trailer after the first part. Their decisions provided an implicit measure of behavioral engagement. Additionally, we used FaceReader Online to measure implicit cognitive and affective engagement. We did so by detecting facial expressions like happiness, sadness, and attention. We also measured explicit cognitive, affective, and behavioral engagement through self-reports. By using both implicit and explicit measures, we aimed to understand engagement more completely. MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now Engagement when staying vs. switching As expected, self-reported engagement was higher for participants who chose to continue watching rather than switch trailers. Decisions to switch were roughly around 50%. Specifically, behavioral and affective engagement were significantly higher in those who continued watching the trailers. However, the cognitive component (e.g., concentration) showed only marginal significance. Interestingly, this pattern was not consistent across all trailers. - Participants who chose to keep watching the Paddington trailer scored higher on all engagement components. - Those who continued watching Fly Me to the Moon only showed higher affective engagement. - For My Spy, there was no difference in explicit engagement between the group that stayed and the group that switched. Implicit engagement: facial expressions reveal different dynamics Facial expression analysis provides an implicit way to measure reactions that are automatic and beyond conscious control. Using FaceReader Online, we analyzed happiness, which is indicated by smiling and laughter. Both of these behaviors are important to measure affective engagement. In addition, we used FaceReader Online to measure cognitive engagement, by estimating the visible attention participants gave to the screen. The implicit responses showed interesting differences between trailers. - In the Paddington trailer, people who decided to continue watching had, on average, 15% higher attention scores. This indicates increased cognitive engagement. - For Fly Me to the Moon, affective engagement was evident. People who kept watching showed a mean happiness level that was three times higher than those who switched. - For My Spy, there was no difference in mean facial expressions between those who stayed and those who switched. However, an interesting emotional dynamic emerged—participants found a particular joke funny, but it did not persuade them to continue watching. One advantage of facial expression analysis is its ability to capture immediate, real-time responses. That's how we learned that across all trailers, larger peaks in happiness were observed for those who decided to continue watching. You may also like to read about how perception of brand authenticity affects brand performance or how to increase attention in commercials for Gen-Z. The value of combining implicit and explicit measures Engagement is a complex, multidimensional construct. The varied responses to each trailer highlight the difficulty of measuring engagement and the importance of understanding the context. Using both implicit and explicit responses allows for a more accurate and nuanced understanding of engagement. This dual approach makes it possible to predict viewer behavior more effectively. As a result, professionals in fields like entertainment, advertising, and education can improve their content creation strategies. By employing tools like FaceReader Online, content creators can test the effectiveness of videos with implicit and explicit measures to measure engagement comprehensively. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources --- ## Why sustained attention matters in infant development URL: https://noldus.com/blog/why-sustained-attention-matters-in-infant-development Published: 2024-12-17 10:23:46 Description: How does sustained attention develop in infants and why is it crucial for learning? Learn about the latest research measuring attention through video and heart rate data. Imagine a baby staring intently at a toy, completely focused despite the sounds and movements around them. This ability to tune out distractions and concentrate on one thing is called sustained attention. It is a key skill that helps infants explore and make sense of their world. Unlike a quick glance, sustained attention shows deeper cognitive engagement. This focused attention is essential for learning and development, setting the stage for skills like problem-solving, communication, and self-control. It can be measured through behavioral cues like looking duration or physiological indicators such as heart rate. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly How researchers study infant attention To better understand how infants develop sustained attention, researcher Jessica Bradshaw and her team from the University of South Carolina designed a unique study. The blend of tools, methods, and long-term observation used in this study provided valuable insights into how infants process and interact with their environment. Their goal was to explore how sustained attention changes in infants over time and whether factors like context (live interactions versus screen-based tasks) or the type of stimulus (social versus non-social) make a difference. A longitudinal study on social development The study followed 53 infants from 1 to 24 months old. Each infant took part in multiple sessions, spaced across their first two years of life. During these sessions, the researchers measured attention during four different tasks: - Watching social videos (e.g., people or puppets interacting) - Watching non-social videos (e.g., animations or scenes with objects like dominoes or moving toys) - Social interaction with a caregiver (like face-to-face play) - Playing with toys without caregiver interaction Combining video and heart rate data to track attention To understand how deeply engaged the infants were, the researchers used a combination of behavioral observations and physiological data. They recorded how long infants looked at a specific target, like a caregiver's face or a toy, to capture their visual focus. At the same time, they collected heart rate data using a wireless electrocardiogram (ECG) sensor placed on the infant's chest. Video ensures detailed view The Viso system provided high-quality video footage of the infants during the different tasks, ensuring that the researchers could accurately track the infants' gaze and interactions with the stimuli. This provided a detailed view of not just how long they looked but how deeply they processed what they saw. Out of the data extracted from the behavioral coding, the research team calculated two dependent variables: the percentage of time that infants spent on looking and the average look duration. FREE WHITE PAPER How does AV recording tool Viso work? Discover how Viso can transform your work—download the free white paper to explore its features and security. - How can Viso benefit your work? - What can you expect of the Viso features? - Is data protection guaranteed within Viso? Start downloading By analyzing changes in the time between heartbeats (inter-beat intervals), the researchers identified three phases of attention: - orienting (initial shift of attention to the stimulus) - sustained attention (staying focused) - attention withdrawal (ending of focus, often followed by a look away from the stimulus) Sustained attention, marked by a steady slowing of the heart rate, reflected moments of focused cognitive engagement. These heart rate-defined moments were synchronized with video recordings to determine what the infant was focusing on. Infants' attention patterns The researchers found that infants' sustained attention develops in different ways depending on the task and type of stimulus. Infants showed an increase in looking time from 1 to 4 months across all conditions, but by 4 to 6 months, their looking behavior began to shift. They spent less time looking at caregivers during social interactions, while their attention to toys and videos remained stable. When it came to sustained attention, infants spent more time focused during video tasks (both social and non-social) than during live interactions, especially in the first 6 months. Even though infants looked at their caregivers less during social interactions, their heart rate-defined sustained attention stayed the same. This suggests that looking less at the caregiver didn't mean they were paying less attention to them. More focus on social videos than toys or live interactions Throughout the first year, infants paid more attention to videos (both social and non-social) than to toys, with social videos becoming particularly engaging by 12 months. In contrast, attention to social and non-social stimuli during live interaction tasks was roughly equal. This indicates that video content may be more engaging than real-world toys and interactions during the second half of infancy. From 6 to 24 months, sustained attention stabilized, but social videos continued to draw more attention. The study also suggests that the first 6 months are a period of rapid change in attention, after which attention patterns stabilize but still show preferences for social videos. It's crucial to consider multiple measurements together The results of the study suggest that different ways of measuring attention to social and non-social stimuli may reflect distinct developmental processes. It's important to compare and consider these measures together, especially when using infant attention as an indicator of typical or atypical development. Reference Bradshaw, J.; Fu, X. & Richards, J.E. (2024). Infant sustained attention differs by context and social content in the first 2 years of life. Developmental Science, 27(4). https://doi.org/10.1111/desc.13500 --- ## What is cognitive load, and how does it help us understand human behavior? URL: https://noldus.com/blog/cognitive-load-human-behavior Published: 2024-12-13 12:00:00 Description: By exploring cognitive load, researchers gain insights into how people process information, respond emotionally, and manage decision-making. How cognitive load and one of its most reliable indicators, pupil dilation, is crucial in human behavior research. Ever wonder why some tasks leave you feeling mentally exhausted, while others seem easy and manageable? Cognitive load may hold the answer. Understanding cognitive load helps researchers see how people take in information, handle emotions, and make decisions while performing a task. The mental effort needed to complete tasks and learn effectively plays a big role in shaping how people act and make choices. By measuring cognitive load, researchers gain insights into how people process information, respond emotionally, and manage decision-making. Let's uncover how measuring cognitive load and one of its most reliable indicators - pupil dilation - can be powerful methods in human behavior research. What is cognitive load, and why does it matter? Think of cognitive load as the mental "weight" or effort required for your brain to process information. Like a workbench that can only hold so much, our minds have a limited capacity for juggling information. The more complex or confusing the task, the heavier the load becomes. For human behavior researchers, measuring cognitive load can reveal when a person is reaching mental overload or when tasks are manageable, offering valuable clues about how people think and learn. Using pupil dilation to measure cognitive load How can we measure cognitive workload in a way that's both accurate and non-invasive? One reliable method is pupil dilation: the automatic widening of pupils during mental effort. Pupil dilation is measured with eye-tracking devices that use near-infrared spectrum light to monitor changes in pupil size. This non-invasive method tracks dilation in real-time during tasks, linking cognitive load and emotional responses to specific stimuli. Here's how it works and why it's useful for researchers: - Cognitive demand: When we focus on something challenging, our pupils dilate as the brain increases mental effort. For researchers, this makes pupil dilation an indicator of cognitive load, especially during complex tasks or learning sessions. - Emotional insight: Our pupils can also reveal emotional responses. If a person feels stressed, excited, or frustrated, these emotions show up in pupil dilation too. This helps researchers distinguish between pure mental effort and emotional reactions to a task. - Decision-making challenges: Pupil dilation can signal moments when a person is struggling to make a decision. The more challenging or uncertain a choice, the more likely pupil dilation will reflect this extra mental workload. Combining pupil dilation with multimodal tools for a full picture For researchers studying human behavior, relying on a single indicator provides valuable insights. When paired with other measurements, it offers a fuller picture of the cognitive and emotional experiences underlying behavior. If pupil dilation tells us when mental effort increases, then combining eye tracking with other physiological measurements can reveal the full story of how people think, feel, and respond. Measuring cognitive load doesn't stop with pupil dilation alone. Multimodal research This approach, known as multimodal research, combines data from different sources, such as ECG (which measures heart activity), EDA (which tracks changes in skin conductance), and skin response sensors (which detect changes in emotional state). Together, these tools allow researchers to capture real-time insights into what people are thinking, feeling, and how they're engaging with tasks or stimuli. Here's how these methods work together: - Experiments and testing: Researchers often set up experiments to track how pupils change during certain tasks. By combining this data with heart activity from ECG, which indicates physical stress or arousal, or skin conductance from EDA, which reflects emotional or cognitive engagement, they gain a detailed view of cognitive and emotional responses to various tasks. - Improving design and UX: In user experience (UX) research, understanding cognitive load helps designers make products that are easier to use. For example, tracking pupil dilation during interaction with an app can reveal which features cause mental strain. This data, paired with physiological responses like increased heart rate, helps refine designs for better usability. - Psychophysiology in real-time: Pupil dilation is also used in psychophysiology, a field that studies how the body responds to mental processes. For instance, combining pupil data with skin conductance can show how stress levels change moment by moment during a task, offering insights into how cognitive load affects behavior and decision-making. Effective tool for multimodal research: NoldusHub Combining multiple types of measurements can be challenging, especially when you use several acquisition tools that must be calibrated and started. NoldusHub is a comprehensive tool designed to streamline multimodal studies, providing direct, pre-processed data on cognitive load and other measurements. It allows researchers to collect and synchronize data from various sources, including eye-tracking devices, physiological sensors, and facial expression analysis, all within a single interface. By utilizing NoldusHub, researchers can: - Integrate multiple data streams: Simultaneously record and synchronize data from eye tracking; like point of gaze and fixation, and pupil dilation, heart rate, skin conductance, and other physiological measures, providing a holistic view of cognitive load. - Get direct cognitive load measurement: NoldusHub uses pupil dilation to measure cognitive load, automatically correcting for light intensity. This provides immediate, pre-processed cognitive load data, saving researchers time and effort in data analysis. - Enhance data accuracy: NoldusHub ensures precise synchronization of all data streams, reducing the risk of errors and enhancing the reliability of findings. - Simplify data management: With a user-friendly and intuitive interface, NoldusHub simplifies the setup, recording, and analysis processes. This allows researchers to focus more on their studies and less on technical complexities. - Export their data: The software provides data files for each recorded modality, including cognitive load data, enabling detailed post-experiment analysis. Why cognitive load research matters Understanding cognitive load through tools like pupil dilation and multimodal measurements allows researchers to uncover how people think, feel, and act. These insights help improve learning environments, make technology more intuitive, and support better decision-making processes. Cognitive load is more than mental strain; it's a key to understanding the mechanics behind our thoughts and actions. Cognitive load isn't just about mental strain. It offers a window into how we process thoughts, emotions, and decisions, allowing researchers to track cognitive effort as it happens. New possibilities in human behavior research By leveraging pupil dilation and combining it with other multimodal methods, researchers can explore human behavior with greater precision. These approaches open doors to new discoveries, offering deeper insights into how we learn, solve problems, and adapt to our surroundings. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more --- ## Validating FaceReader's attention detection: a reliable measure using gaze and head pose URL: https://noldus.com/blog/validating-attention-detection-facereader Published: 2024-12-03 08:05:49 Description: Measuring attention is crucial across many fields, from marketing to user experience design and human-computer interaction. Learn more about how we validated custom expressions for attention in FaceReader. In this blog post, Tess den Uyl, PhD from VicarVision highlights how to use custom expressions to measure attention. Measuring attention is crucial across many fields, from marketing to user experience design and human-computer interaction. Learning more about people's attention helps assess the effectiveness of advertisements. For example, people who pay closer attention to ads are more likely to develop positive feelings toward a brand and make repeat purchases. In user experience research, tracking attention helps to understand what users focus on and how they engage with content. This kind of data helps designers create better interfaces. Easy gaze tracking with FaceReader Traditionally, attention is measured using eye trackers. These systems are highly effective. However, they require you to get additional software and also need an extra calibration step. This can be both expensive and time-consuming. In contrast, facial analysis tools like FaceReader only need a webcam. Easy to access and efficient! To make sure that FaceReader is effective when measuring attention, we validated several custom expressions we created. FREE WHITE PAPER Eye tracking & FaceReader Download this white paper to learn about: - Subconscious processes and emotion recognition - Combining FaceReader™ and eye tracking - Visualizing and analyzing your data Submit to download Studying attention To create a robust dataset for the validation of attention detection, we used two approaches: - We selected participants from previous studies - We recruited additional participants and instructed them to vary their attention, like looking away or checking their phones This approach gave us a dataset of 101 participants, each providing an average of 1.5 minutes of video footage. Manual labeling: very time-intensive We labeled the videos manually, based on a predetermined protocol, resulting in a high inter-rater reliability score of 99%. Manual labeling involves reviewing videos frame-by-frame to categorize behaviors. This involves a lot of work but is needed to have a robust basis for the comparison of custom expressions later in the experiment. Different types of attention Attention is a complex process. It involves both someone's internal cognitive focus and the more visible external signs of attention. In our study, we focused on external, visible cues like head orientation and gaze direction to assess attention. Results of this type of measurement might differ from a participant's self-reported attention, which often involves internal, subjective elements. That's why it's so valuable to capture both implicit (visual) and explicit (self-reported) measures of attention. It helps us to discover the full story. Improving detection of attention We created several custom expressions to find the most effective combination for attention detection. We mostly focused on gaze and head movements. For each custom expression, we measured: - Sensitivity: accuracy in detecting attention - Specificity: accuracy in detecting when attention was absent Some participants faced challenges, such as poor lighting or partial visibility, which could have influenced results. We used median scores to minimize the effect of these outliers. Finding the best custom expression FaceReader's custom expressions use thresholds on different inputs, like facial action units and head orientation. The custom expressions functionality in the Action Unit module allows you to include many simple and complex operations. Using only head rotation measures—yaw and pitch—resulted in high sensitivity but low specificity. In other words, these measures were accurate in detecting attention, but not in detecting when attention was absent. When we included gaze direction as well, it significantly improved specificity, making attention classification much more reliable. In conclusion, this is a well-validated custom expression with a high average accuracy of 0.87, optimizing sensitivity (0.88) and specificity (0.85). Handling challenging situations There are challenging scenarios that can complicate attention detection. For example, in cases where participants turned their heads but kept their eyes focused on the screen, a more complex custom expression was needed to maintain accuracy. Adding additional calculations allowed us to better handle these challenging scenarios. This approach increased complexity but made attention detection more reliable. Read more blog posts about consumer behavior research. Applying attention metrics in your own research Interested in using this attention detection metric for your own research? It's easy to get started. If you already use the FaceReader desktop software and have the Action Unit module, you can immediately begin analyzing attention with the included custom expression for attention. We also offer other pre-made custom expressions—feel free to contact us if you're interested in accessing these! FaceReader online as a flexible tool For those who prefer online tools, FaceReader Online is a great option. It's designed for professionals in fields like advertising, market research, and user experience. With FaceReader Online, you can evaluate which type of content draws the most attention, making data-driven decisions easier. Want to try for yourself? Request a free trial and get started right away! Measure attention to improve your research FaceReader's attention detection offers a reliable way to understand where participants are focusing. Specifically, our study shows that combining gaze and head pose measurements results in the highest accuracy of attention detection. Whether for marketing, user experience, or psychology research, FaceReader helps you create a more informed view of audience engagement. --- ## Reducing eating pace: a behavioral intervention for childhood obesity URL: https://noldus.com/blog/eating-pace-children-obesity Published: 2024-11-25 13:02:00 Description: Studies on eating behavior play an important role in preventing childhood obesity. Faith and his team examined the effectiveness of a family-based behavioral intervention to reduce eating pace. The prevalence of childhood obesity has grown substantially over the last years. Recent estimates suggest that, globally, as many as 37 million children under the age of 5 are overweight. When looking at the ages between 5 and 19, these numbers rise to a staggerng 390 million. As a result, childhood obesity is considered one of most serious public health challenges of the 21st century. Children who are overweight suffer from many short-term and long-term health problems. From a young age, they are at risk for diabetes, physical disabilities, certain types of cancer, and heart disease. Overweight and obese children are also likely to stay obese and maintain these health risks into adulthood. The World Health Organization (WHO) emphasizes that becoming overweight can largely be prevented. Specifically, they recommend increasing physical activity and decreasing the intake of energy-dense, nutrient-poor foods. High eating rate and obesity One way to decrease the intake of unhealthy foods is by changing one’s eating rate. Eating rate describes the amount of food that is consumed within a given time frame, often measured as mouthfuls or kilocalories per minute. Research has shown that a high eating rate during childhood is associated with obesity and expedited weight gain. However, reducing eating rate in children has received little attention so far. Furthermore, the few studies on this subject only focused on older children or adolescents. That's why researcher Faith and his team examined the effectiveness of a behavioral intervention for young children (RePace). This family-based treatment is designed to reduce eating rate and includes different educational and behavioral techniques to influence eating behavior. Learning to eat more slowly The researchers included 28 parent-child dyads in their study, with children between four and eight years old. To participate in the study, both the parent and the child had to be overweight or obese, and children had to display a rapid eating rate. Families attended five interactive meal sessions at a laboratory, which were focused on raising awareness of eating speed, learning to eat more slowly, and increasing social interactions during meal times. For example, rabbit and turtle puppets were used to show the difference between fast and slow eating. Families also learned to use a ‘Turtle Timer,’ which vibrates every 30 seconds and helps children to pace their eating. Lastly, a ‘Chat Jar’ filled with open-ended questions was used to stimulate conversation. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Measuring eating behavior To assess eating rate, researchers asked parents to fill in a questionnaire about their child’s eating behavior. Furthermore, eating behavior was observed in the lab before and after treatment. Observational data was recorded and coded using MediaRecorder and The Observer XT. Researchers also studied BMI scores, a 24-hour dietary intake, and child eating patterns. Particularly, they were interested in changes in responsiveness to satiety and food cues, as well as enjoyment of eating. All measurements were compared to a control group, consisting of families that attended one 30-minute educational session about healthy eating. Changing eating pace Results showed that children from the RePace intervention group decreased their eating rate more than children from the control group, as reported by parents. At first, these differences were not found in the laboratory observations. When examined more closely, Faith and his colleagues found that these results were influenced by how typical a meal at the lab was, compared to a meal at home. Specifically, if the amount of food presented at both meals was similar, children from the intervention group showed a greater decrease in eating rate compared to children from the control group. Better BMI and food enjoyment Researchers also found greater improvements in BMI in children from the intervention group, as well as an increase in food enjoyment. Lastly, when examining families with a high session attendance, results showed a decrease in total energy intake. This study shows that eating rate can be changed effectively with behavioral interventions. Importantly, the results also suggest that changing one’s eating rate has a positive impact on both bodyweight and creating a healthy eating pattern. With the WHO recommendation to decrease intake of energy-dense foods, studies like these play an important role in preventing and reducing childhood obesity. More research is still needed to assess and develop interventions for children from all age groups. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly References Faith, M.; Diewald, L.; Crabbe, S.; Burgess, B.; Berkowitz, R. (2019). Reduced eating pace (RePace) behavioral intervention for children prone to or with obesity: does the turtle win the race? Obesity, 27(1), 121-129. WHO: Childhood overweight and obesity Frequently asked questions What does eating pace have to do with childhood obesity? Eating quickly has been linked to a higher risk of obesity. Studies show that children who eat faster often consume more food before their body signals that they're full. This can lead to a higher total energy intake, increasing the risk of becoming overweight or obese over time. How do researchers measure eating pace in children? Researchers use video recordings and behavioral coding software like The Observer XT to track bite-by-bite behaviors. They record how long a meal takes, how many bites a child takes, and the time between bites. Some studies also combine this with physiological or observational data, like facial expressions or social interactions during meals. Why do some children eat faster than others? Eating speed can be influenced by several factors, including age, individual temperament, parental modeling, food availability, and even cultural habits. Some children may naturally eat faster, while others may be influenced by external cues like distractions, food restrictions, or pressure to finish quickly. Is fast eating always a bad thing? Not necessarily. But when fast eating becomes habitual and leads to overeating, it can contribute to excess weight gain. Slowing down mealtime—such as by encouraging more chewing, putting down utensils between bites, or using mindful eating techniques—can help children better recognize satiety signals. Can eating pace be changed through interventions? Yes. Behavioral interventions that focus on meal structure, pace, and portion awareness have shown promise. For example, encouraging slower eating through games or structured mealtimes, or using wearable tech to give feedback on bite rate, can help modify eating behavior. What methods are commonly used to study children's eating behaviors? Studies often use video observation, behavioral coding, and software-based analysis tools to analyze mealtime interactions. These methods allow researchers to track precise behaviors, like the number of bites or seconds between bites, in both naturalistic and lab settings. Why is it important to study eating pace in the context of family meals? Because children's eating behaviors are shaped in social contexts. Family meals offer insight into how parent-child interactions, household routines, and emotional cues influence how children eat. Understanding this dynamic helps researchers and health professionals design more effective interventions. --- ## SfN 2024: Noldus reflects on key trends in Neuroscience URL: https://noldus.com/blog/neuroscience-trends-2024 Published: 2024-10-24 12:01:00 Description: The Society for Neuroscience (SfN) 2024 conference is behind us! What did we spot as the latest trends? And will we be joining the conference again next year? The Society for Neuroscience (SfN) 2024 conference is behind us! And it was an inspiring event for our Noldus team, as we connected with researchers, talked about known research paradigms, and also explored the latest developments in (behavioral) neuroscience. This year, several key trends emerged, and they closely align with our commitment to advancing behavioral research through flexible, reliable solutions like EthoVision XT. Here is our take: Complex behavioral setups: A balance of innovation and fundamentals One of the most interesting observations at SfN 2024 was the increasing complexity of behavioral research setups. Researchers are pushing beyond traditional paradigms, using elaborate systems such as location-based stimuli, custom maze protocols, and sophisticated multi-room experiments. These innovations reflect the growing need to explore behavior in more dynamic and intricate environments. It’s exciting to see how researchers are thinking outside the box and embracing novel methodologies. However, while these complex setups are certainly on the rise, it's important to note that basic behavioral tests remain just as essential. Simple and known paradigms, like the open field test or other relatively straightforward mazes, are still fundamental for quantifying core behaviors such as locomotion, anxiety, or cognition. These tests continue to provide reliable, quantifiable data that allow researchers to understand essential behavioral phenotypes before moving into more advanced experimental designs. EthoVision XT, a flexible system At Noldus, we’ve designed EthoVision XT to thrive in both worlds. Whether you're conducting a basic open field test or a complex custom experiment, our software adapts effortlessly, providing the precision and flexibility needed to capture meaningful behavioral data in any setup. The feedback we received from researchers at SfN reaffirms this, showing that EthoVision XT is not just for either advanced or simple setups: it's for both. This versatility ensures researchers can transition seamlessly from basic to complex experiments without compromising on data quality. Integration of E-Phys and behavioral data Another major theme at SfN 2024 was the growing demand for integrating electrophysiological (e-phys) data with behavioral data. Researchers emphasized the need to synchronize these two data streams, allowing them to correlate neural activity with behavior more precisely. However, achieving this integration is technically challenging, particularly when dealing with real-time data collection. This is where our collaboration with Blackrock Neurotech really makes a difference. The integration of EthoVision XT with Blackrock’s implantable EEG systems provides researchers with the ability to synchronize e-phys and behavioral data. This allows for highly accurate, real-time insights into how brain activity drives behavior, offering a new level of understanding for researchers investigating neural circuits, cognitive function, and neurodegenerative diseases. AI in behavioral tracking Just like we’ve seen last year, artificial intelligence (AI) remains a prominent trend in (behavioral) neuroscience, particularly for behavioral tracking. At SfN 2024, the use of trained neural networks to interpret animal behavior was a recurring theme. Many research labs are turning to AI to automate the tracking and analysis of complex behaviors, enhancing precision while reducing manual effort. Noldus' use of AI in EthoVision XT At Noldus, we’ve been ahead of this trend with EthoVision XT’s deep learning tracking method. What sets our approach apart is that the AI powering EthoVision XT was developed in-house by our team of behavioral neuroscientists. Our deep learning model was trained on real-world behavioral data, making it ready to use, very reliable, and tailored specifically for behavioral research. Unlike other generic AI tools, EthoVision XT is designed to provide accurate, actionable insights without requiring users to code, build, or train their own models. Researchers appreciate that they can trust our AI to deliver results that are both scientifically validated and easy to interpret. TRY EthoVision XT FOR FREE arrow_forward The rising demand for educational materials: Noldus Academy Another key takeaway from SfN 2024 was the increasing demand for educational materials. As neuroscience research grows more complex, more-and-more researchers from other disciplines are incorporating behavior into their research. Since this group is ever-growing, they need access to high-quality training resources to help them master new tools and methodologies. With NoldusCare you get access to such materials through the Noldus Academy, an online platform offering courses, training modules, and (on-demand) webinars designed to help researchers get the most out of our tools. Whether you’re just starting with EthoVision XT or looking to expand its capabilities, the Academy provides step-by-step guidance. In addition, our e-books cover various topics in behavioral research, offering insights into experimental design, data analysis, and best practices for using our software. The feedback from researchers at SfN was clear: educational resources like these are becoming increasingly essential as the field continues to grow in size and continues to advance. Free e-book Basic behavioral neuroscience in rodents Want some more literature on the basic (behavioral) neuroscience in rodents? Download our free e-book. In this guide we explain why and how we investigate specific types of behaviors. Our goal is to help you advance your research by providing high quality products and accurate information at a high level. Download arrow_forward Noldus is the gold standard in Behavioral Neuroscience Throughout SfN 2024, we were reminded once again why Noldus is regarded as the gold standard in behavioral neuroscience. Our tools are not only scientifically validated but are also built from the ground up by behavioral neuroscientists who understand the intricacies of the field. Whether researchers are working with simple or complex experimental setups, they know they can rely on Noldus to provide accurate, reliable data that drives meaningful insights. As neuroscience continues to evolve, we stay firmly committed to staying at that forefront, offering tools that meet the needs of the research community. All-in-all our SfN 2024 experience was great! And we will be there again next year, where we would love to meet you (again) in person! See you next year in San Diego. Ready to take the next step? We’re passionate about helping you achieve your research goals. Let’s discuss your project and find the tools that fit. Contact us arrow_forward --- ## 5 examples of infant studies URL: https://noldus.com/blog/infant-studies Published: 2024-10-23 10:25:00 Description: Researchers perform infant studies to properly monitor and understand all kinds of development factors. In this blog post, five examples of infant studies are highlighted. A lot happens in the development of a child and many factors play an important role in this process. For example, the interaction with parents, siblings, and peers, but also various complex processes in the brain that determine how a child processes information, how well it can concentrate, and how the child behaves towards others. The learning abilities and behaviors are extremely important for the way infants develop. Throughout development, a child reaches several milestones, recognizable points in the child's development. An important first milestone in social development is the social smile, which is the smile that a baby gives in response to another. It shows that an infant is a social creature right from the beginning of his or her life. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Infancy research: 5 examples of infant studies It is fair to say that collecting data with infants can be difficult. Especially in the early years of their life, when they cannot speak or when they suddenly don't feel like cooperating during the test. It is hard, or even impossible to explain the importance of cooperation. Besides all this, there is a risk on low replicability, small sample sizes, limited experimental control, and measurements with limited reliability. Nevertheless, research remains important. In this blog post, five examples of infant studies are highlighted. Also interesting to read: 'How to study developmental psychology: methods, designs & tools' to discover what you should consider when setting up a study in the field of developmental psychology. 1. Exploring the early development of referential gestural communication In child development, the pointing gesture is a key milestone that shows the child's ability to share attention and interests and to communicate specific needs or information. We are talking about referential communication - a triadic type of communication because it involves a triangulation of attention between the child, the interaction partner, and a shared focus of interest (e.g. a toy). The research team of Salvadori set out to explore whether early socioemotional communication skills can predict how well a child will later develop the ability to point and use gestures. They also investigated whether a child's natural personality traits play a role in this process. To do this, they used a longitudinal mixed-method approach, combining natural observations, lab-based experimental tasks, and reports from parents. The interactions were coded for socioemotional communication behaviors, using The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial 2. Language development and joint engagement in children with Down syndrome When researchers mention joint engagement, they're talking about the shared focus between a child and their caregiver on an object or activity. It's a social skill where both are involved in watching, interacting with, or talking about the same thing. For all children, including those with Down syndrome, joint engagement is an important step toward developing language. The participants in Mattie's and Fanta's study were 16 young children with Down syndrome. The researchers studied them at two-time intervals. They recorded and analyzed each child's engagement behavior during 15-minute free play sessions between mother and child, using The Observer XT. They focused both on quality and duration of joint engagement behaviors. The research team also measured receptive and expressive language skills at both times. Discover what the results of the study were in the blog. 3. The role of mimicry in the development of social communication You smile at your baby and your baby smiles back! Copying facial expressions is one of the great milestones in the social development of a child. The research team of Eliala A. Salvadori, of the University of Amsterdam, conducted a study to investigate the influence of emotional stimuli on mimicry. The infants (six- and twelve-month-olds) and one of their parents were presented with dynamic videos of unfamiliar adults showing happy, sad, angry, and fearful faces. Using a microanalytic facial coding system, the researchers assessed emotional communication, which included facial expressions and gaze direction. With this study, the researchers wanted to unravel the mechanisms controlling early development of emotional mimicry. Baby FaceReader is a state of the art system to automatically detect infant facial expressions in order to help address questions in developmental psychology. 4. Challenging play behavior: does it still exist? Over recent decades, children are left with fewer opportunities for free play, especially outdoors. Children spend more time indoor in sitting activities, and less time in outdoor play and vigorous physical activity. However, children need feelings of exhilaration now and then. Research indicates that risky play and risk-taking activities increase children's physical activity, improve motor/physical competence, increase spatial and perceptual skills, and enhance their ability to assess and manage risk appropriately. The research team of Ellen B.H. Sandseter addressed the question how risky play is connected to spaces and materials in the physical play environment. The extensive dataset of observations that they gathered, coded, and analyzed using The Observer XT, allowed the researchers to quantify the various behaviors and conclude which risky behaviors occurred, with which toys or tools, in what spaces, and how often. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download 5. Facial mimicry and social cognition in children with autism spectrum disorder Research on facial mimicry in individuals with autism spectrum disorder (ASD) has produced mixed findings. While many studies in developmental psychology report deficits in facial mimicry, others suggest that this ability may remain intact in some people with ASD. It's still unclear whether challenges with facial mimicry are a central feature of ASD or how closely they are tied to broader issues with social cognition. To shed more light on this subject, Liu's team examined the underlying processes of facial mimicry in this group. They included 21 children with ASD in their study, as well as 22 typically developing children that were matched in age and IQ. To measure facial mimicry, all participants watched images of facial expressions for 6 basic emotions (happiness, sadness, fear, surprise, anger, and disgust). During this task, children's facial expressions were recorded using FaceReader. Performing infant studies continues to provide new insights Infants learn rapidly and they learn from the culture and the people around them. Research helps to understand what infants learn, what they are processing and what factors are influencing the development. These studies also reveal how early interactions shape cognitive and social skills. By understanding these early stages, we can better support healthy development and identify potential challenges sooner. Additionally, insights from infant research help refine educational practices and parenting strategies to foster optimal growth. INNOVATIVE SOLUTIONS Free product portfolio Check out this portfolio of tools and solutions for psychology research, focusing on the observation and analysis of human behavior. These integrated solutions are designed to streamline your research process, from data collection to analysis, ensuring high-quality, reliable results. Get your copy instantly References - Liu, S.; Wang, Y. & Song, Y. (2023). Atypical facial mimicry for basic emotions in children with autism spectrum disorder. Autism Research, 16, 1375–1388. https://doi.org/10.1002/aur.2957 - Mattie, L. & Fanta, D. (2023). Joint engagement and early language abilities in young children with Down syndrome. Frontiers in Psychology, https://doi.org/10.3389/fpsyg.2023.1152559 - Salvadori, E. A., Colonnesi, C., Oort, F. J., & Messinger, D. S. (2024). Predicting Pointing from Early Socioemotional Communication with Mothers, Fathers, and Strangers Through the Lens of Temperamental Reactivity. Developmental Psychology. Advance online publication. https://dx.doi.org/10.1037/dev0001671 - Salvadori, E.A.; Colonnesi, C.; Vonk, H.S.; Oort, F.J. & Aktar, E. (2021). Infant Emotional Mimicry of Strangers: Associations with Parent Emotional Mimicry, Parent-Infant Mutual Attention, and Parent Dispositional Affective Empathy. International Journal of Environmental Research and Public Health, 18, 654. https://doi.org/10.3390/ijerph18020654 - Sandseter, E.B.H.; Sando, O.J.; Kleppe, R. (2021). Associations between Children's Risky Play and ECEC Outdoor Play Spaces and Materials. International Journal of Environmental Research and Public Health, 18, 3354. https://doi.org/10.3390/ijerph18073354 --- ## Understanding infants’ development of moral and social behavior URL: https://noldus.com/blog/infants-social-moral-development Published: 2024-10-15 11:05:00 Description: At the Centre of Infant Cognition at UBC in Vancouver, researchers conduct independent studies as well as participate in ManyBabies projects to further understand the development of moral and social behaviors of infants. At the Centre of Infant Cognition at the University of British Columbia in Vancouver, Canada, the main goal is to further understand the development of moral and social behaviors and understanding of infants. To achieve that, they conduct independent studies as well as participate in ManyBabies projects (which are large-scale collaborative efforts to advance developmental psychology), and use Noldus tools to support their research. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Social behavior and moral development: The building blocks of connection Social behavior and moral development are deeply intertwined, shaping how infants interact with others and understand right from wrong. From an early age, babies start recognizing emotions, responding to voices, and enagaging in simple social exchanges like smiling and eye contact. As they grow, they start to mimic behaviors, show empathy, and even demonstrate a basic sense of fairness — important building blocks of moral development. Early social interactions shape how children learn to cooperate, build trust, and make ethical decisions later in life. Understanding these early stages gives us a glimpse into how the foundations of kindness, justice, and social bonding take root from the very start. A typical workday of a developmental psychology researcher Francis L. Yuen is one of the researchers involved at the Centre of Infant Cognition, also known as the Hamlin Lab. Much of his work focuses on infant's social and moral development, as well as examination of how infants develop inter-group biases and how these biases come to influence their social and moral judgements. In an interview with Jacqueline Martinali from Noldus, he explains that his workdays are filled with either conducting experiments, preparing the experiments by creating stimuli or getting new stimuli ready, doing background research for new studies, or doing analytic work like running videos through software programs such as Baby FaceReader. He mentions that Baby FaceReader is suitable to use for automating processes, doing back-end analysis, and processing raw data. ManyBabies (MB) Babies come to the Hamlin Lab every day. At a minimum, every week 5 to 6 babies come to the lab for tests that Francis organizes. In a busy week, even more than 20. Some of these tests provide data used in the ManyBabies projects. By means of a collaborative project, the goal of ManyBabies is twofold: - 1. Replication of influential experiments in developmental psychology - bringing together experts in the same field across the world and massively increase the amount of babies that can participate in the experiments. - 2. Provide a way to involve labs that are from less privileged regions - offering a platform to participate in main streams of developmental work, take care of more inclusiveness, and increase the generalizability of the findings. A global network of more than 500 developmental researchers are involved in the ManyBabies projects, which are organized in main projects (either empirical or methodological), spin-off projects, and secondary analyses. The 6 empirical projects aim to gain knowledge by means of direct and indirect observation or experience. Find an overview of the 6 empirical projects on the customer story page of Center of Infant Cognition. Babies' social behavior Francis is one of two co-leads for ManyBabies 4, a large-scale multi-site replication of Dr. Kiley Hamlin's work on infant's preference on helpers and hinders. In the Netflix series Babies (part 2, episode 4), Dr. Hamlin discusses the work of this project. When she started her research, she simply wanted to know whether babies are making social judgements. In particular, she was interested in babies' understanding of those who help others versus those who hinder others. Measuring infants' eye gaze By presenting babies (3, 6, and 10 months of age) a puppet show, they tried to find out if babies pick out whether somebody intends good things or bad things. For that, they captured eye gaze, toward and away from the puppet show, and body behavior of the babies. As babies can't tell in words who they like more, one way the researchers can probe their preference is to let them make a choice between the helper character and the hinder character, for example by pointing at one of the two. What the research team observed, is that the majority of babies who saw the show, chose the helper. These results opened up the possibility that morality is not all learned. Currently the research team is conducting similar experiments to follow-up on these intriguing findings. For this, they use MediaRecorder to capture the behaviors of babies and The Observer XT to code these behaviors. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial The way to present babies stimuli Another possible execution of the tests is showing babies film versions of the puppet show. Francis spends a lot of his time on this, amongst others by creating stimuli such as animations. Because measuring eye gaze via eye tracking requires very precise timing, it is easier to present the infants animations/videos. Baby FaceReader can save lots of time To automatically detect the infants' facial expressions, Francis tried out Baby FaceReader, the software tool for automatic analysis of facial expressions of infants, using the Baby Facial Action Coding System (Baby FACS, developed by Professor Oster). The intention was to use this as a replacement for manual FACS coding, since FACS coding is extremely labor intensive and requires a lot of training. For the ManyBabies 4 project we are not looking at a group of just 30 babies that a typical lab worker normally works with, but hundreds of babies. Therefore, using Baby FaceReader will be immensely beneficial in terms of timesaving, under the condition that the output of Baby FaceReader corresponds to FACS coding. It is hundreds of times faster than manual FACS coding. Besides, it is a user-friendly system according to Francis. Automatic gaze coding promising for the future According to Francis, one very exciting and promising innovation is automatic gaze coding. A lot of infant research work is built on infant's looking time and looking behavior. Eye tracking studies and eye tracking setups are extremely popular. It would be a great thing happening in the near future if we can make this kind of research more easy and accessible, especially when eye tracking tests could run in remote locations without needing a lot of equipment. It would drastically increase not only who can conduct eye tracking work, but also on whom we can conduct the eye tracking work. Expanding networks to answer novel research questions The ManyBabies projects try to build larger networks which can help to answer novel questions which need a large sample size to investigate. Besides, by continuing with ManyBabies projects, replication work will be tackled and we will learn much more about infants' behavior. References - ManyBabies - ManyBabies4 - Netflix series 'Babies', season 2, episode 4 'Relations' - Hamlin, J.K. (2015). The case for social evaluation in preverbal infants: gazing toward one's goal drives infants' preferences for Helpers over Hinderers in the hill paradigm. Frontiers in psychology, https://doi.org/10.3389/fpsyg.2014.01563 - Lucca, K. et al. (2021). Infants' social evaluation of helpers and hinderers: A large-scale, multi-lab, coordinated replication study. In principle acceptance to Developmental Science. - Posters presented as part of the ManyBabies Poster Symposium at the 2022 International Congress for Infant Studies (ICIS) - An Experiment by Kiley Hamlin: Helpers and Hinderers --- ## Facing the food of the future URL: https://noldus.com/blog/food-of-the-future Published: 2024-09-26 10:25:00 Description: Insects are often termed the "food of the future," as they are a healthy and more sustainable alternative to conventional protein sources. But are we ready to face this new culinary frontier? This blog post was written by Eva Speijer, who completed her Master's degree in Biological Sciences: Ecology and Evolution at the University of Amsterdam, The Netherlands. She is also an educational employee at ARTIS | Natura Artis Magistra. Insects are often termed the "food of the future," as they are a healthy and more sustainable alternative to conventional protein sources (Van Huis et al., 2013). Because the global population faces both a health crisis and a climate crisis, the need for such alternatives has never been greater. But are we ready to face this new culinary frontier? Different cultural perspectives on eating insects In many cultures, insects are already a staple or even a delicacy, enjoyed in dishes like ant-egg caviar, roasted weevil larvae, and caterpillar popcorn. These delicacies are deeply embedded in the local cuisine. However, in Western cultures, insects are generally seen as unconventional, even disgusting, and certainly not part of the everyday diet (Onwezen et al., 2021). This aversion significantly hinders the adoption of insects into Western meals. By understanding the underlying causes of this aversion, we can develop more effective marketing strategies and policies to encourage the acceptance of insects as a sustainable and nutritious food source in the West. Read more about neuromarketing research. An evolutionary perspective on insect food disgust In my research, I explored the evolutionary roots of Western aversion to eating insects. Specifically, I sought to determine whether the disgust response to insects as food is an evolved behavior driven by pathogen avoidance or a culturally learned aversion (Fukano & Soga, 2021; Jensen & Lieberoth, 2019). To investigate this, I examined the developmental trajectory - or ontogeny - of emotional responses to insects as food. The ontogeny of a trait provides critical insights into the contributions of both social experience (cultural evolution) and genetic makeup (biological evolution) to its development. If the disgust response is primarily cultural, one would expect it to develop gradually over time, reflecting a learning process. Conversely, if it is genetically based, the response should be relatively consistent across age groups. A special museum experience To test these hypotheses, I conducted an age-comparative study in two museums located in Western countries: Groote Museum ARTIS in The Netherlands and Regionmuseet Kristianstad in Sweden. In these museums, I observed how visitors ranging in age from 5 to 85 reacted when they saw insects presented as food. I was particularly interested in their initial, instinctive reactions, as consumer choices are often influenced by unconscious processes (Dijksterhuis & Smith, 2005). By focusing on these first facial responses, I aimed to capture a more authentic view of participants' emotional processing when confronted with insect-based food. The experiment was designed as follows: participants were invited to take part in a study about "the food of the future." However, they were not informed that the food in question was insects, in order to capture their genuine initial reactions. Participants were then asked to lift the lids of four bowls, one at a time, while their facial expressions were recorded. Two of these bowls contained snacks with visible insects. Afterward, participants had the opportunity to taste the snacks, complete a questionnaire, and ask questions. Measuring emotional responses to insects as food To analyze the facial expressions, I used FaceReader by Noldus, a technological tool that has proven effective in interpreting facial expression patterns from video data (Schoeps et al., 2022). FaceReader is designed for automated analysis of facial expressions in pictures or videos. The software detects and classifies basic emotions—happiness, sadness, anger, surprise, fear, disgust, and neutrality—using an algorithm that examines 468 key points on the face, including landmarks like the eyebrows, eyes, and lips. It then estimates the intensity and probability of each emotion on a scale from 0 to 1. Learn more about how FaceReader is validated in research. In this experiment, facial expressions were analyzed from the moment a participant lifted a bowl until they put it back. The data were categorized based on whether the participant was looking at product with insects or not. The average proportion of each basic emotion per participant was calculated for each category. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources A happy surprise Surprisingly, the most common facial expression was not disgust, but happiness. Many participants laughed, which might suggest a growing openness to the idea of eating insects. Interestingly, the older the participant, the more likely they were to show a disgusted expression, indicating that the aversion to insects as food might be a learned behavior, rather than an innate one. This supports the cultural transmission hypothesis, which suggests that such aversions are learned over time rather than being biologically ingrained. These findings have significant implications. They suggest that the negative perception of entomophagy (the practice of eating insects) in Western cultures may be more flexible than previously thought. This insight can guide the development of strategies to promote insects as a sustainable protein source in Western countries. Improving acceptance of insects as a sustainable food source The results of this study offer a foundation for promoting the acceptance of insects as food in the West. Beyond insects, these findings also contribute to our broader understanding of the evolutionary and cultural influences on food disgust and dietary choices. Future research could explore interventions that leverage these insights to facilitate the acceptance of insects and other sustainable protein sources in Western diets. Bug Appétit! References - Dijksterhuis, A., & Smith, P. K. (2005). What do we do unconsciously? And how? Journal of Consumer Psychology, 15(3), 225-229. - Fukano, Y., & Soga, M. (2021). Why do so many modern people hate insects? The urbanization–disgust hypothesis. Science of the Total Environment, 777, 146229. - Jensen, N. H., & Lieberoth, A. (2019). We will eat disgusting foods together–Evidence of the normative basis of Western entomophagy-disgust from an insect tasting. Food Quality and Preference, 72, 109-115. - Onwezen, M. C., Bouwman, E. P., Reinders, M. J., & Dagevos, H. (2021). A systematic review on consumer acceptance of alternative proteins: Pulses, algae, insects, plant-based meat alternatives, and cultured meat. Appetite, 159, 105058. - Schoeps, K., Velert Jiménez, S., Mesa-Gresa, P., Gil-Gomez, J. A., & Montoya-Castilla, I. (2022). Analysing facial expressions of basic emotions with FaceReader: An experimental study. - Van Huis, A., Van Itterbeeck, J., Klunder, H., Mertens, E., Halloran, A., Muir, G., & Vantomme, P. (2013). Edible insects: future prospects for food and feed security (No. 171). Food and agriculture organization of the United Nations. --- ## Our gut microbiota influences how we feel URL: https://noldus.com/blog/gut-brain-vagus Published: 2024-09-18 08:30:00 Description: Our guts are our second brain. But how does that work? Researchers implanted the gut flora of depressed mice into non-depressed mice and observed the results. For a long time, we believed that the brain was the sole commander of the body, sending out instructions while receiving minimal feedback, such as signals like pain. However, recent research has flipped this notion on its head. We now know that communication between the brain and the gut is much more complex, and even more surprising—the gut has a profound influence on the brain. In fact, the digestive system not only sends signals about fullness (satiety) but also plays a crucial role in regulating our mood and behavior. The Gut: Your "second brain" Scientists have begun to understand the vast role the digestive system, and the bacteria living in it, plays in our overall health and well-being. The gut's influence on mood and behavior is so significant that it's often referred to as a "second brain." Although it's been clear that the gut impacts our mental state, the exact mechanism of this communication remained elusive, until recently. Experimental setup: Uncovering the Gut-Brain connection To investigate how the gut affects brain function, researcher Eleni Siopi and her team conducted an intriguing experiment [1] using three groups of mice: - A control group of socially housed, undisturbed mice. - A group exposed to long-term mild stress. - A group that received a fecal transplant from the stressed mice, thus inheriting the stressed mice's gut bacteria. Interestingly, the third group wasn't exposed to stress themselves, but simply had gut bacteria from the stressed mice. Unpredictable chronic mild stress The stressed group of mice endured "unpredictable chronic mild stress" over eight weeks. This meant two stressful events each day, randomized and mild, like exposure to predator scents, cage shaking, or wet bedding. While these stressors mimic what wild mice would experience, they were delivered at a higher frequency, which typically leads to depression-like behaviors in captive mice. A deep dive into anxiety testing To measure the impact of stress on behavior, the researchers used a battery of behavioral tests. These tests, recorded using EthoVision XT, included: - Open Field Test: Anxious mice explore open spaces less. - Elevated Plus Maze: Anxious mice prefer closed arms with high walls over open, exposed arms. - Light and Dark Box Test: Mice prone to anxiety spend more time in the dark. - Sucrose Preference Test: Depressed mice show less interest in sweetened water. - Novelty Suppressed Feeding Test: Anxious mice hesitate to retrieve food in brightly lit environments. - Tail Suspension Test: Depressed mice stop struggling sooner when suspended by their tail. - Forced Swim Test: Similarly, depressed mice give up trying to escape when placed in water. FREE E-BOOK Basic behavioral neuroscience in rodents Want to know more about anxiety testing and other aspects of rodent research? Then, download our free e-book. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download Key findings: Stress in the Gut, stress in the brain The stressed mice exhibited behaviors typical of depression across these tests, which was expected. However, the mice that had received fecal transplants from stressed mice also displayed the same depression-like symptoms, despite not being stressed themselves. This suggests that signals originating in the gut were being sent to the brain, triggering these behaviors. The question is, how were these signals transmitted? To find out, the researchers removed the vagus nerve from the mice that had received the fecal transplants. The vagus nerve is a critical communication pathway between the brain and various organs, including the digestive system. Once the nerve was removed, the transplanted mice no longer showed signs of depression, indicating that the vagus nerve was the key pathway transmitting signals from the gut to the brain. What does the Vagus nerve do? The vagus nerve has about 200,000 fibers connecting the brain to major organs like the heart, lungs, and digestive tract. It controls many bodily functions, such as heart rate, digestion (by managing peristalsis), and even signals satiety—telling you when you've eaten enough. In this case, the nerve was acting as a conduit for stress signals from the gut to the brain. Image from sayostudio.com (Science Communication) Neurotransmitter disruption in the Brain The researchers also examined the brains of the fecal transplant mice and discovered that key neurotransmission pathways for serotonin and dopamine were impaired. Serotonin plays a major role in mood regulation, cognition, and learning, while dopamine is essential for motivation and reward-based behaviors. Disruptions in these systems explained why the mice exhibited depression-like symptoms. So, what did we learn? In summary, if the gut flora of a 'depressed' mouse is transplanted to another mouse, that mouse will also show symptoms of depression. That works by transmission of a signal from the gut to the brain by the vagus nerve. This study thus reveals that gut bacteria can directly influence brain function to the extent that symptoms of stress and depression can indeed be transferred between individuals. The gut and brain truly are very closely linked, the next time you think about mental well-being, remember that it may just start in your gut. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References [1] Siopi, E., Galerne, M., Rivagorda, M. et al. Gut microbiota changes require vagus nerve integrity to promote depressive-like behaviors in mice. Mol Psychiatry 28, 3002–3012 (2023). https://doi.org/10.1038/s41380-023-02071-6 --- ## Exploring the early development of referential gestural communication URL: https://noldus.com/blog/pointing-gestures-infants Published: 2024-09-16 13:12:00 Description: Understanding the importance of pointing gestures can provide valuable insights into children's developmental progress and support their overall growth and learning. Imagine a sunny afternoon at the park, where children are playing happily. Amidst the laughter, an infant spots a colourful kite soaring high in the sky. Excitedly, she tugs at her father's sleeve and points upwards, her face lighting up with awe. This simple act of pointing does more than just direct her father's gaze; it connects them in a shared moment of joy and communicates her fascination with the vibrant kite. In child development, the pointing gesture is a key milestone that shows the child's ability to share attention and interests and to communicate specific needs or information. We are talking about referential communication. Socioemotional communication and referential communication Socioemotional communication is the way we express and understand emotions and internal states and create social connections when we interact with others. It's not about the words we use but about our gaze direction and focus of attention, facial expressions, vocalizations and body language. Referential communication is the way we share specific information or facts with others to make sure they understand what we are talking about. It involves being clear and precise, so the other person knows exactly what we mean. Referential communication, including pointing, is considered a triadic type of communication because it involves a triangulation of attention between the child, the interaction partner, and a shared focus of interest (e.g. a toy). Differently, socioemotional communication typically characterizes dyadic face-to-face interactions, which are especially prominent during the first months of life. Pointing is one of the first forms of conscious communication Children use pointing gestures to communicate their desires, preferences, and intentions to others by indicating objects or events. This requires an important realization in children: their perspective may not be the same as that of someone else. This ability is called the 'theory of mind'. It is part of the cognitive development and pointing is the very beginning of it. In addition to being aware of different perspectives, the child must also be able to put itself in the other person's shoes. The child realizes that when they point, someone else will respond because that person understands their gesture. This pointing gesture communicates "I see something, and I want you to see it too!". How do infants communicate with caregivers and strangers? The research team of Salvadori focused on pointing gestures. Understanding the importance of pointing gestures can provide valuable insights into children's developmental progress and support their overall growth and learning. The team aimed to investigate if and how early socioemotional communication skills can predict how well a child will be able to point and use gestures later in life. The team also investigated whether a child's natural personality traits affect this process. They used a longitudinal mixed-method approach that integrated naturalistic observations, experimental tasks in the lab, and parental reports. The final sample of this study consisted of 51 children. They were observed at 4 and 8 months during 2-minute home-based interactions and later at 12 and 15 months during structured lab-based observations. On-site observations During the home-based interactions, the father, mother or (female) experimenter sat across from the infants, engaging in face-to-face interactions without toys. This ensured for comparability of communication behaviors at the two different ages. Parents were instructed to interact with their infant as they would typically do in their everyday life. Experimenters were instructed to be visually attentive and expressively positive with the infant, in line with the infant's emotional state. The interactions were coded for socioemotional communication behaviors, using The Observer XT. Observing infants in a stationary lab During the lab sessions at 12 and 15 months, the infants took part in activities where they were encouraged to point at objects behind the person conducting the experiment. The infant and the experimenter interacted when a stimulus (e.g. a spinning spiral creating an optical illusion effect) suddenly appeared from the curtain behind the experimenter, out of her sight. The experimenter would respond to the infant pointing at a stimulus by acknowledging the object in line with its emotional valence. For example, for pleasant stimuli (i.e. spinning spiral), the response would be, "Yes, I see it too, it's beautiful," and for unpleasant stimuli (e.g. spider toy), the response would be, "Yes, I see it too, brrr it's scary." The pointing gestures were microanalytically coded along with other nonverbal communication behaviors (facial expressions, vocalizations, and gaze directions). The interactions were recorded by two cameras and systematically coded using the video analysis software The Observer XT, which was also used to calculate interrater reliability. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial The predictive value of early infant socioemotional communication To examine the predictive value of early infant socioemotional communication (such as smiles, vocalizations, and gaze) on pointing production at 12 and 15 months, the team employed a multilevel Poisson regression analysis. The infant socioemotional communication variables measured at 4 and 8 months were included as predictors in the analysis, as well as temperamental factors like surgency and negative affectivity. The effects of early socioemotional communication on pointing were tested separately for interactions with the mother, father, and a stranger (the female experimenter). Children high in surgency typically exhibit traits such as high levels of energy, positive emotions, approach behaviors, and impulsivity. They may be more likely to seek out new experiences, engage with others, and show excitement in social interactions. Children high in negative affectivity may be more prone to feelings of anxiety, frustration, and discomfort in response to various stimuli or situations. They may exhibit behaviors such as withdrawal, avoidance, and difficulty in regulating their emotions. What are the differences between the interaction partners? The research team presents their results per interaction partner of the infants. Interaction with parents: - Infant smiling with both fathers and mothers at 8 months was positively associated with the frequency of pointing at 12 and 15 months. - The association between smiling at 8 months and later pointing was strongest in infants rated high in surgency by their parents. - Affective awareness and positive affect displayed during interactions with the mother were linked to later pointing gestures. Interaction with stranger: - The frequency of gazes to the stranger's face at 8 months was positively associated with pointing, except in infants with high levels of negative affectivity. - Infants with high levels of surgency or negative affectivity showed the most positive associations between gaze behavior with strangers and later pointing. - Visual attention to the stranger's face played a role in predicting pointing gestures, particularly in infants with specific temperamental reactivity. With each partner (mother, father, and stranger), at least one temperament dimension formed a significant interaction with each emotional communication modality (smile, vocalizations, gaze) in predicting pointing. High levels of temperamental surgency tended to enhance the positive associations between early emotional communication behaviors with mothers and fathers and pointing, while high levels of negative affectivity tended to dampen the associations between early communication behaviors with strangers and pointing. Mixed-method approach led to detailed insights The researchers employed a mixed-method design which combined naturalistic observations, experimental procedures, microanalytic coding of behavior, and parental reports. It allowed them to gather detailed information about how infants develop their communication skills during the first two years of life by analyzing data at various levels. By examining different aspects closely, the researchers could paint a detailed and comprehensive picture of infants' communication growth. The research team found that the way infants interact early in life can affect their pointing skills later. Their temperament, like being outgoing or easily upset, influenced how they communicate with parents and strangers and how (and if) such early interactions influence later pointing. It's crucial to consider this when planning interventions to improve early social interactions and language skills. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Reference Salvadori, E. A., Colonnesi, C., Oort, F. J., & Messinger, D. S. (2024). Predicting Pointing from Early Socioemotional Communication with Mothers, Fathers, and Strangers Through the Lens of Temperamental Reactivity. Developmental Psychology. Advance online publication. https://dx.doi.org/10.1037/dev0001671 --- ## How to use facial expression analysis in pain research URL: https://noldus.com/blog/pain-research Published: 2024-09-05 13:23:00 Description: As the world seeks more efficient research methods, automated facial expression analysis tools offer great potential for studying facial expressions. Could these tools be applied to pain assessment? This blog post was written by Victor Lemain, who completed his Master's degree in Science, Management & Innovation at the Radboud University in Nijmegen, The Netherlands. For his thesis, he did a market research internship at Noldus. How to use facial expression analysis in pain research As the world is continuously looking for new, innovative ways to conduct research in the most efficient way possible, automated facial expression analysis tools can already be a big help when studying facial expressions. What if we were to use these tools in pain assessment? Challenges in pain assessment Assessing and measuring physical pain can be accomplished through a variety of methods, considering factors such as behavioral cues and physiological responses. Currently, the golden standard for pain measurement relies on self-reporting, a subjective process that may create challenges for individuals with a lack of verbal communication skills. For example, for infants, individuals with aphasia, or patients suffering from Alzheimer's disease (AD) [1] [2]. Facial expression analysis in pain research There are four key target groups where facial expression analysis is used most in pain research: in children under one year of age, patients suffering from dementia or Parkinson's disease, and non-communicative people with nociceptive pain [1-5]. We analyzed publications to find more information about the trends in these research fields. For example, in research focused on children under one year old, more than 350 authors published a paper in 2022. Interestingly, we observed a trend of an increasing number of authors exploring this field of research from 2020 onwards. As this trend analysis suggests, there is a rising recognition of the importance of facial expression analysis in understanding pain. Understanding the needs of pain researchers We set up a project to explore the feasibility of tools like FaceReader for applications in pain research. This included a series of interviews with experts in pain research in the field, such as researchers of dementia and those studying young children. Key objectives were identifying their potential obstacles or challenges for using automated facial expression analysis in pain research. To successfully apply automated facial expression analysis in pain research, validation must be addressed. This means that the facial expression analysis algorithms and deep neural networks accurately and reliably detect and interpret pain-related facial expressions. This should hold across diverse populations and settings, verifying that the results are both valid and true. Secondly, it's important to focus on the lack of specific measurement of pain. With this, we mean the inability to precisely quantify and differentiate between various intensities and types of pain through facial expressions alone. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Quick and objective measurements with FaceReader The results from interviews with pain researchers indicated that they perceived facial expression analysis tools like FaceReader as very useful and necessary in this field. Currently, manual coding is the standard. From the conducted interviews it became clear that the time-consuming process of manual coding is a major bottleneck when studying facial expressions in pain research. Another important advantage of automated facial expression analysis they mentioned is the objectiveness of such a tool. After all, as is described in the literature, biases from doctors or pain assessors can result in different measurements of pain levels [6]. Also read: The 5 best ways to use FaceReader: a systematic review. Next steps in pain research using FaceReader This study investigated the feasibility of facial expression analysis in four fields of pain research. Trend analysis and interviews showed that pain researchers view automated facial expression tools as highly useful, especially for assessing pain in infants. A possible direction to enable for pain research is the use of custom expressions in facial expression analysis. FaceReader's newest versions allow users to create their own algorithms, by combining parameters like Action Units, valence, gaze direction, and head orientation. Using these custom expressions can help researchers gain more insights into pain related facial expressions. To implement this type of tool in pain research, it's vital to focus on FaceReader's validation for pain assessment. This will help researchers gain the reliable results they need and move the field of pain research forward. References - T. Hadjistavropoulos et al., "A biopsychosocial formulation of pain communication," Psychological bulletin, vol. 137, no. 6, p. 910, 2011. - S. Lautenbacher and M. Kunz, "Facial pain expression in dementia: a review of the experimental and clinical evidence," Current Alzheimer Research, vol. 14, no. 5, pp. 501-505, 2017. - Z. Chen, R. Ansari, and D. Wilkie, "Automated pain detection from facial expressions using facs: A review," arXiv preprint arXiv:1811.07988, 2018. - E. Pegolo, D. Volpe, A. Cucca, L. Ricciardi, and Z. Sawacha, "Quantitative Evaluation of Hypomimia in Parkinson's Disease: A Face Tracking Approach," (in eng), Sensors (Basel), vol. 22, no. 4, Feb 10 2022, doi: 10.3390/s22041358. - A. C. Williams, "Facial expression of pain: an evolutionary account," (in eng), Behav Brain Sci, vol. 25, no. 4, pp. 439-55; discussion 455-88, Aug 2002, doi: 10.1017/s0140525x02000080. - T. R. Dawes et al., "Objectively Measuring Pain Using Facial Expression: Is the Technology Finally Ready?," Pain Management, vol. 8, no. 2, pp. 105-113, 2018/03/01 2018, doi: 10.2217/pmt-2017-0049. --- ## Neuromarketing research: Innovative research methods and techniques URL: https://noldus.com/blog/neuromarketing Published: 2024-08-30 12:00:00 Description: Get your face read, your brain measured, and your heart rate checked. Innovative research methods and techniques found their way into neuromarketing. For decades, marketers relied on questionnaires and interviews to understand consumer behavior, preferences, and motivations. However, these methods often fall short, capturing only the conscious thoughts of consumers while leaving their subconscious drivers unexplored. Non-verbal responses can also provide important information. Repeatedly, behavioral research has demonstrated that people often don't do what they say they will do. The rise of neuromarketing To get a better understanding of the unconscious preferences of consumers, innovative research methods and techniques found their way into the field of marketing studies. Neuromarketing, the science of understanding how consumers brains respond to marketing stimuli, has surged in popularity. This interdisciplinary field blends marketing, neuroscience, and psychology to uncover the hidden factors influencing consumer behavior. Neuromarketing research is a field of marketing that studies consumers' sensorimotor, cognitive, and affective response to marketing stimuli. It is an interesting mix of companies and universities that invest in neuromarketing to gather more information about consumer behavior. Medical techniques and insights of neuroscience are used to reveal consumer decision-making processes. Neuromarketers make use of neural- and physiological responses, and behavior, to understand the subconscious reactions of consumers. Neuromarketing has become increasingly more popular Innovative methods and techniques in neuromarketing research Neuromarketing employs a range of sophisticated technologies to delve into the brain's inner workings, capturing both neural activity and physiological responses. These tools include techniques like EEG, which records electrical brain activity, and fMRI, which tracks blood flow changes, providing a window into how specific marketing stimuli activate different brain regions. All techniques are aimed at learning more about why consumers make the decisions the way they do, and if a part of the brain is telling them to make these decisions. Implicit responses Implicit responses are the body's automatic, unconscious reactions to stimuli, often revealing true preferences that might not surface in traditional verbal responses. These reactions are invaluable in understanding consumer behavior at a deeper, more authentic level. To measure brain activity, researchers most commonly use EEG, MEG, or fMRI systems. For example, the subject is instructed to watch a commercial while their neuronal electronical activity is measured by using an EEG-cap. With the measured changes in brain activity, one can draw conclusions about the effects of specific elements in the commercial. Another method to measure an implicit response is using Galvanic skin response (GSR). This method measures the electrical conductance of the skin, and can indicate whether a person is bored or tense. If a person is excited, the level of electrical conductance increases if a person gets bored, the level of electrical conductance drops. There are more ways to measure implicit responses: blood pressure, heart rate, skin temperature - Learn more about these data acquisition systems. NOLDUSHUB Simplify your multimodal research Discover how NoldusHub benefits your behavior research, and why it is the best multimodal platform for you to use. - Integrated data collection - Synchronization from the start - Immediate feedback on data quality Learn more Emotions and facial expressions Basic emotions, represented by facial expressions, are not conscious and can thus deliver great information about subconscious processes. Facial expressions can tell us a lot, sometimes even more than we are aware of. Automated analysis of facial expressions brings clear insights into the effect of different stimuli on emotions. In neuromarketing research, especially the affective states (interest, boredom and confusion) of the participant show an added value. It tells a lot about appreciation towards commercials, brands or products. How do you know a consumer is feeling (highly) engaged? Dayenne Sarkol-Teulings created a custom expression in FaceReader to measure the level of engagement: learn more about her validation study in this blog post. A positive emotion towards a product can determine a positive decision. It's all about the connections that are made unconsciously. Immediately after a product or visual is introduced to the consumer, he or she feels positive or negative emotions. Researchers worldwide measure these emotions by using FaceReader, software that automatically classifies facial expressions. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Eye tracking combined with facial expression analysis Often eye tracking technology is combined with facial expression analysis techniques to provide insight in preferences, desire, appreciation, and more. Both eye tracking and expression analysis can add substantial power to your research by providing information about attention and emotion. Scan paths indicate for example how people look at websites and advertisements: which parts of an advertisement they actually look at and for how long they look at various items. And when a participant has previous experience with an application, the scan path of the eyes will have fewer fixations. Modern eye trackers can easily generate this information, which makes them increasingly popular in neuromarketing studies. Combining research tools such as an eye tracker, FaceReader, The Observer XT (coding and analysis software) or multimodal research tool NoldusHub, can add substantial power to your research. Sub-consciousness Our own subconscious has a lot more influence on our behavior then we could ever imagine. What do we really see, notice, and what is registered in our memory? How do we make decisions? As neuromarketing continues to evolve, these innovative research methods are unlocking new possibilities in understanding and influencing consumer behavior. By tapping into the subconscious mind, marketers can design more effective campaigns, craft messages that resonate on a deeper level, and ultimately drive better business outcomes. The better we know how the brain functions, the better we know how to influence decision making processes. Of course, advertisement placement and government campaigns can then be adjusted and made more effective. In tools such as NoldusHub and The Observer XT, facial expressions, physiological data, eye tracking data, and video can be integrated. To provide a good overview of stimulus-response, such a tool can be of real value to your research. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download --- ## Fake or real? AI illusions on the street URL: https://noldus.com/blog/ai-and-advertisements Published: 2024-08-22 09:05:00 Description: In Faux Out-Of-Home (FOOH) advertisement, real-world images are combined with computer-generated imagery and shared on social media. What happens to consumers' perceptions and emotions when you disclose that AI was used? This blog post was written by Joyce Massop, who completed her Master's degree in Communication Sciences at Radboud University in Nijmegen, The Netherlands. The thesis was supervised by Paul Ketelaar, Assistant Professor in Communication Science and the Behavioural Science Institute (BSI) at Radboud University. In today's digital society, the use of AI in creating online marketing campaigns plays an increasingly significant role. One example of this is the viral marketing technique called Faux Out-Of-Home (FOOH), where real-world images are combined with computer-generated imagery and spread across social media. A notable instance is a video of the French fashion brand Jacquemus, which went viral in a matter of seconds with a catchy campaign. The video showed the popular Bambino bags shaped like buses driving through the streets of Paris. AI use in advertising: new rules Given this trend, governments are introducing regulations that require the use of disclosures for AI-generated content [1]. An AI disclosure informs consumers about the technological origin of the advertisement and helps them recognize the presence of AI [2,3]. This can take the form of a hashtag or textual mention in a post, such as "Generated by AI." Using AI disclosures may give consumers the impression that the campaign creators put less effort into making the advertisement [4]. On the other hand, disclosing AI techniques can lead to a sense of transparency [5], thereby eliciting more positive emotions [6] compared to when there is no disclosure. Learn more about neuromarketing research. Understanding AI disclosures in FOOH marketing The study examined the impact of AI disclosures on the emotional response among young adults. The goal was to understand whether revealing AI-generated content via an AI disclosure affected how young adults emotionally perceive a brand. To better comprehend the effect, the study investigated whether perceived effort played a mediating role in this process. Figure 1 shows the research model of this study. Figure 1: Research model Measuring emotional response with FaceReader Online The study was conducted using FaceReader Online among Dutch young adults between the ages of 18 and 29. A total of 110 participants were randomly assigned to two groups. Both groups were shown an Instagram reel (short video) featuring the Louvre in Paris showcasing a Fake Out-Of-Home marketing campaign. In this video, the pyramids of the Louvre opened up, releasing numerous heart-shaped balloons. Participants in the experimental condition saw a visual AI disclosure in the video, while those in the control group did not see any AI disclosure. The textual AI disclosure read: "Created with Artificial Intelligence (AI)" (Figure 2). Figure 2: Textual disclosure in the experimental condition The study utilized a Qualtrics survey seamlessly integrated with FaceReader Online. Combining the Qualtrics survey with FaceReader Online allowed the researcher to measure the emotional response quickly and easily. Clear instructions were provided to participants during the measurement, resulting in reliable data collection. The recorded data was immediately analyzed and clearly presented with graphs and figures. No effects of AI disclosure Interestingly, no noticeable effect of AI disclosure (present/absent) was found on both emotional responses and perceived effort. This suggests that disclosing AI-generated content might not have a direct impact on the emotional responses and perceived effort of young adults. You may also like this blog post about how to increase attention in commercials for Gen Z. How FaceReader Online can offer new insights This study highlights the importance of understanding consumers' emotional responses to AI-generated content, as this can influence their attitude towards the promoted brand. Therefore, future research on consumers' emotional responses to AI disclosures might benefit from using FaceReader Online more frequently. This study has demonstrated that FaceReader Online is an effective method for measuring subtle and unconscious emotional responses in the context of FOOH marketing. Especially in experimental settings, FaceReader Online can be valuable because even when participants are aware of the camera and try to present neutral reactions, unconscious emotions can still influence brand attitude [7]. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Uncovering unconscious emotions FaceReader is a reliable tool for assessing emotions, as traditional methods for measuring emotions, like self-report scales, may not always be considered accurate due to the subjective nature of emotions and personal interpretations. Moreover, cognitive processes triggered by advertisements often operate at an unconscious level, making it difficult for consumers to be aware of them. Additionally, emotions have often been measured with self-report scales in previous research, but this method is not always seen as accurate due to the subjective nature of emotions and individual interpretations [8,9]. Moreover, cognitive processes activated by advertisements often occur unconsciously, making it hard for consumers to be aware of them [10,11]. FaceReader Online offers significant potential in this regard, as it is a valuable tool to enhance our understanding of emotions and, more specifically, to effectively measure the impact within the context of FOOH marketing. FaceReader Online is a valuable addition in this respect and can complement scientific knowledge in the context of efficiently measuring emotions and, more specifically, AI disclosures in FOOH marketing. Also read: Why you should use FaceReader Online for your human behavior research. Facilitating large-scale emotion research Lastly, FaceReader Online is user-friendly and allows for the recruitment of a large number of participants. Integrating FaceReader with online surveys makes research easy to distribute. Participation is convenient for respondents, as they can choose if and when they want to take part in the study. This facilitates large-scale research. By utilizing FaceReader Online, we can improve our understanding of emotions, supplement existing scientific knowledge and measurement methods, and gain valuable insights into the effects of emotional responses. References - Auteursbond. (2023, 16 oktober). AI en auteursrecht. Auteursbond. https://auteursbond.nl/ai-en-auteursrecht/ - Evans, N. J., Phua, J., Lim, J., & Jun, H. (2017). Disclosing Instagram Influencer Advertising: The Effects of Disclosure Language on Advertising Recognition, Attitudes, and Behavioral Intent. Journal of Interactive Advertising, 17(2), 138–149. https://doi.org/10.1080/15252019.2017.1366885 - Boerman, S. C., Van Reijmersdal, E. A., & Neijens, P. (2012). Sponsorship Disclosure: Effects of Duration on Persuasion Knowledge and Brand Responses. Journal of Communication, 62(6), 1047–1064. https://doi.org/10.1111/j.1460-2466.2012.01677.x - Rhee, H., & Lee, K. (2024) Generative AI disclosure in fashion marketing: A tectonic shift in the advertising landscape, ITAA Proceedings, Conference: Bridging the Divide, Baltimore Maryland, 1-3. DOI: 10.31274/itaa.17359. - Wojdynski, B. W., Evans, N. R., & Hoy, M. G. (2018). Measuring Sponsorship Transparency in the Age of Native Advertising. Journal of Consumer Affairs, 52(1), 115–137. https://doi.org/10.1111/joca.12144 - Beckert, J., Koch, T., Viererbl, B., & Schulz-Knappe, C. (2021). The disclosure paradox: how persuasion knowledge mediates disclosure effects in sponsored media content. International Journal of Advertising, 40(7), 1160–1186. https://doi.org/10.1080/02650487.2020.1859171 - Hudders, L., De Jans, S., & De Veirman, M. (2020). The commercialization of social media stars: a literature review and conceptual framework on the strategic use of social media influencers. International Journal of Advertising, 40(3), 327–375. https://doi.org/10.1080/02650487.2020.1836925 - Barrett, L. F. (2017). How Emotions are made. The secret life of the brain. Revue québécoise de psychologie, 40(1), 153-157. https://doi.org/10.7202/1064926ar - Suhr, Y. T. (2017). FaceReader, a Promising Instrument for Measuring Face Emotion Expression? A Comparison to Facial Electromyography and Self-Reports (Master's thesis). Accessed from https://dspace.library.uu.nl/handle/1874/352187 - Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The Role of Emotions in Marketing. Journal of the Academy of Marketing Science, 27(2), 184–206. https://doi.org/10.1177/0092070399272005 - Mizerski, R., & White, D. J. (1986). Understanding and using emotions in advertising. Journal of Consumer Marketing, 3(4), 57-69. https://doi.org/10.1108/eb008180 --- ## What is a placebo? And how does it work? URL: https://noldus.com/blog/how-does-a-placebo-work Published: 2024-08-20 12:00:00 Description: The placebo effect reveals how belief alone can influence pain and symptoms. Recent research uncovers brain mechanisms, like the panacea effect, involved in this effect in mice The placebo effect is one of the most intriguing and mysterious phenomena in both medicine and psychology. At its core, it's the ability of a person's belief or expectation to influence physical and mental health outcomes, even when no active medication is involved. While it may seem almost magical, the placebo effect is backed by significant research and plays a crucial role in how we experience pain, fatigue, and other symptoms. But how exactly does this work, and what does recent research reveal about the underlying mechanisms in the brain? Let's dive into the science behind this fascinating phenomenon. What is a placebo? If someone that you trust gives you a pill and tells you that it will make your headache go away, then it helps. Even if there is no painkiller in the pill. That is the completely bizarre phenomenon that we know of as the placebo effect. It typically affects symptoms like pain, fatigue and depression and can increase or decrease the effects of drugs. And has also been found to work extremely well in the case of sea-sickness! Dopamine The placebo effect only works if you expect it to, hence the importance of trusting the person who administers it. Some people are genetically more predisposed to placebos than others, apparently related to dopamine levels in the brain. Dopamine is a neurotransmitter which plays a role in motivation and reward-related behavior. Personality traits also play a role in how strong the placebo effect is. Side-effects You can even get negative side effects like headaches or dizziness from placebos. That is called the nocebo effect. Placebo effects are so strong that in any medical trial, it is necessary to give the control group a placebo (not just an absence of treatment) so that the researchers can distinguish between the effects of the treatment being studied and the placebo effect. Sometimes people talk as if placebo effects are imaginary, 'it is just in the mind', but our entire experience of the world is in our minds, we know no other reality. Double blinding Even if the researchers know which treatments are with drugs and which are placebos (and the participants are not told), that can still have an effect. For that reason, trials are normally double-blind, so that neither the people administering the treatment, nor the subjects know which treatment they receive. Physicians also prescribe placebos In one survey [1], 77% of UK physicians said that they prescribed placebos at least once a week. That was mostly not a pure placebo (like a sugar pill) but one with an active ingredient, like vitamins or antibiotic for a viral disease, but which would have no biological effect on the disease in question. Various studies [2] have shown that up to 50% of the effects of some treatments for diseases like bipolar, insomnia and depression can be due to the placebo effects. But it is not only diseases of the brain that can be affected, also cardiology, dermatology, Crohn's disease, and urology are all areas where the placebo effect has been demonstrated, albeit sometimes with smaller effects. It is also sometimes suggested that the benefits of homeopathic medicine can be partly due to the placebo effect. Placebos in research Most research on placebos has been on their effects on pain ('placebo analgesia'), but until recently, there was still not so much known about the mechanisms in the brain that caused it. However, a new study (published in 2024 [3]) has at last unravelled some of the biological mechanisms behind the phenomenon. Behavioral experiment A study by Chen and colleagues [3] designed an experiment in mice to investigate how the placebo effect operates in the brain. They used heated floor plates set to 48°C, which caused mild pain to the mice without causing any harm. Next to the hot plate, they placed a cooler plate at 30°C. The mice quickly learned that moving to the cooler plate would relieve their discomfort, and their movements were tracked using EthoVision XT software. Interestingly, even when the temperature of the hot floor was lowered back to 30°C, the mice still preferred the plate they had learned was cooler. This behavior mirrors the way humans trust the person administering a placebo, showing how expectation alone can influence perception and behavior. When on the hot plate, the mice displayed behaviors to alleviate their discomfort, such as jumping and licking their paws. Remarkably, when both plates were heated to the same 48°C, the mice still preferred the previously cooler plate and exhibited fewer pain-relief behaviors. This demonstrated that the mice had developed a learned expectation of relief—similar to the placebo effect in humans. To further confirm that this was indeed a placebo-like response, the researchers performed additional tests. To better understand the underlying brain mechanisms, the researchers mounted tiny microscopes on the mice's heads to observe brain activity during the experiment. They discovered that a specific brain region called the pontine nucleus, typically associated with controlling body movements, was highly active during the placebo effect. When the researchers turned off neurons in this area, the placebo effect vanished, indicating its crucial role in pain relief expectations. Purkinje cells Digging deeper, the researchers identified Purkinje cells in the pontine nucleus as the specific cells responsible for encoding the expectation of pain relief (i.e., the panacea brain mechanism). Purkinje cells, are the second-largest cells in the brain, with a long axon and many branched ends (called dendrites), and are vital for coordinating motor activity and are known to have receptors for natural opioids produced by the body. Painkillers work by stimulating these opioid systems, and the research suggests that these same cells are involved in the brain's response to placebo-induced pain relief. Drawing of pigeon Purkinje cells (A) by Santiago Ramon y Cajal 1899 (Wikipedia Commons) Two key insights This research uncovers two key insights. - 1. First, it reveals that the panacea brain mechanism—the process by which the brain produces pain relief in response to the expectation of relief—operates in a way that parallels how actual painkillers work. Specifically, the placebo effect triggers the brain's opioid system, much like a drug would, leading to real pain reduction. This mechanism involves areas such as the pontine nucleus and Purkinje cells, which are key players in controlling motor functions and processing the brain's natural opioid responses. - 2. Second, while the panacea brain mechanism shares similarities with how painkillers function, it also has unique elements. These differences suggest that the brain has alternative pathways to manage pain, beyond what current drugs target. Understanding these distinct pathways opens up the potential for developing new types of pain therapies that might be more effective by tapping into these specific placebo-related brain mechanisms. In essence, this research not only validates the power of the placebo effect but also points toward future innovations in pain management. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial References - Howick J, Bishop FL, Heneghan C, Wolstenholme J, Stevens S, Hobbs FD, Lewith G. Placebo use in the United Kingdom: results from a national survey of primary care practitioners. PLoS ONE. 2013;8:e58247. doi: 10.1371/journal.pone.0058247. - Pardo-Cabello AJ, Manzano-Gamero V, Puche-Cañas E. Placebo: a brief updated review. Naunyn Schmiedebergs Arch Pharmacol. 2022 Nov;395(11):1343-1356. doi: 10.1007/s00210-022-02280-w. Epub 2022 Aug 9. PMID: 35943515; PMCID: PMC9361274. - Chen, C., Niehaus, J.K., Dinc, F. et al. Neural circuit basis of placebo pain relief. Nature (2024). https://doi.org/10.1038/s41586-024-07816-z --- ## Conference about techniques and methods for measuring behavior URL: https://noldus.com/blog/conference-measuring-behavior Published: 2024-08-15 15:00:00 Description: With so many meetings, in so many fields of behavioral research, what makes the Measuring Behavior conferences stand out? A quick search on the internet reveals that no one seems to know how many scientific conferences take place in a year. The best I could find was “it’s got to be huge”, and when it comes to it, that is as a good a quantification as you need. With so many meetings, in so many fields of behavioural research, what makes Measuring Behavior stand out? Two very important things.  New methods and techniques are vital for the advancement of science First it is not about results, which is very unusual. Virtually every conference focuses on scientific results. However, in practice, it is often the developments in methodology that have lead to the real advances in science. Without the microscope there would have been no microbiology. Without the telescope, there would be no astronomy. And without x-ray crystallography, Watson and Crick would never have discovered the structure of DNA. New methods and techniques are vital for the advancement of science. Multi-disciplinary conference Second, Measuring Behavior is an astonishingly multi-disciplinary conference. ‘Behavior’ is something you can study in drivers of vehicles, rats in cages, eagles in the air, fish in the sea and players in games. In the every edition of the conference, all these topics have special sessions devoted to them. Likewise, participants will include ethologists, behavioral ecologists, neuroscientists, experimental psychologists, human factors researchers, movement scientists, robotics engineers, software designers, electronic engineers, human-computer interaction specialists, physiologists, and countless more. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources History of Measuring Behavior It started in 1996 as a workshop organised by Dr. Berry Spruijt and Dr. Lucas Noldus in Utrecht, The Netherlands. Lucas Noldus’s company, Noldus Information Technology, has had a long-term commitment to the conference over the years, and is the chief sponsor. Each edition, great care is taken that the conference program is scientifically independent of the sponsor by means of an anonymous peer review supervised by a Scientific Program Committee. Since its first edition in 1996, there have been numerous conferences organized. The second edition was held at the University of Groningen, The Netherlands, 18-21 August 1998. Two years later in 2000, the conference took place in Nijmegen (NL), followed by the 2002 edition in Amsterdam. Measuring Behavior 2005 The 5th Measuring Behavior conference was held in Wageningen (The Netherlands) from 30 August through 2 September 2005. Delegates from 36 countries enjoyed four intensive days, with 250 presentations in symposia, tutorials, special interest groups, user meetings, scientific tours, free paper sessions and poster groups! Besides that, delegates visited demonstrations of exhibiting companies. And last but not least, the great weather made the social events even more enjoyable. Measuring Behavior 2008 The 6th Measuring Behavior conference was held in Maastricht (The Netherlands) from 26 - 29 August. Delegates from 42 countries enjoyed four intensive days. The Measuring Behavior conference featured three insightful keynote lectures. Professor Gregory D. Abowd from Georgia Institute of Technology discussed measuring behavior in home environments. Professor David P. Wolfer from the University of Zürich explored the promises of automated testing of mouse behavior in home cages. Lastly, Professor Sir Patrick Bateson from Cambridge University highlighted innovative techniques for measuring behavior. Measuring Behavior 2010 The 7th International Conference on Methods and Techniques in Behavioral Research took place in Eindhoven, The Netherlands, from August 24-27, 2010. Nearly 400 attendees participated in four days filled with engaging keynote lectures, symposia, tutorials, workshops, scientific tours, and enjoyable social events. Measuring Behavior 2012 In 2012, the International Conference on Methods and Techniques in Behavioral research returned to its roots. Over 300 participants from more than 30 countries worldwide attended Measuring Behavior 2012 in Utrecht, The Netherlands. Delegates from various backgrounds blended in with exhibitors and developers from leading companies, ensuring a productive cross-fertilization between research fields. Measuring Behavior 2014 Measuring Behavior 2014 was successfully held in the city of Wageningen from 27-29 August 2014. Best known for it's international Wageningen University and many research institutes, Wageningen has a considerable number of groups working on research related to both animal and human behavior. Like previous editions the conference focused on methods and techniques in behavioral research. This year there was a special emphasis on new inventions, prototypes, and techniques. Measuring Behavior 2016 For the first time ever Measuring Behavior was hosted outside of The Netherlands. From 25-27 May 2016, Dublin formed be the stage for the latest inventions, prototypes, and techniques in behavioral research. The conference was hosted by Dublin City University and the Insight Centre for Data Analytics. The welcome reception took place in the Guinness Storehouse at their legendary Gravity Bar, an iconic spot that offers breathtaking 360-degree views of the city. The conference banquet was held at Clontarf Castle. Measuring Behavior 2018 From 6-8 June 2018, Manchester was the stage for the latest inventions, prototypes, and techniques in behavioral research. The conference was hosted by Manchester Metropolitan University and welcomed over 250 international delegates. The event featured a variety of keynote lectures, workshops, and symposia, fostering interdisciplinary discussions and collaborations among researchers from diverse fields. Measuring Behavior 2022 After events were postponed due to the worldwide pandemic, the conference moved entirely online for the first time. The 12th International Conference on Methods and Techniques in Behavioral Research, together with the 6th International Seminar on Behavioral Methods, took place as a virtual meeting. Measuring Behavior 2024 The 13th International Conference on Methods and Techniques in Behavioral Research, Measuring Behavior 2024, was held in person again in Aberdeen, Scotland. The Department of Biomedical Sciences at Aberdeen University has a long and impressive track record in both behavioral research and supporting the Measuring Behavior conferences. Three excellent keynote speakers covered methods for research in human behavior, animal behavior and AI analysis. Anne-Marie Brouwer spoke about measuring mental states, Robert Gerlai presented about learning and zebrafish, and Albert Ali Salah gave a keynote talk about computational tools. Measuring Behavior conferences It must be clear that at any Measuring Behavior meeting, you'll find yourself among researchers from all fields of behavioral research. While the research questions and applications may be highly diverse, what all delegates share is an interest in methods, techniques and tools for the study of behavior. You can learn more about the Measuring Behavior conferences and future editions at www.measuringbehavior.org. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more --- ## Should you use a combination of modes to optimize behavioral studies? URL: https://noldus.com/blog/combination-of-modes Published: 2024-08-06 09:15:00 Description: If you ask a scientist what they think of when you say, ‘behavioral study’, they will come up with wildly differing answers, depending on their own type of work. If you ask a scientist what they think of when you say, 'behavioral study', they will come up with wildly differing answers, depending on their own type of work. Behavioral studies of people can be roughly divided into four categories: - Observational studies are about watching and recording people's behaviors. - Implicit measures are measurements of physiology, facial expressions, etc. - Explicit measures are where you ask individual test participants or subjects questions either during a task or afterwards. - Surveys are similar to explicit measures but in this case you ask questions to large groups of people and the questions are not normally related to a task. Each type has specific advantages and disadvantages. Observational studies These are the classic type of study in psychological research. They are objective (and therefore potentially unbiassed), take place in controlled conditions, can be replicated and are often designed to test a falsifiable hypothesis (and so fall under the usual definition of scientific experiments). However, they can be more difficult to interpret than might appear at first sight and can be subject to various biases. Many classic psychological experiments have proved difficult to replicate. Stanford marshmallow experiment For example, the famous Stanford marshmallow experiment first carried out in the 60s and published in 1970 [1] was designed to be a test of will power. Young children were offered marshmallows and told that if they didn't eat the one in front of them that they would get two later. The children who did better in the test, scored better in school tests ten years later. That was called delayed gratification. During the experiment itself, it became clear that the successful children were the ones who devised techniques to distract themselves (one child even succeeded in falling asleep), not those with the greatest will power. The children were also not a representative sample of the population, they were all from the university day care center. Later it was shown that results varied enormously across different countries [2], proving that the results were at least in part culturally determined and that if family background was corrected for, the correlation with doing better in school tests disappeared. Standard in psychology Nevertheless, if enough attention is paid to the study design (and scientists have learnt a lot about that since the '60s), it is possible to gain a lot of insights and this type of research has been the standard in psychology for the past decades. Psychologists often use The Observer XT for those studies, either as a stand-alone program or as part of a complete observational lab. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Explicit measures A disadvantage of a purely observational study is that it is difficult to know what is going on inside the subjects' heads. One solution to that is simply to ask the participants in order to get their subjective insights. That can be done after the experiment, or at critical moments in a task ('how do you feel now?'). In longer studies, the questions can be put at set times each day or related to the behaviors or physiological signals of the subjects ('why did you do that?'). That is sometimes referred to as ecological momentary assessment (EMA) if it is carried out whilst the subjects' go about their daily life. However, this method also has more problems than you might think at first. If the questions are put whilst the subjects are carrying out a task, they can distract from the task itself. If carried out afterwards, studies have shown that the responses relate primarily to the last few minutes and not the entire task. Subjects will subconsciously give answers to that they think the researchers want to hear (out of a desire to please) or give answers that they think gives a better impression of themselves (studies on unhealthy eating are notorious in that respect). Mental states It is also surprising how little insight people normally have into their own mental states. I remember hearing a talk at Measuring Behavior in which Jennifer Healey told us that a subject had heard gunfire whilst driving along and said that they were completely unbothered by it, whereas in fact their heart rate went through the roof. Surveys A big disadvantage of the above two methods is that it is hard to know if their findings apply to the general population or only the group on which the study was carried out (which is typically psychology students). A solution to that is to ask questions to a much larger representative group by means of a survey. This can go out to hundreds of people living in many different places and circumstances. However, those questions usually cannot be related to a task, and they still have the disadvantage that the answers may not be both honest and with sufficient self-understanding. If asked about the price of a product, many people will say that it is too expensive, even if they don't really believe that, because they don't want the manufacturer to put the price up. Psychologists often refer to the questionnaires that they use in surveys or in studies with small groups as validated. However, remarkably often that turns out to mean that they give the same results as other questionaries, rather than be validated by an independent measure. Surveys comparing attitudes in different countries or cultures need to be treated with particular caution, as the interpretation of questions is often culturally dependent, and even more so if the survey is translated. Surveys are particularly useful for following trends and other changes over time. It is unlikely that their biases will change from one year to the next, so an increase in whatever they are asking about is probably a real increase. Implicit (objective) measures In the past, measures like physiology (heart rate, skin conductance, etc), eye-tracking, EEG, fNIRS, and facial expression analysis were largely confined to laboratory studies of subjects more or less sitting still. However, in recent years, those technologies have become increasingly mobile. In addition, technologies like NoldusHub have made them much easier to use. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more Their big advantage is that they are entirely objective and therefore much less susceptible to all kinds of biases. Another advantage is that they can pick up effects which explicit questionnaires miss. For example, de Wijk and Noldus [3] carried out an experiment where they measured the eating experience of participants in a laboratory and the participants' home, with everything else (food, plates, cutlery, measurement devices, etc) kept exactly the same. There was almost no effect on the explicit measures but a large effect on heart rate and facial expressions. They then tried to see if they could replicate that effect with an experiment in which the participants were in a laboratory, a simulated café and a real café. The replication succeeded: the explicit measures showed no effects of location, but the implicit measures did show an effect. However, use of just implicit measures alone is often insufficient, and the technical needs of the measurement can form a constraint for the experimental design. Mixed-methods design: optimizing objectivity and insights It is clear that the researcher should not just use one measurement technique, but wherever possible use multiple ways of measuring the responses of their subjects to the experimental conditions. This will both give more insights and more objective results. Of course, if a fundamental element of good experimental design like an unrepresentative group of subjects or insufficient replication (or pseudoreplication) is not taken care of, then the results might still be misleading. Nevertheless, a mixture of methods can be very useful in optimizing but the objectivity and insights. References 1. Mischel, Walter; Ebbesen, Ebbe B. (1970). "Attention in delay of gratification". Journal of Personality and Social Psychology. 16 (2): 329–337. doi:10.1037/h0029815. 2. Yanaoka, Kaichi; Michaelson, Laura E.; Guild, Ryan Mori; Dostart, Grace; Yonehiro, Jade; Saito, Satoru; Munakata, Yuko (22 June 2022). "Cultures Crossing: The Power of Habit in Delaying Gratification". Psychological Science. 33 (7): 1172–1181. doi:10.1177/09567976221074650. 3. René A. de Wijk, Lucas P.J.J. Noldus (2021), Using implicit rather than explicit measures of emotions, Food Quality and Preference 92, 104125. doi: 10.1016/j.foodqual.2020.104125. --- ## All the little things that affect your animals' behavior URL: https://noldus.com/blog/all-the-little-things-that-affect-animal-behavior Published: 2024-08-01 14:30:00 Description: In behavioral research, even the smallest details can significantly influence the behavior of animals. Understanding these nuances is crucial for the accuracy of your data. In behavioral research, even the smallest details can significantly influence the behavior of animals. Understanding these nuances is not only crucial for ensuring the accuracy of your data, but also the welfare of your animals. In this blog we lay out some key factors that can affect animal, particularly rodent, behavior and tips on how to manage them effectively. 1. Handling techniques When we talk about handling animals in a research setting, consistency and care are paramount. Handling is often the most direct interaction researchers have with their animals, and these interactions can significantly influence their behavior. Consistency in handling Why it matters Variations in handling techniques can introduce stress, leading to behaviors that do not accurately reflect an animal's natural state. Stress responses can alter physiological and behavioral parameters, making data unreliable. Best practices Ensure the same person handles the animals using the same method every time. For example, scooping rodents with both hands instead of lifting them by the tail can reduce stress considerably. But also tunnel handling is becoming increasingly popular, where the tunnel serves as both cage enrichtment as well as a means of handling you animals. In general it is the consistent handling routines help animals get used to human interaction, reducing variability in behavior data. Research shows that consistent handling reduces stress-related behaviors and improves data reliability in studies of anxiety and stress in mice. Minimizing stress Why it matters Stressful or too much handling can cause behaviors that do not represent the animal's normal state, thus affecting the reliability of experimental results. Stress hormones like cortisol can affect both behavior and physiological responses. Best practices Handle animals gently and only when necessary. Use calm, smooth movements and avoid loud noises or sudden actions that might startle them. Regular, brief (and consistent) handling sessions can help animals become accustomed to human interaction without causing undue stress. Handling time of day: keep it the same The timing of handling and testing are also crucial for obtaining reliable behavioral data. Animals have natural rhythms and habits that must be respected to ensure valid research outcomes. Why it matters Animals have circadian rhythms that influence their behavior. Testing at different times can yield different results, affecting the reliability of data. Best practices Conduct experiments at the same time each day to reduce variability due to circadian rhythms. Consistency in testing times helps ensure that any observed behavioral changes are due to the experimental conditions rather than the time of day. Studies show that controlling for circadian influences improves the repeatability and accuracy of behavioral tests. But also your handling routine, again going back to consistency, definitely matters Why it matters Establishing a routine helps animals become accustomed to handling, reducing stress over time and improving data consistency (Advance Research). Best practices Handle animals regularly but keep interactions short and consistent. This familiarization process can significantly reduce stress and enhance the reliability of behavioral observations . Consistent handling routines have been shown to reduce variability in behavioral tests such as the open-field. Lastly there are the personal factors of the handler Personal characteristics of the handler, including scent, appearance, and behavior, can subtly but significantly influence animal behavior. Attention to these details can improve research outcomes and animal welfare. Why it matters Animals, particularly rodents, have a highly developed sense of smell. Strong scents from perfumes, lotions, or even the handler's diet (or smoking habits) can affect their behavior. Best practices Avoid wearing strong scents and ensure hands are clean before handling animals, particularly when moving between rooms. Preferably use unscented soap and avoid fragrant products on testing days to minimize olfactory disruptions. Also, when moving between male and female rooms, consider doing all the work in the female rooms first before moving to the male room. Getting male scent in a female room could trigger a shift in their estrous cycle. Attire and appearance Why it matters Changes in the handler's appearance, such as different clothing or hairstyles, could startle animals and affect their behavior. Best practices Wear consistent clothing when handling animals, preferably lab coats or other neutral, familiar garments (have a dedicated lab coat you can wear in the animal rooms). This consistency helps animals remain calm and reduces behavioral variability. 2. Environmental factors Environmental conditions are crucial in shaping animal behavior. Factors like lighting, temperature, and noise can either promote natural behaviors or lead to stress and atypical responses. Lighting Why it matters Animals have species-specific lighting preferences that affect their activity levels and stress responses. Lighting impacts circadian rhythms and can influence behaviors such as feeding, mating, and sleeping. Best practices Mimic natural light conditions as closely as possible. For nocturnal animals like rodents, dim lighting is essential to avoid stress and encourage natural behavior. Avoid abrupt changes in lighting, which can disturb the animals' circadian rhythms. Additional insight Bright TL (tubular fluorescent) light bars are known to cause stress due to high intensity and flicker effects, which are often undetectable to humans but can be perceived by animals. Natural light and adjustable LED bulbs are better alternatives, providing a fuller spectrum of light and reducing stress. Temperature and humidity Why it matters Extremes in temperature and humidity can cause stress and impact animal behavior, leading to inconsistent data. These conditions can affect physiological processes like metabolism and thermoregulation. Best practices Maintain stable environmental conditions that fall within species-specific comfort zones. Make sure your temperature system works correctoy, regularly monitor and adjust if needed. But in this, consistency again is key. Maintaining optimal temperature and humidity reduces stress and enhances behavior predictability in lab animals. Additional insight Here are some of the species-specific temperature zones for commonly used animals in behavioral research Species Thermoneutral zone (TNZ) Optimal temperature range Considerations Mice 26°C - 30°C (78.8°F - 86°F) 20°C - 26°C (68°F - 78.8°F) Mice are sensitive to temperature fluctuations due to their high surface-area-to-volume ratio. Temperatures below the TNZ may increase metabolic rates and food intake, while higher temperatures can lead to heat stress affecting reproduction and immune response. Rats 26°C - 30°C (78.8°F - 86°F) 20°C - 24°C (68°F - 75°F) Rats prefer slightly warmer environments than typical room temperatures. Deviations can cause changes in aggression and lethargy. Consistent exposure to non-optimal temperatures affects growth and reproduction. Voles 22°C - 28°C (71.6°F - 82.4°F) 18°C - 22°C (64.4°F - 71.6°F) Voles are less tolerant to cold stress, increasing metabolic rates. High temperatures can lead to heat stress and altered activity levels. Fruit Flies (Drosophila melanogaster) N/A 20°C - 25°C (68°F - 77°F) Fruit flies thrive within a narrow temperature range. Temperatures outside this range can delay development and reduce fertility. High temperatures speed up metabolism, affecting lifespan. Zebrafish (Danio rerio) 26°C - 28°C (78.8°F - 82.4°F) 26°C - 28°C (78.8°F - 82.4°F) Zebrafish are ectothermic; their body temperature matches water temperature. Lower temperatures slow growth, while higher temperatures affect breeding. Noise levels Why it matters Loud or unexpected noises can startle animals and alter their behavior, leading to stress and data variability. Chronic noise exposure has even been found to impact health and behavioral responses. Best practices Keep noise levels low and consistent. Implement soundproofing measures if necessary, and avoid noisy activities near the testing area to minimize disturbances. Additional insight In addition to the potential negative impacts of noise, it's worth mentioning that some labs intentionally play music in housing rooms. Music can have varying effects on different species, ranging from calming to stimulating. In some cases, playing specific types of music, such as classical or ambient soundscapes, may help mask sudden noises and create a more stable auditory environment. If using music in housing rooms, select calming and consistent soundtracks that do not have sudden changes in volume or intensity. Studies suggest that genres like classical music can reduce stress markers in some species. Conclusion Understanding and controlling the numerous factors that can influence animal behavior is essential for ensuring the accuracy and reliability of behavioral research. By paying attention to details such as handling techniques, environmental conditions, and the consistency of the handler's approach, you can minimize stress and variability in their subjects, leading to more reliable data and better animal welfare. Ethical and meticulous handling of animals not only enhances the quality of research but also upholds the principles of humane treatment. Consistency seems to be the key in everything mentioned above. Now you just need a consistent and reliable way to collect your data. Take a look at the PhenoTyper for example, which gives you a controlled environment with tons of customization options. RESOURCES Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources --- ## 5 tips to help behavioral researchers comply with privacy legislation URL: https://noldus.com/blog/viso-gdpr Published: 2024-07-29 11:00:00 Description: Privacy legislation can mean extra concerns for behavioral researchers, but these tips make your life easier. We all generate data about ourselves every time that we use the internet, take a journey or purchase an item. That sort of information can reveal a lot about a person, including private and personal things that you don't necessarily want everyone to know and that could lead to discrimination. Because of that, many countries and regions have upgraded their privacy laws in recent years. Legislation The personal data of the entire European Union is protected by the General Data Protection Regulation (GDPR) and the health data of American citizens is protected by the Health Information Portability and Accountability Act (HIPAA), for instance. California gives its consumers additional protection with the California Consumer Privacy Act (CCPA). All those laws are valuable in protecting citizens' rights, but they can make the work of scientists such as psychologists, health researchers and consumer behavior researchers more complicated. If you are doing that sort of research, you routinely collect personal information in your experiments and often sensitive personal information like data about children or health. How can you be sure that you are complying with the laws that apply in your area? GDPR (and how to comply) The EU GDPR is still the toughest privacy legislation in the world, so if you comply with that, you will most likely be ok wherever you live. Of course, if you are a researcher, your own organization's ethics committee might have additional requirements that go beyond the law. The tips below are written specifically from a GDPR perspective, but they will help you wherever you live and work. 1. Professional software Use good professional software, but in the end, it is up to you to use it correctly. Software for behavioral researchers like Noldus' Viso has been designed with privacy in mind. If you use Viso, you can be confident that your data is safe. If you choose an alternative like an open-source program, you will need to check if it meets your needs. For instance, if the computer is in a lab or shared with colleagues, is there proper user management to ensure that everyone can only access their own experiments? However, even if the software is good quality, that doesn't make it impossible for you to use it improperly. 2. Physical security In this digital age, it is easy to forget the importance of physical security. If you are coding a video and you walk away from the screen, do you lock the computer? If not, who can see it? Colleagues working on other projects? Your housemates when you are working from home? Who can enter the room where the data is kept? If you want to be sure that a camera in your lab is not accidentally recording when it should not be, a physical cover can be a good option. 3. Digital security Just because you have to log on to Windows to open your computer, doesn't mean that all the data on it is secure. It is essential that the hard disk is encrypted using software like Bitlocker. That is built into more recent versions of Windows if you have a modern computer. Software like Noldus' Viso has sophisticated user management to ensure that people working on different experiments in the same lab only have access to their own data, which adds an extra layer of protection. It is also important to note that all the data is stored on the client's computers and that Noldus has no access to it. 4. Install updates Always install all security updates, both for Windows and for the software that you use to collect your observational data. That applies both to your own computer and to any network drives and backups. There is not much point encrypting your hard drive if you make a backup to an unencrypted external drive or to a network drive which can be accessed by people not involved with the experiment that you are running. 5. Permission A key aspect of dealing with privacy issues is to make sure that you have got permission from your participants for everything that you will do with the data and that they are well-informed. Don't forget to include aspects like your retention policy (how long you will keep the data before deleting it) and data sharing with others (e.g. the helpdesk of the company providing the software that you use) in the consent form. It is also the case that no matter what consent people sign on the forms, their legal rights are retained, so for instance, they still have the 'right to be forgotten', also if you have paid them to participate. When starting a recording/experiment in The Observer XT and Viso, a reminder is displayed to remind you to ask the participant for permission. AV tool Viso Viso is the easy-to-use solution for creating audio-video recordings to capture the behaviors of your participants, including screen capture if you want that. You can use it to educate, train, and improve the skills of students and trainees. Viso enables you to record in multiple rooms with all the data reliably coming together into one system, even if they are in different buildings. You can view it anywhere, even on your phone, with the web app. You can also mark and comment on the videos to make feedback quick and easy. FREE DEMO Try Viso yourself! Request a free demonstration to find out why Viso is the right tool for your training facility! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback and debriefing Free Demo --- ## How to increase attention in commercials for Gen-Z URL: https://noldus.com/blog/increase-attention-commercials-gen-z Published: 2024-07-16 09:03:00 Description: Generation Z has the shortest attention span for commercials, yet they are becoming an increasingly important market segment. Understanding what captures their interest and how to engage them in commercials is crucial. This blog post was written by Pim Sommerdijk, who completed his Master's degree in Commercial communication in Communication Sciences at Radboud University in Nijmegen, The Netherlands. The thesis was supervised by Paul Ketelaar, Assistant Professor in Communication Science and the Behavioural Science Institute (BSI) at Radboud University. Advertising avoidance In today's saturated digital advertising landscape, the battle for consumer attention is fiercer than ever. Consumers increasingly avoid ads, perceiving them as intrusive, annoying, or boring1. Generation Z has the shortest attention span for commercials, yet they are becoming an increasingly important market segment. Understanding what captures their interest and how to engage them in commercials is crucial for marketers aiming to compete in this competitive market and design effective ads2. Learn more about tools for neuromarketing research. Top-down and bottom-up visual attention processes Advertising avoidance is a result of visual attention processes, where the brain determines which visual information is (un)consciously processed or ignored. Visual attention is driven by both top-down and bottom-up processes. Top-down processes stem from conscious decisions such as motivation, while bottom-up processes are triggered by external automatic stimuli3 4. By strategically leveraging these two processes, advertisers can reduce the likelihood of consumers avoiding ads5 6. This experimental study examined the effects of humor and audio-visual synchrony stimuli on the visual attention of Gen Z in commercials. Humor in advertising can play a crucial role in maintaining conscious attention, engaging top-down processes7 8. Additionally, synchronizing audio with visual elements in ads can automatically draw people's attention to these visuals, engaging bottom-up processes9 10. Figure 1: This study examines the effects of humor and audiovisual synchronicity on visual attention when watching an advertisement. Measuring visual attention with FaceReader Online Using FaceReader Online eye tracking software enables real-time measurement of where and for how long individuals gaze at commercials, eliminating the need for post-viewing attention recall through survey questions. This is crucial in advertising, as consumers often engage with ads subconsciously11. To compare the results of both methods, this study utilized both survey questions and FaceReader Online to measure attention. FREE WHITE PAPER Eye tracking & FaceReader Download this white paper to learn about: - Subconscious processes and emotion recognition - Combining FaceReader™ and eye tracking - Visualizing and analyzing your data Submit to download Creating ads with humor and audiovisual synchronicity For the experiment, four commercials were created, each employing various combinations of humor and audio-visual synchrony. In the initial segment of the ads, humor manipulation involved adding or removing comedic elements from an existing commercial. Humor was manipulated in this segment to enhance engagement and alertness for the subsequent segment of the commercial. Subsequently, a complementary second segment of the commercial was developed. Additional visuals were incorporated in a manner that demanded viewer attentiveness to notice, such as placing them in the corners of the screen. The idea behind this was that individuals exposed to a more humorous commercial would be more alert than those who were not, thus more likely to notice the additional visuals. To manipulate audio-visual synchrony, sound effects were either synchronously or asynchronously added to the additional visuals in the second segment of the ads, aiming to test how audio-visual synchrony influences visual attention. Using eye tracking technology, the duration of gaze towards these additional visuals was measured among different groups, followed by result comparisons12. Figure 2: How gaze directions where measured Enhancing visual attention An experiment involving 133 participants, aged 18 to 29 with an average age of 22, was conducted to study visual attention. Participants were randomly divided into four groups, each exposed to different combinations of humor and audio-visual synchronization in commercials. The study was conducted online via Qualtrics, requiring participants to use a webcam and the appropriate browser for the FaceReader software, which recorded their visual attention. The survey began with demographic questions, followed by a two-commercial block, with the second commercial serving as the primary stimulus. FaceReader tracked participants' gaze directions during the commercial. Afterwards, they answered questions about their attention to specific areas of interest (AOIs). The results of the study showed that commercials infused with a substantial dose of humor attract more visual attention compared to their less humorous counterparts. This underscores the potent role humor plays in capturing the attention of Generation Z. Additionally, it was observed that commercials in which visual and auditory elements synchronize receive more attention than those where that is not the case. Furthermore, the findings indicate that smartly combining both elements further enhances visual attention, surpassing the impact of using them separately. You may also like to read about the effects of disclosures on sponsored or AI-generated content. How FaceReader Online may provide new insights for measuring attention While not the primary focus of the research, this study underscores the importance of utilizing eye tracking software for measuring visual attention. Eye tracking revealed significant effects of humor and sound synchronization, as well as their combination, whereas self-reporting showed no significant results. In previous studies, attention has often been measured using self-report scales, but this method isn't always deemed accurate due to memory lapses and lack of engagement in self-reporting13. Additionally, cognitive processes elicited by commercials often occur unconsciously, making it challenging for consumers to consciously reflect upon them14. FaceReader Online holds significant promise in this regard, as it serves as a valuable tool to enhance understanding of attention by examining real-time screen-viewing data. Also read: Why you should use FaceReader Online for your human behavior research. Facilitating large-scale attention research Finally, FaceReader Online is user-friendly, enabling the recruitment of a large number of participants. By integrating FaceReader with online surveys, it's easy to scale up your research. Participation is also convenient for respondents, as they can choose whether and when to participate in the study. This facilitates large-scale research. Utilizing FaceReader Online allows us to enhance our understanding of attention, complement existing scientific knowledge and measurement methods, and gain valuable insights into the effects of attention. References - Jeon, Y. A., Ryoo, Y., & Yoon, H. J. (2022). Increasing the Efficacy of Emotional Appeal Ads on Online Video-Watching Platforms: The Effects of Goals and Emotional Approach Tendency on Ad-Skipping Behavior. Journal Of Advertising, 53(1), 1–18. https://doi.org/10.1080/00913367.2022.2073299 - Southgate, D. (2017). The Emergence of Generation Z And Its Impact in Advertising. Journal Of Advertising Research, 57(2), 227–235. https://doi.org/10.2501/jar-2017-028 - Zhang, X., Fan, C., Yuan, S., & Peng, Z. (2015). An Advertisement Video Analysis System Based on Eye-Tracking. IEEE. https://doi.org/10.1109/smartcity.2015.118 - Parkhurst, D., Law, K., & Niebur, E. (2002). Modeling the role of salience in the allocation of overt visual attention. Vision Research, 42(1), 107–123. https://doi.org/10.1016/s0042-6989(01)00250-4 - Rosengren, S., Eisend, M., Koslow, S., & Dahlén, M. (2020). A Meta-Analysis of When and How Advertising Creativity Works. Journal Of Marketing, 84(6), 39–56. https://doi.org/10.1177/0022242920929288 - Gordon, N., Tsuchiya, N., Koenig-Robert, R., & Hohwy, J. (2019). Expectation and attention increase the integration of top-down and bottom-up signals in perception through different pathways. PLoS Biology, 17(4), e3000233. https://doi.org/10.1371/journal.pbio.3000233 - Strick, M., Van Baaren, R. B., Holland, R. W., & Van Knippenberg, A. (2009). Humor in advertisements enhances product liking by mere association. Journal Of Experimental Psychology: Applied, 15(1), 35–45. https://doi.org/10.1037/a0014812 - Schmidt, S. R., & Williams, A. (2001). Memory for humorous cartoons. Memory & Cognition, 29(2), 305–311. https://doi.org/10.3758/bf03194924 - Miller, J., Carlson, L., & McAuley, J. D. (2012). When what you hear influences when you see. Psychological Science, 24(1), 11–18. https://doi.org/10.1177/0956797612446707 - Simmonds, L., Bogomolova, S., Kennedy, R., Nenycz‐Thiel, M., & Bellman, S. (2020). A dual‐process model of how incorporating audio‐visual sensory cues in video advertising promotes active attention. Psychology & Marketing, 37(8), 1057–1067. https://doi.org/10.1002/mar.21357 - Vraga, E., Bode, L., & Troller-Renfree, S. (2016). Beyond Self-Reports: Using Eye Tracking to Measure Topic and Style Differences in Attention to Social Media Content. Communication Methods And Measures, 10(2–3), 149–164. https://doi.org/10.1080/19312458.2016.1150443 - Zhang, X., & Yuan, S. (2018). An Eye Tracking Analysis for Video Advertising: Relationship Between Advertisement Elements and Effectiveness. IEEE Access, 6, 10699–10707. https://doi.org/10.1109/access.2018.2802206 - Badejo, M. A., Ramtin, S., Rossano, A., Ring, D., Koenig, K., & Crijns, T. J. (2022). Does Adjusting for Social Desirability Reduce Ceiling Effects and Increase Variation of Patient-Reported Experience Measures? Journal Of Patient Experience, 9, 237437352210791. https://doi.org/10.1177/23743735221079144 - Greene, B. A. (2015). Measuring Cognitive Engagement With Self-Report Scales: Reflections From Over 20 Years of Research. Educational Psychologist :/Educational Psychologist, 50(1), 14–30. https://doi.org/10.1080/00461520.2014.989230 --- ## How to study developmental psychology: methods, designs & tools URL: https://noldus.com/blog/how-to-study-developmental-psychology Published: 2024-07-09 08:35:00 Description: What should you consider when setting up a study in the field of development psychology? Read on to learn more about methods, designs & tools. Every person goes through a development during his life. A physical development, but also a social, emotional, cognitive, and intellectual development. Researchers in developmental psychology examine the various stages of life, from baby to schoolchild, to adolescent, to adult and finally to the elderly. They look at how and why people do the things they do. Observing people’s behavior is a good method for this. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial What is developmental psychology? Developmental psychology is a scientific discipline that explores how individuals change and grow across their lifespan, focusing on the physical, cognitive, emotional, and social aspects of development. It examines how various factors, such as genetics, environment, and experiences, shape and influence an individual's development from infancy to adulthood.  By studying developmental processes, researchers gain insights into typical and atypical patterns of human behavior, contributing to our understanding of human development and informing interventions to support healthy development. Studying changes across the lifespan Not only the observable actions are studied, but also how people perceive themselves and the world, how they think and fantasize and which feelings and desires they experience. Moreover, it is not only about the development of an individual researchers look at, but also about the development of interactions between people and about the development of relationships and groups. The knowledge that arises from these studies can make a difference in areas such as youth health care, education, in policy formulation, or it can contribute to solutions for societal challenges. After all, while most people follow common patterns in their development, others reach developmental milestones at a different pace. Research in developmental psychology is designed to help all people reach their full potential. Research methods to study developmental psychology Besides behavioral observation, as mentioned above, there are other additional ways to scrutinize the development of humans and answer your research questions. For example, think of: - Controlled experiments, such as the Still Face Experiment or Piaget’s conservation tasks - In-depth interviews - Self-reports or surveys, such as the Social Skills Questionnaire (SSQ) or the Minnesota Multiphasic Personality Inventory (MMPI) - Correlational studies - Archival research Since developmental psychology is all about time and how things change over the course of life, it is important to combine the above mentioned methods with a longitudinal or cross-sectional research design. For example, you can conduct a longitudinal experiment or a cross-sectional survey. See more research examples of Developmental Psychology. Longitudinal versus cross-sectional research design The main idea behind longitudinal research is that you take one group of people – all of the same age – and study them over some period of time. This could be weeks, months, or even years. §This way, you can investigate changes in individuals over time by comparing one person’s data at several moments in time.  It brings you in-depth data and a high internal validity. The disadvantages are that this is very time-consuming and the chance that participants drop out is high. Instead, you can do a cross-sectional study. In this case, you compare groups of people of different ages at one point of time. This is a much quicker way of doing research, you get fast results, and you do not have to worry about people dropping out.  However, it is possible that cohort effects will appear. The differences found in one group may be caused by age, or because people in a particular group grew up under different circumstances or were exposed to different influences. Equipment available for developmental psychology research There is quite a few equipment available to gather data in the best possible way. Things to consider when you set up a study for answering your research questions are for example: 1. Do you want to go on site to gather data, use an online tool, or is a laboratory setting more suitable? A perfect solution for the first option is to use a portable lab. This way, all equipment needed is packed in a suitcase, which you can carry around, put in the back of your car, or even take with you on a plane trip. It is easy to set up and enables you to gather data from participants while they behave in their natural environment, such as their own home. If you want to engage a large number of participants located all over the world, FaceReader Online can help you collect data about their facial expressions. This online tool allows you to capture participants' responses to websites or videos and easily see which element triggers the desired responses – such as joy, interest, or arousal. In addition, with the integrated EyeReader, eye tracking analysis with a regular webcam is available as well.  To be able to control all kind of settings or circumstances for your experiment or if you need a lot of additional hardware to measure your data with and you do not want to be dragging all this stuff back and forth, a stationary observation lab is more suitable.  It can be equipped with cameras, microphones, a one-way mirror to observe participants unobtrusively, data acquisition systems, eye-trackers, and much more. All the equipment is built in and integrates nicely, making it a smoothly running lab.  BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download However, building a lab is not just about the hardware, you also need software to facilitate your data collection. To choose which software fits best, something to consider is: 2. Will your dataset mostly exist of qualitative or quantitative data? A software system such as Viso is particularly suitable to gather qualitative data. This audio and video recording system enables you to control multiple cameras from different angles and to zoom in on certain situations. In the picture below, you can see an example. One camera is pointed at the parent’s face, the second on the child, and the third one on both parent and child, providing an overview of the situation. Besides, in Viso you can predefine relevant behaviors you want to study and annotate these during or after your observations or recording sessions. You can play back the recorded sessions immediately afterwards, without any downtime. If you want to add other measurement tools to your observations to  enrich your data on (unconscious) behavior, NoldusHub will fit perfectly. It simplifies the process of calibration and starting several acquisition tools to collect data such as facial expressions, gaze, skin conductance, and heart rate, all at the same time. From setting up to connecting all your devices, to recording and visualizing results in a clear way, NoldusHub makes multimodal research easy. To be able to analyze your data quantitatively, you need a software tool such as The Observer XT. This is a manual event recorder for detailed annotations and analysis. With use of more detailed coding schemes, you can create a log of annotated behaviors, thus providing insight on length and frequency of the behavior and then analyze these behaviors in a descriptive or numerical way. The analysis options make The Observer XT a unique tool. Also read: how to make coding behavioral data more fun. To finish, there is a third important element that you should take into account in your study setup and choice of equipment: 3. Are your participants able to describe their feelings in spoken words? If your research includes children, especially babies, they may not be able to let you know how they feel or what there are thinking by putting it into words or answering a survey question. §To be able to measure some of these feelings and emotions in another way, you can assess their non-verbal behavior. A quantitative tool to measure non-verbal behavior from facial expressions is for example FaceReader. Based on Action Units in the face, FaceReader determines six basic emotions, as well as valence and arousal. Especially for infants ranging in age from 6 to 24 months old, Baby FaceReader is available. Put it all together in one clear overview There are many ways to conduct your research in developmental psychology and available tools to support you in this. In order to put everything together in an orderly manner, we have developed an informative pdf. Check it out at your convenience: Innovative solutions for psychology research. References - Webinar ‘Research in Developmental Psychology’: https://www.noldus.com/webinars#developmentalpsychology - Still Face Experiment: https://www.youtube.com/watch?v=apzXGEbZht0 - Piaget’s conservation tasks: https://www.youtube.com/watch?v=gnArvcWaH6I - Research methods in developmental psychology: https://www.youtube.com/watch?v=P3sWPGMg-9U - Theories of Development: Research Methods: https://www.youtube.com/watch?v=F_HTEYwa0UI - Must-reads on psychology and behavioral coding --- ## How FaceReader is validated in research URL: https://noldus.com/blog/how-facereader-is-validated-in-research Published: 2024-06-26 10:50:00 Description: In this blog post, we'll dive deeper into the validity and different applications of FaceReader—the most robust tool for automated facial expression analysis. From psychology to education or consumer behavior: facial expressions provide researchers with valuable insights into human emotions. Yes, you can use surveys or interviews to ask people about what they feel—but we're often not able to recognize or explain exactly what we feel at that moment. Facial expressions, on the other hand, reveal our immediate and unconscious emotional reactions. And with the latest tools, you can measure facial expressions quickly and objectively. In this blog post, we'll dive deeper into the validity and different applications of FaceReader—the most robust tool for automated facial expression analysis. What can you measure with FaceReader? FaceReader measures the six basic emotions as proposed by Ekman1: happiness, surprise, anger, fear, disgust, and sadness. The software is also able to recognize contempt and a neutral state, and provides information on gaze direction and head orientation. You'll also find measurements of Action Units (AUs), which describe muscle movements in the face. Moreover, FaceReader shows you how positive or negative an emotion is (valence), as well as the level of activity or alertness (arousal). These can be visualized in FaceReader as a circumplex model, as described in Russell's theory of emotion2. For additional options, FaceReader offers modules to analyze your data in more detail, create custom expressions, measure heart rate and heart rate variability, and analyze eating and drinking behavior. You can also choose Baby FaceReader for research with children between 6 and 24 months old, or go for greater flexibility in data collection with FaceReader Online. Dr. Erin Heerey from Western University explains how FaceReader has not only increased throughput, accuracy, and ease of scoring social behaviors, but has also made it possible to share this data more easily amongst other researchers. Watch the video to learn more about her research. How researchers determine FaceReader's accuracy With all of these options for automated analysis available, it's important to know if it actually works. How accurate is FaceReader in determining facial expressions? Luckily, FaceReader has been validated extensively by different parties and researchers—unlike a lot of other facial expression analysis tools in the market, both freeware and paid tools. To examine FaceReader's validity, these researchers compared the results of the software with that of trained human coders. Another way to study accuracy is to compare FaceReader's results with the intended expressions of existing databases. Examples of these databases are the Amsterdam Dynamic Facial Expression Set (ADFES)3, Radboud Faces Database (RaFD)4, and Warsaw Set of Emotional Facial Expression Pictures (WSEFEP).5 They consist of highly standardized images of emotional expressions from people with different ethnicities. Accuracy of classification Let's look at a couple of studies that focus on FaceReader's accuracy in determining the basic emotions. - In a comparison between results of FaceReader 9 and the ADFES dataset, available in our FaceReader Methodology note, you can see that FaceReader determines the basic emotions very accurately. - Researcher Stöckli and her colleagues found that FaceReader was 88% accurate, while iMotion's AFFDEX algorithm only gained 70% accuracy in determining facial expressions6. - Researcher Lewinski and his colleagues studied the validity of FaceReader 6 against the WSEFEP and ADFES databases7. They found an average accuracy rate of 88%. FaceReader performed best when determining happiness (96%) and faced most challenges with recognizing anger (76%). - A systematic literature review by researcher Landmann showed accuracy rates for FaceReader between 80 and 90 percent, including different FaceReader versions8. As Landmann puts it: "Since, in the conducted studies, such mappings by humans achieved maximally equally good results, it can be assumed that FaceReader evaluations do not require any additional correction by humans and even outperform humans in some cases." RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources How accurately does FaceReader measure Action Units? There are also several studies examining FaceReader's accuracy in detecting Action Units (AUs). - When examining the accuracy of FaceReader Action Units, Gudi and Ivan looked at agreement scores between human coders and the FaceReader software.9 On average, they found an agreement score of 0.81, indicating that FaceReader provides reliable results. Looking more closely, they found agreement scores between 0.79 and 0.95 for most AUs. - The same researchers also compared Action Unit results from Baby FaceReader with those of human coders and found an average agreement score of 0.83, with only two AUs performing under 0.80. These results show that FaceReader is also a reliable tool for facial expression analysis with infants. - Zaharieva and her team studied AU classifications in Baby FaceReader as well10. They found that automated detection of smiling (AU12) worked well in discriminating positive from negative or neutral facial expressions. Similarly, brow lowering (AU3 + AU4) performed best when distinguishing neutral from negative expressions. - In the study by Lewinski that we discussed above, the team also studied FaceReader 6 accuracy in determining AUs. They found that FaceReader detects AUs 1, 2, 4, 5, 6, 9, 12, 15, and 25 with high accuracy, making them suitable to use in research. Why you should choose automated facial expression analysis Automated facial expression analysis is fast, objective, and reliable. FaceReader is highly accurate in determining facial expressions and offers researchers a wealth of options when collecting or analyzing their data. It allows you to collect more detailed emotion data—in less time. References 1. Ekman, P. (1992). An argument for basic emotions. Cognition & emotion, 6(3-4), 169-200. https://doi.org/10.1080/02699939208411068 2. Scarantino, A. (2015). Basic emotions, psychological construction, and the problem of variability. In L.F. Barrett & J.A. Russell (Eds.), The psychological construction of emotion (pp. 334–376). The Guilford Press. https://psycnet.apa.org/record/2014-10678-014 3. Van der Schalk, J.; Hawk, S.; Fischer, A.; Doosje, B. (2011). Moving faces, looking places: Validation of the Amsterdam Dynamic Facial Expression Set (ADFES). Emotion, 11(4), 907–920. https://doi.org/10.1037/a0023853 4. Langner, O.; Dotsch, R.; Bijlstra, G.; Wigboldus, D.; Hawk, S.; van Knippenberg, A. (2010). Presentation and validation of the Radboud Faces Database. Cognition & Emotion, 24(8), 1377—1388. http://dx.doi.org/10.1080/02699930903485076 5. Olszanowski, M.; Pochwatko, G.; Kuklinski, K.; Scibor-Rylski, M.; Lewinski, P.; Ohme, R. (2014). Warsaw set of emotional facial expression pictures: a validation study of facial display photographs. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.01516 6. Stöckli, S.; Schulte-Mecklenbeck, M.; Borer, S.; Samson, A. (2017). Facial expression analysis with AFFDEX and FACET: A validation study. Behavior Research Methods, 50, 1446-1460. https://doi.org/10.3758/s13428-017-0996-1 7. Lewinski, P.; den Uyl, T.; Butler, C. (2014). Automated Facial Coding: Validation of Basic Emotions and FACS AUs in FaceReader. Journal of Neuroscience, Psychology, and Economics, 4, 227-236. http://dx.doi.org/10.1037/npe0000028 8. Landmann, E. (2023). I can see how you feel - Methodological considerations and handling of Noldus's FaceReader software for emotion measurement. Technological Forecasting & Societal Change, 197. https://doi.org/10.1016/j.techfore.2023.122889 9. Gudi, A.; Ivan, P. (2022). Validation Action Unit Module [White paper]. Available at Noldus Information Technology upon request. 10. Zaharieva, M.; Salvadori, E.; Messinger, D.; Visser, I.; Colonnesi, C. (2024). Automated facial expression measurement in a longitudinal sampleof 4 and 8 month olds: Baby FaceReader 9 and manual coding of affective expressions. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02301-3 --- ## Human Factors and Ergonomics research in the spotlight URL: https://noldus.com/blog/human-factors-and-ergonomics Published: 2024-06-14 12:00:00 Description: We want to set the spotlight on new developments and publications in Human Factors and Ergonomics research. From maritime simulation centers to the use of video observations in human factors research. The Human Factors and Ergonomics Society was founded in 1957. Today it is the world’s largest scientific association for human factors and ergonomics professionals. With over 3,500 members globally, comprised of psychologists, designers, and engineers, all of whom have a common interest in designing systems and equipment to be safe and effective for the people who operate and maintain them. Human Factors and Ergonomics research in the spotlight Every year the Human Factors and Ergonomics Society (HFES) organizes a major scientific event where colleagues can discuss recent developments in Human Factors and Ergonomics research. We have been exhibiting at their annual meetings regularly over the past years. This year the HFES Annual Meeting is organized in Chicago, IL from October 13-17, 2025. We want to set the spotlight on new developments and publications in Human Factors and ergonomics research. Human factor research in a ship bridge simulator The Maritime Research Institute Netherlands (MARIN) in Wageningen is one of the world's leading maritime research institutes. They have developed a brand new 'seven oceans simulation center' that was officially opened in May 2024. These groundbreaking facilities showcases several advanced simulators, including an emission-free ship powered by hydrogen and wind propulsion, a maintenance vessel equipped with cranes and underwater drones for offshore wind turbines. This top-notch simulator center enables MARIN to dive into Human Factors research and analyze ship crew performances under challenging circumstances. This is made possible with a Noldus toolkit for human factor research. Thanks to the integrated technology of NoldusHub, evidence-based behavioral research can be conducted in various virtual training settings, and help optimize communication, interaction and performance. Take a look in their playground, and how they do multimodal research into human decision-making. Study: Assessing user’s acceptance of voice assistant advertising within human-machine interaction Researcher Elaine Mathe used FaceReader during her study about voice assistant marketing. As the user base for digital assistants grows, so does the potential for marketing through voice assistants. However, there is a lack of research on this subject, especially regarding user acceptance, leaving significant knowledge gaps in this emerging field. The experiment In this study, the researcher aimed to assess user acceptance of voice assistant advertising within human-machine interaction. The methodology employed a combination of experimental and quantitative methods, with a focus on autonomic responses to voice assistant marketing. The experiment involved 25 participants divided into experimental and control groups, who interacted with a concealed voice assistant while the researcher manipulated the assistant's responses to gauge user reactions. This approach aimed to provide insights into the effectiveness of voice assistant advertising. Continue reading here for the findings. FREE WHITE PAPER Eye tracking & FaceReader Download this white paper to learn about: - Subconscious processes and emotion recognition - Combining FaceReader™ and eye tracking - Visualizing and analyzing your data Download Study: Courier truck redesign In the International Journal of Industrial Ergonomics, Hurley et al. (2012) present an interesting evaluation study. They studied the use of a standard courier truck compared to a prototype courier truck to be able to reduce the unnecessary and double-handling of packages. Since many courier truck drivers fall victim to MSDs (musculoskeletal disorders) due to everyday tasks of a courier driver, it is a logical step to work on improving their current situation. A possible solution could be an effective redesign of the courier truck. The experiment Hurley et al. set up an experiment in which they used a simulated delivery route where courier truck drivers had to deliver small, lightweight boxes along with large, heavy boxes. By using four cameras, the researchers captured all the behaviors of the truck drivers. A set of muscles were selected and surface EMG was collected to capture the demands of the distal upper extremity, shoulder and lower back which Hurley et al. identified as highly loaded body parts during previous observations of courier drivers. Integrate EMG data with video observations The video and EMG data were loaded and synchronized into video analysis software The Observer XT. All of the tasks performed were coded using the program. The researchers explain that this allowed for the assessment of the task performed, timing of tasks, number of lifts, location of lifts, and the ability to synchronize the EMG data with the specific tasks being performed. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Suitable intervention? Hurley et al. conclude that the productivity improved with the prototype courier truck. Also, all ten courier drivers rated the prototype courier truck as being superior to the current truck. The researches gained a lot of knowledge by observing the prototype courier truck. One of the biggest changes between trucks was the number of times the cart was lifted on and off the truck. When wanting to prevent MSD’s, a redesigned truck could be a suitable intervention, keeping in mind that there are several factors which play a role in the physical and mental workload of the driver. Reference Hurley, K.; Marshall, J.; Hogan, K.; Wells, R. (2012). A comparison of productivity and physical demands during parcel delivery using a standard and a prototype electric courier truck. International Journal of Industrial Ergonomics, 42, 384-391. --- ## Did you know about these tips and tricks in EthoVision XT? URL: https://noldus.com/blog/ethovision-tips Published: 2024-06-13 15:00:00 Description: Whether you are a seasoned user of EthoVision XT or just starting out. There is always an opportunity to learn more about the best video tracking software available. EthoVision XT, one of the most advanced behavioral tracking softwares, has been around for quite some time now and is used by many scientists of various skill levels. At Noldus we strive to provide software to our users that are both easy to use and have all the capabilities you might need. However, since EthoVision XT is such an expansive program there are a myriad of features you might have missed. A new user or seasoned veteran, that doesn't matter: there is always an opportunity to learn more about this great piece of tech. In this blog post we will go over some of the best features of EthoVision XT that make your research easier and better! 1) Gain a head-start with templates If you are doing behavioral research and are using standard tests like the Morris water maze or the open field test, there is a good chance you don't have to do much to get started with EthoVision XT. When you start a new experiment, you can choose to start your experiment from a template. With this template, you can select your subject animal, test, and a variety of other parameters. After selecting, EthoVision XT will help to set-up your experiment in a few clicks. But don't worry! EthoVision is not a black box, you can still change all the detection settings to perfectly fit your research needs. Not only can you use the templates EthoVision XT provides, but you can also use your own previous experiments to function as a template for the next. This saves you time and work and makes it easy for anyone in your lab to pick up where you left off. (and also keeps it consistent!). 2) What should I actually measure? EthoVision XT has many features that can advance your research. However, this great variety of features can also make it difficult to focus on the things you really need. When creating an experiment be very mindful of: • What are you trying to measure? By that we mean the behavioral significance of that data. • Make sure that all the data that is relevant to your study is tracked. This way, your data set will be focused and clearly defined and make your analysis cleaner, which also reduces the chance of misinterpretations. Therefore, being aware of all these possibilities within EthoVision XT is very important. Luckily, we have plenty of resources available to help you find your perfect set up! And we are always happy to discuss all the options that EthoVision XT can offer you, for your specific needs. FREE E-BOOK Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download 3) The most optimal detection settings EthoVision XT can analyze a great variety of animals in many environments. However, to get the most accurate results it is essential that you correctly prepare and set your detection settings. Here are some quick tips to optimize your detection settings. • Resetting the background Having trouble with certain objects or reflections in your arena? EthoVision XT has a quick and easy feature to reset the background in the detection settings. Under the playback control is a camera icon. Clicking this icon will reset the background and prevent certain objects from being tracked as a subject. Obviously, only reset the background on a video frame that doesn't include your subject animal. • Fixing nose-tail point detection If you are using pixel based 3-body-point analysis sometimes the nose or tail point can be misinterpreted. To make the detection more accurate you can erode the pixels on the outside of the detected animal. This will reduce the number of "jumps" to body parts that are not supposed to be tracked. Furthermore, making sure that your arena is prepped well and your hardware is up to date is key to proper detection. The lighting of the arena, the distance to the camera and the type of camera are all very important things to consider in your preparation. You can read more about the importance of the type of camera in this blog. However, some misinterpretations may persist even after erosion and setting everything up perfectly, and for this we have developed a deep learning-based algorithm that can flawlessly track nose and tail points: more on that in the next tip! 4) Use deep learning-based tracking! Did you know that EthoVision XT can use AI to detect the nose and tail points in rodents? This method is vastly superior to the original contour-based tracking. EthoVision XT uses a trained neural network to very accurately track these nose and tail points. This results in extremely stable detection of the body points and therefore really takes your research to the next level, and simply much more efficient! Don't worry, from EthoVision XT 16 and onwards, deep learning is part of the base version! You do need a graphics processor (GPU) in your workstation to handle the computations. Deep learning-bases detection is ideal for any researcher doing research on rodent behavior, like novel object testing, mazes with holes, or social preference tests. You can see the difference between the old and new method in this video. 5) Not using a standard test? Use hidden zones! Some behavioral tests require the animal to enter or exit an obscured area. You can think of a study looking into circadian rhythms, using a CognitionWall, or an arena with more complex structures or hiding spots (for example a visual burying system), or even the 'darker' enclosed part of an elevated plus maze. When an animal enters one of these holes it is usually obscured from the camera and therefore no tracking data can be obtained. Hidden zones can be implemented in the detection settings as a separate zone group. Each hidden zone is accompanied by an entry zone. This entry zone is the part of the hidden zone where the animal enters the zone (for example the entry hole to a shelter). If the animal disappears from the camera's view while in the entry zone it is counted as in the hidden zone. Then, when the animal comes out of the hidden zone normal tracking resumes. Hidden zones are very useful when performing these types of behavioral tests. If you want to learn more about hidden zones and want a step-by-step guide on how to make them? We have an great webinar on the ins and outs of hidden zones in our webinar catalog. 6) Noldus is here to help along the way Even with all the tips we provided there might still be some questions left unanswered or features you don't know about. Luckily, Noldus has a plethora of resources to help you along. Last year, we released the NoldusAcademy. Within this learning platform you can learn all about EthoVision XT and its many features by following the Academy training course, ideal for new users like students or seasoned researchers that might need a quick reminder course. Furthermore, the academy also holds our full library of webinars we have hosted over the years. These webinars cover everything from research applications to technical briefings and scientific discussions. You can access the academy when you are subscribed to NoldusCare. However, you can check out this sample lesson for free. Moreover, Within EthoVision XT you can find clear explanation videos in the help menu. These videos clearly explain everything from setting up an experiment to analyzing the data. Lastly, if you have any questions regarding EthoVision XT or your research? You can always contact us, and we will help you out. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial --- ## The 5 best ways to use FaceReader: a systematic review URL: https://noldus.com/blog/5-best-ways-to-use-facereader Published: 2024-05-23 14:02:00 Description: Facial expressions offer a rich source of information about human emotions. In this study, Elisa Landmann examines the best ways to collect, handle, and analyze FaceReader data in different areas of research. Facial expressions offer a rich source of information about human emotions. Unlike surveys or interviews—which rely on people's ability to articulate what they feel—facial expressions can reveal immediate, unconscious emotional reactions. One of the areas where facial expression analysis is particularly valuable is consumer behavior research, where emotional reactions can significantly influence decision-making processes. But facial expression analysis is also widely used in other research areas, including behavioral science, medicine, psychology, finance, and education. In this study1, Elisa Landmann examines the best way to use FaceReader in these different areas of research, focusing on experimental designs, accurate data handling and analysis, and other methodological considerations. Understanding emotions In the field of emotion research, two important theories of emotion include the basic emotion theory (Ekman2) and the circumplex model (Russell3). The basic emotion theory suggests that there are six universal emotions—happiness, surprise, anger, fear, disgust, and sadness—that we express through our facial muscles. These are also referred to as action units (AUs). The circumplex model describes emotions along a continuum of two main dimensions: valence and arousal. Valence refers to how positive or negative an emotion is, while arousal indicates the level of activity or alertness caused by the emotion. How FaceReader works FaceReader is an automated system for facial expression analysis. The software measures facial expressions according to both the basic emotion theory and the circumplex model, providing researchers with a wealth of information. Other benefits of FaceReader include successful validation in different research areas and a very high accuracy rate—validated with the ADFES dataset4. To learn more about the practical applications of FaceReader in collecting, analyzing, and interpreting emotion data, Landmann performed a systematic literature review. This review includes studies from different areas of behavioral research. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Systematic review of FaceReader After careful selection, Landmann included 64 FaceReader studies in her systematic review, all from peer-reviewed academic articles published between 2013 and 2023. In her examination, she focused on 5 key areas of research with FaceReader: - Relevance and benefits - Collecting and preparing data - How to handle and analyze output - Validity of results - Limiting factors Below, we will discuss her findings for each of these areas. Relevance and benefits of FaceReader FaceReader is used in a variety of research and commercial settings, including medicine, psychology, education, finance, and marketing. As the software is based on algorhitms, facial expression analysis is free from personal bias that would occur in a human coder. It's also much faster. Dr. Erin Heerey from Western University explains how FaceReader analyzes 800 hours of manual coding in just 14 hours! Read more in this blog post about her research on dyadic interactions. Landmann also describes FaceReader's benefits compared to other tools on the market, such as classification of individual AUs, a user-friendly interface, having access to data about valence and arousal, and being able to analyze facial expressions in real-time. Collecting and preparing FaceReader data To optimize data collection with FaceReader, researchers need high-quality video material with clear visibility of facial expressions. This means focusing on adequate lighting and camera angles, but also instructing participants to look directly into the camera and not move their head too much. Moreover, FaceReader evaluates the image's or video's quality, helping researchers to gain and select accurate data for their analysis. By adhering to standardized protocols for data collection and preparation, researchers can enhance the quality and validity of their facial expression analysis. How to handle FaceReader output FaceReader provides researchers with both state logs and more detailed logs, which you can export to other (statistical) programs, like Excel or SPSS. Landmann discusses the different ways that researchers process and analyze their FaceReader data, including AUs and emotion categories. This discussion includes good data handling techniques, such as data cleaning, calculating means or standard deviations, transforming scores into ranks, using cut-off scores, and more. The Project Analysis Module in FaceReader offers advanced analysis of facial expression data. You can easily evaluate stimuli, such as a commercial or an image, by comparing different groups of participants. Create your own filters and base your selection on independent variables. Validity of FaceReader results It remains important to evaluate the accuracy and consistency of FaceReader measurements in capturing emotions across different individuals and contexts. For example, by comparing the software's results with established emotion coding systems or human ratings. Findings from the current literature review show success rates between 80% and 90%, showcasing the software's high accuracy. As Landmann puts it: "FaceReader evaluations do not require any additional correction by humans and even outperform humans in some cases." Landmann suggests that FaceReader is most accurate when assessing the basic emotions, although the distinction between subtle display of surprise, fear, and anger may need to be overseen by a human coder. Limiting factors when using FaceReader Lastly, Landmann discusses the limitations of FaceReader. As the software is only able to analyze one face at a time, she argues that this makes it less suitable to measure emotions of multiple people at the same time. For example, when studying interactions. Moreover, the quality of an image or video determines whether researchers can use the data—and it can be distorded by factors like using the wrong recording angle or a participant moving too much. Understanding FaceReader's strengths and limitations is essential for researchers, so they can consider what methods to supplement their facial expression analysis with. Wide applications of FaceReader Landmann's study not only highlights the robustness of FaceReader in analyzing emotional responses, but also emphasizes how standardized guidelines help to optimize its use across different research domains. In marketing, for example, understanding consumers' emotional reactions to advertisements can help improve company content to better meet their needs. In mental health research, objective measures of emotional states could improve the diagnosis and treatment of different disorders. Landmann suggests that as FaceReader software continues to evolve, its applications will expand, offering deeper insights into human emotions. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources References 1. Landmann, E. (2023). I can see how you feel - Methodological considerations and handling of Noldus's FaceReader software for emotion measurement. Technological Forecasting & Societal Change, 197, https://doi.org/10.1016/j.techfore.2023.122889. 2. Ekman, P. (1992). An argument for basic emotions. Cognition & emotion, 6(3-4), 169-200. https://doi.org/10.1080/02699939208411068 3. Scarantino, A. (2015). Basic emotions, psychological construction, and the problem of variability. In L.F. Barrett & J.A. Russell (Eds.), The psychological construction of emotion (pp. 334–376). The Guilford Press. https://psycnet.apa.org/record/2014-10678-014 4. Schalk, J. van der; Hawk, S.T.; Fischer, A.H.; Doosje, B.J. (2011). Moving faces, looking places: The Amsterdam Dynamic Facial Expressions Set (ADFES). Emotion, 11, 907-920. DOI: 10.1037/a0023853 --- ## Why you want to find out if your customers are bored URL: https://noldus.com/blog/facereader-affective-attitudes Published: 2024-05-16 09:53:00 Description: Emotions deeply influence our daily lives, shaping our moods and behaviors - including our decision making. That's why facial expression analysis is often used in consumer and behavior research. Emotions deeply influence our daily lives, shaping our moods and behaviors. When you feel happy, you are more likely to have a productive day at work and enjoy the things you do. It might also make you more receptive to that billboard you saw at the bus stop on your way to work. On the other hand, if you are moody or even getting bored while watching an advertisement, chances are you are not very interested in the product - let alone buy it. Why are emotions important to study? No wonder researchers, advertisers, and marketers are interested in studying these emotions. They play a key role in non-verbal communication and decision making, and are essential to understanding human behavior. For the same reason, many marketing conferences are filled with talks about advertisement effectiveness or the most persuasive texts for packaging design. This general interest in emotions is one of the reasons that facial expression analysis is often used in consumer and behavior research. Emotion data provides crucial insights that allow researchers to explain complex human behaviors in greater depth. Limitations of self-reports on emotion How do you get this emotion data? You can always just ask someone directly, for example, in a survey. However, it is unlikely that you get honest, objective replies. That's because people usually find it very difficult to comment on their own emotions and state of mind. Self-reported emotions are not necessarily what a person is actually feeling at that moment. Moreover, asking how someone feels also means you get an 'after the fact' reply, while you may want to know their real-time emotions. Also try this blog post about consumer experiences during a self-designing process Analyze emotions in real-time That's exactly why facial expression analysis software like FaceReader is such a valuable addition as a research tool in consumer behavior research, as it helps you to collect objective data in real-time. Based on the original basic or universal emotions defined by Paul Ekman1, FaceReader automatically determines the presence and intensity of emotional states happy, sad, angry, surprised, scared, and disgusted. The software also recognizes contempt and a neutral state. This will ensure better understanding of interactions between people, or between people and machines or products. Affective attitudes predict behavior Another perspective from which to study emotion is to include measurement of affective attitudes. Attitudes describe the way we evaluate things, in a negative or positive way. This includes three different elements: affective attitudes (emotions), cognitions (thoughts and knowledge), and actions (past behaviors or experiences).2 The strength of an affective attitude is often a good predictor of behavior. In other words, the stronger the attitude, the more likely it is that it affects behavior. This means that knowing a person's affective attitude can help predict their behavior. This is valuable information for consumer behavior researchers and marketers, as this can also help with predicting whether people will buy a product after seeing an advertisement. You may also like this blog post about influencer marketing for young adults: Disclosure Dilemma Custom expressions in FaceReader In the FaceReader software, you can study the emotions of participants by measuring three common affective attitudes as custom expressions: interest, boredom, and confusion. To estimate these custom expressions, FaceReader determines the intensities of a number of facial action units (AUs), which refer to muscle movements in the face. These intensities are combined with other cues, like head shaking and nodding. These secondary facial affects - available in the Action Unit Module - are more complex than the basic emotions. They are not completely expressed within a single instance, but computed over a window of time. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Measuring affective attitudes supports your marketing efforts Including affective attitudes in your research helps you to gain better insights in how an audience engages with your content or advertisement. Knowing whether your test participants get bored by watching your advertisement for your new product launch can make all the difference in the success of it. References - Ekman, P. Friesen, W.V. (1971). Constants across cultures in the face and emotion. Journal of Personality and Social Psychology, 17, 124-129. - Attitude (psychology) - Wikipedia (WP:CC BY-SA). --- ## Student facial expression analysis while watching instructional videos URL: https://noldus.com/blog/student-facial-expression-analysis Published: 2024-05-06 09:32:00 Description: Is boredom the opposite of interest? Lídia Vinczéné Fekete and her research team used FaceReader and The Observer XT to find out what makes students get bored and which elements encourage interest. This blog post was written by Lídia Vinczéné Fekete, Education Methodology Advisor at the Centre for Educational Quality Enhancement and Methodology of the Corvinus University of Budapest. Student facial analysis while watching instructional videos: Is boredom the opposite of interest? Boredom, a common challenge among higher education students, has been extensively studied in recent years (Finkielsztein, 2020; Sharp et al., 2020; Yadegaridehkordi et al., 2019). Studies have shown its significant negative impact on student performance and well-being. While boredom involves reduced attention and task involvement, it's more than just a lack of interest. (Pekrun et al., 2023; Westgate & Wilson, 2018). With help of the results of such studies, educators can develop instructional materials more effectively by understanding the factors that influence student engagement. A recent study (Sass et al., 2023) explores the dynamic between boredom and interest in student facial expressions during instructional video watching, shedding light on their interplay. Methods to measure students' emotional state The study measured students' emotional states using different tools and channels: - Their facial expressions while watching the video were analysed with FaceReader - Before and after watching the video, they completed a questionnaire assessing their emotional state - Finally, they shared their experiences and opinion about the video in the frame of interviews Results of the questionnaires and automated facial expression detection were analysed by SPSS, FaceReader, and The Observer XT. The instructional video was 22.4 minutes long, so, with the help of The Observer XT, the videos of each participant (recorded by FaceReader) were divided into 30-second time windows. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Boredom and interest were measured with the help of the custom expression analysis function of FaceReader. With The Observer XT the mean values for boredom, interest, arousal, and valence for these intervals (see the graph below) were calculated. Figure 1: Changes in the mean values of boredom and interest per 30 seconds while viewing a 22-minute long video presentation (N=25), measured by facial expression analysis, in 30-second long periods. What makes students get bored Contrary to the assumption that boredom is solely a lack of interest, results revealed an asynchronous relationship between boredom and interest. Factors such as low arousal levels and a "neutral" state played significant roles in boredom. Surprisingly, low interest did not always correlate with high boredom, and vice versa. In the analysis of average scores, however, the study identified periods where boredom and interest moved in opposite directions. This raises the question: what occurred in the instructional video during these intervals when boredom increased while interest decreased? In other words, what made students bored? Figures 2 & 3: What happened in the video when boredom and interest contradict? Elements that encourage students' interest Interviews with students provided additional insights. Visual elements such as graphs and pictures, along with engaging examples and the appearance of the presenter's face, played crucial roles in maintaining attention. Conversely, text-heavy slides and lengthy explanations hindered interest. Overall, the study underscores the importance of video design principles in promoting student's continued interest. Multimedia elements, personalization, and minimizing textual overload can enhance learning experiences and mitigate boredom. By understanding the factors influencing student interest, educators can create more effective instructional materials. The results of the study are summarized in the table below. Table 1 – Features of video followed by episodes of viewer boredom and interest References - Finkielsztein, M. (2020). Class-related academic boredom among university students: A qualitative research on boredom coping strategies. Journal of Further and Higher Education, 44(8), 1098–1113. https://doi.org/10.1080/0309877X.2019.1658729 - Sass, J., Vinczéné Fekete, L., & Bodnár, É. (2023). Boredom as a Challenge to Knowledge Acquisition: Mapping Boredom-Inducing Elements of a Video Presentation, Using Multimodal Measurements. In Proceedings IFKAD: Managing Knowledge for Sustainability (pp. 2379–2393). https://m2.mtmt.hu/api/publication/34026526 - Sharp, J. G., Sharp, J. C., & Young, E. (2020). Academic boredom, engagement and the achievement of undergraduate students at university: A review and synthesis of relevant literature. Research Papers in Education, 35(2), 144–184. https://doi.org/10.1080/02671522.2018.1536891 - Yadegaridehkordi, E., Noor, N. F. B. M., Ayub, M. N. B., Affal, H. B., & Hussin, N. B. (2019). Affective computing in education: A systematic review and future research. Computers & Education, 142, 103649. https://doi.org/10.1016/j.compedu.2019.103649 The implementation of the study presented was supported by the UNKP-23- 3-II-CORVINUS-139 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund. --- ## Did you know you can (semi) socially house tethered animals? URL: https://noldus.com/blog/social-housing-tethered-animals Published: 2024-05-02 13:30:00 Description: Socially housing tethered animals can be challenging, but also crucially beneficial to your study. Read more about how with our PhenoTyper we can solve that dilemma! A significant challenge in behavioral neuroscience research is maintaining social housing for tethered animals. Tethering, which involves attaching devices like EEG electrodes or infusion cannulas to animals, is crucial for continuous physiological monitoring and substance delivery. However, such a setup does not only restrict an animal's movement, but also prevents social housing, which can be vital for the well-being and natural behavior of rodents. Pros and cons of social housing in rodents Pros - Behavioral enrichment: Social interactions facilitate the development of natural behaviors such as grooming, playing, and social hierarchies. These interactions are essential for cognitive and emotional development, contributing significantly to the physiological health of rodents. - Stress reduction: Rodents housed in groups typically exhibit lower stress levels. This reduction in stress can decrease the occurrence of stress-induced pathologies, enhancing the general health and well-being of the animals. - Reliable research outcomes: Studies conducted in socially housed environments often yield more reliable and generalizable results, as the behaviors observed are (more) representative of a natural setting. Cons - Aggression and competition: Social housing can lead to aggression and competition among rodents, potentially resulting in injuries and skewed experimental data. - Increased stress: Because of the above-mentioned, social housing can actually also increase (social) stress. Especially in larger groups that deal with strong hierarchal structures within the cage. Why Tethering? - Continuous monitoring: Tethering allows for the uninterrupted collection of physiological data, crucial in studies requiring detailed, real-time monitoring such as sleep cycles, seizure activities, or drug effects. - Precise substance delivery: Infusion cannulas can deliver drugs or other substances directly into specific regions of the brain, providing targeted therapy and precise dosing controls essential for pharmacological studies. Tethering typically involves securing the animal to a flexible yet restrictive system that permits some movement while ensuring the stability and integrity of the monitoring devices. And while tethering can limit natural behaviors, the use of lightweight cables, swivels to prevent tangling, and customized cage setups can help minimize stress and discomfort. Combining tethering with social housing So, in studies where continuous monitoring is essential, for example in those involving electroencephalography (EEG) to assess neural activity during sleep or response to stimuli, or when conducting a study with continuous drug delivery (by using Instechs swivel arm in the PhenoTyper 2, see image below). In these cases retaining an animal's social environment would be beneficial, but unfortunately very challenging until now. Noldus' PhenoTyper 2 with perforated wall dividers, offers an innovative and interesting compromise. By partitioning the cage into separate yet accessible sections, you can maintain sensory interactions among the animals. This setup not only retains the essential social context, but also accommodates the logistical demands of tethering, striking a balance between animal welfare and research integrity. In the PhenoTyper 4500 (version used for rats) you can even divide the arena into 4 areas. This wall divider allows researchers to divide the enclosure into two or more distinct compartments, and incorporates a semi-social housing condition. This can thus strike a balance between the well-being and natural behavior of rodents, while the PhenoTyper 2 topunit accommodates the necessary equipment for tethered neurological monitoring and other interventions. The subject can be connected to monitoring equipment via a tether, while it can still interact with a partner. The wall divider can for example be outfitted with holes that are sized and positioned in such a way to allow the rodents (mice) to interact and communicate with their cage mates, thereby retaining a level of social interaction. This mitigates both the (social) stress associated with complete social isolation, and any severe aggression issues as well. A PhenoTyper cage with the perforated wall divider Also beneficial with the use of wireless headstages Wireless headstages, a useful tool for monitoring neural activity without the restriction of cables, can also prove to be difficult to use in social housing settings: The headstages can be prone to dislodgment due to fighting or gnawing, common behaviors when animals are housed together. The implementation of wall dividers in the Noldus PhenoTyper can help mitigate these risks. These dividers will thus still allow for social interactions through sensory contacts without full physical contact, reducing the likelihood of aggressive interactions that can lead to the displacement or damage of the wireless headstages. Protecting the integrity of the data and valuable equipment while also maintaining a higher level of animal welfare. Customizable and easy to integrate The wall divider is easy to install and can be customized to meet specific experimental requirements. This flexibility makes the PhenoTyper, in general, an invaluable tool for researchers who require adaptable solutions for complex behavioral studies. The system is powered by Noldus' EthoVision XT software to further ensure that data collection and analysis are seamless and precise, providing researchers with high-quality, reliable data for in-depth behavioral analysis. The PhenoTyper is thus the ideal choice, and sustainable (future-proof) solution, for researchers aiming to conduct cutting-edge studies in neuroscience and related fields. Real world use Here are two real-world examples where the PhenoTyper has been used in studies that could benefit from this wall divider functionality: - Researchers from Baylor College of Medicine used the PhenoTyper system to study the Stargazer mouse model for epilepsy. These mice, which have a genetic mutation affecting their balance and causing spike-wave seizures, were observed in a home cage environment to monitor their behavior and response to environmental changes over time. This kind of study could benefit from the use of the wall divider to house mice socially and separate them, In this way, studying social and environmental impacts on neurological conditions becomes a realistic research goal. Find the blog and the study here! - Buschoff et al did a study with Noldus' PhenoTyper, in which they effectively managed the tethering of rats while allowing considerable freedom of movement, which is essential for normal behavior during EEG monitoring. Their PhenoTyper was equipped with an electrical swivel with a counterbalanced arm, enabled rats to move freely and lift their head while still being connected to EEG recording equipment. This setup facilitated the continuous monitoring of electrical activity in the rats' brains, specifically looking at spike wave discharges, which are crucial for studies involving epilepsy. Adding a social component to this study could be interesting. Find the blog and the study here! - Although the study by Bin et al does not use Noldus' PhenoTyper, it does describe the modifications to a standard mouse cage, which was divided into compartments to facilitate both housing and recording needs. In this case the use of a low torque slip ring as an EEG commutator for continuous tethered EEG monitoring of mice. The setup and/or customization for this study could have been a much more out-of-the-box solution with the PhenoTyper and its wall divider. All in all, the PhenoTyper is a very powerful and versatile piece of tech. You can read about all of the many uses of the PhenoTyper here. Interested to use it to advance your research? Then make sure to also check out the resources below. And of course, always feel free to reach out if you have any comments or questions! RESOURCES Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## 5 reasons to attend Measuring Behavior 2024 URL: https://noldus.com/blog/MB2024-animal Published: 2024-04-22 11:00:00 Description: Measuring Behavior is the conference for all those interested in new methods and tools for measuring the behavior of people and animals. Have a look at all the great learning and networking opportunities you can have. Measuring Behavior is the conference for all those interested in new methods and tools for measuring the behavior of people and animals. We go over 5 reasons why you should attend Measuring Behavior 2024. Also, it is almost May and therefore we have also included some of the presentations and tutorials you can attend during your visit to Aberdeen. 1. It has a unique focus on tools and methods Most scientific conferences focus on the results of studies. However, without methods, there are no results. In recent years, results of previous studies in the behavioral sciences have been called into question because of errors in their methods or because they cannot be reproduced. Therefore, correct methods are vital, and papers associated with methods often have the highest citation rate. Measuring Behavior is mostly focussed on discussing and exploring methods old and new. At the conference you can learn about the latest innovations in rodent, zebrafish, and many other animal and human behavioral research methods. This edition of the conference will have three keynote speakers. These are, zebrafish expert Robert Gerlai (whom we visited last year), professor of mental state monitoring Anne-Marie Brouwer, and lastly Albert Ali Salah who will give a keynote presentation on designing computational tools for behavioral and clinical science. BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Download 2. Measuring Behavior has a strong multi-disciplinary focus At Measuring Behavior you will meet neuroscientists, psychologists, engineers, AI experts, computer scientists, animal welfare experts, livestock researchers, and many more. Experts in measuring both animal and human behavior will be there. Whilst some sessions focus on the detailed issues of a particular discipline, others take advantage of the multitudes of expertise present to discuss cross-cutting issues. You can attend a great variety of symposia to spark your curiosity. For example, - AI advances in pose estimation and behavior recognition in laboratory animals — Loes Ottink, Noldus Information Technology - Methods for the Study of Olfactory learning and Memory — Richard Brown, Dalhousie University - Digital Innovations in Home Cage Monitoring: Advancing Animal Welfare and Pharmaceutical Development— Stefano Gaburro, Tecniplast - Measuring behavior and physiology in and around the cockpit – Anne-Marie Brouwer, TNO and Radboud University - Behavioural phenotyping of genetic mouse models of Alzheimer's disease and frontotemporal dementia — Szu-Han Wang, University of Edinburgh This isn't even the complete list. You can find the full list of symposia here. 3. Demonstrations of the latest technical innovations Measuring Behavior has the normal range of program elements, with symposia, workshops, posters, tutorials, commercial exhibition and social events. In addition, there is the demonstration showcase in which both companies and academics present new inventions and prototypes. Those presentations are often very dynamics and interactive, so that you can be amazed and inspired by the latest innovations in behavioral analysis. Throughout the conference multiple companies will give a demonstration of their latest innovations, which you can listen to and interact with. - Climbing test for automated measurement of vertical activity in mice – Frederico Montechiaro (Ugo Basile) - The Ethometer – Willem Dekkers (Royal GD) - Advanced in-depth phenotyping smart cage – Michael Florea (Olden Labs) - Beats – Alard Weisscher (Eumedia) - A New Approach to Setting Up Operant Conditioning Experiments – Aishwarya Vishwanathan (Stoelting Europe) You can find the schedule to these demonstrations here. 4. It is a well-established conference series, with a rich history Measuring Behavior 2024 will be the thirteenth edition of the conference. The series started as a small workshop in the Netherlands in 1996 and over the years has grown to a well-established scientific meeting. It is sponsored by the industry (Noldus IT is the main sponsor, and they ensure continuity from edition to edition), but it is scientifically independent. Competing companies to Noldus also attend, and they present papers and participate in the exhibition. The scientific presentations are all blind peer-reviewed. 5. Scotland is absolutely stunning Aberdeen is in North-East Scotland. It fronts onto the sea coast, with its sandy beaches and dramatic cliffs. More inland, there are many historic castles and the magnificent Grampian Mountains in the Cairngorms National Park. Aberdeen itself is an attractive bustling city. It was historically a fishing port and in recent years has benefited from the prosperity brought by the oil industry. Even more things to do at Measuring Behavior Of course, the things we mentioned in this blog are not the only events you can visit while you are at Measuring Behavior. There will also be tutorials on how to use certain methods and tools. Furthermore, posters are featured in the same room as the commercial exhibition. On the Thursday the presenters of the posters will stand by their poster to answer question or elaborate on their publication. Lastly, Measuring Behavior is not only about technology and science. It is also about networking and having a great time while doing so. Therefore, we encourage you to join us at the conference dinner and reception, which are held in some of the most beautiful buildings in Aberdeen. If you have any additional questions regarding the measuring behavior conference, you can find all the specific contact information here. --- ## How stress and emotions can affect performance URL: https://noldus.com/blog/how-stress-emotions-affect-performance Published: 2024-04-10 09:38:00 Description: Medical first responders need to undergo extensive trainings to maintain and enhance their skills. Malfait and her team developed a methodology to measure the management of stress and emotions. Every day, medical first responders (medics, nurses, and physicians) bravely rush into the heart of emergencies, ready to save lives and provide critical care. While their dedication and expertise are commendable, what often goes unnoticed are the emotional challenges and stressors they face behind the scenes. Witnessing trauma, grappling with loss, and navigating their own vulnerability, these heroes confront a myriad of emotional and stressful hurdles in their line of duty. Regular practice through simulation training is essential Because they face such complex situations, first responders need to undergo extensive trainings. It enables them to maintain and enhance their skills and to practice various procedures. They will engage in realistic scenarios that closely mimic actual emergency situations. They can practice to coordinate their efforts as a team, delegate tasks, and make critical decisions. By recording these simulation training sessions on video, they get a detailed picture of the situation. By debriefing after the sessions, responders can identify errors, gaps in knowledge, or areas for improvement and implement corrective measures accordingly. This is a vital component of first responders' professional development. Also read: 3 debriefing steps to evaluate a training session Understanding how stress and emotions can affect technical performance In addition to improving both technical and non-technical skills, these training sessions must also address how to recognize and effectively manage emotions and stress. Both individually and at a team level. The research team of Malfait in Brussels, Belgium, focused on this topic in their study. They developed a methodology to measure the performance on technical skills alongside the psychophysiological load during simulation training sessions. Recording observations for detailed analysis In the simulation lab, equipped with multiple pan-tilt-zoom cameras and ceiling microphones, integrated with help of Viso software, participants were invited to perform several medical technical tasks. For example, a cricothyroidotomy - an intervention to help a patient breathe better, such as in cases of severe airway obstruction, trauma, or respiratory failure. Live observations were conducted to monitor participants' performances. They also recorded observations for detailed retrospective microanalysis, using The Observer XT. Therefore, several components of the medical technical skill were coded by an expert. Viso offered the ability to adjust the orientation and zoom of the cameras during recording. Moreover, because images from multiple cameras were available, it became possible to observe the performances from different angles. This created more detailed views and made coding more accurate. Advantages of using The Observer XT for coding and analysis The researchers took advantage of the functionality to pause and play back videos unimpededly at recorded speed, as well as at half-speed, at one fifth- and one twenty-fifth of the speed. Moreover, they appreciated measurement of time intervals and the possibility to perform more in-depth analysis. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Managing stress and emotions The team also wanted to see how much stress the participants felt during the simulation training and how they managed their individual resources, such as coping skills, the ability to bounce back, and the belief in one's ability. Because stress occurs when there is a perceived gap between the demands of the situation and the individual's perceived ability to cope with those demands. The researchers recorded facial expressions using FaceReader and performed voice analysis using Matlab and PRAAT. Both methods rely on systematic measurements of arousal and emotion. Combining both types of analyses allowed them to quantify arousal and valence, according to the circumplex model of emotions. An important condition was that no invasive sensors were needed to capture the information they wanted. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Benefit from a unique combination of simultaneous analysis The study of Malfait and her team offered insight into how first responders perform during simulation training or real-life situations. Big benefits of their developed method lies in the unique combination of simultaneous analysis of technical skill and assessing psychophysiological load. But also in using non-invasive and objective methods, like facial expression analysis and voice analysis, to let us understand the stress level without needing people to tell us, and without interrupting the simulation. Reference Malfait, A.; Puyvelde, M.; Detaille, F.; Neyt, X.; Waroquier, F. & Pattyn, N. (2023). Unveiling Readiness of Medical First Responders in Simulation Trainings: Insights beyond Queries. In: Jay Kalra (eds) Emerging Technologies in Healthcare and Medicine. AHFE International Conference. AHFE Open Access, vol 116. AHFE International, USA. http://doi.org/10.54941/ahfe1004375 --- ## Language development and joint engagement in children with Down syndrome URL: https://noldus.com/blog/joint-engagement-down-syndrome Published: 2024-04-03 09:03:00 Description: In children with Down syndrome, delays in speech and language skills are common, while early social skills are relatively strong. How are these developmental milestones related? Developmental milestones in children with Down syndrome (DS) can be very different from those in neurotypical children. For example, delays in speech and language skills are common in children with DS, while early social interactions are relatively strong. Researchers Mattie and Fanta wanted to know how these early social skills are related to later language development in children with DS. Specifically, they wanted to know more about the role of different types of joint engagement.1 Joint engagement and language development When researchers talk about joint engagement, they refer to the shared focus between a child and their caregiver on an object or activity. It's a social skill, where both participate in observing, interacting with, or discussing an object or event. For all children, including those with Down syndrome, joint engagement is a precursor to language development2. In their study, researchers Mattie and Fanta focus on two types of joint engagement: supported and coordinated joint engagement. First, a child is able to participate in joint engagement with the support of a caregiver. For example, the caregiver can gesture towards or talk about an object in the room. As they develop, children become able to engage more actively with an object and their caregiver, using more initiative and reciprocity. This is referred to as coordinated joint engagement. You may also like to read about cognitive delays, early exploratory behavior, or the relationship between parenting behaviors and executive function in children with Down syndrome. Flexible use of joint engagement Interestingly, research shows that children keep using both forms of joint engagement, depending on the demands of the social situation they're in. Moreover, different studies show a lot of variability in joint engagement skills in DS. Taken together, this indicates that the use of these skills is flexible over the course of a child's development. Understanding more about this relationship between joint engagement and language development helps us to know exactly what children with Down syndrome need help with and at which time. Measuring engagement with The Observer XT The participants in Mattie's and Fanta's study were 16 young children with Down syndrome. The researchers studied them at two time intervals, while the children were 12-30 and 21-38 months of age, respectively. They recorded and analyzed each child's engagement behavior during 15-minute free play sessions between mother and child, using The Observer XT. They focused both on quality and duration of joint engagement behaviors. The research team also measured receptive and expressive language skills at both times. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Children were engaged mostly in supported joint engagement The researchers found that children with Down syndrome engaged more frequently in supported joint engagement than in coordinated joint engagement. This was true for both the initial and the follow up sessions. Interestingly, a few children who had previously used coordinated engagement did not do so in the follow-up, demonstrating again the variability in their use of this engagement type over time. Moreover, the results showed that children who showed higher levels of supported joint engagement during the first time interval tended to have lower expressive language abilities at that same time. However, as time progressed, those with greater levels of joint engagement at the start showed improvements in both expressive and receptive language abilities. These results suggests a complex relationship between joint engagement and language development. Early reliance on supported engagement seem to reflect childrens' efforts to compensate for their language challenges, but over time, this type of engagement appears to support language learning and development. How to support language development in children with Down syndrome With these findings in mind, the researcher team suggests that targeting joint engagement may be helpful for language interventions in children with DS, especially in their second year. Caregivers could pay attention especially to the transition to coordinated joint engagement, by being responsive to their child's attention and providing them with input for language learning. For example, pointing and speaking aloud about what they see helps to focus their child's attention and promotes joint engagement. This active participation from parents and caregivers might lead to better language outcomes for children with Down syndrome. Curious why others choose Noldus for their behavioral research? In this blog post, you'll learn more about what sets us apart. References 1. Mattie, L.; Fanta, D. (2023). Joint engagement and early language abilities in young children with Down syndrome. Frontiers in Psychology, https://doi.org/10.3389/fpsyg.2023.1152559. 2. Smith, C. B.; Adamson, L. B.; Bakeman, R. (1988). Interactional predictors of early language. First Language 8, 143–156. doi: 10.1177/014272378800802304. --- ## Psychology conferences in 2024 and 2025 URL: https://noldus.com/blog/psychology-conferences-2024-2025 Published: 2024-03-31 12:00:00 Description: Conferences are an excellent way to combine work, learning, and social interaction. To help you plan your year, we've curated a comprehensive list of international psychology conferences for 2024 and 2025. Are you looking to expand your knowledge, network with peers, and stay updated on the latest trends in psychology? Conferences are an excellent way to combine work, learning, and social interaction. To help you plan your year, we've curated a comprehensive list of international psychology conferences for 2024 and 2025. Whether you prefer in-person, virtual, or hybrid events, you'll find something that suits your needs. Discover psychology conferences in 2024 and 2025 Conferences offer a unique opportunity to meet fellow professionals and gain valuable insights into the latest research and techniques in psychology. But with so many events happening around the world each year, how do you choose which ones to attend? Our ultimate guide to psychology conferences in 2024 is here to help. We've meticulously sorted the top conferences by region, ensuring you can easily find and attend the best events to advance your career. Don't miss out on these opportunities to learn from industry experts and connect with like-minded individuals. Psychology conferences in Europe in 2024 and 2025 European countries are hosting plenty of psychology conferences where all aspects of psychology research, developmental psychology, and related research will be discussed and showcased: - Global Conference on Psychology – May 17-19, 2024 in Liverpool, United Kingdom - ECPP 2024 (11th European Conference on Positive Psychology) – July 10-13, 2024 in Innsbruck, Austria - The latest advancements in the field of positive psychology and the science of well-being, practical interventions and hands-on experiences will be brought together by leading experts. - ICP 2024 (33rd International Congress of Psychology) – July 21-26, 2024 in Prague, Czech Republic European psychology conferences in 2025 - ECP 2025 (19th European Congress of Psychology) – July 1-4, 2025 in Paphos, Cyprus This European conference will be hosted by the Cyprus Psychologists' Association and is one of the leading international conferences on psychology. - EADP 2025 (European Conference on Developmental Psychology) – August 25-29, 2025 in Vilnius, Lithuania FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly Psychology conferences in USA + Canada in 2024 and 2025 Discover the best psychology conferences in North America. These psychology conferences are taking place on Northern American grounds in the USA and Canada in 2024 and 2025: - SPSP 2024 Annual Convention – February 8-10, 2024 in San Diego, CA - 2024 APS (36th Annual Convention of the Association for Psychological Science) – May 23-26, 2024 in San Francisco, CA - CPA 2024 (84th Annual Convention of the Canadian Psychological Assocation) – June 21-23, 2024 in Ottawa, Canada Program themes include History & Philosophy of Psychology, Environmental Psychology, Social & Personality Psychology, and Quantitative Methods. - APS Global Psychological Science Summit - October 2024 (Virtual) US Conferences on Psychology in 2025 - SPSP 2025 (Annual Convention of the Society for Personality and Social Psychology) – February 23-25, 2025 in Denver, CO - SRCD 2025 (Biennial Meeting of the Society for Research in Child Development) – May 1-3, 2025 in Minneapolis, MN Psychology conferences in Central and South America - WCP24 (24th World Congress of Psychiatry) – November 14-17, 2024 in Mexico City, Mexico This four-day event will offer a dynamic platform for collaboration and dialogue with mental health care peers from all over the world. Psychology conferences in Asia and Oceania Asia and Australia are hosting several conferences – both national and international – on psychology and related topics in 2024 and 2025: - Australian Association of Psychologists Inaugural Conference (AAPI) – 20-22 March, 2024 in Brisbane, Australia - 2024 APS College of Clinical Psychologists Conference – 22-24 March, 2024 in Adelaide, Australia - 2024 Australian Psychological Society (APS) College of Counselling Psychologists Conference – July 26-27, 2024 in Gold Coast, Queensland, Australia - ACP 2024 (14th Asian Conference on Psychology & the Behavioral Sciences) – March 25-29, 2024 in Tokio, Japan and online. FREE WHITE PAPER How to build an observation lab Do you want to learn more how to set up an observation lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download Did we miss any conferences on psychology? And are any of these meetings on your 2024 or 2025 calendar? Want to know more about Noldus and tools for behavioral and psychology research? Discover our brand-new multimodal software system NoldusHub, that enables you to control, calibrate, and monitor multiple behavioral data streams at once. Find out more about our other solutions for human behavior studies here. Or sign up for the Noldus Newsline to stay updated on the conferences we are attending as exhibitor or sponsor! Please note: Noldus Information Technology is not responsible for organizing these conferences and events. More details on each event can be found by visiting the conference event websites. --- ## How to use FaceReader in the lab URL: https://noldus.com/blog/how-use-facereader-lab Published: 2024-03-24 13:00:00 Description: Are you interested in using automatic facial expression analysis in a standardized lab setting? Here are 5 tips to get you started! Many researchers have turned towards using automated facial expression analysis software to help them with getting objective assessments of emotions. FaceReader is a well-established tool for the automation and analysis of facial expressions. How to use FaceReader in the lab Are you interested in using automatic facial expression analysis with FaceReader software in a standardized lab setting? Here are some tips to consider in addition to our earlier tips to optimize facial expression analyses. With these five tips you are ensured to optimize your facial expression analysis during your lab research. 1. Position the camera below the computer screen It is important to record participants' faces from the front as much as possible (see also Loijens' tip 2). When participants are in front of a computer screen, the facial expression coding works better when you place the camera below the computer screen instead of on top of the screen (i.e., record slightly from below instead of from above). This angle reduces the chance of the eyebrows or upper facial muscles being obscured by a downward gaze, which can interfere with accurate emotion detection. Placing the camera slightly lower also aligns better with the participant's natural eye line, improving facial visibility during screen-focused tasks. 2. Record the entire face To make sure participants' entire face is visible on the video (see also Loijens' tips 1 and 2), establish an optimal seating distance to the camera that allows you to record participants with different heights from top to chin. We use stickers on the floor to indicate the optimal position of the chair and ask participants to stay seated against the back of the chair throughout the study. You may also consider using adjustable chairs or a movable camera mount to adapt quickly to participants of different sizes. Clear instructions at the start of the session help participants understand the importance of staying within the camera's frame for data quality. 3. Avoid participants looking down You want to avoid that participants look down to check the computer keyboard as this may result in coding errors. Where possible, use response keys that are easy to use (e.g., colored stickers on keyboard keys where participants can keep their fingers on without looking down). In addition, it helps to do some practice trials to familiarize participants with the way they are supposed to respond. Reducing head movement also limits facial occlusion, which is critical when using automated analysis tools like FaceReader. If applicable, consider using button boxes or touchscreen responses to further minimize the need for keyboard use. 4. Make recordings comparable between participants and conditions To be able to compare expression between participants or conditions, it is often useful that videos are equally long for different participants. To this end, we program critical elements of the study to proceed automatically instead of allowing participants to self-pace. With the use of event markers, it is possible to identify the critical moments in the data or, if necessary, cut the videos from there. Consistency in video length and timing helps ensure that emotion coding algorithms analyze similar context windows. Additionally, synchronized timestamps between the video and stimulus presentation can simplify post-hoc analysis and improve data alignment. 5. Make the study engaging The lab is typically not a very natural or social environment (see also Loijens' tip 3). This may lower the chance that participants show intense expressions. A way to address this is to make studies as engaging as possible. Use, for instance, self-relevant stimulus material or, if possible, create a social interaction (e.g., with a webcam). Interactive elements, storytelling, or personalized feedback can boost emotional involvement and lead to more expressive reactions. The more the participant forgets they're in a lab, the more authentic their emotional responses will be—which greatly benefits facial expression analysis. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Accurate facial expression analysis starts with smart lab setup and participant preparation. By positioning the camera correctly, recording the full face, minimizing head movement, ensuring consistency across recordings, and keeping participants engaged, you can significantly improve the quality of your data. These practical tips help ensure that your analysis reflects authentic emotional responses. Want to read more about using FaceReader in the lab or in your research? Whether you're a student just getting started or a seasoned researcher, small adjustments in your setup can make a big difference in data quality. Want to learn more about using facial expression analysis tools like FaceReader in your research? Feel free to explore our other blog posts or get in touch with our team—we're happy to help you get the most out of your behavioral research. - How to master automatic Facial Expression Recognition - Using facial expression analysis during a musical experiment - Creating a custom expression for Engagement: A validation study with FaceReader - Facts about FaceReader and automated facial expression analysis This guest post was originally written by Marret K. Noordewier, PhD – Leiden University --- ## What makes Noldus special in measuring behavior? URL: https://noldus.com/blog/why-choose-noldus-measuring-behavior Published: 2024-03-20 14:00:00 Description: Why do we write e-books, white papers and even this blog? What drives us in behavioral research? And why choose Noldus? When it comes to behavioral research, having Noldus as your partner is a game-changer. But what exactly sets us apart? In short: It's not just our state-of-the-art tools; it's our deep-rooted expertise, commitment and passion to the field itself. When we create, advertise, and sell our products, we aim to make sure that our behavioral solutions make sense. Our passion for science Whether you’re exploring anxiety with the Elevated Plus Maze, or assessing learning and memory with the Morris Water Maze; it's our understanding of the subtleties in behavior that allows us to offer products such as EthoVision XT that truly meet the needs of behavioral researchers. Then, there's the CatWalk XT system, which showcases our approach to measuring free-walking gait in rodents. Unlike methods that might induce forced gait, potentially skewing the natural representation of gait in rodents, the Catwalk XT system allows for the observation of voluntary movement. This method captures a wealth of data on gait dynamics in a more natural and unrestrained environment, offering critical insights into motor function for neurological studies. This distinction highlights our commitment to providing sophisticated, yet user-friendly, solutions that empower researchers to gain a deeper understanding of behavior and its underlying mechanisms. What does the name ‘Noldus’ actually mean? Going back to the beginning, we can ask the question: What's in the name 'Noldus'? What does it mean? It’s actually just the last name of our founder; Lucas Noldus. Prof. Dr. Lucas Noldus holds a background in ethology and behavioral research, he completed his Ph.D. at Wageningen University in 1989, focusing on "Chemical Espionage by Parasitic Wasps." Interestingly, his Ph.D. fieldwork was conducted in the very location where the Noldus headquarters now stands, and where he developed Noldus’ first ever behavioral solution: The Observer XT (firstly dubbed as The BugWatcher), a behavioral coding program written in BASIC for the DOS operating system.  Within this work, and the solution he created, he had a sort of 'Eureka' moment, where he realised that a behavioral recording tool for insects could also work for all other animal species including humans by decoupling the data structure (distinction of subject, behavior, modifiers) and the technology (computer-aided recording, timing and analysis of events) from the species-specific model of behavior (the ethogram or the 'coding system'), in which then a universal tool was created and The Observer XT was born. He envisioned his passion, measuring behavior, could evolve with technological development. And thus also Noldus Information Technology was born. This unique connection between his academic work and the foundation of the company highlights Noldus's deep-rooted connection to integrating scientific research with practical applications. "I am fascinated by new technologies to measure brain, body, and behavior. Building high-quality research tools that allow our customers to advance science, thus contributing to sustainable development and quality of life, fills me with pride. And doing this with a global team of professionals is a daily source of joy!"  Prof. Dr. Lucas Noldus   |  Founder & CEO Noldus Information Technology  | Wageningen, the Netherlands More than behavioral research tools This brings us to what really makes Noldus stand out: we don't just provide tools, we offer solutions. Our products are born from real research needs, designed by people who've faced the same challenges our customers do, and our support doesn't end with the sale. We're here to guide, educate, and assist. For example, take a look at the time and effort we put in our services such as support, NoldusCare, and even an online learning environment with the Noldus Academy. That is why our commitment to advancing behavioral research extends beyond our products, because we believe in empowering the research community, including clients, non-clients, and even competitors. We also do this through an abundance of free resources like e-books, white papers, webinars, and blog posts. In these, we share our expertise and insights openly. Yearly conference hosted by Noldus: Measuring behavior Noldus also co-organizes the measuring behavior conference (since 1996!). Noldus has been the main sponsor of this conference since its inception, where it was even one of the founding members! This conference tries to create bridges between disciplines by bringing together people who may otherwise be unlikely to meet each other. At a Measuring Behavior meeting, you will find yourself among researchers from all fields of behavioral research. Want to attend? Register here! Here is a glimpse of some of those recourses! E-books - Basic Behavioral Neuroscience in Rodents: A comprehensive guide for researchers interested in rodent behavior, covering experimental design, methodologies, and best practices. - Basic Behavioral Neuroscience in Zebrafish: Tailored for researchers working with zebrafish, this e-book dives into the specifics of conducting behavioral neuroscience research with this model organism. - How to Build a Rodent Neurobehavioral Core: This e-book provides a step-by-step guide for setting up a neurobehavioral core facility focused on rodent research, offering insights into equipment selection, experimental design, and best practices for conducting and analyzing behavioral studies. Buyer's guides - How to set up the perfect video tracking setup: A detailed guide to help researchers select and implement the most suitable video tracking system for their research needs, focusing on camera selection, software capabilities, and setup optimization. - Buyer’s guide to the perfect audiovisual lab: The goal of this buyer’s guide is to assist in finding the right AV solution for your training or research project. White papers - Aquatic Eco-neurotoxicology: Co-authored with a renowned zebrafish researcher, this white paper explores the intersection of environmental science and neurobehavioral research, highlighting the impact of environmental factors on neurobehavioral health. - FaceReader methodology: A guide on how FaceReader technology works for analyzing emotions through facial expressions, useful for research in psychology, marketing, and UX design. - Water maze testing and Alzheimer's: Discusses the role of water maze tests in understanding Alzheimer's disease, focusing on cognitive function. - Autism research: Offers insights into the latest tools and methods for autism research in humans, aiming to improve diagnosis, understanding, and support. - Eye tracking & FaceReader: Explains combining eye tracking with FaceReader to study where people look and how they feel, ideal for studies in consumer behavior and psychological research. - Fear conditioning, a deeply rooted behavior: Covers the basics and applications of fear conditioning in research, from setup to analysis, highlighting its importance in studying learning, memory, and anxiety. But we also have a broad selection of intriguing webinars! These often focus on the latest in animal and human behavioral research technologies and methodologies, with speakers throughout the scientific field. With NoldusCare you have instant access to our full library of webinars in the NoldusAcademy. Below are a few examples of what you can expect.  Animal behavior webinars - Zebrafish research in the spotlight: Dive into the world of zebrafish research, exploring cutting-edge methodologies and the impact of this model organism on neuroscience and behavioral studies. - Automated rodent behavior recognition with EthoVision XT: Learn how EthoVision XT's advanced algorithms can automatically recognize and categorize rodent behaviors, streamlining research workflows. - The standardization paradox: better data with naturalistic behavioral tests: This webinar tackles the challenge of balancing standardization with the need for naturalistic behavioral tests in animal research, offering insights into achieving reliable, reproducible data. Human behavior webinars - Tools and methods for facial action coding: An in-depth look at the tools and methodologies for analyzing facial expressions, leveraging the latest in facial action coding systems. - How to integrate psychophysiological & behavioral data using both Noldus and BIOPAC tools: Discover how to combine psychophysiological measurements with behavioral data for a comprehensive analysis of human responses. - Innovative methodologies for consumer behavior research: Explore cutting-edge approaches to understanding consumer behavior, from eye tracking to emotion analysis, and how these insights can drive product development and marketing strategies. These webinars represent just a fraction of all the resources available! Take a look a our full webinar repertoire here. What topics would you like to see covered in our future e-books, webinars, or white papers? Whether it's a deep dive into a specific research methodology, innovative uses for our tools, or exploring new frontiers in behavioral neuroscience, your input is invaluable to us. Feel free to send us an e-mail at marcom@noldus.com Make the difference with Noldus To summarize, with Noldus, you're not just getting top-notch behavioral research tools; you're gaining a partner with a foundation in real scientific inquiry. When you partner with us, you're joining a community of scientists, with highly validated and robust research (and methods). There are so many other great companies out there, that also make great products. But remember that we at Noldus are specialists, and measuring behavior is not just a side-project, but lies at the very core of our company. Check what others have experienced in their research by partnering with Noldus: Customer succes stories. --- ## Understanding the micro-dynamics of couples’ interactions URL: https://noldus.com/blog/understanding-micro-dynamics-couples-interactions Published: 2024-03-12 11:05:00 Description: How do aspects of romantic relationships, such as communication and emotions, develop during real-time couples’ interactions? A study on this was conducted in the Department of Psychology at the University of Zurich. This blog post was written by Myrto Dolcetti, PhD student and assistant at the Gerontopsychology and Gerontology Unit & the Clinical Psychology Children/ Adolescents and Couples/ Families Unit, Department of Psychology, University of Zurich. Understanding the micro-dynamics of couples' interactions across the adult lifespan The way romantic partners communicate in their daily interactions, as well as experience and express emotions, is associated with the partners' and couples' well-being, both in daily life and in the long-term (e.g., Hoppmann et al., 2011; Weber, 2021). Investigating and understanding these communication and affective patterns is thus crucial for promoting couples' well-being over the adult lifespan. This includes examining their development during everyday couples' interactions as well as over a longer period of time. Romantic partners mutually and continuously influence each other. Changes in the behavior or emotions of one partner affect the behavior and emotions of the other partner. Which in turn can have an effect on how the first partner will act or feel (e.g., Butler, 2011). These dynamic processes are taking place within each couple and can vary depending on contextual factors (e.g., the type of interaction: conflict or support discussion) or temporal factors (e.g., Gable et al., 2012; Schoebi, 2008). For example, these within-couple dynamic processes can be observed over the course of days or weeks, but can also take place in a second-by-second basis. Observing couples' real-time interactions over time A longitudinal study with a duration of ten years (2011-2022) was conducted in the Department of Psychology of the University of Zurich. Aim of the study was, among others, to understand how several aspects of romantic relationships, such as communication and emotional expression, develop during real-time couples' interactions, but also over a period of ten years. Moreover, possible factors influencing this development were examined. In this project, three chairs have been involved: Clinical Psychology for Children/ Adolescents and Couples/ Families Unit, Gerontopsychology and Gerontology Unit as well as Psychology of Motivation, Volition and Emotion Unit. For this project, a collaboration was also built with the Methods for Intensive Data in Psychology Unit of the University of Konstanz. A group of 368 Swiss, heterosexual couples, belonging in three age cohorts, participated in the first year of the study. During the first five years and in the last year of the study, the participating couples, besides completing self-report questionnaires, also took part in a laboratory observation. This behavioral observation included three eight-minute interactions: one conflict and two support (dyadic coping) discussions on a topic that, for each partner separately, represented a stressor outside of their relationship. Thus, an investigation of couples' real-time interactions over years was enabled. Easy recording of each interaction with MediaRecorder - in the laboratory and at home For the tenth and final year of the study, a high-tech and user-friendly observation lab, the Dyadic Communication Analytics Lab (current: Dyadic Dynamics Analytics Lab) was set up with the assistance of Noldus Information Technology. By using MediaRecorder, installed in the control room of our lab, we managed to easily record each interaction with four cameras - located in our observation room - from four different angles simultaneously. Two of the cameras - installed on the wall besides each interacting partner - were recording frontal videos of each of the two romantic partners and two dome cameras, installed on the ceiling, collected frontal and rear behavioral data from each couple. In total, during the last year of the study, 119 couples participated in the laboratory observation. Moreover, thanks to the Noldus portable lab, we ran on-site observations in the homes of 16 couples, who would otherwise not be able to participate in the study, since they could not visit the laboratory due to several reasons. Patterns in verbal communication between romantic partners A growing body of literature has examined the verbal communication between romantic partners in order to understand the patterns that underlie the functional or dysfunctional couples' interactions. For example, the use of function words, such as pronouns, has been found to be associated with the relationship functioning (for a review, see Horn & Meier, 2022). This association was investigated, both in conflict as well as dyadic coping interactions, in a recent study using data from couples who participated in the first year of the above-described longitudinal project (Meier et al., 2021). In the dyadic coping interactions, each participant talked to their partner about a stressor outside of their relationship (e.g., stressful experience at work, difficulties with the family of origin). It could be shown that, in the context of dyadic coping, an asymmetric focus on the self-disclosing partner - manifested in the use of the pronouns "I" and "you" - was associated with higher relationship functioning. On the contrary, in the context of conflict interaction, "you-talk" (i.e., an asymmetric focus on the partner) was linked to dysfunctional communication patterns. Moreover, using more "we-talk" (i.e., focus on the couple) during conflict interactions was found to be associated with a higher relationship functioning. Also interesting to watch is the customer success story of The Social Behavior Lab at Western University in London, Ontario, where dr. Erin Heerey works on social interactions, mainly dyadic interactions. Coding verbal and nonverbal communication and dyadic coping behavior To further observe and understand the possible functional and dysfunctional communication and support patterns, the eight-minute video recorded conflicts and dyadic coping interactions of the couples were subsequently coded by trained assistants. The dyadic coping interactions were coded based on a well-established coding system (Bodenmann, 2008). In particular, trained assistants rated the verbal and nonverbal stress expression behavior of the self-disclosing partner (e.g., verbal problem-oriented stress expression, explicit stress expression) as well as the verbal and nonverbal dyadic coping behavior shown by the supporting partner (e.g., active listening, verbal emotion-oriented dyadic coping, negative dyadic coping). The communication behavior shown by the romantic partners during the conflict interaction was also coded by trained assistants, based on an adapted version of the Specific Affect Coding System (Bodenmann, 2011; Gottman, 1994). This coding system includes categories regarding verbal and nonverbal positive communication (e.g., interest, validation) as well as categories for verbal and nonverbal negative communication (e.g., criticism, contempt, stonewalling). Examining these communication and support patterns as well as their temporal dynamics is of great importance, since they seem to be associated with important relationship outcomes, such as relationship satisfaction (e.g., Kuhn et al., 2018; Leuchtmann et al., 2019). FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Easier, quicker, and more accurate coding with The Observer XT In the tenth wave of the study, The Observer XT (version 16) was used for coding the couples' conflict and dyadic coping behavior. It provided a user-friendly environment that made the coding of couples' behavior easier and quicker and at the same time less error-prone in comparison to the tools applied in the past. By using the setting of instantaneous sampling, the video recordings stopped automatically every ten seconds and the coders were requested to code each interval with the corresponding category. Moreover, the inter-rater reliability between the coders was easily calculated in The Observer XT. Also read: 7 tips to make coding behavioral data more fun Analyzing nonverbal emotional behavior with FaceReader Emotions represent another central aspect of couples' everyday interactions (e.g., Gottman, 1994). One component of emotions constitutes the emotional expression, which includes, among others, the individuals' facial emotional expressions (Meyer et al., 2001; Rothermund & Eder, 2011). The crucial role of facial expressions in revealing information about the occurrence and intensity of emotional states has been underlined in the emotion literature (e.g., Ekman & O'Sullivan, 1991). Therefore, a number of studies examining emotions in couples' interactions have focused not only on self-reports of emotional states but also on the facial emotional expressions of the romantic partners (e.g., Gottman et al., 1998; Yuan et al., 2010). In the majority of those studies, trained observers viewed videotaped couples' interactions and manually coded the emotional behavior of the partners over the course of these interactions, a procedure which can, however, be very time-intensive. The high quality characterizing the frontal video recordings of the romantic partners' faces, collected in the tenth wave of the above-described longitudinal study, allowed an automated analysis of the facial emotional expressions of each participant by FaceReader (version 9.0). Among the different output options that FaceReader provides, we were mainly interested in the continuous values of the discrete emotions' intensity during couples' interactions (ranging from 0 to 1, with 1 representing the maximum value). FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Examining emotional micro-dynamic processes The outputs of the intensity of each discrete emotion (e.g., happiness, sadness etc.) were extracted from FaceReader and subsequently imported into The Observer XT. This was used for preparing the observational data for the main statistical analyses. In this software, one can divide the video-recorded interactions in time intervals of the desired length. The software then provides automatically calculated statistics (e.g., mean value) for each specific emotion and for each single interval. These extracted data will thus enable us to examine also the emotional micro-dynamic processes taking place within couples' real-time interactions. Multimodal research brings better insights Thanks to the growing availability of multimodal, high-density data, it is nowadays possible to examine within-couple real-time and short-term dynamic processes (e.g., Butler, 2011; Hamaker, 2012). Advances in analytic tools (e.g., continuous and automated analysis of facial emotional expressions) and statistical methods have played a vital role in this. By bringing these micro-dynamics of communication and emotional exchange "into light", one can turn them from "invisible" to "visible" and accordingly inform several prevention and therapeutic programs for couples. References - Bodenmann, G. (2008). Kodiersystem zur Erfassung des dyadischen Copings (SEDC). Erweiterte und adaptierte Version [Coding System to Assess Dyadic Coping. Modified and adapted version]. Zurich, Switzerland: University of Zurich. - Bodenmann, G. (2011). Kodiersystem zur Erfassung der dyadischen Kommunikation bei Paaren. [Coding System to Assess the Dyadic Communication in Couples]. Zurich, Switzerland: University of Zurich. - Butler, E. A. (2011). Temporal interpersonal emotion systems: The "TIES" that form relationships. Personality and Social Psychology Review, 15(4), 367-393. https://doi.org/10.1177/1088868311411164 - Ekman, P., & O'Sullivan, M. (1991). Facial expression: Methods, means, and moues. In R. S. Feldman & B. Rimé (Eds.), Fundamentals of nonverbal behavior (pp. 163–199). Cambridge University Press; Editions de la Maison des Sciences de l'Homme. - Gable, S. L., Gosnell, C. L., & Prok T. (2012). Close Relationships. In M. R. Mehl & T. S. Conner (Eds.), Handbook of Research Methods for Studying Daily Life. The Guilford Press. - Gottman, J. M. (1994). What predicts divorce? Lawrence Erlbaum. - Gottman, J. M., Coan, J., Carrere, S., & Swanson, C. (1998). Predicting Marital Happiness and Stability from Newlywed Interactions. Journal of Marriage and Family, 60(1), 5–22. https://doi.org/10.2307/353438 - Hamaker, E. L. (2012). Why researchers should think "within-person": a paradigmatic rationale. In M. R. Mehl & T. S. Conner (Eds.), Handbook of Research Methods for Studying Daily Life. The Guilford Press. - Hoppmann, C. A., Gerstorf, D., Willis, S. L., & Schaie, K. W. (2011). Spousal interrelations in happiness in the Seattle Longitudinal Study: Considerable similarities in levels and change over time. Developmental Psychology, 47(1), 1-8. https://doi.org/10.1037/a0020788 - Horn, A. B., & Meier, T. (2022). Language in close relationships. In M. Dehghani & R. L. Boyd (Eds.), Handbook of language analysis in psychology (pp. 102–124). The Guilford Press. - Kuhn, R., Bradbury, T. N., Nussbeck, F. W., & Bodenmann, G. (2018). The power of listening: Lending an ear to the partner during dyadic coping conversations. Journal of Family Psychology, 32(6), 762–772. https://doi.org/10.1037/fam0000421 - Leuchtmann, L., Milek, A., Bernecker, K., Nussbeck, F. W., Backes, S., Martin, M., Zemp, M., Brandstätter, V., & Bodenmann, G. (2019). Temporal dynamics of couples' communication behaviors in conflict discussions: A longitudinal analysis. Journal of Social and Personal Relationships, 36(9), 2937–2960. https://doi.org/10.1177/0265407518806582 - Meier, T., Milek, A., Mehl, M. R., Nussbeck, F. W., Neysari, M., Bodenmann, G., Martin, M., Zemp, M., & Horn, A. B. (2021). I blame you, I hear you: Couples' pronoun use in conflict and dyadic coping. Journal of Social and Personal Relationships, 38(11), 3265-3287. https://doi.org/10.1177/02654075211029721 - Meyer, W. U., Reisenzein, R., & Schützwohl, A. (2001). Einführung in die Emotionspsychologie, Band II: Evolutionspsychologisce Emotionstheorien. Hans Huber. - Rothermund, K., & Eder, A. B. (2011). Allgemeine Psychologie: Motivation und Emotion. VS Verlag für Sozialwissenschaften. - Schoebi, D. (2008). The coregulation of daily affect in marital relationships. Journal of Family Psychology, 22(4), 595. https://doi.org/10.1037/0893-3200.22.3.595 - Weber, E. (2021). Longitudinal Co-development of Well-being and Emotional Experiences in Dyadic Partner Relationships in Old Age [Doctoral dissertation, University of Zurich]. ZORA - Yuan, J. W., McCarthy, M., Holley, S. R., & Levenson, R. W. (2010). Physiological down-regulation and positive emotion in marital interaction. Emotion, 10(4), 467. https://doi.org/10.1037/a0018699 Source header picture: https://www.freepik.com/free-photo/woman-shouting-megaphones-each-other_7540221.htm --- ## How does perception of brand authenticity affect ad performance? URL: https://noldus.com/blog/brand-authenticity-ads Published: 2024-03-04 11:50:00 Description: For brands seeking to resonate with customers, being seen as authentic is vital. Using custom expressions in FaceReader, we explore how perception of brand authenticity relates to ad performance. What is authenticity? When we talk about authenticity, we're diving into what makes something real. It's about being genuine and connecting with people on a deeper, more meaningful level. It means being true to oneself by doing what is promised, being open and transparent, and acting according to one’s values. This is true for people, but also for brands. Imagine a brand as a person—it needs to keep promises, show its true colors, and act on real values to truly connect. It's this essence of authenticity that can make a brand stand out in the crowded marketplace of ideas. For brands seeking to resonate with consumers, being seen as authentic is vital for creating trust and loyalty. Why brand authenticity matters In the United States, television advertising spending is estimated to be between $60-65 billion per year. Single events, like the Super Bowl, cost $7 million for a 30-second spot. That's why it's imperative that commercial spots yield results for a brand’s targeted segment. But what happens when a brand is judged as inauthentic? And are brands viewed more favorably by those who see them as authentic?  For this blog post's study, we partnered with marketing research company Breakthrough Research to test how people reacted to different commercials. Our respondents were people who rated the brands as either high or low in authenticity.  How to measure perceived authenticity Breakthrough Research created a new proprietary Authenticity measure to assess the genuineness of brands. Their Authenticity measure leverages embodied cognition to have respondents pull statements they find to be "true to the brand" closer together or drag statements they find to be "contradictory to the brand" further apart.  We combined the scores and transformed the distances between statements to a brand authenticity score. Next, we created authenticity scores based on a 5-point scale, where the top two points were High Authenticity scores and the bottom three points were Low Authenticity scores. Measuring facial expressions during the ads In addition, we used facial expression analysis to measure respondents’ reactions while watching the ads. The software we used, FaceReader 9.1, is built on a Deep Face Model and captures expressions in a reliable, quantitative way. It measures facial expressions and twenty different facial muscles known as Action Units (AUs). These AUs can be combined to create custom expressions, such as confusion, laughing, and smiling. One hundred and thirty-two respondents watched one of two ads for either Progressive Insurance or Amazon. Progressive features a group of parody ads whereby a doctor, Dr. Rick, teaches new homeowners who are “becoming their parents”, that is, becoming technologically or socially inept. The Amazon ad features a heartfelt story about a man changing careers.  Respondents watched the ads at their own leisure, for example, at home. Their facial expressions were recorded via webcam and FaceReader Online.  FREE WHITE PAPER: FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download arrow_forward Psychographic segmentation with FaceReader Sixty respondents viewed the Progressive ad “Social Listening” whereas seventy-two respondents viewed the Amazon ad “Gourmet Guard”. There were similar levels of attention and interest between groups. Moreover, all respondents showed similar levels of attention and interest throughout the ads. We determined these using custom expressions in FaceReader 9.1. We also used FaceReader to segment respondents based on brand authenticity score. For both ads, we created a High Authenticity and a Low Authenticity group. We hypothesized that respondents who rated a brand as highly authentic would view ads more favorably than those who rated the brand with a low authenticity score. Expressions were more positive with higher perceived authenticity Indeed, with the Progressive ads, the High Authenticity group laughed more frequently and with higher intensity than did the Low Authenticity group. Laughing moments occurred when Dr. Rick taught the group and not when he spoke directly to the camera. The Low Authenticity group did laugh at some of the same moments, but only a few and with minimal intensity. Curiously, this group displayed higher amounts of confusion, so it is possible that this group didn’t understand the in-jokes, that it was a parody, or possibly the point of the ad.   Amazon’s ad did not feature parody or in-jokes. Therefore, it did not have periods of laughter. Instead, this ad focuses on the transformation of a security guard as he upgrades his lunch, then his skills, ultimately leading him to apply for a job as a chef. Accordingly, the High Authenticity group smiled progressively as the man transitioned from guard to chef. The Low Authenticity group, however, showed minimal periods of smiles, but increased amounts of confusion from start to finish. You may also like this blog series about consumer experience while self-designing a product: - Just the way I want it: a study on consumer experience in self-designing - Design your own product: consumer experience and abandonment behavior - From start to finish: decreasing abandonment when self-designing a product Facial expressions and psychographic segmentation generate greater insights There are two important findings from this study. First, the perception of a brand’s authenticity affects how individuals react to that brand’s advertising. Brands high in authenticity tend to produce more positive emotions (such as laughs and smiles), whereas brands low in authenticity tend to elicit a flatter affect and more confusion. Second, this study demonstrates how custom expressions in FaceReader can generate insights beyond the basic expressions - including attention, interest, laughing, and confusion.  Furthermore, when you gather facial expression data in a respondent’s preferred environment, paired with psychographic segmentation, you understand your respondents much better compared to surveys or expression analysis alone. Taken together, these data demonstrate the capacity and flexibility of custom expressions in FaceReader, especially when combined with ad testing using FaceReader Online. References - https://www.statista.com/statistics/217134/total-advertisement-revenue-of-super-bowls/ - https://www.visualcapitalist.com/top-tv-advertising-spenders - https://bthrough.com/ - Conference: Trend Lens: How To Build (And Measure) An Authentic Brand, TMRE2023, Denver, CO - https://www.progressive.com/commercials-campaigns/dr-rick/ - https://www.aboutamazon.com/news/retail/amazon-prime-commercial-security-guard-chef --- ## CatWalk XT gait analysis vs treadmills URL: https://noldus.com/blog/catwalk-xt-gait-analysis-versus-treadmills Published: 2024-02-29 09:00:00 Description: In this blog post, we will discuss how the CatWalk XT method and treadmill method for gait analysis differ from each other, and what you should consider about both methods when performing gait analysis. Traditionally, there are two fundamentally different ways to perform gait analysis in animals. One can either observe or measure gait in a forced manner, as seen when using a treadmill or treadwheel, or in an unrestricted manner, such as with CatWalk XT. In this blog post we will discuss the pros and cons of different gait assessing methods, and compare them to the CatWalk XT gait analysis method. Unforced vs forced gait analysis The unforced way of assessing gait ability is what we see in many daily practices of physicians- watching closely as the patient moves towards them in a straight line. In lab animals, this is translated into traditional methods such as BBB scoring and paw inking. The main advantage of unforced gait analysis is that the animal is allowed to move at a speed that its gait (ab)normality or endurance will allow while it preserves all vestibular and visual inputs. Variety between treatment groups When analyzing gait differences, there is often variety within and between treatment groups, such as speed or weight. Since speed of movement influences a lot of gait parameters, researchers find it important to adjust for speed even though it is the most obvious gait phenotype. Adjusting for speed The most obvious method of regulating speed is using a motorized treadmill or treadwheel system, which largely eliminates variations in speed within treatment groups, but not completely. The only thing you can be sure of is that the animals all walk with the same average speed; the speed to which the treadmill system is set. However, they typically reach this average speed by constantly varying their speed moving up and down the treadmill while frantically searching for a way out. This causes high stress levels in the subjects under investigation, together with different endurance levels or types of injury this will produce different strategies to ‘stay up to speed’, which will eventually result in huge variations in walking speed, jumping, and limping behavior, etc. LABEL Title Learn more RESOURCES: Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent publications using CatWalk XT  Resources LABEL Title Learn more The stress to keep up in forced gait analysis Generally speaking, a treadmill does not frighten a human patient, because they can be told what is going on, and they can stop the treadmill if necessary. Animals, however, cannot comprehend what is going on, potentially leading to increased stress levels. This stress can have a significant influence on the readout of the gait parameters.  The rodents natural instinct is to do whatever it takes to keep up with the treadmill, possibly introducing gait artifacts but also behaviors related to the desire to escape the situation. While this set speed potentially reveals deviations in gait, it might also mask those subtle changes in gait that are the focus of your research. The CatWalk XT gait analysis system CatWalk XT successfully gives you the best of both worlds by combining a walkway system with an advanced software program. CatWalk XT allows animals to walk at their own intrinsic speed in an unforced manner, guided in a straight line due to the restriction introduced by the walls of the corridor. Unlike a treadmill system that requires a very bright environment to operate, the low light environment of CatWalk XT ensures a low stress environment for photophobic rodents. Afterward, the software allows you to adjust for speed and speed variations. This way you can detect artifacts in gait in a non-artificial manner, all while introducing the least amount of stress on the animal, and decreasing bias in your experiment. All in all, this ensures that the subject behaves as naturalistic as possible. Results derived from this more naturalistic environment result in a better representation for translational research.  Motivating the animal Of course, the freely moving method is subject to the willingness to undergo the analysis, like so many other behavioral tests. First, animals might not want to walk. Although habituation through training helps, motivation often works even better. That is why CatWalk XT uses a goal box at the end of the runway. This way, animals are motivated by the prospect of their home cage or some other reward. The CatWalk XT goal box makes it easier to train your animals to get straight runs along the 70 cm glass plate. This results in faster data collecting and an overall smooth experiment. Do you want to know more about the CatWalk XT? Our product manager Reinko Roelofs is happy to tell you all about  in the product video below! LABEL Title Learn more Capturing footprints in detail The biggest advantage of CatWalk XT is the way in which it measures the footfalls. CatWalk XT uses a technology called Illuminated Footprints. The animal traverses the glass walkway that houses a high speed camera mounted underneath it. Light is captured inside this glass walkway, escaping and reflecting only when a footprint touches the glass. This results in a very precise detection of the actual placement of the feet. Belt driven systems are far less accurate, often detecting part of the feet that are not actually touching the walkway or guessing the moment of first contact. This means that more manual labor is needed to correct mistakes, which costs resources and increases bias risks. Curious on what an experiment with the CatWalk XT looks like? Watch the video below to see the CatWalk XT in action!  LABEL Title Learn more CatWalk XT gait analysis choosing the right parameters Gait analysis, treadmill or not, is not always straightforward. Systems like CatWalk XT can produce over 50 different parameters to draw conclusions from. It can be difficult to determine which of those parameters you should choose for your specific model. A recent study published by Ivanna Timotius and, among other, CatWalk XT product manager Reinko Roelofs, explores which gait parameters are influenced in certain disease models. You can find a more in depth look into this meta-analysis in this blog. The advantages of CatWalk XT according to users - Due to the runway set-up, the CatWalk XT system resembles the normal gait of animals; - Both static and dynamic gait parameters can be evaluated in one analysis with the CatWalk XT system - The registration of the CatWalk XT system is very accurate when animals are trained well. This provides clinically relevant and extensive data on gait behavior. Your challenge As you can see, the need for a forced gait analysis system is no more. Because all in all, the CatWalk XT is a complete and easy to use gait analysis system for quantitive assessment of footfalls and locomotion in small animals. If you are interested in CatWalk XT make sure to get into contact with one of our colleagues, together we can make the right solution for your research. REQUEST INFORMATION Are you interested in CatWalk XT, and want to get in contact? Learn more --- ## How to easily apply multimodal measurement during research with children URL: https://noldus.com/blog/integrating-multiple-data-streams Published: 2024-02-26 08:56:00 Description: A child development researcher can encounter quite a few challenges when wanting to measure multiple data streams. How do you make that run as smoothly as possible plus integrate all data seamlessly? Researchers today are not only using observations to study behavior, but they are complementing their toolbox with a wide range of other measurement tools. §For example, tools to measure pupil reactions, blood pulse, blood volume, skin conductance, heart rate, and brain activity will greatly increase the insights you gain during research when you combine this with video-based observation. Assessing social skills or emotional empathy in children For example, when social skills are the topics of your research and you want to study how infants and parents respond to emotions of others, their pupil sizes will tell you something about the physiological arousal while they observe other people. Eye-tracking data can be used to measure the pupil reactions [1]. Or, to provide insights into infants’ responses to sociomoral scenes, especially infants who do not use spoken words yet, neuroimaging techniques such as electroencephalography (EEG) better explain the nature of the mental processes. §Several studies used this technique to find out if there were differences in antisocial versus prosocial interactions by investigating the frontal alpha power while the infants viewed helping and hindering scenarios [2,3]. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Gathering multiple data streams Another example is measuring autonomic nervous system activity using data acquisition software. The research team of Palser used ECG, GSR, and respiratory measurement tools to investigate resting parasympathetic nervous system activity in children with dyslexia — a reading disorder — and its relationship to autonomic and behavioral responding to others’ emotions [4]. These components were measured: 1. Physiological data - Cardiac activity | inter-beat interval (IBI) - Respiration | respiratory cycle time and respiratory sinus arrhythmia (RSA) - Electrodermal activity (EDA) | skin conductance level (SCL) 2. Emotional facial behavior - Emotional reactivity - Empathy - Emotion regulation In such an experiment, a participant must be connected to a lot of equipment before the test can start. NoldusHub will solve these challenges. It enables you to control, calibrate, and monitor all devices from one place.  Also read: The power of multimodal research in human behavior studies to discover why multimodal research is gaining popularity. Tips and tricks when working with children As a researcher who works with children, you probably face quite a few challenges. A child can get fussy during or following testing. Or the child may suddenly pull the EEG cap off the head, refuse to sit still, or become distracted. How do you handle this kind of situations, or better, how can you prevent them from happening? I asked my colleague Patrick Zimmerman for advice, since he is an experienced trainer and human behavior consultant. What to do before the actual experiment starts? Before you can start a test, it is important that you carry out some test runs to make sure all equipment is working properly. On the day of the test, allow yourself sufficient time to do a final check of the equipment and make sure everything is ready to go when the first participant arrives. Check if all cables are plugged in properly and if the software is standby. When a participant arrives at your lab, take the time to welcome and to make the child feel comfortable. Of course, before a test, each participant should be fully informed about the measurements and must give consent for participating in the test and having their behavior recorded. In case of young children, the parents must give consent. How to make it run as smoothly as possible Making participants feel comfortable and explain to them what will happen before, during, and after a test, is even more important when working with children. It helps if the experimental room is (temporarily) designed with bright colors or objects that makes it feel more like a playroom than a lab. Sometimes it is useful to have one of the parents present to make the child feel more at ease. The downside could be that the parent gets involved in the test even if he or she is not supposed to. Therefore, it is important to instruct the parent clearly what to do and what not to do during a test as well. How to deal with invasive measurement tools Of course, it can happen that young participants are not comfortable with some of the more invasive measurements, for example, electrodes on their body or a cap for measurement of brain activity. §In this case, it is important that you explain to them, in simple language, what the equipment entails and what they can expect to happen. Let them know they cannot do anything wrong, and that it’s okay if any wires are pulled loose. Also, inform them that they won't feel any pain or other discomfort. Let them know if they might hear noises. Reassure them about all this and tell them to warn you if they feel uncomfortable. Obviously, it helps if one of the parents is there to make it easier for them. When you work with children, it is likely that some measurements fail due to the child’s behavior. Be prepared for this and recruit some more children than you actually need for answering your research questions. Pay attention to the time spend A test for children should be designed in such a way that it takes into account the attention span of children. Thus, no long boring tests, but regular breaks to bring back attention to the test. Tip: give them a reward during this short break and/or play a quick game, such as throwing/rolling a ball to each other. Take a moment to do something completely different before returning the full attention to the test itself. Of course, it should be noted in the acquired data when breaks take place to have the most accurate possible data during data selection and analysis. To be able to perform this analysis properly, it is important that all data streams are synchronized. How do you handle that? How to make data synchronization easier Making sure participants feel at ease is one thing, but equally important is data synchronization. The whole point of carrying out multimodal measurements, e.g. combining behavioral, video, facial expression, eye tracking, and physiological data, is that you want to look at the relationship between different types of data. For this it is vital that different data streams are recorded synchronously or can be easily (preferably automatically) synchronized after data acquisition. §NoldusHub represents our latest multimodal platform for human behavior studies, designed to combine multiple types of measurements and ensuring the attainment of reliable, high-quality data and direct insights. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more The synchronized data set yields more insights into the response of your participants. Moreover, if something is going wrong within one of the data streams, you will receive a notification during the session. No surprises afterwards, but an immediate warning if an issue arises. This helps you to keep control of your data streams and ensures successful measurements. References [1] Aktar, E.; Nimphy, C.A.; Kret, M.E.; Pérez-Edgar, K.; Bögels, S.M. & Raijmakers, M.E.J. (2021). Pupil responses to dynamic negative facial expressions of emotion in infants and parents. Developmental Psychobiology, 63 (7), https://doi.org/10.1002/dev.22190 [2] Cowell, J. M. & Decety, J. (2015). Precursors to morality in development as a complex interplay between neural, socioenvironmental, and behavioral facets. Proceedings of the National Academy of Sciences, 112 (41), 12657-12662. https://doi.org/10.1073/pnas.1508832112 [3] Tan, E. & Hamlin, K. (2021). Infants’ Neural Responses to Helping and Hindering Scenarios. https://doi.org/10.31219/osf.io/nuxwv [4] Palser, E.R.; Morris, N.A.; Roy, A.R.K.; Holley, S.R.; Veziris, C.R.; Watson, C.; Deleon, J.; Miller, Z.A.;  Miller, B.L.; Gorno-Tempini, M.L. & Sturm, V.E. (2021). Children with developmental dyslexia show elevated parasympathetic nervous system activity at rest and greater cardiac deceleration during an empathy task. Biological Psychology, 166. https://doi.org/10.1016/j.biopsycho.2021.108203. --- ## 5 reasons that prove why a high-quality camera is essential for video tracking URL: https://noldus.com/blog/5-reasons-why-you-should-use-high-quality-cameras-for-video-tracking Published: 2024-02-21 13:00:00 Description: In animal behavioral research, especially when we're looking at rodents and zebrafish, getting your behavioral analysis right is crucial. Top-notch camera technology therein is a must have. In animal behavioral research, especially when we're looking at rodents and zebrafish, getting your behavioral analysis right is crucial. We need to be precise and reliable. And a big part of that comes down to using high-quality cameras for video tracking. In this blog, we're going to explore why top-notch camera technology isn't just a nice-to-have—it's a must-have for researchers who want to collect data that's not only accurate and detailed but truly insightful. Camera just as important as tracking software When it comes to cameras, think Orwell's Animal Farm: They're all equal, but some are more equal than others, meaning that all will provide images for tracking, but there is a trade-off between price and quality. - You could easily use a Microsoft Lifecam for tracking if you don't mind losing image frames or sacrificing image-to-image timing. This might not be a problem for tracking rats in the water maze but won't suffice examining twitching or other stereotypy behaviors. - GigE cameras have great resolution, are capable of higher frame rates (i.e., above 30 fps), and don't place a heavy load on the CPU; however, they can be more expensive than other options. - Our Buyer's Guide to the Perfect Video Tracking Setup provides a full list of pros and cons, but here is a brief overview BUYER'S GUIDE: The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Download 5 reasons that prove why a high-quality camera is essential for video tracking We would argue that the quality of the camera is as important as the software used to track the animal and the task required of the animal! Inferior equipment creates bad data. Bad data doesn't (or shouldn't) get published in high-impact journals. Here are five reasons why a high-quality camera is essential for good video tracking. 1. Enhanced image clarity and resolution High-quality cameras give clearer and sharper images. This clarity is essential when we're trying to track the small and subtle movements of rodents and zebrafish. These tiny behaviors can tell us a lot about their neurological health or how they're responding to treatments. With lower-quality video, we might miss these important cues or not see them clearly enough. Being able to catch these fine details, like a small twitch or a slight shift in how they're standing, helps researchers dig deeper into their studies, giving us a fuller picture of what's going on. USB2.0 was launched at the turn of the century and typically streams at 640x480 pixels. It is not capable of providing enough bandwidth for 1080p at 30 frames per second. USB3.0 on the other hand, provides ten times the bandwidth of USB2.0. Another consideration is the lens itself. USB cameras have a fixed lens, which means you're stuck with a specific focal length. GigE cameras, on the other hand, allow for a variety of lenses depending on your exact needs. 2. Improved low-light performance Behavioral studies often require low-light conditions. This could be to mimic their natural habitats more closely or to study their sleep-wake cycles. High-quality cameras are vital for capturing clear, detailed footage even in dim settings. We aim to keep the environment as undisturbed as possible, avoiding any artificial lighting that could affect the behavior we're trying to observe. This capability is crucial for accurately recording how rodents or zebrafish act in these low-light scenarios, ensuring our data is as true to life as possible. If you prioritize low-light performance, a GigE camera has inherent infrared sensitivity. Whether you have nocturnal experiments or dimly lit environments, GigE cameras deliver. 3. Higher frame rates for capturing fast movements Rodents and zebrafish are speedy movers, which means we need cameras that can keep up with their fast-paced actions without blurring the details. As already noted, UBS2.0 cameras cannot record 30 fps at 1080. High-quality cameras, such as GigE or USB3.0, with their ability to record at frame rates of 60 fps or higher, are perfect for this job. They help us catch every bit of the action clearly. This clarity becomes super important in studies that look at how these animals move or react to different things. To really understand the nuances of their movement—how fast they go, the paths they take—we need every frame to be as clear as possible. So how many frames is enough? Surely the more the merrier, right?! Not so much. In our experience, unless you are recording stereoscopic images or gait in CatWalk, recording higher than 100 fps is not necessary. The optimal rate is 25-30 fps, or up to 60 fps depending on the application. 4. Robust data for quantitative analysis In the end, our aim in behavioral research is to get data that we can measure, analyze, and trust, making it possible to give us insights that really matter and are accurate. Even though EthoVision XT software is amazing at handling video of various qualities, to really get the best out of your research, high-quality cameras are key. Think of it like this: EthoVision XT is like a super smart detective that can work with any clues you give it. But when you give it clearer, sharper clues (thanks to better cameras), it can solve the mystery faster and more accurately. This means we can catch every tiny detail in our studies, making sure we don't miss anything important. In short: pairing EthoVision XT with a high-quality video takes your research to the next level. It's about making sure we're not just getting by, but really nailing those discoveries with the best data we can get. 5. Long-term reliability and consistency Opting for high-quality camera equipment is a strategic investment in the reliability and consistency of research outcomes. Cameras that maintain consistent performance over time significantly reduce variability in data collection, an essential aspect of longitudinal studies or experiments requiring replication. This consistency underpins the validity and reliability of research findings, thereby enhancing the credibility of the study. In essence, selecting superior camera technology is not just about capturing clearer images; it's about ensuring the integrity and reproducibility of scientific research. Not convinced? Need some more information on camera types? Make sure to take a look at the overview provided below, courtesy of Basler. Here they explain what the advantages and/or tradeoffs are of specific camera connection types. In the current market and with current technology, the discussion really centers around 3 connection types: USB 2.0, USB 3.0 and GigE. - USB 2.0 cameras are generally very affordable, however have a lower data transfer rate compared to USB 3.0 and GigE. - USB 3.0 provides higher throughput, allowing for faster data transfer, and in turn higher quality, while requiring a low CPU load due to a different protocol than USB 2.0 and GigE. However it lacks capabilities when wanting to use a larger multi-camera setup - GigE cameras offer high throughput, especially with Gigabit Ethernet, you can achieve longer cable lengths (up to 100 meters) due to Ethernet technology, they support Power over Ethernet (PoE), and offer good synchronization capabilities. They do require a bit more tech-savvy setup compared to USB 3.0 cameras (which are more "plug-and-play") Image courtesy of Basler It's a wrap! High-quality cameras are a necessity, not just a fancy upgrade Bringing high-quality cameras into our rodent and zebrafish studies is a necessity, not just a fancy upgrade. It's all about getting the clear, reliable data we need for cutting-edge research. These cameras help us see the tiny details that matter, making our work better and more efficient, and let's be honest: in the end we're looking for conclusions that are both reliable and meaningful. Top-notch video tracking is an investment in making sure our research can lead to real breakthroughs. Any questions about what camera you need for your research setup? Do not hesitate to contact us! We have an extensive (international) team of behavioral experts. --- ## Using Baby FaceReader for automated analysis of infant emotions URL: https://noldus.com/blog/baby-facereader-automated-facial-expression-analysis Published: 2024-02-21 10:50:00 Description: What if you had a way to understand a baby's unspoken needs? Analyzing facial expressions in infants helps researchers and caregivers understand more about the early development of emotions and social interactions. Facial expression analysis is vital in understanding human emotions and social interactions. It can be even more valuable when studying infants, as they have not yet developed verbal communication skills. Babies have to rely on nonverbal cues to convey their feelings. What if you had a way to understand their unspoken emotions and needs? Analyzing facial expressions in infants helps researchers and caregivers understand more about the early development of emotions and social interactions. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Why automated facial expression analysis is better Traditionally, experts relied on manual observation to study emotions. The downsides of this way of working are that it can yield inconsistent results and is highly time-consuming. The development of automated facial expression analysis has promised a significant leap in measuring emotions. That's because using dedicated software for facial expression analysis, like Baby FaceReader, not only speeds up the process but also provides a much higher level of consistency and objectivity. Moreover, it makes it easier to obtain large datasets and to replicate earlier studies. Martina Zaharieva explains more about the validation of Baby FaceReader in this Noldus webinar: Validating Baby FaceReader 9 Analysis of Infant Affective Facial Expressions in Face-to-Face Interactions. Watch the webinar on demand now! Technical innovation: Baby FaceReader Baby FaceReader represents a significant milestone in automated facial expression analysis. Developed with advanced algorithms and machine learning techniques, it uses a convolutional neural network (CNN) to identify and interpret various facial action units (AUs). The software is specialized in infant facial expressions and is based on Oster's Baby Facial Action Coding System (Baby FACS). Baby FaceReader uses AUs to calculate overall emotional valence. This way, the software can detect subtle changes in facial expressions, providing nuanced insights into an infant's emotional state. Unlike manual coding, which can be prone to subjective interpretation, Baby FaceReader offers a standardized approach to understanding facial expressions. To use this software in research more confidently, it is vital to explore its reliability and validity in more detail. Baby FaceReader is a state of the art system to automatically detect infant facial expressions in order to help address questions in developmental psychology. Comparing Baby FaceReader with manual coding That's why researcher Zaharieva and her team evaluated how well Baby FaceReader measured emotions compared to manual coding. In their study, they observed 58 infants aged 4 and 8 months during face-to-face naturalistic interactions with different caregivers. During these early stages of life, facial expressiveness evolves rapidly, making it an ideal time to study emotional communication. The researchers paid close attention to the software's ability to differentiate between positive, negative, and neutral expressions, understanding that accurately interpreting these nuances is crucial in developmental psychology. For their manual coding, they used The Observer XT. Better results with positive emotions The results of the study provided mixed insights. When compared to manually coded facial expressions, Baby FaceReader demonstrated reasonable accuracy in distinguishing positive expressions from negative or neutral ones. However, its performance in differentiating between negative and neutral expressions was more challenging. Therefore, the researchers studied the performance of specific action units in discriminating between positive, negative, and neutral expressions. They found that automated detection of smiling (AU12) performed well in discriminating positive expressions from negative or neutral ones. And by analyzing brow lowering (AU3 + AU4) in the software, the team was able to reliably distinguish negative facial expressions from neutral ones. You may also like these blog posts on infant behavior research: - How to study developmental psychology: methods, designs & tools - The importance of a multi-method approach in infant behavior research - How does communication with strangers develop? Advancing infant research with Baby FaceReader The introduction of automated facial expression analysis in developmental psychology and pediatric care is a significant step forward. This technology offers new insights into the development of infant emotional expression, leading to better-informed caregiving and treatments of developmental disorders. As the technology continues to evolve, it will help us to understand the earliest stages of human emotion and communication even better. References - Oster, H. (2006). Baby FACS: Facial action coding system for infants and young children. Unpublished monograph and coding manual. - Zaharieva, M.; Salvadori, E.; Messinger, D.; Visser, I.; Colonnesi, C. (2024). Automated facial expression measurement in a longitudinal sample of 4‑ and 8‑month‑olds: Baby FaceReader 9 and manual coding of affective expressions. Behavior Research Methods, doi https://doi.org/10.3758/s13428-023-02301-3 --- ## What is biometric research? URL: https://noldus.com/blog/what-biometric-research Published: 2024-02-18 09:00:00 Description: Biometric research helps scientists uncover subconscious processes related to attention, cognition, emotion, and physiological arousal. Biometric research helps scientists uncover subconscious processes related to attention, cognition, emotion, and physiological arousal. While explicit behavior is often studied through interviews and surveys, implicit responses tell a deeper story: one that cannot always be captured through self-reporting. What is biometric research? Biometric research involves measuring physiological and behavioral signals to understand how people think, feel, and respond. It provides real-time data on subconscious reactions, helping researchers analyze emotions, cognitive workload, and physiological arousal. These tools are now widely used in fields that study human behavior, including: psychology, educational research, UX research, and neuromarketing. Each biometric sensor provides different insight into human behavior: combining multiple sensors, researchers can gain a better understanding (and prediction!) of human behavior. Different sensors to measure behavior By using biometric sensors, researchers can measure physiological and behavioral signals, providing objective insights into how people react to different stimuli. Whether in psychology, consumer research, or neuromarketing, biometric research plays a crucial role in understanding human behavior. Biometric research relies on specialized sensors to record various physiological signals, from facial expressions and eye movements to heart rate and brain activity. For example, when watching an advertisement or video: - Your eyes follow the most engaging elements. - Your facial expression changes based on your emotional reaction. - Your hands may become sweaty, reflecting physiological arousal. Each of these signals tells a true, unbiased story about how you're feeling in response to a stimulus. This makes biometric research a powerful tool in fields like psychology, consumer research, and neuromarketing. FREE WHITE PAPER Data integration & visualization: mix and match Download this white paper to learn: - What kinds of data can be synchronized and integrated - How to synchronize data - How to visualize and analyze synchronized data Submit to download Why biometric research matters: quantify your results Traditional methods like interviews and surveys rely on self-reported data, which can be influenced by social desirability bias or inaccurate recall. People may not always express their true thoughts or emotions, either consciously or unconsciously. Biometric research goes beyond self-reporting, capturing real-time physiological responses that provide objective and reliable insights. By combining biometric tools with traditional research methods, scientists and businesses can gain a better understanding of human behavior. Interviews and surveys study behavior and motives but not the implicit or "first moment of truth". For example, think about socially desirable answers. Research shows that respondents are unable or unwilling to speak their mind and instead say what they think is more socially acceptable. Key biometric research tools Combine tools for biometric research with traditional methods and techniques - like interviews or questionnaires - in order to create a broader picture. Eye tracking and facial expression analysis Eye tracking shows where participants focus their attention, while facial expression analysis detects emotions. Combine the two to find out where the participant looked when frustrated, or, for example, what element in the video surprised the participant the most. Perfect synchronicity is key to matching the measurement of attention or cognitive workload to emotions. This is especially useful in advertising and UX research. Galvanic skin response (GSR) When we experience something physiologically arousing (for example a roller coaster ride), you can feel your fingers tingle. GSR devices can detect this change in physiological arousal. Galvanic skin response measures changes in sweat gland activity, revealing the intensity of emotional arousal but not what the feeling actually is. Researchers often combine GSR with facial expression analysis or pre/post-experiment interviews for a more complete understanding. EEG (Electroencephalography) EEG measures brain activity, offering insights into cognitive engagement, workload, and motivation. It helps researchers understand whether someone is actively processing information, feeling focused, or disengaged. EEG is widely used in neuroscience, UX testing, and media research, but requires expert interpretation. ECG (Electrocardiography) Changes in your heart rate provide information about how you are experiencing your environment. If you feel anxious or excited, your heart rate will increase, and if you feel drowsy, your heart rate will decrease. Monitoring fluctuations between physiological excitement and behavior will help you gain insight into what is physiologically arousing and what is calming. For instance: - Increased heart rate can indicate stress, excitement, or anxiety. - Decreased heart rate may reflect relaxation or drowsiness. The power of data integration The true power of biometric research lies in combining multiple data sources. By integrating biometric signals with video recordings, interviews, and self-report surveys, researchers can build a more comprehensive picture of human behavior. For example, in neuromarketing, combining eye tracking, facial expressions, and GSR can reveal: - What caught the viewer's attention? - How did they emotionally react? - Was the reaction positive, negative, or neutral? This multimodal approach makes biometric research an invaluable tool for understanding human responses and to measure what people cannot always express in words. By tracking physiological signals like eye movement, facial expressions, brain activity, and heart rate, researchers gain a deeper, more objective understanding of how humans think, feel, and react. When combined with traditional research methods, biometric data unlocks deeper insights, making it a crucial part of modern human behavior research. Examples of biometric research Prof. Julien Mercier from L'Université du Québec à Montréal (UQAM) is studying educational research. His lab is looking at refined brain information over time, involving the cognition and the affect of the learner. Jean-Marc Diverrez, from bcom Institute of Research and Technology, France talks about measuring emotions. He hopes that the projects will go out of the lab and into the real world. He looks into all kinds of new technologies and sensors to better measure and thus understand emotions. The Social Media Lab at the University of Louvain uses Noldus' software to integrate different data streams and set up experiments. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more --- ## The science behind your emotions URL: https://noldus.com/blog/science-of-emotions Published: 2024-02-13 12:00:00 Description: Have you ever wondered where your emotions come from? Let’s dive into the science behind our emotions and discover how our brain and body work together to make us feel. Have you ever wondered where your emotions come from? Of cried out that your emotions were all over the place? Why do you feel happy when you see a loved one, but sad when you hear about a tragedy? Would you be surprised to learn that there is a lot of science behind our emotions? Read on and discover how our brain and body work together to make us feel. The brain's role in our emotions Believe it or not, your emotions are believed to come from the brain. Yes, you read that right, the brain! The limbic system to be more precise, a complex network of structures deep within our cerebral cortex. This is the part of the brain responsible for our emotions, motivation, and behavior. It's the control center of our body and is responsible for processing and interpreting different emotional stimuli. The limbic system, a group of structures within the brain, is primarily responsible for our emotions, motivation, and behavior. Meet the limbic system: your emotional HQ So how does the limbic system actually work? Well, it's a complex network of structures, including the amygdala, hippocampus, and hypothalamus. These structures work together to regulate our emotional responses to different situations. One of the key structures within the limbic system is the amygdala, which is responsible for processing emotions like fear, anxiety, anger and aggression. When we encounter a potentially threatening situation, the amygdala sends a signal to our hypothalamus, which triggers our fight or flight response. The Incredible Hulk of Emotions: how your brain responds when you see a spider How would that work? Picture this: you're sitting at your couch, having a casual dinner in front of the television, and out of the corner of your eye, you spot it - a spider. Cue the dramatic music! Your heart races, your palms get sweaty, and suddenly you're ready to take on this eight-legged foe. Or, as I must admit I've done once: you panic. In a desperate attempt to get off the couch after spotting a spider crawling next to you, you jump up - sending your plate of pasta flying through the air as you scramble to escape. I will never forget the stunned look on my partner's face as they watched me scream, pasta soaring and landing on the floor, followed by my uncontrollable laughter about the whole scence afterward. Fight or flight But how does this fight or flight reaction happen? Enter the amygdala, the superhero of our emotional responses. This little guy is responsible for processing emotions like fear and aggression, and when it senses danger, it sends a distress signal to the hypothalamus - the hotline to the body's emergency response team. Also read: How the ability to manage emotions shapes perception of risk Your hypothalamus then signals your adrenal glands to release adrenaline, which gets your heart racing, your breathing quickening, and your muscles tensing up. All of this is the perfect recipe for your fight or flight response - your body's way of either fighting the spider or running away from it. So next time you see a spider, just remember - it's not just your fear of spiders that's kicking in, it's your amygdala and hypothalamus tag-teaming to save the day (or at least get you to safety). Hormones and emotions: what's the connection? But wait, there's more! It's not just the limbic system that's responsible for our emotions. In fact, hormones also play a big role in how we feel. For example, when we experience stress, our bodies release a hormone called cortisol. This hormone helps us deal with the stressor by increasing our heart rate and blood pressure. On the other hand, when we're happy or in love, our bodies release dopamine and oxytocin. These hormones make us feel good and help us form emotional bonds with others. But what about those times when we can't seem to control our emotions? Like when we get angry and snap at someone for no reason, or when we feel sad and can't seem to shake it off. Nature vs. Nurture: how our environment shapes our emotions Well, it turns out that our emotions can also be influenced by external factors, such as our environment, our upbringing, and even our genetics. For example, some people are naturally more prone to anxiety or depression due to their genetic makeup. Similarly, our upbringing and experiences can also shape our emotional responses. If we grew up in a household where emotions were repressed, we might have difficulty expressing our feelings later in life. Conversely, if we grew up in an environment where emotions were expressed freely, we might be more comfortable sharing our feelings with others. Complexity of emotions: why there's no easy explanation So, what can we take away from all of this? For one, emotions are complex and multifaceted. There's no one-size-fits-all explanation for where they come from or how they work. But what we do know is that emotions are an essential part of what makes us human. They help us navigate the world around us, form connections with others, and respond to different situations in meaningful ways. So, the next time you feel a surge of emotion, take a moment to appreciate the intricate and fascinating workings of your brain and body. And, of course, keep on researching, because there's always more to discover! MEASURE YOUR EMOTIONS: What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now Read more on human behavior and emotions: - How to measure emotions - How to study human behavior - Must-see TED Talks on emotions - What are stimuli in human behavior research? --- ## Why you should use custom expressions in your facial expression analysis URL: https://noldus.com/blog/why-you-should-use-custom-expressions Published: 2024-02-06 14:15:00 Description: Using custom expressions in facial expression analysis can unlock a deeper understanding of human behavior. How can you use custom expressions in different fields of research? When delving into the complexities of human emotion, researchers often turn to the Facial Action Coding System (FACS), which breaks down facial expressions into individual components known as Action Units (AUs). Using these AUs - in combination with other metrics - it is possible to create your own custom facial expressions for your research. How can you use these custom expressions in different fields of research? And how do you create them in your facial expression software, like FaceReader? Benefits of custom expressions The use of custom expressions in facial expression analysis is a growing field. They offer benefits for researchers across various disciplines. That's because custom expressions can unlock a deeper understanding of human behavior that basic facial expressions might not reveal. Curious about how it could benefit your research? Below, we list some of the ways that custom facial expression enrich different fields of study. MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now Clinical psychology: beyond the basic emotions In clinical settings, the precision that custom expressions offer can be invaluable. For example, a standard set of expressions may not capture the nuanced difference between sadness and melancholy, or between a genuine and a social smile. By measuring custom expressions, researchers can discern these subtleties, helping to provide more accurate diagnosis and treatment planning. Developmental psychology: formation of emotional expression Developmental psychologists can benefit greatly from custom expressions by observing the formation and variation of expressions in young children. This can help in understanding developmental milestones and the emergence of social and emotional skills. In developmental psychology, custom expressions of interest may include subtle expressions of empathy, confusion, concentration, or frustration.  User experience: fine-tuning feedback In the field of user experience (UX) research, custom expressions allow for a more detailed analysis of user satisfaction. Instead of simply identifying frustration, custom expressions can differentiate between confusion, overwhelm, or disappointment. This provides actionable insights for product or website development, helping companies to better meet user needs. Also read this blog post if you want to know more about how to study human behavior. Neuroscience: better insights into cognitive processes Neuroscientists can use custom expressions to correlate specific facial movements with brain activity. For example, researchers may want to study expressions of concentration, frustration, or anxiety, helping them to find biomarkers for neurological conditions and shed light on memory processes. They may also gain insights into affective states associated with cognitive tasks. Human factors: enhancing safety and performance Custom expressions can play a critical role in optimizing safety and efficiency within human-machine interactions. By analyzing the specific combinations of AUs that signal cognitive load, boredom, anxiety, or stress, researchers can design more intuitive interfaces and controls. For example, we can learn when pilots get overloaded in complex decision-making by measuring their specific reactions in a flight simulator, prompting the redesign of cockpit alerts to prevent real-world incidents. Neuromarketing: understanding consumer emotion Researchers in neuromarketing may use custom expressions to delve into the subconscious reactions of consumers. By identifying the subtlest shifts in facial expressions that may indicate confusion, skepticism, or delight, brands can measure genuine emotional responses to products, advertisements, and shopping experiences. This type of feedback goes beyond what traditional surveys can capture, allowing marketers to fine-tune campaigns for their target audience. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Creating and using custom expressions in FaceReader When you're working with FaceReader, custom expressions are available in the Action Unit module. The software allows you to add different input blocks to form a custom expression, like action units, basic emotions, heart rate, and head orientation. Next, you choose how you want to combine and process these input blocks. With this formula, FaceReader calculates your custom expression in real-time.  Because you create your calculation beforehand, you can see the response right away and treat your custom expression like any other facial expression in the software. This will also save you a lot of processing time.  The power of custom expressions in research The key to successful facial expression analysis is not just in recognizing an emotion, but in understanding its complexity and context. Custom expressions enable researchers to study behaviors or emotions that basic expressions can’t always capture. This helps them to gain insights into emotions with a level of detail that was previously unattainable. This deeper analysis can lead to more personalized and effective interventions, products, and therapies.  Did you know? With FaceReader Online, you can measure facial expressions from any location. Read more in our blog post Why you should use FaceReader Online for your human behavior research. --- ## The many uses of the PhenoTyper URL: https://noldus.com/blog/phenotyper-applications Published: 2024-02-01 12:00:00 Description: With its new top unit, the PhenoTyper is even more versatile than before. Follow in the footsteps of those who have already added the PhenoTyper to their lab and learn all about its varied applications. PhenoTyper is more than just a cage, it's the perfect standardized environment for behavioral testing. Paired with EthoVision XT, it becomes a complete, automated solution for both short-term studies and long-term home cage experiments. EthoVision XT controls every aspect of the PhenoTyper setup, from video tracking and behavior recognition to precise hardware control. Whether you're running cognitive tasks, monitoring circadian rhythms, or designing complex learning protocols, this integrated system adapts to your research needs. However, you might be wondering; "what are the research applications of the PhenoTyper?", "and what can I achieve with this powerful combination? In short: PhenoTyper 2 can be adjusted to facilitate a great variety of tests! Long term behavioral recording The PhenoTyper is an ideal environment for long term behavioral testing. Rodents can spend hours, days, or even weeks in the PhenoTyper with no, or minimal human interference. This limits the stress an animal experiences from observers or handlers during an experiment. Moreover, there are many different long-term studies that can be performed, like learning tests and circadian rhythm analysis. Circadian rhythm tracking If you want to get the full picture of an animal's behavior, observing the animal throughout the day is a very good way to gain insight into the diurnal variations in behavior. Rats and mice are nocturnal animals. Therefore, observing them only during the day influences the outcome of activity testing. If your read-out parameters include behaviors like activity, drinking and eating behavior or use of enrichment like wheels, it is important to consider the difference time of day will have on these behaviors. The design of the PhenoTyper lends itself perfectly to observing a rodent for a continuous amount of time. Since everything can be automated using EthoVision XT, which is the engine of the PhenoTyper, a rat or mouse can be observed for a long time without a human observer entering the room. Need to measure additional, non-standard, parameters? For example food and drinking behavior? The PhenoTyper has many add-ons that include easy integration in EthoVision XT for synchronised behavioral readouts: - LickoMeter for measuring drinking behavior (detects change in capacitance, does not involve a current flow passing through the animal!). - Food pellet dispenser (for reinforcement-based conditioning tasks or timed feeding). - Mouse Feeding Monitor: beam break system for monitoring mouse interactions with a stainless-steel feeder. But also cage enrichment such as - Shelter with IR translucent black Plexiglas: this means you can see through this black material with IR lighting and a camera. A rodent perceives this as dark since they cannot detect light within the infrared wavelength range. - Wheels for mice and rats for measuring activity and cage enrichment. - Cognitive test addons, such as the CognitionWall. CognitionWall cognitive learning test Even though learning tests are often standardized, and commonly performed using short-term testing paradigms, learning, memory, and cognition can also be measured in long-term set ups. The CognitionWall is a test that can assess learning and reversal learning behavior and can be fully automated using EthoVision XT. The CognitionWall is a plastic barrier with three holes and a pellet dispenser behind it. The animal must enter a specific hole to gain a food reward, this way the rodent learns how to get a reward. Want to know more about how CognitionWall can be used in practice? Then check out this recent blog post. Short observational tests The integrated cage design of the PhenoTyper also lends itself perfectly to a variety of short-term tests. The PhenoTyper can easily be adapted to fit the needs of those tests, while retaining its reliability and data consistency. Open field If you want to measure exploratory behavior, for example in relation to anxiety, the PhenoTyper is a great environment to test this type of behavior. One such test is the open field test. In this test an animal is placed in a novel environment and several behavioral parameters are recorded. These readouts like total distance moved (and in which zone it moved, and how many times it crossed zones), defecations, and other behaviors like stretching and rearing are indicative of the rodents' emotional state. Square or round open field? One might make the argument that a round field is better than a square field but in practice this doesn't seem the case (Grabovskaya and Salyha). Moreover, with EthoVision XT and the uniform design of the PhenoTyper, your tests are consistent and easy to perform. This decreases variability between tests, and therefore, increases your data quality. Since the introduction of the PhenoTyper, hundreds of publications have used the PhenoTyper to perform the open field test. If you want to know more about the open field test or other rodent behavioral tests, be sure to check out our basic behavioral neuroscience e-book. FREE E-BOOK: Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download Novel object & place recognition test Memory and cognition are very important subjects in research concerning neurodegenerative diseases like Alzheimer's disease. However, measuring these parameters can be difficult and a variety of tests exist to test this. - One such test is the novel object recognition test. Typically performed in a similar area to the open field test, this experiment tests the Perirhinal cortex functioning of the rodent. - Another test that is similar to the object recognition test is the novel place recognition test. This experiment focuses on spatial memory and is therefore more about hippocampal functioning. As with the Open field test, the PhenoTyper's uniformity lends itself perfectly to performing these tests. Placement of objects in the cage can be perfectly measured and zones around the object can easily and consistently be drawn with the help of EthoVision XT. Accommodating tethered animals Performing behavioral tests with tethered animals can sometimes be difficult. The new PhenoTyper 2 top unit has been designed with accommodating tethered animals in mind. Researchers might use tethered animals during calcium imaging or optogenetic studies. Using the PhenoTyper for Calcium imaging studies In calcium imaging studies, fluorescent calcium indicators are introduced into neurons, allowing researchers to visualize changes in intracellular calcium levels in real-time. Tethered animals are typically equipped with miniature microscopes or imaging probes that capture neuronal activity as the animal performs specific tasks or experiences sensory stimuli. By leveraging the capabilities of calcium imaging, researchers can: - Map neural circuits, - Decode neural representations. - Investigate the neural basis of various cognitive processes and behaviors. This approach has broad implications for understanding brain disorders, neuroplasticity, and the mechanisms underlying learning and memory. Optogenetics in the PhenoTyper In optogenetic experiments, pulses of light delivered through the optic fibers trigger the activation or inhibition of neurons in real-time. This precise control enables researchers to elucidate the causal relationships between neural activity patterns and behavioral outcomes. Tethering ensures that the animal's movements are restricted, allowing for precise monitoring and control during optogenetic stimulation. Both optogenetic and calcium imaging studies have been performed in the original PhenoTyper. However, the design of the new top unit makes performing studies with tethered animals even easier. The central camera module can be fitted with holes in which you can feed all the cables needed for optogenetic and calcium imaging studies. This, in combination with with the automatic behavioral tracking from EthoVision XT, makes for a robust way to measure the behavior of rodents while performing optogenetics. Anxiety testing Anxiety testing in rodents using PhenoTyper opens up a realm of possibilities for researchers seeking an understanding of behavioral responses. The PhenoTyper, equipped with its versatile features, allows for the incorporation of mild aversive stimuli, providing a nuanced exploration of anxiety-related behaviors in rodent models. Automatic stimuli One approach to anxiety testing involves the use of automatic triggers, such as illuminating a specific zone or activating a light over the food hopper when the animal has been engaged in eating or drinking for a defined period. This subtle manipulation introduces mild aversive stimuli, allowing researchers to observe how rodents respond in these situations within the controlled environment of the PhenoTyper. With the new PhenoTyper 2 top unit, you will, in the future, be able to slot in specific modules that can give these aversive stimuli, like lights or sounds. This makes sure that the PhenoTyper is always tailored to your specific experiment. Curious about the practical application of anxiety testing in the PhenoTyper? Dr. Thomas Prévôt from the University of Toronto provides valuable insights into their laboratory's methodology. In a captivating video, he explains how they use the PhenoTyper to conduct anxiety tests. Check out what the PhenoTyper can do for you! In conclusion, having a PhenoTyper system enables you to do a great variety of tests. And even though this list that we present here is not complete, it gives a great impression into the many uses of the PhenoTyper. If you want to learn more about the PhenoTyper 2's new features, then check out our what's new page. Or if you want to explore how PhenoTyper is used in the field, you can check out the resources page. --- ## How to develop your training and education facility URL: https://noldus.com/blog/how-to-develop-training-and-education-facility Published: 2024-01-30 13:14:00 Description: The use of video in education can be very helpful to develop required technical skills, soft skills, and specialized knowledge. Many professionals, such as counselors, teachers, medical staff, and others, need to have developed the necessary practical skills prior to starting the actual job. Training and education facilities are crucial for this kind of individual development. Getting trained and educated helps individuals acquire and enhance skills relevant to their chosen fields. This can include technical skills, soft skills, and specialized knowledge. Training and education also contribute to personal growth. It fosters critical thinking, creativity, and problem-solving abilities. FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly Many professions require ongoing education to stay current with industry trends, technologies, and best practices. Training facilities offer courses and programs to support professionals in their career development. But all these learning processes only happen when trainees receive feedback on their performance on a regular basis. This feedback is logically preceded by observation. When observation is part of professional development (including frequent and targeted feedback), this is a powerful way to build self-confidence, get motivated, and cultivate a mindset in which people learn and grow. Also read: Why use video feedback in education? to discover the benefits for students and trainers. Why you should integrate video feedback Remember the days when feedback was just a few lines scribbled on paper? Boring, right? Well, video feedback is here to shatter that monotony and take feedback to the next level. By using video, teachers can now provide more engaging, personalized, and comprehensive feedback to students. Thus, if you're planning to develop a training or education facility, a tool that provides video feedback should be on your list. Put theory into practice in a safe and controlled environment The use of video in education can be very helpful to develop required skills. AIXTRA's competence center for training and patient safety created a modern simulated learning environment that allows trainees to put theory into practice in a safe and controlled environment. The Viso software suite allows trainers and educators to focus on what really matters: providing students with immediate feedback on their skills and practices. Within the competence center, trainees work through a wide range of scenarios in different healthcare settings, including the home environment. From developing therapeutic communication skills to caring for critically ill patients, these scenarios will help prepare trainees for future placement and work opportunities. How to develop a training and education facility: questions you should ask When designing this type of center, it is best to describe the training or educational program in great detail. With greater levels of detail, it becomes clear what kind of equipment you will need, as well as which physical environment would best suit your observations, simulation, or training. Questions to help you - How many trainees do you want to train at the same time? - Do you need video recordings of all trainees? - Do participants need to walk around during the training? - How is security of video material guaranteed? For example, it's not safe to store videos on an external hard drive, as there is a possibility of theft. Storing the videos on a server is more secure. Overall, protecting the sensitive video material is of the highest importance. - How many rooms are available? You can use a single room training facility, but it is more common to equip multiple rooms with video and audio recording tools to allow more students to train at once. Alternatively, students may rotate the training, where one group of students observes the other through a one-way mirror, and switches once the first group's training has ended. Answering these questions is just a first step in setting up an educational training facility, but it is a necessary one. Video and audio data can be of great use in training, but can also be used in further research. For example, comparing multiple training sessions may provide additional insights into training and instruction methods. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download Example of an education facility with tools to analyze interactions At the Institute of Educational Management of the University of Mons in Belgium, the interaction between a trainee teacher and students is studied to improve teacher practices. Marie Bocquillon uses two labs. An observation lab, where trainee teachers are recorded while giving a lesson to their peer students, and an interaction lab, where the video feedback sessions take place. These feedback sessions are conducted based on the video of the trainee's teaching practice performance, that has been annotated by the supervisor. During debriefing, the supervisor and the trainee teacher watch and discuss how the trainee teacher acted during the lesson. Example of a training facility in a counseling psychology program Delaware Valley University has created a state-of-the-art training facility for their Master of Arts in Counseling Psychology program. In this program, students specialize in either child and adolescent counseling, or social justice community counseling. Throughout their training, graduate students are continually engaged in counseling, outreach, and advocacy. The university transformed an obsolete laboratory facility into a comprehensive training space with multiple rooms, fully equipped for students undergoing training to become professional counselors. The lab serves as a dynamic environment for highly interactive, skill-based courses, enabling students to engage in role-playing, practical exercises, and hands-on learning experiences. Each practice session is observed, recorded, and reviewed to offer genuine feedback and foster opportunities for growth. Check out what they say about the process of designing and building a state-of-the-art training and education facility. --- ## Research examples of developmental psychology URL: https://noldus.com/blog/research-examples-of-developmental-psychology Published: 2024-01-19 16:00:00 Description: When you are studying developmental psychology, you’re studying how people grow and develop, all the way from childbirth to the end of their lifespan. What are examples of developmental psychology? When you are studying developmental psychology, you’re studying how people grow and develop, all the way from childbirth to the end of their lifespan. What are examples of developmental psychology? It could be anything within a range of subject matters that are related to human growth. Not just psychological behavior, but anything from thoughts and emotions, cognitive and linguistic development, to decision making and motivation, moral and even physical development like motor skills. Research examples of developmental psychology Over the years we’ve come across many examples of research in developmental psychology, often done with various behavioral research tools. Are you looking for topics for developmental psychology research papers? We’ve put together an overview of research examples in developmental psychology that were published on the Behavioral Research Blog. Table of contents - Infant Stage - Adolescent Stage - Adult Stage Examples of developmental psychology: Infant stage The infant stage is the time from birth until children are (roughly) two years old. A time that has been well studied by researchers, as changes are rapid and these first years in life are considered fundamental in our development. Early infant behavior development of hand preference In learning about objects and their parts, transporting objects to new locations, and sharing objects with others, the hands are essential. Infants discover how to control each hand and how to use the hands together. There are many reasons to study the development of hand preference in infants, as it can provide clues about motor skills or any developmental disorders. A team of researchers was particularly interested in asymmetric bimanual actions and presented “Unimanual to bimanual: Tracking the development of handedness from 6 to 24 months”. Read the full post here: Early Infant behavior development of hand preference In the Noldus Webinar 'How emotions are made in Baby FaceReader', we tell you about emotions, how they are 'made' and how this relates to facial expression analysis in FaceReader with a focus on Baby FaceReader.  Observing and analyzing repetitive movements in infants to detect autism In the first year of life, an infant learns how to use his or her arms, legs, mouth, hands, and fingers by repeating movements over and over again. They discover a wealth of possibilities. However, an increased frequency of repetitive movements has been widely described in neurodevelopmental disorders as well.  To examine if a specific repertoire of repetitive movements was present in children with autism, researchers used home videos to code the behaviors of the infants. Continue reading: Observing and analyzing repetitive movements in infants to detect autism Gaze behavior in infants Infant siblings of children with or without ASD participated in a study to determine whether gaze behavior, showed during a test with an unfamiliar examiner, could predict gaze behavior in a more naturalistic context. The team of researcher Gangi examined prospectively infant gaze behavior at 6, 9, and 12 months of age in infants who were later diagnosed with ASD, as well as low- and high-risk infants without autism spectrum disorder outcomes. To measure the cognitive functioning of the infants, the Mullen Scales of Early Learning was filled in at each visit by an examiner. Meanwhile, infant gaze to the examiner’s face was recorded, and play interaction with a parent took place. Read the full post here: A closer look at eye contact Understanding infants’ social and moral development At the Centre of Infant Cognition at UBC in Vancouver, researchers conduct independent studies as well as participate in ManyBabies projects to further understand the development of moral and social behaviors of infants. Discover the full story here: Understanding infants’ social and moral development Developing social communication and the role of mimicry Children learn from interacting with others, especially their parents. For example, reproducing the emotions that others express is part of that. Copying facial expressions is one of the great milestones in the social development of a child. Still, little is known about the mechanisms controlling the early development of emotional mimicry. Therefore, a research team of the University of Amsterdam conducted a study to investigate infant emotional mimicry, parent-infant mutual attention, and parent dispositional affective empathy. Read more about this study here: The role of mimicry in the development of social communication  FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Adolescent stage Adolescence is the period of transition between childhood and adulthood. It is a time for rapid cognitive development. When entering adolescence children are going through many changes at the same time: both physical and intellectual, as well as their personality and social skills that are developing. We’ve published several articles about studies into the adolescent stage. Direct observations help develop effective interventions in adolescence In a study by a team of researchers from Arizona State University, John Hopkins School of Medicine in Baltimore, Maryland, and the Oregon Research Institute, family and friendship dynamics in adolescence were observed in order to develop more personalized interventions that prevent problem behaviors and adjustment issues. Continue reading about effective interventions in adolescence. Dealing with depression in adolescence In adolescence, the ability to regulate emotions is heavily challenged by numerous biological, social, and psychological changes. How are adolescents’ emotions socialized by mothers and close friends? A study by a team of researchers from Canada and The Netherlands focused on dealing with depression in adolescence. Continue reading: Understanding adolescent emotions Studying conflict interactions between mothers and adolescents Adolescence is a developmental phase with many physical, neurodevelopmental, psychological, and social changes. It is common for conflicts to arise between adolescents and their parents. However, severe conflicts can have negative effects on adolescent development. What can parents do to prevent escalating conflicts?  FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly Read 5 more examples of research in adolescence here >> Research examples in developmental psychology research: Adult stage Adult development encompasses the changes that occur in biological and psychological domains of human life from the end of adolescence until the end of one's life1. When studying adult development, many researchers tend to focus on aging and health.  Some study eating behavior in residential care homes which enables them to take environmental factors into account. Others focus on family relations and communication and try to facilitate and improve contact between parents and children living a distance apart. Some examples of developmental psychology research in the adult stage of life. How to measure couple communication patterns Communication between husbands and wives is often discussed on TV, in magazines, and is frequently a topic of discussion amongst friends. Additionally, it is also a popular research theme. Effective husband-wife communication can benefit a relationship. But are there specific behaviors which need enforcing and are they the same for every couple? Read more: How to measure couple communication patterns Measuring flow Flow is a state in which a person is fully involved in an activity, decreasing self-consciousness and sense of time. This process requires a person to be extremely focused, as well as exactly have the skills to master a task. Several researchers have developed methods of measuring flow. Find out more: Measuring flow MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now Do your emotions and moods change as you get older? Are emotions affected differently for younger than for older people? Researchers used FaceReader to complement self-assessments and objectify mood changes to answer this question. They exposed participants to film segments to induce four basic emotions: anger, disgust, happiness, and sadness. Behavior and emotions of older adults It's important to develop user-friendly products and services to assist older people in daily activities and improve their quality of life. Therefore researchers wanted to find out if TV footage could motivate older persons to start being more active? Being active can improve the overall health of a person (65+ but of course also 65-!).  Read the full blog post on research projects on behavior and emotions of older adults. On-site observational studies with older persons In certain cases, observations for your study are best performed on-site. There are many examples of observational studies with older age groups, conducted at home or at a healthcare facility. We've highlighted two examples of on-site observational studies with older persons. Robots helping people with dementia Behavioral and psychological problems affect most individuals with dementia at some point during the progression of the disorder. Researchers explored if the use of a robotic seal as a therapeutic tool would influence the emotional and behavioral symptoms of dementia.  Find out more about this large study on robotic pets here! RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources More topics in developmental psychology research Of course there are many more topics in developmental psychology. An overview of the research topics can include: - Cognitive development: Piaget's theory, information processing, and language development - Social and emotional development: attachment theory, moral development, self-concept and identity formation - Physical development: motor skills, sensory development, growth and maturation - Perceptual development: visual perception, object permanence, perceptual constancy - Personality development: nature vs. nurture debate, temperament, self-esteem and resilience - Contextual factors in development: the role of culture, family, peers, media and technology - Adolescent development: puberty, identity formation, moral reasoning and decision-making - Lifespan development: aging, retirement, end-of-life issues - Education and development: learning theories, early childhood education, motivation and engagement in school - Neurodevelopmental disorders: ADHD, autism, or dyslexia. These articles might interest you as well: - How to study human behavior - Learn about people's behavior by observing them - Examples of human behavior research - Behavioral coding: What and how - Five studies showing the power of multi-modal data in behavioral research --- ## Agricultural pesticides and Parkinson's Disease: current screening procedures URL: https://noldus.com/blog/proper-screening-for-toxins-parkinsons-disease Published: 2024-01-17 12:00:00 Description: Parkinson's disease, what are its symptoms? What role do environmental toxins play in its development? And why should we be critical on current toxin research methods? Parkinson's disease (PD) is one of the most prevalent neurodegenerative diseases in the world, increasing significantly over recent decades. PD is characterized by the loss of dopaminergic neurons in the substantia nigra (Latin for "black substance"), a critical structure in the midbrain region which plays a vital role in movement control. Its dark appearance (and hence the name) is due to high levels of neuromelanin in the dopaminergic neurons. Although PD is primarily recognized as a movement disorder, it also encompasses several non-motor symptoms. Key Parkinson's Disease symptoms in humans and rodents Motor symptoms Humans Motor symptoms Rodents Non-Motor symptoms Humans Non-Motor symptoms Rodents Tremor: often a resting tremor, noticeable in the hands, arms, or legs when relaxed. Tremor-like movements: Although not as prominent as in humans, some models show tremor-like activity. Cognitive changes: issues with memory, planning, or decision making. Cognitive impairments: memory and learning deficits are evaluated using mazes and other cognitive tests. Bradykinesia: slowness of movement, a hallmark of PD, making daily activities difficult and time-consuming. Reduced movement and slowness: Analogous to human bradykinesia. Sleep disturbances: insomnia, restless leg syndrome, and REM sleep behavior disorder. Sleep disturbances: altered sleep patterns observed in some models. Rigidity: stiffness in the limbs or torso. Rigidity and postural instability: assessed through various behavioral tests. Mood disorders: depression and anxiety. Mood alterations: changes in behavior indicative of depression or anxiety. Postural instability: issues with balance and coordination, leading to a higher risk of falls. Impaired coordination and balance: evaluated using tests like the rotarod or beam-walking assays. Gastrointestinal issues: such as constipation. Gastrointestinal dysfunction: such as changes in bowel movement regularity.     Sensory symptoms: altered sense of smell and pain       Autonomic dysfunction: changes in blood pressure, sweating and bladder control.   Modeling Parkinson's Disease in rodents To study PD, researchers often turn to rodent models, primarily in mice and rats. These models provide a valuable tool for understanding the disease mechanisms and testing for potential treatments. These models replicate many key aspects of human PD, including both motor and non-motor symptoms, though with some limitations in fully replicating the human condition. By observing and quantifying changes in rodents' behavior and neurological function, these can be used as proxies for human symptoms. For example, in assessing motor coordination and balance, a rat or mouse might be placed on a rotating rod (rotarod test) to measure its ability to maintain balance, mirroring the motor coordination issues seen in PD patients. Creating rodent models of Parkinson's Disease Rodent models of PD are typically created using neurotoxins like 6-hydroxydopamine (6-OHDA), MPTP, or rotenone, which selectively destroy dopaminergic neurons in the substantia nigra. Genetic models, which replicate mutations found in familial forms of PD, are also used. A recent review by Shan et al. compared the toxins rotenone and paraquat, which induce PD-like features in mice, and provide a broader perspective, as they are commonly used pesticides, thus linking PD research to real-world environmental concerns. Agricultural pesticides, a serious (mental) health threat Shan et al.'s review aims to substantiate the relationship between exposure to environmental toxins and the risk of developing Parkinson's disease (PD). The authors highlight the inadequacy of current screening procedures to assess specific PD risks associated with exposure to toxins, particularly pesticides, solvents, and heavy metals such as lead, mercury, arsenic, cadmium, and chromium, which can be found in the environment, products we use, and even in our food and water. They therefore suggest a detailed and enhanced approach to toxin screening, involving multiple stages, as a crucial step in generating useful information. This data can then guide policymakers and governments in identifying environmental factors that may contribute to the risk of Parkinson's disease. Multi-tiered screening process Shan et al. propose a multi-tiered screening process, starting with in silico studies and followed by in vitro tests, whole-organism models, and in-depth rodent models. This approach which aims to identify neurotoxic compounds and understand their mechanisms, creates a more robust approach to better understand the effects these environmental toxins can have, and perhaps offer a pathway to more effective PD prevention strategies. Measuring behavior in Parkinson's disease (PD) rodent models The use of rodents in testing for the effects of neurotoxic compounds on the onset of Parkinson's disease is crucial. Furthermore, rodent models also give key insights into the progression of the disease. Behavioral changes in rodents serve as indicators of neurodegenerative processes and are used to evaluate the efficacy of the multi-tier screening approach reviewed by Shan et al. The following tests can be used to research these behavioral endpoints. Methods of measuring behavior - Behavioral test battery: This includes a series of tests such as the open field test for exploratory behavior, rotarod test for motor coordination, Catwalk XT test for gross motor function, pellet grasping test for fine motor function, grip test for muscle strength, and apomorphine-induced rotation test for detecting dopaminergic circling deficits. - Automated home cage monitoring: Tools like Noldus' PhenoTyper are used to assess day/night activity patterns and anxiety levels in rodents. This includes tests like the light spot test for anxiety and cognition wall for measuring reversal learning. - Neurochemical assessments: In addition to behavioral tests, some of the animals need to be sacrificed at different time points to assess dopamine neuron degradation in the substantia nigra, which is critical for understanding the neurochemical changes underlying the observed behaviors. In the context of PD research, behavioral measurement is crucial, especially in the latter stages of toxin screening involving rodent models. Such behavioral data are essential for understanding the neurotoxic impacts of these compounds and their potential link to PD. RESOURCES Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources A comprehensive approach to Parkinson's disease The work by Shan et al. represents important steps in the understanding of PD. Taking a critical look at the pesticides we use in agriculture, and what effect they can have on our health long term, is crucial for our long-term health. Many debates exist, and have long existed, about the use of pesticides, and we must remain critical. Clear screening and testing procedures for its health effects, short and long term, are crucial to collect the evidence we need to fully understand these effects. Which is why the review by Shan et al. is important to take note of. Linking pathology to behavior still remains a crucial last step in validating disease models such as described here. Using tools like the PhenoTyper and CatWalk XT, researchers can make these leaps, and validate on symptom level, that we are indeed modelling a human analogue, and work accordingly towards treating these symptoms, maybe even the disease itself. Reference Shan, L.; Heusinkveld, H.J.; Paul, K.C.; Hughes; Darweesh, S.K.L.; Bloem, B.R. & Homberg, J.R. Towards improved screening of toxins for Parkinson's risk. npj Parkinsons Dis. 9, 169 (2023). https://doi.org/10.1038/s41531-023-00615-9 --- ## How to debrief a training session URL: https://noldus.com/blog/how-to-debrief Published: 2023-12-19 09:00:00 Description: What is debriefing, what to expect of debriefing, how to debrief a training session, and why is using a video feedback tool helpful? When you google 'How to debrief a training session' you will find out that debriefing takes place in many different fields. Originally, debriefing sessions were used strictly for military purposes. Nowadays, in healthcare, education, and psychology, it is also very common to gather together after a training session and discuss what really happened during that session. What is debriefing? After a certain activity – such as a simulation session, a mock interview, or a training exercise – follows a meeting (the debriefing) in which a number of events that occurred during the activity are explored, lessons are learned, and extra information is given. A debrief is a simple, yet powerful tool that enables participants to reflect on what happened during a session and why it happened. Debriefing takes place soon after the activity, so that the events are still fresh in mind. This way, gaps in knowledge and performance can be identified. By reflecting on and recognizing the knowledge, skills, and attitudes used in the session, participants develop personal awareness and insight and become consious of personal learning goals to ensure future success. FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly What to expect of debriefing? - It facilitates recall and insight - It clarifies learning points - It builds trust and self-confidence - It improves (team) performance - It promotes a positive change in behavior How to debrief a training session Good, thorough preparation of a debriefing session is required to establish a safe and engaging learning environment. During the debriefing, the group explores what happened (the What), why it happened (the So What) and what should happen in the future (the Now What). You can start with some general, open questions, such as 'how did it go?', 'what did it feel like?', and 'did you accomplish your predefined goals?'. Subsequently, the important events can be identified and the personal experiences of the participants can then be supported with video images. Video reviews give substance to the understanding phase, and help answer the questions of why things happened, were said, and were decided. Use a video feedback tool That's where Viso comes into play: Viso is the user-friendly system used to create and play back audio- and video recordings. At its core, Viso is a video feedback tool, which allows users to add feedback with personalized markers. Trainers can set markers and/or add comments either while watching the training session in real time or while reviewing the recorded video after the fact. While playing back the recordings during debriefing, you can see at a glance which behaviors were marked and at what moment. Participants will see what actually happened, discuss the marked moment and consequently gain deeper insight. Why use audiovisual tool Viso? A customer explains Dennie Wulterkens, paramedic and owner of Secta Medical, explains that using Viso as a dedicated debriefing system enables you to look back at your own and each other's performance and see what the interactions were. He claims that people learn a lot from that. Watch the video to discover all the benefits. Summarize the main learning points To conclude a debriefing session properly it is important to explicitly summarize lessons learned from the session and consider how the main learning points can be incorporated into future practices. Ask questions such as 'What did you do well; what did you find difficult and why?' to reinforce learning points. Finally, determine how the participants can improve on these points. Focus on one or two topics, as more than that can be overwhelming. How to use video-based feedback for debriefing sessions Example in education: Marie Bocquillon trains future teachers to use the tools she and her research team has developed to improve teacher practices. After the trainees give a lesson to their peer students, a video feedback session takes place. During debriefing, the supervisor and the trainees watch and discuss how the trainees behaved during the lesson. Example in clinical psychology: With a multi-room, fully equipped training space for students, Delaware Valley University trains its students to become professional counselors. Viso allows the faculty and trainers to record all sessions, particularly the mock counseling sessions. Equipping the facility with Viso has allowed faculty and students to quickly debrief at the end of an interview to discuss the session. Example in healthcare: At the Child surgical Intensive Care ward of the Erasmus MC Sophia Children hospital in Rotterdam a Crew Resource Management (CRM) Training has been implemented, together with scenario training. The scenario begins with the nurse starting "the shift" as usual on the ward. In the meantime, the trainers simulate an incident, for example an infant crying because of pain, a rapid heart action, or a lowering blood pressure in shock after a bleeding. A scenario ends after 15-20 minutes, when the predetermined learning points (skills, knowledge, and teamwork) have been achieved. The trainer, doctor, and technician discuss which part should be played back during the debriefing session. In the Noldus Webinar about Simulation-based training, Karin Kuiper tells you all about this scenario training. Curious? Watch the webinar on demand now! BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download References Debriefing for clinical learning Debriefing: A Simple Tool to Help Your Team Tackle Tough Problems --- ## The Noldus SfN 2023 recap URL: https://noldus.com/blog/noldus-recap-sfn-2023 Published: 2023-12-14 07:00:00 Description: A quick recap of our SfN 2023. What were some common trends? And what did our trusted customer base most commonly ask for? Find out this and more in this blog! It's already been a month since we visited SfN! We wanted to share a quick recap with you of our great week in Washington D.C. In this recap, you can read about some of the big trends during the conference, and new innovations we showed our trusted customers and newcomers to Noldus alike! The most common trend: AI AI was all the hype Current and new technologies are investing in, and promoting, AI strongly. AI is revolutionizing the way we measure behavior, quantify physiological parameters, and even how we read and dissect research papers. Noldus is not new to the AI field. We've already been implementing AI tracking for a few years, going back a few iterations of EthoVision XT, where we introduced deep learning tracking. Deep learning technology in EthoVision XT works on rats and mice with an even fur color and hooded (Long-Evans) rats. Using deep learning requires substantial computation power, you need a Graphics Processing Unit (GPU) that is able to sustain those computations. Our customers' trust in Noldus tools Our existing customer base also visited the booth a lot! A common question they asked was: What's new this year!? Why do they ask that? Well, as existing customers, they know that we at Noldus are constantly innovating, evolving, and advancing our behavioral research tools. We collaborate heavily with the scientific community to create solutions that are needed in the field. This bottom-up approach has always been at the forefront of Noldus' vision. So, what was new this year? PhenoTyper 2: a revolutionary update PhenoTyper 2 brings some long-awaited updates to our behavioral home-cage system! By far the most exciting change is the modular top unit, which can fit modular pieces that can be removed and/or swapped out for other integrated add-ons, making it highly customizable to your needs, while ensuring flexibility for the future. The Smart Annotator: our new AI-based smart annotation tool We are constantly looking for smart and effective ways to reliably increase your data acquisition capabilities. When looking at additional behaviors, such as grooming, jumping, and rearing, this has traditionally been scored by human observers. This takes time, is prone to repeatability issues, and is inherently subjective. This is why, with EthoVision XT, you can add the behavioral recognition module that automatically, objectively, accurate, and tirelessly scores additional behaviors in rats or mice. Enter: The Smart Annotator. Noldus' newest AI tool uses data from the Behavior Recognition Module and gives you suggestions of the recognized behavior, which you can then choose, correct, or fine-tune. The Smart Annotator automatically detects behavior in mice and rats from a trained AI model in an intuitive layout. Difficult cases are presented to the user, who can then decide where the model is unsure. The AI will do the heavy lifting, but the user remains in control. You might ask yourself: "What is the added benefit compared to the already existing behavioral recognition module?" The trained AI network is not static. By selecting the suggested behavior, the AI network within The Smart Annotator improves its recognition based on your input. The Multi Subject Tracker: Accurately video track multiple subjects simultaneously More AI integration! With The Multi Subject Tracker (MST) in EthoVision XT, tracking and analyzing social interactions of mice and/or rats will be done in pre-trained AI models. This innovation is taking our renowned behavioral research tools to new levels of accuracy, efficiency, and user-friendliness. These were some highlights, read more about upcoming products in our pre-SfN blog! Research with Noldus tools If there is research done that includes measuring behavior with video tracking, there is over 60% chance that this is done with Noldus tools. It is one of 10 reasons why you should use software in your lab, such as our flagship product EthoVision XT. At SfN we had a great booklet filled with research projects that were being presented there and then at SfN! It provides an overview of presentations from the Noldus community at Neuroscience 2023 (organized by date). These studies incorporate one or more Noldus tools, such as EthoVision XT, DanioVision, PhenoTyper, or CatWalk. Prize winners Everyone who filled in their information to be displayed in the booklet, by submitting their abstract, had the chance to win a Noldus conference prize of $500. Dr. Bethany Kondiles, from the University of British Columbia, won one of our abstract prizes about her research with CatWalk XT on remyelination in a Spinal Cord Injury model. She has used the CatWalk XT to examine the potential of repurposing the drugs metformin and clemastine to improve recovery from spinal cord injury (SCI), particularly by promoting remyelination. Congrats Bethany! And also congrats to Maricela Martinez from the University of California, Irvine, with her prize about her research on the Assessment of Microflia Function After Adolescent delta-9-tetrahydrocannabinol and Adulthood Opioid Exposure. In her research she asks the question: Does Adolescent THC persistently increase vulnerability to opiod addiction in part via actions of Microglia? She used EthoVision XT to measure behavior in rats after exposure to THC (a cannabinoid drug) during adolescence. A great quote by Maricela: "EthoVision is such a staple of the lab!" We are always delighted to hear how our products change the game for researchers. Record number of booth visitors We've never had so many visitors in our booth than this year! We would like to thank everyone that visited us, the conversations were great, engaging, and insightful. We were able to help so many researchers with any questions they had regarding their setup or what they desired in terms of measuring behavior in the future. The SfN 2023 Noldus team had a great time talking to everyone and enjoyed every last second of SfN! Noldus mouse Also we had a lot of fun with our beloved green Noldus mouse! We started a campaign on social media: #noldusmouse, which will continue to run indefinitely! So did you take a Noldus mouse home? Or to the lab? Take a picture and post it with the hashtag #noldusmouse With love from the Noldus crew! And we hope to see you again next year, at SfN 2024! --- ## Unlocking the link between CNS infections and cognitive decline URL: https://noldus.com/blog/infections-cognition Published: 2023-12-05 10:00:00 Description: Bacterial infections in the brain can have lasting effects even after recovery. In this blog we will look a study that used PhenoTyper and the CognitionWall to study the mechanisms behind this cognitive impairment. Bacterial infections can be very harmful to our body. This is especially true in the central nervous system (CNS), where infections can lead to cognitive decline. A recent study shows that experiencing a CNS infection increases the risk of developing a form of dementia [1]. A key cause of the neurological damage is inflammatory responses to the infection. In this blog we will explore a research paper by Cassidy and colleagues that aims to explore the underlying mechanisms of these neurological complications using the PhenoTyper with the CognitionWall [2]. Studying brain infection with a mouse model For this study Cassidy et al., injected Listeria monocytogenes (Lm) into eight-week-old mice. Lm is a food borne bacteria that invades the brain and can cause neurological complications after infection. Lm is a traceable model organism, which makes is especially useful to study immune responses to CNS infections. The researchers injected D57BL/6J mice with either phosphate buffered saline or PBS containing a strain of Lm. In this experiment two different strains of Lm were used. The first was the Lm 10403s strain (which is lethal to the mouse without antibiotic treatment), and a mutant strain that has the gene that encodes for listeriolysin O deleted. This mutant does not invade the brain. After injection, the mice were provided with antibiotics. The CognitionWall was used to assess cognitive ability of the mice. The mice were observed in the PhenoTyper using EthoVision XT. The combination of the PhenoTyper cage and EthoVision XT tracking software allowed the researchers to observe the animals and conduct tests without having to handle the animals or be present, minimizing the influence of humans. RESOURCES Read more about PhenoTyper The PhenoTyper is ideal for these kinds of tests. Do you want know more about what the PhenoTyper is? Then follow the link to the PhenoTyper product page. - Free white papers and case studies - Customer success stories - Recent blog posts Resources How do you test learning behavior? The CognitionWall is an add-on for the PhenoTyper cage that assesses both discrimination learning and reversal learning. The CognitionWall contains three holes that the mouse can enter to gain a food reward. When a mouse enters the area through the correct hole it receives a food reward. The recording of the mouse movement and the dispensing of the food reward are all controlled by EthoVision XT using the Trial and Hardware Control Module. The number of entrances or any combination of correct response can be programmed into the system. Cassidy et al. also changed the protocol to test if the mouse was able to extinguish the previously learned behavior and learn how to obtain the new reward. Reversal learning is more complex as it involves multiple brain regions, like the hippocampus, amygdala, orbitofrontal-frontal cortex, and dorsal striatum in humans. BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Download Bacterial infection causes cognitive decline Cassidy and colleagues were able to show that mice that had recovered from a Lm infection had lower performances in both learning and extinction of learning tasks. Although slight differences were shown as early as one month after infection, the most significant results were observed four months after infection. Furthermore, the strongest cognitive decline was found in the neuro invasive strain, as opposed to the mutant strain. This was due to a persistent neuronal inflammation. However, mice injected with the mutant strain showed cognitive decline compared to the control. The underlying mechanism is most likely related to the trigger of systematic cytokines in response to the infection. This was not explored further by the researchers but does suggest that the cognitive decline is not solely caused by cellular infiltration of the bacteria into the brain. Interestingly, mice infected with the neuro invasive Lm showed decreased movement, which is also something that has recently been observed in humans suffering from cognitive impairment. Furthering understanding of infection in the brain The authors state that it is important to perform more experiment with different strains of Lm, especially a strain that causes brain inflammation while not invading the brain. Furthermore, they conclude that a broader study is necessary that looks at a more diverse age group and sex of the mice (since only male mice of a specific age were used in the study). The ability to understand and measure the effects of these infections on cognitive functioning is a key step towards identifying how different infections affect the brain through neuro toxic actions. This information is vital towards developing effective therapies for minimizing cognitive decline after an infection. FREE E-BOOK Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download References [1] Sipilä, P.N.; Heikkilä, N.; Lindbohm, J.V.; Hakulinen, C.; Vahtera, J.; Elovainio, M.; Suominen, S.; Väänänen, A.; Koskinen, A.; Nyberg, S.T.; et al. Hospital-Treated Infectious Diseases and the Risk of Dementia: A Large, Multicohort, Observational Study with a Replication Cohort. Lancet Infect. Dis. 2021, 21, 1557–1567, doi:10.1016/S1473-3099(21)00144-4. [2] Cassidy, B.R.; Logan, S.; Farley, J.A.; Owen, D.B.; Sonntag, W.E.; Drevets, D.A. Progressive Cognitive Impairment after Recovery from Neuroinvasive and Non-Neuroinvasive Listeria Monocytogenes Infection. Front. Immunol. 2023, 14. --- ## Observing effective leadership and teamwork URL: https://noldus.com/blog/observing-effective-leadership-teamwork Published: 2023-12-05 09:28:00 Description: How do organizations, leaders, teams, and employees work together to ensure efficient improvements and effective changes? The OBCC team combined video-based behavioral observations and physiological measures to examine this. This guest blog is written by Dr. Desirée van Dun, Dr. Lara Carminati, Dr. Pauline Weritz, and Aninka Spekle of the Organizational Behaviour, Change Management & Consultancy (OBCC) team within the High-tech Business & Entrepreneurship department at the University of Twente. Observing effective leadership and teamwork through The Observer XT and BIOPAC software Society expects organizations to deal with the manifold global challenges that require major (technological) business transformation. In line with the United Nations Sustainable Development Goals, many organizations pursue digital, agile, lean, and green, and employee-healthy ways of working. The Covid-19 pandemic accelerated the potential of fostering the professional teaming up in virtual and cross-cultural ways. Still, leaders and employees need a wide range of skills and behaviors to support these transformations and thus make a positive impact in our complex world. To support such an impact, we, the Organizational Behaviour, Change Management & Consultancy (OBCC) team within the High-tech Business & Entrepreneurship department at the University of Twente, research how organizations, leaders, teams, and employees work together to ensure efficient improvements and effective changes. To achieve this, we apply a unique mix of complementary and interdisciplinary areas of expertise and study change processes in a wide array of organizational settings. Video-based behavioral observation methods OBCC is specialized in adopting a unique and powerful combination of video-based behavioral observation methods and physiological arousal measures. We used The Observer XT software and the BIOPAC measurement system to do field research to uncover the observable behaviors of effective leaders and teams. In this blog post, we guide you through the various phases of our research, where we unveil new discoveries and explore the software's wide potential. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Phase 1: Examining how leaders behave and their leadership dynamics In the first phase, we used The Observer XT software in, among others, a study by Van Dun et al. (2017) to explore how middle managers behave in team meetings. The study focused on examining effective leader behaviors in the context of Lean Management, a way of making organizations work better and more customer friendly. As the 2007 financial crisis made companies rethink how they work and use their resources, Lean Management was further popularized. Although leadership is crucial in making Lean Management work, leaders' role in Lean practices has often remained unclear. Hence, we conducted two studies to learn more about how leaders behave in Lean initiatives. In the first study, we reviewed the literature and asked Lean experts for their opinions to develop a list of behaviors and values. In the second study, we video-observed experienced middle managers in Lean Management to find out their specific values and behaviors. In a second study, we used The Observer XT software to minutely observe 19 specific behaviors, with two independent coders. Examples of those behaviors are "asking for ideas" or "information sharing". In doing so, we also compared the 'Lean' middle managers with the video-observations of another set of effective middle managers from Hoogeboom's PhD study, which got published in 2019. Indeed, Hoogeboom and Wilderom (2019) also used The Observer XT in their study to look at generally-effective leaders' behaviors. For many years, there have been two main ways of thinking about leadership, transformational leadership focusing on motivating and inspiring people, and transactional leadership focusing managing tasks and giving directions. Their study explored these two polar ways of thinking leadership and tried to dissect which behaviors were important for a leader to be successful whilst also finding better ways to measure these behaviors. Through The Observer XT software, 27 observable leaders' behaviors were found during regular staff meetings and this helped to gain more insights into effective leadership dynamics. Also read: How to study human behavior. Phase 2: Examining the interaction between leaders and team members In our second phase, we investigated not only the behavior of leaders but also that of their team members. Therefore, we video-observed team meetings as well as on the work floor through video shadowing. The findings of this research have been published in the study of Van Dun and Wilderom (2021). This study aimed to understand how successful work teams, their leaders, and top-level leaders behave and learn from each other. Grounding our study in a theory that posits that people tend to learn by copying the behavior and values of their successful superiors, we followed five high-performing work teams for three years, using The Observer XT software to study how the teams and their leaders behave, objectively. The study discovered a collective activity pattern known as a "coactive vicarious learning-by-doing" that helps teams perform well and consistently. Employees started to copy the behaviors of their team leaders, and leaders adapted the employees' behaviors based on what they observed on the work floor. In other words, the teams learn by copying their leaders' behaviors and adapting their behavioral repertoire. The study adds to what we already know about how high-performing teams operate and learn from each other. It offers a more detailed model for how teams can get even better which can inspire future research. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download Phase 3: Combining observational data and physiology Next, based on a study performed by Hoogeboom et al. (2021), we used both The Observer XT software as well as the Empatica E4 measurement system to understand how leaders' physiological arousals are related to their behaviors and how they lead. We collected data from 36 leaders in an organization during staff meetings, looking at both their physical responses and how they behaved by coding with the same codebook of 19 mutually exclusive behaviors. This unique study found that highly effective leaders had higher arousal levels when engaging in both positive and negative relations-oriented behaviors during meetings, such as, respectively, providing positive feedback or showing disinterest. Interestingly, these arousal effects were not visible when leaders adopted task-oriented behaviors, such as information sharing. This suggests that effective leaders show distinct physical responses when dealing with people, which is important to consider when studying leadership. As there currently is increasing interest in biological theories of leadership including the influence of leaders' physiological responses (Nofal et al., 2018), this cutting-edge study paved the way for far more accurate and insightful leadership studies than the more common perceptual ones. The body never lies. Phase 4: Measuring team dynamics Following up on our team's previous work, in the current fourth phase, we are using 360-degree video cameras, The Observer XT software as well as the BIOPAC measurement system to accurately observe agile team effectiveness and team members' arousal over the course of several meetings. The advanced research equipment was co-financed by the BMS Lab, the social science innovation lab at the University of Twente (https://www.utwente.nl/en/bmslab/). The advantage of switching from Empatica E4 to the more sophisticated BIOPAC system offered by Noldus was the possibility of promptly syncing the video observations with the arousal data, easing the data analysis. During the COVID-19 pandemic, with an extension of BIOPAC, we also pioneered the remote tracking of team members' arousal during virtual meetings. In this research, we investigate a multitude of factors related to team effectiveness and use the Noldus equipment and software to find new ways of measuring team dynamics over time or concepts that has gained increased attention such as psychological safety (O'Donovan et al., 2020) and emotional intelligence (Van Dun & Kumar, 2023). In the joint webinar 'How to integrate psychophysiological and behavioral data using both Noldus and BIOPAC tools' we dive deeper into the benefits of integrating data seamlessly. Curious? Watch the webinar on demand now! Observing effective leadership and teamwork using advanced technology In conclusion, our journey through several research studies utilizing the powerful combination of high-tech equipment and software offered by Noldus has shed, and will continue shedding, valuable light on the intriguing but fascinating behaviors of (team) leaders and team members. These high-resolution methods allowed us to delve deeper into the behavioral dynamics within teams, providing insights that would be challenging to attain with traditional research approaches. Our exploration into leadership and team behavior, including the coactive vicarious learning-by-doing phenomenon, has shown the potential of the combination of video and physiological recordings to uncover previously hidden aspects of human interactions in professional settings. By observing and measuring behavior with such precision, we've contributed to a richer and more actionable understanding of effective leadership and teamwork. The ability to capture the co-occurrence of within-person variability in leaders' bodily responses and their precisely measured behaviors over time in functional social settings has been a significant milestone. Our findings have extended existing theories and opened doors for further explorations in understanding the intricate web of behaviors that shape high-performing teams. As we look to the future, The Observer XT software and BIOPAC measurement system continue to offer a promising path for those seeking to gain a novel and more profound understanding of leadership, teamwork, and the human dynamics at play within organizations. These tools serve as beacons, guiding us to uncover the behavioral patterns that make teams thrive and leaders excel in their roles. Next steps will be to explore how algorithms might be used to optimize the behavioral coding procedure, enabling even faster data analysis and participant feedback procedures. In the ever-evolving landscape of organizational-behavior research, we are excited to embark on the next phase of our journey, armed with these innovative technologies, as we continue to unravel the complex tapestry of leadership and teamwork. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download References - Hoogeboom, M., Saeed, A., Noordzij, M. L., & Wilderom, C. P. M. (2021). Physiological arousal variability accompanying relations-oriented behaviors of effective leaders: triangulating skin conductance, video-based behavior coding and perceived effectiveness. The Leadership Quarterly, 32(6), 101493. https://doi.org/10.1016/j.leaqua.2020.101493 - Hoogeboom, M., & Wilderom, C. P. (2019). Advancing the transformational–transactional model of effective leadership: integrating two classic leadership models with a video‐based method. Journal of Leadership Studies, 13(2), 23–46. https://doi.org/10.1002/jls.21655 - Nofal, A. M., Nicolaou, N., Symeonidou, N., & Shane, S. (2018). Biology and management: a review, critique, and research agenda. Journal of Management, 44(1), 7-31. https://doi.org/10.1177/0149206317720723 - O'Donovan, R., Van Dun, D. H., & McAuliffe, É. (2020). Measuring psychological safety in healthcare teams: developing an observational measure to complement survey methods. BMC Medical Research Methodology, 20(1). https://doi.org/10.1186/s12874-020-01066-z - Van Dun, D. H., Hicks, J., & Wilderom, C. P. M. (2017). Values and behaviors of effective lean managers: mixed-methods exploratory research. European Management Journal, 35(2), 174–186. https://doi.org/10.1016/j.emj.2016.05.001 - Van Dun, D. H., & Kumar, M. (2023). Social enablers of Industry 4.0 technology adoption: transformational leadership and emotional intelligence. International Journal of Operations & Production Management, 43(13), 152-182. https://doi.org/10.1108/IJOPM-06-2022-0370 - Van Dun, D. H., & Wilderom, C. P. M. (2021). Improving high lean team performance through aligned behaviour-value patterns and coactive vicarious learning-by-doing. International Journal of Operations & Production Management, 41(13), 65–99. https://doi.org/10.1108/ijopm-11-2020-0809 --- ## How to study social behavior and dyadic interactions URL: https://noldus.com/blog/round-robin-dyadic-interactions Published: 2023-11-30 09:00:00 Description: Social behavior is often studied by psychology researchers using the Round Robin design, especially in dyads. It ensures that all participants in a group interact with each other. When studying social behavior and dyadic interactions in psychology research, the Round Robin design is the way to go. This methodology ensures that all participants in a group interact with each other. The Round Robin design helps researchers study the complexities of interpersonal relationships. What is a Round Robin design? A Round Robin design is a systematic approach used both in research and in competitions. In short, it means that each participant is given the opportunity to interact or compete with every other participant, one at a time. In the context of psychological research, particularly in studies involving dyadic interactions, this design ensures that every possible pair of participants engages in an interaction. As a result, you have comprehensive and balanced overview of the interactions within the entire group. What are dyadic interactions? Dyadic interactions refer to the social exchange between two individuals, encompassing both verbal and non-verbal communication. Understanding dyadic interactions involves exploring how each individual perceives, responds to, and influences the other. These interactions help us understand social behavior, such as friendships, romantic relationships, parent-child-interactions, and professional interactions. Why you need the Round Robin design to study social behavior When studying dyadic interactions, the Round Robin design is invaluable. It helps researchers understand patterns of social behavior or the relationships between behavioral strategies and social outcomes. By collecting data in groups, rather than from single dyads, their data set is more reliable. For example, social behavior that occurs within the context of a single dyad is more prone to "noise", like having something in common or feeling ready to engage with the other. The Round Robin design provides a more complete view of the social dynamics within the group. Implementing the Round Robin design: an example from Dr. Erin Heerey's research Dr. Erin Heerey, Associate Professor at the department of Psychology of University of Western Ontario, used the Round Robin design to explore the subjective value of smiles and how they alter social behavior. Her research revealed that the valuation of polite smiles and subsequent social interactions were influenced by changes in social need. Discover more about Dr. Erin Heerey's work in this video. Studying social behavior with FaceReader In the context of dyadic interaction research, especially studies similar to Dr. Erin Heerey's, FaceReader adds more depth and objectivity to the findings. FaceReader, with its ability to accurately classify emotions and facial expressions, helps to analyze the moment-by-moment facial expressions of participants during their interactions. This helps researchers gain additional insights into the interpersonal dynamics and emotional exchanges within the group. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download The power of FaceReader: 800 hours of coding in 14 hours Also, FaceReader classies expressions in a fraction of the time that human coders need to perform the same work. Imagine a small pilot study in which five groups of five participants each, a mere 25 participants, have a series of two 10-minute discussions in a round robin design. The resulting data would include 800 minutes of video to be coded. Human coders would need about 800 hours to produce frame-by-frame expression classifications, whereas FaceReader would require only about 14 hours to produce the same output. Given the volume of data that Round Robin social interaction studies generate, FaceReader makes the investigation of Round Robin data possible. Helping researchers understand social behavior The Round Robin design ensures a comprehensive and robust dataset when studying social behavior and dyadic interactions. This helps researchers gain better insights in the complexities of human interactions and interpersonal perceptions. FAQs: Social behavior and facial expression analysis 1. Why study social behavior? Researchers study social behavior, emotions, and group dynamics to understand how we connect with others. Their findings help improve mental health support, workplace interactions, and social skills. 2. How does facial expression analysis help in social behavior research? Facial expressions reveal emotions we don't always put into words. By analyzing these expressions, researchers can track mood shifts and emotional intensity. This helps in research areas like psychology, marketing, and AI-human interaction. 3. What types of research questions can a Round Robin design help answer? This method is great for studying interpersonal interactions in psychology studies. Researchers use it to explore questions like: Do people behave differently with different individuals? Are certain social traits, like dominance or trust, consistent across different relationships? 4. What are the challenges of using a Round Robin design? One challenge is managing the logistics—ensuring that every participant interacts with every other participant takes time and careful planning. Data analysis can also be complicated due to the interconnected nature of the results. Specifically, researchers need the right statistical tools to separate individual effects from interaction effects. 5. Can facial expression analysis be combined with other research methods? Yes! Researchers often pair it with eye-tracking, physiological measurements, or behavioral coding. Combining these methods helps gain better insights in human behavior. 6. What ethical concerns come with facial expression analysis? Privacy and bias are the most common concerns in facial expression analysis. That's why researchers need to get informed consent from their participants before collecting data. They should also store facial data securely to protect participant privacy. Misinterpretation is another risk, since cultural differences affect how emotions are expressed. --- ## Neuroscience conferences you should visit in 2024 URL: https://noldus.com/blog/neuroscience-conferences-2024 Published: 2023-11-24 14:00:00 Description: Conferences are a great way to connect and learn. Here you can find a list of our favorite neuroscience conferences taking place in 2024. This is an old list. For our overview of 2025 click here. Last week we went to our largest animal conference, SFN. And with SFN finished we start looking forward towards the new year. Conferences are always a great way to learn and connect with the forefront of behavioral neuroscience. In this blog we have made a list of our favorite animal neuroscience & behavior conferences held this year. We hope to be able to see you at one or more of these meetings. International Neuroscience Conference (INC) | January 25-26 The first conference we will visit after the new year is INC, in Pécs, Hungary. This meeting is held from the 25th till the 26th of January 2024. As a sponsor of this event we are happy to support this conference. Join us in Hungary for two days filled with interesting symposia, plenary sessions, and poster presentations. mitt2024.mitt.hu/invitation 4th Italian Zebrafish Meeting (IZM) | February 7-9 We are proud to announce that we are sponsoring this year's Italian zebrafish meeting. From the 7th till the 9th of February, the University of Palermo and the Fondazione Guido Bernardini are organizing this 4th IZM. This meeting focuses on recent advancement in the field of zebrafish research. Do you want to know how Noldus could help you in making your zebrafish research easier? Then, check out our product pages for EthoVision XT or DanioVision or watch this Customer story. itazebrafishmeeting.wixsite.com/izm2024 Measuring Behavior 2024 | May 15-17 The 13th International Conference on Methods and Techniques in Behavioral Research is the premier interdisciplinary event for scientist and practitioners concerned with the study of human and animal behavior. This unique community and its biannual conference focus on methods, techniques and tools in behavioral research in the widest sense. This year Measuring Behavior is held in the beautiful city of Aberdeen, Scotland. As the main sponsor of this event, you have the ability to see our full range of animal and human products. But that is not all, you can expect over 40 different topics, from the ethical aspects of behavioral research to AI and machine learning in research. Come visit us in Aberdeen from the 15th till the 17th of May. See you there! measuringbehavior.org FREE E-BOOK Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download Canadian Neuroscience 2024 | May 19-22 From May 19th till 22th the Canadian Neuroscience meeting is held in the stunning city of Vancouver. At this conference you can learn about cutting-edge research and network with the top of neuroscience from Canada and abroad. 4 full days of interesting topics ranging from the effect of psychedelics to the role of social context in mouse research. We will also come to Vancouver to present our solutions for behavioral neuroscience. Can we expect you to be there as well? can-acn.org/meeting-2024 Dutch Neuroscience Meeting (DN) | June 13-14 On Thursday the 13th and Friday the 14th of June this edition of the Dutch Neuroscience Meeting is held in the Van der Valk Hotel in Tiel, The Netherlands. Just like other years, DN is a great place for not only Dutch, but also international neuroscientist to connect and share insights. Get inspired by exciting ideas and data, by attending parallel sessions and plenary talk led by neuroscientists from all over Europe and beyond. DN actively promotes veteran and new researchers from various backgrounds to discuss and engage in scientific debate. So consider visiting the Dutch Neuroscience meeting! dnm24.azuleon.org FENS 2024 | June 25-29 Save the Date: The Federation of European Neuroscience Societies (FENS), Austrian Neuroscience Association (ANA), Hungarian Neuroscience society (MITT) are organizing FENS Forum 2024 in Vienna, Austria. From the 25th till the 29th of June 2024 you can partake in Europe's largest neuroscience congress. You can expect topics like brain disorders, cognition, gait analysis and much more. You can engage in these topics during technical workshops, symposia, lectures, etc. There are also many opportunities to develop your career with networking opportunities and other events. During the conference you can find us at booth #708. We hope to see you there. fensforum.org BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Download SFN 2024 | October 5-9 Society for Neuroscience 2023 is just behind us, but we are already looking forward to next year. In 2024 SFN will be held in Chicago from the 5th till the 9th of October. As the premier neuroscience event, it is always a great opportunity to meet colleagues from all over the world. Themes and topics include everything neuroscience, from development, neurodegenerative disorders, motor and sensory systems, integrative physiology and behavior, to cognition, history, ethics, and education. Obviously, we will also go to SFN again in 2024. So, make sure to check out our booth to see our latest innovations and discuss your research with us. sfn.org/meetings/neuroscience-2024 --- ## How students can learn through hands-on experience URL: https://noldus.com/blog/observing-students-behavior Published: 2023-11-21 10:59:00 Description: In the field of engineering, practical experience is highly important. Students need to work with state-of-the-art equipment. However, often resources are limited. Might Virtual Reality (VR) provide a solution? Engineers are professionals who invent, design, analyze, build, and test new products. These may be machines, complex systems, innovative gadgets, or even new materials. Engineers make sure these new products work well and are safe to use. In short, engineers apply new discoveries to the real world. They are at the forefront of innovation, developing new and improved solutions to the challenges people face. Simple examples in everyday life are the bridges we ride on, the refrigerators we store our foods in, the elevators that bring us to the highest floor, or the new toys our kids play with. In the field of engineering, practical experience is highly important. Students in the engineering field need to work with state-of-the-art equipment, such as collaborative robots (CoBots). Characteristic of CoBots is that they work together with people (instead of independently). Besides, they are more affordable, smaller, and can easily be deployed in various processes. However, resources are often limited at educational institutions. Therefore, Virtual Reality (VR) might provide a solution. Studying learning successes and cognitive load Virtual reality is an immersive technology that can create a virtual learning environment for engineering education and training. Advantages of these learning environments are, for example, that they are: - more scalable - independent from physical assets - location independent - able to cover different learning scenarios To study the learning successes and cognitive load of novice engineering students who use virtual learning environments, the research team of Professor Gräßler of the Heinz Nixdorf Institut, Universität Paderborn, formulated the following research question: Is a virtual environment suitable to compensate a conventional learning environment in terms of achieved learning success, assuming the same self-educated teaching methods? Observing students' behaviors The research team set up a collaborative and immersive game-based virtual learning environment, including an integrated VR tool that allowed students to become familiar with the movements and basic functions of CoBots. To be able to validate the research question, the virtual learning environment was compared with a traditional learning environment concerning subjective and objective learning gains. Both environments were equipped with observation cameras to be able to capture the behaviors of the students. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo How do students learn, think, and act? The students who participated in the study had to perform a training task: the programming of the CoBots for a pick-and-place task. The robot picks up a given object at position A, guides it over an obstacle, and deposits it at position B. To do this, the following six steps must be completed: - Establishing a connection between the robot and computer - Execution of the script for the pick and place - Programming the gripping point (starting point) - Programming suitable points on the movement curve - Programming the end point where the object is released - Automated execution of the pick and place process Students' knowledge levels were assessed before and after the training task. The researchers compared a conventional learning setup in the automation lab with a virtual one. They divided the students into two groups: one used the regular lab with a physical manual to instruct the students about the task, and the other used VR glasses in a new interactive virtual learning environment. Also read: How to choose the best audiovisual lab for your project. Directly after the execution, a subjective and objective learning level test was carried out. The research team played back the recorded observations using the AV recording tool Viso and analyzed the data with The Observer XT. Together with the used questionnaires, these software tools helped them to study how the students learn, think, and act while they were being trained. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Learn through hands-on experience The results showed that both test groups had a very high learning gain, more than 90%. They had no knowledge of how to use CoBots before the training and learned a lot during the training. The two groups differed in terms of the time used for training, which was shorter for the students in the VR group; 10 versus 18 minutes on average. This means that productive CoBot time could be saved by using the virtual learning environment, without negative effects on learning outcomes. The researchers conclude cautiously that VR can help students learn through hands-on experience and fill the gap when universities have limited resources. In future research, it would be beneficial to explore virtual learning environments for specific university courses. Additionally, exploring how virtual learning environments can be used in different learning situations, like operating machines for creating and developing future products, seems promising. Reference Gräßler, I.; Hieb, M.; Roesmann, D.; Unverzagt, M. & Pottebaum, J. (2023). Virtual learning environment for teaching the handling of collaborative robots. 13th Conference on Learning Factories. http://dx.doi.org/10.2139/ssrn.4471596 --- ## Facial mimicry and social cognition in children with autism spectrum disorder URL: https://noldus.com/blog/facial-mimicry-autism-spectrum-disorders Published: 2023-11-14 11:00:00 Description: When we want to understand each other better, we tend to copy one another's facial expressions. How does this work in children with autism spectrum disorder? In this blog post, you’ll learn more about facial mimicry in ASD. When we want to understand each other during social interactions, we tend to copy one another's facial expressions. This facial mimicry not only helps along the conversation but is also associated with better emotional understanding and empathy1. So, what happens when facial mimicry is impaired? In this blog post, we discuss the work of researchers Liu, Wang, and Song as they study the underlying processes of facial mimicry in children with autism spectrum disorder (ASD)2. Facial mimicry in ASD When studying facial mimicry in people with autism spectrum disorder (ASD), researchers have found mixed results. Many developmental psychology studies show deficits in facial mimicry, while other researchers find that this skill is intact in people with ASD. It is also unclear whether problems with facial mimicry are core deficits in ASD and what their relationship is with social cognition. To shed more light on this subject, Liu's team examined the underlying processes of facial mimicry in this group. This includes Theory of Mind (ToM) and executive functioning (EF), both important functions in understanding social cognition. Moreover, they distinguished between two types of facial mimicry: automatic and voluntary. Want to read more about research on autism spectrum disorders? Check out this free white paper. Different aspects of facial mimicry Automatic facial mimicry is fast, spontaneous, and unconscious. It just happens, you don't have to think about. On the other hand, you have voluntary facial mimicry. This is when you consciously focus your attention on copying another's facial expression. It's slower and more effortful. So, what if people with ASD don't have an overall deficit in facial mimicry, but only for specific types? Based on earlier research on this subject3, the research team hypothesized that people with autism spectrum disorders may only have an impairment in automatic facial mimicry, and not the voluntary type. Moreover, facial mimicry in ASD may vary across different emotions4. In other words, individuals with ASD may copy facial expressions in an atypical way, instead of not being able to. How to measure facial mimicry What's the best way to study automatic and voluntary facial mimicry of different emotions? Some studies have employed electromyography (EMG) to examine the activity of a specific facial muscle that's a clear marker for an emotion, such as happiness or anger. However, this type of study has its limitations, as it's too difficult to study entire facial expressions or for researchers to observe muscle activity for themselves. That's why the research team from the current study chose a different approach. Using FaceReader, they gained a classification of six basic emotions, as well as a quantitative measurement of facial action units. With this type of facial expression analysis, they were able to study facial mimicry in entire facial expressions. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Facial mimicry, Theory of Mind, and executive functioning The research team also examined how ToM and EF relate to facial mimicry in ASD. Theory of Mind refers to the ability to understand the mental states of other people, which is essential for social cognition. Executive functioning is a set of higher-order cognitive processes we need to plan our next move or inhibit our behavior. As such, EF is also a necessary skill for controlling imitation behavior. As the researchers from this study point out, it is worth investigating whether ToM or EF mediates the mechanisms of facial mimicry in children with autism spectrum disorders. Facial expression analysis with FaceReader The team included 21 children with ASD in their study, as well as 22 typically developing children that were matched in age and IQ. To measure facial mimicry, all participants watched images of facial expressions for 6 basic emotions (happiness, sadness, fear, surprise, anger, and disgust). At first, the children were simply told that they would watch facial expressions. This way, the researchers could observe automatic facial mimicry. Next, they asked participants to watch and simultaneously copy the facial expressions they saw on the screen, as a measure of voluntary facial mimicry. During this task, children's facial expressions were recorded using FaceReader. The team used these recordings to measure how accurately they copied facial expressions and with which intensity. MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now Lower intensity of facial mimicry In both groups, children's facial mimicry was more accurate in the voluntary condition compared to the automatic copying of facial expressions. Interestingly, there were no differences in accuracy between the groups. However, the research team found that children with ASD show lower facial mimicry intensity than their typically developing peers, for emotions happiness, sadness, and fear. Moreover, they found that both automatic and voluntary facial mimicry were correlated with Theory of Mind (ToM), and not executive functioning (EF). As reduced facial mimicry is also associated with greater social dysfunction5, these results support the idea that ToM mediates the relationship between ASD symptoms and intensity of facial mimicry. Facial mimicry as a potential marker for autism So, what does this mean for helping children with ASD? As the researchers suggest, atypical facial mimicry may be an additional marker to help refine the diagnosis of autism spectrum disorder. In other words, studying how children copy facial expressions may help to figure out more about their symptom severity, particularly regarding social dysfunction. To use this information more reliably in clinical settings, the research team suggests that future research should focus on bigger and more varied samples of participants, as well as more dynamic facial expressions. This way, we'd get a better look at how children with ASD perform on facial mimicry in everyday life. References - Holland, A.; O'Connell, G.; Dziobek, I. (2021). Facial mimicry, empathy, and emotion recognition: A meta-analysis of correlations. Cognition and Emotion, 35(1), 150-168. https://doi.org/10.1080/02699931.2020.1815655 - Liu, S.; Wang, Y., Song, Y. (2023). Atypical facial mimicry for basic emotions in children with autism spectrum disorder. Autism Research, 16, 1375-1388. - McIntosh, D.; Reichmann-Decker, A.; Winkielman, P.; Wilbarger, J. (2006). When the social mirror breaks: Deficits in automatic, but not voluntary, mimicry of emotional facial expressions in autism. Developmental Science, 9(3), 295-302. https://doi.org/10.1111/j.1467-7687.2006.00492.x - Oberman, L.; Winkielman, P.; Ramachandran, V. (2009). Slow echo: Facial EMG evidence for the delay of spontaneous, but not voluntary, emotional mimicry in children with autism spectrum disorders. Developmental Science, 12(4), 510-520. https://doi.org/10.1111/j.1467-7687.2008.00796.x - Deschamps, P.; Coppes, L.; Kenemans, J.; Schutter, D.; Matthys, W. (2015). Electromyographic responses to emotional facial expressions in 6-7 year olds with autism spectrum disorders. Journal of Autism and Development Disorders, 45(2), 354-362. https://doi.org/10.1007/s10803-013-1890-z --- ## What can you expect from Noldus at SfN 2023? URL: https://noldus.com/blog/noldus-at-sfn-2023-washington Published: 2023-11-08 14:00:00 Description: Whether you are or aren't going to Neuroscience 2023, we would love to give you a sneak preview of our latest innovations! Just a few days to go until Neuroscience 2023! Are you ready? We sure are! Maybe you're reading this after the conference, which is great since it also serves as a great resource for what we show in our booth! We will be in booth #1223 Make sure to drop by our booth! We will be present with a number of our behavioral experts and product managers that can tell you everything about our upcoming innovations, but also (most importantly) we can help you in finding the right research solution for you! Every research project is different, but we are here to help and have a ton of resources to smooth out the process for you! Wondering what that green mouse is doing at the top of this blog? Come by our booth to pick one up and take it around D.C. and SfN with the hashtag #SfN23 Get a first impression on some exciting upcoming products PhenoTyper 2: a revolutionary update PhenoTyper 2 brings some long-awaited updates to our revolutionary behavioral home-cage system! This hardware upgrade ensures you get better video quality compared to the old model, but by far the most exciting change is the modular top unit. This top unit can fit modular pieces that can be removed and/or swapped out for other integrated add-ons, making it highly customizable to your needs, while ensuring flexibility for the future. Think of specific light spots or buzzers that produce sounds. With the new top unit, no room lighting is necessary since the PhenoTyper 2 provides its own infrared and white light. The white light comes from an internal light ring that evenly distributes the light on the bottom. This means that experiments do not have to rely on, and shadows are not influenced by, external light sources in the experiment room. With this you can easily simulate day and night cycles during your study. We will be showcasing the PhenoTyper 2 in our booth at SfN! The Smart Annotator: our new AI-based smart annotation tool We are constantly looking for smart and effective ways to reliably increase your data acquisition capabilities. In this case it's all about measuring additional behaviors in rodents, think of rearing, grooming, sniffing, etc. The Smart Annotator automatically detects behavior in mice and rats, and you can choose a suggested behavior from the trained AI model. Sneak peek only at SfN 2023! The Multi Subject Tracker: Accurately video track multiple subjects simultaneously EthoVision XT has become the golden standard in video tracking. EthoVision XT 16 brought us deep learning tracking, EthoVision XT 17 expanded this to multiple arenas. Now we bring you: deep learning (AI) tracking in multiple subjects in the same arena! The Multi Subject Tracker (MST) in EthoVision XT will have pre-trained AI models for tracking and analyzing social interactions of mice and/or rats. Want to become a Beta tester? Let us know at: marcom@noldus.com NORTIO: Our new and improved I/O platform with unparalleled data integration possibilities The Noldus USB-IO box is a device that enables EthoVision XT to communicate directly with external equipment, and provides essential and seamless integration with Noldus' PhenoTyper. NORTIO is our latest iteration of this I/O box, and you will be able to get a sneak preview at SfN! NORTIO stands for Noldus Real Time Input Output and is an I/O box that is truly ready for the future. Among other things, NORTIO will eventually feature better scalability, less use of cables, analog signal capabilities, better 3rd party integration, real-time I/O (fixed timing), easy to use robust connectors, and faster THC. These improvements are all aimed at providing a flexible experiment interface. See how it works at SfN! Noldus-Bitbrain-Tobii integration: Improve research insights using multimodal systems We are proud to announce a collaborative integration that brings together the capabilities with Noldus' comprehensive software and analysis system The Observer XT and Bitbrain's state-of-the-art wearable dry-EEG headset Diadem. The combination of The Observer XT and the 12 channel Diadem allows researchers to synchronize behavioral observations with neural data, enabling practical applications such as cognitive load assessment, user experience studies, neuromarketing research, and more. Also, eye tracking systems add substantial power to your (multimodal) lab set-up. They employ various technologies to track and record both the position and movement of a person's eyes, generating extensive data related to attention and emotion. Communication between Tobii Pro Lab and The Observer XT makes use of the Noldus communication protocol N-Linx, which simplifies start and stop of the eye tracking recording and synchronization with the Event Log in The Observer XT. Find out more about these exciting collaborations at: www.noldus.com/data-integration $500! - Abstract contest Winners We've asked you to send in your presentation at Neuroscience 2023 if you have done research with Noldus tools (like EthoVision XT, CatWalk XT, DanioVision or PhenoTyper). Many of you did, and as a result, we have compiled them in a nice program book. You can pick it up at our booth! And of course, we have also picked two winners... Congratulations to Maricela Martinez and Bethany Kondiles! They are both winners of our $500 cash prize Maricela Martinez is a PhD student in the Mahler lab at the Department of Neurobiology & Behavior of the University of California, Irvine. She used EthoVision XT to measure behavior in rats after exposure to THC (a cannabinoid drug) during adolescence, which can lead to long-term changes in brain function and increase susceptibility to opioid addiction. She will present her findings with a poster on November 13th between 8:00 AM - 12:00 PM in WCC halls A-C (PSTR228 session) Dr. Bethany Kondiles is a postdoctoral fellow at the University of British Columbia, and she has used the CatWalk XT to examine the potential of repurposing the drugs metformin and clemastine to improve recovery from spinal cord injury (SCI), particularly by promoting remyelination. She will present the outcomes in a nanosymposium on November 14th between 1:00 PM - 3:30 PM in WCC 140 (NANO64 session). Hope to see you at the Annual Neuroscience Meeting! --- ## Zebrafish Research made easy: a dive into the Gerlai Lab URL: https://noldus.com/blog/gerlai-lab Published: 2023-11-02 12:00:00 Description: Recently, we published a customer story on the Gerlai Zebrafish Lab in Toronto. In this blog we would like to tell you about the things we learned that could not fit into the video. Last May we visited the Gerlai lab at the University of Toronto. We spoke to Robert Gerlai and some of his students about what they do and how they use EthoVision XT to learn about doing behavioral research. However, we couldn't fit everything in our customer story on the lab. Therefore, I have written this blog to tell you more about what we learned at the renowned zebrafish (Danio rerio) lab. Check out the original video! Importance of zebrafish research From brain research to modeling diseases, you can't go without measuring behavior. For the past decades Robert Gerlai has been studying zebrafish behavior at his lab. This is quite unique, since there are not many labs focused solely on zebrafish behavior. The first reason he chose zebrafish for his lab was to advance science in that field. The second reason was mainly for educational purposes. Indeed, in his lab many students are doing hands-on projects with zebrafish. The methods are quite easy to learn, and this facilitates an environment where students can engage with science and even publish papers. From the beginning the Gerlai lab used the Observer XT and EthoVision XT. These programs are ingrained in the scientific process. From pilot studies to sophisticated tracking-based studies, Noldus products help the students understand and interpret the behavior of zebrafish. Stories from the students Stephanie – learning, handling and housing of zebrafish Stephanie is a M.Sc. student at the Gerlai lab. We talked with her about two studies she conducted at the lab using EthoVision XT. The first of these studies is about how housing density and tank sizes influence the levels of anxiety in zebrafish [1]. In order to test this, Stephanie housed the fish in three different tank sizes (1.5, 10 or 50 Liters), at three levels of density (1,2 or 4 fish/L), for two weeks. The behavior of the fish was observed in a novel tank test. Using EthoVision XT, Stephanie looked at a variety of swim parameters in relation to an artificial shoal. The distance to the artificial shoal and the types of swim patterns were an indicator for anxiety like behavior. Anxiety like behaviors in this case were: staying close to the shoal, erratic movements and freezing behavior, among others. Indeed, this study showed that a small tank size and a high fish density had a perceived negative effect on the behavior of zebrafish. Even though the study was a proof of concept, they do advice that more research is done on this subject, to find the optimal way to house zebrafish. The second study we discussed with Stephanie is about how handling affects learning behavior [2]. Handling is a very important component of animal research. This is why Stephanie and her colleagues tested the effect of different handling techniques on zebrafish behavior. She exposed the fish to four different types of handling (net chasing followed by air suspension, gentle net catch followed by air suspension, gentle net catch followed by being placed in a beaker, and transportation in the home tank with a direct pour into the test area). They found that the type of handling affected the swim patterns and many other swim parameters of the fish. Indeed, both netting and chasing induced the most negative behavioral changes in the fish, and thus could possible affect test outcomes. It is important to consider the type of handling when designing behavioral studies. Yashi – novel object recognition in zebrafish Next, we spoke to Yashi. Who, together with a senior student, works on novel object recognition in zebrafish. At the Gerlai lab, undergraduate students are paired with PhD student to increase learning and teaching opportunities. Not only are students taught the ins and outs of science, they also learn how to correctly handle the zebrafish. For her project, Yashi studied novel object remembrance. This type of test hasn't been done much in zebrafish. She mostly looked at what types of objects zebrafish are sensitive to. It is currently unknown what types of objects the fish are sensitive to, and how they react. Therefore, this study was set up at the Gerlai lab. For this, mostly naturalistic objects (like rocks) in different colors were used, since it was more likely that the animals would react to these stimuli. If they are successful in showing how zebrafish react to these objects, the researchers can use that knowledge in further zebrafish cognition and memory studies. Veronica – using ram cichlids as a learning model Lastly, we would like to talk about an interesting innovation in fish learning studies. Veronica recently co-wrote a publication on the use of ram cichlids (Mikrogeiophagus ramirezi) as an animal behavior model. As the oldest vertebrates (evolutionarily speaking), fish are a great species to test the fundamental mechanisms of behavior. Currently, the most used fish model is the zebrafish. However, Veronica and others tested whether or not ram cichlids could also be used. The usage of this species of fish has various advantages over the zebrafish. Zebrafish are naturally a very skittish animal and are easily stressed. The handling performed before behavioral tests, and the stress it causes, often has a major effect on the fish's behavior. Ram cichlids are less anxious, when compared to zebrafish, which causes less disruption of learning (and other) behavior. Furthermore, this species of cichlid is solitary in the wild. Zebrafish are social animals and get anxious when housed alone, which is less apparent in ram cichlids. Lastly, ram cichlids' natural habitat consists of closed spaces and crevices. This habitat more closely resembles the mazes and tanks that are usually used in learning tests, than the open water zebrafish prefer. Aside from biological and environmental advantages, there are also technical advantages of using ram cichlids over zebrafish. They are much larger and move slower when compared to zebrafish. This makes it easier to accurately track the behaviors. Tsang et al. tested the learning capabilities in a plus maze and found that ram cichlids indeed can be used for learning and memory trials [3]. Moreover, EthoVision XT was able to track this type of fish, which increases the potential of using ram cichlids in observational studies. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial 3.1 billion years of shared history To end of our visit to the Gerlai lab we ask ourselves the question: why should we use zebrafish? Robert gave a great quote regarding this query: "Life on earth is 3.5 billion years old. Humans last common ancestor with fish existed 0.4 billion years ago. This means that fish and humans have more than 3.1 billion years of common evolutionary history. That's the answer, that is why zebrafish is translational relevant". And while there are structural differences between zebrafish and humans, there is always a guarantee that there is a connection between the two. Zebrafish are cheaper to breed and house, simpler in structure, and smaller than rodents. This makes it easier and more cost effective to perform many tests, while reducing the number of animals needed. And even though zebrafish will not replace the use of rodents in behavioral studies, comparing both to each other can tell us a lot about the structural responses to certain stimuli. References 1. Shishis, S.; Tsang, B.; Gerlai, R. The Effect of Fish Density and Tank Size on the Behavior of Adult Zebrafish: A Systematic Analysis. Front. Behav. Neurosci. 2022, 16. 2. Shishis, S.; Tsang, B.; Ren, G.J.; Gerlai, R. Effects of Different Handling Methods on the Behavior of Adult Zebrafish. Physiol. Behav. 2023, 262, 114106, doi:10.1016/j.physbeh.2023.114106. 3. Tsang, B.; Venditti, V.; Javier, C.M.; Gerlai, R. The Ram Cichlid (Mikrogeophagus Ramirezi) Learns an Associative Task: A New Fish Species for Memory Research. Sci. Rep. 2023, 13, 13781. --- ## Replacing rodents with insects in behavioral testing URL: https://noldus.com/blog/flies-fst Published: 2023-10-24 13:00:00 Description: In this blog we delve into the use of flies as a new perspective for behavioral testing. How do they compare to rodents? And can conventional rodent tests be adapted to insects? A lot of work is being done on reducing the number of animals used in scientific experiments. In some cases, it is possible to completely replace the use of animals by cell culture or computer models, for instance in some toxicology research. In other cases, more data can be obtained from fewer animals by having more sophisticated experiments and automating the measurements (for example, with Noldus' PhenoTyper and EthoVision XT). However, for some research, such as diseases of the brain and behavior, there is currently no alternative, and it is hard to image that there will be one in the coming years. The brain is an immensely complex organ with not only more electrical connections than we can imagine (something like 1-200 billion neurons with 150 trillion synapses), but also has refined interactions using hormones and neurotransmitters. Behavior is generated when that complex organ interacts with an equally complex body. In this blog we will discuss the replacement of often used rodents and fish with more easily housed flies. Alternatives to rodent models Another approach is to switch away from using mammals like rats and mice to animals which probably experience less pain, such as the larvae of zebrafish or insects. Which can also have advantages when they are used as models of human diseases. Rodents are nocturnal, and their brain is organized around processing sensory data from smell, whereas both fish and insects are, like us, visually centered animals. Key aspects of their brains, like neurotransmitter systems, are very similar, due to their shared evolutionary origins. Insects as a model Behavioral tests modeling human diseases have been carried out for decades with mice and rats. Using insects for that purpose is a relatively new approach. Wendi Neckameye and Andres Nieto investigated using fruit flies (Drosophila) in four behavioral tests commonly used in rodents, which they adapted for use with flies [2]. Drosophila is commonly used as a model animal, and its genetics and behaviors are very well understood. Open field test The open field test is probably the most commonly used test for rodents. A mouse or rat is placed in a walled open area. If they are stressed, then they will normally stay by the walls. How much they explore by moving around is also informative. For the insects, they were simply placed in a petri dish (presumably with the lid on) and their activity was measured and segmented to stopping, walking and hopping, based on EthoVision's measurements of their velocity. Light-Dark box preference test The light-dark box in rodents relies on the fact that mice and rats prefer darkness to light, and will therefore only come out into a light area when they are not anxious or stressed. Flies prefer light to darkness, so the opposite results might be expected. The flies were placed in 5 x 2 x 1.5 cm box, of which half had been painted black. Then the time spent by the flies in a certain zone and amount of crossing were recorded. Alcohol exposure test Exposure to stress can affect an animal's sensitivity to alcohol, for instance, in the time that it takes for the animal to be sedated. That is true for both rodents and flies. In this test the amount of time until sedation by alcohol exposure was correlated with a stress and control group. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Forced Swim Test The Forced Swim Test (or Porsolt test) in rodents is used as an assay for depressive-like behaviors. Rats or mice are placed in a cylinder with tall vertical walls and which is half filled with water. At first, they struggle to escape, but then they give up struggling and float in the water. The idea is that when a 'healthy' rat is placed in the cylinder for a second time, they will struggle to get out again, whereas a 'depressed' rat will exhibit learned helplessness and give up faster. For the flies, they were placed in a small container which contained water with a weak detergent solution (to prevent them from walking on the water surface). The time until they first stopped trying to escape (latency to immobility) and number of immobility periods (bouts) was measured. The use of the Forced Swim Test is often a topic of contention in rodent research, and being able to potentially replace rodents with flies for this test could be a possible solution to this ethical dilemma. Diverse results Remarkably, they found different results to the tests dependent on the flies' gender, age (adults or immature) and what type of stress they had been exposed to. For instance, in the forced swim test, the mature flies struggled to escape for longer than immature flies and males had fewer periods of immobility than females as well as a reduced time until the first period of immobility. Sometimes the effects were opposite, e.g. female flies treated with paraquat (a toxin) moved less than controls, but male flies with that treatment moved more. That means that that the interpretation of the results is far from straightforward. Psilocybin influence on depression Meghan Hibicke and Charles Nichols recently validated the forced swim test for flies [3]. They did this using psilocybin. Psilocybin is a chemical which is extracted from fungi including the 'magic mushroom' or liberty cap, Psilocybe semilanceate. It is a hallucinogen and has been used recreationally for millennia, but more recently it has been discovered to have anti-depressant properties and is prescribed clinically in some countries, e.g. Australia. Image from Wikipedia Commons They gave flies control (zero), low and high doses of psilocybin. When they just looked at activity (locomotion), they saw that males were less active than females, but that psilocybin decreases activity in males and increases activity in females. In the forced swim test, the psilocybin reduced the time to the first immobility and reduced the bouts of immobility (in both males and females). They got the same results for an anti-depressant called citalopram. They also saw that the results differed according to the genotype of the flies and how the drug was administered (pulsed or continuous). Conflicting results in flies The complexity of the results obtained means that it is difficult to interpret them for a new test. If the outcome depends on sex, age and other factors, to what extent does it also depend on the mental state of the animal? The test also seems to follow a different protocol — the authors don't report using two phases, as is normal with rats. In addition, rats are good swimmers and can easily float, unlike flies, so the biological meaning of immobility might be quite different. In a sense, the difficulties of translating a test from rats to flies mirrors the difficulties of translating a test from rodents to people. BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Download Interpreting animal models Bale and colleagues [1] point out that the reason for carrying out studies in animals of human mental diseases is not because it is possible to make an exact model of the human disease in an animal. That is in any case impossible because diseases like depression are very variable, so no one model can capture all the mechanisms. Furthermore, depression is only about 35% heritable, with many hundreds of genes causing that risk, each one only having a small impact, making it impossible to capture in an animal model. The largest risk factor for depression is experience of stress or trauma over the patient's entire lifespan (and even before) and that is also very variable and cannot simply be mapped to an artificial stress imposed on an experimental animal. They wrote, "the idea is not to pretend that we are fully modelling the human illness or even specific dimensions of the illness. Rather, the goal is to achieve a better understanding of an essential biological function that is key to the illness, and to ensure that our level of understanding is actionable for translation". Sometimes that can be done just as well in insects as in rodents. References 1. Tracy L. Bale, Ted Abel, Huda Akil, William A. Carlezon Jr., Bita Moghaddam, Eric J. Nestler , Kerry J. Ressler and Scott M. Thompson. The critical importance of basic animal research for neuropsychiatric disorders. Neuropsychopharmacology (2019) 44:1349–1353; https://doi.org/10.1038/s41386-019-0405-9 2. Wendi S. Neckameyer* and Andres Nieto (2015). Response to stress in Drosophila is mediated by gender, age and stress paradigm. Stress. 2015 ; 18(2): 254–266. doi:10.3109/10253890.2015.1017465. 3. M. Hibicke & C. D. Nichols (2022). Validation of the forced swim test in Drosophila, and its use to demonstrate psilocybin has long lasting antidepressant like effects in flies. Nature Scientific Reports 12:10019. https://doi.org/10.1038/s41598-022-14165-2 --- ## From start to finish: decreasing abandonment when self-designing a product URL: https://noldus.com/blog/self-design-feedback-and-abandonment Published: 2023-10-23 15:57:00 Description: Research shows that we like to design your own products, but often abandon the process before we're done. Does it help to provide feedback, and if so, what type of feedback works best? Many major companies offer their customers the option to design their own products - from personalized gifts to customized jewelry or shoes. In the first blog post of this series on consumer experience and abandonment behavior, you've read about changes in valence during the self-design process. In the second blog post, we zoomed in on the relationship between these experiences and abandonment of a self-designed product. In this final blog post, we'll explore the possibility of influencing whether people finish their design or abandon the process. Does it help to provide feedback, and if so, what type of feedback works best? Read on to learn about the last two studies in the article by Krause and Franke.1 Unobtrusive observations with FaceReader When people design their own product, their experience follows a U shape: they start out motivated, get disappointed along the way, but end up satisfied with their final design - if they choose to persevere, that is. Using FaceReader, researchers Krause and Franke were able to make unobtrusive observations of valence during this process. They also studied abandonment behavior in more detail and found that three different types of valence - regarding design, process enjoyment, and process costs - played a role in whether people abandon or finish their products. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Feedback improves expectations Finally, the research team studied whether the right kind of feedback may help people to finish their designs. They focused on the timing, source, and form of this feedback. Why choose to focus on feedback? Several studies on motivation suggest that positive feedback helps to improve expectations of an outcome.2 In turn, these improved expectations strengthen goal pursuit. Krause and Franke suggest that it might work the same when people are designing their own product. What if you provide people with positive feedback, just before that dip in the U shape? Effects of different types of feedback in consumer research Krause and Franke were interested in two sources of feedback: social and automatic. Social feedback refers to feedback from other users of the customization tool people are working with. One advantage is that people will probably view it as trustworthy, as the company itself is not involved. However, this also means that companies have no control over the feedback and that it may even be negative, which would actually decrease motivation. Automatic feedback, on the other hand, is provided by the company. This way, they can ensure that people receive positive feedback, exactly at the time they need it the most to improve their valence. But will it work? You may also like: - How to measure consumer behavior - 5 tips on how to measure facial expressions - The influence of ad-evoked emotions on brand attitudes Feedback and consumer experience Krause and Franke studied the effects of social and automatic feedback regarding two aspects of the self-design process - whether people liked their design and whether they enjoyed the process. In their study, they asked 556 participants to customize a phone case with a real configurator, offering them the option to buy it afterwards. After three minutes, participants either received feedback on their product design or their mastery of the configurator. This was presented as social feedback from another user or provided as automatic feedback. In reality, both types of feedback were provided by the researchers. Social Automatic Product design "Wow. Great design. Looks really good. I like it a lot." "Aesthetics of your current design: 96 (of 100) points." Configurator mastery "Wow. You obviously master the configurator well - are you an expert?" "Professionalism of configurator handling: 96 (of 100) points." Feedback, valence, and abandonment When analyzing their results, Krause and Franke found that social feedback reduced abandonment, while automatic feedback did not. Specifically, social feedback reduced a critical decline in valence - that dip in the U shape - for both product design and process enjoyment. In turn, this had a positive effect on the self-design process. How to apply feedback to the self-design process To gain even more practical insights into the use of feedback in self-designing, they studied whether different forms of feedback produced different results. In this study, they included feedback on the self-design process in the form of a picture and text, text only, or a points rating. Again, people received either social or automatic feedback. A group of 549 participants received a vignette, describing a situation in which they designed their own phone case with a configurator. In these stories, people were presented with different forms of feedback. After reading them, participants were asked how likely they were to continue the self-design process. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Social feedback is key Interestingly, they found that it did not matter in what form the feedback was presented. Instead, their results showed a clear repetition of what they found before: social feedback works, while automatic feedback does not. In conclusion, these studies show that social feedback during the self-design process can help motivate people to finish their creations. Of course, companies incorporating this type of feedback need to consider carefully how they do so. In this study, automated feedback was constructed to look like real social feedback. It was the best way to study its effects on consumer experience. However, this is not an ethical solution for companies to use. Alternatively, it may work well to establish online communities that are related specifically to the company's configurators, to provide customers with genuine social feedback. The best consumer experience Krause and Franke's research on valence, abandonment, and feedback provides valuable insights to help companies provide their customers with the best experience in self-designing. Curious about other studies in consumer research? Or want to read about other applications of FaceReader? Be sure to check out other posts on our behavioral blog! References 1. Krause, F.; Franke, N. (2023). Understanding Consumer Self-Design Abandonment: A Dynamic Perspective. Journal of Marketing, https://doi.org/10.1177/00222429231183977. 2. Fishbach, A.; Eyal, T.; Finkelstein, S. (2010), How Positive and Negative Feedback Motivate Goal Pursuit. Social and Personality Psychology Compass, 4(8), 517-530. --- ## The value of tracking software: using EthoVision XT to monitor broiler activity URL: https://noldus.com/blog/poultry-behavior-tracking Published: 2023-10-12 14:00:00 Description: What can EthoVision XT provide over manual observations? We explore that question in the context of a animal welfare study, where fly larvae were provisioned to broilers. In the past, we have written about how EthoVision XT is used in rodents, fish and other laboratory animals. Fortunately, EthoVision is not limited to these species. This blog post was co-written by a former classmate of mine, Noa van Leuffen. She recently published a paper about utilizing pixel changes in EthoVision for Mapping Broiler Activity during Dried Black Soldier Fly Larvae (Hermetia illucens) Provisioning. We will look at the results of her study and the value that EthoVision has for monitoring poultry behavior. Using EthoVision to measure broiler behavior Fast-growing broilers in barren housing conditions may experience various welfare problems such as poor leg health and inactivity [1,2]. Securing and understanding proper welfare is essential for providing proper animal care. One approach to better broiler welfare is to increase their expression of natural behavior and general activity, for example by providing dried larvae, such as Black Soldier Fly Larvae (Hermetia illucens, BSFL). In this blog post, we will explore manual and automatic methods to observe poultry behavior, and how black soldier fly larvae could influence this behavior. What is the benefit of using Black soldier fly Larvae? The high weight of fast-growing broilers makes it difficult for the chickens to move, and this decreases their activity. This combined with poor litter quality can increase the occurrence of lesions when the skin has repeated and prolonged contact with the ground. Chickens with lesions to their skin experience severely decreased welfare, and this is something that we as a society tend to think about more and more. So how do we go about fixing this problem? Scattering larvae in the broilers' pen stimulates activity and decreases the time in which they are in contact with the dirty litter material. Therefore, providing these larvae could help alleviate the lesions on the skin. However, it is not well known if providing dried BSFL actually increases the activity of broilers. Therefore, Noa and her fellow scientists set up this study, analyzing the behavior of broilers provided with dried insect larvae. Why use automatic activity assessments? Analyzing behavior on a detailed level can be time-intensive and training is needed in order to obtain proficiency [3,4]. It is therefore of interest to explore novel and time-efficient methods that can measure specific aspects of animal behavior that are often of interest, such as movement. Using EthoVision XT seems to be a promising, time-saving tool to score broiler activity. When analyzing activity in EthoVision, each pixel gets a value ranging from 0 for black to 255 for white. The pixel value changes when a broiler moves. The more movement there is, the more pixel alterations are detected. To compare conventional methods with automatic ones, EthoVision and 30-s manual observations of activity were compared in their ability to display activity [5]. Manual vs Automatic, what are the differences? The percentage of manually recorded activity was moderately correlated with the percentage of pixel changes measured by EthoVision. Both measurements revealed differences in activity between the control group and broilers that received dried larvae, but the exact effects found varied somewhat between the two groups. When using 30-s manual observations, an increase in activity was observed after dried larvae were provisioned on all observation days. Generally, automatic assessment seemed to find a similar effect but activity patterns around feeding BFSL varied between hours of the day, with the lowest activity at the last provisioning moment (17:00h). Manually recorded activity and percent pixel changes per minute, thus, slightly differed in revealing the effects of dried larvae provisioning on the activity of broilers at different hours. It seems that the pixel changes assessment might have missed some activity if manual scoring is regarded as the gold standard. There are, however, several other possible explanations for the different effects found by both methods. Manual scoring might be more accurate for detecting small movements that may not be reflected in the change in many pixels [5], such as ground pecking. Furthermore, the broilers were always filmed from a top view. This meant that vertical movements were less represented than horizontal. Pixel changes reflect movement. However, the manual scoring method solely assessed whether broilers were active or not, and no distinction was made in the degree of activity. In addition, pixel changes were calculated and averaged per pen and over time, whereas manual observations were not. The continuously assessing nature of the software analysis is able to assess frequency and magnitude differences in a way that 30-s scan sampling could not. Moving forward Further validation of the found results with a bigger sample size and in variating settings (e.g., intensive and extensive poultry farming systems) can contribute to a simple and time-efficient method of scoring broiler activity. In conclusion, Noa commented: "Assessing pixel changes should be considered complementary to manual behavioral assessments, as it provides additional information on a more detailed level". References 1. De Jong, I.C.; van Harn, J.; Gunnink, H.; Hindle, V.A.; Lourens, A. Footpad Dermatitis in Dutch Broiler Flocks: Prevalence and Factors of Influence. Poult. Sci. 2012, 91, 1569–1574. 2. Bessei, W. Welfare of Broilers: A Review. Worlds. Poult. Sci. J. 2006, 62, 455–466. 3. Viscardi, A.V.; Hunniford, M.; Lawlis, P.; Leach, M.; Turner, P.V. Development of a Piglet Grimace Scale to Evaluate Piglet Pain Using Facial Expressions Following Castration and Tail Docking: A Pilot Study. Front. Vet. Sci. 2017, 4, 51. 4. Stamp Dawkins, M. Observing Animal Behaviour: Design and Analysis of Quantitative Data; Oxford University Press: Oxford, UK, 2008. 5. Van Leuffen, N.; Ipema, A.F.; Bolhuis J.E. Comparing Pixel Changes and Manual Observations for Mapping Broiler Activity during Dried Black Soldier Fly Larvae (Hermetia illucens) Provisioning. Animals. 2023, 13, 2200. --- ## Why measuring behavior is awesome (+3 examples to prove it) URL: https://noldus.com/blog/why-measuring-behavior-is-awesome Published: 2023-10-03 13:00:00 Description: As ways to behave are numerous and we are a curious species, people have been measuring behavior for centuries now. So, why is measuring behavior awesome? These 3 examples prove it. Behavior is a general and universal thing. To state it simply: behavior is the way a person or animal acts in a particular situation/environment. As ways to behave are numerous and we are a curious species, people have been measuring behavior for centuries now. So, why is measuring behavior awesome? These 3 examples prove it. Why measuring behavior is awesome People have been measuring both animal and human behavior for a long time. Behavior is the actions and mannerisms made by individuals, organisms, systems or artificial entities in conjunction with themselves or their environment. It is the computed response of the system or organism to various stimuli or inputs, whether internal or external, conscious or subconscious, overt or covert, and voluntary or involuntary.[1] Measuring these behaviors can give amazing insights. By gaining insights into our behavior, we can unlock a deeper understanding of ourselves, our habits, and our choices. This self-awareness can lead to personal growth, improved decision-making, and even better mental and physical health. Moreover, on a larger scale, behavior measurement can drive societal changes, from enhancing educational methods to designing more efficient public policies. Let me share some examples that show why it is so interesting to measure our behavior. 1. It can change behavior for the good Remember that movie clip of people taking the escalator instead of the stairs next to it, until they transformed the stairs into one giant piano? It led to an impressive 66% increase in people taking the stairs instead of the escalator that day. They changed their behavior for the better, because they were triggered by something fun, rather than alarming news articles on our declining health. Although this experiment was not scientifically conducted, it does show that the changing human behavior and measuring the results is something everyone can relate to. 2. It can involve anything and anyone Why one person behaves a certain way and someone else can act completely the opposite way has been the subject of studies for ages. It's not just human behavior that is that scientists find worthwhile studying; the study of animal behavior – or ethology - goes back as far as Charles Darwin and American and German ornithologists of the late 19th and early 20th century. The modern discipline of ethology is generally considered to find its roots in the work of Dutch biologist Nikolaas Tinbergen. Without behavioral research we would have never known the Pavlov effect, why wolves howl, or more recently, the "Science of the Resting Bitch Face", where facial expression analysis made it possible to discover why so many people – especially women – seem to suffer from a social phenomenon that labels them as bitchy, solely based on their expression. 3. It can bring people from different disciplines together One way for behavioral research to get its limelight are the numerous conferences dedicated to the measuring of behavior, with Measuring Behavior as the ultimate conference bringing it all together in one meeting. This unique conference focuses on methods, techniques and tools in behavioral research in the widest sense. While most conferences focus on a specific scientific area, this conference tries to create bridges between disciplines by bringing together people who may otherwise be unlikely to meet each other, with measuring behavior as the binding factor. Meeting researchers from other disciplines teaches you to combine different perspectives and establish links as a way of analyzing problems. During the upcoming Measuring Behavior conference in Aberdeen, Scotland (15-17 May 2024), you'll see dozens of examples on measuring a multitude of behaviors. This could be shopper behavior at airports, cows in a stall, drivers in vehicles, and players on the field and online. Measuring Behavior includes discussion on observing all of those behaviors, and more, from both humans and animals. Reference 1. Behavior - Wikipedia PRODUCT OVERVIEW Behavioral research solutions Download our free product overview and find out which Noldus products are suitable for your research. - Divided into research areas - Find the solution for your research - Trust our 30 years of experience Download Read more about measuring behavior: - Examples of Human Behavior Research - How to study human behavior - Cognitive neuroscience: Behavior - Many ways to measure behavior What are the best examples of measuring behavior you encountered? --- ## 8 reasons why EthoVision XT is the superior video tracking software URL: https://noldus.com/blog/ethovision-superior-video-tracking-software Published: 2023-09-28 12:00:00 Description: Discover the unparalleled efficiency and user-friendliness of EthoVision XT, the superior video tracking platform in behavioral research, offering advanced features and worldwide recognition. When you're doing behavioral research, having video tracking software that's both powerful and easy to use isn't just nice to have: it's essential. EthoVision XT stands out as the superior choice, offering a plethora of features and benefits that save time and enhance user experience compared to other software like ANYmaze and DeepLabCut. Here's why EthoVision XT is the preferred choice for researchers around the globe. 1. Time-efficiency and user-friendly interface EthoVision XT is renowned for its fast and easy setup, allowing even inexperienced users quickly to get started. The automatic detection settings and intuitive interface enable users to upload videos in a batch and receive analysis results in a matter of seconds or minutes, as opposed to hours, saving invaluable time compared to other platforms like ANYmaze. 2. Advanced tracking algorithms EthoVision XT employs the most advanced tracking algorithms, including superior detection methods and deep learning technology. This allows researchers to track animals in all conditions imaginable, such as tethered setups or even with obscured sight of the animal. These state-of-the-art tracking algorithms are accessible at the click of a button, eliminating the need for complex coding required by platforms like DeepLabCut. 3. Versatility in animal tracking The software's superior detection methods are not limited to rodents. EthoVision XT has proven to be an essential tool for tracking various species, including fish and insects, making it a versatile choice for diverse research needs. 4. Transparency and control Unlike other behavioral software tools that operate as a 'black box', EthoVision XT offers full insight and control. Researchers know exactly where their data is coming from and can adjust data points as they see fit, ensuring transparency and reliability in the research process. 5. High-throughput and high-content analysis EthoVision XT can track up to a hundred arenas and up to 16 animals per arena simultaneously. It offers a substantial amount of parameters available for analysis, including trial duration, time in zone, distance to zone, distance moved, velocity, and many more, providing comprehensive insights into animal behavior. 6. Cost-effective solution With a low price tag, EthoVision XT offers the best value for money. The base version provides access to all essential tracking methods, and the software is scalable to individual budgets and needs, allowing researchers to customize it according to their specific requirements with a plethora of modules. BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Submit to download 7. Worldwide recognition and validation With 30 years of experience and evolution, EthoVision XT is the most used and validated video tracker in the world, used at almost 4000 sites worldwide and validated in thousands of publications in renowned journals. It is by far the most cited video tracking system, ensuring that work done using EthoVision XT gets published faster and easier. 8. Support and assistance Noldus offers EthoVision XT users help along the way with templates, built-in video tutorials, and a searchable user manual. Additionally, Noldus provides free technical support worldwide, ensuring that users have assistance whenever they need it. Need even more support, access to the upcoming Noldus Academy and free upgrades? Then make sure to check out if NoldusCare is something for you. Conclusion EthoVision XT's advanced features, user-friendly interface, versatility, and worldwide recognition make it the superior video tracking platform in behavioral research. It stands out for its time-efficiency, advanced tracking algorithms accessible at the click of a button, and its transparency and control over the research process, making it a much more user-friendly and reliable choice compared to ANYmaze and DeepLabCut. Whether you are a novice or an experienced researcher, EthoVision XT is designed to meet your needs and ensure you can advance your research. --- ## Design your own product: consumer experience and abandonment behavior URL: https://noldus.com/blog/self-design-abandonment-behavior Published: 2023-09-26 13:05:00 Description: Researchers Krause and Franke studied how our experiences change while designing our own products. How do these experiences influence whether we finish a product or abandon the process? In the first blog post of this series about consumer experience and abandonment behavior during self-designing, we discussed how people's experiences change while designing their own product. This provides valuable information for companies offering customization tools to their customers - for example, to design their own gifts, jewelry, or shoes. Researchers Krause and Franke found that consumers' valence follows a U shape: people start out motivated and positive, followed by a phase of disappointment when their expectations are not met, and ending with satisfaction after persevering with their design. Or, in a lot of cases, resulting in an abandoned design process. In the next part of their research, the team zoomed in on the exact relationship between valence and abandonment behavior. What makes people either leave the process or finish their product? Also read: Why you should use FaceReader Online for your human behavior research. Consumer research on self-designing In their study, Krause and Franke asked 132 students to try out an augmented reality app from a car manufacturer. As a 'preparation excercise', they had to use the computer for at least three minutes, but were allowed to take more time if they wished. During this time, participants were offered the option to use a real wristwatch configurator and even to buy the design they made. Little did they know that this was actually part of the experiment. The researchers wanted participants to feel free to decide for themselves whether they wanted to continue their self-design process, and to feel no time pressure to finish. This allowed the research team to make realistic and unobstrusive observations of their behavior. Observing consumer experiences with FaceReader Interestingly, all participants started using the wristwatch configurator, which confirmed that the product category was attractive to this group. The research team also recorded for how long participants continued the self-design process and whether they completed their designs. During the experiment, they recorded participants' valence with FaceReader. The results of their facial expression analysis showed that when valence goes down (in other words, when people have a negative experience), the risk of an abandonment increases. On average, this risk increases by as much as 75 to 80 percent. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Relationship between valence and abandonment To gain more insights in how valence influences abandonment during self-designing, the team continued their consumer research. In their next study, they examined three types of valence: what people thought of their design solutions, whether they enjoyed the process, and how they experienced the time and mental energy they invested in designing. This time, they asked a group of 587 participants to self-design a pair of sneakers. The first group was only shown a picture of the configurator, while the second group actually got started on the self-designing process. Based on the three types of valence, both groups were asked about their experiences: - "I expect that I will like the product design I will create" or "I like the sneaker design I created so far" - "I expect the process to customize my sneakers to be fun" or "The process to customize my sneakers is fun" - "I expect the process to customize my sneakers to be laborious" or "The process to customize my sneakers is laborious" Lock-in effect for process costs They found that a positive valence regarding design solution and process enjoyment increases the chance that participants continue the self-design process. Even more interestingly, they found the exact opposite effect for perceived process costs. A more negative valence of process costs actually keeps participants in the process of designing their own product. This seems to indicate a lock-in effect, where people view process costs as an investment they don't wish to lose. Want to read more about consumer research? Check out our top 5 blog posts on consumer research. Next steps in consumer research about self-design Taken together, these results show a clear relationship between valence during the self-design process and consumers' abandonment behaviors. They also highlight that the three types of valence - regarding design solution, process enjoyment, and process costs - play a different role in whether people finish their designs or abandon the process. In the next blog post of this series, we'll dive deeper into the effects of different types of feedback on people's abandonment behaviors. Is it possible to decrease abandonment rates? Coming soon! MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now Reference Krause, F.; Franke, N. (2023). Understanding Consumer Self-Design Abandonment: A Dynamic Perspective. Journal of Marketing, https://doi.org/10.1177/00222429231183977. --- ## Let's work together: mother-adolescent interactions in fragile X syndrome URL: https://noldus.com/blog/fragile-x-syndrome-mother-adolescent-interactions Published: 2023-09-19 09:00:00 Description: All parents want their children to comply with their requests - for at least some of the time! What's the best way to request something when you have an adolescent boy with fragile X syndrome? All parents want their children to comply with their requests - for at least some of the time! What's the best way to request something when you have an adolescent boy with fragile X syndrome? Fragile X syndrome is a genetic condition that causes a range of developmental problems, including learning disabilities and cognitive impairment. Researcher Fielding-Gebhardt and her colleagues studied interactions between mothers and their sons with fragile X syndrome.1 Specifically, they wanted to know how mothers' requests and responsivity interacted with adolescent compliance while performing different tasks together. Understanding fragile X syndrome Fragile X syndrome (FXS) is a genetic disorder that affects about one in 4,000 men and one in 6,000 women. People with FXS often experience difficulties with language, social communication, cognition, and daily living skills. Typically, boys have more severe deficits and behavioral problems. Also, about 50-75 percent of boys with fragile X syndrome meet criteria for autism spectrum disorder (ASD).2 Studying the best way to interact with children who have fragile X syndrome helps parents and other caregivers provide the best guidance for their further development. This includes teaching children to comply with their parents' requests. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly How children learn about the world Learning to comply with parental requests is an important aspect of developmental psychology. After all, by following their parents' directions and requests, children learn about how the world works and what part they play in it. Compliance is a stepping stone in learning new skills, helps foster a positive family environment, and is needed to succeed well in school. Within FXS research on this topic, studies have mostly focused on interactions between compliance and mothers' responsivity. Researchers found that children with fragile X syndrome whose mothers are more responsive - showing more attention and warmth - generally show less behavioral problems and better language skills.3 Parental requests and compliance What else plays a role in compliance? There are different ways to request something, and it also matters how often you ask for something. For example, a request may be direct ("Pass me the butter") or more indirect and ambiguous ("My roll needs butter" + reach gesture). These indirect requests may be more difficult to understand and to comply with, although research in this area shows mixed results. In the current study, researcher Fielding-Gebhardt and her team studied the effects of directness and frequency of mothers' requests on their adolescent sons' compliance. Moreover, they examined whether adolescent compliance and mothers' behaviors are the same over different types of tasks. Finally, they examined differences in dyads of adolescents with or without ASD. Read more about parent-child interactions, developmental disorders, and other developmental psychology examples in these blog posts: - The New Jersey Families Study: unlocking the black box - Parenting behaviors and executive function in Down syndrome - Improve the interaction between parent and child with autism Compliance behavior in different settings They included 35 mother-son dyads in their study (average ages 46 and 16 years) and asked them to perform three different tasks together. Their aim was to vary these tasks in how familiar and rewarding they would be for the adolescents. In the first task, mothers and sons completed Castle LogicTM puzzles together. For the second task, they played pre-installed two-player games on an iPad. In the third task, mothers and sons worked together to make a snack, using step-by-step instructions. All mother-son interactions were coded using The Observer XT. Coding behavior in mother-adolescent interactions When observing mothers during mother-adolescent interactions, the researchers coded requests for behavioral compliance ("Give me the milk"), requests for verbal comply ("Say thank you"), recodes ("Yes, the yellow ball"), comments ("I know you like this flavor"), and praise ("Good job"). They also coded whether requests were direct or indirect. Mothers' responsivity was defined as the amount of turns they took while communicating with their sons. For the adolescents, the coders observed whether they were compliant or noncompliant. They also noted when adolescents had no opportunity to comply, for example, when their mothers took over for them or didn't allow sufficient time to comply with their request. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Interactions between requests, task demands, and compliance The research team's most important finding was that adolescent compliance decreased when mothers' requests were more frequent. However, it's not possible to say how this relationship works exactly. Does a higher rate of requests lead to decreased compliance, or do mothers make more requests when they have adolescent sons who are already less compliant? Or is adolescent temperament a more important factor? The team also found that mothers' responsivity was highest during the puzzle task, while request frequency was highest during the snack task. Adolescent compliance did not vary by task. Furthermore, it didn't matter whether mothers requested something directly or indirectly. How can we understand mother-adolescent interactions in fragile X syndrome? Researcher Fielding-Gebhardt and her colleagues suggest that mothers may have adjusted their behavior to what their sons need and how they behaved. In other words, they may be highly attuned to their child's abilities in combination with different task demands. The researchers also note that autism symptoms may play a role in the effects they found. The relationship between adolescent compliance and request frequency was most pronounced in the group of adolescents with both FXS and ASD. Moreover, they found that both autism symptoms and receptive language skills were significantly associated with compliance. Improving fragile X syndrome treatment The findings from this study may not translate easily to clinical practice. As the researchers note, their sample size is small and may not reflect the entire population of children with fragile X syndrome. Also, the tasks involved may be too different from what these adolescents encounter in daily life. However, these findings do help us better understand interactions between mothers' behaviors, task demands, and adolescent compliance in fragile X syndrome. As this field of research grows, parents and other caretakers may learn how to adapt their requesting behaviors or task demands to better fit with their child's development, increasing the chances that they will comply. As a result, this will support children with FXS in their further development. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources References 1. Fielding-Gebhardt, H.; Brady, N.; Bredin-Oja, S.; Warren, S. (2023). Transactional relationships between maternal requesting and responsivity, adolescent compliance, and task demands in fragile X syndrome. Research in Developmental Disabilities, 134, https://doi.org/10.1016/j.ridd.2022.104417. 2. Abbeduto, L.; Thurman, A.; McDuffie, A.; Klusek, J.; Feigles, R.; Brown, T.; Roberts, J. (2019). ASD comorbidity in fragile X syndrome: symptom profile and predictors of symptom severity in adolescent and young adult males. Journal of Autism and Developmental Disorders, 49(3), 960–977. https://doi.org/10.1007/ s10803-018-3796-2 3. Warren, S.; Brady, N.; Fleming, K.; Hahn, L. (2017). The longitudinal effects of parenting on adaptive behavior in children with fragile X syndrome. Journal of Autism and Developmental Disorders, 47(3), 768–784. https://doi.org/10.1007/s10803-016-2999-7 --- ## The effect of environmental levels of lead on zebrafish development URL: https://noldus.com/blog/lead-exposure Published: 2023-09-14 13:00:00 Description: Lead exposure has a negative influence on the developing brain and body. Zebrafish research allows us to understand the effects of lead poisoning on the different stages of life. It is a well-known fact that lead ingestion leads to potentially serious health consequences. This is especially true in infants, since their brain and nervous system are still developing and growing. If they are exposed to even very small amounts of lead, this can cause, among other, memory difficulties, hyperactivity disorder and even deformities. Unfortunately, lead pollution is common in the current industrialized society, which means that exposure of infants and adults alike to toxic concentrations of lead is common as well. Systematic research to lead exposure There is currently a lack of systematic research into this topic, and especially behavioral analyses have not been performed much yet. Because of that, scientists from China and Germany collaborated to study the effect of environmentally relevant concentrations of lead on zebrafish development. Due to the similarities of zebrafish to humans at the genomic level, they are a good species to use as an animal model. Neurobehavior after exposure to environmental levels of lead For this study, zebrafish were exposed to environmentally relevant levels of lead, i.e. 0-2 μM. The exposure took place only during the larval stage, in order to see what kind of lasting effect, if any, it had on adult zebrafish. The larval stage was counted as being from 2 - 120 hpf (hours post-fertilization), after which the fish were raised in normal, lead-free conditions from 5 dpf (days post fertilization) (juvenile) to 4 months old (adult). During the lead-free period of their lives, the researchers tested the zebrafish' neurobehavior using Noldus Ethovision XT. Neurobehavior in juvenile zebrafish The zebrafish were put into 48 well-plates (age 6 dpf) and 6 well-plates (age 1 month), and placed into the observation chamber of the Noldus IT DanioVision Tracking System. They could adjust for 10 minutes after which the researchers started a 5:5 min light-dark cycle. Additionally, every 30 seconds the plates were mechanically tapped. The responses of the fish to these stimuli was recorded by EthoVision XT, and the distance travelled, acceleration and velocity of the fish was registered automatically. The lead-exposed fish behaved more actively and were much more easily startled compared to control zebrafish, pointing to anxiety and hyperactivity disorders. Furthermore, their heart rates, survival and growth were severely affected and they suffered from deformities like spinal curving and hemorrhage. Neurobehavior in adult zebrafish Open field & novel tank diving test Each adult fish (4 months old) was put individually into a square tank in the DanioVision Tracking System, after which they could adapt for 10 minutes. Then, the fish were each recorded for 20 minutes, during which velocity, swimming distance and time spent in each region were analyzed automatically. These analyses showed that healthy zebrafish preferred to swim close to the surface, while lead-exposed fish spent significantly more time at the bottom. This points out that the anxiety they suffered from as juveniles did not disappear. RESOURCES Read more about DanioVision Find out how DanioVision is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Social interaction test After the diving test, a new test tank was attached to another tank containing 6 zebrafish (3m and 3f). The main tank was divided into a social and non-social area. Each zebrafish to be tested was placed in the center of the main tank, and allowed to acclimatize for 10 minutes. Then, they were recorded for 20 minutes, and the swimming duration and distance travelled in each area were calculated using the DanioVision Tracking System. These tests showed a decreased preference for social activities. T-maze test Lastly, the researchers wanted to check the fishes' memory and learning abilities. They used a T-maze, with the fish being placed at the end of the long arm. At the end of one of the short arms was a food reward, and for 6 days the fish were trained to find this reward. For the final test, the fish were placed at the end of the long arm again. The DanioVision Tracking System recorded the time spent before arriving in the target area, and exploration duration in the target area. This test showed a remarkable impairment in learning and memory, both during training and during the final test. Apart from the behavioral tests, the researchers performed both cell apoptosis tests and gene expression analysis in the zebrafish. For more information on these tests, please read the original article. Consequences of lead exposure on zebrafish development This study clearly shows that even the smallest dosage of lead severely affects zebrafish development. The fish had a wide variety of deformities, and suffered from various kinds of mental disorders like anxiety, hyperactivity disorders and a clear impairment in learning and memory. These symptoms did not disappear when the fish matured. These findings, and the animal model from this study, could help develop medicines that can treat, though not cure, the often severe side effects of lead exposure. --- ## Why use video feedback in education? URL: https://noldus.com/blog/why-use-video-feedback-in-education Published: 2023-09-12 09:28:00 Description: By using video and audio recordings in education, students and educators can receive and benefit from direct feedback. The more personal and detailed feedback is, the easier it is for students to relate to. By using video and audio recordings in education, students and educators can receive and benefit from direct feedback. By recording skill training sessions, role-plays, simulations, or presentations, the student's actions and behaviors can be assessed. During review, interactions can also be observed. The more personal and detailed feedback is, the easier it is for students to relate to. This fosters motivation within students. It helps them to continue excelling and enhancing their skills the next time they engage in these activities. FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly Empowering student learning: what are the benefits for students? Students are used to receiving information by watching short video clips. On a daily basis, students find themselves browsing multiple platforms for information (and for fun, of course), such as YouTube, Instagram, TikTok, and Snapchat. But what advantages are there for students to see and assess their own behavior in a learning situation? - Personal | Video-based feedback truly makes a student's learning journey unique. It is all about the students themselves, they are in the spotlight. They get to watch themselves in action, to understand how they behave and react. The feedback they receive is finely tuned to align with their specific behaviors, increasing their levels of engagement. - Awareness of non-verbal cues | Watching themselves on video helps students become more conscious of their non-verbal cues, like body language, facial expressions, and tone of voice. These are crucial aspects of effective soft skills. - Goal oriented | Preset personal goals can be coded and marked by the teacher (or fellow student) while recording the video, making it quick and easy to discuss them during the review session. - Objective | Video feedback helps students to objectively understand their strengths and weaknesses. What went well and what could be improved? Because it is recorded, they cannot ignore the facts. But also, they can track progress by comparing their earlier recordings to later ones. - Motivating | Witnessing successful actions or behaviors and their positive outcomes boosts self-assurance, fosters a positive self-view, and drives motivation for continued positive behavior. - Unobtrusive | Using video recordings, rather than an observer present in the same room, makes students feel more comfortable. They can better focus on the skills they practice. Incorporating video recordings into training sessions empowers students to take charge of their learning and development in a dynamic and comprehensive way. Benefits of video feedback for educators Looking at it from the teacher's viewpoint, the feedback process reveals a student's current educational position and aids in recognizing and preparing for upcoming learning opportunities. Effective feedback goes beyond general praise or criticism and is specific, actionable, and focused on facilitating growth and development. Reasons for employing video feedback are myriad, but most of all it makes the teacher’s job much easier. - Saves time | Using a AV system, such as Viso, it is possible to record in multiple rooms at the same time, allowing sessions to take place in parallel. Video processing is quick and easy, videos can be played back right after recording, and no time to load is needed. - Easier to take exams | The ability to record sessions works well for administering tests. Students can start and stop recording themselves, a teacher does not have to be present. The teacher immediately has access to the recordings. - Innovative | This active form of learning will improve the quality of skills education. Students learn more from the lessons and training sessions because the feedback was personal and goal-oriented. - Up-to-date | Nowadays, students grow up with video. Learning and improving skills by watching videos is second nature. Video is the future, thus to keep up, teachers are being challenged to refine their pedagogical methods. This innovative approach enhances skill education through personalized and goal-oriented feedback, using the familiarity of video learning for modern students. Also view: 10 reasons why AV tool Viso is beneficial for video feedback [INFOGRAPHIC] Video technology for feedback If you are looking to implement video feedback throughout your facility for simulation and training sessions for your students, as well as feedback sessions for your staff, a complete package with video and audio technology is the best solution. Implementing a complete solution might sound extensive, but it can be done by setting up four IP cameras in multiple rooms. If you don’t want to equip a number of rooms, you can choose a portable solution, which includes a suitcase with a microphone, cameras, and a laptop. It is no longer necessary to control cameras and recordings from the experiment room or from an adjacent room. Using specially-developed software, the video recordings are stored safely and securely and can only be accessed by the right person. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download Debriefing the recorded sessions After being recorded, the videos are immediately available for debriefing. Debriefing shows why things happened and provides input for future learning. By engaging in debriefing sessions for soft-skill training sessions, role-play scenarios, simulation-based training, or any experiential learning, you will uncover the fundamental factors contributing to both successes and setbacks. These insights will guide you in determining which aspects to replicate and which to modify for future improvement. Whether the video feedback is used to train psychology students in interview techniques or to provide the English faculty team with examples of working teaching methods, you will notice that procedures have changed for the better. By using the latest video and audio management and control technology, you will see that it doesn’t require a major investment to achieve a maximal return. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo References - How teachers video feedback can improve student performance - Mahoney, P.; Macfarlane, S. & Ajjawi, R. (2018). A qualitative synthesis of video feedback in higher education. Teaching in Higher Education, 24 (2). https://doi.org/10.1080/13562517.2018.1471457 - Kam, B.; Yune, S.; Lee, S.; Im, S. & Baek, S. (2019). Impact of video feedback system on medical students’ perception of their clinical performance assessment. BMC Medical Education, 19 (252). https://doi.org/10.1186/s12909-019-1688-6 --- ## Using augmented toys to facilitate play in children with visual impairments URL: https://noldus.com/blog/augmented-toys-children-visual-impairments Published: 2023-09-06 14:28:00 Description: How can we help children with visual impairments in their development of play and social interactions? Drs. Suzanne Verver and her team examined the effects of sound-augmented toys on peer play. One of the main objectives of developmental psychology is to increase our knowledge on child development, so that we may help children who face developmental difficulties or delays. Researcher Verver and her colleagues focused on the development of social interactions in children with visual impairments. How can we help these children in their development of peer play? This blog post explores a study on sound-augmented toys in dyads of visually impaired children. Social and cognitive development Children with visual impairments face many challenges when growing up, including the development of social and cognitive playing behavior. With fewer opportunities to learn from observation and imitation, these children may experience difficulties in joint attention, understanding non-verbal behavior, and cooperative play. By playing alone more often, their development of complex playing forms, such as symbolic or pretend play, can be delayed up to two years compared to sighted children. This limits their opportunities to practice social communication, which is necessary to form and maintain friendships. Stimulating certain playing behaviors may help visually impaired children to develop these skills more easily. Can parents help? Parents or other adults can help create positive social experiences by assisting children with peer play. However, this support can also lead to passive behaviors, as well as feelings of dependency and helplessness. Furthermore, research with visually impaired adolescents shows that peer support is a better predictor for their wellbeing than parental support. These results suggest the need for positive peer play experiences without adult help. Interaction between children and their parents is a classical study object in developmental psychology, pediatrics, and child psychiatry. Download this white paper to discover how The Observer XT can help you with your study of parent-child interactions. Augmented toys That is where augmented toys come into play. By combining play materials with technology, augmented toys can offer new play experiences and stimulate development in different ways. And for children with visual impairments, adding sound may be just the thing. Drs. Suzanne Verver and her colleagues, from the Radboud University in the Netherlands, studied the effects of a Playmobil® castle that was enhanced with radio-frequency identification (RFID) tags. When children put play figures on specific locations in the castle, these figures produced pre-programmed sounds. The researchers were interested to know whether playing with augmented toys would influence social and cognitive play behaviors in children with a visual impairment. They hypothesized that the auditory cues would facilitate shared experiences, joint attention, and symbolic play. Observing playing behaviors The study included 52 children between 4 and 12 years of age, who were paired into 26 dyads. Researchers randomly assigned children to these dyads, based on age group and location. The participants varied in their visual impairments, ranging between moderate impairments, severe impairments, and blindness. Each dyad completed six 30-minute play sessions over a period of three weeks. Each week, children played once with the augmented toy and once with a regular version of the same toy. The dyads were randomly assigned to start with either version. Coding behavior during peer play Play sessions were recorded and a selection of video fragments was coded using The Observer XT. The researchers observed both social and cognitive play behaviors. Social aspects of play included playing alone, playing parallel to another child, and playing together with another child, as well as disengaging from the play situation. Behaviors such as exploration, functional play, and symbolic play were coded as cognitive behaviors. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download More parallel, less cooperative Results showed that children were engaged and played cooperatively for the majority of time. When examining differences in playing with both versions of the toy, results showed that children played parallel to one another more often when playing with the augmented toy. However, with the regular version of the toy, children played together more often. Verver and her colleagues also found that children spent more time in explorative play when playing with the augmented toy. On the other hand, functional and symbolic play occurred more often when playing with the regular toy. Finally, results showed different play behaviors for children with different visual impairments. Children with a severe visual impairment spent more time in explorative play than children with a moderate impairment. Also, children with blindness engaged in less functional pretend play than children with a severe impairment. Should we use sound augmentation? In line with what the researchers expected, children showed parallel play more often when sound augmentation was available. They even continued to do so after three opportunities to play with the toy. This indicates that sounds can capture children's attention, as well as facilitate joint attention and awareness of others. However, results also showed that children did not play together as often when playing with the augmented toy. The researchers argue that this effect may be caused by the sounds' interference with children's storylines and pretend acts, preventing cooperative play. This means that, in the current study, sound augmentation did not facilitate social play. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Future research on peer play These findings provide a meaningful addition to the study of visual impairments in children. Verver and her colleagues also have several suggestions for future research. They argue that increased flexibility, where children can record their own sounds, may prevent interferences in pretend play. This way, playing with an augmented toy may facilitate social play after all. They would also be interested to learn more about interactions between sighted children and children with visual impairments, as you would find more often in regular education. Finally, they emphasize that other characteristics may be more important in understanding social play difficulties. This includes verbal abilities, social skills and the presence of autism spectrum disorder. Reference Verver, S.; Vervloed, M.; Steenbergen, B. (2019). The use of augmented toys to facilitate play in school-aged children with visual impairments. Research in Developmental Disabilities, 85, 70-81. --- ## Diving deeper: Obesity and Anxiety, a scientific perspective URL: https://noldus.com/blog/fish-anxiety-obesity Published: 2023-09-05 12:00:00 Description: It seems that there is a relationship between poor mental health and obesity. But the exact reasoning is far from clear. Animal experiments can shed light on the situation It seems that there is a relationship between poor mental health and obesity. However, the relationship is far from clear. Does obesity damage mental health, perhaps through various hormonal and physiological mechanisms, or does poor mental health sometimes lead to lifestyle changes causing obesity (anxiety can cause an increase in appetite)? Perhaps it is a combination of the two. This proposed relationship between anxiety and obesity makes one think: "Can we expect an even greater increase in obesity as a result of the anxiety caused by the Covid-19 pandemic? And which mental health issues are involved; is it predominantly depression or is it anxiety?" Both are common conditions (clinical anxiety disorder is experienced by almost 30% of people at some time during their life), with a variety of causes, making it hard to figure out what is exactly going on. In this blog we will explore a variety of studies that aim to explain the relation between anxiety and obesity. Rodent experiments to gain insights To tackle problems like this, correlations can sparks ideas, but for a deeper understanding conducting experiments is required. For instance, Xia and colleagues fed a long-term high fat diet to laboratory mice [1]. They then carried out a number of behavioral assays using EthoVision XT. Mice are nocturnal animals, active at night. So it was not so surprising that they found no significant differences between the behavior of the mice with different diets during the day (light). However, when they carried out the same measurements at night (dark conditions) they did find significant effects. Which in itself is interesting because some laboratories carry out behavioral studies on nocturnal animals like mice and rats only in the daytime. Some laboratories reverse the day and night cycle of the lighting, so that the dark phase for the animals coincides with the light phase of the researchers. These significant effects not only indicate that it is likely a good idea to carry out behavioral measurements in the active phase of animals, but also that in this specific case it is likely that the day-night rhythm of the animals had been disrupted (a typical symptom of depression). Testing anxiety in rodents One common test of anxiety is the open field. This is simply an open area (in this case, 50 x 50 cm) where the animals can freely walk for a set amount of time. If an animal is anxious, it will tend to stay by the edge of the cage. Just like when you are in a large unfamiliar public square, you will tend to walk around the edge rather than across the exposed center. That is precisely what the animals on a high fat diet did; they felt more anxious. Another test for anxiety is the elevated plus maze. That is a maze in the shape of a cross, with four arms of 30 x 5 cm (in this case). It is placed high above the floor. Two arms are enclosed in high walls, so the mice feel safe, and the other two are open, with no walls. If the mice are feeling anxious, they will not venture out into the open arms. Mice which had been on a high fat diet spent much less time in the open arms than the mice on a low fat diet (again, only in the night phase). In addition, a number of tests for depression (tail suspension test, forced swim test and the marble burying test) all showed that the mice which had eaten a high fat diet showed strong signs of depression. Swimming towards clues: a Zebrafish approach Medine Türkoğlu and her colleagues investigated the effect of high fat diet in zebrafish [2]. Zebrafish have a number of advantages over mice as model animals. For example, some varieties and the larvae are transparent. That means that it is possible to measure parameters such as heart rate and blood flow rate using DanioScope, which this group did in order to measure the effects of parental obesity on their offspring. Türkoğlu and colleagues measured the behavior of both adult Zebrafish (in an aquarium, using EthoVision) and larvae (using DanioVision). The readouts for the adults have similarities to the tests carried out on mice. For fish, when they are anxious, they tend to move to the bottom of the tank and stay there (just like mice staying at the edge of an open field). Both can be seen as behaviors indicating anxiety related to possible predators. In addition, certain characteristics of their movement like sudden erratic movements and freezing behavior (without a stimulus causing them) also indicate anxiety. Swimming patterns and diet The experiments focused on comparing high fat with (HF) high carbohydrate (HC) diets. Both caused obesity in the fish. That was seen with not only an increase in body mass index (BMI), but also changes in gene expression (that is, which genes became active) related to fat metabolism. Also, the offspring of obese parents had significantly more fat in their bodies than the controls. From this study, the most striking result was that the different diets had a very strong effect on the anxious behavior of the fish. The controls (which had a regular diet) swam all over the tank, more or less equally. The high fat (HF) diet fish showed anxious behavior (anxiogenic), staying at the bottom of the tank, and the high carbohydrate (HC) diet fish showed reduced anxiety (anxiolytic) behavior, staying in the top region of the tank. The differences in behavior were not seen in the next generation, although the offspring of parents on a high carb diet had less anxiety. The researchers also carried out detailed measurements to determine the physiological and metabolic differences causing these behavioral effects. Those details are beyond the scope of this blog, but high fat diets do reduce cognition in zebrafish and oxidative stress (causing damage to the hypothalamus) is also a key factor. However, translation to the human situation is not so straightforward. Zebrafish have some differences in their metabolism compared to humans. For instance, they are able to synthesize long-chain saturated fats from short-chain unsaturated fats. Nevertheless, the results do help us understand the mechanism behind the relationship between obesity and anxiety and also give pointers to the causes of childhood obesity. FREE DEMO Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free Demo References 1. Xia, G.; Han, Y.; Meng, F.; He, Y.; Srisai, D.; Farias, M.; Dang, M.; Palmiter, R.D.; Xu, Y.; Wu, Q. Reciprocal Control of Obesity and Anxiety–Depressive Disorder via a GABA and Serotonin Neural Circuit. Mol. Psychiatry 2021, 26, 2837–2853, https://doi.org/10.1038/s41380-021-01053-w 2. Türkoğlu, M.; Baran, A.; Sulukan, E.; Ghosigharehagaji, A.; Yildirim, S.; Ceyhun, H.A.; Bolat, İ.; Arslan, M.; Ceyhun, S.B. The Potential Effect Mechanism of High-Fat and High-Carbohydrate Diet-Induced Obesity on Anxiety and Offspring of Zebrafish. Eat. Weight Disord. - Stud. Anorex. Bulim. Obes. 2022, 27, 163–177, doi:10.1007/s40519-021-01140-5. Acknowledgements Thanks to Saltuk Buğrahan Ceyhun for giving permission to use the picture of the heatmap. The obese mouse in the header is from Wikipedia. --- ## Calcium imaging and measuring behavior URL: https://noldus.com/blog/calcium-imaging-measuring-behavior-benefits Published: 2023-08-29 16:00:00 Description: What is calcium imaging, and how can you this technique to get a better understanding of complex rodent behavior? Read more about the basic principles and benefits of calcium imaging Rodents such as rats and mice are powerful animal models for studying the mechanisms of behavior. Recent advances in imaging technology have enabled scientists to study the underlying neuronal networks responsible for various behaviors in rodents. One of the most powerful methods is calcium imaging, which allows researchers to observe activity patterns within neuronal networks and track changes in neuronal responses associated with different behaviors. In this blog, we will explore what this technique is, and how it can advance your behavioral research. What is Calcium Imaging? Calcium imaging enables researchers to observe and measure the activity of individual neurons in real-time, offering valuable insights into complex behaviors and the functioning of deep brain regions like the prefrontal cortex or hippocampus. Calcium ions (Ca2+) are essential signaling molecules involved in numerous cellular processes, including neuronal communication, muscle contraction, and gene expression. Changes in calcium ion concentrations indicate cellular activity, allowing researchers to decode neural activity associated with specific behaviors by monitoring these shifts within neurons. The basic principles of calcium imaging Calcium imaging involves using specialized fluorescent dyes or genetically encoded calcium indicators to detect changes in calcium ion concentrations. There are several types of calcium indicators that emit fluorescence when they bind to calcium ions. These indicators can be synthetic dyes or genetically encoded proteins. The most commonly used synthetic dyes include Fluo-4, Rhod-2, and Oregon Green BAPTA, while genetically encoded indicators include GCaMP and R-GECO. - The chosen calcium indicator is introduced into the target cells. For example, in the case of neurons, the indicator can be injected into the neurons. They are loaded via diffusion through a patch pipette, or expressed using viral vectors for genetically encoded indicators. - Once the indicator is inside the cells, it is excited by a specific wavelength of light, typically using a fluorescent microscope. When the indicator molecule binds to calcium ions, its fluorescence properties change. This change can be detected using a sensitive camera or photodetector. - The microscope captures images of the cells over time, recording the changes in fluorescence intensity. The intensity of fluorescence emitted by the indicator is proportional to the concentration of calcium ions in the cell. An increase in calcium ion concentration leads to an increase in fluorescence intensity, while a decrease leads to a decrease in intensity. - The collected fluorescence intensity data can be analyzed to extract information about cellular activity. Researchers can quantify the frequency, amplitude, and duration of calcium transients, which correspond to specific cellular events. For instance, in neurons, calcium transients often correspond to action potentials or other types of electrical activity. - Calcium imaging allows researchers to visualize both spatial and temporal patterns of calcium activity. By observing multiple cells simultaneously, researchers can gain insights into how cells interact within a network. However, calcium imaging has some limitations, including potential phototoxicity (damage to cells due to intense light exposure), photobleaching (loss of fluorescence signal over time), and potential interference of the indicator with cellular processes. Additionally, the indicator's affinity for calcium ions and its rate of binding/unbinding can impact the accuracy of the measurements. Image credit: Society for Neuroscience Calcium imaging and studying (rodent) behavior To analyze and interpret these large amounts of data from within the brain, and link them to behavior, researchers often rely on sophisticated behavioral software tools, such as Noldus' EthoVision XT. This software platform enables researchers to precisely track and analyze the behavior of rodents during calcium imaging experiments. Examples of calcium imaging behavioral studies - One such study, published in the journal Nature Communications utilized calcium imaging techniques to investigate the role of serotonergic neurons in social behaviors in mice. The researchers employed a combination of calcium imaging and behavioral analysis to study how activity in specific serotonergic neuron populations influenced social interaction in mice. This study revealed the importance of serotonergic neurons in modulating social behaviors and provided valuable insights into the neural mechanisms underlying social interaction. - Another example is a study published in the journal Cell Reports that examined the neural activity in the amygdala of mice when faced with a threat. The researchers describe the presence of neurons expressing calcitonin gene-related peptide (CGRP) in two specific brain regions: the parvocellular subparafascicular nucleus in the thalamus and the external lateral parabrachial nucleus in the brainstem. These neurons are found to respond to threat cues from multiple sensory modalities and convey negative emotional valence signals to different parts of the amygdala. The study shows that both populations of CGRP-expressing neurons and their connections to the amygdala are crucial for the perception of multi-sensory threats and the formation of aversive memories. This finding suggests a unified neural pathway for innate threat perception, which could have implications for the development of therapeutic approaches for disorders related to innate fear responses. VIDEO TRACKING SOFTWARE Track behavior with EthoVision XT Analyze rodent behavior during calcium imaging experiments with precision and ease. Learn more Benefits of calcium imaging and studying behavior - One of the key benefits of calcium imaging is its ability to capture the dynamics of neuronal activity in real-time. This enables researchers to observe how specific behaviors activate distinct populations of neurons and track their temporal dynamics. By analyzing the neural activity associated with different behavioral states, such as exploration, social interaction, or fear response, researchers can gain a better understanding of the neural mechanisms underlying these complex behaviors. - In addition, calcium imaging allows for the investigation of deep brain regions, which play critical roles in various behaviors and brain functions. By imaging these deep brain regions, such as the prefrontal cortex or hippocampus, researchers can reveal how neural activity in these regions contributes to specific behavioral outputs. - Furthermore, calcium imaging has promising applications in evaluating therapeutic efficacy. Researchers can use calcium imaging to assess how neuronal activity is altered by different interventions, such as drug administration or deep brain stimulation. By longitudinally monitoring the neural activity in targeted brain regions, researchers can determine the impact of these interventions on neural circuit dynamics and behavior. Other species used in calcium imaging studies In addition to mice and rats, other species are commonly used in calcium imaging research to study behavior. These species provide unique opportunities to explore a wide range of behaviors in various contexts. Here are some examples: Zebrafish Zebrafish are a popular model organism for studying behavior due to their transparent embryos and larvae, which allows for non-invasive imaging of neural activity. Their small size and rapid development make them well-suited for high-throughput behavioral assays. Calcium imaging studies in larval zebrafish has, for example, potentially uncovered personalized epilepsy treatments. Drosophila (fruit flies) Fruit flies are a widely used model organism in neuroscience research. They have a well-characterized nervous system and exhibit a diverse range of behaviors, including courtship, locomotion, learning, and memory. Calcium imaging in Drosophila provides insights into the underlying neural circuitry involved in these behaviors. Check out this study by Patel et al (2022) that employs calcium imaging and behavioral analysis with EthoVision XT to understand how animals would sense innocuous and/or potentially harmful stimuli C. elegans (roundworms) Despite their small size and simple nervous system, C. elegans (roundworms) offer unique advantages for behavioral studies. However, calcium imaging in C. elegans is challenging due to the difficulties associated with immobilizing the organism. Check out this recent study, in which the authors have developed a new method to immobilize worms by trapping them in sodium alginate gel. Zebra Finch Songbirds such as the zebra finch are known for their complex vocal learning behaviors. This study focuses on understanding how zebra finches learn and produce their complex songs. Using calcium imaging and two-photon microscopy, the authors examined the process that extends from higher-order brain centers to muscle movements. They monitored ensemble activity during singing to establish that a crucial forebrain structure known as HVC contains premotor neurons that become active at specific time points during song production. HOME CAGE OBSERVATION Study behavior in the PhenoTyper Integrate calcium imaging with automated home cage monitoring for comprehensive behavioral analysis. Discover PhenoTyper Conclusion In summary; calcium imaging, by using optical imaging technologies such as single and two-photon imaging of calcium indicators, will continue to play an important role for measuring behavior and its neural correlates in rodents. This technique's ability to measure neuronal activity with high spatial resolution stands out; allowing researchers to not only measure the activity of individual neurons, but also to pinpoint the specific neurons and brain regions involved in a particular behavior. These findings have implications for understanding the neural basis of behavior and may have potential therapeutic applications in the future. With the advancement of technology and software tools, such as Noldus' EthoVision XT and the PhenoTyper, which can seamlessly integrate with calcium imaging systems, giving researchers the ability to analyze and interpret calcium imaging data in freely moving rats and mice, further enhancing our understanding of behavior. --- ## Understanding cognitive delays in infants with Down syndrome URL: https://noldus.com/blog/cognition-infants-down-syndrome Published: 2023-08-28 13:35:00 Description: Did you know that Down syndrome is one of the most common chromosomal diseases in people? Researcher Fidler and her colleagues aim to understand more about early cognitive development in people with Down syndrome. Down syndrome is a genetic disorder that affects around one in every 700 babies born in the US. People with Down syndrome may experience intellectual disability and often have growth delays and distinct facial features. They are also at risk for autism, epileptic seizures, and Alzheimer's disease. Furthermore, people with Down syndrome experience a general delay in cognitive development. Difficulties in this area are most pronounced in attention, memory, and executive function. Cognitive development in early childhood In this study, Fidler and her colleagues examined cognition in infants with Down syndrome. They argue that it is important to understand delays in early development better, so that we can improve preventative care for this vulnerable group. Specifically, they focused on the relation between cognitive functioning and early attention and memory skills. During infancy, these skills include the ability to sustain and shift visual attention and the ability to temporarily store and retrieve visual information. Relationship between biomedical factors and cognitive development delay Another aim of the study was to examine whether biomedical factors play a role in the observed cognitive delays. For example, many infants with Down syndrome are born with heart defects, are born prematurely, or experience significant illness. These factors are known to impact cognition in the general population, but have not been examined in a population of infants with Down syndrome before. You may also like these blog posts on developmental psychology: - How to study developmental psychology: methods, designs & tools - How maternal responses support child language development in adversity - How to deal with noncompliant toddlers - Research examples of developmental psychology - Understanding infants' social and moral development Cognitive development of infants with Down syndrome Fidler and her team included 38 infants with Down syndrome in their study. Cognitive functioning was assessed using the Bayley Scales of Infant and Toddler Development. While the mean chronological age was nine months, the mean cognitive age was six months. Of these participants, 13 infants were born prematurely, 11 were diagnosed with a congenital heart defect, and five had had a significant illness. Sustained attention and attention shifting Infant attention and memory behaviors were observed in three different tests and coded using The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial The first test measured sustained attention, or focusing on a stimulus without interruption or distraction. To assess this skill, infants were presented with a red teether, and observed on total time spent looking at the teether. The second test involved attention shifting. Infant attention shifting is observed as visual engagement with a stimulus, followed by disengaging and redirecting attention to a new stimulus. In the experiment, this was tested by holding up a red ball to the left and a schematic face to the right, and alternately shaking them. In each trial, researchers coded the time it took infants to look at the object that was shaken, and the time between attention shifts. Observing infant memory In the third test, visual short-term memory was measured as time spent on exploration during a 'changed preference' task. In this task, infants were presented with the same Lego in three consecutive trials. Researchers hypothesized that as the infants got used to the Lego, the time spent on visual exploration would decrease. On the fourth trial, the experimenter presented a new Lego, different in color and size. If the infant remembered what the previous Lego looked like, it would recognize that this was a new Lego. As a result, time spent on exploration would increase again. Attention shifting and Down syndrome cognitive development Results showed a clear association between attention shifting and cognitive development. Infants with lower cognitive performances were slower to shift attention, even when controlling for chronological age. When examining the role of biomedical factors in these results, Fidler and her colleagues found that premature birth was also associated with attention shifting. Early interventions for cognitive development delay The research team emphasized that they found a great deal of variability in their data, and that they didn't use a comparison group. They also recommended doing longitudinal studies to examine whether early attention shifting predicts further developmental outcomes. Still, as one of the first studies examining these factors in early cognitive development in Down syndrome, their study provides valuable insights that can be used in targeted treatments. Specifically, knowledge like this can be used in early interventions, where cognitive development can be stimulated during periods of infant neuroplasticity. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - Fidler, D.; Schworer, E.; Will, E.; Patel, L.; Daunhauer, L. (2019). Correlates of early cognition in infants with Down syndrome. Journal of Intellectual Disability Research, 63(3), 205-214. - CDC - Down Syndrome Data and Statistics - Wikipedia - Down syndrome --- ## Just the way I want it: a study on consumer experience in self-designing URL: https://noldus.com/blog/self-design-consumer-experience Published: 2023-08-22 08:46:00 Description: Consumer research suggests that you value a product more when you design it yourself - like sneakers or a gift. So, why do we abandon the self-design process so often? Find out in this blog post! Consumer research suggests that you value a product more when you design it yourself. For example, companies offer the option to customize jewelry, clothing, beverages, or gifts. It's easy to see why this creates high value, as you can choose exactly what you want1 and may even experience a sense of pride2 in creating your own product. So, why do we abandon the self-design process so often?3 In this blog series, we'll explore six studies by researchers Krause and Franke4. They studied how people's experiences change while self-designing a pair of sneakers (blog post 1) and examined how these experiences influence abandonment behavior (blog post 2). Finally, they tested whether different types of feedback would help consumers to finish their products (blog post 3). In this first blog post of the series, we'll dive a bit deeper in consumer experience during the self-designing process. Self-design: high value, low completion Many major companies are introducing customization applications5. In other words, they're providing their customers with the tools to design their own versions of a product. This may be a can of soda or bottle of wine, a T shirt or pair of shoes, or something more expensive like jewelry and watches. This trend is fueled by evidence from empirical studies, showing that self-designing a product results in high value for consumers. However, consumer research also shows that abandonment rates are extremely high. People start the process of designing their own product, but many of them don't finish what they started. Which means that, in some cases, companies are missing out on sales. You may also like this blog post about influencer marketing for young adults: Disclosure Dilemma What happens to buying intentions? Krause and Franke point out that not every abandonment of a self-design process indicates a lost sale. People may simply be curious or enjoy trying out different customizations, without an intention to buy the product. However, results from their own survey suggests that the majority of consumers at least considers buying the product when starting out with their designs4. That means that, somewhere along the line, these people lose their buying intention. What's happening here? Examining mental processes To find out, Krause and Franke conducted two studies on consumer experience during a self-design process. In the first study, they asked 65 students to design their own sneakers, using a real customization tool. With the help of think-aloud protocols and sentiment analyses, they aimed to uncover what participants were thinking at each moment. They examined three types of valence: what people thought of their design solutions, whether they enjoyed the process, and how they experienced the time and mental energy they invested in designing. FaceReader: unobtrusive observations In the second study, they used FaceReader to examine participants' general valence. Where think-aloud procedures may influence how participants react, FaceReader provides more unobtrusive observations, helping to minimize these effects. They recorded a group of 62 participants during the same sneaker self-designing process and used FaceReader's composite measure of valence in their analyses. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Valence follows a U shape In all types of valence, they found that their participants' experiences followed a U shape. Consumer experience started out positive, followed by disappointment as their experiences didn't meet their expectations, and ending with satisfaction after persevering with the process. This U-shaped model remained significant even after controlling for age, gender, brand attitude, and personal involvement. How can we understand abandonment? The results from these first two studies show that valence plays a critical role in whether or not people complete their own design of a product. It seems that people are disappointed in their expectations after an initial phase of motivation, which may explain why abandonment rates are so high in customization processes. To examine the relationship between valence and abandonment in more detail, Krause and Franke continued their consumer research on product customization. Stay tuned for the next blog post in this series! Read these 5 tips on how to get the most out of your facial expression analysis References 1. Franke, N.; Keinz, P.; Steger, C. (2009). Testing the Value of Customization: When Do Customers Really Prefer Products Tailored to Their Preferences? Journal of Marketing, 73(5), 103-121. 2. Franke, N.; Schreier, M.; Kaiser, U. (2010). The "I Designed It Myself" Effect in Mass Customization. Management Science, 56(1), 125-140. 3. Kalantari, H.; Johnson, L. (2019). Willingness to Pay and Wait for Mass Customised Products. International Journal of Mass Customisation, 5(2), 111-129. 4. Krause, F.; Franke, N. (2023). Understanding Consumer Self-Design Abandonment: A Dynamic Perspective. Journal of Marketing, https://doi.org/10.1177/00222429231183977. 5. Klesse, A.; Cornil, Y.; Dahl, D.; Gros, N. (2019). The Secret Ingredient is Me: Customization Prompts Self-Image-Consistent Product Perceptions, Journal of Marketing Research, 56(5), 879–93. --- ## 6 TED talks to kick off your academic year URL: https://noldus.com/blog/neuro-ted-talks Published: 2023-08-17 15:55:00 Description: Let's get a good warming up for the new academic year. We have compiled six interesting neuroscience TED talks, ranging from optogenetics to AI, to inspire you in the new year. Summer vacation is almost over. That means that we have to go back to work or school and crack our brain over complicated biological processes, or a menagerie of behavioral data. However, just like in sports, it is important to have a good warming-up. Therefore, we present to you a list of interesting TED-talks all about the brain, behavior, and neuroscience. Perhaps these amusing talks can inspire you for your next project. Enjoy! 1) A mouse. a laser beam. A manipulated memory Controlling memories with lasers might sound a bit like science fiction, but it is definitely real. Steve Ramirez and Xu Liu from MIT studied the use of optogenetics to change the memory and behavioral response to certain environmental stimuli. In this TED-talk they explain their methods and how they came to the idea of their research. And while erasing or altering memories might sound scary, it is still in its infancy. It is important for researchers in this field to remain aware of the ethical ramifications of their work. However, I see a world where PTSD or other trauma related disorders can be treated much more easily, and it all starts with research. 2) Are insect brains the secret to great AI? Recently, there has been a lot of talk about Artificial Intelligence. ChatGPT has taken over schools and thousands of tools are being developed as we speak. In this talk Frances S. Chance talks about how we could use the brains of insects to develop neural networks for AI. Insect brains have fascinating abilities compared to their size. The number of neurons in a dragonfly brain is approximately 1 million. Which sounds like a lot but is nothing compared to the 86 billion a human has. Frances explains how understanding the neural pathways of insect brains could help us design smart and energy efficient AI driven technology. 3) How we're reverse engineering the human brain in the lab Growing a brain, now wouldn't that be cool? No more need for using rodent brains to test chemicals or donor brains to test how a brain would react. And while we aren't there yet, Sergiu P. Pasca from Stanford has been conducting research precisely in this area. He is able to turn skin cells into stem cells and convert those into brain cells. Those cells can be turned into organoids that represent all types of brain cells, like the cerebral cortex or spinal cells. However, organoids are not full brains and thus won't fully replace animal testing just yet. But these replica's of brain structure can be vital in the future of developing drugs for a plethora of mental disorders. 4) The paralyzed rat that walked Grégoire Courtine would like to engage you in a thought experiment. Imagine a world where a person that just suffered a spinal cord injury can regain their ability to walk with only chemicals and electricity. This reality is not question of if, but a question of when. Prof. Courtine and his team are developing personalized neuroprosthetics. They are able to make a rat with a lower body paralysis walk with the help of an electrochemical prothesis. The neurons in the spinal cord even started healing themselves during therapy. I encourage you to watch Prof. Courtine explain it for himself, but be advised as the video of the paralyzed rat can be viewed as shocking. 5) Trust, Morality and Oxytocin Paul Zak a.k.a. Dr. Love explains why oxytocin is the moral molecule. Oxytocin encourages people to be more trusting and more people more trustworthy. It increases our ability to emphasize with others. It is mostly released during pleasant and social interactions, like dancing, praying, and sex. However, there are also people who don't release oxytocin during these stimuli. Around 5% of humans have this deficiency and they show attributes of psychopaths. This can be caused by many factors both nature and nurture. Watch this talk by Dr. Love to learn more about the effects and how to increase your levels of oxytocin. 6) A new way to study the brain's secrets Looking at a brain is hard. It is complex and its parts are very small. Microscopes are limited in how far they can zoom in. So, Ed Boyden thought: why enlarge and separate the cells in the brain. By using polymers similar that emulate the workings of diapers (yes really), Professor Boyden can make it easier to look at the brain circuits and unravel the mysteries of mental illnesses and other brain disorders. --- ## Behind the Scenes: Human Behavior Research Labs URL: https://noldus.com/blog/human-behavior-research-labs-in-action Published: 2023-08-14 12:00:00 Description: Observation and analysis of human behavior is often done in labs. From babies to business, it can all be researched. Want to see how some of this research is done? Check out these amazing human behavior labs in action. Exploring human behavior is at the heart of our business. We have made it our mission to help researchers around the world advancing their research. Observation and analysis of human behavior is often done in labs. From babies to business, it can all be researched. Want to see how some of this research is done? Check out these amazing human behavior labs in action. Behind the Scenes: Human Behavior Research Labs Over the past three decades we've been building research labs all over the world. They are always fully integrated with hardware and software for observation, recording, and analysis. Do you want to get some insights into some of the world's best human behavior labs? We go behind the scenes of some renowned behavioral research labs. Behavioral Research in Business Laboratory Hofstra University in Hempstead, NY is home to a state-of-the-art facility that was specifically designed to conduct multi-disciplinary behavioral research. The Behavioral Research in Business Laboratory is powered by cutting-edge software and tools, that are all geared toward analyzing behavior for business-focused research. The lab has a total of 27 workstations, divided over several lab and observation rooms. Analytical hardware like eye-tracker devices and software like FaceReader, Viso, and The Observer XT enables them to design, conduct, and analyze complex research studies. We visited the lab at the Frank G. Zarb School of Business to see it in action. We also spoke to Dr. Anil Mathur, Brodlieb Distinguished Professor in Business and director of the Behavioral Research in Business Lab. Watch the video to discover more about the lab and how Dr. Anil Mathur designed this lab for the future, together with Noldus. "The advice I would give is, think of the future. Actually that was one of the driving things when we asked Noldus to help us design this lab: I don't want to design the lab with my today's research questions. I want to design the lab that can help me research questions five years down the road. And actually this is exactly what is happening. New problems, new questions will come up that I would like to answer tomorrow." BUYER'S GUIDE The perfect audiovisual lab Free buyer's guide - What is an audiovisual lab? - What do you need to complete your setup? - How does an audiovisual lab help you answer your research questions? Get your copy Research in Educational Psychology Researchers at the Leipzig University focus on gaining further insights into future teachers' moral emotions using Noldus' tools. The research team is focusing on professionalization of teachers and with the upgrade of their lab, they are able to measure facial expressions automatically instead of relying on self-reports. A Tobii eye tracker enables them to include reading research in their studies. Prof. Dr. Brigitte Latzko and Dr. Sandra Dietrich show us the upgrade of their lab at the Faculty of Education, Leipzig University in Germany. With this new lab, they will start a whole new line of research in educational psychology. Watch the video below to learn more about their research, and why they choose Noldus' tools. "We need a lab that works; where people very quickly can learn how to work with all the software and the technology. That is what we got from Noldus." Dr. S. Dietrich | Leipzig University, Germany Human factors research in a ship bridge simulator MARIN is one of the world's leading maritime research institutes, based in The Netherlands. They have a state-of-the-art ship bridge simulator, where a complete ship's crew can undergo training and observation, exposing them to various demanding scenarios. Following a simulation, debriefing occurs immediately, allowing for the assessment and enhancement of their decision-making and performance in these pivotal 'safety-critical' circumstances. They are also developing a brand new 'seven oceans simulation center' which is integrated with a Noldus toolkit for human factors research. Hans Huisman shows us around the ship bridge simulator at MARIN. Take a look behind the scenes of their unique simulator, and how they do multimodal research into human decision making. Child development research at Baby and Child Research Center At the Baby & Child Research Center (BRC) in Nijmegen, The Netherlands, researchers are part of a large European Research project that collects data to identify differences in behavior and brain development in young children. Professor Sabine Hunnius and Johanna Harder, research assistant, explain more about the behavioral and developmental tests that are done. This helps to gain better insight in how, for example, autism or ADHD develops, what the children's social skills are, and what their developmental age is. Because the better we understand typical and atypical development, the better we will be able to develop treatments and interventions for children with developmental conditions, such as autism and ADHD. Early childhood development research at the Fisher-Price Play Lab When observing children, and looking at how they play with toys, it's important that they're able to use the toy and have fun with it. But that it also challenges them so that they're able to reach a new milestone and grow to the next level. At the Fisher-Price Play Lab in East Aurora, New York, the kids are the real experts! Dr. Corinne Eggleston, manager of early childhood development research, and Nicole Mackiewicz, child testing researcher at Fisher-Price, tells us how they have proven in the Play Lab that their line of toys, the Linkimals™, promotes learning. They used Noldus' Viso to record the interactions the children have with the toys. They used The Observer XT for coding behavior and analyzing the results. More interesting reads - How to choose the best audiovisual lab for your project - How to train students in soft skills: Tools and Techniques - Resources on Psychology Research: Case Studies, Webinars and White Papers - UX Research Tools for analyzing and visualizing your user research - Three UX Lab examples with the latest UX research tools - Using an AV lab to teach skills for counseling psychology REQUEST INFORMATION Interested in our behavioral research solutions? Let's talk! - Advance your research - Get expert guidance - Profit from our 35+ years of experience Contact us --- ## A 5-HT1A agonist and NMDA antagonist against Parkinson’s disease URL: https://noldus.com/blog/receptor-interaction-parkinsons-disease Published: 2023-08-03 16:00:00 Description: Reducing side effects of L-Dopa with 5-HT1A receptor agonists can improve motor activity in a Parkinson’s disease model when combined with NMDA antagonists. Parkinson's disease is a medical condition that is well-known for a common symptom; a resting tremor. Other symptoms are for example postural abnormalities, difficulties with voluntary movement and rigidity. Often, Parkinson's disease patients are prescribed L-dopa, the precursor to dopamine, in the early stages of their disease, but there are long-term use side effects in the form of involuntary motor complications. Therefore, scientists from the Capital Medical University in Beijing researched a way to reduce these symptoms. L-dopa effects compared to 5-HT1A receptor agonists Based on other studies, they tested among others the effect of 8-OH-DPAT (a 5-HT1A receptor agonist), and that of L-dopa on a Parkinson's disease rat model. Various kinds of these agonists are often used together with L-dopa in order to reduce the long-term use side effects. However, the effect of only 8-OH-DPAT on Parkinson's disease was not tested before. The researchers also tested other drugs and (ant)agonists combined with 8-OH-DPAT. In the current study a 6-OHDA-lesioned rat model was used, created by injecting 6-OHDA into the brain. This causes changes in basal ganglia circuitry, which is characteristic of Parkinson's disease in humans. After two weeks of recovery, all rats received an apomorphine injection (a Parkinson's disease treatment). Then, for 30 minutes their behavior was tested to see which rats had a minimum of 5 net contralateral rotations/min. These rats were selected for further testing, a.o. brainwave analysis (see original article for description and test results) and behavioral analyses. Forepaw adjusting steps Experimenters tested the rats' forelimb akinesia using the forepaw adjusting steps (FAS) test. They hold the rats' hindlimbs and one forelimb, moving it sideways across a table for 90 cm in 10 seconds. Both forelimbs were tested multiple times in both directions, and the number of steps the rats took to stay balanced were counted. More steps indicates better motor ability. The effect of 8-OH-DPAT on the rats was similar to that of L-dopa, which shows that it improves Parkinson's disease's akinesia. Parkinson's disease combined drug treatment Further experiments used rats that were injected with various kinds of drugs, or vehicle (0,9% saline), to test these drugs' effectiveness. Several of the non-vehicle injected rats were in turn divided over more groups (see fig. 1) and received additional drugs 30 minutes after the first injection. All 8-OH-DPAT-injected rats received either vehicle, raclopride, WAY100635, MK-801 or DCS, and all L-dopa-injected rats received either vehicle or raclopride. Raclopride is a common Parkinson's disease treatment in trials, and WAY100635 is a 5-HT1A receptor antagonist (whereas 8-OH-DPAT is an agonist). MK-801 is an NMDA receptor antagonist and DCS is an NMDA agonist, i.e. they have more or less opposing effects. Figure 1: The various treatment combinations used in the experiments by Jiang et al. Open field tests and motor symptoms Each rat, treated according to fig. 1, could explore an open arena for 10 minutes. Those sessions were recorded with a camera that was connected to Noldus EthoVision XT. The program automatically tracked the distance travelled, the complete route the rat travelled during this time period, and its exact position in the cage related to time. This drew a very clear image of both the types of movements the rats carried out during the experiment and potential motor symptoms (see original paper for images). The analysis pointed out that both 8-OH-DPAT and L-dopa increased rats' locomotor activity compared to vehicle-treated rats. Both also increased movement velocity, though the effect lasted longer in L-dopa treated rats. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Interaction between the 5-HT1A receptor and the NMDA receptor This shows that 8-OH-DPAT is indeed able to significantly reduce motor deficit in the used rat model, by activating the 5-HT1A receptor. On top of that, the scientist also applied NMDA receptor antagonist MK-801 and agonist DCS. Through this, it seems that the ability of 8-OH-DPAT to improve motor function is related to the interaction between the two receptors (5-HT1A and NMDA). If and how exactly this interaction improves Parkinson's disease motor symptoms is still not clear. Abnormal involuntary movements test The rats that were injected with either only vehicle or only with L-dopa underwent another behavioral test, checking for abnormal involuntary movements (AIMs). A vertical, clear plastic cylinder was the tool that each rat was placed inside. Exploring rats tend to stand on their hind limbs and place their forelimbs against a vertical surface. AIMs of limbs, axis and tongue were scored on severity for one minute every 10 minutes, for a total of 120 minutes. The scientists found that AIMs were already triggered when the L-dopa dose was still quite low. The potential of 5-HT1A receptor agonist and NMDA receptor antagonist This study pointed to the 5-HT1A receptor agonist (8-OH-DPAT) being capable of improving Parkinson's disease motor function when used in a 6-OHDA-lesioned rodent model. This effect might take place through 8-OH-DPAT modulating NMDA receptors, or through a different mechanism caused by NMDA antagonism. This should be studied in further research. Original article Jiang, X., Liang, P., Wang, K., Jia, J., & Wang, X. (2022). Serotonin 1A receptor agonist modulation of motor deficits and cortical oscillations by NMDA receptor interaction in parkinsonian rats. Neuropharmacology, 203, 108881. --- ## How to choose the best audiovisual lab for your project URL: https://noldus.com/blog/how-to-choose-the-best-audiovisual-lab Published: 2023-08-01 15:20:00 Description: AV recordings are becoming more important in the fields of education, professional skills, training, and medical simulation. But what are the right tools for you? Learn how to choose the right AV lab for your project. Audiovisual (AV) recordings are becoming more important in the fields of education, professional skills training, medical simulation, and more. AV data helps students and professionals to learn more effectively, while also providing trainers with more insights and flexibility. But what is the best solution for you? It can be a challenge to choose from the many different AV tools available. In this blog post, you'll learn how to find the right AV lab for your project. Why do you need an AV lab? Audiovisual data greatly enhances your research, education, and training projects. AV data helps you to capture a wider range of information and better understand your participants. For example, audiovisual data may help you to gain insights into learning processes, teamwork, and communication. Moreover, students and professionals learn much faster when they can see what they do and immediately receive personalized video feedback on their performance. This evidence based learning strengthens their knowledge and skills, as well as builds their confidence. This works especially well for students' learning goals in soft skills, such as interviewing, listening, working together, or giving a presentation. And what about improving your teamwork or clinical skills with a medical simulation? With the right AV setup, your projects will flourish. Components of your AV lab So, what kind of lab do you need? That depends on your projects and goals. How many people do you want to observe at the same time? Are you working from one location or do you need multiple rooms, or even a portable lab? What kind of cameras and microphones work best for your project? Other considerations include: - Communication. Consider whether you need to be able to communicate live with one or more participants through speakers or headphones. - Remote control and scheduling. Need to be somewhere else? With remote control and scheduling options, you can record your participants in the lab while working in another location. And with a recording button, participants can even start and stop recordings themselves. - Review and debriefing. To improve the process of evidence based learning, you need immediate video feedback after your sessions. That way, all the information is still fresh in everyone's minds. - Video annotation. When you're training students and professionals, you'll want to mark the recording when participants do something interesting. These video annotations will help you get the best insights for your project. - Data analysis. After recording, reviewing, and debriefing your sessions, you may also want to analyze your annotated data in more detail. Make sure your AV setup enables you to export data to the statistical or behavioral analysis program of your choice. - Privacy and security. Choose an AV solution that makes it easy to secure your data and helps you to comply with GDPR or HIPAA regulations. FREE WHITE PAPER How does AV recording tool Viso work? Discover how Viso can transform your work—download the free white paper to explore its features and security. - How can Viso benefit your work? - What can you expect of the Viso features? - Is data protection guaranteed within Viso? Start downloading Choose which types of data you need An audiovisual lab offers many options for data collection. What do you need to create the best study or learning experience? Obviously, you need video data of excellent quality, especially when you're observing several people at the same time. That means recording participants from different angles, capturing body language, eye contact, and other relevant behaviors. But do not forget that audio is equally important to record every part of a conversation, even when people are talking softly or all at the same time. You may also want to include screen recordings or combine your AV setup with other data streams. For example, physiological data, eye-tracking, and facial expression analysis provide you with even more insights. How to get the most out of your AV lab Once you know which data and components you need, it's time to set up your lab. How do you get started? And how do you make sure you get the most out of your AV lab? Decide which basic components you need to get started on your project. And don't leave out more practical considerations, such as soundproofing, air circulation, lighting, and preventing disturbances. Get started, learn from your experiences, and expand your lab as your project progresses. That way, you can keep building on your successes. Of course, you not only want the best solution right now, but you also want to be ready for the future. That's why it's so important to choose a solution that you can scale up easily and has ongoing support and innovation. Want to know more about how to choose the right AV lab? In our buyer's guide, you'll learn more about different components and types of AV labs, including information about costs and a detailed comparison of different vendors. BUYER'S GUIDE Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download --- ## Disclosure dilemma URL: https://noldus.com/blog/emotional-responses-disclosures-ads Published: 2023-07-25 10:55:00 Description: Isabelle Leenders examined the influence of disclosures in influencer advertising on the brand attitudes and purchase intentions of young adults, mediated by their emotions and activation of persuasion knowledge. This blog post was written by Isabelle Leenders, who completed her Master's degree in Communication Sciences at Radboud University in Nijmegen, The Netherlands. The thesis was supervised by Paul Ketelaar, Assistant Professor in Communication Science and the Behavioural Science Institute (BSI) at Radboud University. Unveiling the dilemma In today's digital society, influencer marketing plays an increasingly prominent role in how young adults make purchasing decisions1,2. Considering this trend, stricter regulations have been introduced by governments, requiring the inclusion of disclosures for sponsored content3. Through a disclosure (an advertising notification), consumers are informed about the commercial intent of an influencer's advertising message, and it helps them recognize the presence of advertising4,5. This can take the form of a hashtag, verbal mention, or description accompanying a post. Examples include "Advert," "#ad," or "paid promotion"6. The use of disclosures creates a dilemma: on one hand, disclosures can create critical7, skeptical8 and negative emotional responses from young adults5,9. On the other hand, disclosures create trust in the influencer and transparency in the message10, which can lead to positive emotional responses from young adults11. Towards understanding disclosures in influencer marketing The study examined the impact of disclosures on purchase intention and brand attitude among young adults. The goal was to understand whether disclosing sponsored content through a disclosure influenced how young adults perceive a brand and whether they are inclined to make a purchase. To better comprehend the effect, the study investigated whether the activation of persuasion knowledge and emotional response played a mediating role in this process. Figure 1 shows the research model of this study. Figure 1: Research model Measuring emotional response with FaceReader Online The study was conducted among Dutch young adults between the ages of 18 and 30. A total of 89 participants were randomly assigned to two groups. Both groups were shown a video of a well-known Dutch vlogger. This vlogger advertised a product from Airup, a well-known brand of water bottles among the target group. Participants in the experimental condition were presented with an auditory and visual disclosure following the product endorsement, while participants in the control condition did not receive any disclosure. The auditory disclosure delivered by the influencer stated, "Air up is the sponsor of this video and the perfect sponsor for this video. Thank you, Air up, for sponsoring this video." The textual disclosure appeared on screen only when the auditory disclosure was spoken (Figure 2). Figure 2: Textual disclosure in the experimental condition The study utilized a Qualtrics survey that seamlessly integrated with FaceReader Online. By combining the Qualtrics survey with FaceReader Online, the emotional response could be measured quickly and easily by the researcher. Clear instructions were provided to the participants during the measurement, resulting in reliable data collection. The recorded data was promptly analyzed and presented clearly with graphs and figures. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Revealing perspectives on the disclosure dilemma Interestingly, no noticeable effect of disclosure (present/not present) was found on both brand attitude and purchase intention. This suggests that disclosing sponsored content may not have a direct influence on the brand attitude and purchase intentions of young adults. Additionally, no noticeable effect was found of disclosures on the activation of persuasion knowledge or the emotional responses of young adults. Furthermore, these emotional responses did not have a noticeable effect on the purchase intention of young adults. However, FaceReader Online did reveal a noticeable effect of emotions on brand attitude. More positive emotional responses were found to have a positive influence on how the brand was perceived. This indicates that creating positive emotions in influencer content can help promote a positive brand attitude. How FaceReader Online may provide new insights Although not proven the main goal of the research, this study emphasizes the importance of understanding consumers' emotional responses to sponsored content, as it can influence their attitudes towards the promoted brand. Therefore, in future research on consumers' emotional reactions to disclosures, FaceReader Online could be used more frequently. This study has demonstrated that FaceReader Online is an effective method for measuring subtle and unconscious emotional responses in the context of influencer marketing. Particularly in experimental settings, FaceReader Online can be valuable because even when participants are aware of the camera and try to provide neutral responses, unconscious emotions can still influence brand attitude and how the brand was perceived behavior2. Also read: Why you should use FaceReader Online for your human behavior research. Uncovering the unconscious emotions Facereader is a reliable tool for assessing emotions, as traditional methods of measuring emotions, such as self-report scales, may not always be deemed accurate due to the subjective nature of emotions and personal interpretations. Moreover, cognitive processes triggered by advertisements frequently operate at an unconscious level, making it challenging for consumers to consciously reflect upon them. Furthermore, in previous research, emotion has often been measured using self-report scales, but this method is not always considered accurate due to the subjective nature of emotions and individual interpretations13,14. Additionally, cognitive processes evoked by advertisements often occur unconsciously, making it difficult for consumers to consciously reflect on them15,16. Noldus FaceReader Online holds significant potential in this regard as it serves as a valuable tool to enhance our understanding of emotions and, more specifically, to effectively measure the impact within the context of influencer marketing. Noldus FaceReader Online is a valuable implication in this regard and can complement the scientific knowledge in the context of efficiently measuring emotions and more specifically disclosures in influencer marketing. Facilitating large-scale emotion research Finally, FaceReader Online is user-friendly and allows for the recruitment of a large number of participants. By integrating FaceReader with online surveys, research can be easily disseminated. Participation is convenient for respondents, as they can choose whether and when they want to participate in the study. This facilitates large-scale research. By utilizing FaceReader Online, we can enhance our understanding of emotions, complement existing scientific knowledge and measurement methods, and gain valuable insights into the effects of emotional responses. References - De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36(5), 798–828. https://doi.org/10.1080/02650487.2017.1348035 - Hudders, L., De Jans, S., & De Veirman, M. (2020). The commercialization of social media stars: a literature review and conceptual framework on the strategic use of social media influencers. International Journal of Advertising, 40(3), 327–375. https://doi.org/10.1080/02650487.2020.1836925 - DDMA. (2023, 21 februari). Mediawet - Influencer Regels. Influencer Regels. Accessed March 6, 2023, from: https://influencerregels.com/mediawet/ - Evans, N. J., Phua, J., Lim, J., & Jun, H. (2017). Disclosing Instagram Influencer Advertising: The Effects of Disclosure Language on Advertising Recognition, Attitudes, and Behavioral Intent. Journal of Interactive Advertising, 17(2), 138–149. https://doi.org/10.1080/15252019.2017.1366885 - Boerman, S. C., Van Reijmersdal, E. A., & Neijens, P. (2012). Sponsorship Disclosure: Effects of Duration on Persuasion Knowledge and Brand Responses. Journal of Communication, 62(6), 1047–1064. https://doi.org/10.1111/j.1460-2466.2012.01677.x - Stichting Reclame Code. (2022, 30 juni). Toelichting Reclamecode Social Media & Influencer Marketing - Stichting Reclame Code. Accessed May 28, 2023, from https://www.reclamecode.nl/social-toelichting/ - Van Reijmersdal, E. A., Rozendaal, E., Hudders, L., Vanwesenbeeck, I., Cauberghe, V., & Van Berlo, Z. M. C. (2020). Effects of Disclosing Influencer Marketing in Videos: An Eye Tracking Study among Children in Early Adolescence. Journal of Interactive Marketing, 49(1), 94–106. https://doi.org/10.1016/j.intmar.2019.09.001 - De Veirman, M., & Hudders, L. (2020). Disclosing sponsored Instagram posts: the role of material connection with the brand and message-sidedness when disclosing covert advertising. International Journal of Advertising, 39(1), 94–130. https://doi.org/10.1080/02650487.2019.1575108 - Lee, S. I., & Kim, E. E. (2020). Influencer marketing on Instagram: How sponsorship disclosure, influencer credibility, and brand credibility impact the effectiveness of Instagram promotional post. Journal of Global Fashion Marketing, 11(3), 232–249. https://doi.org/10.1080/20932685.2020.1752766 - Kay, S., Mulcahy, R., & Parkinson, J. (2020). When less is more: the impact of macro and micro social media influencers' disclosure. Journal of Marketing Management, 36(3–4), 248–278. https://doi.org/10.1080/0267257x.2020.1718740 - Beckert, J., Koch, T., Viererbl, B., & Schulz-Knappe, C. (2021). The disclosure paradox: how persuasion knowledge mediates disclosure effects in sponsored media content. International Journal of Advertising, 40(7), 1160–1186. https://doi.org/10.1080/02650487.2020.1859171 - Kagan, J. (1994). On the nature of emotion. SRCD, 59(2–3), 7–24. https://doi.org/10.1111/j.1540-5834.1994.tb01275.x - Barrett, L. F. (2017). How Emotions are made. The secret life of the brain. Revue québécoise de psychologie, 40(1), 153-157. https://doi.org/10.7202/1064926ar - Suhr, Y. T. (2017). FaceReader, a Promising Instrument for Measuring Face Emotion Expression? A Comparison to Facial Electromyography and Self-Reports (Master's thesis). Accessed from https://dspace.library.uu.nl/handle/1874/352187 - Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The Role of Emotions in Marketing. Journal of the Academy of Marketing Science, 27(2), 184–206. https://doi.org/10.1177/0092070399272005 - Mizerski, R., & White, D. J. (1986). Understanding and using emotions in advertising. Journal of Consumer Marketing, 3(4), 57-69. https://doi.org/10.1108/eb008180 --- ## Everything you need to know about EthoVision XT URL: https://noldus.com/blog/everything-you-need-to-know-about-ethovision-xt Published: 2023-07-25 10:00:00 Description: Over the last 25 years EthoVision XT has evolved from a video tracking software into an advanced, but user friendly, software platform. In this blogpost we tell you everything you need to know about EthoVision XT! With over 35,000 publications, we can safely say that EthoVision XT is a widely used and applied video tracking software. Over the last 25 years EthoVision XT has evolved from a video tracking software into an advanced, but user friendly, software platform. Everything you need to know about EthoVision XT Recently we released EthoVision XT version 17.5, which includes a lot of great new features and improvements. In this blog, we summarized everything you need to know about these new features, the strengths of EthoVision XT and why you should use it in your research! Video tracking software First things first: what is EthoVision XT? EthoVision XT is a video tracking software that tracks and analyzes behavior, movement and activity of any animal. It means that the software detects an animal in a video file or from a live video feed and can track its whereabouts and movement. EthoVision XT can even measure movement at pixel-level. This is ideal for studying specific behaviors in rodents such as freezing, rearing or grooming, but is also widely applied in (zebra)fish studies. Transparency is key EthoVision XT is not a black box software tool, it gives you full insight and control. You know exactly where your data is coming from at any point in your research and you can even adjust data points if necessary. As a researcher you still have the responsibility to interpreted the data coming from the software. Therefore, having a transparent tool allows for an easier and validated analysis. Many parameters for analysis and visualization EthoVision XT extracts a number of parameters: velocity, distance moved, time spent in a certain zone, rotation and many more. But not only can you extract many parameters, there are several ways to visualize your results. Think of plots, graphs, tracks and heatmaps. These all give you great insight into your results and helps you understand them. New! EthoVision XT 17.5 EthoVision XT 17.5 introduced a variety of third-party integrations, among which are Live Mouse Tracker (LMT) and the Ugo Basile fear conditioning chamber. Upgrade to the latest version to also receive various performance improvements for your EthoVision usage. Developed by Institut Pasteur, LMT is a cutting-edge system for real-time behavioral analysis of multiple mice. EthoVision XT 17.5 simplifies LMT data importing and analysis, allowing researchers to seamlessly integrate and leverage EthoVision functionality for deeper insights into individual and social behaviors. Furthermore, EthoVision XT 17.5 enhances the integration of the Ugo Basile fear conditioning chamber with plug-and-play USB connection for up to 4 chambers. Researchers can now set up protocols effortlessly, saving time and ensuring robust results in fear and anxiety-related behavior studies. Better tracking with deep learning What is deep learning? Deep learning is a technology that uses neural networks to allow a computer to learn by experience. This takes video tracking to a whole new level, because it provides a more accurate and stable body point detection. Especially in tricky situations where objects might block or obscure a direct line of sight to the animal. In the video below, you can see a comparison between the classic contour-based tracking and the new advanced deep learning tracking. At the core of your lab, EthoVision XT can be used for basically any behavioral test and with a variety of animals. The flexible, modular approach of EthoVision XT makes it possible for you to build your own personal EthoVision solution. Even though you’ll often see studies with zebrafish or rodents, EthoVision XT is scalable for any animal.  Configurations range from basic video tracking to a multi-functional (automated) system. A platform to build on for the future! Learn more about the modules here. Are you interested in building your own rodent neurobehavioral core? Download this free guidebook on how to build a rodent neurobehavioral core and learn more about the why, who, what and how. Best tracking results With EthoVision XT you can track in a video file or from a live video feed. This all works well under both normal and IR lighting conditions. With a large range of cameras, while also being possible to track one or more animals from multiple camera inputs simultaneously. Considering this, and due to the superior detection methods (including deep learning technology) and automatic detection settings, EthoVision XT gives you the best tracking results compared to any other software currently on the market. Work remotely Modern problems require modern solutions. Nowadays working from home, or working remotely is not uncommon at all. We’ve got a couple of solutions for you to not miss any work when working remotely! Such as being able to analyze your data without a USB dongle (after you’ve acquired the tracks). Also, we now offer a digital license, which can be activated/deactivated depending on the computer you are currently working on. But it is also possible to remotely access a computer, which has the USB dongle (or digital license) installed for video tracking. High-throughput and high-content In EthoVision XT you can track up to 100 arenas and up to 16 animals per arena simultaneously. In these arenas you can define up to 10,000 different zones. Think of cumulative zones, hidden zones, etc. What users say about EthoVision XT Students from the Gerlai lab in Toronto use EthoVision XT to study the behavior of zebrafish. They comment that: “it’s quick and easy to use, and that it is quite amazing”. It allows them to look at behaviors they are not able to assess manually. Dr. Robert Gerlai comments that EthoVision XT is a great tool for his students to use while they are learning to become behavioral scientists. The choice is yours! Prof. Roberto Rimondini finds EthoVision XT easy to use and as he says: ‘dummy proof’! Prof. Roberto Rimondini is a neuropsychopharmacologist at the Department of Medical and Clinical Sciences DIMEC, Alma Mater Studiorum Bologna (University of Bologna in Italy) and he has been using the video tracking software since its DOS version. In the video below you’ll learn more about why he chooses to use EthoVision XT. But if you are more technologically attuned and/or simply want more insight into your data. Or want to add complex hardware control settings or custom scripts? This is also possible in EthoVision XT, and makes this an extremely versatile piece of software.               RESOURCES: Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts  Resources     --- ## Do we help students by surprising them? URL: https://noldus.com/blog/make-instructional-videos-more-engaging Published: 2023-07-17 10:13:00 Description: The role and usage of instructional videos are increasing in higher education. The research team of Sass & Vinczéné Fekete investigated which features make them more or less engaging for students. This blog post was written by Lídia Vinczéné Fekete, Education Methodology Advisor at the Centre for Educational Quality Enhancement and Methodology of the Corvinus University of Budapest. Despite the end of remote education, the role and usage of instructional videos are increasing in higher education. They provide new opportunities for flexible and self-paced learning, which is especially helpful for those who, due to their individual learning style or difficulties, can learn more effectively using audio-visual resources than through text alone. However, the production of instructional videos is time and resource intensive, so it is worth investigating which features make them more or less engaging for students. How do you know someone is feeling (highly) engaged? Dayenne Sarkol-Teulings created a custom expression in FaceReader to measure the level of engagement. Learn more about her validation study by reading her blog post. Unobtrusive facial expression analysis A recent low-sample preliminary study (Sass & Vinczéné Fekete, 2022) detected student emotions by FaceReader while they watched a 22-minute-long instructional video. In such a context, FaceReader provides an unobtrusive opportunity for facial expression analysis during video watching, using the webcam of the laptop on which the video is played. In addition to facial expression analysis, participant (N=10) emotions were detected by further methods as well, to test the validity of the results gained by FaceReader: participants reported their emotional state and their opinion on the video through an online questionnaire and they shared their experiences in the form of retrospective interviews. This way, emotional states during learning can be observed by applying a multi-methodological approach. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Analysing teacher behavior with The Observer XT The research team also examined the teacher's behaviors in the videos that were shown to the students. After all, the presenter in the video plays a crucial role in student engagement. A dynamic and enthusiastic presenter can captivate students' attention and make the content more relatable. Besides, incorporating a variety of presentation styles can help maintain student interest throughout the video. Key is to understand the needs and preferences of the students and adapt the instructional videos accordingly. In this study, behaviors such as the appearance of the presenter's face, humour, but also the presentation tools applied in the video, such as the slide variations (with or without text/picture), a short story, or an animation, were compared with the viewers' emotions. To examine the relationship between teacher communication and the appearance of certain academic emotions, data was exported from FaceReader to The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Are you experiencing sadness or are you concentrating? Two emotions showed a strong correlation between the values from automated facial expression analysis and self-reports; these were happiness and anger. The most intense facial emotion identified by FaceReader during this activity was sadness. However, retrospective student interviews (when the test leader rewatched the episodes with the participants when their faces showed a high level of sadness) clarified this information: most of the participants reported that during these episodes, they experienced intense concentration, instead of sadness. In this specific situation, i. e. watching an instructional video with new information, the facial expression reflecting strong concentration seems to be very similar to the usual manifestation of sadness. Surprise as a positive emotion The strong correlation between the appearance of happiness and surprise (detected by FaceReader and self-report questionnaires) which was in line with student interviews, suggests that surprise is considered by students as a positive emotion in the context of online learning. The relationship between student engagement and surprise was already reported by previous studies (Altuwairqi et al., 2018) as well. The most motivating elements, as perceived by students, were the topic's relevance and attractiveness, the structured nature of the content, the comprehensibility of the information, and the clarity of the visual representation. References Funding: The implementation of the study presented was supported by the UNKP-22-3-II-Corvinus-121 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund. - Altuwairqi, K., Jarraya, S. K., Allinjawi, A., & Hammami, M. (2018). A new emotion–based affective model to detect student's engagement. Journal of King Saud University - Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2018.12.008 - Sass, J., & Vinczéné Fekete, L. (2022). Secrets revealed by boredom: Detecting and tackling barriers to student engagement. 2022 International Conference on Advanced Learning Technologies (ICALT), 417–419. https://doi.org/10.1109/ICALT55010.2022.00129 --- ## Choosing the right parameters in CatWalk XT URL: https://noldus.com/blog/catwalk-meta-analysis Published: 2023-07-13 10:30:00 Description: CatWalk XT provides the opportunity to study a variety of gait parameters. But, which parameters should you use for your mouse model? Read this blog to learn more! Every year many researchers switch from traditional paw inking to an automated system for gait analysis. Automatic gait analysis systems like Noldus' CatWalk XT vastly improve reliability and efficiency of your research. However, making sense of the data generated with by automated methods is not always straightforward. You might be asking yourself questions like: What parameters are important for my disease model? Which parameters are important during disease progression? And perhaps many more. In this blog we will be looking at a paper written by Ivanna Timotius together with, among others, CatWalk XT product manager Reinko Roelofs [1]. In this paper Timotius et al. performed a meta-analysis of studies that used CatWalk XT. They looked at the readouts of those studies and which parameters were significantly impacted by certain diseases models. The aim was to use this information to help users select parameters to initially focus on in their disease model. Uncovering gait parameters For this meta-analysis the researchers analyzed 91 peer-reviewed studies that used gait analysis in commonly studied disease models. They assessed the parameters that were reported as results in these studies and whether they significantly increased, decreased, or were not significantly different when compared to control animals. Most of these studies were published recently (between 2017 and 2022). The researchers highlighted 6 commonly used disease models related to gait impairments, namely: Parkinson disease (PD), stroke, spinal cord injury (SCI), traumatic brain injury (TBI), severe neurological damage (SNI), and Ataxia. What is CatWalk XT? But before we continue, what is the CatWalk XT? And why is choosing the right parameters so important? CatWalk XT is the golden standard forobjectively detecting overground gait in rodents. While an animal walks across a glass walkway, its gait is recorded from below. Green LED light is internally reflected inside this glass plate except when contact is made with the plate. This way only the actual footprints scatter light and are detected by the software. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources Rodents in the CatWalk XT are trained to traverse voluntarily a narrow dark walkway corridor towards a goalbox. This eliminates stress and gives great insight into the walking ability of all disease or injury models. From each traversal many different parameters can be assessed like stride length, stand time, duty cycle, print area, to name a few. Using an automated gait analysis system with a high spatial and temporal resolution allows for the detection of subtle changes in gait that cannot be observed by manual observation. However, this is where confusion might arise. Having the option to measure more than 50 parameters doesn't mean you should consider them all in your analysis, or that they will provide any valuable insight. Therefore, knowing which parameters to use, and determining them beforehand, is essential in correctly using an automated gait analysis system. Which parameters should I use? So, what were Timotius et al. able to conclude? Many papers had conflicting results when analyzing the same disease models due to differences in mouse strain, injury model and laboratory practises. However, some parameter changes were more consistent. For example, PD mouse models had an increased stand time and decreased swing speed, when compared to control mice. This was also the case for SCI mice, which also had a significantly different regularity index (the exclusive use of a normal step sequence patterns during uninterrupted locomotion). Differences in stride length and changes in hind paw base of support shows that parameters related to compensatory mechanisms to restore balance are very useful for ataxia models. Run speed, maximum contact area and swing speed were all significantly decreased in stroke mice. In SNI mice the intermediate and average toe spread was significantly decreased or increased, which could be because of the different mouse models used. Lastly, phase dispersion and the mean of max intensity were different for mice with TBI. Interestingly, the less site specific the disease is (like stroke and TBI), the more parameters were significantly changed by the injury. This is likely because of the large and varied effect these parameters have on the brain, which causes more symptoms to develop. Moving forward So, how do we move forward with these conclusions? It is important for researchers to know the parameters to initially look for in their disease model as highlighted above. Furthermore, it is essential that researchers consider how certain environmental or genetic factors have an influence on gait variables such as housing, handling, disease model and many other factors. This doesn't mean that everything can or should be perfectly standardized. If certain results are truly robust, it will be less influenced by external factors. However, it is crucial to state that reporting on these factors is still needed for a complete understanding of why certain results might deviate from other studies. In conclusion the study by Timotius et al. recognizes the inherent biases and limitations in their approach due to reliance on published data. They do also emphasize the need for comprehensive and detailed reporting in gait studies, which will significantly enhance the reliability and relevance of gait analysis tools such as the CatWalk XT, while in turn increasing the understanding of CNS and PNS injury models. REQUEST INFORMATION Get expert advice on gait analysis Do you want to learn more about gait analysis and need expert advice? Let's talk! - Advance your research - Get expert guidance - Profit from our 35+ years of experience Contact us References 1. Timotius, I.K.; Roelofs, R.F.; Richmond-Hacham, B.; Noldus, L.P.; von Hörsten, S.; Bikovski, L. CatWalk XT Gait Parameters: A Review of Reported Parameters in Pre-Clinical Studies of Multiple Central Nervous System and Peripheral Nervous System Disease Models. Front. Behav. Neurosci. 2023, 17, 1147784. --- ## AI and deep learning: Responsible use of facial expression analysis URL: https://noldus.com/blog/ai-responsible-use-facial-expression-analysis Published: 2023-07-12 10:00:00 Description: The European Parliament adopted its negotiating position on the first-ever regulation of AI. In this blog post, we explore how to use facial expression analysis responsibly and how it can contribute to scientific research. On June 14, 2023, the European Parliament adopted its negotiating position on the AI Act, the first-ever regulation of artificial intelligence (AI). The goal of the act is to ensure that AI developed and used in Europe adheres to EU rights and values, namely those related to human safety, privacy, transparency, non-discrimination, and social and environmental well-being. The AI Act is expected to go into effect in 2024. The act establishes differing rules based on four levels of perceived risk: unacceptable, high, limited, and minimal. While the act prohibits certain AI practices, such as social scoring and intrusive biometric identification, it is crucial to note that the European Parliament was clear about the use of such technologies for academic research, stating on page 64 in their response to the European Commission: "It is therefore necessary to exclude from its scope AI systems specifically developed for the sole purpose of scientific research and development and to ensure that the Regulation does not otherwise affect scientific research and development activity on AI systems." In this blog post, we will explore how to use facial expression analysis responsibly and how it can contribute to various fields of scientific research. Ethical considerations of facial expression analysis Before exploring the contributions of facial expression analysis, it is important to note that Noldus Information Technology agrees with the AI Act in regards to use in unacceptable and high-risk systems, such as emotion recognition in law enforcement or border management. Noldus does not allow the use of its facial expression analysis tool, FaceReader, in a number of applications, including: - Active defense, meaning the application in weapon systems. For example, to support a pilot in a fighter plane or an operator controlling a weaponized drone. - Biometric data collection in a judicial context such as a police interrogation. FaceReader cannot and shall not be used as a 'lie detector'. - Surveillance of people in public spaces for security purposes. - Any other use that may potentially violate fundamental human rights. FaceReader is not capable of recognizing or identifying faces or people, and therefore unsuitable for surveillance purposes. Furthermore, Noldus disapproves of the use of the technology without explicit prior consent from the individuals whose faces are being captured. How this consent is obtained may differ, depending on the application in which FaceReader is being used, but the responsibility for acquiring consent rests with the organization applying the software. Find out more about our ethical policy regarding facial expression analysis on our website. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download How does facial expression analysis work? Facial expression analysis involves the study and interpretation of facial movements and expressions to create meaningful insights. Noldus' FaceReader 9 uses several trained models to derive facial expressions. First, using a face finding algorithm, the position of the face within an image (static or dynamic, i.e., video) is found. From there, a neural-network based face analysis model processes the image(s) through a series of layers. These layers were trained using deep learning, a type of machine learning in which an artificial neural network is trained on a large amount of data and used to make predictions on new data. The training process involves iteratively adjusting the model's parameters based on feedback to improve prediction accuracy until no further improvements are observed. Discover more FaceReader facts in this blog post. Deep learning in FaceReader In the case of FaceReader 9, the training and testing of the network1 is done on a large collection of diverse facial images manually annotated by human (FACS) experts. The result is an output of the seven "basic" expressions or emotions: happy, sad, angry, surprised, scared, disgusted, and neutral. Additionally, the optional Action Unit Module evaluates the engagement of twenty individual muscles, or action units. Over the past decade, FaceReader has been used in many peer-reviewed scientific publications, from children's reactions to moral transgressions2 to responses to odors3 to predicting advertising effectiveness4, to name a few. Since its initial launch, there have been over 1,700 publications using FaceReader. Furthermore, FaceReader has been shown to be accurate and at parity with human coders5. Supporting scientific innovation It should be noted that the European Parliament's President, Roberta Metsola, began the press conference announcing the adoption of the AI Act by reading a statement prepared by ChatGPT. This, of course, was done to illustrate the point that everyone must be cautious with Generative and other AI technologies. The European Parliament's recognition of the importance of exemptions for research activities is commendable. These exemptions facilitate scientific innovation and enable researchers to leverage facial expression analysis tools to explore new frontiers of knowledge. At the same time, they provide safe environments for testing and refining AI models before their deployment, striking a balance between innovation and citizen protection. Contributions of facial expression analysis Facial expression analysis, when implemented responsibly and ethically, has the potential to significantly contribute to scientific research, innovation, and the overall betterment of society. By understanding and interpreting facial expressions, researchers can deepen their understanding of human behavior and enhance human-computer interaction. Want to learn more about facial expression analysis? Check out one of our on-demand webinars on FaceReader! The AI Act's adoption by the European Parliament demonstrates a commitment to strike the right balance between harnessing the positive potential of AI technologies while ensuring the protection of human rights, privacy, and non-discrimination. As negotiations continue, it is crucial to foster dialogue and collaboration among policymakers, researchers, and technology developers to ensure that facial expression analysis remains a valuable tool for scientific advancement, while upholding the highest ethical standards. By doing so, we can maximize the benefits of facial expression analysis while safeguarding individual rights and societal well-being. References - Gudi, A.; Tasli, M.; Den Uyl, T.; Maroulis, A. (2015). Deep Learning based FACS Action Unit Occurrence and Intensity Estimation. International Conference on Automatic Face and Gesture Recognition (FG2015), https://doi.org/10.1109/FG.2015.7284873. - Dys, S.; Malti, T. (2016). It's a two-way street: Automatic and controlled processes in children's emotional responses to moral transgressions. J Exp Child Psychol, 152, 31-40, https://doi.org/10.1016/j.jecp.2016.06.011. - He, W.; Boesveldt, S.; De Graaf, C.; De Wijk, R. (2014). Dynamics of autonomic nervous system responses and facial expressions to odors. Front. Psychol, 5-110, https://doi.org/10.3389/fpsyg.2014.00110. - Lewinski, P.; Fransen, M.; Tan, E. (2014). Predicting advertising effectiveness by facial expressions in response to amusing persuasive stimuli. Journal of Neuroscience, Psychology, and Economics, 7(1), 1-14. https://doi.org/10.1037/npe0000012. - Küntzler, T.; Höfling, T.; Alpers G. (2021). Automatic Facial Expression Recognition in Standardized and Non-standardized Emotional Expressions. Front. Psychol. 12:627561. https://doi.org/10.3389/fpsyg.2021.627561. --- ## How maternal responses support child language development in adversity URL: https://noldus.com/blog/maternal-responses-child-language-adversity Published: 2023-07-10 09:29:00 Description: Studies show that mothers’ responses to their children is crucial for their language development. How does this work for families facing adversity? Researchers Boulton, Levickis, and Eadle aimed to find out. As a parent, you want to support your child in their language development. Research1 shows that how you talk to them and respond to what they are saying is crucial in this. How does this work in families facing adversity? Researchers Boulton, Levickis, and Eadle studied mothers and children facing adversity to find out what helps best in stimulating their language development. Stimulating language development in early childhood Studies show that mothers' responsive behaviors have a positive influence on their children's language development. Specifically, it works well to ask responsive questions, imitate what a child says, and expand on a child's words. There is also some evidence that labeling has a positive effect. What do we mean by these behaviors? For example, a responsive question can be "What's that?" when a child picks up a toy. Imitation means that a parent simply repeats what a child says. With expanding, a parent not only repeats their child's words, but adds something new as well. For example, when a child exclaims "Car!" a parent may respond with "Yes, it's a red car." Lastly, labeling is about naming what a child is seeing, holding, or doing. Different needs for each developmental stage It's important to note that these maternal responses only stimulate language development when it's appropriate for their children's developmental stage. This is in line with Vygotsky's theory of scaffolding2, which states that parents should respond in a way that is slightly above a child's current developmental level - but not too high. This way of responding supports development of language in childhood. Read more about behavioral research with The Observer XT. Parents and children facing adversity With this in mind, it makes sense that children who are vulnerable for difficulties in their language development may benefit from different maternal responses at a certain age. One cohort that is at risk for language delays and disorders is children facing adversity. In the study by researchers Boulton, Levickis, and Eadle, adversity can have different meanings. For example, childhood adversity may mean that their mothers got pregnant young, have dimished health or income, or experience an anxious mood. As a result of childhood adversity, children may experience language difficulties at a young age, as well as long-term consequences such as poorer academic performance and social difficulties. Early intervention is key in preventing developmental problems. That's why the research team studied maternal responses and language development in families facing adversity. Observing mothers' behaviors For the first part of the study, the research team studied 138 mother-child dyads at home, when the children who participated were 2 years old. They were recorded during 8 minutes of free play, of which 300 seconds from the middle of the recording were used for analysis. When these children were 5 years old, another home assessment was completed, this time using the Clinical Evaluation of Language Fundamentals - 4 (CELF-4) to assess receptive and expressive language outcomes. Using The Observer XT, the researchers coded the four maternal responsive behaviors we discussed earlier in this blog post: expansions, imitations, responsive questions, and labels. They studied the relationship between these behaviors and child language outcomes at 5 years old. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Best results for imitation They found that using imitations, responsive questions, and labels was positively associated with child languages scores at the age of 5 years. Surprisingly, they did not find a significant association with expansions. However, for more accurate analysis, they also corrected for other factors that play a role in language development, including children's earlier communication skills. The result? After adjusting for these factors, only imitations were still associated with better child language outcomes. The researchers suggest that these maternal responses fit the developmental stage of this group of children best, while responsive questions and adding labels were less appropriate for them at this age. How to stimulate language development in early childhood This study used behavioral coding to study the relationship between mothers' responses and their children's later language outcomes, in families facing adversity. The results highlight how important it is to consider a child's developmental stage when responding to them. More specifically, it's worthwhile for parents in this cohort to focus on using imitations in their communication, as it's the most effective way to stimulate language development in early childhood. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - [1] Madigan, S., Prime, H., Graham, S. A., Rodrigues, M., Anderson, N., Khoury, J., & Jenkins, J. M. (2019). Parenting behaviour and child language: A meta-analysis. Pediatrics, 144(4), e20183556. - [2] Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press - Boulton, C.; Levickis, P.; Eadie, T. (2022). Maternal responsive behaviours and child language outcomes in a cohort of mothers and children facing adversity. Early Child Development and Care, https://doi.org/10.1080/03004430.2022.2071872 --- ## Must-reads on psychology and behavioral coding URL: https://noldus.com/blog/psychology-must-reads Published: 2023-06-29 08:00:00 Description: We've picked the best blog posts on psychology and behavioral coding from the Behavioral Research Blog. This curated summary lists some of our most useful and popular blog posts on psychology and behavioral coding. We've picked the best blog posts on psychology from the Behavioral Research Blog and curated them together for you! This summary lists some of our most useful and popular blog posts on psychology, behavioral coding, and multimodal research. Psychology top picks Behavioral Research Blog Table of contents - Behavioral coding: What and how - 7 tips to make coding behavioral data more fun - How to study developmental psychology - Research examples of developmental psychology - The power of multimodal research in human behavior studies - How to easily apply multimodal measurement during research with children - Understanding behavioral psychology with The Observer XT Behavioral coding: What and how The coding of your data is the first and most important step in data analysis when studying human behavior. For evaluation and conclusion-drawing, unprocessed data from (video) observations, surveys, or experiments needs to be refined and organized. In order to quantify qualitative data and provide raw data structure, behavioral coding is essential. Your data can be meaningfully categorized thanks to it, which gives it significance and consistency. Learn more about behavioral coding in this blog post. 7 tips to make coding behavioral data more fun You can summarize and highlight key facts that are necessary for the analysis of the observed behavior by coding videos. In terms of what participants say or do, you'll be looking for repetitions, lengths, sequences, similarities, or differences. Behavioral coding helps quantify qualitative data and makes your raw data understandable. Your data is meaningfully categorized by it, which makes it easier to comprehend what it means. But let's face it, it isn't much fun to do and it takes a lot of time. We share 7 tips to make the coding process more effective. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial How to study developmental psychology: methods, designs & tools The scientific field of developmental psychology examines how people develop throughout their lives, concentrating on the physical, cognitive, emotional, and social aspects of development. It looks at how various elements—including genetics, environment, and experiences—shape and have an impact on a person's development from childhood to adulthood. What should you consider when setting up a study in the field of development psychology? Read on to learn more about methods, designs & tools. Research examples of developmental psychology When you are studying developmental psychology, you're studying how people grow and develop, all the way from childbirth to the end of their lifespan. Over the years we've come across many examples of research in developmental psychology, often done with various behavioral research tools. We've put together an overview of research examples in developmental psychology that were published on the Behavioral Research Blog. The power of multimodal research in human behavior studies New tools and insights are being offered by contemporary technologies to researchers to aid in their understanding of human behavior. In today's research, using technologies like video observations, eye tracking devices, and facial expression analysis has become standard practice. By implementing multimodal research, scientists are hoping to gain a more complete and nuanced understanding of human behavior than is possible through the examination of any single modality. Let's explore the challenges in multimodal research, and how to overcome them in this blog post. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn More How to easily apply multimodal measurement during research with children A child development researcher can encounter quite a few challenges when wanting to measure multiple data streams. You probably encounter a lot of challenges while conducting your work as a researcher who interacts with kids. A child may become unhappy during or after testing. He or she may abruptly refuse to remain still, remove the EEG cap from the subject's head, or become preoccupied. How do you deal with these kinds of circumstances, or better yet, how can you stop them from occurring? We asked one of experienced trainers and human behavior consultants for useful tips; you can find them here. Understanding behavioral psychology with The Observer XT Have you ever pondered the reasons behind our behaviors or the motivations that drive our actions? Consider the instances where you find yourself procrastinating, indulging in unhealthy food choices, or forming habits. If these questions intrigue you, then you're delving into the fascinating research field of behavioral psychology. It encompasses the study of the intricate link between our minds and our behaviors, unraveling the complexities that shape our actions. Noldus' The Observer XT software has been designed specifically to help gather and analyze observational data, making it a perfect tool for studying people and their emotional responses to their social and physical environments. Read more: Understanding behavioral psychology with The Observer XT RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## Why you should use FaceReader Online for your human behavior research URL: https://noldus.com/blog/why-use-facereader-online Published: 2023-06-26 12:00:00 Description: Facial expression analysis can help to get objective insights into the emotions of humans. A great tool to use for this is FaceReader Online. If you are involved in any kind of research into human behavior, you’re likely wanting to get insights in how people feel. One way to do this is by choosing observational research, however, this form of research can be time-consuming and subjective. Facial expression analysis can help to get objective insights into people's emotions. A great tool to use for this is FaceReader Online. Why you should use FaceReader Online for your human behavior research Human behavior has fascinated us human beings, probably since our existence. Why do we act the way we do? And how has our behavior and lifestyle changed over the centuries? It's a topic that has been studied extensively. Nowadays, market research and studies into consumer behavior are popular as well, especially amongst anyone working in marketing. After all, don't we want to know how our customers feel and what they want? Using FaceReader Online in market and consumer research Consumer behavior research focuses on studying consumer actions (in the moment) and getting to know the underlying motives. This type of research benefits from systematic observation and a structural analysis, providing key insights to successfully predict consumer preference and consumer buying behavior. Facial expression analysis is one way to get objective insights into the emotions of consumers. A great tool to use is FaceReader Online. Based on proven technology FaceReader Online is an online research tool that allows you to capture responses to websites or videos, based on proven facial expression analysis technology. It's built by the developers of FaceReader, the premier automated software tool for facial expression and emotion analysis that is used at over 1,000 sites worldwide. So, there are no worries when it comes to reliable and stable software for your research. Time is money and you do not want to waste it. You might want to read this: 7 ways to continue your research from home               RESOURCES: Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts  Resources   Provides direct insights into human behavior Capturing emotions by analyzing facial expressions offers additional and objective insights. You can study the impact, appreciation, liking, and disliking of products, mobile apps, websites, commercials, movie trailers, and so on. FaceReader Online delivers you direct insight into human responses – such as joy, sadness, or arousal. Whilst FaceReader is not capable of recognizing or identifying faces or people, it is the ideal online tool for facial expression analysis. It makes it very easy to see which video or website element triggers the desired responses from respondents. It can also be combined with questionnaires (likert scale, multiple choice, open). While your test participant answers the questions, you can automatically measure their facial expressions. The primary reactions of test subjects are recorded, without any bias. Person-specific biases can be calibrated automatically. Emotion data is analyzed immediately in FaceReader, thus saving you valuable time and money. FaceReader Online is also integrated with FaceReader 9.1. A great benefit of this integration is that you can always import your online data into the FaceReader 9.1 software for additional analyses, helping you to gain even more insights in your data. Also read: Facts about FaceReader and automated facial expression analysis Easily incorporated into your research One of the biggest advantages of FaceReader Online is that this version runs online on a cloud server and does not need any on-site installation. As FaceReader only requires a webcam and the easy-to-use software needs no calibration, emotions of test participants are measured unobtrusively. This means that you can test appreciation or impact on-site while participants can stay at home, allowing you to incorporate a much larger number of participants. Simply invite your participants with a personalized email to participate in a remote survey. You can include questions defined in FaceReader Online or choose your own survey software, like Qualtrics. FaceReader Online is developed by Human Insight Services B.V., which is an initiative of VicarVision and Noldus Information Technology. Find out more about FaceReader Online here.               MEASURE YOUR EMOTIONS: What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be  Try now     --- ## FaceReader and different scientific theories on emotion URL: https://noldus.com/blog/scientific-theories-on-emotion Published: 2023-06-26 11:07:00 Description: In this blog post, Tess den Uyl, PhD, Peter Lewinksi, PhD, and Amogh Gudi, PhD from VicarVision outline how FaceReader is designed with scientific rigor and in accordance with responsible AI principles. In this blog post, Tess den Uyl (PhD), Peter Lewinksi (PhD), and Amogh Gudi (PhD) from VicarVision outline how FaceReader is designed with scientific rigor and in accordance with responsible AI principles. FaceReader and different scientific theories on emotion Emotion has been a popular research topic for decades. This is evident by the vast amount of papers on the topic and the scientific debate surrounding it. For example, a well-known discussion is about the existence of a basic set of emotional expressions and whether emotions are universally similar or culturally diverse1. There is currently still not a singular theory on emotion that is widely accepted. Some critics also put doubt on the general idea of classification of emotion based on facial expressions2. We understand this leads to questions about the scientific foundation of FaceReader. In this post, we outline how FaceReader is designed with scientific rigor and in accordance with responsible AI principles, which allows all researchers to use FaceReader within the scientific school of thought that they fit in. Scientific theories of emotion There are many different approaches to researching emotions. This is nicely outlined in Figure 1, created by Gross & Barrett (2011)3. Notice the position on the spectrum of the theories of Ekman (red) and Russell (green). They hail from different schools of thought, which are Basic Emotion Theory and Psychological Construction Theory. These main theoretical perspectives have different viewpoint on what constitutes an emotion, what causes an emotion, how emotions are categorized, and how they are researched. FaceReader offers flexibility to accommodate alternate theories of emotion, enabling users to apply the software within diverse theoretical frameworks and research contexts, thereby broadening its applicability and relevance across various fields of study. Figure 1. Representative theorists on emotions grouped into 4 major perspectives (from Gross & Barrett, 2011). Facial expressions and emotional responses Although these different theories address emotions from a wider perspective, we focus mostly on the relation to facial expressions. Facial expressions are a prominent type of emotional response and the main focus of FaceReader. Many researchers already indicate the relation between facial expression and emotion is not certain, but rather one of probability4. Some researchers focus on the overlapping information and see the universality of emotions (both in individuals and cultures), while others focus on the differences and highlight the diversity within emotional responses. Currently, there are still researchers theorizing from all these different emotion perspectives. Basic Emotion Theory may be the most openly critiqued, but there are still researchers continuing along the lines of it 56. In general, the relevance of facial expression research is shown by the large variety of research on emotional expressions7. There is an abundance of research on the recognition and production of facial expressions, and it has been dominated by primary emotions such as fear and happiness. The outputs that FaceReader generates allow the researcher to study emotions from the theoretical perspective they choose. Build your own interpretation in FaceReader FaceReader is defined as AFCS (automated facial coding system). FaceReader derives output from the following combinations: facial expressions, eye movements, changes in absorption of light in the face (RPPG), and other auxiliary face parameters. FaceReader can then present that output, arranged in four ways. The first two ways are theory-driven, the third is an agnostic way, and the fourth a user-defined way: - 1. Basic Emotion Theory (Ekman) - 2. Circumplex model of emotions with arousal and valence (Russell) - 3. Facial Action Coding System (FACS) - the most cited agnostic measure of facial expressions - 4. Custom expressions - together with inputs such as gaze tracking, relative distance to the screen, and RPPG, the user is allowed to build their own output in a GUI*-based module * A graphical user interface (GUI) is a digital interface in which a user interacts with graphical components such as icons, buttons, and menus. FREE WHITE PAPER Facial Action Coding System Download here the FREE white paper 'Facial Action Coding System (FACS)' and learn more about: - Objective results with FACS - Action Units - Examples using FACS Submit to download By creating custom expressions, researchers can build their own output. They do this by using existing research on established Action Unit combinations that are associated with different facial expressions of emotions. Or they can choose to create additional dimensions (e.g. approach vs. avoidance based on head position) or physical signals, such as smiling without interpretation labels (for example, 'happiness'). After all, the fact that someone is smiling does not necessarily mean that someone is feeling happy. User is end-responsible By constructing FaceReader in a modular way, users can build their own (emotion) classification system. For example, emotion eagerness - how badly does someone wants to buy something - is an emotion closely linked to interest. However, maybe you want to measure something slightly different. In FaceReader, it is possible to build this specific emotion. The main responsibility is now left to the user as the software provides the three most common ways to interpret the output (basic emotions, circumplex model, and FACS). Also, FaceReader gives a structured drag-and-drop GUI to make one's own recognition system. Also read: Creating a custom expression for Engagement: A validation study with FaceReader. Context is necessary for interpretation In addition, the study design of experiments allows the researchers to know a lot about the context (e.g., the stimuli or interaction). This helps with the interpretation. Moreover, researchers can perform additional measurements on participants to further shed light on the experienced emotion, such as physiology and eye movements. FaceReader: from responsible science to responsible AI There are different approaches to researching emotions. FaceReader allows the researchers to choose the theoretical framework they operate in. This way, FaceReader is built from a responsible science approach, where the FaceReader user completely controls how they will interpret and label the expressions and the signals from their participants' faces. Facial expressions are not directly related to the underlying emotional process. Facial expressions are signals, and - like in any measurement tool - there can be a large signal variability. Whether the signal is relevant for a certain process, population, or context should be investigated and validated within each specific research field, using multiple tools. Furthermore, FaceReader is engineered with Responsible AI principles in mind, striving for privacy-by-design and fair algorithms. For example, it does not use sensitive input (e.g., ethnicity) and it cannot execute facial recognition (i.e., recognizing a person as that specific person). In addition, care is taken to limit bias by gathering training datasets with a balanced representation of gender, age, and ethnicity, and by testing for the degree of bias repeatedly. In conclusion, the use of different (theoretical) perspectives and a lively discussion are very normal and important in science. FaceReader can be a useful tool to help the field. References - Ekman, P. (1992). An argument for basic emotions. Cognition & emotion, 6(3-4), 169-200. https://doi.org/10.1080/02699939208411068 - Gendron, M., Crivelli, C., & Barrett, L.F. (2018). Universality reconsidered: Diversity in making meaning of facial expressions. Current directions in psychological science, 27(4), 211-219. https://doi.org/10.1177/096372141774679 - https://www.paulekman.com/blog/darwins-claim-universals-facial-expression-challenged/ - Wallbott, H.G. & Scherer, K.R. (1986). How universal and specific is emotional experience? Evidence from 27 countries on five continents. Social science information, 25(4). https://doi.org/10.1177/053901886025004001 - Barrett, L.F., Adolphs, R., Marsella, S., Martinez, A. M., & Pollak, S.D. (2019). Emotional expressions reconsidered: Challenges to inferring emotion from human facial movements. Psychological science in the public interest, 20(1), 1-68. https://doi.org/10.1177/1529100619832930 - Gross, J. J., & Feldman Barrett, L. (2011). Emotion generation and emotion regulation: One or two depends on your point of view. Emotion review, 3(1), 8-16. https://doi.org/10.1177/1754073910380974 - Scarantino, A. (2015). Basic emotions, psychological construction, and the problem of variability. In L.F. Barrett & J.A. Russell (Eds.), The psychological construction of emotion (pp. 334–376). The Guilford Press. https://psycnet.apa.org/record/2014-10678-014 - Hutto, D.D., Robertson, I. & Kirchhoff, M.D. (2018). A new, better BET: rescuing and revising basic emotion theory. Frontiers in psychology, 9, 1217. https://www.frontiersin.org/articles/10.3389/fpsyg.2018.01217/full - Keltner, D., Sauter, D., Tracy, J., & Cowen, A. (2019). Emotional expression: Advances in basic emotion theory. Journal of nonverbal behavior, 43(2), 133-160. https://link.springer.com/article/10.1007/s10919-019-00293-3 E.g. as indicated by almost 100k papers on facial+expression+emotion on Scopus and ±25k papers on facial+expression+emotion+fear/happiness/anger --- ## Why you shouldn’t use a black box to measure animal behavior URL: https://noldus.com/blog/black-box-research-tool-measuring-behavior Published: 2023-06-23 10:30:00 Description: When studying animal behavior you should avoid using a research software tool that is a black box. What does that mean exactly? It should be easy and user-friendly, but also still flexible. When studying animal behavior, as a researcher we want to rely on using video tracking tools that are reliable, insightful, easy to use, and most crucially to avoid using a research software tool that is a black box. Below we layed out a clear explanation of the potential risks and limitations of using a black box tool in behavioral research, along with questions you can ask your software supplier to make sure this isn't the case! Why you shouldn't use a black box to measure animal behavior Lack of transparency in data processing algorithms Blackbox tools often lack transparency in their algorithms, making it difficult for researchers to understand how the software processes specific readouts. But what does this mean? For example, if a blackbox software tool is used to measure anxiety in an elevated plus maze, the researcher might not have access to the specific algorithms (or settings) that the software uses to track and interpret the animal's movements, but more importantly in this example: what it classifies as anxiety-like behavior. As a researcher it remains your responsibility to determine what readouts are linked to specific behavioral outcomes. We thus don't want the software to measure anxiety, but we want it to measure (and show us) the time the animal spent in the open arms versus the closed arms of the maze (and head dips for example). Without visibility into the underlying algorithms, researchers cannot assess the accuracy and reliability of the results. We want to have full insight into the data and into its acquisition, because a lack of transparency can undermine the scientific rigor of the study and raise concerns about the validity and replicability of the findings. Limitations in customization and adaptability Blackbox tools also often lack flexibility in customization to fit specific research requirements. Studying animal behavior does have a lot of standardized setups, but there are also many situations that need unique experimental setups or specific parameters. A blackbox tool restricts your ability to adapt the software to your specific needs, limiting the exploration of novel research questions or refinement of experimental designs. To quickly summarize, using a blackbox research software tool to study animal behavior can introduce considerable risks and limitations. The lack of transparency, inability to validate results, potential biases and errors, and limited customization capabilities can compromise the accuracy, reliability, and scientific rigor of research findings. Researchers should prioritize using software tools that provide transparency, customization options, and opportunities for independent validation to ensure the integrity of their studies. BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Download So how do we choose the right research tool? What questions should every researcher ask their software supplier? What algorithms and methodologies are employed in the software? Transparency is paramount in scientific research. Request detailed information about the algorithms and methodologies utilized in the software. Understanding how the software processes data and generates insights will allow you to evaluate the reliability and validity of the results. This knowledge empowers you to identify potential biases, errors, or limitations that could impact the accuracy of your findings. How does the software ensure data quality control? Data integrity is crucial for obtaining reliable research outcomes. Inquire about the measures taken by the software to ensure data quality control. Does it have features to detect and correct errors, filter noise, or handle confounding factors? Robust data quality control mechanisms will enable you to eliminate inaccuracies and ensure the validity of your research. Can the software provide comprehensive reports and visualizations? Effective communication of research findings relies on clear and visually appealing reports and visualizations. Ask the software supplier if their tool offers features for generating comprehensive reports and visual representations of the data. This capability allows you to present your results in a compelling manner, facilitating understanding and enhancing the impact of your research. Can the software be customized to suit specific experimental requirements? Each research project has unique requirements. Inquire about the customization capabilities of the software. Can it be tailored to fit different experimental setups, specific animal species, or behavioral parameters? The ability to customize the software ensures that it aligns with your research needs, allowing you to explore novel research questions and refine your experimental designs. Does the software support data export and integration with other tools? Seamless data analysis and collaboration are vital in scientific research. Ensure that the software allows for easy data export and integration with other analysis tools or statistical software. Compatibility with commonly used data analysis platforms enables you to integrate data from multiple sources and enhances the overall efficiency of your research process. Is there a supportive and responsive user community? A vibrant user community can greatly enhance your research experience. Inquire about the availability of user forums, online communities, or support channels where you can seek guidance or share experiences with fellow users. Engaging with such communities provides valuable insights, troubleshooting assistance, and fosters collaboration among researchers in the field of animal learning and memory behavior. Conclusion It is crucial to select the software tool for your research that provides transparency, accuracy, and reliability in data analysis. Choosing the right tool for your research will be key to your success, because measuring animal behavior can be a fickle thing. By having insight in the way your data is acquired you can be confident in the conclusions you draw from your data, and make sure your study is replicable. By seeking clarity from your software supplier on these aspects you can make an informed decision and make confident claims. REQUEST INFORMATION Get in contact with us Are you interested in our behavioral research solutions, and want to get in contact? - Worldwide: Always near to you - Make your project a success - Trust our 30 years of experience Contact us --- ## How to measure emotions URL: https://noldus.com/blog/how-to-measure-emotions Published: 2023-06-23 10:11:00 Description: Measuring or assessing emotions is not always straightforward and easy. How do we view the nature of emotions in the first place? In a previous blog post titled "How emotions are made", I have outlined how neuroscience research in the past decades has shown that our brain gives meaning to our experiences/sensations through concepts such as emotions. So, emotions are created in the brain, rather than triggered by fixed brain circuitry in response to specific stimuli. In a follow-up post, "Why so angry? The role of context and function in facial expression analysis." I explained how context is important when studying facial expressions. How to measure emotions The current blog post will be about how to measure emotions. What tools are available to us to, for example, measure the emotional response of a consumer to a commercial or different products? Can we rely on self-reports only, or do we also have to take into account behavioral measures (e.g., gestures, body position), physiological responses (e.g. heart rate, skin conductance), and facial expressions? In the current blog post, I will outline the concept of emotions in relation to how to possibly measure emotions. Spoiler: measuring/assessing emotions is not always straightforward and easy. Let me illustrate this with a story. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Good grief I had boarded the plane at Amsterdam Schiphol airport as one of the first passengers and was pleased that I had managed to book a seat with extra leg room in one of the emergency exit rows. This would mean that I would probably be able to get a good night's sleep on the 12+ hr. flight that would take me to Changi airport in Singapore. After I had situated myself with a pillow, book, smartphone and noise-canceling headphones, I started watching the other passengers entering the plane. One woman that was part of a group of 4 or so women caught my eye because she appeared to be in grief: her face was very sad, her cheeks were wet with tears, and she wiped her eyes with a tissue. Immediately my brain started to devise all kinds of scenarios to explain why the woman might be distressed: she was on her way to a deceased family member in Singapore, or she might just have heard that a good friend was terminally ill. I felt sorry for her as she really seemed heartbroken. As I tried to radiate my sympathy towards her, the woman turned around to one of her friends, who also had a solemn look on her face, and as soon as their eyes met, both started roaring with laughter. The grieving woman nearly fell down to the floor laughing, her friend had to hold her to prevent that from happening. Laughing and screaming they made their way to their seats at the rear of the plane. I felt amused but at the same time surprised and puzzled. How could I have been so wrong assessing this woman's emotional state? Want to learn more about facial expression analysis? Check out one of our on-demand webinars on FaceReader! The classical view vs. the construction approach The answer lies in how one views the nature of emotions. The picture below shows a continuum with three representative emotion theories from the field of psychology. Figure 1. Three 'zones' with emotion theories throughout the ages: Basic emotion, Appraisal and Psychological construction theories. Explanation about the Basic emotion and Psychological construction theory is shown below. Taken from: Barret, 2016, Navigating the science of emotion. In: Emotion Measurement, edited by Herbert L. Meiselman, Woodhead publishing. In Basic emotion theory (i.e., the classical view), an emotion is understood to be an independent faculty caused by its own specific processes. Something like in the schematic drawing below: Figure 2. The measurement model for the classical view of emotion. Taken from: Barret, 2016, Navigating the science of emotion. In: Emotion Measurement, edited by Herbert L. Meiselman, Woodhead publishing. This classical view assumes a causal mechanism (the emotion essence: Anger, in this example) for the resulting emotion fingerprint, which can be measured by behavioral, facial and physiological (BP = blood pressure) outputs. At the opposite side of the continuum is the Construction approach. The schematic drawing below shows the measurement model for this theory of constructed emotion: Figure 3. The measurement model representing the construction approach to emotion. Taken from: Barret, 2016, Navigating the science of emotion. In: Emotion Measurement, edited by Herbert L. Meiselman, Woodhead publishing. The Construction approach to emotion does not provide mechanisms that cause emotion but only tries to explain how measures might configure to assess an instance of emotion. The brain constructs an emotion based on information from inside the body, information from the outside world, and based on past experiences. "The nearest exit may be behind you" I fell victim to the Classical view when I assessed the tearful woman as being sad. I assumed that something must have happened ('Stimulus' from figure 2) that resulted in the emotion essence Sad of which the emotion fingerprint is tears, red eyes and a sad face. Just like emotion Anger, according to the Classical view, always causes a person to start yelling, scowling and hitting someone. However, this is not how it works in real life, just like the fastest way out of a plane is not always by running forward. Measuring emotions needs variation Variation is the norm when it comes to measures of emotion. One happy person might fall down to her knees and shed tears of joy (like Simona Halep winning Wimbledon), while another person might just smile and look like he is going to get another beer from the fridge (like Novak Djokovic winning Wimbledon). Obviously, this poses a challenge when measuring emotions. Not only individual differences and the context need to be taken into account; optimal measurement of emotion requires a multimodal approach. Assessment of facial expressions, behavioral and physiological responses will not necessarily be correlated, so all need to be measured in order to assess experience of emotion. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more --- ## How to train students in soft skills: Tools and Techniques URL: https://noldus.com/blog/how-to-train-students-soft-skills Published: 2023-06-20 11:30:00 Description: It is essential to provide students with opportunities to develop their soft skills. In this blog post, we will explore some of the best tools and techniques for training students in soft skills. Soft skills are a vital component of student success in both academic and professional settings. Soft skills involve a person's ability to communicate, collaborate, solve problems, manage time, and work effectively with others. These skills are often essential for success in the workplace and can help individuals develop strong relationships with coworkers, clients, and customers. Therefore, they are highly valued by employers, and they can make a significant difference in whether a student is hired or not. As a teacher, it is essential to provide students with opportunities to develop their soft skills. In this blog post, we will explore some of the best tools and techniques for training students in soft skills. FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly Role-playing activities A great way to help students develop their communication and interpersonal skills is by role-playing activities. In these activities, students take on different roles and scenarios, such as a job interview, teamwork communication, a conflict resolution situation, or a customer service scenario. Through these activities, students can practice their soft skills and gain valuable feedback from their peers. Group projects Assigning students to a project that requires working together and achieving a common goal can be an effective way to help them develop their teamwork, collaboration, and leadership skills. In these projects, students need to complete a task or solve a problem. For this, they must communicate effectively. They also need to delegate tasks and collaborate with each other. By working in a group, students can learn how to listen to others and provide constructive feedback. Another benefit is that, this way, they build strong relationships with their peers. Reflective journaling Reflective journaling is a technique that can be used to help students develop their self-awareness and emotional intelligence. In this technique, students write down or share their thoughts and feelings about their experiences, and reflect on how they can improve and grow as individuals. For this, they can use a journal or reflection worksheet or discuss their experiences and reflections in a group. By practicing reflective journaling, students can learn to recognize their own strengths and weaknesses, which helps improve their soft skills. Moreover, they become aware of how to manage their emotions, build resilience, and develop a positive mindset. Feedback sessions The term feedback has already been mentioned a few times in this blog post. Giving and receiving feedback is essential for developing soft skills and offers students, above all, lots of valuable information. However, it can be very scary and intimidating to give and receive feedback. A student can feel overwhelmed by feedback. To create a comfortable and constructive feedback culture, teachers should create a safe environment where students feel safe. The provided feedback must be specific, actionable, and focused on areas for improvement. Besides, the teacher should be open to receiving feedback him- or herself as well. This offers the opportunity to demonstrate how to respond to feedback in a receptive and constructive manner. Video recordings Video recordings allow individuals to record themselves, review their performances, and make improvements based on self-reflection. This works especially well when you define specific goals or events of interest for each recording session, such as improving active listening, body language, or public speaking. By watching the recorded videos afterwards, these goals and the performances can be objectively evaluated. Strengths and areas for improvement can be analyzed and specific actions students can take to enhance their soft skills can be identified. A software tool such as Viso can support teachers in recording training sessions and conducting feedback sessions afterwards. Also read: Why use video feedback in education How to debrief a training session Effectiveness of video feedback in education 10 reasons why AV tool Viso is beneficial for video feedback [INFOGRAPHIC] Online resources There are many online resources available that can help students develop soft skills. For example: - Online courses specifically focused on soft skills development. - Podcasts discussing and providing insights, tips, and strategies into various soft skills. - YouTube channels and videos on topics like effective communication, time management, public speaking, negotiation skills, and other soft skills. - Blogs on personal and professional growth. While these online resources can be valuable, it's important to supplement them with practical application and real-world experiences. The importance of developing soft skills In conclusion, developing soft skills is an essential part of a student's education, and it can help them to succeed in their personal and professional lives. By using tools and techniques such as role-playing activities, group projects, reflective journaling, feedback sessions, video recording, and online resources, teachers can provide their students with valuable opportunities to develop their soft skills. By incorporating these tools into their teaching strategies, educators can help their students develop the soft skills they need to succeed in academic and professional settings. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo --- ## Why so angry? The role of context and function in facial expression analysis URL: https://noldus.com/blog/how-emotions-are-made-angry-face Published: 2023-06-19 12:26:00 Description: Why do respondents show an angry facial expression when evaluating a website or product, when there is no reason to expect them to actually be angry? Read more in this sequel to the blog post "How emotions are made". In a previous blog post titled “How emotions are made”, I outlined how neuroscience research in the past decades has shown that our brain gives meaning to our experiences/sensations through concepts such as emotions. So, emotions are created in the brain, rather than triggered by fixed brain circuitry in response to specific stimuli. I ended the blog with the question: “Why do respondents sometimes show an angry facial expression when evaluating a website or product, when there is no reason to expect them to actually be angry”? In the current blog post I will try to answer this question. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Hint: context and function. Facial expressions have a function in social communication. Humans can ‘read’ a fellow human being’s face to infer the mental state of this other person. This might result in the receiver experiencing and sharing the same emotional state as the sender. Subsequently, this can evoke some kind of action in the receiver, depending on what the emotional state and the circumstances require. 'The Expression of the Emotions' by Charles Darwin There is also a different but important aspect to facial expressions that was already proposed in 1872 by Charles Darwin in his book The Expression of the Emotions in Man and Animals (1). Darwin suggested that facial expressions do not originate in social communication, but initially have evolved as functional adaptations to modify an organisms perception and prepare for action in response to specific stimuli. Let’s look at an example When an early human encountered a potential dangerous situation in the form of a predator it was adaptive to enhance vigilance and perception. This is exactly what happens with a facial expression of fear: the face shows a general ‘expressive widening’ with eye, nose/mouth opening and brow raising, resulting in a better perception of visual stimuli. [Adapted from Figure 2A, page 844, Susskind et al, 2008, Nature Neuroscience (2)] Principle of form Besides this principle of function, Darwin also proposed the principle of form. According to this principle, emotional states with opposite functions also have opposing facial actions. The example of the principle of form that Darwin gives in The Expression of the Emotions in Man and Animals is that of a dog in two opposing states.  In one drawing a dog is shown in a dominant, hostile state. The whole body is upright, head raised, ears pricked, tail is held high and the hairs are raised, especially along the neck and back. In contrast, a dog in a submissive, humble state displays an opposing body posture: the body and head are held low, ears are lowered, the tail is held low and sometimes retracted underneath the body. Investigate fear and disgust These principles of function and form in relation to facial expressions were studied by Susskind et al (2). They looked at fear and disgust, as opposing emotional states, because fear is about sensory vigilance whereas disgust is about sensory rejection. They set about to investigate if this is reflected in differences in the facial expressions associated with fear and disgust. Susskind and coworkers first looked at the shape of the face using vector representations in a computer graphics model of facial appearance. They found that when they created an antiprototype of the classic fear expression, participants reported that it most closely resembled a disgust expression.  When they created an antiprototype of disgust, it most closely resembled a fear expression. This is also displayed in the opposing vector representations of fear (A in the picture below) and disgust (B in the picture below): raised versus lowered brows, increased versus decreased eye aperture and vertical elongation versus compression of the nose associated with raised versus lowered lips.   [Figure 2A & B, page 844, from Susskind et al, 2008, Nature Neuroscience (2)]           Next, they asked participants to judge the size of their visual field relative to posing neutral expressions during a facial-action task in which participants posed both fear and disgust. From the picture below it is clear that the subjective visual field was larger in a fear expression compared to a disgust expression (with a neutral expression in between). The decreased eye aperture in the disgust expression allows the person to better see proximate stimuli that need close inspection before rejection.   [Figure 3a, page 845, from Susskind et al, 2008, Nature Neuroscience (2)]                 They also tested whether sensory rejection, associated with facial expression of disgust, was reflected in a different olfactory intake from a facial expression of fear. They indeed found that the expression configuration had a significant effect on air intake, increasing from disgust to neutral to fear.                 Read more about the possibilities and limitations of FaceReader in our facts about FaceReader blog post. Is it real anger? How do these results affect the interpretation of the angry expression on someone’s face who is looking at a website? At the beginning of this blog post, I gave two hints. The first one was context. In the context of a website, it is unlikely that this creates strong emotions in a participant (of course, depending on the contents of the website). Therefore, the angry facial expression might be better explained by the second hint: function.  One of the main characteristics of an angry facial expression is brow lowering combined with more closed eyes. This is also part of the disgust expression, where we saw that functionally this allows a person to better focus on stimuli close-by. In the website context, the function of the brow lowering + eye closing is to better be able to concentrate / focus on the contents of the website. Why would I make this face? So, next time you are puzzled by FaceReader’s output, think about context and function. Is the emotion detected appropriate within the context of your study? Or is there an individual muscle/AU driving that ‘emotion’ that is likely to blame? For that, you must consider the functional outcome of the expression.  Try it for yourself: Make the same face that you recorded. Ask yourself, ‘Why would I make this face?’ Then you might catch a glimpse of what your brain has just created for you. MEASURE YOUR EMOTIONS: What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now arrow_forward --- ## The impact of handling technique on rodent welfare and scientific accuracy URL: https://noldus.com/blog/handling-rodents Published: 2023-06-15 10:00:00 Description: Proper handling technique is essential in not only ensuring welfare, but also for reliable results. Check out this blog to learn more about how to handle rodents in an experimental setting! Ensuring welfare in laboratory animals is an essential part of keeping animals for research purposes. One major part of this is the interaction an animal has with caretakers and experimenters. Incorrect handling of the animals causes stress, which in turn may affect research outcomes. Therefore, it is important to educate experimenters on the correct handling of animals, and know the effect that different techniques can have on research outcomes. In this blog we will explore the impact of different techniques, their pros and cons, and how this can impact your research by looking at an example study. The pros and cons of different types of handling techniques Many different handling techniques exist, but there are three that seem to be the most prevalent in research with mice. These are tunnel handling, cupping and picking up the animal at the tail base. While, picking up the tail has been the most used method in the past, it also runs the risk of inducing anxiety in the rodents. Furthermore, using the tail grabbing method while not grabbing the tail base, or supporting the body of the mouse causes discomfort. Fortunately, more techniques exist to make the handling less stressful for the animal. In mice, tunnel handling can be used to guide into a plastic tube. A major advantage of this method is that the tube can be placed in the cage. This will enable the animal to familiarize itself to the object. Habituation to the object will reduce stress and make handling easier. Tunnel handling is good method for moving animals between environments. However, while in the tunnel it is more difficult to investigate the animal or perform interventions. Lastly, cupping the hands and letting the animal sit or walk across the open hands is method that can reduce stress compared to using tail handling. The mouse is unrestrained while performing this technique which is the reason anxiety is reduced. However, this method requires familiarization to the handler's hands, which is more time consuming for the experimenter than acclimatizing an animal to a tunnel. In conclusion, while many techniques exist, it is important to weigh the pros and cons in the context of your specific research needs. It is essential to be aware of benefits and effects reduced anxiety has on your research and to report on the methods used to improve repeatability of your study. You can read more about these research methods, and best practices in our e-book linked below! FREE E-BOOK Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download How tickling rats can improve your research We talked about how certain handling techniques can reduce anxiety. In rats, there is another method to reduce the stress, rat tickling. Rat tickling was first developed in 1999 by Dr Jaak Panksepp. This method simulates play fighting behavior, which is a natural occurring behavior in rats. Rats also perform many positive high-pitched vocalizations while being tickled by rats or humans, which is an indicator for a positive affective state. Rat tickling has been used over the years to reduce anxiety in rats while they are being handled by the experimenter. By performing tickling the rat will be less aversive to the hand of the observer and also be less stressed after procedures like injections [1]. Source: Gaskill lab via www.projectbrainlight.org/blog/rat-tickling How do you tickle rats? Rat tickling works by first engaging in dorsal contact (which is also how most of play fights start in rats) and then moving to the so-called pin. To perform the pin, you lift the rat up and put it on its back, restraining it for approximately 3 seconds. After this, the rat is released and the motion can be repeated. Research shows that 15 seconds of tickling is more than sufficient to gain the benefits from the technique, as long as it's done for multiple days before certain procedures, like marking or injections, are going to be performed. It is important to note that tickling works best when the animal is young and hasn't had much contact with humans. Tickling builds a bond between the rat and human, and if the rat is already aversive to humans, rat tickling might actually have a negative effect. Tickling might sound time consuming or laborious, but the benefits are numerous. Not only are the tickled rats less stressed, and thus less affected by stress, they are also easier to handle. This will in turn save time and improve the welfare of your animals. If you want to learn more about rat tickling or learn how to do it, I advise watching this webinar by Dr Megan LaFollette. She explains more in depth the methods and do's and don'ts of rat tickling. The role of experimenter familiarization on mouse behavior Recently a study was performed that look at the influence of (amongst other things) experimenter familiarization on the symptoms of chronic pain [2]. Segelcke et al. exposed groups of mice to varying housing and other conditions. They measured the stress levels in the rats by fecal corticosterone levels and correlated that to the mice physiological ability during behavioral and gait observations. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Mice were familiarized to the experimenter by exposing them to the gloved hand. The mice were allowed to explore the hand and climb onto it. This was done twice a week for 5 minutes per mouse. The researcher used the previously mentioned cupping method for most of the handling. However, when placing the mice into a maze or enclosure the tail base method was used. Using the CatWalk XT for gait analysis, the researchers found that mice that were familiarized to the experimenter had a less pronounced alterations in their gait. Furthermore, Segelcke et al. found that familiarization had an effect on the outcome of certain behavioral tests, when compared to non-familiarized mice. Familiarized mice were less stressed by performing behavioral tests like the elevated plus maze and tail suspension test. In conclusion, proper handling techniques are crucial for ensuring the welfare of laboratory animals. Choosing the appropriate technique based on research needs improves animal welfare and enhances research quality. The type of handling and familiarization to the experimenter will have an effect of behavioral tests and is therefore crucial to consider and document when performing behavioral research. References 1. Cloutier, S.; LaFollette, M.R.; Gaskill, B.N.; Panksepp, J.; Newberry, R.C. Tickling, a Technique for Inducing Positive Affect When Handling Rats. JoVE J. Vis. Exp. 2018, e57190, doi:10.3791/57190. 2. Segelcke, D.; Talbot, S.R.; Palme, R.; La Porta, C.; Pogatzki-Zahn, E.; Bleich, A.; Tappe-Theodor, A. Experimenter Familiarization Is a Crucial Prerequisite for Assessing Behavioral Outcomes and Reduces Stress in Mice Not Only under Chronic Pain Conditions. Sci. Rep. 2023, 13, 2289, doi:10.1038/s41598-023-29052-7. --- ## Examining parent-adolescent interactions during a career discussion URL: https://noldus.com/blog/parent-adolescent-interaction Published: 2023-06-07 11:33:00 Description: As an adolescent you have no idea what awaits you in working life, what you are capable of. Looking for answers to these questions is part of the vocational development, in which parents play a crucial role. As a child, we all want to become a firefighter, kindergarten teacher, nurse, police officer, or astronaut when we're old enough. However, nothing is more difficult than actually deciding which direction you want to take in your career the moment you are faced with that choice as an adolescent. There is so much to choose from and how can you be sure, at such a young age, what is and stays the most fun, challenging, and satisfying job to do? You have no idea what awaits you in working life, how it will go for you, what you are capable of. Looking for answers to these questions is part of vocational development. Effective vocational development requires adolescents to have a clear understanding of their interests, values, and strengths. Interactions always involve emotions Of course, your parents have lots of experience, so discussing career choices with your parents is a logical step in this phase. The interaction between parents and adolescents plays a crucial role in vocational development. Adolescents need to feel that their parents are supporting and reassuring, and that they allow them to make their own decisions. During a dyadic interaction, facial expressions play a crucial role in conveying important information about a person's emotional state. They are a central component of the emotional message that a person conveys. The research team of Bourret, at the University of Laval in Canada, aimed to investigate the behaviors and emotions of parents during career choice discussions with their adolescent child. This study included three objectives: - 1. Identify and describe parental behaviors and emotions manifested by parents and adolescents during discussions. - 2. Examine simultaneous associations between parental behaviors and emotions. - 3. Examine the extent to which parental behaviors and parents' and adolescents' emotions predicted each other during discussions. Observations in a naturalistic environment In this study, parents and their teenage children were invited to a family lab, which is designed to look like a cozy living room. Each of the 42 dyads was asked to freely discuss for 20 minutes topics related to career choice (e.g., career and course selection, pros and cons of choices) while being recorded. The cameras were mounted on the wall to blend in with the decor and not be intrusive. A research assistant controlled the cameras and microphone to capture the best audio and video recordings. The researchers focused on parents' controlling and autonomy supportive behaviors. Did the parents put pressure on their child, e.g. using words such as 'must' and 'should'? Did they induce guild or push towards achieving a goal? Or did they look at the child's perspective and offer meaningful choices if possible? Structured coding procedure To analyze their behaviors, discussions between parents and their kids were coded using The Observer XT. A coding scheme was used to ensure the reliability of behavioral coding. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download The research team saw a great advantage in the fact that The Observer XT can simultaneously display multiple camera views, allowing coders to observe participants' body language from different angles. It made coding much easier to do. Also, data from these multiple camera angles were combined to increase the amount of data available and improve the validity of the emotion classification. The team used FaceReader to analyze facial expressions of the participants. Combining observed behavior and emotions for more detailed insights The methodological approach of the research team allowed for both objective measurement and observation of behaviors and emotions during an interaction. Results showed that both parents and adolescents expressed more negative than positive emotions during the interactions. This highlights the stressful nature of these discussions. Obviously, being insecure can elicit negative emotions. Luckily, during these discussions, parents behaved more in an autonomy supportive way, instead of being controlling with their child. Additionally, the study showed that parents' and adolescents' emotions were dynamically interrelated – indicating emotional contagion. The results of the study showed that talking about career choice with parents can be beneficial for adolescents as parents will mostly provide them with opportunities to feel autonomous and competent toward vocational decision-making. It can help reduce negative emotions and anxiety, as well as foster career exploration. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Reference Bourret, M.; Ratelle, C.F.; Plamondon, A. & Boisclair Châteauvert, G. (2023). Dynamics of parent-adolescent interactions during a discussion on career choice: The role of parental behaviors and emotions. Journal of Vocational Behavior, 141, https://doi.org/10.1016/j.jvb.2022.103837 --- ## Breathe easy, a novel approach to monitoring respiratory activity in zebrafish URL: https://noldus.com/blog/breathing-danioscope Published: 2023-05-30 09:00:00 Description: Researchers from the University of Heidelberg used DanioScope in a novel way to objectively measure breathing in zebrafish embryos and larvae. Take a deep breath, nice, isn't it? Breathing is an essential part of maintaining bodily function for all animals. Therefore, when oxygen homeostasis is disrupted, the body tends to react by adjusting the breathing parameters. However, measuring the breathing movements objectively has been proven difficult in small organisms like zebrafish (Danio rerio) embryo/larvae. This blog will explore a novel implementation of our product DanioScope, by researchers from the University of Heidelberg. Nadine Kämmer and her colleagues used DanioScope to objectively measure breathing movements of zebrafish and compared this method to a manual assessment [1]. Why not just measure breathing manually? Maintaining oxygen homeostasis is very important, as oxygen is needed for the aerobic production of energy from oxidative phosphorylation to maintain cell metabolism). When exposed to a low oxygen environment (hypoxia) fish will tend to increase breathing movements in order to enhance oxygen extraction. Contrarily, when exposed to a high oxygen environment (hyperoxia) they will save energy by breathing less, which also prevents excess oxygen uptake and thus, oxidative stress. However, a potential negative side effect of this decreased breathing frequency, is the build-up of CO2 in the bloodstream, causing acidosis. From this we can conclude that the breathing response is a good indicator of the physiological response of a fish to its environment. However, manually counting breaths in zebrafish is time-consuming and most of all unreliable. Problems with both inter -and intra-reliability play a part in making manual counting unfeasible in the modern age of science. A lack of good objective protocols While objective measures do exist, they are not optimal for most studies. Studies have been performed by attaching electrodes to the operculum (series of bones that provide structural support and provide protection to the gills). However, this method is very invasive and only works on larger fish species and not for embryos and larvae. Electrodes have also been used in a non-invasive way by detecting changes in water conductivity, which is mediated by bioelectrical signals. However, because of the size of fish embryo, their body movements can interfere with the detection of breathing movements and is therefore not suitable for research in fish embryos. Every breath you take, I will be measuring you Nadine Kämmer and her colleagues set out to solve this problem. To compare breathing movements and responses in different life stages of zebrafish, measurements were taken in 4 d old zebrafish embryos and in 12 d old larvae. Fish were short-term exposed (1 h) to different concentrations of lindane (neurotoxic pesticide causing respiratory stress), a solvent control (DMSO), or a negative control in water. Video recording was done while the fish embryos were anesthetized to prevent body movements intervening with the measurements. After transferring the fish to a gel bag, they were acclimatized for 2 minutes, then the fish were video-tracked under a microscope at a 25-fps frame rate. These videos were then used for both manual counting as well as the analysis in DanioScope. Manual counting was done by two observers by looking at the mouth or the operculum of the fish. Here one breath was defined as the movement of one of these body parts (depending on the orientation of the fish). A novel use of DanioScope To facilitate the objective measurements Noldus' DanioScope was used. Originally DanioScope was designed to automatically detect activity in early zebrafish. It can measure many parameters like: Burst activity/ duration, inactivity, but also more specific physiological parameters, like tail coiling and blood/gut flow. It does this analyzing the video for gray scale pixel changes. Since, DanioScope doesn't have a build in detection for breathing some pre and post processing steps had to be undertaken by the researchers. In summary, the frame rate of their imported videos had to be made constant, since DanioScope does not work with irregular frame rates. Then, areas of interest (operculum, mouth, or buccal cavity) had to be drawn in the program, after which the detection settings were optimized for this study. For the exact steps undertaken by Kämmer et al. we refer you to their article. Where do we go now? In general, measurements with DanioScope revealed a much higher breathing frequency in stressed fish when compared to manual counting. This could mean that manual counting could miss instances of breathing movements, especially in higher lindane concentrations, when the breathing frequency increased dramatically, and movements become fast and irregular. Moreover, manual counting in these situations underestimated breathing frequency by up to 250%. With this novel application of DanioScope, the researchers were able to successfully measure both breathing frequency and amplitude in zebrafish larvae and embryos. These objective measures can prove very valuable in zebrafish research, especially in toxicology and pharmacology. It enables researchers to see the effects of certain substances and drugs in different life stages, where this was previously not possible. RESOURCES Read more about DanioScope Find out how DanioScope is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Kämmer et al. concluded by saying that while some steps are needed to perform this analysis with DanioScope, it is an interesting subject for further research and validation. Furthermore, the manual setting of the regions of interest could also prove useful for detecting other small movements in zebrafish, like eye movement or the passage of plastic particles through the intestine and/or gills. We would like to thank Nadine Kämmer for providing illustrations and feedback on this post. If you like to learn more about this methodology you can check out Nadine Kämmer's LinkedIn page or her next paper: Neurotoxic pesticides change respiratory parameters in early gill-breathing, but not in skin-breathing life-stages of zebrafish (Danio rerio), which is currently under preparation for the journal of Aquatic Toxicology. References 1. Kämmer, N.; Reimann, T.; Ovcharova, V.; Braunbeck, T. A Novel Automated Method for the Simultaneous Detection of Breathing Frequency and Amplitude in Zebrafish (Danio Rerio) Embryos and Larvae. Aquat. Toxicol. 2023, 258, 106493. --- ## Resources on Psychology Research: Case Studies, Webinars and White Papers URL: https://noldus.com/blog/white-papers-psychology-research Published: 2023-05-26 12:00:00 Description: At Noldus, we have dedicated ourselves to make the best tools to advance human behavioral research for over 30 years and love to share our knowledge with you! As a behavioral researcher, staying updated with the latest advances and resources in psychological research is crucial for expanding your knowledge and staying at the cutting edge of your field. Fortunately, there are many resources available that can provide valuable insights and practical guidance. In this blog post, we explore a variety of resources to help you on your path as a behavioral scientists. Let's jump in! Resources on Psychology Research Research into understanding human behavior and perception has been around for centuries. The science of behavior and mind was already studied by the ancient Greek philosophers. Nowadays psychologists rely upon data to make sense of the world. By exploring webinars, case studies, white papers, and other resources, you can enhance your knowledge, gain insights from real-life examples, and discover the latest advancements in psychology research. At Noldus, we have dedicated ourselves to make the best tools to advance human behavioral research for 30 years, and love to share our knowledge! Make sure not to miss these webinars, white papers, case studies and other resources on psychology research! Case studies and white papers on psychological research Look for case studies published in reputable psychology journals or books. These real-life examples provide valuable insights into the application of research methods and the complexity of human behavior. Visit websites of renowned research institutes and think tanks, such as the National Institute of Mental Health (NIMH). These organizations often publish white papers and research reports that address specific areas of psychology and provide comprehensive analysis and evidence-based recommendations. We have also created multiple case studies and white papers on topics related to (developmental) psychology and behavioral research. CASE STUDY: Infant behavior research Interaction between children and their parents is a classical study object in developmental psychology, pediatrics, and child psychiatry. At the Institute of Developmental Neurology of the Beatrix Children's Hospital of the University Medical Center Groningen researchers developed an observation protocol to quantify in a systematic way the contents of the physiotherapeutic sessions. They looked into setting up an observation protocol, and how to compare the effect of different interventions. It will help you understand why systematic observations are used to measure the effect of a new intervention. Download this case study here. FREE WHITE PAPER Tools for Infant Studies Download the free White paper to learn more about the software tools available for infant studies. - Video observations to capture behaviors - Coding behaviors accurately - Unobtrusive emotion analysis Download WHITE PAPER: Autism research and The Observer XT Research on Autism Spectrum Disorder has increased enormously over the years. The extensive research has led to many findings and has resulted in new understandings of how to detect ASDs early in life, setup therapies, stimulate developmental processes, and much more. Autism is the most common Autism Spectrum Disorder, and knowledge is key to developing a better understanding of the disorder. In this white paper you will learn more about how and why observational research methods are used in autism research worldwide. The two most important questions that often come up in these kind of research: Why observe behavior and how to observe behavior in a structured way? Download your free white paper on autism research here. FREE WHITE PAPER Autism Research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Download WHITE PAPER: How to Build an A/V Lab Among the methods used for collecting data, video observation is a non-invasive form. It enables psychologists, and other observers, to capture the (inter)actions of the subject(s) remotely without distracting them. Another benefit is the unlimited number of times video recordings can be re-played, in order to make sure you didn't miss anything. An AudioVisual lab is designed to allow you to observe your test participants unobtrusively, in an environment similar to your test participant's natural surroundings. Get your white paper on how to build an A/V lab here: FREE WHITE PAPER How to build an AV lab Do you want to learn more how to set up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download Webinars and online courses As a behavioral researcher, the key to staying at the forefront of your field lies in accessing and utilizing the wealth of available resources. Webinars can be very helpful in getting quick updates on research tools and methods. WEBINAR: Research tools in Developmental Psychology Researchers in developmental psychology examines the various stages of life, from baby to adolescent, adult and finally to the elderly. They look at how and why people do the things they do, and observe people's behavior. In the Noldus Webinar about Research tools in Developmental Psychology, we explain how our research tools can be used to study behavior. How do children acquire language, how do learning behaviors develop, and how do they interact socially with other people, for example in parent-child interaction? Curious? Watch the webinar on demand now from our webinar section on our website (go over the Replay Human Behavior Research Webinars for all on demand webinars). Other webinars and online courses - American Psychological Association (APA) Webinars: APA offers a range of webinars on diverse topics, including research methods, data analysis, ethics, and emerging trends in psychology. These webinars provide in-depth insights and expert guidance from renowned professionals in the field. - Coursera: Explore online courses from reputable institutions, such as Yale University's "Introduction to Psychology". These courses provide foundational knowledge and practical skills for conducting psychological research. Psychology conferences Last but not least: conferences are a great way to combine work, knowledge, and social interaction with your peers. To give you some insight in the best psychology conferences that take place in 2023, we've put together this extensive list of meetings, sorted by region: - The Ultimate List of Psychology Conferences in 2023 --- ## 5 tips to optimize your facial expression analyses URL: https://noldus.com/blog/how-to-optimize-facial-expression-analysis Published: 2023-05-18 11:00:00 Description: Are you involved in emotion recognition and facial expression analysis? These 5 tips will guarantee the best results! Are you involved in research with emotion recognition or facial expression analysis? These 5 tips will guarantee the best results! How to optimize your facial expression analyses Emotion data provides crucial insights that allow researchers to gain insight in complex human behaviors in greater depth. Facial expression analysis software like FaceReader™ is ideal for collecting this emotion data. Do you want to get the best results from your experiments? These 5 tips will help to optimize your facial expression analyses. 1. The whole face should be visible You may normally offer your test participants something to eat or drink during the test to make them feel comfortable. However, when eating or drinking, the test participant blocks part of the face with his/her hand and the cup/glass/spoon. So, make sure the test participant finishes his/her cup of coffee before you start the test… unless, of course, the purpose of the test is to see a reaction to a new food or beverage! There are still steps you can take to minimize interference: if testing a soda, for example, test participants could drink through a straw, which would ideally be transparent and colorless. A tip to consider: Some people have a natural tendency to touch their face without realizing it. You may want to warn the test participants to keep their arms on the table throughout the test in order to get the best possible results. 2. Make sure the test participant looks into the camera Rotation of the face is OK with automatic facial analysis, but it should be limited (<40°). That means that you should sit opposite of the test participant and not next to him/her if you want to ask questions during the test. In a social interaction setting (medical student – patient or consultant - client interaction) you would ideally position the camera on the conversation partner’s shoulder.  With this set-up, people almost look straight into the camera when they talk to their partner. In practice, this may not always be possible. But if you put the camera a short distance away, at the same height, with direct sight line to the participant’s face, you have a working solution. A tip to consider: In a taste-test study, you can use a cup or bowl holder so the dish is closer to the face and the test participant does not need to tilt the head downward as much to taste the drink/food. Another tip to consider: If you're asking clients to read instructions or answer a questionnaire, you can present this information on a screen with the relevant text and attach the camera to the screen, or use an on-board webcam. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download 3. Test people in their natural environment When you include emotional expression analysis in your research, you hope to see some displayed emotions. “All my test participants looked neutral throughout the test” is an often-heard complaint. It may help to test people in their home or other familiar environment (like a restaurant, school, office, etc.). Running your tests in the test facilities at your office has the obvious advantage that you can control the test conditions much better than out in the field. The downside, however, is that people may react differently to your stimuli. Particularly when you're interested in emotions, this is a major factor to take into account. Noldus has created new software, FaceReader Online, to allow testing to occur at home. With FaceReader Online, participants can view an advertisement or series of images/ads at home, with all results sent directly to you upon completion. You can also import your FaceReader Online data into the FaceReader 9.1 software for additional analyses, helping you to gain even more insights in your data. A tip to consider: Testing people via an online service also allows collection of data from people in remote locations, which can help to gather more diverse demographic data. 4. Real products are best What approach is best to use when testing your product? You can show test participants pictures of your product, videos/commercials featuring your product, or you can give them the real product to view. What we have seen is that real products elicit greater responses. While having the real product at hand to view it is preferable to seeing a photo, real-life use is even more preferred.  So, if you wanted to know whether your test participants like your new healthy flour mix, for example, you can ask them to bake pancakes in a test kitchen, and observe the displayed reactions during the baking process and the consumption phase. A tip to consider: Making the environment as natural as possible when doing this type of testing will elicit the most “real” emotional response! Interesting read: Three ways to understand consumer emotions 5. Present more than one stimulus If you want to test your new product (like a commercial, beverage, etc.), it is best to embed it in a series of other products. In this way the test participants do not concentrate fully on the focus product and will respond in a more natural way. This also allows the participant to evaluate your product compared to similar, and to allow the emotion response to be evaluated compared to other products. A tip to consider: Be sure to randomize the order in which you present the products. There you have it: five useful tips to help optimize your facial expression analysis. Want to learn more about facial expression analysis or how FaceReader works, and what's possible and impossible to do with FaceReader? Make sure to check these resources! RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources --- ## Understanding mouse social interaction using objective measures URL: https://noldus.com/blog/social-interaction-livemousetracker Published: 2023-05-17 11:00:00 Description: Measuring social interaction is an important, but due to technical limitations, often overlooked part of behavioral research. Live mouse tracker was designed to alleviate this problem. Recently we released a new version of our state-of-the-art video tracking software, EthoVision XT 17.5. One of the main new features in this release is the ability to easily import and analyze data derived from the Live Mouse Tracker (LMT). LMT was developed by the Human Genetics and Cognitive Functions unit of Institut Pasteur, is a solution to a problem that has made measuring social interaction difficult, namely how do you track multiple animals' behavior at the same time? Why measure social interaction? But, why is measuring social behavior important in behavioral neuroscience? In humans, social interaction is an important read out of many neurological disorders (like autism spectrum disorder, Alzheimer's disease, etc.). Therefore, when developing treatments for these disorder with animal models, it is important to also take social behaviors into account. Even though mice and rats are not humans, they are social animals and perform social behaviors. Measuring only individual paradigms runs the risk of not being able to assess the complete effect of certain treatments. Thus, assessing social behavior is important, however often overlooked, in behavioral assays. Social behavior in rodents is multifaceted, and can encompass anything from aggressive to cooperative and parental interactions. Measuring social behavior in an objective way is quite complex. Traditional behavioral observations carry the risk of observer bias, and conventual observation software's are not able to distinguish multiple animals from each other in a reliable way. These issues made observing social interactions difficult and halted the development of using social interactions in behavioral neuroscience for quite some time. What is Live Mouse Tracker? The Human Genetics and Cognitive Functions unit of Institut Pasteur has developed a tool that achieves to overcome these problems. Live Mouse Tracker is used for real-time behavioral analysis of groups of up to four mice in a dedicated set-up. Through the use of RFID, computer vision, and machine learning, LMT is able to track multiple mice at once and extract their behaviors as well as account these parameters to individual mice. Previously, data from LMT had to be analyzed using convoluted Python scripts, which is complicated for many of the LMT users. With the release of EthoVision XT 17.5, LMT data can easily be imported, which brings all of the functionality of EthoVision XT to LMT data. EthoVision XT allows for easier organization of trials, which in turn enables easier data filtering, nesting and analysis. Furthermore, with EthoVision XT, LMT data can be visualized with graphs and integrated data plots. RESOURCES: Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Using social interaction to study affectionate touch So, what type of tests are possible with Live Mouse Tracker? As of the writing of this blog, LMT has appeared in 50 published articles, one of which we will highlight here. How do we know that a gentle touch is affectionate, and that a slap to the face is aggressive? It's all in the way our body perceives the signals coming in. However, the way we perceive social touch signals can be disrupted by certain neurological disorder, like Autism Spectrum disorder. Understanding the physiology behind these disorders is key in finding treatments for them. Therefore, it is important to know the underlying mechanisms of touch in a social context. Huzard et al. used the LMT in their study researching the role of certain mechanoreceptors in affective touch and social interaction. They used chemo genetics to increase the function of C-LTMR (a sensory neuron believed by Huzard et al. to be important in perceiving touch sensation with a social context), and bred C-LTMR knockout mice, to investigate the functioning of C-LTMR in various social and sensory behavioral tests. Influence on the social behaviors of mice From their experiments, Huzard et al. found that C-LTMR indeed has an influence on the social behaviors of mice. The knockout strain reduced active social interactions, which resulted in more isolated behaviors. On the contrary, activation of C-LTMR led to an increase in social interactions between mice. Therefore, they conclude that C-LTMR plays an important role in the regulation in pro and anti-social reactions to conspecific animals. The LMT gave the researchers the opportunity to define the nature of these increased or decreased social interactions. They were able to classify the interactions into passive and active contacts. From this they found that the knockout mice did not avoid passive interactions (walking by, or reciprocal interactions) but they were not actively seeking for social contact with other mice themselves. This precise analysis of the behaviors that Live Mouse Tracker provides, gives a more complete insight into the complex nature of social behavior. A more complete picture of the effects of certain treatments or interventions in mice can give a more complete translation to the possible effects in humans. Innovations like the LMT are crucial in moving the field of behavioral neuroscience forward, and we are excited to provide LMT users with a sophisticated, and user-friendly way to import and analyze their data through EthoVision XT. FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial --- ## How do people with antisocial and psychopathic traits process emotions? URL: https://noldus.com/blog/emotion-processing-antisocial-psychopathic Published: 2023-05-16 09:14:00 Description: Understanding more about emotion processing in people with antisocial personality disorder and psychopathic traits can improve interventions. The team of researcher Kyranides studied how facial mimicry can help. What happens when you're unable to show others how you feel, or to understand the emotions of other people? We need these social skills to function in society, work, or school, and to build interpersonal relationships. Unfortunately, this is exactly what people with antisocial personality disorder (APD) and psychopathic traits have trouble with. Understanding more about how these individuals process emotions, and how to strengthen these skills, can help to improve interventions. That's why researcher Kyranides and her team studied how well people high in APD symptoms and/or psychopathy express and recognize emotions. In one condition of their study, they also asked participants to imitate facial expressions before performing their task. Curious about the effects? Read on to find out! Want to know about FaceReader's latest features? Check out what's new in FaceReader! What are psychopathy and antisocial personality disorder (APD)? Antisocial personality disorder (APD) and psychopathy have considerable overlap, but there are also some important differences. People with APD generally show no regard for the rights and feelings of others. They may behave impulsively, irresponsibly, and even violently. A subset of people with APD also have psychopathic traits, which means they lack empathy and have a tendency to manipulate others. They also have trouble expressing and interpreting emotions. However, not everyone with APD has these traits of psychopathy. Why emotion processing is so important Our facial expressions play an important role in interpersonal relationships. Subtle nonverbal cues tell you about the emotions of others, or show someone else what you're thinking or feeling. This helps to signal what you're expecting of each other. Maybe you want someone to answer a question or wait their turn speaking, or the other person expects you to smile or to understand they're feeling sad and need some comfort. For people with psychopathic traits, research shows, this is very difficult. It's still unclear whether people with APD experience the same difficulties, or if it's specific for psychopathy. By learning more about the differences between people with and without psychopathic traits, and the way they might improve their emotion processing, interventions for APD can be improved. The role of attention in emotion processing Experts think that emotion processing difficulties in people with psychopathic traits reflect an attentional bias. Specifically, they suggest that these people are highly goal-oriented and have difficulty extending their attention to information that doesn't relate to their goals. This includes social interactions. So, if attention is part of the problem, why not steer people's attention to emotional information? As part of their study on emotion processing in people with psychopathic traits and/or APD, researcher Kyranides and her team asked participants to mimic the facial expressions they saw in an emotion recognition task. Not only does this instruction direct people to emotional cues, but it may also strengthen empathy, as research shows that facial mimicry and empathy are related. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Facial expression analysis Their study included 107 young adults, divided over four different groups: low-risk, psychopathic traits, APD symptoms, and psychopathic traits + APD symptoms. All participants completed an emotion recognition task. They received three different kinds of instruction, in randomized order: imitate the facial expressions in the task, suppress any facial responses of your own, or simply to respond to the test items (no other instructions). While performing the emotion recognition task, participants' facial expressions were recorded using FaceReader. This way, the research team could assess their responses to the different instructions, as well as analyze their emotional expressivity. Analyzing emotion recognition and expression The team examined differences in emotion recognition between groups. Similar to earlier research, they found that participants with APD symptoms and the group with both APD and psychopathic traits recognized emotions less accurately than the low-risk group. Interestingly, the group with only psychopathic traits performed similarly to controls. Using FaceReader, the research team also analyzed how the different groups expressed positive and negative emotions. They found that people from the group with combined APD and psychopathic traits expressed more anger compared to the group with only psychopathic traits. Surprisingly, the APD group expressed more sadness than the group with combined symptoms. These results highlight the importance of considering groups with isolated or co-occurring APD symptoms and psychopathic traits. They also suggest that emotion regulation interventions, like anger management, could be beneficial for individuals with combined APD and psychopathic traits. Imitation improves emotion recognition So, what's the effect of different instructions? The results show that participants were most accurate in the emotion recognition task during imitation. Additional analyses show that these results were most pronounced in the APD group and the group with combined APD and psychopathic symptoms. Overall, these results indicate that imitation of facial expressions helps to improve accuracy on emotion recognition, again providing valuable information for designing or improving interventions. Reference Kyranides, M.; Petridou, M.; Gokani, H.; Hill, S.; Fanti, K. (2022). Reading and reacting to faces, the effect of facial mimicry in improving facial emotion recognition in individuals with antisocial behavior and psychopathic traits. Current Psychology, https://doi.org/10.1007/s12144-022-02749-0 --- ## How emotions are made URL: https://noldus.com/blog/how-emotions-are-made Published: 2023-05-11 15:08:00 Description: Neuroscience research in the past decades has shown that our brain gives meaning to our experiences and sensations, through concepts such as emotions. How to measure emotions of respondents I regularly get this question from clients: “How do we measure the emotions of our respondents?” At this point, I explain that in order to get a good picture of the respondents’ emotional responses, you can use The Observer XT to monitor their overt behavior, FaceReader to measure their facial expressions, and psychophysiological measures to get an idea of what occurs on the inside. To combine and streamline these multiple types of measurements on one platform, NoldusHub® is the way to go.  After data has been acquired using one of these tools, another question often pops up: “Why does FaceReader measure so much anger?" Our product / website was not designed to elicit anger?!” FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download How emotions are made Total confusion The first time I got this question, I was also confused. Surely the respondents were not truly angry, so why would they show an angry facial expression? It wasn’t until I read Lisa Feldman Barrett’s book “How Emotions Are Made (The Secret Life of the Brain)” that I fully understood how the classical view on emotions causes this confusion. In this well-written book, Dr. Barrett convincingly argues that the classical view on emotions and how our brain works is based on a number of flawed premises that have been disproven by neuroscience research in the last two decades. Two flawed assumptions about emotions and our brain are: - Each emotion is located in a specific part of the brain. For example, the amygdala (part of the limbic system, which plays a role in processing emotional reactions) is supposed to be the ‘fear center.’ - When the right stimuli are presented, a specific emotion is triggered, accompanied by a fixed facial expression. First of all: read the book! Dr. Barrett does such a great job in explaining how our brain works and how emotions are made. Emotions are created by our brain Neuroscience research in past decades has shown that emotions do not have ‘fingerprints’ in the brain. Different networks in the brain can create the same emotion. And yes, emotions are created by our brain. It is the way our brain gives meaning to bodily sensations based on past experience. Different core networks all contribute at different levels to feelings such as happiness, surprise, sadness, and anger. Figure 1. Picture of seven core networks that form ingredients for the ‘recipe’ for feeling anger. A line closer to the perimeter of the circle indicates that this network shows a higher activity for the feeling of anger (this picture is a screenshot from a video created by Houghton Mifflin Harcourt, hmhco.com). What is going on: sensing and past experience Let me try to explain a bit more. The interoceptive network in the brain continuously monitors your bodily sensations: your heart beating, your lungs filling/emptying, your intestines working, and your stomach (slightly) aching. Your brain (locked in its dark, silent box we call the skull) tries to figure out what these bodily sensations mean based on both the information it receives from the outside world through your senses and based on past experience. Figure 2. Picture representing how our brain (stuck inside the dark box called skull) uses current and past information to make sense of what is going on. Information from the outside world comes in through the senses (air pressure, light, chemicals). Information from the inside world (aches, shivers, tightness) comes in via the interoceptive network. Past experiences are stored in the brain (this picture is an adapted screenshot from a video created by Houghton Mifflin Harcourt, hmhco.com). The main task of the brain is to keep you alive and well. To achieve this, it constantly monitors your inner and outer world and redistributes energy to the body part that currently needs it the most. While monitoring the outside world, the brain is not just a passive spectator. How are emotions created in the brain Neuroscience research has shown that the brain actually predicts and simulates the outside world. For this, our brain uses concepts. For example, when I mention the word/concept ‘apple,’ your brain immediately pictures an apple. It might be red, or green, and your brain might even simulate the touch of the smooth surface against your hand. If you’re hungry while reading this, try simulating the crunchy sensation and sweet/tangy taste when taking a bite out of your simulated apple. Figure 3. Schematic representation of the brain’s basic process of monitoring the world. Based on ‘concepts’ that are built by past experiences it predicts and simulates the outside world. Your brain then compares the simulation with the real-world situation coming in via sensory input. If there is a mismatch, either the concept is changed, or the sensory input (see the snake-example below) (this picture is a screenshot from a video created by Houghton Mifflin Harcourt, hmhco.com). Let’s apply this to emotions. For example, you take a walk through a forest, and you suddenly hear/see the rustling of leaves. Based on past experiences, your brain predicts what’s going on. In this case, there might be a snake nearby in the bushes. Your brain starts to simulate the sights and sounds of a snake and prepares your body for action, i.e. running away as fast as you can. To this aim, your heart rate goes up, you start breathing more deeply, and you start to feel agitated. The meaning your brain gives to this feeling might be ‘fear’ (which can be considered as just another brain concept, just like, ‘apple,’ ‘mother,’ ‘dog,’ or ‘chair’). Three possible behaviors as outcome There are three possible outcomes of this situation. A snake slithers out from underneath the bushes, and you make a run for it. Fear was your brain’s best guess for what just caused your bodily sensations. The second possible outcome is that there is no snake, and it was just the wind. In this case, your brain corrects it prediction (a snake in the bushes), your body calms down again, and you make sense of your agitated feeling in some other way. The third less likely but still possible outcome is that there actually is no snake but you still see one. In this case, your brain does not correct the prediction (see outcome two), but your brain’s simulation overrules the sensory input. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources What does our brain tell us? To sum it all up, according to Lisa Barrett our brain continuously produces predictions and simulations, and so we experience a world of our own creation held in check by our sensory world. Our brain gives meaning to our experiences/sensations through concepts such as emotions. Can we possibly measure emotions / the emotional state of a person? Stay tuned for a series of blogs that will address the question: How to measure emotions. References Barrett, L. F. (2017). How emotions are made: The secret life of the brain. Boston, MA, Houghton Mifflin Harcourt. --- ## Are fish empathic? URL: https://noldus.com/blog/empathy-in-fish Published: 2023-05-11 12:00:00 Description: Ever wondered if fish can be empathetic towards each other? Find out in this blog how oxytocin plays a role in fish behavior! Oxytocin is famously known as the 'love hormone' because it is released when people touch each other and it enhances bonding. It is also important in childbirth and stimulating milk production in new mothers. Moreover, it also affects social behaviors such as cooperation. Oxytocin enhances trust by suppressing activity in the amygdala, which is the area of the brain regulating anxiety. Oxytocin can also help counter negative reactions. For example, if a partner of a prairie vole dies, it shows depressive-like behavior. However, if that prairie vole is given oxytocin, then the depression is prevented [1]. Furthermore, oxytocin has also been shown to reduce anxiety in embarrassing situations. Oxytocin plays a key role in empathy, and it is that aspect which we will look at further in this blog. How does Oxytocin play a role in empathy? Empathy is the ability to recognize the emotions that other people have and to respond appropriately. It is why we smile when we see people who are happy and why we are upset when we see someone in pain. Empathy is enabled by using a group of neurons in the brain called mirror neurons [2]. When you see someone smiling, your mirror neurons for smiling fire. They are the only neurons which are activated by the actions of other people rather than ourselves, and are the basic reason why we feel the emotions of others. Providing oxytocin to people (by nasal spray) improves a subject's ability to be empathetic. They recognize emotions in facial expressions better and they are more likely to have a generous reaction. Better recognizing the facial expressions can be tested by making it difficult, for example by only showing the eyes rather than the whole face. Compassion towards the group Improved empathic responses, as a result of oxytocin, occur particularly when someone perceives the person that they are responding to as being in the same social group as themselves. Oxytocin can have an almost opposite effect on interactions between people of the same in-group and on responses to outsiders. If someone is perceived as being an outsider, then oxytocin can actually decrease the empathy towards them. This phenomenon indicates the importance of education and a broad experience to people outside our usual social group. This will enable a better understanding of people who look or act differently from ourselves and increase empathetic feelings towards them. Empathy in other animals I don't think it will be very surprising for many readers of this blog to hear that other mammals also have empathy mediated by oxytocin. Anyone who has petted a cat or dog will understand that. The stroking action stimulates oxytocin production, which causes bonding. What is perhaps more surprising, is that oxytocin also affects empathy for other animal groups, even including fish. We don't think of fish as showing emotions because they don't have facial expressions like mammals. However, it is now well-established that fish feel pain in a very similar way to mammals [3], so there is no reason to suppose that they don't experience other emotions as well. The effect of oxytocin in fish But, how does oxytocin work in non-mammals? Ibukun Akinrinade and her colleagues investigated the role of oxytocin in empathy in zebrafish [4]. They looked at fish displaying the same emotions (fear or distress) as other fish which they were watching, which is called emotional contagion. They measured fear behavior of the fish using Noldus' EthoVision XT video tracking software. Fear is characterized by erratic movement followed by freezing (not moving at all). Erratic movement was measured by EthoVision using the definition of when the fish had an acceleration of more than 8 cm/s² and more than 5 changes in direction of more than 90° per second (angular velocity). Freezing was categorized by EthoVision when the fish were swimming less than 0.2 cm/s. When fish are distressed, they emit an alarm substance, and this was also tested in the experiment. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Social transmission of emotions Their experiments had three treatment groups to investigate the social transmission of fear. One group of fish could see other fish which had been exposed to the alarm substance (and thus those watched fish were showing fear behaviors). A second group were exposed to the alarm substance directly, and the third group was a control (no alarm substance and no sight of other distressed fish). Both the fish exposed to the alarm substance and the fish watching the fearful fish copied the fearful (erratic and freezing) behaviors but those in the control treatment did not. An advantage to a fish of copying the fearful behaviors of other fish is that if the fearful behaviors are caused by the fish seeing a predator, then other fish can respond appropriately without having to also see the predator, just like with alarm calls by birds. Genetically modified fish So those tests show that fear behaviors can be transmitted from one fish to another (which could be counted as empathy) just by watching. However, they do not prove whether or not oxytocin is involved. To look into that, the researchers made use of one of the reasons why zebrafish are so popular with scientists. It is possible to obtain all sorts of different genetic lines of zebrafish. In this case the researchers used three different mutant lines. One was fish which were unable to produce oxytocin (called oxt). The other two were for fish which were unable to detect oxytocin with two different receptors in the brain (oxtr and oxtrl). None of the fish in those three mutant lines increased their fear behavors when they were exposed to a distressed shoal of fish. If the fish which could not produce oxytocin themselves were injected with oxytocin, they did show the fear-like behaviors when watching other fish showing fearful behaviors. Those experiments elegantly and conclusively prove that both that fish show empathic behaviors and that their empathy is regulated with oxytocin. The actual experiments were more complicated than described here. So, if you are interested, take a look at the study by Akinrinade et al. Oxytocin and evolution Because fish and mammals have the same complex mechanism for empathy, it is likely that it evolved millions of years ago, before fish and mammals split from each other in the evolutionary tree. If empathy had evolved independently in fish and mammals, then it would have had most likely a different working mechanism. Birds and reptiles don't have oxytocin, instead they have mesotocin, a hormore which is chemically similar to oxytocin and plays a similar role in regulating their behavior [5]. The fact that this has been conserved over such a long time, indicates just how important it must be. Social interaction often plays a key role in the evolutionary success of animal species, and empathy is clearly a key factor in that. References [1] Bosch OJ, Young LJ. Oxytocin and Social Relationships: From Attachment to Bond Disruption. Curr Top Behav Neurosci. 2018; 35:97-117. doi: 10.1007/7854_2017_10. PMID: 28812266; PMCID: PMC5815947. [2] Rizzolatti G, Craighero L. The mirror-neuron system. Annu Rev Neurosci. 2004; 27:169-192. doi:10.1146/annurev.neuro.27.070203.144230 [3] Sneddon Lynne U. Evolution of nociception and pain: evidence from fish models. Phil. Trans. R. Soc. 2019; B374: 20190290. http://doi.org/10.1098/rstb.2019.0290 [4] Ibukun Akinrinade, Kyriacos Kareklas, Magda C Teles, Thais K. Reis, Michael Gliksberg, Giovanni Petri, Gil Levkowitz, Rui F. Oliveira. Evolutionarily conserved role of oxytocin in social fear contagion in zebrafish. Science379. 2023;1232-1237. doi:10.1126/science.abq5158. (The EthoVision parameters are described in the supplementary materials). [5] Martina Stocker, Jonathan Prosl, Lisa-Claire Vanhooland, Lisa Horn, Thomas Bugnyar, Virginie Canoine, Jorg J.M. Massen, Measuring salivary mesotocin in birds - Seasonal differences in ravens' peripheral mesotocin levels. Hormones and Behavior. 2021; 134, 105015, https://doi.org/10.1016/j.yhbeh.2021.105015. --- ## Noldus top tips! Our latest must-read animal blogs URL: https://noldus.com/blog/noldus-top-animal-blogs Published: 2023-04-27 15:00:00 Description: Dive into our latest collection of top behavioral research blogs! Discover fascinating studies and learn how Noldus tools can advance your research. We regularly post about interesting studies, and how other researchers use Noldus tools to measure behavior in animal models. And although some setups are pretty straightforward, there are a lot of setups which definitely are not. At Noldus we aim to offer this flexibility through our product line, but also the expertise of our (scientific) staff to give you the best possible foundation for your research set-up and analysis. Our latest must-read animal blog posts So here you go! A carefully curated summary of some of our most popular blogs of the last few months you might have missed. Learn about how to set up your behavioral suite, to studying complex behavior in rats, and more. Take your pick! 5 steps to set up the perfect behavioral suite Unlock the key to setting up an ideal behavioral suite! We describe 5 crucial steps, such as camera selection for EthoVision XT compatibility, choosing a powerful workstation, integrating external equipment like optogenetics, selecting the right maze, and leveraging Noldus' on-site installation and training services. Improve the quality of your data and advance your research with these expert insights. When setting up your lab it is important to make well-informed decisions, considering various components that you might not have previously considered. By following the expert advice shared in this blog, researchers can ensure a smooth set-up process and optimize the quality of their behavioral data. Read the full blog here! What you need to know about the CatWalk gait analysis method Discover the history and technology of CatWalk XT! CatWalk XT is an automated gait analysis system for rodents, initially created for research on rat models for spinal cord injury. The system has since expanded to other species, such as mice and marmosets. Learn how the CatWalk XT system has evolved since its inception in 2001 by Dr. Frank Hamers to its present state, featuring green LED Illuminated Footprints technology and a high-speed digital camera. Understand how the accompanying software analyzes over 50 spatial and temporal parameters, providing crucial insights for researchers studying various disease models. Essential features of the CatWalk XT such as the goal box encourage straight, even runs, which together with the adjustable side walls can accommodate different animal sizes. But the software also provides powerful data visualization capabilities, which allows for an intuitive understanding and presentation of research findings. With over 2,400 publications featuring CatWalk XT, the system has become a popular choice among researchers seeking an efficient and effective solution for gait analysis in rodents. Read the blog here! RESOURCES: Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Does well plate size matter? A methodological study in zebrafish Does the size of the well plate you in zebrafish research impact your results? This insightful blog post explores the use of the DanioVision observation chamber to study zebrafish embryos and larvae and highlights a study by Wolter and Svoboda that investigates how circadian rhythms, based on locomotion, change depending on the well plate size used in your study. The authors raise concerns about the potential bias introduced by using different well plate sizes, as zebrafish larvae exhibit higher amounts of locomotion in larger areas.The study's findings suggest that long-term experiments in 48 and 96 well plates may impose stress on zebrafish larvae due to space constraints, which could impact nervous system function and/or behavior. Moreover, the researchers concluded that the typical high-throughput method in 96 well plates may increase individual variability of circadian rhythms. Based on these results, the authors recommend using 24 well plates for long-term zebrafish behavioral experiments to increase standardization, despite shifting from a high-throughput to medium-throughput set-up. Read the full blog post here to learn more about the importance of well plate size in zebrafish research. Measuring behavior of coral larvae in response to antifouling coatings Measuring coral larvae behavior? Yes! One of the many other-than-standard animal models possible with the flexibility EthoVision XT offers. This blog post describes the studies done by Lisa Röpke from the Leibniz Centre for Tropical Marine Research. She highlights the importance of studying coral larvae's behavioral responses to potentially non-toxic alternatives of antifoulings, which are specialized coatings applied to ships' hulls that can contain toxic compounds that negatively impact marine life, including coral reefs. Röpke's study focuses on the behavior of Acropora millepora coral larvae, using Noldus' EthoVision XT to track and analyze their swimming velocity and activity during exposure to three different antifouling coatings. The results show significant decreases in mobility, emphasizing the importance of measuring behavior in ecotoxicological research. The study also provides a valuable resource for using EthoVision XT with coral larvae, promoting the standardization of research protocols in similar studies. Read the full blog here! Using video tracking to study operant behavior in rodents Operant behavior is a form of learning and memory linked to reward and punishment. Typically, operant behavior is measured using an operant conditioning chamber (Skinner box), where rodents learn to perform tasks to receive positive or negative consequences. Video tracking technology, such as EthoVision XT, plays an essential role in observing and analyzing rodent behavior during these tasks, allowing researchers to collect and analyze multiple variables simultaneously. A recent study in obesity research exemplifies the power of video tracking in operant conditioning tasks. Using Noldus' PhenoTyper and EthoVision XT, the researchers examined diet-induced obese mice, assessing the effects of gut bacteria on the rodents' reward system. The study showcases how video tracking technology has significantly improved our ability to follow and analyze behavior during training and testing sessions in operant conditioning tests, providing valuable insights into learning and memory in rodents. Read the full blog here! Your trusted partner in measuring behavior The study of behavior is both complex and essential, as it uncovers the hidden intricacies in the way living beings interact with their environment and each other. By employing cutting-edge tools and methodologies, researchers can better understand these behaviors, paving the way for novel discoveries and potentially new applications in various fields. At Noldus, we remain committed to supporting your journey in behavioral research by providing the tools and expertise needed to measure, analyze, and interpret these behaviors accurately. Stay tuned for more inspiring content and breakthroughs in the world of behavioral research. Happy measuring! FREE E-BOOK: Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download --- ## UX Research Tools for analyzing and visualizing your user research URL: https://noldus.com/blog/ux-research-tools Published: 2023-04-21 10:00:00 Description: Planning and conducting user experience tests can be time-consuming. With these UX research tools you can take your user research to a higher level and save valuable time! UX Research and tools go hand in hand. Don’t we all want tools to make our daily work and life a little easier? While there are plenty of tools that would work for both work and daily life, I’d like to focus on UX research tools specifically for user researchers. UX Research Tools for your user research It is extremely important and interesting to know what happens to your users when they interact with your product, website, application, or tool. Testing that user experience includes everything the users see, hear, and do as well as their emotional reactions.  Usability testing tools typically offer features such as screen recording, heat maps, and task completion metrics, making it easier to capture and analyze user interactions and feedback. Planning and conducting user experience tests can be time-consuming. With these UX research tools you can take your user research to a higher level and save valuable time! Miro: Online whiteboard Miro is an online collaboration platform that can be used for team collaboration. It is a handy whiteboard tool to plan and prep for user research, and keep your team organized during projects. It can be used for many things, from brainstorming and ideation to agile workflows, strategy meetings, and visual mapping and diagramming. Best of all? You can start using it for free! Eye-tracking tools Eye-tracking tools such as Tobii enable UX researchers to understand where users look and how their eyes move while interacting with a product or website. These tools use eye-tracking technology to capture and analyze eye movements, gaze patterns, and fixations, providing insights into visual attention and user engagement.   Eye-tracking tools can help researchers identify areas of a product or website that receive the most attention, understand how users scan and process information, and optimize visual elements for better user experiences. FaceReader Online: Facial expression and emotion analysis Capturing emotions by analyzing facial expressions offers additional and objective insights into the impact, appreciation, liking (and disliking) of websites and apps, commercials, movie trailers, and so on. FaceReader Online is an independent, online tool for facial expressions and emotion analysis. It delivers you direct insight into user responses – such as joy, anger, or arousal. You can incorporate FaceReader Online in your UX and market research to get more insights into user experience. As it runs on a cloud server you do not need any on-site installation, enabling user testing while participants stay at home. Read more: Why you should use FaceReader Online for your human behavior research Hotjar: Behavior analytics of your website users Hotjar is a tool that provides behavior analytics and product experience insights beyond traditional web analytics tools like Google Analytics. The online service works by adding snippets of code to your website, and recording anything during user sessions, from mouse movements to scrolling and clicks. These insights will help you to better understand your users, and get their feedback through tools like heatmaps, polls, and surveys. NoldusHub: All-in-one software suite for multimodal research Researchers have been trying to understand motivations and emotional states of people. In recent years multimodal research has increasingly gained popularity in human behavior studies as data from multiple modalities can provide a more comprehensive understanding of human behavior. For example, a researcher might use eye tracking to see how a test person reads a web page, EEG to measure brain activity while reading, and facial expression analysis to see how they respond to the content emotionally.  But combining multiple types of measurements can be quite challenging, especially when you use several acquisition tools that have to be calibrated and started. NoldusHub enables you to collect data from a webcam, eye tracker, and physiological devices, and synchronize all these signals and behavioral input at once. You can access, control, and visualize all behavioral responses and recorded signals from one dashboard.  Thanks to the system heartbeat of NoldusHub, you can also easirly monitor all the status of all connected devices in real-time. The entire process is organized and streamlined into one platform, from start to end, saving you valuable time and effort in your user testing. NOLDUSHUB: Your data in a heartbeat Discover how NoldusHub benefits your multimodal research by managing multiple data acquisition tools at once: - Integrated data collection - Easy overview of your data streams - Immediate feedback on data quality Learn more arrow_forward Survey and feedback tools Survey and feedback tools like SurveyMonkey, Google Forms, or Typeform are valuable for collecting quantitative and qualitative data from users. UX researchers can create surveys or feedback forms to gather insights on user preferences, needs, and perceptions.  These tools enable researchers to create and distribute surveys quickly, collect responses, and analyze the data for trends and patterns. Survey and feedback tools also allow researchers to segment and analyze data based on user demographics or other variables, providing deeper insights into user behavior and preferences. Viso: Audio/video feedback tool for user experience research Viso is an easy-to-use solution for creating video and audio recordings in order to capture behaviors and interactions of test participants. It's an all-in-one system for recording and playback, making it an ideal tool to use in trainings and usability & user testing. You can use it for independent recordings in multiple rooms at once, and score events of interest quick and easy. With these markers – set with just a single click of a button – you can find back interesting moments during a research, like responses or usability errors, in no time. FREE DEMO VISO: Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo arrow_forward Overall, these types of UX research tools can be valuable assets for UX researchers, providing insights into user behavior, preferences, and interactions with a product or website. By leveraging these tools, UX researchers can make data-driven decisions, optimize user experiences, and create more user-centric designs. --- ## Early-life stress and the onset of depression later in life URL: https://noldus.com/blog/early-life-stress-and-the-onset-of-depression Published: 2023-04-13 15:00:00 Description: I had a chat with my old department at the University of Groningen to see what they are currently working on. Read more about their reseach into early life stress! I am still in contact with my old lab in Groningen from graduate school. So, I recently asked about their current projects which resulted in this collaborative blog about the upcoming work of one of Prof. Jocelien Olivier's PhD students: Mayerli Prado Rivera. Research at the Olivier lab in Groningen by Mayerli Prado Rivera Mayerli studies the vulnerability to depressive symptoms later in life, based on the fact that people with a history of early life stressful events are more susceptible to this. Pre- and postnatal early life stress So far, the majority of clinical and preclinical research has studied the role of prenatal and/or postnatal early-life stress (ELS) in the onset of depressive symptoms later in life. Remarkably, some of these studies indicate that stress experienced by the mother before conceiving the child can also be considered ELS, naming this pre-gestational or pre-conceptional stress. Yet resilience can be observed despite ELS exposure in those critical periods of development. Depressive genes Vulnerability to depression has also been related to genetics. A number of studies suggest that the genotype that regulates the serotonin transporter (SERT) expression moderates the influence of stress on depression. All this together has led researchers to believe that cumulative ELS exposure plays a critical role in increasing the risk of depressive disorders later on in genetically vulnerable people (regarding the SERT gene). Measuring depression in animals Mayerli aims at studying the interaction of the SERT genotype with cumulative early-life stress (ELS), which for ethical and methodological reasons is not feasible in humans. She therefore investigates this by using an animal model: the Wistar rat. In the first part of the project, they will study whether cumulative exposure to ELS (pregestational + prenatal + postnatal ELS) in SERT transgenic rats produces a more robust depressive-like phenotype in comparison to less cumulative ELS exposure by measuring both behavioral and neurobiological markers. In the second part, they will focus on social functioning and transgenerational effects of the model. Behavioral readouts for depression in rats To test affective related behaviors, Mayerli will perform several tests: - Elevated plus maze to assess anxiety-like behavior. - Sucrose preference test to evaluate anhedonia. - Open field test which apart from anxiety-like behavior also is used to evaluate locomotor activity. To test cognitive performance Mayerli will also make use of the: - Object location test, which is designed to evaluate spatial memory in rodents. After habituation to specific objects, and their location(s), the rats are subjected in an open field arena in a final session to the same objects, of which one of them has moved to a different location. - Novel object recognition is similar to the object location test, however in this final session one of the objects (which has been familiarized to the rat) switched for a novel object of a different shape. FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Social functioning will be tested through social interaction in an open field, as well as social recognition in a 3-chamber arena. - Social interaction is evaluated through the frequency and time spent sniffing, grooming, and mounting an unfamiliar animal. - Social recognition is based on the time spent exploring a novel versus a familiar social stimulus. Thus the ability to recognize an unfamiliar mate/rat in comparison to a familiar one. And to further explore social behavior in young and adult rats: - Social play-fighting test will be conducted, for evaluating the motivation to play or be socially active in young rats. Time spent pinning, pouncing, chasing and boxing a mate is scored in an open field arena. - Resident intruder test will allow to assess aggressive behavior in adult rats by measuring offensive and defensive responses. Offensive responses include time/frequency of lateral threat, clinch attack, keeping down and chasing; defensive responses include time/frequency of keeping off and showing submissive behavior. The Behavioral Neuroscience department within the Neurobiology research unit at the University of Groningen is extremely experienced in evaluation of all types of rodent behavior, especially readouts such as anxiety, cognition and social behavior. Make sure to check out some of their work and publications! We wish Mayerli a great time and good luck as a graduate student with Prof. Olivier, and we will follow her work in the future. FREE E-BOOK: Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download --- ## Facts about FaceReader and automated facial expression analysis URL: https://noldus.com/blog/facts-about-facereader Published: 2023-04-06 16:00:00 Description: There have been many statements about using automated facial expression analysis to assess emotions. Let’s take a look at what is actually possible and impossible to do with FaceReader, through a game of true and false. Facial expressions are widely associated with emotions. Emotions are mental states induced by neurophysiological changes. These mental states are often seen as indicator for how a person feels or thinks. Understanding emotions is immensely helpful for researchers and companies, as they can provide insights into behavior and user responses. Think of usability and user experience research, where products, services, or websites are being tested to discover if the intended use actually works out in practice. Or developmental psychology and parent-child interaction, for instance to study the role of mimicry in early development of social communication. Reliable analysis with the Facial Action Coding System (FACS) Many researchers code muscle movements to learn more about how and why the facial muscles move. They use the Facial Action Coding System (FACS) which provides them with a technique for the reliable coding and analysis of facial movements and expressions. FACS coders describe every observable change in facial movement on the basis of Action Units (AUs). They indicate which AUs moved to produce the changes observed in the face. While this way of analyzing facial expressions is quite unbiased, it is also very time-consuming. Automated facial expression analysis with FaceReader Measuring facial expressions with the use of an automated tool like FaceReader can help to provide a quick and objective assessment of emotions. FaceReader is a renowned software tool for automated facial expression analysis, broadly used in scientific research. Over the years, there have been many statements and ‘facts’ about using automated facial expression analysis to assess emotions. Let’s take a look at some of those facts, and what is actually possible and impossible to do with FaceReader, through a game of true and false. False: Facial expression analysis and facial recognition are the same Facial expression analysis and facial recognition are often confused and sometimes even interchanged. They are, however, not the same thing. Let’s look into the difference between facial expression analysis and facial recognition. Facial recognition is a way of identifying or confirming an individual's identity using their face (source). Facial recognition software or systems work by mapping, analyzing, and identifying faces live or from photos or videos, and then confirming the identity of those faces by cross-referencing the images to other databases with personal photos.  FaceReader does not do this. Automated facial expression analysis is a computer-based technology that can detect and classify expressions that are described by Paul Ekman as the basic or universal emotions. Obviously, facial expressions vary in intensity and are often a mixture of emotions. In addition, there is quite a lot of inter-personal variation. FaceReader has been extensively trained to classify these facial expressions, using a database of photos to discover patterns. But it does not cross-reference these against other faces in a database attempting to identify a person. So, facial recognition is impossible with FaceReader. True: Impossible to use facial expression analysis as a lie detector or mind reader Despite popular belief (and prime time television shows), reading minds is not a validated science. Although FaceReader can automatically analyze facial expressions, it cannot read your mind. FaceReader can objectively assess someone’s facial expressions, muscle movements in the face, and link these to basic emotions like happy or surprised, or detect if someone is aroused. But the results of these measurements still need human interpretation. So, FaceReader’s facial expression analysis cannot serve as a lie detector. False: Use FaceReader to identify people FaceReader software can automatically distinguish 6 basic emotions, 20 Action Units, and specific facial features like the state of the eyes (open or closed), eyebrows (raised or lowered) and mouth (open or closed). While FaceReader can recognize general facial features, the tool is not capable of recognizing or identifying faces or people, and therefore unsuitable for mass surveillance purposes. Even though the software detects facial features and maps those into an artificial face model describing key points in the face, FaceReader’s main output is a classification of the facial expressions of a participant taking part in a research. True: Recognize specific facial properties and states FaceReader software can recognize specific facial states of test participants. For instance, the software can detect whether eyes or the mouth are open or closed, and whether eyebrows are raised or lowered. It detects if someone is wearing glasses and gives an estimate of the test participant’s gender and age. FaceReader can also detect the test participant’s head orientation and gaze direction: does the participant look to the left or to the right, up, down, or forward? This data on gaze direction can be useful in communication and social encounters, and provides researchers with information about interest and attention. When you combine all these measurements from FaceReader with eye tracking, you can get rich, quantitative, and reliable data for attention, mental load, and arousal. These combined measurements are often used in UX research, for instance, to determine a user’s experience with a product or website. False: FaceReader can be used to automatically identify facial expressions in public spaces or a crowd FaceReader is a scientific software tool that is installed on a PC and can only be used to record or analyze one person at a time. In order for FaceReader to properly analyze facial expressions, a person has to sit in front of a camera linked to a computer. When using pictures or pre-recorded videos, FaceReader can analyze only one face at a time. Diffused frontal lighting for best results For reliable analysis, FaceReader requires strict light conditions with diffused frontal lighting ensuring the best results. Uncontrolled light conditions in an outdoor setting – like strong reflections or shadows – have a negative impact on the use of the software. Strict privacy protocols The use of FaceReader also adheres to strict privacy-by-design protocols. For example, the software offers you the option not to record the test participant’s face during the analysis. In this case, all the data can be acquired but cannot be related to an identifiable person. Examples are facial expressions, head pose, age, and gender. If video is recorded, this should comply with GDPR or other privacy regulations and participants should give informed consent prior to recording. These privacy protocols and strict conditions for good results makes the software unusable for crowd analysis or in public spaces. Read more: 5 tips on how to measure facial expressions True: Context is key when using automated facial expression analysis Facial expression analysis alone can give insights into emotional states but for accurate and complete interpretations, it is important to look at the full context of someone’s behavior. For instance, what is the test participant watching on the screen and what expression does that trigger? Or which events occurred in the room while the facial expressions recognized as ‘happy’ were recorded? To learn more about these outside factors, automated facial expression analysis is often combined with other measurements, like eye movement, heart rate (HR) and heart rate variability (HRV), and post-experiment participant interviews. Taking the context into account can complement the strengths of facial expression analysis by revealing the environmental cues and context that shape facial expressions and emotions. Using the software outside of the restraints significantly reduces its accuracy. Human interpretation of all the combined measurements and full context is still widely important and vital to any conclusions. The facts about FaceReader: a summary So, these are the facts about FaceReader: facial recognition and facial expression analysis are not the same, you cannot identify people with FaceReader, and context is key when using automated facial expression analysis. Do you want to know more about how FaceReader works? Feel free to contact us or download the FaceReader methodology note to learn more. --- ## Examples of eye tracking lab set-ups URL: https://noldus.com/blog/eye-tracking-lab-set-ups Published: 2023-04-04 10:00:00 Description: Can you imagine, in the 19th century the study of eye movements for instance was done by means of direct observations? Luckily, nowadays eye tracking can easily be automated. Wouldn't every researcher want to automate certain measurements and save valuable time? In the 19th century, the study of eye movements for instance was done by means of direct observations! Can you imagine the time investment? Examples of eye tracking lab set-ups Fortunately, the process of measuring the point of gaze or the motion of an eye relative to the head - shortly called eye tracking - can now easily be automated. Direct observations are nowadays used to observe the surroundings or specific behaviors of the test participant where necessary. These observations add extra information to the eye tracking data. Automated measurements Eye trackers, mobile or stationary, have proven to be effective and reliable tools to assist researchers in answering questions about for example attention processes. They enable you to see what exactly your test participant is looking at, and is not looking at, or missing during interactions. Find out more: What can you use eye tracking for? Eye tracking devices Eye trackers are available in multiple formats: there are mobile unites like glasses, stationary eye trackers or VR units including eye tracking, each with unique benefits. Computer-monitor eye trackers are stationary and are also commonly used in an office setting. Mobile eye trackers like glasses can provide insight in real-life settings into consumers' or users' attention and responses to product placement or other stimuli. FREE WHITE PAPER Webcam-based eye tracking Download this white paper to learn about: - The technology behind webcam-based eye tracking - Validation of its accuracy - Practical applications and usability Read now Eye trackers integrated in a lab Eye trackers are often integrated into lab set-ups, for example in a game lab or in a simulator. They add substantial power to a lab set-up, as they produce gaze path video and large quantities of rich data, all related to attention and emotion. Eye tracking in developmental psychology research Eye tracking is a valuable method in developmental psychology, providing insights into how infants and children perceive and interact with the world around them. Observational research often takes place in a specialized observation lab that mimics a home environment, allowing researchers to study natural behavior unobtrusively during parent–child interactions and developmental processes. Because infants are unable to provide verbal feedback, researchers rely on nonverbal signals such as facial expressions and gaze patterns to understand their emotional and cognitive responses. These subtle cues reveal how infants explore their surroundings and react to social stimuli, offering a window into early emotional development. Combining observation with technology In a controlled lab environment, eye tracking can accurately measure where and how long infants look at certain stimuli, shedding light on exploratory and emotional behavior. When combined with synchronized video recordings, researchers gain a more complete picture of developmental changes and attention patterns. Automated facial expression analysis Complementary tools such as Baby FaceReader can automatically measure facial expressions in infants aged 6 to 24 months. Based on the Baby FACS1 system, it identifies specific facial movements to analyze expressive and cognitive behavior in both naturalistic and experimental settings, including parent–child interactions. FREE WHITE PAPER Facial Action Coding System Download here the FREE white paper 'Facial Action Coding System (FACS)' and learn more about: - Objective results with FACS - Action Units - Examples using FACS Submit to download Differentiating between task experiences Office software, games, or other applications can be evaluated by differentiating between participants with and without previous task experience. When a participant has previous experience with a website, game, or other application, the scan path of the eyes will most likely have fewer fixations than the scan path of a participant with no previous experience. In all of these lab set-ups eye tracking can also be used to obtain data such as pupil height and width, ocular torsion, pupil position, velocity of eye movement/saccades, and location and duration of eye fixation. Record all data in perfect sync When working with multiple data sources such as eye tracking, physiological measures, and behavioral observations, managing and synchronizing all these streams can become complex. NoldusHub offers a smart and centralized solution to bring all your data together. With NoldusHub, you can easily connect devices like eye trackers, and physiological sensors, and record their data in perfect sync. The platform enables you to visualize, monitor, and validate all incoming signals in real time, ensuring data quality and consistency across sessions. Using eye tracking in combination with research software such as The Observer® XT allows researchers to specify subjects and behaviors which can be coded during a test and afterwards played back alongside the eye tracking data. Eye trackers usually produce multiple data modalities, such as a video image of the participant's field of view, hotspots, pupil width, fixations, and areas of interest (AOI). In The Observer XT video coding software you can synchronize all data and analyze it to see exactly what happened in an experiment. Read more on eye tracking, data integration, and multi-modal data: - How to easily apply multimodal measurement during research with children - Five studies showing the power of multi-modal data in behavioral research - What is Biometric Research? Reference Oster, H. (2016). Baby FACS: Facial Action Coding System for infants and young children. Unpublished monograph and coding manual. New York University. --- ## The challenges of measuring epilepsy in rodents URL: https://noldus.com/blog/eeg-measuring-epilepsy-in-phenotyper Published: 2023-03-30 15:00:00 Description: EEG on freely moving rats? It's possible in the PhenoTyper. This was necessary to measure if delivering drugs directly to the brain could help epilepsy patients. What is epilepsy? Epilepsy is a disease (actually, a group of disorders) in which the patients experience a large synchronous discharge of electrical discharge in their brains - a seizure. Seizures often cause convulsive muscle contractions, which can cause accidents, broken bones and bitten tongues. (Here is what to do if you see someone having a seizure). Sometimes the seizure causes absences, in which the patient has decreased levels of consciousness. Those typically last about ten seconds, but it can be much longer. Epilepsy has a variety of causes include genetics (typically in younger people), brain trauma, and stroke (typically in older people). The blood brain barrier Over fifty million people worldwide suffer from epilepsy. Although there are working drugs, which can help most epilepsy patients, about 30% of patients cannot be helped by current medicines. One of the reasons for that is that the brain has a mechanism called the blood brain barrier (BBB) to protect it. The BBB is a wall of cells which selectively prevents bacteria, viruses and chemicals in the blood from getting into the central nervous systems (the brain and spinal cord). Chemicals like oxygen and hormones are allowed through the barrier or are actively transported, for example glucose as 'fuel' for the brain. The BBB is a powerful mechanism defending the brain, but it does result in medicines intended to alleviate diseases like epilepsy to be prevented or restricted from getting to the brain. If a higher dose of the medicine is given, so that enough gets through to help the patient, that can cause all sorts of negative effects in other organs of the body. Diagram of the function of the blood brain barrier (Wikimedia Commons). Injecting directly into the brain An alternative is to inject medicines directly into the brain. Specifically, they can be injected into the cerebrospinal fluid in the cerebral ventricels (intracerebroventricular administration, i.c.v.). The cerebral ventricles are cavities in the brain that produce the cerebrospinal fluid. Cerebrospinal fluid is a clear liquid found in the brain and spinal cord of vertebrates, which provides mechanical and immunological protection. However, until recently, it wasn't known if this i.c.v. injection was likely to work. Anna-Sophia Buschhoff and her colleagues [1] in Kiel University (Germany) investigated this using a special variety of rat, with a genetic disposition to having epileptic seizures: the Genetic Absence Epilepsy Rats from Strasbourg (GAERS). Measuring behavior with the PhenoTyper The researchers implanted a thin polythene tube into one of the ventricles of the rat's brains (an i.c.v. cannula) and injected them with ethosuximde (ETX). ETX is a medicine widely used to treat epileptic patients to reduce seizures. They monitored if there were any abnormal behaviors by observing the rats in an open field (no such behaviors were observed) and measured the electrical activity of the rat's brains (EEG) to monitor spike wave discharges (electrical activity that leads to seizures). That was easier said than done, the EEG headstages needed to be connected to recording equipment by a cable, but the rats also needed to have freedom of movement so that they could behave normally. This problem was solved by using a PhenoTyper from Noldus IT. The PhenoTyper is an instrumented cage which can facilitate the measuring of the behavior of laboratory rats and mice, but it also has the possibility to attach cables to a swivel so that the rats could move freely. In this case, it was an electrical swivel with a counterbalanced arm, so that the rats' heads could also move up and down. The behavior of the rats was also monitored using EthoVision XT. The effects were compared with i.c.v. injections and injections into the tail vein, and at various different dosages (including a control with no ETX). RESOURCES: Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Direct injection in the brain reduces seizures The results were quite spectacular. In the rats which had ETX injected through the tail vein, there was no reduction in spike wave discharges. However, in the rats which had i.c.v. injections of ETX into the brain, there was a strong reduction in spike waves and seizures, and also fewer convulsions, even at low doses. Treating epilepsy in humans Of course, for human patients, injection of a drug via a cannula into the brain is not a very appealing prospect. However, there are some better possibilities, which are currently being researched: - The drugs could be combined with a molecule that the blood brain barrier does let through. - Drugs could also be used to increase the permeability of the BBB (though that is a risky procedure that can only be carried out in controlled circumstances). - The most promising route is to attach the medicine to coated nanoparticles, which can get through the BBB [2]. For some of the millions of epilepsy patients who cannot be helped with current medical techniques, these innovations might make a huge difference to their lives in the future. References 1. Anna-Sophia Buschhoff, Regina Scherließ, Johanne G. de Mooij-van Malsen, Thomas Schiffelholz, Ulrich Stephani, Peer Wulff, (2022). Intrathecal application of ethosuximide is highly efficient in suppressing seizures in a genetic model of absence epilepsy. Epilepsy Research 184, 106967. https://doi.org/10.1016/j.eplepsyres.2022.106967. 2. Dadparvar, M., Wagner, S., Wien, S., Kufleitner, J., Worek, F., von Briesen, H., & Kreuter, J. (2011). HI 6 human serum albumin nanoparticles—Development and transport over an in vitro blood–brain barrier model. Toxicology Letters, 206(1), 60-66. doi:10.1016/j.toxlet.2011.06.027 --- ## The power of multimodal research in human behavior studies URL: https://noldus.com/blog/multimodal-research Published: 2023-03-28 17:00:00 Description: By implementing multimodal research, scientists are hoping to gain a more complete and nuanced understanding of human behavior than is possible through the examination of any single modality. Understanding human behavior is no easy feat. So, it should come as no surprise that the study of human behavior is a complex and interdisciplinary field. It is also one that has challenged scientists and researchers since the beginning. While we have come a long way from simply observing people's behavior, the field of human behavior studies will always keep evolving. What is the purpose of human behavior studies? So why do we study our behavior so extensively? The purpose of human behavior studies is to understand and explain the actions, thoughts, and emotions of individuals and groups. This field draws on theories and methods from psychology, sociology, anthropology, and other related disciplines to advance our knowledge of human behavior and the underlying processes that drive it. The goal of all this? To increase our understanding of the human experience and to apply this knowledge to support individuals and communities to achieve their goals and live fulfilling lives. For example, human behavior studies may be used to develop more effective treatments for mental health disorders, to design educational programs that more effectively engage students, or to improve organizational practices in the workplace. In addition, these studies can provide insight into the complex social, cultural, and historical factors that shape our actions and reactions, as well as the individual differences that exist between people. How human behavior research can benefit from technology Scientists have been using many different methods and tools to study human behavior. It started with observing people with pen and paper in hand. Soon, physiological measurements came into the mix, from measuring blood pressure and skin conductance, to studying heart rate and brain processes. Fortunately, modern technologies are providing researchers with new tools and insights to help them better understand human behavior. The use of technologies such as video observations, eye tracking devices, and facial expression analysis has become the norm in research nowadays. Human behavior research can benefit from software tools and technology in several ways: - Data collection: Software tools can be used to efficiently collect and store large amounts of behavioral data, such as responses to surveys, mouse and eye tracking data, and physiological measurements. These tools allow researchers to gather more data in less time than would be possible through manual methods. - Data analysis: Advances in technology have also made it easier to analyze and interpret large amounts of data. For example, machine learning algorithms can identify patterns and relationships within datasets that might be missed by traditional statistical methods. Data visualization tools can help researchers to identify trends and patterns more easily, and make it easier to communicate research findings to others. Additionally, software tools can automate the process of data analysis, allowing researchers to focus more on the interpretation of results. - Experiment design: Finally, technology can be used to create and conduct complex experiments, such as immersive rooms that simulate real-world situations. This way, researchers can manage and study human behavior in controlled environments, like a consumer lab or medical training room. Similarly, using technology and software tools can help researchers to design experiments more efficiently, reducing the time and cost required to conduct research. Overall, software tools and technology can greatly support human behavior researchers in gathering, analyzing, and interpreting data. They can also help to increase the speed and efficiency of research, enabling researchers to answer questions more quickly and with greater precision. What is multimodal research? In recent years, multimodal research has increasingly gained in popularity. Multimodal research is an innovative and interdisciplinary approach for studying human behavior that combines multiple modalities. This includes modes such as speech, gestures and eye tracking, and physiological measures like blood pressure or skin conductance. By collecting and analyzing data from different modalities, researchers can gain a more comprehensive understanding of complex phenomena and identify patterns and relationships that may not be apparent through a single modality. This approach provides a deeper understanding of human behavior and enables researchers to draw more accurate and insightful conclusions. By combining multiple forms of data, researchers can overcome the limitations of studying human behavior through a single modality and obtain a more complete picture of the phenomena being studied. By implementing multimodal research, scientists are hoping to gain a more complete and nuanced understanding of human behavior than is possible through the examination of any single modality. Why multimodal research is gaining popularity Moreover, multimodal research can also help to advance our understanding of the cognitive processes underlying human behavior, such as attention, memory, and decision-making. By examining the ways in which people use multiple modes of communication to process information and respond to their environment, multimodal research can provide insight into the complex interplay between perception, attention, memory, and action. Examples of multimodal research Combining all of these different modalities enables researchers to gain insights into how different aspects of behavior are related and how they interact with each other. For example, a researcher might use eye tracking to study how people read a web page, EEG to measure brain activity while reading, and facial expression analysis to see how people respond emotionally to the content. By combining these different modalities, you can gain a much more complete understanding of how people engage with online content. FREE WHITE PAPER: Eye tracking & FaceReader Download this white paper to learn about: - Subconscious processes and emotion recognition - Combining FaceReader™ and eye tracking - Visualizing and analyzing your data Submit to download The challenges of multimodal research (and how to overcome them) Multimodal research often involves the use of advanced technologies and software tools to analyze and synthesize data from different modalities. But combining multiple types of measurements can be quite challenging, especially when you use several acquisition tools that have to be calibrated and started. This often leads to time delays, not to mention frustration when things go wrong or don't work. And how do you know for sure that all these data streams are recorded in sync? Multimodal research made easy That is why the all-in-one software tool NoldusHub® was developed by Noldus. With over 30 years of experience with behavioral software development and working together with researchers, we understand the urgent need for an easy, yet powerful, multimodal research tool. We strive to empower scientists in advancing their research on human behavior by providing a user-friendly and technically robust system: NoldusHub. We understand that integrating data from multiple sources can be challenging, especially when dealing with equipment from different manufacturers that require calibration, start-up, and synchronization. That's why NoldusHub is designed: to simplify these technical hurdles, allowing researchers to focus on what really matters – their research. Setup, connect, record and visualize your data streams: NoldusHub will streamline multimodal research from start to finish, providing high-quality data, and insights into human behavior. Your data in a heartbeat with NoldusHub From setting up to connecting all devices, to recording and visualizing results in a clear way, NoldusHub makes multimodal research easy! The system collects data from a webcam, eye tracker, and physiological devices, resulting in the synchronization of a variety of signals and behavioral input. From ECG, and EDA, to PPG, with NoldusHub you can access, control, and visualize all behavioral responses and recorded signals from one dashboard. Scheduling several experiments with several participants is also possible, as you can record data from up to four participants at the same time. Thanks to the system heartbeat of NoldusHub, you can monitor all the status of all connected devices in real-time. The entire process is organized and streamlined into one system, from start to end, saving you valuable time, effort and frustration. NOLDUSHUB: Simplify your multimodal research Discover how NoldusHub benefits your behavior research, and why it is the best multimodal platform for you to use: - Integrated data collection - Synchronization from the start - Immediate feedback on data quality Learn more The power of multimodal research In conclusion, multimodal research is a powerful approach for investigating human behavior and understanding complex interactions between different modalities. By combining various measurement tools, researchers can gain a more comprehensive understanding of their subject matter, leading to more accurate and insightful findings. However, integrating data from different sources can be technically challenging and time-consuming. That's why solutions such as NoldusHub are so important. With user-friendly tools that automate the calibration, synchronization, and analysis of data from different sources, researchers can focus on the science, not the technology. --- ## How to study human behavior URL: https://noldus.com/blog/how-to-study-human-behavior Published: 2023-03-24 15:00:00 Description: Many people are fascinated by human behavior. Why do we act the way we do? How is our behavior influenced, or measured? And why is behavioral change so difficult? How to study human behavior Many people are fascinated by human behavior. Why do we act the way we do? How is our behavior influenced, or measured? And why is behavioral change so difficult? In this blog post, we describe several behavioral theories, as well as different ways to measure human behavior. Lastly, we discuss research fields in which human behavior analysis plays a central role, like psychology, health care, education, and consumer research. Table of contents - Perspectives on behavior - Qualitative versus quantitative research - Observation - Physiological measures - Implicit measures - Developmental psychology research - Mental disorders - Health care research - Education & training - User experience and human factors research - Consumer behavior research Perspectives on behavior Influenced by prominent thinkers like John B. Watson and B.F. Skinner, behavioral psychology gained popularity between 1920 and 1950. With its focus on observable behavior instead of mental states, behaviorism provided a systematic way to study human behavior. Behaviorism: it’s the environment Behaviorists argue that behavior is learned in interaction with our environment, and that all behaviors are learned through experience. Behavior analysis is the scientific approach to understanding behavior and how it is influenced by environmental factors. It is based on the principles of behaviorism, which emphasizes the role of the environment in shaping behavior. Behavior analysts focus on identifying the antecedents (what happens before behavior occurs) and consequences (what happens after behavior occurs) that influence behavior, and then use this information to develop interventions that can change behavior. Two key principles that are involved in new behavior are classical and operant conditioning. In classical conditioning, something new is paired with something that occurs naturally. After a while, this new stimulus triggers the same reaction as the original stimulus, resulting in a new association. A famous example of this principle is found in Ivan Pavlov’s research. What is classical conditioning? In his experiments with dogs, Pavlov paired the sound of a bell (new stimulus) with the presentation of food (naturally occurring stimulus). Eventually, the dogs started salivating when hearing the bell, even when no food was presented (new association). And voilà, new behavior is learned. What is operant conditioning? The second learning principle, operant conditioning, describes the way our behavior is shaped by consequences. Specifically, it states that reward and punishment can influence the likelihood that behaviors occur again. Think about how you praise a child when she eats her vegetables, or how you might take away a favorite toy when she’s mean to her brother. In both cases, you provide her with a consequence for her behavior. Chances are, she’ll eat her vegetables next time as well, and will think twice about teasing her brother. These methods explain much of how human behavior is shaped. However, critics argue that behaviorism fails to take into account important factors like free will, internal influences, and other types of learning. In the next paragraphs, we will explore two other behavioral theories. Social learning theory: it’s other people Social learning theory was proposed in the 1970’s by Albert Bandura, who believed that conditioning alone could not account for all behaviors. At its core, social learning theory proposes that people learn from observing others. This observational learning does not only occur when observing another person, but also when listening to descriptions of behavior or viewing symbolic models. From very early on, this provides us with many learning opportunities. Importantly, social learning theory emphasizes that behavior is also influenced by mental states, like motivation or thoughts. Another difference with behaviorism is that observational learning does not necessarily lead to permanent behavioral changes. In other words, people might learn new information without actually showing new behaviors. So far, we’ve established that human behavior can be shaped through experience and observation. A third method of learning behavior is described by Relational Frame Theory. Relational Frame Theory: it’s our language Relational Frame Theory (RFT) was developed in the 2000’s by Steven Hayes, Dermot Barnes-Holmes and Brian Roche, and builds upon classic behaviorism. What’s new in this theory is the role of human language in learning new behavior. Specifically, RFT researchers argue that language enables us to learn new information indirectly. The key learning processes of this theory are centered on relations between stimuli, or relational frames. An example As an example, imagine you meet three new people: Aaron, Bianca and Chris. Aaron introduces himself to you, and explains that Bianca is his sister and Chris is his father. Importantly, with these relations learned directly (B-A, C-A), you now know several other relations indirectly. First, you can derive that Aaron is Bianca’s brother (A-B) and Chris’ son (A-C). This is called ‘mutual entailment’ in RFT. But you can also understand that Bianca is Chris’ daughter (B-C) and that Chris is Bianca’s father (C-B), which is referred to as ‘combinatorial mutual entailment’. Even though these relations may seem obvious, the example shows that we can learn indirectly, through relations or frames we already know. The more relations we know, the more relations we can derive. And, like social learning theory, it shows that we don’t need actual experience to learn new information. Why is changing behavior difficult? As you might know from personal experience, changing behavior can be difficult. Maybe you have tried to exercise more or to eat more healthy foods, only to find yourself back to your old habits one week later. Why is behavioral change so difficult? And what can you do to succeed anyway? First, it is important to know that about 95% of our behavior is driven by unconscious processes. It would simply take too much mental energy to be aware of all our behaviors. So instead, most of it becomes automatic, part of our habits. Second, behaviorism has taught us that the environment, through associations and consequences, shapes our behaviors. So let’s examine the consequences of a behavior we want to change. To return to our previous example, imagine that you want to exercise more often. What are the consequences of that behavior? More energy, better health, slimmer body. Sounds good, right? But to get there, you have to work out, sweat, and skip comfortable hours on the couch. Do you notice the difference between these consequences, specifically in their timing? The unpleasant consequences come immediately, while you have to persevere for weeks or even months until you can experience the pleasant consequences of your behavior. If consequences drive our behavior, it’s not surprising that the immediate, visible rewards win over the long-term, abstract ones. And if we’re not aware of 95% of our behaviors, how can we expect to change them? Luckily, we can also use these principles to our advantage. Behavioral change A powerful way to make use of our automatic behaviors is through habit stacking. Basically, this means that you take an existing habit, and then add a new behavior to it. For example, when you regularly forget to take your medicine, you ‘stack’ this behavior on top of a habit you have already mastered, like brushing your teeth in the morning. By making a new behavior part of an automatic routine, you are more likely to stick with it. The beauty of it is that you can keep stacking on new behaviors, once a new behavior has become a habit of itself. The power of consequences You can also harness the power of consequences, by creating ways to make the short-term consequences of your desired behavior more positive, while making the short-term consequences of procrastination more costly. For example, you can reward yourself each time you eat a healthy meal. Simply praising yourself for each step in the right direction can make a difference, as can actively imagining the long-term benefits of your behavior. And if you want to make the consequences of procrastination more costly, you can try teaming up with a buddy, making your intentions public, or putting an expensive bet on your behavior. Change your environment Another important step you can take is changing your environment. If your TV is on and your sports clothes are in the attic, it’s much easier to lounge on the couch than it is to start your workout. Instead, unplug the TV and keep everything you need to start exercising in sight. Principles like these are also used in (cognitive) behavioral therapy. With the help of a therapist, behaviors involved in anxiety, depression, addictions or other mental disorders are examined and changed gradually. To provide people with the best care possible, accurate measurements and continued research of behavior are essential. Qualitative versus quantitative research To measure human behavior, all kinds of research instruments are at our disposal. These instruments can be divided into qualitative measurements and quantitative measurements. What is the difference between qualitative and quantitave research? Let us explore this further. What is qualitative research? Qualitative measurements help researchers to understand human behavior on a deeper level by studying underlying reasons, opinions, and motivations. Usually it is used for exploratory research. They are particularly helpful in understanding the context of phenomena, and how they affect individuals and groups. It is all about the details. It seeks to explain ‘how’ and ‘why’ people behave as they do. Methods to measure qualitative data The sample size in this type of research is typically small since it’s hugely labor intensive. Methods to measure qualitative data are for example in-depth interviews, focus group interviews, behavioral observations, and unstructured questionnaires using open-ended questions. Preferably, qualitative research is conducted in a natural setting. What is quantitative research? On the other hand, quantitative measurements are used to quantify preferences, opinions, facts, behaviors, and other defined variables – and generalize results from a larger sample population. It is used to answer questions such as “How many?”, “How often?”, “How much?” of which the answers are expressed with numbers. You can statistically analyze the collected data. Methods to collect this data are e.g. surveys, structured questionnaires, and online polls, using close-ended questions. Combining qualitative and quantitative data The overall purpose of research is discovering the truth. However, “without good data, you’re just guessing.” Combining qualitative data with quantitative data will provide researchers in-depth information about a certain behavior, and various aspects of that behavior. The two different approaches complement each other, while the shortfalls of each will be balanced. Read more: Examples of Human Behavior Research Observation A very important part of studying human behavior is performing observations. What better way to explain someone's behavior than by observing that person? How is your test participant interacting with a child, a patient, or computer? Observational research Observational research is typically performed in one’s home, workplace, or a specially designed observation lab. The best way to observe one's true behavior is unobtrusively. With a one-way-mirror, it is possible to watch every move of your subject, without being physically present in the room. By using The Observer XT, you can annotate all of the behaviors of interest and perform analysis, turning qualitative data into quantitative data. Video observations are also a great way to study human behavior. The use of video greatly expands the scope of any research project. Annotating from video allows you to make frame-accurate descriptions of behavior. Viso is an ideal solution for high quality recording of video and audio in multiple rooms, and provides the video material needed to gain insights into processes, human performance, and communication. Observing behavior in the brain Another way of observing one's behavior is by looking at the inside, more specifically: by looking at their brain. As we are not conscious of most of the processes that happen on the inside, looking into brain activities can give new insights into the behavior of people. We can observe correlations between behavior and brain activity, for example when studying an injured brain and the influence this has on a patient. In some cases, brain evidence helps to resolve puzzles that psychologists have wrestled with for decades. Learn more about observing behavior by looking at the brain in the blog post: Cognitive neuroscience: Behavior. Physiological measures Although your test participant may appear to be calm, he or she may be concealing a substantial amount of stress. To reveal this level of stress, you can combine behavioral coding with physiological measurements acquired with a data acquisition system. This allows you to simultaneously acquire physiological data, such as EEG, ECG, EMG, blood pressure, skin conductance, and facial expressions, while you are collecting observational data. For example, skin conductance is a method of measuring the electrical conductance of the skin, used as an indication of psychological or physiological arousal. EEG makes it possible to include neuronal activity during a test, while FaceReader captures the facial expressions. These measurements make it possible to study the interplay of physiology and behavior, caused by an external event. Multimodal research made easy Combining multiple types of measurements can be demanding, especially when using acquisition tools from different manufacturers that have to be calibrated, started, and synchronized. Straightforward yet powerful is NoldusHub, an all-in-one research platform for human behavior studies. This brand-new software suite was specifically designed to streamline multimodal research from start to finish, and take the hassle out of measuring multiple modalities with a range of devices at the same time. By doing so, researchers are able to get high-quality data and a more comprehensive understanding of human behavior. From setting up to connecting all devices, from recording to visualizing in a clear way, NoldusHub makes multimodal research easy Implicit measures While questionnaires can be useful in capturing opinions, personality traits, or (mental) health issues, they also have some limitations. One important issue is that people can be biased in their responses. We tend to give answers that are socially desirable, we are influenced by an experimental setting, or we answer all questions a certain way (mostly extreme or neutral, mostly ‘yes’ or ‘no’). Also, we’re not always aware of what we think, feel or do. As we mentioned earlier in this blog, about 95% of our behavior is unconscious and automatic. Some information about ourselves might escape our attention. With these limitations in mind, researchers developed measures to capture our unconscious opinions, emotions and behaviors. These implicit tests require people to respond very quickly to different stimuli. Differences in response times reflect how you really feel about something. Basically you respond faster when you agree. For example, a test might involve asking participants to sort words into categories that are on either side of a computer screen. You’d have to choose left when encountering a positive word (‘good’, ‘happy’) or a picture of a cat. You’d choose the right side when seeing a negative word (‘bad’, ‘ugly’) or a picture of a dog. In another phase of the test, these pairings are reversed. If you were to respond more quickly when ‘positive’ and ‘dogs’ are associated, compared to when ‘positive’ and ‘cats’ are, this suggests you have an implicit preference for dogs. Other implicit tests assess approach and avoidance behavior, attention biases, or relational frames. NOLDUSHUB Simplify your multimodal research Discover how NoldusHub benefits your behavior research, and why it is the best multimodal platform for you to use. - Integrated data collection - Synchronization from the start - Immediate feedback on data quality Learn more Developmental psychology research Developmental psychology is the scientific study of how and why humans change over the course of their life. Developmental psychologists aim to explain how thinking, feeling, and behaviors change throughout life. Although developmental psychology involves the entire lifespan, researchers mostly focus on the period in which changes follow each other fast, from birth to early adulthood. They explore topics such as children’s basic understanding of the physical world, how children acquire language, how learning behaviors develop, and how they interact socially with other people, for example in parent-child interaction studies. Ways to study development The use of video greatly expands the scope of such a research project. It enables researchers to capture infants' behaviors and reactions while they perform a task, are exposed to a novel object, are playing with a sibling or peer, or are having a meal. Coding the videos, whether they are made at home or in a lab, enables you to review, visualize and analyze the behaviors quickly. Baby FaceReader has been developed as a state of the art system to automatically detect infant facial expressions in order to help address questions in developmental psychology related to affect and developmental disorders such as Autism Spectrum Disorder (ASD). Research helps us to understand what infants learn, what they are processing, and what factors are influencing the development. In another blog post, 5 examples of infant studies are highlighted. Mental disorders Understanding human behavior is essential in the prevention and treatment of mental disorders. Mental disorders are defined as a combination of abnormal thoughts, emotions, and behaviors. Worldwide, millions of people suffer from disorders like depression, addiction, anxiety, and dementia. Aside from a range of psychological and cognitive symptoms, people with mental disorders often experience problems in school, work, or family life as well. Understanding mental disorders With this variety in symptoms and contributing factors, research plays an important role in the further understanding of these disorders. For example, recent studies examined the effectiveness of a game-based intervention in social anxiety, the best ways to observe pain expressions in dementia, doctors’ emotions during the treatment of depression, and the role of social cognition in the development of social anxiety. Studies like these help to improve the prevention and treatment of mental disorders, and contribute to overall mental health. Health care research In the field of health care research, it is all about quality of life and consequently about quality of care. Health-related quality of life is an assessment of how the individual's well-being may be affected over time by a disease, disability, or disorder. Health care professionals’ highest aim is to improve quality of life for their patients, by providing the best possible quality of care. Various topics can be of interest for health care research, such as doctor-patient interaction, operating room layout, simulation training, team performance and communication, or dealing with emotions. All have an impact on the quality of care and thus life. Using video technology With help of Noldus solutions, researchers will gain the insight they need in processes, human performance, and communication. For example, the use of video technology offers important advantages to scientists in unraveling complex behavior patterns and finding relationships between behaviors, effectiveness of interventions, and more. Education & training Education is all about gaining knowledge about facts, events, values, beliefs, general concepts, principles, etc. to students. On the other hand, training is a way to develop skills, rather than just know about something. Training is based on practical application, it involves hands-on experience and helps people to implement a new system, improve a specific ability or further their ability in something. Education and training can take place in a wide variety of fields, and in many different settings such as classrooms or skills labs. Theory can be put into practice in a safe and controlled environment. Video feedback tool More and more video feedback is used in education and training facilities. It continues to prove its effectiveness for both educators and students. By using video and audio recordings in education and training, students and educators can receive, and benefit from, direct feedback. Classroom observations To examine, for example, effective teaching and teacher-student interaction, classroom observations can be used as a technique to gain the desired insights. Using a software tool to observe the questions students ask, how the teacher reacts, and whether the teacher checks if the students understand his explanation, will make the research much easier. It enables to code behaviors accurately, record one or multiple videos, integrate data modalities, and explore the results. User experience and human factors research What happens with a person’s emotions and attitudes when using a particular product, website, application, or system? What does the user experience, and how does the user interact? Is it used in the way that it is meant to be used? Finding answers to these questions enables to optimize that particular product, website application, or system. To meet the needs of its users, to improve the user experience. Tools to measure ease-of-use and efficiency Feedback methodologies such as observation and task analysis will reveal the ease-of-use and efficiency of a product or service. While you observe the user of your product, you can receive direct feedback about your product. To facilitate UX tests, you can record audio and video streams from digital cameras, capture the eye tracking gaze-overlay and emotions, and add notes or markers on the fly for quick lookback. How to build a usability lab? UX tests can be carried out in a usability lab, or on-site with a portable lab. It provides controlled conditions, and fully integrated equipment and software to make the tests as realistic as possible. A few examples are the Social Media Lab in Mons, Belgium, which connects with business and academics in order to better understand social media use and the digital world in general. In the Human Factors and Ergonomics Laboratory of Zodiac Seats, participants were asked to evaluate six different travel pillows on head and neck support while sitting in an airplane seat and trying to rest or sleep. In a study with bicyclists, researchers at VTI, the Swedish National Road and Transport Research Institute, observed cyclist behavior using eye tracking technology, video recordings, and behavioral coding. All data combined enabled them to assess whether the cyclists met the demands in specific situations. Find here an overview of example labs. Consumer behavior research Getting to know your target audience is the best way to understand consumer choice behavior and preferences. How do consumers use a product? Why did they choose to buy that product in the first place? Did packaging or store layout have anything to do with that? Or did unconscious emotions play a role? Recent studies aimed to answer several of these questions. Here, we list a few: - The study of Eliza Kostyra and colleagues used face-reading technology in order to determine the effect of smoked ham samples on consumer emotion, which may lead to deeper insight on whether or not a consumer chooses to buy the sampled product. - In France, a team of researchers designed a test kitchen including four dome cameras and one portable GoPro camera to investigate food storage processes. - Researchers Torrico and Fuentes tried different implicit measurement techniques in order to get closer to measuring liking and preference using images and chocolates! A more in-depth blog post about consumer behavior research can be found here: Understanding consumer buying behavior. CONTACT US Ready to start studying human behavior? Book a meeting for an online or onsite session. Together, we can discuss your research requirements and come up with the best solution! - Expert consultation - Tailored solutions - Free meeting Contact me for a meeting References - www.verywellmind.com/behavioral-psychology-4157183 - www.verywellmind.com/social-learning-theory-2795074 - contextualscience.org/what_is_rft - jamesclear.com/habit-stacking - jamesclear.com/time-inconsistency - www.simplypsychology.org/qualitative-quantitative - www.socialresearchmethods.net - www.theclassroom.com/ - keydifferences.com/difference-between-training-and-education - www.nextiva.com/blog/response-bias - implicit.harvard.edu/implicit/iatdetails - www.who.int/news-room/fact-sheets/detail/mental-disorders --- ## Using zebrafish as an early warning system of neurotoxic substances URL: https://noldus.com/blog/zebrafish-early-warning-system Published: 2023-03-23 15:00:00 Description: How can we use a zebrafish (Danio rerio) embryo model to detect possible neurotoxic chemical mixtures that are difficult to detect with normal chemical analyses? Pollution of aquatic environments and the effects on (human) health Industrial, urban and agricultural activity produce chemical waste that eventually reaches lakes, rivers, oceans and other bodies of water. These aquatic environments are vulnerable to pollution, and many chemical substances may form mixtures that are difficult to detect with normal chemical analyses. Furthermore, these substances and mixtures can exert neurotoxic effects, thus may have neuroactive properties. This is not only harmful for the aquatic ecosystem, but could potentially harm human health as well through drinking water exposure and/or the ingestion of fishery products. Zebrafish embryos as a research model To measure this real impact of aquatic (neuro)toxicity, researchers from the Italian National Institute of Health aimed at verifying the feasibility of using a zebrafish (Danio rerio) embryo model. Zebrafish larvae and embryos make great models for managing ecotoxicity. This model is simple to utilize in the laboratory and is very scalable. This is mainly due to its rapid development, compact size, and transparency. The three Rs of animal testing methods—reduction, replacement, and refinement—are also supported by the use of zebrafish embryos and larvae. Want to read more about Aquatic eco-neurotoxicology? Check out this white paper written in collaboration with Prof. Donald Wlodkowic, an expert in eco-neurotoxicology from the RMIT University in Melbourne Australia. Here we dive into the topic of contaminated surface and drinking water, and how we use the latest technology to investigate the neurotoxic and/or neuromodulating effects of these contaminants. Tail movements as an indicator for neurotoxicity: The Coiling Activity Test Assessing tail movements (coiling) in zebrafish embryos is a screening technique for developmental neurotoxicity brought on by toxins. These spontaneous tail movements of the zebrafish embryo is an effective readout for eco-neurotoxicological investigations since it can quickly screen for the presence of harmful neurotoxic chemicals in the environment. Lacchetti et al. evaluated this coiling activity test (CAT) on its efficiency and dependability. Mainly spontaneous tail movements are monitored since this identifies potential neurotoxic effects in water samples. This was compared to the Fish Embryo Acute Toxicity (FET), which is a method more commonly used to pinpoint chemical concentrations in aquatic environments that acutely poison fish. Usually zebrafish embryos are used in the procedure, and are used to identify the concentration at which 50% of the embryos die (i.e., is fatal) after being exposed to a chemical for 96 hours. What is the benefit of the Coiling Activity Test The benefits of using the Coiling activity test (CAT) compared to the Fish Embryo Acute Toxicity test (FET) are the very quick screening (it can be performed within 24 hours), but more importantly the CAT does not focus on lethality per sé, but rather on behavioral alterations. This thus emphasizes the possible neuroactive/neurotoxic effects, that can have lifelong and considerable ecological consequences. Using Noldus' DanioScope®, a versatile hardware and software combination specifically designed for zebrafish larvae and embryos, videos of the embryos were recorded and analyzed. Burst activity, mean burst duration, and burst count/minute are the three key measuring metrics that DanioScope® evaluates for characterizing the coiling tail movements. Measuring behavior with DanioScope® Lachetti et al. presented three different aquatic situations to the zebrafish embryos: standard fresh water (negative control), 1% ethanol and 5% ethanol as references for hyper- and hypoactivity, respectively. Ethanol produces hyperactivity at doses below 2% and hypoactivity at concentrations above 4%. The embryos were incubated in 96-well plates at 26°C in the dark for around 22 hours to bring the embryos to the 23 hpf stage. RESOURCES: Read more about DanioScope Find out how DanioScope is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Conclusion A 2018 paper by Legradi et al. [2] estimates that neurotoxic compounds are very likely to be increasingly released into the environment. With a test such as the CAT, Lacchetti et al. demonstrated the test as a valid and rapid early warning system for this presumed neurotoxicity. In conclusion, the coiling activity test (CAT) as used in this study by Lacchetti et al. is considered a promising, smart and efficient tool due to its sensitivity. The authors do warrant however for harmonization and standardization of its protocols to improve its accuracy and possible future implementation in regulatory guidelines. References - Lacchetti, I, Christiano W., di Domenico K., Carere, M., Mancini, L. (2022). Coiling tail activity in zebrafish embryo: a protocol for an early warning system of neurotoxic substances. Fresenius Environ. Bulletin 31(08A/2022):8427-8434 - Legradi, J. B. et al. (2018). An ecotoxicological view on neurotoxicity assessment. Environ. Sci. Eur. 2018 301, 30 (1), 1–34 --- ## How do people with Parkinson's disease express emotions? URL: https://noldus.com/blog/parkinsons-disease-facial-expressions Published: 2023-03-15 08:50:00 Description: A mask-like facial expression is an early symptom of Parkinson's disease. How can we understand the relation between changed facial expressions and disease severity? Researcher Yang and their team used FaceReader to find out. Parkinson's disease (PD) affects millions of people worldwide. It's a progressive disease that affects the brain and impacts a person's ability to control their movements. As a result, many everyday activities become a struggle, including walking, taking care of oneself, and communicating. Facial expressions are affected as well. In fact, a mask-like facial expression is one of the early symptoms of Parkinson's disease. But what is the relation between these changes in facial expressions and the severity of PD? Want to know more about measuring emotions? Watch this webinar on demand. Click on 'Replay Human Behavior Research webinars' and choose 'How to measure emotions'. The role of facial expressions in emotion Facial expressions are essential in communication and social interactions. Not only do we use them to express our feelings, but they also play a role in reading and sharing emotions. That's because we have subtle feedback mechanisms that mimic others' expressions, which helps us to understand each other. As a result, people with impaired facial expressions may be misunderstood or unable to share their experiences with another person. How Parkinson's disease affects the face An important symptom of Parkinson's disease (PD) is impaired motor ability, which affects facial muscles and expressions as well. Research has shown that people with PD have slower and less pronounced facial movements. Also, their facial muscles may react more strongly to negative emotions (like anger or sadness) compared to more positive ones. Facial expression analysis during a phonation test How can we better understand the link between these changes in facial expression and the severity of Parkinson's disease? That's what researcher Yang and their team aimed to find out. They studied two groups of participants during a phonation test, which involves sounding out different vowels and consonants. Specifically, they included a single-syllable, double-syllable, and multi-syllable test. Earlier research from this group showed that these tests are good indicators of stiffness in the face. Using FaceReader for facial expression analysis, they observed muscle group movements and facial expressions for neutral feelings, happiness, sadness, anger, surprise, fear, disgust, valence, and arousal. RESOURCES: Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Comparing PD patients with healthy controls To study the link between disease severity and facial expressions, the research team compared performance on the phonation test between a patient group and a healthy control group. Their study included 16 patients with Parkinson's disease (average age of 71.38 years) and a matched control group of 16 participants (average age of 66.69 years). For the patient group, the researchers noted disease duration and dosage of anti-PD drugs. Furthermore, they included measures of disease severity from a neurology evaluation, using the Hoehn-Yahr scale (H&Y) and the Unified Parkinson's Disease Rating Scale (UPDRS III). Parkinson's disease, face changes, and severity of disease Consistent with earlier research, the team found that patients with PD showed decreased expressions for neutral feelings, happiness, surprise, valence, and arousal. The patient group also showed increased facial expressions of sadness, anger, fear, and disgust. These results applied to all variations of the phonation test. Furthermore, the researchers found significant correlations between disease severity and facial expressions. In other words, when severity increased, all changes in facial expressions were more pronounced. According to the team, these results suggest that patients with PD may show dull expressions in the middle and late stages of the disease. Parkinson research When we know more about how specific symptoms progress with disease severity, we'll know better how to help people who are dealing with Parkinson's disease. And that's why Parkinson research is so important. As there is no cure for PD, we need to keep developing and refining the best type of treatment. Reference Yang, L.; Chen, X.; Guo, Q.; Zhang, J.; Luo, M.; Chen, Y.; Zou, X.; Xu, F. (2022). Changes in facial expressions in patients with Parkinson's disease. Computer Speech & Language, 72(3), https://doi.org/10.1016/j.csl.2021.101286. --- ## A plant-based treatment for Alzheimer's disease? URL: https://noldus.com/blog/alzheimers-dioscin Published: 2023-03-10 15:00:00 Description: Researchers are constantly looking for new ways to treat Alzheimer's disease. Can Dioscin, a plant-based steroid, decrease the symptoms in mice? Alzheimer's is a neurodegenerative disease afflicting more than 30 million people over the world (WHO). Since Alzheimer's disease (AD) affects not only the physical state of a patient but also the mental state, it is a very difficult disease for patients and their close ones to deal with. Moreover, there is currently no cure for AD, and the detection of the disease is often late, in terms of pathology, since recognizable symptoms do not immediately arise. Researchers are therefore constantly looking for new ways to treat AD and this blog will cover an animal study that assessed whether or not Dioscin could be used for treating Alzheimer's disease. Alzheimer's disease in a nutshell While dementia can take many forms, AD is by far the most common variant and contributes to roughly 60-70% of cases (WHO). As a neurodegenerative disease, Alzheimer's has a major effect on brain activity. It impacts many brain functions from memory and communication, to more motor function related areas coordinating movement and swallowing. The definitive way AD develops it still unknown. But one hypothesis is that plaques and tangles appear in the brain formed by amyloid beta plaque deposition (extracellular) and neurofibrillary tangles (intracellular). Amyloid beta plaques disrupt neuron to neuron signalling, can trigger an immune response and therefore induce inflammation. The neurofibrillary tangles disable neuron function leading to apoptosis. These two processes cause the brain to shrink and thus impair brain function. Currently there is no cure for AD. There are treatments that can improve life quality of AD patients but these solutions often come with many side effects (like nausea, lowered heartbeat insomnia and weight loss). Therefore, it is worth looking into new methods for treating AD. What is Dioscin? As a natural steroid derived from plant extracts, Dioscin has been a part of traditional Asian medicine for quite some time. Dioscin can be extracted from the rhizomes of plants in the Dioscorea genus, a genus that also includes yams. Dioscin works by activating or suppressing certain pathways by bringing about structural changes on a nuclear level. It does this by attacking mitochondria, modifying gene expression, and targeting diseased tissue. Dioscin has shown to be able to complement the functioning of certain types of medication while suppressing some negative effects that medication might cause. Many studies have been done to assess the pharmacological benefits of Dioscin. From anti-inflammatory to anticancer and neuroprotective effects; Dioscin has shown many potential uses. Dioscin has even shown to be able to help in multi-drug resistance by inhibiting the expression of certain proteins. Most of these studies were done in vitro or in vivo in animal models, thus not much can be said about the clinical use of Dioscin at the moment. However, Dioscin does show potential due to its low toxicity. If you want to read more about the applications Dioscin check out the following papers [1,2]. But how would Dioscin help in alleviating symptoms of Alzheimer's Disease? Research has demonstrated that Dioscin has certain neuroprotective properties. It has the ability to regulate neuro-inflammation and alleviate the activation of glial cells (which are often abnormal in AD patients). However, the true mechanisms are poorly understood. Therefore, a study was conducted by Guan et al. to test whether Dioscin could improve brain and motor function in AD challenged mice [3]. Can Dioscin alleviate AD symptoms? For this study, 80 male C57BL/6 mice were divided into multiple groups (multiple levels of Dioscin, a model group exhibiting AD symptoms and a control group, given donepezil). These mice were then tested to see if Dioscin mitigated the effects of AD on spatial memory (using a morris water maze) and physical coordination (using the CatWalk XT). CatWalk XT is a complete system that enables automatic gait and locomotion analysis. During a trial, the footprints of an animal are detected using illuminated footprint technology, and the software automatically records and analysis the data. Lastly, to find out the exact workings of Dioscin several biochemical tests were conducted. RESOURCES: Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Improved cognitive function So, then the question arises, does Dioscin help alleviate AD symptoms? Interestingly, multiple effects of Dioscin were found. Mice that were treated with Dioscin indeed showed an improved cognitive function and better limb balance when compared to model mice. The footsteps of mice were disorganized in the model group, which is characterized by a variable stride size and abnormal gait. However, Dioscin distinctly improved the gait pattern. Moreover, escape latency out of the water maze was improved significantly when the mice were exposed to Dioscin. Measuring the behavior of these animals is key in getting a more complete understanding in these types of studies. Mediating the RAGE pathway But how does Dioscin cause these beneficial effects? The researchers contribute the effects of Dioscin on the mediation of RAGE. This doesn't mean that they went to anger management. RAGE, or receptor for advanced glycation end-products, is a multiligand receptor that mediates inflammation but also induces oxidative stress. RAGE has also been shown to facilitate the transport of amyloid beta into the brain across the blood brain barrier. Lastly, RAGE seems to be linked to the formation of reactive oxygen species (ROS), which in turn leads to oxidative stress. The results from the study done by Guan et al. showed that Dioscin is able to down-regulate the RAGE mediated pathway that lead to neuroinflammation and oxidative stress. This resulted in less damage to the brain and the maintained motor and cognitive functioning, as was seen in the behavioral tests. So what's next? This unfortunately doesn't mean that we can start given every AD patient a treatment with Dioscin. There is currently a lack of information regarding clinical safety of the usage in humans. However, studies like this one are an essential starting point for developing treatments and testing new compounds. If this work continuous, we will hopefully be able to improve the life of AD patients, and possibly look towards a cure in the future. References 1. Yang, L.; Ren, S.; Xu, F.; Ma, Z.; Liu, X.; Wang, L. Recent Advances in the Pharmacological Activities of Dioscin. BioMed Res. Int. 2019, e5763602, doi:10.1155/2019/5763602. 2. Bandopadhyay, S.; Anand, U.; Gadekar, V.S.; Jha, N.K.; Gupta, P.K.; Behl, T.; Kumar, M.; Shekhawat, M.S.; Dey, A. Dioscin: A Review on Pharmacological Properties and Therapeutic Values. BioFactors. 2022, 48, 22–55. 3. Guan, L.; Mao, Z.; Yang, S.; Wu, G.; Chen, Y.; Yin, L.; Qi, Y.; Han, L.; Xu, L. Dioscin Alleviates Alzheimer's Disease through Regulating RAGE/NOX4 Mediated Oxidative Stress and Inflammation. Biomed. Pharmacother. 2022, 152, 113248, doi:10.1016/j.biopha.2022.113248. --- ## What is behavior? URL: https://noldus.com/blog/what-is-behavior Published: 2023-03-03 12:00:00 Description: What is behavior? Behavior is a fundamental aspect of human and animal life. In scientific terms, behavior is a subject of study within the field of behavioral research, which aims to understand different behaviors. Behavior is a fundamental aspect of human and animal life, and includes patterns of behavior, reactions, and activities that individuals or groups exhibit in relation to their environment. The term 'behavior' refers to the observable and measurable activities of humans and animals, ranging from simple reflexive actions to complex cognitive processes. What is behavior? Simply put, behavior is all about exploring and discovering why we do the things we do. In scientific terms, behavior is a subject of study within the field of behavioral research, which aims to understand the causes, mechanisms, and consequences of different behaviors. Scientists observe and study different behaviors to learn what makes us behave the way we do. It includes a wide range of fields, such as psychology, neuroscience, animal behavior and ethology, sociology, and anthropology. Types of behavior When it comes to behavior, it can take on various forms and types, each with its unique characteristics and significance. It can be influenced by a multitude of factors, such as genetics, environment, learning, social interactions, and physiological processes. Understanding the different types of behavior allows researchers to examine and analyze behavior from various perspectives. Behavior can be categorized into different types, including overt behavior (observable actions), covert behavior (internal mental processes), and social behavior (interactions between individuals). Let's dive a little deeper into the different categories of behavior studied in scientific research: 1. Overt Behavior Overt behavior refers to observable actions or activities that can be directly seen and measured. These behaviors can include physical movements, gestures, vocalizations, or any other visible manifestations. For example, a person walking, a dog barking, or a child raising their hand in a classroom are all examples of overt behaviors. By studying overt behavior, researchers can examine the actions and responses individuals exhibit in different situations. 2. Covert Behavior Covert behavior, also known as internal behavior, refers to the mental processes and activities that occur within an individual's mind and are not directly observable. These behaviors encompass cognitive processes like thinking, memory, perception, problem-solving, and decision-making. While we cannot see these behaviors directly, their influence can be inferred through observable actions and external indicators. Psychologists and neuroscientists employ various methods, such as neuroimaging techniques, to study covert behaviors and understand the underlying cognitive processes. 3. Social Behavior Social behavior involves interactions and relationships between individuals or groups. It encompasses a wide range of behaviors, including communication, cooperation, aggression, affiliation, empathy, and altruism. By studying social behavior in either animals or humans, researchers aim to unravel the dynamics of social interactions, the formation of social bonds, and the impact of social factors on individuals' behavior and well-being. Social behavior is of particular importance in research fields such as sociology, anthropology, and animal behavior studies. Elephants are known for their social behavior and strong family and social bonds. Measuring and studying behavior The study of behavior involves observing, describing, and measuring behavioral patterns displayed by individuals or groups, as well as investigating the underlying mechanisms and processes that drive them. Researchers use various methods and techniques, such as observations, and experiments. When studying human behavior researchers can also use surveys or physiological measurements to collect data and analyze behavioral phenomena. You might want to read: Why measuring behavior is awesome (+3 examples to prove it) By studying behavior, we gain valuable insights into the fascinating world of human and animal life, enabling us to better understand ourselves and the intricate tapestry of behavior that shapes our existence. Understanding behavior Understanding behavior is crucial for gaining insights into how organisms interact with their surroundings, adapt to changes, make decisions, and navigate social relationships. It allows researchers to explore topics such as motivation, cognition, emotion, learning, development, and social dynamics. By studying behavior, scientists can unravel the complexities of human and animal life, shedding light on the mechanisms that drive behaviors, identifying factors that influence behavior, and developing interventions or treatments for behavioral disorders. It helps us comprehend the intricacies of our own actions and those of other living beings, ultimately contributing to a deeper understanding of ourselves and the world we inhabit. Reading tip: Understanding behavioral psychology with The Observer XT RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources To summarize In short, behavior refers to the actions and reactions of individuals or groups that can be observed and measured. Behavioral research helps us uncover why people act the way they do, exploring the causes, processes, and outcomes of behavior in different settings. By looking at various types of behavior—what we think, what we do, and how we interact—researchers gain a deeper understanding of how people function. These insights not only reveal the complexities of human and animal behavior but also drive progress in fields like psychology, education, and healthcare, helping us better understand the world. LET'S TALK Start your journey with us today Get in touch if you want to: - Advance your behavioral research - Get expert guidance - Profit from our 35+ years of experience Get started Want to read more on human and animal behavior research? You might want to read one of these articles that we've published on our Behavioral Research Blog: - Behavioral coding: What and how - How to measure emotions - The power of multimodal research in human behavior studies - How to study developmental psychology: methods, designs & tools - 5 Animal blogs not about Rats, mice or zebrafish --- ## In utero alcohol exposure, the effects on brain and behavior URL: https://noldus.com/blog/in-utero-alcohol-exposure Published: 2023-03-02 15:00:00 Description: About 10% of women worldwide drink during their pregnancy. This could cause the fetus to suffer from fetal alcohol syndrome, which can lead altered tissue structures in the brain to motor deficits. Fetal alcohol syndrome Still today, about 10% of women worldwide drink alcohol while pregnant, which can have a severe effect on fetus development. This is called prenatal alcohol exposure (PAE), which could cause nongenetic mental retardation. One of the potential effects of this is the fetal alcohol syndrome (FAS), and is the most severe form of fetal alcohol spectrum disorder (FASD). Drinking alcohol can be harmful for the fetus at any stage of the pregnancy, and affects them throughout their body. However, especially the developing brain is highly affected, which can result in motor deficits and atypical brain structures. Lifelong consequences FASD can have a wide variety of, sometimes lifelong, consequences for an affected child. It's hard to diagnose this syndrome, since there are no clear outward physical signs of it, meaning treatment is often applied with a delay. FASD mouse model A group of scientists from Rouen and Caen in France wanted to test the results of alcohol during pregnancy and lactation, and for that they used mice. The pregnant mice would receive a daily subcutaneous injection with either a physiological saline solution or with diluted alcohol, from gestational day 15 (GD15) to GD20. On parturition/postnatal day 0 (P0) and P1 they received the same injections. After this treatment, the scientists carried out various analyses, like qRT-PCR experiments from RNA, density measurements of oligodendrocytes and measurements of microvascular organization. Read more about these analyses in the original article! Behavioral evaluations Each mouse born from either the alcohol or the control group underwent various behavioral tests. Since humans suffering from FASD often have motor disabilities, the focus of the behavioral tests was on sensorimotor impairments. Rightening reflex The first test consisted of testing the pups' rightening reflex, from P2 to P8. Each pup was put on their back on a flat horizontal surface, and the time they needed to righten themselves properly was noted. These tests were done twice consecutively, with a cutoff time of 60 s. The final rightening time value was calculated as the mean of 2 successive trials. Increased latency The latency of the control mice to turn themselves upright decreased from P2 to P8. The PAE mice tended to rapidly turn back to a prone position, and their latency did not change until P6. Starting that day, they were significantly slower to righten themselves than the control pups. The effect was more clear in female mice. Tilted plane rightening reflex From P5 to P8, the same test was done, but then on a 20° tilted plane with the mouse's head facing downward. Again, the mean time to righten themselves was measured, and the latency for a semi-rotation of 90°. In this test, no significant difference between control and PAE could be found. Locomotion activity In order to find any long-term effects on PAE mice, the scientists tested locomotion activity at P15 and P45. Each mouse was first isolated for 5 minutes in an individual cage, and then put in a sound-muffling 50 x 50 x 38 cm box at 20°C, limiting anxiety. In this open arena they were allowed to explore. Traveling distance Using video tracking in EthoVision XT, the distance that each mouse traveled during a 30-min period was measured . All data was expressed in 10-min intervals and also for the whole 30-min recording period. There was no significant effect of distance travelled on P15, and none either in the time spent in the central zone of the arena. However, at P45, the PAE mice travelled a significantly reduced distance compared to the control, caused by increased periods of immobility in the outer zone of the arena. Sex differences Furthermore, it becomes clear that there are slight sex differences caused by PAE, with the females being slightly slower in the rightening test. It shows that even environment-caused defects could be gender-specific, due to the perinatal life being a vital period for the brain's sexual differentiation. FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Conclusion The behavioral experiments show that prenatal alcohol exposure is capable of causing longterm motor deficits. On top of that, it takes time for the effects of the alcohol exposure to become visible. This means that any treatment applied on humans usually happens with a delay, since it is hard to notice when they are very young. Various brain structures are also affected, please see the original paper below for more information on that part. Reference Brosolo, M., Lecointre, M., Laquerrière, A., Janin, F., Genty, D., Lebon, A., Lesueur, C., Vivien, D., Marret, S., Marguet, F. and Gonzalez, B. J. (2022). In utero alcohol exposure impairs vessel associated positioning and differentiation of oligodendrocytes in the developing neocortex. Neurobiology of Disease, 171, 105791. --- ## Air pollution and brain development, mouse behavior gives insight URL: https://noldus.com/blog/Diesel-fumes-mouse-cognition Published: 2023-02-23 13:00:00 Description: Air pollution can have major detrimental effects on health. But, what happens to brain development if a mouse is only exposed in early life. Researchers from the University of Washington studied just that. Air pollution carries with it a major health risk for human health. Exposure to polluted air can increase the development of cardiovascular and respiratory diseases. Consequently, the World Health Organization estimates that air pollution contributes annually to 7 million deaths worldwide. Hence, it is important to investigate the effects that different types of air pollution can have on the body. Air pollution can impact the brain Previous research on the topic has shown that air pollution can negatively impact the central nervous system. It is important to know how certain polluting substances effect the brain at different life stages, and whether or not these changes persist later in life. Therefore, researchers from the University of Washington (Seattle, Washington, USA) conducted a study, where they investigated the effect of diesel fume exposure in early life on behavioral and biochemical parameters in mice [1]. They were particularly interested in the effect of diesel fumes on the development of Alzheimer's disease. Diesel fumes exposure in early life Fertilized female mice (wildtype C57BL/6J) were individually housed after breeding. They were exposed to a preset amount of air throughout their pregnancy and postnatally until weaning (day 21 after giving birth). The control group received fresh air, while the treatment group were exposed to diesel fumes (250-300µg/m3, over a period of 6 hours daily). This amount is based on equivalent levels that are reported in highly polluted areas [2]. After exposure, both the treatment and control new born mice were group housed and kept for 22 months in fresh air conditions. Interestingly, Garrick et al. found that exposure to diesel fumes affected the birth outcomes. Of the pregnant mice, the group that was exposed to diesel fumes had significantly lower birth rates (54.2% for diesel fumes vs 82.1% for control). Furthermore, the survival of the newborns was also lower for the group exposed to diesel fumes (80.9% for diesel fumes vs 93.4% for control). Home-cage testing using PhenoTyper Alzheimer's is often categorized by a loss in cognitive functioning. Therefore, the behavior of the mice was tested at adult and aged life stages with various tests. The first of the behavioral tests was a home-cage test. Using the PhenoTyper from Noldus, Garrick et al. were able to observe the mice in the same environment for a long duration. They used EthoVision XT in combination with their PhenoTyper to track the movement of the mice during the day and night period. The researchers used EthoVision XT to divide the PhenoTyper into distinct areas during data acquisition. These areas were used to determine the time spend at certain regions of the PhenoTyper as well as overall activity. RESOURCES: Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Interestingly, male mice that were exposed to diesel fumes spent less time at the feeding station and spent less time moving around during the light cycle. This difference was not observed in females. Furthermore, even though this behavioral change didn't persist into later life, a weight reduction was observed for these treatment males. How diesel fumes affect cognitive abilities As previously mentioned, there are strong indications that air pollution can affect the central nervous system. To see if the diesel fume exposure has an effect on cognitive abilities the mice were observed in a T-maze and with the object recognition test. The T-maze and spatial memory The T-maze is used as a measure for exploratory behavior and spatial memory. The object recognition test also measures spatial memory, but more specifically object location memory. The T-maze reflects the function of the dorsal hippocampus, basal fore-brain and prefrontal cortex. On the other hand, the object recognition test engages primarily the dorsal hippocampus. Even though, both experiments test spatial memory the results did differ between the experiments. Aged mice that were exposed to diesel fumes had a modest reduction in spontaneous alternations in the T-maze, but no significant effect of diesel fumes was found in relation to object recognition. This could mean that the effect of the particle matter in diesel fumes is specific to certain brain areas. It could be assumed that the hippocampal memory is not affected by perinatal diesel fume exposure. Instead the exposure to the fumes may cause deficits in the basal fore-brain and prefrontal cortex. Biochemical effect of diesel fumes Naturally, it is also important to look at what is happening inside the body. Garrick et al. measured malondialdehyde levels in the cerebral cortex and the hippocampus as an indicator for lipid peroxidation. The results show that aged mice that were prenatally exposed to diesel fumes were experiencing oxidative stress at an aged stage. This was not what the researchers expected, since most harmful particles that would cause oxidative stress do not persist in the brain over time. However, it seems possible that some particles do continue to stay in the brain. It would be interesting to perform an analysis on the brain to see if these particles truly stay inside the brain for an extended period of time. If these particles remain in the brain for longer periods of time it could give insight to the health risk of early life diesel fume exposure. Do these results translate to humans? Garrick et al. set up this experiment to see whether or not diesel fume exposure in early life could be related to Alzheimer's disease. When looking at classical biochemical pathologies for Alzheimer's (tau neurofibrillary tangles and amyloid beta plaques), they didn't find any differences between control and diesel fume exposed mice. However, Garrick et al. do recognize that the mouse model used in this particular study is not ideal to show Alzheimer's Disease. What Garrick et al. do conclude, is that early life diesel fume exposure could permanently alter neural pathways and the oxidative stress response. Thus, a decrease in worldwide emissions would reduce health risks for exposed children at a later age. However, the researchers say that early life diesel fume exposure alone would not lead to Alzheimer's disease later in life. Using mouse models Of course, directly translating these results to humans is more complicated. However, using these mouse models does give valuable insight in the biological functioning in relation to external stimuli. PhenoTyper enables long term, repeatable and easy measurements. This enables researchers to get the full picture of the behaviors an animal performs, in a less stressful home-cage environment. References [1] Garrick, J.M. et al. (2023) 'Perinatal diesel exhaust exposure causes persistent changes in the brains of aged mice: An assessment of behavioral and biochemical endpoints related to neurodegenerative disease', Environmental Toxicology. [2] Wang, J.-F. et al. (2013) 'Estimation of Citywide Air Pollution in Beijing', PLOS ONE, 8(1), p. e53400. https://doi.org/10.1371/journal.pone.0053400. FREE E-BOOK: Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download --- ## What is the connection between depression and rheumatoid arthritis? URL: https://noldus.com/blog/rheumatoid-arthritis-and-depression Published: 2023-02-16 13:10:00 Description: Is depression in patients with rheumatoid arthritis caused only by the pain, or is something else also going on? Rheumatoid arthritis (RA) is an autoimmune disease in which the joints swell up, causing pain and damage. An autoimmune disease is one where your own immune system attacks your own body, somehow confusing it with something like a disease-causing bacteria. There are about 100 autoimmune diseases including diabetes type I, Crohn's disease and multiple sclerosis (MS). Whereas rheumatoid arthritis is an autoimmune disease, osteoarthritis is age-related. There are also many other less common forms of arthritis. Hand with rheumatoid arthritis (Copyright © James Heilman). Depression in rheumatoid arthritis patients Many RA patients also experience depression, about two to four times as many as in the general population [2]. The large variance is due to the different ways of measuring if someone has depression. At first sight, that is hardly surprising. If you are in pain all the time, then that is likely to cause a negative mood and that can cause depression. Rheumatoid arthritis patients can also experience handicaps due to not being able to use their joints properly, which will also make depression more likely. However, there are some clues that there is more to it than that. For instance, antibiotics can sometimes relieve the symptoms of RA. That is strange; antibiotics kill bacteria, but RA is not caused by bacteria. How is that possible? Gut bacteria Although we tend to think of bacteria as being bad things, causing diseases, actually we would not be alive without healthy bacteria in our digestive tract (and elsewhere). Without those bacteria, we could not take up some of the nutrients that we need. When we take a course of antibiotics, the bacteria in our gut are also killed, although the gut flora quickly re-establishes itself afterwards. Perhaps the effect of antibiotics on RA and the prevalence of depression in RA patients could have a common cause? Gut-brain-microbiota axis That common cause could be found in the gut-brain-microbiota axis. For many years, it has been known that there is an important interaction between the gut and brain for maintaining homeostasis. Homeostasis means regulating that the body so that it maintains a constant state with respect to its internal physical and chemical conditions. This role of the gut is so important that its nervous system (called the enteric nervous system) has been referred to as the "second brain", also because it can act independently of the body's other nervous systems (parasympathetic and sympathetic) which are controlled by the brain. More recently, it has become apparent that the microbiological population of the gut (that is, the bacteria and other microorganisms) also play a crucial role in that relationship, so that it is possible to speak of a microbiota-gut-brain axis. The microbiota and the brain communicate with each other using various routes including the immune system, the vagus nerve and the nervous system of the gut. Various metabolites produced by the microbiota have an effect on those organs, which then have an indirect effect on the brain. T cells For example, lymphoid tissue associated with the gut (called Peyer's patches) can receive signal molecules from gut bacteria and those cells then determine the balance between T-helper and T-regulatory cells. T cells are a sort of lymphocyte (white blood cell), which are a key component of the immune system. When T-helper cells are stimulated by an antigen (e.g. a pathogenic bacteria) they release chemical messengers (called cytokines) which stimulate other lymphocytes to attack antigens. T-regulatory cells control the immune reactions. So if the numbers of T-regulatory and T-helper cells get out of balance, then the whole system will not work correctly. T-helper cell It is known that the gut-brain-microbiota axis can play an important role in depression [3]. T-regulatory cells are reduced in patients with major depressive disorder. That shows the possibility of a direct connection between gut bacteria and depression. Seeing RA is an autoimmune disease, possibly the depression frequently experienced by RA patients could be not just due to the pain, but might be a direct effect caused by the gut-brain-microbiota axis. Transplant experiment Yaoyu Pu and colleagues [1] wanted to investigate if that might be a real connection. Could certain gut bacteria be disrupting the immune system and being an additional cause of why more RA patients often have depression than the general population? That is quite hard to answer, because it is one thing to show a correlation between RA and depression, but that doesn't mean that one causes the other. The cause and effect could be the other way around, e.g. a faulty immune system affecting the gut bacteria and the depression being purely caused by pain. They tackled this problem with an ingenious approach, combining laboratory mice and people suffering from RA. Fecal transplants They transplanted feces from human patients with RA and from a healthy control group, into laboratory mice. Then they measured if there were any differences between the behaviors of the two groups. If the feces from RA patients caused the mice to show depressive-like behaviors, then this proves that it is a real causal effect, not just a correlation. They measured a number of different behaviors in the mice using EthoVision XT. EthoVision is an advanced video tracking system which can accurately measure movements and a range of behaviors in experimental animals. Results: testing depression in mice Locomotion in an open field Firstly, they looked at locomotion. That is simply how much the mice moved around in an enclosed area with nothing in it for ten minutes. They found no difference between the two groups. Lack of activity can be a symptom of depression, but it is also affected by all sorts of other factors like the health status of an animal. Learned helplessness with the tail suspension test Secondly, they carried out two tests related to a concept called learned helplessness. Normally if you try something, and you don't succeed, and then you are faced with the same problem again, you will try again. However, if you are suffering from depression, you are more likely to give up sooner, when you are faced with a problem that you have previously failed to solve. In the tail suspension test, a mouse is suspended by its tail. This does not hurt it, but it does make it anxious. The mouse will try to escape, but after a while, it will give up and become immobile. The idea is that becoming immobile earlier is a measure of depression. Yaoyu Pu and colleagues found that the mice that had received fecal transplants from RA patients were immobile for longer than the mice with transplants from healthy controls. The forced swim test The other test related to depression is the Porsolt forced swimming test. In this test, mice are placed in a glass cylinder, half filled with water. At first, the mice try to escape, but after a while, when they fail to climb the cylinder's walls, they give up. The mice which had received the fecal transplants from RA patients gave up significantly earlier than the control group. Sucrose preference test The final test that they did was the sucrose preference test. In that test, the two mice groups are fed water & 1% sucrose (sucrose solution) for 48 hours, which was followed by four hours with neither water nor food. After that, they had acces to a sucrose solution for one hour. The amount of sucrose solution consumed in that hour is measured. The idea is that the more pleasure they get from the sweet sucrose, the more they will drink. A symptom of depression is a reduced ability to experience pleasure, in this case reduced sucrose preference, also called anhedonia. In the RA treatment group, sucrose preference was significantly lower compared to the control group. Gut microbiota Both groups of mice were treated with antibiotics before the experiment, so their gut flora would be severely reduced, such that they can be assumed to have a similar starting point. After the fecal transplant, the mice receiving the feces from RA patients had a completely different gut flora (bacterial composition) than the mice receiving feces from the control group. The RA group also had a much greater diversity of microbiota than the controls. Conclusions The conclusion of Yaoyu Pu his colleagues was that the data indicate that fecal transplants from rheumatoid arthritis patients could activate abnormal differentiation of T cells by changing the gut microbiota in the antibiotic treated mice. The T-regulatory cells protect against depressive behaviors in rodents. This study showed that alterations in the gut microbiota can cause a decrease in T-regulatory cells, leading to systematic inflamation, which in turn can lead to depressive like behaviors. Their final conclusion was the traditional one, that more research is needed. The study indeed raises all sorts of interesting questions. Mice and human gut anatomy are very different [4]; how much did that affect the results? Laboratory mice are kept in a sterile environment and fed a very uniform diet, might that cause the gut flora to develop in a different way? What happens if you compare fecal transplants from people with and without depression (but with RA)? How much of the depression is caused by the pain of RA and how much by the gut bacteria? Yaoyu Pu's paper is actually more complex than the simplified version presented here, with additional experiments and measurements. It is available open access and I encourage you to take a look [1]. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial References - 1. Yaoyu Pu, Qiuping Zhang, Zhigang Tang, Chenyang Lu, Liang Wu, Yutong Zhong, Yuehong Chen, Kenji Hashimoto, Yubin Luo1and Yi Liu (2022). Fecal microbiota transplantation from patients with rheumatoid arthritis causes depression-like behaviors in mice through abnormal T cells activation. Translational Psychiatry 12:223. https://doi.org/10.1038/s41398-022-01993-z - 2. Margaretten M, Julian L, Katz P, Yelin E. Depression in patients with rheumatoid arthritis: description, causes and mechanisms. Int J Clin Rheumtol. 2011;6:617–23. - 3. Cryan JF, O'Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, et al. The microbiota–gut–brain axis. Physiol Rev. 2019;99:1877–2013. DOI: 10.1152/physrev.00018.2018 - 4. Mouse and human abdominal anatomy --- ## How to make communication easier for children with severe motor impairments URL: https://noldus.com/blog/communication-made-easier-with-eye-gaze-assistive-technology Published: 2023-02-07 09:15:00 Description: A decrease in the ability to make contact with others leads to limitations in communication. A Swedish research team investigated whether eye tracking assisted therapy could help children with motor impairments communicate. Communication has a central function in our life: body language, gestures, gaze direction, intonation, sounds, words, you name it. Every day we use words and sentences to communicate with each other. We ask each other how things are going, we tell each other what is on our mind, and talk about what keeps us busy. Verbal behavior is inseparably linked to communication. Making communication easier But what if speaking or making words is difficult or not possible? If you know what you want to say, but you can't say it? For example, if you are dealing with severe motor impairments due to cerebral palsy or a posture and movement disorder. This can result in limited oral motor skills or control over breathing, voice, or articulation. Besides, the mouth area can be very sensitive, causing strongly deviant mouth movements. Or due to Rett syndrome, a rare genetic neurodevelopmental disorder. This disorder particularly affects speech, purposeful hand use, and coordination, leaving individuals understanding more than they can communicate. This decrease in the ability to make contact leads to limitations in communication. This could hinder the motivation to communicate, halt communication development, and restrict participation in social life. Or are there ways in which these individuals can be helped to communicate in ways other than speech? To make communicating easier? FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Opportunities to communicate using eye-gaze assistive technology For example, we can use eye-gaze assistive technology (EGAT). This can provide children with severe motor and speech impairments other communication opportunities, by using their eyes to control a communication interface on a computer. This innovative technology can detect eye movements using a specialized infrared video camera mounted on a tablet/computer. It requires less physical effort and assistance from communication partners, resulting in the opportunity for the children to take initiative, express opinions, and interact with others. Gaining more control is critical for these children in order to enjoy shared participation and build self-efficacy. An international team controlled by Yu-Hsin Hsieh from Stockholm University and Maria Borgestig from Uppsala University, both in Sweden, investigated the impacts of employing EGAT on communicative interaction, compared to the Non-EGAT condition. Communication is part of the interaction Communicative interactions provide the foundation for cognitive and social development early in life and continue to affect our behaviors, social patterns, and thoughts throughout our lives. It includes behaviors such as initiation of a conversation, giving responses, answering questions, and making a request. For this international study, the research team formulated two main questions to be answered: - Which interactional structures are shown by children/youths with complex needs and their communication partners when EGAT is or is not used? - Which communicative functions are used by the dyads when EGAT is or is not used? They expected that children would more often take initiative in communicative interaction when they used EGAT than when they did not, and that communication partners would take fewer communicative turns and make fewer requests or demands. Data was collected from the Assisted Therapy centers in Sweden and special needs school in Dubai and the USA. Coding behavior to investigate communicative interaction The participants (aged 4-19 years old) and their communication partners were recorded 5-10 minutes per day in a natural setting, during three consecutive days. Their facial expressions, gaze direction, body movements and gestures, and the computer screen with EGAT were captured during a communication activity. Such an activity was for example playing, performing an educational or mealtime task, or talking with an adult about something that had happened. The participants were involved in both EGAT and Non-EGAT conditions. Interesting reading material: In FaceReader Online it is now possible to perform eye-tracking analysis with a regular webcam, which increases flexibility greatly. Read more about the methodology and accuracy in the white paper 'EyeReader'. A systematic coding scheme was used to investigate the characteristics of communicative interaction between the dyads. The coding scheme consisted of subjects (e.g. child and parent), behaviors (e.g. moves such as initiation and response), and modifiers to specify the behaviors of the subjects (e.g. requests or informative). FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Observe, code, and analyse behavior The Observer XT was used to analyze each specified communicative interaction behavior in the participating dyads, as well as to check inter-rater reliability. The research team reports that when using EGAT, the children/youths initiated a conversation more frequently and tended to provide more information during the communicative interactions. Their communication partners made fewer communicative turns, initiated less frequently, and made fewer requests compared to the Non-EGAT condition. This study supports that children can benefit from using this technology to increase the power of communication during social interactions. It will enlarge their roles as active participants. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Tools to study children's development In the Noldus Webinar about Research tools in Developmental Psychology, we explained how our research tools can be used to study the behavior of children both in a natural and in a laboratory setting. Curious? Watch the webinar on demand now! References - Hsieh, Y.-H.; Borgestig, M.; Gopalarao, D.; McGowan, J.; Granlund, M.; Hwang, A.-W. & Hemmingsson, H. (2021). Communicative Interaction with and without Eye-Gaze Technology between Children and Youths with Complex Needs and Their Communication Partners. International Journal of Environmental Research and Public Health, 18, 5134. https://doi.org/10.3390/ijerph18105134 - https://www.rettsyndrome.org/ --- ## How to deal with noncompliant toddlers URL: https://noldus.com/blog/effects-modeling-collaboration-noncompliant-toddlers Published: 2023-02-02 10:50:00 Description: We’ve all been there: getting a toddler to do what you want is a real challenge. What should you do in this situation? Researcher Larzelere and his team studied how behavioral modeling and collaborating can help. We've all been there: getting a toddler to do what you want is a real challenge. Especially when you're clearing away toys. So, what should you do in this situation? Researcher Larzelere and his team studied how behavioral modeling and collaborating can help. Not just during the clean-up, but to improve children's future behavior as well. Their mission? To provide enough detail with their research to really help parents. Modeling the right behavior Many examples of developmental psychology research have demonstrated the effects of modeling on behavior, including prosocial actions, antisocial behavior, and coping strategies. But what about noncompliant behavior? As we all know, it's very common for young toddlers not to listen to their parents. To elaborate on existing theories of effective parenting, it would be valuable to know how best to respond to noncompliant children. The best way to do that, is to get really specific about what you're studying. That's why the researchers from this study distinguished between two types of behavior modeling: indirect and deliberate modeling. Indirect modeling means that children simply observe adults' behaviors, without the adults trying to get their attention. With deliberate modeling, on the other hand, the adult actively encourages the child to observe and imitate their behavior. Let's work together They also examined the effects of collaborating, which is a more direct way to get a child to cooperate. It also relies more on the relationship between a parent and a toddler. Research shows that having these kinds of interactions at a young age has a positive impact on children's development. For example, it helps to strengthen their compliance, self-regulation, and conscience development. Knowing more about the effects of collaborating when a child is noncompliant may help parents to foster the right environment to improve future behavior. Immediate and long-term effects So, what kind of effects were Larzelere and his team looking for? First, they examined the immediate effects of modeling and collaboration on a toddler's compliance. In other words: were the children more likely to help their mothers in clearing away their toys? Second, the researchers examined the long-term effects on behavior control, after 2 and 16 months. By studying multiple time intervals, as well as two different types of modeling, they were able to study these behaviors in great detail. Coding behavior in mother-toddler interactions During their experiment, the researchers observed 85 mother-toddler pairs during a 5-minute clean-up task in the laboratory. Using The Observer XT, coding behavior continuously was an easy task for the research team. Other measures included questionnaires about child behavior and discipline practices, as well as detailed descriptions of discipline episodes. To improve their results, they also considered possible confounding variables. The researchers expected both modeling and collaboration to have a positive effect on cooperation, as well as long-term child behavior. They also hypothesized that deliberate modeling would have a greater effect than indirect modeling. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Collaboration is key Their results showed that both forms of modeling and collaborating were immediately effective in getting toddlers to cooperate. Collaboration was especially effective, they found, when toddlers were not cooperating at the beginning of the clean-up task. And what happened after the experiment? Surprisingly, when reviewing long-term results, only collaborating predicted any significant improvements in toddlers. After 2 months, toddlers showed fewer externalizing behavior problems. Furthermore, the children showed greater behavior control after 16 months. As the researchers hypothesize, these results may reflect the benefits of a positive parent-child relationship, where collaboration is common. This type of interaction may help to model larger values, such as cooperation, working together, and staying on task. Recommendations for parents Based on these results, what can Larzelere and his team recommend? For parents, it may be a helpful strategy to collaborate with their young children when they're not listening. For example, handing them a toy and asking them to put it away. Or making a deal to finish a task together. Specific recommendations like these are more meaningful than advice like "just be positive" or "don't be harsh." Reference Larzelere, R.E.; Ritchie, K.L.; Knowles, S.J.; Curtis, J.; Lin, H.; Oliver M.G.; Bigler, J.F.; Larzelere, W.A. (2022). Immediate and longer-term effects of modeling desired behavior and collaborating when toddlers are noncompliant. Journal of Child and Family Studies, https://doi.org/10.1007/s10826-022-02367-1. --- ## Zebrafish behaviors shows true effect of chemicals on aquatic animals URL: https://noldus.com/blog/cpc-zebrafish Published: 2023-02-01 13:00:00 Description: Modern industrial processes, agricultural practices and domestic waste result in all sorts of chemicals getting into our waters. CPC is widely used. How does it affect the fish? Modern industrial processes, agricultural practices and domestic waste result in all sorts of chemicals getting into our rivers and streams. Nutrients like nitrogen and phosphorus can cause algal blooms and eutrophication, leading to severe reductions in biodiversity. Medicines can have all sorts of unexpected effects on aquatic animals. For example, metformin (a medicine commonly used to treat diabetes) changes the hormone levels in fish, causing disruption of the development of their sexual characteristics, so that some fish have both male and female organs. Chemicals in fresh water | CPC In addition, there are all sorts of other chemicals which we use which end up in freshwater. One of those is CPC, or cetylpyridinium chloride, to give it its full name. It has antiseptic, antibacterial and fungicidal properties, so it is used in a wide variety of products. You find it most often in mouthwashes, but it is also used in deodorants, shampoos, toothpastes, and dental plaque inhibitors. It is even used sometimes to reduce microbes in food products. It is completely safe for human use (at normal doses), but that is another story when it comes to fish (and probably other aquatic organisms, although less is known about that). Because it is used so widely, quite a lot goes down the drain. Some water treatment plants remove almost all of it, especially those with UV-C treatment facilities. However, not all (especially smaller) treatment plants have that capability. In some areas, up to 50 µg/liter is found [1] in the water. That is enough to kill some invertebrates outright [2]. Zebrafish study Kejung Dong and her colleagues [3] investigated what that sort of concentration (and lower) does to fish. They used zebrafish (Danio rerio). Zebrafish is a model species used in all sorts of different experimental paradigms, so a lot is known about it. The fish were placed in clear water with 10 and 40 µg/liter of CPC in it for only four days. They also looked to see if the effects were different for juveniles and for adults. Although they only used three replicates per treatment, they still got very significant results. Fish behavior Shoaling Firstly, they looked at the behavior of the fish. Their experiments were carried out in a special chamber called DanioVision and measured using EthoVision XT software, both from Noldus. That setup provides accurate measurements of how the fish move and behave. The behaviors measured were locomotor activity (using EthoVision's Mobility parameter) and shoaling (defined as all five individuals staying within a circle of 7 cm diameter) as well as other measures of social activity like frequency of body contact and the average distance between individuals. Locomotion and social interaction The CPC decreased the locomotor activity of the fish (how much they moved), and it also decreased their social interactions. There were effects on body contact, distance between the fish and shoaling. The juveniles were more sensitive to the CPC than the adults. Brain chemistry The researchers also measured the neurotransmitter levels in the fish's brains, especially dopamine and serotonin. Like in humans, those neurotransmitters are important mediators of various behaviors in fish like zebrafish (teleost fish). Neurotransmitters are chemicals in the brain that enable a signal to be passed on from a nerve cell to another nerve cell (or sometimes another type of cell). Dopamine Dopamine is important in reward, motor and memory functions. Anticipating a reward causes dopamine to increase, and many addictive drugs work by affecting dopamine. Dopamine signals the desirability of a given outcome, which propels the animal's behavior towards achieving that goal. When the juvenile zebrafish were exposed to CPC, the dopamine activity (DOPAC/DA ration) significantly decreased. The adults didn't show an effect. Seratonin Serotonin controls fighting behaviors (aggression, threats, etc; agonistic behaviors), stress responses and social behaviors like shoaling. The serotonin turnover was significantly reduced in the adults when they were exposed to CPC. The importance of investigating the effects of chemicals on fish behavior The study by Kejung Dong and her colleagues [3] was the first to show that when fish are exposed to CPC at the sort of concentrations that might typically be found in the environment that they show both behavioral changes and that those can be explained by changes in neurotransmitter levels. Would those changes in behaviors affect the fish? Shoaling is an important behavior for fish to resist predation and locomotor activities are essential for all sorts of activities like feeding, spawning, migrating and avoiding predators. Vulnerable juvenile fish are worse affected than adults. If those behaviors are negatively affected, then that will certainly have negative affect on the fish populations - and therefore on the whole aquatic ecosystem. Traditionally, environmental impact of chemicals is assessed by simple toxicological tests of how much of the chemical is needed to kill an animal (LC50 tests). This study clearly shows that this can be far too simplistic approach and that, if you really want to understand the effects of a chemical on an ecosystem, then it is also necessary to look at how it affects key aspects like the animals' behaviors. FREE DEMO Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free Demo References - 1. Shirvas & Wu, 2007. A rapid, sensitive and effective quantitative method for simultaneous determination of cationic surfactant mixtures from river and municipal wastewater by direct combination of single-drop microextraction with AP-MALDI mass spectrometry. J. Mass Spectrom. 42, 1637–1644. - 2. Li, M.H., 2012. Survival, mobility, and membrane-bound enzyme activities of freshwater planarian, Dugesia japonica, exposed to synthetic and natural surfactants. Environ. Toxicol. Chem. 31, 843–850. - 3. Kejun Dong, Lixia Li, Chen Chen, Michaela Sia Tengbe, Kun Chen, Yanhong Shi, Xiangyang Wu, Xuchun Qiu, 2022, Impacts of cetylpyridinium chloride on the behavior and brain neurotransmitter levels of juvenile and adult zebrafish (Danio rerio). Comparative Biochemistry and Physiology, Part C 109393, https://doi.org/10.1016/j.cbpc.2022.109393 --- ## Classical music affects affiliative behaviors in bottlenose dolphins URL: https://noldus.com/blog/classical-music-dolphin-behavior Published: 2023-01-26 12:00:00 Description: Researchers from the University of Padova used The Observer XT to measure the behavior of dolphins when exposed to different types of enrichment. Music can have a major influence on the emotional state of both humans and animals. In the past, studies in a variety of mammals have shown that classical music can decrease agitated behaviors and increase social behaviors. Therefore, it has been assumed that classical music can be used to improve the welfare of captive animals by decreasing their aggression and relaxing them. Studying behavior in bottlenose dolphins with classical music Scientists from the university of Padova studied the response of bottlenose dolphins (Tursiops truncates) to classical music, by doing behavioral observations using The Observer XT. Different types of enrichment Enrichment is an important part of keeping animals in captivity. It reduces stereotypical behaviors and stimulates the animals to interact with the enrichment. In this study, aside from classical music, three other types of enrichment were utilized to control for any aspect of the classical music that could have elicited a behavioral response. Firstly, rain sounds were used to see whether or not sound characteristics matter when it comes to supplying sound as an auditory stimulus. Secondly, a slide show of photographs was provided to see if a visual and auditory stimulus induce different responses in dolphins. Lastly, dolphins were provided with very familiar floating objects in their enclosure. These objects were used to see whether or not the novelty of enrichment would induce a response. The researchers used The Observer XT to observe the animals from video recordings taken before, during and after the enrichment was provided. Both the relative duration of certain behaviors (% of total time), as well as the frequency of these behaviors (events/20minutes) were used in their analysis. Classical music has positive effects on the affective state Synchronized swimming, frequency of touches and interest shown in other dolphins were increased when dolphins were provided with the classical music when compared to other types of enrichment. Furthermore, the supplementation of classical music also increased the amount of touches to a conspecific dolphin after the music had stopped. All these behaviors are categorized as social behaviors in dolphins. An increase in social behavior could originate from both negative and positive affective states. When exposed to stressors, dolphins will comfort each other as a form of social support. However, the researchers concluded that this is unlikely in this case since behaviors related to stress were not increased with the addition of classical music. Therefore, it is assumed that this observed behavioral change is due to a positive affective state in the dolphins. The music would, similarly to humans and primates, excite the endogenous opioids system, which will give a sense of pleasure to dolphins. It is hypothesized that species that employ vocal learning, which includes dolphins, can synchronize their behavior to the beat of sounds in their environment. The harmonic sound of the classical music could have improved the capability of the dolphins to coordinate behaviors, which would improve social bonding. What to do with these results The researchers concluded that classical music, as an enrichment for dolphins, could be used to facilitate enrichment in situations where social interaction should be encouraged. For example, introducing a new animal to the group or to encourage mating behavior. The researchers were able to use The Observer XT to easily analyze the behaviors of multiple dolphins over many trials. Recording the behaviors beforehand allowed for more accurate analysis and easier cooperation between different researchers. The Observer XT has many more features that could enhance your behavioral research, like synchronizing multiple signals from video, audio and physiological data, as well as tools to easily visualize results. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Literature Guérineau, C., M. Lõoke, G. Ganassin, D. Bertotto, M. Bortoletti, L.Cavicchioli, S. Furlati, P. Mongillo, and L. Marinelli. 2022. Enrichment with classical music enhances affiliative behaviours in bottlenose dolphin. Appl. Anim. Behav. Sci. 254:105696. --- ## Measuring behavior of coral larvae in response to antifouling coatings URL: https://noldus.com/blog/measuring-behavior-coral-larvae Published: 2023-01-12 14:00:00 Description: What effect do ship hull coatings have on coral viability and restoration? And how can non-toxic alternatives effect mobility behavior in coral larvae? The pressure on tropical coral reefs and coastal areas due to climate change and human activity remains ever-increasing. Heat stress is a well-known example as one of these factors, but also antifouling agents from ships (mostly from ship groundings) can lead to heavy contamination of coral reefs. Toxic marine coatings Antifoulings, usually applied in by painting, are specialized coatings on hulls of ships (or other marine man-made structures) to slow down or even prevent the growth of (sub)aquatic organisms. This is aimed at performance and cost management of said ship. Historically, antifouling paints have been known to contain a considerable amount of toxic compounds, such as tributyltin (banned) and copper, greatly affecting marine life. Paint particles eaten by the smallest of organisms, such as (zoo)plankton, can trickle down into the food chain and cause bioaccumulation in larger species such as fish. The effect of antifoulings on coral reefs In coral reefs, antifouling agents have been found to inhibit coral larval settlement and survival, which are crucial for reef recovery. Non-toxic antifouling alternatives may decrease toxicity, which indeed seems to be the case for coral larvae [1]. However, Lisa Röpke from the Leibniz Centre for Tropical Marine Research in Bremen (Germany), flags attention for behavioral responses in coral larvae such as mobility/swimming activity during exposure to these potentially non-toxic agents. If mobility of coral larvae is compromised in any way, other functional responses such as habitat selection, feeding, predator avoidance, competition and reproduction are also at risk, all-in-all reducing fitness and survival of coral larvae. This is why measuring behavior is crucial and the development of innovative tools, that allow for automatic and quantitative measurements of behavior, may complement ecotoxicological studies significantly. Acropora millepora and EthoVision XT Röpke's most recent study focusses on the behavior of Acropora millepora coral larvae [2]. Per exposure group, 32 larvae were recorded for 25 min in a dark box while tracking analysis was performed with Noldus' EthoVision XT. Three recently-developed, and potentially non-toxic, antifouling coatings were tested: (1) antiadhesive (silicon-based sol-gel coatings which exhibit antiadhesive surface properties), (2) cerium dioxide (CeO2-x) nanoparticle and (3) encapsulated biocide dichlorooctylisothiazolinone (DCOIT). RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Decreased mobility Swimming velocity and activity of Acropora millepora coral larvae were measured, and were found to be considerably decreased during exposure to all three antifouling compounds, with a 2-fold decreased mean swimming velocity in one treatment, compared to the control. In the DCOIT exposed group, activity and velocity were decreased to almost zero. Dark box recording setup with antifouling-coated tile and silicone ring pools with coral larvae (Copyright © Lisa Röpke) Measuring behavior is essential Measuring behavior in coral larvae is extremely innovative. And the results of this study by Röpke et al. suggest that these coatings do have an effect on larval behavior, however without a clear indication whether this is due to biochemical interaction(s) with the larvae, toxicity, physical topographies, or some combination of these. The coatings measured in this study were originally presumed to be non-toxic, thus to not cause mortality or interferences with juvenile coral fitness. However, when applied freshly without former conditioning in natural seawater they do seem to affect ecologically relevant parameters that are of extreme importance to coral reef viability. These changes in behavior are thus important endpoints to consider. Standardization The study by Röpke [2] also provides an insightful manual for using EthoVision XT with coral larvae, providing other scientists the means to perform rapid and reliable quantification of behavior in similar research, while also working towards standardization of such protocols. Lisa Röpke is in the final stages of her PhD studies. Feel free to contact her regarding any questions on her study via email: lisa.roepke@leibniz-zmt.de Copyright © Jan Meier, Leibniz Centre for Tropical Marine Research (ZMT) Literature - 1. Roepke, Lisa K.; Brefeld, David; Soltmann, Ulrich; Randall, Carly J.; Negri, Andrew P.; Kunzmann, Andreas (2022). Antifouling coatings can reduce algal growth while preserving coral settlement. Sci. Reports 2022 121, 12 (1), 1–14 - 2. Roepke, Lisa K.; Brefeld, David; Soltmann, Ulrich; Randall, Carly J.; Negri, Andrew P.; Kunzmann, Andreas (2022). Applying behavioral studies to the ecotoxicology of corals: A case study on Acropora millepora. Front. Mar. Sci., 9, 2458 --- ## Network and learn – our favorite neuroscience conferences in 2023 URL: https://noldus.com/blog/neuroscience-conferences-2023 Published: 2022-12-27 12:00:00 Description: We’ve put together a short list of the best (behavioral) neuroscience conferences for you to attend. Opportunities to meet up and talk science! This list contains conferences for the year 2023. We have recently uploaded a blog about the 2024 conferences, which you can find here. It's January, and last year was a tumultuous year to say the least. But, also a year in which we finally got to meet you face to face again at conferences such as Neuroscience 2022. Now, let's look forward to next year. We've put together a short list of the best (behavioral) neuroscience conferences for you to attend. Opportunities to meet up and talk science! Meet Noldus at some of these neuroscience meetings this year! These 11 neuroscience conferences have been a stapler on many calendars for years. They have been some of our favorite meetings when it comes to meeting researchers and customers. We're looking forward to meeting you again in person and can't wait to see you at some of these neuroscience conferences! MITT-ANA 2023 | February 1 – 3 Budapest, Hungary The Hungarian Neuroscience Society (MITT) and the Austrian Neuroscience Association (ANA) invite all neuroscientists to their joint meeting this February. Scientists from all over the world will give lectures, which will be complimented by symposia and poster sessions. This meeting is an example of long-standing collaborations between Austrian and Hungarian neuroscientists. We are looking forward to meeting you in Budapest. More information: www.mitt2023.mitt.hu Göttingen Meeting | March 22 – 24 Göttingen, Germany The German Neuroscience Society is hosting their 15th Göttingen Meeting. 7 plenary speakers, 36 planned symposia, and plenty of face-to-face discussions in front of posters are what is waiting for you in Germany this March. Discover the latest scientific and technological developments in the world of neuroscience. Of course, there will also be an exhibition. We are also excited to attend this conference, so come and visit us at booth #42. More information: www.nwg-goettingen.de/2023/ AD/PD 2023 | March 28 – April 1 Gothenburg, Sweden The International Conference on Alzheimer's and Parkinson's Diseases and related neurological disorders, or AD/PD conference as most of us know it, is striving for a better future for all those affected by neurodegenerative diseases. Visit Gothenburg at the end of March for new insights on disease mechanisms, the latest in clinical trials, and advanced in diagnostic markers. Of course, it's also an excellent place to meet up and network and learn about collaboration strategies. More info: www.adpd.kenes.com FENS regional meeting | May 3 - 5 Algarve, Portugal Founded in 1998 at the first Forum of European Neuroscience, the FENS (Federation of European Neuroscience Societies) is the main organisation for neuroscience in Europe and has more than 22,000 member scientists. The FENS organizes Forums, regional meetings, and Brain Conferences. Coming up this May is the regional meeting in Portugal, organized by the Portuguese Society for Neuroscience. More information: fensrm2023algarve.pt NeuroFrance 2023 | May 24 - 26 Lyon, France After a virtual event in 2021, Lyon is the home of a full live conference where neuroscientists from all over France will share their research, host mentoring sessions for young researchers and have interventions from clubs and research groups. We will also attend as an exhibitor, and we hope to see you at the trade exhibition. Looking forward to seeing you in France! More information: www.neurosciences.asso.fr/SN23/ 16th Canadian Neuroscience Meeting | May 28 - 31 Montréal, Canada Mark your calendars for the next Canadian Neuroscience Meeting! The Canadian Association for Neuroscience (CAN) is the largest association of neuroscientists in Canada and is dedicated to advancing brain research. Four days of plenary and parallel symposia, poster sessions, and of course an exhibition and plenty of opportunities to socialize and network. Preceded by public lectures on Saturday. Will we see you in Montréal this spring? More information: can-acn.org/meeting-2023/ BUYER'S GUIDE The perfect video tracking setup Interested in creating a video tracking setup, but you don't know where to start? Then this buyer's guide is for you! - Benefits of video tracking software - Additional equipment options - The ideal setup for your study Download 32nd IBNS Annual Meeting | June 25 - 30 Niagara Falls, Canada The scenery alone is worth traveling to Niagara Falls – the Sheraton Fallsview hotel that is hosting this meeting has breathtaking views of all three waterfalls! Founded in 1992, the IBNS has members from 34 countries and consists of scientists, clinicians, teachers, and others with a background and interest in the relationship between brain and behavior. Amongst four keynote speakers is Suzana Herculano-Houzel, Ph.D. She will be talking about her work on a new framework for the evolution of brain diversity. We will also attend this conference to talk with you about the latest developments in the field of behaviroral neuroscience. More information: www.ibnsconnect.org/2023-annual-meeting 12th European Zebrafish Meeting | July 9 - 13 Krakow, Poland Not only is Krakow a beautiful city to visit, it is also the home of the 12th European Zebrafish meeting. This conference is a collaboration between the Polish zebrafish society, European zebrafish society, international zebrafish society and Krakow's own Jagiellonian University. A wide variety of topics about zebrafish research will be discussed during this 4-day meeting. We will also attend, and hope to see you this summer in Krakow. More information: zebrafish2023.org 20th SINS National Congress | September 14 - 17 Turin, Italy The National Congress of the Italian Society for Neuroscience (SINS) is held in Turin this September. The organizers are excited hold a live event with multidisciplinary topics. They will be focused on processes regarding nervous system function, and pathogenesis of neurological and psychiatric disorders. See you in Italy! For more information visit: www.sins.it 16th international Congress of the Polish Neuroscience Society | September 20 - 23 Toruń, Poland There is another conference in Poland, but this time it's moving to Toruń for the 16th international Congress of the Polish Neuroscience Society. This conference is co-organized by the Nicolaus Copernicus University and will take place in the university facilities. Aside from opportunities to learn from established colleagues, the organizers are also focusing on reconnecting after years of online meeting. With exciting social events, they hope to facilitate a great environment for learning and connecting. More information: congress2023.ptbun.org.pl/ Neuroscience 2023 | November 11 - 15 Washington DC, The United States The Neuroscience meeting (or SfN annual meeting, as it is known to some) will take place in Washington this year! It's the premier event for scientists from around the world to congregate to share and discover new research. Themes and topics include everything neuroscience, from development, neurodegenerative disorders, motor and sensory systems, integrative physiology and behavior, to cognition, history, ethics, and education. We were just at the last Neuroscience meeting in San Diego a couple of weeks ago, and we have already started preparations for this meeting. We cannot wait to meet you there! More information: www.sfn.org/meetings/neuroscience-2023 PRODUCT OVERVIEW Behavioral research solutions Download our free product overview and find out which Noldus products are suitable for your research. - Divided into research areas - Find the solution for your research - Trust our 30 years of experience Download --- ## Extracellular vesicles from umbilical cords improve traumatic spinal cord injury URL: https://noldus.com/blog/new-treatment-spinal-cord-injury Published: 2022-12-22 14:00:00 Description: Spinal cord injury is crippling and hard to treat. Secondary injury caused by inflammation and scarring significantly impact motor function and locomotion. Extracellular vesicles can improve recovery. Traumatic spinal cord injury could happen to anyone, and it is a very crippling neurological disorder. Spinal cord injury treatments Available treatments are not bad, but a group of scientists from Austria and Croatia thought they could still be improved significantly. They developed a new version of a potential treatment, which decreases the consequences of secondary damage after a traumatic spinal cord injury. Inflammation and scarring The initial injury triggers inflammation in the body, causing secondary damage. This happens very soon after the injury, so any treatment needs to be applied as soon as possible. Usually, the local inflammation is maintained by the body, which on one hand helps repairing the damage done, but on the other hand is suspected to block healing. The latter seems to be caused by the forming of fibroglial scarring at the injury site. Basic treatment with extracellular vesicles Once someone has received a traumatic spinal cord injury, they usually receive a systemic treatment with a specific type of extracellular vesicles (EVs). These EVs are from human umbilical cord mesenchymal stromal cells (hUC-MSCs). However, it is suspected that this systemic treatment does not work fast enough and that a local delivery of high doses is needed instead. Experimental treatments In order to test these ideas, the scientists tested various treatments using a rat tSCI (traumatic Spinal Cord Injury) contusion model. They used 4 groups of 26 female rats each. One group was the control, the other groups received either a vehicle injection, an EV injection to the lesion site or an EV injection to the tail vein. All groups underwent the same surgery (a laminectomy). The rats underwent various motor function and locomotion tests, a thermosensitivity test and bladder voiding checks (see paper for the latter two). Surgery and treatment All rats underwent a laminectomy, where a contusion was applied to vertebra Th8. Immediately after, all rats (except the control group) received an injection either at the lesion site or in the tail vein. Following surgery and treatment, the rats underwent various tests in order to find out the long-term results of the treatments. Motor function and locomotion Following the traumatic spinal cord injury, the researchers tested the rats' motor function, locomotion and response to thermal stimuli in order to check their neuroregeneration. Before surgery, the rats had had 4 weeks of acclimatization to handling of experimenters, including 2 weeks of training for the tests. The last training pre-surgery was intended as a baseline comparison. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Mobility Using a 1m diameter arena, the rats' BBB-score (0-21) was taken regularly until week 8 post-injury. From being nearly paralyzed, the rats' mobility improved significantly, with the lesion site EV injected rats recovering fastest after week 2 post-injury. In another test, conducted once pre-surgery and twice post-surgery, they walked an irregularly spaced horizontal ladder. Each rat walked 3 times, on different ladders, and the missteps were calculated. The EV treated rats performed slightly, but not significantly, better at week 8 post-surgery. Gait analysis Lastly, the rats' gait was analyzed, using Noldus CatWalk XT. Apart from gait, the program also analyzed limb coordination. Each rat walked over a glass plate towards a goal box several times. Using the built-in camera, the rats' pawprints were documented individually and automatically. The rats had to complete 6 valid runs, meaning walking across the recording window without pause. These tests were done 2 times pre-surgery, and at weeks 3, 5 and 7 post-surgery. Starting from week 5, the lesion site EV injected rats performed, not quite significantly (p = 0.06), better than the intravenous EV injected rats. Recovery from traumatic spinal cord injury Rats treated with an intralesional injection of EVs recovered significantly better than the other treatment groups. Especially long-term recovery is improved by this treatment. Generally, both EV treated groups recovered better than the vehicle-treated rats. Reduction of inflammation and scarring The researchers found that acute intralesional EV application significantly reduced inflammation during the acute phase post-surgery, and is expected to improve long-term functional outcome. This reduced inflammation is still detectable at day 14 post-surgery, and also helps reducing scarring. The latter effect was not nearly as strong in intravenous EV injection. However, since post-tSCI scarring in humans develops over a longer timespan, recurring treatment might be more effective. The most effective treatment for traumatic spinal cord injury In short, a fast intralesional application of EVs seems to be the most effective treatment. They cause a more robust improvement of motor recovery compared to IV delivery and it is more potent. Early application reduces inflammation and scarring most. The actual way EVs help after tSCI is not clear yet, but these two effects, and improvement of vasculature integrity, seem to play a major role. References Romanelli, P., Bieler, L., Heimel, P., Škokić, S., Jakubecova, D., Kreutzer, C., Zaunmai, P., Smolčić, T., Benedetti, B., Rohde, E., Gimona, R., Hercher, D., Dobrivojević Radmilović, M. & Couillard-Despres, S. (2022). Enhancing functional recovery through intralesional application of extracellular vesicles in a rat model of traumatic spinal cord injury. Frontiers in Cellular Neuroscience, 15, 795008. --- ## How the ability to manage emotions shapes perception of risk URL: https://noldus.com/blog/emotions-risk-perception Published: 2022-12-21 13:15:00 Description: Can our ability to recognize and control our emotions determine how dangerous we perceive certain hazards to be and whether or not we think we are at risk? Contributors Andrea Pittarello, PhD – Hofstra University, Frank G. Zarb School of Business Enrico Rubaltelli, PhD – University of Padova, Psychology Department Elisa Tedaldi – University of Padova, Psychology Department Acknowledgment – Bhavana Surapaneni - Hofstra University, Frank G. Zarb School of Business How the ability to manage emotions shapes perception of risk Should you buy stocks or bonds? Should you quit your job to pursue a new one? How about purchasing flood insurance? In one way or another, we encounter these dilemmas daily. And although we want to think that we are rational decision makers (Ariely, 2008), it turns out that most of our choices are driven by emotions (Lerner, Valdesolo, & Kassam, 2015). That is, we rush to buy flood insurance because we read a telling story about a couple who lost their property because of water damage. Truth is, the actual odds of this hazard in our area are almost nil. Similarly, we might install an alarm system just because someone broke into the apartment of one of our friends. Do emotions influence risk perception? Although there is enormous evidence that our emotions shape our reactions to different risks (see Lerner et al., Slovic et al., 2007), only recently did we learn that our ability to manage, recognize, and control our emotions matters, too. This concept is called Trait Emotional Intelligence (Petrides , Pita, & Kokkinaki, 2007). In recent studies, researchers found that when feeling negative emotions, individuals who score lower on trait emotional intelligence are more likely to believe that a terrorist attack will occur in their city (which is very unlikely) and also to see outgroup members as dangerous (Rubaltelli & Pittarello, 2018; Rubatelli et al., 2020; Scrimin & Rubaltelli, 2021). However, this research mainly relied on self-reported emotions. What happens when emotions are recorded implicitly and in real-time? Automatically measuring facial expressions Researchers in the behavioral research in business lab at Hofstra University and at the University of Padova have just begun to address this question. They brought participants to the lab and showed them pictures of different hazards. Each picture remained on screen for 5 seconds during which FaceReader recorded facial expressions. After each hazard (there were 17 in total, e.g., car accident, wildfire, theft) participants reported how worried they were and their estimate that they would be exposed to each risk (0-100%). FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Trait emotional intelligence At the end of the survey, the researchers administered the trait emotional intelligence scale. This questionnaire measures different facets of trait emotional intelligence. It describes our perceptions of our emotional world: what our emotional dispositions are and how good we believe we are in terms of perceiving, understanding, managing, and utilizing our own and other people's emotions. What were the results? There was some evidence that participants with higher (vs. lower) trait emotional intelligence reported lower likelihoods of being exposed to the hazards, even controlling for how scared, surprised, and disgusted they were. When looking at different facets of trait emotional intelligence, it turned out that people with higher (vs. lower) self-control reported lower likelihoods despite feeling sadness in response to the hazards. Similarly, people with higher (vs. lower) well-being were overall less worried even if they felt angry. Finally, the researchers grouped the different risks in clusters (e.g., economic risks, medical, controllable). It turned out that for personal medical hazards (e.g., car accident, disease), people with higher (vs. lower) trait emotional intelligence, self-control, and sociability were overall less worried despite feeling angry. Strengthening our emotion management skills In sum, this preliminary (and ongoing) research tells us that not only do our emotions matter when it comes to our reactions to different hazards, but also (and perhaps more importantly) that the way we manage them play a big part. This finding replicates past research. Obviously, more work is needed to draw conclusions given the preliminary nature and richness of the data. Clearly, not all hazards are the same: A promising future step is to classify different risks and explore if different emotions are at play when hazards are say caused by people, or uncontrollable. From an applied perspective, this research also seems to suggest that strengthening our emotion management skills can help us keep cool and under control without the need to suppress the way we feel. References - Ariely, D. (2008). Predictably irrational: The hidden forces that shape our decisions. HarperCollins Publishers, 68-69. - Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015). Emotion and decision making. Annual Review of Psychology, 66, 799-823 - Lerner, Jennifer S., Roxana M. Gonzalez, Deborah A. Small, and Baruch Fischhoff (2003). Effects of fear and anger on perceived risks of terrorism: A national field experiment. Psychological science, 14 (2), 144-150. - Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2007). The affect heuristic. European Journal of Operational Research, 177, 1333-1352. - Petrides, K. V., Pita, R., & Kokkinaki, F. (2007). The location of trait emotional intelligence in personality factor space. British Journal of Psychology, 98, 273-289. - Rubaltelli, E., & Pittarello, A. (2018). Negative emotion and trait emotional intelligence in reaction to terrorist attacks. Personality and Individual Differences, 123, 247-252. - Rubaltelli, E., Priolo, G., Scrimin, S., & Moscardino, U. (2020). Media Exposure to Terrorism and Perception of Immigrants as a Threat: The Role of Emotional Intelligence and Psychophysiological Self‐Regulation. Risk analysis, 40(8), 1666-1676. - Scrimin, S., & Rubaltelli, E. (2021). Dehumanization after terrorism: the role of psychophysiological emotion regulation and trait emotional intelligence. Current Psychology, 40(6), 2707-2714. --- ## Simulation-based training – it’s just like the real thing! URL: https://noldus.com/blog/simulation-based-training Published: 2022-12-13 09:18:00 Description: By conducting training sessions, students in a simulation lab develop and maintain knowledge, skills, and competencies such as interviewing skills, working with certain equipment, and teamwork procedures. A simulation lab is designed to provide a lifelike point-of-care learning experience for undergraduate and graduate students, specialists, and experts. Real-life circumstances are simulated for learners to practice tasks and processes using models such as manikins, or virtual reality. By conducting simulation-based training sessions, students in the lab develop and maintain knowledge, skills, and competencies such as communication skills, working with certain equipment, teamwork procedures, and so on. All this can happen without any risk of, for example, patient harm. Focus on patient safety and quality of care Simulation is a technique for practice and learning that can be applied to many different disciplines and types of trainees. It has been widely applied in fields such as aviation, the military, and healthcare. In a clinical setting, for instance, simulation helps to augment patient safety and improve patient care. Teamwork training conducted in the simulated environment may offer an additive benefit to the traditional didactic instruction, enhance performance, and also help reduce errors. Simulation-based training is just like the real thing. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo What does a simulation-based training look like? At the Child Surgical Intensive Care ward of the Erasmus MC Sophia Children hospital in Rotterdam, the Netherlands, a project was started to improve patient safety. An important condition to achieve this goal was that employees should be aware of the risks and danger of their daily acts. Therefore, the Crew Resource Management (CRM) Training has been implemented, together with scenario training. The two-day basic CRM training at the PICU of the Erasmus MC covered seven topics: information management, communication, stress management, group processes, effective leadership and followers, decision-making, and risk management. Under the guidance of the trainers, the participants evaluate during debriefing what went right or wrong, what insights they received, and what they would do differently next time. More information about the scenario training can be found in the free white paper 'Simulation-based training'. Just click on the download button below. FREE WHITE PAPER Simulation-based training Simulation-based training is an important part of the development and learning process of knowledge and skills. - 5 reasons why - Practical examples - Innovative solutions Get your copy instantly Repeat simulation-based training sessions At the Máxima Medical Center in The Netherlands, multiprofessional teams are involved in simulation-based team training with caregivers in obstetric care. These teams, including ambulance staff, maternity nurses, independent community midwives, obstetric nurses, hospital midwives, residents, and gynecologists are trained in communication and teamwork skills in the simulation lab. Results of the research conducted by Sophie Truijens and her team showed that repeating team training sessions is of the utmost importance. The research team observed that both trainees and trainers benefit from recording the training scenarios on video, since this provides the opportunity to evaluate medical skills and non-medical skills in a more objective manner. Additionally, the video recordings proved very illustrative for self-evaluation. Also read: the guest blog of Sophie Truijens with full details about her study. Education of teamwork skills The study performed by Annemarie Fransen and her team consisted of a large cluster-randomized controlled trial that evaluated the effect of simulation-based obstetric team training. Twelve of the 24 participating hospitals received the intervention: a one-day, multi-professional, simulation-based obstetric team training that was provided in a medical simulation center. In total, 74 multi-professional teams, including 471 trainees, had to manage five simulated obstetric emergencies. The debriefing was provided after each scenario by a medical specialist and communication expert, which mainly focused on the education of teamwork skills. A few months later, teamwork performance was measured using the Clinical Teamwork Scale. The teams from the intervention groups showed better results on the Clinical Teamwork Scale. Besides, they used predefined essential medical skills more often, in comparison to the teams in the control group. Read more details on this study in the guest blog of Annemarie Fransen. References Truijens, S.E.M., Banga, F., Fransen, A., Pop, V., Runnard Heimel, van P. & Oei, G. (2016). The effect of multiprofessional simulation-based obstetric team training on patient-reported quality of care: a pilot study. Simulation in Healthcare 2015, 10, 210-216. Fransen, A.F.; van de Ven, J.; Schuit, E.; van Tetering, A.; Mol, B.W. & Oei, S.G. (2017). Simulation-based team training for multiprofessional obstetric care teams to improve patient outcome: A multicentre, cluster randomised controlled trial. BJOG, 124, 641-650. --- ## How to analyze different characteristics of olfaction in rodents URL: https://noldus.com/blog/mouse-olfactory-testing Published: 2022-12-08 14:00:00 Description: Correct analysis of olfaction is crucial for an accurate interpretation of mouse social behavior. Today's guest article describes how to analyze different characteristics with the olfactory habituation/dishabituation test. Today we are honered with a great contribution to our blog from Betty Hornix. She is about to get her PhD and works at the lab of Martien Kas, at the University of Groningen (The Netherlands). She describes with great detail how to set up and perform a mice olfactory test with EthoVision XT video tracking. Enjoy! Olfaction and behavior Interaction between people and between animals depend on proper olfactory processing. When something is off in this processing this could affect proper social behavior (Hornix et al., 2018). Correct analysis of olfaction is crucial for an accurate interpretation of various mouse behaviors, especially when looking at social behavior. Below we will describe how to perform the olfactory habituation/dishabituation test. We will explain how to DIY your own test cage, which preparations are necessary, how to perform the test, and how to analyze the videos using EthoVision XT. The olfactory habituation/dishabituation test The olfactory habituation/dishabituation test (OHDT) assesses whether an animal is able to detect and distinguish different odors. It consists of successive presentations of different odors. We used a sequence of water, two non-social odors, and two social odors. Each smell is presented to the animal in three consecutive trials for a duration of 2 min (see timetable below). A decrease in olfactory investigation of the odor over these three trials is defined as habituation. When an increase of sniffing is seen when a novel odor is presented, the animal shows an intact behavior called dishabituation. Minimal inter-trial manipulations The method described here, the olfactory habituation/dishabituation test, involves minimal inter-trial manipulations as the inside of the cage is not disturbed (adapted from Yang & Crawley, 2009 and Oummadi et al., 2019). Since the odor stimulus (the cotton tip inside the 500 ul tube) does not touch any part of the cage or cage lid, cross-trial contamination is easily avoided. How to make your own test cage The test can be executed in normal home cage that needs a couple of small adjustments. A separate cage is used for each animal that is tested on one day. This is done because the odors will linger in the cages. We burned a hole in the short side of the cage and we made holes in small tin cans with a small nail. One small tin can is attached with hot glue in the hole burned in each cage (see pictures below). We advise to not use silicone glue, as this smells a lot. You want to keep the presence of distracting smells to a minimum. The odor will be presented to the animal via this tin can. This way the inside of the cage is not disturbed during the test. Preparations necessary before testing The test takes place over two consecutive days. On the first day the animals are acclimatized to their cage and the odor tubes are prepared. Furthermore, the cages are cleaned and filled with a small layer of bedding. We used a very mild cleaning agent to reduce smells lingering in the cage. Acclimatization and testing Acclimatization of the animals to their test cage We used 500 ul tubes to present the odors via the tin can to the animals. 17 tubes per animal are necessary and the tips of the tubes need to be cut off (see pictures below). Two of these tubes are filled with dry cotton swabs. It is important to wear gloves during every step of preparation and execution of the test to prevent odor transfer as much as possible. In the afternoon, each animal is acclimatized to their testing cage for 30 min while a tube with dry cotton swab is inserted in the tin can. Preparations of the olfactory stimuli On the morning of the testing day the odor tubes are prepared. We used water, almond extract, orange extract, juvenile fecal matter, adult fecal matter. Almond and orange extract were selected because they are very distinct, yet neutral odors. We prepared the dilutions in water and the tubes in the order that you test them (distilled water> almond (1:15) > orange (1:5) >social odor 1> social odor 2), change gloves between odors and do not touch the cotton end of the swab (see pictures above). It is very important to not mix the odors! This is a very time-consuming task, so take enough time to prepare everything. Performing the test The test takes in total 49 min, incl. 5 min acclimation at the beginning with a new tube holding a dry cotton swab. The odors are presented 3 times after each other, every time for 2 min with an ITI of 1 min, which comes down to 15 trials (see timetable above). We used Media Recorder to record the videos from above the testing table. The animal can freely explore the testing cage. Great care needs to be taken (by changing gloves constantly) when preparing the odors and between animal changes to avoid transferring and mixing odors. Multiple animals can be tested at the same time in their own testing cage as long as great attention is being paid to exacting the timing of presenting the odors for the best success with automatic analysis with EthoVision XT 16. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial Analyze the videos with EthoVision XT In EthoVision XT, the time spent sniffing the odor was measured when the nose point of the animal was inside the zone we digitally marked around the tin can of 3.5 cm. Extraction and visualization of the data The data was exported in time bins of 1 min and the 2 min duration of each trial was added up. We visualized the results by plotting the time sniffing the odor over the 15 trials. Habituation and dishabituation worked perfectly for the non-social odors and the first social odor in this experiment. This was apparent as the sniffing time decreased with each of the 3 trials for each of these odors. Furthermore, an increase in sniffing time was seen when the odor was changed to a novel one. In addition, the animals were able to distinguish the first social odor from the last non-social odor in a similar fashion. They had more difficulty with distinguishing the two social odors. We recommend to use more distinctive social odors, like different strains or bigger age differences. Effective testing and automation of olfaction In conclusion, the olfactory habituation/dishabituation test is very effective to test olfactory function and to separate different characteristics within olfactory behavior. Furthermore, this method leaves the animals undisturbed during testing which reduces stress and which makes it possible to very easily automate the analysis with EthoVision XT. References - Hornix, B. E., Havekes, R., & Kas, M. J. H. (2018). Multisensory cortical processing and dysfunction across the neuropsychiatric spectrum. Neuroscience & Biobehavioral Reviews. https://doi.org/10.1016/J.NEUBIOREV.2018.02.010 - Oummadi, A., Meyer-Dilhet, G., Béry, A., Aubert, A., Barone, P., Mortaud, S., Guillemin, G. J., Menuet, A., & Laugeray, A. (2019). 3Rs-based optimization of mice behavioral testing: The habituation/ dishabituation olfactory test. https://doi.org/10.1016/j.jneumeth.2019.108550 - Yang, M., & Crawley, J. N. (2009). Simple behavioral assessment of mouse olfaction. Current Protocols in Neuroscience, CHAPTER(SUPPL. 48). https://doi.org/10.1002/0471142301.ns0824s48 --- ## Suture anchors for rotator cuff injuries: a new animal model URL: https://noldus.com/blog/suture-anchors-rotator-cuff-injuries-new-animal-model Published: 2022-12-01 13:00:00 Description: Almost half of the people over the age of 60 have a rotator cuff tear in the shoulder. Research is aimed at improving surgical techniques, but techniques used in animal models differ from those applied on humans. Rotator cuff injuries are quite common and have significant consequences. Almost half of the people over the age of 60 have suffered a rotator cuff tear, causing pain and decreased usability of the shoulder. These limitations also seriously impact quality of life, and if the tendon has torn completely, it needs to be repaired surgically. The tears often heal poorly, and overall further research is warranted to improve surgical techniques. Suture anchors vs transosseous surgery In rats, the most commonly used surgical technique in rotator cuff tear research, the transosseous bone tunnel technique, is not the primary technique used on humans. A group of researchers from the Chinese University of Hong Kong aim to develop a new rotator cuff repair model, based on suture anchors. Suture anchors are used in the actual human surgeries that patients receive nowadays. In the current study, a version of the suture anchors is developed that is suitable for use on rats and can be compared to the transosseous bone tunnel technique. This is especially important since surgeries that are effective on animals are often not as effective on humans, probably due to physiological differences. An animal model on rotator cuff injuries For the study, sixty male adult Sprague-Dawley rats were selected and randomly assigned to either the transosseous or the suture anchor surgery group (n = 30 per group). Creating the rotator cuff injuries All rats received surgical rotator cuff injuries: the supraspinatus (SS) tendon in the right shoulder was found and transected, and the rats were allowed to recover for 24 hours. After four weeks of recovery, the two respective repair surgeries were carried out. The techniques of transosseous surgery and suture anchors For the transosseous bone tunnel technique, the SS tendon was stitched onto the bone using holes drilled all the way through the humeral head at an angle. For the suture anchors technique, custom-made anchors were developed, since all commercially available versions were too big. Through weaving two pieces of suture together, the scientists created a small anchor which was then pushed into a pre-drilled hole, thus attaching it to the bone. The SS tendon was then stitched with the lengths of suture sticking out from the anchor. (For images of both techniques, please take a look at the original article, referred to below.) RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Gait analysis The rats underwent various tests, including gait analysis. During 2-week, 4-week, 6-week and 8-week post-repair, a downhill walking gait analysis was carried out and analyzed using Noldus' CatWalk XT. Walking tests Each rat could walk back and forth freely, starting from the right side of the walkway which was tilted up at 10°. The experiment stopped once the rat had finished two complete walks with a speed variation of less than 30%. At a predetermined 10 x 60 cm area, the detection system automatically recorded the pawprint images, using a digital camera set at 60 cm below the walkway. Pawprint area, swing duration of a forelimb, max intensity and stride length were calculated automatically. Initial recovery of rotator cuff injuries At 4-weeks post-tear, the rats' gait had completely recovered, contrary to humans, whose shoulder functionality kept decreasing after injury. Once the tear had been repaired, the rats' gait deteriorated again for 2 weeks, and after 4 weeks returned to normal. This fast recovery is probably caused by the natural healing capacity of rats combined with the fact that rats have to put weight on their shoulder where humans do not. Biomechanical tests Next to gait analysis, the repaired tendons underwent various pulling strength tests. Every two weeks, shoulder samples were taken from the rats and tested to see how well the connection between bone and tendon held. After the rats had fully healed from either surgery, the researchers found that the new tissue connecting the severed tendon to the bone was of a different structure than before surgery. Most re-tears caused by the pulling strength test took place in this soft scar tissue, indicating a lower strength of said tissue. Healing of suture anchors vs transosseous repair Both techniques caused the torn tendon to be fixed in place properly right after surgery. After 4 weeks, the suture anchors showed better tendon healing and decreased bone healing than transosseous repair, though after total recovery the two techniques showed comparable functional recovery. It is possible that the initial better healing of the suture anchors is caused by compression of the tendon onto the bone. This is compensated by lesser bone damage from the drilled holes in transosseous repair, causing less swelling compared to the suture anchors. An animal model on rotator cuff injuries Although the suture anchors did not promote better healing compared to transosseous surgery, the Hong Kong researchers successfully developed the novel suture anchor surgery for rats. This means that future research in this topic has an increased clinical relevance and is easier and more effective to carry out. References Liu, Y., Fu, S. C., Yao, S. Y., Chen, X. D., & Yung, P. S. H. (2022). Application of suture anchors for a clinically relevant rat model of rotator cuff tear. Journal of Tissue Engineering and Regenerative Medicine. --- ## The Hypothalamus is involved in locomotion? Complex dopamine circuitry uncovered URL: https://noldus.com/blog/hypothalamus-and-locomotion Published: 2022-11-24 14:00:00 Description: By measuring locomotion and investigating dopaminergic neurons, complex dopamine circuitry is uncovered. How are amphetamine and our biological clock involved in this? Behavior serves as an essential proxy for brain function. Where and how this is regulated is not always as simple as finding the appropriate wire going from point A to point B. Complex circuitry, many neurotransmitters and hormones, and multiple brain areas are usually involved. Piece by piece researchers are gaining a full picture of the brains' inner workings. Behavior is essential in neuroscience This blog post touches the surface of such a topic, and partly dissects a recent paper in Nature communications by Korchynska et al [1] on locomotion control from a brain area that is primarily associated with homeostatic body functions; the hypothalamus. The hypothamalus: our smart thermostat The hypothalamus is a brain structure that is often referred to as a smart control center of your body. By controlling and coordinating hormones and/or nervous system signaling it functions to regulate physiological parameters such as sleep, mood, body temperature, hunger/thirst, blood pressure, and other parameters that contribute to homeostasis. The hypothalamus gets chemical messages from nerve cells in your brain as well as nerve cells throughout your body (your peripheral nervous system), which is also responsive to signals from outside your body. Hormones of the hypothalamus: essential messengers These chemical messages are mostly sent through hormones. The hypothalamus itself produces such hormones like corticotropin-releasing hormone (CRH; highly involved in the stress response), growth hormone-releasing hormone (GHRH), somatostatin (inhibits insulin and glucagon secretion), to name a few. Many of these hormones serve a messenger function, simply to activate or stimulate a physiological function or response. A good example of this is GHRH; it is released by the hypothalamus and merely signals the release of growth hormone (GH) from the anterior pituitary which goes directly into your bones and muscles to stimulate growth. What is the role of dopamine? Dopamine is also released from the hypothalamus, which is a neurotransmitter as well as a hormone. In the body, dopamine is involved in a variety of vital activities, including mobility, memory, and pleasure reward and motivation. Dopamine levels are linked to a variety of mental health and neurological disorders as well. Specifically in the hypothalamus, dopamine is best known for its role as a signaling molecule for the inhibition of prolactin release from the anterior pituitary, thus the production of milk after child birth. Mapping all of dopamine's roles and functions remains extraordinarily complex. Summarizing all of it's functions and involvements within normal physiology (and diseases) might require a book on itself. It is suggested however that the heterogeneity of dopamine roles lies in dopaminergic cell groups, which are collections of neurons in the central nervous system that express/produce dopamine and are in this way involved in their own distinct efferent dopaminergic pathway(s). Measuring behavior and looking at dopaminergic cell groups Going back to the topic of measuring behavior; the abovementioned recent publication in Nature communications by Korchynska et al describe such a cell group (A14), or dopamine locus, in the hypothalamus which seemingly is involved in a commonly investigated behavioral parameter: locomotion. Korchynska et al focused on the A14 neuron cluster in mice, in which they found: - Spontaneous activity of A14 dopamine neurons in the periventricular nucleus (PeVN) was increased during dark hours, suggesting that dopamine cells in the PeVN are directly entrained by input from the suprachiasmatic nucleus (SCN; "the biological clock"). - A14 neurons give rise to long projections that leave the hypothalamus and densely innervate the lateral septum (LS), which is in essence a relay center from the hippocampus and is involved in a variety of functions, including emotional, motivational, and spatial behavior. - a PeVN-to-LS projection operates with dopamine as a neurotransmitter acting at enzyme-activated (metabotropic) G-protein coupled receptors. Involvement of day/night rhythms and the use of amphetamine Korchynska et al further hypothesized based on previous research that A14 dopamine neurons could be central to the diurnal (during the day) regulation of locomotion. They found that particularly during the dark phase (which is the active phase in mice), activation of dopamine neurons in the PeVN increased locomotion in mice. This time-of-day dependent activation can however be overridden by a psychostimulant, in this case: amphetamine. Korchynska et al uncovered that amphetamine significantly increased locomotor activity in control mice regardless of time-of-day or rather; day/night cycle. How to measure behavior in a complex study Continuous behavioral assessment of locomotion was achieved in this study by using Noldus' PhenoTyper cages. These "home" cages allow for continuous housing and video monitoring of rodents, and can even integrate complex hardware such as optogenetics and operant walls or in this case: running wheels. Korchynska et al defined the following parameters over a 6-day period in EthoVision XT to achieve the above-mentioned results: distance moved, total activity, walking duration, and wheel running (number of wheel rotations). RESOURCES Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Human relevance Shift workers frequently use amphetamine to sharpen their focus and increase their own activity at night (the rest phase in humans). The explanation given here on how amphetamine can override the neural control of the central pacemaker on locomotion is of significant human relevance. The authors also suggest that the primary adverse effect of methylphenidate (commonly known as Ritalin) treatment for attention deficit hyperactivity disorder (ADHD), increased evening and nighttime activity, may also be connected to the drug's ability to inhibit dopamine and norepinephrine reuptake along the SCN anterior PeVN LS circuit as studied by Korchynska et al. Why we shouldn't underestimate measuring behavior In conclusion the findings of this studies show that this this A14 dopaminergic cell group might serves as a junction between the hypothalamus and further circuitry directly involved in motivated behavior. This builds on the existing known framework of midbrain dopaminergic circuitry (involved in locomotion). Measuring behavior often seems simple and is often underrated. But behavior is the main physiological output of the brain and its associated circuitry. There can be no neuroscience without the behavioral component that is associated with it. And this complex study by Korchynska et al highlights that very nicely. REQUEST INFORMATION Are you interested in our behavioral research solutions, and want to get in contact? - Worldwide: Always near to you - Make your project a success - Trust our 30 years of experience Contact us Reference - 1. Korchynska, Solomiia et al. (2022). A hypothalamic dopamine locus for psychostimulant-induced hyperlocomotion in mice. Nat. Commun. 2022 131, 13 (1), 1–16 --- ## 3 debriefing steps to evaluate a training session URL: https://noldus.com/blog/debriefing-steps-to-evaluate-training-session Published: 2022-11-21 14:20:00 Description: Debriefing digs into what and why things happened and explores implications for the future. You will gain insights in what to repeat and what to change. In one of our webinars, the host kicks off with explaining how we actually learn. For that, he used this philosophic quote: "I hear and I forget; I see and I remember; I do and I understand." The quote talks about how easy it is to understand and learn something when you put the time into "doing" it. If you simply study from a book, you will never fully understand what it's all about. Watch this webinar on demand. Click on Replay Human Behavior Research webinars and on Simulation-based training: Why and how. Debrief, evaluate, and get feedback But what if we add a fourth way of learning? I evaluate and I gain insights. Debriefing digs into why things happened and explores implications for the future. When you debrief your soft-skill training session, role-play scenario, simulation-based training, or any other experience, you will truly understand root causes of your successes and failures. You will gain insights in what to repeat and what to change. There really is value in doing that - and there's an art to it too: reflecting and extracting these insights from what we experience is a skill. Learning how to debrief, evaluate, and get feedback in a positive, constructive way is an asset for individuals, teams, and organizations. Using skillful questioning techniques helps gain insights that make a positive impact. During debriefing, you explore three things: what happened (the What), why it happened (the So What) and what should happen in the future (the Now What). 1. The What: describe the event The goal of the first step is to collect data of what actually happened during the training session, scenario, or experience. Draw out as much information as possible to get the discussion off to a good start. Assuming that more than one person is involved, there are various perspectives. Gather all the different perspectives, for instance on notepads. Do not overlook details, but stay focused on the facts. Be sure to set a trusting tone in the debrief environment so that people do not feel intimidated and can respectfully voice what happened. Example questions for this first step: - What happened? - What took place during the session? - What did you notice? Using video images helps to identify important events that occurred during the training session or scenario and the personal experiences of the participants can be supported. The perfect tool to provide effective video feedback is Viso. Viso can record and play back sessions in an easy to use way. Both after and during the recording of the video, markers and comments can be placed at moments that are of interest and important for the learning process, with the simple press of a button. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo 2. The So What: uncover reactions and feelings In the second step of the debriefing, the focus is on the impact of the experience. In other words, you move on to the interpretation of the events that happened. You replay and evaluate. Example questions in the second step are: - Why do you think this and that happened? - How did you feel about it? How did others feel about it? - What did you learn/relearn? These questions relate the activity back to the pre-defined goals, and add meaning to it. You can "unpack" the more subtle levels of what took place, which often results in "Aha" moments. This is the step where the real learning takes place, because of the feedback participants get. Receiving real and honest feedback can be considered as a main source of learning. It can boost the motivation to improve. Discussing the improvements is the third and last step of debriefing. Also view: 10 reasons why AV tool Viso is beneficial for video feedback [INFOGRAPHIC] 3. The Now What: identify the course of action or new solutions After the participants have interpreted the events, it is time to move forward and discuss future behaviors and goals. The participants need to think ahead and apply what they have learned by making a bridge from what just happened during the session to future experiences. Example questions in the third step are: - What should you start, stop, or continue doing? - What do you need for this? How can you apply this? - What hidden opportunities has this event uncovered? The simplest first step to take now is not to make the same mistakes again. That is the first and easiest gain. Furthermore, you can determine realistic and reachable actions, tasks, and deadlines to apply what you have learned. References - What? So what? Now what? - What Is Debriefing and How Is It Done? - The 5 most powerful debrief questions and why they're important --- ## Understanding behavioral psychology with The Observer XT URL: https://noldus.com/blog/understanding-behavioral-psychology Published: 2022-11-16 11:45:00 Description: What causes you to procrastinate, eat junk food, or form a habit? Questions like this, about the connection between our minds and our behavior, are studied in behavioral psychology. Have you ever wondered why we behave a certain way or what drives your actions? For example, what causes you to procrastinate, eat junk food, or form a habit? If so, you're pondering about behavioral psychology – the study of the connection between our minds and our behavior. Understanding behavioral psychology with The Observer XT That's where we come in – Noldus' The Observer XT software has been designed specifically to help gather and analyze observational data, making it a perfect tool for studying people and their emotional responses to their social and physical environments. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial What is behavioral psychology? Some background on behavioral psychology. Behavioral psychology is also known as behaviorism, which is a psychological school that was established by the American psychologist John B. Watson. In 1913, Watson published his views in an article commonly known as "The Behaviorist Manifest," which argued that it was foolish to try and interpret the inner workings of the mind, and that psychology should focus more on the science of behavior. He was especially interested in studying fear, which culminated in his famous "Little Albert" study. In this study, Watson used a baby ("Little Albert") in order to show that fear can be taught through classical conditioning. For those of you who are wondering what classical conditioning is, it involves learning a new behavior through association. Little Albert learned to be afraid of white rats, rabbits, and other stimuli including masks. Each time he was presented with one of these objects, Watson made a loud noise by hitting a metal pipe with a hammer. As the study progressed, the pairing of each object with the loud noise caused Little Albert to burst into tears. His fear of these things lessened over time, but were still evident. Classical conditioning vs. operant conditioning Classical conditioning is not the only way to help modify behavior – there is another type of conditioning known as operant conditioning. The main difference between the two is that classical conditioning occurs when a stimulus automatically triggers an involuntary response, while operant conditioning occurs when a voluntary response is followed by a positive or negative reinforcement or punishment. Example of classical conditioning An everyday example of classical conditioning can be illustrated by someone who has been in a car accident fearing going back inside a car or having difficulty driving. Those who have experienced trauma may find themselves involuntarily scared or anxious when presented with a similar situation, as they have formed a strong negative association or phobia. Everyday example of operant conditioning On the other hand, an everyday example of operant conditioning can be illustrated by a child who has learned to stop having outbursts after their favorite toy is taken away following each outburst. The outburst is a voluntary behavior, and the negative punishment of taking away the toy has caused the child's behavior pattern to decrease so that the positive stimulus will not be removed. Using The Observer XT to collect behavioral data While we may all experience or even implement classical or operant conditioning in one way or another, we still often have difficulty understanding our own behavior and the behaviors of others. According to a large number of scientists, at least 95% of our behavior is unconscious whereas only 5% is conscious. The Observer XT allows for better behavioral analysis in that it provides accurate and quantifiable results in the form of visualizations and descriptive statistics of coded behavior. In addition, there are now many psychology perspectives besides the behaviorist perspective that help to explain different types of behavior. For example, modern approaches like psychophysiology – or examining the ability of the mind to directly affect physiological responses – have proven useful in providing a more complete picture of how and why behavioral patterns are formed. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Integrating behavioral and physiological data Oftentimes, physiological reactions underlie changes in overt emotional responses. These reactions are especially important in better understanding the communication between subjects (ex. parent and child or patient and doctor). The Observer XT can help to integrate behavioral and physiological data through the use of a data acquisition system, and some examples of commonly used measures in behavioral studies are heart rate, respiration, skin temperature, and electrodermal activity. To learn more about The Observer XT and how it can help you collect, analyze, and present your observational data as well as automatically synchronize different data streams, visit our website or contact one of our sales representatives at any of our worldwide locations. References - https://jamesclear.com/behavioral-psychology - https://www.betterhelp.com/advice/psychologists/john-b-watson-and-behaviorism/ - https://www.simplypsychology.org/classical-conditioning.html - https://www.learning-theories.com/operant-conditioning-skinner.html - https://advergize.com/psy/7-classical-conditioning-examples-daily-life/ - https://psychologenie.com/operant-conditioning-examples --- ## The New Jersey Families Study: unlocking the black box URL: https://noldus.com/blog/in-home-naturalistic-observational-study Published: 2022-11-07 11:44:00 Description: Families are children's first teachers and home is their first school. Often we wonder or guess how such teaching is going. The NJFS, performed by the University of Princeton, offers insights. In the first years of their life, parents, caregivers, or other persons in a custodial role are the most influential when it comes to a child's general development. Providing encouragement, support, and access to activities that enable the child to learn key developmental skills is one of the parent's responsibilities. It helps children get off to a strong, healthy start in life. Families are children's first teachers, and home is their first school. However, often we wonder or guess how such parenting and teaching is going. We do not know exactly what goes on in a family at home and how parent-child interactions go. Kind of a black box idea. FREE WHITE PAPER: Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly An in-home naturalistic observational study To be able to unlock this black box, a research group at the Office of Population Research of Princeton University, Princeton, NJ, USA, set up the New Jersey Families Study (NJFS). A video ethnographic examination of how families support their pre-school children's early learning. Ethnography is a type of qualitative research that involves immersing yourself in a particular community or organization to observe their behavior and interactions up close. In this study, the particular community consisted of twenty-one families with a child aged 2-4 years old. The participating families agreed to have their behaviors and interactions observed in their own home environment for two weeks of their daily life. Cameras and microphones were located in up to four rooms and were activated throughout the day and evening. To enrich the video data, the research team collected survey and interview data during six points of contact with the families. Advantages of this innovative ethnographic study Ethnography is a useful approach for learning first-hand about the behaviors and interactions of people within a certain context. It allows exploring many different aspects. The research team emphasizes that video ethnography reduces the social desirability bias that can sometimes surface in survey responses when either respondents give answers to make themselves appear in a more favorable light or that they believe researchers want to hear. Another advantage of this newer mode of data collection is that it does not require participants to remember what happened or when. Besides, observing families in their daily routines has the potential of capturing spontaneous events and behaviors that researchers might not have thought to ask about in standard surveys. The New Jersey Families Study breaks new ground With the NJFS, the researchers aim to make two contributions: first, to the understanding of early childhood development and education and, second, to the emerging science around big data. 1. Understanding early childhood development The more than 11,000 hours of in-home video recordings shine a bright light on parent-child interactions. Behaviors that are influential in the formation of children's cognitive and social-emotional skills were observed, coded, and analyzed. This included behaviors such as: - the amount of talking and reading parents do with children - children's sleep routines - children's diets and nutrition - children's exposure to electronic screen time - structures and routines at home - the way that stress outside the home affects parenting practices This unique study will lead to a better appreciation of the daily struggles facing many families and thereby help schools become more "children-ready". Complete software for behavioral research With The Observer XT at the core of your lab, you can code such behaviors accurately on a timeline, from multiple videos including audio, and integrate data modalities such as eye tracking or emotion data, and visualize and analyze your results all together. Using The Observer XT, the GOLD STANDARD for coding and analyzing behavior, will higher the probability that the results of your study will be published in a high impact paper. FREE TRIAL: Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial 2. Building a user-friendly, searchable database This study has generated a huge amount of digital data (video, audio, etc.) which can serve as a model for future research projects. Therefore, all 504,000 individual video clips will be housed in a searchable database, attached with a variety of metadata derived from room views, data and time stamps, and household demographic and socioeconomic characteristics. Using a manageable set of filters based on the metadata facilitates easy access to the video clips. NJFS video data are securely stored on Citadel, Princeton's new secure and compliant research data infrastructure environment. Use of this data will be restricted-access, not public-use. Setting up a coding structure The research team conducted two focus group sessions in order to receive input on the development of a coding structure for the project's video data set and other insights about how the data could be best organized to support work of those in the field. They suggested using three categories: - 1.Participants, e.g. target child, mother, father, sibling, non-family member. - 2.Activity and behavior, e.g. media and screen time, mealtime, grooming, movement, playtime and cognitive stimulation, sleeping. - 3.Interaction periods, e.g. joint engagement, serve and return interactions, moments of potential connection and reciprocity. The goal is that the NJFS becomes a community resource that is made available as soon as possible. This will allow researchers to further develop the understanding of the roles of parent-child interactions, family dynamics, and the home environment in helping young children get off to a strong and healthy start in life. FREE WHITE PAPER: How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download References - New Jersey Families Study, Princeton University, Princeton, NJ, USA - Kim. C.H. (2021). A Report on the New Jersey Families Study's Focus Groups from December 2020. New Jersey Families Study, Office of Population Research, Princeton University - What Is Ethnography? | Definition, Guide & Examples --- ## Does well plate size matter? A methodological study in zebrafish URL: https://noldus.com/blog/well-plate-size-zebrafish-behavior Published: 2022-11-03 15:30:00 Description: The DanioVision observation chamber is a versatile research tool to study Zebrafish embryos and larvae by using well plates. Does the size of the wells in these plates affect study outcomes? The DanioVision observation chamber is a versatile research tool to study zebrafish, Danio Rerio, embryos and larvae by using well plates that fit in the device. Well plates can vary from 6 wells all up to 384 wells. The standard well plates used in zebrafish studies have 24, 48 or 96 wells. Does well plate size matter? A methodological study with DanioVision Wolter and Svoboda described in a Neuroscience Methods paper how they used DanioVision to investigate if circadian rhythms, based on locomotion, change depending on which well plate size was used [1]. For obvious reasons: more wells in a plate means less space (to move in). Increasing the number of wells you use for your study increases throughput of your study, but you might be at risk of decreasing the robustness of your outcomes. RESOURCES: Read more about DanioVision Find out how DanioVision is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources What are the advantages using multi well plates? The main advantage of using a multi well plate is the ability to track and analyze many (zebra)fish embryos and larvae simultaneously for behavior and nervous system function(s). For example, the zebrafish visual-motor assay probes the nervous system by using locomotion as a main readout. Zebrafish larvae increase their locomotion when triggered by environmental changes such as a light to dark switch. This specific phenomenom was initially studied in a 96 well plate as described by Emran et al in 2008 [2]. Can a variation in plate sizes cause behavioral differences? Wolter and Svoboda raise the point in their paper that many groups investigate behavior in zebrafish, to look at nervous system development and function, but that there is a large variation in the well plates that are being used: some perform these behavioral assays in 96 well plates, while other perform them in 24 well plates. How does this size difference affect (circadian) behavior during the developmental stages of zebrafish? Although the lab Wolter and Svoboda was already committed to using 24 well plates, they sought to investigate this issue, since they were concerned they unintentionally biased their experiment. Zebrafish larvae exhibit higher amounts of locomotion as their surrounding area increases, would this directly affect circadian rhythmicity/locomotion? Long term experiments are at risk in smaller wells Between 5-23 dpf circadian rhythmicity (by locomotion) was tracked and analyzed in zebrafish in 24, 48 and 96 well plates using EthoVision XT. They found that particularly longer term experiments in 48 and 96 well plates invoke larger amount of stress in the zebrafish larvae due to space constraints. This in turn could impact nervous system function and/or behavior. They also concluded that the typical high throughput method in 96 well plates may increase individual variability of circadian rhythms due to the decrease well diameter (less space to move in). For short term experiments, these constrains found by using 96 well plates, have yet to be confirmed. A 24 well plate is recommended in long term zebrafish embryo and larvae studies Ultimately Wolter and Svoboda give a clear recommendation: long term zebrafish behavioral experiments should not be performed in 48 or 96 well plates due to variability in circadian rhythmicity (measure by locomotion behavior). Using a 24 well plate shifts these studies from high-throughput to medium-throughput, but is a necessary concession to in order to increase standardization. FREE DEMO: Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free Demo References - Wolter, Matthew E.; Svoboda, Kurt R. (2020). Doing the locomotion: Insights and potential pitfalls associated with using locomotor activity as a readout of the circadian rhythm in larval zebrafish. J. Neurosci. Methods, 330, 108465 - Emran, Farida; Rihel, Jason; Dowling, John E. (2008). A Behavioral Assay to Measure Responsiveness of Zebrafish to Changes in Light Intensities. J. Vis. Exp.(20), 923 --- ## New method for early detection of Alzheimer's disease URL: https://noldus.com/blog/ViS4M Published: 2022-10-25 09:30:00 Description: The color x-maze can be used to pick up symptoms of Alzheimer's disease in AD-mice months before traditional cognitive tests. Almost everyone reading this will know someone who has Alzheimer's Disease, or a similar form of dementia. Six millions Americans (1) and 10 million Europeans (2) are suffering from the disease. Many countries have an aging population, so if no progress is made in prevention and treatment, it will only get worse. That means that there has been a huge volume of research done in the last decades in this area, both with human subjects and with animal models of the disease. It is hard to investigate in humans, not only because sometimes invasive techniques are unavoidable, but simply due to the timescale. To understand how the disease works and how to treat it, it is necessary to see what is going on in its early stages. With people, that can be many years before those who have it become aware of its symptoms. However, animals like mice only live a few years, so they can go from adult to elderly within the time of one experiment. In this blog, we explore how a new type of test enables scientists to research the onset of Alzheimer's disease at an early stage. Alzheimer's disease Although there is still no good medicine available to treat it, we now know that a healthy diet and regular exercise are really important in holding off the symptoms. We also understand a lot about its causes, especially that a build-up of protein plaques seem to be important, although the jury still seems to be out on how much that is cause, and how much affect. Some people in their 60s develop mild cognitive impairment (MCI). MCI is characterized by forgetfulness and problems with cognition. Some people with MCI then go on to develop Alzheimer's (or other forms of dementia) when those problems get severe enough so that they interfere with their daily life. They also develop other symptoms like getting lost and other behavioral changes. The eye is considered by some anatomists to be part of the brain and one of the lesser-known effects of Alzheimer's is that it can also affect the eye's retina, also in the earlier MCI stage. Protein plaques can build up, and the nerves can degenerate (3). Alzheimer's and vision Alzheimer's patients can experience significantly impaired color and also contrast sensitivity. This gives a visual impairment which is rather like tritan color-blindness (tritanomaly). This is quite a rare form of color-blindness. People with that condition have less sensitivity in their blue cone cells. The human eye has three types of cone cell to detect color; red, blue, and green. Someone with trital color-blindness might have difficulty distinguishing red from purple, because blue is the difference between red and purple. Cataracts and glaucoma can have a similar effect, but that is due to filtering the blue out of the light. Blue color discrimination impairment has also been reported for other diseases including multiple sclerosis, Parkinson's disease, Huntington's disease, and Gilles de la Tourette syndrome, so its relevance is wider than just Alzheimer's. Color vision in mice Although humans and other primates have red, blue, and green cone cells, many other mammals, including mice, have just two types; blue to near ultra-violet and green. That means that they will see colors a little bit like the 4% of humans with red-green color-blindness, but (like many insects) can see more differences at the blue end of the spectrum and a little beyond (4). Mice have relatively few cones, leaving more space for the more light-sensitive but monochrome (black and white) rod cells, enabling them to see well in low light. Objects seen in moonlight look monochrome to us because we are viewing them with our light-sensitive red cells. The visual-stimuli 4-arm maze The conclusion is that although the color vision of mice is different from people, they can detect subtle differences in color and brightness. The eyes of older mice are less sensitive to contrast. The question is, do mice from a genetic strain which gives them Alzheimer's symptoms ('AD mice') also show the sort of degeneration in color vision that people get in the early stages of Alzheimer's? In order to determine that, Vit and colleagues developed a new type of maze (4, 5). It has 4 arms in an x-shape, which have black walls and semi-transparent white floors. The floors can be lit up with LEDs underneath with red, green, blue, and white light with variable brightness. As the mice cannot see red, this can be regarded as a control arm, which looks dark to the mice. Although mice can see near UV, this was not used due to safety consideration for the human researchers. The maze is called ViS4M (Visual-Stimuli 4-arm Maze). The position and movements of the mice can be tracked and analyzed using EthoVision software. You can see the maze in operation in this video: Interpretation The interpretation of data obtained with the maze relies on the fact that, as a prey species, mice naturally avoid brightly-lit areas. The mice also tend to explore the four arms is a specific sequence, before returning to the arm that they started in. AD mice show a dramatic decrease in activity, speed of movement, and how often they move between the different arms (percentage of alternation). They showed this at 8.5 months age, whereas memory problems could not be detected (with the Barnes maze) until the mice were 13-months old. They prefer the red arm, which looks dark to them. AD mice preferred both the green arm and the blue arm compared to the white arm, which indicates color-specific visual impairments in the AD mice. There were also color-specific effects on the transitions between the different colored arms. The AD mice moved less between the white and blue arms than wild-type mice, again indicating color vision impairment (4, 5). Conclusions The conclusions are that the ViS4M 4-arm color maze is a sensitive tool to assess color discrimination and contrast sensitivity in mice. Color vision guides spontaneous behavior. AD-specific impairments can be picked up with the maze months earlier than traditional cognitive tests. Do you want to use this test? You can obtain a complete solution from Noldus using a maze made by Maze Engineers and tracking and analysis with Noldus' EthoVision software. Maze Engineers and Noldus have an official partnership which enable them to offer an integrated solution combining Maze Engineers' high quality mazes with EthoVision's unparalleled tracking and analysis. Acknowledgments Part of this blog is based on the protocol published in reference 5. We are grateful to J. Vit and colleagues for permission to use their video in this blog. The mouse color wheel illustration is from colormatters.com and the eye/brain anatomy illustration is from the open text Psychology textbook from OpenStaxCollege. The figure showing mouse/human color vision in relation to red light was modified from a figure from kenall.com. References - https://www.alz.org/alzheimers-dementia/facts-figures - https://www.alzheimer-europe.org/dementia/prevalence-dementia-europe - Rizzo, M., Anderson, S. W., Dawson, J. & Nawrot, M. Vision and cognition in Alzheimer's disease. Neuropsychologia 38, 1157–1169. https://doi.org/10.1016/s0028-3932(00)00023-3 (2000). - Vit, J. et al. (2021a). Nature Scientific Reports 11:1255. https://doi.org/10.1038/s41598-021-80988-0. - Vit, J. et al. (2021b). Visual-stimuli Four-arm Maze test to Assess Cognition and Vision in Mice. Bio-protocol 11(22): e4234. DOI: https://10.21769/BioProtoc.4234. (https://bio-protocol.org/e4234). --- ## 5 Animal blogs not about rats, mice or zebrafish URL: https://noldus.com/blog/5-animal-blogs Published: 2022-10-20 13:30:00 Description: The scope of measuring behavior goes beyond rats, mice and (zebra)fish. As behavioral experts we love to also highlight research in animals such as mites, elephants, dolphins and shrimps. Cover image credit: Oregon Zoo The scope of animal behavior goes beyond rats, mice and (zebra)fish. At Noldus we are behavioral experts, which applies to all animals. Behavioral solutions such as EthoVision XT and the Observer XT offer the flexibility to also be used for elephants, dolphins, numerous types of insects and even shrimp (and much more). 5 Animal blogs not about rats, mice or zebrafish | measuring behavior Take a look at a collection of blogs we've assembled for you about these other types of animals! Video tracking insects to study behavior There are many reasons why researchers study insect behavior. Fruit flies like Drosophila melanogaster, which are easily manipulated to produce genetically distinct strains, have a genetic structure that is quite comparable to that of the human genome. This makes them a highly useful model for learning about the influences of genes on behavior in neuroscientific studies. But in another field, insect pest resistance research, EthoVision XT (in combination with EntoLab) has also proven to be a robust research tool. 1: Pest resistance research: Video tracking walking speed in Mites Patrice Jacob Savi [1] demonstrated that tomato genotypes with a high density of glandular trichomes significantly reduce the red tomato spider mite's walking speed and mobility. Additionally, these genotypes have a high level of spider mite resistance [2]. This is very encouraging for plant breeding for resistance to the major tomato pest species: the red tomato spider mite. Read the full blog post here: https://www.noldus.com/blog/mites-trichomes-walking-speed-ethovision 2: Screening plants for resistance to insect pests EntoLab provides a long awaited solution to investigate the feasibility and efficacy of applying natural defense mechanisms to crops. This come forth from an urgent call and a need to reduce the use of harmful pesticides. In recent years, there has been a lot of interest in breeding for host-plant resistance to sucking insects. EntoLab provides reliable phenotyping technologies that can efficiently and accurately screen a wide range of plant lines where conventional plant phenotyping methods mainly focus on costly, labor-intensive, and time-consuming end-point measurements of feeding damage or insect performance (reproduction and mortality). Read more about this in the full post on insect resistance: https://www.noldus.com/blog/insect-resistance Observing behavior in domesticated and wild animals The Observer XT is a powerful piece of software that can be used to study the behavior of wild and domesticated animals. Scoring behaviors with the Observer XT can be done either live or offline, and can be adapted to your methods and your research circumstances. It is designed to make your research more efficient and extensive with data synchronization: allowing you to study correlations between location, physiological responses, and specific behaviors. Check out these two blogs of studies that used the Observer XT to (3) study Elephants in the Oregon Zoo and (4) study dolphins in the Caribbean sea. 3: Do elephants at the Oregon Zoo like their new habitat? Elephants in the Oregon Zoo were closely observed over a four-year period. Blood and feces samples were collected to detect reproductive and adrenal hormones and GPS bracelets were fitted to record walking distances, all serving to perform in-depth behavioral evaluations [3]. Why was this done? The zoo wanted to enhance their animals' welfare; for the elephants this meant a sophisticated new environment was built with more (feeding) choices and natural substrates to improve psychological well-being. By assessing their activity, hormone levels, and behavior prior to, during, and after construction, the researchers found some interesting benefits! Read more in the full blog post here: https://www.noldus.com/blog/behavioral-research-elephants-new-habitat 4: Using The Observer XT to measure aggressive behavior in Dolphins As part of the Wild dolphin project, bottlenose dolphins (Tursiops truncates) and Atlantic spotted dolphins (Stenella frontalis), which are sympatric species, were studied in the northern Bahamas [4]. It is known that these species move and hunt together, yet also engage in hostile confrontations. A behavioral ethogram was developed which was scored using The Observer XT. Behavioral readouts were put in three categories: - Display: Arching, producing bubbles, open mouth, jaw clapping, etc. - Pursuit: Chasing or following another dolphin - Contact: Charging, holding down, biting, tail slapping, etc. If these activities were aimed against a member of the same species or a member of a different species, they were rated as intra- or inter-specific, respectively. The two species of dolphins showed a degree of behavioral plasticity based on forced adaptation of moving into a new (shared) territory. Read about all findings in this blog post: https://www.noldus.com/blog/aggression-in-dolphins 5: Overcoming challenges to video track small shrimp Research on the ecology of tiny water shrimps called Gammarus insensibilis, published by scientists of the University of Salento in southern Italy, pushed the boundaries of video tracking [5]. Gammarus insensibilis is challenging to track: it avoids sunlight and is semi-transparent. Not one, but three high-resolution cameras were positioned above a complex maze with multiple compartments/areas. The video feeds were analyzed as one arena in EthoVision XT and compiled with a complex, but very clever analysis: As the shrimps traveled from one area to the next, or made a "transition", EthoVision XT captured the event. Each channel between the chambers (stocked with food) was separated into three pieces. In this method, the frequency and speed at which an animal exited one chamber and entered another could be measured. With this information these transitions could be linked to a specific animal. Read more about this innovative technique in the full blog post: https://www.noldus.com/blog/gammarus Experts in measuring behavior Noldus has a strong academic backbone. We have, and distribute, a lot of information apart from our behavioral solutions. We hope you enjoyed reading this blog and if you're thinking about doing research in rodents but don't know where to start? Make sure to check out our free e-book on the basics of behavioral neursocience. This is one of many downloadables to help you advance your research. Until next time! FREE E-BOOK: Basic behavioral neuroscience in rodents This e-book serves as a stepping stone for your behavioral research, providing background information and references. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Download References - Krips, O., Kleijn, P., Willems, P. et al. Leaf hairs influence searching efficiency and predation rate of the predatory mite Phytoseiulus persimilis (Acari: Phytoseiidae). Exp Appl Acarol23, 119–131 (1999). https://doi.org/10.1023/A:1006098410165 - Savi, P.J., de Moraes, G.J., Carvalho, R.F. et al. Bottom-up effects of breeding tomato genotypes on behavioural responses and performance of Tetranychus evansi population. J Pest Sci95, 1287–1301 (2022). https://doi.org/10.1007/s10340-021-01437-5 - Glaeser, S.S.; Shepherdson, D.; Lewis, K.; Prado, N.; Brown, J.L.; Lee, B.; Wielebnowski, N. (2021) Supporting zoo Asian elephant (Elephas maximus) welfare and herd dynamics with a more complex and expanded habitat. Animals 11, 2566 - Volker, C. L.; Herzing, D. L. (2021). Aggressive Behaviors of Adult Male Atlantic Spotted Dolphins: Making Signals Count during Intraspecific and Interspecific Conflicts. Anim. Behav. Cogn., 8 (1), 35–51 - Shokri M, Cozzoli F, Ciotti M, et al. A new approach to assessing the space use behavior of macroinvertebrates by automated video tracking. Ecol Evol. 2020;00:1–11. https://doi.org/10.1002/ece3.71292. --- ## Home cage behavior and epilepsy in the Stargazer mutant mouse URL: https://noldus.com/blog/home-cage-tests-epilepsy-stargaze-mice Published: 2022-10-13 17:00:00 Description: Using long-term home cage behavioral research, scientists successfully created a behavioral characterization of Stargazer mutant mouse, a model often used in epilepsy research. Epilepsy is not just seizures. Many childhood-onset genetic epilepsies also cause motor disabilities and neurobehavioral impairments. To study such complex neurological profiles, standard short-term tests might not suffice. This is where long-term home cage analysis can help, a method that is relatively new and uncommon in epilepsy research. Scientists from the Baylor College of Medicine (Houston, Texas) used this to study the Stargazer mouse model for epilepsy. Stargazer mice in epilepsy research Stargazer mutant mice have a genetic disruption of the Cacng2 gene, making them suitable for research to precision genetic treatments. This disruption causes problems with walking and balance and absence-like spike-wave seizures. A battery of tests vs home cage testing To monitor mouse behavior and responses to both specific objects and environment changes over time, the researchers decided on prolonged video analysis and instrumented home cage monitoring. Behavior is followed more or less continually instead of through serial tests such as the open field test, elevated plus maze, etc. These classic short tests are more like snapshots in comparison. A growing group of scientists believes that continuous analysis of spontaneous, naturalistic, and self-motivated behavior in an experimenter-free home cage provides more reliable results. Behavioral characterization Schirmer and her colleagues wanted to study the severity and extent of behavioral impact in Stargazer mutant mice, and they aim to provide a behavioral characterization. Behavioral phenotyping The researchers carried out various kinds of home-cage tests during this study. Additionally, six of the mutant mice received an EEG implant in order to measure spike seizures during the tests. Habituation to the home cage During the first experiment, mice had two hours to habituate to their new surroundings, a PhenoTyper home cage. The videos resulting from the integrated camera were analyzed using EthoVision XT. With this program, mouse position in the cage, time spent in each location, movement, and velocity were video tracked. Immobility for 40 seconds or more was counted as "sleep". FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Monitoring drinking and eating behavior During the experiment, the number of licks on the two water bottles (the second containing sucrose water) and the number of feeding zone entries were recorded automatically by the EthoVision XT video tracking software. Hyperactivity behavior Generally, mutant mice behaved hyperactively in their enriched novel cage, repeatedly circling around and avoiding novel objects. The hyperactivity was somewhat unexpected, since gait ataxia and spike-wave seizures are likely to actually limit mouse movement. Baseline recordings of home cage behavior After habituation, two baseline recordings were made, each being 23 hours long and starting at 14.00 on two consecutive days. During the nighttime, mutant mice were again more active than wild type mice. Furthermore, they slept more often but less long, and spent less time in their shelter. Causes of this are not yet clear. Licking ataxia and anhedonia? In general, mutant mice licked at their water bottles less often, but licking bouts lasted longer. This might indicate licking ataxia or a perceived increased thirst. They also showed a decreased preference for the sucrose water, possibly indicating anhedonia. Light and sound startle tests Next, researchers started with a light spot test, where the light in the cage was turned on for one hour during nighttime. Wild type mice responded startled and showed a sudden increase in activity, whereas the mutant mice did now show such a strong response. The experiment was repeated, but with a 60 second pure tone instead. Again, mutant mice had a decreased startle and sheltering response in comparison to wild type mice, which might indicate either decreased vigilance or indifference, potentially caused by ongoing or cumulative epileptic episodes. Additional testing After the light and sound tests, the mice underwent several more experiments in the PhenoTyper home cages, which were again filmed and analyzed using EthoVision XT. Running wheel access Mice got 23-hour long access to a running wheel. Hardly any mutant mice managed to use it, while the wild type mice used it frequently, spending less time on feeding and sheltering. The mutant mice spent their time almost solely on the latter two activities and not on running, possibly due to anhedonia and balance problems. Shelter removal The shelter was removed for 2 hours. Mutant mice tried to hide at the shelter's former location while wild-type mice huddled in a corner. Cage swap A cage swap of 2 hours was done to test the response to novel cage stress. There was no clear difference between mutant mice and wild type mice. RESOURCES: Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Epilepsy research and home cage assessment Using the relatively new home cage research method, the researchers created a behavioral characterization of the Stargazer mutant mouse. They found significant differences between mutant mice and wild type mice, which classic behavior tests could not always have discovered, such as differences in sleep behavior and response to light and sound. This method could well be applied in broader studies of seizures, motor abnormalities and neurobehavioral impairment, and provide reliable results based on a larger dataset compared to the classic maze experiments. Reference Schirmer, C., Abboud, M. A., Lee, S. C., Bass, J. S., Mazumder, A. G., Kamen, J. L., & Krishnan, V. (2022). Home-cage behavior in the Stargazer mutant mouse. Scientific reports, 12(1), 1-8. --- ## Examples of Human Behavior Research URL: https://noldus.com/blog/examples-human-behavior-research Published: 2022-10-10 12:00:00 Description: We humans are an intriguing species and it's no wonder researchers have always been fascinated by human behavior. Here are some examples of human behavior research over the years. We humans are an intriguing species and it's no wonder researchers have always been fascinated by understanding human behavior. We recently wrote about how to study human behavior, and different ways to measure human behavior. Examples of Human Behavior Research On our Behavioral Research Blog, there are plenty of examples of human behaviors and research on behavior. In this blog post we are highlighting some examples of human behavior research and behavior studies. Table of contents - What is human behavior? - Cognitive neuroscience - Autism research in infants - Adolescent research - On-site observational research - Doctor-patient interaction - Healthcare research examples - Emotion analysis - Sensory science and eating behavior - Consumers' food choices and emotions - User experience research What is human behavior? In science, human behavior commonly refers to the way humans act and interact: the actions, thoughts, and emotions of individuals and groups. It encompasses a wide range of activities, from physical movements and interactions with the environment, to complex mental processes such as decision-making and problem-solving. It is based on and influenced by several genetic and environmental factors, such as genetic make-up, culture, and individual attitudes and values. Human behavior research and human behavior studies look into several research questions, like: Why do we act the way we do? How is our behavior influenced, or measured? The study of human behavior is a broad and interdisciplinary field that draws on theories and methods from psychology, sociology, anthropology, economics, and other related disciplines. The goal of this field is to understand why people behave in the ways that they do and to use this understanding to improve people's lives and solve real-world problems. The ultimate goal is to increase our understanding of the human experience and to use this knowledge to enhance individual and collective well-being. NOLDUSHUB Simplify your multimodal research Discover how NoldusHub benefits your behavior research, and why it is the best multimodal platform for you to use: - Integrated data collection - Synchronization from the start - Immediate feedback on data quality Learn more Cognitive neuroscience Cognitive neuroscience is the overlapping science of the 'dry and the wet' part of the brain: where dry represents the cognitive part (mind, emotions, and senses), and where wet represents the brain. This combination of scientific disciplines tries to explain the connection between neural activities in the brain and mental processes, in order to find answers to the questions of how neural circuits in the brain affect cognition. This blog series addresses the interplay between the brain, behavior, and emotions, in the field of cognitive neuroscience: - Cognitive neuroscience: the basics - Cognitive neuroscience: Emotions - Cognitive neuroscience: Behavior Autism research: Observing infants to detect autism Making the same movement multiple times, or making repetitive movements, is an important step in the development of a newborn child and them learning how to use their limbs. Repeating these movements is typical for motor development; but an increased frequency of repetitive movements can be an early indicator for neurodevelopmental disorders. Purpura et al. conducted a retrospective analysis of video clips taken from home videos recorded by parents, to verify if a higher frequency of repetitive movements could differentiate infants with ASD from infants with Developmental Delay (DD) and Typical Development (TD), analyzing the age range between six and 12 months. Read more about their study here. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Adolescent research How are adolescents' emotions socialized by mothers and close friends? What can parents do to prevent escalating conflicts? What is the role of early childhood stress and inhibitory control adolescent substance use? These and more studies are excellent examples of adolescent research: - Direct observations help develop effective interventions in adolescence - Understanding adolescent emotions - Studying conflict interactions between mothers and adolescents - The role of inhibitory control on substance use in adolescence On-site observational studies In some cases observations for your study are best performed on-site. For example, you might want to observe people in a natural setting: at home, in a shop, in the classroom, or in the office. Another case where on-site research would be beneficial is when your participants are experiencing health issues, preventing them from travelling to your lab. Conducting your research on location enables you to study people that are otherwise difficult to reach. In this blog post, we highlighted two cases of on-site observational studies with older age groups, conducted at home or at a healthcare facility. Doctor-patient interactions and the use of humor Science has proven that laughter is healthy. However, how often is humor actually used during doctor-patient interactions? Researcher Phillips and her team set out to study the role of humor in medical encounters. They focused on aspects such as its frequency, who introduces it, and the topics it covers. To achieve this, they analyzed audio and video recordings of clinical interactions. Their goal was to describe the frequency and other characteristics of humor during outpatient primary and specialty care visits. More healthcare research examples Healthcare research - sometimes also called "medical research" or "clinical research" - refers to research that is done to learn more about healthcare outcomes. There are plenty of healthcare research examples on our Behavioral Research Blog: - Evaluating ergonomics in healthcare – paramedics - Evaluating the effectiveness of simulation in healthcare - Improving patient safety - How to assess medical team effectiveness - Optimizing safety and efficiency in an OR - What is simulation training? FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly Emotion analysis: The emotions of people who think they're nice What does 'nice' actually mean in relation to psychological variables? And does it positively correlate with self-reported levels of health, happiness, and wellbeing? Researchers of i2 media research from the Goldsmiths University of London, UK, developed a tailored questionnaire to explore this and got some interesting results. Read this: Must-see TED Talks on emotions MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try now Sensory science and eating behavior Sensory science focusses on the effects of sensory (like taste, smell) and metabolic signals (like nutritional properties, hormones) on the physiological and neurobiological responses underlying eating behavior. Professor Kees de Graaf (Wageningen University & Research, The Netherlands) has been involved in sensory science and resarch into eating behavior for years. Things like measuring bite size, chewing behavior and frequency are vital in order to understand eating behavior. He hopes that in 5-10 years, we will be able to measure food intake in an accurate way without interfering with subjects. Watch the movie below to learn more about his research. Consumers' food choices and emotions Is there a relationship between food choice and a person's mood? Bartkiene et al. examined the factors that influence our food choice, using facial expression analysis. User Experience Research User experience (UX) is the overall experience of a person using a product (a website, app, game, e.g.) or service, and his or her emotions and attitudes while using it. UX research dives into these user experiences, often carried out in a lab. A UX Lab is used for usability testing and user experience research. Users are observed in a specific environment while interacting with a product or system. Most UX research is conducted in state-of-the-art UX labs. Understanding the digital world at the Social Media Lab - In this unique lab, technology is applied to understanding user experience, behavior on social media, and much more. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources --- ## Tracking tiny transparent fish with EthoVision XT URL: https://noldus.com/blog/tracking-tiny-transparent-fish-with-ethovision Published: 2022-10-06 13:30:00 Description: Danionella cerebrum, a recently discovered cyprinid fish, has the smallest known vertebrate brain. What are the behavioral differences or similarities to their zebrafish relatives? Cover image credit: Dr. Ralf Britz, Senckenberg Society for Nature Research What can we learn from the smallest known vertebrate brain? Isn't bigger better? Sometimes it is easier to see when structures are larger. However, in the case of the recently discovered Danionella cerebrum, a new window (of opportunity) is opened through which we can take a live look into a working and developing brain. Read further on how the latest technology is applied in this rapidly growing niche of behavioral neuroscience. Tracking tiny transparent fish with the smallest known vertebrate brain Danionella is a genus of small freshwater cyprinid fish. Recently, a new species within this genus was discovered in a mountainous range in Myanmar: Danionella cerebrum. This newly discovered fish got its name (cerebrum: Latin for 'brain') by having the smallest currently known adult vertebrate brain. This new species of Danionella was previously misidentified as Danionella translucida, since the two species share great external similarities, making it challenging to identify the taxonomic differences. However, a thorough comparative morphological and molecular taxonomic analysis of Danionella translucida and Danionella cerebrum revealed several differences, e.g. in skeletal characters, and clearly showed that these were two different species, which, according to molecular analysis, separated from each other about 13 million years ago [1]. Image credit: Dr. Ralf Britz, Senckenberg Society for Nature Research Taking a look into the brain of a fish The different species within the genus of Danionella are currently beginning to emerge as important neurophysiological model organisms for (behavioral) neuroscience. The brain functions of these fish can be studied at a cellular level due to their miniature size, simple anatomy, highly specialized communication system and optical translucency. Evolutionary, Danionella cerebrum, is also closely related to the zebrafish, Danio rerio, a well-established model within behavioral neuroscience, which, like Danionella cerebrum, also displays a rich behavioral repertoire. A recent study by Nina Lindemann et al [2] aimed to compare larval locomotor activity between Danionella cerebrum and zebrafish in a light-dark test, measuring the startle response and other behaviors. Video tracking in fish: EthoVision XT meets Danionella Lindemann et al used a custom-built Noldus observation chamber, which is powered and controlled by EthoVision XT, to determine the behavioral differences between Danionella cerebrum and zebrafish larvae. FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Get your Free trial Thigmotaxis Thigmotaxis in the light-dark test was assessed by defining an outer and inner zone (with an equal surface area) within each well of a 12-well plate, wherein during 80 minutes, the light was switched on – and off – two times each. Switching and timing between the light-dark states was controlled using Noldus' USB-IO box, which was integrated with the researchers' custom-built setup and EthoVision XT. After measuring an average larval body length of 4.2 mm, the authors set a movement threshold between 0.42 and 0.84 mm/s (averaging across 3 frames: 100 ms) to differentiate between moving and non-moving larvae. This means that when larvae move less than 1/10 of their body length per second they are considered non-moving, while when they move more than 1/5 of their body length per second they are scored as moving. Is Locomotor activity different in zebrafish? At first glance, larval locomotor activity of 4-6 dpf Danionella cerebrum and Danio rerio seems largely similar. Decreases in resting time and increases in velocity in the dark phases (compared to the light phases), for example, were similar between the two species. Also, at 4 dpf, the startle response to illumination changes was different and less pronounced in both species compared to 5 and 6 dpf larvae. Furthermore, at 4 dpf Danionella cerebrum but not zebrafish occasionally showed 'Rosetta-like' locomotor patterns. Thigmotaxis in the light and in the dark Danionella cerebrum showed an increased thigmotaxis compared to zebrafish during the light, and a strong startle response during a dark-to-light transition. It has also been found that Danionella cerebrum prefers to occupy the lower zone of a water column [3]. All this points towards a preference of this species to be in a dark(er) environment. Anxiety-like behavior and the environment Thigmotaxis is associated with anxiety-like behavior. Lindemann et al do not suggest that Danionella cerebrum presents increased levels of anxiety, although they exhibit increased thigmotaxis in the light relative to zebrafish (Danio rerio), instead the authors rather favor an environmental-based hypothesis as a possible explanation. This seems plausible based on the different natural habitats of Danionella cerebrum and Danio rerio, which may underlie the different startle responses between these two species. Zebrafish larvae respond strongly to a light – dark switch, and weakly to a dark – light switch. While Danionella cerebrum do the opposite: respond strongly to a dark – light switch and weakly to a light – dark switch. Zebrafish prefer to live closer to the surface Danionella cerebrum and Danio rerio live at different depths of water bodies. Danionella cerebrum have been reported to live at a depth below 30 cm of the surface, while zebrafish – Danio rerio typically spawn in shallow and clear water near the surface [1, 3]. Indeed ̴80% of Danionella cerebrum was found to occupy the lower zone of a tank (0-12 cm) in a laboratory setting, while zebrafish mainly ( ̴80%) occupy the upper zone of a tank (24-36 cm) [4]. This would explain the typical startle response of zebrafish larvae, which is weaker in dark – light transitions, as they are presumably more accustomed to a lighter environment. In vivo brain imaging in fish Both Danionella cerebrum and Danio rerio are uniquely suited for whole-brain (in vivo) brain imaging during their larval stage. The phenotypic behavioral differences (in the light – dark and dark – light responses) discovered in the study by Lindemann et al present an opportunity to investigate the neurophysiological mechanisms and possibly the evolution of neural circuits between these two related species. They are in fact different in their response, while the environmental stimuli are similar. Behavioral neuroscience models are advancing The amount of information we are able to gather from such small animal models is ever increasing with advancing technology, which is ultimately pushing the boundaries of behavioral neuroscience. Fish in general are gaining popularity in this field and others since it is proving it's usefullness as an alternative to classic animal testing for various diseases such as cancer, cadiovascular disease, diabetes and other chronic or neurological disorders. The 3 R's of reduction, refinement and replacement of laboratory use of animals comes into play in this perspective which further incentivizes technological advances and alternatives. FREE DEMO: Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free demo References - Britz, Ralf; Conway, Kevin W.; Rüber, Lukas (2021). The emerging vertebrate model species for neurophysiological studies is Danionella cerebrum, new species (Teleostei: Cyprinidae). Sci. Reports 2021 111, 11 (1), 1–11. DOI: 10.1038/s41598-021-97600-0 - Lindemann, Nina; Kalix, Leon; Possiel, Jasmin; Stasch, Richard; Kusian, Tamia; Köster, Reinhard Wolfgang; von Trotha, Jakob William (2022). A comparative analysis of Danionella cerebrum and zebrafish (Danio rerio) larval locomotor activity in a light-dark test. Front. Behav. Neurosci., 16, 302. DOI: 10.3389/fnbeh.2022.885775 - Parichy, D.M. (2015) Advancing biology through a deeper understanding of zebrafish ecology and evolution. eLife, 4. DOI: 10.7554/eLife.05635 - Rajan, G.; Lafaye, J.; Faini, G.; Carbo-Tano, M.; Duroure, K.; Tanese, D.; Panier, T.; Candelier, R.; Henninger, J.; Britz, R.; Judkewitz, B.; Gebhardt, C.; Emiliani, V.; Debregeas, G.; Wyart, C.; Del Bene, F. (2022). Evolutionary divergence of locomotion in two related vertebrate species. Cell Rep.38:110585. DOI: 10.1016/j.celrep.2022.110585 --- ## The importance of measuring infant behavior for early diagnosis of autism URL: https://noldus.com/blog/measuring-infant-behavior-diagnosis-of-autism Published: 2022-10-04 12:00:00 Description: Most efforts to detect autism before the age of two rely on parental reports rather than infant behavior. Most efforts to detect autism before the age of two rely on parental reports rather than infant behavior. However, directly measuring infant behavior provides vital information that may enable diagnosis of autism in infants as young as 12 months. Understanding autism The last 50 years have seen a radical shift in the understanding and attitudes towards autism or autism spectrum disorder (ASD). What was once a narrowly-defined and rare disorder of childhood onset is now a well-publicized, broadly advocated and intensively researched lifelong condition. Autism is now understood to be both extremely heterogeneous – that is, its characteristics and severity can vary greatly from person to person – and not uncommon. The core features of autism are problems with verbal and nonverbal social communication, as well as restricted or repetitive sensory-motor behaviors [1]. Most of the times autism manifests in infant behavior and is believed to be strongly associated with a number of genetic components as well as environmental factors (though the causes remain relatively poorly understood). Autism is generally considered to be a lifelong condition – though this perception is starting to change as the efficacy of early interventions becomes more established [2]. The outlook for autistic people is dramatically better than it once was. More people with autism are able to speak, read, drive, and live in the community rather than in institutions, and many people with autism will be largely symptom-free by adulthood. Autism can include cognitive strengths and even talents, such as memory for and attention to detail. Nonetheless, there are individuals with autism that cannot work full time or live independently, often requiring support of some kind. FREE WHITE PAPER Autism Research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Download Detection and diagnosis of autism As there are no reliable biomarkers for autism, diagnosis instead depends on the assessment of infant behavior and development. Conventionally, diagnosis of a person on the autism spectrum by an experienced professional in children aged two years or older can be considered reliable [3,4]. Though autism is occasionally detected earlier; many children do not receive a final diagnosis until they are much older. As with many conditions, early diagnosis of autism is generally considered to be a good thing as it enables timely (and thus more effective) intervention [5,6]. Several studies suggest that low-intensity coaching of parents on how to interact with young autistic children can result in immediate benefits in terms of infant behavior and communication skills [7]. Other research suggests that interventions based on applied behavior analysis (ABA) – the most common therapy for people with an autism diagnosis – benefit from an early start [8]. As a result, the exploration of the effects of autism on infant behavior in children under the age of two is an active area of research. Investigating autism in young infants While infant behavior is the primary concern of autism research in infants, most efforts to investigate emotional difficulties in autism in infants younger than two rarely utilize direct observation of infant behavior: instead, they tend to rely on parental reports [9]. However, new research shows that directly recording and analyzing infant behavior can unlock a wealth of information that parental reports cannot provide. For example, a study by Gangi et al. demonstrated that detecting autism in children as young as 12 months of age is possible by observing infant behavior [10]. In the study, researchers used behavioral observation software to monitor a specific parameter of infant behavior: infant gaze to the face of an adult. Using cameras to record both adult and infant behavior, the researchers were able to easily compare gaze-to-face infant behavior in two different social contexts: during semi-structured play with a parent and during structured testing with an unfamiliar examiner. The researchers found that infants who did not go on to get diagnosed with autism would gaze more at their parent's face during play than at the examiner's face during testing – whereas the infants who were later diagnosed with autism through use of ADOS-2 did not differ by context. These results could suggest that infants developing autism may be less sensitive to social context or interactive partners. Certainly, the study supports the validity of directly assessing infant behavior in structured laboratory settings as a means of investigating autism. Using behavioral coding software Another study conducted by Sacrey et al. also used automated behavioral coding software to monitor infant behavior in relation to autism. In this study, researchers compared infant behavior at 12 and 18 months in two groups: infants with an "increased likelihood" of developing autism (i.e., an older autistic sibling) and infants with a "lower likelihood" of developing autism (i.e., no family history of autism) in some emotion evoking tasks. Using behavioral coding software enabled the researchers to assess infant behavior automatically. Affect was coded in five-second intervals based on both facial and vocal cues, while gaze was coded continuously – providing a simple means of characterizing infant behavior throughout the tasks. The researchers found that these infant behaviors, coded as affect and gaze scores, were predictors of autism symptoms at 24 months. Automatically measuring infant behavior Behavioral responses provide important information that complements parental reports of emotional regulation, providing a more detailed assessment of infant behavior. At Noldus, we develop systems that make sophisticated behavior research simple. The Observer XT is our most complete software for human behavioral research, enabling researchers to easily code behaviors on a timeline and carry out thorough analyses. We also provide a suite of other software solutions for behavior tracking: from Viso, our audio and video recording suite, to Baby FaceReader, a version of our standard FaceReader emotion classification software developed specifically for infant behavior analysis. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download All our software tools are easily integrated, enabling researchers to integrate video, audio and eye tracking data into one powerful software package for analysis. In addition to our standalone tools, Noldus develops custom-built infant behavior labs. We integrate computers, cameras, eye trackers and physiological measurement systems to meet the specific needs of your infant behavior research – yielding comprehensive and accurate data, ready for publication. We know that unobtrusive observation is often critical in behavioral research. From portable labs deployed in a naturalistic environment to observation labs replicating natural home conditions, we can provide a range of discrete behavior tracking solutions that enable infant behavior to be studied with minimal stress or influence on the subjects. Want to find out more about our behavior tracking systems or customized turn-key labs? Get in touch with Noldus today. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References and further reading - Lord, C.; Elsabbagh, M.; Baird, G.; Veenstra-Vanderweele, J. (2018) Autism spectrum disorder. Lancet 392, 508–520. - Orinstein, A. et al. (2014). Intervention for Optimal Outcome in Children and Adolescents with a History of Autism. Journal of developmental and behavioral pediatrics : JDBP, 35, 247–56. - CDC. Basics About Autism Spectrum Disorder (ASD) | NCBDDD | CDC. Centers for Disease Control and Prevention https://www.cdc.gov/ncbddd/autism/facts.html (2022). - Lord, C. et al. (2006). Autism From 2 to 9 Years of Age. Arch Gen Psychiatry, 63, 694. - Dillenburger, K. (2022) Why early diagnosis of autism in children is a good thing. The Conversation http://theconversation.com/why-early-diagnosis-of-autism-in-children-is-a-good-thing-33290. - Children, Y. & Corsello, C. M. Early Intervention in Autism. (2005). - Weitlauf, A. S. et al. (2014) Therapies for Children With Autism Spectrum Disorder: Behavioral Interventions Update. - Peters-Scheffer, N.; Didden, R.; Korzilius, H.; Sturmey, P. (2011) A meta-analytic study on the effectiveness of comprehensive ABA-based early intervention programs for children with autism spectrum disorders. Database of Abstracts of Reviews of Effects (DARE): Quality-assessed Reviews [Internet] (Centre for Reviews and Dissemination (UK), 2011). - Sacrey, L.-A. R. et al. (2021) Affect and gaze responses during an Emotion-Evoking Task in infants at an increased likelihood for autism spectrum disorder. Molecular Autism 12, 63. - Gangi, D. N. et al. (2018). Gaze to faces across interactive contexts in infants at heightened risk for autism. Autism, 22, 763–768. - Reducing distress in mothers of children with autism and other disabilities: a randomized trial - PubMed. https://pubmed.ncbi.nlm.nih.gov/25049350/. --- ## What you need to know about the CatWalk gait analysis method URL: https://noldus.com/blog/history-and-technology-of-catwalk-xt Published: 2022-09-29 12:00:00 Description: Let's take a little step back and talk about the history and technology of the CatWalk system. What was the reason of creating this gait analysis system for rats and mice? How does it work? We have talked a lot about gait analysis lately, particularly about methods in animal research and the pros and cons of different systems. Today, I would like take a little step back and tell you about the history and technology of the CatWalk system. CatWalk and models Ok, so let's start with the name. When hearing the word catwalk, you might think of fashion models strutting down a runway. Actually, that's not that far off, as it is a runway made for rodents. Only we're not talking fashion here, but scientific research. In a nutshell: CatWalk XT is a system for automated gait analysis in rodents. It was originally created for research on rat models for spinal cord injury and is mostly used for rats and mice, but has expanded to other species, such as marmosets as well. Turn-key gait analysis The basic idea is that the animal freely traverses a walkway from one side to the other. This is a glass plate with green LEDs running through it. A technology called Illuminated Footprints captures the footprints made on the glass plate from a high-speed camera mounted underneath. (More about that later.) This corridor is placed on a frame that also holds everything together, including a control unit to control the power. For convenience, this whole system is placed on lockable swivel casters. Accompanying software analyzes the footprints recorded by the camera. A bunch of (read: more than 50) spatial and temporal parameters, not to mention some really cool 2D and 3D visuals, help you answer your research question. CatWalk: the original The original CatWalk was designed by Dr. Frank Hamers in 2001, because he and his colleagues wanted to find a better way to measure peripheral and central nervous system damage in spinal cord injury models. Like the current method, it was based on an animal traversing a glass walkway. Footprints were captured using white LEDs sent through the glass plate and an analog camera underneath. Hamers and his colleagues collected data such as paw print area, swing duration, stride length, and base of support and compared these in two different models of spinal cord injury. Using this new method, they were able to capture gait impairments introduced by two different rat models of spinal cord injury. No other typical method (like BBB scoring) came close, and so they quickly figured this way of gait assessment would be useful for other disease models as well. Green light, red light This is where we (Noldus) stepped in. By 2006 the system was ready for a commercial release, in 2009 it got a major upgrade. It now uses green light for the Illuminated Footprints technology. Green LED light is emitted in the glass walkway and footprints are illuminated where the paw touches the glass. We also added a ceiling with red LED light to provide backlight for the video, creating a nice outline of the animal without disturbing it. And of course, the camera is now a high speed digital camera. A system would not be a system without analyses, so the dedicated CatWalk XT software got some upgrades over the years, too. It automatically labels and classifies the prints, and has a lot of options for analysis and visualization. I won't go into too much details here, because you can read all about on our website. Extra motivation with a goal box In 2011 we added the option of a goal box to provide some extra motivation for the animal to traverse the runway in a straight line. Because that's the thing about free-run based systems: while it captures a more natural gait (instead of forced locomotion), the animal might linger or turn around on you. Please enjoy this video I made when I just started to discover the joys of video editing. It's pretty old, but I think it gets the point across: At Noldus, we want research to be efficient, in addition, we encourage appetitive reinforcement, so one of the ways to motivate the animal is by providing a goal. The reward could be the home cage, food, or (as Kristina Ängeby Möller shows in this white paper linked below) a social stimulus which often seems to work best, at least for rats. RESOURCES: Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources Another way to get a nice, straight, even run, is to adjust the side walls of the corridor. Adjust them to your animal so it has enough room to comfortably run, but is less likely to take a U-turn. Visualize data Automating your research makes things easy and objective, which is of course a major advantage of systems like CatWalk XT. What is sometimes overlooked is the presentation of all that data you can acquire. I don't know about you, but I am not one that can easily make sense of large tables with numbers. So, I like the visualizations in the CatWalk XT software a lot. It immediately gives a good sense of your data. First, there's the run video itself. You can replay it at different speeds and it will show you the classification of footprints as well. Then there are separate visualizations that show paw and run information in a two or three dimensional plane. What's also really nice: you can export all in video files to use in lab meetings, presentations and defenses. CatWalk XT provides a lot of data on the individual paws, the single runs, and overall trials. You pick what suits your research. This article would be way too long if I'd go into all of them, but trust me, there's a lot. What's really nice: each parameter is described in full in the manual. In many cases, the exact formula is shown along with a publication to support it. CatWalk XT in publications Ok, so one last thing and then I promise to stop bragging about this system (for now). It has six times the number of publications than any other system. Six times! That amounts to over 2,400 publications and we are pretty proud of that. Did I spark your interest? Then you might also like how our Product Manager Reinko Roelofs explains a bit more in this video. References Hamers, F.P.; Lankhorst, A.J.; Laar, T.J. van; Veldhuis, W.B.; Gispen, W.H. (2001). Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries. Journal of Neurotrauma 18(2), 187-201. Pickett, K.A.; Schultz-Darken, N.; Bradfield, A.F.; Malicki, K.; Pape, B.; Ausderau, K.K.; Emborg, M.E. (2020). Spatiotemporal quantification of gait in common marmosets. Journal of Neuroscience Methods 330, 108517. --- ## The importance of a multi-method approach in infant behavior research URL: https://noldus.com/blog/multi-method-approach-infant-behavior Published: 2022-09-22 14:30:00 Description: The study of infant behavior provides incredible insight into the field of psychology, developmental biology, neuroscience, and other social and life sciences. The study of infant behavior provides incredible insight into the field of psychology, developmental biology, neuroscience, and other social and life sciences. A primary method of conducting infant behavior research is observation. Various research tools are available to improve the quality and efficiency of behavioral data acquisition and analysis. The Observer XT behavioral research tool is one such example that helps researchers gain insight into infant behavior and includes data integration options to take a lab to the next level. Advantages of combining research methods for infant behavior studies Various methods exist for studying infant behavior, including recording videos, measuring physiological markers, and analyzing facial expressions. Often, researchers choose to combine these methods [1]. Combining research methods gives researchers the opportunity to gain a more comprehensive view of infant behavior. For example, using multiple methods ensures that the collected data is not limited to participant interviews, as this is typically just parents giving an account of how they think their infant is behaving. Acquiring different types of information Supplementing interviews with direct observations of the infant and measuring physiological markers can help strengthen the data being collected. Thus helping researchers to get their research questions answered. By acquiring different types of information on infant behavior, researchers can obtain a more holistic understanding, compare different data types, analyze relationships, and combine the outcomes to come to valid and strongly supported conclusions. Behavior is a multifaceted and complex topic to study, especially in infants who cannot articulate emotions; therefore, using a combination of research methods ensures a more objective, representative approach to both collecting and interpreting data. FREE WHITE PAPER Tools for Infant Studies Download the free White paper to learn more about the software tools available for infant studies. - Video observations to capture behaviors - Coding behaviors accurately - Unobtrusive emotion analysis Download Analyzing and integrating data on infant behavior using The Observer XT Behavioral research is a valuable way to better understand humans by helping to understand connections between disorders or conditions and behavior. For example, research conducted by The University of South Carolina involved early behavioral and physiological markers of social anxiety in infants with fragile X syndrome. The researchers used a multi-method approach to identify markers like behavioral inhibition, increased attention toward a stranger, and a blunted respiratory sinus arrhythmia response in infants with fragile X syndrome [2]. While data from the parent interviews did not signify a large difference between control and fragile X infant behavior, direct observation identified several behavioral and physiological markers. Code observation videos In The Observer XT the video recordings of in this case the Stranger Kneel task were coded for escape behaviors, distress vocalizations, bodily fear, and visual attention. The software enabled the researchers to code the direct observation videos in a structured and reliable way (Cohen's kappa of 0.81-0.90). Study authors Black and colleagues concluded that the multimodal approach of both interviews and direct observation is integral to helping the researchers understand the complex early characteristics of social anxiety in infants with fragile X syndrome [2]. This knowledge can then be used to address the challenges of the syndrome that can negatively impact infants later in life if left untreated. Thus, taking a research approach in which data from different data sources can be easily combined in advanced software is crucial in analyzing infant behavior. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Using The Observer XT to make sense of data As a previous blogpost mentioned, researchers are amplifying their observations with tools that measure criteria such as pupil reactions, blood pulse, heart rate, and brain activity [3]. To make sense of all the different types of data, robust coding and analysis software for infant behavior research are required. The Observer XT - behavioral research software from Noldus - provides a complete software solution for studying behavior. The Observer XT can conduct behavior coding in a quantitative way with easy timeline visualization, synchronized data streams, and reliable statistical calculations [4]. Learn more about Observer XT here. References and further reading - Psychology research | Noldus. (2022). Psychology Research | Noldus. https://www.noldus.com/psychology - Black, C. J.; Hogan, A. L.; Smith, K. D.; Roberts, J. E. (2021). Early behavioral and physiological markers of social anxiety in infants with fragile X syndrome. Journal of Neurodevelopmental Disorders, 13(1). https://doi.org/10.1186/s11689-021-09356-3 - Martinali, J. (2022, January 4). How to easily apply multimodal measurement during research with children. How to Easily Apply Multimodal Measurement during Research with Children | Noldus Information Technology. Read more: Integrating multiple data streams - Behavioral coding - Event logging software | The Observer XT. (2022). Behavioral Coding - Event Logging Software | the Observer XT. Learn more about The Observer XT --- ## Using video tracking to study operant behavior in rodents URL: https://noldus.com/blog/using-video-tracking-operant-behavior Published: 2022-09-22 13:00:00 Description: What is operant behavior? And how can we use software such as EthoVision XT to increase our understanding in the learning and memory processes involved in these studies? Within the field of learning and memory research lies operant behavior, also called operant conditioning. On the first hand this form of learning and memory seems straightforward to study. However it can become quite complex when trying to interpret certain responses in an animal that are linked to a certain degree of emotionality in humans. In this blog we explain what these types of behaviors are, and how they are effectively measured in rodents using video tracking tools. What is operant behavior? The term "operant" was first used in B.F. Skinner's book The Behavior of Organisms, in 1938. In operant conditioning, three main types of stimuli are used to reinforce behavior: positive reinforcement, negative reinforcement and punishment. It is called operant because it produces some type of consequence that can be understood and learned. In classical conditioning, Pavlov's dog could not control it's salivation. With operant behavior, also called operant conditioning, as a result of reward or punishment, a response (for example getting a treat) is learned and the memory is retained. This gives us insight in the functioning of the brain in memory formation and retention. How is operant behavior measured? The operant conditioning chamber, sometimes called a 'Skinner box' or 'Skinner box apparatus', is an enclosure used to study operant behavior. Such a chamber has several compartments that can be separated by doors that can open upon activation of, for example, an electric buzzer or upon pressing of a lever. In these chambers, (typically) rodents can be taught to press levers (or perform certain tasks) in order to obtain food rewards such as pellets. The likelihood that the animal will repeat, or not, such a behavior is dependent on an associated consequence, which can be either positive or negative (reinforcement or punishment). A negative stimulus, i.e. punishment, is an event that decreases the likelihood of (in this case) a rat or mouse repeating an action. An example of such a stimulus is a foot shock. In this situation a lever press can initiate a foot shock. But this negative stimulus can also be turned around into a negative reinforcement, where if the lever is not pressed, a foot shock is given, thus enforcing lever-pressing behavior. By using punishment and reinforcement in this way, it can help us understand and learn how memories are retained and how they are linked to our previous experiences. In other words, operant behavior is that which operates on the environment, producing consequences. It is the result of operant conditioning and can be observed in many species. How do you train operant tasks? Behavioral tasks in an operant conditioning chamber are typically performed in two stages. Stage 1: Training the task The first stage of training involves learning a new operant response, such as "touch", "jump" or "avoid". This can be accomplished through simple trial-and-error training, where you have your subject perform the task and reward them when they've reached their goal: 'press the lever, receive reward', or as described earlier; 'press the lever, receive punishment'. Stage 2: Recording behavior Once an operant response has been learned, you'll want to record all of its occurrences during a given period of time so that you can later analyze whether it was actually reinforced (i.e., reinforced at least once). This establishes, whereafter you can begin recording behavior. This is a critical step because it allows for future analysis and comparison of your results with other studies. To record behavior, you will need to use video tracking software. The advancements in video tracking technology have greatly improved our ability to follow behavior throughout training and testing sessions. The ability to directly analyze your data is one of the most exciting aspects of using video tracking software in operant conditioning tasks. Why is video tracking essential to study operant behavior? Video tracking is extensively used in operant conditioning research because it allows researchers to record multiple variables at once while keeping track of what happened during each trial. But video tracking is also a useful tool when studying other aspects of behavior during operant behavior studies such as social interactions, anxiety-like behavior or depressive-like behavior. By tracking these types of behaviors it allows researchers to observe what's happening around the animal(s) without having to move them around too much, thus standardizing the environment. This standardization is essential since it helps us isolate important pieces of information from other factors that may interfere with our results, or would rather give us added readouts. Now that we've covered some background on operant behavior, let's take a look at a recent study in this field that ties in video tracking. Example of an operant conditioning study Obesity research: EthoVision XT in action A recent study by Wahli and Huwart et al set out to investigate the food reward system, as this shows neuronal and behavioral dysregulation during obesity [1]. They investigated if inflammation in the striatum was affected in diet-induced obesity (DIO) mice compared to control-fed mice, while also testing the potential effects of gut bacteria on the reward system. For this reason, the mice that were subjected to DIO were split again in a control (placebo) group, and a group that was daily administered Akkermansia muciniphiladaily, an intestinal bacterium heavily associated with obesity, type 2 diabetes and inflammation due to its function(s) in increasing mucus thickness and increasing gut barrier function. This bacterium generally triggers host metabolic and immune responses. Liking and wanting Noldus' PhenoTyper, powered by EthoVision XT, was used to perform a food preference test to test the 'liking' component, while these cages were also used as operant conditioning chambers to test the 'wanting' component in food reward (operant wall test). The 'liking' component is related to the pleasure felt by eating a specific rewarding food whereas the 'wanting' component is related to the motivation to obtain it. RESOURCES: Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Food preference test The food preference test showed that DIO mice showed a lower preference towards choosing a high-fat high-sucrose diet compared to mice that were exposed to a palatable diet for the first time. This shows that there is a dysregulation of the hedonic component of food intake associated with (diet-induced) obesity. Operant wall test The operant conditioning paradigm confirmed the altered motivational reward system associated with obesity, since the DIO mice did not press a lever to obtain a food reward (from the operant wall) as much as control/lean mice. It is suggested that these effects are underlying of a hypo-functioning of the dopaminergic pathway in the brain. The effect of gut bacteria Daily administration of Akkermansia muciniphiladaily showed to be able to diminish these dysregulated responses associated with obesity, possibly through a decreased activation of inflammatory pathways and lipid-sensing in the striatum. This study, which utilizes the full potential of fully integrated operant conditioning chambers (video tracking and hardware control), provides exciting evidence in the fields of gut microbiota and behavioral neuroscience, and how those can be integrated to develop innovative therapeutics to improve food-reward responses in obesity, neuropsychiatry, or other (metabolic) diseases. Video tracking technology has greatly improved our ability to study operant behavior Video tracking technology has greatly improved our ability to follow behavior throughout training and testing sessions in operant conditioning tests (and others alike). Software like EthoVision XT allows us to record the interactions between animals and their environment and then analyze them, in real time, with advanced algorithms that can distinguish between different types of tasks. It makes it possible to see what happens when certain stimuli are presented and you can use this information to analyze the effects of different parameters on operant behavior, such as time or type of response. This allows you to quantify the amount of time an animal spends in one place when given access to food pellets versus another location where there were no pellets available (or vice versa), adding additional information to your readouts. This technology has truly helped us understand how rats and mice learn new behaviors in novel environments. Reference [1] S.J.P. Huwart et al., "Food Reward Alterations during Obesity Are Associated with Inflammation in the Striatum in Mice: Beneficial Effects of Akkermansia muciniphila," Cells 2022, Vol. 11, Page 2534, vol. 11, no. 16, p. 2534, Aug. 2022, doi: 10.3390/CELLS11162534. --- ## Using observational research to capture parent-child interaction URL: https://noldus.com/blog/observational-research-to-capture-parent-child-interaction Published: 2022-09-13 10:54:00 Description: Researchers examined whether a combination of child and parental factors, such as the child's emotional temperament and parents' controlling feeding practices, influence food fussiness. As a parent, you want your child to eat well. When a child gets an adequate variety of food and gets enough nutrients, you can be sure of a healthy foundation to grow. But what if your child won't eat? If that happens sporadically, it is annoying but not a huge problem. However, if it is structural, it will become problematic and will cause great concerns for parents. Not to mention the extent to which this can frustrate parents. Eating problems in children Food fussiness is a common feeding problem: the child is very selective about which foods he/she is willing to eat. As a child, I used to fish out the onions my mother put into the meal. No way was I going to eat that. I did not like the taste and texture. Same goes for mushrooms, yuck. All kinds of factors can play a role when a child does not want to eat. For example: - Physical problems such as swallowing difficulties, allergies, intestinal complications, or an abnormality of the esophagus. - After the first year, children grow less quickly and therefore have less need for food. - Developmental disorders such as Autism Spectrum Disorder can cause mealtime difficulties. - Going through psychological development can cause stubbornness or rebelliousness. - A combination of child and parent factors, such as emotional child temperament and parents' controlling feeding practices, namely verbal pressure, physical prompts, and food rewards. These latter factors were the subject of the study of Stella Rendall, Helen Dodd, and Kate Harvey. FREE WHITE PAPER: Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Food fussiness, emotionality, and controlling feeding practices The importance of the research of Rendall and her team was to provide further insight into the characteristics and experiences of children who are fussy eaters as well as to yield information to support interventions for children at risk of fussy eating. For that, they wanted to explore associations between controlling feeding practices and food fussiness further. They also wanted to investigate whether the relationship between children's emotional temperament and food fussiness is moderated by maternal use of controlling practices. They chose an observational approach, using structured coding schemes, to objectively capture the parent and child behavior. FREE WHITE PAPER: How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Coding mealtime behaviors Sixty-seven mother-child dyads, with children aged 2-4 years, were video-recorded during a typical meal in their home. The meal consisted of four food items, two of which were familiar (appealing and unappealing) and two of which were unfamiliar (appealing and unappealing). Mothers' use of controlling feeding practices during this meal were coded afterwards, using the Family Mealtime Coding System (FMCS). Three subscales of the FMCS were used to study the parent-child interaction: - Use of verbal pressure (encouragements to eat, such as 'try some more of the soup'). - Use of physical prompts (such as pushing a plate of food towards the child). - Use of verbal incentives/rewards (food rewards and non-food rewards, for example 'if you eat your peas, you can have your favorite pudding'). One researcher and a second coder used The Observer XT for offline coding. An interrater reliability of 90% was reached. The second coder subsequently coded 25% of the videos with the percentage agreement between coders ranging from 82 to 96%, an indication that coding achieved a high reliability. FREE TRIAL: Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Furthermore, mothers completed two questionnaires: - Children's Eating Behavior Questionnaire – food fussiness subscale (CEBQ FF) containing 6 statements to assess mother's perception of their child's food fussiness and evaluate whether the child eats a variety of foods, the child's interest in new foods and how difficult the child is to please with meals. - Emotionality Activity Sociability Scale (EAS) containing 20 statements to assess children's temperament, emotionality, activity, sociability, and shyness. Is the emotional tone of mealtimes a crucial factor? The research team describes that the key finding of their study is that the relationship between emotional temperament and food fussiness was significant when mothers used more verbal pressure and physical prompts but was not significant when mothers used fewer verbal pressure and physical prompts. The findings suggests that while emotional temperament may potentially be a risk factor for the development of children's food fussiness, the feeding practices that mothers use during mealtimes may ultimately determine if such children become fussy eaters. References Rendall, S.; Dodd, H. & Harvey, K. (2022). Controlling feeding practices moderate the relationship between emotionality and food fussiness in young children. Appetite, 178. https://doi.org/10.1016/j.appet.2022.106259 --- ## (Un)social rats: the role of dopamine and the amygdala in social adversity URL: https://noldus.com/blog/dopamine-amygdala-social-adversity Published: 2022-09-08 13:30:00 Description: With optogenetics and behavioral testing, researchers found a link between infant social adversity and decreased social behavior in the circuitry of the amygdala. (Un)social rats: the role of dopamine and the amygdala in social adversity Many psychiatric and developmental conditions, including autism, anxiety, and depression, often have a common denominator: disrupted social behavior. Though researching the influence of the brain on behavior is not easy, scientists from various institutes in the USA and Canada have come up with an interesting approach [1]. They used viruses and optogenetics in an attempt to link certain brain circuits to social deficits. Badly-functioning neural circuits are known to be capable of causing social interaction deficits, often occurring in psychiatric conditions. Technical limitations so far made it difficult to study those circuits, so not much is known yet about their development, be it typical or pathological. Amygdala and dopamine in development The researchers in this current study used the TH-Cre rat model (useful for studying neurodegenerative conditions), and wild type rats as a control. The main focus was on specific parts of the amygdala, which has a primary role in emotional responses, and is used in the current study to investigate social behavior during infancy. This specific age group was studied with the goal to investigate the role of the amygdala, and the dopamine networking therein, to uncover the emergence of social deficits during early-life which show a lifelong propagation. Circuitry in the Amygdala Adversity in the rat pups was introduced through procedures with the caregiver. Deciding if social stimuli are a threat (adverse) or not is done through the basolateral amygdala (BLA), which receives most of its dopamine from the ventral tegmental area (VTA). Together, they form the VTA-BLA circuit. Too much dopamine, and the threat/safety evaluation is impaired. Early trauma in infants, associated with the caregiver, can have severe effects on this system. Adapting an optical circuit dissection technique made it possible in this study to investigate this neural system in these very young pups. Treatments during pup development Adversity through parenting For the experiment, infant Long-Evans rats are used. Their date of birth is counted as PN0, and they were reared normally until PN8 and again after PN12, while half of the rat litters were assigned to scarcity-adversity rearing, where cage bedding was reduced to 1.2 cm (control litters had a typical layer of 5-7 cm bedding material) from PN8 to PN12. See the full materials and methods used in this study in the paper by Opendak et al [1]. Reduced bedding material caused rough handling of the pups by the mother and an inability to build a proper nest, while maintaining normal weight gain. The goal of this treatment was to cause social adversity at an early age. Shock procedures At PN12, the pups were split into 3 groups; "shock alone", "shock with mom" and "control". Each pup was put into a transparent container alone, or with their respective 'mom', which either was or was not anesthetized. A non-shock, no mother group served as a control. It did not matter for the outcome whether the mom was conscious during this shock procedure or not. This procedure was repeated over 5 days, in which, among other, the pups' ultrasonic vocalizations, limb movement per shock (4 limbs + head) were recorded, and behavioral activation was measured using Noldus' EthoVision XT. Infant ultrasonic vocalizations are a measure of pup distress, and serve an important communicative role in eliciting caregiving behaviors. Ultrasonic vocalizations and atypical maternal (social) behavior Initially the researchers in this current study found that on the first day of shock procedures, pups with their mom present (whether anesthetized or not) emitted fewer ultrasonic vocalizations than shocked pups that were alone. This difference however dissipated as the 5-day testing procedure continued. No difference in ultrasonic vocalizations was found in the adversity-reared pups compared to control, nor were there significant atypical behaviors found towards the mother in this groups (such as sleeping behind the mother's back or failing to approach the dam and nurse). This effect was however clearly distinguishable in the pups that were shocked with their mom present. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Description of the social interaction tests The pups underwent a mom-pup social interaction test on PN13. For 30 minutes, the pups were together with the anesthetized mom, and several behaviors were scored: time nipple-attached, time at mother's ventrum (not nursing), going behind mother's back, and stereotyped behaviors. A different group of rats (weaned at PN21) was tested at 22 ± 1 days old, in a 3-chamber social test apparatus. After 5-min acclimation, a littermate and a novel peer were put into two small, perforated metal boxes, one in each of the outside chambers. The test animal then had 10 minutes to explore. Using Noldus EthoVision XT, duration of nose contact with the other rats, time spent in each chamber and activity level were recorded and analyzed automatically. Surgery treatments Next to various brain analyses (see the original paper), the pups had two surgeries, one for optogenetic manipulations, the other for microdialisys, in order to prepare them for the social behavior tests. Microdialysis at PN13 (after probe implantation in the BLA at PN10-11) showed that shock with the mother was associated with a specific increase in dopamine efflux. Adapting these procedures for these young pups showed that there was engagement of the amygdala which was causal in decreasing social approach towards the mother (and towards novel peers). Optogenetics The surgery to prepare the optogenetic manipulation took place at PN1, where each rat received a dose of a tailored virus into their amygdala. Both the TH-Cre pups and the wild type pups each received one of three viruses, so six viruses in total. The viruses were either a control, or contained genes that are capable of either suppressing (Arch) or enhancing (ChR2) amygdala activity. Each virus contained a "light switch", which could be used to activate the genes once a laser beam was aimed at them. During PN8-12 the shock procedures and behavioral assessment (as described above) took place, and on PN13, each rat received an optical fiber implant into the BLA. After recovery, the pups underwent social testing (PN14-15) with their 'mom'. This showed that the previously described decreased approach towards the mother after the shock procedures, could be rescued by inhibition of the BLA with 532 nm light. Using Noldus' EthoVision XT, the behavior between "on" and "off" bouts was analyzed automatically and compared. Conclusion This study revealed that VTA-BLA brain circuit is indeed causal when it comes to decreased social behavior both toward the mom and their peers. The circuit will become hyper-engaged in social adversity experienced during infancy, but not in adversity experienced alone. It might therefore be a good new therapeutic target for the social interaction deficits that are rooted in psychiatric disorders. If this adversity is repeated, the caregiver of the rat infants has a decreasing ability of regulating the neurobehavioral response to threat, i.e. calming their young. Reference - Opendak, M., Raineki, C., Perry, R. E., Rincón-Cortés, M., Song, S. C., Zanca, R. M., ... & Sullivan, R. M. (2021). Bidirectional control of infant rat social behavior via dopaminergic innervation of the basolateral amygdala. Neuron, 109(24), 4018-4035. --- ## 5 Tips for writing better Horizon Europe grant proposals URL: https://noldus.com/blog/tips-better-horizon-proposals Published: 2022-09-05 10:00:00 Description: Noldus has been a partner in many research projects, which means that we have a lot of experience writing grants. Read our tips for writing better grant proposals, based on our own practical experience. Experience with grant writing Noldus has been a partner in dozens of funded EU projects, as well as many more regional and national ones, about 140 in total. That means that we have a lot of experience writing grant applications. The tips below are all based on our own practical experience from reviewers' feedback, as well as from being reviewers ourselves. Horizon proposals are very competitive, with almost 90% not being funded in Horizon 2020. As well as the tips below, we can help you personally with our grant assistance program. 1. Consortium composition is crucial It is tempting to invite the people who you happen to know to join the consortium. However, to succeed, you should aim to have the best in their field. You must also have enough diversity, with all the disciplines necessary to carry out the research and to achieve the impact you will claim. Include SMEs and possibly large industry partners. If scores between projects are equal, gender balance, geographical diversity (number of counties) and SME involvement are used to decide which get funded. The consortium is presented both in Part A (more extensively than in Horizon 2020) and at the end of the proposal, so make sure those two sections are well-aligned. 2. Plan in enough time for the proposal Normally you should aim to start putting the consortium together at least six months before the deadline, maybe even before that. The days when proposals could be written as an extra task in the evenings and weekends are long gone. For researchers involved in grant writing, it is an integral part of their normal professional work, and a consortium member who has no time for meetings or repeatedly misses deadlines for their inputs will be seen as a problem. Coordinating a proposal takes a lot of time, and it is not unusual for a consortium to stop because no one wants to coordinate. A solution can be to divide the coordinating tasks up between two or more partners, or to hire a company to help. Allow enough time to proofread and review the whole document. A review by someone outside the team is useful at a stage when there is enough text to understand the project idea, but not too late to make important changes. 3. Focus on the Call Don't just read the Call at the beginning of the process, but regularly check the text as your proposal develops. The proposal is evaluated against the call text. It is also important that you understand the structure of the call and how that relates to your proposal. For instance, the call defines Expected Outputs, and those must be clearly related to the project Deliverables. Topic outcomes are related to medium term impacts, and the Destination defines the wider scientific, economic and social effects in the long term. It is good practice to start with the project objectives and impact summary, as the other sections should flow from them, rather than the other way round. 4. Impact This is the section that proposals most often loose points on. The impact is assessed on both the scale (how big an impact) and significance (how important an impact) as well as the credibility of the path that you describe to reach that impact. Is it credible to claim an EU-wide (or even global) impact if the partners are all in one region of Europe? Is a project worth funding if its results will only benefit a small number of people? Is it credible that the project results will come onto the market if there is not a company in the consortium? Try to go beyond the standard measures to maximize the impact - communication, dissemination and exploitation. Make sure you understand the difference between those three: communication is about all aspects of the project, dissemination only about the results, and exploitation is about use of the results by stakeholders after the project (e.g. for commercial purposes or as input for policymakers). This must also be credible; no one will believe that you will influence policy if there is no specific activity to communicate the results to the right policymakers. 5. Remember who you are writing for The reviewers have many proposals to assess in a limited time, so do everything you can to make their life easy. A Horizon proposal should articulate how you will help the EU to solve its problems, not how you will further your research & development interests (except for ERC calls). You are not writing a scientific paper, and some reviewers will be from a different discipline than your own. That means not too many references, make it easy to read, without jargon, and clearly structured. Avoid fuzziness everywhere, but especially in your objectives. Graphics and illustrations help; even with the 45-page limit, there should be room for some. Familiarize yourself with the expert briefing explaining to reviewers what the assessment criteria are. The evaluators will often read the summary in Part A first, so make sure that is really well-written and very clearly presents the heart of your project idea. The impression that the summary creates will affect the way that the reviewers read the rest of the proposal. Help Are you busy with a Horizon proposal? Maybe Noldus could be a partner in your project. If the grant could be used to buy solutions from Noldus, we offer a grant assistance program to help you improve your proposal. See here for more information about that. GRANT ASSISTANCE PROGRAM How can we help you with your grant applications? - We want to position you with the best competitive advantage upon review. - Our scientific research consultants will work collaboratively with you. Apply now --- ## Better together or happier apart? The effects of housing on stress in mice URL: https://noldus.com/blog/the-effects-of-housing-on-stress-in-mice Published: 2022-08-31 15:00:00 Description: Does housing mice on their own affect animal welfare and reduce experimental validity? How was EthoVision XT video tracking software used to automate this investigation? Better Together or Happier Apart? Investigating the Effects of Housing on Stress in Mice Does housing mice on their own affect animal welfare and reduce experimental validity? Researchers at the University of Brussels (Buckinx et al) investigated this question using EthoVision XT video tracking software to automate their experiments [1].  Housing Strategies for Mice Research has shown that animal welfare is a key factor in animal experimentation, not only for minimizing stress in animal subjects, but also to ensure the validity of scientific results gained in this way [2, 3].  Since mice are the most commonly used animals for biomedical research, the question of how best to house laboratory mice in order to minimize the amount of stress they experience is an important consideration in biomedical research [4]. Since mice are social animals, group housing or pair housing are the recommended default housing conditions. However, aggression between male mice frequently means that single housing is more practical. Also, single housing might be a more favorable experimental condition in certain studies, for example when group environments might compromise specific individualistic behavioral variables that are under investigation. In such cases, single housing can help scientists draw conclusions aimed at changes to a mouse’s specific individual behavior based on stimuli from the experiment itself and not influenced by other mice present. In the interests of maintaining the potential social benefits of group housing while precluding inter-male aggression, the use of cage dividers – which permit sensory contact between mice without physical contact – have been suggested for experiments where group housing is not possible.5 Analyzing Behavior, Movement and Activity Using EthoVision XT Buckinx et al decided to investigate the impact of different housing methods on the stress levels of mice in a series of tests [1]. Their research team first housed mice in a variety of conditions – single housed, pair housed, or pair housed with a cage divider – for several weeks. After this period, the researchers used EthoVision XT video tracking software to automatically monitor and analyze the movement and behavior of the mice during three different tests. Open Field Test The Open Field Test (OFT) is a test used to assess general activity levels, gross locomotor activity and exploration habits [6]. In this test, the researchers used EthoVision XT to automatically calculate several parameters: total distance traveled, time spent in the center zone, and measurements to evaluate exploratory/locomotor activity and anxiety-like behavior. The researchers found that while total distance traveled was statistically different between housing conditions in these experiments, the time spent in the center zone – a measure of anxiety-like behavior – did not differ significantly. LABEL Title Learn more Elevated Plus Maze Test The Elevated Plus Maze (EPM) test is used to investigate anxiety-like behavior [7]. In this test, mice are placed in a cross-shaped maze elevated from the ground. Two of the arms of the plus-shaped maze are open, while the two other arms are enclosed, providing a more sheltered area that tends to get more (and longer) visits by mice that are more anxious. In this test, EthoVision XT enabled the researchers to completely automate measurements of time spent in the open arms, total distance traveled, and exploratory/locomotor activity. The team observed that time spent in the open arms of this maze and the total distance traveled remained unaffected between housing conditions. LABEL Title Learn more Fear Conditioning/Freezing Behavior Finally, the researchers used the auditory fear conditioning paradigm to study fear memory formation in the mice [8]. In this test, EthoVision XT was used to examine freezing behavior in mice during habituation periods and as they were presented with various auditory stimuli. By defining “freezing” in terms of a difference between pixels (max 0.3%) in consecutive frames over a period of 1s, the researchers were able to use EthoVision XT to automate the process of data collection for this test.  While there was a general trend recorded, no significant difference in freezing behavior was found between single and group housed mice in these fear retrieval tests. Learn more about fear conditioning in our free white paper LABEL Title Learn more So what do these outcomes mean? The results from the open field, elevated plus maze and fear conditioning test did not show any particular differences between mice that were singly or pair-wise housed, nor with a cage divider. This was unexpected considering the hypothesis of the study, stating that single housing would probably increase stress and anxiety (and would be decreased again by the cage divider). The authors suggest that this method is highly context-dependent, and should be further investigated before being considered a viable housing strategy in mice. Such investigations are extremely valuable for the ongoing improvements in animal welfare and ethics in general, which are made possible with powerful and versatile tool such as EthoVision XT. The value of EthoVision XT EthoVision XT has evolved over the years from video tracking software into a fully-fledged software platform, offering full integration of data and automation of animal behavior experiments. From simple tests like open field to complex or high-throughput protocols, EthoVision XT provides accurate measurement of a huge range of parameters along with unparalleled versatility in data processing and visualization. EthoVision XT is now by far the most cited video tracking system in the world [9]. RESOURCES: Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References and Further Reading - Buckinx, A. et al. Exploring Refinement Strategies for Single Housing of Male C57BL/6JRj Mice: Effect of Cage Divider on Stress-Related Behavior and Hypothalamic-Pituitary-Adrenal-Axis Activity. Frontiers in Behavioral Neuroscience 15, (2021). - Poole, T. Happy animals make good science. Lab Anim 31, 116–124 (1997). - Science-based assessment of animal welfare: laboratory animals - PubMed. https://pubmed.ncbi.nlm.nih.gov/16358504/. - Carbone, L. Estimating mouse and rat use in American laboratories by extrapolation from Animal Welfare Act-regulated species. Scientific Reports 11, 493 (2021). - Social enrichment by separated pair housing of male C57BL/6JRj mice | Scientific Reports. https://www.nature.com/articles/s41598-020-67902-w. - Open Field. Behavioral and Functional Neuroscience Laboratory https://med.stanford.edu/sbfnl/services/bm/sm/openfield.html. - Elevated Plus Maze Test. Behavioral and Functional Neuroscience Laboratory https://med.stanford.edu/sbfnl/services/bm/ep/bml-plusmaze.html. - Effects of repeated anodal transcranial direct current stimulation on auditory fear extinction in C57BL/6J mice - PubMed. https://pubmed.ncbi.nlm.nih.gov/33454396/. - Benefits - EthoVision XT. Benefits - EthoVision XT https://www.noldus.com/ethovision-xt/benefits. --- ## How music affects children’s development URL: https://noldus.com/blog/music-emotions-and-learning Published: 2022-08-30 10:00:00 Description: Researchers dove deeper into building an understanding of the relationship between music and emotions and how music affects children’s development. Do you remember the first time you listened to music? Or when you sang your first song? Where does this take you: a memory of your parents singing you to sleep, a birthday party with friends or maybe the start of a school day as a young child? Or maybe something completely different? Children’s facial affect in musical imitation and improvisation Wherever this question might take you down memory lane. If you went there in your thoughts, did you notice anything? Maybe a little smile appeared on you face. Maybe you are surprised, how well you remember a specific song after all these years. The implied connection here between music, emotions, and learning is more than a hunch. In fact: “Some scholars suggested that children learn to sing prior to speaking (Malloch & Trevarthen, 2018; Stadler Elmer, 2011). In addition: “Social experiences in early childhood contribute to an understanding of emotions and appropriate responses. These experiences become the foundation for social competence, which contributes to academic performance” (Heller et al., 2012). Connection between music, emotions, and learning In the early stages of life where we learn to understand emotions and their role in communication, music plays an important role. Bugos et al. recently dove deeper into building an understanding of the relationship between music and emotions with 89 children between 4 and 6 years old. How to measure emotions of children? However, this poses one slight problem. How do you scientifically measure emotions if your young participants are still developing their own understanding of these emotions? The researchers therefore decided to support self-reports outcomes with data provided by FaceReader. This is a software tool build for quantitatively measuring emotions based on the activation of Action Units. FREE WHITE PAPER Facial Action Coding System Download here the FREE white paper 'Facial Action Coding System (FACS)' and learn more about: - Objective results with FACS - Action Units - Examples using FACS Submit to download Data collection was done using a brief version of the Advancing Interdisciplinary Research in Singing-Test Battery of Singing Skills (AIRS- TBSS). The children were asked to perform three singing tasks: - sing a favorite song - imitate a song - improvise a song ending To establish more comfort in performing the tasks the children sung in front of a stuffed giraffe, named Gerald. After each task the children were asked to rate their experiences using a Likert-type scale. The researchers cross-referenced these results to the data generated by FaceReader using a chi-square analysis. In addition, children’s responses were examined for emergent themes. Hereafter, the verbalized emotions emerging from the responses were compared with FaceReader. The alignment was found to be 84.87%. Positive perception of improvisation As a result, the researchers found that both singing a favorite song and improvising correlated with happy affect. Imitation of a familiar folk song (father Jacob) resulted mainly in surprise. It is especially interesting to see the positive perception of improvisation. The researchers suggest that this may contribute to reduced anxiety or tension for young children. More research is needed to also gain understanding in how emotions in turn influence vocal development. How music affects children’s development As currently many schools are eliminating musical lessons it becomes increasingly important to understand how music might affect the development of children regarding their emotions and communication skills. As social creatures it is important we develop these skills at a young age so they benefit us and the people around us for the duration of our lifetime. We should remind ourselves of the importance of these soft skills next to learning hard facts, because if seems that learning through music provides us with more than pleasant memories alone. This blog post was written by Kay Potters (Consultant at Towson, and former Sales Consultant at Noldus Information Technology).  FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download References - Bugos, J.; Demarie, D.; Torres, M. & Fuller, N. (2022). Face the music: Children’s facial affect in musical imitation and improvisation tasks. Psychology of Music, 50(2), 460-474. https://doi.org/10.1177/03057356211003320 - Cohen, A. J. (2015). The AIRS test battery of singing skills: Rationale, item types, and lifespan scope. Musicae Scientiae, 19, 238–264. https://doi.org/10.1177/1029864915599599 - Heller, S.S.; Rice, J.; Boothe, A.; Sidell, M.; Vaughn, K.; Keyes, A., & Nagle, G. (2012). Social- emotional development, school readiness, teacher–child interactions, and classroom environment. Early Education and Development, 23, 919–944. https://doi.org/10.1080/10409289.2011.626387 - Malloch, S. & Trevarthen, C. (2018). The human nature of music. Frontiers in Psychology, 9, 1680. https://doi.org/10.3389/fpsyg.2018.01680     --- ## How to observe adolescents and teachers in a classroom URL: https://noldus.com/blog/how-to-observe-adolescents-in-a-classroom Published: 2022-08-25 10:20:00 Description: Many researchers focus on classroom interaction to learn more about group dynamics, teaching behavior, and student engagement. One of the research methods used is behavioral observation. Many researchers focus on classroom interaction to learn more about group dynamics, teaching behavior, and student engagement. One of the research methods used is behavioral observation. By using video and audio recording equipment placed in a classroom, researchers collect the material they need to improve teacher-student interaction, evaluate interventions, and much more.  Here are three examples of how researchers observe adolescents and teachers in a classroom using the latest tools and techniques. Example nr. 1: Teacher training Marie Bocquillon of the University of Mons, Belgium explains how she uses technology like IP cameras, microphones, and software from Noldus in order to improve the training of teachers. "We are observing things like: what kind of questions are said, what kind of feedback do the future teachers use in front of their students? Do they check for understanding? Are they talking with each student, and not only with the two or three good students? Things like that we can see with an observation."  She explains in this video that it is challenging to find the right balance between seeing the bigger picture and coding behaviors in great detail.  Taking that into consideration, it is always advised to think about what questions you actually want to answer and what behavioral coding is necessary to answer these questions. Example nr. 2: Evaluate an intervention program Behavioral role play is often used to look into thought processes and behaviors. David Wolfe and colleagues from the University of Toronto, Canada made use of this method and evaluated a classroom-based healthy relationship program.  This study included classroom observations of in total 21 lessons. Older students were asked to participate as actors in the role playing exercise: bullying or pressuring the participants of the study for example.  To capture all responses, David Wolfe and colleagues recorded the interactions on video and coded relevant behaviors afterwards. The Observer XT included the behavioral coding scheme Wolfe and his team developed: delay, refusal, negotiation, yielding, and compliance.  FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding - 7 tips' and learn more about - Defining your behavior group - Point events - Coding from a diversity of sources Download These classroom observations provided the researchers with information about the strategies adolescents used when managing the interactions. One of the conclusions drawn was that adolescents who participated in the program showed more negotiation skills and delay tactics compared to adolescents who did not participate.  By combining this behavioral study with a post-intervention study, these researchers are able to determine the success of an intervention program. Example nr. 3: Student-teacher interaction study Researchers from the Netherlands (Cents-Boonstra et al. 2021) teamed up to explore patterns in teachers' use of specific motivating teaching behaviors in relation to students' positive engagement. Results from this particular study showed that specifically asking motivating questions and providing positive feedback and support during exercises were associated with subsequent positive student engagement.  FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Download In the paper, published in the European Journal of Psychology of Education, you can find the complete coding scheme. It comprises of the actor (teacher), value (motivating), and the behavior (provides choice, provides (non) verbal positive feedback). Moreover, you can also find coded examples, like 'Super', 'Very good', and 'Thumbs up' to see exactly how the researchers quantified behavior. It was mentioned that the student engagement was coded for all the students as one actor since the focus was on the teacher in this study. When coding individual student behavior in the future, the researchers could discover more about the interactions of students with different degrees of engagement, with the same teacher making the individual student's behavior part of the classroom dynamics.  Also read: 10 reasons why AV tool Viso is beneficial for video feedback [INFOGRAPHIC] References - Cents-Boonstra, M.; Lichtwarck-Aschoff, A.; Lara, Mascareno Lara, M.; Denessen, E. (2021). Patterns of motivating teaching behavior and student engagement: a microanalytic approach. European Journal of Psychology of Education, 37, 227-255. https://doi.org/10.1007/s10212-021-00543-3 - Cents-Boonstra, M.; Lichtwarck-Aschoff, A.; Denessen, E.; Aelterman, N.; Haerens, L. (2021). Fostering student engagement with motivating teaching: an observation study of teacher and student behaviours. Research papers in Education, 36 (6). https://doi.org/10.1080/02671522.2020.1767184 - Wolfe, D.A.; Crooks, C.V.; Chiodo, D.; Hughes, R.; Ellis, W. (2012). Observations of adolescent peer resistance skills following a classroom-based healthy relationship program: a post-intervention comparison. Prevention Science, 13, 196-205. https://doi.org/10.1007/s11121-011-0256-z --- ## The social interaction test: effortless and dependable with EthoVision XT URL: https://noldus.com/blog/social-interaction-in-fish-and-rodents Published: 2022-08-24 13:30:00 Description: What is the social interaction test? This blog dives into this topic for fish and rodents. Why is social interaction important to measure, and how do we go about doing it? Social interaction in fish and rodents: effortless and dependable with EthoVision XT       What is the social interaction test? First things first: what is a social interaction test? A social interaction test is the study of behavioral interaction between two or more individuals. These behaviors can be directed at each other, thus mutual, but also one-sided, for example when there is specific interest in a novel individual. Social interaction can be studied in different types of set-ups and the behavior of interest can vary from sexual and mating behavior to agnostic behavior, maternal behavior and so on. Engaging in social interaction Social behavior is conserved in many animal species. It has a clear evolutionary benefit in terms of food seeking behavior, predation risk, caretaking, and many more related to survival and fitness. In general, all creatures like to live in groups, although for certain species this (social) preference is particularly strong. This is because for some species it is advantageous, while for others it is simply necessary. Typical social behaviors in rodents Rats and mice are the most commonly used rodents in biomedical research. By nature, they are social species. Group housed rats or mice perform an array of behaviors that do not occur in singly housed mice. Moreover, individually housing these species can greatly impact their behavioral and metabolic phenotype. Broad categories of rodent social behavior include social dominance and aggression, maternal and parental behavior, and social recognition and approach behavior. To study behavioral variations within each of these groups, specific tests have been developed that are based on sight, smell, (un)familiarity and social isolation.    LABEL Title Learn more The three chamber test A three chamber test is, as stated in the name, a test based on an arena with three distinct areas. These areas are separated by walls, but accessible through removable doors. The most commons social interaction tests that are performed in this arena are: sociability and social novelty. Because they are social creatures, rodents typically prefer to spend more time with other rodents (sociability) and are more likely to examine a strange visitor than a familiar one (social novelty). In the "sociability" session, a rodent (after habituation to the arena) experiences an unknown ‘stimulus’ animal in a barred plastic cylinder (to allow for interaction without direct confrontation) in one of the lateral chambers (the center chamber remains empty and serves as the starting zone) while the remaining “third” chamber contains the same barred cylinder, however empty. This creates the following readout: preference towards a novel object (empty cylinder), versus preference towards a novel object + ‘stimulus’ animal.   During a "social novelty" session, the subject rodent is introduced (in a similar setting as above) to a familiar animal in one of the chambers, while the other chamber contains a cylinder with a completely unfamiliar animal.   These tests are helpful for estimating impairments in social behavior in, for example, transgenic animals with autistic features. But also for assessing the impact of novel pharmacological substances on social behavior. LABEL Title Learn more Typical social behaviors in fish Fish social behavior includes mating and courtship behavior, cooperative interactions, shoaling, social hierarchy, which is characterized by aggressive interactions to advance in social rank and protect territory, as well as resource-related activity. Fish generally increase their locomotor activity to demonstrate the above-mentioned social behaviors. The coordination of locomotion reflects the type of social behavior. Interactions between individuals of the same species are usually mediated via olfactory (pheromone) and visual cues, as well as phenotypic traits including body type, color, and gender. Additionally, social behavior is also impacted by the time of day (and/or circadian rhythm). Check out this white paper on social behavior in zebrafish  LABEL Title Learn more Testing social interaction in zebrafish In (zebra)fish social interaction can be tested in similar ways as in rodents, however there are some distinct differences. Shoaling and social preference are two common behavioral readouts in the ‘social’ category. In shoaling tests, fish are tested in one tank and allowed to freely move throughout this tank. Interfish distance determines the degree of shoaling, which has multiple benefits in the wild such as reduction of predation risk, better orientation and synchronized hunting. In a fish social preference test a similar three chamber arena setup, as in rodents, can be used. However the lateral chamber are not generally accessible to the subject fish. These chambers contain stimulus fish (or shoals), and the subject remains in the center area. The time spent close to one of the stimulus then says something about social preference. This sociability arena for (zebra)fish is available from ConductScience (also know as Maze Engineers) Social interaction test with the help of EthoVision XT Noldus has developed specific algorithms in its state-of-art video tracking software, EthoVision XT, to detect the nose point and tail base of rodents. This allows for precise detection of an animal’s location and position in a social interaction test. Similarly, algorithms have also been designed to specifically detect these body points in fish. Therefore, with EthoVision XT, it is possible to differentiate between nose-to-nose contact and nose-tail contact. These two can have a completely different biological meaning and are essential to detect separately. For instance, nose-to-nose contact could be very interesting when studying aggression while nose-tail contact could be interesting when studying mating behavior. Other social parameters are based on the position and movement between the animals. The relative movement parameter tells you whether two animals were moving towards each other or away from each other,  but also if there was no relative movement, or if the animals were too far away from each other for social interaction to even take place. Because the changes of position between two animals have a smaller effect when animals are further away from each other, EthoVision XT also calculates the net relative movement. In this case, the absolute distance between these animals is taken into account. Read more about Noldus' tools for a social interaction test  The social interaction test in practice! Check out the work by these labs:  Social interaction research at The Bleakley Lab At the Bleakley Lab at the Stonehill College in Easton, Massachusetts, US, inbred and wild line of guppies are used for this test. Here they explore how the genetic component of the social environment influences antipredator behavior and cooperation. Dr. Bleakley’s research focuses on the evolutionary genetics of social behavior. Social learning task in rats at the Heinrich Heine University PI Dr. Marijn van Wingerden and his PhD student Sander van Gurp study social learning behavior in rats at the Heinrich Heine University in Düsseldorf in Germany. With their team, they are studying if rats can learn from each other. If something good happens to the partner rat, will this affect the learning process in the observer rat? With this study they hope to contribute to the development of potential interventions. Learn more about this study by watching the video down below! --- ## How do parenting practices relate to children’s nutrition risk? URL: https://noldus.com/blog/parenting-practices-nutrition-risk Published: 2022-08-22 12:07:00 Description: Nutrition plays a vital role in children’s growth, development, and health. Researcher Walton and her team observed family mealtimes to gain a better understanding of children’s nutrition risk. Nutrition plays a vital role in children's growth, development, and health. Good nutrition supports their cognitive development and decreases the risk for many diseases, including diabetes and heart disease. Sadly, millions of children around the world suffer from malnutrition. Malnutrition occurs in different forms, ranging from shortages in food intake or specific nutrients to overweightness and obesity. Because dietary patterns develop early in life, improving eating behaviors in young children is key to preventing malnutrition. Food parenting practices As the primary source of influence in young children's lives, it has been suggested that parents play an important role in establishing healthy eating patterns. Indeed, evidence suggests that food parenting practices are related to children's dietary intake and nutrition risk. However, findings in this field of study are inconsistent. For example, while some studies indicate that restricting access to unhealthy foods results in higher intakes of these foods, others show more favorable results for restrictive parenting. Recent scientific reviews suggest that these inconsistencies may be due to methodological limitations. First, research in this area relies mostly on parents' own reports on food parenting. Factors like inaccurate recall or social desirability bias may limit the validity of these measurements. Second, these studies are often conducted in a laboratory setting. It is plausible that eating behaviors are different in the home environment, where parents are present during mealtimes and various family interactions can occur. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly Nutrition risk Researcher Walton and her colleagues addressed these limitations by conducting an observational study in families' homes. Their aim was to study parenting practices during mealtimes and explore their relation with nutrition risk and nutritional status. Specifically, they hypothesized that controlling and pressuring parenting practices would result in a higher child nutrition risk. They also predicted that positive encouragement during meals would be associated with a lower risk. Moreover, they examined whether family functioning influenced these results. Family functioning describes how family members manage daily routines, communicate with each other, and connect to one another emotionally. Lastly, they were also interested in food parenting differences between mothers and fathers. Observing family meals The research team included 73 families in their study, each with children between 1.5 and 5 years old. Families were asked to record three "typical" evening meals with a video camera. After each recording session, the primary parent was asked to report on food parenting practices, aspects of their home environment, and their child's nutrition. Parent behaviors were observed and coded using The Observer XT. The software package was also used to calculate coders' intra-rater and inter-rater reliability. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Behaviors were coded according to the Family Mealtime Coding System (FMCS). This coding system maps different methods in food parenting, including pressure to eat, physical prompts, verbal and physical restriction, food and non-food rewards, and positive comments about food. As a measure of nutritional status, the researchers also studied children's body mass index (BMI). Mothers and fathers To gain a better understanding of different parenting practices, all data was analyzed separately for mothers and fathers. Among mothers, more frequent physical restriction – moving a specific food away from the child - was associated with a higher nutrition risk in their children. On the other hand, more frequent positive comments about the child's food were associated with a lower nutrition risk. These results remained significant after controlling for family functioning and were in line with the researchers' predictions. When examining fathers, positive comments about their child's food were also associated with a lower nutrition risk. However, these results were no longer significant after adjusting for family functioning. No relations were found between food parenting practices and child BMI. What works? Overall, findings from this study suggest that controlling parenting practices work adversely in establishing a healthy eating pattern in children. Earlier research suggests that this is the case because parental restriction undermines a child's ability to recognize and respond to internal cues of hunger and satiety. The results also indicate that positive commenting, especially regarding the child's food, may help to reduce young children's nutrition risk. Strengths & limitations The current study differed from earlier research by using direct observation, studying eating behaviors in a home environment, and including fathers as well as mothers. The research team also made an effort to study "typical" mealtimes and used a validated screening tool to assess nutritional risk (NutriSTEP ®). A few limitations should also be mentioned. For example, the final sample for analysis included mostly families with a low nutrition risk, high family functioning, and highly educated parents, limiting the generalizability of the results. Furthermore, most reports on nutritional risk were made by mothers, which may explain why the researchers found limited associations in the fathers' group. Finally, the research team did not account for multiple comparisons. Taken together, the findings from this study should be interpreted with caution, but nevertheless provide new insights and methodologies in the field of feeding research. Results from studies like these help support the development of interventions for families with higher nutrition risk and can help to reduce malnutrition in young children. References - Walton, K.; Haycraft, E.; Jewell, K; Breen, A.; Simpson J.; Haines, J. (2019). The family mealtime observation study (FaMOS): exploring the role of family functioning in the association between mothers' and fathers' food parenting practices and children's nutrition risk. Nutrients, 11, 630-643. - WHO Fact Sheet: Malnutrition --- ## 5 steps to set up the perfect behavioral suite URL: https://noldus.com/blog/setting-up-the-perfect-behavioral-suite Published: 2022-08-18 13:00:00 Description: Noldus is your partner in research, and with versatile tools such as our state-of-the-art video tracking software EthoVision XT, we can help you achieve that next crucial goal in your animal experiment(s). Noldus is your partner in research, and with versatile tools such as our state-of-the-art video tracking software EthoVision XT, we can help you achieve that next crucial goal in your animal experiment(s). 5 steps to set up the perfect behavioral suite The perfect set up is very much achievable, but we need to review a few topics before we get there. When you are setting up a new behavioral suite, there are many decisions to make that can ultimately impact the quality of your data. Here are a couple of components that you might not have considered: 1. What camera are you going to use to capture videos? When deciding what camera to use, consider if you plan to record live by hooking up the camera to EthoVision XT during the experiment, or if you plan to record the videos first, and run them in a batch through the software. If you are connecting the camera directly to EthoVision XT during the experiment, then you want to make sure it is a camera that EthoVision XT recognizes.  We recommend the Basler GigE Camera, as it has been extensively tested by our technical team and achieves the optimal framerate. USB 3 cameras might work as well, but often provide a less stable framerate. With EthoVision XT, you can output your videos up to 1920x1200 resolution (1280x960 with deep learning). If you are batch processing videos that were pre-recorded, then you want to ensure they are in an appropriate file format. Files like MPEG-4, H.264 AVC, and DV-AVI work well with EthoVision XT. If you are unsure if your file format is compatible, reach out to your Scientific Consultant and they can assist! LABEL Title Learn more 2. What computer are you going to run the software on? For acquisition (getting the x,y coordinates of the subject) EthoVision XT processes 30-60 frames per second, for up to three body points. To process this data in real time, EthoVision XT will need a high-powered workstation. We recommend a Dell Precision Workstation, with an NVIDIA standalone graphics card that is at least 2GB, GDDR5. The exact model we recommend changes frequently, so make sure to talk to your Scientific Consultant to find out the latest card we recommend.  If you are analyzing data after acquisition, or batch processing videos after the fact, you might be able to use a slightly less powerful computer. If you plan to do so, check in with your Scientific Consultant to make sure your computer will be sufficient. Important! As we have been advancing our technology, so does the requirement for more powerful hardware. Our new deep learning tracking technology makes use of the processing power in the graphics card (GPU). To be more specific, deep learning relies on the CUDA computing platform, meaning the GPU must support CUDA version 10. Please reach out to your Scientific Consultant so they can assist with making the right choice! 3. Do you want to integrate EthoVision XT with any external equipment? Did you know EthoVision XT can control external equipment (like optogenetics, fiber photometry, fear conditioning box, and more)? Within the EthoVision XT software, you can instruct a timed start/stop pulse to be sent to other equipment. This ensures that your behavioral data is aligned with any external sources.  EthoVision XT also notates when the pulses are sent, so you can analyze behavioral data pre, post, and mid pulse! If you want to do this, you will need a Noldus I/O box, the EthoVision XT Trial and Hardware Control Module (THCM), and the appropriate cables. Discover how to build your EthoVision solution here >> LABEL Title Learn more 4. Mazes Looking for a specific maze for rodents and/or zebrafish? Noldus also offers these! Your Scientific Consultant will typically ask if you need any mazes for your behavioral suite. Our partner, Maze Engineers (aka Conduct Science), has a vast array of mazes which, in North America, can all be purchased through Noldus (at the same price). Are you a researcher in Europe? Please ask your sales engineer about our maze solutions. Make sure to get a maze that is a contrasting color to the subject you have! If you plan to have a variety of colored subjects, you can also get a light blue or light gray maze. 5. On-site Installation and Training Setting up your behavior suite can be a daunting process, but Noldus is happy to help. We offer on-site installation and training; our trainers will come to your lab, setup your equipment (computer, camera, mazes, software), and will provide a training on how to use the software.  These trainings will be specific to what assays you plan to run, and we are more than happy to walk you through making a template experiment, analyzing your data, and generating visualizations.  LABEL Title Learn more Has this list of things to consider before buying generated even MORE questions? Or has it sparked your curiosity? Feel free to get in touch with your personal Noldus Scientific Consultant. They are here to help you navigate the process.  Once you submit a web request, someone from your Noldus team will email you to schedule a phone call or meeting. If you are able to chat, this is often the easiest way to customize your behavioral setup, but we can also talk via email. Just let us know which option works better for you.  We will ask you many of the questions above, and a few more! This helps us ensure we provide you with a complete solution that will get your behavioral suite up and running quickly. Thinking of setting up a behavioral core lab?  Our behavioral expert, Dr. Jason Rogers, has written a clear guide that takes you through a step-by-step proces of setting up your own behavioral lab.  FREE GUIDE: How to build a rodent neurobehavioral core This guidebook is designed for researchers and administrators who are considering building a rodent behavioral core. - Guidance, information, and tips - Three benefits of building a behavioral core - Planning, setting up and maintaining  Download Don’t need a complete setup? No problem! We can help you determine if your current equipment is useable with EthoVision XT, or what might need to be updated. We strive to come up with the best plan of action to provide you with a setup that meets both your research and budget needs. To talk to your regional Scientific Consultant/Sales Engineer, click here: https://www.noldus.com/form/request-information --- ## A story told: using an AV lab to teach skills for counseling psychology URL: https://noldus.com/blog/viso-lab-train-students-become-professional-counselors Published: 2022-08-17 09:17:00 Description: Creating a great clinical space to train students was what Dr. Audrey Ervin, psychologist and teacher at Delaware Valley University, wanted to achieve. Read the story about how she handled this. Do you remember why you wanted to become a teacher? Probably because you thought it is cool to be able to teach other people something. That you can transfer your knowledge to someone else. You probably already saw yourself standing in front of a class with students that are eager to hear what you have to say. You may have already imagined how grateful the students are for all the new and useful information you can provide them with. After all, you know it is your job and responsibility as a teacher that students get to learn more about their chosen specialty, the profession itself, and the skills needed for their future job. Figuring out the best way of teaching Ideally, you want the students to be satisfied with what they can learn from you. However, maybe this idea actually frightens you. Because how on earth do you do that?  How do you match everyone's level in a classroom with those entirely different students? Will you be able to cover everything they have to learn in the limited time that is available? Moreover, how do you ensure that they can learn not only from you but also from each other and even from themselves? How can you make sure the students become the professional they want to be? Especially when they want to become a psychology counselor. Because this means they have to deal with vulnerable children and adults a lot during their career. They have to stand firm for this. Creating a great clinical space to train students It comes down to making choices. Always a difficult step: considering all kinds of options, such as learning methods and tools that are available for this and eventually choose one. Together with the counseling psychology team at Delaware Valley University, Dr. Audrey Ervin, psychologist and teacher, wanted to develop a great clinical space where they could train their students in counseling techniques. She went looking for the most suitable tool that met her wishes: - Students learn counseling skills by doing - Students develop confidence - Mock counseling sessions are carried out in multiple rooms simultaneously - Teachers give students real-time feedback - The tool is very easy to use - Stand out as a university with a special and fully equipped training space Immediate feedback of utmost importance In her search, she discovered that there were quite a few practical problems to solve. Which tool was able to record practice sessions in multiple rooms at once? Because otherwise it would take ages before all students have had their turn.  And when sessions would take place simultaneously, it would be super handy if cameras can be controlled easily from a distance. For example, being able to turn them on all at the same time. Besides, the system should be able to play back the recorded sessions fast, allowing immediate feedback. This is of utmost importance to increase the learning effect. FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly Viso lab as the cornerstone of the program The team took an outdated laboratory facility and turned it into a multi-room, fully equipped training space for students as they train to become professional counselors. The faculty at Delaware Valley University has proven their dedication to using Viso software to train new counselors.  Skill-based courses are highly interactive and held in the lab, where students role-play, practice, and learn through hands-on experience. Practice sessions are observed, recorded, and reviewed to provide authentic feedback and growth opportunities. The lab is a cornerstone of the program. Throughout putting the lab into operation, installing Viso, and getting everything in place, the team got full support of Noldus. They had a great experience: when they had questions or concerns, Noldus got back to them right away and solved it. BUYER'S GUIDE: Choose the perfect audiovisual lab Learn exactly what you need to consider for your AV lab. - Best options for your AV lab - Practical considerations & tips - Get the most out of your setup Submit to download arrow_forward --- ## True or false? 10 statements about gait research in rodents URL: https://noldus.com/blog/true-or-false-10-statements-gait-analysis Published: 2022-08-11 17:00:00 Description: There are many ‘facts’ going around about rodent gait research tests and systems. How well they work, drawbacks, what they can and cannot measure. In this article, we get some of the facts straight. There are many ‘facts’ going around about rodent gait research tests and systems. How well they work, drawbacks, what they can and cannot measure. Jason Rogers is an expert in this field, and in this article, he helped me get the facts straight, so you can, too.   Measuring gait in rodents is important True. Of course it is! (You knew that.) Locomotion is a major behavioral endpoint that has important applications in many fields of research. Changes to locomotor behavior, measured by the rat’s or mouse’s gait, can be affected due to age, genetic variation, or from changes within the central nervous system, peripheral nervous system, or from the muscles or bones themselves. LABEL Title Learn more Measuring gait should be done with ink and paper False. Observational scoring is traditionally done with ink and paper or the BBB method (Basso, Beattie, and Bresnahan invented this scale for open field locomotion). And of course, we all know the running wheels. But research has evolved and automated methods offer an objective and effective way to gather an abundance of parameters. Abundance of gait parameters That is actually one of the major advantages of automated systems: the volume of data produced. Most commercially available systems provide over fifty parameters, such as stand time, swing time, swing speed, base of support, print length, width, & area, inter-limb coordination (phase dispersion), regularity index, and cadence, for example. This is important, because a rodent’s gait is a complex process and it is important to offer many parameters to accurately describe the locomotor patterns displayed. RESOURCES: Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! Learn more Manual methods are cost-effective True. They can be. Ink and paper are cheap. With this classical test from the late nineties you just ink up the paws with some India ink and let the animals run over a piece of paper. But it’s messy, you have to measure everything manually, and you cannot use temporal parameters. Making sense of this data can be a challenge. Automated systems are difficult to master True and false. It depends on the system. Literature reports that treadmill systems (such as TreadScan) can be quite difficult to master, meaning novice users have a more difficult user experience. It is also more difficult to maintain uniform lighting and to keep clean. Literature also reports that about 45% of the data could be reproduced. Free-walking systems such as CatWalk XT work differently. Our CatWalk XT system is turn-key and experience with our customers says it is easy to learn, use, and keep clean. LABEL Title Learn more You need to set the speed for good data False. The assumption here is that you need to have all animals walk the exact same speed to be able to compare data. We respectfully disagree. There are basically two types of systems: free-walking or treadmill-based. The main advantage of free-walking systems like CatWalk XT is that the animal is allowed to move at a speed that its gait or endurance will allow. If you force a certain speed, you might miss an important gait phenotype. Forcing a speed might also cause the animal to move up and down the treadmill, jump, or limp in order to keep up, possibly introducing gait artefacts. Adjusting for speed The CatWalk XT software does allow you to adjust for speed and speed variation. It also has a setting that requires the animal to maintain a consistent speed in order for that run to be compliant. This means that the animal cannot go slow and then speed up and then slow and then speed up. It has to be consistent throughout each run. Additionally, the design of the walkway is such that the animal is motivated to walk in a straight consistent line. Read more about this in this blog post. LABEL Title Learn more Free-walking systems struggle with paw-dragging False. At least for the CatWalk XT method. As long as the animal makes contact with the walkway, you are going to generate data. Dragging a paw means you have nothing but stand data (no swing), but you will have data nonetheless. In addition, you will have data for the other three paws compensating for the damaged limb. One drawback manufactured by other systems is in the speed of the animal. While treadmill systems claim that maintaining consistent speed is their primary advantage, that’s not always the case.   Did you know Jason Rogers recently presented a webinar with these and many other comparisons between different kind of gait analysis systems? If you are interested in finding out what the differences are, and what would suit your research, this might really help! You can watch the on-demand replay of the webinar here. The CatWalk XT method measures foot pressure False. It is important to note that CatWalk XT measures intensity of light and not pressure. The light intensity is measured on grey scale values. The Detection Settings within the software calibrate the green and red light voltages to ensure equal paw intensity throughout the experiment. LABEL Title Learn more Illuminated Footprint technology The Illuminated Footprint technology works like this: Green LED light is internally reflected inside the glass walkway. The contact of a paw on the glass surface allows light to escape because the paws have a higher reflective index than the glass. The paw reflects the light towards the camera underneath the glass plate. CatWalk XT automatically detects the green light ‘blobs’ (paws) in the video. The Automatic Footprint Classification Module assigns the blogs as paws (right front, left hind, etc.) based on the direction of movement and the type of rodent (rat vs mouse). The surface area and XY position is calculated 100 times per second. The animal’s body contour is created by the red-illuminated ceiling. From there, CatWalk XT automatically creates relational footprint information, such as stride length, base of support, and print positions, along with temporal footprint information, such as cadence, step sequence, regularity index, phase dispersions, stand, swing, max contact, etc.  LABEL Title Learn more All those gait parameters are overwhelming! True. For some. But we have each parameter described in full in the manual. In many cases, the exact formula is shown along with a publication to support it. CatWalk XT parameters CatWalk XT provides data on the individual paws, the single runs, and overall trials. The software allows you to choose the parameters most relevant for your research. All of these parameters are calculated per paw, as well as the front and back paws: initial stand time, stand time, stand index, max contact (time, area, intensity), X & Y position, print length, print width, print area, mean intensity, swing speed, stride length, step cycle, duty cycle, phase dispersions, base of support, cadence, step sequence, percent time standing on a single paw, two paws (diagonal, girdle, or lateral), three paws, and four paws. If you have the Interactive Footprint Classification Module, you get the Sciatic Functional Index, Peroneal Functional Index, Posterior Tibial Functional Index, toe spread, intermediate toe spread, and paw angle. I’m sure I missed a few more. LABEL Title Learn more Automated systems offer great visualizations True. At least CatWalk XT does! First you have the run video itself. This provides a replay of the animal’s run with the classified footprints at an adjustable speed. In addition, three separate visualizations show the paw and run information in a two or three dimensional plane. These visualizations may be exported as image files or along with the run video itself into a separate *.avi file. These are perfect for lab meetings, presentations, and defenses! CatWalk XT is the most cited system True. (Yay!) With over 2,400 publications using CatWalk XT, it has six times more than any other gait system available. Interested to learn more? News-medical.net posted an interview with Jason Rogers, or watch the on-demand webinar on treadmills and free-walking systems for gait analysis.  --- ## 5 tips on how to measure facial expressions URL: https://noldus.com/blog/how-to-measure-facial-expressions Published: 2022-08-09 12:00:00 Description: It may sound very simple, but recording video and playing it back enables more detailed analysis of facial expressions. 5 useful tips on how to measure facial expressions! Facial expressions are an important form of non-verbal communication, used by humans and some animals. They convey personal emotions and are often analyzed by researchers who study human behavior. But how to measure facial expressions? We share 5 tips! What are facial expressions? First of all, you might wonder what facial expressions are. They are a non-verbal behavior, created by muscle movements beneath the skin of the face. For researchers that study human behavior, emotions can provide crucial insights into why people do what they do. Facial expressions can be measured and analyzed in several ways. One way is to observe a person and manually code any facial expressions. Another way is by automated facial expression analysis, using a scientific software tool like FaceReader. FaceReader cannot be used for identifying people, but it can recognize facial characteristics and expressions, and classify facial movements like head orientation, or whether a person has their eyes open or closed. 5 tips on how to measure facial expressions Are you working with a tool like FaceReader and do you want to know how to measure facial expressions? We share 5 useful tips for the automated measuring of facial expressions. 1. Make video recordings It may sound very simple, but recording video and playing it back enables more detailed analysis of facial expressions. When only annotating events and facial expressions live without recording it on video, it is likely the annotator may miss essential information. When making video recordings, it can still be difficult to record the face. For example, Forestell and Mennella recorded infants as their mothers fed them green beans in order to objectively quantify infants' facial expressions by manually coding Action Units. In this study 16 mother-infant dyads had to be excluded because the infant's face was partially or fully occluded during the feeding session. Fortunately, the researchers had a final sample of 92 dyads, which was sufficient to finish their study. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Download Investigating facial expressions in autism and borderline personality disorder Video recordings of the reactive facial expressions of participants have also been used with people with autism spectrum disorder (ASD) or borderline personality disorder (BPD). In a study of De Meulemeester et al. (2021), the capacity for transparency estimation in individuals high and low in BPD features was investigated by presenting a series of emotion-eliciting movie clips to the participants, while filming their reactive facial expressions. After each clip, participants estimated how transparent their emotional experience was while watching the particular clip. In addition, the observable transparency (i.e. how observable their mental states in fact are to others) of the participants' emotional experience was defined as the actual intensity of their facial emotional expressions, measured via FaceReader software. 2. Use a stationary microphone and chair Platt et al. gave a great tip on how to keep a participant from moving/ shaking/ turning his or her head. They placed a voice-recording instrument in front of the participant and asked the participant to speak in the direction of the device. The researchers explained that this limited the participant from turning to face the interviewer. He/she only turned to the interviewer to exchange information and these parts were irrelevant for the study and therefore later excluded. Furthermore, one can easily imagine what happens when a participant sits on an office chair. Therefore, Platt et al. fixed the chair and table so that no turning was possible. In short, this study was aimed at identifying whether individuals with a fear of being laughed at (gelotophobia) respond with less facially displayed joy (Duchenne display) generally towards enjoyable emotions or only those eliciting laughter. FREE WHITE PAPER How to build an AV lab Do you want to learn more how to set up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download 3. Ensure good illumination of the participant's face Whether working in a laboratory or on-site, adequate illumination is of great importance. This is especially true when using software such as FaceReader to recognize facial expressions because good lighting can increase the reliability of your results. For example, Danner et al. used FaceReader software to automatically analyze facial expressions of participants drinking fruit juice. Their set up provided sufficiently accurate data to detect significant differences in facial expressions elicited by different orange juice samples. A set up can be optimized by using photo lamps. This results in diffused frontal lighting on the test participant. Strong reflections or shadows (for example caused by lights from the ceiling) should be avoided. Read this article for more tips to optimize your facial expression analyses 4. Choose a lower frame rate for analysis When using the software to analyze videos, make sure to select a frame rate that suits your research needs. A lower frame rate will allow for a faster analysis while still providing the results you need. Gorbunov used FaceReader software to analyze every third frame of the video. They explain that they chose this frame rate in order to reduce the computational time needed for the generation of the data describing facial expressions in a quantitative way, and the computational time required for the analysis of these data. In this particular case facial expressions were measured in the Mars-500 isolation experiment. In his dissertation, Gorbunov explains that the chosen frame rate still enabled them to get smooth dependencies describing the facial expressions. 5. Record context Now you know how to measure facial expressions, it is important to look at the context of behavior. You can choose to include more measurements in your study, such as eye tracking, physiological measurements, and screen capture technology. Answer for example this question: at what user interface is the test participant looking or which events occurred in the room while the facial expressions recognized as 'happy' were recorded? Taking the context into account can complement the strengths of facial expression analysis by revealing the environmental cues and context that shape facial expressions and emotions. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - Danner, L.; Sidorkina, L.; Joechl, M.; Duerrschmid, K. (2013) Make a face! Implicit and explicit measurement of facial expressions elicited by orange juices using face reading technology. Food Quality and Preference, 32, 167-172. doi:10.1016/j.foodqual.2013.01.004 - De Meulemeester, C., Lowyck, B., Boets, B., Van der Donck, S. & Luyten, P. (2021). Do my emotions show or not? Problems with transparency estimation in women with borderline personality disorder features. Personality Disorders: Theory, Research, and Treatment, 13(3), 288-299. doi.org/10.1037/per0000504. - Forestell, C.A.; Mennella, J.A. (2012). More than just a pretty face. The relationship between infant's temperament, food acceptance, and mothers' perceptions of their enjoyment of food. Appetite, 58, 1136-1142. - Gorbunov, R. (2013). Monitoring emotions and cooperative behavior. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: prof.dr. G.W.M. Rauterberg, dr.ir. E.I. Barakova & dr. K.P. Tuyls). - Platt, T.; Hofmann, J.; Ruch, W.; Proyer, R.T. (2013). Duchenne display responses towards sixteen enjoyable emotions: Individual differences between no and fear of being laughed at. Motivation and Emotion, 37, 776-786. doi.org/10.1007/s11031-013-9342-9. --- ## How horse riding and gardening improve quality of life for people with dementia URL: https://noldus.com/blog/horse-riding-and-gardening-increase-quality-of-life-in-dementia Published: 2022-08-04 14:00:00 Description: Quality of life is an important aspect of dementia care. Horse riding and gardening may provide positive emotional experiences and even enhance daily functioning. Today’s post is a little personal to me. My mom has a rare type of early-onset dementia. A type that does not allow her to communicate verbally anymore, and even from her behavior it’s hard to tell what she wants, likes, and needs. I feel like she has a good quality of life, but how can I really know?   A couple of weeks ago, a pony visited her care facility. She seemed to love it, as she was smiling and laughing, actively walking the pony around the garden, petting it as they went. Her behavior indicated to me, this was an enrichment to her day. As a horse-owner myself, I have seen and experienced how interacting with horses has a very beneficial effects on our wellbeing. A recent publication by Rebecca Lassell and her colleagues from Colorado State University underlines this. What is quality of life? Quality of life is an important aspect of dementia care, but it has many definitions and can be difficult to assess. Lassell used behavioral observations to mark indicators of quality of life during meaningful activities such as gardening and horsemanship adapted for people living with dementia. Activities like these provide positive emotional experiences to people with dementia. Maybe even more importantly: participation in relatively complex activities such as horse riding can enhance functioning and prevent loss of capacities.   Emotional well-being from gardening and horse riding In Lassell’s study, a group of people with differing types of dementia and a broad range of physical and cognitive needs participated in self-elected activities of gardening or horsemanship on a weekly basis. These sessions were caught on camera, and videos were used for a descriptive study. All this was done to answer two questions: “To what extent do people with dementia participate and evidence emotional well-being during adaptive gardening and adaptive riding?” “Are observed durations of participation and emotional well-being similar and different across these interventions?” Descriptive study of quality of life A descriptive study like this means a lot of behavioral observations. These take time, but it does yield rich data. By carefully investigating and describing how the participants reacted and participated during the gardening or horsemanship activities, researchers were able to get a good indication of how the interventions compare to each other and if there is evidence of emotional well-being during the activities. How to deal with intensive behavioral observations Getting the right data out of elaborate behavioral observations such as these can be a challenge. There are a couple of things the researchers did really well to make sure their data would make sense and the work was done efficiently. - They created a solid and uncluttered coding scheme. They really thought this through; this coding scheme was adapted from a system they had created, used, and adapted over the years. This provided a great fundament for their study. - By using The Observer XT was used to set up the coding scheme according to occupational opportunities, participation, and apparent affect. Then two researchers coded the 31 hours of video with a continuous time sampling method and performed an inter-reliability check which resulted in a kappa of 0.85. This high rate assures the researchers coded in a similar method and that data is reliable. Positive emotions All participants seemed to enjoy their activities, especially grooming and petting their horse. No sadness or anger were observed and both activities supported positive quality of life indicators, with a lot of interested gazing and active participation. It also seemed that horse riding offered more opportunities for complex activities, such as riding and petting at the same time, or riding while playing a bean bag tossing game. Retained capacities Interactions with horses required a higher level of active complex participation. Participants seemed to be motivated by the dynamic nature of horse-human interactions and able to tap into their retained capacities, according to the researchers. So while both activities seemed to support quality of life and provide emotional enrichment, especially interactions with the horses provided opportunities to utilize a person’s retained capacities. Like the researchers concluded, this merits further scientific development for such interventions. References Lassell, R.; Wood, W.; Schmid, A.A.; Cross, J.E. (2021). A comparison of quality of life indicators during two complementary interventions: adaptive gardening and adaptive riding for people with dementia. Complementary Therapies in Medicine 57(03), 102658. Wood, W. (2005). Toward developing new occupational science measures: an example from dementia care research. Journal of Occupational Science, 12(3). --- ## The circle is complete: Mites, trichomes, walking speed and EthoVision XT URL: https://noldus.com/blog/mites-trichomes-walking-speed-ethovision Published: 2022-08-02 14:00:00 Description: In my previous life as Entomologist, I was a pioneer in video tracking with extremely small creatures. I worked with mites, which are about 0.5 mm in size. In fact, I was an overall pioneer in video tracking. In my previous life as Entomologist, in the ‘90s of the previous century, I was a pioneer in video tracking with extremely small creatures. I worked with mites, which are about 0.5 mm in size. In fact, I was an overall pioneer in video tracking, I worked with one of the first versions of EthoVision.  The application was running on DOS, which was a challenge in itself. But, that challenge was negligible compared to detecting the tiny mites on leaf discs that had all sorts of shadows and reflections from plant nerves and trichomes. However, somehow I managed, and one of my first publications was on the effect of trichomes on the walking speed of predatory mites, in relation to host plant resistance to spider mites, their prey. [1] The same topic, 25 years later Now, 25 years later, after having been a Noldus employee for almost 13 years, I am writing a blog on the research by Patrice Jacob Savi and his colleagues about trichomes, host plant resistance, walking speed, mites, and EthoVision XT [2]. This makes my circle complete.  Patrice Jacob Savi showed that the walking speed and mobility of the red tomato spider mite drastically goes down on tomato genotypes with a high density of glandular trichomes. Also, these genotypes are highly resistant to the spider mites. This is very promising for plant breeding for resistance to the red tomato spider mite, which is serious pest species on tomato. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more How life has become easier So has nothing changed over the past 25 years? On the contrary, life of an Entomologist has become so much easier with EthoVision XT. Firstly, the application now has much better methods to distinguish the animal from the background. So the struggle that I had to detect the mites is solved.  Secondly, the camera quality has increased dramatically. This means that you can record a much larger surface area, which gives the possibility to scale up your research. It is now possible to run 300 video tracking trials with insects simultaneously. Check out how that works here: https://www.noldus.com/entolab References - Krips, O., Kleijn, P., Willems, P. et al. Leaf hairs influence searching efficiency and predation rate of the predatory mite Phytoseiulus persimilis (Acari: Phytoseiidae). Exp Appl Acarol23, 119–131 (1999). https://doi.org/10.1023/A:1006098410165 - Savi, P.J., de Moraes, G.J., Carvalho, R.F. et al. Bottom-up effects of breeding tomato genotypes on behavioural responses and performance of Tetranychus evansi population. J Pest Sci95, 1287–1301 (2022). https://doi.org/10.1007/s10340-021-01437-5 --- ## Guest blog: Having a look at operant behavior URL: https://noldus.com/blog/having-a-look-at-operant-behavior Published: 2022-07-28 12:00:00 Description: Scientists from Idorsia Pharmaceuticals in Switzerland provide an expert view on operant behavior, and how we can improve our understanding of this complex behavior with the help of video tracking. Giorgio Bergamini and Sean Durkin are highly skilled scientists from Idorsia Pharmaceuticals in Switzerland specializing in (pre)clinical behavioral paradigms in rodents. In this blog they provide an expert view on operant behavior, and how we can improve our understanding of this complex behavior with the help of video tracking.  Having a look at operant behavior: the benefits of video tracking What is operant behavior? And how do you test it? Operant testing has been widely used to study emotional and cognitive functions in laboratory animals. It is based on the concept of operant conditioning in which an animal’s behavior is maintained through the scheduled delivery of reinforcers (e.g., food rewards) according to a specific rule (reinforcement schedule). A typical example of operant test is the five-choice serial-reaction time task (5CSRTT), which has been extensively used to study attention and impulse control. In the 5CSRTT, animals are presented with 5 apertures, and for each trial an operant cue (i.e., light stimulus) is presented into one of the apertures; nose-poking into the illuminated aperture leads to delivery of a food reward. What are some advantages of operant testing? Operant tests offer several advantages over other tests that assess spontaneous animal behavior under defined conditions. Specifically, operant techniques provide excellent experimental control over the behavior shown by the trained animals such that it remains stable over the course of the experiment. As a consequence, the behavioral actions also become very reproducible across different experiments, and this is a feature that is especially desirable for longitudinal testing and comparison of psychoactive drug candidates. Disadvantages of standard operant conditioning protocols Classically, assessment of animals’ behavior is achieved using infrared beam-break sensors installed in the operant chamber: for example, sensors may provide time stamps for emitted response (e.g., nose-poking to the apertures) and for collection of rewards (e.g., from the food magazine). However, depending on the task, an interpretation of the results solely based on the sensors output may limit our understanding of animals’ behavior and its significance. Indeed, animals are normally allowed to freely move inside the operant boxes, and their position relative to the operant cue can heavily impact their performance. This aspect is fundamentally different from neuropsychological testing conditioning in humans, which are usually instructed to constantly look where stimuli are presented. For example, Turner et al. (2016) assessed the impact of the rats’ position during an attentional task and its impact on interpretation of the results: omitted trials (i.e., trials without an operant response) were frequently associated with the rats being far and not looking towards the cues (i.e., illuminated apertures) [1]. Therefore, an omitted trial might be considered as indicative of reduced vigilance, while the response omission actually depends on the fact that the cue was not within the animal’s visual field. Expanding our understanding of operant behavior with video tracking One method to improve our understanding and interpretation of operant behavior is to add video tracking to the classical sensor-based readouts. Different experimental approaches are possible: - Videos might be recorded in synchrony with the sensors-based outputs to perform an off-line tracking of animal’s position to exclude from the analysis selected trials depending on the animals’ position: for example, Clemensson et al. (2020) used video recording during the 5CSRTT to differentiate omitted trials when the rat failed to notice the operant light cue, from those in which the rat was showing reduced interest or vigilance towards the cue [2]. Alternatively, off-line tracking could also be used to better understand animals’ behavior during the different training and testing phases: for example, Mazziotti et al. (2020) showed that over the course of operant training the distance travelled during a single session reduces while velocity does not, suggesting that the reduction in reaction time depends on the optimization of the motor sequence to realize the operant task [3]. In addition, by detecting frequently visited areas in the operant arena during the test, they identify possible stereotyped strategies used by the mice to execute the task. Iversen et al. (2002) also used off-line video tracking to assess behavioral strategies during the different phases of operant task execution: during a continuous reinforcement schedule rats show a stereotyped operant response topography, while during extinction session rats show a variable response topography [4]. - A different approach consists in using closed-loop experimental setups (e.g., Werkhoven et al., 2019), where animal’s position is tracked in real-time and this information is used to command the operant apparatus (e.g., by triggering a trial only when the animal’s head has a specific angle relative to the chamber wall where the operant stimuli are positioned) [5]. For example, Schweihoff et al. (2021) developed the DeepLabStream tool which allow to track in real-time the position and the head direction of the animal, so that the visual cue is only presented to animals which are facing the screen where the stimulus would be displayed [6]. Integrating operant conditioning with video tracking Considering all factors named in this blog, integrating classical operant protocols with information derived from video tracking (either off-line or in real-time) improves our understanding of animals’ behavior during the execution of the operant tasks (Kuroda et al., 2018) and increases the resemblance of the testing conditions between rodents and humans [7].   “Ethovision is a very versatile tool, which we used for several different experimental set-ups. With its easy-to-use analysis work menu with the different tabs it allowed us to perform our analysis in a reproducible manner”  Giorgio Bergamini| Idorsia Pharmaceuticals, Switzerland   The power of EthoVision XT EthoVision XT is a powerful and versatile video tool software that can be used for this automation of operant conditioning tasks. Within EthoVision XT, certain behaviors can be detected, that can then trigger a signal to turn certain stimuli on or off. For example when an animal enters specific area of its cage, which is combined with a reward. From detection, to controlling the food dispenser, is all done by EthoVision XT. Also other external equipment can be controlled with the Trial & Hardware Control Module. This saves precious time, effort and money, while increasing the reliability and validity of your research. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial References - Turner, Karly M.; Peak, James; Burne, Thomas H. J. (2016). Measuring Attention in Rodents: Comparison of a Modified Signal Detection Task and the 5-Choice Serial Reaction Time Task. Front. Behav. Neurosci., 9 - Clemensson, Erik K. H.; Abbaszadeh, Morteza; Fanni, Silvia; Espa, Elena; Angela Cenci, M. (2020). Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut. J. Vis. Exp., 2020 (160), 1–30 - Mazziotti, Raffaele; Sagona, Giulia; Lupori, Leonardo; Martini, Virginia; Pizzorusso, Tommaso (2020). 3D Printable Device for Automated Operant Conditioning in the Mouse. eNeuro, 7 (2) - Iversen, Iver H. (2002). Response-initiated imaging of operant behavior using a digital camera.. J. Exp. Anal. Behav., 77 (3), 283 - Werkhoven, Zach; Rohrsen, Christian; Qin, Chuan; Brembs, Björn; de Bivort, Benjamin (2019). MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology. PLoS One, 14 (11) - Schweihoff, Jens F.; Loshakov, Matvey; Pavlova, Irina; Kück, Laura; Ewell, Laura A.; Schwarz, Martin K. (2021). DeepLabStream enables closed-loop behavioral experiments using deep learning-based markerless, real-time posture detection. Commun. Biol. 2021 41, 4 (1), 1–11 - Kuroda, Toshikazu (2018). A system for the real-time tracking of operant behavior as an application of 3D camera. J. Exp. Anal. Behav., 110 (3), 522–544 --- ## Must-see TED Talks on emotions URL: https://noldus.com/blog/ted-talks-on-emotions Published: 2022-07-26 15:00:00 Description: Emotions are fundamental in understanding human behavior. Do you want to get a better understanding of emotions? We’ve put together a list of must-see TED Talks on emotions. We have written our fair share of blog posts about emotions, and what role they play in our daily life. Our face is often the best indicator for our emotional state, as our facial expressions can be observed by others and convey emotions without saying a word.  For researchers, emotions are fundamental in understanding human behavior, as they are a crucial part in non-verbal communication and a rich source of social signals.  6x Must-see TED Talks on emotions Do you want a better understanding of emotions? We have put together a list of must-see TED Talks on emotions. Watch and learn! Are there universal expressions of emotion? Facial expressions are created with the help of muscle movements beneath the skin of the face. Back in the 60’s, the American psychologist Paul Ekman identified several core expressions, that we now identify as universal. These so-called universal expressions are: happiness, sadness, anger, fear, surprise, and disgust. Since then, researchers have proposed additional mental states such as contempt, shame, and disapproval. These kind of mental states - or Custom Expressions - are essential in consumer research for instance, as they provide insights into user responses and buying behavior.  The concept of universal emotions But do these expressions look the same and communicate the same meaning around the world, regardless of country and culture? Is one person's smile another's grimace? Sophie Zadeh investigates the concept of universal emotions in this TED-Ed, the youth and education initiative by TED. Read this: SUKIPANI: The magic word for making a smile Source: TED.com LABEL Title Learn more FREE WHITE PAPER: Facial Action Coding System Download here the FREE white paper 'Facial Action Coding System (FACS)' and learn more about: - Objective results with FACS - Action Units - Examples using facs  Download LABEL Title Learn more Source: TED.com LABEL Title Learn more Source: TED.com LABEL Title Learn more “Emotions and logic do not oppose each other. They complement each other, and they reinforce each other.” Dr. Ilona Stengel|Merck KGaA, Darmstadt, Germany   LABEL Title Learn more Source: TED.com LABEL Title Learn more FREE WHITE PAPER: FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output  Download LABEL Title Learn more Source: TED.com LABEL Title Learn more The hidden power of smiling And last but not least: did you know your smile can be a predictor of how long you’ll live – and that a simple smile has a measurable effect on your overall well-being? Entrepreneur Ron Gutman reviews a number of studies about facial feedback and smiling, and reveals some surprising results.  Check out his TED Talk and learn more about and this evolutionarily contagious behavior. LABEL Title Learn more LABEL Title Learn more MEASURE YOUR EMOTIONS: What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be  Try now --- ## Gender differences in rodent research URL: https://noldus.com/blog/summer-reading-list-rodent-gender-differences Published: 2022-07-21 11:00:00 Description: Gender differences matter in research. Many studies focus on male mice, but female representation is crucial for accurate, inclusive, and impactful science. Gender differences matter in research. Many studies focus on male mice, but female representation is crucial for accurate, inclusive, and impactful science. From love and heartbreak to alcohol and drugs, these thought-provoking articles shed light on the ways we think, feel, and make decisions. Gender differences in behavioral studies Everybody is different, and that is a good thing. We also see specific differences in mice. In character, probably, but today we address gender differences. Males and females are biologically not the same, and that is an important factor to take into account in scientific studies. Most studies are done in male mice. Mostly because it is easier, as the estrous cycle of females often presents cofounding factors. This is slowly but surely changing in the last years. And that is a good thing, because why study heart problems in male mice only, while heart (& vascular) disease is the leading global cause of death for human females? And why study depression in male mice only, while major depression affects more women and symptoms can differ so vastly between men and women?   Biological, physical, and emotional gender differences should not be overlooked when conducting (preclinical) research, as every part of the human – or animal – population should be represented. It’s only fair. And scientifically correct. Male mice go bananas Some differences are discovered by accident, like The Scientist reported last month.  Jeffrey Mogil, a specialist in pain studies at McGill University, was conducting two different studies, and noticed that male mice were acting weird around pregnant mice. Males got stressed out, while other non-pregnant females in the neighbourhood did not. So, he decided to investigate. What he discovered was a form of social signalling behavior, as pregnant and lactating females left urine marks to warn males to stay away from their pups. That smell, coincidentally the same as that of bananas, stresses male mice out. Read the article here Longer heartbreak for females 5% of mammals are monogamous. The California mouse is part of this group, showing exclusive mating behavior. One mate to grow old with, share food, and take care of the kids and the household. But not all love is meant to last, and even California mice show infidelity. Valentino, Roy, and Becker set out to find out what happens after a – somewhat forced – breakup in the lab. Did they find new romance, and was it build to last? Mostly, yes. 85% of the ‘re-pairs’ gave birth to new kids. But it took females a little bit longer to get over their past relationship, it seems, as females took longer to birth a new litter compared to original breeding pairs. Read the full story here Binge drinking in men and women When you think about alcohol misuse, you probably picture someone that drinks a good amount each day. But alcoholism can take several forms, one of which is binge drinking. Instead of a typical alcohol dependence, binge drinkers infrequently consume heavy amounts of alcohol. Recently, researchers from the Colombia University in New York concluded that alcohol consumption and binge-drinking are increasing mostly among women in their 30s and 40s. We know that alcohol use disorders have a comorbidity with depression and anxiety. These disorders might be provoked by the effect alcohol has on the nervous system and metabolism. At the same time, women also seem to suffer more from affective disorders. So, are they more susceptible to binge-drinking and its effects? Cortez, Brocardo, and Leasure investigated these possible differences in male and female rats. They predicted females would be more anxious, show more depression-like symptoms, and have more physical effects such as oxidative stress. But while binge drinking did certainly affect behavior and physiology, no gender differences in effects of alcoholism were found in this study. After three binge-drinking episodes, rats were tested to assess locomotion (open field test), anxiety-like behavior (elevated plus maze test), and depressive-like behavior (forced swim test). They used EthoVision XT video tracking to automatically measure the activity and behavior of the rats during the tests. Check out the full publication for more details on the test. FREE E-BOOK Basic behavioral neuroscience in rodents Want to know more about anxiety testing and other aspects of rodent research? Then, download our free e-book. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Submit to download Gender difference in effects of drug abuse Millions of people suffer from opioid use disorder. In other words: they are addicted to drugs. Fentanyl is a heavy pain killer, but has also gained popularity are as a recreational drug. It is often the cause of overdose and unintentional consumption because of contamination with other drugs. But we don’t know a lot about fentanyl, so Gaulden and his colleagues set out to gain more knowledge, specifically on sex-related differences in responses. And there are differences, at least in rats. For example, exposure to fentanyl enhanced activity in females, but not in males. After repeated exposure, activity was enhanced even more (behavioral sensitization) in females, but not in males. On the other hand, fentanyl produced a significant conditioned place preference (preferring the place paired with the drug) in both sexes, but it was more pronounced in males. The researchers measured the effects of both acute and chronic exposure to fentanyl by assessing activity and behavior in an open field test. Effects of low and high doses of the drugs were tested in a conditioned place preference test. For both tests, EthoVision XT video tracking was used. Check out the paper for more details. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial Men, women, non-binary… we are all equal but not the same. Some of us strongly believe we must come from different planets. Science confirms at least some of the differences we see related to gender. This underlines the importance of research in both male and female subjects. It uncovers a lot of previously unknown differences in biological mechanisms, and inclusiveness is a necessary step in biomedical research. It takes us closer to improving not only our understanding, but also better ways to treat specific diseases and/or disorders better. References - Cortez, I.; Brocardo, P.S.; Leasure, J.L. (2021). Changes in affective behavior and oxidative stress after binge alcohol in male and female rats. Brain Sciences 11, 1250. - Gaulden, A.D.; Burson, N.; Sadik, N.; Ghosh, I.; Khan, S.J.; Brummelte, S.; Kallakuri, S.; Perrine, S.A. (2021). Effects on fentanyl on acute locomotor activity, behavioral sensitization, and contextual reward in female and male rats. Drug and Alcohol Dependence 229, 109101.   --- ## Behind the scenes at MARIN: research into human decision making URL: https://noldus.com/blog/MARIN-human-factor-research Published: 2022-07-20 10:55:00 Description: One of the world's leading maritime research institutes: MARIN, took us on a tour in their ship bridge simulator. A great customer success story that highlights the importance of human factor research. Right in Noldus’ backyard in Wageningen (in the Netherlands) lies MARIN, one of the world’s leading (applied) research institutes in the maritime domain. Their history in the Dutch maritime industry dates back to 1873. And their goal is to contribute to a more sustainable use of the sea with cleaner, smarter and safer maritime structures and operations: better ships, blue oceans. Although they are mainly a commercial player in the maritime industry, their backbone is scientific research. Thus, not surprisingly, MARIN loves to collect data. And with the help of Noldus, they have implemented a human factor research toolkit to collect hard data on the human element of all kinds of maritime operations. What is human factor research? Human factors (and ergonomics) are defined as the use of psychological and physiological principles in the engineering and design of goods, services and systems. The emphasis herein lies on the interaction between the person and the object (or technology) of interest. The primary objective is to decrease human error, boost productivity, and improve safety and comfort. Operating a virtual ship to understand complex decision making Hans Huisman is team leader human factors within MARIN, and in our latest customer success story he gives us a special tour in their largest ship bridge simulator. A ship’s crew can operate a (virtual) ship in this simulator as if it was a normal ship. A range of situations can be introduced to the crew, such as challenging weather conditions or specific navigational tasks.  This is, for one, to best prepare them for all types of scenarios, but equally as important, to monitor, track and score their behavioral response which helps to improve the understanding of the human factor involved in such complex decision-making. Direct debriefing: performance and decision-making Data ranging from eye movements, heart rate and other physiological parameters are recorded (and/or analyzed from a video feed), whereafter a crew can directly be debriefed on their performance. A person can think he/she acted in a proper way in a specific scenario, but are often still surprised if you show them the data afterwards on their performance and decision-making.  “Noldus has a lot of knowledge on human performance, data collection and synchronizing data sources"  Hans Huisman | MARIN, Wageningen, The Netherlands   Multimodal data This synchronization of data is vital in multimodal research. Being able to study time relationships and synchronously play back multiple modalities, such as video, screen captures, location data, behavioral data and various physiological and psychological parameters is difficult, but a necessity.  Noldus will provide MARIN with the tools to overcome these challenges, which they will incorporate in their, currently under development, ‘seven oceans simulation center’. This will be a state-of-the-art center with 7 high tech maritime simulators, which will all include a human factors measurement toolkit. This will also be integrated with virtual reality and augmented reality technology which provides great data visualization and integration. Not only in the sea While the focus of MARIN is in the maritime domain, gathering data on human performance, and its visualization and integration, is also crucial in other, ‘safety critical’ domains. A great example is aviation. But also in the military, where making strategic decisions is an integral part of the job.   Take a look for yourself on MARIN’s website to learn more about their history, current projects and future perspectives and ambitions. Want to take a quick tour first? Check out the customer success story at MARIN’s headquarters here.  Want to know more about human factor research? Or multimodal data integration? Feel free to browse on our website as well.   --- ## Behavioral neuroscience in the circular economy: the contribution of Zebrafish URL: https://noldus.com/blog/behavioral-neuroscience-circular-economy-zebrafish Published: 2022-07-13 10:20:00 Description: What do Zebrafish and sewage sludge have in common? In this blog their use as a screening tool is highlighted to asses the ecotoxicity in soil. The use of zebrafish, in all life stages, is increasing in popularity considering its use as a bioassay. This small, versatile and easy to study fish provides valuable information on (eco)toxicity questions/issues , whether on a behavioral or morphological level.   We highlighted a recent study by Camilla Della Torre et al, that use the zebrafish to study the (eco)toxicity of sewage sludge in soil.  The contribution of Zebrafish in sewage sludge processing: Behavioral neuroscience in the circular economy. To combat soil loss with sustainable practices, sewage sludge (SS) is often used as a soil supplement or substitute to also increase nutrients and soil resilience. There are however concerns about using sewage sludge related to toxicity of certain compounds. Although wastewater treatment processes removes the bulk of the harmful materials, there are still toxic chemicals in sewage sludge that pose a risk to terrestrial and aquatic plant and animal life. To overcome this, and implement circular economy strategies in the implementation of sewage sludge for soil supplementation, an innovative process called hydrothermal carbonisation (HTC) can be used to convert the sewage sludge into hydrochar (HC). Hydrochar is a carbon rich solid with applications in agriculture, soil amendment, and even has substantial environmental benefits due to its ability to absorb CO2. But what about the chemical contaminants that were possibly already present in the sewage sludge? And what does this have to do with Zebrafish?  Bioassays are an interesting and innovate approach to use as a screening tool for assessing ecotoxicity for wastewater and sludge. Most of the investigations surrounding hydrochar considering ecotoxicity however have mostly been done in soil organisms. A recent study by Camilla Della Torre et al aimed at using Zebrafish (Danio Rerio) embryo/larvae in such a bioassay to evaluate the hazards for natural (aquatic) ecosystems associated with sewage sludge and hydrochar exposure [1].            Zebrafish as a model for ecotoxicity The zebrafish embryo/larvae is an excellent model organism in ecotoxicity management. Fast development, small size and transparency make this an easy and scalable model to use in laboratory conditions. Using zebrafish embryo/larvae also contributes to the three Rs (reduction, replacement and refinement) in animal testing methods. Della Torre et al hypothesized that hydrochar induces a lower amount of toxicity compared to sewage sludge. To achieve this, their study first aimed at the suitability of zebrafish embryo contact testing for sewage sludge and hydrochar. This is basically an acute toxicity test used to identify concentrations of chemicals (in this case those present in SS and HC) that cause acute toxicity. A standardised approach herein is the determination of the lethal concentration (50%; LC50). Behavioral assessment using DanioVision To screen for these possibly toxic effects of sewage sludge and hydrochar, a sediment contact assay (SCA) was used. This is a widely adopted assay to screen for hazards that are associated with pollutant-bound sediment. Enzymes related to detoxification, oxidative stress and neurotoxicity were analysed. This was all coupled with an investigation into behavioral alteration using Noldus’ DanioVision™ observation chamber, which is powered by EthoVision XT.  Locomotor behavior was assessed in larvae at 96 hpf in multi-well plates in control, sewage sludge and hydrochar exposure groups. The swimming performances were assessed following a light/dark transition locomotor response test specifically designed for zebrafish larvae. Hydrochar is less toxic than sewage sludge Della Torre et al found with this behavioral assay that larvae exposed to hydrochar reduces the load of some neuroactive molecules that impact swimming performances, compared to exposure to sewage sludge. Swimming activity usually decreases significantly when exposed to (neuro)toxic chemicals. This decline in swimming behavior was greatest in the sewage sludge and in hydrochar exposed groups compared to control, and the effect was higher in sewage sludge with respect to hydrochar. This partial recovery of swimming activity might be related to a “cage-like effect” of hydrochar towards chemicals with neuroactive potential. The importance of behavioral assays and ecotoxicity studies in (zebra)fish The study by Della Torre et al contributes to promoting the zebrafish as a representative biological model of the aquatic system. In terms of practically assessing the environmental risk of sewage sludge and hydrochar, the zebrafish embryo-larval contact assay emerged as a suitable screening tool. Behavioral observations are essential within this framework since this relates to the ecological wellbeing of, in this case, aquatic species. In terms of the observed swimming behavior, which is less impaired in the hydrochar exposed groups compared to the sewage sludge groups, the findings of Della Torre et al are crucial: Impairment of swimming behavior poses a big risk for fish populations in terms of predation and food foraging.   Want to know more about ecotoxicity and fish behavior? Check out this white paper and this application page.  References - Della Torre, Camilla; Liberatori, Giulia; Ghilardi, Anna; Del Giacco, Luca; Puccini, Monica; Ferraro, Fabrizio; Vitolo, Sandra; Corsi, Ilaria (2022). The zebrafish (Danio rerio) embryo-larval contact assay combined with biochemical biomarkers and swimming performance in sewage sludge and hydrochar hazard assessment. Environ. Pollut., 302, 119053               RESOURCES: Read more about DanioVision Find out how DanioVision is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources     --- ## Part 2: How researchers use the Morris water maze to find treatments for AD URL: https://noldus.com/blog/morris-water-maze-alzheimers-2 Published: 2022-07-07 12:00:00 Description: In this second part of a two-part mini series, we highlight two more studies on potential Alzheimer’s disease treatments that are investigated using a Morris water maze. In this second part on Alzheimer’s disease (AD), two more papers are explored. A brief recap: in each of the four papers, both in this blog and the previous one, researchers test the effectiveness of potential AD treatments using the Morris water maze. If you have not yet read the previous part of this blog, you can read it here. The studies in this current blog were conducted by scientists from Rostock in Germany, who tested caloric restriction as a treatment, and from Qiqihar in China, who chose a treatment using probiotics. The potential influence of food on Alzheimer’s is very interesting in my opinion, which is why I chose these papers. The Morris water maze test In each paper, the water maze test was used in order to test mice’s spatial memory (in other words, how good they are at not getting lost!). The exact testing- and training method can be found in the previous blog post. Just like in the other papers, each study used Noldus EthoVision XT. Water maze tests are especially useful in research to cognitive behavior. The videos of their trials were analyzed using the Morris water maze settings in order to collect data more accurately. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more Long-term caloric restriction According to Müller et al. (2021), going on a diet has more benefits than just getting fit. It may even decrease the effects of Alzheimer’s through inducing glial autophagy, which probably has a neuroprotective effect and might positively influence AD. The term “glial autophagy” might sound complicated, the process is relatively easy to explain. Cell parts and misfolded proteins are recycled and degraded, like clearing your desk in order to make room for new processes and projects. The mice in this study were divided into four treatment groups split over control mice and AD model mice, making eight groups in total. The mice were fed either ad libitum, or a caloric-restricted diet (60% of ad libitum), for 68 weeks. Low-calorie diet increases platform crossings All mice subsequently underwent the water maze test, and each test was recorded. Through analyzing these videos with Noldus EthoVision XT, the scientists measured variables like escape latency and the number of platform crossings. The low-calorie diet mice almost doubled their number of platform crossings compared to their fellow mice, both in the AD and the control group. On top of that, the ad libitum control mice crossed the platform location about twice as often compared to the ad libitum AD mice. Eating all you want when you have AD therefore does not seem wise for these mice, if they do not want to lose their way. Limiting caloric intake seems to have a significant positive influence on memory, have an anti-aging effect and results in an improved cognitive performance. LABEL Title Learn more Probiotics Tan et al. (2022) studied the application of probiotics, since recent studies found a strong link between gut microbiota and the brain. (Maybe you could eat yourself clever?) On top of that, other studies show that the intestinal flora of someone with AD is quite different from someone without AD. Proof on the effect of probiotics on AD, however, is still missing. Therefore, Tan et al. fed a probiotic diet, also containing vitamins and fatty acids, to 12 weeks old mice, 5 times a week for 20 weeks. The diet was tested on an Alzheimer’s mouse model and on wild type mice, each with a control group. Probiotics reverse symptoms of AD In the water maze test, the effect of these diets were thoroughly studied using Noldus EthoVision XT, and the resulting data were analyzed. Both the escape latency and the swimming time of the probiotic diet AD mice was significantly shorter than that of AD mice without treatment. Contrary to that, the diet did not influence the cognitive abilities of wild type mice. These results show that the AD mice’s spatial memory had improved, and their learning capabilities as well, and that it is indeed the probiotics that seem to cause this. The damage of AD seems to have been reversed somewhat. Over-the-counter probiotics most likely will not cut it, but this treatment does show promise. Conclusions Both the caloric restriction diet and the probiotics diet are able to significantly improve AD symptoms in mice, in vastly different ways. The former “cleans up” the brain a little through the process of glial autophagy, and the latter influences the brain through the gut. These results show some promise for people suffering from Alzheimer’s disease. Although deceptively simple, but they clearly worked for these mice. These treatments that pass the water maze tests are potentially able to contribute to the health and wellbeing of people with AD. References  Müller, L., Power Guerra, N., Stenzel, J., Rühlmann, C., Lindner, T., Krause, B.J., Vollmar, B., Teipel, S. & Kuhla, A. (2021). Long-term caloric restriction attenuates β-amyloid neuropathology and is accompanied by autophagy in APPswe/PS1delta9 mice. Nutrients, 13(3), 985. Tan, C., Liu, Y., Zhang, H., Di, C., Xu, D., Liang, C., Zhang, N., Han, B. & Lang, W. (2022). Neuroprotective Effects of Probiotic-Supplemented Diet on Cognitive Behavior of 3xTg-AD Mice. Journal of Healthcare Engineering, 2022. --- ## Should you buy EthoVision XT? Reviews from our customers URL: https://noldus.com/blog/should-you-buy-ethovision-xt-an-honest-customer-review Published: 2022-07-05 10:00:00 Description: Are you wondering if EthoVision XT might be the right tool for your study? In this blog we sum up some of our favorite and honest customer reviews about EthoVision XT. Are you wondering if EthoVision XT might be the right tool for your study? Our video tracking software EthoVision XT has been used in a variety of studies and has been published in over 30,000 publications, so there might be a chance it could be of good use for you as well. In this blog we sum up some of our favorite and honest customer reviews about EthoVision XT. EthoVision XT user opinions In a survey we did in 2021, we asked the users of EthoVision XT to rate the advantage in saving time when using EthoVision XT for data acquisition. The options ranged from ‘no advantage at all’ to ‘vital advantage’. The option ‘big advantage’ definitely stood out with 55% of the EthoVision XT users. Even 30% of the users saw a vital advantage with EthoVision XT. Are you interested in building your own rodent neurobehavioral core? Download this free guidebook on how to build a rodent neurobehavioral core and learn more about the why, who, what and how. EthoVision XT helping in research against bipolar disorder In the Judith Homberg lab at the Donders Insitute of Radboud University in Nijmegen, postdoctoral researcher Mina Sadighi Alvandi, is doing research into the neuroscience of bipolar disorder and the mechanism that is associated with this disease. '‘With the help of EthoVision I can record the behavior for six days and in the same time I’m doing online analyzing with the software, but still, we save the videos. It’s very helpful, because then I can assess the behavior of rats for a long time, which is not possible with another behavioral set-up.’’ The video shown below shows Mina’s satisfaction with EthoVision XT, and how it makes her research easy and controllable. LABEL Title Learn more What our users say Another outcome of the survey that we’re very proud of, was that the overall opinion/rating of EthoVision XT is, with 89% of the users who filled in the survey, good to very good! We picked out our favorite review quotes from our users to highlight here for you: “EthoVision has been crucial for high throughput behavioral experiments in our department. We hardly have detection issues, and the software is easy to use.”, - Karienn Souza Montgomery “EthoVision is a great resource for behavioral scientists - the time saved is invaluable!” - Fiona Hollis “EthoVision is the best available tool for tracking cephalopods in behavioral studies, despite being designed for rats and mice! It has improved the speed and accuracy of our analysis workflow hugely, and we recommend it to our colleagues all the time.” - Robyn Crook “EthoVision provides a great platform for running behavioral experiments. It would benefit people who consider all aspects with respect to acquiring quality data. I recommend researchers to avail the edge which EthoVision offers for behavioral neuroscientists.” - Vijayakumar Kapgal “Noldus has been a game-changer in the field of behavioral sciences.” - Stefano Tarantini “Tracking insect behaviors precisely has been a profound desire of insect ecologists which only came true late in 20th century by Noldus group.” - Jalal Shirazi LABEL Title Learn more LABEL Title Learn more REQUEST INFORMATION Are you interested in our behavioral research solutions, and want to get in contact? - Worldwide: Always near to you - Make your project a success - Trust our 30 years of experience  Contact us --- ## How researchers use the Morris water maze to find treatments for Alzheimer's URL: https://noldus.com/blog/morris-water-maze-alzheimers Published: 2022-06-30 12:00:00 Description: In this first part of a two-part mini series, we highlight how potential Alzheimer’s disease treatments are being investigated using a Morris water maze. Alzheimer’s disease (AD) is a prevalent neurodegenerative disease and the most common form of dementia in the USA and western Europe. Therefore, research is being done continuously in order to find potential treatments, and some look quite promising. I would like to highlight four recent studies. Two in this article, and another two in a second post next month. Every study used the Morris water maze (MWM) for testing the effectiveness of their potential treatments. The studies in this blog were conducted by scientists from Shenyang in China, who tested a molecule called SPG302, and from California in the USA, who chose vitamin D as a treatment. I personally think it is impressive that vitamin D might actually help with AD! LABEL Title Learn more Spatial memory and the Morris water maze test All four studies used an AD mouse model. The treatments described below were tested for effectiveness through various paradigms, including the MWM. This test was used to survey the animals’ spatial memory, as a reference for the effectiveness of the treatment. The test itself went swimmingly, and below you will find out how the treatments went. Pools Depending on the study, the mice were trained to locate a platform in a circular pool of 100 - 150 cm diameter. The pools were divided into four quadrants, and the platforms were located in a fixed position inside one of these quadrants, about 1 cm under the surface of the water. The platform was invisible to the mice by making the water opaque, so they had to fully rely on visual cues. Each animal was put inside the pool at a random location, after which it swam until it found the platform (hopefully they all brought their swimming diploma). Once they reached the platform, the mice were taken out after a few seconds. If it took them more than 60 seconds, they were guided to the platform by the researchers and also kept there for several seconds. This is meant to help them memorize the platform location. LABEL Title Learn more Training For several days, the mice were trained in finding the platform, during which their speed at locating it showed the (in)effectiveness of the training (or the mice’s ability to use a GPS device). The AD mice are not expected to learn that fast, unless the treatment turns out to be effective. After the training bouts, the platform was removed and the mice were supposed to locate it from memory. Paying enough attention during the training certainly helped here! Analysis The probe trials were recorded, and the resulting videos were analyzed using Noldus EthoVision XT. For each mouse in the tests many water maze-specific parameters were tested. Examples are escape latency to platform, visits to, and time spent in, the target area, distance traveled in each quadrant, and many more. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more Different kinds of treatments As mentioned before, each study researched a different kind of treatment. Two of these are explained here, and the other two will be in part II of this mini series. Novel molecule In the study of Estrada et al. (2021), mice were treated with a novel spinogenic molecule called SPG302, which is a small molecule with a hard name and impressive power. It is capable of inducing regeneration of synapses, making it a good candidate for a potential AD treatment. Three groups of AD model mice were treated daily with this molecule, for 4 weeks. Each group received either a vehicle, or a light or strong dose of the molecule. As a control, wild type mice received the same treatments. Results The AD mice that received the SPG treatment showed significant improvement in their spatial memory, and their escape latency even came close to that of the wild type mice. The same is true for their frequency and duration of visits to the target area. Since no significant influence on distance traveled and velocity were found, only memory could explain these results. Based on this data, it seems that SPG is capable of reversing memory deficits in the mouse model used in this study. Vitamin D Pan et al. (2021) have tested the effects of vitamin D on AD. Though the mechanism behind it is still unknown, vitamin D is known to improve memory, cognitive functions and learning in AD models (so working on a project in the sun seems like an even better idea now!). In this study, an OKA mouse model was used. In this model, okadaic acid is injected in the mice’s hippocampus in order to mimic AD. Half of the OKA mice and half of the control mice received vitamine D not through sunbathing, but in their drinking water for 3 weeks. The other half served as the control. Results The OKA mice treated with vitamin D had an increased escape latency, meaning they needed less time to find the platform. Their pathway length had also increased, and they had less center place crossings, meaning the mice searched more actively. Both indicate that vitamin D might be capable of decreasing memory difficulties in AD mice. Potential AD treatments Both SPG and vitamin D are able to significantly improve AD symptoms. SPG restores synapses, but the exact effect of vitamin D on AD is still unknown. The advantage of the SPG study is that it provides strong proof of its effectiveness as a future medicine, and on top of that there are no other approved treatments yet that address synapse loss. Vitamin D on the other hand has the advantage that it is already readily available, has known side effects and therefore could potentially be applied safely already to people suffering from AD. References  Pan, Y., Zhang, Y., Liu, N., Lu, W., Yang, J., Li, Y., ... & Kong, J. (2021). Vitamin D Attenuates Alzheimer-like Pathology Induced by Okadaic Acid. ACS Chemical Neuroscience, 12(8), 1343-1350. Trujillo-Estrada, L., Vanderklish, P.W., Nguyen, M.M.T., Kuang, R.R., Nguyen, C., Huynh, E., da Cunha, C., Javonillo, D.I., Forner, S., Martini, A.C. & LaFerla, F. M. (2021). SPG302 Reverses Synaptic and Cognitive Deficits Without Altering Amyloid or Tau Pathology in a Transgenic Model of Alzheimer’s Disease. Neurotherapeutics, 1-16. --- ## WHY use a Y-maze? Automating learning and memory tests in rodents URL: https://noldus.com/blog/y-maze-learning-and-memory-testing Published: 2022-06-17 12:00:00 Description: Y-maze testing is exactly what you would think: a maze with three arms that maze rodents have to navigate on their way to food, shelter, or another reward. It is often used to test spatial learning, but why? You are on a deserted island and you are hungry. As you start to explore the island you decide to go right side of the island and you find trees filled with fruit. You eat some, then return to your shelter for the night. The next day you wake up hungry again. Where do you go? Yeah, right. Because your spatial memory is functioning just fine. In many neurological diseases, spatial memory is affected. Imagine you forgot where to turn right. Or, once you ate all the fruit, you forget to not return there because there is nothing left. Not so beneficial for your survival. This basic principle is the base of the Y-maze test in rodents (and nowadays, also zebrafish). It is a way to study cognition and navigational strategies, something that is of great importance in discovering brain mechanisms and possible treatments for a wide range of disorders. What is a Y-maze?  Like the names suggests, the Y-maze is shaped as a Y, consisting of three arms of the same length positioned at 120 degrees to each other. It is very similar to the well-known T-maze, but of course, a T is not a Y. Like the T-maze, the Y-maze is often used to investigate spatial learning and memory in rodents. With this test, the animal can learn to get a reward by choosing the correct arm of the maze, or show its preference for a certain type of environmental cue, if it recognizes a novel environment, etc. A maze shaped like a Y Unlike the T-maze, the Y-maze has arms are at a more natural, 120-degree angle, making it easier for the animal to focus on the task at hand and making the test easier to learn. A decrease in learning time is an increase in test efficiency. Another added benefit is that the Y-maze is relatively small. Cognition testing with the Y-maze Many neurological impairments present with memory problems. Spatial or working memory can be affected in a large variety of disorders, such as Alzheimer’s disease and dementia, Parkinson’s disease, Attention deficit/hyperactivity disorder (ADHD), schizophrenia, substance abuse, autism, and stress-related disorders. Examples of protocols with a Y-maze The Y-maze offers several protocols to test the capability of drugs or other treatments to improve (or worsen) the cognition of rat or mice models. Let’s highlight some examples of protocol you can use the Y-maze for: Spatial memory testing To test spatial memory, you can simple bait one of the arms with a food reward. After being able to freely explore the maze, the animal will discover the treat and eat it. At a later point in time, you place the animal back in the maze. If it remembered correctly, it will go straight to where it found food last time. Based on spatial cues in the environment, it might even know where to go from a different starting point. To assess how well spatial memory is working, you can measure the amount of time it took the animal to enter the correct arm, and how many wrong entries it makes before that, for example. Recognition memory test A slightly different test without a food reward involves blocking off one of the arms while letting the animal explore the rest of the maze. At a later point in time, the animal is returned to the maze, now fully accessible, and the test is to see whether the animals recognizes there is a “new” arm and spends more time exploring it, similar to the concept of novel object/environment recognition testing. Again, the number of entries into the new arm and the time spent there, compared to the rest of the maze is taken as a measure of memory functioning. Spontaneous or continuous alternation test Animals have a natural tendency to explore. This tendency is exploited in many maze-based tests, think of the plus maze for example, and this is no different for the spontaneous alteration test in the Y-maze. When allowed to explore the Y-maze freely, rats and mice tend to explore each arm instead of only returning to the same one. If they don’t, this can be a sign of a memory deficit in the hippocampus, septum, forebrain, prefrontal cortex or other parts of the brain. During this test the number of times each arm gets visited, in what order, and how much time they spend there can be of importance. Usually, the percentage of spontaneous alternation is defined as the entry into the three different arms in concession, and this is used as a measure of working memory functioning. Rewarded alternation test Instead of letting the animal roam freely, you can bait one of the arms with a food reward. Only this time, we learn the rat or mouse to alternate. In other words, where the food was, it is now gone, so it has to go to another arm. To teach this to the animal, you block off the previously rewarded arm and bait another. Next, both arms are open and only the correct arm is baited. Automating the Y-maze test Arm entries are a really important measure in the Y-maze, and one is only counted with the animal moves all his four feet into that arm. How fast and how often each arm is visited, how much time the animal spends in each arm, the order of arm entries, are all important measures. To greatly improve the efficiency of these tests, video tracking offers a great way to automate these observations. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial EthoVision XT and the Y-maze With EthoVision XT the nose, center, and tail base of rats and mice is automatically detected and tracked. In EthoVision XT 16, deep learning was introduced for a very accurate detection of these body points. This is a very useful feature for tests such as the Y-maze, because only when all body points are detected in a specific arm, this counts as an entry. With the new EthoVision XT, you can now increase throughput of your behavioral test by tracking 4 arenas simultaneously with our advanced deep learning tracking module. The software also measures latencies, durations, and the order of arm visits.  If you are interested in how this works, visit our EthoVision XT pages, contact us, or request a free trial!  --- ## How does communication with strangers develop? URL: https://noldus.com/blog/emotional-communication-infants Published: 2022-06-09 10:55:00 Description: Various factors contribute to shaping social-emotional developmental trajectories, such as familiarity of the interaction partner, the child’s age, but also individual predispositions, such as temperament. As a parent, you offer your child structure, and you give your child a lot of attention and positive affection. As a result, your child becomes attached to you, feels safe with you, and learns that it can rely on you. Your child will increasingly notice the difference between familiar people he knows and trusts and strangers. At first, strangers may trigger some fear because of the novelty and uncertainty. However, despite this fear, eventually your child will engage in social interactions with strangers. How does this develop? Social interaction development Social interaction development concerns the child’s experience, expression, and regulation of emotions, and the ability to interact with others while learning social skills. This leads to social and emotional well-being, which are important conditions for children to function and learn well. Various factors contribute to shaping social interaction developmental trajectories, for example, the familiarity of the interaction partner - as mentioned above, the child’s age, but also individual predispositions, such as temperament, which influences a child’s attention, emotions, and motions. Temperament contributes to the child’s reaction to the novel situation either in an excited, curious way, or in an irritated, stressed out, or sad way. Children displaying high levels of temperamental surgency tend to elicit positive affect from interaction partners, thereby gaining access to a greater amount of social interactions than more introverted children. In children, surgency is an emotional dimension that is characterized by high levels of activity and positive emotion, impulsivity, and engagement with their environment. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly How does communication with strangers develop? In her PhD research, Eliala A. Salvadori wanted to know more about preverbal communication with strangers. Therefore, she designed a longitudinal study with these three goals: - Examining differences in the development of infant visual, facial, and vocal communication patterns between strangers and each parent (mothers and fathers). - Determining how individual differences in the development of infant communication with strangers (vs. mothers and fathers) are modulated by infant levels of temperamental reactivity. - Examining concurrent and longitudinal associations between infant communication with strangers and each parent. A sample of 58 children (25 girls, 33 boys) was included in this study. An innovative aspect of this study was the participation of both mothers and fathers. Also read: 5 examples of infant studies Observing interactions to assess emotional communication At four and eight months of age, each infant was tested via naturalistic observations during home visits. In a random order, two-minute face-to-face interactions took place with the infant’s mother, father and the experimenter, to assess emotional communication. Parents were instructed to interact with their infant as they would normally do. Experimenters were instructed to be visually attentive and expressively positive with the infant. At four months of age, the infant was seated in an infant seat on the table, while at eight months of age the infant was seated in a high chair next to the table. In between the infant and the parent or experimenter was mounted a 360° camera to record the interactions (see figure 1). Figure 1 - Example of the set ups Coding gaze behavior, facial expressions, and vocalizations With The Observer XT software, three components of the interactions were coded using a coding scheme for emotional communication: - Gaze behavior: the direction the infant looked at (communication partner, elsewhere, not visible) | coded as a state event (duration in seconds). - Facial expressions: using the categories positive, negative, neutral, and not visible | coded as a state event (duration in seconds). - Vocalizations: comprehensively (i.e., positive, neutral, and negative vocalizations were aggregated) and separately for positively and negatively valenced vocalizations (i.e., vocalizations combined with a simultaneously occurring positive/negative facial expression) | coded as point events (frequency of occurrence). Figure 2 - Visualization of the data streams in The Observer XT To avoid observer bias, a senior coder randomly selected and double coded 15% of the observations. A high inter-rater reliability was found. To measure infant temperament, both parents filled in a short, Dutch version of the Infant Behavior Questionnaire. Partner-directed gaze behavior The research team found that infants looked longer at strangers (female experimenters) than they did at their fathers during the interactions. Age seemed to have an effect here. The gaze duration was lower at eight months of age than at four months of age. The researchers found no significant difference between infant gaze at mothers and strangers. It is possible that strangers and mothers interacted in a similar way with the infants and that as a result there was no difference in the infants’ gaze behaviors. It is also possible that the infants were very interested in the unfamiliar (female) adult and curiosity caused the infants' visual involvement. Besides, the social interactions took place in the family's home, hence a familiar and safe environment, which may have influenced infants' visual patterns. Negative affectivity was associated with lower levels of gaze, regardless of the identity of the interaction partner. Levels of smiling and vocalizations Interaction with mothers trigged the infant’s more smiles and sounds, as compared to the strangers. There were also more frequent infant vocalizations with fathers than with strangers at eight months, but not at four. So again, age played a role. Temperamental surgency was associated with higher levels of positive affect and vocalizations with strangers and both parents (positive affect was particularly accentuated with mothers). Interaction with strangers In summary, the results of this study showed that infants gaze longer at strangers than at fathers, exhibit less smiling to strangers than to mothers, and produce fewer vocalizations with strangers than with either parent.  Temperament contributes to individual differences in infant communication with strangers and both parents over development: infants higher in surgency expressed more positive affect and vocalizations while infants higher in negative affectivity exhibited less positive affect and visual engagement. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial References Salvadori, E.A.; Colonnesi, C.; Elsammak, L.; Oort, F.J. & Messinger, D.S. (2022). Beyond the familial: The development of emotional communication with mothers, fathers, and strangers. Infancy, 1– 27. https://doi.org/10.1111/infa.12467 https://en.wikipedia.org/wiki/Surgency Pictures created by E.A. Salvadori --- ## 10 reasons why AV tool Viso is beneficial for video feedback URL: https://noldus.com/blog/viso-tool-for-effective-video-feedback Published: 2022-05-19 09:40:00 Description: Receiving real and honest feedback can be considered as a main source of learning. It will help evaluate your own learning process and identify gaps, which results in better achievements. Receiving real and honest feedback can be considered as a main source of learning. Whether you want to learn how to have a conversation with a patient or a staff member, what the best way is to pitch your new product or service, how to best communicate with your team through CRM, or if you need to learn a technical skill, for example CPR. Feedback will help evaluate your own learning process and identify gaps, which results in better achievements. Developing more effective learning strategies Feedback allows knowing where and how people can improve their skills by letting them confirm, correct, fine tune, or restructure their knowledge or beliefs. Effective feedback can boost the motivation to improve. One of the main features of effective feedback is understandability and clarity. Video-based feedback provides these features. Studies indicate that video-based feedback is: - personal and motivating to revise - easier to understand and more detailed which makes it more useful - supportive for student-teacher communication and interaction - effective in revealing weaknesses and strengths - supportive of learning FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly Tool to provide effective video feedback Viso has been developed to provide audio and video feedback in learning processes. It can record and play back scenarios, training sessions, and role-plays in an easy to use way. §Both after and during the recording of the video, markers and comments can be placed at moments that are of interest and important for the learning process, with the simple press of a button. The actions, behaviors, and interactions of the learners are recorded and can be assessed during debriefing. This allows to learn new skills and improve already existing skills. Also read: Why use video feedback in education How to debrief a training session Effectiveness of video feedback in education 10 reasons why AV tool Viso is beneficial for video feedback There may be many reasons to choose an AV system. The infographic "Top 10 reasons why Viso will benefit your research' highlights why Viso stands out as the ideal tool for video-based feedback. With its ability to capture, review, and analyze interactions in detail, Viso empowers researchers and trainers to deliver precise, impactful feedback that drives learning and improvement. Get to know this multi-room AV tool Due to the continuous development of the product, Viso has already reached version 12. All this progress has made the system faster, more secure, and more user-friendly.  Viso is well-organized and has a super quick playback function to name a few interesting gains. All you need is stored in one system. Do you want to check out if this tool works for you? Request a free demo now, the choice is yours! FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo References - The importance of feedback - Yiğit, M.F. & Seferoglu, S.S. (2021). Investigating the Effect of Video-Based Feedback on Perceived Feedback Quality. Pamukkale University Journal of Education, 51, 92-122. https://doi.org/10.9779/pauefd.707224 --- ## Determining the best housing strategy for mice URL: https://noldus.com/blog/determining-the-best-housing-strategy-for-mice Published: 2022-05-12 09:20:00 Description: When using animal models for scientific research, their welfare should be a priority. Here, we're looking at the effects of different housing strategies for mice, and how PhenoTyper provides researchers with insight. When using animal models for scientific research, their welfare should be a priority. Here, we're looking at the effects of different housing strategies for mice, and how PhenoTyper provides researchers with insight into animal well-being. There is, of course, a strong ethical argument for maximizing the well-being of animals used in research. William Russel and Rex Burch famously laid out this case in their 1952 paper The Principles of Humane Experimental Technique; in which they provided a blueprint for animal welfare considerations in science.1 Hopefully, the value of minimizing unnecessary suffering and distress in animals is readily apparent to most. But the argument for animal welfare goes deeper than this. A large volume of research shows that animals whose well-being is compromised are likely to exhibit physiological and behavioral abnormalities.2,3 As such, factors that contribute to an animal's well-being – insofar as that can be assessed – should be carefully controlled to ensure experimental validity. Are you interested in building your own rodent neurobehavioral core? Download this free guidebook on how to build a rodent neurobehavioral core and learn more about the why, who, what and how. The importance of housing Since mice are, by far, the most commonly used animal models in biomedical research, maximizing their well-being is important. How mice are housed plays an important role in this. Mice are naturally sociable animals. As a result, it's generally recommended that they should be housed in groups wherever this is practical.4 However, male mice don't naturally share territories, and inter-male aggression is a welfare concern for mice housed in captivity where they cannot escape from each other.5 This means that pair housing or single housing are often more practical choices. Other factors – experimental design and disease control in particular – also make single housing a more appealing option in many cases. Where single housing cannot be avoided, some advocate the use of cage dividers that permit sensory but not physical contact between neighboring mice to facilitate some level of social interaction.6 The exact effects of housing on mice's well-being, behavior, and physiology are still subject to debate. However, research indicates that the single housing of mice is linked to various physiological ailments. These include reduced growth rates and reduced lean body mass during growth, higher susceptibility to obesity in adulthood and higher levels of visceral adipose tissue mass.7,8 Behavior is affected by housing too. Single-housed mice are shown to exhibit anxiety-like and depressive-like behaviors alongside disrupted cognitive function compared to pair- or group-housed mice  – though it appears that these effects also depend on a range of other environmental and physiological factors.9–11 "Separated pair" housing using cage dividers appears to produce some behavioral and locomotor differences compared to single housing – although it's not entirely clear whether this correlates to a difference in well-being. All of these changes should ideally be taken into account in the research goals of experimenters using mice. Choosing the optimal housing strategy for your experiment Ultimately, housing conditions tend to be constrained by experimental parameters. For example, studies involving cannulation of mice must use single housing in order to prevent mice from damaging each other's cannulas.12 Studies of energy balance regulation also typically prefer single housing so that the food intake and thermal profiles of individual mice can be monitored accurately. Single housing in individually vented cage (IVC) systems can also play a crucial role in preventing disease transmission between mice. Nonetheless, it's always worth considering whether your experimental parameters could allow for paired (or separated pair) housing to reduce stress, achieve longer testing periods, and improve experimental validity. Many experiments involve testing mice in a novel environment separate from their home cage – testing them in their home environment instead provides another opportunity to lower stress and eliminate the confounding effects of a change in environment.13 RESOURCES: Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! Learn more Evaluating the effects of housing paradigms on mice Housing can have profound behavioral and physiological effects on mice: phenotypically, a socially housed mouse is not the same animal as an individually housed mouse. Monitoring animals in their home cage and comparing their behavior during experiments is crucial to understanding the effects of different housing paradigms. So – whether you opt for social or separate housing – make sure you score everything! PhenoTyper is a fully integrated and automated cage monitoring system. By enabling easy monitoring of individual animals in their home cage, PhenoTyper provides researchers with increased resolution when considering their behavior within a specific housing paradigm. PhenoTyper is fully customizable to suit your research needs. Each configuration consists of a bottom plate, four replaceable walls, and a PhenoTyper top unit. Different walls are available to accommodate any set up, with attachments for accessories such as drinking bottles, feeding stations, and shelters. These can be used to provide feedback on animal behavior to EthoVision XT. The PhenoTyper top unit houses LEDs and a camera for automated tracking, with other sensor and stimuli options available. Automated tracking using EthoVision XT offers full integration of data and automation of experiments. EthoVision XT furthermore provides accurate tracking and calculation of a wide range of physiological and behavioral parameters and provides researchers with unparalleled versatility in data processing and visualization. As a result, EthoVision XT is now by far the most cited video tracking system in the world.14 Find out how PhenoTyper can give you deeper insight and faster results – get in touch with Noldus today. References and further reading - Russell, W. M. S. & Burch, R. L. (1959). The principles of humane experimental technique. The principles of humane experimental technique - Poole, T. Happy animals make good science. (1997). Lab Anim 31, 116–124 - Baumans, V. (2005). Science-based assessment of animal welfare: laboratory animals. Revue Scientifique Et Technique-Office International Des Epizooties 24, 503 - Code of Practice for the Housing and Care of Laboratory Mice, Rats, Guinea Pigs and Rabbits | Agriculture Victoria. https://agriculture.vic.gov.au/livestock-and-animals/animal-welfare-victoria/pocta-act-1986/victorian-codes-of-practice-for-animal-welfare/code-of-practice-for-the-housing-and-care-of-laboratory-mice-rats-guinea-pigs-and-rabbits. - Kappel, S., Hawkins, P. & Mendl, M. T. (2017).  To Group or Not to Group? Good Practice for Housing Male Laboratory Mice. Animals (Basel) 7, E88 - Hohlbaum, K. et al. (2020). Social enrichment by separated pair housing of male C57BL/6JRj mice. Sci Rep 10, 11165 - Schipper, L., van Heijningen, S., Karapetsas, G., van der Beek, E. M. & van Dijk, G. (2020). Individual housing of male C57BL/6J mice after weaning impairs growth and predisposes for obesity. PLoS ONE 15, e0225488 - Schipper, L., Harvey, L., van der Beek, E. M. & van Dijk, G. (2018). Home alone: A systematic review and meta-analysis on the effects of individual housing on body weight, food intake and visceral fat mass in rodents. Obesity Reviews 19, 614–637 - Liu, N. et al. (2019). Single housing‐induced effects in cognitive impairment and depression‐like behavior in male and female mice involve neuroplasticity related signaling. European Journal of Neuroscience 52 - Pasquarelli, N., Voehringer, P., Henke, J. & Ferger, B. (2017). Effect of a change in housing conditions on body weight, behavior and brain neurotransmitters in male C57BL/6J mice. Behavioural Brain Research 333, 35–42 - Buckinx, A. et al. (2021). Exploring Refinement Strategies for Single Housing of Male C57BL/6JRj Mice: Effect of Cage Divider on Stress-Related Behavior and Hypothalamic-Pituitary-Adrenal-Axis Activity. Frontiers in Behavioral Neuroscience 15 - Xavier, A. L. R. et al. Cannula Implantation into the Cisterna Magna of Rodents. J Vis Exp 57378 (2018) doi:10.3791/57378. - Home cage & Welfare - PhenoTyper: https://www.noldus.com/applications/home-cage-welfare. - Benefits - EthoVision XT: https://www.noldus.com/ethovision-xt/benefits. --- ## The relevance of emotions on the evaluation of a transactional website URL: https://noldus.com/blog/role-emotions-evaluation-website Published: 2022-04-19 09:38:00 Description: A UX test is a method of evaluating a product or service by having users test it. Researchers studied how emotions influence opinions about a website by conducting UX tests. This article was written by Gabriel Bergeron-Proulx, a master's student in marketing at the University of Sherbrooke, Quebec, Canada. It explains the usefulness of a facial expression analysis software in the context of a customer retention mandate for a company's digital environment (digital marketing). Marketing Retention Mandate Customer retention is defined as a company's ability to keep its customers, i.e. to make them loyal so they continue to use the services over a given period of time. Therefore, customer retention is a strategic objective. Usability testing (UX Test) In order to conduct a retention quality analysis of a lifestyle company's digital environment, we evaluated its website, its Instagram social network, and a promotional email. We randomly selected 12 volunteers to conduct user testing (UX research) of the company's digital media. Usability testing is a method of testing the functionality of a website, app, or other digital product by observing real users as they attempt to complete tasks on it.  Volunteers completed a sign-up sheet promoted on the company's Facebook page.  Our UX test consisted of 4 tasks: - Create an account on the company's website. - Add a comforter cover and a puzzle to the shopping cart and go to the checkout process. - Read the promotional email message and click on a link to the website.  - Take notice of a product promotional post on the company's Instagram page and find it on their website.  The tests took place over a period of one week. Once the UX tests were completed, we conducted one-on-one interviews to learn more about the user experience. All tests and interviews were conducted via video conference using the Teams platform and were recorded. We then conducted an emotional analysis of the UX test recordings using FaceReader software. FREE WHITE PAPER: Download the free FaceReader methodology note to learn more about facial expression analysis theory. Learn more How did FaceReader help to deepen our observations? Non-verbal behavior is a strong indicator of how our subconscious works. Non-verbal communication goes beyond what participants perceive of themselves. Therefore, it can be an effective way to target a sensitive point in them without them even being aware of it [1].  For example, in our analysis of the emotions of our UX tests for emails, we detected several times that consumers tend to click on the company's logo to access their website. In our case, the logo does not offer the possibility to redirect to the company's website, which created frustration for the users.  In the individual interviews, no participant mentioned that this element seemed to affect them. Yet, these micro-moments are crucial in digital marketing as consumers expect to have everything within a click's reach [2]. They are immersed in a world of choice and therefore, they will not hesitate to look elsewhere at the slightest hitch.  For a marketing email to be effective, it needs a perceived enjoyment in the eyes of consumers [3].  Automatic facial expression analysis with software such as FaceReader is then particularly useful for targeting the "silent" strengths and weaknesses of a digital communication channel to improve its effectiveness.  LABEL Title Learn more Figure 1: Conceptual framework [3]  LABEL Title Learn more Figure 2: Moment of frustration when trying to click on the logo LABEL Title Learn more Figure 3: Moment of sadness during research via an Instagram post Benefits of using emotion software When analyzing emotions, researchers always face the same problem related to emotion measurement: subjective self-report methods are highly biased. It is difficult to confirm what the participant says.  On the other hand, objective methods of direct measurement of emotions such as facial electromyography require expensive tools and a well-defined context, which makes it difficult to collect and interpret the data.  Today, emotion measurement through the use of software can be done at fairly low cost and is extremely easy to implement; we can record the facial expressions that lead to emotions remotely or face-to-face with everyday tools such as a cell phone, a webcam, a tablet, or a computer. Moreover, the considerable advantage is that this technology is not at all intrusive for consumers, which allows us to collect data that is more true to reality. RESOURCES: Find out how FaceReader is used in a wide range of studies and how it can elevate your research! Learn more References - Stewart, D.W.; Hecker, S. & Graham, J.L. (1987). It's more than what you say: Assessing the influence of nonverbal communication in marketing: ABSTRACT.Psychology & Marketing (1986-1998), 4(4), 303.  - Solis, B. (2017). Impatience Is A Virtue: How The On-Demand Economy Is Making Mobile Consumers Impatient. Forbes, accessed at 23 October 2021.  - Reimers, V.; Chih-Wei, C., & Gorman, S. (2016). Permission e-mail marketing and its influence on online shopping. Asia Pacific Journal of Marketing and Logistics, 28(2), 308-322. https://doi.org/10.1108/APJML-03-2015-0037 --- ## Top 5 Consumer behavior research on the Behavioral Research Blog URL: https://noldus.com/blog/top-5-consumer-behavior-research-blog-posts Published: 2022-04-12 12:00:00 Description: Observational research is becoming more and more popular in consumer science and market research. From on-site behavioral observations in supermarkets to advanced multimodal lab studies. Observational research is becoming more and more popular in consumer science and market research. From on-site behavioral observations in supermarkets to advanced multimodal lab studies, researchers are more and more familiar with measuring and observing participant behavior. Researchers combine for example the measurement of behavioral and physiological data in order to get a more complete picture of the person's response. Top 5 Consumer behavior research blog posts This Behavioral Research Blog post features the top 5 blog posts about consumer science, market research, and neuromarketing that were published in recent months. Consumer behavior research: On-site or in a lab? When you need to follow your subjects while they choose items in a store, you can code behaviors on a mobile device such as a tablet, and use an eye tracker to follow the gaze of the participant. Eye tracking glasses, for example, allow your test participants to move and look around freely. An observation lab allows for the integration of video, eye tracking, physiological data, and more. For example, in a lab situation you can also accurately measure facial expressions with FaceReader that allows you to analyze and report about participant responses to commercials. Top 5 blog posts on consumer behavior research Now let us focus on the top 5! These blog posts on consumer behavior research discuss recent studies and inform you about how researchers carried out their projects. 1. How to measure consumer behavior Measuring consumer behavior enables you to really know your customers and get key insights into consumer preferences and buying behavior. There are several ways how consumer behavior can be measured. We highlight four of these ways for you in this blog post. Learn more about innovative methodologies for Consumer Behavior Research - Replay our free webinar now! 2. How to build a consumer behavior research lab A Consumer Lab is designed to allow you to observe your test participants unobtrusively. But how do you build a consumer behavior research lab? Find out more in this blog post, and discover some essential questions to ask. Continue reading: How to build a consumer behavior research lab 3. Neuromarketing research: Innovative research methods and techniques Neuromarketing research is a field of marketing that studies consumers' sensorimotor, cognitive, and affective response to marketing stimuli. It is an interesting mix of companies and universities that invest in neuromarketing to gather more information about consumer behavior. Read the full blog post here: Neuromarketing research 4. Measuring consumer choice behavior If you are measuring consumer behavior, the setting in which the experiment takes place, can have a huge effect on the outcome. And even though this is a well-known fact to scientists studying consumers' responses to food, still the majority of experiments carried out today are done in controlled conditions in a lab. Two recent projects provide new insights into how best to measure the choices that we make. Continue reading here. FREE WHITE PAPER How to build an observation lab Do you want to learn more how to set up an observation lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download 5. Three ways to understand consumer emotions Really knowing your customer is what you need to design loved products and applications. Therefore many companies are seeking ways to understand consumer emotions in order to predict product acceptability. We've written about three ways you could set up your study to assess consumer emotions. Would you like to learn more on consumer behavior research and observation labs? Download our free 'how to' guide. --- ## 3 ways to use rodent gait analysis in CatWalk XT URL: https://noldus.com/blog/3-ways-to-use-rodent-gait-analysis-in-CatWalk-XT Published: 2022-04-11 11:00:00 Description: CatWalk XT has been used for gait analysis in multiple studies and has helped experimental procedures for a number of neurological disorders and in lesion models. These 3 blogs tell you more about that! CatWalk XT has been used for gait analysis in multiple studies and has helped experimental procedures for a number of neurological disorders and in lesion models. The great benefit of this gait analysis system is that it lets mice walk freely without being forced. With the Illuminated Footprint Technology and a high-speed camera this system gives you an accurate and automated analysis of the locomotor ability of your rodents. LABEL Title Learn more LABEL Title Learn more 2. Evaluating walking mice with gait analysis after a complete spinal cord crush Researchers from the University of Bochum recently achieved a major break-through in their search for a potential therapeutic approach for spinal cord injury (SCI). Spinal cord injury is damage of the spinal cord that often occurs after traumatic incidents like a car accident, a fall from great height or from a non-traumatic disease, such as tuberculosis. In their study, the researchers discovered that a protein called hyper-interleukin-6 (hIL-6) stimulates signaling and axonal regeneration in a deeper brain area that is difficult to reach. These deeper brain areas are important for movement processes, such as walking and running. They injected the hIL-6 into the easily accessible sensorimotor cortex of the brain and observed the regeneration of neuros in a deeper level of the brain. The axonal regeneration in this level is essential for functional recovery after spinal cord injury. With the hIL-6 injected, paralyzed animals started to walk again after two to three weeks! To evaluate this, the researchers used CatWalk XT for gait analysis of functional recovery after spinal cord injury. The CatWalk XT captures the actual footprints of the subjects and is therefore the ideal tool to get accurate results of each paw touching the glass, the total area touching the glass, stride length, base of support and regularity which are also the parameters that the researchers looked at in this study.  Curious to know more about this study? Click here to read more. LABEL Title Learn more LABEL Title Learn more RESOURCES: Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! Learn more --- ## 3 high impact papers about measuring anxiety in the Elevated Zero Maze URL: https://noldus.com/blog/measuring-anxiety-elevated-zero-maze Published: 2022-04-06 14:15:00 Description: The elevated zero maze (EZM) is a variation on the elevated plus maze (EPM) and was created to eliminate the center region of the EPM. This blog highlights 3 studies that use the EZM to test for anxiety-like behavior image credit: Maze engineers Measuring anxiety in the Elevated Zero Maze: 3 high impact papers The elevated zero maze (EZM) is a variation on the elevated plus maze (EPM) and was created to eliminate the center region of the EPM. The EZM is an elevated ring-shaped arena with two open and two closed quadrants (with elevated walls), and has been described as valid test for anxiety-like behavior in rodents as early as 1994 [1]. Benefits of the elevated zero mazed compared to the elevated plus maze The first benefit of the EZM, as already mentioned, is the removal of the center square. This takes away the availability of a logical starting point while also removing any ambiguity in the interpretation of the time spent in the center of the maze.  Secondly, Tucker and McGabe describe an experiment in which they compare the EPM and EZM in male and female C57BL/6J mice [2]. They found that the EZM encourages greater exploration of the anxiogenic regions (open quadrants), while also finding consistent outcomes over multiple sessions, while the EPM is advised to be only performed once per mouse to avoid learning and habituation to the maze, potentially masking anxiety-like behavior. The elevated zero maze is gaining in popularity The EPM is still the most used behavioral test to assess anxiety-like behavior in rodents. The EZM has however been gaining somewhat in popularity over the last few decades, as seen by a graphic based on search result numbers in Google Scholar for the keywords: ‘Elevated plus maze’ and ‘Elevated zero maze’, summarized in 5-year periods.  LABEL Title Learn more Paper 1: Depression, not anxiety, is affected by the FTO gene. Fat mass and obesity-associated protein, also known as alpha-ketoglutarate-dependent dioxygenase (FTO) was shown to be downregulated in the hippocampus of patients with Major depressive disorder (MDD) and in mouse models of depression. “Knockdown or knockout of Fto in the hippocampus induces depression-like behaviors, whereas overexpression of FTO has antidepressant effects” [3].  This study by Liu et al in ‘Nature communications’ showed that specifically depressive-like behaviors were affected by their FTO mouse model, while anxiety-like behaviors, as measured with the EZM, and growth/body weight changes were not observed. This is argued by the authors to be due to their FTO deficiency model presenting what is called: ‘nonanxious MDD’. This model actually creates a very nice opportunity to investigate the depressive symptoms of this model in a very isolated manner, meaning there is little influence by other behavioral confounders. Paper 2: The alcohol deprivation effect (ADE) as a model of relapse-like drinking Alcohol use disorder (AUD) is still a prevalent conditions nowadays, and has a very debilitating effect for individuals. Unable to regulate drinking behavior, increased feelings of cravings and chronic episodic relapsed towards heavy alcohol drinking make this an extremely difficult psychological and physiological disorder to treat. Stress, for example, has been identified as a major trigger for cravings and relapses.  The study by Chandler et al in ‘Neuropharmacology’ makes use of the Alcohol Deprivation Effect (ADE), a pre-clinical model for relapse drinking in rats [4]. They subject Sprague-Dawley rats to the ADE protocol, which introduces alcohol next to drinking water, but is taken away for a set period of time, whereafter it is re-introduced. This creates a relapse model, which can then be pharmacologically treated with different α5GABA-A receptor agonists. Anxiety was tested in the elevated zero maze using Noldus’ EthoVision XT video tracking. Want to know more about tracking automated video tracking in EthoVision XT? We have a number of webinars that explain everything in great detail!  FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more Paper 3: Identifying neural circuitry underlying avoidance behavior Avoidance behavior is a fundamental part of survival in any animal species. External cues can trigger an avoidance (when that trigger indicates a potential risk), but also an approach (when there is a potential for a reward). These signals can be interpreted as conflicting, leading to an approach-avoidance conflict. The dorsomedial prefrontal cortex (dmPFC) has been linked to avoidance and decision-making under conflict. These are also key neural computations that seem to be altered in anxiety disorders.  The study by Loewke et al in ‘The Journal of Neuroscience’ uses fiber photometry recordings in both male and female mice during the elevated zero maze task [5]. They show heightened neural activity in frontostriatal but not frontoamygdalar projection neurons during exploration of the anxiogenic open arms of the elevated zero maze. This work identifies a specific corticostriatal circuit involved in encoding and controlling avoidance behavior, this will enable the development of more targeted symptom-specific treatments for anxiety disorders. The future of the elevated zero maze This blog highlights the gaining interest in the elevated zero maze, and its use in a number of interesting scientific papers. Its very simple, yet distinct, difference from the elevated plus maze is based on a valid argument; that the interpretation of an animals’ time spent on a center square can be somewhat ambiguous. It would be nice to see more studies that compare these two mazes, such as the paper by Braun et al [6]. Want to read more about the elevated plus maze? Check out this blog!  References -  Shepherd, J. K.; Grewal, S. S.; Fletcher, A.; Bill, D. J.; Dourish, C. T. (1994). Behavioural and pharmacological characterisation of the elevated “zero-maze” as an animal model of anxiety. Psychopharmacology (Berl)., 116 (1), 56–64 - Tucker, L. B.; McCabe, J. T. (2017). Behavior of male and female C57Bl/6J mice is more consistent with repeated trials in the elevated zero maze than in the elevated plus maze. Front. Behav. Neurosci., 11, 13 - Liu, S. et al. (2021). Fat mass and obesity-associated protein regulates RNA methylation associated with depression-like behavior in mice. Nat. Commun. 2021 121, 12 (1), 1–13 - Chandler, C. M.; Reeves-Darby, J.; Jones, S. A.; Li, G.; Rahman, M. T.; Cook, J. M.; Platt, D. M. (2021). Modulation of relapse-like drinking in male Sprague-Dawley rats by ligands targeting the α5GABAA receptor. Neuropharmacology, 199, 108785 - Loewke, A. C.; Minerva, A. R.; Nelson, A. B.; Kreitzer, A. C.; Gunaydin, L. A. (2021). Frontostriatal Projections Regulate Innate Avoidance Behavior. J. Neurosci., 41 (25), 5487–5501 - Braun, A. A.; Skelton, M. R.; Vorhees, C. V.; Williams, M. T. (2011). Comparison of the elevated plus and elevated zero mazes in treated and untreated male Sprague-Dawley rats: Effects of anxiolytic and anxiogenic agents. Pharmacol. Biochem. Behav., 97 (3), 406 --- ## Quantifying locomotion in rats using CatWalk XT URL: https://noldus.com/blog/quantifying-locomotion-in-rats-using-catwalk Published: 2022-03-29 15:00:00 Description: Gait analysis is a powerful tool in evaluating behavioral and physiological changes in clinical and pre-clinical rodent models. Gait analysis is a powerful tool in evaluating behavioral and physiological changes in clinical and pre-clinical rodent models, providing valuable insight into pathology and experimental treatments for a wide range of health conditions. The CatWalk XT provides detailed, accurate, and fully automated gait analysis, enabling researchers to easily quantify footfalls and locomotion in rats and mice. The power of gait analysis The concept of gait analysis is not new. Following developments in the understanding of the anatomy and mechanics of walking throughout the 18th and 19th centuries, the first human and quadrupedal gait patterns were recorded by Edward Muybridge in the late 1800s.1  In the 20th century, the amount of information that could be gained from gait analysis was enhanced by the introduction of force-measuring plates and an improved understanding of kinetics. With the first clinical applications pioneered in the 1970s, it soon became apparent that gait analysis was a rich source of information into an organism's physiological and neurological functioning. Alongside applications in prosthetics, zoology and exercise physiology; gait analysis became recognized as a valuable tool in the analysis of medical conditions such as cerebral palsy, arthritis, and traumatic brain injury.2,3  Gait Analysis of Rodents Small, inexpensive, and easily genetically modified; rats and mice are widely regarded as near-ideal animal disease models. As a result, they've served as the leading model organisms in biomedical research for over a century. While the quadrupedal gait patterns of rodents are, of course, different to the bipedal gait patterns of humans, the conceptual basis for gait analysis in both species remains the same. Members of each species will alter their gait pattern in order to protect an injured limb from pain due to loading or movement, or in response to peripheral nerve damage, for example.3,4 Gait analysis in rodents therefore has great potential in medical research with human applications. Until recently, accurate gait analysis was only possible for larger animals such as humans and horses. Early attempts to quantify the motor function of rats – such as BBB scoring, running wheels, and ink-on-paper – are subjective and fail to accurately assess the temporal dynamics of gait.5 However, improvements in high-speed videography have enabled accurate gait analysis of rodent models, enabling researchers to evaluate the changes that experimental treatments may provide. The CatWalk XT combines high temporal and spatial resolution cameras with our proprietary Illuminated Footprints™ technology to bring affordable and sophisticated rodent gait analysis to laboratories of all sizes. The CatWalk XT While other systems rely on error-prone paw recognition, the CatWalk XT uses light refraction to capture actual footprints as a rodent voluntarily traverses a glass walkway.6 Our Illuminated Footprints™ technology enables accurate distinction between the parts of the animal that make contact with the floor and those which do not, allowing built-in software to identify subtle changes within the dimensions, positioning and timing of each footprint.  Detection of individual pawprints means the CatWalk XT never mistakes one part of the body for another, and is capable of unparalleled accuracy in measuring footprint size and shape. Using this footprint data, CatWalk XT calculates over 100 parameters for qualitative and quantitative analysis of footfall and gait. Applications of CatWalk XT As the use of rodent gait analysis for research continues to increase, the CatWalk XT is helping researchers worldwide to rapidly obtain accurate and objective data on locomotion in rats and mice. The CatWalk XT is, by far, the most cited gait analysis system in the world, with over 2400 publications based on the system.7 A common confounding factor with rodent gait analysis is that many gait parameters are velocity dependent, making it difficult to ascertain whether variations in gait are due to treatment, injury, or simply natural variation in speed. The CatWalk XT provides researchers with the data so they can compensate for this velocity dependence, eliminating this common confounding factor and improving the validity of their data.8,9 Being able to rapidly determine multiple gait parameters such as swing speed, stride length, paw intensity and interlimb coordination makes the CatWalk XT a powerful and versatile tool. Previous applications include: - Development of a new sensory and motor scale for predicting functional deficits in arthritis mouse modeling. By evaluating voluntary movement, the CatWalk XT enabled researchers to monitor pain and sensitivity non-invasively and without the need for extra-nociceptive stimuli. - Detection of subtle yet significant impairments due to traumatic brain injury is undetectable by human observation. - Development of an effective method for the early detection of Parkinson's disease in rat models. Are you interested in finding out more about the CatWalk XT? Read more about recent applications of the system here, or get in touch with us to book a free demo. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources References and Further Reading  - Baker, R. The history of gait analysis before the advent of modern computers. Gait & Posture 26, 331–342 (2007). - Kirtley, C. Clinical Gait Analysis: Theory and Practice. (Elsevier Health Sciences, 2006). - Lakes, E. H. & Allen, K. D. Gait analysis methods for rodent models of arthritic disorders: reviews and recommendations. Osteoarthritis and Cartilage 24, 1837–1849 (2016). - Assessing motor outcome in rats with peripheral nerve injury | Noldus. Assessing motor outcome in rats with peripheral nerve injury | Noldus noldus.com/blog/motor-performance-femoral-nerve-injury. - de Barros Filho, T. E. P. & Molina, A. E. I. S. Analysis of The Sensitivity and Reproducibility Of The Basso, Beattie, Bresnahan (BBB) Scale in Wistar Rats. Clinics 63, 103–108 (2008). - Noldus | CatWalk XT | Methodology. Methodology CatWalk XT - white paper. - Methods to Quantify the Velocity Dependence of Common Gait Measurements from Automated Rodent Gait Analysis Devices. www.ncbi.nlm.nih.gov/pmc/articles/PMC4560675/. - Pitzer, C., Kurpiers, B. & Eltokhi, A. Gait performance of adolescent mice assessed by the CatWalk XT depends on age, strain and sex and correlates with speed and body weight. Sci Rep 11, 21372 (2021).   --- ## 5 EthoVision XT webinars for you to watch URL: https://noldus.com/blog/five-ethovision-xt-webinars-for-you-to-watch Published: 2022-03-15 10:45:00 Description: In this blog you’ll find five webinars on EthoVision XT from five different angles. Each webinar will get you more in depth on how to use EthoVision XT in your own study or research. Video tracking software EthoVision XT is a great tool to help you track and analyze behavior, movement and activity of any animal. In the last 25 years EthoVision XT has evolved from video tracking software into a software platform with a wide variety of application possibilities in different researches. Even though EthoVision XT makes it easy for you to track and analyze data, it is a software that can be widely applied. Can’t see the forest for the trees? Our EthoVision XT experts have come to the rescue! 5 EthoVision XT webinars for you to watch In this blog you’ll find five webinars on EthoVision XT from five different angles. Each webinar will get you more in depth on how to use EthoVision XT in your own study or research. 1. Hiding in Plain Sight: EthoVision XT and Hidden Zones If you’re a beginner or intermediate user of EthoVision XT this webinar could be of good use for you. In this webinar Matt Feltenstein covers everything you need to know about hidden zones in the video tracking system EthoVision XT. It’s a technical briefing that covers everything you need, to do it right from the beginning. Watch the full webinar here.   2. Tips and tricks in EthoVision XT: Insights into the unkown Chances are, that you’re already working with EthoVision XT. If you’re working with this videotracking software already, but would like to get a more in-depth overview of EthoVision XT, then this is the webinar for you! In this webinar we show you all the hidden tips and tricks that EthoVision XT has to offer. From custom templates to arena settings: all things EthoVision XT. Watch the full webinar here. 3. Don’t fear the procedure: EthoVision XT and fear conditioning  Fear conditioning is a typical learning task in a wide range of studies. This form of Pavlovian learning will let the subject associate stimuli with a negative stimulus or situation. A typical reaction of rodents in such situation is a behavior described as freezing. The EthoVision XT videotracking system is excellent at detecting freezing and with the integrated analysis view in the system, you can see results and data in the most intuitive way. Breaking a sweat only by the thought of using EthoVision XT in combination with fear conditioning? No worries, we’ve got you covered. In this webinar we discuss everything you need in EthoVision XT to do it right from the beginning. From using Activity analysis, to programming your Trial Control Settings, and analyzing timed events using the Data Profile. Let us show you the way so you don’t have to sweat, worry, or freeze. Watch the full webinar here. RESOURCES: Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! Learn more 4. Analysis of spatial behavior: Heatmaps in Ethovision XT When using EthoVision XT video tracking software in your experiment, it is possible that the resulting coordinates and time stamps allow for many different kinds of analyses. Luckily, EthoVision XT has a wealth of visualization tools to analyze your data. One of the them is Heatmaps. Heatmaps help you analyze place preference behavior. This will help you to find hotspots and accompanying figures in a manuscript. If you want to know how heatmaps in EthoVision work and how you can get the most out of them, this webinar is for you! Watch the full webinar here.     5. Data analysis, organization, and visualization in EthoVision XT and Microsoft Excel In need of a kick-start into using Microsoft Excel with video tracking tool EthoVision XT? In this 45-minute technical briefing you’ll learn more about the typical workflow in EthoVision XT. Noldus Trainer Wilant van Giessen will show you all his pro-tips and tricks on how you can select, analyze, organize and export your data into Microsoft Excel. Watch the full webinar here. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more --- ## Using CatWalk XT to analyze variations in gait performance in adolescent mice URL: https://noldus.com/blog/analyze-variations-in-gait-performance Published: 2022-03-14 16:05:00 Description: Rodents are the most common model organisms in biomedical research. Automated gait analysis provides a precise and objective means of analyzing behavioral and physiological changes in rodent models. Rodents – particularly mice and rats – are the most common model organisms in biomedical research. Over the last century, rodent models have been instrumental in gaining insight into a staggering range of medical conditions, enabling researchers to explore pathologies and discover new treatments for injuries and disease. Rodent Models and Gait Analysis Analyzing motor and coordination dysfunctions is a key part of assessing rodent models. Just like humans, rats and mice alter their gait in a predictable manner in order to protect injured limbs from pain due to loading and/or movement, or in response to peripheral nerve damage or neurological disease.1–3 Indeed, motor and coordination dysfunctions, including gait abnormalities, are the main diagnostic criteria for a number of CNS disorders, including Parkinson's, Huntington's and Alzheimer's diseases. However, the majority of rodent motor function tests – including manual gait analysis techniques such as BBB scoring, running wheels, and ink-on-paper – are inaccurate and subjective.4 Automated gait analysis using the CatWalk XT provides a precise and objective mea Automated Gait Analysis with the CatWalk XT The Noldus CatWalk XT is a powerful all-in-one rodent gait analysis system that provides researchers with a non-intrusive and fully-automated way of accurately quantifying rat and mouse locomotion. Rather than relying on video interpretation like competing systems, the CatWalk XT instead uses Illuminated Footprints™ technology, in which a high temporal and spatial resolution camera tracks light refracted off the paws of mice or rats that traverse freely over a glass walkway.  The CatWalk XT can measure subtle changes in each footstep's dimensions, position, and timing by capturing high-resolution images of the animal's pawprints. This enables the calculation of over 100 gait parameters, including swing speed, stride length and interlimb coordination. Unraveling Factors Affecting Gait Performance in Adolescent Mice Researchers at Heidelberg University and the University of Washington used the CatWalk XT system to investigate the effects of confounding factors including age, strain, sex, speed and body weight on gait performance.5 The researchers noted that while the CatWalk XT system has been widely used for research into adult mice, a number of motor and gait abnormalities in neuropsychiatric disorders commonly manifest prior to adulthood. In addition, the team noted strain- and sex-specific effects in other behavioral tests. Using the CatWalk XT, the researchers carried out a complete gait analysis of adolescent mice. Detailed footprint mapping enabled the system to accurately measure multiple temporal, spatial and interlimb coordination parameters simultaneously in the investigated strains during adolescence; allowing the researchers to examine the effects of these confounding variables. Using these results, the researchers confirmed the effects of genetic strain differences on motor and gait functions; and unraveled the effects of age, sex, speed and weight on mouse gait. This enabled them to make recommendations to decrease intra-laboratory discrepancies and increase the validity of rodent models for future investigations of neuropsychiatric disorders. Having been used in over 2,400 published research projects, the CatWalk XT is by far the most cited rodent gait analysis system in the world.6  To find out more about the benefits of CatWalk XT or book a free assessment, get in touch with a member of our team today. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources References and further reading  - Kirtley, C. Clinical Gait Analysis: Theory and Practice. (Elsevier Health Sciences, 2006). - Lakes, E. H. & Allen, K. D. Gait analysis methods for rodent models of arthritic disorders: reviews and recommendations. Osteoarthritis and Cartilage 24, 1837–1849 (2016). - Assessing motor outcome in rats with peripheral nerve injury | Noldus. Assessing motor outcome in rats with peripheral nerve injury | Noldus https://www.noldus.com/blog/motor-performance-femoral-nerve-injury. - de Barros Filho, T. E. P. & Molina, A. E. I. S. Analysis of The Sensitivity and Reproducibility Of The Basso, Beattie, Bresnahan (BBB) Scale in Wistar Rats. Clinics 63, 103–108 (2008). - Pitzer, C., Kurpiers, B. & Eltokhi, A. Gait performance of adolescent mice assessed by the CatWalk XT depends on age, strain and sex and correlates with speed and body weight. Sci Rep 11, 21372 (2021). --- ## Designing a behavioral coding scheme to identify complex trauma URL: https://noldus.com/blog/designing-behavioral-coding-scheme Published: 2022-02-25 09:06:00 Description: In order to contribute to the development of diagnostic tools and a better understanding of the effects of complex trauma, Ana Granados and her team proposed a new coding scheme and tested its validity. When you delve into the subject child maltreatment, you most likely come across the key facts the World Health Organization mentions on their website. It is quit shocking to read that nearly 3 in 4 children, aged 2-4 years, regularly suffer physical punishment and/or psychological violence at the hands of parents, caregivers, or other persons in a custodial role. And that is just the beginning of the list with key facts. Concept of complex trauma Child maltreatment includes all types of physical and/or emotional ill-treatment, sexual abuse, neglect, negligence, and commercial or other exploitation, which results in actual or potential harm to the child’s health, survival, development, or dignity in the context of a relationship of responsibility, trust, or power. A very serious problem, which needs serious attention. Especially because of its life-long consequences. Therefore, researchers have developed the concept of complex trauma (CT). It refers to both the exposure and the wide-ranging effects of the chronic exposure of a person to multiple traumatic events. CT experiences are often invasive and interpersonal in nature. It affects the normal development of children because of the disruption of feeling secure. Diagnosing and understanding the effects of complex trauma In order to contribute to the development of valid diagnostic tools and a better understanding of the effects of complex trauma, Ana Granados and her colleagues at the National University of Colombia conducted a study based on these three goals: - Proposing a coding scheme of emotional regulation and stress response behaviors. - Implementing the resulting coding scheme to compare a sample of children with a history of CT versus a comparison group without this history. - Exploring associations between the results obtained observationally through the coding scheme and those obtained through several scales of the Child Behaviour Checklist (CBCL). In total 84 children, aged 6-14 were selected from child protection institutions and the afterschool community services centers. The Complex Trauma Checklist for Children and Adolescents (CTCL-CA) was administered to all participants to determine whether they had exposure to interpersonal trauma or not. The CBCL was used to detect behavioral and emotional problems. FREE WHITE PAPER: How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download arrow_forward Crossed-Puzzle Game In addition, the research team made use of the Crossed-Puzzles Game. A semi-controlled 20-minute group task that seeks to spontaneously move the participants from an individual activity to a collaborative one. Participants are not aware of this condition and neither of the fact that the only possible way to successfully solve their puzzle is to collaborate with others. The Crossed-Puzzles Game was carried out with groups of 4-6 children per game. The children started with an individual puzzle that was composed of 50% of their own pieces. For the other 50% of the puzzle, they needed pieces from other children. Designing a behavioral coding scheme The behaviors of all children were recorded on video. Recurring behaviors were identified, as well as non-verbal behaviors associated with stress, emotional regulating, and other noticeable or clinically relevant behaviors. Next, these behaviors were categorized. A coding scheme emerged. A range of statistical methods was used to validate the coding scheme. The coding scheme was composed of five categories: - Self-support – e.g. leaning on a surface, holding the head, or self-touching. - Distraction – e.g. clapping, dancing, and manipulating objects not related to the task. - Fatigue – e.g. sighing, yawning, and stretching - Hyperactivation – e.g. moving legs, nibbling, and moving hands or fingers. - Externalizing of frustration – e.g. hitting pieces, throwing pieces, and standing up and out of the task’s designated space. An assistant – blind to the study aims and the groups – was trained in recognizing the categories of the coding scheme. Inter-observer agreement was calculated between the assistant and an expert. Subsequently, the behaviors were coded with The Observer XT. FREE TRIAL: Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial arrow_forward The coding scheme’s validity as a research and assessment tool Of the coding scheme, the category ‘Externalizing of frustration’ proved to be one of the strongest predictors for the complex trauma group. It allowed to discriminate the belonging to the complex trauma group. Nonetheless, it was not the most significant predictor. The CBCL subscale ‘Aggressive behaviors’ was. Admittedly, these two categories are very similar. The researchers reason that this result shows that conducting clinical assessments through the triangulation of information from different sources (e.g., direct observation of child’s behavior and caregiver’s reports), instead of relying exclusively on one, regardless if they have an observational or a hetero-reporting nature, leads to better assessments. References - https://www.who.int/news-room/fact-sheets/detail/child-maltreatment - https://www.nctsn.org/what-is-child-trauma/trauma-types/complex-trauma - Granados, A. V.; Sabogal, J. C.; Muñoz, P.; Caicedo, J. C.; Martínez-Cotrina, J. & Aponte Canencio, M. (2021). Ethogram of non-verbal behaviours associated with emotional regulation and stress response in children and adolescents with complex trauma, Behaviour, 158(14-15), 1421-1448. https://doi.org/10.1163/1568539X-bja10124 --- ## What is the Barnes maze? A dry-land environment for testing learning and memory URL: https://noldus.com/blog/what-is-the-barnes-maze Published: 2022-02-23 13:50:00 Description: The Barnes maze is a behavioral paradigm for testing learning and memory in rodents models for autism spectrum disorder, Alzheimer’s disease and ageing. How does it compare to the Morris water maze? Carol Barnes designed this behavioral paradigm in 1979 to test memory deficits in aging rats [1], while only being adapted to mice as late as 1995 [2]. It is often referred to as an alternative to the Morris water maze, which relies on swimming behavior potentially confounding learning and memory readouts.   What is the Barnes maze? A dry-land environment for testing learning, memory and cognitive flexibility At this point in time, the Barnes maze is a well-established behavioral paradigm, and is used to test learning and memory in rodent models for autism spectrum disorder [3], Alzheimer’s disease [4] and ageing [5], to name a few. The Barnes maze is constructed as a circular table with circular holes around the circumference. The goal of this test is that the subject (rat or mouse) reaches an escape box that is positioned beneath one of the holes. This task relies on visual cues, which thus prompts spatial learning and memory. Essential in such a protocol is learning the position of this box beforehand. This can be done in a number of ways, food reward is a popular choice. Searching strategy Investigating the animal’s searching strategy over consecutive trial can also be an interesting readout of the Barnes maze. For example, some animals randomly search for the correct hole while in the acquisition phase, while other animals stick to a certain pattern when systematically checking each hole. Advantages of the Barnes maze versus the Morris water maze - The Barnes maze does not involve swimming, which can be perceived as stressful and increases corticosterone levels [6]. - Swimming in the Morris water maze also causes reductions in core body temperature which can affect performance [7], this can be circumvented somewhat by regulating the water temperature properly. - While in a swimming task, rodents can take to floating, which is thought to represent a state of behavioral despair, a common readout of depressive-like behavior in the Forced swim test. Disadvantages of the Barnes maze versus the Morris water maze - A lack of stressful stimuli in the Barnes maze can result in slow learning. To increase the motivation to escape a mild stressor such as white noise or a buzzer sound can be played [2]. - The Barnes maze requires a bit more training/trials than the Morris water maze. Where a Barnes maze generally takes 15-20 acquisition trials, even having protocols of up to 40 trials. The Morris water maze is generally performed over ± 12 trials. - It is said that the Barnes maze is somewhat limited to the use of young (3-5 months of age) adult C57BL/6J mice. [8, 9] In general, performance in the Barnes maze and/or the Morris water maze is highly sensitive to anxiety in rodents, which can be induced (or of greater levels) in animals subjected to for example pharmacological and/or genetic manipulation. This can be mitigated for example by decreased light intensity. Barnes maze or Morris water maze? Which one should I choose? Both the Barnes maze and the Morris water maze are well validated behavioral paradigms for studying learning and memory. Both have clear advantages and disadvantages. It should thus be pragmatically considered which one is the best for you. Do you have a validated setup of one or the other in your lab? Have you previously published with one of these tests? Or do you simply want to avoid swimming, for example in mice which are less-than-natural swimmers compared to rats? Think practically about these thing when writing/planning your study design. Video tracking in the Barnes maze with EthoVision XT In EthoVision XT there is a predefined template for the Barnes maze, making tracking and analyzing as easy as dragging and dropping the circles (for the escape holes) to the correct place in the video image. Specify which hole has the goal box underneath, and you are ready to acquire your data. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more References - Barnes, C. A. (1979). Memory deficits associated with senescence: A neurophysiological and behavioral study in the rat. J. Comp. Physiol. Psychol., 93 (1), 74–104 - Bach, M. E.; Hawkins, R. D.; Osman, M.; Kandel, E. R.; Mayford, M. (1995). Impairment of spatial but not contextual memory in CaMKII mutant mice with a selective loss of hippocampal LTP in the range of the theta frequency. Cell, 81 (6), 905–915 - Yang, K. et al. (2021). SENP1 in the retrosplenial agranular cortex regulates core autistic-like symptoms in mice. Cell Rep., 37 (5), 109939 - Macêdo, P. T.; Aquino, A. C. Q.; Meurer, Y. S. R.; Brandão, L. E. M.; Campêlo, C. L. C.; Lima, R. H.; Costa, M. R.; Ribeiro, A. M.; Silva, R. H. (2018). Subtle alterations in spatial memory induced by amyloid peptides infusion in rats. Front. Aging Neurosci., 10 (JAN), 18 - Weber, M. et al. (2015). Cognitive Deficits, Changes in Synaptic Function, and Brain Pathology in a Mouse Model of Normal Aging. eNeuro, 2 (5), 47–62 - Harrison, F. E.; Hosseini, A. H.; McDonald, M. P. (2009). Endogenous anxiety and stress responses in water maze and Barnes maze spatial memory tasks. Behav. Brain Res., 198 (1), 247–251 - Iivonen, H.; Nurminen, L.; Harri, M.; Tanila, H.; Puoliväli, J. (2003). Hypothermia in mice tested in Morris water maze. Behav. Brain Res., 141 (2), 207–213 - Pitts, M. W. (2018). Barnes Maze Procedure for Spatial Learning and Memory in Mice. Bio-protocol, 8 (5) - Kesby, J. P.; Kim, J. J.; Scadeng, M.; Woods, G.; Kado, D. M.; Olefsky, J. M.; Jeste, D. V.; Achim, C. L.; Semenova, S. (2015). Spatial Cognition in Adult and Aged Mice Exposed to High-Fat Diet. PLoS One, 10 (10) --- ## 6 reasons to go to the Measuring Behavior conference URL: https://noldus.com/blog/mb2020 Published: 2022-02-20 10:00:00 Description: Not sure if you want to go to MB2022? Read on... This spring the 12th edition of the Measuring Behavior conference will take place. Over the years it has grown from just a small workshop, to a fully-fledged international scientific conference with a high reputation. There are so many conferences to go to. What makes Measuring Behavior special? Why you should attend the Measuring Behavior conference 1. Multidisciplinary conference Behavior is a wide concept encompassing many disciplines. In practice neuroscientists, psychologists, UX researchers, ethologists, and all the other specialties represented at Measuring Behavior have their own traditions and ways of doing research. However, often they face the same problems and can learn a lot from each other. One of the great strengths of the meeting is that the conference has both sessions which go into depth for researchers focusing on one topic, as well as broader symposia in which delegates can take advantage of the knowledge of other disciplines. 2. Joint meeting The coming meeting will be a joint one between Measuring Behavior and the International Symposium on Behavioral Methods. Professor Jarosław Barski, from the Medical University of Silesia, is the local Chair for Measuring Behavior and has organized the International Symposium on Behavioral Methods for many years, so he is uniquely qualified to ensure that in May all the delegates will benefit from the coming together of the two conferences. 3. Virtual event Although originally scheduled to take place in one of the most beautiful cities in Europe, Measuring Behavior will now take place online. This will enable people from all over the world to attend. 4. Demonstration showcase In addition to the usual types of sessions like symposia, workshops and posters, one of the unusual features of Measuring Behavior is that there is a special format for the presentation of inventions and prototypes. Both academics and companies can give interactive demonstrations of their new software and hardware. This program element is often the most appreciated by delegates. Incidentally, although Noldus helps organize the conference, it is open to all and Noldus' competitors are also exhibitors and will often demonstrate their products. 5. Publications In addition to the short abstracts which presenters submit for the Program, the conference also has a full peer-reviewed Proceedings of short papers (open access and with ISBN). Because of the multi-disciplinary nature of the delegates, we are very flexible about the length of the Proceedings papers allowed, with submissions from one to seven pages being accepted. For those who wish to write full papers in journals, we have arranged special issues of the Journal of Neuroscience Methods and Frontiers in Psychology. Some of the individual symposia also offer the possibility to publish in special issues as well. 6. Interesting keynotes We are fortunately to have three very interesting professors giving keynote speeches. Frederic Dehais studies flight safety and he will give a talk about neuroergonomics: monitoring the brain in complex real-life situations. Chris de Zeeuw will bring us up to date on the latest techniques for measuring learning and memory. Liesbeth Zandstra will present about going from food perception to behavior. Please note that Measuring Behavior 2020 has been rescheduled to May 18-20, 2022 and will take place online. Check www.measuringbehavior.org for the latest news or to subscribe to the mailing list. --- ## Examples of Animal Behavior Research URL: https://noldus.com/blog/examples-animal-behavior-research Published: 2022-02-18 11:00:00 Description: Researchers in ethology are interested in understanding all aspects of animal behavior. We have highlighted some great examples of Animal Behavior Research on our Behavioral Research Blog. Animal behavior research can involve a wide range of animal species and research subjects. In ethology, animal behavior is studied under natural conditions. Ethology has its roots in the scientific work of Charles Darwin (1809-1882), as well as Dutch biologist Nikolaas Tinbergen (1907-1988). Ethology combines laboratory and field science, and also has strong relations to other disciplines, such as neuroanatomy, ecology, and evolutionary biology. Researchers in this field of study are interested in understanding the functions, causes, development, and evolution of animal behavior. Examples of Animal Behavior Research In this blog post we describe several examples of animal behavior research. Want to read even more? Please visit our Behavioral Research Blog! Table of contents - 1.Observing monkey behavior - 2.Interactive enrichment for great apes - 3.Behavioral observation of new zoo habitat for elephants - 4.Neuroscience research with guinea pigs - 5.Domesticated vs wild animals - 6.Chicken welfare - 7.Spatial behaviors in sheep - 8.A rat model for Parkinson's disease - 9.How to monitor rat social behavior - 10.Spatial learning in rats - 11.How fruit flies find your food - 12.Zebrafish studies - 13.Studying shrimp feeding behavior - 14.Measuring aggressive behavior in dolphins Observing monkey behavior and their use of tools We already know some monkeys display above average intelligence. Behavioral studies have shown that capuchin monkeys use tools such as boulders and logs as anvils upon which they can crush nuts. Fragaszy et al. studied a group of wild capuchin monkeys in Brazil, specifically the placement of nuts prior to striking them. An interesting detail: they studied this same behavior in humans as well. Keep reading: Observing monkey behavior – cracking the nut Interactive enrichment for great apes There is growing empirical support demonstrating improved welfare in captive animals when they can exert control over their environment. Research shows that great apes can successfully interact with digital media devices and can demonstrate behavioral changes when presented with digital enrichments. Nicky Kim-McCormack and her colleagues from Australian National University studied the effects of digital enrichment on animal welfare. They included Seoul Zoo's six orangutans and four chimpanzees in their study. Continue reading: Measuring changes in captive great ape welfare Behavioral observation of new zoo habitat for elephants The Oregon Zoo (Portland, OR, US) houses a herd of 5 Asian elephants. The zoo wanted to improve their welfare with evidence-based approaches. This meant creating a complex new habitat and monitoring the elephants closely by measuring hormone levels, activity, and behavior before, during, and after construction. They used The Observer XT behavioral analysis software to monitor the transition of the elephant herd to their new zoo habitat at the Oregon Zoo. This study, recently described in Animals, is a great example illustrating why behavioral observation matters. Continue reading: Behavioral research shows how elephants like their new habitat at the Oregon Zoo Photo: Oregon Zoo Neuroscience research with guinea pigs According to Kiera-Nicole Lee and her colleagues, guinea pigs differ from mice and rats, and that just might make them more suitable for some neuroscientific studies. This is due to the fact that results from studies with guinea pigs are more easily translated to humans. Find out more: Why guinea pigs are just like us Domesticated vs wild animals Not many studies have compared the behaviors of wild and domesticated animals. When they do, such as with guinea pigs, they mostly compare adults. Zipser et al. were curious to find out whether the differences in behavior between domesticated guinea pigs and the wild cavies were also found earlier on, and so they compared these species during the early and late phase of adolescence. Read more: How wild cavies and domesticated guinea pigs differ Chicken welfare There are almost 100 million chickens in the Netherlands — that's about 17 times as many chickens as people. Their welfare has improved enormously in the past few years, but there is still plenty of room for improvement. In the ChickenStress project, we work with different partners to improve chicken welfare and reduce problems like feather pecking. Read more: Research aims of the ChickenStress project Spatial behaviors in sheep The study of movement, activity, and behavior is valuable in research on animal health and welfare, specifically in livestock research. Understanding animal behavior in different environments provides insights that can help improve their living conditions. There is still a lot to learn about the behavioral and social patterns in sheep. At the Aberystwyth University in Wales, UK, researchers used TrackLab for tracking and detailed analysis of spatial behaviors in sheep. Tracking sheep to learn their behavior. FREE DEMO Try TrackLab yourself! Request a demo to obtain real-time insights into the activity, welfare, and health of your livestock. - Accurate tracking data - Gain insights into many parameters - Easily access, export, and analyze data Free Demo A rat model for Parkinson's disease Parkinson's disease is a neurodegenerative disorder that affects mobility in a life-changing way. Slow movement, shuffling of the feet, and difficulties initiating movement are all impairments we recognize as typical for this disease. Researchers Jordi Boix and his colleagues, from the University of Auckland in New Zealand, used two rat models to investigate a number of gait parameters. Their aim was to find resemblance to human symptoms, and to specifically find them early on. Read more: Using gait analysis in research on Parkinson's disease How to measure spatial learning in rodents: 5 proven ways Spatial learning basically refers to the association or representation of an organism in a three-dimensional environment. If we translate this to basic animal research terms: An animal learning its position in a given space. This task highly relies on visual cues and/or landmarks, whether in humans or animals. Why is it important and how do we measure it? Here we dive into 5 different behavioral tests that specifically measure spatial learning and memory in rodents. How to monitor rat social behavior Monitoring and analyzing the social behavior of group housed rodents is something that many researchers find extremely challenging. It can also be very time consuming. However, including social behavior as part of a phenotypic screen has important benefits, and eventually leads to better translational value of rodent models. During her PhD research, Suzanne Peters developed an automated analysis that allows for the monitoring of socially interacting rats. Read more: Into the lab: how to monitor rat social behavior A recent study by Bartal et al drove our curiosity to write this blog about altruistic behavior in rats. This study shows how this type of behavior is neurally linked to the social functioning of humans. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial How fruit flies find your food (and mates!) Those tiny flies that take over your garbage cans in the summer? They are called fruit flies for a reason! They have a fantastic sense of smell. Drosophila melanogaster (or fruit flies) are a popular animal model for researchers, because they have a fairly similar genetic makeup to our human genome, and they are easily manipulated to create genetically different strains. For neuroscientific studies, this makes them a really good model to learn about the effects of genes on behavior. Find out what researchers discovered about fruit flies and their smell. Zebrafish studies The zebrafish has become an important vertebrate model to study (developmental) neurobiology and behavior, not in the least because of recent improvements in transgenic, optogenetic and imaging techniques, and behavioral assays. More and more studies with zebrafish are conducted. Some examples: - A new zebrafish model for ALS-related gene mutations - How to measure complex exploratory behavior in larval zebrafish - How optogenetics is used to study the stress response in zebrafish larvae - Social buffering in zebrafish - Strain differences in zebrafish behavior and physiology - Studying zebrafish behavior using video tracking software FREE DEMO Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free Demo Studying shrimp feeding behavior Shrimp is a popular dish, and these crustaceans are a very large part of commercial aquaculture. Especially Pacific white-leg shrimp, as they grow fast and are able to adapt to a wide range of environments. Finding the optimal way to feed shrimp can make or break profitable farming. This is why investigating the best feeding protocols has gained more interest lately, and a big part of that is looking at feeding behavior. In fact, understanding the basics of shrimp behavior is a crucial fundament to the refinement of feeding practices. Learn more about studying shrimp feeding behavior and why it's important for aquaculture. Using the Observer XT to measure aggressive behavior in Dolphins Atlantic spotted dolphins (Stenella frontalis) and bottlenose dolphins (Tursiops truncates) are a sympatric species, meaning they are very closely related while also inhabiting the same geographic region, in this case, the northern Bahamas. These species are known to travel and forage together but they also engage in aggressive interactions. Volker and Herzing, from the Florida Atlantic University, recently published an article in 'Animal behavior and cognition' on aggressive interactions between dolphins. References - Lee, K.-N.; Pellom, S.T.; Oliver, E.; Chirwa, S. Characterization of the guinea pig animal model and subsequent comparison of the behavioral effects of selective dopaminergic drugs and methamphetamine. Synapse, accepted article, doi: 10.1002/syn.21731. - Zipser, B.; Schleking, A.; Kaiser, S.; Sachser, N. (2014). Effects of domestication of biobehavioural profiles: a comparison of domestic guinea pigs and wild cavies from early to late adolescence. Frontiers in Zoology, 11, 30. - Boix, J.; von Hieber, D.; Connor, B. (2018). Gait Analysis for Early Detection of Motor Symptoms in the 6-OHDA Rat Model of Parkinson's Disease. Frontiers in Behavioral Neuroscience, 12, 39. - Capriello, T.; Consiglio Grimaldi, M.; Cofone, R.; D'Aniello, S.; Ferrandino, I. (2019). Effects of aluminium and cadmium on hatching and swimming ability in developing zebrafish. Chemosphere, 222 (2019), 243-249. - Kim-McCormack, N.E.; Smith, C.L.; Behie, A. M. (2016). Is interactive technology a relevant and effective enrichment for captive great apes? Applied Animal Behavioural Science, 185, 1-8. - Fragaszy, D.M.; Liu, Q.; Wright, B.W.; Allen, A.; Welch Brown, C.; Visalberghi, E. (2013). Wild bearded capuchin monkeys (sapajus libidinosus) strategically place nuts in a stable position during nut-cracking. PLOS ONE, 8 (2), e56182. - Volker, C. L.; Herzing, D. L. (2021). Aggressive Behaviors of Adult Male Atlantic Spotted Dolphins: Making Signals Count during Intraspecific and Interspecific Conflicts. Anim. Behav. Cogn., 8 (1), 35–51 --- ## What is simulation-based training? URL: https://noldus.com/blog/what-is-simulation-training Published: 2022-02-14 09:00:00 Description: Simulation-based training provides learners with an opportunity to test out different scenarios to see what works and to understand how they arrived at the right and wrong answers. The word "simulation" implies an imitation of a real-life process in order to provide a lifelike experience in a controlled environment. It can be thought of as somewhere to learn from mistakes without doing any damage. What is simulation-based training? Simulation trainings are used as a tool to teach trainees about the skills needed in the real world. Simulation-based training replicates real-world scenarios for immersive, risk-free practice. It helps learners refine skills, build confidence, and make better decisions, bridging theory and practical application effectively. This provides a lifelike point-of-care learning experience, and has been widely applied in fields such as aviation, the military, and healthcare. The added value of simulation-based training A well-constructed simulation allows trainees to answer the question, "If I do this, what happens?" It provides learners with an opportunity to test out different scenarios to see what works and to understand how they arrived at the right and wrong answers. This trial-and-error approach gives trainees the knowledge and confidence they need to apply their new skills in the real world. The value of simulation training is further enhanced by following up with a debriefing and coaching session. With the help of video recordings, the training sessions can be analyzed, errors identified, successes marked, and emotions or feelings that influenced the trainees can be discussed. This is when the real learning takes place. Five reasons why simulation training in healthcare works The highest goal for every healthcare worker is to improve the quality of a patient's life and to ensure patient safety. Training simulators and simulation-based training can achieve that for the following reasons: 1. Practicing in a safe environment Training simulators are an invaluable tool when it comes to teaching and training. They provide a realistic, interactive learning environment with real-world scenarios that can help enhance the educational experience. In a simulation facility, preferably in a real clinical area where the staff normally works, you can test new tools and methods, focus on crisis resource management, and develop knowledge, skills, and attitudes in a safe and secure environment. It is important for the trainees to be assured that the simulations are confidential, and that video recordings are private. 2. Understanding human behavior Simulating events show us how we react in real life situations, and in some sense, show us how unconscious processes work. Since it is not occurring in real life, it enables us to learn from our mistakes. As such, it can help prevent errors and optimize responses in (critical) situations. For example, noise, a bad smell, or other disturbances can be simulated, and can give a good feel for how distraction works. In the experimental study conducted by Jessica Jones and her colleagues, the researchers examined the impact of clinical interruptions on simulated trainee performances during central venous catheterization (CVC). They found that interruptions during the experimental condition resulted in a number of serious procedural errors. The reduction in performance, time taken, and number of attempts made was significantly worse when the interruption occurred during a more complex part of the procedure. 3. Improving teamwork Teamwork includes behaviors such as effective communication, collaboration, team leading, team building, and crisis resource management. Teamwork is not an automatic consequence of placing people together in the same room; it depends on a willingness to cooperate toward shared goals. In healthcare, shared goals might include maintaining a patient's health status and avoiding errors. In a simulated environment, teamwork can be studied and significantly improved by training specific teamwork skills. 4. Providing confidence Simulation training provides an opportunity to apply theory and gain experience in skills or procedures, which provides trainees with the confidence to manage similar real-life scenarios. Confidence is directly linked to competence. For example, the robust communication skills needed when interacting with patients requires being able to handle the situation with confidence. As trainees gain confidence, they are more comfortable in making their own decisions and exerting their autonomy. As well as confidence being essential for an individual, demonstrating confidence is important for the patients who have put a lot of trust in healthcare professionals. 5. Giving insight into trainees' own behavior In a simulation facility, you can record the training sessions on video. By expanding the video recording with an eye tracker or data acquisition system to measure eye gaze behavior or physiological responses of the trainees, even more insight into behavior can be gained. Immediately after the session, the video recordings can be shown with all other data during debriefing, giving a complete picture. Using realistic scenarios For years, simulation-based training uses mannequins, i.e. fully bodied patient simulators for safe training of technical medical skills. Adding an immersive room to a simulation-based training enhances the lifelike experience even further. By projecting a scene on three surrounding walls, it actually feels like you are in that scene. The experience is complete by adding elements such as smell and temperature. Transform a team of experts into an expert team Clearly, the major role of simulation is to educate, train, and provide rehearsal for those actually preparing for or working in the delivery of healthcare. Simulation-based training can transform a team of experts into an expert team. The user-friendly software suite Viso is an ideal recording solution for simulation training. With Viso, recordings are easily captured, and immediate viewing facilitates debriefing after each scenario. FREE WHITE PAPER Simulation-based training Simulation-based training is an important part of the development and learning process of knowledge and skills. - 5 reasons why - Practical examples - Innovative solutions Get your copy instantly Interested in human behavior research? Also read: 'How to study human behavior'! References - Training simulation - Wikipedia - Gaba, DM (2004). The future vision of simulation in health care. Qual Saf Health Care 2004;13 (Suppl 1):i2–i10. - Jones, J.; Wilkins, M.; Caird, J.; Kaba, A.; Cheng, A. & Ma. I.W.Y. (2017). An experimental study on the impact of clinical interruptions on simulated trainee performances of central venous catheterization. Advances in Simulation, 2 (5). - Weaver, S.J.; Dy, S.M.; Rosen, M.A. (2014). Team training in healthcare: a narrative synthesis of the literature. BMJ Quality & Safety, 23, 359-372. - Wang Z, Liu Q, Wang H. Medical simulation-based education improves medicos' clinical skills. J Biomed Res. 2013; 27(2):81–84. --- ## 7 ways to continue your research from home URL: https://noldus.com/blog/7-ways-to-continue-research-from-home Published: 2022-02-10 10:00:00 Description: We have gathered lots of ideas and ways to facilitate working from home and to continue research projects. In this blog post, we will list these seven approaches for you. In the past two years, many of us have become accustomed to working from home due to the COVID-19 pandemic. During this period, we have gathered lots of ideas and ways to facilitate working from home and to continue research projects. In this blog post, we have listed seven approaches for you. 7 ways to continue your research from home 1. Remotely access the coding and analyzing software As a researcher, you may still have a large database of videos that have not yet been annotated or analyzed. Or perhaps you have some other or even new research questions drawn up which you want to answer with the data that were collected in the past. It is possible to continue your video annotation, data analysis and/or facial expression analysis work remotely. Both The Observer XT and FaceReader support software-based licensing, which ensures that no hardware key is needed to access the software. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial 2. Online facial expression analysis Capturing emotions by analyzing facial expressions offers additional and objective insights into the impact, appreciation, liking and disliking of products, websites, commercials, movie trailers, and so on. When your research is about measuring emotions, you can continue your study by inviting participants all over the world via FaceReader Online! With FaceReader Online you can take tests remotely while participants can stay at home and watch your video(s) at a time convenient to them. This allows you to incorporate a much larger number of participants and still get direct insight into user responses.  Besides, you can integrate the test in your favorite survey tool. FaceReader Online will analyze all (pre-)recorded videos automatically in the cloud and results become available just minutes after the participant has finished the recording. FaceReader Online is a cloud-based solution, based on Microsoft Azure architecture, offering you a safe, scalable, and reliable solution. 3. Streaming videos What can you do if you want to conduct your research with research fellows located elsewhere? How can you join your efforts and watch a video together? For example, when students need to practice skills, but as a teacher you cannot be present at the site? An option is to make a video of the participants or students with Viso and stream it to YouTube. While they do the training, you can observe them from another room or location. You can even invite a fellow teacher or researcher to watch from a different location, so that you both watch the training video, while it is being recorded. Meanwhile, the safety of the Viso system makes sure the videos are securely recorded on site. After the training, you can debrief the recorded sessions with the students in a similar way, from your home, using the debriefing in Viso and streaming the video to YouTube for the students to learn from. 4. Be ready for Post-Corona: Grant Assistance Program While you might still be homebound, this is the perfect time to prepare for your post-corona research and make sure you have the funding to restart your lab. Your success in securing funds is vital for the progression of your research. We realize that grants—public, private, large or small—are the lifeblood of research. Let us help you with your grant applications! With over 30 years of experience, we’re more than happy to help you locate and secure your next grant. We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to the researcher! 5. Watch our webinars live and on-demand From the moment we were all hit by the pandemic, we started to significantly increase our number of webinars. Through these webinars, 30-minute talks, technical briefings, and virtual meet-ups we share our expertise and show you how our innovative tools can help you do your research. Also, the sessions offer the possibility to connect with Noldus employees, industry experts, and most importantly, one another. By participating, you can expand your knowledge and ask questions to the experts in the Q&A. Good to know: All webinars and online events from the last two years are still available for you to watch whenever you like. Watch live or replay our webinars at your convenience! 6. Free one-hour training courses This may be a good time to familiarize yourself with the latest version of FaceReader or The Observer XT. We are offering a free one-hour remote walkthrough to all users with a current NoldusCare subscription. Please contact us to arrange this training. In addition, The Observer XT provides you with clear video tutorials in the software itself that will guide you through every step of your research process.  You can also find many demo's, instruction-, and product videos on our YouTube channel. It is definitely worth checking out!  7. Lab experiments during COVID-19 Are you going to pick up research with human participants again? Offer safety and hygiene for your participants in your corona-proof lab before, during, and after the experiment. How? What needs to be done differently? What should you pay extra attention to and how to accomplish that?  Read some useful tips in the post on our Behavioral Research Blog: https://www.noldus.com/blog/research-human-participants-covid-19 Stay ahead in behavioral research! Subscribe to Noldus Newsline - Discover innovations – Be the first to know about new tools and software to advance your research and get insights that help you stay ahead. - See real research in action – Get inspired by real-world studies from our community, discovering fresh approaches for your work. - Access exclusive perks – Receive early updates on promotions, product releases, and events crafted for you. Subscribe Now arrow_forward --- ## Unobtrusive observations URL: https://noldus.com/blog/unobtrusive-observations Published: 2022-02-08 10:00:00 Description: Would you like to learn more about how to build an AudioVisual lab? Check out this ‘how to’ guide! Read tips & tricks to learn more! A question researchers ask themselves is: Where and how should we observe test participants in order to collect reliable data? Unobtrusive observation is seen as a reliable and effective method. Comparing it with participant observation, it is seen as more effective because the observer's presence could influence the situation. Observation lab with ceiling cameras An observation lab is designed to allow researchers to observe test participants unobtrusively, in an environment similar to natural surroundings like a living room, kitchen or office space. Of course, test participants first give written permission to participate in the test and allow researchers to make recordings. Portable lab set-ups For some participant groups, for example elderly living in a nursing home, transfer to a stationary lab can be stressful or even impossible. In these situations, a portable observation lab would be ideal. An empty office space or the communal area can be turned into a lab in no-time. How to build an AV lab? Stable images, high quality video recordings, and clear recordings of speech and other sounds make all the difference in your data analysis and research results. Would you like to learn more about how to build an AV lab, so you can perform unobtrusive observations? Check out our 'how to' guide! Read tips & tricks to learn more! How to build an observation lab? To get off to a good start, it is best to describe the research or tests that are going to be performed in great detail. With this description it becomes clear what kind of equipment will be needed and which physical environment would best suit this test or research. In general, the description should answer questions such as: - How many participants need to be recorded at the same time? - Do participants need to walk around in the lab? - What kind of participants are observed? Realize that for children different camera positions may be needed than for adults. - Are participants being invited to visit the lab? Is on-site research going to be performed? Or both? - Do participants need to work at a computer, do they need to drink or eat, or play with toys? - Where and in which room(s) should the lab be built? Download the white paper and discover which requirements you should take into account when building an observation lab. Because you have to deal with many choices, this 'how to' guide will support you in overseeing the entire process. FREE WHITE PAPER How to build an AV lab Do you want to learn more how to set up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download The Observer XT event logging software Many different types of observations have in common that one or more participants are observed and that important events are written down or coded in event logging software. Customer success story Please watch the video of one of our customers and discover how The Observer XT is the right solution for gathering data and coding and describing behavior in an accurate and quantitative way. Marie Bocquillon uses two labs, an observation lab, where trainee teachers are videotaped while giving a lesson to their peer students, and an interaction lab, where the video feedback sessions takes place. --- ## Studying zebrafish behavior using video tracking software URL: https://noldus.com/blog/zebrafish-video-tracking Published: 2022-02-07 11:00:00 Description: When it comes to studying zebrafish behavior, video tracking software is the ideal tool. Here we highlight five recent posts about studies on zebrafish behavior where researchers applied video tracking software. When it comes to studying zebrafish behavior, video tracking software is the ideal tool. Every aspect of zebrafish behavior, in both adults and larvae, is easily measured using EthoVision XT video tracking software with additional tools like DanioVision and aquatic mazes. These aspects include social interaction, anxiety-like behavior, exploration, swimming patterns, or just general activity. Studying zebrafish behavior using video tracking software In this blog post we highlight five recent posts about studies on zebrafish behavior where researchers applied video tracking software. Want to read even more? Please visit this interesting page of our Behavioral Research Blog.  Table of contents - Attracting zebrafish with 2D images - All zebrafish are different - What is DanioVision? - Zebrafish exposed to cannabinol - Zebrafish create insight in neurological diseases LABEL Title Learn more LABEL Title Learn more RESOURCES: Read more about DanioVision Find out how DanioVision is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts  Resources LABEL Title Learn more LABEL Title Learn more References - Lenzi, C.; Ciobîcă, A.; Nicoară, M.; Plăvan, G.I.; Curpan, A.S.; Timofte, D.; Strungaru, S.A. (2020). Shoaling preference and social partner selection – behavioral, metabolic and psychiatric relevance in a zebrafish (Danio rerio) study. Bulletin of Integrative Psychiatry, doi: 10.36219/bpi.2020.4.06. - Fitzgerald, J.A.; Tulasi Kirla, K.; Zinner, C.P.; Berg, C.M., vom (2019). Emergence of consistent intra-individual locomotor patterns during zebrafish development. Scientific Reports, 9, 13647 - Chousidis, I.; Chatzimitakos, T.; Leonardos, D.; Filiou, M.D.; Stalikas, C.D.; Leonardos, I.D. (2020) Cannabinol in the spotlight: Toxicometabolomic study and behavioral analysis of zebrafish embryos exposed to the unknown cannabinoid. Chemosphere, 252, 126417. - Fu, J.; Gong, Z.; Kelly, B.C. (2018) Metabolomic profiling of zebrafish (Danio rerio) embryos exposed to the antibacterial agent triclosan. Environmental Toxicology and Chemistry, 38(1), 240-249. - Capriello, T.; Consiglio Grimaldi, M.; Cofone, R.; D'Aniello, S.; Ferrandino, I. (2019). Effects of aluminium and cadmium on hatching and swimming ability in developing zebrafish. Chemosphere, 222, 243-249. - Chin-Chan, M.; Navarro-Yepes, J.; Quintanilla-Vega, B. (2015). Environmental pollutants as risk factors for neurodegenerative disorders: Alzheimer and Parkinson diseases. Frontiers in Cellular Neuroscience, 9, 124. - Jomova, K.; Vondrakova, D.; Lawson, M.; Valko, M. (2010). Metals, oxidative stress and neurodegenerative disorders. Molecular and Cellular Biochemistry, 345(1e2), 91e104. --- ## 5 blogs on why you should use video tracking in behavioral research URL: https://noldus.com/blog/why-use-video-tracking-behavioral-research Published: 2022-02-04 08:00:00 Description: In this blogpost you can find an overview of our top 5 favorite blogs on why you should use video tracking in your behavioral research. Video tracking in behavioral science can be used in a variety of studies. Video tracking means detecting an animal in a video file or from a live video feed, distinguishing it from its background, and tracking its whereabouts and movements. With our EthoVision XT we created a software that fits the bill for all of your experiments.  5 blogs on why you should use video tracking in behavioral research EthoVision XT is used in over 10,000 publications, which of some, we wrote blogs about. In this blog you can find an overview of our top 5 favorite blogs on why you should use video tracking in your behavioral research. 1. EthoVision XT video tracking software in combination with the radial arm maze For over 40 years, the radial arm maze has been used extensively for memory testing in a variety of conditions. This includes the effects of psychoactive drugs and medication, as well as research into behaviors related to autism spectrum disorder and brain injury. It has also been used to characterize basic functions of the brain’s various centers of memory function and individual differences in cognition between animals.  The radial arm maze often is used in combination with our video tracking software: EthoVision XT. In this blog you can read more about the use of the radial arm maze in combination with EthoVision XT and how well it works to analyze spatial memory, working memory and reference memory. RESOURCES: Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! Learn more 2. How video tracking makes or breaks profitable shrimp farming Shrimp lover? Then you might like to know more about the Pacific white-leg shrimp, since these crustaceans are a large part of commercial aquaculture. The downside of these shrimps is that they can be slow feeders, which has a lot more consequences than you might expect. Leftover food is not only a waste of money, but it also contaminates the water.  In this blog you can read about a publication of Bardera and colleagues (2020, Aquaculture) and how they introduced video tracking with EthoVision XT to shrimp behavior research. With 27 shrimp, they tested feed attractability of three experimental diets with different theoretical levels of attraction.  LABEL Title Learn more 3. Diazepam in the battle against Alzheimer’s disease Did you know that Diazepam can help in the battle against Alzheimer’s disease (AD)? Researchers from the University of Latvia do! They have found that low doses of diazepam (0.05 mg/kg – 1 mg/kg) reduce the decay of neurons in rats induced with AD. To study spatial memory, these researches used the Morris water maze test, a common test in behavioral neuroscience.  In combination with EthoVision XT video tracking software, this test can easily confirm spatial memory in rats that are induced with AD. Read everything about the test and its outcome in this blog.  LABEL Title Learn more 4. Why use a Y-maze in combination with video tracking?  Like the name suggests, the Y-maze is shaped as a Y, consisting of three arms of the same length positioned at 120 degrees to each other. The Y-maze is often used to investigate spatial learning and memory in rodents. With this test, the animal can learn to get a reward by choosing the correct arm of the maze, or show its preference for a certain type of environmental cue, if it recognizes a novel environment, etc. With EthoVision XT, the nose, center, and tail base of rats and mice is automatically detected and tracked in the Y-maze.  In the latest version of EthoVision XT 16, a deep learning algorithm was introduced for very accurate detection of these body points. This is a very useful feature for tests such as the Y-maze, because only when all body points are detected in a specific arm, this counts as an entry. Curious on what can be tested in a Y-maze and how the EthoVision XT comes in handy? Read this blog! LABEL Title Learn more LABEL Title Learn more 5. EthoVision XT and the open field test  Imagine you are dropped in the center of a wide open field. Would you explore the entire area? Or hunker down around the edges, fearing predators and other unknowns? Your internal state probably impacts how you respond in this situation.  With the open field test, differences in behavior in groups of animals exposed to, for example, a negative environmental stimulus can be tested and compared to a control group. This is a labor-intensive test for researchers. That’s where EthoVision XT video-tracking software comes in handy. Click here to learn more on how the video tracking software can be a great tool to track and analyze data in the open field test. Are you ready to use video tracking in your own research? FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more --- ## Zebrafish attracted to superfish: video tracking sex differences in shoaling URL: https://noldus.com/blog/video-tracking-sex-differences-zebrafish-shoaling Published: 2022-01-18 15:00:00 Description: Are images enough to evoke a shoaling response in zebrafish? Do males and females respond differently to shoals or the opposite sex? A recent study finds out. Social behavior is disrupted in a number of psychiatric disorders and disabilities. In an attempt to develop therapies and treatments, we need to find out more about the biological underpinnings of these behaviors and how they are disrupted. Social genes We know that rats, mice, and even zebrafish are genetically similar to us in many ways. I wrote about a mouse model for macrencephaly/autism last week, a study that showing promising results for late intervention therapies. This week, we will focus on zebrafish – like rats and mice, very social animals. They show clear social preferences, shoaling attraction, and even copy each other’s motions. How animals communicate Let’s take a look at social cues. We know that chemical communication is important for zebrafish. Females produce pheromones and males are attracted to them. Visual communication is another very important aspect, and one that is easily manipulated in a variety of ways. Researchers have done so in many studies. LABEL Title Learn more Animated social stimuli Almost ten years ago I wrote about social aspects of zebrafish behavior. Here I highlighted the work of Saverino and Gerlai from 2008, an interesting study using a video screen to project computer animated images of zebrafish, investigating the influence of color, size, and patterning of the fellow zebrafish on social interaction.   Still images of conspecifics Recently, Dr. Lenzi and his colleagues show that you do not necessarily need a computer animation to trigger social behavior. In their study, non-moving 2D images of conspecifics were enough to induce shoaling attraction in zebrafish, and even differentiate the behavioral responses in male and female subjects.  LABEL Title Learn more Superfish The aim of Dr. Lenzi’s study was to see how both male and female adult zebrafish would respond to superstimuli – photoshopped images of male and female stimuli fish with exaggerated features. They wanted to see if this would be enough to evoke a response and validate the existence of sex-dependent discrepancies regarding shoaling preferences. The superstimuli fish were created from pictures of a normal male and female zebrafish. With the magic of graphics, they enlarged the abdomen of the female to signify an egg-bound condition. The super male got an enlarged caudal fin as the researchers hypothesized this would make them more attractive to the females. In addition to the normal size superfish (4 cm), smaller superfish of 2.5 cm were created. All images were fixed to the testing arena, one at each end in different combinations per trial. T-maze video tracking The testing arena was adapted from a multifunctional cross maze into a T maze. The top area was closed off by a panel and conveniently used to put an aerator to maintain a constant oxygen concentration.   Read more: Are you planning on running several behavioral tests with adult zebrafish? A range of setups is possible, such as: Learn more Testing protocol During testing, the subject male or female zebrafish was placed at the starting point; the bottom of the T. After a bit of habituation, it got the chance to explore the maze for four minutes, and researchers used EthoVision XT video tracking to monitor interest (time spent) in either arm displaying the superfish in the following manner: - Trial 1: Big female vs 3 big females - Trial 2: Big female vs small female - Trial 3: Big female vs small male - Trial 4: Big female vs big male - Trial 5: Big male vs small male Preference to shoal When given the choice between one or more superfemales… well, that was not much of a choice. All fish spend more time with the picture of three, which makes sense because zebrafish generally prefer to shoal with larger groups. Interestingly, size did not seem to matter that much to them. In both the second and third tests, there were no significant differences found. In the fourth test, females wanted to side with their own, as they preferred the female over the male stimulus. Males did not show a preference. In the last test, females preferred a the big supermale over the smaller supermale, but males did not show a preference. LABEL Title Learn more Sex differences Generally speaking this study shows that males were less selective in their shoaling preference than females. But I think the most interesting part about this study is that these non-moving 2D images of stimuli fish were enough to induce shoaling attraction and discriminate certain preferences. This provides a nice fundament for future studies, because this methodology is relatively easy and endlessly adjustable way to test social preferences and behavior in adult zebrafish. References - Lenzi, C.; Ciobîcă, A.; Nicoară, M.; Plăvan, G.I.; Curpan, A.S.; Timofte, D.; Strungaru, S.A. (2020). Shoaling preference and social partner selection – behavioral, metabolic and psychiatric relevance in a zebrafish (Danio rerio) study. Bulletin of Integrative Psychiatry, doi: 10.36219/bpi.2020.4.06. - Saverino, C.; Gerlai, R. (2008). The social zebrafish: Behavioral responses to conspecific, heterospecific, and computer animated fish. Behavioural Brain Research, 191(1), 77-87. --- ## Environmental enrichment rescues autistic-like behaviors in mice URL: https://noldus.com/blog/environmental-enrichment-rescues-autism-mouse-model Published: 2022-01-11 13:00:00 Description: A recent mice study from The Scripps Research Institute shows that behavioral therapy might still be successful in later diagnosis of ASD with macrocephaly, laying groundwork for successful late interventions. As we know, Autism Spectrum Disorder (ASD) has no cure. There is no pill to take to make it go away, but there are several behavioral therapies that seem to help people with varying degrees of autism. Early diagnosis of autism Generally, behavioral therapy is most effective when started early. The sooner the better, so early diagnosis of ASD is important. Unfortunately, many children are diagnosed when they are a couple of years old. By that age, neuro-anatomical abnormalities are already established, and behavioral therapy might be less effective. Groundwork for effective therapy A recent study done by a group of researchers at The Scripps Research Institute (Florida) gives new hope. Using a mouse model, they show that multi-modal intervention can at least partially rescue the behavioral abnormalities. These are promising results, laying the groundwork for the development of new effective therapies, even in late ASD diagnosis. Brain overgrowth and ASD As we know, autism is a spectrum disorder with varying degrees of severity. A subset of ASD patients presents with macrocephaly and megalencephaly, meaning that they have overgrowth of the head and brain. These people have a genetic PTEN mutation. The research group at The Scripps Research Institute used a Pten+/- mice strain as a model for the PTEN mutations in macrocephaly/autism syndrome. They previously found that these mice show social and repetitive behavior deficits and brain overgrowth. LABEL Title Learn more Environmental enrichment The environment one is raised in and experiences in life can have effect on how the brain develops. So this research group was interested in finding out if environmental enrichment and play sessions might help with behavioral deficits in this mouse model. More specifically, they wanted to test this after the brain overgrowth was already established, to see if ‘behavioral therapy’ could still alter the phenotype after neuro-anatomical changes were hard-wired. Mutated and wild type mice were reared in groups in either standard cages or enriched cages. The latter group was also exposed to daily play sessions in another area. Several tests for social and repetitive behavior were done, as is typical in ASD research. Social approach Researchers started with a 3-chambered setup to investigate social approach. Mice were given the choice between spending time in a chamber with or without a same-sex stimulus mouse confined to a small cage. EthoVision XT video tracking was used for automatic measurement of the time spend in each chamber, distance from social stimulus, and distance traveled. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more Interestingly, only female Pten+/- mice raised in standard cages showed significantly less social preference than the control mice did. Raising them in an enriched environment completely restored their social interest. Social recognition The 3-chambered arena was also used to test for social recognition, using a so-called habituation/dishabituation procedure. In consecutive trials, the stimulus mouse from the previous test was presented four times in a row. The fifth time, a novel mouse was used. Most mice show normal habituation in this test, getting used to the stimulus mouse and showing less interest over trials. Pten+/- males did too, but interestingly they showed no dishabituation, not recognizing that the last stimulus mouse was new to them. This ‘deficit’ was corrected when these males were raised in an enriched environment. Marble burying Next up was the marble burying test, in which mice got 30 minutes and 20 black marbles at their disposal. Marbles that were buried at least 2/3 into the bedding were counted as a measure for repetitive behavior. From previous studies, researchers knew that the male Pten+/- mice would probably show increased repetitive marble burying, and that the females with this mutation would not. And indeed, they met expectations. Here, raising these males in an enriched environment saved the phenotype, normalizing their behavior. LABEL Title Learn more Rescue of phenotype In this study, the environmental enrichment and play sessions show to have the potential to at least partially rescue the behavioral phenotype of decreased social behavior in Pten+/- females and decreased repetitive behavior in Pten+/- males. Restoration of protein balance So how about the neuroanatomical changes? The increased brain size of Pten+/- mice stayed the same, regardless of how they were raised. But environmental enrichment did have another important effect. Researchers found that in Pten+/- mice the balance between specific inhibitory and excitatory proteins in the frontal cerebral cortices was off, and that this effect was partially reversed by raising them in an enriched environment. Differences between males and females The impact of environmental enrichment differs between males and females. This is something researchers were not surprised about given their previous experiences with the sexual dimorphic character of Pten mutation lines. Benefits from late intervention This study shows that, although some neuro-anatomical changes were set, changes in the brain are still possible and autistic-like behavior was ‘normalized’ by subjecting mice to multi-modal interventions. These results give hope for late intervention therapies in human ASD patients. It provides great groundwork for further study into the mechanisms behind the effects of behavioral therapy. Reference Clipperton-Allen, A.E.; Zhang, A.; Cohen, O.S.; Page, D.T. (2021). Environmental Enrichment Rescues Social Behavioral Deficits and Synaptic Abnormalities in Pten Haploinsufficient Mice. Genes, 12, 1366. --- ## Early infant behavior development of hand preference URL: https://noldus.com/blog/measuring-hand-preference-infancy Published: 2022-01-11 12:54:00 Description: There are many reasons to study the development of hand preference in infants. For one thing, being left-handed can be an advantage in one-on-one sports such as tennis. The development of hand preference In learning about objects and their parts, transporting objects to new locations, and sharing objects with others, the hands are essential. Infants discover how to control each hand and how to use the hands together. They learn to distinguish the left and the right side of the body. The cooperation between the two halves of the body becomes more and more coordinated. Eventually a hand preference develops: the preferred hand performs the fine motor actions and the other hand assists. Why measure handedness There are many reasons to study the development of hand preference in infants. For one thing, being left-handed can be an advantage in one-on-one competitions, in sports such as tennis, baseball, and combat sports. For example, Rafael Nadal is a left-handed player and with this natural advantage, he became a star tennis player with many successful matches to his name.  The advantage being in a population with a left-handed minority and a right-handed majority, the left-handed Rafael Nadal plays most of his matches against right-handed opponents and is therefore well-practiced at dealing with this asymmetry. A right-hander plays the majority of his matches against other right-handers. In conclusion, when confronted with left-handers, they are less practiced, thereby giving the lefty a natural advantage. How to measure handedness in infancy The research team of Eliza Nelson presented “Unimanual to bimanual: Tracking the development of handedness from 6 to 24 months”. One of their findings was that, as infants, 39% of these children showed preference for the right hand, whereas 61% had no hand preference. In toddlerhood, this 39% increased to 97%. This study provides some evidence that handedness might begin to stabilize earlier than traditionally assumed. However, in order to confirm this conclusion, more research was required. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly The researchers were particularly interested in asymmetric bimanual actions. They explain: The current study is the first longitudinal attempt to connect unimanual and bimanual preferences, and emerging handedness patterns, over repeated monthly assessments in a large group of developing children (N = 38). They focused on actions where two hands work together to achieve a goal, a skill known as Role-Differentiated Bimanual Manipulation (RDBM). The development of a series of tasks that should reliably elicit RDBM actions was an important part of this study. To test the tasks, the researchers set up experiments in their laboratory, Greensboro Infant Development Center. In the experiment, the passive hand stabilized or held the item for the active hand to perform the action. For example, when a child wanted to remove a ball from a tube the passive hand stabilized the tube while the active hand removed the ball from the tube.  Coding and analyzing behavioral data Test sessions were recorded with two cameras providing adequate views of the child’s actions. Video coding was done offline afterwards with The Observer XT coding and analysis software. After analyzing the data, they concluded that their series indeed elicited RDBM actions in toddlers as well as adults. As the series was found reliable, Nelson and her team tried to connect hand-use preferences from this new RDBM series to prior unimanual hand use data collected when the same children had been observed as 6-14 month old infants. The results, as mentioned earlier, were the outcome of this longitudinal study.  In addition to the conclusion that development of handedness could stabilize earlier in life than previously thought, the researchers also indicate that there is no single pattern found to get to stabilization of handedness. They actually found 5 patterns leading to 97% lateralized handedness at the end of their study. Tools to study children's development In the Noldus Webinar about Research tools in Developmental Psychology, we explained how our research tools can be used to study the behavior of children both in a natural and in a laboratory setting. Curious? Watch the webinar on demand now! FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial References - Nelson, E.L.; Gonzalez, S.L.; Coxe, S.; Campbel, J.M.; Marcinowski, E.C. & Michel, G.F. (2017). Toddler hand preference trajectories predict 3-year language outcome. Developmental Psychobiology, 59(7), 1-12. https://doi.org/10.1002/dev.21560 - Nelson, E.L.; Campbell, J.M.; Michel, G.F. (2013). Unimanual to bimanual: Tracking the development of handedness from 6 to 24 months. Infant Behavior and Development, 36, 181-188. --- ## How to build a consumer behavior research lab? URL: https://noldus.com/blog/how-to-build-a-consumer-behavior-research-lab Published: 2022-01-07 11:25:00 Description: In order to get off to a good start, it is best to describe the research or tests that are going to be performed in detail. Really knowing your customer is very important. It's widely known that emotions define our mood, and our mood has a great impact on our buying behavior. No wonder researchers, advertisers, and marketers are interested in understanding emotions. They play a key role in non-verbal communication and are essential to understanding human behavior. How to build a consumer behavior research lab? Measuring consumer behavior enables you to really know your customers and get key insights into consumer preferences and buying behavior. A Consumer Lab is designed to allow you to observe your test participants unobtrusively. But how do you build a consumer behavior research lab? In order to get off to a good start, it is best to describe the research or tests that are going to be performed in detail. How will you measure the consumer behavior? For instance, will you just show pictures of food items, or do people actually get to taste them? Will you be looking into facial expressions, or do you want to know what they are looking at and include eye tracking? How to define the lab requirements? With this research description it becomes clear what kind of equipment will be needed, and which physical environment (on-site or in a lab) would best suit this test or research. In general, the description should answer the following questions: - Do consumer goods, products, food items need to be tested? - Do participants need to walk around in the lab? - How many people are present during a test, besides the participant(s)? - Are participants being invited to visit a lab and/or is on-site research going to be performed? - What kind of participants need to be selected (age, gender, etc.)? - How big are the rooms? And, does the building have special aspects (i.e. is it a monument)? You can also build a lab in an existing restaurant or cafeteria making it into a 'living lab'. Would you like to learn more about setting up a consumer lab? Download this free 'how to' guide for more information. In this free 'How to' guide you can find a list of equipment you can think about when building a consumer behavior lab. Of course, the exact combination of tools used in a lab depends on specific requirements and wishes. FREE WHITE PAPER How to build a consumer lab This white paper helps answer the following questions: - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download Solutions for consumer behavior research Learn more about the tools and solutions offered by Noldus in consumer behavior research, sensory science, and marketing research. Or read one of these articles from our Behavioral Research Blog: - How to measure consumer behavior - Why you want to know if your customers are bored, and how to find out - Three ways to understand consumer emotions - Understanding consumer buying behavior RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References Are you interested in reading more about actual research applications, please view the list below. This list is a small selection of scientific publications in this area. - Berčík, J., et al. (2021). Consumer Neuroscience as a Tool to Monitor the Impact of Aromas on Consumer Emotions When Buying Food. Applied Sciences, 11(15), 6692. https://doi.org/10.3390/app11156692. - Forde, C.G.; Kuijk, N. van; Thaler, T.; Graaf, C. de; Martin, N. (2012). Oral processing characteristics of solid savoury meal components, and relationship with food composition, sensory attributes and expected satiation. Appetite, 60, 208-219. - Wilfinger, D.; Weiss, A.; Tscheligi, M. (2009). Exploring shopping information and navigation strategies with a mobile device. Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (Bonn, Germany, 15-18 September 2009). - Zeinstra, G.G.; Koelen, M.A., Colindres, D.; Kok, F.J.; Graag, C. de (2009). Facial expressions in school-aged children are a good indicator of 'dislikes', but not of 'likes'. Food Quality and Preference, 20, pp.620-624. --- ## Behavioral research shows how elephants like their new habitat at the Oregon Zoo URL: https://noldus.com/blog/behavioral-research-elephants-new-habitat Published: 2021-12-16 12:00:00 Description: The elephants at the Oregon Zoo got a new and improved place to live. This 4-year study described in detail how the animals adapted and liked the new features of their habitat. When I was just a little kid, my parents took me and my younger brother to the zoo on a regular basis. I used to love those trips. Funny monkeys, colorful flamingos, and impressive elephants. I grew up loving animals, and ended up studying Animal Sciences at Wageningen University. As I traveled for my internship at the Smithsonian Institute and later for my job here at Noldus, I visited different zoos in Europe and across the US. I got some peeks behind the scenes and participated in a couple of small projects. This is where I learned how behavioral research not only benefits the welfare of zoo animals, but also impacts the conservation of species and wildlife management. Behavioral research shows how elephants like their new habitat at the Oregon Zoo In this post, I want to share a recent study in which researchers used The Observer XT behavioral analysis software to monitor the transition of an elephant herd to their new zoo habitat at the Oregon Zoo (Portland, OR, US). This study, recently described in Animals, is a great example illustrating why behavioral observation matters. LABEL Title Learn more Elephants at the Oregon Zoo The Oregon Zoo houses a herd of 5 Asian elephants. The zoo wanted to improve their welfare with evidence-based approaches. This meant creating a complex new habitat and monitoring the elephants closely by measuring hormone levels, activity, and behavior before, during, and after construction. Over the course of four years, elephants were closely monitored by collecting blood and fecal samples to measure reproductive and adrenal hormones, respectively, measuring walking distances with GPS bracelets, and detailed behavioral assessments. Giving the herd a new environment Dr. Sharon Glaeser and her colleagues elaborately described this whole process of transition to the new habitat in Animals. An environment with improved spatial features, offering the elephants more choice in how and where to spend their time, and with whom. Natural substrates, a multitude of areas, and several feeding systems gave the elephants more choice and control for psychological well-being. What I especially like about this study, is that the benefits from the new habitat as seen by caretakers, is backed by actual data, by science. Which means that these finding can be helpful for other zoos, and even conservation of species in wildlife projects under human management. LABEL Title Learn more Designing choice and challenges The zoo wanted to create an environment to suit natural herd dynamics, with multi-generational matrilineal groups in which the bulls could join and leave as they would in the wild. Studies show that animals need choice, control, and challenges for optimal well-being. This requires a flexible habitat, with indoor and outdoor access. The new habitat was designed with a complexity that made sure the elephants could not see the entire space at once, and they got their exercise exploring it. Feeding strategies The design also included flexible feeding strategies: food was offered at unpredictable times and places, using timed feeders. Sometimes certain manipulation was needed to get the food from puzzle feeders. This encourages the elephants to forage - good for their mental and physical wellbeing. Monitoring behavior in detail Researchers set up an extensive ethogram to describe relevant elephant behaviors and used The Observer XT behavioral analysis software to make detailed observations and control for accuracy. Data was collected in the morning and afternoon, and video was only recorded for self-initiated behavior to exclude the influence of caretakers. Using the software, behavior measurements were performed by 14 trained volunteers, supervised by a principal investigator.  RESOURCES: Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! Learn more Why behavioral observation matters Behavior gives information about activity levels, social relationships, habitat utilization, and resource use. Behavioral changes over time says a lot about how the elephants are feeling and if the new habitat improves their well-being. Physical and physiological measurements are put in a context - a high amount of movement can indicate exploration, but also stereotypical behavior, for example. The success of the new habitat  Caretakers saw the elephants enjoying their new habitat, as backed by the results of this study. Herd dynamics evolved and elephants took advantage of the opportunity to spend as much time outdoors and as they wished. The new enriched environment and dispersed feeding were also successful. Elephants moved around more, one of the females even doubled her walking distance. Another female replaced her stereotypical movement with walking. Contrary to the old habitat, this new environment made the animals spent a lot more time seeking food or puzzling for food. They also spend a lot of time socializing and sharing food and showed less stereotypical behavior. In other words, the new design reached its goal in offering the elephants more autonomy. LABEL Title Learn more Responding to change Of course, construction of and adapting to a new habitat is a significant challenge. This study showed that the elephants responded in a healthy and adaptive manner, physically and behaviorally. This study shows that the increased complexity of the new habitat at the Oregon zoo gives the elephants a place to thrive in. Benefits for wildlife conservation  This study – the physical and behavioral assessments – is not only significant to this particular zoo, it also provides important information for creating models to monitor the wellbeing of wildlife. Wild populations are facing changing landscapes and many are under human management. The more knowledge on how animals respond to certain social and environmental factors, the better change we have at creating the best circumstances for animal welfare and the conservation of species. Think of facility transfers or ex situ conservation, changes in social structure, rescue, rehabilitation and release, habitat conservation, and anthropogenic disturbances. References If you are interested in more details of this study and the elephant habitat, please read: Glaeser, S.S.; Shepherdson, D.; Lewis, K.; Prado, N.; Brown, J.L.; Lee, B.; Wielebnowski, N. (2021) Supporting zoo Asian elephant (Elephas maximus) welfare and herd dynamics with a more complex and expanded habitat. Animals 11, 2566. Or go to www.oregonzoo.org/discover/animals/asian-elephant  Want to learn more about the best way to do behavioral analysis? Go to www.noldus.com/observer-xt-animal All photos are courtesy of the Oregon Zoo. --- ## Five studies showing the power of multi-modal data in behavioral research URL: https://noldus.com/blog/multimodal-data Published: 2021-12-13 10:00:00 Description: The advantages of using multimodal data over a single modality are that it reveals deeper insights and also if one modality fails there can be enough redundancy in the data to still make sense of it. In recent years, a major trend in behavioral research has been the adoption of multi-modal measurements. Whereas in the past an observation, or even computer-aided video observation, might have been sufficient to answer the research question, today’s scientists need to gain deeper insights. Multi-modal data can help with that.  Case studies showing the power of multi-modal data collection An observation can tell you what someone is doing, but the insights into mental states given by physiology can tell you why they are doing it. For example, eye tracking can reveal patterns of interest that the subject themselves are not even aware of and EEG can give insights into detailed brain processes. One reason that researchers use multi-modal methods more than in the past is that modern solutions like The Observer XT, or the newly released all-in-one platform NoldusHub, make it easier to integrate and synchronize different data streams and harness the power of multimodal research.  Here are five different examples of research that would not have been possible without combining different data modalities.   1. Developmental psychology — Investigating social anxiety with video observations together with PPG and temperature sensors. Social anxiety is something that we have all experienced. Public speaking, job interviews, and dates are all circumstances that can make us feel anxious and fear what others will think of us. Sometimes that is accompanied by blushing – the face reddens and feels hot. Everyone knows that, but what was not known until a recent study [1] by psychologists from the University of Amsterdam what role blushing plays in an extreme version of this; social anxiety disorder (SAD).  That disorder is characterized by an extreme and persistent fear of negative evaluation by others. It severely interferes with social situations and can have all sorts of negative knock-on effects. It is known that blushing is a symptom of SAD and can help maintain it, but what is blushing’s role in its development? The researchers asked young children of various ages to sing a song in front of them. They combined systematic observations using audio-video recordings with The Observer XT with measurement of blushing using a combination of three techniques. Blood volume and blood pulse amplitude were measured using photoplethysmography (PPG).  This is the same sort of technique to that used in sports watches to measure heart rate, where light is shone into the skin and the reflected signal is then processed (see diagram below). Cheek temperature was measured using a platinum electrode. Both the PPG and temperature sensors were fastened to one cheek of the children. Image from Gudi A. Tasli HE, Spink AJ & Theuws JH (2015). 11th Pangborn Sensory Science Symposium It is clear that for a study like this, the combination of video observations and using sensors to measure a specific variable (in this case, blushing) had a considerable added value. If blushing had just been estimated by observations, it would have been far less accurate, and data would have been missed.  Observations alone would not have been able to quantify the extent of the blushing; it would have only revealed its presence or absence. That would have considerably restricted the analysis possibilities.                FREE TRIAL: Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data  Free Trial   The exact relationship between blushing and social anxiety disorder is a complex one. For the details, you will need to read the paper [1]. However, it was clear the development of self-conscious emotional reactivity (shown by blushing) by children in early childhood can be an important influence on the development of SAD in late childhood.  The three different ways of measuring blushing indicated different aspects. Temperature showed the clearest relationship with social anxiety development – probably because the children can feel their cheeks getting hot and become self-conscious about the situation. 2. Neuroscience — Brain waves in rodents EEG is a technique which places electrodes on the surface of the skull and which are able to pick up the electrical activity of the neurons in the brain. The activity goes up and down in a waveform, and how fast the wave oscillates, is correlated with what the subjects are doing.  If it is 8-12 times a second (8-12 Hz), then that is related to relaxed behavior. That was the first association to be found, and so they are called alpha waves. Beta waves (16-31 Hz) indicate active thinking (alertness) and motor behavior, theta (4-7 Hz) drowsiness and meditation, delta (less than 4 Hz) high attention and deep sleep. Gamma waves (shown in the diagram below) are quite high frequency, 30-100 Hz, and are caused by groups of neurons acting together for certain cognitive and motor functions. EEG Gamma waves By Hugo Gambo - Own work, CC BY-SA 3.0, The EEG is often associated with a particular location, e.g. alpha waves are measured at the posterior (back) regions of the head. It is also possible to look in much more detail at EEG waveforms, for example one of the stage of sleep is called REM sleep – rapid eye movement. The movements of the eyes result in very specific shapes in waveforms from equally specific regions of the brain. By looking at these waveforms, it is possible to tell not only that REM sleep is going on, but also in which direction which individual eye is moving at a particular moment [2].  Typical REM sleep EEG patterns (from [2]). EEG can also be used to help understand what is going on in diseases of the brain like Alzheimer’s and depression. There are a lot of similarities between the EEG of humans and other animals including rats and mice. Often there are also fine differences like peak latencies but the general pattern of, for instance, the response to various drugs are rather similar [3]. This means that it is often used in drug discovery. A group of researchers in Chile studied gamma waves in the EEG of rats [4]. They looked at these in the area of the brain called the nucleus accumbens. That area is part of the reward system of the brain and it is related to the experience of pleasure. Dopamine is an important neurochemical in that region. In that study, the scientists combined measurement of the EEG of the nucleus accumbens with behavioral measurements which were made using EthoVision XT.  Two rats were allowed to interact with each other in an open area that was neutral territory for both animals. There were more gamma waves, indicating reward and pleasure, when the rats interacted with each other, than then they were just given a novel object to interact with. Note that this can only be measured by combining the behavioral data from EthoVision XT with the EEG data. In the illustration below (by kind permission of the authors of [4]) the graph on the bottom right shows how the gamma waves are clearly are more powerful when the rats are interacting with each other. They also looked at how the interaction went when one of the two rats interacting had been stressed. The stress was caused by being introduced to the territory of another rat. This leads to a stressful confrontation. It is the sort of stress that rats in the wild will experience frequently in their everyday lives. The data showed that the stressed rats were no longer able to gain as much pleasure from the interactions on neutral territory as they would otherwise have done. That is not very surprising, but its importance was that it showed, for the first time, some of the details as to exactly how that works in the brains of the rats. 3. Educational psychology — Studying engagement whilst learning using many data modalities. The NeuroLab at the University of Quebec in Montreal was established to research various aspects of education and learning using multi-modal techniques. They use a whole battery of techniques to study test subjects who are working on online learning problems [5].  The interaction with software (mouse clicks and movement) are recorded. Eye trackers record gaze and pupil diameter. Emotional engagement was measured using FaceReader and electrodermal conductivity (EDA, also known as skin conductivity). This works on the principle that you sweat when aroused or nervous. In addition EEG is used. As mentioned above, beta waves give an indication of cognitive alertness. This was combined with information from alpha and theta bands to give an engagement index. All these data streams were combined together using a special setup from Noldus, as explained in this interview: Synchronization is especially important in a setup like this, otherwise it is impossible to make a meaningful analysis of the data.  4. Behavioral ecology — Studying stress in trapped badgers Studying the behavior of animals in the wild has particular challenges and use of multiple types of data can also help there. When working outside the laboratory, it is more common for equipment to fail and to have missing data, so having several types of data can be a way of compensating for that and still being able to get publishable results, even if not all goes according to plan. That was what a group of Swedish scientists found in their study [6] of how stressful being trapped was for badgers.  Image by hrw1973 from Pixabay Even if the trap is designed so that there is no physical damage, it is still stressful for the badger, because of the way that they perceive the situation. The gold standard for measuring stress levels is to measure cortisol. Cortisol is a hormone produced by the body directly in response to stress.  The researchers put food out for the badgers containing small indigestible colored pellets. Each badger got different colored pellets, so when the researchers collected their droppings, they could measure the cortisol and know which badger it was from. But, as is common in fieldwork, things didn’t turn out as planned. A lot of the samples they collected didn’t have any colored markers in them, so they couldn’t be used.  Live and video-recorded observations using The Observer XT However, fortunately they didn’t only rely on cortisone measurements. They implanted sensors which enabled them to measure both heart rate and body temperature, which are also indicative of stress (although that is more complex to interpret because those measures also increase with activity). In addition, they made both detailed live and video-recorded observations of all the behaviors of the badgers using The Observer. This was far from trivial, as badgers are nocturnal animals and it involved many nights of painstaking work.  The results were not surprising, though nevertheless important from an animal welfare point of view. Being trapped was indeed very stressful for the animals. All the time they were in a trap they were trying hard to escape. The stress effects continued afterwards; when they returned home they had less social interactions and less “comfort behaviors” like preening and scratching. Three nights later, they still had less social grooming. The longer they were trapped, the more stressful it was. Also if they were trapped at nighttime (their active period), that was more stressful than if they were trapped during the day. What this study showed particularly nicely was the combination of behavioral observations, physiological measurements, and hormonal observations all contributed to the complete understanding of the experiment and gave much deeper insights that just observations alone would have done. 5. User experience and health research — Use of multimodal data to study how people with dementia can be helped by technology Two labs in Canada have worked together to develop methods for studying the use of mixed reality (MR) technologies (virtual reality and augmented reality) [7]. The labs are the Social and Technological Systems (SaTS) lab and the Dementia Ageing Technology and Engagement lab (DATE), both in Toronto, Canada. The particular application that they studied was how those technologies can support people with dementia. Normally when developing technologies, users can be asked to fill in questionnaires to give feedback on whether the technologies meet their needs. However, people with dementia are not always able to do that, so observational methods need to be used.  The basis for the observations was The Observer XT, using the special remote licenses supplied to customers during the pandemic. That was used to make a detailed coding of what exactly the participants were doing when they were using the mixed reality (MR) devices.  However, that was not sufficient to get the insights the researchers needed. They also measured gaze and pupil data with eye tracking glasses, emotions expressed in the face with FaceReader and also EEG for measuring neurological processes in the brain. In addition, a task assessment tool was created in order to quantify to what extent the participants were able to carry out the tasks both with and without using the MR tools. Finally, the data were all brought together, synchronized and integrated using The Observer XT.               RESOURCES: Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts  Resources   The conclusion of the study [7] was that the MR devices were indeed helpful and also that the multi-modal setup powered by The Observer XT was a useful way of studying the interaction of the participants with the technologies. Involvement of end users of technologies in developing new technologies is critical if the technologies are to be developed in such a way as to meet the needs of those people. Good studies of people who are using the technologies are the best way to determine that. Conclusions Use of data from many different modalities is really taking off. The advantages over a single modality are that it reveals deeper insights and also if one modality fails there can be enough redundancy in the data to still make a good publication. A few years ago, working with multimodal data was very complex, especially when it came to integration and synchronization. Modern technologies like The Observer XT increasingly make it easier and more practical.  References [1] Milica Nikolić, Mirjana Majdandžić, Cristina Colonnesi, Wieke de Vente, Eline Möller, and Susan Bögels (2020). The unique contribution of blushing to the development of social anxiety disorder symptoms: results from a longitudinal study. J. Child Psychology & Psychiatry 61, 1339-1348. doi:10.1111/jcpp.13221. [2] https://www.learningeeg.com/normal-asleep  [3] Drinkenburg WH, Ruigt GS, Ahnaou A. Pharmaco-EEG Studies in Animals: An Overview of Contemporary Translational Applications. Neuropsychobiology. 2015;72(3-4):151-64. doi: 10.1159/000442210. Epub 2016 Feb 23. PMID: 26901596. [4] Iturra-Mena AM, Aguilar-Rivera M, Arriagada-Solimano M, Pérez-Valenzuela C, Fuentealba P and Dagnino-Subiabre A (2019) Impact of Stress on Gamma Oscillations in the Rat Nucleus Accumbens During Spontaneous Social Interaction. Front. Behav. Neurosci. 13:151. doi: 10.3389/fnbeh.2019.00151. [5] P Charland, PM Léger, S Sénécal, F Courtemanche…(2015) - Assessing the multiple dimensions of engagement to characterize learning: A neurophysiological perspective. JoVE, 101, e52627. doi:10.3791/52627.  [6] Schütz, K. E., Ågren, E., Amundin, M., Röken, B., Palme, R., & Mörner, T. (2006). Behavioral and physiological responses of trap-induced stress in European badgers. The Journal of Wildlife Management, 884-891. [7] Desai, S., & Astell, A. (2021). Mixed reality technologies for people with dementia: Participatory evaluation methods. arXiv preprint arXiv:2107.07336. --- ## Predicting behavior from non-verbal communication URL: https://noldus.com/blog/predicting-behavior-from-non-verbal-communication Published: 2021-12-06 10:09:00 Description: Suppose a darts player is ready to throw a dart while showing a smile on his face. Would he hit the attempted number of points as opposed to missing the shot if he looked grumpy? Research has been done to figure this out. In several blog posts that I’ve written, an important topic is communication. Let me highlight a few sentences from those posts to illustrate that: - The face is probably the first thing we look at when we meet each other. One of the social functions of a face is communicating non-verbally. - It is very natural to look at someone's face when we have a conversation. Often, we do this without thinking, unconsciously. - Human beings are sociable creatures, and we have developed many ways to communicate our messages, thoughts, and feelings with others. Communicating is a natural behavior and everyone shows this behavior. One cannot not communicate, we exchange information with each other almost continuously. Verbal and non-verbal communication We distinguish verbal communication, which involves communicating with words, and non-verbal communication, which involves communicating with body language. The latter includes facial, vocal, and postural expressions, as well as touch, proximity, and gaze. We use non-verbal communication to inform other people how we feel and are likely to behave. Predicting behavior from non-verbal behavior It is very useful to know in advance how someone is going to behave. An important cue for this appears to be non-verbal behavior. This can be very convenient when you are playing games, for example. You would then be able to see what the opponent's next move would be. Unless, of course, someone shows a good poker face. Suppose a darts player is ready to throw a dart while showing a smile on his face. Would he hit the attempted number of points as opposed to missing the shot if he looked grumpy? Research has been done to figure this out. Observing differences in non-verbal behavior The team of Philip Furley wanted to find out whether it is possible to determine differences in non-verbal behavior as a function of good and poor performance. For this, they used thin-slices rating. Thin slicing describes the ability to find patterns in events based on only “thin slices”, or narrow windows, of experience. In just a fraction of a second, observers make inferences about the state, characteristics, or details of an individual or situation with minimal amounts of information [source]. Instead of lengthy video clips, the researchers used brief clips with an average duration of only 4 seconds. This way, they captured the very first impression. Using facial expressions analysis to predict dart player’s performance For the study, observers watched televised video recordings of the first two rounds of the 2017 PDC World Darts Championship. Two performance categories for each dart player were screened: - High-performance category with possible scoring range of 103-180: two big triples (17-20 points) and at least a single (1-20 and 25) or better. - Low-performance category with a scoring range of 0 to 75: only single scores or no scores. All video clips were analyzed with FaceReader. The intensities of Action Units, emotional facial expressions, valence and arousal were measured. Besides, the preparation time of the three individual darts that make up a throw were computed. The starting point of every video was determined as the first frame in which the player made a clear upwards movement with the to-be-thrown dart in his throwing hand. A throwing sequence ending point was determined as the last frame before the dart left the hand. All three pre-performance throwing sequences of a throw were merged together to one video clip. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download The observers were asked after each shown video clip to estimate the score of the throw (all three darts together as this is how it is scored in competition) based on the pre-performance non-verbal behavior of the dart player. Therefore, a digital slider bar was available with a 180 points scale, where the left pole represented 0 points (the poorest possible performance) and the right pole represented 180 points (highest possible performance). Using facial expressions to create positive impressions The research team found that observers were able to correctly differentiate high and low performance of individual dart players based on short glimpses of preparatory non-verbal behavior. Besides, the pre-performance preparation time, the expressions neutral and sad, as well as arousal correlated to subsequent performance. From all these cues, the performance of a professional dart player can be derived. However, the researchers mention that all of these correlations are small and only explain small proportions of variance. Also, they were limited to the use of broadcasted footage for television, which might not show all the pre-preparation time the dart player actually took. It can be interesting for applied research to investigate the possibility if athletes can deliberately use certain facial expression to create favorable impressions in observers like opponents or spectators. References - Furley, P. (2021). The nature and culture of nonverbal behavior in sports: theory, methodology, and a review of the literature. International Review of Sport and Exercise Psychology, https://doi.org/10.1080/1750984X.2021.1894594 - Furley, P., Klingner, F. & Memmert, D. (2021). Nonverbal pre-performance expressions of professional darts players distinguish between good and poor performance. Scientific Reports, 11, 20147. https://doi.org/10.1038/s41598-021-99729-4 - Thin slices of behavior --- ## Citizen science in research: studying contaminated drinking water with zebrafish URL: https://noldus.com/blog/citizen-science-zebrafish Published: 2021-12-01 12:00:00 Description: Local residents, students and scientists joined forces to investigate harmful contaminants in drinking water wells in New England. Behavioral effects of these contaminants were studied in zebrafish. Almost half of the residents from New England states Maine and New Hampshire depend on private wells for drinking water. Due to natural and human causes, well water in New England often contains contaminations with metals such as cadmium, lead and even uranium, but also arsenic. This causes an important public health concern since chronic or high level exposure to these contaminants have been associated with multiple diseases such as cancers and even impaired neurological development. Toxic drinking water Arsenic levels that exceed 5 μg/L has been shown to affect IQ in children. Shockingly, Arsenic levels in 1/3 of wells in Maine tested exceeded 10 μg/L. Early lead and cadmium exposure has also been linked to lower IQs and behavioral disorders in children. Determining the drinking water quality in Maine and New Hampshire however is limited by two main factors: homeowner participation in water testing and the lack of information related to metal mixture effects and the difficulty communicating this to the broader public. This is why the University of Maine partnered with local teachers, students, and other scientific partners in Maine and New Hampshire and collected 92 drinking water samples from wells and utilized a multivariate analysis that examined behavioral outcomes in a zebrafish (Danio rerio) model [1]. LABEL Title Learn more          Image from Babich et al [1] Surprisingly, some of the levels of these metal mixtures (also with arsenic) are considered safe to drink. These however have still shown to be significant drivers of behavioral toxicity. This emphasizes the importance of monitoring the level of contamination in these drinking water wells and possibly strengthens advocating for improvement of water quality.  The strength of citizen science Additonaly, this paper proves the utilization of citizen science and how this collaborative work can have a broad impact and even empower local communities to indeed push for this advocation. Also, the societal importance of the use of the zebrafish as a relevant toxicological model is highlighted once more in this study. Although not a direct comparison to human development, the resolution and high-throughput capabilities of the zebrafish make this model extremely valuable. Eco-neurotoxicology If you would like to read more relating to this topic, we recently published a white paper on eco-neurotoxicology, which can be found on this page. In this white paper we dive into the topic of contaminated surface and drinking water, and how the latest technology is used to investigate the neurotoxic and/or neuromodulating effects of these contaminants in (for example) zebrafish.  Reference 1.      Babich, R.; Craig, E.; Muscat, A.; Disney, J.; Farrell, A.; Silka, L.; Jayasundara, N. (2021). Defining drinking water metal contaminant mixture risk by coupling zebrafish behavioral analysis with citizen science. Sci. Reports 2021 111, 11 (1), 1–11 --- ## Parent-child interaction – research in a lab and on-site URL: https://noldus.com/blog/parent-child-interaction-research Published: 2021-11-29 12:00:00 Description: Early in life, children are not capable of filling out a complete questionnaire or talking to an interviewer. Early in life, children are not capable of filling out a complete questionnaire or talking to an interviewer. In that case, observing behavior can provide valuable information in combination with parental interviews. We share an interesting list of examples of child development observations. How to study parent-child interaction: examples of research in a lab and on-site Child development observations: Lab or natural setting? Researchers can choose to observe behavior in a laboratory setting or in a natural setting such as a family home. When 100% control of the situation is required, a laboratory setting is the most favorable option. But, in a study that needs to answer questions about behavior in its natural context, an unobtrusive set-up in a daycare center, family home, or shop is preferred. In both cases, the researcher can record the interaction on video and code behaviors in great detail. By using video, researchers don't lose any information and can test their coding scheme and/or coders by asking different coders to code the same scene. FREE WHITE PAPER How to build an AV lab Do you want to learn more how to set up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download Example case: the role of toddler emotion Umemura et al. observed parent-child interaction in their laboratory as well as at the family's home. They tested Bowlby and Ainsworth's hypothesis: a hierarchy of caregivers exists whereby infants prefer one caregiver over another when distressed. In other words, Umemura et al. asked themselves: Who is the primary caregiver (mother or father)? Does the infant feel secure/insecure at the age of 1? At 2-years-of-age is the same child more likely to prefer a particular parent (mother, father) at home, both when distressed and when in a positive mood? Infant Behavior and Development In their publication in Infant Behavior and Development they describe how the lab test was performed at the university laboratory. The mother or father came to the lab with the infant for the strange situation procedure (Ainsworth's strange situation test). This procedure is widely used to assess attachment and also often performed in an unobtrusive, controlled environment such as a stationary observation lab with two rooms: an observation room and a second room in which the observers can watch the interaction through a one-way mirror. Two-way classification In order to measure the level of attachment an infant feels and relate it to the role a caregiver plays, Umemura et al. used a two-way classification (secure vs. insecure: insecure-avoidant, insecure-resistant, or disorganized). They continued their study a year later. So when the same children turned 2, one of the researchers visited the family at home to record a triadic family interaction on video. In order to calculate and compare frequencies of behaviors, they coded with whom the toddler initiated interaction and the toddler's emotional state when initiating the interaction. In addition to observing behavior, the researchers also collected data by asking the parents to complete a questionnaire about their own involvement in caregiving tasks. Emotion matters The researchers found that distressed toddlers preferred their mothers over their fathers and that when toddlers were content, they didn't display a preference for either caregiver. Moreover, mothers in a clear primary caregiver role were compared to mothers who equally shared the role of caregiver with their partner. The results supported the hypothesis that toddlers prefer their primary caregiver when seeking comfort. Behavioral observations in child development Behavioral observations can identify particular patterns. For example, by observing how secure an infant feels with his parents (Ainsworth's strange situation test), researchers are able to test if a history of security and attachment influences parent-child interaction later in life. Umemura et al. conclude that a positive history of attachment and security predicts how quickly toddlers recover from distress after seeking interaction from a parent. By examining this study from an interdisciplinary point of view, it can be suggested that it is a traditional mother-father role which influences the infant's preference. Could it be that children with two mothers (a homosexual female couple) show different behaviors? It is really interesting to also look at this issue from a biological perspective. Is this infant/toddler behavior biologically determined? In the discussion of their article, Umemera et al. propose a broader perspective for future research. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Download References - Umemura, T.; Jacobvitz, D.; Messina, S.; Hazen, N. (2012). Do toddlers prefer the primary caregiver or the parent with whom they feel more secure? The role of toddler emotion, Infant behavior & development, 36 (1), 102-114, doi.org/10.1016/j.infbeh.2012.10.003. --- ## 7 tips to make coding behavioral data more fun URL: https://noldus.com/blog/7-tips-for-behavioral-coding Published: 2021-11-24 11:05:00 Description: Coding behavioral data helps to understand what your data represents. But let's face it, it isn't much fun to do and it takes a lot of time. Here are 7 tips to make the coding process more effective. Human behavior consists of many aspects, which are worthwhile to investigate. Doing research is to understand why things happen and what relationships between phenomena are. For example, parent-child interactions, language development, handedness, and mealtime behaviors are well-known topics in developmental psychology research. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly As a researcher who works with children and their parents or caregivers, you know that part of your job is to record the experiment, review the sessions, and code numerous videos of your participants. Especially the coding part is a time-consuming, but necessary activity. Why is coding behavioral data important? Coding videos will help you summarize and highlight important pieces of information that are essential for the analysis of the observed behavior. You will be looking for frequencies, durations, sequences, similarities, or differences with respect to what participants say or what participants do. Behavioral coding supports quantifying qualitative data and gives sense to your raw data. It categorizes your data meaningfully and helps to understand what it represents. 7 tips to make coding behavioral data more fun But let's face it, coding isn't much fun to do and it takes a lot of time. Tips to make coding behavioral data more effective and a bit more enjoyable are therefore more than welcome. 1. Keep your research questions in mind To keep focused and to prevent doing work that ends up not being used in the analysis, it is wise to stick to the components which will answer your research questions. Not all behaviors that your participants show on the video will be equally good for this purpose. Be sure to make considered choices in what is important and what is not. Constantly keep referring back to your research questions. 2. Use a coding scheme As you code more and more data, it can be hard to remember all of your codes off the top of your head. A coding scheme helps keep you organized throughout the data analysis process. In addition, you give the other members of the research team insight into which behaviors are coded and how. It ensures transparency. However, creating a scheme for behavioral coding is not as straightforward as it may seem. It often requires quite some thinking to define the perfect scheme for behavioral coding. Keep in mind that once it’s ready, you will benefit a lot from the energy you put into drawing up the coding scheme. FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download 3. Select a few videos to find common codes Depending on the size of your sample you can select, for example, 10% of your videos to get a first impression what emerges from your data. You don’t want to do this with all your videos, since that is very time consuming. Selecting a smaller number of videos can give you your set of common codes to look for in the rest of the data. Although you should keep in mind that you might come across things that you did not expect. 4. Document why you make certain choices Be thorough in documenting the coding process and especially how the codes fit together. This proves that the process is transparent, which contributes to your credibility. Put in your memos whether you noticed something that was expected based on your literature review or whether you learned something totally new. What patterns or contradictions are emerging that you’re noticing while coding? This gives you a log of your coding process and also helps you write the first draft of your final report. Another win. 5. Divide the coding work Once you’ve created a solid coding scheme the next step you can take is to invite others to help you with the coding work. Diving this large amount of work prevents workload and stress. Multiple people can work on coding at the same time, speeding up the entire process. In such collaboration, avoiding observer bias is, of course, crucial. Reliability analysis assesses the extent to which two observations are in agreement with each other and helps determining when your co-workers are ready for the real work. 6. Check out sources of information about coding behavioral data In the blog post ‘Behavioral coding: What and how’ you can read more about the benefits and how to use behavioral coding. Or watch the Technical Briefing ‘Behavioral Coding - Designing optimal coding schemes in The Observer XT’, in which we will show you how to create coding schemes that allow you to reach your behavioral endpoints but, at the same time, are clear enough for efficient and reliable coding. The practical guide in the article ‘Developing and Modifying Behavioral Coding Schemes in Pediatric Psychology’ can also be useful. 7. Smile while you are coding Surely, this header immediately put a smile on your face. A smile is very powerful, we enjoy things more when smiling. Besides, smiling can reduce stress since it decreases hormones such as cortisol and adrenaline, and it can lower blood pressure. The muscles used while smiling trigger your brain to produce more endorphins and provide a sense of well-being. This will make your coding work much more fun! Behavioral coding software A great tool that can help you with your coding and analysis work is The Observer XT. It supports the entire workflow of your research project. The software offers many benefits and meets your requirements: - The Observer XT guides you through the process of creating a coding scheme. Want to add behaviors? The software shows an example of the kind of results you can expect. - While coding, you can use shortcut key codes to keep up the speed. The time of each code is recorded automatically and errors are stopped by an online check. - The Observer XT uses smart coding; when starting one event you do not have to stop the previous event of the same group, one cannot run and stand still at the same time. - Both time (instantaneous) sampling and continuous recording are available as sample methods. - You can use the playback functions to easily position the video, play it back at different speeds, play it frame by frame, and play multiple videos in sync at the same time to ensure accurate coding of the behaviors. - You can set a loop in the video and audio files to code this particular episode in great detail, or use the quick review button to take a small step back in the video. - Combining data from different sources in your observation, such as eye trackers or physiological measurements is no problem at all. - With the coder licenses you can work with multiple people on the same research project, which saves you lots of time. With the reliability analysis, observer bias can be avoided. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial References - MacLaren Chorney, J.; McMurtry, C.M.; Chambers, C.T. & Bakeman, R. (2015). Developing and Modifying Behavioral Coding Schemes in Pediatric Psychology: A Practical Guide. Journal of Pediatric Psychology, 40(1), 154–164. https://doi.org/10.1093/jpepsy/jsu099 - How to Know You Are Coding Correctly: Qualitative Research Methods - What is a Code?: Qualitative Research Methods - The Cycles of Coding: Qualitative Research Methods - Smile: A Powerful Tool --- ## How to collect high quality data in an observation lab URL: https://noldus.com/blog/how-to-collect-data-in-an-observation-lab Published: 2021-11-18 12:00:00 Description: Controlled conditions and accurate data recording are key in scientific success. A stationary observation lab provides these controlled conditions while allowing scientists to observe test participants unobtrusively. Observational research is often best carried out in a stationary lab. Controlled conditions and accurate data recording are key in scientific success and a stationary lab provides these controlled conditions while allowing scientists to observe test participants unobtrusively. How to collect high quality data in an observation lab Behavioral researchers have developed a refined methodology to evaluate behavioral change that depends upon accurate measurement of behavior. Direct observation of behavior has traditionally been the pillar of behavioral measurement. Consequently, researchers must attend to the psychometric properties, such as interobserver agreement, of observational measures to ensure reliable and valid measurement (source). Interobserver agreement refers to the extent to which two or more independent observers report the same observed values after measuring the same events. Furthermore, interrater reliability is the extent to which two or more raters (or observers, coders, examiners) agree (source). Research in a Noldus Observation Lab With a Noldus observation lab, comparing across sessions and quantifying data is very straightforward. It is possible to combine video observations, physiological data collection, facial expression analysis, sensory testing, and more in a lab. And thus a myriad of different experiment setups and designs based on the type and position of cameras, microphones, eye trackers, webcams: whatever is necessary to gather rich and meaningful data. See some examples of research in an observation lab, and interobserver agreement percentages below. 1) Investigating the organization of spontaneous eye blinks Mei-Hua Lee et al. investigated the mean rate and time-dependent sequential organization of spontaneous eye blinks in adults with intellectual and developmental disabilities. They also explored the behavior of individuals from this group who were additionally categorized with stereotypic movement disorder. So how did they set up their behavior experiment? They positioned one camera in a clinical exam room. Researchers then asked test participants to sit in a chair and look directly into the camera. This observation room was created to record natural, spontaneous eye-blink behavior while free of external noise and interruption. Two observers coded the recordings and reached an average of 93.2% interobserver agreement. 2) Exploring the relationships between sensory perception and facial reactions Wendin et al. recorded behavior using a dome camera. Participants were asked to taste several samples served in plastic cups. The dome camera was located in the ceiling approximately 3 meters from the test participant, and after the experiment two trained observers coded facial expressions. The aim of this study was to explore relationships between sensory perception and facial reactions. The observers rated the facial reactions such as frown, eye widening, and lips pursed independently with inter-observer agreement exceeding 90%. In the end they concluded that a combination of sensory and facial expression analysis successfully added insight into the perception of basic tastes. FREE WHITE PAPER Autism Research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Download 3) Studying play behavior in an observation lab Freeman and Kasari of the Semel Institute for Neuroscience and Human Behavior observed play behavior, in particular to which extend parents of young children with autism match and support their child's play. The researchers designed an observation lab with an assessment room and an observation room. The study focused on the similarities and differences in play interactions between dyads with and without a child with autism. Parents - both of children with autism and with typically developing children - were invited to the observation lab for assessments. Trained lab members coded parent and child behaviors displayed in the play session afterwards, using The Observer XT. Reliability was calculated on several components: - Types and frequencies of play behaviors. Overall average intraclass correlation coefficient was 0.97. - Scheme duration and frequency. The child-initiated schemes' duration and parent-initiated schemes' duration scored the highest coefficients: 0.99. - Play acts. The highest intraclass correlation coefficients was found on imaginative child's play act: 0.87. The research team concluded that children with autism differed from typical developing children in their level of play, and child engagement was affected by specific parent interaction strategies. Read the full blog post on their study here. FREE WHITE PAPER How to build an observation lab Do you want to learn more how to set up an observation lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download References - Lee, M.; Bodfish, J.W.; Lewis, M.H.; Newell, K.M (2010). Low dimensional temporal organization of spontaneous eye blinks in adults with developmental disabilities and stereotyped movement disorder. Research in Developmental Disabilities, 31, 250-255. - Wendin, K.; Allesen-Holm, B.H.; Bredie, W.L.P. (2011). Do facial reactions add new dimensions to measuring sensory responses to basic tastes?, Food Quality and Preference, 22 (4), 346-354. - Freeman, S.; Kasari, C. (2013). Parent-child interaction in autism: Characteristics of play, Autism, doi 10.1177/1362361312469269. --- ## Advancing the novel object test: 3D printing and deep learning URL: https://noldus.com/blog/3d-printing-and-deep-learning Published: 2021-11-17 12:00:00 Description: To improve standardisation and consistency in the novel object test, Spry et al designed the 'CapTouch' system: capacative objects that can automatically register interaction. But what about deep learning in EthoVision XT? Recently, we updated our white paper on novel object recognition. This white paper also approached the dilemma of the use of the actual objects, and the many inconsistencies and lack of object standardization that exists within and between labs. This is exactly what Spry et al tried to tackle in a recent publication by investigating the use of 3D-printed objects [1].  3D-printing capacitive objects Spry et al provide a proof-of-principle demonstration that employing 3D-printed capacitive objects is a cost-effective, reliable, and precise way to perform object recognition tasks when compared with manual scoring. This novel approach could ultimately contribute to a more standardized approach to object recognition tasks, which would greatly improve reliability in basic and applied neurobehavioral research. LABEL Title Learn more Quick recap Object recognition typically involves familiarizing a subject animal with a set of objects and then presenting a novel object or displacing an object to a novel location. Time spent exploring the novel and/or displaced object can be used to infer learning and memory. The ‘CapTouch’ system Two versions of the innovative ‘CapTouch’ system, with an estimated cost of about $85, were implemented: version 1.0 used conductive 3D-printer filament, and version 2.0 used traditional printing filament combined with copper tape. This second version was implemented to provide additional lower-cost objects in more common printing materials (for example PLA and PETG). CapTouch 1.0 Objects and their bases for CapTouch 1.0 were printed with conductive filament and connected to a touch board using solid core wire which was attached to a within-object magnet. This then could be connected to header pins on the touch board. A twist-off design ensured easy removal and attachment of the object to the base. CapTouch 2.0 The second iteration of the CapTouch was printed in a non-conductive filament. These objects were hollow, and copper foil tape was placed inside to serve as the capacitive sensor and were simply attached to the base by a simple peg-in-hole design.  LABEL Title Learn more Trained neural networks - EthoVision XT 16 Spry et al state that current video-based automated algorithms can often be unreliable whereas manual scoring of object investigation is time consuming, tedious, and more subjective. Although Spry et al make a comparison between manual scoring and their new capacitive-based system, they don’t compare their system to video-based tracking algorithms.  Contour-based video tracking can indeed cause for some inconsistencies, especially when subjects are lost during tracking due to objects present in the arena. EthoVision XT 16 however has introduced deep learning based tracking, which uses trained neural networks that has drastically improved the detection of body points (nose point, centre and tail base). Particularly in novel object recognition tests, the detection of object interaction has resulted in unsurpassed video tracking quality. A recent webinar by Alicia Brantley, PhD, dives into this topic, and shows how with this new feature, the novel object test can be further standardized and improved. Other key topics of this webinar include:  - Defining novel object test procedures and goals - Understanding primary challenges to reproducibility in novel object tests - Successfully utilizing behavioral tracking software to increase reliability in novel object tests LABEL Title Learn more Advancing research The CapTouch system proved that technological advancements can indeed contribute to improving scientific quality through standardisation. Future improvements on this system are however warranted since limitations lie in the filament (printing material), but also in the criteria of object exploration. Although there was a high correlation, the capacitive objects did detect slightly less interaction than manual scoring due to a greater requirement for direct physical contact.  This discrimination can be made using EthoVision's trained neural network. Using video tracking in EthoVision XT 16, which is basically a turn-key system, does not require constructing capacitive objects, a skill that is not native to every researcher.  Taken together, research like this current paper by Spry et al are important steps in advancing our understanding of animal models and their basic neurobehavioral mechanisms. Output resolution only increases as technology advances, and gives us more insight into these workings.   References 1.        Spry, K. P.; Fry, S. A.; DeFillip, J. M. S.; Drye, S. G.; Stevanovic, K. D.; Hunnicutt, J.; Bernstein, B. J.; Thompson, E. E.; Cushman, J. D. (2021). 3D-Printed Capacitive Sensor Objects for Object Recognition Assays. eNeuro, 8 (1), 1–9 --- ## Anxiety and Autism URL: https://noldus.com/blog/anxiety-and-autism Published: 2021-11-12 10:00:00 Description: The EU-AIMS and AIMS-2-TRIALS projects have carried out some interesting studies teasing out the causes of anxiety in children with autism. Autism is a condition which is characterized by difficulties in social communication (e.g. avoiding eye contact), restricted and repetitive behaviors (e.g. body rocking, rituals) and sensory anomalies (e.g. insensitivity to pain or hypersensitivity to noise).  Those characteristics are used in the diagnosis of children with autism. That can be difficult though because they are very variable (it is not called the autistic spectrum for nothing), and also communication difficulties can mask other factors.  FREE WHITE PAPER: Download the free White paper to learn how and why observational research methods are used in autism research. Learn more Anxiety and autism In addition to those diagnostic features, autistic children experience other problems, including anxiety, much more than other children. In general, 27% of children experience problems with anxiety, but in children with autism that can be as high as 70%.  What is the relationship between the behaviors typical of autism (communication difficulties and repetitive behaviors) and anxiety? Does one cause the other, and if so which way round? How are they related? It is most likely a bidirectional relationship, with communication problems causing anxiety and anxiety making communication more difficult. But if we can better understand the roots of anxiety in autism, then that might help provide targets for early interventions, which should improve long-term prospects for the children. Autism Innovative Medicine Studies (AIMS) Often, by the time a child has an official diagnosis, both autistic behaviors and anxiety are already present, and then it is too late to be able to figure out what is going on. Scientists working in the EU-AIMS project and its successor, the AIMS-2-TRIALS project (both of which Noldus was happy to participate in) figured out a way to solve this problem [1]. Part of that research is what is described in this blog.  Autism has a genetic component - it tends to run in families. That means that if a child has an autism diagnosis, there is a 20% chance of their younger brother or sister also having autism. That compares with about 2% of the general population. Those children were followed from before their birth, and in that way it was possible to see in detail how they developed and tease out how various factors relate to each other. Fear of the unknown Behavioral inhibition is a term for heightened fearfulness, shyness and wariness towards novel stimuli. If presented with something new, infants with behavioral inhibition are likely to be a bit afraid of it. That can lead to them avoiding new things and unfamiliar people. That in turn can mean that they will be less socially competent and less assertive. In the end, that can lead to problems with anxiety.  That is so in the general population, and this study [1] showed that it was also the case for autistic children. Autistic children with increased behavioral anxiety at 24 months showed increased anxiety at 36 months. Emotional control When children get to about one year of age, they begin to develop emotional control. That means that they can regulate their emotions appropriately in response to what is going on around them. That is also called effortful control. If children do not develop the ability to be able to do that, it can lead to behavioral inhibition and then anxiety (as well as other problems).  This study showed that you can also see that the other way round. If the child can learn regulatory control, then this can protect them against developing anxiety later. That means that interventions which help a child develop self-control in late infancy could help, and that the timing of those interventions is probably important. The final conclusion from the study is that one reason that anxiety tends to occur in autistic children is because their autism means that they have less effortful (or regulatory) control. That means that they are less able to compensate for other background risk factors, that is, risk factors which occur to a varying extent in the general population. PROJECT PARTNER If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! Learn more Limitations Those conclusions are interesting and can potentially lead to valuable interventions to reduce anxiety in the children when they get older. However, it is worth noting that all the information about anxiety and other problems were reported by the parents. There are a number of potential problems with that, which might lead to inaccuracies or biases in the data.  The children studied all have an older brother or sister with a diagnosis of autism. That might affect the judgement of the parents of the younger child. It might also mean that the parents themselves are more anxious or that they shield their children from novel situations and people, which could itself result in behavioral inhibition and anxiety in the children studied.  Objective measures Those sorts of limitations are inevitable in studies which rely on subjective opinions of people. In order to go a step further, it is necessary to find objective ways of measuring the behavior of the people being studied. That methodology is also being developed in the AIMS-2-TRIALS project.  In partnership with the academics in the project, Noldus and DEMCON are developing a smart baby suit. This will enable the researchers to objectively measure the movements and physiology of the baby in his or her home environment. The physiology gives insights into stress and other relevant mental states. The information is complementary to the subjective input from the parents and avoids the stress and disturbance of bringing the baby into the lab for studies. Reference [1] Ersoy, M., Charman, T., Jones, E. J. H., & Team, BASIS. (2020). Developmental Paths to Anxiety in an Autism-Enriched Infant Cohort: The Role of Temperamental Reactivity and Regulation. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-020-04734-7 Acknowledgements The work described here was funded by a variety of sources, including the EU's Innovative Medicines Initiative (IMI) EU-AIMS (grant No. 115300) and AIMS-2-TRIALS (grant No.777394) projects. For details of the other grants, see the Funding section of the above paper. The illustration is taken from the AIMS-2-TRIALS website. --- ## Using the Observer XT to measure aggressive behavior in Dolphins URL: https://noldus.com/blog/aggression-in-dolphins Published: 2021-11-03 12:00:00 Description: The Observer XT is often used in the field to score complex ethograms. This blog touches upon a study of the 'Wild Dolphin Project' that investigates aggresive behavior between two species of dolphins. Although we commonly write about behavioral quantification in rodents or zebrafish, other animal research models should not be forgotten! Volker and Herzing, from the Florida Atlantic University, recently published an article in ‘Animal behavior and cognition’ on aggressive interactions between Dolphins [1]. This is part of the Wild dolphin project, which has been collecting underwater data since 1985. Using the Observer XT to measure aggressive behavior in Dolphins Sympatric species Atlantic spotted dolphins (Stenella frontalis) and bottlenose dolphins (Tursiops truncates) are a sympatric species, meaning they are  very closely related while also inhabiting the same geographic region, in this case, the northern Bahamas. These species are known to travel and forage together but they also engage in aggressive interactions. Research area in the Bahamas Intra- and interspecific aggressive interactions Throughout the animal kingdom, animals express aggression towards another. This can be between members of the same species (intraspecific) or between members of different species (interspecific). This competition usually stems from competition over food or during competition over mates, and can specifically be aimed at preventing hybridization when two species live sympatrically. Spotted dolpins It is known that birds and chimpanzees change their aggressive tactics based on their opponent being intra- or interspecific. This is why the aim of this study was to investigate whether these two types of dolphins also showed a similar behavioral plasticity in aggressive behavior. Bottlenose dolphins The Observer XT A behavioral ethogram was developed which was scored using the Observer XT.  Behavioral readouts were put in three categories: -  Display: Arching, producing bubbles, open mouth, jaw clapping, etc. - Pursuit: Chasing or following another dolphin - Contact: Charging, holding down, biting, tail slapping, etc. These behaviors were scored as intra- or inter specific respectively if they were directed at a member within the species or towards a member of different species. The full ethogram can be found in the publication by Volker and Herzig [1]. Findings Volker and Herzig found that there was no difference in the overall behavioral rate, meaning that these dolphins did not use more aggressive events during either type of aggression. There were unique behavioral events per type of aggression, such as tail cavitation (interspecific) and spinning (intraspecific). Size matters One important finding was that the two species of dolphins did use different tactics based on their body size: The spotted dolphins used display tactics more often than contact tactics during intraspecific (same species) aggression, while during interspecific (different species) these two types were not used more than the other. These spotted dolphins are smaller than the bottlenose dolphins, and thus need strength in numbers in order to move aggression in their favor. This also means the spotted dolphins expend more energy and take more risks when fighting a bottlenose dolphin. Defending their females, defending themselves against sexual harassment and reverting more to pursuit behavior to effectively communicate during interspecies aggression all play a role in this. All in all this thus suggest that there is indeed a high degree of behavioral plasticity in these dolphins, by altering their aggressive behavior based on their opponent. Forced adaptation Behavioral plasticity shows that dolphins can learn and alter their behaviors based on (changing) stimuli in their environment, including the possibility of species overlap. This plays a large role when communities are forced into new habitats as a result of climate change and have to adapt in order to survive. Reference 1.         Volker, C. L.; Herzing, D. L. (2021). Aggressive Behaviors of Adult Male Atlantic Spotted Dolphins: Making Signals Count during Intraspecific and Interspecific Conflicts. Anim. Behav. Cogn., 8 (1), 35–51 --- ## Parent-child interaction in autism: play behavior URL: https://noldus.com/blog/parent-child-interaction-autism-play-behavior Published: 2021-10-29 13:35:00 Description: Stephanny Freeman and Connie Kasari observed play behavior in an observation lab. They invited parents with their children to their observation lab and coded behavior in great detail. Stephanny Freeman and Connie Kasari of the Semel Institute for Neuroscience and Human Behavior observed play behavior, in particular to which extend parents of young children with autism match and support their child’s play. They explain that it is important to provide these parents with the necessary tools to properly stimulate engagement. In this blog post I’ll explain why engagement is important and how this research was designed in an observation lab. Play behavior The study examined the extent to which parents of young children with autism match and support their child’s play. The researchers concluded: “playing within the child’s zone of development (at or just above their mastered play level) resulted in greater engagement and increased children’s play level and diversity of play”. Parents need to understand the level at which their child plays in order to either match or extend beyond their current level. Parents follow or match their child’s play behavior when they respond at the same level. Simply put, when a child brings an empty cup to their mouth to drink it is categorized as pretend play behavior. A parent could match this behavior by pretending to eat a cookie or pretending to drink, etc. The researchers categorized the type of play-act using the Developmental Play Skills Levels (in Freeman and Kasari 2013, source: Kasari et al. (2006) and Lifter et al. (1988).), who carried out the act (parent or child), and how it was presented/the strategy the parent used (suggested, commanded, or imitated). Freeman and Kasari's study demonstrated that parents of children with autism found it more difficult to match or increase the level of play of their child compared to parents with typically developing children. Parent-child interaction Another result the researchers presented was that periods of joint engagement were longer when the parent commanded and suggested less during playtime. The researchers explain that with this type of presentation (commanded, suggested) the interactions are not balanced between adult and child. Understandably, for parents with children with autism, presenting a play scheme in a different way can be a challenge compared to parents with typically developing children who experience no need to command or suggest, because the child is more responsive to the engagement attempts of parents. Freeman and Kasari advise the implementation of particular strategies in early interventions with parents and their children with autism. FREE WHITE PAPER Autism research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Get your copy instantly Observation lab The researchers designed an observation lab with an assessment room and an observation room. The study focused on the similarities and differences in play interactions between dyads with and without a child with autism. Parents of children with autism and parents with typically developing children were invited to the observation lab for the assessments. In order to measure play level in children with and without autism, the children participated in a structured play assessment, during which the child and tester sat facing each other at a table. This play interaction lasted 15 to 20 minutes and was recorded on video. In addition to this structured play assessment, parent-child free play sessions were analyzed. To observe and analyze this parent-child interaction, the parent and child were asked to play with a standard set of toys for 10 minutes, which were again recorded on video. Do you want to learn more? Simply download the publication, one interaction which was coded was transcribed in the publication completely (Freeman and Kasari, 2013). The parent and child in this particular interaction pretended to drink tea together. The parent initiated play by putting a fork next to the bowl and a spoon next to the bowl, after which the child imitates this by repeating the same actions. Next the child initiates the next act by bringing his cup to his mouth which the parent then follows by also bringing his own cup to his mouth. Coding behavior Trained lab members coded parent and child behaviors displayed in the play session afterwards. The Observer XT software enabled the coding of: - The play scheme (tea party or dinosaur battle) - Play act (the acts that make up the scheme) - Initiation - The level of play according to the Developmental Play Skills Levels (in Freeman 2013 source Kasari et al. (2006) and Lifter et al. (1988)) - Who carried out the act (play behavior) - How the act was presented (suggested, commanded, or imitated) The results of the study presented will guide further research and play intervention for parents with children with autism. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Reference Freeman, S.; Kasari, C. (2013). Parent-child interaction in autism: Characteristics of play, Autism, https://doi.org/10.1177/1362361312469269. --- ## The open field test: A staple in behavioral batteries URL: https://noldus.com/blog/open-field-behavioral-staple Published: 2021-10-20 13:00:00 Description: The open field test is a locomotor, exploratory and/or anxiety test. Can we measure all these behaviors in a simple enclosed arena? This is exactly what we talk about in this blog, and the discussion surrounding this. The open field test The open field test is a behavioral paradigm that has become a true staple in behavioral batteries. The arena is quite self-explanatory: an open field (enclosure), which is usually a round, square or rectangular ‘box’ with raised walls (to prevent escape) in which animals can move freely and are recorded from the top. Size depends on the research model: rats or mice, or on other specifics relating to the desired output parameter. LABEL Title Learn more History The earliest recording of this test dates back to the 1930s, where Calvin Hall observed that rats behave differently in this arena when food or no food is present [1]. Food obviously being a strong motivational que, the behavior in this setting was centered around the ability to reach and encircle the location of this source.  However the finding that is most applied today is that when no food is present the animals were less eager to explore the central part of the arena, increased whole-field exploration, but tended to stick close to the walls. Thus in lack of a strong motivational que, the natural behavior seems to indicate exploration. Thigmotaxis ‘Sticking close to the walls’ refers to ‘Thigmotaxis’, which is an indicator of animal fear and is often considered as an index of anxiety and relates to agoraphobia in humans. This tends to decrease gradually during the first minutes of exploration of the open field, and is one of the main reasons why this test, and many others, are performed in a time span of minutes, at least in a classical setting (in a novel arena). Home cage testing: acute versus long term The open field can also be performed in a home cage, over a longer period of time. But be aware a different interpretation of the results is warranted, since the motivation of the test changes. Noldus’ PhenoTyper box is often used to perform the open field test in mice, since it’s top unit has an integrated video camera, powered by the EthoVision XT software.  The PhenoTyper, being a home cage monitoring system, generally is used to study long term locomotor behavior, in order to phenotype specific differences of a research model. The open field as it is implemented in behavioral batteries is intended to study acute thigmotaxis. LABEL Title Learn more Is the open field an anxiety test? Much discussion exists on the interpretation of the behavior displayed in the open field. This is based on the motivation of the animals’ behavior, which is thought to involve fear-induced escape rather than anxiety. Measuring anxiety, according to critics, should have both a positive and negative outcome. Which could be argued to be the case in the open field, since the central area is often well-lit and considered aversive (thus an interpreted negative outcome).  In any case, what is established, and seems to be the most common approach is to perform the open field at the beginning of the behavioral battery to asses general locomotor activity and anxiety before moving on to more complex behavioral paradigms. Anxiety in rodents also obviously much more complicated than a single parameter: thigmotaxis. This important anxiety-linked behavior is however often considered as a starting point for further anxiety tests, which can obviously strenthen the outcome.  Although the readout on anxiety can be subject to unreliability due to a high degree of sensitivity to variables, it still remains a common outcome, and important phenotypic, parameter of the open field test. LABEL Title Learn more Replication is key The open field, whether used to specifically measure anxiety or not, is an essential part of behavioral phenotyping. It creates a baseline behavioral profile for the specific research model. Also because of its widespread use there is an abundance of data on how specific interventions act upon the output of this test, therefore it’s value should not be underestimated.  As a researcher, pay very close attention to the testing conditions, limiting human interaction as much as possible, and aim for standardization within your own lab, and preferably other labs. Accurate documentation of your testing conditions is key for this, thus being replicable when others read your paper. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more [1] Hall, C., & Ballachey, E. L. (1932). A study of the rat's behavior in a field. A contribution to method in comparative psychology. University of California Publications in Psychology, 6, 1–12. --- ## The influence of teachers' motivation behaviors on students' engagement URL: https://noldus.com/blog/students-engagement-motivating-teaching-behavior Published: 2021-10-11 09:45:00 Description: The presence or absence of engagement determines the difference between success and failure. Does motivating teaching behavior keep students' focused and engaged? Engagement is a positive state, a happy feeling, the sum of powerful parts. It ensures that people become proactive, energized, focused, and that they feel more connected with what they are doing. When people are engaged, their motivation, productivity, and performance improves and there is no stress. The presence or absence of engagement determines the difference between success and failure. That is why this phenomenon is important in all kinds of places in society. At work, in social interaction with others, in marketing, and also in education. How do you know someone is feeling (highly) engaged? Dayenne Sarkol-Teulings created a custom expression in FaceReader to measure the level of engagement: learn more about her validation study by replaying the webinar 'How to measure engagement from facial expressions'. Students’ engagement and motivating teaching behaviors As a student, I was sometimes tempted to stare out the window during class to see what was happening there. That could be far more interesting, especially during a boring lesson about statistics. However, I learned nothing important from that. Instead, I missed critical notes. It is quite difficult to continuously pay attention or participate during class, but if you manage not to be distracted, it has a huge positive impact on your learning performance, skills development, and the grades you get. The way in which the teacher teaches has a big influence on whether or not you’ll manage to take part of the lesson. Teachers can increase their students’ engagement by establishing an overall motivating classroom climate and through adopting a motivating teaching style. The self-determination theory (SDT) is the basis for this. This video shows a customer story about improving teacher practices by using The Observer XT to analyze the interactions. Exploring behavioral patterns The research team of Miriam Cents-Boonstra of Radboud University, the Netherlands, aimed to extend previous SDT-related work and offer new insights into the dynamics of motivating teaching behaviors and students’ engagement, by exploring behavioral patterns. In order to gain clarity about these concepts, it is good to know that students’ engagement has two important characteristics to distinguish: - positive engagement – such as paying attention, asking questions, supplementing the teacher without any prompt, or taking initiative - negative engagement – such as being distracted, expressing boredom, disobeying rules, or complaining The concept motivating teaching behaviors support the basic needs of students: - autonomy – addressing students’ interest or opinions by asking questions or by offering choices - competence – providing support during assignments and positive constructive feedback - relatedness – providing warmth and unconditional respect In contrast, demotivating teaching behaviors neglect the basic needs of students and consist of (combinations of) controlling, chaotic, or ‘cold’ teaching. Observing – coding - analyzing Lessons of 52 teachers to first-years students of one Vocational Education and Training (VET) lecture were video-recorded, coded, and analyzed. The researchers aimed to answer three research questions: - How to offer new insights into the dynamics of motivating teaching behavior? - How to offer new insights into students’ engagement behavior? - Exploring patterns of teachers’ behavior. By observing, the researchers wanted to get insight into real-time manifestations between teacher and student behaviors. To investigate the patterns of teacher student interactions event coding was required. In other words, coding behaviors at the exact moment they occur. Creating a new coding scheme Another goal was to explore patterns comprising motivating and demotivating teaching behaviors on the one hand, and students’ positive and negative engagement on the other hand, both within and across lessons. Since an existing coding scheme was not available, they had to create their own. All videos were coded in The Observer XT by four coders. To compute the interrater reliability, five videos (10% of the available videos) were double coded. Download here the FREE white paper 'How to set up behavioral coding - 7 tips'. Data analysis using The Observer XT To answer the research questions, the analysis was divided in three different ways: - Descriptive statistics to gain a sense of the most recurrent behaviors. - Lag-sequential analyses to investigate the relationship between motivating or demotivating teaching behavior (lag0) and subsequent positive or negative student engagement (lag+1). - T-pattern analyses to identify patterns in teacher and student behavior. FREE TRIAL: Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial arrow_forward The research team identified more than 24,000 patterns. They used quantitative selection criteria in order to refine the pattern list to those relevant to this study: patterns of events that contained two actors (teacher and student), a minimum of one or two switches between actors, and a maximum length of three events were selected. This selection yielded 329 patterns. Additionally, a qualitative selection was made to derive patterns that started with (de)motivating teaching behaviors and ended with student engagement. Within the 329 found patterns, 126 patterns were relevant in answering the research questions. Out of these 126 patterns, all patterns that started with teaching behaviors followed by student behavior (TS) were selected and further investigated. Ways to motivate students A high percentage of the coded teaching behaviors (84%) was labeled as motivating. The observations showed that teachers mostly asked autonomy-supportive questions, called students into account in a motivating way, and provided positive feedback. Motivating teaching behavior was followed directly by positive student engagement in 85% of the occurrences. The most observed demotivating behaviors were asking controlling questions, providing negative feedback, and one-dimensional instructions. Remarkably, demotivating teaching behaviors were also followed by positive student engagement (66%), although to a lesser extent. Of all coded student behaviors, more than 81% were rated as positive student engagement. The students seemed eager to learn and asked lots of questions. However, students taking initiative was hardly ever observed.   Keeping students focused To ensure that students are positively engaged during class, a teacher can promote this by displaying motivational behavior. That will keep the students focused. Both existing teachers and future teachers should be supported in this, for example within the teacher education. References Ryan, R. M. & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. The American Psychologist, 55(1), 68–78. Cents-Boonstra, M.; Lichtwarck-Aschoff, A.; Lara, M.M. & Denessen, E. (2021). Patterns of motivating teaching behaviour and student engagement: a microanalytic approach. European Journal of Psychology of Education. https://doi.org/10.1007/s10212-021-00543-3 --- ## Scientific collaboration at its best: Home cage monitoring reviewed URL: https://noldus.com/blog/home-cage-monitoring-reviewed Published: 2021-10-06 14:30:00 Description: The latest insights and views on home cage monitoring was reviewed by Grieco et al. A collaborative paper with an expert team on home cage behavior was published last week. This blog touches upon their findings! Noldus is here to advance your research. This is not only realized through innovative technology, but academic contributions as well. Last week a multi-author review of PhenoTyper studies has been published in Frontiers in Behavioral Neuroscience, which is a co-production of 29 authors with a team of experts on home cage behavior from Noldus. Home cage monitoring reviewed Reproducibility crisis Grieco et al [1] address the reproducibility crisis (or replication crisis) in biomedical research, diving into several known and unknown sources of confounding environmental factors that add variance. This often leads to the inability of reproducing, or duplicating, the results of a prior study. Two major contributors to this are human interference and novelty-induced anxiety. To ameliorate this, automated home-cage monitoring systems like Noldus’ PhenoTyper have been developed that integrates with the powerful video-based tracking software: EthoVision XT. This makes it possible to perform prolonged and longitudinal recordings, providing information of spontaneous behavior that can be analyzed across multiple time scales and extracting digital biomarkers of motor, emotional, social and cognitive behavior. LABEL Title Learn more Image from Grieco et al [1]. Home cage monitoring system with cogition wall Standard tests This out-of-cage principal has been considered to be the standard in behavioral testing. However, these “standard” tests, like the open field or elevated plus maze, only capture brief behavioral snapshots at pre-determined time-points.  Home cage monitoring allows for continuous monitoring of behavior, adding an incredible amount of resolution to the behavioral output. Minor observations such as body posture changes and/or interaction with stimulus devices in the cage that are not observable with standard (short) tests can be included in the output with home cage monitoring. Also, previously unknown (pharmacological or genetic) models can be thoroughly phenotyped. Controlling variation Inter- and intra-laboratory variation needs attention according to the authors of this paper. There is a long list of environmental variables that researchers want to control: temperature, humidity, cage type, cage cleaning, position of cage, housing room, smells, experimental designs, handling, lighting, time of day, order of testing, to name a few. The scope of these variables can be daunting when setting up an animal experiment, and does cause a lot of variation, even between similar studies performed in the same lab. Home cage monitoring is aimed at limiting experimenter interactions and using uniform protocols. Handling of the animals for example is such an interaction and has a major impact on anxiety. The PhenoTyper has already facilitated reproducibility of activity-related (but not anxiety-related) phenotypes in the open field test, showing that it does eliminate environmental factors influencing reliability. LABEL Title Learn more FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system  Free Trial Reference 1.         Grieco, F. et al. (2021). Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives. Front. Behav. Neurosci., 15:735387. --- ## A critical view on the Forced swim test URL: https://noldus.com/blog/critical-view-forced-swim-test Published: 2021-09-21 12:30:00 Description: The forced swim test (FST), a staple in depression research, has been under discussion for a while. What is the FST? How is it used? And why is it under discussion? Here we share our view on this topic The forced swim test (FST) was first introduced as the ‘behavioral despair test’ by Porsolt et al. in the 70s [1,2]. As a common test for the evaluation of depressive-like state, this test has been extensively used, although modified from its original form, in the behavioral neurobiological field. Depression As depression is the world’s most predominant mental health problem [3], affecting approximately 280 million people worldwide, it is no surprise there is need for an adequate depression testing model. The development of new, but also the testing of existing, antidepressants often rely on tests like the forced swim test to predict their efficacy. The basics of the FST The forced swim test involves placing a rodent in a container filled with (lukewarm) water. The rodents naturally tries to escape, however fails to do so as is the design of the test. As animals give up after a certain period of time, and become immobile, they are removed from the container. Parameters such as activity and latency until immobility are used as readouts. Swimming behavior is generally increased after administration of (clinically used) antidepressants, which indicates a positive result in this test. This image is licenced under the Wikimedia Commons. Author: DataBase Center for Life Science (DBCLS) Valid model for depression? Discussion surrounding the FST has been around for a while. Primarily due to the severity of the test and its impact on animal welfare, the FST has come under considerable scrutiny. Also its scientific utility as a depression model is debated, as there is a lack of neurobiological correlation between the behaviors measured in this test, and the human situation. This discussion was also raised in a recent paper written in part by the staff of the National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) in the United Kingdom (UK) [4]. They address misconceptions and provide clarification about the use of the FST as a regulatory requirement for the development of new antidepressants. As a result of researchers using regulatory requirement as justification for the continued use of the FST, the authors of this paper clarified that this is not stipulated by regulators. These authorities are pushing to refine in vivo tests and alternatives to increase animal welfare while retaining robustness and translational validity. 3R funding The NC3Rs has a number of funding possibilities aimed specifically at the 3Rs (replacement, refinement and reduction) to promote future advancements in this context. Wellcome is another UK based foundation involved in 3R funding, but other countries, for example Germany and Sweden (applications closed), also promote this. Should we still use the FST? It is important to compartmentalize the discussion surrounding the FST, as it still remains an important scientific tool in academia, drug discovery and the research industry where high throughput screening of novel compounds is essential. The FST is still a test with a considerable level of predictive validity, however should definitely not be considered a full spectrum analog of human depression. The outcomes of the FST are one-dimensional, however the implementation is also relatively simple and inexpensive. This is an extremely important trade-off to consider, but should not devalue the usefulness of the FST as a drug discovery and validation tool. Full disease models, analog to humans, are very difficult (if not impossible) to approach. Usually a model approaches a specific subset of symptoms, which can then be investigated separately, gaining a piece-by-piece understanding of its underlying mechanism. Lastly, due to the wealth of data regarding the effects of antidepressants in the FST, researchers are able to compare and contrast their own results with others. This becomes even more so due to advancements in behavioral scoring software and standardized setups. This blog represents a realistic view on the topic of the FST. We at Noldus are aware of the discussion surrounding this test and are constantly aiming at the abovementioned technological advancements and refining behavioral research tools. With a large amount of in-house knowledge and collaboration with the scientific field, these advancements are made in tracking software and hardware. This greatly contributes to the reduction and refinement of animal experiments, while warranting unseen distress.               FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system  Free Trial   References - Porsolt, R. D.; Anton, G.; Blavet, N.; Jalfre, M. (1978). Behavioural despair in rats: A new model sensitive to antidepressant treatments. Eur. J. Pharmacol., 47 (4), 379–391 - Porsolt, R. D.; Le Pichon, M.; Jalfre, M. (1977). Depression: a new animal model sensitive to antidepressant treatments. Nature, 266 (5604), 730–732 - Institute of Health Metrics and Evaluation. Global Health Data Exchange (GHDx).  http://ghdx.healthdata.org/gbd-results-tool?params=gbd-api-2019-permalink/d780dffbe8a381b25e1416884959e88b (Accessed 1 October 2021). - Sewell, F.; Waterson, I.; Jones, D.; Tricklebank, M. D.; Ragan, I. (2021). Preclinical screening for antidepressant activity – shifting focus away from the Forced Swim Test to the use of translational biomarkers. Regul. Toxicol. Pharmacol., 125, 105002 --- ## The influence of ad-evoked emotions on brand attitudes URL: https://noldus.com/blog/influence-ad-evoked-emotions-brand-attitudes Published: 2021-09-16 10:30:00 Description: Can brand authenticity generate positive emotions among consumers and turn into a positive brand attitude? This blog post was written by two guest bloggers: Juliette Geerts and Jade Kraan, both graduated for their Master in Communication Sciences at the Radboud University, Nijmegen, The Netherlands. The influence of ad-evoked emotions on brand attitudes Two studies on the influence of ad-evoked emotions on consumer brand attitudes were conducted using FaceReader Online. This blog post explains the design and results of both studies, and explains how FaceReader Online offered a solution for obtaining new insights. Study 1: The effect of brand activism ads on consumer emotions Consumers today expect brands to speak out on social issues and do not accept it when brands remain silent on these issues1,2,3,4. This has led to the emergence of a new marketing trend, with advertising at the intersection of politics, commerce, and activism5. These brand activism ads seem to be the ultimate opportunity to start a conversation with the target group. However, experts indicate that there is a brand activism paradox: consumers want brands to take a stand, but when brands do, consumers are suspicious about their motives6. The solution according to science? Brands must appear authentic in their brand activism advertisements by naming a concrete action7. Brand authenticity can then generate positive emotions among consumers, which in turn can generate a positive brand attitude8,9,10.  For marketing managers, this could be a beneficial solution to the brand activism paradox. This theory has therefore been tested in this study (see figure 1). Figure 1. Research model study 1 Experimental design of study 1 The research population of study 1 consisted of Dutch young adult consumers (18-30 years). For the purpose of the experiment, a brand activism video ad was manipulated so that the experimental group and the control group were exposed to different ads (brand activism ad with action vs. without action). The brand advertised in the study was Vitality Clothing. This American brand is unknown in the Netherlands. This way, participants could not use existing cognitive brand schemas (knowledge about the brand) and these schemas would not influence the perceived brand authenticity and brand attitude. Study 2: Does a character’s facial expressions affect a consumer? Today’s large number of advertisements increases consumer’s selective attention. More and more consumers need to decide which advertisements they pay attention to and which they don’t. As a result, advertisers compete for consumer attention, leading to ever-increasing advertising costs11,12. Therefore, advertisers need an advertising method that will reach many consumers without having to pay high advertising costs. Customer-led storytelling is such a method that may offer an effective solution for advertisers13. Customer-led storytelling is a narrative advertising method in which the customer of a brand shares his or her personal emotions and experiences with that brand in the form of a story. This personal customer story links emotions and experiences to features and functions of the advertised brand. This link is what makes customer-led storytelling unique14,15. This study expects that a consumer exposed to a customer-led storytelling ad will be able to empathize with the character. This empathy leads to the consumer feeling what the character feels, which can influence the consumer's brand attitude. A schematic representation of this expectation can be found in the research model (Figure 2). Figure 2. Research model study 2 Experimental design of study 2 Study 2 was conducted among Dutch-speaking young consumers between the ages of 18 and 30, living in the Netherlands or Belgium. In the study, 105 participants were randomly divided into two groups. Both groups were shown a video ad of an existing suitcase brand (AWAY). This is an American brand, which has a high chance of non-existing brand attitude of the participants for the advertised brand AWAY. This was necessary in order to avoid previous attitudes to influence the experiment. The content of the message, which was shown in subtitles in each video, was different between the groups. Group 1 was shown an advertisement with a customer-led storytelling message and group 2 received an actual (non-narrative) message without a character. Other variables of the video such as footage, length, and background music remained the same for both groups. Figure 3. Screenshot video ad group 1. Translation of the subtitles: I am Sandra and I know that my AWAY suitcase won’t let me down. Figure 4. Screenshot video ad group 2. Translation of the subtitles: Travel without any worries with the suitcases of AWAY. How FaceReader Online could provide new insights In previous studies in the context of brand activism and storytelling, other researchers used self-report scales for measuring emotions. However, this method cannot be considered as an accurate way to capture emotions for a number of reasons. First of all, emotions are known to be unstable and temporary and are interpreted differently by different consumers8,16,17. In addition, the mental activity evoked by advertisements often operates on a subconscious level, making it impossible for consumers to report on18,19. One way to accurately measure emotions is to measure muscle activity in facial expressions. For this reason, Noldus' FaceReader Online was used in the studies described in this blog. With FaceReader Online the various conscious and unconscious emotions can be accurately measured on the basis of facial expressions. In addition, FaceReader Online provided a solution to the limitations of Covid-19, since it allowed the respondents to participate in the research, without the need of visiting a research lab. FREE WHITE PAPER: FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download arrow_forward Speed up the analysis process The studies in this blog post used a Qualtrics survey. FaceReader Online could easily be linked to the survey. In this way, the integration of the measuring instrument was experienced as simple and pleasant for both the researchers and the respondents.  In addition, the respondents were guided through clear instructions during the measurement, which led to high quality measurements and little dropout of respondents. The recordings were analyzed very quickly and then displayed in a clear dashboard with handy graphs and figures. What is most useful about FaceReader are the outcome measures that are calculated. Mainly valence of all emotions and arousal are calculated for each individual respondent, which greatly simplifies and speeds up the analysis process. Research findings using FaceReader Online Study 1: Brand activism Using FaceReader Online, it was found that women experience more positive emotions than men when viewing a brand activism video ad. FaceReader Online also confirmed that product engagement has a positive effect on consumer emotions. Study 2: Customer-led storytelling This study found no effects between customer-led storytelling and brand attitude. On top of that, the empathy for the character, which respondents did or did not experience, and the shown emotions of the respondents could not explain the relationship between customer-led storytelling and brand attitude. Despite the fact that no relations have been found, this study does give reason to further research. This study has several limitations, which a follow-up study could take into account. As a first limitation, the results showed that the respondents did not find the brand attractive, which hindered their ability to empathize with the character20. Secondly, it is also possible that the participants experienced the advertisement as intrusive. Research shows that showing neutral facial expressions can be a resistance reaction to the persuasive message21. Since mostly neutral facial expressions were measured, this may explain why the ad had no influence on the respondents' brand attitude. Finally, this study also opted for one advertisement that differed solely in the content. A non-expressive product has been chosen for this. Even though this type of product is not based on emotions, it is not possible to develop an advertisement with an expressive product without communicating about emotions. This choice may have hindered participants from experiencing a strong emotional response, which may have resulted in no effects being found. Considering these limitations, a follow-up study should use a pre-test to find out which brand the respondents find attractive. By doing this, the study makes sure that the respondents empathize with the character. Besides, instead of manipulating a customer-led story advertisement versus a non-customer-led storytelling advertisement, the follow-up study could manipulate the storytelling perspective by telling a customer-led story versus a brand story told from a company’s perspective. This way the advertisement of the follow-up study would use an expressive product that communicates strong emotions.  FaceReader Online scores well among researchers FaceReader Online is an effective, reliable and easy way of measuring emotional responses to advertisements. Not only did it allow the researchers to easily analyze the respondents’ facial expressions, it was also experienced as a pleasant measurement tool by the respondents. References - Cramer, K., & Koene, A. (2020). How brands are working on the economy of the 21st century. Amsterdam, Nederland: BR-ND People Emotive Transformers. - Gast, A., Illanes, P., Probst, N., Schaninger, B., & Simpson, B. (2020). Purpose: Shifting from why to how. Accessed on February 2, 2021 of https://www.mckinsey.com/business-functions/organization/our-insights/purpose-shifting-from-why-to-how - Schoeneck, H., & White, P. (2020, 16 oktober). Why Brand Activism Will Be Here to Stay, Long After 2020.  Accessed on February 2, 2021 of https://www.triplepundit.com/story/2020/brand-activism-2020/707201 - Wilcox, D. L. (2019). Dialogic Communication Theory in the Age of Corporate Activism: A Postmodern Perspective. Communication and Media in Asia Pacific, 2(1), 1-10. https://so01.tci-thaijo.org/index.php/CMAP/article/view/163778 - Manfredi-Sánchez, J.L. (2019). Brand activism. Communication & Society, 32(4), 343-359. https://doi.org/10.15581/003.32.4.343-359 - Livas, C. (2020). The Powers and Perils of Societal Advertising. Journal of Macromarketing. 1-17. https://doi.org/10.1177/0276146720978261  - Vredenburg, J., Kapitan, S., Spry, A., & Kemper, J. (2020). Brands Taking a Stand: Authentic Brand Activism or Woke Washing? Journal of Public Policy & Marketing, 39(4), 444-460. https://doi.org/10.1177/0743915620947359  - Hong, C. (2018). Boycotting or Buycotting? An Investigation of Consumer Emotional Responses towards Brand Activism (Dissertatie). https://scholarship.miami.edu/esploro/outputs/doctoral/Boycotting-or-Buycotting-An-Investigation-of/991031447968002976 - Romani, S., Grappi, S., Zarantonell, L., & Bagozzi, R. P. (2015). The revenge of the consumer! How brand moral violations lead to consumer anti-brand activism. Journal of Brand Management, 22(8), 658-672. https://doi.org/10.1057/bm.2015.38  - Yoo, C., & MacInnis, D. (2005). The brand attitude formation process of emotional and informational ads. Journal of Business Research, 58(10), 1397-1406. https://doi.org/10.1016/j.jbusres.2005.03.011  - Tabor, E. (2018). Waarin zit ’m de positieve invloed van influencers? Accessed on January 11, 2021 of  https://twinklemagazine.nl/2018/11/ influencermarketing-onlineretailers/index.xml - Zatwarnicka-Madura, B. & Nowacki, R. (2018). Storytelling and its impact of effectiveness on advertising. In F. Bylok, A. Albrychiewicz, & L. Cichoblazinski (Eds.), 8th International conference on management - leadership, innovativeness and entrepreneurship in a sustainable economy (pp. 695-700). Czestochowa: Czestochowa University of Technology. - Willemsen, L. (2019). Storytelling: zo effectief zijn brand stories echt. Accessed on February 1, 2021 of  https://www.marketingfacts.nl/berichten/storytelling-zo-effectief-zijn-brand-stories-echt - Kattan, O. (2012). Consumer-led Storytelling: Brand communication in a new Age. Accessed on January 31, 2021 of https://www.huffpost.com/e ntry/consumerled-storytelling-_b_1956919?guccounter=1 - Katz, L. (2019). 8 exceptional examples of customer-led storytelling. Accessed on January 31, 2021 of https://www.clearvoice.com/blog/customer-led-storytelling/ - Barrett, L. F. (2017). How Emotions are made. The secret life of the brain. Revue québécoise de psychologie, 40(1), 153-157. doi: 10.7202/1064926ar - Suhr, Y. T. (2017). FaceReader, a Promising Instrument for Measuring Face Emotion Expression? A Comparison to Facial Electromyography and Self-Reports (Master’s thesis). Accessed on https://dspace.library.uu.nl/handle/1874/352187 - Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The Role of Emotions in Marketing. Journal of the Academy of Marketing Science, 27(2), 184-206. https://doi.org/10.1177/0092070399272005  - Mizerski, R., & White, D. J. (1986). Understanding and using emotions in advertising. Journal of Consumer Marketing, 3(4), 57-69. https://doi.org/10.1108/eb008180  - Kim, C.K., Han, D. & Park, S.B. (2002). The effect of brand personality and brand identification on brand loyalty: applying the theory of social identification. Japanese psychological research, 43(4), 195-206. https://doi.org/10.1111/1468-5884.00177  - Lewinski, P., Fransen, M.L. & Tan, E.S. (2016-b). Embodied resistance to persuasion in advertising. Frontiers in psychology, 7, 1202. https://doi.org/10.3389/fpsyg.2016.01202  --- ## Sunshine and romance: ultraviolet light enhances sexual behavior URL: https://noldus.com/blog/ultraviolet-light-enhances-sexual-behavior Published: 2021-09-13 12:00:00 Description: Ultraviolet B rays in sunshine enhances our romantic passion. How this actually works is still largely unknown. Research at the Tel Aviv University provides new insights. Sunshine makes me happy. And apparently, it also makes us romantic. Maybe that is why sunny afternoon strolls are part of so many romantic movies… Well, unlike many things that only happen in movies, sunlight enhancing romance is a scientific fact.  It’s the UV  So, it’s the sun that makes us all lovey-dovey? It is actually the ultraviolet (UV) light that makes us act this way. It enhances our romantic passion. How this actually works in our body is still pretty unclear, but we do see a lot of similarities in other species. A group of researchers at the Tel Aviv University, Israel set out to investigate. Their results were recently published in Cell Reports.  How our skin dictates our behavior The UV light in sunshine affects the production of hormones and our behavior. Researchers found specifically UVB rays are responsible for this.  While our skin is often the target of hormones, it is also a source of hormones. In this way, it is implicated in sun-addiction and stress-related behaviors, and it is fair to assume it also plays a role in social, sexual, and reproductive behavior.  How it is regulated Triggered by UVB exposure, the skin signals the brain: the hypothalamus and in turn the pituitary gland. They produce hormones that activate the male testicles and female ovaries to produce sex-steroids like testosterone, estrogen, and progesterone. During pre-ovulation female sexual behavior changes, and males are more attracted to their scent and facial appearance.  Mouse test The researchers from the Tel Aviv University wanted to know more about this mechanism and tested a group of mice. They were partially shaven to take away their ‘natural sunscreen’ and got a daily UVB radiation dose similar to 20-30 minutes of midday sun.  There were no acute results, but over time blood samples showed a chronic upregulation of estrogen, androgen, estradiol, progesterone in female mice and estradiol, testosterone, and estrogen in male mice.  LABEL Title Learn more Mice and mating behavior They continued by studying the romance between mice: mating behaviors sniffing, self-grooming, intromission, lordosis, and ejaculation were measured. It turns out that males were more attracted to UVB exposed females and also more successful in mating with them. These females (all in their estrus/proestrus stage) were also more receptive. Scream for love: ultrasonic vocalizations Mice talk, but we cannot simply hear the ultrasonic frequency they converse at. So, using UltraVox XT, these vocalizations were recorded. Male mice dominated the conversation: call duration and frequency were significantly higher when these males were matched with UVB treated females. This confirms the behavioral findings. Perfume or love: does partner smell matter? The next question was what actually attracts mice to each other. Is it just behavior or do they also like the way their partner smells? Researchers conducted a three-chambered test with EthoVision XT video tracking to find out.  A subject mouse was free to explore three adjacent chambers, the outer two each held one wired cage each containing a mouse of the opposite sex: one UVB treated and one untreated.  When given a direct choice, males were again clearly more attracted to the UVB treated females. Interestingly, the opposite was not true. UVB exposure did not make a male more attractive for females. However, it did seem that the UVB exposure increased overall social behaviors in both male and female subjects.  The ‘sun-gene’ One question remained: what makes the skin set all of this in motion? These researchers found the answer: A transcriptor gene regulates this process: “p53” found in skin cells. When this gene was knocked out in a group of mice, the effect of the UVB exposure on both hormone levels and behavior disappeared.  Sunshine makes the heart grow fonder Mice are not men. So how do these results compare to our human love story? A cohort of human patients underwent sessions of phototherapy and were asked to fill out a questionnaire before and after, to measure “passionate love” and “longing for each other”. After a good dose of sunshine, men reported to have more obsessive thoughts about their loved one, yearn to learn about this person and have more desire for affection from this person. Women scored higher when they were asked if their partner is the perfect romantic partner and they had a higher physical response when they touched that person.  Skin color and testosterone Researchers were also able to recruit human volunteers for blood sampling and found an increase in sex hormones in both men and women after sun exposure, similar to the results obtained from the mouse study.  In addition, other samples from health services indicated that men have a significant peak in testosterone during the summer, and revealed that skin coloration actually correlates with the amount of testosterone found in these samples taken during the summer, but not in the winter months.  Discover something new This study took an elaborate look at how sunshine sets a hormonal pathway in motion and affects romantic/sexual behavior, and gave more detail on how this mechanism works. Its role in our romantic happiness, or more specifically, how our body makes this happen.  The discovery of the involvement of the p53 gene, as well as the details of this causal mechanism will hopefully prove useful in the treatment of sex-hormone-related dysfunctions in humans in the future.  References - For more research from the group at the Tel Aviv University, visit their website.  - Parikh, R.; Sorek, E.; Parikh, S.; Michael, K.; Bikovski, L.; Tshori, S.; Shefer, G.; Mingelgreen, S.; Zornitzki, T.; Knobler, H.; Chodick, G.; Mardamshina, M.; Boonman, A.; Kronfeld-Schor, N.; Bar-Joseph, H.; Ben-Yosef, D.; Amir, H.; Pavlovsky, M.; Matz, H.; Ben-Dov, T.; Golan, T.; Nizri, E.; Liber, D.; Liel, Y.; Brenner, R.; Gepner, Y.; Karnieli-Miller, O.; Hemi, R.; Shalgi, R.; Kimchi, T.; Percik, R.; Weller, A.; Levy, C. (2021). Skin exposure to UVB light induces a skin-brain-gonad axis and sexual behavior. Cell Reports, 36, 109579. --- ## Why use Virtual Reality in Neurosciences? URL: https://noldus.com/blog/virtual-reality-in-neuroscience Published: 2021-09-06 09:55:00 Description: Virtual Reality may become an easy way to calibrate or standardize complex tasks in immersive environments. How can researchers easily apply VR? This blog is written by Professor Stéphane Besnard. He and his colleagues from the University of Caen, Normandie, France, developed a tool to measure cognitive functions in a virtual reality environment.  If you are interested in using such a tool, please contact Arjan Veenboer (arjan.veenboer@noldus.nl). Why use Virtual Reality in Neurosciences? Investigating human behavior is challenging, especially if you want to do this in a natural or realistic environment. Studying social interactions, investigating the ergonomics of a workstation, or monitoring a patient at home for follow-up purposes or for early screening of disease symptoms are a few examples of that. Within this kind of research obstacles such as technological challenges, expansive costs, and a lack of standardization remain. Measuring specific and complex brain functions When we want to test even more specific and complex brain functions like spatial cognition, multitasking skills, and cognitive saturation in an active way, we face several limits again. Current tools like questionnaires (“Do you often get lost in the city?”) are unreliable, weakly sensitive, and unable to scale all the subjective aspects that this method involves. Virtual Reality (VR) may offer a very good compromise with great potential for neuroscience research. Indeed, virtual reality may now become an easy way to calibrate or standardize complex tasks in immersive environments. However, how can researchers easily apply VR? To learn more about the basics of cognitive neuroscience, check out this blog post' Origins and current use of VR Maze A few years ago, our research team started from the need to compare spatial memory deficits in patients suffering from vestibular pathology with our vestibular-deficient animal models. Vestibular patients suffer from cognitive troubles (disorientation, loss way, self-perception troubles, and even symptoms that may be related to psychiatric syndromes) that are not routinely investigated by clinicians.  Although, it was easy to test our animal models in physical calibrated mazes, such as T-maze, Y-maze, Eight radial maze, and Morris Water Maze [1,2,3,4], we didn’t have any similar evaluation with our patients. The current neuropsychological tests were not sensitive enough and could not be compared to rodent testing. The search for more complex tests in 2D and 3D, without any commercial solution, did not yield a good match. Therefore, in collaboration with our Virtual Reality department we developed three first tests in 3D VR, similar to rodent mazes. We then validated on control subjects whether these tests allowed orientation and spatial memory learning evaluation [5]. Developing protocols to further research vestibular pathology Next, we developed protocols to investigate specific orientation impairments in patients suffering from a vestibular pathology. The vestibular system is the sense organ of gravity related motion perception. In case of vestibular pathology or microgravity conditions, the sensors of the vestibular organ are damaged or become not functional respectively. For example, this happens to astronauts when they are in space, their spatial orientation gets impaired [6]. We developed protocols testing attentional abilities and orientation in microgravity during parabolic flights [7]. In the context of microgravity studies, we work more globally on Human’s Adaptation in Extreme Environment. Therefore, we need to specifically explore complex brain functions and have an individual cross-sectional approach by combining a complete assessment from physiological parameters to emotional and cognitive functions as well. It is now extended to study cognitive, physiological functions, and locomotor activity  during a scientific expedition (www.deeptime.fr) combining quantitative parameters (heart rate, electromyographic activity, or postural/balance control) with psychological questionnaires and 3D virtual reality testing (emotion and spatial cognition) programmed from VR Maze. The results of this study are foreseen by the end of 2021. What is VR Maze? VR Maze is a software solution, which allows you/scientists, without infographics and programming expertise, to easily design any experimental protocol in 2D or 3D in an interactive 3D virtual environment. VR Maze displays tasks on a computer screen, virtual reality headset, or complex Cave-type system/immersive room. We have developed this tool to enable unlimited evaluations of performances or deficits of brain functions (cognition, emotion, attention, memory, etc.). It offers the possibility to combine a questionnaire-based assessment with a more sophisticated assessment using 2D and 3D tests. VR Maze offers the same tests as those used with rodents (Morris pool, eight-branch maze, inverted T-maze, etc.) in 2D and 3D, enabling research units working with animal models to evolve towards human and patient exploration. Moreover, VR Maze can reproduce in-situ environments in a lab or work directly in extreme environments. Measuring multiple variables The analysis module of VR Maze combines all the variables measured during VR tests, such as: - reaction time - head position - walking speed - gaze position - number of errors - virtual and physical trajectories These variables can be combined with external parameters synchronously recorded from our data acquisition systems (ECG, EMG, EEG, gravity and pressure centers, etc.) and/or can be synchronized to stimulation modules (e.g. vestibular sensory stimulation). All the recorded data is then filtered on demand and compared to produce a highly accurate result extraction. LABEL Title Learn more What environments can be generated? VR Maze is now opened up to create environments specific to your needs. From simple mazes to explore spatial memory and orientation skills, to scenarios to explore the effectiveness of rehabilitation or hypnosis protocols, to specific dedicated professional environments. VR Maze has been designed to push the limits of human behavioral exploration in multiple areas, for example: - Research - Health - Rehabilitation - Neuromarketing - Security - Defense LABEL Title Learn more 3D antic environment for spatial navigation and memory LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more Virtual health care unit for learning or testing LABEL Title Learn more Virtual boat for specific professional learning and spatial strategy LABEL Title Learn more LABEL Title Learn more REQUEST INFORMATION Are you interested in our behavioral research solutions, and want to get in contact? - Worldwide: Always near to you - Make your project a success - Trust our 30 years of experience  Contact us References - Besnard, S.; Machado, M.L.; Vignaux, G.; Boulouard, M.; Coquerel, A.; Bouet, V.; Freret, T.; Denise, P. & Lelong-Boulouard, V. (2021). Influence of vestibular input on spatial and nonspatial memory and on hippocampal NMDA receptors. Hippocampus, 22(4), 814-826. https://doi.org/10.1002/hipo.20942 - Machado, M.L.; Lelong-Boulouard, V.; Smith, P.F.; Freret, T.; Philoxene, B.; Denise, P. & Besnard, S. (2012). Influence of anxiety in spatial memory impairments related to the loss of vestibular function in rat. Neuroscience, 218:161-9. https://doi.org/10.1016/j.neuroscience.2012.05.029  - Machado, M.L.; Lelong-Boulouard, V.; Philoxene, B.; Davis, A.; Denise, P. & Besnard, S. (2014). Vestibular loss promotes procedural response during a spatial task in rats. Hippocampus, 24(5), 591-597. https://doi.org/10.1002/hipo.22251 - Machado, M.L.; Kroichvili, N.; Freret, T.; Philoxène, B.; Lelong-Boulouard, V.; Denise, P. & Besnard, S. (2012). Spatial and non-spatial performance in mutant mice devoid of otoliths. Neuroscience Lett., 522(1):57-61. https://doi.org/10.1016/j.neulet.2012.06.016  - Machado, M.L.; Lefèvre, N.; Philoxene, B.; Le Gall, A.; Madeleine, S.; Fleury, P.; Smith, P.F. & Besnard, S. (2019). New software dedicated to virtual mazes for human cognitive investigations. J Neurosci Methods, 327. https://doi.org/10.1016/j.jneumeth.2019.108388 - Stahn, A.C.; Riemer, M.; Wolbers, T.; Werner, A.; Brauns, K.; Besnard, S.; Denise, P.; Kühn, S. & Gunga, H.C. (2020). Spatial Updating Depends on Gravity. Front Neural Circuits,14. https://doi.org/10.3389/fncir.2020.00020 - Friedl-Werner, A.; Machado, M.L.; Balestra, C.; Liegard, Y.; Philoxene, B.; Brauns, K.; Stahn, A.C.; Hitier, M. & Besnard, S. (2021). Impaired Attentional Processing During Parabolic Flight. Front. Physiol. https://doi.org/10.3389/fphys.2021.675426  --- ## Entrepreneurs’ facial expressions & emotional contagion during investor pitches URL: https://noldus.com/blog/facial-expressions-emotional-mimicry Published: 2021-09-02 09:54:00 Description: What is the influence of emotions in a decision-making process? Dinkla and Liebregts wondered if displaying joy and emotional mimicry play a role during pitches. This blog post was written by two guest bloggers: Daan Dinkla and Werner Liebregts from Tilburg University, the Netherlands. Raising funding is crucial for most startups to realize their growth ambitions and become successful. Convincing investors to fund your startup can be difficult as large information asymmetries exist. Investors are typically generalists and the entrepreneurs usually know more about their startup, motivation, commitment and target market than they do. Therefore, investors partly rely on signals provided by the entrepreneur to reduce this asymmetry. These signals consist of concrete actions like the entrepreneur committing personal wealth, but also certain emotions displayed by the entrepreneur like passion or joy for solving a problem are shown to help convince investors. Investigating mechanisms behind emotions This might sound like a familiar topic to you. A few months ago, the blog post: “The role of entrepreneurs’ facial expressions to gain financial support” on this medium was written about the display of positive emotions by entrepreneurs during their pitches and the effect these emotions have on attracting funding. That blog was based on academic research by Jiang, Yin and Liu (2019). This new blog post describes recent research by Daan Dinkla under the supervision of Werner Liebregts, who both are authors of the current blog. They replicated the work by Jiang et al. (2019) using a different sample of (student) entrepreneurs and professional investors in a different context, and investigated the mechanisms behind the emotional effects using FaceReader.               FREE WHITE PAPER: FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output  Download   Peak moments of experienced emotions Like Jiang et al. (2019), Dinkla and Liebregts looked at a specific moment of displaying positive emotions, namely the peak intensity. Why peak intensity? When evaluating and summarizing an event retrospectively, not every moment is equally important; people are shown to rely most on peak moments of experienced emotions during that event. Through emotional contagion, a process by which people automatically mimic and subsequently ‘catch’ the emotions of others they are interacting with, investors are thought to reach this peak emotional state at the time when the displayed emotion by the entrepreneur is at its peak level. The entrepreneur is thus thought to ‘infect’ the audience with their displayed emotions. The research by Jiang et al. (2019) showed support for a positive relation between the peak intensity of displayed joy and the amount of funding Kickstarter entrepreneurs raised. However, the process of emotional contagion is still a black box in contemporary entrepreneurship research. It is assumed to happen during pitches, but no research has actually verified whether contagion really takes place. Dinkla and Liebregts are the first to evaluate this mechanism behind the effect of displaying joy on pitch success. Emotional contagion during investor pitches They do this by investigating the first step in the contagion process, which is emotional mimicry. They specifically test whether or not immediately after the peak intensity of displayed joy by the entrepreneurs, displayed joy levels of the investors rise above a certain significance level as well. This would indicate that investors indeed mimic the happiness that entrepreneurs display. This mimicry can then potentially lead to emotional contagion. Video recording behaviors during pitches How were the effects measured in their replication study? Student entrepreneurs pitched their business ideas during a pitch competition in front of three professional investors (VCs and BAs). For the pitch success measure, investors were asked to indicate how willing they were to invest in the startup pitched by the students. Both the students and the investors were video recorded during the pitch. Their facial expressions were analyzed using FaceReader, a software program for facial expression analysis by Noldus Information Technology. FaceReader is trained to classify facial expressions into one of the six basic emotions (happy, sad, angry, surprised, scared, disgusted) or a neutral state using artificial intelligence (AI). Facial action units indicate the expression Facial expressions are classified into emotions by looking at facial action units, these are the smallest visually discriminable facial movements. The co-occurrence of some of these action units indicates the expression of a certain emotion. Joy is for example characterized by the presence of two action units, lip corner puller and cheek raiser. The FaceReader software package is one of the most scientifically validated automated facial recognition programs and is shown to be of similar, or even better, accuracy as human coders (Lewinski, den Uyl & Butler, 2014). FaceReader allowed Dinkla and Liebregts to classify movement of facial muscles (action units) into emotions automatically for each frame of every video. Download here the FREE white paper 'Facial Action Coding System (FACS)' Does emotional mimicry lead to an investment? So what effects of displaying joy were found? Dinkla and Liebregts found support for the hypothesis that occurrence of emotional mimicry is related to peak joy. In other words, emotional mimicry is more likely to happen if the intensity of joy displayed by the entrepreneur is higher. An effect of this mimicry on the willingness to invest is absent, however. There is no significant relationship between mimicking the emotion of the entrepreneur by the investor and their willingness to invest. Possible explanations for this non-result are that investors are able to cancel out their emotional state and mainly focus on other, possibly more concrete, aspects of the pitch to make an investment decision. Or possibly investors mimic the entrepreneur subconsciously but this mimicry does not lead to contagion; academic research has shown that mimicry does not always lead to emotional contagion. The influence of emotions in a decision making process Dinkla and Liebregts also find in their replication study that an entrepreneur displaying joy has a negative effect on the willingness to invest of the investors in the audience. Interestingly, this is the opposite effect found by Jiang et al. (2019). Those authors find displaying joy has a positive effect on the amount of funding raised by the entrepreneur on Kickstarter. What might be the cause of this difference in effects? Well, there are a few differences between both studies. Most importantly, Dinkla and Liebregts focus on students pitching to professional investors, while Jiang et al. (2019) study (non-live) pitch videos on Kickstarter. Differences might exist between how much the different types of audiences (professional vs. mostly consumers) rely on or are influenced by emotions in their decision making process. Results on the effect of displaying emotions during pitches are thus not conclusive yet. Future research hopefully identifies when and how exactly emotions influence the outcome of a pitch in greater detail. References Jiang, L., Yin, D., & Liu, D. (2019). Can joy buy you money? The impact of the strength, duration, and phases of an entrepreneur’s peak displayed joy on funding performance. Academy of Management Journal, 62(6), 1848-1871. Lewinski, P., den Uyl, T. M., & Butler, C. (2014). Automated facial coding: validation of basic emotions and FACS AUs in FaceReader. Journal of Neuroscience, Psychology, and Economics, 7(4), 227. For more information please contact  Dr. Werner Liebregts W.J.Liebregts@tilburguniversity.edu --- ## What is DanioVision? A brief insight in zebrafish tracking URL: https://noldus.com/blog/what-is-daniovision Published: 2021-09-01 12:00:00 Description: In this blog we provide a quick refresh on the topic of zebrafish, and how DanioVision contributes to this field. A small fish might not be the first thing that comes to mind in (neuro)biological studies. Nonetheless, the zebrafish (Danio rerio), a tropical fish native to Southeast Asia, has been used as a model organism since the 1960s, although only gaining popularity since the 1990s/2000s. The zebrafish: - is small and robust - reproduces, and grows, at an extremely fast rate - is cheaper to maintain than mice These are among the many advantages of the use of the zebrafish as a model organism, but most importantly, the complete genome of the zebrafish has been sequenced, which uncovered 70 per cent shared genes with humans. What is DanioVision? A brief insight in zebrafish tracking The zebrafish combines some of the best features of other model organisms. But one extremely useful characteristic is it’s transparent embryonic and larval stage. This makes it possible to label specific cells (for example with GFP), allowing researchers to externally examine the internal development of blood vessels, muscles and the nervous system using a low-power microscope. This gives a unique insight into vertebrate development. LABEL Title Learn more A complete, but customizable, turn-key system Cleverly named DanioVision, this complete system is specifically designed for the purpose of studying zebrafish larvae activity, movement patterns and other basic measurements. This can reveal information on stereotypic and epileptic behaviors, circadian rhythmicity, motor control, movement disorders, neural development, and more. Making this an essential tool for researchers to implement high-throughput testing of zebrafish larvae. DanioVision is however not limited to zebrafish. Other organisms such as  amphibians (in the tadpole stage), larval fruit flies (Drosophila Melanogaster) and even juvenile cuttlefish (Sepia Bandensis) are studied using this system. LABEL Title Learn more DanioVision consists of an observation chamber integrated with EthoVision XT video tracking software. The design of the chamber is standardized in order to observe larvae, tadpoles or other juvenile models in standard ANSI and SBS compliant multi-well plates. DanoVision’s observation chamber shuts out external light, absorbs vibrations as much as possible and has an add-on temperature control unit. This ensures a controlled and stable testing environment.  A backlit plate holder provides even lighting across the well plate and ensures that your plate or other container is placed in the exact same position every time, making video recalibration between trials a thing of the past.  For a detailed description, and all possible features and add-ons of the DanioVision system, check out this page! LABEL Title Learn more The power of the zebrafish The real importance of zebrafish research with the DanioVision system is brought to light by the sheer impact of recent published papers on this model organism. Treatments of neurodevelopmental disorders, such as epilepsy, have been investigated with the use of a mutant Dravet syndrome line in a recent study by Banerji et al [1]. Griffin et al also performed crucial phenotypic analysis of epilepsy in zebrafish as part of ‘the Epilepsy Zebrafish Project’ [2].  Further research topics can include, but are not limited to, muscle disorders [3], senescence [4] and even ALS [5]. Zebrafish research is however not limited to neuroscience. Environmental studies on the toxicity of herbicides and its detrimental effects on aquatic vertebrates (Ecotoxicology), have been recently performed by Yuan et al [6]. Which since the start of the industrial revolution remains a complex problem. Also the use of insecticides and its effect on behavior has been studied [7]. Small, but not overlooked This is not the first, and will not be the last, post on zebrafish as a model organism (Check out this page to find more blog posts on this topic). Here at Noldus, we find it important to keep emphasizing the scientific importance, and it’s relevance towards the scientific community and public health.  This is why we want to keep you up to date with the latest developments and insights in the zebrafish research field and how DanioVision can contribute to creating a better understanding of this not-to-be overlooked “small fry” and it’s ever-growing scientific reach. FREE DEMO: Request a free demo for your zebrafish research. Learn more References [1]         Banerji, R., Huynh, C., Figueroa, F., Dinday, M. T., Baraban, S. C., Patel, M. (2021). Enhancing glucose metabolism via gluconeogenesis is therapeutic in a zebrafish model of Dravet syndrome. Brain Commun., 3 (1) [2]         Griffin, A. et al. (2021). Phenotypic analysis of catastrophic childhood epilepsy genes. Commun. Biol. 2021 41, 4 (1), 1–13 [3]         Hsu, P.-J. et al. (2021). l-Carnitine ameliorates congenital myopathy in a tropomyosin 3 de novo mutation transgenic zebrafish. J. Biomed. Sci. 2021 281, 28 (1), 1–21 [4]         Liu, J. et al. (2021). Resveratrol Alleviates 27-Hydroxycholesterol-Induced Senescence in Nerve Cells and Affects Zebrafish Locomotor Behavior via Activation of SIRT1-Mediated STAT3 Signaling. Oxid. Med. Cell. Longev., 2021 [5]         Soll, M., Goldshtein, H., Rotkopf, R., Russek-Blum, N., Gross, Z. (2021). A Synthetic SOD/Catalase Mimic Compound for the Treatment of ALS. Antioxidants 2021, Vol. 10, Page 827, 10 (6), 827 [6]         Yuan, W. et al. (2021). Effects of sulfometuron-methyl on zebrafish at early developmental stages. Ecotoxicol. Environ. Saf., 220, 112385 [7]         Faria, M. et al. (2021). Androgenic activation, impairment of the monoaminergic system and altered behavior in zebrafish larvae exposed to environmental concentrations of fenitrothion. Sci. Total Environ., 775, 145671 --- ## Altruism in rats, suspiciously human URL: https://noldus.com/blog/altruism-in-rats Published: 2021-08-25 12:00:00 Description: A recent study by Bartal et al drove our curiousity to write this blog about altruistic behavior in rats. This study shows how this type of behavior is neurally linkend to the social functioning of humans. Do you sometimes feel like you have the social functioning of a rat? Probably not. But if you have, there is good explanation for that! We as humans share 99% of our genes with rats. It is indeed no secret that rats and humans share a large amount of anatomical, physiological and genetic properties, which (partly) explains the use of rats as a model organism in (bio)medical research. The latest in these shared properties was identified in a very recent publication by Bartal et al, explaining a shared neural mechanism in altruistic behavior [1]. Altruism in rats, suspiciously human Helping behavior Their publication focusses on prosocial behavior, particularly uncovering the neural mechanisms responsible for mammalian helping behavior. Their study starts with their uniquely designed ‘Helping behavior test’ (HBT). This test determines whether there is emphatic concern in rodents, more simply put: if they are capable of ‘helping behavior’. A trapped cagemate is used as the motivator, rescuing this cagemate from a restrainer is used to quantify this pro-social motivation. They found a general empathy towards all trapped rats. However rats only worked to free others from the restrainer when they were of their own strain (‘ingroup’), not rats of an unfamiliar strain (‘outgroup’). This suggests social selectivity and this distinction could be made by tracking the rats’ movement within the arena containing the restrainer, showing general interest in a trapped rat versus leaning or head butting the restrainer door to release the trapped rat. LABEL Title Learn more image from Bartal et al [1] Shared neural network They directly followed behavioral testing by the immediate sacrifice of the animals to determine peak expression of c-Fos through immunohistochemistry. With this method, determining brain-wide neural activity, a shared network was found. The frontal and insular cortices showed activity during the helping test which was irrespective of group membership, while the striatum showed specific activity for ingroup members. Additionally, rats were injected with a viral vector in the nucleus accumbens and implanted with a fiber patch cord. This allowed in vivo calcium imaging which showed activity in the brains’ reward circuitry when rats rescued a trapped ingroup member. The human comparison Humans share the same mechanisms and regions when it comes to empathy and reward as investigated in this study by Bartal et al. However this can never be brought back to a one-on-one comparison, as human prosocial behavior is uniquely complex. When brought back to basic emphatic responses this study shows that there is a highly conserved biological mechanism, which is also suggested to cross other social species. The authors of this paper conclude that this data provides evidence towards a step of better understanding the socially complex creatures that humans are. They state that the understanding of the empathy gap for outgroup members is a major goal for society: “Why do we help some, but remain impervious to the suffering of others?”   The impact of behavioral neuroscience This study is a great example of the importance of using rodent models in behavioral neuroscience, since the interpretation of behavioral responses often isn’t distinct or intuitive. Advancements in behavioral tracking has improved resolution in this context. Noldus’ Ethovision XT is a fully automated behavioral tracking software which can be implemented in a wide array of behavioral experiments. This can also be paired with Noldus’ PhenoTyper box, which has additional options such as optogenetics and in vivo calcium imaging as used in the current study by Bartal et al. RESOURCES: Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! Learn more Using tech as a behavioral tool By using these powerful technological advancements to our advantage, investigating shared neurobiological mechanisms in rodents can greatly increase our understanding of social behavior, and place it in a societal context. This bridges an extremely important gap between rodents as a scientific (social) model, and social studies in humans with the role that they play in nowadays’ complex society.  After all, it was Aristotle that stated “Man is by nature a social animal” and “Society is something that precedes the individual”. References [1]         I. Ben-Ami Bartal et al., “Neural correlates of ingroup bias for prosociality in rats,” Elife, vol. 10, Jul. 2021, doi: 10.7554/ELIFE.65582. --- ## Do your emotions and moods change as you get older? URL: https://noldus.com/blog/what-induces-emotions-moods Published: 2021-08-19 12:00:00 Description: Are emotions affected differently for younger than for older people? Researchers used FaceReader to complement self-assessments and objectify mood changes to answer this question. All kinds of things affect in what kind of mood we are. For example, the situation of having diner and discovering new dishes that surprise you. Or, when you’re asked to give a presentation to many important people for the first time - which scares you - makes you nervous. Our mood can also be influenced by certain circumstances, such as a bad night’s sleep, being in a new and unfamiliar place, or facing a lockdown due to the COVID-19 pandemic. Our mood is what one feels inside, whether pleasant or unpleasant. The factors that influence our mood are personal. Everyone is sensitive to certain factors in their own way. The same circumstances can affect other people differently. What is great for one person can be terrible for another.  Are emotions affected differently for younger than for older people? Listening to music or watching a movie induces or intensifies mood states as well. Researchers wondered what the difference would be between young and old persons. Would the mood induction be more intense in older than in younger persons? Or are older persons perhaps better able to regulate their emotions?  The research group of Zempelin and Sejunaite of the Ulm University in Germany exposed 29 young participants (age 24.4 ± 2.3) and 28 old participants (age 69.2 ± 7.4) to film segments to induce four basic emotions: anger, disgust, happiness, and sadness. A second goal of the experimental study was to find out how the information of subjective mood corresponds to analysis of mood using automated analysis of facial expressions. FREE WHITE PAPER: FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download arrow_forward Objectifying mood induction Four movie sequences were selected to present to the participants in a randomized order. Each to elicit another basic emotion: - When Harry met Sally to target the emotion happiness - Dangerous Minds to target the emotion sadness - Schindler’s List to target the emotion anger - Trainspotting to target the emotion disgust During the session, the participant watched the movies on a screen while a camera recorded their faces to enable analysis of facial expressions using FaceReader™. Using this automated software tool ensured that the success of mood induction could be objectified. To assess the subjective mood on the other hand, participants were asked to complete three questionnaires: - Actual Mood State (AMS): to evaluate their current emotional state for each of the four emotions as well as for arousal, before and after each video. - Berkeley Expressivity Questionnaire (BEQ): to assess negative expressivity, positive expressivity, and impulse strength. Rating statements such as ‘I sometimes cry during sad movies’ and ‘I've learned it is better to suppress my anger than to show it’. - Short Suggestibility Scale (SSS): to assess one’s susceptibility to accept and internalize external influences uncritically. Rating statements such as ‘I am easily influenced by other people’s opinions’ and ‘I question what I see on the news’. What brings emotion into being? Stimulus Presentation tool E-prime was used to present the scripts and videos to the participants. FaceReader was used to analyse the captured videos of the participants’ faces. The collected data from the experimental script and the camera was synchronized using The Observer XT. FREE TRIAL: Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial arrow_forward Analysis showed no effect of age on induction of any of the target emotions. Only for the target emotion sad the research team observed a difference between young and old faces, which might have been the result of ‘smile wrinkles’ that prevented the classification sad. Furthermore, the researchers found that pre-exposure mood was to be associated with post-induction success for disgust and sadness. The association between pre-exposure facial expression of mood state and post-exposure intensity of facial expression was much more clear-cut for all emotions. This confirms the hypothesis that the emotional facial action modulates the subjective experience of emotion.  Download here the FREE white paper 'Facial Action Coding System (FACS)' FaceReader supports objective perception of emotions The researchers concluded that regardless of age, mood induction is successful using film clips targeting these emotions. Analysis of facial expression complements self-assessment of mood and may serve as a means of objectification of mood change in both young and old persons.  Reference Zempelin, S.; Sejunaite, K.; Lanza, C. & Riepe, M.W. (2021). Emotion induction in young and old persons on watching movie segments: Facial expressions reflect subjective ratings. PLoS ONE, 16(6): e0253378. https://doi.org/10.1371/journal.pone.0253378 --- ## Furthering behavioral studies for understanding microbiota-brain insights URL: https://noldus.com/blog/microbiome-brain-research Published: 2021-08-19 10:31:00 Description: How and to what extend do microbes in the gut affect the brain and behavior? Discover how they do this kind of research at UCLA. Today we are pleased to share with you a guest blog post by Dr. Christine Ann Olson from University of California, Los Angeles (UCLA). Enjoy reading! LABEL Title Learn more RESOURCES: Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more --- ## EthoVision XT and the Morris Water Maze: expert tips and tricks URL: https://noldus.com/blog/ethovision-morriswatermaze-tipsandtricks Published: 2021-08-11 15:30:00 Description: Neuroscientist Colleen McSweeney, Ph.D. shares her expert knowledge on using EthoVision XT and the Morris Water Maze. From a brief history to valuable tips and tricks, here is all you need to know on automated tracking. The Morris Water Maze, developed in 1981 by Richard Morris [1], is a tried and true method for assessing spatial learning and memory in rodents. What is the Morris Water Maze? The task involves a large circular pool filled with opaque water (typically colored with milk or nontoxic paint). A platform is than placed somewhere in the maze, below the level of the water so the rodent cannot see it. There are a variety of protocols for how to run this test, but typically the protocol involves placing the rodent in the water from varying entry points, then measuring the amount of time it takes to reach the platform. If the animals do not reach the platform in 60 seconds, they are guided towards the platform and removed. After a certain number of these training trials, a probe trial is completed. In the probe trial, the platform is removed, and the amount of time the rodent spends swimming near the platform is quantified.  Tracking and visualization: from 1981 to 2021 When Richard Morris first started tracking the rodents in the maze, it required a complex system of an image-analyzer and a microcomputer to monitor degrees of contrast - the black head of a hooded rat against the white milk colored water. LABEL Title Learn more Once your data profile is complete, go to Heatmap Visualization and click Group Mean on the right. This will merge your group data to create a Heatmap for your two distinct groups. You can then overlap important maze features by going to Show/Hide in the top right, and selecting Arena Features. The resulting image is a great way to emphasize group changes for your papers, presentations and posters. LABEL Title Learn more To get started using EthoVision XT, or for more tips and tricks, contact your regional account manager! FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more References [1]     Morris, R.G.M. (1981). Spatial localization does not depend on the presence of local cues. Learning and Motivation. 12, 239-260. [2]     Morris, R. (1984). Developments of a water-maze procedure for studying spatial learning in the rat. Journal of Neuroscience Methods, 11, 47-60 --- ## 5 proven ways to measure spatial learning in rodents URL: https://noldus.com/blog/5-ways-to-measure-spatial-learning-rodents Published: 2021-07-29 12:00:00 Description: What is spatial learning, why is it important and how do we measure it? Here we dive into 5 different behavioral tests that specifically measure spatial learning and memory in rodents. Imagine your local supermarket having a complete renovation. Coming into the new and improved store, you suddenly have to deal with finding your favorite coffee or cereal again. A task that used to be easy, even mostly on auto-pilot, needs to be completely re-learned. This is where spatial learning comes in. What is spatial learning? Spatial learning basically refers to the association or representation of an organism (you) in a three-dimensional environment (the supermarket). If we translate this to basic animal research terms: An animal learning its position in a given space. This task highly relies on visual cues and/or landmarks, whether in humans or animals.   Why is spatial learning relevant in neurosciences? Apart from being very practical to be able to find your favorite coffee, spatial learning is vital for humans and animals alike. In humans, spatial learning is an important form of declarative memory, which refers to remembering names, places, events etc. (also called working memory). This is accompanied by fast processing in the brain: new information can be encoded after a single event, however also forgotten within minutes, hours or days. The weakening of this working memory, executive function and processing speed in humans can also be classified as cognitive decline. This can be age-related, linked to dementia such as Alzheimer’s disease or even due to traumatic brain injury. Impaired memory (formation) is usually associated with a decline in hippocampal functioning. The role of the Hippocampus Spatial learning is primarily processed in the hippocampus, which is very dependent on neural plasticity: the capacity of a network to modify its existing connections. This plasticity generally decreases with age and underlying to this are changes in synaptic strength: weaker connections (less repeated input) are retained for a shorter amount of time than stronger connections (more/longer repeated input). Measuring of spatial memory, essentially ‘probing’ the functioning of the hippocampus, can thus serve as a very important diagnostic parameter of cognitive decline. In rodents, this form of cognitive assessment is brought back to very basic reactions of the animal, such as identifying a novel or familiar object, or finding a specific location in a walled-off area. Morris water maze The latter is exactly what Richard Morris intended to measure in the Morris water maze in 1981: a tool to assess spatial learning and memory in rodents. Although it is not shaped as a maze, but rather a round arena filled with water (much like a swimming pool for rodents), the learning and retrieval process does resemble the workings of a maze. Completing the “tasks” in a Morris water maze is highly incentivized by the need to escape cold water. This  requires complex navigation skills, which is exactly what researchers are looking for when measuring spatial learning in rodents. A variation of the Morris water maze task is the Cincinnati Water maze, which has a much more complex pathway to the escape platform. It also relies more on internal cues, as opposed to external cues in the Morris water maze (check out this blog on this topic!). Barnes maze Developed by Dr. Carol Barnes in 1979, the Barnes maze makes use of the same navigational paradigm as the Morris water maze. This maze however consists of a brightly lit circular surface with up to 20 circular holes around its circumference. The animal must learn over a number of sessions that there is an ‘escape box’ present under one of the 20 holes. Though similar to the navigation and escape task in the Morris water maze, this task is incentivized by the rodents’ aversion of open spaces compared to the need to escape cold water, which is a crucial difference between these two mazes. Y-maze A Y-maze (like a T-maze) is also often used to investigate spatial learning in rodents. The benefit of this maze is that the test is generally easy to learn, thus making it very time efficient. Also, its small size makes it very easy and fast to set up in virtually any testing chamber. Decision making, and consequently learning, in the Y-maze is incentivized by placing a reward at one of the ends of the maze. The animal then learns this position of the reward. After this training this results in an output based on the amount of time it took for the animal to find the correct arm, or the number of mistakes it made. Check out this blog post on the Y-maze!  Radial arm maze First designed by Drs. David Olton and Robert Samuelson in 1976, you can’t help but notice the similarities between this test and the Y-maze. In the radial arm maze animals are, like the Y-maze, incentivized by the presence of a reward in an arm of the maze. The animal however has 8 arm choices in the radial arm maze as opposed to 3 in the Y-maze. This serves as a great tool for testing “serial learning”, which is a term to describe how we learn and recall lists or other sequential information. Spatial object recognition (SOR) test This final test we describe is different from other spatial learning tasks because it does not rely on motivational cues like ‘escape’ or ‘reward’, but rather the innate curiosity of rodents to explore novel objects in their environment. In the spatial object recognition task the animals are trained, usually in an open field or PhenoTyper box, to a specific set of objects that are placed in specific areas of the arena. 24 hours after this training one of these objects is moved to a different location in the arena. The difference in the time spent exploring the moved versus unmoved objects can then be used to assess the mouse’s spatial memory. FREE TRIAL: Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system  Free Trial --- ## Diver behavior captured with wearable cameras URL: https://noldus.com/blog/observing-diver-behavior Published: 2021-07-19 10:02:00 Description: Observing the actual wreck diver behavior using video recordings made with wearables cameras, researchers aimed to enhance effective management strategies for underwater cultural heritages. When you descend below the surface of the water, you are welcomed into a world that is full of color, life, and beauty. There is a lot to discover in the underwater world, for example turtles, coral and reefs, old shipwrecks, and many fish. Diving is adventurous, makes you feel like you are flying without the danger of falling, and you will experience an ultimate peace and quiet, which enables you to unwind and relax.  Wreck diving is, just like ice and cave diving, one of the specialties in diving. It is exciting to dive into a historic site, and view something that once floated on the surface, now shelters marine life. Each wreck dive offers a chance for a new discovery. Wrecks are fascinating windows to the past.  It is beyond dispute that the underwater world must remain as well protected as possible. However, the divers' behaviors can unintendedly pose risks to the integrity of site cultural heritage.  Understanding actual diver behavior Cultural heritage sites are often fragile and cannot regenerate once disturbed or damaged. Most likely behaviors involving physical contact by the diver or their equipment with underwater cultural heritage can have undesirable affects. The research team of Joanne Edney of the Southern Cross University in East Lismore, Australia, conducted a study to understand the actual wreck diver behavior to enhance effective management strategies for underwater cultural heritages and dive tourism.   Using wearable cameras to understand in-water behavior, their study aimed to: - identify diver contact and non‐contact behaviors at shipwrecks - clarify the frequency of diver contact behaviors and durations of non‐contact behaviors on shipwrecks How to make accurate and reliable observations How can you make a detailed and reliable observation underwater? Self-reporting is not really an option, as it can be inaccurate and social desirability may play a role. Studying actual behavior entails participant observation, but having an observer present at the site isn’t an option either, as this can influence someone’s behavior (Hawthorne effect).  Video observation, on the other hand, improves reliability, accuracy, trustworthiness, and quality of data and data analysis. The method is discrete, less distracting, and moreover, the data can be viewed, coded, and analyzed repeatedly. Applying wearable cameras as a research tool Wearable action cameras have become commonplace amongst recreational scuba divers due to their small size, ability to be taken to 60 m depth, high video quality, and ease of use. Therefore, the researchers used head-mounted cameras in the present study. The wearables provided a dynamic view of the diver’s visual environment, were unobtrusive, and were able to capture data over a period of time. Coding diver behavior to enable analysis The study was conducted at Chuuk Lagoon, a world‐renowned wreck diving destination. Chuuk was a key strategic advance military base during World War II for Japanese navy vessels, merchant vessels and aircraft, pivotal to Japan’s push into the Pacific. Today, sustainable diving practices are important for the longevity of this tourism resource and protection of the important cultural heritage values. On 23 dives by 20 divers on 12 shipwrecks located, data was collected. The behaviors recorded reflected diver impacts on underwater cultural heritage, such as touching artifacts, activities divers engaged in and what divers spent time looking at.  All data was exported to The Observer XT for coding and analysis. Each behavior was coded and noted in real‐time for the duration of time they occurred, with the exception of ‘hand pulling’ behavior, which was coded as ‘point’ type. Examples of coded diver behaviors were: - diver entered an overhead environment - diver was actively engaged in looking at feature of a wreck - diver deliberately touched an artefact - diver sits on wreck or artefact Download here the FREE white paper 'How to set up behavioral coding - 7 tips' Behaviors recorded around or inside the wrecks The research team analyzed 14 hours of participant-generated data. It appeared that contact behaviors accounted for almost 15% of behavior frequencies, of which hand pulling on wrecks was the most frequent. This is a wreck diving technique used to minimize silting (swirling sand or fine particles from the ground) and move more efficiently against currents. Other frequent contacts were touching artifacts and holding onto wrecks.  The behavior ‘touching artifacts’ was examined in more detail because it can have consequential impacts on underwater cultural heritage. Modifiers were added to this analysis to enable more detailed descriptions of this behavior. For example, modifiers were cleaning, picking up and holding, or picking up and moving the artefact. Picking up and inspecting artifacts was the most frequent behavior. Non‐contact behaviors represented the majority (>98%) of behavior durations, such as looking at features of wrecks (e.g. machinery), viewing marine life, and being inside wrecks (e.g. cargo holds) to see features such as munitions, vehicles, glassware, shoes, and clothing.  FREE TRIAL: Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial arrow_forward Insight into diver behavior The first‐person perspective of the data collected in this study offers unique insight into diver behavior, capturing the participant’s environment as they saw it. The contact and non-contact behaviors have been mapped which provides extensive knowledge of diver in‐water behaviors. It is encouraging to notice that the ‘touching artifacts’ behavior accounted for a small proportion of contact behaviors. Any contact with a wreck’s fabric or artifacts can accelerate decay, and cleaning removes protective coatings, further accelerating their decay. This should be avoided as much as possible. Therefore, education of divers about the causes and consequences of diver contacts with wrecks and their contents as well as encouraging more sustainable use of the sites, remains important. References Edney, J.; Dimmock, K. & Boyd, W.E. (2021). Understanding Diver Behavior on Underwater Cultural Heritage: Enriching the Observation Record Using Video Methods. Sustainability, 13, 5601. https://doi.org/10.3390/su13105601 https://onderwatersport.org/ https://www.bunchofbackpackers.com/why-scuba-diving-travel-backpacking/ --- ## Mimicking human decision-making in a mouse model URL: https://noldus.com/blog/decision-making-mouse-model Published: 2021-07-13 09:22:00 Description: Choosing the appropriate behavioral test can be a challenge, but is very important. And sometimes, researchers will have to develop their own. Assays to test the cognitive behaviors in animals have been widely used for decades. The choice of the appropriate behavioral test is arguably one of the most important factors for measuring the desired behaviors and parameters. Testing cognitive behavior in animals There are many different paradigms, including mazes and operant chambers, to test an animal’s cognitive function, learning and memory, as well as anxiety and other disorders. On rare occasions though, researchers have to develop a new paradigm to test questions that have not been explored in experimental animal laboratories yet. Decisions to eat or drink One of those questions, that is especially relevant in our society with ever growing obesity rates, is how humans make decisions to either eat or drink. This is a complex question that involves many different variables, including the time and size of the last meal, internal hormones, daily routines, and the external environment (e.g. being at a social dinner with friends). Interestingly, clinical research suggests that we humans are not particularly good at evaluating whether we are truly hungry or thirsty. A lot of our daily decisions to eat or drink might be driven by habits and cues in our environment, rather than an actual need. This led healthcare professionals to advice drinking a glass of water before eating as an appetite-reduction approach. However, the mechanisms for why we would confuse hunger and thirst are unclear and could give important clues for developing preventative behavior recommendations. LABEL Title Learn more Novel paradigm that mimics key elements of human decision-making Researchers from the Howard Hughes Medical Institute recently discovered the neural mechanisms underlying the decisions to eat or drink by developing a novel paradigm that mimics key elements of human decision-making in mice. These key elements include: a similar behavior to obtain food and water, hydrated food, and alternating between states of thirst and hunger. Ethologically relevant food source To mimic a similar behavior to obtain water and food that compares to humans going to the fridge or faucet, mice had to press a lever in a two-alternative forced choice task. But unlike a standard dry food pellet, the food option was a hydrated gel to mimic a similar water content that resembles natural food sources like vegetables and meat. Hydrated food is ethologically more relevant than dehydrated food, as dry pellets become aversive in thirst and, thus, simplify the decision-making process. Custom behavioral apparatus To accurately deliver compressible, gelled food and test a variety of behavioral parameters simultaneously, the scientists built a custom behavioral apparatus (see Figure for more details). LABEL Title Learn more Custom designed behavioral apparatus with pneumatic actuator for reward delivery, capacitive lick detection, and field programmable gate array (FPGA) circuits for controlling and monitoring stimuli, and motorized levers and spouts, with behavioral video images from two separate cameras. Need-state switching Lastly, humans switch between being hungry and thirsty within a couple of hours (sometimes minutes), whereas in most rodent studies, animals are held constant in either thirst or hunger for many days or weeks. To assess realistic decision-making, the scientists frequently alternated mice between being hungry and thirsty. Food Bias The group found that when those key elements were combined in this novel approach, mice developed a food bias: Regardless whether the animal was hungry or thirsty, it would first consume food before eventually switching to water when thirsty. In fact, when the research team inactivated the part of the brain that is responsible for decision-making and outcome evaluation (the medial Prefrontal Cortex, mPFC), thirsty mice “got stuck” eating food instead of drinking water. Drinking water as a habit The authors of this recent publication in Nature Neuroscience showed that this food bias could be reversed by developing a habit to drink water, similar to what health professionals recommend to overweight patients. Reaching for food is a behavior that is easily formed into a habit that does not depend on the resource-intense mPFC. However, building a water-seeking habit (i.e. when in doubt, reach for a glass of water) can overwrite the urge to mindlessly reach for food even in the absence of hunger.    Important insights for new strategies and treatments for obesity These findings are a fundamental step towards understanding how the brain guides ingestive choices and provide a causal link for the involvement of the mPFC in evaluating physiological states like hunger and thirst, which was previously only observed in humans. These insights will aid in the development of new behavioral strategies and treatments addressing obesity and other eating disorders. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more Measuring cognitive functions in animal models does not always require investing the time and energy to develop and validate a new paradigm or custom-built behavioral chamber. There are many turn-key solutions available for studying decision-making, memory, or motor learning, that are well-established and reliable. Contact us to learn more. References Eiselt AK, Chen S, Chen J, Arnold J, Kim T, Pachitariu M & Sternson SM (2021) Hunger or thirst state uncertainty is resolved by outcome evaluation in medial prefrontal cortex to guide decision-making. Nature Neuroscience 24, 907-912. --- ## Robust and reliable: Measuring anxiety in the Elevated plus maze URL: https://noldus.com/blog/robust-reliable-measuring-anxiety-elevated-plus-maze Published: 2021-07-08 12:00:00 Description: Screening of anxiety-like behavior in the elevated plus maze becomes more reliable with Ethovision XT combined with the standardization of testing parameters and common practices. Animals models of anxiety often rely on the simply designed ‘elevated plus maze’. Two open and two closed arms allow researchers to look into a number of anxiety related behaviors with great speed, efficiency and reproducibility, which further standardization can improve. Lighting conditions, circadian rhythmicity, housing conditions, habituation methods, scoring methods and observer bias are all topics of debate among the scientific community. EthoVision XT Automated tracking software, such as Noldus’ EthoVision XT, has already provided a great step in removing observer-bias and standardizing scoring methods in order to increase reliability and reproducibility of this test. Researchers in various locations can use shared setups and software settings to accurately compare the outcomes and reduce inter-laboratory variation of this test. In order to achieve this ‘universal template’ however, a few considerations have to be made. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more The importance of diffuse lighting In order to standardize tracking settings, lighting should be as equal as possible across labs, preferably as diffuse as possible. Rodents however show a specific anxiety-like phenotype according to light intensity (measured in lux). In very slight to no lighting at all (0 – 1 lux) time spent in the open arms is significantly higher compared to the all-or-none threshold starting from around 2 lux [1]. The elevated plus maze is highly motivated by thigmotaxis; the tendency to be close to vertical surfaces, which in turn is far more reliant on tactile inputs compared to vision [2]. Video capturing also benefits from dim lighting or complete darkness, since IR-backlighting provides great visibility and mouse-to-arena contrast in these low lighting conditions. Lighting can thus be considered a tool in the elevated plus maze, as it can be tweaked based on the sensitivity to light-induced anxiety of different strains and species.  LABEL Title Learn more To test in complete darkness or not? Active- or rest-phase testing has always been a great debate among researchers. Rats and mice are nocturnal animals, meaning they are most active in the dark phase and rest during the light phase. With a regular day/night cycle, animals tested will be most active in the evening, followed by the afternoon, followed by the morning. Using a reversed day/night cycle, animals will show higher activity in the morning. A reversed cycle however requires working under red-light conditions, which is considered to be bothering to some researchers. In many cases it is thus a matter of within-laboratory logistics and/or planning of the experiment. A pragmatic approach seems most adequate; counterbalancing the testing order during the day, but avoiding the beginning of the rest phase, which causes animals to appear groggy, showing little activity.   LABEL Title Learn more LABEL Title Learn more Common practices to consider - Habituation to a testing room (if separate from housing room) is a common practice before most behavioral tests, usually for a duration between 30 minutes to 1 hour. The elevated plus maze is no exception to this general rule-of-thumb, moreover because the main outcome parameter being anxiety-like behavior, it should receive extra attention. - Group housing is commonly implemented in rodents since rats and mice are social animals. Animals are however individually placed into the testing apparatus which can create a testing-order effect, as a stressful reaction to the sudden exclusion of a cage mate can greatly impact anxiety-like behavior. This can be circumvented by true randomization of this testing order, or also perform habituation to a brief period of social isolation (± 10 minutes) prior to the test. Furthermore, group housed rats and mice establish social hierarchies, which in turn also affects anxiety-like behavior. It is thus important to quantify these hierarchies, preferably after the completion of other behavioral tests. Most importantly is that it should be clear to not directly compare data from individually versus group housed animals. - Cleaning the testing arena after each test is usually done with a 30-70% solution of ethanol. This can also be done, fully drying afterwards, with water or an acetic acid solution. The key with cleaning the arena is to make sure the starting situation is the same for all animals, as it homogenizes the scent of previous animals across the arena. - Avoid behavioral testing on days when home cages are cleaned, animals are weighed and/or food is changed as this can typically increase stress and activity, affecting the outcomes of the elevated plus maze. When intervention and/or handling on day of testing is unavoidable, it is also possible to expose every group/animal to the same situation, which can standardize the outcome. The elevated plus maze is seen as a simple anxiety screening test. Researchers should however pay great attention to fully describe the circumstances, whether they are standard or special, in their experimental methods, since the perceived simplicity of this test does have some pitfalls. Detailed reporting can ensure consistency, but also serve as a great way for other researchers to discover the cause of certain variations in the elevated plus maze and learn from them for further experiments. References [1]       A. M. B. Garcia, F. P. Cardenas, and S. Morato, “Effect of different illumination levels on rat behavior in the elevated plus-maze.,” Physiol. Behav., vol. 85, no. 3, pp. 265–270, Jun. 2005, doi: 10.1016/j.physbeh.2005.04.007. [2]       G. B. Filgueiras, E. F. Carvalho-Netto, and C. Estanislau, “Aversion in the elevated plus-maze: role of visual and tactile cues.,” Behav. Processes, vol. 107, pp. 106–111, Sep. 2014, doi: 10.1016/j.beproc.2014.08.005. --- ## How to measure consumer behavior URL: https://noldus.com/blog/how-to-measure-consumer-behavior Published: 2021-07-05 09:55:00 Description: Measuring consumer behavior enables you to really know your customers and get key insights into consumer preferences and buying behavior. We highlight four of these ways for you in this blog post. Measuring consumer behavior enables you to really know your customers and get key insights into consumer preferences and buying behavior. There are several ways how consumer behavior can be measured. We highlight four of these ways for you in this blog post. How to measure consumer behavior - 1.Measure eating behaviors and consumers liked and dislikes with facial expressions - 2.Measuring shopping behavior - 3.Testing consumer behavior in a natural environment - 4.Neuromarketing research Measure eating behaviors and consumers likes and dislikes with facial expressions One way to measure consumer behavior is to record facial expressions of participants, and examine their food preferences. Food scientist Prof. Susan Duncan from Virginia Tech focuses on sensory evaluation, the way people interact with food and the way their senses capture this reaction. She uses FaceReader to record facial expressions, as they demonstrate how we react to a particular food. If something smells disgusting, if a weird color makes us feel anxious, or if we like the taste of something: our face can tell, without us being aware of it. This type of research provides insights in the relationship between emotions, consumer acceptability, and purchase intent, and gives guidance towards food and packaging innovation. FREE WHITE PAPER Eye Tracking & FaceReader Download this white paper to learn about: - Subconscious processes and emotion recognition - Combining FaceReader™ and eye tracking - Visualizing and analyzing your data Download Measuring shopping behavior A spectacles camera, head mounted eye tracker or eye tracking glasses can be used as exploration instruments in a shopping mall. Researchers, and marketers, want to observe how shoppers move through malls and the displays they look at in retail stores. An eye tracker allows your test participant to move and look around freely, while the researcher gets to see where the test participant is looking at, or is not looking at. This allows you to better understand consumer buying behavior. Another way to measure consumer behavior is by studying the route customers are taking when visiting a store or a supermarket. A specific question supermarket Jan Linders had: 'Do customers predominantly walk the same (common) route and is it possible to change this most commonly followed route by changing the layout of the supermarket and/or the placement of certain products?' By using TrackLab, our consultants tracked the movements of customers while they were wearing an ultra-wideband tag on their coat. Based on the outcomes of this research, the supermarket implemented some changes and influenced the products their consumers buy. Testing consumer behavior in a natural environment The environment of your test participant has a great influence on the results of experiments. As the traditional example goes: the wine you drink at the French vineyard tastes better than the same wine you drink when you're back home. So how can you manipulate the influence of the environment in a sterile laboratory, and simulate a home or restaurant environment? By creating a dedicated experience room! A simulated environment, with video projected on the walls and background sounds, can change the context of how much we enjoy food. You can even create a complete test kitchen, as researchers from Université Paris-Saclay in France did. They concluded that participants behaved quite spontaneously, although they were aware of cameras in the lab. Their paper describes the approach of filming consumers in a controlled yet naturalistic environment. Read more: How to build a consumer behavior research lab? Neuromarketing research Get your face read, your brain measured, and your heart rate checked: Neuromarketing lets you dive deeper into the unconscious preferences of consumers and their decision-making processes. In the field of neuromarketing several different technologies are used to measure changes in activity in parts of the brain, outward expressions such as facial expressions, and changes in one's physiological state. All techniques are aimed at learning more about why consumers make the decisions the way they do, and if a part of the brain is telling them to make these decisions. The better we know how the brain functions, the better we know how to influence decision making processes. FREE WHITE PAPER How to build an AV lab Do you want to learn more how to set up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download Would you like to learn more about measuring consumer behavior? Find more information about tools for research on consumer behavior research or download the free paper 'How to build a consumer lab' which contains practical tips, equipments lists, and much more. --- ## Challenging play behavior: does it still exist? URL: https://noldus.com/blog/analyzing-challenging-play-behavior Published: 2021-07-01 10:09:00 Description: Although children tend to spend more time indoor in sitting activities, they need feelings of exhilaration for behavioral development. Researchers investigated how risky play behavior can be encouraged. When I was little it was common to play outside, build a hut out of branches and leaves, find frogs in a ditch, climb walls that were just a little too high, and play a ball game with the neighbor children on the street in front of our houses. From time to time, we pushed the limits and looked for thrilling situations, which created healthy tension. We engaged in risky play. Nowadays, my teenage children mostly watch YouTube, TikTok, or Netflix, and play on the PlayStation. Admittedly, this may say something about my parenting skills. However, it is also a trend of the present time. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Risky play beneficial for children’s development Over recent decades, children are left with fewer opportunities for free play, especially outdoors. Children spend more time indoor in sitting activities, and less time in outdoor play and vigorous physical activity. However, children need feelings of exhilaration now and then. Research indicates that risky play and risk-taking activities may increase children’s physical activity, improve motor/physical competence, increase spatial and perceptual skills, and enhance their ability to assess and manage risk appropriately. Engaging in risky play will be rewarded by experiencing feelings such as enjoyment, pride, achievement, and good self-esteem when children master new challenges. What exactly does risky play mean? The connection of risky play to spaces and materials Based on observations and interviews in Early Childhood Education and Care (ECEC) institutions and facilities such as daycare centers, kindergartens, and preschools, eight categories of risky play can be determined: - play with great heights (e.g. climb trees or jump from high places) - play with high speed (e.g. swing at high speed or roll down steep hills) - play with dangerous tools (e.g. ropes, hammers or knives) - play near dangerous elements (e.g. steep cliffs or deep water) - rough-and-tumble play (e.g. play fighting or chase-and-catch play) - play where children go exploring alone (e.g. no constant supervision) - play with impact (e.g. crash their wheeled toys into the fence) - vicarious play (e.g. observe other children taking risks) For children that spend a large amount of time in ECEC institutions, the play environment is of great importance. Researchers have conducted several studies to discover, for example, the relationship between children’s play preferences and the physical environment (play environment) available. The research team of Ellen Sandseter, of the Queen Maud University College of Early Childhood Education in Norway, addressed the question how risky play is connected to spaces and materials in the physical play environment. Coding risky play behavior Eighty children from ages of 3 to 5 years participated in the study. Following a strict protocol, each child’s free outdoor play was recorded in two-minute sequences, with a total of six sequences. The recordings at two data points (T1 in 2017 and T2 in 2018) eventually resulted in 935 video observations. The researchers coded risky play behavior using The Observer XT, following to a coding scheme with the eight types of risk. In the further analysis, play with great heights, play with high speed, and rough-and-tumble play were analyzed in detail, in addition to the category of total risky play, which included all risky play categories. The appearance of the other categories were too low. Play spaces (e.g. sandbox, open area, fixed play equipment such as swings) and play materials (e.g. sand, water, toys) were coded as a percentage of time for each observation. Download here the FREE white paper 'How to set up a coding scheme - 7 tips' Analyzing the video observations After analyzing the data in The Observer XT, the researchers found that almost all children seemed to engage in risky play to some level. They showed this behavior on average 13% of the outdoor free playtime. Risky play mostly consisted of play with high speed and play in great heights, and some rough-and-tumble play, which all include movement and physical activity. Natural environments, such as areas with trees, bushes, grassy hills, and uneven surfaces, facilitated risky play. It also became evident that children predictively engaged in risky play on play equipment designed for physical activity such as climbing, sliding, and balancing (e.g., climbing towers and slides) as well as wheeled toys that guaranteed high speed. Additionally, they created risky play themselves with tables and chairs, sheds, and toy storage buildings, which were not intended for play. Children seemed to climb anything that can be climbed. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Encouraging challenging play behavior This extensive dataset of observations allowed the researchers to quantify the various behaviors and conclude which risky behaviors occurred, with which toys or tools, in what spaces, and how often. These insights will help developmental psychologists, practitioners, and other stakeholders in balancing safety and healthy stimulation with challenges for behavioral development. And to design and equip children’s play environments in ways that give access to various spaces and materials that encourage challenging play. Reference Sandseter, E.B.H.; Sando, O.J.; Kleppe, R. (2021). Associations between Children’s Risky Play and ECEC Outdoor Play Spaces and Materials. International Journal of Environmental Research and Public Health, 18, 3354. https://doi.org/10.3390/ijerph18073354 --- ## How we turned our office into a living lab with a green roof URL: https://noldus.com/blog/green-roofs-research-biodiversity Published: 2021-06-29 12:00:00 Description: Green roofs are becoming more and more popular around the world. These living roofs transform buildings into ecological systems that benefits its surrounding environment. Green roofs are becoming more and more popular around the world. These living roofs transform buildings into ecological systems that benefits its surrounding environment. A green roof, or living roof as it’s also called, is a roof of a building that is (partially) covered with vegetation that is planted over a waterproofing membrane¹. It goes beyond the average container gardens where plants are usually maintained in pots. While the installation of a green roof initially takes investing time and money, there are plenty of advantages. The advantages of a green roof - A green roof provides extra insulation, so cooling in the summer, heating in the winter, and saving on energy costs at the same time. - A green roof contributes to the retention of rainwater, thus reducing the burden on the sewer system, which is an important theme in urban environments these days. - A green roof extends the life of the bitumen roofing. - And last but not least: a green ‘living’ roof provides for a beautiful natural view when looking outside. LABEL Title Learn more Figure 1 Cross section of possible green roofs (by Eva Drukker) Figure 1 shows a cross section of three possible green roofs. Depending on how much the roof can carry, the substrate (soil) depth can vary. On the Noldus building the roof load was calculated to be able to carry the Herbaceous roof type represented in the middle. Noldus and sustainability We believe that companies of any size can make a difference in sustainability. That is why we organize our business processes in an ecologically sustainable manner. We minimize waste, choose our materials responsibly, and are mindful about travelling. Our office buildings are also included in our efforts for sustainable business. Our building in Wageningen is partially equipped with a sedum roof (figure 1a). It covers the building’s social area and canteen. On the top roof, solar panels and heat pumps are installed to regulate the temperature inside the building. Also, the surrounding grounds are planted with native trees and shrubs, and managed without use of chemicals. LABEL Title Learn more The sedum roof that covers our building's canteen How we turned our office into a living lab with a green roof Recently we decided to take it a step further and convert two pebble-covered roofs of our Wageningen office into ‘green roofs’, with a biodiverse vegetation cover (figure 1b). The bearing capacity of these concrete roofs is high, making a thicker substrate possible, which offers many more options for vegetation, and subsequently research. A living lab The design of the vegetation layer is a co-production of Koninklijke Ginkel Groep (a Dutch company specialized in sustainable landscaping and roof gardens) and Eva Drukker, researcher at Wageningen University and Research (WUR), the Netherlands. Eva will use the roofs for her PhD research to look into the effect of green roofs on biodiversity, in particular the diversity of insects. She will study the effect of two variables on vegetation development and colonization by insects. The design has divided the two roofs into four different zones, based on orientation towards the sun (north, south) and mineral content of the substrate (low or high in calcium). A seed mixture of locally and regionally occurring grasses and herbs are sown. By sowing seeds, we are also giving nature a chance to colonize the green roof by itself and make this roof more natural. Usually “sedum mats” are rolled out over the roof, so that it will immediately look “nice and pretty”. However these mats do not contribute much to biodiversity as many bees and butterflies do not use these sedum plants for their life cycle events and pollination. LABEL Title Learn more LABEL Title Learn more Research the effect of green roofs on biodiversity In the research, Eva is investigating how the surrounding landscape influences the colonization of plants and insects on green roofs. Several questions are adressed regarding the Noldus roof: - How does the initial vegetation and soil composition affect the colonization of spontaneous plants species, soil communities and larger insects? - Which species are able to survive on these green roofs over time? The research conducted here is quite unique, as we will be able to perform t0 measurements (starting right after construction of the roof) and measuring everything from the roof; soil quality, vegetation structure, as well as micro-, macro- and megafauna. We will do moth catching, bat and bird monitoring and assess how a green roof might enhance their populations. Urban Green Infrastructure With the information gathered over the years we will have a better understanding of these small ecosystems and how to effectively integrate them in the Urban Green Infrastructure, where they can play an important role for flora and fauna as stepping stones and green corridors in our heavily packed cities.   This research is being conducted also in Amsterdam and can be followed on her Instagram account: GreenroofBiodiverCity. We’re very much looking forward to the study and results in the upcoming years. Read more about our mission and values here. This blog post was co-written by Eva Drukker References ¹ https://en.wikipedia.org/wiki/Green_roof --- ## Investigating facial expressions in autism and borderline personality disorder URL: https://noldus.com/blog/investigating-facial-expressions-asd-bpd Published: 2021-06-24 09:38:00 Description: Within two specific populations researchers investigated the role of facial expressions on social interactions. This blog post is a guest post by Dr. Stephanie Van der Donck and Prof. Dr. Bart Boets of the Center for Developmental Psychiatry of the KU Leuven in Belgium. Facial mimicry in children with autism spectrum disorder Facial mimicry, which can be defined as the unintended, unconscious reproduction of the facial expressions of the interaction partner1, plays an important role in social interactions. It has been found to facilitate affiliation between interaction partners2, foster affective and cognitive empathy towards each other3, and boost prosocial behavior4.  However, this natural tendency to automatically mimic the facial expressions of the interaction partner may lack in individuals with autism spectrum disorder (ASD)5,6, who are characterized by deficits in social communication and interaction7.  Although contradicting findings have been observed8,9, previous studies have reported reduced or delayed automatic facial mimicry in adults10,11 and children12,13 with ASD as compared to controls. Given that numerous studies have suggested that spontaneous facial mimicry is associated with emotion recognition performance14,15, impairments in facial mimicry in ASD may contribute to difficulties with emotion recognition. Observing and analyzing facial expressions In previous studies16,17, we observed that, despite equal emotion recognition performances, the brains of children with ASD were less sensitive to rapidly and implicitly detect angry and fearful faces, as compared to typically developing (TD) controls. Therefore, we wanted to broaden our understanding of possible underlying differences in facial emotion processing mechanisms. We investigated spontaneous facial mimicry of 20 boys with ASD and 20 matched TD boys while performing a facial expression recognition task.  More specifically, we explored whether boys with ASD differed in the extent of their facial mimicry while processing expressive face stimuli, in comparison to TD controls, by analyzing video recordings of the participants’ concurrent facial expressions using FaceReaderTM software. As an index of facial mimicry, we expected that a particular expression displayed on the screen (i.e. one of the six basic expressions: anger, fear, happiness, disgust, sadness, surprise) would elicit congruent facial expressions on the participants’ faces. Our results suggested the absence of facial mimicry in both participant groups18.  The intensity values of all expressions were very low, except for the neutral facial expression. This combination of high neutral scores and low expressive scores indicated little variation in the participants’ facial expressions, and, accordingly, no mapping between the observed and produced facial expressions.  FREE WHITE PAPER: Download the free FaceReader methodology note to learn more about facial expression analysis theory. Learn more Transparency estimation in women with borderline personality disorder features Another key component of social interactions is mentalizing (i.e. the ability to reflect on the internal mental states of self and others). Similar to individuals with ASD, individuals with borderline personality disorder (BPD), who are characterized by self- and interpersonal dysfunction, among others7, display profound difficulties in mentalizing19.  These impairments in mentalizing with regard to the self and others may hamper their capacity for transparency estimation (i.e. the ability to estimate the extent to which one’s own mental states are observable to others20). This estimation requires awareness of one’s own mental state and processing of the internal information associated with bodily signals through which the mental state may be communicated to others (i.e. mentalizing of the “self”).  It also requires the ability to take a third-person perspective on the self in order to gauge how one is perceived by others (i.e. mentalizing of the “other”)21. These two processes are often impeded in individuals with BPD.  LABEL Title Learn more (Un)Awareness of communicative bodily signals These mentalizing impairments may lead to transparency over- or underestimation. For example, the enhanced salience of their self-experience (e.g. feelings of shame) may lead individuals with BPD to overestimate the transparency of these experiences22. However, reduced awareness of signals arising from within the body23 may lead them to assume that these states are not transparent, when they may in fact be communicating mental states through various bodily signals, resulting in an underestimation of their transparency21.  Likewise, difficulties with third-person perspective taking on the self may lead individuals with BPD to overestimate the transparency of their mental states when their own experience is highly salient to themselves, and to underestimate their transparency when they are unaware of their own mental state and of their communicative bodily signals21.  Measuring the actual intensity of facial expressions In the study of De Meulemeester et al.21, we investigated the capacity for transparency estimation in individuals high and low in BPD features by presenting a series of emotion-eliciting movie clips to the participants, while filming their reactive facial expressions. After each clip, participants estimated how transparent their emotional experience was while watching the particular clip. In addition, the observable transparency (i.e. how observable their mental states in fact are to others) of the participants’ emotional experience was defined as the actual intensity of their facial emotional expressions, measured via FaceReader software.  RESOURCES: Find out how FaceReader is used in a wide range of studies and how it can elevate your research! Learn more Results showed that individuals high in BPD features were less able to gauge how much of their emotional experience is observable to others through their facial expressions. Those who estimated their transparency to be high were not objectively more transparent, indicative of transparency overestimation21.  Similarly, those who judged the transparency of their emotional experience to be low did not exhibit less intense facial emotion expressions during the task, showing transparency underestimation. On the contrary, high levels of experienced transparency in individuals without BPD features were effectively associated with higher intensity levels of facial expressions, across all movie-clips21.  This impaired transparency estimation in individuals high in BPD features that is expressed in two directions (overestimating and underestimating their transparency) demonstrates that they are less able to represent their embodied selves from the perspective of others21. References 1.    Duffy, K. A. & Chartrand, T. L. Mimicry: Causes and consequences. Curr. Opin. Behav. Sci. 3, 112–116 (2015). 2.    Kavanagh, L. C. & Winkielman, P. The functionality of spontaneous mimicry and its influences on affiliation: An implicit socialization account. Front. Psychol. 7, 1–6 (2016). 3.    Drimalla, H., Landwehr, N., Hess, U. & Dziobek, I. From face to face: the contribution of facial mimicry to cognitive and emotional empathy. Cogn. Emot., 1–15 (2019). 4.    Van Baaren, R. B., Holland, R. W., Kawakami, K. & Van Knippenberg, A. Mimicry and Prosocial Behavior. Psychol. Sci. 15, 71–74 (2004). 5.    Moody, E. J. & McIntosh, D. N. Micmicry and Autism: Bases and Consequences of Rapid, Automatic Matching Behavior. Imitation and the social mind: Autism and typical development (eds. Rogers, S. & Williams, J.) 71–95 (Guilford Press, 2006). 6.    Vivanti, G. & Hamilton, A. Imitation in Autism Spectrum Disorders. Handbook of Autism and Pervasive Developmental Disorders (eds. Volkmar, F. R., Paul, R., Rogers, S. J. & Pelphrey, K. A.) 278–302 (John Wiley & Sons, Inc, 2014). 7.    American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (Dutch version). (Uitgeverij Boom, 2014). 8.    Deschamps, P. K. H., Coppes, L., Kenemans, J. L., Schutter, D. J. L. G. & Matthys, W. Electromyographic Responses to Emotional Facial Expressions in 6–7 Year Olds with Autism Spectrum Disorders. J. Autism Dev. Disord. 45, 354–362 (2013). 9.    Schulte-Rüther, M. et al. Intact mirror mechanisms for automatic facial emotions in children and adolescents with autism spectrum disorder. Autism Res. 10, 298–310 (2017). 10.    Mathersul, D., McDonald, S. & Rushby, J. A. Automatic facial responses to briefly presented emotional stimuli in autism spectrum disorder. Biol. Psychol. 94, 397–407 (2013). 11.    Yoshimura, S., Sato, W., Uono, S. & Toichi, M. Impaired Overt Facial Mimicry in Response to Dynamic Facial Expressions in High-Functioning Autism Spectrum Disorders. J. Autism Dev. Disord. 45, 1318–1328 (2015). 12.    Beall, P. M., Moody, E. J., McIntosh, D. N., Hepburn, S. L. & Reed, C. L. Rapid facial reactions to emotional facial expressions in typically developing children and children with autism spectrum disorder. J. Exp. Child Psychol. 101, 206–223 (2008). 13.    Oberman, L. M., Winkielman, P. & Ramachandran, V. S. Slow echo: Facial EMG evidence for the delay of spontaneous, but not voluntary, emotional mimicry in children with autism spectrum disorders. Dev. Sci. 12, 510–520 (2009). 14.    Borgomaneri, S., Bolloni, C., Sessa, P. & Avenanti, A. Blocking facial mimicry affects recognition of facial and body expressions. PLoS One 15, (2020). 15.    Lakin, J. L. Behavioral mimicry and interpersonal synchrony. Nonverbal Communication (eds. Hall, J. H. & Kapp, M. L.) 539–575 (De Gruyter Mouton, 2013). doi:10.1515/9783110238150. 16.    Van der Donck, S. et al. Fast Periodic Visual Stimulation EEG Reveals Reduced Neural Sensitivity to Fearful Faces in Children with Autism. J. Autism Dev. Disord. 49, 4658–4673 (2019). 17.    Van der Donck, S. et al. Rapid neural categorization of angry and fearful faces is specifically impaired in boys with autism spectrum disorder. J. Child Psychol. Psychiatry 61, 1019–1029 (2020). 18.    Van der Donck, S. et al. Investigating automatic emotion processing in boys with autism via eye tracking and facial mimicry recordings. Autism Res. (2021) doi:10.1002/aur.2490. 19.    Luyten, P., De Meulemeester, C. & Fonagy, P. The Self–Other Distinction in Psychopathology: Recent Developments from a Mentalizing Perspective. The Neural Basis of Mentalizing (eds. Gilead, M. & Ochsner, K. N.) 659–680 (Springer, 2021). doi:10.1007/978-3-030-51890-5_34. 20.    Gilovich, T., Savitsky, K. & Medvec, V. H. The Illusion of Transparency: Biased Assessments of Others’ Ability to Read One’s Emotional States. J. Pers. Soc. Psychol. 75, 332–346 (1998). 21.    De Meulemeester, C., Lowyck, B., Boets, B., Van der Donck, S. & Luyten, P. Do my emotions show or not? Problems with transparency estimation in women with borderline personality disorder features. Personal. Disord. Theory, Res. Treat. (2021) doi:10.1037/per0000504. 22.    Peters, J. R. & Geiger, P. J. Borderline Personality Disorder and Self-Conscious Affect: Too Much Shame But Not Enough Guilt? Personal. Disord. Theory, Res. Treat. 7, 303–308 (2016). 23.    Löffler, A., Foell, J. & Bekrater-Bodmann, R. Interoception and Its Interaction with Self, Other, and Emotion Processing: Implications for the Understanding of Psychosocial Deficits in Borderline Personality Disorder. Curr. Psychiatry Rep. 20, (2018). Dr. Stephanie Van der Donck, Center for Developmental Psychiatry, Katholieke Universiteit Leuven, Belgium (stephanie.vanderdonck@kuleuven.be)  Prof. Dr. Bart Boets, Center for Developmental Psychiatry, Katholieke Universiteit Leuven, Belgium (bart.boets@kuleuven.be)  www.laures.be  --- ## Mice walking again after a complete spinal cord crush URL: https://noldus.com/blog/mice-spinal-cord-crush Published: 2021-06-08 09:04:00 Description: Researchers from the University of Bochum achieved significant scientific results by making mice walk again after a complete spinal cord crush! Read more about it in this blog post. LABEL Title Learn more LABEL Title Learn more Paralyzed mice walk again Deeper areas in the brain are important for movement processes, such as walking and running. Therefore, the stimulation of axonal regeneration in these areas is essential for functional recovery after spinal cord injury. Hyper- interleukin-6 (hIL-6) was transported and was able to reach the nerve cells deep in the brain stem via transneuronal delivery. This resulted in previously paralyzed animals to start to walk again after two to three weeks! LABEL Title Learn more RESOURCES: Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts  Resources LABEL Title Learn more Automated evaluation of footprints For automated evaluation of footprints and coordination of mice during walking, researchers used the CatWalk XT, which is a frequently used gait analysis system for analysis of functional recovery after spinal cord injury. CatWalk XT consists of a corridor with a glass plate through which each animal traverses from one side to another. Only where each paw touches the glass plate, the light escapes thought the surface and reflects towards the camera underneath the glass plate. This way, the actual footprints are captured from below and automatically classified by the CatWalk XT software. Later on, the software identifies the changes in position, timing of each footprint and the dimensions. The parameters researchers looked at in this study were max area of each paw touching the glass, total area, stride length, base of support, and regularity index. LABEL Title Learn more New possibilities for treatment in the horizon Based on positive results and observation of mice walking again after a complete spinal cord crash, this gene therapeutic approach with hIL-6 is a potential strategy for reparation of a spinal cord after injury. Besides, it also opens new possibilities for further improvements of the functional outcome by combining it with other approaches. These combinations of strategies could increase axon regeneration and functional recovery after spinal cord injury. In future, hopefully, also in humans. LABEL Title Learn more --- ## The role of entrepreneurs’ facial expressions to gain financial support URL: https://noldus.com/blog/role-entrepreneurs-facial-expressions Published: 2021-05-25 14:16:00 Description: As an entrepreneur, attracting financial support is essential to get your start-up of the ground. How can positive facial expressions help to be more successful in a funding pitch? As an entrepreneur, attracting financial support is essential to get your start-up of the ground. However, entrepreneurs typically face tremendous challenges in convincing investors to fund their early-stage ventures. Many researchers have pointed out that displaying positive emotions during a funding pitch can help persuade investors. But how exactly does this work? How can positive expressions help entrepreneurs be more successful in their funding pitch?  Jiang, Yin, and Liu (2019) researched this by looking at joy as a positive emotion, to answer the question: Does displaying positive emotions (e.g. joy) during a funding pitch help an entrepreneur gain more financial support? Emotions as temporally dynamic and not static Since gaining financial support is critical for an entrepreneur, many researchers have looked at the roll of an entrepreneur’s positive emotional display on funding support. It turns out that it is the displayed emotions and not the experienced emotions that the audience directly observes and uses as input for assessment. Only, most studies looked at expressions as static and overall or average levels, and recent research has shown that emotions are temporally dynamic and more salient in some moments or phases than others.  Therefore, Jiang et al. (2019) used a dynamic approach in their research to examine the “peak” moments of entrepreneurs’ displayed joy – specifically, the strength and duration of peak displayed joy during different phases of a pitch.  Peak displayed Joy – strength and duration during different phases Why “peak” moments? When evaluating one's feelings after a certain event (either positive or negative), people tend to rely on peak moments of experienced emotions during that event rather than giving an overall evaluation. As an entrepreneur, you want your audience to give you a positive evaluation right? Well, when expressing positive emotions, you can ‘contaminate’ your audience with your positivity. Emotional contagion is particularly strong when the displayed emotions are highly expressive. Hence the researchers’ interest in the peak moments of displayed joy. But that’s not all. Duration plays an important role here. The more intense and longer the peak displayed joy, the more attention from the audience and therefore increasing the emotional contagion. However, there is a limit here.  Beyond a certain threshold, when peak displayed joy is overly long, the audience may instead develop negative inferences about it. So apparently, there is a so called “inverted U-shape” effect here as you can see in Figure 1. LABEL Title Learn more Figure 1. The inverted U-shaped relationship Lastly, the researchers also hypothesize about the timing of displayed joy during a funding pitch. Particularly the beginning and ending phases may play a salient role due to primacy and recency effects, which is the tendency of a person to recall the first (primacy) and last (recency) part of an event best.  To sum it up, the researchers were interested in examining the impact of an entrepreneur’s peak displayed joy level (a unique strength feature of emotional displays), as well as the total time length of these peak moments (a unique temporal feature of emotional displays). Moreover, they investigated the level and duration of peak displayed joy in two salient temporal phases of a funding pitch: the beginning and ending. Measuring the effect of displayed Joy on financial support To test the hypotheses, the researchers looked at the effect of displayed emotions in an important entrepreneurial context: pitching their business ideas to gain financial support from others. Therefore, 1460 pitch videos from Kickstarter (one of the biggest crowdfunding platforms) were used, with a display of entrepreneur’s faces.  To measure displayed emotions, the researchers found FaceReader™ to be the most suitable tool to automatically analyze facial expressions. FaceReader can accurately measure joy (96-100%) by analyzing the facial expressions (e.g. the movement of facial muscles in the lips and eyes) for each frame and calculate the intensity and duration of joy.  LABEL Title Learn more Financial support (funding performance) was measured by (1) the number of backers who pledge money to the project, and (2) the total amount of funding in U.S. dollars pledged by backers.   Can Joy buy you money? So, is it true? Does displaying positive emotions during a funding pitch help an entrepreneur gain more financial support?  Jiang et al. (2019) found consistent support for the positive effect of peak displayed joy on funding performance, especially in the beginning and ending phases of a funding pitch. They also found support for the inverted U-shaped effect of peak duration in the entire pitch and in the beginning of a pitch.  So interestingly, although a higher level of peak displayed joy leads to better funding performance, prolonged display of peak joy can undermine funding performance. Timing is also key here, since the effect is highest in the beginning phase. Thus, if you are an entrepreneur and you ask yourself if displaying joy can buy you money: Well, if you keep in mind to peak at the right moment and not peak too long, you might increase your chances! FREE WHITE PAPER: Download the free FaceReader methodology note to learn more about facial expression analysis theory. Learn more Reference Jiang, L., Yin, D. & Liu, D. (2019). Can joy buy you money? The impact of the strength, duration, and phases of an entrepreneur’s peak displayed joy on funding performance. Academy of Management Journal, 62, 1848-1871. https://doi.org/10.5465/amj.2017.1423  --- ## Screening plants for resistance to insect pests URL: https://noldus.com/blog/insect-resistance Published: 2021-05-19 13:30:00 Description: EntoLab is a computerized system for automated screening of plants for resistance to sucking insects. It can accurately screen many different plant lines in a high-throughput manner. LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more --- ## Observing and coding the behavior of siblings URL: https://noldus.com/blog/observing-and-coding-behavior-siblings Published: 2021-05-17 12:30:00 Description: Would it help if your brother or sister is sitting by your side when you're in pain? Would that ease the pain, or provide some distraction? Suppose you are asked to keep your hand in a bowl of ice-cold water for as long as possible. Kind of like an ‘ice bucket challenge,’ but slightly different. You know in advance that this experiment will be unpleasant, and that it might even be painful. Would it help if your brother or sister is sitting in front of you to support and encourage you? Would that ease the pain, or provide some distraction? This likely depends on the quality of the relationship between you and your sibling. How do parents or siblings best support a child in pain? Usually, when children need to be supported or are in pain, we naturally ask their parents to provide that support. Also, research on family factors in pediatric pain has mainly focused on parents. For example, in the OUCH lab (Opportunities to Understand Childhood Hurt laboratory) in Toronto, researchers primarily focused on understanding how caregivers and children interact within the context of pain. But what about the role of siblings? Approximately 80% of individuals have a sibling. Siblings are important in our lives, especially while growing up. Siblings help each other to learn how to socialize, share, and deal with feelings. The bond between brothers and sisters is usually much stronger than the differences that exist between them. The effect of a strong and positive sibling relationship A team led by Schinkel conducted a study that included a sample of 92 sibling dyads between the ages of eight and 12 years old. They were asked to complete two tasks: a tower-building task, and the cold-pressor-task (CPT) in a counterbalanced order. Furthermore, each child and one of their parents completed respective versions of the Sibling Relationship Questionnaire–Revised, addressing items such as intimacy, companionship, admiration of and by siblings, affection, quarrelling, and competition. The researchers used these measures to examine: - 1.Relations between the quality of the sibling relationship (warmth/closeness) and the behaviors of the siblings while they observed their brother or sister’s pain, as well as experiencing pain themselves during the CPT; - 2.Relations between an observing sibling’s behavior and a child’s pain outcomes Completing tasks while unobtrusively observed For the tower building task, the children were provided with a set of everyday craft materials (e.g. paper, tape, straws, and rubber bands) and were instructed to build the tallest tower they could. During the CPT, children were instructed to put their non-dominant hand into the water up to the bend of their wrist. They were told to keep their hand in the water for as long as they could (even if it was uncomfortable), until it became too uncomfortable or hurt too much. The water was maintained at 10 ± 1°C. Observing siblings were seated across from the child participating in the CPT and were not given direct instructions regarding how to interact with one another. The children took turns completing the CPT in a counterbalanced order (older vs younger sibling) with their sibling present. Video observations Both tasks were video and audio recorded, and the behaviors of the siblings was subsequently coded with The Observer XT to provide an observational measure of sibling relationship quality. Pain tolerance was scored as the duration of time in seconds each child left their hand submerged in the water during the CPT, up to a maximum of 240 seconds. Immediately after each CPT, the child who completed the CPT was asked to provide ratings of their pain intensity (“most” pain) and pain-related fear. Behavioral coding while viewing the videos The videos of both tasks were viewed three times. On the first pass, the behaviors were just observed without providing scores. On the second pass, the behavior of the older sibling was coded, and on the third pass, the behavior of the younger sibling and the dyadic behaviors were coded. A total score was calculated for each sibling dyad for positivity and negativity by summing the relevant codes across the intervals. In the Noldus Technical Briefing 'Behavioral Coding', we will show you how to create coding schemes that allow you to reach your behavioral endpoints but, at the same time, are clear enough for efficient and reliable coding. The behaviors were grouped by the researchers into: - attending (e.g. “Don’t worry, you’re going to be fine”) - non-attending (e.g. “Let’s ask mom if we can get a pizza for dinner”) - coping/encouragement (e.g. “You’re doing a great job”) - other behaviors (e.g. “Let’s see who can do it longest”) The examples given here relate to the observing sibling. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial The quality of the sibling relationship The results of the study showed that more observed positivity was related to the second sibling engaging in more non-attending and less attending behaviors while participating in the CPT. This means they were more often searching for distraction, or used more humor to cope. They also showed less resistance, and expressed less negative talk about the situation (e.g. ‘The machine is noisy’, or ‘I can’t do this anymore’). Also, greater levels of the first sibling’s self-reported warmth/closeness were related to themselves engaging in more non-attending behaviors while completing the CPT. In response to these results, the researchers concluded that children with positive/warmer relationships tended to engage in less pain-oriented behaviors, and in more behaviors that shifted the focus away from their pain (e.g., distraction). They say that children with better sibling relationships may engage in natural conversation and humor more often, and are more likely to use “non-attending behaviors” as a potentially helpful strategy while in pain and with their sibling present. Does the behavior of an observing sibling influence a child’s pain outcome? Findings for the second research question show that greater attending behaviors by the observing child were related to their sibling having lower pain tolerance scores, which was the case for both siblings. Greater coping and encouragement behaviors by the second sibling while observing were related to their sibling reporting higher pain intensity and pain-related fear. The results of this study emphasize the importance of family factors in children’s pain experiences, and highlights the potential role siblings may play in how children learn to interpret and respond to acute pain across development. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly References Schinkel, M.G.; Chambers, C.T.; Corkum, P. & Jacques S. (2018). Dyadic analysis of siblings’ relationship quality, behavioural responses, and pain experiences during experimental pain. Pain, 159 (8), 1569-1579. --- ## Vestibulopathy: movement and balance issues investigated in rats URL: https://noldus.com/blog/vestibulopathy-investigated-rat-model Published: 2021-05-03 10:30:00 Description: It is hard to diagnose vestibulopathy, so a rat model was developed to study the progress of symptoms, from day one to day 30 after ear injury. Results can improve future human diagnosis and therapy options. Many people suffer from vestibular pathologies, which are often caused by damage to the inner ear. Symptoms consist of, a.o., affected eye movement (bouncy vision) and weaker posture control (e.g. balance problems), and can cause cognitive deficits. However, it is hard to diagnose these disorders. Diagnosing vestibulopathy A collaboration was started between the university of Marseille and the French society of vestibular kinesiotherapy. The researchers analyzed symptom evolution of vestibular disorders in a rat model with Noldus EthoVision XT, and then compared the results to similar data obtained from humans. This data could help diagnose the condition better, especially in dynamic situations, which is very useful when it comes to treating vestibulopathy. Movement difficulties This research yielded some insightful results. For example, people with a vestibular disorder typically feel they are unable to run, because of their balance issues. Unexpectedly, the injured rats in this study developed a higher maximum speed compared to fully healthy control rats. This seems to show that the faster affected rats walk and run, the more stable their gait will be, just like when riding a bicycle. However, unlike rats, human patients often do not dare to walk faster, for fear of losing their balance. Applying this to human therapies, this notion could decrease the patients’ fear, and increase their ability to move around significantly, despite their injury. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more Rodent model By removing the vestibulocochlear nerve from the rats’ left ear, the researchers mimicked the typical symptoms of vestibulopathy. They couldn’t tell anymore when their head was straight, which gave them trouble moving forward. Rats usually walk by first pointing their head to the direction they want to go to, and then walking in that direction. Throughout the experiment, those symptoms (partially) improved. Furthermore, humans affected by vestibulopathy suffer from unstable vision, while rats do not, probably because rats lack a fovea. This could cause humans to experience more balance problems, and therefore patients reduce head movement as much as possible. Very fast head movements can cause unstable vision as well, since the reflex needed for vision stabilization is damaged too. Behavioral experiments In order to test the effects of the surgery in rats, open field tests were done on specific days post-surgery. One test was done a day before surgery, as a reference. On each testing day, the rats were allowed to explore the arena individually, for 10 minutes. Videos of the experiment were analyzed using Noldus EthoVision XT 14, which kept track of three specified body-points, i.e., tail base, center point and nose point. Among other variables, body and head rotation, acceleration and maximum speed were tracked. LABEL Title Learn more Locomotor activity Acceleration Head and body acceleration of a rat were measured automatically for the first time, using Noldus EthoVision XT. During the first three days post-surgery, the rats had trouble accelerating above their average pre-surgery acceleration, after which it increased again until above average from day 7 onwards post-surgery. Post-surgery acceleration was also more varied than pre-surgery, which might be caused by rats not being able to detect acceleration properly anymore due to the nerve damage Circling and rotation behavior Two specific behavior types were noted during the experiments, namely rotating, i.e., turning around while exploring, and circling, i.e., running in tight circles. Turning around could happen in either direction, though they would prefer turning ipsilaterally (to the left in this study). Circling would only ever happen ipsilaterally. There could be various explanations for that, for example an increase of weight applied on the left paw, or a specific spinal neuron group being inactivated. Contrary to rats, humans do not walk in full circles. Instead, they walk in a star shape: a specific test called the “star walk” makes the patient repeatedly walk several steps forward and backward in a straight line, with their eyes closed. The star shape is caused by a consistent ipsilateral deviation in their walking direction. Vestibular compensation Modelling vestibulopathy in rats consisted of two phases; an acute phase (7-10 days post-surgery) followed by a compensation phase. During the acute phase, various parameters like head and body velocity first return to normal, and then exceed that level, up to a maximum that is maintained until 1 month after surgery. This seems to be a way of the rat’s body to eventually find a new balance where part of the symptoms are fully compensated.  The same happens in humans, where the acute phase after trauma usually seems to last a few hours up to a few days, after which the (partial) recovery takes place. An interesting new therapy that might help vestibular patients recover is by having them practice walking at higher speed. As mentioned before, an increased pace might improve their balance, and thus help them get around more independently. So, despite differences between rats and humans dealing with vestibulopathy, results from this study may help improve treatment and therapy in humans. Further study into their mean and maximum speed may gather more insights into the level of compensation a patient could achieve following their injury. --- ## Nearly impossible to video track: small shrimp URL: https://noldus.com/blog/gammarus Published: 2021-04-08 16:48:00 Description: Gammarus shrimps are exceptionally difficult to track, but Noldus solved the puzzle, resulting in interesting insights into its ecology. Scientists at the University of Salento in southern Italy have published [1] an interesting study on the ecology of  tiny aquatic shrimps called Gammarus insensibilis. In order to carry out the study they had to overcome some challenging technical hurdles, but in the end they succeeded, and it produced fascinating results.  Optimal foraging Finding enough food whilst not wasting too much energy looking for it, is a key problem that all animals have to solve. There is a strong evolutionary pressure to be good at that. If you can forage more efficiently than your neighbor, you will have more time and energy left over for other activities, and so you will have a higher evolutionary fitness.  That means that many studies have found that foraging strategies of animal species are often mathematically close to optimal. However, what is optimal is very different for different types of animals. Size, metabolism, and position in the food chain (predator/prey) are among the important factors. Aquatic ecosystems often work just a bit differently than terrestrial ones [2], and we know less about them because they are harder to study.  So studying the foraging of a typical species like Gammarus insensibilis has the potential to give insights not only in that one species, but more generic insights into the way that those ecosystems work. Shrimps No matter where you live, if you find a clean stream and rummage around in the bottom of it with a net, you will probably come up with some freshwater shrimps. Often they will belong to the genus Gammarus. There are over 200 different species of Gammarus in the world and they are found in salt and brackish water (partly salty, e.g. in an estuary) as well as in freshwater.  The species used in this study, Gammarus insensibilis, is called in English the Lagoon Sand Shrimp, and indeed it lives in brackish water in coastal lagoons. It is found along southern European coasts of the Mediterranean, the Black Sea, and also on the coast of the English Channel. It can be found living up to 15 meters deep and lives off rotting vegetation and algae. Gammarus is a crustacean, like crabs and woodlice; although it is an invertebrate, it is not an insect (count the legs!).  Nearly impossible tracking Gammarus insensibilis is really difficult to track by video. It hides away from sunlight, so normal illumination doesn't work. It is semi-transparent, so the camera has great difficulty distinguishing it from the background. They can be as small as 5 mm long (so it is much thinner than 5 mm). To make matters worse, as it moves, it likes to stick close to the walls of the maze. That means that if the camera isn't directly overhead, then it cannot see it.  Aquatic invertebrates can be tracked with DanioVision, but not for this sort of experiment. In order to be able to measure the foraging behavior of Gammarus, the maze needs to be quite large, with a number of chambers with food in, connected by channels. The recordings also need to be long, six hours, to give the shrimps time to move around enough in the maze. Small terrestrial animals that blend in with their background are sometimes tracked with the help of colored dots painted onto their bodies using a technique called mark and recapture. Unfortunately that won't work for Gammarus and similar aquatic animals. Scientists have tried to mark them in various ways, and it always ends up damaging them and having an effect on their behaviors, so the results are not reliable. The solution for this video tracking problem Video images are composed of pixels and like with every video tracking system, EthoVision XT needs the animal that it is tracking to be at least a few pixels wide. Theoretically, a solution might be to have a really high resolution (that is, with many pixels) video camera placed above the large maze. However, that would mean that the camera was not directly be situated above the chambers and channels at the edge of the maze, and so the animals would be able to hide from it as they swim along hugging the walls. The solution that Noldus and the researchers at the University of Salento came up with, is to have multiple cameras above the maze and for each of those images to be analyzed as one EthoVision XT arena.  However, that creates a new issue; how to deal with the problem of the animals moving from one camera to another. This was solved by a clever approach to the analysis. Each channel between the chambers filled with food was divided into three sections, and EthoVision XT recorded when the animals moved from one section to the other, a 'transition'. In that way, the speed and frequency of when an animal left a food chamber and entered a new one, could be quantified. From those transitions all sorts of other statistics could then be worked out. The problem of the animals reacting to light and their transparency was solved by making a large infra-red lighting unit illuminating the whole maze from underneath and using near infra-red sensitive cameras together with filters blocking out white light.  RESOURCES: Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! Learn more Successful new method to track shrimps and analyze their behaviors The custom setup with EthoVision XT at its heart worked very well. Only a small number of animals couldn't be tracked because they were too small or too transparent. The new method was a success! The scientific results were also interesting: - The general pattern was: at the beginning of the six hours the Gammarus started foraging and afterwards they shifted to exploration - Hungry animals showed fewer transitions. That is, they kept foraging longer in the food chambers before leaving them and go searching for better food. - Larger animals spent less time in the chambers filled with food, and they moved around more in the maze, with a greater cumulative space. That is, the sum of the area of all the areas they visited was more. The reason for this is probably that energy requirements increase with body size (larger animals need to eat more) and also they have more efficient locomotion (larger animals can move faster).  References 1. Shokri M, Cozzoli F, Ciotti M, et al. A new approach to assessing the space use behavior of macroinvertebrates by automated video tracking. Ecol Evol. 2020;00:1–11. https://doi.org/10.1002/ece3.7129 2. Spink, AJ, 1992, Ecological strategies of Batrachian Ranunculus species. PhD Thesis, University of Glasgow. Acknowledgements The diagrams from Shokri et al. 2020  are available for reproduction in any medium under the Creative Commons Attribution license. The photograph of Gammarus is from Wikipedia and is of Gammarus locusta. Although the author of this blog was not involved in the custom setup described here, he did make an earlier visit to install and train EthoVision and other related setups, and he would like to thank the researchers for their welcome and hospitality. --- ## How does handedness relate to infant language development? URL: https://noldus.com/blog/observing-analyzing-infants-handedness-language-abilities Published: 2021-04-06 10:33:00 Description: Developing motor skills appears to be related to language abilities. The research team of Sandy Gonzalez investigated whether consistency in handedness predicts receptive and expressive language. When you talk about handedness, the first question that comes to mind is ‘What hand do you write with?'. In addition, movements such as combing your hair or throwing a ball are tasks that uncover your hand preference. We usually perform these activities with one hand. There are also a lot of tasks we fulfill using both hands. For example, cutting a piece of paper, unzipping a bag, peeling a sticker from its backing, or unscrewing a lid from a jar. These skills are called Role Differentiated Bimanual Manipulation (RDBM). Fine motor skill development is key Role-differentiated hand use can be defined as a bimanual manipulation skill in which each hand performs a different action, but these actions unite in the manipulation of an object. The different actions of the two hands have complementary functions; one hand has a supporting, or stabilizing role as the other manipulates or explores the object. Thus, the one hand holds the paper steady, while the other hand cuts it in half with a scissor. A sophisticated fine motor ability. Developing these motor skills is key to children’s learning and exploration. It also appears to be related to spatial, social, and language skills. According to research, consistency in hand preference early in development is linked to language skills. For example, Nelson and colleagues performed several studies to confirm this. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Developmental research on handedness and language Researcher Sandy Gonzalez from the Florida International University and New York University conducted a study together with her team to investigate whether consistency in handedness predicts receptive and expressive language abilities. What are receptive and expressive language abilities? - Receptive language ability: the child understands and comprehends spoken language that he or she hears or reads. - Expressive language ability: the child makes requests, choices, asks questions, answers, and describes events. Speaking, gesturing (waving, pointing), writing (texting, emailing), facial expressions (crying, smiling), and vocalizations (crying, yelling) are all variations of expressive language. Score infant behavior for analysis A group of 90 children was included in the study. The researchers assessed hand preference for RDBM at monthly intervals from 18 to 24 months. Twenty-nine objects that afford actions where one hand stabilizes the object (non-preferred hand) while the other hand manipulates the object (preferred hand), were presented individually at the child’s midline while they sat on their parent’s lap. Children were video recorded during the RDBM assessment. Video data were scored afterwards by trained observers using The Observer XT. Three latent classes for toddler hand preference were identified using the Latent Class Growth Analysis (LCGA): right-mild left (largely right hand use with little left hand use), right-moderate left (mostly right hand use with some left hand use), and left-moderate right (mostly left hand use with some right hand use). Receptive and expressive language skills were measured at 5 years of age, using the Preschool Language Scales 5th edition (PLS-5). The scales assessed various areas of language development including vocal development, social communication, semantics, language structure, and emerging literacy skills. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Consistency in hand preference important for language outcomes The majority of the sample fitted a right-mild left classification of hand use for RDBM. This hand preference as well as the other two classes demonstrated distinct hand preferences at 18 months, and did not change over time from 18 to 24 months, indicating that hand preference for RDBM was stable throughout toddlerhood. Furthermore, the researchers found that toddlers with consistent right hand use for RDBM had greater receptive language skills at the age of 5, compared to toddlers with a right hand preference but moderate left hand use, and compared to toddlers with a left hand preference but moderate right hand use. They also demonstrated greater expressive language skills at 5 years compared to toddlers with a left hand preference but with moderate right hand use. These results indicate that early consistency in hand preference for fine motor skills during toddlerhood serves an important role in language outcomes in early childhood. Tools to study children's development In the Noldus Webinar about Research tools in Developmental Psychology, we explained how our research tools can be used to study the behavior of children both in a natural and in a laboratory setting. Curious? Watch the webinar on demand now! References Gonzalez, S.L.; Campbell, J.M.; Marcinowski, E.C.; Michel, G.F.; Coxe, S. & Nelson, E.L. (2020). Preschool language ability is predicted by toddler hand preference trajectories. Developmental Psychology, 56(4), 699–709. https://doi.org/10.1037/dev0000900 Kimmerle, M.; Mick, L.A. & Michel, G.F. (1995). Bimanual role differentiated toy play during infancy. Infant Behavior & Development, 18, 299-307. https://doi.org/10.1016/0163-6383(95)90018-7 --- ## Observing and analyzing repetitive movements in infants to detect autism URL: https://noldus.com/blog/repetitive-movements-infants-detect-autism Published: 2021-03-18 10:52:00 Description: To examine if a specific repertoire of repetitive movements was present in children with autism, researchers used home videos to code the behaviors of the infants. Making the same movement multiple times, or making repetitive movements, is an important step in the development of a newborn child. In the first year of life, an infant learns how to use his or her arms, legs, mouth, hands, and fingers and discovers a wealth of possibilities. In the beginning, their movements are reflexes, but soon they develop into conscious, voluntary movements. Now, the infant really wants to move his or her hand to the toy and grab it. Or, the infant consciously waves repeatedly to his or her dear grandmother. Repetitive movements and motor development Repeating these movements is typical for motor development; it lays the foundation for the ability to adopt the acquired repertoire of movements in order to function properly and to expand variability. However, an increased frequency of repetitive movements has been widely described in neurodevelopmental disorders as well. One of the core symptoms of Autism Spectrum Disorder (ASD) is the frequency and persistence of repetitive and stereotyped movements during toddlerhood, together with restricted interests and activities. Evidence for this is mainly found in studies with infants ages 1 year and older. FREE WHITE PAPER Autism research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Get your copy instantly Using home videos to detect early signs of autism The purpose of the study of Purpura et al. was to verify if a higher frequency of repetitive movements (described through their rate and duration) could differentiate infants with ASD from infants with Developmental Delay (DD) and Typical Development (TD), analyzing the age range between six and 12 months. In addition, they described the repertoire of these movements analyzing both the body parts involved and their symmetry. The researchers conducted a retrospective analysis of video clips taken from home videos recorded by parents in a sample of 30 children equally distributed among three groups. The groups were comprised of 10 infants with ASD, 10 with DD, and 10 with TD. Home videos have the advantage to capture infants in their natural environments and the behaviors that regularly occur within them. Children with ASD and DD were diagnosed at an age range between three and four years. At the time of diagnosis, parents were asked to provide their home videos. The videos showed the children's behaviors when they were six – 12 months old, long before they had been diagnosed with autism, to examine if a specific repertoire of repetitive movements was present earlier in life. Coding behaviors to analyze repetitive movements The research team first extracted all the sequences in the video clips in which the entire body of the child was clearly visible. A total of 148 video clips lasting at least one minute and a total of 10 minutes of video clips for each child was used for coding. To code the behaviors of the infants, the team set up a coding scheme for the Repetitive Movement Episodes (RMEs) considering head, mouth and tongue, arms, hands, lower limbs, and torso as parts of the infant's body potentially involved in repetitive movements. The selected video clips were randomly assigned to two coders who were trained to use The Observer XT and to detect the RMEs. The rate per minute and percentage duration of RMEs, which were automatically generated by The Observer XT, proved to be a useful measure for the occurrence and the prevalence of target behaviors within observations with a variable duration. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Bilateral repetitive movements as a specific risk marker for ASD The analysis of the observations revealed that frequencies and durations of bilateral RMEs with arms, hands, fingers, and lower limbs were significantly higher in ASD than in the other two groups. In addition, an adequate diagnostic accuracy of those RMEs was found as well. No significant difference was found between the distributions of unilateral RMEs between ASD and DD/TD. The presence of an ASD-specific pattern of bilateral repetitive movements at this early age was indicated by this study, although some limitations, such as the study design and the small sample size, cause the results to be preliminary in nature. The researchers point out that greater attention should be given to repetitive movements as specific risk markers for an early diagnosis of ASD. Perhaps, when diagnosis at this early age is possible, therapeutic behavioral interventions can start early and might provide a more effective therapy for potentially autistic children. Tools to study children's development The behavior of children includes not only body language, but also facial expressions, eye gaze and psychophysiological responses. Measuring these will help answer your research questions. In the Noldus Webinar about Research in Developmental Psychology, we will explain how our research tools can be used to study the behavior of children both in a naturalistic and a laboratory setting. The webinar is available on demand! References Purpura, G.; Costanzo, V.; Chericoni, N.; Puopolo, M.; Scattoni, M.L.; Muratori, F. & Apicella, F. (2017). Bilateral Patterns of Repetitive Movements in 6- to 12-Month-Old Infants with Autism Spectrum Disorders. Frontiers in Psychology, 8, 1168. Doi: 10.3389/fpsyg.2017.01168 --- ## Measuring consumer choice behavior URL: https://noldus.com/blog/measuring-consumer-choice-behavior Published: 2021-03-11 09:42:00 Description: Two recent projects provide new insights into how best to measure the choices that we make. Imagine that you are sitting in a laboratory. You're surrounded by bright white and stainless steel surfaces. Someone wearing a lab coat comes in with a white plastic tray in his or her hand. On the tray there is a small square of chocolate, which is offered to you. You pick it up and eat it.  Later that day you are at home, on a comfortable chair, listening to your favorite music, in front of a warm fire. When a friend offers you some chocolate, do you think you might enjoy it more that the one you ate in the sterile laboratory environment?  Of course you will! However, even though this is a well-known fact to scientists studying consumers' responses to food, still the majority of experiments carried out today are done in conditions like the first example.  The influence of control The advantage of a laboratory is that everything is controlled and uniform. If you do the experiments in people's homes, everyone's living room will be different, there is the problem of privacy, and it will probably cost a lot more time to carry out. Nevertheless, researchers are increasingly turning to carrying out those types of experiments in real life environments, simply because otherwise their carefully collected data might actually not mean much in the real world.  For instance, if you have developed a new flavor of chocolate, but it can only be distinguished from the old brand and appreciated by trained experts in controlled conditions, then it is not so likely that anyone will buy it in preference to the old one. The vast majority of new food products flop; they are withdrawn from sale before the year is out. The traditional way of assessing them is thought to be one of the reasons for that failure. Technology to the rescue There are two ways in which technology can come to the rescue of researchers struggling with this issue. Firstly, a simulated environment can be a good substitute for the real world. This can range from a simple computer monitor, to a VR headset, to an experience room in which the participants can move around naturally, with video projected on the walls and the background sounds, lighting and sometimes even smells can be adjusted accordingly. In that way everyone's living room can indeed be identical and the context can quickly and easily be changed. Breaking Habits In the Breaking Habits for the Better project, led by Wageningen University and Research with a number of other partners including Noldus, they carried out such experiments. One of the questions that they investigated was how much the appropriateness of the context influences how much we enjoy food. Does sushi really taste better in a sushi restaurant?  In their experience room they built two contexts. A sushi restaurant complete with the right furniture, subtle lighting and background sounds, and also a beach with deck chairs, bright bluish light, beach sounds and even beach balls and shells. In both setups the relevant background was projected around the walls.  Image from https://doi.org/10.1016/j.foodqual.2021.104193, available under Creative Commons license [1]. They tested two products; sushi and popsicles (ice lollies). The results were striking; the participants liked the sushi more in the restaurant than on the beach, and they liked the popsicles more on the beach than in the restaurant. This shows two things. Firstly, that the context really does make a difference to how much we enjoy food. And secondly, that it is possible to create an immersive enough experience in a simulated environment that it will significantly affect participants, even though they were well aware the whole time that they weren't really on the beach or in a restaurant.   Objective measures A second way in which technology can come to the rescue of researchers struggling to measure the consumer experience is by objectively measuring the emotions and behaviors of the participants. In studies like the one above, participants are asked how they feel about the food. That does indeed yield valuable information.  However, there are also shortcomings to that method. There is the danger that they give socially desired answers, perhaps subconsciously. For instance, they might guess that they are testing a new product and that the person in front of them might be pleased if they say that they like it. Also, people vary a lot in their ability to articulate or even in how much they know how they feel about things. That can be trained, but then you are no longer testing the response of your buying public.  A solution is to complement the questions asked with measurements such as facial expressions (recent versions of FaceReader also work when the mouth is obscured or if the participant is chewing) or physiology. Facial expressions are the primary way in which we communicate our emotions to others, and we often make them without thinking about what we are communicating.  Responses like changes in heart rate, pupil diameter, and sweating occur without us realizing and can give a lot of information about how and especially how much someone feels about something. It is important to note that it is not that the objective measures give right answers and subjective questions wrong answers, but that they provide complementary insights [2]. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more COMFOCUS These objective methods have been used in psychological studies for decades, but they are relatively new to the field of consumer behavior research. A large European project called COMFOCUS has started at the end of 2020. That project is also led by Wageningen University and Research with Noldus as one of the partners. One of the aims of that project is to develop methodologies for objective measurements of consumer behavior.  An important aspect of the methodology development is to harmonize the protocols and define standards for taking objective measures. That will be carried out for a number of different methodologies including physiological measures, virtual reality research, text mining, and longitudinal studies.  There will also be work done on integrating the data. Partly that will consist of working out how to integrate the different types of data just mentioned, which is a far from trivial problem. In addition, Noldus will be creating a software platform which will integrate, synchronize, and analyze the data, especially data gathered using a variety of different sensors. The availability of standard methods and tools for carrying out this research is expected to give a great boost to the field and Noldus is happy to be able to contribute to that.  RESEARCH PROJECT Want to partner with us? If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 35+ years of experience Learn more References 1.  G. van Bergen, E.H. Zandstra, D. Kaneko, G.B. Dijksterhuis, R.A. de Wijk (2021). Sushi at the beach: Effects of congruent and incongruent immersive contexts on food evaluations. Food Quality and Preference, 91, 104193. https://doi.org/10.1016/j.foodqual.2021.104193. 2. Roelien van Bommel, Markus Stieger, Michel Visalli, Rene de Wijk, Gerry Jager (2020). Does the face show what the mind tells? A comparison between dynamic emotions obtained from facial expressions and Temporal Dominance of Emotions (TDE), Food Quality and Preference, 85, 103976. https://doi.org/10.1016/j.foodqual.2020.103976. --- ## The role of mimicry in the development of social communication URL: https://noldus.com/blog/role-mimicry-development-social-communication Published: 2021-02-16 11:00:00 Description: Children learn from interacting with others, especially their parents. For example, reproducing the emotions that others express is part of that. Child development is an exciting process to study. Thanks to all kind of research, we have discovered that this development is without any doubt linked to daily living with people. Children learn from interacting with others, especially their parents. For example, reproducing the emotions that others express is part of that.  Mimicry important for social development You smile at your baby and your baby smiles back! Copying facial expressions is one of the great milestones in the social development of a child. This way, the child learns what is funny and nice and discovers how to communicate non-verbally. Moreover, it fosters social bonding since mimicry tells the other that ‘I am like you’ and ‘I feel you’.  Still, little is known about the mechanisms controlling the early development of emotional mimicry. Therefore, the research team of Eliala A. Salvadori, of the University of Amsterdam, conducted a study to investigate three things: - Infant emotional mimicry of strangers’ facial expressions and its association with parent emotional mimicry. Emotional mimicry was identified as the time (duration in seconds) when participants displayed positive facial expressions (i.e., smiling) in response to the strangers’ happy faces, and negative facial expressions (i.e., frowning/scowling) in response to the sad, angry, or fearful stimuli. - Parent-infant mutual attention, which was quantified as the time (duration in seconds) spent by the infant and the parent simultaneously looking at one another. - Parent dispositional affective empathy, and to what extent this influences the infant mimicry during triadic situations. The triadic situation includes the child, the parent, and the stimulus on screen.  Looking at the parent-child social interaction Salvadori and her team included 117 infant-parent dyads, living in Amsterdam and surrounding areas. The infants (six- and twelve-month-olds) and one of their parents (mother or father) were presented with dynamic videos of unfamiliar adults showing happy, sad, angry, and fearful faces.  Besides, parents were asked to complete an online questionnaire (Interpersonal Reactivity Index) to measure the tendency to experience feelings of sympathy or concern for unfortunate others.   Interested in parent-child interaction research? This free white paper will show you how to facilitate the study, how to set up your experiment, and analyze your data. Capturing automatic and spontaneous responses on video The main interest of the study was on the natural development of the triadic social interaction. The researchers wanted to measure the participants’ automatic and spontaneous behavioral responses. Therefore, parents were asked to behave as they would normally do and not to intervene unless the child sought for their attention. The behaviors of the participants were recorded on video.  Emotional stimuli were employed from the Amsterdam Dynamic Facial Expression Set (ADFES), in which facial expressions are based upon prototypes of the “basic emotions” as described in the Facial Action Coding System (FACS). Participants were presented with eight blocks of five videos each. Each block always started with strangers’ neutral face, followed by videos of happy, sad, angry, and fearful facial expressions in a randomized order. Behavioral coding of emotional communication In their study, the researchers made use of a microanalytic facial coding system that relied on second-by-second offline coding of the infants and parents. This enabled them to capture micro changes in the facial-expressive behavior that would typically be invisible to the human eye. With that, the measurements showed more information than just assessing the presence (vs. absence) of the mimicry.  The coding system of Colonnesi et al. 2012 was used for emotional communication, which include these categories: - Facial expressions - identified as positive when involving smiles and raising corners of the lips, and negative when involving frowns or lowered-lip corners.  - Gaze direction - coded as to the stimulus, the screen, the interaction partner, or elsewhere. Whereby must be noted that coding gaze direction to a stimulus was an adaptation of the original coding scheme. An additional coding category was included to classify the stimuli as neutral, happy, sad, angry, or fearful. The observational data was coded and analyzed using The Observer XT and the inter-rater reliability was calculated for the six coders who participated in the project.  FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial The influence of emotional stimuli on mimicry The research team extensively reported about the results of this study in their publication. They found that, in case of: - Happy stimuli, infant emotional mimicry was positively associated with parent emotional mimicry and affective empathy. The infants who mimic the happy stimuli longer have parents who both mimic longer and score higher levels of affective empathy.  - Sad stimuli, infant emotional mimicry was positively associated with parent-infant mutual attention, indicating that infants who mimic the sad stimuli longer are those who share longer attention with their parents. Also, parents seemed to mimic sad stimuli longer when they showed higher levels of affective empathy. - Angry or fearful stimuli, unfortunately no significant relation was found.  To automatically analyze the effects of stimuli on facial expressions of infants, the researchers aim to validate Baby FaceReader. Therefore they use a sample of 4- and 8-months-old infants whose facial expressions are already coded with The Observer XT during a study on the development of infant emotional communication with strangers vs. mothers and fathers. Using Baby FaceReader will save them resources, because coding of expressions is done automatically.  FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Understanding the development of emotional communication in infants The researchers conclude that only when the emotional stimuli are happy, and thus perceived as affiliative, emotional mimicry occurs as an automatic and spontaneous parent-infant shared behavior. It surprised the researchers that infants’ responses to angry and fearful stimuli did not relate to the dimensions of parent-infant mutual attention, nor to parent emotional mimicry. Perhaps because these emotions are related a threatened feeling and provoke introvert behaviors. Identifying which factors underpin individual differences in emotional mimicry as early as in the first year of life is the next step towards a better understanding of communicative development. Reference Salvadori, E.A.; Colonnesi, C.; Vonk, H.S.; Oort, F.J. & Aktar, E. (2021). Infant Emotional Mimicry of Strangers: Associations with Parent Emotional Mimicry, Parent-Infant Mutual Attention, and Parent Dispositional Affective Empathy. International Journal of Environmental Research and Public Health, 18, 654. https://doi.org/10.3390/ijerph18020654   --- ## Learn about people's behavior by observing them URL: https://noldus.com/blog/learn-about-people-observing-them Published: 2021-02-08 12:38:00 Description: An observation or usability lab allows researchers to observe test participants unobtrusively, in an environment similar to the participant’s natural surroundings. Everyone is unique; everyone behaves differently. What is more fun than sitting somewhere - on a park bench, at the beach, or on a terrace, and watch people go by? Postures, movements, nonverbal and verbal behavior - all can be observed. Watching people, seeing their behaviors, looking at their performance, is interesting for many reasons. It's fun, but it is also very revealing. Knowing what motivates people, why they do what they do, and how they respond to influences around them will lead to improvements in terms of quality of life. If you want to control as much of the environment as possible, to prevent your observation from being interrupted by a rainstorm, or a barking dog, the best place to perform your observations is in a laboratory where you have full control. FREE WHITE PAPERS How to build a research lab Do you want to learn more how to set up a research lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download 3 free 'how to' guides! Submit to download Observational research One type of a controlled setting that is often used by researchers is an observation lab. For example, observation is an obvious method of carrying out research in psychology. In the case of controlled observations, the researcher decides where the observation will take place, at what time, with which participants, under what circumstances, and uses a certain procedure with all participants. Coding behavior Rather than writing a detailed description of all behavior observed, it is often easier to code behavior according to a previously agreed scale using a coding scheme (i.e. conducting a structured observation). Often, videos are collected in the observation lab, which allows easier behavior coding, and also provides a backup to the researcher, who can go back to these videos as often as needed after collection. Download here the FREE white paper 'How to set up behavioral coding - 7 tips' Approaching real life situations To give an example: The Opportunities to Understand Childhood Hurt (O.U.C.H.) Laboratory run by Dr. Rebecca Pillai Riddell focuses on understanding how caregivers and children interact within the context of pain. Their research is performed in a variety of settings, from their own lab space at the York University Campus to the Neonatal Intensive Care Units of major Toronto hospitals. For researchers in the O.U.C.H. laboratory, observations are made as similar to real life situations as possible, but with the advantage of easier and more efficient data collection. The data obtained is highly quantitative (i.e. numerical) in nature, so analysis can be done quickly. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Additionally, many observations can take place within a short amount of time, which ensures that using the lab is a less time consuming method for both researcher and child. With controlled observations, results can be easily replicated by other researchers using the same observation schedule. This provides reliability of results, which is a hallmark of psychology research. Evaluate the usability of a product by testing it on users Another type of observation which can be carried out in a laboratory is usability testing. This methodology is a must when you aim to assess use of your app, website, or product. By means of these usability tests you are able to assess the degree of successfulness in usability – are people using your product in the way you've intended and does it increase their user experience? When necessary, the data from these tests can be used to make improvements in usability. If the product does not add value to the way in which the user normally performs tasks, then the user has no need to use the product at all. With usability testing, the focus is always user-centric. Typically, during a usability test, participants will be asked to complete tasks while observers watch, listen, and takes notes. The goal is to identify any usability problems, collect qualitative and quantitative data, and determine the participant's satisfaction with the product. Make your test as realistic as possible One way in which usability testing can be done is in a User eXperience (UX) lab. Users perform different tasks in a simulated environment; as with observation labs, an advantage of testing in a lab is that the researcher can control the environment. Distractions (sound, nearby objects, screens, etc) can be minimized, and accessories can be added as desired, in any location: cameras, eye trackers, a one-way mirror, and even physiological monitoring devices. Moreover, facial expression analyses software can be used to assess emotions, arousal, and valence of the participants. The test space is always available when you have your own lab, and it can be furnished for various study scenarios: an office, living room, or group discussion settings, for example. An example: a high tech laboratory At the Tech3Lab at HEC Montréal, Prof. Pierre-Majorique Léger and his co-workers study what users really experience when they interact with technology, like mobile phones or tablets. They use neuroscience tools to provide when and where modifications are needed in a user design, in order to make it more optimal. Watch the video to discover more details. Setting up a well-equipped lab Interested in setting up an observation or usability lab for answering your research questions? Please visit our website to read more about the many different possibilities Noldus provides. Take a tour through the labs of some of our customers: you can see how we helped design spaces for our clients, what equipment they chose, and which software tools are used for data collection and analysis, such as The Observer XT and FaceReader. --- ## Creating a custom expression for engagement: a validation study with FaceReader URL: https://noldus.com/blog/custom-expression-engagement-validation-study Published: 2021-01-18 10:57:00 Description: The concept engagement is gaining more and more attention. Many companies are looking for ways to increase consumer engagement. But, how do you know a consumer is feeling engaged? By Dayenne Sarkol-Teulings, graduate student at Applied Cognitive Psychology at the University of Utrecht, The Netherlands.  During my 3-month graduate research internship project for my master Applied Cognitive Psychology at the University of Utrecht, I was asked to create a custom expression for the emotional state engagement. In this blog, I will briefly tell you the highlights of this fun and interesting project. Why engagement? Over the last years, the concept engagement has been of increasing interest within multiple domains: organization behavior, marketing, social psychology, and education [1]. For example marketing is very interested in engaged consumers, especially since research has shown that highly engaged consumers spend 60% more in each transaction, make 90% more frequent purchases, and are four times more likely to advocate for the brand [2]. No wonder companies are extremely interested in finding ways to increase their consumers’ level of engagement. What does an engaged consumer look like? But how do you know a consumer is feeling (highly) engaged? What does an engaged consumer look like? Well, for example, to test if advertisements are increasing one’s level of engagement, you can look at the facial expressions people show while watching the advertisements. We all know that people have a hard time hiding their real feelings. Even back in 1872, Darwin already noticed that there is a strong link between experienced emotions and facial expressions [3]. To measure facial expressions, an automated facial expression analysis tool like FaceReader can be used. Aside from accurately measuring the basic emotions, FaceReader has the option to create custom expressions, where you can design your own algorithm by combining variables such as facial expressions and Action Units (AUs). FREE WHITE PAPER Facial Action Coding System Download here the FREE white paper 'Facial Action Coding System (FACS)' and learn more about: - Objective results with FACS - Action Units - Examples using FACS Submit to download What is engagement? So what exactly is engagement? It’s a broad concept with lots of room for interpretation. A thorough literature review learned that many articles have been addressing the concept engagement, all with fairly overlapping but yet slightly different definitions. What emerges was that engagement can be categorized into three components, namely emotional, cognitive, and behavioral engagement, as you can see below in Figure 1. Figure 1. Hierarchy of engagement according to literature [4, 5, 6, 7, 8, 9].  With the information from literature, I’ve created a definition for engagement: “Engagement seems to be the product of a two-way interaction, initiated by either the individual or the organization. On the one hand, the organization has to attract someone’s attention by presenting themselves as something that is appealing to the individual. They need to hold that attention long enough for a person to provoke a second level of attention, where feelings of involvement, interest, and motivation seem to contribute to this sustained attention. On the other hand arises the individuals’ free will to deliberately connect with the organization on such a level that a person is willing to go beyond the personal requirements associated with the organization.” Now that the definition was made, it was time to gather information to create an algorithm. The expressions of an engaged face What does an ‘Engaged person’ look like? In literature, I found lots of contradictory information. From lots of expression versus no expression at all, to negative and positive correlations of expressions with engagement. I decided to do my own experiment and found out myself what an engaged face looks like. For this purpose, I’ve created an online survey with the use of Qualtrics and FaceReader Online, where the stimuli (movie trailers) were set up in FaceReader Online and later embedded in Qualtrics with JavaScript.  Movie trailers were specifically chosen as stimuli because their duration is typically two to three minutes, which is long enough to evoke sustained attention, yet remains within the limits (0-3 minutes) of losing this sustained attention [10]. Thereby, movie trailers are specially designed to attract and maintain someone’s attention [11]. These movies were not out in theatres yet, so no bias could influence the experience. People were invited to participate in a Qualtrics survey, and were recorded with their own webcam while looking at movie trailers, after which they were asked to rate their overall feelings of engagement per movie trailer. The recordings were exported to FaceReader for extensive analyses, and the survey answers could be exported from Qualtrics to Excel and SPSS. Amazing how well all programs worked together! FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download To analyze the results, I used the self-reported scores of level of overall engagement to create two groups: High Engaged people (scoring 70 and higher) and Low Engaged people (scoring 30 and lower). I analyzed both groups in FaceReader 8.1, and calculated the mean activation of expressions and AUs per participant in Excel. With the AUs, only the intensity of AU 4 (Brow Lowerer) was slightly higher with Low Engaged people. As you can see in de bar chart below (Figure 2), the difference between the expressions of High and Low Engaged people was also very small. It is interesting to see that High Engaged people score higher on Neutral, which was quite unexpected. Figure 2. A bar chart visualizing and comparing the mean results of all the participants on the seven expressions (basic emotions), two custom expressions (boredom and interest) and valence & arousal. Validation study So unfortunately, my experiment did not help me much with creating an algorithm. Therefore, I decided to create not just one but two custom expressions, based on both the information from literature and the results from my first experiment.  The condition was set that there can be no engagement with a high boredom score. With a low boredom score, the Valence score is taken. Valence is chosen because a Valence score of 0 is equal to a high Neutral score, exactly the main results from my first experiment. With one custom expression, I subtracted AU 4 from the Valence score, since my first experiment showed that AU 4 was slightly higher with Low Engaged people. To test these custom expressions, I have set up a second online experiment, again with Qualtrics and FaceReader Online. This time I used advertisements for people to look at, so I could record their expressions. Afterwards, they were asked to rate their overall feelings of engagement, so I could compare the activation score of the custom expressions with the self-reported engagement scores. Unfortunately, there was no significant effect, meaning that the custom expressions could not be validated. Despite this disappointing result, some interesting findings need to be mentioned when looking at an individual level. Figure 3 shows that the custom expressions of some participants are on the right track. This can be used as a starting point for follow-up research. Figure 3. Scores of participants 23 Recommendations First and foremost, I would highly recommend to look at engagement as an affective state which is prolonged in nature, and should be measured as an overall score, rather than an expression being measured and estimated per frame, such as basic expressions like happy or angry. Also, for follow-up research it might be interesting to measure engagement in groups or pairs, especially if you keep in mind that the expression of emotions is a form of communication. When looking at stimuli as a couple, you might show more expression. Lastly, due to COVID-19, I had to execute all experiments online. The advantage was that I could reach more participants, since they could participate from home. In this way the COVID-19 regulations could be respected.  Yet the disadvantage was that, when using the participants’ webcam instead of the Noldus lab camera, several analyses like heart rate and head orientation could not be used, and we had less control over the quality of the recordings compared to a lab study. Using the Noldus Experience Lab for follow-up research might gain some interesting findings! Despite the fact that the custom expressions for engagement could not yet be validated, this research showed insights in the concept of engagement. When keeping the recommendations in mind, follow-up research is highly recommended. Interested in using FaceReader for follow-up research? Contact Noldus for more information! If you are interested in continuing this validation study with use of FaceReader data, please contact Niek Wilmink for more information.  References - Alvarez-Milán, A., Felix, R., Rauschnabel, P. A., & Hinsch, C. (2018). Strategic customer engagement marketing: A decision making framework. Journal of Business Research, 92, 61-70. https://doi.org/10.1016/j.jbusres.2018.07.017 - Rosetta Consulting (2014). The economics of engagement (pp. 1–9). Retrieved from http://www.rosetta.com/assets/pdf/The-Economics-of-Engagement.pdf. - Wallbott, H. G. (1998). Bodily expression of emotion. European journal of social psychology, 28(6), 879-896. - Christenson, S. L., Reschly, A. L., & Wylie, C. (Eds.). (2012). Handbook of research on student engagement. Springer Science & Business Media - Trowler, V. (2010). Student engagement literature review. The higher education academy, 11(1), 1-15. - Harmeling, C. M., Moffett, J. W., Arnold, M. J., & Carlson, B. D. (2017). Toward a theory of customer engagement marketing. Journal of the Academy of marketing science, 45(3), 312-335. - Brodie, R. J., Hollebeek, L. D., Jurić, B., & Ilić, A. (2011). Customer engagement: Conceptual domain, fundamental propositions, and implications for research. Journal of service research, 14(3), 252-271. https://doi.org/10.1177/1094670511411703  - Hollebeek, L. D., Jurić, B., & Ilić, A. (2011). Customer engagement: Conceptual domain, fundamental propositions, and implications for research. Journal of service research, 14(3), 252-271. - O’Brien, H., & Cairns, P. (2015). An empirical evaluation of the User Engagement Scale (UES) in online news environments. Information Processing & Management, 51(4), 413-427. https://doi.org/10.1016/j.ipm.2015.03.003 - Guo, P. J., Kim, J., & Rubin, R. (2014). How video production affects student engagement: An empirical study of MOOC videos. In Proceedings of the first ACM conference on Learning@ scale conference,  41-50. https://doi.org/10.1145/2556325.2566239 - Wang, L., Liu, D., Puri, R., & Metaxas, D. N. (2020). Learning trailer moments in full-length movies with co-contrastive attention. arXiv preprint arXiv:2008.08502. --- ## Getting robust results: one zebrafish is not like the other URL: https://noldus.com/blog/robust-results-intra-individual-locomotor-patterns-zebrafish-larvae Published: 2021-01-15 13:00:00 Description: Zebrafish larvae locomotor behavior often has a high variability, which can have a big impact on your results. Still, it is one of the most used parameters. So how can you make your study more robust? Today, let’s talk about zebrafish. You know, one is definitely not like the other and that can have a big impact on your study. Especially if you are performing a high-throughput study. So, what does that mean, and how can you prevent variability? Zebrafish locomotion as an important indicator We can safely say that the zebrafish is an excellent model for a wide range of human psychiatric diseases, but also in toxicology and drug discovery studies. Larval locomotor behavior, the most popular and seemingly straight-forward behavioral endpoint, is used as an indicator for nervous system development and functioning. Not the same fish Thousands of studies focus on the activity and swim patterns of larvae, mostly in multi-well plates for high-throughput. A major challenge, like in many fields of research, is that results can vary. Literature shows that there is a high rate of variability between individuals, and while this is normal for natural populations, it can be problematic when interpreting the results of a study. For this reason, the Swiss Federal Institute of Aquatic Science and Technology wanted a better understanding of the variability and predictability of larval locomotor behavior. Dr. Fitzgerald, postdoc at the Department of Environmental Toxicology, recently published a paper on it in Scientific Reports. Intra- and inter-individual variability This variability within groups of zebrafish might lead to irreproducible results. If there is a large difference in locomotion within a group, then the differences between treatment groups might be obscured. An otherwise nicely standardized protocol might seem not so robust anymore… Testing at an individual level Fitzgerald and her colleagues pose an interesting point: if certain aspects of zebrafish larva locomotion show consistency within the individual, then testing on an individual level, before and after treatment, might create a more robust experiment than comparing treatment groups. Zebrafish larvae activity In their study, they tested 132 wild-type zebrafish larvae in multi-well plates in a DanioVision system. Over the course of 3 days, animals were tested in the morning and afternoon at ages 5, 6, and 7 days post fertilization (dpf). A regimen with light and dark conditions tested for spontaneous swimming behavior, swimming in darkness, and swimming in light right after a period of darkness, as measured with EthoVision XT. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your zebrafish research! Learn more Consistent locomotion in the dark It turns out that swimming activity stays pretty consistent within an individual, variability was especially low during the dark phase. Fish were more active in the dark, and it seems that the more they move, the less variable activity is.  The consistency seems highest between ages 6 and 7 dpf. This seems to be a developmental effect as starting testing at an earlier age did not change the outcome. Though in general larval activity differed between the morning and the afternoon, individuals moved consistently: animals that moved more in the morning also moved more in the afternoon. Startle responses While general locomotion seemed a very consistent factor, startle response was not so predictable. In addition to the immediate effect of light conditions changing, two other startle responses were measured: in response to a dark flash and in response to tapping from the Tapping Device built-into DanioVision. All stimuli evoked an increase in activity, but looking at the activity index (percentage of moving) and radial index (location within the well), this response was not predictable or consistent at the individual or population level. Physiological correlations Using MediaRecorder to film the larvae after each afternoon testing session, researchers investigated the resting heart rates and morphological characteristics (body length, swim bladder size) with DanioScope. Locomotor activity did not correlate with any of these parameters, there was also a large inter-individual variety. Measurements did show that individuals grew at a constant pace. Getting more robust results This study gives a deeper insight into the differences between inter- and intra-individual measurements. It shows that locomotor activity of an individual larva remains consistent and is predictable throughout larval development, especially during dark phases. Studies that can make use of this consistency by testing on an individual level, might benefit from an improved sensitivity of their assay using locomotor activity as an endpoint. For the future Especially given the scrutiny scientific research is under lately, because of irreproducible results and non-comparable findings (also see my previous blog post on standardization in behavioral cores), these types of studies are a valuable contribution to making science better. References If you are interested in zebrafish larvae studies using locomotor behavior as a behavioral endpoint, but also include physiological and morphological measurements, be sure to check out the publication: Fitzgerald, J.A.; Tulasi Kirla, K.; Zinner, C.P.; Berg, C.M., vom (2019). Emergence of consistent intra-individual locomotor patterns during zebrafish development. Scientific Reports 9, 13647. --- ## Emotional responses to winning a paralympic medal URL: https://noldus.com/blog/emotional-responses-winning-medal Published: 2021-01-11 11:00:00 Description: Guest blogger Jeffrey J. Martin conducted a study to examine the emotional reactions of Paralympians right after winning a medal, using automated facial expression analysis. Jeffrey J. Martin, Ph.D. at the Division of Kinesiology, Health, and Sport Studies, at the Wayne State University, in Detroit, Michigan, USA studied the emotional reactions of Paralympians right after winning a medal. It became clear that not all wins and losses are equal and it’s not only the medal color that matters to athletes.  Emotional responses to winning a paralympic medal Sport psychology research examining Paralympic sport is limited and in particular few researchers have examined what Paralympian’s feel after winning a medal [1, 2, 3]. More specifically, researchers examining Olympic and Paralympic athlete’s emotional reactions tend to ignore important criteria (e.g., self-referenced standards such as time) that athletes use to judge performance, and instead, focus on common objective standards like place and medal won.  The current study extends the knowledge base on the psychology of the Paralympics by examining emotional reactions while considering the subtle nuances of competition that are important to athletes in the following ways. First, in addition to emotional reactions to medal won (Gold, Silver and Bronze), I also examined emotional reactions relative to the previous year’s world ranking and best race time. Second, athlete’s emotional reactions were examined depending on if their winning medal performance was a close win or an easy win.  Similarly, the emotions of athletes who lost a medal by a small margin (won bronze and missed silver) were examined relative to those who lost a medal by a much wider margin. Half a second was used to designate if wins and losses were close or not close. Measuring Emotion Many researchers ask human raters to assess research participant’s (e.g., athletes) facial expressions to determine the emotions they are experiencing. However, with the development of FaceReader technology researchers can examine facial expressions automatically to determine emotional content.  In the current study I used Facereader to analyze broadcast footage of 138 swimmers at the 2016 Paralympics as they completed their races and won gold, silver or bronze medals. FREE WHITE PAPER: Download the free FaceReader methodology note to learn more about facial expression analysis theory. Learn more Emotional responses are complex For medal winners, silver medalists were angrier and sadder than gold medalists, and angrier and more disgusted than bronze medalists. These findings offer partial support for the counterfactual thinking hypothesis. For instance, silver medalists may look upward and regret missing out on gold.  In contrast, bronze medalists may look downward and be grateful they were not fourth and missed winning a medal. Swimmers who swam slower than their 2015 world ranking best time were angrier than Paralympians who swam faster. Paralympians who finished lower than their 2015 world ranking had more neutral emotions and were less happy than Paralympians who finished higher.  These findings support the idea that athlete’s emotional responses are complex and are a function of multiple criteria and not simply how well they fare against the competition. Wide-ranging and diverse emotions Gold, silver, and bronze medalists with close wins were more surprised than medalists with easier wins, likely due to the uncertainty of how competitors were performing (e.g., vision obscured by water or competitors being multiple lanes away). Gold medalists who narrowly defeated silver medalists were less happy and more fearful than gold medalists who won easily. Medalists with easy wins may have more time to anticipate the win, which may contribute to greater happiness and less fearfulness. Bronze medalists with close wins had fewer neutral emotions, were happier, less angry, and more surprised than bronze medalists with not close win. Bronze medalists with close losses to silver medalists were happier and less angry than bronze medalists who lost more easily. The differences in emotional intensity were not trivial as effect sizes ranged from d = .27 to 1.01. These results provide theoretical support for basic emotion theory and add to the value of FaceReader for emotion assessment. Furthermore, the results confirm the anecdotal observations that Paralympic competition generates wide ranging and diverse emotions linked to personal performance standards and the type of win or loss.  In conclusion, when it comes to the emotions athlete’s experience in response to how well they perform, it is clear that not all wins and losses are equal and it’s not only the medal color that matters to athletes. LABEL Title Learn more References Source header image: https://pixabay.com/photos/swimmer-competition-competitive-1477650/ - Martin, J. J. (2017). Handbook of Disability Sport and Exercise Psychology. NY: Oxford University Press. - Martin, J. (2012). Coping and Emotion in Disability Sport. In J. Thatcher, M. Jones & D. Lavallee (Eds.), Coping and emotion in sport (pp. 194-212). London, UK: Routledge. - Martin, J., Vassallo, M., Carrico, J., & Armstrong, E. (2019). Predicting Happiness in Paralympic Swimming Medalists. Adapted Physical Activity Quarterly, 36(3), 309-324. --- ## How behavioral core facilities advance research URL: https://noldus.com/blog/core-facilities-advance-behavioral-research Published: 2021-01-06 12:00:00 Description: Behavioral cores benefit universities as well as science in general. Recent cases show improved reproducibility of tests and protocols to assess a more complex phenotype of model animals. Recently we sponsored an Inside Scientific webinar called Lessons From The Core: Longitudinal Assessment vs. Point Sampling of Behaviors in Mice In this webinar Lior Bikovski and Shivang Parikh talked about today’s home cage monitoring technology and how it compares to other standard tools in the field of behavioral research.  If you missed it, be sure to watch it on demand. Managing a behavioral core Prof. Lior Bikovski manages the Myers Neuro-Behavioral Core Facility at the Tel Aviv University. He recently collaborated on a publication in Journal of Neuroscience Methods that highlights the benefits of behavioral cores. It contains a couple of great examples that show how behavioral research advanced in four behavioral cores in Sweden, the UK and Tel Aviv. Are you interested in building your own rodent neurobehavioral core? Download this free guidebook on how to build a rodent neurobehavioral core and learn more about the why, who, what and how. The importance of behavioral cores The more we want to learn about psychiatric diseases and other neurobehavioral disorders, the more complex neurobehavioral studies become. This leads to an increasing demand for more detailed phenotyping of (rodent) models. Reproducibility is a very important aspect here. Promoting standardization As you can imagine, standardizing procedures plays a big role in increasing the reproducibility of neurobehavioral tests. The test protocol, but also the specific way it is executed, staff training, and testing environment in terms of lighting, noise, and even odor, will attribute to data reliability and accuracy. This is where behavioral cores can really make a big impact on science, as knowledge, experience, expertise, and technologies are all present in one facility. LABEL Title Learn more Dealing with confounding factors Of course, there are always confounding factors such as a new mouse strain or a change in the testing environment. Better protocols help. This paper lists a couple of examples on how these behavioral cores have provided. Pre-calibration Let’s start with pre-calibrated experimental protocols. The authors explain how this helps to verify that control animals exhibit the desired behavior, and to optimize the behavioral output so that significant differences in control and model animal behavior can be accurately measured. This is illustrated with open field tests. The open field test The open field test relies on the opposing behaviors provoked by different degrees of illumination. Simply replicating light settings from another publication often does not result in the same behavioral phenotype. Pre-calibrating the light intensity may seem like a lot of work, but it can save valuable time in the end. At the Myers Neuro-Behavioral Core Facility they investigated the ability of a certain compound to elicit increased motor behavior. However, when copying a previously published protocol, it seemed that the environmental conditions increased exploration in the control mice, potentially overshadowing the effect of the compound. By pre-calibrating the experiment, they found a protocol that improved the ability to detect an increase in explorative behavior in response to the compound. Using EthoVision XT, a significant difference in distance moved was detected. FREE TRIAL: Request a free trial and find out what EthoVision XT can do for your research! Learn more Social factors Another example from the Myers Neuro-Behavioral Core Facility concerns the investigation of a genetic manipulation to elicit a motor defect. During pre-calibration, researchers found that naïve mice only explored the open field arena at moderate levels, potentially overcasting the genetically induced effect. The test was performed in parallel with four mice in four arenas. While initially saving time this way, it confounded the experiment with social stress. When testing a single mouse at a time, substantial exploration was recorded. This proved to be a more suitable protocol so further testing was done and significant differences between naïve and genetically modified mice were found with use of EthoVision XT. LABEL Title Learn more New testing arenas At the Uppsala University Behavioral Facility in Sweden they wanted to find a way to better understand psychiatric disorders. Standard test protocols generally focus on one isolated behavior, and fail to assess the behavioral complexity of the disease model. The multivariate concentric square field (MCSF) offers an opportunity to measure a more complete behavioral phenotype in a complex test arena. The researcher from this Swedish facility developed this arena for rats, mice, and even zebrafish. Multivariate testing The MCSF arena has explorative incentives, areas associated with shelter, and different kinds of risk in open and illuminated areas. It has now been used and validated for the behavioral profiling of rats. This protocol shows robustness. A study done on this rat strain in Sweden was repeated in US years later, and results were remarkably well replicated. The MCSF also shows great promise for zebrafish studies during initial experiments in Sweden. Video tracking complex behavioral phenotypes The MCSF was designed for use with video tracking such as EthoVision XT. The authors nicely visualize their data in tracks and heatmaps to show behaviors such as risk assessing and risk taking, exploration, and shelter seeking. Better behavioral phenotyping If you are interested in better behavioral phenotyping, or the advantages and considerations associated with a behavioral core, this paper is a great read! For more information on video tracking options, please check out EthoVision XT. References Bikovski, L.; Robinson, L.; Konradsson-Geuken, A.; Kullander, K.; Viereckel, T.; Winberg, S.; Roman, E.; Tsoory, M. (2020). Lessons, insights and newly developed tools emerging from behavioral phenotyping core facilities. Journal of Neuroscience Methods, 334, 108597. The Myers Neuro-Behavioral Core Facility Uppsala University Behavioral Facility --- ## Why a clear mask is essential for clearer communication URL: https://noldus.com/blog/clear-masks-essential-for-clearer-communication Published: 2020-12-15 08:30:00 Description: For people who are deaf or hard of hearing, it is essential to be able to see the movements of the mouth while communicating. With the help of clear masks they can access the full facial expressions. It is very natural to look at someone's face when we have a conversation. Often, we do this without thinking, unconsciously. After all, it is pleasant to look your conversation partner in the eye. Besides, seeing how someone's mouth moves when he or she is talking helps to listen and understand. The COVID-19 pandemic increasingly forced us to wear face masks in all kind of situations, in order to protect ourselves and to prevent spreading the corona virus. For example, when we travel by public transport, when we are in public places, and of course when we provide care to patients. Earlier this year, my colleague Patrick Zimmerman wrote a blog post about face masks and non-verbal communication. He described how wearing a face masks affects communication since we then have to rely on facial signals that are visible, which are the eyes and eyebrows. Barriers to communication For people who are deaf or have hearing impairments, it is essential to be able to see the movements of the mouth. These movements make the facial expressions complete, and lip reading helps understand the conversation. Losing this element in communication can lead to confusion and misunderstanding. In any way, it takes a lot more effort to understand the other. It might even make it impossible. This extra barrier to communication should be prevented as much as possible. Effective communication in doctor-patient interaction This also applies to the interaction between patients and health workers. Efficient and effective communication is necessary in doctor-patient as well as nurse-patient consultations. For example, it is essential that a patient understands the doctor's explanation about a treatment or examination. This enlarges the likelihood of successful progression, it prevents a patient from feeling insecure, and ultimately increases the patient's well-being. Many factors play a role in these interactions. For the deaf and hard of hearing, but also, for example, for people with dementia or learning disabilities, this includes being able to see the movements of the mouth. It creates a human connection and reduces stress. However, with opaque masks covering the faces around us, we are unable to access the facial expressions and lip movements that are so vital to daily communication. Clear masks are essential for clearer communication with people with hearing impairments That is why clear or ‘see-through’ face masks have been designed to support communication with people with e.g. hearing impairments, dementia, or learning abilities. ATiC of the University of Wales Trinity Saint David cooperated with Tyddyn Môn, a non-profit organization working with people that live with learning disabilities, and Dr. Sarah Bent of the Betsi Cadwaladr University Health Board who led the project to study the effectiveness of different clear mask designs. They aimed to understand the benefits of clear masks in preventing barriers to communication between health staff and patients. The full facial expression is essential The collaborative team developed a remote test method to rapid assess fitness for purpose for a number of masks, including clear and full-covering masks, that were tested with 5 representative users from their homes. Using the site license for FaceReader allowed them to assess the performance of these products, even during lockdown, with a study protocol that focused on analyzing users’ emotional responses and usability of the masks. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download In terms of emotional response and facial expression analysis, the researchers repeated a few exercises with the representative users whilst wearing the different masks so they could establish a base line for the comparative analysis between the final results obtained for all study participants and masks. Overall, those masks with clear sections demonstrated consistency in both usability and facial expression analysis against the full-covering ones, showing a clear need for clear mask options to be available for ease of communication between clinicians, patients, and the community. Their aim was also to inform the future production of clear view face coverings. In conclusion, it can be said that clear masks help communicate better as they remove communication barriers. Even if someone is wearing a mask, you can still see them smiling. References - https://www.uwtsd.ac.uk/news/press-releases/press-2020/user-centred-innovation-project-to-understand-how-face-masks-affect-communication.html - https://bcuhb.nhs.wales/news/health-board-news/clear-face-masks-to-be-trialled-to-support-people-with-hearing-loss/ - Chodosh, J.; Weinstein, B.E. & Blustein, Jan (2020). Face masks can be devastating for people with hearing loss. BMJ, 370:m2683. https://doi.org/10.1136/bmj.m2683 Thanks to Yolanda Rendón Guerrero, ATiC Innovation Fellow, for providing in-depth information. Photo Courtesy: ATiC --- ## Three ways to understand consumer emotions URL: https://noldus.com/blog/understand-consumer-emotions Published: 2020-12-03 10:00:00 Description: Many companies are seeking ways to understand consumer emotions in order to predict product acceptability. Here are three ways you could set up your study to assess consumer emotions. Many companies are seeking ways to understand consumer emotions in order to predict product acceptability. Here are three ways you could set up your study to assess consumer emotions. Learn more about innovative methodologies for Consumer Behavior Research - Replay our free webinar now! 1. Multi-sensory research In order to understand consumer emotions, you can use a variety of different technologies. In one recent project, a company claimed to have developed shampoo and hair serum (PIVOINE range, KLORANE) that would have superior relaxing effects. However, they wanted (and according to EU law, needed) proof! Understanding consumer emotions Using the Noldus toolkit (which has behavioral metrics along with physiological measurements such as blood pressure, electro-dermal activity, and heart rate) together with the customer, we found out that the relaxing shampoo and serum both had physiological and behavioral effects that pointed to relaxation. The serum had an impact on blood pressure and heart rate, and the shampoo had an impact on EDA and heartbeat intervals. The relaxing shampoo and serum have been on the market since April 2017, with a claim backed up by scientific data. Check out the poster about this study for more information! 2. Automatic facial expression analysis Another way to assess emotions would be to look at the face. Researchers from Mississippi State University and Virginia Tech (USA) explain that the food industry is looking to use implicit measurements to differentiate acceptability of products in the marketplace, and that automated facial expression analysis is a prospective analysis for product acceptability. Validation of facial expression analysis software They invited 65 participants to their study and recorded their facial expressions during the experiment. These videos were analyzed frame-by-frame using FaceReader software batch analysis. In this experiment, bitter drinks (distilled water with caffeine) were used to determine and validate automatic facial expression analysis. The published work shows that a time series analysis is a promising tool for interpreting emotional trends of a population. They explain that time series analysis provided a more holistic picture of the emotional changes and presence over time, and can provide a view of the profile elicited by products. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download The role of sensory evaluation In the video below, Dr. Susan Duncan explains more about another study of hers. In this project the research team aimed to characterize the relationship between emotions, consumer acceptability, and purchase intent towards milk packaging. The facial expression analysis data provided evidence of significant differences in emotion intensity. 3. In-home observations Nestle Research Center in France aimed to understand consumers' satisfaction levels while interacting with a packaged food in their homes. Were they happy with their purchase, and what was the greatest factor in determining their satisfaction? A total of 64 consumers participated in this study. They were willing to buy and try the commercial packaged food chosen in this study. All consumers provided self-recorded videos while interacting with the packaging at home, from the unpacking stage through food preparation. Coding videos Researchers from Nestle worked together with Noldus consultants to code behaviors of interest. The analysis showed that specific behaviors occurring during food unpacking and food preparation impacted overall user satisfaction, but explicit questionnaire assessment did not significantly contribute to explain overall satisfaction. The next step So, in addition to facial expressions and physiological data, video observations can also give you a wealth of information. Eye tracking is also ideal to follow the gaze of a consumer. It allows you to better answer questions like, "What attracts people's attention?" and "What is the most convincing product visualization?" Furthermore, using eye tracking glasses you can also follow consumers in a supermarket or at home to see how they walk through a shop or how they use your product in their own kitchen. By combining different measurement techniques, you can get the best insights into consumer emotions and preference. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial References - Crist, C.A.; Duncan, S.E.; Arnade, E.A.; Leitch, K.A.; O'Keefe, S.F.; Gallagher, D.L. (2018). Automated facial expression analysis for emotional responsivity using an aqueous bitter model. Food Quality and Preference, 68, 349-359. https://doi.org/10.1016/j.foodqual.2018.04.004 - Clark, E.A.; Duncan, S.E.; Hamilton, L.M; Bell, M.A.; Lahne, J.; Gallagher, D.L. & O'Keefe, S.F. (2021). Characterizing consumer emotional response to milk packaging guides packaging material selection. Food Quality and Preference, 87, 103984. https://doi.org/10.1016/j.foodqual.2020.103984 - Labbe, D.; Ferrage, A.; Martin, N. (2014). An implicit behavioral approach to understand user satisfaction while preparing and consuming food at home. In Proceedings of Measuring Behavior 2014, (Wageningen, The Netherlands, August 27-29, 2014). --- ## A new sensory and motor scale for the CIA arthritis mouse model URL: https://noldus.com/blog/arthritis-new-scale Published: 2020-11-24 16:00:00 Description: Dr. Bonnefont and her colleagues at IRMB in France just recently proposed a new ArthriSM scale to predict motor and sensory functional deficits in arthritis mouse model. Read more about it in her blog post! Today we are happy to share with you a guest blog post by Anne-Laure Bonnefont in which she explains how she and her colleagues developed the ArthriSM scale - a new sensory and motor scale to predict functional deficits in arthritis mouse model. Enjoy reading!  LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more RESOURCES: Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more --- ## Video recording used in psychology URL: https://noldus.com/blog/video-recording-used-in-psychology Published: 2020-11-02 13:00:00 Description: Understanding behavior during an interaction becomes much easier with video observations, and enables students to watch and learn. Much of psychology education deals with the challenge of how to effectively teach and evaluate skills professionals need in certain interactions. For example, think about conversational skills psychologists need in interactions such as a parent-child interaction, group discussion, or an individual counseling meeting. In these cases, the feedback given by the expert to the student is of crucial importance. However, having a teacher sit in on the interaction might have an unwanted effect on the situation at hand. What can we do to improve the learning experience of the student and make the process run as smoothly as possible for the teacher? What if I were a teacher? Record interactions on video Understanding behavior during an interaction becomes much easier with video observations. You as a teacher can comment on video images, and the student can watch him/herself over and over again to learn skills he/she needs. The possibility to see exactly what is happening during a training session enables the student to understand and embrace feedback much faster compared to other feedback instruments such as written reports. Video feedback enables students to watch and learn. FREE DEMO Try Viso yourself! Request a free demonstration to find out why Viso is the right tool for your training facility! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback and debriefing Free Demo In addition, you as a teacher can set up interactions that require certain skills. Record the sessions, provide feedback and let the student sharpen his or her competences. What are others already attempting? Learn more about this training facility At Delaware Valley University, a state-of-the-art training facility has been created to train Counseling Psychology students. The faculty at Delaware Valley University has proven their dedication to using Viso software to train new counselors. Skill-based courses are highly interactive and held in the lab, where students role-play, practice, and learn through hands-on experience. Practice sessions can be observed, recorded and reviewed to provide authentic feedback and growth opportunities. The lab is a cornerstone of the program, and consists of a large conference room, six small counseling rooms, and a control room. Video recording used in psychology With the Viso system (the video system that captures information) installed in the Counseling Psychology training facility since early 2014, Delaware Valley University will remain at the forefront of training counselors. The training facility allows students to observe mock counseling sessions through two-way mirrors, and to make video recordings of those sessions. FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Download From a student's point of view, faster learning is motivating Students should critically evaluate which school would really help them learn. I remember choosing a driver school to be able to pass my driving test fast. I saw that on average, 40 lessons would be enough to pass the test. I passed with 24. Why? I chose a school where I would be able to sit in the back seat while watching another student drive. For both of us, this meant that we passed our driving exam faster. I would say I was able to pass the test quickly because I learned from his (sorry Bert) many mistakes. Back to psychology education The experiences you undergo at school empower you to become a better professional in the field. Bring your experience and skills into the real world, and you will feel that you can really make a difference. For example, video and audio recordings made by Viso can be viewed by students including the feedback the teacher gave. You can also be asked to comment on each other and see what you can learn from another student making their own mistakes (remember the driving school experience I told you about). Seeing what happens and providing feedback is almost as valuable as being the psychologist-in-training during the mockup counseling session. Having an index of your own recordings will later allow you to locate particular events in your rapidly growing portfolio of recordings, and will help you learn in the most efficient way. You can also ask a teacher to review an old recording to get his/her feedback on a particular interaction. Viso is an available system that can help you find recordings quickly by date, teacher name, or session name. Psychology education Since many faculties for psychology have multiple classes of students wanting to learn skills at the same time, a system such as Viso can be set up as a multi-room video recording system. That means that teachers do not have to wait on each other to be able to schedule sessions. You can schedule training sessions in two rooms at a time. For example, students can practice conversation skills in one room, while counseling psychology students practice an intake interview in another room. No matter what kind of facility, large or small, video systems can be implemented with one to four cameras per room in order to best facilitate learning. Watching yourself or your fellow students make mistakes enables you to learn. RESOURCES Read more about Viso Find out how Viso is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## Exploring learning experiences of undergraduate nursing students URL: https://noldus.com/blog/learning-experiences-nursing-students Published: 2020-10-27 10:48:00 Description: Simulation-based training sessions are essential in healthcare education. How do nursing students experience the use of a virtual interactive digital simulator compared to a human patient simulation? Years ago, when I was trained as a nurse, my fellow students and me were regularly found in an exercise room, standing next to a hospital bed with a plain manikin, or just one of us, in it. We practiced all kind of technical skills, such as measuring vital functions and lifting techniques. I experienced this as a pleasant way to learn skills and to gain confidence in my own abilities. Gaining confidence is an important goal of simulation-based training and an essential part of education. Fortunately, many improvements have been made to these simulation-training courses in the meantime. For example, virtual reality is now being implemented. In my time this didn’t even exist… such a pity! FREE WHITE PAPER Video feedback in skills education 10 Reasons why video feedback is essential in skills education. - Benefits for students - Advantages for teachers and trainers - Practical examples Get your copy instantly Performing simulation-based training in healthcare Healthcare simulations aim to educate students and professionals, are used to assess performance or to practice with new tools or methods, and help to study, for example, teamwork and communication. Simulations may also add to our understanding of human behavior in the true–to–life settings in which professionals operate. An advantage of simulation-based trainings is that it allows students and professionals to learn in an environment that permits errors, and that they do not put actual patients at risk. The highest goal for every healthcare worker is to improve patient safety. Simulation-based training can achieve that. In a previous blog post, you can find five reasons why simulation training in healthcare works! What is human patient simulation (HPS)? In healthcare education and in nursing programs in particular, there has been an increasing use of human patient simulation (HPS). A HPS is a life-like, anatomically correct, computer driven manikin with physiologic responses that mimic real patients. Using HPS can assist in reducing the gaps between theory and practice by improving critical thinking, decision-making, and patient outcomes. However, the costs of using HPS are significant and can be a barrier for institutions. The HPS simulation program requires someone to facilitate the briefing, scenario, and debriefing; a technologist to manage manikins and recording equipment; and a high-fidelity simulation suite, along with the costs of manikins and supplies. Is there another way to increase quality simulation time for students in a cost-effective manner? Interactive digital simulator (IDS) as an alternative Perhaps a virtual interactive digital simulator (IDS) is the solution. Instead of learning on a manikin, students work with the image of a patient that appears on an interactive, computerized, touch-table patient simulator. After choosing from a set of scenarios, such as patients with respiratory distress, and setting the duration, students can carry out their assessment or treatment plan and reevaluate their decisions. The research team of Lorraine Betts at the George Brown College Centre for Health Sciences in Toronto, Canada, decided to evaluate both the HPS and the IDS learning experience with Year 2 practical nursing students. Both groups were given an asthmatic patient scenario. This scenario design expected the students to follow the nursing process, aligned with all four stages and learning styles of Kolb’s theory of experiential learning (experience, reflect, conceptualize, and test). Record and analyze behavior Various components were measured: - Satisfaction and self-confidence using the Satisfaction and Self-Confidence in Learning Questionnaire (National League for Nursing, 2005) - Competency using the Asthma Scenario Performance Checklist (ASPC), a tool developed by George Brown College which is based on established protocols - Behavioral research using the audio/video recording software Viso - Completion rates for the 26 priority actions identified on the ASPC, such as assessing lung sounds and vital signs, using the analysis software tool The Observer XT Results showed that the mean satisfaction score for the IDS group was 16.2/20 (81.4 percent) compared to 18.6/20 (93.1 percent) for the HPS students. The mean self-confidence score for the IDS group was 26.5/35 (75.9 percent) compared to 29.3/35 (84.6 percent) for HPS. On the other hand, IDS students completed 58.3 percent of the top priority action items and students in the HPS group completed 43.9 percent. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo Keep exploring systems to improve learning opportunities The explanation given by the researchers for the higher satisfaction and self-confidence scores in the group that used HPS is that they are more familiar with this type of education, whereas IDS was completely new to them. The reason that IDS resulted in a higher performance of priority actions was most likely because it is easier to take action using IDS than with the HPS. With IDS, it is just as simple as pressing a button. The researchers conclude that both IDS and HPS offer important although different types of simulation learning opportunities. Therefore, the need for exploring systems such as IDS that support student learning through simulation within the budget constraints of educational institutions remains very important. Debriefing the interventions It was also noted that nursing students need to be able to evaluate their interventions. These two systems can contribute to this since the systems respond to the questions and actions of the students, but also the debriefing function of Viso is very suitable for this. While playing back the audio/video recordings of the simulations during debriefing, students can see what actually happened, discuss the annotated moments, and consequently gain deeper insight. References Betts, L; Schmid, J.; Sivaramalingam, S. & Verkuyl, M. (2020). Using Virtual Interactive Digital Simulator to Enhance Simulation Experiences for Undergraduate Nursing Students. Nursing Education Perspectives, 41(3), 193-194. doi: 10.1097/01.NEP.0000000000000472 Kolb, D. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall. https://www.simplypsychology.org/learning-kolb.html https://www.ssih.org/About-SSH/About-Simulation https://escholarship.umassmed.edu/gsn_diss/15/ RESOURCES: Read more about Viso Find out how Viso is used in a wide range of industries and how it can elevate your project. - Free white papers - Customer success stories - Featured blog posts Resources arrow_forward --- ## Studying spatial learning and memory with Cincinnati Water Maze URL: https://noldus.com/blog/cincinnati-water-maze Published: 2020-10-23 16:00:00 Description: Studying spatial learning and memory is important to develop treatment for Alzheimer's and other diseases influencing on orientation and navigation. One way to study it is with Cincinnati Water Maze. Spatial learning and memory plays an important part in our everyday lives. Orientation in space, finding a path to our desired destination, and remembering where different objects or buildings are located, seems natural to most of us. Unfortunately, some diseases like Alzheimer’s, Cushing’s, or epilepsy make spatial orientation and navigation a lot more difficult. Research on spatial learning and understanding specific brain areas involved in spatial memory is therefore important in order to develop new treatments for these types of diseases. Brain regions responsible for memory The brain is a complex and dynamic network. Even though there is no brain region responsible for only one specific function, the hippocampus appears to play a crucial role in spatial memory. With its connections to the medial temporal lobe, and links to the retrosplenial cortex and parietal cortex, it allows an organism to navigate and orientate in its environment. The importance of the hippocampus Interestingly, people that need an outstanding spatial navigation in their daily lives, for example taxi drivers, have bigger hippocampus and more connections to other parts of the brain. On the other hand, atrophy in the hippocampus leads to impairments in navigation and spatial orientation. We can for example clearly see this as an early sign in patients with Alzheimer disease. Through manipulation, such as lesions, optogenetics and electrophysiological studies, researchers discovered that the hippocampus plays an equally important role in spatial memory of animals. Because of this, research on animals can help us find new treatments for diseases, such as Alzheimer’s. Studies of spatial learning and memory on animals Many researchers use a water maze in their studies of spatial learning and memory in reaction to genetic modification or treatment. Rodents require very little training in water mazes as they learn very quickly that they can escape the water if they search for a hidden platform underneath the water surface. Water works as a motivator to escape by itself, meaning there is no need for additional reward or reinforcement. With help of a video tracking tool (such as EthoVision XT), it is possible to measure many parameters like the amount of time the animal needs to reach the platform, distance moved, latency etc. Different water mazes Depending on their study, researchers use different kind of water mazes. The most commonly known is a Morris Water Maze where researchers place a rodent in a large circular pool. In this test, subject is required to find an invisible platform from different start locations. A second commonly used maze is Cincinnati Water Maze (9 unit multiple T maze), which we consider as a modified version of the Biel Water Maze (6 unit multiple T maze). Before the start of the first trial, animals are tested for their swimming ability and trained to find the platform under the water surface in a straight water channel. Afterwards, the real test starts and rodents have to find their way to the end of the maze by allocating the open sides of each T. Every time they navigate to the dead-end or return back to the start arm after leaving it, researchers count this as an error. Another maze some researchers use is Radial-arm Water Maze where they use negative reinforcement. Morris Water Maze vs Cincinnati Water Maze When comparing the two most commonly used water mazes, we can find three major differences between them: Conclusion Further research on spatial memory and learning is important in order to search for effective treatments for different diseases such as Alzheimer's and Cushing's. Since the water works as a motivator for rodents, researchers often use a water maze for these kind of research. Depending on the research question, scientists can choose between different types of water mazes. For testing egocentric navigation, learning, and memory on different drugs and lesions in animal disease models, the most suitable choice could be a Cincinnati Water Maze.  References Arias, N., Mendez, M. and Arias, J. L. (2014). Brain network underlying navigation in the Cincinnati water maze with external and internal cues. Neuroscience Letters, 576, 68-72. Braun, A. A., Amos-Kroohs, R. M., Gutierrez, A., Lundgren, K. H., Seroogy, K. B., Skelton, M. R., Vorhees, C. V. and Williams, M. T. (2015). Dopamine depletion in either the dorsomedial or dorsolateral striatum impairs egocentric Cincinnati water maze performance while sparing allocentric Morris water maze learning. Neurobiol Learn Mem, 118, 55-63. Grech, A. M., Nakamura, J. P. and Hill, R. A. (2018). The Importance of Distinguishing Allocentric and Egocentric Search Strategies in Rodent Hippocampal-Dependent Spatial Memory Paradigms: Getting More Out of Your Data.  Vorhees, C. V. and Williams, M. T. (2016). Cincinnati water maze: A review of the development, methods, and evidence as a test of egocentric learning and memory. Neurotoxicology and Teratology, 57, 1-19. Vorhees, C. V. and Williams, M. T. (2014). Value of water mazes for assessing spatial and egocentric learning and memory in rodent basic research and regulatory studies. Neurotoxicology and Teratology, 45, 75-90. Try EthoVision XT yourself The gold standard in video tracking for behavioral research. Request a free trial. Start free trialarrow_forward --- ## What can you use eye tracking for? URL: https://noldus.com/blog/what-can-you-use-eye-tracking-for Published: 2020-10-20 10:00:00 Description: Eye tracking is a technique which records what you are looking at. With more complex analysis, it can give all sorts of information about a subject's mental state. Eye tracking is a technique which records what you are looking at. At its simplest, it records if someone looked at a given object or not. With more complex analysis, it can give all sorts of information about a subject's mental state and the tasks they are carrying out. When you are reading a page of text, you don't see all the words in focus at once, just the one you are reading at that moment. As your eye skips from word to word, your brain builds up a picture of the total scene and as soon as we pay attention to particular area, it springs into sharp focus. That area of focus corresponds to a small point on the retina of your eye called the fovea (about 2° of vision), and eye-tracking equipment uses that to determine what you are looking at. Where we stop and pay attention to a word, that is called a fixation and where we skip, that is a saccade. During a saccade, no visual information is transmitted to the brain. Fixations and saccades don't just occur during reading, they happen all the time. Two sorts of eye trackers There are essentially two sorts of eye trackers; head-mounted and remote. Remote eye trackers are often mounted under a computer monitor so that the system can work out where you are looking on the screen (when combined with screen capture) but they can also be in the form of a number of cameras placed in the scene. Multiple eye tracking cameras are normally used when the researcher is interested in 3D situations such as someone sitting in a car simulator. These days, head-mounted eye trackers are often in the form of eye tracking glasses. In that case, instead of the scene that the subjects are looking at being fixed in relation to the camera, it is moving around. So eye tracking glasses record a video of the scene in front of the glasses and combine that with the point of gaze of the subjects. New techniques In order to know what it is that the subjects are looking at, the researchers normally have to manually label the video, which is a lot of work seeing there is a new image 25 or 30 times a second. However, new techniques are being developed which use computer vision and machine learning to automate that. There is also a third technique which uses electrodes attached to the skin next to the eye (electrooculogram, EOG). As it is more invasive, it is used less often these days. The advantage is that it can measure eye movements when the eyelids are closed, for example to detect the REM phase of sleep. FREE WHITE PAPER Eye tracking & FaceReader Download this white paper to learn about: - Subconscious processes and emotion recognition - Combining FaceReader™ and eye tracking - Visualizing and analyzing your data Submit to download What can you use eye tracking for? Reading Eye tracking has been used a lot to investigate reading. If someone lingers on a word that they are reading, most likely they are having to think about it more. That can be used to puzzle out the answer to all sorts of questions. For example, in studies of bilingualism, researchers want to know if the vocabularies of the two languages are stored separately in the brain. Normally bilinguals read the less dominant second language slightly slower. However, for cognates (words that are similar in both languages), that is less so - proving that there is a 'cross lingual overlap'. [1]. Dyslexia Dyslexia can be hard to diagnose using traditional methods, with accuracies typically of 70-80%, increasing to 90% with repeated tests. The traditional tests are also better at excluding non-dyslexic children than they are in correctly identifying dyslexic readers. If eye tracking is used, this can be increased to 95% after a single quick test [2]. The exact features used are complex, but in general children with dyslexia fixate longer on individual words and the saccades are shorter, which indicates that greater mental effort is needed to decode the individual words. Human factors research Eye tracking is also used a lot in human factors studies. That is the study of the interaction of people driving cars, piloting planes and so on. Cognitive psychologists working in that area are often interested in the mental workload of operators of vehicles and other machinery. If the tasks is too demanding then mistakes can be made, possibly leading to accidents. But also if it is too easy, then the work is boring and that can also lead to errors. In those studies, researchers don't look only at the fixations and saccades, but more at other data that the eye trackers acquire. For example, there is a lot of evidence that the higher the mental workload, the higher the blink rate [3] and the greater the speed with which the pupil diameter changes [3]. Dwell time is closely rated to fixation duration in that it measures how long someone looks at a particular relevant area (not just one point) such as an instrument dial. As you would expect, the high the mental workload, the longer someone needs to look at an instrument to extract the necessary information from it. The pattern of looking at different instruments (and at other things, like out the window) also changes, becoming less random with increasing workload (this is called visual entropy) [4]. Visual tunnelling is also a well-known phenomenon - under conditions of high mental workload, the attention narrows. For example if you are driving and make a phone call, even when hands-free, you give less attention to what is happening on the road [5]. Another parameter that some eye trackers can measure is how much the eye lid is closed. Unsurprisingly, the percentage of time that the eye lid is 80% closed can be used as an indicator of fatigue [3]. This sort of application has potential for use in actual cars to detect driver drowsiness as well as just in research. Design Where a driver or operator looks is also revealing to designers of cars, cockpits and so on. For instance, if you ask if they have looked at a particular indicator dial then you get an unreliable answer because a lot of monitoring actions are carried out automatically without our consciousness being aware of them (and asking also interrupts the task), but eye tracking will give more reliable data [6]. The actual scan path of an operator can be compared to what the designer had in mind which will (hopefully) be the same as how the operator was trained [7]. It is not only in designing complex cockpits and similar setups that eye tracking is used. It is also used in designing all sorts of other products from websites to advertising and computer games and understanding how consumers use those and experience products (neuromarketing). For example, a recent study [8] used eye tracking as well as other techniques to help understand why Facebook can be so engaging. Designers typically use heat maps visualising how much time subjects have looked at various elements in order to work out how much attention they get. That will frequently be in done by comparing two different designs, for example placing banners differently on a web page. Designing the layout of supermarket shelves can be improved with the same technique. Read more: Shopping behavior - what can we measure in a retail environment? Communication Another important field of study which uses eye tracking, is that of human communication. When you are talking to someone, it is natural to look them in the eye. However, if that is more frequent than normal, it can come across as intimidating and if less frequent it can be an indication of autism (ASD). It is not just the frequency, but also the synchrony that is indicative. If someone looks at you, it is normal to look back. Unlike the measures used in human factors studies, the way we make eye contact during communication is very heavily influenced by our culture and varies across different societies [9]. Noldus has developed prototype software which even makes those measurements possible using normal cameras [10]. Eye trackers can also be used to enable communication with patients who cannot speak. The patient looks at a special keyboard and the computer then uses text-to-speech software to enable them to talk. Read more: 3 Examples of eye tracking lab set-ups Other species Eye tracking isn't just used on humans. The systems have been adapted for use on a whole variety of different animal species including mice, fish, cats and dogs. For instance, cats show a higher precision in their eye stabilization eye movements when looking at a natural scene than at 'drifting gratings' whereas humans show a similar precision for both [11], which is probably related to the cats' hunting abilities. What eye tracking doesn't do It is also important to remember that eye tracking, like all measurement techniques, has its limitations. It measures where the eye focusses, but says nothing about peripheral vision. In a lot of tasks like driving, we make use of a glimpse of something moving at the edge of our field of vision and don't need to focus on the object to know to avoid driving into it. For example, a study showed that if pilots were presented airspeed information only in their peripheral vision, they did make use of it [12]. That also has implications for other studies like design. Just because the person using your website didn't focus directly on the logo doesn't mean to say that they didn't notice it. Some of the eye tracking measures are also influenced by other factors. Most obviously, pupil diameter (and to a lesser extent blink rate) are changed by changing light levels. That's fine in a situation where that is all under control like a driving simulator, but out in a real car the lighting changes all the time. Stress levels can also interfere with the parameters used to measure mental workload, making it difficult to distinguish the two. New techniques in eye tracking Eye tracking is a technique which has been around for over 100 years, but it is still developing. The hardware is getting better (more compact, cheaper, easier to use). Eye tracking data can be combined with other data, such as the subjects' emotions to give deeper insights, or EEG to see if a subject is just looking at something or if they cognitively process the visual information [13]. Noldus is participating in some research projects to innovate in this area. Soon it will be possible to carry out basic eye tracking with a normal webcam. The measurement of mental states like fatigue and mental workload will also be better in the future. Noldus is also able to offer expert advice to its customers to provide them with the best eye tracking solution for their needs. RESEARCH PROJECT Want to partner with us? If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 35+ years of experience Learn more References 1. Van Assche, E., Drieghe, D., Duyck, W., Welvaert, M. and Hartsuiker, R.J., 2011. The influence of semantic constraints on bilingual word recognition during sentence reading. Journal of Memory and Language, 64(1), pp.88-107. 2. Nilsson BenfattoM, Öqvist Seimyr G, Ygge J, Pansell T, Rydberg A, Jacobson C (2016). Screening for Dyslexia Using Eye Tracking during Reading. PLoS ONE 11(12):e0165508. doi:10.1371/journal.pone.0165508 3. Gerhard Marquart, Christopher Cabrall, Joost de Winter (2015) Review of Eye-related Measures of Drivers' Mental Workload. Procedia Manufacturing 3. DO - 10.1016/j.promfg.2015.07.783 4. Tole, J.R., Stephens, A.T., Vivaudou, M., Harris Jr, R.L. and Ephrath, A.R. (1982). Entropy, instrument scan and pilot workload. NASA. 5. Strayer DL, Drews FA, Johnston WA. Cell phone-induced failures of visual attention during simulated driving. J Exp Psychol Appl 2003; 9(1):23-32. 6. J. C. F. de Winter · Y. B. Eisma · C. D. D. Cabrall · P. A. Hancock · N. A. Stanton, (2019). Situation awareness based on eye movements in relation to the task environment. Journal of Cognition, Technology and Work 99: 1-11. DOI: 10.1007/s10111-018-0527-6 7. Eye tracking metrics for workload estimation in flight deck operations. Kyle Kent Edward Ellis 2009 MSc thesis University of Iowa. 8. Maurizio Mauri, Pietro Cipresso, Anna Balgera, Marco Villamira, and Giuseppe Riva. Cyberpsychology, Behavior, and Social Networking. Dec 2011. 723-731.http://doi.org/10.1089/cyber.2010.0377 9. Blais C, Jack RE, Scheepers C, Fiset D, Caldara R (2008) Culture Shapes How We Look at Faces. PLoS ONE 3(8): e3022. https://doi.org/10.1371/journal.pone.0003022 10. Palmero, C., van Dam, E.A., Escalera, S., Kelia, M., Lichtert, G.F., Noldus, L.P., Spink, A.J. and van Wieringen, A., 2018. Automatic mutual gaze detection in face-to-face dyadic interaction videos. In Proceedings of Measuring Behavior 2018 Pp 158-163. measuringbehavior.org. 11. Moeller, G.U., Kayser, C., Knecht, F. et al. Interactions between eye movement systems in cats and humans. Exp Brain Res 157, 215–224 (2004). https://doi.org/10.1007/s00221-004-1835-z 12. Schaudt WA, Caufield KJ, Dyre BP. Effects of a Virtual Air Speed Error Indicator on Guidance Accuracy and Eye Movement Control during Simulated Flight. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 2002;46(17):1594-1598. doi:10.1177/154193120204601714 13. A.-M. Brouwer, I. Stuldreher, S. Huertas Penen, K. Lingelbach and M. Vukelić (2020). Combining eye tracking and physiology for detection of emotion and workload. In: Spink, Andrew, Barski Jarosław, Brower, Anne-Marie, Riedel Gernot, Sil Annesha (2020). Volume 1 of the Proceedings of the 12th International Conference on Measuring Behavior to be held in Krakow, Poland, October 15-18 2021. Pages 2-11. measuringbehavior.org. doi:10.6084/m9.figshare.13013717 --- ## The relationship between social hierarchy and social stress URL: https://noldus.com/blog/relationship-between-social-hierarchy-social-stress Published: 2020-10-14 16:30:00 Description: Today, Deepika Patel kindly shares her research on social structures with us. She investigated rat behavior in detail, using several test paradigms. Today, Deepika Patel kindly shares her research on social structures with us. During her PhD at GELIFES (University of Groningen), she investigated rat behavior in detail, using several test paradigms. Congratulations with your thesis, Deepika! A key feature of group living is the establishment of dominance relationships in competition for resources. The competition for a high rank is often accompanied with social conflicts due to a natural result of interactions between individuals, which can be a source of chronic stress leading to stress-related psychopathologies. Social structures Animals live together in groups with a hierarchical structure installed with dominant, subdominant and subordinate males. According to various studies this can induce chronic social stress of subordination [1]. The social dominance structure in humans is more complicated compared to the animal kingdom. Looking at the socioeconomic status (SES) however, the stepwise descent predicts increased risks of cardiovascular diseases, strokes and psychiatric diseases [2,3]. Dominance studies in animal models Measuring the true consequences of a dominance ranking in humans is rather difficult since we live in multiple social networks simultaneously [4]. Therefore, studies in animal models, on the consequences of high or low dominance ranking in social structures, are of importance in understanding the effect of hierarchical status on our well-being. Hence, we investigated the consequences of different hierarchical rankings on brain and behavior in wild-type Groningen (WTG) rats living in colony-like structure. Specifically, we focused on behavioral, physiological and neurobiological indicators of chronic social stress exposure during colony housing. Using wild-derived rats Most rodents are social animals by nature, living together in hierarchical colonies. There are several well-characterized tools used to measure social dominance in rodents [5]. For instance, agonistic behavior is often used as a marker for the determination of dominance. In our experiments, we have used feral rats of which the ancestors were caught in the wild and outbred for many generations in our laboratory. They specifically appear to have a rich and diverse behavioral repertoire, particularly in the social domain, and also display individual variability in offensiveness [6]. Establishment of social hierarchy among WTG rats For the installation of social hierarchies among male WTG rats, male and female rats were co- housed in a colony-like structure called the Visible Burrow System (VBS) for 3 weeks. The VBS is a habitat containing continuously dark burrows and an open area with a circadian light regime. Monitoring and recording The VBS' were monitored 24/7 using digital monochrome GigE cameras connected to a computer running MediaRecorder by Noldus. Formation and maintenance of hierarchy during the colony period was assessed by scoring agonistic behaviors using The Observer XT by Noldus. Male dominance was validated by scoring agonistic behavior towards an unfamiliar male intruder. Behavioral observation manifested a clear formation of social hierarchy in male WTG rats. Dominants exhibited offensive behavior towards subordinate and intruder male rats, whereas subordinate males showed defensive and social avoidance behavior. Schematic representation of the Visible Burrow System taken from [7]. Consequences of living in the colony-like structure The first indication of stress vulnerability can be the change in an individual's behavior [8]. Therefore, we behaviorally tested VBS housed male rats on social avoidance, open field and elevated plus maze tests for anxiety-like behaviors. The behaviors shown were analyzed using the EthoVision XT by Noldus. Data from these tests did not show any significant differences among control, subordinate and dominant individuals. However, we did observe that the subordinate individuals spent maximum time in the dark burrows, hiding from the dominant rats. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - check_circleA cost-effective solution - check_circlePowerful data selection - check_circleMost cited video tracking system Free Trial arrow_forward Physiological and Neuronal changes The amount of social stress that animals undergo in VBS housing is reflected in various physiological and neuronal alterations. Both dominants as well as subordinates lost a considerable amount of body weight and fat mass whereas adrenal glands were larger in VBS housed rats. Furthermore, we studied proteins (p-cofilin/cofilin proteins ratio) involved in dendritic spine remodeling in several brain regions in dominant and subordinate males. A higher protein ratio was found in the subordinate as well as in dominant rats particularly in the medial prefrontal cortex and amygdala regions, respectively. This relates to enhanced behavioral flexibility in the subordinates and enhanced amygdala-dependent aggressive behavior in dominant males. Visible burrow system as a model of chronic social stress Although animals seem more stressed socially, chronic social stress induced by the VBS did not seem to affect general anxiety in male WTG rats. WTG rats appear to be highly resilient to the negative consequences of social stress, behaviorally, despite strong physiological and neurobiological response to social stress. We speculate that to observe a differential behavioral response to stress in WTG rats, we might need more sensitive behavioral paradigms. Future studies using VBS could help in studying individual differences to stress susceptibility by using social status as a factor of vulnerability. Image taken from PhD thesis- Deepika Patel Extrapolating results to human life Some of the common and consistent features experienced by conspecific individuals living in social groups are bullying, domestic violence and subordination. These are successfully modelled in the laboratory settings and have helped to investigate behavioral, neural and endocrine correlates of social stress. Lastly, housing rats in semi-natural environments produces large individual differences in ranking position, making this a promising model to study underlying mechanisms of individual differences in social ranking and the potential role of high or low ranking in health and disease. References - Sapolsky, R.M. (2005). The influence of social hierarchy on primate health. Science (80), 308, 648–652, doi:10.1126/science.1106477. - Cohen, S.; Doyle, W.J.; Baum, A. (2006). Socioeconomic Status Is Associated With Stress Hormones. Psychosom. Med., 68, 414–420, doi:10.1097/01.psy.0000221236.37158.b9. - Goodman, E.; Slap, G.B.; Huang, B. (2003). The public health impact of socioeconomic status on adolescent depression and obesity. Am. J. Public Health., 93, 1844–50. - Cummins, D.D. (2000). How the Social Environment Shaped the Evolution of Mind. Synthese, 122, 3–28, doi:10.1023/A:1005263825428. - Wang, F.; Kessels, H.W.; Hu, H. (2014). The mouse that roared: neural mechanisms of social hierarchy. Trends Neurosci., 37, 674–682, doi:10.1016/j.tins.2014.07.005. - Boer, de, S.F.; Vegt, van der, B.J.; Koolhaas, J.M. (2003). Individual variation in aggression of feral rodent strains: A standard for the genetics of aggression and violence? Behav. Genet., 33, 485–501, doi:10.1023/A:1025766415159. - Patel, D.; Kas, M.J.; Chattarji, S.; Buwalda, B. (2019). Rodent models of social stress and neuronal plasticity: Relevance to depressive-like disorders. Behav. Brain Res., 369, doi:10.1016/j.bbr.2019.111900. - Schmidt, M.V.; Scharf, S.H.; Sterlemann, V.; Ganea, K.; Liebl, C.; Holsboer, F.; Mu, M.B. (2010). High susceptibility to chronic social stress is associated with a depression-like phenotype. Psychoneuroendocrinology, 635–643, doi:10.1016/j.psyneuen.2009.10.002. --- ## Measuring the intensity of emotional response to political advertisement videos URL: https://noldus.com/blog/intensity-emotional-response Published: 2020-10-12 11:55:00 Description: To convince voters, all kinds of strategies can be used to stimulate the electorate. Researcher Dias and his team evaluated how voters respond to changes in the scenario of videos of political propaganda. To convince prospective voters to choose you as a candidate, all kinds of strategies can be used to stimulate the electorate. The use of videos is most common, mainly because the internet makes sure the videos are universally accessible and shared widely and freely. Valence of emotion The research team of Carlos Magno Machado Dias, from the Federal University of Minas Gerais in Brazil, conducted a study to evaluate how voters responded to changes in the scenario of videos of political propaganda. They used four different background scenarios in the videos: - Completely white background - Library - Luxury house - Popular house The images shown here are not the original images used in the study, but are meant to give an impression of the scenarios. The researchers compared the emotional valences found among individuals who watched the political propaganda videos, whose only difference was the scenario in which the candidate presented himself. The data collected in this study was obtained by measuring facial expressions automatically, instead of using self-reports of emotional states, which is therefore subject to bias. Especially the use of the Facial Action Coding System (FACS) offered the opportunity to measure all visible facial behavior in any context on the basis of Action Units (AUs). Download here the Free white paper 'Facial Action Coding System (FACS)' Measurement of emotions through facial expressions The experiment was carried out in a lab, with controlled conditions, with a fictitious candidate (a male actor), and prospective voters who were selected randomly among students. The prospective voters watched only one of the 30-seconds political commercials, randomly selected, with one of the four backgrounds. While the video was played, images of the voter’s face were recorded. The recordings of 108 participants were analyzed using FaceReader software. The research team completed a temporal analysis of the valences throughout the video and divided the time into three segments (about 10 seconds per segment) for better performance of the comparison. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Intensity of emotions During the first segment, the candidate tried to convince the voters with the text: “We need to transform our country into a better place. This requires political will and candidates with a history of life committed to work and honesty.” Analysis showed that the highest valence average was presented in the ‘popular house group’. The average values of the valence among the individuals who watched the video with a luxury house setting and a white setting was noticeably lower than the others. Note that higher valences involve a higher intensity of positive emotion (happy) and a lower intensity of other emotions (negative). There is a more pronounced presence of negative emotions in the luxury house and white scenarios. Influencing the voter’s receptiveness In the following 10 seconds of the political propaganda video, the candidate says: “I have been working for many years defending the rights of the citizens and the well-being of countless families. Your life will improve.” For this part of the video, the ‘library group’ showed the highest average on valence. It confirmed that the scenarios over which political messages are transmitted alter the voter’s receptiveness. The candidate concludes in the third segment with the words: “Have confidence. My party and I know the situation and we know what needs to be done. What we want is to contribute to the construction of a more justifiable society.” This time, the individuals who watched the video with the white scenario presented the highest average on valence. Enhance the emotional effects The researchers conclude in their article that the voters’ responses to the videos express different valences according to the scenario, both qualitatively and quantitatively. They assume that the video with a popular house scenario, which presented statistically higher average values than the others did, produced a more positive emotional response than the other tested scenarios. The individuals who watched the video with a luxury house scenario showed a lower valence than all the other individuals throughout the video. It is obvious that the scenarios can enhance the emotional effects of this type of advertising. When we consider that positive emotions play an important role in decision-making processes, the found differences in valence must have an implication on the reaction to a political propaganda video. Reference Dias, C.M.M.; Ribeiro, Â.M. & Gonçalves, C.A. (2020). Valences in voters’ emotional response: Experimental design with neuroscience. ReA UFSM | Brazilian Journal of Management, 13 (3), 483-500. https://doi.org/10.5902/1983465943111   --- ## A to Z on optogenetics and video tracking studies URL: https://noldus.com/blog/a-to-z-on-optogenetics-and-video-tracking-studies Published: 2020-10-08 12:00:00 Description: Optogenetics allow researchers to either activate or inhibit neurons in the brain. To see how this affects behavior, you need to record that behavior and synchronize it with the stimulation. Here's how. Today, I've snuck into the blog from the Noldus Support and training department to talk about EthoVision XT. One of the things that keeps my job interesting is that scientists always want to try something new. Existing tools get applied to new problems in new ways. Optogenetics provides a great example. Optogenetics Optogenetics is a transformative technique which allows researchers to either activate or inhibit neurons in the brain, in order to determine the function of those brain cells. This technique is applied in living fruit flies, nematodes, zebrafish, and mice and rats. The technique of optogenetics In an optogenetics experiment, neurons are treated in various ways to incorporate light sensitive receptor proteins in their cell membranes. A fiber optic cable is implanted in the animal to bring light to the targeted cells. (In case of developing zebrafish, for example, no implants are necessary as larvae are transparent.) When these cells are exposed to light of the correct wavelength, ion channels open, causing the neuron to fire. These channels remain open as long as the light remains on, preventing the neuron from returning to its resting state. The result is that the neurons are "turned off" or inhibited; whatever signals they would normally respond to now elicit no response. Activating neurons Alternatively, the researcher may want to see what happens when the neurons are activated. In this case the light is flashed rapidly (typically on the order of 20 times per second). When the light turns on, the neuron fires, and when it turns off, the neuron recovers so that it is ready to fire again. Flashing the light repeatedly causes the neuron (or neurons) to fire rapidly and repeatedly. Optogenetics in video tracking experiments If the goal is to see how these changes affect behavior, then you need a tool to record that behavior and synchronize it with the stimulation. This is where EthoVision XT comes into the picture. An optogenetics system consists of EthoVision XT, a computer, a USB IO-box, a light source with a trigger input, and usually a pulse generator. The light source may be a laser or a high intensity LED. In addition, fiber optics, connectors, and a canula get the light into the animal's brain. Inhibiting neurons during a behavioral test Inhibition is the easiest scenario, since the light simply needs to be turned on and remain on as long as inhibition should continue. At the appropriate point during the trial, EthoVision XT uses the USB IO-box to trigger the light source. The light remains on until EthoVision turns off the signal. Using pulse generators to activate neurons Activating the neurons requires one additional step. It's not enough to turn the light on and leave it on, it must also be rapidly flashed on and off repeatedly. This is where a pulse generator must be added. EthoVision XT triggers the pulse generator to start, and the pulse generator handles the rapid pulsing of the light source. Although we often use the Pulser by Prizmatix (shown in the picture with PhenoTyper setup above), EthoVision XT is highly adaptable and can be used with a wide variety of pulse generators. This type of equipment normally uses a simple 5V trigger signal, regardless of maker, so it's just a matter of providing the correct type of cable and setting the pulse generator correctly. An Arduino can also be used in place of a pulse generator for those willing to do their own wiring. Controlling stimulation Now that the hardware is set up, when should the light be turned on? In EthoVision XT, we use the Trial Control to define how long the trial should run, and at what points devices should be turned on and off. The simplest possible optogenetics trial would present the stimulation (or inhibition) at a particular time. The Trial Control is simply a flow chart of the events of the trial. Individual steps in the trial can be named to make it easier to refer to them in the analysis. Here, we have an initial 5 minute pre-stimulation period, followed by a minute of stimulation, and then 5 minutes post-stimulation: Any number of events can be strung together this way. The events flow in the direction of the arrows, and when they reach "Stop Track", the trial is over. Repeated stimulation However, sometimes you want to repeat events over and over. It's possible to do that by stringing many boxes together, but it can be easier to create a Sub-Rule which repeats a predefined number of times. In this example, after the 5 minute pre-stimulation period, the sub-rule is called three times. Each time, the stimulation is activated for two minutes, then turned off for two minutes. When the sub-rule has completed the third run-through, we continue to the Stop Track box and the trial ends. Place-preference A common scenario is a place preference test. In this case, the stimulation (or inhibition) occurs whenever the animal is in a particular zone. Instead of running the sub-rule a pre-determined number of times, we want it to run repeatedly, checking whether the animal is in the zone or not. In this example, the stimulation begins when the animal enters the Left zone, and stops when the animal moves to the Right zone. Because the sub-rule will never complete (it will just keep checking which zone the animal is in), we add a time condition to control the duration of the whole trial (10 minutes in this example). Other options Although in this example we used the zone to trigger the stimulation, in fact it's possible to use any behavior the same way. Stimulation (or, for that matter, lights, sounds, pellet dispensers, or any other type of device) can be triggered based on the activity level, velocity, degree of turning, or other behavioral measures. It could also be based on sensors, for example when a lever is pressed or a nose-poke sensor is triggered. Whatever the needs of your research, EthoVision XT is ready. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Read more about optogenetics on our website and in this blog post. Read more: Optogenetics applications Read more: Optogenetics blog post Read more: Optogenetics and operant conditioning --- ## The role of facial expression of emotion in joint activities URL: https://noldus.com/blog/role-facial-expression-emotion-joint-activities Published: 2020-10-06 10:27:00 Description: How does emotion expression guide interactive value learning and interactive corrective action selection? Dr. Robert Lowe investigated this and shares his findings in this guest blog post. By Robert Lowe, Associate Professor at the Division of Cognition & Communication at the University of Gothenburg, Sweden. The role of facial expression of emotion in joint activities Robert Lowe's group at the University of Gothenburg have been researching the role of processing facial expression of emotion on cognitively demanding tasks. Their focus has been on whether and how emotion expression guides: - interactive value learning, and - interactive corrective action selection. The researchers have carried out different social interaction-based studies on the differential outcomes learning paradigm and an interactive map navigation task requiring corrective action selection. The researchers' broader interest concerns the use of emotion in joint activities. MEASURE YOUR EMOTIONS: What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Download Differential outcomes learning In a recently published article by Rittmo et al. (2020), the researchers adapted an existing psychology-learning paradigm – differential outcomes learning for transfer of response knowledge. Differential outcomes training is utilized in classical stimulus-response training setups where an arbitrary stimulus (e.g. an image of an umbrella, in a computerized task) is followed by different response options (e.g. a left and right response tab to be pressed) where only one such response provides 'correct' feedback. Learning is by trial and error. Participants are required to match various stimuli with the different response options in order to receive a rewarding or reinforcing outcome (e.g. image of money). Unlike the standard behavioural learning approach, differential outcomes training entails the different stimulus-response pairings being followed by differential rewarding outcomes (e.g. presentation of images for: large money reward versus low money reward). A differential outcomes effect – faster learning under differential versus non-differential (same reward for every correct response) outcomes training – has been reliably found across studies (McCormack et al. 2019) using this experimental setup. Interactive value learning from expressed emotions The researchers at Gothenburg University performed a novel variant of the differential outcomes procedure in the form of a computerized task in a social setting. This required participants having to learn from videos of an actress (confederate) expressing positive and negative emotions following high or low rewarded instrumental responses (image of large amount of money, or small amount of money, respectively). Negative emotion, in this case, served as an expression of mild frustration for a relatively low rewarding outcome following the correct response to the previously presented stimulus. Download here the Free white paper 'Facial Action Coding System (FACS)' Associations between visual stimuli and response options In the experiment, participants were initially required to learn associations between visual stimuli and response options where different pairings led to different valued (rewarding) outcomes (images of high versus low cash rewards). The participants were then required to observe a confederate participating in the same task but with novel visual stimuli presented. So whereas in initial training the stimuli included images of a broom (on the computer screen) in the observation training an image of a bus might be presented. Below can be seen a trial progression diagram of the initial training. In the observation training, the trial progressed as for the initial training but now the response options were hidden from the observing participant's view whilst the video of the actress played throughout the trial. At the presentation of the outcome (also hidden from the observing participant's view) the actress would smile to illustrate mild frustration as shown below. The actress was instructed to express emotions naturally. FaceReader was used to evaluate the tractability of the affective valence of the expressions, which was shown to be reliable when assessed for the 20 successive trials used for observation training. In this way the expressed emotion served as a proxy for the high and low valued outcomes from which the participant could potentially learn. Associative Two-Process Theory The experiment of Rittmo et al. (2020), evaluated the interactive value learning of participants from the initial training, and then observation training, stages through a test stage. In this test stage, response options were again made visible (as for initial training) to the participants who tended to select the responses 'chosen' by the actress in spite of never having seen the actress respond to the particular novel stimuli (in fact she didn't select responses but merely reacted to a videoed set up). Based on Lowe et al. (2016), participant test stage response selection was predicted according to an adapted (social) version of Associative Two-Process theory (Trapold 1970, Urcuioli 2005). Classic Associative Two-Process is schematized below in relation to our experiment. On the top row is shown the trial procedure. In Stage 1 can be seen the correct response for a given presented stimulus (e.g. R1 following S1, where R2 is 'incorrect' for this trial) and the rewarding outcome that follows (O1 for the S1->R1 pairing), with no reward or a punishing outcome presented when the incorrect response is chosen, e.g. S1->R2->punishment. In each stage of the experiment, different Stimuli (S1, S2, S3, S4), and Response (R1, R2) options are presented over a number of trials (one stimulus per trial). In Stage 1 and 3 both response options are presented (consistent with the schema above) and the 'correct' response leads to a rewarding outcome (O1 or O2), otherwise no reward. Forming expectations Associative two-process theory predicts (bottom row of above diagram) that participants form expectations (values) for the different outcomes (E1, E2), in our case for high (O1) and low reward (O2), respectively. These expectations serve as internal stimuli that can be associated with both (external) Stimuli and Responses. In this way, participants may learn that, for example, E2 was associated with R2 (Stage 1), and with S4 (Stage 2). Thereby, if S4 is presented again in Stage 3, it should associatively cue a representation of E2 that in turn associatively cues a representation of R2. As such, participants are biased to a particular response (R2) in spite of never having been presented in the same trial with the S4-R2 pairing. FREE WHITE PAPER: FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Social Associative Two-Process Learning In Lowe et al. (2016) it is hypothesized that participants who are not competing with another in the joint activity will "place themselves in the other's shoes" and learn value-based outcome expectations (high versus low reward) of the other as if they were their own. We call this vicarious value learning. It provides an adaptation of the above-mentioned 3-stage set up. In the classical set-up in Stage 2, participants perceive differential outcomes for each presented novel stimulus (Pavlovian conditioning). Instead, in the adaptation of Rittmo et al. (2020) the participants observe emotion expression from the confederate as a proxy for the actual (now non-visible) outcomes. This Social Associative Two-Process hypothesizes participants valuating the novel stimuli in Stage 2 as if they were present in the place of the confederate. The participants then used their updated stimulus valuations to select responses using the above-discussed associative transitive inference (in the diagram, by associative transitive inference: S4->E2, E2->R2 gives S4->R2). Such interactive value learning, based on incomplete information (i.e. the other's responses are not visible) may be of use during joint activities where interacting agents are required to collaborate on 'quick-fire' tasks. Emotional cues transmitting information about how the task is going for another agent might provide a means for circumventing a lengthy trial and error learning process. This should particularly apply in situations where differential affective states (outcome expectations) constitute a common class for task-related stimuli, i.e. where certain groups of stimuli typically evoke a particular type of response. Emotions guide corrective responses Another aspect of observing another's performance during joint activity concerns monitoring the other and corrective responding, i.e. providing compensatory responses during collaborative tasks when something unexpected occurs. Emotions are said to guide corrective responses in such cases (Oately & Johnson-Laird, 1987, 2014). Borges et al. (2019) used a video data set collected at the University of Gothenburg that consisted of instructor-follower dyads engaging in a map navigation task. The task was designed to induce miscommunications between instructor and follower requiring corrective responses (e.g. questions, confirmation statements). An example interaction is given below (as being analysed using FaceReader 8.0) where one participant observes the other (inset) and they are able to audibly communicate. The focus of the work of the DICE lab research group, however, was on the training of a neural network (Long Short-Term Memory/LSTM) for categorizing states of facial expressions of confusion from the videos. Within the FaceReader software, confusion is considered as an affective attitude (along with 'boredom' and 'interest' (Noldus 2019). It is, nevertheless, an affective state whose constituents are not universally accepted and may be specific to the particular task. The affective attitude confusion The benefit of being able to automatically detect confusion states from processing facial expressions of emotion, and relatively rapidly, is apparent in studies of Human-Computer Interaction (Lago & Guarin, 2014). If, for example, confusion in a human participant is detected by a software agent, responses to resolve the confusion can be carried out by the agent before the subject becomes disengaged in the activity. This has potentially many applications from joint activities in human-computer interactive tasks to gaming and gamification of cognitive tasks. In Borges et al. (2019), we trained the LSTM on action unit inputs from the FaceReader analysed videos and derived respectable classification accuracy, precision, and recall relative to ground truth values (inter-rater coded) for Positive, Negative, Neutral and Confusion affective states. This work we consider promising in the context of Human-Robot interaction tasks we are developing (Lowe et al., 2019) that require the robot to learn vicariously from others (as in Rittmo et al., 2020) while responding to other's affective states that might disengage them from the joint activity (e.g. as manifested in 'confusion'). References Borges, N.; Lindblom, L.; Clarke, B.; Gander, A. & Lowe, R. (2019). Classifying confusion: Autodetection of communicative misunderstandings using facial action units. 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), 401–406. IEEE. https://doi.org/10.1109/ACIIW.2019.8925037. Lago, P. & Guarin, C.J. (2014). An affective inference model based on facial expression analysis," IEEE Latin America Transactions, 12(3), 423–429. https://doi.org/10.1109/TLA.2014.6827868. Lowe, R.; Almér, A.; Gander, P. & Balkenius, C. (2019). Vicarious value learning and inference in human-human and human-robot interaction. 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), 395–400. IEEE. https://doi.org/10.1109/ACIIW.2019.8925235. Lowe, R.; Almér, A.; Lindblad, G.; Gander, P.; Michael, J. & Vesper, C. (2016). Minimalist social-affective value for use in joint action: A neural-computational hypothesis. Frontiers in Computational Neuroscience, 10, 88. https://doi.org/10.3389/fncom.2016.00088. McCormack, J. C., Elliffe, D. & Virués‐Ortega, J. (2019). Quantifying the effects of the differential outcomes procedure in humans: A systematic review and a meta‐analysis. Journal of applied behavior analysis, 52(3), 870-892. https://doi.org/10.1002/jaba.578. Noldus. (2019). FaceReader: Tool for automatic analysis of facial expression, Version 8.0 [Software]. Wageningen, The Netherlands: Noldus Information Technology B.V. Oatley, K. & Johnson-Laird, P.N. (1987). Towards a cognitive theory of emotions. Cognition and emotion, 1(1), 29-50. https://doi.org/10.1080/02699938708408362. Oatley, K. & Johnson-Laird, P.N. (2014). Cognitive approaches to emotions. Trends in cognitive sciences, 18(3), 134-140. https://doi.org/10.1016/j.tics.2013.12.004. Rittmo, J.; Carlsson, R.; Gander, P. & Lowe, R. (2020). Vicarious Value Learning: Knowledge transfer through affective processing on a social differential outcomes task. Acta Psychologica, 209, 103134. https://doi.org/10.1016/j.actpsy.2020.103134. Trapold, M.A. (1970). Are expectancies based upon different positive reinforcing events discriminably different? Learning and Motivation, 1, 129–140. https://doi.org/10.1016/0023-9690(70)90079-2. Urcuioli, P.J. (2005). Behavioral and associative effects of differential outcomes in discrimination learning. Animal Learning & Behavior, 33, 1–21. https://doi.org/10.3758/BF03196047. --- ## Discussing uncertainty during cancer genetic counseling URL: https://noldus.com/blog/discussing-uncertainty-during-cancer-genetic-counseling Published: 2020-10-01 10:00:00 Description: Getting screened preventively to find out whether a genetic predisposition increases the chance of developing cancer, causes great uncertainty. Which communication manners help to deal with this? By Niki Medendorp, researcher at the Department of Medical Psychology of the Amsterdam UMC, The Netherlands. Background of research project Multigene panel testing In approximately 5% of all cancer patients, cancer is caused by an underlying genetic predisposition. Cancer patients or their relatives (i.e., counselees) can undergo genetic testing to find out if they carry a genetic predisposition that increases their chance of developing cancer during their lifetime. Until recently, genetic testing consisted of the sequencing of individual genes associated with the cancer(s) in the family to identify genetic predispositions. Technological developments within the genetic field have resulted in the possibility to sequence multiple genes associated with cancer simultaneously. This is also called 'multigene panel testing'. Multigene panel testing increases the diagnostic yield as it involves a higher probability to identify genetic predispositions. As a result, counselees can undergo preventive screening to detect cancer at an early stage. In addition, relatives of carriers can be tested to determine whether they carry the same predisposition and are in need for screening. However, panel testing also generates an increased level of uncertainty. For example, a multigene panel test causes a higher chance to determine a genetic variant for which the meaning and implications are unknown. The communication of uncertainty Uncertainties surrounding multigene panel testing need to be discussed with counselees to prepare them for potential uncertainties afterwards. For example, preparing counselees for uncertainty increases their ability to deal with an uncertain variant. Moreover, communicating uncertainties enables them weigh the pros and cons of panel testing and make an informed decision about pursuing such a test [1]. Previous research, however, showed that the communication of uncertainty can have harmful effects on patients, such as higher distress and anxiety [2, 3]. Discussing uncertainty during genetic counseling is therefore not straightforward. Insights into communication manners The PhD thesis of Niki Medendorp focuses on how to discuss uncertainty concerning multigene panel testing during cancer genetic counseling. The research team of Niki Medendorp specifically aimed to provide insights into communication manners that help counselees feel more supported, deal with uncertainty, and engage in decision-making about whether to pursue multigene panel testing. For this purpose, three sub-aims were addressed: - 1. To explore whether and how uncertainty is discussed in current cancer genetic counseling in general, and multigene panel testing in particular, and how this discussion is experienced by both parties, i.e., counselors and counselees. - 2. To investigate how counselors' discussion of uncertainty affects cancer genetic counseling in the context of multigene panel testing. - 3. To identify how counselors can be supported in optimally discussing uncertainty during genetic counseling. Research methods To address the above mentioned aims, a variety of research methods was used such as qualitative, observational, experimental, and literature studies. One of the observational studies was performed to provide insight into the current practice of discussing uncertainty, by using The Observer XT software. In this observational study, 29 genetic consultations between counselors and a standardized counselee (an actor who acted as a counselee) were videotaped. Using a standardized counselee allowed comparing the communication between counselors. Then, The Observer XT software was used to analyze counselors' communication manners. All verbal uncertainty expressions of genetic counselors and the manner in which they responded to the uncertainty expressions of the counselee were coded. This study showed a great variation between counselors in how they communicate and respond to uncertainty. Based on the findings of the observational study, an experimental study was performed in which the effects of six communication manners were compared. These manners were developed based on the communication manners identified in the observational study. Counselees (n=224) viewed a video consultation in which one of the six communication manners was used. Afterwards, they completed a questionnaire assessing several outcomes such as their feelings of uncertainty and satisfaction. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Conclusion This PhD thesis provided evidence for communication behaviors that counselors may use to discuss uncertainty. More importantly, the findings emphasize the importance of exploring uncertainty expressions of counselees, and tailoring the communication of uncertainty to the needs and preferences of the individual counselee. Genetic counselors are therefore recommended to loosen their primary focus on informing counselees about uncertainties, and give more attention to helping counselees deal with uncertainty and enable them to make an informed decision about pursuing multigene panel testing. Implications Based on the study findings presented in this thesis, a communication skills training was developed. This training is aimed at improving counselors' skills to communicate uncertainty, and provides genetic counselors with guidance on how to discuss uncertainty during cancer genetic counseling about multigene panel testing. To this end, participants are first provided with theoretical background after which they are enabled to practice their skills during role play. By providing genetic counselors with these insights and allowing them to enhance their communication skills, this research contributes to an optimization of the communication of uncertainty with counselees in clinical practice. Discover the 10 reasons why video feedback is essential in skills education. Download the Free white paper! More information Publications resulting from the research of Niki Medendorp can be found below. Medendorp et al. (2018). Uncertainty in consultations about genetic testing for cancer: an explorative observational study. Patient Education and Counseling, 101(12), 2083-2089. https://doi.org/10.1016/j.pec.2018.08.002 Medendorp et al. (2019). Uncertainty related to multigene panel testing for cancer: a qualitative study on counsellors' and counselees' views. Journal of Community Genetics, 10, 303-312. https://doi.org/10.1007/s12687-018-0393-1 Medendorp et al. (2020). 'We don't know for sure': discussion of uncertainty concerning multigene panel testing during initial cancer genetic consultations. Familial Cancer, 19, 65-76. https://doi.org/10.1007/s10689-019-00154-4 Medendorp et al. (2020). The impact of communicating uncertain test results in cancer genetic counseling: A systematic mixed studies review. Patient Education and Counseling, 103(9), 1692-1708. https://doi.org/10.1016/j.pec.2020.03.015 Medendorp et al. (2020). Communication skills training for healthcare professionals in providing genetic counseling: A scoping literature review. Patient Education and Counseling. https://doi.org/10.1016/j.pec.2020.07.018 References [1] T.L. Beauchamp, J.F. Childress, Principles of biomedical ethics, Oxford University Press, USA2001. [2] M.C. Politi, P.K. Han & N.F. Col (2007). Communicating the uncertainty of harms and benefits of medical interventions, Medical Decision Making, 27(5), 681-695. [3] D.C. Blanch, J.A. Hall, D.L. Roter & R.M. Frankel (2009). Is it good to express uncertainty to a patient? Correlates and consequences for medical students in a standardized patient visit, Patient education and counseling, 76(3), 300-306. --- ## Studying shrimp feeding behavior and why it’s important for aquaculture URL: https://noldus.com/blog/studying-shrimp-feeding-behavior Published: 2020-09-24 11:29:00 Description: Shrimp is a popular dish, and these crustaceans are a very large part of commercial aquaculture. Especially Pacific white-leg shrimp, as they grow fast and are able to adapt to a wide range of environments. Shrimp is a popular dish, and these crustaceans are a very large part of commercial aquaculture. Especially Pacific white-leg shrimp, as they grow fast and are able to adapt to a wide range of environments. How shrimps feed The downside of these shrimps is that they can be slow feeders, which has a lot more consequences than you might expect. For example, when food is left, it is not only a waste of money, it also contaminates the water. You can imagine that finding the optimal way to feed shrimp can make or break profitable farming. This is why investigating the best feeding protocols has gained more interest lately, and a big part of that is looking at feeding behavior. In fact, understanding the basics of shrimp behavior is a crucial fundament to the refinement of feeding practices. Wasting food Food waste may occur if there is simply too much food to take in, but also when it is of low quality and shrimp are not attracted to it, cannot detect it, don't want to eat it, or it partially breaks down in the water before they get a change to grab it. So, in addition to the quality of the food, it also matters how much you give them, when during the day, and where. Testing behavior So how do you figure out what the best practice is? You ask the shrimp. You monitor their behavior closely and see how they respond to different feeding protocols. How shrimps behave A lot is already known about shrimp feeding behavior. When feed is offered, the crustaceans start exploring, crawling, using chemoreception to find food across distances. When food is detected with their chemoreceptors, and the animals start orienting themselves towards the food, you can see antennule flicking behavior. Once the animal is close to the food, it grabs it with its "hands", called dactyls, which are at the end of its walking leg. It then brings the food to its maxillipeds (jaw-like feature that handles the food) and mouthparts. But the onset of feed handling does not guarantee that the animal is actually eating the food. After-eating rituals Like many animals, after feeding, shrimp start grooming. Crustaceans also have clear feed rejection patterns, for example, they move around the food, without interaction. Or they pick it up, but no mouthpart movements are observed. Food can also be thrown away or backed away from. They are also creatures of habit, and can habituate to a particular feeding area. The effectiveness of feeding The effectiveness of the feed protocol is reflected in behavior, but feeding is also influenced by other effects, such as moulting, shrimp character, gender, environmental enrichment, and water quality. Video tracking feeding behavior A recent publication of Bardera and colleagues (2020, Aquaculture) introduced video tracking to shrimp behavior research. In this particular study they validated EthoVision XT for these types of experiments. With 27 shrimp, they tested feed attractability of three experimental diets with different theoretical levels of attraction. Two times a day, the shrimp were recorded for 20 minutes in a rectangular arena. They gathered data both manually and with EthoVision XT, comparing results for consistency. "Distribution heatmaps provided by EthoVision offered a quick and reliable assessment of feed attractability [in Pacific white shrimp]." Guillermo Bardera | University of the West of Scotland, Paisley, UK Parameters of feeding in video tracking experiments EthoVision XT was used to measure time spent in the feeding area, attraction to feed score, number of transitions to the feeding tray, average distance to the feed throughout a trial, time spent moving, distance travelled, and average speed. Heatmaps were used to visualize the results. The similarity between manual observations and those made with EthoVision XT video tracking was very high, varying between 93,4% and 99,8%. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - Track any animal, in embryo, larval, or adult stage - Suitable for tracking in any arena - Most cited video tracking system Free Trial Feed attractability The next step was to use EthoVision XT to determine feed attractability and effect of time of day. Shrimp showed little motivation to eat when presented with the negative diet, which showed by the longer distances they covered, the higher velocity, greater time spent moving around and more transition to the feeding tray. Time of day seemed to have little effect on feeding behavior. Applications in commercial farming Bardera and his colleagues concluded that EthoVision XT shows clear potential to track shrimp feeding behavior and for developing automated protocols to assess feed attractability in the aquaculture industry. Prairie AquaTech studies Luke Fredrickson and his colleagues from Prairie AquaTech picked up on this and are currently in the early stages of their research focusing on scoring feeds. EthoVision XT improved their understanding of shrimp behavior in response to different feed formulations. Fredrickson especially likes the ability to track and report long-term feeding data. It is also helping them understand the role and value that specialized ingredients such as ME-PRO® can play in the future of sustainable aquaculture. "EthoVision XT does much of the analysis for you. I do not have to watch hours of video or spend considerable time watching over the tanks. The improvements that we are making are very exciting for Prairie AquaTech and will be for the aquaculture industry as well." Luke Fredrickson | Prairie AquaTech, Brookings, SD, USA Behavior in relation to feeding zones Similar to Bardera and his colleagues, they are using video tracking to look at the number of times a shrimp enters the feeding area during specific intervals of time and the time it takes for the shrimp to first enter the feeding zone. "I have been impressed with how well the software can track the movements of shrimp, especially head and tail orientation. EthoVision XT can quickly provide us with heatplots of each trial, which can quickly show the amount of time spent in each area of the tank," Fredrickson explains. Future research at Prairie AquaTech Prairie AquaTech is planning on continued research with EthoVision XT to evaluate additional behavioral dimensions such as speed, not moving/moving, distance, as well as preferential feeding behavior of white shrimp Litopenaeus vannamei under different salinity and temperature real-time interaction. They are also planning to look into the feeding behavior of other species such as Atlantic salmon, Trout, Seabass and Cobia. References - Bardera, G.; Owen, M.A.G.; Pountney, D.; Alexander, M.E.; Sloman, K.A. (2019). The effect of short-term feed-deprivation and moult status on feeding behaviour of the Pacific white shrimp (Litopenaeus vannamei). Aquaculture 511, 734222. - Bardera, G.; Usman, N.; Owen, M.A.G.; Pountney, D.; Sloman, K.A.; Alexander, M.E. (2019). The importance of behaviour in improving the production of shrimp in aquaculture. Reviews in Aquaculture 11(4), 1104-1132. - Bardera, G.; Owen, M.A.G.; Façanha, F.N.; Sloman, K.A.; Alexander, M.E. (2020). The influence of sex on feeding behaviour in Pacific white shrimp (Litopenaeus vannamei). Applied Animal Behaviour Science 224, 104946. - Bardera, G.; Owen, M.A.G.; Façanha, F.N.; Alcaraz-Calero, J.M.; Sloman, K.A.; Alexander, M.E. (2020). Assessing feed attractability in Pacific white shrimp (Litopenaeus vannamei) using an automated tracking software. Aquaculture 529, 735692. --- ## Father’s genes affect their offspring’s future success URL: https://noldus.com/blog/fathers-affect-offspring-fitness Published: 2020-09-22 13:00:00 Description: The early life environment of male bank voles can influence their offspring significantly. Both social stress and nutrient supply have an effect on the chances of survival for two generations. A research group from Jyväskylä University in Finland has studied the fitness of rodent offspring, and what role the early life environment of their father could play. Far-fetched as it sounds, previous studies have already found evidence that fathers can 'relay' those experiences to their offspring. As a model species, the researchers chose the bank vole (Myodes glareolus), a common rodent in Finland. Intergenerational effects Bank vole fathers are not involved in rearing their offspring, meaning fathers can only influence their offspring through DNA. Examples of these early life environments could be the amount of nutrition available, diseases and population density. Paternal effect In general it is easy to study the mother's influence on offspring, since they are the ones raising the young. They influence the pups directly, through for example nutrition and social care. The indirect influence of the fathers is possible through various markers in DNA. Those can change through environmental influences like food and population density, which will then be passed on to the next generation. Basically, this makes DNA adjustable. Father's early life environment This study aims to find if a father's early life experiences could influence their offspring's survival. Groups of male bank voles (generation F0) were exposed to various environmental elements, after which they were allowed to mate. Their offspring (generation F1) was then tested on various traits, including reproductive success. The resulting F2 generation was tested on winter survival. Experimental adaptation Four experiments were done to test the bank voles: early life environment, reproductive success, a female preference test and lastly winter survival. For the early life environment test the amount of food and the population density were selected as testing traits. A protein-restricted diet and some social confrontation The F0 females were divided over four treatment groups: control (C), protein-restricted diet (PR), social confrontation (SC) and protein restriction and social confrontation (PR/SC). Each female could mate with a randomly chosen male. At the same time, the feeding with either regular or protein-restricted food started. Starting seven days later, every other day a SC female was put in a cage together with an unfamiliar SC female for 10 minutes. Both PR and SC treatment lasted until weaning. The resulting, fully grown PR and SC pups were found to weigh less than control pups. Father's reproductive success After the previous experiment, a reproductive success experiment was done. One F1 male of each experimental group was chosen and placed in a cage system, consisting of four interlinked cages. Two non-experiment females were placed in the system as well, and they were allowed to explore and mate for nine days. Afterwards, paternity of the resulting pups (F2) was determined using DNA tests. The researchers found that heavier F1 males had significantly more often fathered at least one pup, though the lighter males that had fathered pups, often had more pups than heavier males. Do females prefer the fittest males? A similar test was carried out to determine the preference of F1 females for F1 males. One male per treatment was placed in their own wire-mesh boxes, which were then placed in an open arena with the female in the middle. She could explore freely for 20 minutes though could not reach the males. Using EthoVision XT, her behavior was analyzed through video tracking. Each box had a virtual zone so that the tracking software could detect how often and how long she would visit there. The females were found to have no preference for males from specific treatments, though they preferred the ones that had fathered pups. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Pups adapt depending on father's influence The researchers found that PR and SC treatment lowered F2 pup weight, but PR/SC increased it. This makes clear that early life environment significantly influences even the next generation, though exactly how depends on the type of environment that influences the fathers. The most likely explanation for the increased PR/SC pup weight is that the treatment caused those pups to adjust their feeding behavior based on their father's early life environment. Winter survival of the third generation The researchers wanted to find out if the paternal treatments of F1 males was able to affect F2 winter survival. Therefore, the F2 voles were divided equally over semi-natural outdoor enclosures, and captured monthly in order to see which individuals survived. It was found that SC pups survived on average one month longer than control, while PR had no effect. Females also survived significantly longer than males. Father's early life environment influences offspring This research shows that early life experience can significantly influence fitness and survival of later generations through paternal influence only. The effect and its strength depend on the environment. Finding out what the potential long-term consequences of these treatments/environmental factors are could be a next research step. References Van Cann, J., Koskela, E., Mappes, T., Mikkonen, A. M., Mokkonen, M., & Watts, P. C. (2019). Early life of fathers affects offspring fitness in a wild rodent. Journal of Evolutionary Biology, 32(10), 1141-1151. --- ## Screening insecticides for efficacy or tolerance URL: https://noldus.com/blog/screening-insecticides Published: 2020-09-20 00:00:00 Description: Maarten Jongsma and colleagues use EntoLab to detect changes in insect behavior that provide a sensitive method for identifying and quantifying resistance development. They tested this approach with pyrethrins against aphids. LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more --- ## Identification of an aphid resistance gene in Arabidopsis URL: https://noldus.com/blog/screening-insect-resistance-aphids Published: 2020-09-20 00:00:00 Description: Karen Kloth used EntoLab in her research on the genetic basis of plant resistance to aphids. Genome-wide association mapping of aphid behavior on 350 natural Arabidopsis accessions led to the discovery of a new gene. LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more LABEL Title Learn more --- ## High-throughput screening of beneficial insects URL: https://noldus.com/blog/screening-beneficial-insects Published: 2020-09-20 00:00:00 Description: Jessica de Bruijn used EntoLab for automated high-throughput screening of parasitic wasps in individual olfactory 2-choice tests. Various behavioral parameters were measured to compute a memory retention index. LABEL Title Learn more De Bruijn et al. (2018) used the EntoLab system with two very different parasitic wasp species: the larval parasitoid Cotesia glomerata and the pupal parasitoid Nasonia vitripennis. The system proved to be highly suitable for testing memory retention in both these species. Unlike other bioassays, the EntoLab system allows for both high-throughput assays and recording of detailed individual behavior. The high-throughput individual T-mazes in EntoLab provide a standardized, labor-efficient and cost-effective method to test various kinds of behavior, offering excellent opportunities for comparative studies of various aspects of insect behavior. LABEL Title Learn more www.bugsinspace.nl LABEL Title Learn more LABEL Title Learn more Cross section of the T-maze set up of De Bruijn (2018). This single T-maze consists of multiple layers of plexiglass plates. The bottom compartment consists of a bottom sliding door plate, which allows insertion of insects, and the cage plate. Above the bottom compartment is the gate plate, which only opens at the start of the experiment. The top compartment consists of the arena plate with agarose zones and the top plate with gauze to allow gas exchange. The figure shows a cross section of a single T-maze, frontal view, out of a complete block of potentially 50 arenas. The bar is the lateral length of a single maze. LABEL Title Learn more Reference - De Bruijn, J.A.C. (2020). Information reliability shaping parasitoid foraging behaviour. PhD thesis, Wageningen University, 181 pp. https://edepot.wur.nl/506702 - De Bruijn, J.A.C.; Vet, L.E.M.; Jongsma, M.A.; Smid, H.M. (2018). Automated high-throughput individual tracking system for insect behavior: Applications on memory retention in parasitic wasps. Journal of Neuroscience Methods, 309: 208-217. http://dx.doi.org/10.1016/j.jneumeth.2018.09.012 LABEL Title Learn more --- ## Identification of thrips resistance in Arabidopsis URL: https://noldus.com/blog/screening-insect-resistance-thrips Published: 2020-09-20 00:00:00 Description: Maarten Jongsma explains how he used EntoLab to facilitate insect choice assays and automate the acquisition and analysis of movement tracks. Two Arabidopsis accessions were tested for resistance to western flower thrips. LABEL Title Learn more To validate the benefits of the system, two Arabidopsis accessions that were previously analyzed for differential resistance to western flower thrips were contrasted. Jongsma et al. (2019) describe how settings are optimized for the different filters and statistics. The statistics are reported in terms of frequency, duration, distance and speed of behavior events, both as sum totals and event averages, and both for the total trial period and in time bins of 1 h. Also included are higher level analyses with subcategories like short-medium-long events and slow-medium-fast events. The time bins showed how some behavior elements are more descriptive of differences between the genotypes during the first hours, whereas others are constant or become more relevant at the end of an 8 h recording. The three overarching behavior categories, i.e., choice, movement, and halting, were automatically corrected for the percentage of time thrips were detected and 24 out of 38 statistics of behavior parameters differed by a factor 2–6 between the accessions. The analysis resulted in much larger contrasts in behavior traits than reported previously. Compared to leaf damage assays on whole plants or detached leaves that take a week or more to complete, results were obtained in 8 h, with more detail, fewer individuals and higher significance. LABEL Title Learn more Comparison of different two-choice assays to assess plant resistance to thrips (from Thoen et al., 2016). LABEL Title Learn more Determining the behavior state and zone position of thrips. (A) Histogram of the velocity distribution of one thrips in a selected arena to aid in selecting proper thresholds for the determination of movement and halting events (velocity in mm/s); (B) Zoom of 12 arenas of the T-maze array with the two Arabidopsis accessions; (C) View on the left of the 2D arena shape position trace (red line) and on the right the 1D thrips zone position and velocity traces (black line) and movement state (green band for moving and red for halting) for a selected time interval (ca 18min). LABEL Title Learn more Thrips choice behavior statistics in time (A–N). Overview of 14 different statistics that are automatically indexed per hour by EthoAnalysis. The 95% confidence intervals are indicated by blue and green shading (excluding effects of experimental design). The results are based on 39 arenas. LABEL Title Learn more References - Jongsma, M.A.; Thoen, M.P.M.; Poleij, L.M.; Wiegers, G.L.; Dicke, M.; Noldus, L.P.J.J.; Kruisselbrink, J.W. (2019). An integrated system for the automated recording and analysis of insect behavior in T-maze arrays. Frontiers in Plant Science, 10:20. http://dx.doi.org/10.3389/fpls.2019.00020 - Thoen, M.P.M. (2016). Host-plant resistance to western flower thrips in Arabidopsis. PhD thesis, Wageningen University, 195 pp. https://edepot.wur.nl/387275 - Thoen, M.P.M.; Kloth, K.J.; Wiegers, G.L.; Krips, O.E.; Noldus, L.P.J.J.; Dicke, M.; Jongsma, M.A. (2016). Automated video tracking of thrips behavior to assess host-plant resistance in multiple parallel two-choice setups. Plant Methods, 12:1. http://dx.doi.org/10.1186/s13007-016-0102-1 LABEL Title Learn more --- ## How to conduct research with human participants during COVID-19 URL: https://noldus.com/blog/research-human-participants-covid-19 Published: 2020-09-10 09:49:00 Description: Are you going to pick up research with human participants again? Here are some useful tips to ensure safety and hygiene in a corona-proof lab. The COVID-19 outbreak and resulting pandemic has had a big impact on all of us. Many adjustments in our daily life and work were necessary and have been made. Some were easy to accomplish, while others took more effort. Labs closed, projects were put on hold, we had to work from home in order to keep physical distance from each other, and the circulating virus may have created uncertainties about our own health and that of our families. Particularly the physical distance made many things impossible. In some cases experimental data were lost because of the interrupts. Resuming research with human participants We are now a few months later, and although a lot of research work could continue using a site license, we feel that the need to do experiments in a physical lab again is growing. Luckily, restrictions have slowly been lifted, but the questions remains how to safely conduct an experiment with human participants nowadays? What needs to be done differently? What should you pay extra attention to and how to accomplish that? How can you set up a corona-proof lab? Safety and hygiene in a corona-proof lab First of all, it is important to assure that the research activity or experiment really needs to be done in the lab. Describe why it can't be done remotely and how the activity will be conducted in a manner that will meet safety requirements. Make sure participants complete questionnaires at home as much as possible. When participants are invited to come to the lab, make sure you can offer safety and hygiene surrounding corona before, during, and after the experiment. Always follow any guidelines or instructions from the specific facility (e.g. college, hospital, clinic) where the participant interaction would occur. Before the experiment - Plan well if several participants are invited to come to the lab on the same day. Make sure they do not have to run into each other or congregate at the research site. - Participants should fill in screening questions to identify any COVID-19 related symptoms, exposure to COVID-19 via close contact with others diagnosed with COVID-19, or air travel and/or travel to a country/state with a recommended quarantine period. Participants who do not "pass" the screening process will not be able to participate in studies until the conditions are met. - Close access to common areas where possible (e.g. waiting areas, staff break areas). - Position equipment and seats and tables in a way to allow for at least 1.5 meters (6 feet) of distance. - Both researchers and participants should wash their hands before the experiment starts. During the experiment - Make sure the lab space is properly ventilated. - Maintain physical distancing wherever possible, for example make sure you enter the experiment room separately. - The researcher should wear disposable gloves, a facial covering, and safety glasses (if necessary), when physical contact with the participant is required. For example, when attaching a sensor. After the experiment - Both researchers and participants should wash their hands again. - Clean all the equipment, such as devices, chairs, computer mice and keyboards, and even pens after the experiment is over. Flexible lab setup Social distancing measures are likely to persist for several months. The best way for researchers to be able to continue collecting their research data, is to observe one participant at a time, or dyads of the same household. This way the requirements for social distancing are met. Especially if the researcher can give the instructions from outside the observation room. For example, the software Viso provides the Push-to-Talk functionality. With this software feature you can give the participants live feedback from outside the room they are in, using the built-in Push-to-Talk button in Viso. You do not have to meet at a close distance. Besides, with Viso, you can remotely start and stop recording and play back and annotate the recordings from your own device. There is no need to share computers in the lab with others, eliminating the need to clean this equipment and saving time. The Viso Web App allows you to join sessions from outside of the Viso lab and to involve stakeholders, allowing them to join the session from their own desk. FREE WHITE PAPERS How to build a research lab Do you want to learn more how to set up a research lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download 3 free 'how to' guides! Submit to download Portable observation lab If inviting participants to a stationary lab is not possible, but your research requires observing human subjects, the portable observation lab is the answer! It is more flexible, contains less equipment to install and thus to clean, and it enables you to do research on-site, in the natural environment of the participants. A portable lab can be set up in under 10 minutes: - Open the suitcase - Set up your lab equipment - Plug in and start to record When your study involves multiple participants, who need to keep physical distance, it can be difficult to properly record the audio of all participants. Noldus supplies the Sennheiser microphone (type MEB 114-s b) along with the portable lab to solve this problem. It guarantees excellent speech accuracy. After recording, all videos can be stored using Viso software, which ensures for a safe storage and offers the possibility to use the portable lab immediately for new recordings. Take appropriate steps to eliminate risks The novel coronavirus that causes COVID-19 will keep on going. COVID-19 remains a risk until effective treatments and vaccines are widely available. No one can predict how long restrictions will last. This causes a lot of uncertainty. Therefore, researchers performing research with human subjects must inform participants of the risks of COVID-19 that might be encountered due to the research, and take appropriate steps to mitigate these risks. References - https://www.cmu.edu/coronavirus/researchers/index.html - https://bmslab.utwente.nl/research-with-human-participants-becomes-possible-again/ - https://www.research.uky.edu/office-research-integrity/covid-19-research-faqs#Precautions - https://humanresearch.gwu.edu/covid-19 --- ## Decoding memories during day and night URL: https://noldus.com/blog/decoding-memories-during-day-and-night Published: 2020-09-03 13:00:00 Description: Unraveling the role of protein synthesis in memory storage across the day and night in a mouse model - how researchers are gaining insights into sleep deprivation and its consequences. Today we have a guest article by Frank Raven, who just finished his study on the effect of sleep deprivation on memory and plasticity at the Groningen Institute for Evolutionary Life Sciences (GELIFES). His thesis describes a series of experiments to characterize specific changes in the brain and how this helped him gain insights into sleep deprivation and the underlying mechanisms. In the future, Frank hopes to further his research on the neurobiology of sleep. Congratulations with your thesis, Frank, and thank you for contributing to the Noldus Behavioral Research Blog! Day and night rhythms in memory processing Human beings and most other species of the animal kingdom have the fundamental ability to form, store, and later retrieve memories. Memory processing is very delicate can be affected by many different factors. One of those is day and night rhythmicity. Such a rhythmicity can arise from rhythmic variation at the cellular, neurobiological level, or behavioral level, for example from alternation between sleeping and waking [1, 2]. The latter raises an important point as it is challenging to separate the time-of-day effects on memory storage from changes in the sleep/wake cycle. Moreover, sleep by itself is also very important for proper memory function [3]. Nevertheless, a study published in 1998 showed that the production of new proteins during the first hours of the night is crucial for memory formation [4]. Other studies have shown that the level of certain proteins that are important for memory formation also show a day and night rhythm [5, 6]. Protein synthesis and information storage It was not yet clear whether the day-night differences in the basal values of those proteins mean that the storage of new information also differs between day and night. Therefore, we investigated whether protein synthesis inhibition affects memory consolidation differently during the day and night. Why mice? Mice were used for this project, as they go through the same sleep stages as us, and the structure of their hippocampus – a brain region crucial for memory processing – is also quite similar. It is important to note that, like other nocturnal animals, mice are active when it is dark and passive when it is light. During this experiment half of the animals were tested in the beginning of the dark (active) phase, and the other half at the start of the light (inactive) phase. How to study memory in mice? To study memory, we trained mice in a fear conditioning cage using the Noldus/Ugo Basile Fear conditioning setup. Using a hippocampus-dependent contextual fear conditioning protocol, mice had to learn to associate an unpleasant event (a very mild shock) with the neutral context (the fear conditioning cage) [7]. Half a minute after a mouse was placed inside the cage, we programmed EthoVision XT software to deliver a 2-second mild electric shock to the mice. After two more minutes, the mouse was returned to its home cage. Twenty-four hours later, the mouse was placed back into the fear conditioning cage and we tested if the mouse formed a contextual fear memory. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Measuring freezing behavior During the training and test session, we measured freezing activity, which is defined as the complete lack of movement (except for respiratory behavior) and determined using EthoVision XT software. When the animals have made an association between the negative experience (the shock) and the context (the cage), they show this typical freezing behavior, which is the indicator for learning and memory processes. We also measured freezing during the training sessions to measure baseline freezing levels, which are generally very low. Inhibition of protein synthesis during the day and night Immediately after training, mice were injected (subcutaneously) at various times with anisomycin, a protein synthesis inhibitor, or with physiological saline as a control. Mice tested in the light (inactive) phase showed less freezing after injections of anisomycin at times T0 (immediately after training), T4 (4 hours after training) and T8 (8 hours after training). Mice injected at T12 (12 hours post-training), however, showed as much freezing as the control animals and were thus able to remember the association. Proteins matter for the storage of memories From this we can conclude that immediately, until at least 8 hours after the training in the light phase, the production of new proteins is important for the storage of contextual fear memories. Surprisingly, we found the same results for mice trained in the dark (active) phase. Also, there appeared to be no differences in this respect between male and female mice. Thus, these data show that protein synthesis plays an important role in memory storage immediately after a learning task up to 8 hours later. Moreover, not all underlying mechanisms of memory storage differ between day-time or night-time learning [8]. Insights into the dynamics of memory consolidation across the day and night is crucial for all studies that aim to elucidate the underlying molecular mechanisms of memory storage. Future studies should investigate whether other molecular processes regulating memory storage (for example transcription, translation, and ubiquitination), follow a day and night rhythm. Lastly, technological advances allow for more sophisticated approaches (e.g., optogenetics) and may answer questions such as how, and when, certain memories are formed and preserved in time [9, 10]. References - Snider, K.H., K.A. Sullivan, and K. Obrietan, Circadian Regulation of Hippocampal-Dependent Memory: Circuits, Synapses, and Molecular Mechanisms. Neural Plast, 2018. 2018: p. 7292540. - Abel, T. and K.M. Lattal, Molecular mechanisms of memory acquisition, consolidation and retrieval. Curr Opin Neurobiol, 2001. 11(2): p. 180-7. - Abel, T., et al., Sleep, plasticity and memory from molecules to whole-brain networks. Curr Biol, 2013. 23(17): p. R774-88. - Bourtchouladze, R., et al., Different training procedures recruit either one or two critical periods for contextual memory consolidation, each of which requires protein synthesis and PKA. Learn Mem, 1998. 5(4-5): p. 365-74. - Eckel-Mahan, K.L., et al., Circadian oscillation of hippocampal MAPK activity and cAmp: implications for memory persistence. Nat Neurosci, 2008. 11(9): p. 1074-82. - Jouffe, C., et al., The Circadian Clock Coordinates Ribosome Biogenesis. PLOS Biology, 2013. 11(1): p. e1001455. - Phillips, R.G. and J.E. LeDoux, Differential contribution of amygdala and hippocampus to cued and contextual fear conditioning. Behav Neurosci, 1992. 106(2): p. 274-85. - Raven, F., et al., Elucidating the role of protein synthesis in hippocampus-dependent memory consolidation across the day and night. Eur J Neurosci, 2020. - Ryan, T.J., et al., Memory. Engram cells retain memory under retrograde amnesia. Science, 2015. 348(6238): p. 1007-13. - Tonegawa, S., et al., Memory engram storage and retrieval. Curr Opin Neurobiol, 2015. 35: p. 101-9. --- ## CatWalk XT: Valid tool for objective gait analysis in TBI mice model URL: https://noldus.com/blog/gait-analysis-tbi Published: 2020-08-25 09:00:00 Description: Many people suffer from TBI and consequently also long-term gait and motor function deficits. For this reason, functional outcome became the focus when developing new treatment strategies for TBI. Researchers all over the world are conducting studies to better understand the lasting effects of Traumatic Brain Injury (TBI), and develop treatments and therapies associated with the best outcomes in people who suffer from this type of injury. Up until now, medical treatments that showed a promising neuroprotective effect in animal models unfortunately did not translate to a successful therapy in clinical trials in humans. With this in mind, an important question arises: How could we improve this? Translation of experimental results into the clinical practice In order to enhance the outcomes of research on animal models, a pre-clinical drug-screening consortium for TBI was established: Operation Brain Trauma Therapy. The latter reevaluates potential neuroprotective drugs in animal models of TBI by investigating drug effect on different pathophysiologic aspects of traumatic brain injury. However, there is another important aspect that would help to improve this translation further: precise and objective evaluation of functional outcome in experimental models. Traditional clinical tests and their limitations One of the most frequently used animal models of TBI is the Controlled Cortical Impact (CCI) model. Mice with CCI show relevant gait impairment and deficits in motor function, just as people with traumatic brain injury do. Even though this is one of the most commonly used animal models, objective and valid assessment of gait and motor function is difficult when using traditional clinical tests like the rotarod, beam walk, grid walk, the cylinder test, etc. All those tests have several limitations: - They are subjective (observer dependent) - They use force or reward in order to make animals move - They can only detect gross deficits of motor function and gait - They are performed in surroundings that are usually creating an insecure and stressful environment for the animals, which results in animals trying to hide their gait deficits Lastly, most of the TBI injuries in mouse models are of moderate intensity. The tool used for assessing gait must thus be able to detect subtle changes of gait and locomotion. Ways to improve gait analysis research In order to tackle the limitations of traditional tests, Walter et al. (2020) decided to evaluate the gait analysis system CatWalk XT, which is developed for automated and objective assessment of gait and locomotion in rodents. In contrary to the traditional tests, rodents are allowed to move voluntarily, without force. While they freely traverse a glass plate, high-speed camera captures their footprints and body weight distribution. In their study, Walter et al, (2020) used a CCI mouse model, and examined more than 100 different spatial and dynamic parameters that are automatically analyzed by mentioned device. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Establishing a gait and locomotion phenotype of CCI mice Researchers gathered data on day one, three, and seven after the Controlled Cortical Impact in their mice models. Mice had to perform at least three compliant runs for CatWalk XT analysis, and in most cases, only three runs in total were sufficient to obtain them. There was no set time limit to complete each individual run, while maximum speed variation was set on 60%. It is worth mentioning that average Run Maximum and Body Speed Variations were similar or even lower than in other studies where they set a maximum speed variation under 30%. Automation and elimination of human error improves gait analysis After collecting the data and running the analysis, Walter et al. (2020) concluded the following: - CatWalk XT is an objective tool, limiting observer intervention to a minimum - Automatic data collection and analysis save a lot of time and does not result in reduction of data quality - When using CatWalk XT, reproducibility of data improves due to automation and elimination of possible human errors - CatWalk XT detects very subtle yet significant impairments which are otherwise impossible to detect by human observation "The CatWalk XT® is very well applicable to animals subjected to CCI and generates well reproducible data." Walter et al (2020) | In Behavioural Brain Research Important steps in the development of new treatment for TBI There is a growing population of people with traumatic brain injury and poor gait prognosis and functional outcome. Many of them suffer from gait and motor function deficits for decades after the injury and unfortunately, there is still no effective therapy to help them. For this reason, functional outlook became the focus when developing new treatment strategies for TBI. In order to improve translation from medical treatments that showed a promising neuroprotective effect in animal models, to a successful therapy in clinical trials in humans, precise and objective evaluation of functional outcome in experimental models is crucial. Further research on laboratory animals using a valid, accurate, and observer independent tool, such as CatWalk XT, is thus necessary. Literature Walter, J., Kovalenko, O., Younsi, A., Grutza, M., Unterberg, A. and Zweckberger, K. (2020). The CatWalk XT® is a valid tool for objective assessment of motor function in the acute phase after controlled cortical impact in mice. Behavioral Brain Research, 392. --- ## Alexa, Siri, Google – Are voice assistants the future of marketing? URL: https://noldus.com/blog/voice-assistants-future-of-marketing Published: 2020-07-28 13:45:00 Description: Voice assistants – they are found in almost every aspect of our daily lives. Elaine Mathe studied how users interact with voice assistants and what emotions they show in response to played ads. This is a guest blog post by Elaine Mathe. Elaine used FaceReader during her study about voice assistant marketing. Enjoy reading! Alexa, Siri, Google – Are voice assistants the future of marketing? Voice assistants – they are found in almost every aspect of our daily lives. Asking Siri about the weather, telling Alexa to play music, and setting a reminder simply by saying 'Hey, Google'; while these interactions might have seemed strange in the beginning, they have become the norm these days as the growing number of voice assistant users suggests [1]. With more active users, the marketing potential of these digital assistants increases [2] alongside the uncertainty about the new communication tool [3]. Voice assistant marketing? Yes! But how? Little research has been done on this topic [4] particularly with regard to user acceptance, so there are still considerable gaps in knowledge in this field. Methodology To address this issue, I have designed a study with the objective of assessing the user's acceptance of voice assistant advertising within the human-machine interaction. The applied methodology was based on a mixture of experimental and quantitative methods. Since the implicit approach measured the autonomic responses to voice assistant marketing, it was of particular relevance in this study. The explicit approach however was used to apply existing models and to verify the results generated by the experiment. Experiment – Autonomic Measures The experiment carried out involved 25 participants of which 13 were in the experimental group and 12 in the control group. The participants were asked to perform a prescribed interaction with a veiled voice assistant. The experimental variation was achieved by manipulating the answer given by the voice assistant. In the case of the experimental group, as a reply to the question 'Computer, what is the distance from Berlin to Hamburg?' the voice assistant played a promotional message before giving the informative reply. However, the assistant of the control group did not use manipulation and responded with the regular phrase 'From Berlin, Hamburg is 285.3 kilometers away by car.' Facial expressions were recorded in both groups during the interactions and later on translated into emotions using the analyses software FaceReader 8, which is amongst others based on the Facial Action Coding System by Paul Ekman and Wallace Friesen. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Survey – Self-Reports Following the interactions, the participants were asked to take a short survey. The first part of the survey focused on the self-report of emotions felt while interacting with the voice assistant. The design of the second part of the survey used with the experimental group was based on the cognitive-affective model of Christina Olarte-Pascual et al [5]. Outcome and Conclusions The results demonstrated that participants in the experimental group showed more positive emotions compared to the control group. This can be supported by the outcome of the survey. However, only 38% of the participants that received the promotional message indicated that they are willing to accept listening to advertising on voice assistants in the future. The acceptance within the control group was only half as much. This supports the hypothesis that positive emotions have a constructive impact on the attitude towards voice assistant marketing, which eventually leads to its acceptance. Thanks to the conducted survey, it was proven that the perceived usefulness of advertising on voice assistants and positive emotions towards voice assistant marketing, positively affects the attitude towards it. Equally, negative emotions towards voice assistant marketing have a negative impact on the attitude towards it. Additionally, the results showed that positive attitudes towards advertising on voice assistants positively affect the intention to receive it. Emotional responses towards voice assistant marketing The study demonstrates that users are still hesitant when it comes to advertising during the interaction with voice assistants. However, voice assistant marketing – if done properly – can have fairly positive effects on user acceptance. Hence, it is time for companies to take first steps in this direction. When doing so, it is of particular relevance to consider the specifics that the voice assistant marketing implies. Due to the intimacy of the human-machine interaction, advertising on voice assistants should focus on need-oriented communication only [6]. Classic campaigns won't work and disturbing advertising should be avoided to prevent triggering bad emotions. Instead, companies should focus on producing personalized, dialogue- and need-oriented communication that creates value for their customers [7]. Elaine Mathe | elainejasmin@gmx.de | Photo credits: Anita Bresser References - cf. Statista, usage of voice assistants worldwide, 2016. - cf. Hörner, T., marketing with voice assistants, 2019, p. 50; cf. Kollhorst, B., Alexa, 2019, p. 187. - cf. Hörner, T., marketing with voice assistants, 2019, p. V. - cf. Hörner, T., marketing with voice assistants, 2019, p. V. - cf. Olarte-Pascual, C. et al., Cognitive-affective Model of Acceptance, 2016, p. 134 –148. - cf. Hörner, T., marketing with voice assistants, 2019, p. 63. - cf. Hörner, T., marketing with voice assistants, 2019, p. 61 ff. Bibliography Gentsch, Peter (ed.): Künstliche Intelligenz für Sales, Marketing und Service. Mit AI und Bots zu einem Algorithmic Business – Konzepte und Best Practices, 2. Aufl., Wiesbaden: Springer Gabler, 2019 Hörner, Thomas: Marketing mit Sprachassistenten. So setzen Sie Alexa, Google Assistant & Co strategisch erfolgreich ein, Wiesbaden: Springer Gabler, 2019 Kollhorst, Bruno: Showcase: Aus Alexa wird Relaxa – Schulterblick in die Entwicklung des Skills „Smart Relax" der Techniker Krankenkasse, in: Gentsch, Peter (ed.), Künstliche Intelligenz für Sales, Marketing und Service. Mit AI und Bots zu einem Algorithmic Business – Konzepte und Best Practices, 2019, p. 186–198 Olarte-Pascual, Cristina, Pelegrín-Borondo, Jorge & Reinares-Lara, Eva: Cognitive-affective model of acceptance of mobile phone advertising (2016). Ekonomie a Management, 19 (4), 134– 148, http://dx.doi.org/10.15240/tul/001/2016-4-010 Statista: Anzahl der Nutzer virtueller digitaler Assistenten weltweit in den Jahren von 2015 bis 2021 (in Millionen), (2016) --- ## Simulation-based training in times of crisis URL: https://noldus.com/blog/simulation-training-improving-response-coronavirus Published: 2020-07-23 10:48:00 Description: Simulation can be a useful tool in the development of new standard operating procedures and policies needed to respond to crises like COVID-19. The coronavirus has greatly affected our lives and our work the last few months. The pandemic that began in March 2020 put high pressure on hospitals, emergency services, and healthcare institutions, among others. The coronavirus is still wandering and continues to cause infections. Can simulation-based training play a role in preparing for another outbreak or other similar crises? Why organize simulation-based trainings in times of crisis? Researcher Dieckmann and his team published an article in the journal Advances in Simulation in which they describe the potential of simulation to prepare and improve hospital responses to outbreaks like COVID-19. Practice through simulation can reduce the cognitive load of the staff involved in patient care, thereby helping to reduce errors in times of pressure and exhaustion. Moreover, findings from such training sessions can help in identifying and shaping learning goals, staff preparedness, improving systems and protocols, and ultimately patient safety. According to the authors, simulation can play a role within several layers: - 1. Educational: the (re) qualification of personnel For example by focusing on infection prevention for healthcare professionals, dealing with an agitated COVID-19 patient, and ensuring clear leadership and followership roles where needed. - 2. System: understand and optimize workflows, bottlenecks, dependencies For example by focusing on optimizing the layout and equipment available, testing systems and improving processes, optimizing flow of patients, or dealing with the lack of equipment. - 3. Personal: dealing with the emotional strain of the situation All staff should informally share experiences and consider ways to keep healthy. When conducting simulation-based training sessions, a feeling of safety is very important, especially in this setting, as participants may be very anxious and overwhelmed by the protocols and guidelines. Preparing, running, and debriefing simulation sessions Simulation can be a useful tool in the development of new standard operating procedures and policies needed to respond to crises like COVID-19. Besides preparing and running the simulations, debriefing the sessions is central to learning as well. Debriefing facilitates recall and insight, clarifies learning points, builds trust and self-confidence, and improves (team) performance. Using a video feedback tool, such as Viso, to create and play back audio- and video recordings of the simulation sessions, allows adding feedback with personalized markers. While playing back the recordings during debriefing, participants will realize what happened, discuss marked events, and consequently gain deeper insight. The debriefing can also be used to inform relevant others in and beyond the organization about the findings. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo Improve the response The tables included in the article of Dieckmann et al. provide an extensive overview of areas to focus on, learning goals, target groups, methods, and practical considerations to conduct simulation sessions and improve the response to infectious disease outbreaks like COVID-19. Because of the infectiousness, extra attention should be paid to prevent contamination, such as using personal protective equipment, clarifying routines, and which equipment to use and which not. The use of personal protective equipment, such as a face mask, reinforces the need for teams to communicate very clearly. By wearing a mask, is will be less clear what people say and it will disrupt lip-reading and the understanding of facial expressions. Advance team performance and self-confidence Simulation-based team training will improve team preparedness so that caregivers can treat patients safely and self-confidently. Running the scenarios support practicing core skills and develop know-how to control the emergency. Reference Dieckmann,P.; Torgeirsen, K.; Qvindesland, S.A.; Thomas, L.; Bushell, V. & Ersdal, H.L. (2020). The use of simulation to prepare and improve responses to infectious disease outbreaks like COVID-19: practical tips and resources from Norway, Denmark, and the UK. Advances in Simulation, 5 (3), https://doi.org/10.1186/s41077-020-00121-5 --- ## The eyes have it: face masks and non-verbal communication URL: https://noldus.com/blog/eyes-important-part-communication Published: 2020-07-14 11:40:00 Description: When seeing another person wearing a face mask, humans have to rely on visible facial signals, which are the eyes and eyebrows. Looking someone in the eye is an important part of communication. It is safe to say that the coronavirus pandemic has changed our world, in many different ways. As I write this (July 2020), in The Netherlands, restrictions continue to be lifted, but we must still adhere to socially distancing from people not from our own household and wear face masks on public transport and other situations in which you cannot maintain a distance. How does wearing face masks affect communication? As a trainer & consultant at Noldus IT, I spent the last 4 months in my home office doing remote training courses instead of traveling the world. It turned out that technically it is perfectly fine to remotely explain how our behavioral observation systems work. PRODUCT OVERVIEW Behavioral research solutions Download our free product overview and find out which Noldus products are suitable for your research. - Divided into research areas - Find the solution for your research - Trust our 30 years of experience Download However, as many people have experienced using programs such as Zoom, Teams, or Skype, it changes the way we are able to communicate compared to meeting someone in the flesh. It made me also wonder how wearing face masks affects communication. Last week, I got first-hand experience with this as I went to Antwerp, Belgium, to do my first on-site training course since 4 months. Because the room in which the DanioVision system was set up was too small to keep the social distance of 1.5 meters, we all had to wear face masks. Communication is vital Two factors in a training course are important to me: the technical side of things, and the social/communicative aspect. Technically, I want to make sure that at the end of the training day the customer understands what the system can do for her and that she is able to acquire good quality data. But the social aspect is also important: I want the training to be a pleasant experience and for this communication is vital. But with half of our faces covered, would we still be able to communicate properly? Visible facial signals When facing (pun intended) another person wearing a face mask, humans have to rely on facial signals that are visible, which are the eyes and eyebrows. Looking someone in the eye is an important part of communication (however, it is also important to occasionally look away because a strong gaze can be perceived as threatening), and sets off all kind of brain processes. Our body also produces a chemical called phenylethylamine that evokes a sense of connectedness when the brain grapples with the overwhelming awareness that we are looking at another conscious being. Sense of closeness Could this sense of closeness be experimentally elicited? This is what Arthur Aron, a social psychologist, decided to study in the late sixties. He and his wife Elaine developed three dozen questions to create closeness in a lab setting. On top of this, after going through the questions, some people tried to look each other into the eye for a couple of minutes to corroborate this closeness. This might mean that the unexpected consequences of having to wear masks, during these sometimes challenging times, are greater empathy and compassion between humans. Did I fall in love during the training course in Belgium? I did not, but I certainly experienced a sense of closeness that I probably would not have felt to this extent when I hadn't worn a face mask. Of course, the fact that this was the first real-life meeting (for me and the customer) in a long time, also made this a special occasion. I'm looking forward to the next masked session. References https://www.nytimes.com/2015/01/09/style/no-37-big-wedding-or-small.html https://www.nytimes.com/2015/01/11/style/modern-love-to-fall-in-love-with-anyone-do-this.html --- ## How to unravel the long-term memory of cuttlefish: automated video tracking URL: https://noldus.com/blog/video-tracking-cuttlefish Published: 2020-07-13 13:00:00 Description: Did you know that cuttlefish have three hearts, have such an advanced vision that they can see what’s behind them, and can count to five? Did you know that cuttlefish have three hearts, have such an advanced vision that they can see what's behind them, can count to five, and that males can make half of their body colorful to attract females and display subdued female colors on the other half of to avoid competition with other males? [1] Amazing creatures, right? Intelligent little creatures And there is more. Cuttlefish are intelligent; they are able to learn. When they know that their favorite food will be 'served' in the evenings, they will eat less of the less tasty food during the day [2]. They also learn to stop chasing a prey when they can see it but are unable to reach it [3]. That is what this article is about. RESOURCES Read more about DanioVision Find out how DanioVision is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Interesting model for behavioral research Now why is this interesting? Cuttlefish resemble vertebrates in several ways and they are small. This makes them suitable as a model in behavioral studies. Like vertebrates, they have a centralized nervous system and a highly evolved vision. That makes research on their memory so interesting. Automating predator-prey research But isn't behavioral research extremely labor intensive? Well, yes, but there is where automation comes in. And that is what Jessica Bowers [3] and her colleagues did. They used DanioVision, Noldus' high-throughput video tracking tool that was originally developed for zebrafish larvae. They used well plates with six relatively large wells. Each well contained a tiny transparent tube in which they could place a shrimp, which is the cuttlefish' favorite prey. With this setup, they measured the behavior of six juvenile dwarf cuttlefish towards their prey, simultaneously and automatically. Using the nose-tail algorithm in EthoVision XT, they measured whether the cuttlefish' head was in the zone surrounding the tube with the shrimp. This way they could tell how long the cuttlefish showed interest in their prey. Long-term memory experiments The authors showed that the cuttlefish can learn and that they adapt their predatory behavior when they cannot reach their prey. This movie [4] clearly shows what that predatory behavior looks like, first attention, then body orientation towards the prey, and finally the strike with the tentacles. The authors found out that when prey was present in the transparent tube, the cuttlefish moved more and longer. They remained oriented towards the shrimp, but gradually stopped the strikes with their tentacles to catch it, because they learnt they could not access it. Four days later, these strikes were still almost absent, while in a control group the number of strikes was as high as before. This way, the authors demonstrated that these tiny invertebrates have a long-term memory. Conclusion The authors conclude that they were successfully able to automate memory studies with these tiny creatures. They mention that DanioVision enabled them to analyze behaviors that they would not have been able to measure by direct observation alone. The size of the dwarf cuttlefish larvae and the fact that they show many adult behaviors already in early stages of their development, makes them very well suited for high-throughput behavioral studies with DanioVision. This is all very promising regarding automated behavioral essays with a model animal. References - https://www.mnn.com/earth-matters/animals/blogs/5-amazing-facts-about-strange-beautiful-cuttlefish - Billard, Pauline, et al. "Cuttlefish show flexible and future-dependent foraging cognition." Biology Letters 16.2 (2020): 20190743. https://doi.org/10.1098/rsbl.2019.0743 - Bowers, Jessica, et al. "Evidence of learning and memory in the juvenile dwarf cuttlefish Sepia bandensis." Learning & Behavior (2020). https://doi.org/10.3758/s13420-020-00427-4 - https://www.youtube.com/watch?v=XlhCOYS2GJ8 --- ## The Internet of Things, LoRa, 5G, and measuring behavior URL: https://noldus.com/blog/internet-of-things Published: 2020-07-02 10:00:00 Description: New techniques for connecting sensors will provide opportunities for researchers measuring behavior. When the pioneers of behavioral science, Karl von Frisch, Konrad Lorenz, and Niko Tinbergen did their research which would result in their Nobel Prize in 1973, more or less the only tools they had available to help them was a notebook and pencil. Later, such research was supplemented by video cameras and computer-aided observation (the basis of The Observer XT from Noldus). In recent years a whole load of new sensors have come onto the market which can measure all sorts of things about the subjects of such research including their position, fine movements, physiology, gaze, muscle movements, brain activity, and levels of chemicals like glucose and hormones. Sensor measurements have three main advantages over pure observations; they are completely objective, they save a lot of time, and they can measure things which you cannot measure just by looking. Field observations There is one aspect to measuring with such sensors which, until very recently, meant that they were less flexible than observations; they needed to be connected to a computer, either directly, or with a wireless protocol like Bluetooth or Zigbee. In practice this meant that they needed to be within a few meters of the computer. Tinbergen describes his work in the book Curious Naturalists (downloadable here), which makes fascinating reading. He spent hundreds of hours making detailed observations in diverse places including the inland dunes on the Veluwe in the Netherlands and in the hostile climate of Greenland. Even today those places are too remote to think of using sensors connected directly to a computer. Of course there are some workarounds; sensors can write the data to memory cards which can be periodically retrieved and there are even special (but expensive) satellite channels reserved for this sort of data. In theory mobile phone networks could be used for that sort of application, but they are currently too energy-hungry to really work well for long-term sensor data transfer. IoT The game-changer in this field is the upcoming development of the Internet of Things (IoT). In the IoT, not just computers and phones, but all sorts of other devices can be connected to the internet. Current applications include strain monitors on bridges so that they are continually monitored instead of waiting for the next expensive manual inspection, monitoring the health status of patients recuperating at home, and giving passengers information about how full trains are so they can plan their journeys accordingly. Future applications currently being worked on will include things like traffic lights informing self-driving cars that they are changing to red and a farmer being automatically notified if one of his or her cows don't have optimal health or welfare. LoRa One of the links in the technology chain that is currently being improved, is how to get the information from the sensor to the internet. Many sensors only produce a small amount of data, but they might be a long distance from the nearest computer. Especially for this scenario, the LoRa protocol has been developed. LoRa is short for Long Range and it is designed to send a small number of bytes of data, at most a few times an hour, up to 10 km. The sensors are typically battery operated, low cost, and designed to last in the field for over ten years. Typical applications are water and gas metering, and smart parking. In some countries LoRa connectivity is available from telecom providers, but it is also not difficult to set up your own LoRa network if you know what you are doing. GPS Those specifications mean that LoRa can also be suitable for certain types of sensors which are used to measure behavior. For instance, in the GenTORE project, Noldus' engineers have implemented LoRa support into a GPS tracking tag which is designed for larger animals like cows and includes a built-in solar panel to power it for a long time period. The engineers also implemented a prototype of this solution for a temperature sensor used to monitor the health status of cows in another project, VetBioNet. In that case, the cows were living in a secure veterinary bio contained research facility. If it wasn't for the LoRa connection, the scientists would have to dress in biohazard suits and undergo decontamination (a big time-consuming hassle) just for a simple task like measuring the temperature of the animal. In this case the LoRa antenna could simply be attached to a laptop, making it a very practical solution. 5G Noldus' work with LoRa has shown it to be very suitable for its intended purpose; long distance transmission of low frequency data. However, some sensors produce a lot of data or it can be very important that none of the data is lost, or real-time communication might be needed. A typical example of that would be applications related to safety in traffic or remote control of heavy machinery in hazardous environments. For those sorts of uses, 5G is being developed. 5G is mostly known as the network standard which will give much higher speed internet access to mobile phones than the current 4G network. It will use several frequency bands, some of which are new for cell phone communication (30 to 300 GHz). There is some concern about the new frequencies, but in fact they are already in use for many other applications, including airport security scanners, anti collision radar for cars, and to link present-day cellular base stations. However, in addition to the high speed internet, 5G will include protocols for very robust and fast (low latency) connection to sensors and the internet, which could provide interesting possibilities for the future. But, for the coming few years, LoRa will remain a very attractive solution for transmission of behavioral data acquired with sensors. RESEARCH PROJECT Want to partner with us? If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 35+ years of experience Learn more Acknowledgements VetBioNet is funded by the Horizon 2020 program of the European Union, project number 731014. The GenTORE project is funded by the Horizon 2020 research program of the European Union under grant number 727213. --- ## Learning how to use software for video tracking in animals URL: https://noldus.com/blog/learning-software-for-video-tracking-in-animals Published: 2020-06-30 12:00:00 Description: A couple of months ago, we had the pleasure to visit the University of Groningen to record a customer success story. A couple of months ago, we had the pleasure to visit the University of Groningen to record a customer success story. Over 2000 sites around the world work with video tracking software EthoVision XT and we regularly visit customers to see how they use this software in their research or education. Today, I would like to share how EthoVision XT helps young researchers to learn more about behavioral testing in a practical course. University of Groningen, The Netherlands As a professor in developmental behavioral neuroscience, Jocelien Olivier works at the University of Groningen, at the GELIFES Institute. In the minor Neuroscience, she and her colleagues show students what neuroscience is all about. For example, she wants students to get in touch with 'how do we score behavior'. Practical 'Tracking behavior' with EthoVision XT During the practical 'Tracking behavior', the students analyze movies of completed open field experiments in EthoVision XT and investigate whether treatment with fluoxetine increases the anxiety levels in the offspring rats. Read more about the study of Jocelien Olivier here. She enthusiastically explains: "Our students are using EthoVision XT during their practical. The software is easy to handle, the students explore how they can use the program. In the end we always hear that they really like this practical." Using EthoVision XT as an educational tool EthoVision XT is the perfect tool to train your students in doing behavioral tests. Jocelien Olivier has particularly good experiences with this, as you could see in this movie! If you think about organizing a practical with EthoVision XT yourself, please feel free to download the educational materials from our website. Jocelien Olivier was so kind to share a presentation, practical, background story, and practice videos with the research community. These work in perfect combination with the EthoVision XT free trial you can download for your student computers. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Teach what video tracking animals is Video tracking means detecting an animal in a video file or from a live video feed, distinguishing it from its background, and tracking its whereabouts and movements. Explaining the theory in a (virtual) classroom is great, but showing the technique and allowing students to see the results from an experiment themselves really adds to the learning experience. In addition to tracking, EthoVision XT can also detect activity changes at pixel-level, ideal for studying behaviors such as freezing. You can also manually or automatically score behavioral events, such as rearing or grooming. In the neuroscience classroom, the integration between methods and techniques can be of great value to the students. --- ## CFI Exceptional Opportunities Fund – COVID-19 URL: https://noldus.com/blog/cfi-exceptional-opportunities-fund-covid19 Published: 2020-06-29 14:00:00 Description: The Canada Foundation for Innovation (CFI) has issued an Exceptional Opportunities Fund (EOF) in the fight against the coronavirus SARS-CoV-2, known as COVID-19. The Canada Foundation for Innovation (CFI) has issued an Exceptional Opportunities Fund (EOF) in the fight against the coronavirus SARS-CoV-2, known as COVID-19. Through this EOF, the CFI will invest up to $25 million to support equipment for ongoing research related to COVID-19. Unlike other competitions, this particular EOF will cover up to 100 percent of the eligible costs of a project! The deadline for proposal submission, Monday, July 6, is approaching rapidly. Fortunately, Noldus is here to help with your submission. Please join us on Tuesday, June 30, at 1pm EDT, for an informational webinar on Noldus' Grant Assistance Program followed by a presentation of our solutions and tools for the fight against COVID-19. This webinar is open to all; however, it is limited to the first 100 registrants. Program description The threat of infectious disease is on the rise. COVID-19 has proven to be a global concern for humanity and has taken a significant toll on the healthcare system and economy. This global crisis is killing people and increasing suffering throughout the world. In response to this, the CFI launched an EOF competition with the goal of investing up to $25 million to support urgent needs for equipment for ongoing research related to COVID-19. Furthermore, the EOF competition seeks proposals from all disciplines, such as: epidemiology, virology, vaccine development, diagnostics, therapeutic devices, mental health, social and economic policy and public health response. Noldus is here to help Noldus has launched a Grant Assistance Program to help researchers in Canada. We are trained scientists who have experience writing and capturing external funding, as well reviewing manuscripts for scientific journals. We can help review your proposal prior to submission. For example, we can proofread the proposal, help draft the Plain language summary, and/or view the Assessment Criteria through the eyes of a potential reviewer. Alternatively, we can provide the technical specifications of our solutions to include in your Project and Finance Modules. Please join us on Tuesday, June 30, at 1pm EDT, for an informational webinar on Noldus' Grant Assistance Program followed by a presentation of our solutions and tools for the fight against COVID-19. This webinar is open to all; however, it is limited to the first 100 registrants. REGISTER NOW Join our webinar on June 30th Are you interested in joining the informal webinar on June 30th, at 1pm EDT? - Grant Assistance Program - Tools for the fight against COVID-19 - At no costs, max 100. participants Register now Proposal structure Researchers and institutional administrators will use the CFI Awards Management System (CAMS) to prepare, share, and submit proposals. There are three separate CAMS modules: Project, Finance, and Suggested Reviewers. The Project Module should include the following five subsections: Project information, Plain language summary, Researchers, Assessment criteria, and Financial resources. Although all subsections are critical, it is important to detail how the proposal meets the assessment criteria, as each proposal will be evaluated against a standard on the criteria below. The Finance Module has four subsections: Cost of the individual items, Contributions from partners, Infrastructure utilization, and an Overview of infrastructure project funding. Finally, each proposal should identify a minimum of six reviewers who are well-qualified and are not in any conflict of interest. Assessment As noted above, addressing the Assessment Criteria is crucial to success. Proposals will be evaluated on five criteria: Research or technology development, Researchers, Infrastructure, Sustainability, and Benefits to Canadians. In this section, researchers should ask themselves five questions: 1) How will this proposal study the virus in novel/innovative ways? The research/technology development should describe the research related to COVID-19 and its innovativeness and feasibility of fighting the current pandemic. 2) How will the equipment in the proposal aid in ways currently lacking? The infrastructure assessment ascertains the needs of the equipment against the existing structures in place. 3) Who is doing the research and how is s/he qualified to do so? The researcher assessment looks at the qualifications of the researchers in the proposal in terms of his/her previous research record, excellence at the level appropriate for the career stage, technical expertise, and proposal contributions to the success of the project. 4) Does the research in this proposal commit to a sustainable future? The sustainability assessment judges the management plan for the optimal use of resources. This operation and maintenance plan must include any institutional commitment. 5) Finally, how does this help your follow Canadian? The benefit to Canadians assessment evaluates how the results of this research will provide any socio-economic benefits, knowledge mobilization, and/or better training and improved skills for qualified personnel. Register now or contact Jason directly! See the links before for how to join. See you on Tuesday! Can't make it? That's ok, feel free to contact us: Jason Rogers, Ph.D., jason@noldus.com. REGISTER FOR THE WEBINAR Helpful links - EOF: https://www.innovation.ca/awards/exceptional-opportunities-fund-covid-19 - Webinar registration link: https://us02web.zoom.us/webinar/register/WN_NN1aEDs4T0S4CV4Vcmmehw - Grant Assistance Program: https://www.noldus.com/grant-assistance-program --- ## UX / Neuroscience lab in the spotlight URL: https://noldus.com/blog/ux-neuroscience-lab-in-the-spotlight Published: 2020-06-25 12:00:00 Description: After a successful launch in June 2019, the LabUX team has been designated the innovation of the year for the digital transformation at Desjardins. Marie-Laure Di Fabio is a senior User Researcher at Desjardins Group, Canada's leading financial cooperative group. One of my colleagues had the pleasure to meet up with her in Montreal end of 2019 to discuss their UX research and UX / Neuroscience lab. Desjardins Group entrusted Marie-Laure with implementing its new research laboratory, the LabUX. After a successful launch in June 2019, the LabUX team has been designated the innovation of the year for the digital transformation at Desjardins. Congratulations from the Noldus team! UX / Neuroscience lab in the spotlight So what brought about this prize? Let's have a look at this innovative laboratory in Montreal, Canada where they find out what the real user experience is. UX Research at Desjardins Group Desjardins Group aims to offer the best online experience possible. When developing digital solutions like a website or an app, the value for the final customer needs to be maximized. Improving the user experience for end users of any product is key. With feedback from customers collected in the LabUX, Desjardins Group improves this user experience during development. The importance of UX research As a senior User Researcher at Desjardins, Marie-Laure Di Fabio is very aware of the importance of UX research. She played a key role in setting up their new UX lab by evangelizing the importance of taking design decisions based on empirical data gathered by skilled researchers and reliable technologies in a business context. These technologies – nowadays still mainly used in the scientific community – are of great value to corporations. Desjardins Group is constantly innovating to meet the needs of its members and clients and did not hesitate to take the leap forward to enhance its user centric corporate culture. Showing the lab In this video, Marie-Laure Di Fabio tells you about the process of setting up their UX lab and how relying on one go-to partner for all the technologies helped her speed up her research. She explains that: "to have Noldus technology solutions allows you to have a clear understanding of what's happening on the platform". She also puts forward that it is as important to have the trustful data streams as it is to be able to present it: "You should be able to communicate the results, communicate the output of your studies". FREE WHITE PAPER How to build a usability lab Do you want to learn more how to set up a usability lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download --- ## Researching comorbidity in patients with autism spectrum disorder URL: https://noldus.com/blog/comorbidity Published: 2020-06-18 08:00:00 Description: Patients with autistic spectrum disorder also tend to have other disorders like epilepsy. Why is that and how can understanding that help us understand autism? The word 'morbid' in normal English is normally used to mean an unhealthy interest in death and disease, so the medical term comorbidity comes across as rather gruesome. However, medically, 'morbidity' simply means 'of disease' so comorbidity is about diseases occurring together. For some common diseases and disorders, that is a big problem, and made worse by the way that our health care is normally organised, being split up into departments dealing with different diseases separately. In recognition of the magnitude of the problem of comorbidity, the EU put out a call to further research the issue and the CANDY project is a response to that. The scientists in that project are investigating why it is that people with autism spectrum disorder (which I'll simply call autism in the rest of this blog) have ten times the chance of also having epilepsy as the general population does, and that it is even higher if they also suffer from intellectual disorder. Coincidence? If two things occur at the same time, there are three possible explanations. Scientific methodology is fundamentally based on untangling those possibilities. Firstly, it might simply be coincidence. There are amusing websites like Spurious correlations where you can see a strong relationship between clearly unconnected things like per capita cheese consumption and the number of people who died by becoming tangled in their bedsheets. Causal? The science of statistics has largely to do with proving if it is more likely that two things occurring together are coincidence or not. In the case of autism and epilepsy there is such a large number of patients involved that we know it cannot be coincidence. If it is not coincidence, that leaves two possibilities. Perhaps one causes the other. A severe epileptic attack in a young child damages the brain, and autism is a developmental brain disorder. So it is plausible that one causes the other. Theoretically, it could also be the other way around. The biological basis of autism is that children affected by autism have a surplus of synapses, or connections between brain cells. The excess is due to a slowdown in the normal pruning process that occurs during brain development. Although you might imagine that more brain connectivity would be a good thing, in fact it results in decreased processing speed, especially in those parts of the brain related to social interaction. Epilepsy is characterized by too much excitation in the brain, which may stem from too little inhibition, a characteristic of brains with excessive conductivity. Perhaps a different brain structure could make children more susceptible to epilepsy? Common factor? Another possibility is that it could be a common factor which causes both epilepsy and autism, as well as intellectual disorder. There is increasing evidence that this is the case, and that that factor is genetics. For instance, there is a genetic disorder called Fragile X syndrome which causes intellectual disability. It is also the case that about one third of the people with Fragile X syndrome have autism and even those who don't often show autistic traits such as avoiding eye contact. Difficult diagnosis One of the difficulties in puzzling out exactly what the relationship is between epilepsy and autism is that the diagnosis of autism is difficult. Previously four separate categories of autism were recognized (Asperger syndrome being a well-known category) but nowadays these are consolidated into one umbrella diagnosis of "autism spectrum disorder." Many more boys are diagnosed with autism than girls. Is this because more boys have autism or because the tests were developed largely using data from boys? Or are boys more likely to be over-diagnosed because of a changing perception about what 'normal' behavior is? In the US at least, black children, are more likely to have a wrong or late diagnosis for autism: on average, more than a year and a half later than white children. This is mostly due to worse access to health care. In addition, criteria such as returning eye contact could have a cultural bias. To further complicate matters, if a child has autism, that can lead to epilepsy not being diagnosed, due to communication barriers and overlap of symptoms. CANDY All of which indicates the need for research, which will be carried out in the CANDY project. One of the unique features of the project is that in the same project researchers are both using animal models to try and better understand the neuroscience of developing brains with these comorbidities and also clinical studies on patients. It is hoped that by combining the two ways of addressing the problem in one project, that there will be a synergistic effect, with the different teams learning from each other. A lot of the symptoms of autism are about interactions, and the role of Noldus in the project will be developing innovative new tools to study the interactions in animal models. The project as a whole will focus on whether the co-occurrence of symptoms can be explained by combinations of genetic factors and immune activation acting at different 'sensitive periods' during development. Those patients who have a combination of autism, intellectual disability and epilepsy have a reduction in lifespan of about 20 years. The CANDY project aims to generate substantial new insights into the fundamental mechanisms and so ultimately find a way to tackle that problem. PROJECT PARTNER Partner with Noldus If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 30 years of experience Contact us References - Autism diagnosis: Autism Speaks - DSM-5 Criteria - Research in animal models investigating excess connectivity in autism: https://doi.org/10.1016/j.neuron.2014.07.040 - Research in people showing increased connectivity and decreased processing speed in people with autism: JAMA Network Open - Illustrations in this blog post are from Wikipedia commons. --- ## Taking opioids during pregnancy: short- and long-term consequences in rats URL: https://noldus.com/blog/consequences-of-opioids-during-pregnancy-on-rat-pups Published: 2020-06-15 17:00:00 Description: Women worldwide are suffering from opioid addiction. Many receive so-called opioid-maintenance therapy using bup, but consequences for both mother and baby are largely unknown. Throughout the world, many women of a reproductive age are addicted to opioids. When they are pregnant, this could cause severe consequences for the mother, the pregnancy, and the unborn baby. Opioid-maintenance therapy Many undergo so-called opioid-maintenance therapy, despite not all of the consequences being known. A group of researchers from the Wayne State University in Detroit (Michigan, USA) went to find out the short- and long-term consequences of this treatment, testing the drug buprenorphine (BUP) on rats. The behavior of pups was assessed using video tracking. Developmental impact An opioid addiction can have various effects, like infants being born prematurely or lacking oxygen during birth. On top of that, they might be more sensitive to opioid addiction later in life. Treatment with BUP potentially reduces several of those effects, though not all consequences of BUP-use are known yet. Studying buprenorphine Most studies only administered BUP after conception and stopped before birth. However, mothers are often already using opioids during conception and keep using them until long after birth. Therefore, this study started treatment on the rats a week before conception and only stopped after weaning. Treatment on rats The rats used to test the effect received one of two different BUP dosages; one was comparable to normal treatment (BUP-LD), one was higher than normal (BUP-HD), and a control group received saline treatment. The doses were injected daily. Behavioral experiments The researchers carried out various behavioral tests in order to assess any effects of BUP. They found that BUP negatively affects maternal care and pup development, and that this effect was stronger in the BUP-HD rats. Some examples are a lower offspring body weight, increased mortality, reduced pain sensitivity and the presence of Neonatal Opioid Withdrawal Syndrome (NOWS) symptoms. Maternal care After birth, offspring care was observed daily for 5 days. On day 2, a pup retrieval test was carried out where the researchers scored how many "misplaced" pups were returned to the nest by the mother. The BUP-HD mothers were found to decrease the amount of caring behavior and did not retrieve pups from outside the nest as often compared to control mothers. A similar, but weaker effect was found in BUP-LD mothers. Furthermore, the continued reduced maternal care in the BUP-LD group might have influenced pup maturation and behavior. Because of the severe lack of maternal care, BUP-HD pups were given to control mothers which greatly increased their survival. The more severe effects of BUP compared to other studies might be caused by the extended exposure period, from before conception until weaning. Since those other studies showed no mortality from BUP-HD treatment, said mortality might be caused by maternal neglect in the current study. Neonatal Opioid Withdrawal Syndrome test Two days after birth, symptoms of NOWS were assessed. One group of pups received an injection with an opioid antagonist, which should eliminate the effects of the BUP. The other group served as a control. Subsequently, pups were observed for 30 minutes while researchers scored withdrawal-related behaviors like mouth movements, vocalization, and/or tremor. No significant behavioral differences were found between the groups. It is possible that the BUP was already mostly eliminated by that time, which made the antagonist ineffective. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Anxiety in rat pups Using an elevated-zero maze, anxiety was tested in the now early-adolescent pups. Each pup was placed in a closed area of the maze and allowed to explore for 5 minutes. Using EthoVision XT 13, distance travelled and time spent in each area were recorded and analyzed. However, the results showed no significant effect of BUP-LD on anxiety. Testing stress responses For testing stress-sensitivity, each pup was physically restrained for 30 minutes. Blood samples for corticosterone analysis were collected at 3 different moments, 1. before the test, 2. immediately after the test, and 3. 90 minutes after the test. No significant effects of BUP-LD on stress sensitivity was found. Hot-plate experiment Lastly, a pain sensitivity test was carried out by placing pups for maximum 60 seconds on a hot-plate which was heated to 50ºC. The latency to a response, like withdrawing a paw, was recorded, after which pups were taken off the plate immediately. A week later the pups received a morphine injection and the experiment was repeated. The rats showed a reduced pain sensitivity during the first hot-plate experiment, though this effect disappeared in the morphine experiment. Conclusions The effects of BUP exposure proved to be more severe than reported before, possibly because the exposure period that we used is longer and therefore more realistic. Furthermore, BUP-HD effects seem to be more severe as well, despite systematic evaluation not being possible due to high pup mortality. Lastly, the effects of a repeated overexposure to opioids during pregnancy need to be studied thoroughly due to its commonness in today's society. References Wallin, C. M., Bowen, S. E., Roberge, C. L., Richardson, L. M., & Brummelte, S. (2019). Gestational buprenorphine exposure: Effects on pregnancy, development, neonatal opioid withdrawal syndrome, and behavior in a translational rodent model. Drug and Alcohol Dependence, 205, 107625. --- ## Homology and analogy in behavioral neuroscience URL: https://noldus.com/blog/homology-and-analogy-in-behavioral-neuroscience Published: 2020-06-01 12:00:00 Description: The point of this blog is to encourage you, as researchers, to ‘double think’, which is to say think like a scientist and think like an animal. Behavioral experiments employ a variety of animals, such as fish, pigeons, rats, monkeys, and humans, to name a few (for a discussion of invertebrates see here1). The decision of which animal model to use has many factors2, but is it valid to compare data from that animal without first considering the anatomical homology or behavioral analogy? To that end, what does that even mean? Having a shared origin According to the National Human Genome Research Project3, mice and humans share a remarkable homology: approximately 85% of protein-coding regions of the mouse and human genomes are identical. Between rats and mice, there is approximately 83-100% overlap4. Campbell and Hodos5 suggest "structures and other entities are homologous when they could, in principle, be traced back through a genealogical series to a stipulated common ancestral precursor irrespective of morphological similarity". This makes sense as humans, mice, and other mammals share a common ancestor some 80 million years ago. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Having a shared function On the other hand, analogs share a similar functional role6. Simply put for those of us who took more philosophy than biology courses: homologous means a shared origin, whereas analogous means a shared function. For example, rodents and humans have a homologous neuronal structure for acquiring spatial information, called the hippocampus; however, honey bees have an analogous structure, called the mushroom bodies, and zebrafish (Danio rerio) have an analogous structure called the anterodorsolateral pallium. Making comparisons in behavioral neuroscience This is important for many reasons. If you want to compare across things (neuronal structures, behavioral patterns, etc), then it is extremely important to note the relationship among those things. People are not rodents and rodents are not fish. So if one were to make any comparisons among the behaviors of any given species, then that comparison must be made on either a shared homology or with an analogous task. This may seem obvious, but it is very important. Let's begin with an example: In the mid-1980s, a novel behavioral paradigm for rats was described7. It consisted of a raised cross-shaped maze with two open arms and two closed arms. The task was called the elevated plus maze for obvious reasons. The premise is simple: rats have a natural fear of heights. Interestingly, the researchers noted that the animals would not readily explore the open arms unless they were treated with clinically effective anxiolytics. Conversely, anxiogenics caused significant more time to be spent in the closed arms; however, antidepressants had no effect whatsoever. Thus, the elevated plus maze became a standard task for testing anxiety in rodents. But what about testing anxiety in a fish? Recently, researchers at MacEwan University8 created a behavioral analogous task for assessing anxiety in zebrafish. As fish swim in a tank, the behavioral analogy makes use of a danio's natural aversion to bright, open spaces in favor dark, hidden ones. In this way, the task is completely analogous to the rodent version: it has a similar shape, testing protocol, and behavioral metrics such as dwell times, distance traveled, etc. Video tracking suites, such as EthoVision XT, make quick and easy work of the data collection and analysis. Similar tasks exist for other exploratory tasks, such as the open field for rodents and the novel tank diving task for fish. All these tasks make use of the innate behavior of the animal, but those innate differences cause researchers to use creative and clever means to create analogous tasks. Double think Thus, the point of this blog is to encourage you, as researchers, to 'double think', which is to say think like a scientist and think like an animal. Presumably you have a homologous animal model for your research question, disease model, and/or clinical application. But if you want to add a behavioral component, then you must think about the behavioral outputs exhibited by your animal model. In addition to providing tracking suites and mazes, Noldus can help with behavioral paradigms and protocols. In addition, we can teach your research group the proper way to conduct a behavioral experiment and analyze data. Contact us today and let us help you design your next behavioral analog! References - Byrne, J. H., & Crow, T. (1991). Examples of mechanistic analyses of learning and memory in invertebrates. In J. L. Martinez, Jr. & R. P. Kesner (Eds.), Learning and memory: A biological view (p. 329–358). Academic Press. - Davidson, M.K., Lindsey, J.R., & Davis, J.K. (1987). Requirements and selection of an animal model. Israel Journal of Medical Sciences, Jun;23(6):551-5. - Retrieved from National Human Genome Research Institute. - Nilsson, S., Helou, K., Walentinsson, A., Szpirer, C., Nerman, O., & Ståhl, F. (2001). Rat-mouse and rat-human comparative maps based on gene homology and high-resolution zoo-FISH. Genomics, Jun 15;74(3):287-98. - Campbell, C.B., & Hodos, W. (1970). The concept of homology and the evolution of the nervous system. Brain, Behavior and Evolution, 3(5):353-67. - Lauder, G.V. (1994). Homology, Form, and Function. In Homology: The hierarchical basis of comparative biology. Edited by Brian K. Hall (1994) San Diego: Academic Press, xvi + 483 pp - Pellow, S., Chopin, P., File, S.E., & Briley, M. (1985). Validation of open: closed arm entries in an elevated plus-maze as a measure of anxiety in the rat. Journal of Neuroscience Methods, Aug;14(3):149-67. - Hope, B.V., Hamilton, T.J. & Hurd, P.L. (2019). The submerged plus maze as an assay for studying anxiety-like behavior in fish. MethodsX, 6:1832-37. --- ## Noldus Grant Assistance Program launched in North America URL: https://noldus.com/blog/grant-assistance-program-north-america Published: 2020-05-25 08:30:00 Description: Grant funding is the lifeblood of academic research. Is successful funding the best path to securing future funding? Grant funding is the lifeblood of academic research. In the United States, the pinnacle of research awards is the NIH R01 grant. At many universities, getting a R01 is the key to getting tenure1; however, according to data provided by NIH, only 16.3% of applicants get awarded on the first submission, and 31.7% get funded on the first resubmission2. Furthermore, funding rates have remained relatively stable for the past ten years (see Figure 1). The Canadian equivalent of such an award is provided by the Canada Foundation for Innovation (CFI). In the science sector, only 18% of proposals were funded in 20173. Noldus Grant Assistance Program launched in North America Moreover, there is ample evidence to support the idea of a "Matthew Effect"4, meaning that successful funding is the best path to securing future funding. Where does that leave new researchers, professors at smaller institutions, and especially minorities5? There are proposed solutions6, but one thing is clear: There is an obvious need to help academics in the path to funding. As of May 2020, Noldus Information Technology offers to do just that. Two goals of the Grant Assistance Program Dubbed the Grant Assistance Program, the goals of the program are simple enough: help researchers get funding. To do this, Noldus has tasked Jason Rogers, PhD, with designing the program and establishing connections with researchers and partners. For researchers, the program serves two purposes: First, to assist with the writing, reviewing, and capturing of grants by providing budget justifications, use cases, behavioral protocols, publications, documentation, insider tips, and general writing assistance. We are happy to provide researchers with the leg work necessary to demonstrate the effectiveness, validity, and reliability of our solutions. The second goal of the program is to locate funding sources, funding requests (RFPs), etc, and share them with our academic community. We understand that researchers spend their days teaching and doing research. As such, they don't always have the time to search for new funding opportunities. Our mission as a research partner is to help find them! This reflects our core values The best part: All of this comes at no cost to the researcher! This program reflects the core values embedded into the DNA of Noldus: "Our tools support the objective assessment of health and well-being, in humans and animals, and thus contribute to better solutions"7. This can be seen in Noldus' response to the global Coronavirus COVID-19 (SARS-CoV-2) crisis. Furthermore, approximately 60% of employees in North America have advanced degrees (MBA, MS, PhD). We are committed to researchers because we are very much a part of the research community. FREE GUIDE Write better proposals - get your free guide here We offer resources to locate funding sources and assist with the grant writing process, with no cost or commitment to you! Download for free Stay tuned! In the coming months, we will be publishing a series of blogs aimed at helping write better, more successful grant proposals. Stay tuned and be sure to check back as more content becomes available. About Jason Rogers Jason got his PhD from the Department of Psychology at University of Utah, under the guidance of Ray Kesner. His dissertation focused on the interactions and dissociations between the hippocampus and parietal cortex in processing spatial information. He was a Post-Doctoral Fellow in the Department of Neuroscience at the Medical University of South Carolina. His research focused on the neuropsychopharmacology of relapse to drugs of abuse. It was during this time that Jason first received NIDA funding. In 2008, Jason joined Noldus as the lead trainer and product specialist. Along the way, Jason has been providing online and remote trainings, sales in the Midwest, and consulting for all of North America. Jason has held seminars, lectures, and trainings on four continents and has visited approximately 75% of the academic universities and the entire continental USA. Despite not publishing a peer-reviewed publication in over twelve years, Jason maintains a H-Index above 10. He has a passion for research, psychology, neuroscience, and new age music. Grant Assistance Program Contact us today to begin a collaboration: Together we can create something special. LET'S TALK Start your journey with us today! Get in touch if you want to: - Advance your research - Get expert guidance - Profit from our 35+ years of experience Get started References - 1. National Research Council (US) Committee on Bridges to Independence: Identifying Opportunities for and Challenges to Fostering the Independence of Young Investigators in the Life Sciences. Bridges to Independence: Fostering the Independence of New Investigators in Biomedical Research. Washington (DC): National Academies Press (US); 2005. 6, Establishing Stable Research Programs. Available from: NCBI. Excel see, retrieved from: NIH Success Rates - 2. Data retrieved from: NIH Data Book - 3. Canada Foundation for Innovation, retrieved from: CFI by the numbers - 4. Bol, T.; de Vaan, M.; van de Rijt, A. (2018). The Matthew effect in science funding. Proceedings of the National Academy of Sciences May 2018, 115 (19) 4887-4890; DOI: 10.1073/pnas.1719557115 - 5. Funding disparities research and underrepresented minority scientists - 6. Retrieved from: Scientific funding problems have solutions --- ## Let the software work for you! URL: https://noldus.com/blog/ethovision-xt-let-the-software-work-for-you Published: 2020-05-20 15:00:00 Description: Why spend extra time on tedious tasks? Instead of manually checking behavior tracking data for errors, streamline your workflow with the right tools. Gain accurate insights effortlessly and focus on what truly matters: your research and discoveries. Why do more work than you have to, am I right?! While I was on the sales team at Noldus, I used to say, "Let the software work for you, don't get stuck working for the software". It was my poor attempt at a catchy sales pitch, but the message I wanted to convey was genuine. Because ask yourself this; do you really want to be stuck behind your computer scouring over your behavior tracking data to make sure there aren't any missing samples or tracking jumps between frames? No. You just want it to work, so you can focus on other things. Noldus software tools to the rescue Within all of the Noldus software packages, there are always built-in tools or features that are designed to make the data collection process and subsequent analysis as painless as possible. EthoVision XT in particular is full of these for virtually every phase of the experimental process. In this article, I would like to highlight some of the ones that I think can take your EthoVision XT workflow from potentially tedious to fabulous! RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources Custom templates in EthoVision XT If you find yourself repeating the same types of experiments, just with different subject cohorts, don't waste your time creating a new EthoVision XT experiment from the ground up! A Custom Template will create that new experiment file for you utilizing the exact same settings from your previous study (Arena, Trial Control, Detection, Analysis Profiles, and Data Profiles). As long as nothing changes within the physical testing space (i.e. the camera doesn't move, or the testing arena/maze is in the same spot as last time), you can be up and running in three easy steps. Multiple arenas – copy and arrange Being able to track in multiple arenas at the same time is a great time saver for high-throughput testing. On the other hand, setting up all the tracking arenas within the camera view(s) can be tiresome, especially if you have several zones/zone groups. Well, not only is there a way to copy all of these settings to your subsequent arenas, but you can also arrange and fit them to the background image all at the same time. Copy/paste your trial & hardware control settings Speaking of copying settings, the latest version of EthoVision XT allows you to copy and paste your Trial & Hardware Control boxes. You can now quickly build complex trial settings from the ground up without having to re-configure each of the available settings. This is game-changer for designing larger protocols involving not only hardware, but multiple if/then conditions as well. Automated detection Need I say more, it's automated for you! Starting with EthoVision XT 11, this handy time saver allows you to draw a box around your subject(s) and the software configures the Detection Settings for you. As one of the most important steps in the experimental setup process, why not take the stress off yourself, and avoid the time-consuming tweaks to the contrast, brightness, subject size, etc. Batch acquisition Working with prerecorded videos is great! With the physical work done, all that is left is to collect the data. Unfortunately, having an experiment with tons of trials can mean some serious time at the computer tracking videos. Not the case when you use batch acquisition! Create your full trial list within the Experiment Settings (Note: be sure to change the other relevant settings – Arena, Trial Control, and Detection – if using multiple versions) and link the corresponding video files in one easy step. You can then choose to "Track All Planned Trials" within the Acquisition Settings, and with that, you're free to go grab a fresh cup of coffee. Track editor It can happen - a tracking "blip" as I call it. Whether it's a quick jump in the tracking plot or a nose/tail swap, one of the best ways to fix it is with the Track Editor. You definitely want to make use of the built in tools like "Auto Select…" and "Auto Swap…" (with 'Auto' in the name, you can't go wrong). These will comb through the trial for you and highlight the samples that fit the error criteria you specify. You tell me: would you rather watch video playback frame by frame, or just click a button and EthoVision XT does it for you? Statistics & charts Do you know that if you have multiple Data and Analysis Profiles you can mix-and-match them ahead of time to do a quick batch processing of all the statistics? Just click the 'Batch…' button (right next to 'Calculate'), and you can export all the relevant profile combinations quickly and effortlessly. It's also nice to pair this with batch statistics calculations within the Acquisition window, so that analysis starts automatically right after the acquisition of the last trial has finished. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial I hope that some of these built-in helpers will come in handy and streamline some of the more, potentially time-consuming aspects of a behavioral experiment for you. This is by no means an exhaustive list, but if some these features can positively change your workflow, then you are on the way to letting the software work for you (and not the other way around)! --- ## Organized chaos or well-oiled machine? Optimizing safety & efficiency in an OR URL: https://noldus.com/blog/optimizing-safety-efficiency-or Published: 2020-05-18 13:00:00 Description: Dr. Joseph and her team searched for solutions to minimize flow disruptions in Operating Rooms and make them as safe and efficient as possible. Hospital operating rooms (OR) are spaces in which medical personnel performs often complex surgeries and tasks with many interactions between humans and equipment. Even though to the casual observer an operating room may come across as organized chaos, it's meant to be a well-choreographed sequence of procedures. Any issues with regard to teamwork, communication, workflow, and equipment design are known to lead to complications and increased mortality. Dr. Anjali Joseph and her team use a Portable Noldus Observation Lab, behavioral coding with The Observer XT, and computer modeling to qualify and quantify the goings on during surgeries in real operating rooms, not simulated versions of one. Their goal is to identify flow disruptions, determine what's causing them, and come up with solutions to minimize them and make ORs as safe and efficient as possible. Direct observation and behavioral coding Joseph et al. (2019) used a Portable Noldus Observation Lab (with 4 cameras and microphones) to record activity during 28 surgeries in 3 operating rooms. The locations, roles, and activities of all medical personnel, along with any flow disruptions (FD), were then coded in detail with The Observer XT software. Across all surgeries a total of 2504 FDs were observed, 26% of which were major ones. The researchers found that the rate of major FDs increases with the rate of minor FDs, especially when they are related to particular equipment and its positioning in the room, and certain specific locations in the OR. More FDs were observed in the anesthesia zone than any other zones. The central role of the circulating nurse The role of the circulating nurse (CN) was studied in more detail by Neyens et al. (2018) and Bayramzadeh et al. (2018). Across 25 surgeries, in 3 different ORs, the CN spent 34 hours performing 1471 tasks, each categorized as patient, equipment, material, and information related. CNs were more likely to be involved in layout and environmental hazard FDs when involved in patient, material, or equipment-related tasks compared to information tasks, while the latter tasks involve the least movement. The OR was divided up in multiple zones, each of which was categorized as functional (work stations, preparation zones, surgery, etc.) or transitional. The CN traveled through multiple zones during the vast majority of activities. Of all flow disruptions, 58% happened in the transitional zones, while behavioral coding revealed that even though the layout of the 3 ORs varied, the flow disruption patterns were quite similar: certain zones will always be adjacent to each other. Digging deeper: Simulation modelling to analyze traffic flow in the OR To dig deeper into what all is going on in an operating room, Taaffe et al. (2020) used the behavioral data set generated with The Observer XT to model the traffic flow during surgery. They looked at the effect of the size and shape of the room, the orientation of the surgery table, and the location of the workstation of the circulating nurse. A larger room reduced the number of contacts and transitions, even though it required more movement. Positioning the table at an angle into the center of the room with the workstation at the foot of the table resulted in a reduction of undesired contacts among medical personnel. Future work: Adapting the OR to COVID-19 conditions Dr. Joseph and her team are presently using the Noldus Portable lab and The Observer XT to observe and code telemedicine sessions for stroke patients conducted in an ambulance. They also just finished coding a set of videos from 25 additional surgeries in new, optimized ORs that were finished in January 2020. Plans are now underway to use the Portable Lab and The Observer XT to study adaptation of operating rooms for use during COVID-19. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References Joseph, A.; Khoshkenar, A.; Taaffe, K.M.; Catchpole, K.; Machry, M.; Bayramzadeh, S. & RIPCHD.OR study group. (2019). Minor flow disruptions, traffic-related factors and their effect on major flow disruptions in the operating room. BMJ Quality & Safety. http://dx.doi.org/10.1136/bmjqs-2018-007957 Bayramzadeh, S.; Joseph, A.; San, D.; Khoshkenar, A.; Taaffe, K.; Jafarifiroozabadi, R.; Neyens, D.M. & RIPCHD.OR Study Group (2018). The Impact of Operating Room Layout on Circulating Nurse's Work Patterns and Flow Disruptions: A Behavioral Mapping Study. Health Environments Research & Design Journal, 11, 124-138. https://doi.org/10.1177/1937586717751124 Neyens, D.M.; Bayramzadehb, S.; Catchpole, K.; Joseph, A.; Taaffe, K.; Jurewicza, K.; Khoshkenara, A.; San, D.; RIPCHD. OR Study Group (2019). Using a systems approach to evaluate a circulating nurse's work patterns and workflow disruptions. Applied Ergonomics, 78, 293-300. https://doi.org/10.1016/j.apergo.2018.03.017 Taaffe, K.; Joseph, A.; Khoshkenar, A.; Machry, H.; Allison, D.; Reeves, S.T. & RIPCHD.OR Study Group (2020). Proactive Evaluation of an Operating Room Prototype: A Simulation-Based Modeling Approach. Journal of Patient Safety. https://doi.org/10.1097/PTS.0000000000000693 Image Credit: Dr. A. Joseph --- ## Toxicometabolism and behavior of zebrafish exposed to cannabinol URL: https://noldus.com/blog/toxicometabolism-and-behavior-of-zebrafish-exposed-to-cannabinol Published: 2020-05-14 14:00:00 Description: THC and CBD are well-know compounds of cannabis (Cannabis sativa), use for recreational purposes or health benefits. We have less knowledge of the effects of another active compound: CBN. I had the pleasure of working on this article with Ieremias Chousidis (University of Ioannina). He studied the effects of CBN, a lesser known compound of Cannabis leaves, in order to investigate the impact of cannabis on organisms. Cannabis use and abuse Cannabis (Cannabis sativa) leaves are amongst the most abused drugs in human history due to their psychoactive effects. Various products and extracts of cannabis have gained great interest due to beneficial/therapeutic effects for a series of syndromes, including Dravet syndrome, epilepsy, anxiety, schizophrenia, chronic pain, even for cancer, as well as for recreational purposes e.g. euphoria. While in most countries the medical and recreational use is illegal (except for Canada, Israel and 16 EU countries), the cannabis world market today is reaching 30 billion dollars, with the profits made from illicit trafficking being even higher. Active substances Cannabis leaves have several compounds, or cannabinoids, that cause the effects that people use it for. You have probably heard of THC (tetrahydrocannabinol), the main psychoactive that causes the "high" sensation. Another well-known cannabinoid is CBD (cannabidiol), which does not have the psychoactive effects, but rather is used for health benefits, such as pain relief, to treat anxiety and depression, help with acne, etc. Cannabinol, the unknown cannabinoid Cannabinol (CBN) is a less familiar compound. It is actually a degradation product of THC, and its concentration in cannabis leaves increases as the plant ages. Its formation is also strongly affected by the storage conditions. Why investigate CBN? Studying the impact of CBN on living organisms is crucial to address potential future health issues. There is an increasing amount of attention for the cannabis plant, so more studies should focus on CBN and other relevant degradation products. Their production is not controlled, but depends on many aspects, such as plant growing conditions, processing, storage, etc. Every bit of plant extract can differ significantly in their CBN content and hence, in their medicinal activity (Fu et al., 2019). Research at the University of Ioannina Humans have two cannabinoid receptors, CB1 and CB2, that are involved in various regulatory mechanisms in our brain. The CB1 receptor has a key role in the central nervous system, and is also found in zebrafish, making them a suitable model to study the effects of CBN on several health aspects. At the Zoology and Analytical Chemistry laboratory of the University of Ioannina, CBN was examined for toxicity, effects on heart physiology, morphological malformations, behavioral changes and alterations in metabolic pathways of zebrafish larvae. Morphological malformations of zebrafish embryos exposed to cannabinol. (A-B) Control larvae, (C-D) larvae exposed to 0.25 mg/l with no or very minor malformation, (E-F) larvae exposed 0.75 mg/l with indicative pericardial edema, (G-H) larvae exposed to 1 mg/l with indicative pericardial edema and tail bending, (I-J) larvae exposed to 1.2 mg/l with indicative pericardial edema, yolk sac edema and tail bending. Malformations are indicated by arrows. Effects of CBN on zebrafish embryos and larvae "Our study showed that the LD50 value was estimated at 1.12 mg/l. Malformations in zebrafish larvae increased significantly in a dose-dependent manner and exposure to CBN concentrations greater than 0.75 mg/l provoked abnormalities like pericardial edema, yolk sac anomalies and tail bending," Chousidis explains. He also mentions that concentrations above this threshold resulted in elongated and shorter in width hearts and in a separation between ventricle and atrium. The metabolomic analysis revealed alterations, mainly to amino acids, which are related to acute toxicity and hint towards systemic metabolic and neuropathophysiological changes. Behavioral evaluations of zebrafish larvae Chousidis and his colleagues studied the behavioral changes in zebrafish larvae using DanioVision and Ethovision XT software. "The total movement, distance moved, and velocity of the zebrafish larvae were increased during dark and decreased during light conditions, in a concentration-dependent manner. Our results also showed that CBN acts both as a stimulant and a sedative, with larvae exhibiting altered velocity and bradycardia, respectively." FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Negative effects of CBN Results of this study demonstrate a negative, dose-dependent effect of CBN exposure on the morphology, behavior, physiology and metabolome of the organism, highlighting the unexplored adverse effects of CBN on aquatic organisms. This research also underlines the active role of CBN in modulating systemic changes and can serve as a future reference point to assess the risk of cannabis products intended for human use. References - Chousidis, I.; Chatzimitakos, T.; Leonardos, D.; Filiou, M.D.; Stalikas, C.D.; Leonardos, I.D. (2020) Cannabinol in the spotlight: Toxicometabolomic study and behavioral analysis of zebrafish embryos exposed to the unknown cannabinoid. Chemosphere, 252, 126417. - Fu, J.; Gong, Z.; Kelly, B.C. (2018) Metabolomic profiling of zebrafish (Danio rerio) embryos exposed to the antibacterial agent triclosan. Environmental Toxicology and Chemistry, 38(1), 240-249. --- ## STAY AT HOME! URL: https://noldus.com/blog/stay-at-home Published: 2020-05-11 10:39:00 Description: What is the best way to communicate an important message such as 'Stay at home'? The research team of Mauri compared the emotional reactions to three short videos containing this message using FaceReader. This is a guest blog post by Maurizio Mauri, head of User Experience & Neuro-Marketing Research at SRLABS in Milan, Italy. He is kindly sharing the results of a study with FaceReader during the COVID-19 pandemic. Enjoy reading! STAY AT HOME! This is the message that we have all heard in the past few months because of the "Corona virus". Have you ever thought about the best way to communicate such an important message? We compared three short videos of influential persons who adopt three completely different communication styles to approach the topic of the pandemic caused by the spreading of the virus called Covid-19, in order to persuade Italians to "STAY AT HOME". Emotional reactions to "stay-at-home" messages The comparison of the effects of the three audiovisual messages is based on the emotional reactions of people, detected through the analysis of their facial expressions, while watching the three videos. Take a guess… which one would be the most effective video message? - The statement made by Italian first minister Giuseppe Conte - The message communicated by the well-known virologist Roberto Burioni - The video made by Italy's most famous scientific popularizer Alberto Angela FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download How to persuade Italian people to "STAY AT HOME" Is it better to convey a message in a "strong way", communicated by an expert virologist (like Roberto Burioni), while being interviewed by a famous TV presenter? Does this make the message more effective and vivid? Or is it better to perform it in a "calm way", by a famous scientific popularizer (such as Alberto Angela), who speaks in an "informal" setting? Or rather in the "serious and institutional way", expressed by the Italian political leader, responsible for managing the crisis (the first minister Giuseppe Conte)? Ah, of course, all in a minute only! This was the time available to expose the participants to our little research in which three audiovisual messages were shown (communicated by the three mentioned persons). Measuring satisfaction and emotional responses The answer about which audiovisual message was most effective, in terms of satisfaction and emotional responses, is presented here by our company SR LABS, together with our partner JUNGLES, with whom we have designed the research. The project was conducted by means of an online participation and combined the results of the innovative technique based on the automatic analysis of the emotional expressions of the face with those of a short traditional questionnaire about the perceived satisfaction. In our research, 34 people (mainly university students from the course in "Cognitive Sciences applied to Ergonomics, User and Customer Experience", at the Catholic University of Milan, we thank the students together with all the other volunteers) were invited by e-mail to participate in the study. After receiving a link, the participants comfortably opened each of the three videos sitting in front of their own PC while staying at home. The three audiovisual messages were presented to each participant in a random order. The random order of the exposure of the three videos allows to avoid any kind of "sequence effects". Which messenger is preferred? The results of the analysis of the questionnaire, which explored the level of satisfaction, show that: - Alberto Angela was the most appreciated (18 people out of 34 reported to prefer his message in comparison to the other two audiovisual communication) - Roberto Burioni (12 people out of 34) - Giuseppe Conte (4 people out of 34) It is clear that a preference emerges for the "calm and informal way" performed by a scientific popularizer who is quite appreciated in Italy. Both in comparison to a virologist who takes advantage of a strong and assertive way to explain why people must stay at home, as in comparison to a political leader who must maintain the greatest seriousness within an institutional communication format. However, so far we have measured the "WHAT", not the "WHY". To understand the "WHY", it is possible to take advantage of insights from neuroscience and experimental psychology. Insights from neuroscience From neuroscience we know that, thanks to the brilliant scientific research of Stephen Porges and his "polyvagal theory", facial expressions represent direct reactions of the nervous system (such as the psychophysiological reactions reflected by the cardiac system, the respiratory system, etc.). For this reason, facial expressions can be useful for exploring spontaneous "non-verbal" reactions, together with "verbal" and more "rational" ones (as more "reasoned" and less spontaneous) collected in the questionnaires. Insights from experimental psychology From experimental psychology we know that for campaigns based on "negative emotions", such as fear or sadness, to be more effective, they must induce a moderately high level of emotion. We've learned this from the theory of the so-called "Fear Arousing Appeals", a theoretical framework commonly used in communication campaigns when a message tries to convince members of the public to adopt a more "healthy behavior". Ideally, the negative emotion trend should describe a sort of inverted "U", where the negative emotion begins with an increase in intensity, until it reaches an apex or "emotional peak", which then returns to fall, in which there is a sort of final "relief", compared to the emotion of fear (or sadness) elicited in the initial part of the message. By providing solutions or explanations (also known in psychological terms as "coping instructions") in the final part of the communication, it is possible to help people understand how to reduce or avoid the threat generating negative emotions. This "relief" is elicited thanks to the possibility to face or manage the danger presented in the message, thus also conveying the hope of being able to reduce or avoid the threat itself. MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Try it now Analyzing emotions The emotions reflected by faces of participants while watching the three videos were analyzed. Given the difficult general context caused by the emergency of COVID-19 and the "heaviness" raised by the new rule to stay at home for a long period, sadness (after the "neutral expression) was undoubtedly the most predominant emotional reaction, at least in absolute values: - in the video with Burioni, the average is 10% - in the video with Conte, the average is 9% - in the video with Angela, the average is 8% To better understand these results in percentages, keep in mind that every emotional expression (fear, anger, sadness, joy, etc.) is revealed with a percentage ranging from 0% to 100%: an expression of joy, for example, 100% could be detected when the person finds out he/she has won the lottery! Obviously, with the exception of special cases, it is rare for people to show an emotional expression in its maximum intensity equal to 100%. In most cases, people's facial expressions represent an "inkling" of emotional expressions (such as an inkling of a smile), a prodromal of the expressions of joy, which reveals more a slight satisfaction or contentment (what in psychology is also called "engagement"), rather than a real expression of "joy". For this reason, when we mention emotions like "joy" or "sadness" equal to 10%, we refer to an expression that in that second or in those seconds shows an inkling of the configuration of the muscles of the face that is organized in order to express that emotion in a mild way (up to 10%). By studying the trend of emotions during the exposure to the various videos, however, you can see different trends (like different "stories", told differently): - in the case of Burioni, the percentage of sadness is always around or above 10%, from the beginning to the end, it never shows big changes, neither downward nor upward, for all 60 seconds of the audiovisual message - in the case of Conte, it remains below 10%, around 8% more or less, with the same trend without big changes, downside nor upside, from the beginning till the end - in Angela's case, however, there is a continuously descending trend. It starts with values around 12%, when the message begins, he says: "... we are going through an important moment in our history, it is not easy, I know ..." and then he adds, to the second number 5 of the video: "... we have to stay at home ...", in which one of the highest peaks of percentage of sadness is revealed. Then, at about 20 seconds, the percentage average values decrease to approximately 10%. Especially in the final part of the message, there is a negative peak that falls down to 5%. In short, in the video of Angela the negative emotion diminishes up to the minimum in the final part of the message The facial expression "sad" The graph below shows the trends of the "sad facial expression" during the three videos, with relative "trend lines" (a simple algorithm that calculates the general trend, rising or falling). Looking at the chart, notice how the green signal (Angela) is the only one that has a downward trend: sadness systematically decreases as the video is shown to participants, while the other two signals (Burioni, in red; Conte, in blue) increase progressively as an average percentage. This reveals that there is, on the contrary, an increase in percentage of expressions of sadness. On the x-axis of the graph, time is represented according to the sampling points provided by the technology (equal to 5 times per second: thus 60 seconds become 300 samples). The emotion "joy" Another emotion is slightly elicited in all three videos: joy ("happy facial expression"). In absolute terms, we see here the average results in percentage: - 1% in the video with Burioni - 2% in the video with Conte (interesting to note that when Conte claims: "... in the first place there is and there will always be the health of Italians...", there is a peak of increase in intensity of "joy" that exceeds 4%) - 4% in the video with Angela However, it is interesting to consider once again the trends, related to "happy facial expressions" during the exposure to the three videos: - Angela's video shows the most important change. It starts very low (similarly to the other two videos, between 1% and 2%), but increases as the video goes on, to the 23rd second (when saying: "... friends can also meet with social networks, books can be rediscovered..."). It exceeds 6-7%, up to a peak, raised in the final part, equal to 10% (when Angela claims "... one person who saves another, is a hero; but if this person saves 100 people, he/she is a nurse, or a physician..."). The relative trend line (in green, in the graph below) is the only one that rises upwards. - Conte's video shows a general decreasing trend: in the very last final seconds only it is possible to see an increase (when he declares "... all together we will make it..."), but the increase is less accentuated, and in fact the relative trend line decreases always. - Burioni's video, after a peak that shows an increase in "happy" expressions (at the 5th second, when he declares "... this virus is not a flu...", in which it exceeds 5%), rises a completely flat reaction in terms of "Happy facial expression", and in fact, the relative trend line is always inclined downwards and the video closes near 0%. The graph below shows the three trends of "happy" for the three videos, with the related "trend lines". Only the one relating to Angela's video rises upwards with a rather steep "slope", signaling a significant increase in terms of percentage of joy, especially at the end of the message. Towards the end, Alberto Angela's video message conveys words aimed at trying to show the positive effects of the adoption of the new rule that invites to "stay at home". This corresponds to the "relief" which also leads to the hope of reducing or avoiding the threat, which are reflected by the participants' facial expressions, marked by a pattern of "joy" in their face muscles equal to 10% of "happiness". Therefore, a inkling of "joy", however enough, thanks to the high-level sensitive detection of the technology, to reveal a greater satisfaction and participation aroused by the message (the "WHY" it was more appreciated), which then mediated the levels of satisfaction ("WHAT" was more appreciated). Comparing emotions within different groups Another interesting result is revealed when we tried to divide the participants into two macro-age groups: young (under 25) and more "aged" (over 25): younger people respond less intensely to messages, while those over 25 years of age show intensities of emotions systematically more accentuated than younger ones. As mentioned, since the participants are mostly university students, we could only compare a dozen young subjects taken at random with a dozen over 25. Despite the small number of participants for each age group, different emotional reactions to the same audiovisual film already emerge according to the age group they belong to. The usefulness of facial expression analysis We hope to have shown the contribution of the automatic analysis of facial expressions in deepening why people can appreciate one audiovisual message more than another can. It is not just a matter of prevalence of one emotion over the other, but rather the dynamics of the trends, as learned by studying Angela's video, in which we started with a predominant emotion of sadness equal to or even greater than the other two videos, followed by the insight to see the same emotion of sadness diminishing systematically. At the same time leaving space for a new emotion rising, a growing of "contentment" and "satisfaction" (10% of "Happy facial expressions"). All this can be applied to any type of audiovisual message; actually, to any type of experience, whose effects can be assessed in terms of emotional reactions mediating the perception of liking and satisfaction. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## Improve the interaction between parent and child with autism URL: https://noldus.com/blog/improve-interaction-parent-child-autism Published: 2020-05-08 08:49:00 Description: Children with ASD are three times as likely to exhibit disruptive behavior as their typically developing peers. Can PCIT help coping with behaviors such as defiance, stubbornness, and temper tantrums? As children grow up, they develop all kinds of skills, among which social, communication, and adaptive skills. They learn many of these skills at home, from their parents. After all, they spend most hours with their parents. Therefore, when problems arise in the development of these skills, it can be interesting to use parents as change agents. For example in case of children with disruptive behavior that may be caused for instance by Autism Spectrum Disorder (ASD). Differences in development The rate of ASD in the United States is approximately 1 in 59 children. Children with ASD are three times as likely to exhibit disruptive behavior problems as their typically developing peers. This can be very challenging and stressful for parents. It therefore seems sensible to address this as early as possible in development. This could result in more rapid gains in a child's development and behavior and improve parent-child interactions in everyday life. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly PCIT: an intervention to improve skills Parent-Child interaction therapy (PCIT) is one possible intervention therapy. PCIT directly addresses behaviors that parents of children with ASD report to be most problematic for them – defiance, stubbornness, and temper tantrums. PCIT consist of two phases: - Child Directed Interaction (CDI) – focus is on learning the best ways to pay attention to desired behaviors to reinforce good behaviors when they happen and increase positive interactions. Parents were taught to use the PRIDE skills (Praise, Reflection, Imitation, Description, and Enjoyment) and to avoid questions, commands, and negative talk (Negative Skills). - Parent Directed Interaction (PDI) – focus is on teaching parents to give clear, direct commands and consistently follow through with appropriate consequences for compliance (labeled praise) and non-compliance (time-out procedure). How to measure the value of PCIT According to the research team of Scudder, there is only limited evidence supporting the efficacy of PCIT among children with ASD. Therefore, they conducted a randomized, wait-list control trial using both the CDI and PDI phases of PCIT. Children with ASD between 2, 5 and 7 years of age and their parents participated. Families were randomly assigned to either immediate treatment (n=13) or wait-list control (n=10). The immediate treatment consisted of 8 sessions of CDI, followed by 8 sessions of PDI. At baseline, week 9, and week 18 the researchers performed several measurements: - Eyberg Child Behavior Inventory (ECBI): a parent completed questionnaire of disruptive behavior for children and adolescents. - Dyadic Parent-Child Interaction Coding System-IV (DPICS): a behavioral observation system designed to assess particular features of parent–child social interactions. The DPICS was also used for coding during live PCIT sessions, which was conducted using The Observer XT. - Social Responsiveness Scale-2 (SRS-2): to assess social behavior in children with ASD, parents rate statements about their child's behaviors. - Parenting Stress Index – Short Form (PSI-SF): a self-report measure of parent stress. - Therapy Attitude Inventory (TAI): to measure parent satisfaction following parent training or family therapy. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Effect on disruptive behaviors, ASD severity, and parenting skills The research team expected to find that those receiving immediate treatment would experience greater decreases in disruptive behaviors and ASD severity as well as improved parenting skills. Moreover, the expectation was that parents in the treatment group would report lower ratings of stress. Indeed, this study found significant differences in reduced child disruptive behavior severity and increased parent skills, but no significant differences were found between the two groups in parental stress or autism severity. Clearly, parents of children with ASD are able to acquire and steadily increase PRIDE Skills and reduce their use of Negative Skills across the treatment sessions. Eight out of the 10 families of the waitlist control group completed PCIT treatment after the end of the trial. The pre-post assessment revealed that also in this group improvements were found on the intensity of disruptive behaviors of the children, compliance rates, autism severity, parenting skills, and parental stress. Future PCIT-ASD research The researchers indicate that they didn't explore whether any gains in children's language use or complexity over time with PCIT training occurred. Similarly, possible changes in children's play were not examined. As both language and play are specifically targeted in PCIT, it is most likely that within these two areas changes in autism severity can be observed. In order to optimize the treatment, future PCIT-ASD research should focus on exploring differences across clinical presentations and the variability of changes in autism severity and parenting stress. References Scudder, A.; Wong, C.; Ober, N.; Hoffman, M.; Toscolani, J. & Handen, B.L. (2019). Parent–child interaction therapy (PCIT) in young children with autism spectrum disorder, Child & Family Behavior Therapy, 41 (4), 201-220, https://doi.org/10.1080/07317107.2019.1659542 Also interesting: https://www.autismparentingmagazine.com/autism-meltdowns/ --- ## Gait analysis after a bone fracture URL: https://noldus.com/blog/gait-analysis-bone-fracture Published: 2020-05-06 15:00:00 Description: Recovery after a bone fracture is more than just healing bone and soft tissue. Research on gait analysis is necessary in order to improve knowledge about bone regeneration and rehabilitation after lower extremity fractures! Recovery after a bone fracture is more than just healing bone and soft tissue. A very important factor is the regeneration of mobility, especially for the quality of life in patients with lower extremity fractures. In contrast to the gaining clinical interest in gait analysis during the rehabilitation of patients with fractures, gait analysis is still only rarely used in the most common small animal fracture healing models in experimental research. Recently, Hofman et al. were the first to use the CatWalk XT system to establish an accurate gait analysis method for fracture healing research in small animal models and evaluate the influence of a lower extremity fracture on gait pattern [1]. Why the CatWalk XT system Hofman et al. concluded that the CatWalk XT system offers big advantages compared to treadmill-based gait analysis in small animals: 1) the CatWalk XT system uses a runway set-up, which resembles the normal gait of animals; 2) with the CatWalk XT system both static and dynamic gait parameters can be evaluated in one analysis; 3) when the animals are trained well, the registration of the CatWalk XT system is very accurate, providing clinically relevant and extensive data on gait behavior. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources Femur fracture recovery measurements After training the animals in the CatWalk XT runway for 2 weeks, they performed a baseline gait analysis with Sprague-Dawley rats. After intramedullary stabilization, they induced an isolated femur fracture on the right side. Over a period of 3 months, gait analysis were performed at DPO (days post-operative) 3, 7, 14, 28, 42, and 84 with the CatWalk XT system. They evaluated different static and dynamic gait parameters (e.g. intensity, print area, stand duration, duty cycle, and swing speed) and compared the injured side to the baseline measurements and to the uninjured side of each animal [1]. Bone healing in rats With radiological evaluation, they confirmed the consolidation of the fractures (healing) in all animals at DPO 42. In the first 2 weeks after fracture induction, the fractured hind leg demonstrated significantly reduced values for all gait parameters, compared to baseline values. These values normalized to baseline values during the later period of fracture healing for almost all parameters. They observed similar pattern also when comparing injured hind leg to the uninjured one [1]. Clinical interest in gait analysis Gaining data on post-traumatic or -operative gait patterns are very important to evaluate the recovery of patients after lower extremity fractures. Therefore, it is gratifying to see that the clinical interest in gait analysis after lower extremity fractures is increasing. Expand experimental gait research On the other hand, because ca. 50 % of all animal fracture healing studies are performed in small animal models [2], it is also necessary to gain experimental research data on gait analysis. The results from the study of Hofman et al. showed a close association between the normal fracture healing process and the normalization of the gait parameters in this model [1]. Also Archdeacon et al. showed similar results in a clinical study of patients with femoral fractures [3]. This and other study groups emphasized the importance of gait dysfunction in short- and long-term functional outcomes [3-8]. Accordingly, Hofman et al. demonstrated that the gait patterns of rats resemble those of patients with lower extremity fractures, although the healing process, and thus the impaired mobility lasts longer in human beings [1]. Non-invasive, longitudinal testing Hofman et al. concluded that the CatWalk XT system is practicable and useful to assess both static and dynamic gait parameters in a non-invasive, longitudinal manner in an experimental small animal model of fracture healing. Their pre-clinical findings are in line with clinical observations in patients with lower extremity fractures [1]. Therefore, this system has the potential to become a standard gait analysis method in fracture healing research in experimental small animal models, improving knowledge about behavioral and locomotor recovery after lower extremity fractures. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources References 1. Hofman M, Kolejewska A, Greven J, et al. Gait analysis and muscle weight analysis after lower extremity fractures in a small animal model. Gait & posture 2020; 77: 207-13. 2. Garcia P, Histing T, Holstein JH, et al. Rodent animal models of delayed bone healing and non-union formation: a comprehensive review. European cells & materials 2013; 26: 1-12; discussion -4. 3. Archdeacon M, Ford KR, Wyrick J, et al. A prospective functional outcome and motion analysis evaluation of the hip abductors after femur fracture and antegrade nailing. Journal of orthopaedic trauma 2008; 22(1): 3-9. 4. Pfeufer D, Zeller A, Mehaffey S, Bocker W, Kammerlander C, Neuerburg C. Weight-bearing restrictions reduce postoperative mobility in elderly hip fracture patients. Archives of orthopaedic and trauma surgery 2019; 139(9): 1253-9. 5. Siu AL, Penrod JD, Boockvar KS, Koval K, Strauss E, Morrison RS. Early ambulation after hip fracture: effects on function and mortality. Archives of internal medicine 2006; 166(7): 766-71. 6. Kamel HK, Iqbal MA, Mogallapu R, Maas D, Hoffmann RG. Time to ambulation after hip fracture surgery: relation to hospitalization outcomes. The journals of gerontology Series A, Biological sciences and medical sciences 2003; 58(11): 1042-5. 7. Kammerlander C, Gosch M, Kammerlander-Knauer U, Luger TJ, Blauth M, Roth T. Long-term functional outcome in geriatric hip fracture patients. Archives of orthopaedic and trauma surgery 2011; 131(10): 1435-44. 8. Frenkel Rutenberg T, Vitenberg M, Haviv B, Velkes S. Timing of physiotherapy following fragility hip fracture: delays cost lives. Archives of orthopaedic and trauma surgery 2018; 138(11): 1519-24. --- ## Cognitive neuroscience: Behavior URL: https://noldus.com/blog/cognitive-neuroscience-behavior Published: 2020-04-20 13:30:00 Description: We are in a pandemic where most of us are forced to change our daily behavior. Fortunately, we have our neocortex: it gives us considerable flexibility and creativity in adapting to a changing environment. In the previous blog posts, we dived into the basics of cognitive neuroscience, and zoomed into the role of emotions in the field of cognitive neuroscience. This final blog post of this blog series addresses the last subject: behavior and cognitive neuroscience. System 1 and system 2 In the field of psychology, the terms System 1 and System 2 are widely used. These are two types of systems that can be distinguished within the brain. Do you remember how we discussed in the previous blog post how different types of brain regions trigger reactions such as fight or take flight? According to Kahneman, Nobel Prize winner, this is an example of System 1. This is a fast system, and determines 98% of our thinking. It's automatic, without having to think about it. This is, as discussed earlier, the 'survival' system. System 2 is slower and more conscious. You use it to find information, make choices and make them rationally. This system is responsible for 2% of our thinking. System 1 is not a fan of big changes. After all, it wants to protect you, ease your pain, so that you can survive. And why would you want to change something that has kept you alive for so long? What is interesting here, is that we are currently in a completely different situation due to COVID-19. A threatening situation, so to speak. We are in a pandemic where most of us are forced to change our daily behavior. Your entire daily rhythm needs to be adjusted, because you can no longer move as freely as before. Hence our brain is a bit upset. It has to get rid of its automatic system and adapt itself to this new situation. This can be quite uncomfortable, emotionally. Fortunately, we have our neocortex: it gives us considerable flexibility and creativity in adapting to a changing environment. Which means that after the first awkward days, we will adapt to our new situation. Learn more about working from home strategies in the blog post of my colleague Jason. The brain as a predictor The brain constantly anticipates, for example while reading this sentence, or while walking down the street. If you were connected to an EEG, we could measure so-called 'Event-related potentials', also known as ERPs. ERPs are electrophysiological responses of the brain to environmental events. These events can be simple sensory stimuli, such as sounds, flashes of light, or an electric shock to the skin. Also, motoric events such as typing can trigger ERPs. In neuromarketing research for example, these ERPs can be measured to define neurological responses to a trigger in a commercial. These ERPs tell you when someone is feeling engaged. It tells you even more when this data is combined with emotional data, or eye tracking data. Combining methods is crucial for gaining insight in something as complex as liking and wanting. REQUEST INFORMATION Get in contact Are you interested in our behavioral research solutions, and want to get in contact? - Worldwide: Always near to you - Make your project a success - Trust our 30 years of experience Contact This anticipation of the brain shows that your long-term memory is constantly popping up with things that it thinks you will need soon, so that you are better 'prepared' for the future. The brain can thus be seen as a chronic predictor: it lets you estimate whether you have enough time to cross the streets, or whether or not you should organize a social gathering during a pandemic (spoiler alert: you shouldn't). How can we observe behavior in the brain? Researchers typically combine brain and behavioral observations. They can present visuals on a screen, have the subject play a game, or try to solve a puzzle. Therewith, we typically observe a correlation between behavior and brain activity. In methods with high spatial resolution, such as fMRI, different tasks show local increases or decreases in the BOLD (blood oxygenation level) signal, indicating that the brain is more active in some regions than others. In some cases, brain evidence helps to resolve puzzles that psychologists have wrestled with for decades. The social brain: prosocial behavior Researchers Masten et al. examined neural activity during empathy for social exclusion. They assessed how empathy-related neural mechanisms might relate to prosocial behavior toward the excluded victim. The researchers asked participants to undergo an fMRI scan and measured their neural responses. During the test, one group of participants watched a video showing how one person was excluded by two other persons. The other group saw the opposite: the video showed how a person was included in a group. The group who observed exclusion activated brain regions linked with mentalizing. Highly empathic participants activated social pain-related regions as well. Findings suggest that empathy-related neural responses to social experiences may promote spontaneous prosocial treatment of those in need. Recap To recap this blog series: the key principle is that there are multiple layers at work in our brain. Because of this, we don't have to think about all the things we are doing – such as breathing. The lower centers, our ancient brain, is keeping us alive. It is our neocortex what makes us human, and makes us able to have deep conversations and have retrospective. Emotions are related to physical or social interests, and regulate our life. They serve as a little package of intelligence to quickly solve a problem. Finally, our brain can be seen as a predictor: it constantly anticipates so that you are prepared for the future. Stay up-to-date To stay up-to-date of the latest blog posts, subscribe to our monthly blog updates – and don't miss the latest developments of behavioral research! References Baars, B. J., & Gage, N. M. (2010). Cognition, brain, and consciousness: Introduction to cognitive neuroscience. Burlington, MA: Academic Press/Elsevier. Masten, C. L., Eisenberger, N. I., Pfeifer, J. H., & Dapretto, M. (2010). Witnessing peer rejection during early adolescence: Neural correlates of empathy for experiences of social exclusion. Social Neuroscience, 5(5-6), 496-507. --- ## The role of emotional expressions after face transplant URL: https://noldus.com/blog/role-emotional-expressions-after-face-transplant Published: 2020-04-16 10:09:00 Description: “Would undergoing a face transplant have any value to it if somebody across the room couldn’t tell you were happy by just looking at you?” The face is probably the first thing we look at when we meet each other. We use this part of the body daily for identifying and interacting with the world around us. One of the social functions of a face is communicating non-verbally. However, this becomes much more difficult, or in a lot of cases impossible, when the face is severely deformed. Last January, my colleague told me about a LinkedIn post of one of our customers, Dr. Miguel I. Dorante. He is a plastic surgery resident at Lahey Hospital & Medical Center in Burlington, MA who wrote about the study he and the team led by Dr. Bohdan Pomahac, Director of Plastic Surgery Transplantation, conducted at the Brigham and Women's Hospital in Boston, MA, USA. The research team found that face transplant can partially restore emotional expression to patients. The post intrigued me and I continued to explore what a face transplant actually means. I watched several stories of patients and their relatives on YouTube, which impressed me deeply. I wanted to learn more. Therefore, I read Dorante's article and reached out to him to ask some questions about his study. Social functions of the face A face transplant shows promising results in improved functionality of the face (e.g. ability to breath, eat, and speak) and quality of life for these patients. Nevertheless, Dorante wondered, "Would undergoing a face transplant have any value to it if somebody across the room couldn't tell you were happy by just looking at you?" For him the answer was undoubtedly no. That is why the focus of his research turned to social functions of the face like having a human aesthetic and the ability to produce non-verbal communication. Dorante states that, "Research into emotional expressions has determined that there exists a universal language with cultural-specific dialects. This is suggestive of the significant role emotional expressions play in an individual's ability to integrate into their society. After face transplant, the goal is societal reintegration. Up to now, this has been achieved in all cases of face transplant and has become an ethical pillar justifying the continued practice of this operation. The challenge for our group then became how to convert a subjective evaluation of a person's facial expression to an objective measure of outcome after face transplant." Measuring emotional expressions Dorante and his team began searching for video analysis software that would be able to provide them with information on the expressive state of the video subject in an objective, noninvasive, and nonobtrusive way. The emotion expression analysis should serve as an indicator of functional outcomes and rehabilitation after face transplant. Using facial recognition technology paired with a deep learning algorithm trained to pick up and detect emotional expressions would be an ideal tool. Indirect and direct evaluation of emotional expressions The study included videos of six patients with face transplants (representing 15% of patients with face transplants worldwide) and six healthy controls. Two different protocols were used to either indirectly or directly evaluate emotional expressions. Dorante explained the difference between these protocols by using the analogy of computer software and hardware: "The transplanted face is the hardware that is composed of bones, nerves, blood vessels, muscle and overlying skin. Appropriate function of the hardware is necessary to run software. The software is the code that animates the face and allows it to run its functions appropriately. We wanted to explore if both the hardware was functional (indirect evaluation) and if the code was functional (direct evaluation)." Direct evaluation was performed by asking patients to show the face they would make when feeling happy, sad, angry, surprised, fearful, and scared. This test would show the researchers whether face transplant could restore emotional expression but was limited by individual and cultural biases in expression. This is why they also tested their potential to perform emotional expressions indirectly by asking them to perform facial movements like a smile or a frown. Detect the facial expression happiness FaceReader was used to detect and track faces, extract facial features, and analyze facial expressions. The results showed that for this group of patients, only the emotion of happiness could be reliably detected in comparison to the healthy controls. Dorante thinks that the reason for this is that it takes the fewest number of individual facial movements. 'A smile is predominantly the only movement needed to denote happiness whereas a complex emotion like anger could involve wrinkling the nose, tightening the lips, closing the eyes and furrowing the brow.' The research team found that expression of happiness in the first five years after face transplant was restored to a mean of 43%, compared to healthy controls. This means that you could tell every other patient with a face transplant was happy from across the room. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download The benefits of using FaceReader software Using software-based video analysis to measure underlying muscle recovery indirectly via emotional expression could provide novel information about a patient's recovery. In essence, this tool measures the return of recognizable human aesthetic and nonverbal communication in an unbiased manner. It can objectively provide data helpful to determine whether face transplant meets its ethical goal of restoring functions necessary for societal reintegration. Moreover, Dorante points out that the software is able to detect changes over time that were not evident to their clinical team. The ability to detect and track changes will help them determine progress in rehabilitation efforts as well as overall progress in the recovery after face transplant. Maximize the viability and increase the longevity of face transplants To my question, what kind of current or future challenges are important, Dorante answers: "It is very important to continue asking more questions now that we have proven objective data can be extracted from digitizing the profile of patients with face transplants." He continues: "Personally, the additional value of measuring social functions after face transplant stimulates me to want to maximize the viability and increase the longevity of face transplants. Rejection of the donor allograft by the host body is the primordial challenge of transplants. Looking for markers of rejection that are not invasive or require blood work would be beneficial for efficient management that could increase the lifetime of the graft. Using image analysis software to evaluate changes to the allograft during rejection episodes and overtime would be an area worth exploring in the field of face transplantation." Reference Dorante, M.I.; Kollar, B.; Obed, D.; Haug, V.; Fischer, S. & Pomahac, B. (2020). Recognizing Emotional Expression as an Outcome Measure After Face Transplant. JAMA Network Open, 3(1) https://doi.org/10.1001/jamanetworkopen.2019.19247 --- ## 4 recent blog posts about understanding autism spectrum disorder URL: https://noldus.com/blog/4-recent-blogs-about-understanding-autism Published: 2020-04-13 12:00:00 Description: Our understanding of autism spectrum disorder (ASD) has developed a great deal over recent years, but there is still much work to be done. Our understanding of autism spectrum disorder (ASD) has developed a great deal over recent years, but there is still much work to be done. Over the years the blog writers of this Behavioral Research Blog focused on research into ASD in April, the Autism Awareness month, in order to bring awareness to recent studies that add to understanding ASD. So that's what I'm doing now! Below you can find links to four recent blog posts, related to both human and animal research. For example, learn all about how infant behavior can be studied in order to improve early diagnosis and intervention, or learn more about why gut microbes can increase or decrease typical ASD related behaviors via metabolites. FREE WHITE PAPER Autism Research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Download Human behavior studies Studying posture development in infants at risk for autism Research discussed in this blog post shows that early posture development is delayed in infants who are eventually diagnosed with ASD. Understanding these delays helps to improve early diagnosis and intervention. Infants were observed at home during the families' normal activities and during a time period of free play with their favorite toys. The durations of all infant postures were coded with The Observer XT coding and analysis software. How do children interact with their older autistic siblings? This blog post focuses on the social interactions between children and their older siblings diagnosed with ASD. Autism has many faces, but all children with autism have one thing in common: they struggle to communicate with others. Siblings were observed at home while playing together. The play sessions were recorded on video and the researchers used The Observer XT to code the behaviors of both siblings. A closer look at eye contact Infant siblings of children with or without ASD participated in a study to determine whether gaze behavior showed during a test with an unfamiliar examiner could predict gaze behavior in a more naturalistic context. The researchers coded gaze behaviors, as in gaze to the face, during the first 6 minutes of the test and during the 3-min parent–child play interaction using The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Animal behavior studies Gut microbes: both cause and cure of autism? Gut microbes can increase or decrease typical ASD-related behavior (stereotypies, social behavior, locomotion, and communication) via metabolites and influencing alternative gene splicing. Various typical ASD behaviors were tested, i.e., stereotypies and decreased locomotion, social behavior, and communication making use of EthoVision XT, the automated video tracking software that gives insight into social behavior and locomotion. --- ## Assessing motor outcome in rats with peripheral nerve injury URL: https://noldus.com/blog/motor-performance-femoral-nerve-injury Published: 2020-04-08 15:15:00 Description: At LBI Trauma, CatWalk XT is one of the most important tools to evaluate functional recovery in different animal models. Read more about what they found to be key factors when studying motor performance in rats with femoral nerve injury. This is a guest blog post by Johannes Heinzel. He has done some really interesting research with the CatWalk XT device to assess functional recovery in rats with femoral nerve injury. Enjoy reading! About the Ludwig Boltzmann Institute for Experimental and Clinical Traumatology (LBI Trauma) At LBI Trauma more than 80 researchers and associates investigate the broad field of traumatology and intensive medical care. Within our group we focus on all areas of neuro regeneration, from spinal cord to peripheral nerves, from cell culture to large animal models, from bench to bedside. The CatWalk XT is one of our most important tools to evaluate functional recovery in different animal models of central and peripheral nerve injury. While the CatWalk XT is mostly used to study locomotor function in rats with sciatic nerve injury and spinal cord contusion, we recently pioneered its use to study gait behavior in rats with femoral nerve injury. Interestingly we were able to show that functional recovery to original condition was observable after segmental nerve damage and autograft repair in this model, contrasting the sciatic nerve model. Key factors which were of high importance to gain this new insight are listed in the following sections. It's all about the pressure As the CatWalk XT system records data related to the pressure exerted by the rodents' paws it is of high importance to consider this for your experimental setup. Initially, animals will be relatively light weighted and therefore signals will be of lower intensity than at the end of your experiments (strongly depending on the strain and sex used). Take care to carefully adjust the intensities of the green-light and red-light sources of the CatWalk XT before starting any experiment. On the other hand, make sure the glass plate is not contaminated with urine or other liquids, as it will lead to blurring of the paw prints. Take care to clean and swipe the CatWalk XT thoroughly between runs to keep it dry and clean [1]. Speed and strain Both, your rats strain as well as their speed while crossing the CatWalk XT will significantly affect some of the parameters of gait recorded. Therefore, it is crucial to control the crossing speed to make individual runs and trials comparable. Study the behavior of the respective rat strain you chose for your experiment, as strains differ in terms of their gait behavior in general and at different walking speeds. While the different patterns of how they place their paws while crossing the walkway is not significantly speed dependent in uninjured Sprague-Dawley rats and Wistar rats, Lewis rats will significantly alter these patterns when running at higher velocities [1-3]. Regeneration needs time Make sure to select an appropriate observation period for your respective peripheral nerve injury model. While it takes about ten weeks for rats to recover their gait behavior back to baseline after femoral nerve excision and repair [4, 5], rats with sciatic nerve excision and repair may not recover back to baseline values even a year after injury. On the other hand, when you assess motor outcome in rats with sciatic nerve crush injury, several parameters will reach baseline values around six to seven weeks after nerve injury [6, 7]. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Be prepared to go the distance twice (or three times) Studying functional behavior in small animal models essentially means: Practice makes perfect. As it needs time, practice and patience to learn how to handle the animals adequately, it is inevitable that you will learn some important aspects of their locomotor behavior after you finished data acquisition. While you will become more experienced and confident in identifying individual paws you will realize you have been doing it wrong in previous data sets. Do not hesitate to return back to already classified data and to apply your newly gained insight. Conclusion Assessment of functional recovery via the CatWalk XT device is a highly valuable tool to evaluate locomotor function by means of a voluntary movement task. In addition, its use in the femoral nerve model as proposed by us, offers the possibility to monitor regeneration to original condition after nerve resection and autograft repair, contrasting the most commonly used sciatic nerve model. As other models of peripheral nerve injury remain unstudied with the CatWalk XT so far, we strongly recommend applications of the beforementioned principles to optimize data acquisition and classification. We are convinced that optimal use of the CatWalk XT will result in optimal gain of knowledge regarding the studied model of peripheral nerve injury. Contact Information Ludwig Boltzmann Institute for Experimental and Clinical Traumatology Neuroregeneration Group Donaueschingenstraße 13 1200 Vienna Austria https://trauma.lbg.ac.at/en hannes.heinzel@gmx.de Recent Publication Heinzel, J.C., D. Hercher, and H. Redl, The course of recovery of locomotor function over a 10-week observation period in a rat model of femoral nerve resection and autograft repair. Brain Behav, 2020: p. e01580. References - Deumens, R., et al., Assessing motor outcome and functional recovery following nerve injury. Methods Mol Biol, 2014. 1162: p. 179-88. - Koopmans, G.C., et al., Strain and locomotor speed affect over-ground locomotion in intact rats. Physiol Behav, 2007. 92(5): p. 993-1001. - Cheng, H., et al., Gait analysis of adult paraplegic rats after spinal cord repair. Exp Neurol, 1997. 148(2): p. 544-57. - Hercher, D.K., M.; Schuh, C. M.; Heinzel, JC.; Gal, L.; Stainer, M; Schmidhammer, R.; Hausner, T.; Redl, H.; Nógrádi, A.; Hacobian, A., Spatiotemporal differences in gene expression between motor and sensory autografts and their effect on femoral nerve regeneration in the rat Frontiers in Cellular Neuroscience, 2019. - Heinzel, J.C., D. Hercher, and H. Redl, The course of recovery of locomotor function over a 10-week observation period in a rat model of femoral nerve resection and autograft repair. Brain Behav, 2020: p. e01580. - Bozkurt, A., et al., Aspects of static and dynamic motor function in peripheral nerve regeneration: SSI and CatWalk gait analysis. Behav Brain Res, 2011. 219(1): p. 55-62. - Bozkurt, A., et al., CatWalk gait analysis in assessment of functional recovery after sciatic nerve injury. J Neurosci Methods, 2008. 173(1): p. 91-8. --- ## Four ways to study visitor behavior URL: https://noldus.com/blog/study-visitor-behavior-on-site-living-lab Published: 2020-04-06 10:00:00 Description: Museums, zoos, theme parks, and aquariums all observe the behavior of their visitors in order to find the best ways to entertain and educate. Museums, zoos, theme parks, and aquariums all observe the behavior of their visitors in order to find the best ways to entertain and educate. In Timing and Tracking: Unlocking Visitor Behavior, Steven Yalowitz and Kerry Bronnenkant review the history of timing and tracking in museums and provide a detailed description of methods used to record, analyze, and report timing and tracking data. Visitor behavior studies through the years Yalowitz and Bronnenkant explain that in the past, researchers only recorded where the visitor went (and in some of the earliest studies, they even tracked wear patterns on the carpet!) Today, researchers record which displays visitors look at, for how long, and which paths they take to walk through the exhibition. At the same time, they describe if the visitors' expectations are met. Exhibition designers and planners are very interested in knowing if the exhibition has a good flow and whether visitors are engaging the exhibition as intended. Software versus Paper-and-Pencil methods In terms of methodology, a lot of researchers still rely on paper-and-pencil methods to record how visitors move through exhibitions. Yalowitz and Bronnenkant found some limitations to this commonly used research method. They explain that electronic behavioral coding and analysis systems such as The Observer XT have distinct advantages over paper-and-pencil measures – they are more accurate, able to record separate times for concurrent behaviors, easy to learn, do not require data entry, and are less intrusive to visitors. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Four ways to study visitor behavior - Pencil-and-paper methods – simple and affordable but with some limitations. - Code behaviors on the go using handheld computers - provides precise timing data and is relatively unobtrusive. - Cameras with laptop, coding, and analysis software (portable lab) – video is very useful and facilitates accurate data collection, but is not always suitable. - Living lab set ups – an advanced set up including dome cameras, eye trackers, and more. Interested? Read on! Below I'll describe three examples of visitor behavior studies. Observational research gives insight into how visitors behave and how learnings can be improved. Example one: Lincoln Park Zoo Stephen Ross and Katie Gillespie (2009) recorded the behavior of 338 visitors at the Regenstein African Journey in Lincoln Park Zoo using handheld computers in order to evaluate the use of the building and educational components. They found that the use of signs and symbols differed: those in groups without children spent more of their visit engaged with signage than those with children. Example two: The Field Museum, Chicago's natural history museum Researchers from Loyola University Chicago chose a museum as the setting for their experimental and observational research. They were specifically interested in how young children experienced an exhibit. In this blog post you can learn how they designed the study. Example three: Visitor behavior in the living treehouse at Zoo Atlanta The aim of this project was to study visitor behavior in the Living Treehouse at Zoo Atlanta. Montana Holland and colleagues from Kennesaw State University report that visitors spent significantly more time watching animals than reading signage. Limited interaction with relatively static displays may not lead to the intended change in knowledge and conservation attitudes among zoo visitors. Read more about this project in this poster presentation. References - Ross, S.R.; Gillespie, K.L. (2009). Influences on Visitor Behavior at a Modern Immersive Zoo Exhibit. Zoo Biology, 28, 462-472. - Yalowitz, S.S.; Bronnenkant, K. (2009). Timing and Tracking: Unlocking Visitor Behavior. Visitor Studies, 12 (1), 47-64. - Visitor Behavior in the Living Treehouse at Zoo Atlanta - Poster presented at the 20th Annual Symposium of Student Scholars at KSU and the 14th Georgia Undergraduate Research in Psychology Conference, April 2015. View poster presentation --- ## Antidepressants during pregnancy: effects on offspring social behavior URL: https://noldus.com/blog/antidepressants-during-pregnancy-offspring-behavior Published: 2020-03-31 12:00:00 Description: Many depressed women struggle with this: can I use antidepressants during pregnancy? The lab of Jocelien Olivier studies the effects of SSRI's on offspring behavior in an animal model. Today, we have another guest blog post for you. Danielle Houwing is kindly sharing her experiences using PhenoTyper and The Observer XT in her research on the use of antidepressants during pregnancy. Enjoy reading! Depression and antidepressant treatment during pregnancy During pregnancy, about 1 in 5 women experience depressive symptoms, resulting in a major depression in about 5% of pregnant women. Many depressed women struggle whether to initiate or continue antidepressant treatment during pregnancy. Selective serotonin reuptake inhibitors (SSRIs) are the most frequently prescribed antidepressants as they have been considered relatively safe for both mother and child. However, SSRIs cross the placenta and are evident in breast milk, reaching the developing child. The consequences of depression and medication on child development Both maternal depression and SSRI antidepressant treatment have been associated with changes in neurodevelopment of the offspring. For example, taking SSRIs during pregnancy has been associated with an increased the risk for the child to develop a social disorder such as autism spectrum disorder [1], but effects may be the result of the underlying depression [2]. So far, clinical studies have been unable to completely separate the effects of the SSRIs from the effects of the underlying maternal depression. Using an animal model of maternal depression, we were able to dissociate these effects. An animal model of depression In the lab of Jocelien Olivier at the University of Groningen, we developed an animal model for depression. This animal model is based on the assumption that humans with lower gene expression levels of the serotonin transporter (SERT) are more susceptible to stress and have an increased risk to develop mental disorders after repeated exposure to stressful (early) life events. Therefore, we exposed female rats with reduced SERT gene expression to early life stress, which induced a depressive-like phenotype later in life [3]. Treatment with selective serotonin reuptake inhibitors Subsequently, both healthy and depressive-like female rats were treated with the SSRI fluoxetine (FLX) or a placebo throughout pregnancy until weaning of the pups. This way, we could study the effects of the maternal depression and FLX treatment, both separately as well as combined, on offspring social behavior. Assessing offspring social behavior We tested male and female offspring in various tests for social behavior, including juvenile social play behavior and adult social interaction. Social play behavior was tested at 4-5 weeks of age. Animals were matched with a same sex and same treated partner and were allowed to socially interact in PhenoTyper cages for 15 minutes under red light conditions. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Social (play) behavior Play behavior was videotaped from above using an infrared camera in the PhenoTyper top unit and four couples in different cages were tested at the same time (Figure 1). Characteristic play behaviors such as pouncing and pinning were manually scored using The Observer XT. At 10-11 weeks, adult animals were again tested for social interactions with the same play partner and adult social behavior was scored using The Observer XT. Antidepressant treatment reduces offspring social behavior, sex dependently Our results showed that offspring from mothers treated with FLX antidepressant are considerably less social than offspring from placebo treated mothers. More specific, FLX treatment of the mother lowered juvenile social play behavior in both sexes, while the combination of FLX treatment and the depressive phenotype of the mother reduced social play behavior in male offspring, but not in female offspring [4]. Social effects less pronounced later in life The observed effects of FLX treatment were still present, but less pronounced for adult social interaction in male offspring and were completely absent in female offspring. A considerable impact Overall, the present study agrees with clinical work showing that FLX treatment during pregnancy increases the risk for children to develop a social disorder, as we found a considerable impact on social behavior in rat offspring as well. Effects are especially evident in male offspring, suggesting that they are more vulnerable to the FLX treatment than female offspring. Making informed decisions during pregnancy These findings provide new information on the effects of SSRI treatment during pregnancy on offspring neurodevelopmental outcome, which can help pregnant women that are suffering from a depression during pregnancy, as well as their physicians, to make more informed decisions about the initiation or continuation of antidepressant treatment. FREE EthoVision XT in education Dr. Jocelien Olivier from the GELIFES institute at Groningen University shares her experiences with teaching video tracking. - Most validated video tracking tool in labs - Easy to learn Watch now References - Andalib, S., Emamhadi, M. R., Yousefzadeh-Chabok, S., Shakouri, S. K., Høilund-Carlsen, P. F., Vafaee, M. S., et al. (2017). Maternal SSRI exposure increases the risk of autistic offspring: A meta-analysis and systematic review. Eur. Psychiatry 45, 161–166. doi:10.1016/j.eurpsy.2017.06.001. - Brown, H. K., Hussain-Shamsy, N., Lunsky, Y., Dennis, C. L. E., and Vigod, S. N. (2017). The association between antenatal exposure to selective serotonin reuptake inhibitors and autism: A systematic review and meta-analysis. J. Clin. Psychiatry 78, e48–e58. doi:10.4088/JCP.15r10194. - Houwing, D. J., Ramsteijn, A. S., Riemersma, I. W., and Olivier, J. D. A. (2019a). Maternal separation induces anhedonia in female heterozygous serotonin transporter knockout rats. Behav. Brain Res. 356, 204–207. doi:10.1016/j.bbr.2018.08.031. - Houwing, D. J., Staal, L., Swart, J. M., Ramsteijn, A. S., Wöhr, M., de Boer, S. F., et al. (2019b). Subjecting Dams to Early Life Stress and Perinatal Fluoxetine Treatment Differentially Alters Social Behavior in Young and Adult Rat Offspring. Front. Neurosci. 13, 1–15. doi:10.3389/fnins.2019.00229. --- ## Consumer behavior research in the spotlight: consumption behavior URL: https://noldus.com/blog/measure-disgust-gut-wrenching-movies Published: 2020-03-27 16:30:00 Description: Why do we drink less when watching gut-wrenching movies? How does exposure to moral violations influence consumption? It has never been said that humans are immune to the emotional effects of lying, stealing, and cheating, but the majority of us are not easily fazed since we encounter this type of thing every day. It might only be a fragment of a movie we are watching: morally offensive acts such as crime and deception are all around us on the news, in the papers, and on the streets. Cindy Chan and her colleagues (Department of Marketing, Wharton Business School, University of Pennsylvania) posed the question: How does exposure to moral violations influence consumption? The researchers explain that, for example, people may drink less coffee while reading the Sunday paper's exposé of corporate fraud, a violation of ethical business practices. Or people may consume less candy at the theater while watching Wall Street, a film that portrays destruction, crime, and greed. Consumer behavior research: investigating disgust To find answers, Chan and colleagues started by investigating disgust. Why this emotion? When confronted with disturbing scenarios, people often feel disgusted and exhibit this disgust in their faces. Core disgust involves for example facial activity such as nose wrinkling, upper lip retraction, and gaping; and disgust also produces distinct behavioral responses, including withdrawal from or avoidance of food intake (Ekman & Friesen 1975, 1978). The researchers explain that if moral disgust is grounded in core disgust, then moral disgust should elicit a similar multi-model response profile, including reduced oral consumption. In order to investigate this missing piece of critical evidence, they set up three types of experiments. Three experiments Cindy Chan and colleagues tested whether people involved in situations where moral principles were violated consumed less than those in control conditions. The tasks included: - watching a film portraying incest - writing about cheating or theft - listening to a report about fraud and manipulation In all three experiments, self-reports were used to measure the level of disgust of the participants. For example, in the film experiment participants were asked to report how offended they felt after watching the movie. In the second experiment the researchers took the scores participants gave the characters in their own made up story (was the character in any way involved in something immoral, unfair, and harmful?) and calculated an index of moral violation by averaging scores on immorality, unfairness, and harmful behavior. Both in the first and second experiments, the researchers found that a higher level of moral violations correlated with reduced oral consumption. The third experiment involved listening to a report about fraud and manipulation: a clip about the London Interbank Offered Rate (LIBOR) scandal, in which banks were described as engaging in deceitful activities to manipulate interest rates. In the control condition, participants heard a similar recording about the LIBOR scandal; however, the story was told from a different angle and was described as the effect of unintentional errors. Another group listened to a recording of Mazurka No. 10 in B Flat Major Op. 17-1, a classical piano piece by Chopin. As with the other two experiments, the researchers aimed to create a typical consumer experience in this case: listening to the radio while drinking a beverage. Participants were asked to imagine themselves having breakfast and listening to the radio. Using automatic facial expression analysis to measure disgust In the listening experiment, in addition to self-reports, participants' faces were video recorded and analyzed. Chan et al. used FaceReader to observe facial expressions of disgust in both the experiment and control conditions. The FaceReader software measures seven emotional expressions for every video frame in which it can find and classify a participant's face: disgusted, scared, sad, angry, surprised, happy, and neutral. FaceReader measurements showed that when participants were listening to the scandalous news story, the emotion they most frequently expressed was disgust – whereas no significant differences were found concerning the other 6 facial expressions measured. As in the previous two experiments, these results indicated that participants drank less when exposed to morally unacceptable situations. Moral disgust influences consumption The researchers conclude that moral disgust influences consumption in ways similar to core disgust, and thus provides evidence for the link between moral violations, emotions, and consumer behavior. One last word from Cindy Chan and her colleagues: This research highlight a psychological truth in the metaphorical observation that moral violations "leave a bad taste" in one's mouth. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Reference Chan, C.; Van Boven, L.; Andrade, E.B.; Ariely, D. (2014) Moral violations reduce oral consumption. Journal of Consumer Psychology, 24 (3). --- ## How bank voles take the future into account URL: https://noldus.com/blog/bank-voles-cross-generational-scent-behavior Published: 2020-03-25 12:00:00 Description: Bank voles are often exposed to predator odor and alarm pheromones. This perceived predation risk may cause cross-generational behavior changes, which seem to be context-dependent on their in utero exposure. As a researcher, you are always proud of the projects you work on, so I am happy to share this article about my own research. My research team tried to identify if a predator's scent-triggered fear response could be transferred to the next generation of bank voles. The experiments described below resulted in definite proof that these cross-generational effects actually exist, which is fascinating to me. It also opens up pathways to many other potential studies on this topic. My personal favorites were trying to work out how well this mechanism works in an ecologically meaningful environment, and how exactly this transfer happens in the first place (i.e., what response is triggered by which scents). I am very grateful I was able to contribute a small, but significant part to this study. Enjoy reading! Copyright © Airwolfhound from Hertfordshire, UK / CC BY-SA (https://creativecommons.org/licenses/by-sa/2.0) Predator - prey interaction Predator odors and alarm pheromones For this study on bank vole behavior, I collaborated with researchers from the Netherlands and Finland. In the wild, bank voles are hunted by the least weasel. If they survive an encounter with this predator, they produce a specific scent (i.e., alarm pheromones) which warns conspecifics of weasel presence. The scent of the weasels themselves are also an olfactory (i.e., scent) warning. Behavioral changes These scents play an important role in bank vole survival and cause them to change their behavior. They might avoid high-risk areas and try to find hiding places. It might even be possible, likely through hormonal pathways, that they can change their offspring's behavior. Experimental design We wanted to find proof for this cross-generational behavior transfer. We started the experiments by preparing nine 50 x 50 m outdoor enclosures, each containing 25 live traps. Early in the mating season we put six females and four males in each enclosure, so 54 females and 36 males in total. The voles are divided over three groups, i.e., Control Treatment (C), Predator Odor (PO) and Alarm Pheromone (AP). The offspring from each group (F1) is again divided into three groups, resulting in nine unique treatment groups. Parental odor treatment The group of 90 voles was divided into three (i.e., 3 enclosures per group), and after activation we checked the live traps twice a day. Whenever a vole was trapped, we would expose it to either predator odor (PO, weasel bedding), alarm pheromones (AP, bedding of a weasel-exposed bank vole), or to a control scent (C, clean bedding) for three minutes. During this two-week period they had the possibility to mate. After the period ended, all voles were caught and brought to a lab where we put them in individual cages. Then, we checked females twice a day to see if they had given birth. Pup odor exposure After weaning, the pups that were born from these voles were again divided into three groups, PO, AP and C (see figure X). Each pup underwent a behavioral test in an open arena, in which bedding was spread out containing the pup's assigned scent. Then, we put the voles in the center of the arena and let them explore for 10 minutes. All experiments were filmed and later analyzed using Noldus Ethovision XT. We recorded the vole's total movement distance, movement bouts (i.e., a constant movement with --- ## A coding scheme to capture interactive behaviors during triadic consultations URL: https://noldus.com/blog/development-coding-scheme-to-capture-interactive-behaviors Published: 2020-03-23 09:51:00 Description: The research team of Yuan developed and refined a coding scheme which can serve as a tool to identify specific triadic communicative strategies that are effective in improving children’s engagement and reducing distress. Usually, when I have an appointment with the dentist, it's for a checkup, which is nothing to be afraid of. Still, there are always those scary noises and weird smells when I enter the dentist's practice. They then ask me to lie down in a chair, horizontal, with my mouth wide open, as I wait for what is to come. More than not, all these stimuli do frighten me. My children are all teenagers now, but I still go with them when they have an appointment with the dentist. I want to make sure that they are really going. However, when they were younger, there were more reasons than just that. As a parent, my role was to support them and help them communicate with the dentist. How does such an interaction between a child, parent, and dentist actually work? Triadic communication between dentist, child and parent It is important we prepare children to understand dental procedures in order to enhance oral health outcomes. But, young children are more likely to become anxious when they visit dental practices due to the potentially invasive nature of treatment and perceived threatening stimuli. Because of this, good communication is of great importance. To identify specific triadic communicative strategies that are effective in improving children's engagement and reducing their distress in the dental setting, Yuan and her research team used a communication coding system as a tool. Download here the FREE white paper 'How to set up behavioral coding - 7 tips' A video-based observational study As part of the Childsmile Programme in Scotland, children from ages two to five years old received advice twice (annually) about oral hygiene, sugar consumption, and healthy snacking as well as a fluoride varnish application. The study of Yuan et al. was conducted within this program. Five dental professionals and 50 child-parent/caregiver dyads participated. The interaction within the triad of dentist, child, and parent was recorded real-time, in order to capture both verbal and non-verbal communication behaviors. Developing the coding scheme Based on an iterative process, the research team developed a coding scheme: the Paediatric dental triadic interaction coding scheme (PaeD-TrICS). The team sought for behavior codes that: - Captured the specifics of the triadic interactive features, such as the conversation flow between child & professional, child & parent, or professional & parent - Embodied the typical communicative behaviors that were exhibited in a dental setting and were representative of different participants - Reflected the specific features of this clinical context The result contained a list of 45 adult and child behaviors such as social talk, tell-show-do (TSD) talk, information giving, reassuring, rewarding (stickers), crying, withdrawing, and agreeing. The purpose of the TSD technique is to reduce the child's anticipatory anxiety and avoid subsequent behavioral problems. The inclusion of this specific code enabled the researchers to test whether 'TSD talk' will contribute to the prediction of child's cooperation when receiving dental treatments. Coding and analyzing data with The Observer XT The PaeD-TrICS coding scheme was converted to an electronic format for use with The Observer XT. With help of The Observer XT, the researchers conducted systematic observations to identify, code and analyze the data according to frequency, duration, timing, and sequence of the behaviors. The most frequent behavior during the triadic consultation was "parental verbal facilitation". Concerning dental professionals' behaviors, "dentally engaging talk", "praise", and "instruction" were most frequently seen in the consultation. Children's common behaviors included "speech other" (child says any other utterances except for 'yes' and 'no') and non-verbal behavior i.e. "non-verbal agreement" and verbal behavior "speech yes" to express their agreement. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial The primary coder coded all the observations. However, the research team introduced the second coder to double code four randomly selected videos (nearly 10% of sample) to assess observer agreement and ensure a consistent benchmark. The inter-coder consistency was assessed twice with Cohen's Kappa of 0.83 (95%CIs: 0.81, 0.85). The intra-coder Cohen's Kappa was 0.90 (95%Cis: 0.89, 0.92). The triadic interaction captured The PaeD-TrICS demonstrated its capability to embody the detailed complex process of the triadic interaction in a pediatric dental setting. Among others, it offers the opportunity to assess child involvement in the consultation, which is a valuable addition. It can enhance future research to test the extent of child participation in the healthcare encounter. Additionally, the research team advises to use video observation software to examine the effect of communication behaviors on outcomes (clinical outcome, behavior outcome, etc.) and investigate the association between behaviors. Reference Yuan, S.; Humphris, G.; MacPherson, L.; Ross, A. & Freeman, R. (2019). Development of an interaction coding scheme (PaeD-TrICS) to record the triadic communication behaviours in preventive dental consultations with preschool child patients and families: a video-based observational study. BMC Oral Health, 19 (162). https://doi.org/10.1186/s12903-019-0836-z --- ## Working from home strategies URL: https://noldus.com/blog/working-from-home-strategies Published: 2020-03-18 10:51:00 Description: In the midst of an unprecedented global pandemic, many people find themselves in a particularly novel situation in the coming days and weeks: working from home. - WFH is not a working-PTO - Have a "commute" - Develop a workspace and a routine - Know how to reach your network - Embrace the perks but avoid the pitfalls In the midst of an unprecedented global pandemic, government agencies and companies alike are rightfully taking aggressive strategies to avoid the spread of Coronavirus. As a result, many people find themselves in a particularly novel situation in the coming days and weeks: working from home. Since many of you are experiencing this for the first time, I thought I might share some of my tips and strategies for making the most of your time. Granted, everyone's experience is different. But I've had to sit through meetings with My Little Pony playing in the background. I've had to lead a remote training session with what seemed like a herd of cattle stampeding over my head (turns out it was two teenagers playing Just Dance). So I empathize with your situation. Together we'll get through and before you know it, you'll be back at the office wishing you were at home in your pajamas. 1. Working from home is not the same as a working PTO day Despite your lack of commute, despite the fact that you didn't shower this morning and are still in your pajamas (like me), and despite the load of towels you just put in the washing machine, working from home is not a staycation. Sure, it has perks, which we'll discuss, but first and foremost, you have to work. That might seem obvious, but it's important to remember. Turn off that TV, limit your distractions, and remember that today is still a workday. 2. Have a "commute" A few years ago, I met a qualitative researcher in Boston who also worked from home. She said that she gets ready for work and leaves the house. She walks around the block and comes into the house through the back door to signify that it is time to work. When her workday ends, she leaves through said door and walks back around to the front to signify her coming home. One of the biggest challenges to working from home is getting into a "work-mode" mindset. Although you don't have to drive, it might be helpful to mimic some sort of commute to get your head ready for the day. I take our Aussiedoodle, Winston, for a 15-30 min walk in the morning before work. When we get home, I give him breakfast, I get coffee, and then I head downstairs to my office to begin my day. When my day is over, I shut down my computer, put my phone on Do Not Disturb, and then Winston and I go back outside and play. Being the smart little bugger that he is, he always comes downstairs at about 4pm to 'remind' me that it's getting to be 'that time'. But more than just some exercise in an otherwise sedentary day, it helps me mentally prepare for my day and decompress afterwards. Whatever it is for you, find a way to signify the start and end of your day. 3. Develop a workspace and a routine Humans, like all animals, are habit-based creatures. Our brains are lazy. That lump of fat in your head that's about the size of both of your fists uses approximately 20% of your body's energy. Mental energy is expensive and automation helps conserve that energy. At work, we all have routines to help maximize our capacities and energy. Then suddenly your office isn't there anymore. Now what? Well, it's important to establish a workspace and develop some routines. Most of us who regularly work remotely have a dedicated area to do so. A few years ago, we lived in a smaller place and I didn't have an 'office', per se. I set up each morning on the kitchen table. Each night I would have to 'break down my office' so we could have dinner together! I had piles of papers downstairs and each day I'd have to recreate my work area before I could start my day. Not ideal. Once we moved, the first priority was getting my own desk and space to add a second monitor, leave my notes, extra USB drives, and misc items strewn about. This devoted space affords you the opportunity to get your own routine and get into the groove of remote productivity. It also keeps you separated from the rest of the house, particularly your spouse and/or kids. Since they're also home, they don't want to hear about the latest innovations in human behavioral research, nor do you want to hear another episode of Doc McStuffins! Having that space gives you freedom to work. Likewise, it gives you a great place to develop your own habits for success. Robert Miller, the CEO of IntelliQ Health, told me that when he first started working remotely that he used an egg timer to segment his day. He would work on any given task until the timer went off, then he would stand up, stretch, get coffee/water, take a bio-break, etc, then go back to work with a new timer. It helped focus his time and energy so he could stay productive. 4. Connect to your network Let's face it, working from home can be a lonely experience. Even with the kids (or pets) around you, working in a remote office is isolating from your colleagues. While us introverts don't particularly mind, it's important to know you're not alone or 'on an remote Noldus island', as a former colleague used to say. Fortunately, we all have Slack, Skype, Zoom, etc, to help us connect with our colleagues. For extroverts, setting up a video conference might be necessary, whereas for some of us introverts, a quick check-in chat message will suffice. Don't let yourself feel alone. Unfortunately, avoiding public places and human interaction is frowned up, so I don't recommend going to the library or meeting up with colleagues for lunch. Stay in self-quarantine and turn on your webcam; just remember to put on a clean shirt before you do! MEASURE YOUR EMOTIONS What does your face say? Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality. - Enter a url or browse for an image - Use passport photo like pictures - Make sure that the pictures you upload are the best they can be Download 5. Embrace the perks and avoid the pitfalls Despite its potential for loneliness, working from home can be wonderful. You'd be amazed at how productive you can be without the phones, chatter, or distractions of colleagues. Plus there is no commute and you can stay in your pajamas all day! But working from home is also great because you can accomplish household chores as well. Winston needs to go outside for a bio-break? Oh ok, I'll let him out. The dishwasher needs emptied? Great, I can do that while my lunch heats up in the microwave. The break helps divide your day like Robert's egg timer. Now, small household chores are simple and don't take much time. Am I saying you should leave your desk to repaint the kitchen or go cut the grass? Um, no. I don't advise that. Take the dog out for a quick break, don't walk him around the neighborhood for an hour. Be smart. Again, you have a job to do. It's easy to plop down on the couch, laptop in your lap, and turn on the TV. "I can work while I'm watching Law and Order", you say. But can you? Remember Point #1: this isn't a staycation. I know your kids are happy to have mom or dad at home. I know your pets love having you around. But just because you're at home doesn't mean you're at home to be home. It is a balance and you have to be smart. Enjoy the opportunity to be home and take advantage of what you can get done. Just don't take too much advantage and lose productivity to your office. Speaking of which, I hear the timer on the dryer. My towels are done. Time for my quick break. Enjoy your time at home, stay safe, wash your hands at every instance, and be grateful that we live in a time in history where we can all be remote without losing productivity and/or connectivity to our office, colleagues, and customers. What did I miss? What strategies do you have for helping us all get through this pandemic? --- ## Livestock Research: Tracking sheep to learn their behavior URL: https://noldus.com/blog/tracking-sheep Published: 2020-03-16 12:00:00 Description: We recently installed TrackLab at Aberystwyth University in Wales, UK, for the tracking and detailed analysis of the spatial behavior of sheep. Bhaa Bhaa now time to eat! There is still a lot to learn about the behavioral and social patterns in sheep. The more we know about them, the better we can improve the health and welfare of these livestock animals. Recently, researchers found out that 'Sheep know the grass isn't always greener when it comes to their health'. Sheep appear to forage and avoid parasites differently depending on how healthy they are, according to the new University of Bristol research published in Proceedings of the Royal Society B. For outdoor tracking, the researchers used remote GPS sensing data to monitor the foraging patterns of sheep. Indoor tracking, on the other hand, is another field of study. We were recently involved in a research project where the researchers were interested in using indoor tracking methods to understand behavioral patterns & activity in sheep. The focus is increasing the health & welfare of these livestock animals. Read this blog to learn more about the Aberystwyth University's project in sheep behavior tracking. TrackLab at Aberysthwyth University in Wales, UK Noldus consultants installed TrackLab at Aberystwyth University in Wales, UK, for the tracking and detailed analysis of the spatial behavior of sheep. TrackLab TrackLab is the system designed for the recognition and detailed analysis of spatial behavior. The software tracks animal movements and can help researchers analyze & understand their behavior, as well as recognize social interaction patterns. Researchers can gain insights such as location preference, if they are walking, running, standing still or lying down, and how these animals transition between areas. Analysis and statistics can be collected for the whole research area, or for specific zones (e.g. by the feeder). Collecting these patterns and activity can all be done automatically with TrackLab, which uses Ultra-Wideband (UWB) sensors and tags for precise location tracking. TrackLab for Livestock Research at Aberystwyth University Aberystwyth University's Institute of Biological, Environmental and Rural Sciences (IBERS) recently chose TrackLab to help understand the behavioral patterns and activity of sheep, within the scope of the small ruminant phenotyping platform integrated in the Centre for Innovation Excellence in Livestock (CIEL), one of United Kingdom's four Agri-Tech Centres. They seek to examine sheep exploratory behaviors (distance walked, speed), location (animal dispersion within the pen, where they tend to rest and ruminate), and eating & drinking patterns (time spent at the feed bunk and drinker stations, at what time of the day). The researchers also hope to get more information on social interactions, sheep's temperament, and affective state under different scenarios. The whole system uses time stamped x, y, and z coordinates. The x and y pinpoints the location of a sheep in the pen. With the z coordinate, the height of the tag is measured, which is on the top back of a sheep, and from this one can derive if a sheep is standing or lying down. This installation process was a simple setup that took 2 days. The first day was the hardware installation, which included cabling and positioning the sensors to their correct angles. The second day was tuning the system. Tuning is the necessary step to calibrate the tracking equipment with the software to get accurate tracking data. Around 15 cm accuracy was achieved! The group of researchers received a formal training on how to use the entire system, as well as the TrackLab software for their behavioral research and analysis. Conclusion The installation of TrackLab was a success at the Aberystwyth University and the team present for the installation were pleased with the accuracy and possibilities of the system. FREE DEMO Get a virtual walkthrough! Request a demo to obtain real-time insights into the activity, welfare, and health of your livestock. - Accurate tracking data - Gain insights into many parameters - Easily access, export, and analyze data Free Demo Interested in learning more about TrackLab? Find resources about TrackLab, read about new and upcoming functionalities, or learn about how TrackLab can benefit your research! --- ## Non-invasive home cage testing of epilepsy in mice URL: https://noldus.com/blog/home-cage-study-epilepsy-mice Published: 2020-03-13 12:08:00 Description: Epilepsy is more than seizures; behavioral changes that occur in between seizures are rarely assessed. A new home cage study from the Baylor College of Medicine aims to change this. Epilepsy is a very common chronic neurological disorder, affecting people at all ages, all over the world. Although it can be successfully treated, treatment doesn't work for everyone, so research on epilepsy remains important. Epilepsy disability The burden of unpredictable seizures is not the only debilitating factor of epilepsy. The severity of seizures and the acute medical complications make up the so-called ictal component of epilepsy. There is also an interictal component to this disease, such that patients with epilepsy suffer from high rates of depression, anxiety, autism and other mental health disorders. The determinants of interictal behavior are largely unknown. Home cage study of epilepsy A recent study from the Baylor College of Medicine (Houston, TX) aimed to change this. Jankovic, Kapadia, and Krishnan performed a quite elaborate home cage study to measure both the ictal and interictal severity of epilepsy. They described the daily behavioral patterns of three mouse models of epilepsy, with complete automation. No human interference, no surgical implants. Data integration The study was based on PhenoTyper home cages with cameras for video tracking with EthoVision XT. They were equipped with infrared-lucent shelters, Lickometers to measure drinking, Feeding Monitors, and a running wheel. Data from these devices was brought into EthoVision XT and used to complement video tracking data. Alternatives to EEG testing The gold standard to detect seizures is an invasive procedure involving surgically implanted EEG electrodes. Jankovic and her colleagues choose a different approach (integrated visualization), measuring the seizure severity by screening all spikes in mobility from the video tracking data and confirming true convulsive seizures. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial How to measure the interictal severity of epilepsy To assess the interictal component of the seizures, the researchers used kinematic and behavioral parameters from both the video tracking data and devices, monitoring feeding, drinking, distances, and sheltering. They also did additional testing with a light spot and cage swap. PTZ model of epilepsy In line with other epilepsy studies, researchers used PTZ (Pentylenetetrazole) injections to evoke seizures in mice. After two days of baseline recordings in PhenoTyper home cages, mice were subjected to 10 daily PTZ injections or saline as a control group. They measured the acute effects of the injections in the first 90 minutes, interictal effects were measured in the following 19 hours. Effects of PTZ on wild-type mice The first tests were done with a commonly used wild-type strain (C57BL/6J). Here, relative to saline, PTZ injections caused profound hypoactivity in the first half hour, followed by relative hyperactivity in the next hour. During that time, mice also displayed a significant sheltering deficit. Therefore these researchers hypothesize that immobility outside the shelter may represent a objectively measurable behavioral correlate of the severity of a first time seizure. These behavioral effects improved over subsequent injections of PTZ, but so did the likelihood of convulsions. Seizure severity and behavioral effects Interestingly, the severity of the seizures also correlated with different behavioral effects: convulsive seizures resulted in an early activity spike, while non-convulsive (milder) seizures seemed to be associated with a more sustained sheltering deficit and relative increase exploratory activity. RESOURCES Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources PTZ and seizure-susceptible mice Next, researchers were curious about the effects of PTZ on the DBA/2J strain, mice that are known to be more susceptible to seizures. Indeed, they convulsed sooner and more severely after PTZ injections. But even prior to PTZ injections, they were also less active and had different feeding and sleeping patterns. Testing Dravet mice Finally, a mouse model for Dravet syndrome (Scn1a+/-) underwent home-cage testing. This neurodevelopmental disorder is characterized by intellectual disability, autism spectrum disorder, and epilepsy. Compared to their wild-type littermates, these mice showed early hypoactivity, without alternations in feeding and sheltering. Showing similarities with PTZ-treated mice, Dravet mice spent more time sheltering at the cost of reduced feeding. They also slept more and in longer bouts. Unique epilepsy study What's interesting about this study is that it uses home-cage testing to identify aspects of epilepsy disability in mouse models across both ictal and interictal domains. It also shows that both ictal and interictal effects differ for different strains of mice. We already knew that repeated injections of PTZ make mice more susceptible to convulsions. This study shows that changes in behavioral severity are more complex and may reflect a habituation to PTZ. By identifying similarly altered patterns of home-cage behavior across three different models of generalized epilepsies, these data lend to further studies that compare these behavioral themes with focal and/or other genetic models of epilepsy. References Jankovic, M.J.; Kapadia, P.P.; Krishnan, V. (2019) Home-cage monitoring ascertains signatures of ictal and interictal behavior in mouse models of generalized seizures. PLOS ONE, e0224856. Header Photo by Levi Guzman on Unsplash --- ## Traumatic Brain Injury: effects on the brain and motor coordination URL: https://noldus.com/blog/tbi-effects-brain-motor-coordination Published: 2020-03-11 15:02:00 Description: Do you think of wearing a helmet while skiing, cycling or horseback riding? Read more about how the brain is affected after the head injury and how you can examine locomotion in a mouse model with TBI. Traumatic brain injury (TBI) occurs more often than you might think. After Dewan et al. gathered data from World Health Organization (WHO) and World Bank (WB), the results showed, that approximately 69 million of individuals suffers from TBI of all causes each year! Do you think of wearing a helmet on a bicycle, while skiing or rollerblading? Causes and symptoms of TBI TBI usually results from a bump, blow or jolt to the head, as a consequence of a fall, motor vehicle crash, violence, etc., and can lead to serious disruption in brain functioning. Traumatic brain injury can be mild, moderate, or severe based on the level of consciousness. A person with a mild TBI (commonly called concussion), may not experience loss of consciousness at all or only for a brief moment. People who suffer from moderate TBI are often drowsy, inactive and may lose consciousness for a few minutes to a few hours. In case of severe injury, the patient is extremely lethargic or comatose. Long-term effects of TBI People who endure TBI can suffer from different impairments. Those can be related to movement, memory or thinking, sensation (visual or hearing), or emotional functioning. The effects of TBI can last for a few days or a lifetime. Many studies actually show that we should consider TBI as a chronic health condition since it tends to evolve long after initial recovery. Improvement or deterioration can show up to two decades after injury and there is a bigger chance for a variety of neurological illnesses during this time (for example epilepsy, stroke, and neurodegenerative diseases). How it affects the brain Mild TBI typically affects brain cells only temporarily and full neurological recovery is common. Bigger changes may occur with more severe traumatic brain injuries, resulting in bruising, tearing of tissues, bleeding or other physical damage that injure nerve fibers and cause inflammation, progressive neurodegeneration, and chronic neurological dysfunction. How the initial biomechanical injury transforms into a chronic neurodegeneration and neuroinflammation is still not completely clear. Most observations of neuropathological changes and neurological dysfunctions are done shortly after TBI, focused on histological analyses. But what about functional outcome at the cellular levels after a couple of months of moderate TBI? Investigating late neurobehavioral changes after TBI Ritzel et al. tried to answer this question by running different tests (motor performance, depressive-like and social behavior, learning and memory) and looking at neurons and microglia in mouse model 8 months after controlled cortical impact (CCI) injury (which is a typical localized injury in TBI mouse model). They confirmed that the late neurobehavioral changes in their mouse model were similar to those found after moderate/severe human head injury and that these changes are associated with changes in neuronal activity and microglial dysfunction. As mentioned above, the researchers also examined motor performance in mice after 26 weeks of experimental CCI injury and with this address the issue that not a lot of research was done in later point after the TBI in mice. It is important to keep in mind that experiments done several months after injury in mice can be translated to decades in human years. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Motor performance after traumatic brain injury Motor dysfunctions are common, especially in moderate to severely injured patients. These impairments may include loss of fine motor control and coordination, and difficulty with balance. Even though the goal of rehabilitation is to restore functional impairment and improve quality of life, the recovery of motor deficits is usually not complete. Examination of motor performance is extensively studied in animal models of stroke and focal lesions, and not so much in animal models of TBI. Further testing is therefore necessary to understand the motor (recovery) process and rehabilitation process after the head injury. Measuring motor coordination in a mouse model with TBI For assessing motor coordination, Ritzel et al. used the automated system CatWalk XT from Noldus Information Technology. At the beginning of the experiment they placed a mouse on the open end of the CatWalk XT under the red ceiling light. From there, the mouse walked over the green illuminated walkway towards the goal box. While walking across the walkway, the software obtained live footprint videos that were later used for the analysis. Researchers gathered data for at least three valid runs for each subject through a complete walkway. If the animal stopped or turned around during a run through the walkway, they excluded the trial from the analysis. Altered locomotion after TBI To evaluate motor coordination, researchers looked at the regularity index. Their results showed a significantly reduced regularity index in mice with CCI injury in comparison with control mice. Even though there was no significant difference in number of steps or average speed between the control and experimental groups, the differences showed in multiple other observations. Mice with TBI had decreased stride length of the right hind limb and there was a decrease in swing speed in right-sided limb movement. The distance between print position of the front right paw and the hind right paw was significantly increased and there was bigger asynchrony in paw movements between placements of two paws in mice with TBI. Overall, Ritzel et al. concluded that their mouse model with TBI suffered from chronic disruption in gait-dynamics. Towards better rehabilitation programs Traumatic brain injury occurs very commonly among people and differs in severity and symptoms between individuals. Even though some aspects of TBI are extensively studied, there is still a lack of research done on functional outcome after a longer period of time post-injury. One of the missing aspects is also motor performance. For this reason, it is important to further examine and truly understand the motor recovery and rehabilitation process after traumatic brain injury in order to offer better rehabilitation programs. References - Ritzel, R. M., Li, Y., He, J., Khan, N., Doran, S. J., Faden, A. I. and Wu, J. (2020). Sustained neuronal and microglial alterations are associated with diverse neurobehavioral dysfunction long after experimental brain injury. Neurobiology of Disease, 136 - Dewan, M. C., Rattani, A., Gupta, S., Baticulon, R. E., Hung, Y.C., Punchak, M., Agrawal, A., Adeleye, A. O., Shrime. M. G., Rubiano, A. M., Rosenfeld, J. V. and Park, K. B. (2018). Journal of neurosurgery, 1, 1-18. - Wilson, L., Stewart, W., Dams-O'Connor, K., Diaz-Arrastia, R., Horton, L., Menon, D. K. and Polinder, S. (2017). The chronic and evolving neurological consequences of traumatic brain injury. Lancet Neurology, 16 (10), 813-325 - Corrigan, J. D. and Hammond, F. M. (2013). Traumatic brain injury as a chronic health condition. Archives of physical medicine and rehabilitation, 94 (6) - Forslund, M. V., Perrin, P. B., Roe, C., Sigurdardottir, S., Hellstrom, T., Berntsen, S. A., Lu, J., Arango-Lasprilla, J. C. and Andelic, N. (2019). Global Outcome Trajectories up to 10 Years After Moderate to Severe Traumatic Brain Injury. Frontiers in Neurology - Mayo Clinic Stuff. (2019). Traumatic brain injury. https://www.mayoclinic.org/diseases-conditions/traumatic-brain-injury/symptoms-causes/syc-20378557 --- ## Saying Ouch Without Saying It: Measuring Painful Faces URL: https://noldus.com/blog/measuring-painful-faces Published: 2020-03-02 10:20:00 Description: What happens when we’re in pain, real physical pain, but we cannot tell someone where or how badly it hurts? We can look at the facial expression! Unlike the song by Three Days Grace1, I am not a fan of pain. Call it Epicurean, call it hedonistic, whatever, I don't want to experience pain, either psychological or physical. In the past two months I lost a grandfather to dementia and a sister to a unfathomable act of violence. In the past three years I have been to more funerals than in my previous thirty-eight years combined. So yeah, I'm not a fan of pain. I don't like it when I stub my toe or twist my ankle, and I really don't like seeing a lifeless family member lying in a box. But it happens and you deal with it, either by relying upon your support network for emotional/psychological pain, or with something pharmacological for physical pain. This can be a slippery slope, of course, as opioid-abuse has reached epidemic status, particularly here in Southwestern Ohio2,3. There are some interesting neural mechanisms for this, which I won't go into here, but if interested I encourage you to check out some of my peer-reviewed published materials4. Non-verbal behavior instead of verbal behavior What happens when we're in pain, real physical pain, but we cannot tell someone where or how badly it hurts? For example, the last few weeks of my grandfather's life, he was non-verbal. First went English, then his native German, with the only remaining communication done in grunts, but only on some days. So how can his hospice care know if my Opa is in pain when he can't express that he's hurting? I assume you read the title, so spoiler alert: we can look at the facial expression. Not limited to basic facial expressions By now we all know FaceReader. It automatically analyzes facial expressions based upon the 'basic', universal expressions. However, a recent update to FaceReader now allows researchers the opportunity to design your own algorithms by combining variables such as facial expressions, action units, and heart rate to create "Custom Expressions". What this means is that we can create our own states and attitudes. We don't have to limit ourselves to happy or sad, but can expand our research horizons, so to speak. Now, let's get back to the topic at hand, introduced by Mr. T's Clubber Lang: pain5. Oh wait, let's back up one more second. Remember that in addition to the basic emotions, FaceReader can also classify twenty individual muscles, known as Action Units (AUs). The combination of AUs around the eyes and mouth creates the emotions we know and recognize. For example, smiling uses the cheek raiser, orbicularis oculi (pars orbitalis) - AU6, and the lip raiser, zygomaticus major - AU12. Action Unit 4, the brower, is involved in a host of emotions: anger, fear, concentration, and frustration. If you remember previous posts, the dimpler, AU14, is heavily involved in contempt as well as fake smiles. This means that it's not the individual muscles, per se, but the delicate interaction of all the muscles in our faces. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download The identification of pain in non-verbal patients Interestingly, pain is a really complicated expression. It involves a multitude of muscles, upon which some research agrees and others upon which there is disagreement (see review in Arif-Rahu & Grap, 20106). Recently, in collaboration with Dr. Thomas Hadjistavropoulos at the University of Regina7, we built a custom expression for the identification of pain in nonverbal ICU patients. The algorithm is based on a number of factors. Let's begin with the eyes. We start with AU9 and AU10, the lid tightener. Throw in AU4, the brower. Then look at the nose by adding AU10, the 'wrinkler'. Think about an unpleasant odor or something that disgusts you. For me, it's a walk-in cooler full of every species of cockroaches on Earth. Yuck. Sorry, distracted. So once the nose goes, though, the upper lip is quick to follow. This is AU17. The final act of the painful expression is the actual closing of the eyes, measured by AU43. Taken together you get a symphony of pain. Oh, that sounds like a great doom metal album. Reaction of the face to pain In order to test the new algorithm, I found a video on YouTube where people stuck their hands in ice cold water, a common test of pain8. As shown below, the algorithm works! Interestingly, if one were looking at the 'basic' emotions, one might say these people are disgusted or even happy, as the muscles for pain overlap with those individual expressions. But taken together, we see that the ice water is, in fact, causing physical distress and their faces are reacting accordingly. Of course, at first there is a bit of surprise, as the jolt of temperature lights up the face. But once the nociceptors start feeling that ice cold water, you can see the painful expression rise. Wanna try it for yourself? Feel free; take a video of yourself and send it to me*. I'll analyze it for you, unless of course I open my big mouth and offer something that results in thousands of images being sent to me daily. If that happens, we might have to build a new website to let you try it yourself, kinda like we did for RBF9. If you're feeling saucy and charitable, might I recommend the Polar Bear Plunge10. Which emotions can FaceReader analyze? Are there others, more complex emotions that FaceReader can analyze? Of course, hence the rhetorical question. Right now, FaceReader comes with an analysis of confusion, boredom, and interest. It would interest me to see your confusion or boredom while reading this. Too much? Ok, I'm almost done. At any rate, the emotional landscape has opened well beyond the initial six expressions, and researchers now have a powerful tool to automate complex expressions. Drop us a line and let's talk about what pains you in your research and how we can take the pain out of your facial expression analysis. *As a post script, I don't encourage you to record yourself getting seriously hurt. I was half-joking about the ice water, but that's the full extent to which I want you to feel pain. Interested in the algorithm for the identification of pain? Please fill in this form and we'll get in touch! References - Three Days Grace - Pain - UC Opioid Task Force - Mapping Cincinnati's Opioid Crisis - Rogers, J.L., Ghee, S., See, R.E. (2007). The neural circuitry underlying reinstatement of heroin-seeking behavior in an animal model of relapse. Neuroscience, 151, 579-88. - Rocky III - Pain Scene - Arif-Rahu, M. & Grap, M. J. (2010). Facial expression and pain in the critically ill non-communicative patient: state of science review. Intensive & critical care nursing, 26 (6), 343–352. https://doi.org/10.1016/j.iccn.2010.08.007 - Dr. Thomas Hadjistavropoulos - University of Regina - Ice Water Challenge - Test RBF - Polar Bear Plunge --- ## The role of parent-child interaction on child development URL: https://noldus.com/blog/role-parent-child-interaction-child-development Published: 2020-02-27 11:18:00 Description: When children face cognitive and motor delays, they are often unable to reach developmental milestones at the expected times. Does this influence the interactive behaviors of parents and children? As a child grows up, each parent looks forward to the milestones that their child will reach. Some of these milestones are keeping his/her head up high and steady, sitting upright without tumbling down, taking the first independent steps, saying the first intelligible words, responding to others, cycling without training wheels, and going to school. However, when children face cognitive and motor delays, they are often unable to reach the developmental milestones at the expected times. Delays that occur in gross or fine motor skills, language, social, emotional, or cognitive skills can cause learning difficulties, or problems in communicating and playing with others. Children with these type of difficulties seem clumsy or have trouble walking, or holding onto small objects such as toys. The earliest possible detection of developmental delays can be helpful in minimizing the impact these hiccups can have on a child's skill development and subsequently their confidence. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly Parents play a crucial role in child development When it comes to a child's general development, parents, or those who serve the parenting role in the child's life, are the most influential. A parent provides encouragement, support, and access to activities that enable the child to learn key developmental skills. A child learns throughout interactions, whether or not these are consciously aimed at encouraging child development. Van keer and her colleagues conducted a study to be able to characterize (the perception of) interactive behavior of both parents and children within this target group. The researchers applied a molecular approach in which specific interactive behaviors are registered within very small time segments (i.e. micro-level coding). The research team determined three questions that they wanted to answer in this study: - Frequency | which types of interactive behaviors are frequently shown by parents and children and which are not? - Co-occurrence | which types of interactive behaviors co-occur across participants? - Temporal dependency | which types of child interactive behaviors are temporally dependent on which types of parental interactive behaviors, and vice versa? Using a coding scheme to mark parent-child interaction A group of 29 parent-child dyads participated in the study. The children were between six months and four years old and had both a cognitive and a motor delay. Recordings of the dyads took place during a 15-minute unstructured play situation (either at home or at the familiar day care facility of the child). Parents received instructions to engage with the child as they would normally do and to play with toys the children were familiar with. Two cameras were used, each directed at one interaction partner. A self-developed coding scheme for ten interactive behaviors, such as looking, facial expression (e.g. smiling, crying, looking angry), touch, movement (e.g. pulling away, moving closer), object-related behavior (e.g. touching or taking a toy, biting on an object), gesture (e.g. waving, nodding), and vocalization of both parents and children was made. Coding was performed continuously, using The Observer XT with a time label that is accurate to the millisecond. Each code was rated as 'present' (1) or 'absent' (0) for each 1-second interval. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Frequency of interactive behaviors Both parents and children frequently showed the behaviors looking, vocalization, and movements, although the children showed these behaviors strikingly less. Parents showed facial expressions as well as object-related behavior somewhat more often than the children did. An obvious difference occurred in relation to touching behavior, which was more frequent in parents than children, who barely showed this behavior. Children need parental triggers Parents seem to look, touch, move, manipulate objects, vocalize, and show a facial expression at the same time on a regular basis. Even though the combined use of different behavior(s) is difficult for children with multiple disabilities, this study showed that these children do (to some extent) combine different types of behavior in interaction with their parents. The researchers discovered, for example, that children combine facial expressions with vocalizations. However, they did seemed to need a parental 'trigger' for showing this behavior, while parents more often socially engaged with their child on their own initiative. Stimulating interactive behaviors in children The researchers conclude that combining several social behaviors is more effective than showing singular behavior in evoking the child's looking behavior. They think it would also be interesting to investigate if combining object-oriented behaviors and socially-oriented behaviors by parents, can increase children's responsiveness to objects. The outcomes can then be translated into concrete guidelines for parents. References Van keer, I.; Ceulemans, E.; Bodner, N.; Vandesande, S.; Van Leeuwen, K. & Maes, B. (2019). Parent-child interaction: A micro-level sequential approach in children with a significant cognitive and motor developmental delay. Research in Developmental Disabilities, 85, 172-186. https://doi.org/10.1016/j.ridd.2018.11.008 Child Development Information --- ## How does heat stress affect the health and welfare of dairy cows? URL: https://noldus.com/blog/heat-stress-cows-health-welfare Published: 2020-02-24 08:00:00 Description: When environmental temperatures rise, livestock animals, such as dairy cows, are vulnerable to heat stress. Researchers Polsky and von Keyserlingk reviewed how heat stress affects animal productivity, health, and welfare. When environmental temperatures rise, livestock animals, such as dairy cows, are vulnerable to heat stress. Heat stress occurs when an animal is unable to lose excess heat, resulting in an increased body temperature and a range of physiological responses. Heat stress can impact an animal's productivity, health, welfare, and may even lead to fatalities. Heat stress is a challenge in regions with long summers, constant sunlight, and high humidity. However, with global temperatures rising, farmers from all over the world should take the risks of heat stress into consideration. In this blog post, we discuss a review by researchers Liam Polsky and Marina von Keyserlingk on the effects of heat stress on dairy cows. Coping with the heat Dairy cows have different strategies to cope with elevated temperatures. Physiological responses include increased panting, sweating, and respiration. Furthermore, their milk yield and reproductive performance decreases. They also display a range of behavioral coping strategies. For example, dairy cows drink more water and shift their eating times to cooler periods during the day. They also decrease their activity and movement, increase their standing time, and spend more time seeking shade. Studying animals' biological functioning and behavior provides insights into the effects of heat stress on health and welfare. However, Polsky and von Keyserlingk argue that to gain a fuller understanding of heat stress, it is also important to study their affective states and natural living conditions. Affective states Thirst When an animal experiences heat stress, it is vital that they can access water easily. Drinking more water helps animals stay hydrated, especially chilled water which can lower their body temperature and respiration rates. Monitoring drinking behaviors can help prevent health issues in dairy cows. For example, in extreme cases of heat stress, an animal's thirst can decrease or disappear completely, putting animals at risk for serious illness and even death. Hunger During heat stress, animals may lose their appetite, which can result in weight loss and undernourishment. In fact, research has shown that an animal's feed intake can decrease as soon as one day after temperatures start to rise. To compensate for these issues, farm managers often increase the energy density of the diet. However, research suggests that the digestion of protein elevates internal temperatures. This means that an altered diet may actually worsen the effects of heat stress instead of reducing them. Lameness Heat-stressed cows increase their standing time to expose more of their skin's surface for heat reduction, water loss, and air movement. On the other hand, prolonged standing may be a risk factor for lameness and pain. Therefore, when monitoring animal health, it is important to study animal activity. Frustration and aggression If animals are interrupted in their heat alleviating behaviors, they can get frustrated. They may also get frustrated if they experience conflict on whether to stand to cool down or lie down to rest. Feelings of frustration can turn into aggression towards other animals, especially when competing for resources such as shade or drinking water. As a result, dominant cows may have better access to these resources than cows lower in the social hierarchy. As subordinate cows already have a weaker immune system, their risk for heat stress increases. Natural living conditions When dairy cows live in an environmental that is similar to their evolutionary living conditions, it provides them with the best opportunities to use their natural coping strategies. However, different breeds of dairy cows have different abilities to deal with heat. For example, B. indicus cows are better adapted to deal with heat stress conditions than B. taurus cows. Research indicates that B. indicus evolved in tropical Asian regions and, therefore, developed biological traits that improved their ability to deal with heat stress. This includes characteristics such as greater skin pigmentation, shorter hair, and lighter-colored coats. In regions where elevated temperatures are constant, farmers may want to choose breeds that are better adapted to heat conditions. Solutions for animal heat stress Several technologies in housing and animal management can provide immediate relief for animals with heat stress. This includes options such as fans, misters, and showers. However, research shows that dairy cows display avoidant behaviors in reaction to water exposure. Researchers Liam Polsky and Marina von Keyserlingk speculate that this method of cooling may go against dairy cows' natural living conditions, and that they prefer to seek shelter instead. Furthermore, with large amounts of wastewaters, such solutions quickly become economically and environmentally unsustainable. It may be better to use physical structures to provide shade and choose farm locations and orientations more carefully. Tracking animal behavior Solutions for immediate relief are important in treating the effects of heat stress. Of course, it would be even better to prevent heat stress itself. Measuring animal behavior is invaluable in this field of study. TrackLab can help you gain valuable insights in animal behavior during heat stress. The software offers reliable tracking, as well as various options for the analysis and visualization of your data. For example, you can monitor how much time your animals spend lying, standing, and walking. This is a great way to monitor your animals' coping strategies and keep an eye on signs of lameness. You can also study place preference and learn about accessibility of drinking areas or shade. Moreover, measuring social behavior can help you monitor grouping behaviors and identify which animals are dominant. This can help prevent the escalation of heat stress, as well as aggression and competition for resources. RESOURCES Read more about TrackLab Find out how TrackLab is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Reference Polsky, L.; Von Keyserlingk, M. (2017). Invited review: Effects of heat stress on dairy cattle welfare. Journal of Dairy Science, 100 (11), 8645-8657. --- ## Testing motor coordination in a mouse model with muscular dystrophy URL: https://noldus.com/blog/motor-coordination-muscular-dystrophy Published: 2020-02-19 16:45:00 Description: Muscular Dystrophy is a broad group of diseases recognized by the loss of muscle mass and strenght. Researchers tried to discover if gene therapy strategies can help with reducing symptoms. Muscular dystrophy is a group of inherited diseases, identified with a progressive loss of muscle mass and a consequent loss of muscle strength and degeneration. There is currently no cure for this disease. The person's quality of life improves with different types of therapy and drug treatment, but there is no way to prevent or reverse muscular dystrophy. Depending on the type and severity, the effects of this disease can be mild or fatal and the progression can differ between patients. One of the more severe types of muscular dystrophy is congenital muscular dystrophy with megaconial myopathy (MDCMC) which is pathologically recognized by abnormally enlarged mitochondria. There are at least 48 reported cases of MDCMC worldwide. This disease appears in early childhood, and may not only be restricted to muscle degeneration, but can also affect the brain and other organ systems. Choline kinase beta gene in MDCMC During the investigation of MDCMC, researchers observed reduced choline kinase activity, indicating that loss of function mutations in choline kinase beta (Chkb) gene causes this disease. This gene has an important role in normal physiological and mitochondrial function as well as muscle development. Furthermore, Chkb gene encodes the choline kinase β that catalyzes the first enzymatic step in a biosynthetic pathway for phosphatidylcholine, one of four major biolipids. RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources What happens with upregulating Chkb gene? Ambreen A. Sayed-Zahid and her colleagues tried to discover if gene therapy strategies help with reducing severity of MDCMC symptoms, and help with restoration of muscle strength and coordination. To answer their question, researchers used mice models with rostrocaudal muscular dystrophy (rmd) accompanied by removed Chkb gene, resulting in an MDCMC-like phenotype. For testing pre-disease upregulation of Chkb gene, an engineered, muscle-specific (skeletal and cardiac muscles) transgenic mouse with rostrocaudal muscular dystrophy (Tg-rmd mouse) was used. The researchers performed four different behavioral tests to discover if their transgene rescued motor performance: the open field, rotarod, grip strength, and the ErasmusLadder test. Motor performance after upregulation of the Chkb gene Assessing fine motor performance in mice The researchers used the fully automated ErasmusLadder from Noldus IT to test fine motor coordination. This instantaneously registers and analyzes the walking pattern of mice, as all rungs are equipped with pressure sensors. Researchers focused on evaluating how many missteps and back steps control and Tg-rmd mice models will do while testing. A misstep is counted, when the mouse uses a lower rung instead of the higher one. Greater percentage of missteps and back steps would mean a greater motor and coordination deficit. Each mouse was tested for 4 days in a row and no perturbation or sound stimulus was used during the tests. The results indicate that there was no significant difference in the percentage of back steps or missteps between the control and Tg-rmd group. Assessing basic locomotion and grip strength in mice Basic locomotor function was tested with the Open field test, in which the Tg-rmd mice showed similar vertical activity and travelled distance as their age- and sex-matched wild-type littermates in the control group. This suggests normal locomotion and rearing ability. Results from the test of the Rotarod showed, that motor endurance and performance levels of the Tg-rmd mice equal the endurance and performance levels of the control mice. Also, the grip strength of forepaws and all paws was not different from the Tg-rmd mice and their age- and sex-matched littermate controls. Potential therapy for MDCMC The researchers came to the conclusion that introduction of a muscle-specific Chkb transgene completely saved motor functionalities in the rmd mice. Replacement of the Chkb gene could for this reason serve as a potential therapy for MDCMC patients. Besides, researchers also tested post-disease therapy strategy with intramuscular injections of adeno-associated viral vectors expressing either Chka or Chkb genes in rmd mice. They concluded that upregulating Chka could also be implemented as a potential therapy. References Sayed-Zahid, A. A., Sher, R. B., Sukoff Rizzo, S. J., Anderson, L. C., Patenaude K. E. and Cox, G. A. (2019). Functional rescue in a mouse model of congenital muscular dystrophy with megaconial myopathy. Human Molecular Genetics, 28, 16. --- ## For Pete’s Sake: Measuring Frustration URL: https://noldus.com/blog/measuring-frustration Published: 2020-02-17 10:01:00 Description: Within the field of human factors and usability, frustration poses an interesting challenge. It can be a barrier for learning. So how can we measure frustration in order to minimize it? If you've ever met me then this is obvious, but for those who haven't: I'm not a patient person. Patience may be a virtue, but unless reincarnation is a thing, I've got one life to live and I don't like to waste it. Did you know that over the average lifespan, you will spend six months of your life waiting in line, for your plane, train, etc1? That's half a year wasted, in my opinion. Thanks to breathing exercises and new age music, I'm a work in progress and getting better with age; however, one thing that really tests all those breathing exercises is traffic. I loathe traffic so much that I work from home! This is worse in Cincinnati, which consistently ranks as having the worst drivers in the US2. For any Cincy folks reading this, you know who you are; the left lane is for passing, not cruising five miles per hour below the speed limit! Whew. Breathe in, breathe out. I'm ok. The point I'm trying to make is that for me, traffic is very frustrating. It causes a host of emotions: anger, anxiety, stress, etc, very much akin to the opening scene to Office Space3. As part of my own self-reflection into why I am so bothered by things like traffic, I began to peel back the onion, so to speak. We begin there: what exactly is frustration? Our emotional reactions First things first: Frustration is not anger. It's related to anger, but also disappointment and annoyance, and arises when one's needs are blocked. Put simply: it's an emotional reaction to things (internal or external) getting in your way. Hi, my name is Jason and I have control issues whereby I don't like it when people or things block my ability to get to where I'm going. Granted, driving isn't the only source of frustration. Spouses, kids, co-workers, video games, etc, all can create frustrations at times. It's perfectly natural and I know my Aussiedoodle, Winston, certainly experiences his own version of frustration, especially when I take too long to get ready for his walks. He huffs and grumbles rather loudly. It's rather funny. But I digress. The influence of frustration If frustration is natural, then why does it matter? We all experience it, so why can't we just focus on the soothing sounds of Peter Kater, David Arkenstone, or my favorite, Constancy Demby? Well, within the field of human factors and usability, frustration poses an interesting challenge. For example, if I'm shopping online and can't find that for which I'm looking, how likely am I to continue shopping on a website? If I get frustrated, not very likely, especially for someone like me. This goes for any task, be it computer-based, hand-held, wearable, etc (for an excellent summary of frustration in HCI, see Euijung Yang's thesis work4). What is important is that frustration can be a barrier for learning. Minimizing frustration is the key to creating a better user interface, smartphone app, retail experience, etc. Great, so we all experience frustration, but minimizing it can help us learn quicker and find greater satisfaction with our technological world. But in order to minimize something, we have to look at how we measure it. How to measure frustration Of course, we could put someone in a scenario and then ask them how he/she feels about it. Easy enough. Ride along with me on Beechmont Ave at 5pm on a rainy Friday and I'll tell you all about how I'm feeling, and how I feel about everyone around me! But beyond simple self-report, we can start by looking at someone's physiological responses, as frustration is characterized by changes in GSR and heart rate5. Think to the last time your flight was delayed, you had a tight connection, and you know there is nothing you can do about it. You might miss that connection, miss that meeting, or your kids soccer game. As you sit there and ponder all the ways you cannot change your situational outcome, how was your breathing, pulse, and overall mood? As someone who lacks the Zen-like patience of my colleague, Peter, I can tell you that my breathing is quickened and my palms are sweaty. More than just 'basic' emotions Another option would be to scan someone's brain while performing a frustrating task6. As a neuroscientist, I think that's super cool. Brain scans are fun. But who has access to a magnet? In fact, some of my friends tell me that waiting for MRI time can itself be a frustrating experience. So let's think simpler than sensors, wires, and magnets. If you've ever read anything I've written, you know my preferred strategy. You guessed it: measure someone's facial expression. But, Jason, I hear you saying, I thought automated facial expression analysis only measured the "basic" emotions (happy, sad, angry, surprised, scared, disgusted)? Well good news, dear reader, not anymore. Measure frustration by using facial expression analysis A recent update to FaceReader now allows researchers the opportunity to design your own algorithms by combining variables such as facial expressions, Action Units (AU), and even heart rate to create "Custom Expressions". In English that means you can create your own affective attitudes, emotional states, or whatever you choose to call it. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Remember a previous post looking at false vs felt smiles? To refresh your memory, the FaceReader analytical outputs were imported into The Observer XT for subsequent analysis. Now we can calculate those expressions directly in FaceReader. Pretty cool, eh? So let's look at an example. Facial Action Coding System (FACS) tells us more about how and why the face moves FaceReader can measure twenty different facial muscles, known as Action Units, or AUs. A real smile combines the mouth (AU12) with the eyes (AU6 and/or AU7). Going back to frustration, recent studies have shown the engagement of both AU4, the 'brow lowerer' muscle between your eyebrows, and AU14, the 'dimpler'7. Try it for yourself: furrow the 'unibrow' muscle between your eyebrows, and pull back on side of your mouth, like a contemptuous face. Finish it by putting your hands on your head and ask someone to guess what expression you're showing. Now, in the interest of your health, take the next few minutes to smile and combat any unintentional negative influences from making a frustrated face. It's ok, I'll wait. Good? Ok. Funny enough, there is also data to show that people sometimes smile when they're frustrated8. In my experience, that's usually accompanied by sarcasm or a cynical remark. But even in my own research or projects we've done for companies, I've noticed that some people indeed smile or chuckle when they eat something they don't like or can't figure out how to accomplish their task. Automatically analyze facial expressions with FaceReader Important disclaimer: I am not a facial expression researcher. I'm a curious behavioral neuroscientist with access to FaceReader, the most powerful facial expression analysis software in the market. That means that I leave it for you to decide what exactly constitutes a frustrated face. The point is that you can now automate the analysis of such without the need for heart rate sensors, expensive MRI or MEG machines. Imagine the possibilities of what you can do with a simple camera instead of wires, sensors, and pesky artifacts? Now measuring facial expressions does not have to become a frustrating experience! See what I did there? References - How much time of an average life is spent waiting? - America's Best Drivers Report - Office Space - Traffic Scene - Yang, E. & Dorneich, M.C. (2018). Evaluating Human–Automation Etiquette Strategies to Mitigate User Frustration and Improve Learning in Affect-Aware Tutoring. Applied Sciences, 8 (6), 895, https://doi.org/10.3390/app8060895 - Jost, H. (1941). Some Physiological Changes during Frustration. Child Development, 12 (1), 9-15 - Bierzynska, M.; Bielecki, M.; Marchewka, A.; Debowska, W.; Duszyk, A.; Zajkowski, W.; Falkiewicz, M.; Nowicka, A.; Strelau, J. & Kossut, M. (2016). Effect of frustration on brain activation pattern in subjects with different temperament. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.01989 - Grafsgaard, J.F.; Wiggins, J.B.; Boyer, K.E.; Wiebe, E.N. & Lester, J.C. (2013). Automatically Recognizing Facial Expression: Predicting Engagement and Frustration. PDF - MIT DSpace --- ## Evaluating ergonomics in healthcare – paramedics URL: https://noldus.com/blog/evaluating-ergonomics-in-healthcare Published: 2020-02-12 09:05:00 Description: The chance that a paramedic suffers an injury is 3x higher than other occupations. Because of the global health worker shortage, we need to make sure these professionals are taken care of. The chance that a paramedic suffers an injury is 3x higher than other occupations. The cause of 94% of these injuries is a musculoskeletal disorder (MSD) like back pain, strains, and sprains. Because of the global health worker shortage, we need to make sure these professionals are taken care of. That's one of the reasons Yaar Harari and colleagues from Ben-Gurion University of the Negev, Israel, and Magen-David-Adom (Israeli National Emergency Medical Services) decided to focus their research on improving human behavior in healthcare – specifically paramedic behaviors in relation to the equipment they have to use for both in- and out-of-hospital cardiopulmonary resuscitation (CPR). Harari and colleagues evaluated out-of-hospital CPR because this situation is very demanding for these professional and there are no clear guidelines on how to use their equipment in these kind of situations. Improving the details in such a workflow and providing clear guidelines might make a huge impact on the injury rate and improve healthcare in general. Observing simulations of a cardiac-arrest scenario Twelve paramedic teams participated in two 10-minute in-situ simulations of a cardiac-arrest scenario. The researchers invited all the teams to the Human-Systems Integration in Healthcare Lab at the Ben-Gurion University of the Negev, Israel. In order to capture all the behaviors in detail, all simulations were video-recorded from four angles using MediaRecorder software. The Observer XT professional research software allowed the scientists to observe the paramedics' interactions with the equipment around the patient. You can see an event as an interaction in which the bag was either moved or used without being moved. The researchers explained that they used a marked grid on the ceramic tiled floor (which is very common in homes and buildings in Israel) to help them define the position of each bag at the precise moment the interaction began and ended. The researchers measured work efficiency by calculating the time each person spent on CPR as compared to other activities. CPR quality was measured by taking standard resuscitation measures and evaluating them (compression depth, rate, etc.). FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Measure posture and push/pull of the bag In the scenario the researchers also paid attention to how much strength it took to push and pull the bag via the physiological signals of the paramedical professional, such as heart rate and level of exertion. Both measurements may predict the level of fatigue of the professional. Biomechanical load was assessed using direct measurements (number of times the equipment bags were handled and the cumulative force during the simulation that was required to move the bags) and ergonomic assessments (risk level for MSD based on the paramedics' postures and loads, the range of spinal compression forces acting on the paramedics when they lifted, pushed, and pulled the bags). Results The study results show that the initial positions of the equipment bags influence clinical measurements of CPR quality, as well as measures of the paramedics' work efficiency, effort, and biomechanical loads. Improving CPR quality and patient outcomes, and reduce paramedics' risk of injury Yaar Harari and colleagues demonstrated with these simulations that 72% of paramedics' postures were categorized as high or very high risk for musculoskeletal disorders. This calls for action! The researchers call for a discussion about the positioning and handling of the equipment bags during out-of-hospital CPR when seeking to improve paramedics' performance and reduce their risk of MSD. These guidelines related to bag positioning and equipment handling might also improve CPR quality and patient outcomes, as they found that paramedics wasted time moving around the patient in order to reach their equipment. Reference - Harari, Y.; Riemer, R.; Jaffe, E.; Wacht, O.; Bitan, Y. (2020). Paramedical equipment bags: How their position during out-of-hospital cardiopulmonary resuscitation (CPR) affect paramedic ergonomics and performance. Applied Ergonomics, 82. - 5 ways to bridge the global health worker shortage --- ## Neuromarketing: hope or hype? URL: https://noldus.com/blog/neuromarketing-hope-or-hype Published: 2020-01-31 13:00:00 Description: The application of neuroscience methods to marketing – neuromarketing research – is growing in popularity. Can neuroscience be the holy grail of the study of consumer behavior? The application of neuroscience methods to marketing – neuromarketing – is growing in popularity. Last week at an event with 13.000 visitors, a colleague of mine Patrick Zimmerman presented 'Neuromarketing for webshops' together with Evoworks. Patrick explained the practical application of neuroscience tools in marketing. The hope of all marketers Marketers hope that neuroscience will provide them with information that is not obtainable through conventional marketing methods such as questionnaires and focus groups. Can neuroscience be the holy grail of the study of consumer buying behavior online or offline? Solving the puzzle There are a number of well-established methods for measuring and mapping brain activity. The most commonly used methods applied in neuromarketing include electroencephalo-graphy (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) but other ("non-neuro") methods like eye tracking, face reading, and measuring physiological responses are growing in popularity. In my experience combining methods is crucial for gaining insight in something as complex as liking and wanting. Each method (including the traditional ones like interviews and focus groups) can give valuable information. The combination is like bringing the pieces of the jigsaw puzzle together. Limitations of using neuroscience methods for neuromarketing EEG is a relatively old technology in neurology, but it is still considered a good way to measure brain activity. However, the limitation of EEG is that it does not have good spatial resolution, which means it cannot precisely locate where the neurons are firing in the brain (especially in deeper, older structures). While EEG measures the electrical activity in the brain, MEG measures the magnetic field created by neuronal activity. MEG has excellent temporal resolution and better spatial resolution than EEG. However, like EEG, MEG is limited to picking up activity at the surface of the brain. Another disadvantage of MEG is that the technique is expensive and therefore not readily available to the average marketer or market research agency. fMRI measures the change in blood flow in the brain. fMRI has the major advantage of being able to image deep brain structures, especially those involved in emotional responses. Although it is often claimed that fMRI is a non-invasive method, that is, of course, not the case. A scanner is not a supermarket or a home situation where factors like the presence of other people or the abundance of other products than the one your company is interested in can influence choice behavior. This technique is also expensive, which is another disadvantage of using fMRI. Extremely hard to explain buying behavior The major drawback of all three methods is that the data are difficult to interpret. It is one thing to see which parts of the brain become active in response to a stimulus; it is another to interpret what this means or what you can do with it. Neuroscience is a discipline in itself and although there is a wealth of scientific information about the brain and specific areas such as the reward center, the translation of all this information into predictive models that explain why we buy certain products and not others is still extremely hard. The marketing hype And let's face it: marketing is not interested in science or complexity. A marketer wants to increase the conversion ratio with a solution that just says 'this advertisement will generate lots of traffic to our webshop' or 'this online quote generator will increase sales'. Rather than trying to understand complex neuroscientific data, there is a temptation to oversimplify and over-claim. And there is the threat. If we keep in mind that hidden "buy buttons" are a fantasy, neuromarketing is here to stay and will evolve in a discipline that can fundamentally change how we design, promote, price, and package our products. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## Parenting behaviors and executive function in Down syndrome URL: https://noldus.com/blog/parenting-executive-function-down-syndrome Published: 2020-01-21 09:13:00 Description: Understanding more about developmental delays in Down syndrome is vital in developing targeted interventions. In this study, the relationship between parenting behaviors and executive function was examined. In the US, about one in every 700 babies is born with Down syndrome (DS). DS is a genetic disorder that is characterized by intellectual disability, as well as delays in different areas of development. In cognitive development, difficulties are most pronounced in attention, memory, and executive function. Understanding more about these difficulties supports the development of targeted interventions for young children with DS. Influences on executive function Executive function (EF) describes the different abilities we need for goal-directed behavior. It includes processes such as working memory, inhibition, initiating behavior, and cognitive flexibility. Research has shown that, across the lifespan, EF is associated with academic and social skills, and daily functioning. It is likely that individual differences in EF are influenced by both biological and environmental factors. For children, parents are one of the most important sources of influence. Indeed, studies with typically developing children have shown that parenting behaviors are associated with child EF performance. For example, research has highlighted links between parent-child interactions and the development of brain regions responsible for EF. More specifically, researchers also found that maternal sensitivity and responsiveness are related to childhood EF. But what kind of parenting behaviors are we talking about exactly? FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Download Parenting behaviors When a parent demands or requests a behavior change in their child, we describe this as directive parenting behavior. Directive parenting is often used in preschool aged children, to offer guidance for tasks they cannot complete independently. However, the overuse of directives may undermine the development of self-regulation skills, as it reduces the need for a child to problem-solve during a task. On the other hand, parental teaching behaviors may stimulate the development of EF skills. Teaching behaviors include instructions or explanations, as well as questions that promote children's learning. One particular form of teaching that benefits EF development is scaffolding. Scaffolding guides a child towards the correct solution, and includes methods such as giving hints or asking guided questions. Parent-child interaction and Down syndrome Parents of children with DS often use more directives than parents of typically developing children. This may benefit interactions between parents and children with DS, but may also impact certain aspects of EF. Parents of children with DS have also been found to use teaching behaviors, which seems to benefit EF development. Researcher Emily Schworer and her collaborators at Colorado State University and Pennsylvania State University argue the importance of understanding more about the relationship between directive and teaching parenting behaviors and the development of EF in children with DS. They studied child EF abilities and observed parent-child interactions during a collaborative puzzle task. They predicted that parents of children with DS would show more directive behaviors than parents of typically developing children, as well as an equal amount of teaching behaviors. They also predicted that children with DS would respond differently to parental directives when compared to a control group, while responding similarly to teaching behaviors. Finally, the researchers hypothesized that the use of more directives would be associated with more impaired EF performance, while using more teaching behaviors would be linked to more advanced EF performance. They predicted these trends in both groups. Observational study The study included 42 children with DS between 5 and 10 years old and 28 typically developing children aged 2.5 to 4 years old. Although the two groups differed in chronological age, they were similar in nonverbal mental age. Parents rated their children's EF skills with a questionnaire and children completed an EF task that assessed working memory and inhibition. In this task, children were asked to perform a certain animal sound (activation), while not making the sound of another animal (inhibition). Finally, parents and children completed a challenge task together, in which they had to build three castle puzzles. Parent-child interactions were videotaped and coded using The Observer XT. Coders observed directive and teaching behaviors in parents. Moreover, they coded whether children complied with their parents' directive, continued their work without any parent behavior, or disengaged from the task. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Parent and child behaviors Results of the study showed that parents of children with DS used more directives than parents of typically developing children, even when a child complied or continued with the task on his or her own. This highlights the tendency of parents to provide continued support during interactions. The frequency of teaching behaviors did not differ between groups. Moreover, children with DS showed more compliant behaviors than children from the control group. However, further analysis indicated that this is likely a result of the greater number of parenting behaviors in this group, providing children with DS with more opportunities to comply with directives. Patterns in parenting Parent teaching behavior was associated with stronger working memory and inhibition skills, as reported by parents. This result was only found for DS dyads. Furthermore, increases in directive behaviors were associated with more impaired inhibitory control and working memory in the EF task. This association was found for both groups. As the researchers note, it is important to realize that we cannot know the direction of these associations. Childhood EF may be influenced by parental directives or parents may use more directive behaviors because EF is impaired in their children. Similarly, teaching behaviors may affect EF performance in children. Another explanation is that parents use more teaching behaviors because their child has more advanced EF abilities. Even so, the results from this study provide new insights in parent-child interaction in DS, and demonstrate that parenting behaviors can be a meaningful target for early interventions in this group. References Schworer, E.; Fidler, D.; Lunkenheimer, E.; Daunhauer, L. (2019). Parenting behavior and executive function in children with Down syndrome. Journal of Intellectual Disability Research, 63(4), 298-312. CDC: Down Syndrome Data & Statistics Wikipedia: Down Syndrome --- ## Direct observations help develop effective interventions in adolescence URL: https://noldus.com/blog/direct-observations-adolescence Published: 2020-01-16 10:00:00 Description: Presenting a study in which family and friendship dynamics in adolescence were observed in order to develop more personalized interventions that prevent problem behaviors and adjustment issues. At the end of December 2019, the NIH's National Institute on Drug Abuse published its annual Monitoring the Future Survey: High School and Youth Trends. Monitoring the Future reports on the drug use and attitudes among American 8th, 10th, and 12th graders and in past years has seen promising downward trends for illicit drug use, cigarette use, and opioids. However, the 2019 survey results show a continued dramatic increase in vaping, stating that "Increases in adolescent marijuana vaping from 2018 to 2019 ranked among the largest single-year increases ever observed by Monitoring the Future in the past 45 years among all outcomes ever measured. In 2019 the percentage of adolescents who had vaped marijuana in the last 12 months was 21% in 12th grade, 19% in 10th grade, and 7% in 8th grade." Preventing problem behavior, such as drug use starting in adolescence, has been a research topic for many years. Some interventions are successful, some aren't. What determines success? How can we prevent adolescents from making these unhealthy choices? In this blog post I present a study by Dr. Thomas Dishion and colleagues from Arizona State University, John Hopkins School of Medicine in Baltimore, Maryland, and the Oregon Research Institute, in which family and friendship dynamics in adolescence were observed in order to develop more personalized interventions that prevent problem behaviors and adjustment issues. Why friendships and family relationships are equally important Thomas Dishion and colleagues explain that the friendship and family dynamics considered each uniquely influence adolescents in their transition to adulthood. The example given by the researchers explains: "An adolescent who has conflict with a parent and spends time with drug-using peers is potentially more likely to escalate to problem behavior." If one fails, the other might compensate for it, but if both relationships fail it becomes harder to follow a normal development path. Why direct observations help us understand interpersonal relationships According to Dishion and colleagues, a particular useful method for understanding relationship dynamics between parents and peers is direct observation. Observations help us find patterns in behavior and thus help us develop effective interventions. And, Dishion et al. explain: "interobserver reliability assures that the measurement will be more objective". Hence, a software product such as The Observer XT automatically calculating this measure helps in studying relationship dynamics and preventing researchers from drawing conclusions based on incorrectly interpreted data. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Antisocial, disaffected, or healthy 784 adolescents participated in this study. The researchers first established three adolescent groups that indicated unique observed interpersonal dynamics with parents and friends. High levels of deviant and drug use talk, aggressive interactions with friends, and force or threat in family interactions defined the antisocial group. High levels of drug use talk with friends and negativity about their parent(s) were defining codes for the disaffected group. Luckily 587 of the 784 adolescents who participated were classified into the healthy relationship group, showing overall low levels of deviant and drug use talk with friends and positive, noncoercive (not using threats or force to achieve compliance) relationships with their parents. Data collection consisted of video recording observations of peer-youth interactions, parent-youth interactions, and a parent and youth five-minute speech task. Research assistants blind to the experimental conditions coded the tapes in a detailed and structured way using The Observer XT coding software. With a macro and micro rating scale they rated participant behavior, first rating the episode as a whole, followed by second-by-second behavioral coding. One of the many outcomes found by the researchers was that compared to the healthy relationship group, the disaffected and the antisocial groups reported significantly higher substance use problems in early adulthood. What does this mean for interventions? Dishion and colleagues explain that with this information, it is possible to tailor and personalize interventions with adolescents to address key dynamics in the family and friendship relationships, to more effectively prevent adult substance use problems, depression, and violence. Anxiety? We ALL know the feeling After re-reading the article of Dishion and colleagues, it sprang to mind that they didn't find any significant relationship with anxiety. What happened there? The transition from childhood to adulthood is an anxious one, period. Having to overcome many emotional and other hurdles makes this a period of stress and anxiousness. Therefore, friends and family can make a difference. Much more information can be found in the paper cited below. Enjoy reading and we look forward to what else Thomas Dishion and colleagues bring to the press. References - Dishion, T.J.; Mun, C.J.; Ha, T.; Tein, J. (2019). Observed family and friendship dynamics in adolescence: a latent profile approach to identifying "Mesosystem" adaptation for intervention tailoring. Prevention Science, 20, 41-55. - NIDA. (2019, December 18). Monitoring the Future Survey: High School and Youth Trends. Retrieved from https://www.drugabuse.gov/publications/drugfacts/monitoring-future-survey-high-school-youth-trends on 2019, December 23 - Monitoring the Future Press Release (PDF) - Monitoring the Future Website --- ## Useful consumer neuroscience tools URL: https://noldus.com/blog/useful-consumer-neuroscience-tools Published: 2020-01-14 14:30:00 Description: Marketers track consumer behavior and try to understand it by learning more about the magic buy button. "Black Friday shoppers spent more in stores, broke records online over the weekend" USA today tells us. CNBC mentions a spend of $7.4 billion in the second largest online sales day ever! Many consumers hit the "buy" button on either Black Friday, Cyber Monday, Singles Day, or Boxing Day. Although BBC reports a decline in Boxing Day 2019 shoppers, there were still some bargain-hunters disregarding the rain, with some shoppers on London's Oxford Street even waiting for stores to open at 9am. Find the magic buy button Marketers track consumer behavior and try to understand it by learning more about the magic buy button. Spoiler alert – that button does not exist! The decision-making process of consumers is much more complicated, researchers from Slovakia tell us. This blog post explains more about their research and how consumer neuroscience tools (FaceReader, eye tracking) can help marketers understand consumer buying behavior so they can improve their business success. Learn more about consumer buying behavior Don't we all want to understand our potential clients' buying behavior? Researchers Katarina Neomániová, Jakub Berčík and Anka Pavelka from the Department of Marketing and Trade of the Slovak University of Agriculture explain the importance of using the tools and techniques of neuroscience to understand how consumers make decisions about purchasing goods and services. How can the results of tests with these consumer neuroscience tools be linked with business success? Think about this $7.4 billion Black Friday sales figure! How to capture decision-making consumer behavior Traditional research methods like consumer surveys bring in a lot of information, but show a lack of deeper understanding about consumers' attitudes towards a product and actual consumer behavior at the point of purchase. Eye tracking technology as well as emotion measurement provide more information about preference "in the moment". Neomániová and colleagues explain that consumer neuroscience tools such as eye trackers and FaceReader provide information about this specific moment of subconscious mental processing of information that plays a part in decision-making consumer behavior. Furthermore, they explain that it should not be perceived as an attack on traditional consumer research but is a complementary element to further investigate specific consumer decision-making. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Logo and brand awareness According to Neomániová and colleagues, brands have gradually become a natural part of our lives. That is why they chose to study logo design for a local company and researched if this logo not only appealed to consumers' conscious mind but also to the subconscious mind. This can be tested through the approaches and methods provided by consumer neuroscience. They studied logo design because it is the first point of contact of a consumer and a company. The study design In a controlled laboratory environment with eye tracking and FaceReading technology running, Neomániová and colleagues invited 22 respondents – 9 men and 13 women – for a test and asked them to look at the original logo and at three newly designed logos. Eye tracking technology Eye trackers create heat maps of gaze fixations to present the results to the researcher. They are a convincing tool for two primary reasons, Neomániová and colleagues explain. - 1. The intuitive nature of the color scale associated with temperature minimizes the amount of learning and knowledge needed to understand them correctly. - 2. Because heat maps represent the data directly in the measured stimulus, interpreting them is simple. Using heat maps, Neomániová and colleagues were able to summarize a large amount of data that would be harder to interpret in numerical form. FaceReader software FaceReader software automatically calculates a valence from analyzing the emotions from the face of the participant. The researchers selected this scale as a metric for their research, which allowed them to find positive or negative emotions linked to one of the four logos. Which logo will bring in more business success? Based on the research outcomes, they selected the best logo. The researchers describe that for both male and female test participants logo 1 was the preferred logo: it held the gaze of the respondents for the longest time and each respondent's gaze returned repeatedly to this color combination. FaceReader results showed a more positive valence for men for logo 1 compared to the original logo. Women showed the most negative attitude towards logo 3. In this project, the researchers chose to work only with valence as a measure of attitude; thus why only positive or negative can be reported. In the future they might want to use the new affective states in FaceReader such as interest, boredom, and confusion. Affective attitudes could also useful in the A/B testing they propose for the future. Reference - Neomániová, K., Berčík, J., Pavelka, A. (2019). The use of eye-tracker and face reader as useful consumer neuroscience tools within logo creation. ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRUNENSIS, 67, 1061-1070. - CNBC: Black Friday shoppers spend record $7.4 billion - USA Today: Black Friday shoppers spent more in stores - The Independent: Boxing Day sale tips - The Independent: Boxing Day sales 2018 - BBC News: Boxing Day 2019 --- ## The role of inhibitory control on substance use in adolescence URL: https://noldus.com/blog/substance-use-adolescents Published: 2019-12-19 09:13:00 Description: Adolescents are vulnerable to risk-taking behaviors such as substance use. Dr. Roy Otten and his team examined how early childhood stress and inhibitory control influence the risk of adolescent substance use. As the adolescent brain is developing, it is especially sensitive to cues of reward and pain. At the same time, skills such as emotion regulation, reasoning, and self-control are still developing. This combination leaves adolescents vulnerable to risk-taking behaviors like substance use. Substance use in young adolescents is associated with a range of health issues and risks. For example, substance use before the age of 15 is related to impaired neurocognitive functioning, depressive symptoms, and diminished academic performance. These issues do not only impact adolescents' well-being, but can extend into adulthood as well. Understanding which factors play a role in adolescent substance use is important for the prevention and treatment of this global health issue. Research shows that deviant behavior is one of the best predictors for early substance use. Specifically, adolescents with a history of antisocial behavior and deviant peer involvement are more likely to initiate alcohol, tobacco, and cannabis use by the age of 15. Another important factor is early life stress. Longitudinal research One of the best ways to learn more about the risks for early substance use is to study children and adolescents over a longer period of time. In some longitudinal studies on adolescent substance use, researchers use a developmental cascade model. They assess risk factors in early childhood and study how these risks influence each other and unfold over time. One of these studies found that family stress and early parenting practices predicted peer difficulties in middle childhood. This predicted deviant peer involvement and, in turn, later adolescent substance use. Dr. Roy Otten and his colleagues build upon this research by examining inhibitory control as a potential underlying mechanism in the link between early life stress, deviant behavior, and adolescent substance use. Inhibition during childhood Inhibitory control, or the ability to control one's own impulses, is a core skill in self-regulation. It helps us to withhold or stop certain behaviors to reach our long-term goals. During early childhood, adverse life events and poor parenting practices may undermine the refinement of children's inhibitory control. Evidence suggests that low levels of inhibitory control in early and middle childhood lead to problem behaviors during late childhood and adolescence. A developmental cascade model can help determine more precisely how impulse control problems influence these later behaviors, including adolescent substance use. Observing parent-child interactions The study included 364 families with children who were at risk for future behavioral problems. This meant that families met risk criteria in at least two of the following domains: child behavior, family problems, and socio-demographic status. The research team assessed families during home visits when children were 2, 3, 4, 5, 7, 8, 9, 10, and 14 years old. They asked about stressful life events and parental substance use, and used questionnaires to assess childhood inhibitory control and deviant behavior. Furthermore, they observed parent-child interactions and coded them using the Relationship Affect Coding System (RACS). The RACS includes codes for verbal and physical behaviors, as well as affect. Behaviors of all interaction partners were categorized as positive, neutral, directive, negative, not talking, and ignoring. Interactions were videotaped and coded using The Observer XT, which allows for continuous coding. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Cascade model Results showed that early stressful life events and negative parent-child interaction were negatively associated with inhibitory control in childhood. In turn, inhibitory control was negatively associated with later problem behavior, and late childhood deviance was predictive of substance use at age 14. Interestingly, parental drug use was not related to childhood stress or inhibitory control, but was directly associated with early adolescent substance use. The authors argue that genetics or behavioral modeling may play a role in this relationship. Prevention The results from this study suggest that childhood inhibitory control can be influenced by environmental factors. Specifically, events that cause stress and exceed children's coping abilities may undermine development of inhibition. In turn, inhibition seems to influence later problem behaviors, including substance use. The authors argue that, in addition to focusing on the family situation, it is important to prevent problem behavior in general. The results of this study also suggest that it is important to improve self-regulation abilities in children and adolescents. Lastly, it may be beneficial if family-based intervention programs include education about the effects of parental substance use on the family context. References Otten, R.; Mun, C., Shaw, D.; Wilson, M., Dishion, T. (2018). A developmental cascade model for early adolescent-onset substance use: the role of early childhood stress. Addiction, doi:10.1111/add.14452. NIDA: Principles of Adolescent Substance Use Disorder Treatment --- ## Studying conflict interactions between mothers and adolescents URL: https://noldus.com/blog/mother-adolescent-conflict-interaction Published: 2019-12-05 08:57:00 Description: It is common for conflicts to arise between adolescents and their parents. However, severe conflicts can have negative effects on adolescent development. What can parents do to prevent escalating conflicts? Adolescence is a developmental phase with many physical, neurodevelopmental, psychological, and social changes. One of these changes involves the relationship between adolescents and their parents. As adolescents strive for more autonomy and equality in the relationship, it is common for conflicts to arise. Conflicts provide parents and adolescents with opportunities to express and negotiate their mutual expectations and reach their personal goals. However, severe conflicts can have negative effects on adolescent development, relationships, and future adjustment. It is important to understand what parents can do to prevent escalating conflicts. That is why researcher Debbie van Bommel and her colleagues examined conflict interactions between mothers and adolescents. Emotional variability One of the factors considered important for conflict resolution with adolescents is the ability to flexibly switch between expressed emotions. This flexibility related to less aggressive behaviors, higher relationship quality, and less internalizing problems. However, negative emotions are more contagious than positive ones, and both parents and adolescents tend to reciprocate negativity. This means that it can be difficult to break negative interaction cycles. Examining how transitions are made between negative and positive emotions in conflict interactions can help us understand how to improve emotional variability and conflict resolution. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of emotion recognition studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources A mother's influence Research suggests that mothers can positively influence adolescents' emotional behaviors. For example, social learning theory suggests that people learn new behaviors by observing others. This means that mothers' expressiveness of emotions can model the way adolescents express and regulate their emotions. Other studies have shown that mothers are likely to initiate positive interactions, regardless of the positivity or negativity of adolescent behaviors. On the other hand, adolescents seem more prone to maintain a negative interaction pattern. These results highlight how mothers can influence adolescent behavior and conflict interactions through their own emotional states. But what happens when mothers suffer from anxiety or depression? Internalizing problems Anxiety and depression, as well as other emotional problems, can influence the way mothers express emotions. For example, they may experience more negative emotions and have more difficulties regulating their emotions. This can make it more difficult to initiate positive interactions or to flexibly switch between emotions. In other words, internalizing problems can change the way that mothers handle a conflict situation with their adolescent. Research aims Van Bommel and her colleagues examined real-time transitions between positive, negative, and neutral emotions in mother-adolescent conflict situations. This included transitions within a person as well as the way both parties influenced each other. They predicted that mothers would be more inclined to initiate positivity after negativity than adolescents. They also argued that adolescents would reciprocate mothers' emotions more than the other way around. Furthermore, the researchers wanted to know whether mothers' internalization of problems influenced conflict interactions. They assumed that, compared to other mothers, mothers who tended to internalize problems were less likely to initiate positivity after negativity and more likely to reciprocate negativity. Observing conflict interactions The study included 84 mother-adolescent dyads studied for three consecutive years, from adolescent ages of 13 to 15 years old. Each of these years, dyads were visited at home and videotaped during a 10-minute conflict interaction task. In this task, mothers and adolescents were instructed to discuss and attempt to resolve an issue that had recurred most often during the last month (school problems, chores, etc.). Emotional states were recorded and coded using The Observer XT. Coders used a simplified 10-code version of the Specific AFFect coding system (SPAFF), observing verbal content, voice tone, facial expressions, and physical cues of both parties. The researchers analyzed their data with three categories of emotional states: positive, negative, and neutral. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Transitions in emotional states Results showed that of all emotional states, adolescents expressed positive emotions the least often. Mothers, on the other hand, expressed negative emotional states the least often. The researchers also found that most changes in emotional states happened within a person, in which one's own positivity and negativity were most likely followed by one's own neutrality. The authors suggest that these neutral emotional states support the transition between positive and negative emotions. When mothers and adolescents did influence each other, it was mostly through neutral emotional states. Whereas positive and negative emotional states seemed to prevent emotional changes in the other, neutrality was most likely to provoke emotional transitions in a partner. Leading conflict resolution In line with predictions, mothers were more likely to change to positivity after one's own or the other's negativity than adolescents were. They were also more likely to reciprocate positive emotional states, whereas adolescents were more inclined to reciprocate negative emotions. These results confirm that mothers play a more important role in preventing conflict interactions from becoming rigidly negative. The researchers recommend that mothers take an active role in resolving conflicts and in modeling effective emotion regulation, instead of ignoring the negative moods of their adolescents. Differences between mothers The researchers found no differences in emotional responses between mothers high and low in internalizing problems. They argue that this unexpected result may be explained by the relatively healthy sample they used in the study. However, they did find that adolescents with mothers low in internalizing problems were more likely to reciprocate negative emotional states. Mothers with depression or anxiety may be less sensitive to environmental cues and, as a result, show less emotional responses. This may provide adolescents with fewer opportunities to reciprocate negativity. Insight in interactions Overall, this study provides insight about how conflict interactions unfold in real-time, and how emotional states change within a person and between partners. The study also provides practical suggestions for parents to apply in conflict situations. To further improve our understanding or parent-adolescent interactions, the researchers suggest including interactions with other family members or studying increased duration of conflicts in future research. Reference Van Bommel, D.; Van der Giessen, D.; Van der Graaff, J.; Meeus, W.; Branje, S. (2018). Mother-adolescent conflict interaction sequences: the role of maternal internalizing problems. Journal of Research on Adolescence, doi:10.1111/jora.12441. --- ## Early exploratory behavior in infants with Down syndrome URL: https://noldus.com/blog/exploratory-behavior-infants-down-syndrome Published: 2019-11-28 09:38:00 Description: Object exploration is part of infants’ early development. How do infants with Down syndrome explore the world around them? And how is exploratory behavior related to their general development? Down syndrome (DS) is one of the most common genetic disorders in the world. Children with DS experience intellectual disabilities, as well as delays in motor and cognitive development. They are also at risk for a range of health conditions, including heart defects, stunted growth, and obesity. To provide the best care for children with DS, it is vital to study their early development. Understanding learning processes in different areas of development, as well as the way they influence each other, helps us to develop targeted interventions. In the current study, Dr. Deborah Fidler and her colleagues examined the link between overall development and exploration behavior in infants with DS. Exploratory behavior stimulates development When infants start exploring the world around them, they increasingly engage with the people and objects they encounter. This provides important opportunities to learn and grow! Indeed, evidence suggests that object exploration is an important factor in different areas of development. For example, experiences with objects lead to a better understanding of their physical properties, causal relations between movements, and the best ways to use them. These skills support mental representations of objects and help infants understand intentional behaviors. In this way, object exploration helps to form the basic skills for motor development, communication, language acquisition, and social interaction. How do infants with Down syndrome develop? Infants with Down syndrome show early delays in motor development, particularly regarding milestones such as reaching, grasping, and walking. Across their lifespan, they are vulnerable to problems in goal-directed behavior. Indeed, research shows that later difficulties with planning can be observed by toddlerhood. As a group, people with Down syndrome also show a great deal of variability in outcome. For example, some individuals show milder forms of intellectual disability and language difficulties, while others may experience severe impairments across a range of developmental domains. To improve our understanding of Down syndrome, Fidler and her colleagues argue that it is important to examine infant developmental profiles. In line with research in other clinical groups, they suggest that developmental delays in children with Down syndrome may be rooted in diminished exploratory experiences during infancy. Observing exploratory behavior The researchers studied 45 infants with Down syndrome, with an average age of 9.5 months. They collected information on each child's development and family history, and administered the Bayley-III developmental assessment. This assessment includes indices for cognition, receptive communication, expressive communication, fine motor development, and gross motor development. Infants participated in a one-minute object exploration trial. They were seated on the lap of their caregiver and supported when necessary, to ensure that they could move their head and arms properly. The examiner placed an unconventionally-shaped teether on the table and observed infants while they explored it visually, manually, and orally. Video recordings of the trials were coded using The Observer XT. To account for small differences in trial duration, the researchers analyzed their data based on the percentage of time engaged in each exploratory behavior. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Infant profiles The research team used their observational data to identify different infant developmental profiles. Using latent profile analysis, they found the best fit for a two-profile solution. Based on the behavioral characteristics of each profile, the infants were categorized into either passive or active exploration profiles. In the passive exploration profile, infants showed a moderate amount of visual exploration (51% of the trial), a low-to-moderate amount of manual exploration (20% of the trial), and a minimal amount of oral exploration (0.36% of the trial). Infants in the active exploration profile showed a moderate amount of visual exploration (60% of the trial), a high degree of manual exploration (79% of the trial), and a low-to-moderate amount of oral exploration (20%). The relationship between exploration and development When compared to the developmental assessment, results showed that the active exploration profile was associated with higher cognitive, expressive communication, and receptive communication scores. This profile was also associated with a higher cognitive age on several indices. Additional tests showed that factors like maternal age, premature birth, and congenital heart defects were unrelated to the probability that infants belonged to either profile. Individual needs These findings show that infants with Down syndrome display systematically different levels of visual, manual, and oral exploration. Differences in passive and active profiles were most pronounced in the amount of time spent in manual exploration of objects. Also, exploratory behaviors were related to general development. These results demonstrate the within-group variability of people with Down syndrome and highlight the need to tailor interventions to individual needs. Early intervention for children with Down syndrome As early exploration forms the basis for other areas of development, it is important to stimulate this behavior in infants with Down syndrome. Infants showing a passive form of object exploration may benefit especially from this type of intervention. For infants who already explore more actively, object exploration can be used as a platform for enriched learning experiences in other developmental areas. Because the current study did not include a comparison group, it is difficult to know whether these patterns are specific to infants with Down syndrome, or whether they can be observed in infants with developmental disabilities in general. Therefore, future research should focus on exploratory behaviors in other clinical groups as well. References Fidler, D.; Schworer, E.; Prince, M.; Will, E.; Needham, A.; Daunhauer, L. (2019). Exploratory behavior and developmental skill acquisition in infants with Down syndrome. Infant Behavior and Development, 54, 140-150. https://www.cdc.gov/ncbddd/birthdefects/downsyndrome.html --- ## Cognitive neuroscience: Emotions URL: https://noldus.com/blog/cognitive-neuroscience-emotions Published: 2019-11-21 11:47:00 Description: In my previous blog post, I shared some of the basics of cognitive neuroscience. In this blog post, we will zoom into a more specific part of cognitive neuroscience: emotions. Have you ever been at the most wonderful place during your vacation, standing on top of the world or at a beautiful square in the middle of the most idyllic town, and thought: 'It's just the firing of neurons that is making me feel happy right now'? Most of us probably don't think that way. It is bizarre to realize that most of our emotional moments are caused by electric signals in our brain, leading to an increase in hormones, creating an instant feeling of happiness, sadness, or anger. Cognitive neuroscience: the brain In my previous blog post, I shared some of the basics of cognitive neuroscience, such as the triune brain, and methods to detect brain activities. In this blog post, we will zoom into a more specific part of cognitive neuroscience: emotions. Are you interested in emotion analysis? Download the free white paper on the Facial Action Coding System and find out more about the benefits of using FACS. What are emotions? Emotions are related to interests: they signal that your interests are at stake, in a positive or negative way. These could be physical interests as well as social interests. Your brain is hierarchical, and your cortex is only notified when you need to take action. Emotions can cause your cortex to pay attention because of the interests that are at stake. Emotions to survive As mentioned before, the limbic system in the brain constantly scans for things that you should pay attention to in order to survive. Whether it is something dangerous in our environment, such as a predator, or the smell of a rotten piece of meat, the limbic system sends out a signal to the neocortex to make you aware of this danger. In that case, you will not eat the meat but instead, you will throw it away. The parts of the limbic system that cause these reactions are ancient: the amygdala (fear) and ventral striatum (pleasure). Amongst other things, these brain regions influence the reactions to fight or take flight, or to explore the possibilities of rewards. Automated actions As explained by Dr. Antonio Damasio, a professor of neuroscience at the University of Southern California, emotions are a collection of automated actions aimed at a particular effect that will have importance for the regulation of life. Our brains have evolved such that emotions serve as a little package of rapid intelligence to help you quickly solve a problem without you having to think about it. Some of these actions are very visible (facial expressions, posture, behavior). Other reactions involve less visible changes in bodily functions such as heart rate, blood pressure, and cortisol levels. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Feelings versus emotions There is a difference between feelings and emotions. Emotions are a brief episode of coordinated brain, autonomic, and behavioral changes that facilitate a response to an event. They are lower level responses, coded in our genes. Feelings are high-level responses which provide a mental and perceptual representation of what is physically happening inside our bodies. They are internal, subjective, and personal: the way you experience the emotion is based on your individual experiences, beliefs, and memories. As Dr. Damasio said: "The order of such events is: I am threatened, experience fear, and feel horror." From self-reports to advanced techniques Back in the day, researchers mostly used self-reports to ask how someone felt. However, since feelings are internal and subjective, they cannot be measured accurately. Because emotions are physical, they can be brought to light by combining different physiological measurements like heart rate and blood pressure, or by analyzing facial expressions. Facial expressions can tell us a lot. A smile can indicate happiness or approval; a frown can signal anger or unhappiness. These facial expressions expose our emotions, and thus our true feelings, about a situation. It can also be the other way around. Facial expressions can influence your emotions, as Marsha Wichers shows. As a cosmetic doctor and visual artist in the Netherlands, Marsha underwent full facial Botox injections and found it difficult to experience the emotion that was linked to the expression. She could not show the expression, and thus could not feel it strongly. Learn more about how to measure emotions in the blog series of my colleague Patrick. Cognitive neuroscience: behavior Emotions guide your thinking and your behavior through powerful consciously experienced emotions and through unconscious emotional associations (intuitive preferences or aversions). But more about behavior in the next blog post… Don't want to miss this next blog post? Stay posted and subscribe now! You will receive updates of new blog posts every month. References Baars, B. J., & Gage, N. M. (2010). Cognition, brain, and consciousness: Introduction to cognitive neuroscience. Burlington, MA: Academic Press/Elsevier. This Time With Feeling: David Brooks and Antonio Damasio. The Aspen Ideas Festival. https://www.youtube.com/watch?v=IifXMd26gWE --- ## Machine learning and object detection URL: https://noldus.com/blog/machine-learning-object-detection Published: 2019-11-14 11:00:00 Description: Humans are incredibly good at recognizing patterns. Now computers can do it as well, and that can be useful. Read more about machine learning and object detection. Imagine two circles next to each other. Then imagine a horizontal line underneath the two circles. You cannot help it, your brain sees a face in that simple pattern. Pattern recognition is something that human minds are incredibly good at, enabling us to find meaning from very sparse information but also to interpret rich and complex patterns. Not only do we recognize something looking like a face when we see one, we can separate the images of thousands of different faces, and remember the names of at least hundreds. Some of us are better at that than others! Machine learning and object detection This is not a uniquely human ability, other species can also recognize the different faces of animals they know and domesticated animals are even quite good at distinguishing human faces. Computer-vision based machine learning is all about trying to make software which has similar abilities. There isn't a computer program that can handle anything like the range of different types of images that we can, but there are many AI programs which are getting really good at recognizing specific things. For bird watchers and other naturalists there are websites which you can upload photos to and it will not only tell you what the plant or animal is, but also how confident it is in its guess. For psychologists there are programs which look at the image of a human face and tell you what emotion is being shown. Noldus' FaceReader is a good example. For farm robots there are programs which look at peppers and determine if they are ripe and then tell the robot how to place its claw to pick them without damaging them. Automatic object detection Noldus is very interested in this computer vision technology, not only in emotion recognition but also in a number of other applications. One of them is object detection and recognition in the field of human factors or user experience research. In a complex environment like a plane's cockpit or ship's bridge, there are many different elements like a radar screen or control lever. For the researcher to label those by hand in a video is an awful lot of work. Where this technology becomes really interesting and useful is when that object detection technology is combined with eye-tracking technology. That is exactly what Noldus has been working on in the ACROSSING project. That means that we can automatically determine not only that a ship's captain is looking towards the right of the bridge, but that he or she is looking at the radar screen. And we can measure that both when the captain is walking around and when the radar display is switched to a different monitor. The AI-trained computer vision can recognize a radar screen wherever it is in the video image. Furthermore, because this is a specialized application trained with a specific set of images, if there are two different types of radar, say weather and ships, it can learn to distinguish them. RESEARCH PROJECT Want to partner with us? If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 35+ years of experience Learn more Egocentric vision With traditional eye tracking, this is only possible with a fixed eye tracker, for instance, underneath a computer monitor. The head doesn't move with respect to the screen, and the system knows what is shown on the screen at a given time, so it can work out that if someone looks at the top right of a certain web page, that they are looking at the company logo. That is not so difficult with a fixed monitor and a person who is sitting still, but as soon as the person gets up and starts walking around, 'top right' of their field of view means something different from one minute to the next and the images shown on the monitor can be captured separately. Eye tracking glasses still record where someone is looking and also make a video of what they see (this is called 'egocentric vision'), but translating those two things into information about what they are looking at is an expensive task. That is where the automatic object detection technology comes into play. It is used to analyze the egocentric video and detect if there is (for instance) a radar screen in view and where it is in 3D space. Deep learning The technology works using deep convolutional neural networks to perform the object detection on each video frame. The network is trained on pre-defined classes of objects such as a generic monitor or sub-classes, for example monitors showing the radar. At test time, it shows the objects it has found by annotating bounding boxes around them, signalling their areas of interest automatically without any effort by the researcher, as shown in the picture at the top of this blog. Most importantly, the network can detect multiple objects at the same time, from a single video frame. At the same time, the eye tracker is still measuring where the person wearing the eye tracking glasses are looking. The coordinates from the eye tracker and the coordinates of the detected objects are transformed so that they are in the same coordinate space as each other. All those pieces of technology amount to a system that synchronizes a person's gaze with the objects found in the video and documents the contents of the areas of interest that captured the focus of the user. Valuable for designers This is not trivial, our colleague who developed this wrote over a million lines of code in his work in the ACROSSING project. Was it worth it? Actually, this is very valuable information. It lets researchers answer questions such as how often a ship's captain looks out of the window (or is he or she too absorbed in watching the instruments?), how systematically the bridge staff scan all the different sources of information, and if they noticed a warning lamp. That knowledge is critical both in designing safe and usable systems and in training new crew. Acknowledgments The work described here was carried out by Georgios Kapidis in the ACROSSING project, which was funded by the Horizon 2020 program of the European Union as a Marie Skłodowska-Curie Innovative Training Network, project number 676157. The specific work on the ship's bridge simulator was carried out in cooperation with MARIN. References The following papers give more details about the technology developed: G. Kapidis, R. Poppe, E. van Dam, L. P. J. J. Noldus, and R. C. Veltkamp, "Multitask Learning to Improve Egocentric Action Recognition," in IEEE International Conference on Computer Vision (ICCV) Workshops, 2019. G. Kapidis, E. van Dam, R. Poppe, L. P. J. J. Noldus, and R. C. Veltkamp, "Action Detection from Egocentric Videos in Daily Living Scenarios," in Measuring Behavior 2018, Manchester, UK, 2018, pp. 405 – 407. G. Kapidis, R. Poppe, E. van Dam, L. P. J. J. Noldus, and R. C. Veltkamp, "Object Detection-Based Location and Activity Classification from Egocentric Videos; A Systematic Analysis," in Smart Assisted Living, Springer, 2019. --- ## Decreased learning abilities in diabetic rats: Silymarin to the rescue URL: https://noldus.com/blog/decreased-learning-abilities-diabetic-rats Published: 2019-11-14 10:16:00 Description: Silymarin is a substance that works as an antioxidant, is anti-inflammatory and increases BDNF levels. After supplementing silymarin to diabetic rats, typical diabetes symptoms were greatly improved. Consequences of diabetes Three researchers from the Düzce University and the Selçuk University in Turkey have researched a potential diabetes treatment. Diabetes sometimes has far-reaching consequences on people's lives, because of the organ, brain and central nervous system damage it can cause. Silymarin: a cure? A potential treatment for this damage consists of silymarin supplementation. Next to various other properties, this substance can decrease inflammation, works as an antioxidant and, on top of that, can pass through the blood-brain barrier. Furthermore, it can regulate glucose uptake and it has a positive influence on the central nervous system. Testing the cognitive function Preparation of behavioral tests Using streptozotocin injections to induce diabetes, the scientists divided rats into four groups, i.e., control, diabetes, silymarin and diabetes + silymarin. Starting 7 days after the diabetes induction, the rats in the silymarin groups were fed silymarin dissolved in maize oil daily for 35 days. Testing the cognitive function In order to test movement, anxiety and spatial memory of the rats, various behavioral tests were carried out. All tests were filmed for analysis, after which the scientists used Noldus EthoVision XT 9.0 to collect data from the videos. Open field test For 5 minutes, the rats were put in a black open field arena, and were allowed to explore freely. Various types of data related to spontaneous movement were collected, like movement speed and distance, grooming, and rearing. Furthermore, as an anxiety measure, defecation was noted. Elevated plus maze In another test, an elevated plus maze (EPM) was used. It had two enclosed and two open arms, and for each test the rats were placed in the center facing one of the open arms. They were again allowed to explore freely for 5 minutes, after which the researchers noted down the number of entries in both types of arms, and how much time was spent inside them. Morris water maze for spatial memory A Morris water maze test (MWM) was done in order to test spatial memory. The maze was divided into four imaginary quadrants; northeast, southeast, northwest and southwest. In one of the imaginary quadrants (northwest), an escape platform was present, away from the wall and hidden by the color of the painted water. Visual cues were placed around the tank which could be used by the rats for orientation. For 4 days, the rats were trained 4 times daily, starting from a different quadrant each time. They were expected to find the platform within 60 seconds, and if this failed a researcher would physically put the rat on the platform. At 24 hours after the training, a 90s probe trial task was done, this time without a platform. Brain tissue samples After the behavioral tests, the researchers took brain tissue samples. Those were frozen and later homogenized for biochemical analysis (BDNF and HDAC3). Read more about this in the original study (see reference below). FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Diabetes influencing cognitive function Anxiety in the open field test The scientists from this study have found that diabetic rats defecated more than diabetic rats treated with silymarin. This was probably caused by the rats trying to create a safer area for themselves, which indicates that diabetes increases anxiety levels. It also shows that silymarin seems to be able to decrease diabetes-induced anxiety. Rats prefer closed arms in the EPM The EPM has shown increased anxiety in diabetic rats as well, because this group spent more time in the closed arms. Furthermore, they entered the closed arms more often than rats from other groups did. MWM shows decreased learning abilities It seems that diabetic rats have a harder time learning than both non-diabetic and diabetic + silymarin rats. After the MWM, the probe trial task showed that diabetic rats passed over the former location of the escape platform less often than the other groups did. BDNF and HDAC3 In diabetic rats, lower numbers of BDNF were found compared to the other groups, but their levels were equal compared to the diabetes + silymarin rats. Low BDNF levels in diabetics are associated with cognitive deficits. This result indicates that silymarin could help counter various negative effects of diabetes that are related to learning abilities. No differences in HDAC3 levels were found between the various rat groups. This substance decreases spatial memory abilities in rodents and is needed for proper brain development. Silymarin helps with diabetes-caused cognitive dysfunctions A difference was found in learning abilities between the diabetes and the diabetes + silymarin group, which suggests that silymarin is able to ameliorate cognitive dysfunctions caused by diabetes. The Düzce University and Selçuk University scientists carried out this study as the first in its field, and therefore, many potential silymarin effects on diabetes are still to be discovered. Reference Yön, B., Belviranlı, M., & Okudan, N. (2019). The effect of silymarin supplementation on cognitive impairment induced by diabetes in rats. Journal of basic and clinical physiology and pharmacology, 4, 30. --- ## Consumers' food choices and emotions URL: https://noldus.com/blog/consumers-food-choices-and-emotions Published: 2019-11-07 10:41:00 Description: Is there a relationship between food choice and a person’s mood? Bartkiene et al. examined the factors that influence our food choice, using facial expression analysis. If you ask me, the answer is "chocolate"! Eating a piece (or preferably a whole bar) of sweet chocolate will definitely change my mood positively. Therefore, I would choose that specific piece of food when I am feeling down. I believe that chocolate is the answer to everything. Which food a person chooses to eat is influenced by many factors. Hunger is the most obvious one. However, not only physiological or nutritional needs determine what we choose. What influences our food choices? The research team of Prof. Dr. Elena Bartkiene from the Lithuanian University of Health Sciences focused their study on evaluating the connection between gender, age, and education level of consumers and their perception, emotional motivations, and knowledge about healthy eating. Additionally, they examined a possible relationship between food choice and a person's mood in people with and without depressive disorder (DD). Facial expression analysis to evaluate food induced emotions Over 500 participants were involved in the study. The researchers used two methods to gather their data: - 1.A questionnaire to evaluate perceptions of healthy eating, sources of information about healthy diets, and emotional motivations associated with food choices and eating practices - 2.FaceReader software to evaluate possible differences in food induced expressions The latter method was performed with 80 participants. Participants were divided into two groups: people diagnosed with DD and a control group not diagnosed with a mental disorder for at least a 1-year period. During the tests, which took place in the morning (after 8 hours of fasting), different food tastes (sweet, salty, bitter, sour, and neutral) were presented. The sessions were recorded with MediaRecorder. Additionally, the researcher used the 9-point Hedonic Scale (ranging from like extremely to dislike extremely) to measure whether the food tastes were liked or not. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download The role of gender when choosing food Everyone knows that healthy eating is important. It ensures that your body functions well and that you feel fit. A good diet therefore increases the quality of life. The government, food companies, general practitioners, and many others, inform us about healthy food. The results of the research of Bartkiene et al. showed that gender has a significant influence on the selection of sources of information about a healthy diet: according to questionnaire data, males obtained information from television and books more 'sporadically' than females. In contrast, females gather information from these resources more consciously and frequently. The team also found that gender does not influence consumer perceptions about healthy eating. However, female participants did agree more than male participants did when they were asked whether food helped them cope with stress, if food could serve as emotional consolation, and whether they craved more sweets when depressed. On the other hand, men reported associations between job stress, drinking status, and unhealthy eating patterns. Women seem to be more aware of and attentive to their emotions and are determined to change them. The 'food-mood' link Mood and food are sometimes linked. Different foods induce different emotions, and consumers choose foods depending on their mood. In this study, age was found to be a significant factor for the 'food–mood' association of participants. The older persons were more likely to report positive emotions after having eaten their favorite comfort food. Comfort foods have a high calorie content and tend to be associated with childhood and/or home cooking, often prepared in a simple or traditional style. It makes us feel sentimental, reminding us of home, family, and friends. To examine the impact of education on emotional motivations and perceptions about healthy eating, the researcher asked the participants questions about the role of food regarding aspects such as weight control, feeling depressed or alone, costs, traditions, and desire for sweets. For most of the analyzed emotional motivations, participants' education level had a significant influence. In the video below, Prof. dr. Susan Duncan from Virginia Tech explains that her research focuses on the role of sensory evaluation. With the help of FaceReader, she can capture how people are responding emotionally to products. Relationship between food choice and emotions Regarding the sweet, sour and salty tastes, it was found that persons with DD expressed less 'happy' emotions compared to the control group. While eating food with a bitter taste, persons with DD expressed lower 'neutral' and 'contempt' emotions. Higher 'sad' and lower 'contempt' expressions were observed in persons with DD for a neutral taste. Mood has a strong link with the choice of food The results of the study showed that expressions induced by different food tastes vary when comparing healthy people with people suffering from DD. The research team conclude that many factors are of high importance in the analysis of food choices. They state: "The results obtained using FaceReader are very promising and sufficiently accurate to detect differences in facial emotion expressions induced by different tastes of food for different mood groups (with and without DD)." References Bartkiene, E.; Steibliene, V.: Adomaitiene, V.; Juodeikiene, G.; Cernauskas, D.; Lele, V.; Klupsaite, D.; Zadeike, D.; Jarutiene, L. & Guiné, R.P.F. (2019). Factors Affecting Consumer Food Preferences: Food Taste and Depression-Based Evoked Emotional Expressions with the Use of Face Reading Technology. BioMed Research International, 4, 1-10. DOI: 10.1155/2019/2097415 --- ## SUKIPANI: The magic word for making a smile URL: https://noldus.com/blog/sukipani-magic-word-making-smile Published: 2019-10-31 12:10:00 Description: The SUKIPANI smile is an exercise to train the muscles you use while smiling. Dr. Sugahara explains the effect of the movements of the muscles and uses FaceReader to analyze the smiles. A smile is a powerful tool. It makes us enjoy things more. We smile because we feel happy, and in fact, we feel happier because we smile. A smile is contagious: seeing other people smile makes you smile. A smile attracts attention and expresses self-confidence. Facial expressions studied Dr. Toru Sugahara, also known as the smile doctor, worked with colleagues at Waseda University in Japan to examine how facial features and impressions affect emotions. A group of 18 adult women were asked to recall either an unpleasant or a pleasant memory, and their facial expressions were analyzed using FaceReader. The experiment showed that the expression of the face was directly impacted by the emotions felt in the previous moments. Does this mean that we can always read from someone's face how that person feels? Maybe not. The researchers concluded that in everyday life, people tend to suppress their emotions and expressions. However, a genuine smile is a smile you cannot cover up. Just look at the SUKIPANI smile! FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Facial Action Coding System The SUKIPANI smile is an exercise to train the muscles you use while smiling. The more you practice, the more genuine your smile will be. Dr. Sugahara explains the effect of the movements you make when saying ‘SUKIPANI’ and uses the Action Units defined by the Facial Action Coding System (FACS) to illustrate this. ‘SU’ ensures that the muscles used for smiling will be stretched, meant as a warm up. While saying SU, open the eyes, move the mouth to a round position, and make a frown. The word ‘KI’ uses all the muscles for a big smile. Here you can see Action Units 6 (cheek raiser), 10 (upper lid raiser), 11 (nasolabial deepener), 12 (lip corner puller), 14 (dimpler), and 25 (lips part) in action. Saying ‘PA’ subsequently releases the muscles by opening the mouth widely and breathing out. This way it changes gradually into a smooth smile. The last syllable ‘NI’ puts a brilliant smile on your face with all the stretched muscles, thanks to the previously performed exercises. By repeating the song over and over again, the smiling muscles will be trained. The exercise of the SUKIPANI smile also includes several hand and arm movements, which are carried out simultaneously. It has been found that blood circulation improves when tension in the muscles around the shoulder is reduced. This movement also leads to physical and mental relaxation, resulting in a positive attitude. Moreover, a better posture means that a brighter and bigger smile can be achieved. FREE WHITE PAPER Facial Action Coding System Download here the FREE white paper 'Facial Action Coding System (FACS)' and learn more about: - Objective results with FACS - Action Units - Examples using FACS Submit to download A scientifically proven improved smile Using software for automatic facial expression analysis, Dr. Sugahara’s small experiment showed that 81% of participants successfully trained their smile muscles after a few repetitions of the SUKIPANI exercise. FaceReader displayed a higher ‘happy’ score than when the participants had not trained their smiles with SUKIPANI. There are many different kinds of smiles: a grin, a giggle, an audible smile, a naughty smile, a forced smile, a fake smile, and a Duchenne smile, to name a few. Now we can add the SUKIPANI smile! References Miyazaki, M.; Sugahara, T.; Orihara, N. & Umezawa, S. (2019). Footprint of Emotions that Remain in Facial Features. The influence of emotion and facial expression is given to the complexion. Waseda University, Saitama, Japan. Translations by Mayuko Kanemura --- ## Improving patient safety URL: https://noldus.com/blog/improving-patient-safety Published: 2019-10-22 12:18:00 Description: We all agree that communication in the operating room is essential. It saves time and ensures a better quality of patient care. Using the WHO Surgical Safety Checklist supports this. How can we learn to use this checklist? Imagine that it happens to you. You come out of the operating room and it seems that they have performed an operation that was not intended for you. Luckily, this happens only occasionally, it is not daily news. But, according to the World Health Organization (WHO), the risk of a patient dying while receiving medical care is currently estimated at 1 in 300. This underlines the importance of learning to work well with checklists by healthcare professionals. Checklists are the ultimate safety nets. You just have to be sure that the patient you are about to operate is the right one. You need to answer questions such as 'is this the right patient' and 'what operation are we performing', before reaching for your tools. WHO checklist evaluation Already in 2008, the WHO published guidelines identifying multiple recommended practices to ensure the safety of surgical patients worldwide. The WHO Surgical Safety Checklist is developed by professionals and is based on a core set of safety standards. It consists of three phases: - 1.Sign in, before induction of anesthesia - 2.Time out, before skin incision - 3.Sign out, before patient leaves operating room The Checklist helps ensure that important safety steps are reliably followed for each operation. Recently, the WHO updated the 10 facts on patient safety. They are quite shocking facts. Reasons enough to keep insisting that students and professionals should practice using checklists, keep improving teamwork and communications, and participate in simulation-based training. The AV recording tool Viso is very suitable for such a training. Simulation-based training to improve communication One of the goals of the WHO checklist is to facilitate communication between team members. Medical professionals carry out their jobs with the utmost precision, but one of the biggest pitfalls is in the space between them—communication. A simulation-based training is suitable for training communication skills as well as using a checklist. By recording the sessions and marking events of interest, which can be viewed afterwards, the team can discuss what went well and what did not. The lessons learned can be discussed during a more extensive debriefing. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo Improving patient safety by observing behavior Rydenfalt et al. (2013) evaluated the usage of the WHO checklist (version 1). The research team focused on the occurrence of checklist items in the Time out phase and identified several points for improvement. In order to analyze this phase quantitatively, Rydenfalt and colleagues recorded 24 surgical procedures using one camera in the operating room. To accurately code behaviors, the researchers used The Observer XT software. They assessed whether participants engaged actively and coded the frequency in which items on the checklist occurred. Active participation was defined as "a team member having some input either by asking or by answering questions on the checklist". Checklist items were then coded as performed or not performed. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Naturalistic observation studies Regarding the chosen method, Rydenfalt et al. explained that "naturalistic observation studies can avoid the selective perception of participants and enable researchers to notice things that escape the awareness of the participants". Although the results showed that the checklist was not always used as intended, the results also indicated that the Time out phase (step 2 in the checklist) was initiated in almost all surgical procedures. The study also showed that team members sometimes conducted other professional tasks, unrelated to the Time out, during the Time out phase, such as throwing out trash or raising the operating table. Communication in healthcare Because introductions can promote trust amongst team members and encourage team building, they are a part of the checklist that should not be overlooked. However, the study showed that team members did not always introduce themselves. Although it could be argued that team members already know each other from previous operations, this may not always be the case. When a stressful situation occurs, it may be too late to clarify names and roles of team members. Stressing the importance of underlying processes Rydenfalt et al. explain that it is important to describe 'risk' as what can and should be done to avoid risks that expose patients to danger and thus improve patient safety. All personnel should be aware of the risk-reducing intention of the checklist. Additionally, risks are often linked to active failure, such as avoiding an incision in the healthy leg as opposed to the leg that requires surgery. However, risk can also be linked to communication failure. Rydenfalt et al. state that "communication failures and the checklist items related to facilitating good and clear communication may be perceived by hospital personnel as being less significant". They conclude that adherence to the checklist will most likely involve altering the staff attitude towards checklist items, thereby facilitating effective risk-reducing communication. By addressing the importance of underlying processes, teamwork can be improved, thus positively influencing and increasing patient safety. References - Rydenfalt, C.; Johansson, G.; Odenrick, P.; Akerman, K.; Larsson, P.A. (2013). Compliance with the WHO surgical safety checklist: deviations and possible improvements. International Journal for Quality in Health Care, 1-6. - World Alliance for Patient Safety. WHO guidelines for safe surgery. Geneva: World Health Organization, 2008. --- ## What is RPPG? URL: https://noldus.com/blog/what-is-rppg Published: 2019-10-17 11:31:00 Description: Nowadays, measuring heart rate and heart rate variability can be done remotely, without all kinds of devices being attached to the test participant, using remote photoplethysmography (RPPG). What is RPPG and how does it work? This blog post is written by Mayuko Kanemura. During her internship at Noldus, she performed a validation study of the use of Remote PPG in FaceReader. She compared three heart rate measurements: RPPG, PPG, and the gold standard, ECG. In this blog post, she explains what RPPG is and gives recommendations on how to best measure this. What is RPPG? Tools for automated analysis of facial expressions provide an objective assessment of a person's emotional expressions in consumer behavior and sensory research. FaceReader also offers other video-based functionalities that are useful for sensory and consumer research such as automated registration of the frequency and variability of heart rate. Heart rate and heart rate variability Heart rate (HR), the measure of how often the heart beats per minute, is influenced by the autonomic nervous system (ANS) which consists of two primary branches, the sympathetic and the parasympathetic nervous system. The former is active when we are in an exciting situation (threat, fear, stress, and exercise) and increases heart rate. The latter is active when we are in a relaxed situation (feelings of love, compassion, and calm) and decreases heart rate. As you can see, the responses are influenced by mental and physical conditions. Heart rate variability (HRV) Heart rate variability (HRV) is the indicator of the balance of those conditions, being a marker of health and stress. When the sympathetic nervous system is predominant like when people feel stressed, HRV decreases. When the parasympathetic nervous system is predominant like when people are relaxed, HRV increases. There has been growing attention for HRV as an indicator of cardiovascular disease, and internal emotions such as depression and work stress, etc. [1]. Measuring HR and HRV remotely FaceReader can measure heart rate and heart rate variability remotely using remote photoplethysmography (RPPG), a tool to measure heart rate remotely without attaching sensors. It only requires video recording with a high-resolution camera. It can be beneficial in various kinds of physical, health and emotional monitoring, such as monitoring of drivers, consumers, the elderly, and infants [2]. Those kinds of monitoring are now available with less discomfort, using remote PPG. As part of my research, I looked at HR and HRV while participants consumed different kinds of foods, because I wanted to observe the physiological mechanism changes during food consumption. The principles of PPG The principles of PPG are the following: Using the example of a wearable, such as a heartrate-sensing watch, light emits to the skin from one sensor and a second sensor detects how much light is returned to the device. This forms the contrast between emitted light and reflected light. The amount of reflected light changes according to the blood volume, which is caused by capillary dilation and constriction, hence it can estimate the heart rate. Figure 1. Optical heart rate sensing. Left: lower pressure preceding the pulse wave means narrower arteries and less absorption (higher reflectivity) of the green light source. Right: a higher blood pressure pulse causes wider arteries and more light absorption (lower reflectivity) [3]. Credit: The Conversation. Remote PPG How does remote PPG detect heart rate? It is the same principle but it is a contactless measurement. It measures the variance of red, green, and blue light reflection changes from the skin, as the contrast between specular reflection and diffused reflection. Specular reflection is the pure light reflection from the skin. Diffused reflection is the reflection that remains from the absorption and scattering in skin tissue, which varies by blood volume changes. Figure 2. The skin reflection model that contains specular and diffuse reflections, where only the diffuse reflection contains pulsatile information [4]. Credit: Wang et al. (2017). Algorithmic principles of remote-PPG. IEEE Transactions on Biomedical Engineering, 64(7), 1479–1491. DOI: 10.1109/TBME.2016.2609282 The approach to remote detection is the following: - [Skin pixel selection] The face in the captured webcam image is detected and modeled in order to determine facial landmarks and head orientation. Subsequently, approximately the top two-thirds of the face, where most of the blood vessels are concentrated, is selected as the region of interest. - [Signal extraction] The average of each pixel colors (red, green, blue) of the region is measured over time (both specular + diffuse reflections). - [Signal filtering] The noise from the head motions is detected by fitting the facial model and then noise-free heart rate is produced. - [Output calculations] By detecting peaks, inter-beat intervals are measured and then the heart rates and heart rate variability are estimated. Figure 3. An overview of the proposed heart rate and heart rate variability estimation pipeline (left to right). The face in captured webcam images is detected and modelled to track the skin pixels in the region of interest. The average value of RGB signals is extracted over time. In parallel, the head movements are tracked and used to suppress motion noise. The process of filtering the wide and narrow band signals produces a clean pulse waveform from which peaks are detected. The inter-beat intervals obtained from these peaks are then used to compute heart rate and heart rate variability. The full analysis can be performed in real time on a computer [5]. FaceReader validation study In the validation study, 25 participants were asked to watch a video (still condition) and to consume different food stimuli, ranging from liquid to solids (water, yoghurt, chicken, sausage), and the other way around. To validate the RPPG by FaceReader, BIOPAC ECG and BIOPAC PPG were used. Within the still condition, the measurement of RPPG was successful. However, during food consumption, the differences between measurements from RPPG and ECG were bigger during consumption, indicating that RPPG underestimated higher heart rates. The movement of the face during food consumption disturbed the RPPG measurement. On the other hand, BIOPAC ECG and PPG showed high agreements. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Recommended conditions As a result of my research, the following conditions are recommended for FaceReader RPPG: - Use of high resolution and uncompressed cameras, since both lead to a more accurate heart rate detection. - Use of good light conditions, solely from a front lamp. However, avoid frontal lighting that is too strong, to prevent overexposure. A ceiling lamp causes overexposure, which interrupts the skin color detection. - Avoid video compression. Video compression decreases the resolution and video quality. Moreover, RPPG measurement is sensitive to motion of the head. It is recommended to use a setting where participants are sitting and not moving too much. A high correlation between the gold standard and RPPG in these situations has been observed in many studies. Because of the increasing attention to remote PPG, these drawbacks are expected to be solved, at least partly, with the improvement of algorithms in the near future. References - Thayer, J. F.; Yamamoto, S. S. & Brosschot, J. F. (2010). The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors. International journal of cardiology, 141 (2), 122-131. - Wang, W.; Den Brinker, A. C. & De Haan, G. (2018). Single Element Remote-PPG. IEEE Transactions on Biomedical Engineering. - NeuroData Lab. (2019, March). Every beat counts. Comparing Remote Webcam Heart Rate Detector to Wearables. https://medium.com/@neurodatalab/every-beat-counts-comparing-remote-heart-rate-webcam-detector-to-wearables-d8d59aab863c - Wang, W.; den Brinker, A. C.; Stuijk, S. & de Haan, G. (2016). Algorithmic principles of remote PPG. IEEE Transactions on Biomedical Engineering, 64 (7), 1479-1491. - Gudi, A.; Bittner, M.; Lochmans, R. & Van Gemert, J. (2019) Efficient Real-Time Camera Based Estimation of Heart Rate and Its Variability. International Conference on Computer Vision (ICCV) Workshop. --- ## Can caffeine prevent Alzheimer's? URL: https://noldus.com/blog/can-caffeine-prevent-alzheimer Published: 2019-10-08 15:44:00 Description: What is the most popular drug in the world? It’s not alcohol, cannabis, or cocaine, but something most of us start with each day. Coffee; or, more specifically: caffeine. A Morris water maze memory study What is the most popular drug in the world? It's not alcohol, cannabis, or cocaine, but something most of us start with each day. Coffee; or, more specifically: caffeine. Like millions of other people, it helps me get started and prevents my morning headaches. Caffeine also has been shown to prevent age-related cognitive decline by reducing the risk of developing Alzheimer's Disease (AD) and dementia. It is not surprising, then, that much research has already been done on the effect of caffeine in the development of AD. Mouse models of Alzheimer's disease AD has two major pathological hallmarks: so-called plaques and tangles in the brain. Amyloid beta peptides accumulate to form plagues outside of the cells, and hyperphosphorylated tau proteins form tangles inside of the cells. Both types of abnormal protein deposits are associated with the cognitive impairments observed with AD. To investigate the effect of caffeine on AD, studies have been done on AD mouse models with amyloid plaques, but previously no work had been done on models based on the tau-tangles. Cyril Laurent and his colleagues thought it was time to change this. Testing the memory with a water maze A transgenic mouse model with progressive AD-like tau pathology (THY_Tau22) was tested against a wild-type group. Half of each group received caffeine in their drinking water, resulting in four treatment groups. To test learning and memory, researchers used the Morris water maze. A standard protocol was followed: basic learning was testing using a hidden escape platform. Each mouse was given four swimming trials a day for five consecutive days. The mouse was released in the water and once it had found the platform is was allowed to stay there for fifteen seconds. If the mouse did not reach the platform in two minutes, it was guided to the platform. Escape latency, path length, and swimming speed were automatically measured with EthoVision XT. Exactly three days later a probe trial (no platform) was conducted for sixty seconds to measure memory retention. In this case, proportion of the time spent in the target quadrant (that previously held the platform) was measured with EthoVision XT. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Caffeine prevents memory impairment All the mice in this experiment seemed to learn well. Their results improved over the five learning trials, and there were no differences in this improvement between the four treatment groups. The tau-pathology did not cause the 'AD-mice' to have any problems in learning. It did however result in specific memory issues. During the retention-trial, THY-Tau22 mice that did not receive any caffeine spent an equal amount of time in each of the quadrants. Interestingly, but as expected, the THY-Tau22 mice that did receive caffeine performed identically to wild type mice, spending more time in the target quadrant than any other. Therefore, caffeine did help maintain spatial navigation memory in tau-impaired mice. Caffeine did not seem to have any effect on the learning and memory of the wild-type mice. Fewer tangles in the brain Consistent with the results from the water maze retention trials, researchers found fewer tau-tangles in the brain cells of the THY-Tau22 mice that received caffeine compared to those who just got water. The level of caffeine taken by the mice in this experiment is considered to be equal to approximately two cups of coffee a day for humans. Chronic and moderate caffeine intake, at least in this study, did indeed seem to have a neuroprotective effect against this AD-related pathology. So, there you have it, drink your coffee! Or tea, of course. References Laurent, C.; Eddarkaoui, S.; Derisbourg, M.; Leboucher, A.; Demeyer, D.; Carrier, S.; Schneider, M.; Hamdane, M.; Müller, C.E.; Buée, L.; Blum, D. (2014). Beneficial effects of caffeine in a transgenic model of Alzheimer's disease-like tau pathology. Neurobiology of aging, article in press, doi: 10.1016/j.neurobiolaging.2014.03.027 --- ## Measuring the user experience of tube feeding URL: https://noldus.com/blog/measuring-user-experience-tube-feeding Published: 2019-10-04 09:21:00 Description: Tube feeding has had a fascinating history, but there is still scope for innovation. Noldus will develop a system to measure its users' experience in the FoodFriend project. When an amoeba eats, it is very straightforward. The single-celled animal simply wraps itself round an alga or other small food particle and engulfs it. Once inside the amoeba, a vacuole forms round the particle, enzymes are secreted in to digest it and that's it, feeding completed. In stark contrast, the human digestive system is highly sophisticated with all sorts of organs joined together in our alimentary canal so that we can eat a huge variety of all sorts of different foods. Although that has the considerable advantage that we don't have to survive by eating microscopic food particles, not to mention the great pleasure that eating can give, like all complex systems, it does mean that it gives a problem if it doesn't work properly. That can be for all sorts of reasons; a patient might not be able to swallow due to a stroke, there might be a problem with the mouth, or the patient can eat, but just not enough. Tube feeding Fortunately, there is a solution - tube feeding. That means that special food is delivered to the stomach or small intestine (jejunum) from a tube which can be inserted via the nose (sometimes with the help of endoscopy or x-rays) or directly via a stoma through the stomach or intestine wall. The technique of tube feeding is surprisingly old. The ancient Egyptians documented its use on papyrus scrolls from 3500 years ago. Until the 12th century, tube feeding was only possible rectally, but then in 1598 Capivacceus (a professor of science ('philosophy') and medicine in Padua) used a hollow tube with a bladder filled with a nutrient solution inserted into the esophagus. Subsequently, the technique was improved with the development of more flexible tubes, first with leather and later with rubber. There have also been important developments over time in the composition of the liquid food delivered. Early solutions were often milk or cream based, though all sorts of other foods like mashed potatoes were also tried. Presumably the latter was for direct delivery to the stomach, not through a nasal tube. In the early 20th century, significant progress was made in understanding human dietary requirements, especially with respect to protein (amino acid) composition. However, the liquid foods were difficult to keep free of contamination and were labor-intensive to make. Food for astronauts A breakthrough was made with the development of special foods for the space program. A lot of research was carried out into creating condensed diets which had just the right composition, with no side effects and minimal fecal output. They had exactly the right mix of essential amino acids, glucose, vitamins and minerals and also had a high nutrient density, were highly soluble, easily transported, completely digestible and had good storage properties. You would think that they were perfect, but the nutritional scientists who developed them had forgotten one crucial aspect. They tasted dreadful, with a strong bitter flavor. A classic example of forgetting to include the user in the design process. However, in this case, there was also an unexpected benefit. Patients receiving tube feeding don't taste it, because their mouth is bypassed. The specifications of the high-tech food developed for astronauts turned out also to be just what manufactures of tube-feeding needed to have. The food was tried out in a hospital near to where the astronauts' food was developed and it was a success. This was then followed by developments of better tubes and then later of intravenous (parenteral nutrition, PN) systems. In recent years, both intravenous and tube feeding has continued to develop further. Special foods have been developed specifically for various illnesses, such as diabetes, burns or transplants. The healing process can be helped by providing exactly the right balance of nutrients. The importance of dietary fiber (roughage) has been recognized and also the discovery that fibers can be supplied in a completely soluble form. Future innovations in tube feeding With so many developments, you might be forgiven for thinking that tube feeding systems are now perfect. However, there are still aspects that can be improved. To that end, a consortium of partners have started a project called FoodFriend to research a number of specific aspects of the system from Danone (Nutricia). The different partners will investigate different questions. For instance, Noldus is going to develop a system to measure the user experience of tube feeding. PROJECT PARTNER Partner with Noldus If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 30 years of experience Download One of the innovations of tube feeding in recent years, is that it is also possible to use it outside the hospital, in the home environment. That of course has a lot of advantages, fitting with the trend that patients are not kept in hospital any longer than is strictly necessary. However, there are also potential difficulties, including that there are no nurses or technical staff to supervise the use of feeding tube. Just as with the food developed for the astronauts, the user experience is critical for its acceptance. It is, of course, inherently less pleasant that eating normally, so anything that can be done to improve it will help. If the experience of the patients using the system can be properly understood then the system can be optimized for that. That can occur in two ways, either to change the system itself or (if that isn't possible) then to inform the patients better about what to expect, so that they can be well-prepared. Noldus has a lot of experience and expertise in developing systems to measure the user experience, but this use-case has some specific challenges related to the home environment. The conditions are not controlled in terms of lighting and so on, and data security and privacy are even more important than in a laboratory environment. That makes it a great use-case for improving Noldus' measurement systems so that they can work in those conditions. Reference An excellent review of the history of tube feeding can be found here: Chernoff R. (2006). An Overview of Tube Feeding: From Ancient Times to the Future. Nutrition in Clinical Practice 21:408–410. --- ## Depressed with a failing reward system: social stress disrupts brain waves URL: https://noldus.com/blog/depressed-with-failing-reward-system Published: 2019-10-01 13:56:00 Description: Chronic social stress has a huge impact on well-being. Gamma oscillations have been found to be an electrophysiological link between social stress and reward processing. Social interactions and the nucleus accumbens Depression and social rewards In humans, social interactions are extremely important to emotional well-being. Social interactions activate a reward system in the brain, making us feel good. Impairment of this reward system leads to feeling less pleasure from social interactions, and thus to mood disorders like depression. Dr. Ann Mary Iturra-Mena has investigated this system, together with her colleagues from Chile and the United States. Reward system and depression The reward system involves a brain region called the nucleus accumbens (NAc). Among other things, the NAc motivates us to partake in social interactions, which in turn increases brain activity. It seems that during reward processing, it also produces gamma oscillations. Furthermore, there seems to be a link between gamma oscillation alterations and major depression. However, it is not yet known what role those oscillations play in depressed and healthy individuals during social interaction. Gamma oscillations and social stress Social stress severely decreases the activity of the reward system, resulting in anhedonia. In this study, researchers aimed to find out the effect of chronic social defeat stress (CSDS) on gamma oscillations during social interaction. They expected the gamma oscillation to be disrupted during social interaction, and thus they measured brain waves of non-stressed and stressed rats in social situations. Social behavior experiments CSDS exposure For the behavioral component, two groups of rats were tested, one of which was exposed to CSDS while the other was not (control group). CSDS was inflicted by placing the stressed rats in the home cage of a conspecific daily for 7 days, which usually resulted in intruder defeat or subordination. Social preference-avoidance test To test the influence of CSDS on social behavior, the rats were placed in an open field arena containing a transparent, perforated box. The rat was allowed to explore for 2.5 minutes, during which the time spent in the interaction zone was recorded. Then, a novel rat was placed inside the small box, and the experimental rat could explore for an additional 15 minutes. Total interaction time with the novel rat was measured using Noldus EthoVision XT, and heat maps were generated to visualize the areas in which the experimental rats spent most of their time. Stressed rats with interaction times two standard deviations below the mean of the non-stressed group were chosen for further experimentation. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Spontaneous social interaction Using a second open field test, gamma oscillation was measured through brain implants in the rats' NAc. The goal was to test the influence of the social distress on social interactions and on the brain waves. After habituation, the rats were allowed to explore the open arena for 5 minutes (non-social condition). Then, a small transparent cube was introduced as a novel object and subsequently removed after 5 more minutes. Lastly, a second rat was introduced in the arena, and both could interact freely for another 5 minutes (social condition). Noldus EthoVision XT was used to track and analyze the rats' movements. Links between gamma oscillation and social behavior Main results Dr. Iturra-Mena and her team aimed to find an electrophysiological link between social interaction and a reward processing brain region like the NAc. This link now seems to be found, and consists of high-gamma oscillations. In non-stressed rats, these oscillations increased during social interactions. However, stressed rats showed no differences in high gamma between social and non-social interactions. NAc as a switchboard Earlier research suggests that NAc might be a "switchboard", capable of regulating signal exchange and "selecting" a dominant input. This could mean that, when creating high-gamma oscillations in non-stressed rats, other brain regions are synchronized to the NAc, and are thus capable of influencing the rats' behavior as well. Furthermore, it is possible that distress is capable of influencing the connection between NAc and the cortex, resulting in a decrease of gamma power in stressed organisms. This could potentially lead to failure of processing of social behavior input in the NAc. Dopamine and gamma oscillations Normally, it seems, dopamine (DA) in the NAc generates oscillations in gamma frequency during social interactions. Based on this theory, scientists propose that DA levels decrease in stressed rats whenever they interact with an unfamiliar conspecific. This then leads to alterations in their brain which cause a decrease of gamma oscillation in the NAc during social interaction. Other research suggests that social interaction does not cause much DA release towards the NAc in stressed mice compared with non-stressed mice. However, DA concentrations in NAc have not yet been measured during social interaction in stressed rodents, so that puzzle piece is still missing. Conclusion As found in previous research, Iturra-Mena's study suggests that high-gamma oscillations are involved in the rewarding effect caused by a conspecific being present, and socially interacting with it. Furthermore, the oscillations can be disrupted by chronic social stress, resulting in stress-related disorders like anxiety and major depression. References Iturra-Mena, A. M.; Aguilar-Rivera, M.; Arriagada-Solimano, M.; Pérez-Valenzuela, C.; Fuentealba, P. & Dagnino-Subiabre, A. (2019). Impact of stress on gamma oscillations in the rat nucleus accumbens during spontaneous social interaction. Frontiers in behavioral neuroscience, 13, 151. --- ## Working memory and emotion regulation in children with ADHD URL: https://noldus.com/blog/working-memory-emotion-regulation-adhd Published: 2019-09-05 12:15:00 Description: How can we understand emotional reactivity in children with ADHD? In the current study, Tarle and her colleagues examined the relation between emotion regulation and working memory in children with and without this disorder. In the United States alone, around one in fourteen children is diagnosed with attention-deficit hyperactivity disorder (ADHD). ADHD is a complex and lifelong developmental disorder, and is characterized by symptoms of inattention, impulsivity, and hyperactivity. Children with ADHD may have trouble concentrating in school, paying attention to others, thinking things through, or sitting still. Children with ADHD are also at risk for a range of other symptoms, including mood disorders, learning disabilities, and impairments in emotion regulation. ADHD and emotion regulation Emotion regulation is described as the ability to produce and maintain an emotion, and to decrease an emotion's intensity or frequency. It's about the control you have over the emotions you feel and show to others. Research suggests that children with ADHD have more trouble regulating emotions than their typically developing peers. This includes difficulties in recognizing and understanding emotions, heightened emotional reactivity, decreased emotion regulation, and impaired empathy. Neurocognitive development in ADHD Emotion regulation is closely related to the development and refinement of executive functions. Executive functions include abilities like inhibition, planning, and working memory. They are central in controlling your behavior, as well as your emotions. For example, we learn to restrain our emotions to fit social norms, or use our working memory to interpret and react to complex emotional situations. Findings from cognitive research also show that working memory helps with understanding emotions, emotional responding, and distraction from negative moods. Therefore, several theories suggest that emotion regulation difficulties in children with ADHD are caused by underlying neurocognitive deficits. Specifically, researchers argue that inhibition and working memory may be involved. Studying working memory and emotion regulation Earlier research on the relation between emotion regulation and working memory in ADHD shows inconsistent results and may have methodological limitations. For example, the tests used in these studies often target memory skills, while placing low demands on executive processes – in other words, not targeting the 'working' part of working memory. Also, these studies rely mostly on rating scales of emotion regulation. These measures are vulnerable to both rater bias and errors in retrospective recall. They may also be confounded by an overlap in items targeting emotion regulation difficulties and other disorders. Varying demands on working memory To address these limitations, researchers Tarle and her colleagues used an observational design for their study and included a different working memory test. Observing behavior also provided them with another advantage: they could directly measure real-time changes in behavior. By measuring real-time changes in behavior, they were able to examine neurocognitive processes described by dual process theory. Dual process theory suggests that our 'cognitive fuel' is limited and can become depleted when high demands are placed on our working memory. This means that after performing a difficult task, there may not be as much 'fuel' left to regulate emotions. That is why the research team studied children in conditions of high and low demand on working memory, and studied their effects on emotion regulation. They predicted that children with ADHD would not only have more difficulties in emotion regulation than their typically developing peers, but would also respond more strongly to increased demands on working memory. Observing child behavior Tarle and her colleagues included 36 children with ADHD and 32 typically developing children in their study. Children were assigned to these groups following a comprehensive diagnostic procedure. Working memory was measured with a computer test in which a series of shuffled numbers and one letter were presented. Children were instructed to rearrange the numbers from low to high, followed by the letter, and to say this sequence out loud. The test was split into four blocks of varying set-sizes. In the control condition, children could draw or paint anything they wanted for five minutes, using a computer program. Children's behaviors were observed and coded using The Observer XT. Specifically, the researchers were interested in behaviors that showed decreased regulation of emotions. This included self-criticism, emotion ventilation, solicitations with the examiner, positive emotion expression, and more. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Group differences As expected, children with ADHD showed poorer working memory performance compared to their typically developing peers. Overall, they also demonstrated poorer emotion regulation. Specifically, they showed more frequent emotion ventilation and solicitations with the examiner, compared with children from the control group. Children from both groups showed greater emotional expression during the working memory test, compared to the drawing condition. For example, they vented their emotions and shut down more often. These findings are in line with predictions from dual process theory. Most interestingly, results showed significant interaction effects for self-criticism and positive emotion expression. In other words, the effects of increased working memory demands on these emotion regulation behaviors were greater for children with ADHD than for those in the control group. These results are in line with findings from previous research, suggesting that a majority of children with ADHD show greater emotional reactivity than their typically developing peers. Environment Results from the current study show that the relation between working memory and emotion regulation works differently for children with ADHD. These findings have important implications for the treatment of this disorder. For example, by understanding how emotion regulation is influenced in children with ADHD, caretakers can structure their environments more optimally. They might benefit from variations in task, activity level, and social environment, which could help prevent depletions in 'cognitive fuel' and the difficulties in emotion regulation that may follow. Findings from studies like these can also help to advance the development and refinement of diagnostic criteria, and inspire new treatment possibilities. Reference Tarle, S.; Alderson, R.; Arrington, E.; Roberts, D. (2019). Emotion regulation and children with attention-deficit/hyperactivity disorder: the effect of varying phonological working memory demands. Journal of Attention Disorders. DOI: 10.1177/1087054719864636 --- ## Emotional responses to infant crying URL: https://noldus.com/blog/emotional-responses-infant-crying Published: 2019-08-15 12:00:00 Description: Hearing an infant cry can cause negative emotions, which can impact the way we respond. Researchers Riem and Karreman instructed parents to apply specific emotion regulation strategies in response to infant crying. What do you do when an infant cries? Do you try to find out whether the infant is in pain, or needs something from you? Or, do you try to comfort the child or distract him or her, for instance by presenting a toy, making funny noises, or singing a song? Maybe you just want to ignore the crying sounds. Infants cry for many reasons; it is their main form of communication. They want to alert the parent that something is not right and that it needs to be fixed. They search for attention and care. However, crying can also trigger negative emotional reactions in parents, such as feelings of dread, frustration, or worry. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly How to prevent negative emotions Anxiety and aversion can undermine any good intentions that parents have while responding to their infants. Researchers Riem and Karreman, working at Tilburg University in the Netherlands, believe it is important to examine effective strategies that may prevent parents from feeling overwhelmed by negative emotions. The goal is not only to produce a desirable immediate reaction, but also to preserve the long-term relationship between parent and child. Thus, their study focused on instructing parents to apply specific emotion regulation strategies. They wanted to know whether this affected their perception of, and responses to, infant crying. Interested in parent-child interaction research? This free white paper will show you how to facilitate the study, how to set up your experiment, and analyze your data. Emotion regulation strategies One hundred mothers with infants younger than three years old participated in the study. They were visited at home after they had completed an online questionnaire about anxiety, using the Trait Anxiety Inventory (STAI), and depressive symptoms, using the Edinburgh Postnatal Depression Scale. During the visit, the mothers were instructed to listen to an infant cry sound in three different conditions. E-Prime, a stimulus presentation program, was used to present this task to the mothers. In each condition, mothers received different instructions on how to control their emotions during exposure to the crying sound: - 1.Control: "You will hear an infant crying sound. Listen to it." - 2.Suppression: "You will hear an infant crying sound. Listen to it in a matter-of-fact manner. Do not pay attention to your feelings or anything raised by the sound." - 3.Reappraisal: "You will hear an infant crying sound. Listen to it, telling yourself: It is nothing very serious. This baby is not sick or hurt." Responses to infant crying After each cry sound presentation, the mothers' emotional experience was measured with the Positive Affect Negative Affect Scale (PANAS). In addition, the mothers were asked to indicate how sick, aversive, and urgent the cry sounded, and whether they felt irritated during exposure to the cry. Lastly, the mothers were asked to rate the likelihood of using the following behaviors: pick up, cuddle, wait and see, feed, firm handling, and focus on something else than on the crying baby. In addition, skin conductance was measured and facial expressions were analyzed using FaceReader. The researchers only analyzed the emotion 'sad', since the cry sound hardly evoked happy, surprised, disgusted, angry, or scared expressions. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Effect on parent-child interactions The research team found that, compared to the suppression condition, reappraisal resulted in a less negative perception of the crying and a lower skin conductance activity. This reveals reduced arousal at a physiological level. Thus, consciously thinking that nothing serious is happening to the child ensures that mothers are less concerned. Moreover, the suppression and reappraisal conditions had no effect on self-reported negative feelings such as being upset, irritable, or nervous, nor on the mothers' intended caregiving responses to the crying children. This indicates that these strategies did not result in changes in negative moods. Facial expressions and skin conductance levels Suppression resulted in increases in skin conductance activity, as well as facial expressions of sadness, compared to the control condition. This might indicate that this coping strategy is abnormal in cases of infant crying. The researchers suggest that future studies should examine what increased arousal during suppression means in terms of actual caregiving. This study is the first to indicate that simple instructions on how to reframe thoughts about an infant crying sound in a more positive way can change the perception of and reaction to crying. These strategies may help parents gain more emotional control, and lead to more adequate and comforting caregiving responses. Simple but effective! References Riem, M.M.E. & Karreman, A. (2019). Experimental manipulation of emotion regulation changes mothers' physiological and facial expressive responses to infant crying. Infant Behavior and Development, 55, 22-31. DOI: 10.1016/j.infbeh.2019.02.003 --- ## User Meeting: exploring external data integration URL: https://noldus.com/blog/user-meeting-ethovision-external-data Published: 2019-08-13 11:48:00 Description: A few months ago, we organized our very first User Meeting about EthoVision XT and external data integration! The meeting included interesting talks, discussions, and demonstrations with a diverse group of participants. On the 20th of May we had our very first User Meeting about EthoVision XT and external data integration! The meeting was held in the heart of the DACH region (which consists of Germany, Austria, and Switzerland) in Augsburg, Germany. This way, it was accessible for a broad base of neuroscientists. Augsburg Over 2000 years old, Augsburg is one of Germany's oldest cities. It's known for its varied architecture and beautiful medieval buildings. Luckily, we had a chance to see some of the sights! We had lunch at the "Bayerisches Haus am Dom," a restaurant where we were told the abbess and nuns of cloister "Oberschönenfeld" dined as well. The restaurant's location also took us close to the Augsburg Cathedral, a Roman Catholic church founded in the 11th century. The meeting itself took place at the Hotel Augusta, a superior venue with modern conferencing facilities. Multimodal research We organized the User Meeting to connect with other researchers and discuss the possibilities of multimodal research. Specifically, we explored how EthoVision XT could be used to connect different types of data with behavioral measurements. This topic inspired a range of interesting subjects to include in talks, discussions, and workshops. For example, we discussed how EthoVision XT could be combined with PhenoTyper, Inscopix, and Neurolinx. We were happy to get feedback from professionals who integrated electrophysiology data, calcium imaging, audio data, and many more. We also learned about new possibilities with upcoming products for multiple animals video tracking and system integration. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free trial Connect & discuss The meeting attracted a diverse and interested group of people. Participants ranged from students to professors, and included professionals from fields like pharmacology and cell biology. They worked with different animal species, including fish, rodents, pigs, and insects. After the presentations, we started our Atelier Workshop, consisting of different discussion groups and demonstrations. Subjects included physiological data integration, social interaction measurements, synchronization of vocal and behavioral data, and track editing in a three chamber system. Will we see you next time? The User Meeting was very successful and inspired several new topics for the next meeting to be organized. We would like to thank everyone who contributed or participated, and we hope to see you (again) next time! --- ## LIFESTART project URL: https://noldus.com/blog/lifestart Published: 2019-08-01 14:37:00 Description: The importance of good nutrition for human babies is well known. But what about young animals? Every new parent is acutely aware that good nutrition is important for babies and young children. Even before the baby is born that is important. For example, iron deficiency in pregnant mothers can impair cognitive and motor development. Studies from the Dutch 'hunger winter' during the Second World War have shown that if the mother is malnourished, that can lead to obesity in the adult child, and that tendency can even be passed down to the next generation. Even though there is a lot known, that isn't to say that there isn't a lot of uncertainty. Some studies came to the conclusion that ADHD (Attention Deficit Hyperactivity Disorder) is caused by eating too much sugar or foods with certain additives. However, if you have a closer look at the methodology of those studies it is not so clear. The additives used were at unrealistically high doses and perhaps the children ate more sugar because they were more active, not the other way around. More recent studies with double-blind design and a control group didn't reach the same conclusions. The jury seems to be still out on that question. Complex phytobiochemistry One of the reasons that research on this question is so difficult is the enormous complexity of the issue. Not only is our digestive system very complex (for instance, with all sorts of interactions with the immune system, and even behavioral effects) but food itself is complicated. Take for instance Hop (Humulus lupulus, photo below). That is a plant native to much of the world. It is cultivated on a large scale and has been grown for over a thousand years because it is the ingredient which gives beer its bitter flavor. However, it does not just have chemicals which are bitter, but a whole range of other special chemicals with various interesting properties. Already in 1158, the botanist, composer and Abbess Hildegard von Bingen showed that it had antimicrobial properties. Of course, she didn't call it that, but she did prove that it prolonged the shelf life of beer. It was also already known by then that it increased gastric juice volume (without changing its acidity), and has anti-inflammatory properties. Nutrition and behavior Does Hop also have an effect on behavior? Clearly drinking beer does, but what about Hop itself? It has been claimed for centuries that it can have a sedative effect and traditionally has been combined with more powerful herbal medicines such as Valerian to aid sleep. Modern studies have confirmed that idea. Even drinking non-alcoholic beer can have mild sedative effect. But where modern interest has been more stimulated is that it is also full of antioxidants. Free radicals (a sort of toxic reactive chemical which the body naturally produces) can possibly be damaging, and even lead to all sorts of diseases such as cancer and premature aging. This is called oxidative stress. Super foods The idea is that if you eat more antioxidants, this boosts the body's ability to counteract those free radicals, protecting against disease and reducing stress. That idea is strongly promoted by those selling "super foods", but actually there is little scientific evidence for it and the studies are inconclusive. Even less is known about the role of antioxidants in young children. If we don't fully understand all the ins and outs of the relationship between nutrition and healthy growth of children and adults, we know even less about the interaction of different foods on the health and welfare of young animals. Can plants like Hop be used to increase their health and welfare and reduce their stress? The LIFESTART project LIFESTART is a new project which is investigating these questions. The consortium has a diverse and complementary set of partners. Trouw Nutrition is the project leader, and they are primarily interested in the practical application of the knowledge generated. Can they develop innovative high-quality, high-value food supplements from natural sources (like Hop) which will reduce stress and benefit the welfare of young farm animals? Wageningen University will research the effects of nutrients on the intestines of the animals and develop new biomarkers and diagnostic methods to better measure its all-important barrier function. Radboud University Medical Center will develop their rodent models using a new battery of tests to measure the behavior of young pups, enabling deeper insights than when working with slower-growing animals. Noldus will develop new instrumentation for measuring the health, welfare and behaviors of both the young farm animals, and the rodents so that the effects of the nutrition on the animals can be accurately monitored. One of the ways that they will do this will be by integrating with the technology of the final partner, Sorama. They have sound cameras which will be able to pinpoint the vocalizations of the animals, so allowing quantification of their individual communication, even when many animals are together. Once the project gets going, the main results will be published here. Reference For a fascinating review paper all about the phytobiochemistry and more of Hop, see Karabín, M., Hudcová, T., Jelínek, L. and Dostálek, P. (2016), Biologically Active Compounds from Hops and Prospects for Their Use. Comprehensive reviews in food science and food safety, 15: 542-567. doi:10.1111/1541-4337.12201. --- ## Is a unique calcium regulating mechanism a cause of Gulf War Illness? URL: https://noldus.com/blog/calcium-regulating-mechanism-gulf-war-illness Published: 2019-07-25 08:52:00 Description: Gulf War Illness (GWI) is potentially caused by organophosphate exposure. Through behavioral experiments, using a DFP rat model, researchers tested levetiracetam as a potential cure. Many soldiers that fought in the First Gulf War suffer from a disorder popularly known as the Gulf War Illness (GWI). It especially affects the nervous system, and often causes anxiety, depression, mood disorder and cognitive deficits, amongst other symptoms. Gulf war illness and organophosphates A possible cause is the chronic exposure to organophosphate (OP) compounds. Scientists from the Virginia Commonwealth University researched potential cures. Calcium dynamics in GWI It is already known that Ca2+ signals in many neurodegenerative disorders (e.g., acquired epilepsy, Parkinson's disease, and traumatic brain injury) are disrupted. These signals are regulated by many different processes and can influence mood, memory, and behavior. GWI showed various similarities with those disorders, and more specifically, an elevated level of Ca2+. The GWI rat model The typical GWI symptoms are mimicked in various GWI rodent models. This study examined a diisopropyl fluorphosphate (DFP) model. DFP is an OP compound, and causes symptoms that are similar to GWI. The development of the DFP rodent model combined with the discovery of Ca2+ elevation in GWI led scientists to investigate if Ca2+ inhibitors could improve the disorder's symptoms. Testing the effects of levetiracetam therapy Mimicking GWI with DFP solution For 5 days, rats were injected with DFP solution daily in order to mimic the GWI symptoms. Three months later, various analyses were carried out, including behavioral experiments. Furthermore, a portion of the rats received levetiracetam (LEV) injections, a medicine for treating epilepsy. Pleasure-seeking behavior Scientists carried out a pleasure-seeking (hedonia) test by offering rats both sucrose water and plain water. Following a period of acclimation and food deprivation, for one hour each rat was given access to two water bottles, one containing plain water and one sucrose water. They found that DFP rats drank less sucrose water than both LEV-treated DFP rats and control rats. Between the latter two, no significant differences were found, which suggests that LEV can improve anhedonia. Behavioral despair Through a forced swim test, behavioral despair was tested. Rats were put into a water tank, and for 6 minutes, their behavior was noted. They distinguished between active (diving, climbing, and swimming) and passive behavior (immobility). DFP rats were passive for at least twice as long as control rats, and LEV therapy improved this, but not to the level of control rats. This indicates that LEV could potentially be used as an antidepressant. Anxiety test Anxiety was tested using an elevated plus maze. Normally, rats prefer dark and enclosed spaces. The maze therefore had two arms with walls and two without. Rats were put in the centre of the maze, facing an open arm. For 5 minutes, they were filmed by an overhead camera, and behavioral data was automatically collected using Noldus Ethovision XT. Both control rats and LEV-treated DFP rats spent significantly more time in the open arms than untreated DFP rats, which indicates an anti-anxiety effect of LEV. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Memory deficits To test memory deficits, rats underwent a novel object recognition test. They were habituated to an open field arena, after which 2 identical objects were placed inside. For 3 minutes, the rats were allowed to explore both of them. After an hour, one of the objects was replaced with a novel one, and the animals could explore for 2 additional minutes. The tests were filmed from above, and behavioral data (exploring the new object) was automatically collected using Noldus Ethovision XT. DFP rats spent no more time with the novel object than with the familiar object, indicating memory deficits. LEV helped, but could not completely restore their behavior to control values. Heightened [Ca2+]i and Ca2+ regulating mechanisms From the rats' brains, the [Ca2+]i was measured, and they found chronically elevated [Ca2+]i in DFP rats compared to control rats. Furthermore, they found that the ryanodine receptor stabilizing protein Calstabin2 (a Ca2+ regulation mechanism) was less expressed in DFP rats, and that its antagonist decreased elevated [Ca2+]i. LEV therapy significantly reduced [Ca2+]i, but did not lower it to control levels, which indicates that additional mechanisms are involved. If you want to find out how they did these tests, read more in the article cited below. Potential cause and cure for GWI In this study, researchers discovered that Calstabin2 levels were reduced in DFP rats, and that its antagonist decreased heightened [Ca2+]i. This mechanism might be a main source of the Ca2+ dysregulation in the DFP rats. Furthermore, LEV therapy improved GWI symptoms and also decreased [Ca2+]i. However, LEV was not able to completely restore the DFP behaviors to normal. It is not certain yet if LEV therapy can reverse the underlying molecular changes causing increased [Ca2+]i in DFP rats. It is likely that more mechanisms are involved in influencing [Ca2+]i levels, because LEV alone was not able to restore behaviors back to baseline completely. However, LEV still could be a potential treatment to improve GWI symptoms. Reference Phillips, K. F., Santos, E., Blair, R. E. & Deshpande, L. S. (2019). Targeting Intracellular Calcium Stores Alleviates Neurological Morbidities in a DFP-Based Rat Model of Gulf War Illness. Toxicological sciences, 169(2), 567-578. --- ## 3 reasons to join us at Applied Human Factors & Ergonomics meeting (DriveLab) URL: https://noldus.com/blog/ahfe-meeting Published: 2019-07-23 10:42:00 Description: The International Conference on Applied Human Factors and Ergonomics (AHFE) is held annually. Here is why you should attend. Every year the International Conference on Applied Human Factors and Ergonomics is organized in the United States. It is always great to use the summer season to meet other researchers, walk along the poster boards, discuss and exchange ideas about new applications, and view the latest tools and solutions for human factors research. AHFE facilitates it all: keynote presentation, parallel sessions, demonstration and poster sessions, tutorials, exhibitions, and meetings of special interest groups. 3 reasons to join us at the AHFE meeting this year Here is why you should attend the International Conference on Applied Human Factors and Ergonomics: 1) Get the trends AHFE is the place for exhibitors to present their latest, state-of-the-art ergonomics products, systems and services for users, professionals, and researchers in the AHFE field. If you attend the conference you will be joining some 1,500 fellow researchers and professionals. The ideal set-up for meeting peers, discussing the latest trends, and discovering the best tools and techniques in your field. The conference objective is to provide an international forum for the dissemination and exchange of scientific information on theoretical, generic, and applied areas of human factors and ergonomics. With a Keynote Address by Prof. Peter A. Hancock (University of Central Florida, USA) called "In The Future Will There Be Humans to Factor In?" there will be a stern look at the future too. 2) We're showing DriveLab DriveLab is a powerful tool that helps researchers understand driver behavior and the influence of support systems on behavior and performance. It furthermore helps vehicle and electronics developers in testing how their products are being used and what the effect of these products will be on driving behavior, providing them with valuable information for further improving their designs. Check out this research solution developed by Noldus in collaboration with our partners Green Dino, Smart Eye, Delft University of Technology, TNO, TomTom, and HAN University of Applied Sciences. 3) Turn-key solutions for your (applied) human factors research Noldus Information Technology develops innovative solutions for behavioral research: from software packages and lab equipment to fully integrated human factors and observation labs, including training and support. With 30 years of experience we translate your questions into practical and proven solutions. Our turn-key observation labs come complete with Viso, FaceReader, The Observer XT, eye trackers, and data acquisition systems. Will we meet you there? HUMAN FACTORS Discover our solutions for human factors research Explore our integrated solutions for observation labs, behavioral coding, and human factors research. Learn more --- ## Understanding consumer buying behavior URL: https://noldus.com/blog/understanding-consumer-buying-behavior Published: 2019-07-11 12:00:00 Description: What predicts a sale, and what causes consumers to buy from a particular brand over another? To know how and why customers make decisions, you can take a deeper look at consumer behavior. In order to win over the hearts and minds of consumers, businesses need to know how and why their customers make decisions. What predicts a sale, and what causes consumers to buy from a particular brand over another? Additionally, how do consumers make positive associations with products, and what factors go into creating the best shopping experience possible? You can get answers to all these questions by taking a deeper look at consumer behavior, or the study of how emotions, attitudes, and preferences affect buying behavior. The benefits of unobtrusive observation Traditionally, researchers often used questionnaires to gauge consumer attitudes and preference. However, questionnaires are unable to provide an unbiased response, as consumers might feel pressured to provide socially desirable answers. It is generally in our nature to try to please the people we are talking to, so subjects who answer questionnaires often subconsciously give answers they think will be pleasing. Furthermore, paper and pencil measures such as questionnaires are often less accurate, require some sort of data entry in order to log results, and can be seen as intrusive to consumer privacy. To remedy this, companies are increasingly shifting towards using measurements that can provide an unbiased view of consumer buying behavior. Case Study: The Restaurant of the Future One way to do this is to actually record behaviors on video. To get a better understanding of the role that situational factors play in food choice, the 'Restaurant of the Future' in Wageningen, The Netherlands, observed restaurant visitors in conditioned situations for prolonged periods. When it opened in 2007, it used Noldus' The Observer XT behavioral coding software, cameras, PC's, and microphones, to monitor factors like how light, color, sound, and presentation affected consumer behavior. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Though the 'Restaurant of the Future' is no longer running as a research facility, while it was active it functioned like "a living lab". According to NPR's interview with Rene Koster, co-founder and manager of the restaurant, "Every day we could have a project ongoing. And the people that come here are not aware if there's a project ongoing or not, basically because they don't see it. On one hand, it's a normal restaurant run by professionals where people come and have an enjoyable meal and there could be research ongoing, but you don't feel it, you don't smell it, you don't taste it." By filming consumers in a controlled, yet naturalistic environment, you can discover insights into the motivational drivers of their behavior. Want to learn more? Check out this Webinar If you're interested in learning more about unobtrusive information, click here to download a PDF of Noldus' webinar hosted by L&E, "The What, When, Why & How of Unobtrusive Observation." Analyzing consumer movement The 'Restaurant of the Future' is not alone in its research. To get a better idea of its consumer movement, Jan Linders supermarket teamed up with Noldus to answer this question: Do customers predominantly walk the same (common) route, and is it possible to change this most commonly followed route by changing the layout of the supermarket and/or the placement of certain products? Case Study: Jan Linders To do this, Jan Linders used TrackLab, a tracking technology that lets you import accurate and reliable tracking data offline or in real-time. With TrackLab, it is possible to monitor specific zones for activity and design algorithms to detect and classify key behaviors. Once specific zones of interests were defined within the supermarket, TrackLab sensors were installed, and customers were tracked for two weeks. Tracking was voluntary, and 4,500 people agreed to wear an ultra wideband tag during their normal shopping routines. Based on the data acquired, Jan Linders was able to pinpoint the most commonly walked routes, as well as customer "hot spots" and "cold spots" using heat maps. As a result, changes were implemented to successfully direct customers towards specific areas and influence the products they buy. FREE DEMO Try TrackLab yourself! Request a demo to obtain real-time insights into a wide range of spatial behaviors. - Accurate tracking data - Gain insights into consumer behavior - Easily access, export, and analyze data Free Demo Using eye tracking in attention based studies Another way to track the movement of consumers in stores is by using eye tracking. Both marketers and research teams use this technology to better understand consumer buying behavior. Our Noldus partner, Tobii Pro, supplies eye trackers that can help capture shoppers' habitual and subconscious behavior naturally and without bias. By using wearable eye trackers on study participants, researchers can reveal what truly attracts attention and can better understand the entire shopper experience. Photo ©Tobii AB In an email communication with Small Business Trends, Mike Bartels, senior research director at Tobii Pro, stated, "The researchers are able to watch a live feed of each consumer's attention in real-time and through subsequent data analysis answer a number of critical questions about their customers." Case Study: FDA For example, a recent study conducted by eye tracking research consultancy Tobii Pro Insight on the behalf of the Food and Drug Administration (FDA) studied the attention being paid to nutritional labeling in the grocery store aisle. According to the Progressive Grocer, the study revealed that customers spend the majority of their time looking at branding and product imagery. As a result, the FDA concluded there is room for improvement in conveying nutritional information to consumers. Eye tracking in advertising Eye tracking is also helpful to determine how advertising is reaching its audience. With so many consumers actively tuning out or unconsciously ignoring ads, researchers are trying to get a better idea of how to make campaigns more effective. According to a study by InSkin Media, Research Now, and Sticky, eye tracking revealed that an online ad must be on the screen for 14 seconds to have any chance of being viewed. The study also uncovered other valuable insights such as how gaze time differs by ad format and how clutter affects ad recall. Gauging consumer emotion Measuring consumer emotions is another way in which you can make an effort to improve customer experience. A big part of deciding to buy something comes from emotions on both the conscious and subconscious level. Moreover, when it comes to customer buying behavior, being able to read into these reactions is key. For example – if you are able to get feedback on your products or services through obvious positive or negative sentiments, you can get a better idea of how to improve your investments, please your customers, and improve your ROI. Case Study: Instituto Universitário de Lisboa, Portugal A number of factors can influence brand loyalty, but one of them is most assuredly emotion. Researchers José Chavaglia Neto and José António Filipe set out to test this by measuring consumer facial expressions as a way to look into the value of advertisements. During their study, they used a commercial related to Apple to see if they could derive any insights that might improve the brand's marketing communication strategy. Using FaceReader, they were able to pinpoint specific moments of interests that stood out on emotion curves. By mapping consumer emotions, not only can you get a better look at responses to your marketing material – you can understand key drivers of emotion and how to better incorporate them into your brand. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Analyzing autonomic responses and facial expressions Facial expressions alone can be powerful insight tools, but when you add physiological analysis to the mix it gets even better! To gain a deeper understanding of how to recognize fullness, Wei Hei and researchers from Wageningen University and the University of Geneva measured sensory-specific satiety by analyzing autonomic nervous system responses and facial expressions. By doing these types of tests, they hoped to see how novel behavioral research testing could provide value for consumer behavior studies in the future. The food was separated into three groups: 1) same food, 2) similar uneaten foods, and 3) different uneaten foods. Four test foods were chosen (two sweet, two savory) and given to 24 female participants. While they ate, they faced a camera for optimal analysis via Noldus FaceReader software and were hooked up to Mindware Technologies BioLab physiological response acquisition software. After the researchers analyzed the facial expression results offline, they then imported it into The Observer XT to synchronize both sets of data. The influence of anticipation This gave them the ability to position all acquired data in one timeline, and the results of the study were interesting. While participants ate their food, they had an increase in heart rate, reduced skin conductance and skin temperature, and an increase in anger and disgust facial expressions. This suggested that in this case, satiety could be a result of a change in emotion as the foods' anticipatory pleasantness decreased. Perhaps anticipation is sometimes better than the real thing! In fact, if you think about it, anticipation has a huge impact on many of our decisions. According to Insights Association, anticipation influences our goals and decisions, and quite a wide variety at that. For example, we might anticipate our competitors' responses when playing a game, an exciting vacation, what foods we should and should not eat, or how someone will respond to a compliment. Looking at it through the lens of business, decision-makers must anticipate future customer needs as well as how customers might react to new initiatives in order to better direct consumer buying behavior towards a favorable outcome. Safeguarding consumer privacy Recently, the troubling issue of consumer privacy (or lack thereof) has been on many people's minds. There are cases where monitoring and trying to anticipate consumer behavior can go too far – while the participants in the Jan Linders study were aware they were being tracked, not all consumers have that benefit. For example, retail analytics technology often comes with privacy trade-offs. According to the Federal Trade Commission (FTC), newer approaches include active and passive monitoring of signals from individuals' personal devices. Active monitoring communicates with cellular providers or WiFi connection, while passive monitoring intercepts signals from devices while they communicate with other devices and networks. While active monitoring typically gives consumers notice of their tracking approach, not all retailers adhere to this standard. As for passive monitoring, many techniques typically operate under an opt-out method. Suggestions for privacy best practices So, what can businesses do to safeguard consumer privacy? In a 2012 report, the FTC focused on three broad principles. The first, privacy by design, encourages companies to build in privacy at every stage of product development. Second, businesses and consumers should have a simplified choice and be able to make decisions about their data at a relevant time and context. Third, all businesses should have greater transparency and make information and use practices clear. The Noldus mission Noldus' mission is to facilitate data exchange and insights discovery, allowing you to make results rapidly and easily available, anytime and anywhere, while safeguarding privacy and security. By listening to our stakeholders and sharing our knowledge, we are inspired by scientific and societal challenges and strive to respond to the demands of today and prepare for those of tomorrow. For more details, please check out our privacy policy. References - Consumer behaviour - Wikipedia - NPR - Restaurant of the Future - Small Business Trends - Eye tracking shopper behavior - Progressive Grocer - Eye tracking consumer insights - Sticky - Online ads viewability study - Insights Association - Power of anticipation - FTC - Privacy trade-offs in retail tracking - Insights Association - FTC data privacy report --- ## Gut microbes: both cause and cure of autism? URL: https://noldus.com/blog/gut-microbes-cause-cure-autism Published: 2019-07-04 15:12:00 Description: Gut microbes can increase or decrease typical autism spectrum disorder behavior (stereotypies, social behavior, locomotion, and communication) via metabolites and influencing alternative gene splicing. Gut microbes can increase or decrease typical autism spectrum disorder behavior (stereotypies, social behavior, locomotion, and communication) via metabolites and influencing alternative gene splicing. Many people in the world suffer from autism spectrum disorder (ASD). In order to help improve their lives, scientists from Israel and all over the USA explored potential causes of ASD through behavioral research. Previous studies already have already shown potential influences of gut bacterial communities. The goal of the present paper was to find out if and how much those communities can influence ASD-like behaviors. What is ASD? The most prominent symptoms of ASD are altered social behaviors and communication and repetitive, stereotyped behaviors. Previous research, mainly focused on the genetics of ASD, has already shown that both gut microbiota and various genetic mutations can potentially influence these symptoms. Microbiota influence ASD Gut bacterial communities in individuals with ASD are different from the ones in typically developing (TD) individuals. Various types of microbial-based treatments can improve ASD symptoms, which is probably caused by their capacity to change the diversity and availability of microbial metabolites. Behavior and gut analyses Various typical ASD behaviors were tested, i.e., stereotypies and decreased locomotion, social behavior, and communication. They did a marble burying test for stereotypies, various other behavioral tests, and a vocalization experiment. Furthermore, they identified microbiota and metabolites to see if they differ between treatment groups and have any potential behavioral effects. Transplanting human gut microbiota into germ-free mice Solutions of fecal samples from ASD and TD donors were used to colonize germ-free (GF) mice, after which they were allowed to rest for three weeks. Then, they were mated according to donor, and after weaning their pups were housed in small, same-sex groups. Behavioral experiments At six weeks old, a set of behavioral tests was carried out as described below. Mice could rest between tests, and were acclimated to the test room overnight in order to help reduce stress. Locomotion Mice were allowed to explore a 50x50 cm open field arena for 10 minutes. An overhead camera recorded the tests, and the videos were analyzed using Noldus EthoVision XT version 10. The program automatically recorded time spent and number of entries in the center square and total distance traveled. Compared to TD mice, ASD mice showed a decrease in locomotion. Stereotypies Stereotypies were investigated with a marble burying test. For 10 minutes, mice were allowed to habituate to a cage. Then, the bedding was leveled and 20 (4x5) glass marbles were put on top. After 10 more minutes, the number of buried (≥50% covered) marbles was counted. Stereotypies had increased in ASD individuals compared to TD. Social behavior Mice were habituated for 10 minutes to a 60x40 cm open box, divided with clear plexiglass into three equally sized areas. Next, they were put into the center area, while a second area contained a cage with a sex-matched stimulus mouse (the social area). The third area was the non-social area. Again, for 10 minutes, the mice were free to walk between areas. In order to record the time mice spent in each area, videos of the test were analyzed using Noldus EthoVision XT version 10. In another test, mice were put in a fresh cage for 10 minutes. During the latter 5 minutes, they scored grooming behavior, after which they introduced a stimulus mouse into the cage for 6 additional minutes. Videos of the tests were scored for grooming behavior, aggression, and social approach. In both tests, ASD mice showed a decreased sociability compared to TD mice. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Communication Male mice were exposed to a new female daily for three days. Subsequently, they were allowed to habituate to an empty cage containing a drop of fresh female urine for 10 minutes. After removal of the urine, a novel female was introduced to the males' cage. For 3 additional minutes, vocalization counts and total vocalization were recorded. A decrease in communication of ASD mice compared to TD was found. Genetic analyses In addition to the behavioral results, RNA analysis also showed events typical for ASD brains, including alternative splicing of risk genes. Furthermore, DNA from the microbes differed between TD and ASD mice. It was also found that concentrations of certain metabolites (i.e., taurine and 5-aminovaleric acid) were lower in ASD mice, and further behavioral tests showed that higher concentrations can protect from ASD-like behavior. If you would like to learn more about this part of the research, please take a look at the original article (citation below). Linking gut microbes and ASD This study found that gut microbiota are indeed a probable cause for autism. However, this does not conclude that microbiota are the cause, because other factors like genetics may also play a part. It is suggested that certain microbiota and metabolites can affect alternative splicing in mice brains, thus influencing behavior. Furthermore, amino acid (e.g., taurine and 5AV) metabolism was impaired in ASD individuals. Both metabolites can decrease typical ASD-like behaviors, i.e., social limitations and stereotypies. These results suggest that, in the context of ASD modeling in mice, microbial metabolites can regulate communication between the brain and gut. Genome editing is not yet possible, but the development of fecal microbiota transplantation, probiotics, or metabolites might help with the lifelong challenges of ASD. References Sharon, G., Cruz, N. J., Kang, D. W., Gandal, M. J., Wang, B., Kim, Y. M., ... & Bramer, L. M. (2019). Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice. Cell, 177(6), 1600-1618. --- ## Studying posture development in infants at risk for autism URL: https://noldus.com/blog/posture-development-infants-autism Published: 2019-07-01 13:14:00 Description: Research shows that early posture development is delayed in infants who are eventually diagnosed with an autism spectrum disorder (ASD). Understanding these delays helps to improve early diagnosis and intervention. In the first year and a half of life, infants reach many milestones in motor development. At first, they need full support from a surface and are only able to lie down. However, as they gain greater strength and balance, infants develop postures that are more challenging, like sitting and standing. With new postures come new possibilities to interact with caregivers, objects, and one's own body. For example, when infants develop from lying to sitting positions, their reach and field of vision expand. This promotes exploration, eye-hand coordination, and even early communication skills such as joint attention. In other words, posture development does not just indicate advanced motor control, but stimulates other forms of development as well. Early development in autism Research shows that early posture development is delayed in infants who are eventually diagnosed with an autism spectrum disorder (ASD). Understanding these (sometimes subtle) differences in development is vital in improving early identification of ASD. However, these studies rely mostly on retrospective observations from available footage. This limits both sample size and experimental control. To advance this field of study, research has recently expanded to prospective observations of infants who are at heightened biological risk for ASD. Specifically, this concerns infants who have an older sibling with a disorder in this spectrum. Children from this high-risk group are diagnosed with ASD more often than children from the general population. Even when these infants are not eventually diagnosed with ASD, growing evidence suggests that they are still at risk for developmental delays or subclinical symptoms of ASD. Observing posture In the current study, researchers examined posture development in infants with a high (HR) or low risk (LR) of developing ASD. All children were assessed at six, eight, 10, 12, and 14 months. The HR group consisted of infants who eventually got a diagnosis of ASD (N=14), delayed language development (N=17), or no diagnosis at all (N=28). The LR group consisted of 25 typically developing infants. Infants were observed at home during the families' normal activities and during a time period of free play with their favorite toys. Infant postures were classified as lying, (un)supported sitting, leaning on all-fours, or (un)supported standing. For supported sitting and standing positions, coders also observed whether these positions were sustained by a caregiver or by the infant itself. The durations of all infant postures were coded with The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Differences in posture development Results showed that ASD infants from the HR group developed differently compared to all other groups. Generally, infants from this group were slower in developing from less advanced to more challenging postures. These differences were most pronounced when studying all-four posture. Not only did the HR-ASD infants consistently spend less time in this posture than their peers, but they also exhibited a distinctive pattern of developmental change. Furthermore, infants from the HR group who were later diagnosed with ASD or language delays showed a slower progression in the development of unsupported sitting and standing. Lastly, researchers found that HR-ASD infants spent more time in sitting and standing postures that were sustained by a caregiver, compared to all other groups. Clinical implications Findings from this study indicate that infants with ASD, and to a lesser extent those with language delays, exhibit unique developmental paths compared to their peers. Furthermore, they suggest that studying posture may also differentiate between children who will receive a diagnosis of ASD and those who will be diagnosed with language delays. Knowledge from studies like these can be used to improve early identification of developmental disorders. Targeted interventions As was described in the beginning of this blog post, posture development can also influence other areas of development, such as exploration and communication. As a result, disruptions in early postural development may be especially far-reaching for infants with ASD, who are already vulnerable to developmental delays and social-cognitive difficulties. Therefore, the researchers from this study recommend incorporating interventions for infant posture development in current treatments for ASD. Transforming infants' earliest experiences in this area may stimulate other areas of their development as well, improving overall care for children with ASD and other developmental disorders. References Leezenbaum, N.B.; Iverson, J.M. (2019). Trajectories of posture development in infants with and without familial risk for autism spectrum disorder. Journal of Autism and Developmental Disorders, doi: 10.1007/s10803-019-04048-3 --- ## Stereotypical effects on cognitive bias URL: https://noldus.com/blog/stereotypical-effect-cognitive-bias Published: 2019-06-21 15:25:00 Description: Stressed-induced stereotypical behavior in lab mice have different effects on cognition. The radial arm maze is often used to investigate this. Scientists have found out that different stress-induced stereotypical behavior in laboratory mice have different effects on cognitive processes. On top of that, genetic strains play a role in whether or not the stereotypical behavior influences cognitive bias. This gives us a new view on animal welfare. Have you ever found yourself looking for your car in a parking lot, where all spots are identical? You first try to go in the direction of the place where you think your car is placed, and then you find yourself walking around various lanes. This is a standard example of making an appeal on your reference memory and working memory. Working memory & reference memory Your reference memory is the knowledge required for a certain situation that remains constant over time. In this case, it would be the location of your car. If you are going to park repeatedly in the same spot, you are likely to remember the location. Your working memory is the ability to manipulate or use the memories being held. In this case, this would refer to the places you visit before finding your car. It would be logical that when looking around, you wouldn't go to the same lane twice, as you had already looked there. So, through constantly looking around in new places for your car, you ultimately will find it. Both working and reference memory are part of cognitive bias. Radial arm maze A way to measure working memory and reference memory in laboratory animals is by using a radial arm maze. In this maze, eight arms are connected with each other through a center place. At the end of some of these arms, a positive stimulus is located, normally in the form of food. By observing which arms the animal investigates before all food is eaten, the working memory and reference memory can be evaluated. Varying the positions of the food can give multiple approaches to behavioral tests. Through the usage of EthoVision XT video tracking software, the path of the laboratory animals can be analyzed, evaluating both working and reference memory. Stereotypy vs genetics Novak et al, from the University of Bern, also used a radial arm maze in their research. These scientists investigated the effect of stereotypical behavior and genetics on the working and reference memory of mice. Stereotypical behavior is the display of a repetitive behavior without a clear cause or goal. It is often seen in zoo and farm animals, and is known to be a display of severe stress. The researchers here investigated cage-induced stereotypies in two genetic strains of mice. The stereotypies here were found to be chewing on the bars (bar mouthing), spinning around the longitudinal body axis (cage top twirling), back-flipping, running around the cage in circles (circling), and moving along the same route on the cage lid (route tracing on the cage lid). They found that in one of the genetic strains, mice with higher stereotypy levels displayed a negative cognitive bias, which was influenced by the form of stereotypy performed. In this strain, negative cognitive bias was evident in back-flipping mice, but there was no effect in mice that were bar-mouthing or cage-top twirling. However, for the other strain, there was no correlation between the type of stereotypy and cognitive bias. This research shows that similar stereotypical behavior can depend on the genetics of an individual to eventually have influence on cognitive bias. This illustrates that welfare is received differently by different genetic strains within a species. It also supports the idea that different forms of stereotypy should be considered separately in studies about their relationship with brain function, affective state, or other measures of animal welfare. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial References Novak, J., Bailoo, J. D., Melotti, L., & Würbel, H. (2016). Effect of cage-induced stereotypies on measures of affective state and recurrent perseveration in CD-1 and C57BL/6 mice. PloS one, 11(5), e0153203. --- ## How to assess medical team effectiveness URL: https://noldus.com/blog/how-assess-medical-team-effectiveness Published: 2019-06-20 13:07:00 Description: Healthcare professionals working in an operating or emergency room, frequently deal with unpredictable situations in which they need to stay focused and think clearly. How do they manage that? Everyone knows that it is hard to stay focused and think clearly when you are in a very stressful situation. However, when that situation is all about saving someone's life, that is exactly what you need to do: stay focused and think clearly. Healthcare professionals, particularly in the operating or emergency room, deal with this all the time. In unpredictable situations, they need to carry out complex medical procedures. Then, effective teamwork is of the utmost importance. This means there must be effective communication, coordination of activities, clarity on decision making, and managing of errors. These aspects will all influence the outcome of the crisis. Multiple data streams can be used to measure team effectiveness The performance and effectiveness of teams has been the focus of many researchers. On our Behavioral Research Blog, we already mentioned a few studies. In this blog post, the spotlight is on the study of Hoogeboom and colleagues from the University of Twente, The Netherlands, which was performed in a medical simulation room for advanced life support (ALS) training. ALS is a complex emergency situation following the cardiac arrest of a patient, and is characterized by "extreme time pressures, diagnostic uncertainty, and rapidly evolving situations." [1] In their study, the researchers combined different research methods: - Video observation: to systematically analyze the content of team interaction behaviors - Innovative sensor technologies: to explore the structure of team interaction processes in more detail and identify moments of high arousal - Surveys: to assess team effectiveness The study sets out to uncover what the added value, pitfalls, and hurdles are when using and combining different sensor technologies with additional measures in order to better understand team interactions. They claim that outcomes of their research will help optimize simulation-based team trainings, and thus improve the medical and interactions skills of healthcare professionals. What's the big picture? Twenty-one teams, consisting of four first-year master's students, participated. During the ALS course, students learned to diagnose and manage a patient with cardiac arrest and perform cardiopulmonary resuscitation (CPR) on an advanced human-patient simulator [2]. All four students of each team were randomly assigned to these fixed team roles: - Team leader - responsible for task distribution, monitoring team performance, creating an overview of the situation, and patient handover at the end of the scenario - Medication nurse - responsible for drug administrations and connecting devices to the patient - Two CPR administrators - responsible for chest compressions and airway management They all wore a sociometric badge, which is a wearable device that measures proximity, body movement and speech features. In addition, a wristband was placed on the wrist of the team leader's non-dominant hand to help record skin conductance responses and consequently detect the moments of high arousal. In the context of medical simulations, higher levels of arousal may arise when time pressure forces an ALS team member to act quickly. The content of the team interactions was coded with The Observer XT. Behaviors such as giving a command, summarizing, confirming, and asking questions were collected by the team leader. The remaining three team members were only coded on checking back with the team leader. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Finally, to assess team effectiveness, two teachers scored on four effectiveness items directly after the simulation was finished: "This team is a consistently well performing team," "This team is effective," "This team makes few mistakes," and "This team delivers high quality work." As a result, the teams were categorized as 'more' or 'less' effective. Team interaction during stressful moments Regarding the content of the team interaction, the results showed that in the beginning of the scenario, the team leader expressed many commands. However, at the end of the scenario, when teams had to reach a diagnosis and handover the patient, there was more communication back and forth. Moreover, in the more effective teams, one person was more dominant in terms of speaking time, while in less effective teams the team members contributed more equally. On average, more effective teams were less imbalanced during moments of high arousal. During those moments of high arousal, team leaders mostly gave commands and asked less often for confirmation or opinions. They also made fewer suggestions. Stay focused and think clearly It is crucial for an ALS team to be well organized so that individual skills can be deployed efficiently and effectively. Therefore, understanding team interactions is key. The authors conclude in their article: "This and future studies might enable future medical professionals to better understand what is required at stressful moments. Using these results in training and during debriefing sessions can potentially optimize team interactions of future medical professionals and enhance the quality of medical care." References - 1.Doumouras, A. G., Keshet, I., Nathens, A. B., Ahmed, N., & Hicks, C. M. (2012). A crisis of faith? A review of simulation in teaching team-based, crisis management skills to surgical trainees. Journal of Surgical Education, 69 (3), 274-281. https://doi.org/10.1016/j.jsurg.2011.11.004 - 2.Endedijk, M.; Hoogeboom, M.; Groenier, M.; Laat, S. de & Sas, J. van (2018). Using sensor technology to capture the structure and content of team interactions in medical emergency teams during stressful moments. Frontline Learning Research, 6 (3), 123-147. https://doi.org/10.14786/flr.v6i3.353 --- ## Cognitive neuroscience: the basics URL: https://noldus.com/blog/cognitive-neuroscience-basics Published: 2019-06-17 14:17:00 Description: What is cognitive neuroscience? As my professor once said, it is the overlapping science of the ‘dry and the wet’ part of the brain. What is cognitive neuroscience? As my professor once said, it is the overlapping science of the 'dry and the wet' part of the brain: where dry stands for the cognitive part, or the study of the mind, emotions, and senses, and where wet stands for the slippery organ consisting of different lobes that is called the brain. This combination of different scientific disciplines tries to explain the connection between neural activities in the brain and mental processes, in order to find answers to the questions of how neural circuits in the brain affect cognition. Cognitive neuroscience: the basics This blog series addresses the interplay between the brain, behavior, and emotions, in the field of cognitive neuroscience. This blog post addresses the first subject: the brain. Functional specialization: Phineas Gage The frontal lobes are engaged in almost all aspects of human cognitive function. However, what happens when you damage a part of the frontal lobe? You may have heard the story of Phineas Gage, who got an iron bar shot into his skull and frontal brain. He survived this accident, but did not recover as the 'old Phineas.' Although he was still able to work, as his intellect and memory were intact, he became repulsive in his behavior. According to Harlow, who treated Gage, he became impatient, irreverent, and gross. He became very rude and started drinking too much. His consciousness was impaired; he did not know that his behavior was socially impulsive. The case of Phineas Gage is often seen as the start of the modern cognitive neuroscience, as it shows that different parts of the brain do different things, and that damage to a specific part of the brain can result in specific impairments. This key principle is called functional specialization. The damaged part of Phineas' brain was in the orbitofrontal cortex, which gives context to our emotional drives. As a result, he no longer got the bad feeling you get when you do something bad or unwanted, which helps to explain the change in his behavior. Triune brain Let's dig deeper into the brain itself, more specifically: the triune brain. As proposed by the neuroscientist MacLean, our brain consists of three layers. The eldest part, the reptilian brain, is responsible for our instincts. It basically keeps us alive. The second layer is the mammalian brain, a limbic system that senses danger, makes us have emotions, and makes sure we go looking for food. The final layer is what makes us human – the neocortex, or neomammalian brain. It contains our cognitive, linguistic, motor, sensory, and social abilities. The key principle is that these layers are hierarchical. This is a good thing, because this is the reason why we are not conscious of most of the things the brain is doing. Could you imagine having to think about taking a breath or beating your heart? Gladly, we don't have to! The lower centers, the brain stem and limbic systems, are doing many things underneath your consciousness. Again, the main goal is to keep you alive. Your cortex is solely notified when you need to take action. How to measure brain activities The brain is activated when we are engaged in solving a task, thinking, speaking, etc. Brain evidence can help resolve issues that psychologists have wrestled with for a long time. How can we measure brain activities? Unfortunately, no device is yet able to record both spatial and temporal resolution at the same time. If you would like to measure where in the brain something is happening, fMRI and PET systems show high spatial resolution. These systems show increases or decreases in the BOLD (blood oxygenation level) signals, indicating that the brain is more active in some regions than others. If you would rather know when something is happening in the brain, you could consider using EEG or MEG. For example, EEG uses electrodes to detect brain waves, indicating direct activity of the brain. Which method you use is dependent on the type of research you perform. Neuromarketing research Researchers typically combine brain and behavioral observations. They can present visual images on a screen and have the subject read aloud, while looking at their brain activity. For example, in neuromarketing research, the subject could be watching an ad or commercial while their brain activity is measured. This will give marketers insights into the effectiveness of their commercial. REQUEST INFORMATION Are you interested in our behavioral research solutions? Get in contact with us and learn how we can help make your project a success. - Worldwide: Always near to you - Make your project a success - Trust our 30 years of experience Contact Studying the brain activities of an injured brain, like this blog post about hemineglect, tells us more about the brain and how dysfunctionalities influence behaviors. The emotional brain The frontal lobes of the brain are engaged in almost all aspects of human cognitive function. Our emotions are strongly coupled with the brain systems underlying human cognitive functions. What brain areas are involved in emotions, and how do we measure them? You can read all about it in the next blog post. Or learn more about how emotions are made in this previous blog post. Don't want to miss new blog posts? Stay posted and subscribe now! You will receive updates of new blog posts every month. Reference Baars, B. J., & Gage, N. M. (2010). Cognition, brain, and consciousness: Introduction to cognitive neuroscience. Burlington, MA: Academic Press/Elsevier. --- ## Food and Cognition project URL: https://noldus.com/blog/food-and-cognition-project Published: 2019-05-20 13:25:00 Description: The Food and Cognition project will form a cluster of partners in the East of the Netherlands, who will exchange knowledge on the topics of eating behavior, targeted nutrition and enabling technologies. Scientists are learning more and more about how a healthy diet can help the brain to be healthy and also the complex relationship between diet and diseases such as Parkinson's, Alzheimer's, and even depression. A healthy diet is also key to development of babies and young children and so can have an effect that lasts a lifetime. A lot of expertise has been built up in the East of the Netherlands on this topic. In the Food and Cognition project, the main organizations working in this area are getting together to form a network, work out the most pressing questions, and deliver knowledge about food and cognition. The project will address three areas; eating behavior, targeted nutrition and enabling technology. The latter is of particular interest to project partner and technology company Noldus. There are a number of different technologies that are relevant in measuring eating behavior. In some ways, the technology for this application lags behind some other areas because it is technically so challenging. There are a vast number of different food types in the world and a lot of them look very much like each other. Even the same food item can have a very different nutritional content when it is fresh, compared with when it is close to its expiry date. Vitamins can be destroyed by over-cooking and meals are composed of multiple ingredients, often all mixed up and cooked together. Biased self-reporting What makes it worse, is that self-reporting is much less reliable when it comes to food than in many other areas. That is for two main reasons. Firstly, because we eat so often - multiple times every single day - it is a huge amount of effort for subjects in a study to report precisely what they eat and very easy for them to occasionally forget to write it down, even with the most user-friendly of apps to help them. Secondly, it is often far from neutral information. The context of such studies is that they are often carried out when there is perceived to be a problem with the food, like with diabetes or obesity. In such a context, there is an additional psychological pressure for subjects not to report that one chocolate bar, and what is worse, that pressure is most likely different between the 'control' and study groups. New technology to measure eating Nevertheless, a number of new technologies are being developed which are beginning to make measurements of eating behavior easier and less reliant on self-reporting. Cloud-based spectroscopy can be used to determine food quality and safety (e.g. if it is beginning to go off because it is too old) and small portable scanners claim to be able to determine the nutritional and chemical content of foods. 3D imagine can estimate the weight of food on a plate. Weight sensors can be built into tables, which can work well in e.g. a restaurant situation. A step further is to embed those sensors completely into the plates, preferably in a way that is dishwasher safe and with wireless data transfer and charging. A prototype of such a system developed by the University of Leuven is so accurate that it not only measures individual bites, but the location of those bites on a plate. If the researchers know which foods are in which compartments, they can accurately measure the intake of calories and nutrients. The SmartPlate from KU Leuven university (Gert Mertes) Measuring intake There are also a number of computer vision-based devices on the market (including Slow Control, SmartPlate Topview and Smart Diet Scale). The current systems have limited functionality, for instance, only quantifying the food before eating, not during the eating process, but undoubtedly in the coming years this will be an area of active development. Accelerometers on people's arms or cutlery can quantify when and how fast people are eating and there are also computer vision systems under development for that purpose. A different approach is not to measure the eating itself, but the glucose in the subjects' bloodstream. In the past this had to be done by taking blood samples, but there are a number of prototypes and one or two products available (often developed to monitor diabetes), in which a smart patch carries out that measurement automatically. Effects of eating on emotions As well as measuring the food intake itself, researchers are also often interested in the effect of the food on the subjects. Do they enjoy it? How is that linked to satiety (feeling full)? Which foods arouse people and which calm them down? Computer vision-based techniques like FaceReader can measure the emotions as shown in facial expressions, and devices for measuring people's physiology (like heart rate and skin conductivity) are getting cheaper, more mobile and less intrusive all the time. Sports watches are still not able to deliver research grade physiological data. However, they are getting better all the time and their measurement of fine movements with accelerometers can be a quite reliable way of monitoring different activities during the day. That is especially the case when the data are analyzed with the latest AI algorithms. In terms of factors like data security and access to raw data, they are still not suitable for research purposes. Using FaceReader to measure emotions whilst eating Using social media to gain insights into eating patterns A different approach is not to look in detail at individuals, but instead to use big data. What people purchase, gives a good indication of what is being eaten. Also, people leave a huge digital footprint when talking about what they are eating, especially with photos of food. This is potentially a great source of information, so long as the potential biases can be identified and compensated for. It is also often possible to obtain additional information about social media postings, for example knowing that the photo below was posted on Mother's Day gives some additional context. We are still a long way from the 'holy grail' of being able to easily, accurately and unobtrusively monitor people's food intake in their home environment, but there are so many developments going on in this area at the moment that it certainly looks really hopeful for the future that we will make serious progress towards that goal in the coming years. PROJECT PARTNER If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 30 years of experience Contact Us --- ## The effect of microplastics and pharmaceuticals on trophic interactions URL: https://noldus.com/blog/microplastics-pharmaceuticals Published: 2019-05-16 15:23:00 Description: Microplastics (found in common products such as toothpaste) and pharmaceuticals have an impact on the environment. Their combined effect, however, is still largely unknown. Today we have a guest blog post from EMERGEINTERACT. Dr Josie South, Dr Tarryn Lee Botha, Dr Josephine Pegg, Dr Martine Jordaan, Dumisani Khosa, Gina Walsh, Lubabalo Mofu (South Africa) who visited Dr Lisette de Senerpont Domis and Dr Sven Teurlincx (Netherlands) as part of the AQUACOSM Transnational Access grant collaborative project. Enjoy! Microplastics have dominated the news and media in recent years, from BBC's Blue Planet to the EU banning microbeads in products. Microplastics are plastic materials less than 5 mm in length which can be found in various shapes and sizes. These microplastics can be formed by the degradation of larger plastics, or are part of various consumer products such as exfoliants and toothpastes that replace natural ingredients such as oatmeal. When microplastics become pollutants Due to their continuous discharge as well as their persistency, microplastics are accumulating in the aquatic environment with a potential to bioaccumulate in organisms with ensuing effects such as starvation. Microplastics are not the only pollutants that may affect aquatic systems; another group of so-called contaminants of emerging concern (CEC) are pharmaceuticals. As waste water treatment plants do not have targeted removal of these CECs, aquatic systems show a continuous rise even more exacerbated by increasing human consumption. The effect of combined pollutants on aquatic organisms While individually microplastics and pharmaceuticals are known to cause changes in animal behavior and ecosystem functioning, the effect of their combined exposure is largely unknown. The effect assessment of multiple emerging contaminants on aquatic organisms is a relatively new field, which leaves much to be discovered about the possible consequences of our progressively urban lifestyle. Research project on the effects of microplastics and fluoxetine A collaborative project was made possible by an AQUACOSM Transnational Access grant (EU H2020-INFRAIA-project No 731065) where the Aquatic Knowledge Centre Wageningen (AKWA) based at NIOO-KNAW hosted a group of seven EMERGEINTERACT researchers from four different South African Institutions (The South African Institute for Aquatic Biodiversity, Cape Nature, University of the Witwatersrand and North-West University). The aim of their study was to investigate how microplastics may interact with the selective serotonin re-uptake inhibitor fluoxetine (an anti-depressant) and understand what their effects may be on aquatic communities. This study was conducted using the limnotron mesocosm facility at NIOO-KNAW to understand large scale outcomes in tandem with microcosm experiments and behavioral trials. Behavior and functional response analysis Noldus DanioVision equipment was used to determine how emerging pollutants affect fine scale trophic interactions through behavioral analysis and functional response analyses (resource density dependent consumption). Ecologically important differences can be assessed by measuring the interaction between predators and prey within a contaminated environment within the semi-natural mesocosms. Experimental design with different species A model predator – prey system of commonly found aquatic invertebrates, larvae of the ghost midge Chaoborus flavicans and the water flea, Daphnia magna, were assessed using Noldus DanioVision to test whether the pollutants have different effects on the different species. Aspects such as whether a mismatch of performance ability (i.e. speed of swimming, time spent moving, maximum acceleration) and if these effects changed depending on exposure time, pollutant concentration, and combinations of both pollutants were assessed. The same treatments were used to test whether the individual or mixture of the pollutants caused a change in the functional response type, attack rate, handling time, and maximum feeding rate of C. flavicans and used the behavioral parameters to determine how and why these performance parameters changed. Preliminary results suggest that microbeads have a more subtle effect than expected in comparison to fluoxetine when assessing behavior. However, the combined CECs show an exacerbated effect on trophic interactions. Acknowledgements A special thank you to Noldus for letting us borrow their DanioVision equipment while abroad. Our research will provide an important step towards understanding how plastic microbeads and pharmaceutical drugs can alter responses in model freshwater organisms. Image attributions - Micropollution: MakeevaIN [CC BY 4.0 (https://creativecommons.org/licenses/by/4.0)] - Water flea: Are We Underestimating Species Extinction Risk? PLoS Biology Vol. 3/7/2005, e253 doi:10.1371/journal.pbio.0030253 see Source [CC BY 2.5 (https://creativecommons.org/licenses/by/2.5)] - Ghost midge: AfroBrazilian [CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0)] - Limnotrons (The Netherlands): NIOO-KNAW, (https://www.aquacosm.eu/mesocosm/limnotrons/) --- ## About unexpected results: predator odor excites mice URL: https://noldus.com/blog/predator-odor-excites-mice Published: 2019-05-15 14:49:00 Description: The temperature of the tail and eyes of rodents is indicative of their emotional state. What would be the effect of a specific predator cue? The temperature of the tail and eyes of rodents is indicative of their emotional state. This study researches what the effect is of a specific predator cue, using a thermal camera and behavioral experiments. The result might not be what you expect. It is not easy to determine emotions in animals, but thanks to extensive research it is now possible to reliably assess the emotional state in various species. In order to test this, scientists measured minor temperature changes in specific body parts and connected them to certain response. Unconditioned fear In a recent study, scientists from the Université Paris and the University of British Columbia collaborated to assess the emotional response to predator odor in rodents, using infrared thermography and behavioral research. Predator odors are often used as an unconditioned fear-inducer. Therefore, they are useful in research to short-term physiological fear response. A thermal response to predator odor When animals experience emotions, their body responds with blood flow regulation, causing minor body temperature changes. Therefore, infrared thermography, together with behavioral experiments, are useful in assessing emotions triggered by various treatments. In rodents, the eye and tail temperature are the most indicative. Eye temperature and emotional states Changes in eye temperature are linked to both positive and negative emotional states, thus suggesting arousal. Unconditioned fear is associated with an increase in eye temperature. This is explained as the body's attempt to ensure blood support of vital body parts, like the brain and muscles used in fight or flight response. Tail temperature decrease When exposed to both conditioned and unconditioned fear, rodents often show a decrease in tail temperature. This prevents excessive bleeding when they get hurt, therefore increasing the chance of survival. In this study, a decrease in tail temperature was expected, as well as an increase in eye temperature, after exposure to predator odor. A behavioral analysis was carried out as well. Predator odor to induce unconditioned fear In this research, a predator cue, TMT is used to induce unconditioned fear. TMT (2,5-dihydro-2,4,5-trimethylthiazole) is a predator odor component isolated from fox feces, which is used often in rodent studies on anti-predator responses. Fear responses in naïve mice Naïve male house mice were exposed to either TMT or water during a behavioral test. Individuals were placed in a Plexiglas open arena (36x24x60cm), and allowed to habituate for 30 minutes. Odor exposure After habituation, the mice were exposed to one of the treatments. Using a syringe, 1 ml of liquid was injected into a cotton ball, which was then placed inside a small plastic tube pierced at both ends. From there, flexible tubes were connected to the arena and to an air pump, through which the air was continuously pumped into the arena. Infrared thermography The experiments were filmed using a thermal camera, from five minutes before until five minutes after the treatment started. Each minute, three images were selected where the mouse walked straight. The maximum peripheral body temperature (a proxy of eye temperature) and tail temperature of each image were used for the analysis. Behavioral analysis The behavioral analysis took place during the full 10 minutes of the experiments. The researchers used Noldus EthoVision XT to analyze how much time the mice spent both close to and far away from the odor. Duration and frequency of freezing behaviors were recorded as well. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Rapid eye temperature increase The rapid eye temperature increase that indicates arousal was found in the present study. Another research study showed similar results after predator exposure, thus indicating that eye temperature is a reliable measure of emotional state in rodents. This also indicates that TMT causes general excitement. Furthermore, mice with a higher eye temperature increase also showed a higher tail temperature increase, thus indicating that some individuals were more excited by predator cues than others. Tail temperature suggest arousal Various fear tests in rodents show specific physiological responses, for example stress-induced hyperthermia, decrease of tail temperature, and changes in heart rate and blood pressure. Unexpectedly, exposure to TMT caused an increase in tail temperature, suggesting general arousal, where previous studies suggested that TMT can increase heart rates and corticosterone, suggesting fear. Other studies related to stress-induced hyperthermia indicated that various physiological stress-responses can change independently. No typical fear response The mice showed no typical fear response after TMT treatment. They approached the predator cue, showed a notable absence of typical defensive behaviors, and they were aroused, which are all results confirmed by previous research. Furthermore, heart rate and corticosterone increases found in previous research seem to be a typical predator cue response. Those results indicate that rodents respond differently to predator cue in comparison to an actual predator, and try to collect more olfactory information. Animal fear response varies depending on the situation In short, TMT causes no decrease in tail temperature, which is typical during other fearful situations. Instead, it shows a short-term increase, indicating excitement. This might indicate that TMT is an indirect threatening cue. The present research and previously mentioned reports suggest that animal fear response could vary among different kinds of fearful situations, depending on the triggering cues. In order to increase understanding of responses to TMT, further research is needed to both physiological and emotional responses to the cue. References Lecorps, B., Rödel, H. G., & Féron, C. (2019). Short-term thermal responses after exposure to predator odor (TMT) in the house mouse. Mammalian Biology, 94, 25-29. --- ## How doing exercises counteracts the effects of Alzheimer’s disease URL: https://noldus.com/blog/doing-exercises-alzheimers-disease Published: 2019-05-10 15:15:00 Description: Recent research has shown that rats induced with Alzheimer’s disease suffered less from the effects of the disease when subjected to exercise. Recent research has shown that rats induced with Alzheimer's disease suffered less from the effects of the disease when subjected to voluntary, involuntary, and forced exercises. This non-pharmacological approach was shown to reduce the symptoms causing the disease. How doing exercises counteracts the effects of Alzheimer's disease Alzheimer's disease (AD) is a common, age-related neurodegenerative disorder in which braincells are progressively damaged and die, leading to symptoms of dementia like loss of memory, thinking skills, and eventually all other brain functions. A possible cause for AD is the accumulation of the so-called plaques and tangles inside the brain. Plaques and tangles in Alzheimer's disease Plaques are formed when the enzyme β-secretase breaks down the amyloid precursor protein, a protein present in the cell membrane of brain cells that plays a role in the neuron's growth and repairment. The product of the breakdown, the amyloid beta peptide (Aβ), is insoluble and binds together with other Aβ molecules outside the neuron, forming beta amyloid plaques. These plaques get between the neurons, hampering the neuronal signaling. Moreover, these plaques can activate an immune response, causing inflammation that might damage the neurons around it. Tangles can be found inside a neuron. Each cell is held together by the so-called microtubules, which are long polymers used for transport inside the cell. The protein tau is located on the microtubule to make sure it doesn't fall apart. It is thought that formation of Aβ plaques outside the cell activates a pathway that liberates the tau from the microtubule. This results in microtubules falling apart and tau sticking together, forming tangles. Accumulation of both plaques and tangles is known to cause AD. Exercise and Alzheimer's disease Past research found that regular exercise training improves neuroprotection, inflammation, and cognitive and non-cognitive functions through a reduction of plaque and tangle formation. Researchers Belvianli and Okudan of Selçuk University, Turkey, investigated the difference between the effects of voluntary, involuntary, and forced exercises on cognitive and non-cognitive functions in rats induced with AD. The researchers did this through the examination of three different behavioral tests: the open field test, the elevated plus maze test, and the Morris water maze test. Prior to these tests, the rats were trained for 90 days. The group assigned to voluntary exercises were housed in cages with running wheels. The group assigned to involuntary exercises was subjected to swimming exercise of one hour per day. The group assigned to forced exercises was forced to swim for one hour per day with the addition of a load attached to their tail. Open Field test For this test, animals are placed in a square arena for a certain amount of time. Observation of the rats gave insight on locomotor activity, anxiety level, and exploratory behavior. These observations were recorded and analyzed with EthoVision XT video tracking software. Elevated Plus Maze test For this test, animals are placed in a plus-sign shaped maze that contains two open and two closed arms. Observation of the rats gave insight into their anxiety level. These observations were recorded and analyzed with EthoVision XT video tracking software. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Morris Water Maze test For this test, animals were placed in a circular pool with a hidden platform. The time searching for the platform can be used to evaluate spatial learning and memory function. These observations were recorded and analyzed with EthoVision XT video tracking software. Exercise is beneficial to counteract AD While AD caused a decline in locomotor activity, this impairment was reversed by exercise training. This also counted for the exploratory behavior. Furthermore, anxiety levels were increased by AD, but the severity of this was attenuated by the exercise trainings. On top of that, the impairment in learning ability induced by AD was prevented by the exercise trainings. Biochemical analysis revealed that voluntary, involuntary, or forced exercise training decreased the formation of plaques and tangles in the hippocampus, which is the part of the brain responsible for spatial memory. Therefore, this research shows that all three types of exercise protocols improve behavioral deficits and suppress AD pathology. Voluntary, involuntary, and forced exercise almost equally attenuated non-cognitive disturbance and cognitive dysfunction in the rats induced with Alzheimer's disease. This non-pharmacological approach brings us one step closer in the direction of finding more therapeutics for the disease. References - Belviranlı, M., & Okudan, N. (2019). Voluntary, involuntary and forced exercises almost equally reverse behavioral impairment by regulating hippocampal neurotrophic factors and oxidative stress in experimental Alzheimer's disease model. Behavioural brain research, 364, 245-255. - Alzheimer's disease explained (video) - Read more: Diazepam and Alzheimer's --- ## The ultimate list of usability lab software tools URL: https://noldus.com/blog/usability-lab-software-tools Published: 2019-05-09 09:50:00 Description: For those of you interested in what we offer for usability studies, see how we can get you the analysis you need quickly, easily, and reliably with our UX tools. These are the Usability lab software tools you want to use! Did you know that Noldus Information Technology provides all the necessary components you need to start or update your lab for both animal and human behavior studies? If you haven't read our blog post on the ultimate list of neuroscience software tools yet, check it out! Usability lab software tools you want to use For those of you interested in what we offer for usability studies, read on to see how we can get you the analysis you need quickly, easily, and reliably with our FaceReader, Viso, and eye tracking software. Facial expression recognition software Automated facial expression analysis software is becoming increasingly popular amongst researchers to provide an objective assessment of emotions. As human assessment of emotions has many limitations and biases, using facial expression technology can deliver a greater level of insight into behavior patterns. FaceReader software is one example of a tool specifically designed for this purpose. It is often used in human behavior research for markets such as consumer behavior and advertising, psychological research, and usability studies. Emotion analysis with FaceReader FaceReader can automatically determine the presence and intensity of basic emotions, including Happy, Sad, and Angry. It can also analyze the commonly occurring affective attitudes interest, boredom, and confusion. Depending on your research needs, you can then expand your software capabilities with additional add-on modules. - Project Analysis Module - For advanced analysis and reporting, this module can automatically show test participants stimuli while accurately analyzing their facial expressions - Action Unit Module - For automatic analysis of a selection of 20 common Action Units, such as raising of cheeks, wrinkling of nose, and lip tightening. Or create your own custom expressions (ex. embarrassment, pain, etc.) - Remote Photoplethysmography (RPPG) - By measuring the small changes in color caused by changes in blood volume under the skin epidermis, the RPPG module can analyze heart rate and heart rate variability of your test participant without any additional hardware - Consumption Behavior Module - To analyze behavior related to eating and talking, including taking a bite or sip, chewing, chewing motion, and talking RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources If you are interested in trying it out, we recommend contacting us for a walkthrough with your Scientific Sales Consultant via screen share. In addition, if you would like more information, access our FaceReader page to request a quote or download a free white paper! Multi-video and multi-room video and audio recording If you are looking for a solution that provides you with multi-room and multi-video recording, we would like to suggest Viso. Viso is a complete AV software suite, developed to provide the video and audio material needed to gain insights into processes, human performance, and communication. This can include any sort of team training or simulation exercise, and is particularly helpful as a teaching tool for providing feedback. Viso allows you to start and stop recordings across an unlimited number of rooms, independently of one another. By allowing you to view your test participants from different angles, Viso is an ideal solution that lets you capture the behavior of your test participants in detail. In addition, while you are recording, you can mark events of interest per subject or add comments. This comes in handy for video playback and debriefing, and analysis is available both during and after recording. Viso is mainly used in the user experience, healthcare, psychology, and education markets, but it can be applied to almost every need or market. To request a free demonstration via screen share with your Scientific Sales Consultant, view an explainer video, or download a free white paper, visit our Viso page! FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo Eye tracking What are eye trackers, exactly? According to one of our preferred suppliers, Tobii Pro, they are a technology that allows you to have complete control of your device by using your eyes as you naturally would. We often integrate eye trackers into labs as well as portable set-ups thanks to the number of great benefits they provide in UX research. Using eye trackers, you can "know" exactly what your test participants are looking at, as well as data such as number of blinks, fixations, pupil dilation, and gaze position. Fields they are commonly used in include human factors and simulation, usability testing and UX research, consumer behavior and market research, psychology research, medical research, PC and gaming research, and more! UX testing with Tobii Pro eye tracking glasses (Source: Tobii Pro) Noldus offers eye trackers in the form of lightweight glasses, computer monitor and desktop trackers, and remote, contact-free eye trackers. In addition, when you purchase an eye tracker from Noldus, we will assist you in the process from start to finish, including lab installation, training your team and setting up experiments, and creating custom scenarios. To request a quote or more information, contact us here and we will be happy to get you started. Wait, there's more! Aside from the usability lab software and tools mentioned here, there are still a number of solutions we haven't discussed yet, like NoldusHub and The Observer XT. We also encourage you to reach out and chat with us – we are always ready to find you a custom solution that is the best possible fit for your research. We look forward to working with you! --- ## Hemineglect - and how to study recovery from it URL: https://noldus.com/blog/hemineglect Published: 2019-05-06 15:54:00 Description: Hemineglect is a condition caused by strokes or brain damage in which part of the sensory inputs to the brain are ignored and it is as if that part of the world which is sensed doesn't even exist. The late great Oliver Sacks was one of the 20th century's best scientific communicators. He wrote an amazing series of books about brain diseases and how they help us to understand how a healthy brain functions. One of his best-known books was 'The Man Who Mistook his Wife for a Hat'; and one of the case-studies he presents there was a woman who could not perceive one half of the world. She had what is called hemispatial neglect, or hemineglect. Hemineglect - and how to study recovery from it The patient had had a stroke which had damaged part of her right brain, which, due to the anatomy of the brain, meant that it ignored signals coming from the left side. Amazingly, it wasn't like wearing an eye-patch where you know that something is on your left side, but you just can't see it. It was more as if that side of the world didn't exist. So she only put on make-up on one side of her face and she only brushed her hair on that side. It is not just to do with processing sensory inputs, but the processing of attention for inputs coming from that side; they are simply ignored. Other studies have shown that it works just the same for things remembered or imagined. Patients were asked to imagine they were in a large public square, which they knew well, and describe what they saw. They could only describe things on one side of the square. For example, if they imagined they were standing on the South side, they could only say what shops were on the East side (to their right), but if they then imagined themselves standing on the opposite side they then could only describe things on the other side (for example, the West side, when imagining standing on the North). Recovery from hemineglect Hemispatial neglect is not always as severe as that. It all depends on which parts of the brain have been affected by stroke (or injury) and how seriously. The above description is based on damage to specific parts of the parietal lobe, which has a number of important functions including processing sensory inputs and regulating awareness and attention. Recovery is also possible. Patients have been trained with various techniques to learn to pay attention to the missing half (with various degrees of success) and patients who have had strokes or brain injuries sometimes recover. Measuring the effects If stroke patients recover, they can gradually take up their normal daily lives again. This is not without risk. If they are crossing a road or driving a car, the possibility that they aren't aware of one half of the road doesn't bear thinking about. Obviously, the more the recuperation process is understood, the better. To study that properly, researchers want to not just carry out abstract laboratory tests, but also to measure what is going on in real life situations. An important one of those situations is to look in detail at how a stroke patient functions when they are driving. There are a number of challenges facing researchers who want to do that sort of study, including that it is too risky to put stroke patients into a real car on the public road and that driving is a complex process. Fortunately, Noldus Information Technology specializes in meeting that sort of measurement challenge and was able to help out. Noldus has a lot of experience in both integration, synchronization and analysis of multi-modal sensor data and also in integrating with virtual environments such as a driving simulator. FREE EBOOK Neuroscience research Discover how to advance your neuroscience research with innovative tools and techniques for behavioral analysis. - Behavioral analysis methods - Multi-modal data integration - Real-world application examples Download DriveLab for health project In the DriveLab for health project, Noldus developed an instrumented driving simulator that was suitable for the task. The solution delivered a number of key variables which were displayed to the research team on a special dashboard including reaction time (for example time to braking after seeing an obstacle) and steering quality (measured as the variation in position with relation to road). These were measured using a driving scenario specially-created by WIVW, which represented a quiet country road with road sections with and without lines, with and without oncoming traffic, with wild animals crossing the road, a breakdown car, and some cars driving ahead. The good news is that the solution developed delivered the results well and in a format that was usable by the researchers. It looks like this will be a promising tool for further study in this important area. Acknowledgment The work on developing the system for measuring the drivers was, in part, carried out in the DriveLab for Health project in cooperation with Dr. Lilian Beijer (Saint Maarten's Clinic, Nijmegen, The Netherlands) and funded by the ACTTiVAte program and the project partners. ACTTiVAte has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement Nº 691473. --- ## Two examples of on-site observational studies with older persons URL: https://noldus.com/blog/two-examples-observational-studies Published: 2019-04-30 15:03:00 Description: In certain cases, observations for your study are best performed on-site. In this blog, we describe examples of observational studies with older age groups, conducted at home or at a healthcare facility. In some cases, it is necessary to bring your research to your participants. For example, you might want to observe people in a natural setting: at home, in a shop, in the classroom, or in the office. Another case where on-site research would be beneficial is when your participants are experiencing health issues, preventing them from travelling to your lab. Conducting your research on location enables you to study people that are otherwise difficult to reach. These factors should be taken into consideration when choosing the location for your research, especially when conducting studies with older age groups. Practical aspects of on-site observational studies If you want to conduct your study in another location, there are some practical aspects to think about. For example, you have to set the right lighting conditions and camera position. You also have to make sure that you capture voices and other sounds accurately. FREE WHITE PAPERS How to build a research lab Do you want to learn more how to set up a research lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download 3 free 'how to' guides! Submit to download Observational research examples The first study we describe in this blog post explores how familiarity influences the use of electronic devices in different age groups. In the second study, researchers compared different methods of observing pain expressions in dementia patients. 1. Familiarity and intuitive use Improving products for older age groups It is generally assumed that older adults have difficulty using modern electronic devices, such as mobile telephones or computers. Because this age group is growing in most countries, changing products and processes to adapt to their needs is increasingly more important. Improving technological experiences in older age groups supports their social inclusion, productivity, and their independence. To gain more insight in the learning processes involved in using electronic devices, Lawry and his colleagues compared levels of familiarity between age groups. Comparing familiarity between older and younger adults Familiarity describes the way an action is recognized or understood, based on prior experience and knowledge. It develops from a general level of knowledge, to knowledge that is based on experience, and finally to effortless and unconscious action. The researchers identified several behaviors that suggest familiarity with an action. These include anticipation and planning, relative speed, verbalization, and task attention. They recorded these behaviors during a verbal report of how participants thought they would perform a task, as well as during the performance of the task itself. Specifically, participants were asked to use a product they were familiar with and a product that was new to them. The study included 32 participants with different educational backgrounds, who were divided into different age groups (18-44, 45-59, 60-74, and 75+). Observing familiarity at home What better place to study familiarity than in the familiar place of home? By conducting part of their research in the participants' homes, researcher Lawry and his team created a more realistic learning environment, had easy access to familiar products, and were able to recruit older participants more easily. They coded verbal and visual data from both studies using The Observer XT, and used this software to calculate inter-rater reliability as well. Results showed significant differences in familiarity between age groups, concerning both known and new products. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Differences between younger and older adults When using their own products, the youngest adult group showed more familiar behaviors than the two oldest groups. These younger participants also showed more familiarity when using a new product, compared to all other age groups. Importantly, these results indicate that intuitive use of new products declines as early as during middle age. Therefore, the researchers advise product designers to incorporate more features that are based on prior knowledge of both middle-aged and older adults. 2. Pain expressions in dementia Observing pain expressions In dementia, severe cognitive impairment can lead to an inability to communicate verbally. When these patients can't tell their caregivers about the pain they feel, an accurate assessment of pain expressions becomes essential. Browne and her colleagues examined how the angle of observation influences this assessment, both in trained and untrained observers. It is widely assumed that a front view provides the most information on pain. However, caregivers also often observe patients from the side. Not only can this information be used to improve human observations, but it can also support the development of computer vision systems, further improving care for people with dementia. On-site observational study The researchers included 102 adults over the age of 65 in their study, with and without dementia. Video recordings were made from both the front and profile of their faces, during a physiotherapy examination and a baseline period. Observers used this video data to assess pain expressions with two different coding systems. They made their observations in long-term care facilities and an outpatient physiotherapy clinic. This approach provided opportunities to observe participants in their beds, as well as during their treatments. When analyzing their data, Browne and her colleagues used The Observer XT to code the video data and calculate reliability between raters. Benefits of a profile view Both trained and untrained observers were able to discriminate between pain and pain-free situations. When comparing assessments between these observers, results showed that undergraduate students relied less on specific pain cues when making their observations. During physiotherapy, the students also rated pain intensity higher and more accurately when viewing patients' profiles. This suggests that the assessments of less experienced observers could improve when including a profile view. Observer accuracy may also benefit from the use of computerized systems, particularly when viewing patients from the front. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Interested in human behavior research? Read more on 'How to study human behavior'! References - Lawry, S.; Popovic, V.; Blackler, A.; Thompson, H. (2019). Age, familiarity, and intuitive use: an empirical investigation. Applied Ergonomics, 74, 74-84. - Browne, E.; Hadjistavropoulos, T.; Prkachin, K.; Ashraf, A.; Taati, B. (2019). Pain expressions in dementia: validity of observers' pain judgments as a function of angle of observation. Journal of Nonverbal Behavior, https://doi.org/10.1007/s10919-019-00303-4. --- ## How to best assess pain-related behaviors in preclinical studies URL: https://noldus.com/blog/preclinical-studies Published: 2019-04-26 14:34:00 Description: Most humans can tell you they’re in pain. However, assessing pain sensitivity in rodents during preclinical studies is a challenge. Most humans can tell you they're in pain. However, assessing pain sensitivity in rodents during preclinical studies is a challenge. Gait analysis is a great method to address this issue, but which system works best? Chronic pain is one of the leading causes of global disability. Lower back pain, neck pain, and migraines are an especially large burden to a large part of society. Studies into analgesics and therapies rely on good models and accurate assessment. Researchers from Peking University and the Capital Medical University (Beijing, China) have been looking into the investigation of pain. Measuring pain sensitivity and pain-related behaviors can be a challenge, both in the clinic as well as in preclinical studies. Traditional pain parameters Common methods used for the assessment of pain sensitivity and pain-related behaviors in rodents include punctate allodynia (Von Frey assay) and dynamic (brush) allodynia. With dynamic allodynia, the rodent's paw is lightly stroked with a paintbrush. Healthy animals usually don't respond, while injured animals more likely to respond with rapid and sustained lifting of the paw. In case of punctate allodynia, the rodent's paw is probed with a Von Frey fiber, and the paw-withdrawal threshold is measured. For each consecutive probe, a thicker (i.e. stiffer) fiber is used, increasing the effect of the stimulus. After nerve-injury or inflammation, the subject is expected to be more sensitive to this stimulus. Pain severity versus gait parameters While well validated, these measurements offer a limited insight into the pain behavior of the animal. In their research, Xu and colleagues found that gait analysis can be better than traditional evaluations, and decided to compare pain sensitivity (they selected the results from the Von Frey assay for this) to gait analysis results. Pain models and medication The researchers selected two rodent pain models for their study. The SNI (spared nerve injury) rats served as a model for chronic neuropathic pain, and the CFA (intraplantar complete Freund's adjuvant) rats were used as a model for inflammatory pain. Test were performed before and after treatment with medication (pregabalin and tramadol, respectively). Comparing gait analysis methods In gait analysis, a distinction can be made between methods that are based on the voluntary movement of animals, like CatWalk XT, and systems that are based on forced movement on a treadmill, like DigiGait (also see this blog post about the issue of speed in gait analysis). Using both apparatuses, coordination data (swing duration and duty cycle) and print area were measured. In addition, print intensity was measured only with CatWalk XT, as DigiGait does not offer this readout. Comparing these to the results of the Von Frey testing, researchers were hoping to see if these gait parameters would correlate with pain sensitivity, and to changes due to medication. Pain sensitivity reflected in gait parameters At first sight, coordination data from both systems did correlate with results from Von Frey punctate allodynia testing. Print area and print intensity did not correlate. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Print area calculations The print area was calculated differently by both systems. Where DigiGait uses direct recordings from the ventral direction to calculate the "projected area" (not merely the actual paw-floor contact), CatWalk XT uses the pressured area to define the print area. In addition, CatWalk XT offers the mean intensity of the contact area during a step cycle as a parameter. To remove possible bias in this data (e.g. due to weight), the authors compared the injured to the uninjured paw. A closer look into the data With no correlation found between print area/intensity and the pain sensitivity of the animals, researchers decided to look at data from both hind paws separately. In doing so, CatWalk XT data did reveal an augmentation of print area due to the administration of medication. Comparing systems While in principle both systems offered coordination data that is able to reflect the pain sensitivity in rats, CatWalk XT surpassed the treadmill system used in this study, especially in the CFA inflammation model. This is due to the additional intensity data, but also because the Illuminated Footprints™ technique allows for insightful 2D and 3D imaging of the footfalls. For example, the 2D imaging demonstrated the longer duration of the footprint, in turn building up more pressure over time. This behavior is neither visualized nor possible (because of the fixed speed the animals have to walk at) in a treadmill system. References Xu, Y.; Tian, N.X.; Bai, Q.-Y.; Chen, Q.; Sun, X.-H.; Wang, Y. (2019). Gait assessment of pain and analgesics: comparison of the DigiGait™ and CatWalk™ gait imaging systems. Neuroscience Bulletin, doi: 10.1007/s12264-018-00331-y For more information on CatWalk XT gait analysis, visit www.noldus.com/catwalk, or learn more about gait analysis. --- ## The effects of negative campaigning on emotions URL: https://noldus.com/blog/effects-negative-campaigning-emotions Published: 2019-04-25 09:10:00 Description: Do people display different emotions when they watch a commercial with or without negative campaigns? Sabine Dennert shares her findings in this guest blog post. This is a guest blog posted by Sabine Dennert. She studied at the Technical University Dresden in Germany and finished with a Master's degree in communication science. The title of her Master Thesis is "Negative Campaigning in federal election. An experiment on the effects of campaigning on emotions and political attitudes based on FaceReader." The effects of negative campaigning on emotions The main topic of my work was Negative Campaigning. Geer defines Negative Campaigning as "any criticism leveled by one candidate against another during a campaign. An appeal in a campaign either raises doubts about the opposition (i.e. negative) or states why the candidate is worthy of your vote (i.e. positive)." [1] Political campaign commercials, including Negative Campaigning, can have a variety of effects on party supporters or opponents. In German-speaking regions, the influence of attacks within an advertising spot – one of the widest-reaching advertisement channels – to the recipient's emotions and their political attitude isn't well investigated yet [2]. The emotions of people watching the "Alternative für Deutschland" campaign commercial were investigated using the FaceReader facial expression reading software from Noldus Information Technology. Emotional involvement allows voters to attach personal importance to their desired political issues. This allows them to have a stronger identification with their chosen political party [3] and suggests that party identification is influenced by emotion and acts as a crucial factor and mediator. Measuring facial expressions while watching a commercial This master thesis used FaceReader version 7.1. The investigation took place from August 29, 2018 to October 2, 2018 with 55 participants. All participants were divided into two groups. Out of all the participants, 28 people received an edited commercial without "negative campaigning" while 27 people received the original "Negative Campaigning" commercial. While watching the commercial, all participants were recorded using a camera. This recording was evaluated by the FaceReader software. Something that was very important for the study was the valence, or the emotional overall mood. It helps to provide information about how the two groups differed, and where the commercial had particularly positive or negative emotions. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Emotional analysis With the help of the second-by-second emotional analysis, it was possible to determine the exact scenes where the highest eruptions of emotions were located. For example, consider the average emotions "happy" and "angry" per frame in Figure 1 (with negative campaigning) and Figure 2 (without negative campaigning). Figure 1. Curve of the emotions "happy" and "angry" during the AfD spot with Negative Campaigning scenes (from 00:00:25 - 00:01:04). The values correspond to the average values of all "happy" and "angry" rashes per frame in subjects with negative campaigning (N = 27). Figure 2. Curve of the emotions "happy" and "angry" during the AfD spot without negative campaigning scenes (cut 00:00:25 - 00:01:04). The values correspond to the average values of all "happy" and "angry" rashes per frame in subjects with negative campaigning (N = 28). Emotional mood influences political attitude Based on the results, the thesis shows that political campaign attacks can have a strong psychological effect and could influence the emotional mood, even if in a negative way. For the party's opponents, it could be shown that the recognized attacks influenced emotional moods and also changed political attitudes. References - Geer, J. G. (2006). In defense of negativity. Chicago: University of Chicago Press. P. 23 - Schicha, C., & Skroblies, M. (2017). Politik im Spot-Format. regierungsforschung.de. P. 4 - Kießling, D., & Zolleis, U. (2005). Politische Werbung in modernen Wahlkampagnen. Die Politische Meinung (422). P. 47. --- ## ChickenStress project URL: https://noldus.com/blog/chickenstress-project Published: 2019-04-23 10:51:00 Description: The abolition of battery farming has improved chicken welfare, but there are still problems like feather pecking. In the ChickenStress project, we will try to understand better how to reduce stress and improve welfare. There are almost 100 million chickens in the Netherlands — that's about 17 times as many chickens as people. Their welfare has improved enormously in the past few years, especially with the abolition of battery farming in the European Union in 2012, but there is still plenty of room for improvement. For example, stressed chickens sometimes peck at each other, and that can lead to the death of literally billions of chickens in Europe every year. The ChickenStress Project In the ChickenStress project, the partners, including Noldus Information Technology, will try to understand better the issues around how to improve chicken welfare and reduce problems like feather pecking. Although scientists don't understand everything about the issue yet, we do know what the main topics of research should be. If we understand it better, we can make recommendations for breeders and farmers leading to better welfare for the chickens. Understanding stress in chickens Firstly, we know there is a genetic factor. Some breeds of hens are more aggressive than others and we know that this is caused by a side effect of the breeding for other traits (like productivity) that has taken place. The ancestors of modern chickens were forest birds called Red Jungle Fowl and this research has the huge advantage that those birds are still around today. We already know that the stress response in the red Jungle Fowl is stronger and with a much faster recovery than in some modern breeds. If we can puzzle out the genetics, we can perhaps give modern breeds back some of the stress resilience of their ancestors. Stress mechanisms in the brains of birds Secondly, we know that the stress mechanisms in the brains of birds (especially the amygdala and hippocampus) are analogous to the well-understood mechanisms in mammals, but the details still need working out. The brains of birds have evolved differently from mammals, so we cannot just extrapolate from what we know about lab mice and about humans. However, the research groups in this project have already discovered a group of cells in the birds' amygdala which controls the levels of the stress hormone cortisol which is equivalent to a similar structure in mammals' brains. They have also found that it looks like the rate of creation of new nerves in the hippocampus is an excellent indicator of the welfare of birds, so that will also be one of the things the project will be investigating. Environmental factors Thirdly, the environment is critical, including factors like light levels and day/night alternation in early life and the possibility to be able to carry out natural behaviors like dust bathing and moving to different levels. If young birds are stressed then they will respond differently to stress later in life, for example if they are deprived of maternal care as young chicks. In their natural forest, the hens occasionally leave the eggs during incubation, which means there is a natural variation of dark and light. However, modern incubator units hatch eggs in total darkness, which can affect brain development. Likewise, in the natural habitat of chicks, they immediately start foraging for food in litter as soon as they have imprinted on the mother hen, whereas commercial chicks often have no litter to forage in for the first days of their lives. This might mean that even if they are provided with a more enriched environment later in their lives, they are unable to explore and use it fully. Perhaps the barns where the hens brood the eggs can be redesigned to overcome that problem. The exploratory (and other spatial) behaviors of the chickens will be measured using Noldus' state-of-the-art TrackLab solution to see if the redesigned barns have the desired effect. The ChickenStress project The European Union is investing almost €4 million in this project, which is coordinated by Newcastle University, has 19 partner organizations and will educate 14 PhD students. The PhD students will not only work in their own universities but also spend significant time on secondments at other universities in the project and also at the industrial partners, including leading poultry breeders. Noldus' solutions are going to be crucial for measuring the welfare and behaviors of the animals. We expect that TrackLab will be particularly important but also other tools will play their part, such as The Observer XT for computer-aided behavioral observations. RESEARCH PROJECT Want to partner with us? If you are setting up a research project and think that Noldus could be a partner in your consortium, let us know! - Develop solutions in consortia - Co-develop - Trust our 35+ years of experience Learn more Acknowledgement This project is funded by a Marie Skłodowska-Curie grant from the Horizon 2020 program of the European Union. --- ## How mice regain their memory: Betaine against Alzheimer’s Disease URL: https://noldus.com/blog/betaine-against-alzheimers-disease Published: 2019-04-15 14:36:00 Description: As a potential Alzheimer medicine, betaine was tested on an AD animal model in a novel object recognition test. Using video tracking, scientists studied the influence of betaine and betaine transporter on mouse memory. A potential Alzheimer's disease medicine In the world of science, researchers are always looking for a cure for Alzheimer's disease (AD). Using various tools like behavioral research tests, the effects of potential new medicines are assessed and their possible mechanisms unlocked. Betaine One of those potential drugs is betaine. This substance is often found in plants, and is known to suppress oxidative stress and reduce inflammation. However, its effects on neurodegenerative disorders are still unknown. Using behavioral research and an AD animal model, Ibi and colleagues from Meijo University, Japan, tried to find out what effect betaine has on AD, and how it gets through the blood brain barrier (BBB). They used a novel object recognition test, which should show any effect of betaine on the mice's memory. Alzheimer's disease symptoms The symptoms of AD mainly result from a specific type of proteins, called amyloid-beta (Aβ). They increase oxidative stress in the brain, which is associated with brain dysfunction. Because of these traits, Aβ is often used to mimic AD in mice. An AD animal model For this research, mice were used as a model species. The roles of betaine and its transporter were assessed through the novel object recognition test, and the MDA levels (a marker of oxidative stress) in their brain were measured. The behavior of the mice was recorded and analyzed using Noldus EthoVision XT in order to collect detailed data from the tests. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Betaine transporter GAT2/BGT-1 is a known betaine transporter in mice, but it is not yet certain if it is responsible for betaine transport through the BBB as well. Therefore, NNC-05-2090 was used, an inhibitor specifically targeting this transporter. Mimicking (the treatment of) AD First, the mice were injected with Aβ or distilled water, followed by either a betaine injection or both a betaine and an NNC-05-2090 injection. Betaine was injected either subcutaneously or straight into the brain fluid to see if it is transported through the BBB or not. Novel object recognition test To investigate memory function, mice were subjected to a novel object recognition test. After a habituation period of two days, each mouse was trained by letting them explore freely in an open box (30×30×35 cm) for five minutes, with two identical objects placed inside. Five minutes after the training session, the test session started. One of the objects was replaced with a novel object, and again the mice were allowed to explore for five minutes. An increased interest in the novel object compared to the familiar one indicates recognition of the former as being new, while equal interest in both objects suggests a memory impairment. Video tracking All tests were recorded, and data was collected using Noldus EthoVision XT. Data consisted of time spent exploring the objects, and the distance the mice moved. A recognition index was calculated, i.e., the ratio between novel object exploration time and total object exploration time. The same was done for the training session, using instead the exploration time of the object that was replaced with the novel object in the test session. After the sessions, MDA levels in the mice's brain were measured to determine the levels of oxidative stress. Effectiveness of betaine in AD treatment Betaine as a potential medicine The control mice had a higher recognition index for the novel object in the test session than in the training session. The preference of Aβ injected mice for the novel object was significantly lower, indicating a decreased ability of object recognition. When Aβ treatment was combined with a betaine injection, however, the mice seemed to behave similar to the control mice. This indicates that betaine could be effective in fighting AD symptoms. The role of GAT2/BGT-1 The mice treated with NNC-05-2090 after their betaine and Aβ treatment had similar MDA levels as mice not treated with the inhibitor, indicating that GAT2/BGT-1 is not involved in distributing betaine to the brain. However, NNC-05-2090 treatment decreased the improving effects that betaine had on the memory of the mice, indicating that GAT2/BGT-1 might be involved in betaine transport after all. It is possible though, that the antioxidant effects of betaine result from lesser known transporting mechanisms than GAT2/BGT-1. It is also possible that the transporter expression pattern changes depending on the situation. Several different types of AD medicines are already on the market, but betaine is the first potential medicine that can act preventively, instead of just easing the symptoms. Conclusions This study shows that betaine significantly improves memory and oxidative stress in mice, which indicates that a new AD medicine might have been found. The role of GAT2/BGT-1 is not entirely clear yet, since the treatment with its inhibitor seemed to point towards two mutually exclusive possibilities. Therefore, the exact properties of GAT2/BGT-1 should be studied further. References Ibi, D.; Tsuchihashi, A.; Nomura, T. & Hiramatsu, M. (2019). Involvement of GAT2/BGT-1 in the preventive effects of betaine on cognitive impairment and brain oxidative stress in amyloid β peptide-injected mice. European Journal of Pharmacology, 842, 57-63. --- ## What does an infant’s gaze tell us about how hungry they feel? URL: https://noldus.com/blog/infant-gaze-during-feeding Published: 2019-04-11 08:55:00 Description: McNally and her colleagues developed a coding scheme to observe infant gaze behavior and applied it in a study of complementary feeding. Research suggests that infant gaze can indicate hunger and satiation. Understanding these needs at an early age supports the development of a healthy appetite. McNally and her colleagues developed a coding scheme to observe infant gaze behavior and applied it in a study of complementary feeding. Gaze behavior signals interest in food From a very early age, we use our gaze to communicate with others. Gaze is involved in predicting intentions, understanding emotions, and directing someone's attention. Furthermore, this non-verbal behavior provides clues on what we feel and what we're interested in. Researchers focusing on nutrition use this valuable information to study how visual processing influences our eating habits. For example, studies have found that our gaze towards food images varies according to how hungry we feel, and that gaze duration is associated with how much we eat. Findings like these have important implications for the development of a healthy appetite, and may even play a role in reducing the risk of obesity. FREE WHITE PAPER Tools for Infant Studies Download the free White paper to learn more about the software tools available for infant studies. - Capturing behaviors with video - Coding behaviors accurately - Unobtrusive emotion analysis Download Measuring infant gaze Despite this research potential, gaze has received little attention in the study of infant feeding. Only a few studies examined links between infant gaze and feeding state, with observations that were restricted to milk feeding. McNally and her colleagues argue that if infant gaze is examined more systematically, it could provide new insights into the signaling of infant hunger and satiation. These insights can be especially meaningful in the transition to complementary feeding, when parental responsiveness is an important factor in the development of healthy eating behaviors. Therefore, the researchers decided to develop a coding scheme and use it to examine gaze behavior in the context of complementary feeding. Gaze behavior during feeding Specifically, the researchers were interested in the way infant gaze changes during meals. They predicted that gaze behavior differs between the start and end of a meal, and between a main meal and dessert, as a result of satiation. Research also suggests that a change in the sensory qualities of a meal renews appetite despite increased levels of satiation. Therefore, they also expected to find similar patterns of gaze change during both the main meal and the dessert. Reliability of gaze observations Infant gaze was observed in twenty parent-infant dyads. The infant group consisted of eight boys and twelve girls, between six and eighteen months old. Infants were either raised using self-feeding methods or through spoon feeding by a parent. They were filmed during two separate feeding episodes, eating a familiar meal at their regular lunchtime. The video materials of the first, middle and last twenty percent of each meal were used to observe frequencies of different gaze behaviors. This video data was coded using The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial As part of their study, the researchers developed and tested The Infant Gaze at Mealtime (IGM) coding scheme. The IGM describes different gaze directions, such as 'gazing at food' or 'gazing at caregiver.' A random selection of available video clips was coded with the IGM by three different observers. Using The Observer XT, they then calculated the initial inter-rater reliability for each gaze. After reviewing disagreements between coders, results across all observations showed excellent inter-rater (ICC=.95) and test-retest (ICC=.97) reliability. Changes in infant gaze Analyses of gaze behavior during meals confirmed the hypothesis that infant gaze changes as a function of satiation. As meals progressed, infants spent less time gazing at food and more time doing exploratory gazing. These changes were found within both meals, as well as between the main meal and the dessert. Also, hunger related gazing increased when infants were exposed to dessert, confirming the hypothesis of sensory specific satiety. The results of this study suggest that the IGM is a reliable tool to examine infant gaze. Further research may be needed, however, to ensure that the coding system accurately captures gaze behaviors from a wide range of infants. Moreover, observations from this study are in line with predictions that gaze behaviors signal hunger and satiation. Understanding these processes, both in milk and complementary feeding, helps to support the development of responsive feeding interventions and healthy eating behaviors. Reference McNally, J.; Hugh-Jones, S.; Caton, S.; Vereijken, C.; Weenen, H.; Hetherington, M. (2019). The eyes have it: Infant gaze as an indicator of hunger and satiation. Appetite, 133, 353-361. --- ## Diazepam in the battle against Alzheimer’s URL: https://noldus.com/blog/diazepam-alzheimers Published: 2019-04-08 12:00:00 Description: Scientists have found out that a low dose of the tranquilizer diazepam reduces the breakdown of neurons, seen in the development of Alzheimer’s disease. How a low dose of diazepam in early Alzheimer's disease development lowers the decay of neurons Scientists have found out that a low dose of the tranquilizer diazepam reduces the breakdown of neurons, seen in the development of Alzheimer's disease. Low doses of diazepam have been shown to enhance spatial learning and memory retention in rats induced with Alzheimer's disease. GABA and its role in Alzheimer's Alzheimer's disease (AD) is a common neurodegenerative disorder in which braincells are progressively damaged and die, leading to a loss of memory, thinking skills, and eventually all other brain functions. The loss of memory is induced by an abnormally high production of gamma- aminobutyric acid (GABA), an inhibitory neurotransmitter. GABA plays a role in the communication in the brain, specifically the hippocampus and neocortex, which are associated with spatial memory. High production of GABA leads towards the inhibition of neurotransmission in these parts of the brain. Diazepam is a GABAA receptor modulator. It is used as a medicine and known to cause sedative and memory impairing effects. Nevertheless, these effects are caused by doses above 1 mg/kg. Recently, researchers Pilipenko and colleagues from the University of Latvia have found that low doses of diazepam (0.05 mg/kg – 1 mg/kg) reduce the decay of neurons in rats induced with AD. Morris water maze test To research spatial memory, these researches used the Morris water maze test, a commonly known experiment in neuroscience. In this test, animals are placed inside a round pool filled with water, containing a visible escape platform. Firstly, the animal is trained to find the platform. Secondly, the escape platform is made invisible and the animal is tested to find the same platform. The time spent searching for the platform, which can be recorded by the software Ethovision XT video tracking software, can confirm spatial memory. During this research, the rats induced with AD displayed difficulty finding the platform. The decay of neurons in the hippocampus, caused by AD, impaired the rat's spatial memory. Treatment with low doses of diazepam reduced the effects caused by AD, in early development of the disease. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Open field test To investigate locomotor activity, the team of Pilipenko also used the open field test. For this test, animals are placed in a round arena for a certain amount of time. The total distance walked and the total time spent in the center zone, which can be recorded by Ethovision XT 11.0 video tracking software, can serve as a unit for locomotor activity. Rats treated with diazepam would normally be expected to have reduced locomotor activity due to the tranquilizing effect. However, they found that low doses of diazepam did not influence locomotor activity, nor did induction of AD. Diazepam and its effect on brain proteins Alzheimer's disease is known to cause neuroinflammation and the dysfunction of neurotransmitter systems. The breakdown of neurotransmitter acetylcholine, increased synthesis of GABA, and reduction of synaptic plasticity are all symptoms of AD development, which can be measured through certain protein concentrations in the brain. Treatment with a low dose of diazepam reduced this so-called protein pathology in rats induced with AD. Analysis of the neocortex and hippocampus revealed that diazepam prevented neuroinflammation, preserved synaptic plasticity, and normalized protein concentrations associated with acetylcholine breakdown and GABA synthesis. Diazepam in the battle against Alzheimer's disease Though these findings show great potential for the treatment of early development of Alzheimer's disease, the mechanism behind the non-sedative effect of diazepam remains unclear. GABA-receptors play a large role in the development of AD, and other studies found that the effect of other GABA receptor agonists, like muscimol and baclofen, also reduced memory impairments and neuroinflammation caused by the disease. Though much further research needs to be done, this study shows that treatment with a low dose of diazepam in the early development of the disease can reduce the effects caused by Alzheimer's. This different application of an existing medicine brings us one step closer in the direction of therapeutics for the disease. References - Pilipenko, V., Narbute, K., Pupure, J., Rumaks, J., Jansone, B., & Klusa, V. (2019). Neuroprotective action of diazepam at very low and moderate doses in Alzheimer's disease model rats. Neuropharmacology, 144, 319-326. - Morris water maze video - Open field test video --- ## Assessing gait in a mouse model for Leigh Syndrome URL: https://noldus.com/blog/assessing-gait-mouse-model-leigh-syndrome Published: 2019-04-04 13:38:00 Description: There is an unmet medical need to develop clinical effective treatments for Leigh Syndrome and other mitochondrial diseases. Today, Dr. de Haas shares some of her research insights. Today we have a guest blog post by Dr. Ria de Haas, on her preclinical research on Leigh Syndrome at the Radboud Center for Mitochondrial Medicine (Nijmegen, The Netherlands). Enjoy! Leigh Syndrome Mitochondrial diseases are heterogeneous multisystem disorders mostly caused by mutations affecting the oxidative phosphorylation (OXPHOS) system, which is involved in cellular energy production. Leigh Syndrome is one of the OXPHOS deficiency disorders with an incidence of one in 77,000 live births and also known as sub-acute necrotizing encephalomyelopathy. Symptoms typically begin early in life, and include ataxia, loss of muscle strength, and neurodegeneration. Abnormal gait in patients Mitochondrial disease patients also show abnormal gait. The GAITrite is an electronic walkway used for patients and shows marked differences in gait between mitochondrial disease patients and controls 1,2. The observed gait differences correlate with markers of disease severity. Treatment Currently, there is an unmet medical need to develop clinical effective treatments for Leigh Syndrome and other mitochondrial diseases. Several potential new treatment strategies are currently under (pre-)clinical development; one of them is a novel small molecule KH176 3-6. Mouse model for Leigh Syndrome Because mitochondrial diseases are heterogeneous and multisystem disorders, it is important to investigate interactions at multiple levels (molecules, cells, organs and physiological functions). Therefore we are using the Ndufs4 knockout (Ndufs4-/-) mouse model which is a model for Leigh Syndrome and develops, similarly to the clinical situation, a fatal progressive neurodegenerative disease phenotype. Symptoms include loss of motor function, ataxia, epilepsy, and short life span. This model is used to gain more insight into the pathogenesis of this disease and to evaluate the efficacy of novel therapeutics. Methodology Previously we used more traditional readouts, such as rotarod and grip strength, to characterize this animal model. However, these readouts remain subjective and difficult to translate to the clinical situation. Therefore, in line with the GAITrite studies in patients, we used the CatWalk XT gait analysis to evaluate gait in the Ndufs4-/- mice 7. We used the following protocol in our studies. Starting at the age of three weeks, mice were habituated to the CatWalk with their cage mates for 10 minutes during four consecutive days. By using this habituation protocol, the animals walked voluntary across the walkway without the use of any rewards. Weekly testing was performed individually, starting at four weeks of age. A session was successful after four compliant runs. A compliant run meets the run criteria set at a maximum run duration of 15s, with a maximum speed variation of 65%. Abnormal gait in Ndufs4-/- mice Marked genotype differences were noted between Ndufs4-/- and wild type mice in dynamic, static, coordination, and support parameters 7. Specifically walking speed variation, intensity of the individual limbs, number of patterns, and diagonal and lateral support were significantly affected in Ndufs4-/- compared to wild type mice. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources Treatment effect on gait Therapeutic effects of KH176 on gait were evaluated in the Ndufs4-/- mice model 4. Long-term treatment with KH176 significantly reduced walking speed variation, increased intensity of the hind limbs, and number of patterns. Furthermore, diagonal and lateral support values were normalized. This research indicates the ability of the CatWalk XT to sensitively and objectively assess gait abnormalities in Ndufs4-/- mice. CatWalk XT can be of great value in translational neuroscience, intervention studies, and drug development. Learn more about gait analysis. References - Koene, S., et al., (2018). Quantification of gait in children with mitochondrial disease. J Inherit Metab Dis, 41(4), 731-740. - Ramakers, R., et al., (2017). Quantification of gait in mitochondrial m.3243A > G patients: a validation study. Orphanet J Rare Dis, 12(1), 91. - Beyrath, J., et al., (2018). KH176 Safeguards Mitochondrial Diseased Cells from Redox Stress-Induced Cell Death by Interacting with the Thioredoxin System/Peroxiredoxin Enzyme Machinery. Sci Rep, 8(1), 6577. - de Haas, R., et al., (2017). Therapeutic effects of the mitochondrial ROS-redox modulator KH176 in a mammalian model of Leigh Disease. Sci Rep, 7(1), 11733. - Janssen, M.C.H., et al., (2019). The KHENERGY Study: Safety and Efficacy of KH176 in Mitochondrial m.3243A>G Spectrum Disorders. Clin Pharmacol Ther, 105(1), 101-111. - Koene, S., et al., (2017). KH176 under development for rare mitochondrial disease: a first in man randomized controlled clinical trial in healthy male volunteers. Orphanet J Rare Dis, 12(1), 163. - de Haas, R., F.G. Russel, and J.A. Smeitink. (2016). Gait analysis in a mouse model resembling Leigh disease. Behav Brain Res, 296, 191-198. Images courtesy of author Dr. Ria de Haas, Radboud Center for Mitochondrial Medicine, Nijmegen, The Netherlands --- ## How do children interact with their older autistic siblings? URL: https://noldus.com/blog/social-interactions-between-siblings Published: 2019-04-01 15:07:00 Description: In celebration of World Autism Awareness Day, this blog post focuses on the social interactions between children and their older autistic siblings. Autism has many faces, but all children with autism have one thing in common: they struggle to communicate with others. Making eye contact, sharing attention with others, and responding to social cues are just a few examples of social skills that children with Autism Spectrum Disorder (ASD) find difficult. They often do not know how to handle social situations. What are social skills? Social skills are the rules, customs, and abilities we use to communicate and interact with each other, both verbally and non-verbally, through gestures, body language, and our personal appearance. Human beings are sociable creatures, and we have developed many ways to communicate our messages, thoughts, and feelings with others. For children with autism, it can be harder to learn and build up these skills, forcing them to guess how to act in situations and with others. As a result, their social communication is often disrupted. A delayed and/or deviant language development plays a role in this as well. Social interactions between siblings During the first years of life, the social world mainly consists of interactions with caregivers and siblings. These interactions influence development. For example, siblings help each other to learn how to socialize, share, and deal with feelings. You might wonder how siblings whose older sibling has autism influence each other. Through observing, remembering, and imitating actions from their older sibling, children who have an older sibling with ASD (a so-called high-risk sibling) might learn ASD-specific behaviors. Do high-risk siblings interact differently? The study Chloè Bontinck and her team conducted, aimed to characterize the social interactions between 24-month-old high-risk siblings (HR) and their older siblings with ASD. They compared these HR sibling pairs with low-risk (LR) sibling pairs of 24-month-old LR-siblings and a typically developing older sibling (TD). They focused on three research questions: - Do sibling interactions differ between both groups? They expected lower levels of social interaction in HR sibling pairs compared to LR sibling pairs. - At which rate do HR siblings imitate their older sibling with ASD in comparison with low-risk controls? This is an important aspect of social learning. - Are the overall sibling interactions and the HR-sibling's current development related? In other words, do positive sibling interactions have a positive influence on social-communicative and language skills? Observing in a naturalistic environment Both HR- and LR-siblings were assessed at 24 months using four measures: the Mullen Scales of Early Learning (MSEL), the Dutch version of the MacArthur—Bates Communicative Development Inventory (N-CDI), the Autism Diagnostic Observation Schedule (ADOS-2), and the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Results indicated that HR-siblings showed lower scores in terms of language development and cognitive functioning, as well as a higher level of ASD characteristics. Additionally, the siblings were observed at home while playing together. Using different sets of toys, they were stimulated to play in a parallel, associative, and cooperative way. Parents were asked to only intervene when necessary. The play sessions were videotaped, and the researchers used The Observer XT to code the behaviors of both siblings. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Interaction during play By coding the behaviors, the researchers obtained different types of input. They collected data about the frequency of both negative and positive social interactions and responses, such as refusing a request or sharing a toy, and several aspects of the play itself. For example, these aspects included the distance between both children during the play (proximity), imitation of the other's behavior, the degree to which both children enjoyed the interaction together, and parental interference. Playing alone together The results of the study show that, in both groups, siblings spent 16-20% of the observed time in interaction with someone else: the sibling, parent, or researcher. Only 5% of the total play session was set as mutual interaction with the sibling. Just now and then, there were short instances of togetherness between both children. The children played on their own most of the time, even though they were sitting closely together. However, the researcher did find a difference between the two groups when it concerned the frequency of interactions. Siblings in the HR group interacted less frequently with each other. They showed lower levels of positive behavior compared to LR dyads, and were less likely to initiate social interaction or respond to the other sibling. Social learning In both groups, siblings did not imitate each other very often. However, it was remarkable that HR-sibs imitated their older sibling less frequently than LR-sibs during interactions. Since (positive) sibling interactions are an important aspect of social learning, younger HR siblings might miss opportunities to practice adequate social behaviors. However, the researchers note that the age of the children could be of influence in this case. Regarding the question of whether positive sibling interactions have a positive influence on social-communicative and language skills, the researchers found that even though positive interactions were less frequent in the HR group, these positive exchanges appeared to benefit the language development of HR-sibs. If you are looking for other topics related to autism, you can surely find it on our behavioral research blog! Want to stay ahead in behavioral research? Subscribe to Noldus Newsline now! You will receive expert insights and the latest innovations, straight into your inbox every month. Reference Bontinck, C.; Warreyn, P.; Demurie, E.; Bruyneel, E.; Boterberg, S. & Roeyers, H. (2018). Social Interactions Between 24-Month-Old Children and Their Older Sibling with Autism Spectrum Disorder: Characteristics and Association with Social-Communicative Development. Journal of Autism and Developmental Disorders, 48 (12), 4118-4137. https://doi.org/10.1007/s10803-018-3660-4 --- ## Serious gaming reduces anxiety in children URL: https://noldus.com/blog/serious-gaming-reduces-anxiety-children Published: 2019-03-22 10:58:00 Description: What is the effectiveness of the applied game called MindLight in teaching children how to cope with anxiety? Wols et al. investigated this game-based intervention. Anxiety disorders are among the earliest and most prevalent forms of psychopathology in children. Currently, treatments based on cognitive behavioral therapy (CBT) are considered the most effective in reducing anxiety symptoms. Wanting to improve the way CBT techniques are taught to children, researchers investigated the effectiveness of an applied game called MindLight. Using applied games to treat anxiety With studies on CBT showing mixed outcomes and small to moderate effect sizes, researchers hypothesized that teaching methods are important in determining treatment success. For example, not all children are engaged or motivated by the didactic-based approach that is often used in treatment. Clinicians may also deviate from protocols, resulting in varying approaches to CBT. Lastly, children may not have enough opportunities to put the knowledge they learn into practice. Game-based interventions may be the answer. Teaching children how to cope with anxiety using MindLight Designed to be playful and to provide ample opportunity for practice, MindLight is an applied game that incorporates three evidence-based CBT techniques. The first, relaxation through neurofeedback training, uses real-time electroencephalogram (EEG) recordings to promote relaxation. The game also includes exposure training, which encourages individuals to approach fearful events. Lastly, attention bias modification (ABM) helps to focus one's attention from negative to more positive stimuli. In the game, the player needs to move through grandma's dark and decrepit mansion to save her from evil forces. To do so, he/she needs to chase away or uncover "fear events" (exposure) and solve puzzles (ABM). To help them move through the dark, players can use their "mindlight", which shines brighter when they relax (neurofeedback). To complete the game successfully, children need to display engaged behaviors and suppress avoidant/safety behaviors. Reducing anxiety symptoms with MindLight To examine the effectiveness of MindLight in treating anxiety symptoms, the researchers studied in-game behaviors and anxiety symptoms in 43 children with elevated levels of anxiety (ages 8 to 12). All participants completed six sessions of MindLight, with a total gameplay of approximately six hours. They filled out the Spence Children's Anxiety Scale (SCAS-C) two weeks before participation, as well as several times after completing the intervention. The researchers hypothesized that higher pretest anxiety scores would be related to less engaged and more avoidant/safe in-game behaviors during the first session. They also predicted that increases in engaged behavior and decreases in avoidant/safety behaviors would be associated with reduced anxiety symptoms at a three-month follow-up measurement. Measuring child behavior: behavioral analysis software and video annotation Each in-game behavior was classified as either "engaged" or "avoidant/safe." For example, when a child encounters a monster, he/she can approach it to uncover it or chase it away (engaged). Other options include hiding in a chest or turning on a ceiling light (avoidant/safe). All on-screen behavior was videotaped using Fraps and coded with The Observer XT. Observational codes were based on the MindLight Coding System (MCS-II). To control for differences in duration of play-sessions, behaviors were transformed to proportions or frequencies per minute. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Child behavior during the game predicted real-world outcomes Contrary to predictions, pretest measurements of anxiety symptoms were not related to behaviors during the first play-session. The researchers argue that these results may be due to limited variation in anxiety levels between participants. Another explanation may be that the first session was highly standardized, leaving little room for variation in behaviors. However, results of the study did indicate that developments in in-game behaviors predicted changes in anxiety symptoms. Specifically, both increased engaged behaviors and decreased safety/avoidant behaviors in the game were associated with reduced anxiety symptoms at a three-month follow-up measurement. These results, as well as outcomes from similar studies, show that applied games are successful in delivering CBT techniques to children with anxiety symptoms. With the added possibilities of easily tailoring and personalizing treatments, game-based interventions are very promising in the further development of treatments for these disorders. Interested in human behavior research? Read more on 'How to study human behavior'! Reference Wols, A.; Lichtwarck-Aschoff, A.; Schoneveld, E.A. & Granic, I. (2018). In-Game Play Behaviours during an Applied Video Game for Anxiety Prevention Predict Successful Intervention Outcomes. Journal of Psychopathology and Behavioral Assessment, 40 (4), 655-668. --- ## Zebrafish help us to understand neurodegenerative and neuromuscular diseases URL: https://noldus.com/blog/zebrafish-neurodegenerative-diseases Published: 2019-03-20 15:58:00 Description: Teresa Capriello and colleagues use zebrafish to study the neuronal mechanisms of heavy metals in connection to neurodegenerative and neuromuscular diseases. Swimming against the stream: zebrafish help us to understand neurodegenerative and neuromuscular diseases like Parkinson's Teresa Capriello and colleagues from the University of Naples 'Federico II' have found something fishy about the effects of cadmium and aluminum on behavior. The team uses zebrafish to study the neuronal mechanisms of these heavy metals in connection to neurodegenerative and neuromuscular diseases. Zebrafish are increasingly used as a model for neurotoxic effects because the neuropathological behavior is relatable to that shown in humans. Uncontrolled movements are typical in human patients with Parkinson's. We will see that the fish in this study seem to show similar behavior. Cadmium and aluminum are neurotoxins Accumulation of cadmium and aluminum in the environment is a risk factor for the development of neurodegenerative diseases such as Parkinson's and Alzheimer's (Chin-Chan et al., 2015; Jomova et al., 2010). Since the modes of action of these heavy metals are not completely understood yet, they are subject to many studies. The neurotoxic mechanisms of aluminum are still especially unclear. Shedding more light on neurotoxicity with zebrafish research In previous studies, the team in Naples showed some neurotoxic effects of cadmium and aluminum in adult zebrafish during embryological development. The objective this time was, therefore, to find out more by studying the behavior of larvae. Controlled circumstances for zebrafish larvae with DanioVision The researchers studied both hatching rate and swimming ability. The motility of the larvae – both in the chorion and after hatching – was captured with DanioVision and analyzed with EthoVision XT software. To represent swimming ability, the parameters measured were distance moved, mean velocity, cumulative movement, heading, and meander. The larvae were exposed to increasing levels of cadmium and aluminum. The larvae were placed in the observation chamber and kept individually in 96 well plates. Their motor activity was monitored for 72 hours, until 78 hours after hatching. In order to eliminate bias, the researchers performed the experiment three times, while keeping a steady temperature and giving the larvae 10 minutes to adapt to the light in the observation chamber. FREE DEMO Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free Demo Low frequency of spontaneous movements delays hatching Hatching rate was lower in all treatments in comparison to the control group. The hypothesis was that the low frequency of movements in the chorion delayed the hatching process. For cadmium, the rate decreased with increasing levels of exposure, consistent with other results. For aluminum, more larvae hatched when exposed to higher doses. As we will see in the following behavioral results, the dose-response pattern repeated itself for almost all parameters, suggesting a similar underlying mechanism. Sluggish and uncontrolled behavior Exposure to cadmium and aluminum showed a clear detrimental effect on all measured motility behaviors. The interesting thing was the change in behavior for different doses of the metals. For cadmium, the effects were dose-dependent, with the larvae becoming increasingly lethargic with increasing doses. The larvae covered less and less distance, at a lowering speed and they didn't swim in one direction from the center anymore. Following that trend, these zebrafish also showed increasingly uncontrolled behavior (meander) with increased doses. In contrast, the fish exposed to aluminum took a different route (pun intended). Their behavioral parameters all showed the opposite effect of cadmium exposure, increasing their motility with increasing doses of aluminum. Researchers suggested this might be a recovery of swimming ability. There was one exception, however: meander. Exposed to 200µM AlCl3, the movements of the larvae became increasingly uncontrolled – like with cadmium, they meandered more. Does the dose make the poison? According to the authors, this was the first time abnormal behavior of larval zebrafish to cadmium and aluminum has been compared. The contradicting results on motility prompted the researchers to formulate a new hypothesis; low levels of metal do not fully activate 'protective mechanisms,' thereby allowing extensive but not lethal damage. Next to that, the increased uncontrolled movements of the larvae exposed to high levels of aluminum are considered important, because uncontrolled movements are typical of neurologic pathologies like Parkinson's disease. The zebrafish will be back The authors emphasize that the mechanisms are still largely unclear. They do suggest there might be something interesting in the connection between the behavior seen in this study and the workings of the cholinergic system, affecting locomotor activity. The story doesn't end here. Lots of new questions have arisen and extra research is needed into the behavior of the zebrafish larvae exposed to cadmium and aluminum. It will contribute to a bigger understanding of the mode of action of these neurotoxins. References - Capriello, T.; Consiglio Grimaldi, M.; Cofone, R.; D'Aniello, S.; Ferrandino, I. (2019). Effects of aluminium and cadmium on hatching and swimming ability in developing zebrafish. Chemosphere, 222 (2019), 243-249. - Chin-Chan, M.; Navarro-Yepes, J.; Quintanilla-Vega, B. (2015). Environmental pollutants as risk factors for neurodegenerative disorders: Alzheimer and Parkinson diseases. Frontiers in Cellular Neuroscience, 9, 124. - Jomova, K.; Vondrakova, D.; Lawson, M.; Valko, M. (2010). Metals, oxidative stress and neurodegenerative disorders. Molecular and Cellular Biochemistry, 345 (1e2), 91e104. --- ## A closer look at eye contact URL: https://noldus.com/blog/closer-look-eye-contact Published: 2019-03-19 15:53:00 Description: Infant siblings of children with or without ASD participated in a study to determine whether gaze behavior showed during a test with an unfamiliar examiner could predict gaze behavior in a more naturalistic context. "Eyes are the mirrors of the soul," the saying goes. Therefore, to make eye contact can be extremely valuable. Through eye contact, you can recognize emotions, intentions, self-assurance, weaknesses and more information in addition to the normal communication that usually exists. Feeling uncomfortable when making eye contact Making eye contact is an important skill infants develop during the first year of life. However, when infants show atypical social-communicative behavior, this may serve as a marker of autism spectrum disorder (ASD). Reduced eye contact is a known symptom of autism. However, why children with autism look less at the eyes of others is unknown. There are several possible explanations; perhaps they avoid eye contact because they find it stressful and annoying to look someone else in the eye. Or, maybe they do not consider the social indication that eye contact can be important and they don't see the point of it. However, autism is heterogeneous, so some individuals with autism may be indifferent to eye contact, whereas others may experience it as unpleasant. FREE WHITE PAPER Autism research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Get your copy instantly Research in different interactive contexts A lot of research has been done to assess social-communicative behavior in a single interactive context, for example during play with a parent, or interactions with examiners in structured settings. The team of researcher Gangi examined prospectively infant gaze behavior at 6, 9, and 12 months of age in infants who were later diagnosed with ASD, as well as low- and high-risk infants without autism spectrum disorder outcomes. They investigated whether gaze behavior was associated across two interactive contexts: - 1.Structured testing with an unfamiliar examiner - 2.Semi-structured play interaction with a parent The intention was to determine whether the behavior that infants showed during context 1 did in fact predict behavior in a more naturalistic context, with familiar people. Parent-child play interaction Infant siblings of children with ASD (high-risk siblings) or without ASD (low-risk siblings) participated in the study. At 36 months of age, ASD outcome was determined for all participants, who were classified as either ASD or not ASD. For analysis, the researchers arranged the participants into one of three groups: a low-risk non-ASD group (n = 53), a high-risk non-ASD group (n = 66), and an ASD group (n = 17). To measure the cognitive functioning of the infants, the Mullen Scales of Early Learning was filled in at each visit by an unfamiliar examiner. Meanwhile, infant gaze to the examiner's face was recorded. Also, a 3-min play interaction with a parent took place, using toys and following the instructions to play together as they normally would at home. Lastly, the ADOS-2, part of the international gold standard for diagnosing autism, was used to provoke various communicative and social behaviors in a standardized manner. Coding gaze behavior The researchers coded gaze behaviors, as in gaze to the face, during the first 6 minutes of the Mullen test and during the 3-min parent–child play interaction using The Observer XT. Different camera angles provided clear views of both the infants' and the parents' faces. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Infants that were 9 months old with higher levels of gaze to the face of an examiner during structured testing also had higher levels of gaze to the face of the parent during a play interaction. Therefore, gaze behavior in context 1 predicted gaze behavior in context 2. By 12 months, infants without ASD outcomes exhibited higher mean rates of gaze to faces during parent–child play than during the Mullen test, while the gaze behavior of the ASD group did not differ by context. This suggests that infants developing autism spectrum disorder may be less sensitive to context or interactive partners. The associations found in this study support the validity and use of observing social-communicative behavior with an examiner, a setting in which the gaze behavior of children with ASD or at risk for ASD is frequently tested. References Gangi, D.N.; Schwichtenberg, A.J.; Iosif A.-M.; Young, G.S.; Baguio F. & Ozonoff, S. (2017). Gaze to faces across interactive contexts in infants at heightened risk for autism. Autism: the international journal of research and practice. (00), 1-6. https://doi.org/10.1177/1362361317704421 --- ## 5 blog posts about brain research URL: https://noldus.com/blog/brain-research Published: 2019-03-11 15:34:00 Description: During the annual Brain Awareness Week, international attention focuses on the brain to increase public awareness of the progress and benefits of brain research. During the annual Brain Awareness Week (BAW), international attention focuses on the brain to increase public awareness of the progress and benefits of brain research. Some key questions are as follows: How does the brain work? How does a disorder of the brain develop? What is the importance of neuroscience research? Celebrate brain awareness There are a wide variety of brain disorders, and they can occur at any age. Alzheimer's disease, brain cancer, epilepsy, Parkinson's disease, cerebral palsy, Huntington's disease, and mental disorders are just a few examples. Practically everyone knows someone in his or her surroundings who is familiar with a brain disorder. However, we do not always consider the impact of these diseases upon a person's life. During BAW, events and educational activities will take place to change that. For example, there are lectures on brain-related topics, open days at neuroscience laboratories, brain fairs with hands-on activities, games, and experiments, displays at malls, libraries, and community centers, classroom workshops, and social media campaigns, to name a few. Research in the brain sciences A lot of research is done and is still occurring in the field of the brain. For example, neurobehavioral studies which are carried out with the help of rodents and zebrafish. 5 blog posts about brain research Brain research often addresses topics such as learning and memory, processing information and the ability to recall, effects of brain damage, locomotion, novel object recognition, and fear conditioning. The five highlighted blog posts about the brain or brain disorders contain these mentioned topics. Just read along with me: - Assessing motor deficits in mice following Traumatic Brain Injury. While animal models have been remarkably successful in furthering our understanding of Traumatic Brain Injury (TBI), an assessment of subtle motor deficits in mouse models that arise post-injury can be challenging. In this blog post, we'll outline some of the common tests currently used by researchers to assess motor deficits in mice following TBI, and give you a basic understanding of the protocols used for these tests. - Parkinson's disease research – relevant measures in pre-clinical studies. Slow movement, shuffling of the feet, and difficulties initiating movement are all impairments we recognize as typical for Parkinson's disease. Researchers are always trying to find new therapeutics, and an important aspect for the translational value of these studies is measuring relevant behaviors in animal models. - Isolated and stressed zebrafish as a model for major depression. Depression is not easy to model in animals, as we cannot really determine if a rat has low self-esteem or if a zebrafish is suicidal. But that doesn't mean researchers haven't found other behaviors to characterize depression-like symptoms in animals, and several – sometimes very successful – models have been developed to study this disease. - How sleep heals the brain. Sleep helps us to process what we have learned, to let our nervous system function properly, and to concentrate during the day. Now researchers have proven that it can heal the brain. The question is, how? - Spatial and odor memory impaired mice – new model for Alzheimer's. Plaques and tangles… those of you even remotely familiar with Alzheimer's disease (AD) will immediately recognize these hallmarks. Many rodent models, focusing on plaques and tangles, have been developed to explore the cause and possible treatments of AD, and much progress has been made. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial Unravel the brain Brains are complicated. We all know that. They are kind of like an entangled bunch of wires. Still, over the years, neuroscientists have been able to map out several brain regions and their functions in behavior and physiology. So let's keep on supporting brain research and, for now, let's celebrate brain awareness. If you are still looking for other topics related to brain research, you can surely find it on our behavioral research blog! Want to stay ahead in behavioral research? Subscribe to the Noldus Newsline now. You will receive expert insights and the latest innovations, straight into your inbox every month. --- ## Shopping behavior - what can we measure in a retail environment? URL: https://noldus.com/blog/shopping-behavior Published: 2019-03-08 13:51:00 Description: Shopping ambience conditions such as light, sound, and smell are thought to affect shoppers’ browsing behavior and can increase sales due to impulse buying. Today we have a blog post written by Tamara Reid. During her internship at Noldus she investigated the applications of TrackLab software in the consumer market. Enjoy reading! Shopper movements, sales, and the effects of light, sound, and smell (in a supermarket) Shopping ambience conditions such as light, sound, and smell are thought to affect shoppers' browsing behavior and can increase sales due to impulse buying. Insights into shopping ambience conditions and shopping behavior are beneficial not only to marketers, but also to store owners. Studies are increasingly showing that shopping behavior is not clear-cut rational behavior. A great deal of purchases are based on impulsive and unconscious decision-making. Previous studies on shopping behavior With the recent development in sensor technology such as RFID tags, studies on shopper movement patterns are more available. However, these are mostly limited to studies on the movement of shopping carts between the aisles in a store. Monitoring shopping behavior in more detail A recent study (de Wijk et al., 2017) monitored shopping behavior in more detail in a supermarket. The focus of the tracking were the shoppers and not their carts, and their movements were analyzed using stereo cameras placed around individual shelves rather than aisles. Since shelves need to be visited before a sale is made, it is then logical to assume that the number of visits to a shelf correlates positively to the number of sales. This is a debatable topic and seems to vary depending on product assortment. There are other reasons a shopper might be in front of a shelf other than to make a purchase. Three shopper personas were identified in the study: - The "passing through" shopper- This shopper passes by a shelf on the way to another shelf or aisle. These visits are short with high acceleration, and have none or minor directional changes. For these shoppers, the conversion rate to a sale is low. - The "exploratory" shopper- This shopper requires an initial browsing stage in front of the shelves before making a purchase. These are usually longer visits with frequent direction changes, acceleration, and deceleration. For these shoppers, the conversion rate to a sale is higher. - The "determined" shopper- This shopper enters the aisle and approaches a shelf, decelerates to a standstill, picks up an item, changes direction, and accelerates away from the shelf. These visits are also short, but the conversion rate to a sale is high. Shopper behavior and conversion rates also vary with product assortment. For instance, in the fresh produce section there can be visits with longer duration and frequent directional changes because the shopper is surveying the freshness of the fruit before making a purchase. Ambient effects used to influence shopping behavior The study also looked at the effects of light conditions, sounds, and smells on shopper movement patterns and the sales of fruits, wines, and coffee in a medium size supermarket in Oosterbeek, the Netherlands. The supermarket had the typical layout of fruits at the entrance and wine and coffee at the back sections. Suitable lighting, scents, and sounds were put in place for each section. - Scent - The fruit section had a "fresh citrus" scent, the wine area had a "warm wood" naturalistic scent, and the coffee section had a cappuccino scent. - Sound - Natural sounds (birds tweeting) were selected for fruit, classical music for wine, and pop-jazz for coffee. - Lighting - The fruit section had fixtures mimicking daylight, LED light was used to illuminate the wine section, and a LED spotlight was used for the coffee area. Tracking technology The multiple shopper movement patterns were recorded with stereo cameras mounted on the ceiling (EagleEyes, Eagle Vision Systems B.V., Naarden, the Netherlands). These cameras generated tracks per shopper that were stitched together in a software system (Eagle Area Monitor, Eagle Vision Systems B.V., Naarden, the Netherlands). The tracks were then displayed on a floorplan map of the supermarket and analyzed using a software system for the recognition and analysis of spatial behavior (TrackLab, Noldus Information Technology, Wageningen, the Netherlands). In the TrackLab software, the areas of interest were defined (fruit, wine, and coffee) and the relevant statistics were computed: visit frequency, duration, speed, and directional changes (in degrees). Interested in the technology? FREE DEMO Try TrackLab yourself! Request a demo to obtain real-time insights into a wide range of spatial behaviors. - Accurate tracking data - Gain insights into consumer behavior - Easily access, export, and analyze data Free Demo This was all done over an 18 week period with 3 sub periods dedicated to the effects of scent, sound, and lighting conditions. Shopping behavior and sales During the course of the study, the wine section of the supermarket had the most average daily visits but also the lowest average number of sales (#visits per sale 41.2). This is possibly explained by just looking – not buying behavior (which is typically Dutch by the way), or because shoppers were just "passing through" the wine test area to reach other aisles. Fruits had the lowest average visits, but the highest daily number of sales (#visits per sale 3.7). This is indicative of the average visitor being a "determined shopper" or that fruits tend to be purchased in larger quantities. With these results, the visit frequency only correlated positively with sales for the fruits and coffee sections. The speed of travel through the different sections were relatively the same. Directional changes occurred more in the fruit sections of the supermarket, followed by coffee and then wine. It seemed that directional changes were inversely related to visit duration. Directional changes occurred more during short visits. The study concluded that movement patterns correlated more to sales than the number of visits. Effects of light, sound, and smell "Rome wasn't built in a day…" The ambience conditions used showed little effect on shopper behavior and sales. Minor effects on the speed of shoppers in the wine and coffee sections were observed depending on the type of ambience condition. Wine sales also experienced marginal changes as a result of the number of directional changes caused by conditions. The presence of light, sound, and smell did not affect visit frequency, duration, and sales for either of the test product categories. Store managers and marketers deploy many strategies to stimulate store traffic and sales, but their efforts may not be entirely in vain. A broader study of shopping ambient conditions and product categories can produce different results. Less localized ambient conditions may prove more effective, as would a study of ambient conditions in supermarkets in different locations. References De Wijk, R.A. (2017). Supermarket shopper movements versus sales and the effects of scent, light, and sound. Food Quality and Preference. doi:10.1016/j.foodqual.2017.03.010 --- ## Parkinson's disease research - Relevant measures in pre-clinical studies URL: https://noldus.com/blog/parkinsons-disease-research Published: 2019-03-05 11:52:00 Description: Parkinson’s disease: the neurodegenerative disorder that affects mobility in a life-changing way. Learn more about relevant measures in pre-clinical studies. Parkinson's disease: the neurodegenerative disorder that affects mobility in a life-changing way. Slow movement, shuffling of the feet, and difficulties initiating movement are all impairments we recognize as typical for this disease. Researchers aim to find new therapeutics, and an important aspect for the translational value of these studies is measuring relevant behaviors in animal models. Another focus of Parkinson's research is the side-effects of current drugs such as levodopa. Parkinson's symptoms in animal models Though gait impairment is one of the most prominent symptoms of Parkinson's disease (PD), it is not always that well investigated. Researchers (1) at the Southern Medical University (China) argued that you need to be able to examine symptoms in detail before learning how to treat them. So, they created different rat models for PD and compared their locomotion to clinical symptoms in human patients. For this, they used the CatWalk XT system. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources This resulted in a rat PD model with clinically relevant behaviors. Where Parkinson's patients take small slow steps, these rats showed in increase in stance, step cycle, and duty cycle. The increase of the terminal dual stance in limbs in the rats could be translated to the delays or freezing of gait, or gait hesitation as seen in patients. Read more about this study here. Assessing relevant behaviors for Parkinson's disease studies A more recent study posed a similar question: why do most commonly used behavioral tests in animal research on PD not actually assess behaviors that resemble these symptoms? At the University of Auckland in New Zealand, researchers (2) used two rat 6-OHDA lesion models of PD to investigate a number of gait parameters with CatWalk XT in hopes of finding a resemblance to human PD symptoms, and more specifically finding them early on. They found gait analysis to be a reliable method for the detection of motor deficiencies relevant to PD. Particularly, it allowed for early detection, some as early as one week after the lesion was applied. Read about it in this blog post. Ataxia and cerebellar functioning in Parkinson's studies After discussing two studies that looked at gait impairments, let's look at ataxia. A specific form of gait impairment, ataxia is the incoordination of movement that can be the consequence of compromised cerebellar functioning. The cerebellum, or our "little brain," is therefore an important focus in many Parkinson's studies. Researchers (3, 4) at the Erasmus MC (The Netherlands) studied the role of several cerebellar cell types in motor learning, locomotor adaptation, motivation, and avoidance behavior using several knock-out mouse strains. They used the ErasmusLadder to run these tests, and it proved to be a sensitive way to test for cerebellar functioning. Read about these studies here. RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Studies on the effect of typical L-DOPA treatment A large part of Parkinson's studies focus on the long-term effects of L-DOPA, or levopoda, a common clinical treatment for PD with which many patients struggle. In one example, researchers (5) studied the influence of L-DOPA on the binding of dopamine to its receptor in relation to motor and exploratory behavior in rats, using an open field set-up PhenoTyper) and EthoVision XT video tracking software. More drugs led to a higher dopamine release, and in turn to less activity. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial In a second example, researcher (6) investigated the link between the long-term side effects of L-DOPA treatment: dyskinesia and motor fluctuations. Rats were subjected to an open field test, during which their activity was video tracked with EthoVision XT. Specific measures included distance moved, velocity, and full rotation frequencies. While there was no correlation found, the researchers observed an interesting L-DOPA withdrawal effect, with motor performance being worse after the treatment than before the start of the treatment. Research suggests that different neural mechanisms underlie these two long-term effects of L-DOPA usage. Read more about these studies in this blog post. References Read more about behavioral and functional research on ataxia and cerebellar functioning: Ataxia and cerebellum research - 1.Zhou, M.; Zhang, W.; Chang, J.; Wang, J.; Zheng, W.; Yang, Y.; Wen, P.; Xiao, H. (2015). Gait analysis in three different 6-hydroxydopamine rat models of Parkinson's disease. Neuroscience Letters, 584, 184-189. - 2.Boix, J.; von Hieber, D.; Connor, B. (2018). Gait Analysis for Early Detection of Motor Symptoms in the 6-OHDA Rat Model of Parkinson's Disease. Frontiers in Behavioral Neuroscience, 12, 39. - 3.Galliano, E.; Gao, Z.; Schonewille, M.; Todorov, B.; Simons, E.; Pop, A.S.; D'Angelo, E.; Maagenberg, A.M.J.M.; Hoebeek, F.E.; De Zeeuw, C. (2013). Silencing the Majority of Cerebellar Granule Cells Uncovers Their Essential Role in Motor Learning and Consolidation. Cell Reports, 3, 1239-1251. - 4.Vinueza Veloz, M.F.; Zhou, K.; Bosman, L.W.J.; Potters, J.-W.; Negrello, M.; Seepers, R.M.; Strydis, C.; Koekkoek, S.K.E.; De Zeeuw, C.I. (2014). Cerebellar control of gait and interlimb coordination. Brain Structure and Function, doi: 10.1007/s00429-014-0870-1. - 5.Nikolaus, S.; Beu, M.; De-Souza-Silva, M.A.; Huston, J.P.; Hautzel, H.; Chao, O.Y.; Antke, C.; Müller, H.W. (2014). Relationship between L-DOPA-induced reduction in motor and exploratory activity and degree of DAT binding in the rat. Frontiers in Behavioral Neuroscience, 8(431), doi: 10.3389/fnbeh.2014.00431 - 6.Sgroi, S.; Kaelin-Lang, A.; Capper-Loup, C. (2014). Spontaneous locomotor activity and L-DOPA-induced dyskinesia are not linked in 6-OHDA parkinsonian rats. Frontiers in Behavioral Neuroscience, 8(331), doi: 10.3389/fnbeh.2014.00331 --- ## PCIT: Parent-Child Interaction Therapy URL: https://noldus.com/blog/pcit-parent-child-interaction-therapy Published: 2019-02-28 12:24:00 Description: What is Parent-Child Interaction Therapy? It helps improve family dynamics by working to reduce negative behavior and interactions, and to practice new behaviors and ways of communicating that are more encouraging. Parent-Child Interaction Therapy (PCIT) is an evidence-based treatment program for children with emotional and behavioral problems and their parents. The program aims to improve the quality of the parent-child relationship, and to change parent-child interaction patterns. As a result, both the child's behavioral problems and parents' stress level are reduced. PCIT improves parent-child relationships To start, parents in this treatment program learn more about the relationship enhancement and discipline skills that they will be practicing in therapy sessions in an observation lab and at home with their child. PCIT includes a combination of play therapy and behavioral therapy. PCIT helps improve family dynamics by working to reduce negative behavior and interactions, and to practice new behaviors and ways of communicating that are more encouraging and reassuring. When practiced consistently, these new skills and techniques can instill more confidence, reduce anger and aggression, and encourage better individual and interactive behavior in both parent and child. FREE WHITE PAPER Parent-child interaction This free white paper informs you how to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly Conducting research on parent-child interactions Early in life, children are not capable of filling out a complete questionnaire or talking to an interviewer. In that case, observing behavior can provide valuable information in combination with parental interviews. Several of our customers have focused their research on parent-child interactions. They performed their studies in either a laboratory setting or a natural setting, such as a family home, to measure the behavior of the parents and their children. In both settings, the researchers recorded the interactions on video and coded behaviors in detail. By using video recordings, researchers did not lose any information and were able to replay the same scene as often as needed. FREE WHITE PAPERS How to build a research lab Do you want to learn more how to set up a research lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download 3 free 'how to' guides! Submit to download In-home video recordings provide accurate measure For example, Lisa Edelson and colleagues from the Nestlé Research Center in Sweden studied how parents' prompts to eat fruits and vegetables relate to children's intake of these foods. The research team studied videos taken in an in-home setting. By using portable recording devices, the researchers were able to observe the parent-child interactions in natural settings without the disruptive influence of having observers physically present in the room. The study showed that parents who gave neutral prompts such as 'eat your peas' or 'try your hot dog' with a neutral or positive tone of voice were most successful. Teaching parents to use new parenting skills The key to successful interventions is the use of modifiable parenting practices. In the randomized controlled study by Montaño et al., researchers examined the relationship between positive behavior support (PBS) and dietary quality of the meals served to children between the ages of two and five years old, a critical period for the development of a dietary lifestyle. Part of the study consisted of observing parent-child interaction while carrying out various tasks, including free play and cleaning up, followed by meal preparation. The main purpose of the study was assessing parenting behavior. Ways to support parent-child interaction Researchers at the University of Wisconsin-Madison, USA, conducted a study to explore the frequency and characterize the purpose of props used during mealtimes with children with autism. Props are items that support child participation during mealtime, such as toys, typically child-friendly items, or common household objects. Mealtime videos were uploaded into The Observer XT. Hereby, coders were able to review, visualize, and independently code observational data in the coding software. The study showed that props such as toys could help to calm a child and provide comfort, or support the child's focus. In some families, props were also used as a reward to reinforce positive eating or mealtime behavior. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Encouraging more parent-child joint talk The need to observe parent-child interactions in natural settings has been stressed by many researchers. An exhibit designed specifically for children is therefore ideal as a research setting. The team from Loyola University in Chicago chose a museum as the setting for their experimental and observational research. They examined the effects of parent-child conversation and object manipulation on children's learning, transfer of knowledge, and memory of the exhibit. The invention resulted in more parent-child joint talk. Although children can learn a great deal on their own, conversations with parents have a big influence on the content, recall, and transfer of what they learn. Behavioral Research Blog | Noldus In this blog post, I have highlighted a number of studies conducted by some of our customers. These studies focused mostly on mealtime behaviors. If you are interested in reading more or about different topics, please have a look at our Behavioral Research Blog, or find some interesting publications in the list below. References Dishion, T.J.; Mun, C.J.; Drake, E.C.; Tein, J.Y.; Shaw, D.S. & Wilson, M. (2015). A transactional approach to preventing early childhood neglect: The Family Check-Up as a public health strategy. Development and Psychopathology, 27, 1647-1660. Talbott, M.R.; Nelson, C.A.; Tager-Flusberg, H. (2013). Maternal Gesture Use and Language Development in Infant Siblings of Children with Autism Spectrum Disorder. Journal of autism and developmental disorders, 1-11. Thomassin, K.; Suveg, C. (2014). Reciprocal positive affect and well-regulated, adjusted children: A unique contribution of fathers. Parenting: Science and Practice, 14 (1), 28-46. Weisman, O.; Zagoory-Sharon, O.; Feldman, R. (2014). Oxytocin administration, salivary testosterone, and father-infant social behavior. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 49, 47-52. --- ## How botulinum toxin affects facial expression URL: https://noldus.com/blog/how-botulinum-toxin-affects-facial-expression Published: 2019-02-25 14:59:00 Description: For the past twenty years, the demand for cosmetic procedures to the face has increased drastically. New technologies have become available that make it possible to look ‘better and younger’. For the past twenty years, the demand for cosmetic procedures to the face has increased drastically. New technologies have become available that make it possible to look ‘better and younger’. In particular, the use of botulinum toxin (BTX) has increased enormously. BTX treatments increasingly popular The number of BTX treatments in the USA increased from 65 thousand in 1997 to more than 4.5 million in 2016. This increase is also reflected in my own medical-cosmetic practice in the Netherlands. The taboo on the use of BTX is beginning to disappear and more and more people want to have their appearance improved. However, they are also afraid to “lose themselves”: While eager to be treated, many clients stress that it should look natural and they don’t want anyone to notice that they had something done. But what makes a face look unnatural after BTX injections? How botulinum toxin affects facial expression Botulinum toxin (BTX) works against wrinkles, but few people realize that it also profoundly affects our facial expressions. Facial expressions are important for interpersonal communication, but also for feeling and expressing emotions. More and more people at ever younger ages are using BTX. This increase in BTX use could therefore have consequences for our society. Will we still understand one another if we can no longer fully utilize our facial expressions in non-verbal communication? Revealing the impact on human communication To gain insight in what makes a face appear unnatural after BTX and to reveal the impact on human communication, I filmed myself making 18 facial expressions before and after having undergone full facial BTX injections. I noticed how difficult it is to show anger when you can’t frown, or disgust when you can’t depress the corners of your mouth. It felt difficult to experience the emotion that was part of the expression after having the BTX injections. It was almost like I felt less positive when I smiled (Smile like you mean it) Full facial botulinum toxin treatment. I received injections with botulinum toxin in multiple facial muscles (red dots). I used Facial emotion reading software (FaceReaderTM) to interpret the facial expression before and after the botulinum toxin injections. Note the differences! Here you find an example of the expression of disgust in which normally the corners of the mouth are depressed (face on the left side). Because of the absence of this movement the FaceReader interprets this facial expression as ‘Neutral’ instead of ‘Disgusted’ in my face after the BTX injections (right side). Here you find an example of a genuine smile (in which normally the muscle around the eye contracts and forms wrinkles). Because of the paralyzing effect of BTX, the muscles around the eyes cannot contract. A magnification of this remarkably different feature is highlighted in the circles on the right. Notice that the software doesn’t detect the absence of the contraction around the eye; it rates both expressions as ‘happy’. In human interpretation, this feature makes a very important difference between a real and a ‘fake’ smile. To see a video of the above shown 'before and after' facial expression analysis, you can visit the website of Project Face Design. Outcomes and conclusion The recordings show a clear difference before and after botulinum toxin. This difference is most evident in the expressions where the corners of the mouth should be pulled down, where there should be frowning and where the eyebrows should be pulled up. The experiment also shows that human judgment is still different from that of a computer. While the FaceReader algorithms can’t tell a real (so called ‘Duchenne’) smile from a fake one, the difference can easily discerned by the human eye, most notably from the wrinkling of the skin around the eyes. This wrinkling is no longer visible after BTX – clearly making the smile less sincere. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download For many expressions however, particularly for the cases of fear, anger, surprise and disgust, the FaceReader algorithms return markedly different scores before and after BTX treatment, and these scores generally match those as assessed by the eye. During this experiment I was very aware of what happened to my face in terms of movement and communication after the injections with botulinum toxin. When I had to express my emotions, I found it very difficult to make certain faces, such as the face that belongs to the expression ‘I do not know’. Because my face did not co-operate, it was as if there was a link missing in the chain that normally makes my brain understand what I should do. I actually needed the ‘before’ photographs of the 18 depicted expressions to support me in reproducing these expressions after BTX treatment. By delving deeper into this surprising fact about BTX use, we may become more aware of possible future consequences of long-term and large-scale use of BTX. Armed with this knowledge we may be able to make more conscious choices about what to do, and more importantly what not to do, to our faces. Marsha Wichers (1980) is cosmetic doctor and visual artist, specialized in sculpture. She works and lives in the Netherlands. Marsha: “I work on people’s faces in my medical-cosmetic practice, and what I see as a doctor fascinates and inspires me as an artist. I use botulinum toxin to treat wrinkles, but its profound effect on facial expression made me curious of the effect on human communication. I decided to use my own face as a testcase for an analysis with the FaceReader after having ondergone full facial botulinum toxin injections”. Website: www.marshawichers.nl --- ## Alzheimer's research - From prevention research to natural treatment URL: https://noldus.com/blog/alzheimers-research-prevention Published: 2019-02-15 15:01:00 Description: Experts estimate that by 2050, 100 million people will have Alzheimer’s disease (AD), which is a shockingly large number. Learn more about the research that has been done in order to find a cure. Experts estimate that by 2050, 100 million people will have Alzheimer's disease (AD), which is a shockingly large number. Although a lot of research has been done, researchers still haven't been able to find a cure. Our Behavioral Research Blog regularly highlights Alzheimer's research. Check out these four blog posts! Alzheimer's hallmarks and symptoms Those of you familiar with Alzheimer's research know about the plaques and tangles. The beta amyloid plaques between neurons and tangles of tau protein within the cells are hallmarks of the disease. However, a longitudinal early onset Alzheimer study in Columbia (1) showed that clinical symptoms appeared as early as age 40, before plaques were identified in the brain. Researchers also tested a transgenic mouse model of Alzheimer's disease. To investigate their symptoms, they did motor performance and learning tests using ErasmusLadder. Again, symptoms became evident before the presence of plaques in mouse brains. Researchers are now working on ways to prevent or slow down the disease at early stages, instead of trying to cure or treat it later on. Read more about this study. Natural treatments for Alzheimer's So, there is no cure yet, but many possible treatment and therapies are tested. One of them is not medication per se, but rather a supplement: Ginkgo biloba. This dietary supplement is supposed to enhance cognitive function. The plaques we talked about earlier, which are the hallmark of Alzheimer's disease, actually cause inflammation. This damages the neurons, which in turn leads to dementia or cognitive impairment. After noticing different positive effects of Ginkgo biloba on AD-patients in preclinical and clinical studies, researchers (2) decided to focus more on the molecular level. Using a transgenic mouse model, researchers gave the supplement and varied the period of supplement treatment. The mice were then tested for how good their memory was using a Barnes maze task. It turned out that AD-mice receiving Ginkgo biloba actually did have better memory, but only if they had been taking the supplement for a long period of time. Read about the study here. Sporadic Alzheimer's By now, if we hear "Alzheimer's disease," we automatically think about plaques and tangles, at least in the scientific research context. However, that is not entirely correct. These hallmarks are linked to familial Alzheimer's disease. This type of Alzheimer's disease is actually a far less common type of AD than sporadic Alzheimer's disease. Sporadic AD is far more common, and typically late-onset, meaning that most patients are over 70 years old. There is also a lack of transgenic rodent models. In sporadic AD, episodic memory is one of the first things to decline. Olfactory deficits may arise even prior to this, a fact that opens up opportunities for future early detection. As a result, researchers (3) looked at olfactory memory and developed a new mouse model. They tested these mice with olfactory habituation tests. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources They also tested these mice on spatial memory with a Morris water maze test, and investigated depression and anxiety-like symptoms as well as their circadian rhythm. The preliminary results indicated this new murine model to be suitable for this far more common type of Alzheimer's disease. Read more about this study in this blog post. Morris water maze testing and Alzheimer's research Behavioral research on rodent models for Alzheimer's disease has a focus on cognition. One the most used tests for cognition in rodents is the water maze. In a nutshell, during a water maze test the rat or mouse learns the location of the platform by using cues in the environment. Normally, subjects decrease their searching time over multiple trials, indicating healthy cognition. To investigate cognition, variables like escape latency, correct quadrant, swim path, and velocity are important and are easily measured with video tracking software. Read more about this in this blog post. You might also be interested in our previous roundup of Alzheimer's disease studies! References - Sepulveda-Falla, D.; Barrera-Ocampo, A.; Hagel, C.; Korwitz, A.; Vinueza-Veloz, M.F.; Zhou, K.; Schonewille, M.; Zhou, H.; Velazquez-Perez, L.; Rodriguez-Labrada, R.; Villegas, A.; Ferrer, I.; Lopera, F.; Langer, T.; De Zeeuw, C.I.; Glatzel, M. (2014). Familial Alzheimer's disease-associated presenilin-1 alter cerebellar activity and calcium homeostasis. The Journal of Clinical Investigation, 124(4), 1552-1567. - Liu, X.; Hao, W.; Qin, Y.; Decker, Y.; Wang, X.; Burkart, M.; Schötz, K.; Menger, M.D.; Fassbender, K.; Liu, Y. (2015). Long-term treatment with Ginkgo biloba extract EGb761 improves symptoms and pathology in a transgenic mouse model of Alzheimer's disease. Brain, Behavior, and Immunity, doi: 10.1016/j.bbi.2015.01.011. - Coronas-Samano, G.; Baker, K.L.; Tan, W.T.J.; Ivanova, A.V.; Verhagen, J.V. (2016). Fus1 KO mouse as a model of oxidative stress-mediated sporadic Alzheimer's disease: circadian disruption and long-term spatial and olfactory memory impairments. Frontiers in Aging Neuroscience, 8, 268. --- ## Analysis of facial expressions of emotions in children URL: https://noldus.com/blog/facial-expressions-emotions-children Published: 2019-02-14 16:00:00 Description: The study described in this guest blog post focuses on the facial expressions of emotions induced by affective stimuli in children aged between 7 and 14. In this guest blog post, researchers involved in the FIRB and NARSAD projects from the Vita-Salute San Raffaele University and the Sigmund Freud University in Milan, Italy, tell us more about their study carried out to characterize a set of emotionally charged stimuli in terms of the induced facial activation. In the project, FaceReader along with a FACS coder were used to investigate the differences between the two. The team consists of: Dr. Regina Gregori Grgič (Vita-Salute San Raffaele University, Milano); Dr. Simona Scaini (Sigmund Freud University, Milano); Dr. Chiara Ferrero (Vita-Salute San Raffaele University, Milano); Dr. Valentina Latronico (Unit for Cognitive Neuroscience (UCN), Department of Psychology, University of Copenhagen, Denmark); Prof. Anna Ogliari (Vita-Salute San Raffaele University, Milano); Prof. Clelia Di Serio (Vita-Salute San Raffaele University, Milano); Dr. Chiara Brombin (Vita-Salute San Raffaele University, Milano). Analysis of facial expressions of emotions in children The present study has been developed within the activities of a larger project1 aimed at measuring emotional response by integrating different sources of information such as facial expressions, physiological measurements, psychometrics, and clinical data. Here, we focus on the facial expressions of emotions induced by affective stimuli in children taken from the general population. Using Facial Action Coding System (FACS) for emotion recognition Why facial expressions? And why children? The early identification of deficits in emotion recognition and expression skills may prevent poor social functioning in adulthood. Moreover, facial expressions represent the most effective way to convey information on one’s emotional state to others. Using the Facial Action Coding System (FACS; Ekman and Friese, 1978), facial configurations may be decoded using specific, quantitative, and sharable rules. Facial expressions are described in terms of single movements of face muscles (Action units, AUs) and their intensity. FREE WHITE PAPER Facial Action Coding System Download here the FREE white paper 'Facial Action Coding System (FACS)' and learn more about: - Objective results with FACS - Action Units - Examples using FACS Submit to download Measuring facial expressions of children To elicit emotions, we used a pre-tested set of 15 images from the Anger and Fear Eliciting Stimuli for Children (AFES-C, Scaini et al., 2017), specifically suited to elicit anger, fear, and neutral emotions. These emotions are actually linked with the development of both internalizing and externalizing problems. A group of 61 children aged between seven and fourteen took part in the experimental sessions, which were carried out in a laboratory. The children’s facial expressions were recorded during the stimuli administration. No instruction was given to display a specific emotion, so the recording attested to the spontaneous reaction of the children. Lighting conditions were carefully controlled. Figure 1: The lab setup. Emotional responses After each stimulus presentation, children were asked to describe their emotional experience using both the discrete and dimensional models of emotions. Children were allowed to move and assume natural poses, thus making the analysis of their facial expressions more difficult for the software. No real-time analysis of the videos was performed. The goal of the analysis was to characterize emotional response induced by the AFES-C stimuli using facial expression data recorded by FaceReader and the certified FACS human coder. The idea was to identify patterns of AUs specific to each target emotion. Automatic detection of Action Units versus a FACS coder The most frequently detected AUs by FaceReader were 43 (eyes close), 17 (chin raise) and 25 (mouth open); the least detected were 9 (curl nose), 20 (pull the chin back) and 27 (stretch mouth). The FACS coder detected some AUs as more frequent, including the AUs 4 (wrinkle eyebrow), 5 (dilate eyes) and 1 (wrinkle front). The AUs that were the least detected were AUs 20, 43 and 27. Results are shown in Figure 2. Figure 2: Barplot showing the relative frequency of the occurred Action Units, detected by FacerReader 5 (on the left) and by the FACS coder (on the right), in decreasing order. When considering FaceReader, the most frequently detected AU was AU43, indicating “eyes closed”, while the FACS coder detected AU4 with the highest frequency, indicating “brow lowerer”. The least detected AU with Facereader was AU9 (nose wrinkler), while for the FACS coder it was AU 20 (lip stretcher). Since the occurrence of AUs for the FACS coder is a binary variable, to compare the two methods, the continuous AU signal provided by FaceReader was dichotomized using an empirical threshold: the AU occurred if the maximum of the signal was larger than 0.2 (in the 0-1 range) at least once throughout the stimulus presentation time. Clustering techniques were then applied on the variables indicating the occurrence of the AUs detected by both the automatic and the manual method. In particular, we focused on the most emotion-relevant AUs, e.g., on the AUs 1 (raise eyebrows), 4, 5, 7 (tighten the eyes), 10 (pull on cheeks), 12 (smile), 14 (dimples), 15 (corners of the mouth down), 17 (chin upward), 20, and 23 (stiffen lips). Hence, we excluded AUs which were never or always detected by the two methods, e.g., the 27 and the 43. When considering AUs detected by FaceReader, we identified two clusters of images, including respectively neutral and non-neutral stimuli; when considering AUs detected by the FACS coder, three clusters, almost reflecting the three target emotions, were identified. Figure 3: Clustering stimuli based on the Action Units detected by FacerReader 5 (on the left) and by the FACS expert (on the right). Each picture is labelled with its ID. N denotes neutral pictures, anger-eliciting pictures are indicated by the letter A, and finally letter F is associated to fear- inducing pictures. Experience with FaceReader Exploring FaceReader 5 capabilities in an experimental setting involving children was very interesting. Also, in our study we were interested in natural, spontaneous facial expressions. In some cases, FaceReader failed to detect a child’s face, due to the size of the face itself, movements of the child, or the presence of glasses/hair causing partial occlusions. We used static stimuli without inducing strong emotional responses, but whenever the child expressed a stronger emotional facial display, the software successfully analyzed the facial expression. We found that the “General” model of FaceReader performed better than the “Children” model (Loijens and Krips, 2018). We are aware that the definition of AU “occurrence” based on the 0.2 empirical threshold could affect our results, and we are currently refining the definition of this threshold using functional analysis techniques. The latest version of FaceReader actually uses a new deep learning algorithm, called Deep Face Model, allowing you to analyze facial expressions under challenging conditions. Hence, as matter of future work, we would like to test its performance in the same experimental setting. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download References - Ekman, P., Friesen, W. V. (1978). “Manual for the facial action coding system”. Consulting Psychologists Press. - Loijens, L., Krips, O. (2018). “FaceReader Methodology Note”. Behavioral research consultants at Noldus Information Technology. - Scaini, S., Rancoita, P. M., Martoni, R. M., Omero, M., Ogliari, A., & Brombin, C. (2017). Integrating Dimensional and Discrete Theories of Emotions: A New Set of Anger-and Fear-Eliciting Stimuli for Children. The Journal of genetic psychology, 178 (5), 253-261. 1 This research has been funded by the FIRB Project RBFR12VHR7 “Interpreting emotions: a computational tool integrating facial expressions and biosignals based on shape analysis and bayesian networks” (PI, Dr. Brombin) and by a NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation, grant number: 23553, entitled “Integrating multimodal affective information for emotion recognition in children with symptoms of anxiety disorders” (Dr. Scaini recipient). --- ## The ultimate list of neuroscience lab software tools URL: https://noldus.com/blog/ultimate-list-neuroscience-lab-software-tools Published: 2019-02-08 16:12:00 Description: Are you interested in starting a new lab, or perhaps in updating your current lab to its maximum potential? If so, this list of ultimate neuroscience software tools is the place to begin. Are you interested in starting a new lab, or perhaps in updating your current lab to its maximum potential? If so, this list of ultimate neuroscience software tools is the place to begin. At Noldus Information Technology, we make it our mission to ensure that our software can get you the analysis you need quickly, easily, and reliably. Take a look at some examples of Neuroscience software tools and how they're used by researchers around the world. Video tracking software Our EthoVision XT video tracking software is a software platform – you can start with the Base module, which allows you to track the center point of one animal in one arena. Depending on your research needs, you can then expand your software capabilities with eight different add-on modules that include the ability to track in multiple arenas at once, analyze social interaction, track the nose point, center, and tail base of your subject, and control interaction with external equipment in your test protocol. EthoVision XT is mainly used in fields related to neuroscience, such as behavioral neuroscience, genetics, pharmacology, and toxicology. It is included in package deals for a variety of tests including Morris water maze, radial arm maze, Barnes maze, and T-maze tasks. In addition, we also have a variety of cameras and computers for you to select from if you do not already have hardware equipment. If you are interested in trying it out, we also provide free 30-day downloadable trials – just let our Scientific Sales Consultants know when you want your trial to start! If you like, our consultants can also walk you through your trial via a remote screen sharing session in order to answer any questions you might have and ensure you get the introduction you need in order to decide if EthoVision XT is right for you. Want more information? Access our EthoVision XT page to read further and to request a quote or free trial. Behavioral coding and analysis software Set up, gather, and analyze your observational data with The Observer XT. This software system supports your entire research process, allowing you to design your own observational studies and coding schemes. Like EthoVision XT, The Observer XT consists of one Base module that can be combined with additional modules for added functionality. On its own, the Base module allows you to set up your study and coding scheme design, perform live coding, offline editing, and analysis, and present your data. Additional modules come with abilities such as scoring digital media files offline, performing reliability and lag sequential analysis, and importing data from a wide range of acquisition systems. You can use The Observer XT in both animal and human studies, and due to its capacity to synchronize and analyze multiple signals (video, audio, physiology, etc.), it proves to be a useful tool for researchers in many fields. These include wildlife behavior, fundamental neurosciences, and farm animal welfare. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Just like our offer for EthoVision XT, we recommend free 30-day downloadable trials of The Observer XT as well as walkthroughs via screen share. Why not try it out? Request a free trial here and get on your way to saving time as well as coding and describing behavior accurately and quantitatively. Zebrafish research software and hardware If you are doing research on zebrafish or insect larvae and would like a complete tracking system that offers reliable data and analysis, look no further. Powered by our EthoVision XT tracking software, DanioVision can track up to 96 individuals in well plates at once. Its main components are as follows: - EthoVision XT software - DanioVision Observation chamber (includes lighting and IR-sensitive camera) - Temperature Control Unit (optional, to control the temperature of your subjects) - Tapping Device (optional for sound/vibration stimuli) - Computer with EthoVision XT software pre-installed Using EthoVision XT, you can track each of your larvae simultaneously and control stimuli such as light, sound, and vibration. It can also calculate variables such as velocity, distance moved, and turn angle. You can use DanioVision in studies on toxicology, circadian rhythmicity, and Parkinson's disease, to name a few. For more information on DanioVision, visit our zebrafish website to watch our short introduction video, view recent publications, and request a free demo. Instrumented cage for uninterrupted behavioral testing using EthoVision XT software If you are using rats or mice in your research and are looking to study them in a home cage environment or overnight, then our PhenoTyper is the solution for you. Powered by EthoVision XT, the PhenoTyper is an instrumented cage, typically equipped with an IR sensitive camera, IR light, white and yellow lights, and sound stimuli located within a top unit. It is available in either a basic or home cage version, and while it is ideal for long-term studies, it provides considerable advantages for shorter studies as well. When you use a PhenoTyper, you gain access to a fully integrated test environment with video equipment. What's more, there are a wide range of add-on and custom options like a pellet dispenser, Mouse Feeding monitor (to measure feeding behavior via IR beam break), PhenoWheel (to measure running activity), IR translucent shelters, and optogenetics. You can run a multitude of learning tests such as novel object recognition and operant conditioning, and if you choose to perform a long-term study, home cages can operate for several days in a row without any human intervention. This means that you can assess your subject in a natural environment while performing multiple or repeated experiments for a long period of time. Interested? Check out our website to learn more about how you can adapt PhenoTyper to suit your research needs and watch our customer success stories. And there is more! Aside from the neuroscience lab software tools and complete solutions mentioned here, there are still a number of solutions we haven't introduced yet, like CatWalk XT or ErasmusLadder. We also encourage you to reach out and chat with us. If for any reason the options on this list are not exactly what you are searching for, we are happy to discuss alternative means in order to provide you with the best possible fit for your research. We look forward to working with you! --- ## Three UX Lab examples with the latest UX research tools URL: https://noldus.com/blog/ux-lab-examples Published: 2019-02-05 14:29:00 Description: A UX Lab is used for usability testing and user experience research. Users are observed in a specific environment while interacting with a product or system. Most UX research is conducted in state-of-the-art UX labs. A UX Lab (or usability lab) is used for usability testing and user experience research. Users are observed in a specific environment while interacting with a product or system. Their interactions are important, as the usability of a product or system is key to its success. Most UX research is conducted in state-of-the-art UX labs. Three UX Lab examples with the latest UX research tools Over the past few years we've been involved in some of the most amazing UX labs. From gaming research labs to modern social media labs and purpose-built usability testing labs. Let me share three recent examples of UX labs that we've helped establish in recent years, including the latest UX research tools. Dubai's first purpose-built usability lab Home to some of the world's tallest buildings and most luxurious hotels, Dubai is increasingly becoming a smart city where technological innovation is key. User experience experts Digital of Things identified the growing need for good UX in the region and established the UAE's first purpose-built, state-of-the-art usability testing lab. The Digital of Things usability lab is a high-tech user testing lab with world class analytical features, including facial expression analysis with FaceReader. Together with Noldus, they've set up an ultra-modern usability lab, equipped with the most advanced software for user experience testing. The lab has a comfortable living room atmosphere so testers feel at home, ensuring reliable results from user testing. Thanks to the one-way mirror, cameras and microphones in each room, testers are observed unobtrusively. These lab facilities and their expertise enable Digital of Things to combine quantitative data with qualitative insights, and provide their clients with useful recommendations. NOLDUSHUB Your data in a heartbeat Discover how NoldusHub benefits your research, and why it is the best multimodal platform for you to use: - Clean and easy to use interface - Synchronization from the start - Powerful data visualizations Learn more Social Media Lab at Mons, Belgium Closer to home, we've set up a lab that is adapted to our modern digital world. Everybody uses social networks like Facebook and Instagram, but are not really aware of how their data is used. The Social Media Lab in Mons, Belgium brings together researchers, students, and professionals from different disciplines as communication, marketing, journalism, computer science, and more. Together they try to understand the digital world, train themselves in the use of new technology, and learn more and advice about new professional practices. They conduct tests to find out how people make sense of data, and data visualizations. They use tools like The Observer XT for easy data integration and behavior analysis, and MediaRecorder for synchronous AV recording. The Social Media Lab at the University of Louvain uses Noldus' software to integrate different data streams and set up experiments. Montréal-based UX Lab Most recently we teamed up with the Tech3Lab at HEC Montréal. Prof. Pierre-Majorique Léger tells more about user experience research, and how to measure users' interactions with technology in the video below. Thanks to research in their UX lab, they have designed a new technology for UX research compatible with Noldus tools. This cloud-based software platform combines behavioral data collected from human behavior research in order to provide fast and rich insights to professionals developing human experiences. From data collection to insightful results at this Canadian UX Lab Cognitive and emotional data collected during user experience tests are usually visualized into heat maps. Going beyond traditional gaze heat maps used in eye tracking, it captures the complete user experience. Thanks to the triangulation of facial expressions, physical reactions, and eye tracking data, it provides UX researchers and designers with unique insights on what generates emotion or cognitive load on their interface. The world of user experience research is always developing and we can't wait to see what other usability and UX labs will be set up in the future! FREE BUYER'S GUIDE Buyer's guide to the perfect audiovisual lab - What is an audiovisual lab? - What do you need to complete your setup? - How does an audiovisual lab help you answer your research questions? Get your copy --- ## 7 Tips how to set up a coding scheme URL: https://noldus.com/blog/7-tips-set-up-coding-scheme Published: 2019-01-31 15:39:00 Description: The coding scheme or ethogram determines what data you collect and is, thus, an essential part of your behavioral study. Tips to set up a coding scheme (+free white paper with all 7 tips to set-up your coding scheme). The coding scheme or ethogram determines what data you collect and is, thus, an essential part of your behavioral study. How to develop a coding scheme that will provide you with the information you need? You can set up your coding scheme on paper, but you can also use The Observer XT software, a tool that can assist you in the entire workflow of an observational research project. How to set up a coding scheme (+ FREE white paper with all 7 tips to set-up your behavioral coding) So let's start at the beginning: - Set up a draft coding scheme or start with a template - As a behavioral researcher you will recognize the need for a well-defined coding scheme. In many cases your coding scheme is not perfect at the beginning. Some behaviors may be too detailed and others may be missing. The Observer XT software allows you to fine-tune your coding scheme while observing. You can add elements during scoring and afterwards reorganize your coding scheme and delete redundant elements. This means that you can start your observations with a draft coding scheme and develop and refine it to bring it to perfection. You can also decide to start your observation with a coding scheme from a template and adjust it so it fits your research needs. - Specify your subjects, behaviors, and modifiers - In the coding scheme you can define your subjects and behaviors and use modifiers to specify your subjects and behaviors more precisely. Examples of modifiers are the number of words an infant utters when speaking or the person whom the focal subject is talking to. Modifiers can be nominal or numerical. The order in which you score the coding scheme elements is not fixed. You can score your data in the order you prefer, instead of subject – behavior - behavior modifier, you can score, for instance, behavior - behavior modifier – subject. It is not mandatory to score all four elements, you can use any combination you like, for instance, score subjects and behaviors without modifiers or score behaviors only. In fact, you can also decide to score none of the usual elements (subjects, behaviors, and modifiers), but record comments only. You can start your study by registering comments, synchronized with video or in a live situation. Based on these comments you can make a draft coding scheme and use this to start scoring. - Define your behavior group - Depending on your research you may want to know the duration, frequency, and/or sequence of behavior. In The Observer XT you can define your behaviors as state or point events. State events have a duration, point events don't. Eye blinks for instance are often defined as point events because of a negligible duration. State events may be defined either as 'mutually exclusive' or 'start-stop'. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Want all 7 tips to create your scheme for behavioral coding? Download the white paper and get started with your own coding schemes. --- ## Evaluating the effectiveness of simulation in healthcare URL: https://noldus.com/blog/effectiveness-simulation-in-healthcare Published: 2019-01-11 11:47:00 Description: Teamwork is important in many occupations but it is crucial when working under pressure. Most of us can only imagine how stressful it could be when working as a fire fighter or operating room nurse. Effective teamwork is important in many occupations but it is crucial when working under the pressure of time in a crisis situation. Most of us can only imagine how stressful it could be when working as a fire fighter, squad team member, or operating room nurse. Comparing real cases with simulated cases in healthcare communication Understandably, researchers dive into these teamwork processes to see how effective and efficient they are and how they could be improved. In these cases, one minor change in the procedure could influence the stress level and the efficiency in teamwork and thus, the outcome of a crisis situation. Train and evaluate teamwork Simulation is used to train and evaluate teamwork. One example where simulation is used to train and evaluate teamwork is a hospital. In an operating room (OR), nurses, anesthesiologists, and surgeons work closely together to complete the operation successfully. Jennifer Weller and colleagues investigated whether communication patterns during simulation reflect communication patterns in the clinical environment during routine cases. The team aimed to evaluate simulation-based education since it is often used to develop both effective teamwork and communication, and in assessment and recertification. Therefore, they formulated a second hypothesis: "anesthesiologists would exhibit different communication patterns in routine cases (in the OR or simulated environment) and in simulated cases involving a crisis". Simulation in healthcare In 'Building the evidence on simulation validity', Weller et al. (2013) compared communication patterns. In particular, they observed anesthesiologists in OR cases and simulated cases (crisis and routine). All interactions were recorded on video to enable detailed analysis. Weller et al. placed unobtrusive audiovisual equipment in the OR. Structured coding framework Because verbal communication supports many dimensions of teamwork, the focus of the researchers was to observe key communications. They coded the type of communication, with whom the anesthesiologist was communicating, and sharing situational information. By using a structured coding framework to code verbal behaviors, the events in the real and simulated cases could be compared and analyzed in The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Analyze behaviors in the OR In this study, 20 anesthesiologists participated. Weller et al. explain that often the validity of simulation is measured by comparing an expert with a novice in the simulator. Instead of following this approach, Weller et al. chose to compare the clinical environment (OR) with a simulated environment (OR) and analyzed differences and similarities. They found no differences between routine cases in the operating room and routine cases in the simulated cases. This emphasizes the ecological validity of simulation. There were differences found in communication patterns between the crisis simulations and both the OR and the routine simulations. These differences under the challenge of a crisis support the use of simulation to assess crisis management skill. Reference Weller, J. et al. (2014). Building the evidence on simulation validity. Comparison of Anesthesiologists' Communication Patterns in Real and Simulated Cases. Anesthesiology, 120 (1). --- ## Can facial expressions and emotional reactions predict likeliness to buy? URL: https://noldus.com/blog/facial-expressions-likeliness-buy Published: 2018-12-24 15:21:00 Description: Think about some of your favorite holiday foods – what are they? Maybe gingerbread, candy canes, or pies? Good food = Good mood? Think about some of your favorite holiday foods – what are they? Maybe gingerbread, candy canes, or pies? On the other hand, perhaps something more savory, like turkey or mashed potatoes? The list goes on. Many of us tend to associate these dishes with pleasant emotions and the comfort of being home with family, which is what many companies rely on when creating their marketing campaigns or targeting specific consumer demographics. However, what if you could objectively determine the emotional reactions of consumers in relation to food products rather than make a guess? Facial expressions and likeliness to buy That is exactly what Eliza Kostyra and colleagues did in a study that took place at the Sensory Analysis Lab of the Laboratory of Food Assessment and Diagnosis in the Faculty of Human Nutrition and Consumer Sciences, Warsaw University of Life Sciences, Poland. In this blog post, I will be referencing findings from Kostyra's paper, "Consumer facial expression in relation to smoked ham with the use of face reading technology. The medical aspects and informative value of research results." Using FaceReader to gauge consumer emotion As the title of the paper suggests, this study used face-reading technology in order to determine the effect of smoked ham samples on consumer emotion, which may lead to deeper insight on whether or not a consumer chooses to buy the sampled product. After all, sensory reactions to food like smell and taste are very important and can either make or break a consumer experience! Kostyra and colleagues used Noldus FaceReader software in order to make these non-verbal measurements, which differs from many past studies that used methods like a traditional conscious verbal approach. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download The study used six types of emotions: happiness, sadness, anger, surprise, scared, and disgust. Any lack of emotion was recognized as neutrality or indifference, and the emotions of each participant were video recorded within 30 seconds after consumption of a piece of ham that was taken from five possible different ham samples. Each of the 30 consumers involved in the study faced the camera directly, and Noldus Media Recorder software was used to synchronize video and audio recordings. A surprising conclusion What the study found may surprise you! The researchers expected that a product would significantly explain an expressed emotion. However, they saw that only happiness clearly depended on a product, followed by anger. Further tests concluded that the emotional variability of each participant was a large factor, since each person has their own individual preferences and personal experiences that shape their interest and emotional reaction to a product. In addition, the emotions that the researchers found dominant were neutral and sad, which may have resulted from an expression of disappointment or expecting a sensation other than what occurred. Overall, the researchers advised that any conclusions should be made with caution and that further studies should be performed. In this specific study, the emotional expressiveness of consumers turned out to be rather small, which may have affected the results. In terms of conducting further studies, there is also the option to perform tests using multiple data streams (such as GSR and ECG), which have been used in past studies to allow for further exploration. In addition, researchers could also look at Action Units in depth in order to get even further detail behind an emotion. With that in mind, we encourage you to conduct your own informal studies with family and friends at your own dinner table over the holidays – eat up, enjoy, and prepare yourself for people who ask for a second serving! Interested in human behavior research? Read more on 'How to study human behavior'! --- ## How to build a usability lab? URL: https://noldus.com/blog/how-to-build-a-usability-lab Published: 2018-12-18 12:00:00 Description: Usability testing is an essential part of user centered design processes. It is necessary to evaluate prototypes. So how do you build a usability lab? This how to will help you out! Usability testing is an essential part of user centered design processes. It is necessary to evaluate prototypes: if designers made wrong assumptions or missed requirements, a usability test is likely to reveal them. Usability testing can be carried out in a usability lab, or on-site with a portable lab. So how do you build a usability lab? This 'How to' will help you out! How to build a usability lab? In today’s rapidly evolving digital landscape, the creation of an effective usability lab is not just a matter of technical know-how, but also of understanding the intricate dynamics of human-computer interaction. How to build a usability lab that is customized for your research needs? A usability testing lab needs controlled conditions, and fully integrated equipment and software to make your tests as realistic as possible. What equipment is needed for a usability lab? Video and audio recording is necessary to capture what test participants see, and how they interact with an interface. An easy-to-use solution for creating AV recordings like Viso includes everything you need to produce high-quality projects. Tools to gather facial expressions and emotional data like FaceReader and eye trackers allow you to capture how test participants feel as they carry out the tasks. Professional data integration and analysis software will allow you to synchronize all available data. An all-in-one research platform like NoldusHub can streamline multimodal research from start to finish, providing high-quality data, and insights into human behavior. FREE DEMO Try Viso yourself! Request a free demonstration to find out why Viso is the right tool for your training facility! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback and debriefing Free Demo Performing usability tests in a usability lab To get off to a good start, it is best to describe the research or tests that are going to be performed in great detail. With this description, it becomes clear what kind of equipment will be needed, and which physical environment would best suit this test or research. The description should answer questions such as: - How many participants need to be recorded at the same time? - How many people are present during a test, besides the participant(s)? - Are participants being invited to visit the lab? Is on-site research going to be performed? Or both? - Where and in which room(s) should the lab be built? How big are the rooms? And, does the building have special aspects (i.e. is it a monument)? The answers to these questions will help you establish your lab and research needs. Download your free white paper Would you like to learn more? Download this free ‘how to’ guide for more information. Whether you're setting up a new lab from scratch or refining an existing one, our guide promises to be an invaluable resource in your quest to enhance user experience through rigorous testing and innovative research methodologies. In this white paper you can find a list of equipment you can think about when building a usability lab. Of course, the exact combination of tools used in a lab depends on specific requirements and wishes. FREE WHITE PAPER How to build a usability lab Do you want to learn more how to set up a usability lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download Usability research publications Are you interested in reading more about actual usability research applications, please view the list below. This list is a small selection of scientific publications in this area. - Goldberg, J.H. (2012). Relating perceived web page complexity to emotional valence and eye movement metrics. Proceedings of the Human Factors and Ergonomics Society 56th Annual Meeting, 501-505. - Barendregt, W.; Bekker, M.; Bouwhuis, D.; Baauw, E. (2006). Identifying usability and fun problems in a computer game during first use and after some practice. International Journal of Human-Computer Studies, 64, 830-846. - Yammiyavar, P.; Clemmensen, T.; & Kumar, J. (2008). Influence of Cultural Background on Non-verbal Communication in a Usability Testing Situation. International Journal of Design [Online], 2 (2). - Tenopir, C.; Wang, P.; Zhang, Y.; Simmons, B.; Pollard, R (2008). Academic users’ interactions with ScienceDirect in search tasks: Affective and cognitive behaviors. Information Processing and Management, 44, 105-121. --- ## Gait analysis at the PSDL using CatWalk URL: https://noldus.com/blog/gait-analysis-catwalk-xt Published: 2018-12-17 15:46:00 Description: Our lab studies the Neuronal Ceroid Lipofuscinoses (NCLs) or Batten disease, which are a group of progressive and genetically inherited neurodegenerative diseases that affect children and young adults. This guest post was happily provided to us by the Pediatric Storage Disorders Laboratory (PSDL) lead by Jonathan Cooper at Washington University School of Medicine, St. Louis, MO, USA. For those who are interested in gait analysis with rodents, we encourage you to read on and learn more about their experiences with the CatWalk XT system. About the PSDL Our lab studies the Neuronal Ceroid Lipofuscinoses (NCLs) or Batten disease, which are a group of progressive and genetically inherited neurodegenerative diseases that affect children and young adults. We are characterizing mouse models of these diseases in order to better understand the underlying disease mechanisms, so that we can more effectively target experimental therapies. We found significant pathology in the cerebellum and spinal cords of some of these mouse models, and therefore wished to understand what effect this had on the sensorimotor system. We decided to analyse the gait of these mice using the CatWalk XT gait analysis system as it would provide us with a detailed analysis of the locomotor ability of our mice. Achieving high throughput and a reliable and detailed analysis of natural gait Our lab has been using the CatWalk XT system since 2015, and we have found that it is an invaluable tool for our research and provides a reliable and detailed analysis of gait and how it varies in our disease models. Since it is not a measure of forced locomotion, but instead allows mice to freely move along the corridor, we believe it to be a more accurate representation of the natural gait of mice. We found that closing the end of the CatWalk corridor with the provided enclosure meant that mice would run the length of the corridor to move away from the handler and turn around once they hit a dead-end and head back to the entrance, thus providing two runs in a short time period. Unlocking vital information, unbiased gait parameters, and more We were particularly impressed with the auto-classification system, which greatly sped up the time taken for analysis of data as most of the time each auto-classified run only needed very minor adjustments to be considered accurate. With robust data for how gait varies during disease progression, we also have sensitive outcome measures for judging the efficacy of a variety of experimental therapies. The large number of unbiased gait parameters that the CatWalk XT system provides has also been very helpful as it has provided vital information for our research. In a mouse model of Infantile NCL, we were able to describe a novel early hypermotility phenotype that had until now been overlooked. With detailed readouts for individual limbs, we were also able to better define differences between contralateral limbs and fore- and hindlimbs and how this related to the regional pathology in the spinal cord and cerebellum. Indeed, our finding of increased dependence on forelimbs for locomotion with age in the Infantile NCL mouse model was juxtaposed to the generalised spread of pathology in the spinal cord and has led us to explore the peripheral nervous system as a potential site of pathology to help understand these rostro-caudal differences. We now are working to expand this analysis to mouse models of other forms of NCLs to understand the similarities and differences between these diseases. Noldus technical support allows for little downtime Lastly, having moved labs twice over the past 3 years, we are also very appreciative of the logistical and technical support we have received from Noldus with regards to operating and troubleshooting our CatWalk XT usage. Whenever there has been any technical issue, the problem was quickly identified and resolved, and this has meant very little downtime in our experiments despite these moves. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources More about gait analysis --- ## The effectiveness of physical therapy sessions for children with cerebral palsy URL: https://noldus.com/blog/effectiveness-physical-therapy-sessions Published: 2018-12-14 16:37:00 Description: Researcher Sébastien Vanderlinden is committed to describe which and how long physical therapy skills are performed during NDT sessions. In this guest blog post, researcher Sébastien Vanderlinden from Belgium writes about his study around the effectiveness of physical therapy for children with cerebral palsy. Cerebral palsy is a developmental disorder and is caused by damage to the motor cortex of the brain. This is the part of the brain that affects muscle control and coordination. Children with cerebral palsy frequently struggle with walking and fine motor skills. VanderLinden is searching for other physical therapists and Ph.D.'s who are willing to participate in his study. Validation of an evaluation protocol to describe and quantify the therapeutic content performed during neurodevelopmental physical therapy (NDT) sessions of children with cerebral palsy In recent years, an intensification of studies that document the effectiveness of physical therapy for children with cerebral palsy (CP) resurfaced. According to a recent systematic review of Novak [1], which focuses on therapeutic interventions, it seems that the recommendation not to practice neurodevelopmental therapy (NDT, of which the terminology is based on the Bobath Concept - http://www.bobath.be/fr/Info/Worldwide and had been used in research for many years) needs to be considered. Evidence regarding the effectiveness of this therapy is still developing today. This systematic review thoroughly details the limits and motivating arguments of this point of view, and to a certain extent, encourages the content of this pilot study. Analyzing therapy sessions with The Observer XT The main goal of our study is to validate an evaluation protocol including the use of a measurement tool, The Observer XT, that could be used to describe and quantify the therapeutic content performed during a NDT session for a child with CP and its associated procedures. As Novak mentions it, there is a lack of published scientific data that describes which and how long physical therapy skills are performed during NDT sessions. Neurodevelopmental therapy has been medically prescribed and practiced worldwide for nearly half a century by physical therapists as well as occupational therapists and speech therapists, who have completed its regulated NDT basic 8 weeks course. Within the clinical settings, if its main indication has always been cerebral palsy, it also remains a therapy of choice for the (re)habilitation and parental guidance of newborns and children under 24 months with developmental neuromotor delay. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial A problem-solving approach In addition to this target population, this therapy seems to provide relevant clinical benchmarks for clinical assessment and rehabilitation of the children who suffer from a multiple handicap, from a progressive disease of the central nervous system, or from other related medical conditions. It is relevant to be reminded that NDT fits within a broader "concept" (sometimes called "approach") facing the child suffering with cerebral palsy. The NDT concept could be defined as "a problem-solving approach to the assessment and treatment of individuals following a lesion of the central nervous system that offers therapists a framework for their clinical practice" or therapeutic content performed during a neurodevelopmental physical therapy session of a child with cerebral palsy. Sébastien Vanderlinden Belgium Research in PT & Neurorehabilitation sebastienvanderlinden@gmail.com References - Das, S.P. et al. (2019). Evidence-based Approach to Physical Therapy in Cerebral Palsy. Indian J Orthop. 2019 Jan-Feb; 53(1), 20–34. - Marsico, P.; V Graser, J. & Hedel, van H.J.A. (2018). Based on evidence? Techniques applied in Neuro-Developmental Treatment within the Bobath Concept: an AACPDM report. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=48583 - Novak, I.; McIntyre, S.; Morgan, C.; Campbell, L.; Dark, L.; Morton, N.; Stumbles, E.; Wilson, S.A. & Goldsmith, S. (2013). A systematic review of interventions for children with cerebral palsy: state of the evidence. Developmental Medicine & Child Neurology, 55 (10), 885-910. - Novak, I.; Morgan, C.; Fahey, M.; Finch-Edmondson, M.; Galea, C.; Hines, A.; Langdon, K.; Mc Namara, M.; Paton, M.C.B.; Popat, H.; Shore, B.; Khamis, A.; Stanton, E.; Finemore, O.P.; Tricks, A.; Velde, A. te; Dark, L.; Morton, N. & Badawi, N. (2020). State of the Evidence Traffic Lights 2019: Systematic Review of Interventions for Preventing and Treating Children with Cerebral Palsy. Current Neurology and Neuroscience Reports, 20 (3). https://doi.org/10.1007/s11910-020-1022-z - Mayston, M.,J.; Saloojee, G.M. & Foley, S.E. (2023). The Bobath Clinical Reasoning Framework: A systems science approach to the complexity of neurodevelopmental conditions, including cerebral palsy. Developmental Medicine & Child Neurology, 00, 1-9. https://doi.org/10.1111/dmcn.15748 - Te Velde, A.; Morgan, C.; Finch-Edmondson, M.; McNamara, L.; McNamara, M.; Badawy Paton, M.C.; Stanton, E.; Webb, A.; Badawi, N. & Novak, I. (2022). Neurodevelopmental Therapy for Cerebral Palsy: A Meta-analysis. Pediatrics, 149 (6). https://doi.org/10.1542/peds.2021-055061 - Tittelboom, van V. et al. (2023). Intensive Therapy of the Lower Limbs and the Trunk in Children with Bilateral Spastic Cerebral Palsy: Comparing a Qualitative Functional and a Functional Approach. J. Clin. Med., 12 (12), 4078; https://doi.org/10.3390/jcm12124078 - Zanon, M.A.; Pacheco, R.L.; Latorraca, C.O.C.; Martimbianco, A.L.C.; Pachito, D.V. & Riera, R. (2019). Neurodevelopmental Treatment (Bobath) for Children With Cerebral Palsy: A Systematic Review. Journal Child Neurology. doi: 10.1177/0883073819852237 --- ## Into the lab: how to monitor rat social behavior URL: https://noldus.com/blog/how-monitor-rat-social-behavior Published: 2018-11-26 11:24:00 Description: Including social behavior as part of a phenotypic screen has important benefits and eventually leads to better translational value of rodent models. This is a second guest blog post by Suzanne Peters, PhD. Her thesis is named "The importance of rat social behavior for translational research. An ethological approach", which she defended on April 4th this year. Read the first blog post here. Monitoring and analyzing the social behavior of group housed rodents is something that many researchers find extremely challenging. It can also be very time consuming. However, including social behavior as part of a phenotypic screen has important benefits. As I argued in my first blog, it eventually leads to better translational value of rodent models. During my PhD research, I have developed an automated analysis that allows for the monitoring of socially interacting rats. Research equipment In my experiments, I used an enlarged version of the PhenoTyper (90 x 90 cm, called PhenoTyper-9000) to allow for social housing of rats. Additionally, this PhenoTyper is equipped with ultrasonic microphones to customize tracking software as well as ultrasound recording software to automate behavioral analysis, including ultrasonic vocalizations of socially interacting rats. In the long run, my aim is to fully synchronize the ultrasonic vocalizations with the (visible) behavior of the animals. This is important because analysis of these vocalizations can provide more insight into the emotional states driving social behavior. Setup At the start of an experiment, two rats are placed simultaneously inside the PhenoTyper-9000. For identification purposes, both rats are marked with either black or red on their backs. Due to the infrared lighting and infrared filter on the camera, in the video image only one animal has a visible (black) mark. Videos of the behaving animals are stored and afterwards processed with the help of EthoVision XT. Simply said, the path of each individual animal is stored, and from that data other behavioral parameters, such as speed and distance between the animals, are extracted. We did so with help of customized algorithms programmed in Matlab. Behavioral analysis Next, behavioral analysis of these parameters (distance and speed) follows. My analysis is based on the original idea of Prof. Ilan Golani and co-workers (e.g. Drai et al., 2000). Basically, it consists of the analysis of frequency distributions of the parameters and subsequent classification of behavioral modes according to Gaussian curves that best represent the data. I will explain this with help of the figure below. The figure is an example to illustrate the basic concept of the analysis that leads to the "social modes." On the right, we see the frequency distribution of all samples containing a certain velocity, and on the left for all samples the distance between the animals (proximity). The blue dashed line represents the empirical data while the red lines are the Gaussian curves that are plotted on the empirical data. The intersection of the red lines, highlighted with the black arrow, are used as threshold for determining the different modes. "Social modes" Using the thresholds determined by the intersections, I have categorized three distinct "social modes" of inter-individual distances: 'contact,' 'in proximity,' and 'alone.' In one of my studies, we could find effects of pharmacological treatments and environmental manipulations on these modes. This further strengthens the idea that these modes are indeed representing the social behavior of the rats. Additionally, the behavioral modes are consistent with the categories obtained with human scoring of these behaviors (hand scoring of the same experiments). Therefore, automated recognition of patterns in social behavior is a powerful tool for data analysis. For details, see Peters et al., 2016. Example of pharmacological effect on social behavior The next step was to implement this approach in an existing model for reduced social behavior, the chronic phencyclidine (PCP) model. The results of this study (Peters et al., 2017) showed that PCP treated animals spent less time in each other's proximity after 3 or 4 days of chronic treatment, regardless of being exposed to a familiar (cage) partner or unfamiliar partner. Particularly, time in proximity when moving with high velocity was reduced for PCP treated pairs. In contrast, at long-term, PCP treated animals spent more time in contact when exposed to an unfamiliar partner as compared to SAL treated rats. However, this difference was not observed when exposed to a familiar partner. This illustrates that effects of pharmacological treatment on social interaction behavior may be more subtle than they might appear at first glance. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Future directions Eventually, evaluating the social behavior of animals using an objective, ethological, and automatic approach must contribute to understanding the complex mechanism driving social behavior. As a result, the translational value of our models increases, which will facilitate better research strategies for understanding and eventually treating human psychological diseases that involve reduced or abnormal social behavior. References - Drai D, Benjamini Y, Golani I. (2000). Statistical discrimination of natural modes of motion in rat exploratory behavior. Journal of Neuroscience Methods, 96, 119–31. - Peters, S.M.; Pinter, I.J.; Pothuizen, H.H.J.; Heer, R.C. de; Harst, J.E. van der; Spruijt, B.M. (2016). Novel approach to automatically classify rat social behavior using a video tracking system. Journal of Neuroscience Methods, 268, 163–170. - Peters, S.M.; Tuffnell, J.A.; Pinter, I.J.; Harst, J.E. van der; Spruijt, B.M. (2017). Short- and long-term behavioral analysis of social interaction, ultrasonic vocalizations and social motivation in a chronic phencyclidine model. Behavioral Brain Research, 325, 34-43. - Previous blog post from Suzanne Peters: Towards automated homecage monitoring of group housed rats. --- ## Retail analysis - Using TrackLab in a supermarket URL: https://noldus.com/blog/retail-analysis Published: 2018-11-19 13:06:00 Description: Noldus Information Technology teamed up with Jan Linders supermarkets, a chain of supermarkets in the southern part of The Netherlands. Noldus Information Technology teamed up with Jan Linders supermarkets, a chain of supermarkets in the southern part of The Netherlands. Jan Linders approached us because they wanted to know more about the route their customers are taking when visiting one of their supermarkets. More specifically their question was: Do customers predominantly walk the same (common) route and is it possible to change this most commonly followed route by changing the layout of the supermarket and/or the placement of certain products? We set out to study this in a specific Jan Linders supermarket that was chosen for its specific layout. First, together with the people from Jan Linders we defined specific areas of interest in the supermarket that would enable us to follow a customer's route. Next, the TrackLab system was installed with sensors placed at strategic locations to capture the customers' movement in the areas of interest. The picture below shows a schematic drawing of the supermarket with the position of the 8 sensors. Retail analysis - Using TrackLab in a supermarket The movement of customers was tracked with TrackLab during one full week (week 1: Monday - Sunday) in the standard supermarket layout. Customers were asked to wear a ultra wideband tag on their coat during their normal shopping round through the supermarket. The incentive for participation was a free pack of Dutch "stroopwafels" (syrup waffles). As Dutch people like free stuff, over 2500 customers were willing to have their movement tracked. We would have liked to combine each customer's route to the pay desk with the products bought as listed on their receipt, but the professionals at Jan Linders reckoned this would be too much an invasion of privacy. FREE DEMO Try TrackLab yourself! Request a demo to obtain real-time insights into a wide range of spatial behaviors. - Accurate tracking data - Gain insights into consumer behavior - Easily access, export, and analyze data Free Demo 4500 customers allowed us to track their movements in the supermarket After week 1 the data were analyzed: for example, average time spent in different areas of interest, percentage of the total number of participants that visited specific areas of interest, route taken in/around specific areas of interest. Before data acquisition in week 2 started, the layout of the supermarket was changed in/around certain areas of interest, to see if customers would change their route and the time they would spent in the areas of interest. In week 2, around 2000 customers allowed us to track their movements in the supermarket. Based on acquiring two full weeks' worth of data of around 4500 customer, we were able to show the people from Jan Linders not only the most commonly walked routes but also the hot spots (and cold spots) in their supermarket in both weeks. Below is a picture of the heat map around the Jan Linders kitchen that shows that customers mainly pass the kitchen on the left side. Directing customers to specific areas in the supermarket Based on this, Jan Linders has already implemented some changes! These changes seem to be successful in directing customers to specific areas in the supermarket, thereby influencing the products they buy. Stay tuned to learn more about how research can help retailers make the best possible store layouts! --- ## Simulation-based team training in obstetrics URL: https://noldus.com/blog/simulation-based-team-training-obstetrics Published: 2018-11-01 11:04:00 Description: The study of Annemarie Fransen and her team shows that simulation-based team training is effective in improving communication and cooperation of obstetric care teams. The author of this guest blog post, Annemarie Fransen of the Máxima Medical Center in Veldhoven, The Netherlands, focused in her PhD thesis on the development and evaluation of simulation-based team training in obstetrics. Her research shows that simulation-based team training is effective in improving communication and cooperation of obstetric care teams. Obstetric care is characterized by life threatening events that can happen at any moment. The quality of obstetric care is influenced by the quality of teamwork performance of the involved care teams. Unfortunately, this team performance is not always optimal, and in 75% of medical errors there is a relation with a lack of teamwork skills and/or communication. These medical errors can lead to serious morbidity and mortality for mothers and their babies. In order to reduce the number of medical errors, training of healthcare teams by using simulation-based medical education is proposed. This blog is about the effect of simulation-based obstetric team training on teamwork performance and patient outcome. Teamwork skills Teamwork skills are defined as behaviors that facilitate effective team member interaction (Beaubien et al, 2004). It includes skills like leadership, communication, situational awareness, and decision-making. Being educated in these skills is necessary and can be provided by the use of simulation-based team training. Evaluation of team training showed better capabilities for dealing with fatigue, teambuilding, communication, recognition of dangerous situations, and decision-making (Grogan et al, 2004). Also in obstetrics, simulation-based team training programs have demonstrated positive effects on trainees' attitude, perception of performance, knowledge, clinical management, and task completion (Robertson et al., 2008; Birch et al., 2007; Daniels et al., 2010). There was also an association with positive effects on patient outcome (Draycott et al, 2006). However, most of these trials were non-randomized studies, and a comparison with no intervention was missing. For this reason, we initiated a randomized trial, evaluating the effect of simulation-based obstetric team training on teamwork performance and patient outcome. Debriefing simulation training We performed a large cluster-randomized controlled trial that evaluated the effect of simulation-based obstetric team training (Fransen et al., 2012; Fransen et al., 2017). In total, 24 Dutch hospitals were included, of which the complete obstetric department participated in the study. After randomization, 12 hospitals received the intervention and 12 hospitals received no intervention. The intervention comprised a one-day, multi-professional, simulation-based obstetric team training that was provided in a medical simulation center. In total, 74 multi-professional teams, including 471 trainees, received the intervention. The multi-professional teams had to manage five simulated obstetric emergencies. Each scenario lasted approximately 15 minutes, and was videotaped. The video recordings were used to provide feedback on teamwork and medical technical skills. This debriefing was provided after each scenario by a medical specialist and communication expert. We mainly focused on the education of teamwork skills. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo Effect on teamwork performance and patient outcome Approximately 6-8 months after the intervention, we visited all included hospitals to measure the effect on teamwork performance. This was done by performing two unannounced in situ simulations on their delivery rooms. The team on call had to manage a shoulder dystocia. The second scenario comprised the resuscitation of a pregnant woman. To measure teamwork performance, we used the Clinical Teamwork Scale (Guise et al. 2008). The teams from the intervention groups showed better results on the Clinical Teamwork Scale. Besides, they used predefined essential medical skills more often, in comparison to the teams in the control group. All included hospitals registered 5 obstetric complications during a one year follow-up. These complications included: low Apgar score after 5 minutes, postpartum hemorrhage, trauma due to shoulder dystocia, eclampsia, and hypoxic-ischemic encephalopathy. After one year, there was no difference between study groups in the combined outcome measure that included the obstetric complications described above. However, we did found a lower number of trauma due to shoulder dystocia in the intervention group. Moreover, the intervention group used more frequently invasive treatment options for severe postpartum hemorrhage, which was advised during the training course. Future research In order to increase the effectiveness of simulation-based obstetric team training courses, team behaviors need to be explored. In cooperation with Noldus Information Technology, we performed a pilot study to investigate the walking behavior of team members. Two patient actors, using a birthing simulator, imitated two obstetric scenarios. Each scenario was performed twice (with intermittent feedback) by a novice leader together with both an experienced and unexperienced nurse. The same scenarios were performed once by an expert team comprising of an expert leader (obstetrician with > 15 year experience in a Dutch perinatal center) and two experienced obstetric nurses. Movements were visualized and analyzed by TracklabTM. Their software enabled us to calculate the relative walking time (the absolute time the participant was moving divided by the absolute time the participant participating in the scenario), and to generate a heat map (an overview of how much time a leader spent at a location). Interested in human behavior research? Read more on 'How to study human behavior'! References - Beaubien JM, Baker DP. The use of simulation for training teamwork skills in health care: How low can you go? Qual Saf Health Care. 2004;13:i51-6. - Birch L, Jones N, Doyle PM, et al. Obstetric skills drills: evaluation of teaching methods. Nurse Educ Today. 2007;27:915-22. - Daniels K., Arafeh J., Clark A., Waller S., Druzin M., Chueh J. Prospective randomized trial of simulation versus didactic teaching for obstetrical emergencies. Simul Healthc. 2010;5:40-5. - Draycott T, Sibanda T, Owen L, et al. Does training in obstetric emergencies improve neonatal outcome? BJOG 2006;113:177-82. - Fransen AF, Ven van de J, Merién AER, De Wit-Zuurendonk LD, et al. Effect of obstetric team training on team performance and medical technical skills: a randomised controlled trial. BJOG 2012;119:1387-93. - Fransen AF, van de Ven J, Schuit E, van Tetering A, Mol BW, Oei SG. Simulation-based team training for multiprofessional obstetric care teams to improve patient outcome: A multicentre, cluster randomised controlled trial. BJOG. 2017;124:641-650. --- ## UX: from the Anthropocene to science fiction and moonshots URL: https://noldus.com/blog/user-experience-research-nordichi Published: 2018-10-26 13:26:00 Description: Even after spending a decade in contact with User Experience researchers and professionals, the domain never stops to fascinate and amaze me. In October I had the privilege of joining the 10th NordiCHI conference, in Oslo. Guest blog written by Bram van Mil. Even after spending a decade in contact with User Experience researchers and professionals, the domain never stops to fascinate and amaze me. In October I had the privilege of joining the 10th NordiCHI conference, in Oslo. User Experience research revisited at NordiCHI 2018 The keynotes clearly showed how broad the User Experience domain really is. Where Jeanette Blomberg told about her broad experience and challenges using ethnography in design processes, even having to 'thingify' her research in order to convince the developers and marketeers of the importance and impact of her findings. What a difference with the work of Carly Gloge at X, Google's "moonshot factory". She gave an inspiring talk about solving large societal problems through technology. Great examples were delivering medicines to remote locations with drones, and disrupt mobility and transportation with the Waymo autonomous cars. Of course it helps working for a company where budgets are limitless, but still it is great to see and hear about how diversity really adds to the success of a team, and how a culture where failing is seen as an indispensable part of progress truly helps innovation. UX: From the Anthropocene... Steven Jackson even took it one step further, and made us think about the Anthropocene, the era in which humans have played the dominant role on the planet earth. (Interesting question: when did this era start? When we started settling? At the industrial revolution?). Everything we design has a great impact on the world, so we should consider this when designing and make this impact an integral part of the user experience. It was great to hear his view on UX, and on repairing and reusing discarded electronics for their original purpose or for something completely different. Experiencing Oslo ... to science fiction The rest of the program included a lot of great presentations as well. Some of the talks really stood out for me, maybe because of personal preferences or relevance to my own work. How much fun must it be to create science fiction future scenarios to get stakeholders to think outside of the box, presented by Sus Lyckvi (sorry, I love science fiction, so how not to like this idea). And how cool is it to develop a personalized robot as a personal assistant for someone who suffered late brain injury, presented by Kasper Rodil (especially because the robot was a bearded tough guy wearing shades and carrying bow and arrows). Something completely different: The paper by Gayathri Gopalakrishnan was very practical, as she redesigned the design thinking model, in order to make it more applicable and better explainable in commercial organizations, definitely a model that I will be using. Many usability studies still involve ethnographic work Overall, it surprised me how much of the studies still involved ethnographic work. Carly Gloge had a great example of a situation where a human observer was necessary to see what the Waymo could not see: Apparently they do not train cars to recognize women in wheelchairs chasing ducks with a broom. Tools as FaceReader were hardly used for measuring experiences, neither was eye tracking to find out what people are looking at. An integration of these modalities can give great new insights, and it does not have to be complex. So it is possible to include these approaches in modern, agile development processes. FREE WHITE PAPER How to build a usability lab Do you want to learn more how to set up a usability lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download Maybe you picked different highlights of the NordiCHI (or any other) conference, but that is the benefit of such a diverse and high-quality program. It is great to be active in this domain, and to provide the tools that help make products that people will love. --- ## Validation-study: Basic emotions and Action Units detection URL: https://noldus.com/blog/validation-study-facereader Published: 2018-10-24 10:02:00 Description: Guest blogger Jan Zumhasch, a certified FACS-coder, explains why FaceReader is amazing if you want to analyze facial expressions and emotions. This is a guest blog post by Jan Zumhasch. He studied at the Technical University Dresden in Germany and finished with a master’s degree in communication science. Starting point According to Ekman (19701), seven culture-independent basic emotions can be distinguished: joy, anger, disgust, sadness, surprise, fear and later on also the emotion contempt2. These correspond with specific facial expressions and can therefore be observed. The most empirically founded observation system for identifying these emotions is the Facial Action Coding System (FACS) developed by Ekman and colleagues (19783), reviewed repeatedly, subsequently revised (1992 and 2002) and used by numerous researchers. In addition, it was used to develop FaceReader, a software tool to analyze these facial expressions and emotions automatically. But how good is the software doing it’s job? For the performance of version 6, Lewinski et al. (20144) published a validation study. Meanwhile, the software has been revised and expanded. Since I am a certified FACS-Coder myself, I was very interested in testing a newer version of the software. Testing the facial expression recognition software tool In my master's thesis I have validated version 7.1 of FaceReader, including the Action Unit Module. To specify this investigation part of my research, I used selected study materials, including photos and videos of the "Amsterdam Dynamic Facial Expression Set" (ADFES)5 and material taken from the Facial Action Coding System (FACS), the holy grail for learning about the face. Results All in all I manually coded 176 photos as well as 143 videos. After that I had the Action-Unit-combinations and the corresponding emotions of for every single photo and video which I could compare with the results of FaceReader. A. High performance based on high quality of photos and videos The FaceReader recognized the photo and videos included in the ADFES-dateset with high precision when analyzing six basic emotions: joy, sadness, anger, surprise, fear, and disgust and additionally the neutral facial expressions. The recall of the correct Action Units was also very high. The exact explanations for "Recall", "Precision" and "F1" can be found in the Lewinsky et al. validation from 2014. For example the "Recall" for AU 1 in the following chart means that 113 out of 122 times FaceReader correctly identified the Action Unit. This is equal to 0,93 or 93%, an amazing result.   All in all the results all lie above the findings of Lewinsky et al. 2014, both in recall of emotions and Action Units. In addition, the values for the accuracy of the six basic emotions correspond approximately to the values or specifications in the software manual. The only difference lies in the less acurate identification of the basic emotion contempt. However it has to be noted that FaceReader is still in an experimental state for the detection of this specific emotion. Additionally it has to be said, that FaceReader labeled the contempt expressions as neutral because the intensity bar was way higher for neutral than contempt. The reason for this could be because contempt is quite the subtle expression and FaceReader has it’s problems with very low intensities of facial expressions (see below). B. Specific difficulties with low image quality The analysis for selected training material of the FACS shows a more nuanced picture: on the one hand on average FaceReader has precisely identified the observable emotions in videos. Ultimately, only three were not sufficiently precise detected. The "performance values" calculated in the present work and the calculated "agreement index" speak for a relatively high reliability of the software. On the other hand FaceReader recognized less exactly the base emotions contained in the videos of the FACS as in the emotional visualizations of the ADFES.  However, it must be taken into account that the facial expressions of the selected FACS material contains only partly basic emotions with little pronounced muscle activity and low intensities, which is why FaceReader has often given the neutral facial expression a higher priority than a basic emotion when coding. Incidently FaceReader failed this toughness test. Although FaceReader was amazing in identifying the rightful Action-Unit-combination for a certain facial expression, suprisingly the software still couldn‘t identify the correct and corresponding basic emotion which could indicate that the analysis of Action Units and emotions are two different things for FaceReader when in reality these Action-Unit-combinations indicate an emotion and FaceReader sometimes can’t make the connection it seems. Therefore, it needs be clarified why FaceReader makes mistakes in analyzing certain high quality photos, sometimes even when the Action-Unit-combination was identified correctly, but then the corresponding matching emotion was not and also why sometimes a photo of outstanding quality could not be analyzed by FaceReader. One idea for making the software more flexible would be to support profile pictures, which means that emotions and Action Units can be analysed, even when the face can only be seen from the side. Higher precision and performance ability All in all this addition in the versions of the FaceReader-family (version 7.1) shows, that the software has made progress over the years and continues to do so. The validation study shows higher precision and performance-ability. As long as the photo and video quality are high (as stated in the FaceReader handbook), the camera angle is straight, shows the front of the face and the lightning is right, the results will be outstanding. The most surprising and also most relevant issues of FaceReader are listed below: - FaceReader is really good in finding out the correct emotion, but in many cases the parameter value is not high enough to get labeled correctly. Instead the neutral facial status is displayed. - FaceReader sometimes produces different results for identical photos. This is the case for emotions as well as for Action-Unit-combinations and it is one of the more striking result of the validation. Concerning Action-Unit-combinations: even the intensities seems to differ from time to time with the exact same photo. - Sometimes FaceReader can’t analyze a seemingly "perfect" photo that has top conditions for an analysis by FaceReader according to the handbook. The fact stands that FaceReader is amazing if you want to analyze facial expressions and emotions and the software has a bright future considering the steadily progressing digitalization and growing interest of companies in knowing the emotional state of their target groups. References - Ekman, P. (1970). Universal Facial Expressions of Emotions. California Mental Health Research Digest,8(4), 151-158. - Ekman, P. & Heider, K. G. (1988). The Universality of a Contempt Expression: A Replication. Motivation and Emotion, 12(3), 303-308. - Ekman, P., Friesen, W. V. & Hager, J.C. (2002). Facial Action Coding System. Salt Lake City: Research Nexus, a subsidiary of Network Information Research Corporation. - Lewinski, P.; Fransen, M. L.; Tan, E.S.H. (2014). Predicting Advertising Effectiveness by Facial Expressions in Response to Amusing Persuasive Stimuli. Journal of Neuroscience, Psychology, and Economics, 7, 1-14. - Van der Schalk, J., Hawk, S. T., Fischer, A. H., & Doosje, B. J. (in press). Moving faces, looking places: The Amsterdam Dynamic Facial Expressions Set (ADFES), Emotion. --- ## Analyzing the mealtime behaviors of children with autism URL: https://noldus.com/blog/analyzing-mealtime-behaviors-children-autism Published: 2018-10-15 11:29:00 Description: Disrupted mealtimes and feeding challenges may risk the development of family stability, as well as the social skills and well-being of a child. Which strategy should families use to support meal time engagement? Nutrition is one of the basic needs of human beings. In Maslow's pyramid, it is at the basis of all our needs. Among other things, we require food to keep our bodies in balance. Yet, mealtimes are often a challenge to parents. When it comes to food, or healthy nutrition, a kids' statement such as "I'm not going to eat that" is not unusual, just like not wanting to try new foods or just refusing to eat. The food ends up on the floor, or on the wall, but definitely not in the kid's mouth. This behavior is very frustrating, and it worries many parents because eating is vital and everyone wants their child to be healthy and grow well. FREE WHITE PAPER Tools for infant studies Learn more about the software tools available for infant studies. - Capture behaviors with video - Annotate behaviors accurately - Unobtrusive emotion analysis Get your copy instantly Children with autism are often very selective eaters Mealtimes are an especially complex matter for children with Autism Spectrum Disorder (ASD). Children with autism search for predictability in the ritual of eating. For example, they want to know what is being eaten, how much should be eaten, how long the meal will last, and what exactly is expected from them during mealtimes. Another thing that makes mealtime complex is that many children with ASD often show a preference for a certain color of food that they absolutely do not want to deviate from, or they might have another specific preference like the food should not crack too much when they put it in their mouth. In addition, some kids only want to eat bread or will not eat hot meals. Eventually, parents don't feel like struggling anymore and they give in. These disrupted mealtimes and feeding challenges may risk the development of family stability, as well as the social skills and well-being of the child. Ways to support participation during mealtimes So, which strategy should families incorporate to support mealtime engagement? Should they intervene, distract, or ignore their child, modify the environment, prepare preferred food, or disguise nutrients in other food? Researchers at the University of Wisconsin-Madison, USA, conducted a study to explore the frequency and characterize the purpose of props used during mealtimes with children with ASD. Props are items that support child participation during mealtime, such as toys or typically child friendly items or common household objects. Twelve families with a total of 14 children with ASD that experienced mealtime challenges participated in the study. For this, a secondary video analysis was taken from a previous, larger mixed-methods study on the impact of mealtime challenges and eating difficulties in children with ASD on family mealtimes. Using behavioral coding software to review and visualize observations The use of props, coded as "present" or "not present" during mealtime videos, was identified as a component of caregiver strategies embedded within six categories: - 1.Parent intervening and ignoring - 2.Meal preparation and adaptability - 3.Positive reinforcements - 4.Play and imagination - 5.Distractions - 6.Modeling Mealtime videos were uploaded into The Observer XT. Hereby, coders were able to review, visualize, and independently code mealtime observational data in the coding software. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Results of behavioral analysis In 75% of the cases, props were used during mealtime, mainly within the strategies of meal preparation and adaptability, distraction, and positive reinforcement (e.g. holding toys or stuffed animals, or reading books aloud throughout mealtimes). The props were meant to support child participation and regulation. For instance, the prop could help to calm a child, as holding a toy provided some comfort, or support the child's focus. In some families, props were also used as a reward to reinforce positive eating or mealtime behavior. For example, a mother required that the child take bites of food in order to put their preferred stuffed animals on the table. Using props during mealtime makes sense for children with ASD Children with ASD may benefit from integrating toys or other items (such as electronics or books) into mealtimes to support their behavioral regulation. However, chances are that parents may be resistant to exploring the integration of these items or are not revealing that they are currently using such items for their child during meals due to social disgrace. After all, not everyone finds it appropriate to bring toys or tablets to the table during mealtimes. Perhaps practitioners could play an important role in this and examine the effectiveness of using props in each specific home context. Surely, props have the potential to be simple, affordable, and supportive tools to be integrated into family mealtime. Reference Muesbeck, J.; St. John, B.M.; Kant, S. & Ausderau, K.K. (2018). Use of Props During Mealtime for Children With Autism Spectrum Disorders: Self-Regulation and Reinforcement. Occupational Therapy Journal of Research: Occupation, Participation and Health, 38(4), 254-260. https://doi.org/10.1177/1539449218778558 --- ## Smile like you mean it URL: https://noldus.com/blog/automated-facial-expression-analysis Published: 2018-09-06 15:01:00 Description: Of all human expressions, a smile is the most universal. But can you tell which smile is real and which is false? Of all human expressions, a smile is the most universal. It has tremendous power and can even transform your own subjective state. For example, when not in a good mood originally, smiling can increase subjective-rated happiness1. Pretty cool, eh? But when is a smile not a smile? When it’s literally not that. But when and how can a smile not be a smile? Simple: when it’s false. Automated facial expression analysis In the early 80s, Paul Ekman and Wallace Friesen2 proposed that there are two types of smiles: real, or ‘felt’ smiles, and false ones. The real ones are also called Duchenne smiles, named for Guillaume Duchenne, who first characterized the facial muscles needed to make the expression happen. According to their research, felt smiles activate muscles in the eyes and false smiles do not3. In addition, false smiles have been shown to be more unilateral, meaning the mouth curls more to one side. In the classic image to the side4, can you tell the difference between the two smiling Pauls? Two smiling Pauls. Can you tell which smile is real and which is false? Automated facial expression analysis tools, such as FaceReader5, can not only characterize expressions like happiness, but they can also determine the individual muscles used. The muscles, called Action Units6, are expressed on a categorical scale (ranging from A to E) based on the amount of muscle needed. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download FACS Action Units There are twenty eight main Action Units in the face7, of which FaceReader can classify twenty. Three of those, AU6, AU7, and AU12 are the three muscles needed to express happiness (see here for video). FaceReader detects the presence of a unilateral smile with AU14. Thus, using FaceReader, I wanted to test expressions from those who were really smiling or just faking it. A video8 was sent to volunteers via the online platform, FaceReader Online9. The video, which was found via YouTube, was a series of clips of ‘fails’, which is to say, situations of physical comedy. The results were exported to FaceReader in order to classify the Action Units. Finally, data were exported to The Observer XT for segmentation and detailed analysis. Each respondent video was subsequently classified as ‘neutral’, ‘real’, or ‘false’ smiling. Data were segmented blindly, which is to say that I had no idea what muscles were active. I simply coded ‘real’ and ‘false’ based on my own expertise and knowledge of faces. Finally, the Action Unit data was exported as a percentage of time in which the AUs were active. Real or false smiles? The hypothesis was simple: real smiles will show more AU6 and AU7, whereas false smiles will show more AU14. In addition, the categorical expression of the AUs will be stronger in the eyes of real smiles. Not surprisingly, that’s what I found. Real smiles showed more AU6 and AU7, whereas false smiles showed more AU14. In addition, the AUs themselves were stronger with their respective smile. It can truly be said that you smile with your eyes. What does that mean for you and your business? Can your interviewer tell the difference between that felt or false smile when the respondent is describing her experience with your product? Maybe your respondent isn’t sure if she liked that sample, so she’s just telling you what she thinks you want to hear. Two of Dominic’s smiles. Which is real and which is false? Furthermore, what about your facial expression analysis tool: can it tell the difference? Smiling Paul was a warm-up. Let’s try another example. In the image to the side, can you tell which of Dominic’s smiles is real and which is false? What if I made it even easier and showed you the AUs? Remember, AU6 and AU7 vs AU14: You guessed it. It was the one on the right. Interestingly, FaceReader reads Dominic as happy in both images; however, only one smile was real. So when you ask a respondent about your brand, product, or service, be sure to check their eyes. Can’t tell the difference or don’t want to have someone trained to do it? Try FaceReader with Action Unit Module. The Eagles may have said it best when they wrote, “You can’t hide your lying eyes.” I struggled with this for many years. I have a very hard time showing a real smile in pictures. It has gotten better, but only after my friends finally told me that I looked bored and angry in pictures. The breaking point was one person commented that my face was ruining the shot! It was a joke, but many a truth is said in jest. To fix the issue, and to keep my friends, I spent many years practicing in front of the mirror. The issue was simple: I couldn’t fake it. It seems that in order to express happiness, I must actually be happy! The practicing paid off. Now, whenever I’m forced into having my picture taken, I remember my mirror training. But now, like Harry Potter with his stag, I conjure my Patronus10 and you get a smile. See for yourself; progress: Progress: a genuine, felt smile after plenty of mirror practice. Oh: still wondering about which Smiling Paul was the correct one? It was the Paul on the left. References - Smile: A Powerful Tool - Ekman, P. & Friesen, W.V. J Nonverbal Behav (1982) 6: 238. https://doi.org/10.1007/BF00987191 - What Science Has to Say About Genuine vs. Fake Smiles - Retrieved from https://sonnemann.files.wordpress.com/2012/05/paul-ekman1.png - FaceReader - https://en.wikipedia.org/wiki/Facial_Action_Coding_System - https://www.youtube.com/watch?v=yRB_UBef-sA&t=124s - FaceReader Online - The Observer XT - Patronus Charm by J.K. Rowling --- ## How to master automatic Facial Expression Recognition URL: https://noldus.com/blog/automatic-facial-expression-recognition Published: 2018-08-30 13:36:00 Description: Many researchers have turned towards using automated facial expression recognition software to better provide an objective assessment of emotions. Emotions can be both a gift and a curse. They are what makes us human, and we all experience them – whether it is through the ability to feel love and happiness, or pain and suffering. In addition, they are difficult to hide. All emotions, whether they are suppressed or not, are likely to have a physical effect. However, studying emotions can be hard, since it is not often clear how to exactly interpret them. Automatic facial expression recognition For this reason, many researchers have turned towards using automated facial expression recognition software to better provide an objective assessment of emotions. Because human assessment of emotions has many limitations and biases, facial expression technology can be used to deliver a greater level of insight into behavior patterns. This video shows FaceReader results. Noldus' FaceReader software is one example of a tool that is specifically designed for this purpose, and is used in human behavior research for applications such as psychological research, usability studies, and advertising and consumer behavior. Classifying facial expressions and emotions The American psychologist Paul Ekman found that some facial expressions are universal, and can be reliably measured in different cultures. FaceReader bases its algorithms on these original basic expressions, and can automatically determine the presence and intensity of the following emotions: Happy, Sad, Angry, Surprised, Scared, Disgusted, and Neutral (no emotion). It can also analyze interest, boredom, and confusion, which are three commonly occurring affective attitudes. The software works by following these consecutive steps: - 1.Face Finding – FaceReader finds an accurate position of the face using the popular Viola-Jones algorithm - 2.Modeling – An accurate 3D modeling of the face is made, which describes over 500 key points - 3.Classification – An artificial neural network uses over 10,000 pictures to classify the basic emotional expressions and a number of properties - 4.Deep face classification – This method allows FaceReader to directly classify the face from image pixels using an artificial neural network to recognize patterns. This allows the software to analyze the face even if a part of it is hidden Types of input sources commonly used with FaceReader include video analysis, live analysis using a webcam, and still images. Once classified, emotions can be represented as line and/or bar graphs as well as in a pie chart, which shows the percentage per emotion. In addition, FaceReader can also calculate gaze direction, head orientation, and characteristics such as gender, and age. Action unit analysis Automated facial coding can be further extended to an action unit level, according to the FACS (Facial Action Coding System). To backtrack a little, the FACS is a facial expression coding system meant for measuring facial expressions and describing all observable facial movement. The movements of individual facial muscles are broken down into specific action units. FaceReader's Action Unit Module is capable of analyzing 20 of these action units, including Cheek Raiser, Nose Wrinkler, and Dimpler. Action Units are responsible for facial expressions. Fields of research using facial expression detection Because FaceReader can serve as an automated, non-intrusive measure of engagement, it can be used in many applications. Some notable examples of fields using facial expression research include: - Ad testing and consumer behavior FaceReader can be used to examine metrics such as consumer interest in a product and the effectiveness of video advertisements. Emotional responses to advertisements tend to have a heavy influence on consumers' intentions to buy a product – using facial coding analysis, researchers could perform testing and present evidence that a certain expression (ex. Happy) may predict an advertisement's success or a positive shift in attitude towards the brand. - Usability testing In order to understand how real users experience a website or application, researchers can use facial expression technology to analyze participants' facial expressions during testing. This helps to analyze how participants feel as they navigate through a site, and could clarify which tasks are frustrating or enjoyable, as well as what needs to be improved upon. - Psychological research If you have an interest in better understanding the emotions and communication between people, you can benefit greatly from a more in depth understanding of facial expressions. Some examples of interactions that could be studied with FaceReader include those between parents and children, teachers and students, businesspeople and negotiators, and health professional and patients. Would you like to learn more? For more information, please feel free to contact us to speak with a Sales Consultant about how FaceReader can help assist you with your research. In addition, you can download a free whitepaper about FaceReader's methodology. We look forward to working with you! FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download More information on these websites - Noldus FaceReader - Usability First - Usability Testing - APA - Facial Expressions - Wikipedia - Facial Action Coding System - Insights Association - Facial Recognition in Market Research - Wikipedia - Paul Ekman Selection of scientific publications - Danner, L.; Sidorkina, L.; Joechl, M.; Duerrschmid. (2014) Make a face! Implicit and explicit measurement of facial expressions elicited by orange juices using face reading technology. Food Quality and Preference, doi:10.1016/j.foodqual.2013.01.004. - D'Arcey, T.; Johnson, M.; Ennis, M. (2012). Assessing the validity of FaceReader using facial electromyography. Proceedings of APS 24th annual meeting. - D'Arcey, J.T.; Johnson, M.R.; Ennis, M.; Sanders, P.; Shapiro, M.S. (2013). FaceReader's assessment of happy and angry expressions predicts zygomaticus and corrugator muscle activity. Poster presentation VIII-014 Association for Psychological Science meeting, 23-26 May 2013. - den Uyl, M.J.; van Kuilenburg, H. (2005). The FaceReader: Online facial expression recognition. Proceedings of Measuring Behavior 2005 (Wageningen, 30 August – 2 September 2005), pp. 589-590. - Gudi, A.; Tasli, H.E.; den Uyl T. M. & Maroulis, A. (2015). Deep Learning based FACS Action Unit Occurrence and Intensity Estimation. Automatic Faces and Gesture Recognition (FG), doi: 10.1109/FG.2015.7284873. - Lewinski, P.; den Uyl, T.M.; Butler, C. (2014). Automated facial coding: validation of basic emotions and FACS AUs in FaceReader. Journal of Neuroscience, Psychology, and Economics, 7(4), 227-236. - Van Kuilenburg, H.; Wiering, M; Den Uyl, M.J. (2005). A Model Based Method for Automatic Facial Expression Recognition. Proceedings of the 16th European Conference on Machine Learning, Porto, Portugal, 2005, pp. 194-205, Springer-Verlag GmbH. --- ## Understanding the digital world at the Social Media Lab URL: https://noldus.com/blog/understanding-digital-world-social-media-lab Published: 2018-08-15 09:39:00 Description: In this unique lab, technology is applied to understanding user experience, behavior on social media, and much more. Many people enjoy using social media to share personal and professional activities with friends, colleagues, and so on. Because social media is an essential communication channel these days, it is of great importance to understand how people make use of social media. The Social Media Lab in Mons, Belgium connects with business and academics in order to better understand social media use and the digital world in general. In April 2018, the usability lab part of the Social Media Lab, in Mons was officially opened. Prof. François Lambotte and his team received the press and many guests to present the premises where exciting experiments will be taking place. I had the pleasure of visiting this lab myself and interviewing two researchers. Social Media Lab The Social Media Lab in Mons, Belgium brings together researchers, students, professionals, and professors from different disciplines (communication, marketing, journalism, computer science, etc.). Together they try to understand the digital world, train themselves and others in the use of new technology, and learn more and advice about new professional practices. The Social Media Lab at the University of Louvain uses Noldus' software to integrate different data streams and set up experiments. User Experience Lab / Social Media Lab components - The Observer XT for easy data integration and behavior analysis - FaceReader for detailed emotion analysis - MediaRecorder for synchronous AV recording - Tobii eye tracker for the best analysis of eye movements and attention - Biometric tools allowing for precise measurements such as blood pressure, sweating and others FREE WHITE PAPER How to build an AV lab Do you want to learn more about setting up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download The Social Media Lab at UCL Mons The research center of communication of UCL acquired a true laboratory of expertise in the digital world. The Social Media Lab's research has a theoretical, practical, and technological scope: the analysis of interactions and uses makes it possible to identify new needs and new tools and to support their implementation and use by researchers and professionals. Three main areas of interest The activities in this Social Media Lab can be assigned into three main areas: - Service to society: the SML is committed to developing relationships with professionals and civil society actors active on socio-digital media issues; - Research: SML wants to be a laboratory of expertise in technological appropriations and unique interface design in Belgium; - and finally, Education. Human behavior labs Are you interested in getting to know how other teams have designed their lab? At Noldus Labs we take you on a photographic tour and show you how they designed their rooms, what equipment they chose, and which software tools are used for data collection and analysis. This section covers a wide range of application domains, organizations, and technology: from desktop software to mobile applications, from healthcare to military systems, from consumer electronics to office hardware, from focus groups and qualitative testing to physiological measurements and eye tracking, from corporate to educational facilities, from stationary to portable labs. Enjoy the tours! Interested in human behavior research? Read more on 'How to study human behavior'! EXPLORE Human behavior research labs Discover how research teams around the world have designed their labs for studying human behavior. - Lab design inspiration - Equipment and software choices - Data collection and analysis tools Explore labs --- ## How to characterize behavioral phenotypes in a behavioral analysis facility URL: https://noldus.com/blog/behavioral-analysis-facility-rouen Published: 2018-07-27 11:45:00 Description: Introducing the Behavioral Analysis Facility. Researchers evaluate the behavioral and functional activities of new pharmacological drugs using diverse functional tests. Learn more about their recent projects. The Behavioural Analysis facility (Service Commun d'Analyse Comportementale, SCAC) is a research infrastructure for life science of Institute of Research and Innovative in Biomedicine (IRIB) of University of Rouen, France. Watch this video and learn more about recent research at this lab such as research into the relationship between food intake and mood disorders. And find out why Dr. Do Rego chooses automatic measurements to analyze behavior. How to characterize behavioral phenotypes in a behavioral analysis facility Watch the video on YouTube Behavioral Analysis Facility | Noldus Customer Success Story Researchers at this lab evaluate the behavioral and functional activities of new pharmacological drugs using diverse functional tests such as: anxiety, fear, and depression, nutrition, food and drink consumption, metabolism, development (neonatal development and maternal behavior), learning and memory, pain, motor behavior (spontaneous activity, motor coordination), sensorimotor gaiting, addiction (appetitive or aversive properties), neurotoxicity and stroke. Automate behavioral tests Next to PhenoTyper, SCAC has animal rooms and rooms specially dedicated to animal behavioral experiments. It brings together various classical and original devices, at the forefront of current technology. For example for gait analysis, and of course EthoVision video tracking software to automate for example an open field or plus maze experiment. This is what Dr. Do Rego tells us about these tools "CatWalk XT & EthoVision XT, without question, are very valuable behavioral testing tools for both novices as well as for experts due to their easy handling, flexibility and user-friendliness." Animal models This facility is specialized in the creation and evaluation of animal models, mainly rodents, reproducing some emotional, dementia, neurodegenerative and motor diseases affecting humans. The lab has the objective to develop new animal models, to characterize complete behavioral phenotypes and in the reproducibility of our experimental models presenting deficits of neurological, psychiatric order or associated to the ageing and stroke and consequently to be able to test new pharmacological drugs with therapeutic aim within the framework of national and international scientific collaborations with academic and industrial partners. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## Normalization of blood sugar reduces enhanced rewarding effect of smoking URL: https://noldus.com/blog/blood-sugar-rewarding-effect-smoking Published: 2018-07-18 12:03:00 Description: Why are the rewarding effects of nicotine greater in diabetic rats? When you think of diabetes and tobacco use in the same context, there are some clear similarities between the two – they are both prevalent, and can both be deadly. According to the World Health Organization, in 2014 there were 422 million people worldwide counted as having diabetes, with most of them diagnosed with type 2. And, in 2015, an estimated 1.6 million deaths were directly caused by diabetes. Switching gears to tobacco use, the World Health Organization reports that in 2015, over 1.1 billion people smoked tobacco. In addition, Centers for Disease Control and Prevention reports that tobacco use causes nearly 6 million deaths per year. This number is estimated to increase to 8 million in 2030. The link between diabetes and smoking Type 2 diabetes and smoking clearly both cause serious health issues on a global scale. But did you know that they are also linked? In fact, nicotine use increases the risk of type 2 diabetes. It also increases insulin resistance, which can make diabetes worse. Diabetes type 1 and 2 Diabetic patients have hyperglycemia, or high blood sugar (glucose levels) resulting from a lack of insulin. In Type 1 diabetes, patients have no insulin at all, as the insulin producing cells are destroyed by their own immune system. In the more common type 2 diabetes, patients have too little insulin and are also "insensitive" to insulin; they have a lack of action at the insulin receptors. Rewarding effects of nicotine In addition to this link between nicotine and diabetes, animal studies have also pointed to the enhanced rewarding effect of nicotine in animal models of diabetes. If these results could be translated to humans, this would indicate that smoking is even more "enjoyable" for diabetic patients. Recent research from the Western University of Health Sciences (Pomona, CA, USA) and the University of Texas (El Paso, TX, USA) investigated these rewarding effects of nicotine, and how they are enhanced in rat models of diabetes. In their study, they sought to find the mechanism behind this effect. STZ Rat model for diabetes The rat model for diabetes used in this study was created by a streptozotocin (STZ) treatment. The administration of this chemical induces diabetes by destroying insulin producing cells in the pancreas. Sex-dependent effects Interestingly, the researchers studied both male and female "diabetic" rats, and the effects of nicotine seem to be sex-dependent: the effects of STZ on blood glucose levels were larger in male rats. Study design This study investigated whether the rewarding effects of nicotine in these diabetic rats was caused by the direct effects of insulin or due to excessive blood glucose levels. Rats underwent a conditioned place preference (CPP) procedure to study the rewarding effects of nicotine, while receiving either insulin supplementation or a drug called dapagliflozin to increase blood glucose levels. Conditioned Place Preference test The CPP apparatus used in the study was made out of two chambers and a small start box. The flooring and the black and white patterns on the wall were different in each chamber. On the first day of the CPP procedure, each rat was placed in the start box, which closed after it left the box. Then, time spent in the two chambers during a total of 15 minutes was measured using EthoVision XT video tracking. Throughout the next six days, the rat would receive daily nicotine or saline injections and was placed in the chamber they initially did not prefer. On day eight, the same procedure as day one was repeated. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Nicotine conditioning Nicotine conditioning worked for all male rats, as they preferred the nicotine paired chamber over the other. This effect was even larger in STZ male rats. Insulin and dapagliflozin both decreased this effect. The effect of STZ differed for males and females, as well as the effect of nicotine on the STZ females compared to males. Female STZ mice did not experience an increased effect from nicotine in comparison to their "non-diabetic" female conspecifics. Researchers suggest that one of the explanations for this is that females are less sensitive to insulin actions in the brain. Nicotine did increase blood glucose levels in all rats. Mechanism behind the rewarding effects of nicotine This study provides proof that the enhanced rewarding effects of nicotine in diabetes, at least in rats, can be reduced by the common drugs insulin and dapagliflozin. The latter increases blood glucose levels without altering insulin levels, suggesting that the reduced rewarding effect of nicotine is not mediated by insulin alone. References Íbias, J.; O'Dell, L.E.; Nazarian, A. (2018). Insulin dependent and independent normalization of blood glucose levels reduces the enhanced effects of nicotine in a rodent model of diabetes. Brain Behavioural Research, 351, 75-82. --- ## Using facial expression analysis during a musical experiment URL: https://noldus.com/blog/facial-expression-analysis-musical-experiment Published: 2018-07-10 13:46:00 Description: Music affects people, that's for sure. But to what extent varies per person. To measure facial expressions during a musical experiment, FaceReader Online is the easy-to-use tool. The influence of music on our emotions intrigues me, and raises many questions. For example, how is it possible that my emotion changes as music speeds up or slows down? Why does the song 'Happy' by Pharrell Williams make me smile, and why do I react in the opposite manner to the song 'Tears in Heaven' by Eric Clapton? Is it really the music itself that triggers these emotions, or is it the memory of a particular event that fits with the music or any other association? Why do I prefer to listen to fast songs at one time and to slow songs at another time? Can anyone else around me read my face and figure out what emotion the music that I'm listening to evokes? Does everyone react the same way? And if they don't, why not? The link between music and emotion Many processes that take place in our brains determine how we react to music. Scientist have figured out that music affects people, but to what extent varies per person. For example, the volume of the music has the most influence on emotions. After that, the pace of the music follows. The melody and the instruments play a role as well. Time to do a small experiment I decided to do a small experiment using FaceReader Online to measure facial expressions while my participants watched a music video on their own computer or laptop. I chose three different music fragments: - 1. Drummer boy Gordo performing his act on the street, using plastic baskets - 2. A rendition of Beethoven's "Ode to Joy" by Beaker, Dr. Bunsen Honeydew's loyal assistant from the Muppets - 3. A sad and emotional piano song, purely instrumental FaceReader Online has an advantage in that you can invite people from all over the world to join your study. Sending a link via an email and starting the experiment was fast and simple. Several people responded, and the recordings simply appeared one by one on my dashboard. Did the Muppets make people smile? After easily grouping my participants, the next step was to look at the results. Within FaceReader Online, it is possible to make a quick comparison of your results. For example, you can compare the media files, the participant groups (male/female or based on age or country e.g.), or certain episodes within the media files that you have selected beforehand. Expression comparison of all participants Expression Intensity of the males The results mostly confirmed my expectations. The Muppets fragment indeed resulted in the happiest faces. The drummer boy and the piano man mainly triggered neutral facial expressions. What surprised me was that the piano song showed little sad emotions overall. Maybe in this case, the distinction between a neutral feeling and a sad feeling was not large enough. When comparing males and females, two fragments showed some differences. Males responded with a much higher level of excitement (arousal) to the piano song, and were happier when listening to the drummer boy. The ease of use of FaceReader Online FaceReader Online offers an interactive web page allowing you to choose how you want to visualize your results. It is quick, easy, and straightforward to use. For a more detailed analysis, all results can be exported to the 'offline' FaceReader environment. This allows you to review all participant recordings and gives you access to a larger number of analysis tools and visualization options. As a result of this experiment, I discovered that music and emotions are complex. But, on the other hand, FaceReader Online definitely is not. In fact, it is just the opposite; it is easy to work with, and the online manual is very useful. In my opinion, the convenience with which you can let people from all over the world participate in your research is its greatest advantage. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources References - FaceReader Online - Waarom muziek ons raakt (in Dutch) - Music and emotion - Wikipedia --- ## Using gait analysis to analyze Parkinson’s in rat model URL: https://noldus.com/blog/gait-analysis-parkinsons-rat-model Published: 2018-06-28 08:14:00 Description: Contrary to common methods, gait analysis can detect clinically relevant symptoms early on, researchers say. We all know Parkinson's as the neurodegenerative disorder that affects mobility in a life-changing way. The slow movement, shuffling of the feet, and difficulties initiating movement are all bradykinesia signs that we recognize as typical for this disease. Clinically relevant symptoms So, why do most commonly used behavioral tests in animal research on Parkinson's disease (PD) not actually assess behaviors that resemble these symptoms? That is what Jordi Boix and his colleagues from the University of Auckland in New Zealand asked themselves. Parkinson's model in rats In their study, which was recently published in Frontiers in Behavioral Neuroscience, the researchers used two rat models of PD to investigate a number of gait parameters in hopes to find resemblance to human PD symptoms, and to specifically find them early on. The rat model used in this study was a 6-OHDA lesion model as is common in many PD studies. Injection of 6-OHDA causes degeneration of the dopaminergic system causing effects in the brain similar to those observed in PD. The severity of the symptoms depend on the location of the injection, as it clinically does depending on the location of the cell death. In this study, placing this lesion in either medial forebrain bundle (MFB) or in the striatum resulted in two models with differing severity of symptoms. The MFB lesion had much more devastating effects. Gait analysis method To measure a range of gait parameters, the researchers used CatWalk XT gait analysis. Before each session, the animals were pre-trained. In combination with use of a goal box and some Cocopops®, this resulted in the collection of enough straight runs along the 70 cm glass plate to accurately acquire and assess gait and footprint parameters. Parameters range Using CatWalk XT, Boix assessed 21 gait parameters. General parameters such as average speed, but also dynamic paw parameters (stand phase, swing phase, etc.), coordination parameters (print position, phase dispersion, etc.), and static parameters like print area were measured. Bradykinesia The greatest impact the 6-OHDA lesion had was on average walking speed and cadence. Especially in the MFB lesion group, almost all gait disturbances the subjects showed paralleled human PD symptoms. Moving slowly in combination with reduced cadence and the altered swing phase reflected bradykinesia. Also, the altered stand index, stride length, and print position mimic the typical small steps shown in PD patients. Gait analysis as reliable method Boix and his colleagues found gait analysis to be a reliable method for the detection of motor deficiencies relevant to PD. Particularly, it allowed for early detection, some as early as one week after the lesion was applied. As the symptoms closely resemble clinical symptoms, the use of gait analysis can provide a valuable tool in the development of future therapeutic strategies for PD. References - Boix, J.; von Hieber, D.; Connor, B. (2018). Gait Analysis for Early Detection of Motor Symptoms in the 6-OHDA Rat Model of Parkinson's Disease. Frontiers in Behavioral Neuroscience, 12, 39. Interested in reading more about CatWalk XT studies? RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## The role of explicit bias in working with depressed cardiac patients URL: https://noldus.com/blog/explicit-bias-depressed-patients Published: 2018-06-18 15:20:00 Description: Using simulated medical encounters, Dr. Crapanzano and her team measured the influence of bias in the medical students' diagnosis and treatment plans for a patient presenting as mildly depressed. Living with a heart disease can be stressful. After all, a well-functioning heart is vital, and it can be tough to realize that your heart is failing. Coronary artery diseases (CAD) can often lead to experiences of psychological problems, such as becoming anxious and feeling tired or lifeless, with the possibility that depression can occur or get worse. In addition, depression can lead to a greater chance of developing a CAD as well. As there is a strong link between our physical health and our mental health, it should not come as a surprise that depression is an independent risk factor for CAD and its complications, and CAD in turn can be a cause of depression. Physicians' attitudes towards depressed patients Unfortunately, evidence suggests a lack of awareness of such links between mental and physical conditions among physicians, especially in cases where the mental illness is complex and accompanied by communication or behavioral challenges that interfere with the clinical presentation. However, once physicians become aware of their attitude towards such patients, it is possible to modify their behavior with education, motivation, skill, and cognitive resources. In order to explore this topic further, Dr. Kathleen Crapanzano and her team conducted a study to explore the role of explicit bias in medical students' diagnoses and treatment plans for a standardized patient (SP) presenting as mildly depressed. They then compared these students' performance with medical students encountering an SP without depression. Simulating medical encounters to measure the influence of bias Crapanzano and her team intended to answer three questions in this study: - 1.What is the incidence and degree of internal medicine students' extrinsic bias toward patients with depression as measured by the Medical Condition Regard Scale (MCRS)? - 2.What relationships, if any, exist between medical students' MCRS scores and objective structured clinical exam (OSCE) evaluation scores? - 3.What differences in OSCE performance and facial expressions are observed in medical students who encounter a depressed SP compared to medical students who encounter a non-depressed SP? The randomized controlled trial included 185 internal medicine students (97 of these students were placed with the depressed SP-group). All SPs were actors who portrayed a patient with acute chest pain. Half of the SPs were also trained on symptoms of depression. However, they were instructed not to mention their depression unless specifically asked about it by the students. Measuring students' facial expressions when meeting with depressed patients Within 15 minutes, the medical students were instructed to obtain a history, perform a physical examination, and inform the SP about their diagnostic impression and treatment plan. Afterwards, the SPs completed the OSCE checklist in order to assess the students. All clinical exams were videotaped and analyzed using FaceReader to measure the facial expressions of the students. The medical students completed a structured post-encounter note (PEN) that described their primary diagnoses and workup plan, and a questionnaire (MCRS) to measure their self-reported extrinsic bias toward depressed patients. Working with depressed patients releases feelings of disgust The researchers found an overall low regard towards patients with depression in both groups of students. However, the results of the study did not support the hypothesis that this low regard was related to the students' performance during the simulated clinical exam. The students may have been aware of their biases while examining and treating the patients during the simulated encounter, and could have suppressed these feelings. The students who worked with the depressed patients showed more occurrences of the disgust affect while students who worked with non-depressed patients showed more occurrences of a neutral affect. Crapanzano and her team also found differences within gender groups. Male students were more likely to demonstrate an angry affect, while female students were more likely to show a sad or scared affect and express feelings of empathy. In conclusion, the researchers recommend conducting further research to examine the effects of patient mental health conditions on physician examination procedures, diagnostic behaviors, and patient outcomes. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Interested in human behavior research? Read more on 'How to study human behavior'! References - Crapanzano, K.; Fisher, D.; Hammarlund, R.; Hsieh, E.P. & May, W. (2018). Internal Medicine Residents' Attitudes Toward Simulated Depressed Cardiac Patients During an Objective Structured Clinical Examination: A Randomized Study. Journal of General Internal Medicine, 33 (6), 886-891. DOI: 10.1007/s11606-017-4276-7 - Jones, S.; Howard, L.; Thornicroft, G. (2008). Diagnostic overshadowing: worse physical health care for people with mental illness. Acta Psychiatrica scandinavica, 118 (3), 169–71. - Merrick, J.; Merrick, E. (2007). Equal Treatment: Closing the Gap. A Formal Investigation into Physical Health Inequalities Experienced by People with Learning Disabilities and/or Mental Health Problems. J Policy Pract Intellect Disabil, 4(1), 73. --- ## World Cup success and emotions URL: https://noldus.com/blog/world-cup-success-and-emotions Published: 2018-06-15 15:10:00 Description: Recent scientific research shows that emotional expressions like anger and happiness matter in being successful in the group phase of the soccer World Cup. Recent scientific research shows that emotional expressions like anger and happiness matter in being successful in the group phase of the soccer World Cup. Researchers took collectible stickers of all players and automatically analyzed their facial expressions in order to get more insight into how emotions influence team performance. FIFA Soccer World Cups Researchers Astrid Hopfensitz and Cesar Mantilla from the University of Toulouse and Universidad del Rosario, Bogotá analyzed 4318 pictures of soccer players from 304 participating teams in 12 editions of the FIFA Soccer World Cup. They wanted to focus on the important role of emotions and expressions during high stakes team contests. Collectible stickers The players' portraits that were used for this study were from collectible stickers that have been produced by Panini for every world cup since 1970. The researchers analyzed the individual players' display of emotions in order to characterize a team's overall emotional level. These stickers are ideal for this kind of study since the photos are generally high quality and taken from a frontal point of view. Automatic face reading Researchers used automated face-reading to evaluate the display of emotions in the players' portraits and concluded that the display of both anger and happiness correlates with a team's performance in the World Cup. Noldus' FaceReader software was used to automatically analyze the photos from 76 different squads. Here are some results you don't want to miss: - Teams whose players display more anger, an emotion associated with competitiveness, concede fewer goals. - Teams whose players display more happiness, an emotion associated with confidence, score more goals. Happy and angry faces over time The researchers indicate that these results are in line with research done about the functional nature of emotions. When discussing the function of emotions, dominant behavior is often shown through angry faces, and confident behavior is seen in happy faces. According to the researchers, angry faces were particularly popular throughout the first half of their period of study (1970-2014). Happiness was found more in the second half of the period of the study (1990-2014). Did you know that the '3 points for a win' rule was introduced in 1994 at FIFA World Cup? It aimed to encourage more attacking and scoring. What now? By having read this blog post, you'll now know that it's all about emotions. Why not test your own angry or happy face? Are you playing defense or offense (midfielders can choose for themselves)? Check your own emotions here by uploading a picture. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Future research Another important thing to mention is that this study concerned only male soccer players. The researchers explained that this was the case because the very first Panini World Cup soccer album for women was produced online in 2011. In addition, due to the links between testosterone, aggressiveness and anger, and differing norms concerning smiling and display of happiness for men and women, the researchers might expect different results for female players. Let's encourage the researchers to pick up this challenge, so we can report on that in another blog post!! Did you know that after six German victories in a row, the Dutch female soccer team became the European champion in 2017? That still puts a smile on my face. Reference Hopfensitz, A.; Mantilla, C. (2018). Emotional expressions by sports teams: An analysis of World Cup soccer player portraits. Journal of Economic Psychology, doi:10.1016/j.joep.2018.04.008 --- ## Alzheimer research and the Morris water maze task URL: https://noldus.com/blog/alzheimer-research-morris-water-maze-task Published: 2018-06-12 09:55:00 Description: First developed in 1981 by Richard Morris, the Morris water maze task is still one of the most popular tests for memory and learning in rodents. The Morris water maze task: first developed in 1981 by Richard Morris, it is still one of the most popular tests for memory and learning in rodents. Alzheimer research One of the research fields this task is commonly used in is Alzheimer's disease (AD). As the most common form of dementia, AD is a neurodegenerative disease that comes with memory impairments, which is precisely what we can test with a water maze. Recent studies focus on several AD risk factors such as insulin resistance and diabetes. Variation in water mazes The Morris water maze task does not require much in setup. The basic needs consist of a large round pool, a platform, and visual cues. Instead of timing the animal by using a stopwatch to measure how long it took the animal to get to the platform, most researchers opt for an automated test using video tracking software such as EthoVision XT. Testing protocols In a nutshell, during a water maze test the rat or mouse learns the location of the platform by using cues in the environment. Normally, subjects decrease their searching time over trials, indicating healthy cognition. In these studies, different variations to the protocol were used. For example, a probe trial, in which the platform is removed, is used to test reference memory. Another example is reversal learning, which is tested by changing the location of the platform. Escape latency Probably the most important parameter in water maze tests is the escape latency, or how long it takes the animal to reach the platform. Correct quadrant Probe trials often use additional parameters like time spent in the correct quadrant or platform zone. Alternatively, Knezovic et al. define the number of mistakes as entering the incorrect quadrant. Swim path In addition to how fast the animal gets to the platform, it is often important to know how it gets there. In other words, what kind of a search strategy is the animal using? Does it rely on the external cues provided, or does is simply swim in circles until it finds the platform? Researchers therefore use parameters like meandering or Whishaw's index to assess the swim path. Velocity Velocity is an important part of how fast an animal can reach the platform, but is it also often taken into account during a water maze test to reflect motivation and/or locomotor abilities. If one of these is impaired, this can cause huge differences in the test results of the rodents while in actuality there might be nothing wrong with their learning and memory capabilities. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Research results Caccamo et al. focused on a gene that plays a crucial role in the insulin signaling pathway, and found that removing this gene alleviated mouse models of AD of their memory deficits. Knezovic et al. investigated whether galactose, an epimer of glucose, could alleviate memory impairment in a rat model of AD. It did. Majkutewicz et al. investigated the age-dependent effects of dimethyl fumarate (DMF), an anti-inflammatory, antioxidative, and neuroprotective drug. Spatial memory and neurodegeneration was more severe in aged STZ rats, but DMF therapy was also more effective. References - Caccamo, A.; Belfiore, R.; Oddo, S. (2018). Genetically reducing mTOR signaling rescues central insulin dysregulation in a mouse model of Alzheimer's disease. Neurobiology of Aging, doi: 10.1016/j.neurobiolaging.2018.03.032. - Knezovic, A.; Osmanovic Barilar, J.; Babic, A.; Bagaric, R.; Farkas, V.; Riederer, P.; Salkovic-Petrisic, M. (2018). Glucagon-like peptide-1 mediates effects of oral galactose in streptozotocin-induced rat model of sporadic Alzheimer's disease. Neuropharmacology, 135, 48-62. - Majkutewicz, I.; Kurowska, E.; Podlacha, M.; Myslinska, D.; Grembecka, B.; Rucinski, J.; Pierzynowska, K.; Wrona, D. (2018). Age-dependent effects of dimethyl fumarate on cognitive and neuropathological features in the streptozotocin-induced rat model of Alzheimer's disease. Brain Research, 1686, 19-33. The project for the heat map image in this post was kindly provided by Istvan Hernadi, PhD, from the University of Pecs in Hungary --- ## Towards automated homecage monitoring of group housed rats URL: https://noldus.com/blog/homecage-monitoring Published: 2018-06-08 11:57:00 Description: Rodent social behavior is important in research on neuropsychiatric disorders, but major limitations hamper progress. This is a guest blog post by Suzanne Peters, PhD. Her thesis is named "The importance of rat social behavior for translational research. An ethological approach", which she defended on April 4th this year. Rodent social behavior is an increasingly important readout parameter in animal research in light of neuropsychiatric disorders, such as schizophrenia and autism. In translational research, animal models are used to understand the mechanism by which disease symptoms manifest. The issue of limited translational value Ultimately, translational research must result in possible treatments. However, there are some major limitations that hamper progress[1]. For example, the limited translational value of animal models[2, 3], as becomes apparent by the lack of reproducibility of research results[4] and an overestimation of treatment effects[5]. Improve housing conditions Several key elements are limiting translational value. First, inadequate housing and developmental conditions. It is important to provide sufficient social experiences to ensure a healthy animal, free from abnormal behavior. As is also imbedded in the European guidelines for the accommodation and care of laboratory animals (European Directive 2010/63/EU and the Commission Recommendation 2007/526/EC). Which indicate that: 'Animals should be socially housed when and whenever possible and provided with an adequately complex environment within the animal enclosure to enable them to carry out a range of normal behavior'. Occurrence of natural behavior Secondly, there is a reduction in natural variation of behavior, through the process of inbreeding and by selection of relatively tame, easy to handle, animals. Behavioral analysis Thirdly, limited and too simplistic analysis of animal behavior. The performed behavioral tests tend to be too simplistic and too short (to capture the full repertoire of behaviors demonstrated by the animal), while the analysis of the behavioral readouts is too limited. Even if an animal demonstrates its full behavioral repertoire, most of the currently used analysis methods are not able to qualify and/or quantify it completely. Animal behavior is thus, mistakenly reduced to a few single behavioral parameters, while covering the full complexity of all behavioral elements displayed by the animal should be the aim. In particular, simplistic behavioral analysis is problematic when the outcomes of experiments are used to interpret the functional meaning of observed behavioral differences. Improving animal behavioral experiments In light of these issues I have performed several experiments to illustrate that a different approach can yield more appropriate measures of behavior. Hereby, the aim is contribute to an improvement in animal behavioral experiments in order to increase the translational value of current animal models, with a special focus on social behavior of rodents. Two main characteristics of my approach are: 1) ethology and 2) automation. Ethology in a rodent lab Ethology is a discipline in which natural behavior of animals is studied in the context of proximate and ultimate causation. The functional meaning of behavior depends on these two distinct causes. Thus, also the biological relevance of observed behavioral changes is taken in account. Adopting an experimental approach that allows, as much as possible, the occurrence of ethological needs, i.e. self-rewarding behaviors of laboratory animals is certainly a challenge. Fortunately, this has been recognized and resulted in the development of systems that monitor socially interacting animals, e.g.[6, 7] for mice. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Socially housed rats For socially housed rats there is currently limited systems available[8], therefore we wanted to develop a system that can monitor socially housed rats. Such systems offer considerable advantages above setups that rely on manual observations of social interaction behavior, because they permit group-housed monitoring of animals in relatively large arenas containing for example shelters, tubes and bedding materials. The test setup should be relatively large, because the expression of social behavior requires space[9]. Automation of social behavior observation The automated analysis of behavior offers great advantages. It allows the measurement of complex behaviors, that usually escape the human eye. It is objective and less prone to errors, plus it can record behavioral changes faster than a human observer[9-11]. PhenoTyper development In the past, our lab has played an important role in the establishment and development of the PhenoTyper and its tracking software EthoVision, both available via Noldus. The tracking software uses top view video images in order to recognize the animals in the cages. This system was originally developed for 24/7 monitoring of individual mice and rats in an environment that allows normal rodent behavior, e.g. exploration, sleeping, nesting and feeding[12]. PhenoTyper 9000 We developed, together with our partners, an enlarged version of the PhenoTyper (90 x 90 cm, called PhenoTyper 9000) that allows social housing of rats. Additionally, this PhenoTyper is equipped with ultrasonic microphones (Metris, the Netherlands) to customize tracking software and ultrasound recording software (SonoTrack) to automate behavioral analysis including ultrasonic vocalizations of socially interacting rats. I have utilized the PhenoTyper-9000 as a test environment for behavioral analysis of pairs of rats. During the developmental phase of the large PhenoTyper, pilot studies confirmed the feasibility of the system to study rat social behavior. In the following blog, several examples of experimental behavioral analysis of socially interacting rats will be featured. WHITE PAPER PhenoTyper for home cage observation Download our free white paper and learn how to monitor rodent behavior in their home cage environment. - 24/7 monitoring capabilities - Automated behavior analysis - Social housing options Learn More References - 1. Belzung, C. (2014). Innovative drugs to treat depression: Did animal models fail to be predictive or did clinical trials fail to detect effects. Neuropsychopharmacology, 39, 1041-1051. - 2. Barrett, J.E. (2015). The pain of pain: Challenges of animal behavior models. European Journal of Pharmacology, 753, 183-190. - 3. Braff, L.; Braff, D.L. (2013). The neuropsychiatric translational revolution still very early and still very challenging. JAMA Psychiatry, 70, 777-779. - 4. Fonio, E.; Golani, I.; Benjamini, Y. (2012). Measuring behavior of animal models: faults and remedies. Nat Meth, 9, 1167-1170. - 5. Reichlin TS, Vogt L, Würbel H. The researchers' view of scientific rigor-survey on the conduct and reporting of in vivo research. PLoS ONE, 2016;11 doi: 10.1371/journal.pone.0165999. - 6. De Chaumont, F.; Coura, R.D.; Serreau, P.; Cressant, A.; Chabout, J.; Granon, S.; Olivo-Marin, J. (2012). Computerized video analysis of social interactions in mice. Nature Methods, 9, 410-417. - 7. Weissbrod, A.; Shapiro, A.; Vasserman, G.; Edry, L.; Dayan, M,; Yitzhaky, A.; Hertzberg, L.; Feinerman, O.; Kimchi, T. (2013). Automated long-term tracking and social behavioural phenotyping of animal colonies within a semi-natural environment. Nature Communications, 4. - 8. Castelhano-Carlos, M.J.; Baumans, V.; Sousa, N. (2017). PhenoWorld: Addressing animal welfare in a new paradigm to house and assess rat behaviour. Lab Anim, 51, 36-43. - 9. Spruijt, B.M.; Peters, S.M.; de Heer, R.C.; Pothuizen, H.H.J.; van der Harst, J.E. (2014). Reproducibility and relevance of future behavioral sciences should benefit from a cross fertilization of past recommendations and today's technology: "Back to the future". J Neurosci Methods, 234, 2-12. - 10. Schaefer, A.T.; Claridge-Chang, A. (2012). The surveillance state of behavioral automation. Curr Opin Neurobiol, 22, 170-176. - 11. Robie, A.A.; Seagraves, K.M.; Egnor, S.E.R.; Branson, K. (2017). Machine vision methods for analyzing social interactions. J Exp Biol, 220, 25-34. - 12. Spruijt, B.M.; DeVisser, L. (2006). Advanced behavioural screening: automated home cage ethology. Drug Discovery Today: Technologies, 3, 231-237. --- ## Many ways to measure behavior URL: https://noldus.com/blog/many-ways-measure-behavior Published: 2018-06-07 11:12:00 Description: So what kind of behavior can you measure? We haven't had time to follow all five behavior research tracks but here are a few highlights of the first conference day. So what kind of behavior can you measure? At the Measuring Behavior conference, researchers present methods and techniques to get insights into pig behavior in a stable, teacher behavior in a classroom, visitor behavior in a museum, crab behavior in an open field, citizen behavior in a smart city, consumer behavior in a store, and much much more. We haven't had time to follow all five behavior research tracks but here are a few highlights of the first conference day. Understanding animal behavior The first conference day of the eleventh Measuring Behavior conference was opened by a keynote speech of Prof Françoise Wemelsfelder from the Animal and Veterinary Sciences Group, Scotland's Rural College, Edinburgh, UK. Her main topic question was: can we get closer to how animals experience their world? This keynote was a great opening for this multi-disciplinary conference. She talked about using a method from Consumer and Food Science - the Free Choice Profiling method - and using it to describe animal expressiveness. Looking at the 'whole animal' instead of single behaviors, and having researchers using their own words to describe the emotional states brought her and her team a wealth of information. This has now led to a list of 15 to 20 terms with which animal welfare can be assessed taking the overall emotional state of the animal into account. She explained that combining methods and techniques for measuring behavior from different disciplines is a win-win situation. Isn't that what this whole conference is about? Understanding human behavior in a smart city Annelies Smets presented context-aware experience sampling as a method to study human behavior in its context and capture the influence of external factors. In a large-scale IoT living lab for smart city services in Antwerp (Belgium) this method was tested for the first time. In a real-life environment you need to capture external factors that influence the behavior. For example think about your preferred choice of vehicle. Participants in the Antwerp experiment discovered that the weather had a much larger impact on their preference compared to their self-reported determinant in choice of vehicle. Would you choose your bike over your car sooner if you would know for sure it is not going to rain along your route? This research showed that only relying on a classic interview wouldn't give you the insights you needed. It's more and more about combining multiple data streams in order to find out what really drives decision making. Understanding art lovers How can we change experiences through understanding emotions? In his presentation, Christian Caldato explained how neuroscientific techniques were used to measure the emotional experience of a museum visitor. In Gallerie d'Italia Museum, Milan, Italy, a total of forty visitors participated in the study. They visited the special exhibit "The last Caravaggio: heirs and new masters". In order to develop the best possible experience, visitors were asked to look at the paintings which their eyes were tracked and their brain activity and skin conductance were measured. The researchers explain that only by combining different measurements it is possible to assess the emotional impact of each painting. After the analysis, the researchers were able to design the best route for museum visitors. Aimed at remembering the highlights of the exhibit. Manchester Museum After two keynotes and multiple symposia, we were all looking forward to the reception. In the Manchester Museum, which honestly is a marvelous place to discover both the collection and the building itself, drinks, dinner, and discussions took up the rest of the evening. Can you imagine drinks with the dinosaurs in the Fossils Gallery? We're looking forward to another day of interesting symposia and don't forget to talk to the exhibitors showing the latest innovations. --- ## A new zebrafish model for ALS-related gene mutations URL: https://noldus.com/blog/zebrafish-als-gene Published: 2018-06-05 15:16:00 Description: How zebrafish are helping us to discover the mechanisms behind this neurodegenerative disease. Amyotrophic lateral sclerosis, better known as ALS, is a neurodegenerative disease that leads to the demise of motor neurons. As a consequence, muscle movement control is lost. ALS gene The gene most strongly associated with ALS is a gene on chromosome 9, called C9orf72. Patients with ALS have shown large expansions within this gene, while healthy individuals only show small expansions. However, the mechanism in which this DNA repetition actually leads to symptoms of the disease is still largely unknown. DNA repetitions causing symptoms of ALS There are three main theories in this specific branch of ALS research. One is that because of these DNA repetitions, the gene is mutated and consequently unconventionally translated. This leads to the formation of proteins called DPRs, which can have a toxic effect on motor function. A recent study from Swaminathan et al., focused on this theory. Toxic proteins To put it briefly, the C9orf72 gene expansion can lead to five different DPR proteins, each having a different level of toxicity, which also depends on the length of the gene-expansion. While several studies have demonstrated the toxicity of these proteins, not much is known about the effect on motor function in a vertebrate model. Zebrafish model of DPR proteins In this study, the researchers investigated just that, and expressed three different lengths of DPR proteins in zebrafish. The short length reflected the situation in healthy individuals, while the intermediate and high repetitions represented disease. The effects on survival, morphology, and motor function were observed. Coiling as a measure of locomotion in zebrafish embryos To investigate motor function, the researchers studied coiling behavior in zebrafish embryos. DanioScope was used to measure coiling by determining the percentage of burst activity time. The researchers also studied the swimming activity of larvae in 96-well plates in DanioVision and determined total distance swum with EthoVision XT. In addition, DanioScope was used to acquire the heartbeat rates of larvae during three-minute videos. FREE DEMO Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free Demo Different proteins lead to different effects The low repetitions did not really have an effect on locomotion or morphology. However, at intermediate lengths, the different types of DPR showed different effects. At high repetitions, all DPR variations led to locomotor deficits, even though not all DPRs were found to be toxic enough to have morphological effects. GR toxicity One specific DPR, abbreviated as GR, appeared to be most toxic, so the researchers developed a zebrafish line expressing this GR protein at 100 repetitions. General expression of GR lead to several developmental and behavioral defects. When these repetitions were limited to motor neurons, the effect seemed less toxic, but the affected phenotype persisted. New therapeutic approaches With this study, Swaminathan et al. shed more light on how different DPRs might contribute to the symptoms of ALS, which in the future might help to determine targets for new therapeutic approaches. This GR zebrafish line has the potential to aid in future studies on ALS mechanism and drug discovery projects. Reference Swaminathan, A.; Bouffard, M.; Liao, M.; Ryan, S.; Callister, J.B.; Pickering-Brown, S.M.; Armstrong, G.A.B.; Drapeau, P. (2018). Expression of C9orf72-related dipeptides impairs motor function in a vertebrate model. Human Molecular Genetics, 27(10), 1754-1762. --- ## The effects of parasitic infections on learning and memory in mice URL: https://noldus.com/blog/parasitic-infection-memory-mice Published: 2018-05-30 11:20:00 Description: Worm infections can cause cognitive problems. But it’s unclear if it affects learning, memory, or both. Worm infection Hookworm infection is an infection in the intestine by parasites. Aside from abdominal pain and other physical discomforts, it also causes cognitive problems. It is also still endemic in developing countries. Cognitive impairments Although impaired cognition as a result of parasitic infections has been widely reported, it is unclear specifically what kind of cognition is affected and how. Dr. Brombacher and her colleagues from the International Centre for Genetic Engineering and Biotechnology in Cape Town, South Africa, set out to investigate. Testing worm infection on mice The effect of worm infection was tested using a mouse model. In this case, mice were infected with N. brasiliensis, a roundworm with a life cycle similar to human hookworms. The researchers used a Morris water maze test and EthoVision XT video tracking software to assess mouse behavior as well as learning and memory capabilities. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Morris water maze testing The Morris water maze task was used to test learning and memory, but the authors used additional parameters to measure general activity and anxiety. The learning phase Mouse cognition was tested over a period of eight days. The first four days were used as an acquisition phase in which the mice learned to locate the platform hidden just beneath the surface of the water. A light was used as a distal navigational cue. This is because the balb/c mice subjects had poor vision, but were able to clearly distinguish light from dark. To rule out any bias due to differences in locomotor abilities caused by the infection, velocity and distance swum were compared between the mice. No differences were found, so worm infection did not seem to affect locomotion or activity. Mice infected with roundworm performed just as well as the other mice, indicating that learning itself was not affected. Reference memory phase Reference memory was tested using a probe trial without the platform on day five. Infected mice spent less time swimming over the area where the platform was previously located, so memory did seem to be affected by the infection. To make sure this effect was not caused by anxiety, scientists measured how often the mice swam near the edges, froze in response to stimuli, and were rendered immobile. No differences were found, so it seems that the roundworm infection impaired the subjects' reference memory. Complex learning phase During a reversal phase on days six and seven, the mice were trained using the platform located at the opposite quadrant. On day eight, the platform was moved again, but stayed visible during the test. These phases were used to test more complex learning, and again, there were no differences between the infected and non-infected mice. Disrupted memory consolidation While the infection did not affect learning significantly, it did disrupt memory consolidation. To further investigate this, the number of macrophages and microglia in the hippocampi of the mice were counted. These increased in number in the infected mice, which might explain the interference of optimal reference memory. References - Brombacher, T. M.; De Gouveia, K. S.; Cruywagen, L.; Makena, N.; Booley, F.; Tamgue, O.; Brombacher, F. (2018). Nippostrongylus brasiliensis infection leads to impaired reference memory and myeloid cell interference. Scientific Reports, 8, 2958. - Read about Morris water maze testing with EthoVision XT. --- ## The use of humor during doctor-patient interactions URL: https://noldus.com/blog/use-humor-during-doctor-patient-interactions Published: 2018-05-02 11:56:00 Description: How often do medical professionals use humor during the interaction with patients? After all, such positive interactions help build a relationship, establish trust, and support the exchange of relevant information. Science has proven that laughter is healthy. Laughter is pain relieving, relaxing, and helps people deal with their fears. These are all important factors that patients often have to deal with. How nice would it be if while during a visit to the doctor or during a hospital stay, you could forget your pain, relax, and be less anxious, if only just for a moment? However, how often is humor actually used during doctor-patient interactions? Aiming for positive health outcomes A review about doctor-patient communication shows that positive interactions help build a relationship, establish trust, and support the exchange of accurate and relevant information [1]. All of these benefits can contribute to achieve positive health outcomes. Humor reduces anxiety, puts things in perspective, affects connectedness, and brings some warmth into an interaction that can otherwise be formal, cold, and distant. In short, humor is gold in the hands of health care providers. Besides, you don't have to put a red clown nose on to bring some humor into the equation! To characterize the logistics of humor in medical encounters, e.g. frequency, who introduces it, or what it is about, researcher Phillips and her team analyzed audio/video-recorded clinical encounters to describe the frequency and other features of humor in outpatient primary and specialty care visits [2]. Coding the presence and frequency of humor The researchers included 51 videos that were recorded in specialty care, and 61 videos that were recorded in primary care. They aimed to quantify and evaluate the use of humor. Beforehand, they defined what constitutes an instance of humor, calibrated the coding, and identified variables to collect, such as expressions of laughter and jokes. Humor was defined as a statement made with the intent to make others in the room laugh or react positively and to which a positive response was elicited. The researchers accomplished the coding through the use of the software The Observer XT. The use of humor was coded as a binary variable (humor present or absent during the whole visit) and a quantitative variable (how many times humor was noted in the visit). For each instance of humor within the encounter, reviewers recorded: - who introduced humor (patient, provider or guest) - timing (introduction, history taking, physical examination, or counseling) - subject - apparent function of the humor - whether the instance was a single statement ("dead end") or resulted in a string of humorous back-and-forth comments Next, a comparison was made between the amount of encounters with humor by setting, decision aid use, and participant gender. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial The benefits of humor during the counseling part of a medical encounter Humor was present in 59% of the medical encounters, which were an average of 30 minutes. On average, there were two humorous moments per encounter. The researchers did not find any differences regarding gender of the participant, setting (primary- or specialty care), and encounters with and without shared decision-making tools. However, they did find that more humor was used when the doctor and patient were of the same gender. Doctors and patients used humor most often during the counseling part of the visit. This is when they discuss subjects such as the diagnosis, treatment, and other potentially difficult topics. Humor allows doctors and patients to handle these otherwise uncomfortable topics more easily. What about patient satisfaction? The most common subject of humor were the patients' medical condition, treatment, and tests. It was often limited to one-line exchanges. Humor was mostly used to relate to general life events and circumstances. For example, patients and doctors commonly discussed pets or spouses in humorous ways. This allowed for connection on a simple level, which could serve as an introduction for more serious and intimate conversations. An improved personal connection may explain the increased patient satisfaction noted in visits with more humor. Although this study encountered several limitations, such as the lack of confirming judgements regarding the humorous intent of each statement made with the patients, it does support the idea that humor is a tool that can be used to discuss difficult topics and bring warmth into a medical encounter. References - 1.Ha, J.F.; Longnecker, N. (2010). Doctor-patient communication: A review. The Ochsner Journal, 10, 38–43. - 2.Phillips, K.A.; Ospina, N.S.; Rodriguez-Gutierrez, R.; Castaneda-Guarderas, A.; Gionfriddo, M.R.; Branda, M. & Montori, V. (2018). Humor During Clinical Practice: Analysis of Recorded Clinical Encounters. Journal of the American Board of Family Medicine, 31 (2), 270-278. --- ## Freeze! A recent study on PTSD and the immune system URL: https://noldus.com/blog/ptsd-and-immune-system Published: 2018-04-12 15:26:00 Description: It is pretty well-known that stress and anxiety have an effect on the immune system. This can be a real problem, especially in psychiatric disorders. It is pretty well-known that stress and anxiety have an effect on the immune system. This can be a real problem, especially in psychiatric disorders involving depression and anxiety, such as Post-traumatic stress disorder (PTSD). Researchers are now identifying critical neurological factors in the physical and mental consequences of this disease. PTSD PTSD is a mental disorder often associated with survivors of combat, but can also occur after natural disasters, serious accidents, or abuse. According to PTSD United, it affects about 7.7 million American adults in a given year. Aside from the obvious mental strain on these patients, these people also have among the highest rates of healthcare service use. Research on PTSD There is an obvious need for effective treatment. In a recent study, Meghan Jones and her colleagues (Brain, Behavior, and Immunity, 2018) investigated the role of a protein called interleukin-1β (IL-1β) in PTSD. IL-1β is a cytokine, a small cell-signaling protein in the brain that has a regulatory role in the immune system. It has found to be elevated in cases of PTSD, and Jones et al. wanted to unravel the immune dysregulation and specifically the role of IL-β in PTSD. Rat model for PTSD For this, they used a rat model of stress-enhanced fear learning. This means that the animal is exposed to stress prior to a typical fear learning test. In the fear learning (or fear conditioning) test, the animal is exposed to a foot shock in a certain context, such a cage with patterned walls. It quickly learns to associate the context with this negative experience; in subsequent exposure to this context, the animal becomes fearful even without the shock. Free white paper on fear conditioning Stress-enhanced fear mimics PTSD A typical rodent will show fear in the form of freezing behavior in a fear conditioning test. Stressing the animal beforehand, as is done in the stress-enhanced fear learning method, is known to reproduce many core symptoms of PTSD, such as enhanced fear learning, anxiety, a heightened startle response, and impaired fear extinction (Blouin et al., 2016). Methodology In this research by Jones and colleagues, animals were exposed to "beforehand stress" in context A on day 1. After spending a couple of days in the home cage, rats underwent mild stress on day 8 in a new environment, context B. In the following days, their response to just exposure to context B, without a stressor, was measured. Measuring fear Freezing is a behavior generally accepted as a reliable measure of fear. During freezing, the animal is completely still, except for small movement caused by breathing. Freezing can be automatically detected using the Activity parameter in the video tracking software EthoVision XT. The software analyzes changes on the pixel level from one video frame to the next to detect activity vs inactivity. In this study, the activity threshold was set at 10, but this can be modified by the researcher, as it might need tweaking for smaller or larger animals. Stress and hypersensitivity During the experiments, it became apparent that rats that were stressed in context A showed significantly more freezing in context B compared to a control group of non-stressed rats that did not receive foot shocks in context A. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial The effect of IL-1β Not only did the stressed animals show more freezing, they also had higher levels of IL-1β in their brains. So to further investigate the role of IL-1β, half of the rats from both the stressed and control group received a IL-1β antagonist, in between the exposure to contexts A and B. This blockage of IL-1β attenuated the enhanced fear learning effect, and brought it down to the levels of the control groups. Possible therapeutic target This study shows the important role of IL-1β in the development of PTSD-like symptoms in rats, as stress caused higher levels of IL-1β and rendered the animals hypersensitive for subsequent fear learning. In line with previous studies, this shows that IL-1β signaling can be an interesting therapeutic target in the treatment of PTSD. References - Blouin, A.M.; Sillivan, S.E.; Joseph, N.F.; Miller, C.A. (2016). The potential of epigenetics in stress-enhanced fear learning models of PTSD. Learning & Memory, 23, 576-586. - Jones, M.E.; Lebonville, C.L.; Paniccia, J.E.; Balentine, M.E.; Reissner, K.J.; Lysle, D.T. (2018). Hippocampal interleukin-1 mediates stress-enhanced fear learning: A potential role for astrocyte-derived interleukin-1β. Brain, Behavior, and Immunity, 67, 355-363. Photo credit header: keaneyefoto --- ## How to study consumer behavior in a kitchen URL: https://noldus.com/blog/how-study-consumer-behavior Published: 2018-04-10 11:04:00 Description: Masson and colleagues from Université Paris-Saclay, France, designed a test kitchen to investigate food storage processes. According to them, the use of video cameras was of great value for analyzing behaviors. Testing consumer behavior in a natural environment can give great insight into behavioral patterns. How do consumers use a product? For example, what do they use to cook dinner? Masson and colleagues from Université Paris-Saclay, France, designed a test kitchen including four dome cameras and one portable GoPro camera to investigate food storage processes. According to them, the use of video cameras was of great value for analyzing behaviors. Marine Masson and colleagues revealed that consumers do not consider the nature of the food in the organization of the refrigerator, and this blog post delves into how this was studied. Worldwide, various organizations are working on the question of why food might go to waste. Recommendations for fresh food storage Food storage practices can be studied by direct observation. First, the researchers evaluated if the recommendations of the French Agriculture and Food Department were known and followed. The recommendations issued by the French Agriculture and Food Department about fresh food storage were thus taken as main behavioral points that should be analyzed: - #1The set point of temperature of the refrigerator is 4˚C - #2One must wash hands before storing food - #3The food packaging must be removed before storing food - #4The refrigerated food must be stored first - #5The refrigerator must not stay open for a long time - #6The food must be stored according to its nature and the gradient of temperature in the refrigerator Kitchen lab The researchers then equipped the test kitchen with a refrigerator with two shelves at 0-4˚C, two shelves at 4-6 ˚C, and one drawer for fruits and vegetables. In total, the door had three shelves. To ensure that they could follow the process of consumer food storage, they invited participants to the lab and asked them to 'buy' items from a shopping list. The items from the list were then delivered to them for storage. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Consumers / shopper identity All participants were from families with at least one child. In addition, participants had to be responsible for the grocery shopping and food storage in their household. In total, 20 volunteers took part in this study. The researchers concluded that the participants behaved quite spontaneously, although they were in principle aware of the cameras in the lab because they had given written permission to allow filming. Video coding The results of the study reveal a wide diversity of behaviors when storing food in the refrigerator. All video material was coded in The Observer XT to get these insights. The researchers defined zones in the kitchen, including a zone for the refrigerator itself. They were thus able to analyze which food went where, and how long it took to place the food items into the refrigerator. They also coded if the bag and/or packaging was removed from the items, and they noted in the software whether someone washed their hands or not. This delivered great insight into behavioral patterns related to the recommendations. #2 - Nobody washed their hands before storing food (as is recommendation number 2 of the French Agriculture and Food Department). #4 - There were also people storing the refrigerated food items immediately after receiving them. However, others placed everything on the kitchen counter to first look over all the delivered items (see recommendation #4). #6 - The main safety issues concern meats, ready-to-eat salads, and ready-made dough because they are sensitive to contamination with pathogens, which is a bacterium, virus, or other microorganism that can cause disease. These items should be stored at the appropriate place in the refrigerator. In general, it was found that the recommendations of the French Agriculture and Food Department were clearly not observed or even known. Reflecting on the method of choice The use of a coding software is quite intuitive and allows for faster coding, but it still required a lot of work according to Masson and the team. However, it did provide them with the insights that they were after. This paper described the approach of filming consumers in a controlled yet naturalistic environment. Interested in human behavior research? Read more on 'How to study human behavior', or 'Understanding consumer buying behavior'! Reference Masson, M.; Delarue, J.; Blumenthal, D. (2017). An observational study of refrigerator food storage by consumers in controlled conditions. Food Quality & Preference, 56 (B), 294-300. --- ## Top 5 blog posts about autism URL: https://noldus.com/blog/top-5-blog-posts-about-autism Published: 2018-04-02 11:56:00 Description: World Autism Awareness Day is an internationally recognized day on April 2nd. A good reason to sum up the top 5 best read blog posts about autism of the last year for you. Each year, April transforms into World Autism Awareness Month. Events and educational activities take place throughout the month to increase understanding and acceptance of autism and foster worldwide support. Awareness - Action - Acceptance - Appreciation Autism has a big impact on someone's life. Everything that people with autism see, hear, smell, and feel is processed in a different way, and that offers a diverse mix of strengths and weaknesses. For example, people with autism often have a good eye for detail, and they are honest, straightforward, analytical, and hard-working. However, they can have difficulty processing everyday sensory information and maintaining social contacts. FREE WHITE PAPER Autism research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Get your copy instantly Research in the field of autism A lot of research has been done and is still occurring in the field of autism. Topics such as restrictive and repetitive behaviors, processing faces, sensitivity to social cues, play behavior, social communication skills, and much more have been addressed by researchers. The top 5 blog posts about autism in the past year contain these mentioned topics: - 1.The impact of sounds on autistic children's behavior. Children with autism can have trouble dealing with external distractions. Researcher Shireen Kanakri conducted a study to observe the impact of the acoustic environment on restrictive and repetitive behaviors. - 2.Improving social communication skills in children with ASD. Many children with an Autism Spectrum Disorder (ASD) suffer from deficits in social communication and interaction, especially with peers. They participate in fewer social interactions than typically developing children. Researchers Qualls and Corbett observed social exchanges between children with and without ASD in a naturalistic playground setting, and shared their findings. - 3.Parent-child interaction in autism: play behavior. According to the study conducted by Freeman and Kasari, the importance of play and engagement in young children with autism is rooted in parental strategies. Therefore, it is important to provide parents with the necessary tools to properly stimulate engagement. - 4.Are there objective tests for predicting autism severity? Some disorders cannot simply be diagnosed with a blood test or tissue-culture. Autism Spectrum Disorder (ASD) is a good example; its diagnosis relies upon behavioral tests and questionnaires. - 5.Understanding face perception in ASD. Researchers at KU Leuven wanted to gain more insight into whether or not there are differences in the implicit abilities of children with ASD to detect faces, different identities, and different expressions. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Increasing awareness about autism Individuals with autism and the people they live and interact with, such as their parents, siblings, and classmates, benefit from this Autism Awareness Month being a time for education, acceptance, and further research into the causes of and best therapies for individuals with an autism spectrum disorder (ASD). Do you know someone with autism, or are you perhaps familiar with autism yourself? Take some time and ask for his or her experiences or share yours with someone. If you are still looking for other topics related to autism, you can surely find it on our behavioral research blog! Want to stay ahead in behavioral research? Stay up-to-date and subscribe to the Noldus Newsline! You will receive expert insights and the latest innovations straight to your inbox every month. --- ## Measuring consumer responses to chocolate and images URL: https://noldus.com/blog/measuring-consumer-responses Published: 2018-03-26 15:42:00 Description: Researchers all over the world are trying to find ways to measure real consumer responses and behavior. Researchers all over the world are trying to find ways to measure real consumer responses and behavior. This blog features a study in which researchers tried different implicit measurement techniques in order to get closer to measuring liking and preference using images and chocolates! I'd want to be a test participant – wouldn't you? Implicit vs explicit measures As rational responses do not represent the totality of consumers' attitudes and preferences toward specific stimuli, researchers are looking into ways of measuring unconscious consumer responses. Implicit measurement techniques don't rely on opinion research. Traditionally, researchers relied heavily on techniques such as customer surveys in order to predict product preferences. Physiological, facial expression, and sensory/emotional responses In this study, Melbourne based researchers Damir Torrico, Sigfredo Fuentes, and colleagues investigated the effect of collecting physiological, facial expression, and sensory/emotional responses in order to study the response to different images and chocolate stimuli. The researchers asked two groups of participants to look at different stimuli (neutral, positive, negative) and taste four types of chocolate (milk, moderate bitter, dark, and popping candy). They were each asked to sit down in an individual booth, which ensured controlled conditions similar to that of a laboratory. How to measure implicit responses Test participants were presented with the images and were then asked to taste the chocolate. The tablet running a biosensory app developed by Sigfredo Fuentes et al. captured videos and infrared images to record physiological reactions from participants. Heart rate was estimated (BPM) using Matlab algorithms. Skin temperature was captured using the FLIR ONE infrared thermal camera, and facial expressions were measured using the facial recognition software FaceReader. In this particular experiment, Torrico and colleagues divided participants into two groups: one with a Western cultural background, and one with an Asian background. They explain that by comparing responses of two culturally different groups, they wanted to gain insight into potential differences related to cultural background. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Results and implications for further research The researchers found that BPM wasn't different among stimuli. Skin temperature was. It changed depending on the type of chocolate sample presented. For Asian background participants, skin temperature was positively correlated to 'happy' as calculated with FaceReader software, for participants with a Western background, skin temperature positively correlated to 'sad'. Cultural differences were found as well for the self-reported face-scale responses of images, in specific the researchers found lower scores from participants with an Asian background. These findings are useful to better understand consumers acceptability based on both physiological and emotional responses. FaceReader analysis showed different results. What the researchers did find were differences in base levels on emotionality, but what does that mean and why where to differences not that outspoken? Emotions are made to communicate As stated before, individual booths were used. Looking back at the experiment, Torrico and colleagues explain that by using these individual booths they didn't take the social element of expressing emotions into consideration. In their words: "Macro facial expressions are more pronounced in social interaction environments than in isolation conditions. This situation may potentially be the reason for the lack of detectable facial movements in the present experiment by FaceReader". Emotions are made to communicate. Asking a consumer to test food in an individual booth doesn't necessarily elicit facial expressions since this person doesn't have to communicate his or her feelings to another person. Natural environment or more social testing locations? You can keep in mind that testing in natural environments is tricky due to the number of factors influencing the decision or preference process, but a test in a supermarket or restaurant will show more communication or emotions in general, since the social context is there. This study adds to our knowledge and understanding of how we can better understand the acceptability of an item based on unconscious and emotional responses. Interested in human behavior research? Read more on 'How to study human behavior', or 'Understanding consumer buying behavior'! --- ## Package testing - Emotional journey in packaging research URL: https://noldus.com/blog/package-testing Published: 2018-03-06 11:11:00 Description: A product package should help consumers make a quick decision. Donata Tania Vergura and Beatrice Luceri from the University of Parma, Italy investigated different packaging designs. You likely know the feeling of leaving the office, racing to the supermarket and then buying just a little bit more than necessary. As we are all consumers, we make decisions on what to buy, which can be influenced by many factors such as packaging and store layout. During a controlled laboratory situation, it was found that package design with a product image that is more on the foreground compared to the background elicited more positive emotional responses. The same researchers would now like to run this experiment in a store, which would enrich the results of the study. Lab study into package testing Donata Tania Vergura and Beatrice Luceri from the University of Parma, Italy investigated different packaging designs, in particular the placement of the product image (foreground vs. background) and the effect on the emotional state of the consumer and the intention to buy. Since shopping is increasingly perceived as a hastened activity, the researchers explain that a product packaging should help consumers make a quick decision. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources The product tests The researchers designed two tests. In the first test, two well-known brand name food products in the area of Parma, Italy were chosen: - Biscuits for breakfast by Balocco - Foccacia snack by Mulino Bianco Vergura and Luceri follow a theory in social psychology known as the Construal Level Theory (CLT), and explain why they choose a product picture in the foreground (claiming to be more concrete) vs. a product picture in the background (claiming to be more abstract). The packaging was changed according to this theory. For example, the focaccia packaging showed flour as one of the ingredients, and moved its snack product image to the background. A total of forty students participated in the first study. They were welcomed to the laboratory room and were asked to watch a video with various pictures (e.g. landscapes, foods, or animals). While the students watched the video, their facial expressions were recorded on video for analysis with FaceReader software. The second test was designed around two fictional brands for lemon cake and crackers. The same procedure was followed, and a total of sixty students participated. Purchase intent was measured with a questionnaire showing the package design. Positive emotional response In both tests FaceReader analysis clearly showed more positive emotional responses with the foreground product picture. This outcome is in line with the Construal Level Theory. Because the picture is positioned in the foreground, consumers feel nearer to the product by perceiving a smaller psychological distance from the product packaging. This systematically changes peoples' responses to the product (positive valence). FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Chasing after the buy button Purchase intent didn't differ significantly. However, the questionnaires did give insight into the attractiveness of the package design when comparing the two versions. Products in foreground positions received a significantly better evaluation compared to packages featuring the products in background positions. In addition, there always is the option of going into a store and testing the product design in a real-life environment! Noldus Consulting is a research partner that can help you set up these studies in a natural environment in order to collect valuable insights in an unobtrusive way using technology such as eye tracking, physiological measures, and behavioral mapping. Reference Vergura, D.T.; Luceri, B. (2018). Product packaging and consumers' emotional response. Does spatial representation influence product evaluation and choice? Journal of Consumer Marketing, https://doi.org/10.1108/JCM-12-2016-2021 --- ## Facial expression analysis in video content marketing URL: https://noldus.com/blog/facial-expression-video-content-marketing Published: 2018-02-22 15:41:00 Description: This study shows that emotions in company messages or advertisements could be used to build and measure brand value. This measure can thus be added to social media metrics guidelines to assess success rate. What if you could predict the popularity of campaign videos? Corporate communications can incorporate neuromarketing and nonverbal communication analysis as social media metrics in order to understand not only what content is effective, but also how it should be presented. Campaign videos are often distributed via a video platform such as YouTube. The more views they get, the more successful the campaign becomes. Automatic facial coding What video will be successful? The study presented here concludes that it is not only the content that matters, it is also the body language — in this case the facial expressions — that influence the success rate of a video campaign. In this study, Amsterdam based researchers used two measures to assess behavior: automatic facial coding and video views on YouTube. Measure success This proof-of-concept study shows that the emotional face behavior of actors in company messages or advertisements could be used to build and measure brand value. This measure can thus be added to social media metrics guidelines to assess success rate. Predict video popularity Researcher Peter Lewinski from the University of Amsterdam looked at micro expressions of the face in great detail. In total, he analyzed 25,000 video frames of 16 speakers in order to predict video popularity over time. He presented his research in the Journal of Neuroscience, Psychology, and Economics. FaceReader software FaceReader software is used in this type of research, and is used worldwide at universities and companies to assess emotions automatically. It is research software that has a large installed base in different market segments. By analyzing facial expressions using video images, you can get insight into 10,000 combinations of facial movements (Ekman & Rosenberg, 1997). The Active Appearance Model in FaceReader creates a three dimensional superimposed model of a face with over 500 hyper connected tracking points. FaceReader then uses a neural network trained on more than 10,000 facial images depicting basic emotions. It uses this network to recognize a particular expression. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Campaign video analysis For this project, Lewinski selected sixteen ING Private Banking and ABN AMRO campaign videos, where the speaker was forward-facing, under good lighting conditions, and speaking to the YouTube channel watcher. All 16 campaign videos were analyzed using FaceReader software to get insight into the emotional level of communication of the ABN AMRO and ING speakers in the video. FaceReader analysis showed that the lack of facial emotions and the presence of facial non-emotions were important indicators of a video's popularity. The data shows that the fewer emotions that make you feel like you want to approach the person expressing the emotion (happy / sad), the more popular the video. No emotions please Concluding, the research outcomes show that in case of professional institutes such as these banks, a simple and non-emotional nonverbal message is what viewers and potential customers find most compelling. Happiness and sadness might just be too out of context in this case. It is explained that social media users who watched the videos may have assumed the speakers to be employees of the bank, perhaps causing this serious tone of voice to be much appreciated. Context matters Lewinski mentions: "Several factors, for which we didn't control, could have influenced the number of video views." It is a challenge to predict success of a video, but Lewinski concludes that context certainly matters, like the bank employee (or actor) presenting in a simple and non-emotional nonverbal matter. Reference Lewinski, P. (2015). Don't look blank, happy, or sad: Patterns of facial expressions of speakers in banks' YouTube videos predict video's popularity over time. Journal of Neuroscience, Psychology, and Economics, 8(4), 241-249. https://psycnet.apa.org/record/2015-47847-001 --- ## Operating room layout: impact on work patters and flow disruptions URL: https://noldus.com/blog/operating-room-layout Published: 2018-02-20 13:41:00 Description: With use of prerecorded videos of surgeries, researchers examined the impact of the layout of an OR on work patterns and flow disruptions of a circulating nurse. The first time I entered an operating room was during an internship in a Dutch hospital. As part of my nursing education, they allowed me to attend some general surgeries. After I had exchanged my white nurse suit for a green surgical version, I was ready for it. I was fascinated from the first minute onwards. All that equipment, all those people working together, a real patient on the table who had no clue what was going on due to the anesthesia… so much happened in a relatively short time. Impressive! An operating room (OR) is an exciting workplace, where all team members must cooperate toward shared goals, such as making safe and efficient patient care a priority. Each member of the surgical team has specific personal responsibilities in order to achieve that goal. Maintaining a big-picture oversight of the patient's condition is one of the circulating nurse's responsibilities. A circulating nurse is the ultimate patient advocate The research of Sara Bayramzadeh and her team focuses on the impact of healthcare facility design on user experience, safety, and efficiency. She investigated whether the layout of an operating room can influence the movement patterns and disruptions of a circulating nurse (CN). Circulating nurses are vital to the surgical team. The CN is the most mobile team member, and works outside the sterile field. The CN makes sure the patient is comfortable and safe, and is responsible for charting what is happening in the operating room, keeping a sterile environment, and tracking the supplies and equipment used. The CN serves as an advocate for patients since they are unable to speak for themselves due to being under anesthesia. The CN observes, monitors, and manages potential threats at and around the surgical field. Efficiently moving around within the OR Because CN's are constantly moving between various zones within the OR, the zone location of equipment, storage units, phones/intercoms, computer workstations, and doors are important to the efficiency and effectiveness of the CN's workflow. But aren't these zones too far apart? The layout of the OR may contribute to unnecessary movement or create barriers to movement inside the OR, resulting in workflow disruptions. Do you need to capture a sequence of scenarios in multiple rooms or areas, for example in the anesthetic room, the OR, and the recovery room? With Viso it is possible to combine the recordings into one chronological session. Behavioral mapping The researchers used prerecorded videos of 25 pediatric and general adult surgeries, conducted in three different OR's, which varied in size. With four cameras of Media Recorder in each OR, they captured the scenes from different angles, offering a complete overview. The Observer XT facilitated viewing all four videos simultaneously and coding the observations, including codes for the location of each surgical team member by location (zone), their activities at any time, and any surgical flow disruptions they might have experienced. The activities of the CN, associating to the term PEMSI, were either P: patient related, such as transferring or preparing the patient E: equipment related, such as preparing, monitoring, moving, or cleaning equipment MS: materials, instruments, or supplies related, such as preparing, or cleaning material, trash disposal, retrieving supplies I: information related, such as phone calls, computer work, and paperwork. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Observing and coding the activities of the circulation nurse Within PEMSI activities, information related activities were most frequent and the highest in total duration. The CN visited the CN's workstation the most, which was extended to the surgical table. Across all surgeries, 91% of the CN's activities required traveling through multiple zones. The movement patterns appeared to be similar in all three OR's. Since the CN makes frequent trips to different parts of the OR to support the activities of other team members, it was important to understand how the adjacencies between zones might support optimal travel patterns for the CN. It appeared that direct proximity between the CN's workstation and the supply zone where key supplies are located was strongly recommended. Furthermore, indirect adjacency between the CN's workstation and the areas surrounding the surgical table where the CN may need to deliver or exchange items with the scrub nurse (who is in the sterile zone and responsible for handling instruments and assist the surgeon during the operation) is recommended. This allows for a timely response and at the same time allows the CN to maintain distance from the sterile zone to avoid contaminating the area. What about the surgical flow disruptions (SFDs)? The researchers looked at two kinds of disruptions: - 1.Layout related SFDs - incidents due to the lack of space to move around or the position of certain items in the OR that hinder the surgical staff's performance. - 2.Environmental hazard SFDs - incidents such as the slipping or falling of staff members, cases with sharp objects and contaminated needles, excessive reach for assessing the patient, objects, or equipment. In total, the CN was involved in 26% of all SFDs observed during all surgeries. Layout related SFDs were consistently more frequent than environmental hazard SFDs. Since frequent disruptions during surgery can pose threats to both patient and staff safety, locating the frequently traveled zones closer together may reduce the involvement of the CN in disruptions. Understanding the nature of the CN's movement patterns is important for the design and layout of an OR. The goal is patient safety and high quality care Appropriate adjacencies between zones can help minimizing unnecessary travels, and as a result, may help decrease the duration of each activity, distance traveled, and the risk of being involved in a flow disruption. A safe and efficient patient care is likely to be guaranteed. Interested in human behavior research? Read more on 'How to study human behavior'! Reference Bayranzadeh, S.; Joseph, A.; San, D.; Khoshkenar, A.; Taaffe, K.; Jafarifiroozabadi, R.; Neyens, D.M. (2018). The Impact of Operating Room Layout on Circulating Nurse's Work Patterns and Flow Disruptions: A Behavioral Mapping Study. Health Environments Research & Design Journal, 1-15. DOI: 10.1177/1937586717751124 --- ## A new rat model for neonatal white matter injury URL: https://noldus.com/blog/new-rat-model-neonatal-white-matter-injury Published: 2018-02-13 15:27:00 Description: Preterm birth is a major problem in neonatal healthcare. Erik van Tilborg developed a new animal model to closely mimic this clinical situation, an important step in finding new treatment options. A guest blog post by Erik van Tilborg, PhD student in the research group of Cora Nijboer at the laboratory for Neuroimmunology and Developmental Origins of Disease (NIDOD), UMC Utrecht, The Netherlands. White matter injury in preterm infants Preterm birth is a major problem in neonatal healthcare. In the Netherlands 8% of all births occur prematurely, which means after a pregnancy of 37 weeks or less. Some babies are even born after a pregnancy of 24-27 weeks. These children are referred to as extremely preterm infants, and are often exposed to preterm birth-related health problems such as inflammation (due to an immature immune system and vulnerability to infections) and fluctuating oxygen levels (due to immature lungs, respiratory problems and underdeveloped vasculature in the brain). In many preterm infants such complications, associated premature birth, cause diffuse injury to the white matter of the brain. Later in life, this type of white matter injury (WMI) leads to impaired cognitive performance, social dysfunctioning and decreased motor skills. Moreover, neonatal WMI is associated with an increased risk of psychiatric disorders, such as autism spectrum disorders, ADHD, schizophrenia and depression (reviewed in [1]). Currently, no treatment options are available in neonatal clinics to prevent or cure WMI in preterm infants. Therefore, it is crucial that more research is performed to find out the cellular and molecular mechanisms that contribute to WMI in preterm infants, but also to find new treatment options. A new rat model for neonatal WMI In order to unravel the mechanisms underlying WMI and to develop new therapies, it is crucial to perform translational animal experiments. Mimicking neonatal WMI in rodents allows us to study this type of brain injury under controlled conditions and enables us to investigate new treatment options. In order to develop a new rat model of neonatal WMI, we used to two insults that preterm infants are often exposed to and that are important risk factors to develop WMI: fetal inflammation and postnatal hypoxia. Careful analysis of the brains of rats exposed to these insults revealed that they show a pattern of brain injury that closely resembles the clinical situation of neonatal WMI [2,3]. To study the effects of the combination of these two insults on functional outcome, we used various behavioral paradigms. Behavioral outcome in rats with neonatal WMI To study motor performance, we used a rotarod task in which animals are placed on a beam that rotates at an increasing speed. In this task, it is measured how long it takes before the animal is not able to keep up anymore and falls down. This is considered to be a measure of motor performance. We observed that rats with WMI (induced by fetal inflammation and postnatal hypoxia) demonstrated a reduction in motor skills compared to control rats. To study anxiety-like behavior, we studied the behavior of rats after being placed in an open field. During this task, the movement of the animals was tracked using Ethovision XT. It was measured how often the animals entered the middle 'unsafe' zone of the open field. Rats with WMI did this less often, which is considered a sign of anxiety as the animals spent more time in the 'safe' zone guarded by the walls of the field. To determine the effects of combined fetal inflammation and postnatal hypoxia on social functioning, rats were placed in transparent cages in pairs and their social play behavior was scored using Observer XT. We observed that WMI animals showed a decrease in the initiation of social play interactions. Furthermore, using Observer XT the grooming behavior or the animals was studied. WMI rats showed an increase in the time spent on grooming – a sign of repetitiveness. Together, the observations of impaired social interactions and repetitive behavior are indicative of autism-like behavior. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial From these behavioral experiments it can be concluded that WMI in rats is associated with impaired motor skills, anxiety-like behavior and autism-like behavior. This accurately reflects the clinical situation of WMI in preterm infants, who show similar behavioral problems later in life. Future research As the new animal model closely mimics the clinical situation of neonatal WMI, it may be used to study the cellular and molecular mechanisms that contribute to WMI in preterm infants and to develop novel therapies. Currently, we are using this animal model to test various treatment options by investigating whether they can reduce brain injury and improve functional outcome. Hopefully, this will lead to novel treatments that can improve outcome of vulnerable preterm infants for the rest of their lives. More detailed information regarding this study is available open access [3]. References - van Tilborg E, Heijnen CJ, Benders MJ, van Bel F, Fleiss B, Gressens P, Nijboer CH (2016). Impaired oligodendrocyte maturation in preterm infants: Potential therapeutic targets. Progress in Neurobiology, 136, 28-49. - van Tilborg E, van Kammen CM, de Theije CGM, van Meer MPA, Dijkhuizen RM, Nijboer CH (2017). A quantitative method for microstructural analysis of myelinated axons in the injured rodent brain. Scientific Reports, 7(1), 16492. - van Tilborg E, Achterberg EJM, van Kammen CM, van der Toorn A, Groenendaal F, Dijkhuizen RM, Heijnen CJ, Vanderschuren LJMJ, Benders MNJL, Nijboer CHA. Combined fetal inflammation and postnatal hypoxia causes myelin deficits and autism-like behavior in a rat model of diffuse white matter injury. Glia, 66(1), 78-93. --- ## Exercise vs anabolic steroids: a rat study URL: https://noldus.com/blog/anabolic-steroids-rat-study Published: 2018-02-01 11:06:00 Description: A recent study shows that the use of anabolic steroids diminishes the positive effects of exercise in rats. Anabolic steroids. The first thing that pops into your head when reading this term is probably a bodybuilder or powerlifter (or a lot of muscle, in any case). Anabolic androgenic steroids or AASs, are basically synthetic testosterone. While it might mostly be known for its use / abuse by athletes and bodybuilders, it is also prescribed by health care providers to treat muscle loss in diseases or hormonal issues. AASs abuse and behavior Abuse of AASs has become a public health concern because it increases the prevalence of behavioral disorders such as unprovoked aggression. Abuse in the long term can cause high levels of anxiety and mood-swings. Interestingly, while exercise has general beneficial effects on physical performance, abuse of AASs has the opposite effect, which begs the question: what is the actual effect of the combination of these two? Exercise and anxiety Certain exercise protocols are proven to have anxiolytic and antidepressant effects, though animal studies show certain high-intensity protocols can also induce anxiogenic effects. The main reason athletes use AASs is to improve their performance in sports. However, the generally positive effects of sports might be abolished by the use of these steroids. Selakovic and colleagues from the University of Kragujevac and the University of Belgrade (Serbia) investigated this with rat models. Chronic ND administration This study focusses on the use of nandrolone decanoate (ND), one of the most common AASs. The effect of chronic ND on behavior was compared to the effect of exercise, as well as the combination of both treatments. The exercise applied in this case was chronic swim training. Open field testing To study anxiety behavior, well-validated open field and elevated plus maze testing was used. Both tests used EthoVision XT video tracking technology. The open field showed that ND treatment was anxiogenic, while chronic exercise seems to work anxiolytically. However, this was only the case when compared to the ND treatment, not when compared to the control group. In fact, the combined treatment of ND and exercise abolished the beneficial effects of exercise and even brought them down below the level of the control group. Elevated plus maze testing Results of the elevated plus maze test were similar; chronic exercise works anxiolytically, while ND had the opposite effect. Again, the combined treatment results showed that ND administration abolished the positive effects of exercise. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Video tracking parameters Open field and elevated plus maze testing was conducted using EthoVision XT video tracking. Parameters for the open field were total distance moved, velocity, percentage of time moving, cumulative duration in the center zone, and frequency in the center zone. The elevated plus maze parameters included cumulative duration in open arms, frequency in open arms, total distance moved, velocity, and percentage of time moving. In addition, rearing and head-dipping behavior were counted. Immunohistochemistry of exercise and ND abuse In addition to behavioral testing, researchers also measured the number of PV immunoreactive neurons in the hippocampus. The hippocampus is important in mood regulation, and alterations in PV content have been implicated in exercise-induced behavioral changes. In line with the behavioral results, exercise increased the number of PV immunoreactive neurons, while ND administration decreased it. The combination of both treatments still resulted in a decrease, again showing the dominant effect of AASs use on hippocampal plasticity. Opposite and abolishing effects This study, like many others, shows the beneficial effects of exercise, or at least this specific protocol of chronic swimming in rats. This effect is opposite to the effects of AASs (ND) administration, and even abolished by it when combined. Reference Selakovic, D.; Joksimovic, J.; Zaletel, I.; Puskas, N.; Matovic, M.; Rosic, G. (2017). The opposite effects of nandrolone decanoate and exercise on anxiety levels in rats may involve alterations in hippocampal parvalbumin-positive interneurons. PLoS ONE, 12(12), e0189595. --- ## Knockout of Down syndrome gene in zebrafish leads to autistic-like behaviors URL: https://noldus.com/blog/zebrafish-down-syndrome-gene-autism Published: 2018-01-09 15:40:00 Description: Knockout of Down syndrome gene in zebrafish leads to autistic-like behaviors: Though earlier knockout models in mice failed, researchers have developed a successful zebrafish model. Autism Spectrum Disorder (ASD) is not a clear-cut disease, but rather a genetically heterogeneous group of neurodevelopmental disorders. This makes it hard to point to one specific cause, for example, one gene linked to autism. However, recent studies suggest that abnormal functioning of the DYRK1A gene might play a causal role in autism. Down syndrome gene The DYRK1A gene is mostly known within the context of Down syndrome. It is located on chromosome 21, at the critical region for Down syndrome. Overexpression of this gene is linked to intellectual disability and microcephaly. Researchers now suspect that underexpression of this gene is linked to autism. However, while overexpression and consequent clinical symptoms is replicable in murine models, underexpression is hard to investigate in mice due to the high mortality rate in knockout models. New zebrafish model After finding an individual with an intragenic microdeletion of DYRK1A and microcephaly and autism, Kim et al. (2017) wanted to know more about the influence of this gene on autism. They recently published a paper in Molecular Autism proposing a new zebrafish to investigate the role of this gene. Contrary to mice, knocking out the analogue for this gene (dyrk1aa) did not cause lethality in zebrafish. It did lead to reduced brain size and impaired social behavior, indicating that underexpression of DYRK1A can indeed cause autism-like symptoms. Behavioral investigation This study involved a rather comprehensive list of behavioral tests. For starters, early larval zebrafish were exposed to a dark flash test as well as sleep and waking measurements. Furthermore, adult zebrafish were exposed to a novel tank assay, social interaction assay, and shoaling bowl assay. DanioVision testing Larvae were placed in 24-well plates in a DanioVision Observation Chamber and exposed to dark flash pulses to induce a startle response. This response was assessed by measuring the distance moved per 10 second time bins with EthoVision XT video tracking. Sleep and waking behavior was measured by analyzing locomotor activity (velocity in 30 second time bins) during night and day phases over the course of two days. Both tests revealed no differences between wild type zebrafish (WT) and the dyrk1aa knockouts (KO). Tracking of adult fish To analyze anxiolytic behavior, adult fish were individually placed in a novel tank. The location of the fish in the tank (bottom, middle or top part) was recorded during a span of 10 minutes. Interestingly, knockout fish showed less bottom dwelling, indicating less anxiety in these fish. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Social interaction To investigate social behavior, which is a hallmark to autism, two social tests were performed. In a social interaction test, fish were placed in a two-chambered tank. Social stimuli fish were placed in a smaller part of the tank, and the test subject fish were placed in the larger part. The location of the fish (near, second near, or in the third or fourth zone away from the stimuli fish) was measured during a span of 15 minutes. Where WT fish spent most of their time right next to the stimuli fish as expected, the KO fish spent their time swimming all over the tank, not showing specific interest in the other fish. Shoaling Shoaling was measured as inter-fish distances in groups of three to seven fish in a round, flat-bottomed bowl. Again, KO fish did not show specific social interest, indicated by their lack of social cohesion, whereas the WT fish were shoaling as expected. The authors supplemented these experiments with one in a rectangular tank, confirming earlier findings. References Kim, O.-H.; Cho, H.-J.; Han, E.; Hong, T.I.; Ariyasiri, K.; Choi, J.H.; Hwang, K.-S.; Jeong, Y.-M.; Yang, S.-Y.; Yu, K.; Park, D.-S.; Oh, H.-W.; Davis, E.E.; Schwartz, C.E.; Lee, J.-S.; Kim, H.-G.; Kim, C.-H. (2017). Zebrafish knockout of Down syndrome gene, DYRK1A, shows social impairments relevant to autism. Molecular Autism, 8, 50. --- ## Putative neurorestorative drug for Parkinson’s disease tested in zebrafish URL: https://noldus.com/blog/pd-drugs-zebrafish Published: 2017-12-20 15:54:00 Description: About zebrafish and their important role in finding a cure for Parkinson’s disease. An estimated 7 to 10 million people have Parkinson's disease (PD). Needless to say, this disease has a major impact on society, especially since it has no cure. The most common prescription for PD is levodopa, which is effective in helping with motor functioning. But, thus far, the need for a neuroprotective or neuro-restorative drug is still unmet. Dopamine PD develops when the dopamine producing cells in the substantia nigra stop working properly. The loss of dopamine mostly causes locomotor issues, from walking to talking. The most common drug available right now is still levopoda. Developed 5 decades ago, this purely symptomatic treatment increases the levels of dopamine in the brain, but does not halt or slow down the actual decay of dopamine-producing neurons. The need for a cure Obviously, there is a need for a cure, or something to interfere with the progression of the disease. There are a couple of drugs already being used clinically that show promise to this effect. Putative neurorestorative drugs Isradipine, for example, is a drug that is used to treat high blood pressure. Several studies showed that people taking these drugs had a lower risk of getting PD, suggesting it might be neuroprotective and thus prevent the development of this disease. Minocycline is an antibiotic that shows neuroprotective properties, making it another interesting candidate in the quest for a cure for PD. In addition, Rasagiline is a drug that is already used to treat symptoms of PD, usually in later stages of the disease. It is often used in combination with levodopa to help prolong its effects. However, it has also been used on its own in early stages of the disease and it seems to show neuroprotective effects. Zebrafish model for PD To investigate the actual effects of these drugs, Cronin and Grealy developed a zebrafish model for PD that's suitable for high-throughput studies, as described in their recent paper in Neuroscience. The model they used is on based on the administration of 6-OHDA (oxidopamine), a toxic substance that destroys dopaminergic and noradrenergic neurons in the brain and is commonly use to product parkinsonism in animal models. DanioVision and EthoVision XT testing In order to test whether isradipine, minocycline, and rasagiline could protect or restore locomotor functioning after treatment with 6-OHDA, the zebrafish larvae were tested using DanioVision. Individual larvae were placed in a 96-well plate, and their activity was measured during a 50-minute period at 5 days post fertilization, with 10-minute alternating light-dark cycles. The researchers used EthoVision XT to calculate mean distance moved per minute and total distance moved. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial The promise of rasagiline Researchers found that rasagiline restored locomotor function in 6-OHDA-treated zebrafish. It also restored dopaminergic neurons. Minocycline also restored locomotor function, but did not have the restorative effect in the brain. Isradipine showed no significant improvement in either area. High throughput testing Findings for minocycline and rasagiline in this study are in line with other rodent studies. Another important conclusion from this research is that this zebrafish model for PD can be used to test drugs for their neuroprotective and neurorestorative functions in a high-throughput manner, in this case using DanioVision and EthoVision XT video tracking. References Cronin, A.; Grealy, M. (2017). Neuroprotective and Neuro-restorative Effects of Minocycline and Rasagiline in a Zebrafish 6-Hydroxydopamine Model of Parkinson's Disease. Neuroscience, 367, 34-46. --- ## How to study communication in young children URL: https://noldus.com/blog/how-study-communication-young-children Published: 2017-12-18 10:51:00 Description: If you are born profoundly deaf, it is very likely that modern technology in the form of cochlear implants can improve your hearing. If you are born profoundly deaf, it is very likely that modern technology in the form of cochlear implants can improve your hearing. The cochlea is the organ in your ear that translates sound vibrations in the air into nervous impulses in the auditory nerve, and a cochlear implant carries out that function electronically. Helping children with hearing impairments However, for medical reasons, the procedure for a cochlear implant cannot occur when the child is less than 12 months old. That means that the period when they miss out on hearing sound is the critical period when children are normally learning to speak. It is therefore really important that the communication between the child and his or her parents is of the best possible quality after the device has been implanted. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly Studying behavior At the moment, psychologists measure how this interaction goes so that they can give feedback using systematically structured observations. This is incredibly labor intensive, even when computer-aided video observations are used. If this measurement could be automated, then there would be a lot of potential to save costs and provide better information. Improving children's auditory rehabilitation The iCare (Improving Children's Auditory Rehabilitation) project is a network of young researchers working in the field of communication concerning children with hearing impairment. In this context, Cristina Palmero Cantariño at Noldus has developed an innovative technique to automatically measure a key aspect of non-verbal communication behavior — mutual eye contact. She has developed a novel system that combines geometric and appearance-based methods which works independently from the cameras used, the appearance of the subjects, and their orientation. The gaze estimation is calculated using a deep learning method more accurate than any method yet published. Palmero and colleagues hope that once this prototype is turned into a product, it will be useful not only for psychologists in this specific field but also for other people studying non-verbal communication in many different contexts. Acknowledgments The work described here has been carried out in cooperation with Astrid van Wieringen and Guido Lichtert (KU Leuven & KOCA) and funded by the FP7 Marie-Curie ITN program of the European Union, project number 607139. --- ## Buying a travel pillow: do our experiences make our expectations come true? URL: https://noldus.com/blog/buying-travel-pillow Published: 2017-12-13 12:53:00 Description: During a long flight, it is often tempting to take a nap in the airplane seat. Which travel pillow offers you the most comfort for this? There are many types of traveling -- business travel with defined schedules and justifications for the trip, vacation travel to spend sitting on a beach looking at boats (or in a boat looking at beaches), and adventure travel based on exploration and new experiences. In order to arrive at the destination of our choice, we increasingly travel through the air. During a long journey, it is often very tempting to go to sleep. However, in an airplane seat, sleeping is almost never comfortable. The chance of a stiff neck after some nodding in your airplane seat is very likely. As a passenger, you need to find a solution to cope with the minimal living space available during a trip. When I googled 'comfort during traveling,' all kinds of shops offered me all kinds of products: special compression stockings, a sleeping bag, sleeping masks, earplugs, and a travel pillow. All products came in all shapes, sizes, and colors, and claimed to improve comfort. Are expectations about comfort equal to experienced comfort? Comfort is a convenient experience that guarantees a person is satisfied with the product used, whereas discomfort refers to physical inconveniences. Joyce Bouwens and her team selected five travel pillows to answer the following questions: - Which travel pillow provides the head and neck with ideal support? - Does ideal support correspond with expected comfort when selecting a travel pillow? Each of these pillows had different characteristics in terms of head and neck support as well as restriction of movement in some directions: - Total Pillow: a doughnut-shaped pillow filled with microbeads that can be twisted to a preferable shape for optimal support of the head from the side or the back - J-pillow: shaped in the letter J and filled with original pillow stuffing that supports the head on the side and under the chin - Inflatable Travelrest: a tall and inflatable pillow; the pillow is positioned from the shoulder to the waist and provides support on the side of the head - Carex Memory Foam: a traditional horseshoe shaped travel pillow filled with memory foam that is placed around the neck and supports the back and the sides of the head - Embrace Sleep Collar: a hard plastic U shape, covered with foam that is tightly placed around the neck in order to support the head under the chin and on the side by restricting movement in these positions Comfort expectations A questionnaire was sent out to 50 participants with previous flight experience in order to quantify the expectations of passengers. They were asked to rank pictures of people with the travel pillows used in this study based on expected comfort. The majority of the participants expected that the J-pillow and the Total pillow would offer the most comfort. Comfort experience In this study, the comfort experience and user behavior were measured using 10 participants. The participants were invited to the Human Factors and Ergonomics Laboratory of Zodiac Seats, and were asked to evaluate six conditions (five conditions with the five different travel pillows and one condition without a pillow) while sitting in airplane seat and trying to rest or sleep. Video recording the movements of the heads With the help of Noldus' Media Recorder software, four synchronized network cameras were installed around each participant. One was installed in the front, one from above, one at the left, and one at the right side. After each condition, the participants were asked to rate their perceived discomfort on a visual analog discomfort scale. The video recordings were then evaluated using The Observer XT by coding the position of the head relative to three different axes: pitch-down direction (y-axis), neutral roll position (x-axis), and yaw position (z-axis). The total time spent in each position was calculated, and the number of times the participants moved to a given position was recorded. Observations bring clarity The observations showed that the inflatable Travelrest caused the highest number of head movements, and the Embrace Sleep Collar resulted in the lowest number. Regarding the three different axes, the Embrace Sleep Collar exhibited the least movements as well as the most neutral position. This was confirmed by the ratings of the participants, which also indicated that the Embrace Sleep Collar caused the least discomfort. The fewer times the head moved to another position, the higher the participant rated the comfort of the pillow. This research supports the statement that a participant's discomfort experience is objectively measurable by observing the movement behavior of the participant. Formatting the equation The comfort ranking that the 10 participants made after experiencing all six conditions differed from the expected comfort by the 50 participants, suggesting that passengers are unable to predict the comfort associated with a travel pillow based on pictures. Nevertheless, this is increasingly occurring alongside the growing popularity of online shopping. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Interested in human behavior research? Read more on 'How to study human behavior'! Reference Bouwens, J.M.A.; Schultheis, U.W.; Hiemstra-van Mastrigt, S. & Vink, P. (2017). Expected versus experienced neck comfort. Hum Factors Man, (00), 1–9. https://doi.org/10.1002/hfm.20721 --- ## Strain differences in zebrafish behavior and physiology URL: https://noldus.com/blog/zebrafish-strain-differences Published: 2017-12-07 10:53:00 Description: A zebrafish is not just a zebrafish. Strain differences in zebrafish behavior and physiology. A zebrafish is not just a zebrafish – ZFIN (The Zebrafish Information Network) lists about 30 strains often used in the lab. This is one of the reasons why there might be difficulties with the repeatability and comparison of experiments within and between labs. Ruud van den Bos and his colleagues investigate these strain differences at the department of Animal Ecology and Physiology of the Radboud University in Nijmegen (The Netherlands). Mutations and morphology Two of the strains they investigate include the AB and the Tupfel long-fin (TL) zebrafish. The latter fish have a recessive mutation that causes spots instead of the typical stripes, and, as the name suggests, long fins. Genetics causes differences in behavior In earlier studies, Van den Bos and his colleagues found that differences between these strains were not just morphological, but also behavioral and physiological. They differ in baseline activity of the HPI-axis (hypothalamus-pituitary-interrenal axis, or the "stress-axis") and neuroplasticity. In turn, their behavior is also affected. Behavioral differences at larval stages For their recent work, the researchers were interested in whether these differences would also be apparent in the larval stages. They indeed found that AB zebrafish larvae show a higher baseline activity of the stress-axis. To investigate the functional implications, they used DanioVision to study light-dark and startle behavior. DanioVision testing Two tests were performed with the DanioVision system: the first was a dark-light-dark test, and the second was an acoustic/vibrational startle test. Dark-light-dark tests After 20 minutes of acclimation, zebrafish underwent a 10 minutes dark – 10 minutes bright light (3000 lux) – 10 minutes dark regime. During that time, the following parameters measured by EthoVision XT were of main importance: - General distance moved within 30 minutes (in 5-minute bins) - Maximum velocity during the dark to light transition - Change in distance moved during the light to dark transition Startle response Using a built-in tapping device, the zebrafish's response to acoustic/vibrational startle (at intensity setting 6) was investigated. After 10 minutes of acclimation, a series of stimuli were administered. - 10 stimuli at 20 second intervals - 10 minute pause - 30 stimuli at 1 second intervals The startle response is shown as a short burst of activity, so researchers used maximum velocity as parameter to measure it. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Stronger activity and habituation These tests showed that AB fish show a stronger increase in activity in response to light-dark changes. They also have a stronger habituation to the acoustic/vibrational stimulus. High impact of strain differences on repeatability Results of this study are mostly in line with literature on the subject, and underline the importance of taking into account the differences mutations cause and how they influence the outcome of studies. This shows that strains should be carefully selected to the goal of the study, and also conveys how important it is to take differences into consideration for the comparability between studies and labs, as well as the repeatability of studies. References Bos, R. van den; Mes, W.; Galligani, P.; Heil, A.; Zethof, J.; Flik, G.; Gorissen, M. (2017). Further characterisation of differences between TL and AB zebrafish (Danio rerio): Gene expression, physiology and behaviour at day 5 of the larval stage. PLoS ONE, 12 (4), e0175420. --- ## How innovative solutions advance your behavioral research URL: https://noldus.com/blog/advance-your-behavioral-research Published: 2017-11-30 13:02:00 Description: Good behavioral research requires good methods, and good tools. Three Noldus customer stories display how innovative solutions have advanced their behavioral research. We have all seen it in sci-fi movies: a scientist is frantically working to find a last-minute solution to save the world or a loved one. While stressing out a test tube is accidentally knocked over and lo and behold, at the brink of world destruction, the ultimate solution is found and the day/lover/world is saved. Science fiction or not, there are plenty of accidental discoveries that turned out to have a dramatic impact, like the discovery of Penicillin by Scottish scientist Alexander Fleming in 1928. These accidental discoveries may have shaped history, but usually much more is needed before research leads to actual discoveries and solutions for everyday life. Good behavioral research requires good methods, and good tools Good behavioral research requires good methods, and good tools. The scientific world is always on the move, new tools are developed at an increasingly rapid rate. At Noldus we work closely together with the scientific community, in order to develop and deliver the best software and instruments for behavioral research. Three Noldus customer stories display how innovative solutions have advanced their behavioral research. How to study sensory science and eating behavior Prof. Kees de Graaf talks about how to study sensory science and eating behavior. And how software such as The Observer XT helps his team achieve their goals in science. Watch the video on YouTube How to measure emotions in the Uses and Acceptability Lab Jean-Marc Diverrez, from bcom Institute of Research and Technology, France talks about measuring emotions. He hopes that the projects will go out of the lab and into the real world. He looks into all kinds of new technologies and sensors to better measure and thus understand emotions. Read the full story here or watch the video: Watch the video on YouTube FREE TRIAL Try The Observer XT yourself! Request a free trial and find out what The Observer XT can do for your research! - Collect and analyze behavioral data - Integrate with physiological data - Reliable and easy to use Free Trial Why good tools are important for reliability and reproducibility in zebrafish experiments Dr. Ruud van den Bos talks about his work in neurobiology and experimental psychology, and how zebrafish studies contribute to his field of research. He is experienced with DanioVision and EthoVision XT, and explains why good tools are important for reliability and reproducibility in zebrafish experiments. Watch the video on YouTube --- ## Tracking chickens: A promising approach for identifying feather-peckers URL: https://noldus.com/blog/tracking-chickens Published: 2017-11-21 09:15:00 Description: Manually observing chickens in barns is a tedious job to which ultra-wideband tracking offers a solution. But does it interfere with normal behavior? Manually observing individual chickens in today's large chicken housing systems has become a tedious job. From laying hens to broiler chickens, one of the major problems with chickens grouped together is feather-pecking behavior, where a chicken will peck at the feathers of another chicken and causes them harm. Tracking systems have gained popularity over the years to automatically locate subjects and to analyze location-based data for livestock behavioral research. Following this trend, automated tracking systems such as ultra-wideband (uwb) have become very important in quickly identifying individual chickens in large groups for behavioral analysis. However, do the uwb tags interfere with normal behavior? For example, do they increase feather-pecking behavior or lead to tagged chickens being victims of feather-pecking behavior? Influence of wearing uwb tags on chicken behavior and health For quality results, researchers studying behavior need the collected data to be accurate and true. It is also good to know if monitoring chickens with uwb tags negatively affects their health and welfare. With uwb tracking, the researcher receives the exact location of a chicken, which is good for determining proximity and analyzing their behavior. However, tags are active which means they need a battery, presenting a potential problem of the weight of the tag. Flanders Research Institute for Agriculture, Fisheries and Food (ILVO) in Belgium, carried out a research with the goals of assessing the effect of uwb tags on broilers (Stadig et al, 2017). Would they be less active? Would the tag decrease their health and growth or would the tag lead to more pecking behavior? Method and data collection The tags were attached to randomly selected chickens using backpacks with adjustable straps around the wings to accommodate for growth. The chickens were observed using continuous video recordings. Results on chicken behavior and health The results of the research show no substantial difference in activity including feather-pecking, health, or growth because of the tag. Any differences observed were diminished over the course of the research, indicating that the tagged chickens adapted to the tags or that their increasing body weight reduced the effect of the tag. More research is needed here to determine the exact cause. Automated tracking and detecting behaviors Seeing as uwb tags do not interfere in chicken behavior and health, a next question would be if the tracking system helps to measure feather-pecking behavior. To find out, Wageningen University (The Netherlands) aimed to developed methods for automatic recording of location. With PhenoLab, activity and proximity information on laying hens was gathered. (Rodenburg et al, 2017). Method and data collection The activity levels of chickens known to show pecking behavior were compared to chickens that didn't. Two tracking systems were used: video tracking with EthoVision XT and uwb tracking with TrackLab. Because the PhenoLab offers a controlled environment for studies on multiple animals, it was the ideal test-site to validate the accuracy of TrackLab compared to EthoVision XT, a validated and commonly used video tracking system for tracking in controlled environments. Video tracking, however, is a solution that does not work well for individual tracking of multiple animals in real barn environments. FREE DEMO Try TrackLab yourself! Request a demo to obtain real-time insights into the activity, welfare, and health of your livestock. - Accurate tracking data - Gain insights into many parameters - Easily access, export, and analyze data Free Demo Results on detecting behaviors In line with previous studies, high feather-peckers show a higher activity level in this research. The study in the PhenoLab also showed that with an accuracy of 96% compared to EthoVision XT, TrackLab is a reliable tool for research on spatial behavior in real-world environment studies. Conclusion It can be said that automated tracking systems such as those using uwb tags are becoming increasingly popular because of their accuracy and the insights into behavioral patterns they provide. The tags do not seem to interfere with a chicken's behavior or health. Therefore, this technology is suitable for providing early warning signs for damaging behaviors such as feather-pecking. References - Stadig, L. M., Rodenburg, T. B., Ampe, B., Reubens, B., & Tuyttens, F. A. (2017). An automated positioning system for monitoring chickens' location: effects of wearing a backpack on behaviour, leg health and production. Applied Animal Behaviour Science, doi:10.1016/j.applanim.2017.09.016 - Rodenburg T.B., van der Eijk J.A.J., Pichová K., van Mil B., de Haas E.N. (2017). PhenoLab: automatic recording of location, activity and proximity in group-housed laying hens. Precision Livestock Farming '17, pg 269-274. --- ## How oncologists’ communication impacts patients’ information recall URL: https://noldus.com/blog/patients-information-recall-emotional-stress Published: 2017-11-16 11:00:00 Description: In her study, Visser focuses on one of the possible mechanisms that may underlie limited information recall in patients: the relationship between emotional stress and memory performance. Blog post by Leonie (N.C.) Visser, researcher at the Department of Medical Psychology of the Academic Medical Center, University of Amsterdam, The Netherlands. Background of the study Patients' recall of information provided by their physician For patients, receiving medical information from their physician is important. Unfortunately, patients' recall or ability to remember medical information provided to them by their physicians is generally poor. For example, approximately half of provided information is not remembered by cancer patients. Uncovering the mechanisms that lead to limited recall of medical information may provide insights that help to improve recall and inform physicians about communication behaviors that can optimize information transfer to patients. Reducing emotional stress as a potential mechanism The PhD thesis of Leonie Visser focuses on one of the possible mechanisms that may underlie limited information recall in patients: the relationship between emotional stress and memory performance. Emotional stress is defined as the increase in self-reported negative feelings and/or physiological arousal caused by an emotional stimulus. Highly stressful situations are thought to induce poor memory formation. Consequently, if physicians could reduce patients' emotional stress during consultations, they might improve patients' information recall. Such an effect might be accomplished by means of affect-oriented communication, or communication behaviors expressing care for and affective engagement with the patient. The video-vignettes approach The video-vignette design is especially suitable to systematically investigate the effects physician-communication on patient outcomes. A video vignette is a video recording of a situation in which actors mimic a scripted doctor-patient consultation [1]. In a video-vignette design, participants are called analogue patients. They can be either disease-naïve participants (individuals without a disease history) or former patients, and are instructed to watch the video vignette while imagining themselves in the video patients' situation. The analogue patients are usually randomly allocated to watch one (or more) of multiple versions of a video vignette. The medical content, the environment, and the interaction between characters are exactly identical across the video-vignette versions, except for specific communication elements of interest. These elements, in this case the physician's response to the patient's emotions, are manipulated to vary between video-vignette conditions. This allows for systematic testing of the effects of these specific communication behaviors on analogue patient outcomes. Figure 1. A model of hypothesized relationships Notes. Without accounting for emotional stress, affect-oriented communication was expected to positively impact information recall, which is called the total effect. When accounting for emotional stress as a potential mediator of this relation, the total effect can be broken down into two effects. The first type of effect is the indirect effect, or in other words the mediation effect, whereby communication exerts its influence through analogue patients' emotional stress. Specifically, affect-oriented communication was assumed to reduce emotional stress (path a), and these lower levels of emotional stress were assumed to result in higher levels of information recall (path b). The second type of effect is the direct effect. It can be calculated by predicting information recall based on communication while controlling for emotional stress, thus taking into account a possible mediation effect. Since emotional stress was expected to be a partial mediator of the impact of affect-oriented communication on information recall, we hypothesized that an indirect effect could be demonstrated, and -as a consequence- the direct effect was expected to be smaller than the total effect. Aims How oncologists' communication impacts patients' information recall and emotional stress Testing this model presented in Figure 1 was the main objective of this thesis. As displayed in the model, we aimed to investigate the mediating role of emotional stress in the relationship between physicians' communication and analogue patients' information recall. Affect-oriented communication was assumed to reduce emotional stress levels, which in turn was expected to improve information recall (free recall and/or recognition of information provided by the physician in the consultation). Using equipment from Biopac Systems, we planned to assess emotional stress by means of both self-reported and psychophysiological arousal measures to increase our ability to detect any relations and to examine replicability across measures. As this thesis was part of a research line addressing understanding and improving physician-patient information transfer within the field of oncology and emotions are an inherent part of most oncological consultation, we focused on the impact of communication by oncologists. Conclusions The research presented in this thesis provided evidence for the causal and positive influence of two specific forms of affect-oriented communication --trust-conveying and emotion-oriented communication -- on patients' recall of medical information. These results underscore that oncologists' affect-oriented communication can positively impact patients' information recall. Furthermore, our research suggested emotion-oriented speech as the best way to respond to patients' emotions in comparison to emotion-oriented silence. Still, the findings presented in this thesis also indicate that it is important for oncologists to attune their communication to each individual patient, as differences in preferences and impact exist. Implications Showing evidence that affect-oriented communication strategies can improve not only patients' emotional wellbeing, but also patients' ability to recall highly relevant information may encourage oncologists (and physicians in general) to adopt such strategies. Additionally, providing educators with these obtained insights will help them to teach trainees the skills to deal with patients' emotions and to scientifically validate the importance of these skills for patients' information recall. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Contact details Leonie (N.C.) Visser, Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands (n.c.visser@amc.uva.nl). Title of PhD thesis: "HOW ONCOLOGISTS' COMMUNICATION IMPACTS PATIENTS' INFORMATION RECALL AND EMOTIONAL STRESS. A VIDEO-VIGNETTES APPROACH." – Public defense at the University of Amsterdam, 8th December 2017. --- ## Understanding face perception in ASD URL: https://noldus.com/blog/understanding-face-perception-asd Published: 2017-11-06 08:26:00 Description: Researchers at KU Leuven want to gain more insight into whether or not there are differences in the implicit abilities of children with ASD to detect faces, different identities, and different expressions. This blog post is a guest post by Stephanie Van der Donck from the Center for Developmental Psychiatry of KU Leuven in Belgium. The study Stephanie writes about, investigates different processing abilities in children with and without autism spectrum disorder (ASD). She explains why they choose to apply an innovative scalp electroencephalography (EEG) approach combined with fast periodic visual stimulation (FPVS). Processing faces The human face is a highly familiar, complex, and multidimensional visual pattern that provides a wealth of information about someone (e.g. his or her identity, gender, age, emotional state, etc.). Recognizing people and accurately interpreting non-verbal cues like facial expressions are required to successfully interact with others. Individuals with autism spectrum disorder (ASD) are characterized by deficits in social communication and interaction (American Psychiatric Association, 2013). Many individuals with ASD show impairments in processing faces (e.g. Webb, Neuhaus, & Faja, 2016; Weigelt, Koldewyn, & Kanwisher, 2012). They show impaired sensitivity to social communication cues conveyed as, among others, difficulties with non-verbal communicative behaviors and deficits in expressing and recognizing facial affect (Constantino & Charman, 2015). Face processing abilities in people with ASD have already been widely studied, both implicitly (e.g. brain imaging studies) and explicitly. However, results are mixed and inconsistent. A partial explanation for this variability could be the use of explicit behavioral tasks. This is because performances of these tasks can be influenced by several factors beyond face processing, such as attention and motivation. Implicit measures do generate information that is more consistent across studies. However, they usually yield weak effects and low signal-to-noise ratio, which requires long recordings, complex measures, and/or time-consuming analysis. This large variability and inconsistency in results impedes defining and understanding the nature of face processing impairment, especially at the individual level. Fast periodic visual stimulation To address the limitations of the methodologies used in previous studies, we apply an innovative scalp electroencephalography (EEG) approach combined with fast periodic visual stimulation (FPVS). With FPVS, a flickering stimulus is generated by rapidly presenting images (e.g. at 6 Hz). The general principle of FPVS is that it elicits a brain response (i.e. a steady-state visual evoked potential) at exactly the same frequency as the frequency of visual stimulation (for review, see Norcia et al., 2015). We use FPVS in an oddball paradigm where we periodically enter oddball images every 5th image (i.e. 6 Hz/5 = 1.2 Hz). The quick transition from the base images to the oddball images measures a discrimination response by forcing the participants to detect rapid changes in, for example, identity and/or expression. We also added an orthogonal task: the participants have to press a button as quickly as possible when they detect a change of color in the fixation cross that is presented on the screen. This orthogonal task ensures that all neural responses will be evoked implicitly. FPVS EEG has several advantages compared to approaches used in previous studies. By adding the orthogonal task, FPVS EEG yields implicit measures. Furthermore, these measures are objective, since the responses can be identified at a predefined frequency (the oddball frequency and its harmonics). Consequently, getting a response at that predefined frequency and its harmonics allows direct quantification of the response of interest. Data can be collected within a few minutes (e.g. 4 sequences of 40 seconds) and can be analyzed without any complex post hoc comparisons of responses evoked by standard and deviant stimuli as in standard ERP studies. Implicit vs explicit sensitivity to social cues In this stage of our study, we will investigate different processing abilities in children with and without ASD. By using FPVS, we want to gain more insight into whether or not there are differences in the implicit abilities of children with ASD to detect faces, different identities, and different expressions in comparison to typically developing matched controls. Besides these implicit measures, we also added several explicit identity and expression recognition tasks. The explicit tasks are implemented in combination with FaceReader software and eye tracking. This way, we want to assess if the strategies used to scan faces and the level of facial mimicry could be linked to potential differences between children with and without autism in detecting and/or recognizing faces and expressions. Through the combination of implicit and explicit measures, we hope to get a better idea of the extent to which children with and without autism are able to detect and process identities and expressions. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download References - American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.) Arlington, VA: American Psychiatric Association - Constantino, J.N., & Charman, T. (2015). Diagnosis of autism spectrum disorder: reconciling the syndrome, its diverse origins, and variation in expression. The Lancet Neurology, 15(3), p.279-291. - Norcia, A.M., Appelbaum, L.G., Ales, J.M., Cottereau, B.R., & Rossion, B. (2015). The steady-state visual evoked potential in vision research: A review. Journal of Vision, 15(4). - Webb, S.J., Neuhaus, E., & Faja, S. (2016). Face perception and learning in autism spectrum disorders. The Quarterly Journal of Experimental Psychology. - Weigelt, S., Koldewyn, K., & Kanwisher, N. (2012). Face identity recognition in autism spectrum disorders: a review of behavioral studies. Neuroscience and Biobehavioral Reviews, 36, p. 1060-1084. Contact details Stephanie Van der Donck, Center for Developmental Psychiatry, Katholieke Universiteit Leuven, Belgium Prof. Dr. Bart Boets, Center for Developmental Psychiatry, Katholieke Universiteit Leuven, Belgium www.laures.be --- ## 3 Emotional studies with FaceReader URL: https://noldus.com/blog/emotional-studies-with-facereader Published: 2017-10-31 09:06:00 Description: Many researchers have discovered FaceReader as a tool for their research. These 3 recent studies with FaceReader show how emotion data helps you to better understand human-human, human-machine, and human-product interactions. For researchers emotions are fundamental in understanding human behavior, as they are a crucial part in non-verbal communication. Emotion data provides crucial insights that allow researchers to gain insight in complex human behaviors in greater depth. Facial expression analysis software like FaceReader is ideal for collecting this data. The software automatically analyzes the six basic facial expressions defined by Paul Ekman, plus neutral, contempt, and boredom, interest, and confusion. Many researchers have discovered FaceReader as a tool for their research. These three recent studies with FaceReader show how this emotion data helps you to better understand human-human, human-machine, and human-product interactions. The emotions of people who think they're nice What does 'nice' actually mean in relation to psychological variables? And does it positively correlate with self-reported levels of health, happiness, and wellbeing? Researchers of i2 media research from the Goldsmiths University of London, UK, developed a tailored questionnaire to explore this, and asked 100 participants to rate themselves. Turns out, most of them thinks they are part of the nicest half of the population. Could everyone really be that nice? Read the full blog post here: The emotions of people who think they're nice Do emotions affect preferences to opera music? What does music trigger? What emotions arise as people listen to music or watch a music video? Does it provoke happiness, sadness, disgust or appreciation perhaps? It depends whether people like or dislike the music, and their personal preferences. Many researchers are interested in the relationship between facial expressions and music preference. Hong Chen (University of South Florida) explored the preference of Chinese undergraduate music majors for Chinese Xi-Qu and Western opera, using audiovisual examples. FaceReader was used to find the relationship between preference ratings and emotions. Read the full blog post here: Do emotions affect preferences to opera music? Emotions distracts people with eating disorders Eating disorders (ED) are usually accompanied by difficulties in social-emotional communication. Most likely these difficulties contribute to the development and maintenance of disordered eating. People with anorexia nervosa need to be in control, feeling emotions distracts them from this. Studies show that people with anorexia nervosa have reduced facial expressivity of emotions while viewing emotionally provoking stimuli. Researcher Leppanen and her team wanted to know if people with eating disorders show less facial affect, and used FaceReader to investigate this. Read the full blog post here: Emotions distracts people with eating disorders Want to learn more about FaceReader? Download the free white paper about the FaceReader methodology or request more information. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download --- ## Interacting with autonomous cars URL: https://noldus.com/blog/interacting-with-autonomous-cars Published: 2017-10-27 14:23:00 Description: When I get in the train next week at the Düsseldorf airport, I know that there is something different about it in comparison to a normal train. When I get in the train next week at the Düsseldorf airport, I know that there is something different about it in comparison to a normal train. It drives itself; there is no human driver. The first time I rode in that train, it seemed a bit odd. Now that I've ridden that train a few times, I'm used to it and it is normal. Will it feel normal once our cars start driving themselves as well? We can already buy cars that park themselves and automatically slow down when they get too close to the car in front of them. Once cars start to do much more on their own, how much trust will we have in them? Humans vs computers On the one hand, we know that people are pretty poor at tasks involving monitoring. We get bored, sleepy, and distracted by our smartphones. On the other hand, computers and robots are good at monitoring things; they don't know what boredom means. Everybody expects that this will lead to a great increase in road safety. Probably in a few decades, we will look back with horror at the road accident statistics from today, hardly able to believe that we let people control those dangerous high-speed machines. But when it does go wrong, humans have one advantage over computers: they are much better at improvising. Self-driving WEpod in Wageningen Driver safety The human driver will probably still need to be able to intervene on occasion, but when something goes wrong and the computer doesn't know what to do in the face of the impending accident, will we be able to intervene fast enough? Will the skills we need to do this be the same as the skills that our current driving tests examine us for? That is where the Prautocol project comes in. The HAN university of applied sciences has put together a consortium of specialists to investigate how certification will need to change with the advent of autonomous cars — both the certification of the car and of the driver. For instance, Noldus will be developing its tools for measuring the behavior of the driver for aspects like attention/boredom, mental workload, and stress. As the technology in the car develops in the coming years, it will be critical not to forget about how people will need to interact with autonomous vehicles to ensure that the new vehicles will not only be safe on paper, but also safe out in the real and more complicated world. Interested in learning more? Stay tuned! --- ## Robots helping people with dementia URL: https://noldus.com/blog/robots-helping-people-dementia Published: 2017-10-23 09:39:00 Description: Researcher Wendy Moyle and her team explored if the use of a robotic seal as a therapeutic tool would influence the emotional and behavioral symptoms of dementia. Every time I walk in the front door, my dog greets me as if we have been apart for months. On bad or good days, rain or shine, he is always excited to welcome me home. And, let's face it, even on a lousy day it's impossible not to smile at the sight of an ear-to-ear doggy smile and a wildly wagging tail. Pets are good for us; they provide companionship and unconditional love. They can even offer health benefits such as lowering blood pressure and heart rate, reducing the stress hormone cortisol, and boosting levels of the feel-good hormone serotonin. How can robotic pets help out? Pets often forge a special connection with people with Alzheimer's disease and dementia. It is not uncommon to watch someone change over from emotionless to joyful when a pet enters the room, especially if it triggers pleasant memories. However, a pet does not always fit in a health care setting. Allergic reactions, pet illness, or fears of a pet are problems that can occur. However, this does not apply to a robotic pet. Behavioral and psychological problems affect most individuals with dementia at some point during the progression of the disorder. For example, individuals with dementia possibly suffer from depression or anxiety. These behaviors are often difficult for care staff to manage and may ultimately result in increased medication use and decreased quality of life. Researchers have sought to investigate how robotic pets can be used to control such behaviors. Cuddling a pet reduces stress and depression The therapeutic seal robot PARO was launched in Japan in 1993 and elicits emotional responses in the older people, thus giving a calming effect. The cuddle robot has the same effect that a pet can offer, namely, reducing stress and depression. The big advantage of robotic animals as opposed to real pets is that they do not have to be taken care of. The "owner" does not have to feed or walk the pet. The seal robot is equipped with tactile sensors that react to touch, sound, and movement. It shows autonomous behavior: it can move its tail and flippers, open and close its eyes, and make sounds similar to a real baby harp seal. Its soft pelt is also very appealing. The largest study ever done on robotic pets Researcher Wendy Moyle, who has had several family members suffer from dementia, is driven to improve the quality of life for people with dementia. She and her team set up a cluster randomized controlled trial to explore if the use of a robotic seal as a therapeutic tool would influence the emotional and behavioral symptoms of dementia. They compared sessions with PARO to sessions with a look-a-like plush toy and usual care. More than 400 people with documented diagnoses of dementia living in 28 long-term care facilities in Australia participated. Participants allocated to the PARO intervention group received an individual 15-minute session with PARO three times a week for 10 weeks. The research assistant left the participant alone with PARO to interact with it as he or she liked -- for example cuddling it, making eye contact, or talking to it. Participants allocated to the plush toy intervention group received the same sessions as described above, but were given a plush toy (PARO with robotic features disabled). Participants in facilities assigned to usual care received standard care. Measuring the outcomes using video observation The three primary outcomes of interest were changes in participants' levels of engagement, mood states, and agitation after 10 weeks of the intervention. Video observation of participants was used to measure these changes. All video data were coded with The Observer XT using the Video Coding Protocol-Incorporating Observed Emotion Scheme. Facility care staff completed the 14-item Cohen-Mansfield Agitation Inventory-Short Form (CMAISF) at baseline, week 10, and week 15, rating on a 5-point scale the frequency that participants displayed agitated behaviors during the previous 2-week period. People with dementia benefit from a robotic pet What the researchers hoped for was found to be true. The PARO group was significantly more verbally and visually engaged with the robotic seal than the plush toy group. Participants demonstrated greater verbal communication and eye contact with PARO. Regarding mood states, both PARO and plush toy groups demonstrated greater reductions in neutral affect than usual care, while PARO was specifically more effective than usual care in improving pleasure. Moreover, PARO demonstrated effectiveness in reducing agitated behavior compared with usual care, although the size of this difference was small. The researchers stress that PARO should not be used to replace staff time, but rather be used during those inevitable periods when staff are otherwise occupied, or when the individual may benefit from comfort from PARO. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial References - Moyle, W.; Jones, C.J.; Murfield, J.E.; Thalib, L.; Beattie E.R.A.; Shum, D.K.H.; O'Dwyer, S.T.; Mervin, M.C. & Draper, B.M. (2017). Use of a Robotic Seal as a Therapeutic Tool to Improve Dementia Symptoms: A Cluster-Randomized Controlled Trial. Jamda, 18, 766-773. - https://www.youtube.com/watch?v=3opo3yOZweo&t=49s - https://www.youtube.com/watch?v=g1WR3jsOpbo --- ## Learn to cooperate toward shared goals using the principles of CRM URL: https://noldus.com/blog/teamwork-behaviors-healthcare Published: 2017-09-25 13:53:00 Description: Teamwork plays an important role in ensuring patient safety and avoiding errors. The most commonly used method to promote teamwork, is training entire teams together to better prepare them for effective cooperation. Throughout the health care community, small groups of individuals work together as teams. Physicians, nurses, pharmacists, technicians, and other health professionals must coordinate their activities to make safe and efficient patient care a priority. In health care, it is not enough to be proficient in just your own individual tasks; one should also be a good team player. However, even though a myriad of the conditions addressed by health professionals require interdisciplinary teams, members of these teams are rarely trained together. Furthermore, they often come from separate disciplines and diverse educational programs. Given the interdisciplinary nature of the work and the necessity of cooperation among the workers who perform it, it is likely that teamwork plays an important role in ensuring patient safety and avoiding errors. Teamwork behaviors Teams make fewer mistakes than individuals do, especially when each team member knows his or her responsibilities, as well as what other team members are responsible for. Team structures, such as recognizing and acknowledging the mistakes of others, coordinating work, and compensating for each other ensures that fewer errors are made. Still, simply installing a team structure does not automatically ensure it will operate effectively. Teamwork is not an automatic consequence of placing people together in the same room; it depends on a willingness to cooperate toward shared goals. In health care, shared goals might include maintaining a patient's health status and avoiding errors. Learn to work together Teamwork can be promoted in several ways. The most commonly used method is training entire teams together to better prepare them for effective cooperation. A team training is very suitable to achieve: - Improved communication between the team members - Better coordinated clinical processes and use of medical equipment - Enhanced decision-making process - Well managed errors and incidents Simulation-based team training in a safe and realistic environment Obstetrics, for example, lends itself to multidisciplinary team training. It is a field in which nurses, midwives, obstetricians and paediatricians work together and where decisions must be made and actions must be carried out under extreme time pressure. The Máxima Medical Centre (MMC) in Eindhoven/Veldhoven, has taken the initiative in the Netherlands in applying team training using practical medical simulation. Multiprofessional teams are trained in teamwork skills using the principles of Crew Resource Management (CRM) and Noldus' technology. During the one-day training, the teams provided care to a simulated patient. The scenarios were all videotaped, and the recordings were used to facilitate the debriefing after each scenario. Discover the 10 reasons why video feedback is essential in skills education. Download the free white paper! The teams of MMC have gathered that both trainees and trainers benefit from video recording of the training scenarios, since Viso provides the opportunity to evaluate medical skills and non-medical skills in a more objective manner. Aside from knowledge and skills, cooperation and communication between the various team members was monitored. The non-obtrusiveness of video recording with Viso allows the performing team to completely focus on the medical scenario, since the trainers (and any other observers, such as colleagues) can monitor the training session from another room. The learning moment is in the debriefing Debriefings are structured discussions facilitated by a team leader for the purpose of reviewing individual and team performance in an open, blame-free, non-punitive environment. The latter is of great importance. Debriefing serves to identify areas where the team performed well along with opportunities for improvement, and it serves to build teamwork and facilitate communication. Feedback has positive effects on team members. Discussing the scenarios afterwards constitutes an important and possibly even the most important part of the simulation. The use of video recordings in team training is the basis for debriefing. It enables you to show what really happened. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo References - Weaver, S.J.; Dy, S.M.; Rosen, M.A. (2014). Team training in healthcare: a narrative synthesis of the literature. BMJ Quality & Safety, 23, 359-372. - Fluit, C.R.M.G.; Klaassen, T.P.F.M. (2011). Achtergronden bij de Richtlijn simulatie teamtraining. Tijdschrift voor Medisch Onderwijs, 30, 11–27. - Baker, D.P.; Gustafson, S.; Beaubien, J. M.; Salas, E. & Barach, P. (2005). Medical Team Training Programs in Health Care. Advances in Patient Safety: From Research to Implementation. --- ## Video recording medical trainees who are interrupted during a complex task URL: https://noldus.com/blog/video-recording-medical-trainees-interruption Published: 2017-09-12 11:34:00 Description: Interruptions in your work have a negative effect on completing your tasks correctly. Jones and her team examined the impact of clinical interruptions on simulated trainee performances during central venous catheterization. How often do you get disturbed during your workday? Maybe you receive an unexpected phone call, a text message on your mobile phone, or a colleague sticks his head around the corner? In other words: these disruptions are made by others who instantly want to claim your time. Interruptions in your work have a negative effect on completing your tasks correctly. The number of mistakes increases, even if the interruption is very short. Due to an interruption, you may forget to resume your original task, take longer to complete the task, or complete the task with higher error rates. At the end of the day, you did not get to what you actually intended. Interruptions kill productivity. Interrupting the workflow In a healthcare setting, interruptions are also common, and the effects may be adverse for the patient. Several studies observed how often physicians and nurses in an emergency room or operation room got disturbed, and found that this could go up to 14 times in an hour, or 50 times per case. Overall, this happens quite a lot. But the interruptions are not always unnecessary. A message or a telephone call can contain important information about the patient, such as blood results. Realistic clinical scenarios in the simulation lab In the experimental study conducted by Jessica Jones and her colleagues from the Department of Psychology at the University of Calgary, Canada, the researchers examined the impact of clinical interruptions on simulated trainee performances during central venous catheterization (CVC). This is a commonly performed procedure. The insertion of CVCs is a challenge for many trainees, as the procedure involves multiple steps and requires aseptic measures to reduce the risk of infection. The simulation lab enabled the researchers to develop realistic clinical scenarios to study the performance of CVC insertion in a controlled environment. Concentration is of the utmost importance Logically, during a complex task like this one, especially for trainees, the risk of making mistakes gets higher when concentration has been broken by interruptions. That is why the researchers expected to find that in comparison to a task that is low in complexity, interruptions during a task that is complex would result in a lower procedural performance score, longer time spent on the procedural task, and a higher number of attempts to establish venous access. Control versus experimental Internal medical residents of the University of Calgary were assigned to two groups in this study. In the control group, participants were interrupted during skin cleaning for the insertion site (a task that is low in complexity). Participants of the experimental group were interrupted while establishing venous access under direct ultrasound guidance. As soon as the needle entered the simulated skin, a 5 second interruption was introduced by a telephone call. Multiple-angle capture to help answer the research questions Twenty-six participants finished the study protocol. The sessions were video recorded using four camera angles, which allowed for capturing views of the room (overview), procedural site, procedural tray, and ultrasound screen. Afterwards, all participants underwent a 30-minute debriefing on their strategies for dealing with interruptions. These views were captured by Viso, which is the ideal recording solution for this kind of study in healthcare education. Viso enables capturing participants' behavior with remotely controlled PTZ cameras, annotating to make descriptions of behavior, and gaining insights into performances while viewing the sessions live. Markers, comments, videos, and audio recorded in Viso are quickly and easily imported into The Observer XT for analysis. Performance review All performances were time coded with The Observer XT. Although results showed that performance scores did not differ between the control and the experimental group, interruptions during the experimental condition resulted in a number of serious procedural errors. Some errors included leaving the needle open to air and failing to aspirate during needle insertion. The reduction in performance, time taken, and number of attempts made was significantly worse when the interruption occurred during a more complex part of the procedure. The researchers concluded that limiting interruptions for trainee performances of CVC may be warranted, as well as developing effective strategies to assist trainees in tempering the negative effects of interruptions. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo Reference Jones, J.; Wilkins, M.; Caird, J.; Kaba, A.; Cheng, A. & Ma. I.W.Y. (2017). An experimental study on the impact of clinical interruptions on simulated trainee performances of central venous catheterization. Advances in Simulation, 2 (5), DOI 10.1186/s41077-017-0038-1 --- ## In home study of older persons URL: https://noldus.com/blog/in-home-study-older-persons Published: 2017-09-05 13:50:00 Description: Older people are healthier these days and like to live in their own homes as long as possible. As a result, the need for home care services is increasing. We all know by now that the number of older persons worldwide is increasing: the proportion of the world's population over 60 years of age is expected to nearly double by 2050. Older people are healthier these days and like to live in their own homes as long as possible. As a result, the need for home care services is increasing. Today's blog is about a study done in Sweden, where researchers looked into the emotional needs of individuals age 60 and above and the communication processes involved in home care situations. Recording communication in the home Annelie Sundler and colleagues explored to what extent people (age 60+) express emotional cues and concerns during home care visits. To find these cues, they asked nurses to make audio recordings. A total of 188 recordings were made. The verbal communication during the audio recorded home care visits was analyzed using the VR-CoDES. This coding scheme was developed by the Verona network to facilitate comparative research on patients' expressions of emotional distress during medical consultations. In this context, it facilitates coding the emotions expressed in a home visit. Download here the Free white paper 'How to set up a coding scheme - 7 tips' Cues that were coded consisted of utterances related to verbal hints to hidden concerns, words, or phrases that emphasized physiological or cognitive correlates. Also included were neutral expressions that mentioned issues of potential emotional importance that stand out from the narrative background. You can find the complete list in the publication by Sundler and colleagues. The analysis was performed in The Observer XT coding and analysis software. First, two coders co-coded audio recordings to find an agreement on certain utterances. By discussing ambiguous units of analysis, the coders reached a high level of agreement. Download here the FREE white paper 'How to set up behavioral coding - 7 tips' How to measure negative emotions In this study, Sundler and colleagues found that negative emotions were expressed in approximately half of the recorded home care visits. Most of these expressions were vaguely expressed as implicit cues, such as a hint towards uncertainty or to a hidden concern such as "I get so tired of this" or "Yes, I do not know, I do now know how it feels…". In order to really recognize these concerns and act upon them, nursing staff should be attentive and open to what comes up in conversations during home care visits. It is important to find out how professionals act upon these subtle messages. What should the next move be? Specific training in this area? What can you study when recording home care visits on video? The authors indicate that they could only study verbal communication because they only had audio recordings to work with. Non-verbal communication such as eye contact, stance, and touch were not analyzed. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial In-home video observations Audio recordings are considered less intrusive compared to in-home video observations. However, to gather more information about communication processes, non-verbal behavior cannot be ignored. In the future, researchers will surely also study non-verbal behavior when they get the chance to record behavior on video in a way that is acceptable for the professional, the patient or client, and other stakeholders. Reference Sundler, A.J.; Höglander, J.; Håkansson Eklund, J.; Eide, H.; Holmström, I.K. (2017). Older persons' expressions of emotional cues and concerns during home care visits. Application of the Verona coding definitions of emotional sequences (VR-CoDES) in home care. Patient Education and Counseling, 100, 276-282. VR-CoDES papers - C. Zimmermann, L. Del Piccolo, J.M. Bensing, S. Bergvik, H. De Haes, H. Eide, I. Fletcher, C. Goss, C. Heaven, G. Humphris, Y.M. Kim, W. Langewitz, L. Meeuwesen, M. Nuebling, M. Rimondini, P. Salmon, S. van Dulmen, L. Wissow, L. Zandbelt, A. Finset, Coding patient emotional cues and concerns in medical consultations: the Verona coding definitions of emotional sequences (VR-CoDES), Patient Educ. Couns. 82 (2011) 141–148. - L. Del Piccolo, A. Finset, C. Zimmerman, Verona Coding Definitions of Emotional Sequences (VR-CODES): Cue and Concerns Manual 2009, European Association for Communication in Healthcare (EACH), 2009. --- ## Why it doesn’t seem fair to prefer male mice in behavioral studies URL: https://noldus.com/blog/male-mice-behavioral-studies Published: 2017-08-10 13:57:00 Description: Is it justified to use male mice only in behavioral studies, as many diseases affect men and women differently? This might be the most important argument to favor including female mice in certain studies. Most behavioral studies using mice, use male mice only. That is because most researchers fear hormones get in the way; estrous cycles might cause data variability. But is this justified, as many diseases affect men and women differently? At the Wolfer lab at the Institute of Anatomy from the University of Zurich in Switzerland, they were pondering the same question, so they surveyed 100 water maze publications from 2016 on PubMed. Most studies used just males, only 12% included both sexes. Why exclude females? One common apprehension of researchers is variability in data. Chances of this happening in females, they assume, are higher because of their estrous cycle. That's the theory. This theory is disproved in at least one study Ann-Kristina Fritz and her colleagues found, which focused on pain sensitivity. This retrospective analysis (Mogil and Chanda, 2005) in almost 8000 mice showed that data were equally reliable regardless of estrous phase. This study also showed significant differences in males and females. Why include females? That's just it: most nervous system diseases affect men and women differently. This might be the most important argument to favor including female mice in certain studies. New retrospective study There are not many studies similar to the one from Mogil and Chanda. Having a large amount of data available from past water maze and open field tests at the Wolfer lab, Fritz and her colleagues had the opportunity to perform a new large retrospective analysis. To investigate male and female data differences for memory, learning, exploration, and anxiety-related parameters, data from 1991 to 2016 were analyzed. The last ten years' worth of data were collected with EthoVision XT video tracking software. Determining variation in data To compare variability in data between male and female test results, the coefficient of variation was calculated. Some differences in variability were detected, but not necessarily in favor of male mice. For example, while swim speed in water maze tests was more variable in female mice, male mice showed more variability when it came to probe trial error. Males vs females Data also revealed differences in scores (performance) between male and female mice for these specific tests (water maze place navigation trials, water maze probe trials, and open field tests), but none reached statistical significance. Gender equality Fritz and her colleagues showed that, at least in water maze and open field tests, there is no significant support for excluding females in these types of experiments. So especially for disorders that (might) affect men and women differently, it is worthwhile to carefully consider choosing males, females, or both for a specific study. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial References - Fritz, A.K.; Amrein, I.; Wolfer, D.P. (2017). Similar reliability and equivalent performance of female and male mice in the open field and water-maze place navigation task. American Journal of Medical Genetics. Part C, Seminars in Medical Genetics. doi: 10.1002/ajmg.c.31565. - Mogil, J.S.; Chanda, M.L. (2005). The case for the inclusion of female subjects in basic science studies of pain. Pain, 117(1-2), 1-5. --- ## The response of oxytocin to mother-infant interaction URL: https://noldus.com/blog/response-oxytocin-mother-infant-interaction Published: 2017-08-08 16:32:00 Description: Researcher Rebecca Knapp was interested to know whether infant eye gaze away from the mother, or eye gaze directed to the mother, would correspond to increased maternal oxytocin. Read her blog post to learn more. Posted by Rebecca Knapp (Deakin University, Centre for Social and Early Emotional Development, Melbourne, Australia). Background to the research field Oxytocin Oxytocin is a hormone with special properties. Everyone produces oxytocin; men, women and children. Originally found to be of particular importance in birth and lactation, researchers have started to look at other, broader influences oxytocin may have on human behavior and relationships. Animal models have found that oxytocin plays a role in a wide range of maternal behaviors and in the quality of maternal caregiving.1 Studies are now looking at whether oxytocin might share a relationship with human maternal and infant behavior as well.1-5 Oxytocin and maternal behavior In human studies, oxytocin has been found to correspond to increased gaze, touch and positive affect in mothers towards their own infants. In adults, oxytocin has been found to increase trust and to improve the reading of emotional cues; important qualities in a developing relationship.2, 6 The general view of those researching oxytocin's potential role in maternal and infant relationships suggest that oxytocin supports mutual reward and synchrony. Mothers and infants who share similar oxytocin response to interaction appear to share greater synchrony in those interactions, such as greater mutual gaze, and greater mutual positive affect.7-9 There is some data to suggest that certain maternal behaviors release oxytocin in mothers, and that the release of oxytocin increases certain maternal behaviors in what is considered by some to be a 'bio-behavioral feedback loop'.10 There is further research to suggest that maternal oxytocin and behavior might influence infant oxytocin and behavior, suggesting that this bio behavioral feedback loop goes beyond the individual, and is expressed between individuals in the mother-infant dyad. But relationships are not one-way. Mothers respond to infants, and infants respond to mothers. A mother might tickle her baby who shows pleasure by giggling and reaching for more, perpetuating the mother's behavior. An infant might look away when he has had enough, and the mother waits for her baby's gaze to return before starting a new game. A baby might shift her gaze to an interesting toy, and when she experiences a moment of delight, looks back to her mother to share this moment. It is a delicate dance between mother and infant, each responding to, and influencing each other. Part of this dance is one of parental sensitivity and the development of infant attachment security to the caregiver. Maternal behavior and infant attachment security In the field of infant attachment research, two maternal behaviors are fundamental to the development of infant attachment security: the mother's capacity to allow her baby to explore, and her capacity to welcome her infant back to her in times of need.11, 12 Whilst some studies have speculated that oxytocin might support maternal caregiving behavior and thereby support the development of infant attachment security, none have explored specific infant behaviors that might influence maternal oxytocin response and maternal behavior. Synchrony is not enough, as it does not explain maternal readiness to welcome an infant back following a rupture in the relationship or at times of infant need. Eye gaze, mother-infant communication and oxytocin Eye gaze between two individuals is central to communication and is a key feature of both maternal sensitivity and infant attachment security.13-17 Gaze aversion is one way infants help regulate their own emotional state, particularly when they feel over-excited.13-17 Infants may also look away as part of their exploration as they take in their surrounding environment. A mother who experiences her infant's attentional shift away as a sign of the infant rejecting her will feel and respond differently from a mother who experiences this same behavior as a sign of the infant's fatigue, boredom or interest in other things. This study sought to investigate whether oxytocin might pay a role in facilitating the openness of the mother to the infant 'coming back in' after a break in interaction. For the purpose of this study, a 'break in interaction' was defined as the period during which the infant looked away from his or her mother. I was interested to know whether infant eye gaze away from the mother, or eye gaze directed to the mother, would correspond to increased maternal oxytocin. If it is synchrony and social reward alone that corresponds to oxytocin release, then one would expect greater infant gaze to the mother to correspond to greater oxytocin concentration in the mother. If oxytocin however serves a function of maintaining maternal engagement through increasing eye gaze, and readiness to welcome the infant back in, then infant disengagement (looking away) should correspond to a maternal oxytocin response. How the data was gathered Method Ten mothers and their infants attended the lab at Deakin University, at a time which fell 1 hour either side of a feed, as salivary oxytocin has been found to peak in that period.18 Following a 10-min familiarization period where mother and infant became accustomed to the room, the mother provided a baseline saliva sample using a Salivette (Sarstedt, Rommelsdorft, Germany). The mother was then asked to place her baby on an infant beanbag positioned on the floor, and to sit on the floor facing her baby. Two cameras were placed in the room, one facing the mother, the other facing the infant. A third camera behind a two-way screen was positioned to capture the mother and infant in profile. (Image obscured to protect participant privacy) The three videos were then synchronized and combined into a single split screen image using The Observer XT. Mothers were asked to engage in 10 minutes of play with their infants without toys. Play could include any type of interaction, game, vocalisation, or touch they typically used. Mothers were told they could pick up their baby if the baby became distressed however they were otherwise encouraged to keep their infant in the beanbag to aid videoing of infant and maternal gaze direction. Fifteen minutes after the end of the interaction task, a second saliva sample was collected from mothers. Saliva samples were analyzed by an EIA commercial kit, consistent with previous research.4, 10, 18 Coding of gaze Gaze was coded separately for mothers and infants, using The Observer XT. Maternal gaze was coded in relation to it being directed to the infant's face (on/off). Infant gaze was coded in relation to it being directed to the mother's face (on/off). Results First, maternal gaze and maternal oxytocin were explored to see if previous research would be replicated, which it was. Increasing maternal oxytocin from pre- to post-interaction was associated with increased maternal eye gaze during the interaction task, whilst decreasing maternal oxytocin was associated with decreasing maternal eye gaze. Then, the relationship between infant eye gaze and maternal oxytocin was explored. Infants whose gaze increased over the interaction task were compared with infants whose gaze decreased over time. For these two groups, increasing infant gaze was associated with decreasing maternal oxytocin, whilst decreasing infant gaze was associated with a slight increase in maternal oxytocin. Conclusions As expected, increasing maternal gaze was associated with increasing maternal oxytocin, consistent with previous research.19 Interestingly, in regards to infant gaze and maternal oxytocin, increasing infant gaze was associated with decreasing maternal OT. It is possible that when there is greater degree of engagement by an infant with their mother, maternal oxytocin may decrease as the socially affiliative properties of oxytocin are not required to maintain or repair a connection, however when infants are disengaging, maternal oxytocin may be elicited as a social stress response, in order to support maternal readiness for reconnection. This would be consistent with the observed increase in maternal OT predicting increasing maternal eye gaze, as mothers possibly reorient to and attempt to reengage with their disengaging infants. Thus, infant gaze away from the mother may elicit a maternal oxytocin response. Oxytocin may serve to increase maternal vigilance of the infant's emotional state as the infant explores, maintaining the balance between supporting infant exploration, and readiness for her infant to return to the relationship. Future directions Of course this was a very small pilot study and these results would need to be replicated on a larger scale to demonstrate reproducibility. Further, it is likely that different mothers responded differently to their infants looking to and away from them, in terms of their own behaviour, their interpretation of their infants' behaviour, and potentially in terms of their oxytocin response. It would be interesting in future, larger scale studies to compare two groups – one where infants increased their gaze and the other where infants decreased their gaze over the interaction task, and compare mothers whose oxytocin rose, to those whose oxytocin fell over the course of these two conditions. Seeing how those mothers responded in terms of their own eye gaze would help determine whether infant behaviour does indeed influence maternal behaviour, and whether maternal oxytocin mediates the relationship between the two. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Thanks to Noldus I wanted to thank Noldus for very kindly offering an extended trial loan of the Observer XT. The detailed behavioural coding that was required would not have been possible without sophisticated software like The Observer XT. It enabled me to code not only gaze, but several other behavioral variables, quickly, accurately and efficiently. I cannot thank Noldus enough for their generosity, support and their interest in my research project. References - 1.Ross, H. E., & Young, L. J. (2009). Oxytocin and the neural mechanisms regulating social cognition and affiliative behavior. Frontiers in Neuroendocrinology, 30(4), 534-547. doi:http://doi.org/10.1016/j.yfrne.2009.05.004 - 2.Feldman, R. (2012). Oxytocin and social affiliation in humans. Hormones and Behavior, 61(3), 380-391. doi:10.1016/j.yhbeh.2012.01.008 - 3.Carter, C. S. (2014). Oxytocin pathways and the evolution of human behavior. Annual Review of Psychology, 65(1), 17-39. doi:10.1146/annurev-psych-010213-115110 - 4.Carter, S. C., Pournajafi-Nazarloo, H., Kramer, K. M., Ziegler, T. E., White-Traut, R., Bello, D., & Schwertz, D. (2007). Oxytocin: behavioral associations and potential as a salivary biomarker. Annals of the New York Academy of Sciences, 1098(1), 312-322. doi:10.1196/annals.1384.006 - 5.Feldman, R. (in press). The neurobiology of mammalian parenting and the biosocial context of human caregiving. Hormones and Behavior. doi:http://dx.doi.org/10.1016/j.yhbeh.2015.10.001 - 6.Lee, H.-J., Macbeth, A. H., Pagani, J. H., & Scott Young 3rd, W. (2009). Oxytocin: The great facilitator of life. Progress in Neurobiology, 88(2), 127-151. doi:http://doi.org/10.1016/j.pneurobio.2009.04.001 - 7.Feldman, R. (2003). Infant-mother and infant-father synchrony: The coregulation of positive arousal. Infant Mental Health Journal, 24(1), 1-23. doi:10.1002/imhj.10041 - 8.Feldman, R. (2007). Parent-infant synchrony and the construction of shared timing; physiological precursors, developmental outcomes, and risk conditions. Journal of Child Psychology and Psychiatry and Allied Disciplines, 48(3-4), 329-354. doi:10.1111/j.1469-7610.2006.01701.x - 9.Feldman, R. (2012). Interactive synchrony: A biobehavioral model of mutual influences in the formation of affiliative bonds in healthy and pathological development. Neuropsychiatrie de l'Enfance et de l'Adolescence, 60(5), S2. doi:10.1016/j.neurenf.2012.04.016 - 10.Feldman, R., Gordon, I., Schneiderman, I., Weisman, O., & Zagoory-Sharon, O. (2010). Natural variations in maternal and paternal care are associated with systematic changes in oxytocin following parent-infant contact. Psychoneuroendocrinology, 35(8), 1133-1141. doi:10.1016/j.psyneuen.2010.01.013 - 11.Ainsworth, M. D., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: Assessed in the strange situation and at home: Hillsdale, NJ: Erlbaum. - 12.Marvin, R., Cooper, G., Hoffman, K., & Powell, B. (2002). The Circle of Security project: Attachment-based intervention with caregiver-pre-school child dyads. Attachment & Human Development, 4(1), 107-124. doi:10.1080/14616730252982491 - 13.Beebe, B., Jaffe, J., Markese, S., Buck, K., Chen, H., Cohen, P., Bahrick, L., Andrews, H. & Feldstein, S. (2010). The origins of 12-month attachment: a microanalysis of 4-month mother-infant interaction. Attachment & Human Development, 12(1-2), 3-141. doi:10.1080/14616730903338985 - 14.Beebe, B., Lachmann, F., Markese, S., Buck, K. A., Bahrick, L. E., Chen, H., Cohen, P., Andrews, H., Feldstein, S. & Jaffe, J. (2012). On the Origins of Disorganized Attachment and Internal Working Models: Paper II. An Empirical Microanalysis of 4-Month Mother-Infant Interaction. Psychoanalytic Dialogues, 22(3), 352-374. - 15.Beebe, B., & Steele, M. (2013). How does microanalysis of mother-infant communication inform maternal sensitivity and infant attachment? Attachment & Human Development, 15(5-6), 583-602. doi:10.1080/14616734.2013.841050 - 16.Beebe, B., Steele, M., Jaffe, J., Buck, K. A., Chen, H., Cohen, P., Kaitz, M., Markese, S., Andrews, H., Margolis, A. & Feldstein, S. (2011). Maternal anxiety symptoms and mother–infant self‐and interactive contingency. Infant Mental Health Journal, 32(2), 174-206. - 17.Koulomzin, M., Beebe, B., Anderson, S., Jaffe, J., Feldstein, S., & Crown, C. (2002). Infant gaze, head, face and self-touch at 4 months differentiate secure vs. avoidant attachment at 1 year: A microanalytic approach. Attachment and Human Development, 4(1), 3-24. doi:10.1080/14616730210123120 - 18.White-Traut, R., Watanabe, K., Pournajafi-Nazarloo, H., Schwertz, D., Bell, A., & Carter, C. S. (2009). Detection of salivary oxytocin levels in lactating women. Developmental Psychobiology, 51(4), 367-373. doi:10.1002/dev.20376 - 19.Kim, S., Fonagy, P., Koos, O., Dorsett, K., & Strathearn, L. (2014). Maternal oxytocin response predicts mother-to-infant gaze. Brain Research, 1580, 133-142. doi:10.1016/j.brainres.2013.10.050 --- ## IR backlight in rodent behavioral testing URL: https://noldus.com/blog/ir-backlight-rodent-behavioral-testing Published: 2017-07-27 15:24:00 Description: How do mice act in complete darkness? Ann-Kristina Fritz and her colleagues ordered a large, round open field with IR backlight, custom made by Noldus, to investigate. How do mice act in complete darkness? How do mice act in complete darkness? Ann-Kristina Fritz and her colleagues ordered a large, round open field with IR backlight, custom made by Noldus, to investigate. Infrared (IR) light cannot be seen by the human eye, nor by rats and mice. As rodents are nocturnal, testing during the dark is often preferred; using IR light the test environment remains dark for the animal, but their behavior can be monitored and tracked with IR sensitive cameras. Additionally, using IR light during video tracking experiments improves contrast for better detection. So, the question is: how can you easily incorporate IR lighting in behavioral testing? Incorporating IR in experiments Theoretically, this is simple to do: place an IR light source beneath the testing area. Of course, this only works if the maze or arena is IR translucent. Some mazes already incorporate an IR backlight source, and many suppliers can create a custom-built solution. Custom build setup Ann-Kristina Fritz and her colleagues from the Wolfer lab at the Institute of Anatomy from the University of Zurich in Switzerland opted for the latter option, and ordered a large, round open field with IR backlight, custom made by Noldus. I recently called her to ask her about her plans with this setup. Shared labs need to be multi-functional "At the Institute of Anatomy, we have one big room were we do all the behavioral testing", Ann-Kristina explains. The lab is shared by several groups; over the years, the room has evolved into one shared space with combined setups. "A large part of the room was occupied by a big water maze. We wanted to get more out of that space, so we thought of ways to make it multi-functional." Why IR backlight Ann-Kristina and her colleagues had done previous experiments using IR backlighting in other setups and liked the results. So in addition to wanting a large, multi-functional open field, they decided it needed to be IR backlit. "This way, we can use it for open field testing, novel object recognition, and as a background for other tests. For example, using IR translucent black Plexiglas, we were able to build a zero maze to use on top of the open field". Results with IR backlight This lab is currently trying out different applications for IR studies, and testing if behavior is different in normal light vs IR light studies. According to Ann-Kristina, preliminary results show that mice do act differently in dim light vs complete darkness (with IR light): "In an open field test, mice are quicker, more active, and enter the center zone of the arena more often in the complete dark. Light intensity might be a good variable to investigate, especially in studies on stress, and I have found almost no papers that show an interest in this aspect." FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Adjustments While IR light has its perks, there are some things to keep in mind when switching to IR in your experiments. "You might have to adjust your setup", she explains. "Obviously, you need an arena or maze made out of IR translucent material, but there are other aspects to keep in mind, too." "For example, if you incorporate an IR translucent shelter in your setup, you will be able to see the animal move inside of the shelter. However, your video tracking results will not automatically be able to differentiate between the animal being in, or on top of, the shelter." Certain tests will benefit more from IR backlight than others, according to Ann-Kristina. "A great example being the light-dark test. You can see everything that the animal is doing in the dark compartment. How useful you'll find IR backlight also depends on fur color and markings." Interesting links Want to find out if IR backlight will be beneficial for your experiments? Need to order a custom setup? At Noldus we can tell you all about it. Contact us today! Ann-Kristina Fritz works in Prof. David Wolfers' group at the Institute of Anatomy from the University of Zurich in Switzerland. Recent papers - Fritz, A.K.; Amrein, I.; Wolfer, D.P. (2017). Similar reliability and equivalent performance of female and male mice in the open field and water-maze place navigation task. American Journal of Medical Genetics. Part C, Seminars in Medical Genetics. doi: 10.1002/ajmg.c.31565. - Hick, M.; Herrmann, U.; Weyer, S.W.; Mallm, J.-P.; Tschäpe, J.-A.; Borgers, M.; Mercken, M.; Roth, F.C.; Draguhn, A.; Slomianka, L.; Wolfer, D.P.; Korte, M.; Müller, U.C. (2015). Acute function of secreted amyloid precursor protein fragment APPsα in synaptic plasticity. Acta Neuropathologica, 129, 21-37. - Mircsof, D.; Langouët, M.; Rio, M.; Moutton, S.; Siquier-Pernet, K.; Bole-Feysot, C.; Cagnard, N.; Nitschke, P.; Gaspar, L.; Žnidarič, M.; Alibeu, O.; Fritz, A.-K.; Wolfer, D.P.; Schröter, A.; Bosshard, G.; Rudin, M.; Koester, C.; Crestani, F.; Seebeck, P.; Boddaert, N.; Prescott, K.; The DDD Study; Hines, R.; Moss, S.J.; Fritschy, J.-M.; Munnich, A.; Amiel, J.; Brown, S.A.; Tyagarajan, S.K.; Colleaux, L. (2015). Mutations in NONO leads to syndromic intellectual disability and inhibitory synaptic defects. Nature Neuroscience, 18(12), 1731-1736. Thank you, Ann-Kristina, for working on this with me! --- ## The emotions of people who think they’re nice URL: https://noldus.com/blog/emotions-people-who-think-they-are-nice Published: 2017-07-18 10:56:00 Description: What does ‘nice’ actually mean in relation to psychological variables? And does it positively correlate with self-reported levels of health, happiness, and wellbeing? The word 'nice' is a commonly used word. We encounter it on a daily basis when we want to make clear that something or someone is positive in our opinion. 'That was a very nice meal, 'We had a nice conversation, 'What a nice boy…' we use it frequently and easily, and we all understand its meaning. Do people find themselves nice? But what does 'nice' actually mean in relation to psychological variables? And does it positively correlate with self-reported levels of health, happiness, and wellbeing? Researchers of i2 media research from the Goldsmiths University of London, UK, developed a tailored questionnaire to explore this. Being nice in everyday life The British researchers presented 100 participants with a list of 'nice' behaviors and asked them to rate themselves. Which 'nice' things for others, such as 'giving directions to a stranger,' 'helping someone carry heavy bags,' and 'donating blood' had they done and which had they not? It turned out that nice people are more likely to do nice things for others than those who rated themselves as less nice. Also, nicer people reported being happier, relaxed, healthier, and more fulfilled in their careers. They scored higher on emotional intelligence, which describes how well a person is able to understand the emotions of others, recognize their own, and label feelings appropriately. The research team found out that 98 percent of the participants think they are part of the nicest 50 percent of the population. Clearly, that is not possible. More than half of the participants who rated themselves as the second-highest level of nice scored below the sample average on the questions about kindness in the questionnaire. So, some of them think they are nicer than they really are. What if someone is rude to you? People cannot always be nice. In some situations and contexts, you tend to forget that you want to be nice. For example, this often occurs in situations like when someone else is rude to you, which was found to be the biggest trigger, or when you've just find out that your keys are missing, or when you're frustrated that the bus is late. Participants were asked to report what makes them 'lose their nice.' An interesting finding was that people who rated themselves as 'very nice' or 'quite a bit nice' were less likely to report that some of these situations or events would trigger them to lose their nice. Apparently, they deal with stress and criticism better than others. They are better able to control the chaos of everyday life. Facial expressions matched Out of the 100 participants, the researchers selected 10 people for a lab based demonstration. They were asked to watch a selection of videos with positive and negative scenes, including overcrowded underground stations, crying children, and scenarios such as interviews or exams. The second tasks was to listen to an aversive sound played at a high volume for as long as possible. Meanwhile, their facial expressions were measured with FaceReader. Professor Freeman, who led the study, finds FaceReader very handy: "It analyzes frame by frame the expressions and how they vary on people's faces. So you capture even micro expressions that people don't have control over." Negative facial expressions, indicating stress, were clearly visible in participants' reactions to the stimuli. However, as expected, nice people showed fewer negative emotions. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Reference Ferrari, E.; Freeman, J. (2017). The power of nice: A study exploring the relationship between participant ratings of how 'nice' they are, their behavior, and their reported levels of health, happiness and success. i2 media research, research report on behalf of Monarch. --- ## Emotions distract people with eating disorders URL: https://noldus.com/blog/emotions-distracts-people-eating-disorders Published: 2017-07-18 10:40:00 Description: Studies show that people with anorexia nervosa have reduced facial expressivity of emotions while viewing emotionally provoking stimuli. Researcher Leppanen and her team used FaceReader to investigate this. It happens to me sometimes: standing on the bathroom scale, looking at the numbers that appear, and thinking ‘oh no…, you’re kidding me?!’ Weight and the way we look play an important role in our daily lives. We need to look good and feel good. It's quite normal to be insecure about this occasionally. However, when eating behavior modifies into a disorder, when someone exaggerates in starvation or, in contrast, eats huge amounts of food, which he or she tries to get rid of as soon as possible afterwards, problems arise. In the first case, we speak of anorexia nervosa (AN), in the second case of bulimia nervosa (BN). The need to be in control of emotions These eating disorders (ED) are usually accompanied by difficulties in social-emotional communication. Shame plays an important role. Most likely these difficulties contribute to the development and maintenance of disordered eating. People with AN need to be in control, feeling emotions distracts them from this. Therefore, the eating disorder functions as a maladaptive emotion regulation strategy, numbing the expression of emotions, which leads to social isolation and family conflicts. The advantage of automated facial expression recognition Studies show that people with AN have reduced facial expressivity of emotions while viewing emotionally provoking stimuli. Most of the studies in eating disorders have examined emotion expression utilizing manual coding systems, such as the Facial Expression Coding System. However, such manual coding methods require extensive training, are labor-intensive, time consuming, and potentially problematic for interrater reliability. The use of more physiological techniques such as facial electromyography, on the other hand, can be obstructive as it requires electrodes to be placed on the participant’s skin. Using computerized automated facial expression recognition software that classifies facial expressions from still images and video and provides information about the intensity of the emotion expressed, can be methodologically and ecologically more sound and robust. Do people with eating disorders show less facial affect? The aim of the current study was to pool together data from previous studies, as well as new and unpublished data, in order to create a large dataset relating to emotion expression in people with ED across the diagnostic spectrum and stage of recovery. The researchers hypothesized that people with ED would display less facial affect while viewing emotionally provoking stimuli compared to healthy control participants and people recovered from AN. Happiness and sadness 297 female participants, of which 100 were diagnosed with AN, 33 with BN, 38 recovered from AN, and 126 were part of the healthy control group (HC), completed a self-report questionnaire and a film task. The Eating Disorders Examination Questionnaire (EDEQ), provided an assessment of restraint, eating concern, weight concern, and shape concern over the past 28 days. During the film task participants were presented with two video clips. They were recorded while they watched these. The first video clip (film 1) featured a humorous scene from the film ‘Four weddings and a funeral’ and was used to evoke positive emotions. The second video clip (film 2) featured a sad scene from the film ‘Shadowlands’ and was used to evoke negative emotions, particularly sadness. The recordings were analyzed with FaceReader and pooled from datasets of previously published studies. Unpublished data from these studies was also included. The researchers focused on emotions the film clips were designed to elicit, happiness and sadness. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Submit to download Indeed, people with anorexia nervosa express less happiness The findings revealed that all participants expressed significantly more happiness in response to film 1 than film 2. Pairwise comparison revealed that HC participants expressed significantly more happiness than AN participants during film 1. Similarly, the recovered participants expressed significantly more positive affect than AN participants during film 1. The decrease of positive facial affect of AN participants, may be part of acute illness and possibly exaggerated by starvation. People with AN report greater tendency to rely on emotion avoidance and denying. All participants expressed more sadness while viewing film 2 than film 1. There were no other significant effects of interactions found. People with BN displayed marginally more positive facial affect than the people with AN, but were not significantly different from the HCs.  Clinical implications The elevated negative mood and inability to experience pleasure in anything, poor social relationships, and isolation reported by people with ED may be in some way related to reduced facial expressivity. Thus, the present findings highlight the need for interventions that target emotion expression in ED, particularly those aimed at increasing the expression of positive affect. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers - Customer success stories - Featured blog posts Resources Reference Leppanen J.; Dapelo M.M.; Davies H.; Lang K.; Treasure J.; Tchanturia K. (2017) Computerised analysis of facial emotion expression in eating disorders. PLoS ONE 12(6): e0178972. https://doi.org/10.1371/journal.pone.0178972 --- ## Brain & behavior: data integration in horse studies URL: https://noldus.com/blog/data-integration-horse-studies Published: 2017-07-12 08:19:00 Description: EEG recordings – they produce useful data, but are not always easy to obtain in animal studies. You can’t really ask a horse to sit still, so these researchers invented a promising new system for EEG recording. Electroencephalography (EEG) EEG is an ideal diagnostic tool for assessing brain wave activity. The data can assess brain dysfunction, or investigate the different stages of sleep. In humans, gathering EEG data is simply a matter of placing the electrodes on the scalp; the hardest part is getting the subject to sit still, as the quality of the recordings depends on minimal movement or muscle activity. EEG in animals EEG recordings are also valuable in animal models, to study brain diseases, brain damage, sleep, the impact of anesthesia, epilepsy, to name a few. But, as you can imagine, it is difficult to gather reliable recordings. To do so, often the animal needs to be shaved and fixated (sedated), and in some instances it even requires surgery and implants. This is not practical for many reasons, especially for clinical studies using large animals, like horses. EEG in horses Hugo Cousillas and his colleagues from the University of Rennes (Brittany, France) wanted to more easily obtain reliable EEG data from horses in a way that is more suitable for veterinary purposes and welfare research. In other words, avoiding fixation of the horse and heavy headgears. They set out to create a system that could be used on a freely moving horse in its home environment (stable). The goal was to create a system that would be easy to apply, adjustable to the individual horse, and put no more restraint on the horse than a normal halter would. Horse headset So they developed a headset – or, as described by the researchers, "a necklace made of large rubber bands" - that allowed for good and stable contact of the electrodes with the horse's head. With this headset, recordings were obtained from both hemispheres (two electrodes on each side) to obtain data on the differential activity between the occipital and frontal parts of the brain. Pilot testing The first tests with this headset were recently reported in Frontiers in Veterinary Science. Five sport horses wore the headsets for two daily sessions of 15 minutes, while standing and resting in their stables. The authors were able to capture alpha, beta, and gamma waves, and the data seems consistent with previous studies. Quite impressive if you ask me, because the horse's head contains a lot of muscles that could easily interfere with the signals. Data integration Complex data, such as EEG recordings, needs context in order to make full sense of it. In this case, that context is the horse's behavior. To monitor the behavior of the horses, the researchers used Media Recorder to record and synchronize several videos at once, and then brought those videos into The Observer XT to score behaviors of interest, and synchronize the behavioral data with the EEG data. Data analyses Having synchronized data is advantageous in that you can select periods of one data stream, based on what happened in the other data stream. In this case, EEG data was analyzed while the horses were standing relaxed. During these periods, none of the horses exhibited a difference between EEG data across hemispheres, and there was also no difference between the two days of data collection. This supports the notion that the electrodes were precisely placed both times. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Unobtrusive Also, the researchers note that with this EEG headset, all horses showed alpha waves, whereas in other studies horses sometimes failed to present these. In this study, the horses seemed relaxed and not bothered by the headset; apprehensive horses are likely to have increased cortical arousal, resulting in a decrease in alpha frequencies, as the researchers explain. Good start These researchers are certainly off to a good start in getting better EEG data in freely moving horses. In these first try-outs of this headset, the headset seems unobtrusive to the horses, it works great in a data integration setting, and seems a valuable tool for future studies. I'm curious to see how the headset works in larger sample groups, and in long-term studies, and if this would work as a veterinary application! References Cousillas, H.; Oger, M.; Rochais, C.; Pettoello, C.; Ménoret, M.; Henry, S.; Hausberger, M. (2017). An ambulatory electroencephalography system for freely moving horses: an innovating approach. Frontiers in Veterinary Science, 4, 57. --- ## Behavioral tests to select police horses URL: https://noldus.com/blog/behavioral-tests-select-police-horses Published: 2017-07-04 13:26:00 Description: The personality of police horses influences how well they do in their ‘job’. That’s why personality tests are important for both animal and human welfare and safety. I'm sure you've heard someone say a dog looks like its owner? Or that cats have a character of their own? As an owner of four cats and a horse, I can definitely say I agree that animals show personality. And personality can be important if the animals serve a specific role. Personality in horses Take police horses, for example. Their personality surely influences how well they do in their 'job'. That's why personality tests are important for both animal and human welfare and safety. Selection of police horses Marc Pierard and colleagues from the University of Leuven (Belgium) and the University of Sydney (Australia) have developed a procedure to support the selection of police horses, and recently carried out a pilot study with these horses to see if the 9 tests were feasible to execute. Tests and trials In these behavioral tests, the personality of 48 horses was assessed based on behavioral coding and subjective rating. The horses were studied while they ran loose, were presented with an umbrella coming from the ceiling, exposed to sudden sounds, were led over a wooden plank and tarp, and exposed to a conspecific. Video recording During these tests, a video camera recorded the horses from above, and these videos were used to code behaviors of interest with The Observer XT software. Assessments were made on their movements, behaviors such as jumping, bucking, and whinnying, as well as contact and proximity to objects and the handler. Heart rate data integration Initially, the researchers wished to also integrate the horses' heart rate data. These types of external data are easily integrated with The Observer XT for combined analysis. However, as the horses were moving freely, rolling and bucking, the electrodes did not stay put. In addition, the receiver was placed in the corner of the arena instead of on the animal, resulting in loss of data. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Good trial run This protocol proved to be feasible, safe, and practical in this study, which was the main aim of this study. The 48 horses in this study were all trained police horses, so it is not that surprising that the behavioral test did not yield significant differences between 36 "well-suited" and 12 "less-suited" horses. Further developed, these tests might prove useful in the future selection of police horses, using current results as a benchmark. References Pierard, M.; McGreevy, P.; Geers, R. (2017). Developing behavioral tests to support selection of police horses. Journal of Veterinary Behavior, 19, 7-13. --- ## Interview skills training for adolescents with language disorder examined URL: https://noldus.com/blog/adolescents-language-disorder-examined Published: 2017-06-29 14:41:00 Description: The study of Mathrick and colleagues evaluated an interview skills training package targeting both verbal and non-verbal skills for adolescents with severe and persistent Language Disorders. In order to communicate, one must be able to send messages in a manner that the recipient understands, but also be able to perceive and understand the messages received in return. Communication can have different forms here, including printed, verbal, and non-verbal. Children with developmental language disorders (LD) have difficulty understanding language or talking to others. They make short sentences, and are often poorly understood. This can create an insecure feeling for the child. Enhancing employment opportunities Imagine that you're about to begin a job search. Getting a job is a difficult task in general; performing well in the job interview is often anxiety provoking. This is particularly true for individuals with LD, where job interviews are likely to be extra challenging, due to demands on verbal and non-verbal communication and the need to respond quickly and appropriately to interviewer questions. A key factor in personnel selection is a good impression of the candidate at the interview. Non-verbal behaviors also have a great impact on the judgment of a job candidate. Cues, such as smiling, eye contact and head nods contribute to a positive evaluation of the candidate. Individuals with LD have varying degrees of difficulty with social communication skills that are critical to interview success, including: difficulties using and understanding non-verbal cues (head nods, taking turns appropriately, expressing ideas, and understanding what they have been told), limited speech fluency, use of immature grammar, and frequently irrelevant answers to questions. Focus on non-verbal communication behaviors There is a need to develop and evaluate techniques that increase the likelihood that individuals with LD can succeed at employment interviews. The study of Mathrick and colleagues evaluated an interview skills training package targeting both verbal and non-verbal skills for adolescents with severe and persistent LD, including individuals with ASD. They predicted that targeting and reinforcing positive non-verbal and verbal social communication skills during therapy would result in increased use of these behaviors in formal employment interviews. The researchers conducted two studies. Role play as intervention In the first study, twelve participants (17-18 years old) received an interview letter with information about the interview. After discussing this letter in a group therapy session, they individually participated in a mock interview (T1). Together with the speech language therapist, the video of this interview was watched and the therapist provided feedback. Twelve sessions of group therapy followed. Using role play, the therapists demonstrated how to respond appropriately to target questions and how to use non-verbal skills, including shaking hands, using appropriate body language, and facial expression. They then practiced all this in smaller groups, with one target question per week. Positive feedback to increase positive behavior To increase confidence, therapists provided more explicit positive feedback for behaviors that the participants needed to increase (e.g., using examples to evidence responses, making eye contact, and smiling), and did not highlight negative behaviors that needed to decrease (e.g., excessive or irrelevant information in response to questions). A second mock interview (T2), immediately after the interview skills therapy, was conducted to complete this first study. A behavioral coding scheme was developed that incorporated behaviors identified as important for successful interviews, likely to be problematic for individuals with LD, and likely to be targeted in the therapy program. Coding was carried out using The Observer XT, which allowed moment by moment coding of the behavioral data. Encouraging results of the first study There was a significant increase in positive non-verbal behaviors such as eye-contact, appropriate facial expression and use of gesture from T1 to T2. Positive verbal behaviors, such as responding to a comment, requesting clarification, and providing examples to questions also increased. There were no changes in negative verbal or negative non-verbal behaviors. Important to develop interview skills in therapy content For the second study, thirty young people with severe LD (17-18 years old) participated. The intervention consisted of the same treatment program as in study 1, with some adjustments. Therapy time was increased to 16 group sessions, and more role play and prompt cards were introduced to model positive non-verbal behaviors. Each participant received three mock interviews: one baseline interview (T1), an interview after a no-treatment baseline period and prior to the onset of interview skills therapy (T2), and one immediately after the therapy sessions had finished (T3). Compared with study 1, there were marked improvements in positive non-verbal communication skills, which may reflect the importance on developing these skills in the therapy content. Reducing negative non-verbal behaviors appeared to be a more gradual process, with declining scores during the baseline period. Preparing for job interviews useful The two studies show evidence that adolescents with severe LD can improve a range of verbal and non-verbal social communication skills in response to a focused intervention that provides many opportunities for role play, discussion and visual supports. This study focused on adolescents in real-life clinical settings and the results should encourage future research with this group of vulnerable young people. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Reference Mathrick, R.; Meagher, T.; Norbury, C.F. (2017). Evaluation of an interview skills training package for adolescents with speech, language and communication needs. International Journal of Language & Communication Disorders, DOI: 10.1111/1460-6984.12315. --- ## Gait recovery and other effects: treatment of cervical myelopathy URL: https://noldus.com/blog/gait-recovery-cervical-myelopathy Published: 2017-06-22 08:24:00 Description: At the Dr. Michael Fehlings' lab, they are on a quest to find out what exactly causes the lower success rate of delayed surgery in cervical myelopathy. Degenerative cervical myelopathy (DCM); a mouthful to describe what happens when the spinal cord and blood vessel become compressed and causes all kinds of neurological symptoms such as clumsy hands, unstable gait, and sensory changes in arms. Degenerative cervical myelopathy DCM encompasses a spectrum of arthritic and ligamentous conditions of the cervical spine, such as Cervical spondylotic myelopathy (a neck condition). It is the most common cause of non-traumatic spinal cord injury, is often age-related, and happens mostly to older patients. Clinical signs vary, and can include loss of manual dexterity, pain and impaired gait. Decompression The good news is that the standard treatment, surgical decompression, can halt the progression of the disease and improve neurological and functional status dramatically. The bad news is that symptoms are not always recognized quickly, and the success of the surgery seems to largely depend on how soon it takes place after symptoms started, how young the patient is, and the comorbidities patients present before surgery. Success rate of surgery Pia Vidal and her colleagues from Dr. Michael Fehlings' lab, are on a quest to find out what exactly causes the lower success rate of delayed surgery. In previous work (Karadimas et al., 2015), her colleagues found ischemia-reperfusion injury (IRI) to be a key factor in the neurological decline in rat models after decompression surgery. However, the role of inflammation in this process was unclear. Mouse model Vidal's recent paper in JCI Insight describes the study of a mice model with C5-C6 compression (the most common site for DCM in the spinal segment in patients), comparing the results of early versus late decompression. They show that the restoration of the spinal cord blood flow after surgery runs in parallel with an acute activation of an immune response, however, the duration of response does differ between the early and late decompressed subjects. Prolonged immune response When surgery is performed early the acute activation of the immune system is resolved within the first weeks, whereas after delayed surgery there is a prolonged response. This response is characterized by increase cell signaling (more cytokines in the spinal cord), in the number of astrocytes (a cell type that supports and protects neurons), and in the number of peripheral monocytes (white blood cells). As expected, mice that received late decompression showed more complications and less recovery after surgery, potentially due to this ongoing unresolved activation of the immune response associated with a longer duration of symptoms. Early decompression resulted in neurological improvement in upper and lower limbs. Functional recovery of gait Gait impairment in one of the first symptoms in patients with DCM, so for this study, the assessment of gait was important to measure functional outcomes. Using the CatWalk XT method, swing speed and stride length, similar to what is affected in patients, were measured in all mice. In the first two weeks after surgery, this revealed no differences between the mice. At five weeks after surgical decompression, mice that received early decompression showed significant improvement, while the other did not benefit that much from the surgery. Vidal also investigated interlimb coordination and found pattern and speed to be visibly affected in all mice. After surgery, the early decompression cohort showed much more improvement in step patterns than the others. Novel therapeutic target This study underlines the importance of early diagnoses of DCM. The IRI and inflammation mechanism plays an important role in the poor functional outcomes of delayed surgery, and thus presents a novel therapeutic target to improve this. References - Fehlings, M.G.; Wilson, J.R.; Kopjar, B.; Yoon, S.T.; Arnold, P.M.; Massicotte, E.M.; Vaccaro, A.R.; Brodke, D.S.; Shaffrey, C.I.; Smith, J.S.; Woodard, E.J.; Banco, R.J.; Chapman, J.R.; Janssen, M.E.; Bono, C.M.; Sasso, R.C.; Dekutoski, M.B.; Gokaslan, Z.L. (2013). Efficacy and safety of surgical decompression in patients with cervical spondylotic myelopathy. The Journal of Bone and Joint Surgery. 95(18), 1651-1658. - Nouri, A.; Tetreault, L.; Singh, A.; Karadimas, S.K.; Fehlings, M.G. (2015). Degenerative Cervical Myelopathy: Epidemiology, Genetics, and Pathogenesis. Spine (Phila Pa 1976), 40(12), e675-693. - Karadimas, S.K.; Laliberte, A.M.; Tetreault, L.; Chung, Y.S.; Arnold, P.; Foltz, W.D.; Fehlings, M.G. (2015). Riluzole blocks perioperative ischemia-reperfusion injury and enhances postdecompression outcomes in cervical spondylotic myelopathy. Science Translational Medicine, 7(316), 316a194. - Vidal, P.M.; Karadimas, S.K.; Ulndreaj, A.; Laliberte, A.M.; Tetreault, L.; Forner, S.; Wang, J.; Foltz, W.D.; Fehlings, M.G. (2017). Delayed decompression exacerbates ischemia-reperfusion injury in cervical compressive myelopathy. JCI Insights, 2(11), e92512. Acknowledgements A big thanks to Pia Vidal for providing information about her research. Go check out Dr. Michael Fehlings' lab at drfehlings.ca and follow Dr. Fehlings on Twitter @DrFehlings Other research with CatWalk XT: RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## The impact of sounds on autistic children’s behaviors URL: https://noldus.com/blog/impact-sounds-autistic-childrens-behaviors Published: 2017-06-15 11:13:00 Description: Children with autism can have trouble dealing with external distractions. Researcher Shireen Kanakri conducted a study to observe the impact of the acoustic environment on restrictive and repetitive behaviors. How well can you concentrate on reading a paper while the radio is playing loudly? Or if something is making distracting sounds next to your working space? These can disturb your concentration. They affect you, it possibly irritate you for a minute or two, but eventually you are able to ignore them and continue your activity. Dealing with distractions can be hard Children with autism have trouble dealing with these external distractions, because they have different sensitivities to the environment than other individuals. They must expend more effort to process stimuli, such as sounds, colors, feelings, and odors. Controlling the noise, careful use of color, limiting details, and purposeful design are therefore important components in designing spaces for these children, particularly classrooms. These environmental concerns are increasingly considered in architectural and interior design work. Researcher Shireen Kanakri conducted a study to observe the impact of the acoustic environment on autistic children's behaviors. She specifically focused on repetitive speech and motor movement, while in a classroom setting. Children were observed in four different classrooms, each with a different decibel (dB) level in the room. Restrictive and repetitive behaviors The research looked specifically at "restrictive and repetitive behaviors" (RRBs). These behaviors are identified as behaviors that have no observable goal, but are repetitiously executed. They are often vocal or motor behaviors such as hand flapping, repeatedly uttering or echoing words or phrases, bizarre body movements, foot tapping, and head movements. Repetitive behaviors and routines can be a source of enjoyment for autistic people and a way of coping with everyday life. But they may also limit involvement in other activities, and cause distress or anxiety. Attention to the acoustical environment was expected to improve the well-being of children with autism through decreasing psychological and physiological distress, and enhancing the ability to concentrate. Capturing behaviors in the classroom Two schools for children with autism located in the southern United States agreed to participate in the study. Two classrooms were observed in each school. One classroom was located near the playground, and a heating, ventilation, and air-conditioning system (HVAC) turned on and off every ten minutes. This classroom was coded as "loud". The other classroom, coded as "quiet", was located further away from the playground and did not have an HVAC system. Video data was collected during a seven week period, for 42 children, 6-9 years old. Trained graduate students coded the RRBs and speech. The decibel levels and observations of repetitive motor movement and repetitive speech were then compared in The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial How to design a classroom for children with autism The results revealed that children in the loud classrooms showed higher numbers of repetitive behaviors and repetitive speech than did children in the quiet classrooms. The findings indicated that as dB levels increase, repetitive behaviors and repetitive speech increases. Furthermore, the repetitive speech behaviors influenced the repetitive behaviors as well. The more children used echolalia, the more they showed repetitive behaviors. The findings that repetitive behaviors are correlated with the acoustical condition of the environment should be considered in the design of classrooms for children with autism, for the benefit of user comfort and educational performance. Quieter classrooms decrease distress and increase positive behavior, which then enhances these children's ability to function effectively in the learning environment. References Kanakri, S. (2017). Acoustic design and repetitive speech and motor movement in children with autism. Environment and Ecology Research, 5 (1), 39-44. DOI: 10.13189/eer.2017.050105 --- ## Video tracking makes bird watching much easier URL: https://noldus.com/blog/video-tracking-bird-watching Published: 2017-06-01 15:05:00 Description: Everyone with children knows the phenomenon that what is good for a child is not always the best for a parent. The same counts for birds. Parent-offspring conflict Everyone with children knows the phenomenon that what is good for a child is not always the best for a parent. Although having children may be the best that can happen to someone, caring for a young child often conflicts with the parent's need for rest. The same counts for birds, the more effort parent birds put into feeding their chicks, the more chicks survive. However, this comes at a cost. The parents themselves spend energy and risk predation. On the other side, lowering the effort in feeding the chicks is bad for the chicks but good for the parents. Somewhere along that line there is an optimum in the amount of care at which the offspring over generations is maximal. Bird watching is tedious Inter- and intraspecific variation in parental care in birds is well studied in several bird species. It is relatively easy to determine the effort of parent birds to bring food into the nest. And determining the survival of offspring is also not too difficult. However, easy is definitely not the same as quick. Nesting observations are incredibly tedious and time consuming. Even if the nesting behavior is recorded on video, analyzing the behavior takes a lot of time. Can video tracking replace bird watching? For this reason, Dean Evans [2] and colleagues investigated whether nesting observations for Mountain Bluebirds (Sialia currucoides) could be automated using video tracking software. They first examined whether flight activity of free-living birds near their nests could automatically be analyzed using the video tracking software EthoVision XT. Then they compared these data with manual observations of food provisioning events. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Video tracking makes life easier and faster The authors were able to successfully analyze the bird flight behavior with EthoVision XT. The automatically obtained results matched those obtained by manual observers. The number of errors made with both methods was very low and did not differ between methods. But most importantly, the analysis time was reduced with up to 69 %. As an example, manual analysis of 1 hour video takes on average 52 minutes for an unexperienced manual observer. For an experienced observers, this time is lower, on average 26 minutes. However, analysis with EthoVision XT is even faster, 16 minutes per hour of video. Concluding In conclusion, video tracking is a very promising tool for research on parental care in birds. This will make it much easier for birdwatchers to further unravel evolutionary concepts in bird species. References - Parent-offspring conflict (Wikipedia) - Evans, D.R., McArthur, S.L., Bailey, J.M. et al. J Ornithol (2015) 156: 1125. doi:10.1007/s10336-015-1267-5 --- ## Measuring parent-infant behavior from another point of view URL: https://noldus.com/blog/measuring-parent-infant-behavior Published: 2017-05-23 13:58:00 Description: Parent-child interaction is an important focus of child development research. Lee’s research team compared recordings of play behavior from both a traditional third-person point of view, and through the babies' eyes. Quality of parent-child interaction is one of the major predictors of emotional and social development of children in the first two years of life. Since the consequences of maladaptive parental responsiveness can be so profound, parent-child interaction is an important focus of child development research. The gold standard for measuring mother-child interactions is to have a researcher observe or film an interaction in a clinical, research, or home setting, and film from the third-person point of view. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Download Research examples For example, the Opportunities to Understand Childhood Hurt (O.U.C.H.) Laboratory, run by Dr. Rebecca Pillai Riddell, focuses on understanding how caregivers and children interact within the context of pain. At the Institute of Psychology of the University Paris Descartes in France, the general objective of Emmanuel Devouche's research is to improve the knowledge about the exchanges of a baby within his or her social environment. With The Observer XT, researchers noted in detail behaviors such as: expressed vocalizations, gaze directions, time spent smiling, parent talking to the child, emotions demonstrated, and more. Through babies' eyes Another example comes from Lee's research team at the University of Bristol, United Kingdom. They recruited mothers with infants between 3 and 12 months and compared recordings of play behavior from both a traditional third-person point of view, and a first-person point of view. First person cameras (1st PC) are small portable cameras worn on headbands by the participant, facing outward to capture the viewpoint of the individual. In this study, both the mother and the child used such cameras simultaneously. Using these cameras offers several advantages: - It eliminates the need for a researcher to be present, reducing potential influences of the researcher on mother and infant behavior. - It enables the ability to record the viewpoints of each participant, so different perspectives are captured. - It reduces the burden of attending or hosting a research visit for the participants. So far, however, published studies have only analyzed and reported on the viewpoint of one half of the dyad; data from the combined footage, and any interplay between the two, has yet to be reported. FREE WHITE PAPER Tools for Infant Studies Download the free White paper to learn more about the software tools available for infant studies. - Capturing behaviors with video - Coding behaviors accurately - Unobtrusive emotion analysis Download How to avoid social desirable answers In this study, the researchers explored and evaluated the gains and limits of using 1st PCs. They expected that when the mothers and infants were left alone, it would be more likely that negative behaviors would occur, compared to when a researcher is present. A greater frequency of less socially desirable maternal behaviors was also predicted. By recording the same interactions with 3rd PCs as well, the researchers explored whether the recordings of the different cameras corresponded. High concordance would mean that the majority of the same information is picked up by both viewpoints, and interpreted the same way by coders. Low concordance, however, could indicate that one of the recording methods picks up unique information. Capture behavior on video The babies were placed on a play mat and mothers were asked to play with their baby as they would normally do. Mothers and infants were filmed by a researcher, and both wore 1st PCs. After instructions, the researchers left the 1st PCs with the mothers for an average of 1 week. The mothers were asked to record at least three 30-min sessions at home. The observations were coded with The Observer XT to categorize each maternal behavior. These categories included: comforting, engagement, encouragement, positive affect, monitoring, routine care, distracted, critical, mismatched affect, persistent ineffective, and intrusive. The infant's affect (happy, neutral, or distressed) was coded separately. The results of the study The 15 mother-infant dyads recorded 1-5 meal time or free play sessions. Analysis showed that the 1st PCs videos resulted in similar overall coding on a relatively simple mother-infant coding system to that recorded from the 3rd PC. This demonstrates that 1st PCs capture a situation reliably. Some elements, however, such as gaze direction or posture, were missed by the 1st PCs due to the camera position. As predicted, once the researcher was not present, the videos contained less sensitive maternal behavior, such as intrusive or distracted maternal behavior. The researchers found several advantages of using a 1st PC. They were better able to capture subtle facial expressions and vocalizations, since the camera is much closer to the face. The viewpoints offered by 1st PCs are unique and possibly more naturalistic, as the visual angle is that of the first person. Another advantage is that the cost associated with researcher's time can be reduced. See the world from another point of view Many evaluations of parenting interventions involve filming mothers during free-play sessions, in the presence of a researcher, while using a 3rd PC. However, there is a possibility that mothers 'perform' the behaviors desired by researchers, resulting in potential bias. Using 1st PCs, researchers can help reduce this bias through removing the researcher's physical presence, and increasing duration of recordings, which is key to an accurate evaluation. 1st PCs can benefit researchers interested in understanding aspects of the environment that infants and mothers focus on, particularly if the study involves facial expression analysis. Another possible application is facilitating video feedback interventions. For example, 1st PCs could be used to improve maternal sensitivity in adolescent mothers, to aid mothers with schizophrenia, and mothers with poor attachment styles. With this type of camera, researchers see the mother as her baby does: from the baby's point of view. FREE WHITE PAPER How to build an AV lab Do you want to learn more how to set up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download References Lee, R.; Skinner, A.; Bornstein M.H.; Radford, A.N.; Campbell, A.; Graham, K.; Pearson, R.M. (2017). Through babies' eyes: Practical and theoretical considerations of using wearable technology to measure parent-infant behaviour from the mothers' and infants' view points. Infant Behavior and Development, 47, 62-71. --- ## Ticking clocks – tides and activity peaks in American horseshoe crabs URL: https://noldus.com/blog/tides-american-horseshoe-crabs Published: 2017-05-18 11:12:00 Description: Recently, I came across an interesting paper in which American horseshoe crabs were video-tracked to investigate their internal clocks. Video tracking crustaceans In a previous blog post I wrote about the resemblance between crustaceans and vertebrates. In a setup that very much resembled the Elevated Plus Maze for rodents, crayfish behavior was analyzed with EthoVision XT video tracking software. Recently, I came across another interesting paper in which crustaceans were tracked with EthoVision XT. The authors studied the behavior of American horsehoe crabs. They were interested in the animals' internal clocks, which regulate the crabs' daily activity. Tides and activity American horseshoe crabs live in environments in which the water level varies due to tides. The crabs have synchronized their behavior with these tides. Their main activity takes place when the water level is high [1,2]. Tides and crab activity peaks vary Most coastal areas have two high tides a day. In such areas the crabs have two activity peaks per day. However, there are also areas where one of the two tides is much more pronounced than the other. This is for example the case for the Gulf of Florida. Crabs from this region have one main activity peak. There are also areas with small irregular tides, which are mostly driven by the weather. This is the case for the Indian River Lagoon in Florida. Crabs from this region have irregular activity patterns that follow the higher water levels. Investigating the cause of activity peaks Rebecca Anderson and colleagues [3] investigated whether the crab activity peaks are triggered by the environment, or are caused by an endogenous clock. They collected crabs from several sites, either with two high tides per day, one main tidal peak per day, or small irregular weather driven tides. They exposed the crabs to a series of different tidal regimes and measured the crab activity peaks. The authors used EthoVision XT video tracking software to automatically determine the crab behavior. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Plasticity depends on predictability The crabs from the region with two tides per day continued to show two activity peaks, independent of the tidal regime to which they were exposed. Likewise, the crabs from the region with one dominant tidal peak continued to show one daily activity peak during all tidal regimes. However, the crabs from the region with irregular weather driven tides were plastic in their activity. When they were exposed to two daily high tides, they had two activity peaks and when they were exposed to one daily high tide, they had one activity peak. Ticking clocks The authors conclude that the crabs from the regions with clear, predictable tides have an endogenous clock that regulates their activity. In contrast to this, the crabs from the region with unpredictable tides are able to adjust their activity peak to new tidal regimes. So all crabs have ticking clocks, but these are not set in the same way. The crabs from the regions with predictable tides have endogenous clocks. The crabs from the unpredictable region have clocks that are set with an external trigger, which is the current tidal regime. References - 1.Brockmann HJ, Johnson SL (2011) A long-term study of horseshoe crabs in Florida. Estuaries Coasts 34: 1049–1069. doi:10.1007/s12237-011-9419-1 - 2.Watson WH III, Chabot CC (2010) High resolution tracking of adult horseshoe crabs Limulus polyphemus in a New Hampshire estuary using fixed array ultrasonic telemetry. Curr Zool 56: 599–610 - 3.Anderson, R.L., Watson, W.H. & Chabot, C.C. Mar Biol (2017) 164: 63. doi:10.1007/s00227-017-3098-9 --- ## Flower preference in solitary bees URL: https://noldus.com/blog/flower-preference-solitary-bees Published: 2017-05-11 13:00:00 Description: Mason bees are fascinating and friendly creatures. Tibor Bukovinszky and his colleagues investigated how their foraging behavior affects their offspring. Mason bees (Osmia species) have long been rather unknown to the majority of people. But they are fascinating creatures and they are very friendly, although they can sting they will hardly ever do so. Mason bees? Unlike their well-known family members that produce honey, mason bees live a solitary life. The females lay their eggs in cavities in wood and in cane stems of, for example, thatched roofs. After depositing an egg, they build a little wall that separates the egg from the next one. This way a series of eggs, each in its own cell, is laid in the cavity. The first eggs that are deposited will become females and the last ones males, so that in early spring the males emerge first and fly impatiently nearby until their mating partners emerge [1]. Accommodating Mason bees In my garden, the little creatures colonized the holes of the counter set screws of my garden table. But also in other gardens they are becoming more apparent, because people have become aware that they exist. Nowadays, many people have placed wood blocks with drilled holes in their garden to accommodate mason bees. The primary school of my son even has built a big mason bee hotel and in early spring the area around it is buzzing with activity. Mason bees and flower preference Like honey bees, mason bees feed on pollen and nectar. The females deposit pollen and nectar in the cells with eggs, so that the larvae have food when they emerge from the eggs. Different species have preference for different flower species. Some have specialist preference for a plant or plant family, others are generalists [2]. Flower preference and offspring performance Tibor Bukovinszky, who regularly supplies the Noldus Behavioral Research Blog with beautiful pictures of insects (www.bugsinthepicture.com), is a scientist who is also fascinated by mason bees. Together with his colleagues, he investigated how the foraging behavior of the generalist mason bee Osmia bicornis affects the performance of the offspring [3]. They investigated the preference for three plant species from distinct plant families: borage (Boraginaceae), cornflower (Asteraceae) and rapeseed (Brassicaceae). The authors used Pocket Observer to record the bee behavior and The Observer XT to analyze it. Picture by Pam van Stratum (info@inbuzz.nl) Rapeseed is the best After careful observations, the researchers discovered that when the mason bees were only offered rapeseed, their offspring had the highest survival and body mass. Interestingly, this also led to the highest fraction of females in the offspring. The offspring did not do well at all on the other two plant species. But bees do not prefer rapeseed As rapeseed seemed so beneficial, it was surprising to find that when the bees could forage freely among the three plant species, they did not have a preference for rapeseed. However, there is an explanation for this. A generalist like Osmia bicornis lives in an environment that is unpredictable where plant species and thus flower resources will vary over time. What flowers do mason bees like? The authors hypothesize that it probably pays to collect pollen from a mixture of plants, even if a superior plant species is available. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Interested in Mason bees? Did this post raise your interest in mason bees? Have a look here how you can help them in your garden: Mason Bee Resource Guide References - 1.Mason bee - Wikipedia - 2.C. Cripps, R. W. Rust; Pollen Preferences of Seven Osmia Species (Hymenoptera: Megachilidae). Environ Entomol 1989; 18 (1): 133-138. https://doi.org/10.1093/ee/18.1.133 - 3.Tibor Bukovinszky, Ijsbrand Rikken, Sanne Evers, Felix L. Wäckers, Jacobus C. Biesmeijer, Herbert H.T. Prins, David Kleijn. Effects of pollen species composition on the foraging behaviour and offspring performance of the mason bee Osmia bicornis (L.), Basic and Applied Ecology 2017; 18: 21-30. https://doi.org/10.1016/j.baae.2016.11.001. --- ## Time is of the essence in fish studies URL: https://noldus.com/blog/time-essence-fish-studies Published: 2017-05-04 15:22:00 Description: You recently moved into your new house. How do you feel? How do you act in this new space? The answers may depend on how long you have lived there… You recently moved into your new house. How do you feel? How do you act in this new space? The answers may depend on how long you have lived there… At least, this is the conclusion reached by researchers from Griffith University's Australian Rivers Institute (ARI) in Southport Australia regarding fish behavioral (toxicology) studies. After a thorough literature review, they identified 165 toxicity studies that looked at fish swimming behavior, and found that 'timing' is not a standard thing when designing these type of experiments. Swimming behavior These researchers conducted their own experiment, studying the swimming behavior of mosquitofish over time. The reason is that, when studying the behavior of fish (and other aquatic species) in toxicology, it is very common to transfer animals to 'experimental arenas' for video recording – but there are no standard criteria for how to do this correctly. The researchers were interested to see if fish behavior changed over time, and if differences in acclimatization period would influence test results. After all, getting used to a new environment might drastically influence behavior. They were also curious to find how it would affect behavioral analysis if short versus long observation periods were used. The ultimate goal of exploring these questions was to try to improve the way behavioural tests are being applied in toxicology. Literature research To be able to compare their results with global research, these researchers also performed a literature review to compare their experimental findings with some of the most commonly used endpoints in behavioural toxicology studies. Specifically, they looked at basic swimming parameters, mating/courtship/aggression, anxiety, feeding/predation, avoidance/attraction, and learning/memory. They found that most study designs allowed less than one hour of acclimatization before testing, and most behavioral observations were also less than one hour. Interestingly, the actual durations varied greatly, with many studies only conducting behavioral observations for a couple of minutes. Video tracking In their own experiment, the researchers recorded fish for 8 hour sessions, beginning immediately after introduction to the arena. For this, an EthoVision XT set-up was used. With video tracking, the average and maximum swimming velocity and angular velocity were automatically measured. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Timing matters They found that the exploratory behavior of the fish changed significantly over the course of several hours. There was a drastic difference between the beginning of the recording and 3 to 4 hours into the test, characterized by an increased average velocity, and a decreased angular velocity. Their experiment showed not only that habituation time matters, but that the actual observation duration matters too; analyzing 5-minute timeframes (which is close to the current status quo in behavioral toxicology research) versus 2-hour timeframes yielded very different results in swimming behavior. Why is this important? So…what does this mean? How long should you acclimate, and then test, your fish? The answer of course depends on the question you are asking. If you want to know if a new environment scares them (anxiety in a novel tank), then behavioral assessments should be done prior to tank acclimation, because otherwise the new environment is not so unfamiliar anymore. But if that is not the question, you might want to wait several hours before doing any behavioral observation, because otherwise you are measuring the behavior of stressed fish that may not be a very good representation of fish in natural environments. Change of pace Behavioral changes in fish are often characterized by swimming velocity. But a new environment or a certain compounds are not the only possible reasons for these types of changes. For example, other studies show that hungry fish tend to swim faster as well (Hansen et al., 2015, Pang et al., 2010). In addition to timing, the duration of the observation also matters. This study shows that 2 hours of observation time, in contrast with 5 minutes, helped account for the population variance in average and angular velocity. According to the researchers, longer observational durations are critical to improve the repeatability of behavioral studies. And now? These researchers are hoping that these findings provoke thought and stimulate discussion. Because if timing is so important, it would only improve the quality of science if we pay more attention to it when designing experiments. Time is of the essence, but time is also money. Luckily, with EthoVision XT video tracking, the parameters is question are easily automatically monitored and analyzed, whether you are tracking for 5 minutes, or 8 hours! References - Melvin, S.D.; Petit, M.A.; Duvignacq, M.C.; Sumpter, J.P. (2017). Towards improved behavioural testing in aquatic toxicology: Acclimation and observation times are important factors when designing behavioural tests with fish. Chemosphere, 180, 430-436. - Hansen, M.J.; Schaerf, T.M., Ward, A.J.W. (2015). The effect of hunger on the exploratory behaviour of shoals of mosquitofish Gambusia holbrooki. Behaviour, 152(12-13), 1659-1677. - Pang, X.; Cao, Z.-D.; Peng, J.-L.; Fu, S.-J. (2010). The effects of feeding on the swimming performance and metabolic response of juvenile southern catfish, Silurus meridionalis, acclimated at different temperatures. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 155(2), 253-258. Image Credit: Hunter Desportes & etrusko25 --- ## Fetal electrocardiography URL: https://noldus.com/blog/fetal-electrocardiography Published: 2017-05-01 15:43:00 Description: The results of the fundamental research reported in Kim Verdurmen's thesis show that fetal ECG is a technique that is still developing but has shown to have multiple promising prospects, both during pregnancy and labour. In electrocardiography (ECG) the electrical activity of the heart is measured. In adults this is performed with self-adhesive electrodes on the chest. From research and adult cardiology we know that heart rate, heart rate variability and other parameters derived from the ECG can give us a lot of information. Fetal heart rate registration via the pregnant belly During pregnancy and labour, it is important to have information regarding the fetal condition. Besides the perception of fetal movements by the mother and ultrasonography, we can make a registration of the fetal heart rate via the pregnant belly. Since the fetus is safely protected within the womb, it is inaccessible for direct measurements during pregnancy. Nowadays, heart rate registration is performed as "cardiotocography"; registration of the heart rate is performed with a Doppler-ultrasound based system, detecting heartbeats as a reflection from moving parts of the fetal heart. Simultaneously, contractions of the womb are registered. However, cardiotocography is prone to signal loss, inadvertent maternal heart rate monitoring, signal artefacts and it does not provide the heart rate as a beat-to-beat signal. Multi-lead recordings increase the signal quality A fetal ECG can be obtained non-invasively with electrodes on the maternal abdomen. In our research, eight electrodes are used, of which six fetal ECG channel electrodes, one reference and one ground electrode. For each of the six fetal ECG electrodes, the voltage difference between a recording electrode and the reference electrode is calculated. By using multi-lead recordings we can combine different leads in order to increase the signal quality and to allow recombination of leads to reconstruct the standard Einthoven leads. The chances of recording good quality fetal ECG signals in at least one of the electrodes is maximised by spreading the electrodes over the womb. A portable prototype recording and storing device is used to process the recordings. Several filters are applied and the ECG of the mother is removed by weighted averaging of maternal ECG segments. By spatially combining the signals of the six fetal ECG channels, the signal-to-noise ratio is enhanced. Following detection of the R-peaks in the fetal ECG, a beat-to-beat fetal heart rate signal is created. Several applications of fetal ECG With this fetal ECG signal, we have more information regarding the fetal condition. During my PhD, our research group studied several applications of fetal ECG; - Detection of congenital heart diseases (CHD). Fetal ECG seems to be a promising diagnostic tool to complement in the screening for CHD. It reflects the intimate relation between the conduction system and the structural morphology of the heart, and it is particularly helpful in detecting the electrophysiological effects of cardiac anatomical defects (e.g. hypotrophy, hypertrophy and conduction interruption). - Study the effect on heart rate and heart rate variability of drugs that are administered during threatened preterm birth. Since heart rate variability is one of the most reliable indicators of fetal wellbeing, it is very important to know the exact influence on drugs that are frequently administered in obstetric care. In our research, we described the effects of two groups of drugs. - During labour, when the water has been broken and there are a few centimetres of dilation, the fetal ECG can be registered directly with an electrode attached to the fetal head. In order to detect oxygen shortage during delivery, "ST monitoring" can be applied. In ST monitoring, the fetal ECG is analysed to detect signs of fetal distress and the monitor can give an alarm. However, in clinical practice a lot of false alarms are encountered. Our research group developed a hypothesis describing how these false alarms might be caused, proved this hypothesis and proposed a solution for this problem. FREE WHITE PAPER Neuroscience research Download the free White Paper to learn more about neuroscience research and the tools available for your studies. - Neuroscience techniques - Research tools and methods - Data analysis approaches Get your copy instantly The results of the fundamental research reported in my thesis show that fetal ECG is a technique that is still developing but has shown to have multiple promising prospects, both during pregnancy and labour. By Drs. K.M.J. Verdurmen - PhD: "The prospects of fetal electrocardiography during pregnancy and labour" - Defence Technical University Eindhoven, 5th July, 16:00h. --- ## Social buffering in zebrafish URL: https://noldus.com/blog/social-buffering-zebrafish Published: 2017-04-25 15:35:00 Description: Shared sorrow is half a sorrow, according to the old proverb. New research indicates that social support is not only important for us humans, but also for zebrafish! Shared sorrow is half a sorrow, according to the old proverb. New research indicates that social support is not only important for us humans, but also for zebrafish! Better recovery with social support We cope better in a threatening or unpleasant situation if we are not alone, a phenomenon scientists call social buffering. We humans are not the only species that exhibit social buffering; several animals demonstrate this adaptation, which of course has some evolutionary advantages. The presence of conspecifics makes a threatening situation less dangerous, and thus the behavioral response to this situation is downregulated. Sounds pretty logical, right? Zebrafish feel supported Zebrafish are no exception. Faustino et al. recently found that zebrafish showed less fear in a threatening situation when they were not alone. In their behavioral paradigm, the researchers exposed fish to an alarm substance. Some fish were alone, while others were exposed to conspecific cues – meaning that they were swimming in shoal water (olfactory cue only), were in visual contact with their shoal in an adjacent tank (visual cue only), or both (olfactory + visual cues). Caught on camera With the use of two cameras, fish were video monitored from the top and from a side view. EthoVision XT was used to track the animals and extract xyz coordinates. From these tracks detailed analysis of freezing behavior and erratic movements was performed to assess fear behavior in the zebrafish. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial To validate correct behavioral analysis, results were compared to human observation using The Observer XT. Seeing is believing The results indicate that there was social buffering: zebrafish that were exposed to the aversive stimulus dealt with it better when they were not alone, as evidenced by less freezing behavior. The visual cue – being able to see their shoal – showed to be more effective than the olfactory cue (shoal water); size of shoal did not influence behavior. Gaining more insight Researchers also found that social buffering elicited a specific co-activation pattern in the brain, instead of specific activation of certain brain areas, similar to a pattern that is found in mammals. This study adds to the growing understanding of the evolution of social buffering in social animals and the underlying mechanisms. The authors also hint at further research with zebrafish larvae and optogenetic techniques to get more in-depth insight at the circuit level. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References Faustino, A.I.; Tacão-Monteiro, A.; Oliveira, R.F. (2017). Mechanisms of social buffering of fear in zebrafish. Scientific Reports, doi:10.1038/srep44329. --- ## Fish live longer and are more active after eating “young poo” URL: https://noldus.com/blog/fish-live-longer-with-young-poo Published: 2017-04-20 11:33:00 Description: Have you got the guts for it? Well, I hope you at least have the gut bacteria for it. Gut flora – they're not the most appetizing thing to talk about, but by now, we know those tiny organisms are important. They have a direct role in maintaining our immune systems, they influence and are affected by several diseases, and our individual microbiome composition changes throughout the lifespan. In several other species, it's no different. Mice, flies… and even the African turquoise killifish (Nothobranchius furzeri) that was recently investigated at the Max Planck Institute for Biology of Ageing (Germany). Killifish African turquoise killifish typically live for only a couple of months, which makes them a good subject to study changes in gut flora during the aging process. Additionally, research shows that their microbial composition resembles those of other vertebrate aging model organisms. Changes as fish get older This study compared the microbial composition of 6-week-old fish (the youngsters) to that of 16-week-old fish (the oldies), and found that microbial composition was significantly altered, with older fish having a great reduction in gut bacterial richness, and a higher prevalence of potentially pathogenic bacteria. Eating poo So here is where you'll need a strong stomach: to test the effect of microbial gut composition on the aging process, the researcher made middle-aged fish (9.5 weeks) eat young fish poo. Experimental setup First, the older fish were subjected to antibiotic treatment to clear out their gut flora as much as possible. This in itself had a positive effect on the life span of the fish. But fish that were exposed to the youngster's poo actually lived longer (they normally don't eat poo, but according to Valenzano in Nature News, they will probe and bite at the poo, and thus ingest the microbes). Like to move it Not only did ingesting flora from the young fish poo make the fish live longer, it also increased their exploratory behavior, which the researchers used as a measure for individual health. They were as active as 6-week-olds, and the effect was long lasting: the increased activity was still noticeable at 16 weeks of age. Measuring activity To measure fish activity, EthoVision XT video tracking system was used. During a 20-minute test, they were tracked using an overhead mounted camera, and total swimming distance was analyzed within the EthoVision XT software. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial References - Smith, P.; Willemsen, D.; Popkes, M.; Metge, F.; Gandiwa, E.; Reichard, M.; Valenzano, D.R. (2014). Regulation of life span by the gut microbiota in the short-lived African turquoise killifish. Nature, 544, doi:10.1038/nature.2017.21770 - 'Young poo' makes aged fish live longer – by Ewen Callaway for Nature.com nature.com/news/young-poo-makes-aged-fish-live-longer Image credits: German wikipedia user Ugau [GFDL (gnu.org/copyleft/fdl.html) or CC-BY-SA-3.0 (creativecommons.org/licenses/by-sa/3.0/)], via Wikimedia Commons --- ## Technical demonstration of FaceReader in Seville, Spain URL: https://noldus.com/blog/technical-demonstration-at-the-aps Published: 2017-04-14 16:08:00 Description: GO-LAB demonstrated FaceReader's amazing possibilities and efficient replacement of manual coding procedures. By Stefanie Duijndam MSc, GO-LAB, Department of Medical & Clinical Psychology. Tilburg University This year, the American Psychosomatic Society (APS) celebrates its 75th anniversary. The world's foremost leaders in psychosomatic science and related disciplines, including genetics, neuroscience, and cardiology, come to the annual APS meeting to share their most recent research findings. Although an American society by origin, every 5 years, the society's meeting moves to Europe, and this year the meeting was held in Sevilla, Spain. Mobilizing Technology to Advance Biobehavioral Science and Health This year's meeting theme was "Mobilizing Technology to Advance Biobehavioral Science and Health". More and more, research is dependent upon new technologies, but with these advancements in technology we may also lose sight of patient wishes and needs. It is therefore very important to discuss and show new developments in health and research technology, and at the same time be critical of these developments. Technical demonstration of FaceReader Besides very interesting symposia about newly created technology, such as apps to treat depression or anxiety, there was also a demonstration session, during which technology could be shown. Our research group from Tilburg University's Behavioral Physiology lab (GO-LAB) did not want to pass this opportunity by to show the world what we are using to collect our data. One of our most used software systems is Noldus' FaceReader, which we were invited to demonstrate during the meeting. Psychosomatics and Emotion The mission of APS is to advance and integrate the scientific study of biological, psychological, behavioral and social factors in health and disease. The expression of emotions plays a very significant part in this. Research has shown that emotions and physiology are closely linked. The way in which people regulate their emotions or cope with their emotions has a large influence on the autonomic nervous system. For example, when we suppress our emotions, an increase in heart rate may be observed. At GO-LAB, we are currently working on combining physiological data with both subjective and objective measurements of emotions or facial expressions. We wanted to show the APS community FaceReader's amazing possibilities and efficient replacement of manual coding procedures. The demonstration of FaceReader On Thursday March 17th, 2017 from 6-8pm the technology demonstration session took place, during which three research groups were presenting their technology. A large poster explaining the features of FaceReader was placed on the wall to attract the audience. Many researchers were interested in what we had to say, and in the two hours demonstration period, there was not a single moment that we were not talking. We demonstrated FaceReader by letting the researchers sit in front of the camera. We then started an experiment, in which the people had to mimic the emotions that were shown on the screen. Afterwards we would look at the video and show them how FaceReader measured their facial expressions. People were surprised to see how well this system works! By showing them the intensity of the emotion displayed, and also focusing on the facial action units, people were very enthusiastic and wanted to know more about the software. Among these researchers were also experienced manual FACS coders, who were enthusiastic about its efficiency and detail. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Collaborations Some researchers were so interested in the system that they wanted contact information to perhaps order the system themselves. There were even some amazing collaboration ideas. For example, online mental health care is a rapid growing field. Researchers wondered whether they could use video material during online sessions and then use these videos for facial expression recognition. It seemed that a lot of people were interested in whether they could use the system for clinical practice. Nowadays, FaceReader is used mostly for research purposes, but in our opinion it can most definitely be implemented in clinical practice as well. Conclusion We had a very successful and fun event at APS and we have definitely made people enthusiastic about the product. Hopefully we will see more and more (psychosomatic) publications in which the FaceReader is used. Our first publication on FaceReader is expected later this year. --- ## Robots in the operating room URL: https://noldus.com/blog/robots-operating-room Published: 2017-04-11 15:34:00 Description: Dr. Ahmad and his team analyzed surgical team movements during robot-assisted surgery to understand and categorize causes for interruptions. Recent developments in robot technology allows robots to handle more and more tasks that previously were only possible for humans. There are robots that are able to vacuum your house or mow the grass; there are self-driving vehicles, or even drones which sends packages through the air. Robots are all around us. Can a robot replace a surgeon? A number of surgeries that take place in an operating room (OR) now utilize robots; these include prostatectomies, cardiac valve repair, and gynecologic surgical procedures. Robots have been used in these procedures to improve upon conventional laparoscopy, for quite some time now. Due to robotic use, these types of surgeries can be done with greater precision, miniaturization, and smaller incisions, which leads to decreased blood loss, less pain, quicker healing time, and shorter hospital stays. A robot is accurate, stable, and tireless. It is able to make specific movements which are stressful or even impossible for a surgeon. However, opinions about the use of robot-assisted surgery (RAS) are diverse. There are obvious benefits, but disadvantages as well, such as expense and the large amount of time that must be invested to teach the staff (particularly surgeons) to work with the robot. The influence of the da Vinci™ in the OR RAS has changed the traditional OR layout, with equipment occupying more space without a proportionate increase in room size. The additional required hardware, and large size of the equipment, may hinder the flow within the OR. The da Vinci robot system consists of a surgeon's console that is typically in the operating room (with the patient), as well as a patient-side cart with four interactive robotic arms controlled from the console. If the da Vinci robot obstructs movement, or causes additional unnecessary movements, operating room teams may have altered team interactions, increased distraction, tension, and frustration, and impaired team performance, all of which could eventually compromise patient safety. Interruptions to surgical workflow Dr. Ahmad and his team analyzed surgical team movements during RAS in order to understand and categorize procedural interruptions and to identify modifiable factors that can be eliminated to enhance surgical performance. Ten robot-assisted radical prostatectomies (removal of the prostate gland) were analyzed retrospectively. Three cameras were used to maximize the coverage of the OR environment, and eight audio tracks were recorded for each team member. Tracking, observing and coding movements The OR was divided in eight zones, and all movements were tracked and described in terms of start and end zones, duration, personnel, and purpose. Movements were further classified into avoidable (can be eliminated/improved) and unavoidable (necessary to complete the procedure). Recordings from the da Vinci™ surgical system, lapel microphones, and video cameras were synchronized. The videos were viewed by a trained medical student and physician assistant student, supervised by a Urology fellow and a human factors engineering expert. The purpose of each walking motion was established based on visual and audio cues from the recordings. The Observer XT was used to code and analyze the collected data. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Analyzing the movements A total of 2,896 ambulatory movements were observed. The circulating nurse contributed to the majority of traffic, followed by the lead surgeon. Overall, procedure-related ambulatory movements (such as receiving/delivering biopsies, paperwork, scrubbing in, and checking on patient progress) were the most common, followed by miscellaneous (e.g. shift changes/breaks, washing hands), and technology-related movements (for example equipment handling, and use of computers/monitors). Further analysis showed that 50% of these walking movements were avoidable, since they had no positive impact on the surgical procedure, or could have been avoided with a refined OR layout. Ambulatory movements are considered potential distractions and/or obstacles to surgical flow, which makes the large amount of avoidable ambulatory movements in this study alarming for patient safety. Improvements needed to guarantee patient safety Repositioning equipment with optimization of supply areas, along with set-up of needed items before surgery, should be a priority to eliminate the potential flow disruptions that could occur during surgery. Room layout improvements should target unobstructed views, more efficient locations of computers and monitors, and better access to supplies and equipment, thereby reducing unnecessary movements in the operating room. Furthermore, simulation training may in evolve in the future to support the surgical staff in optimizing and avoiding unnecessary movements during robot-assisted surgery. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - Ahmad, N.; Hussein A.A.; Cavuto, L.; Sharif, M.; Allers, J.C.; Hinata, N.; Ahmad, B.; Kozlowski, J.D.; Hashmi, Z.; Bisantz, A. & Guru, K.A. (2016). Ambulatory movements, team dynamics and interactions during robot-assisted surgery. BJU International, 118, 132-139. - Allers, J.C.; Hussein, A.A.; Ahmad, N.; Cavuto, L.; Wing, J.F.; Hayes, R.M.; Hinata, N.; Bisantz, A.M. & Guru, K.A. (2016). Evaluation and impact of workflow interruptions during robot-assisted surgery. Urology, 92, 33-37. --- ## Two ways to learn more about medical simulation and debriefing URL: https://noldus.com/blog/medical-simulation-and-debriefing Published: 2017-04-03 16:03:00 Description: There are two ways to get ahead and stay ahead in healthcare education. One - learn from the best and - two - stay on top of your game! Training is crucial in almost every profession, but in healthcare education it is indispensable. Using simulation-based training began in flight simulators; new pilots cannot fly a real craft without successfully completing training sessions in a flight simulator. In medical education, simulation-based training has also taken off. Why is medical simulation so important? It ensures that doctors and nurses around the world make the right decision when confronted with an emergency, for example. By simulating emergency situations, the medical team is better able to cope with the stress in the real life scenario. After the training, a debriefing takes place in order to immediately learn from the scenario. Were procedures followed? Who took the lead? What verbal cues were given? FREE DEMO Try Viso yourself! Request a free demonstration to find out why Viso is the right tool for your training facility! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback and debriefing Free Demo In order to set up simulation, the necessary tools must come together. What tools are available for simulation and training? How do these tools allow an effective debrief? What tools will help nursing students learn skills fast, while keeping quality high? There are two ways to get ahead and stay ahead in healthcare education. 1. Learn from the best One option is to sit at your desk or on your couch and watch training videos. That's what many of us do! The Royal College of Physicians and Surgeons of Canada created such a video course: the Simulation in Health Care Video Series. Dr. Michelle Chiu explains here that it is an important step to prep the debriefing. How? First, designate a lead debriefer and a second debriefer. This second person can handle the video and audio equipment and also assist when there are unexpected developments in the scenario. As Dr. Chiu explains, one requirement is a good speaker set in the debrief room, as students can then better hear the combination of feedback on posture (from video) and positive verbal cues from the primary debriefer. Good and thorough preparation is also required, as this prevents too many people from talking at the same time. Think about the seating arrangement in the debriefing room. Where is the screen? Does everyone have a clear view of the video? You want to think a little bit about how you sit in the debrief session. Everyone must be able to see the recorded scenario, and ideally you will have a balanced discussion. If possible, try to place extraverts next to introverted colleagues, and also split up the debrief team to avoid a competitive or 'us vs. them' atmosphere. By watching these videos, you can learn the foundational principles for simulation-based education, assessment, and research from renowned simulation experts. 2. Stay on top of your game Get to know what information is available, including visiting events or watching webinars. The International Meeting on Simulation in Healthcare, IMSH, is the most important healthcare simulation conference of the year. In 2017, over 2600 medical professionals attended to learn all about medical simulation research and the latest tools. At IMSH 2017 there were many interesting sessions about communication in healthcare, debriefing, and training. This big event also hosts a great exhibit where medical professionals can taste, smell, and feel all the latest innovations. Noldus highlighted our Viso software to about 100 professionals; this software solution is ideal for A/V recording in multiple rooms for simulation and training in medical simulation research. Next year's IMSH will take place in Los Angeles - come visit us there! --- ## Improving social communication skills in children with ASD URL: https://noldus.com/blog/social-communication-children-asd Published: 2017-04-02 11:48:00 Description: Many children with ASD suffer from deficits in social communication and interaction, especially with peers. They participate in fewer social interactions than typically developing children. An important annual moment is World Autism Awareness Day. It is organized to raise awareness on this developmental disorder and all its associated difficulties, and especially the opportunities out there for people with Autism Spectrum Disorder (ASD). Since the event’s inception in 2008, autism awareness and research around the world has increased as a result. Reciprocal communication in children with ASD Researchers Qualls and Corbett of the Vanderbilt University in Nashville, TN, USA, conducted a study to examine social communication in children with ASD [1]. They used the social communication scale of the gold-standard diagnostic measure ADOS (Autism Diagnostic Observation Schedule) to predict reciprocal communication in children with ASD. The ADOS is a semi-structured observation. The examiner provokes social, communicative, stereotyped, and play behavior to detect behavior that might indicate autism. Depending on the selected module, this can vary from pretend play with dolls and play peekaboo with a young child to making a puzzle with abstract figures and having a discussion about emotions with an adult. Struggling in participating Characteristics for ASD are deficits in social communication and interaction, especially with peers, as well as restricted interests and repetitive behaviors. Due to these deficits, many children with ASD participate in fewer social interactions than typically developing (TD) children. They struggle more with participating when they try to interact, and seem to be less aware of their social difficulties. These challenges often lead to difficulty forming friendships. “It's as if everybody is playing some complicated game and I am the only one who hasn't been told the rules.” [2] Assessing skills and deficits as shown in daily life The diagnosis of ASD is based solely on observable traits. To effectively and accurately indicate a diagnosis, it is necessary that subjects demonstrate the same skills and deficits during the assessment as they show in daily life. The ADOS is a good tool for this. However, observing interactions in natural environments, such as during informal play with peers, seems to be best. Play is extremely important, since it allows children to develop new skills through trial and error. That’s why Qualls and Corbett used the Peer Interaction Paradigm (PIP) in their study as well. PIP allowed them to observe social exchanges between children with and without ASD in a naturalistic playground setting. Measuring peer interaction During Qualls and Corbett’s study, thirty children with ASD (8 – 12 years old) made two visits, one for an assessment in which the ADOS and other neuropsychological measures were administrated, and the other consisting of the Peer Interaction Paradigm (PIP). With remotely controlled cameras and microphones concealed in a waist pack, the researchers made audio and video recordings of the 20-min sessions. The researchers monitored the interactions from the lab inside the building, which allowed the children to play more naturally. Each interaction involved three children: two typically developed children, with one being the same age and gender as the participant, and a child with ASD. The sessions consisted of periods of independent free play and invited play. The parents filled in two questionnaires (Social Communication Questionnaire (SCQ) and the Social Responsiveness Scale (SRS)) about the child’s current and past behavior, the child’s ability to repay a favor, gift, or invitation, and the child’s social communication. These tools allowed for better coding of human behavior. Coding reciprocal verbal exchange and self-play The researchers used the variables verbal bout (reciprocal verbal exchange between two or more children), and self-play (independent play with a toy or object alone but in presence of others) to determine social communication and interaction. They used The Observer XT to complete the analysis of the interaction observation data and conduct reliability analysis. With this software tool, behaviors of multiple subjects can be coded simultaneously with temporal accuracy down to the hundredth of a second. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Naturalistic video observations capture children as they really are This study is the first to compare scores of social communication of the ADOS to peer communication in a structured, natural setting. The results indicate that these scores were predictive of reciprocal social communication in a natural playground setting for children with ASD. This positive outcome allows the clinician to make appropriate recommendations for social skills training. After all, good social skills can improve and maintain relationships, as well as help to make friends. References - 1.Qualls, L.R. & Corbett, B.A. (2017). Examining the relationship between social communication on the ADOS and real-world reciprocal social communication in children with ASD. Research in Autism Spectrum Disorders, 33, 1-9. - 2.Sainsbury, C. (2009). Martian in the Playground: Understanding the schoolchild with Asperger's Syndrome. --- ## Three examples of nurse-patient interaction research URL: https://noldus.com/blog/examples-nurse-patient-interaction-research Published: 2017-03-21 09:40:00 Description: The use of video technology in nurse-patient interaction research offers important advantages to scientists in unraveling complex behavior patterns. Learn more! Behavioral observation has become a fundamental component of medical practice and a primary source of clinical research data. The use of video technology in nurse-patient interaction research offers important advantages to scientists in unraveling complex behavior patterns and finding relationships between behaviors, nutrition, effectiveness of interventions, and more. As Kim Kopenhaver Haidet explains: "Video recordings of behavioral responses are preferable as they afford the rater with the ability to freeze frame and replay data for review and coding of behavior, thus, enhancing reliability". Read three interesting studies in which nurse-patient interaction was recorded on video. 1) Nutrition in nursing homes Proper eating behavior can greatly affect patient health. A healthy diet is particularly important for nursing home residents. In a blog post, Jacqueline Martinali wrote about mealtime difficulties in nursing homes. Reducing mealtime difficulties may result in better eating, which in turn could lead to better nutrition and healthier patients. Researcher Andrea Gilmore-Bykovskyi observed the interaction between residents and their caregivers during breakfast or lunchtime (with an average of two video observations per resident). FREE DEMO Try Viso yourself! Request a free demonstration to find out why Viso is the right tool for your training facility! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback and debriefing Free Demo A good research method for this target group is video observations. They allow the researcher to note behavior in detail, and review the videos as needed, including from multiple angles. Using video, no behaviors are overlooked by the researcher, as both video and audio signals can be visualized together and can be repeatedly analyzed to capture every desired behavior in great detail. Viso and Media Recorder are tools that allow for video recording in one or multiple rooms. Learn more about the study of Andrea Gilmore-Bykovskyi by reading the full blog post. 2) Adapting the message in nurse-patient consultations Communicating at the proper level is important, but to effectively do so, the professional needs to know the communication level of the patient. Is a patient more likely to receive, understand, and process certain messages at the beginning, or at the end of an intervention program? To find out how this communication process works, Janneke Noordman and colleagues analyzed a large number of practicing nurse-patient consultations. Noordman and colleagues were particularly interested in if and how nurses adapt their motivational interviewing techniques to the patient's readiness to change. To assess nurse behavior, they positioned a camera in the consultation room which enabled them to unobtrusively record each interaction. Read the blog post to find out what kind of behaviors Noordman et al. looked for when analyzing the video material. 3) Implementing Tailored Activity Programs in a hospital Researchers would like to find a way to increase positive behaviors of patients with dementia. In one study, Laura Gitlin and colleagues studied the feasibility of implementing a tailored activity program in hospitals. They observed both the reactions of the staff and the patients to the activity program. Patients were given three activity "prescriptions" and a schedule for when these activities were to be performed. These activities varied depending on the level of cognitive functioning for the patient. The first video recordings were of the patients within three days of admission prior to the occupational therapist's activity prescriptions as a baseline. Then patients were also observed in up to six of the activity sessions. Results were encouraging, with observed increases in pleasure and decreases in anxiety and anger compared to the baseline results. Many of the families, contacted a month after discharge, were highly satisfied with the program: over 50% of the total activities prescribed were continued in the home. Looking at the hospital staff, while they were hesitant at first to engage in the program, by the end of the study they had embraced it as beneficial to the patients. Learn more by reading the full blog post! Subscribe to our newsletter Do you find this blog interesting to read? Do you want to learn more about behavioral research tools and methods? Get regular updates on behavioral research methods, exciting research, video technology, conferences, and more. Click here to subscribe! --- ## Do emotions affect preferences to opera music? URL: https://noldus.com/blog/do-emotions-affect-preferences-opera-music Published: 2017-03-16 14:10:00 Description: Many researchers are interested in the relationship between facial expressions and music preference. This is the first study that uses FaceReader to investigate this. What does music trigger? What emotions arise as people listen to music or watch a music video? Happiness, sadness, disgust or appreciation perhaps? It depends whether people like or dislike the music, or what they prefer. Personally, hard rock music is a genre I strongly dislike. On the other hand, I can become very happy by hearing a certain pop song. Opera is a kind of music that you may or may not appreciate. However, the range of preferences is wide within this genre as well. For instance, there's Western European opera and Chinese opera. As you can imagine, they differ tremendously. Xi-Qu (戏曲) is an important musical genre in China Xi-Qu refers to the Chinese music genre formed in the twelfth century. This Chinese opera integrates Chinese literature, drama, singing, instrumental music, acting skills, dance, visual arts, and acrobatics. It is one of the oldest dramatic art forms in the world. Accompanied by traditional musical instruments, actors present unique melodies - which may sound strange to foreigners - as well as dialogues which are beautifully written and of high literary value. Different styles of facial make-up and marvelous acrobatics are the most remarkable features. Comparison to Western European opera In comparison, Western European opera is a musical art form developed in Western Europe in the sixteenth to the twentieth century, and remains a major genre of classical music. Singing plays a dominant role in portraying the actions and emotions of the characters. In traditional opera, singers do two types of singing: recitative, a speech-inflected style, and arias, a more melodic style. Besides music, Western European opera includes drama, poetry, and visual arts. Music preferences The purpose of the study Hong Chen conducted at the University of South Florida was to explore the preference of Chinese undergraduate music majors for Chinese Xi-Qu and Western opera. She used audiovisual examples for this. She also studied the reasons for preference, the influence of familiarity on preference, and the relationship between preference ratings and emotions detected by FaceReader. Many researchers are interested in the relationship between facial expressions and music preference. This is the first study that uses FaceReader for music preference and affective response. Like or dislike Using a sample of 27 Chinese undergraduate music majors (13 vocalists and 14 instrumentalists), the study intended to provide preliminary information about Xi-Qu preference and reasons for liking or disliking Xi-Qu. This knowledge would help music teachers select appropriate teaching materials at college level, since Xi-Qu and opera have become compulsory teaching content in the Chinese music education. In addition, it would enhance students' experience with Xi-Qu in class. Rigoletto versus Zhongkui Four Chinese Xi-Qu and four Western opera audiovisual examples were selected as stimuli. The examples covered several singing forms (aria, duet, chorus), and originated from different geographic locations (South and North of China for Xi-Qu examples, and Italy, French, and the United States for the Western opera examples). Multiple measures and instruments were utilized to explore the Chinese music majors' music preferences, such as a questionnaire and interviews. FaceReader was used to collect participants' facial expressions while they were watching the stimuli, and was helpful because of its unobtrusive way of measuring. Items on the questionnaire were related to participants' level of preference for the stimuli, the most liked and disliked elements of the stimuli, familiarity with the given stimuli, participants' demographic information, and participants' music training background. During the interviews, the responses to the questionnaires were further deepened. The results of the study According to the findings, the participants generally preferred the Western opera to Chinese Xi-Qu. The outcomes of the most liked and disliked elements showed that singing and acting were always among the top three most liked elements across the four operatic examples, and the top three disliked elements in the operatic examples were all related to visual information. As for the Xi-Qu examples, singing and facial make-up were always among the top three disliked elements. Formal training was identified as a major way of gaining familiarity with the Western singing skills and had positive influence on preference for the operatic examples. Watching television together with (grand)parents during childhood and participation into community activities, such as weddings, parties, and the Spring Festival (Chinese new year) were major ways of gaining familiarity with Xi-Qu and had various effect on preference for Xi-Qu. Participants who did not have extensive experience with Xi-Qu found it hard to evaluate Xi-Qu examples. Emotional responses to the opera music The results relating to facial expressions showed that "neutral" was the dominant emotional state across the eight examples. The participants' self-reported emotional responses confirmed that they didn't have emotional responses to the examples or only responded just a little bit. "Angry" was the only emotion that correlated to the preference ratings. However, no participant ever reported that they felt "angry" when they were watching any of the examples. It is possible that music could provoke more emotions than the seven emotions plus neutral in FaceReader. "Frustrated" could probably better represent negative emotion instead of "angry" in this study. "Happy" was not a reliable indicator of preference in this study, although it could predict the most preferred piece with happy expressed emotions. The findings suggest that formal training has a strong influence on the development and shaping of the participants' taste and attitudes toward Western vocal works and Chinese Xi-Qu. The findings seemed to support the literature that preference for music could be increased by actual teaching. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download References Chen, H. (2015). Preference of Chinese Undergraduate Music Majors for Chinese Xi-Qu and Western Opera. Graduate Theses and Dissertations, University of South Florida. --- ## Consumer behavior: do we enjoy the buffet to its fullest potential? URL: https://noldus.com/blog/consumer-behavior Published: 2017-03-13 11:37:00 Description: In a buffet restaurant, do you also want to try another dish? Just because it's available? Read this blog post about how choice influences eating behavior. There are parts of the world where people eat primarily for pleasure, and less so to fulfil nutritional needs. In my eyes, that is a sign of prosperity and wealth. In these areas, there is more than enough to eat, and a wealth of different foods to choose from. But in these same parts of the world people are overweight, more and more diabetic, and suffering from cardiovascular diseases. So what is wealth, in terms of food? To address this, let's zoom in on a consumer study that focuses on recognizing signs of fullness. Sensory-specific satiety – eat more or eat less? Have you ever been to an all-you-can-eat buffet restaurant? People (yes, me too) are more likely to eat a larger amount of food at a buffet restaurant. Why? Researchers explain that this occurs in part due to the large variety of foods and flavors available, which continually renew a sense of appetite in the individual. As a food is consumed, its perceived pleasantness declines compared to that of other foods. This is what is called 'sensory-specific satiety', and is a likely contributor to the termination of eating due to decreased pleasantness of a single food. In a buffet setting, intake may increase because people tend to eat another dish because it is available and offers a different sensory experience. Autonomic nervous system responses and facial expressions Wei He and other researchers from Wageningen University and the University of Geneva measured sensory-specific satiety using autonomic nervous system (ANS) responses and facial expressions. The goal was to assess novel behavioral research techniques to evaluate their value for consumer behavior studies. They set up three tasting conditions based on all same foods, similar uneaten foods, and different uneaten foods, and compared the food consumed to satiety. The test with four test foods A total of 24 female participants were recruited and four test foods (2 sweet, 2 savory) were selected. The test foods could be ingested through a straw without chewing. This was chosen to minimize motor activity that may produce artefacts in ANS responses and facial expressions. During the test, participants were asked to face a camera while tasting and consuming the foods to ensure optimal analysis by the FaceReader software. After every three sips, participants provided their own ratings for pleasantness of the test food and indicated whether they wanted to continue eating, until they felt comfortably satiated. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Biometrics and behavior During the session, participants' physiological responses and facial expressions were continuously measured. The researchers used BioLab (version 3.0 from MindWare Technologies Ltd.) and FaceReader (version 5 from Noldus Information Technology bv). The close up images of the participant's face were analyzed off line in FaceReader with results then imported into The Observer XT, which enabled synchronization of MindWare and FaceReader data. If you'd like to learn more about tools for behavioral and biometric research, go to the consumer research toolkit page. Synchronization is key in understanding behavior because you're searching for patterns in behavior, emotions, and physiological signals. When your different data streams are accurately synchronized as they were in this study, it tells you the complete story. Integration of data is something that Noldus specializes in. The moment that test foods reached the lip of participants was marked manually as tasting moment 0 in the video recordings. Video data was combined with a trigger in The Observer XT software each time a test food was tasted. Synchronization of data signals was automatic in the case of the skin conductance level, heart rate and skin temperature, and video signals. Consumption results in increased heart rate The researchers observed a time window of 20 seconds with the tasting moment in the middle. As The Observer XT software positions all data on one time line, the researchers had an accurate overview of all their integrated data. They found out that in general, consumption of the test meals resulted in increased heart rate, reduced skin conductance and skin temperature, as well as intensified anger and disgusted facial expressions. Results suggested that satiety results in a shift in emotions associated with shifts in the foods' pleasantness as well as the arousal triggered by the food. However, the researchers did note that this study tested in a lab situation with people drinking from a straw. They would like to test in a more natural eating situation. They believe these methods are a good way to start explorations in the field of emotions and eating behavior, given the novel combination of methods and study design. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Reference He, W.; Boesveldt, S.; Delplanque, S.; de Graaf, C.; de Wijk, R. (2017). Sensory-specific satiety: Added insights from autonomic nervous system responses and facial expressions. Physiology & Behavior, 170, 12-18. --- ## Isolated and stressed zebrafish as a model for major depression URL: https://noldus.com/blog/isolated-stressed-zebrafish-model-depression Published: 2017-03-09 10:28:00 Description: Depression: a fifth (!) of us cope with it, making it the most prevalent psychiatric disorder. Prof. Gerlai recently investigated the interaction between mild stress and developmental isolation in zebrafish models. Depression: a fifth (!) of us cope with it, making it the most prevalent psychiatric disorder. It comes as no surprise that researchers try to wrap their minds around it, not to mention the interest gained from the pharmaceutical industry. How to model depression Depression is not easy to model in animals, as we cannot really determine if a rat has low self-esteem or if a zebrafish is suicidal. But that doesn't mean researchers haven't found other behaviors to characterize depression-like symptoms in animals, and several – sometimes very successful – models have been developed to study this disease. How does one get depressed? "Life stress" is a well-known factor in the development of depression (Hill et al., 2012). In animal research, this is mimicked by "Unpredictable Chronic Mild Stress" (UCMS). Another factor is early life adversity, such as abuse or neglect – in animal research, they use "developmental social isolation". Better characterization While zebrafish proved to be a suitable model for both paradigms (UCMS and social isolation), the interaction between the two is not clear. The lab of Prof. Robert Gerlai recently investigated this interaction and aimed for a better characterization of both behavioral and neurochemical changes in zebrafish. (Fulcher et al., 2017) Rearing and stressors To characterize these changes, the researchers exposed both socially reared fish and fish reared in isolation to UCMS. The stressors included partial exposures to air due to lowered water levels, tank changes, net chasing, complete elevation from the tanks, water replacement, and individual restrainment. In addition, two groups of fish (one reared socially and one reared in isolation) were not exposed to UCMS. This way, the researchers could determine the sole effect of early life adversity. Novel tank testing For behavioral testing the fish were placed in a novel tank, which in itself is a known stressor. Behavior was automatically measured for 3 minutes using video tracking (EthoVision XT). Turn angle, distance traveled, freezing, and distance to the bottom were used as a measure of anxiety-like behaviors. Shoaling to video screens To measure shoaling (social) behavior, the fish were exposed to video images of 5 conspecifics projected on two screens on either side of the tank after being in the tank for 10 minutes. The distance to the screen, also measured with video tracking, was also used to measure shoaling. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Stress increases anxiety Being exposed to UCMS increased anxiety-like behavior in the zebrafish. Developmental isolation alone did not have this effect. It also did not decrease the distance of the fish to the screens while they were exposed to conspecific images, suggesting they did not decrease their shoaling behavior. It did have other effects on their behavior, though. For example, they traveled a larger distance. UCMS also decreased dopamine and serotonin levels in the fish, but only if they were reared in isolation. Different effects Both the social isolation during development and the exposure to mild chronic stressors have their behavioral effects. While the latter seems to increase anxiety in the fish, the first mainly affects motor responses. Weight gain and neurochemical changes show an effect of the exposure to UCMS, but only in fish reared in isolation. A combination for the best model? This study shows that to model depression in research, a combination of developmental isolation and exposure to mild stressors seems useful. References Fulcher, N.; Tran, S.; Shams, S.; Chatterjee, D.; Gerlai, R. (2017). Neurochemical and behavioral responses to unpredictable chronic mild stress following developmental isolation: the zebrafish as a model for major depression. Zebrafish, 14(1), 23-34. --- ## Dynamic winners and sluggish losers URL: https://noldus.com/blog/dynamic-winners-and-sluggish-losers Published: 2017-03-03 11:27:00 Description: We all know the phenomenon: some have it all. Look around a classroom and you see immediately who gets all the attention and who doesn’t, who are “winners”, and who are “losers”. Are we born this way, or do we learn it? Born this way? We all know the phenomenon: some have it all. Look around a classroom and you see immediately who gets all the attention and who doesn't, who are "winners", and who are "losers". Are we born this way, or do we learn it? Winning and losing in crickets Winners and losers do not only occur amongst humans, but are also apparent in animals. In crickets, for example, males fight with each other and research shows that winners of a fight remain winners, and losers stay losers [1]. Jacqueline Rose and colleagues [2] wanted to know whether this is a matter of experience, or are male crickets born as winners or losers? Selecting winners and losers Based on two observed fights with other males, the authors selected individual cricket males. Those males that won both fights were classified as winners, while males that lost both fights were classified as losers. There were few males that won only once. Analyzing cricket behavior with videotracking The authors assessed locomotor behavior of the winners and losers in an arena both before and after the two fights took place. The arena bordered a compartment that contained four other male crickets. The male in the arena could see and smell these other crickets, but not directly interact with them. Locomotor behavior of the individual crickets in the arena was analyzed with the video tracking software EthoVision XT. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Winners are dynamic, losers are sluggish Prior to the fights, males that would turn out to be winners started walking earlier and walked more than the males that would later become losers. Additionally, the winners to be had a preference for the area close to the compartment with the other males, while the losers to be avoided that zone. This difference in activity between winners and losers became even more evident after the two fights. Winners and losers are born this way From these results, the authors conclude that male crickets are most likely born as either a "dynamic winner" or a "sluggish loser". Fighting with conspecific males makes this difference even larger. The authors describe that such a correlation between locomotion and winning is also apparent in other insect species and in mammals as well. Perhaps, that is why we experience that some have it all; winners may be visibly more active than losers. References - 1. Hsu, Y., Ryan, L., & Wolf, L. L. (2006). Modulation of aggressive behaviour by fighting experience: Mechanisms and contest outcomes. Biological Review, 81, 33e74. http://dx.doi.org/10.1017/S146479310500686X. - 2. Rose, Jacqueline, et al. (2017). Born to win or bred to lose: aggressive and submissive behavioural profiles in crickets. Animal Behaviour, 123, 441-450. http://dx.doi.org/10.1016/j.anbehav.2016.11.021 --- ## Effectiveness of video feedback in education URL: https://noldus.com/blog/effectiveness-video-feedback-education Published: 2017-03-01 12:59:00 Description: Did you know that video feedback in education is efficient? This and 5 more reasons why video debriefing in education is effective. Discover the transformative impact of video feedback in education. Explore how the use of video and audio recordings has become an essential tool, benefiting both educators and students. Learn why this dynamic approach to feedback is revolutionizing the educational landscape. Unlocking the power of video feedback in education: 6 compelling reasons Video feedback in education is increasingly used in education, and continues to prove its effectiveness for both educators and students. By using video and audio recordings in education, students and educators can receive, and benefit from, direct feedback. Let us share 6 reasons why this is beneficial for both teachers and students. 1) Did you know that… Many students experience stress when they have to participate in video feedback sessions, but that support and reassurance helps them overcome this stress? Two Norwegian researchers, Nilsen and Baerheim, found that some students experienced emotional distress before the start of the course. Their study shows the importance of reassurance and support in the process, and demonstrates the importance of carefully considering the design and execution of such educational programs. 2) Studies have proven that team training in health care improves teamwork processes and can positively impact patient outcomes? Multi professional teams from a large obstetric collaborative network in the area of the Máxima Medical Center Veldhoven, The Netherlands, received training in teamwork skills. This was accomplished by using the principles of Crew Resource Management (CRM) and Noldus' Viso video recording and debriefing technology. Viso video debriefing system In the morning, all residents received lectures on normal labor and delivery physiology, and on possible emergency obstetric situations. In the afternoon, the residents were divided into two groups. The first group participated in the scenario, while the second group observed the first group from another room using the Viso video debriefing system. The latter group debriefed the former group on medical skills, communication, teamwork and leadership, under the supervision of a communication trainer and a gynecologist. Next, they switched roles and repeated the scenarios. AV feedback system and educational training The residents were very enthusiastic about this form of educational training. They felt more equipped to deal with obstetric emergency situations in which they are responsible. The residents reported the use of the AV feedback system as adding great value to the training. Noldus' technology system is of added value for providing feedback, as it makes the debriefing more effective. 3) Gender influences students' general communication skills? Tee Pey Chiau and colleagues from the Universiti Kebangsaan Malaysia investigated video recording feedback in communication and counseling among pharmacy students. Their results clearly show that female students showed significant improvement in general communication after intervention in comparison to the male students. Since the female students showed more engagement (positive talk, partnership-building, question-asking, and information-giving) compared to the male students, you could say they were better trained for the job. In counseling, knowing the mechanics of counselling is insufficient for being an effective counselor. Personal awareness is critical for knowing when and how to use counseling skills. In software such as Viso, researchers can simply add subjects, making it easy to find gender differences. 4) The same Malaysian research group found that both verbal and video feedback had significant effect on students' counselling performance? The benefits of both types of feedback were further supported by the comments from the students. Areas mainly affected were non-verbal communication and the importance of facial expressions, body posture, eye contact, and voice tone. They refer to a Turkish study (see point 5) which shows that video feedback is superior to only verbal feedback. 5) Researchers from the Dokuz Eylul University, one of the biggest universities in Turkey, conclude that verbal feedback alone is less effective compared to feedback based on video-recorded interviews? Nilgun Ozcakar's study aimed to investigate whether the use of video recordings is superior to verbal feedback alone in the teaching of clinical skills and the role of student self-assessment on history taking skills and communication skills. Their sessions showed that the overall scores for the group having feedback both verbal and videotaped were higher than the scores of the group having only verbal feedback. 6) In emergency care training situations, using video recordings when giving feedback is a good way for students to develop skills and to understand their own actions? Together with colleagues from the Faculty of Health and Occupational Studies, University of Gävle, Swedish researcher Anita Nyström designed a study in which 44 undergraduate nursing students participated. She found out that video recordings may cause nervousness at first (and we're back at number 1 with the Norwegian research team). However, seeing these same video recordings promotes dialogue and acknowledgement, and it also promotes increased self-knowledge and professional growth. Viso video recording software facilitates sessions in which students can really see what happened and learn from their experiences. The teacher can give feedback using the presenter view in the software. Nyström reports that all of the students felt that the dialogue with and responses from the teacher in connection with visualized feedback were beneficial: "Watching the video recordings allowed the students to see themselves clearly; they saw what they had done and what they had failed to do, which gave them the opportunity to prepare for their future professional role" explains Nyström in her article. Noldus developed Viso to facilitate video recordings in educational contexts. This software allows for video recording, easy annotation, and debriefing in an easy to use system. FREE DEMO VISO Capture skills training sessions Request a free demonstration to find out why AV recording tool Viso is the right tool for your educational institution! - Easy-to-use solution - Train and educate, enhance teamwork - Immediate playback of recordings Get your Free demo References - Nilsen, S.; Baerheim, A. (2005). Feedback on video recorded consultations in medical teaching: why students loathe and love it – a focus-group based qualitative study. BMC Medical Education, 5 (28). - Chiau, T.P.; Ali, A.M.; Bakry, M.M.; Azmi, N.; Paraidathatu, T. (2016). Video Recording Feedback in Communication and Counselling Among Pharmacy Students. Is it Better than Verbal Feedback? Indian Journal of Pharmaceutical Education and Research, 50 (2). - Nyström, A., Pålsson, Y., Hofsten, A., Häggström, E. (2014). Nursing students' experiences of being video-recorded during examination in a fictive emergency care situation. International Journal of Nursing Practice, 20 (5), 540-548. - Ozcakar N, Mevsim V, Guldal D, Gunvar T, Yildirim E, Sisli Z, et al. (2009). Is the use of videotape recording superior to verbal feedback alone in the teaching of clinical skills? BMC Public Health, 9 (1). - Maxima Medical Center --- ## Spatial and odor memory impaired mice – new model for Alzheimer’s URL: https://noldus.com/blog/new-mice-model-sporadic-alzheimers Published: 2017-02-27 12:14:00 Description: Plaques and tangles… those of you even remotely familiar with Alzheimer’s disease (AD) will immediately recognize these hallmarks. But they are linked to familial AD, while sporadic AD is far more common. Plaques and tangles… those of you even remotely familiar with Alzheimer's disease (AD) will immediately recognize these hallmarks. Many rodent models, focusing on plaques and tangles, have been developed to explore the cause and possible treatments of AD, and much progress has been made. Sporadic Alzheimer's Here's the thing: these hallmarks, with more or less clearly genetic causes, are linked to familial AD. Familial AD is an early-onset form of AD that actually is far less common than sporadic AD. Sporadic AD (sAD) is typically late-onset, meaning that most people get it when they are over 70 years old. The typical genetics associated with familiar AD are not risk factors for sAD per se; environmental factors play an even bigger role. While sAD is far more common, the lack of suitable rodent models makes it a much less investigated subject. A new model A while back, I wrote about olfactory habituation and how Justus V. Verhagen and his colleagues took a new approach to this test. In a recent study, they looked at olfactory memory in the context of sAD, hoping to find a suitable new model. Click here for a free download of a white paper on this olfactory memory test, courtesy of Verhagen and Coronas-Samano. In sAD, episodic memory is one of the first things to decline. Episodic memory is a dominant symptom often used clinically to diagnose the disease. Olfactory deficits may arise even prior to this, a fact that opens up opportunities for future early detection of sAD. Oxidative stress Instead of focusing on plaques and tangles, this study looks at the so called mitochondrial cascade hypothesis, which states that as humans age, they can experience problems on a cellular level that result in the increase of ROS – reactive oxygen species and oxidative stress. Fus1 knockouts Fus1 is a tumor suppression protein connected to the production of ROS. According to this hypothesis, aging can cause an increase in ROS, in turn leading to a decrease in Fus1. This then causes even more production of ROS, leading to chronic oxidative stress and symptoms of sAD. This study proposed using mice lacking Fus1 (Fus1 KO mice) as a new model for sAD. Phenotyping Fus1 KO mice were tested for their compatibility with sAD symptomology in a battery of behavioral and video tracking tests. The females were tested at a young age, and results were compared to those of wild type mice. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Olfactory memory Fus1 KO mice have good odor sensitivity – they can smell just fine as the habituation/cross-habituation test showed. However, memories of odor proved to be slightly problematic for these mice, as they showed mild impairments both in short term and long term memory tests. This was confirmed in a cookie test. While the Fus1 KO mice had no problem finding the cookie in the bedding, they made no progress in locating it over the next few days. In comparison, wild types were able to locate the cookie more quickly every day. Spatial memory In addition to odor memory, spatial memory was impaired in the knockouts as well, as demonstrated using the Morris water maze test. Depression and anxiety A sucrose preference test, in which mice are given the choice between normal water and sugar water, indicated that the Fus1 KO mice did not show anhedonia. They were not depressed, nor did they show abnormal anxiety or locomotion in the open field test and light-dark box. Interestingly, a fear-motivated avoidance (passive avoidance) test showed that the knockout mice might even be less anxious than wild types, but no differences in associative memory were found. Circadian rhythm The sleep/awake cycle of the knockouts showed disturbances, and measures deviated from normal both during the light and dark phases. They generally slept more than wild types. New insights In addition to these behavioral tests, a number of molecular tests showed that this mouse model can be used to investigate early olfactory and spatial memory deficits in relation to sporadic Alzheimer's disease, providing a useful alternative to classical models that are more specific to familial Alzheimer's. References - Coronas-Samano, G.; Baker, K.L.; Tan, W.T.J.; Ivanova, A.V.; Verhagen, J.V. (2016). Fus1 KO mouse as a model of oxidative stress-mediated sporadic Alzheimer's disease: circadian disruption and long-term spatial and olfactory memory impairments. Frontiers in Aging Neuroscience, 8, 268. - EthoVision XT video tracking for behavioral testing. --- ## To be ravenous or to be social URL: https://noldus.com/blog/be-ravenous-or-be-social Published: 2017-02-15 16:10:00 Description: Prosocial behavior, a voluntary behavior to benefit another, is an interesting concept from an evolutionary point of view. At first sight it may seem logical to be social. To voluntarily benefit another Prosocial behavior, a voluntary behavior to benefit another, is an interesting concept from an evolutionary point of view. At first sight it may seem logical to be social, because everyone in the group benefits from it. But evolutionarily that does not hold up, because to propagate one's own genes, cheating and being selfish pays. Therefore, many believe that prosocial behavior only exists because it is rewarded with social status, reputation, company, and receiving social behavior from others in return. Prosocial behavior in animals In animals, prosocial behavior is well studied in various monkey and bird species. However, it is difficult to truly study whether giving a reward to a conspecific is really without benefit for the supplier. And in studies in which it was carefully ruled out that a reward to a conspecific was also rewarding to the supplier, the experiments often gave contradictory results. Investigating prosocial behavior in ravens Triggered by these earlier studies and the evolutionary theories surrounding them, Megan Lambert and colleagues studied whether ravens showed prosocial behavior towards a conspecific bird. In addition to this, they investigated whether prosocial behavior was affected by affiliation between the birds and whether the behavior of the conspecific bird, like standing in view, vocalizing and displaying feathers, mattered. The authors used The Observer XT to quantify the bird behavior. The set-up In an ingenious set-up, the birds could choose to move one of two drawers by pulling a rope attached to it. By pulling the drawer on one side, food was delivered to a conspecific bird in an adjacent compartment. This was visible to the test bird. Pulling the drawer on the other side resulted in food delivery to an empty compartment. The birds had been trained extensively prior to the task, to rule out that no prosocial behavior was found because the ravens did not understand the task. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Ravens are not prosocial The ravens did not display any prosocial behavior: they pulled both drawers equally often. The results did not change when the adjacent bird was a relative and the behavior of the conspecific bird also did not matter. In fact, when the test bird did not receive any food reward itself, almost all birds stopped pulling the drawers completely. To raven So are ravens more selfish then social? Ravens will only carry out a task when they receive a reward for themselves. As concluded by the authors, this type of selfish behavior may have given the bird species their somewhat unfriendly name. References - Prosocial behavior - Wikipedia - Lambert, Megan L., et al (2017). "An 'unkindness' of ravens? Measuring prosocial preferences in Corvus corax." Animal Behaviour, 123, 383-393. doi:10.1016/j.anbehav.2016.11.018 --- ## Helping children cope with social anxiety URL: https://noldus.com/blog/helping-children-cope-social-anxiety Published: 2017-02-09 15:44:00 Description: Researchers Colonnesi et al. investigated whether social anxiety in 4 year-olds is related to the level of Theory of Mind, and expressing shyness. Now and then, we all feel afraid to some extent. For example, imagine when thunder nearby strikes hard, or when you're in a dark, small room and you don't know how to get out, or when you think you've gotten lost.  Last summer, my children and I were in a climbing park. It was supposed to be fun and my children enjoyed themselves a lot, but I discovered that it was quite scary to be so high off of the ground, forced to make steps that seemed too big, dangling around, brrrr…. I experienced a true sense of fear while I was there. This kind of fear is healthy. It makes sure that you avoid danger. However, fear shouldn't affect your daily functioning. For example, when fear influences school performance or family life, there may be a case of a social anxiety disorder. Social anxiety symptoms Anxiety disorders are the most common form of psychopathology in children and adolescents, and often do not disappear spontaneously. Moreover, anxiety disorders can lead to all sorts of other problems such as school dropout, depression, alcohol abuse and family problems. These consequences are reason enough to ensure that these symptoms are detected and, if necessary, treated in an early stage. Researchers Colonnesi et al. of the University of Amsterdam investigated whether social anxiety in 4 year-olds is related to a lower level of theory of mind, a lower tendency to express shyness in a positive way, or a higher tendency to express shyness in a negative way. Developing a Theory of Mind (ToM) Young children often have difficulty predicting and explaining the behavior of others, and the difference between reality and fiction. They are primarily engaged with their own needs, without even being aware that they have these needs, or that others have needs too. As they grow older, children learn that other individuals also have certain feelings. They attain an explicit Theory of Mind (ToM). A normal ToM development seems to be necessary for healthy socio-emotional development. Individuals with ToM deficits have a lesser understanding of what they can expect from other people, and they are less able to deal with complex social situations in an appropriate way. Expressing shyness Shyness is typically manifested by specific shy facial expressions and physiological reactions such as blushing or by disorganized behavior. When experiencing shyness, people are often concerned or worried about being socially exposed to others' evaluations but, still wish to remain engaged in the situation and make a good impression. Positive expressions of shyness are behavioral manifestations of children's capacity to regulate their ambivalent feelings and fear during social situations. They are expressed by positive facial expressions (e.g. a smile). In contrast, negative expressions of shyness are more often an avoidant-ambivalent type of shyness. They include combinations of gaze and head aversions during negative facial expressions (e.g. a frown). According to Colonnesi and colleagues, the negative expressions of shyness are possibly associated to social inhibition, early experience of social failure, rejection by others, and social anxiety. Coding video observations Using a sample of 110 children that were 4.5 years of age, researchers aimed to investigate how ToM and shyness were associated with the level of social anxiety reported by parents in both positive and negative ways. Furthermore, they explored the interplay between children's ToM and children's positive and negative expressions of shyness on their level of social anxiety. The children visited the lab twice, once with their mother and once with their father. During the first visit, a shortened version of the TOM-test-r was conducted. The children were requested to give answers to questions such as 'Who in this picture is angry?', or 'Can people see the bicycle you are dreaming about?' in reaction to 14 short illustrated stories. These interviews were video-taped and coded. FREE WHITE PAPERS How to build a research lab Do you want to learn more how to set up a research lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download 3 free 'how to' guides! Submit to download Sing a song During the second visit, performance and self-watching tasks were conducted in order to determine whether the children expressed positive or negative shyness. The children were asked to sing a song they liked, on a podium, with a spotlight and a microphone, in front of a small audience in a costume they had chosen themselves. During the self-watching task, children watched their recorded performance on a television screen. The Observer XT was used to code the video observations. Social anxiety was measured with the social anxiety subscale of the Dutch version of the revised Preschool Anxiety Scale (PAS-R) completed by both the parents. The answers of this study The researchers reported many outcomes. For instance, they found that early social anxiety symptoms are associated with a low basic level of ToM, a low use of positive expressions of shyness, and a high use of negative expressions of shyness during socially stressful situations such as public performance. Their results suggest that a good ToM development in early childhood can facilitate social understanding by promoting positive social experiences, self-confidence, and peer relations. It is important that children develop adaptive coping strategies in order to cope with social anxiety. In conclusion, at the age of 4.5 the interplay between ToM and expressions of shyness can be used to detect children's level of social anxiety and then prevent the onset of social anxiety disorders. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your free trial Interested in human behavior research? Read more on 'How to study human behavior'! Reference Colonnesi, C., Nikolić, M., Vente, W. de & Bögels, S.M. (2016). Social Anxiety Symptoms in Young Children: Investigating the Interplay of Theory of Mind and Expressions of Shyness. Journal of Abnormal Child Psychology, DOI 10.1007/s10802-016-206-0 --- ## Free-choice digital interactive enrichment and human-animal interaction URL: https://noldus.com/blog/digital-interactive-enrichment-apes Published: 2017-02-06 14:50:00 Description: Great apes have fast reflex, gazes, and movements: The Observer XT’s features allow frame by frame coding and accurate data integration. Read this guest blog post about an Australian National University PhD research at the Seoul Zoo by Nicky Kim-McCormack and colleagues. Measuring changes in captive great ape welfare and conservation attitudes As orangutan (Pongo spp.) and chimpanzee (Pan troglodytes) populations decrease, captive individuals play an important role in species’ conservation management making information about their cognitive stimuli and enrichment essential. Essential study on digital cognitive stimuli offering freedom of choice There is a growing empirical support demonstrating improved welfare in captive animals when they can exert control over their environment (1). Research shows that great apes can successfully interact with digital media devices (2&3) and there can be behavioral changes when presented with digital enrichments (4). However, to date, there have been no studies that look at the effect of free-choice using digital interactive mediums, and the implementation’s impact on human visitors’ attitudes towards the animals and their conservation. What is best for the great apes’ well-being? Assumptions are often made that natural enrichments produce better welfare.5 and strive to offer activities that mimic wild behaviors. Such anthropomorphic and broad-stroke views should be avoided when considering new enrichment strategies (4&6). If the animal’s well-being is considered paramount, enrichment strategies should be based on scientific study outcomes rather than from potential anthropomorphic bias. In light of this, the study investigates whether the provision of freedom of choice and control, can improve welfare using a novel digital touch-glass technology. In addition, we will look at the effects of Human-Animal interaction (HAI) from animal welfare and visitor perspectives, by looking at whether a direct interactivity/experience through digital technology can lead to greater conversation awareness and changes in attitudes. Accurate data integration To measure the changes in welfare of Seoul Zoo’s six orangutans and four chimpanzees using the digital enrichment, we used Noldus’ Media Recorder via their IP cameras to capture the study sessions. The videos were directly linked to The Observer XT along with the interactive touch points custom imported directly into the program and thereby negating the need for extremely time-consuming manual handling of data. 792 videos of pre, post and study session observations will be coded in the coming months using The Observer XT, where six controlled phases will be analysed against baseline observations to determine any changes in the animals’ behaviour and stress levels. Preliminary results Great apes’ (especially chimpanzees) have fast reflex, gazes, and movements, and The Observer XT’s features not only allow frame by frame coding as needed, it also handles external data logs with some customisations. Although the video coding is at its infancy and progress is slow, preliminary qualitative results show that: - Orangutans and chimpanzees can interact with digital touch-glass devices. - Younger animals appeared to have higher engagement with the digital enrichment activities. - As the phases progressed and visitors observed increasing level of choices for the animals and experienced HAI, positive changes in attitude increased as the negative responses decreased. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial References - 1.Cocks, L. (2007) Orangutan species survival plan: Husbandry Manual, C. S. Sodaro ed., Chicago Zoological Gardens. - 2.Perdue, B.M.; Clay, A.W.; Gaalema, D.E.; Maple, T.L.; Stoinski, T.S. (2012). Technology at the zoo: The influence of a touchscreen computer on orangutans and zoo visitors. Zoo Biology, 31, 27-39. - 3.Boostrom, H (2013). Problem-solving with Orangutans (Pongo pygmaeus and Pongo abelii) and Chimpanzees (Pan troglodytes): Using the iPad to provide novel enrichment opportunities, Department of Wildlife and Fisheries Science of Texas A&M University, Unpublished Master’s thesis. - 4.Woolverton, W.L.; Ator, N.A., Beardsley, P.M.; Carroll, M.E. (1989). Effects of environmental conditions on the psychological wellbeing of primates: A review of the literature. Life Sciences, 44, 901-917, Pergamon Press - 5.Wells, D.L. (2009). Sensory stimulation as environmental enrichment for captive animals: A review. Applied Animal Behaviour Science, 118, 1-11. - 6.Kim-McCormack, N.E.; Smith, C.L.; Behie, A. M. (2016). Is interactive technology a relevant and effective enrichment for captive great apes? Applied Animal Behavioural Science, 185, 1-8. Authors Nicky N.E. Kim-McCormack1, Carolynn L. Smith2, Pauline Ding1, Jae C. Choe3, Colin P. Groves1 & Alison M. Behie1  1) School of Arch. & Anth., The Australian National University, ACT, Australia 2) Dept. of Biology, Macquarie University, NSW, Australia  3) National Institute of Ecology, South Korea --- ## How obese mice get moving URL: https://noldus.com/blog/how-obese-mice-get-moving Published: 2017-01-26 14:39:00 Description: By a showing of hands: how many of you started this New Year with the resolution to get moving? Burn off those extra holiday calories, or finally really get in shape? By a showing of hands: how many of you started this New Year with the resolution to get moving? Burn off those extra holiday calories, or finally really get in shape? Because, let's be honest, it's all about willpower right? "Just do it!" It might not be that straight-forward… We all know getting active is good for our health; it is scientific fact that obesity and physical inactivity are linked. But what comes first? Gaining weight because you don't move enough, or decreasing activity because it's just harder to get around with the physical burden of that extra weight? The science behind the weight A couple of weeks ago, I spoke to Alexxai Kravitz at Neuroscience 2016 in San Diego. His lab at the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK, National Institutes of Health, US) has the goal of understanding the underlying physical behaviors related to obesity. Their work was recently published in Cell Metabolism and received quite a bit of attention in the press. It's in your head The Kravitz lab asked the question: "…dopamine is critical for movement, and obesity is associated with a lack of movement. Can problems with dopamine signaling alone explain the inactivity?" They actually found that inactivity, at least in part, was caused by problems in the dopamine system in the brain, specifically, activity of the dopamine 2 (D2) receptor. Getting fat One group of mice was fed a normal diet, while a second identical group was given high-fat food. Within a week, a noticeable difference in body weight appeared between the two groups. By week four, the heavier mice were also significantly slower. However, here is the interesting part: the overweight mice got slower before they gained significant weight. What's going on? Analysis of brain chemistry showed that the high-fat diet caused a deficit in activity at the D2 receptors in the striatum, which in turn caused the decrease in activity. How to get lazy So if this is true, lean mice with a defect in the D2 receptors should show the same decrease in activity, right? Indeed, they did. When researchers later restored D2 receptor activity in the heavy mice, they showed an increase in locomotor activity, despite being overweight. Investigating behavior Activity was quantified in this study using automated methods, and the researchers measured activity and speed via the video tracking system EthoVision XT in open field environments (Noldus PhenoTyper chambers). EthoVision XT was also used to automatically measure grooming and rearing (via the Mouse Behavior Recognition Module). The measurements showed that the overweight mice got 'lazy' by week four. Decreased movement was characterized by spending less time moving, and slower movement overall. Although they seemed to rear less, this was not a significant difference compared to the lean mice; time spent grooming also did not differ. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial The bigger picture Obesity is a leading cause of preventable death. In 2014, over 600 million people were classified as obese (World Health Organization). The health issues are obvious, as are the need for interventions. Getting active is a vital part of getting healthier, but as this study suggests, it is often not simply a case of willpower or mindset. Insights from this study, and further research Kravitz and his team are planning to do, offers great steps towards a better understanding into the pathway underlying obesity. Read more - Friend, D.M.; Devarakonda, K.; O'Neal, T.J.; Skirzewski, M.; Papazoglou, I.; Kaplan, A.R.; Liow, J.-S.; Guo, J.; Rane, S.G.; Rubinstein, M.; Alvarez, V.A.; Hall, K.D.; Kravitz, A.V. (2016). Basal ganglia dysfunction contributes to physical inactivity in obesity. Cell Metabolism, 25, 1-10. - More about EthoVision XT: www.noldus.com/ethovision - More about PhenoTyper: www.noldus.com/phenotyper - More about automatic behavior recognition: www.noldus.com/behavior-recognition --- ## Attention! Drive safely URL: https://noldus.com/blog/attention-drive-safely Published: 2017-01-24 14:29:00 Description: In a recent study with bicyclists, researchers at VTI, Sweden, observed cyclist behavior using eye tracking technology, video recordings, and behavioral coding. This blog post is a guest post by Katja Kircher from VTI, the Swedish National Road and Transport Research Institute. In a recent study with bicyclists, researchers at VTI observed cyclist behavior using eye tracking technology, video recordings, and behavioral coding. All data combined enabled them to assess whether the cyclists met the demands in specific situations. Did receiving a text message influence the cyclist's behavior, particularly in high-attention demanding circumstances? Read the blog post to learn more! How much attention do we need to pay while in traffic? Almost all of us drive, cycle, walk, or move around in traffic every now and then. We go to work, to school, on holidays, to the dentist, or to pick up our children. Some of us use the transport system professionally, often to transport goods or people. While we travel, we still want to, or must, deal with other things in addition to driving/cycling/walking. A taxi driver has to book the next passenger, a cyclist might be called by a friend, a parent would like to soothe the crying baby, and a bus driver may have to make an announcement to the passengers. All those road users, and most likely you as well, divide their attention every now and then, focusing both on traffic and on an additional task. While this has long been known, recently it became a hot topic of discussion with the advent of mobile phones. Is it acceptable or not to use your phone while driving? Is it safer to call instead of text? Is it ok to soothe your crying baby? Or to change track on the music player? If we do, what happens with our attention? For years, researchers focused on "driver distraction", investigating how long a driver can look away from traffic safely, and how adding a phone or some other task changes driving behavior, with the goal to determine the influence on crash risk. However, it turned out that this is a very difficult question to answer, and there is still no consensus on what driver distraction really is. Minimum Required Attention Our research group explored a new approach to the topic, which we call MiRA, or "Minimum Required Attention". We assume that each traffic situation makes certain demands on the road user, be it a driver, cyclist, or pedestrian. Depending on the situation, these demands can be unchallenging; for example, when going along at a leisurely pace on an empty, straight country road. They can also be very complex, such as when navigating a large intersection in an unfamiliar city. As a road user, you have some ability to influence the demands by changing your speed, choosing to overtake or not, or even by choosing not to drive at all under certain circumstances. Meet the demands We claim that you as a road user should be regarded as attentive when you meet the demands of the situation, and as inattentive when you don't. On the lonely country road, you may meet the demands easily, and still have a lot of spare capacity available, which you may devote to other tasks or to daydreaming – in any case you would be considered attentive. In the unfamiliar city junction, you may be able to just meet the demands, and every additional activity would render you distracted. What are the specific situational demands? With this theory as a starting point, we shift the focus of research to the question of whether road users attend to the situational demands, and if they adjust their behavior to accommodate additional tasks while still meeting the demands. As this approach is quite new, we are still defining the situational demands, and how we can assess whether they actually were met by the road users. Video, eye tracking and more to study bicyclist behavior In a recent study with 41 bicyclists, we asked them to cycle on a route through the city center, and we sent them a few text messages on the way. They were asked to respond to these messages just as they would have normally, so they had the option to ignore them, answer later, stop for answering, or continue cycling while answering. Two small video cameras were installed on the cyclist's bike and on the bike of an experimenter following the cyclist, and we tracked the cyclist's gaze direction with the help of an SMI eye tracker. These four videos were combined in The Observer XT so that we could later assess whether the cyclists met the demands in specific situations. Did receiving a text message influence the cyclist's behavior, particularly in high-attention demanding circumstances? Simple vs complex situation We are still in the process of analyzing the data of where attention was directed, but we know already that the cyclists chose to read and reply to the messages to a much greater extent while cycling when the context was simple (on a street without car traffic), than in more complex situations. In those contexts, cyclists either delayed their interaction with the telephone or made a dedicated stop. This is likely connected to the fact that the cyclists could sample enough information in the simple environment, even while texting at the same time, but this was not possible in the more complex scenarios. And more… Further studies on the same topic, which we are currently conducting and have planned, include attention distribution when driving a rather highly automated car on the motorway while conducting an additional task; attention distribution of cyclists and car drivers in the same environment; and self-paced visual occlusion while driving in different simulated scenarios. We hope to be able to operationalize our theory enough that it will be a tool that can be used when assessing the suitability of infotainment systems for road users, to improve education in automated driving, and for other applications connected to road user attention. Contact details vti, Sweden Katja Kircher, PhD, Research Leader e-mail: katja.kircher@vti.se FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Interested in human behavior research? Read more on 'How to study human behavior'! --- ## How optogenetics is used to study the stress response in zebrafish larvae URL: https://noldus.com/blog/optogenetics-stress-response-zebrafish-larvae Published: 2017-01-23 11:00:00 Description: Stress might seem like a bad word, but it does have its perks. A recent study by Rodrigo J. De Marco uncovered the role of the pituitary in zebrafish larvae behavior after the onset of stress. Optogenetics - making neurons sensitive to activation by light - is a great tool in the unraveling of the function of the brain in biological processes and behavior. A recent study by Rodrigo J. De Marco and his colleagues used optogenetic techniques to uncover the role of the pituitary in zebrafish larvae behavior after the onset of stress. Stress Nowadays, "stress" is often seen as a bad word, but of course the stress response does have its perks. Evolutionary, it is critical to adaptation and survival. In humans, the HPA axis (hypothalamus-pituitary gland-adrenal gland) and a selection of neurotransmitters and hormones comprise the stress system, much of which has already been extensively studied. However, the stress response is a very fast phenomenon, making it difficult to study certain aspects in detail, such as the role of the pituitary in the regulation of behavior right after the onset of stress. This is what Rodrigo De Marco and his colleagues want to unravel. Tightly organized The stress response is a very tightly organized system. In this study, the researchers focused on the pituitary, specifically, cells in this gland called corticotrophs. Corticotrophs release several active molecules, including ACTH (adrenocorticotropic hormone), which is rapidly followed by the release of cortisol in the adrenal cortex. In hormonal terms, this cycle defines the stress response. The perfect model De Marco argues that zebrafish are excellent model subjects in this case: "This is what all this is about: exploiting a unique opportunity (larvae are small, transparent and have a fully functional stress axis) to - 'non-invasively'- ask important questions. For example, can pituitary products exert fast effects on behavior?" In addition, their HPI (hypothalamus-pituitary gland-interrenal gland) axis is homologous to the human HPA axis. Let there be light To investigate the role of corticotrophs, researchers genetically manipulated zebrafish in this study to make their corticotrophs sensitive to optogenetic activation by blue light. These fish were called the bPAC+ larvae. Light is a known stressor for zebrafish, so to control for the optogenetic activation by blue light, researchers also used yellow light. In addition to the bPAC+ larvae, siblings without the sensitivity to optogenetic activation (bPAC- larvae) were also tested. All larvae showed a stress in response to the yellow light. The bPAC+ larvae showed an amplified stress-response when exposed to the blue light, compared to their bPAC- siblings, and compared to the yellow light circumstances. Assessing behavior and controlling the light To assess zebrafish behavior, video recordings were made with EthoVision XT video tracking software. The same computer controlled light and other stimuli via TTL control (USB-IO box). De Marco says: "At the center of all this was a complex customized setup with EthoVision XT playing a highly significant role." FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Light and stress The results showed that exposing briefly dark-adapted larvae to a pulse of either blue or yellow light caused stress, as determined by both locomotor behavior and cortisol release. Also, activating corticotrophs of zebrafish in the bPAC+ group, by exposure to blue light, resulted in an even higher humoral response to stress. Behavior dependent on light power Further tests showed that in the bPAC+ larvae both stressor-mediated locomotor reactions and the amount of cortisol release was positively correlated with the power of the blue light. High temps and soothing waves So how does stress later affect the behavior of zebrafish? To find out, larval zebrafish were exposed to other stimuli. Unstressed larvae responded to a significant rise in temperature by increasing their locomotion, while subtle hydrodynamics (water motions) seem to sooth them, causing them to move less. Pre-stressed animals (exposed to light only a few minutes before tests) showed exaggerated responses, an effect that was even greater in the bPAC+ animals pre-stressed with blue light. More stress is good? In this study, the researchers were able to find a way to non-invasively influence the stress system by directly enhancing the release of corticotroph products upon the onset of stress. Further, they were even able to control the size of the effect, as a higher blue light power caused a higher cortisol rise. De Marco adds: "Altogether, the results demonstrated that enhanced activity of pituitary corticotrophs upon stress onset can cause fast organizing effects on behavior, namely, increased locomotor and avoidance reactions, tolerance and arousal." Read more This post refers to the following publication: De Marco, R.J.; Thiemann, T.; Groneberg, A.H.; Herget, U.; Ryu, S. (2016). Optogenetically enhanced pituitary corticotroph cell activity post-stress onset causes rapid organizing effects on behavior. Nature Communications, 7:12620. Read more about EthoVision XT or about hardware control with EthoVision XT. Read about combining optogenetics with DanioVision for zebrafish larvae research. --- ## Autistic mice have motor learning difficulties specific to the cerebellum URL: https://noldus.com/blog/autistic-mice-cerebellum Published: 2017-01-13 15:40:00 Description: Autism is often associated with social behavior deficits and repetitive behaviors. However, motor abnormalities are also a part of the behavioral spectrum. Recent studies have implicated the cerebellum. Most of us are familiar with the typical behavioral characteristics associated with autism: social behavior deficits and repetitive behaviors. However, motor abnormalities are also a part of the autism behavioral spectrum. These have generally been linked to malfunction of the cerebral cortex, but recent studies have also implicated the cerebellum. Autistic phenotype in mice Shank2 is a gene that encodes a postsynaptic protein and has been linked to autism spectrum disorders (ASD). In short, inactivation of this gene in mice creates "autistic mice" (Won et al. Nature 2012). Shank2 and motor problems The Shank2 protein is abundantly found in the cerebellum, particularly in the Purkinje Cells (PCs), but that does not necessarily mean that the motor problems observed in these autism models come from the cerebellum. To address this issue, two research groups recently generated mice that are specifically deficient in cerebellar Shank2. Peter et al. published their findings in Nature Communications in March 2016, and Ha et al. authored an article in The Journal of Neuroscience two months ago. Shank2 gene deletion To pinpoint the role of cerebellar Shank2 in autism, both groups compared behavioral and motor abnormalities between global and cerebellum-specific Shank2 knockout mice. Social phenotype Interestingly, while Peter and colleagues found a phenotype consistent with ASD in both motor learning and social interaction in the PC specific knockouts, Ha et al. did not see the social impairments in their mice. According to the authors, this might be due to the different ways in which these knockouts were created (e.g. a different exon deletion and slightly different genetic background). Behavioral testing Both groups performed an array of behavioral tests to assess motor performance, social behavior, repetitive behaviors, and anxiety. Tests employed for these assessments included the three-chambered social interaction test, marble burying, open field, and olfactory tests. For motor performance and learning measurements, mice were tested on ErasmusLadder. ErasmusLadder ErasmusLadder is a fully automated test in which mice have to learn to efficiently cross a horizontal ladder. After they gain familiarity to the ladder (phase one), mice are presented with an obstacle during phase two, in which one of the ladder rungs is raised. The obstacle is paired with a sound cue, which allows the system to assess motor learning. How animals deal with this obstacle over repeated runs allows for interpretation of cerebellar functioning. For the principle behind ErasmusLadder testing, please watch the video below. Adaptation issues Peter et al. did not observer significant ErasmusLadder motor performance issues in the PC specific knockouts during phase one, meaning that they are able to learn to efficiently cross the horizontal ladder. However, problems arose for the mice as they were presented with the obstacle in phase two. In the challenged runs, control mice increased their speed to avoid the obstacle; this strategy was not employed by the PC knockouts. Peter et al. concluded that cerebellar Shank2 is indeed important for associative motor adaptation. Different social phenotypes The results in the study of Ha et al. were not completely the same. Their PC specific knockouts had problems in motor performance, already showing learning difficulties during non-challenged ladder-crossings. In fact, these mice showed the same motor deficits as the global mutants, and, unlike the mice of Peter et al., normal social behavior. So while the results found by Peter and his colleagues point towards a role of the PCs in social behavior, the study of Ha et al. does not confirm this. Motor testing Another interesting result from the study of Ha and colleagues is that while the PC specific knockouts showed impaired motor coordination on the ErasmusLadder, they performed normally on the rotarod test, suggesting a very distinct influence of Shank2 in different motor functions. This shows the added value of several types of motor testing, and the sensitivity of the ErasmusLadder test in this scenario. RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Learn more To learn more about ErasmusLadder, please visit noldus.com/erasmusladder. References to the publications are found below: - Ha, S.; Lee, D.; Cho, Y.S.; Chung, C.; Yoo, Y.-E. Kim, J.; Lee, J.; Kim, W.; Kim, H.; Bae, Y.C.; Tanaka-Yamamoto, K.; Kim, E. (2016). Cerebellar Shank2 regulates excitatory synapse density, motor coordination, and specific repetitive and anxiety-like behaviors. The Journal of Neuroscience, 36(48), 12143. - Peter, S.; ten Brinke, M.M.; Stedehouder, J.; Reinelt, C.M.; Wu, B.; Zhou, H.; Zhou, K.; Boele, H.-J.; Kushner, S.A.; Lee, M.G.; Schmeisser, M.J.; Boeckers, T.M.; Schonewille, M.; Hoebeek, F.E.; De Zeeuw, C.I. (2016). Dysfunctional cerebellar Purkinje cells contribute to autism-like behavior in Shank2-deficient mice. Nature Communications, 7:12627. - Won, H.; Lee, H.R.; Gee, H.Y., Mah, W.; Kim, J.I.; Lee, J.; Ha, S.; Chung, C.; Jung, E.S.; Cho, Y.S.; Park, S.G.; Lee, J.S.; Lee, K.; Kim, D.; Bae, Y.C.; Kaang, B.K.; Lee, M.G.; Kim, E. (2012). Autistics-like social behavior in Shank2-mutant mice improved by restoring NMDA receptor function. Nature, 486, 261-265. --- ## Investigating the relationships between the immune system and the brain URL: https://noldus.com/blog/relationships-immune-system-brain Published: 2016-12-21 14:50:00 Description: Our research group is investigating the relationships between the immune system and the brain in humans. By Julie Lasselin, PhD, Universitätsklinikum Essen, Germany and John Axelsson, PhD, Karolinska Institutet, Stockholm, Sweden Using The Observer XT to investigate overt signs of sickness and health communication Our research group is investigating the relationships between the immune system and the brain in Humans. One of the models we use is the experimentally-induced sickness. In this model, we intravenously inject a component of a bacteria (but not the bacteria itself), which makes the immune system believe that the body is infected and that it needs to fight the infection. Therefore, this injection activates the immune system for a short time (3-4 hours) during which a sickness response is triggered. This sickness response is composed of all symptoms that we may feel when sick, such as fatigue, reduced appetite, difficulties to concentrate, reduced motivation to see people, etc (1). Figure. Activation of the immune system and sickness symptoms using lipopolysaccharide (LPS) and placebo. This experimental sickness model is commonly used to study acute sickness in humans and animals. We evaluated films taken the first 4 hours after injection. One way of assessing the behavioral effects of the immune activation is using questionnaires, that can be self-completed or completed by a trained investigator, and that include items regarding the state of the individuals. These questionnaires encompass for instance assessment of fatigue, anxiety, depressed mood, or sickness symptoms (e.g., headache, nausea), which have all been shown to increase during experimentally-induced sickness (e.g., (2)). The questionnaires are therefore all based on the subjective feeling of individuals, and on their willingness to share this feeling. Although subjective feelings are of high importance, this may bias the outcomes. A recent study found higher biological response during experimentally-induced sickness in women in comparison to men, but both sexes reported similar anxiety symptoms and depressed mood (3). Although it is possible that the behavioral outcomes are similar in men and women, it could also be that women tend to report less symptoms to what they actually feel, or that they interpret their feelings in a different way. This is why the objective assessment of signs of sickness, and their association with subjective symptoms, are of importance. Also, healthcare personnel would benefit to know whether they can rely on subjective feelings or whether they should also take into account other objective signs of sickness, and which ones. In order to assess overt signs of sickness during experimentally-induced sickness, we filmed the participants during four hours after the intravenous injection of the bacteria component (lipopolysaccharide) or a placebo (saline solution), meaning during the acute phase of the sickness response. These videos were then analyzed by two Master students using The Observer XT. Although very time consuming, this is a unique way of analyzing behavioral symptoms during experimentally-induced sickness in Humans. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Behaviors such as yawning, sniffing, stretching, sighing, complaining and moaning were scored in participants and caregiving (e.g., pampering) in the caregivers. Difficulties you will face in these kind of studies: - 1. Distinguish between some subtle differences in behavior when filming the entire room (e.g., sighing and deep breaths or facial expressions); - 2. Very time consuming; - 3. A necessity to decide on a precise definition of the behaviors and to train the raters extensively; - 4. Problems with unblinding of the raters (although not with all subjects, but the majority). Advantages: - Overt sign of sickness and how we communicate about our ill-health during sickness, understanding interaction between sick individuals and healthcare personal (could be extended to other caregivers, e.g. close ones). References - 1. Dantzer, R., et al. (2008). From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci, 9 (1), 46-56. - 2. Lasselin, J., et al. (2016). Lipopolysaccharide Alters Motivated Behavior in a Monetary Reward Task: A Randomized Trial. Neuropsychopharmacology. - 3. Engler, H., et al. (2016). Men and women differ in inflammatory and neuroendocrine responses to endotoxin but not in the severity of sickness symptoms. Brain Behav Immun, 52, 18-26. --- ## The effect of simulation-based obstetric team training URL: https://noldus.com/blog/effect-simulation-based-obstetric-team-training Published: 2016-12-16 12:05:00 Description: Dr. Truijens describes the positive effects of simulation-based obstetric team training on communication between health care professionals, clear leadership, and more. The main objective of dr. Truijens' thesis is to contribute to the exploration of patient-reported outcomes in perinatal care by focusing on developing and validating questionnaires, evaluating the quality of perinatal care, evaluating the effect of simulation-based team training on patient reported quality of care, and assessing aspects of mental health during pregnancy. In this blog post dr. Truijens will tell us more about her study, and share her insights. During the last decade, there has been a growing interest in patient-centered health care, with perceived quality of care and patient satisfaction becoming important indicators of care quality. Therefore, patient-reported quality of care is also becoming more important as an outcome measure of training and education. This blog is about patient-reported quality of care as an outcome measure of multiprofessional simulation-based team training in obstetrics. Team training in health care A review of Weaver and colleagues (2014) concluded that team training in health care improves teamwork processes and can positively impact patient outcomes. Some previous studies have also shown that simulation-based obstetric team training improves team performance (Ellis et al., 2008; Fransen et al., 2012) and might improve perinatal outcomes (Draycott et al., 2006; Goffman et al., 2014). However, since no previous research has focused on the effect of simulation-based obstetric team training on patient-reported quality of care, we performed an experimental study on this topic (Truijens et al., 2015). Teamwork skills Multiprofessional teams from a large obstetric collaborative network in the area of the Máxima Medical Centre Veldhoven in the southern part of The Netherlands were trained in teamwork skills using the principles of Crew Resource Management (CRM). During five one-day trainings, 80 care providers of the obstetric collaborative network were trained in teams of approximately 16 health care professionals, including: 2 ambulance staff, 2 maternity nurses, 4 to 5 independent community midwives, 2 obstetric nurses, 2 hospital midwives, 2 residents, and 2 obstetricians. Before the start of the scenarios, the teams received an explanation concerning the equipment and environment of the simulation rooms. The scenarios started with a short introductory briefing video with actors mimicking the medical situation and providing some background information about the simulated patient. Thereafter, the participants moved to the simulation room where they managed the simulated patient (Noelle, Gaumard Scientific, Miami, FL). The scenarios were approximately 15 minutes each, were all videotaped, and the recordings were used to facilitate the debriefing after each scenario. The debriefings of approximately 45 minutes were facilitated by a communication trainer and an obstetrician who were educated in facilitating simulation-based team training. The trainers provided feedback on both technical and non-technical skills using the video-recordings, with a focus on standardized communication and handovers based on the SBAR system of communication. Quality of care To measure the quality of care as perceived by patients, the validated Pregnancy and Childbirth Questionnaire (PCQ, Truijens et al., 2014) with 25 items on a 5-point Likert scale was assessed in a group of 76 postpartum women prior to the training, and another group of 68 postpartum women at three months after the training. The two groups of postpartum women showed comparable characteristics. At the evaluation assessment three months after the training, the mean quality of care score measured with the PCQ was significantly higher compared to the group of women who filled out the questionnaire before the simulation-based team trainings. The questionnaire items with the largest increase in mean scores were found to be about communication between health care professionals, clear leadership, involvement in planning, and better provision of information. Simulation-based obstetric team training is effective Despite the methodological restrictions of this pilot study and its non-randomized design, the results indicate that multiprofessional simulation-based obstetric team training seems to improve patient-reported quality of care. The possibility that this improvement relates to the training is supported by the fact that the items with the largest increase are about the principles of Crew Resource Management, used in the training. In summary, the results of this pilot study showed a higher score on patient-reported quality of care after multiprofessional simulation-based obstetric team training. Taking into account the limitations of the study design, this study contributes to the field of research that evaluates the effects of simulation-based obstetric team training on patient outcome level and will hopefully stimulate further research and deliberate practice using simulation-based education. More details about this study can be found elsewhere: Truijens S.E.M.; Banga F.R.; Fransen A.F.; Pop V.J.M.; Runnard Heimel P.J. van; Oei S.G. (2015). The effect of multiprofessional simulation-based obstetric team training on patient-reported quality of care: a pilot study. Simulation in Healthcare, 10, 210-6. FREE DEMO Try Viso yourself! Request a free demonstration to find out why Viso is the right tool for your UX research! - Easy-to-use solution - Create video and audio recordings - Ideal tool to conduct UX studies Free Demo References - Weaver S.J.; Dy S.M., Rosen M.A. (2014). Team-training in health care: a narrative synthesis of the literature. BMJ Qual Saf, 23, 359-72. - Ellis D., Crofts J.F., Hunt L.P., Read M., Fox R., James M. (2008). Hospital, simulation center, and teamwork training for eclampsia management: a randomized controlled trial. Obstet Gynecol, 111, 723-31. - Fransen A.F.; Ven J. van de; Merién A.E.R.; De Wit-Zuurendonk L.D.; Houterman S.; Mol B.W.; Oei S.G. (2012). Effect of obstetric team training on team performance and medical technical skills: a randomised controlled trial. BJOG, 119, 1387-93. - Draycott T.; Sibanda T.; Owen L.; Akande V.; Winter C.; Reading S.; Whitelaw A. (2006). Does training in obstetric emergencies improve neonatal outcome? BJOG, 113, 177-82. - Goffman D.; Brodman M.; Friedman A.J.; Minkoff H.; Merkatz I.R. (2014). Improved obstetric safety through programmatic collaboration. J Healthc Risk Manag, 33, 14-22. - Truijens S.E.M.; Pommer A.M.; Runnard Heimel P.J. van; Verhoeven C.J.M.; Oei S.G.; Pop V.J.M. (2014). Development of the Pregnancy and Childbirth Questionnaire (PCQ): evaluating quality of care as perceived by women who recently gave birth. Eur J Obstet Gynecol Reprod Biol, 174, 35-40. - Truijens S.E.M.; Banga F.R.; Fransen A.F.; Pop V.J.M.; Runnard Heimel P.J. van; Oei S.G. (2015). The effect of multiprofessional simulation-based obstetric team training on patient-reported quality of care: a pilot study. Simulation in Healthcare, 10, 210-6. --- ## Discrimination learning without human intervention or food restriction URL: https://noldus.com/blog/discrimination-learning-cognitionwall Published: 2016-12-15 13:55:00 Description: Sylics recently introduced CognitionWall, a new paradigm for discrimination learning in the home cage that avoids the necessity for food restriction and handling in learning tests. Learning paradigms have long been the hallmark in studies on neurological and psychiatric disorders, but they often present challenges and come with limitations. For example, many of these tasks require some combination of food restrictions, handling of the animals, and/or are quite labor-intensive. Sylics recently introduced a new paradigm, called CognitionWall, that you might have already seen on our website, and aims to get around some of these limitations. Home cage protocols So for those of you not familiar with CognitionWall yet, it's an automated home cage testing protocol for discrimination learning and reversal learning. It is designed to work with PhenoTyper, EthoVision XT, and AHCODA. The protocol Esther designed involves two days of discrimination learning, followed by two days of reversal learning. The elegance of this protocol lies within the lack of limitations: there is no human intervention, nor is there a need for pre-imposed food restriction. Get rewarded In addition, the CognitionWall itself is a very straight-forward tool: a wall placed in one corner of the home cage, in front of a pellet dispenser, with three holes in it. Mice stay in their home cage for the entire testing period, and simply learn to earn their food by accessing the correct hole in the wall; in this initial study, the mouse learned to go through the right-most hole. No intervention The video camera in the top unit of the PhenoTyper is connected to EthoVision XT software, allowing for constant location-based monitoring of the animal. This way, the activity and whereabouts of the mouse is automatically measured, and when entering the correct wall, EthoVision XT sends out a signal to the pellet dispenser to deliver the automated food reward. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Getting it right Over two days, discrimination learning is assessed by how often the animal "gets it right" and enters through the correct hole in the CognitionWall. Over the following two days, reversal learning is studied, simply by changing the "correct entry" to a different hole. Validation To validate this new method, Esther tested performance using a common mouse model for Alzheimer's disease (APP/PS1) and brain lesions (orbitofrontal cortex manipulations) that are known to underlie flexible stimulus-reinforcement learning. While the Alzheimer's mice showed difficultly learning during the discrimination phase (compared to wild type mice), no such difference was found between the brain-lesioned mice and their sham-lesioned littermates. However, during the reversal phase, the brain-lesioned mice did show significantly more trouble learning the new correct entry. Esther's study shows that CognitionWall offers a sensitive and also very elegant and accessible new method to test discrimination learning in mice. For more information on PhenoTyper, go to noldus.com/phenotyper. Did you know PhenoTyper is fully customizable to your study, simply by picking four different walls to create the cage you need? Watch the video below for some examples! --- ## Comparing two different skin-to-skin contact techniques URL: https://noldus.com/blog/comparing-skin-contact-techniques Published: 2016-11-23 15:00:00 Description: Skin-to-skin contact is essential in developing a feeling of safety, and in creating the bond between parent and child, especially with premature babies. Buil et al. compared two kangaroo positioning techniques. Three times I have experienced how it feels to hold my newborn baby in my arms. To feel that warm, small, naked body on top of you, the baby that is yours and grew inside you…that is probably the most precious gift I have ever experienced. The little baby that just left the warm space it has spent all those months, and now exposed to the outside world - the only thing he or she needs is to feel safe with his or her mother or father. Feeling safe Skin-to-skin contact is essential in developing that feeling of safety, and creating the bond between parent and child, especially with premature babies. The birth of a preterm baby often creates mental stress for the parents. The baby is so vulnerable; will it stay alive and be okay? In the first hours and days, sometimes even weeks, many worrying moments will occur. In neonatal intensive care units (NICU’s) skin-to-skin contact is used as a multisensory care method offered to both parent and child immediately after birth. Such care has numerous well-known positive effects on the development of premature children, both physically and psychologically. The Kangaroo Mother Care (KMC) program is an often chosen method to ensure this parent-child contact. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Get your copy instantly Making eye-contact with a baby Within the NCIU at the Centre Hospitalier Sud Francilien (France), the baby was positioned vertically inside the mother’s clothes to provide that skin-to-skin contact. However, mothers often complained about the impossibility to look the baby in the face and make eye-contact. Hospital workers decided to address this issue and implemented a new position based on a flexed body axis, with the child positioned diagonally on the mother’s chest and supported by a stretchy wrap. This position was named the supported diagonal flexion (SDF) kangaroo positioning (see the picture below: the vertical kangaroo positioning technique on the left and the supported diagonal flexion kangaroo positioning on the right). It would ensure that parents were less preoccupied by the fear of the baby slipping, more relaxed in order to interact with their baby, and more able to make eye-contact and still have good skin-to-skin contact. All this was hypothesized to result in improved well-being of both the parent and the baby. A study using kangaroo “supported diagonal flexion” positioning Fifteen mothers and their premature babies (the mean gestational age of the children at birth was 29.3 ± 2.5 weeks gestation) were assigned to one of the two kangaroo positioning modes: either the current vertical positioning or the new SDF positioning. Physiological variables such as heart rate, respiratory rate, oxygen saturation, and all critical events of the babies were recorded automatically before, during, and after each skin-to-skin session. Ten sessions of skin-to-skin contact were scheduled, with the first and last sessions recorded to allow behavioral measurements. The Observer XT was used to code and analyze these video recordings. Mothers’ risk for depression and feelings about the way they experienced communication with their baby were assessed through questionnaires. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Results show positive effects During the skin-to-skin sessions, significant decreases in heart rate and respiratory rates were measured in both groups, suggesting that skin-to-skin contact in general helps the baby calm down. The researchers did not find any negative effects associated with the SDF positioning in comparison with the usual vertical positioning. SDF positioning led to a reduced amount of restlessness, fewer negative vocalizations, and drowsiness of the babies, in favor of more deep sleep. The skin-to-skin sessions also lasted longer in the SDF group than in the vertical group. Mother-child interaction The mothers in the SDF group tended to look more at their child’s face and looked elsewhere less. Clearly, these exchanges were less effortful for both the baby and the parent in this position. Not only did the mothers look more at their child’s face, but they also spent more time smiling at and talking to their child. The mothers appeared to feel more comfortable in a position that allows for face-to-face contact. A simple change in positioning has immediate and obvious benefits. Overall, this study highlights the positive impact of the kangaroo SDF positioning technique, in terms of early mother-child interaction. The technique is physiological safe and improves the well-being of both the parent and the child. It’s an innovative, inexpensive, and easy-to-use technique in daily practice by all healthcare professionals working in a NICU. Reference Buil, A., Carchon, I., Apter, G., Laborne, F.X., Granier, M. & Devouche, E. (2016). Kangaroo supported diagonal flexion positioning: New insights into skin-to-skin contact for communication between mothers and very preterm infants. Archives de Pédiatrie, Volume 23, 9, 913-920. https://doi.org/10.1016/j.arcped.2016.04.023 --- ## The value of facial expression analysis in advertisements URL: https://noldus.com/blog/facial-expression-analysis-in-advertisements Published: 2016-11-07 14:58:00 Description: José Chavaglia Neto and José António Filipe investigated the effect of one commercial on consumer emotion. They asked consumers to watch this commercial related to a specific brand. I love Apple. I am a fan. I deny being an addict, which of course makes me one. Very few brands achieve the status of being "lifestyle brands". According to José Chavaglia Neto and José António Filipe from Instituto Universitário de Lisboa, Portugal, whose study I discuss in this blog post, consumers' fascination for particular brands on the market is rising considerably. Therefore, companies are trying to consistently create a strong identification with their brand(s), what allows the company to add economic value because people will keep buying this particular brand. I bought a new iPhone, and couldn't wait to show it to my friends and family. I did pay a lot of money for it…yet I keep buying Apple. I am truly a fan of their technology, brand, and style. Are there other brands that you feel so strongly about? Do Samsung and Sony also have fans? Of course, I wouldn't know. I do know that Saab has an enormous group of fans. When a Saab is bought, the car is often as spoiled as an only child. And do you know Bose speakers? These speakers are proudly displayed in people's homes, and people want to show them off. They also have a high price tag – saying something about what people can or cannot afford. Convincing consumers Many companies face a great difficulty in convincing consumers that their products and services are worthy of being purchased by them. On top of that, many have the ultimate goal of creating brand loyal fans. To study consumer behavior, many companies try to find effective neuromarketing tools with predictive value. José Chavaglia Neto and José António Filipe set out to measure value as reflected on the consumer's face, using a tool that automatically analyzes micro expressions. Companies would love this insight into behavior - from the moment a consumer sees the first ad to the moment he unpacks the box in his home. Role of emotions In Neto and Filipe's study, they investigated the effect of one commercial (Shot on iPhone-6 by Jin C.) on consumer emotion. They asked consumers to watch this commercial related to a specific brand (Apple!) while they had a camera capturing the consumers' facial expressions. From such an analysis, companies could adjust their marketing communication strategy to take advantage of their brands competitive positioning in the market. But: does it work? What can FaceReader tell you? Neto and Filipe used FaceReader – software for automatic measurement of facial expressions. It automatically analyzes basic facial expressions, neutral, contempt and three affective states. It also calculates gaze direction, head orientation, and person characteristics. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Two moments of interest The researchers concluded that FaceReader data showed two moments of interest during the fifteen second video film that stood out on the emotion curves. They found a rise in happiness when crossing the ninth second, and explain that a sudden change of pace in the music contributes to that happiness peak. The second emotional moment occurs precisely on the 13th second of the video; to see what accounts for that emotional change, you are better served to watch the video for yourself and see if you smile - I did! Understanding emotions in marketing As José Chavaglia Neto and José António Filipe state, the results obtained through the use of this kind of software allows the mapping of emotions, in real time, generated by a marketing stimulus. Automated facial emotion software provides another insight into the consumer's reaction to marketing material by focusing on one key aspect that will help create brand loyalty: emotion. Read more about other solutions for consumer research that can help you understand behavior and develop the best products and advertisements. Reference Neto, J.C., Filipe, J.A. (2015). Consumers economic behavior and emotions: the case of iPhone 6 in neuromarketing. International Journal of Latest Trends in Finance and Economic Sciences, 5 (4), 1041-1047. --- ## Marketing and market research blogs URL: https://noldus.com/blog/marketing-market-research-blogs Published: 2016-11-01 09:11:00 Description: Learn all about gamification in marketing, facial expression analysis, and the difference between self-report, qualitative research, and unobtrusive observations. You have never met such a colorful team as the Noldus Consulting Team of Noldus Information Technology. They go to conferences where there are wheel of fortune games and water-pong challenges in vendor booths, harbor cruise dinners and cocktail parties with all conference attendees, and fantastic conference swag to bring home. Marketing really is a different world! It's not all fun and games - they also have time to write brilliant blog posts about consumer behavior which are published on the Noldus Consulting website. Consumer behavior, and how consumers make choices, is of particular interest to our team; we'd like to share some popular posts on these topics here with you. Learn all about gamification in marketing, facial expression analysis, and the difference between self-report, qualitative research, and unobtrusive observations. Quantifying Ethnography: qualitative vs quantitative We believe that combining objective quantitative analysis of observations with the insights gained by participant observation comes closest to taking a peek inside a persons' mind and heart. If you want to truly learn how your target group behaves in your area of interest, and not just take their word for it, quantification of the ethnographic approach may well be the method for your objective. Declared vs revealed data Abbe tells us that being able to accurately measure consumer emotion provides insights that would be hidden if researchers were to only use self-report. In one example, we were tasked by a shaving company to examine emotional reactions while using premium and non-premium razors – how are consumers reacting to these razors during product use? Is this even a valid way to assess "likeability" of a razor? By assessing facial emotions as women shaved their legs, we obtained deeper insights than via self-report alone. One respondent self-reported similar feelings of "liking" for each razor type in the post-usage assessment, but during use she actually cut herself with the premium razor and expressed negative emotions on her face that she did not verbalize - the depth of her negative emotions during usage could not have been assessed from self-report alone. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Beyond the Taste: The Bean Boozled Challenge Jason shows us how valuable automated facial expression analysis can be in marketing. Did you know that scientists can determine your food preferences within three seconds? Jason refers to researchers from the Wageningen University and Research center who showed that "liking" a flavor takes place very quickly. To illustrate this rule and the value of facial expression analysis in marketing, he analyzed Bean Boozled challenges with FaceReader (the tool which analyzes micro expressions in the face). The Bean Boozled Challenge shows how brands can grow by engaging consumers to play games, even if that brand creates flavors that are literally disgusting. Whether intentional or not, the Jelly Belly Candy Company exemplifies the principles of gamification and the Peak End Rule with one box of brilliant beans. --- ## Video tracking for high-throughput screening of plant resistance to thrips URL: https://noldus.com/blog/video-tracking-plant-resistance-thrips Published: 2016-09-26 14:53:00 Description: A thrips is a tiny insect that can have a not-so-tiny effect on plants. A lot of research is currently carried out on how to get rid of these creatures. Unless you grow plants commercially, you may very well not know what a thrips is. It is a tiny insect that can have a not-so-tiny effect on plants. Thrips pierce plant leaves and flowers and suck out their contents. And, not less important, many plant viruses are known to be transmitted by thrips [1]. Needless to say, a lot of research is currently carried out on how to get rid of these creatures. Photo courtesy of T. Bukovinszky (www.bugsinthepicture.com). In a previous blog I explained that plants have numerous ways to defend themselves against insects. This natural variability in plant defense mechanisms offers possibilities to breed for plant varieties that are better protected against pest insects [2]. In this way we can decrease the amount of pesticides needed and produce cleaner crops. However, breeding for plant resistance requires an easy method to screen many plants at once for resistance. Low-throughput screening Host plant resistance to insects is generally studied with end-point measurements, such as counting the number of insects on the plants, or assessing insect damage some weeks after infestation. However, this is very labor intensive, it requires space in the order of magnitude of a greenhouse, and the results give no insight into the background of the resistance. This makes it difficult to locate resistance genes that could be used to breed for new plant lines with insect resistance. New video tracking method Manus Thoen and his colleagues developed a new, very promising, method to screen plants for thrips resistance [3]. They used wellplates in which they could run multiple dual-choice tests with leaf discs simultaneously. With the video tracking software EthoVision XT, they could automatically determine the time spent on either plant line. In addition to this, they automatically measured the time the thrips was moving and not moving on each plant line. Movement was assumed to be associated with searching behavior and no movement with probing and feeding. With this setup, 88 dual choice test can be run simultaneously in just 8 hours at a benchtop surface of approximately 1 m2. Compare this to the time, space, and effort needed with traditional screening methods! FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial New method validated To validate the new setup, Thoen et al, compared the results of the new test with end-point measurements after 6 days with whole leaves and whole plants. In addition to this, the video tracking results were compared with those of manual annotations of the location of the thrips and whether they were moving or not. They found a very high correlation in all cases. Plant resistance was negatively correlated with the time spent on the plant line and the time not moving on this line. High-throughput screening At present almost 100 plant varieties can be screened simultaneously in one run of 8 hours. This makes the new method very promising for high-throughput screening for plant resistance to thrips. Hopefully, we can soon rid plants of these creatures in an environmentally friendly way. References - Thrips (Wikipedia) - Wink M. Plant breeding: importance of plant secondary metabolites for protection against pathogens and herbivores. Theor Appl Genet. 1988; 75:225-33. - Thoen, M. P., Kloth, K. J., Wiegers, G. L., Krips, O. E., Noldus, L. P. J. J., Dicke, M., & Jongsma, M. A. (2016). Automated video tracking of thrips behavior to assess host-plant resistance in multiple parallel two-choice setups. Plant Methods, 12(1), 1. Read more - Host-plant resistance to western flower thrips in Arabidopsis. Thoen, M. P. (2016) PhD thesis, Wageningen University, The Netherlands. library.wur.nl/WebQuery/clc/2177085 - How you can efficiently screen plant resistance to aphids - Developing a high-throughput method: EthoGenomics - High-throughput screening of plant lines for resistance to pest insects --- ## High-throughput screening of plant lines for resistance to pest insects URL: https://noldus.com/blog/resistance-pest-insects Published: 2016-09-16 16:05:00 Description: The EthoGenomics project focused on screening for host plant resistance to insect pest species. Video tracking provides the possibility to scale up the screening method largely. One of the great things about working for Noldus IT is its involvement in scientific research projects. Because the tools that we offer are used in scientific research, it is logical that we also participate in projects for which such tools are developed. High-throughput screening of plant lines for resistance to pest insects I was personally involved in one of these projects, EthoGenomics. Since its primary research area, entomology (for lay people, "the scientific study of insects"), matches my own scientific background, I had a weak spot for this project. The two PhD students involved, Karen Kloth and Manus Thoen, recently defended their excellent theses and did so with great success. Plant resistance to insects The EthoGenomics project focused on screening for host plant resistance to insect pest species. Traditionally, plant lines are screened with end-point measurements, such as counting the number of insects on the plants, or assessing insect damage some weeks after infestation. However, this is very labor intensive, it requires space in the order of magnitude of a greenhouse, and the results give no insight in the background of the resistance. This makes it hard to locate resistance genes that could be used to create new plant lines with insect resistance. Video tracking for high throughput Video tracking provides the possibility to scale up the screening method largely. However, one needs to have a parameter that is a proxy for resistance and can also be measured automatically with video tracking. Karen searched for such a parameter for aphids and Manus did the same for thrips. And both were successful. Karen found that the number of long probes on leaf discs is a good measure for host plant resistance to aphids. These long probes can be measured automatically with video tracking by determining the time the aphids are not moving on the leaf discs. Read more about it in this blog. Meanwhile, Manus developed a high-throughput two-choice assay in which plant lines can be screened automatically with video tracking for resistance to thrips. In both cases, almost 100 plant lines can be screened simultaneously in a relatively short time and in a benchtop area of about 1 m2. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Proud We are extremely proud that the project has been so successful and has resulted in high quality scientific papers. In the follow-up project, we are involved to further develop the methods and test them on commercial vegetables and ornamentals. We will keep you informed. Read more - Kloth, K. J., ten Broeke, C. J., Thoen, M. P., Hanhart-van den Brink, M., Wiegers, G. L., Krips, O. E., Noldus, P. J. J., Dicke, M. & Jongsma, M. A. (2015). High-throughput phenotyping of plant resistance to aphids by automated video tracking. Plant methods, 11(1), 1. - Thoen, M. P., Kloth, K. J., Wiegers, G. L., Krips, O. E., Noldus, L. P. J. J., Dicke, M., & Jongsma, M. A. (2016). Automated video tracking of thrips behavior to assess host-plant resistance in multiple parallel two-choice setups. Plant methods, 12(1), 1. - Host-plant resistance to western flower thrips in Arabidopsis. Thoen, M. P. (2016) PhD thesis, Wageningen University, The Netherlands. http://library.wur.nl/WebQuery/clc/2177085 - How you can efficiently screen for plant resistance to aphids - Developing a high-throughput method - EthoGenomics - More about insect studies --- ## How to measure infant behavior URL: https://noldus.com/blog/how-to-measure-infant-behavior Published: 2016-09-12 13:00:00 Description: In infancy you can observe an explosive growth. Many researchers focus on this age group. Think about studies aimed at learning more about speech behavior, maternal sensitivity, or learning behavior in infancy. Infants undergo astonishing physical, cognitive, and social transformations in their first year of life, making them a captivating subject for scientific study. By measuring infant behavior, researchers gain insights into early speech development, maternal sensitivity, and foundational learning processes. How to measure infant behavior Recent advancements in technology - such as eye-tracking systems, neuroimaging techniques (fNIRS, EEG), and sophisticated observational tools - have revolutionized how we assess infant behavior both in controlled lab settings and in naturalistic home environments. In this blog post, we’ll explore modern strategies and methodologies for measuring infant behavior, discuss the importance of ethical considerations, and highlight how cutting-edge research benefits caregivers, educators, and policymakers alike. Observing mother-infant behavior Current research from Prof. Cristina Riva Crugnola, University of Milano-Bicocca tells us that adolescent mothers as well as their babies (vs. adult mother and infant interactions) spent more time in negative engagement, meaning that the mothers showed more pushy behaviors towards the infant, even hostility. The infant also showed more negative behaviors, such as protesting with expressions of anger and crying. Read more: Observing mother-infant behavior Behavioral observations in autism research Mothers play a crucial role in the development of communication of their children. The use of gestures by the mother strongly correlates with the gesture use and language development of their children.  Mothers that have an older daughter or son that was diagnosed with ASD, may change their behavior towards the younger HRA children. For example, these mothers have learned to use more gestures when communicating with their children. This could affect the gesture use and language development of HRA children.  Read the full post here: Behavioral observations in autism research FREE WHITE PAPER Autism research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Get your copy instantly Early Infant behavior development of hand preference  Recently, Nelson et al. presented “Unimanual to bimanual: Tracking the development of handedness from 6 to 24 months”. One of their findings was that, as infants, 39% of these children showed preference for the right hand, whereas 61% had no hand preference. In toddlerhood, this 39% increased to 97%. This study provides some evidence that handedness might begin to stabilize earlier than traditionally assumed. However, in order to confirm this conclusion, more research was required.  Learn more: Early Infant behavior development of hand preference The facial action coding system in infant behavior research Forestell and Mennella (2012) used the FACS to objectively quantify infant’s facial expressions. As a result, they gained insight in the relation between infant behavior and the assessment made by his or her mother concerning the infant’s temperament.  Forestell and Mennella looked into responses to green vegetables and coded the facial expressions using the Action Unit codes. After analysis, they compared the outcomes with the before mentioned parental assessments. Temperament of the infants was described using the Infant Temperament Scale. On this scale, a parent can indicate the frequency of approach/ withdrawal behavior and to what extend the infant can adapt to a situation.  Find out more: The facial action coding system in infant behavior research Infant behavior experiments Interested in a free coding scheme? Olafsen et al. (2006) observed mother-infant interaction and investigated whether early intervention could be beneficial for infants with a low birth weight. The coding scheme they used is available online.  Read the full post here: Infant behavior experiments FREE WHITE PAPER How to set up a coding scheme Download here the FREE white paper 'How to set up behavioral coding' and get 7 tips about: - Defining your behavior group - Point events - Coding from a diversity of sources Submit to download Examples of infant behavior research experiments In infancy you can observe an explosive growth. A lot of researchers focus on this age group and observe parent-infant dyads to get more insight in specific behaviors. Experiments are often set up to study looking behavior, language acquisition, attachment, or learning behavior. You can find the full blog post here: Examples of infant behavior research experiments How caregivers and children interact within the context of pain O.U.C.H. Lab - The Opportunities to Understand Childhood Hurt (O.U.C.H.) Laboratory run by Dr. Rebecca Pillai Riddell (watch her TEDx Talk) focuses on understanding how caregivers and children interact within the context of pain. Their research is performed in a variety of settings, from their own lab space on the York University Campus to the Neonatal Intensive Care Units of major Toronto hospitals.  Noldus and the O.U.C.H. Lab staff worked together to create the perfect lab space. Their lab is divided into two areas with observational technology (including up-to-date audio/video equipment), physiological equipment (by MindWare, LLC), and portable observational computing systems. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial --- ## The power of rejection (in fruit flies) URL: https://noldus.com/blog/the-power-of-rejection Published: 2016-09-01 15:41:00 Description: Fruit flies have amazing sense of smell. This includes the ability to navigate to a food source, as well as search out a preferred mate. However, there are other areas in which their olfactory systems come into play. In a previous post we talked about fruit flies and their amazing sense of smell. This includes the ability to navigate to a food source, as well as search out a preferred mate. However, there are other areas in which their olfactory systems come into play. This includes courting behavior (did you know the male does all the work?) and obesity. Yes - obesity can be studied in fruit flies. Courtship. The male does all the work, but feminizing specific parts of his olfactory system can suppress this behavior. But it is not easy, as Kido and Ito (Ochanomizu University, Japan) found out. The male does the work We already established that the sense of smell is important in mate preference. These researchers thought it was time to figure out what exactly makes the male act as it does during courtship display. Apparently, the whole brain is involved in this gender-specific behavior. Using a specific genetic modification, Kido and Ito were able to 'feminize' specifically targeted parts of the fly brain. When specific regions were targeted, courtship behavior was not affected; only feminizing almost all neurons suppressed male courtship behavior. The power of rejection Rejection can hurt. And it might do so in fruit flies as well, as Winbush and colleagues from the University of Southern California discovered. A male that has been repeatedly rejected by potential female mates is less likely to court another female. So why is this important? It indicates that fruit flies do have some ability to form long-term memories, which could be relevant in many avenues of research. A magic pill Some might wish there was a magic pill to prevent overeating, and fruit flies might be able to help us find one. Gasque and colleagues from The Rockefeller University in New York used fruit flies to screen a range of molecules for potential food-intake modulation. They identified one called metitepine. They then used fruit flies to find that the 2A serotonin receptor was responsible for the inhibiting effect of metitepine on feeding behavior. To study feeding, researchers had to get up close and personal with their insect models: they observed mouth-hook contractions, and measured the optical density of the gut, to estimate food intake. Nature vs nurture What happens early in life may affect how you do later in life, but genes also seem to influence how you behave. The same is true for fruit flies, as Burns and his colleagues show. They studied two strains of fruit flies, called sitters and rovers. As their names imply, these strains normally show different behaviors in the presence of food: one primarily sits, while the other roves through the environment. However, sitters fight against their genetic propensity and rove as needed for food if deprived of food during early life, while rovers did not feel the need to up their game when raised under the same adverse circumstances. Night-time activity We have something else in common with fruit flies: our day-night rhythmicity. Like us, Drosophila are diurnal – they are active during the daytime, and inactive at night. Unless you pair up a male and a female (fruit fly, that is), as shown by Fuiji and colleagues from the Duke University Medical Center in North Carolina. While male-male and female-female couples got their night's rest, heterosexual couples did not… Hugging the walls When you find yourself in an unknown environment, especially in a precarious situation, you might feel the need to stay close to the walls. This is a behavior known as thigmotaxis (or wall-hugging), and is observed in many animal species. This is an evolutionarily protective behavior; as open spaces can lead to more predation or other negative outcomes. Soibam and his colleagues from the University of Houston, Texas found that fruit flies are no different. Interestingly, they showed that not all walls are equal: fruit flies prefer outer walls and smaller corners more than inner walls and large corners. Image of Drosophila courtship behavior by Francisco Romero Ferrero [CC BY-SA 4.0], via Wikimedia Commons. References For more information on video tracking with EthoVision XT, click here. For more information about scoring behavior with The Observer XT, click here. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial - Burns, J.G.; Svetec, N.; Rowe, L.; Mery, F.; Dolan, M.J.; Boyce, W.T.; Sokolowski, M.B. (2012). Gene-environment interplay in Drosophila melanogaster: chronic food deprivation in early life affects adult exploratory and fitness traits. PNAS 109, 17239-17244. - Fuiji, S.; Amrein, H. (2010). Ventral lateral and DN1 clock neurons mediate distinct properties of male sex drive rhythm in Drosophila. PNAS, 107, 23. - Fuiji, S.; Krishnan, P.; Hardin, P.; Amrein, H. (2007). Nocturnal male sex drive in Drosophila. Current Biology, 17(3), 244-251. - Gasque, G.; Conway, Stephen, C.; Huang, J.; Rao, Y.; Vosshall, L.B. (2013). Small molecule drug screening in Drosophila identifies the 5HT2A receptor as a feeding modulation target. Scientific Reports, 3, 21220. - Kido, A.; Ito, K. (2002). Mushroom bodies are not required for courtship behavior by normal and sexually mosaic Drosophila. Journal of Neurobiology, 52(4), 302-311. - Soibam, B.; Goldfeder, R.L.; Manson-Bishop, C.; Gamblin, R.; Pletcher, S.D.; Shah, S.; Gunaratne, G.H.; Roman, G.W. (2012). Modeling Drosophila positional preferences in open field arenas with directional persistence and wall attraction. PLOS ONE, 7(10), e46570. - Winbush, A.; Reed, D.; Chang, P.L.; Nuzhdin, S.V.; Lyons, L.C.; Arbeitman, M.N. (2012). Identification of gene expression changes associated with long-term memory of courtship rejection in Drosophila males. G3: Genes/Genomes/Genetics, 2, 1437-1445. --- ## The use of video tracking in a HaXha test URL: https://noldus.com/blog/video-tracking-haxha-test Published: 2016-08-25 14:46:00 Description: When you get used to something, after a while you might not notice it anymore. Like a sent. The lab of Justus Verhagen investigated sniffing behavior with video tracking. When you get used to something, after a while you might not notice it anymore. It's called habituation. When you are repeatedly presented with the same stimulus you might cease to respond to it altogether. Habituation is a form of learning that is often studied in animals, especially in olfactory learning. In a cross-habituation (HaXha) test, the animal is first presented with an odorant and the time it explores the odor is measured. Getting used to a smell Then, over time, the habituation process is assessed. A new odorant presents a novel stimulus, and this time the cross-habituation phase is measured. If the animal spends more time investigating this new stimulus than it did the previous one, it is considered to be cross-habituating. Sniffing behavior Last year I spoke to Justus Verhagen and he told me he was planning on investigating sniffing behavior in this context. He recently published his work in Neural Plasticity (Coronos-Samano, Ivanova, and Verhagen, 2016) and was kind enough to even write up a white paper for us. You can find a link to it below. Video tracking data combined What is really interesting about the study is that the authors combined whole-body plethysmography to assess sniffing behavior, which underlies odor exploration, and compared this data to video tracking data on nose proximity to the odor stimulus. A classic criterion for odor exploration is a nose proximity of 2cm or less. With this combination of methods, Verhagen and his colleagues were able to determine that the classic criteria are indeed a fairly accurate assessment of sniff-modulated exploration. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Preventing bias Verhagen explains that using video tracking prevents possible observer bias that might occur in a human experimenter-with-stopwatch scenario and allows for higher resolution assessment of exploration time. In addition, this study shows that sniff rate, the elevation of which is equivalent to active odor exploration, is especially well-predicted when combining the nose distance to the odor with data on movement velocity. Head angle to the odor source did not prove useful in this study. Free white paper! If you want to learn more about this study, download this white paper for free! References The Neural Plasticity paper: Coronas-Samano, G.; Ivanova, A.V.; Verhagen, J.V. (2016). The Habituation/Cross-Habituation Test Revisited: Guidance from Sniffing and Video Tracking. Neural Plasticity, Article ID 9131284, 1-14. --- ## How fruit flies find your food (and mates!) URL: https://noldus.com/blog/how-fruit-flies-find-your-food Published: 2016-08-15 11:32:00 Description: Those tiny flies that take over your garbage cans during the summer? They are called fruit flies for a reason! They have a fantastic sense of smell and these tiny creatures are a popular animal model for researchers. Those tiny flies that take over your garbage cans in the summer? They are called fruit flies for a reason! They have a fantastic sense of smell and these creatures are a popular animal model for researchers. How fruit flies find your food (and mates!) I am usually irritated by these little flies, but as I read up on some research using them, I have to say I am starting to appreciate them more and more! It's truly impressive how much information researchers are able to get out of these tiny creatures. Smelling is a complicated business Much of the research using drosophila has focused on olfaction. In fruit flies, smelling is not simple, but involves a complex system. In fact, I could devote this whole article to interesting scientific facts about it...which is exactly what I am going to do! How does a fruit fly smell? First things first: how exactly do fruit fly smell? Fishilevich and colleagues from the Rockefeller University in New York identified 21 olfactory sensory neurons. If one of those neurons does not work, it doesn't seem to matter much, as another neuron will step in to compensate. While some of those neurons seem more important than others, in general a combination of specific neurons allows fruit flies to identify each specific smell. Two noses Those olfactory neurons are divided over two 'noses'- symmetrical dorsal organs. Matthieu Louis and his colleagues found that there is a left-right asymmetry in the functioning of these organs. Both are needed for the fruit fly to navigate an effective path towards the odor, but if one of the "noses" is eliminated the fly can still find the odor, but with significantly more meander to the target. How can we tell? So how can we tell if a fruit fly (adult or larva) is actually smelling anything? Through chemotaxis, which is a fancy way of saying that you want to know if an animal is attracted by a smell and shows it by moving towards that odorant. In most assays of this type, a fruit fly larva is placed in a petri dish that contains a cap with an odorant. If the larva moves towards the cap, it is likely picking up on the smell. Smelling in HD Matthieu Louis and his colleagues upped the game by creating an assay with a gradient line of odor, to assess the larvae's ability to detect an increase in odor concentration. Turns out, they are smart smellers, moving through the gradient until they found the highest concentration, but turning back if the concentration decreases again along that line. Smelling your age Despite being such visually-dependent creatures, even we as humans reply upon smell as an important factor in how much we like someone. In fruit flies, this is particularly important. Hu and colleagues (Tongji University, Shanghai) discovered that male fruit flies are able to smell an age difference between two females. When given a choice, they reliably choose the younger female. This choice seems to depend on a specific receptor: when the 33a receptor was genetically cancelled out, the preference was eliminated. Measure behavior I cannot imagine how painstakingly cumbersome it would be to manually measure how a fruit fly moves, how fast it is going, and how straight its path is. Luckily, there is automated video tracking for that. All of the studies mentioned in this blog post used EthoVision XT video tracking for these parameters. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Up next… I have gather some more scientifically proven fun facts about fruit flies, so stay tuned! References - Fishilevich, E.; Domingos, A.I.; Asahina, K.; Naef, F.; Vosshall, L.B.; Louis, M. (2005). Chemotaxis behavior is mediated by single larva olfactory neurons in Drosophila. Current Biology, 15(23), 2086-2096. - Hu, Y.; Shao, Y.; Wang, X.; Ma, Y.; Ling, E.; Xue, L. (2015). Gr33a modulates Drosophila male courtship preference. Scientific Reports, 5, 7777. - Louis, M.; Piccinotti, S.; Vosshall, L.B. (2008). High-resolution measurement of odor-driven behavior in Drosophila larvae. Journal of Visualized Experiments (JoVE), 11. - Louis, M.; Huber, T.; Benton, R.; Sakmar, T.P.; Vosshall, L.B. (2008). Bilateral olfactory sensory input enhances chemotaxis behavior. Nature Neuroscience, 11(2), 187-199. --- ## Video-recording children with ASD in-home URL: https://noldus.com/blog/video-recording-children-asd-home Published: 2016-08-08 10:39:00 Description: Anne Kirby and colleagues studied sensory and repetitive behaviors among children with autism spectrum disorder (ASD). 32 children with ASD participated. Nowadays we often come across signs or printed versions of funny, motivational, and inspirational quotes about our homes. You'll probably confirm this for yourself: we've all seen a postcard, a doormat, or a picture in a magazine with sentences like: 'Home is where the heart is', 'Home is where you can be yourself' or 'Home sweet home'. A funny one I like is 'Home is where your Wi-Fi connects automatically'. We also read listings which convince us that 'in this house we are real, we make mistakes, we say I'm sorry, we have fun, we forgive, we love' and so on. In home study I think it is safe to say that most of us are at our best in our own homes. This creates a strong argument for researchers who study behavior influenced by environmental factors to carry out their research in-home. So that's exactly what Anne Kirby and colleagues [1] did in their study about sensory and repetitive behaviors among children with autism spectrum disorder (ASD). The study involved video recording observations of 32 children with ASD (2-12 years of age), going about activities within their own homes. React differently to stimuli Sensory and repetitive behaviors can affect the everyday lives of children with ASD, depending on how severely these behaviors manifest. Processing and integrating sensory information or stimuli, such as sights, sounds, smells, tastes and/or movement, is often difficult for children with ASD and requires more effort for them to do so. They may not react at all to stimuli, or overreact, get fascinated, or even annoyed by stimuli that non-ASD children filter out. These sensory problems can lead to difficulties with eating or dressing; ASD children often limit their food intake, or always want to wear the same clothing. Common repetitive behaviors include hand-flapping, rocking, jumping and twirling, arranging and rearranging objects, and repeating sounds, words, or phrases. Repetitive behaviors can take the form of intense preoccupations, or obsessions [2]. Unfamiliar spaces make sensory and repetitive behaviors more pronounced and problematic; another reason for Kirby et al. to study these children's behaviors in the safe, familiar environment of their homes. Observe and describe The researchers emphasize that observational research provides more objective measure of sensory and repetitive behaviors and can support or supplement parent-report measures. Moreover, home videos capture children in their natural environments and the behaviors that regularly occur within them. This current research focused on two aims: 1) describe the home activity contexts within which children with ASD engage in four patterns of sensory and repetitive behavior (hyper responsive, hypo responsive, sensory seeking, and repetitive/stereotypic), and 2) describe the sensory modalities and stimulus characteristics associated with each pattern of sensory and repetitive behavior. Research assistants visited the homes of participating families three times each to collect a series of naturalistic video recordings of each child in their home environment while engaging in everyday activities. They collected video recordings using a hand-held digital recorder in three segments lasting approximately 15 minutes each. Code daily living activities The research team developed a coding manual with detailed procedures, instructions, and operational definitions for behavioral coding and completed coding using The Observer XT. They coded activities of daily living, social activities, and free play. The stimulus characteristics were divided in novel or familiar, child- or family-initiated, and social or non-social settings. Hyper responsive behavior Throughout coding, behaviors were coded as "hyper responsive" 110 times. These observed behaviors included children covering their ears or negatively reacting in response to everyday sounds (e.g. television at moderate volume and sound of water running in the kitchen sink) and sights (e.g. sunlight through a window), as well as avoiding or expressing pain during everyday activities (e.g. hair brushing, teeth brushing, face washing). Most hyper responsive behaviors were associated with familiar stimuli, and were non-social in nature. Sensory seeking and repetitive/stereotypic behavior Both sensory seeking and repetitive/stereotypic behavior patterns most commonly occurred in the context of free play activities and involved child-initiated stimuli. They occurred in the presence of familiar stimuli, and often in non-social contexts. The behaviors coded as sensory seeking included behaviors such as jumping on stairs, bouncing on large balls, throwing body into furniture or onto floor, rubbing objects on face and body, rolling around on carpet floors, and placing objects in mouth. Repetitive/stereotypic behaviors involved some actions with objects (e.g. lining up toys over and over, and repeatedly watching segments of video) or actions related to their own bodies, such as flapping hands and rocking back and forth, alone or in a combination of actions. The study adds new knowledge about contextual factors surrounding hyper responsive, sensory seeking, and repetitive/stereotypic behaviors engaged in children with ASD in their homes. Naturalistic video observations capture children as they really are, not influenced by unexpected, unfamiliar, and surprising stimuli, which affect children with ASD adversely and can alter results of the study. There's no place like home, also applies to them! References - 1. Kirby, A.V., Boyd, B.A., Williams, K.L., Faldowski, R.A. & Baranek, G.T. (2016). Sensory and repetitive behaviors among children with autism spectrum disorder at home. Autism, 1-13, DOI: 10.1177/1362361316632710 - 2. Autism Speaks: What is Autism - Symptoms Also interesting: Autism Parenting Magazine: Autism Meltdowns FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial --- ## Implementing Tailored Activity Programs URL: https://noldus.com/blog/implementing-tailored-activity-programs Published: 2016-08-02 15:30:00 Description: Tailored Activity Programs (TAP) have been shown to have significantly reduce behavioral occurrences in dementia patients and improve engagement and positive behaviors. Sometimes pharmacological strategies can hurt more than they help. This is why non-pharmacological strategies are meant to be used as the first-line in the treatment of patients, but it can be difficult to tell which strategies should be used with dementia patients in hospitals. Implementing Tailored Activity Programs for Hospitalized Dementia Patients Tailored Activity Programs (TAP) have been shown to have significantly reduce behavioral occurrences in dementia patients and improve engagement and positive behaviors. Although TAP has been used in homes and residential care, this study was a pilot for applying this strategy to dementia patients in hospitals. By using the strategy, researchers aimed to find a way to increase positive behaviors of patients with dementia. Behavioral symptoms and dementia One of the largest difficulties with dementia patients is that with the decline in their mental state, they start to have cognitive functional challenges. This results in increased negative reactions to their environment. Behavioral symptoms, such as agitation or aggression, can cause an increased risk of admission for dementia patients into both psychiatric and non-psychiatric hospitals. A goal of TAP is to address these behavioral symptoms by identifying patient interests and their abilities to perform tasks, thus creating a tailored activity. These activities are meant to give the patient a way to positively reengage with their environment, which will allow a higher frequency of positive behavioral states. Implementing a TAP in a hospital setting Laura Gitlin and colleagues studied the feasibility of implementing this program in hospitals. It not only aimed to evaluate the reaction of the patients to the program, but also the reaction of the hospital staff. After being evaluated by occupational therapists, patients were given three activity prescriptions and a schedule for when these activities were to be performed. These activities varied depending on the level of cognitive functioning for the patient. The recreational therapists and certified nursing assistants were then trained in how to help the patient complete these prescriptions. The Observer XT was used to code video recordings. The first video recordings were of the patients within three days of admission prior to the occupational therapist's activity prescriptions as a baseline. The patients were also observed in up to six of the TAP sessions. There were 11 categories for verbal behaviors, including positive, repetitive, aggressive, delusions, and depressive. As for nonverbal behaviors, there were 12 categories, including positive gestures, aggression, eyes closed, somatic, and distracted. This behavioral coding occurred in 10 second intervals. A month after patient discharge from the hospital, the family satisfaction with the care and if the prescribed activities were still used at home was determined by a brief telephone survey. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Results of the study This was a pilot study with a small sample size, so findings cannot be considered definite. However, the findings in this study did indicate that implementing a TAP in a hospital for dementia patients could have a positive impact. The increase in positive behaviors supports the feasibility of this program. Results overall were encouraging with increases in pleasure and decreases in anxiety and anger compared to the baseline results. Many of the families when contacted a month after discharge were highly satisfied with the program and over 50% of the total activities prescribed were used at home. On the side of the hospital staff, the results appeared to be positive as well. Though staff may have been hesitant at first with the program, by the end they had embraced it. It was able to fit within the work flow of the hospital and readiness of the staff improved. Upon completion of the study, staff continued to use the program. TAP effectively engages patients and results in positive responses with no apparent harmful results. Overall, it appears to be a successful strategy for treating dementia patients, though there is still much research to be done on evaluating TAP treatment effects in a hospital setting. References Gitlin, L.N.; Marx, K.A.; Alonzi, D.; Kvedar, T.; Moody, J.; Trahan, M.; Van Haitsma, K. (2016). Feasibility of the Tailored Activity Program for Hospitalized (TAP-H) Patients With Behavioral Symptoms. Gerontologist, 00, 1-10. --- ## Students’ first contact with The Observer XT URL: https://noldus.com/blog/animal-husbandry Published: 2016-07-08 14:00:00 Description: Prof. Dr. Stefanski and Dr. Flauger explain why it is important to introduce students to professional software tools at an early stage. Systematic behavior research in farm animals has increasingly gained importance, especially during the last years. Since the intensification of animal husbandry has substantially enhanced the discrepancy between natural and artificial environment, the following questions arise: What are the prerequisites for an animal to be able to show its full range of social behavior? How much space do animals require? What is the optimal group size? The close monitoring of the social behavior of pigs, cattle, poultry and horses plays a major role in terms of welfare assessment and health research. Introduce students to professional software For Prof. Dr. Volker Stefanski and Dr. Birgit Flauger of the University of Hohenheim, it is very important that Bachelor and Master students of Agricultural Science and Agricultural Biology are introduced to professional software tools to analyze the behavior of animals at an early stage. The focus of their research at the Department of Behavioral Physiology of Livestock are the effects of endogenous and exogenous factors on the neuroendocrine-immune-network and the behavior of farm animals. Basic research is performed for a better understanding of the interaction between animals and their environment, and the consequences for health and productivity of farm animals. In addition, the department also conducts applied research in order to provide practical advice on animal welfare and the production of high-quality food. Projects in the field of farm animal behavior Bachelor and Master degree students are introduced to the professional software package in different courses and seminars, and are therefore well-prepared for their Bachelor or Master theses in which they realize own projects in the field of farm animal behavior. In the last few years, students observed and analyzed aggressive behavior and nearest neighbor choice in pregnant sows, activity in growing pigs, behavior during novel object tests in piglets, and social behavior in horses. Some of their results have already been published in final degree theses or as conference talks and posters. Consistent positive feedback "We are very pleased to have the opportunity to use The Observer XT in our courses. It is always fascinating to see how the students are at first overwhelmed by all the possibilities of the program. But already within a few hours they can easily deal with the applications. The feedback of students concerning handling and working with The Observer XT has been consistently positive. As lecturers we have also experienced The Observer XT as a userfriendly and time-saving software package which can easily be introduced especially for students who work in the field of behavioral observations in farm animals, even if they use this software for the first time." - Birgit Flauger, Christiane Schalk More information Contact details: Prof. Dr. Volker Stefanski Dr. Birgit Flauger Christiane Schalk University of Hohenheim Institute of Animal Science (460) Behavioral Physiology of Livestock (460f) Garbenstr. 17 70599 Stuttgart For more information about the Department of Behavioral Physiology of Livestock, visit their website. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial --- ## In-home video recordings provide measure for more objective comparisons URL: https://noldus.com/blog/in-home-video-recordings Published: 2016-06-28 16:45:00 Description: Edelson and her colleagues from the Nestlé Research Center in Sweden studied parent-child interactions during meal time using in-home studies. Who doesn't know Jo Frost, A.K.A. the Super Nanny[1]? Her television show has aired across Europe, the UK and the US; currently, she is starring in a Netherlands-based version, where she visits Dutch families. Although I don't have any kids, I watch this show quite regularly with great interest to see how families function. This super nanny keeps telling parents that children also have to eat healthy as part of her program to correct poor behavior. Many parents forget how proper nutrition can influence behavior. But many parents then ask: how do we get our kids to eat more fruits and vegetables? How in-home video recordings provide accurate measure and allow for more objective comparisons Eating healthy Lisa Edelson and colleagues[2] from the Nestlé Research Center in Sweden studied how parents' prompts to eat fruits and vegetables are related to children's intake of these foods. They are convinced that a better understanding of this process will help promote healthy eating habits. As the best place to look at typical eating behavior is in the home, not in a lab setting, Edelson and her colleagues studied parent-child interactions during meal time using in-home studies. Unobtrusive observations Seventy-five families participated in the study. They were given two video cameras and were instructed to video record each occasion over the course of two days when their toddler ate or drank. No researcher was present in order to disturb the natural setting as little as possible. In studies like these, videos taken in an in-home study need to be stored with great attention; therefore, videos were gathered and stored safely, on a password-protected server. Behavioral analysis Afterwards, the researchers from Nestlé analyzed the videos and coded behaviors of interest using The Observer XT software. This type of systematic coding allowed them to look at patterns that would be missed using a checklist-style questionnaire. It also created the possibility to identify the order of behaviors, including how the parents responded to the child's actions and vice versa. Getting food into your child Results from this study suggest that many parents were generally most concerned with getting food into their children. Better something than nothing right? However, results indicate otherwise. On the list of no-go areas there is the 'reward your child with a sausage' (freely translated) technique. Edelson and colleagues explain that parents who offered other food as a reward for eating the less desirable food were found to be the least successful. The study showed that children were easily distracted by this other food reward and wanted it immediately. Therefore, this is a technique to be discouraged. According to the researchers, parents who gave neutral prompts such as 'eat your peas' or 'try your hot dog' with a neutral or positive tone of voice were most successful. Children who ate the most vegetables had parents who used more 'reasoning' prompts, explaining to the child why they should want to eat the food. Edelson and colleagues explain that this may have an effect on internalized motivation to eat these foods, and they recommend researchers to look into this effect in a future study. In-home video recordings The way this research was carried out has great advantages compared to questionnaire-only research. Questionnaire formats may be limited in measuring parents' use of specific feeding practices. It is important for researchers to learn about these feeding practices, which are specific behavioral strategies parents use to control what, how much, or when their child eats, such as pressure to eat, restricting foods, or making foods available in the home. As we know that self-report can be unreliable, studies that only collect this type of data after the fact, and not during meal time, may be missing certain aspects of feeding practices. In this case from Nestlé, behavioral observation provided the researchers a more accurate measure and allowed for more objective comparisons between participants. Lisa Edelson and colleagues tell us: "In addition to its objectivity, behavioral coding also has the advantage of capturing patterns that would be missed using a checklist-style questionnaire as it is possible to identify the order of the behaviors, including how the parents responded to the child's actions and vice versa". Home invasion? I don't think so By using portable recording devices, Edelson and colleagues were able to observe these parent-child interactions in natural settings without, and I quote "the disruptive influence of having observers physically present in the room". I've learned from my colleague Xandra (who just blogged about Quantifying Ethnography) that ethnographic research with a researcher present in a home situation is quite normal but for many researchers today, IP cameras or even cameras integrated in tablets or mobile phones are the best way to follow their respondents' every move. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - jofrost.com - Edelson, L.R.; Mokdad, C.; Martin, N. (2016). Prompts to eat novel and familiar fruits and vegetables in families with 1-3 year-old children: Relationships with food acceptance and intake. Appetite, 99, 138-148. --- ## Declared vs revealed data URL: https://noldus.com/blog/declared-vs-revealed-data Published: 2016-06-02 15:00:00 Description: How do consumer researchers get valuable data? Consumer and market researchers can turn to observation and experimentation to observe consumers. Declared vs. revealed data. How much do you like a store’s logo? When do you moisturize? How often do you buy new razor blades? Where in your refrigerator do you store eggs? These are exemplary questions to which consumer researchers badly want to know your answers. Liking leads to buying, so how much you like the logo can influence you going to that store over a competing one. When you moisturize, and how much, can influence the type of moisturizer you buy and how often you buy it; the same goes for razor blade usage. And if an appliance company spends the time to design the interior of a refrigerator with a specific use in mind, it is desirous for them to know if consumers actually use the refrigerator that way! Traditional methods in consumer research So, how do consumer researchers get at these valuable answers? The traditional methods include interviews, surveys, and focus groups. With these, consumers can answer honestly and accurately…or can they? All of these mechanisms fall under the heading of self-report – consumers provide answers directly to researchers about their habits and practices. These studies could be done in a variety of ways, each of which have pros and cons:  Method Pros Cons Surveys - Gather a lot of data - Reach many respondents - Inexpensive - A lot of data to process and analyze - Low response rates - Very susceptible to question bias Focus Groups - Easily get at broad issues - Allows for elaboration - Respondents can interact, which can promote deeper insights - Target very specific demographic - Represents a small sample size - Worry over what others think may skew respondents’ answers - Moderator must remain impartial - Costly Interviews - Gather in-depth answers - Obtain personal interest stories - Difficult for researcher to remain impartial - Costly Consumer and market researchers have to decide which of these is right for them, based upon the type of study being conducted. Self-reporting bias Once that choice is made, there are some biases that are inherent with any self-report. Two types tend to come to the forefront1: - Unintentional reporting bias: participants forget about their purchasing habits, and so fail to report them accurately. - Intentional reporting bias: participants want to be seen in a favorable light, so they aren’t fully truthful regarding their purchasing habits. With both of these biases, consumers aren’t intending to mislead researchers, but for either (or both) reasons, they’re unable to fully explain their habits. Further impacting the use of self-report is evidence that consumers are not always aware of why they purchase a specific good, or even what happens during the purchase process. Often purchases occur out of habit and routine, or while the consumer is distracted, so accurate self-reporting can be difficult. Failures in self-report don’t just occur in consumer research – in many areas, people are unable to accurately report on their habits2. Declared vs revealed data When self-report fails, what can researchers do? One option is to look at actual consumer behavior. Why do we, as market researchers, want to get into anything as difficult as measuring behaviors? There are two main reasons. - Actions speak louder than words. - Behavior does not always match what people think they will do. Observation and experimentation Knowing this, consumer researchers can turn to observation and experimentation to observe consumers as they obtain, consume, and dispose of products and goods. Let’s assume a consumer states in a focus group, or on a survey, that she likes Brand X’s yogurt and plans to buy it. The question then becomes: when she’s in a store, does she actually BUY Brand X’s yogurt? Or does the new packaging of Brand Y, which she previously overlooked, now jump out to her and she buys Brand Y yogurt instead? By observing a consumer as she is shopping, market researchers can better understand decision making that happens at the shelf. Similarly, a skin care company has received self-report data that women of a certain age group find moisturizer to be very important to their daily skin care routine…yet these women are not buying moisturizer at the rate that would be expected from daily use. How do researchers delve further into the skin care routine if self-report data isn’t reliable? The only real way is through actual behavioral observation; to record and note what behaviors women engage, in their homes, related to skin care. Observing consumer behavior Observing behavior, in a store or in the home, can allow researchers a better look into what consumers actually do, and not just what they say they will do. There are pros and cons with this methodology as well:  Pros Cons - Very in-depth - Note exactly what consumer does - Note many activities, particularly when video capture is employed - Less subject to researcher bias - Easily analyze larger data sets - A lot of data to process and analyze - Time consuming - Requires a priori knowledge of anticipated outcomes - Costly Again, consumer researchers need to assess these pros and cons prior to conducting an observational study. But what about trying to influence the consumer before she ever makes a purchase? In our example above, what did Brand Y do to get the consumer to notice them, when previously she was a Brand X loyalist? Self-report vs. observational research Here is where consumer researchers can turn to experimentation. There are many methods that can be put into place3, and this includes going back to self-report. If we want to ask someone whether they like a product’s packaging, we can do that – simply ask. The consumer can then rate the package on a scale (let’s say 1-5, 5 being the best), and we can compare that to the rating of a competitor product.  But what happens when the researcher asks the consumer “Why did you rate Brand X as higher?” and the answer comes back “I don’t know”? Here is where self-report fails, and behavioral observation can only shed a tiny amount of light. In these situations, it’s better for the market researcher to focus on the unconscious motivators of behavior, and the best place to start is by looking at emotion4. LABEL Title Learn more FREE WHITE PAPER: How to build an consumer lab Do you want to learn more how to set up a consumer lab? Read on for the perfect tips & tricks! - Which requirements do you need? - Do participants walk around the lab? - Download this free 'how to' guide!  Download LABEL Title Learn more Declared vs revealed data Applying emotion research properly can provide researchers with a very powerful tool. Understanding how emotions affect the decision making process arms marketers with a wealth of information. Indeed, advertising researchers continually take advantage of our emotions: they include cute animals and babies; remind us of when we were kids; condition us to certain jingles, etc – all of which is designed to create an emotional bond between the consumer and the product. Being able to accurately measure consumer emotion provides insights that would be hidden if researchers were to only use self-report. In one example, we were tasked by a shaving company to examine emotional reactions while using premium and non-premium razors – how are consumers reacting to these razors during product use? Is this even a valid way to assess “likeability” of a razor? By assessing facial emotions as women shaved their legs, we obtained deeper insights than via self-report alone. One respondent self-reported similar feelings of “liking” for each razor type in the post-usage assessment, but during use she actually cut herself with the premium razor and expressed negative emotions on her face that she did not verbalize - the depth of her negative emotions during usage could not have been assessed from self-report alone. Actually measuring consumer behavior, which can range from taste tests to shopper behavior to usage in the home, provides additional insights that, often in combination with standard measures of self-report, provides consumer researchers with a better look into the consumer as a whole. And, as a way of showing how in-the-moment emotion assessments can work in real-world contexts, check out this video below. References - http://blogs.bmj.com/injury-prevention/2015/06/14/self-report-versus-observation/ - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2588639/ - https://www.youtube.com/watch?v=dN5lpRWms8I&index=2&list=PL84g9FUImokBT5Rio-5cCw7kP2igA2bia - http://www.quirks.com/articles/2016/20160508.aspx --- ## How to use CatWalk XT and Incapacitance Tester in non-clinical pain research URL: https://noldus.com/blog/how-use-catwalk-xt Published: 2016-05-13 13:36:00 Description: Heta Svard from Orion Pharma studies pain and neurological disorders and resports on recent research. Today we have another guest blog post for you! Heta Svard from Orion Pharma studies pain and neurological disorders and will be presenting a poster on a recent study at Measuring Behavior 2016 in Dublin this month! I encourage you to pay her a visit (poster no. 39), but for now, you can read about her study in this post. Thanks, Heta! CatWalk XT is an apparatus for quantitative analysis of gait and motor performance in rats and mice. Gait analysis is typically used for studying locomotor effects of spinal cord injuries in rodents. In the Central Nervous System (CNS) research group at Orion Pharma, we study pain and neurological disorders. This includes testing efficacy of novel analgesics in vivo in rats and mice. Our interest has been whether CatWalk XT gait analysis could be used in our research. Measuring pain in rodents is challenging due to their prey nature to hide pain. Therefore, assessing spontaneous non-evoked behaviour, such as walking, rather than evoked behaviour (i.e. hypersensitivity to mechanical or thermal stimuli) would give more reliable results. We thought CatWalk XT could serve as an ideal tool for our needs, but the stumbling block with using the system was the great number of parameters it spouted. Which of them, if any, were relevant for our use? There were no published studies where CatWalk XT was used in pain research, but one recent from Ängeby-Möller et al. (2015) on analgesic research, where they used an in-house built gait analysis system for rodents. We decided to try and adapt the findings of Ängeby-Möller and colleagues to the commercially available CatWalk XT system and to compare the results obtained from the CatWalk XT (pain at walking) system to data from the Incapacitance tester (pain at standing). Figure 1. CatWalk XT system measured walking pain. When the rat walks, body weight can be distributed between all four legs and the three normal legs can compensate the load of the injured paw. What did we aim at? Our main aim was to produce a method with high translational validity to study efficacy of novel analgesics in rats with inflammatory joint pain. Because examination of joint pain in osteoarthritis patients involves assessment of pain during walking and standing, we aimed to measure the same endpoints in rats. To attain the goals, we needed to i) induce inflammatory joint pain in rats, ii) try to relieve the pain with clinically used analgesic, and iii) quantify the pain in walking and standing in i) and ii). How did we do it? To induce inflammatory joint pain in rats, we injected Freund's complete adjuvant (CFA) into their left ankle joint. CFA contains heat-killed and dried Mycobacterium tuberculosis and is widely used in preclinical research to induce inflammation in research animals. After the injection, the rats were daily treated with naproxen, pregabalin or vehicle for four days, and they went through gait analysis on CatWalk XT (fig. 1) and weight bearing measurement on Linton's Incapacitance tester (fig. 2). We measured the following default parameters in CatWalk XT: regularity index, duty cycle and base of support, and maximum area and mean intensity. We used the latter two in calculating additional gait parameters – weight bearing percentage and guarding index. Linton's Incapacitance tester measured static weight bearing as force exerted by each hind limb. Using these data, we calculated the percentage weight bearing of each hind limb. Figure 2. Linton's Incapacitance tester measured standing pain as weight bearing by each hind leg. While standing on the hind legs, the rat cannot utilize its tail or front legs in body weight bearing. What was the outcome? Intra-articular injection of CFA caused long-lasting inflammation, limping and guarding of the paw and uneven weight distribution between the hind paws during walking and standing. In the CatWalk XT, these were indicated as changes in each paw's weight bearing percentage and guarding index. Other gait parameters were also changed but the effects on those were more transient with greater inter-individual variance within the treatment groups. Naproxen partially reversed the changes in gait and static weight bearing, while pregabalin did not. What does this all mean? Naproxen is an anti-inflammatory medicine, having efficacy in patients with inflammatory joint pain. Pregabalin is used for neuropathic pain and does not usually relieve inflammatory pain. Our results show that naproxen reduced walking and standing pain in rats but pregabalin did not – as in osteoarthritis patients who suffer from inflammatory joint pain. This suggests that the method is sensitive with high translational value, and the effects of the drugs on walking and standing pain were quantifiable with CatWalk XT and Linton's Incapacitance tester. Guarding index was found to be the most robust and sensitive CatWalk XT parameter for this model to reveal the effects of CFA and drugs on walking pain. Weight bearing percentage was a sensitive parameter to indicate drug effects on pain at standing. Altogether our results support the use of rat CFA model of inflammatory joint pain together with CatWalk XT and Incapacitance tester in pain and analgesic research. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References Ängeby Möller, K.; Berge, O.G.; Finn, A.; Stenfors, C.; Svensson, C.I. (2015). Using gait analysis to assess weight bearing in rats with Freund's complete adjuvant-induced monoarthritis to improve predictivity: Interfering with the cyclooxygenase and nerve growth factor pathways. European Journal of Pharmacology, 756, 75-84. Heta will be presenting her poster on May 25th at the Measuring Behavior 2016 conference in Dublin. --- ## The bat - moth aerial battle in 3D URL: https://noldus.com/blog/the-bat-moth-aerial-battle Published: 2016-05-05 13:44:00 Description: Moths arrived first on the evolutionary stage; when much later on bats appeared with their sophisticated apparatus for echolocating prey, moths were forced to change or die. Any insect that flies at night must deal with bat predation. Take a moth, for example. Moths arrived first on the evolutionary stage; when much later on bats appeared with their sophisticated apparatus for echolocating prey, moths were forced to change or die. Some species developed ears to hear the approach of a bat; this generally evokes evasive flight maneuvers like loops and dives. Other species acquired distasteful chemicals that gave them a repugnant or poisonous taste. Some even developed the ability to produce sounds that seem to confuse, and sometimes thwart, an attacking bat. A never-ending battle Not less fascinating is the set of countermeasures that bats have taken. Some bats use a quieter mode of echolocation, calling at a reduced volume and further reducing the volume of their clicks as they close in on prey moths. In order to better understand this battle, we need to know what each counterpart does, at what time and where. In other words, we need accurate recording of the position of the bat and the moth in the three dimensions. At Dartmouth College, Hanover, USA, the research group led by Dr. Hannah ter Hofstede has chosen the 3D approach to the study of this interesting interaction. They will use the Noldus Track3D system, an add-on to the EthoVision XT video tracking suite, to track bats and moths in a large outdoor enclosure. The bat-and-moth flight room Hunting bats are usually filmed in small areas around ultraviolet lights which are placed to attract the prey moths. In contrast with this approach, a large, outdoor flight room ensures more natural behavior of both predator and prey. This setup has, however, a few challenges. First, the size of the flight room (approximately 6 x 5 x 3 m (L x W x H)), in which a small moth must be filmed and detected by software. Infrared lamps must provide enough light without interfering with the animal's behavior. Furthermore, it must be possible to simultaneously track two animals (bat and moth) without having to mark them. Even before the flight room was set up, we modeled the space in which the animals would fly. This was done to acquire important information, like the optimal camera position, the lenses being required, and to design the calibration frame (see below). 3D calibration Track3D is based on video-tracking of the animals from two camera views. In order to reliably reconstruct the position of the animals in the three dimensions, accurate calibration is a must. We designed a calibration frame that could be assembled in the flight room, just the time needed for calibration. The calibration frame has a number of reference markers with known 3D coordinates. The calibration error, which measures the deviation from the expected marker positions, was just 7 millimeters, in a room of approximately 6 x 5 x 3 m. This gives an idea of the accuracy of the model that reconstructs the 3D trajectory based on the tracks recorded from the camera views. Watch the bat and moth 3D tracking video on YouTube The first 3D tracks After releasing the moth and the bat, we recorded video from two cameras using Media Recorder. The resulting video files are then analyzed with EthoVision XT, which tracks bat and moth and saves their 2D coordinates from each camera view. In the Track3D add-on software, we combine the 2D tracks to create a 3D track for each subject. See an example in the video. As soon as the bat approached, the moth changed dramatically its behavior. Together with an increase in speed, the moth showed a series of turns, spirals and loops making its trajectory much less predictable. Eventually, the bat did not manage to catch its prey. Track3D produced highly reliable data. The degree of uncertainty in the 3D positioning was just 2 pixels. Such high accuracy is only possible when you have a good video tracking system like EthoVision XT, and software with sophisticated 3D calibration and positioning algorithms, like Track3D. Dr. ter Hofstede and her group also use Track3D in experiments where moths fly in acoustic chambers. There, the trajectory of the moth in response to sound stimuli is analyzed in a way similar to that described above. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial This article was written by Fabrizio Grieco, project leader of Track3D. --- ## Understanding adolescent emotions URL: https://noldus.com/blog/understanding-adolescent-emotions Published: 2016-04-12 15:15:00 Description: How are adolescents’ emotions socialized by mothers and close friends? A recent study focuses on dealing with depression in adolescence. I was waiting for my exam results, and so was the son of our neighbors. And then there was a bang. A really loud one. I could guess the outcome of his exam simply by hearing that bang. Afterwards we indeed heard that he didn't pass his exam and that the telephone suffered the consequences… Emotions are hard to deal with. I would have felt the same if I had to retake exams. When you are young and experience so many challenges, it is hard to deal with emotions. During my adolescence, there were computer games wanting to be played, friends wanting to go out with, and TV programs wanting to be watched…which resulted in schoolwork receiving a little less attention. Dealing with depression A few days ago, I read a report about adolescent emotions from the NIMH (Bethesda, MD). It stated that in 2014, 11% of the 12 to 17 year-olds in the US reported at least one major depressive episode over the period of a year [1]. That's almost 3 million adolescents! Jessica Lougheed from Queen's University, Kingston, Ontario, and colleagues explain that depression is considered a disorder of emotion regulation, as it is associated with difficulties in regulating both positive and negative emotions. Regulate your own emotions In adolescence, the ability to regulate emotions is heavily challenged by numerous biological, social, and psychological changes. By learning to adequately regulate emotions, people are attempting to control the intensity, form, and duration of the emotion [2]. Adolescents should learn to increase or decrease the intensity of the moment. I now see that it's this mechanism making emotions stronger. Observing interactions Jessica Lougheed and colleagues set up a study in order to understand how adolescents' emotions are socialized by their mothers and close friends, since both mothers and close friends play important roles in adolescent lives. In total they observed 83 adolescents. They recorded interactions on video and coded interactions using The Observer XT professional analysis software. Understanding adolescent emotions The sessions were conducted either in participants' homes or in a private location at their school. The task given by the researchers was an interaction task consisting of two 7 minute conflict discussions. Prior to the interaction task, the participants acclimatized to the video camera in a 'warm-up' discussion about how to plan a party. According to Lougheed's study, this work is the first step towards understanding the microsocial processes in both maternal and peer relationships that can factor into regulating adolescent depressive symptoms. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Depressive symptoms under investigation The researchers found that mothers were less likely to show supportiveness to adolescents with higher depressive symptoms, regardless of adolescents' expressed emotions. Peers were less likely to up-regulate adolescent positive emotions for adolescents with higher depressive symptoms. The researchers conclude that maternal and peer emotion socialization play a role in late-adolescent depressive symptoms, but in different ways. There is a possible confound in the study: adolescents with depressive symptoms may also have mothers with depressive symptoms, Lougheed et al. note. Future studies should include measurements of all interaction partners' depressive symptoms (for example, mothers and peers in this study). Furthermore, Lougheed et al. indicate that an important direction for future research will be to incorporate both microsocial and longitudinal designs. They believe this will shed light on the specific social processes involved in the etiology of depression, as well as how specific features of depressive symptoms affect real-time social dynamics. References - 1.NIMH: Major Depression Statistics - 2.Wikipedia: Regulation of Emotion - 3.Lougheed, J.P.; Craig, W.M.; Pepler, D.; Connolly, J.; O'Hara, A.; Granic, I.; Hollenstein, T. (2015). Maternal and peer regulation of adolescent emotion: associations with depressive symptoms. Journal of Abnormal Child Psychology, doi:10.1007/s10802-015-0084-x. --- ## Become and stay aware about children with autism URL: https://noldus.com/blog/children-autism Published: 2016-04-06 09:55:00 Description: Autism is a developmental disability that remains with a person for his or her whole life. The World Autism Awareness Day tries to bring awareness to this growing health concern. Last week I had a chat with a friend of mine whose eldest son (8 years old) was diagnosed several years ago with Autistic Spectrum Disorder (ASD). She told me about a conversation she and her husband had with a speech therapist, who explained to them that when someone asks their son a question or tells him something to do, it usually takes 7 seconds before his brain processed this information. Imagine that, 7 seconds – that's quite a lot. In those 7 seconds many other words can be said or questions can be asked. But for this little boy it means that it is important to speak slowly and give one instruction at a time, or you will likely get little to no response, or only partial task completion. Become and stay aware about children with autism When there is a lack of understanding, you don't realize that he needs this time to see the whole picture. When you have to deal with this over and over again, every single day, you can become very frustrated and annoyed by the child's seeming failure to understand, or worse, lack of desire to listen. FREE WHITE PAPER Autism Research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Download World Autism Awareness Day Autism is a developmental disability that remains with a person for his or her whole life. It is a neural development disorder that affects the ability to socialize normally by impacting both verbal and non-verbal communication. Every year, on the 2nd of April, World Autism Awareness Day tries to bring awareness to this growing health concern. Respect, Acceptance, and Inclusion are the themes this year. Speaking with my friend helped me become aware that when I talk to her son, the resistance I sometimes experience is not a result of a child who doesn't care or doesn't feel like listening or talking to me; it just takes him additional time to process what I'm saying to him or asking of him. Most of the time, I'm not aware of that keep speaking, telling him more information and asking him more questions. I understand now I need to respect his disabilities and accept that it takes time to have a talk with him. Acting techniques can help improve social cognition In 2015 researchers at Vanderbilt University, Nashville, USA, used a randomized trial to investigate improvements in social competence for children and adolescents with ASD, ages 8 to 14. They evaluated and extended the impact of a peer-mediated, theatre based intervention. They emphasized that acting is an inherently interactive process that involves many aspects of socializing: observing, recognizing, interpreting and expressing thoughts, feelings and ideas. Therefore, the training in and practice of acting techniques had the potential to target basic shortfalls in ASD, such as communication with others, flexible and imaginative thinking, and theory of mind. They used the SENSE Theatre program, which involves role-playing, improvisation, and play performance. Moreover, this theatre based intervention consisted of peer-mediating: trained peer actors were paired with a child or adolescent with ASD. The third component of the treatment was homework of watching and practicing with video models. The Observer XT was used for the collection, analysis, and presentation of observational data. The researchers found that participation in the theatre intervention resulted in improvement in social cognition for the experimental group. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial What goes on in the head of a child with autism? Autism affects approximately 1 out of every 150 children around the world, girls and boys of all races and in all geographic regions and has a large impact on children, their families, communities, and societies. The diagnosis and prevalence is currently rising in many countries around the world. Caring for and educating children and young people with this condition places challenges on health care, education and training programs. A program like the SENSE Theatre, using peer mediating, could be a valuable contribution in education and symptom treatment. And as for me, I realize it's important to learn more about autism and what goes on inside of the head of someone with autism to expand my relationship with my friend's son, and have more fun together with him. Reference To read more on this study, find the original results here: Corbett, B.A.; Key, A.P.; Qualls, L.; Fecteau, S.; Newsom, C.; Coke, C. & Yoder, P. (2015). Improvement in social competence using a randomized trial of a theatre invention for children with autism spectrum disorder. Journal of Autism and Developmental Disorders, DOI 10.1007/s10803-015-2600-9. --- ## Assessing motor deficits in mice following traumatic brain injury URL: https://noldus.com/blog/assessing-motor-deficits-traumatic-brain-injury Published: 2016-03-31 14:04:00 Description: Today Marcelle Cline and Donna Cross are so kind to share their insights on testing TBI mice with the CatWalk XT system. Half a year ago, I wrote about rats on the CatWalk XT system, and we added a great white paper written by Kristina Ängeby Möller to the collection. Today, I am very excited to tell you that Marcella Cline (University of Washington) and Dr. Donna Cross (University of Utah) are so kind to share their insights on working with mice on the CatWalk XT system in both a blog post and a white paper. Enjoy! Traumatic brain injury (TBI) represents a significant health concern worldwide. While animal models have been remarkably successful in furthering our understanding of TBI, an assessment of subtle motor deficits in mouse models that arise post-injury can be challenging. In this post, we'll outline some of the common tests currently used by researchers to assess motor deficits in mice following TBI, and give you a basic understanding of the protocols used for these tests. Rotarod Perhaps the most common test available to detect motor function in mice, the rotarod test consists of a rotating beam, on which mice are required to walk. The speed of rotation is gradually increased until the mouse falls from the rod or the trial ends, and time spent on the device without falling is recorded. The rotarod is a well-characterized test of gross motor function(1), and has been proven useful in TBI models(2). Gridwalk test The gridwalk test consists of an elevated grid surface (shown: 30 L x 35 W x 31 H cm with grid spacing of 2.5 cm), on which the mouse is placed and allowed to explore. The number of times a mouse attempts to place weight on a foot falling between the wire grids (an action termed a 'foot-fault') is scored. This particular test is especially useful in models of unilateral TBI, as the number of foot-faults made by the affected (contralateral to injury) side can then be compared to the total number of foot-faults made to give researchers an idea of limb bias(see 3). Beam balance The beam balance/walk test, while similar to the rotarod, is useful for measuring more subtle motor deficits. Mice are placed on a long, suspended beam, and allowed to walk from one end to the other. The number of foot-faults (in this case, when a paw slips from the beam) are recorded. As with the gridwalk test, the beam balance is useful when testing unilateral injury models, as it gives researchers the opportunity to analyze countra- versus ipsilateral limb involvement(1). Noldus CatWalk Gait Analysis The CatWalk automated gait analysis system (Noldus Information Technology, Wageningen, The Netherlands) consists of a 1.3-m-long glass plate walkway, into which green light is injected from the side. A camera underneath the glass plane and projected upward records green paw prints as the mouse makes its way across the walkway, from one end to the other. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Following the identification and labeling of each footprint using Noldus software, an extensive array of data related to gait, paw placement and locomotion can be produced and subsequently analyzed. The CatWalk is a highly sensitive gait analysis tool, capable of detecting very subtle motor deficits which tests of gross motor dysfunction (such as the rotarod) may miss. A main advantage of this system over other tests of motor function, is the relative degree of observer-independent assessment and analysis of disrupted gait. This apparatus has been used successfully to detect subtle motor changes in mice following TBI in a number of recent studies(3,4). Proper assessment of the motor deficits associated with TBI is crucial when using mice to model neurological injury. For studies investigating a potential therapeutic intervention for TBI, behavioral tests that can reliably distinguish TBI from non-TBI animals are necessary if researchers hope to detect a drug effect on outcomes. While the tests described here do not represent all of those available to researchers, they are excellent and efficacious measures of motor function, which can be readily implemented in most labs. For most studies, a combination of these tests will provide a sensitive and comprehensive evaluation of post-injury outcome as well as an objective measure of efficacy for therapeutic development in TBI. Marcella M Cline, BS & Donna J Cross, PhD These authors also wrote a white paper with tips and tricks they learned in their research with TBI mice on the CatWalk XT system. Download it now! References - Curzon, P.; Zhang, M.; Radek, R.J.; Fox, G.B. (2009). The behavioral assessment of sensorimotor processes in the mouse: Acoustic startle, sensory gating, locomotor activity, rotarod, and beam walking. In: Buccafusco JJ, editor. Methods of Behavior Analysis in Neuroscience. 2nd edition CRC Press; Boca Raton, 20–31. - Onyszchuk, G.; Al-Hafez, B.; He, Y.; Bilgen, M.; Berman, N.; Brooks, W. (2007). A mouse model of sensorimotor controlled cortical impact: Characterization using longitudinal magnetic resonance imaging, behavioral assessments and histology. Journal of Neuroscience Methods, 160(2), 187-196. - Cross, D.J.; Garwin, G.G.; Cline, M.M.; Richards, T.L.; Yarnykh, V.; Mourad, P.D.; Ho, R.J.Y.; Minoshima, S. (2015). Paclitaxel improves outcome from traumatic brain injury. Brain Research, doi:10.1016/j.brainres.2015.06.006 - Neumann, M.; Wang, Y.; Kim, S.; Hong, S.; Jeng, L.; Bilgen, M.; & Liu, J. (2009). Assessing gait impairment following experimental traumatic brain injury in mice. Journal of Neuroscience Methods, 176, 34-44. --- ## How to measure complex exploratory behavior in larval zebrafish URL: https://noldus.com/blog/exploratory-behavior-larval-zebrafish Published: 2016-03-22 14:17:00 Description: Behavioral tests as the open field may overlook complex patterns of behavior. Today our guest bloggers explain about a new set-up for zebrafish larvae. The Zebrafish Multi-Chambered Exploratory Test (ZEMCET) Today we have another guest writing for us, or actually two. I met Frank Scalzo (Bard College, New York) at last year's annual meeting of the Society for Neuroscience in Chicago and I was very curious to find out more about their research using multi-chambered set-ups for their zebrafish larvae. Frank M. Scalzo and his colleague Brandon Chen were kind enough to share their insights in this blog post. Enjoy! Limitations of 'simple' tests Behavioral tests such as the open field test (or novel tank test for adult zebrafish), mazes, and the like, have been used as the standard for characterizing a variety of behaviors in a range of animal models. However, these methods are inherently limited in the number and specificity of behaviors that can be measured. For example, the open field test has commonly been used to determine anxiety-like behavior expressed by measures such as thigmotaxis. While there is great merit in such tests to identify different behavioral phenotypes and great utility in their simplicity, the lack of complexity in their design may also result in overlooking more complex patterns of behavior. Measuring complex behaviors Such behavioral patterns may provide insight into fundamentals of behavioral regulation, as well as how environmental (e.g., light versus dark), genetic or pharmacological manipulations affect behavior. For example, exploratory behavior has been measured in zebrafish larvae using EthoVision XT by tracking movement in a single circular or square well in standard multiwell plates. In order to measure more complex patterns of exploratory behavior in larval zebrafish, we have developed the Zebrafish Multi-Chambered Exploratory Test (ZEMCET) to characterize complex exploratory behavior across multiple wells in zebrafish larvae. The ZEMCET The ZEMCET utilizes a 6-chamber testing arena in which larval zebrafish are allowed to move freely between multiple chambers (Figure 1). The channels between the chambers were made by carefully melting the dividers of adjacent chambers. Using video tracking in Ethovision-XT and the ZEMCET, we observed and measured behaviors in larval zebrafish that are not obtainable by using conventional testing methods (i.e. a single well). Figure 1. The ZEMCET consists of two, six-well testing arenas. Some wells in each arena are connected by a channel allowing zebrafish larvae to travel between individual wells and thus, the possibility to explore all six-wells. The asterisks indicate the starting chamber. EthoVision XT enabled us to make conventional measures of movement in a single well and more importantly, allowed for the measurement of larval movement between chambers, resulting in a more comprehensive analysis of swimming behavior and exploratory behavior. Figure 2. Trackings from single zebrafish larvae in the ZEMCET. The ZEMCETs on the right side of the panels show the path of larval movement between chambers. The ZEMCETs on the left do not contain a larva. ZEMCET and video tracking: a powerful combination While conventional behavioral methods still provide valuable behavioral information, the ZEMCET can be employed to gain more depth into the complex behavioral repertoire of larval zebrafish. In a recent study we used the ZEMCET to measure exploratory behavior in 5-day old larvae and found that larvae are capable of actively moving into all six chambers (Figure 3). When coupled with EthoVision XT, the ZEMCET becomes a powerful tool with numerous possibilities for measuring a variety of behaviors. For example, the ZEMCET also allows for a more detailed measure of thigmotaxic behavior by allowing for the detailed analysis of the path larvae take when transitioning from chamber to chamber. Figure 3. The left panel depicts total distance moved in the ZEMCET over a 15 minute observation period. The right panel shows the pattern of transitions between different chambers within the ZEMCET. With the ZEMCET, a deeper understanding of the behavioral repertoire of larval zebrafish can be elucidated and much progress can be made in identifying the effects of environmental, pharmacological, genetic and other manipulations on behavior that until now, have not been measureable with conventional testing approaches. By Brandon Chen and Frank M. Scalzo, PhD Psychology Program, Bard College, 50 Sands Road, Annandale-on-Hudson, New York 12504; Scalzo@bard.edu FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Get your Free trial --- ## Who is the best product representative? URL: https://noldus.com/blog/who-best-product-representative Published: 2016-03-17 12:11:00 Description: We all have our favorite celebrities, then there are those we love to hate. Who would you want to pay to represent your product or brand? This week we have a guest blog post from Dr. Lora Becker. She is Director of the Neuroscience Program at the University of Evansville. Her primary research activity seeks to understand human and animal emotions. Thank you Lora for the knowledge and enthusiasm you share in this blog! We all have our favorite celebrities, then there are those we love to hate. Some time it is hard to know if we really like the celebrity because we want to be them or we want to laugh at them. But how do we really react to images of celebrities? Furthermore, who would you want to pay to represent your product or brand? Emotions recognized by software As Jason Rogers and Abbe Macbeth explained to us recently, the answer may lie in specific areas of our brains (fusiform face gyrus and specific regions of the right parietal cortex) that allow us to recognize faces and facial expressions. Current technology can do this, too. FaceReader uses over five hundred points on the face to determine basic emotional expressions happy, angry, sad, scared, surprised, and disgusted, which are expressed by all people, no matter their age or race. One later addition to these 'basic' emotions is 'contempt', which played a major role in Rogers' and Macbeth's recent investigation into the Resting Bitch Face. Liking and disliking celebrities To demonstrate the power of FaceReader to the University stakeholders, we asked participants of a weekend workshop to submit an internet image of a celebrity they 'liked' and one they 'did not like'. These images were arranged in a slideshow movie where each face was displayed for 3 seconds. After the movie, participants were asked to rate the name of each celebrity on a scale of 1 – 5. Like Score: Total number of respondents marking 1 'Like Very Much' and 2 'Like' Dislike Score = Total number of respondents marking 4 'Dislike' and 5 'Dislike Very Much' With this simple survey we may be quick to choose the Son of God to endorse your product or you may walk away from using Donald Trump. However, when faces of the participants were analyzed we see a different story. The image of Jesus Christ lead to the least happy expressions and the most scared expressions. Conversely, the happiest expressions were recorded when Donald Trump was displayed on the screen where both images had the same proportion of surprised looks. It can be suggested that the two images 'got the participant's attention' but then each seemed to elicit an opposite reaction to their survey response. Along those lines, the official wedding family picture of Will and Kate scared the participants (most likely because there were 17 people in the photo!). Other interesting results were found such as Taylor Swift was on the lower end of the survey, scoring a 2 out of 16, but this is explained by the mostly female sample (14 F 4M) where the largest facial expression for her was that of contempt. Of all the images, Bill Cosby and Kim Kardashian elicited the highest record of sad expressions. Although both of these celebrities were disliked in the survey, there is a heartwarming touch of sadness for Mr. Cosby, for the fall of this once revered celebrity. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download --- ## Measuring flow URL: https://noldus.com/blog/measuring-flow Published: 2016-03-15 14:54:00 Description: Real time measurement techniques like FaceReader might be the key to measuring flow in real-time. By Martijn van den Berg Flow is a state in which a person is fully involved in an activity, decreasing self-consciousness and sense of time. This process requires a person to be extremely focused, as well as exactly have the skills to master a task. Achieving flow is desirable, because during flow a person can reach maximum skill level as well as creativity within a domain [1]. However, measuring when a person is in flow and subsequently finding out how to get a person in a flow state is difficult, because flow causes persons to decrease self-consciousness, not recalling to what extent flow occurred [2]. Serious games One of the main applications of flow is within serious gaming. Serious games are games which are used for other purposes than merely entertainment, mostly within education and behavior assessments. Games are a perfect tool for measurement of flow, because these naturally satisfy most of the ten building blocks required for flow [1]: - There are clear goals every step of the way. - There is immediate feedback to one's actions. - There is a balance between challenges and skills. - Action and awareness are merged. - Distractions are excluded from consciousness. - There is no worry of failure. - Self-consciousness disappears. - The sense of time becomes distorted. - The activity becomes an end in itself. Methods of measuring flow Several researchers have developed methods of measuring flow. Examples include interviews and surveys and the experience sampling method [2]. The experience sampling method requires participants to answer a questionnaire at several times during an activity. Doing so, however, interrupts focus and therefore also flow. More recently, several approaches were developed to measure experience, a factor related to flow [3]. This approach follows the building block of measuring whether skills and challenges are in balance, and is therefore more measurable. While conducting a study on TeamUp, an offline virtual game in which four participants cooperate on separate laptops to complete various puzzles, speech and video was recorded to analyze emotions. When analyzing speech, we found that individuals achieving the best time at completing the puzzles were also least aroused by TeamUp (p: 0,422, s<0,001). We also found that valence decreased as participants achieved lower times at completing the puzzles (p: 0,294, s: 0,017). When analyzing facial expressions, we found that mainly happiness and valence decreased as the challenges progressed (s<001). The arousal findings in vocal analysis contradict initial hypothesis in [1] which states that arousal is only achieved at high skill and high challenge provided and [2], which states that flow is more likely achieved at high skill levels. These results can indicate either that the multiplayer nature of this game has an effect on arousal, or that high arousal is also reached at flow in a low skill level. Valence and happiness findings confirm hypothesis by [1], indicating that happiness is not achieved when in flow, but is subsequently caused by flow. Subsequently, correlations between vocal temper and game time were expected, to indicate that participants achieving higher game times would become more frustrated. This could indicate that participants did not achieve frustration (mean: 29,55/100, SD: 5,25), or that vocal analysis is not a valid instrument in measuring flow. Above findings are inductive and experimental. Although a lot of research exists on flow, few approaches exist in computerized measurement of flow. More research towards this subject is the first step in constructing systems which are able to adapt content to skill level. Systems like these can be used to make more immersive games, provide more engaging education and increase employee productivity in a digital environment. Real time measurement techniques like FaceReader (video) and Beyond Verbal (speech) might be the key be able to measure flow real-time. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download References - Csikszentmihalyi, M. (1996). Flow and the psychology of discovery and invention. New York: Harper Collins. - Nakamura, J.; Csikszentmihalyi, M. (2014). The concept of flow. Flow and the Foundations of Positive Psychology, 239-263. Springer Netherlands. - Nacke, L. E.; Drachen, A.; Göbel, S. (2010). Methods for evaluating gameplay experience in a serious gaming context. International Journal of Computer Science in Sport, 9(2), 1-12. --- ## How to get reliable results on object recognition using video tracking URL: https://noldus.com/blog/object-recognition-automated-video-tracking Published: 2016-03-12 13:00:00 Description: In the beginning of this year I wrote a post about the Morris water maze test, a popular and well-validated paradigm to study learning and memory in rats and mice. In the beginning of this year I wrote a post about the Morris water maze test, a popular and well-validated paradigm to study learning and memory in rats and mice. This blog is about another very popular test, the (novel) object recognition task. Novel object recognition This basic idea behind this test is simple; a mouse (or rat) spends more time and attention on a novel object than on a familiar one. If it doesn't, then something must be wrong with its memory. Not surprisingly, the novel object test is a useful method to evaluate the efficacy of memory enhancing compounds [2,6,8]. There are many studies that investigate the basics of learning and memory, and the influence of factors such as gender, stress, and adolescence [4,5,9,10,11]. Then there are studies that focus on chemicals, such as metamphetamine [11] or nicotin. In fact, the nicotinic receptor is a target of many studies on disorders such as Alzheimer's and Schizophrenia [7,8,12,13]. How does novel object recognition test work The set-up of this test is straight-forward and flexible. In the first stage, the animal is trained, which means nothing more than the animal is allowed to explore two (or more) objects to get to know them. After a waiting period, one of the objects is replaced by a new one and the animal is tested to see if it can tell the difference. The waiting period can vary, depending on whether short- or long-term memory is tested. In some cases, both durations of memory are tested. [2,9,10]. Automatic measurement of object recognition Some researchers still believe that manual observation is the only reliable way to execute this test. However, several publications comparing manual against the automatic method, prove otherwise [1,2,4,9]. In fact, this test is easily automated. When you place a camera overhead, automatic video tracking takes care of monitoring the interest your rat or mouse shows in the different objects. But, you want to make sure the animal shows actual interest in the object, faces it and explores it, instead of just accidentally being near it. In other words, knowing the location and position of your animal relative to the object is the only way to really tell if there is actual interest. Can automatic tracking do this? Yes. This answer came many years ago, and it lies in multiple body points tracking. How researchers are using multiple body points tracking Exploration of the object is defined as the animal either touching the object (with any body part, except for the tail) [3] or being in close proximity of the object. The latter is defined as facing the object within a small distance (e.g. 2 cm [3]), or the nose point being within the object zone, usually a couple centimeters around the object. In some instances, you need to be more specific. For example, Benice and Raber [1] defined exploration as the nose point of the mouse being near the object (2-4 cm zone around the object) while the center point of the mouse was outside of this zone. This way, sitting on top of the object was not counted as interest in the object. Smart data selection and analysis To accomplish the automatic measurement of this variable, there are a few simple steps to take when you use software such as EthoVision XT with the Multiple Body Points tracking module. First, define the zones around the objects. Then, after tracking, select your data. Narrow the results down to the data when the mouse has its nose point inside of the object zone, but its center point outside the object zone. Then total time spent or percentage of time spent that way is calculated automatically. To learn more about Multiple Body Points tracking. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial Discover more about automating the novel object recognition test with EthoVision XT and other resources here. To read up on novel object recognition research, see the reference list below. References - Benice, T.S.; Raber, J. (2008). Object recognition in mice using nose-point digital video tracking. Journal of Neuroscience Methods, 168, 422-430. - Chambon, C.; Wegener, N.; Gravius, A.; Danysz, W. (2011). A new automated method to assess the rat recognition memory: Validation of the method. Behavioural Brain Research, 222, 151-157. - Chévere-Torres, I.; Maki, J.M.; Santini, E.; Klann, E. (2012). Impaired social interactions and motor learning skills in tuberous sclerosis complex model mice expressing a dominant/negative form of tuberin. Neurobiology of Disease, 45, 156-164. - Cyrenne, D.M.; Brown, G.R. (2011). Effects of suppressing gonadal hormones on response to novel objects in adolescent rats. Hormones and Behavior, 60, 625-631. - Eiland, L.; McEwan, B.S. (2012). Early life stress followed by subsequent adult chronic stress potentiates anxiety and blunts hippocampal structural remodeling. Hippocampus, 22, 82-91. - Grauer, S.M.; Pulito, V.L.; Navarra, R.L.; et al. (2009). Phosphodiesterase 10A inhibitor activity in preclinical models of the positive, cognitive, and negative symptoms of schizophrenia. The Journal of Pharmacology and Experimental Therapeutics, 331, 574-590. - Haydar, S.N.; Ghiron, C.; Bettinetti, L.; et al. (2009). SAR and biological evaluation of SEN1233/WAY-317538: Novel alpha 7 nicotin acetylcholine receptor agonist. Bioorganic & Medical Chemistry, 17, 5247-5258. - Marquis, K.L.; Comery, T.A.; Jow, F.; et al. (2011). Preclinical assessment of an adjunctive treatment approach of cognitive impairment associated with schizophrenia. Psychopharmacology, 218, 635-647. - McDowell, K.A.; Hutchinson, A.N.; Wong-Goodrich, S.J.E.; et al. (2010). Reduced cortical BDNF expression and aberrant memory in Carf knock-out mice. The Journal of Neuroscience, 30(22), 7453-7465. - Roncarati, R.; Scali, C.; Comery, T.A.; et al. (2009). Procognitive and neuroprotective activity of a novel α7 nicotinic acetylcholine receptor agonist. The Journal of Pharmacology and Experimental Therapeutics, 329, 459-468. - Siegel, J.A.; Park, B.S.; Raber, J. (2011). Long-term effects of neonatal methamphetamine exposure on cognitive function in adolescent mice. Behavioural Brain Research, 219, 159-164. - Sydserff, S.; Sutton, E.J.; Song, D.; et al. (2009). Selective α7 nicotinic receptor activation by AZD0328 enhances cortical dopamine release and improves learning and attentional processes. Biochemical Pharmacology, 78, 880-888. - Werkheiser, J.L.; Sydserff, S.; Hubbs, S.J.; et al. (2011). Ultra-low exposure to alpha-7 nicotinic acetylcholine receptor partial agonist elicits an improvement in cognition. Neuroscience, 186, 76-87. --- ## EthoVision XT and the open field test URL: https://noldus.com/blog/ethovision-xt-open-field-test Published: 2016-02-19 11:26:00 Description: Imagine you are dropped in the center of a wide open field. Would you explore the entire area? Or hunker down around the edges, fearing predators and other unknowns? We recently teamed up with a new partner, Maze Engineers, to extend our portfolio of video tracking solutions. They also have a great blog, and today we would like to share one of their recent posts with you. Find the original article here. Thanks, Maze Engineers, for letting us share this post with our readers! EthoVision XT and the open field test Imagine you are dropped in the center of a wide open field. Would you explore the entire area? Or hunker down around the edges, fearing predators and other unknowns? Your internal state probably impacts how you respond in this situation. Researchers have long used this situational paradigm to test for anxiety-like behavior in rodents. The "open-field test" is most commonly used to test for differences in behavior in groups of animals exposed to, for example, a negative environmental stimuli, or an ameliorative drug, as compared to a control group. Common behavioral metrics for the open field test are a) distance traveled, b) time spent in center of open field, c) freezing and d) rearing (exploratory behavior in which animals stand on their hind legs). Coding an animal's behavior in an open-field test is labor intensive for researchers when performed manually. In the last twenty years, technologies for automatically scoring video recordings of behavior have become a great asset to researchers. Automating scoring videos with EthoVision XT EthoVision® XT, a video-tracking software offering from Noldus, has been used to automatically score anxiety-like behaviors in open-field tests, as well as other behavioral tests. EthoVision® XT software is able to track the center of gravity for animals being observed, and for rodents, the software is sophisticated enough to track the nose point, center point and tail points. In addition to saving researchers time, scoring a behaviors in the open-field test automatically with EthoVision® XT ensures that no human bias or error effects the scoring. This technology has been used in thousands of publications to date. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Open Field Test – Experimental Validation with EthoVision XT A recent paper examined the role of plasticity and the relationship between two distinct areas of the striatum (subcortical part of the forebrain), namely the dorsolateral striatum (involved in habit formation) and dorsomedial striatum (important for goal-directed activity), on behavioral responses. These researchers utilized EthoVision® XT to track animal behavior in the Elevated Plus Maze and the Open Field Test. It is known that the striatum is critical for motor activity, but if it alternates behavior during emotional challenges, such as fearful situations, is an open question. The goal of the paper was to examine whether disrupting brain plasticity in these two areas on affected motor behavior under anxious conditions. In this paper, the authors assume that being in the open arms of the Elevated Plus Maze or the center zone of the Open Field Test, is sufficient to induce "anxiousness" in mice. Plasticity in the striatum was disrupted chemically, via injection, by inhibiting the dynamics of a receptor important to the plasticity process (AMPAR). A key finding of the paper was a decrease in mobility in the center area during the Open Field Test in treated animals injected in the dorsomedial striatum, as compared to control animals; the finding did not hold for animals given an injection in dorsolateral striatum. This suggests that motor responses to anxiety may be controlled by the areas of the brain involved in goal-directed activity rather than habit formation. The analysis of behavior performed by this group was facilitated, and validated, by the automated tracking and analysis of the open-field test with EthoVision® XT, which saves researchers time, and helps improve reproducibility. EthoVision® XT has been utilized in a number of other studies as well, for purposes as distinct as testing a new mechanism for modeling Parkinson's Disease, to examining the effects of radiation exposure on behavior and memory, to exploring the impact of a mother's lifetime experience on the spatial abilities of her pups. References - Lee, Y, et al. (2014). Neuroscience Letters. PMID: 25459286. PubMed - Van Der Perren A, et al. (2015). Neurobiology of Aging. PMID: 25599874. PubMed - Heredia L, et al. (2015). Toxicology. PMID: 25602925. PubMed - Cutulini D, et al (2015). Frontiers Behavioral Neuroscience. PMID: 25814946. PubMed - This article is re-posted from Maze Engineers. --- ## 4 Facts about zebrafish and zebrafish larvae URL: https://noldus.com/blog/four-facts-zebrafish-and-zebrafish-larvae Published: 2016-02-11 14:32:00 Description: Did you know that zebrafish larvae are able to detect minute movement in the water and that zebrafish are better than fruit flies? Read all 4 facts! Did you know that zebrafish larvae are able to detect minute movement in the water and that zebrafish are better than fruit flies? Read all four facts! Did you know that zebrafish larvae are able to detect minute movement in the water? At the Max Planck Institute in Germany, Groneberg and colleagues (Groneberg et al. 2015) showed that larval zebrafish show approach reactions followed by a form of positive taxis and gradual motion damping in response to water flows. That might sound complicated, but what it basically means is that zebrafish larvae are able to detect minute movement in the water and respond in a stereotypical way. Read more... Did you know that zebrafish are better than fruit flies? Prof. Richard Baines' lab investigates how the electrical development of neurons is regulated. His research was long based on the larvae of fruitfly, but the lab recently started using zebrafish larvae. The Baines lab at the University of Manchester has recently begun to use the DanioVision system to identify novel anticonvulsive compounds. The Baines group have identified a number of novel compounds that have the potential to become next-generation antiepileptics. Read more... Did you know that zebrafish 3D-movement tells more than just tracking 2D? Currently, advances in data-processing, high-resolution cameras, calibration methods, and a combination of highly advanced software programs provide a reliable way to track the movement of zebrafish in X,Y, and Z coordinates, as the Kalueff Lab reports (Stewart et al., 2015). 3D tracking results were compared to manual observations of zebrafish behavior in a novel tank test, post application of the psychotropic drugs nicotine, LSD, and PCP. Read more... Did you know that the zebrafish brain allow us to study drug addiction pathways including alcoholism? Researchers at the University of Toronto Mississauga in the Gerlai lab use zebrafish to unravel the mysteries of alcohol addiction. Similar to humans and rodents, the neurochemical dopamine was found to play a large role in regulating alcohol's locomotor stimulant effects in zebrafish. Read more... FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial --- ## 4 Cool cow facts URL: https://noldus.com/blog/four-cool-cow-facts Published: 2016-02-11 11:28:00 Description: The investigation of movement, activity, and behavior of animals in stables gives great insight. Read this blog to learn more about that, but also about cow behavior in paddocks. The investigation of movement, activity, and behavior of animals in pens or stables gives great insight into differences between group and individual housing, enriched and plain stables, different types of feeding systems, and so on. Read this blog to learn more about that, but also about cow behavior in paddocks. Cool facts about cows and cow behavior 1) Balanced diet for calves Calves, whether raised for milk or meat production, are typically fed diets that differ from diets of feral cattle herds. For example, veal calves receive large quantities of milk replacer and solid feed with little structure to chew on, while dairy calves are weaned off milk early on and receive mostly solid feed. Diets typically fed to calves can cause a number of welfare problems, including poor stomach health as well as stress due to the inability to perform highly-motivated natural behaviors such as rumination or sucking on a teat. Furthermore, there is much research indicating that animals, and in particular ruminants, are able to select a balanced diet and maximize their comfort. So why not let calves choose? RESOURCES Read more about TrackLab Find out how TrackLab is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources 2) Standing cows There are now advanced tracking techniques available which will enable researchers to get more detailed information about exactly where and how cows and other farm animals are moving, and so get even better insights into their welfare and behavior. Although at first sight this may seem a slightly odd thing to investigate, it is actually very important for animal welfare. Read more... 3) Dutch Dairy Centre Only recently registered as an association at the Chamber of Commerce, the Dutch Dairy Centre [1] is already growing into an important network of companies based in the Netherlands. Companies supply a wide range of products and services to the international dairy industry for farmers, farmer co-operatives and milk factories. The members can also work together for you as a group or in a consortium. Why the Netherlands? Well, according to the popular blog Stuff Dutch People Like [2], Dutch people like milk products a lot and consume as many as 14,3 kilos of cheese per person/year and the Dutch produce 650,000,000 kilos of cheese every year! Read more... References - 1. http://www.dutchdairycentre.com/ - 2. http://stuffdutchpeoplelike.com/2010/12/03/24-dairy/ --- ## How sleep heals the brain URL: https://noldus.com/blog/how-sleep-heals-the-brain Published: 2016-02-10 10:34:00 Description: We sleep a large portion of our lives. And now researchers have proven that it can heal the brain. We sleep a large portion of our lives. We need to, we know this, and science proves it. Sleep helps us to process what we have learned, to let our nervous system function properly, and to concentrate during the day. We have all been there: a bit of stress or anxiety for a big day coming up leads to not sleeping well, and we suffer the consequences. Loss of concentration, maybe a bit cranky… my mother always told me sleep makes everything better. And now researchers have proven that it can heal the brain. The question is, how? How sleep heals the brain Traumatic brain injury Researchers led by Daniela Noain and Christian R. Baumann from the University of Zurich (Switzerland) investigated the effect of sleep on traumatic brain injury (TBI) in rats. TBI is a major cause of disability and even death worldwide. As you can imagine, injury to the head has primary damaging effects, but secondary effects can also cause major complications in the months or even years after the occurrence. One of these secondary effects is that a build-up of waste products in the brain can cause cell damage, which in turn can result in memory deficits. In research, this type of cell damage is referred to as diffuse axonal injury, or DAI. This is where sleep seems to help, by limiting the secondary damage. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial TBI and sleep So how can sleep influence the occurrence or the amount of DAI and memory impairment after trauma? To investigate this, researchers first had to find a suitable model. While there are a number of TBI models (in rats and mice), they are generally not suitable to measure sleep-wake patterns (such as REM or slow wave sleep). These measurements require EEG measurements, and most existing TBI models do not allow for the implantation of intracranial devices to measure EEG before the induced injury. New TBI rat So a new closed skull TBI rat model was developed (reported by Fabian Büchele and Marta M. Morawska, et al., in Journal of Neurotrauma in November 2015). This model resembles human TBI at histological and behavioral levels: evidence was found for DAI and memory impairments, as assessed by the novel object recognition test, both similar to clinical data. Sleep modulation and TBI symptoms This new TBI model was then used to investigate the effects of sleep modulation on axonal damage and memory. This research was published last month in The Journal of Neuroscience. Both TBI rats and sham treated rats received sleep induction (pharmacologically induced), sleep restriction (gentle handling), or no sleep treatment, and again memory and brain cell damage were measured. Daniela Noain explains: "We aimed at two different ways of inducing deep sleep, one non-physiological by means of pharmacology, the other physiological by means of sleep rebound after sleep deprivation. The objective was to prove that the common factor between sleep induction and sleep restriction, i.e. the increase in sleep depth, was the key player in the process observed." Enhancement of slow wave sleep To be honest, I was expecting some beneficial effect from the induced sleep when I was reading up on this research, with what my mother used to say to me when I was young still resounding in the back of my head. But remarkably, both induction and restriction of sleep had a beneficial effect on the memory of the TBI rats. How is this possible? Well, as Daniela Noain explained, it indeed has to do with deep sleep. The deeper the slow-wave sleep, the more clearance of waste products in the brain. Less waste products means less DAI, and consequently, cognitive impairment was prevented. Deep sleep rebound The depth of sleep was measured by deducting the 'delta power' (reflecting the high amplitude, low-frequency oscillatory activity) from the EEG readings. Inducing sleep, this research shows, also increases the depth of sleep during the slow-wave (non-REM) sleep. The sleep-deprived animals showed another phenomenon: strong deep sleep rebound after sleep deprivation, which is also seen in humans and confirmed in other rat studies. Deep sleep heals the brain This research teaches us that an increase in sleep depth can prevent brain damage and subsequent memory problems after head injury. I can see this opening up opportunities for sleep modulation as a therapeutic option, and I am excited to see where the CRPP Sleep and Health from the University of Zurich is taking this research in the future. References - Büchele, F.; Morawska, M.M.; Schreglmann, S.R.; Penner, M.; Muser, M.; Baumann, C.R. (2016) Novel rat model of weight drop-induced closed diffuse traumatic brain injury compatible with electrophysiological recordings of vigilance states. Journal of Neurotrauma, 32, 1-10. - Morawska, M.M.; Büchele, F.; Goncalves Moreira, C.; Imbach, L.L.; Noain, D.; Baumann, C.R. (2016) Sleep modulation alleviates axonal damage and cognitive decline after rodent traumatic brain injury. The Journal of Neuroscience, 36(12), 3422-3429. Interesting links - Sleep and health research at the University of Zurich - Report on this research on EurekAlert - EthoVision XT video tracking technology for open field and novel object recognition (memory) testing in rodents --- ## Let children design their own playground URL: https://noldus.com/blog/let-children-design-their-own-playground Published: 2016-01-28 14:10:00 Description: The impact of playing outside on the social, motor and emotional development of children and their learning ability is immense. What makes the best playground, according to children? Getting outside, playing, and exercising is essential for healthy child development. It goes without saying that playing outside must be encouraged in children, especially when we realize that an estimated 80 percent of young children don't exercise enough. The impact of playing outside on the social, motor and emotional development of children and their learning ability is immense. Therefore, it is of interest to researchers to answer the question: what makes the best playground, according to children? Healthy schoolyards In the Netherlands, the organization of Jantje Beton develops many projects and activities aimed at improving outdoor play facilities for children. They operate as a partner in a government-facilitated project to realize 70 new, healthy schoolyards. Because children are the experts in the field of playing and often have great ideas, Jantje Beton involves children in designing and realizing the schoolyard. The children are asked to think about which activities they like, and what they desire in a schoolyard. The children fantasize about their "dream" schoolyard and make drawings. They present the plan to the architect and argue why their choices are important to them. The ultimate goal is to design a schoolyard that offers challenges to every age. Although some ideas were not carried out exactly as the children had invented, the resulting newly designed schoolyard was in line with the children's ideas and they were very enthusiastic. How do children design a playground? Researches from the University of Groningen studied what kind of playgrounds children create themselves. They wondered if children opt for standardization as many adult designers do. In this study the question was how children construct their own jumping stone playground. They provided 40 children (6 to 12 years old), with six identical jumping stones; one was fixed in place and could not be moved, while the other five stones could be placed wherever the child wanted, allowing for jumping or stepping from one stone to another. Afterwards, the distances between the stones were measured as well as the perceived and actual stepping and jumping capabilities of the children. Recording behaviors of the children The researchers used cameras to photograph the created playgrounds, and to record the (gap-crossing) behaviors of the children. They coded and analyzed the play behaviors with The Observer XT. They found that children underestimated their maximum stepping and jumping distances, which is common when there are potential risks involved, such as getting injured when an overestimation leads to unsuccessful gap-crossing. Furthermore, the children varied in the number of different gaps that they crossed in their playground and, more interestingly, none of the children created a playground in which the crossed gaps had the same width. 78% of the children created 4 or more different gap widths. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Interacting with children When children are the architects of their own playground, as a group they create a play area with variety, as measured by gap widths of jumping stones. Apparently, children don't opt for standardization within their own playground. Hence, a way to make sure that a playground matches the (perceived) action capabilities of children is to let the children be the designers; to create a playground in dialog with children. Such an approach would result in the construction of non-standardized playgrounds, which can be beneficial for the motor development of the child, and encourage more free outdoor play. Reference To read more on this study, find the original results here: Jongeneel, D., Withagen, R. & Zaal, F.T.J.M. (2015). Do children create standardized playgrounds? A study on the gap-crossing affordances of jumping stones. Journal of Environmental Psychology, 44, 45-52. --- ## Emotion analysis can be beneficial to researchers in decision making URL: https://noldus.com/blog/emotion-analysis-decision-making Published: 2016-01-13 09:35:00 Description: David Schindler and colleagues developed a software, µCap (muCap), which is capable of creating a link between video footage and phases of the experiment, suitable for automated analysis in FaceReader. By David Schindler Introducing µCap David Schindler is the laboratory manager of the interdisciplinary decision making laboratory MELESSA at the University of Munich, currently visiting the University of Pennsylvania. Many researchers interested in human behavior have used Noldus FaceReader in the past to determine emotional states of their subjects. By now, it has become somewhat of a standard to analyze emotions in small-scale psychological studies, to gain insights into consumer behavior from a marketing perspective and in many more areas. In need of larger sample sizes? Very recently, experimental economists and also experimental psychologists who need larger sample sizes (i.e. up to 400 subjects) have found interest in analyzing the role of emotions in decision making. Those studies are often conducted in computerized laboratories, where subjects in several sessions sit in small cubicles at separate computer workstations and, with the help of experimental software, make decisions or work on different kinds of tasks. While FaceReader in general is capable of handling large numbers of participants, it has no built-in routines to link it to the standard experimental software that exist (in economics, the top dog is z-Tree [1], while psychologists use a diverse set of software of which for example E-Prime or Qualtrics are often used). FaceReader and z-Tree The recent interest in emotional responses as correlates of decision making in economics have sparked a series of papers that have used FaceReader (in connection with z-Tree), e.g. [2,3,4]. An increased interest in such studies has led us [5] to develop a software, µCap (muCap), which is capable of creating a link between video footage and phases of the experiment, suitable for automated analysis in FaceReader. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download µCap The idea behind µCap is very simple: the program constantly reads out a specific pixel in the top left corner of the screen. Whenever this pixel changes color, µCap creates a timestamp in a .csv file. This timestamp contains the exact time at which the change of color happens (on the client computer) and reflects a point of interest to the researcher. While our release version of µCap contains a sample file, for how this color change can be triggered in z-Tree, it is not necessarily limited to be used with z-Tree. Any experimental software that allows to change color of a specific screen area can be used to connect to FaceReader. As an example, consider a decision making experiment, where subjects choose between a risky option (e.g. receive either $5 or $0 with equal probability) and a safe option (e.g. receive $2) after they went through several other decision problems. Just by looking at video footage of the participants' faces, the experimenter is unable to determine at which point in time subjects saw this particular decision problem. With the help of µCap, the experimenter can implement a color change that takes place when the decision problem of interest is first displayed and thus knows the exact time at which this happened and can link it to the footage. µConfig, µCap, µProject µCap consists of three independent tools that allow a fully automatized recording and analysis in FaceReader of a virtually unlimited number of subjects: µConfig is a visual interface that allows experimenters to define color codes at which timestamps should be recorded, the main tool of µCap records the videos and creates the timestamps, and µProject will automatically create a new project in FaceReader such that the analysis can be started with just simply one click. µCap can be used free of charge in academic contexts, you can find the latest downloadable version and the corresponding paper at http://mucap.david-schindler.de/. Analyze emotions The µCap software makes it feasible to run medium- to even large-scale experiments and analyze emotions using FaceReader with only a few clicks. While we hope that the research community will benefit from our tool, we also hope that future versions of our software can benefit from input from our user base. References - Fischbacher, U. (2007). z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171-178. - Joffily, M., Masclet, D., Noussair, C. N., & Villeval, M. C. (2014). Emotions, Sanctions, and Cooperation. Southern Economic Journal, 80(4), 1002-1027. - Nguyen, Y., & Noussair, C. N. (2014). Risk aversion and emotions. Pacific Economic Review, 19(3), 296-312. - Breaban, A., & Noussair, C. N. (2013). Emotional state and market behavior, Working Paper. - Doyle, L., & Schindler, D. (2015). MuCap: Connecting FaceReaderTM to z-Tree. Munich Discussion Paper (No. 2015-4). --- ## Serotonin and social skills: how adult mice differ from juveniles URL: https://noldus.com/blog/serotonin-and-social-skills Published: 2016-01-07 10:14:00 Description: Serotonin is a busy neurotransmitter, influencing processes as memory, mood, emotion, appetite, and sexuality. A prime role for this neurotransmitter is social behavior, across a variety of species; humans, rodents, primates. Serotonin (5-HT) is a busy neurotransmitter, influencing such varied neuronal processes as memory, mood, emotion, appetite, and even sexuality. A prime role for this neurotransmitter is social behavior, across a variety of species; humans, rodents, primates, and even flies all rely upon serotonin to display normal social behaviors. These social effects are partly mediated through the serotonin receptor 5-HT2CR. This role has been confirmed by pharmacologic treatment, but until recently this work had focused primarily on adult rodents. In this current article, Séjourné and colleagues from the Scripps Research Institute (Florida, USA) for the first time investigated the role of 5-HT2CR in the development of social behavior. Social approach In order to assess the role of 5-HT2CR in proper development of social behavior, Séjourné et al. tested juvenile and adult mice in a three-chambered social approach task. In this task, mice have the choice between remaining in a neutral middle chamber and venturing into one of two side chambers; one holds a novel object (empty tube), and one holds a novel, same-sex conspecific (within an identical tube). Mice with normal social behavior spend significantly more time in the chamber with a novel animal than in either of the other two chambers. EthoVision XT was used to assess time in each chamber, as well as velocity and distance traveled. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Adults behaving differently from juveniles Results showed that animals lacking the 5-HT2CR suffered from abnormal social behavior, but only during adulthood, not in the juvenile stage. Juvenile mice lacking the receptor had the same preference for social stimulus animals as did wild types while mutant adults spent significantly less time in the chamber with the novel animal. Additionally, velocity and distance traveled were significantly higher in knockouts compared to wildtypes, providing additional evidence that removal of 5-HT2CR decreases social interaction, while increasing locomotor behavior, but only in adults. Seizure susceptibility Another interesting result from this study is that mice without the 5-HT2CR are also highly susceptible for audiogenic seizures, but again, only as adults. This was measured in a PhenoTyper home cage while activity was recorded with EthoVision XT. All adult knockouts, but not juveniles, exhibited seizures that were induced by a 108-db white noise for one minute. This is interesting because one third of ASD (Autism Spectrum Disorder) patients show comorbidity with epilepsy; and the onset of social deficits coincides with the onset of high seizure activity. Serotonin interacts with Pten Evidence in literature points to an interaction with Pten and the 5-HT2CR. Pten is a protein that, amongst other things, has a tumor suppressor role, and mutations in the Pten gene are a known risk factor for ASD. So in this study, an additional mutant strain was bred as a double knockout for both 5-HT2CR and Pten; this double mutant had only a 20% survival rate into adulthood; it's possible that the early lethality in these mice is due to their increases seizure susceptibility. Because social approach/investigation could not be assessed in these animals, females who were heterozygous for Pten were administered a 5-HT2CR selective antagonist and assessed on the social approach task, again using EthoVision XT. These female demonstrated rescued social behavior, showing a high preference for the novel social stimulus, no different from that of wild types. Putting the pieces together Séjourné et al. have shown nicely that complete removal of the 5-HT2CR in the mouse impairs normal social behavior once animals have reached adulthood, but not earlier in life. By combining social approach behavioral data with seizure activity, results indicate that deficits in both social behavior and seizure susceptibility are likely mediated through an excitation/inhibition imbalance in the mutant mice. Furthermore, the data supports to the hypothesis that interactions between 5-HT and Pten modulate the neural circuitry underlying social behavior. Reference Séjourné, J.; Llaneza, D.; Kuti, O.J.; Page, D.T. (2015). Social behavioral deficits coincide with the onset of seizure susceptibility in mice lacking serotonin receptor 2c. PLOS ONE DOI:10.1371/journal.pone.0136494. --- ## Shopping behavior analysis- improving the shopping experience at airports URL: https://noldus.com/blog/shopping-behavior-analysis Published: 2016-01-04 10:54:00 Description: The retail industry is currently booming in some regions, and with travel such an important part of modern life, so is the retail industry at airports. Learn more about consumer buying behavior by reading this blog post. We've all been there: arriving at an airport hours before your flight leaves, wandering around to pass time before you can board. Luckily, most airports offer stores where you can buy food, books, and tax-free items, but how often is it that you're not truly interested in shopping and just keep strolling without actually buying? Improving the shopping experience at the airport The retail industry is currently booming in some regions, and with travel such an important part of modern life, so is the retail industry at airports. Plenty of market researchers have devoted their time to get the numbers behind the perfect selling strategy, but limited research has been done towards the actual retail experiences of passengers at airports. Much of the current work on shopping at the airport focuses on passenger purchasing, and how this expenditure can be increased. But this research does not address the fundamental issue that with so many things going on at airports, passengers are likely to simply not shop. Australian researcher Dr. Alison Livingstone decided to address this gap by researching how passengers experience airports and how they use the retail environment of airports. Shopping behavior analysis Dr. Alison Livingstone's project had three aims: - To understand and document the full range of activities and interactions which passengers undertake during their actual airport experience, in both retail and non-retail locations. - To provide new knowledge of how passengers actually interact with retail environments. - To understand how passengers' retail experiences are influenced by their airport experiences. Observational studies at the airport Livingstone conducted two field studies at three Australian international airport departure terminals. In contrary to previous research, her data collection methods combined both pre and post experience interviews as well as observations of passengers' complete retail experiences. By observing passengers at airports and not just interviewing them about their experience, in-depth information on what people actually do within a particular environment could be gained, giving the researcher insight on the passenger's perspective, rather than from their own. As a direct result of these observational field studies, Livingstone was able to identify the full range of retail activities and interactions undertaken by passengers during their time in an international departure terminal. Passenger behavior was recorded on video. A custom coding scheme was used to note behaviors and actions. The observational data was then analyzed in The Observer XT, while the coding scheme was further developed during the analysis process. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Insights to passenger behavior Thanks to these video observations and subsequent analysis with The Observer XT, interesting insights were gleaned from the data. It quickly became clear that passengers are involved in a broader range of activities and interactions, at both landside and airside environments, than described in current research. All these activities and interactions are responsible for their airport experience and drive any retail experience at these airports. Livingstone's research shows that passengers have different experiences at the landside and airside retail environments. If these two separate retail environments, and the terminal areas they're located in, would be redesigned and improved to reflect specific needs of passengers, the passenger retail experience could be improved. This would result in passengers not only enjoying the overall airport experience more, but also increase the chances they will give in to their impulses and buy that awesome headset or that comfortable sweater that will keep them warm on the airplane. More details and suggestions are available in the full thesis. Passenger experience and their implications for airport retail environment design (2014). Faculty of Creative Industries, Queensland University of Technology. --- ## What, Why and How to learn in a museum URL: https://noldus.com/blog/what-why-and-how-learn-museum Published: 2015-12-29 14:55:00 Description: Although children can learn a great deal on their own, conversations with parents have a big influence on the content, recall and transfer of what they learn. In the Netherlands we have a so called "museum card" which allows you to visit museums for free. In the last few years I visited quite a few of them together with my children. In Amsterdam we saw the 'Nachtwacht' in the Rijksmuseum, did science experiments at Nemo, and learned about how the sea has shaped our Dutch culture at The National Maritime Museum. We have also visited the 'Openluchtmuseum' (Netherlands Open Air Museum) in Arnhem several times, because this one is the closest to us. At this museum you can learn a lot about how people lived in the past, and the objects they used for cooking their meals, brewing beer, doing the laundry, and so on. Each and every time we visit this museum, my children and I discover new facts. It's a great learning environment, but what do my children actually recall of these many museum visits? Natural setting for research Researchers from Loyola University Chicago also chose a museum as the setting for their experimental and observational research. In two museum exhibits, they examined the effects of parent-child conversation and object manipulation on children's learning, transfer of knowledge, and memory of the exhibit. Many studies of learning and parent-child interaction have stressed the need to observe informal learning in natural settings; an exhibit designed specifically for children is therefore ideal for this research. Specifically, hands-on activities in the room represented the daily practices of the Pueblo people 800 years ago. What influences children's learning in a museum? To examine the influences of conversation, they created a set of conversation cards about objects in the Pueblo exhibit. On one side of each card was a picture of one of the objects, on the other side were questions that invited parents and children to talk about the object pictured on the card. In particular parents' open ended questions (e.g., What, Why and How – the Wh-questions) could make sure that children focus on relevant aspects of an exhibit object or activity, and elicit information from children to diagnose what they do (and do not) know. Children and their parents were randomly assigned to receive these conversation cards, the physical objects themselves, both, or neither, before their exhibit visits. Coding behavior The study consisted of several activities: the pre-exhibit activity where the parent and child did or did not receive the cards and/or the target objects, visiting the exhibits, filling in a family questionnaire, and recalling at home (optional). Parents were asked to recall the visit with their children 1 day and 2 weeks following the museum visit. Verbal and non-verbal behaviors were videotaped during the exhibit visits and at home, and coded using The Observer XT. The researchers focused on the parents' elaborative talk by defining the total number of Wh-questions and prior knowledge associations, children's responses to parents' Wh-questions and also their spontaneous talk in the Pueblo exhibit and nonverbal behavior. They also assessed information about transfer of information across the two exhibits and from museum to home. Intervention results in more parent-child joint talk The researchers found that the conversation cards did influence parents' conversations and actions in the exhibit. As predicted, the cards appeared to cue parents to talk in more elaborative ways and enable children in more spontaneous talk. They engaged in more joint nonverbal activities with the objects than children and parents who did not receive the cards. Also families transferred more information between the two exhibits if they had received the cards. In conclusion, the researchers state that learning from direct experiences with objects and learning through conversations with others are intertwined. Although children can learn a great deal on their own, conversations with parents have a big influence on the content, recall and transfer of what they learn. Wh-questions focus a child's attention on aspects of an event and help determine the parent what the child does know and does not know. So now I know even better how to engage with my children during our next museum visit, to best enhance long-term retention of the information we learn! FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References Jant, E.A., Haden, A., Uttal, D.H. & Babcock, E. (2014). Conversation and Object Manipulation Influence Children's Learning in a Museum. Child Development, 85 (5), 2029-2045. --- ## How to analyze bird calls with UltraVox XT: a summer love on a spectrogram URL: https://noldus.com/blog/bird-calls-ultravox-xt Published: 2015-12-22 14:33:00 Description: You may know that the recently-released UltraVox XT 3 is used to study ultrasound vocalizations, especially in rodents and bats. But the fact that it analyzes full-spectrum sound, makes it ideal for analyzing bird calls. You may know that the recently-released UltraVox XT 3 is used to study ultrasound vocalizations, especially in rodents and bats. But the fact that it analyzes full-spectrum sound, together with the filter options and cool features like the spectrogram and the automatic call detection, makes it ideal for analyzing bird calls. Yours truly must admit that he is not fond of quantification of behavior at any cost, but this time he could not resist. How to analyze bird calls with UltraVox XT: A summer love on a spectrogram I am personally interested in the ecology of a small nocturnal raptor, the Scops owl (Otus scops), the cutest of the owls in Europe, and certainly one of the least known. The Scops owl inhabits most of continental Europe, but the Mediterranean regions are definitely its strongholds. There, a melancholic, monosyllabic whistle interrupts the evening chorus of cicadas. It's the male Scops owl, claiming its territory. "Tjuut, tjuut" resounds almost uninterrupted in the forests and pine plantations along the coastline, and is a familiar sound to people spending their summer holidays in camping sites (note: hearing them is the easy part; spotting them is a totally different matter). Sometimes male and female owls make duets, giving the impression that one follows the other. Putting the vocalizations on a spectrogram is the starting point of my analysis. For example, I want to know whether the male changes its call tone when a female starts calling, or when another male, an intruder, closes in. Visualizing the song After loading the recording file in UltraVox XT, I can immediately look at the spectrogram, with the frequency in kHz on the y-axis. We know from the literature that female calls are slightly higher-pitched than male calls. And there, you see the difference: Tjuut (He; left) vs. Tiùut (She; right). Because the female was further away, her call looks weaker in the spectrogram (darker blue means higher amplitude). Analyzing the calls First of all, I wanted to know whether UltraVox XT is able to discriminate between male and female calls. Therefore, I drew rectangles around sample spectrograms like those in the figure below. I gave each rectangle a name and a color. From those samples UltraVox XT extracts frequency range, mean amplitude and duration to be used as search parameters. Then I let UltraVox XT find the calls in the recording. And there they are, after zooming out to view a longer time fragment: For each call category, UltraVox XT shows statistics like the time of occurrence, the dominant frequency and mean duration. It was immediately clear that each bird has a strikingly constant frequency fingerprint. I also had a look at other, more complex bird songs, like that of a reed warbler here below. Here I could easily detect repetitive elements in a phrase (see the green rectangles on the left). When clicking one of the detected calls, UltraVox XT makes an enlarged spectrogram (right). After call detection, the statistics and even the spectrograms are ready for export. In short, there is plenty of opportunities to analyze bird calls with this software. Have fun! Featured photo by Nouhouhouk CC BY-SA 4.0, via Wikimedia Commons --- ## Zebrafish provide key insights into alcohol addiction URL: https://noldus.com/blog/zebrafish-insights-alcohol-addiction Published: 2015-12-11 16:03:00 Description: Why is it that when people drink, only small subsets of individuals develop an alcohol addiction? Steven Tran from the Gerlai Lab tells us why zebrafish are very helpful in the search for the answer to this question. At this year's Neuroscience I talked to someone from the Gerlai Lab at the University of Toronto (Ontario) who is involved in very interesting research on alcohol addiction. That person was Steven Tran, and I am very happy to say that he agreed to share a story on our Behavioral Research Blog. Take it away, Steven! Two and a Half Men's Charlie Harper, although fictional, is the prototypical image of alcoholism. What makes individuals such as Charlie Harper different from the rest of us? Why is it that when people drink, only small subsets of individuals develop an alcohol addiction? Despite decades of research into alcohol addiction, the sad truth is that what we know about this debilitating disease is vastly outweighed by what we don't know. For example, we know that individuals that are more sensitive to the stimulant and pleasurable effects and less sensitive to the sedative and negative effects of alcohol are actually at a much higher risk of developing alcohol addiction. However, we don't know what mechanisms underlie sensitivity to alcohol's addictive effects, and to a larger extent, we don't know the exact mechanisms through which alcohol acts on the brain or how individuals develop alcohol addiction. Alcohol induced locomotor activity in zebrafish The zebrafish brain, although anatomically different, exhibits evolutionarily conserved neurotransmitter systems which may allow us to study drug addiction pathways including alcoholism. The zebrafish is a small freshwater vertebrate which has been gaining traction in the behavioral sciences and specifically for investigating the neurochemical mechanisms underlying alcohol's effects on the brain and behavior. One of the simplest and arguably most relevant effects of alcohol examined in zebrafish is altered locomotor activity, which is easily quantified using EthoVision XT (Noldus), an automated video tracking software. Analysis of different animal models including rodents, fish and humans has suggested a link between alcohol's stimulant effects and the development of alcohol addiction. However, the exact mechanisms in the brain underlying alcohol induced locomotor activity are not completely understood. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Neurochemical basis of alcohol induced locomotor activity In the brain, neurons communicate with each other using neurochemical messages. Researchers at the University of Toronto Mississauga in the Gerlai lab use zebrafish to unravel the mysteries of alcohol addiction. Similar to humans and rodents, the neurochemical dopamine was found to play a large role in regulating alcohol's locomotor stimulant effects in zebrafish. For example, by inhibiting the rate-limiting enzyme that produces dopamine in vertebrates, including the zebrafish, researchers were able to reduce the locomotor stimulant effects of alcohol in zebrafish [1]. Likewise, when the receptors to which dopamine binds to were blocked, the locomotor stimulant effects of alcohol were completely abolished in zebrafish. These key findings are similar to those found in rodents and humans. However, studying how alcohol affects the brain is not enough. Since only a small proportion of individuals who consume alcohol develop addiction, research has to focus on these subset of individuals. Individual sensitivities to alcohol's locomotor stimulant effect Similar to humans, zebrafish also exhibit individual differences in their sensitivity to the effects of alcohol. The Gerlai research group at the University of Toronto Mississauga recently identified a subset of zebrafish within the general population that exhibit elevated anxiety-like behavioral responses. These fish also exhibited elevated brain tissue levels of the neurochemical serotonin [2]. Interestingly, experimentally induced stress can increase anxiety-like behavioral responses and reduce serotonin metabolism in zebrafish [3]. In humans, serotonin is highly implicated in anxiety, depression and addiction. However, what was most intriguing was that fish with elevated anxiety-like responses exhibited a potentiated response to alcohol's locomotor stimulant and anxiolytic (i.e. anxiety reducing) effects. This discovery may help explain why certain individuals are more sensitive to the effects of alcohol and may be at a higher risk for the development of alcohol addiction. The mechanisms underlying alcohol addiction in humans are still not fully understood, but the above example demonstrates how using model organisms, including the zebrafish, may yield insights into this debilitating disease. References - 1.Nowicki M.; Tran S.; Chatterjee D.; Gerlai R. (2015). Inhibition of phosphorylated tyrosine hydroxylase attenuates ethanol-induced hyperactivity in adult zebrafish (Danio rerio). Pharmacol Biochem Behav, 138, 32-39. - 2.Tran S.; Nowicki M.; Muraleetharan A.; Chatterjee D.; Gerlai R. (2015). Neurochemical factors underlying individual differences in locomotor activity and anxiety-like behavioral responses in zebrafish. Prog Neuropsychopharmacol Biol Psychiatry, 65, 25-33. - 3.Tran S.; Nowicki M.; Fulcher N.; Chatterjee D.; Gerlai R. (2015). Interaction between handling induced stress and anxiolytic effects of ethanol in zebrafish: A behavioral and neurochemical analysis. Behav Brain Res, 298, 278-285. --- ## Does pesticide resistance make malaria mosquitoes “smarter”? URL: https://noldus.com/blog/pesticide-resistance-malaria-mosquitoes Published: 2015-11-19 15:32:00 Description: In one of my previous blog posts, I wrote about the success of insecticide treated bed nets in preventing malaria. In the past five years, mortality from malaria has dropped with 60%. In one of my previous blog posts, I wrote about the success of insecticide treated bed nets (ITNs) in preventing malaria. In the past five years, mortality from malaria has dropped with 60%, which is at least partly due to the widespread use of ITNs [1]. However, ITNs do not offer a 100% effective solution against malaria, primarily due to the fact that not everyone in malaria-affected areas has access to ITNs. But even if they did, malaria-spreading mosquitoes may still be able to bite their victims if the bed nets have holes. In addition, mosquitoes may develop resistance against the insecticides the bed nets are treated with. By James D. Gathany (The Public Health Image Library, ID#444) [Public domain], via Wikimedia Commons Insecticide resistance and holes in bed nets The ability of malaria mosquitoes to find holes in bed nets may have a dramatic effect on ITN effectiveness. To investigate this, Malal Diop and colleagues [2] used a free-flight approach in a wind tunnel to see whether malaria mosquitoes could reach an attractive odor source through a 1 cm hole in a bed net. The bed net was either untreated, or treated with the synthetic pyrethroids Permethrin or Deltamethrin. They tested mosquitoes that were susceptible to pyrethroids (wild types), or were either heterozygous or homozygous for the Knock-down-resistance-gene (Kdr) that causes pyrethroid resistance. The authors analyzed the mosquito flight behavior with EthoVision XT video tracking software. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Mosquitoes are smart Shockingly, in all treatments, at least 50% of the mosquitoes were able to pass through the 1cm hole in the bed net, regardless of genotype. This shows how important it is to use bed nets properly, and without damage. About 50% of the susceptible mosquitoes were able to access the hole in the ITN. This was also the case for Kdr homozygous mosquitoes. As would be expected, susceptible mosquitoes that failed to pass the hole almost all died. In contrast, the Kdr homozygous ones almost all survived, due to their genetic resistance to pyrethroids. Partial resistant mosquitoes are even smarter Interestingly, Kdr heterozygous mosquitoes were best able to pass the hole in treated nets; about 75% managed to do so. Depending upon the type of pesticide used, mortality of those that failed to pass through the hole was 45 to 90%. These results show that Kdr heterozygous mosquitoes were better able to pass the treated net through the hole than Kdr homozygous ones, but more died if they failed to find the hole. Heterozygosity, the best of both worlds The authors state that homozygous mosquitoes have a high resistance against synthetic pyrethroids, but that this resistance comes with a fitness cost. This may be due to the resistance gene causing impairments in the nervous system. The heterozygous mosquitoes have best of both worlds: they are partially resistant to pyrethroids and their searching ability is not impaired. This makes them better able to pass through a hole in the ITN than both the susceptible and the Kdr homozygous mosquitoes. The importance of investigating mosquito behavior In conclusion, Diop et al. showed how important it is to study the behavior of resistant mosquitoes in detail. If the authors had studied mortality alone, they would have concluded that heterozygous mosquitoes had a lower resistance than homozygous ones. However, the behavioral research reveals that this disadvantage is counterbalanced by a higher searching efficiency. The authors state that only with detailed insight into the interaction between resistance, the malaria mosquito, and its behavior, can effective, innovative tools against malaria be developed. References - 1.WHO Malaria Fact Sheet - 2.Diop MM, Moiroux N, Chandre F, Martin-Herrou H, Milesi P, Boussari O, et al. (2015) Behavioral Cost & Overdominance in Anopheles gambiae. PLoS ONE 10(4): e0121755. doi:10.1371/journal.pone.0121755 --- ## Consumer research – what determines food satisfaction? URL: https://noldus.com/blog/consumer-research-food-satisfaction Published: 2015-11-17 14:05:00 Description: In a recent study, Barbara Andersen and Grethe Hyldig from the National Food Institute of Denmark zoomed in on food satisfaction from a consumer perspective. My mother makes the best apple crumble. The top is crunchy, the apples warm and mushy (but not too mushy!), and the level of cinnamon is in perfect balance with the sugar and the apples. Honestly, I've never tasted a more delicious apple crumble, which sets a high standard for friends or restaurants offering me an apple crumble dessert. Expectations and desires - consumer behavior & emotions Today's blog is about expectations and desires. In a recent consumer research study, Barbara Andersen and Grethe Hyldig from the National Food Institute of Denmark honed in on food satisfaction from a consumer perspective. You'll learn, as the researchers did, that expectations and desires based on memories play a very important role in determining the level of food satisfaction (as with my mom's apple crumble). Gaining insight Barbara Andersen and Grethe Hyldig set up a study using two focus groups (a total of 20 consumers), varying in age, gender, employment level, and food interest (participation/interest in food related household activities). The goal for Andersen and Hyldig was to gain insight into what determines levels of food satisfaction for different consumers. With particular knowledge about influencing factors, the food industry can develop products that meet or even surpass consumers' needs and wishes. The focus groups were organized at the National Food Institute at the Danish Technical University. In the 90 minute focus group sessions, participants were asked questions related to their experience of food satisfaction while eating, and which factors they would identify as important for the feeling of satisfaction. All sessions were recorded using Media Recorder software. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources During the sessions, photos of lunch dishes were presented in order to get the discussion going. As the discussions continued, participants' dialogues progressed further towards associations instead of discussing the exact dishes in the pictures. All video recordings were repeatedly reviewed, and quotes were pulled and transcribed to illustrate themes. Main themes identified were: - Sensory properties - Physical well being - Expectations and desires (the apple crumble again) - The food context - Comparison of the importance of the various determinants to satisfaction. Sensory variation In general, Andersen and Hyldig conclude that sensory experience seemed to be the primary determinant of food satisfaction. For example, they found that some participants stated that both during and in between meals, they were primarily looking for sensory variation. According to Andersen and Hyldig, this need for variation leads back to an innate need to ensure intake of an adequate amount of varied nutrients. Furthermore, the results indicate that consumers desire a positive sensory experience, but what makes the sensory experience is subjective… bad news for the food industry, who would love to find an exact recipe or ingredient! Memories about eating food in a particular Italian restaurant Andersen and Hyldig also found that before intake, the most important factors were expectations and desires based on memories about previous food experiences, and the context in which the food was perceived. Take for instance my expectations when visiting my parents; I already know that I can look forward to a marvelous food experience! The context of a restaurant, according to the panel members, also raised the bar when talking about what is expected of the food. Imagine an Italian restaurant and you'll already think about delicious home-made pasta primavera. Feeling fulfilled Physical wellbeing was mentioned as important for the feeling satisfied. Included in this was the experience of an appropriate energy level after intake. Imagine eating something and not feeling fulfilled; I know that feeling quite well – 2hrs after you finished eating your fast food order! And then there is the famous after lunch dip, that happens in the early afternoon when you ate too much, or just too heavy of food. That is also not the kind of physical wellbeing consumers are after. Sensory experience In general, Anderson and Hyldig have shown us that the sensory experience seemed to be the primary determinant to satisfaction. But what exactly does that mean? It means that there are many factors influencing food satisfaction, with none truly standing out as most important. So if you want to gain more insight in food satisfaction, you as the food purveyor need to take multiple factors into consideration seeing that they all, no one more than the other, influence the level of satisfaction. And that makes me think…maybe it isn't just the delicious apple crumble, but the setting and memories it evokes when we sit down as a family to eat that crumble! FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Reference - Andersen, B.V.; Hyldig, G. (2015). Consumers' view on determinants to food satisfaction. A qualitative approach. Appetite, 95, 9-16. - Image by Randy Robertson (Own work) (CC BY 2.0) --- ## Positive Behavior Support: Good behavior can be learned URL: https://noldus.com/blog/positive-behavior-support Published: 2015-11-04 13:57:00 Description: With the observed increase in pediatric obesity in recent years, a child’s family, particularly his parents, may influence eating behavior, diet, and physical activity through their parenting and food choices. 'Mom, what's for dinner tonight?' It's a daily recurring question from my children. Having dinner is an important part of the day and also a way for parents or caregivers to influence a child's diet. With the observed increase in pediatric obesity in recent years, a child's family, particularly his parents, may influence eating behavior, diet, and physical activity through their parenting and food choices. Some factors that affect eating behavior can be: what and how much food do parents serve their children? To what extent do they encourage their children to eat healthy food instead of unhealthy food? It's important to raise awareness amongst parents of young children of the consequences of unhealthy eating habits, and teach them to create a healthy nutritional environment for their children. FREE WHITE PAPER Parent-child interaction This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment. - Perform tests in a lab or in-home - Collect data with video - Design a coding scheme Download Parent-child interaction therapy (PCIT) The key to successful interventions is modifiable parenting practices. In the randomized controlled study by Montaño et al., researchers examined the relationship between positive behavior support (PBS) and dietary quality of the meals served to children in the age of 2 to 5 years, a critical period for the development of a dietary lifestyle. Part of the study consisted of observing parent-child interaction while carrying out various tasks, including free play and cleaning up, followed by meal preparation. The main purpose of the study was assessing parenting behavior. Positive Behavior Support PBS stimulates positive behavior and prevents problem behavior. Instead of criticizing the things that go wrong, you compliment the things that go right. People, especially children, thrive in a positive environment, so hearing compliments, stating clear expectations for positive behaviors, and positively engaging with the child should, in the context of healthy diets, prevent them from making unhealthy decisions and get used to unhealthy nutrition habits. This can optimally be measured using direct observations. For parents of young children it's important to get feedback on their strengths and on the issues that may need improvement; this may need to happen on a regular basis. For example, parents need to hear whether the food they choose to buy and prepare for their children is the right food and whether the way they encourage their children to eat healthy food is the optimal way. Reducing problem behaviors 731 families were included in the study by Montaño et al. 367 of these were randomly assigned to the intervention condition: the Family Check Up (FCU). The FCU ensured that parents' use of PBS improved and observed problem behaviors reduced. For this, home visits and feedback sessions were scheduled for each year from ages 2 to 5. The researchers used three different kinds of observation scales to assess the degree of PBS observed in each family. The Observer XT provided researchers with a measurable scale to determine the level of involvement between parents and children. For this purpose, direct observation of the parent-child interaction were coded as either positive or neutral engagement. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Results of the research The findings of this study were noteworthy. Results provided strong evidence that PBS has a positive effect on better dietary quality, across the three years of study. Positive behavior management and parents who provide their children with healthy eating and feeding behaviors in early childhood are an important basis for establishing a healthy nutritional environment. To prevent pediatric obesity, PBS is certainly one key to success. Reference To read more on this study, find the original results here: Montaño, Z.; Smith, J.D.; Dishion, T.J.; Shaw, D.S. & Wilson, M.N. (2015). Longitudinal relations between observed parenting behaviors and dietary quality of meals from ages 2 to 5. Appetite, 87, 324-29. --- ## Seizing fish: a high-throughput screen for novel antiepileptic drugs URL: https://noldus.com/blog/zebrafish-novel-antiepileptic-drugs Published: 2015-10-16 09:25:00 Description: The lab of Prof. Richard Baines investigates how the electrical development of neurons is regulated. His research was long based on the larvae of fruitfly, but the lab recently started using zebrafish larvae. This week we have a guest blog post from Prof. Richard Baines. His lab investigates how the electrical development of neurons is regulated. His research was long based on the larvae of fruitfly, but the lab recently started using zebrafish larvae. He kindly agreed to share his insights on our blog. Zebrafish are being used to model many human diseases such as Parkinson's disease, cancer and autism [1]. Many labs are also using this versatile fish to identify novel drugs to treat epilepsy [2,3]. Proconvulsant testing in zebrafish Exposing 2 to 4 dpf fish to moderate concentrations of water-soluble proconvulsants, such as pentylenetetrazol (PTz), is sufficient to dramatically increase locomotion that can very easily be measured using the DanioVision system. Prior exposure to clinically used antiepileptic drugs (e.g. sodium valproate) imparts protection that is evidenced as a reduced locomotor track length. The ability to scale-up the assay to 96-well plates with DanioVision makes this an attractive primary screen for compounds with potential anticonvulsive activity. The 48-multiwell plate shows 10 min locomotor path-lengths in the presence of increasing concentration of PTz. The same data are averaged in the histogram (see reference in editor's note). Courtesy of Richard Baines. FREE DEMO Find your zebrafish solution Request a free demo for your zebrafish research. - Measure activity, heartbeat, and flow - Track the movement of adult zebrafish - Control your testing environment Free Demo From fruitfly to zebrafish The Baines lab at the University of Manchester has recently begun to use the DanioVision system to identify novel anticonvulsive compounds. Their work has its origins in an even smaller animal model - the fruitfly Drosophila melanogaster. This insect, which in many ways can be considered the forerunner of zebrafish, allows easy genetic manipulation which the Baines group has fully exploited to identify changes to gene expression that occur during seizure. Identification of genes facilitates subsequent identification of possible anticonvulsive compounds. However, whilst ideal for genetic studies, the fly is a long way removed from humans and zebrafish are providing the ideal bridge. Whilst still the subject of active investigation, the Baines group have identified a number of novel compounds that have the potential to become next-generation antiepileptics. RESOURCES Read more about DanioVision Find out how DanioVision is used in zebrafish research and how it can elevate your studies! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - Stewart, A.M.; Braubach, O.; Spitsbergen, J.; Gerlai, R.; Kalueff, A.V. (2014). Zebrafish models for translational neuroscience research: from tank to bedside. Trends in Neurosciences, 37(5), 264-78. - Baraban, S.C.; Dinday, M.T.; Hortopan, G.A. (2013). Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet syndrome treatment. Nature Communications, 4, 2410. - Baxendale, S.; Holdsworth, C.J.; Meza Santoscoy, P.L.; Harrison, M.R.; Fox, J.; Parkin, C.A.; Ingham, P.W.; Cunliffe, V.T. (2012). Identification of compounds with anti-convulsant properties in a zebrafish model of epileptic seizures. Disease Models & Mechanisms, 5(6), 773-84. Editor's note: Find here the original and full description of the example of the larval PTZ model using Noldus software and EEG in this article. --- ## How to capture the 3D swimming patterns of fish URL: https://noldus.com/blog/how-to-capture-the-3d-swimming-patterns-of-fish Published: 2015-10-01 11:58:00 Description: Zebrafish have more in common with humans than meets the eye. This is why they have become a “go-to” model in neuroscience research. But one difference remains: we walk and they swim. We have learned that zebrafish have much more in common with humans than meets the eye, which is why they have become a "go-to" model in neuroscience research. But one obvious difference remains: we walk and they swim, which means movement in 3 dimensions. So while video tracking from one camera angle (e.g. above) can give us a lot of information about the movement of humans (or rodents), all the information from the third dimension (depth) is entirely missed from single camera tracking. 3D tracking makes a difference Researchers from Allan Kalueff's lab demonstrated four years ago that in some studies, tracking depth can really make a difference. When examining different effects from known anxiolytics and anxiogenics, they found that 3D tracking revealed much more pronounced differences in zebrafish behavior, and that some behavioral effects are even undetected when you limit your observations to 2D video tracking. So why are we not all tracking in 3D right now? There are, of course, some obstacles: computing power, equipment and space limitations, and more. But, as I already mentioned in this blog post, at Noldus we have been working together with the Kalueff lab to improve a software program called Track3D. This revolutionary program has led to some very promising results, now published in the Journal of Neuroscience Methods. The humble origins of Track3D Track3D is not all new; it was, in fact, originally designed to track movement of insects in a wind tunnel. Over the years, researchers found new applications for the software, and have benefitted from updated technologies. Currently, advances in data-processing, high-resolution cameras, calibration methods, and a combination of highly advanced software programs provide a reliable way to track the movement of zebrafish in X, Y, and Z coordinates, as the Kalueff Lab reports in their latest publication (Stewart et al., 2015). Novel tank testing: validation with Track3D In this study, 3D tracking results were compared to manual observations of zebrafish behavior in a novel tank test, post application of the psychotropic drugs nicotine, LSD, and PCP. The results showed a strong correlation with the known phenotype of these drugs, the manual method of tracking, and the 3D Tulan methods from previous publications (Cachat et al., 2011 and Cachat et al., 2013). In addition, with 3D tracking the researchers were able to discover behavioral patterns that could be missed with 2D tracking. For example, angular change in 3D (change in velocity vector calculated for each point in the 3D track relative to the previous point), is markedly elevated in PCP- but not in LSD-treated animals. "Wall" swimming at the surface is observed in nicotine-treated zebrafish; both of these behaviors are more easily missed with traditional 2D. Example of visualization of results when combining data into a 3D trajectory. Challenges of 3D tracking Setting up a 3D tracking system does entail adjustments in the experimental set-up. Tracking in 3D requires two synchronized cameras, and the testing arena must be calibrated with real-world dimensions. In this experiment, the first challenge was tackled by Noldus' MediaRecorder, software that automatically synchronizes multiple video feeds. Calibration took place via use of a specially designed unit with markers, placed in the testing tank; all other calculations occurred within the Track3D software, after video tracking was captured. Process of 3D tracking First, both of the two synchronized video feeds were tracked within EthoVision XT video tracking software, as the actual tracking of each video takes place in 2D. The resulting EthoVision XT data output was then combined in Track3D (functioning as an add-on module to EthoVision XT) to get a 3D trace, visualization of this track, and analysis. The combination of two 2D tracks into this 3D visualization, with data points for analysis, allows for the gathering of much more information than from 2D tracks alone, as can be seen in the current methodology article. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial To the future 3D tracking holds great promise for the future, particularly given the rising number of zebrafish studies in drug-phenotyping research. If you would like more detail, I recommend reading the publications listed below. If you think 3D tracking might be interesting for your lab, please contact your local sales representative. References - Soleymani, A.; Cachat, J.; Robinson, K.; Dodge, S.; Kalueff, A.V.; Weibel, R. (2014) Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement. Journal of Spatial Information Science, 8, 1-25. - Stewart, A.M.; Grieco, F.; Tegelenbosch, R.A.J.; Kyzar, E.J.; Nguyen, M.; Kaluyeva, A.; Song, C.; Noldus, L.P.J.J.; Kalueff, A.V. (2015). A novel 3D method of locomotor analysis in adult zebrafish: implications for automated detection of CNS drug-evoked phenotypes. Journal of Neuroscience Methods, 255, 66-74. - Cachat, J.; Stewart, A.; Utterback, E.; Hart, P.; Gaikwad, S.; Wong, K.; Kyzar, E.; Wu, N.; Kalueff, A.V. (2011). Three-dimensional neurophenotyping of adult zebrafish behavior. PLoS ONE, 6(3), e17597. - Cachat, J.M. (2013). Developing zebrafish models of complex phenotypes relevant to human brain disorders. Neuroscience, Tulane University: New Orleans, 2013: 150. --- ## A new fish on the block: Japanese medaka in toxicology studies URL: https://noldus.com/blog/japanese-medaka-toxicology Published: 2015-09-11 10:38:00 Description: We are all very familiar with zebrafish as a model species in neuroscience research. Today, let's talk about another fish, the Japanese medaka. By now, we are all familiar with the zebrafish as a model species. It has many advantages over rodent models and thus has complemented and/or replaced many studies that use the traditional mouse or rat. But today, let's talk about another fish: the Japanese medaka (Oryzias latipes). It has much in common with the zebrafish, such as external embryogenesis and transparency in early life stages, and genetically speaking is also complementary to zebrafish (see Porazinski et al., 2011). Environmental toxicology studies with medaka fish A research group from the University of Bordeaux (France) has published a number of toxicology studies using these fish. In a 2013 study, they reported on the effects of various polycyclic aromatic hydrocarbons (PAH), a class of organic environmental pollutants that have been identified as being carcinogenic as well as mutagenic. Researchers tested the toxicity of PAH as can be found in different compositions (sediment, heavy oil, and light crude oil) by investigating the effects on survival, hatching delay, hatching success, developmental abnormalities, larvae swimming activity, and DNA damage. Light-dark activity Swimming activity was measured using the DanioVision Observation Chamber and EthoVision XT video tracking software. Specifically, they tested for visual motor response in 4 dph (days post hatching) larvae in 46-well plates. The 50-min test cycle started with 20 min of darkness, followed by 10 min in the light, and ended with another 20 min in darkness. Velocity, distance swum, and mobility, as measured with EthoVision XT, were the parameters of interest. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Hyperactivity due to PAH All larvae followed the same pattern of activity in the dark-light-dark cycle: a stabilization of activity during the first dark period, a slight increase during lights on, and then a sharp increase immediately after the lights went off. This activity stabilized over the course of ten minutes to levels similar to those in the first dark phase. However, PAH contamination did significantly affect behavior: exposed fish swam faster and over longer distances. In addition, the researchers found that environmental concentrations of PAH delayed hatching, increased developmental abnormalities, and altered DNA. Effect of psychiatric drug residues In 2014 the same researchers investigated the effects of often used psychotropic drugs, such as fluoxetine and oxazepam. As these pharmaceuticals are used more and more to treat humans, environmental levels also increase. Similar to the previous study, several tests were conducted investigating drug effect on Japanese medaka behavior. Locomotion was assessed in a slightly different protocol, this time using a 10 min dark – 10 min light – 10 min dark – 10 min light cycle. In addition to the activity parameters used previously, now time spent in the peripheral zone was also taken into account. The different drugs had different effects during the light period, with oxazepam inducing hyperactivity, while fluoxetine induced hypo-activity. Almost all drugs tested induced larvae to spend more time in the periphery; in rodents this is commonly referred to as thigmotaxis. However, these effects were only noticeable in moderate to high concentrations (relative to normal environmental concentrations in rivers and sewages). Hypo-activity due to BaA This year a study was published testing the effects of another PAH, the carcinogenic environmental pollutant BaA, on 2 dph medaka larvae. At a low concentration, BaA was found to induce developmental defects, DNA damage, and behavioral disturbances in medaka larvae. Using a similar dark-light cycle to the locomotor experiment in 2014, the 2015 study demonstrated that exposure to the PAH BaA strongly decreased activity in medaka larvae. Taken together, these 3 studies indicate that environmental pollutants and psychiatric drug residues can have severe impact on the development and behavior of Japanese medaka larvae, which can present a risk to wild fish species in urban or industrial areas. References - Le Bihanic, F.; Clérandeau, C.; Le Menach, K.; Morin, B.; Budzinski, H.; Cousin, X.; Cachot, J. (2013). Developmental toxicity of PAH mixtures in fish early life stages. Part II: adverse effects in Japanese medaka. Environmental Science and Pollution Research, 21(24), 13732-43. - Chiffre, A.; Clérandeau, C.; Dwoinikoff, C.; Le Bihanic, F.; Budzinski, H.; Geret, F.; Cachot, J. (2014). Psychotropic drugs in mixtures alter swimming behavior of Japanese medaka (Oryzias latipes) larvae above environmental concentrations. Environmental Science and Pollution Research, doi:10.1007/s11356-01-3477-4. - Le Bihanic, F.; Sommard, V.; Perrine, L. de; Pichon, A.; Grasset, J.; Berrada, S.; Budzinski, H.; Cousin, X.; Morin, B.; Cachot, J. (2015). Environmental concentrations of benz[a]anthracene induce developmental defects and DNS damage and impair photomotor response in Japanese medaka larvae. Ecotoxicology and Environmental Safety, 113, 321-328. - Image by Seotaro (Own work) [GFDL or CC BY-SA 3.0], via Wikimedia Commons. --- ## Dementia symptoms following surgery URL: https://noldus.com/blog/dementia-symptoms-following-surgery Published: 2015-09-03 09:49:00 Description: This week we have a guest post by Iris Hovens. She has done some really interesting research into the consequences of surgery in terms of reduced memory and concentration problems. This week we have a guest post by Iris Hovens. She has done some really interesting research into the consequences of surgery in terms of reduced memory and concentration problems. This is especially a concern for older people. We are very happy that Iris has so kindly agreed to write about her research on our blog. At the end of this post, you will also find a link to a free white paper about this research! Thank you, Iris! Characterizing postoperative cognitive dysfunction with a novel rat-model In the Netherlands, yearly more than 400.000 patients aged over 60 undergo surgery. Although the surgeries are aimed at improving health and well-being, ten percent of these older surgery patients will develop dementia-like symptoms, such as reduced memory and concentration and problems with planning and information processing. This postoperative cognitive dysfunction (POCD) seriously affects the life of patients and their near friends and relatives, as it is associated with a reduced quality of life, increased dependency on social care and an increased risk of lasting mental and functional disability. Translation in POCD research The last decades many human and animal studies have been performed with the aim to understand POCD and its underlying mechanisms [1]. As the cognitive symptoms of POCD can vary widely among patients, human studies investigating the incidence and risk-factors have usually defined POCD as a persisting cognitive decline in general. In contrast, mechanistic research in animals has focused on a simplified model of POCD investigating the effects of surgery on one specific brain region, the hippocampus, and the cognitive function related to this region, spatial learning and memory. These studies have greatly contributed to our understanding of POCD. For example, we now have strong evidence that inflammatory processes that result from surgical trauma may play a key role in POCD development. However, the large differences in the view on POCD may hamper translation of animal studies into clinical practice. A new rat-model for POCD The aim of my PhD project was to develop a new model for POCD in rats to aid translation and gain more insight in the mechanisms underlying POCD. The model we developed made use of abdominal surgery in male rats, mimicking the effects of major abdominal surgery in humans. To be able to measure several aspects of cognition and mood related behavior in different time-windows of interest after surgery, we developed a compact behavioral test protocol (5 days, see figure). For this protocol we chose behavioral tests that could be performed quickly and of which the execution and analysis could be easily standardized using Ethovision software: An open field test to measure interest and anxiety, the novel object test and location recognition test to measure object recognition and spatial recognition, and the Morris water maze test to measure spatial learning, memory and cognitive flexibility. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial Additionally, we analyzed markers for inflammation and neuronal functioning in the blood and in brain regions critically associated with cognitive performance: hippocampus for spatial learning and memory; prefrontal cortex for object memory; and striatum for cognitive flexibility [2]. Using this rat-model we investigated postoperative impairment in cognitive domains and related brain areas under conditions associated with different risk for POCD. As low POCD-risk condition we used healthy adult rats [2]. As elevated risk conditions we used aged rats (25 months) and adult rats that had experienced an infection prior to surgery [3,4]. Risk-factors determine the pattern of POCD By researching multiple behavioral parameters and brain areas, we found that distinct cognitive domains and brain regions are differently affected by surgery. Spatial memory, regulated by the hippocampus, is particularly vulnerable to surgery and may even be impaired under conditions associated with low risk of POCD. This finding promotes interpretation of postoperative cognitive complaints in low-risk patients. Conditions associated with an elevated risk for POCD are associated with more generalized postoperative cognitive and behavioral deficits. This is more alike to the situation in POCD patients and may therefore be a more representative and clinically relevant condition to study the underlying mechanisms of POCD. Inflammation and POCD We found that rats with an elevated risk for POCD show more extensive and prolonged neuroinflammation and changes in neuronal functioning in several brain regions critically associated with cognitive performance. This suggests that inflammatory processes may indeed be involved in the development of and vulnerability to postoperative cognitive impairment. Further and future research In addition to the experiments in our rat-model we investigate POCD in different cognitive domains in older surgical patients. The results of my PhD project will be defended at the University of Groningen on September 9, 2015. Future research will be aimed at the modulation of these inflammatory processes as a potential therapy for POCD. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources References - Hovens, I.B.; Schoemaker, R.G.; van der Zee, E.A.; Heineman, E.; Izaks, G.J.; Leeuwen, B.L. van (2012). Thinking through postoperative cognitive dysfunction: How to bridge the gap between clinical and pre-clinical perspectives. Brain, Behavior and Immunity, 26(7), 1169-79. - Hovens, I.B.; Schoemaker, R.G.; van der Zee, E.A.; Absalom, A.R.; Heineman, E.; Leeuwen, B.L. van (2014). Postoperative cognitive dysfunction: Involvement of neuroinflammation and neuronal functioning. Brain, Behavior and Immunity, 38, 202-10. - Hovens, I.B.; van Leeuwen, B.L.; Nyakas, C.; Heineman, E.; van der Zee, E.A.; Schoemaker, R.G. (2015). Prior infection exacerbates postoperative cognitive dysfunction in aged rats. American Journal of Physiology - Regulatory, Integrative and Comparative Physiology, 309(2), 148-159. - Hovens, I.B.; van Leeuwen, B.L.; Nyakas, C.; Heineman, E.; van der Zee, E.A.; Schoemaker, R.G. (2015). Postoperative cognitive dysfunction and microglial activation in associated brain regions in old rats. Neurobiology of Learning and Memory, 118, 74-9. --- ## Bigger is not always better: hypothesis testing in sexual evolution URL: https://noldus.com/blog/testing-sexual-evolution Published: 2015-08-20 14:45:00 Description: Sexual selection can lead to fascinating phenomena. We are all familiar with the fabulous color display of male peacocks to attract females. Less well known, but definitely not less interesting, are stalk-eyed flies. Sexual selection can lead to fascinating phenomena. We are all familiar with the fabulous color display of male peacocks to attract females. Less well known, but definitely not less interesting, are stalk-eyed flies. Due to the fact that the females strongly prefer males with wideset eyes, the males have developed eyes on stalks that can be larger than their bodies. And did you know that the Irish elk developed antlers through sexual selection that span over two-and-a-half meters? Some people believe that the males with antlers this large could hardly move through the forest, which may have led to the species' extinction. It's no wonder that sexual preference is so well-studied with so many hypotheses formulated in relation to it. Adaptive canalization hypothesis The adaptive canalization hypothesis is one of these evolutionary hypotheses on sexual preference. In simple words, it says that a feature that is important for fitness will have little variation. For example, if it is important for reproductive success to have a red nose, natural selection will lead to a high proportion of red noses in the population. If the color of the nose is not important, more individuals will have noses with other colors. Validating the hypothesis Andreas Walzer and Peter Schausberger [1] studied the validity of the adaptive canalization hypothesis with two species of predatory mites. Predatory mites are tiny spider-like animals that eat plant-eating pest species and are, as a result, commonly used as biological control agents. The two species used were Phytoseiulus persimilis and Neoseiulus californicus. Phytoseiulus persimilis males vary little in body size and will, for readability, be called LV (low variation). Neoseiulus californicus males vary much more in size and will be called HV (high variation). The authors investigated the mating behavior of the mites and automated the study with EthoVision XT video tracking software. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial To be picky or not to be picky If the adaptive canalization hypothesis is true, there is sexual selection on body size in LV animals and not, or less-noticeably, in HV animals. Therefore, LV females should prefer larger males, which are assumed to be more fit than smaller ones. On the other hand, HV females should be less picky about male body size. This is exactly what the authors found. LV females spent more time with larger males, mated more often with them, and for longer periods of time than with small males. However, male size did not matter to HV females, which is also in agreement with the proposed theory. Waterloo revisited Interestingly, the authors also discovered that small HV males were more aggressive than the larger ones. It is possible that they needed to be aggressive to compete with larger males for mating. This phenomenon leads us to another interesting theory in sexual evolution, the Napoleon complex theory, which states that small men are aggressive to compensate for their lack of height. But that is a completely different story which may be a subject for a future blog. Reference Walzer, A., & Schausberger, P. (2015). Interdependent effects of male and female body size plasticity on mating behaviour of predatory mites. Animal behaviour, 100, 96-105. --- ## A new approach in the battle against malaria URL: https://noldus.com/blog/new-approach-battle-against-malaria Published: 2015-08-18 12:06:00 Description: Bed nets treated with insecticide (ITNs) greatly decrease malaria illness and mortality. ITNs can decrease infant mortality from all causes by more than 20%. Insecticide treated bed nets Bed nets treated with insecticide (ITNs) greatly decrease malaria illness and mortality. ITNs can decrease infant mortality from all causes by more than 20% [1,2]. However, the development of pesticide resistance is a threat to the effectiveness of ITNs. [3]. WHO standard bioassays In standard bioassays conducted by the World Health Organization (WHO) for pesticide effectivity in ITNs, mosquitoes are kept in a small enclosure in which they are forced to touch a piece of treated bed net for three minutes [4,5]. After one hour, the number of immobile mosquitoes is counted, and mortality rates are determined after 24 hours. However, there is no escape for the mosquitoes in these tests. Therefore, a possible repellent effect of the pesticides is not taken into account. If ITNs are repellent to malaria mosquitoes, the mosquitoes will not touch the treated net. This means that the effectiveness of the ITNs can be less than predicted by the WHO standard bioassays. Wind tunnel assays Jeroen Spitzen and his colleagues [6] compared the results of WHO standard bioassays with a wind tunnel assay in which the natural flight behavior for mosquitoes towards ITNs was studied. In the wind tunnel, mosquitoes were released downwind and could fly towards and land on a framed piece of bed net, which was either untreated or treated with deltamethrin. Deltamethrin is an insecticide from the synthetic pyrethroid group, which is, at present, the only allowed pesticide type for ITNs. Spitzen et al. tested normal malaria mosquitoes and pyrethroid-resistant ones. The mosquito flight behavior in the wind tunnel was automatically analyzed with the video tracking software EthoVision XT. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Lower mortality in wind tunnel In all treatments, mosquitoes flew towards the bed net within three minutes. Mosquito mortality was much lower in the wind tunnel assays than in the WHO standard bioassays. Susceptible mosquitoes did not alter their flight pattern and landings on the net when the net was treated with deltamethrin. However, the pyrethroid-resistant mosquitoes had fewer landings on a treated net and took longer to reach the net. In addition, they spent less time in close proximity to the net. Mosquitoes always spent much less time touching a treated net than the three minutes used in the WHO standard bioassays. The authors state that the lower mortality in the wind tunnel assay, in comparison to the WHO assays, is likely caused by the shorter amount of time spent on the treated net. No repellency Spitzen et al. found no proof that susceptible malaria mosquitoes are repelled by deltamethrin. However, the pyrethroid-resistant mosquitoes did alter their flight and landing behavior when the net was treated with deltamethrin. But these mosquitoes also flew towards the net within three minutes after they were released into the wind tunnel. Therefore, the authors conclude that the observed effects on the mosquito flight behavior were not caused by repellency of the pesticide. Conclusions In the WHO standard bioassays, the mosquitoes were forced to touch the treated net for three minutes, while in the wind tunnel they never stayed on a treated net for such a long time. This explains why mosquito mortality was so much lower in the wind tunnel than in the WHO bioassays. The authors, therefore, conclude that the wind tunnel setup gives a more realistic estimate of ITN effectiveness than does the WHO standard. In addition, the wind tunnel assay provides valuable information on malaria mosquito flight behavior in response to pesticide exposure. This can help to make better bed nets to protect people against malaria mosquitoes. References - Steketee RW, Campbell CC, 2010. Impact of national malaria control scale-up programmes in Africa: magnitude and attribution of effects. Malar J 9: 299. - Lim SS, Fullman N, Stokes A, Ravishankar N, Masiye F, Murray CJL, Gakidou E, 2011. Net benefits: a multicountry analysis of observational data examining associations between insecticide-treated mosquito nets and health outcomes. PLoS Med 8: e1001091. - http://en.wikipedia.org/wiki/Pyrethroid - http://www.biogents.com/cms/website.php?id=/en/contract/test_protocols/cone_tests.htm - http://www.biogents.com/cms/website.php?id=/en/contract/test_protocols/tube_tests.htm - Spitzen, J., Ponzio, C., Koenraadt, C. J., Jamet, H. V. P., & Takken, W. (2014). Absence of Close-Range Excitorepellent Effects in Malaria Mosquitoes Exposed to Deltamethrin-Treated Bed Nets. The American journal of tropical medicine and hygiene, 90(6), 1124-1132. --- ## How to let rats run perfectly URL: https://noldus.com/blog/rats-run-perfectly Published: 2015-08-14 08:54:00 Description: Letting animals walk freely in gait research. At Noldus, we strongly believe this is the way to go, so that is how our CatWalk XT system works. In a recent blog post, we talked about letting animals walk freely in gait research. At Noldus, we strongly believe that this is the way to go in gait research, so our CatWalk XT system makes use of free gait. This is consistent with the constant feedback from, and collaborations with, scientists who actually perform gait, locomotor, or pain research. Stress-less Working with a closed-off, dark corridor like the CatWalk XT walkway has several advantages. It limits the amount of stress placed on the animal. Besides the obvious effect on the wellbeing of an animal, stress can also cause gait artifacts. The animal may freeze up or lose the desire to move at all. The straight corridor also guides the animal to walk in a straight line, which is beneficial for the footprint measurements. Lights off please The dark environment inside the corridor provides the rats with a safe environment, mimicking the natural underground habitat of wild rats. They cannot see the red light in the ceiling that provides the background lighting that is used by the CatWalk XT software. (The CatWalk XT system uses the red ceiling light for body contour lighting, visible in the software and used to automatically classify footprints.) Mates or food? Generally, animals quickly learn to cross the corridor. Rats are especially good at this, says Kristina Ängeby Möller, researcher at Karolinska Institute. Although the rats do well crossing the corridor, a little motivation never hurts to get them to cross consistently. She gives some tips on how to positively motivate rats. Does food serve as a good motivator or do friends? You know rats are picky eaters… Read more in this free white paper, courtesy of Kristina Ängeby Möller. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## Mice in the spotlight: why you should perform your tests in a home cage URL: https://noldus.com/blog/mice-in-the-spotlight Published: 2015-08-06 15:09:00 Description: Mouse models are essential for neuroscience research. Many tests are susceptible to bias. Home cage testing provides a number of solutions. Mouse models have proven to be essential in discovering the neurological underpinnings of diseases and to the development of a deeper understanding of genotype-phenotype relations. Behavioral phenotyping of these mice is very important, evidenced by the variety of tests that have been described in literature. Unfortunately, many of these tests are susceptible to bias, for example, testing in a novel environment. Bias can also result from handling animals prior to the tests, which can induce artificial behaviors that confound results. Win-win-win A number of researchers have found the answer to this problem in home cage testing. By letting the animal stay in its familiar environment researchers can prevent pretest stress and the novelty of the environment from influencing the behavior of the animal. Better welfare, better results, and improved efficiency. It seems like a win-win-win situation. Emmeke Aarts and her colleagues thought so too, and they have developed and validated a mild anxiety test in the PhenoTyper home cage system. By performing this test in a home cage, they not only prevented bias introduced by handling or the novel environment, it also allowed them to use the baseline behavior of the mice previous to the test as a control measure. In the spotlight Their test is a light spot test, which uses the mouse's natural aversion to bright light. They confirmed the anxiogenic effect of this test through the use of Diazepam, a common anxiolytic drug. Mice are nocturnal animals. Aarts' light spot test takes advantage of the mouse's natural tendency to peak in activity during the beginning of the night, and of its photophobia. By aiming a light beam at the feeding station, the researchers presented the mice with a mild aversive stimulus. The decrease in time spent outside of the shelter (compared to previous baseline measures) was taken as a measure of anxiety. As multiple tests can be executed in the home cage, they also performed learning tasks to see if these would influence the light spot test results. Staying in In a home cage environment, test protocols can take several days. The first experiment Aarts and her colleagues performed lasted for four days: the first three day were reserved for habituation, and the light spot test took place on the fourth night. During habituation, baseline behavior was measured, allowing for the mice to serve as their own control group. The researchers also included a group of mice that would not undergo the light spot test, serving as an external control group. The light spot indeed made the mice stay in their shelter more. After the light was turned off, the mice seemed to compensate for lost time, spending more time outside. Maybe they were hungry? Getting bold During the second experiment, Diazepam was used to verify if the light spot had an anxiogenic effect. Since Diazepam is a known anxiolytic, the mice were expected to be less anxious in regards to the light presentation after receiving Diazepam. This proved to be the case: mice that had consumed the anxiolytic spent more time in the light than mice that had not consumed the drug. Despite a decrease in anxiety-like behavior among the mice receiving the anxiolytic, the drugs did not completely remove the anxiogenic effect of the spotlight on the mice. Under the influence of Diazepam, the mice still spent less time outside of the shelter than they did on light-free nights. When the test was repeated after a light-free night, the Diazepam seemed to have less of an effect. Though it made a noticeable impact on behavior, the data did not reach statistical significance. Mice taking drugs It is important to note that drug administration can be invasive and thus influence behavior. To avoid this, the researchers used a voluntary intake method by creating a fatty palatable matrix with the Diazepam in it. The mice voluntarily took their drugs. Testing for a week The third experiment lasted for six days, again beginning with three days of habituation and baseline measurements. On the fourth night, the mice were subjected to a learning task: they had to hop onto the shelter to receive a food reward. On the fifth night, an avoidance test was performed, in which the mice were required to cope with the fact that using their favorite of two entrances into the shelter would cause a light to be turned on in the shelter. To avoid the illumination, the mice had to cope: either enter through the other side or stay outside. This test was repeated on the sixth night in combination with the light spot test. A control group was subjected to the same protocol, but without the spotlight on the sixth night. Not surprisingly, test order effects became apparent. The learning tasks seemed to have shifted the circadian rhythm of the mice, resulting in a different effect of the light spot test as compared to the previous experiments. There was no longer a direct behavioral effect of the light spot test, and after the test, the mice spent less time outside the shelter, instead of more. Into the future This study shows that the home cage light spot test is as effective as classical anxiety tests, without confounding factors such as handling and environmental novelty. Also, in this test, the aversive stimulus is mild and ecologically valid. As in other situations, test order matters. Future studies by these researchers will focus on identifying behavioral differences between mutants and wild-type mice in similar settings. RESOURCES Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References Aarts, E.; Maroteaux, G.; Loos, M.; Koopmans, B.; Kovačević, J.; Smit, A.B.; Verhage, M.; Sluis, S. van der; Neuro-BSIK Mouse Phenomics Consortium. (2015). The light spot test: measuring anxiety in mice in an automated home-cage environment. Behavioural Brain Research, 294, 123-130 10.1016/j.bbr.2015.06.011. --- ## How you can efficiently screen for plant resistance to aphids URL: https://noldus.com/blog/efficiently-screen-plant-resistance-aphids Published: 2015-07-30 14:20:00 Description: Aphids are small insects that pierce plant leaves and suck out their contents. Although they inflict limited physical destruction to the plant, aphids commonly infect plants with viruses, which can destroy complete harvests. Aphids are small insects that pierce plant leaves and suck out their contents. They can cause considerable crop damage. Although they inflict limited physical destruction to the plant, aphids commonly infect plants with viruses, which can destroy complete harvests [1]. Plant resistance to aphids In nature, plants have numerous ways to defend themselves against insects. Some species have a thick waxy epidermis or spines on their leaves; others produce toxic substances or nasty smells [2]. By taking advantage of plants' natural defenses, researchers can breed for plant varieties that are better protected against pest insects [3]. In this way we can decrease the amount of pesticides necessary so we can produce cleaner crops. However, breeding for plant resistance requires an easy method to screen many plants for resistance. Low-throughput screening Until now, host plant resistance to aphids has been investigated either in aphid population growth studies, or in detailed studies of aphid feeding behavior. Both methods are very labor intensive. In population growth studies, the number of aphids is counted over time. This requires many plants, much time, a climate-controlled space, and a lot of man-hours to count the aphids at the end of the test. Aphid feeding behavior can be measured with the Electrical Penetration Graph (EPG) technique in which the different aphid feeding stages are measured with changes in an electrical current going through them [4]. Individual aphids are connected to a volt meter with a tiny gold wire, and the electrical signals indicate whether and from which plant part the aphid feeds. Although this gives very accurate information on the feeding behavior, the method requires very labor intensive handling of the tiny creatures, and only eight plants can be screened simultaneously. Therefore, the throughput of both methods is low. New video tracking method Karen Kloth and her colleagues at Wageningen University developed a new method that is very promising for screening plants for aphid resistance [5]. They used the video tracking software EthoVision XT to analyze aphid behavior automatically. They found that the number of long probes (periods of penetration longer than 15 minutes) on leaf discs was a good measure for host plant resistance to aphids. These long probes can be measured automatically by determining the amount of time the aphids are not moving on the leaf discs. Other parameters that can be measured automatically with video tracking as well, such as the distance the aphid walked, were also related to plant resistance. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial New method validated Kloth et al. compared the video tracking data with results from manually scored EPG experiments. As expected, the labor-intensive EPG method gave accurate results of plant resistance levels using just a few replicates. However, although the video tracking method necessitated a higher number of replicates to obtain similar outcomes, it allowed many more samples to be screened at once, with the added benefit of automating the data annotation. High-throughput screening Video tracking opens up the possibility of large scale screening for plant resistances and, on a more general level, insect behavior. At present, 100 plant varieties can be screened simultaneously with just one of Kloth's setups. Thus, the method Kloth et al. developed is very promising for high-throughput screening for plant resistance to aphids. With this method, searching for suitable plant lines to develop pest-resistant crops can be made much easier. References - Minks AK, Harrewijn P. World crop pests. Aphids. Their biology, Natural enemies and control. Elsevier Science Publishers, Amsterdam, the Netherlands; 1989. - Schoonhoven, L. M., Van Loon, J. J., & Dicke, M. (2005). Insect-plant biology (No. Ed. 2). Oxford University Press. - Wink M. Plant breeding: importance of plant secondary metabolites for protection against pathogens and herbivores. Theor Appl Genet. 1988; 75:225-33. - McLean DL, Kinsey MG. A technique for electronically recording aphid feeding and salivation. Nature. 1964; 202:1358-9. - Kloth, K. J., ten Broeke, C. J., Thoen, M. P., Hanhart-van den Brink, M., Wiegers, G. L., Krips, O. E., & Jongsma, M. A. (2015). High-throughput phenotyping of plant resistance to aphids by automated video tracking. Plant methods, 11(1), 4. --- ## Revealing the secret social role of the CA2 hippocampus URL: https://noldus.com/blog/secret-social-role-ca2-hippocampus Published: 2015-07-23 08:00:00 Description: Aggressive behavior is adaptive for most species. But how is this aggressive behavior mediated in the brain? A study indicates that the hippocampus is a crucial neural component in mediating social recognition. Aggressive behavior is typically adaptive for most species in the animal kingdom. Examples of this can be seen in maternal aggression to protect one's young, and defense of a home territory; both of these contribute to the survival of an individual, and the species as a whole. But how is aggressive behavior mediated in the brain? Recent work indicates that the hippocampus in general, and the CA2 region in particular, is a crucial neural component in mediating social recognition and aggression. What CA2-specific mechanisms allow for such regulation? Vasopression 1b receptor in the hippocampus The neuropeptides Oxytocin (Oxt) and Vasopression (Avp) underlie many different types of social behaviors in rodents, including maternal behavior, aggression, and social recognition. Oxt receptors, and one type of Avp receptor (Avpr1a) are expressed throughout the central nervous system; a second Avp receptor (Avpr1b) is expressed almost exclusively in the CA2 region of the hippocampus. Indeed, researchers from Scott Young's lab at the National Institute of Mental Health showed that male genetic knockouts (KO), lacking the Avpr1b receptor, show reduced male-male aggression (Wersinger et al., 2002, Mol Psychiatry). This data, and the location of the Avpr1b, suggest a specific role for this receptor in proper regulation of social aggression and recognition. Regulation of social aggression via Avpr1b receptor In a continuation of their earlier work, new research from the Young lab has further investigated the role of Avp in regulating social aggression, acting at the Avpr1b receptor in the CA2 hippocampus. By using lentiviral injections to partially restore the Avpr1b receptor back into the CA2 of Avp KO mice, Pagani et al were able to test the idea that Avpr1b receptor in the CA2 is necessary for proper social aggression. Three groups of mice underwent social aggression testing: Wildtype (WT), KO with a GFP lentivirus (KO+GFP; this should not restore social aggression in a KO mouse), and KO with Avpr1b lentivirus (KO+Avpr1b). Lentivirus was injected in 6 locations throughout the CA2 hippocampus, covering 60-100% of the CA2 hippocampus, as observed by in situ hybridization of the subjects' brain tissue after behavior testing. Resident-intruder test Control and injected male mice were tested for aggressive behavior via the resident-intruder test, where experimental subjects were allowed to establish a home cage territory (resident), and an intruder was introduced until either an aggressive encounter occurred (and allowed to continue for 2 minutes), or 5 minutes total elapsed; when either condition was met the intruder was removed. Aggressive interactions were recorded, and The Observer XT software was used to score and analyze the aggressive encounters for behaviors including latency to attack, attack duration, number of bites, and number of tail rattles. Changes to aggressive behavior often co-occur with altered anxiety-like behavior; EthoVision XT tracking software was used to assess performance on the elevated zero maze and open field test. For both tasks, distance traveled was measured, as was duration and frequency of entry into open arms of the elevated zero maze and center of the open field. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Avpr1b receptor replacement rescues social aggression As hypothesized, only WT and KO+Avpr1b mouse groups expressed the Avpr1b receptor in the CA2. These two groups also exhibited significantly different aggressive behavior compared to the KO+GFP group, with a significantly higher percentage of attacks in both WT and KO+Avpr1b groups compared to KO+GFP group. Of note is the fact that WT and KO+Avpr1b groups did not differ from one another on this variable. The groups did not significantly differ in attack duration, or number of attacks. The rescue of aggressive behavior in KO+Avpr1b males was not linked to changes in anxiety-like behaviors. Analysis with Ethovision software in both the open field revealed no differences across groups in general locomotor activity, or frequency and durations of entries into the central area of the open field. Similarly, there were no differences across groups in locomotor activity on the elevated zero maze, or in frequency of entries or duration of entries into the closed arms of the maze. Avp induces synaptic change in CA2 cells Finally, the lab showed that during whole cell recordings in the pyramidal cells of the CA2 hippocampus, applying a selective Avpr1b receptor agonist induced a significant potentiation of excitatory post synaptic currents (EPSCs) in WTs, but not in Avpr1b KOs. The same Avpr1b receptor agonist did not induce this response in the CA1 hippocampus. By acting to potentiate only the AMPA receptor-dependent component of the EPSCs, not the NMDA receptor-dependent component, and not affecting paired-pulse facilitation, the results suggest that the Avp agonist acts postsynaptically to facilitate synaptic transmission in CA2. As this is not seen in other regions of the hippocampus, the CA2 may be unique among hippocampal regions in allowing Avp to modulate the synaptic strength of the CA2 neurons. Earlier research indicates that inhibiting CA2 synaptic transmission has the same effects on social memory as is seen in Avpr1b KO mice. The current work supports the idea that activation of the Avpr1b receptor in the CA2 hippocampus is critically important for proper expression of appropriate social behavior, including social aggression. To learn more about the study described in this post, read the complete article: Pagani, J.H., Zhao, M., Cui, Z., Williams Avram, S.K., Caruana, D.A., Dudek, S.M., and Young, W.S. 3rd (2014). Role of the vasopression 1b receptor in rodent aggressive behavior and synaptic plasticity in hippocampal area CA2. Molecular Psychiatry, 1-10. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources --- ## Behavioral effects of optogenetically induced myelination in mice URL: https://noldus.com/blog/optogenetically-induced-myelination Published: 2015-07-16 09:44:00 Description: Myelination, the ‘ensheathment’ of neurons, is essential to the functioning of the central and peripheral nervous systems. So it is not surprising that problems with myelination can lead to a number of crippling diseases. Myelination, the 'ensheathment' of neurons, is essential to the functioning of the central and peripheral nervous systems. So it is not surprising that problems with myelination can lead to a number of crippling diseases. Known examples include multiple sclerosis and other neurodegenerative autoimmune diseases. Mature neurons augmenting neural circuits In the central nervous system, oligodendrocytes produce myelin, an insulating material, which wraps around nerve axons in order to facilitate fast conduction of neural impulses. This is an especially important process during infancy, and therefore often investigated at this stage. However, how the modulation of myelination takes place after infancy is still largely unclear. Erin Gibson, David Purger, and their colleagues at the Stanford University School of Medicine (CA, USA) recently looked into the intriguing idea that postnatal myelination may be modulated by mature neurons to augment active neural circuits. Behavioral output of myelination Gibson and Purger investigated how neuronal activity affected the regulation of myelin-forming cells in vivo using optogenetic stimulation of the premotor cortex in mice. They then measured behavioral output with the CatWalk XT system. CatWalk XT gait analysis is based on the voluntary movement of the animal across a glass floor. Light is reflected where paws touch the floor, allowing the camera underneath to capture actual footprints. Using these images, the software calculates parameters that are derived from individual footfalls and the time and distance relationships between footfalls. Parameters Three parameters were used in this study: swing speed (as a difference between the left and right forepaw), stride length (distance between successive paw placements), and paw intensity (degree of contact with the glass plate). Myelination improves motor function Four weeks after unilateral optogenetic stimulation, researchers expected to find improved motor behavioral performance of the correlating (in this case left) forelimb. Indeed, they found swing speed to be increased, with no change in either stride length and paw intensity. This was not caused by asymmetrical muscle development, as muscle mass and fiber diameter were unaffected. By pharmaceutically blocking oligodendrogenesis, myelination was prevented and the animals' gait was also not affected, thus supporting the necessity of myelination for measured motor improvement. Further research This study shows that active neurons influence the process of myelination. Now, further research might unravel exactly what happens at the neuron level: is new myelin produced, or do existing sheets get bigger or thicker? These insights may prove useful in treating demyelinating disorders. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Gibson, E.M.; Purger, D.; Mount, C.W.; Goldstein, A.K.; Lin, G.L.; Wood, L.S.; Inema, I.; Miller, S.E.; Bieri, G.; Zuchero, J.B.; Barres, B.A.; Woo, P.J.; Vogel, H.; Monje, M. (2015). Neuronal activity promotes oligodendrogenesis and adaptive myelination in the mammalian brain. Science, 344(6183), 1252304. --- ## How to measure a zebrafish larva’s highly stereotyped response to water motion? URL: https://noldus.com/blog/zebrafish-larvaes-response-to-water-motion Published: 2015-07-09 15:52:00 Description: At the Max Planck Institute for Medical Research in Heidelberg, Germany, Groneberg and colleagues researched one of the neural bases for behavior in Danio rerio. At the Max Planck Institute for Medical Research in Heidelberg, Germany, Groneberg and colleagues researched one of the neural bases for behavior in Danio rerio. They showed that larval zebrafish execute approach reactions followed by a form of positive taxis and gradual motion damping in response to water flows. That might sound complicated, but what it basically means is that zebrafish larvae are able to detect minute movement in the water and respond in a stereotypical way. Interesting experimental set-up Aside from the results, what is also interesting in their research is the way the experiment was conducted. To ensure that the behavior of the zebrafish was as natural as possible, the complete experiment was pre-programmed in the EthoVision XT software. This way, the researchers did not have to interact with the set-up; sounds and vibrations in the room did not influence the behavior of the zebrafish at all. Such automation also eliminated the risk of observer bias, delayed responses by the experimenter, or even completely missing a cue. But the zebrafish larvae were swimming around freely. How do you program a stimulus when you don't know when the animal will show that specific behavior? Testing each animal individually, the idea of the researchers was to elicit a lateral displacement (water motion) when the zebrafish larvae's heads appeared within a distance of 1.75 mm from the center of the swimming chamber. This was all executed by EthoVision XT. EthoVision XT calculated where the larvae were compared to the center of the chamber. When the head of the larvae entered the "virtual triggerzone", the EthoVision XT software triggered the flow-device to start the lateral displacement (LD). What about the stereotyped responses? During 300 seconds of experimentation, freely swimming larvae elicited an average of 8.2 (± 0.9) LDs, with an average time interval of 21.2 seconds (± 2.1 s) between LDs. With long and varying inter-LD intervals, both reaction latency and maximum displacement remained invariant to the number of LD presentations. To further investigate behavior towards LDs, two protocols were tested. One protocol looked at behavior when the LD was given, invariant to the larva's position. The larvae shortened their distance to the stimulus source and showed reduced locomotor activity, reaching almost complete immobility as long as the LDs persisted. They recovered, but very gradually, to pre-stimulation locomotion levels. The second protocol tested LD stimulation when the larvae swam near the stimulus source. Again, the animals approached the source and reduced their locomotor activity. These experiments have been tested in more detail to investigate the effect of stimulus properties and sensory background on motion damping. The effects of group housing vs. individual housing were also examined; surprisingly, larvae that had been raised individually showed a greater response than larvae raised in groups. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Four categories of responses revealed for future research The results of this research uncovered a response in zebrafish larvae that meets four categories of behavior: - 1.Orienting: unconditioned species-specific responses - 2.Stimulus differentiation: selective responsiveness to stimuli and discrimination against sensory background - 3.Parallel processing: altered capacities to process parallel inputs - 4.Sustained responsiveness: reactions to stimuli over prolonged periods of time These responses could be beneficial for behavioral screens commonly used for research on arousal, high-throughput genetics and pharmacological screening. Find out more Groneberg, A.H.; Herget, U.; Ryu, S.; De Marco, R. (2015) Positive taxis and sustained responsiveness to water motions in larval zebrafish. Frontiers in Neural Circuits, 9(9), doi: 10.3389/fncir.2015.00009. Read more about behavior in zebrafish in these blog posts, or about the application of automated stimulus responses based on actual behavior of an animal here. --- ## Examples of infant behavior research experiments URL: https://noldus.com/blog/examples-infant-behavior-research Published: 2015-07-07 11:54:00 Description: In infancy you can observe an explosive growth. A lot of researchers focus on this age group and observe parent-infant dyads to get more insight in specific behaviors. In infancy, you can observe an explosive growth. Many researchers focus on this age group and observe parent-infant dyads to get more insight in specific behaviors. Experiments are often set up to study looking behavior, language acquisition, attachment, or learning behavior. Look Who's Talking Who cannot remember 'Look Who's Talking' a 1989 movie with Kirstie Alley and John Travolta in which the audience was given an insight into the infant's thoughts and behaviors? Since a talking infant is something out of a Hollywood movie, today's researchers have developed a large number of tests or experiments to get a good impression of developmental processes in infancy. FREE WHITE PAPER Tools for Infant Studies Download the free White paper to learn more about the software tools available for infant studies. - Video observations to capture behaviors - Coding behaviors accurately - Unobtrusive emotion analysis Download Infant orientation towards their mother For example, Parade and Leerkes examined associations between marital aggression and infant orienting towards mother when infants are faced with a fearful or frustrating context. They set up an experiment including 92 mothers with their infants. Infant's responses to the fear task In the fear task they placed a remote-control truck on a wooden table in front of the infant. The truck approached the infant, made a series of loud sounds with flashing lights, and then backed away from the infant. They repeated this sequence of movements three times over the first 3 minutes of the task. During the last minute of the task the truck was turned off but remained within reach of the infant. Frustration task In another task, the frustration task, the infant's forearms were gently held down by the experimenter. Throughout this task the experimenter held her head down and did not interact with the infant. Infant gaze was continuously coded during each of the tasks using coding software The Observer XT. The researchers coded the following behaviors: - look at stimulus - look away from stimulus - eyes closed - look at mother FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Results of infant observations So what did they find? Parade and Leerkes conclude that marital aggression was linked with less orienting toward mothers in frustrating situations, in fearful situations marital aggression was linked with less orienting among infants who were high on fear reactivity only. The researchers explain that it may be the case that infants' fear cues aren't picked up by their mothers and that the infants, therefore, rely less on their mothers for assistance in the regulation of their fear. References - Parade, S.H.; Leerker, E.M. (2011). Marital aggression predicts infant orienting toward mother at six months. Infant Behavior and Development, 34, 235-238. --- ## Movement analysis in volleyball URL: https://noldus.com/blog/movement-analysis-in-volleyball Published: 2015-07-07 09:11:00 Description: Researchers from Aix-Marseille Université and the University of Groningen analyzed match plays to gain insight into the whole-body and arm movements. When analyzing movement in sports, there is more that matters than the way players handle their rackets or hockey sticks. Observation of the way players move and their response time, overall fitness, body strength, and, of course, the overall team performance all help create a more complete picture. Sports scientists look into effective interplay of team members and actions including on-the-ball behaviors. In team sports, complex tactics and routines can be revealed by detailed behavior analysis. At the same time, however, it is also important to focus on the individual players in team sports. How does each person move, interact, and balance his/her energy? What can we learn from them? A volleyball player steps into the ball's trajectory to pass an oncoming serve, a tennis player crosses the court to hit a return, and a baseball player runs to catch a fly ball. Each of these interceptions requires a team member to move both his/her body and arms. Niek Benerink and colleagues from Aix-Marseille Université and the University of Groningen were intrigued by these actions and analyzed real match plays of elite-level volleyball players during serve reception to gain insight into the whole-body and arm movements. This analysis raised the following question: Are arm and foot movements controlled on the same temporal basis? Video recording volleyball matches Benerink and colleagues observed and analyzed five international matches of the Netherlands men's national volleyball team. In order to ensure good video material, the researchers positioned the camera 10 meters behind the court. This provided Benerink with a clear view of the nearest half of the field. Video footage of these matches allowed the researchers to systematically code and analyze 347 different serve reception events. Event analysis For each event, the researchers identified the time of the serve and the time of contact, focusing on the moment the feet first moved, the moment the arms first moved, and the moment of passing. Benerink et al. used The Observer XT software in order to accurately analyze all coded behaviors. All serve-pass events were coded by the same person Coding reliability was determined by comparing the first coder with two additional researchers. Benerink and his group independently coded 70 serve-pass events from one of the matches. Benerink explained that intraclass correlations for flight times and movement-initiation times of the feet and arms were 0.996, 0.818 and 0.867, respectively, providing numbers upon which an analysis could be confidently built. Whole-body and arm movements Benerink's team concluded that arm and foot movements are controlled on different temporal bases. Their results revealed that movement of the feet and arms of the elite volleyball players were initiated with reference to different temporal key moments of the serve-pass event. What were the key moments? Foot and arm movements The researchers explain that the start of foot movement seemed timed with respect to the moment of serving and the start of arm movement was timed with respect to the moment of ball contact for passing. This knowledge adds to an understanding of the control of intercepting a volleyball serve and might also be helpful in understanding other interceptions in ball sports. Benerink and colleagues indicate that the player needs to prepare for the serve. However, it's important to note that the defender has less time to move the whole body for a stable support of arm movements when receiving a jump serve in volleyball than when receiving a float serve. In-depth behavior analysis Benerink's advice is to look into the timing of preparing to receive a jump serve, as it can be important in the design of volleyball practice. The process of passing a serve in an unorthodox way towards the setter so he/she can properly set up the counterattack could be subject to future in-depth behavior analysis. Future analyses like this one could provide greater insight into specific detailed behavior patterns, not just in volleyball, but in all sports. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Reference Benerink, N. H.; Bootsma, R. J.; Zaal, F. T. J. M. (2015). Different temporal bases for body and arm movements in volleyball serve reception. Scandinavian Journal of Medicine & Science in Sports, doi: 10.1111/sms.12384. --- ## How to study ataxia URL: https://noldus.com/blog/study-ataxia Published: 2015-07-03 15:39:00 Description: Ataxia is a common problem in Parkinson’s disease (PD), and many early onset Alzheimer’s disease patients (AD) also deal with it. Now there is a non-invasive test for mouse models. Gait and motor performance are studied extensively in neuroscience research, which is not surprising when you come to think of it, because it is affected in many neurological diseases. Ataxia is a common problem in Parkinson's disease (PD), and many early onset Alzheimer's disease patients (AD) also deal with it. Motor skills are also affected in patients with autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD). To study the underlying mechanisms and possible treatments of the motor control issues associated with these disorders, several, mostly invasive, tests have been developed to investigate mouse models. The cerebellum plays a crucial role in motor coordination, precision, and accurate timing and thus is the focus of many studies in this area. A couple of years ago, the Erasmus MC (Rotterdam, The Netherlands) started the development of the ErasmusLadder, a completely new testing paradigm specially designed to assess motor learning and performance. The ErasmusLadder is now commercially available, and this post will list three examples of research with this tool. RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources The essential role of granule cells in motor learning Cerebellar granule cells form a large and important part of the vertebrate central nervous system. To uncover the role of these neurons in motor functioning, Galliano et al. minimized the output of these cells in a mice model and compared their locomotor performance to a wild type group. The ErasmusLadder test was one of the tests used to investigate both motor performance and motor learning skills. Interestingly, they found that overall motor performance was intact, indicating that only a few functioning granule cells are necessary for this. But, when it came to testing actual motor learning and memory, the significant differences between the treatment and the wild type group made it clear that this requires a higher number of functional granule cells. Galliano, E.; Gao, Z.; Schonewille, M.; Todorov, B.; Simons, E.; Pop, A.S.; D'Angelo, E.; Maagenberg, A.M.J.M.; Hoebeek, F.E.; De Zeeuw, C. (2013). Silencing the Majority of Cerebellar Granule Cells Uncovers Their Essential Role in Motor Learning and Consolidation. Cell Reports, 3, 1239-1251. Different cells have different roles in motor performance Maria Fernanda Vinueza Veloz and her colleagues also investigated specific neurons. In their study Purkinje cells, interneurons, and granule cells where the focus. Several knock-out strains were tested on the ErasmusLadder to unravel the role of each of the cell types. Motor performance was decreased in mice with decreased Purkinje cell output, as was evident from their ataxia-like phenotype. Other knock-out strains did not seem impaired in their motor performance, however, motor learning was difficult for all the treated mice. In addition, none of the mice showed lack of motivation as was evident from their willingness to leave the goal box. (For more about this research see this blog post.) Vinueza Veloz, M.F.; Zhou, K.; Bosman, L.W.J.; Potters, J.-W.; Negrello, M.; Seepers, R.M.; Strydis, C.; Koekkoek, S.K.E.; De Zeeuw, C.I. (2014). Cerebellar control of gait and interlimb coordination. Brain Structure and Function, doi: 10.1007/s00429-014-0870-1. Do plaques in the cerebellum cause ataxia? Diego Sepulveda-Falla and his colleagues were part of a study that was described in the media as groundbreaking research last year. They worked together with a cohort of 25 families from the Antioquia area in Colombia with a high prevalence of early onset familial Alzheimer's (FAD) that was discovered to be caused by a mutation in the presenile1 (PS1) gene. Here, patients were symptomatic even before beta amyloid plaques were likely to occur in the brain, which is striking, since these protein build-ups in the brain were main suspects in the cause of the symptoms thus far. The same effect was found in a murine model of PS1 FAD – tests with the ErasmusLadder revealed motor performance and motor learning problems even before plaques were found in the cerebellum. While previously it was thought that the gene mutation causes plaques, which in turn causes the symptoms, this study suggests that the PS1 mutation causes ataxia in these patients through a different mechanism in the cerebellum. This is especially interesting in light of the current clinical study family members have entered, because here a drug is tested that is specifically targeted at preventing the formation of plaques. The researchers are now eagerly awaiting the data to see if the ataxia also disappears (For more about this research see this blog post.) Sepulveda-Falla, D.; Barrera-Ocampo, A.; Hagel, C.; Korwitz, A.; Vinueza-Veloz, M.F.; Zhou, K.; Schonewille, M.; Zhou, H.; Velazquez-Perez, L.; Rodriguez-Labrada, R.; Villegas, A.; Ferrer, I.; Lopera, F.; Langer, T.; De Zeeuw, C.I.; Glatzel, M. (2014). Familial Alzheimer's disease-associated presenilin-1 alter cerebellar activity and calcium homeostasis. Journal of Clinical Investigation, 124(4), 1552-1267. --- ## Behavioral techniques to empower consumers: resisting persuasion by controlling URL: https://noldus.com/blog/persuasion-advertisements-facial-expresssion Published: 2015-06-15 13:14:00 Description: The role of facial expression in resisting enjoyable advertisements. Over a period of 30 months, Peter Lewinski, Research Fellow at the University of Amsterdam and VicarVision B.V., carried out 12 experiments with an automated facial expression coding software called FaceReader Online. This new neuromarketing technology helped him to test more than 1200 facial emotional reactions to dozens of famous advertisements. The experiments yielded 1 million frames that provided more than 10 million data points to analyze on variables such as emotions of happiness, sadness, anger, surprise, fear, disgust, contempt or valence, arousal, and attention. The role of facial expression in resisting enjoyable advertisements All of the experiments are part of a 200-page PhD dissertation, titled "The role of facial expression in resisting enjoyable advertisements", to be publicly defended on 24 June 2015 at the University of Amsterdam. The funding for this project came from a European Union €3.76 Million grant for KULeuven, Utrecht University, London Business School, INSEAD, ESMT, Philips, Tobii, and VicarVision to establish the European Union-wide "Consumer Competence Research Training (CONCORT)" network. Effective counter persuasion Because of the sheer detail and amount of data and scalability of the cloud-based analysis, Mr. Lewinski was able to extract previously unknown insights on how consumers can resist persuasion by controlling their facial expressions. Mr. Lewinski's research was one of 14 EU-wide projects within the CONCORT network, and his project focused on establishing behavioral techniques that consumers can use to counter the persuasion they face from powerful and emotional TV and internet advertisements. To illustrate how this is possible, imagine that you are watching a funny advertisement and you are enjoying it even though the ad is promoting unhealthy food. Somewhere, on the edge of your consciousness, you notice that you are smiling. You suddenly realize that this funny advertisement not only targets your feelings to make you feel good but also it makes you move the muscles in your face involuntarily so that your facial muscle form a simple smile. In the past, it was shown that amusing ads work because they make consumers "feel good." However, a complementary explanation might be equally plausible. It could be that such ads evoke positive facial expressions of consumers (i.e. those ads move consumers' bodies). Figuratively speaking, such ads are taking control of consumers' bodily responses in a way that consumers enjoy such bodily experience without really realizing it. Facial feedback hypothesis The mechanism behind a smile influencing how consumers feel about the advertisement comes from a theoretical mechanism called facial feedback hypothesis, pioneered in 1988 by Fritz Strack. The idea is simple: if a person puts on a fake smile for around 10 seconds, it will make feel them better because of the inherent like between expression and emotion (i.e. a smile and happiness). This link between facial expression and feelings about objects, products, or advertisement is grounded further in the embodiment, the idea that our own bodies influence how we think and feel. However, the crucial question for resisting persuasion remains: if there is a connection between an expression and the feeling, is it possible to directly modify positive facial expressions to decrease positive feelings felt about advertisements? Control expressions of emotion In this thesis, it is argued that consumers can resist persuasion by controlling their facial expressions of emotion when exposed to advertisements. Following the embodiment literature and the facial feedback hypothesis, it is proposed and demonstrated that controlling the expression of emotions elicited by an ad (for example, refusing to smile) might be a fruitful way to resist the ad's persuasive potential. Specifically, if consumers are instructed to control their emotions and not to express any while watching an advertisement, it leads them to like the advertisement and the brand less and they are less willing to purchase the product. Furthermore, the consumers might receive no instruction but watch the same advertisement with someone else who shows skeptical and negative facial expression to these enjoyable advertisements. The negative facial expressions of the skeptical co-viewing person are mimicked by the consumer and thus decrease the consumer's own positive facial expression. The lack of feedback from positive facial expression again leads said consumer to like the advertisement and the brand less as well as being less willing to purchase the advertised product. Resist the persuasion of advertisements The bottom line message for consumers is this – if you want to resist the persuasion of advertisements, do not laugh at advertisement or watch them with someone who does not laugh. Podcast If you would like to listen to 34 minutes podcast about this specific research on iTunes from Mr. Lewinski, see here for Podcast #61: Web Psychologist Podcasts on iTunes Bio Mr. P. (Peter) Lewinski, MSc is a Marie Curie Research Fellow in VicarVision in ITN CONCORT. He is also a PhD candidate (2012-2015) in Persuasive Communication at Amsterdam School of Communication Research (ASCoR) at the Faculty of Social and Behavioural Sciences – University of Amsterdam, the Netherlands. His promotors were – prof.dr. E.S. Tan (UvA); – dr. M.L. Fransen (UvA) and M. den Uyl (Sentient Machine Research group). His academic interests are consumer emotions, embodiment, and neuromarketing. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download References - Lewinski, P.; Fransen, M. L.; Tan, E.S. (2014). Predicting advertising effectiveness by facial expressions in response to amusing persuasive stimuli. Journal of Neuroscience, Psychology, and Economics, 7(1), 1-14. doi: 10.1037/npe0000012 - Lewinski, P.; den Uyl, T. M.; Butler, C. (2014). Automated facial coding: Validation of basic emotions and FACS AUs recognition in FaceReader. Journal of Neuroscience, Psychology, and Economics, 7(4), 227-236. doi: 10.1037/npe0000028 --- ## Bonobos not always as tolerant as generally believed: the plot thickens… URL: https://noldus.com/blog/social-tolerance-bonobos Published: 2015-06-04 12:25:00 Description: In Planckendael Wild Animal Park (Belgium), researchers have been observing a group of bonobos and have found that the differences between chimpanzees and bonobos are not always as black and white as generally believed. A guest blog post by Jeroen MG Stevens & Katherine A Cronin Bonobos (Pan paniscus) are the least well known of the great apes, discovered only in 1929. Often they are contrasted with their closest relatives: the chimpanzees. In a common dichotomous view, chimpanzees are portrayed as brutal, aggressive, and demonic, while bonobos are portrayed as nice, peaceful, and hedonistic. Bonobos and chimpanzees In Planckendael Wild Animal Park (Belgium), researchers have been observing a group of bonobos for twenty years and have found that the differences between chimpanzees and bonobos are not always so black and white. Previous experiments have shown that when it comes to food sharing, bonobos are not always more tolerant than chimpanzees (Jaeggi et al., 2010). Recently scientific interest for tolerance has increased since it is believed to be important factor in human evolution, as it has been shown that tolerance is linked to the evolution of social learning, cooperation, prosociality, and fairness in non-human primates and humans. Social tolerance In a recent experiment the Planckendael researchers teamed up with Katherine Cronin, now at Lincoln Park Zoo, who had conducted a nice set of experiments on chimpanzees in a sanctuary in Zambia (Cronin et al., 2014). There, four groups of chimpanzees were provided with peanuts to measure how tolerant they are. The number of peanuts and the surface area that they cover was scaled by group size, and the proportion of the group that simultaneously occupies the resource zone was measured as an indicator of social tolerance. This research had the advantage that differences in group size could be controlled for, and allow the researchers to compare tolerance across different social groups. The results show that tolerance differed between the chimpanzee groups. The question now was: where would bonobos fit in this story? The peanut plot For Planckendael, the design was slightly modified. We worked with a peanut plot: a dedicated place in the bonobo outdoor enclosure of about 1.6m² where, prior to the actual experiment, 12 peanuts per bonobo were distributed to teach the bonobos that food could be found here. During the experiment, we distributed peanuts in three periods of five days. In the first five days we just distributed the peanuts in the plot. In the next five days we added leaf litter to make the peanuts more difficult to obtain and encourage the bonobos to stay in the plot longer. Finally we returned to the original state without leaves. The behavior of the bonobos was videotaped and later analyzed with The Observer, following an ethogram developed in Planckendael. We recorded which individuals were in the plot, and whether aggression and/or affiliative behaviors occurred between them. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Grab and run We found that overall the bonobos were less tolerant than the chimpanzees in the previous study. Three of the eight bonobos never entered the resource zone. Moreover, most of the individuals that did go in the resource zone quickly left after the first 15 seconds. Basically, most of the bonobos used a "grab and run" strategy and quickly gathered as much of the peanuts as they could and ate them outside the plot. Only the group's alpha female remained seated inside the plot. When leaf litter was introduced, the bonobos did stay in the plot a bit longer, but once the leaves were removed the bonobos quickly returned to their old strategy. Apparently, the bonobos preferred to eat the peanuts far away from other members of their social group, unlike the chimpanzees. Further research While this research showed us that bonobos are not necessarily more tolerant than chimpanzees, the group studied here was relatively small. We plan to repeat the experiment in larger groups to see how bonobo groups of different sizes respond to the challenges of the peanut plot. These additional groups will also be essential to understanding whether there is a real difference between species. References - Cronin, K.A.; De Groot, E.; Stevens, J.M.G. (2015). Bonobos Show Limited Social Tolerance in a Group Setting: A Comparison with Chimpanzees and a Test of the Relational Model. Folia Primatologica, 86, 164–177. - Jaeggi, A.V.; Stevens, J.M.G.; Schaik, C.P. van (2010). Tolerant food sharing and reciprocity is precluded by despotism among bonobos but not chimpanzees. American Journal of Physical Anthropology, 143, 41–51. - Cronin, K.A.; Leeuwen, E.J.C. van; Vreeman, V.; Haun, D.B.M. (2014). Population-level variability in the social climates of four chimpanzee societies. Evolution and Human Behavior, 35, 389–396. --- ## The man in the maze: A behavioral science journey into consumer studies URL: https://noldus.com/blog/behavioral-science-journey-consumer-studies Published: 2015-05-20 15:29:00 Description: As a researcher, one of my biggest thrills was being able to predict how someone was going to behave, especially without asking him or her. As a researcher, one of my biggest thrills was being able to predict how someone was going to behave, especially without asking him or her. This was a learned skill, forged in the long hours of maze-running on the 11th floor of the Behavioral Science Building at the University of Utah. You see, you cannot ask a rat how he solved a maze, but with a clever design and an observant eye, you just know how he did. It was especially amazing to watch that moment of insight, of AH-HA, when he just 'got it' and started running perfectly. But in order to truly understand that moment, I had to have my own AH-HA moment, and it happened five thousand miles from my mazes in Utah. Milan, Italy The Piazza del Duomo in Milan, Italy, is a magnificent plaza. Originally created in the 14th century, it houses one of my favorite churches: the Milan Cathedral (Duomo di Milano). Anyone who knows me knows that I love grand, old churches, but the Milan Cathedral is special for many reasons, including the number of architects needed to complete it across its 500 year history (look it up on Wikipedia, it's fascinating). Another reason is best summarized by Oscar Wilde: he called it "an awful failure". It's not, by the way. It's quite stunning. But more than that, the Piazza houses the seed of my doctoral dissertation. In a fantastic demonstration of the complexity of the brain, two Italian scientists [1] asked parietal lobe damaged patients to recall the layout of the Piazza from memory. These patients exhibited a very specific type of parietal damage called "Neglect Syndrome", in which the opposite side of the world from the damage is "neglected" or ignored. Patients were asked to imagine that they were standing at one end of the Piazza and describe what they saw. As anticipated, patients with damage to the right lobe only described the right side of the Piazza. When the patients imagined the Piazza from the other side, however, a remarkable thing happened: the patients still remembered half, but it was the formerly neglected half! The entire Piazza lived somewhere in their memories; however, the ability to recall it depended on their view. For me, as a naive graduate student reading this study as I shared a Froot Loop or two with my rats in their mazes, this study had a huge influence over my theoretical views. Paris, France About the same time I first read this, my friends and I took a holiday to Europe. It was during the Winter Olympics in Salt Lake City (SLC) and the university was closed for a few weeks. It was also February in Western Europe, and that means the sky had a depressive gloom that would cause a Seasonal Affective Disorder sufferer to collapse into peril. For a few days we stopped in Paris to explore the City of Light. As we attempted to navigate the streets, I was dumbfounded at how I kept getting lost. I was a spatial navigation researcher, with an exceptional memory, and a Master's Degree just months away: why did I keep getting turned around? I never got lost in SLC. After a few days of aimlessly wandering confounded through the Parisian streets, we took the TGV to Bordeaux. While enjoying the thrill of traveling at 220kph it hit me like a bug on the windshield of the train: I kept getting lost because I had no cues to guide me. The sky was always grey. One could not see the sun, much less orient by it. Furthermore, Paris developed as a city though the centuries, as opposed to the perfect grid-like planned layout of SLC. As such, the Parisian streets have no linear organization and the buildings impaired any ability to look around. The streets of SLC, however, are the exact opposite: there are mountains on three sides and a giant lake at the other. Furthermore, the grid-like street pattern centers on Temple Square downtown. Thus, the reason I kept getting lost in Paris but couldn't get lost in SLC was because they were different spatial environments! Much like my little Froot Loop eating, maze-running companions, this was my AH-HA moment. People do not notice signs above 10ft After graduating I left spatial navigation research, vowing to one day return once I had my own lab. As my career took another path, questions remained and nagged like a cliffhanger in a cancelled TV series. Fast forward ten years, to now where technology has developed leaps and bounds. Selfie sticks. Twitter. But of the more useful developments, Noldus now has TrackLab and Tobii Pro has Glasses 2.0. Like a lightning bolt reminiscent of Harry Potter's head, I knew immediately what these new technologies afforded me the opportunity to do: return to those nagging questions, but this time leaving the Froot Loops on the shelf and the rats in the pet store! An interesting search of available extant shopper data shows what we already know from rats: people do not notice signs above 10ft [2,3], shelf endcaps serve a distinct purpose by providing landmarks, and that grocery stores are perfectly suited for thigmotaxic behavior. I love that word, by the way. I use it at every opportunity. It's fancy-pants-speak for 'navigation by sticking close to the walls'. At any rate, there seemed to be a disconnect between shopper studies and spatial navigation research. Beacons and shopper behavior There is much being done with beacons and shopper behavior. For example, wearable tracking technology is becoming so pervasive that Apple built the iBeacon into iOS7 [4]. It's brilliant, but it's being done by market researchers, not experts in spatial navigation. This, in my opinion, is not a negative thing per se, but is definitely something that needs to change. Studies rooted in psychological theory conducted by behavioral researchers can truly understand the consumer experience by, for example, tracking the journey to the store and in the store. Future technologies must rectify internal position (IPS) with global position (GPS). We must leverage the expertise of Noldus Consulting Services to understand consumers to answer not just the how, but the why. I can track how I drive and where I go, but why do I drive out of my way to pass four supermarkets to go to my favorite store? Furthermore, research using facial expression analysis has exploded, but who has shown its ability to generate insights? The method is a tool, but we, the researchers and consultants, are the Artists, generating insights like Picasso on canvas. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Brain and behavior Although a long, circuitous journey, my foray into consumer studies comes deeply rooted in a profound understanding of both the brain and behavior. Market research has parallels to academic research and both share similarities. Both want to drive understanding and not let our technology drive away our insights. Both have the intense need to use our research tools in the best possible way. Now, there are consultants who can be leveraged to create genuine value so that clients can find the sweetest Froot Loops at the end of their own mazes: fulfilled consumers. - 1.Bisiach, E., and Luzzatti, C. (1978). Unilateral neglect of representational space. Cortex 14, 129–133. - 2.Turleya, L.W., and Millimanb, R.E. (2000). Atmospheric Effects on Shopping Behavior: A Review of the Experimental Evidence. Journal of Business Research 2, 193–211. - 3.Lam, S.Y. (2001). "The Effects of Store Environment on Shopping Behaviors: a Critical Review", in NA - Advances in Consumer Research Volume 28, eds. Mary C. Gilly and Joan Meyers-Levy, Valdosta, GA : Association for Consumer Research, Pages: 190-197. - 4.BEACONS: What They Are, How They Work, And Why Apple's iBeacon Technology Is Ahead Of The Pack. --- ## A new method to evaluate if dogs are suitable for IED bomb detection URL: https://noldus.com/blog/dogs-ied-bomb-detection Published: 2015-05-07 13:09:00 Description: Margaret Gruen and her colleagues recently investigated a new method to assess sound induced fear and anxiety in candidate IED-detection dogs – specifically, Labrador retrievers. Military dogs, especially improvised explosive device (IED)-detection dogs, work in war zones under harsh conditions. Being attuned to fear-inducing sounds and recovering quickly is a critical requirement. Margaret Gruen and her colleagues recently investigated a new method to assess sound induced fear and anxiety in candidate IED-detection dogs – specifically, Labrador retrievers. Working dogs An IED is a bomb constructed and deployed in ways other than in conventional military action. In the second Iraq War, IEDs were used extensively against US-led invasion forces. By the end of 2007 IEDs had become responsible for approximately 63% of coalition deaths in Iraq (source). In 2003, there were 81 recorded IED incidents in Afghanistan. In 2009, there were 7,228 (source: Washington Post). This emphasizes the need for reliable military dogs, dogs who are not easily affected by fear and anxiety due to loud sounds such as rapid gunfire, explosives and other military noise. Recently an Open Field Test using recorded thunderstorm sounds was shown to be a robust model of noise-induced fear and anxiety in laboratory beagles (Araujo et al., 2013). But is this test also a suitable indicator for emotional resilience in military dogs? Attempts to induce fear and anxiety For Gruen's study, 16 Labradors were selected from a private training firm. The open field test (OFT) arena consisted of a room of approximately 3 x 3 m and included one hiding place to which the dogs could retreat. Two cameras monitored the dog at all times, when they were in the open as well as in hiding. Digital-audio recordings of thunderstorms or simulated gun battles were played for 3 minutes through two speakers at a fixed decibel level (104-105dB) during a 9-minute session in the OFT arena. The sound stimulus was only played on day 2 (thunderstorms) and day 4 (gunfire) of a five day test; on days 1, 3, and 5, only ambient noise was played. Parameters measured Heart rate, cortisol (via saliva), and body temperature data were collected immediately before and after each 9-minute session. Behavioral data was collected during the entirety of the 9 minutes: EthoVision XT automatically tracked the distance travelled in the room, and the researchers used the dogs' postures to calculate fear/anxiety scores. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Indicators of habituation Two forms of habituation were seen in the OFT. Over the course of five days, there was a significant decrease in distance traveled both within each day and across each subsequent day, suggesting that the dogs acclimated quickly to the room. Salivary cortisol, heart rate and body temperature levels did not decrease between sound stimulus test periods; however, heart rate did show an overall decrease within the control (stimulus free) sessions. Persistence of sound-induced anxiety What was interesting to see in the fear/anxiety scores was that after the sound stimulus of three minutes, the dogs' scores quickly returned to the baseline level (period before the sound stimulus). However, the scores did not fall below baseline levels during sessions in which the sound stimulus was presented as they did during control periods. The overall increase in fear/anxiety scores on sound stimulus days suggests a persistence of sound-induced anxiety. OFT is useful for evaluating candidate IED dogs During the periods in which the thunderstorm or gunfire sounds were played, there was a significantly increased level of fear/anxiety scores and significantly increase in motor activity levels, suggesting that the OFT is a useful model for evaluating acute sound-induced aversion or fear reactions in candidate IED-dogs. OFT fear/anxiety scores correlated with a screening test for emotional resilience (Sherman et al, 2014), therefore making the OFT a suitable evaluation method for candidate Labrador retrievers to be used as IED dogs. Find out more Read more in the complete study: Gruen, M.E.; Case, B.C.; Foster, M.L.; Lazarowski, L.; Fish, R.E.; Landsberg, G.; DePuy, V.; Dorman, D.C.; Sherman, B.L. (2015) The Use of an Open Field Model to Assess Sound-Induced Fear and Anxiety Associated Behaviors in Labrador Retrievers, Journal of Veterinary Behavior, doi: 10.1016/j.jveb.2015.03.007. Read more about dog behavior on this blog here. Other references - Araujo, J.A.; deRivera, C.; Landsberg, G.M.; Adams, P.E.; Milgram, N.W. (2013). Development and validation of a novel laboratory model of sound-induced fear and anxiety in Beagle dogs. J. Vet. Behav. Clin. Appl. Res. 8, 204-212 - Sherman, B.L.; Gruen, M.E.; Case, B.C.; Foster, M.L.; Fish, R.E.; Lazarowski, L.; DePuy, V.; Dorman, DC. (2014). Development of an emotional reactivity test for behavioral evaluation of explosive-detecting military working dogs, J. Vet. Behav. in submission. --- ## Alzheimer's: prevent instead of cure? URL: https://noldus.com/blog/alzheimers-groundbreaking-research Published: 2015-04-23 10:36:00 Description: Alzheimer’s disease (AD) is a huge public health issue as it affects a large part of the aging population. Neuropathology is studied primarily in the end stages of the disease. What about prevention? Alzheimer's disease (AD) is a huge public health issue as it affects a large part of the aging population. By 2050, experts estimate this number will exceed 100 million worldwide. Those of you that are a familiar with the underlying pathological hallmarks of AD will recognize the terms plaques and tangles. These protein built-ups in the brain are well-researched; however, this neuropathology is studied primarily in the end stages of the disease. Plaques and tangles Plaques and tangles are discovered in postmortem studies of humans, and in rodent models of the disease. But while these clusters of beta amyloid plaques between neurons and tangles of tau protein inside of the cells have always been prime suspects in AD symptoms, recent studies show that clinical symptoms can appear independently of their onset. Early onset Alzheimer's in Columbia One recent study demonstrating groundbreaking research on AD, was carried out in collaboration with a group of 25 families from the Antioquia area in Colombia. Researchers from the University of Antioquia learned of a high prevalence of early onset familial Alzheimer's disease (FAD) in these families, which they now know is caused by a presenile1 (PS1) gene mutation. Results from a longitudinal study showed that in this population clinical symptoms appeared as early as at 40 years of age, even before plaques were identified in the brain. These findings might lead to important discoveries in the treatment of Alzheimer's in general. Prevention instead of cure Working together with these families, researchers from the University of Antioquia, the Banner Alzheimer's Institute, National Institutes of Health, and Genentech are now investigating if, instead of trying to cure or treat the symptoms in later stages of the disease, AD can be prevented or slowed down during the onset phase. Young members of these families that were identified to carry the gene mutation have entered a clinical trial to address this possible area of treatment. Murine model laboratory research In addition to clinical research, a mouse model of the PS1 gene mutation FAD was studied in the lab by Diego Sepulveda-Falla and his colleagues (The Journal of Clinical Investigation, 2014). Previous research has shown that this murine model develops plaques and tangles in the brain similar to that seen in humans with AD. Using the ErasmusLadder test, which focuses on cerebellar-based motor performance and learning, PS1-FAD mice were found to have deficits in both motor performance and motor learning (see below). Strikingly, these symptoms occurred before amyloid plaques were found in the brain, indicating that the PS1 mutation results in AD symptoms in another (perhaps additional) way than through the "typical" protein build-ups. Motor performance and learning tests During the ErasmusLadder task, mice went through two phases of testing. First, motor performance while mice were learning to step across alternating high and low horizontal ladder rungs. An efficient stepping pattern requires use of the higher rungs; usage of a lower rung was counted as a misstep. Skipping rungs, or slower stepping, was also measured. Normally functioning mice learn, over repeated runs, to traverse the ladder quickly and efficiently, indicating good motor functioning. In contrast, PS1-FAD mice exhibited difficulties in this phase as was evident from their longer step times and a higher number of missteps. Furthermore, PS1-FAD mice demonstrated problems with learning when to leave the goal box (as cued by a sound); these mice left before the cue was given or stayed in too long after the cue was given. In the second phase of testing, a perturbation was introduced on the horizontal ladder. Precisely timed for each individual run, a single rung was raised above stepping level, higher than the previous high level rungs. Cued by a sound, introduction of the obstacle rungs challenged the motor learning abilities of the mice. Again, PS1-FAD mice demonstrated difficulties in navigating this reflexive motor learning task. PS1 mutation causes symptoms independent of plaque formation The combined clinical and laboratory studies discussed above suggest that the specific PS1 mutation in the Purkinje cells of these patients from Antioquia is causing symptoms that are independent of the formation of amyloid plaques. Currently, a large group of members from these families are entering into a clinical trial for AD prevention, testing a drug that specifically works to prevent the formation of these plaques. It will therefore be interesting to see if this drug will control any or all aspects of the PS1-FAD pathophysiology, as it appears that these symptoms occur independently of plaque formation. New avenues of treatment may need to be assessed. RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Read more Sepulveda-Falla, D.; Barrera-Ocampo, A.; Hagel, C.; Korwitz, A.; Vinueza-Veloz, M.F.; Zhou, K.; Schonewille, M.; Zhou, H.; Velazquez-Perez, L.; Rodriguez-Labrada, R.; Villegas, A.; Ferrer, I.; Lopera, F.; Langer, T.; De Zeeuw, C.I.; Glatzel, M. (2014). Familial Alzheimer's disease-associated presenilin-1 alter cerebellar activity and calcium homeostasis. The Journal of Clinical Investigation, 124(4), 1552-1567. --- ## Prof. Berry Spruijt says goodbye (but not really) URL: https://noldus.com/blog/berry-spruijt-says-goodbye Published: 2015-04-21 14:19:00 Description: Prof. Dr. Berry M. Spruijt recently retired from his position at Utrecht University. I had the honor of attending the symposium that was organized to reflect on and celebrate his career. Did you discover something new today? This was the question Prof. Berry Spruijt used to get from his kids on a daily basis. As little ones, they might have expected their father to come home with the Nobel Prize every day. While we normally focus on a specific study or type of research or research tools, today's post is a little different. Prof. Dr. Berry M. Spruijt recently retired from his position at Utrecht University. I had the honor of attending the symposium that was organized to reflect on and celebrate his career. On Friday the 10th of April, Berry Spruijt and his family and friends looked back on his career at a symposium organized in his honor. Although he will now retire from his work at Utrecht University, Spruijt made it clear that he is not ready to say goodbye. It is merely another point in his career, and this symposium was a great opportunity to reunite with former colleagues and old friends. Magic black box Several speakers were there to educate us, not only on the subjects that are all too familiar for those that have worked with Spruijt in the past, but also on the path that was Spruijt's career. Looking through old college photos to recent publications, it became clear that Spruijt has always been fascinated with the magic black box we call the brain. Over the years he unraveled part of its mysteries, and in doing so, gained important knowledge on emotion, cognition, anticipation, welfare, and well-being in animals. Grooming rats For Spruijt, it all started with one hormone and one behavior as he published his first work on ACTH and grooming in rats. Soon he would integrate automation of behavioral observations into his regular research, as his 1983 publication titled "Prolonged animal observation by use of digitized video displays" reads. Later his interests navigated him towards social behavior and welfare, while his determination to use computer technology to improve animal research grew ever stronger. Monkey friendship Spruijt's research was not limited to rats and mice – it did not take long for him to take on some monkey business. Liesbeth Sterck told us how they used computer models to compare different theories with their behavioral observations. What they found was revolutionary: they discovered that monkeys, like humans, cultivate friendships. In addition to rats, mice, and monkeys, Spruijt has worked with several other species over the years, including apes, horses, and chickens. International ties The second speaker, Gernot Riedel, came all the way from Aberdeen to tell us about approaches in behavioral neuroscience, but instead of the usual suspects (rats and mice) he took Berry Spruijt himself as a study subject. He tried to explain the logic behind Spruijt's mind-boggling publication count - 179 in 32 years! Comparing day-night rhythms and cross-referencing the data with trips Spruijt took, he came to the term play-night rhythm. All in good fun, of course. Pleasure is the money of the brain Ruud van den Bos and Johanneke van der Harst described their work on well-being, brains, and animals – a subject that was bestowed upon them by SPRUIJT BV, as Van den Bos jokingly put it. "Pleasure is the money of the brain," Spruijt had often said, and Van der Harst explained their methods in measuring this pleasure. Wanting, liking, and anticipating seem to be important factors in what they liked to call the S-rate (or S-factor, or schaal van S in Dutch, in which the S stands for Spruijt, of course!). Automation of behavioral observation Then Lucas Noldus talked about valorization, which is an important process within every company. Spruijt has been a scientific partner in many projects and a good friend of Noldus for about as long as the company Noldus IT has existed. He might be called the "godfather of EthoVision" as his group wrote the first software program and he was a driving force behind the further development of this video tracking technology. Later he also became the mastermind behind PhenoTyper and Ultravox, as Spruijt knows – better than anyone – how important a home cage environment is for both animal welfare and scientific validity. Discover something every day After a lecture on science and journalism by Jan Staman and some more personal reflections, Berry Spruijt closed the symposium by telling us all about his journey through the brain. While it is time to retire from his work in Utrecht, Spruijt is far from done. Animal welfare, legislation, and goodwill causes will stay part of his daily agenda, as will the mysteries of the brain in general…because you can take the professor out of the scientific department, but you can never take the science out of the professor. All grown up, his children will still have reason enough to ask their father – did you discover something new today? FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial --- ## Does the sex of a simulated patient affect CPR? URL: https://noldus.com/blog/does-sex-simulated-patient-affect-cpr Published: 2015-04-20 09:30:00 Description: When faced with either a male or female patient simulator, both men and women rescuers appeared reluctant to remove a female patient simulator’s clothing. It shouldn't, but it does. Although men and women are equally at risk for sudden cardiac arrest, studies have found that women are less likely to be resuscitated – by both bystanders and medically-trained personnel. Chelsea Kramer and her colleagues discovered that in the experiment they set up, when faced with either a male or female patient simulator, both men and women rescuers appeared reluctant to remove a female patient simulator's clothing, with men being significantly more hesitant to do so. However, the hand placement for CPR on the female was more ideal compared to on the male simulated patient. Out-of-hospital cardiac arrest Kramer and colleagues conducted their study in the Healthcare Human Factors and Simulation Laboratory (HHFSL) at the University of Calgary's W21C Research and Innovation Centre. They invited 69 participant to the lab and set up two scenarios: an out-of-hospital cardiac arrest (OHCA) with a male simulated patient and an OHCA with a female simulated patient. Reviving a cardiac arrest patient The patient simulator, "iStan," was used in the control condition. The same simulator was transformed from the male iStan into the female patient "iSam" with the addition of a wig, make-up, silicone breasts, a front opening brassiere, and color-coordinated women's clothing; for this experiment, test participants were randomly assigned to either the male or female simulator. Upon arrival to the test site, each participant was introduced to the patient simulator and told that he/she would be rescuing an unconscious patient. Then, the OHCA scenario began when the participant found either iStan or iSam in an apparent state of shock; the participant was given an AED and barrier mask and tasked with the resuscitation of the patient. Once activated, the AED instructed the participant in performing CPR on the patient by providing chest compressions and rescue breaths, resulting in an eventual recovery of the simulated patient. Following the OHCA scenario, participants were interviewed about their experience, including how they felt about removing the patient's clothing and their discomfort and reservations, if any, in doing so. Removing clothing and planting down hands Participants were observed live through a one-way mirror at the same time that video/audio recordings were being made for detailed analysis afterwards. The recordings were triggered via the Noldus MediaRecorder software, coded in The Observer XT, and analyzed with IBM SPSS. The researchers primarily focused on the percentage of rescuers who completely removed clothing from the simulated female patient's chest compared to the male's, and the placement of rescuers' hands when CPR was initiated. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Hand placement So what is considered good hand placement? Kramer and colleagues explain that initial hand placement in CPR is important and should be centered on the chest, as compressions outside of the "red zone" can result in harm. On iStan, hand placement of both male and female rescuers was scattered across the chest. In contrast, on iSam, the rescuers' hands tended to be centralized between the breasts. They either chose to avoid touching the breasts or used the breasts as 'landmarks' to aid in placing the hands in the correct position. Disrobing the patient After the experiment, the participant video data was analyzed to find the relationship between patient sex and rescuer sex. While the researchers found no difference between the men and women rescuers in baring iStan's chest, men were significantly less likely to remove iSam's clothing than were women; only a couple of men removed her brassiere, and only 14 out of all the rescuers removed both the blouse and the brassiere. Interviews with the rescuers revealed that, despite clear AED instructions for complete clothing removal for proper CPR, most participants thought they only needed to remove enough clothing to place the defibrillator pads. The reluctance to reveal iSam's chest was most commonly pointed towards social norms and a concern for patient modesty. How can we improve patient care? Reasons for why female OHCA patients are less likely to be resuscitated than men have thus far only been suggested, not supported by data. In comparing the iStan and iSam results, Kramer et al. emphasize the importance of using realistic female patient simulators in CPR training: Up to this point, CPR training and research typically tend to use a single type of mannequin, which is described as having "perceived low levels of realism." Kramer's study suggests that unrealistic simulator models are insufficient for training medical professionals – much the general public – to deal with complex social norms and adequately tend to patients in case of emergencies. Further research is suggested to find effective ways to overcome societal and cultural inhibitions, and provide better care for female patients. Reference Kramer, C.E.; Wilkins, M.S.; Davies, J.M.; Caird, J.K.; Hallihan, G.M. (2015). Does the sex of a simulated patient affect CPR? Resuscitation, 86, 82-87. Image by Rama (Own work) [CeCILL or CC BY-SA 2.0 fr], via Wikimedia Commons --- ## Which head and neck positions are stressful for your horse during lunging? URL: https://noldus.com/blog/head-and-neck-positions-horse Published: 2015-04-17 15:20:00 Description: Being a horse owner and a Noldus employee is the perfect combination when it comes to keeping track of the scientific background for my horseback riding hobby. Being a horse owner and a Noldus employee is the perfect combination when it comes to keeping track of the scientific background for my horseback riding hobby. Since horses communicate differently than humans, I always wonder if I have a "happy athlete" when we are exercising together. Esmee Smiet and colleagues recently investigated the effects of different head and neck positions (HNPs) on behavior, heart rate variability (HRV) and cortisol levels in lunged Royal Dutch Sport horses. Interestingly, they were able to find significant differences in stress response between different head and neck positions, suggesting that there are indeed low stress and high stress ways to exercise your horse. Horses and people Almost all horse owners, from recreational riders to professional riders, have an opinion on the best way to train your horse. Recently, public awareness has been drawn to the welfare of sport horses and, in particular, dressage horses. For example, "Rollkur"- a position in dressage training/sports in which the head-neck position is hyperflexed - has led to much discussion in both the Fédération Equestre Internationale (FEI) as well as the general public. This training technique may cause unnecessary discomfort and possibly pain in horses; however, this effect has not been demonstrated in base level trained horses (Sloet van Oldruitenborgh-Oosterbaan et al., 2006 and Becker-Birck et al., 2012). There is a demand for scientific research on horse training methods to acquire objective information instead of opinions and to allow organizations such as the FEI to define new guidelines for training and competition. Head and neck positions investigated For Smiet's study, five standard predetermined HNPs were used. The figure below shows: (1) HNP1 (free, unrestrained); (2) HNP2 (neck raised, bridge of the nose around the vertical); (3) HNP4 (neck lowered and considerably flexed; nose pointing towards the chest); (4) HNP5 (neck raised and considerably extended; bridge of the nose in front of the vertical), and (5) HNP7 (neck lowered and flexed; nose pointing towards the carpus). HNP3 and HNP6 were not included in this study, as they were considered to be too similar to HNP2 and HNP4/7. Exercise test After warming up (8 minutes of unrestrained walk and trot) the animals were assigned to a specific HNP. The standard exercise test (SET) consisted of a 15 min. trot, 4 min. canter and 5 min. walk, followed by an unrestrained cool-down of 5 minutes. Measuring stress levels Before, during and after the SET the horse's behavior was recorded on camera and analyzed with The Observer. Their heart rate (HR) and heart rate variability (HRV) was measured with a telemetric device and the cortisol levels were measured via saliva and plasma samples. The complete ethogram can be found in Table 1 of Smiet's paper. Behavioral indicators of stress During the exercise, positive and relaxed behaviors such as ears pointing forward lasted significantly longer in HNP1, HNP5, and HNP2, as did playing with the bit in HNP4 and HNP7. The horses most often exhibited conflicting behaviors during exercise if they were in HNP2 and HNP5. Previous research has shown, and the authors of this study agree, that the horses probably learned which aids are for which HNP and might have anticipated positively or negatively, accordingly. During application of the side reins during HNP2 and HNP7, the horses showed an aversive anticipation. Interestingly, when in HNP4 the horses did not display any aversive anticipation even though past studies have suggested that HNP4 may have negative effects on airway function and neuromuscular transmission. Biological indicators of stress An HRV analysis revealed an effect related to stress in HNP2 and HNP4. The nervous system is possibly activated in these HNPs, resulting in a deviation from the normal HRV due to muscle fatigue, pain or altered respiratory function. This effect is in line with a previous studies on lactate dehydrogenase and increased intrathoric pressure during exercise in the same horses. Additionally, saliva measurements showed that of all the HPNs, the highest concentration of cortisol was found in HNP2 – thus further supporting the evidence of elevated stress levels. HNP2 is the worst The combination of behavioral and physiological data suggested that exercise positions which forced the horses' heads higher was more stressful compared with exercise in the hyperflexed HNPs. This study shows that HNP2 was the most prominent position for inducing HRV, cortisol levels and behavior responses. Based on the HRV and cortisol analyses, training in HNP7 may be preferable to HNP4/HNP2. The horses showed negative anticipation during applications of both HNP2 and HNP7. Smiet et al.'s research refutes the claim that hyperflexion results in discomfort for horses during exercise. These results are a step towards defining new guidelines for ethically training and competing with horses, and hopefully for better human and horse athletes across the world. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References E. Smiet; M.C. Van Dierendonck; J. Sleutjens; P.P.C.A. Menheere; E. Van Breda; D. De Boer; W. Back; I.D. Wijnberg; J.H. van der Kolk. (2014). Effect of different head and neck positions on behavior, heart rate variability and cortisol levels in lunged Royal Dutch Sport horses. The Veterinary Journal, doi: 10.1016/j.tvjl.2014.07.005. Read more about research on horses here. --- ## Gait research: let your animals walk freely URL: https://noldus.com/blog/gait-research Published: 2015-04-15 08:43:00 Description: Researchers use different ways to analyze gait in animals. In what instances would a study benefit from a system that is based on voluntary walking? Researchers use different ways to analyze gait in animals. Basically we can distinguish two methods: one can either observe or measure gait in an unrestricted manner, or one chooses a forced manner, such as a treadmill or treadwheel. A while back I wrote a post about pros and cons of these methods. Recently, we got in some questions about different ways to measure gait and locomotion in rats and mice, and in what instances a research would benefit from a system that is based on voluntary walking. In this post I will be touching base on some of the factors you can keep in mind when choosing a method for your study. Just like real life Many studies aim to (eventually) find relevant solutions for clinical problems. One might argue that the closer your study resembles real life, the better. What physicians do is closely watch how their patients move while they walk towards and away from them. In a lab situation, you can do something similar by letting the animal walk and observe closely. Traditionally, methods referred to as BBB scoring and paw inking have brought some standardization and comparability to these studies. The main advantage of unforced gait is that the animal is allowed to move at a speed that its gait (ab)normality or endurance will allow. The issue of speed Speed is an important gait parameter, but is also influences a lot of other parameters. This presents a dilemma for many researchers, creating the necessity to adjust for speed. One way of doing so is by regulating the speed in the test itself, using a motorized treadmill or treadwheel system. The question is if this really does eliminate variations in speed, because it only really assures you that all the animals walk with the same average speed. In practice, animals still constantly vary their speed moving up and down the treadmill. In fact, different animals will have different strategies to stay up to speed, which might lead to huge variations in walking speed. What's more, the stress of keeping up can even introduce gait artifacts. Eventually, you still have to adjust your results for their real speed. Intrinsic speed and software algorithms So, alternatively, you can choose to do just that: correct for speed in your results. The CatWalk method combines a walkway system with advanced software program that does exactly that. It allows animals to walk at their own intrinsic speed in an unforced manner, guided in a straight line due to the restriction introduced by the walls of the corridor. Training and a goal box at the end of the corridor learns and motivates the animal to walk in a straight and consistent manner. Afterwards, the software can adjust for speed and speed variations. Also, there is no need to work with bright lights. This way you can detect even subtle artifacts in gait in a non-artificial manner, all while introducing the least amount of stress on the animal. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Footfalls CatWalk XT is a very accurate method, measuring each footfall in detail unlike belt driven systems that often detect parts that are not actually touching the walkway. If you would like to learn about parameters extracted from these footfalls, you can read the following posts: - What a print can tell – about parameters extracted from each print - Going the distance – about parameters related to the relationship between prints - Time is of the essence – about the time relationship between prints and related parameters --- ## Video-tracking the effect of influenza infection on ferrets URL: https://noldus.com/blog/video-tracking-effect-influenza-infection Published: 2015-04-10 15:12:00 Description: Ferrets are the ideal animal model to assess influenza virus infection and pathogenicity as they display similar clinical symptoms to humans such as sneezing, fever and lethargy. A guest blogpost by Ding Yuan Oh, PhD Conventional ferret activity measurements by human observation Ferrets are the ideal animal model to assess influenza virus infection and pathogenicity as they display similar clinical symptoms to humans such as sneezing, fever and lethargy. Conventionally, lethargy or ferret activity is determined manually by an observer. However, this method is prone to bias and requires trained personnel to recognise subtle changes in individual ferret activity. Simple and less subjective method by video-tracking We assessed the usefulness of EthoVision XT as an alternative method to measure ferret activity throughout the course of influenza virus infection. We utilise mobility measurements such as activity, distance and velocity in EthoVision XT as a read-out of the 'activity level' of ferrets. In contrast to the conventional manual observation method, video-tracking by EthoVision XT proved to be a more sensitive method in detecting a reduction in ferret activity level after influenza infection. Not only does video-tracking provide greater detection sensitivity, it also simplifies the process of activity measurement by eliminating the reliance on trained personnel and being less subjective than the conventional method. Wide application to other ferret model of infection Our study is the first to use video-tracking to monitor the activity of ferrets. The ferret is a widely used animal model for studying influenza infection and is beginning to be adopted as a model for other infectious viruses such as Hendra virus, Nipah virus and SARS-CoV. Therefore, we anticipate that this improved method could be used to study both the pathogenesis of different viruses and the effectiveness of existing and novel therapeutic interventions in a ferret model. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial References Read more in the complete study: Oh, D.Y.; Barr, I.G.; Hurt, A.C. (2015). A Novel Video Tracking Method to Evaluate the Effect of Influenza Infection and Antiviral Treatment on Ferret Activity. PLoS ONE, 10(3): e0118780. --- ## Behavior and emotions of older adults URL: https://noldus.com/blog/behavior-emotions-older-adults Published: 2015-03-25 13:39:00 Description: Can TV footage motivate older persons to start being more active? Being active can improve the overall health of a person (65+ but of course also 65-!). With the predicted increase of the older persons population worldwide, it has become increasingly important to develop user-friendly products and services to assist older people in daily activities and improve their quality of life. Did you know that it is expected that in 2050 an estimated 1.5 billion people will be 65+, representing about 16% of the world's population?[1] Research projects on behavior and emotions of older adults Worldwide researchers focus on aging and health. Some study eating behavior in residential care homes which enables them to take environmental factors into account. Others focus on family relations and communication and try to facilitate and improve contact between parents and children living a distance apart. MIME – a recent project Understanding and acting upon emotional signals is very important. Showing different facial expressions is one way to express emotions. Researchers at TNO started a project called MIME (Memory Banks Interactive Metadata Extraction) that investigates the possibility of registering the emotions, reactions, and conversations of older persons viewers while watching television. They placed cameras and sensors in a living lab environment to measure the responses and aimed to automatically interpret and link these reactions to specific content to provide recommendations for the viewer[2]. Watching TV As part of the MIME-project the researchers posed the question: "Can TV footage motivate older persons to start being more active?" Being active can improve the overall health of a person (65+ but of course also 65-!). But what influences this behavior. Is this decision made conscious or unconscious? In this experiment they tried to increase the exercise motivation of the participants on an unconscious level in two ways. First by showing video fragments with inactive persons (sitting) or with active persons (hiking, riding his/her bike, etc.). Second, these fragments were from a period when the participants were adults themselves (1964-1980) or from the present showing older persons. Which combination would be most motivating: older versus recent footage, active versus passive persons, or another combination? In total the researchers prepared four 3-minute segments. Half of the participants watched active persons and the other half passive persons. Each participant (60-75 years of age) was asked to watch 2 videos, an older and recent video fragment. Living lab – living room TNO built a living room at their premises which they equipped with cameras and sensors to capture the behavior. In addition to TNO, Ziggo, and Noldus Information Technology made a financial contribution to this project. And now that the tests are completed, the researchers indicate that their results are encouraging! Motivation So can TV footage motivate older persons to start being more active? Yes. It seems possible. Especially the 'bad' examples – the older person sitting in a more recent fragment – seems to be motivating. As one of the participants stated: "I didn't feel a connection, because we are very active in sports, gardening, and we have a lot of hobbies and grandchildren. I didn't feel the connection with the sitting person". The researchers conclude that it seems that people want to stay active to prevent them from becoming an inactive older person as displayed in the video fragment. Old footage showing active persons also influenced the group. The footage seemed to take the participants back in time to an age where they were active and remembered them of how they used to be. So lots of potential to influence behavior on an unconscious level. Since the risk of becoming isolated or getting heath complications decreases with a healthy lifestyle, it is very important to find out what method of motivation works best! RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - http://www.nia.nih.gov/sites/default/files/global_health_and_aging.pdf - https://www.tno.nl/en/focus-area/industry/networked-information/information-creation-from-data-to-information/mime-memorybanks-interactive-metadata-extraction/ - Image courtesy TNO https://www.tno.nl/en/focus-area/industry/networked-information/information-creation-from-data-to-information/mime-memorybanks-interactive-metadata-extraction/ --- ## 10 behavioral studies on Alzheimer’s and Parkinson’s URL: https://noldus.com/blog/10-studies-alzheimers-parkinsons Published: 2015-03-17 12:31:00 Description: This blog post features 10 interesting studies that use innovative techniques to study models of AD and PD and important underlying neuronal mechanisms. Tomorrow the 12th International Conference on Alzheimer's and Parkinson's diseases (ADPD) in Nice, France starts. Last week I blogged about a study on Ginkgo biloba and Alzheimer's, and I thought this would be a great opportunity to highlight some more studies and get you in the mood for the conference.  10 behavioral studies on Alzheimer's and Parkinson's This blog post features 10 interesting studies that use innovative techniques to study models of AD and PD and important underlying neuronal mechanisms. Gait analysis and locomotion Several methods can measure gait and locomotion, and using an automated one gives researchers many advantages. Let's start with a recently developed technique called the ErasmusLadder method: a horizontal ladder with rungs that measures the motor performance but also learning abilities of mice. One of the great advantages of this method is that it is non-invasive. Specifically studying the cerebellum Vinueza Veloz et al. used this method to study the role of Purkinje cells, interneurons and granule cells of the cerebellar cortex in motor learning and adaptation, motivation, and avoidance behavior in several mouse strains. Read more about this research here. Motor deficits in Alzheimer's Sepulveda-Falla et al. described the study of a kindred of people in Colombia, in which 12% had Familial Alzheimer's disease (FAD). Clinical tests were complemented with ErasmusLadder testing, using APPsw/PS1Δ9 mice that showed deficits in both motor performance and associative motor learning. Read more here. FREE E-BOOK Basic behavioral neuroscience in rodents Want to know more about anxiety testing and other aspects of rodent research? Then, download our free e-book. - Including protocol suggestions - Theory behind behavioral paradigms - Why and how to test these Submit to download Illuminated footprints Another methods that measures gait is the CatWalk method, only this time a glass plate is combined with a light and a camera to capture the actual footprints on video. Researchers have used this to get data on anything from print dimensions to the time and distance relationships between footfalls. Parkinson's gait studied in different models Zhou et al. used three different oxidopamine injection sites to create PD mice and evaluated their gait with the CatWalk method and compare the results with clinical symptoms. Read more here.   Creating an AD mice model Plucinska et al. created AD-like endophenotypes in mice by expression of human bace1. Gait testing revealed only minor differences in gait in these animals, implicating no major motor impairments in this transgenic model. More studies using the CatWalk method can be found here. Video tracking Video tracking technology has proven useful in many studies of behavior, including movement and memory related studies on Parkinson's and Alzheimer's. RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Featured blog posts Resources Effects of typical PD treatment For example, Sgroi et al. used video tracking to investigate the link between two of the major long-term effects of the typical L-DOPA (levodopa) treatment: dyskinesia and motor fluctuations. Their results suggest different neural underpinnings. Nikolaus and her colleagues also did research on L-DOPA in relation to motor and exploratory behavior in rats. Read about both studies here. Caffeine helps AD mice remember Laurent et al. investigated the effects of caffeine on a transgenic mouse model with progressive AD-like tau pathology, and found that caffeine helped to maintain spatial navigation memory in tau-impaired mice. They used video tracking and water maze testing. Read more here. The link between AD and diabetes Serena Abbondante and her colleagues investigated the protein tau as a possible link between AD and diabeter, because according to them, recent evidence from animal models of diabetes shows that impaired insulin signaling causes tau hyperphosphorylation. Read about their study here. If you are interested in video tracking for your research, you can find a list of studies using the EthoVision XT software here. Or you can try it out for yourself with this free trial version. Parkinson's studied in zebrafish As seen in the examples above, rat and mouse models have proven to be very valuable in AD and PD research. Another animal that has helped the understanding of the underlying mechanisms of PD, is the zebrafish Zhao and colleagues studied bradykinesia using a PARK15 (atypical early-onset parkinsonism) zebrafish model. They used a DanioVision system that includes an environment for testing larvae in multi-well plates and a video tracking system. Morphants were less active or showed no locomotion at all. A typical apomorhpine treatment of PD restored the level of activity completely. Read more here. Lopes de Fonseca et al. reported on an interesting point mutation that has been linked to cases of familial PD. Zebrafish also express this gene, and this study using DanioVision showed that it plays a crucial role in embryonic development. Read more here. --- ## How Ginkgo biloba helps treat Alzheimer’s URL: https://noldus.com/blog/ginkgo-biloba-alzheimers Published: 2015-03-12 09:05:00 Description: Xu Liu and colleagues recently investigated the effects of Ginkgo biloba extract on a mouse model for Alzheimer’s disease (AD). Ginkgo biloba. Some of you might recognize it as a dietary supplement that is supposed to enhance cognitive function, but studies investigating these claims have mixed results. Xu Liu and colleagues recently investigated the effects of Ginkgo biloba extract on a mouse model for Alzheimer's disease (AD). Interestingly, they were able to confirm positive effects on AD pathology, such as improved memory, but only after long-term treatment. The cause of Alzheimer's One of the major hallmarks of AD is the build-up of amyloid beta (Aβ) plaques outside of the brain cells. These abnormal protein deposits cause inflammation, which damages the neurons, thus leading to the cognitive impairments seen in AD patients. A natural extract The dry extract from Ginkgo biloba leaves has exhibited anti-AD effects in several preclinical and clinical studies (for references, see the article from Liu et al.). To find out how this exactly works, Liu et al. focused on the effects of Ginkgo biloba on a molecular level. Transgenic mice on supplements The TgCRND8 APP-transgenic mouse overexpresses human mutated amyloid precursor protein (APP) in neurons, giving the mouse AD-like pathology. For Liu's experiment, 2-month-old mice were given Ginkgo biloba extract as a dietary supplement for 5 months and 5-month-old mice were given the same dosage for 2 months. Control groups received the same diets, but without the supplement. A long-term treatment Some supplements and drugs have to be taken for a while before they start to have any effect. This seems to be the case for Ginkgo biloba as well: At the end of the test period, mice's plasma levels were similar to levels found in humans taking the recommended dosage, inflammation in the brain was inhibited, and the loss of important proteins was attenuated. But this effect was far from immediate. Two months appeared to be too short a time frame to attain real results, and only the 5-month mice showed any significant improvement in cognitive function. Remember where to go The cognitive function of the mice was tested using a Barnes maze. This is a brightly lit, open disk with a number of holes around the circumference. One of these holes has a goal box underneath, providing a more preferable environment for the mouse. Mice typically learn to find this location using visual cues, similar to finding the platform in a Morris water maze test, and the traveling time and distance it takes them to enter the escape hole is used as a measure of spatial learning. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Ginkgo biloba helps in finding a safe place Using video tracking (EthoVision XT), the traveling time, distance moved, and velocity of the mouse was automatically measured in the Barnes maze test. Researchers found that all the AD-mice were able to use the spatial reference points to learn the location of the escape box. The more training they got, the easier it was for them to find it, as was reflected by the decrease in distance moved and travelling time. They did not get there faster by moving faster; the velocity of the mice did not increase over trials. That said, the mice receiving Ginkgo biloba over 5 months showed a significant decrease in travelling time and distance, confirming the positive effects that were found on a molecular level in plasma and brain samples. Ginkgo biloba helps in the long-term This study shows that Ginkgo biloba extract treats the dementia symptoms of AD-mice through various mechanisms of protecting the brain cells and enhancing the concentration of important proteins in the brain, but it appears that a prolonged duration of supplementation is required. These results suggest that Ginkgo biloba may indeed be helpful in improving the symptoms and daily lives of Alzheimer's patients. References Read more in the complete study: - Liu, X.; Hao, W.; Qin, Y.; Decker, Y.; Wang, X.; Burkart, M.; Schötz, K.; Menger, M.D.; Fassbender, K.; Liu, Y. (2015). Long-term treatment with Ginkgo biloba extract EGb761 improves symptoms and pathology in a transgenic mouse model of Alzheimer's disease. Brain, Behavior, and Immunity, doi: 10.1016/j.bbi.2015.01.011. - Read more about learning and memory tests in these blog posts, or about the application of the Barnes maze here. --- ## Motivation and eating: deep brain imaging in freely moving mice URL: https://noldus.com/blog/deep-brain-imaging Published: 2015-03-05 08:44:00 Description: Craving a snack, the joy of eating it. The part of our brain that regulates this is the lateral hypothalamus. An interesting targer for addiction and eating disorder research. Craving a certain snack, getting it from the fridge or at the store, then the joy of eating it. It's a familiar ritual for most of us. Scientist say we are performing appetitive and consummatory behavior, and the part of our brain that regulates these behaviors is the lateral hypothalamus (LH). You can imagine that this is an important element in the investigation of, for example, addiction and eating disorders. The problem is that the LH seems to be a mosaic of different neurons with different functions, making it difficult to specifically target them. The mystery of the mosaic So while it is widely known that the LH holds this crucial role, the precise functions and mechanisms of its many different neurons are still largely unknown. Joshua Jennings, Randall Ung, and their colleagues at the Stuber Lab (University of North Carolina) unraveled a part of this mystery when they identified and investigated a specific subpopulation of LH neurons. They did so by applying sophisticated techniques like optogenetics and micro-endoscopic imaging in active mice during conditioning paradigms and other behavioral tests. Their findings were recently reported in Cell. Behavioral tests In this study, several behavioral tests were combined with techniques to stimulate, inhibit, and even monitor the activity of specific brain cells (see below). A first test consisted of animals freely exploring a two-chambered arena with unlimited access to food. Video tracking automatically monitored the whereabouts and movement of the animal. This method is easily combined with techniques such as optogenetics. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Mice also underwent real-time place preference tests in which one of the two chambers was paired with either optogenetic stimulation or inhibition, and self-stimulation tests in which the mouse received optogenetic stimulation (reward) upon nose-poking. A PR3 (progressive ratio 3) test was used to measure motivation, and appetitive and consummatory behavior. After a nose poke, the mouse received a liquid caloric reward, then each successive reward required 3 more nose pokes than the previous. Licking while there was a reward (consummatory licks) or not (nonconsummatory licks) were measured. Unraveling brain function at cell-level The specific brain cells Jennings and Ung focused on are a subset of LH neurons that produce GABA (gamma-Aminobutyric acid), an important inhibitory neurotransmitter in the mammalian nervous system. The researchers first explored functional role of these GABAergic LH neurons using optogenetics to selectively stimulate or inhibit the specific cells, combined with video tracking to automatically track the location and movement of the animals. (Read more about optogenetics in this blog post.) When GABAergic neurons were stimulated, the mice spent more time in the food area and ate more. Mice also spent more time in an area that they had previously learned to associate with stimulation of these neurons. Optogenetic inhibition of these neurons led to less time spent in the food area, less eating, and less time in the location associated with this inhibition. The results implicate these neurons in the modulation of appetitive and consummatory behavior. Confirming the essential role in appetitive response and consumption The researchers used additional methods to further detail the role of the LH GABAergic neurons. Chemogenetic activation, for example, also enhanced consummatory behavior. But genetic ablation - essentially removing LH GABAergic neurons - blunted weight gain, reduced food intake, and decreased appetitive behavior and motivation, showing that these neurons are important for the regulation of appetitive responding, consumption, and energy balance. Deep brain imaging to detect cell activity So what remains is determining if appetitive and consummatory processes are regulated by the same or discrete neurons. To this end, the researchers used in vivo microendoscopic imaging, essentially implanting a mini-microscope into the mouse's skull. With this deep brain calcium imaging, the researchers were able to detect activity in individual LH GABAergic neurons while mice were freely moving and performing behavioral tasks. Each cell has its own task Researchers found that some neurons spiked in the presence of food, while others showed decreased activity. When mice had to work to get a reward, hundreds of neurons were active in response to either the consummation of the food reward (first lick after the reward delivery) or the unreinforced active nose pokes (appetitive response). Nonconsummatory licks after not receiving a reward for the nose poke led to much less neuronal activity. Microendoscopic imaging exposed the functionally distinct subpopulations of LH GABAergic neurons that encode aspects of appetitive or consummatory behaviors, but rarely both. The same neurons that respond to the presence of food during the free access feeding task also responded to the consummation of the reward and the nose pokes during the PR3 task. Mapping out the mosaic to find targets for addiction and eating disorders With this research, Jennings, Ung, and their colleagues showed that the lateral hypothalamus has distinct neurons regulating either appetitive or consummatory behaviors. This suggests that separate networks in the brain regulate the motivation to eat and the actual consumption of the food. The deep brain imaging technique in freely moving animals, especially during behavioral tests, has allowed the identification and even mapping of individual neurons. This no doubt opens up important opportunities for future research in specific targeting of these neurons and can eventually lead to the effective treatment of addictions and eating disorders. References Jennings, J.H.; Ung, R.L.; Resendez, S.L.; Stamatakis, A.M.; Taylor, J.G.; Huang, J.; Veleta, K.; Kantak, P.A.; Aita, M.; Shilling-Scrivo, K.; Ramakrishnan, C.; Deisseroth, K.; Otte, S.; Stuber, G.D. (2015). Visualizing hypothalamic network dynamics for appetitive and consummatory behaviors. Cell, 160, 516-527. Be sure to check out the supplementary material, including impressive videos of the deep brain imaging and mouse behavior. --- ## How autistic fruit flies behave URL: https://noldus.com/blog/how-autistic-fruit-flies-behave Published: 2015-02-26 13:21:00 Description: The number of children diagnosed with developmental disorders has increased exponentially in the past 20 yearschemicals such as BPA have been under investigation lately. The number of children with developmental disorders such as autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) has increased exponentially in the past 20 years: one out of six children in the US now suffers from a developmental disability. Of course some might say this sharp incline is due to better diagnostics and increased awareness; but whether or not this is the case, such a high prevalence is concerning. And since the environment is considered a strong contributor, chemicals such as BPA have been under investigation lately. BPA and developmental disorders BPA (bisphenol A) is a chemical used in plastic containers and the lining of food and beverage cans, meaning that a lot of us are exposed to it on a daily basis. BPA has been suggested to play a role in developmental disorders such as ASD. Thousands of studies have investigated the effects of BPA on rats, mice, monkeys, and zebrafish. Far fewer studies have been done with Drosophila melanogaster, which, according to Kulbir Kaur and colleagues, is a shame. Autistic fruit flies Drosophila melanogaster, or fruit flies, have little in common with humans…right? Surprisingly, many fruit fly genes are similar to human genes for normal cognitive functions. They exhibit complex behaviors relevant to humans. In addition, they are easy to maintain and reproduce quickly and in large numbers, giving them a significant advantage over rats and mice in research studies. In this study, Kaur et al. combined several behavioral assays evaluating autism-related impairments to examine the effects of BPA and evaluate the fruit fly as a model for developmental disorders. Altered movement patterns Fruit fly behavior was monitored with EthoVision XT, tracking the center point of the fly for 5 minutes and monitoring mobility according to pixel changes in the video image. Fruit flies that were exposed to BPA early on in life displayed disturbances in locomotion patterns that may relate to the decision-making and motivational state of the animal. BPA treated flies showed no difference in walking speed (velocity) or movement. Interestingly, the distance traveled was lower due to BPA. Clean as a fly The monitored changes on pixel level revealed that the small body movements (while the fly was staying in place) were increased in the BPA treatment group. When scoring grooming episodes from the same video recordings later, researchers could correlate these repetitive movements with an increase in grooming in the BPA flies. Poor decision making In their natural environment, flies constantly change direction in response to external cues such as food availability and predation risks. To quantify these behaviors, turn angle, angular velocity, and meander were used to assess change in direction and tortuosity. A small turn angle, for example, can indicate the immediate decision of a fly to change direction in response to something that it noticed in the environment. BPA treatment increased this angle, indicating a reduced ability of the fly to process and respond to changes in the environment. The authors draw a parallel here to the difficulty that ASD patients have in decision-making. BPA flies also showed more meandering, indicating they constantly reoriented themselves. Personal space Flies have a normal social space of about two body lengths, just like many other animals. Previous studies have shown that social isolation has a number of consequences for fruit flies, such as a decrease in their functional equivalent of the hippocampus (the mushroom bodies) and an increase in aggression. Hence, social behavior is recognized to be an important part of their everyday behavior. Kaur et al. found that BPA-exposed flies did not seem to care for personal space, clustering close together instead of maintaining a respectable social distance. The model fly With this research, Kaur and his colleagues both demonstrated some of the negative effects of BPA and argue the practically and validity of using fruit flies as an alternative model organism to rodents in the investigation of developmental disorders with a strong behavioral component. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Reference Kaur, K.; Simon, A.; Chauhan, V.; Chauhan, A. (2015). Effect of bisphenol A on Drosophila melanogaster behavior – a new model for the studies of neurodevelopmental disorders. Behavioural Brain Research, article in press, doi: 10.1016/j.bbr.2015.02.001. Read more about the fruit fly as a research model in this blog post. --- ## Location is everything: Measuring visitor behavior URL: https://noldus.com/blog/measuring-visitor-behavior Published: 2015-02-23 12:08:00 Description: Want to know where the action is? Interested in getting real-time feedback about a conference, concert, or event hotspots? Read more about the Crowd Emotion Monitor app. Want to know where the action is? Interested in getting real-time feedback about a conference, concert, or event hotspots? At the Measuring Behavior conference in August 2014, a number of meeting participants took part in an exciting experiment in which they received real-time updates on their own smartphones about the "hotness" of several conference events. Did this information lead them to the most interesting lectures, booths, or poster sessions? Crowd Emotion Monitor and SWEET These conference delegates were the first to test out a special app called the Crowd Emotion Monitor, which they installed on their own phones. This app was created with the goal of enhancing the overall user experience during conferences and other events. With further development, it could potentially also increase safety at mass events by monitoring the emotion of a crowd. Below you can see examples of the app (screenshots). SWEET is short for Sense & Tweet. In this project a software tool is being developed that combines state-of-the-art sensory, event processing, reasoning, and data communication technologies. The result is a Crowd Emotion Monitor, an application that assesses the behavior and emotion of groups of people and relays that information to stakeholders in a highly intuitive manner. The Crowd Emotion Monitor is being developed in the context of COMMIT, a Dutch public-private research program in information and communication science. Partners of the consortium are CWI/MonetDB, TNO, University of Twente, VicarVision, and Noldus. To quote Lucas Noldus in I/O Magazine about the technique: "For example, during a conference, smartphone cameras will measure facial expressions of visitors. This large amount of data is sent to servers. There, data information gets translated real-time into information and is sent back to the smartphone at that conference. By doing so, now all new participants on that conference are able to check on their smartphone on all these different emotions that are taking place at all different parts of the conference. With this information they can pick choose for the part of the conference that appeals to them the most." Measuring consumer or visitor behavior Combining information from many mobile devices at once makes it possible to gauge the reactions of a crowd. The SWEET app measures location, emotion (of the phone user or others), and subjective feedback via a participant survey in order to draw a complete picture. TrackLab could help researchers gain insight into spatial behavior by combining all the tracks (visitors at a conference moving around). During an experiment, participant responses are used to give real-time feedback, with the idea that users will flock to the location with the most positive ratings. The app shows an 'emotion map' of the conference venue, using the combined data to generate a visual heat map and indicate hotspots. FREE DEMO Try TrackLab yourself! Request a demo to obtain real-time insights into a wide range of spatial behaviors. - Accurate tracking data - Gain insights into consumer behavior - Easily access, export, and analyze data Free Demo More to come The experiment at Measuring Behavior 2014 demonstrated how multimodal measurements can create insight into group processes. It also inspired the participants to think about other applications of this new technology. Back to the original question: Did this information lead them to the most interesting lectures, booths, or poster sessions? Not that many people participated, but the SWEET development team received useful feedback regarding the pros, cons, and added value of this type of data collection and analysis. Want to follow the development of SWEET? Check out COMMIT's website. Save the date! More information about upcoming Measuring Behavior conferences on measuringbehavior.org or join the Measuring Behavior group on LinkedIn. --- ## How to measure the social behavior of Fragile X mice URL: https://noldus.com/blog/social-behavior-of-fragile-x-mice Published: 2015-02-20 15:26:00 Description: The treatment of Fragile X syndrome is limited to the symptoms. One of the factors currently holding back drug development is the difficulty of finding a reliable behavioral test for neurobiological studies. Fragile X syndrome (FXS), formerly known as mental retardation, is a common developmental disorder with a prevalence of 1 in 3600 to 4000 males and 1 in 4000 to 6000 females (www.fragilex.org). Besides the intellectual challenges, patients often show behavioral abnormalities, which in a large part of the male patients strongly resembles autism-like behavior. Unfortunately, treatment of FXS is limited to the symptoms – think of behavioral therapy or pharmaceuticals to treat attentional deficits, anxiety, and impulse control problems. Finding a treatment According to Celine de Esch and her colleagues at Erasmus MC (Rotterdam, The Netherlands), one of the factors currently holding back drug development is the difficulty of finding a reliable behavioral test for neurobiological studies and drug screening. Their recent paper in Neurobiology of Disease describes a good candidate: the Automated Tube Test (ATT). Automated Tube Test The ATT is an apparatus with two goal boxes connected by a tube. This tube is just big enough for one mouse to pass, so when two mice meet each other in the middle, one is forced to back down. The one that ends up in the other one's start box is designated the winner. The location of the mice is monitored using infrared light beams. When a mouse is reluctant to leave the start box, an air puff is applied to motivate them. This way, human intervention is limited. Mouse model The Fmr1 knockout mouse is a model for FXS, exhibiting many hallmarks of the disease. It has been substantially validated in literature; however, behavioral phenotypes can vary greatly between labs. De Esch et al.'s experiment used the ATT and a thorough training and housing regimen to find that these FXS mice show a robust phenotype in the test. Dominant FXS mice After thorough habituation and training, De Esch tested FXS and wild-type (WT) mice together in the ATT. At first, FXS mice turned out to be clear winners across the board, showing robust social dominance. However, this seemed to be strongly influenced by social experience: Prior to starting the ATT rounds, the mice were housed in pairs – each FXS mouse with a WT littermate – but when the housing was changed to couples with the same genetic background, mice from both genotypes won an equal proportion of the matches. The social dominance of FXS mice did appear to be intrinsic, because when housed individually, they again won significantly more matches than WT mice. Partial rescue by mGluR5 manipulation FXS is caused by a lack of the FMR protein, and in its absence, signaling of the small brain receptor protein mGluR5 goes into overdrive. This causes many of the neurological problems in FXS, so the researchers also investigated both genetic and pharmaceutical rescue strategies that targeted mGluR5. Both interventions of the mGluR5 signaling normalized the outcomes in the tube test; however, the change was not enough for a complete rescue of the social behavior. Future translational studies According to Celine de Esch and her colleagues, the ATT is a robust and reliable behavioral test for this FXS mouse model. The limiting of human intervention compared to the manual version of this test has distinct advantages, such as a high level of precision. Additionally, the robustness of the behavioral phenotype of the Fmr1 KO model in this test shows promise for future translational studies. RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References Esch, C.E.F. de; Berg, W.E. van den; Buijsen, R.A.M.; Jaafar, I.A.; Nieuwenhuizen-Bakker, I.M.; Gasparini, F.; Kushner, S.A.; Willemsen, R. (2015). Fragile X mice have robust mGluR5-dependent alterations of social behavior in the Automated Tube Test. Neurobiology of Disease, 75, 31-39. --- ## Side effects of L-DOPA investigated in parkinsonian rats URL: https://noldus.com/blog/l-dopa-and-parkinsonian-rats Published: 2015-02-16 11:00:00 Description: These studies specifically investigate the long-term effects of L-DOPA or levopoda, a common clinical treatment for Parkinson's disease, with which many patients struggle. Just recently, I blogged about a Parkinson's disease (PD) study that compared the locomotion of Parkinsonian rats to those of human patients using automated gait analysis. Following up on that, this time I would like to highlight two recent Parkinson's studies that use video tracking for their behavioral analysis. These studies specifically investigate the long-term effects of L-DOPA or levodopa, a common clinical treatment for PD, with which many patients struggle. Side effects of common PD treatment Shortage of dopamine in the brain is the well-known cause of PD. L-DOPA (levodopa) is often used to treat PD, but while it initially compensates for the dopamine deficiency, inhibitory feedback eventually leads to more dopamine depletion, resulting in dyskinesia (involuntary muscle movements), motor fluctuations, and the 'wearing-off' of the effects of the medication. Open field motor and exploratory behaviors In 2014, Susanne Nikolaus and her colleagues published their research on the influence of L-DOPA on the binding of dopamine to its receptor in relation to motor and exploratory behavior in rats. Nikolaus tested two different dosages of the drug. To assess behaviors, an open field set-up (PhenoTyper) and automated video tracking software were used. The distance travelled was monitored by EthoVision XT and in addition, several specific behaviors were rated: ambulation, sitting still, rearing, head-shoulder motility to assess motor activity and non-selective attention, and grooming*. More drugs is more dopamine and less activity Treated animals showed less head-shoulder motility and more sitting, and imaging of dopamine receptor binding (DAT imaging) indicated an association between this decrease in activity and an increased availability of dopamine. Both doses of the drug reduced the binding of dopamine to its receptor and made the animals less active in a dose-depended manner. The findings also suggest that the decline in activity after L-DOPA administration may be due to the drug's effect on the rate of behavioral habituation to a novel environment. Are the side effects of L-DOPA linked? In another study on L-DOPA, Stefania Sgroi and her colleagues (2014) investigated the link between the long-term side effects, dyskinesia and motor fluctuations. Spontaneous motor activity in rats was measured before PD-inducing surgery and before treatment, during treatment, and after treatment with L-DOPA. Open field activity testing To measure activity, rats performed an open field test for two periods of 15 minutes. During these tests, they were video-taped, and their activity was automatically measured by EthoVision XT video tracking. The variables included total distance moved, mean velocity, maximum distance moved, and frequency of full rotations. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Different neural mechanisms The researchers found no correlation between the dyskinesia and spontaneous locomotor activity. Interestingly, an L-DOPA withdrawal effect was observed, with motor performance being worse after the treatment than before the start of the treatment. This suggests that different neural mechanisms underlie these two long-term effects of L-DOPA usage. Automatic behavior recognition Nikolaus and her colleagues used a set of distinct behavioral markers in their study, including rearing, resting, and grooming. Did you know that these and other behaviors can be automatically identified with EthoVision XT video tracking? You can read about Automatic Rat Behavior Recognition on our website. References - Nikolaus, S.; Beu, M.; De-Souza-Silva, M.A.; Huston, J.P.; Hautzel, H.; Chao, O.Y.; Antke, C.; Müller, H.W. (2014). Relationship between L-DOPA-induced reduction in motor and exploratory activity and degree of DAT binding in the rat. Frontiers in Behavioral Neuroscience, 8(431), doi: 10.3389/fnbeh.2014.00431 - Sgroi, S.; Kaelin-Lang, A.; Capper-Loup, C. (2014). Spontaneous locomotor activity and L-DOPA-induced dyskinesia are not linked in 6-OHDA parkinsonian rats. Frontiers in Behavioral Neuroscience, 8(331), doi: 10.3389/fnbeh.2014.00331 --- ## Parkinson’s & gait impairment: comparing rats and humans URL: https://noldus.com/blog/parkinsons-gait-impairment Published: 2015-02-05 11:51:00 Description: Gait impairment is one of the most prominent symptoms of Parkinson's disease. For good research you need good models and good tests. When you hear about Parkinson's disease (PD), the first thing that comes to mind is probably impaired movement. And that there is no cure. As PD is one of the most common neurodegenerative diseases, you can imagine why it is the focus of many drug development and clinical studies. Studying gait impairment of PD Dr. Ming Zhou and colleagues (Southern Medical University, Guangzhou, China) felt that gait impairment, though it is one of the most prominent symptoms of PD, is still insufficiently studied in research. Before learning how to treat any symptoms, however, you first need to be able to examine them in detail. Simply put, you'll need two basic ingredients; good models and good tests. Parkinsonism in rats PD – its symptoms, neurology, and possible treatments – is often studied in rat models. Dr. Zhou et al. first created different rat models for PD and compared their locomotion to clinical symptoms in human patients. A common method to induce Parkinsonism in rats is by injecting oxidopamine into the brain, thus destroying dopaminergic and noradrenergic neurons. In this particular study, three different injection sites were used (the caudate putamen (CPU), medial forebrain bundle (MFB) and substantia nigra compact (SNC)) to create three different models. How to effectively study gait impairment To evaluate the gait of their rats, Zhou and colleagues used CatWalk XT, a gait assessment apparatus that automatically records the footprints of a rat moving voluntarily (completely unforced) from one end of a walkway to the other. Using the footprint data (their placement, dimensions, timing, etc.), the software measured and calculated several parameters. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources And the best model is… The researchers found that the MFB model was the best out of the three for studying PD related gait impairment, showing a stable loss of dopaminergic neurons as well as accompanying gait impairments. Comparing rats and humans Stance, step cycle, and duty cycle were all increased in the impaired rats, similar to clinical PD symptoms of taking small, slow steps. There also was a longer duration of contact between the paws and the glass, which can be compared to PD patients having an increased stance duration. Additionally, the increase of the terminal dual stance in limbs that was found in this study can be translated to the delays or freezing of gait, or gait hesitation, as seen in these patients. These results may be useful in future research into the disease progression and therapeutic methods for PD. References Zhou, M.; Zhang, W.; Chang, J.; Wang, J.; Zheng, W.; Yang, Y.; Wen, P.; Xiao, H. (2015). Gait analysis in three different 6-hydroxydopamine rat models of Parkinson's disease. Neuroscience Letters, 584, 184-189. --- ## How males and females are different: can this explain autism? URL: https://noldus.com/blog/males-females-differences-autism Published: 2015-01-22 11:00:00 Description: Women and Venus, men and Mars, right? In mice, the establishment of social hierarchies is sex-dependent. Women and Venus, men and Mars, right? Men and women are fundamentally, biologically, and emotionally different. We also act differently in social situations. Wouter van den Berg and his colleagues at the Erasmus University Medical Center (Rotterdam, The Netherlands) recently published an interesting study that, using mice, shows the establishment of social hierarchies as being sex-dependent. Autism caused by an extreme male brain? These sex differences are especially interesting in light of the 'extreme male brain theory' that suggests that autism behavior is actually an exaggeration of typical sex differences. In their 2006 paper, Knickmeyer and Baron-Cohen suggest that high testosterone levels during prenatal and neonatal brain development play a causal role in the development of autism. Organizational effects of hormones in early development Population-based studies have shown that autism occurs two to three times more often in males than in females. Also, testosterone is vital in the development of a male brain, and – as studies show – dysregulation of this testosterone-dependent masculinization can increase the chances of developing social impairments. This might explain why the prevalence of autism is higher in males. Social differences and the role of testosterone Aberrant social behavior is one of the most prominent symptoms of autism. Yet the biology behind this is still largely unknown. Van den Berg et al. investigated the differences in social behavior between male and female mice, and the role of testosterone in this story. Social dominance tube test Social behavior, or in this case social dominance, was tested using the automated tube test. In short, this is a fully automated apparatus consisting of two goal boxes connected by a tube. This tube is just big enough for one mouse to pass, so when two mice meet each other in the middle, one is forced to back down. The one that ends up in the other one's start box is designated the winner. By performing several matches like this, a hierarchy structure can be determined. Interestingly, Van den Berg and his colleagues found that the way this hierarchy is structured differs between males and females. In other words, social strategy is sex-specific. Match-fixing Several tournament designs were used to test the animals' social strategy. The 'intrinsic attributes' tournament was based on the concept that if mouse A won against mouse B and mouse B won against mouse C, then mouse A should win over mouse C. If this was true, then it could be argued that the animals' social hierarchy was established using intrinsic attributes. Another tournament tested the effect of prior experiences on social dominance. In this case, matches were fixed, meaning that one of the doors to the start/goal box was closed, and only one mouse could win. Then another match between the same mice, this time honest, tested whether their previous experience determined the second outcome. Sex-dependent social strategies From these different tournaments it became evident that while female mice used intrinsic attributes to establish social hierarchies, males were strongly influenced by prior experience. Testosterone was identified as a critical sex-specific factor in determining the social strategy used: Castrated males utilized a similar social strategy as females, and females implanted with testosterone pellets used a typically male strategy. Similarly, males that inherited a null mutation of the sex-determining region Y (Sry) gene and females with transgenic expression of Sry also showed a reversal of their social cognitive strategy. Translational value for autism research Van den Berg's results show that there are sex-specific and testosterone-dependent differences in the establishment of social hierarchies in mice, which is consistent with the extreme male brain theory. These intricacies of social dimorphism could greatly complement translational studies in autism research. References - Berg, W.E. van den; Lamballais, S.; Kushner, S.A. (2014). Sex-specific mechanism of social hierarchy in mice. Neuropsychopharmacology, doi: 10.1038/npp.2014.319. - Knickmeyer, R.C.; Baron-Cohen, S. (2006). Fetal testosterone and sex differences in typical social development and in autism. Journal of Child Neurology, 21(10), 825-845. --- ## Why non-verbal behavior matters URL: https://noldus.com/blog/why-non-verbal-behavior-matters Published: 2015-01-21 10:20:00 Description: Basil Preisig and his colleagues at the University of Bern, Switzerland, were especially interested in communicative development of people diagnosed with language disorders like aphasia. Take a typical conversation: Hello, how are you? Fine! How are you? {pause} Fine! Shall we ……etcetera. The opening of this conversation is highly structured, isn't it? The process of turn taking is a crucial and cooperative aspect of conversational speech. Gestures are also of great importance. When your feet are already turned to the door, you are getting ready to run out. Try to read your own signals and you will see! Conversation closers In a conversation we include hints like conversation openers, closers, and shifters. It's a feeling we're all familiar with: you're trying desperately to end a conversation, and the other person keeps on talking and does not read the clues you are giving. You say: "Anyway… " {…Person B keeps talking} "see you Thursday, all right?" and edge toward the door… {Person B talks over you.} "Thursday noon, was it, right?" {Person B still doesn't get the hint to leave.}…and so on. In this frustrating exchange, Person B repeatedly ignores your conversation closers, both verbal ("right", "all right", "anyway") and nonverbal. Social interactions Social interactions are subjective to culture, but some behaviors, especially those related to conversation, remain consistent across the world. What methods do researchers use to gain insight into verbal behavior? Nonverbal cues are an equally important part of conversation, as they provide additional information between interlocutors. Basil Preisig and his colleagues at the University of Bern, Switzerland, were especially interested in communicative differences between healthy control subjects and people with language disorders like aphasia. Why non-verbal behavior matters: Understanding the message In his study, Preisig tracked eye movement in aphasic patients and concluded that co-speech gestures helped guide the observer's attention towards the speaker's face. As the source of semantic input, the speaker's face was the natural focal point for both healthy and aphasic subjects; but in some cases, accompanying nonverbal signals were needed to direct the listener's focus. Preisig's project was aimed specifically at gaining more insight into the visual exploration strategies of aphasic patients. Measuring focus A total of sixteen aphasic patients and 23 healthy control subjects participated in the study. To each subject, Preisig and colleagues presented videos of two people engaging in spontaneous dialogues. An infrared eye tracking device enabled the researchers to follow each subject's gaze behavior and calculate the amount of time they fixated on the speaker's face, hands, and body. Furthermore, eye movement recordings were synchronized with event data – co-speech gestures and voice activity of the actors – to get the complete picture. Eye movement and co-speech gestures The presence of gestures was rated frame by video frame using The Observer XT software. As expected, aphasic patients fixated less on the speaker's face than did healthy controls. The researchers also found that the presence of co-speech gestures greatly encouraged subjects to look at the speaker; however, the aphasic patients did not seem to fixate on the gestures themselves. According to Preisig and colleagues, people with aphasia tend to have limited attentional resources that then become allocated to focusing more on the acoustic speech signal than the visual speech signal. They refer to other studies to illustrate this conclusion. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Guiding attention In conversation, gestures help guide attention to the speaker, the source of semantic input. However, it might be the case that the visual signal interferes with the auditory signal and subtracts from the attentional resources of a listener. This is interesting material for further research. References Preisig, B.C.; Eggenberger, N.; Zito, G.; Vanbellingen, T.; Schumacher, R.; Hopfner, S.; Nyffeler, T.; Gutbrod, K.; Annoni, J.; Bohlhalterc S.; Muri, R.M. (2015). Perception of co-speech gestures in aphasic patients: A visual exploration study during the observation of dyadic conversations. Cortex, 64, 157-168. --- ## How young zebrafish cope with stress URL: https://noldus.com/blog/how-young-zebrafish-cope-with-stress Published: 2015-01-15 14:26:00 Description: Stress is a natural thing, and how we cope with it differs from person to person. In research, we use the term coping style, something that emerges early on in life for zebrafish. We are all a bit stressed from time to time. Maybe some of you a bit more than usual right now, it being the post-holiday, catch-up-with-everything season and all… But stress is a natural thing, and how we cope with it differs from person to person. In research, we use the term coping style. And now Christian Tudorache and his colleagues from Leiden University (The Netherlands) have found that these coping styles emerge early on in life, or at least they do in zebrafish. They recently published a paper in Stress. Coping styles based on the emerging test Coping styles can be defined as either proactive or reactive, with proactive individuals being more explorative, bold and aggressive, while reactive animals are shy, nonexploratory and nonagressive. To investigate the difference in behavior and physiology between young individuals with different coping styles, Tudorache and his colleagues used an emergence test to identify zebrafish larvae (8 days post fertilization) as early emerging (EE) and late emerging (LE) based on their order of exit from a dark shelter into a well-lit environment. These EE and LE results correspond with pro-active and re-active coping styles, respectively. Netting stress The two larval groups were separated into well plates. During acclimatization and a recording period of 15 minutes, the larvae were able to swim around freely in the well plate. Subsequently, a strong stressor was applied: during a netting procedure larvae were suspended into the air for one minute, three times in a row. Then a second recording period of 30 minutes commenced. Kinematics and physiology During both recording periods, video recordings were made from above and swimming kinematics were measured with video tracking software EthoVision XT. To assess the physiological stress response, whole-body cortisol measurements were also taken. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Coping styles correlations The two groups showed significant differences in both behavior and physiology. Contrary to what you might expect, the late emerging (LE) larvae were more active with a larger distance travelled and higher overall velocity than the early emerging (EE) larvae. With that amount of movement, it is somewhat surprising that LE larvae did not find the exit to the lighted area more easily during the emergence test, but apparently that was not the deciding factor. Maybe scototaxis plays a role? Recovery after stress The EE zebrafish did show straighter swimming lines based on swimming directionality, and, after the stressor of netting was applied, a quicker recovery to their normal activity levels than LE fish. Also, cortisol levels spiked higher in EE larvae, but again, baseline levels were recovered more quickly. Coping at a young age Tudorache and his colleagues found that zebrafish already show differences in coping style at a young age, both in behavior and physiology. This is a very nice starting point for further research. Zebrafish, as a typical vertebrate, again prove to be a useful model in the medical field and for conservation and animal welfare research. Read more about the methods and results of this study in the complete publication: - Tudorache, C.; Braake, A. ter; Tromp, M.; Slabbekoorn, H.; Schaaf, M.J.M. (2014). Behavioural and physiological indicators of stress coping styles in larval zebrafish. Stress, doi: 10.3109/10253890.2014.989205 For more information about tools for zebrafish research go to EthoVision XT. Thanks to Christian Tudorache for providing additional information about this research! --- ## Zinc deficiency, depression and electrical signals in the brain URL: https://noldus.com/blog/zinc-deficiency-depression Published: 2014-12-18 11:15:00 Description: Depression has a dramatic effect on quality of life because it results in a persistent low mood that is accompanied by a low self-esteem and a loss of interest in things that give pleasure. Major depressive disorder The chance that one of us will suffer from a major depressive episode during our life is approximately 10% [1]. Depression has a dramatic effect on quality of life because it results in a persistent low mood that is accompanied by a low self-esteem and a loss of interest in things that give pleasure [2]. Reason enough to carry out research on the background of major depression. Current versus new medicines Traditional medicines to treat a major depression increase the activity of monoamine neurotransmitters like serotonine or dopamine. However, it may take four to six weeks before these medicines have any effect and for a large percentage of people, they do not work at all. More recently, focus has shifted towards N-methyl-D-aspartate receptors (NMDAR), which allow transfer of electrical signals between neurons in the brain and the spine. Treatment with ketamine, which is an NMDAR inhibitor, had an antidepressant effect on patients that are resistant to monoamine-based medicines. Furthermore, this effect is immediate, in contrast to monoamine-based medicines. Does zinc deficiency cause depression? Ursula Doboszewska and colleagues [4] investigated the effect of zinc, an NMDAR inhibitor, in rats on behaviors associated with depression. In addition to this, the authors assessed the effect of zinc deficiency on several chemicals that are associated with NMDAR. The authors kept rats on either a zinc deficient diet or a normal diet for four or six weeks. Then they assessed depression in a Porsolt Forced Swim test, in which the rats are placed in a water cylinder. In this test the duration of immobility, during which the rats do not try to escape or swim, is a measure of depression. The authors also determined locomotor ability, the motivation to consume sucrose, and social interaction with another rat. To score social interaction, behavior was annotated and analyzed in The Observer XT annotation software. In addition to this, the concentration of several compounds associated to NMDAR was measured in the rats' hippocampus and prefrontal cortex. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Zinc deficient rats are depressed The rats that were on a zinc deficient diet had longer periods during which they were immobile and did not struggle or try to escape in the Porsolt Forced Swim test. This is a measure for depression-like behavior. In addition to this, the zinc deficient rats were less motivated to consume sucrose. This is a measure for anhedonia, which is the inability to gain pleasure from enjoyable experiences. In the behavioral observations, the zinc deficient rats showed less social behaviors, like sniffing the other rat or licking the other rat's fur. There was no effect of zinc deficiency on locomotion. These results together indicate that zinc deficiency induces depression. Zinc deficiency alters NMDAR The chemical analysis of the rats' hippocampus and prefrontal cortex showed that several chemical compounds associated with NMDAR were affected. It looks like zinc deficiency alters the way NMDAR functions in the brain and thereby alters the transfer of electrical signals through the nerves. The effect on the compounds associated with NMDAR was larger in the hippocampus than in the prefrontal cortex and took longer to become apparent in the prefrontal cortex. Interestingly, the hippocampus is the brain area with the highest zinc concentration. Therefore, NMDAR in the hippocampus may be more susceptible to zinc restriction. Concluding The authors conclude that zinc deficiency causes behavioral changes in rats that resemble depression. Furthermore alterations in NMDAR may be involved in the pathology of depression. Zinc deficient rats are a valuable model to study depressive behavior and its chemical background. References - 1.Epidemiology of depression - 2.Major depressive disorder - 3.NMDA receptor antagonist - 4.Doboszewska U, et al, Zinc deficiency in rats is associated with up-regulation of hippocampal NMDA receptor, Prog Neuro-Psychopharmacol Biol Psychiatry (2014), doi:10.1016/j.pnpbp.2014.09.013 --- ## Fearful chicken: Fear affects stress, behavior patterns, and other individuals URL: https://noldus.com/blog/fearful-chicken Published: 2014-12-16 15:43:00 Description: Elske de Haas, Ph.D. studied the effects of fearfulness on the chickens' own behavior and physiology, but also what it did to other individuals. A guest blog post by Elske de Haas, Ph.D. Fear and stress Being fearful is a state which most humans have experienced at some point in their life. By being easily frightened and anxious, many species show to be very sensitive to stress. Many studies have shown that anxiety can be influenced by the neurophysiological characteristics of an individual. It appears that heightened levels of corticosterone as well as low levels of serotonin constitute to many neuro-pathological disorders, such as depression and obsessive compulsive disorder (OCD). To chicken out We studied the domesticated laying hen chicken (Gallus Gallus domesticus), and found that levels of serotonin coincide with high levels of anxiety and development of feather pecking, a maladaptive behavior which shows similarities with the human OCD trichotillomania [1,2]. We used the Observer XT to assess fearful behavior of young chickens inside the Open Field. The chickens that responded highly fearful were found to be more reactive to stress at an adult age. The level of corticosterone (a hormone involved in the flight-fight response) was elevated in fearful chickens compared to non-fearful chickens. Contagious stress? We further studied the influence fearful chickens may have on their group members. As can be imagined, a highly stressful individual may affect its group mates. Indeed, we found that the group members of fearful chickens were exhibiting higher levels of corticosterone compared to group members of groups with no fearful chicken present. How this exactly works remains to be further studied. But we did find some evidence that activity patterns differ in fearful and non-fearful animals whereby potentially the fearful animals influence the whole group. When using the Observer Package on a PSION Workabout for home-pen behavior activity of individuals, by means of scan sampling. We found that fearful chickens are significantly more active than non-fearful chickens. Evidence was also found that if in a group more aggressive interactions took place this also led to higher stress levels [3]. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - 1.E.N. de Haas, B. Kemp, J.E. Bolhuis, T. Groothuis, T.B. Rodenburg, 2013. Fear, stress, and feather pecking in commercial white and brown laying hen parent-stock flocks and their relationships with production parameters. Poultry Science, 92, 9, 2259-2269. - 2.M.S. Kops, E.N de Haas, T.B. Rodenburg, E.D. Ellen, G.A.H. Korte-Bouws, B. Olivier, O. Güntürkün, J.E. Bolhuis, S.M. Korte, 2013. Physiology & Behavior, 120, 3, 77-82. - 3.E.N de Haas, M.S Kops, J.E. Bolhuis, T.G.G. Groothuis, E.D. Ellen, T Bas Rodenburg, 2012. The relation between fearfulness in young and stress-response in adult laying hens, on individual and group level. Physiology & Behavior, 107, 3, 433-439. Elske, thank you so much for providing us with the details of your study and a free case study for everyone to download! --- ## The impact of health information technology on doctor-patient interaction URL: https://noldus.com/blog/health-information-doctor-patient-interaction Published: 2014-12-12 08:39:00 Description: Embracing the technological advances of the last decade, many health care professionals have incorporated information technology into their daily routines. Embracing the technological advances of the last decade, many health care professionals have incorporated information technology into their daily routines. Doctors can carry patient files around on their tablets or laptops and can quickly update a status when needed. Convenience has without a doubt increased, but does such easy access to technology impact the quality of doctor-patient interactions? Researchers from the Medical College of Wisconsin, the University of Wisconsin–Madison, and Northwestern University's Feinberg School of Medicine examined and compared clinically experienced primary care physicians' use of paper medical records and an electronic health record (EHR) (Asan et al., 2014) in order to gain insight into doctor-patient interaction. Human or technology centered? Dr. Onur Asan and colleagues explain that a recent study (Asan and Montague, 2012) identified three different interaction styles that primary care physicians may use with an EHR in the examination room: (1) technology centered; (2) mixed (displaying both technology-centered and human-centered behaviors); and (3) human centered. Technology-centered doctors were reported as, in general, younger doctors who typed more and made less eye contact with patients. Human-centered physicians were reported as more clinically experienced, older doctors with less screen time and more face time with patients, who tended to use papers or dictation for documentation during the visit rather than typing. This blog focuses on a recent study of Asan and his colleagues published in Journal of Evaluation in Clinical Practice, 2014. According to the researchers, this study's results add to the improvement of EHR design to help accommodate physicians with lower computer skills, and hopefully facilitate better physician–patient communication. Physician-patient communication A total of 80 primary care visits were recorded in this study, and the videos were coded afterwards in great detail using The Observer XT software. The behaviors compared by Asan et al. included: physician gaze at patient, physician gaze at computer monitor, physician gaze at paper chart, shared gaze at chart and shared gaze at computer monitor. All behaviors were part of a coding scheme, and start and stop times were annotated for each code. After all the videos were coded, the software calculated the start and stop times, duration and simultaneous occurrence of two or more behaviors. For medical encounters including the EHR, the researchers placed three video cameras as unobtrusively as possible in each examination room. The cameras were positioned to capture the face of the physician as he/she looked at the health record, the patient while sitting in a chair, and both physician and patient for overall interaction. For paper based settings, one high-quality video camera was used to record overall interactions in the examination room. Results and future implications To understand how experienced physicians interacted with EHRs and patients, the researchers measured eye gaze durations. The results show, for example, that the proportion of time that physicians spent looking at medical records during EHR visits (gaze at computer monitor and gaze at printed copy of portion of the EHR or worksheet) was significantly greater than during paper chart visits. If physicians are spending a lot of time looking at reports instead of the patient, the researchers conclude, their patients' perception of the overall visit may be negatively affected. Asan hopes that his findings will contribute to the improvement of future EHR designs. As we learn more about the detractors of our existing systems, physicians will be better trained, and technological barriers such as voice and writing recognition will be improved. Our next big challenge, according to Asan, is to modify the design of the current EHRs to enhance the physician-patient experience while simultaneously improving quality of care and decreasing costs. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - Asan, O.; Smith, P.D.; Montague, E. (2014). More screen time, less face time – implications for EHR design. Journal of Evaluation in Clinical Practice. doi:10.1111/jep.12182 - Asan, O. & Montague, E. (2012) Physician interactions with electronic health records in primary care. Health Systems, 1(2), 96–103. --- ## Ladybugs and lacewings do not spy on their prey’s alarm pheromone URL: https://noldus.com/blog/aphid-predators Published: 2014-12-08 13:18:00 Description: Leaf sucking creatures like plant aphids are common and can cause considerable damage to plants. Therefore, quite a lot of effort is made to control these tiny creatures. Leaf sucking creatures like plant aphids are common and can cause considerable damage to plants. Therefore, quite a lot of effort is made to control these tiny creatures. And because of environmental awareness, sustainable methods to control aphids are well developed. Aphids can be controlled successfully with ladybugs (Coccinella septempunctata) and also with lacewings (Chrysoperla carnea). Both species are natural enemies of aphids. How do aphid predators find their prey? Aphids are maximally a few millimeters in size, which makes it difficult to see them by eye, especially from a longer distance. This is something that natural enemies will have to deal with. If they cannot use vision to locate their prey, what feature should they then use? Are odors perhaps more useful? Odors are well known to mediate the interaction between plant-eating insects and their natural enemies [1, 2]. It is, for example, common that natural enemies spy on odors that the plant-eating insects use to communicate with their conspecifics. Do aphid predators spy on their prey's alarm pheromone? Christoph Joachim and colleagues [3] investigated whether ladybugs and lacewings use the aphid alarm pheromone (E)-β-farnesene to locate their prey. Previous studies showed that this alarm pheromone attracted or arrested aphid natural enemies. However, Joachim et al., [3] describe that in these studies doses of 1 to 1000 µg were applied, while one aphid produces less than 1 ng to maximally 50 ng. The authors hypothesize that the pheromone doses used in previous studies may be unrealistically high and therefore may have little biological meaning. Joachim et al., used 50 and 1000 ng in their study, which is more comparable to what aphids actually produce. Scoring behaviors The authors glued one aphid with its hind legs to a leaf and waited a few hours before starting the test. Believe it or not, but by then most aphids were calmly eating. The authors then released the alarm pheromone close by the aphid and placed a predator at the base of the plant stem. They did so in both a laboratory and a field study. The foraging behavior of the predator was scored and analyzed with The Observer XT annotation software. The authors scored the following insect behaviors: - Search – predator walks on the plant. - Stop – predator rests or cleans itself on the plant. - Encounter – predator encounters the aphid. - Walk off – predator leaves plant. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Aphid predators do not use alarm pheromone The speed at which the predators found the aphid and the time they stayed on the plant was the same on the control plants as on the plants treated with either the low or the high alarm pheromone dose. So, contrary to previous reports, the authors found no evidence that aphids or lacewings use the aphid alarm pheromone to find their prey. The authors conclude that previous reports on attractiveness of the aphid pheromone to aphid predators is based on the use of unrealistically high doses of the compound. Alarm pheromone does not guarantee prey presence The authors hypothesize that the aphid alarm pheromone may not be a reliable indicator for prey presence. Think of it, aphids respond to this substance by walking away or falling from the leaves [4]. So when the predator arrives at such a spot, it may find no aphids there anymore. In addition to this, the alarm pheromone may indicate the presence of another predator. So it may be better to search for prey somewhere else. Concluding In conclusion, ladybugs and lacewings do not use the aphid alarm pheromone (E)-β-farnesene to locate their prey. Possibly they use other odors produced by the aphids, or by the plants that suffer aphid damage. References - Pickett, J. A., Wadhams, L. J., Woodcock, C. M., & Hardie, J. (1992). The chemical ecology of aphids. Annual review of entomology, 37(1), 67-90. - Dicke, M. & Hilker, M. (2003) Induced plant defences: from molecular biology to evolutionary ecology. Basic and Applied Ecology, 4, 3–14. - Joachim, C., Vosteen, I., & Weisser, W. W. (2014). The aphid alarm pheromone (E)-β-farnesene does not act as a cue for predators searching on a plant. Chemoecology, 1-9. - Montgomery, M. E., & Nault, L. R. (1977). Comparative response of aphids to the alarm pheromone, (E)‐ß‐farnesene. Entomologia experimentalis et Applicata, 22(3), 236-242. - Image ladybug - By Gilles San Martin from Namur, Belgium (Coccinella magnifica) [CC-BY-SA-2.0 (http://creativecommons.org/licenses/by-sa/2.0)], via Wikimedia Commons --- ## How to really challenge mice cerebellar plasticity URL: https://noldus.com/blog/mice-cerebellar-plasticity Published: 2014-11-27 15:18:00 Description: Jan-Willem Potters used the ErasmusLadder in his thesis research to study the role of specific mutations of plasticity in the cerebellar microcircuit of mice. Guest post by Jan-Willem Potters Successful locomotion and the maintenance of balance is the result of an intricate collaboration of the sensory system, sensorimotor integration and the motor system. Needless to say, there are many parts of the brain that work together to carry out this type of behavior. Locomotion is affected in many different neurological diseases, and is an interesting candidate to study symptoms in detail and the effect of possible therapies of these diseases. The cerebellum and behavior During my PhD, I studied the role of the cerebellum in different aspects of behavior, ranging from simple reflex-like movements to complex systems such as emotion and cognition. One of the questions our group investigates is how exactly the cerebellum (or 'little brain') is involved in locomotion. For scientists that work on the cerebellum there are several interesting reasons to study locomotion. First, patients with cerebellar diseases often display ataxic gait, characterized by increased variability and poor accuracy of movements (see for example: this video on ataxic gait). This is a clear indication that the cerebellum is crucial in the proper execution of locomotion. Animal studies over the years also showed that different sites in the cerebellum control different aspects of locomotion. Furthermore, locomotion is a process that requires precise temporal control, and a correction in locomotion needs to be carried out within several milliseconds in order to maintain a certain gait or restore balance. This is the exact temporal domain in which the cerebellum operates. Timing and motor learning in locomotion Despite evidence of the functional localization about different aspects of locomotion in the cerebellar cortex, not much is known about the plasticity mechanisms that drive the timing and motor learning in locomotion. Our goal was to study the role of specific mutations of plasticity in the cerebellar microcircuit. Unfortunately, studying locomotion in mice is not an easy job. Mice need to be handled and trained, and are less suitable candidates for distinct learning tasks compared to rats. Mice are on the other hand the ideal candidates to study genetic mutations, given the abundance of mice with genetically induced alterations in neuronal function. In our lab, we have been working several years on a device, called the ErasmusLadder, that gives us the possibility to study the parameters of locomotion in an systematic, reproducible and objective manner. Earlier versions of the ErasmusLadder showed interesting phenotypes in mice with specific cerebellar mutations, leading to publications in high-end neuroscience journals (see for example: Van Der Giessen et al., 2008 and Vinueza Veloz et al., 2010). Detailed parameters of locomotion Several years of testing and usage have lead to refinement of the hard- and software that makes it now possible to study more quantitative and qualitative parameters of locomotion. Combining the latest version of the ErasmusLadder with mice that lack specific proteins that play a role in the structure or the formation of new memories in the cerebellum has led to an extremely detailed publication about the parameters of locomotion in these mice (see other blog post). It also clearly shows how specific mutations affect specific aspects of locomotion. Really challenge the cerebellum The ErasmusLadder can assess baseline locomotion in which mice walk over the ladder undisturbed. In our study, we only saw a clear phenotype in the pcd mice, which is predictable since these mice lack a functional cerebellum. Over the course of time, it is possible to increase the demands on the mouse (and on the neuronal machinery) by introducing locomotor adaptation. In this scenario, the mouse needs to quickly respond to an obstacle in several tens of milliseconds. This really asks computing power from the cerebellum (and the rest of the brain), because we could identify deficits in several lines of mice that were unaffected or almost unaffected during the normal sessions. Practical advantages of ErasmusLadder Practically, working with the ErasmusLadder brings in several advantages. The device itself makes it possible to study mice mutants in a reasonably fast time frame. Each session takes a maximum of 15-20 minutes in which the device works fully automatic, making it possible to study a group of mice in an acceptable time. This makes it a good machine to attain data about locomotion in different groups of mutant mice, giving the possibility to quickly select candidates for further investigation. The final ErasmusLadder is the result of years of testing in our lab, leading to interesting publications, where the investigator can study extremely detailed parameters regarding locomotion, interlimb coordination and locomotor adaptation. RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources We would like to thank Jan-Willem Potters for sharing his insights and knowledge of working with the ErasmusLadder and for providing this free case study. For more information on the ErasmusLadder, go to www.noldus.com/erasmusladder. --- ## Picky cats and tasty food – sniffing is an indicator for tastiness URL: https://noldus.com/blog/sniffing-indicator-tastiness Published: 2014-11-20 13:34:00 Description: Cats can be extremely picky when it comes to food. If the cat doesn’t like it, it will refuse to eat. Reason enough for the pet food industry to try to find out what cats really like. Picky cats Any cat owner will acknowledge the fact that cats can be extremely stubborn. They let you hear loud and clear that they want to come in, but when you open the door, they just sit at the doorstep and stare at you. And they can be extremely picky when it comes to food. If the cat doesn't like it, it will refuse to eat. Reason enough for the pet food industry to try to find out what cats really like. Testing food tastiness Traditionally, the palatability of cat food is assessed by looking at consumption. Cats generally are given the choice between two types of food that are offered simultaneously during a couple of hours. These tests are a bit like a black box, the actual cause of preference remains unknown. Furthermore, it is unclear what the food intake will be when cats have no choice. Cat behavior Aurélie Becques and colleagues (2014) studied food preference of cats in more detail. They followed the cats for two days in a no-choice situation with either tasty or unpalatable food. They recorded the cat behavior on video and analyzed it with The Observer XT annotation software. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Sniffing and tastiness As expected, the cats ate more from the tasty food than from the unpalatable food. The consumption speed was not different for the two types of food, the cats just ate longer from the tasty food than from the unpalatable food. The cats spent more time sniffing the unpalatable food than the tasty food. But this effect disappeared over time and the effect was opposite by the end of the second day. The cats then spent less time sniffing the unpalatable food than the tasty food. Do these arrogant cats just ignore the unpalatable food after a while? Sniffing is a good indicator The authors conclude that sniffing food, and especially the sniffing time during the first encounter with the food, is a good indicator for the tastiness. This offers possibilities to develop short term standard tests to assess the palatability of cat food. This way cat food can be made entirely according to the cats' desires. Reference Becques, A., Larose, C., Baron, C., Niceron, C., Féron, C., & Gouat, P. (2014). Behaviour in order to evaluate the palatability of pet food in domestic cats. Applied Animal Behaviour Science, 159, 55-61. --- ## A high-throughput method to screen natural behavior of mice URL: https://noldus.com/blog/high-throughput-method-natural-behavior-mice Published: 2014-11-13 15:25:00 Description: Traditional standard tests with rats or mice are carried out immediately after human interference. Therefore, the behavior of the animals may not be natural and spontaneous. Standard behavioral tests Traditional standard tests with rats or mice to study human diseases or to test drugs generally take minutes to a few hours. A combination of these tests can give valuable information about the behavior of the rodents. However, these tests are carried out immediately after human interference. Therefore, the behavior of the animals may not be natural and spontaneous. To study spontaneous behavior, long-term studies in the rodents' home cage are more suitable[1]. Long-term behavioral observation The PhenoTyper home cage observation unit is a cage with a top-view camera. The rodent behavior is analyzed with EthoVision XT video tracking software. Rats or mice can be followed over a long time period without the necessity to carry out labor-intensive experiments. This makes it possible to study the natural behavior of rats and mice in their home environment. Furthermore, it gives a wealth of behavioral data, with hardly any human effort. But which of these data are suitable to analyze treatment effects, or genetic differences? FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Screening mouse strains Maarten Loos and colleagues[2] screened a large number of mouse strains in the PhenoTyper home cage. The cage contained a feeding area, a drinking bottle, and a shelter. The authors carried out extensive statistical analyses on the vast dataset, to find behaviors that can be used to phenotype the mice. And they came up with some spontaneous behaviors that can automatically be determined and analyzed. Movement and shelter visits The walking pattern of the mice could be divided into short movements when the mice were rearing or turning, and long movements when they were walking. Similarly, the mice either spent a short time in the shelter when they were passing through, or a very long time when they were sleeping. The distribution of short and long movements, and short and long shelter visits, differed largely between mice strains. So movement duration and time spent in the shelter can be used to characterize mice strains. Great possibilities for high-throughput screening The authors conclude that movement duration and time spent in the shelter can be used to test genetically knockout rodents and behavioral effects of drugs. This spontaneous rodent behavior can only be assessed in long-term behavioral studies. This may give the impression that such studies require intensive labor. But the opposite is true, the behavioral observations are automated with video tracking software and are therefore labor extensive. This offers great possibilities to use such a setup for high-throughput screening. References - 1.Tecott, L. H., & Nestler, E. J. (2004). Neurobehavioral assessment in the information age. Nature neuroscience, 7(5), 462-466. - 2.Loos, M., Koopmans, B., Aarts, E., Maroteaux, G., van der Sluis, S., Verhage, M., ... & Neuro-BSIK Mouse Phenomics Consortium. (2014). Sheltering Behavior and Locomotor Activity in 11 Genetically Diverse Common Inbred Mouse Strains Using Home-Cage Monitoring. PloS one, 9(9), e108563. --- ## Making sense of the senses: The real cost of paying attention URL: https://noldus.com/blog/senses-distraction Published: 2014-11-11 09:51:00 Description: We live in a demanding world: the snort of an email, the squeal of a text, fare alerts, breaking news, SQUIRREL! What was I saying? Oh yes, we live in a distracted world. We live in a demanding world: the snort of an email, the squeal of a text, fare alerts, breaking news, SQUIRREL! What was I saying? Oh yes, we live in a distracted world. With DVRs holding thousands of hours of entertainment; phones and tablets keeping us occupied while we watch those thousands of DVRed hours, it seems that something always has our attention. But what does that really mean? The term itself is used a bit like a commodity: always demanding that we pay for it. The affectionally dubbed "Brain Bank" allows a controlled bit of withdrawal at any given moment. We are literally trapped in a world bombarded by sensory information. As you read this, you are neglecting your world in order to process these words. What do you hear right now? What sweater are you wearing? Now are you thinking about what you are going to wear tomorrow? Or what's on your calendar? SQUIRREL! Please allow me to withdrawal a bit of currency from your Brain Bank to discuss the real cost of paying attention. The Senses We have but five: seeing, smelling, tasting, hearing, and feeling. Like the confluence of a mighty river, our brains process all five streams at once in various neuronal nooks and crannies, and individually we experience this world as one concrete illusion. But there is no such thing as reality. The truth, if there is such a thing, is that life is an individual experience. I can experience the color green, but how do I know that you know what my green is? The Lacrimosa movement by Mozart can reduce me to tears, yet others find it boring and blasé. I could go on and on. In fact, my original draft had over five pages of information on the individual senses. But I believe for the sake of brevity, I will quote the Floyd's Dark Side of the Moon, "All you touch and all you see is all your life will ever be." Association Cortices The goblins of your attentional finances If the senses are streams of information flowing into the mighty river that is your brain, then you have a Lock Tender. But this one is far more elusive. Some would even say imaginary. This, of course, is the voice in your head. It is you, or at least what you think is you. We call it consciousness. We call it an emergent property. We call it the Ghost in the Machine. Philosophers love to talk about the brain as the fat & neural tissue and the mind as that inexplicable part that makes you, you. Psychologists refer to this as perceptual "top-down" processing, as opposed to the sensory "bottom-up" experience. When I was younger, my Momma would say to my sister and me, "Turn the radio down so I can see." What?! What she meant is that she could not concentrate on her visual world when her auditory world was too loud. Missing information How much information do we miss because our Brain Bank is too busy paying attention elsewhere? There is a fancy name for this: "change blindness". There is a hilarious video in which there are people wearing black or white shirts. They have a ball and you are instructed to count the number of passes among the group wearing black. Little do you notice that a gorilla dances his way through the video! In research seeing what is not there or missing what is right in front of you is called "observation bias". It can be very difficult to stay "blind", which is to say naïve, when conducting research. This is why we often employ others to help. Others who have no bias towards anything and can accurately record an experience. But this top-down vs bottom-up dance is occurring right now in your head, a million times a second, as Clapton said, "Carving deep blue ripples in the tissue of your mind." This battle spills out to your attention. Too much internal chatter, and your Brain Bank has paid all your resources and you stop attending to what you hear. Attention in your own life and/or business So what does all this mean? Our bottom-up experiences continually battling our top-down processing for control of where and how our Brain Bank spends our focus and attention, much like headlights onto the night freeway. Some of us have a lot of internal noise - SQUIRREL! - that makes it difficult to sustain our attention. Others spend significantly less time looking at socially relevant information because of afflictions like Autism Spectrum Disorder. We are easily distracted. They make medications for that. I self-medicate with coffee and music. Others try Ritalin. But learning how to spend your Brain Bank's attention has the potential to mean much more in our daily lives. If we can filter out distractions we can enrich our sensory experience. Buddhists call this "quieting the mind" so you can experience the world with "beginner's mind", which is to say with no bias. You are free to experience the world without the Lock Tender prohibiting anything. Eliminating distraction means we can focus more on what matters, like driving. But working with our Brain Bank to pay out our attention can also benefit our relationships as well. Communication and attention Some will say the key to any relationship is communication. I do not disagree, per se, but instead offer that the keys (plural) are communication and attention. Not enough attention and the dog poops on the carpet. He's vindictive and he wants attention. He doesn't differentiate yelling from praise. To him attention is attention. On the contrary, too much attention from anyone and I feel overwhelmed. I like my space. Finding that balance is the key. Are you paying your clients enough attention? The same principle applies to your business as well. Are you paying your clients enough attention? Could some use more and others less? The relationship grows when all parties are comfortable with the attentional expenses and happy to pay in return. Furthermore, both must be able to communicate effectively. Otherwise we end up talking more when we should be talking less. Finally, it must be a two-way street and reciprocated. New relationships often demand much of our attention, sometimes to the expense of existing ones. How many friendships are strained due to a new romantic relationship? But again, the Brain Bank allows small withdrawals at a time, so we must be careful with whom we spend our attention. Finding that balance is difficult, but can be rewarding. Driving without distraction, with full attention, can be monotonous but reduces accidents. That email can wait until you get home. That tweet probably isn't as important as watching out for the deer on the side of the road. Listening attentively to others can improve retention and create a closer bond. Focus One of my favorite stories tells of a Zen Buddhist Master. He was having tea with a friend when a letter arrived from family. It was urgent and needed to be opened immediately. But the Master, ever present with Beginners Mind, left it unopened, choosing instead to focus his Brain Banks's expenses on his guest. A powerful lesson in our ever-distracted world. May all your squirrels stay up their trees Riddle me this: in the time you spent reading, what else was trying to withdrawal from your Brain Bank? Perhaps it was the TV? Or yet another snort from an email? A thousand times a second our senses are overwhelmed and we do live in a distracted world. Learning how to budget our attention and spend wisely can vastly improve many aspects of our lives, both personal and professional. May you be like the Zen Master and leave your letters unopened when visiting with company. May your Brain Bank pay appropriately for each and every relationship you hold dear. And may all your squirrels stay up their trees and leave you be. Visit Jason on Facebook, LinkedIn, and/or Instagram (@xaveig). --- ## Anxiety is ancient – how crayfish resemble vertebrates URL: https://noldus.com/blog/anxiety-ancient-crayfish Published: 2014-10-28 12:38:00 Description: Fear is something we all know. It changes our behavior: we freeze, try to escape, or respond with aggression. Fear can also cause anxiety, which is a more complex phenomenon. Fear and anxiety Fear is something we all know. It changes our behavior: we freeze, try to escape, or respond with aggression. Fear can also cause anxiety, which is a more complex phenomenon. While fear disappears when the source is absent, anxiety stays when there is no threat anymore. Rodents, for example, avoid the open arms of an Elevated Plus Maze when they previously were subjected to stress 1,2. Chemistry behind anxiety Anxiety is well-studied in humans, rodents, and zebrafish larvae. There are remarkable similarities between these three vertebrate groups in anxiety behavior and chemical pathways associated with it. Serotonine induces anxiety and benzodiazepine makes it disappear. These compounds are involved in two different chemical pathways, the serotonergic pathway and a pathway in which ɣ-aminobutyric acid (GABA) plays a role. Anxiety in invertebrates Up till now, hardly any research has been done on fear and anxiety in invertebrates. But this has now changed. Fossat et al.3 published a very interesting paper in the world-leading scientific journal Science. They investigated fear and anxiety in crayfish, which are invertebrates. They used an underwater plus-shaped maze with two dark arms, two light arms and a release zone in the center. This setup is very similar to an Elevated Plus Maze, which is used to study the exploratory behavior of rodents. The crayfish behavior was analyzed with EthoVision XT video tracking software. Try EthoVision XT yourself The gold standard in video tracking for behavioral research. Request a free trial. Start free trialarrow_forward Crayfish can be anxious The crayfish spent less time in the light arms than in the dark arms, took longer to first enter them and had less entries to these arms. This effect increased largely when the crayfish were first subjected to stress induced by electric fields. So, light avoidance was sustainable in the absence of the stress source, which indicates anxiety. This has a striking resemblance with stress-induced avoidance of open arms of the Elevated Plus Maze by rodents. Invertebrate chemical pathways Interestingly, this enhanced light-avoidance could also be induced by injecting the crayfish with serotonin. And light avoidance of previously stressed crayfish disappeared when the animals were injected with serotonine-inhibitors, or with the benzodiazepine drug chlordiazepoxide. Benzodiazepine compounds, a well-known example is valium, are in in vertebrates associated with the GABA pathway and reduce anxiety. So, crayfish have the same chemical pathways linked to anxiety as vertebrates! Evolutionary importance of anxiety The authors found striking similarities between crayfish and vertebrates in anxiety behavior and the chemical pathways linked to it. They conclude that anxiety is an ancient characteristic that has been well preserved in evolution. Apparently, anxiety is important for survival in response to a threat. The authors also conclude that crayfish may well be suitable as a model to further unravel the background of anxiety. References - Pellow, S., Chopin, P., File, S. E., & Briley, M. (1985). Validation of open: closed arm entries in an elevated plus-maze as a measure of anxiety in the rat. Journal of Neuroscience Methods, 14(3), 149-167. - Rodgers, R. J., & Dalvi, A. (1997). Anxiety, defence and the elevated plus-maze. Neuroscience & Biobehavioral Reviews, 21(6), 801-810. - Fossat, P., Bacqué-Cazenave, J., De Deurwaerdère, P., Delbecque, J. P., & Cattaert, D. (2014). Anxiety-like behavior in crayfish is controlled by serotonin. Science, 344 (6189), 1293-1297. --- ## Inhibitory avoidance learning in zebrafish (Danio rerio) URL: https://noldus.com/blog/inhibitory-avoidance-learning-zebrafish Published: 2014-10-24 14:05:00 Description: The zebrafish (Danio rerio) is increasingly being used as model in behavioural, neurobiological and genetic research. By Remy Manuel, Marnix Gorissen and Ruud van den Bos (email: r.manuel@science.ru.nl, m.gorissen@science.ru.nl & r.vandenbos@science.ru.nl) The zebrafish (Danio rerio) is increasingly being used as model in behavioural, neurobiological and genetic research. Underlying reasons are high genetic homology to humans and the many advantages over the use of rodents, such as low cost, easy handling, short reproduction cycle and high fecundity. Furthermore, its genome, transcriptome and proteome are well described, making the species a model of choice for behavioural research linked to genetics. An emerging field addresses learning and memory related to anxiety and fear behaviour, which has been studied through inhibitory avoidance paradigms [1,2]. Assessment of inhibitory avoidance learning in zebrafish is based on the conflict between entering a dark area to avoid a brightly lit area (innate response; innate anxiety) and avoiding this dark area, as it has been associated with an electric shock as negative stimulus (conditioned fear avoidance). Higher latencies of entering the dark area following training are indicative of increased inhibitory avoidance learning. Age Like in mammals, zebrafish show reduced learning at old age: aged zebrafish (24 months) require an additional training day before showing a similar level of avoidance behaviour as 12-month (adult) zebrafish. Gene expression analysis of the telencephalon suggests that lower levels of neuronal plasticity underlie these observations. Photoperiod The zebrafish is a diurnal species with higher activity during the day-time and a lower activity at night. Like other animals zebrafish have circadian rhythms that are entrained by light. Housing zebrafish under long periods (i.e. 42 days) of continuous light leads to a strong reduction in inhibitory avoidance learning. Changes in the expression of stress-related genes suggest that changes in stress-axis activity underlie the observed reduction in avoidance learning. Chronic stress Zebrafish show reduced avoidance learning when exposed to (weeks of) unpredictable chronic stress (UCS). Similar to what has been reported for rats, the negative effects of UCS seem stronger when stressors are applied during the resting/sleep phase than during the active/awake phase. UCS-induced changes in stress-axis activity, expressed as increased levels of whole-body cortisol and accompanying changes in the expression of stress-related genes, likely underlie the observed reduction in avoidance learning [3,4]. Enrichment To ensure proper water quality, laboratory fish are often housed in barren aquaria. However, adding enrichment has been shown to reduce anxiety-like behaviour, increase brain volume and improve performance in spatial learning tasks. Inhibitory avoidance learning is reduced following housing under enriched conditions. Analysis of genes in the telencephalon suggests that zebrafish may be less sensitive to the impact of the electric shock used in the paradigm. Avoiders and non-avoiders In the inhibitory avoidance learning paradigm, two distinct types of responders are observed: fish that strongly avoid the black compartment (avoiders) and fish that quickly enter the black compartment (non-avoiders). These differences in avoidance behaviour are associated with differences in whole-body cortisol content as well as expression levels of genes related to learning, memory and anxiety. [5] Behavioural analysis During inhibitory avoidance learning, behaviour has been recorded and analysed post-hoc using EthoVision XT v10.0 tracking software (Noldus, Wageningen, the Netherlands). Preliminary data analysis suggests that no differences exist between avoiders and non-avoiders in spatial preference, swimming speed and distance moved before lifting the sliding door. However when the sliding door is lifted and the dark – shock associated – compartment is accessible a difference is found: avoiders position themselves in the zone furthest away from the dark compartment, while non-avoiders freely swim around before entering the dark compartment (Figure 1). These data support the differences in levels of conditioned fear between avoiders and non-avoiders. Future perspectives Overall, our data suggest that the zebrafish is a suitable model to study gene-brain-behaviour relationships underlying learning and memory related to anxiety and fear. In addition, these data serve as starting point for unravelling individual differences in anxiety and fear-associated learning. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial References - Blank, M., Guerim, L. D., Cordeiro, R. F., & Vianna, M. R. M. (2009). A one-trial inhibitory avoidance task to zebrafish: rapid acquisition of an NMDA-dependent long-term memory. Neurobiology of Learning and Memory, 92(4), 529–534. doi:10.1016/j.nlm.2009.07.001 - Ng, M.-C., Hsu, C.-P., Wu, Y.-J., Wu, S.-Y., Yang, Y.-L., & Lu, K.-T. (2012). Effect of MK-801-induced impairment of inhibitory avoidance learning in zebrafish via inactivation of extracellular signal-regulated kinase (ERK) in telencephalon. Fish Physiology and Biochemistry, 38(4), 1099–1106. doi:10.1007/s10695-011-9595-8 - Piato, Â. L., Capiotti, K. M., Tamborski, A. R., Oses, J. P., Barcellos, L. J. G., Bogo, M. R., et al. (2011). Unpredictable chronic stress model in zebrafish (Danio rerio): Behavioral and physiological responses. Progress in Neuropsychopharmacology & Biological Psychiatry, 35(2), 561–567. doi:10.1016/j.pnpbp.2010.12.018 - Manuel, R., Gorissen, M., Zethof, J., Ebbesson, L. O. E., van de Vis, H., Flik, G., & van den Bos, R. (2014). Unpredictable chronic stress decreases inhibitory avoidance learning in Tuebingen Long-Fin zebrafish (Danio rerio Hamilton): stronger effects in the resting phase than in the active phase. Journal of Experimental Biology. doi: 10.1242/jeb.109736 - Manuel, R., Gorissen, M., Piza Roca, C., Zethof, J., van de Vis, H., Flik, G., & van den Bos, R. (2014). Inhibitory Avoidance Learning in Zebrafish (Danio Rerio): Effects of Shock Intensity and Unraveling Differences in Task Performance. Zebrafish. doi:10.1089/zeb.2013.0970 This is a guest blog post. Remy Manuel, Marnix Gorissen and Ruud van den Bos thank you so much for your contribution! For more information about tools for zebrafish research, go to www.noldus.com/applications/zebrafish-video-tracking --- ## Measuring experiential, behavioral, and physiological outputs URL: https://noldus.com/blog/social-interaction-task-couples Published: 2014-09-26 08:13:00 Description: In a romantic relationship, it is undoubtedly important to show support when one’s partner shares his or her accomplishments and positive life events. In a romantic relationship, it is undoubtedly important to show support when one's partner shares his or her accomplishments and positive life events. Retelling and reliving such events can evoke certain emotions, but the listener's response often impacts the storyteller's attitude as well. To simulate this process, researchers Samuel Monfort and colleagues created a structured social interaction task with couples: 1) positive event of one partner, 2) disclosure of the event to the other partner, and 3) clear communication of a capitalization response that ranged from actively destructive to enthusiastic, supportive and constructive. Integrating multiple modalities Monfort and his team set out to capture a full range of emotional responses and therefore measured experiential (subjective feelings), behavioral (facial-motor activity), and physiological (skin conductance) outputs. Behavior and physiology are closely linked; as Patrick Zimmerman and his colleagues explain, more and more researchers now see the benefit of combining behavioral observations with other types of data such as heart rate, blood pressure or eye movements. By integrating multiple modalities, researchers achieve a more complete picture of the phenomena being studied. Observing couples A total of 69 couples participated in Monfort's study. During lab interactions, couples were separated into cubicles with no eye contact or talking. Each experiment consisted of partner A successfully completing a computer task, then sharing this success with partner B. Partner B could choose from four possible responses: active-constructive (e.g., ''Wonderful! You did a great job!''), passive-constructive (''Ok. Good.''), active-destructive (''I bet the task wasn't very hard'') or passive-destructive (''Not much happening here''). For each individual, Monfort et al. used FaceReader software to analyze his/her facial expressions. They explain that this software automatically calculates a compound index of facial behavior, i.e., valence. The valence is determined as the intensity of the happy expression minus the intensity of the negative emotion (sadness, fear, anger, and disgust) with the highest intensity at a given moment. Monfort also measured skin conductance via a pair of electrodes taped on digits II and III of the non-dominant hand. Partner's response It was hypothesized that supportive comments such as "Great job" or "Wonderful" would result in increases in happy facial expressions and positive emotions, decreases in sympathetic nervous system activity (skin conductance response), and fewer negative emotions in both partners. While Monfort et al. did not see any clear direct physiological effects, their results on the subjective and behavioral measurements suggested that supportive capitalization responses did indeed lead to greater positive emotion and less negative emotion (felt emotions) in both partners, and an increase in positive facial expressions on the part of the receiver. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Effects were expected to be stronger for the person receiving supportive capitalization responses than for the giver, which proved to be true in this case. In other words, emotions were most greatly impacted when a person received verbal support. Monfort's sample only involved couples with high relationship satisfaction, but it would be interesting to duplicate this experiment using couples with low relationship satisfaction, to test whether these findings can be extended to individuals in different types of relationships. References - Zimmerman, P.H.; Bolhuis, L.; Willemsen, A.; Meyer, E.S.; Noldus, L.P.J.J. (2008). The Observer XT: a tool for the integration and synchronization of multimodal signals. In Proceedings of Measuring Behavior 2008 (Maastricht, The Netherlands, August 26-29, 2008), 125-126. - Monfort, S. S., Kaczmarek, L. D., Kashdan, T. B., Drążkowski, D., Kosakowski, M., Guzik, P., Krauze, T., Gracanin, A. (2014). Capitalizing on the success of romantic partners: A laboratory investigation on subjective, facial, and physiological emotional processing. Personality and Individual Differences, 68, 149-153. "Project funded by National Science Center (Poland). Grant nr N N106 0167 40 awarded to Lukasz D. Kaczmarek (Adam Mickiewicz University).". Image and movie courtesy - Monfort, S. S., Kaczmarek, L. D., Kashdan, T. B., Drążkowski, D., Kosakowski, M., Guzik, P., Krauze, T., Gracanin, A. --- ## Walking the ladder: testing the cellular source of motor functioning in mice URL: https://noldus.com/blog/motor-functioning-mice Published: 2014-09-11 15:35:00 Description: The cerebellum, our “little brain”, is all about motor control; more specifically, it’s about coordination, precision, and timing. The cerebellum, our "little brain", is all about motor control; more specifically, it's about coordination, precision, and timing. So when the functioning of the cerebellum is compromised, incoordination of movement (ataxia) occurs. Ataxia is found in many neurological diseases such as Parkinson's and early onset Alzheimer's. Cerebellar cell types functioning Purkinje cells, interneurons, and granule cells of the cerebellar cortex play an important role in reflexive types of motor learning, as we can tell from studies using the eye blink test and vestibulo-ocular testing. But since their role in more complex behaviors is not well understood, Maria Fernanda Vinueza Veloz and her colleagues decided to study the role of each one of these cell types in motor learning, locomotor adaptation, motivation and avoidance behavior using several knock-out mouse strains and testing them on the ErasmusLadder. The ErasmusLadder: unique motor learning testing The ErasmusLadder is an instrument for testing motor learning. It consists of a horizontal ladder stretching between two goal boxes, with rungs for the animal to walk on; some are "higher" and some are "lower". A 'correct' stepping pattern involves using the higher rungs; using a lower rung is counted as a misstep. Sensors detect when the mouse steps on a rung, so step time, step size, missteps and other parameters can be measured. While similar methods focus on either spatial patterns, general aspects of locomotion, or on balance, ErasmusLadder combines these features in one test. As the researchers of this study put it: "…the ErasmusLadder yields a more complete and quantitative analysis of locomotion than other systems currently available." RESOURCES Read more about ErasmusLadder Find out how ErasmusLadder is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Mouse strains to test specific neurons Vinueza Veloz and her colleagues used four different mouse strains: two strains suffered from impaired Purkinje cell output or potentiation (Pcd and L7-Pp2b), the third strain suffered from impaired interneuron output (L7-Δγ2), and the fourth from impaired granule cell output (α6-Cacna1a). Each group was complemented by a control group of littermates so that the functioning of each cell type could be studied in detail. Behavioral protocol To study motor learning and motor function in the four strains and the control groups, mice were tested in two sets of four consecutive days. During the first four days motor learning and performance were assessed. After a two day break, another four sessions took place in which the mice were challenged with an obstacle: a rung that was suddenly raised to 12 mm above stepping surface. Inserting this challenge accurately tests reflexive motor learning and performance. Baseline locomotion results During the first four sessions, Purkinje cell output and potentiation impaired mice (Pcd and L7-Pp2b) made smaller steps (one rung at a time); when they did make a larger step (skipping a higher rung), it took them significantly longer than the controls. Also, their stepping patterns were less consistent. Purkinje cells are the sole output of the cerebellar cortex and these results show the strategic importance of these cells: they are critical for the generation of basic walking patterns. The phenotypes found in these mice also closely resemble the symptoms of patients suffering from cerebellar ataxia. Interestingly, the interneuron and granule cell output impaired strains (L7-Δγ2 and α6-Cacna1a) had little to no detectable deficits during the first 4 days. Interlimb coordination, adapting locomotion During the last four days (with perturbation) all four mutant strains showed significant differences compared to the control groups, with even the interneuron and granule cell output impaired mice demonstrating abnormal interlimb coordination in dealing with the obstacle. This suggests that, although it did not show in the first four sessions, coordination may indeed also be affected in these two mutants. Because the functional outcome in this study appears normal during the non-perturbed task in the first four sessions, it seems that interlimb coordination is the most sensitive parameter for cerebellar deficits. Cognitive functions In addition to the locomotion skills, two cognitive functions were tested on the ErasmusLadder: motivation and avoidance behavior. To test this, sensory stimuli (light and air pressure) were applied to initiate the subjects' movement across the ladder, from one shelter towards the other (dark) shelter. Air pressure was also used from the other side, to keep the animal inside the shelter if it tried to leave too soon. The percentage of trials during which a mouse used or needed either light or air to initiate running was used to assess motivation and avoidance. None of the four strains showed lack of motivation or tendency to avoid leaving the box. Consistent with literature, these mutants have no phenotypes in common cognitive tasks such as the water maze or open field testing. Sensitive testing method In conclusion, these scientists found a sensitive way to test for cerebellar functioning with the ErasmusLadder. Results indicated significant deficits in all four mutants and thus evidence that Purkinje cells, interneurons, and granule cells all play an important role in interlimb coordination. References Vinueza Veloz, M.F.; Zhou, K.; Bosman, L.W.J.; Potters, J.-W.; Negrello, M.; Seepers, R.M.; Strydis, C.; Koekkoek, S.K.E.; De Zeeuw, C.I. (2014). Cerebellar control of gait and interlimb coordination. Brain Structure and Function, doi: 10.1007/s00429-014-0870-1. A commercial version of ErasmusLadder is now available. For more information go to www.noldus.com/erasmusladder or contact Noldus. --- ## What a horse likes to eat: how to test dietary preferences URL: https://noldus.com/blog/test-dietary-preferences-horses Published: 2014-08-25 15:52:00 Description: Redgate and colleagues looked into the addition of a monadic phase (a phase in which only one food was offered at a time instead of all of the options) to choice testing. When humans are given a choice of food, we usually go for the best-tasting option. Animals also have a preference in which food they eat, although theirs is not based on taste necessarily, but on nutritional value. This choice feeding can be used to learn more about an animal's nutritional needs and dietary preferences. However, in animals such as horses, there is a long gut transit time, which means that the horse may have difficulty making the connection between which chosen food has which nutritional consequence. So what can be done about this? Redgate and colleagues looked into the addition of a monadic phase (a phase in which only one food was offered at a time instead of all of the options) to choice testing. For this study, researchers wanted to see how a monadic training phase would impact the horse's choice of food and if voluntary intake and feeding behavior would be influenced if the energy content was constant, but the macronutrient diet was different. The experiment Seven horses were used in this study. Three mixed forage diets were created using the same batch as Timothy hay as the base. The first was protein rich, the second hydrolyzable carbohydrate rich, and the last was lipid rich. After introducing the horses to the components of this diet over fourteen days to prevent gastrointestinal disturbances, the main experiment began. There were three phases to this experiment: self-selection before the monadic phase, the monadic phase, and self-selection after the monadic phase. Researchers had a before and after period in which they tested self-selection to see how the horses' preferences changed after the addition of the monadic phase. During the self-selection phases, three buckets containing the three different diets were placed in front of the horse's stall. During the monadic phase, one bucket containing one of the diets was placed in front of the stall – the order of which diet was given varied between the horses. Because the food was provided ad libitum, the feeding behavior of each horse was recorded for a single four-hour period of time during the self-selection phases. The Observer was used to analyze these recordings. Every time the horse's head was either in the bucket or, following that, out of the bucket and chewing was recorded as foraging behavior. Also recorded were the time it took for the horse to approach each of the diets and the frequency they visited each. In conclusion In a natural environment, a horse will select its diet based on the food which will provide the most energy and has the highest nutrient content. For most species besides humans, it is all about getting what is essential for survival and not only what tastes the best. However, in a natural environment, the nutritional value of a food source will change over time, making the horse change its selection patterns – it either must increase intake of the food or save energy by decreasing activity or finding shelter. However, in experiments, it is difficult for researchers to show a relationship between the nutrient content and the voluntary intake of the horse. This was due to the horse's long gut transit time. Associations between what was eaten and its nutritional consequence took time to make when there was more than one diet presented at the same time. Redgate et al. sought to eliminate two issues that often took place in studies researching horse diets: any learned associations based on previous experiences and the amount of time it took the horse to show an adaptive change in diet. It is interesting that even with the monadic phase added, the lipid intake of the horses remained consistent. However, there was an increase in the second self-selection phase of horse preference for the protein and hydrolyzable carbohydrate-filled feeds. This study found that horses are capable of associating the nutrient content with sensory information when they ate the food and that using a monadic phase during testing helped the horses build associations. It also showed that horses might be aiming for certain nutrient intake targets to regulate their feed intake, which would explain why the horse did not eat as much of the lipid-filled feed – it had already met its intake target. This suggests a monadic phase could be very useful when it comes to testing dietary preferences in animals with a long gut transit time. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References Redgate, S.E.; Cooper, J.J.; Hall, S.; Eady, P.; Harris, P.A. (2014). Dietary experience modifies horses' feeding behavior and selection patterns of three macronutrient rich diets. Journal of Animal Science, 92, 1524-1530. --- ## The accuracy of measuring fish aggression by using mirror tests URL: https://noldus.com/blog/measuring-fish-aggression Published: 2014-08-18 10:46:00 Description: To examine the response of cichlids to their mirror image, Balzarini et al. used three sympatric species from Lake Tanganyika and did the mirror test for measuring aggression. When we look into a mirror, we see a reflection of ourselves. As humans, we are aware that this is only a reflection and not actually another living person. However, very few animal species are able to acknowledge that their reflection is not another one of their species which could pose a threat to them. Capuchin monkeys, grey parrots, and elephants are among the few that are able to recognize their mirror image. A majority of animal species, including fish, treat the image in the mirror as a conspecific. As a result, it would make sense that a mirror test could be a good indicator of aggression, especially in fish. However, Valentina Balzarini and colleagues questioned this widespread method, noting recent studies which had shown that hormonal and gene expression responses differed between the fish being exposed to a conspecific or a reflection of itself. Three different species of fish To examine the response of cichlids to their mirror image, Balzarini et al. used three sympatric species from Lake Tanganyika and did the mirror test for measuring aggression. The three species studied were Neolamprologus pulcher, Telmatochromis vittatus, and Lepidiolamprologus elongatus. Each of these species has a different breeding strategy. N. pulcher are cooperative breeders, with their population organized into colonies made up of breeding groups. These breeding groups are organized by a size-dependent hierarchy maintained by aggressive interactions. T. vittatus are polygynous breeders who breed in empty snail shells and have four different reproductive tactics based on body size – there are three types of parasitic males trying to steal fertilizations from the territorial males who guard a nest with several females. L. elongatus are monogamous breeders, and will defend their offspring vigorously against any intruders. The differences between these three cichlid species could provide insight into the effects of social organization on the mirror test and how suitable it is. Assessing behavior Three different measures were taken to examine the aggressive behavior of the fish. These were overt aggression, restrained aggression, and time spent close to the intruder. Overt aggressive behaviors were when the fish attempted to bite or ram against the partition or mirror. The restrained aggressive behaviors differed some among species, but included things such as a fast approach or a fin raise. These behaviors were coded using The Observer XT software. It makes sense that fish would have an aggressive response both to a mirror image of themselves and a different fish, but it also makes sense that their aggressive response would differ. Even though fish cannot recognize themselves in a mirror, they can recognize that their opponent is exactly the same size and making the exact same movements as them – thus this fish would be a greater threat to hierarchal fish, as it could take their place. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Different species have different reactions Not all of the species of fish had the exact same aggressive response to their reflection or a conspecific. Just as their breeding strategies differ, so does their aggression towards other fish. The restrained and overt aggression of N. pulcher was influenced by the opponent's behavior, and the fish showed more restrained aggression towards an opponent than its own reflection. However, the correlation for L. elongatus was significant for restrained aggression and time in the frontal zone. The restrained aggression for both species was influenced by the opponent fish, but this was not the case for T. vittatus. The opponent was only able to influence its time spent in the frontal zone. Why do we see these different results in aggression? Is the mirror test valid to use to research aggression? Balzarini et al. believe that the predictive value of mirror tests is species specific. The way the fish will react can depend heavily on its social behavior – is the species hierarchical or territorial? Regardless, mirror tests can work to study individual aggression in some species, but in the future, this needs to be validated for each species before it is used to collect data. References Balzarini, V.; Taborsky, M.; Wanner, S.; Koch, F.; Frommen, J.G. (2014). Mirror, mirror on the wall: the predictive value of mirror tests for measuring aggression in fish. Behavioral Ecology and Sociobiology, 68, 871-878. Image Credit: Guérin Nicolas --- ## The relationship between food scarcity and caching in fox squirrels URL: https://noldus.com/blog/food-scarcity-and-caching-fox-squirrels Published: 2014-08-12 11:33:00 Description: We’ve all seen squirrels carrying acorns around in their mouths and burying them in the ground. This is a way to hoard food, and most squirrels use a strategy called scatter-hoarding. We've all seen squirrels carrying acorns around in their mouths and burying them in the ground. This is a way to hoard food, and most squirrels use a strategy called scatter-hoarding. Instead of storing all of their excess food in one spot for easy access later, squirrels spread their food around in so many different caches that it is hard to believe they could find all of the spots again later. However, a squirrel has a choice to make when it comes across a food item – will it cache it and save it for later or will the squirrel eat it right there? Several factors play into this, such as quality, perishability, and scarcity. Mikel Delgado et al. studied how these different factors had an impact on the food-storing decisions of adult fox squirrels. To cache or not to cache? An animal which hoards survives by depending on the caches it has made. Therefore, it is important that it be able to determine the quality of the food that it decides to keep in caches before it goes to the trouble of hiding the food item. In this study, peanuts and hazelnuts were used. The researchers argued that the hazelnuts are more valuable due to their larger size and lower perishability. Therefore, the squirrels should take more time and cover greater distances when making hiding the hazelnuts than when hiding the peanuts. The experiment Experimenters took video of the squirrels at the University of California at Berkeley campus. All videos were coded using The Observer XT. Researchers gave the squirrels a sequence of fifteen nuts – either five peanuts, five hazelnuts, five peanuts or five hazelnuts, five peanuts, five hazelnuts. They then observed for several behaviors that appeared to be assessments of the nuts that the squirrels were given. Squirrels will assess the food item by first "paw manipulating" it, then "head flicking." "Paw manipulating" means when the food item is held loosely in the paws and rotated in the mouth of the squirrel. This was the common assessment behavior, and the squirrel might then go on to "head flick," which was shaking the head quickly with the food item in its mouth. However, the squirrel did not always "head flick." After the assessment behaviors, the squirrel would decide to either eat the nut it had been given or to cache it. In my opinion, if the nut wasn't very valuable, the squirrel would probably invest less time and energy in it. Delgado et al. tested if fox squirrels changed their assessment and investment in food items based on how scarce it was. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Conclusions Trials were done over two different seasons (summer and fall), so researchers were able to examine the difference in caching behavior at these time periods. Squirrels were more invested in caching during the summer, when food was scarce, than in the fall. In the shorter term, the more nuts the squirrels received, the less time they invested in caching or assessing the nut. If other squirrels were around, social competition increased and the squirrel would invest more time in making a cache, but show less assessment behaviors, as those could signal to the competition where a food source was. All of these results indicate that squirrels are able to monitor scarcity based on numerous different factors, and they integrate these factors to determine how much investment they should put into assessing and caching a food item. Future experiments could look into the squirrels' hoarding habits in other seasons and also how many of the caches the squirrels find again. Reference Delgado, M.M.; Nicholas, M.; Petrie, D.J.; Jacobs, L.F. (2014). Fox squirrels match food assessment and cache effort to value and scarcity. PLOS ONE, 9(3), doi:10.1371/journal.pone.0092892. --- ## How wild cavies and domesticated guinea pigs differ URL: https://noldus.com/blog/how-wild-cavies-domesticated-guinea-pigs-differ Published: 2014-08-05 14:11:00 Description: Domestication has a considerable effect on the behavior of animals. The dramatic change in their environment and provision of food alter the need for behaviors such as exploration. But what exactly is the difference? Domestication has a considerable effect on the behavior of animals, which is not very surprising. The dramatic change in their environment and provision of food and shelter alter the need for behaviors such as exploration and social behaviors. But what exactly is the difference? Domesticated vs wild animals Not many studies have compared the behaviors of wild and domesticated animals. When they do, such as with guinea pigs, they mostly compare adults. Zipser et al. were curious to find out whether the differences in behavior between domesticated guinea pigs and the wild cavies were also found earlier on, and so they compared these species during the early and late phase of adolescence. They compared 10 male guinea pigs to 8 wild cavies. All tests were done twice: during each phase of adolescence, and recorded on video. Behavior was measured and analyzed using The Observer XT. Emotional guinea pigs Emotionality of the animals was investigated using a variety of tests. In the open field test, time spent in the center (1/4th of the total surface) versus the border of the cage was measured. During a dark-light test, the animal was placed in a dark box and had the opportunity to explore a light area. The latency to leave the dark box and the number of times it entered the light area were recorded. Next, to assess risk-taking, the animal was placed on a platform and the latency to step down was measured. Exploration and anxiety The wild cavies showed explorative and anxiety-like behavior less than the guinea pigs did, especially during early adolescence. They also showed more risk-taking, but only during late adolescence. Over the course of adolescence, exploration decreased in both species. Evolutionarily, risk-taking and exploration are important in order to obtain water, food, shelter, and mates. Obviously, these are less of an issue in guinea pigs. The decrease in exploration and risk-taking as seen in guinea pigs can thus very well be a consequence of removal of this selection pressure. Social behavior Next, social behavior was measured. To investigate the general motivation of an animal to initiate social contact, the animals were exposed to an unfamiliar male infant that was put in a small cage. The test enclosure also included an empty cage. The latency to approach and the time spent near the infant was compared the same parameters related to the empty cage. The male subjects were also exposed to unrestricted social contact with unfamiliar females, during which courtship behaviors were recorded. Social attraction The guinea pigs and the cavies took the same time approaching the unfamiliar subjects in both the infant and the female interaction test, during both phases of adolescence. Both were more interested the social stimulus than the empty cage. However, there was a substantial difference in the amount of social interaction: guinea pigs showed more interest in both the infant and the female adolescents. This is in line with the literature; domesticated animals show higher degrees of agreeableness and sexual behavior and lower levels of aggression. Consequences of domestication This is a logical consequence of the domestication process: the first breeders selected for the least aggressive cavies so they would reproduce easily and could be kept in large groups. Stress levels Stress reactivity was investigated by taking blood samples at the beginning and at each hour of a 4-hour novel environment experiment. In these five samples, both cortisol and testosterone levels were measured. The endocrine profiles differed markedly between the two species. While baseline levels of cortisol were similar, the increase during the novel environment test was much higher in cavies during both early and late adolescence testing. Physiological adaptations Evolutionarily, wild cavies require appropriate physiological adaptations to provide the necessary energy quickly when the situation calls for it - this is the main function of the stress system. So the high reactivity of the stress axis as found in the wild cavies does not necessarily have a detrimental effect on the animal. Rather it provides the energy necessary to adapt to their demanding life in the wild. Contrasting, guinea pigs have a much less demanding everyday life. Testosterone and cortisol Testosterone levels were higher in guinea pigs, which seems a logical cause of the increase in social behavior. Indeed, this correlation is often found in literature. Testosterone levels also organize the reactivity of the cortisol system, and acute cortisol reactivity can trigger aggression. So the lower amount of agonistic behavior found in guinea pigs compared to cavies is in agreement with their behavioral profiles. Biobehavioral differences Not surprisingly, this research confirms the differences in behavior that domestication causes. More importantly, these changes were already found in early adolescence, showing that young individuals already show behavior that reflects the adaptation to the made-man habitat. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial References Read the full article here: Zipser, B.; Schleking, A.; Kaiser, S.; Sachser, N. (2014). Effects of domestication of biobehavioural profiles: a comparison of domestic guinea pigs and wild cavies from early to late adolescence. Frontiers in Zoology, 11, 30. For more information about scoring behaviors with The Observer XT, click here. --- ## The impact of visitor access in a shelter on the welfare of shelter dogs URL: https://noldus.com/blog/welfare-shelter-dogs Published: 2014-07-31 15:19:00 Description: If you’ve ever been to a shelter to adopt a dog, you know that when you walk into the holding area, the dogs can get very noisy. If you've ever been to a shelter to adopt a dog, you know that when you walk into the holding area, the dogs can get very noisy. At the introduction of a stranger to the room their kennels are in, the dogs will start barking, which encourages the other dogs around them to bark as well. Barking has been documented as a stressor for dog, as have repetitive behavior and lots of movement. All of these behaviors seem to increase by the access of visitors to the kennel area. Lynn Hewison and colleagues decided to investigate if preventing visitor access to the dogs could lower stress levels and therefore increase general welfare of the animals. The experiment Researchers determined that a cross-over design would not be possible because the dogs that had access to the visitors would still influence the dogs that had prohibited visitor access. So instead, the set up was two weeks of pre-intervention (which was used as the baseline), two weeks of intervention during which there was prohibited visitor access to the kennel area, and two weeks post-intervention. During the intervention, visitors could still come to the shelter, but instead of being allowed to go back to the kennel to look at the dogs, they were informally interviewed in the office and a dog was selected for them to see. In the two weeks before and after, visitors went back to the kennels to look at the dogs themselves. Behavior of the dogs was recorded and analyzed continuously in 60-second periods of a 90-second time intervals using The Observer XT. Data analysis only took place for the last 60 seconds to give the experimenter time to leave and the dog time to settle down. Stress and activity-related behaviors were recorded, although many had too few occurrences to be reliable in statistical analysis. Frequency of behavior was recorded for repetitive behaviors, and the dog's position in the kennel run was noted each time a behavior was recorded. Researchers also kept close track of any sickness events in the dog's kennel and collected urine samples for analysis. Kennel noise, behavior of the dog, kennel location, physiology, and sickness events all worked towards interpreting the stress level in these dogs. Does an intervention impact dog stress levels? During the time period in which the shelter was normally open to visitors, there was a significant reduction in the noise levels of the dogs during the intervention period. The intervention period also seemed to have a significant effect on sedentary, locomotor, and repetitive behaviors, increasing the amount of sedentary behavior and decreasing the amount of locomotor and repetitive behaviors. However, there seemed to be no significant effect on any physiological measures. High noise levels, high locomotion, and high amounts of repetitive behaviors have been linked to stress in dogs, while sedentary behavior suggests that the dog is not very stressed. These results suggest an improvement in welfare due to the intervention. What does this mean? Hewison et al. set out to see if changing the type of visitor interaction with the dogs at a shelter would have a positive impact on the dogs' welfare. While there were a few shortcomings of the study, such as the short time periods used or the fact that a cross-over design was not possible, the results of this study provide evidence that prohibiting visitor access to dogs in their kennels is likely to have a positive impact on their physical welfare and possibly emotional welfare as well. Future studies should look into the form of visitor access that causes the least stress and provides the best welfare for the dogs. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References Hewison, L.F.; Wright, H.F.; Zulch, H.E.; Ellis, S.L.H. (2014). Short term consequences of preventing visitor access to kennels on noise and the behavior and physiology of dogs housed in a rescue shelter. Physiology & Behavior, 133, 1-7. --- ## Adolescent Motherhood – observing mother-infant behavior URL: https://noldus.com/blog/observing-mother-infant-behavior Published: 2014-07-25 13:34:00 Description: Adolescent mothers are tackling their transition to adulthood and the transition to parenthood. This is called the double risk for mother and infant, inherent in adolescent motherhood. Teenagers have the perfect life, right? Living at mom and dad's, eating without worrying about gaining weight, and relaxing all the way through high school. Unfortunately, not all adolescents have an easy-peasy life. Some have to study to achieve good grades and others have to deal with grownup problems on top of dealing with the emotional ups and downs of adolescence. What about teenage moms? Next to dealing with a newborn, adolescent mothers are tackling their transition to adulthood (taking more distance from parental figures) and the transition to parenthood (the nurturing of an infant and caring for his or her physical and emotional needs). This is called the double risk for mother and infant, inherent in adolescent motherhood. (Riva Crugnola et al. 2014) Double risk – invest in a solution Current research from Prof. Cristina Riva Crugnola, University of Milano-Bicocca tells us that adolescent mothers as well as their babies (vs. adult mother and infant interactions) spent more time in negative engagement, meaning that the mothers showed more pushy behaviors towards the infant, even hostility. The infant also showed more negative behaviors, such as protesting with expressions of anger and crying. Riva Crugnola and colleagues state that it is important to train skills and competence in adolescent mother-infant interaction by setting up prevention programs. Young mothers should be supported in learning how to be a mother and regulating emotions (in particular, negative ones). Also, timing is everything - the researchers explain that it is also important to start preventive intervention in the first months of life. The experiment To come to these results, Riva Crugnola et al. set up an experiment in a laboratory furnished as a playroom. A total of 60 mothers and babies participated in a 5-minute play session. The 15 to 21 year old mothers were added to the adolescent group and the other 30 mothers (all over 21 years old) to the adult group. All interactions were recorded on video using a camera in the room. The researchers explain that the camera was positioned in such a way that it captured the behavior and the expressions on the faces of both members of the dyad. Afterwards, all videos were coded and analyzed in The Observer XT using a modified version of the Infant Caregiver Engagement Phases (Weinberg & Tronick, 1999). Riva Crugnola explains that this system evaluates the behavior of mother and infant during face-to-face play on the basis of emotions expressed, gaze direction, vocalization, and verbalization. Riva Crugnola and colleagues added these new categories with the aim of exploring the way 3-month olds infants and their mothers direct attention to objects during play and in particular, their level of reciprocal involvement in play (Riva Crugnola et al., 2013). Maternal caring and comforting behaviors were also added to the coding scheme. This way, the researchers were able to study mother-infant interaction in great detail. This detailed approach is of striking importance for understanding mother-infant interaction. Well-targeted empowerment programs may be improved with this information. The intervention can then focus on the behaviors that will really make a difference for the wellbeing of the infant as well as the mother. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Reference Crugnola, C.R.; Ierardi, E.; Gazzotti, S.; Albizzati, A. (2014). Motherhood in adolescent mothers: Maternal attachment, mother–infant styles of interaction and emotion regulation at three months. Infant Behavior and Development, 37, 44-56. --- ## How an internal clock gene can alter innate behaviors in mice URL: https://noldus.com/blog/internal-clock-gene-mice Published: 2014-07-24 12:56:00 Description: Some might argue that laboratory mice are not the same as wild mice, yet they remain capable of performing the innate, routine behaviors necessary to survive in natural environments, such as courtship and nest-building, Some might argue that laboratory mice are not the same as wild mice, yet they remain capable of performing the innate, routine behaviors necessary to survive in natural environments, such as courtship, nest-building, and exploratory activities. Still, their 'non-natural' (read: laboratory) environment may limit them in the expression of these behaviors. Circadian rhythmicity The internal circadian clock is of fundamental importance for animals to anticipate recurring events and ensuring basic behaviors, such as gathering food and building a nest, occur in time. One of the ways we influence the animal's natural capacity to perform these and other innate behaviors is by altering the light/dark cycle in a laboratory setting. Internal clock functioning In addition to the external environment, proper functioning of the internal clock also depends on biological factors such as genes; specifically, the Per1 gene Bechstein et al. took a closer look at the role of the Per1 gene in cyclical behavior, and compared wild type (WT) laboratory mice with a Per1 knockout (KO) strain. They found that this gene plays an important role in the regulation of innate behaviors, such as nest building and courtship behavior. Marble burying When you place bedding and objects in a cage, mice will typically bury the objects. Bechstein and his colleagues used this test to investigate the differences in explorative behavior between the strains. Video tracking software EthoVision XT was used to analyze running, rearing, and digging behaviors during the 30-minute test period. The Per1KO mice spent less time rearing and a longer latency to initiate digging behavior. There are several possible explanations for this: they may be less interested in the marbles or the new environment, less capable of interpreting the set-up as novel, or they could be more anxious. Since the Per1KO mice reportedly do not display more anxiety-like behaviors (Jilg et al., Hippocampus, 2010), problems in detecting a new environment as novel are compatible with the relative low amount of rearing behavior of the KO strain, which in turn relates to hippocampal defects associated with impaired exploration. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Vocalizations More evidence for deficits in hippocampus-related behaviors in the KO strain was found in ultrasonic vocalization tests. When repeatedly exposed to females, WT males decreased the number of ultrasonic calls per day. The Per1 KO strain showed major impairments in this behavior habituation. It was also interesting to find that the minimal peak frequency of their ultrasonic vocalizations was lower and the structure of the calls differed between WT and the Per1 KO strain. Sexual preference This difference in vocalization may also cause a difference in 'attractiveness' of the male test subjects to WT female mice. To test this, the researchers used a sociability set-up. A WT type female mouse was placed in a three-chambered cage: the middle chamber was empty, while each of the outer chambers contained a mesh cage housing either a WT male or a Per1 KO male. Each session lasted 10 minutes and was recorded and analyzed with EthoVision XT. Interestingly, the female WT mice spent more time exploring the cage areas of the Per1KO males. The authors speculate that this may be caused by the modulated ultrasonic vocalization frequency detected from the male KO mice; it could also be due to different call structure or scent. That females seem to favor the mutant over the WT mice might have an evolutionary reason: a higher genetic diversity of the offspring is a known principle for the elevation of fitness in a population. Clock gene necessary for innate routine behavior This and other studies show that WT mice are, when given the options to do so, quite capable of performing the innate routine behaviors of their ancestors, even though they have been in the lab for quite some years now. This study also suggests that the clock gene Per1 is important for exhibiting some of these innate behaviors. Acknowledgement I would like to thank authors Erik Maronde and Philipp Bechstein for their help writing this blog post. Read their publications at: - Bechtstein, P.; Rehbach, N.-J.; Yuhasingham, G.; Schürmann, C.; Göpfert, M.; Kössl, M.; Maronde, E. (2014). The clock gene Period1 regulates innate routine behavior in mice. Proceedings of the Royal B Society, 281, 20140034. --- ## Interspecific aggression: spotted dolphins vs. bottlenose dolphins URL: https://noldus.com/blog/interspecific-aggression-dolphins Published: 2014-06-30 14:33:00 Description: In the animal kingdom, competition is a part of life. Dominance hierarchies are common both within a group in a species (intergroup) or between two different species (interspecific). In the animal kingdom, competition is a part of life. Dominance hierarchies are common both within a group in a species (intergroup) or between two different species (interspecific). These hierarchies often result in aggression as the groups fight for dominance. It would make sense, therefore, that two species who are similar in status in the dominance hierarchy would have an unstable relationship and therefore engage in interspecific aggression continuously over time. One example of two species consistently engaging in interspecific aggression to establish dominance would be the Atlantic spotted dolphins (Stenella frontalis) and Atlantic bottlenose dolphins (Tursiops truncatus). Building on previous research This is not the first study done on the Atlantic spotted dolphin and Atlantic bottlenose dolphin populations at Little Bahama Bank in the Bahamas. These species have been observed since 1985 in the Wild Dolphin Project's long-term study. The previous years of study have revealed that interspecific encounters make up 15% of all the dolphin encounters on Little Bahama Bank. These encounters can be aggressive or non-aggressive, with the non-aggressive being interactions such as play, foraging, or traveling. When encounters were non-aggressive, spotted dolphins were observed in larger groups than bottlenose dolphins. Interspecific aggression makes up 30% of the interspecific encounters. During interspecific aggression, the overall group size of spotted dolphins is typically larger than bottlenose dolphins, and the average number of individuals that participate in the aggressive behavior is higher in the spotted dolphins than the bottlenose dolphins. The males of both species participate in aggression, while the females are present but inactive. Overall, the presence and the size of male spotted dolphin groups appeared to be important for determining the outcome of the aggressive behavior. However, the presence of the bottlenose dolphin groups seemed to not be an important factor. The focus of this study This study built on the results of the previous research. The goal of this study was to examine specific dynamics of interspecific aggression after it began, including describing and quantifying occurrence, testing if one species was more dominant, and testing which factors ended up having the strongest influence on the outcome of the interspecific aggression. Aggressive encounters consisted of numerous aggressive events within the time Jessica Cusick et al. observed them. The direction of the aggression was not always consistently one-way. Sometimes it switched and the species that had previously been the victim became the aggressor. In order to collect data, video was recorded and then viewed and scored using The Observer XT. The dominant species and the victim species were determined for each encounter. The dominant species was the one that was the aggressor for significantly more behavioral events than the other species. In conclusion Overall, the spotted dolphin group still had the strongest impact on the dynamic of aggression. The spotted dolphins impacted which group initiated aggression, the direction of the aggression, and the occurrence of shifts in dominance. The synchronous behavior of spotted dolphin groups impacted aggression and dominance in the encounters more than the group size of the spotted dolphins or what species they were. However, this does not suggest one species was more dominant than the other. Out of thirty-two aggressive encounters analyzed, spotted dolphins dominated sixteen encounters while bottlenose dolphins dominated twelve. This suggests that over a long period of time, the aggression between the two species of dolphin was bidirectional. Adult groups were typically the ones to dominate encounters, as opposed juveniles. There are many factors which impact aggressive interactions between two species. It is important to examine these when looking at interspecific aggression in order to see their impact. In the future, synchronous behavior of both spotted and bottlenose dolphins should be quantified during aggressive and non-aggressive interactions in order to provide more information about the purpose of synchronous behavior in dolphins. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References Cusick, J.A.; Herzing, D.L. (2014). The dynamic of aggression: how individual and group facts affect the long-term interspecific aggression between two sympatric species of dolphin. Ethology, 120, 297-303. --- ## The welfare of therapy dogs URL: https://noldus.com/blog/welfare-therapy-dogs Published: 2014-06-25 11:50:00 Description: Dogs have been used with adult substance abuse patients in animal-assisted interventions (AAIs) and animal-assisted therapy (AAT). Why use dogs in therapy? The impact of animal-assisted therapy on the dogs. As anyone who owns a pet could probably tell you, animals are great comforts to their human partners. The relationship between animal and human can go beyond just pet and owner, however, and become a therapeutic relationship. For example, dogs have been used with adult substance abuse patients in animal-assisted interventions (AAIs) and animal-assisted therapy (AAT). Why use dogs in therapy? They can be a good motivator for participation in an intervention and become a source of trust and comfort to the patient, thus improving the chance of therapy success. There has been a lot of research done on the impact that using dogs in therapy can have on humans. But what about the effect it has on the welfare of the dogs? The impact of animal-assisted therapy on the dogs Although research has focused mainly on the impact of using dogs in therapy for humans, there still is another side to this story. There have been few attempts to monitor the welfare of the animals – in this case, the dog's ability to cope and adapt to the environment it has been placed in. Lisa Maria Glenk and colleagues looked to change this. In this study, patients interacted with the therapy dogs based on the professional's instructions. There were several components to human-animal interaction behaviors, including verbal contact and tactile contact. Human-animal contact was initiated by the dog and the participants had already been instructed how to interact with the therapy dog in the appropriate way. Glenk et al. used both behavioral measures and salivary cortisol levels to monitor the welfare of the dogs used in this study. Researchers used The Observer XT to analyze the behavior of the dogs, using behavioral variables which were recognized easily by the observers. There was a range of behaviors examined – some were activity-related (such as running, sitting, and standing), while some were behaviors that had been previously shown to be linked to stress (such as lip licking, paw lifting, and panting). Saliva samples were also collected to test cortisol levels. In order to lessen the chance of circadian effects on the salivary cortisol, researchers limited their tests to a certain time of day. Only sessions starting in the morning were used in this analysis. In addition to the saliva samples collected presession and postsession, samples were also taken at home to be used as a baseline. Results Overall, there was no significant difference found in behaviors presession and postsession in the "activity" category or with the stress-related behaviors. Researchers also looked at the salivary cortisol levels in the dogs tested presession and postsession and found no significant differences. So what does these results indicate? Both the consistency in cortisol levels and in behavior suggest that the dogs were not stressed by their participation in therapy. As for the behaviors examined in the dogs, behavior is thought to be closely related to the situation. Therefore, behavioral cues must be interpreted carefully. Glenk et al. propose that certain behaviors that have been seen as related to stressful experiences before, such as lip-licking and body shaking, may be used by the dog to help manage stress. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Next steps in animal-assisted therapy Animal-assisted therapy (AAT) is a field that has been studied before, but most of the attention has been focused on the patients and their reaction to the dogs. This study focused on the behavioral and physiological health of the therapy dog and how a therapy session affected that. In the future, larger studies in this field will help provide further insights on behaviors and their relationships to cortisol and stress. Beyond just focusing on either the patient or the dog, future studies could examine the relationship of the patient to the dog. The continued research in this field will help evaluate the comfort levels of both patient and dog in therapy situations, and it will identify situations where it may be inappropriate to use AAT. Reference Glenk, L.M.; Kothgassner, O.D.; Stetina, B.U.; Palme, R.; Kepplinger, B.; Baran, H. (2014). Salivary cortisol and behavior in therapy dogs during animal-assisted interventions: a pilot study. Journal of Veterinary Behavior, 9, 98-106. --- ## How to measure emotions in pigs URL: https://noldus.com/blog/how-to-measure-emotions-pigs Published: 2014-06-23 08:41:00 Description: A commonly used assay for assessment of fear in animals is the novel environment test.In this test, an animal is placed in an arena for a particular time period and behaviors are scored. A couple of weeks ago, I wrote about why social pigs do better. This week, one of the researchers in this project, Inonge Reimert explains about the novel object/novel environment test they performed. Exploring or looking for an escape? A commonly used assay for assessment of fear in animals is the novel environment test (Forkman et al., 2007). In this test, an animal is placed in an arena for a particular time period and behaviors such as walking, standing, standing alert/freezing, and number of defecations and vocalizations are generally scored. Although these behaviors can provide insight into how fearful an animal was during the test (e.g. Boissy, 1995; Manteuffel et al., 2004; Mendl and Paul, 2004), they also may lead to confusion in this respect. For example, if an animal is found to be very mobile, does this indicate that the animal is not fearful and merely exploring the arena, or does it indicate that the animal is looking for an escape and is thus afraid (Rutherford et al., 2012)? Why use video tracking in emotion research? For a clearer picture of an animal's fear-reactivity in the novel environment test, the EthoVision software of Noldus Information Technology BV seems very promising. This software can track an animal's location in the arena which results in ascertaining very interesting patterns (see figure) that, for example, could help in deciding whether an animal is simply walking or pacing. Pacing animals are more likely to have the desire to escape the arena than non-pacing animals, or they may experience increased levels of stress (Mason et al., 2007). Moreover, the software can calculate the minimum and maximum velocity and the total distance travelled. Such parameters give much more information than just having the walking duration or the percentage of time spent walking. Reducing data using principal component In a study of my colleagues and myself (Reimert et al., 2014), pigs were subjected to such a novel environment test for 10 minutes. After 5 minutes a bucket was lowered from the ceiling and left in the arena for the remaining 5 minutes. In this study, more common parameters, such as those mentioned above, were scored, but with EthoVision we also tracked the pig's locomotion before and after the addition of bucket. In addition, the arena was divided into different zones such as a zone around the entrance and a zone around the bucket. Although having so many parameters to work with was great, during the writing process of the article, it became clear that not all of the results of all parameters could be shown one by one as that made the article too complex and too long. As a solution the number of parameters were reduced with a principal component analysis (e.g. Juul-Madsen et al., 2010). FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Hopes for the future Although this worked fine for the article, it unfortunately did not include the additional parameters for analysis provided by EthoVision XT. Fortunately, a Graduate student became excited about this subject as well and from September onwards she will study these EthoVision XT parameters more closely. Hopefully this will lead to further insight into the behavior of animals in the novel environment test. References - Forkman, B.; Boissy, A.; Meunier-Salaün, M.; Canali, E.; Jones, R.B. (2007). A critical review of fear tests used on cattle, pigs, sheep, poultry and horses. Physiology & Behavior, 92, 340-374. - Boissy, A. (1995). Fear and fearfulness in animals. Quarterly Review of Biology, 70, 165-191. - Juul-Madsen, H.R.; Jensen, K.H.; Nielsen, J.; Damgaard, B.M. (2010). Ontogeny and characterization of blood leukocyte subsets and serum proteins in piglets before and after weaning. Veterinary Immunology and Immunopathology, 133, 95-108. - Manteuffel, G.; Puppe, B.; Schön, P.C. (2004). Vocalization of farm animals as a measure of welfare. Applied Animal Behaviour Science, 88, 163–182. - Mason, G.; Clubb, R.; Latham, N.; Vickery, S. (2007). Why and how should we use environmental enrichment to tackle stereotypic behaviour? Applied Animal Behaviour Science, 102, 163-188. - Mendl, M.; Paul, E.S. (2004). Consciousness, emotion and animal welfare: insights from cognitive science. Animal Welfare, 13, S17-25. - Reimert, I.; Rodenburg, T.B.; Ursinus, W.W.; Kemp, B.; Bolhuis, J.E. (2014). Responses to novel situations of female and castrated male pigs with divergent social breeding values and different backtest classifications in barren and straw-enriched housing. Applied Animal Behaviour Science, 151, 24– 35. - Rutherford, K.M.D.; Donald, R.D.; Lawrence, A.B.; Wemelsfelder, F. (2012). Qualitative behavioural assessment of emotionality in pigs. Applied Animal Behaviour Science, 139, 218-224. Thanks to Inonge Reimert for telling us about her research. --- ## 6 things you must consider to improve your open field testing URL: https://noldus.com/blog/improve-your-open-field-testing Published: 2014-06-12 12:52:00 Description: Here are six recommendations the authors list to improve the translational and predictive value of behavioral readouts. Last week we talked about the new publication by Berry Spruijt and his colleagues in Journal of Neuroscience Methods, in which they tell us about the limitations of classical behavioral tests such as the open field. The article focused particularly on the great lack of reliability and validity in the use of these tests within and across laboratories. So what can we do to fix this problem? Here are six recommendations the authors list to improve the translational and predictive value of behavioral readouts: 1. Research context As mentioned in the previous post, behavioral tests are generally used for two different purposes. Behavior can be used as a simple indicator, in which it has limited explanatory power, or it can be studied to understand its functional role. According to Spruijt et al. the classical tests are sufficient for the first purpose. However, understanding the biological function of behavior requires more. The latter should be done in natural, more ethological settings (e.g. a large environment/arena, with sufficient stimuli to challenge the animal and/or in a social setting). Also in terms of analysis the latter requires more sophistication: a more detailed ethogram, advanced automation, and a detailed characterization of behavioral elements and their order. Thus, before you start, take a moment and choose your set-up wisely. 2. Start at the beginning Each behavioral experiment starts in essence with the breeding of the animals. Housing (e.g. single versus socially, enriched environments) and early life (parental care) conditions program the brain and thus affect behavior. So, take into account the impact of these factors. 3. Understanding the language of behavior As explained in last weeks' post; behavior is like a language. It does not merely exist of behavioral elements (the 'words'), but also the order of the elements (the 'syntax') has meaning. To truly understand behavior, we should dissect behavioral elements into either posture-related (e.g. rearing, grooming) and activity-related parameters (e.g. distance moved, location visited). Moreover, interpreting whether the observed behavior is meaningful or abnormal can only be done if we also analyze the order of the elements. 4. Allow the animal to express itself Behavior is typically preceded by response selection. This can only happen if there are a number of possibilities to choose from. A behavioral test should thus contain a number of stimuli that challenge the animal and offer enough freedom to the animal to make its choices optimally. For example, let's look at a test to measure drug-induced changes in activity in rats. Presentation of an aversive stimulus (intentionally or unintentionally) might make the rat want to hide, and the animal will begin searching for a hiding place in its environment. If there is none, the animal might increase its activity while it continues to search. This increased activity might be falsely interpreted as increased drug-induced exploration. 5. Novelty of the environment When a rodent enters a new environment, it has only one priority: to explore the novel environment. It is thus important to allow the animal sufficient time for exploration and familiarization; otherwise you are measuring the response to novelty instead of behaviors of interest. This is particularly important when studying agonistic and reproductive behaviors, which require strong familiarization with the environment. But even if you are 'only' interested in measuring (drug-induced) effects on activity, it is essential to allocate enough time to your test. According to Spruijt and his colleagues, virtually all open field studies (typically lasting 5 to 60 min) only measure immediate reactions to novelty. Thus, it is important to provide sufficient space and experimental time in your test. 6. All animals are not equal A sufficient number of animals should be included per experimental group (mean sample size 10-20). This is not only necessary for providing sufficient statistical power; it also allows the identification of subgroups (for example based on the animal's activity). When forming these subgroups it can be useful to take measures which are based on the animal's own behavior instead of arbitrary chosen criteria. For example, if you want to define a central zone and a peripheral 'wall' zone in the open field arena, you can take one particular cutoff point for all the animals. It will be more elegant, however, to define a criterion for each individual animal based on its own behavior, e.g. the frequency distribution of its distance to wall. Bring the experiment to the animal So now we have some do's and don'ts. How can we bring this all together for a perfect open field test scenario? Bring the experiment to the animal, rather than transporting the animal to the experiment, Berry Spruijt says. "A slightly more complex test cage appropriate for a longer stay of the animal may solve many problems". To accommodate the six requirements, you ultimately end up with a large automated test cage which gives enough space to the animal, allows for long-term continuous observations and provides access to food, water, bedding and intra-cage stimuli (e.g. a shelter). To address questions about anxiety levels or learning capacity smart tools can be integrated in the cage, allowing operant conditioning paradigms to take place in the animal's own environment. Stress due to transport and handling will be minimized. Let the animal habituate for at least a couple of hours, or rather days, before testing. This way many confounding factors are excluded. The focus on behavioral observations in such a home cage-like environment is slowly growing. Several types of cages are commercially available, among which is the Noldus PhenoTyper. In the paper by Spruijt et al., two examples are given of experiments using the PhenoTyper set-up. The experiments are conducted at Delta Phenomics, an innovative contract research organization specialized in animal behavior and one of the first users of the PhenoTyper set-up for commercial purposes. One experiment clearly illustrates the added value of a larger test cage to allow the animal more freedom to interact socially or not. The other nicely shows that great, and clearer, drug-induced differences can be detected in the PhenoTyper using a prolonged observation time of 3 hours compared to a standard open field test. Next level data analysis Finally, the continuous observation of multiple behaviors yields large sets of video images, which need to be effectively processed and analyzed. Fortunately, recent developments in behavioral science are focused on the development of such sophisticated analysis instruments. Thanks to the rapid evolution of analysis techniques (e.g. sequential or cluster analysis, t-patterns) and data mining algorithms, several automated analysis tools have been published or are currently under construction. So, the tools are out there. Now it is a matter of starting to use them! RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Read more Read more in the previous post dedicated to this paper, or find the publication at: Spruijt, B.M.; Peters, S.M.; Heer, R.C. de; Pothuizen, H.H.J.; Harst, J.E. van der. (2014). Reproducibility and relevance of future behavioral sciences should benefit from a cross fertilization of past recommendations and today's technology: "Back to the future". Journal of Neuroscience Methods, article in press, doi:10.1016/j.jneumeth.2014.03.001. Find out more about PhenoTyper here.  --- ## The do’s and don’ts in behavioral testing: improve your open field test URL: https://noldus.com/blog/behavioral-testing-improve-your-open-field-test Published: 2014-06-05 13:52:00 Description: Scientists have been performing open field tests for quite some time now. Over the years it has become one of the most popular tests in rodent behavioral research. So what’s not to love? Scientists have been performing open field tests for quite some time now. For eighty years, to be exact. And over the years it has become one of the most popular tests in rodent behavioral research, as it allows the researcher to study (locomotor) activity, exploration, and anxiety all in one test environment. So what's not to love? It's easy, short, and straight-forward. Plus, it is a highly validated test…or is it? In their recent review in Journal of Neuroscience Methods, Berry Spruijt (Professor of Ethology and Animal Welfare, Utrecht University, the Netherlands) and his colleagues tell us that, like most of the popular classical tests, it is actually not well validated. This is a well-known problem in behavioral research. In fact, specific for the open field test, there seems to be a lack of reliability and validity. Despite all the efforts labs put into standardizing their methods and procedures, there is still a great amount of variability in behavioral results within and across laboratories. Berry Spruijt and his co-workers have been drawing our attention for many years now to the limitations of the classical behavioral tests and the necessity of using more advanced behavioral methods and technologies. This ambition has even led to the establishment of an innovative contract research organization specialized in animal behavior, called Delta Phenomics. Although most of the classical tests in principle are not bad, there are a few important issues that should be considered when one wants to use them well. An open field is not just an open field Let's start with the obvious: the open field apparatus itself. What is the first image that pops into your head? Is it a round open field? Or square? How big is it? Does it have opaque walls and how high are they? How are the measures taken: via video-tracking, infrared beams, or with a hand-held stop watch? Is the test conducted during the dark (active) or light (inactive) phase? Ask these questions across five different laboratories, and you will probably come across at least five different open field set-ups. Clearly there is little to no consensus there. Even the definition of an inner and outer zone in the arena (used to study behaviors such as thigmotaxis) is not clear-cut. So, how can we compare results of different studies when there is already such variability in the apparatus and test set-up itself? Reading too much into the results The very fact that the open field seems to be such an easy, short, and straightforward test might actually be its downfall. Over the years people have started using open field testing for the wrong reasons and/or have become too liberal when drawing conclusions from the data. As Spruijt and his colleagues mention, people generally tend to use behavioral tests for two different purposes. On the one hand, one applies a test to answer a limited, but clear question: for example, dose-response testing in pharmacological studies. The behavioral readouts are used as simple quantitative measures. On the other hand, one can conduct a test with the aim to assign a biological function to the behavioral changes observed as a consequence of the experimental manipulation (e.g. an altered genome). According to Spruijt et al. the classical tests (like open field and elevated plus maze) are sufficient for the first research purpose. However, understanding the biological function of behavior requires more. This is where things have gone wrong: people have started using tests appropriate and valid for answering the straightforward questions for more hypothesis-free testing purposes. For instance, the time the animal spends in the center of the open field arena is generally used as a measure of anxiety, because anxiolytic drugs typically increase this measure. However, when any given manipulation happens to enhance the time spent in the center, this does not automatically mean that it is anxiolytic. As Spruijt and his colleagues point out we should be careful with these kind of quick and oversimplified interpretations. Simplistic or no automation What clearly does not help is the continuous use of simplistic automated tools (if they are used at all), such as activity measurements with infrared photo beams. Although these tools are preferred above manual scoring of behavior, which is still frequently used, these techniques are limited to general activity of the animal (such as distance moved and time spent in particular areas (zones) in the open field). Moreover, tests tend to be relatively short (5-60 minutes), meaning that they basically only measure reactions to novelty. The choice for these tools is particularly striking as innovation is not the limiting factor here. In fact, available technology now supports a wide range of movement and activity measurements, such as path lengths, kind/number of zones visited, the number of turns the animal makes, etc. In addition to movement-related parameters, quantitative behavioral events can be automatically measured, such as rearing and grooming. Also, the possibilities to analyze this growing amount of data are up to par. So why is it that the methods used in the majority of behavioral research studies seem to have frozen in time? FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Behavior is what you see? The answer to this question is twofold. First, when it comes to observing behavior, we humans think we know better than computers. While genes, molecules, and action potentials are things we cannot see and we obviously need advanced technology to measure them, the added value of innovative technology in measuring behavior has been underestimated for years, explains Spruijt et al. We can simply see an animal's behavior, so why do we need computers for the job? The danger here is that we think we know what we see, and what it means. However, we do not see everything. The automatic – and thus objective – way in which technology allows us to gather behavioral data, allows us actually to see more. Additionally, and maybe even more importantly, animal behavior is much more complex than we are aware of. Behavior is like a language. It does not merely exist of behavioral elements (the 'words'), but also the order of the elements (the 'syntax') has meaning. This order, however, usually remains unnoticed by the human observer, especially across longer observation times. To understand behavior, and grasp its true meaning, we will need to rely on advanced technology that can analyze the frequency and durations of the behavioral elements, as well as the sequential organization of behavior. Second, researchers also seem reluctant to switch to new technology. A huge amount of literature represents 'the old ways' and researchers hold on to these, even when they might be wrong. Most of this referenced data, generated over decades of research, serves as 'backbone' for new developments. According to Spruijt et al. this is a difficult circle to break. How to move on to better things In their article, Spruijt and his colleagues propose a list of solutions and implementations to improve the validation of the classical tests in behavioral research, in particular open field testing. You can read about this in our next post, to be posted here on this blog next week. Curious? Check out the publication yourself, right now! Spruijt, B.M.; Peters, S.M.; Heer, R.C. de; Pothuizen, H.H.J.; Harst, J.E. van der. (2014). Reproducibility and relevance of future behavioral sciences should benefit from a cross fertilization of past recommendations and today's technology: "Back to the future". Journal of Neuroscience Methods, article in press, doi:10.1016/j.jneumeth.2014.03.001. --- ## Insect damage on leaves changes the reproductive strategy of plants URL: https://noldus.com/blog/optimizing-pollination Published: 2014-06-03 14:17:00 Description: We all know that the majority of plant species depends on pollinators, like bees and syrphid flies, for reproduction. What most of us do not know is that this process is far more complex than it looks at first sight. Optimizing pollination We all know that the majority of plant species depends on pollinators, like bees and syrphid flies, for reproduction. What most of us do not know is that this process is far more complex than it looks at first sight. Think about it: pollinators do not visit flowers to transfer pollen, but to collect nectar. If the amount of nectar in the flowers is too large, the pollinators will not visit other flowers to collect more, so no pollen is transferred to other plants. Conversely, if the amount of nectar is too small, it will not pay for the pollinators to visit those flowers. So plants have to fine-tune the nectar production in their flowers to optimize pollination. And did you know that some plant species even add toxins to their nectar, which stimulates pollinators to move to other plants, bringing the pollen with them [1]? Caterpillar damage and seed production The story gets even more complicated when plant-eating insects become involved. Plants may have to change their strategy when their leaves are eaten by herbivorous insects. In a previous blog I wrote about plants that speed up seed production when they are attacked by caterpillars [2]. This way they make sure to reproduce before the caterpillar infestation is so severe that the flowers are eaten, which would mean no reproduction at all. Caterpillar damage and pollination In a recent publication, Bruinsma et al. [3] investigated whether damage by caterpillars of the cabbage white butterfly (Pieris brassicae) on black mustard (Brassica nigra) plants affects pollinator attraction to the flowers. They carried out dual-choice tests with plants with and without caterpillar damage on the leaves. And they did a field study, also with plants with and without caterpillar damage. In both cases, Pocket Observer mobile scoring software was used to observe insects and score whether the number and duration of flower visits by pollinators was affected by plant damage. They also analyzed the nectar composition and the volatiles produced by the leaves and flowers. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Shorter visits, different smells and bittersweet nectar In the dual-choice test, the number of plant visits and the visit duration of the small white butterfly (Pieris rapae) and the visit duration of the honeybee Apis mellifera were lower on the plants with caterpillar damage than on the control plants. In the field study, the authors found that caterpillar damage affected visit duration of syrphid flies. The flowers of the damaged plants produced more volatiles than the control plants and the chemical composition of the volatiles was different. The nectar of the damaged plants was also affected. It contained more sugar, but also more glucosinolates. Interestingly, glucosinolates play a role in plant defense against herbivores. To be continued The authors conclude that the effects of plant damage by caterpillars on the pollinators is subtle and that it is not easy to interpret how it can affect plant fitness. However, the authors found an overall tendency for the pollinators to spend less time per visit on the flowers of the damaged plants. This points in the direction that caterpillar damage enhances the distribution of pollen to other plants. The increased concentration of glucosinolates, which deter insects, in the nectar of the damaged plants may also motivate the pollinators to visit other plants, which further enhances pollination. But in general, the study leaves ample space for follow-up research to understand the effect of insect damage on plant reproduction in more detail. References - Kessler, D.; Baldwin, I.T. (2007). Making sense of nectar scents: the effects of nectar secondary metabolites on floral visitors of Nicotiana attenuata. The Plant Journal, 49 (5), 840-854. - Lucas‐Barbosa, Dani, et al. (2013). Reproductive escape: annual plant responds to butterfly eggs by accelerating seed production. Functional Ecology, 27(1), 245-254. - Bruinsma, Maaike, et al. (2014). Folivory Affects Composition of Nectar, Floral Odor and Modifies Pollinator Behavior. Journal of Chemical Ecology, 40 (1), 39-49. --- ## How zebrafish regenerate (and how to measure their recovery) URL: https://noldus.com/blog/zebrafish-regenerate-measure-their-recovery Published: 2014-05-12 10:36:00 Description: We all know of animals that are able to regenerate: lizards that grow back their tails, flatworms that can grow into new worms when cut in half. Zebrafish have this special ability as well. We all know of animals that are able to regenerate: lizards that grow back their tails, flatworms that can grow into new worms when cut in half. Zebrafish have this special ability as well. You can't cut them in half and expect two new zebrafish, but there are parts of their body that are able to regenerate, such as heart tissue. The heart cell can divide to replenish missing tissue; interestingly, this property is also shown in a newborn mouse heart, but is lost as the mouse matures (European Biopharmaceutical Review, April issue). The key to spinal cord injury treatment? Regenerative abilities may also be the key to spinal cord injury treatment; yet another good reason for scientists to study zebrafish in the lab. They may hold the key to the development of important therapies for spinal cord injury, as Liping Ma and colleagues show us in the April issue of PLOS ONE. Special enzyme Spinal cord injury often leads to permanent disabilities in humans (and other mammals), but zebrafish can recover because they seem to be able to re-express the necessary genes to grow back the axons projecting from the brain. Ma et al. previously showed that the enzyme legumain seems to be involved in this process, as its expression is upregulated in the brain after the spinal cord was severed in zebrafish. Now, they have found that this enzyme is indeed necessary for the recovery of the spinal cord. Experimental set-up Spinal cord injury was surgically induced by cutting the spinal cord completely. A control group received sham surgery. In addition, zebrafish morpholino's for legumain were used to knock-down the enzyme and test it's essentiality for spinal cord regrowth. Functional recovery was tested by performing locomotor analysis in free swimming zebrafish six weeks after surgery. The movement of the fish was recorded in a 50 x 30 cm tank, using EthoVision XT video analysis to automatically track and analyze swim paths. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Impaired recovery after enzyme knock-down Microarray analysis showed that legumain was upregulated after spinal cord injury, both in the brainstem (medial longitudinal fascicle) and in the caudal spinal cord itself. Knockdown of legumain resulted in impaired recovery, showing that this enzyme indeed seems essential for regeneration of the axons. Implications for the future In the future, these scientists plan to this research further and investigate this mechanisms through which legumain functions. Of course, the hope is that eventually this information leads to therapies for mammals. References - Ma, L.; Shen, Y.-Q.; Khatri, H.P.; Schachner, M. (2014). The asparaginyl endopeptidase legumain is essential for functional recovery after spinal cord injury in adult zebrafish. PLOS ONE, 9(4), e95098. - If you are interested in tools for zebrafish research, click here. - Want to read more about video analysis? Go to EthoVision XT - Want to read about spinal cord injury research in rodents, click here. Or read about zebrafish video tracking this free white paper. --- ## How zebrafish are changing neuroscience URL: https://noldus.com/blog/how-zebrafish-are-changing-neuroscience Published: 2014-05-01 10:10:00 Description: Zebrafish. This little fish is a vertebrate, and a relatively complex one. Looking at the major neurotransmitters and hormones that are investigated in neuroscience, they are as good of a model as many mammalian species. Zebrafish. This small little fish is a vertebrate, and a relatively complex one at that. Looking at all the major neurotransmitters and hormones that are investigated in neuroscience, they are as good of a model as many mammalian species. Indeed, recent studies have shown how they are ideal for testing in behavioral domains such as anxiety, sociality, sleep, reward, and cognition. Only fifteen years ago researchers thought fish were too simple, but zebrafish have proven their worth and so Progress in Neuro-Psychopharmacology & Biological Psychiatry is dedicating a special issue to this striped creature. Allan Kalueff and his colleagues have written the preface to this issue and introduce us elegantly into the world of zebrafish and brain disorder research. The zebrafish fan club Why have neuroscientists grown so fond of zebrafish? Kalueff et al. list a great number of reasons. They make a great in-vivo model, offering great translational value due to common organ systems and cell types, and their high genetic homology to humans. They are also the ideal animal for lab studies, as they reproduce quickly and abundantly and are low in costs and maintenance. They develop externally, which allows the larvae to be easily subjected to various environmental factors. Finally, they are transparent in both embryo and larval stages, allowing direct study of internal development. And did you know they live longer than mice? Zebrafish don't just swim around Zebrafish show a well-defined range of behaviors, and these phenotypes resemble those of rodents and humans, making them an ideal subject for psychopharmacological studies. Many popular behavioral tests that are used in rodents, such as T-maze, plus maze, social preference, social interaction, and open field tests, have been successfully translated to zebrafish studies. Added bonus is that video analysis technology available today allows researchers to automate zebrafish (behavioral) tests easily. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Social little fellows Zebrafish have a natural tendency to shoal. Measuring this aspect of social behavior is very straight-forward. Video tracking offers a practical way to measure the inter-fish distances on a frame-by-frame basis. Shoaling behavior is influenced by many factors, such as predation and the availability of food, but also individual appearance and group size. Read more about this in this blog post. Getting curious Anxiety and exploration are studied in straight-forward, established paradigms in rodents (open field, plus maze), but can also be assessed in zebrafish using a novel tank. Diving to the bottom and bottom dwelling are easily-measured indicators of anxiety-like behavior and the effects of pharmaceuticals are often clearly distinguishable. We wrote about this previously. Good learners Zebrafish are fantastic students, and they can show off their learning ability in a T-maze. They also demonstrate color discrimination and are able to learn to swim to a certain color. Read about some recent studies in this blog post. Into the rhythm Chronobiologists also love the zebrafish, because they rapidly develop their inner clock, and this system is highly light-entrainable. This post highlights research that measures rhythmicity in zebrafish larvae. Coming to you in 3D The big difference between rodents and zebrafish is, of course, that they swim. In order to study the details of their movement it therefore makes sense to look at their behavior in three dimensions. Using video tracking, it is actually not so difficult to get detailed data this way. Christine Buske wrote about this a while back. References - Kalueff, A.V.; Echevarria, D.J.; Stewart, A.D. (2014). Gaining translational momentum: more zebrafish models for neuroscience research. Progress in Neuro-Psychopharmacology & Biological Psychiatry, article in press, doi:10.1016/j.pnpbp.2014.01.022 - Solutions for zebrafish research. - More blog posts on zebrafish. --- ## Are there objective tests for predicting autism severity? URL: https://noldus.com/blog/objective-tests-predicting-autism-severity Published: 2014-04-10 13:01:00 Description: Some disorders cannot simply be diagnosed with a blood test or tissue-culture. Autism Spectrum Disorder (ASD) is a good example; its diagnosis relies upon behavioral tests and questionnaires. Some disorders cannot simply be diagnosed with a blood test or tissue-culture. Autism Spectrum Disorder (ASD) is a good example; its diagnosis relies upon behavioral tests and questionnaires. Both are inherently subjective – you can imagine that research, diagnosis, and treatment of autism would benefit from a more efficient and objective way to measure behavior and quantify the severity of autism. FREE WHITE PAPER Autism Research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Download Video tracking children with ASD Ira Cohen and his colleagues have made some significant steps in this direction in recent years. We wrote about his research last year in this blog post, telling you about how video tracking data correlated with the severity of autism in children. This research was presented at the International Meeting for Autism Research (IMFAR) in 2013, and recently published in Molecular Autism. Movement data correlates with autism severity In his paper, Cohen describes their study of 36 children, of which 27 were diagnosed as being on the autism spectrum. These children were studied during a free play session, video tracking their movement with EthoVision XT software. Researchers were specifically interested in how much time the child spent near the parent or in the periphery of the room, and they indicated these areas as zones of interest in EthoVision XT to measure time spent in and latency to approach these areas. They also studied the relative angular velocity of the child's movements. These data were compared with the results of several ASD rating scales. Tracking data correlated with the severity of autism, as well as with problems with arousal regulation and irritability, indicating that this way of objective behavioral testing may serve as a useful and relatively culture-free tool for the assessment of ASD severity. Read more about this research in our previous report on this study or in the paper. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Early identification Cohen has been interested in the early identification of ASD for a long time. Being able to catch the signs early on is very important, because the sooner you know your child has autism, the more effective treatment (behavioral intervention) can be. In this recent paper in Autism Research, Cohen and his colleagues evaluated if signs of early brainstem dysfunction could predict the development of ASD in a longitudinal study of a cohort of NICU (neonatal intensive care unit) graduates. Such children are at greater risk for developing ASD. Brainstem responses as indicators for autism Typically, early recognition of ASD relies on behavioral signs, which are not apparent until the child is about 18 months old or even later. It would help if there were signs that could be picked up early on. Cohen was successful in identifying a predictor in this group of 74 at-risk children in this study. In short, abnormal brainstem responses shortly after birth were linked to repetitive and ritualistic behaviors later in life. (The auditory brainstem response is a typical hearing test performed in newborns; in this study, it was used as an indicator of functional integrity of neural conduction.) Second, visual preference was tested by showing the babies, when they were four months of age, checked patterns flashing at difference rates. A preference for higher stimulation rates at four months of age was linked to the severity of ASD, as well as to the diagnosis of ASD later in life, but only within the group that showed abnormal brainstem responses. Future research These are promising results in the quest for more objective tests and early diagnoses of disorders on the autism spectrum. Cohen is currently further investigating early predictors of ASD in children that are at risk for ASD. He tells us that he is now looking into how video tracking can help in the testing of these at-risk children. We look forward to the results! References - Cohen, I.L.; Gardner, J.M.; Karmel, B.Z.; Kim, S.-Y. (2014). Rating scale measures are associated with Noldus EthoVision-XT video tracking of behaviors of children on the autism spectrum. Molecular Autism, 5(15), doi:10.1186/2040-2392-5-15. - Cohen, I.L.; Gardner, J.M.; Karmel, B.Z.; Phan, H.T.T.; Kittler, P.; Rovito Gomez, T.; Gonzalez, M.G.; Lennon, E.M.; Parab, S.; Barone, A. (2013). Neonatal brainstem function and 4-month arousal-modulated attention are jointly associated with autism. Autism Research, 6, 11-22. - Website of the Department of Psychology of the Institute for Basic Research in Developmental Disabilities, NY, USA --- ## Physiological and behavioral analysis: coping with stress URL: https://noldus.com/blog/physiological-and-behavioral-analysis Published: 2014-04-08 11:33:00 Description: Having a behavioral coping strategy means that a person can regulate emotions and deal with stressful situations. Coping with stress I may be atypical, but for the ease of explaining coping mechanisms in stressful situations, I put myself in the spotlight. I am afraid of heights, spiders, mice, rats, ants, horror movies, needles, and skiing downhill at high speed. So to keep myself from going crazy, I sometimes need to lower my stress levels. How? For example, when watching a scary movie, I tend to look away from the screen when it gets really scary. In those cases, I immediately feel my stress levels reduce. I can breathe again and my heart rate lowers. That's how I cope with stress. Science tells us that when confronted with a stimulus that is threatening, a person can either adopt a vigilant strategy by looking more at the stimulus or an avoidant strategy by looking away. Having a behavioral coping strategy means that a person can regulate emotions and deal with stressful situations. Gaze aversion Danielle de Veld and colleagues from the Behavioural Science Institute, Radboud University Nijmegen, The Netherlands (2014) investigated the use of gaze aversion in their laboratory. They recruited a group of 140 children between 9 and 11 years of age. De Veld and colleagues investigated how the use of gaze aversion as a behavioral response to a stressor is related to cortisol reactivity. They explain that the development of adequate use of gaze aversion as a coping strategy could be an important skill in children's development. Trier Social Stress Test for Children All children were invited to a behavioral research lab in Nijmegen, The Netherlands. The first saliva sample was collected within five minutes after arrival. In total, seven saliva samples were collected pre-testing, during the Trier Social Stress Test for Children (TSST-C, Buske-Kirschbaum, 1997), and after the test. This test was initiated to induce stress. De Veld and colleagues explain that the TSST-C consisted of a public speaking task in which children were asked to provide an ending to a story read out loud by the experimenter and a mental arithmetic task. Both tasks were performed in front of a jury of two researchers in white lab coats. After the test, children were seated in front of the TSST-C jury for judgment. Their perceived stress scores were calculated based on a post-test questionnaire that all of the children filled in. The lab was equipped with a wall-mounted camera that recorded the TSST-C procedure. The video recordings enabled detailed observation. Veld et al. started interval coding just after the initiation of the public speaking component of the TSST-C and ended the behavioral coding when the public speaking task was completed. In this study, intervals were set at 2 seconds. First, the observer coded whether the child's gaze had been towards the jury or averted. Second, the observer coded who spoke: child, jury, or nobody. The researchers used The Observer XT coding and analysis software. Results showed higher cortisol reactivity in children who perceived the task as more stressful. The researchers found a quadratic relation between gaze aversion and cortisol which depended on the level of perceived stress: for children with low levels of cortisol reactivity, the level was lowest with intermediate levels of gaze aversion. However, for children with high levels, cortisol reactivity was highest at intermediate levels of gaze aversion. As a result, they explain that these results indicate that gaze aversion may only play a minor role in behavioral coping strategy at this age. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - Veld, D.M.J. de; Riksen-Walraven, J.M.; Weerth, C. De (2014). The relation between gaze aversion and cortisol reactivity in middle childhood. Hormones and Behavior, 65, 173-178. - Buske-Kirschbaum, A.; Jobst, S.; Wustmans, A.; Kirschbaum, C.; Rauh, W.; Hellhammer, D. (1997). Attenuated free cortisol response to psychosocial stress in children with atopic dermatitis. Psychosom. Med., 59, 419–426. - Veld, D.M.J. de; Riksen-Walraven, J.M.; Weerth, C. de (2012). The relation between emotion regulation strategies and physiological stress responses in middle childhood. Psychoneuroendocrinology, 37, 1309–1319. --- ## Why wolves cry out for their friends URL: https://noldus.com/blog/why-wolves-cry-out-for-their-friends Published: 2014-04-03 14:48:00 Description: Why do wolves howl? From research, movies, and even television series, we learn that wolves cry out to each other to facilitate the reassembling of a pack when members have strayed. Why do wolves howl? From research, movies, and even television series, we learn that wolves cry out to each other to facilitate the reassembling of a pack when members have strayed. These calls are a functional way of long-distance communication, not only for wolves but also other species such as birds and mammals. So the functional importance of this behavior seems evident. But what actually makes a wolf cry? Is it because it misses its friends? Or is it simply something its body tells it to do? Howling for pack members Researchers at the Wolf Science Center in Austria noticed that whenever a wolf was taken out for a walk, the pack members left behind howled. They always cried out for the one that left. Last year, they published a study (Mazzini et al., 2013) which explains why. Why do they cry? One possible mechanism driving the howling could be a purely physiological one. In other words, the body automatically reacts by howling when a pack member leaves or when other members howl. It might also be possible for wolves to use their voice flexibly, or, in other words, they respond differently to different events and social contexts and use their howling accordingly, more or less deliberately deciding how to respond. Recording the howling To find out, Mazzini and his colleagues decided to record the howling behavior of nine wolves (2 packs) whenever one of the pack members left. They were interested to find out if it mattered if the leaving individual was actually taken away or remained in the vicinity (in the latter case, howling would not be functional). So they took each individual out for a long walk. Either before or after that, a control session existed of taking that same individual to a testing house close by. During the first twenty minutes of the absence of their pack member, vocalizations were recorded. After that, saliva samples were taken for cortisol-measurements. Behavioral study to determine hierarchies and relationships Researchers were also curious to know if the hierarchy position of the leaving wolf mattered for howling behavior of its pack members or friendship between the different wolves. First, they had to establish the affiliative and dominance relationships between pack members. For this, they used an extensive ethogram by which they studied the behavior of the packs. This ethogram included affiliated behaviors such as greeting, inspection, grooming, playing, wrestling, and hide seek. Agonistic and dominance behaviors included dominant approach, stand over, submission, bite, growl, attack, fight, and more. Behaviors were studied throughout the day, but only when the pack was complete and there were no disturbances. Each individual was studied for ten minutes straight, eight times in total over a period of four months with Pocket Observer on a handheld computer. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Wolves cry out for their friends The wolves almost always howled when a pack member was taken for a long walk. They almost never howled during the control experiments, indicating that these situations did not require communication and were less stressful for the animals. The dominance rank of the leaving individual had a significant effect on howling behavior: wolves cried out more for a higher ranking pack member. Interestingly, the number of previously recorded affiliative behaviors between the howler and the leaving wolf mattered too. In other words, wolves cry out more for their friends. In fact, friendship seemed to matter even more than hierarchy when researchers took a closer listen at the kind of howls that were emitted. When howls were distinguished as either starting of a chorus or joining the other wolves in a howl, data showed that wolves started a chorus more often for friends. This was not true for the effect of rank. Howls are under flexible control Because wolves cry out more for friends, and the cortisol levels measured in saliva samples were not correlated to the number of spontaneous howls or total number of howls a wolf emitted, the authors conclude that howling behavior may very well be under the flexible control of the individual. Want to try out The Observer XT annotation software? References Mazzini, F.; Townsend, S.W.; Virányi, Z.; Range, F. (2013). Wolf howling is mediated by relationship quality rather than underlying emotional stress. Current Biology, 23, 1677-1680. More information about annotation software and scoring behavior can be found at The Observer XT for animal research. --- ## Healthcare communication - dealing with emotions URL: https://noldus.com/blog/healthcare-communication-dealing-emotions Published: 2014-03-25 15:29:00 Description: Communication studies have shown that breaking bad news is best be done immediately and with clear wording. What is the best step forward? The importance of dealing with emotions in medical encounters Unfortunately, sometimes doctors have to give bad news to their patients. Communication studies have shown that breaking bad news is best be done immediately and with clear wording. What is the best step forward? From previous research, we know that hearing bad news evokes physiological arousal. In an aroused condition, it can be hard to stay focused. The information density of a medical encounter can be quite overwhelming. Since doctors explain treatment options and implications in a medical encounter, it is important that the patient recalls the information given to be able to take a well-founded decision. In a recent study, researchers gave the following advice: Clinicians should deal with patients’ emotions before providing additional medical information (Sep et al., 2014). Affective communication Milou Sep and colleagues explain how behavioral research techniques can help us understand and improve doctor-patient interaction. According to Sep and colleagues, a doctor can influence the information recall by using affective communication. When reassuring the patient and focusing on continued support, the doctor can help decrease evoked physiological arousal. Decreased physiological arousal then improves the level of information recall. Observe reactions In their paper, Sep et al. explain that they chose to observe and measure the response of analogue patients because of ethical reasons. Analogue patients are healthy subjects who rate video recordings of medical consultations while empathizing with the patient on screen. This method has been tested and found reliable as a way to assess doctor-patient communication. A total of fifty participants were asked to watch a video in which a patient was informed about a diagnosis of incurable cancer. In order to understand the influence of affective communication on patients, their Skin Conductance Level (SCL) was measured and they were asked to recall information from the consultation. Two videos were created: one standard and one affective communication video. In these videos, several moments were of interest. For example at T1, the clinician disclosed the bad news. Later on, the affective communication of the clinician differed. In the test group, the clinician added empathetic remarks such as “We will do and will continue to do our very best for you…” in the conversation and focused on reassurance and ongoing support. Deal with the patients’ emotions After the consultation, the analogue patients took off the SCL measurement equipment and were asked to fill in a recall questionnaire. Analyzing the physiological arousal, Sep and colleagues conclude the level of arousal decreased in the group where the clinician dealt with patients’ emotions by using affective communication. Because physiological arousal was objectively measured using BioPac and The Observer XT equipment, the researchers see a clear advantage over studies where researchers relied on self-reporting. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your free trial Research in hospitals These findings suggest that clinicians need to deal with patients’ emotions before providing additional medical information. In order to take this one step further, the researchers explain that it is important to test affective communication in other medical encounters. If it’s not a real consultation, then a simulated event might give even more insight into doctor-patient interaction. Moreover, non-verbal behavior can also be taken into account. Free case study Interested? Read on! Observe doctor-patient interaction to learn more about dealing with emotions, non-verbal communication, and patterns in behavior. The research area of clinical communication has over the last thirty years grown both in the number of publications and in importance in health research. Studies of the psychophysiology of clinical communication may be useful in the process of quality improvement in health care. Reference Sep, M.S.C.; Osch, M. van; Vliet, L.M. van; Smets, E.M.A.; Benzing, J.M. (2014). The power of clinicians’ affective communication: How reassurance about non-abandonment can reduce patients’ physiological arousal and increase information recall in bad news consultations. An experimental study using analogue patients. Patient Education and Counseling, 95, 45-52. --- ## How to mark zebrafish without compromising their behavior URL: https://noldus.com/blog/how-to-mark-zebrafish Published: 2014-03-20 14:07:00 Description: How to mark zebrafish without compromising their behavior? They may have just found the answer to this at the University of Toronto. Cheung et al. tried out a method using subcutaneous injection with dyes. How to mark zebrafish without compromising their behavior is a recurring question in zebrafish research. They may have just found the answer to this at the University of Toronto, Mississauga (Canada). Cheung et al. tried out a method using subcutaneous injection with dyes. How to mark zebrafish without compromising their behavior Clipping fins and adding tags There have been many advances in methods and techniques for experiments with zebrafish, but identifying individuals seems like a difficult problem to tackle. You can't just tell from the pattern of their stripes like with zebras, so even the trained eye can't tell them apart. Many researchers use markings – clipping the fins in a specific way. It's a relatively easy method, but because these fins are mainly transparent, these markings are difficult to see. Moreover, clipping fins might interfere with the fish's swimming abilities, which poses a new problem, especially for behavioral studies. Other well-established methods include implants and tags, which work fine on larger fish, but are simply too big for the small zebrafish, and therefore interfere with their swimming ability as well. Color dye under the skin Eugene Cheung and his colleagues tried a new method: subcutaneous injection. They tested five colors: red, green, black, yellow, and blue on more than a hundred gold (pigment deficient) zebrafish. They found that this injection method had a very high survival rate (96%) and that the pigment lasted for at least 30 days, the period typically needed for behavioral experiments. Behavioral consequences: agonist behavior Next, the behavioral consequences of this injection were tested. Fish were tested in shoals of four, and, while monitored from a side view, their social behaviors (specifically agonistic behaviors) were scored with event recording software The Observer XT. To elude agonistic behavior, the tanks were attired with fake plants, creating a desirable zone to enhance territorial responses. Behaviors that were recorded included: - Chasing: fast swimming while pursuing another fish. - Aggressive display: opening the dorsal anal and caudal fins. - Repel: the focal fish moves toward an approaching fish, forcing it to make a rapid direction change (pooled under aggressive display). - Sparring: two opponents circle each other while undulating their bodies and erecting the fins (pooled under aggressive display). - Biting: the fish opens its mouth and bites into the fin or body of the opponent. No behavioral consequences The frequencies of agonistic behaviors were not significantly different between injected and control fish. This is an important finding, as wild-type colored zebrafish are known to change their own coloration to lighter or darker when they become fearful or aggressive, respectively (Gerlai, 2003). Cheung et al. also did not find motor dysfunction or abnormal postures due to the injection. Zebrafish with and without pigment This study used gold zebrafish, while many well-defined strains of zebrafish are of the wild-type which show the typical zebrafish stripes. You can imagine that the effect of the markings is oppressed by their natural pigment. In a follow-up study these authors therefore tested a few wild-type-colored zebrafish and found that the markings were also visible, although the green and blue color markers were notably less visible against the naturally blue and green coloration of the zebrafish body. Future zebrafish research Now some questions remain, such as if these markers are able to be picked up by video tracking systems and whether zebrafish will be able to distinguish each other on the basis of the color mark. Cheung et al. plan to investigate this in the future. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial References - Cheung, E.; Chatterjee, D.; Gerlai, R. (2013). Subcutaneous dye injection for marking and identification of individual adult zebrafish (Danio rerio) in behavioral studies. Behavioral Research Methods, doi:10.3758/s13428-013-0399-x. - Gerlai, R. (2003). Zebra fish: an uncharted behavior genetic model. Behavior Genetics, 33(5), 461-468. --- ## Why rats help other rats URL: https://noldus.com/blog/why-rats-help-other-rats Published: 2014-02-27 14:04:00 Description: As humans, we help each other because it is the right thing to do. We help our friends and our family. And of course we help strangers as well. Right? As humans, we help each other because it is the right thing to do. We help our friends and our family. And of course we help strangers as well. Right? Most of us would do about anything to help those we love if they are in need, but how far would we go for a stranger? And would this change if we have met that person before? It all has to do with our empathetic abilities. The emotional status of someone in need 'transfers' to us, making us want to help him or her. How emphatic are rats? Our capacity to help strangers is often contributed to our highly developed cognitive abilities. Ben-Ami Bartal et al. wanted to find out if rats have this capacity as well. Previously, they found that albino rats of the Sprague-Dawley (SD) strain can learn to release a cage mate that was trapped in a restrainer. In a recent publication in eLife, they show how the familiarity of this trapped individual influenced the helping behavior of the free rat. Testing the importance of familiarity for helping behavior Inbal Ben-Ami Bartal and colleagues tested the effect of familiarity in different ways, applying different couplings between familiar and stranger rats from the same albino strain (SD) or from a different, hooded rat strain (Long-Evans). In the first part of the study, the albino pups were kept in their biological nest and after weaning were divided into groups, housing with cage mates from either the same albino strain or from the other hooded rat strain. In a second part, researchers also investigated the effects of genes by foster-raising some of the rats, meaning that some of the rats were not kept in the nest with their biological mother after birth, but put in a nest with hooded pups. Freeing a fellow rat To test the helping behavior of albino rats, they were placed in a cage in which another rat was already trapped in a restrainer cage. This trapped rat was either from the same albino strain or from the hooded strain and could be a familiar individual or a stranger to the free rat. The trial took one hour. The only way for the restrained rat to leave the restrainer was for the free rat to open it from the outside. If this did not happen within 40 minutes, the researcher opened it for them. After the door was opened, rats were left together for the remainder of the time to monitor their behavior after door opening. The researchers posted a video of these tests at elifesciences.org Rats help rats they recognize In short: it turns out that helping behavior (and other pro-social behavior such as showing interest in and not fighting) in rats requires a certain degree of familiarity to the individual or to the strain. In other words, rats helped individuals they had previous social interaction with in the nest or after weaning. They also helped strangers if they had previous interaction with a member from the same strain as that stranger was from. Nurture over nature Also, this study showed that nurture trumped nature in this case: albino rats fostered and raised with hooded rats will not help a fellow albino rat out if it has never met another albino before, even though they are biologically from the same strain. It will help hooded rats, whether they know the individual or not. Thus in this study, social exposure to the strain proved to be a crucial factor in the helping behavior from one rat to another. Read more Find out more about video analysis in social interaction tests at www.noldus.com/ethovision. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Read the article from Ben-Ami Bartal et al.: Ben-Ami Bartal, I.; Rodgerts, D.A.; Sol Bernadez Sarria, M.; Decety, J.; Mason, P. (2014). Pro-social behavior in rats is modulated by social experience. eLife, e01385. --- ## How to easily automate the elevated plus maze test URL: https://noldus.com/blog/how-to-automate-the-elevated-plus-maze-test Published: 2014-02-20 13:26:00 Description: Anxiety. It is nature’s way to keep us out of harm’s way, so it is a useful emotion. At times, though, it can also be overwhelming. For some, it gets out of control, irrational, and even disabling. Anxiety. It is nature's way to keep us out of harm's way, so it is a useful emotion. At times, though, it can also be overwhelming. For some, it gets out of control, irrational, and even disabling. This is when we call it an anxiety disorder. Did you know that anxiety affects 20% of all people in some way or form? No wonder anxiety disorders are often subject of scientific study. Anxiety in animals Rats and mice are often used as model organism to study the basics of anxiety and anxiety disorders, possible treatments, neurodevelopment, and genetic backgrounds. The most well-known test paradigm is the elevated plus maze. The elevated plus maze This maze is just what its name suggests it to be: a maze shaped like a +, elevated from the floor. Two opposite arms are sheltered with walls and the remaining two arms are open. How the animals explores this maze says something about its level of anxiety. Rats and mice have a natural tendency to explore, but this can be inhibited by their innate fear for open spaces and height and their preference to stay in dark, enclosed environments. Variables in scientific research Targeted parameters in such an elevated plus maze test include the time spent and distance moved in the center square, open arms, and closed arms, the latency to enter the open arm for the first time, and the amount of rearing and head dipping behaviors. Automating research You cannot easily measure all of these parameters by hand. A stopwatch and a pair of eyes go a long way, but eventually it is way more efficient and objective to automate this test. This is exactly what many researchers do. Video image analysis Video tracking software is an efficient way for many researchers to execute a series of plus maze tests. How this works? A camera is mounted above the maze so that it can accurately spot the animal's location. The image is analyzed by EthoVision XT video tracking software. It locates the animal, its nose point, center point, and tail base, and follows these points as the animal moves through the arena. Then these data (coordinates) are processed to calculate a range of variables, including those mentioned above. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Multiple body points It is important to track not only the center point, but also the nose point and tail base of the animal. This way, the difference between the animal sticking its nose around the corner and completely entering the open arm can be distinguished. Read more More information about the elevated plus maze can be found here, and if you want to know all about video tracking software, see this webpage. --- ## How memory loss caused by diabetes was prevented in transgenic mice URL: https://noldus.com/blog/memory-loss-prevented-transgenic-mice Published: 2014-02-13 14:29:00 Description: Did you know that Alzheimer’s and diabetes are linked? Patients with diabetes have an increased risk for Alzheimer’s disease (AD) and patients with AD show impaired insulin function and glucose metabolism. Did you know that Alzheimer's and diabetes are linked? Patients with diabetes have an increased risk for Alzheimer's disease (AD) and patients with AD show impaired insulin function and glucose metabolism. The tau protein might be one of the connecting factors. This protein, found in neurons, can get hyperphosphorylated, causing it to tangle and 'clog up' the neuron - one of the pathological hallmarks of AD. Investigating tau as the possible link between AD and diabetes Serena Abbondante and her colleagues (The American Journal of Pathology, 2014) investigated the protein tau as a possible link between the two diseases, because according to them, recent evidence from animal models of diabetes shows that impaired insulin signaling causes tau hyperphosphorylation. Tau-knockout and diabetic mice In order to investigate this relationship, they tested both non-transgenic (Ntg) mice as well as a knock-out strain for tau (tau-KO). From both groups a selection of mice were treated with streptozotocin (STZ), a chemical that causes a type 1 diabetes-like disease in mice. This resulted in four testing groups: - Ntg - Ntg STZ - tau-KO - tau-KO-STZ All four groups were tested for hippocampal dependent cognitive impairments in the Morris water maze test. Morris water maze testing In the water maze, the platform was located at a fixed position. Mice were tested in four trials a day, placing them at a different starting location each time around, and were trained for as many days as it took for them to reach to platform within 25 seconds. Every time it took them longer than one minute to find the platform, they were guided to it and left there for 5 seconds. After the last training session a 60-second probe-trial was performed. This data was gathered and analyzed with EthoVision XT. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Diabetes impairs learning only in non-transgenic mice The Ntg STZ mice showed impaired learning in the water maze compared to the untreated Ntg mice. Within the tau-KO group the treatment with STZ did not have this effect. Interestingly, the Ntg mice performed better than both tau-KO groups, (completing the training in 3 versus 4 days), while Ntg STZ mice did not reach the training criterion after five days. This indicates that the removal of tau mitigates the negative effects of STZ on learning in mice. Can we live without tau? Looking at the results of this study, one might conclude that getting rid of the tau protein prevents the negative effects that diabetes can have on memory, however, it is not that simple. Tau has a function in the human body, serving as a binding factor between microtubules, providing structure and flexibility in the axons of the neuron. Interestingly though, the tau-knockout mice in this study did not show behavioral or synaptic disabilities… At the very least, this study indicates that tau is an important key in the interaction between Alzheimer's and diabetes, making it an interesting target for new patient treatments. Further reading Learn more about this study: - Abbondante, S.; Baglietto-Vargas, D.; Rodriguez-Ortiz, C.J.; Estrada-Hernandez, T.; Medeiros, R.; LaFerla, F.M. (2014). Genetic ablation of tau mitigates cognitive impairment induced by type 1 diabetes. The American Journal of Pathology, 184, article in press, doi: 10.1016/j.ajpath.2013.11.021 - Learn more about EthoVision XT video tracking. - Learn more about Morris water maze testing with video analysis. --- ## Why guinea pigs are just like us URL: https://noldus.com/blog/why-guinea-pigs-are-just-like-us Published: 2014-02-08 13:50:00 Description: If zebrafish are the new mice, guinea pigs might be the new rats. Guinea pigs differ from mice and rats, and that just might make them more suitable due to the fact that these results are more easily translated to humans. If zebrafish are the new mice, guinea pigs might be the new rats. According to Kiera-Nicole Lee and her colleagues, guinea pigs differ from mice and rats, and that just might make them more suitable for some neuroscience research due to the fact that these results are more easily translated to humans. Guinea pigs are different than rats and mice Lee predicts that "guinea pigs may offer subtle behavior repertoires that better mimic human activity". They are already favored in ontological research as their ears are similar to ours, and they are widely used in immunology. And while rats and mice are born with relatively underdeveloped eyes and brain, guinea pigs, like humans, are more advanced at birth. Activity data and consequences of methamphetamine In their recent publication in Synapse researchers set out to provide baseline data on activity and how this was influenced by dopaminergic drugs as well as methamphetamine, as they expected guinea pigs to provide a robust small model to measure brain-behavior interactions that are relevant to human behavior. All of their activity tests were performed in a home cage setting using PhenoTyper. Baseline activity Over 30 male guinea pigs were divided over six treatment groups. All of them were first habituated and then observed for a day in the home cage. The day after, the six groups received their treatment, followed by another day of observation in the home cage to determine the effects on baseline activity. Treatment groups The first group served as a control and received a saline injection. The second, third, and fourth groups received a dopamine receptor 1 agonist, a dopamine receptor 1 antagonist, and a dopamine receptor 2 antagonist, respectively. The fifth and sixth groups received a low and high dose of methamphetamine, respectively. Before and after acute administration of each treatment, animals were continuously monitored for a little less than a day. Additionally, the effects of chronic exposure to methamphetamine were measured, and so the saline (control) group and the two groups receiving methamphetamine were injected daily for 7 days. After that an additional day of observation in the PhenoTyper took place. Data Lee and her colleagues were interested in both occupancy profiles and locomotor activity. To determine occupancy, the home cage was digitally divided into 3 areas of interest (zones): the hidden zone, which is the shelter, the food/water zone, and the rest of the arena. Variables measured with EthoVision XT video tracking included: total distance traveled, duration of space occupancy, and peak periods of movement. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial No nocturnal rhythmicity All guinea pigs spent most of their time in their 'safe place'; the shelter. The second most visited area was the food/water zone. In addition, they spent more time in the shelter during daylight than during the nighttime. Guinea pigs also showed thigmotaxis: the majority of their locomotion took place in the periphery of the arena. Although the distance moved was greater during the dark phases, the guinea pigs did not show a nocturnal rhythm, different from rats and mice. Rather, their rhythm indicated to be more ultradian, showing activity throughout the complete 22-hour period in which they were observed. There was also no evidence of prolonged sleep states. Less time in the shelter The only treatment that caused the animals to spend less time in the shelter was the acute administration of the dopamine receptor 1 antagonist. This can indicate a decrease in anxiety levels, but might also be a sign of altered motivation. Effects of methamphetamine on locomotion The differences between low and high doses of methamphetamine were diverse. An acute low dose of methamphetamine caused significant changes in activity; guinea pigs initially showed hyperactivity and a higher peak activity, but locomotor declined after that. As a consequence, total distance moved over the total 22-hour observation period did not differ significantly from baseline levels before treatment. Interestingly, chronic treatment with low doses of methamphetamine no longer produced the hyperactivity. Only the higher dose of methamphetamine caused a higher distance moved over the complete observation period. This hyperactivity was even greater after chronic exposure. Effects of methamphetamine on occupancy Acute versus chronic treatment with low doses of methamphetamine has a significantly different effect - the chronic administration caused animals to spend more time in the shelter compared to before the treatment, while the acute administration did not. This difference was not seen when comparing the acute and chronic administration of high doses of methamphetamine, but there were significant differences between the low and high chronic exposures to methamphetamine. Also, while chronic low doses caused a decrease in time spent in the food/water zone relative to before the treatment, chronic high doses did the opposite. This opposite effect between low and high doses was also seen in the time spent in the rest of the arena. These results show that the effects of methamphetamine are diverse and depend on both dose and repetition of administration. The authors suggest that this can be caused by the complicated and dose-dependent involvement of methamphetamine with various neurotransmitter systems. Guinea pigs vs rats and mice Besides the diverse effects of methamphetamine on the behavior of guinea pigs, this study also reveals some of the similarities and differences between animal species. These findings are of interest for further research that involves guinea pigs as test subjects instead of the traditional rats and mice. For one, guinea pigs, like rats and mice, show thigmotaxis. The authors suggest this makes them suitable for experiments such as fear-conditioning. On the other hand, their rhythmicity makes them stand out. They are neither nocturnal nor diurnal, eliminating the need for a reversed light-dark cycle. Their intermittent activity and sleep patterns might also make them interesting for research on brain processes and sleep. If you want to know more about this study, please take a look at: Lee, K.-N.; Pellom, S.T.; Oliver, E.; Chirwa, S. Characterization of the guinea pig animal model and subsequent comparison of the behavioral effects of selective dopaminergic drugs and methamphetamine. Synapse, accepted article, doi: 10.1002/syn.21731. For more information on home cage phenotyping: PhenoTyper For more information on video tracking: EthoVision XT --- ## Nurse-child interaction - observing medical encounters URL: https://noldus.com/blog/nurse-child-interaction Published: 2014-02-05 13:15:00 Description: In order to help health professionals and parents manage child distress more effectively, researchers started observations of real interactions in healthcare in a community setting. Does reassuring help a child to settle down and be comforted? In order to help health professionals and parents manage child distress more effectively, researchers started observations of interactions in healthcare. They were not observing simulated events, but real interactions in a community setting. In medical encounters, both the parents and the health professionals can play an important role in handling the stress level of children. Yuefang Zhou and Gerry Michael Humphris from the University of St Andrews, Scotland (2013) investigated the relationship between reassurance by dental staff and distress behavior of children receiving preventive procedures. Since this study concerned a preventive procedure where no pain was involved, this study aims to shed light on these specific interventions in healthcare. The researchers selected children aged 3 to 5 years and measured the level of anxiety to determine a base level. The knowledge gained from this study could be used to design more effective interventions for the improvement of child behavioral distress associated with mildly invasive clinical procedures. Observe behavior Using the specially developed St Andrews Behavioral Interaction Coding Scheme (SABICS) Zhou and Humphris coded nurse–child behaviors during a fluoride varnish application. All interactions were recorded on video to enable detailed coding. The Observer XT coding software enabled Zhou and Humphris to measure frequency and duration of nurse-child behavior. Moreover, they described that the precise time location of each behavior (i.e. time stamp) could easily be obtained. By connecting the time stamps, Zhou and Humphris were able to gather insight in behavioral relationships in the actual interactions. Behaviors The SABICS contains 48 behavioral codes relating to nurse and child behavior and six describe the fluoride varnish application protocol. The researchers describe that three behaviors were coded as reassurance: (1) describing the ease of the procedure (e.g., "It's easy-peasy."); (2) describing the pleasantness of the varnish (e.g., "It tastes like bananas."); and (3) providing overall reassurance (e.g., "Don't worry. It won't hurt."). Furthermore, the researchers also looked at nonverbal nurse behaviors such as touch reassurance. Child distress behavior was measured by coding nonverbal behaviors such as moves away or turns head and two verbal behaviors (crying/groaning, speech "no"). Timing of verbal reassurance After analyzing the videos, the researchers found that verbal reassurance significantly promoted child distress behavior. Moreover, they found that the time stamp of verbal reassurance had a significant negative effect on child behavioral distress. Timing is everything – it is not about increasing the frequency of verbal reassurance nor extending the duration of a reassuring comment, but about appropriate timing. Zhou and Humphris advised to employing verbal reassurance closer to the end of a procedure rather than at the beginning of a procedure. Furthermore, they advised to continuing with this kind of research in order to gain more insight in finer categories of reassurance and the child's response. For example, certain forms of reassurance (making a statement vs. a gentle request) could also possibly influence child distress behavior. To come back to the first question: Does reassuring help a child to settle and be comforted? According to Zhou and Humphris, it depends heavily on the timing of the act of reassuring. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - Zhou, Y.; Humphris, G.M. (2013). Reassurance and distress behavior in preschool children undergoing dental preventive care procedures in a community setting: a multilevel observational study. Annals of Behavioral Medicine, p 1-12. - Zhou Y, et al. Development of a novel coding scheme (SABICS) to record nurse–child interactive behaviours in a community dental preventive intervention. Patient Education and Counseling (2012), doi:10.1016/j.pec.2012.01.001 --- ## Doctor-patient communication training program evaluated URL: https://noldus.com/blog/doctor-patient-communication Published: 2014-01-22 14:59:00 Description: Every day, new training programs find their way to hospitals and clinics to help professionals convey their message efficiently and effectively in order to practice their profession. Colleagues from many different universities study communication in healthcare to empower themselves in this process. Every day, new training programs find their way to hospitals and clinics in order to help professionals. From medical encounters between patient and radiation oncologists to nurse-patient interaction between direct-care staff and Korean Americans in nursing or senior living homes, all of these professionals need to be able to convey their message efficiently and effectively in order to practice their profession. Recent project Special education courses are being developed for specific groups - for example, to empower general practitioners (GPs) in palliative care. Willemjan Slort and colleagues (2013) explain that little is known about communication in palliative care. In The Netherlands, an overall majority of patients visits a GP before going to the hospital. This way, a GP has a central role in medical care and also in palliative care. Communication training could help GPs in conversations with patients and their families when confronted with palliative care. But how effective are these training courses? Slort et al. evaluated a new training program: ACA training. This program focuses on Availability of the GP for the patient, Current issues the GP should discuss with the patient, and Anticipation by the GP of various scenarios. Record the interaction on video In the context of a communication training program, trainers often make use of simulated patients. This enables trainees to practice their communication skills without interfering with day to day consultations and medical encounters. Slort et al. recorded 15 minutes of the consultation GP- simulated palliative care patient on video. The researchers recorded how the GP communicated with the patient and the number of current and anticipated issues the GP discussed with the patient (what). To measure 'how' and 'what' the researchers made use of the Roter Interaction Analysis System (RIAS). Verbal utterances can be classified using this analysis system. RIAS, for example, describes task-oriented categories which refers to utterances that address a patient's physical or psychosocial problems. Coding using RIAS was carried out by trained coders using The Observer software. The video recordings in The Observer could be analyzed in great detail. It took the coders three to four times the duration of the consultation to code all behaviors. However, by using a video analysis tool, the coders could look at segments of the consultation multiple times ensuring reliable results. Download here the FREE white paper 'How to set up behavioral coding - 7 tips' Effectiveness training program not found Slort et al. found no effect of the ACA training program on how the GPs communicated with the patient. Moreover, they also found no effect on the number of issues discussed by GPs with the patient. Therefore, the researchers conclude that the ACA training program did not influence the behaviors they observed. As an idea for further research, Slort et al. suggest that research could focus on evaluating whether this training program is effective for GPs who do not have a special interest in palliative care and whether studies using outcomes at patient level can provide more insight into the effectiveness of the ACA program. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Reference Slort, W.; Blankenstein, A.H.; Schweitzer, B.P.M.; Knol, D.L.; Deliens, L.; Aaronson, N.K.; Horst, H.E. van der (2013). Effectiveness of the ACA (Availability, Current issues and Anticipation) training programme on GP-patient communication in palliative care; a controlled trial. BMC Family Practice, 14, 1-10. --- ## Autism Top 8 Blog Articles from the Behavioral Research Blog URL: https://noldus.com/blog/autism-8-blog-posts Published: 2014-01-14 11:37:00 Description: It was no surprise that these blog articles attracted lots of attention. Autism is the fastest-growing serious developmental disability in the U.S. (www.autismspeaks.org). Read the Autism Top 8 Blog Articles. It was no surprise that these blog articles attracted lots of attention. Autism is the fastest-growing serious developmental disability in the U.S. (Autism Speaks). Read the Autism Top 8 Blog Articles from the Behavioral Research Blog to stay updated on the latest developments in Autism Research. - 1.Behavioral observations in autism research – mothers of high-risk children use more gestures - 2.Video tracking of children with autism - 3.Parent-child interaction in autism: play behavior - 4.The search for autism models continues - why rats are important - 5.Can a food preservative increase symptoms of autism? - 6.Vocalizations as an early life behavioral marker for ASD - 7.How research on Autism Spectrum Disorders is developing - 8.Robot-child interactions – helping children with autism learn skills Free white paper on Autism Research Feel free to download the free white paper on Autism Research to learn more about observational research methods in autism studies. In this free white paper we will describe how and why observational research methods and tools are used in autism research worldwide. You can read more about three recent studies in which The Observer XT and Theme software were used to automate behavioral coding and to analyze patterns in behavior. --- ## How Automatic Rat Behavior Recognition was developed URL: https://noldus.com/blog/automatic-rat-behavior-recognition Published: 2013-12-12 13:28:00 Description: If you are familiar with neurobehavioral research in any way, you will know that variables like velocity and distance moved are important parameters in a lot of animal behavioral experiments. If you are familiar with neurobehavioral research in any way, you will know that variables like velocity and distance moved are important parameters in a lot of animal behavioral experiments. While these are difficult to measure with the naked eye, video tracking software does an excellent job of doing this automatically. How Automatic Rat Behavior Recognition was developed More specific behaviors, such as rearing and grooming, are also important in these experiments. They are traditionally assessed by the trained eye, but manual scoring is time consuming and expensive. Automation of this process would bring several advantages, but it seemed difficult to develop the software for it. Until now, as EthoVision XT 10 has a new software module for automatic Rat Behavior Recognition. I talked to one of the developers of this software, Elsbeth van Dam (MA), about the process it took to get to this exciting new technology. Why use automatic behavior recognition? While variables such as velocity are hard to measure without software, specific behaviors, like rearing, are relatively easy to recognize, at least by the trained human eye. So why would we need software to do that job for us? Van Dam explains, "Subjectivity is inherent to human observation, and so is loss of concentration during long observations. Automating behavior recognition makes it possible to perform long-term experiments and get reliable results. In turn, long-term observations make monitoring of natural behaviors, for example in home cage environments, more feasible. It also allows for a higher throughput." The creation of Behavior Recognition software So there are plenty of reasons for the development of this software, but it was not done overnight. At Noldus it all started with the Eureka research project, back in 1993, which was followed by more projects. Van Dam herself got involved in 2007, and started out with a lot of literature research. "The first attempts at automatic behavior recognition lead to the conclusion that the methods described in literature were not suitable. So, together with PR Sys Design, we designed a new technique. Next, we learned that we needed a lot more data", she says. So that is what they did – gather more data with partner Janssen R&D. In 2010 the first Research Edition of the automatic behavior recognition software was prepared for beta testing. Together with Delta Phenomics and Biometris (Wageningen University and Research Centre) the outcome was validated and the validation study was published in the Journal of Neuroscience Methods this year. Finally, the recent integration with the EthoVision XT package made this software available for everyone. Challenges I asked Van Dam what the biggest challenge in this project was for her. She told me, "The literature gave me many valuable ideas about behavior recognition, mostly of humans. But the biggest problem is that these ideas were not generic, not robust, and not fast. Because nothing I could find in the literature would work for rodents in infrared lighting, I had to find new characteristics that would work for behavior recognition. This was the big question: why does it seem so easy for humans to recognize these behaviors, but is it so difficult to recognize them automatically? I also found that many human observers think that that behaviors are clearly defined and they can distinguish them easily, but that there are a lot differences in interpretation of the behaviors amongst observers. Or even between observations repeated by the same observer." What lies ahead Right now the Rat Behavior Recognition software is a new module for EthoVision XT 10. As the name says, it is suitable for rats. In the near future Van Dam hopes to be able to adapt this software for mice as well. She is also working on adding more behaviors, specifically social behaviors. Right now rat behaviors recognized include: eating, drinking, walking, resting, jumping, twitching, grooming, sniffing, rearing supported, and rearing unsupported. She emphasizes that custom software is already possible. "If someone wants to be able to automatically recognize another behavior, one that is not in the list of ten behaviors already included, then we can customize the software for this customer. It is going to be exciting to see which other behaviors we can recognize!" FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Read more The validation study mentioned in this blog post is: Dam, E. van; Harst, J.E. van der; Braak, C.J.F. ter; Tegelenbosch, R.A.J.; Spruijt, B.M.; Noldus, L.P.J.J. (2013). An automated system for the recognition of various specific rat behaviours. Journal of Neuroscience Methods, 218 (2), 214-224. Rat Behavior Recognition is now available as a software module for EthoVision XT video tracking software. --- ## Measuring behavioral effects of laboratory rearing on starlings URL: https://noldus.com/blog/behavioral-effects-laboratory-rearing Published: 2013-12-10 14:02:00 Description: Rearing animals specifically for behavioral research is a very common practice. However, the results from behavioral studies with laboratory animals should be interpreted with care. Laboratory animals and behavioral research Rearing animals specifically for behavioral research is a very common practice. However, the results from behavioral studies with laboratory animals should be interpreted with care. There is much evidence indicating that the behavior of laboratory animals differs from that of animals caught in the wild. Laboratory animals are likely to be tamer than wild animals, but they can also be impaired in some behaviors. Some mammals have impairments in learning and memory when reared in a laboratory. They can also develop abnormal behaviors, called stereotypies, such as route-tracing. Similar effects of rearing in laboratories can be found in some bird species. Does laboratory rearing affect starlings? Gesa Feenders and Melissa Bateson compared the behavior of wild-caught starlings with the behavior of starlings that were taken from nest boxes when they were approximately 10 days old and hand-reared. They hypothesized that the hand-reared birds would have less cognitive abilities than the wild-caught birds and would be more likely to develop the stereotypies of route-tracing and somersaulting. The researchers carried out a large number of different learning tests with both groups of birds. Automating learning experiments In the learning experiments, pecking an area that was indicated with a light cue was rewarded with food. The authors investigated the time the birds needed to learn to peck the light cue, the response to a novel color of the light cue, and the time until the animals changed their preference to the new cue. In addition, they studied the extinction of pecking when they stopped giving a food reward to the birds. The authors used EthoVision XT video tracking software to automate the learning experiments. To determine stereotypies, they used Theme, a program to analyze sequences of behaviors. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Hand-reared birds learn faster The authors found no evidence at all that the hand-reared birds had less cognitive abilities than the wild-caught birds. On the contrary, the hand-reared birds learned to respond to the light cue faster than the wild-caught birds and also switched their preference to a novel cue faster. Also contrary to the hypothesis, only some wild-caught birds developed stereotypies. The results show that there are behavioral differences between the two groups, but these are completely opposite to the hypothesis that hand-rearing leads to behavioral deficits. Are hand-reared birds less stressed? It is possible that the hand-reared birds have better cognitive abilities than wild-caught ones. However, it is more likely that these starlings are less stressed by a novel stimulus. The authors performed additional experiments to investigate this and the results support this hypothesis (see [1]). The authors conclude that hand-reared birds experience less stress and therefore learn to peck the initial light cue and respond to a novel light cue faster. Also the fact that stereotypies only developed in wild-caught birds indicates that the hand-reared birds are less stressed. The authors conclude that hand-reared birds can be used in behavioral studies, since they found no evidence that laboratory rearing leads to behavioral impairments. However both groups of bird do differ in some behaviors, which makes further research necessary before this conclusion can be generalized. Reference Feenders, G.; Bateson, M. (2013). Hand rearing affects emotional responses but not basic cognitive performance in European starlings. Animal Behaviour, http://dx.doi.org/10.1016/j.anbehav.2013.05.002 --- ## Top 5 novel object recognition articles URL: https://noldus.com/blog/top-5-novel-object-recognition-articles Published: 2013-11-26 14:08:00 Description: Novel object recognition is one of the most commonly used behavioral tests on laboratory rodents. It is also easily automated with video tracking software. Want to know how? Novel object recognition is one of the most commonly used behavioral tests on laboratory rodents. It is also easily automated with video tracking software. Want to know how? I've lined up five of the most popular blog posts about this test from our Behavioral Research Blog. Here you go! 1) Cognitive ability of schizophrenic mice Cognitive ability is one of the major functions affected by schizophrenia. So logically, research on this disease and possible therapies often involves object recognition. Glass et al. (2013) investigated the involvement of the NR1 gene in schizophrenia. During a training session, mice were confronted with two identical objects to familiarize. In the first testing round, one object was replaced by a novel one. In a second test, another novel object replaced the second familiar one. EthoVision XT video tracking was used to automatically calculate variables such as duration, latency, and frequency of contact with the object. Read the blog post: Using several behavioral tests to investigate the role of the nr. 1 gene in Schizophrenia 2) Alzheimer mice show no interest in novel objects Webster et al. (2013) showed that a mice model for Alzheimer's failed to show interest in novel objects in the novel recognition test, and that this effect depended on the age of the mice. They used EthoVision XT to analyze the distance moved, velocity, time spent in different zones, and the time the nose of the mice was in proximity of the objects. Read the blog post at Mice with Alzheimer's disease walk well but remember poorly FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial 3) Cognitive impairments due to brain cancer therapy Whole brain radiation therapy is sometimes the only viable treatment for patients with brain cancer. It is effective for many patients, but inevitable brain damage often leads to cognitive impairments. The study of Belarbi et al. (2012) is an example of the research that is done to better understand the mechanisms behind the cognitive impairments. This, in turn, can lead to better therapies and an improved quality of life for the patients. This study focused on inflammation as a major contributor to the impairments, and used the novel object recognition test as one of the tests to place a link between behavior and what goes on at molecular level. Read more about it in Video tracking connects some dots between cognitive impairment and cranial radiation 4) Food preservatives and autism Autism can cause repetitive behavior and restricted interests. In the research of MacFabe et al. (2011), the effect of PPA (food additive) on rat models of autism is tested with the use of a three-piece novel object recognition test. The results indeed point towards a declined interest of the treated rats, while locomotion was not changed, indicating that a general change in activity did not cause this difference. Read all about it at Can a food preservative increase symptoms of autism? 5) Tips for novel object recognition with automatic video tracking Finally, this post features a number of great publications and some tips on how automatic video tracking can really benefit novel object recognition testing. As a bonus, it also has a link to a free white paper! Check it out at How to get reliable results on object recognition using automated video tracking --- ## Facial expressions - reactions to bitter food vary between high and low BMI URL: https://noldus.com/blog/facial-expressions-reactions-to-bitter-food Published: 2013-11-20 15:35:00 Description: Overweight and obese individuals are at increased risk for many diseases and health conditions. By 2050, as much as 50% of the UK population could be obese at a cost of £50 billion a year. Overweight and obese individuals are at increased risk for many diseases and health conditions. By 2050, as much as 50% of the UK population could be obese at a cost of £50 billion a year, warns the National Obesity Awareness Week. To create awareness, they have organized a National Awareness Week from 13 to 19 January 2014. Their goal is twofold:  putting the obesity crisis at the top of the agenda and teaching people how they can begin to tackle the problem. In many recent research projects, the overweight and obese are the subjects under investigation. "Why do people who are overweight or are at risk of becoming overweight eat differently from thinner people?" is the question David Garcia-Burgos and Maria Clara Zamora asked. Basing their study on recent hedonic eating theories of obesity, they hypothesized that overweight individuals would be more reactive to unpleasant tasting food than lean people. Is there a link between obesity and a dislike of bitter-tasting food? Garcia-Burgos and Zamora observed participants with a high body mass index (BMI) and compared this group to a group of participants with a low BMI. They recorded videos to capture the reactions to bitter-tasting food stimuli in order to see if the reactions differed. Participants were asked to drink both a chocolate drink and grape juice. The research presented by Garcia-Burgos and Zamora is the first to examine how affective facial reactions to bitter food, apart from taste responsiveness, can predict differences in BMI. Facial expressions test unravels real feelings In order to provide more direct access to affective systems than subjective reports, the researchers decided to include facial expression analysis. Facial expressions were automatically measured using FaceReader software. The researchers set up the experiment with a camera directly in front of the participants, "located in a hole of the booth wall, directly above the computer screen and in front of the subject at a distance of 1.5 m." Since illumination of the face helps to optimize the results when working with facial expression analysis software, they placed daylight lamps in the lab, in addition to the ceiling lights. Using FaceReader, Garcia-Burgos and Zamora were able to automatically scale the facial expressions from 0 (not present at all) to 1 (maximum intensity of the fitted model). FaceReader reads seven facial reaction patterns or expressions (happy, sad, angry, surprised, scared, disgusted, and neutral). The researchers indicate in their paper that FaceReader technology was a sufficiently suitable and accurate method, in their case, for differentiating between the two bitter foods: stimulus perceived as more bitter was more strongly disliked (on the basis of the intensity of the elicited disgust and angry expressions) in both BMI groups. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download Results After analyzing both groups, the researchers concluded that participants with high BMI reacted to bitter stimuli while showing more profound changes from baseline in neutral and disgust facial expressions. This difference shows that it is worth investigating more so we are able to identify factors that contribute to weight gain or avoidance behavior such as avoiding health-promoting food. Reference Garcia-Burgos, D.; Zamora, M.C. (2013) Facial affective reactions to bitter-tasting foods and body mass index in adults. Appetite, 71 (1), 178-186. --- ## Measuring the creative process URL: https://noldus.com/blog/measuring-the-creative-process Published: 2013-11-18 14:00:00 Description: How can you come to better understand what is going on in the creative process? A living lab studying the work of a writer, painter, musician or other creative person might provide the answer. After Albert Einstein died, his brain was preserved and in the following decades scientists have studied it to try and see if there was anything exceptional about it. It is hard to draw conclusions from just one subject, but one clear difference is that he had an exceptionally large number of glial cells in the area of the brain responsible for incorporating and synthesizing information from other brain regions [1]. Glial cells are important for a number of brain functions, including signal transmission. Really understand creativity It is all very well to see something in brain anatomy, but if you really want to understand creativity then you need to study the process as it takes place in a live subject. That is easier said than done. Brain imaging techniques can be used to see what parts of the brain are active when a person is presented with various stimuli, or when they are asked to think about certain things. Brain imaging is used in a variety of contexts, including clinical studies and neuromarketing. However, those sort of techniques give limited insight into what the creative processes actually are. The results are difficult to interpret because trying to be creative whilst sitting still in a metal cylinder (the imaging device) is just not the same as the normal process in the artist's studio or at the writer's desk. Living lab The way forward is to measure as much as possible, whilst influencing the creative process as little as possible. This sort of setup is often called a living lab. Living labs are increasingly being used to study all sorts of behaviors in their natural environment, from a consumer trying to use the latest TV or smartphone, to a diner in a restaurant making a choice from the menu. Perhaps surprisingly, there have been relatively few studies carried out using living labs to study creative processes. This might be because such processes tend to be subtle and probably vary a lot between different individuals, but maybe also because of the classic division between the sciences and the arts. FREE BUYER'S GUIDE Buyer's guide to the perfect audiovisual lab Everything you need to know about setting up the perfect audiovisual lab for your research. - What is an audiovisual lab? - What do you need to complete your setup? - How does an audiovisual lab help you answer your research questions? Get your copy Dutch writer Arnon Grunberg A team of scientists is now setting up an experiment to try and remedy this situation. The study of well-known Dutch author Arnon Grunberg has been turned into a living lab, and as he writes his next book, what he is thinking, feeling and doing is being recorded and analyzed. Are you interested to read more details about this experiment? Read more about measuring creativity at the GrunbergLab. References Fields, R. Douglas (2009). The Other Brain: From Dementia to Schizophrenia. New York: Simon & Schuster. p. 7. ISBN 978-0-7432-9141-5 --- ## Behavior predicts success of family-based treatment in anorexia URL: https://noldus.com/blog/family-based-treatment-in-anorexia Published: 2013-11-13 10:09:00 Description: Anorexia nervosa is a horrible eating disorder that affects many people around the world. Looking at the United States only, between 0.5–1% of all women suffer from anorexia. Anorexia nervosa is a horrible eating disorder that affects many people around the world. Looking at the United States only, between 0.5–1% of all women suffer from anorexia. Moreover, anorexia is one of the most common psychiatric diagnoses in young women [1]. No matter how hard governments and parents try to influence adolescents, there are still those who are unable to be reached. Among other factors, anorexia is characterized by [2]: - A relentless pursuit of thinness and unwillingness to maintain a normal or healthy weight - Intense fear of gaining weight - Distorted body image There are a number of treatment options for those girls (and boys of course) already diagnosed with anorexia. Different forms of psychotherapy (including individual, group, and family-based) can help address the psychological causes for the illness [2]. The study Recently, Alison Darcy and colleagues [3] from the Stanford University School of Medicine and The University of Chicago presented their study in Behaviour Research and Therapy. They examined family-based treatment (FBT): Do behaviors shown in the first sessions of family-based treatment predict early response to treatment? In this case, early response means weight gain of 1.8 kg by session four. The authors chose to focus on behaviors that differed between early responders and non-early responders because, as is the case with many disorders, among the strongest predictors of positive long-term outcome in FBT is early response to treatment. Adolescent behavior Anorexia nervosa typically appears in early to mid-adolescence [1]. Darcy et al. selected 21 adolescent participants to take part in this exploratory study. The first, second, and fourth sessions of the family-based treatment were recorded on video and behaviors were coded afterwards using The Observer XT coding and analysis software. To prevent drift, Darcy et al. explain that all coders were trained and met regularly to find agreement on the operationalization of codes. By analyzing the frequencies and durations of behaviors related to meal sessions and verbal behavior, the researchers found that adolescents showing fewer negative verbal behaviors in the first session and who were away from the table less during the meal session had the greatest rates of early response. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Parent behavior "Family-based treatment aims to empower parents to assume responsibility for re-nourishing their child back to health," the researchers state. So what can parents do and how is their behavior an indicator for success in family-based treatment? Parents can drive their child into a defensive position. How? Darcy and colleagues' study shows that parents who put the pressure on during meal time are more often found in the group where the family-based treatment doesn't show an early response. "Parents who made fewer critical statements and who did not repeatedly present food during the meal session had children who had the greatest rates of early response," the researchers conclude. It is bigger than you When a parent can refrain from making critical comments all the time, the child will probably feel more at ease and benefit more from the family-based treatment. Of course there are many more factors to take into account, such as how long the eating disorder has already been going on. However, it is all about the individual and his or her surroundings. If you change and your environment stays the same, it is hard to keep up the good behavior. The study by Darcy and colleagues shows that it is as important to observe parent behavior as it is to observe adolescent behavior. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - www.nationaleatingdisorders.org/anorexia-nervosa or https://dopasolution.com/anorexia-nervosa/ - www.nimh.nih.gov/health/publications/eating-disorders/index.shtml - Darcy, A.M.; Bryson, S.W.; Agras, W.S.; Fitzpatrick, K.K.; Le Grange, D.; Lock, J. (2013). Do in-vivo behaviors predict early response in family-based treatment for anorexia nervosa? Behaviour Research and Therapy, 51, 762-766. --- ## Primate behavior - cracking the nut, fur rubbing & mating behavior URL: https://noldus.com/blog/primate-behavior-mating Published: 2013-10-23 15:15:00 Description: Interested in primatology? Today we present to you three blog posts and a couple of interesting websites! Interested in primatology? Today we present to you three blog posts and a couple of interesting websites! 3 blog articles about primate behavior - Observing monkey behavior – cracking the nut We already know some monkeys display above average intelligence. One way by which we can tell is their use of tools. Behavioral studies have shown that capuchin monkeys use boulders and logs as anvils upon which they can crush nuts. Furthermore, these monkeys have demonstrated that they are able to identify hammer stones best for cracking, and nuts that are easy to crack. Fragaszy et al. decided to add to this knowledge-base with their behavioral study, which was published as Wild Bearded Capuchin Monkeys (Sapajus libidinosus) Strategically Place Nuts in a Stable Position during Nut-Cracking. This publication in PLOS ONE elaborates upon the detailed study of monkey behavior, specifically the placement of nuts prior to striking them. An interesting detail: they studied this same behavior in humans as well. Learn more – read the blog post here. - Unraveling primate behavior, why do monkeys rub their fur? In animal behavior research, it is widely believed that fur rubbing is used in social bonding. However, for tufted capuchin monkeys, this is not true (Paukner, Suomi, 2008). Animals that rub their fur encounter more aggression and have less friendly behavior. They have less grooming behavior and play less than animals that do not rub their fur. This of course puzzles the scientists that study primate behavior. Do the monkeys perhaps fight for fur rubbing material? Or does fur rubbing make them smell so bad that their group members become aggressive? In an interesting study, Annika Paukner and Stephan Suomi (2012) investigate the cause of the aggression after fur rubbing. The authors look how much time the animals spend in proximity with other monkeys and whether the monkeys initiate or receive aggression, and initiate or receive friendly behavior. Read this blog post to learn more about the cause of the aggression. - Secret sex and promiscuity - Mating behavior of Rhesus monkeys In Rhesus monkeys the optimal sexual strategy is different for Alpha males, other males and females. Alpha males want females to mate exclusively with them, whereas other males and females benefit from promiscuity. With secret sex, females and bystander males counteract the strategies of alpha males to dominate the group. In a recent article in the American Journal of Primatology, Anne Overduin-de Vries and colleagues hypothesize that females and bystander males (Rhesus Macaques) copulate secretly out of sight of the alpha male. They investigated whether mating between females and bystander males occurs more often in absence than in presence of the alpha male. In addition to this, they looked whether the male's rank is of importance for the effect of their presence on mating behavior of females with other males. Sneaky monkeys….read more! 3 websites on Primatology Check out these websites with the latest developments in Primatology. - Primatology.net - American Society of Primatologists - International Primatological Society FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial --- ## Making the impossible possible – Tracking under water in the dark URL: https://noldus.com/blog/tracking-glass-eels Published: 2013-10-21 09:44:00 Description: European eels (Anguilla anguilla) have a life cycle in which both larvae and adults travel incredible distances. The eggs hatch in the Sargasso Sea near North America and the larvae swim all the way to Europe. European eels (Anguilla anguilla) have a life cycle in which both larvae and adults travel incredible distances. The eggs hatch in the Sargasso Sea near North America and the larvae swim all the way to Europe. Near the European estuaries (the coastal areas with brackish water) they transform into the so-called glass eels that are transparent and approximately 8 cm in size. These glass eels enter the estuaries and move upstream in the fresh water, overcoming all sorts of natural challenges and tackling many obstacles to reach the waters where they will grow up. Then after 5 to 20 years, they mature and make the entire difficult journey back to the Sargasso Sea to spawn and die [1,2]. Dramatic population drop The number of eels that reaches the European estuaries yearly has dropped dramatically during the last decades, with a drop of at least 90% [2]. Most likely this is caused by overfishing, pollution, parasites, and changes in the ocean currents. However, an increased occurrence of obstacles in the estuaries and rivers, such as hydroelectric plants, may be also responsible for the decline. Eels are a popular delicacy and their dramatic population decline has alarmed researchers. This has led to an increased research interest in the migratory behavior of glass eels. Severe tracking challenges Delcourt et al. [3] studied the migratory behavior of glass eels in a laboratory situation. Because glass eels show shoaling behavior, they wanted to investigate the swimming behavior of multiple glass eels simultaneously with video tracking. However, because glass eels travel at night also, the authors had to do part of the tracking in the dark. With the realization that the glass eels are transparent and swim under water, it becomes clear that tracking these animals is a severe challenge. Tracking more than one animal simultaneously is even more difficult. Fluorescent color markers The authors used Visible Implant Elastomer Tags (VIE-tags) [4] which were originally developed for capture-recapture studies on swimming animals. These tags are available in six colors that show up under UV light. Four of these tags (red, blue, orange and green) were used as distinct color markers for tracking fish in EthoVision. The pink tag was too similar to the red one under UV light and the yellow resembled green. The authors could successfully track four individual glass eels with these VIE-tags in a shoal of 50 conspecifics. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Beating the challenge The authors showed that many glass eels swim alternatingly with and against the current, following the tidal rhythm. This way they can swim up to 21 km in 8 days in a laboratory setting, which is comparable to what is found in estuaries. The authors hypothesize that tracking more animals simultaneously should be possible if VIE tags become available in additional colors. Furthermore, they give the suggestion to make color tracking with a combination of color markers on one individual possible, or to identify the animal by the intensity of the color marker. With the current method the authors already have beaten the challenge to track multiple animals under extremely difficult circumstances. References - http://en.wikipedia.org/wiki/Eel_life_history - http://en.wikipedia.org/wiki/European_eel - Delcourt, J.; Ylieff, M.; Bolliet, V.; Poncin, P.; Bardonnet, A. (2011). Video tracking in the extreme: A new possibility for tracking nocturnal underwater transparent animals with fluorescent elastomer tags. Behavior Research Methods, 43 (2), 590-600. - VIE tags, (Northwest Marine Technology Inc., Shaw Island, WA, USA), http://www.nmt.us/products/vie/vie.shtml --- ## Smelly feet and heat – how malaria mosquitoes find their hosts URL: https://noldus.com/blog/how-malaria-mosquitoes-find-their-hosts Published: 2013-10-13 11:27:00 Description: It seems that mosquitoes use human body odor to locate suitable hosts, and different people smell differently to mosquitoes. Why is it that if there is a mosquito in my bedroom, usually it won't bite me, but it does bite my partner? It seems that mosquitoes use human body odor to locate suitable hosts, and different people smell differently to mosquitoes. However, it is not only body odor, but also body heat, CO2 from breathing and wind direction may also be important for the mosquitoes to find you. Furthermore, different mosquito species use different cues. For many mosquito species it is still not known exactly what they do to find their hosts. Malaria mosquitoes It is no accident that many of the studies on host-seeking behavior have been carried out on malaria mosquitoes. Over a million people are killed by malaria every year. This makes research on how these mosquitoes find their hosts ever so important. If we know how they these insects find their hosts, we may be able to stop them. Tracking in 3D Spitzen et al. [1], studied the host-seeking behavior of the malaria mosquito Anopheles gambiae sensu stricto. They used a wind tunnel and applied several stimuli. They used the video tracking software EthoVision for automating behavioral observations. However, this software analyzes the insect behavior in a two dimensional plane, while the mosquitoes fly in a three-dimensional space. Therefore, the researchers joined together with Noldus (the company that makes EthoVision) to develop Track3D. Track3D is a plug-in for EthoVision, which made it possible to analyze of the flying path of the mosquitoes in three dimensions. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Smelly feet and heat Air was pumped in on one side of the wind tunnel and the mosquitoes were released on the other, downwind, side. Clean air was used as control. The treatments consisted of odor from a sock worn for 24 hours by the first author, a heat source at the air inlet, and a combination of heat and foot odor. Combining heat and odor The mosquitoes flew straight against the wind and landed on the wall on the other side of the wind tunnel when only clean air was applied. Only a few mosquitoes landed in a 5 cm circle around the air inlet. The presence of a heat source near the air inlet did not affect the flying path, but more mosquitoes landed near the inlet. When the air contained foot odor, there was a large effect on the flying path. The mosquitoes flew in and out the odor plume at a right-angle to the wind direction. They took much longer to reach the other side of the wind tunnel. However, the number of landings near the air inlet was not affected. The mosquitoes also showed this zig-zag flying pattern when a combination of heat and foot odor was applied. However, in this case, a high percentage of the mosquitoes landed near the air inlet. Heat, odor and host location The results show that the mosquitoes use both odor and heat to find their host and that either of these two stimuli alone is not enough. In presence of foot odor and heat, the mosquitoes alter their flying path and fly in a zig-zag pattern to the odor source. This indicates that they make use of gradients in heat and odor concentration and scan the odor plume intensely to fly to its source. With this knowledge, methods to control malaria mosquitoes can be improved, for example by adding a heat source to an odor baited trap. Wider use Although Track3D was developed for studying mosquitoes, it has since been used for all sorts of 3D animal tracking, 3D movement analysis and other studies of insect behavior. Reference Spitzen J, Spoor CW, Grieco F, ter Braak C, Beeuwkes J, et al. (2013) A 3D Analysis of Flight Behavior of Anopheles gambiae sensu stricto Malaria Mosquitoes in Response to Human Odor and Heat. PLoS ONE 8(5): e62995. doi:10.1371/journal.pone.0062995. --- ## Testing PCBs toxicity - behavior in zebrafish and their offspring URL: https://noldus.com/blog/testing-pcbs-toxicity-behavior-zebrafish Published: 2013-10-08 13:23:00 Description: PCBs are synthetic molecules that were used in transformers, electric motors, and more applications. It was quickly discovered that these molecules are toxic, and subsequently, they were banned. PCBs (polychlorinated biphenyls) are synthetic molecules that were used in transformers, electric motors, and more applications from the 1930s onwards. It was quickly discovered that these molecules are toxic, and subsequently, they were banned. Still, their heavy use then and their long half-life still cause PCB contamination today. As dietary intake is the main source of exposure, it often finds its way into our food chains trough fish. It has been linked to alterations in reproduction, the endocrine system, and organ functioning in both animals and humans. In addition, epidemiological studies have found a link between PCB exposure and ADHD. A new approach to toxicological studies of PCBs Many studies on the effects of PCBs have focused on short-term exposure to high doses. Péan et al. (2013) decided to take a more elaborate approach. They chronically exposed zebrafish to PCBs at levels that were similar to those found at contaminated sites, tested their behavior, and then tested the behavior of their offspring. Treatment groups In the first generation of fish (F0), four treatment groups were created. Two received food that was spiked with PCB either in medium or high doses and two groups served as controls and got food that was spiked with a solvent, or just plain food. After 250 days of contamination, the fish got tested. After 300 days, fish were mated to obtain offspring (F1) that were also tested. Because there were no differences found in the solvent and plain groups during F0 testing, only one control group (Solvent) was used for F1 testing. Contamination passed onto offspring PCBs were found to transfer to zebrafish eggs, so in fact treatment groups of both the F0 and F1 fish were contaminated. Both generations did not show difference in weight and length across the treatment groups that could have caused the behavioral differences found. T-maze experiment F0 fish were first tested in a T-maze. One of the goal arms was deeper and contained marbles, artificial grass, and a shelter. This was designated the more favorable environment. Velocity, mobility, latency to reach the deep arm, number of exits from the deep arm, and time spent in the deep arm were measured automatically with video tracking software EthoVision XT. Different doses of contamination had different effects: while the PCB-medium group swam faster, got to the favorable zone quicker, and settled there, the PCB-high group showed no such difference when compared to the control groups. The authors suggest that the medium dose might have cause the fish to overreact to the situation, while the higher dose had a completely different effect. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial 24 hour activity monitoring The second experiment done with F0 fish consisted of 24 hours of activity monitoring. The fish were divided over 12 tanks (3 fish per tank) on top of an infrared floor and distance traveled was tracked automatically for 24 hours. During the last lights-off period, differences in velocity were found: the PCB-medium had an intermediate increase in velocity and the PCB-high group had a high increase, compared to the controls. Only the PCB-high group differed significantly in activity between day and night, and had a higher activity at the end of the night. The authors speculate that this might be due to anticipation of the oncoming day or due to a modification in circadian rhythm that may only occur at high PCB doses. Light-dark challenge larvae Then the second generation (F1) larvae were presented with a light-dark challenge. Placed individually in cells of a 24 well plate, larvae were subjected to a 5 minutes lights on – 5 minutes lights off – 5 minutes lights on test which was video recorded with EthoVision XT. Distance travelled was measured. All larvae showed a similar activity pattern in reaction to the light changes: when the lights were switched off, activity increased, when the lights were turned on again, activity decreased to even lower levels than before. The activity of both contaminated groups was higher during lights off. In the second lights on phase only the PCB-medium were more active than the rest. 24 hour activity monitoring F1 At two months of age, F1 fish were tested in a 24h swimming activity test with a similar set-up to the 24h activity test for F0 fish. In one session, the camera was placed above the tank to monitor horizontal movements. In another, the camera was placed in front of the tanks to monitor vertical movements. Swimming path length, time spent in each third, and number of passages between sections were measured. Track extraction and analysis was done with EthoVision XT. Only vertical swimming activity revealed differences. All fish shifted their preference from the bottom and mid sections during the day to the upper section during the night. The PCB-high group showed a higher section transition activity than that of the solvent group, while the PCB-medium had intermediate transition activity. During the day, PCB-high fish showed the lowest level of bottom dwelling, which could be interpreted as less anxiety. General conclusions The two contaminated groups responded differently to the behavioral tests. The authors found evidence that the PCB-medium fish had behavioral changes related to the stimulus or environmental change while the behavioral changes of the PCB-high fish were rhythm disruptions. For the first time, effects were also tested in offspring. Larval activity seemed to be stimulated in the PCB-medium larvae, but suppressed in the PCB-high larvae. This effect was also seen in the parents during the T-maze test. In the 24 hour test of the offspring (F1), the positioning of the contaminated fish suggested a decrease of stress and or anxiety. But the decreased bottom section occupancy and increased transitions also might be due to weakened home-base behavior or loss of behavioral inhibition which could lead to increased predation risk. There were only minor changes in vertical positioning during the night suggesting that, contrary to F0 fish, nocturnal behavior was not markedly affected. In both generations and in all tests, contamination always seemed to result in some form of activity. This could be relevant to the established link between PCB and ADHD. Read more Read more about this research: Pean, S.; Daouk, T.; Vignet, C.; Lyphout, L.; Leguay, D.; Loizeau, V.; Bégout, M.-L.; Cousin, X. (2013). Long-term dietary-exposure to non-coplanar PCBs induces behavioral disruptions in adult zebrafish and their offspring. Neurotoxicology and Teratology, 39, 45-56. Find out more about tools for zebrafish larvae activity monitoring or zebrafish adult T-maze testing. --- ## Unraveling the chemistry of mood disorders URL: https://noldus.com/blog/unraveling-chemistry-mood-disorders Published: 2013-10-04 09:23:00 Description: The most common psychiatric disorders are mood and anxiety related. However, the underlying mechanisms of these diseases are still largely unknown. This complicates the development of effective treatment and drugs. The most common psychiatric disorders are mood and anxiety related. However, the underlying mechanisms of these diseases are still largely unknown. This complicates the development of effective treatment and drugs. There are a large number of standard behavioral tests for mouse or rat models of psychiatric disorders. Many of these tests have a very short duration, between 5 and 60 minutes. Handling the animals prior to the test and their response to the new environment can influence the test results. Standard behavioral tests for psychiatric mood disorders Long term observation with PhenoTyper Kas et al. [1] developed a method for testing avoidance behavior in mice over a longer time period in an environment that resembles their home cage. They determined motor and avoidance behavior of different mice strains during 72 hours. The authors used PhenoTyper, an observation cage for rats or mice which is completely optimized for video tracking. The cage contained two feeding areas, one with a shelter and one that was exposed. With EthoVision XT video tracking and analysis software they analyzed the preference for either shelter. This preference was used as a measure for the anxiety level of the different strains, because anxious mice tend to avoid open, exposed spaces. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Linking behavior to genes with PhenoTyper In the first 24 hours of the test, the mice had increased motor activity, indicating an effect of handling and novel environment. Avoidance behavior was determined during the second and third day of the test. Using many inbred mice strains, the authors could locate regions (QTL's) on two mice chromosomes that were linked with avoidance of the exposed shelter. These QTL's were found on chromosomes 15 [2] and 19 [3]. The avoidance behavior only occurred in female mice, indicating that the anxiety related behavior may be gender specific. Interestingly, the QTL's on both chromosomes were homologous with regions in the human genome that are linked with bipolar disorder. The importance of long term observations These results show the importance of long-term observations. Mouse chromosome 19, for example, has not often been linked with anxiety related behavior in previous research. This is possibly due to the fact that only female mice showed the avoidance behavior. But since standard tests have a short duration, the avoidance behavior may also have been confounded by the response of the animals to handling and the novel environment. The results described above would not have been found in a short term standard test, since the avoidance behavior was not found during the first day of the study and the mice had a higher motor activity during this day. PhenoTyper is designed for long term observations, which makes it suitable for research on behaviors that are difficult or impossible to assess with short term behavioral tests. PhenoTyper is a good device for studying mood disorders with mouse models. With these tests the underlying molecular mechanisms of mood disorders could be unraveled, helping to develop effective treatment for these disorders. References - Kas, M. J., de Mooij-van Malsen, A. J., Olivier, B., Spruijt, B. M., & van Ree, J. M. (2008). Differential genetic regulation of motor activity and anxiety-related behaviors in mice using an automated home cage task. Behavioral neuroscience, 122(4), 769. - de Mooij-van Malsen, A. J., van Lith, H. A., Oppelaar, H., Hendriks, J., de Wit, M., Kostrzewa, E., & Kas, M. J. (2009). Interspecies Trait Genetics Reveals Association of Adcy8 with Mouse Avoidance Behavior and a Human Mood Disorder. Biological psychiatry, 66(12), 1123-1130. - de Mooij‐van Malsen, J. G., van Lith, H. A., Laarakker, M. C., Brandys, M. K., Oppelaar, H., Collier, D. A., & Kas, M. J. (2013). Cross‐species genetics converge to TLL2 for mouse avoidance behaviour and human bipolar disorder. Genes, Brain and Behavior. --- ## Effective security screening and airport processes URL: https://noldus.com/blog/behavior-airport Published: 2013-09-30 09:41:00 Description: Do you know this feeling? You are impatiently waiting in line for the security screening. There is a lot going on at an airport and the security screening is just one of the activities. Do you know this feeling? You are impatiently waiting in line for the security screening. While in line you have to take off your shoes and gather all small change from your pockets to put it in a container before walking through a metal detector hoping that it won't detect any forgotten coins or other metal on you? There is a lot going on at an airport and the security screening is just one of the activities. A group of researchers looked into the security screening process at two airports. So how do people behave and what is their role in the process? What actions can be observed and is there a difference between domestic and international airports, and quiet and busy times? Behavior at an airport Passengers play an active role in making airport security screening work, according to Kraal and colleagues. Dr. Ben Kraal from the People and Systems Lab, Queensland University of Technology, Australia presented his work at the 5th International Congress of International Association of Societies of Design Research in Tokyo, Japan. He is one of the researchers in an international research project called Airport of the Future. The program aims to improve the safety, security, efficiency, and passenger experience within Australian airports by developing an integrated and adaptive complex systems approach for the design, management, and operation of airports. Security checkpoint In this case, Kraal and colleagues analyzed behaviors at two airports in Australia (domestic and international) and observed a total of 196 passengers. Their goal was to provide new knowledge on what passengers do as they move through security and to find a way to analyze this behavior. As the researchers explain: "a set of activities are required when moving through a security checkpoint: unpack personal items, walk through a metal detector, collect personal items, repack, and move on". Experiment design Field studies at two airports were conducted to gather data. Two methods were used to investigate activities. The activities of the passengers were coded and analyzed to reveal the common activities at domestic and international security regimes and between quiet and busy periods. Trained coders coded unpacking, waiting in line, walking through the metal detector, waiting for luggage, repacking, and waiting for others using The Observer XT research and analysis software. A second method was used to enrich the picture of passenger activities at airport security screening. In this, Kraal et al. described three cases in depth in order to demonstrate that the seven security activities described in the coding scheme are complexly interwoven with each other and other activities. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial International and domestic airport As explained, the researchers selected four segments: international airport busy time, international airport quiet time, domestic airport busy time, and domestic airport quiet time. Kraal et al. found that during the busy period at the domestic airport time spent in the line and the time that passengers wait for luggage seems to increase while other activities seem to take less time during this period when compared with the quiet period. The main difference between the international and domestic airports was that unpacking activities took longer on average during busy times at the international airport and were faster during quiet times. Conversely, at the domestic airport, unpacking activities took longer when it was quiet than when it was busy. Qualitative and quantitative data Combining qualitative data with quantitative data can provide researchers with more information about a certain phenomenon. It also focuses on different aspects of the problem. Therefore, designers gain knowledge that helps them design gates that will enable a quick and efficient security check at airports. If you are interested in the Airport of the Future project, visit the website. There are many more projects mentioned on the site which contribute to the field of behavioral analysis. Reference Kraal, B.; Popovic, V.; Cave, A.; Taris, A. (2013). Co-production of actions and activities at airport security screening. Proceedings of the 5th International Congress of International Association of Societies of Design Research, Tokyo 26-30 August, 2013. http://design-cu.jp/iasdr2013/papers/1009-1b.pdf --- ## Standing cows URL: https://noldus.com/blog/standing-cows Published: 2013-09-25 10:47:00 Description: Does it matter how much time a cow spends standing up or lying down? Bert Tolkamp thought that it did matter, and he proved his point by winning an IgNobel prize for his work on this. Does it matter how much time a cow spends standing up or lying down? Bert Tolkamp thought that it did matter, and last week he proved his point by winning an IgNobel prize[1] for his work on this[2]. He attached a sensor to the legs of some cows and measured tens of thousands of episodes of lying and standing. His findings were at first sight puzzling and on reflection, revealing (hence the prize). If a cow was lying for a long time, it was more likely to stand up, but it if had been standing for a long time, it was not more likely to lie down. Cow behavior What does this mean? A cow lies down to ruminate (that is, digest its food), and stands to eat. So that means that after it has been lying down (ruminating) a while it is therefore more likely to stand up to eat. The longer it lies, the more likely it is to have finished ruminating, and the more likely it is to be hungry. Cows sitting or lying down But what about the opposite, if a cow has been standing for a long time, will it want to lie down?  Other studies have shown that if cows are prevented from lying down, then they have a strong motivation to lie down as soon as it is allowed[3].  Bert Tolkamp did not see this in his cows. That is good, because it means that the cows were not deprived of lying. Despite sometimes cows have to stand for hours before and during milking, that was apparently not long enough to be a problem in his cows. Looking for natural behavior in cows Why does this matter? Firstly, if you prevent an animal from displaying its natural behaviors then that is, by definition, bad for its welfare. Secondly, an incredible 35% of dairy cows in Europe are lame[4], and this is strongly related to farming methods in which cows spend much or all of their time indoors.  Detailed information on the locomotion of cows (as well as other farm animals) is the only way to get to the bottom of the problem, improve the welfare of the cows and reduce the costs for the farmers. Bert Tolkamp’s research used a relatively simple motion detector on the legs of the cows[2].  There are now advanced tracking techniques available which will enable researchers to get more detailed information about exactly where and how cows and other farm animals are moving, and so get even better insights into their welfare and behavior[5].  As the IgNobel prize-giving committee has shown, although at first sight this may seem a slightly odd thing to investigate, it is actually very important for animal welfare. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your free trial References - The Ig Nobel Prizes honor scientific achievements that first make people laugh, and then make them think. - Bert J. Tolkamp , Marie J. Haskell, Fritha M. Langford, David J. Roberts, Colin A. Morgan (2010). Are cows more likely to lie down the longer they stand? Applied Animal Behaviour Science, 124, 1–10. - Jensen, M.B., Munksgaard, L., Pedersen, L.J., Ladewig, J., Matthews, L., 2004. Prior deprivation and reward duration affect the demand functions for rest in dairy heifers. Appl. Anim. Behav. Sci. 88, 1–11. - Schlageter Tello, A., C. et al. 2011. Selection of a golden standard for visual-based automatic lameness detection for dairy cows. In: Animal hygiene and sustainable livestock production. Proceedings of the Xvth international congress of the International Society for Animal Hygiene. - Spink et al 2013. Animal behavioural analysis with GPS and 3D accelerometers. Proceedings of Precision Livestock Farming 2013, pp 229 - 239. --- ## How zebrafish and optogenetics are great for investigating stress URL: https://noldus.com/blog/zebrafish-and-optogenetics Published: 2013-09-23 09:51:00 Description: By this point, we do not need to tell you how popular zebrafish are. We also probably do not need to point out the great technological advances that are being made in research because of the use of optogenetics. By this point, we do not need to tell you how popular zebrafish are in scientific research. We also probably do not need to point out the great technological advances that are being made in research because of the use of optogenetics. It is safe to say that zebrafish and optogenetics are popular in neuroscience research. Today, let us tell you about the study of De Marco et al. (2013), which combined the two. Stress in humans and animals Stress can have detrimental impact on our health and well-being – ranging from cardiovascular effects to depression and other psychiatric disorders. Glucocorticoids (GCs) are the final effector hormones of the brain stress center (hypothalamic-pituitary-adrenal [HPA] axis) and the focus of many animal and human studies. Investigating glucocorticoids Traditionally, methods to investigate the effects of GCs include stressor exposure or GC infusion. The problem with using stressor exposure is that it only increases the GC levels via the stimulation of other hormones, since GC is the end-hormone in a cascade of hormone stimulation and release. Direct GC infusion can cause bias because the procedure can be stressful in itself. Investigating stress with optogenetics Optogenetics might just hold the answer to the downfalls of traditional methods, because it can offer direct and selective manipulation of GC levels. In fact, De Marco and colleagues effectively developed an optogenetic methods that manipulated the gain of the stress axis with the high temporal accuracy. Zebrafish as the perfect candidates The stress response is strongly conserved across species, and in fact, zebrafish have a hypothalamic-pituitary-interrenal axis that is similar to our HPA axis. This is one reason for using zebrafish as a model for stress studies. Here is another: zebrafish larvae are transparent. This makes them great candidates for optogenetic stimulation. Contrary to rodent studies, there is no need for implantation of fiberoptics. For this study, zebrafish embryos were genetically manipulated to express the light-activated bPAC enzyme in pituitary cells (which govern GC secretion). These embryos were called bPAC+ zebrafish, and compared to their bPAC- siblings in a series of tests. Light as stressor and stimulator Of course, optogenetics works with light, and light in itself is a stressor for zebrafish. (Studies show that wild-type larvae show a drastic reduction in locomotor activity in response to light exposure and an increase in locomotion after the light has been turned off, which gradually decreases to normal levels in minutes.) In this study, De Marco and colleagues took advantage of this double-function of light: it is both a stressor that has an indirect influence on GC levels and an optogenetic stimulator with direct influence on GC levels. Measuring the effects on behavior To assess the behavioral effects of both direct and indirect manipulation of GC levels, the locomotor activity of 30 zebrafish larvae was measured simultaneously with video tracking software EthoVision XT. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Increase in activity and cortisol levels in response to light The researchers aimed to increase levels of cortisol (the most important GC) in response to light stimulation. And in fact, bPAC- larvae showed the normal increase in cortisol levels after exposure to blue light, while the bPAC+ larvae showed an even higher increase. It also led to a higher increase in locomotor activity in bPAC+ larvae compared to their negative siblings. Additionally, early blue-light stimulation caused long term effects; overexposure of GC lead to increased basal cortisol levels in bPAC+ larvae. These larvae also responded to light with higher cortisol levels than bPAC+ larvae that were not exposed to light early on. Future implications This study shows a promising method for stress research, as optogenetics seems to provide a way to establish both rapid and delayed changes in the GC-system, detectable both in brain function as well as behavior. For more details on this study, please find the article at Frontiers in Neural Circuits. Read more - De Marco, R.J.; Groneberg, A.H.; Yeh, C.-M.; Castillo Ramirez, L.A.; Ryu, S. (2013). Optogenetic elevation of endogenous glucocorticoid level in larval zebrafish. Frontiers in Neural Circuits, 7, article 82. - Read more blog posts on optogenetics - Read more blog posts on zebrafish - Read more about zebrafish behavioral research solutions - Read more about optogenetic solutions for behavioral research --- ## Using CatWalk gait analysis to study monoarthritis in mice URL: https://noldus.com/blog/arthritis-gait-analysis Published: 2013-09-19 13:10:00 Description: Researchers are always looking for new ways to alleviate symptoms of arthritis. The CatWalk XT has been shown to be very useful in research involving arthritis in rodent models. Researchers are always looking for new ways to alleviate symptoms of arthritis. The CatWalk XT has been shown to be very useful in research involving arthritis in rodent models. Most of the research done on arthritis with CatWalk has been done with rats, but Parvathy et al. decided that they would use mice in their experiment, being that mice are frequently used in disease studies and they are the preferred animal for genetic modifications when studying biology and disease. The researchers looked at both static and dynamic parameters in this experiment. Methods Researchers injected two groups of mice with the same amount but different types of liquid in their right hind leg. A third group was run through the experiment prior to using the two injected groups to collect baseline data. The control group received phosphate buffered saline (PBS) to make sure that the results were not affected by the injection or the amount of liquid. The experimental group was injected with complete Freund's adjuvant (CFA), which is used extensively for inducing arthritis in mice. Both were compared against the baseline data (mice with no injection) to see if there was a difference. If the mice exhibited signs of arthritis, they were treated with a dose of indomethacin, a non-steroidal anti-inflammatory drug used commonly to treat arthritis, and made to walk at 1, 2, and 3 hours after treatment. Parameters used Both static and dynamic parameters were used in this experiment. The three static parameters were interlimb coordination, paw pressure, and paw print area. Interlimb coordination was measured as the time spent with a normal walking pattern, paw pressure was measured by the intensity of the light where the footsteps showed up using CatWalk, and paw print area was the space that the foot occupied when it touched the walkway. The dynamic parameters used were stance phase, swing phase, duty cycle, stride length, and swing speed. Stance phase was measured by how long the paw touched the floor and swing phase was measured by how long the paw was in the air. Duty cycle was stance duration as a percentage of the step cycle duration. Stride length was the distance between steps of the same paw. Swing speed was the speed of a paw while it was in the air. Results after injection There was a significant decrease in all of the static parameters after mice were injected in the right hind leg with CFA. Some mice stopped using their right hind leg completely. The mice injected with PBS showed no significant difference in interlimb coordination, paw pressure, or paw print area when compared with the baseline data. With the dynamic parameters, duration of stance, duty cycle, and swing speed all decreased significantly. Duration of swing phase increased significantly and stride length did not change significantly. Altogether, this indicates that the mice with CFA injected were trying to spend less time and apply less pressure on their right hind leg, thus less of things like paw pressure and swing speed. Duration of swing phase increased because the rodent took more time to set its foot down. Results after drug After being injected with indomethacin, it was found that the amount needed to alleviate the symptoms of arthritis in the mice was 10mg/kg. For the static parameters, treatments alleviated paw pressure and print area deficits at 1, 2, and 3 hours after treatment, though the effect of the drug was most significant at two hours after treatment. 10mg/kg of indomethacin also alleviated the effects of dynamic parameters at 1, 2, and 3 hours after injection, but showed the most significant effect at 2 hours. Swing phase duration was more sensitive to treatment with indomethacin, and was alleviated by a lower dose. Conclusion The change in static and dynamic gait parameters in CFA-induced monoarthritic mice is able to be quantified by CatWalk. Also, the extent of alleviation was able to be quantified. In fact, CatWalk XT produced quantifiable and easy-to-reproduce data which got rid of observer bias. Changes in gait parameters were not due to the injection or volume of the liquid, because the control group ended up matching up with the baseline data. Most importantly, though, the deficits and alleviation by drug treatment corresponded to what can be seen in humans, showing that using mice as a model organism and CatWalk to quantify data is an effective way to study drugs for CFA-induced arthritis. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Reference Parvathy, S.S.; Masocha, W. (2013). Gait analysis of C57BL/6 mice with complete Freund's adjuvant-induced arthritis using the CatWalk system. BMC Musculoskeletal Disorders, 14(14), 1-9. --- ## The effects of quantum dots on zebrafish larvae locomotor behavior URL: https://noldus.com/blog/quantum-dots-toxicity-zebrafish-larvae Published: 2013-09-16 14:00:00 Description: Ever heard of quantum dots? These dots are nanoparticles made of a semiconductor material, which have unique optical properties, making them of great interest for fields such as biological imaging, medical diagnostics. Ever heard of quantum dots? These dots are nanoparticles made of a semiconductor material, which have unique optical properties: the wavelength (and thus color) of their light emission depends on their size, rather than the material they are made of. This is why they are of great interest for fields such as biological imaging, medical diagnostics, drug delivery, and gene therapy. Image courtesy: Erasmus MC, Rotterdam, The Netherlands Toxicity of tiny dots Quantum dots (QDs) are great stuff, but of course, their value also depends on how safe they are. For example, QDs made of Cadmium Telluride (CdTe) are used to make solar cells, can be used in optical windows and lenses, and are also promising in the field of life sciences (e.g. bio-medicine labeling). However, their use is limited by their toxicity. Testing toxicity in zebrafish Duan et al. recently published an article on the developmental toxicity of CdTe QDs in zebrafish in the Journal of Nanoparticle Research. For their study, they exposed zebrafish embryos to four different concentrations of these nanoparticles and evaluated their development. They also investigated the prolonged effects of QDs in larvae. Effects on zebrafish embryo development Zebrafish embryos of the AB wild-type strain were exposed to the QDs from 4 hours to 96 hours post fertilization. The assessment of developmental toxicity included mortality rates, hatching rates, heart rates, and malformations. All of these showed a time and concentration dependent negative effect. Prolonged effects on zebrafish larvae locomotor behavior Zebrafish larvae were tested at 6 days post fertilization, after the QD exposure had ended. They were tested in two experiments in 24 well-plates in a DanioVision Observation Chamber. In the first test, larvae were acclimatized to visible light for 20 minutes and then the locomotor activity of the larvae was recorded for 5 minutes with EthoVision XT video tracking software. Larvae locomotor activity, automatically measured as total swimming distance, was suppressed in treated larvae in a dose-dependent manner: the higher the concentration of QD-exposure during early development, the lower the activity of the larvae at 6 dpf. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Effects on zebrafish larvae behavior in light-dark cycles In a second test, a light-dark experiment, larvae were acclimatized in 20 minutes of darkness, after which a cycle of 10 minutes of darkness alternating with 10 minutes of lights-on commenced for 70 minutes total. Again, swimming distances were measured. Typically, larvae intend to increase their activity during the dark phases, as did the control group. Again, the QD-exposure showed a dose-dependent effect: significant hypo-activity in larvae treated with the three highest doses, but only during the dark phases. Conclusion These findings confirm the suspected toxicity of CdTe QDs, and, as the authors mention, show that "…the exposure to QDs could be a potential hazardous factor for environmental exposure (…) but more studies of relation between QDs exposure, adverse effects, and biological mechanisms are needed." Read more - Read the publication: Duan, J.; Yu, Y.; Li, Y.; Yu, Y.; Li, Y.; Huang, P.; Zhou, X.; Peng, S.; Sun, Z. (2013). Developmental toxicity of CdTe QDs in zebrafish embryos and larvae. Journal of Nanoparticle Research, 15, 1700. - Read more about zebrafish larvae video tracking, DanioVision, EthoVision XT video tracking software. - Check out other blog posts on zebrafish behavior studies. --- ## A-bad-influence: Parent substance use disorder and child outcomes URL: https://noldus.com/blog/parent-substance-use-disorder-influence-child Published: 2013-09-12 13:27:00 Description: Like parent, like child. Children become who they are with the influence of all of their past experiences and often, the parents are a large part of that influence. Like parent, like child. Children become who they are with the influence of all of their past experiences and often, the parents are a large part of that influence. When there is trouble at home, that can impact a child's everyday life in their behaviors and performance. Prior studies have found associations between parent substance use disorder and negative child outcome (problem behaviors, performing poorly in school, and child substance use). Bailey and colleagues expanded on previous work with their study and took a developmental approach to the association between parental substance abuse and the behaviors children exhibited. The purpose of this experiment Bailey et al. were looking specifically at how parental substance abuse problems affect the parenting behavior and child behavior during key developmental transitions like the one from childhood to adulthood. They had three hypotheses that were possible. The first was that early adult substance abuse ends up disrupting the transition to adulthood, which ultimately results in poor functioning as an adult which has a negative effect on parenting. A second hypothesis for the link between early adult substance use disorder and later parenting practices is that common individual personality or behavioral traits will lead to both of these outcomes. The final hypothesis is that poor parenting of a child may lead to early adult substance abuse and could be reflected in that child's parenting practices when they grow up. Methods used This study used data from two different research projects to find links. The first set of data came from the participants when they were children. A portion of the participants was exposed to preventive intervention in elementary school. The second project collected data on those participants who became parents with the included data of their oldest child. The Observer XT was used by trained coders to code the interactions found in the tapes of the interviews, which occurred within six weeks of the child's birthday each year. The study measured parent early adult illicit drug use disorder (DUD), observed parenting practices, child externalizing behavior, disrupted adult functioning, parent behavior and personality traits, adolescent family process, and other variables. The other variables included data such as the age of the target child (to see if parenting practices are rated differently for younger children than older), the chance of prenatal drug exposure, and the sex and ethnicity of the parent. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Results and conclusion While in early adulthood, 24% of the participants in the study reported meeting at least one of the criteria for illicit DUD; by age 27 that number had decreased to 9%. Also, mothers reported some substance use (mostly smoking cigarettes) during pregnancy in 30% of cases. There was a positive relationship between observed low-skill parenting and early adult illicit DUD. Also, low-skilled parenting had a significant association with parent-rated child externalizing behavior while prosocial socialization did not. As was expected, young adult illicit DUD ended up being associated with the observed parenting practices. Higher levels of DUD symptoms in young adults were associated with higher levels of low-skilled parenting later on. This study does suggest, though, that early adult substance use may end up being relevant to later parenting. There was limited support for the disrupted transition to adulthood explanation the link between parenting practices and early adult DUD. Young adult DUD significantly predicted the measures of parent adult functioning later on. The findings in this study did support the idea that already existing traits in personality or behavior could explain early adult DUD and parenting practices later on. However, it did not support the hypothesis that experienced parenting in childhood and disrupted family processes in adolescence might explain the early adult DUD and parenting practices association. Overall, the results suggest that early adult problem drug use could have an impact on later parenting skills. References Bailey, J.A.; Hill, K.G.; Guttmannova, K.; Oesterle, S.; Hawkins, J.D.; Catalano, R.F.; McMahon, R.J. (2013). The association between parent early adult drug use disorder and later observed parenting practices and child behavior problems: testing alternate models. Developmental Psychology, 49 (5), 887-899. --- ## Tracking a wide variety of animals URL: https://noldus.com/blog/tracking-wide-variety-animals Published: 2013-09-10 10:01:00 Description: Video tracking is used to track a widevariety of animal species in even more different test arenas. From insects of 1 mm on leaf discs, to monkeys in a cage, or zebra fish in an aquarium. Video tracking is used to track a wide variety of animal species in even more different test arenas. While one researcher wants to track insects of 1 mm on leaf discs, another one is interested in monkeys in a cage, or zebra fish in an aquarium. It will be clear that the settings created for detection of the tiny insect may not be suitable to detect the monkey, or the zebra fish. Different setups require different detection methods EthoVision XT tracking and analysis software has four methods to optimize the detection of your animals. Each method has its own benefits. This way the program offers possibilities to track many different animal species under very different circumstances. Below we summarize which method is most suited in which situation and give some examples of research carried out with these methods. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Gray scaling Of the four detection methods, gray scaling is the most robust. This method identifies the animal by its gray scale value. This method is very suitable when the animal contrasts well with the background and there are no objects in the arena of the same size and gray scale as the animal. Furthermore, the background should not change, for example because bedding material is kicked around in a cage. Lavorato et al. [1] successfully used this method to track tadpoles in water. Also, Kloth et al. [2] used gray scaling to create 20 tracks simultaneously of aphids kept individually on small leaf disks. Static subtraction Gray scaling is not suitable if other objects in the arena have a similar color as the animal. If this is the case, for example because there is a novel object in the arena, tracking may be possible with static subtraction. In this method, a reference image of the background without animal is used. When your animal is present in the arena, EthoVision XT detects it by subtracting the reference image from the images with animal. Mathur et al. [3] used this method to track adult zebra fish in aquaria. This method works very well when you can create a reference image of your arenas without animals. But this is not always necessary. It is, however, necessary that the background remains constant throughout the experiment. When this is not possible, dynamic subtraction, as described below, is more suitable. Dynamic subtraction In dynamic subtraction, the background is updated regularly. So changes in lighting, or background, are corrected for. You can use this method, for example, when you track rats or mice in a cage that move bedding material around during the test. Also when the lighting changes during the test, dynamic subtraction may be what you need. This method is also very suitable when you cannot make a reference image of an arena without your animal. Ettrup et al. [4] used dynamic subtraction to track minipigs in pens of 2 x 1.5 m, probably because it would not be very practical to remove all minipigs from the pens to make reference images without animals. Also, Hammamieh, Rasha et al.[5] used this method to track mice in resident cages in which an iron mesh cage with an intruder mouse was placed. Differencing The detection method differencing is the most processor intensive one. For each pixel, EthoVision calculates the probability that its difference with the reference image is large enough, so that it is likely that it is part of the animal. When your animal is not well enough detected in all places of the arena with one of the other methods, try differencing. Differencing is especially suitable when there is a sharp light gradient in the arena, like a shadow, or when your animal has more than one color, like hooded rats. Assareh et al. [6] successfully used differencing to track Lister hooded rats in Perspex boxes. The method that fits your needs The research examples illustrate that EthoVision XT can be used successfully under very different circumstances, from aphids of 4 mm on leaf discs, to zebra fish in aquaria, rats or mice in home cages, and mini pigs in pens of 2 x 1.5 m. There is always a detection method fits exactly your research setup, even when tracking is challenging, for example because the background changes during the experiment, or when your animal has more than one color. References - 1. Lavorato, M.; Bernabò, I.; Crescente, A.; Denoël, M.; Tripepi, S.; Brunelli, E. (2013). Endosulfan effects on rana dalmatina tadpoles: quantitative developmental and behavioural analysis. Archives of environmental contamination and toxicology, 64 (2), 253-262. - 2. Kloth, K.J.; ten Broeke, C.J.M.; Thoen, M.P.M.; Hanhart-van den Brink, M.; Wiegers, G.L.; Krips, O.E.; Noldus, L.P.; Dicke, M.; Jongsma, M.A. (2013). High-throughput phenotyping of plant resistance to aphids by automated video tracking. Plant Methods, 11 (4), doi: 10.1186/s13007-015-0044-z - 3. Mathur, Priya, Michael A. Berberoglu, and Su Guo., 2011 Preference for ethanol in zebrafish following a single exposure. Behavioural Brain Research, 217 (1), 128-133. - 4. Ettrup, K. S., Sørensen, J. C., Rodell, A., Alstrup, A. K. O., & Bjarkam, C. R. (2012). Hypothalamic deep brain stimulation influences autonomic and limbic circuitry involved in the regulation of aggression and cardiocerebrovascular control in the Göttingen minipig. Stereotactic and Functional Neurosurgery, 90 (5), 281-291. - 5. Hammamieh, R., Chakraborty, N., Lima, T., Meyerhoff, J., Gautam, A., Muhie, S., & Jett, M., 2012. Murine model of repeated exposures to conspecific trained aggressors simulates features of post-traumatic stress disorder. Behavioural Brain Research, 235, 55-66. - 6. Assareh, N., ElBatsh, M. M., Marsden, C. A., & Kendall, D. A. (2012). The effects of chronic administration of tranylcypromine and rimonabant on behaviour and protein expression in brain regions of the rat. Pharmacology Biochemistry and Behavior, 100 (3), 506-512. --- ## To mate or not to mate? Females are less choosy when males are rare URL: https://noldus.com/blog/fish-mating-preference Published: 2013-09-04 09:30:00 Description: Having a choice for a mating partner is extremely important for females, so they can be critical in choosing which male to mate with. Having a choice for a mating partner is extremely important for females, so they can be critical in choosing which male to mate with. However, being critical also has its disadvantages; it costs time, energy, and may subject the females to an increased mortality risk (for example due to a higher predation risk. Therefore, being critical about a potential mating partner only pays off when males are abundant or when the risk of being critical is not too high. There are animals, such as green swordtail fish [1], which change their mating preference when predation risk becomes higher or when the mating season is nearing its end. Mating and species diversification Mating usually takes place between a male and a female from the same species. However, there are also examples of hybridization, where males and females of different species mate and produce offspring. This usually happens when mating partners of the own species are rare. Hybridization is an extremely interesting phenomenon from an evolutionary perspective and can play an important role in species diversification. Male abundance and female choosiness Willis et al. [1] studied hybridization in swordtail fish, Xiphophorus birchmanni, with X. malinche. These two species hybridize in nature. The authors investigated whether X. birchmanni females would change their preference to males from X. malinche when the encounter rate with males of their own species was low. Females were first kept for 24 hours with males of their own species and then were introduced either immediately afterwards or after 24 hours into an aquarium in which two other fish were kept behind transparent, porous barriers. Video tracking fish behavior The authors carried out a no choice test and a dual choice test. In the no choice test, an X. malinche female was kept behind one barrier and an X. malinche male behind the other. In the dual choice test, the areas behind the barriers contained either an X. birchmanni male or an X. malinche male. The time that the X. birchmanni female spent in the zone near both barriers and the frequency of visits to these zones was determined automatically with EthoVision XT video tracking and analysis software. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Male scarcity makes females less choosy The female fish behavior was clearly different depending on the presence of males of her own species. In the no choice test, the interest of females in X. malinche males was higher when the test was carried out 24 hours after exposure to males of her species than when the test was done immediately after this exposure. The females spent more time in the area near the X. malinche males and visited this zone more frequently when introduced 24 hours after exposure. However, in the dual choice test, the interest in X. malinche males was not affected by the duration of male deprivation. The females had more interest in their own species than in X. malinche. To mate or not to mate? The results show that female fish change their mating preference in response to the abundance of males from their own species. The females are less choosy and show interest in males from another species when males of her own species are rare. To mate or not to mate? The answer is yes, even with males from another species when her own species is not available. References - Johnson, J. B., & Basolo, A. L. (2003). Predator exposure alters female mate choice in the green swordtail. Behavioral Ecology, 14, 619-625. - Willis, P. M., Ryan, M. J., & Rosenthal, G. G. (2011). Encounter rates with conspecific males influence female mate choice in a naturally hybridizing fish. Behavioral Ecology, 22(6), 1234-1240. - Image: By Wojciech J. Płuciennik (Own work) [CC BY-SA 4.0], via Wikimedia Commons --- ## Vocalizations as an early life behavioral marker for ASD URL: https://noldus.com/blog/vocalizations-asd Published: 2013-08-30 13:58:00 Description: One of the prominent features of autism spectrum disorder (ASD) is impaired communication. However, most diagnoses of ASD happen after the child is more than 3 years old. One of the prominent features of autism spectrum disorder (ASD) is impaired communication. However, most diagnoses of ASD happen after the child is more than 3 years old, so there is not much information on the vocalizations of young children with ASD. Vocalizations as an early life behavioral marker for ASD For children under the age of 3, certain communication skills are not applicable – more information is needed on purely vocalizations (not conversation or language) in order to work on identifying another early life behavioral marker for ASD. In this study, Allison M. Plumb and Amy M. Wetherby chose to examine the vocalizations of ASD children at age 2 and the relationship of these vocalizations to other areas of development. The goals of the study Plumb and Wetherby wanted to examine the vocalizations of children aged 18 to 24 months in one group with those who were later diagnosed with ASD and two matched groups for children with developmental delays (DD) and typical development (TD). First, they wanted to compare communicative and non-communicative vocalizations displayed by the children between the three groups. Second, they wanted to examine the concurrent and predictive relationships between vocalization at age 2 and developmental measures at age 2 and 4 in ASD-diagnosed children. Lastly, they wanted to determine if communicative vocalization at age 2 would predict the child's nonverbal and verbal developmental level at age 3 more than non-communicative vocalizations would. FREE WHITE PAPER Tools for Infant Studies Download the free White paper to learn more about the software tools available for infant studies. - Video observations to capture behaviors - Coding behaviors accurately - Unobtrusive emotion analysis Download The background of the research Much of the early research on young children with ASD has been done through home videos and parent reports, due to most children not being diagnosed with ASD before age 3. However, only so much can be done with the use of past videos. Plumb and Wetherby chose to use direct observation and systematic sampling procedures in their research. Although many of the children chosen for the direct observation studies have not been diagnosed with ASD yet, they are "high-risk" (HR) and have an older sibling with ASD. Another important part of using direct observation was the ability to be able to notice when vocalizations were being used as a means to try to communicate and also to look at the relationship between vocalizations and later spoken language. Data can be collected directly from observing the child at different ages – the researchers do not have to rely on sources which may not be reliable, like home videos. Also, researchers have looked to see if there is a difference between the way ASD children vocalize and the way TD children vocalize. Schoen, Paul, and Chawarska (2011) studied the vocal transcriptions of children age 18 to 36 months, and compared two groups (chronological age or CA and language age or LA) of TD toddlers to a group of ASD children. It was found that though the speech sound use was the same between the ASD and LA-matched groups, the ASD group used significantly more atypical vocalizations that either of the two TD groups. Systematic observational research Another useful part of this study was systematic observational research, which is emerging for children younger than 2 years old with ASD. Many of these identified children come from a general population screen that uses the Communication and Symbolic Behavior Scales Developmental Profile or the CSBS DP (Wetherby & Prizant 2002). Also, Wetherby and colleagues (2004) investigated a subset of this group of CSBS DP children, using the Systematic Observation of Red Flags (SORF) for ASD in Young Children (Wetherby & Woods, 2002). In this study, a lack of communicative vocalizations was discovered to be one of 13 red flags differentiating children with ASD from children with TD. The methodology The 125 participants were sorted into three groups (ASD, DD without ASD, and TD). Researchers used The Observer XT to recode video-recorded CSBS DP Behavior Samples that held vocalization measures and code communicative acts. All of the speech and non-speech vocalizations were coded and segmented based on the silence surrounding the vocalization or a change in category. The three categories were transcribable vocalization, non-transcribable vocalization, and could not be determined. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial To learn more about this experiment and read the results, you can find the publication here: - Plumb, A.M.; Wetherby, A.M. (2013). Vocalization development in toddlers with autism spectrum disorder. Journal of Speech, Language, and Hearing Research, 56, 721-734. - Schoen, E.; Paul, R.; Chawarska, K. (2011). Phonology and vocal behavior in toddlers with autism spectrum disorders. Autism Research, 4, 1-12. - Wetherby, A.M.; Prizant, B.M. (2002). Communication and Symbolic Behavior Scales Developmental Profile (1st normed ed.). Baltimore, MD: Brookes. - Wetherby, A.M.; Woods, J. (2002). Systematic observation of red flags for autism spectrum disorders in young children (Unpublished manual). Florida State University, Tallahassee. - Wetherby, A.M.; Woods, J.; Allen, L.; Cleary, J.; Dickinson; Lord, C. (2004). Early indicators of autism spectrum disorders in the second year of life. Journal of Autism and Developmental Disorders, 34, 473-493. --- ## Zebrafish research: behavioral differences between wild-type strains URL: https://noldus.com/blog/zebrafish-behavioral-differences Published: 2013-08-20 16:11:00 Description: Often in animal research, animals with a certain genetic alteration are compared to a “wild-type”. One might assume that there is no differences between wild-types, but many different strains of wild-type animals are used. Often in animal research, animals with a certain genetic alteration are compared to a "wild-type" (this being the 'normal' rat, mouse, or zebrafish). One might assume that there is no difference between one wild-type animal and the next, but in fact, many different strains of wild-type animals are used. Many wild-type zebrafish strains The same is true for zebrafish. Many studies talk of wild-type animals, but the strain is not always mentioned. Furthermore, wild-type fish can be acquired at the pet shop, from a commercial scientific supplier, or simply caught in the wild. Vignet et al. noticed that there have been reports of differences in behavior between wild-type strains, and therefore they stress the importance of matching the most appropriate strain to the behavioral test. Comparing AB and TU zebrafish strains In their study, recently published in Zebrafish, Vignet et al. report about their comparison between two well-established wild-type strains of zebrafish (AB and TU). They subjected both larval and adult specimens to a series of behavioral testing. All of these tests were recorded on video with an IR backlight and then processed and analyzed with EthoVision XT video tracking software. Circadian rhythmicity of adult zebrafish To investigate adult circadian rhythmicity, multiple fish per tank were tested in multiple tanks simultaneously. After one night of acclimatization, behavior was recorded during 48 hours with a normal day-night lighting cycle. Activity, measured as distance travelled (cm), was automatically determined by EthoVision XT. Both strains were most active during the transition period from light to dark and from dark to light. AB fish were more active at the end of the day, while TU fish were more active at the end of the night. On the whole, activity during the day was greater for AB fish. While AB fish were clearly diurnal (showing significantly more activity during light phases than dark phases), activity levels of the TU fish were more evenly distributed. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Light/dark challenge adults A sudden darkness test elicited an immediate and sustained increase in activity in both strains of adults, though the response was larger in TU fish. When lights were turned on again, an additional increase was measured, which decreased rapidly. TU fish were more active than AB fish, but only during the dark periods. Circadian rhythmicity in larvae Circadian rhythmicity was also measured in larvae, in 24 well-plates. This well plate was chosen (as opposed to 48 or 96 well-plates) to obtain a higher level of activity. Before video tracking, the plate was placed on an IR floor to acclimatize the larvae to their new surroundings before 72 hours of continuous video tracking. Both strains of larvae turned out to be diurnal with activity levels decreasing to a minimum during nighttime. During the day, TU larvae were more active than AB larvae, and they showed a more contrasted activity between day and night. After 5 dpf, AB larvae were more active than TU larvae during most of the nights. Light/dark challenge larvae For the light/dark challenge, larvae were tested at 5 dpf in 48 well-plates in which they already acclimatized for one day. A second acclimatization took place in either the box they used for video tracking (protocol 1, P1) or simply on an IR backlit plate (P2) for 2 hours. In P1, 5 minutes of darkness was preceded by and followed up with 2 hours of light. AB larvae were more active and showed a higher increase in activity during the second light phase compared to TU larvae. The second protocol (P2) was more 'high-throughput': all three phases only lasted for 5 minutes. With this protocol, the darkness did not elicit the expected increase in activity though turning the lights on again did result in the classical decrease. Novel environment testing adults The third experiment measured the exploration of individual adult zebrafish in a novel environment, which in this experiment was either a T-maze or a trapezoidal tank. In the T-maze, one goal arm was deeper and contained marbles and artificial grass to create a more favorable environment. After release in the start area, fish were video tracked for 5 minutes, measuring latency to exit start area, time spent in each area, and distance traveled automatically with EthoVision XT. The time it took fish to reach the more favorable arm did not differ between strains, though TU fish tended to spend more time in the start area. TU fish were also more active in the shallow area. Then, a novel tank test was performed to measure the amount of time spent in the upper (1/3 of the tank) and lower (2/3 of the tank) areas. While all of the fish spent more time in the bottom, time spent in the upper zone increased over time. TU fish spent more time in the top than AB fish and were more active, indicating more exploration by the TU fish and more anxious behavior by the AB fish. Color learning For color learning, adult zebrafish were conditioned to a green light, by subjecting them to green light for 10 seconds, once a day, immediately followed by food. They were reared alongside a control group for each strain. After 15 days of conditioning, 5 days of testing commenced. Researchers used a 'color-test box', containing a home area and a chamber area with three chambers. This box was again placed on an IR floor and animals were video tracked from above. In the first test, one of the chambers lit up green for 30 seconds. Conditioned fish from both strains spent more time in this particular chamber than the other chambers; the control groups did not. In the second test, a blue light was turned on at the same time as the green light, but in another chamber. Only conditioned fish were tested in this color discrimination test and only the AB strain spent more time in the green chamber than in the blue and unlit chambers, while TU showed no distinction. Different genetic backgrounds can lead to differences in behavior So there you have it. With this range of behavioral tests, Vignet and colleagues showed that these two strains can sometimes act the same but at other times show different behaviors. While TU fish seem to be more explorative, AB fish seem to be more anxious and better in color discrimination learning. Care should be taken in selecting the appropriate strain for each study, and in comparing results from different studies with different strains used. More about this research Vignet, C.; Begout, M.L.; Pean, S.; Lyphout, L.; Leguay, D.; Cousin. X. (2013). Systematic screening of behavioral responses in two zebrafish strains. Zebrafish, doi: 10.1089/zeb.2013.0871. More about these behavioral tests If you want to find out more about these types of behavioral tests and how automated video tracking can make these test more reliable and efficient, please visit these webpages: - EthoVision XT video tracking software - DanioVision complete larvae video tracking system - T-maze testing (and color learning) of zebrafish - Novel tank diving in zebrafish --- ## Classroom observations - behavior of children with and without ADHD URL: https://noldus.com/blog/classroom-observations-adhd Published: 2013-08-13 15:29:00 Description: The relationship between reaction time variability and observed attention in children with and without ADHD. The relationship between reaction time variability and observed attention in children with and without ADHD Attention Deficit Hyperactivity Disorder (ADHD) has become a fairly common subject of research in today's society. The disorder affects working memory, attention span, and inhibitory control. There are two types, Combined and Predominantly Inattentive. In this study, 146 participants between the ages of 7 and 11 were split into three groups: ADHD-Combined (ADHD-C), ADHD-Predominantly Inattentive (ADHD-I), and a control. Tanya Antonini and colleagues looked for an association between reaction time (RT) variability and observed behavioral indicators of attention. Building on results Antonini et al.'s study (2013) built on the results that were presented in Epstein et al.'s study (2011). This study examined differences in RT variability between children with and without ADHD across five computerized tasks. The results of this study showed that the RTs of children with ADHD were more variable than those of the control group, and were also less accurate than the control on the majority of the tasks. This study did not have an analog math task. Groupings Both ADHD groups in Antonini et al.'s study had lower IQ and Numerical Operations scores and a higher number of inattentive symptoms than the control. If six or more symptoms of ADHD were present in the child, they fell into one of the categories (ADHD-I if symptoms were in the inattentive domain and ADHD-C if in both the inattentive and hyperactive-impulsive domains). To be in either ADHD group, the child must have fulfilled DSM-IV criteria. The experiment Children in the three groups completed five computerized neuropsychological tasks and one analog math task. The five computerized tasks that the participants took were designed to assess things like working memory, attention span, and inhibitory control. These tasks were the choice discrimination task, Attentional Network Task, go/no-go task, stop signal task, and n-back task. Though these tasks differed, they all required the participant to focus and push a button in certain events. For each neuropsychological task, five neuropsychological variables were calculated. During the analog test, behavior of the children was observed continuously using The Observer XT. Researchers looked at the amount of time the children spent on-task and off-task. The participant was considered off-task if their gaze left the sheet for two or more seconds. To measure attention, researchers calculated the mean duration of on-task behavior. Linear mixed models were then used to examine relationships between the RT variability measures from the neuropsychological tasks and the behavioral inattention observed during the analog task. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial The results For both the ADHD-C and ADHD-I groups, the mean on-task behavior was significantly shorter than that of the control group. The mean did not vary significantly between the two groups with ADHD. There did appear to be a relationship between observed attention and RT variability, which spanned all of the groups in the study, staying consistent regardless of diagnosis. The relationship did not appear to be affected by age, gender, or presence of anxiety or depression. It is a strong relationship, as the associations were viewed across the five different tasks. There was also a significant positive relationship between task accuracy and mean on-task behavior, probably due to the fact that participants are only able to achieve high accuracy if they are paying attention. In the future Future studies should try to assess ADHD-related behaviors outside a lab setting. They should also consider supporting their coding of behavior with psychophysiological indicators of attention to better determine where the attention of the participants is directed. References - Antonini, T.N.; Narad, M. E.; Langberg, J.M.; Epstein, J.N. (2013). Behavioral correlates of reaction time variability in children with and without ADHD. Neuropsychology, 27 (2), 201-209. - Epstein, J.N.; Langberg, J.M.; Rosen, P.J.; Graham, A.; Narad, M.E.; Antonini, T.N.; Brinkman, W.B.; Froehlich, T.; Simon, J.O.; Altaye, M. (2011). Evidence for higher reaction time variability for children with ADHD on a range of cognitive tasks including reward and event rate manipulations. Neuropsychology, 25 (4), 427-441. --- ## Caterpillars speed up seed production in plants URL: https://noldus.com/blog/seed-production-plants Published: 2013-08-12 09:02:00 Description: Did you know that plants are not as passive as they appear to be at first sight? Although plants cannot run away when they are attacked by plant eating insects, they have several sophisticated ways to defend themselves. Plants are sophisticated Did you know that plants are not as passive as they appear to be at first sight? Although plants cannot run away when they are attacked by plant eating insects, they have several sophisticated ways to defend themselves. They can produce nasty substances upon attack. Or they can produce smells that attract natural enemies of their attackers [1]. Now it also shown that the threat of being eaten can speed up seed production in plants and affect the behavior of pollinators. A field study with Pocket Observer Lucas-Barbosa et al. [2] did a field study with the cabbage white butterfly (Pieris brassicae) on black mustard (Brassica nigra) plants. They investigated whether the presence of caterpillars influenced the behavior of pollinating insects like honey bees, bumble bees, and syrphid flies. They used Pocket Observer mobile scoring software to study the pollinators' behavior in the field. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial The setup The field setup consisted of 16 treated plant plots and 16 control plots. Each plot contained five plants. The center plant either contained 30 P. brassicae eggs, or remained untreated. All other plants were untreated as well. The authors studied three phases in caterpillar attack. In the first phase only eggs were present on the leaves and the plants were still undamaged. In the second phase the eggs had hatched and the caterpillars were damaging the leaves. And in the third phase the flowers were also eaten by the caterpillars. Caterpillar damage affects pollinators The pollinators behaved the same on the treated and control plots in the first and second attack phases. But during the third phase, bumble bees visited more flowers in the caterpillar infested plots than in the control plots. Syrphid flies, in contrast, spent less time feeding per flower in infested plots than in the control plots. This shows that the presence of caterpillars, or caterpillar damage, somehow influences the behavior of the pollinating insects. Caterpillars also speed up seed production The researchers went out into the field to observe insects, but they found an extremely interesting phenomenon in the plants. Plants in the infested plots produced more seeds and did so earlier than plants in the control plots. This effect already occurred when the caterpillar eggs had not yet hatched. So while the leaves were not yet damaged, the presence of caterpillar eggs induced the plants to accelerate seed production. Plants are clever Speeding up seed production is extremely important. Once infestation is so severe that caterpillars move to the flowers, these are eaten completely. This, of course, means no seed production. The pollinating insects did not cause the altered seed production. Seed production already speeded up when only eggs were present in the damaged plots and the pollinators were not yet affected. So the plants respond in another way to the threat of caterpillar damage, which will be food for further study. The results found in the present study once again demonstrate that plants are much more clever and less passive than we used to think they are. References - Dicke, M. & Hilker, M. (2003) Induced plant defences: from molecular biology to evolutionary ecology. Basic and Applied Ecology, 4, 3–14. - Lucas-Barbosa, D., van Loon, J. J. A., Gols, R., van Beek, T. A., Dicke, M. (2013), Reproductive escape: annual plant responds to butterfly eggs by accelerating seed production. Functional Ecology, 27, 245–254. --- ## Autism research - mothers of high-risk children use more gestures URL: https://noldus.com/blog/behavioral-observations-autism-research Published: 2013-08-06 12:00:00 Description: Children with autism spectrum disorder (ASD) often have delayed development in communication and language. This impaired development can be present even in the first year of their lives. Autism, language and gestures Children with autism spectrum disorder (ASD) often have delayed development in communication and language. This impaired development can be present even in the first year of their lives. The use of gestures, like pointing and nodding, is very important in communication. Impairments in the use of those gestures goes hand-in-hand with impairments in language development. This is seen in young children with ASD. But such deficits are also more common in infants and toddlers that have a higher risk on autism (HRA), because they have an older brother or sister that was diagnosed with ASD. Gesture use by mothers Mothers play a crucial role in the development of communication of their children. The use of gestures by the mother strongly correlates with the gesture use and language development of their children. Mothers that have an older daughter or son that was diagnosed with ASD, may change their behavior towards the younger HRA children. For example, these mothers have learned to use more gestures when communicating with their children. This could affect the gesture use and language development of HRA children. Behavioral research on autism This is exactly what was studied by Meagan Talbott and colleagues in a recent publication on autism research [1]. They observed two groups of children, HRA and LRA (Low Risk on ASD, no older sibling with ASD), at 12 months and 18 months of age. They observed the number of gestures by the mother and the child, and the type of gestures. The also characterized the language development using two common scales. Parent-child interactions were recorded on video and the videos were analyzed with The Observer XT scoring and analysis software. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Mothers of HRA children use more gestures Nine children were diagnosed with ASD during the study and formed a separate group in the analysis. The video observations showed that mothers of HRA children used significantly more gestures and also more gesture types than mothers of LRA children in communication with their children. However, the gesture use of the children themselves was only affected in the ASD group and not in the HRA group. In all three groups there was a strong correlation between gesture use at the age of 12 months and language development at the age of 18 months. Parent-child interactions and autism The authors concluded that mothers change their behavior towards their children when they have a previous experience with a child that was diagnosed with ASD. This effect does not lead to changed gesture use and language development in the young children under study. Possibly 12 and 18 months was too young to see such an effect. But the study is an important first step in unraveling the effect of ASD risk on early parent-child interactions and communication development in the children. References Talbott, M.R.; Nelson, C.A.; Tager-Flusberg, H. (2013). Maternal Gesture Use and Language Development in Infant Siblings of Children with Autism Spectrum Disorder. Journal of autism and developmental disorders, 1-11. --- ## How environmental enrichment reduces the effects of stroke URL: https://noldus.com/blog/environmental-enrichment-stroke Published: 2013-08-01 11:21:00 Description: Some research requires animals to be studied in groups. For this it is very useful to have video tracking software that can automatically track the behavior of multiple animals simultaneously. A study of environmental enrichment as possible brain tolerance inducing factor for strokes Some research requires animals to be studied in groups. Of course, this is evident in social interaction studies, but it is also done simply to study each individual's behavior while they are in a group. In both cases, it is very useful to have video tracking software that can automatically track the behavior of multiple animals simultaneously. Xie et al. recently published a study which shows just that. Research on ischemic stroke The study of Xie and his colleagues focuses on strokes. A stroke has a high impact on the individual that suffers from one, as well as on society. The rapid loss of brain function due to insufficient blood flow causes a deficiency in oxygen. This can have a number of consequences, varying from minor to major, such as memory loss, paralysis, or inability to speak. Most strokes are ischemic strokes, meaning that they are caused by a blood clot. Brain tolerance to stroke Evidence shows that brain ischemic tolerance (BIT) can induce a greater tolerance to subsequent injury after stroke, meaning that specific experiences prior to stroke might help in lessening its effects. Xie and his colleagues examined the possible neuroprotective effects of environmental enrichment, prior to cerebral ischemia in adult male rats. A stroke model in rats Rats were divided into three groups. The first group was reared under standard conditions: 4 animals per group in standard cages with each animal receiving sham surgery. The second group was also reared under these conditions, but received surgery (arterial occlusion) resulting in cerebral ischemia. The third group was housed in groups of six in an enriched environment containing barrels, ladders, boxes, and more before receiving the same arterial occlusion surgery. Behavioral testing The study involved a couple of tests, including behavioral tests, such as the testing of motor skills, learning and memory in a Morris water maze test, and locomotor activity. The locomotor experiment was performed both before and after surgery. Activity and movement of each animal was measured automatically with EthoVision XT video tracking software, while animals were housed in groups. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Tracking multiple animals simultaneously For tracking multiple animals simultaneously, researchers used EthoVision XT in combination with the Social Interaction Module. This module allowed researchers to track the behavior of all individuals in the same cage. While this module originally is designed to measure interaction between animals, it is just as useful to simply measure other behaviors of each individual. In this case the variables of interest were: distance moved, velocity, duration of mobility, and frequency of mobility. With or without color markers Researchers used color markers to easily identify the animals, but it is also possible to do this type of research with EthoVision XT without color marking the individuals. Environmental enrichment reduces effects of stroke The rats that were reared in an enriched environment showed fewer neurological deficits as a result of the arterial occlusion, when compared to the rats that were reared in standard cages. While there was no difference found morphologically, environmental enrichment did prove to enhance a variety of motor skills following the ischemic stroke surgery. Spatial learning and memory locomotor activity deficits were also attenuated by the environmental enrichment. Diminishing the effects of a stroke The results of Xie and his colleagues show that enriched rearing conditions prior to ischemia robustly increased locomotor activity. This implies that environmental enrichment and the increased levels of activity it caused act as a kind of protection against the consequences of stroke, effectively facilitating a better recovery from brain injury. References - Xie, H.; Wu, Y.; Jia, J.; Liu, G.; Zhang, F.; Zhang, Q.; Yu, K.; Hu, Y.; Bai, Y.; Hu, R. (2013). Enriched environment preconditioning induced brain ischemic tolerance without reducing infarct volume and edema: the possible role of enrichment-related physical activity increase. Brain Research, 1508, 63-72. --- ## Using several behavioral tests to investigate the role of the NR1 gene in schizo URL: https://noldus.com/blog/behavioral-tests-gene-schizophrenia Published: 2013-07-26 14:02:00 Description: Studies of the mental disorder schizophrenia in lab animals often include behavioral tests to investigate social behavior, cognitive abilities, and motor functioning. Schizophrenia is a mental disorder that causes several deficits: emotional, cognitive, and in motor function. So logically, studies of this disease (in lab animals) often include behavioral tests to investigate social behavior, cognitive abilities, and motor functioning. Recently, Michael Glass and his colleagues did just that - they published a study that describes the use of a sociability test and a novel object recognition test, and used automated video tracking in both to investigate the involvement of a specific gene in schizophrenia. Schizophrenia and the NMDA receptor in the nucleus accumbens The gene in question is the one that encodes the NMDA receptor subtype 1 (NR1). This is an important receptor type found in neurons of the nucleus accumbens, a brain region that is involved in pleasure, addiction, the integration of motivated behaviors, and so on. NR1 is often co-expressed with the dopamine receptor D1R and the opioid receptor µ-OR and seems to have a role in the functioning of the dopaminergic system. This is what makes it an interesting study focus for Glass and his colleagues, because dopamine is a neurotransmitter that is well-known for its regulatory role in movement, emotional responses, and reward-motivated behaviors. Additionally, µ-OR mediates behaviors that are adversely affected by schizophrenia. Gene deletion effects on startle response To investigate the role or NR1, gene deletion technology was used to create a group of mice that lacked the NR1 receptor subtype (NR1del). A sham procedure was used to create a control group. Then an acoustic startle test was performed both before and after injection of apomorphine (dopamine agonist) or saline (as control). Normally, the startle effect of a sound stimulus can be attenuated by a predicting stimulus, such as a shorter sound stimulus. This is called pre-pulse inhibition (PPI) of the acoustic startle (AS) response. Literature shows that activation of D1R by apomorphine produces a reduction in PPI of the AS response in rodents, which is a reliable index of a sensorimotor gating deficit typical for schizophrenia. In the normal mice, without the NR1 deletion, the injection of apomorphine, as compared to saline, significantly reduced the AS response. However, there was no difference in percentage of PPI. The NR1del treated mice did not show a difference in AS nor in PPI between the apomorphine and saline injected subgroups. This suggests that the deletion of the NR1 gene prevented the suppression of AS that apomorphine typically induces. Additionally, immunocytochemistry confirmed a role of NR1 in D1R trafficking. Testing social behavior in the sociability test A sociability test was used to study social behavior among the mice. The test subject was confronted with a novel mouse in a container in the corner of the arena. EthoVision XT 8 video tracking software was used to automatically track the behavior of the mouse during a period of 15 minutes. Variables of interest included latency to approach, frequency of approach, and the time spent in close proximity with the social stimulus. These variables were automatically calculated by EthoVision XT. Because the researchers were able to define different overlapping zones of interest (social stimulus, area surrounding social stimulus, and quarters of the arena) within the software, variables were measured both in respect to direct contact with the social stimulus as well as to a 3cm boundary around the container. The video below illustrates the arena definition in EthoVision XT. Novel object recognition The novel object recognition test was also performed with the help of EthoVision XT 8. It started with a training session, during which the mice were confronted with two identical objects to familiarize. In a first testing round, one (now familiar) object was replaced by a novel object. In the second test, another novel object replaced the second familiar one. EthoVision XT was used to automatically calculate presence variables such as duration, latency, and frequency of contact with the object. The researchers investigated direct contact with the object as well as the mice being detected in a 3cm boundary around the object or that specific half of the arena. Behavioral effects of NR1 gene deletion In literature, NMDA receptors have been shown to play an important role in social behaviors. The sociability test in this study showed that deletion of NR1 indeed impaired social interest. A significant effect was found in the amount of time animals remained in contact with the novel mouse, spent orientated towards the novel mouse, and spent in the same quadrant as the novel mouse. Episodic memory, as tested in the novel object recognition test, was not affected by NR1 deletion. Both the control group and the NR1del group of mice spent significantly more time with the novel object. In an additional locomotor test, no differences were found as a consequence of the NR1 deletion. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free trial References Glass, M.J.; Robinson, D.C.; Waters, E.; Pickel, V.M. (2013). Deletion of the NMDA-NR1 receptor subunit gene in the mouse nucleus accumbens attenuates apomorphine-induced dopamine D1 receptor trafficking and acoustic startle behavior. Synapse, 67(6), 265-279. --- ## The effect attention training has on social anxiety disorder URL: https://noldus.com/blog/attention-training-social-anxiety-disorder Published: 2013-07-24 09:02:00 Description: It is inevitable that everyone will experience anxiety and stress at some point in their lives. Most individuals are able to move past their stress with just a little bit of effort. It is inevitable that everyone will experience anxiety and stress at some point in their lives. Most individuals are able to move past their stress with just a little bit of effort. For those with social anxiety disorder (SAD), this becomes a huge task. The effect attention training has on social anxiety disorder Social anxiety disorder, also known as social phobia, is defined by Bunnell et al. as an intense fear and apprehension of social scenarios in which the individual may be assessed or evaluated by others. This social distress is combined with avoidance of the anxiety-provoking situation, thus creating significant functional impairment for those with this disorder. Brian Bunnell and his colleagues chose to replicate a previous study on attention training that had received positive results, and see if they could replicate these results and also observe any changes in social behavior that might occur as a result. Attention training and SAD Cognitive theories tend to suggest that anxious individuals often tend to direct their attention toward stimuli that relates to their specific concerns, and this can lead to more stress. Therefore, it seems reasonable that in order to reduce stress and anxiety levels in an individual, all that is needed is to train them to focus their attention on something other than the threatening stimuli. This is attention training and in theory, this should work, although recent investigations have found null effects for modified versions of this treatment. This experiment aimed to replicate a previous study (Amir et al. 2009). What was predicted to happen? Following treatment, Bunnell et al. believed that three hypotheses would be met. The first was that the percentage of participants who met diagnostic criteria for SAD in the treatment condition would be significantly lower than those in the placebo condition. The second was that the mean Social Phobia and Anxiety Inventory (SPAI) score for the treatment condition would be significantly lower than that of the control condition. The last hypothesis was that significant decreases in social distress would end up leading to improvement in social behavior during in-vivo social interactions relative to the control condition. One of the important things to note in the results would not be if the results were statistically significant, but if they were clinically significant. How it was done Participants were randomly assigned to one of two groups after a pre-treatment assessment – either Attention Training (AT) or Attention Control (AC). In these tests, participants were instructed to attempt to identify the correct letter probe as quickly as possible while maintaining accuracy. Individuals participated in eight sessions, and then completed a post-treatment assessment, which was identical to the pre-treatment assessment. In order to assess social anxiety and behavior, the tests were recorded with video and audio. Behavior was coded by independent raters using The Observer XT. What happened Emmelkamp said "There is no robust evidence that attention training is of clinical value" (2012). The results of the Bunnell et al. study support this statement. Rather than having positive findings for attention training, all of the participants in the study met DSM-IV-TR criteria for SAD at post-treatment regardless of the treatment they received. It had been expected that at least a few participants would no longer meet criteria for SAD, but this first hypothesis was proven false. Also, scores on the SPAI consistently did not differ between the two conditions at post-treatment though the second hypothesis had predicted that the scores would, even when accounting for any pre-treatment differences. And although there was a statistically significant difference found for the amount of talking time by individuals in different groups in the test, this was not clinically significant as well. The participants in the study all reported experiencing distress and avoidance in social situations, and not many noticed any positive change in their condition, unlike the third hypothesis's predictions. All of the participants requested additional treatment. Significance In theory, attention training seems like a good way to treat SAD. However, in practice, the positive results of Amir et al. have not yet been replicated. The results of the tests did not vary from group to group, except on time spent talking and that was not clinically significant. This matches up with other recent tests on attention training and their conclusion – attention training does not have a large positive impact on those who suffer from SAD. So what does? More research is needed in this area. And, since Amir et al. found positive results, scholars could look into that study to find out if there were any other factors influencing the results other than the stimuli presented. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - Amir, N.; Beard, C.; Taylor, C.; Klumpp, H.; Elias, J.; Burns, M.; Chen, X. (2009). Attention training in individuals with generalized social phobia: a randomized controlled trial. Journal of Counseling and Clinical Psychology, 77, 961-973. - Bunnell, B.E.; Beidel, D.C.; Mesa, F. (2013). A randomized trial of attention training for generalized social phobia: does attention training change social behavior? Behavior Therapy, doi: 10.1016/j.beth.2013.04.010 - Emmelkamp, P.M.G. (2012). Attention bias modification: the Emperor's new suit? BMC Medicine, 10(63), 1-3. --- ## Mice with Alzheimer’s disease walk well but remember poorly URL: https://noldus.com/blog/mice-alzheimers-disease Published: 2013-07-18 14:56:00 Description: A large number of genetically engineered mouse models are available to study different aspects of Alzheimer’s disease. Modeling Alzheimer's disease A large number of genetically engineered mouse models are available to study different aspects of Alzheimer's disease. APP/PS1 knock-in mice are mice in which two genes associated with the disease are inserted at a specific place in the genome. Much is known about the development of the disease in these mice. But until recently, there was less detailed knowledge on behavioral changes in APP/PS1 knock-in mice that are associated with the disease. Alzheimer's disease and symptoms It is very well known that Alzheimer's disease affects the memory of people. But the disease can also affect other behavior. People with Alzheimer's disease may be more anxious, can be depressed and can lose initiative and interest when the disease proceeds. Locomotor deficits may also occur, like a lower walking speed and a more variable stride rhythm. Behavioral testing To determine what behaviors are affected in APP/PS1 knock-in mice by the progressing disease, Webster et al. carried out a large number of standard tests with mice of 7, 11, 15 and 24 months old. Laboratory mice have an average life span between 1.5 and 2.5 years. To see whether locomotor behavior was affected, they used a rotarod, performed a grip strength test, a beam walk test, and analyzed the distance moved and velocity in an open field test. To test whether anxiety was affected, they analyzed the time spent in the center of the open field and performed an elevated plus maze test. The authors also carried out a radial arm water maze with platforms in three of the arms, to investigate spatial memory. In addition to this, they did a novel object recognition test to investigate recognition memory. Automating standard tests EthoVision XT video tracking and analysis software was used for the open field test, the elevated plus maze test, the radial arm water maze and the novel object recognition test. EthoVision XT automatically analyzed the distance moved, velocity, time spent in different zones and the time the nose of the mice was in proximity of the objects. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Locomotor behavior and anxiety The locomotor behavior was not affected in any of the test that focused on that behavior. Also no effect on anxiety was found in the open field test, or the elevated plus maze test. Spatial and recognition memory In contrast to the lack of effect on locomotion and anxiety, the memory was clearly affected. This effect depended on the age of the mice and therefore the severity of the disease. APP/PS1 knock-in mice of 7 month performed equally well in the radial arm water maze test as the wild type mice. However, knock-in mice of 11 months old made more errors than wild type mice of the same age. This effect became larger when the mice were older and the disease progressed. The APP/SP1 knock in mice also failed to show interest in novel objects in the novel object recognition test. But this effect only became apparent when the mice were 15 months old. Selecting the correct model The results show that only memory is affected by the disease in this mice model. Spatial memory is affected at an earlier stage of the disease than recognition memory. This is in agreement with results of other studies and with other Alzheimer's disease models. However, in other models in some cases also locomotor behavior or anxiety is affected by the disease. The authors conclude that none of the currently available mice models shows all symptoms related to Alzheimer's disease. Researchers should therefore carefully select an appropriate model for their specific research question. References Webster, S.J.; Bachstetter, A.D.; Van Eldik, L.J. (2013). Comprehensive behavioral characterization of an APP/PS-1 double knock-in mouse model of Alzheimer's disease. Alzheimer's research & therapy, 5(28), doi:10.1186/alzrt182. --- ## Relational Agents: the use and testing of avatars for HCI URL: https://noldus.com/blog/avatars-human-computer-interaction Published: 2013-07-16 16:22:00 Description: Relational Agents (RAs) are computer constructs designed to interact with humans in a way that promotes the long-term formation of social and emotional bonds. Relational Agents (RAs) are computer constructs designed to interact with humans in a way that promotes the long-term formation of social and emotional bonds. Integrating social psychological principles of relationship building such as empathy, shared self-disclosure and emotional feedback into the RA interface helps to establish these bonds. Relational agents Relational agents are generally created with an anthropomorphic (i.e. human-like) form that may be more or less realistic, varying from cartoon-like two-dimensional drawings to animated three-dimensional models developed with advanced graphics software. This type of model, or avatar, is known to most as a character representation found in third-person video games in which the game player character is visible. However, RAs are usually limited to frontal views from the shoulders or neck up due to constraints imposed by limits on computer processing power and the simulation capabilities of artificial intelligence algorithms. The video shown here was created as a final project for a Motion Capture class at New York University, and is intended to illustrate the potential uses of RAs as well as methods for testing the acceptance of such agents by their target audience. MoCap Final Overview from Crystal Butler on Vimeo Promising areas of application for RAs One of the most promising areas of application for RAs is in the provision of health care diagnostics and therapy. Researchers at the Relational Agents Group of Northeastern University in Boston, Massachusetts, USA have been developing avatars for staff and patient support services in hospitals and the home [1]. Mental health care may also improve with the deployment of computer-based agents, especially for underserved populations in rural areas and impoverished regions where access to providers is inadequate. Scientists - Lisetti and colleagues have been working on a behavioral change system that targets problems more likely to be found in these groups, such as obesity and the abuse of legal and illegal drugs [2]. The avatar featured in the video link for this post is intended to target a specialized domain of mental health: caregiver sensitivity. Healthy emotional development during a child's first two years of life is crucial to establishing a solid foundation for future wellness, and is largely determined by attachment formation based on caregiver-infant interactions. Since communication during this period of a child's life is nonverbal, sensitivity and responsiveness to cues such as facial expressions are key to providing good childcare. The video demonstrates how a simulated infant could be created for assessing whether a caregiver responds appropriately to designated facial expressions. RA's and facial expression recognition Other fields that could effectively employ RAs include teaching and security. Facial expression recognition has been researched at the Machine Perception Laboratory at the University of California, San Diego, as a means of interpreting the perceived difficulty level of a lecture [3]. A computerized tutoring system with an interactive agent could respond empathetically to facial expressions correlated with student distress and ask whether the student needs, for example, to review the material again or get additional help. Facial expressions are already being employed as one of several biometric measures used to evaluate truthfulness and detect threat in a test of an RA system at the United States border [4]. The creators built their software into kiosks that display a simulated human face, which asks the viewer a series of questions based on those used by border patrol agents. It is meant to elicit the same automatic physical indicators of deception displayed when talking with a real person, such as changes in blink rate, stance, or alterations in vocal stress. Influencing factors A crucial step in establishing the effectiveness of any RA interface is testing acceptance by the target audience, or intended users. Many factors can influence how individuals react to computer agents, including comfort with technology, ease of use, the avatar's apparent race, gender, and age, cultural appropriateness, and avatar personality type. As indicated by the work of Bickmore and colleagues [5], a contextually correct, well-designed RA may even be preferred to its human counterpart. A product such as FaceReader [6] could be useful in evaluating user responses to RAs by providing information on their emotional reactions and comparing them to those seen in real life, face-to-face communication. By Crystal Butler Master's of Computer Science Candidate, New York University VicarVision Intern, Amsterdam NL RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources - Relational Agents Group: http://relationalagents.com/ - Lisetti, C.; Yasavur, U.; de Leon, C.; Amini, R.; Rishe, N.; Visser, U. (2012). Building an on-demand avatar-based health intervention for behavior change. Proceedings of FLAIRS 2012. - Whitehill, J., Bartlett, M., & Movellan, J. (2012). Automatic facial expression recognition for intelligent tutoring systems. - Higginbotham, A. (2013). Deception is futile when big brother's lie detector turns its eyes on you. Wired. Retrieved from http://www.wired.com/threatlevel/2013/01/ff-lie-detector - Bickmore, T., Mitchell, S., Jack, B., Paasche-Orlow, M., Pfeifer, L., & O'Donnell, J. (2010). Response to a relational agent by hospital patients with depressive symptoms. Interacting with Computers, 22, 289-298. - FaceReader: https://www.noldus.com/facereader --- ## Circadian rhythmicity and other behavioral studies URL: https://noldus.com/blog/circadian-rhythmicity-behavioral-studies Published: 2013-07-09 12:32:00 Description: Many labs use video tracking software to increase the efficiency of their research. In fact, EthoVision XT video tracking software has just reached an impressive milestone: 2000 sites worldwide. Many labs use video tracking software to increase the efficiency of their research. In fact, EthoVision XT video tracking software has just reached an impressive milestone: 2000 sites worldwide. I spoke with Dr. Ilia Karatsoreos, who placed the order, and found out that he was helping to furnish a completely new facility at the Washington State University, and does some very interesting research. (Image courtesy of Lara Swimmer Photography.) Integrative and neuroscience based work Dr. Karatsoreos is part of the Department of Integrative Physiology and Neuroscience, and they just moved into a new, state-of-the-art facility in Pullman, Washington. The department itself also just got a name change to "align our identity with the current work that is going on in the department. The work of the labs here is quite clearly 'integrative' and neuroscience based", he tells me. Core lab The department is furnishing a core lab to facilitate the works of several labs. Dr. Karatsoreos explains a bit about the work of some of his colleagues: "Dr. Joseph Harding's lab studies neurodegenerative disorders such as Parkinson's Disease, and are working on developing new therapeutics to reverse the damage caused by this and other age related neurodegenerative disorders. His lab does cognitive tasks such as the water maze, and the Barnes maze, as well as gait analysis and motor control tasks to determine the broad effects of the diseases and their treatments. His lab is very excited about the automated gait analysis provided by CatWalk XT." A wide range of studies "The lab of Dr. Suzanne Appleyard is interested in how parts of the feeding and energy balance circuits regulate other motivated behaviors. Dr. Jun Xu's lab is interested in how various genes, particularly sex linked genes, that contribute to mental retardation affect both behavior of the whole animal in terms of social behaviors, anxiety, and aggression, as well as how neural tissues develop in vitro and in vivo." Circadian rhythmicity The research of Dr. Karatsoreos focuses on circadian rhythmicity and how disturbances in this rhythmicity can cause mental and physical health problems. He will be making regular use of the water maze, elevated plus maze, and open fields, in combination with EthoVision XT video tracking software. "My research asks the fundamental questions of 'what are the functions of clocks in the brain and the body, how do they help maintain optimal function and good health, and how to they contribute to mental and physical disorders when they malfunction?'" FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Link between disrupted rhythmicity and disorders As Dr. Karatsoreos explained to me, in the world of today, we seem to have broken the link between our internal biological clock and that of the external light-dark cycle. In the last decades, we have been more and more exposed to electric lights, television, computers, tablets, and so on. We have even introduced a work cycle around the clock. Along with this, you can see a dramatic increase in obesity and metabolic disorders. "There are links between altered sleep, poor sleep quality, and disrupted circadian rhythms in numerous neuropsychiatric disorders, from Alzheimer's to Huntington's to depression, and even in Post-Traumatic Stress Disorder. Part of my work is based on the hypothesis that disrupted clocks are not merely a symptom of these disorders, but may be a precipitating cause as they decrease an individual's resilience to stressors in the environment." Promise in basic research So how does his research on circadian rhythmicity translate to and from animal research? Dr. Karatsoreos explains that they are still in the early stages of understanding the similarities between the effects seen in experimental animals and humans. But our circadian clocks have been highly conserved between species over millions of years, so there is great promise in basic research. As links are already found between altered rhythms of 'clock genes' and shift work, obesity, and psychiatric disorders in humans, a two-front approach will help uncover potential treatments sooner. Read more - For more information on Noldus' solutions for animal behavior research, click here. --- ## Playing virtual games with frames URL: https://noldus.com/blog/frames-display-influences-behavior Published: 2013-07-04 13:49:00 Description: For public displays nowadays, we are no longer limited to traditional square and flat designs. More wild and appealing forms like curves, spheres, or columns are now possible as well. For public displays nowadays, we are no longer limited to traditional square and flat designs. More wild and appealing forms like curves, spheres, or columns are now possible as well. Wild and appealing public displays People that pass by such displays may behave differently than when they see a traditional square and flat one. This effect may be unwanted and people might miss important information on the display because they mainly look at other eye-catching parts. But it also offers interesting possibilities to manipulate the people passing by the display. If you know how the display shape influences people, you can use this knowledge to optimize information transfer. Games with frames Beyer et al. [1] investigated in a recent paper whether the presence of frames influences the behavior of people in front of a display. In a human computer interaction (HCI) study, they displayed a virtual game on a large cylinder. Using Microsoft Kinect, they projected cartoon-like images of the people around the cylinder onto it. These images could throw colorful balls at each other in response to the real movements of the people. The projected image on the cylinder was completely seamless and, while gaming, people could move around freely. The image on the cylinder either contained large projected rectangular frames, or no such frames. The people gaming were recorded and video files were created with MediaRecorder. To allow systematic behavioral observations, the videos were imported into scoring software The Observer XT and the positions of the people around the cylinder were coded. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Unconsciously affected People distributed themselves freely around the virtual games cylinder when no rectangular frames were projected. However, when the frames were present, people positioned themselves in front of the middle of the frames. When two people arrived at the same time, they often positioned themselves behind each other in front of the center of the same frame. They did so even if this impaired each other's movements. Alternatively, both persons positioned themselves in front of the center of a separate frame, also if this meant that they were standing too far from each other to play the game well. Interestingly, among the 79 people that were interviewed afterwards, only one actually recalled having seen the frames. Manipulating with frames These results show that people can be manipulated by the shape of a display. The authors suggest that you can use frames to position people, for example, to create a certain distance between them. On the other hand, you should not use frames if you want people to stand closer to each other and cooperate in gaming. As a conclusion, display shapes and frames offer interesting possibilities for directing people to a certain place while they are completely unaware of this. Reference Beyer, Gilbert, et al. "Squaring the circle: how framing influences user behavior around a seamless cylindrical display." Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2013. --- ## Combining physiology and behavior to create a stress scale for horses URL: https://noldus.com/blog/stress-scale-horses Published: 2013-07-02 14:30:00 Description: We all are familiar with stress, and how it can have an impact not only on our behavior, but on our bodies and physiology as well. Many people get stress headaches or start to feel sick if they reach high levels of stress. We all are familiar with stress, and how it can have an impact not only on our behavior, but on our bodies and physiology as well. Many people get stress headaches or start to feel sick if they reach high levels of stress. However, most studies use scales which focus on behavioral scores for animals and don't account for the physiological responses to stress. Young et al.'s goal was to create a scale that could rapidly and reliably measure stress in domestic stable horses while integrating both behavioral and physiological measures. Mixed results in previous studies One thing to note is that there have been mixed results in studies which have tried to correlate physiological measures with behavioral measures. Some studies have had success and found links between the two, where others have found no link or correlation between the behavioral and physiological measures they were studying.  Using husbandry routines for evaluating stress For this study, a sample of 32 horses (a mixture of various breeds of mares and geldings) were used, and all of the horses were kept on similar exercise and management routines. The goal was to use behavioral and physiological measures to analyze stress levels in domestic horses during everyday husbandry routines. The four husbandry procedures used in this study were the sound of electric coat clippers, social isolation, grooming procedures, and the sound of fireworks played on a CD. Each husbandry procedure lasted 10 minutes, the amount of time researchers predicted that a stress response would occur in. Recording behavior using The Observer XT The behavior of the horses during the husbandry procedures was recorded on video and The Observer XT was used for 12 horses to analyze the first five minutes of the behavioral reaction to the husbandry procedure. (This used a pre-defined ethogram, which can be found in the paper.) A panel of 13 expert members was also compiled. These panel members gave behavioral scores of 1-10 on how stressed they thought the horse was. They were also asked to describe the horse's behavior at this score and to note when they thought the onset of stress occurred.  FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Physiological measures The physiological measures used in this experiment were heart rate and salivary cortisol, because these were able to be noted through non-invasive means. For both, a control group was also used to make sure the procedures used for measuring these didn't affect the stress level of the horses. Heart rate was noted directly before the procedure and five minutes into it. Saliva was collected several times before and after the husbandry procedure. Principal component analysis, a mathematical procedure which reduces a complex data set to values that are simple and easier to understand, was used to look for links between behavioral and physiological changes. Making a scale The descriptive terms given by the panel members were combined for horses with the same behavioral scores. Based on the behavioral scores given, researchers determined three levels of stress – no stress, low stress, and medium stress (the high stress category was added later by researchers but was not observed). For no stress, the horse had to have a behavioral score of 1 or 2, for low stress, a score of 3 or 4, and medium stress was 5 and up. Principal component analysis did not include behavioral scores for a fourth level, but researchers also added a category for high stress, which were behavioral scores of 8-10. A scale reflecting behavioral and physiological stress This study was successful in creating a scale that used physiological measures to add to the behavioral measures used to determine stress in domestic stable horses. It was found that with the husbandry procedures of the sound of fireworks being played and grooming, the salivary cortisol levels were higher than when the clippers were on or the horse was socially isolated. This led Young et al. to determine that there was a correlation between salivary control and the same horse's behavioral score during husbandry procedures. This confirmed that the final scale created reflected both behavioral and physiological stress, and can be used as a valuable cost-effective tool. - Young, T.; Creighton, E.; Smith, T.; Hosie, C. (2012). A novel scale of behavioural indicators of stress for use with domestic horses. Applied Animal Behaviour Science, 140, 33-43. --- ## Plants with more linalool smell good, but taste bad URL: https://noldus.com/blog/insect-studies Published: 2013-06-28 13:41:00 Description: Plant volatiles play an important role in the interaction between plants and insects that eat them. Insect damage very often induces plants to produce volatiles. The importance of plant volatiles Plant volatiles play an important role in the interaction between plants and insects that eat them. Insect damage very often induces plants to produce volatiles. These volatiles can improve the plant's defense against insect herbivores. But they can also help the plants indirectly by attracting natural enemies of the plant eating insects. Investigating linalool Linalool is a volatile chemical that is produced by plant leaves in a wide variety of plant species, when they are damaged by insect herbivores. Yang et al. [1] investigated the effect of linalool on Western Flower Thrips (WFT, Frankliniella occidentalis), a common insect pest in greenhouses. They used several transgenic chrysanthemum plant lines that had a higher linalool production than wild type chrysanthemum. The transgenic plants also had a higher concentration of non-volatile linalool derivatives in the leaves. Testing attraction by linalool To test the effect of linalool, dual choice tests were done with leaf discs from wild type plants and plants that produced more linalool. Adult WFT were released on a metal wire in between the two leaf discs. The distribution of WFT was scored several times until 28 hours after release. Initial attraction, but then repellence Immediately after release, WFT preferred plant lines with enhanced linalool production over the control plants. But this effect disappeared after one hour and was reversed after 20 hours. The WFT then preferred the control plants over the plants that produced more linalool. Testing plant extracts To test whether this effect was caused by non-volatile linalool derivatives in the leaves, the authors made leaf extracts from the different plant lines. Adult female WFT were kept in wells that were covered with Parafilm. Two droplets of plant extracts were applied on the Parafilm of each well, one from the wild type plants and one from the plants with enhanced linalool production. The concentrations of linalool derivatives resembled the concentrations found in the leaves. Videos of 40 minutes were made right at the start of the experiment and after 4 and 24 hours. The videos were analyzed with EthoVision XT tracking and analysis software. The areas of the droplets were defined as zones and the time the WFT spent on the downside of the Parafilm under each droplet, was analyzed automatically. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Repellence by linalool derivatives The WFT had no preference at the start of the experiment for either the control plants or the plants that produced more linalool. After 4 and 24 hours the thrips spent more time under the droplets from the control plants than under the droplets from the plants with a higher linalool production, but this effect was only significant after 24 hours. Smelling good but tasting bad The authors conclude that the plants that produce more linalool smell good for WFT, because the insects are initially attracted to these plants. But apparently they do not taste as good as wild type chrysanthemum plants. The attraction already disappears after one hour and after 20 hours the attraction reverses and the thrips are then repelled by plants with enhanced linalool production. It also takes 24 hours before the thrips develop a preference for leaf extracts from control plants over extracts from plants with an enhanced linalool production. The authors hypothesize that an induced physiological response in the thrips may occur, which would explain why it takes time before the thrips are repelled. This repellence is in agreement with previous findings that plant volatiles that are produced in response to insect damage play a role in plant defense against these insect herbivores. References Yang, T.; Stoopen, G.; Thoen, M.; Wiegers, G.; Jongsma, M.A. (2013). Chrysanthemum expressing a linalool synthase gene 'smells good', but 'tastes bad' to western flower thrips. Plant Biotechnol. J., doi: 10.1111/pbi.12080. --- ## Pesticides in bee colonies affect the behavior of bees URL: https://noldus.com/blog/pesticides-in-bee-colonies Published: 2013-06-25 13:21:00 Description: In the past 20 years, populations of honeybees have declined all over the world. This is partly caused by the increased occurrence of parasites and pathogens. In the past 20 years, populations of honeybees have declined all over the world. This is partly caused by the increased occurrence of parasites and pathogens. But the use of pesticides may also affect honeybee health. Pesticides accumulate in bees' food to such levels that the behavior of the bees is affected. Pesticides in beehives Some pesticides are applied in the hives directly, for example to control parasites like Varroa mites. Other pesticides are transferred from crops to the hives by the bees themselves. Some compounds can accumulate in the comb wax to very high levels. Observing bee behavior after pesticide consumption Williamson et al., [1] investigated the effect of several pesticides on the behavior of honeybees. The authors used The Observer XT to observe honeybees. They studied four different pesticides and applied doses that are actually found in the bees' food. To observe behavior, the authors recorded the duration and frequency of walking, flying, falling upside down, grooming the head, grooming the body and unusual abdominal spasms including expulsion of fecal material. Pesticides affect bees' behavior Bees treated with the pesticide chlorpyrifos spent less time walking, were more often upside down and had more abdominal spasms than bees in the control group. Other pesticides had a similar effect on the bees' behavior, but this was not statistically significant. The effect of the chlorpyrifos on the bees was dependent on the season the bees were collected. Bees collected in winter did not have more abdominal spasms after pesticide treatment, while bees collected in summer did. All four pesticides increased the frequency of head grooming and body grooming by the bees, independent on the season in which the bees were collected. Pesticides affect colony health? The behavioral observations show that consumption of pesticides in concentrations that were previously reported in bees' food affect the bees' behavior. Dramatic behavioral changes like difficulty to righting themselves after falling over and abdominal spasms, including expulsion of fecal material and regurgitating food, occurred in all groups treated with pesticides, but never in control bees. This implies that the gut function is disrupted by pesticide treatment. Also a more subtle behavior like grooming was affected by pesticide treatment. Indeed, pesticides accumulate in bees' food to such levels that consumption affects the bees' behavior. All these behavioral changes can result in decreased colony health and can possibly partly explain the worldwide decline in honeybees. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - 1.Williamson SM, Moffat C, Gomersall MAE, Saranzewa N, Connolly CN and Wright GA (2013) Exposure to acetylcholinesterase inhibitors alters the physiology and motor function of honeybees. Front. Physio., 4 (13). - 2.Mullin, C. A., Frazier, M., Frazier, J. L., Ashcraft, S., Simonds, R., Vanengelsdorp, D., et al. (2010). High levels of miticides and agrochemicals in North American apiaries: implications for honey bee health. PLoS ONE, 5:e9754. doi:10.1371/journal.pone.0009754 --- ## Determining the effect of social hierarchy on foraging in coyotes URL: https://noldus.com/blog/effect-social-hierarchy-coyotes Published: 2013-06-14 11:49:00 Description: Whether it’s an older sibling taking the last piece of cake from their younger sibling or a dominant coyote shoving a subordinate out of the way so it can eat the food, nature has its hierarchies. Whether it's an older sibling taking the last piece of cake from their younger sibling or a dominant coyote shoving a subordinate out of the way so it can eat the food, nature has its hierarchies. Generally, the stronger individual is at the top of the food chain – for example, the older sibling or the dominant coyote. Getting to the resource first doesn't matter if you can't defend the resource, as can be seen very well in the example of coyotes. Even if the subordinate coyote discovers the food source, the dominant will still monopolize the food there. Dominant or subordinate? Recently, a study was done by scientists in Millville, Utah, to investigate the effects of social hierarchy on the foraging efficiency of an individual. Eight pairs of coyotes (one male and one female in each pair) were observed in order to determine the effects of a dominant and subordinate being paired in the hunt for food. Before scientists could observe the coyotes, though, they had to determine which of the coyotes was dominant and which was subordinate. Winner-loser trials were used to test dominance, by letting the pair have a single food source and see which of the coyotes was displaced from the food. Recording and analyzing behavior Scientists used Noldus The Observer XT software to record the behavior of the coyotes. Data was broken down by noting if the coyote entered the correct quadrant of the test area first, and if the coyote went to the correct feeder first. Researchers focused on the difference in number of times it took the subordinate to go to the correct feeder in individual and pair trials, to see if the presence of a dominant coyote had an impact on foraging efficiency. The data was used to determine if the foraging habits of a coyote differs when it is by itself and when it is in a pair. Possible strategies Researchers predicted that the subordinate coyotes would either just go for the food and eat as much as possible before being displaced by the dominant (direct strategy) or would purposely avoid the feeder until the dominant coyote had gone away (discursive strategy). They also predicted that in response, the dominant would either displace the subordinate and monopolize the food source (exploitative strategy) or go off on its own to find food (independent strategy). What happened Subordinate coyotes, when tested individually, showed ability to learn where the correct feeder was and improve foraging efficiency. However, when the dominant was also in the pen, though the subordinate went to the correct quadrant first most of the time, it spent more time going to the wrong feeders before the correct one. The attempt to use direct strategy was held up by a reduction in the ability to relocate the feeder accurately when paired with the dominant coyotes. At first, the dominant coyote used independent strategy, but immediately after the subordinate had found the correct feeder, the dominant switched to the exploitative strategy, and the subordinate did not make any moves to defend the food it had found, and did not adapt its strategy over time to keep the resource it had found to itself. The presence of the dominant coyote made the subordinate's foraging and relocation accuracy decrease, showing a large impact on subordinate behavior due to social hierarchy. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Reference Gilbert-Norton, L.B.; Wilson, R.R,.; Shivik, J.A. (2013). The effect of social hierarchy on captive coyote (Canis Iantrans) foraging behavior. Ethology, 119, 335-343. --- ## Developing a high-throughput method - EthoGenomics URL: https://noldus.com/blog/high-throughput-method-ethogenomics Published: 2013-06-11 11:40:00 Description: Ornamental flowers are among the main export products of The Netherlands. Thrips are one of the most important pests on ornamental flowers. Flowers and pesticides Ornamental flowers are among the main export products of The Netherlands. Thrips are one of the most important pests on ornamental flowers. Not only do thrips damage the flowers and the leaves, but they can also infest the plants with devastating plant viruses. Therefore, very strict export regulations apply for the presence of these pest insects and the damage they cause on the plants. This traditionally led to the use of a high amount of pesticides with ornamentals. But pest species become resistant to pesticides over time and, in addition to this, we do not want our flowers covered with pesticides. Breeding for flowers without pesticides There is tremendous natural variation in plant mechanisms for defending themselves against insects. This offers a rich source of possibilities for breeding for plant varieties that are better protected against pest insects. Breeding for plant resistance to pest insects can cause a large decrease in the use of pesticides on ornamental crops. This way we can produce cleaner flowers. Handling these tiny thrips is tedious A large amount of crop lines needs to be screened to select crop varieties with resistance to insects. At present, damage to the plants is mainly what is scored in screening for host plant resistance. However, many different factors influence the damage on the leaves. This complicates breeding for plants with lower damage. For breeding for host plant resistance it is important to understand the mechanisms of resistance. To start, the behavior of the pest insects on the leaves should be studied. However, adult thrips are 1-2 mm in size. Therefore, determining the behavior on different crop lines is extremely labor intensive. If analyzing the behavior of these very small insects could be automated, it would increase the speed at which crop lines are screened tremendously. Developing a high-throughput method EthoGenomics is a collaboration project in which Wageningen University and Research Centre, Noldus Information Technology, and the plant breeding company Royal van Zanten BV work together in order to develop a high-throughput method to screen for host plant resistance. Manus Thoen and Karen Kloth, both PhD students at Wageningen University, are currently working on the project. Manus Thoen is developing the high-throughput screening method for thrips resistance. EthoVision XT is used to automate the analysis of thrips behavior on Arabidopsis thaliana plant lines. With EthoVision XT, dual choice tests can be carried out in which the preference of the thrips for hundreds of plant lines can be compared with a reference plant line. The first choice of the thrips, the time spent on both plant lines, and the walking speed can be determined automatically. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial High throughput screening for resistance At present, Manus Thoen is able to carry out 35 dual choice tests simultaneously. This means that he can screen many plant lines in a short time. This way, Manus will select a number of varieties that are extremely different in thrips resistance. Then, the genetic and metabolic characteristics of these varieties will be determined and correlated to thrips resistance. Hopefully, he will identify genes that are involved in thrips resistance that can then be used to breed thrips resistant plants. We are well on our way to produce flowers that are a lot cleaner than they used to be. More information is available on the EthoGenomics website. --- ## Predicting Advertising Effectiveness: Facial Coding of 120.000 Video Frames URL: https://noldus.com/blog/predicting-advertising-effectiveness Published: 2013-06-06 14:58:00 Description: The advertising and marketing companies have just received a new addition to their repertoire of the neuromarketing tools – automated coding of facial expressions of basic emotions. The advertising and marketing companies have just received a new addition to their repertoire of the neuromarketing tools – automated coding of facial expressions of basic emotions. Three researchers from the Amsterdam School of Communication Research (ASCoR) at the University of Amsterdam (UvA) have demonstrated that the specific patterns of facial expressions partially explain the advertisement's effectiveness in the amusing persuasive video stimuli [1]. This study was conducted on a crowdsourcing platform – yielding more than 120.000 frames of facial video-reactions, which in turn were analyzed within a few hours by a facial coding system called FaceReader [2]. Automatic analysis for facial expressions The software allows automatic analysis for facial expressions of happiness, surprise, sadness, fear, anger, and disgust in a fraction of the time that it would take a team of the independent human facial coders. In the past, it could have taken up to two or three months of tedious manual coding. RESOURCES Read more about FaceReader Find out how FaceReader is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources The study was published in the conference proceedings of 9th Annual NeuroPsychoEconomics Conference, with a theme "Bridging Boundaries: Applying Neuroeconomics to Medicine, Social Science and Business," on 6th June, 2013 in Bonn, Germany by Association for NeuroPsychoEconomics. In the study, ninety U.S. based participants were asked to watch three advertisements that differed in how amusing they were while their facial reactions were video-recorded. After being exposed to the video, they were asked to fill out a self-report on how much they enjoyed the ad and if they liked the presented brand. Facial reactions vs. self-report The researchers - using FaceReader – have analyzed the underlying patterns of the facial reactions and related them to the self-reported scores of the advertisement's effectiveness. Excitingly, they found that the scores on the facial expressions of happiness explain as much as 37% of the variance in the self-reported scores of the attitude toward the ad – the core measurement of the advertisement's effectiveness – in the most amusing video ads. Happiness explained attitude toward the brand Although the other basic expressions did not contribute to predicting attitude toward the advertisement and the brand in the amusing persuasive stimuli, happiness did partially explain attitude toward the brand. Furthermore, FaceReader could have reliably distinguished between high, medium, and low amusing persuasive video advertisements. Importantly, the researchers have also come up with a novel way of linking the FaceReader's continuous interpretation of the subjects' facial expressions with a punctual, static, dependent variable that is the advertisement's effectiveness. However, they also argue that more research is needed, especially testing, if other types of affective stimuli (e.g. gloomy, disgusting, scary, etc.) can be related to constructs typically studied in the advertising research (such as intention to purchase or the actual buying behavior). They also highlight the importance of the cross-validation of FaceReader with other commonly used measures such as AdSAM®, PrEmo or the facial EMG. Conclusion This recent study contributes to the growing field of the affective consumer neuroscience, analyzing important data of facial reactions to predict the advertising effects. The experiment strength was the use of the crowdsourcing platform, where it was possible to record the participants in their natural environment, their homes and offices – the usual places where the consumers watch the persuasive video materials. The material gathered through such platforms is often of poor quality, as it is not possible to control perfectly for the recording conditions as in a laboratory settings. The poor lighting conditions and technical failures on the part of the end-user made it exceptionally hard to analyze the collected material. However, FaceReader has proved to handle this impoverished data exceptionally well, and allowed the researcher to perform a fast, reliable, and automated analysis of facial expressions and basic emotions. By Peter Lewinski PhD Candidate – Amsterdam School of Communication Research, UvA Marie Curie Research Fellow – Vicarious Perception Technologies, B.V. Early Stage Researcher - CONsumer COmpetence Research Training, FP7 - P. Lewinski, E.S. Tan & M.L. Fransen (2013). Predicting advertising effectiveness by facial expressions in the amusing persuasive stimuli. In B. Weber, M. Reuter, A. Falk, M. Reimann & O. Schilke (Eds.), 2013 NeuroPsychoEconomics Conference Proceedings (pp. 45-45). Bonn, Germany: Association for NeuroPsychoEconomics. ISSN: 1861-8243 Databases: EBSCO, Review: double-blind, peer-review. - Noldus. (2013) FaceReader: Tool for automatic analysis of facial expression: Version 5.0.15. Wageningen, The Netherlands: Noldus Information Technology B.V. --- ## How to analyze nurse-patient consultations URL: https://noldus.com/blog/how-to-analyze-nurse-patient-consultations Published: 2013-06-03 15:27:00 Description: Efficient and effective communication is necessary in doctor-patient as well as nurse-patient consultations. Efficient and effective communication is necessary in doctor-patient as well as nurse-patient consultations. When listening to a patient, the professional uses the information given to organize care, diagnostics, or treatment, and utilizes skills which are crucial in these professional conversations, such as summarization as a check on correct interpretation. Good communication is key Communicating at the right level is of great importance, but to do so, the professional needs to know what level the patient is at. To explain further: when changing behavior, such as an unhealthy lifestyle, a patient might not be ready to receive, understand, and process certain messages at the start of an intervention program. However, he or she will more likely be ready closer to the end of the intervention program. To find out how these communication processes work in a real-life situation, Dr. Janneke Noordman and colleagues recently analyzed a large number of practice nurse-patient consultations. They were particularly interested in if and how nurses adapt their motivational interviewing techniques to the patient's readiness to change. Motivational interviewing is a patient-centered directive approach to enhance intrinsic motivation to behavioral change. In this case, nurses discussed behaviors such as smoking, alcohol use, dietary habits, and/or physical activity with their patients. Observe behavior in an unobtrusive way By positioning an unmanned camera in the consultation room, the researchers were able to record all interactions on video in an unobtrusive way. Next, they analyzed the videos using The Observer XT coding and analysis software. Behaviors related to general communication skills (such as exploration and summarization), phase related communication skills (such as introduction and evaluation), and medical aspects (such as physical examination) were scored making it possible to analyze all interactions in an accurate and reliable way. The analysis revealed that the nurses did adjust their communication skills to the patient's level of readiness to change, but only to some extent. The nurses, for example, applied motivational interviewing skills more to patients in the preparation stage compared to consultations with patients who were in a further stage. However, where they could have adjusted more, they only adjusted one generic communication skill ('summarization') to the patient's readiness to change. Identify the state of change In conclusion, Noordman et al. suggest that it is important to teach nurses to explicitly identify the patient's state of change in order to further enhance and adapt their motivational interviewing skills and general communication skills to the individual patient. More nurse-patient interaction That's not all; there is more observational research in nurse-patient interaction. In a recent blog post, a study by Kim and Woods (2012) published in Geriatric Nursing was featured. They looked into social interactions between direct-care staff and Korean Americans with dementia, and developed two social interaction coding schemes to measure the dementia-competent social interaction and culturally-competent social interaction of direct-care staff in this Korean American nursing home. Kim and Woods coded behaviors on handheld devices. Handheld devices with Pocket Observer installed don't attract much attention, are easy to use, and can easily be combined with The Observer XT research software to further analyze the collected data. They concluded that more research is needed to validate the coding schemes. Interested? Read this blog post. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - Noordman, J.; Vet, E. de; Weijden, T. van der; Dulmen, S. van (2013). Motivational interviewing within the different stages of change: An analysis of practice nurse-patient consultations aimed at promoting a healthier lifestyle. Social Science & Medicine, 87, 60-67. - Kim, H.; Woods, D.L. (2012). The development of direct-care staff social interaction coding schemas for nursing home residents with dementia. Geriatric Nursing, 33 (2), 113-117. --- ## Video tracking of children with autism URL: https://noldus.com/blog/video-tracking-children-autism Published: 2013-05-29 15:20:00 Description: Automated video tracking is a valuable tool for studies on animal models of autism (ASD). Diagnosis of ASD is based on behavior alone in humans, so naturally, behavior is an important part of human as well as rodent studies. Automated video tracking is a valuable tool in many rodent studies, such as research on animal models of autism spectrum disorder (ASD). Diagnosis of ASD is based on behavior alone in humans, so naturally, behavior is an important part of human as well as rodent studies. Using video tracking to study human behavior objectively In children, diagnosis and research is based on behavioral tests and questionnaires. These are, by nature, always more or less subjective. The study of behavior in rodents and other animals can be done objectively by using automated video tracking and Dr. Cohen thought this might possibly be of use for children as well who have ASD because of their observed tendency to remain at a distance from their parents and, in an unfamiliar room, to stay near the periphery (a type of thigmotaxis). Dr. Cohen and his colleagues from the New York State Institute for Basic Research in Developmental Disabilities (NY, USA) presented their research at the International Meeting for Autism Research (IMFAR) last month. It showed that video tracking is indeed a valuable addition to ASD research in children. The work of Dr. Cohen and his colleagues Ira Cohen has a long-standing interest in behavioral measurement, specifically in objective recording of behaviors associated with ASD. He started out studying operant conditioning in rats, and designed his own equipment in doing so, such as a brain stimulator and operant chamber. After his postdoc he became involved in psychopharmacological research on autism and again designed his own operant equipment. He tells us: "When I learned about EthoVision XT at an SRCD (Society for Research in Child Development) conference, I immediately suspected it would be useful for objective measurement of this type of behavior." He started using it as new cases came in for diagnosis and follow-up assessments. "I found that having the children wear red shirts worked the best." Study on children with ASD At the IMFAR his team presented a poster on a recent study that examined correlations between ASD rating scale data and data gathered with EthoVision XT video tracking. They studied 31 children between the ages of 2 and 14, of which 22 were diagnosed with ASD. They were observed in a free-play situation in a large room with toys placed on the floor and on a table. One of the child's parents was seated in a corner of the room during observations. Video tracking children During this free-play time, EthoVision XT was used to track the child as he or she moved through the room. Two zones of interest were marked with EthoVision XT: the area around the parent, who was seated in the northwest corner of the room, and the periphery of the room. From the tracking data, several variables related to these zones were selected to compare with ASD rating scales: mean distance from, mean time spent in, and latency to approach the two zones. In addition, path complexity was used to assess stereotyped or ritualistic behavior. Image courtesy of Dr. Cohen (New York State Institute for Basic Research in Developmental Disabilities, NY, USA). ASD rating scales To evaluate the correlation between objective EthoVision XT tracking data and typically used rating scales, tracking data was combined with rating scale results. The scales used included: - The PDD Behavior Inventory (PDDBI) (Cohen and Sudhalter, 2005) completed by the parent prior to the visit - The Sansone et al. (2011) factors of the Aberrant Behavior Checklist (ABC) which was completed by the parent during the observation - Parent interview with the Vineland Adaptive Behavior Scales (VABS) prior to the observation - Clinician ratings based on the Gotham et al (2007) ADOS‐G scoring system Video tracking data predicts rating scale scores The researchers found correlations between the EthoVision XT tracking data and the rating scales results, and concluded that these objective measures could indeed be used as predictors of the rating scale scores. Variables latency and mean distance to the parent were taken as a measure for social avoidance. This predictor associated most with the ADOS assessments of autism severity. Latency and mean distance to the periphery were taken to objectively score periphery preference. This score was most closely linked to parent ratings of autism severity and adaptive skills. Path complexity, as measured with EthoVision XT, when remaining close to the periphery of the room, was predictive for parent ratings of severity of stereotyped behaviors as well as for parent ratings of lack of social competence as measured by the PDDBI and VABS. FREE WHITE PAPER How to build an AV lab Do you want to learn more how to set up an AV lab? Read on for the perfect tips & tricks! - Which requirements do you need? - What equipment is needed? - Download this free 'how to' guide! Download New possibilities This study offers a great basis for building new objective methods of assessing children with ASD. It shows that objective measurement of behavior in children is possible by tracking there movement during the observational period. It also offers great feedback to similar tests done with animal models of ASD and may potentially be of use in objectively tracking change as a result of intervention. Acknowledgements We would like to thank Dr. Cohen very much for telling us more about his research. We look forward to many interesting studies that use video tracking in human behavior research in the future! Update: this research has now been published: Cohen, I.L.; Gardner, J.M.; Karmel, B.Z.; Kim, S.-Y. (2014). Rating scale measures are associated with Noldus EthoVision-XT video tracking of behaviors of children on the autism spectrum. Molecular Autism, 5(15), doi:10.1186/2040-2392-5-15. Read more about observational research on autism spectrum disorder in this free white paper. --- ## Robot-child interactions – helping children with autism learn skills URL: https://noldus.com/blog/robot-child-interactions-children-autism Published: 2013-05-23 09:08:00 Description: Human-Computer Interaction research may go a lot further than just evaluating an office worker interacting with a stationary computer or laptop. Human-Computer Interaction research may go a lot further than just evaluating an office worker interacting with a stationary computer or laptop. For example, researchers worldwide develop and evaluate robots in order to learn more about human-robot interaction, robot-robot interaction, and the roles robots can play in numerous processes taking place in our daily lives. Many years ago it all seemed too futuristic: who doesn't know R2-D2 or C-3PO from the Star Wars movies? Now we know that the future has started. Next to being friendly helpers, film robots such as R2-D2 and the robots in WALL-E also interact with people similarly to how a person would interact with another person. These processes are important to study, because, for example, autistic children often have serious difficulty learning social skills and could potentially benefit from learning these skills by interacting with a robot. Evaluate interactions objectively No matter what kind of HCI or Robotics research topic, behavioral observation is a valuable instrument in this area, being the tool to evaluate interactions objectively. Recently, Sandra Costa from the University of Minho, Guimares, Portugal and colleagues presented their work at the ACHI 2013, the sixth International Conference on Advances in Computer-Human Interactions. They explored if a robot, in this case KASPAR (a humanoid robot with a static body, able to move its arms and head in order to simulate gestures in social interaction), could help elicit interactions between an autistic child and another person and if KASPAR could help the children learn more about body parts and learn to identify their own body parts. Different research methods Costa et al. used questionnaires, structured interviews, behavioral analysis, and a comparison between the pre- and post-test to gather data. The interaction was recorded on video for later analysis in The Observer XT. The researchers used two cameras to record the face of both the child and the experimenter during the tests. Costa et al. decided to code the following behaviors: Looking, touching, following, pointing, imitation, prompts, and identifying body parts. By accurately coding these behaviors, the researchers gained insight in the behavioral changes between the first and the last session. Choose the location The tests in which the robot and child discussed the body parts were executed in the child's school. Being familiar with the room in which the test took place, the child experienced no additional stress. Teaching skills In order to teach the children about body parts, the researchers designed different scenarios with the robot and the child as participants. The children could touch the robot and, because of eight sensors, the robot was able to give direct feedback to the child. Teaching children with autism about body parts using a humanoid robot can be effective, but more research is needed. Costa et al. found differences in knowledge about body parts and the teachers indicated to the researchers that they saw a positive behavior change in the children where it concerned the ability to identify parts of their own body with their own hands. Robot - child interaction It was found that the children directed their eye gaze increasingly less towards KASPAR when comparing the first with the last test session. In comparison, the children did pay more attention to the experimenter. So what happened? Could the robot have helped to stimulate interactions between an autistic child and another person, in this case the experimenter? The researchers conclude that the robot could have certainly been useful in the facilitation of interaction between the child and the experimenter, but they found it difficult to draw causal conclusions because other factors could also have contributed to this increased level of interaction. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Reference Costa, S.; Lehmann, H.; Robins, B.; Dautenhahn, K.; Soares, F. (2013). „Where is your nose?"- Developing body awareness skills among children with autism using a humanoid robot. Proceedings of the ACHI 2013: The sixth International Conference on Advances in Computer-Human Interactions, 117-122. --- ## The power of zebrafish in the study on Parkinson’s Disease URL: https://noldus.com/blog/the-power-of-zebrafish-parkinsons-disease Published: 2013-05-22 15:54:00 Description: Zebrafish have proven to be a good model for Parkinson’s Disease (PD) research. They express several highly conserved genes that are associated with PD. Zebrafish have proven to be a good model for Parkinson's Disease (PD) research, as I already wrote about in Zebrafish with Parkinson's. They express several highly conserved genes that are associated with PD. Lopes de Fonseca et al. recently published about another interesting protein that has been linked to cases of PD in humans that run in families (familial). Zebrafish homologue to human PD gene Point mutations in ATP13A2 have been linked to several familial cases of PD, and zebrafish also express this gene. In fact, it has a high degree of homology with the human version. This particular study showed that it also plays a crucial role in embryonic development, and that partial knockdown of this gene affected zebrafish larvae behaviorally. Gene expression and knockdown model The first step in this study was to confirm ATP13A2 expression in zebrafish. It was found expressed in the entire body of the embryo during the initial stages of development, but in later stages expression was restricted to the brain. To investigate the role of ATP13A2, a knockdown (kd) model was created. A complete kd resulted in a 100% mortality rate, evidence of a crucial role of ATP13A2 in embryonic development. A partial kd resulted in behavioral impairments when compared to wild-type zebrafish larvae. Behavioral research of partial ATP13A2 knockdown The locomotor assays consisted of a light on/light off paradigm. Larvae were placed in 96-well plates in the DanioVision Observation Chamber at 7 days post fertilization. After a short habituation period, video recording started. Video recording and tracking with EthoVision XT took place under IR lighting conditions and the built-in visible light was used as a stimulus. For the first 15 minutes, the visible light was turned on, followed by 45 minutes lights off, and then another 45 minutes of lights on. Velocity of each individual was automatically tracked, and data was averaged over the two groups. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Behavioral deficits of partial ATP13A2 knockdown Partial knockdown of the ATP13A2 gene had a significant effect on zebrafish larvae behavior. On average, the kd group was slower and they also showed an abnormal response to the light stimulus. While the wild type group showed a lower average velocity when the lights were turned off (which is what you would expect), the kd model showed an increase in velocity. When the lights were turned on again, the wild type group increased their velocity as expected, while the kd groups showed no significant difference in behavior. Read more This research is yet another powerful confirmation of the value of zebrafish models in PD research, and in this case specifically for research on the biology of the ATP13A2 gene. If you want to read more, please take a look at this publication: - Lopes da Fonseca, T.; Correia, A.; Hasselaar, W.; van der Linde, H.C.; Willemsen, R.; Outeiro, T.F. (2013). The zebrafish homologue of Parkinson's disease ATP13A2 is essential for embryonic survival. Brain Research Bulletin, 90, 118-126. For other posts on zebrafish, click here. --- ## Testing without stress: high-throughput phenotyping URL: https://noldus.com/blog/high-throughput-phenotyping-home-cage Published: 2013-05-06 13:34:00 Description: The ability to recognize harmful situations and respond accurately is important for the survival of any animal. In order to respond to these situations the animal must be able to learn, remember, and alter its behavior. The importance of being flexible The ability to recognize harmful situations and respond accurately is important for the survival of any animal. In order to respond to these situations the animal must be able to learn, remember, and alter its behavior. Deficits in these abilities are associated with many affective and psychiatric disorders, like Schizophrenia and ADHD. Testing without severe stress Classical behavioral tests on learning and responding to aversive situations make use of rather severe stimuli. An example is the use of foot shock floors in behavioral tests with rats and mice. In addition to this, the animals are manually handled prior to testing because they are transferred to a test cage. This itself is a stress factor and influences the behavior of the animals and thereby the test results. Automated observations in a home cage The PhenoTyper is an observation environment with all the attributes of a home cage. Rats and mice can be observed in a non-intrusive way in a PhenoTyper. The integrated camera allows for continuous behavioral recordings of the animals. Tests can be carried out automatically, without the necessity to move the animals to a test environment. The PhenoTyper is connected to video tracking software, to analyze the behaviors automatically. In addition to this, lamps and buzzers can be controlled automatically in response to the behavior of the animals. Testing a mild aversive stimulus Maroteaux et al. (2012), developed an automated home cage observation test with the PhenoTyper to study the ability of mice to learn to avoid a mild aversive stimulus. Eight commonly used mouse strains were studied. Mice were kept individually in PhenoTyper cages that contained a shelter with two entrances. Most mice had developed a preference for one of the shelter entrances after four days habituation in the PhenoTyper cages. Then, using the full capabilities of EthoVision XT, a light switched on in the shelter only when the animal used the preferred entrance. In the next three days almost all strains switched their preference to the other entrance. The only two strains that did not were visually impaired. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial High throughput screening for flexibility Subsequently, the setup was used for high throughput phenotyping. The authors performed the test with 45 mutated mice strains. One mutant strain switched its preference for the shelter entrance much later than the other strains. All other behaviors of this strain, like walking speed or number of entries in the shelter, remained normal. This mutant strain had a defect in the gene specc1/cytospinB. The function of this gene is currently unknown, but the authors hypothesize it may be involved in cognitive abilities of mammals. Testing without stress The authors conclude that it is possible to study avoidance behavior with subtle stimuli in a home cage environment, which is important for the animals' welfare. In addition to this, automated home cage observations make high throughput behavioral testing, for example for drug development or genetic research, possible. With this developed test, the ability to learn to avoid aversive stimuli can be studied. Reference Maroteaux, G.; Loos, M.; van der Sluis, S.; Koopmans, B.; Aarts, E.; van Gassen, K.; Geurts, A.; The NeuroBSIK Mouse Phenomics Consortium, Largaespada, D. A.; Spruijt, B. M.; Stiedl, O.; Smit, A. B. and Verhage, M. (2012). High-throughput phenotyping of avoidance learning in mice discriminates different genotypes and identifies a novel gene. Genes, Brain and Behavior, 11, 772–784. --- ## Classroom observations including facial expression analysis URL: https://noldus.com/blog/classroom-observations-facial-expression Published: 2013-05-01 13:01:00 Description: Internet and technology usage, including computers, tablets, and mobile phones, has increased exponentially in the past few years. Internet and technology usage, including computers, tablets, and mobile phones, has increased exponentially in the past few years. Besides the fact that people are becoming accustomed to a variety of technology in the workplace and at home; technology has also entered other domains such as in schools, libraries, shopping malls, and restaurants. Classroom observations including facial expression analysis Dr. Tiffany Drape and her colleagues from Virginia Polytechnic Institute, Blacksburg, Virginia were interested in the integration of technology in higher education. Why specifically higher education, you might ask? The researchers explain that technology can help students meet higher standards and promote innovative approaches to teaching and learning. However, many schools are still struggling with this integration. Case study on technology integration using video collection In NACTA Journal, Drape et al. (2013) presented a case study that explored technology integration using video collection, observations, facial expression analysis, qualitative interviews, and video coding with The Observer XT. Drape et al. have chosen different methods to gather data in order to elucidate technology usage from different angles. The case study includes an analysis of an associate's degree program in a college of agriculture and life sciences in the USA. The research questions were: 1) How do educators decide what technology to use and how to integrate it into their program? and 2) What influences educators' decisions to integrate technology? RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Classroom observations In this blog article, the classroom observations are discussed. These observations were a major part of the case study. In order to analyze the videos in a more structured way, the researchers translated the research questions into an observation guide. This guide enabled the researchers to learn more about the behavior of students and the instructor in the classroom. The questions "how does the instructor keep students engaged and motivated using technology?" and "what are the students doing while the instructor is teaching the class" guided the observations. Verbal and non-verbal behavior of students Drape et al. were interested in verbal and non-verbal behavior of students and teachers and used The Observer XT and FaceReader to collect and analyze data. They recorded video unobtrusively in classrooms to collect the data they needed and coded behaviors afterwards. This included the coding of events related to the use of technology, such as a computer, software, or a remote control; how often the instructor and students discussed the use of technology; and what conclusions both groups decided on in reference to the use of technology in and out of the classroom. FaceReader, facial expression analysis software, was used to analyze non-verbal behaviors when students were asked to look at a video on their computer. FREE WHITE PAPER FaceReader methodology Download the free FaceReader methodology note to learn more about facial expression analysis theory. - How FaceReader works - More about the calibration - Insight in quality of analysis & output Download The researchers concluded that their data illustrates that instructors are careful when choosing to integrate technology. The priorities of the program leadership team, technology usage in the agriculture industry, and students' comfort with technology are all factors that are taken into consideration when making decisions about integration. In conclusion, the researchers recommend that technology be integrated on a daily basis and be thoroughly evaluated as a teaching tool. They add as a last remark that technology should never be a substitute for an actual teacher. References Drape, T.A.; Westfall-Rud, D.; Doak, S.; Guthrie, J.; Mykerezi, P. (2013). Technology integration in an agriculture associate's degree program: a case study guided by Rogers' Diffusion of Innovation. NACTA journal, 57(1), 24-35 --- ## Tracking zebrafish activity to study a key element in circadian rhythmicity URL: https://noldus.com/blog/zebrafish-activity-circadian-rhythmicity Published: 2013-04-22 10:12:00 Description: Zebrafish are a popular model of choice for many researchers, including chronobiologists. That’s because zebrafish rapidly develop their ‘inner clock’ (circadian system) – and because this system is highly light-entrainable. Zebrafish are a popular model of choice for many researchers, including chronobiologists. That's because zebrafish rapidly develop their 'inner clock' – their circadian system – and because this system is highly light-entrainable. Most zebrafish tissues (in vivo) have clocks, similar to the mammalian system, which can be studied in cell lines (ex vivo). Although the functional development of this clock system and the genes that compose the 'core clock' of zebrafish are already well understood, specific details of how the core oscillator functions remain unclear. The influence of enzyme activity on circadian rhythmicity Smadja Storz et al. investigated the influence of the activity of two isoforms of the CK1 family. CK1, short for casein kinase 1, is a group of enzymes that function as regulators of signal transduction in many processes, including circadian rhythmicity. The researchers studied the importance of CK1δ and CK1ε activity in circadian rhythmicity on several levels; in zebrafish embryos, larvae, and cell lines. Locomotor activity reflects rhythmicity In order to determine rhythmicity, researchers studied the behavior (activity pattern) of zebrafish larvae in a high-throughput set-up. Larvae were placed in 48 individual well plates in the DanioVision Observation Chamber. Behavioral tracking was then done automatically by EthoVision XT video tracking software. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Initially, larvae were kept under 12h light/12h dim light conditions. Following this, a CK1 inhibitor (or DMSO for the control group) was administrated and the animals were kept under dim light conditions. During the experiment, the activity of the animals was measured as total distance moved during ten minute time windows. CK1δ is important to maintain circadian rhythmicity Zebrafish larvae normally develop circadian rhythmicity when exposed to light/dark cycles, after which the animals are able to maintain this rhythmicity, even under continuous light conditions. As to be expected, the control groups showed this cycle of high-activity/low-activity in the period during which the light was dimmed continuously. In larvae that were exposed to the CK1δ inhibition, this rhythmicity was completely diminished. Specific CK1ε inhibition did not have as significant an effect. A great aquatic model for pharmacological screening and chronobiological research There are a couple of things we can learn from this study. In particular, this study demonstrates the importance of CK1δ activity in the proper development and maintenance of circadian rhythmicity in zebrafish. It also shows that CK1ε activity plays a less important role. More generally, it proves that zebrafish and the utility of CK1 inhibitors are important factors in the creations of high-throughput models for pharmacological studies on circadian clock-related drugs and other chronobiological research. Reference Smadja Storz, S.; Tovin, A.; Mracek, P.; Alon, S.; Foulkes, N.S.; Gothilf, Y. (2013). Casein Kinase 1δ Activity: A Key Element in the Zebrafish Circadian Timing System. PLoS ONE, 8 (1), e54189. --- ## Observing monkey behavior – cracking the nut URL: https://noldus.com/blog/observing-monkey-behavior Published: 2013-04-16 13:04:00 Description: We already know some monkeys display above average intelligence. One way by which we can tell is their use of tools. Studies have shown that capuchin monkeys use boulders and logs as anvils upon which they can crush nuts. We already know some monkeys display above average intelligence. One way by which we can tell is their use of tools. Behavioral studies have shown that capuchin monkeys use boulders and logs as anvils upon which they can crush nuts. Furthermore, these monkeys have demonstrated that they are able to identify hammer stones best for cracking, and nuts that are easy to crack. Fragaszy et al. decided to add to this knowledge-base with their behavioral study, which was recently published as Wild Bearded Capuchin Monkeys (Sapajus libidinosus) Strategically Place Nuts in a Stable Position during Nut-Cracking. This publication in PLOS ONE elaborates upon the detailed study of monkey behavior, specifically the placement of nuts prior to striking them. An interesting detail: they studied this same behavior in humans as well. Strategic placement of the nut before cracking it The researchers studied a group of wild capuchin monkeys at Fazenda Boa Vista in Brazil. They found that these monkeys have a well-defined strategy in placing the nuts on the anvil; they repetitively knock the nut on the anvil before releasing it, until it lays steady. Next, they use short striking motions to strike the nut with a stone. To add to the challenge, the researchers provided the monkeys with piassava nuts, these are nuts that are somewhat more difficult to crack and that usually require more than one strike to open up. To compare strategies between monkeys and men, they also incorporated an experiment with humans. The outline of the study This study had three parts to it. First, monkey behavior was observed for two weeks in a stationary set-up using video recordings. Their research questions included: how did the monkeys place the nuts on the anvil, did they use a particular orientation, did they get the nut to a steady position, and how did their individual behavior relate to the actual success of cracking the nuts? Second, human behavior was studied as they positioned nuts as if they were going to crack them, while blindfolded. In the third part of the test the researchers examined the nuts more closely to find the most stable position of each nut and compare this to how they were placed in the previous experiments. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial The monkey study The behavior of the monkeys was studied in their natural habitat in Brazil. They were provided with stones (to use as hammers) and nuts. For each nut the meridian line was already determined by rolling it on a flat surface until it lay flat (see the study for more detail). Using The Observer XT behavioral coding software, the video tapes were analyzed in two rounds over a course of two weeks. Scoring behaviors from video In a first video coding round, the ethogram (coding scheme) included: the position of the nut and movement of the nut after each strike, whether or not the monkey was using one or two hands, the number of strikes at the nut, whether or not the nut was cracked, and more events. In the second round of video coding, the manual actions performed by the monkeys before each strike were studied. Behaviors included tapping their fingers on the nuts, knocking the nut in the pit of the anvil, releasing the nut, and rotating the nut in the anvil. The human study A group of humans were given the same anvils. They were asked to place the nuts on the anvil, as if they were preparing to strike them open. Only in this case, the humans were blind-folded and encouraged to feel the nut and the pit in the anvil before placing the nut, to investigate haptic sensing. Their behaviors were scored using the same ethogram as in the monkey experiment. Different tactics, same results The behavioral observation of the monkeys showed that the placement of the nuts almost exclusively existed of knocking the nuts in the anvil (a species specific behavior) – barely any tapping, rotating, feeling the pit, or adjusting the nut in the air before placing it was recorded. In other words, the capuchin monkeys generally banged the nut on the anvil until it was in the best cracking position. No handling of the nuts was recorded, which indicates there was no perception of contour. Humans on the other hand, felt the nut and rotated it before placing it on the anvil, relying on haptic perception. These are two very different tactics, but both show skill and both result in successful strategic placement of the nut. Read more Check out the complete publication. It has a really clear and elaborate description of the experiments and some great pictures to illustrate them. Fragaszy, D.M.; Liu, Q.; Wright, B.W.; Allen, A.; Welch Brown, C.; Visalberghi, E. (2013). Wild bearded capuchin monkeys (sapajus libidinosus) strategically place nuts in a stable position during nut-cracking. PLOS ONE, 8 (2), e56182. Read more about The Observer XT or about a stationary observation system for research on wild or zoo animals! Photo courtesy: Capucin monkey with nut, Bart Wright; photo in text: Lauro Sirgado (Own work) [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons --- ## Zebrafish with Parkinson's URL: https://noldus.com/blog/zebrafish-parkinsons-research Published: 2013-03-28 11:04:00 Description: Parkinson’s Disease (PD) is one of the main neurodegenerative diseases and many researchers are involved in investigating this disease and developing treatments Parkinson's Disease (PD) is one of the main neurodegenerative diseases and many researchers are involved in investigating this disease and developing treatments. Still, the underlying mechanisms of PD remain largely unknown. Zebrafish turn out to be a big help in this research, as researchers from the Erasmus Medical Center (Rotterdam, the Netherlands) recently proved. They created a new model for PD in zebrafish, getting us one step closer to a better understanding of this debilitating disease. Zebrafish model for Parkinson's Tianna Zhao and her colleagues established this PD model in zebrafish. Specifically, it is a model for PARK15, a form of early-onset parkinsonism (atypical Parkinson's Disease). PARK15, and PD in general is typified by locomotor disturbances; the slow initiation of movement called bradykinesia. This is essentially caused by cell death of the dopamine producing neurons in the midbrain. In humans, this type of Parkinson's is caused by a mutation in a gene called FBXO7 that causes the loss of dopaminergic neurons. The zebrafish model from the Erasmus MC in Rotterdam is based on the zebrafish analogue of this gene. Creating a Parkinson's zebrafish The first thing to do for Zhao and her colleagues, was to identify the zebrafish gene analogue to the human FBXO7 gene, called zFbxo7. Next, they created a knockout model, resulting in four subtypes of morphant (knockout) zebrafish larvae. These were tested alongside wild-type zebrafish larvae to investigate if they exhibit the pathological and behavioral hallmarks of PARK15. They did. Testing locomotor behavior Because one of the most obvious and important behavioral symptoms of PARK15, and PD in general, is bradykinesia, the study included locomotor tests on the zebrafish larvae. For this, the researchers used DanioVision, a system for high-throughput tracking of zebrafish larvae. The 96 hour-old (post fertilization) zebrafish larvae were placed in a 96-well plate in the Observation Chamber. After a 15 minute acclimation period, the testing consisted of 3 cycles of 10 minutes with the lights on and 10 minutes with the lights off. EthoVision XT was used to automatically track the activity of each individual zebrafish larvae by measuring their velocities. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Verifying the model Zhao found a very pronounced difference in locomotor behavior between wild-type and morphant zebrafish. The morphants Park15 zebrafish larvae were less active, and those that were severely affected showed almost no locomotion. These are definitely signs of the typical dopamine dependent locomotor effect seen in humans with PD. To verify that this difference was in fact caused by dopamine depletion (and not by some general delay in development), a dopamine agonist apomorphine (a typical treatment for PD in humans) was used. This treatment increased the level of activity in morphants up to the level of the wild-type larvae, while it had no effect of the wild-type group itself. Besides behavioral symptoms, other pathological hallmarks consistent with PARK15 were confirmed for this model, including a range of developmental deficiencies such as the loss of dopaminergic neurons. Further reading If you want to read more about this research, check out this publication in PLOS ONE: Zhao, T.; Zondervan-van der Linde, H.; Severijnen, L.-A.; Oostra, B.A.; Willemsen, R.; Bonifati, V. (2012). Dopaminergic neuronal loss and dopamine-dependent locomotor defects in Fbxo7-deficient zebrafish. PLOS ONE, 7 (11), e48911. Or read more on zebrafish larvae research or the DanioVision system on our website. --- ## Connects some dots - cognitive impairment and cranial radiation URL: https://noldus.com/blog/cognitive-impairment-cranial-radiation Published: 2013-03-22 14:39:00 Description: On a yearly basis, an estimated 20.000 individuals are diagnosed with primary brain tumors in the United States alone. About ten times that number of patients will receive treatment for primary or metastatic brain cancer. By Dr. Christine Buske On a yearly basis, an estimated 20.000 individuals are diagnosed with primary brain tumors in the United States alone (Langley & Fidler, 2013). About ten times that number of patients will receive treatment for primary or metastatic brain cancer. Often times, these brain tumors are located in regions that are difficult to reach surgically. This leaves whole brain radiation therapy as the only viable treatment. While effective for many patients, damage to the brain is inevitable and can leave as many as 50% of surviving patients with cognitive impairments. These include functional deficits in attention, memory, and executive functioning that severely affects the patient's quality of life. Radiation-induced cognitive impairments Quality of life is an important consideration, in particular when cognitive impairments are severe after long therapy sessions. While the risks are well known, the mechanisms underlying radiation-induced cognitive impairments are not well understood at this time. To improve the quality of life of treated patients, having a better understanding of these mechanisms, and what may alleviate the onset or progression of these impairments is imperative. The literature suggests that radiation therapy can induce changes in vascular and neuroinflammatory glial cells. Recent studies have focused on the hippocampus, an area where adult neurogenesis takes place and an important brain region in learning and memory functions. Cranial radiation One such study was published by Belarbi et al. (2012). The authors investigated potential mechanisms contributing to the cognitive impairments observed resulting from cranial radiation. They focused on inflammation as a major contributor to these impairments. The study showed that the chemokine (C-C motif) receptor 2 (CCR2) is involved in the cognitive deficiencies by studying two mouse populations after radiation: wild type and CCR2 deficient. In both populations the number of adult-born neurons were reduced after radiation. However, the distribution patterns of these neurons throughout the granule cell layer were different between the two populations. In CCR2 deficient mice, the distribution pattern was unchanged, while in wild-type mice the fraction of pyramidal neurons expressing plasticity related immediate early gene Arc was not normalized. While these observations are interesting, they do not confirm whether the two mouse populations showed any difference in cognitive output. The behavioral tests conducted in the same study offer the supporting link between behavior and the molecular results. The authors used both the novel object test and the Morris water maze to assess cognitive functioning. EthoVision was used to track the behavior of the mice in both tests. Spatial learning and memory was affected Novel object recognition did not appear to be affected by radiation, or at least not at a level detectable by the behavioral test. Both the CCR2 deficient and wild type mice explored the novel objects (mouse directing its nose within 4 centimeters to the object) they were exposed to more than the familiar objects, and no significant difference between the populations could be observed. On the other hand, spatial learning and memory as assessed in the Morris water maze was affected. The CCR2 deficient mice seemed to be at a significant advantage compared to wild type mice after identical radiation exposure. CCR2 deficient mice performed remarkably better in the spatial learning and memory tasks. EthoVision was used to track the swim path of the mice to a hidden platform in the Morris water maze, and in all trials CCR2 deficient mice performed better, suggesting this population enjoyed some protection from radiation effects on cognitive functioning. This study has shown a new role for CCR2 signaling in radiation-induced cognitive impairments, where video tracking was able to capture the differences in cognitive output between the mouse populations. The full article can be found here. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial References - Belarbi, K.; Jopson, T.; Arellano, C.; Fike, J. R.; Rosi, S. (2013). CCR2 Deficiency Prevents Neuronal Dysfunction and Cognitive Impairments Induced by Cranial Irradiation. Cancer Research, 73, 1201–1210. - Langley, R. R.; Fidler, I. J. (2013). The Biology of Brain Metastasis. Clinical Chemistry, 59, 180–189. --- ## Human-robot interaction: Can you trust a robot? URL: https://noldus.com/blog/human-robot-interaction Published: 2013-03-18 09:13:00 Description: How do you know if someone with whom you do business is telling the truth? When buying something from a stranger, we are trying to determine if he or she can be trusted, either consciously or unconsciously. How do you know if someone with whom you do business is telling the truth? When buying something from a stranger, we are trying to determine if he or she can be trusted, either consciously or unconsciously. Non-verbal behavior can often give us cues about the trustworthiness of a person. In a recent study by DeSteno et al. two experiments were performed to identify non-verbal cues. In the first experiment, groups of two people interacted with one another other using a predefined script. The interactions were recorded on video and The Observer XT was used to code and analyze behaviors that indicate whether or not someone is telling the truth. The results revealed that it is very difficult to detect trustworthiness using single cues. However, sets of cues in a specific order can determine a level of trustworthiness. In the second experiment the state-of-the-art robot Nexi from MIT was programmed to mimic specific human behaviors. A group of test participants interacted with the robot while it gave non-verbal cues that are considered indicative of untrustworthiness, and a control group had the same interaction without these cues. It was found that the group who interacted with NEXI while it gave non-verbal cues (commonly indicative of untrustworthy behaviors) perceived the robot to be less trustworthy when compared with the control group. This video shows an initial test of the MDS (Mobile Dexterous Social) Robot designed and built in collaboration with the MIT Media Lab's Personal Robots Group, UMASS Amherst's Laboratory for Perceptual Robotics, Xitome Design, and Meka Robotics. In short, this study confirms that humans do in fact judge people on non-verbal behavior and that these behaviors can be identified and quantified. The study also concludes that humans respond the same way to non-verbal cues, regardless of whether the source is a human or robot. So can you trust a robot? If robot sales people are the future, humans are just as likely to be fooled by their trustworthy behavior as by the robot's human counterparts. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References DeSteno, D.; Breazeal, C.; Frank, R.; Pizarro, D.; Baumann, J.; Dickens, L.; Lee. J. (2012). Detecting the trustworthiness of novel partners in economic exchange. Psychological Science, DOI: 10.1177/0956797612448793. Read the full paper Featured photo by U.S. Navy photo by John F. Williams [Public domain], via Wikimedia Commons --- ## Beautiful birds and UV – What we cannot see URL: https://noldus.com/blog/beautiful-birds-and-uv-what-we-cannot-see Published: 2013-03-12 16:26:00 Description: Don’t we all enjoy the variety and intensity of bird colors? Male birds have perhaps the most impressive color display in nature. Beautiful birds Don't we all enjoy the variety and intensity of bird colors? Male birds have perhaps the most impressive color display in nature. Those with bright colors are generally healthier and have access to good food which contains pigments. Therefore, in general, female birds prefer males with the most conspicuous colors. The importance of UV Unlike humans, birds are able to see light in the ultraviolet color range. Some bird species have structures in their feathers that reflect UV light. A well-known example of structural coloration is peacock feathers which are pigmented brown, but appear blue, turquoise and green because of reflection by a microscopically structured surface [1]. Most research on the role of colors in the UV range on mating preference is done with species with such structural coloration. But pigments themselves can also contain components that are visible in the UV range and these may affect mating preference. Investigating this will increase our knowledge on sexual selection in bird species. Analyzing bird videos Leitão et al. [2] investigated whether pigments in the UV range play a role in preference of the European serin females (Serinus serinus) for their males. European serin males have a very conspicuous carotenoid-based yellow color. The authors divided wild captured birds into a high-pigment and low-pigment group. They used a three-compartment setup in which a high-pigment and a low-pigment male were kept in the two smaller compartments and a female was kept in the larger compartment that was separated from the males by a glass window. They made videos of the experiments and analyzed the time the females spent near both males with the video analysis software The Observer. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial UV and sexual preference The authors showed with The Observer software that the females spent significantly more time near the high-pigment males than near the low-pigment males. However, this preference disappeared when the glass in front of the high-pigment males contained a UV filter. The preference was also absent when the plumage of the high-pigmented males was treated with a UV blocking chemical. This shows that the UV component in the male's plumage is important for female preference. What we cannot see The authors conclude that the yellow pigment of European serin males plays a role in sexual selection. The UV component in this pigment is essential for the preference of the female birds. Hence, we should realize when observing birds that things are not always what they appear to be at first sight. Bird behavior can be affected by factors that we, as humans, are not able to see. References - Structural coloration - Wikipedia - Leitão, A. V., Monteiro, A. H., & Mota, P. G. (2013). Ultraviolet reflectance influences female preference for colourful males in the European serin. Behavioral Ecology and Sociobiology, 1-10. - Photo courtesy - Ana Leitão --- ## Zebrafish tracking to uncover subtle effects of embryonic alcohol exposure URL: https://noldus.com/blog/zebrafish-tracking-embryonic-alcohol-exposure Published: 2013-02-12 10:59:00 Description: Zebrafish are not the first species one might think of as being exposed to alcohol in their natural environment. Zebrafish are not the first species one might think of as being exposed to alcohol in their natural environment. Nevertheless, they have been used in alcohol related research for years. Recently, zebrafish have been shown to be useful in studying Fetal Alcohol Spectrum Disorders (FASD). Fetal Alcohol Spectrum Disorder: A relevant and current problem When a pregnant woman consumes alcohol, her fetus is at risk of developing Fetal Alcohol Spectrum Disorder. There is no known safe amount that can be consumed, and risks involve neurological, physical, and behavioral disabilities. These can be severe, in which case the symptoms are grouped under Fetal Alcohol Syndrome. When symptoms are mild, they are difficult to diagnose and are grouped under Fetal Alcohol Spectrum Disorder. Due to the difficulty of diagnosis, it is also difficult to estimate an exact prevalence of these developmental problems. Equally difficult then, is to estimate the cost to society. As far as this can be estimated, costs runs into the billions of dollars in the United States alone, and prevalence is around 1 in every 100 live births. The need for more research in FASD There is a continued need to better understand the effects of embryonic alcohol exposure. Developing a better understanding may lead to interventions and treatment in the future. Zebrafish can be particularly useful when studying the effects of alcohol on embryonic development, and beyond. While zebrafish may not encounter alcohol in their natural environment, they can easily be exposed to it by introducing it into the water they swim in. Dosing zebrafish at the embryonic stage is equally straightforward; adding alcohol to a petridish containing zebrafish eggs and system water is sufficient. Thanks to development taking place externally from the mother (and alcohol can pass through the chorion), timing of exposure can be chosen precisely; another big advantage of using this small fish. Recent studies using Zebrafish in FASD research I have spent a substantial part of my graduate studies investigating whether we can use zebrafish in FASD studies. It turns out, we have some good evidence that this is the case. Fernandes and Gerlai (2009) first established that behavioral effects of embryonic exposure can be seen in adult zebrafish. It is important to point out that the alcohol doses used in this study were very small (0-1% v/v of which about 1/30th penetrates the chorion, for a single 2 hour exposure). This study used EthoVision XT to measure the distance of focal fish on a shoaling stimulus image on a screen adjacent to the testing tank. EthoVision tracked the movements of a single fish, and while with plain observation fish behaved seemingly normal, after analysis of the data Fernandes and Gerlai found the treated fish to reduce their time spent close to the stimulus fish. The distance between the treated fish and stimulus image was, on average, also larger when compared to control individuals. This study set the stage to show we can observe subtle behavioral changes after a moderate dose, one time, alcohol exposure, which are not apparently from plain observation without video tracking analysis. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Building on the work done by Fernandes and Gerlai, I continued to study the effects of the same low doses of alcohol on zebrafish behavior, but in a slightly different context. Also having been interested in shoaling as a parameter, I used an open field task and ten live focal fish at once to assess the inter-individual distances among the group members. Previously, Fernandes and Gerlai had already established that behavioral differences could be observed in adult fish, but I was also interested in looking at how these behavioral differences develop from the larval stage. The results of this study have been submitted for publication now, but previously we were able to confirm the prior made observations in live shoals as well. In a live shoal, group members treated with alcohol also present a greater average distance from each other compared to control (Buske & Gerlai, 2011). Unlike Fernandes and Gerlai, I was not able to show a dose-dependent trend in this response. This is where perhaps tracking a single fish with EthoVision is able to isolate this observation. Tying in neurochemical changes with behavioral observations Where there is a behavioral change, one would also expect to see changes in the brain. A single dosing event, and using very low concentrations of alcohol, was able to generate reproducible reduction in social behavior in zebrafish, but we did not necessarily expect that this would also generate a measurable neurochemical change. I was not able to discern between the alcohol treated groups, but when comparing alcohol treated groups and control, the whole-brain samples from the alcohol groups showed significant reductions in dopamine and serotonin. Dopamine and serotonin are both important neurotransmitters in social behavior. While I cannot suggest a causal link between the two results, they offer an interesting starting point for future study. In short, zebrafish have shown not only to be an excellent model for studying the effect of high dose embryonic alcohol exposure in previous studies (Carvan, Loucks, Weber, & Williams, 2004; Matsui, Egana, Sponholtz, Adolph, & Dowling, 2006), but also an excellent model to assess the behavioral consequences of low dose embryonic alcohol exposure in adult fish (Buske & Gerlai, 2011; Fernandes & Gerlai, 2009). Learn more! Speakers at the "One stripe ahead: Using zebrafish to model neurobehavioral disorders" symposium presented recent developments in the field of biological psychiatry utilizing zebrafish-based paradigms. References - Buske, C., & Gerlai, R. (2011). Early embryonic ethanol exposure impairs shoaling and the dopaminergic and serotoninergic systems in adult zebrafish. Neurotoxicology and Teratology, 33 (6), 698–707. doi:10.1016/j.ntt.2011.05.009 - Carvan, M. J., Loucks, E., Weber, D. N., & Williams, F. E. (2004). Ethanol effects on the developing zebrafish: neurobehavior and skeletal morphogenesis. Neurotoxicology and Teratology, 26 (6), 757–768. doi:10.1016/j.ntt.2004.06.016 - Fernandes, Y., & Gerlai, R. (2009). Long-term behavioral changes in response to early developmental exposure to ethanol in zebrafish. Alcoholism, Clinical and Experimental Research, 33 (4), 601–609. doi:10.1111/j.1530-0277.2008.00874.x - Matsui, J. I., Egana, A. L., Sponholtz, T. R., Adolph, A. R., & Dowling, J. E. (2006). Effects of ethanol on photoreceptors and visual function in developing zebrafish. Investigative Ophthalmology & Visual Science, 47 (10), 4589–4597. doi:10.1167/iovs.05-0971 --- ## Why it is smart to test your animal in its home cage URL: https://noldus.com/blog/home-cage-testing Published: 2013-02-08 14:00:00 Description: Behavior of laboratory rodents is often studied in well-controlled, simple experiments, in an environment that is fundamentally different from the animal’s home cage. Behavior of laboratory rodents is often studied in well-controlled, simple experiments, in an environment that is fundamentally different from the animal's home cage. These tests usually involve repeated handling of the animal, elevated stress levels due to the new surroundings, and a great variety in laboratory environments. This makes results difficult to interpret, decreases reproducibility and compromises validity. Besides, it can have a negative effect on animal welfare. Why it is smart to test your animal in its home cage Executing tests in a home cage provides a solution to these problems. The PhenoTyper is a home cage that is suitable for a wide variety of tests, including tests on learning and memory, anxiety and depression or eating and drinking behavior. One can also use it to monitor the circadian rhythmicity of your lab animal for days or even weeks with minimal human interference. On the Behavioral Research Blog we have published several articles about home cage assessment and PhenoTyper. Read the posts to learn more. Brain waves and behavior Scheffzük et al. recorded brainwaves (EEG) from 19 freely moving mice during a 24-hour home cage assessment in a PhenoTyper home cage. Additionally, movement and behavior was automatically recorded with EthoVision XT to determine different states such as active wakefulness, quiet wakefulness, slow wave sleep, and REM sleep. Read this blog post to learn more: Brain waves and behavior: sleep to learn Inside the minds of mice and men In 2011 Lucas Noldus was interviewed for a technology feature in Nature; "Inside the minds of mice and men" by Monya Baker. Nature, 475, 123 - 128. In this article, Lucas Noldus explains how an instrumented home cage can be configured to perform any kind of test, from anxiety to memory. Noldus Information Technology supplies home cage testing set-ups, including the PhenoTyper, the instrumented home cage which is designed to be combined with tracking software, EthoVision XT. In the blog post, you can read more about how researchers are learning to use animal models for psychiatric disorders. NeuroBasic PharmaPhenomics Two years ago, Noldus Information Technology joined the research consortium NeuroBasic PharmaPhenomics (www.neurobasic.nl) in their efforts to develop new drug discovery strategies in both neurology and psychiatry. This project builds on the successes of Neuro-Bsik Mouse Phenomics (www.neurobsik.nl), the consortium in which Noldus was responsible for the development of an automated home cage technology that allowed the investigation of mouse models in an enriched environment. Over the years, this has resulted in a successful product that is now known as the PhenoTyper. RESOURCES Read more about PhenoTyper Find out how PhenoTyper is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources --- ## Optogenetics and operant conditioning URL: https://noldus.com/blog/optogenetics-and-operant-conditioning Published: 2013-02-05 09:51:00 Description: A great example of optogenetics in behavioral studies is the work of Dr. Kravitz and Dr. Kreitzer at the Kreitzer lab (currently, Kravitz works at the NIDDK in Bethesda). Let me tell you about it. Not long ago, I wrote about optogenetics (in this post) and the work of Dr. Stuber and his colleagues at the Stuberlab (www.stuberlab.org). Another great example of optogenetics in behavioral studies is the work of Dr. Kravitz and Dr. Kreitzer at the Kreitzer lab. Let me tell you about it. Investigating the dopamine system We all heard about dopamine, right? This chemical in your brain that makes you happy? Actually, dopamine is involved, and even crucial, in a number of processes that take place in the brain. You need it to control and coordinate your movements (so it is not surprising that the loss of dopamine producing neurons (brain cells) is associated with Parkinson's disease). It is also involved in thinking processes and so on. The third important process that involves dopamine is that of emotion and motivation, a focus in the study conducted by Kravitz and Kreitzer. These researchers investigated the function of two types of neurons in the dopamine system of the striatum, specifically two types that are activated by dopamine. The first type contains the D1 dopamine receptor, the binding of dopamine to this neuron causes activation of this neuron, which is thought to positively affect emotional state. The second type contains the D2 dopamine receptor and because binding of dopamine to this neuron is inhibitory (deactivating the neuron), this stimulation is believed to have a negative effect. Using optogenetics to stimulate brain cells Instead of administering dopamine or dopaminergic agonists, these researchers used optogenetics to directly activate the D1 and D2 neurons. In short, this means that by turning on the laser, these brain cells are activated. Their results were recently published in Nature Neuroscience. So how does it work? This will get a bit technical. First, to alter the neurons so they can be activated by light, these neurons needed to be "infected" with a transmembrane protein called channelrhodopsin-2. It's this protein that reacts to illumination, and subsequently activates the neuron. Next, these mice were implanted with a fiberoptic cable. This way researcher were able to send the light to the brain at any given moment, and the mouse were still able to move around freely in their cage. Read more about optogenetics on our website and in this blog post. Operant conditioning via the dopamine system with optogenetics The researchers then proceeded to test if the optogenetic stimulation was in fact effective as a reward (via the D1 neurons) or punishment (via the D2 neurons). For this, they used a variety of behavioral tests. The first test was done in an operant box containing touch sensors as operant triggers. Each time the mouse came into contact with a sensor, this action was recorded by EthoVision XT Trial & Hardware Control software. After contact, the software sent out a signal to turn on the laser, resulting in illumination, and thereby optogenetic stimulation of the neurons. EthoVision XT was also used to record behavior of the mice. Was the mouse touching the sensors more often when the D1 neurons were stimulated? In other words, is stimulation of these receptors rewarding for the mice? And is stimulation of the D2 neurons in fact a punishment, resulting in less touching of sensors? Yes and yes. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Place preference via the dopamine system The second behavioral test was a place preference task, during which the mice were tested in a cage with a black and a white chamber. One of these chambers was designated as the correct chamber, resulting in the optogenetic stimulation of the D1 neurons. Alternatively, one of the chambers was designated as the wrong chamber, resulting in D2 neuron stimulation. The position of the mouse was recorded with EthoVision XT, and Trial & Hardware Control was again used to control optogenetic stimulation. Similar to the operant conditioning test, the mice showed place preference according to which neurons were stimulated. Optogenetic stimulation succesfully reinforces behavior Kravitz and Kreitzer found that optogenetically activating these specific neurons in the forebrain (that are normally activated by dopamine) indeed served as a reward (D1) or punishment (D2), according the behavior of the mice. When the mouse performed the required actions (touching of the sensor or entering the black or white area), and this was followed by 'reward' (the D1 neurons were stimulated), this action was repeated by the mice. However, if their actions resulted in punishment (D2 neurons stimulated), this action was performed less. This confirms the previous notion that neurons with the D1 receptor mediate reward while neurons containing D2 receptors mediate punishment. The authors also found the difference to be greater in reward scenarios, and concluded that positive reinforcement seems more effective than punishment to modify behavior on the long term. A third important conclusion is that optogenetic stimulation of dopamine-sensitive neurons is indeed effective, and can be used as a precise temporal and spatial alternative to administrating dopamine or dopaminergic agonists. Compelling proof of principle Using the well-studied dopamine system, these researchers were able to prove that optogenetic stimulation is a great (or even better) alternative for stimulating neurons, when compared to the traditional chemical way. I would like to thank Dr. Kravitz and his colleagues for the information for this post. This blog is based on the work of Kravitz et al.: Kravitz, A.V.; Tye, L.D.; Kreitzer, A.C. (2012). Distinct roles for direct and indirect pathway striatal neurons in reinforcement. Nature Neuroscience, 15, 816-818. For more information on optogenetics, EthoVision XT, and Trial & Hardware Control, please visit our website. --- ## Observations of surgeons as a tool to assess competency URL: https://noldus.com/blog/observations-surgeons-assess-competency Published: 2013-01-15 10:15:00 Description: Medical doctors receive extensive education and training before and during their time spent working at a hospital or clinic. Medical doctors receive extensive education and training before and during their time spent working at a hospital or clinic. There are many training sessions organized by groups of medical specialists, hospitals, and professional societies worldwide that doctors can choose from to continue improving their communication and technical skills. How can we consistently evaluate performance? Skills and knowledge should be evaluated on a regular basis, shouldn't they? Many researchers are receiving funding to investigate how skills are best taught and practiced. Also, effective communication and positive team interactions are becoming increasingly recognized as crucial components for success in the workplace. Studies are investigating the best way for a physician to speak to a patient while simultaneously obtaining the appropriate medical information and putting the patient at ease. Below you can find a summary of an observational research study conducted by Miskovic et al. (2012) about a new method used to assess the competency level of surgical specialists in advanced laparoscopic surgery. "Observational clinical human reliability analysis (OCHRA) for competency assessment in laparoscopic colorectal surgery at the specialist level" Recently, Miskovic et al. (2012) collected 32 video recordings of laparoscopic colorectal resections. Laparoscopic surgery is a modern method in which small incisions are made. It is meant to minimize post-operative pain by using smaller incisions and speed up recovery times. The surgeon uses small tools to interact with tissue. Experts and delegates of the National Training Program in England performed all surgeries. In total, Miskovic et al. evaluated performances of 4 experts and 27 delegates of which 17 passed the National Training Program in England. With this material, Miskovic et al. were able to evaluate a new method called OCHRA that has been developed to detect errors and near misses during surgeries. Video analysis is at the core of this method. Miskovic et al. used The Observer XT to code events and calculate frequency and duration. The full coding scheme can be found in Surgical Endoscopy. All videos were analyzed by experts (expert reviews) and by observers using the predefined coding scheme: time spent on Dissecting (D) and on Exposing (E) tissue were measured. And, all errors were marked as point events. If an error led to a direct consequence (i.e. when the patient started bleeding), this was also recorded. After accurately coding the videos, the complete error count was extracted from The Observer XT for further analysis in SPSS. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Expert review and behavioral analysis In this study, two methods were used: expert review and behavioral analysis. Miskovic et al. explain that novel methods are required to further rationalize and objectify the process of measuring competence. Individual assessments of operating videos can easily be combined with detailed behavioral analysis to allow for more accurate assessments. Concluding The researchers concluded that OCHRA is a valid method for assessing performance of surgical specialists. The video analysis delivered the researchers with proof that experts have a higher D/E ratio, in other words work more efficient, in comparison to delegates. Note that it is not the operating time that determined the outcome. It is the combination between time spent on for example cutting tissue and exposing tissue time (i.e. grabbing a different piece of tissue). OCHRA can now be integrated into clinical training programs. Miskovic et al. emphasize the importance of assessing the competence of surgeons at this level by evaluating real operations in a real environment. Reference Miskovic, D.; Ni, M.; Wyles, S.M.; Parvaiz, A.; Hanna, G.B. (2012). Observational clinical human reliability analysis (OCHRA) for competency assessment in laparoscopic colorectal surgery at the specialist level. Surgical Endoscopy, 26, 796-803. --- ## Video tracking and a bug repellant stronger than DEET URL: https://noldus.com/blog/video-tracking-bug-repellant Published: 2012-12-31 14:33:00 Description: Last year the news was hitting the internet: The Zwiebel lab (Vanderbilt University, Nashville, Tennessee, USA) may have found a new bug repellant that is stronger than DEET. Last year the news was hitting the internet: The Zwiebel lab (Vanderbilt University, Nashville, Tennessee, USA) may have found a new bug repellant that is stronger than DEET. They published a paper on it this year. It tells us how they used video tracking of insect larvae to test a range of possible variants of this new compound called VUAA1. Stronger than DEET Dr. Zwiebel and his team identified the VUAA1 compound to work like DEET (a well-known insect repellant), only a thousand times stronger. It turns on all the receptors in the mosquito's "nose", effectively overloading the odor-sensing system. Messing with their noses The research of the Zwiebel lab team started at the mosquito's antennae, where their olfactory system is located. They need their antennae to locate their prey: humans. That's why messing with this system might be a perfect way to disrupt their hunt for our blood. This is very important, because mosquitos aren't just annoying, they can also transmit diseases, like malaria. System overload The VUAA1 compound works as a odorant receptor (OR) agonist, meaning that it activates it. Exposing insects to this compound effectively overloads their sensory system. This means they have no way to locate any odor source... In this study the researchers investigated the potential of analogues of this VUAA1 compound. By altering the structure of the compound, they created VUAA0 and VUAA0.5 which showed reduced potency to bind to the OR in in vitro studies. However, they also created VUAA2, VUAA3, and VUAA4. These analogues showed enhanced potency. Especially VUAA4 showed a ten-fold increased agonist potency over VUAA1. Testing on behavior Now that they've created VUAA1 analogues that are potentially even more effective than VUAA1 itself, they were ready to test them out. Mosquito larvae were used to study the effect on the same receptors that are found in adult mosquitos. The larvae were exposed to VUAA1, DEET and two other compounds that are known to affect larval mobility: 3MP and ACP. Larval activity was measured in 6-well plates with DanioVision and EthoVision XT. As expected, 3MP increased larvae activity, as does DEET, while ACP decreased it. And, in accordance with previous findings, VUAA1 increased activity significantly more than DEET. To assure that the effect was actually due to the binding of VUAA1 to the odorant receptor, the researchers selectively blocked this pathway by administration of specific RNA. The effect was no longer present, indicating that it was indeed the binding of the VUAA1 to the odorant receptor that increased larvae activity. Subsequently they tested the VUAA1 analogues. The suspected enhanced potency of VUAA2 and VUAA3 was not confirmed in this behavioral assay. While VUAA0 decreased larvae activity, VUAA0.5, VUAA2 and VUAA3 did not alter larvae activity significantly. But VUAA4 did. Hope for a future free of mosquito-bites This study shows the importance of behavioral research. While 3 out of 5 analogues of the VUAA1 compound showed promise to be as effective (or even more effective) as VUAA1 itself, this was only confirmed for one of them in the behavioral assay. However, this specific compound VUAA4 shows even more potency than the originally discovered VUAA1 which already seemed so much stronger than DEET. These are promising findings for the creation of better mosquito repellants and thus in limiting the spread of malaria and other diseases that can be transferred by insects. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Taylor, R.W.; Romaine, I.M.; Liu, C.; Murthi, P.; Jones, P.L.; Waterson, A.G.; Sulikowski, G.A.; Zwiebel, L.J. (2012). Structure-activity relationship of a broad-spectrum insect odorant receptor agonist. ACS Chemical Biology, 7(10), 1647-1652. --- ## Optogenetics - Shining a light on brains and behavior URL: https://noldus.com/blog/optogenetics Published: 2012-12-13 10:47:00 Description: Brains are complicated. We all know that. Like an entangled bunch of wires. Still, over the years, neuroscientists have been able to map out several brain regions and their functions in behavior and physiology. Brains are complicated. We all know that. Like an entangled bunch of wires. Still, over the years, neuroscientists have been able to map out several brain regions and their functions in behavior and physiology. Pretty impressive but when it comes down to the precise determination of which brain cells are responsible for what function, many things are still a mystery. Traditional methods Traditionally two methods were used for this kind of research, being pharmaceuticals (chemical compounds, drugs) and electrodes. While pharmaceuticals can target specific cell receptors to trigger specific neurons, they are not temporally precise. It takes time for them to work after administration, and once they work, the drugs can stay in the system for a certain amount of time. In most cases, activation actually lasts too long. It would be so much easier if cells could be turned on and off like a light switch. Therefore, many scientists have started using electrodes. The problem with electrodes, however, is that they are often not spatially precise enough. So in many cases, neurons in the vicinity of the targeted neurons are also activated. The light-bulb moment In the last decade a new method was invented to actually activate or even inhibit neurons with light. Just like turning on a light switch, literally. Scientists have found a way to insert light-sensitive receptor proteins (originally found in algae) into mammalian neurons, making them sensitive to activation by light of specific wavelengths. This offers both a temporal and spatial precision that was previously unpreceded. It's not surprising this technique has been named Method of the year (Nature) in 2010. We are talking optogenetics here. Optogenetics "Optogenetics is a technology that allows targeted, fast control of precisely defined events in biological systems as complex as freely moving mammals." (Karl Deisseroth, Nature Methods, 8, 26-29.) Optogenetics has already undergone rapid developments in the last few years. While first tested ex vivo, soon it was possible to use it in live animals, first restrained and now in animals implanted with fiber optics that are able to freely move around in their cages. Initially, blue light was used, now new receptors are developed that are sensitive to other wavelengths of color. Of course optogenetics holds great promise for behavioral research as well. Not only can we now more specifically determine the actual effects of stimulation of certain neurons on behavior, it also refines operant conditioning tasks and preference/avoidance tests. This is where Noldus come in: a perfect challenge for EthoVision XT and Trial & Hardware Control. The way we do neuroscience Garret Stuber (www.stuberlab.org) honored our headquarters (Wageningen, The Netherlands) with a visit a while back, to present his lab's work on optogenetics. As he puts it: "Now it is cutting edge technology, relatively new, and still being refined. But in 5 years, this will be the way we do neuroscience." Addiction and neuropsychiatric disorders At the Stuber Lab, neural circuits that are involved in addiction and neuropsychiatric disorders are studied. They are interested in learning how activation or inactivation of certain neurons influences behavior, by performing several behavioral tests. Stuber says: "It is difficult to do these kinds of test without automated triggers. It doesn't work as well if you have to manually turn on the laser for optogenetic stimulation each time the animal is at the location or performs the behavior you specified. Therefore, Trial & Hardware Control is basically essential for these kinds of tests." FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Real-time place preference As Stuber describes it, at their lab they often like to start with a straight-forward real-time place preference test. In this test the animal is placed in a rectangular open field with two distinct sides. One of these sides is paired with optogenetic stimulation. Depending on whether this stimulation is activating or deactivating, and which neurons are affected, this can be a rewarding or aversive stimulus for the animal. If in further sessions the animal spends more time on the stimulated sides, it is fair to conclude the stimulus had a rewarding effect. If the animal avoids this side, the stimulus was aversive. In practice, EthoVision XT Trial & Hardware Control is programmed to pair a zone (one side) with a trigger. This command goes through the IO-box and turns on the laser for optogenetic stimulation. "The great thing about Trial & Hardware Control is that you can create a protocol more complex than just one pairing of animal location (or behavior) to a trigger. You can create multiple output signals, for example define five different zones and pair these with five different frequencies of optogenetic stimulation. This way you test out what the optimal frequency of stimulation is. This is important because some neurons are responsible for different actions, depending on their firing rate and thus the frequency with which they are stimulated." Anxiolytic and anxiogenic stimuli Stuber also uses optogenetics to study the possible anxiolytic or anxiogenic functioning of neurons. He describes a 15 minute off-on-off stimulus test, in which the animal is placed in an elevated plus maze. EthoVision XT Trial & Hardware Control can be programmed to turn on a optogenetic stimulation between minute 6 and 10 of the test. The first and last five minutes of the test the animal is not stimulated. The behavior of the animal is video tracked. If the animal spends significantly more time in the open arms of the plus maze during the stimulation phase, stimulation of the neurons are thought to have a anxiolytic effect. Other possibilities for optogenetics in behavioral research A very valuable and yet straight-forward test is that of open field locomotion in response to optogenetic stimulation. Velocity, movement, and rotation are interesting behaviors that can be easily assessed with video tracking, and that are useful indicators of neuron functioning. Stuber also mentions that Trial & Hardware Control can be a great asset to automate operant tests in which the behavior of the animal is detected (e.g. a nose poke or lever push) and subsequently triggers optogenetic stimulation. This can be used for either rewarding or aversive learning. A "bright" future for optogenetics While it has undergone rapid developments, there are a lot more possibilities in the future of optogenetic research. For example, while optogenetics is often used to stimulate neurons, it can also be used to disrupt neuron signaling, effectively turning them off. And instead of just stimulating or deactivating neurons, optogenetics can also be used to record the activity of neurons. Stuber comments that there is already a lot of proof of principle, but that actual studies that incorporate this in behavioral testing are not published yet. It does show great promise for the future, as it is already possible to visualize neuron activity and even discriminate firing rate according to the colored light intensity. "It would be great to combine it all; stimulating one type of neuron, while recording the effect it has on the other type of neuron, imaging the firing rate, and while tracking the location and behavior of the animal", says Stuber. Acknowledgements Thank you, Garret Stuber and the Stuber Lab (www.stuberlab.org), for your help with this blog post! Further reading Go to www.stuberlab.org for more information on the work of Garret Stuber and his colleagues. Some recent publications that might interest you: - Stamatakis, A.M.; Stuber, G.D. (2012). Activation of lateral habenula inputs to the ventral midbrain promotes behavioral avoidance. Nature Neuroscience, 15(8), 1105-1107. - Van Zessen, R; Phiilips, J.L.; Budygin, E.A.; Stuber, G.D. (2012). Activation of VTA GABA neurons disrupts reward consumption. Neuron, 73, 1184–1194. - Sparta, D.R.; Stamatakis, A.M.; Phillips, J.L.; Hovelsø, N.; van Zessen, R.; Stuber, G.D. (2011). Construction of implantable optical fibers for long-term optogenetic manipulation of neural circuits. Nature Protocols, 7, 12–23. - Stuber, G.D.; Britt, J.P.; Bonci, A. (2011). Optogenetic modulation of neural circuits that underlie reward seeking. Biological Psychiatry, 71, 1061-1067. - Stuber, G.D.; Sparta, D.R.; Stamatakis, A.M.; van Leeuwen, W.; Harjoprajitno, J.E.; Cho, S.; Tye, K.M.; Kempadoo, K.A.; Zhang, F.; Deisseroth, K.; Bonci, A. (2011). Amygdala to nucleus accumbens excitatory transmission facilitates reward seeking. Nature, 475, 377-380. --- ## What behaviors to focus on – Airport passenger experiences URL: https://noldus.com/blog/passenger-retail-experience Published: 2012-12-06 16:08:00 Description: To learn more about airport design and to investigate how to make time at an airport more enjoyable, Livingstone et al. undertook a study into passenger experience. Airport design - passenger retail experience To learn more about airport design and to investigate how to make time at an airport more enjoyable, Livingstone et al. undertook a study into passenger experience. To be more specific, they looked into airport behavior and experiences in Landside Retail Locations. They specifically chose this part of the airport because people tend to experience travel stress and other negative emotions when inside the Landside Retail Locations. To measure airport experiences accurately Livingstone et al. developed a coding scheme and used several cameras and The Observer XT research software for data collection. They used codes such as Activity – Walking whilst browsing, Purchase type – Book, Alcohol, or Electronic, or Landside Retail Locations – News Travels, Australia Way, Merlo. Processing and discretionary Livingstone et al. explain that passengers undertake two separate categories of activities: processing and discretionary. The results of this study show that 50% of the actions were processing activities, in other words, half of the time was consumed by activities passengers had to complete (mandatory) before boarding an airplane. Livingstone et al. advise that the airport should ensure passengers spend less time taking care of necessary activities. They are happier when undertaking other activities, such as shopping, eating, or relaxing. Passengers can, for example, go shopping between arrival at the airport and check-in. Livingstone et al. named three factors which positively influence the proportion of landside dwell time – whether or not they 1) entered a retail location, 2) made a purchase, and 3) who they were accompanied by. A good example – "Passengers accompanied by wavers [people who go and see their passenger off] were observed to spend a significantly higher proportion of their landside dwell undertaking discretionary activities". The researchers thus conclude: "Through the design of landside terminal environments and services which encourage wavers to enter into and spend time in airports, passenger discretionary time can be increased improving the quality of passenger landside experiences". The researchers note that a limitation of this study is the fact that people were aware of being video recorded. However, it is unethical to record video without permission. And, it should be noted that, although time consuming and labor intensive, systematic behavioral observation "provides a unique understanding of airport retail experiences from a passenger's perspective, which is missing from current research". Greeting rituals at an airport Greeting rituals is a coding scheme set up by Noldus. It can be used at an airport. In this project, researchers observed people greeting each other in the arrivals hall at an international airport. They focused on gestures, emotion, and locomotion. Gestures such as kiss, rub back, shake hands, and hug were defined in the coding scheme. To avoid coding the wrong behavior, you can easily place a camera at the scene and refine the coding work afterwards. The Observer XT research software allows for extensive analysis afterwards. It calculates frequencies and duration and by using elaborate filters, you can compare groups such as females greeting females with males greeting males or whatever combination suits your needs. Results from a recent study, Nagy (2011), show that spontaneous embraces last for about 3 seconds. And there were no differences found on the gender front. How would that compare to greeting rituals at an airport? Nagy did find a difference when it concerned teammates hugging or opponents hugging - when hugging an opponent, the embrace lasted for a shorter amount of time compared to hugging a coach or teammate! FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References - Livingstone, A.; Popovic, V.; Kraal, B.J.; Kirk, P.J. (2012). Understanding the airport passenger landside retail experience. In Israsena, Praima, Tangsantikul, Juthamas, & Durling, David (Eds.) DRS 2012 Bangkok – Research: Uncertainty, Contradiction and Value, Department of Industrial Design, Faculty of Architecture, Chulalongkorn University, Chulalongkorn University, Bangkok. - Nagy, E. (2011). Sharing the moment: the duration of embraces in humans. Journal of Ethology, 29, 389-393. --- ## Three examples of autism research studies URL: https://noldus.com/blog/examples-autism-research-studies Published: 2012-11-29 11:24:00 Description: Knowledge is the key to developing a better understanding of autism. Researchers often observe and code behavior in combination with other research methods. Knowledge is the key to developing a better understanding of autism. To better recognize and explain specific behaviors linked to autism, researchers often combine behavioral observation and coding with other methods such as questionnaires, parental interviews, and structured tasks. By doing so, they gather both subjective and objective data, which leads to more reliable and meaningful insights. Three examples of autism research studies Below are three examples of research studies where behavioral observation played a key role in autism research. 1. Studying social interactions through novel object learning tasks Bhat et al. (2010) introduced a novel social object learning task to study early social development. In this study, researchers focused on a less commonly used triadic interaction: infant, object, and caregiver. While follow-up interviews with caregivers offered valuable insights into their experiences, behavioral observations provided deeper, real-time information about how infants engaged simultaneously with objects and people. This combination of observational data and caregiver reports helped the researchers capture subtle social behaviors that might otherwise be missed. 2. Revealing patterns in self-injurious behavior In a study by Sandman et al. (2012), behavioral observation combined with T-pattern analysis was used to investigate self-injury in individuals with autism. The researchers aimed to determine whether self-injurious actions were part of larger, complex behavioral networks. By observing and analyzing the temporal patterns surrounding self-injury, they revealed how such behaviors are nested within ongoing interactions between the individual and their environment. These findings provided new perspectives on how to interpret and address self-injurious behavior within broader behavioral contexts. 3. Improving social interactions in classroom settings Feldman Klein and Matos (2012) observed behavior in classrooms to assess the impact of social facilitation procedures based on Pivotal Response Treatment (PRT). In this study, paraprofessionals were trained to implement strategies that promote social interaction among students with autism. Behavioral observations allowed researchers to evaluate the effectiveness of these interventions in real-time, offering detailed insights into how small changes in adult behavior influenced peer interactions and overall classroom dynamics. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Get your Free trial Behavioral observation remains a cornerstone of autism research. It allows researchers to capture subtle, real-world behaviors that may not be fully revealed through self-reports or interviews. Whether analyzing early social development, identifying patterns in challenging behavior, or evaluating intervention strategies, observational research provides crucial insights that drive progress in diagnosis, intervention, and support for individuals with autism. In a free white paper we will describe how and why observational research methods are used in autism research worldwide and thus try to answer two questions: why observe behavior and how to observe behavior in a structured way. FREE WHITE PAPER Autism research Download the free White paper to learn how and why observational research methods are used in autism research. - Why observe behavior - How to observe behavior in a structured way - What research tools are available Get your copy instantly References - Bhat, A.N.; Galloway, J.C.; Landa, R.J. (2010). Social and non-social visual attention patterns and associative learning in infants at risk for autism. Journal of Child Psychology and Psychiatry, 51 (9), 989-997. - Sandman, S.A.; Kemp, A.S.; Mabini, C.; Pincus, D.; Magnusson, M. (2012). The role of self-injury in the organization of behaviour. Journal of Intellectual Disability Research, 56 (5), 516-526. - Klein Feldman, E.; Matos, R. (2012). Training paraprofessionals to facilitate social interactions between children with autism and their typically developing peers. Journal of Positive Behavior Interventions, doi 10.1177/1098300712457421. --- ## Tracking zebrafish in 3D URL: https://noldus.com/blog/tracking-zebrafish-in-3d Published: 2012-11-22 13:53:00 Description: Recognizing the lack of hands-on education, Dr. Kalueff has started organizing zebrafish behavioral neuroscience and phenotyping workshops. The workshops ran just before and after the SfN annual meeting, October 2012. Zebrafish are an exciting, but still relatively new, model organism growing in popularity in behavioral neuroscience. We have highlighted recent behavioral work using zebrafish extensively, but compared to other models there are few textbooks or protocols available to those entering the field. Compared to mouse and rat phenotyping, the zebrafish community has a long way to go. Not only when it comes to protocol development and the availability of handbooks, but also with regards to professional training. Tracking zebrafish in 3D at the Zebrafish Behavioral Neuroscience and Neurophenotyping workshop Recognizing the lack of hands-on education, Dr. Kalueff has started organizing zebrafish behavioral neuroscience and phenotyping workshops. The workshops ran just before and after the Society for Neuroscience annual meeting, October 2012. The combination of the two events attracted researchers from around the world to join in on a lively discussion on zebrafish behavioral neuroscience. I had the pleasure of attending this workshop as well. My personal reason for attending was to satisfy my interest in high-throughput screening in adult zebrafish, and automated video tracking. This is an area that is still very much up and coming, and excellent tools for it have already been developed. Nevertheless, the field is still in an exploratory phase. Mostly, because there is not clear standardization of the behavioral paradigms used, compared to rodent models for example. Dr. Kalueff showcased his work using the open field with zebrafish, and a shoaling paradigm. Looking superficially, my own work also used the open field and a shoaling paradigm, but is our work similar or entirely comparable? No. I believe that both approaches show promise and serve their purpose, but my open field is a few orders of magnitude larger than the open field in Dr. Kalueff's experiments. These differing approaches only illustrate that we have not yet established many solid standardized tests yet in the world of zebrafish behavioral research. Different arena sizes could continue to be used depending on the hypothesis or goal of the study. This is the case for rodent studies as well, but for zebrafish not all approaches have been extensively validated yet. Recently, some books have been published describing zebrafish protocols. These provide a valuable framework, but the number of established protocols is not as expansive as in, for example, the rodent literature. As zebrafish research develops, active discussion and collaboration will be the drivers of quality research. This workshop very much provided a starting point for this. The focus of the workshop was on behavioral phenotyping, and particularly automated tracking of behavior using EthoVision XT. One aspect of EthoVision that was particularly highlighted was one of Noldus' newest developments: Track3D. This EthoVision add-on makes it possible to track a subject in three dimensions using two cameras. Conventionally, 2D tracking has been the norm, but 3D tracking may offer some additional insights or benefits when phenotyping behavior. This was illustrated beautifully by Dr. Kalueff, using his laboratory's work on zebrafish exposed to nicotine and LSD. Each compound produces traces that look somewhat similar in 2D, but provide distinctly different patterns when assessed in 3D. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial For the time being, the data shown in the workshop was for a single fish being tracked in 3D. My work has revolved around shoaling, and I see 3D tracking as a phenomenal opportunity in this scope of work; finally we would be able to reliably track each individual fish without any fish being 'switched' or 'lost' by the tracking program. This brought our discussion to shoaling, and Dr. Kalueff's shoaling paradigm. Active in person discussion, which was possible thanks to the workshop, brought up some interesting differences in what we see as shoaling or grouping behavior. Dr. Kalueff uses four fish in a standard home tank, and measures shoaling in response to pharmaceutical compounds. I explained my paradigm, where I use ten fish in a very large arena and try to model shoaling. When looking at each of our papers superficially, I would have first argued that we are looking at shoaling in very different ways and that our results cannot be compared to each other. In fact, when taking a closer look it becomes clear that while we may measure shoaling slightly differently, and different shoal sizes, each of these approaches is able to answer the questions the approaches were designed for. Without active discussion, these subtleties may not have come to light as easily. My studies focus on natural shoaling behavior in a large open field, but for the purposes of pharmaceutical screening Dr. Kalueff required a small shoal confined to a smaller tank. As scientists we have to engage in active discourse to better understand not only how we research but more importantly why. A workshop like this one, is the perfect venue for this. "We hope that this workshop will cover the need in bridging larval and adult zebrafish research, and improving the dialog between experts working with rodent and aquatic models. Eventually, this will foster innovative translational cross-domain and cross-species modeling of brain disorders", Dr. Kalueff expressed. Thanks to the success of this event, similar workshops will be held monthly throughout 2012-2013. --- ## Tracking tadpoles – why video tracking is important in ecotoxicology URL: https://noldus.com/blog/video-tracking-ecotoxicology Published: 2012-10-29 15:41:00 Description: The study of behavior has proven itself to be useful in the context of ecotoxicology; the assessment of the impact of pesticides on ecology systems. It is a valuable tool in the risk assessment. The study of behavior has proven itself to be useful in the context of ecotoxicology; the assessment of the impact of pesticides on ecology systems. It is a valuable tool in the risk assessment, beyond the level of just determining mortality rates. Video tracking and ecotoxicology Of course, studying behavior can be done in many ways. In the past, analysis mostly relied on direct visual observation and manual analysis. This is time-consuming and sometimes highly subjective. Video tracking allows for accurate quantifying of locomotor behavior. It delivers objective spatio-temporal data and can be of great help in the advancement of ecotoxicology. Denoël et al. tried it on the evaluation of the toxicity of pesticides in amphibians. Why this research? So why is this research important? Because more and more species are becoming extinct. Amphibians are suffering a major decline, and they are very important in both aquatic and terrestrial ecosystems. Testing possible pollutants for more than just mortality rates provides better insight on the often complex, long-term effects on ecosystems, and thus a more detailed risk assessment. Endosulfan and tadpoles Endosulfan is an example of a pollutant that has great influence on our ecosystems. It is widely used as an insecticide, and sometimes for wood protection. However, it is also already banned or currently being phased out in over 80 countries, including the European Union and the US, because of its acute toxicity. Denoël et al. studied the effect of insecticides on amphibians with the help of video tracking, specifically testing endosulfan on tadpoles. They were interested to find out if endosulfan impaired locomotion and if behavioral alterations could predict mortality. They also used this study to test the usefulness of video tracking in ecotoxicology. Video tracking and behavioral endpoints After a 2-day exposure to endosulfan in either high or low doses (or none at all, as a control group), tadpoles were tested individually in white plastic aquariums. Following 30 minutes of acclimatization, their behavior was recorded for 15 minutes. Video tracking with EthoVision XT extracted the following behavioral endpoints: distance moved, distance to the periphery, swimming activity, and mean speed. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial The effects of endosulfan Endosulfan had a significant effect on each of the behavioral endpoints measured. Even at low concentrations, all behavioral endpoints except speed was altered. High doses led to a lower survival rate, and survival probability was predicted by the behavioral endpoints. The added value of video tracking Video-tracking analysis showed that tadpoles not only moved less, but also differently. They stayed in the open areas longer, while the control group moved more along the walls. This points out the complex behavioral consequences of endosulfan exposure. Behavior translated So how can these results be translated to what would happen in nature? This experiment showed that endosulfan limited the movement of the tadpoles. Less movement indicates that the tadpoles are able to explore less of their habitat, giving them less chance of gathering enough food. They also might be more visible to predators, or less efficient in escaping them. The effects of endosulfan seem to be dose-dependent. At lower concentrations, the study revealed that tadpoles were able to move as fast as the control group, however they moved shorter distances, suggesting that they could not swim for long periods of time. Video tracking reveals complex implications of pollutants on ecosystems So this study points out two major findings. First, endosulfan does not only induce mortality, it also has a complex effect on behavior and the general fitness at sublethal levels. Secondly, video tracking and analysis of behavior can point out such complex effects on behavior, objectively and efficiently. Want to find a suitable video tracking system for your research? Click here. Reference Denoël, M.; Libon, S.; Kestemont, P.; Brasseur, C.; Focant, J.-F.; De Pauw, E. (2012). Effects of a sublethal pesticide exposure on locomotor behavior: A video-tracking analysis in larval amphibians. Chemosphere, 90(3), 945-951, doi:chemosphere.2012.06.037 --- ## 5 must-read articles on zebrafish behavioral research URL: https://noldus.com/blog/zebrafish-behavioral-research Published: 2012-10-16 11:18:00 Description: I have been reading a lot about zebrafish research lately and I thought it would be nice to share some of my favorite articles with you. I have been reading a lot about zebrafish research lately and I thought it would be nice to share some of my favorite articles with you. Think I missed one? Please let me know what your favorite zebrafish article is by commenting below! (Scroll down for a video on zebrafish video tracking!) Unmarked tracking of shoaling This brand new article was submitted for Neuroscience 2012, which is being held right now, even as I am posting this blog. Green and his colleagues investigated the effect of group-size, LSD, MDMA, and alarm pheromone in the shoaling paradigm. I like this article because they compared the (traditional) manual method of measuring inter-fish distances with automated video tracking. For this experiment they used EthoVision XT in combination with the Social Interaction Module, and they did not mark the zebrafish. Shoal density They found that pairs of fish stays closer together than larger groups, and between the larger groups, no differences were found in shoal density. They also found the optimal group size for robust behavioral data: 4 fish. This was the group size they used to confirm the sensitivity of the automated method to modulations that are known to decrease shoaling (LSD and MDMA) and increase shoaling (alarm pheromone). Correlations between manual and automatic testing were high, and this experiment also showed some added value over manual scoring, such as the ability to add duration of proximity as a useful parameter. Green, J.; Collins, C.; Kyzar, E.; Pham, M; Roth, A.; Gaikwad, S.; Cachat, J.; Stewart, A.M.; Landsman, S.; Grieco, F.; Tegelenbosch, R.; Noldus, L.; Kalueff, A.V. (2012). Automated high-throughput neurophenotyping of zebrafish social behavior. Journal of Neuroscience Methods, 210(2), 266-271. Anxiogenic and anxiolytic manipulations I also really liked the publication from Cachat et al. published in 2011. In this paper, they describe their attempts at 3D phenotyping in zebrafish. They used EthoVision XT video tracking software to track zebrafish from both a side and top view, and combined this data to a 3D track. That, in itself, is a good excuse to go and read this article. (By the way, if you are interested in 3D tracking, check this out.) Anxiogenics and anxiolytics Another reason to like this article is that it gives such a nice overview of the effects of several anxiogenic and anxiolytic manipulations on zebrafish in the novel tank paradigm. It shows the strong anxiogenic effects of using alarm pheromone and repeated morphine withdrawal. To a certain extent, using a leopard instead of wild type zebrafish strain, or exposure to caffeine, also gave these effects. The article also shows the strong anxiolytic effects of chronic exposure to fluoxetine (commonly known under the trade name of Prozac), ethanol (alcohol), nicotine, and to a lesser extent that of chronic morphine (strong painkiller). Cachat, J.; Stewart, A.; Utterback, E.; Hart, P.; Gaikwad, S.; Wong, K.; Kyzar, E.; Wu, N.; Kalueff, A.V. (2011). Three-dimensional neurophenotyping of adult zebrafish behavior. PLoS ONE, 6(3), e17597. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Depth preference with surface and substrate cues Rather than just looking at depth preference from a bottom dwelling point-of-view, Blaser and Goldsteinholm took the original route of differentiating between surface and substrate cues. Zebrafish were tested in a split-level tank the authors call "a modified visual cliff apparatus". Basically, the two sides of the aquarium could be adjusted in both substrate and surface level. Surface level was adjusted by moving the transparent ground glass plate up or down in the aquarium, while the substrate below the ground plate could also be moved away from the ground plate. Preference for the deep Blaser and Goldsteinholm found a clear preferences for greater surface depth, and a less pronounced preference for greater substrate depth (the deeper looking side). I thought it was interesting to read that is looks like zebrafish dive down to get distance from the surface rather than getting close to the substrate level on the floor. Blaser, R.E.; Goldsteinholm, K. (2012). Depth preference in zebrafish, Danio rerio: control by surface and substrate cues. Animal Behaviour, 83(4), 953-959. Responses to computer animated fish Saverino and Gerlai published a paper in 2008 that definitely makes it to my list of all-time favorites. They did quite an elaborate study in which they investigated what actually makes a zebrafish attracted to their shoal mates (and what does not). Rather than using all kinds or different fish, they used a computer screen to project Photo-shopped shoals on. Talk about thinking outside the box! What's on TV Test subject were tested in shoals themselves, and had to choose between a normal shoal on one side, and an alternative shoal on the other. Turns out, zebrafish don't dislike red colored zebrafish, but they prefer normal colored ones. However, when given the choice between wild-type and yellow colored zebrafish, they actually liked the yellow colored ones better! (Authors point out that this might be caused by the fact that vividly colored zebrafish, as they participate in courtship, exhibit more yellow coloration.) Striping does not seem to matter to zebrafish in this study. They showed no clear preference between wild-type and otherwise striped (vertical stripes or no stripes at all) fish. Body shape does seem to matter. While a fat, short looking zebrafish did not elicit preference nor avoidance compared to the wild-type, the stretched, elongated looking one did. Zebrafish strongly avoided this image, which might be explained by the fact that it looks like a predator. To read more about this and the other experiments that were done in this study, read Saverino, C.; Gerlai, R. (2008). The social zebrafish: Behavioral responses to conspecific, heterospecific, and computer animated fish. Behavioural Brain Research, 191(1), 77-87. Modified open field testing The last paper I want to mention today is the one from Champagne and colleagues. I like it because it represents a straight-forward translation from open field testing in rodents, but with a twist. They designed an open field test that was divided into 16 virtual squares. The 16 squares of the open field were divided in outer zones (12 squares) and inner zones (4). So far it is similar to the open field test we know well from rodent studies, where they often measure thigmotaxis. The twist But this is the twist: they combined this inner/outer preferences with an extra dimension by making one wall transparent (giving the illusion of an escape route), and the others opaque, effectively dividing the outer zone into a light zone (4 squares) and darker zone (8 squares). They took two groups of fish, one that was stressed by net handling and one control group. They tested fish individually and tracked them from a top view, using video tracking software. Both groups spent more time in the outer zone than in the inner zone, and this preference was more profound in the control group. Both groups also prefer the transparent zone to the opaque zone; again this was more pronounced in the control group. These results suggest that the natural inclination is to engage in thigmotaxis and to find a way out (go into the lighter zone) was attenuated in the stressed group. The acute stress might momentarily relieve anxiety in zebrafish. Read more in Champagne, D.L.; Hoefnagels, C.C.M.; de Kloet, R.E.; Richardson, M.K. (2010). Translating rodent behavioral repertoire to zebrafish (Danio rerio): Relevance for stress research. Behavioural Brain Research, 214, 332-342. Let us know! If you have any suggestions to add to my list of favorite zebrafish articles, please let me know in the comments below! Read more about zebrafish research in these blog posts. --- ## Don’t dwell on it… dive into zebrafish research! URL: https://noldus.com/blog/dive-into-zebrafish-research Published: 2012-10-11 15:31:00 Description: I recently wrote about other translations from rodent studies to zebrafish, such as the investigation of learning and memory and social behavior. Now it’s time to talk about anxiety and exploration. About the novel tank diving test and bottom dwelling in zebrafish research I recently wrote about other translations from rodent studies to zebrafish, such as the investigation of learning and memory and social behavior. Now it's time to talk about anxiety and exploration. In zebrafish research, the novel tank diving test and behavior known as bottom dwelling are ways to measure anxiety-related responses. The importance of research on anxiety We all know what anxiety is, and normally it is one of the ways your body helps keep you safe. But for some, anxiety is something that can deeply interfere with normal functioning. In fact, anxiety disorders are amongst the most common mental health problems, often with great costs to society. Research on anxiety disorders can shed light on diagnosis, treatment, and prevention. It also helps discover possible genetic components and environmental factors that contribute to these disorders. Many paradigms for studies on rodents have been well validated in research, and now studies on zebrafish show promising results as well. Neuroscience research In neuroscience research, anxiety and curiosity are, in a way, seen as counterparts. Think of a plus maze – a rat or mouse showing anxious behavior stays in arms closed off by walls where it feels nice and protected. But as it becomes more curious, it will go and explore the open arm. The same holds true for the open field test. In a novel, open field, the rat or mouse is likely to show thigmotaxis: sticking to the walls. But as time progresses, or when animals are less anxious due to genetics or drugs, they'll go and explore the center. Anxiety and exploration in zebrafish So how can we translate the novel open field study to zebrafish research? Well, that might be one of the easiest questions ever. A novel aquarium! The novel tank diving test can indeed be seen as the equivalent of the novel open field, and behavior shown by zebrafish is similar to the typical behavior of a rat or mouse. That being said, zebrafish don't stick to the sides of the aquarium, but rather, to the bottom. As time progresses, they gradually explore the top-most part of the aquarium. What to measure in a novel tank test This latency to cross to the top part of the aquarium is seen as an important parameter for anxious behavior, as is the relative amount of time spent in the top portion during the complete trial. Additional parameters include the number of transitions between the upper and lower half of the tank, distance swum, swim speed, number of freezing episodes, and erratic movements. Why video tracking is useful As you can see, this test is pretty straight-forward, but it can be even easier. With video tracking software, you can do this whole test automatically. You will still put the zebrafish in the tank yourself, but tracking its location, speed, distance swum can all be done for you! All you need is a camera and tracking software. In the software you can define the video image: just draw an upper and lower half (or three horizontal zones, if you want some more detail). Then the software tracks your animal and automatically determines the values of the parameters you've chosen. See it in action: Watch the video on YouTube Or read more about how it is done in the white paper! (see below) Changes in behavior So your average zebrafish will dive right down to the bottom as soon as you release it in the novel tank. It might freeze for a while, then it will gradually start exploring. First the bottom half, then the top. If it stays near the bottom, this is referred to as bottom dwelling. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Of course, as zebrafish are highly sensitive to pharmacological manipulation, the effect of several drugs is subject of many studies. This research helps to determine the effectiveness of anxiolytics or the anxiolytic or anxiogenic side-effects of other drugs. To read more about different types of research, download the free white paper. References - 1.Bencan, Z.; Damiyon, S.; Levin, E.D. (2009). Buspirone, chlordiazepoxide and diazepam effects in a zebrafish model of anxiety. Pharmacology, Biochemistry and Behavior, 94, 75-80. - 2.Cachat, J.; Stewart, A.; Utterback, E.; Hart, P.; Gaikwad, S.; Wong, K.; Kyzar, E.; Wu, N.; Kalueff, A.V. (2011). Three-dimensional neurophenotyping of adult zebrafish behavior. PLoS ONE, 6(3), e17597. - 3.Levin, E. (2011). Zebrafish assessment of cognitive improvement and anxiolysis: filling the gap between in vitro and rodent models for drug development. Reviews in the Neurosciences, 22(1), 75-84. --- ## The search for autism models continues - why rats are important URL: https://noldus.com/blog/autism-models Published: 2012-10-04 15:00:00 Description: Autism (ASD) continues to be an important topic in scientific research. Although finding the actual cause of ASD is still years away, there have been several studies that point to a strong genetic component. Autism, or rather Autism Spectrum Disorder (ASD), continues to be an important topic in scientific research. Although finding the actual cause of ASD is still years away, there have been several studies that point to a strong genetic component (though not all cases are hereditary). People with ASD suffer from difficulties in social interaction and communication because they are limited in their empathic abilities and intuition and have a hard time expressing their emotions. There are also a number of other ways ASD expresses itself, such as compulsive and repetitive behavior. The search for autism models continues - why rats are important You can image this can make life hard, and a large part of people suffering from ASD lead lonely lives. There is no cure, but there are some therapies. That is why scientific research is important. As potential causes and cures are being studied, the need for good animal models of ASD is becoming more and more important. Rats over mice ASD is uniquely human, but fundamental aspects can be modeled in animals. Rats and mice are typically the animals used in this research, and often, rats are preferred over mice because they exhibit social behavior that resembles human social behavior. They also have a more complex neural circuitry, giving them greater cognitive capacity. The search continues Recently, Autism Speaks and SAGE labs announced an expansion of their collaboration to find better animal models for ASD. Their goal is to generate genetically modified rat models with important autism-associated genes to accelerate translational autism research. (Find their press release here.) RESOURCES Read more about EthoVision XT Find out how EthoVision XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources The VPA model Not surprisingly, many publications exist that describe the search and validation of several animal models. A recent example is the study from Foley et al. in Neuropharmacology. The rat model in question involves in utero exposure to valproic acid (VPA). Originally, this drug is used as a treatment for several disorders including epilepsy, bipolar disorder, and schizophrenia. VPA alters the development of neurons in the brain. Exposure during pregnancy is associated with the risk of autism in a child, which is why it also reveals its potential as a model for autism. Foley et al. attempt to validate this VPA rat model of autism in terms of social cognitive deficits, a core symptom of ASD. Their experiments tested social reciprocity, detection of biological motion, and spatial learning (as an indicator of dorsal stream processing of social cognition). And indeed, each parameter was found impaired in the VPA treated rats. Social reciprocity Animals were placed in an apparatus that allowed restricted contact (olfactory, auditory, and visual) to other areas through holes in the outer walls. On one side, a social stimulus animal was placed. The apparatus itself was divided into three sections with partial walls, to provide a neutral zone in which the animal started the experiment. Exploratory behavior was monitored with an overhead camera and EthoVision XT video tracking. Time spent in each area (social, center, non-social zones) was of main interest. VPA treated rats spent half the time investigating the social stimulus compared to the control group, and they had a significantly lower approach-avoidance score. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Biological perception Next, the ability to recognize biological motion was tested. A point light display (moving dots) mimicked the movement of a walking hen, representing the biological movement. (See the video files here from Vallortigara et al.) Control animals were able to discriminate this movement from more 'unnatural' representations of the same light dots, whereas VPA treated animals could not. (Choosing the image consisted of a nose poke to the touch screen display. Poking it while the biological motion was played resulted in a food reward.) Spatial learning To test spatial learning, the water maze paradigm was used. It consisted of acquisition and recall components and swim behavior was monitored with EthoVision XT. First the rodent's ability to locate the platform and the improvement during consecutive trails was measured. VPA treated animals were slower at reaching the platform across training sessions. This was not the result of slower swim speeds, but of an inadequate search strategy. Secondly, probe trials (without the platform) were held to test whether the rats recalled the quadrant the platform used to be located. The retention of the platform position was significantly disrupted in VPA treated rats. To learn more about EthoVision XT and the water maze, watch this video: Promising model of ASD This publication validates the VPA model in terms of showing robust deficits in social cognition and recognition of biological motion. These deficits were associated with spatial learning impairments, indicating that hippocampal dorsal stream processing was dysfunctional. VPA exposure in utero indeed seems to result in a significantly compromised cognitive system, crucial to normal social behavior in the adult animal. Thus the authors conclude that this might be "a promising neuroendophenotype to bridge preclinical to clinical drug development initiatives". References - Foley, A.G.; Gannon, S.; Rombach-Mullan, N.; Prendergast, A.; Barry, C.; Cassidy, A.W.; Regan, C.M. (2012). Class I histone deacetylase inhibition ameliorates social cognition and cell adhesion molecule plasticity deficits in a rodent model of autism spectrum disorder. Neuropharmacology, 63, 750-760. - Vallortigara, G.; Regolin, L.; Marconato, F. (2005). Visually inexperienced chicks exhibit spontaneous preference for biological motion patterns. PLoS Biology, 3(7), e208. --- ## Why observe driver behavior and distraction URL: https://noldus.com/blog/why-observe-driver-behavior-and-distraction Published: 2012-09-20 13:58:00 Description: Listening to your favorite music in your car can have a very uplifting effect and can help create a pleasant atmosphere. Also, having a conversation while driving can be a very efficient way of spending your time. Listening to your favorite music in your car can have a very uplifting effect and can help create a pleasant atmosphere. Also, having a conversation while driving can be a very efficient way of spending your time. By selecting great songs or having a fun conversation, our in-car-time becomes enjoyable, sometimes even relaxing (somewhat depending on your choice of music). Nowadays, most people do not simply listen to their CD player - the technology for listening to music has become more sophisticated. A number of different devices and techniques are built into cars to allow the driver to select music while keeping his or her eyes on the road. However, performing a task other than driving can still result in an extremely dangerous situation. There is a reason why making a phone call with a telephone in your hand is forbidden in many countries! Researchers are taking on the challenge to look into the best possible way to select music while driving. Driving simulation experiment Tuomo Kujala (2012) evaluated three in-vehicle touch screen scrolling methods (buttons, swipe, and kinect scrolling) and states that the novel interaction techniques for in-car use should be carefully tested for distraction effects before making them available for consumers. In this study, a driving simulation experiment was designed in which participants needed to search for music. While the participant was driving and searching for tracks, the researchers looked at distractive behaviors: for example lane-keeping accuracy, visual demands, and search task performance were measured. Eye tracking equipment and video analysis software The Observer XT were used to record eye movements, gaze, and behavior. This experiment was set up to select the best suitable in-vehicle display by comparing driver behavior in different situations. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial The safest way is to select your music before you start driving. But, when one is on the road and trying to select music, Kujala recommends page-by-page swiping. He explains this method is the least distracting "due to its systematic nature and low levels of pointing accuracy and visual attention required for scrolling the pages". Interestingly, participant ratings indicated buttons and not page-by-page swiping as the least distracting and the most preferred scrolling method, thereby showing that further research is needed. The participants may choose buttons instead of swiping because of previous experiences using this form of selection. New simulator In Advanced Driver Vehicle Interface in a Complex Environment – (the ADVICE research project) TomTom, TNO, HAN, Delft University, Noldus, and Green Dino take up the challenge to build a driver observation system for human-machine interface evaluation studies. This system's design will be highly adaptable in order to support various automotive research questions. The system will be able to collect and interpret information from various sources, such as the (simulated) vehicle, portable navigation devices, cameras, eye trackers, and psycho-physiology. So when you are interested in the latest in automotive research, it is an interesting research project to follow. Reference Kujala, R. (2012). Browsing the information highway while driving: three in-vehicle touch screen scrolling methods and driver distraction. Personal and Ubiquitous Computing, DOI: 10.1007/s00779-012-0517-2. --- ## Drunken mice get aggressive on Alzheimer’s drugs URL: https://noldus.com/blog/drunken-mice-get-aggressive-alzheimers-drugs Published: 2012-08-16 08:19:00 Description: Will there ever be a cure for alcoholism? Well, some laboratory studies show that certain drugs might stop the cravings. But they might also cause serious side-effects such as aggressive behavior. Will there ever be a cure for alcoholism? Well, some laboratory studies show that certain drugs might stop the cravings. But they might also cause serious side-effects such as aggressive behavior. Drunken mice on drugs Newman et al. tested the behavior of alcoholic mice under the influence of several glutamate-antagonists; drugs that play a role in disorders such as Alzheimer's and schizophrenia but might also be beneficial for recovering alcoholics. They found that certain drugs combined with alcohol resulted in escalated aggressive behavior, while others did not. Their results were recently published in Psychopharmacology. Glutamate can cause brain damage Glutamate is a neurotransmitter that plays an essential role in learning and memory, but overstimulation of brain cells by glutamate causes disruption or even cell death. It is what happens in disorders such as Alzheimer's. Not surprisingly, substances that prevent the work of glutamate (so called glutamate antagonists) are widely studied for their effect on Alzheimer's, schizophrenia, autism, etc. Some of these drugs seem to work on alcoholics, too. Glutamate and aggression In addition to its importance for learning and memory, glutamate also plays an important role in the regulation of aggression. So drugs that disrupt glutamate (and thus prevent cell death) may also cause heightened aggression. In other words, while some glutamate antagonists are suitable to use as a treatment, others can cause severe disturbances in behavior. Alcohol and aggression Alcohol also works as a glutamate antagonist. Newman et al. hypothesized that the violence and aggression that is so closely linked to alcoholism, might be explained by the dysregulating effect alcohol has on the glutamate system and therefor on aggressive behavior. An Alzheimer's drug for alcoholics Alcohol (or ethanol, as it is used in laboratory studies) can possibly be 'replaced' by other glutamate antagonists that might not have the same cognitive and behavioral consequences as alcohol. Memantine, a drug for Alzheimer's, is one example researchers Newman et al. focused on. They combined alcohol (ethanol) with a range of drugs, including memantine, that all in some way inhibit the glutamate system, and then tested the mice for aggressive behavior in resident-intruder tests. The resident-intruder test The resident-intruder test is a test in which – you guessed it – an intruder mouse is put into the home cage of the resident mouse. Then behavior is recorded. The researchers alternated this test with a version in which the resident was put first put in another 'neutral' cage, after which the intruder was introduced. To test the effects of alcohol and drugs on behavior, the mice were trained to self-administer ethanol and subsequently treated with several types of drugs that directly or indirectly inhibit one of the glutamate receptors, the NMDA receptor (such as memantine, neramexane, and ketamine) before the resident-intruder test began. Social instigation Additionally, the effect of an instigator instead of ethanol administration, in combination with NMDA receptor antagonists was investigated. An instigator (experimentally naïve) mouse was put into a protective cage, into the resident's home cage for 5 minutes. This was followed by the neutral cage confrontation as described above. Scoring aggressive and non-aggressive behaviors In all tests, behavior was video-taped and analyzed with The Observer XT software. Aggressive behaviors included attack bites and sideways threats, non-aggressive behaviors described in this study are walking and rearing. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Results Some drugs indeed showed interaction with ethanol, specifically heightening aggression (memantine and MTEP). Others generally heightened activity in combination with ethanol, suggesting more general arousal (neramexane), or showed no interaction with ethanol at all (ketamine and LY379268). The results from the social instigation test, where no ethanol was used, suggests that ethanol interaction is necessary for the select glutamatergic compounds to intensify aggressive behavior. To read more about the specific results: Newman, E.L.; Chu, A.; Bahamón, B.; Takahashi, A.; DeBold, J.F.; Miczek, K.A. (2012). NMDA receptor antagonism: escalation of aggressive behavior in alcohol-drinking mice. Psychopharmacology, epublication. --- ## A story of dogs and dolls URL: https://noldus.com/blog/a-story-of-dogs-and-dolls Published: 2012-08-09 09:06:00 Description: When finding the right dog for yourself, you probably won’t choose an aggressive one, will you? You don’t want it to attack your friends, kids, or other dogs. You could try using a temperament test, but how reliable are they? When finding the right dog for yourself, you probably won't choose an aggressive one, will you? You don't want it to attack your friends, kids, or other dogs. You could try using a temperament test to predict behavior in dogs, but how reliable are they? As good as the real thing? That was the question researchers at the School of Veterinary Medicine (University of Pennsylvania, USA) were asking themselves, too, because these temperament tests involve dolls. And dolls just aren't human. For obvious reasons, you don't want to go about testing if your dog is aggressive towards children by putting an actual child in front of it. So using a doll seems like a good plan. But can it really say something about how the dog is going to react to an actual child, in everyday life, that smells and moves different than the doll? It turns out, it can. Investigating the predictability of the doll-test For the same reason you don't want to challenge a dog with a real child, it is difficult to compare test results with real-life results. ("Ok, so he tore up this doll… let's see how it likes the neighbor's kid!") But you can also investigate predictability by looking at the past. These researchers looked at the behavior towards an adult female experimenter and studied the dog's reaction to three different objects. Two of these objects were dolls, one representing a child, the other, a dog. The third object was a paper-filled garbage bags with eyes, to see if the dogs would differentiate between the ambiguous objects and the dolls. Their reaction to the dolls was compared to the history of the dogs and results from a modified version of the C-BARQ (Canine Behavioral Assessment & Research Questionnaire). Volunteer dogs The researchers found 34 volunteer dogs (and owners) to participate in their study. They were categorized into three different categories according the history of the dog; a control group with no history of aggression and two groups with a history of aggressive behaviors towards children or other dogs, respectively. These dogs were put to the test – confronted with a female stranger (the experimenter) and the three different objects, their behavior was video-recorded and analyzed with The Observer XT. (And they've put the ethogram in their publication, it's worth a look.) They also used The Observer XT to determine the reliability of the observations after rescoring them 8 months later. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Differences in behavior As you might expect, the control group spent a fair amount of their attention on the female stranger, while other groups showed more avoidance or looking away. When confronted with the child-like doll, the group with a history of aggression towards children showed significantly more aggressive behaviors than the other groups. The fake dog test showed somewhat similar results. Of the 6 dogs in total that showed aggression, 1 was a control dog, 2 belonged to the group that had a history of aggression towards other dogs, and 3 belonged to the group that had a history of aggression towards children. However, owners of the last 3 dogs reported that there also had been issues with other dogs as well. The garbage bag turned out to be a bit scary, at least for the dogs with a history of aggression. They barked and showed fearful reactions, while the control group spent a decent amount of their time looking at the object while wagging their tail, and playing. Dolls are good enough for testing The reactions of the dogs to the dolls compared to the other object were clearly distinguishable. The dogs show social reactions to the dolls that they did not show to the garbage bag with eyes. So that is one-zero for the dolls. Second, the reactions to the dolls correlates with the history of the dog, which became clear when the researchers compared the behaviors to the results of the C-BARQ. Another point for the dolls. Even though they might not smell or move like the real thing, dolls are good enough to elicit at least some behavior that indicates how the dog reacts in real life. That makes them a good tool for temperament tests, but the authors stress that these tests with dolls should not be the only screening method. At the very least, excessive reaction to these dolls indicates that these dogs need to be monitored more carefully. And not put in the same room as your Chihuahua… But you guessed that before you read this post, right? References Barnard, S.; Siracusa, C.; Reisner, I.; Valsecchi, P.; Serpell, J.A. (2012). Validity of model devices used to assess canine temperament in behavioral tests. Applied Animal Behaviour Science, 138, 79-87. --- ## Unraveling primate behavior, why do monkeys rub their fur? URL: https://noldus.com/blog/unraveling-primate-behavior Published: 2012-07-30 09:36:00 Description: Did you know that tufted capuchin monkeys (Cebus apella) rub their fur vigorously with substances such as leaves, fruit, or insects? Such substances are often insecticidal, antiseptic, or anti-inflammatory. Did you know that tufted capuchin monkeys (Cebus apella) rub their fur vigorously with substances such as leaves, fruit, or insects? Such substances are often insecticidal, antiseptic, or anti-inflammatory. Therefore, fur rubbing may improve fur condition along with having a medical function. Fur rubbing leads to aggression In animal behavior research, it is widely believed that fur rubbing is used in social bonding. However, for tufted capuchin monkeys, this is not true [1]. Animals that rub their fur encounter more aggression and have less friendly behavior. They have less grooming behavior and play less than animals that do not rub their fur. This of course puzzles the scientists that study primate behavior. Do the monkeys perhaps fight for fur rubbing material? Or does fur rubbing make them smell so bad that their group members become aggressive? What is causing this aggression? In a recent study, Paukner and Suomi (2012) [2] investigate the cause of the aggression after fur rubbing. They keep monkeys for 15 minutes in separate cages, either with pieces of onions, that the animals use to rub their fur with, or pieces of apple, that the animals just eat. Afterwards, the animals are returned to their social group. The authors use Pocket Observer and The Observer to study the behavior of the monkeys during the 15 minutes in the cages and during two 15 minutes intervals after the monkeys return to their group. The authors look how much time the animals spend in proximity with other monkeys and whether the monkeys initiate or receive aggression, and initiate or receive friendly behavior. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Monkeys that rub their furs are treated badly by group members The authors find no difference between the monkeys that were given onion pieces and the ones that had an apple pieces in time spent in proximity of other monkeys. Also, there is no difference between the two groups in initiating aggression or friendly behavior. However, the animals that were given onion pieces receive more aggression and less friendly behavior from group members than the animals that were given apple pieces. Fur rubbing has no social function The authors conclude that the aggression is not caused by competition for fur rubbing material. Remember, in the present research set-up, there is no lack of fur rubbing material. So what is causing the aggressive behavior by group members? Possibly the smell of the onion masks the smells that the monkeys need for social interaction. Or, the animals that rub their fur behave different from the animals that do not and therefore encounter aggression. Future research should unravel this. But the widespread belief in primatology that fur rubbing has a social function, is not true for tufted capuchin monkeys. References - Paukner and S.J. Suomi, 2008. The effects of fur rubbing on the social behavior of tufted capuchin monkeys. American Journal of Primatology, 70, 1007–1012 - Paukner and S.J. Suomi, 2012. Social after-effects of fur rubbing in tufted capuchin monkeys (Cebus apella): increased antagonism and reduced affiliation. Primates, 53(2), 297-301. You might like to read this blog as well: Secret sex and promiscuity - Mating behavior of Rhesus monkeys --- ## Secret sex and promiscuity - Mating behavior of Rhesus monkeys URL: https://noldus.com/blog/mating-behavior-rhesus-monkeys Published: 2012-07-30 08:27:00 Description: In Rhesus monkeys the optimal sexual strategy is different for Alpha males, other males and females. Alpha males want females to mate exclusively with them, whereas other males and females benefit from promiscuity. In Rhesus monkeys the optimal sexual strategy is different for Alpha males, other males and females. Alpha males want females to mate exclusively with them, whereas other males and females benefit from promiscuity. With secret sex, females and bystander males counteract the strategies of alpha males to dominate the group. Conflicting mating strategies Did you know that in social groups of monkeys, the optimal mating strategy of alpha males conflicts with the optimal strategy of females and the other males? A dominant male wants females to mate exclusively with him to ensure that the offspring is his. To ensure this, the alpha male guards females and interrupts mating by other males [1,2]. On the other hand, bystander males of course also want to mate and produce offspring. But how do they achieve this? The benefits of promiscuity While alpha males want females to be monogamous, females benefit from promiscuity. Having more mating partners decreases the chance that offspring is attacked or killed, since males do not attack offspring of their mating partners [3]. Also, by mating with different partners, females increase the amount of goods they get from males and increase the number of males that guard the group [4,5]. Females will therefore try to escape from the exclusive right of the alpha males to copulate with them. But how? Do monkeys have secret sex? In a recent article in the American Journal of Primatology, Overduin-de Vries et al. [6] hypothesize that females and bystander males copulate secretly out of sight of the alpha male. They investigated whether mating between females and bystander males occurs more often in absence than in presence of the alpha male. In addition to this, they looked whether the male's rank is of importance for the effect of their presence on mating behavior of females with other males. The researchers used The Observer XT for their ethological research and used an ethogram with different phases of the mating behavior. For both males and females they coded: - Inviting to copulate - Accepting or rejecting such an invitation - Attempting to copulate - Mounting - Thrusting - Copulating FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Counteracting the alpha male with secret sex Indeed, the presence of males affected the mating behavior of females with other males. This effect was the largest for the absence or presence of the alpha male. The females copulated more frequently with bystander males and spent more time copulating when they were out of sight of other males. This way, females avoid aggressive interruptions of copulations with other males. Hence, while alpha males do their best to monopolize the group and keep the females for themselves, females counteract this strategy with secret sex and promiscuity. This raises the question who is really in charge of the group, the alpha male or his females? RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - Chapais B. (1983). Reproductive activity in relation to male dominance and the likelihood of ovulation in rhesus monkeys. Behavioral Ecology and Sociobiology, 2, 215–228. - Manson J.H. (1996). Male dominance and mount series duration in Cayo Santiago rhesus macaques. Animal Behavior, 51, 1219–1231. - Hausfater G.; Hrdy S.B. (1984). Infanticide: comparative and evolutionary perspectives. New York: Aldine. 598 p. - Engelhardt A. (2004). The significance of male and female reproductive strategies for male reproductive success in wild longtailed macaques (Macaca fascicularis). Göttingen, Germany: Cuvillier verlag. 109 p. - Wolff J.O.; Macdonald, D.W. (2004). Promiscuous females protect their offspring. Trends in Ecology & Evolution, 19, 127–134. - Overduin-de Vries, A.M.; Massen, J.J.M.; Spruijt, B.M.; Sterck, E.H.M. (2012). Sneaky Monkeys: An Audience Effect of Male Rhesus Macaques (Macaca mulatta) on Sexual Behavior. American Journal of Primatology, 74, 217–228. --- ## Sex preference and other social aspects of zebrafish behavior URL: https://noldus.com/blog/social-aspects-zebrafish-behavior Published: 2012-07-19 10:25:00 Description: Social behavior is a well-known topic of neuroscience research, since it is so often affected in psychiatric disorders. Think of obvious examples such as schizophrenia and autism. Image courtesy: Prof. Gerlai, University of Toronto Missisauga Social behavior is a well-known topic of neuroscience research, since it is so often affected in psychiatric disorders. Think of obvious examples such as schizophrenia and autism. Social dysfunction can have a severe impact on daily functioning, therefore many studies in search of genetic disposition or drug targets include social behavior paradigms. Social behavior is complex and multi-faceted. But actually, in studies using animal models, most social interaction is measured in a very straight-forward way; by proximity. Zebrafish have a strong, natural tendency to form shoals, and this tendency and the density of these groups is influenced by several factors, from genetics to pharmacological manipulation. How close they swim together or if one fish approaches the other are practical measures to investigate social behavior in zebrafish. The influence of food and predation on shoaling When competition for food increases, the distance between fish does too. Miller and Gerlai [5] showed this in an experiment where they scattered food in a tank with 16 zebrafish and found that the distance between the fish doubled. This same study also used a hawk model to simulate a predator attack. Zebrafish initially scattered out, increasing the distances between them, followed by fast regrouping into an even tighter shoal than before. Appearances and social behavior Zebrafish care what their group mates look like. The effects of phenotype or gender on social interest have been heavily studied. Engeszer et al. [1] studied wild-type zebrafish and a variant without stripes, and reared them in isolation, with their own phenotype or cross-reared with the other phenotype. It turns out that rearing treatment was the determining factor, not genetics; when given the choice between striped and non-striped fish in a social preference test, they choose to side with the appearances they were used to during rearing. The isolates didn't show a preference at all. What if they have not been biased with how they grew up? Saverino and Gerlai [7] did an interesting study using a video screen to project manipulated images of zebrafish, investigating the influence of color, size, and patterning of the fellow zebrafish. Red zebrafish are not aversive, but not preferred either, while yellow colored ones are. A stretched image of a zebrafish was avoided, while a compressed picture did not make a difference. Stripe-less or vertically striped zebrafish also did not get significantly less or more attention. Do males like females? Yes, Ruhl et al. [6] found that males prefer a shoal of females over a shoal of males. Do females like males too? No: in the same study, females didn't show a preference. Size does matter Onto the next question - do zebrafish like a crowd? Ruhl et al. [6] investigated the effect of shoal size on social behavior, and found that females prefer larger shoals, while males show no preference in a social preference test. Green et al. [2] describe the effect of shoal size on shoal density and report that 2 fish stayed significantly closer together that fish in groups containing 3, 4, 5, 6, 7, or 8 fish. Social behavior and pharmacology Now that we understand the basics of zebrafish social behavior, we can investigate the influence of genetics (modeling disorders) and pharmaceuticals on social behavior. There are many interesting avenues for researchers to explore. Several pharmaceuticals have proven to increase sociability. Some examples includes mescaline [4], sulpiride and haloperidol (both reversing the effect of proline in a zebrafish model of hyperprolinemia [8]). Others prove to decrease sociability: LSD [3], or have no affect: PCP [4]. Automatic tracking of groups So now we know a couple of things. 1) Social behavior is an interesting topic of research because it is so often affected in psychiatric disorders. 2) Zebrafish make for an interesting model in these studies because they show social behavior. 3) Social behavior is readily influenced by genetics, chemicals, and other environmental factors. The good news is that this research, mostly taking place in the form of social preference tests or shoaling (inter-fish distances) tests, is easily and reliably automated. Tracking software follows fish and measures location, proximity, inter-fish distances, velocity, durations, and many more parameters automatically. Green et al. [2] illustrates this great potential of automatic video tracking software and its use in social behavior studies in zebrafish. They tracked individuals in a group of unmarked zebrafish. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Get your Free trial You can read more about zebrafish social behavior applications here. Also check out other zebrafish-related blogs. References - Engeszer, R.E.; Ryan, M.J.; Parichy, D.M. (2004). Learned social preference in zebrafish. Current Biology, 14, 881-884. - Green, J.; Collins, C.; Davis, A.; Kyzar, E.; Pham, M; El-Ounsi, M.; Roth, A.; Gaikwad, S.; Lansdman, S.; Cachat, J.; Grieco, F.; Tegelenbosch, R.; Noldus, L.; Kalueff, A.V. (2012). Towards automated high-throughput neurophenotyping of zebrafish social (shoaling) behavior. Society for Neuroscience SfN-2012 Abstract book, New Orleans, USA. - Grossman, L.; Utterback, E.; Stewart, A.; Gaikwad, S.; Chung, K.M.; Suciu, C.; Wong, K.; Elegante, M.; Elkhayat, S.; Tan, J.; Gilder, T.; Wu, N.; DiLeo, J.; Kalueff, A.V. (2010). Characterization of behavioral and endocrine effects of LSD on zebrafish. Behavioural Brain Research, 214, 277-284. - Kyzar, E.J.; Collins, C.; Gaikwad, S.; Green, J.; Roth, A.; Monnig, L.; El-Ounsi, M.; Davis, A.; Freeman, A.; Capezio, N.; Steward, A.M.; Kalueff, A.V. (2012) Effects of hallucinogenic agents mescaline and phencyclidine on zebrafish behavior and physiology. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 37(1), 194-202. - Miller, N.; Gerlai, R. (2007). Quantification of shoaling behaviour in zebrafish (Danio rerio). Behavioural Brain Research, 184, 157-166. - Ruhl, N.; McRobert, S.P. (2005). The effect of sex and shoal size on shoaling behaviour in Danio rerio. Journal of Fish Biology, 67, 1318-1326. - Saverino, C.; Gerlai, R. (2008). The social zebrafish: Behavioral responses to conspecific, heterospecific, and computer animated fish. Behavioural Brain Research, 191(1), 77-87. - Savio, L.E.B.; Vuaden, F.C.; Piato, A.L.; Bonan, C.D.; Wyse, A.T.S. (2012). Behavioral changes induced by long-term proline exposure are reversed by antipsychotics in zebrafish. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 36, 258-263. --- ## Human-robot interaction in remote friendships and family relations URL: https://noldus.com/blog/human-robot-interaction-in-relations Published: 2012-07-18 10:49:00 Description: Don’t you miss the touch of a loved-one when they are far-away? Skype and a number of other communication channels are great solutions to talk and even video chat when you are apart. Don't you miss the touch of a loved-one when they are far-away? Skype and a number of other communication channels are great solutions to talk and even video chat when you are apart, but they can't make up for the physical connection. There might be a fresh and original alternative. Since robots are becoming more and more common, and technology is improving rapidly, researchers are now looking into the possibilities of using robots as social mediators to enhance remote communication between people. Gaze, smile, talk Papadopoulos et al. (2012) investigated the role of interactive robots as communication mediators. For this study, a Sony AIBO robot was used. This is a little pet-like autonomous robot that is able to learn and mature. Participants were asked to play a game with the help of the robot while communicating with another participant seated in another room. Behavior and game experience were measured using video recording and coding, and a questionnaire. For the video analysis, the researchers developed a coding scheme consisting of the following behaviors: - 1.Gaze: at screen, at robot; - 2.Smiles; - 3.Talk: socially oriented, task oriented. Subsequently, a variety of social cues have been recorded. The Observer XT was used to code participant's behaviors. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Maintain and strengthen distanced relationships After observing and analyzing the behavior and game experience of 40 participants, Papadopoulos et al. conclude that the presence of a robot positively affected the overall remote communication experience during the game. Participants expressed more social cues and shared their game experiences through the robot with each other. Papadopoulos et al. explain that a robot has the potential of enhancing human-human experience in remote communications and that this would consequently make the interaction more enjoyable. Though, concentrating on both the game and the robot seemed a bit difficult. Robots as social mediators Bringing a robot into a conversation can help maintain and strengthen distance relationships. Papadopoulos, Dautenhahn, and Ho are on their way towards their long term goal - developing robots as social mediators that can support human-human communication in remote interaction scenarios. References Papadopoulos, F.; Dautenhahn, K.; Ho, W.C. (2012). Exploring the use of robots as social mediators in a remote human-human collaborative communication experiment. Journal of Behavioral Robotics, 3 (1), 1-10. --- ## Time based relations in gait analysis URL: https://noldus.com/blog/temporal-gait-parameters Published: 2012-07-05 15:45:00 Description: I have written two blog posts about static gait parameters. Now it’s time to talk about all four paws, and the time based relationships between them. If you ask me, we’ve been saving the best blog post for last! In my last two blog posts, I wrote about static gait parameters. Specifically, what a single footprint can tell you and what kind of information you can get from the distance relationships between prints. Now it's time to talk about all four paws, and the time based relationships between them. If you ask me, we've been saving the best blog post for last! Temporal relations Temporal relations are the parameters that have to do with time, such as timing and duration. This is where automation of gait research shows it true colors. So why would you want to know about the timing of footfalls? Let's say you have two rats that walk in exactly the same way, with the same distances between each paw print, and the same pattern of walking. But one gets to the other side faster. In theory, this is because one walks faster. In other words, while the distance between the successive placement of one paw remains the same, the time it took to move this foot, was less. The stride (stance plus swing phase of the foot) was faster, not longer. This might be caused by a shorter stance phase, a shorter swing phase, or both, depending on the disorder that underlies this symptom. Before modern gait analysis systems were used, these temporal differences stayed obscured. Nowadays, systems like CatWalk XT can calculate over 30 different temporal gait parameters. Temporal parameters in action Let me give you some examples of these parameters in action: Shorter stance If your leg or foot hurts, you don't want to put your weight on it. This is exactly what animal models of several disorders show. Animals are found to keep their affected paw on the ground for a shorter amount of time in studies on sciatic nerve injury [1,2,3,11], ischemic stroke [7], and arthritis [10]. Additionally, Hoffman et al. [8] saw this compensated in other paws, in study on arthritis. When the stance duration decreases, the stand duration relative to the total stand and swing duration often also decreases, as Ferland et al. [5] show in their arthritis model. In a study of Encarnacion et al. [4] on ischemic stroke, all paws show shorter time on the ground, but a shorter duty cycle was only found in one paw. Longer stance Contrary, in spinal cord injury research [9] the hind paws stay longer in contact with the ground. This is compliant with the typical 'dragging of the hind body' seen in spinal cord injury models. This longer stance phase is also found in the Parkinson's model used by Westin et al. [12]. Longer swing In most instances, a shorter time on the ground is compensated by a longer air time of that paw, reflected in a longer swing duration. This is found in models of sciatic nerve injury [1,2,3,11] and arthritis [5]. Certain treatments are proved effective in studies on sciatic nerve injury [11] and spinal cord injury [6]. Decreased swing speed In some instances, a decreased swing speed is measured, meaning that the longer air time does not result in a different stride length. Examples include models of sciatic nerve injury [1] and arthritis [5]. Galvan et al. [6] measured an increase in swing speed after the treatment of spinal cord injury models. In relation to the longer stance phase of their model, Westin et al. [12] also found a decreased swing speed. Inter-paw coordination Inter-paw coordination is reflected in several parameters. For example, phase dispersions and couplings describe the relative placement of two paws, the "target" and the "anchor" paw, during one stride. Kloos et al. [9] found deficits that correlate with the amount of recovery in a spinal cord injury model, while Bozkurt et al. [1] found that this parameters was affected in pairs that included the affected paw, reflecting a delayed positioning of the delayed paw. This was also seen by Deumens et al. [3]. Find out more I hope you enjoyed our blog series on gait parameters. If you want to learn more, you can always download our free white paper on gait analysis. Or read more on our website about gait analysis research or automated gait analysis. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Other blogs in this series Other blogs in this series are now online: - What gait can tell: 3 blogs that will help you understand - What a print can tell - Going the distance - and why it matters in gait analysis References - 1.Bozkurt, A.; Deumens, R.; Scheffel, J.; O'Dey, D.M.; Weis, J.; Joosten, E.A.; Führman, T.; Brook, G.A.; Pallua, N. (2008). CatWalk gait analysis in assessment of functional recovery after sciatic nerve injury. Journal of Neuroscience Methods, 173, 91-98. - 2.Bozkurt, A.; Scheffel, J.; Brook, G.A.; Joosten, E.A.; Suschek, C.V.; O'Dey, D.M.; Pallua, N.; Deumens, R. (2011). Aspects of static and dynamic motor function in peripheral nerve regeneration: SSI and CatWalk gait analysis. Behavioural Brain Research, 219, 55-62. - 3.Deumens, R.; Jaken, R.J.P.; Marcus, M.A.E.; Joosten, E.A.J. (2007). The CatWalk gait analysis in assessment of both dynamic and static gait changes after adult rat sciatic nerve resection. Journal of Neuroscience Methods, 164, 120-130. - 4.Encarnacion, A.; Horie, N.; Keren-Gill, H.; Bliss, T.M.; Steinberg, G.K.; Shamloo, M. (2011). Long-term behavioral assessment of function in an experimental model for ischemic stroke. Journal of Neuroscience Methods, 196, 247-257. - 5.Ferland, C.E.; Laverty, S.; Beaudry, F.; Vachon, P. (2011). Gait analysis and pain response of two rodent models of osteoarthritis. Pharmacology, Biochemistry and Behavior, 97, 603-610. - 6.Galvan, M.D.; Luchetti, S.; Burgos, A.M.; Nguyen, H.X.; Hooshmand, M.J.; Hamers, F.P.T.; Anderson, A.J. (2008). Deficiency in complement C1q improves histological and functional locomotor outcome after spinal cord injury. The Journal of Neuroscience, 28(51), 13876-13888. - 7.Hetze, S.; Römer, C.; Teufelhart, C.; Meisel, A.; Engel, O. (2012). Gait analysis as a method for assessing neurological outcome in a mouse model of stroke. Journal of Neuroscience Methods, 206, 7-14. - 8.Hoffmann, M.H.; Hopf, R.; Niederreiter, B.; Redl, H.; Smolen, J.S.; Steiner, G. (2010). Gait changes precede overt arthritis and strongly correlate with symptoms and histopathological events in pristane-induced arthritis. Arthritis Research & Therapy, 12, R41. - 9.Kloos, A.D.; Fisher, L.C.; Detloff, M.R.; Hassenzahl, D.L.; Basso, D.M. (2005). Stepwise motor and all-or-none sensory recovery is associated with nonlinear sparing after incremental spinal cord injury in rats. Experimental Neurology, 191, 251-265. - 10.Möller, K.Ä.; Berge, O.-G.; Hamers, F.P.T. (2008). Using the CatWalk method to assess weight-baring and pain behaviour in walking rats with ankle joint monoarthritis induces by carrageenan: effects of morphine and rofecoxib. Journal of Neuroscience Methods, 174, 1-9. - 11.Sheu, M.L.; Cheng, F.-C.; Su, H.-L.; Chen, Y.-J.; Chen, C.-J.; Chiang, C.-M.; Chiu, W.-T.; Sheehan, J.; Pan, H.-C. (2012). Recruitment by SDF-1α of CD34-positive cells involved in sciatic nerve regeneration. Journal of Neurosurgery, 116, 432-444. - 12.Westin, J.E.; Janssen, M.L.F.; Sager, T.N.; Temel, Y. (2012). Automatic gait analysis in bilateral Parkinsonian rats and the role of L-DOPA therapy. Behavioural Brain Research, 226, 519-528. --- ## Nurse patient interaction - two coding schemes URL: https://noldus.com/blog/nurse-patient-interaction-two-coding-schemes Published: 2012-07-02 14:34:00 Description: The world's population is ageing. International dementia and Alzheimer organizations state that there are an estimated 36 million people worldwide with dementia. The world's population is ageing. International dementia and Alzheimer organizations state that there are an estimated 36 million people worldwide with dementia. And that figure is set to increase to more than 115 million people by 2050. Since dementia primarily affects older people who are often in need of special care, the number of people living in nursing or senior living homes has increased dramatically. Cultural living People with a specific cultural background such as Hindustani people or Korean Americans will establish their own nursing homes to incorporate cultural living into daily care and activities. Why? Sometimes what is seen as polite in one culture can be seen as impolite in another. For example, when you lower your eyes in Japan it is interpreted as a sign of respect as if talking to someone superior. However, when doing the same in a western country, such as the UK or The Netherlands, it might be interpreted as evasive, lying, or uninterested. Two social interaction coding schemes One study which provides more insight in this cultural phenomenon has been conducted by Kim and Woods (2012). They looked into social interactions between direct-care staff and Korean Americans with dementia. As a research method, they chose direct observation and explain that this method is more accurate than proxy reporting to quantify the frequency of behavioral symptoms of dementia (McCann, 1997). Kim and Woods developed two social interaction coding schemes to measure the dementia competent social interaction and culturally competent social interaction of direct-care staff in this Korean American nursing home. The latter is of course meant to measure the appropriateness of approaches of the direct-care staff. Kim and Woods used Pocket Observer to collect data which is software that runs on handheld devices including smartphones. This handheld observation system doesn't attract much attention and can easily be combined with The Observer XT research software to further analyze the collected data. Two research assistants observed and coded behaviors of direct-care staff during care activities. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Improve care for ethnic minority older adults in nursing homes The researchers summarize that this study provides potential schemes to assess direct-care staff's competence in social interactions as a starting point to improve care for ethnic minority older adults in Nursing homes. However, they also mention some limitations, for example that the results of this study cannot be generalized to non-Korean older persons or Korean Americans still living at home. More research is needed to validate the coding schemes. RESOURCES Read more about The Observer XT Find out how The Observer XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - Kim, H.; Woods, D.L. (2012). The development of direct-care staff social interaction coding schemas for nursing home residents with dementia. Geriatric Nursing, 33 (2), 113-117. - McCann, J.J.; Gilley, D.W.; Hebert, L.E.; Beckett, L.A.; Evens, D.A. (1997). Concordance between direct observation and staff rating of behavior in nursing home residents with Alzheimer's disease. Journal of Gerontology, 52B, 63-72. --- ## Going the distance - and why it matters in gait analysis URL: https://noldus.com/blog/automated-gait-analysis Published: 2012-06-28 14:52:00 Description: A footprint, that is. With CatWalk XT, you can extract a lot of information from just one footprint. In this post, I am taking it a step further by talking about the relationship between prints. Parameters that describe the relation and distances between footfalls Last week I wrote about the value of a print. A footprint, that is. With CatWalk XT, you can extract a lot of information from just one footprint. In this post, I am taking it a step further by talking about the relationship between prints. In the study of many different disorders that affect the nervous system, muscles, or bones, it is important to know how the animal walks. Does it have a regular gait, following a normal pattern of footsteps? Or can we detect a lack of coordination, or ataxia? Those are important behavioral observations in many studies. So how can you detect them: by looking at the relation between prints. Clinicians are trained to visually observe the gait of their patients to detect abnormalities. They can ask their patients to walk a certain way or direction, to watch their stability and balance. But what if your patient is a small rodent? Small rodents are often used in research on a wide scale of disorders that cause abnormalities in gait. Automated gait analysis allows for accurate assessment of several parameters (behavioral endpoints) when you can't ask your animal to please walk in a straight line. Regularity In many disease models, the regularity with which the animal walks is important. For example, animal models of ataxia [1], arthritis [5,9], stroke [4], and spinal cord injury [2,3,7] have a lower regularity. So how can you detect irregularity automatically? By using gait analysis software that recognizes 'normal' footfall patterns, and detects deviations from this pattern. Solutions such as CatWalk XT recognizes several normal gait patterns, including: left front, right front, left hind, right hind. This pattern is described in literature as cruciate. If during the run, the animal places one of its paws outside the pattern, that paw is labeled as "not part of a pattern". The number of irregular paw placements relative to the regular paw placements is represented in the regularity index. Base of support The base of support is the distance between either the two hind paws or the two front paws. In spinal cord injury, animals seem to have trouble keeping balance, causing them to place their hind paws wider apart than normal [3,6]. Tail and abdomen drags are not uncommon [3]. In contrast, Parkinson's models are reported to have a smaller base of support in their front paws [10], placing them closer together than non-affected controls. This is similar to the posture human Parkinson's patients show; they also keep their feet closer together and show small movements with a hunched over posture. Stride length Stride length is the distance between the successive placement of the same paw - in other words, the distance one paw travels during one step. Again, similar to human patients, Parkinson's model animals are reported to take smaller steps [10], which can be confirmed with smaller stride lengths found with CatWalk XT automatic gait analysis. There are also reports of a decreased stride length in ataxic animals [1] and spinal cord injury models [3,8]. Curious to find out what more you can measure with automated gait analysis? Sign up to be one of the first to read the last blog in this series! RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Other blogs in this series Other blogs in this series are now online: - What gait can tell: 3 blogs that will help you understand - What a print can tell - Time is of the essence - how you can use it in gait analysis Or download the free white paper! Of course, you can always go to www.noldus.com/catwalk-xt for more information on automated gait analysis. References - 1.Cendelín, J.; Voller, J.; Vožeh, F. (2010). Ataxic gait analysis in a mouse model of the olivocerebellar degeneration. Behavioural Brain Research, 210, 8-15. - 2.Galvan, M.D.; Luchetti, S.; Burgos, A.M.; Nguyen, H.X.; Hooshmand, M.J.; Hamers, F.P.T.; Anderson, A.J. (2008). Deficiency in complement C1q improves histological and functional locomotor outcome after spinal cord injury. The Journal of Neuroscience, 28(51), 13876-13888. - 3.Hamers, F.P.T.; Lankhorst, A.J.; Van Laar, T.J.; Veldhuis, W.B.; Gispen, W.H. (2001). Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries. Journal of Neurotrauma, 18, 187-201. - 4.Hetze, S.; Römer, C.; Teufelhart, C.; Meisel, A.; Engel, O. (2012). Gait analysis as a method for assessing neurological outcome in a mouse model of stroke. Journal of Neuroscience Methods, 206, 7-14. - 5.Hoffmann, M.H.; Hopf, R.; Niederreiter, B.; Redl, H.; Smolen, J.S.; Steiner, G. (2010). Gait changes precede overt arthritis and strongly correlate with symptoms and histopathological events in pristane-induced arthritis. Arthritis Research & Therapy, 12, R41. - 6.Kloos, A.D.; Fisher, L.C.; Detloff, M.R.; Hassenzahl, D.L.; Basso, D.M. (2005). Stepwise motor and all-or-none sensory recovery is associated with nonlinear sparing after incremental spinal cord injury in rats. Experimental Neurology, 191, 251-265. - 7.Koopmans, G.C.; Deumens, R.; Buss, A.; Geoghegan, L.; Myint, A.M.; Honig, W.H.H.; Kern, N.; Joosten, E.A.; Noth, J.; Brook, G.A. (2009). Acute rolipram/thalidomide treatment improves tissue sparing and locomotion after experimental spinal cord injury. Experimental Neurology, 216, 490-498. - 8.Lee, H.; McKeon, R.J.; Bellamkonda, R.V. (2010). Sustained delivery of thermostabilized chABC enhance axonal sprouting and functional recovery after spinal cord injury. PNAS, 107(8), 3340-3345. - 9.Möller, K.Ä.; Berge, O.-G.; Hamers, F.P.T. (2008). Using the CatWalk method to assess weight-baring and pain behaviour in walking rats with ankle joint monoarthritis induces by carrageenan: effects of morphine and rofecoxib. Journal of Neuroscience Methods, 174, 1-9. - 10.Westin, J.E.; Janssen, M.L.F.; Sager, T.N.; Temel, Y. (2012). Automatic gait analysis in bilateral Parkinsonian rats and the role of L-DOPA therapy. Behavioural Brain Research, 226, 519-528. --- ## What a print can tell URL: https://noldus.com/blog/footprint-parameters Published: 2012-06-21 15:58:00 Description: So what can one footprint tell you? Well, it could tell you a lot. Simply putting the paw in ink and studying the print left behind is one way to go about it, but there are far more sophisticated ways of footprint analysis. Gait parameters as behavioral endpoints – parameters from a footprint So here it is – the first blog in a series of three, about rodent gait analysis and what a single footprint can tell us. Modern systems – better than ink So what can one footprint tell you? Well, it could tell you a lot. Simply putting the paw in ink and studying the print left behind is one way to go about it, but there are far more sophisticated ways of footprint analysis. While an ink-print can give you an idea of the print area of a foot, you cannot tell how the animal is distributing his weight across its feet. It also cannot tell you the maximum surface area of a foot touching the ground during the duration of the entire footfall. Modern systems can. Print intensity Modern systems that use light to detect a footfall can indicate the intensity of a print, which in turn can correlate with how the animal is bearing its weight. In models of conditions that affect a single limb, the animal often shows less use of the affected paw. This is reflected in a relatively lower intensity of that footprint, which is found in models of arthritis [8,9] and sciatic nerve injury [1,2,4,10]. Contact and print area Maximum contact area and total print area are two different things that cannot be distinguished using a regular ink print. The total print area is the accumulated picture of the entire time the paw came in contact with the ground. It is what would be left behind if you had dipped that foot in ink. But cleaner. The maximum contact area is the area of the foot touching the plate during the time of maximum contact, which is usually smaller than the total print area. Similar to the changes found in print intensity, a smaller contact area also reflects altered use of the affected limb. Again, in literature this is described in models of arthritis [8,9] and sciatic nerve injury [1,2,4,10]. Other disorders that show one or more affected paws, also show a clear reduction of print and/or contact area, such as models of ischemic stroke [5,7]. On the other hand, research on spinal cord injury reports an increased print and contact area for all four paws in a contusion injury model of spinal cord injury, and a less dramatic but still significant effect in the hind paw print areas in a dorsal cord transection model of spinal cord injury [6]. Shape of the paw The shape of the paw, the length, and how the toes are spread, are important in research on nerve injury, arthritis and pain. These can cause deformation of the feet, altering the parts of the sole that make contact with the ground [1,2,3,4]. The sciatic nerve is a long nerve that originates in the lower back and runs down through the limbs. It branches of in the tibial and the peroneal (also called fibular) nerve. Injury to these nerves in rodents are often used as a model to study nerve regeneration, using print length, toe spread, paw angle and other gait parameters as a behavioral endpoint to measure functional recovery. Nerve injury can cause "clawing" of the feet. In sciatic [3] or tibial nerve injury, this is often reflected in a longer print but a decreased toe spread, while damage to the peroneal nerve often results in a shorter print with a diminished toe spread. These characteristics are represented in nerve specific indexes; the sciatic functional index (SFI), the tibial functional index (TFI), and the peroneal functional index (PFI). Based on print length (PL), toe spread (TS) and intermediate toe spread (ITS), these are automatically calculated by gait analysis systems. We can again find the advantage of using modern technology over ink dipping; the more accurate the print is (in other words: no ink smudges), the more accurate these indexes are. Paw angle Paw angle is the angle between the paw axis and the body axis or between the paw axis and the direction of movement (the vector). This angle can be affected by abnormalities of the muscles responsible for the placement of the paw, the nerves that innervate these muscles, or even deformation of the bones and joints of the leg belonging to the paw. Changes in paw angle are seen in models of arthritis, ataxia, stroke, and spinal cord injury. Automated systems All the parameters and indexes mentioned in this blog can automatically be detected, measured, and calculated with gait analysis systems such as CatWalk XT. Now imagine adding inter-paw parameters such as the distance between paws, or the length of a stride. And what if you added time to your analysis? Stay tuned for the other blogs in this series… RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Sign up for more blogs! If you don't want to miss out on the next two blogs in this series, sign up here to be notified when they are online. (If you have already signed up previously, you don't need to do so again.) Other blogs in this series Other blogs in this series are now online: - What gait can tell: 3 blogs that will help you understand - Going the distance - and why it matters in gait analysis - Time is of the essence - how you can use it in gait analysis References - Bozkurt, A.; Deumens, R.; Scheffel, J.; O'Dey, D.M.; Weis, J.; Joosten, E.A.; Führman, T.; Brook, G.A.; Pallua, N. (2008). CatWalk gait analysis in assessment of functional recovery after sciatic nerve injury. Journal of Neuroscience Methods, 173, 91-98. - Bozkurt, A.; Scheffel, J.; Brook, G.A.; Joosten, E.A.; Suschek, C.V.; O'Dey, D.M.; Pallua, N.; Deumens, R. (2011). Aspects of static and dynamic motor function in peripheral nerve regeneration: SSI and CatWalk gait analysis. Behavioural Brain Research, 219, 55-62. - Costa, L.M.; Simões, M.J.; Maurício, A.C.; Varejão, A.S.P. (2009). Methods and protocols in peripheral nerve regeneration experimental research: Part IV – kinematic gait analysis to quantify peripheral nerve regeneration in the rat. International Review of Neurobiology, 87, 127-139. - Deumens, R.; Jaken, R.J.P.; Marcus, M.A.E.; Joosten, E.A.J. (2007). The CatWalk gait analysis in assessment of both dynamic and static gait changes after adult rat sciatic nerve resection. Journal of Neuroscience Methods, 164, 120-130. - Encarnacion, A.; Horie, N.; Keren-Gill, H.; Bliss, T.M.; Steinberg, G.K.; Shamloo, M. (2011). Long-term behavioral assessment of function in an experimental model for ischemic stroke. Journal of Neuroscience Methods, 196, 247-257. - Hamers, F.P.T.; Lankhorst, A.J.; Van Laar, T.J.; Veldhuis, W.B.; Gispen, W.H. (2001). Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries. Journal of Neurotrauma, 18, 187-201. - Hetze, S.; Römer, C.; Teufelhart, C.; Meisel, A.; Engel, O. (2012). Gait analysis as a method for assessing neurological outcome in a mouse model of stroke. Journal of Neuroscience Methods, 206, 7-14. - Möller, K.Ä.; Berge, O.-G.; Hamers, F.P.T. (2008). Using the CatWalk method to assess weight-baring and pain behaviour in walking rats with ankle joint monoarthritis induces by carrageenan: effects of morphine and rofecoxib. Journal of Neuroscience Methods, 174, 1-9. - Pinho, D.; Morato, M.; Couto, M.R.; Marques-Lopes, J.; Tavares, I.; Albino-Teixeira. A. (2011). Does chronic pain alter the normal interaction between cardiovascular and pain regulatory systems? Pain modulation in the hypertensive-monoarthritic rat. The Journal of Pain, 12, 194-204. - Sheu, M.L.; Cheng, F.-C.; Su, H.-L.; Chen, Y.-J.; Chen, C.-J.; Chiang, C.-M.; Chiu, W.-T.; Sheehan, J.; Pan, H.-C. (2012). Recruitment by SDF-1α of CD34-positive cells involved in sciatic nerve regeneration. Journal of Neurosurgery, 116, 432-444. --- ## What we can learn from zebrafish in a T-maze URL: https://noldus.com/blog/zebrafish-t-maze Published: 2012-06-18 14:42:00 Description: Scrolling through our recent blogs, you can tell how important zebrafish have become in behavioral research. So we thought it was time to tell you a little more about some popular paradigms. Starting with the T-maze. Scrolling through our recent blogs, you can tell how important zebrafish have become in behavioral research. So we thought it was time to tell you a little more about some popular paradigms. Starting with the T-maze. 'T' For those of you who have never seen one; is it exactly what you expect it to be. A maze formed like the letter T. The animal tested starts out at the bottom of the T, and to teach it to choose the 'correct' goal arm, positive or aversive stimuli are used to motivate the animal. By the way, 'T' has a big sister: 'Y'. The Y-maze is similar to the T-maze, the arms are just connected a bit differently. The T-maze was already popular in rodent studies, and seems to work in quite a same way with zebrafish. But why would let your zebrafish swim around in a T? Learning and memory The T-maze is a straightforward method to test the learning ability, long- and short-term memory, and memory plasticity of your animal. And how this is altered due to genetics, chemicals, etc. Just like with rodents, T-maze studies with zebrafish show promising and robust results. The basics Basically, you teach your animal to choose the left arm, the red-colored one, or the deeper one, etc. Then you test the learning curve of different groups: how fast does it swim to this arm, and how does it improve its time over consecutive trials? Then memory plasticity can be tested by reversal learning: the previously 'incorrect' arm is now the 'correct' arm. How long does it take the zebrafish to figure this out? Many researchers also test extinction rate: how fast does the learned behavior fade out when the positive stimulus (like food) is no longer given? Color discrimination Often, colors or patterns discriminate the two goal arms. The arms have painted walls or are fitted with a colored or patterned sleeves. It is useful to alternate the colors left and right to make sure the zebrafish is recognizing the color rather than the side it is on. The same goes for visual cues from the testing environment. Favorite color So do zebrafish have a favorite color? Because that could bias learning, of course. Well, natural preferences for colors seem to differ amongst studies. For example, Avdesh et al. (2012) detect a preference for red and green, while Colwill et al. (2005) found that blue and purple are more popular. This could be a difference between strains. Appetitive and aversive stimuli To motivate an animal to choose the 'correct' arm, several stimuli are described in literature. Providing a favorable environment (artificial grass, deeper arm), for example, is used by Ninkovic et al. (2006) The sight of conspecifics also works (Grella et al., 2010), as does food, of course (Colwill et al., 2005, and Ninkovic et al., 2006). Aversive stimuli often used are mild shocks (Saili et al., 2012) or a water soluble that smells or tastes bad (Grella et al., 2010). Behavioral endpoints So what can we actually measure to determine things like a learning curve? The time it takes the animal to reach the goal arm, and how this improves over consecutive trials, obviously. We also like to know if it entered the wrong arm first. To exclude general fitness or anxiety (due to the treatment?) as factors of influence, total time spent swimming, distance swum, and the number of freezing episodes could be measured. It is actually really easy to get this data, and other parameters. Three words: automatic video tracking. I am talking EthoVision XT here. It even has a pre-set experiment template for the T-maze. It is just a matter of assigning the zones (start box, start arm, goal arm left, goal arm right) to the video image of the T-maze. Then EthoVision XT automatically tracks your zebrafish and calculates the parameters mentioned in this blog post. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial If you'd like to read more about T-mazes and zebrafish, download our free white paper. It features some interesting publications on zebrafish in a T-maze and tells you a bit more about the apparatus itself and the value of automatic video tracking in this paradigm. Don't forget to check back regularly for more blog posts on paradigms with zebrafish! Check here for more information on learning and memory tests in fish. --- ## Infant behavior experiments URL: https://noldus.com/blog/infant-behavior-experiments Published: 2012-05-29 10:47:00 Description: When a baby is born prematurely, this baby and his or her parents often experience a rough start. You can think about eating problems, high risk of infection, or even anemia. When a baby is born prematurely, this baby and his or her parents often experience a rough start. You can think about eating problems, high risk of infection, or even anemia. Researchers focus on the differences between term and preterm infants in order to understand certain behavior, communication abilities, and learning skills so they learn more about the effects of a preterm birth. Learn more about the Early Social Communication Scales And researchers try to assess the effectiveness of interventions, such as the "Vermont Intervention Program for Low Birthweight Infants" (Rauh, 1979). By observing parent-infant interaction, researchers gain more insight in specific behaviors such as joint attention. Observing mother-infant interaction Olafsen et al. (2006) observed mother-infant interaction and investigated whether early intervention could be beneficial for infants with a low birth weight. The observers classified children's behavior into one of three mutually exclusive categories of early social communication behaviors. The authors used the Early Social Communication Scales ESCS protocol described by Mundy et al. (2003). 15-20 minutes of video were coded using the ESCS. This structured observational measure was used to assess children's use of several non-verbal communication skills. Social Interaction Behaviors were described as 'the capacity of the child to engage in playful, affectively positive turn-taking interactions with others'. In this study, the infants sat at a table opposite to the researchers and a set of toys was used as targets. The manual of Mundy describes in depth the ESCS and this procedure was followed. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Girls outperformed boys on all communication elements Olafsen et al. show that an intervention implemented during the neonatal period can positively influence social communication performance in 1-year-old preterm infants. One of the conclusions the authors present is that girls outperformed boys on all communication elements. To the best of the authors' knowledge, gender differences in joint attention have not been reported before. References - Mundy, P., Delgado, C., Block, J., Venezia, M., Hogan, A., & Seibert, J. (2003). Manual for the early social communication scales (ESCS) (2nd ed.). Psychology Department, University of Miami, www.psy.miami.edu/faculty/pmundy/ESCS.pdf. - Olafsen, K.S.; Rønning, J.A.; Kaaresen, P.I.; Ulvund, S.E.; Handegård, B.H.; Dahl, L.B. (2006) Joint attention in term and preterm infants at 12 months corrected age: The significance of gender and intervention based on a randomized controlled trial. Infant Behavior & Development, 29, 554-563. - Rauh, V.A. (1979). Vermont Intervention Program for Low Birthweight Infants. In Olafsen et al. translated into Norwegian, modified by J.A. Rønning and S.E. Ulvund, Unpublished manuscript, University of Tromso, Norway. --- ## Horse training methods: The importance of behavioral analysis URL: https://noldus.com/blog/horse-training-methods Published: 2012-05-10 12:00:00 Description: In equitation sciences, there are at least two training strategies: the ‘natural’ way of horsemanship that allows the horse to evaluate action and reaction and horsemanship that is based on ‘overruling’ of the animal. Nowadays there are many different methods to train a horse. Looking at equitation sciences, it seems you can distinguish al least two different training strategies applied and investigated. First, there is the 'natural' way of horsemanship that allows the horse to evaluate action and reaction. This is often claimed to be the "new" way, but it actually seems based on very ancient methods. The other extreme is horsemanship that is based on desensitizing or 'overruling' of the animal. Scientific research on different horse training methods Baragli et al. (2012, in press) wrote an article comparing two different methods of training young horses, providing a scientific approach to evaluate the success of these methods by closely looking at the behavior of the horses. Twelve young ponies were used, and split up into two groups. Both were trained using a similar basis of learning theory, but provided the horses with different opportunities to control their environment. Group A: in a paddock Group A was housed in a paddock and received training in a small circular enclosure. During training, the horse was not restrained and chased-away until it showed interest in the trainer. The trainer approached the horse while paying attention to its behavior. The horse was allowed to retreat, and if this occurred, this was followed by repeating the same strategy to approach the horse once again. When the horse followed the trainer voluntarily, physical contact was initiated. The last phase included saddling the horse. All the while, the horse was allowed to retreat and all movements were performed slowly, giving the horse time to evaluate each stimulus. Group B: horse's stable In group B the training began in the horse's stable where it was kept individually, isolated from the group. The horse was driven into a corner and the halter was put on. Physical contact and saddling of the horse were continued until the animal accepted, giving it no time to evaluate the stimuli. Evaluation of training success: a behavioral approach After training was completed, two tests were performed to evaluate the behavior of each horse. Behavioral monitoring and evaluation were performed with The Observer XT. Additionally, the subjects' heart rate was monitored. In the person test, the horse was let loose in a familiar arena. An unfamiliar person was introduced and the attention and exploratory behavior directed towards that person was recorded. In the grooming test, the horse was groomed and saddled by a familiar person (the trainer) in the familiar training location (round pen or stall). Behaviors scored included: - Exploration of the person - Attention paid to the person - Head lowered - Kinetic behaviors - Defensive behaviors - Avoidance behaviors Of all behaviors, latency, frequency, and duration were scored with The Observer XT. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Group A took more time to train, but showed more signs of relaxation during both tests, according to the authors. Their heart rate was lower during both tests and all of them approached the unfamiliar human as opposed to horses from group B, where only one horse approached the unfamiliar human. They also spent more time in close proximity to that person. In the grooming test, it was easier to lift the hoofs of the horses in group A. The total time it took to perform the whole grooming ritual did not differ between groups. Differences between horse training methods The authors explain that the high amount of exploratory behavior shown in both tests by group A can be associated with a positive emotional state. They also showed lowering of the head during grooming, a sign of relaxation. Group B showed attention to the humans, but also more defensive and avoidance behavior instead of exploration. The main difference in these two methods is that in group A, the time taken to evaluate a stimulus was determined by the horse, with trainers taking into consideration attentive behavior and the individuality of responses in their actions. Essentially, the trainer's actions were modulated according to the horse's response. Further research This article provides some clear and straight-forward results. It is a nice addition to research on training methods and well-being of horses, and provides a good basis for further research. While many different training methods exist, and many will have components of both methods described in this publication of Baragli et al., the clear difference in approach described here gives us insight into the effects on horse behavior and the value of a detailed behavioral study in the evaluation of different strategies. Reference Baragli, P.; Mariti, C.; Petri, L.; De Giorgio, F.; Sighieri, C. (2011). Does attention make the difference? Horses' response to human stimulus after 2 different training strategies. Journal of Veterinary Behavior, 6, 31-38. --- ## What gait can tell: 3 blogs that will help you understand URL: https://noldus.com/blog/what-gait-can-tell Published: 2012-05-03 16:00:00 Description: The usefulness of gait is well established in research on spinal cord injury, ataxia, and arthritis. But in fact, research on all disorders that influence gait in any way, can benefit from gait and footfall analysis. The usefulness of gait is well-established in research on spinal cord injury, ataxia, and arthritis. But in fact, research on all disorders that influence gait in any way, can benefit from gait and footfall analysis. Gait is an important part of the behavioral repertoire of animals, and detailed gait analysis is a logical endpoint to take into account. What gait can tell: 3 blogs that will help you understand The cause of gait disturbances Numerous diseases and disorders affect gait and four categories of origin can be described. First, the central nervous system can be affected, resulting in lack of coordination, ataxia, paralysis, etc. Examples include Parkinson's, Huntington's, cerebellar ataxia, and ALS. Second, disorders that originate from the peripheral nervous system can cause similar symptoms. Examples include ischemia and sciatic nerve injury. Third, if skeletal systems are affected, as is the case with arthritis or knee and ankle injury, symptoms include less use of a paw or limb, compensation by other limbs, irregular step sequences, etc. Fourth and final, the musculature can be affected, for instance by dystrophy. The benefits of automation Until recently, gait performance in rodents was not only difficult to quantify, it was also labor intensive. Everybody remembers the old bottle of ink. But you can leave that in the cabinet from now on – modern technology, like CatWalk XT, offers you a better (and less messy) way to do it. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources Gait research: let your animals walk freely Researchers use different ways to analyze gait in animals. In what instances would a study benefit from a system that is based on voluntary walking? In this post we share our thoughts on some of the factors you can keep in mind when choosing a method for your study. Don't miss them! In the coming weeks we will highlight some of the parameters that CatWalk XT gait analysis automatically calculates and its relevance to your research, from 'simple' footprints to sophisticated regularity and coordination indexes. So don't miss them - sign up to be notified when the blog posts are online! Other blog posts in this series Other blog posts in this series are now online: - What a print can tell - Going the distance - and why it matters in gait analysis - Time is of the essence - how you can use it in gait analysis --- ## Brain waves and behavior: sleep to learn URL: https://noldus.com/blog/brain-waves-behavior-sleep Published: 2012-04-19 12:39:00 Description: To find out more about human and animal learning and memory, we might just have to go to sleep. Ahem – research on sleep, I mean. To find out more about human and animal learning and memory, we might just have to go to sleep. Ahem – research on sleep, I mean. Sleep to learn At the institute of Physiology and Pathophysiology at Heidelberg University (Germany), they study REM sleep. REM is an important phase in our sleep, not just for humans, but for other mammals as well. We need REM sleep to process recent events, to learn skills, and regulate our emotions. It is thought that predators 'relive' catching their prey during sleep, improving their skills for the next hunt. Brain waves Late 2010, Scheffzük et al. published a paper on brain waves that were recorded with EEG in mice during active wakefulness and REM sleep. This study investigates the cross-frequency coupling between two different 'brain waves': theta and gamma waves. Theta waves are slow waves; in rodents they originate from the hippocampal network and are conducted to the neocortex. Gamma waves are faster, local waves, and can be divided into slow and fast gamma waves. Inside and outside the brain Scheffzük et al. recorded brainwaves (EEG) from 19 freely moving mice during a 24-hour home cage assessment in a PhenoTyper home cage. Additionally, movement and behavior was automatically recorded with EthoVision XT to determine different states such as active wakefulness, quiet wakefulness, slow wave sleep, and REM sleep. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial EEG and data on exploration behavior was also collected in a selection of the mice during a novel open field test and a plus maze test. This combination of tests was used to get robust data: while in the plus maze exploration behavior is more induced by the artificial environment, in the open field behaviors are more spontaneous and less induced. Both tests represented active wakefulness and brain waves were clearly visible during both tests. Waves working together The coupling of theta and gamma brain waves is believed to be important in memory processing and synaptic plasticity. In this study, prominent theta waves were found in active awake animals and during REM sleep, and not during immobile awake states or during slow wave sleep. Both gamma and theta waves had a much higher power during the active awake state. However, EEG recordings revealed a coupling between theta and gamma waves that became much more pronounced during REM sleep: The coupling between theta and slow gamma waves increased 1.5 times, the coupling between theta and fast gamma waves increased 9 times. The future of sleep study Scheffzük et al.'s paper revealed that these local gamma waves seem to be modulated by the global theta waves, especially during REM sleep. This is an interesting fact, since we know REM sleep is important for learning and memory, and other studies have indicated that coupling between different brain waves is found in many behavioral and cognitive processes. For example: theta-gamma coupling is enhanced during working-memory dependent tasks. This research provides a new physiological marker of REM sleep and distinguishes fast and slow gamma waves. Up to now, little was known about the characteristics of REM sleep, so these findings might be of great importance in understanding memory formation and – in the long run – might even shed a different light on learning disabilities. Read more - Scheffzük, C.; Kukushka, V.I.; Vyssotski, A.L.; Draguhn, A.; Tort, A.B.L.; Brankačk, J. (2011). Selective coupling between theta phase and neocortical fast gamma oscillations during rem-sleep in mice. PLoS ONE, 6(12), e28489, doi:10.1371/journal.pone.0028489 - Learn more about the behavioral tools: EthoVision XT and PhenoTyper. --- ## How to find an animal model for obsessive-compulsive disorder (OCD) URL: https://noldus.com/blog/animal-model-obsessive-compulsive-disorder Published: 2012-04-12 13:33:00 Description: We all show some form of compulsive behavior. I triple check to make sure I locked my car, knowing that it’s locked but still feeling the need. But what if compulsions, rituals, and repetition rule your everyday live? The power of temporal behavioral pattern analysis and video tracking We all show some form of compulsive behavior. I triple check to make sure I locked my car, knowing that it's locked but still feeling the need. But what if compulsions, rituals, and repetition rule your everyday live? Obsessive-compulsive disorder (OCD) is a complex psychiatric disease that can have a profound impact on the lives of those affected by it. Typical single-drug treatment (selective serotonin re-uptake inhibitors) fails to help a large percentage of patients, so researchers are trying to come up with more effective therapies. In search of the next top-model Figuring out the biomechanical basis of OCD and finding more successful methods of treatment depends largely on research with animal models. However, finding an adequate model remains difficult. In 2010 de Haas et al. published a paper on an OCD model using quinpirole on rats. They aimed to quantify the dimensions of ritualistic 'compulsive-like' behavior induced by quinpirole with the use of EthoVision automatic video tracking and with Theme, a software program that detects temporal patterns in behavior. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Finding patterns of behavior Rats were studied in an open field with four objects. The total distance moved, number of returns to the home base, number of different behavioral patterns, and the duration, length, and complexity of behavioral patterns were of main interest. In comparison to saline-treated rats (control group) the quinpirole-treated rats showed a significantly smaller behavioral repertoire. Their behavioral patterns were also less complex and shorter in duration and number of behaviors, and showed a two-fold higher occurrence than the patterns of the control group. Furthermore, quinpirole rats showed an excessive number of home base visits. Model versus patient The repetition shown in this rodent OCD model matches the repetitive behavior (increased performance of the same behavior) seen in OCD patients. However, the smaller and shorter behavioral repertoire of the quinpirole rats does not, as OCD patients tend to have complex ritualistic behavioral patterns. Detailed behavioral pattern analysis led to the conclusion that this rat model is not entirely accurate, and researchers continue their search for a better one. What's in the genes? In a second publication, de Haas et al. (2012) investigated whether genetic background has anything to do with this. And indeed, it does. This time they used two different strains of mice: A/J mice, which have shown to be more sensitive to develop compulsive-like behavior, and C57BL/6J mice. The same behavioral tests were performed. One mouse vs the other Left untreated (saline control groups), the C57BL/6J mice showed a greater behavioral repertoire and more motor activity than A/J mice, while the rate of repetition in behavioral patterns was the same. Treated with quinpirole, A/J mice became more active and visited more zones of the open field, while this effect was not seem within the C57BL/6J groups. The C57BL/6J mice did however seem to focus more on specific parts of the open field. The rate of repetition was increased by quinpirole in both strains with a similar effect. Interestingly, the number of patterns showed a dose dependent increase in A/J mice, and a dose dependent decrease in C57BL/6J mice. And the winner is… With this study de Haas et al. showed the importance of a genetic background. Compared to the quinpirole rat model used in the 2010 study (and to the C57BL/6J mice), the quinpirole A/J mice model in this study showed more similarity to actual OCD patient behavior, with a more complex behavioral repertoire and high rates of repetition. What do you think? These papers show the power of discovering temporal behavioral patterns, as does the paper described in this recent blog. What do you think? Are behavioral patterns important? Do you know of research on other disorders that could benefit from the detailed analysis of temporal behavioral patterns? Leave your thoughts in the comment section below! Further reading - De Haas, R.; Nijdam, A.; Westra, T.A.; Kas, M.J.H.; Westenberg, H.G.M. (2010) Behavioral pattern analysis and dopamine release in quinpirole-induced repetitive behavior in rats. Journal of Psychopharmacology, 25(12), 1712–1719. - De Haas, R.; Seddik, A; Oppelaar, H.; Westenberg, H.G.M.; Kas, M.J.H. (2012). Marked inbred mouse strain difference in the expression of quinpirole induced compulsive like behavior based on behavioral pattern analysis. European Neuropsychopharmacology, article in press, doi:10.1016/j.euroneuro.2012.01.003 More product information: EthoVision. --- ## Can a food preservative increase symptoms of autism? URL: https://noldus.com/blog/food-preservative-increase-symptoms-of-autism Published: 2012-04-02 13:35:00 Description: Autism spectrum disorder (ASD) has a strong genetic component – a well-known fact. However, recent studies suggest that environmental factors, such as dietary ingredients, can cause exacerbation of the symptoms. Autism-like behavior studied in rats treated with propionic acid In honor of World Autism Awareness Day, this post will focus on autism research. In particular, I want to share this interesting and very readable publication of MacFabe et al. (2011) with you. Environmental factors in autism Autism spectrum disorder (ASD) has a strong genetic component – a well-known fact. However, recent studies suggest that environmental factors, such as dietary ingredients, can cause exacerbation of the symptoms. Propionic acid (PPA) is a good example, as MacFabe et al. explain to us in their article. They investigated the effects of PPA on several behavioral and physiological measurements as part of the autistic phenotype of rats. PPA is a fatty acid used as a food preservative, and studies have shown that eating food containing this additive exacerbates the symptoms in children with autism. PPA is also a product of gut bacteria, thus produced in our own body. A subset of ASD patients are reported to have high levels of PPA producing bacteria. Why young rats? In this study not just any rats are used – the researchers specifically chose adolescent rats. The reason? Adolescence is a significant period in lives of rats, normally characterized by the increased interest in social contact and novelty seeking behavior. Additionally, this period shows a higher vulnerability to psychopathology. Therefor a perfect phase to test the autistic-like effects of substances that influence the brain, such as PPA. Restricted interests Because autism often causes repetitive behavior and restricted interests, such as towards a specific object, rats are tested in a three-piece novel object test. EthoVision was used to automatically track approaching behavior and the proximity of the rat to the objects. In addition locomotion was measured. As hypothesized, rats treated with PPA did seem to have one favorite object while the control group did not limit their interest towards one specific piece as much. However, locomotion was not affected, ruling that out as a possible cause for the difference in interest. Reduced social interest is another typical symptom of ASD. In the second experiment the rats are faced with an unfamiliar rat (social stimulus) or a novel object. Again, proximity and interaction was measured with EthoVision automatic video tracking. Rats treated with PPA showed less approach and interaction to the novel rat than the control group did. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Learn and unlearn In a third test, the T-maze was used for reversal learning. First the animals were taught to choose one specific arm by baiting it with a food reward, and then the opposite arm was baited. Like the authors predicted, PPA-treated rats showed impaired reversal learning. What goes on in the brain? In this experiment a number of PPA-treated rats showed convulsive behavior. Interestingly, this is also a prominent symptom in a large group of ASD patients. Also, the neuropathological findings in this study were consistent with findings in brain tissue of ASD patients. The answer is yes So, to answer the title of this post: yes, food preservatives can increase symptoms of autism. Ok, that might be a little blunt. But at least MacFabe et al. have shown that PPA, something that is present our food and even produced by the bacteria that live in our own body, induces autistic-like behavior and neuropathology in rats. Read more in the original publication: MacFabe, D.F.; Cain, N.E.; Boon, F.; Ossenkopp, K.-P.; Cain, D.P. (2011). Effects of the enteric bacterial metabolic product propionic acid on object-directed behavior, social behavior, cognition, and neuroinflammation in adolescent rats: Relevance to autism spectrum disorder. Behavioural Brain Research, 217, 47-54. Or look for more autism related research using automatic video tracking with this google scholar search. --- ## Walking in circles - the exploratory activity of Drosophila URL: https://noldus.com/blog/exploratory-activity-drosophila Published: 2012-03-26 15:31:00 Description: Like rats and mice, fruit flies avoid open spaces and stay close to physical borders. In rats and mice this is caused by fear to be out in the open and preference for close contact with borders. Like rats and mice, fruit flies avoid open spaces and stay close to physical borders. In rats and mice this is caused by fear to be out in the open and preference for close contact with borders. However, fruit flies are different from rats and mice. They stay close to the borders because they explore them visually. Uncomfortable to be out in the open Do we not all feel a little uncomfortable when we cross a large square and do we not all secretly prefer to walk along its edges? Centrophobicity, the tendency to avoid open spaces, is a well-known phenomenon in behavioral science. Rats and mice, for example, are strongly centrophobic, because being out in the open makes them vulnerable to predators. This behavior is commonly used in the development of antidepressants, to determine whether the drugs succeed in making the animals braver and more eager to explore their environment. Fruit flies are like rats and mice The habits of insects are comparable to the habits of rodents. Insect studies show that fruit flies, for example, also prefer to stay close to the borders of an open field. But does this mean that fruit flies are centrophobic, like rats and mice? Or can this behavior be explained by the preference of the insects for physical contact with the border, known as thigmotaxis? Or is there perhaps a third explanation? Why stay close to the borders? In an interesting study, Soibam et al. (2012) publicly question whether the preference of Drosophila for the borders of an open field is caused by centrophobicity or thigmotaxis. They placed walls in the center of the open field that differed in shape and opacity. They also altered the shape and opacity of the outer border and created corners of different angles. EthoVision XT, one of their Drosophila research tools, was used to automate the analysis of the exploratory behavior. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Fruit flies are not afraid of open spaces The fruit flies did not prefer corners that were furthest away from the center. Hence, do the authors say, the preference for the arena borders is not caused by centrophobicity. To investigate what could then be the case, the authors used wild-type, visually impaired, and blind fruit flies and determined their preference for clear and opaque arena borders. Fruit flies are not like rats and mice after all The wild-type fruit flies moved more slowly along both the clear and opaque borders than the blind ones. The visually impaired Drosophila moved more slowly along the opaque borders than along the clear borders. The authors conclude that the preference for the borders is not caused by thigmotaxis, but instead by something else. Fruit flies use their eyes to explore the borders. Hence, Drosophila, like rats and mice, avoid open spaces and stay close to borders. However, unlike in rodents, in fruit flies this behavior is caused by neither centrophobicity nor thigmotaxis. The fruit flies stay close to the borders because they explore them visually. References Soibam, B., Mann, M., Liu, L., Tran, J., Lobaina, M., Kang, Y. Y., Gunaratne, G. H., Pletcher, S. and Roman, G. (2012), Open-field arena boundary is a primary object of exploration for Drosophila. Brain and Behavior. doi: 10.1002/brb3.36 --- ## Parent-child interaction: Measuring the effectiveness of interactions URL: https://noldus.com/blog/parent-child-interaction-effectiveness Published: 2012-03-23 11:30:00 Description: Quality of parent-child interaction is one of the major predictors of emotional and social development of children, which makes parent-child interaction an important focus of child development research. Quality of parent-child interaction is one of the major predictors of emotional and social development of children, which makes parent-child interaction an important focus of child development research. By examining patterns of parent-child interaction before and after an intervention, researchers try to identify changes in behavior. In order to reach desired behavior patterns, certain changes need to occur. Then an intervention can be evaluated as effective or non-effective. Understanding treatment effectiveness Recently, De Rubeis and Granic presented an interesting study: Understanding treatment effectiveness for aggressive youth: the importance of regulation in mother-child interactions. They state that studies continue to report variability in outcomes, and researchers have yet to understand why certain interventions only produce behavior change in some children. It is understandable that not all will produce changes, but in behavioral research, you would like to give a negative or positive result about a certain therapy. On-site research De Rubeis and Granic presented their study in Family Psychology. This study focused on mother-child interaction when trying to solve an issue. The observational research was performed on-site, in family homes. Doing research in a natural environment can provide very valuable data. Compared to lab experiments, an experiment in a natural setting allows for the context of the family home to be taken into account. Moreover, people often feel more relaxed in their own environment. Regulated dyads Specifically, De Rubeis and Granic explored the influence of dyadic regulation to see if regulation would make a difference in assessing a treatment's success. They observed regulated dyads and dysregulated dyads and defined regulated as "Dyads in which both partners showed an overall positive slope of expressed affect (despite instances of negativity)". De Rubeis and Granic observed how mother and child tried to manage the situation after an intervention had taken place. Coding behaviors The mother and child were asked to participate in three discussions. The third discussion, marked as "the conflict discussion", was coded and used for further analysis. Coders used a modified version of the Specific Affect Coding System (SPAFF, Gottman et al., 1996a/b) and were trained beforehand. This coding scheme consisted of 10 mutually exclusive affect codes, such as fear/anxiety, whine/complain, and joy/excitement. The Observer software was used for coding behaviors and to make a duration/sequence-based comparison. After 80% agreement was reached, the professional coders started coding the collected videos. Starting an experiment with a detailed coding scheme typically ensures a good start to your research. Developing a coding scheme can be a real challenge, but it helps you to focus on the behaviors that are of real interest to you. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Presenting results De Rubeis and Granic conclude by saying that "dyadic regulation may be an important process associated with treatment success for aggressive youth". When a dyad was regulated in its interaction, a safe context was created for children. In such an environment, negativity seemed less problematic then in unregulated dyads. Mother and child were able to work through these negative phases and they were able to return to a positive or neutral conversation mode. In managing interactions and evaluating treatment success, it is very important to take disharmonies into account. When managed correctly, these negative outbursts don't have to lead to a problematic situation. References - De Rubeis, Sera; Granic, I. (2012). Understanding Treatment Effectiveness for Aggressive Youth: The Importance of Regulation in Mother–Child Interactions, Journal of Family Psychology, 26 (1), 66-75. - Gottman, J. M., Katz, L. F., & Hooven, C. (1996a). Parental meta-emotion philosophy and the emotional life of families: Theoretical models and preliminary data. Journal of Family Psychology, 10, 243–268. doi: 10.1037/0893-3200.10.3.243 - Gottman, J. M., McCoy, K., Coan, J., & Collier, H. (1996b). The specific affect coding system (SPAFF) for observing emotional communication in marital and family interaction. Mahwah, NJ: Erlbaum. --- ## How to know if an animal is nauseated URL: https://noldus.com/blog/know-if-an-animal-nauseated Published: 2012-03-21 13:59:00 Description: Nausea is a prominent factor influencing the quality of life for patients undergoing chemotherapy. That is why it is useful to study the nauseating side effects of therapies or the anti-nauseating potential of drugs. --- ## Zebrafish and withdrawal URL: https://noldus.com/blog/zebrafish-and-withdrawal Published: 2012-03-15 15:28:00 Description: Recent work done by Khor et al. (2011) looked at the effect of mitragynine on behavior in zebrafish going through withdrawal after chronic morphine exposure. The effects of Mitragynine on morphine-withdrawn zebrafish. A major challenge in treatment of drug addictions is the management of withdrawal symptoms, which often lead to relapse. Several pharmacological strategies exist to mitigate withdrawal symptoms, but nevertheless there is a strong need for additional options, and an increased understanding of some strategies of 'self medication' currently being used. The effects of Mitragynine on morphine-withdrawn zebrafish Recent work done by Khor et al. (2011) looked at the effect of mitragynine on behavior in zebrafish going through withdrawal after chronic morphine exposure. Mitragynine is the most common compound found in the native south asian kratom leafs (Mitragyna speciosa). These are frequently used by drug addicts as a self-medication strategy when going through opioid withdrawal. It has a documented use for diarrhea, cough, muscular pain and fatigue, and is a natural antidepressant. Some of these symptoms are common to those experienced in opioid withdrawal as well. Despite its documented use for common ailments and its ability to suppress withdrawal syndrome, the mechanisms by which mitragynine works are still unknown. To help improve this, first Khor et al. investigated the effects mitragynine exposure had on zebrafish going through morphine withdrawal. At first baseline preference behavior for morphine was tested using the Conditioned Place Preference test automated by EthoVision XT. Only individuals with baseline preference between 50.1 and 79.9% for either side were chosen for subsequent experiments. The authors showed that zebrafish chronically exposed to morphine for two weeks, and subsequently withdrawn showed anxiety-related swimming patterns (reduced exploratory behavior and increases in erratic movements). This was evaluated in the novel tank diving test, previously described (Cachat et al., 2010) by analyzing the time spent in top of the tank (s); latency to top (amount of time it takes the fish to cross into the upper half of the tank; average entry duration (total time spent at top divided by the number of entries), top and bottom ratio, number of freezing bouts and duration of freezing bouts. Physiologically, morphine withdrawal was paired with increases in whole-body cortisol levels as well. Both the behavioral and physiological effects of morphine withdrawal were reduced after exposure with mitragynine. On the gene expression level, expression of CRF-R1, CRF-R2, and prodynorphin (PDYN) genes was reduced in morphine-withdrawn zebrafish exposed to mitragynine. These genes code for receptor subtypes in the corticotropin-releasing factor (CRF) system, which is strongly involved in regulating the endocrine and behavioral responses to stress. The link the authors were able to make between the observed behaviors (after chronic morphine exposure, and then after chronic morphine exposure combined with acute mitragynine) and physiological and gene expression changes makes a strong case for zebrafish behavioral research. This research just confirms that behavioral paradigms can form an important first line tool in the assessment of drug effects, and shape our understanding of their underlying mechanisms. However, it also illustrates how automated video tracking combined with the use of standard tests, and new adaptations to those tests, can foster high throughput studies and increase accuracy of data acquisition and analysis. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial References - Cachat, J. M., Stewart, A., Grossman, L., Gaikwad, S., Kadri, F., Chung, K. M., Wu, N., et al. (2010). Measuring behavioral and endocrine responses to novelty stress in adult zebrafish. Nature protocols, 5 (11), 1786–1799. doi:10.1038/nprot.2010.140 - Khor, B.-S., Jamil, M. F. A., Adenan, M. I., & Shu-Chien, A. C. (2011). Mitragynine attenuates withdrawal syndrome in morphine-withdrawn zebrafish. PloS one, 6 (12), e28340. doi:10.1371/journal.pone.0028340 --- ## Three ways to test hallucinogens on zebrafish URL: https://noldus.com/blog/test-hallucinogens-on-zebrafish Published: 2012-03-13 10:05:00 Description: Hallucinogenic drugs (psychedelics) have a growing significance in biopsychiatric research. Zebrafish are a popular animal model and seem highly sensitive to various drugs of abuse. Behavioral endpoints of zebrafish in the novel tank test, the open field test, and the shoaling behavior test Hallucinogenic drugs (psychedelics) have a growing significance in biopsychiatric research. Zebrafish are a popular animal model and seem highly sensitive to various drugs of abuse. The Kalueff lab established these two facts and in a study described in Effects of hallucinogenic agents mescaline and phencyclidine on zebrafish behavior and physiology (Kyzar et al., 2012). To shed some light on the poorly understood psychotropic effects of mescaline and phencyclidine (PCP), Kyzar et al. performed three behavioral tests, each with a naïve group of adult zebrafish. Fish were pretreated with mescaline, PCP, or no drugs at all (control group). 1. Measure behavior in the novel tank In the novel tank test, behavior was viewed from the side of the trapezoidal tank. EthoVision XT video tracking was used to measure distance traveled, velocity, and durations of highly mobile and immobile states. As is common in the novel tank test, behavior related to the place in the tank (upper or lower half) was of interest. Therefore, latency to reach the top half, transitions, and total time spent in the top and bottom half were observed. Additionally, erratic behavior and freezing bouts were scored. 2. Measure open field behavior The open field test was performed in a white plastic cylinder. EthoVision XT video tracking was used to record and measure distance traveled, average velocity, meandering, duration of movement, and the durations of highly mobile and immobile states. Additionally, the ability of mescaline and PCP to evoke rotations was scored manually. 3. Measure shoaling behavior For the shoaling test, the novel tank was used once again. Screenshots were taken to measure distances between each fish and his nearest and farthest neighbor to calculate the average inter-fish distance per group. Additionally the number of fish in the bottom and in the top half of the tank was counted. Anxiolytics and hyperactivity Similar to rodent studies, mescaline and PCP seem to have both an anxiolytic and hyperactive effect. Mescaline also affects patterning in behavior, which is a possible hallucinogenic effect. While mescaline generally increases behavioral activity in the open field test with rodents, this study did not show the same effect in zebrafish. PCP showed a prominent effect on circling behavior in the open field test, possibly mimicking a psychotic-like state. Contrary to studies on several other species, PCP did not affect social behavior in the shoaling test, whereas Mescaline did - it made the fish swim significantly closer together. Opening up possibilities for high-throughput screening This study, and other recent zebrafish data from the Kalueff lab on LSD, MDMA, and ketamine (see further reading below), supports the notion that tests with zebrafish can be used as specific screens for hallucinogenic drugs. The authors conclude: "The possibility of developing such high-throughput zebrafish-based screens not only offers an evolutionary perspective on drug-induced states, but also fosters further searches for new compounds with potential pro- and anti-hallucinogenic properties." FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Reference - Kyzar, E.J.; Collins, C.; Gaikwad, S.; Green, J.; Roth, A.; Monnig, L.; El-Ounsi, M.; Davis, A.; Freeman, A.; Capezio, N.; Stewart, A.M.; Kalueff, A.V. (2012). Effects of hallucinogenic agents mescaline and phencyclidine on zebrafish behavior and physiology. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 37 (1), 194-202, doi:10.1016/j.pnpbp.2012.01.003. Further reading - Grossman, L.; Utterback, U.; Stewart, A.; Gaikwad, S.; Wong, K.; Elegante, M.; Elkhayat, S.; Tan, J.; Gilder, T.; Wu, N.; DiLeo, J.; Cachat, J.; Kalueff, A.V. (2010). Characterization of behavioral and endocrine effects of LSD on zebrafish. Behavioural Brain Research, 214, 277-284. - Riehl, R.; Kyzar, E.; Allain, A.; Green, J.; Hook, M.; Monnig, L.; Rhymes, K.; Roth, A.; Pham, M.; Razavi, R.; DiLeo, J.; Gaikwad, S.; Hart, P.; Kalueff, A.V. (2011). Behavioral and physiological effects of acute ketamine exposure in adult zebrafish. Neurotoxicology and Teratology, 33, 658-667. - Stewart, A.; Riehl, R.; Wong, K.; Green, J.; Cosgrove, J.; Vollmer, K.; Kyzar, E.; Hart, P.; Allain, A.; Cachat, J.; Gaikwad, S.; Hook, M.; Rhymes, K.; Newman, A.; Utterback, E.; Chang, L.; Kalueff, A.V. (2011). Behavioral effects of MDMA ('ecstasy') on adult zebrafish. Behavioural Pharmacology, 22, 275-280. --- ## Bed bug behavior - What smell can tell URL: https://noldus.com/blog/bed-bug-behavior Published: 2012-03-01 10:34:00 Description: Bed bugs are on the rebound in developed countries. Traditionally, bed bugs are controlled with pesticides. However, traps with attractive human body odors are a promising alternative. Bed bugs are on the rebound in developed countries. Traditionally, bed bugs are controlled with pesticides. However, traps with attractive human body odors are a promising alternative. In two interesting studies Harraca et al. investigated the response of bed bugs to human body odors. Bed bug behavior - What smell can tell Bed bugs on the rebound Those of you who think that bed bugs belong to developing countries are wrong. Bed bugs are on the rebound in developed countries. Traditionally, bed bugs are controlled with pesticides. But the development of pesticide resistance has led to a need for alternative control methods. Trapped in odors For blood-feeding insects, traps baited with attractive odors are promising. Experimental biology therefore focuses on the host searching behavior of those insects. Once the attractive body odors are identified, they can be applied to traps to attract the blood-sucking insects. What bed bugs smell Harraca et al. investigated in two interesting studies which body odors are detected by bed bugs. They identified which sensilla on the antennae respond to which human odors. A strong response in the sensilla indicates that the bed bugs smell the odor well and that the odor may affect their behavior. Therefore, the odors that gave the strongest response in the sensilla were used to study the bed bug behavior. These were the aldehydes heptanal, octanal, nonanal, and decanal and the ketone sulcatone. Harraca et al. used EthoVision to determine the preference of the bed bugs for areas with or without these odors and the tendency of the insects to explore their environment. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your free trial Bed bugs don't like the smell of humans The bed bugs were repelled by a high dose of the aldehydes and slightly attracted to a low dose. Sulcatone had a negative effect on the tendency of the bed bugs to explore their environment. In general, bed bugs responded less to human odors as compared to what was found in other insect studies on for example mosquitoes and tsetse flies. The importance to smell from a distance The authors suggest that the insect behavior depends on the association between the insects and their hosts. Mosquitoes and tsetse flies have to find their hosts from a long distance and therefore must be able to smell their hosts. In contrast, bed bugs live much closer to their hosts, which makes the ability to smell them less important. Possibly other cues, like heat and CO2 are more important for bed bugs to locate their hosts. So after all, traps with human body odors do not look so promising to control bed bugs. The search for a sustainable control method continues. References - Harraca, V.; Ryne, C.; Birgersson, G.; Ignell, R. (2012). Smelling your way to food: can bed bugs use our odour? The journal of experimental biology, 215, 623-629. - Harraca, V.; Ignell, R.; Löfstedt, C.; Ryne, C. (2010). Characterization of the antennal olfactory system of the bed bug (Cimex lectularius). Chemical senses, 35, 195-204. --- ## The search for robust fear inducing stimuli in zebrafish research URL: https://noldus.com/blog/fear-inducing-stimuli-zebrafish-research Published: 2012-02-24 11:42:00 Description: Zebrafish behavioral research has grown by leaps and bounds, and behavioral paradigms are being developed with the aim of better understanding mechanisms that might underlie aberrant behavioral phenotypes. Zebrafish behavioral research has grown by leaps and bounds, and behavioral paradigms are being developed with the aim of better understanding mechanisms that might underlie aberrant behavioral phenotypes. This knowledge can be applied to complex human conditions, such as anxiety disorders. Fear paradigms can potentially bring more insights into mechanisms that are involved in these disorders. These require stimuli that consistently produce robust fear responses in zebrafish. Luca and Gerlai (2012) have attempted to expand on the small but growing arsenal of behavioral stimuli that can be used. The search for robust fear inducing stimuli in zebrafish research Not a large body of knowledge exists on effective fear stimuli for zebrafish research prior to this study being published, and this paper definitely provides a greater appreciation for the complexities involved in fear paradigms, and stimulus selection. Not all stimuli that are intended to elicit a fear response, actually do. And visa versa. In fact, Luca & Gerlai show that it isn't just the type of stimulus that matters, but its placement is crucial as well; an image of a growing dot (mimicking an approaching predator) is more effective when shown from above, compared to the side. This highlights an interesting and noteworthy approach the authors took in this study: they chose to position a computer screen over top the testing tank in which the zebra fish was placed, showing the stimulus. Previous work published by Gerlai discusses how the presentation of a visual stimulus on a computer screen adjacent to the testing tank is as effective in eliciting a behavioral response as a live predator. This includes a live predator where zebrafish are exposed to both the visual and physical stimuli (lateral line and olfactory cues). A noteworthy and interesting choice made by Luca & Gerlai in terms of stimulus presentation is the image of a bird silhouette, which was displayed over top the testing tank. They argue that although it is not conclusively confirmed that zebrafish fall prey to fishing birds, the natural habitat and the species that live within the same environment suggest this is highly likely. It is an interesting follow up to previous work showing differences in response to allopatric and sympatric predators, where sympatric predators show a more robust response. Suggesting that if the image of a bird, or an image mimicking an approaching bird's head (the dot) is in fact robust it could support the assumption that zebrafish are preyed on by birds. This in turns opens a new possible approach in studies using fear paradigms. It's not what you show, it's how you show it As it turns out, an approaching dot over the top of the tank was more robust than an image (whether a dot or a bird shape) being shown on the side of the testing tank. This illustrates another level of complexity to behavioral research: it is not sufficient to consider which type of stimulus to present, but the mode of presentation (or location) can be just as important. This article narrows down some of the options researchers might be considering when developing fear paradigms, paving the way for a more focused approach in experimental design. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Get your Free trial Reference Luca, R.M.; Gerlai, R. (2012). In search of optimal fear inducing stimuli: Different behavioral responses to computer animated images in zebrafish. Behavioural brain research, 226, 66-76. --- ## Clinical interviews – analyzing verbal and non-verbal behavior URL: https://noldus.com/blog/clinical-interviews Published: 2012-02-15 15:36:00 Description: In general, researchers choose the methods and techniques that best suit their research objectives. That’s no different when researching doctor-patient communication or any other clinical interview setting. In general, researchers choose the methods and techniques that best suit their research objectives. That's no different when researching doctor-patient communication or any other clinical interview setting. Some researchers use audio recordings to study verbal behavior while others try to get more insight in non-verbal behavior by recording behavior on video. Both of these techniques are aimed at studying the interaction process between clinician and patient. For each research question a different approach can be selected. Let's have a look at two different approaches. In communication verbal and non-verbal behaviors can both be essential to understand the meaning of an utterance or statement. However, in these cases researchers have chosen to study either verbal utterances or non-verbal behavior. Download here the FREE white paper 'How to set up behavioral coding - 7 tips' Non-verbal behavior Montague and colleagues presented a study in which they analyzed non-verbal behavior in clinical interactions, specifically, looking into eye gaze behavior patterns (eye gaze behavior is considered an important aspect of doctor-patient interaction). They introduced a new method to evaluate gaze behavior patterns in doctor-patient interaction based on a lag sequential analysis for the description of eye gaze orientation between clinicians and patients. Video coding of behaviors of the clinician and the patient (using a coding scheme developed by Krippendorff, 2004) has allowed them to analyze non-verbal behavior patterns and draw conclusions: 'the clinician's gaze significantly affects the medical encounter but the converse is not true' (Montague et al. 2011). Verbal behavior Then, Heyn et al. looked into verbal responses. A total of 193 consultations were analyzed. They made audio recordings and coded the conversations using task-focused categories of the Roter Interaction Analysis System (Roter and Larson, 2002). Heyn et al. coded the initiation of symptoms by applying criteria from the Verona coding definitions of emotional sequences (VR-CoDES, Zimmerman, 2011). As a result, they gained insight in the interaction between clinician and patient. A different kind of interaction when compared to what is presented by Montague et al. The background to Heyn et al.'s research falls back on a wish to test Choice, an interactive tailored patient assessment tool. The consultations coded in The Observer XT gave them insight in the effectiveness of Choice. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Interested? Read more about clinical communication in a free case study "Clinical communication - Using The Observer XT in physician-patient interaction". References - Heyn, L.; Finset, A.; Eide, H.; Ruland, C.M. (2011). Effects of an interactive tailored patient assessment on patient-clinician communication in cancer care. Psycho-Oncology, DOI: 10.1002/pon.2064. - Krippendorff, K. (2004). Content analysis: An introduction to its methodology. Thousand Oaks, CA: Sage. - Montague, E.; Xu, J.; Chen, P.; Asan, O.; Barrett, B.P.; Chewning, B. (2011). Modeling eye gaze patterns in clinician-patient interaction with lag sequential analysis. Human Factors, 53 (5), 502-516. - Roter D.; Larson S. (2002). The Roter interaction analysis system (RIAS): utility and flexibility for analysis of medical interactions. Patient Education and Counseling, 46, 243–251. - Zimmermann C.; Del Piccolo L.; Bensing, J. et al. (2011) Coding patient cues and concerns in medical consultations: the verona coding definitions of emotional sequences (VR-CoDES). Patient Education and Counseling, 82, 141–148. --- ## Zebrafish research: growing demands in South America URL: https://noldus.com/blog/zebrafish-research-south-america Published: 2012-02-13 10:49:00 Description: It was at the Society for Neuroscience last November that I was invited to speak at the second annual LAZEN meeting held last December in Porto Alegre, Brazil. Recently I wrote about the growing presence of zebrafish related studies at big international conferences, like the Society for Neuroscience annual meeting. This general infiltration of zebrafish in behavioral and biological sciences as a whole has been significant enough that the demand for specialized zebrafish meetings continues to grow. Specialized meetings have been established for years and new ones continue to surface; from the 10th zebrafish genetics and development conference, to the 13th Australia and New Zealand zebrafish meeting, the 2nd European Zebrafish PI Meeting, and now the second Latin American Zebrafish Network (LAZEN) course. It was at the Society for Neuroscience last November that I was invited to speak at the second annual LAZEN meeting held last December in Porto Alegre, Brazil. This opportunity not only offered a chance for me to speak on zebrafish, behavioral paradigms, and my own research but also gave me a new view and appreciation for the potential of this model. Zebrafish earning their stripes in research Zebrafish use in research has been growing steadily on the world-stage, but in South America in particular this growth is unprecedented. LAZEN beautifully illustrated this, with nearly 100 participants from all over the continent where most attendants were researchers with beginner or intermediate experience. To help investigators expand on their expertise with this organism, mornings were filled with practical hands-on lab sessions and afternoons were populated with traditional talks. I had the pleasure of both giving a talk and leading a morning session on behavioral paradigms. Particularly during the morning sessions participants tended to be beginners armed with questions and enthusiasm, and topics ranged from husbandry and breeding to behavior and molecular assays like DNA injections, inflammation assays, transgenesis, and in situ hybridization. After my talk some of the discussions that came up centered around practical concerns, for example how to test how much alcohol enters the bloodstream in an alcohol paradigm. A discussion about potential factors that can affect zebrafish (and experiments) came up as well, after I brought up the situations I have faced in the past. For example, issues relating to differing PH and salinity conditions, water temperature, and even air pressure: One researcher from Ecuador voiced concerns of high mortality among zebrafish and the possibility that this might have something to do with the altitude and air pressure. What made the discussions interesting was the focus on local concerns and challenges unique to research in South America. This even went beyond the practical laboratory concerns, to import policies that affect zebrafish entering South America. Interestingly, it is shocking to see the promise zebrafish hold in behavioral research, in particular in South America: thanks to the economy of the model (maintenance costs, low start-up costs) average laboratories are able to produce world-class research. Without too large an investment small research groups are able to compete with large laboratories in quantity and quality of publications. This is of course somewhat generalized, but realistically new research groups are able to produce high quality behavioral research with a very minimal investment. Publications and growing recognition can lead to increased funding, which in turn allows these same groups to continue expanding their resources and work on increasingly high caliber projects. The meeting illustrated how work that would require a prohibitive investment using a rat-model can be done at a fraction of the cost in zebrafish. This places previously quite unknown research groups on the world stage. The result has been an increasing number of publications coming from the southern hemisphere, and it will be interesting to keep an eye on this growing body of dedicated researchers. In short, LAZEN created a scientific program to appeal to both beginners and advanced zebrafish researchers. The organization and quality of the course far exceeded the modest cost of and makes it a 'must-attend' for researchers beyond just South America. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial --- ## Three examples of swimming rats in traumatic brain injury research (TBI) URL: https://noldus.com/blog/traumatic-brain-injury-research Published: 2012-01-20 15:03:00 Description: The Morris water maze and EthoVision, a validated solution to investigate learning and memory in rats and mice. Studies with EthoVision XT and the Morris water maze test The Morris water maze test is a well validated and often used tool to investigate learning and memory in rats and mice. This blog post elaborates on three studies from The Walter Reed Army Institute of Research in Silver Spring (Maryland, USA) that use the Morris water maze in combination with automated tracking software EthoVision XT. At the Walter Reed Army Institute, scientists investigate TBI (a leading cause of death and disability in the USA), and established the PBBI model for TBI; penetrating ballistic-like brain injury in rodents. In Shear et al. (2010) the focus is on advancing the test platform for longitudinal research on the PBBI model. When motor, sensory, and cognitive deficits are investigated, a Morris water maze test in combination with behavioral tracking software EthoVision XT is used for the latter. PBBI rats showed thigmotaxic swim patterns, suggesting a general incapacity to switch to a good search pattern. After re-testing, they were able to find the platform increasingly faster, but they never made it up to the level of the control group. When pre-trained in the Morris water maze before their surgery, PBBI rats performed as well as their control group following surgery. However, they remained behind again in a spatial reversal task when the platform was moved and they needed to learn the new location. In conclusion: PBBI rats show normal memory retention, but impaired spatial learning. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Get your Free trial Sensitivity of the testing platform In 2011 Shear et al. the same PBBI model is used to assess the sensitivity of the testing platform across a range of trauma severity levels, ranging from 5% to 12.5% of the rat brain volume. The Morris water maze - EthoVision XT solution was again used to determine cognitive impairment. The results of this study were directly ranked by the degree of injury severity. The rats with the 12.5% injury rate showed the greatest cognitive impairment. New animal model In 2011, the same research group (Chen et al.) also proposes a new animal model of closed-head concussive-induced mild TBI; projectile concussive impact, or PCI. Using the same set-up, spatial learning and memory were tested. One hour after the PCI procedure, rats were given 12 consecutive trials and a probe trial. No differences were found between the test group and the control group. Additionally, sensorimotor performance was tested using CatWalk, and here PCI induced gait abnormalities at 1 to 4 hours after PCI, some of which were still detectable a day later. Read more about the use of EthoVision XT in water maze testing in this white paper. References - Shear, D.A.; Lu, X.-C.M.; Bombard, M.C.; Pederson, R.; Chen, Z.; Davis, A.; Tortella, F.C. (2010). Longitudinal characterization of motor and cognitive deficits in a model of penetrating ballistic-like brain injury. Journal of Neurotrauma, 27, 1911-1923. - Shear, D.A.; Lu, X.-C.M.; Pederson, R.; Wei, G.; Chen, Z.; Davis, A.; Yao, C.; Dave, J.; Tortella, F.C. (2011). Severity profile of penetrating ballistic-like brain injury on neurofunctional outcome, blood-brain barrier permeability, and brain edema formation. Journal of Neurotrauma, 28, 2185-2195. - Chen, Z.; Leung, L.Y.; Mountney, A.; Liao, Z.; Yang, W.; Lu, X.-C.M.; Dave, J.; Deng-Bryant, Y.; Wei, G.; Schmid, K.; Shear, D.A.; Tortella, F.C. (2011). A novel animal model of closed-head concussive-induced mild traumatic brain injury: development, implementation, and characterization. Journal of Neurotrauma, doi: 10.1089/neu.2011.2057. --- ## Observing behavior - Jury deliberations, what happens behind closed doors URL: https://noldus.com/blog/observing-behavior-jury-deliberations Published: 2011-12-19 12:42:00 Description: Researchers increasingly study what goes on behind closed doors. Thirty mock-jury deliberations were filmed and behaviors were then coded using The Observer software. Jury deliberations expected to begin today in Iredell murder trial — Jury deliberations in Whitehead trial continues Wednesday – Jurors continue deliberations in Padilla trial – These are just a few headlines that mention jury trials. Nowadays, researchers increasingly study this deliberation process, which goes on behind closed doors. Take for example Behind closed doors: the effect of pretrial publicity on jury deliberations (Ruva, 2011). The results of this study suggest that negative pretrial publicity (PTP) has a biasing effect on jury verdicts and that PTP exposure can influence juror's interpretations and discussion of trial evidence. Observing mock-jury deliberations Christine Ruva et al. (2011) analyzed 30 mock-jury deliberations. One point of interest, which they explored, was the behavior of jurors who were asked to read actual negative pretrial publicity from the murder trail that they later viewed in comparison with jurors who read unrelated news articles. Researchers performed content analyses in order to discover what occurs during jury deliberations. The mock-jury deliberations were filmed and behaviors were then coded using The Observer software. The authors of this article prefer using this software package instead of transcribed deliberations or video observations, which use less sophisticated content analysis tools. The Observer software allows for more elaborate coding schemes and more accurate event timing. These elaborate coding schemes provide the user tools to more accurately analyze and even detect the most subtle differences in behavior. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Evaluating group processes Furthermore, evaluating group processes, such as jury deliberations, can be extremely valuable for many fields of research. Scientists are examining new methods and techniques that can help them gather relevant data. For example, Waller et al. (2011) studied how individuals contribute to a decision-making process. They hypothesized that individuals in large group settings do not always contribute equally to group decision making processes. Realizing it would be interesting to closely observe any group process, they examined roles such as influencers, deciders, listeners, and bystanders. In the end, Waller concluded that the data gathered did not demonstrate any effect of group size on actual participation during deliberations. What they measured was perceived participation. Not actual but perceived participation, because they used questionnaires to gather data. The results of both might be similar, however, it is still important to clarify how participants truly behaved, which can be done through the gathering of observational data. References - Ruva, C.L.; LeVasseur, M.A. (2011). Behind closed doors: the effect of pretrial publicity on jury deliberations. Psychology, Crime & Law, DOI:10.1080/1068316X.2010.502120, 1-22. - Waller, B.M.; Hope, L.; Burrowes, N.; Morrison, E.R. (2011). Twelve (not so) angry men: managing conversational group size increases perceived contribution by decision makers. Group processes & intergroup relations, 14 (6), 835-843. --- ## Systematic behavioral observation – two coding scales URL: https://noldus.com/blog/behavioral-observation Published: 2011-12-05 15:58:00 Description: Structured observations are one of the many ways to gather data. Observing behavior rather than asking questions about it can provide you with a multitude of valuable information. Structured observations are one of the many ways to gather data. Observing behavior rather than asking questions about it can provide you with a multitude of valuable information. When you start using observations, you can structure the research method by developing a coding scheme and determine what you want to focus on. Structuring your observations means thinking about what you want to observe rather than simply noting down whatever is visible and seems relevant. Martin and Bateson (2007) state that the problem with this type of sampling, ad libitum sampling, is that observations will be biased towards those behavior patterns and individuals which happen to be most conspicuous. So let's see what observation scales are and how they can contribute to observational research. 1) Pretend Play Observation Scale The Pretend Play Observation Scale was developed by Brown in 1997 and over time has been further developed and used in studies which investigated the pretend play of mother –toddler dyads in relation to later child IQ (Morrissey and Brown 2009). The selected samples of video recording were coded using The Observer XT software. Event sampling was used to record the level and number of child and mother play behaviors. They conclude that this study proves that gifted children show differential development (rapid learning) from the first year of life. The combination of the coding scheme by Brown in 1997 and The Observer software provided a powerful and structured method to study pretend play behavior. 2) OPOS - Outdoor Play Observation Scheme OPOS - Outdoor Play Observation Scheme (Bakker et al 2008) is presented as one of the coding schemes used in gaming research. Bakker and colleagues describe four classes: physical activity, social interaction, focus, and general. And behaviors fit into these classes. (This coding scheme is evaluated on http://www.allaboutux.org/opos-outdoor-play-observation-scheme). It is an observation scheme for evaluating head-up play. Bakker et al's proposed observation scheme is found to be objective and reliable, helping evaluators compare pervasive games regarding the play behaviors they provoke. As a weakness, All about UX mentions that coding of videos is very time consuming. It can take a while to code video, no denying that. However, using flexible software such as The Observer XT to help you in the process will ease the pain. This coding scheme OPOS, was used by Soute, Kaptein, and Markopoulos (2009) who presented a case study where two versions of the same outdoor pervasive game were compared. They concluded that the inter-rater reliability for social interaction was poor. They found that it was quite difficult to judge children's verbal utterances from the videos and proposed to improve this by equipping participants with small microphones, so each participant's speech is recorded separately. Of course there is always room for improvement: methods and techniques are rapidly evolving. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial How to develop your own observation scale You can develop your own observation scale by observing behaviors of your test participants, live or from video, and arrange behaviors in classes. Try to sort them and maybe even add modifiers to describe behaviors in great detail. References - Bakker, S.; Markopoulos, P.; Kort, Y.D. (2008). OPOS: an observation scheme for evaluating head-up play. Proceedings of NordiCHI 2008, ACM 2008, 33-42. - Brown, P. M.; Rickards, F. W.; Bortoli, A. (2001). Structures underpinning pretend play and word production in young hearing children and children with hearing loss. Journal of deaf studies and deaf education, 6, 15-31. - Martin, P.; Bateson, P. (2007). Measuring Behaviour. An introductory guide. Cambridge University Press. - Morrissey, A-M.; Brown, P.M. (2009). Mother and toddler activity in the zone of proximal development for pretend play as a predicator of higher child IQ. Gifted child quarterly, 53 (2), 106-120. - Soute, I.; Kaptein, M.; Markopoulos, P. (2009). Evaluating outdoor play for children: virtual vs. tangible game objects in pervasive games. Proceedings IDC 2009, June 3-5 2009, Como, Italy, 250-253. --- ## Recent applications of locomotor and gait analysis URL: https://noldus.com/blog/locomotor-and-gait-analysis Published: 2011-12-01 16:00:00 Description: Stem cell research is a promising area of research for spinal cord injury. With 1,25 million individuals suffering from chronic spinal cord injury in the US alone, new treatment approaches are necessary. Stem cell research is a promising area of research for spinal cord injury. With 1,250,000 individuals suffering from chronic spinal cord injury in the US alone, new treatment approaches are necessary and research in this area is not slowing down (Salazar, Uchida, Hamers, Cummings, & Anderson, 2010). Spinal cord injury typically involves the loss of neurons in the spinal column, which depending on the location of the injury can lead to motor deficits or complete paralysis. Stem cell therapies are a promising area of research for treatment, as stem cells might be able to replace lost neurons and recover some or all motor function. However, there is a strong lack of consensus about the types of stem cell therapies that might be useful (Schira et al. 2011). This is partially fuelled by inconsistent functional outcomes in studies investigating different therapeutic strategies. Functional outcomes can also seem more variable due to different tests being applied to assess the success of a therapy. In addition, only using one behavioral test to assess functional recovery can offer an incomplete view of the results, but it is uncommon for more than one test to be used. In contrast, the research done by Schira et al. uses three behavioral tests, one of which is gait and locomotor assessment using CatWalk™ XT. The most important tool for the assessment of functional recovery after spinal cord injury in rodents CatWalk XT provides systematic and extensive automated gait analysis. Measuring a number of dynamic and static gait parameters simultaneously provides a rich insight in functional recovery in response to treatments like stem cell transplantation. Shira et al. showed that stem cells transplanted to the area of injury accumulated within the lesion area, reducing the size of the lesion. Axon regrowth was enhanced, but more importantly, behavioral tasks showed improved locomotor function. Although biologically we can assess whether stem cells seem to be responsive after being translated into the lesioned area, nothing but behavioral testing can evaluate functional recovery. Ultimately, biological assessments can only hint at what we belief the functional outcome might be. For example, differentiation from umbilical cord-derived stem cells continues to be debated. However, effects from transplanting human umbilical cord blood in spinal cord injury have been supported whether differentiation was observed or not. Whether or not neural differentiation is observed, there could be regeneration through (unknown) mechanisms other than differentiation. This is where behavioral assessment provides most illuminating insights into the viability of therapeutic targets. Ultimately, the functional outcome is what matters, even if the underlying mechanisms require further study. RESOURCES Read more about CatWalk XT Find out how CatWalk XT is used in a wide range of studies and how it can elevate your research! - Free white papers and case studies - Customer success stories - Recent blog posts Resources References - Salazar, D. L.; Uchida, N.; Hamers, F. P. T.; Cummings, B. J.; Anderson, A. J. (2010). Human neural stem cells differentiate and promote locomotor recovery in an early chronic spinal cord injury NOD-scid mouse model, PloS one, 5(8), e12272. doi:10.1371/journal.pone.0012272 - Schira, J.; Gasis, M.; Estrada, V.; Hendricks, M.; Schmitz, C.; Trapp, T.; Kruse, F. et al. (2011). Significant clinical, neuropathological and behavioural recovery from acute spinal cord trauma by transplantation of a well-defined somatic stem cell from human umbilical cord blood, Brain: a journal of neurology. doi:10.1093/brain/awr222 --- ## Horses: behavioral research, physiology and biomechanics URL: https://noldus.com/blog/equitation-sciences Published: 2011-11-15 11:07:00 Description: Besides the study of the relation between humans and popular pets such as cats and dogs, human-horse interaction is an increasingly popular subject of science. Not long ago, we wrote a blog post on human-cat interaction. Besides the study of the relation between humans and popular pets such as cats and dogs, human-horse interaction is an increasingly popular subject of science. International Society of Equitation Sciences There has always been a lot of discussion amongst people that have something to do with horses. Whether leisurely riding them or training them for high level sports, the emotional component of the horse business has always caused many opinions that often clash. Of course, we human beings know the answer to that problem: let's add some science to the mix. What can we actually say with some certainty on horse behavior, welfare, and health? This is where the ISES (International Society of Equitation Sciences) comes in. This year their 7th international conference was held in the Netherlands, and it brought together scientists from many different nationalities and disciplines. Research presented varied from learning and stress tests in horses, to physiological measurements on horse-rider interactions, to eye-tracking measurements of judges in the dressage discipline. Equitation sciences is a field that is going through some interesting developments that could bring many advances in both horse welfare and high level sport accomplishments. Theory and practice This conference is unique in its combination between the theoretical and the practical. Heart rate measurement tools on both rider and horse were demonstrated life; while horse and rider where jumping some fences in the arena, graphs of their heart rates were shown life on the screen. Rain and saddle pressure devices and gait measurement systems were also demonstrated. How to combine behavioral and physiological measurements in horses Equitation sciences is a relatively young field of research. In laboratory rodents, the use of telemetry and combining this with behavioral measurements is not uncommon. In horses however, it is a whole different ballgame. Of course they are much bigger and their space of movement is larger, especially when doing research on horses during training. Equipment needs to be wireless, sturdy, and durable. Another factor that makes research challenging is that horse are very individual animals. While one shows excitement clearly in both behavior and heart rate, another might hide it well and not show any signs while their heart rate is significantly elevated, and yet another may show clear behavioral signs while nothing particular happens to its heart rate. To get a better understanding, more factors (physiological measurements) need to be combined with behavioral measures. A challenge equitation scientists further face in the coming years. What to measure in horse-human interaction Current research can be summarized in three aspects: Behavior, biomechanics, and physiology. Behavior is fairly easy to study. Two focus areas include problem behavior (e.g. in the stables, during handling, during loading onto a trailer, etc.) and behavior during training or competition. Of course, behavioral measurements can be taken of both horse and handler/rider. Biomechanical interaction between the horse and rider can be investigated with the use of strain gauges on bits, rains, and stirrups and force sensors on saddle pads and the rider's legs. Physiological measures, mostly to indicate stress and/or strain include heart rate and heart rate variability, cortisol levels (fecal and saliva), skin and eye temperature, and plasma serotonin levels for the horse. Human measures are mainly limited to heart rate and heart rate variability. Questionnaires are an optional tool for supplemental information. Multimodal research The amount of multimodal research is carefully increasing, and the need for integration systems arises. That is where The Observer XT poses as an interesting platform. Indeed, during the conference, Noldus IT was able to showcase some experiments in which heart rate of both rider and horse and their behavior was combined. This is still a modest example of how The Observer XT helps out in multimodal research, surpassing it's potential as behavioral coding device alone. Find out more on how The Observer XT can be your integration platform for multimodal research at The Observer XT for animal research or request a free trial below. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial --- ## Behavioral assays establish zebrafish in drug screening URL: https://noldus.com/blog/behavioral-assays-zebrafish-drug-screening Published: 2011-10-26 15:52:00 Description: Zebrafish are increasingly swimming into the view of large-scale drug screening projects. Behavioral screens can be used as a first-line detection tool for new drug effects, and their popularity continues to grow. Zebrafish are increasingly swimming into the view of large-scale drug screening projects. Behavioral screens can be used as a first-line detection tool for new drug effects, and their popularity continues to grow. Translating results to what we might see in humans requires an appropriate (vertebrate) model suited for large-scale studies. This is a tall order, but one zebrafish easily fill. Mice and rats are more established model systems, but size and cost are often prohibitive to large-scale analyses. Compromising in favor of size and cost points to an invertebrate model like Drosophila. However, in zebrafish researchers find the economy required for high throughput studies, in a vertebrate model. Swimming down the pipeline: behavioral assays establish zebrafish in drug screening Collwill and Creton (2011) recently reviewed zebrafish behavioral assays and highlight how these can help in discovering new drug targets for anxiety. Successful high throughput screens using zebrafish hinge on using automated imaging, which is a topic touched on in this review. Systems like DanioVision and EthoVision XT have made it possible to track and analyze behavioral traits. This removes the need for time consuming manual scoring, and provides high resolution data gathered in real time. The zebrafish larva's small size (~4mm) lends itself well to large-scale analysis: One 96 well-plate accommodates an equal number of subjects. Using automated imaging, the average lab can process hundreds of zebrafish a day. For example, EthoVision XT has been employed in isolating seizure-resistant zebrafish larvae in a large-scale mutagenesis screen. Combining behavioral assays with physiological measures provides an even more powerful avenue for analysis: stress hormones such as cortisol have shown to be elevated in 'stressed' zebrafish, essentially providing the basis for validating behavioral data. After observing behavior, it is fairly easy to measure hormone levels, although this is not possible in vivo in zebrafish. New options for measuring physiological responses during behavioral tasks are heart rate and skin color monitoring. Zebrafish larvae are optically transparent, and a large number of them can be monitored in multiwell plates. Image analysis software can be used to extract specific parameters of the zebrafish heart beat. At this point, imaging heart beat in a freely moving zebrafish is still technically challenging, but once further developed this paradigm can open interesting new avenues for studying the physiology of fear and anxiety. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial Large scale screens rely on easily measured observations. For example, thigmotaxis is a behavior that correlates with anxiety. In addition, observing skin color can be very informative: zebrafish larvae adjust their color to their background. Screening for blindness can be as simple as looking at adjustments in color after changing lighting conditions in large-scale studies. The development of new behavioral assays for zebrafish is in full swing, and the possibilities are vast. The existence of sophisticated behavioral tracking and analysis tools are fueling this growing field of research, and adding to the arsenal of high throughput screens being used in the discovery of new drug targets. References Colwill, RM and Creton, R. (2011). Imaging escape and avoidance behavior in zebrafish larvae. Reviews in Neuroscience, 22 (1), 63-73. --- ## Observing social behavior and communication in wild elephants URL: https://noldus.com/blog/observing-wild-elephants Published: 2011-08-04 13:31:00 Description: A trunk-to-mouth greeting ritual. Yes. We are talking about elephants here. A trunk-to-mouth greeting ritual. Yes. We are talking about elephants here. Dynamics of dominance hierarchies Last week we've put a great link on our Facebook page, to a blog post from the New York Times. In their 'scientists at work' section, world renowned elephant specialist Dr. Caitlin O'Connell-Rodwell writes about her study on the dynamics of dominance hierarchies in male elephants. Both engaging and intriguing, this post is ready worth a read. Check it out at: Carrots and Sticks in Elephant Land - NY Times Dr. O'Connell-Rodwell seems to be camping out at the Mushara drinking hole in Namibia for quite some time now, in her latest book 'The Elephant Scientist' you can read her research there started almost twenty years ago. From their research tower, she and her colleagues scan the horizon until the elephants appear and they can start observing and documenting their behavior on video and by live scoring (with The Observer XT). A trunk-to-mouth greeting, a displacement from a subordinate from the best drinking place, and affiliative behaviors such as a trunk wrap or some gentle sparring. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial Seismic communication Her research is not limited to social affiliative and aggressive behaviors though - she has also done some fascinating work on seismic communication between elephants. For example, she showed that elephants are able to produce vocalizations that couple with the ground and travel along the surface of the earth. If these are alarm calls, the seismic signals are recognized, and the elephants respond accordingly by getting closer together and changing their body orientation to a position perpendicular to the source of the signal. They also leave the drinking hole sooner. Further study also showed that discriminate differences between seismic playbacks of the same call type made by different callers (unfamiliar vs familiar herds). More about this research can be found here. On our website you find more details on our solutions to score animal behavior. --- ## Learning to use animal models for psychiatric disorders URL: https://noldus.com/blog/animal-models-psychiatric-disorders Published: 2011-07-21 09:44:00 Description: Recently Lucas Noldus was interviewed for a technology feature in Nature; “Inside the minds of mice and men” by Monya Baker. Recently Lucas Noldus was interviewed for a technology feature in Nature; "Inside the minds of mice and men" by Monya Baker. Nature, 475, 123 - 128. "As more molecular biologists want to monitor genetically engineered mice, demand for and applications of automated systems are increasing." Monya Baker quotes Lucas Noldus, president of Noldus Information Technology, in her technology feature in Nature this month. Some animal models for human disorders are pretty straight-forward. Down's syndrome, for instance, has a clear recognized cause and behavioral consequences in animal models (motor problems and learning deficits). However, challenges that researchers face today include neurocognitive disorders that are multifaceted in genetics as well as environmental contributors. Those include autism, schizophrenia, and depression. Engineering the right animal model may be difficult to start with, assessing these models properly can involve even more complications. "Current tests are blunt tools" states Baker. So what is a researcher to do? They can fine-tune the behavioral assays, make them fit better with what can be learned from the human patients. That is exactly what Jacqueline Crawley (chief of Behavioral Neuroscience at the national institution of Mental Health) says: "We talk more to the clinical researchers." Researchers are developing tests that specifically capture relevant behavioral indicators, including developments in video tracking and home cage testing. Video tracking is already widely used and seems to be essential to continuously and automatically capture the full-range of behavior shown by mice and rats during longer periods of time. Unexpected behaviors reveal unanticipated biology, so says Baker. She also states that moving a mouse from its home cage to the testing area may even be the most confounding variable. Or as neurobiologist Laurence Tecott puts it: "We scare the hell out of the animal, then ask it if it's anxious and how it can learn." Home cage testing might prevent this bias in behavioral assays. And it seems to be gaining popularity, as the number of publications on home cage testing has doubled over the last twenty years. In this article, Lucas Noldus explains how an instrumented home cage can be configured to perform any kind of test, from anxiety to memory. Noldus Information Technology supplies home cage testing set-ups, including the PhenoTyper, the instrumented home cage which is designed to be combined with tracking software, EthoVision XT. For examples of research, visit selected publications. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your research! - A cost-effective solution - Powerful data selection - Most cited video tracking system Free Trial Read the complete technology feature at Nature: Inside the minds of mice and men --- ## Zebrafish as lab animal increasingly popular URL: https://noldus.com/blog/zebrafish-as-lab-animal-increasingly-popular Published: 2011-07-08 15:34:00 Description: Zebrafish is the new rat. Or mouse. More and more rodents in the lab are being replaced by these nifty little striped fish. They are easy to maintain, reproduce and develop rapidly. Zebrafish is the new rat. Or mouse. More and more rodents in the lab are being replaced by these nifty little striped fish. They are easy to maintain, reproduce and develop rapidly, and there is a great similarity between the human and zebrafish genome. And because they are easily genetically manipulated, many human diseases and developmental disorders can be modeled in zebrafish, such as Parkinson's, Alzheimer's, and cancer. One stripe ahead; zebrafish increasingly popular as lab animal Like rodents, zebrafish (Danio rerio) can be used in tests investigating fear, stress, and anxiety, learning and memory, and social behavior. And these behaviors can be manipulated by changing their genetics (testing different strains as models for diseases), providing stressful stimuli (tapping on the tank, visuals of predators, etc.) and adding substances (anxiolytics such as buspirone, chlordiazepoxide, and diazepam; anxiogenics; socially relevant substances as ethanol and nicotin) to the water. Many paradigms are already validated in research Many paradigms are already validated in research, such as the open field test, novel tank diving test, light/dark box test, 2- or 3-chambered set-ups and the T-maze. Like rodents, zebrafish show thigmotaxis in an open field set-up. Similarly, when investigating their vertical swimming behavior, zebrafish show bottom dwelling, slowly moving across the bottom only to gradually explore the upper segments of the tank after some minutes have past and habituation sets in. In a light/dark box, uninfluenced zebrafish normally show a preference for the lighter sections (contrary to rodents), which can be explained by the fact that they are diurnal animals, having more luck on finding food in the light. Zebrafish embryos and larvae used in (high throughput) research Not only the adults, but also zebrafish embryos and larvae are often used in (high throughput) research. Zebrafish embryos develop externally, and because zebrafish are translucent until they get their signature stripes, organ and blood vessel development can be watched closely. Larvae absorb compounds from the surrounding water, making them easy to manipulate during each stage of their development. The behavior of zebrafish is studied by measuring variables such as swimming speed, distances swum, time spent in the different sections of the tank or maze, time spent immobile, erratic movements, turn angle, etc. For an accurate, objective, and efficient measurement of these parameters, tracking software provides a practical tool for researchers. Below are some examples of studies that include EthoVision XT tracking software in their research. Additionally, DanioVision is a system that includes EthoVision XT and provides a plug-and-play solution for zebrafish larvae testing. FREE TRIAL Try EthoVision XT yourself! Request a free trial and find out what EthoVision XT can do for your zebrafish research! - Track zebrafish adult, larvae or embryo - Suitable for tracking in any arena - Most cited video tracking system Free Trial References - Ahmed, O.; Seguin, D.; Gerlai, R. (2011). An automated predator avoidance task in zebrafish. Behavioural Brain Research, 216, 166-171. - Bencan, Z.; Sledge, D.; Levin, E.D. (2009). Buspirone, chlordiazepoxide and diazepam effects in zebrafish model of anxiety. Pharmacology, Biochemistry and behavior, 94, 75-80. - Cachat, J.; Stewart, A.; Utterback, E.; Hart, P.; Gaikwad, S.; Wong, K.; Kyzar, E.; Wu, N.; Kalueff, A.V. (2011). Three-dimensional neurophenotyping of adult zebrafish behavior. PLoS ONE, 6(3), e17597. - Champagne, D.L.; Hoefnagels, C.C.M.; de Kloet, R.E.; Richardson, M.K. (2010). Translating rodent behavioral repertoire to zebrafish (Danio rerio): Relevance for stress research. Behavioural Brain Research, 214, 332-342. - Gerlai, R.; Fernandes, Y.; Pereira, T. (2009). Zebrafish (Danio rerio) responds to the animated image of a predator: Towards the development of an automated aversive task. Behavioural Brain Research, 201, 318-324. - Levin, E.D. (2011). Zebrafish assessment of cognitive improvement and anxiolysis: filling the gap between in vitro and rodent models for drug development. Reviews in the Neurosciences, 22(1), 75-84. - Levin, E.D.; Cerutti, D.T. (2009). Behavioral Neuroscience of Zebrafish. Chapter 15 from Methods of Behavior Analysis in Neuroscience, second edition. Boca Raton (FL): CRC Press. - Willemsen, R.; van der Linde, H. (2010). Zebrafish larvae activity – A study of locomotive behavior with DanioVision. Case study provided by Noldus Information Technology. --- ## Temporal patterns (T-patterns) in behaviors cats and their owners URL: https://noldus.com/blog/temporal-patterns-cats-owners Published: 2011-06-15 11:01:00 Description: Noldus provides many solutions for research on the behavior of both animals and humans. On occasion, a Noldus solution is used for both animal and human research at the same time. Crossing the bridge between human and animal behavior research Noldus provides many solutions for research on the behavior of both animals and humans. And on occasion, a Noldus solution is used for both animal and human research at the same time. Manuela Wedl and her colleagues are a prime example with their study on human-animal interaction. In 'Factors influencing the temporal patterns of dyadic behaviours and interactions between domestic cats and their owners', Wedl et al. wrote about their study on forty cat-owner couples. Their experiment comprised of questionnaires, the NEO-FFI scales to determine the personality of the owners, and behavioral scoring to determine the correlation between the personality, age, and sex of both the cat and owner and the durations and complexity of their interactions. The observations (four for each couple) took place in their home situation, and were recorded on video for accurate scoring with The Observer XT. (The elaborate ethogram is published in their article.) Data from the events was analyzed in Theme, enabling the researchers to detect hidden temporal patterns (T-patterns) in behaviors to shed light on the complexity of the interaction between the couples. A glimpse into their results: The higher the owner scored on 'neuroticism', the fewer T-patterns occurred per minute. If the owner scored higher on 'extraversion', a higher number of non-overlapping patterns per minute were found. A more active cat resulted in fewer patterns per minute, but higher event type complexity. Event type complexity was lower in older cats. FREE TRIAL Try The Observer XT yourself! Request a free trial and see for yourself how easy behavioral research can be! - Work faster - Reduce costs - Get better data Free Trial References Wedl, M.; Bauer, B.; Gracey, D.; Grabmayer, C.; Spielauer, E.; Day, J.; Kotrschal, K. (2011). Factors influencing the temporal patterns of dyadic behaviours and interactions between domestic cats and their owners. Behavioural Processes, 86, 58-67. --- # Knowledge Base ## An overview of which software version is supported by which operating system URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/an-overview-of-which-software-version-is-supported-by-which-operating-system Chapter: All Noldus Products The Observer - Observer 3–5: Windows 2000, XP Pro (SP3) - Observer XT 6: Windows XP Pro (SP3) - Observer XT 7–9: Windows XP Pro (SP3), Vista 32-bit - Observer XT 10.0–10.1: Windows XP Pro (SP3), Windows 7 32-bit (SP1) - Observer XT 10.5: Windows XP Pro (SP3), Windows 7 32/64-bit (SP1) - Observer XT 11: Windows 7 32/64-bit (SP1) - Observer XT 11.5: Windows 7 32/64-bit (SP1), Windows 8 64-bit - Observer XT 12: Windows 7 64-bit (SP1), Windows 8 64-bit - Observer XT 12.5: Windows 7 64-bit (SP1), Windows 8.1 64-bit - Observer XT 13–14: Windows 7 64-bit (SP1), Windows 10 - Observer XT 14.1–16: Windows 10 EthoVision - EthoVision 2–3: Windows 2000, XP Pro 32-bit (SP3) - EthoVision XT 4: Windows XP Pro 32-bit (SP3) - EthoVision XT 5–7.0: Windows XP Pro 32-bit (SP3), Vista 32-bit (SP1) - EthoVision XT 7.1–8: Windows XP Pro 32-bit (SP3), Windows 7 32-bit (SP1) - EthoVision XT 9: Windows 7 32/64-bit (SP1), Windows 8 64-bit - EthoVision XT 10–11: Windows 7 64-bit (SP1), Windows 8 64-bit - EthoVision XT 11.5: Windows 7 64-bit Pro (SP1), Windows 8.1 64-bit Pro - EthoVision XT 12–14: Windows 7 64-bit (SP1), Windows 10 Pro - EthoVision XT 15: Windows 10 Pro (tested version 19H1) - EthoVision XT 16: Windows 10 Pro (tested version 20H2) - EthoVision XT 17.0: Windows 10 Pro (20H2), Windows 11 Pro (21H2) - EthoVision XT 17.5: Windows 10 Pro (20H2), Windows 11 Pro (21H2) CatWalk - CatWalk 7: Windows XP 32-bit (SP3) - CatWalk XT 8: Windows XP 32-bit (SP3), Vista 32-bit (SP1) - CatWalk XT 9: Windows XP 32-bit (SP3) - CatWalk XT 9.1: Windows XP 32-bit (SP3), Windows 7 32/64-bit (SP1) - CatWalk XT 10–10.1: Windows 7 32/64-bit (SP1) - CatWalk XT 10.6: Windows 7 64-bit (SP1), Windows 8.1 64-bit, Windows 10 - CatWalk XT 10.7: Windows 10 Pro (22H2), Windows 11 Pro (23H2) DanioScope - DanioScope 1.0–1.2: Windows 7 64-bit (SP1), Windows 8 64-bit FaceReader - FaceReader 1–2: Windows XP 32-bit (SP3) - FaceReader 3: Windows XP 32-bit (SP3), Vista 32-bit (SP1) - FaceReader 4: Windows XP 32-bit (SP3), Windows 7 32/64-bit (SP1) - FaceReader 5: Windows 7 32/64-bit (SP1) - FaceReader 5.1: Windows 7 64-bit (SP1), Windows 8 64-bit - FaceReader 6: Windows 7 64-bit (SP1), Windows 8.1 64-bit - FaceReader 7–9: Windows 7 64-bit (SP1), Windows 10 Media Recorder - Media Recorder 1: Windows XP 32-bit (SP3), Windows 7 32-bit (SP1) - Media Recorder 2: Windows 7 32/64-bit (SP1) - Media Recorder 2.5–2.6: Windows 7 64-bit (SP1) - Media Recorder 3: Windows 7 64-bit (SP1), Windows 8.1 64-bit - Media Recorder 4: Windows 7 64-bit (SP1), Windows 10 - Media Recorder 5–6: Windows 10 UltraVox - UltraVox 2: Windows 2000, XP 32-bit (SP3) - UltraVox 3: Windows 7 64-bit (SP3) - UltraVox 3.1: Windows 7 64-bit (SP3), Windows 8.1 64-bit, Windows 10 - UltraVox 3.2: Windows 7 64-bit (SP3), Windows 10 Viso - Viso 1–3: Windows 8.1 64-bit - Viso 4–10: Windows 10 --- ## Check network settings for a Basler camera URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/check-network-settings-for-a-basler-camera Chapter: All Noldus Products Basler GigE Camera Configuration Guide Basler GigE cameras connect to a computer using a network cable and require proper IP configuration. If a connected camera is not detected, verify the following settings. For additional troubleshooting, see: Basler camera is not detected by EthoVision. 1. Camera Settings Open Pylon IP Configurator (Start Menu > Pylon IP Configurator). If a camera appears as not reachable, its IP address likely conflicts with the network port settings. Use the following static IP configurations for your cameras: - Camera 1: 192.168.200.1 / Subnet Mask: 255.255.255.0 - Camera 2: 192.168.201.1 / Subnet Mask: 255.255.255.0 - Camera 3: 192.168.202.1 / Subnet Mask: 255.255.255.0 - Camera 4: 192.168.203.1 / Subnet Mask: 255.255.255.0 If needed, click the camera in the list, adjust the IP and subnet values, and click Save. 2. Network Adapter Settings If the camera is still unreachable, assign a matching static IP to the network adapter it's connected to: - Open Control Panel > Network and Internet > View network status and tasks. - Click Change adapter settings (left sidebar). - Right-click the relevant adapter (e.g., “Local Area Connection” or “Noldus Camera Network”) and select Properties. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Choose Use the following IP address and enter the corresponding value: - Port for Camera 1: 192.168.200.101 / Subnet Mask: 255.255.255.0 - Port for Camera 2: 192.168.201.101 / Subnet Mask: 255.255.255.0 - Port for Camera 3: 192.168.202.101 / Subnet Mask: 255.255.255.0 - Port for Camera 4: 192.168.203.101 / Subnet Mask: 255.255.255.0 Note: Ensure that the third number group (e.g., 200, 201) matches between the camera and adapter. The camera uses .1 while the adapter uses .101. The Subnet Mask should be 255.255.255.0. Click OK and Close to apply the settings. Restart your computer if necessary. --- ## Connecting a Basler camera URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/connecting-a-basler-camera Chapter: All Noldus Products Noldus primarily uses Basler GigE cameras, which connect to the computer with a network cable. "GigE" is short for Gigabit-Ethernet. Some Basler cameras use USB3 connections instead. If you've connected your camera but it is not detected, also see Basler camera is not detected by EthoVision. USB3 Cameras If you are using a USB camera, connect the supplied cable to the camera and plug it into a USB 3.0 (not 2.0) port on the PC. USB 3.0 ports can usually be identified as blue in color and/or indicated by an “SS” (for "SuperSpeed"). Plug the camera directly into the computer; if it is plugged into a hub, it must share bandwidth with other devices connected to the hub, and performance may suffer. GigE Cameras If using a GigE camera (which connects with a network cable), you may have either a single network cable directly connecting the camera to the computer, or a cable going from the camera to a power injector (aka midspan) and a second cable from the power injector to the computer. In either case, only a single cable is connected to the camera, providing both connectivity and power. 1. On desktop computers supplied by Noldus, there will typically be two or more network ports. One port is up near the USB ports and is normally not used for the camera (it may be used to connect to your local network). A dedicated network card will be located lower down, and is normally labeled. There may be 1, 2, or 4 ports on the card. Use these lower ports. 4-port cards (and newer 2-port cards) supply power so a power injector is not required. If your card has more than one port, note that the camera must be plugged into the correct port. See note below. 2. If you have a power injector, verify that the short cable is connected from the “Data In” port on the power injector to the computer, while the long cable is connected from the “Data & Power Out” port on the power injector to the back of the camera. The purpose of the power injector is to supply power to the camera, so the camera must be plugged into the port that supplies the power. 3. The power injector must also be plugged into a functional power outlet. With everything connected correctly, the light on the power injector should be solid green. (A yellow light indicates power but no network activity, e.g., the computer is turned off. A blinking green light indicates a problem.) NOTE: If you have more than one GigE camera on the PC, make sure they are plugged into the correct network card/port. For example, a camera with an IP address of 192.168.200.1 needs to plug into the network port with an IP address of 192.168.200.101, a camera with an IP address of 192.168.201.1 needs to plug into the network port with an IP address of 192.168.201.101, etc. The first three numbers must match (e.g., 192.168.200) while the last number will differ (Noldus normally uses 1 for the camera and 101 for the network port). --- ## Deactivating a Noldus license on another computer URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/deactivating-a-noldus-license-on-another-computer Chapter: All Noldus Products Want to deactivate a Noldus license on your computer? Here's how to do this in the software on your PC. Sometimes a software license remains active on a computer that you can no longer access or use, for example: - The computer is broken or replaced - A student or employee left without deactivating the software - The software was uninstalled without first deactivating the license When this happens, your license may show that it has reached its maximum number of activations, even though some of those installations are no longer in use. To make this easier, you can manage and deactivate your own licenses through the QLM (Quick License Manager) Customer Portal, without needing to contact Noldus support. What is an SBLK license? An SBLK license (Single Block License Key) is a type of software license that allows activation on a limited number of computers. For example, if your license allows three activations, you can install and activate the software on up to three computers. If you reach this limit, you’ll need to deactivate one of the existing installations before activating it on a new computer. What is the QLM portal? The QLM Portal (Quick License Manager Customer Portal) is an online self-service website where you can view and manage your software activations. Using this portal, you can: - Check which computers your license is activated on - Deactivate licenses that are no longer needed or associated with unavailable computers - Free up your license so it can be used again on a new system Access the QLM Customer Portal: https://qlmlicenses.noldus.com/qlmcustomersite/default.aspx How to deactivate a license using the QLM portal - Visit the QLM Customer Portal Go to: https://qlmlicenses.noldus.com/qlmcustomersite/default.aspx - Retrieve your license information - Click Get License Information. - Enter your Activation Key. - You’ll see a list of all computers where the license is currently active. - Identify the computer to deactivate - Review the list of Computer Names. - Note the Computer ID of the computer you want to deactivate. - Deactivate the license - Select Deactivate License from the menu. - Enter your Activation Key and the Computer ID. - Click the Deactivate button. - Reactivate on a new system (optional) Once the license has been deactivated, it’s immediately available for activation on a new computer using the same activation key. Tip for future use Save the QLM Portal link for future reference. Noldus plans to include it in future software welcome letters so all customers can easily manage their licenses. --- ## How do I get access to MyNoldus? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/how-do-i-get-access-to-mynoldus Chapter: All Noldus Products Table of contents - What is MyNoldus? - Who can access MyNoldus? - How to invite users - Assigning a team administrator - Requesting an invitation - Need help? What is MyNoldus? MyNoldus is your personalized customer portal, designed to support your work with Noldus software. It brings together everything you need in one place: - Software downloads and manuals - License and NoldusCare information - Support ticket submission - Exclusive learning content (including Noldus Academy, if your organization has NoldusCare) Whether you're onboarding or already an experienced user, MyNoldus helps you work more efficiently and independently. Who can access MyNoldus? Access to MyNoldus is available to Noldus customers — including: - License owners, who manage the software licenses - Invited users, who are added to a license owner’s team If you are known to Noldus (e.g., your organization uses Noldus software and your email address is registered), you can already log in to MyNoldus, but until you are invited by the license owner, you won’t be able to view downloads, licenses, or submit support tickets. To unlock these features, you’ll need to be added to your team by your license owner or team manager. How to get full access To gain full access to your organization's downloads, licenses, and support, simply ask your license owner or designated team manager to invite you. Once invited, you'll receive an email confirmation, and when you accept the invite the full portal functionality will be unlocked for your account.  How to invite users  As a license owner, you can invite colleagues to access the portal and assign permissions. Here’s how: - Log in to MyNoldus - Go to Licenses in the top menu - Select Share your license. - Select which licenses the invitee should have access to - Choose an existing email from the dropdown or add a new email address - Enter the first and last name of the invitee - Set the validity period for the sharing - Check the "Make administrator box if you want the invitee to be able to invite others too. - Click Send Invite  The invited user will receive an email to activate their access. Assigning a team administrator As a license owner, you can delegate access management by assigning a team administrator. Team administrators have similar rights to the license owner: they can invite new users, assign license access, and help manage the team — making collaboration and onboarding easier. You can assign someone to be a team administrator when you send the invite, or you can change their role later in the User overview screen. Requesting an invitation (for users) Not sure how to ask access to the downloads and licenses? Here's a message you can copy and send to your license owner or team manager: ✉️ Sample email text Subject: Request for access to MyNoldus Dear [License Owner's Name], I hope you're well. To support my work with Noldus software, I would like to request access to our license information and software downloads via the MyNoldus portal. Could you kindly invite me as a user under our license so I can access the tools and resources needed for my research? Thank you very much in advance for your help. Best regards, [Your Name] Need help? Not sure who your license owner is or having trouble logging in? Ask Noldi; our online chatbot can help troubleshoot or loop in the support team if needed. Related articles - Why don't I see my licenses and downloads in MyNoldus? - MyNoldus registration and password email troubleshooting --- ## How do I upgrade my license? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/how-do-i-upgrade-my-license Chapter: All Noldus Products This article will help you if you want to: - update your software when a new version is released (included with NoldusCare), - upgrade your software to another package, - add a new module to your existing software (legacy scenario). When you get access to new software you have to take some steps to start working with it. The good news is that in most cases, this is a quick and largely automatic process. This article walks you through it. Before you start, two things to know: - Upgrading your license is not the same as updating the software itself. To start using a new version, you'll need to download and install the software from MyNoldus. This is further explained below. - The steps depend on which kind of license you have. Noldus offers two: - Software-based license keys (SBLK): activation codes typed into the software. This is what most customers use today. - Hardware license keys (dongles): USB devices that plug into the computer when the software is in use. Pick the section below that matches your license. Jump to: - Upgrading a software-based license (SBLK) - Floating license (with internet) - Fixed license, online (with internet) - Fixed license, offline - Upgrading a hardware license (dongle) - Where to find your upgrade code - Step-by-step: upgrading to a newer software version - Minor updates vs. full version upgrades - Adding a new module to your license - Still need help? Ask Noldi Upgrading a software-based license (SBLK) Software-based licenses come in two flavors: floating or fixed. A fixed license can be used with or without an internet connection: - Floating licenses: shared across multiple machines, requires an internet connection. - Fixed (computer-locked) licenses, online activation: activated on one specific computer, requires an internet connection. - Fixed (computer-locked) licenses, offline activation: activated on one specific computer, doesn't require an internet connection. If you have active NoldusCare, newer software versions are unlocked for your license automatically. In most cases, all you need to do is download the software from MyNoldus and install the new version and launch it. Floating license - Go to Downloads in MyNoldus and download and install the latest version of your software: - Launch the software. - Your license upgrades on first launch. That's it, no codes to enter. Fixed license, online  The process is the same as for floating licenses: - Go to MyNoldus and download and install the latest version: - Launch the software. - The license picks up the upgrade automatically. Fixed license, offline If your computer doesn't have an internet connection, there's an extra step to refresh the license: - Go to MyNoldus and download and install the latest version: - In the software, go to Help > Deactivate License and choose offline activation. - Follow the QR code procedure with your smartphone. - Reactivate the license in offline mode. Once reactivated, your upgraded license is good to go. Upgrading a hardware license (dongle) If you use a USB dongle, your dongle itself needs to be upgraded with a code so it unlocks the new version. Before you start, make sure the dongle is plugged into a free USB port. If everything's installed correctly, a small red LED inside the dongle will light up. Where to find your upgrade code Your upgrade code is available under Licenses in MyNoldus. Find the card of the license you want to upgrade and the Upgrade key / code is displayed there. Step-by-step: upgrading to a newer software version - Go to MyNoldus and download and install the latest version first. Ideally, uninstall the previous version before you do this. - Launch the new version with the dongle plugged in. - Enter the upgrade code when prompted. Make sure you're entering it in the new version, not the old one. That's the full upgrade. You don't need to edit the Name or License number fields, leave those exactly as they are. If only one key is provided, it's fine to leave the second field blank. What if my upgrade key isn't recognized? You can confirm the upgrade worked by going to Help > About and clicking License Info (depending on the software, this may also be visible on the same screen). Minor updates vs. full version upgrades You only need an upgrade code for full version upgrades — for example, moving from version 17 to version 18. Minor updates within the same major version (such as 17.0 to 17.1) don't require a code. Just install the update and carry on using your dongle as usual. Adding a new module to your license Adding a standalone module to an existing license is less common these days, but if you've purchased one, here's how it works: - Software-based licenses (floating or fixed, online): No action needed. The module is added to your license automatically the next time you launch the software. - Software-based licenses, offline: Deactivate the license via Help > Deactivate License, follow the offline QR code procedure, then reactivate in offline mode. - Dongle licenses: With the dongle plugged in, open the software and go to Help > Upgrade (or Help > License > Upgrade, depending on the product). Enter the code you received. Leave the Name and License number fields untouched, and leave the second field blank if only one key was provided. The window closes when the code is accepted. Still need help? Ask Noldi If anything goes wrong, your upgrade code isn't where you expect it, or you're not sure which license type you have, ask Noldi, our chatbot in MyNoldus. Noldi can help you find it or loop in our support team if something needs a closer look. --- ## How do software-based and hardware-based licenses compare? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/how-do-software-based-and-hardware-based-licenses-compare Chapter: All Noldus Products Software-Based Licensing Traditionally, Noldus has used hardware-based licenses for all of its software, requiring a hardware license key (or “dongle”) to be plugged in while using the software. Starting with The Observer XT 16, EthoVision XT 17, and FaceReader 9, we now offer a software-based license as an alternative. A software-based license does not require a dongle. Fixed vs. Floating Licenses There are two ways a software-based license can be used. You can choose between them during activation: - Fixed License: Activated on a single computer. After activation, the software can be used without a license key or internet connection. Use is limited to that one computer unless the license is deactivated and reactivated elsewhere. Internet is required only for activation/deactivation. (EthoVision XT 17 also supports offline activation via QR code and smartphone.) - Floating License: Allows activation on multiple computers, but only one can use the software at a time (unless multiple seats are purchased). An internet connection is required during use. Once a user closes the software, it becomes available to others. You can switch between fixed and floating types at any time by deactivating and then reactivating the license with the desired mode. Multiple Seats Some licenses allow multiple concurrent users—these are referred to as seats. The seat count is set at the time of purchase (default is one). For example: - If your license has 3 seats, and you activate one computer with a fixed license, then 2 seats remain available for floating use. - Floating licenses consume a seat only when the software is open; fixed licenses always occupy a seat. Notes for EthoVision XT For EthoVision XT specifically: - A license is only needed to acquire tracks (from camera or video) or to create new experiments that use optional modules like trial control or multiple arenas. - Data analysis only (e.g., post-acquisition review of trials) does not require a license. For The Observer and FaceReader, a license is required at all times to use the software. --- ## How to activate your Noldus license: Watch the video URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/how-to-activate-your-noldus-license-watch-the-video Chapter: All Noldus Products Select your product and jump straight to the right video and instructions. EthoVision XT FaceReader The Observer XT EthoVision Follow the steps below to activate your EthoVision license using your software-based license key (SBLK).  Before you start: - Make sure EthoVision is installed on your computer. You can download the latest version from MyNoldus > Downloads. - You'll need your license key, which you can find in your welcome letter or MyNoldus > Licenses. Step-by-step - Open EthoVision. The Noldus license activation dialog opens automatically on first launch. - Select "Use the software activation key" and click Continue. - Choose your license type: - Floating license: shared across multiple computers, requires an internet connection each time you use the software. - Computer-locked license – Online activation: locked/fixed to one computer, only needs internet for the initial activation. - Computer-locked license – Offline activation: locked/fixed to one computer, no internet required. Use your phone to complete activation via QR code. - Enter your license key. You'll find it in your welcome email, or under MyNoldus > Licenses. - Click Continue. EthoVision XT connects to the license server and activates your license. - Click Close when you see "License successfully activated." EthoVision is now ready to use. Need help? Click on the chat icon on the right and chat with Noldi. ↑ Back to top FaceReader Follow the steps below to activate your FaceReader license using your software-based license key (SBLK).  Before you start: - Make sure FaceReader is installed on your computer. You can download the latest version from MyNoldus > Downloads. - You'll need your license key, which you can find in your welcome letter or MyNoldus > Licenses. Step-by-step - Open FaceReader. The Noldus license activation dialog opens automatically on first launch. - Select "Use the software activation key" and click Continue. - Choose your license type: - Floating license — shared across multiple computers, requires an internet connection each time you use the software. - Computer-locked license – Online activation — locked/fixed to one computer, only needs internet for the initial activation. - Computer-locked license – Offline activation — lockedfixed to one computer, no internet required. Use your phone to complete activation via QR code. - Enter your license key. You'll find it in your welcome email, or under MyNoldus > Licenses. - Click Continue. FaceReader connects to the license server and activates your license. - Click Close when you see "License successfully activated." FaceReader is now ready to use. Need help? Click on the chat icon on the right and chat with Noldi. ↑ Back to top The Observer Follow the steps below to activate your Observer license using your software-based license key (SBLK).  Before you start: - Make sure The Observer is installed on your computer. You can download the latest version from MyNoldus > Downloads. - You'll need your license key, which you can find in your welcome letter or MyNoldus > Licenses. Step-by-step - Open The Observer. The Noldus license activation dialog opens automatically on first launch. - Select "Activate software license key" and click Ok. - Choose your license type: - Floating license: shared across multiple computers, requires an internet connection each time you use the software. - Computer-locked license – Online activation: locked/fixed to one computer, only needs internet for the initial activation. - Computer-locked license – Offline activation: locked/fixed to one computer, no internet required. Use your phone to complete activation via QR code. - Enter your license key. You'll find it in your welcome email, or under MyNoldus > Licenses. - Click Continue. The Observer connects to the license server and activates your license. - Click Close when you see "License successfully activated." The Observer is now ready to use. Need help? Click on the chat icon on the right and chat with Noldi. ↑ Back to top --- ## How to deactivate your Noldus license: Watch the video URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/how-to-deactivate-your-noldus-license-watch-the-video Chapter: All Noldus Products You may need to deactivate your license before moving the software to a new computer, reinstalling your OS, or replacing your machine. Select your product to jump to the right instructions. EthoVision FaceReader The Observer Can't access the computer on which you need to deactivate the license? Here's how to deactivate from another PC. EthoVision The steps depend on which license type you have. If you're not sure, check under Help > About in EthoVision. Floating license No deactivation needed. Your seat is released automatically when you close EthoVision XT. You can open the software on any other computer straight away. Computer-locked license — online - Open EthoVision on the computer where the license is currently active. - Go to Help > Deactivate License. - Confirm the deactivation. EthoVision connects to the license server and releases the license. - Your license is now free to activate on another computer.  Computer-locked license — offline - Open EthoVision on the computer where the license is currently active. - Go to Help > Deactivate License and select offline deactivation. - A QR code appears on screen. Scan it with your smartphone and follow the steps to complete the deactivation. - Your license is now free to activate on another computer. Need help? Chat with your 24/7 assistant Noldi! ↑ Back to top FaceReader The steps depend on which license type you have. If you're not sure, check under Help > About in FaceReader. Floating license No deactivation needed. Your seat is released automatically when you close FaceReader. You can open the software on any other computer straight away. Computer-locked license — online - Open FaceReader on the computer where the license is currently active. - Go to Help > Deactivate License. - Confirm the deactivation. FaceReader connects to the license server and releases the license. - Your license is now free to activate on another computer.  Computer-locked license — offline - Open FaceReader on the computer where the license is currently active. - Go to Help > Deactivate License and select offline deactivation. - A QR code appears on screen. Scan it with your smartphone and follow the steps to complete the deactivation. - Your license is now free to activate on another computer. Need help? Chat with your 24/7 assistant Noldi! ↑ Back to top The Observer The steps depend on which license type you have. If you're not sure, check under Help > About in The Observer. Floating license No deactivation needed. Your seat is released automatically when you close The Observer. You can open the software on any other computer straight away. Computer-locked license — online - Open The Observer on the computer where the license is currently active. - Go to Help > Deactivate License. - Confirm the deactivation. The Observer connects to the license server and releases the license. - Your license is now free to activate on another computer.  Computer-locked license — offline - Open The Observer on the computer where the license is currently active. - Go to Help > Deactivate License and select offline deactivation. - A QR code appears on screen. Scan it with your smartphone and follow the steps to complete the deactivation. - Your license is now free to activate on another computer. Need help? Chat with your 24/7 assistant Noldi! ↑ Back to top What if you can't access the computer? Sometimes a software license remains active on a computer that you can no longer access or use, for example: - The computer is broken or replaced - A student or employee left without deactivating the software - The software was uninstalled without first deactivating the license When this happens, please read this article for help.   --- ## License sharing vs. license activation: What's the difference? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/license-sharing-vs-license-activation-whats-the-difference Chapter: All Noldus Products If you've ever wondered why being able to see a license in MyNoldus doesn't mean you can run the software, or why activating the software doesn't automatically give a colleague access to MyNoldus, you're not alone. These are two separate processes that happen to both involve the word "license." This article explains the difference, so you know exactly where to go for what you need. Two different systems, two different jobs   Sharing license info (MyNoldus) Using your license (activation) What it is Giving colleagues access to license details and software downloads in your MyNoldus account Entering your license key in the software so it unlocks on your computer Where it happens my.noldus.com Inside the software itself, on your computer What it affects Who can log in and see the license, key, and downloads Whether the software runs and which seat is checked out Who's involved The license owner, inviting colleagues by email Any user with the license key, on their own machine In short: MyNoldus is about visibility (who can see and manage the license). Activation is about usage (who is actually running the software with that license right now). One doesn't require the other. Sharing license info via MyNoldus Every Noldus license belongs to one MyNoldus account: the license owner. The owner can invite colleagues (PhD students, lab members, IT admins) as invited users. Once invited, they get their own MyNoldus account with access to the same license details and downloads. This is purely administrative. Inviting someone to MyNoldus: - lets them see the license key, expiry date, and included modules, - lets them download the software themselves, and - does not install, activate, or run anything on their computer. Read more in Why don't I see my licenses or downloads in MyNoldus? Using your license: Activation on your computer Activation is what happens when someone installs the Noldus software and enters the license key. At that point, the software contacts our license server (sometimes referred to as the QLM server) to check out a seat. Depending on the license type, this works a little differently: - Floating license: checks out a seat from a shared pool each time the software is launched, and releases it again when closed. Requires an internet connection. - Fixed (computer-locked) license: ties the license to one specific computer after the first activation. Can be used offline afterward. Activation only needs the license key, not a MyNoldus account, and not an invite. Anyone with the key can activate it on a computer, as long as a seat is available. Read more in Activating your Noldus software. Why the distinction matters Because these are independent processes, you can end up in situations like: - You have MyNoldus access but can't run the software. You can see the license and download the installer, but you still need to activate it on your own computer using the key, and a seat needs to be free. - You're using the software but have no MyNoldus access. A colleague can hand you a license key to activate the software directly, without ever inviting you to MyNoldus. You just won't be able to see the license details, downloads, or documentation yourself. - Someone left the lab, but the software still runs fine. Removing someone's MyNoldus access doesn't deactivate any software they've already activated. To free up a seat, it needs to be deactivated separately. Neither process automatically triggers the other. If you need both (visibility in MyNoldus and a working activation) they need to be set up separately. Still stuck? Ask Noldi If you're not sure whether you need to be invited to MyNoldus, need an activation key, or both, ask Noldi, our chatbot in MyNoldus. Noldi can check your account, point you to your license owner, or help with an activation issue. You don't need to figure this out alone, we'd much rather hear from you than have you stuck between the two. --- ## Making screen captures in Windows URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/making-screen-captures-in-windows Chapter: All Noldus Products Capturing Images from the Screen in Windows Windows provides several ways to capture images from your screen, including keyboard shortcuts and built-in tools. Additionally, Noldus software includes features for saving settings and graph images directly. Print Screen Key (All Windows Versions) You can capture your screen using the Print Screen key (usually labeled PrtScr): - Full screen: Press PrtScr to copy the entire screen to the clipboard. - Active window only: Press Alt + PrtScr to copy just the active window. Once copied to the clipboard, paste the image into another application such as Microsoft Word, PowerPoint, or Paint (Ctrl + V). In Paint, you can save the image as a file. Snipping Tool (Windows 7, 8, 10) The Snipping Tool allows you to capture specific screen regions: - Open the Start Menu and search for “Snipping Tool.” - Click New and use the cursor to select the area to capture. - Annotate or save the image using the built-in options. In Windows 10, you may also see Snip & Sketch, which is replacing the original Snipping Tool. Snip & Sketch (Windows 10 and newer) Snip & Sketch provides quick screen captures with annotation support: - Use shortcut Windows + Shift + S to immediately start a snip. - Select an area of the screen using your mouse. - A notification will appear — click it to open the snip in Snip & Sketch. - You can annotate or save the image from there. Alternatively, launch Snip & Sketch from the Start Menu by typing "snip". Capturing Images in Noldus Software Noldus applications often include built-in screenshot tools: - Graphs: Right-click on a graph to copy or save it. - EthoVision XT: Use the camera icon in Arena Settings, Trial Control Settings, or Data Profiles to save a screenshot of your configuration. - The Observer XT: Similar functionality is available in Data Profile and Visualization views. Refer to the documentation of your specific Noldus software for additional image capture options. --- ## My upgrade code is not recognized URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/my-upgrade-code-is-not-recognized Chapter: All Noldus Products Upgrade codes for Noldus Hardware License Keys (Dongles) Upgrade codes are issued when updating Noldus software to a new version or when adding additional modules to an existing hardware license key (dongle). They may also be used to extend the expiration date of loan or rental licenses. Purchased software licenses do not expire. If your upgrade code is not being recognized, check the following guidelines. You may receive a warning that you have a limited number of tries left (this count resets daily). If you do not see this warning, the code was successfully accepted. 1. Software version must match upgrade code Upgrade codes are version-specific. For example: - An upgrade code for EthoVision XT 16 must be entered in EthoVision XT 16. - A code for The Observer XT 14.2 will only work in 14.2, not in 14.0 or 15.0. After entering the upgrade code, the hardware key will also work with older versions, but the code must first be applied in the correct version. If the required software version is not listed on your MyNoldus downloads page, contact Noldus Support. 2. Enter the code correctly - Whenever possible, copy and paste the code to avoid typing errors. - Upgrade codes may include the numbers 0 and 1, but will never include the letters O, I, or L. - Codes are either a single 20-character string or split as 20 characters + 4 characters. Enter the entire code. 3. Check the license number The upgrade window shows your current license number. For version upgrades, expect the license number to change: - EV015-00000-AAAAAAA indicates EthoVision XT 15 - EV016-00000-BBBBBBB would be the upgraded XT 16 version Only the middle numeric segment (e.g., 00000) must match between the existing and new license. If this doesn’t match, the code is for a different license. Contact support if you’re unsure. 4. Using additional computers Once a code is successfully entered, the dongle stores the updated license. You can move it to another computer without re-entering the upgrade code. Read more: How do I upgrade my license --- ## MyNoldus registration and password emails: Troubleshooting URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/mynoldus-registration-and-password-emails-troubleshooting Chapter: All Noldus Products Waiting on a MyNoldus email that just won't arrive is one of those small things that can completely block your day, whether you're trying to register a new account, confirm your address, or reset a forgotten password. The fix is almost always quick once you know where to look. This page walks through the most common reasons our emails don't reach you and what to do about each one. Jump to: - First, check spam, quarantine, and filters - Make sure you're using the right email address - What to do if no email arrives - What if you're not the license owner? - Still no luck? First, check spam, quarantine, and filters Before anything else, it's worth doing a thorough sweep of the places automated emails tend to land: - Spam or Junk folder. This is the most common culprit by far. Search for "Noldus" or "MyNoldus" to spot it quickly. - Promotions, updates, or other tabbed inboxes. If you use Gmail or a similar provider, the email may have been sorted away from your main view. - Institutional quarantine. Universities, hospitals, and research institutes often run their own spam filters on top of your inbox. Sometimes our emails are held there before they ever reach you, your IT department or a quarantine notification email can release them. - Inbox rules and forwarding. If you've ever set up a rule that auto-archives or forwards messages, double-check it isn't catching ours. If you do find the email in spam, click "Not spam" or mark Noldus as a trusted sender so the next one comes straight to your inbox. Make sure you're using the right email address This is the second thing to check, and it trips up more people than you'd expect. Our emails are sent to the exact address you (or your license owner) entered. If there's a mismatch, you'll be watching the wrong inbox. A few specific things to verify: - Are you registering with the address your lab uses on the license? If your PI invited you using your @university.edu address but you're trying to register with a personal Gmail account, the system won't connect the two. - Did you type it correctly? Typos in long institutional addresses are easy to miss. If you can, ask whoever sent you the invite to confirm the exact address on file. - Do you have multiple work addresses? Researchers often have a primary address plus aliases (e.g. firstname.lastname@ vs. f.lastname@). Our system treats these as different accounts. - Have you recently changed institutions? An old address may no longer forward, or may be inactive entirely. If you suspect the address on file is wrong or out of date, that's something we can update. See the support section below. What to do if no email arrives You've checked spam, you're confident about the address, and there's still nothing. Here's what to try, in order: - Wait a few minutes. Most emails arrive within seconds, but during busy periods or institutional filtering, a short delay (up to about 10–15 minutes) is normal. - Request the email again. From the registration or password reset page, trigger a fresh send. Sometimes the first one genuinely doesn't go through. - Try a different browser or incognito window. Cached form data or autofill occasionally sends a slightly different address than the one you see on screen. - Ask your IT department to check the mail logs. If our emails are being blocked or quarantined at the institutional level, only IT can release them or whitelist our domain. You can let them know our emails come from Noldus. If none of these work, don't keep retrying endlessly, go straight to the fallback path below. What if you're not the license owner? If you're a researcher, student, or assistant joining a lab's existing license, you'll only receive a registration or invitation email after the license owner has added your address to their license in MyNoldus. So if no email has arrived and you haven't yet been invited: - Check with whoever in your lab manages the Noldus software (often a PI, lab manager, or senior researcher). - Confirm the email address they used to invite you — and make sure it matches the address you're checking. - Ask them to resend the invitation if it's been a while or if you can't find the original. If the license owner has retired, changed email, or never set up a MyNoldus account themselves, you won't be able to get an invite from them directly. In that case, head straight to the support fallback below, we can help untangle the ownership and get you access. Still no luck? If the above doesn't help, talk to Noldi, our chatbot in MyNoldus. Noldi can help you troubleshoot or loop in our support team if something needs to be updated on our side (a wrong address, an inactive account, a license that needs transferring). Even if you can't get into MyNoldus yet, Noldi is available from our website, so you don't need an account to start a conversation. We'd rather hear from you sooner than have you stuck, most email issues are sorted in a single back-and-forth. Related articles - How do I get acces to MyNoldus - Why don't I see my licenses and downloads in MyNoldus? --- ## No valid hardware key detected after installing Noldus software URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/no-valid-hardware-key-detected-after-installing-noldus-software Chapter: All Noldus Products License Requirements for Noldus Software Most Noldus software requires a valid license to operate: - Fully Required: e.g., The Observer XT - Required for Full Functionality: e.g., acquisition in EthoVision Licenses come in two forms: - Hardware license key (dongle): A USB device that stores license data (not files). - Software activation code: Introduced in newer versions, it replaces the need for a dongle. Software Versions Using Software-Based Licenses The following software versions support software-based activation codes (no dongle required): - The Observer XT 16 - EthoVision XT 17 - Media Recorder 6 - FaceReader 9 If you are using an earlier version or were issued a hardware license key, the dongle must be connected to use the software. Multiple Noldus Licenses If you own multiple Noldus software licenses (e.g., FaceReader, Media Recorder, The Observer), ensure the correct dongle is inserted for the software you wish to use. Each license key is software-specific and not interchangeable. Tip: You can connect multiple keys simultaneously to the same PC without conflict. Troubleshooting a Missing Hardware License Key Problem: "No hardware key detected" This usually indicates that the dongle driver did not install correctly. Common signs include: - The red LED light on the dongle blinks briefly, then turns off. - The software displays a license error message. Cause - Driver installation failed. - Driver is outdated (common on Windows 10/11). Solution Install or update the license key driver using the following file: Download HASP Driver 8.13 - Download and extract the file if zipped. - Right-click the installer and choose "Run as administrator". - Follow the prompts to complete the installation. Still Not Working? If the dongle is still not recognized after installing the driver, contact Noldus Technical Support for further assistance. --- ## Some elements of the software appear too small or cropped when using Windows 10 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/some-elements-of-the-software-appear-too-small-or-cropped-when-using-windows-10 Chapter: All Noldus Products Fixing Scaling Issues on High DPI Displays (Windows 10) If you are using a high DPI display, some interface elements in Noldus software may appear too small or become cropped and difficult to use. This issue can be resolved by changing the application's display scaling behavior in Windows. Steps to Adjust DPI Compatibility Settings - Right-click the shortcut icon of the application you want to adjust. - If the shortcut is pinned to the taskbar, right-click it once, then right-click the program name again. - Select Properties. - Go to the Compatibility tab. - Click Change high DPI settings near the bottom of the window. - Check the box for Override high DPI scaling behavior. - From the dropdown menu below, select System (Enhanced). - Click OK, then OK again to close the Properties window. - Launch the application and verify that the interface now appears correctly scaled. --- ## Understanding Axis camera LEDs URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/understanding-axis-camera-leds Chapter: All Noldus Products Understanding Camera LEDs When troubleshooting an Axis network camera, the camera LEDs can provide useful diagnostic information. Different models have different LED setups. This example uses the AXIS P1365, which has three LEDs: status, power, and network. Each LED can display different colors to indicate camera status. Status LED Steady green: Normal operation. Steady amber: Displayed during startup, reset to factory defaults, or restoring settings. Slowly flashing red: Indicates a failed firmware upgrade. Power LED - Steady green: Normal operation. - Flashing green/amber: Occurs during a firmware upgrade. Network LED - Steady green: Connected at 100Mb/s. Flashes with network activity. - Steady amber: Connected at 10Mb/s. Flashes with network activity. - Unlit: No network connection. --- ## What is Noldus Academy, and how do I get access? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/what-is-noldus-academy-and-how-do-i-get-access Chapter: All Noldus Products Noldus Academy is our online learning platform, built to help you get more out of the software you already use. Whether you're setting up EthoVision XT for the first time or want to sharpen your skills with The Observer XT, Academy walks you through it step by step, at your own pace. What is Noldus Academy? Noldus Academy brings together several kinds of training in one place: - Onboarding courses for EthoVision XT, FaceReader, and The Observer XT: structured, step-by-step training to get new users up and running. - Getting-started video series for CatWalk XT and NoldusHub. - 35+ webinars on best practices, new features, and developments in behavioral research. - Live, on-site training, available on request for teams that want in-person guidance. Courses are broken into lessons with short quizzes. You don't need to finish everything in one sitting: your progress is saved, so you can pick up where you left off. Complete all the quizzes in a course and you'll earn a certificate you can share on LinkedIn. You can retake a quiz as many times as you need to. One thing to know: Noldus Academy needs an internet connection. Offline access to courses isn't supported. How do you get access? You log in to Noldus Academy via MyNoldus, there's no separate account to create. - Go to the Noldus login page. - Enter the email address and password you use for MyNoldus. - Don't have a MyNoldus account yet? Register one, or ask your license owner to invite you, see How do I get access to MyNoldus? - Forgot your password? Use the Forgot my password link on the same page. Want to see what it's like before logging in? A few sample lessons, including the EthoVision XT, FaceReader, and The Observer XT onboarding courses, are open to everyone, no account or NoldusCare needed. You'll find them on the Noldus Academy trial lessons page. Conditions: an active NoldusCare contract Full access to the Noldus Academy course library is a NoldusCare benefit. If you've recently purchased Noldus software, Academy access is normally included automatically for the first year. After that, access depends on your NoldusCare contract staying active: - NoldusCare active: you, and anyone your license owner has invited to MyNoldus, can log in and work through the full catalog of courses and webinars. - NoldusCare expired: you'll lose access to the full catalog, though the trial lessons stay open to everyone. Renew your contract from MyNoldus (open your license and click Renew NoldusCare) to get access back. Not sure whether your NoldusCare contract is currently active? Check your license details in MyNoldus. Did you know that with NoldusCare you also get access to our live Q&As with our expert trainers? Common questions Do I need a separate password for Noldus Academy? No. Academy uses the same login as MyNoldus, one account for licenses, downloads, and training. Does everyone on our license get access, or just the license owner? Anyone your license owner has invited to MyNoldus can log in to Academy, as long as your organization's NoldusCare contract is active.  What happens to my progress if I lose access and then renew? Your progress is saved. Once your NoldusCare contract is active again, you'll pick up right where you left off. Can I try a course before committing to NoldusCare? Yes, the trial lessons let you sample onboarding content for EthoVision XT, FaceReader, and The Observer XT, no account needed. Can I request live, in-person training instead? Yes, on-site training is available on request. Get in touch with us for more info. --- ## Where do I find my Noldus license key and version number? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/where-do-i-find-my-noldus-license-key-and-version-number Chapter: All Noldus Products When you have a software based license, you need your license key to activate your Noldus software after installation. Or, perhaps you want to know which version of the software you are using. There are a few places to look: Option 1: Find it in MyNoldus This is the quickest route. If you're the license owner or have been added as an invited user, your key is waiting for you in MyNoldus. - Sign in at my.noldus.com. - Go to Licenses in the left-hand menu. Your licenses are displayed as cards in a row.  - Your license key (a.k.a. the activation key for your software license) is displayed on the card - Click on the magnifying glass to see the full key. Not seeing any licenses? You may not have been added to the license yet. See Why don't I see my licenses or downloads in MyNoldus? for next steps. Option 2: No access to MyNoldus? Find it in the software If the software is already installed and activated on your computer, you can retrieve your license information directly from the application. - Open your Noldus software. - Go to Help in the top menu and select About. - The full version number of your software is shown here. - To see your license details, click User Info or License Info (the button name varies by product and version). FaceReader: Your license number and registered user name are shown directly in the About window, no extra click needed. Understanding your license number How to read the number depends on your license type: - Software-based license (SBLK): The number is randomized and doesn't indicate version or modules. You'll need it to activate your license after installation. - Hardware key (dongle): The number contains a two-letter software identifier (e.g., EV for EthoVision XT), the version number (e.g., EV150 = EthoVision XT 15.0), a unique five-digit ID, and optional letters for any additional modules. Option 3: No access to the software or MyNoldus? Ask your license owner Every Noldus license is linked to one MyNoldus account — the license owner. This is usually the person who placed the original order: a PI, lab manager, or IT administrator. Ask your license owner to: - Sign in to my.noldus.com and look up the key under Licenses, or - Add you as an invited user so you can find it yourself going forward. Not sure who the license owner is? Check with your PI, lab manager, or whoever manages software purchases in your department. If the original owner has left your organisation and no one has access, contact our support team, we can help transfer the license to a current member of your lab. --- ## Why don't I see my licenses or downloads in MyNoldus? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/all-noldus-products/page/why-dont-i-see-my-licenses-or-downloads-in-mynoldus Chapter: All Noldus Products You've logged in, you know your lab uses Noldus software, and yet your MyNoldus license and download page looks empty. It's a frustrating place to land, especially when you just want to get on with your research. The good news: there's almost always a simple reason for it, and a clear next step. This article walks you through the most common causes and how to fix them. First, a quick mental model: license owner vs. invited user Every Noldus license belongs to one MyNoldus account, the license owner or registered user. This is usually the person listed on the original quote and invoice. The license owner is the first account that automatically sees the license, the downloads, and the activation details in MyNoldus. Everyone else in the lab who needs access, PhD students, research assistants, postdocs, collaborators, joins as an invited user or co-user. Invited users get their own MyNoldus account and can see the licenses and downloads as the owner gives them access to, but only after the owner sends them an invite. So if you log in and the dashboard is empty, the first question to ask is: "Am I the license owner, or am I waiting on an invite?". In most cases, you're the second one. How invites work Sharing access in MyNoldus is quick, but it does need an active step from the license owner. Here's the flow: - The license owner logs in to my.noldus.com with their account. - They go to Licenses in the sidebar menu. - Click on Share license or scroll down to the sharing form. - They add the colleagues details and set a share duration. - If the colleague needs to be able to invite other users (e.g. a lab manager) they check the Make administrator box. - Click Send invite. - The colleague receives an email invitation with a link to either create a new MyNoldus account or sign in with an existing one. - Once they accept the invitation, the license, downloads, and documentation appear in their dashboard too. A few things that catch people out: - The invitation goes to the exact email address the owner typed. If you signed up with a different address (your personal Gmail instead of your university email, for example), the invite won't connect to your account. - Invitation emails sometimes land in spam or in a quarantine filter, worth a quick check before assuming it never arrived. - Accepting the invite is a one-click step, but it does need to happen. The license won't appear in your account until you click through. Why a valid account can still show no downloads You're signed in, your account works, and the dashboard is still blank. That usually points to one of these: - You're a user who hasn't been invited to the license yet. The most common cause by far. Your account is fine,  it just hasn't been linked to any license. Please ask the license owner to invite you. Sometimes the owner simply hasn't gotten around to adding you, or didn't realize they needed to. - You were invited to a different email address. If your lab uses your `@university.edu` address on the license but you created your MyNoldus account with a personal email (or vice versa), the two won't match up. The invite is sitting at an address you're not signed in with. - You didn't accept the invitation yet. Make sure you accept the invitation when you land on the MyNoldus home page. If the invitation expired, ask the license owner to resend it.  - You signed up with a brand-new account. Creating a MyNoldus account doesn't automatically connect you to any existing licenses, those connections only happen through invites or because you're the listed owner. If you're unsure which of these applies, the fastest check is to ask whoever in your lab manages the Noldus software (often a PI, lab manager, or senior researcher) whether they've added you, and to which email address. What if the license owner has retired, changed email, or never created an account? This is a really common situation, especially in academic labs where people come and go. A license might have been bought years ago by a PI who's since retired, moved institutions, or simply never logged in to MyNoldus. When that happens, no one in the current lab can see the license, and there's no one to send an invite. Don't worry, this is fixable. The path forward depends on the situation: - The original owner retired or left the institution. We can transfer the license to a current member of the lab. You'll just need to let us know who the new owner should be and, where possible, a confirmation from the original owner or the department. - The owner changed email addresses. Their MyNoldus account can be updated to the new address, or the license can be moved to a different account. Either is straightforward. - The owner never created a MyNoldus account. No problem, we can help them set one up, or transfer ownership to someone who's actively using the software. - You're not sure who the owner is. If you can tell us the institution, the lab, and roughly when the license was purchased, we can usually trace it. In all of these cases, the next step is the same: reach out to licensing@noldus.com and we'll sort it out from our side. Related articles  - How do I get acces to MyNoldus - MyNoldus registration and password email troubleshooting --- ## Accessing EthoVision XT remotely URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/accessing-ethovision-xt-remotely Chapter: EthoVision XT Remote access software can be used to control a computer (e.g., where EthoVision is running) from another computer located elsewhere. The hardware license key (if needed, see below) should be plugged into the EthoVision computer, not the remote computer. Microsoft Remote Desktop will not work for this purpose if you are using a hardware license key (aka dongle), although it is fine if you have a software-based license (using an activation code rather than a hardware license key). While using Remote Desktop, your hardware key will not be detected. Other remote access software will work. (Note: this applies to all Noldus products with hardware license keys, not just EthoVision.) More details are provided about using TeamViewer and TightVNC at the end of this document. - TeamViewer https://www.teamviewer.com/ (PREFERRED) - TightVNC https://www.tightvnc.com/download.php - RealVNC https://www.realvnc.com/en/connect/trial/ - DameWare https://www.dameware.com/dameware-remote-everywhere/registration When is this needed? Use remote access to a computer in your lab when you need to use hardware in your lab (e.g., cameras, arenas), when you need a hardware key but cannot take it from the lab (e.g., to allow multiple people in different locations to use it), or when it is unfeasible to take the files (e.g., because of their size). A license is required for: - Creating a new experiment using functionality from any optional module (e.g., multiple arenas, nose and tail tracking, behavior recognition) - Acquiring a new track from a camera - Acquiring a track (new or redoing a track) from a video file A hardware license key is not required for analysis of existing tracks. You can simply install EthoVision on an additional computer for this purpose. If you are using EthoVision XT 17 or newer, you have the option of a software-based license instead of a hardware license key. This avoids the issue with Remote Desktop. Contact Noldus support if you are interested in switching from a hardware license key to a software-based license. TeamViewer TeamViewer is easy to use and free for non-commercial purposes. - Download TeamViewer from their site at https://www.teamviewer.com/ - When installing on the EthoVision computer, make sure to select Unattended Access. - Open TeamViewer on the EthoVision computer. - On the General tab under Unattended Access, select Start TeamViewer. - Write down the Partner ID and Password (or take a photo of the screen). - Leave this computer running so you can connect to it. - Install TeamViewer on your remote computer. - Under Control Remote Computer, enter the ID from above, then enter the password when prompted. TightVNC TightVNC may require that you connect to the network using a VPN. - Download the installer from https://www.tightvnc.com/download.php, and run it on the PC with EthoVision. - Use the full install to install both the viewer and the server. Use the default install, but set the passwords for security to ensure others cannot access your computer. - Restart the computer and leave it running in order to be able to connect to it. - Install the viewer on the PC you want to work from. - Make the connection to the local network where the computer is running. - Run the viewer and type the name or the IP address of the PC you want to connect to. - Type in the password. --- ## Activity, Mobility, and Movement: How much is my animal moving around? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/activity-mobility-and-movement-how-much-is-my-animal-moving-around Chapter: EthoVision XT Overview of Activity, Mobility, and Movement EthoVision provides several dependent variables to measure different aspects of animal behavior. Activity, Mobility, and Movement each quantify how much time the animal is moving versus being stationary. These measures can be used to analyze behavior such as: - Sleep – prolonged inactivity - Freezing – brief inactivity - Seizures – brief bursts of intense activity   Each measure has a: - Continuous measure – a value recorded at every sample point - State measure – a classification based on thresholds   Examples: - Activity (continuous) and Activity State (state) - Mobility and Mobility State - Movement is a state derived from Velocity   Mobility Mobility looks at the entire yellow-highlighted area detected as the animal. It measures the percentage of that area that is different between two sample points. Mobility may be high due to translational movement or body shape changes like turning in place. Mobility = % change between A(n-1) and A(n), where A = animal's detected area. CA(n) is the calculated changed area. Mobility States categorize the mobility percentage using thresholds: - Immobile: below 4% - Mobile: 4–10% - Highly mobile: above 10% Activity Activity measures change in the entire arena, not just what’s detected as the animal. It tracks the percentage of changing pixels compared to the previous frame. Shadows or reflections may contribute. Activity States categorize change percentages using thresholds, just like Mobility States. When to use Activity: - Whole-body detection is inconsistent - Shadows/reflections interfere with Mobility - Tracking isn’t possible (e.g., too many animals) To enable Activity: - Enable Activity in Experiment Settings - Click Activity in Detection Settings Settings: - Compression Artifacts Filter: On for video files, Off for live tracking - Background Noise Filter: Use if noise appears across the arena - Activity Threshold: Adjust to show movement (purple) without false detections Movement Movement measures whether the animal’s center point is moving faster than a velocity threshold. It is a binary state—either moving or not moving. Example thresholds: - Moving: ≥ 2.00 cm/s - Not moving: ≤ 1.75 cm/s Limitations: Movement does not distinguish between still but active behavior (e.g., grooming) and complete inactivity (e.g., sleep). Determining Thresholds State-based measures require appropriate thresholds. Use the Integrated Visualization to identify optimal values: - Add Velocity, Mobility, and Activity to your analysis profile - Open the Integrated Visualization to see video, tracking, and data plots - Use zoom and hover to examine specific behaviors If the data is noisy, increase the Averaging Interval (e.g., 10 samples) for smoother results: Use behavioral periods (e.g., freezing, seizures) to guide threshold selection. Then configure Movement, Mobility States, and Activity States accordingly. Be sure to match averaging intervals between continuous and state variables. Use the integrated visualization to refine thresholds. You can also exclude brief intervals (e.g., under 1 second) for Activity States if they are irrelevant to your analysis (e.g., sleeping). --- ## Basler camera is not detected by EthoVision URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/basler-camera-is-not-detected-by-ethovision Chapter: EthoVision XT Error: "Camera Not Found" in EthoVision XT This message indicates that EthoVision XT is unable to detect the connected camera. Solution 1: Check the connections Ensure the camera is properly connected to the PC. For Basler cameras, refer to this guide: Connecting a Basler Camera. Solution 2: Install the correct Basler Pylon driver Check that the installed Pylon Camera Software Suite matches your version of EthoVision XT. A mismatch may cause the camera not to be recognized. - Open the Start menu and search for Programs and Features. - In the list, locate Pylon X Camera Software Suite. - If the version is incorrect, uninstall it. - Use the table below to download and install the correct version: EthoVision XT Version Pylon Software Suite Version 17.0 6.2.0.21487 16.0 5.1.0.12681 15.0 5.1.0.12681 14.0 5.0.9 Installation Notes for Pylon 6.x and above: - Run the downloaded installer. - Accept the license agreement and choose Custom installation. - Select GigE Camera Support (for Ethernet) or USB Camera Support depending on your hardware. - Important: Also select Pylon Viewer and DirectShow Support. Without DirectShow, EthoVision cannot detect the camera. - Finish installation and restart the computer. Solution 3: Check IP address settings Incorrect network configuration may prevent the camera from being found. Follow this guide: Check network settings for a Basler camera. Solution 4: Disable Windows Firewall As a last step, disable the firewall temporarily to rule out blocking issues: - Open the Control Panel. - Go to System and Security > Windows Defender Firewall. - Click Turn Windows Defender Firewall on or off on the left. - Select Turn off for all network types and click OK. --- ## Can I add or alter zones in my Arena Settings after data acquisition in EthoVision XT? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/can-i-add-or-alter-zones-in-my-arena-settings-after-data-acquisition-in-ethovision-xt Chapter: EthoVision XT Editing Arena Settings and Zones After Data Acquisition While Arena Settings are typically configured before acquiring data in EthoVision XT, you may later determine that your Zone(s) need adjustments (e.g., size, position), or that new zones should be added for additional analyses. Below is how you can make such updates after trials have already been run. Changing Zones Once a trial has been acquired using a specific Arena Settings profile: - The background image, calibration scales, and arena outlines will be locked. - However, Zone Groups and the Zones within them will remain editable. This means you can: - Resize, reposition, or rename existing zones. - Add new zones to existing Zone Groups. - Create new Zone Groups and define new zones within them. No re-tracking is needed when you modify or add zones. EthoVision XT will apply those new definitions to existing trial data and include them automatically in your analysis. Exceptions (When Zones Are Locked) There are certain cases where zones cannot be modified: - If a zone was used in Trial Control Settings (e.g., “end trial when the animal is in Zone A for 2 seconds”), then: - That zone and its entire Zone Group will be locked. - You will be unable to modify or delete them unless trials using that trial control profile are deleted or cleared. - Any Hidden Zones are also locked and cannot be altered. Important Note: Zone Changes Must Stay in the Same Arena Settings Zone changes must be made within the same Arena Settings profile that was used during the original acquisition. Creating a new Arena Settings profile will have no effect on previously-acquired trials. If you need to change locked aspects of the arena (e.g., the background image, calibration, or outline), you must: - Redo the trial using the original video file. - To learn how to do this, see: Redo a trial from video files. --- ## Can I get certain dependent measures (e.g., "distance moved") by zone in EthoVision XT? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/can-i-get-certain-dependent-measures-eg-distance-moved-by-zone-in-ethovision-xt Chapter: EthoVision XT Calculating Dependent Variables by Zone EthoVision XT allows you to analyze any dependent variable (DV) per zone. For instance, in a Morris Water Maze study, you can calculate the Distance Moved within each quadrant to understand how much of the total path occurred in each region. Step 1: Enable "Results per zone" in the Data Profile In your Data Profile, click the Settings button on the Result(s) container, then: - Check the box for Results per zone. - Select the specific zone(s) for which you want to analyze dependent variables. Step 2: Add Dependent Measures in the Analysis Profile Navigate to your Analysis Profile and add the dependent measure(s) you're interested in, such as: - Distance moved - Velocity - Time spent Step 3: View Zone-Specific Data in Statistics & Charts Open the Statistics & Charts section. You will now see the selected dependent variables broken down by the zones you enabled in the Data Profile. This approach is especially useful in spatial navigation tasks or when analyzing zone preferences across experimental conditions. --- ## Can I use a webcam with EthoVision? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/can-i-use-a-webcam-with-ethovision Chapter: EthoVision XT EthoVision XT (version 15), has been tested with two webcams, Microsoft LifeCam Studio and Logitech Brio. However, we do not recommend the use of webcams when timing of video frames is important, as they are not very precise and can drop frames. If needed, they can be used for simple tests, e.g., use a webcam to track one subject in an open field, to measure the total distance moved. Do not use webcams for multi-subject tracking, or tracking in multiple arenas, or with Behavior Recognition, or whenever the exact position of the subject’s body points at a specific time is needed. Moreover, test if the webcam still works when other software needed to run during the trials is open (e.g., PowerPoint for stimulus presentation), as other software may attempt to take control of the webcam. Verifying Performance As a general note, if you want to use a camera model other than the ones listed under ‘Cameras supported by EthoVision XT’ in the Help menu, make sure that the timing of the camera is accurate enough for a frame-level video analysis before starting an experiment. To do so, create a live tracking experiment, and carry out a test trial with the video footage of a digital clock for some ten minutes. Make sure you are getting less than 1% Missed Samples or Interpolated Samples during the trial (visible at the bottom of the screen in the acquisition or detection settings). Just before stopping the trial, check that the trial duration shown on your screen does not deviate from that obtained with the clock time. --- ## Changing the exposure settings for Basler cameras URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/changing-the-exposure-settings-for-basler-cameras Chapter: EthoVision XT Exposure is the amount of time the camera spends acquiring a video frame. Increasing the exposure allows more light to reach the sensor (brightening the image), while lowering it reduces the light (darkening the image). Other factors that affect brightness include: - Aperture setting on the lens (marked "Open-Close") – turn to "Open" to brighten - Gain setting of the camera - Lighting conditions If your image is too dark, first try opening the aperture. For more details, see: My image is too dark using a Basler camera. Solution - Close your Noldus software (e.g., MediaRecorder or EthoVision XT). - Start the Basler Pylon Viewer software. - Note: Pylon Viewer is installed with the camera driver. If it's not on your desktop, check the Start menu under Basler. - Go to Tools > Options and ensure the User Level is set to Expert or Guru. - In the Devices panel, double-click the Basler camera under GigE or USB. - In the Features panel, open the Basler camera item and double-click Acquisition Controls. - Note: If you don’t see the Features panel, go to Window > Features to enable it. - Set Exposure Mode to Timed. - Set Exposure Auto to Off. - Enter your value in Exposure Time (Abs) [us] and press Tab to confirm. - Note: Higher exposure = brighter image; too high = dropped frames; too low = flicker. Typical exposure ranges: - Non-DanioVision: 8,000 to 25,000 μs - With IR lighting: ~30,000 μs (reduce frame rate if needed) - DanioVision: 4,000 μs (1280x960) or 2,000 μs (640x480) - Click Continuous Shot to preview the frame rate. - At the bottom of the preview window, verify the actual frame rate matches Acquisition Frame Rate (Abs) [Hz] (recommended: 25 or 30 Hz). - If frame rate is too low, try the following: - a. Lower exposure time and increase Gain (Raw) under Analog Control - b. Open the lens diaphragm (aperture) - c. Lower video resolution in AOI Controls by adjusting Width and Height - Note: Lowering resolution crops the image and may shift the center. Ensure Center X and Center Y are checked. - d. Lower the frame rate. Match this in EthoVision to avoid Missed or Interpolated Samples. - Stop Continuous Shot. Then save the configuration: - Select User Set 1 from Configuration Set Selector - Click Execute next to User Set Save - Set User Set 1 as the Default Startup Set - Close Pylon Viewer - Note: These saved settings will automatically load each time you start your Noldus software. Tip: You can also save different settings in User Set 2 and User Set 3, and choose your preferred default under User Set Default. --- ## Color-marking animals for EthoVision URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/color-marking-animals-for-ethovision Chapter: EthoVision XT Tracking Methods - Color Marker Tracking: Tracks only the colored marker (no nose/tail tracking). Suitable for all species. - Marker-Assisted Tracking: Uses both contrast-based body tracking and the color marker for identification. Recommended for social interaction tests where body points are needed. Lighting Conditions - Brightness: Ensure sufficient illumination; dim lighting reduces color contrast. - Uniformity: Use diffuse lighting to minimize shadows and preserve color fidelity. - Color Temperature: Use daylight-spectrum lamps for optimal hue separation. General Marker Tips - Choose highly distinct hues (e.g., red vs. green; avoid red vs. orange). - Avoid red if possible—it resembles blood. - Set a minimum marker size to ignore false detections from similar colors in the arena. - Apply markers in advance to reduce animal stress during testing. - Use fluorescent markers with UV lighting in dark conditions (for marker-only tracking). - Place markers on the center of the back—not on the head or tail—to maintain visibility. - Ensure the marker is round and uniform to reduce detection error. - Do not oversize the marker, especially on small or light-colored animals. Species-Specific Marking Small Mammals & Birds - Chalk/Terracotta markers: Non-toxic and opaque; effective on dark fur. - Livestock markers: Paint sticks and sprays available in fluorescent colors. - Hair dye: Long-lasting; bleach dark fur if needed. - Permanent markers: Temporary and easy but can be removed by grooming. - Colored jackets: Cloth with Velcro; useful for small mammals with colored fur. Large Mammals Use livestock markers such as: - Carmel Industries - Markal Fish & Amphibians - Plastic pearls: Attach under dorsal fin with non-resorbable filament under anesthesia (e.g., Chromis chromis). - Visible Implant Elastomer (VIE) Tags: NMT produces VIE tags, visible under UV and normal light, suitable for fish and tadpoles. Reptiles - Nail polish: Applied to lizard skin, lasts up to 10 days in small species. Insects - Acrylic paint: Use a fine brush to apply; hold insect until dry. - Food coloring via honey: For parasitic wasps and other insects with translucent abdomens; no anesthesia needed. - VIE tags: Also usable for insects (see fish section). Final Recommendations - Always test marker visibility in your arena before running actual experiments. - Minimize stress by marking animals well before trials begin. - Check that colors are not duplicated in background or arena elements. --- ## Connecting an optogenetics laser to be controlled by EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/connecting-an-optogenetics-laser-to-be-controlled-by-ethovision-xt Chapter: EthoVision XT EthoVision XT can control a laser or LED light source for optogenetics, using time- or behavior-based triggers. For example, stimulation can be activated when the animal enters a specific zone. Note: EthoVision does not pulse the laser directly. If pulsing (e.g., 20 Hz) is needed, a pulse generator is required. EthoVision can trigger the start/stop of this generator. Required Components The full system includes: - EthoVision XT and its host computer - Trial & Hardware Control Module - USB IO Box or Mini IO Box (via USB) - Laser or high-intensity LED source - Pulse generator - Fiber optics, connectors, cannulae (user-supplied) You will need a TTL cable with an RJ45 connector on one end and a BNC (or compatible) connector on the other, connecting the IO box to the pulse generator (or directly to the laser). Basic Setup in EthoVision - In Experiment Settings, enable Use of Trial Control Hardware. - Click Settings and select the appropriate IO box (USB or Mini USB). For the used TTL port, set Custom Hardware as the device type. - In Arena Settings, click Arena-Hardware Mapping. Add and assign your device to Arena 1. Repeat for multiple arenas as needed. - Use the Test function in the Arena-Hardware Mapping window to confirm connectivity: - Output 1 High – Turns device ON - Output 1 Low – Turns device OFF Pulse Generator Configuration Most pulse generators respond to a 5V TTL signal. Settings vary by model: Pulse Mode: Fixed-duration pulse train - Prizmatix Pulser: “Execute pulse sequence each time after trigger(s)” - AMPI Master-8/9: “Train” - Agilent Waveform Generator: “Triggered Burst Mode” Gate Mode: Continuous pulse during trigger HIGH - Prizmatix Pulser: “Execute pulse sequence after trigger HIGH, stop when LOW” - AMPI Master-8/9: “Gate” - Agilent Waveform Generator: “External Gated Burst Mode” - Plexon PlexBright: “Edge Digital Input” (Use one trigger input for ON, another for OFF) Trial Control Settings in EthoVision Use the Trial Control feature to define stimulation timing. Events are shown as a flowchart: Example: Simple timed stimulation (5 min pre-stim, 1 min stim, 5 min post-stim): Repeated Stimulation To repeat events, use a Sub-Rule loop: - Pre-stimulation: 5 minutes - Sub-rule: 2 min ON, 2 min OFF, repeated 3 times Zone-Based (Place Preference) Stimulation Stimulation starts/stops depending on the animal's zone (e.g., Left = ON, Right = OFF). The sub-rule runs continuously, and a time limit controls total duration: Additional Triggering Options Triggers for stimulation are not limited to zones. You can also use: - Activity level - Velocity - Turning angle - External sensors (e.g., lever presses, nose pokes) This allows for highly flexible behavior-based stimulation and inhibition protocols. --- ## Correcting the Basler Drivers URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/correcting-the-basler-drivers Chapter: EthoVision XT Ensuring Proper Driver for Basler GigE Camera Network Adapter To maximize Basler camera performance, the Basler software installs a special Basler GigE Vision Adapter driver to replace the default Intel driver on the network card. However, Windows may revert to the Intel driver, causing performance issues such as low frame rates or Error ID 12015 ("Trial duration does not correspond with system time") in EthoVision XT. Step-by-Step Instructions to Check or Correct the Network Adapter Driver - Open the Pylon IP Configurator tool. - Look for it on your desktop or in the Start menu under Basler. - Identify the Ethernet adapter used by the Basler camera. - Right-click the adapter and select Properties. - Click Configure, then go to the Driver tab. - Click Update Driver → Browse my computer for drivers → Let me pick from a list of available drivers. - Select Basler GigE Vision Adapter from the list. - If it doesn’t appear, uncheck Show compatible hardware and locate it under the Intel list. - Click Next. Confirm any prompts that ask whether you’re sure you want to install the driver. If the Basler GigE Vision Adapter is already in use: - Try switching temporarily to the Intel Gigabit Pro driver. - Apply changes, then repeat the steps above to re-select the Basler GigE Vision Adapter. Optional: Prevent Windows from Automatically Reverting the Driver - Right-click the Start menu and select System. - Click Advanced system settings on the right panel. - Open the Hardware tab. - Click Device Installation Settings. - Select No (your device might not work as expected) and click Save Changes. This will stop Windows from automatically replacing the Basler driver with the default Intel one after system updates. Tip: After applying changes, restart the computer and reopen EthoVision XT to verify that the camera is recognized and running smoothly. --- ## EthoVision will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: EthoVision XT This error in the installation log file may indicate one of the following issues: You do not have the necessary rights to install software Your account may lack administrative privileges. Ensure that you are logged in with an account that has administrator rights, or contact your IT department for assistance with installing software. Windows is currently updating If Windows is in the middle of an update, the FaceReader installation cannot proceed. Wait for all updates to complete and then restart your computer before trying again. There is a problem with system files Malware or a virus may have modified system files. Run a full system scan using your antivirus or anti-malware software to identify and resolve any issues. --- ## EthoVision XT crashes when viewing a GLP log URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-crashes-when-viewing-a-glp-log Chapter: EthoVision XT This issue may occur when using Quality Assurance experiments, particularly after clicking within the GLP Log window or after clicking the Close button in the GLP Log window. To resolve this issue, follow these steps: - Open Windows Notepad and enter the following text: Windows Registry Editor Version 5.00 [HKEY_CURRENT_USER\SOFTWARE\Microsoft\Internet Explorer\Main\FeatureControl\FEATURE_USE_LEGACY_JSCRIPT] "EthoVision.exe"=dword:00000001 - Save the file with a .reg extension (e.g., fix_jscript.reg) on the EthoVision XT computer. - Double-click the file. Click OK in the confirmation message that appears. TIP: Files with the .reg extension are often blocked by Windows and email servers. Avoid running REG files from network drives. If you need to share a REG file by email, first compress it into a ZIP archive. --- ## EthoVision XT error ID 14005 Chart creation failed URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-error-id-14005-chart-creation-failed Chapter: EthoVision XT Error in Statistics & Charts: Chart Component Missing This error occurs when you access the Statistics & Charts section in EthoVision XT and encounter the following message: Although you can still view your data, this error indicates that the software component required for generating charts in the Group Statistics & Charts tab is missing or corrupted. Recommended Fix While the warning suggests reinstalling EthoVision XT, a quicker solution is outlined below: - Close EthoVision XT. - Open the Start menu and search for Programs and Features. - In the list of installed programs, check if Noldus ChartWrapperControl 2 is present. - If it is listed, select it and click Uninstall. - Close the Programs and Features window. - Download the installer for Chart Wrapper Control 2.0.2 from the link below: Download Chart Wrapper Control 2.0.2 Note: This version is compatible with EthoVision XT 12 through 15. For other versions, please contact Noldus Support. Final Steps - Double-click the downloaded file to install the Chart Wrapper Control component. - Once installed, reopen EthoVision XT and verify that the issue is resolved. --- ## EthoVision XT file error Id 10025 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-file-error-id-10025 Chapter: EthoVision XT This error indicates there was a problem opening the experiment, but could arise for a variety of reasons. If this error occurs, you cannot open the experiment until the underlying cause is resolved. Files Missing or Out of Place A complete EthoVision experiment consists of a folder named for the experiment, containing a variety of files and folders. All of these together constitute the experiment. Note that file extensions (e.g., “.evxt”) may not be displayed (depending on your Windows settings), and the Restore.btn files will not appear in older versions of EthoVision. This error will occur if the .evxt file (the file that you select to open the experiment) has been moved and is no longer in the location with the rest of the experiment. The .evxt file on its own does not include, for example, any track data. If this is the issue, copy the .evxt file back into the original location. This error may also occur if some of the files in the experiment are missing. This could happen if you moved some of the files out of the experiment folder or deleted them. It could also happen if you ran out of space on the hard drive where the experiment is stored. Check that you are not low on space. Lastly, you will not be able to open the experiment if any of the listed folders are missing. This may also result in an error message indicating “experimental inconsistencies.” You can create these folders as necessary. They may disappear if you use Windows to create a compressed folder of the experiment; Windows will frequently discard empty folders in this case, but EthoVision still needs those folders. If the Configuration Files folder is missing, copy it from a working experiment. This folder has a number of subfolders, and you'll need all of them. Insufficient Access This error may occur if some or all the files of the experiment are not accessible to the current user. This could happen if you are logged in under a different account on the computer, especially when using a network drive. If you can open the experiment from one user account (including from an administrative account) but not from another, the problem is likely one of user access rights. Please consult your local IT department for assistance. Experiment Database is Damaged This error may occur if the experiment database itself is damaged. This is the .evxt file. Starting in EthoVision XT 8.5, EthoVision automatically creates an extra copy of this file, called “restore.btn”. If after checking the above issues, you still cannot open the experiment, try this procedure. You will likely lose your work from your last session in the experiment, but the remainder will be restored if the .evxt file was the problem. - In the experiment folder, rename your experiment file (e.g., to “my experiment.evxt.old”). - Rename the file “restore.btn” to the original name of your experiment file (including the .evxt extension; it should have exactly the same name so that it replaces that file). Note that if Windows is hiding extensions (e.g., the “.evxt” part of the experiment file name), it will prevent you from changing the extensions. In Windows 10, click View on the ribbon and check the option to show file extensions. In Windows 7 and 8, click the Alt key to show the menu, then go on the menu to Tools/Folder Options, pick the View tab, and uncheck the option “hide extensions for known file types”. --- ## EthoVision XT file error Id 10034 Experiment cannot be repaired URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-file-error-id-10034-experiment-cannot-be-repaired Chapter: EthoVision XT This error may state: “EthoVision has detected some experiment inconsistencies.” It typically occurs because necessary files are missing or the experiment file is damaged. Files Missing or Out of Place The most common cause is that you do not have the entire experiment folder. If you only have the .evxt file, please note that this file alone is not sufficient to open an experiment. The .evxt file acts as an index and does not include tracking data or configuration files. You need the full folder that contains this file—usually named after the experiment. Here is an example of what a complete experiment folder looks like: When the .evxt file is in the folder with all required subfolders and files, the experiment should open correctly. If those files are missing, the software will return an error. Folders Lost in a ZIP or Compressed Folder When compressing and transferring experiment folders, Windows may omit empty subfolders during extraction. EthoVision expects these folders to exist—even if they are empty. Missing folders, such as External/SyncOut or subfolders under Configuration Files, may be recreated manually or copied from a working experiment folder. Preventing File Loss Instead of manually copying or zipping folders, use EthoVision's built-in backup system: - Open the original experiment in EthoVision - Go to File > Make Backup - This will create a .evz file (EthoVision backup) You can choose to exclude video files to reduce the file size. On the receiving computer, use: - File > Restore Backup This will correctly rebuild the entire experiment structure, including any necessary empty folders. Experiment File is Damaged If all files are present, the .evxt file itself may be corrupted. EthoVision creates an automatic backup which you can restore manually: - Go to the experiment folder - Rename your existing .evxt file (e.g., my_experiment.evxt.old) - Rename the file restore.btn to match the original experiment file name (e.g., my_experiment.evxt) Note: If file extensions are hidden: - In Windows 10: Open the folder, go to the View tab, and check File name extensions - In Windows 7 or 8: Tap Alt to show the menu, then go to Tools > Folder Options > View, and uncheck Hide extensions for known file types Reverting to the backup may result in the loss of changes made during your most recent session, but older data should be preserved. --- ## EthoVision XT is unable to detect the Noldus I/O Box URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-is-unable-to-detect-the-noldus-io-box Chapter: EthoVision XT EthoVision will report that the USB I/O Box is not connected if the connection is lost or if it is not present when you attempt to start the experiment or test connections. Use the guidance below to troubleshoot this situation. Connect the I/O Box before starting EthoVision EthoVision will only detect the box if it is connected when EthoVision starts. If you plug in the I/O Box after starting EthoVision, close EthoVision and reopen it. Check connections and power supply Besides the connected Noldus or third-party hardware (via TTL or SDI ports), there are two main cables required. These connections apply to both the USB I/O Box and the Mini USB I/O Box: - The USB cable connects the I/O box to the computer. If connected properly, the USB light on the I/O box should be lit. - A power cable must also be connected. The power LED light should be on. Without proper power, the box might communicate via USB but will not have enough power to control external devices. Is the I/O Box detected by the computer? If both cables are connected and the box is still not detected by EthoVision, verify that the computer recognizes the device: - Open the Start menu and click the Settings (gear) icon. - Go to Devices. - Under the Bluetooth & other devices section, look for a device named I/OWarrior56 listed under Other Devices. If you do not see this device, the driver may be missing, or the I/O box may be malfunctioning. Is the correct I/O Box selected in your Experiment Settings? You might receive a connection error if the incorrect interface was selected when creating your experiment—for example, selecting the Mini USB I/O Box instead of the standard USB I/O Box. EthoVision will search for the wrong hardware and fail to detect it. The USB I/O Box is labeled "USB-IO Box" and features 13 RJ45 ports labeled SDI Control and 12 RJ45 ports labeled TTL Control. The Mini USB I/O Box is labeled "mini USB-IO box" and includes 4 RJ45 ports labeled TTL Control and 1 RJ45 port labeled SDI Control. If you have assigned devices to the wrong interface, go back to that interface, remove the incorrect device assignments, and then add them under the correct interface. Alternatively, you can create a new experiment with the correct settings. --- ## EthoVision XT Resizer error (ID 8359) URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-resizer-error-id-8359 Chapter: EthoVision XT Error: "Resizer error (Id 8359)" when capturing background image If you receive the message "Resizer error (Id 8359)" while trying to grab a background image in Arena Settings, it indicates that the Noldus Resizer component is either missing or has become corrupted. Solution: Reinstall Noldus ResizerFilter The likely cause is a missing or corrupt Noldus ResizerFilter. You will need to reinstall the correct version that corresponds to your version of EthoVision XT. To check your EthoVision version, go to: Help > About EthoVision XT in the software menu. Download the Correct Resizer Filter Use the table below to find the correct Resizer Filter version for your version of EthoVision XT: EthoVision XT Version Resizer Filter Download 16.0, 17.0 Noldus Resizer Filter 13.1.2 14.0, 15.0 Noldus Resizer Filter 13.0.2 12.0, 13.0 Noldus Resizer Filter 12.1.6 Installation Instructions - Download the appropriate Resizer Filter installer using the link above. - Double-click the file to run the installer. - After installation completes, reopen EthoVision XT and try capturing a background image again. Need a different version? If you're using a version not listed here, please contact Noldus Support for assistance. --- ## EthoVision XT Settings are Locked, Unable to Modify URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-settings-are-locked-unable-to-modify Chapter: EthoVision XT Once data has been acquired in EthoVision using a specific profile (such as Arena Settings, Trial Control Settings, or Detection Settings), those profiles become locked from further changes. This is indicated with red arrows. Locking ensures that EthoVision always preserves the settings used during acquisition so the data can be reliably reviewed or replicated. To make changes, right-click the existing settings profile and choose Duplicate. The duplicated profile (shown with green arrows) is editable because it hasn’t been used to acquire any data yet. If your experiment includes multiple profiles (e.g., different Arena Settings), the one highlighted in blue is the one currently selected for the next trial. You can change which profile is used by selecting it in either the Trial List or the Acquisition window. If you are testing settings prior to actual acquisition, you can clear or delete the acquired trial data. This will remove the profile lock (blue arrow), making the settings editable again (green arrows). Note: The Experiment Settings also become locked once trials have been acquired. These settings cannot be duplicated. To modify Experiment Settings after data has been collected, you’ll need to create a new experiment. You can do this in two ways: - Go to File > Save Experiment As, save under a new name, and delete the existing trials in the new version. - Or create a New Template Experiment using the Custom Template option and select the current experiment as the source. This copies all settings but no trial data, leaving all profiles unlocked. Be aware that creating a Custom Template can take time, especially if your experiment contains many trials. --- ## EthoVision XT trial duration does not correspond with system time (Id 12015) URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-trial-duration-does-not-correspond-with-system-time-id-12015 Chapter: EthoVision XT Error: "Trial duration does not correspond with system time (Id 12015)" This error indicates that EthoVision has detected that video frames are arriving slower than expected. The most common cause is that the camera is not delivering frames at the correct rate. This can also result in the trial stopping early if too many consecutive frames are dropped. Alternatively, it may point to performance issues on the computer itself. Check for Skipped Frames You can check for dropped frames using the following indicators: - Detection Settings: At the bottom of the screen, review the values for Missed Samples and Interpolated Samples. These should be below 1%, ideally 0%. High values will be shown in red. Note that Interpolated Samples appears only when Dropped Frames Correction is enabled. - Acquisition View: These indicators are also shown during data acquisition. - Trial List: Enable the “Missed Samples” column via Show/Hide > Variables to review missed/interpolated samples post-trial. Note: The “Subject Not Found” metric is unrelated to frame skipping but may point to incorrect detection settings. Camera Skipping Frames USB Webcam: - Connect to a USB 3.0 port (blue or marked “SS”) directly on the computer, not via a hub. - Reduce the camera’s resolution or frame rate in Experiment Settings if needed. - Avoid other high-bandwidth USB devices (e.g., external hard drives). - Note: USB webcams are not recommended for high-performance setups. IP Cameras (e.g., Axis): - Connect directly to the computer’s network adapter if possible. - Avoid connecting multiple IP cameras via shared network switches. Basler GigE Cameras: - Check the Exposure setting. If exposure time is too high, frames may be dropped. - Refer to the guide on changing exposure for Basler cameras. - Try replacing the Ethernet cable to rule out transmission issues. Other Cameras: - Ensure the camera is configured for a fixed frame rate. - Reduce exposure time if it is too high. Basler Camera Driver Issue To ensure optimal performance, Basler installs a dedicated driver for your network adapter. Windows may override this with a standard Intel driver, which can degrade performance. For more info on restoring the proper driver, visit: Correcting Basler driver issues. Computer Performance Considerations System Requirements: - Use a workstation-class PC (e.g., Dell Precision). - Ensure the system has a dedicated GPU (not onboard Intel graphics). Save Location: - If saving the experiment to an external or network drive, try moving it to the local disk to reduce lag. - Copy the entire experiment folder, not just the .evxt file. Power Settings: - Use “High Performance” mode in Windows Power Settings. - More info: Optimize Windows 10 power settings Possible Hardware Failure A faulty video card or hard disk can also cause skipped frames. Dell computers provided by Noldus include diagnostics tools. To run diagnostics: - Shut down the PC completely. - Restart and press F12 as the Dell logo appears. - Select Diagnostics from the menu and follow the on-screen steps. Be sure to record and report any error codes that appear during the test. --- ## EthoVision XT: Animal is not tracked in Hidden Zone URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/ethovision-xt-animal-is-not-tracked-in-hidden-zone Chapter: EthoVision XT Make sure that the Entry Zone is properly linked to the Hidden Zone and not too small The purpose of the Entry Zone is to help EthoVision determine that if an animal is seen in the Entry Zone and then disappears, it must have entered the Hidden Zone. For each Hidden Zone, at least one Entry Zone must be created and linked. If the animal is tracked correctly in the arena and the Entry Zone, but appears as “missing” once it enters the Hidden Zone, the issue is likely that: - The Entry Zone is not correctly linked to the Hidden Zone - The Entry Zone is too small for reliable detection Step 1: Check the Entry Zone Linking To confirm the Entry Zone is properly linked: - Open your Arena Settings - Right-click the Entry Zone and select Link Hidden Zones - In the dialog that appears, ensure the correct Hidden Zone (e.g., “Dark Side”) is checked ✔ Ensure the box for your desired Hidden Zone is selected. Optional: Enable the setting “Use the entry zone also as a leaving zone”. This setting improves accuracy by ensuring that an animal is considered to have left the Hidden Zone only after it crosses back through the Entry Zone—not just when it is next detected. This reduces false exit counts caused by brief reappearances (e.g., head pokes). Step 2: Make Sure the Entry Zone is Large Enough If the Entry Zone is correctly linked but animals still go “missing” after entering the Hidden Zone, the Entry Zone might be too small. Why size matters: - EthoVision must “see” the animal in the Entry Zone before it disappears Best practice: - Ensure the Entry Zone overlaps slightly with the Hidden Zone - Make the Entry Zone large enough to reliably detect the animal entering from any angle - It's generally safe to make Entry Zones fairly large. If using them also as leaving zones, be aware tracking resumes only when the animal exits the Entry Zone How Hidden Zones Work Hidden Zones are intended for areas where the animal is completely out of view. EthoVision considers the animal to have entered the Hidden Zone if it was last detected in the Entry Zone and then disappeared. If the animal is detected while inside the Hidden Zone, it is no longer hidden and may be marked as having left. If it later disappears again but was not seen in the Entry Zone, it will not be counted as re-entering the Hidden Zone. To avoid this, you may enlarge the Entry Zone to cover the entire Hidden Zone. --- ## How do IR cameras work? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/how-do-ir-cameras-work Chapter: EthoVision XT Understanding IR Cameras in Behavioral Research Most cameras—both color and monochrome—have some sensitivity to infrared (IR) light as well as to visible light. However, the way they handle IR differs: - Color cameras typically have IR-blocking filters built-in to maintain color fidelity. - Monochrome cameras may also have IR-blocking filters, but these are often removable (e.g., via "night mode"). - Dedicated IR cameras are optimized for IR sensitivity, but the underlying detection principle remains the same. Common Misconception: IR Cameras and Heat It's a common mistake to assume that IR cameras detect heat. While hot objects do emit IR, the wavelengths involved differ: - Heat from living beings is emitted in the mid to far infrared range (3000 nm+). - Typical behavior-tracking cameras are sensitive only to the near infrared (NIR) range—between 700 nm and 1000 nm. - Common IR illumination wavelengths are 850 nm or 940 nm (e.g., 940 nm in the PhenoTyper). To detect body heat, you'd need a thermographic camera, which: - Detects mid/far IR radiation. - Produces low-resolution, false-color images. - Is not typically used in behavior tracking due to cost and lack of detail. Why Use IR in Behavior Research? In behavioral studies, IR serves as an invisible light source—a wavelength most animals (including rodents) do not perceive. This allows for unobtrusive observation, even during dark-phase cycles. Sources of IR illumination include: - Standalone IR illuminators mounted in observation cubicles. - Integrated IR sources in systems like the PhenoTyper. Using IR-Pass Filters Sometimes, IR-pass filters are added to the camera to block visible light. This is beneficial when: - You want to maintain image consistency during changing ambient light conditions (e.g., circadian cycles). - You have a controlled IR-only environment. These filters are visually identifiable by the camera lens appearing completely black (no visible light passes through). Considerations for IR Illumination - IR light behaves like visible light—it's reflected or absorbed by surfaces. - Glare may occur with shiny surfaces, so you may need to adjust the camera or IR source position. - Some materials reflect IR differently than visible light. For example: - Corncob bedding often appears brighter in IR than to the naked eye. - Paper-based bedding usually appears darker, though this varies by brand. - For tracking light-colored animals, consider using dark bedding to increase contrast. A recommended option is Purina’s Yesterday’s News (unscented), which provides a dark appearance in IR. --- ## How many GigE cameras can I use on a laptop with EthoVision XT? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/how-many-gige-cameras-can-i-use-on-a-laptop-with-ethovision-xt Chapter: EthoVision XT It is generally recommended to use GigE cameras on a desktop computer equipped with a dedicated Intel gigabit network adapter. This configuration ensures that the built-in network adapter remains available for connecting to your local network and/or the internet. While it is technically possible to use a laptop with a built-in gigabit network adapter to connect to a GigE camera, the necessary configuration will make the Ethernet port unusable for standard network access. If a network connection is required, use wifi or a USB network adapter. Supported Configurations - EthoVision XT 12, 13, and 14 were tested and supported on a workstation-class laptop using one Basler GigE camera for recordings up to 10 hours. - This configuration was not tested or officially supported in EthoVision XT 15 and 16. - Basler USB 3.0 (acA1920-155um) cameras are supported for use on suitable laptops. Multi-Camera Recording On a properly configured desktop PC with a four-port network adapter, you can record from up to four GigE cameras simultaneously. --- ## Image from my camera is flickering URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/image-from-my-camera-is-flickering Chapter: EthoVision XT This issue can occur because fluorescent and LED lighting flashes rapidly at a rate determined by the power frequency. Though imperceptible to human vision, mismatched camera frame rates can result in alternating bright and dim video frames—perceived as flickering. For reference: - 50 Hz power (Europe/Asia) → 100 light pulses per second - 60 Hz power (North America) → 120 light pulses per second   Solution: Alter the Frame Rate of the Camera in Your Noldus Software Under typical North American lighting, a frame rate of 25 fps may cause flickering. Changing to 30 fps often resolves the issue. However, flickering can vary depending on the dimming level of the lights, so you may need to test several frame rates. EthoVision XT In Experiment Settings, adjust the camera's frame rate. Then click the icon below to preview the live image and assess if flickering is resolved: Live image preview: If flickering persists, open the Video Settings window by clicking the same icon again, and test alternative frame rates: Note: It may take a few seconds for the image to update after changing settings. Important: Once trials are acquired, the frame rate setting becomes locked. If your initial trials were only for testing, delete them to unlock the settings. Alternatively, create a new experiment using: - New Template Experiment → Custom Template - Select your original experiment as the template source This method copies all settings but not trial data. Note that this process can take time if the original experiment contains many trials. MediaRecorder In Video Settings, adjust the frame rate for each camera under the Frame rate column. Click Apply to confirm. Review the live preview and repeat adjustments as necessary until flickering disappears. Note: The image will take a few seconds to refresh after any change. --- ## Improving Nose-Tail tracking in EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/improving-nose-tail-tracking-in-ethovision-xt Chapter: EthoVision XT How Nose-Tail Tracking Works EthoVision XT can use two different methods to track the nose and tail: - Contour-based detection looks at the outline of the area detected as the animal to find the correct shape of the nose and tail. - Deep learning uses a trained neural network model to identify the nose and tail of a mouse or rat. This method, available in EthoVision XT 16 and up, uses the image of the animal and can accurately place the nose and tail even outside the yellow detected area of the animal. Deep learning requires a suitable NVIDIA GPU; if that is not present, contour-based detection is required. When deep learning is available and you are working with rodents, it will generally give the best results. Contour-Based Detection When using contour-based detection, it's important to adjust the detection settings so that the yellow area (which indicates everything detected as the animal) corresponds as closely as possible to the real outline of the animal, since the outline is being used to identify the points. In the Detection Settings, under the method there is a pulldown selection of the algorithm to identify the nose and tail points. The options are: - Any species / Default: A general method suitable for many animals. If tracking rodents, ensure the tail is detected. (Previously called "Shape-Based / Default" in XT 14 and earlier.) - Rodents / Default: Fits a model rodent shape to the detected outline. It is more robust because it doesn't require the nose and tail to be visible. Useful for open field, water maze, or novel object tests. (Previously "Simple Model / Rodents".) - Rodents / For Occlusions: Better for cases where parts of the animal may be occluded. More computationally demanding. Works best without tail tracking (adjust using Erosion and Dilation settings). (Previously "Advanced Model / Rodents".) - Adult Fish / For Occlusions: Designed for adult zebrafish and similar species when viewed from above. Ensure the entire body including the tail is detected. (Previously "Advanced Model / Adult Fish".) - Other Species / For Occlusions: May work better for other animals or fish viewed from the side. (Previously "Advanced Model / Other".) Optimizing the "Rodents / For Occlusion" method When using the "Advanced Model / Rodents" method, you can improve results by specifying the animal's size: - In Detection Settings, first optimize the yellow detection area to match the actual body outline. - Click the Advanced button next to Subject Size. - In the "Modeled Subject Size" panel, check the value under Current Pixels. Click Grab to copy it to Average Pixels, or enter the value manually. - Check the box under Fix to lock the average size. This often improves tracking accuracy. If tracking multiple animals and they are sometimes merged into one when in contact, lowering the Average Pixels value may help. Deep Learning Deep learning works best when the animal’s outline is clearly visible throughout the arena. Uniform lighting and a minimum animal size of 30 pixels in length are recommended. There are two specific settings for deep learning in the Detection Settings: - Hooded rats: Check this box if your animals are black and white rather than a single color. - Define (Cutout size): Click this to adjust the yellow box surrounding the animal. The box should extend 0.5–1 body length beyond the animal (excluding the tail). You can use the Automated button or adjust the slider manually. General Advice If center, nose, and tail tracking are generally accurate but with frequent swaps, try the following: - Ensure the arena is large enough to contain the animal even when rearing, but not so large that extraneous elements are detected. The animal’s nose must remain within the arena boundary. - Address reflections on the side walls by lightly sanding them to reduce shininess if EthoVision is mistaking reflections for animal outlines. - Adjust contrast to detect the entire animal. Avoid overly high contrast that detects only the center and misses edges. - Use even, indirect, diffuse lighting. Shadows or uneven lighting can cause detection issues. Refer to the EthoVision manual for lighting placement tips. - Increasing aperture (camera diaphragm) may enhance contrast without increasing light intensity. - Use the maximum sample rate (25–30 samples/sec) to improve nose-tail tracking resolution. - For better tracking, especially under high system load, consider 2-stage tracking: acquire video first, then retrack from that video. Use the "Detection Determines Speed" option for video tracking. --- ## Installing EthoVision XT 17.5 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/installing-ethovision-xt-175 Chapter: EthoVision XT System Requirements EthoVision XT 17.5 runs on Windows 10 Professional and 11 Pro. It is not designed for use with Windows Touch features. If you have EthoVision XT 17.0, this version replaces your current installation but does not delete your experiments. If you're upgrading from EthoVision XT 16 or older, this is not a free upgrade. If you use a hardware license key (dongle), you’ll need to enter an upgrade code. If you have an active NoldusCare contract, the registered user has received an upgrade key. Otherwise, contact your sales representative to purchase an upgrade. For software-based licenses, the license will automatically update if you have an active NoldusCare contract. If not, contact your sales representative to purchase an upgrade. Before You Install EthoVision XT If you are a new user: You received a software activation key. Keep this key ready when starting EthoVision XT. If upgrading from older versions with a hardware dongle: You received a license upgrade key via email. Keep this key ready at first launch. User Rights: You must have administrator rights to install EthoVision XT. Regional Settings: Avoid using a comma as the decimal separator in Windows. To change this setting: - Go to Control Panel > Clock, Language, and Region - Click Change date, time, or number formats - Click Additional settings MediaRecorder: If installing MediaRecorder and EthoVision XT on the same PC, install MediaRecorder first. To Install EthoVision XT 17.5 Close all other applications before installation. If you don’t have the installation files (e.g., from a USB drive), they can be downloaded online. You must log in with an account associated with your license. If you need help, contact support@noldus.com and provide your license number or the registered user’s name. To download: - Click Downloads on the website - Under the EthoVision heading, click Versions - Download Ethovision XT - Installation Package - 17.5.1718.zip This is a large ZIP file containing four installation files. Do not run the installer from inside the ZIP. Extract the contents first: - Right-click the ZIP file and select Extract All - Check Show extracted files when complete To begin installation: - Double-click EthoVision XT 17.5 – Setup – [version number].exe - Select Standard installation - Select drivers as needed: - Basler USB camera driver – for Basler USB 3.0 cameras - Basler GigE camera driver or Daheng Galaxy – for GigE Vision cameras - Euresys Multicam – for analog cameras (works only with Picolo Alert encoder board) If installation fails, the installer will generate a log file. Send this file to support@noldus.com for help. Opening EthoVision for the First Time When you launch EthoVision XT for the first time, it will search for a valid license. If you have a hardware license key (dongle): - Use the purple USB dongle labeled "EthoVision" with the license number - If the dongle is for XT 17.0 or higher, it will be recognized automatically - If the dongle is for an earlier version, you’ll be prompted for an upgrade key (enter once; it will be remembered) If you have a software-based activation code: - Select Activate software license key - Choose either: - Floating – Use on multiple computers (one at a time), requires internet access - Fixed – Use offline, activated via one-time internet access or QR code If you’re acquiring data on just one computer, the Fixed license is typically best. You can install EthoVision on additional computers without using the activation code. Start in unlicensed analysis mode to analyze existing data without tracking capabilities. --- ## Installing EthoVision XT 18 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/installing-ethovision-xt-18 Chapter: EthoVision XT System Requirements EthoVision XT 18 runs on Windows 11 Pro. It is not designed for use with the Touch features of Windows. While it is expected to work on Windows 10, this configuration has not been fully tested. Installing EthoVision XT 18 will not remove previous versions, though you may choose to uninstall them to avoid confusion. Uninstalling previous versions will not delete your experiments. Experiments created in older versions can be opened in XT 18, but once saved, they cannot be reopened in previous versions. If you are using EthoVision XT 17 or older, this is not a free upgrade. If you have a hardware license key (dongle), you will need an upgrade key. If you have an active NoldusCare contract, the registered user should have received the upgrade key. Otherwise, contact your sales representative to purchase one. Software-based licenses will update automatically if NoldusCare is active; otherwise, a new license must be purchased. Before You Install EthoVision XT New users: You will have received a software activation key. Keep this key ready when launching EthoVision XT. Upgrading users (hardware dongle): You should have received a license upgrade key via email. Have it ready when launching the software. User Rights: Administrator privileges are required to install EthoVision XT. Regional Settings: Avoid using a comma as the decimal separator. To adjust this setting: - Go to Apps > Windows System > Control Panel - Click Clock, Language, and Region - Select Change date, time, or number formats - Click Additional settings MediaRecorder: If you are installing MediaRecorder on the same PC, install it before installing EthoVision XT. To Install EthoVision XT 18 Before installing, close all other applications. If you don’t already have the installation files (e.g., from a USB stick), they can be downloaded online. You will need an account associated with your license. If you don’t have access, contact support@noldus.com and provide your license number or registered user name. To download the installation files: - Click Downloads at the top of the page - Under the EthoVision heading, click Versions - Select EthoVision XT - Installation Package - 18.0.1832 and click Download The ZIP file is approximately 5 GB. Installation will fail if run directly from the compressed folder. You must extract the files first: - Right-click the ZIP file and select Extract All - Check the option Show extracted files when complete Then proceed with installation: - Double-click EthoVision XT - Setup - 18.0.1832.exe - Select Standard installation - Select the required drivers: - Basler USB camera driver – for Basler USB 3.0 cameras (USB connection) - Basler GigE camera driver or Daheng Galaxy – for GigE Vision cameras (Ethernet) - Euresys Multicam – for analog cameras via BNC (Picolo Alert only) If the installation fails, a log file will be generated. Send it to support@noldus.com for assistance. Opening EthoVision for the First Time On first launch, EthoVision will check for a license. Hardware license key (dongle): - This applies primarily to users upgrading from previous versions - Use the purple USB dongle labeled “EthoVision” with the license number - If compatible with XT 18, it will be detected automatically - If not, you’ll be prompted for an upgrade key. Enter it once; it will be remembered by the dongle Software-based activation: - Most new users will have a software activation key instead of a dongle - Choose Activate software license key - Select either: - Floating license – use on multiple PCs (one at a time), requires internet - Fixed license – use offline; activation via internet or QR code For data acquisition on a single system, a Fixed license is typically recommended. You may install EthoVision on additional systems without an activation key. Use unlicensed analysis mode to access full analysis features (tracking and acquisition will be disabled). --- ## Missing data in EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/missing-data-in-ethovision-xt Chapter: EthoVision XT Troubleshooting Missing Data in EthoVision XT Missing data may result from suboptimal video, camera, or detection settings. Indicators include: - High values for Missed Samples, Interpolated Samples, or Subject Not Found - Gaps in integrated visualization graphs - Gray segments in the track visualization - Total arena time is less than trial duration - Dashes or asterisks in the Track Editor sample list Checking for Missing Data Counts for Missed Samples, Interpolated Samples, and Subject Not Found appear at the bottom of the Detection Settings and Acquisition screens. High values appear in red: You can also review these values in the Trial List by enabling them via Show/Hide > Variables. Missed Samples When Tracking Live Missed Samples indicate that EthoVision was unable to analyze a frame. This may occur if: - The camera skipped frames (USB webcams, poor cables) - Exposure time is too high (especially on Basler cameras) - The computer cannot keep up with complex tracking tasks (e.g., color detection, multiple animals, high resolution) If needed, use Save video and track later during acquisition, then select Track next saved video file afterward: When Tracking from Video Files Enable the DDS checkbox in Acquisition for optimal tracking speed: Missed Samples from video files typically indicate dropped or poorly encoded frames. Always choose fixed frame rates when converting videos. Interpolated Samples When Dropped Frames Correction is enabled, EthoVision will interpolate missed samples: This is acceptable if interpolation remains below 1%. High values should still be addressed by improving underlying camera or detection performance. Subject Not Found This occurs when EthoVision cannot locate the animal. Causes may include: - Animal is physically missing or hidden (e.g., inside shelter) - Detection settings are inadequate Note: Every Missed Sample also generates a Subject Not Found entry. Fixing Minor Missing Data Interpolation in Track Editor - Go to Track Editor under Acquisition. - Select a trial from the upper-left menu. - Click Auto Select > Missing Samples > Select All. - Click Interpolate Selection (or press Ctrl+I). Note: Interpolation cannot be applied to the very first or last frame, or to asterisks indicating data before trial start. Track Smoothing Track Smoothing averages data using surrounding points and fills in short gaps. Enable this in the Track Smoothing Profile. Effects can be toggled on/off easily: Redoing Trials If a large portion of data is missing or detection is poor, it may be best to retrack the video. See: Redo a trial in EthoVision XT --- ## My color Basler camera is monochrome in EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/my-color-basler-camera-is-monochrome-in-ethovision-xt Chapter: EthoVision XT Solution: Change the Color Space to YUY2 in EthoVision XT In the Experiment Settings, click on the following icon to access a live image and open the Video Settings window: This opens the live video feed and the settings interface: In the Format tab of the Video Settings window, locate the Color Space field and change it to YUY2. After selecting, wait a few seconds for the image to update. Check the live preview to confirm the issue is resolved. Note: The live image may take a few seconds to refresh after making any changes. For experiments where a monochrome image is preferred, choose Y800 as the color space instead of YUY2. --- ## My image is too dark using a Basler camera URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/my-image-is-too-dark-using-a-basler-camera Chapter: EthoVision XT Solution #1: Open the Aperture on the Lens More - Twist the aperture ring on the camera lens toward “Open” until the image reaches the desired brightness in your Noldus software. Solution #2: Increase the Gain and/or Exposure in Pylon - Close your Noldus software (e.g., MediaRecorder or EthoVision XT). - Open the Basler Pylon Viewer software. This can typically be found on your desktop or in the Start menu under Basler. - Note: Pylon Viewer is installed automatically with the camera drivers. - Go to Tools > Options and set User Level to Expert or Guru. - In the Devices panel, double-click the Basler device listed under GigE or USB. - In the Features panel, open the Basler camera section and double-click Analog Controls. - Note: If the Features panel is not visible, go to Window > Features to enable it. Increasing the Gain - Under Analog Control, increase Gain (Raw) to a value up to 2. - Note: Higher gain brightens the image but may increase noise or graininess. - Click Continuous Shot to see the live video with your changes. Increasing the Exposure - Ensure Exposure Auto is set to Off. - Set the Exposure Time (Abs) [us] to your desired value (in microseconds) and press Tab to confirm. - Note: Higher exposure = brighter image. Too high may drop frames. Too low may cause flickering. Recommended exposure ranges: - Non-DanioVision: 8,000–25,000 (depending on lighting and gain) - IR Lighting (NIR GigE): ~30,000 - DanioVision: 4,000 (1280×960) or 2,000 (640×480) - Click Continuous Shot again to verify the new frame rate. - Check that the actual frame rate matches your Acquisition Frame Rate (Abs) [Hz] setting (typically 25 or 30). If it's lower, stop Continuous Shot and try one of the following: - a. Lower the exposure time and increase Gain instead - b. Open the lens diaphragm if not already done - c. Lower the video resolution under AOI Controls by reducing Width and Height - Note: Lowering resolution zooms in the image. Ensure Center X and Center Y are enabled. Repeat the above adjustments until the desired frame rate is achieved. Save Camera Settings to User Set - Once satisfied with gain and exposure settings, stop Continuous Shot. - Open Configuration Sets: - Select User Set 1 from the Configuration Set Selector - Click Execute next to User Set Save - Set User Set 1 as the Default Startup Set - Close Pylon Viewer - Note: These settings will now load automatically each time Noldus software starts. Tip: You can save additional configurations to User Set 2 and User Set 3. Use the Default Startup Set option to choose which one should load by default. --- ## My video image is missing/black/white/grayed out in EthoVision URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/my-video-image-is-missingblackwhitegrayed-out-in-ethovision Chapter: EthoVision XT Troubleshooting display issues in EthoVision If EthoVision XT displays incorrectly — such as large black areas or missing interface elements — the issue is typically related to GPU settings or outdated video drivers. This can occur in areas such as Arena Settings, Detection Settings, Acquisition, Track Editor, Manual Scoring, and Integrated Visualization. Solution 1: Change Graphics Settings Configure Windows to use the correct GPU for EthoVision XT: - Go to Start → Graphics Settings. - If EthoVision XT is not listed, click Browse and locate the executable file: - For XT 16 or newer: C:\Program Files\Noldus\EthoVision XT XX\EthoVision.exe - For XT 15 or older: C:\Program Files (x86)\Noldus\EthoVision XT XX\EthoVision.exe - Select EthoVision from the list, click Options. - If it is set to High performance, switch to Let Windows decide and save. If it is already set to Let Windows decide, switch to High performance and save. Note: In some rare cases, using Power saving provides better compatibility. Try this if other options fail. Solution 2: Check Monitor Connection (Desktop Only) Make sure your monitor is plugged into the correct port. Many desktop computers have both onboard and dedicated graphics outputs. Correct: Use ports located in the PCIe expansion slot area (lower back of the case) to ensure you’re using the dedicated graphics card. Solution 3: Update Your Graphics Drivers To check if you're using a generic display driver: - Right-click Start and open Device Manager. - Expand Display adapters. - If you see Microsoft Basic Display Adapter, it means no proper GPU driver is installed. To fix: - Right-click the adapter and choose Update driver, or - Visit the manufacturer’s website (e.g., NVIDIA, AMD, Intel) and download the latest drivers for your GPU. Contact Noldus Support if you need help determining the right driver or installing it. --- ## Picking the right sample rate in EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/picking-the-right-sample-rate-in-ethovision-xt Chapter: EthoVision XT Understanding Camera Frame Rate vs. Sample Rate in EthoVision XT EthoVision allows you to set both a camera frame rate and a sampling rate: - Camera Frame Rate: Set in the Experiment Settings or during Step 1: Video Sources when creating a new template experiment. This defines how many video frames will be recorded per second. - Sample Rate: Determines how frequently EthoVision analyzes the video to extract the coordinates of the animal and other behavioral measures. Camera Frame Rate For most experiments, use standard frame rates: - 25 fps (Europe, 50 Hz power systems) - 30 fps (North America, 60 Hz power systems) Using a frame rate that matches your region's electrical frequency helps avoid video flickering caused by fluorescent lighting. For high-speed behaviors (e.g. startle or escape responses in fish), higher frame rates such as 60 fps may be useful. The Basler acA1300-60 camera supports up to 60 fps. Note: - You may need to reduce the resolution to achieve higher frame rates. - Check the Missed Samples and Interpolated Samples (if shown) in the Detection Settings or Acquisition. These should remain below 1%. - If your system cannot track in real time at the desired frame rate, consider enabling “Save video only and track later” in Acquisition. Important: The camera frame rate is locked once data acquisition begins and cannot be changed within the same experiment. Sample Rate The Sample Rate is set in the Detection Settings and determines how often EthoVision analyzes video frames. It can never exceed the camera's frame rate. Examples based on 25 fps: - 25 samples/sec = every frame - 12.5 samples/sec = every other frame - 8.333 samples/sec = every third frame Recommended Sample Rates - Rats (center point only): 5–8 samples/sec - Mice (center point only): 10–15 samples/sec - Rats or Mice (nose + tail): 25–30 samples/sec - Zebrafish (adults): 5–6 samples/sec - Zebrafish (larvae): 30 or 60 samples/sec Tracking at unnecessarily high sample rates may introduce jitter or noise, exaggerating movement data. For Activity or Mobility measurements, higher sample rates may reduce the ability to detect meaningful changes due to less variation between closely spaced frames. Tip: Changing Sample Rate Mid-Experiment Although you cannot change the frame rate mid-experiment, you can use a new Detection Settings profile with a different sample rate. However, do not mix data with different sample rates in the same analysis, as the results may not be directly comparable. --- ## Play a tone as a stimulus from the EthoVision XT trial control URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/play-a-tone-as-a-stimulus-from-the-ethovision-xt-trial-control Chapter: EthoVision XT Play a tone as a stimulus from EthoVision XT In general, there are two approaches for creating a sound stimulus during an EthoVision trial. You can either use a sound-producing device that takes a TTL input or play a tone over the computer speaker. The latter is only recommended when there is only a single arena or when sound presentation will be synchronized across all arenas. Also note that when using a computer tone, the volume will depend on the computer’s volume setting, and any other computer sounds will also be audible through the same speaker. If you are using a PhenoTyper, there is a built-in tone stimulus which can be used instead. Use a TTL device To set up a TTL-controlled sound stimulus, you’ll need the Trial & Hardware Control Module and either the USB I/O Box or Mini USB I/O Box. You’ll also need a suitable cable from the RJ45 connectors on the I/O box to your TTL device. Since every device is different, consult Noldus technical support if you need assistance or want to purchase a compatible cable. In the Experiment Settings, check the box for "Use of trial control hardware". (If this option is not visible, the Trial & Hardware Control Module is not available.) Then click the Settings button next to it. Select the appropriate I/O box. For the TTL port connected to your sound device, set the device type to "Custom Hardware". In the Arena Settings, click the Arena-Hardware Mapping button in the lower right. If you have a single arena, each device should appear on its own line. If not listed, click Add Device. Ensure the device appears under Arena 1. The Device Name listed here is how it will appear in the Trial Control Settings. For multiple arenas, each type of device should have its own line. For example, a Tone device would have one line, with individual devices selected in each arena column. The Device Name shown is what appears in the Trial Control Settings. You can test the device by selecting it for the arena and clicking Test. Use "Output 1 High" and click Test to activate output 1, and "Output 1 Low" to deactivate it. Similarly, "Output 2 High" and "Output 2 Low" control the second output on the TTL port. In the Trial Control Settings, add a Hardware Action, select the device, and choose Output 1 (or 2) High to activate it or Output 1 (or 2) Low to deactivate. Insert these actions where appropriate in your trial control sequence. Use an external command To create a tone using an external command, download the required files from here: Beep files Right-click the downloaded file and choose "Extract All." Copy or move the three files it contains to: C:\Users\Public\Documents\Noldus\EthoVision XT (Note: You may use another folder, but if so, edit the "beep.bat" file to reflect the new location.) Edit the "beep.ps1" file if you want to change the frequency (the first number, default is 1500 Hz) or the duration (the second number, default is 1000 ms or 1 second). In EthoVision’s trial control settings, add an External Command action. Click the ... button, change the file type in the bottom-right to "Batch Files (*.bat; *.cmd)", and select the beep.bat file. You can leave the "Command line options" field blank. In recent EthoVision versions, use the Test button in that dialog to check whether the sound plays as expected. --- ## Randomizing Events using EthoVision XT Trial Control URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/randomizing-events-using-ethovision-xt-trial-control Chapter: EthoVision XT Randomized Trial Control Settings in EthoVision XT EthoVision’s trial control settings allow you to plan sequences of events during a trial with specified delays and durations. However, sometimes it’s beneficial to introduce randomness into those sequences for experimental variability. Option 1: Multiple Profiles The simplest method is to create multiple Trial Control Settings profiles and randomly assign one per trial. This maintains simple trial logic and allows you to group trials for analysis based on profile selection. Option 2: Randomization Within a Single Profile You can also incorporate randomization into a single profile using the methods below. Random Durations Use the Time Condition block with a random duration instead of a fixed delay: Random Events and Sequences To randomly select between different events (e.g., a tone vs. noise stimulus), you can use Trial Control Variables. - Create a variable using the “TC Variables…” button. - Use the “Trial Control Variable Action” to assign a random value (e.g., 0–10). - Add conditional logic using “Trial Control Variable Condition” blocks to branch based on the random value. Here is an example where a random number is used to select between a noise or tone stimulus, followed by a randomized delay: - Diverging arrows: All paths execute unless each has a condition that ensures only one becomes true. - Converging arrows: Use an Operator to define when the flow continues (e.g., when Any condition is met). Randomized Events with Count Limits To ensure a fixed number of stimulus presentations (e.g., 5 tone and 5 noise), use additional variables to count how many times each stimulus has been shown. If a stimulus reaches its limit, the logic switches to the other option. This structure adds counting logic to the random selector: Call the sub-rule a fixed number of times (e.g., 10) to distribute stimulus presentations randomly but evenly: Flexible Triggers Beyond Zones While zones are common triggers, EthoVision XT can also initiate events based on: - Activity level - Velocity or turning angle - External sensors (e.g., lever presses, nose pokes) This makes it possible to design complex, behavior-driven experiments using randomized and conditional event sequencing. --- ## Redo a trial in EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/redo-a-trial-in-ethovision-xt Chapter: EthoVision XT EthoVision XT can be used to track in real-time, but sometimes after the trial it becomes apparent that the animal was not tracked well, the arena was miscalibrated, or for other reasons the track is not correct. If you recorded a video during the trial, you can retrack that video in the same experiment. Note that retracking is not needed if you simply want to add or change zones for analysis. You can make those changes in the arena settings originally used to acquire the trial. However, the outline of the arena itself, the calibration, and any zones used for trial control or hidden zones cannot be changed after acquisition. 1. Clear and redo a trial If you were tracking live and recorded a video, to redo a trial, in the Acquisition section on the right side under Redo Trial, click the Select button: 2. Select the trial(s) to redo Pick the trial you want to redo, and choose the option "Clear tracks but re-use the video." That will clear the track but keep the trial in the list with the recorded video. You can repeat this for as many trials as needed. Note: If your experiment originally used video files rather than a live camera, the option will be "Clear tracks but re-use the video reference." This behaves the same, allowing retracking of the original video. Alternatively, for video-based experiments, you can delete the trial and track the video in a new one. 3. Track saved video trials You’ll now be able to select "Track the next saved video trial" in Acquisition and begin retracking. Before starting, go to the Trial List and ensure the correct detection and/or arena settings are selected for that trial. By default, retracking uses the "DDS" (Detection Determines Speed) mode, meaning it will proceed as fast as possible — often faster than real-time. If you have many trials to redo, you can select them all first, update the detection settings per trial in the Trial List, then choose "Track all saved video trials" in Acquisition. It will run through all selected trials automatically. Trials that have been cleared but not yet retracked will show a status of "Postponed" in the Trial List. This indicates that the trial exists but the track data has not yet been reacquired. Create a new experiment Alternatively, you can create a new experiment and reuse videos from the original. In this case, you can configure arena and detection settings based on the existing video files. To do this, create a New Template Experiment, choose the Custom Template option, and select your original experiment as the template. This copies all settings but no data. Be aware that this process may take time if the original experiment contains a large amount of data, as the system duplicates the full experiment first and then removes the data. The original experiment’s videos will be available in its Media Files folder. The advantage of using a new experiment is that you can directly reference the videos while setting up the arena and detection settings. --- ## Reinstalling the Picolo Alert drivers for EthoVision URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/reinstalling-the-picolo-alert-drivers-for-ethovision Chapter: EthoVision XT Picolo Alert is used as the framegrabber card for EthoVision XT 14 and up. This card has four round metal BNC ports directly on the back of the computer, with a small red block of tiny DIP switches next to input 1. Picolo Diligent looks the same from the outside of the computer, but was used only in much older systems. If your system originally had EthoVision XT 8 or earlier, and was running an older 32-bit version of Windows, it would have had the Diligent, not the Alert, unless you upgraded the card when upgrading to EthoVision XT 14 or 15. The Picolo Diligent will not work with Windows 10 or any 64-bit version of Windows (other Picolo cards do work in these versions). If the card has one wide connector on the back of the computer, with a breakout cable splitting into 6 or 10 short (1’) black cables each with a round metal numbered BNC connector on the end, that is the Picolo U4 or U8, not the Picolo Alert. Reinstall the Picolo U4 or U8 Reinstall the Picolo Diligent When is reinstallation required? If your card is the Picolo Alert but it is not recognized by EthoVision, please follow the directions below to uninstall and reinstall the card. Do not install drivers for other Picolo cards (e.g., do not install the Picolo U4-U8 drivers as they will conflict). Note that this card may also cease operating if the computer has gone into Sleep or Standby mode. This can be resolved by simply shutting down the computer and then restarting it. The computer should be set so that it never goes into Sleep or Standby, and disable Fast Startup, to avoid this issue. If the card is recognized by EthoVision, but the image is all black or all white, the problem is more likely with the camera, cables, or connections. Check that the camera has power and is connected to the computer. Uninstall the Picolo Alert You’ll need to uninstall the card first if drivers were ever previously installed and are not currently working. Uninstall the driver from the Device Manager: - In Windows 10, right-click the Windows logo in the lower left corner of the screen and then pick Device Manager. - Click the triangle next to "Euresys capture devices" to expand it. Locate PICOLO Alert PCIe. Right-click on it and select Uninstall. - - If this item is missing from the Device Manager, you can proceed with the next step. Uninstall the driver from the programs list: - In Windows 10, click the Windows logo in the lower left corner of the screen, click the Settings gear, and then click Apps. - Pick Euresys Multicam x.x.x.x (where x.x.x.x is the version number of the drivers installed) and click the Remove button to uninstall. - If other Euresys or Picolo drivers are installed, remove them too. Install the Picolo Alert - If you uninstalled the drivers as directed above, reboot the computer. - You’ll need the file multicam-win10-6.15.1.3573.exe. If you have the installation USB stick for EthoVision, it can be found in the folder \Drivers and tools\Drivers\Euresys MultiCam. Otherwise, it can be downloaded here: Picolo Alert driver - Double-click the downloaded file to install the driver. - Open EthoVision and try it out. EthoVision should detect the card and, assuming you have a camera connected, should be able to get an image from it. If it offers the card as an option for live tracking but you get no image, the drivers and card are ok but there is an issue with the camera or the camera's connection with the card. In that case, check the connections. --- ## Reinstalling the Picolo Diligent drivers for EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/reinstalling-the-picolo-diligent-drivers-for-ethovision-xt Chapter: EthoVision XT Picolo Diligent was used as the framegrabber card for EthoVision XT versions 4–8 and continued to be supported in versions 9 and 10. This card is only usable in Windows XP 32-bit and Windows 7 32-bit. If you have a 64-bit version of Windows or Windows 10, this is the wrong card. In those cases, you might have the Picolo U4, U8, or Alert instead. The Diligent has four round metal BNC connectors on the back of the computer, along with a small red block of DIP switches, just like the Picolo Alert. Starting in EthoVision XT 8, we shipped the Picolo U4 or U8 instead of the Diligent, which had been discontinued. You can distinguish between the two cards by looking at the back of the computer. The Diligent has four BNC ports directly on the computer. The Picolo U4 has one wide connector with a breakout cable that splits into 6 short (1’) black cables with numbered BNC connectors. If the cable splits into 10, that’s the Picolo U8. The U4 and U8 use different drivers. Newer systems with EthoVision XT 14 and up may have the Picolo Alert. This card looks the same as the Picolo Diligent but will not work in older EthoVision versions. Reinstall the Picolo Alert Reinstall the Picolo U4 or U8 When is reinstallation required? If your card is the Picolo Diligent but it is not recognized by EthoVision, please follow the directions below to uninstall and reinstall the card. Installing the wrong driver will prevent the card from working, so double-check that you have the Diligent. Note that this card may stop working if the computer goes into Sleep or Standby mode. Restarting the computer usually resolves this. To prevent recurrence, disable Sleep/Standby and Fast Startup in Windows. If EthoVision detects the card but the image is all black or white, the issue is likely with the camera, cables, or connections. Ensure the camera has power and is properly connected. Uninstall the Picolo Diligent You’ll need to uninstall the card if previously installed drivers are no longer functioning. Uninstall from Device Manager: - Make sure EthoVision is closed. - Go to Start menu > Control Panel > System > Hardware tab > Device Manager. - Expand the Euresys section and locate Picolo Diligent. - Right-click on Picolo Diligent and select Uninstall. - If this item is missing, proceed with the next step. Uninstall from Programs: - Go to Start menu > Control Panel > Add or Remove Programs. - Find MultiCam x.x.x.x (where x.x.x.x is the driver version) and click Remove. - Remove other installed Euresys or Picolo drivers as they may conflict. Install the Picolo Diligent - After uninstalling the drivers, reboot the computer. If you just installed the card, the system should be booting up. In either case, ignore the prompt to install new hardware (click Cancel). - You will need the file multicam-6.7.1.1574.exe. It can be found on the EthoVision installation CD in the folder \Drivers\MultiCam Driver or downloaded here: Picolo Diligent driver - Double-click the file to install the driver. - Reboot the computer again. - Open EthoVision and verify that it detects the card. If the card is listed for live tracking but no image appears, the issue is likely with the camera or its connection. --- ## Reinstalling the Picolo U4 or U8 for EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/reinstalling-the-picolo-u4-or-u8-for-ethovision-xt Chapter: EthoVision XT The Picolo U4 H.264 and Picolo U8 H.264 were used as the framegrabber cards for EthoVision XT versions 8–14 and continue to be supported in version 15. These cards are not supported in EthoVision XT 16 or later. They are compatible with Windows 7, 8, and 10, both 32-bit and 64-bit. The Picolo U4 and U8 have a single wide connector at the back of the computer, connected to a breakout cable that splits into either 6 (U4) or 10 (U8) short black cables with round, metal, numbered BNC connectors. If your card does not have a breakout cable and instead features four round metal BNC connectors, it is likely the Picolo Alert or Picolo Diligent. In that case, do not use the drivers listed here. Follow the appropriate instructions for your card: Reinstall the Picolo Alert Reinstall the Picolo Diligent When is reinstallation required? If your card is the Picolo U4 or U8 but is not recognized by EthoVision, follow the steps below to uninstall and reinstall the card. These two cards share the same drivers, but you must not install drivers for other Picolo cards, such as Multicam drivers, as they will cause conflicts. Note: This card may stop functioning if the computer enters Sleep or Standby mode. This can typically be resolved by shutting down and restarting the computer. To prevent this, configure Windows to never enter Sleep or Standby, and disable Fast Startup. If the card is detected by EthoVision but the image is entirely black or white, check the power and connection of the camera. Uninstall the Picolo U4 or U8 Uninstalling the card involves removing it from both the Device Manager and the Programs list. Uninstall from Device Manager: - In Windows 7: Go to the Start menu, select Control Panel, choose Hardware and Sound, then click Device Manager. - In Windows 10: Right-click the Windows logo in the lower-left corner, then select Device Manager. - Expand Sound, video and game controllers. - Find PICOLO U4 (or U8) H.264 Device. Right-click it and select Uninstall. - If this item is missing, you may proceed to the next step. Uninstall from Programs list: - In Windows 7: Go to the Start menu, open Control Panel, and choose Uninstall a program. - In Windows 10: Click the Windows logo, open Settings, then go to Apps. - Locate Euresys Picolo U4-U8-U16 H.264 x.x.x.x (version number may vary) and click Remove. - Also remove any other installed Euresys or Picolo drivers to avoid conflicts. Install the Picolo U4 or U8 After uninstalling the drivers, reboot your computer. If the card has just been installed, let the system boot normally. When prompted to install new hardware, click Cancel. - You will need the file picolo-u4-u8-u16-h264-win-2.5.0.139-ds-driver.exe. If using the installation USB stick for EthoVision, locate it in: \Drivers and tools\Drivers\Euresys. - Alternatively, download it here: Picolo U4-U8 driver - Double-click the file to install the driver. - Launch EthoVision. It should now detect the card. If it appears as a live tracking option but shows no image, the card and driver are functioning properly, but the issue lies with the camera or its connection. --- ## Toolbars in EthoVision have disappeared URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/toolbars-in-ethovision-have-disappeared Chapter: EthoVision XT EthoVision XT 10 and Older In these versions, the menu bar can be accidentally “floated” out of the main window by double-clicking it. If this happens, it may become misaligned or oddly positioned. To fix this: - Double-click any blank space in the menu bar to float or dock it. - If the bar becomes a tall, narrow rectangle and pushes content to the right, click and drag the dashed line at the top of it. Drag it up toward the top bar of the EthoVision window until you see a wide rectangle appear. Release to dock it properly. Advanced Reset via Registry Editor: - Close EthoVision. - Click the Start menu and open the Run dialog. - Type regedit and click OK. - Navigate to the following registry path: HKEY_CURRENT_USER\Software\Noldus Information Technology\EthoVision\x\ Note: Replace x with your version number (e.g., 10). - In the left panel, look for entries starting with Toolbars. - Right-click each of these and choose Delete. - Close the Registry Editor and re-open EthoVision. The toolbar settings will reset to default. Example from EthoVision XT 10: EthoVision XT 11 and Newer For newer versions, the toolbar positions are stored in files within the experiment folder. To reset toolbar layout: - Close EthoVision. - Navigate to the location of the experiment folder: - Default: C:\Users\Public\Documents\Noldus\EthoVision XT\Experiments - If you're unsure of the location, re-open the experiment and check the path shown at the top of the Experiment Settings window. - Open the experiment’s folder in File Explorer. It should resemble the example below: - Delete the highlighted .pob and .pos files. You can: - Right-click each file and select Delete, or - Select them and press the Delete key on your keyboard. - Close File Explorer. - Reopen EthoVision and the experiment. The toolbar positions should now be reset to their defaults. --- ## Unboxing EthoVision: Video guide to set up your PC, camera and monitor URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/unboxing-ethovision-video-guide-to-set-up-your-pc-camera-and-monitor Chapter: EthoVision XT Welcome to your EthoVision setup! Your system has arrived, let's get it up and running. The video below walks you through every step in detail, from assembling the monitor to connecting your camera. --- ## Using the MediaTypeRegistryCleaner URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/using-the-mediatyperegistrycleaner Chapter: EthoVision XT Fixing Video Playback Issues in EthoVision XT (.mp4 files or Media File Error Id 8356) If video files—especially .mp4 files—that previously worked are no longer functioning properly in EthoVision XT, the likely cause is a problem with video codecs. This often occurs after installing, uninstalling, or updating other video software. Error Message: Media File Error (Id 8356) Solution: Use the MediaTypeRegistryCleaner Tool This utility is designed to fix registry issues related to video codecs. Option 1: If You Have the EthoVision XT 16 or 17 Installation USB - Navigate to the folder: \Drivers and tools\Utilities\MediaTypeRegistryCleaner - Proceed with the steps below under How to Use the Tool. Option 2: Download the Tool Download the ZIP file from the link below: https://noldus.sharefile.eu/d-s23c8e2c4233c4e518dcdf773ec402360 Once downloaded: - Right-click the ZIP file and choose Extract All. - Open the extracted folder and navigate to x64. How to Use the Tool - Right-click on MediaTypeRegistryCleaner.exe inside the x64 folder. - Select Run as administrator. - (You may need IT support if you do not have admin privileges on the PC.) - Once the process completes, reboot your computer. Check the Result After rebooting, try opening your video file in EthoVision XT again. If the issue persists, confirm that the video is playable in another application (e.g., Windows Media Player) and contact Noldus Support if further help is needed. --- ## What are the supported video file formats for EthoVision XT? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/what-are-the-supported-video-file-formats-for-ethovision-xt Chapter: EthoVision XT Supported Video File Formats for EthoVision XT 12–16 EthoVision XT supports playback of the following digital video file formats: - MPEG-1 – No longer supported in EthoVision XT 16. - MPEG-2 – A collection of formats; not all are supported. - MPEG-4 – A collection of formats; not all are supported. - MPEG-4 (mp4v) in MP4 container – Created when recording with analog cameras on the Picolo Alert board. - MPEG-4 DivX in AVI container – Format used by Media Recorder and EthoVision with digital cameras. - H.264 AVC in MPEG container – Created by Media Recorder 2.5 and earlier with Euresys Picolo H.264 board. - H.264 AVC in MP4 container – Created by Media Recorder 4.0 with the Picolo H.264 board. - H.264 AVC – A type of MPEG-4 that is supported. - DV-AVI – Uncompressed video from FireWire cameras. Not recommended due to large file size. Important Notes: - DV-AVI is a special case of AVI. EthoVision does not generally support AVI-format video files, even if the extension is .avi. - MPEG-4 files may have the extensions .mpg, .mpeg, or .avi, which does not guarantee compatibility. - Only MPEG-2, MPEG-4, and H.264 files created with Noldus-supplied encoder boards and Media Recorder are guaranteed to work. Video Decoding Support - MPEG-1 / MPEG-2: Decoded using MainConcept Decoder (installed with EthoVision XT) - MPEG-4: Decoded using the standard Windows decoder - H.264: Requires decoding software installed with EthoVision XT Video Formats Not Supported - DivX – except MPEG-4 DivX from Media Recorder - WMV - QuickTime (.mov) - FLV (Flash / YouTube video) - XviD variants of MPEG-4 Testing Other Formats Some unsupported formats may still function. Check for Missing Samples and Interpolated Samples (in Detection Settings or Acquisition). - If either metric is above 1% or shown in red, the video may be dropping frames or have inconsistent timing. Determining the Format To check the format of your video: - Right-click the file - Select Properties Video Resolution Requirements: Resolution must be at least 640 × 480 and no more than 1920 × 1200. To check resolution: - Right-click the video file - Select Properties > Details Converting Videos If your video format is unsupported, use a converter to change the format to a compatible one. MP4Converter (Recommended) In the converter: - Set Profile to General Video Format Recommended Output Formats: - Observer / FaceReader: DIVX, XVID, MPEG-1, or MPEG-2 - EthoVision / DanioScope: MPEG-1, MPEG-2, or DIVX - For MTS files: Convert to DIVX or XVID (MPEG-1 and MPEG-2 often fail) This tool offers a trial to convert the first 3 minutes of a video for compatibility testing. Handbrake (Free) Settings in Handbrake: - Summary tab: Format = MP4 - Video tab: Codec = H.264, Frame Rate = “Same as Source”, enable Constant Framerate --- ## What's new in EthoVision XT 17? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/whats-new-in-ethovision-xt-17 Chapter: EthoVision XT Application - Software license: EthoVision XT can now be purchased with a software license instead of a hardware key. Licenses can be configured as: - Fixed License: Tied to a single computer. - Floating License: Shared across multiple computers (one user at a time). Video Technology - New digital camera drivers: - Basler cameras: updated to driver version 6.2 (from 5.1). - Daheng cameras: updated to driver version 1.12 (from 1.6). - Deep Learning GPU Compatibility: Expanded support for NVIDIA GPUs. Newly tested cards include: - NVIDIA Quadro P2000 - NVIDIA Quadro P2200 - NVIDIA T1200 Trial Control - Permutation for random variables: A Permutation option ensures that a value is not repeated until all other values have been used—useful for randomized trial designs. - Extended Subrule repeat interval: You can now set repeat intervals of up to 99 hours, 59 minutes, 59 seconds (previously limited to 24 hours). Data Acquisition - Import trials from other experiments: Combine data from separate experiments into one dataset—for example, across multiple PhenoTyper cages or DanioVision units. - Show/hide body points in Manual Scoring: Nose and tail-base points can now be toggled on/off in the manual scoring screen for better event annotation. Data Analysis & Visualization - Group charts: Box-and-whisker plots can now optionally display underlying data points (scatter dots). - Customizable tracks: Adjust track thickness and body point size in: - Detection Settings - Integrated Visualization - Improved results table: Headers now clearly indicate independent variables in the statistics output. Documentation Updates - Temperature Control Unit (DanioVision): Now covered in the DanioVision DVOC-0041 Reference Manual. - Calcium Imaging: New chapter added for experiments combining EthoVision XT with Inscopix nVista/nVoke systems. - Fear Conditioning: Quick Start Guide for Ugo Basile systems now integrated into the Application Manual. - Access: Go to Start Menu > Apps > Noldus > EthoVision XT 17 Other Documentation. Experiment Templates - Track3D: Two new experiment templates for 3D tracking: - Flight chamber - Water tank --- ## Why are my trials ending at an exact time (e.g., 10 minutes) even though my Trial Control Settings are set for longer? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/why-are-my-trials-ending-at-an-exact-time-eg-10-minutes-even-though-my-trial-control-settings-are-set-for-longer Chapter: EthoVision XT Trial Ends Too Soon? Check the Maximum Trial Duration Setting If your trial ends earlier than expected without any warning (such as the "Trial duration does not correspond with system time" message), the likely cause is the Maximum Trial Duration checkbox being enabled in your Trial Control Settings. What does this setting do? When checked, this option acts independently from the rest of the trial control logic. A countdown starts the moment you click Start trial in the Acquisition screen. Once the specified time is reached, the trial will end—regardless of the current state of your Trial Control diagram. How to disable it To prevent the trial from ending prematurely, uncheck the “Maximum Trial Duration” box in the Trial Control Settings panel. Note: Settings May Be Locked If the trial control settings have already been used for data acquisition, they become locked and cannot be modified. In this case: - Right-click on the Trial Control Settings profile used in your experiment. - Select Duplicate. - This creates an unlocked copy. Open it, uncheck the Maximum Trial Duration option, and save it. You can now use this modified version for any future trials without imposing a hard time limit. --- ## Why can't I start acquisition in EthoVision XT? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/why-cant-i-start-acquisition-in-ethovision-xt Chapter: EthoVision XT Troubleshooting: Acquisition Cannot Be Started If EthoVision XT does not allow acquisition to begin, it may be due to one of the following causes: - The license is not present or not recognized - No trials have been added to the Trial List - The Trial List is incomplete - One or more settings (Arena, Detection, or Trial Control) are incomplete 1. License Not Present Acquisition requires a valid license: - Hardware License Key: Must be plugged in and recognized. If not detected, you'll see a warning message such as "no valid hardware key is detected." Without it, you can use analysis features, but not start trials. - Software License: Available for EthoVision XT 16 or newer. An active software-based license is needed. If your hardware key is plugged in but not recognized, download and install HASP 8.13 to ensure the driver is installed correctly. 2. No Planned Trials in Trial List The Start Trial button will not appear unless trials are listed in the Trial List. - To add trials: open Trial List and click Add Trials - Or click the + icon in Acquisition (next to the Start Trial button) 3. Trial List Incomplete If you're using the option Track all planned trials and working with video files, ensure that: - Each trial in the list has a video file associated with it - Remove trials without video, or - Switch to Track next planned trial in Acquisition instead 4. Settings Are Incomplete - Arena Settings: Go to Arena Settings and click Validate Setup. Any issues will be shown in a popup message. - Trial Control Settings: Ensure there is a connected path from the Rule Begin to Rule End box. Drag arrows between boxes if necessary. - Detection Settings: If using the Behavior Recognition Module, complete all required sections in the Detection Settings. - Missing or invalid video: If working from video files, ensure a valid video is selected. In Acquisition, click the ... button next to Video to browse and assign a file. Once all components are in place and validated, you should be able to start the acquisition process without issue. --- ## Why is the sum/total of the cumulative time for all of my zones greater than the trial time? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/why-is-the-sumtotal-of-the-cumulative-time-for-all-of-my-zones-greater-than-the-trial-time Chapter: EthoVision XT Why Zone Durations May Not Add Up to Total Trial Time In EthoVision XT, if the sum of time spent in zones does not equal the total trial duration, it may be due to: - The subject was not tracked for the entire trial. - The zones do not fully cover the arena or zones overlap. - The Zone exit threshold allows an animal to be counted in multiple zones at once. 1. The Subject Was Not Tracked for the Entire Trial If the animal disappears from view or if detection is poor, some frames may be missing. When an animal is not detected for three or more consecutive samples, it won’t be counted in any zone. You can check this using the Subject Not Found indicator during the trial or in the Trial List (enable it via Show/Hide > Variables). If there are frequent missing samples, improve detection or retrack the video. For short gaps, enabling Track Smoothing or manually interpolating in the Track Editor may help. 2. Zones Do Not Cover the Entire Arena, or Zones Overlap Zone coverage problems often arise from: - Gaps between zones due to imperfect alignment - Overlapping zones in separate zone groups Correct method (all areas within a single zone group): Incorrect method (multiple zone groups causing gaps or overlaps): Tip: Use the View checkboxes to hide other zone groups for clarity during editing. 3. Zone Exit Threshold Allows Dual-Zone Occupancy The Zone Exit Threshold setting lets you define a buffer around a zone’s edge to avoid spurious exits due to slight movements: Example: - With a threshold of 0.00 cm, quick exits/re-entries are counted as separate visits. - With a threshold of 0.5 cm, minor exits won’t be counted, reducing false positives. However, if the threshold is too large, it may cause the animal to be counted in two adjacent zones simultaneously (e.g., between quadrants in a Morris Water Maze), artificially inflating zone durations. Set the threshold to 0.00 cm if mutual exclusivity is required. --- ## Windows 10 power settings for EthoVision XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/ethovision-xt/page/windows-10-power-settings-for-ethovision-xt Chapter: EthoVision XT With default Windows settings, Windows may shut down during long unattended recordings (e.g., going into sleep or standby mode), and when the computer is turned off, it may go into sleep/standby instead of turning off, which allows memory issues to accumulate rather than cleaning the slate for a new session. Some hardware may not restart properly after sleep/standby, especially Picolo framegrabbers for video capture from analog cameras. The settings listed below will prevent all of these issues and improve performance. Note that these changes will require an administrative password for the computer. - Go to the Start menu, click the Settings gear, then pick System: - Click Power & Sleep on the left: - Click Additional power settings on the right: - This will display “Choose or customize a power plan.” Click Choose what the power buttons do on the left: - You will see the following settings. Click Change settings that are currently unavailable at the top. You will be prompted for an administrative password. - Pick Shut Down (or “Do nothing”) options rather than “Sleep,” and uncheck the Sleep and Hibernate checkboxes. - Uncheck the “Turn on fast startup” option. - Click Save Changes. You will return to the “Choose or customize a power plan” page. - Click Change plan settings next to the selected power plan. For any computer that will be recording unattended, change the “Put the computer to sleep” option to Never. - Then click Change advanced power settings. You will see this window with a variety of options. Click the + sign next to any option to expand it. - Under Hard disk, under Turn off hard disk, click the time highlighted in blue (if it is not already set to “Never”) and enter 0 (this indicates “Never”). - Then click OK to exit. --- ## Camera is not detected in CatWalk XT 10.6 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/camera-is-not-detected-in-catwalk-xt-106 Chapter: Related to CatWalk XT CatWalk XT Camera Not Detected When CatWalk opens, the camera status appears in the lower-right corner. If it displays "Camera detected: No", the camera is not recognized, and acquisition cannot proceed. However, classification and analysis remain available without the camera. Common Causes - Camera has no power - Camera is still establishing a connection - Camera is connected to the wrong port - Camera configuration is incorrect 1. Basic Requirements and Reconnecting The camera must be powered on and connected before launching CatWalk. After powering on, wait up to 2 minutes for the camera to initialize. Once ready, go to Setup > Camera, select Gevicam, and click Refresh. Alternatively, close and reopen CatWalk XT. 2. Camera Has No Power The camera receives power from the Control Unit (mounted at knee level on the CatWalk frame's left side). Ensure: - The Control Unit power switch is turned on. - The power cable is securely connected. - The walkway LEDs are illuminated (green/red). If your system has a second power switch near the glass plate, that switch should also remain on. Note: The walkway lights need ~15 minutes to reach full brightness. Turn on the walkway at least 15 minutes before acquisition or adjusting detection settings. 3. Camera Is Connected to the Wrong Port The camera uses two cables: - Power cable: tan-colored, plugs into the Control Unit’s Cam Supply port. - Network cable: connects directly to a specific PC network port labeled CatWalk Network. Do not plug the network cable into the Control Unit. Doing so may damage the camera. Computers from Noldus have two network ports: - One near the USB ports – not for the CatWalk camera. - One lower down, near metal slots – labeled for CatWalk. Use this port. When connected properly, a green LED will be visible at the camera’s network port (facing the floor), confirming connection to the computer. 4. Testing the Camera Directly - Close CatWalk XT. - Open GEV Player from the Start Menu under Pleora Technologies. - Click Select/Connect. - Choose the eBus Interface and its listed device, then click OK. - Click Play to verify video feed. If successful, click Stop, close GEV Player, and re-launch CatWalk. 5. Reinstalling the Camera Driver - Open Pleora Technologies > Driver Installation Tool from the Start Menu. - In the list of network adapters, find the one labeled Intel Gigabit CT Desktop. - If eBus Universal Pro Driver is not selected, choose it from the Action column and click Install. - Restart the computer after installation completes. --- ## CatWalk XT 10.0, 10.5, or 10.6 does not open URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/catwalk-xt-100-105-or-106-does-not-open Chapter: Related to CatWalk XT CatWalk XT 10: Troubleshooting Startup Issues CatWalk XT 10 may fail to start if the camera is not connected correctly, if file access is restricted, or if settings files are corrupted. Below are the common causes and solutions. Camera Not Connected Properly This issue typically occurs only when the walkway is connected and powered on. If the software starts correctly after turning off the walkway, the issue is likely with the camera connection. Solution: - Turn off the walkway. - Wait 10 seconds. - Turn it back on and wait 1–2 minutes before opening CatWalk. This resets the camera and resolves most connectivity issues. Insufficient Access Rights CatWalk will not start if you're using a Guest or restricted Windows account. Additionally, if the first person to run CatWalk after installation had administrator rights and you do not, it may fail to open. Solution: - Delete the settings files (see below), then start CatWalk using a standard user account. - Opening CatWalk with an administrative account is fine as long as the first launch was with a regular account. Corrupt Settings Files Corrupted or invalid settings files may prevent CatWalk from opening. Settings file location: - C:\ProgramData\Noldus\CatWalk\XT 10.6\Settings\ Note: ProgramData is a hidden folder. Enable hidden folders to access it. Solution: - Remove one or more files from the folder above. - Try restarting CatWalk after each removal. - Missing files will be automatically recreated by the software. If necessary, remove all settings files. Be aware that doing so resets custom settings like detection profiles. Check the Log File If the issue persists, a log file may contain diagnostic information. Log file location: - C:\ProgramData\Noldus\CatWalk\XT 10.6\Log\ Note: ProgramData is a hidden folder. Enable hidden folders to access it. Send the log file to Noldus Support for further assistance. --- ## CatWalk XT classified footprints are grayed out URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/catwalk-xt-classified-footprints-are-grayed-out Chapter: Related to CatWalk XT Data Segmentation Profile Effects in CatWalk XT Using the Data Segmentation Profile, or accidentally selecting it, can cause footprints that have been classified to be excluded from visualizations and statistics. This can lead to confusion if you're not aware that it's active. Filtered-out results may appear as follows in the Run Visualizations: And in the Run Statistics: What Causes This? At the bottom left of the CatWalk interface, under Profiles Explorer, there is a section labeled Data Segmentation Profile. By default, All data is the active profile and will show all collected data. If a different profile is active, such as Data Segmentation Profile 1 or another custom profile, then only data that matches its criteria (e.g., speed, duration) will be shown. This can lead to footprints being grayed out or missing from the results. How to Fix It If you encounter missing or grayed-out results, you can fix this in one of two ways: - Reactivate the “All data” profile: Double-click All data, or right-click it and choose Set as active. - Modify the segmentation settings: If you want to use a segmentation profile but are missing data, adjust its filters (e.g., duration, speed) to be less restrictive. Using segmentation profiles is useful for specific analysis, such as evaluating gait at specific speeds, but it’s important to ensure the correct profile is selected for your analysis goals. --- ## Moving or Relocating the CatWalk XT Walkway URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/moving-or-relocating-the-catwalk-xt-walkway Chapter: Related to CatWalk XT Moving the CatWalk XT System Your CatWalk XT system can be moved if necessary. Begin by disconnecting the two main cables between the walkway and computer: - Network cable: Connects the PC to the camera. On the PC, it plugs into the network card (usually labeled), not into a standard Ethernet port near the USB ports. On the walkway, it connects directly to the camera (not the Control Unit). - USB cable: Connects the PC to the Control Unit. If you are moving the system a short distance (e.g., down the hall), unlock the casters and carefully roll the system. For longer transport, such as relocation to another facility, follow the guidance below. Preparing the Walkway OEM packaging is not required for most relocations. It is generally best to keep the CatWalk walkway assembled, while carefully protecting sensitive components such as the glass plate and illuminated ceiling. Always lock the wheel casters before moving to prevent accidental motion. For added safety, remove the camera and Control Unit before moving, and unplug all cable connections. Documentation Refer to the official documentation available on MyNoldus, including the Walkway Assembly Instructions, for details on mounting and handling the camera and control unit during disassembly and reassembly. NoldusCare Warranty Considerations Be aware that the NoldusCare Terms and Conditions state that hardware warranties may be voided if damage occurs during packaging or transport. Any resulting damage may require purchasing replacement components at your own cost. --- ## My CatWalk XT experiment will not open as it reports that it was made with a previous (or newer) version of the software, but the same version was used. URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/my-catwalk-xt-experiment-will-not-open-as-it-reports-that-it-was-made-with-a-previous-or-newer-version-of-the-software-but-the-same-version-was-used Chapter: Related to CatWalk XT Cannot Open Experiment Due to Version Conflict This issue occurs when attempting to open a CatWalk XT experiment and receiving a warning that the experiment was created with a newer software version—even if the current version is the same one used previously. In some cases, it may incorrectly state that an older version was used but fail to convert the experiment. A typical error message appears as follows: Cause The version.dat file in the experiment folder has become corrupted. This file stores only the version metadata, so replacing it is safe and will not affect your actual experiment data. Solution: Replace the Corrupted version.dat File - Locate a working experiment. If you don’t have one, open CatWalk XT and create a new dummy experiment using Create a new experiment. - Open the experiment folder using Windows File Explorer. The default location is: C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments - In the folder of the working experiment, right-click the version.dat file and choose Copy. - Navigate to the folder of the experiment that won’t open. Right-click its version.dat file, choose Rename, and change its name to version.dat.old. Confirm any warning that appears. - Right-click in a blank area of the folder and select Paste to copy the working version.dat into this folder. Final Step Close any open instances of CatWalk XT. Then relaunch the application and open the previously problematic experiment. It should now load successfully. --- ## Paw prints are not recognized by the Automatic Footprint Classification Module in CatWalk XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/paw-prints-are-not-recognized-by-the-automatic-footprint-classification-module-in-catwalk-xt Chapter: Related to CatWalk XT Handling Dim Paw Prints in CatWalk XT If a paw print is not being assigned a label during automatic classification, it may be due to low intensity values that fall below the threshold defined in the Classification Settings. By default, the minimum acceptable maximum intensity is set to 100. Cause: Low Intensity Prints Low intensity prints can occur if: - The Detection Settings are not optimized for your specific animals. - The walkway lights have not yet reached full brightness. It can take up to 15 minutes for full illumination after turning on the walkway. Tip: Turn on the walkway at least 15 minutes before beginning trials to ensure consistent illumination. Trials started too soon after powering on the walkway may result in dim prints. Solution for Future Trials Adjust your Detection Settings to improve the visibility of the prints. This will ensure more consistent and reliable results during acquisition. Solution for Existing Trials To handle dim prints in previously recorded runs, you can adjust the classification threshold: - Go to Setup > Classification Settings. - Locate the setting labeled "Only assign a label to footprints with a maximum intensity above..." - Lower the threshold value (e.g., reduce it from 100 to 80). - Repeat automatic classification. --- ## Paw prints look incomplete in the Interactive Footprint Measurements screen in CatWalk XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/paw-prints-look-incomplete-in-the-interactive-footprint-measurements-screen-in-catwalk-xt Chapter: Related to CatWalk XT Footprint Display in Interactive Footprint Measurements When a footprint is displayed in the Interactive Footprint Measurements screen, it is enlarged using smoothing and anti-aliasing algorithms. As a result, pixels outside the footprint rectangle—which contain no data—are displayed as blue pixels. This can lead to visual artifacts, especially at lower resolutions, such as cropped or blurred prints. These effects are more noticeable when the resolution is low. Improving Print Detail To improve the clarity and detail of the footprints: - Raise the camera closer to the walkway to increase resolution. - Important: After changing the camera height, you must: - Refocus the camera - Redefine the walkway - Recalibrate the walkway - Redo the detection settings - It's best to make camera adjustments at the beginning of a study. Handling Low-Quality Prints If only a few prints are unclear or cropped, you can simply skip them during measurement. Unmeasured prints will be excluded from the analysis. Viewing Prints in Normal Color If the false color visualization is difficult to interpret: - Right-click on the footprint in the Interactive Footprint Measurements screen. - Select Switch to 'Normal Color' to view the original image. - To return to the enhanced view, right-click again and select Switch to 'False Color'. --- ## Running out of free memory during acquisition in CatWalk XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/running-out-of-free-memory-during-acquisition-in-catwalk-xt Chapter: Related to CatWalk XT Insufficient Memory Error During Acquisition During acquisition, you may see this error message: This indicates there is insufficient free memory to record acquisition data. Common causes include: - Insufficient RAM - Other applications running in the background - Excessively long runs - Unclean walkway or camera noise - Walkway ceiling being open during trials Recommended Solutions Update CatWalk This issue is resolved in CatWalk XT 10.7, available through MyNoldus. This is a free upgrade for users of CatWalk XT 10.0 or later. Note: CatWalk XT 10.7 requires the newer control unit (a black box mounted on the CatWalk frame). If you are using older hardware, CatWalk XT 10.0 is the latest supported version. Contact Noldus for hardware upgrade options. Add RAM to the Computer We recommend at least 16 GB of RAM. Computers with only 8 GB may struggle with modern memory usage patterns, especially under Windows 10. This error early in acquisition is often resolved by adding more RAM. Important: This refers to system memory (RAM), not storage space on the hard drive. Close Other Applications Background applications, especially web browsers, use memory. Close all non-essential software before running CatWalk XT. Reduce Run Length Long runs require more memory. Set the maximum run length to 10 seconds (or up to 15 seconds for slower rats) to reduce resource use and improve efficiency. Clean the Walkway Dirt or previous prints cause noise that increases memory usage and reduces classification accuracy. Clean the walkway with glass cleaner or diluted ethanol between each animal and click Snap Background after cleaning. Reduce Camera Noise - Ensure Camera Gain in Detection Settings is ≤ 20. - If needed, increase Green Walkway Light slightly to reduce the required gain (e.g., 16.0 V for rats, 16.5 V for mice). - Set the Green Intensity Threshold high enough to eliminate noise but still capture prints. Keep the Ceiling Closed Opening the ceiling during a run introduces a large dark area, detected as a giant animal, overwhelming memory. If you must open the ceiling mid-trial (e.g., to redirect the animal), click Stop Acquisition first, then restart the trial as needed. Reboot the Computer Restarting the PC can clear memory leaks and background usage. It is recommended to reboot the system daily. --- ## Setting up the CatWalk XT 10 walkway: calibration and detection settings URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/setting-up-the-catwalk-xt-10-walkway-calibration-and-detection-settings Chapter: Related to CatWalk XT Setting Up the CatWalk XT Walkway Setting up the walkway involves three main steps: defining the walkway, calibrating it, and adjusting detection settings. These steps ensure accurate data and reduce the amount of work needed during classification. In addition to the initial setup, repeat the following when needed: - Define the walkway if the camera height or corridor width is changed. - Calibrate the walkway if the camera height is adjusted. - Adjust detection settings when lighting changes significantly, camera height changes, or switching between animals of different weights. Defining the Walkway This step outlines the working area. Go to Setup > Define Walkway. Resize the white rectangle to match the usable section of the walkway. For larger animals like rats, avoid including the ends of the walkway to prevent tails from affecting results. The rectangle should sit just inside the visible black bottom edges of the corridor walls, minimizing inclusion of the wall edges. Calibrating the Walkway Calibration enables measurements in centimeters instead of pixels. Calibration must be redone after adjusting camera height. Use a calibration sheet (10×20 cm rectangle). Place it face down within the camera view. Go to Setup > Calibrate Walkway. Adjust the white rectangle to align with the calibration sheet, then click OK. - Download calibration sheet (US Letter) - Download calibration sheet (A4) Be sure to print the sheet at actual size, not scaled. Detection Settings This adjusts the camera sensitivity to detect footprints reliably. Redo this step if lighting changes, camera height changes, or if you switch to animals of a different size. Ensure the room is dark, with consistent trial lighting. The walkway ceiling should be lowered. Let the walkway lights warm up for at least 15 minutes. Use an animal of representative size for your trials. Go to Setup > Detection Settings. Start with Auto Detection by clicking Start Auto Detect. Let an animal run across the walkway; the software will adjust sensitivity accordingly. Multiple passes may be needed. After Auto Detection, check if Maximum Green Intensity is between 200–205. Use Reset Prints to clear the value and measure again with a clean run. If intensity is too high, lower the Camera Gain. If too low, increase the gain. If using CatWalk XT 10.6+, you can also increase the Green Walkway Light (default: 16.5V for mice, 16.0V for rats). Adjust by increments of 0.1 if needed. Next, adjust the Green Intensity Threshold to filter out noise while preserving paw print clarity. A high threshold removes more noise but may cut print details; a low threshold shows more detail but may introduce noise. Once adjusted, click OK to finish setup. --- ## There are no rectangles around the paw prints in CatWalk XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/there-are-no-rectangles-around-the-paw-prints-in-catwalk-xt Chapter: Related to CatWalk XT CatWalk XT: Missing or Incorrect Print Detection If too much of the animal is being detected, CatWalk may not properly focus on paw prints. Alternatively, the display of print rectangles might simply be turned off. Too Much Detection When Camera Gain is too high, or there is too much ambient light in the room—especially if the Green Intensity Threshold is set too low—CatWalk might detect parts of the animal’s body (e.g., abdomen or ventral side) as prints. This results in large green areas instead of isolated paw prints, as shown below: This situation becomes especially problematic if the option "Discard incomplete prints at the start and end of a run" is enabled in the Acquisition Settings. When the animal enters the camera’s field of view and its body overlaps the image border, CatWalk will discard all detected areas—including valid prints—due to this setting. How to Resolve - Go to Setup > Acquisition Settings. - Uncheck the box labeled “Discard incomplete prints at the start and end of a run.” - Review your Detection Settings. Lower the Camera Gain and increase the Green Intensity Threshold as needed to ensure only paw prints are detected. Rectangles Not Displayed If no rectangles appear around detected prints, it's possible the display option is turned off. How to Enable Print Rectangles - Right-click in the orange (background) area of the run visualization window. - Ensure the checkbox for “Show Rectangles” is enabled. With these adjustments, CatWalk should correctly detect and display paw prints during analysis. --- ## Understanding Phase Dispersion, Coupling, and Circular Statistics in CatWalk URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-catwalk-xt/page/understanding-phase-dispersion-coupling-and-circular-statistics-in-catwalk Chapter: Related to CatWalk XT In this article - What phase dispersion and coupling measure - How the values are calculated - Interpreting the numbers, including negative values - When to use phase dispersion vs coupling - Why circular statistics matter for these parameters - Recommended tests, tools, and reporting practices Related content: For a shorter, blog-style introduction with visuals, see Understanding phase dispersion in CatWalk. What phase dispersion and coupling measure Phase dispersion and coupling are interlimb coordination parameters in CatWalk. They describe the temporal relationship between two paws during locomotion, answering one question: when one paw completes its step cycle, at what point in that cycle does another paw make initial contact with the ground? The two parameters describe the same underlying measurement. They differ only in how the value is displayed. Parameter Range Best used for Coupling 0 to 100 percent Scanning values, exporting to standard statistical packages Phase dispersion Signed value (can be negative) Circular plots, correct averaging near the wrap point Both are calculated for pairs of paws, with one paw designated as the anchor (the reference cycle) and the other as the target (the paw whose contact is being timed). The paw pair categories Rodent gait analysis groups paw pairs into three anatomical categories, each with distinct expected coordination patterns. Pair type Combinations Coordination pattern Diagonal LF-RH, RF-LH Near-synchronous contact Girdle LF-RF, LH-RH Alternating (front pair or hind pair) Lateral (ipsilateral) LF-LH, RF-RH Alternating (same side of body) How the values are calculated The calculation places the target paw's initial contact on the anchor paw's step cycle, expressed as a percentage of that cycle. Formula (conceptual): (Time of target initial contact − Time of anchor initial contact) / Anchor step cycle duration × 100 percent Example: The right front (RF) paw is the anchor and the left hind (LH) paw is the target. The RF paw's step cycle lasts 20 milliseconds. The LH paw makes its initial contact 15 milliseconds after the RF paw's initial contact. Value = 15 / 20 × 100 = 75 percent The LH paw touches the ground three-quarters of the way through the RF paw's step cycle. Interpreting the values Reference values for a healthy rodent walking at moderate speed Pair type Expected value Physical meaning Diagonal (LF-RH, RF-LH) ~0 percent (or ~100 percent) Paws strike the ground almost simultaneously Girdle (LF-RF, LH-RH) ~50 percent One paw lands halfway through the other's cycle Lateral (LF-LH, RF-RH) ~50 percent Ipsilateral paws also alternate These reference values assume a symmetric walking gait. Trot, bound, and high-speed running patterns produce different expected values. Reading a deviation Observation Likely biological signal Diagonal pairs drift away from 0 percent Forelimb to hindlimb coordination is degrading Girdle pairs drift away from 50 percent Left-right asymmetry (limp, hemiparesis, unilateral injury) Lateral pairs drift away from 50 percent Ipsilateral coordination is off (often cerebellar or spinal) Increased variability across runs Coordination instability, common in ataxia and neurodegeneration Variability across runs is often as biologically meaningful as a shift in the mean, especially in progressive disease models. Understanding negative values in phase dispersion Since CatWalk 10.7, phase dispersion is calculated using circular statistics. This introduces two visible changes for users: - Values can be negative. - Results are displayed on a circular graph rather than a linear axis. Why negative values exist The step cycle is inherently repetitive. The moment labeled 0 percent (start of the cycle) and 100 percent (end of the cycle) are the same instant. On a circle, they occupy the same point at the top. A negative percentage is simply the counterclockwise way of describing a point on the far side of the circle. -19 percent and 81 percent mark the same instant. The target paw's contact occurs 19 percent of a cycle before the anchor's next cycle starts, or equivalently, at 81 percent of the way through the current cycle. Why this matters most for diagonal pairs Diagonal pairs sit right at the 0 / 100 wrap point. In practice, a healthy animal's diagonal readings across a single trial might include values like 98 percent, 2 percent, 99 percent, and -3 percent. These are all near-synchronous contacts. Signed phase dispersion makes the clustering visually obvious. Linear coupling values do not. Phase dispersion vs coupling: when to use each Both parameters carry the same information. The choice comes down to workflow. Use case Preferred parameter Why Reading a single value at a glance Coupling Always positive, simpler to skim Displaying data on circular graphs Phase dispersion Signed values plot symmetrically around a reference point Handing data to Prism or GraphPad Coupling Fewer confusing negative numbers for downstream users Calculating group averages correctly Either, using the circular mean Avoids the wrap-around error Important caveat: switching from phase dispersion to coupling does not remove the circular nature of the data. If your values cluster near the wrap point (0 percent or 100 percent), you still need a circular mean and a circular test. See the next section. Why circular statistics matter The wrap-around problem Linear statistics assume values live on an unbounded number line. Circular data lives on a loop. When averaging or testing values that cross the wrap point, linear methods produce incorrect results. Illustrative example: A trial produces four phase dispersion values: 75, 75, 5, 5. - Linear mean = (75 + 75 + 5 + 5) / 4 = 40 percent - Circular mean = 90 percent (equivalently, -10 percent) The linear mean of 40 percent is misleading. It sits on the opposite side of the circle from where all four values actually cluster. The circular mean correctly identifies the group as clustered near the 0 / 100 wrap point. CatWalk 10.7 calculates the circular mean automatically for group statistics. Users pulling numbers directly from the software get the correct value. Users exporting raw values to Excel and averaging in a spreadsheet do not. When linear tests are safe (and when they are not) If every value in every group sits well away from the 0 / 100 wrap point, a t-test or ANOVA will give a practically similar answer to a circular test. This is often the case for girdle and lateral pairs whose expected values sit near 50 percent. If any values cross or cluster near the wrap point, linear tests can give misleading p-values. Diagonal pairs are particularly vulnerable because their expected value sits right at 0 percent. Rule of thumb: check where your data lives on the circle before you pick the analysis. Girdle and lateral pairs are usually safe for linear tests. Diagonal pairs are not. Recommended statistical tests Comparison Test Notes Two groups, well-concentrated data Watson-Williams Circular analog of the t-test; assumes von Mises distribution Two groups, no distributional assumption Watson's U² Nonparametric, safer default Two or more groups Mardia-Watson-Wheeler Nonparametric Repeated measures or mixed designs Circular mixed models Available in R via bpnreg, or a GLMM on sin/cos components Software support Software Circular statistics support R Robust support via the circular, bpnreg, and CircStats packages Python Available via pycircstat, astropy.stats.circstats, and pingouin GraphPad Prism Not natively supported SPSS Not natively supported For most behavioral cores and users comfortable with light scripting, R with the circular package is the most direct path. Reporting circular statistics in publications When reporting phase dispersion or coupling results in a manuscript, best practice is to include: - The circular mean (not the linear mean) - A measure of concentration: either the angular deviation or the mean resultant length (r), which ranges from 0 (uniform) to 1 (perfectly concentrated) - The circular test used and its assumptions - The test statistic and p-value The published CatWalk literature has historically applied linear statistics to these parameters. That precedent does not make it correct, and it does not protect authors from reviewers who understand circular data. As circular graphs and statistics become more visible in the software (introduced in 10.7), rigorous reviewers are increasingly likely to expect the appropriate methodology, especially for studies with values near the wrap point. Quick reference summary Question Answer What does 75 percent mean? The target paw contacts the ground three-quarters of the way through the anchor paw's step cycle What does -19 percent mean? Same point on the cycle as 81 percent Why do diagonal pairs show values near 0 percent? Diagonal paws normally strike the ground almost simultaneously Why do girdle and lateral pairs show values near 50 percent? These pairs alternate: one lands halfway through the other's cycle Can I use a t-test in Prism? Sometimes. Safe if values sit away from 0 / 100. Not safe for diagonal pairs or any data clustered near the wrap point What test should I use instead? Watson's U² for a nonparametric two-group comparison; Watson-Williams if data is well-concentrated Where do I get the circular mean? Directly from CatWalk 10.7 group statistics, or calculate in R with the circular package Related content - Blog: Understanding phase dispersion in CatWalk - White paper: What are phase dispersions? (available on the CatWalk resource page) Applies to CatWalk 10.7 and later. For earlier versions, phase dispersion is reported as a 0 to 100 percent value without circular graphing or automated circular means. --- ## DanioScope shows unrealistic high values of heart rate, like 2x the actual heart rate. Why ? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-danioscope/page/danioscope-shows-unrealistic-high-values-of-heart-rate-like-2x-the-actual-heart-rate-why Chapter: Related to DanioScope Incorrect Heart Rate Detection Due to High Video Quality This issue can occur when high-quality video captures too much movement, especially from the heart. This can confuse the software and cause misinterpretation of the heartbeat signal. Check the Activity Plot In the Activity plot: - A represents the true heartbeat waveform. - B and C are narrower peaks making up A. These peaks originate from different parts of the heart — B from wall movement and C from the blood flow immediately following it. Inspect the Power Spectrum The first peak (~105 bpm) corresponds to the general heart rhythm (A). The second, stronger peak results from counting both B and C, effectively doubling the frequency. DanioScope detects this second peak as the heart rate because it has the highest power. Why the Error Happens The secondary wave (C) has an amplitude nearly equal to the primary wave (B), making it appear as a valid second heartbeat. This doubles the frequency in the analysis. How to Fix It Reduce the Heart area to better isolate the desired movement (B). A smaller Heart area limits detection to the heart wall motion, avoiding interference from the blood flow. In the comparison above: - Left: Heart area too large, causing inaccurate detection. - Right: Properly focused Heart area yields correct results.   Tip: For consistent results, use the same magnification level when recording your videos and draw similarly sized Heart areas. --- ## DanioScope shows unrealistic low values of heart rate, like 15 BPM. Why ? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-danioscope/page/danioscope-shows-unrealistic-low-values-of-heart-rate-like-15-bpm-why Chapter: Related to DanioScope Heart Rate Too Low in DanioScope DanioScope calculates heart rate by analyzing changes in the selected heart area of a video. Occasionally, this may result in an unrealistically low heart rate. This typically happens when: - The video has low contrast - The defined heart area includes unrelated motion or noise - A large heart area includes non-heart movements Low contrast can hide the true heartbeat signal, allowing noise or irregular blood movement to dominate the analysis. Example Activity Plot In the plot above, random peaks of high amplitude (due to noise or blood flow) mask the regular but lower true heartbeat signal. Zooming in can help identify which are the actual beats. DanioScope mistakenly selects the highest peak (around 15 BPM) from the power spectrum: This leads DanioScope to incorrectly report a heart rate of 15 BPM. How to Fix It - Play the video and observe the region of the heart that visibly moves. - Draw a smaller heart area tightly around that region. - Rerun the acquisition. Example of a well-defined heart area: Now the correct peak (~180 BPM) is dominant in the power spectrum: DanioScope now reports a heart rate of 183 BPM. Validation Zoom into the activity plot to verify that there are approximately 3 clear peaks per second, confirming the 180 BPM result: Important Tips - This method may not always work if video quality is too low. - Always ensure optimal contrast and sharpness when recording videos to improve DanioScope’s detection accuracy. --- ## Error E01 on the DanioVision Temperature Control Unit URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-danioscope/page/error-e01-on-the-daniovision-temperature-control-unit Chapter: Related to DanioScope Error E01 – Temperature Sensor Not Detected Error E01 indicates that the temperature sensor is not being detected. This usually means the sensor cable is either unplugged or not fully inserted. How to Resolve Check the cable connection between the DanioVision and the Temperature Control Unit: - Ensure there is a cable running from the "Temp" jack on the back of the DanioVision device to the "Temp" jack on the back of the Temperature Control Unit. - This is connector #5 as shown in the image below. - Firmly plug in the cable on both ends to ensure full connection. --- ## Error Messages on the DanioVision Temperature Control Unit URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-danioscope/page/error-messages-on-the-daniovision-temperature-control-unit Chapter: Related to DanioScope DanioVision Temperature Control Unit – Error Codes and LED Indicators The DanioVision Temperature Control Unit (TCU) provides two types of error indicators: - Error codes displayed on the temperature display - Status indicators via blinking LED lights Temperature Display Error Codes If an error is present, the following codes may flash on the temperature display: - E01: Temperature sensor not detected. Check that the cable is connected between the “Temp” ports on the back of both the TCU and DanioVision unit. More information. - E04: Water temperature is more than 0.5°C above the set value. Wait up to 15 minutes for the temperature to stabilize. - E05: Water temperature is more than 0.5°C below the set value. This will self-correct once the temperature adjusts. - Ed1: System error. Refer to the blinking LED indicators for diagnosis. LED Status Indicators The LED lights on the TCU indicate system status and specific error conditions. Filling/Draining Mode - Orange blinking: System is actively pumping — filling, draining, or adding coolant. - Red continuous: No water flow detected for more than 10 minutes. Reset the timer by switching the TCU off and then back to Fill/Drain. Operation Mode - Green blinking: The system is heating or cooling, but has not yet reached the target temperature. - Green continuous: Desired temperature reached. System is ready for use. Error LED Codes If an error occurs, the error light will blink red rapidly in sequences (1–6 blinks), then pause before repeating: - 1 Red Blink: Insufficient water flow. Check the water level, tubing for air bubbles, clogs, kinks, or a possible pump failure. - 2 Red Blinks: Insufficient coolant flow. Verify coolant level and inspect for leaks or blockages. - 3 Red Blinks: Fan malfunction or insufficient speed. Ensure the fan is unobstructed. - 4 Red Blinks: System overheated. Power off the TCU and let it cool. Ensure air vents are not blocked and ambient temperature is below 35°C. - 5 Red Blinks: Electrical fault — simultaneous heating and cooling. Contact Noldus Support. - 6 Red Blinks: SD card issue. Check that the SD card is seated properly, cables are connected, or clear space on the card via a computer. - Red continuous: Temperature deviation >0.5°C. System is actively adjusting back to the target temperature. --- ## DanioScope shows unrealistic high values of heart rate. Why? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-daniovision/page/danioscope-shows-unrealistic-high-values-of-heart-rate-why Chapter: Related to DanioVision DanioScope shows unrealistic high values of heart rate, like 2x the actual heart rate. What is happening? This could happen when the video is of such high quality that it picks too much movement of the heart. First, check the Activity plot. The true heartbeats correspond to the wide waveforms (A). However, each instance of A is composed by a narrow peak (B) and a lower peak (C). The two peaks B and C have equal rhythm, because they result from movements in different parts of the heart. In this case, C represents the flow of blood exiting after the movement of the heart walls. The Power spectrum provides hints about what may have gone wrong. The first peak at about 105 bpm corresponds to the general movement rhythm of the heart (A). The second peak results from counting the peaks B and C together. Because the amplitude of B and C is similar, they are counted as if they were part of a single sequence. The frequency of the waveforms B+C is about two times of that of A. DanioScope takes the second peak (B+C) as indication of heart rate because it is the highest in the spectrum. So why is the second peak of the spectrum so high? The reason is that the second “wave” of activity (C in the Activity plot) is almost as high as the preceding one (B). To reduce this second wave, you probably need to make the Heart area smaller, focusing n the movement that you want to capture. In the following example, I show the Heart area that gives wrong results (left image) and the Heart area that gives good results from the same video. The arrows on the right indicate the movement of the heart’s wall, which produce the first peak in activity (B in the first figure above).  Make sure that you draw the areas of similar size and shape. This is much easier when your video are made at the same magnification level. --- ## DanioScope shows unrealistic low values of heart rate. Why? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-daniovision/page/danioscope-shows-unrealistic-low-values-of-heart-rate-why Chapter: Related to DanioVision DanioScope shows unrealistic low values of heart rate, like 15 BPM. What's happening? This may have to do with a large heart area that contains low contrast pixels. Try to make the heart area smaller, focusing on the region that shows the heart movement, even if this region is smaller than the heart. DanioScope automatically calculates the heart rate based on changes in the selected section of the video. It analyzes the rate of changes to determine the dominant frequency. Occasionally this can result in an implausibly low calculated heart rate. This is most likely when the video has low contrast, and/or when the heart area defined includes noise, or when a large heart area picks movement unrelated to heart activity. Low contrast enhances this effect by covering the true heart beats. In this example, the Activity plot is: Random noise or irregular movement of blood larger than the average can produce the highest peaks in the figure. The peaks of intermediate amplitude are the true heart beats. You can check this by zooming in the plot. The highest peaks are dominant in the resulting power spectrum plot (see “current results”). The highest peak, located at a frequency of about 15 BPM, is the reason why DanioScope thinks that the heart rate is 15. Your task, now, is to modify the heart area in such a way it covers only the true movement of the heart. - Play the video and try to locate the region of the heart which clearly moves. - Draw the heart area around that region, like in this example. - Redo acquisition.  Now the power spectrum shows that another peak, around 180 BMP, has become dominant.  This time DanioScope reports a heart rate value of 183 BPM. You can check the results when you zoom in in the activity plot. A heart rate of 180 should correspond to about 3 peaks per second being clearly displayed in the Activity plot. We recommend to always compare the activity plot with what you see in the video. Note that this solution does not always work. It is always a good idea to make sure that contrast and sharpness in the video image are optimal in order to improve detection by DanioScope. --- ## How to prevent turning off the White Bottom Light in DanioVision URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-daniovision/page/how-to-prevent-turning-off-the-white-bottom-light-in-daniovision Chapter: Related to DanioVision Applies to: DanioVision DVOC-005x systems only. Keep light on after testing A new option has been added to the DVOC-005x Hardware Interface that prevents the system from turning off the White Bottom Light after testing (in Arena Setup or Advanced Trial Control) or after stopping acquisition. This means that once the light has been turned on, for example by opening the Arena Hardware Mapping or Trial Control dialog, it will remain on before, during, and after acquisition. Any hardware protocols that adjust lighting during acquisition (e.g., dark/light transitions in startle response experiments) will continue to work as designed. Note that if a protocol explicitly turns the light off, it will stay off. Why?  In the previous version, the White Bottom Light was automatically turned off when closing a test dialog and when acquisition stopped. This meant subjects could be exposed to a sudden light onset at the moment acquisition began, introducing an unintended stimulus that could confound experimental results. This is especially problematic for protocols such as tapping/startle response experiments, where subjects need to be acclimated to stable light conditions before the actual stimulus is delivered. How to use it? After installing the updated Hardware Interface (DVOC-005x v1.0.14, included with EthoVision XT 19), go to the Default State settings dialog and uncheck "Turn light off after testing or stop acquisition". Make sure to also set the desired light intensity percentage in the Default State settings. The light intensity may change during acquisition depending on what is configured in Trial Control or Advanced Trial Control. The system will use the last applied setting as reference, or the Default State intensity if no other setting has been applied.  How to install Log in to your MyNoldus account. Go to Downloads and click on EthoVision. Then, select the DanioVision tab: Click on the "Hardware Interface DanioVision - White Bottom Light" link and download the .msi package. Double click the file. It will automatically replace the previous HardwareInterface file. --- ## Configuring the Epiphan Broadcaster in FaceReader URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-facereader/page/configuring-the-epiphan-broadcaster-in-facereader Chapter: Related to FaceReader To stream screen capture with an Epiphan Broadcaster in FaceReader, you must change the screen codec from H.264 to Motion JPEG. Step 1: Configure the Epiphan Broadcaster - Open a web browser and go to http:///admin. - Login with username admin; leave the password blank unless configured otherwise. - In the left menu, click Stream Setup. - At the top of the page, change the codec setting to Motion JPEG from the drop-down menu. - Scroll to the bottom of the page and click Apply. - Click on Info to view the streaming URL. - Copy the MJPEG stream URL, which will look like: http://:1881/stream.mjpg. Step 2: Configure FaceReader - Create a new project and participant in FaceReader, if not already done. - Click the camera icon to open the camera selection dialog. - Select IP Camera from the drop-down menu. - Paste the MJPEG stream URL into the Source URL field. - Set the frame rate to 15. - Select the MJPEG stream type. Click OK to apply the settings. FaceReader will begin showing the video feed from the Broadcaster. --- ## FaceReader will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-facereader/page/facereader-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: Related to FaceReader This error in the installation log file indicates one of the following issues: You do not have the necessary rights to install software Your account does not have the required administrative rights to install software. Check that you do have administrative rights, or log into the computer using an account which does. Depending on how your systems are configured, you might require the assistance of your local IT department for installing software. Windows is currently updating Windows is in the process of installing updates, and the FaceReader installation cannot begin until it is finished. Complete any system updates and try again. Reboot the PC after Windows updates complete to ensure no updates are pending. There is a problem with system files Malware or a computer virus has modified system files. Run a scan of the system. --- ## Selecting an Axis IP camera in FaceReader 6 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-facereader/page/selecting-an-axis-ip-camera-in-facereader-6 Chapter: Related to FaceReader Adding an Axis IP Camera Stream To add an Axis IP camera stream in your project: - Click the Camera Analysis button to add a new camera analysis. - Fill in the following settings: - Select Camera: Choose IP Camera from the drop-down menu. - Source URL: Use the format http://xxx.xxx.xxx.xxx/axis-cgi/mjpg/video.cgi Replace xxx.xxx.xxx.xxx with the IP address of the camera (e.g., 192.168.200.1 for the first camera). - Stream Type: Select MJPEG. - Secured: Check this box and enter the camera’s username and password. - If desired, check Use as default camera to apply these settings for future sessions. - Click OK to confirm and connect. The live video feed will display in the preview panel on the left. --- ## Selecting an Axis IP camera in FaceReader 7, 8, or 9 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-facereader/page/selecting-an-axis-ip-camera-in-facereader-7-8-or-9 Chapter: Related to FaceReader Connecting an Axis Camera in FaceReader 7, 8, or 9 - In the Select Camera window, choose IP Camera from the Select Camera drop-down menu. - Under Source URL, enter the IP address of your camera. For Noldus-configured cameras, this is typically: - 192.168.200.1 for the first camera - 192.168.200.2 for the second camera, and so on The IP address may also be labeled directly on the camera. - For Axis IP cameras, enter one of the following (replacing the IP address with the correct one from step 2): - http:///mjpg/video.mjpg - http:///axis-cgi/mjpg/video.cgi - Under Frame rate, set your preferred rate (default is 5 fps). - If your camera requires authentication, check the Secured option and enter the Username and Password. - Select MJPEG as the Stream Type. - Optionally, check Use as Default Camera if you want FaceReader to remember this camera for future use. If everything is set correctly, the camera view should appear in the Preview image window. --- ## What are the supported video formats for FaceReader 8? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-facereader/page/what-are-the-supported-video-formats-for-facereader-8 Chapter: Related to FaceReader Supported Video Formats in FaceReader 8 Container Code Name / Encoder mpg mpg1 MPEG-1 Part 2 mpg mpg2 MPEG-2 mpg H264 H.264 / MPEG-4 vob (DVD) mpg2 MPEG-2 mp4 mp4v MPEG-4 Video mov mp4v MPEG-4 QuickTime avi XVID XviD ISO MPEG-4 avi XVID XviD 1.1.0 Final avi DIB (_RGB) BI_RGB Raw Bitmap avi DIV3 DivX 3 Low-Motion avi DIV5 DivX 5.x / 6.x avi DIVX DivX 4 avi dvsd DVC / DV Video avi DX50 DivX 6.0.0 avi DX50 DivX 5.x avi CRAM Microsoft Video 1 avi cvid Cinepak avi IV32 Indeo 3.x avi MJPG Motion JPEG avi MP42 S-MPEG 4 version 2 avi WMV3 WMP v9 (VC-1 Simple/Main) asf (.wmv) WMV1 WMP v7 asf (.wmv) WMV2 WMP v8 asf (.wmv) WMV3 WMP v9 (VC-1 Simple/Main) asf MP43 S-MPEG 4 version 3 3gp s263 ITU H.263 video (3GPP) Notes - The container is not always the same as the file extension. Different containers may use the same extension. - To identify your video’s format, you can use the GSpot codec information utility. --- ## What are the supported video formats for FaceReader? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-facereader/page/what-are-the-supported-video-formats-for-facereader Chapter: Related to FaceReader Supported video formats in FaceReader 10 Most common video formats (300+ containers and codecs) are supported in FaceReader 10. However, if you encounter playback issues, try converting the video to an MP4 container with H.264 video and AAC audio using HandBrake or similar software. Supported video formats in FaceReader 9 FaceReader 9 supports a wide range of video containers and codecs. Below is a list of compatible formats: Container Codec Name/Encoder mpg mpg1 MPEG-1 Part 2 mpg mpg2 MPEG-2 mpg H264 H.264 / MPEG-4 mpg H265 H.265 / MPEG-4 vob (DVD) mpg2 MPEG-2 mp4 mp4v MPEG-4 Video mov mp4v MPEG-4 QuickTime avi XVID XviD ISO MPEG-4 / XviD 1.1.0 Final avi DIB (_RGB) BI_RGB Raw Bitmap avi DIV3 DivX 3 Low-Motion avi DIV5 DivX 5.x / 6.x avi DIVX DivX 4 avi dvsd DVC / DV Video avi DX50 DivX 5.x / 6.0.0 avi CRAM Microsoft Video 1 avi cvid Cinepak avi IV32 Indeo 3.x avi MJPG Motion JPEG avi MP42 S-MPEG 4 version 2 avi WMV3 WMP v9 (VC-1 Simple/Main) asf (.wmv) WMV1 WMP v7 asf (.wmv) WMV2 WMP v8 asf (.wmv) WMV3 WMP v9 (VC-1 Simple/Main) asf MP43 S-MPEG 4 version 3 3gp s263 ITU H.263 Video (3GPP) Notes - Container vs. File Extension: The container is not the same as the file extension. Multiple containers may use the same extension. - Video Format Identification: If you're unsure of a file’s format, use a tool like GSpot (free download) to identify codec and encoding info. Supported File Extensions in the Project Wizard The following file extensions are compatible with FaceReader's project wizard: - .mpg - .mpeg - .avi - .wmv - .mov - .asf - .3gp - .vob - .mp4 - .mkv - .flv --- ## When using the Baby model of FaceReader 9 the automatic analysis did not detect any negative valences across the whole dataset. URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-facereader/page/when-using-the-baby-model-of-facereader-9-the-automatic-analysis-did-not-detect-any-negative-valences-across-the-whole-dataset Chapter: Related to FaceReader FaceReader 9 Baby Model – Negative Valence Detection Issue In the initial release of FaceReader 9, an issue was identified with the Baby model: automatic analysis did not detect any negative valences across the dataset. As a result, expressions that were actually negative or very negative were misclassified as having positive valence. Do You Need to Re-analyze Videos? No. Fortunately, re-analysis is not necessary. This is because valence can be recalculated directly from the action units, which are still accurate. Resolution This issue has been resolved in FaceReader version 9.0.17. You can download the update from MyNoldus. --- ## MediaRecorder will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-mediarecorder/page/mediarecorder-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: Related to MediaRecorder Installation Error – FaceReader This error in the installation log file indicates one of the following issues: You do not have the necessary rights to install software Your account may lack the administrative privileges required to install software. Please ensure that you are logged in with an account that has administrative rights. If you are unsure, contact your IT department for assistance. Windows is currently updating If Windows is installing updates, the FaceReader installation cannot proceed. Please wait for the updates to complete, reboot the computer, and try installing again. There is a problem with system files Corrupted or modified system files, often due to malware or viruses, can block installation. Run a full system scan using your antivirus software and resolve any issues before attempting the installation again. --- ## What are the supported cameras for MediaRecorder 5.0? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-mediarecorder/page/what-are-the-supported-cameras-for-mediarecorder-50 Chapter: Related to MediaRecorder Analog Cameras MediaRecorder works with the output of any analog camera used with the Euresys Picolo H.264 or Euresys Picolo Alert video capture card. Tested and supported cameras include: - PhenoTyper Top Unit camera (EIA) - PhenoTyper Top Unit camera (CCIR) Maximum Supported Number of Cameras - Euresys Picolo Alert PCIe card: Up to 4 cameras or PhenoTyper Top Units - Euresys Picolo U4 H.264 card: Up to 3 cameras or PhenoTyper Top Units - Euresys Picolo U8 H.264 card: Up to 6 cameras or PhenoTyper Top Units IP Cameras To use MediaRecorder with IP cameras, the following network requirements must be met: - An Intel Pro/1000 CT or Intel Pro/1000 PT (1 Gb) network adapter installed - CAT5e or higher quality Ethernet cables - A dedicated network is recommended for the cameras Supported IP Cameras - Axis P5512 - Axis P5514 - Axis P5515 - Axis P5534 - Axis M1054 - Axis M1065 - Hikvision IP DS-2PT7D20IW-DE USB Cameras - Microsoft LifeCam Studio - Basler acA1920-155um - Logitech BRIO DanioVision FireWire System Includes the ImagingSource DMK 21AF04 camera (note: this system is now discontinued). GigE Vision Cameras - Basler GigE camera AC1300-60gm Screen Capture Devices Epiphan Devices These are hardware devices used to capture screen output from another computer: - Epiphan DVI2USB 3.0 – USB 3.0 device - Epiphan DVI2PCIe – PCIe frame grabber card - Epiphan VGADVI Broadcaster – Ethernet-based streaming device MediaRecorder Software Capture If your license includes the Screen Capture Module, a virtual device is available for software-based screen capture. --- ## Moving or relocating the PhenoTyper Home Cage URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-phenotyper/page/moving-or-relocating-the-phenotyper-home-cage Chapter: Related to PhenoTyper How best to prepare the PhenoTyper home cage(s) for relocation depends on the scale of the move – just down the hall to another room, or to another facility possibly far distances apart. Preparing the PhenoTyper OEM packaging will not be necessary. It will be best to disassemble the cage(s) for relocation, while taking special precautions for the more sensitive components (Top Unit, pellet dispensers, lickometers, running wheels, etc.). Each PhenoTyper wall has two screws at the top, and the Top Unit and floor base rest on the top and bottom of the walls, respectively. We recommend taking pictures of all the various connections prior to disassembling the system to aide with the reassembly. Documentation Please consult the available Documentation in MyNoldus, including the PhenoTyper Reference and Service Manuals, for additional information, including assembly instructions. NoldusCare Warranty Please note, certain provisions in the NoldusCare Terms and Conditions will disqualify any and all hardware warranties should damage occur during packaging and/or transportation. This will result in needing to purchase replacement components that may become damaged during the moving process. --- ## Pellet dispenser indicator light and error troubleshooting URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-phenotyper/page/pellet-dispenser-indicator-light-and-error-troubleshooting Chapter: Related to PhenoTyper The Noldus pellet dispenser has an LED light which indicates the status and can be used to identify an error: - Connect power cable/RJ45 cable — single blink - Waiting for command — LED off - Receiving pellet drop command — Single blink - Dropping pellet — Single blink - Error state — Fast blinking - Reset — Double blink - Blocked — LED solid on Dispenser empty An infrared photobeam detector senses whether a pellet is dropped after a “drop pellet” command has been given (either manually by pushing the blue button on the dispenser or with the USB-IO box and EthoVision XT). When no pellet is detected, the stepper motor moves the carousel within the silo one step further. If, even after a full rotation (15 steps), no falling pellet was detected, the system considers the silo to be empty. The pellet dispenser goes into error mode and the LED at the front of the pellet dispenser blinks continuously. Fill the silo with pellets and press the blue button at the front of the pellet dispenser to reset the device. It is then ready to be used again.  Not empty, but no pellet dispenses If the pellet tube is blocked, the pellet dispenser will go through the same process as above, but pellets remain in the carousel. Remove the carousel (by lifting it off the base) and check whether it is blocked by dropping a pellet into the hole. If it does not come out of the dispenser, the path is blocked. Use a thin, flexible object (e.g., a twist tie or cable tie) to clear the tube. LED light stays on The LED indicator will remain on if the infrared photobeam detector sees something remaining in the path. This could be an obstruction as above. If clearing the path does not resolve the problem, the detector may be covered in dust. A pipe cleaner or a can of compressed air can be used to clear the tube. Using dustless pellets should prevent this problem from occurring. --- ## Can I share my project with another user that has a different version of The Observer XT? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/can-i-share-my-project-with-another-user-that-has-a-different-version-of-the-observer-xt Chapter: Related to The Observer XT Sharing Projects with Colleagues in The Observer XT Solution 1: Your colleague is using the same or a newer version If your colleague is using the same version or a newer version of The Observer XT, you can share your project by sending them a backup file: - Open your project in The Observer XT. - Go to File > Make Backup. - Save the resulting .vpb file and send it to your colleague. - They can restore the backup by opening The Observer XT and selecting File > Restore Backup, then choosing the file you sent. Note: If the backup is restored from an older version, your colleague will see a warning about upgrading the project. A safety backup in the original version will also be created. Missing Backup Option? If you or your colleague does not see Make Backup or Restore Backup in the File menu, you are likely using a Coder license. - Go to Help > About The Observer XT > License Info. - If the license number starts with OC, it's a Coder license (limited functionality). - If it starts with OB, it's a full license. - You must close the software before unplugging or switching license keys. Hardware license keys are labeled accordingly: - Observer Coder = Coder license - Observer XT = Full license   Solution 2: Your colleague is using an older version If your colleague is using an older version of The Observer XT, you should export and share your observation files (.odx files) instead: - Open your project in The Observer XT. - Go to File > Export > Observation Data > The Observer XT. - Check Create separate file per observation and click OK. - Send the resulting .odx files to your colleague. Your colleague can now: - Open The Observer XT and go to File > New Project. - Then go to File > Import > Observational Data and select the .odx files. The coding scheme used for the .odx files will be automatically recreated. Note: This method works for Observer XT versions as low as 10.5. Missing "New Project" Option? If your colleague only sees New Project from Template under the File menu, they are likely using a Coder license and will need to use a full license to create new projects. --- ## Diagnosing the Load Project Failed (Id 10459) error in The Observer URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/diagnosing-the-load-project-failed-id-10459-error-in-the-observer Chapter: Related to The Observer XT Project Open or Copy Error in The Observer This error may also appear as “Project Copy Error”, “Cannot update the current project with the existing temporary project (Id 10465)”, or “Cannot create temporary project file (Id 10452)”. It may be caused by one of the following: - The file being opened is not a valid project file. - The filename does not match after restoring from a backup. - The project database file is damaged. The file is not a project A valid project in The Observer consists of a folder named after the project, containing multiple files and folders, including a .vop file. If you attempt to open a file by double-clicking outside of The Observer, ensure it’s a .vop file. If the file is a Project Backup (with a .vpb extension), it must be restored via File > Restore Backup within The Observer. This will recreate the project folder and open the project correctly. The project file has been renamed If the .vop file is renamed and then a backup is made and restored, The Observer may not find the expected filename and display an error. Ensure the .vop filename matches the folder name. Correct this manually after restoration in the folder: Default path: C:\Users\Public\Documents\Noldus\The Observer XT\Projects\ (or your designated custom folder). The project database is damaged or corrupted If the issue is not due to an invalid file or a mismatch, the project database may be corrupted. Use the backup copy included in the project folder, named restore.btn, to recover: - Rename the current .vop file (e.g., Study.vop → Study.vop.old). - Rename restore.btn to match the original .vop filename (e.g., Study.vop). - Open the project in The Observer. Note: If file extensions are hidden, enable them first: - In Windows 10/11: Open File Explorer, click View, then check File name extensions. - In Windows 7/8: Press Alt > Tools > Folder Options > View tab > Uncheck "Hide extensions for known file types". Using restore.btn may result in loss of the most recent session, but earlier data will be preserved. Reminder: Always make regular backups from File > Make Backup and store them on a separate drive or location. --- ## Error contacting the license server in The Observer XT 16 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/error-contacting-the-license-server-in-the-observer-xt-16 Chapter: Related to The Observer XT If you are using The Observer XT 16 with a software-based license (instead of a hardware license key) and encounter the following error message, please update to the latest version of the software: Error contacting the license server. Check your internet connection, your firewall, or the license server may be offline. If you use a proxy server, you must configure your proxy server settings. Unable to connect to the remote server - URL: https://qlmlicenses.noldus.com:9999/qlmlicenseserver/qlmservice.asmx Cause This error occurs specifically in version 16.0.1201 of The Observer XT. It was resolved in version 16.0.1203. Solution - Download the updated version (16.0.1203 or higher) from the Downloads section of this site. - Install the update to ensure proper license server connectivity. How to Check Your Version To find out which version you are currently using: - Open The Observer XT. - Go to Help > About The Observer. - The version number will be listed in the dialog window. --- ## I cannot find my project’s VOP file. I see a file that looks like it might be it, but I am unsure URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/i-cannot-find-my-projects-vop-file-i-see-a-file-that-looks-like-it-might-be-it-but-i-am-unsure Chapter: Related to The Observer XT Solution: Enable File Type and Extension Visibility in Windows If your project folder looks similar to the example below, Windows File Explorer may be hiding file type and extension information, which can cause confusion when working with Observer XT project files: How to Display File Types and Extensions To reveal full file information, follow these steps: - Open File Explorer. - Go to the View tab on the ribbon menu. - Check the boxes for Details (to display file type) and File name extensions (to display extensions like .vop). Important Note About .vop Files The .vop file is used to open the project in Observer XT, but it is not the complete project. Do not copy only the .vop file or create a duplicate within the same folder. To make a full copy of a project: - Copy the entire project folder, which includes the .vop file and all subfolders (such as Event Data and Multimedia Files). - Alternatively, use File > Save Project As inside Observer XT to create a duplicate safely. --- ## I made a backup file but I cannot see the VPB file extension on the end in File Explorer. URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/i-made-a-backup-file-but-i-cannot-see-the-vpb-file-extension-on-the-end-in-file-explorer Chapter: Related to The Observer XT Displaying Backup File Extensions in The Observer Backup files created in The Observer have a .vpb extension. However, Windows may hide this extension by default, making it appear as if the file has no extension in File Explorer: This occurs because Windows hides extensions for known file types by default. To ensure you can see all file extensions (including .vpb), follow the instructions below based on your version of Windows. For Windows 7 - Open File Explorer. - Press the Alt key to show the menu bar. - Go to Tools > Folder Options. - Select the View tab. - Uncheck the box labeled Hide extensions for known file types. - Click OK to apply the changes. For Windows 10 - Open File Explorer. - Go to the View tab in the ribbon. - Check the box labeled File name extensions. After doing this, the .vpb extension will be visible for your backup files, helping you confirm the file type and use it correctly in The Observer. --- ## Playback control buttons are grayed out in The Observer XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/playback-control-buttons-are-grayed-out-in-the-observer-xt Chapter: Related to The Observer XT If the video opens but the playback control buttons are greyed out and won't let you play, pause, etc. the video, deleting the customization files may resolve the issue. This will also resolve issues with hidden or missing toolbars, windows, and panels. Close the project and The Observer software, go to the location where the problematic project is located (by default, it is C:\Users\Public\Documents\Noldus\The Observer XT\Projects), find and open the problematic project's folder, and delete the .pos and .pob files in it.   Note that if the extensions (.pos, .pob, vop) are not displayed, in Windows 10 click View on the ribbon and check the checkbox for Show Extensions to see them. This ensures you do not delete the wrong file. Do not delete the .vop file! After that, close the project’s folder, re-open The Observer XT software/your project, and the issue should be resolved. --- ## The Observer will not install and the installation log file says Access Denied - 0x80070005 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/the-observer-will-not-install-and-the-installation-log-file-says-access-denied-0x80070005 Chapter: Related to The Observer XT This error in the installation log file indicates one of the following issues. You do not have the necessary rights to install software Your account does not have the required administrative rights to install software. Check that you do have administrative rights, or log into the computer using an account which does. Depending on how your systems are configured, you might require the assistance of your local IT department for installing software. Windows is currently updating Windows is in the process of installing updates, and the FaceReader installation cannot begin until it is finished. Complete any system updates and try again. Reboot PC after Windows updates complete to ensure no updates are pending. There is a problem with system files Malware or a computer virus has modified system files. Run a scan of the system. --- ## The Observer XT Error Id 12524 – Event Log Read Failure URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/the-observer-xt-error-id-12524-event-log-read-failure Chapter: Related to The Observer XT Error 12524 – Event Log Read Failure The message "Event Log Read Failure" (Id 12524) indicates that the event log files cannot be found. These files are separate from the project file (the .vop file). If the files have been moved or separated from the rest of the project folder, this error will occur. Files Missing or Out of Place An Observer XT project is a folder named after your project, which contains: - The .vop file - Subfolders including Event Data, Multimedia Files, Reliability Data, and others Note: Windows may hide file extensions (e.g. .vop), and older versions of Observer may not display Restore.btn files. Crucially, observational data is stored in the Event Data folder, not in the .vop file. Each observation has its own file in this folder. If the .vop file is moved outside the project folder, Observer may recreate the folder structure but will be unable to locate the original data files—triggering the read failure. Best Practices for Moving or Transferring Projects To move a project between folders or computers: - Always move the entire project folder — including the .vop file and all subfolders. - To make a duplicate: Use File > Save Project As inside Observer. - To transfer to another computer: Use File > Make Backup to create a .vpb file. Move this file and use File > Restore Project on the new computer. File Name Mismatch The following project components must have matching names: - The .vop project file - The .pos file - The parent folder containing these files If file names are changed and no longer match, especially after restoring from backup or renaming manually, you may encounter read errors or failure to open observations. --- ## The Observer XT will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/the-observer-xt-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: Related to The Observer XT Installation Fails with Error 0x80070005 This issue occurs when installing The Observer XT on your computer fails and the resulting log file shows the error code: Log File: “Error 0x80070005” After the installation fails, you may see a message like this in the log file: Possible Causes - Insufficient administrative rights: Your account may not have the required administrative rights to install software. Make sure you are logged in as an administrator, or ask your IT department for assistance. - Pending Windows Updates: Windows might be in the middle of installing updates. Finish all pending updates and reboot the system before trying again. - Malware or virus interference: Malware or a virus could have modified essential system files. Run a full system antivirus scan and resolve any issues found. - Microsoft .NET installation problem: The installation may be failing while trying to install or use Microsoft .NET. Download and install the required version of Microsoft .NET Framework manually, then try installing the Noldus software again. --- ## What is the best way to share my Observer project with another user? Can I simply send the .vop (Observer Project) file? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-the-observer-xt/page/what-is-the-best-way-to-share-my-observer-project-with-another-user-can-i-simply-send-the-vop-observer-project-file Chapter: Related to The Observer XT Sharing The Observer XT Projects with Colleagues Note: The .vop file is not the entire project. It is just one component within a project folder, which includes various data and configuration files. The project folder should look something like this: To share a project, do not send the .vop file alone. Instead, use one of the methods below. Solution 1: Colleague is using the same or newer version of The Observer XT - Open your project. - Go to File > Make Backup. - Save the resulting .vpb file and send it to your colleague. - Your colleague can restore it via File > Restore Backup. Note: If restoring from an older version, your colleague will see this upgrade warning: Missing the Backup Options? If the Make Backup or Restore Backup options are not available in the File menu, you are likely using a Coder license (license number starts with OC). A full license (starts with OB) is required to perform these actions. - To check your license, go to Help > About The Observer XT > License Info. - Close the software before unplugging or switching license keys. - Physical dongles: "Observer Coder" = coder license, "Observer XT" = full license. Solution 2: Colleague is using an older version of The Observer XT If your colleague is using an older version than you, send them your observation files: - Go to File > Export > Observation Data > The Observer XT. - Check Create separate file per observation and click OK. - Send the resulting .odx files to your colleague. Your colleague can: - Open The Observer XT and go to File > New Project. - Then go to File > Import > Observational Data and select the .odx files. The coding scheme used to create the observations will be automatically recreated. Note: This method works with versions as old as The Observer XT 10.5. Missing “New Project” Option? If only “New Project from Template” appears in the File menu, a Coder license is in use. A full license is required to create new projects. --- ## How do power outages affect TrackLab operation? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-tracklab/page/how-do-power-outages-affect-tracklab-operation Chapter: Related to TrackLab Power Control in TrackLab TrackLab requires a stable power connection to ensure uninterrupted operation. To avoid interruptions from power cuts, we highly recommend using a UPS (Uninterruptible Power Supply). Controlled Shutdown A controlled shutdown occurs when Windows or the user initiates the shutdown and it is properly communicated to the system. Consequences of a controlled shutdown: - If TrackLab is not recording at the time of shutdown, there are no severe consequences. TrackLab will recalculate the analysis data automatically, during which time some data may not be visible. Once complete, all analysis data will be fully restored. - If TrackLab was recording during the shutdown, the recording will be interrupted. Any unrecorded data will be lost. Recording resumes automatically once power is restored, and TrackLab will recalculate the analysis data. Analysis results are unavailable until recalculation is complete. Note: Recalculation time depends on the recording duration before the power loss. Uncontrolled Shutdown An uncontrolled shutdown includes all outcomes of a controlled shutdown, and may also cause: - Data corruption or incomplete analysis results - System startup issues These issues are logged in the System Diagnostics window, accessible from the top-right menu after logging in to TrackLab. Important: Use of a UPS is critical to prevent uncontrolled shutdowns. TrackLab may not recover fully without Noldus Support intervention in such cases. Recommended UPS Setup To protect your system, install two UPS devices: - One for the TrackLab PC - One for the Sewio Server PC UPS Purpose: - Maintain power during short outages - Trigger a controlled shutdown before battery depletion Note: Disable Windows hibernation mode, as it is not supported by TrackLab. UPS Specifications - At least 2 battery-protected grounded AC outlets (1 PC + 1 monitor) - Country-compatible AC outlet types - Compatible plug for site-specific sockets - Output power: 350W, 600VA - Backup time: ~10 minutes at full 350W load - Capability to initiate a graceful shutdown Regularly check UPS battery health to ensure reliability. Consult your local UPS supplier for appropriate models and installation advice. --- ## How to rename your subjects in TrackLab URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-tracklab/page/how-to-rename-your-subjects-in-tracklab Chapter: Related to TrackLab Subject names can be changed either manually, one by one or by importing new subjects from a file. How to manually rename your subjects Click on a particular subject name in the "subject name" column to enter manually new subject names.  Alternatively, select a known subject name from a drop-down list within a subject name cell. This drop-down menu contains all known subjects names used within TrackLab (all subjects used in any session and site).  If a new subject name is already used for another tag in the opened session the subject cell is outlined in red and the new name is not accepted.  Note: that all manual rename actions only affect the selected session.  Import subject names The import subject names button, located on the right side of the screen, opens a dialogue that allows you to select a file. This file needs to contain the recorded tag MAC addresses assigned to a new subject name. When uploading the file it only applies to the selected session unless the checkbox "to all session" is ticked. If this is the case, the rename actions apply to all existing sessions within the project/experiment.  The name extension of the text file is not restricted although it must contain text. The first line of the file will be ignored as this is seen as header information. All subsequent lines must contain a tag MAC-Id and the subject name to assign to it, separated by a semicolon.  An incorrect format for the mapping file will result in an "incorrect Mapping File" error.  See subject renaming failures for more details about the errors.  Note: Renaming of subjects takes some performance time of the TrackLab software. Especially when larger name files or several sessions are selected. TrackLab does not show any progress indication. You can see when the progress finishes as soon as the new names appear in the Subject-Level variable list. In the meantime, it is not possible to make any adjustments until the progress has finished.    --- ## Re-use of subject names in TrackLab URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-tracklab/page/re-use-of-subject-names-in-tracklab Chapter: Related to TrackLab Reusing Subject Names Across Sessions in TrackLab In most experimental designs, subjects wear the same tag across multiple sessions. TrackLab simplifies this process using the “Re-use subject names” option available on the right side of the Subject Variables list. To ensure subject identities are consistently maintained: - Assign the correct subject names to tags in the first session. - Before beginning the next session, enable the “Re-use subject names” checkbox. Once this option is enabled, TrackLab will automatically assign the same subject names to the corresponding tags in subsequent sessions. Note: For any new tag IDs introduced in a session, TrackLab will initially use the tag’s MAC ID as the subject name. These can then be renamed as needed. --- ## Subject renaming in TrackLab URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-tracklab/page/subject-renaming-in-tracklab Chapter: Related to TrackLab Managing Subject Names in TrackLab TrackLab records location data from your subjects using wearable tags, such as a Sewio UWB tag attached to the collar of an animal. Each tag has a unique MAC identification number. In the TrackLab Software, navigate to the Setup > Variables tab and open the Subject-Level page. There, you’ll find an overview of all tags detected within the selected session. Subject Naming in TrackLab 2.12 and Later As shown in the second column of the interface, each tag is initially identified by its tag ID. With TrackLab version 2.12 and later, users can assign more descriptive names to subjects. These user-defined names replace the default tag codes and are used consistently throughout the software interface and analysis outputs. Subject Naming Rules TrackLab treats each subject name as a unique identifier. The following rules apply: - Unique per session: You cannot assign the same subject name to more than one tag within the same session. - Consistent across sessions: A subject name used across different sessions (even across different sites) refers to the same subject. - Site-specific analysis: Identical subject names can exist across sites, but analysis results in TrackLab are always limited to the selected site. Further Reading - How to rename your subjects - How to reuse subject names across sessions - Continue to the next article to read when subject renaming fails --- ## What are the filter settings in Trackab? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-tracklab/page/what-are-the-filter-settings-in-trackab Chapter: Related to TrackLab TrackLab 2.13 Filter Settings TrackLab version 2.13 includes three filter settings that help optimize tracking data: - Sample Rate - Smoothing Window Size - Minimum Distance Moved (MDM) Threshold 1. Sample Rate This setting defines the maximum number of location data points recorded per second, per tag. If the incoming data exceeds this rate, TrackLab filters out the surplus. While sensor data such as accelerometer readings may come in at higher frequencies, the sample rate filter only limits the location data. For large animals like cattle, a rate of 1 Hz is typically sufficient. Higher rates place more load on the database without improving analysis results. Smaller animals or more detailed analyses may benefit from higher rates. 2. Smoothing Window Size This setting reduces short-term fluctuations (e.g., from noise or jittery movement) by averaging coordinates over a set number of samples. The window is centered around the focal sample. For example, a window size of 25 samples calculates the average of 12 samples before, 12 samples after, and the focal sample. This reduces zig-zag movement paths and creates smoother tracks. Default: Smoothing is enabled by default with a window size of 9. 3. Minimum Distance Moved (MDM) Threshold This filter removes minimal displacements between samples that are likely due to signal noise. It improves the accuracy of total distance moved, especially when the subject is inactive (e.g., sitting or lying down). The filter works by comparing consecutive distances. If the movement is smaller than the threshold, the position is assumed to have not changed, and the sample is adjusted accordingly. - A low MDM threshold has minimal impact at high sample rates (e.g., 10 Hz). - Use a low MDM threshold when: - The tracking area is small - Areas of Interest are small - Analyzing proximity with a low “In proximity below” threshold - Ensure the MDM threshold is smaller than the proximity threshold if used. Recommended MDM thresholds: - Sewio: 0.30 m - GPS LoRa: 1.00 m --- ## How can I play back and hear ultrasound outside UltraVox XT ? URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-ultravox-xt/page/how-can-i-play-back-and-hear-ultrasound-outside-ultravox-xt Chapter: Related to UltraVox XT Playing Back UltraVox XT Recordings in Audacity UltraVox XT allows playback of ultrasound recordings using the Pitch Reduction feature. However, if you prefer or need to play a recording in different software, we recommend using Audacity. Steps to Play Back UVD Files in Audacity - Locate your recording file (extension .UVD) in the experiment folder. - Make a copy of the file: - Select the file, press Ctrl + C, then Ctrl + V. - Rename the copied file to [filename].WAV. - Open the .WAV file in Audacity. - Go to Edit > Preferences. Under the Tracks section: - Choose Spectrograms. - Set the frequency range under Scale (e.g., 0 to 125000 Hz). - To view the spectrogram: - Click the dropdown arrow next to the track name and select Spectrogram. - Select the entire recording by pressing Ctrl + A. - Go to Effect > Pitch and Tempo > Change Pitch.... - In the Change Pitch dialog: - Set the frequency to convert from ultrasonic to audible sound. - For example, From 60000 Hz to 10000 Hz (as human hearing is limited to ~20000 Hz). - Click Apply to process the change. - Press the Play button or spacebar to listen. - If you don’t hear anything, go to Edit > Undo Change Pitch, then try lowering the target frequency further. - To save the audible version of the recording: - Go to File > Export Audio. This method allows effective playback of ultrasound data outside of UltraVox XT for review or sharing purposes. --- ## No data files found for experiment in UltraVox XT URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-ultravox-xt/page/no-data-files-found-for-experiment-in-ultravox-xt Chapter: Related to UltraVox XT Error: "No Recordings Found" in UltraVox XT When attempting to open recordings for analysis in UltraVox XT, you may encounter the following message: This error occurs when UltraVox XT is unable to locate the recordings associated with the experiment. The issue can result from one of two main causes: 1. No Recordings Present in the Experiment Folder Check whether the experiment folder contains any recordings: - Go to the Experiments directory. - Locate the folder with the same name as your experiment. - Ensure it contains .UVD files and other necessary files. If no .UVD files are present, UltraVox XT cannot proceed with analysis. 2. Folder Name Mismatch or Incorrect Path This situation can happen if the experiment folder was copied manually (e.g., via Windows Explorer) and renamed, instead of using UltraVox XT’s built-in File > Save As function. Solution: - Close the experiment in UltraVox XT. - Navigate to the experiment folder on your system. - Right-click the .UVX file and choose Open with > Notepad. - Check the second line that starts with Name =. This specifies the original folder name UltraVox XT expects. - Restore or rename the folder to match the expected name exactly and place it under the Experiments directory. Important: To create a copy of an experiment, always use File > Save As from within UltraVox XT. Do not copy and rename experiment folders manually via File Explorer. Correct folder management will ensure that recordings are found and correctly linked to your experiment data. --- ## UltraVox microphones are not recognized after restarting the computer URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-ultravox-xt/page/ultravox-microphones-are-not-recognized-after-restarting-the-computer Chapter: Related to UltraVox XT Microphones Not Recognized in UltraVox XT UltraVox XT may fail to recognize USB microphones under the following conditions: - Microphones are plugged into different USB ports than previously used. - The computer has recently been in sleep mode. Solution - Disconnect and then reconnect the USB hub cable to the same USB port used previously. - In UltraVox XT, open Experiment Settings and click the Refresh button. - If a red cross (×) appears next to any microphone, click the button in the Microphone column and reselect the correct microphone from the list. The software will remember the original microphone names. Best Practice To avoid recognition issues in the future, always plug each microphone into the same USB port it was initially configured with. --- ## UltraVox XT Error Message - Out of Memory URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-ultravox-xt/page/ultravox-xt-error-message-out-of-memory Chapter: Related to UltraVox XT Error: “Error saving calls: Out of memory (A2)” This error occurs in UltraVox XT when attempting to save calls from a recording with a large number of detected calls—typically more than 500—combined with a high Overlap (%) setting in the Spectrogram settings. The Overlap (%) setting controls how much overlap there is between adjacent Short-Time Fourier Transform (SFT) frames in the spectrogram. While a higher value can improve detection of brief events, it significantly increases memory usage because it causes the same data to be processed repeatedly. This can eventually exhaust available memory and trigger the error. Solution - In the Call Detection screen, go to View > Settings. - Reduce the Overlap (%) setting—for example, change it from 90% to 70%. - Click Close to apply the settings. - Back in the Call Detection screen, click Apply to re-detect calls using the new settings. - Once detection is complete, save the experiment. Tip: Lowering the Overlap setting reduces processing time and memory load, which improves stability for large datasets. --- ## Camera connection lost in Viso URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-viso/page/camera-connection-lost-in-viso Chapter: Related to Viso Description of problem No camera view in Viso Viewer, so you cannot start a recording. This is probably because a camera is not selected in the Location or because there is an error in the camera configuration. When it occurs After opening a Location for recording. Required to solve You must log in into Viso Viewer as a Technician to be able to edit a Location. Solution - Log in into Viso Viewer as a Technician. - Open the Locations from the dashboard. - Click the Edit Locations button. - Unfold the Viso Recorder computer item and click on the pencil/Edit button in the row of the Location you want to change. - To change camera settings, click on the pencil/Edit button in the row of the camera. - Check that the IP address of the selected camera is correct. If not, change it manually or select it from the list if more than one camera is connected. - Select ONVIF as Device Type (this is the default). - Enter the ONVIF User name and ONVIF Password for your camera in case they were not filled automatically.  - Click Get device properties. If the camera is connected then the Quality field appears with the default frame rate and resolution of the camera. - If the Location has more than one camera, please also check the connection to other cameras. - After the connection with the camera is restored, de-select and, five seconds later, select the Select for recording box for the Location with the cameras. The camera view should now be restored. - You can now open the Location again to for a Session recording. --- ## Cannot open, view, playback, import, export or delete sessions in Viso URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-viso/page/cannot-open-view-playback-import-export-or-delete-sessions-in-viso Chapter: Related to Viso Description Problems with opening/viewing recorded Sessions, playback of videos, exporting/deleting videos from a Session or importing videos into a Session. When it occurs When trying to replay a session or trying to extract data from a Session. Required to solve You must log in into Viso Viewer as a Technician to be able to edit a Location. Solution - Log in into Viso Viewer as a Technician. - Open the Locations from the dashboard. - Click the Edit Locations button. - Unfold the Viso Recorder computer item and click on the pencil/Edit button in the row of the Location you want to change. - In the Audio Device column, check that the correct audio source is selected for each camera. - To select/change the audio source, click on the pencil/Edit button under Audio Device. --- ## Configuration error when selecting Location for recording in Viso URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-viso/page/configuration-error-when-selecting-location-for-recording-in-viso Chapter: Related to Viso Description A Location is offline because of a configuration error. This could be because a camera is not selected or not correctly configured (see Camera) or an audio device is not properly configured. When it occurs When trying to open a Location for recording. Required to solve You must log in into Viso Viewer as a Technician to be able to edit a Location. Solution - Log in into Viso Viewer as a Technician. - Open the Locations from the dashboard. - Click the Edit Locations button. - Unfold the Viso Recorder computer item and click on the pencil/Edit button in the row of the Location you want to change.   - In the Audio Device column, check that the correct audio source is selected for each camera. To select/change the audio source, click on the pencil/Edit button under Audio Device. - Choose the correct audio device. - Close this window. - After the connection with the audio is restored, de-select and, five seconds later, select the Select for recording box for the Location with the cameras. The camera view should now be restored. - You can now open the Location again to for a Session recording. --- ## Connection lost with Viso Services URL: https://noldus.com/shared/resources/book/mynoldus-knowledge-base/chapter/related-to-viso/page/connection-lost-with-viso-services Chapter: Related to Viso Description Viso Viewer cannot connect to Viso Services. This is probably because Viso Services is not running. When it occurs - When starting Viso Viewer. Required to solve - Administrator rights on the Viso Viewer PC so you can access Task manager to restart Viso Services.  - Administrator rights on the Viso Viewer so you can access the FireWall settings to check that port 5672 is open for communication between Viso Viewer, Viso Services and Viso Recorder. Solution 1 – Restart Viso Services - Close Viso Viewer. - Next, simultaneously press Ctrl + Shift + Esc to open the Task manager. - In the Task manager, go to the Services menu and search for VisoServices. - Select VisoServices and click the Restart button in the tool bar. - Open Viso Viewer and log in. Solution 2 – Allow communication through port 5672 of the Windows Firewall - Close Viso Viewer. - Open the Control Panel and choose System and Security > Windows Defender Firewall. - On the left side of the window, click Advanced Settings. - Click Inbound Rule and click New Rule in the Actions - In the New Inbound Rule Wizard window that opens, select Port and click Next. - Select TCP and enter 5672 in the Specific local ports field and click Next. - Click Allow the connection and click Next. - Select all networks and click Next. - Give the rule a name, for example Viso connection and click Finish. - Check in the Inbound Rules windows that this rule is set to Enabled. - Click Outbound Rule and click New Rule in the Actions pane. Repeat steps 5 to 8 for the outbound rule. - Close all control panel windows. --- ## How can I get a trial? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/how-can-i-get-a-trial Chapter: Help Center Please contact sales via email: trials@noldus.com View original HubSpot article · HubSpot article 201734392889 · Knowledge Base 201734726298 · Language en · Updated 1747519946924 --- ## How can I get into contact with Noldus Sales? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/how-can-i-get-into-contact-with-noldus-sales Chapter: Help Center Please send an email to contact@noldus.com View original HubSpot article · HubSpot article 201750198606 · Knowledge Base 201734726298 · Language en · Updated 1747519947373 --- ## How to Install Noldus Software URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/how-to-install-noldus-software Chapter: Help Center Just run the setup and start enjoying our software. View original HubSpot article · HubSpot article 201749047071 · Knowledge Base 201734726298 · Language en · Updated 1747519947959 --- ## My hardware license key (dongle) is not recognized URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/my-hardware-license-key-dongle-is-not-recognized Chapter: Help Center Older drivers for the hardware license keys used in Noldus software may not work in newer updates of Windows 10. Please download this driver and then run or double-click the downloaded file to install it: HASP 8.13 View original HubSpot article · HubSpot article 201734392888 · Knowledge Base 201734726298 · Language en · Updated 1748144408202 --- ## Redo a trial in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/redo-a-trial-in-ethovision-xt Chapter: Help Center EthoVision XT can be used to track in real-time but sometimes after the trial it will be apparent that the animal was not tracked well the arena was miscalibrated or for other reasons the track is n...... View original HubSpot article · HubSpot article 201750198607 · Knowledge Base 201734726298 · Language en · Updated 1747519946453 --- ## Tags are shown at the wrong location in the tracking area align at straight lines or not visible at all URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/tags-are-shown-at-the-wrong-location-in-the-tracking-area-align-at-straight-lines-or-not-visible-at-all Chapter: Help Center An example of anchors aligned at a straight line can be seen in the screenshot below:In Sensmap Visualization check if all anchors are at their respective locations. Meaning that they should not be m...... View original HubSpot article · HubSpot article 201734314496 · Knowledge Base 201734726298 · Language en · Updated 1747519944919 --- ## The subject/tag names in TrackLab have technical numbers (MAC address). Can these be changed into human readable names? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/the-subjecttag-names-in-tracklab-have-technical-numbers-mac-address-can-these-be-changed-into-human-readable-names Chapter: Help Center Yes from TrackLab version 2.12 up you can apply custom names in the Variables module....... View original HubSpot article · HubSpot article 201734392890 · Knowledge Base 201734726298 · Language en · Updated 1747519945462 --- ## Tracking from multiple video files (Batch processing) in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/help-center/page/tracking-from-multiple-video-files-batch-processing-in-ethovision-xt Chapter: Help Center Tracking from multiple video files (Batch processing) in EthoVision XT.Applies to: EthoVision XT (9.0 and later)Description of issue: If you recorded a series of video files outside of EthoVision...... View original HubSpot article · HubSpot article 201752460679 · Knowledge Base 201734726298 · Language en · Updated 1747519945993 --- ## A specific user could open experiments normally but, when she selected File > Close, the experiment failed to close and became locked. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/a-specific-user-could-open-experiments-normally-but-when-she-selected-file-close-the-experiment-failed-to-close-and-became-locked Chapter: Noldus Knowledge Base In EthoVision XT version 15 where a specific user could open experiments normally but, when she selected File > Close, the experiment failed to close and became locked. After the failed close, she could not reopen the same experiment file. Other users could open the same file without issue, which cleared the lock. The issue occurred for every file she tried to close. The FAQ below provides general troubleshooting steps for experiment locking problems. FAQ & Step‑by‑Step Instructions Q: Why does an experiment remain locked for one user after closing? A: Experiment lock files are created when EthoVision opens an experiment to prevent simultaneous editing. If the user lacks permission to remove the lock file or EthoVision crashes during closing, the lock file may persist. A different user with full permissions can typically remove the lock automatically by opening the experiment. Q: How can I unlock an experiment file that will not reopen? Check user permissions – Ensure the affected user has full read/write access to the experiment folder. Without write permissions, EthoVision cannot remove its lock file. - Locate and delete the lock file – Navigate to the experiment’s folder in Windows Explorer and look for files with extensions such as .lock, .lck or files named ~experiment.lock. Delete these lock files to clear the lock. Always make a backup of the experiment folder before deleting files. - Use another user account – Have another user with working access open and close the experiment file. This often resets and removes the lock file. - Upgrade EthoVision – Consider updating from version 15 to a more recent version (e.g., 17.5). Later versions include fixes for file‑locking issues. - Avoid network interruptions – If the experiment file is stored on a network drive, make sure the connection is stable. Unstable network connections can lead to orphaned lock files. Q: How do I properly close an experiment to avoid locking issues? - Always save your work before closing, then use File > Close and wait for EthoVision to finish processing. Do not force‑quit the application while an experiment is closing. If possible, close experiments when connected directly to the storage location (not over a remote or wireless connection). Q: What if the problem persists after clearing the lock file? - If the experiment remains locked or the issue recurs, copy the entire experiment folder to a new location and open the copy. You can also contact Noldus support for assistance; providing the experiment folder and a description of the steps you have taken will help them troubleshoot. View original HubSpot article · HubSpot article 194934578741 · Knowledge Base 187958790447 · Language en · Updated 1755874286335 --- ## A TrackLab 1 customer reports that their license has expired and TrackLab stopped working. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/a-tracklab-1-customer-reports-that-their-license-has-expired-and-tracklab-stopped-working Chapter: Noldus Knowledge Base The customer can extend the TrackLab 1 license free of cost by following the instructions below. Please also recommend the customer to upgrade to TrackLab 2. Instructions for TrackLab 1 license extension: - Tell the customer to follow the instructions in the dialog that appears after TrackLab 1 start up. IF the TrackLab PC is connected to the internet, a request to receive a new registration key can be send straight away. IF the TrackLab PC is NOT connected to the internet, the customer needs to choose the option to create a file, which needs to be send to the displayed mail address. - The customer will receive a new registration key, within 24 hours after sending the request. Note: The registration key request will be received by Technical Support. If you have never generated a TrackLab 1 registration key before, get the required tool including instructions at R&D (Ben Loke or Mike Kelia). View original HubSpot article · HubSpot article 190573052193 · Knowledge Base 187958790447 · Language en · Updated 1752679653079 --- ## Accessing EthoVision XT remotely URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/accessing-ethovision-xt-remotely Chapter: Noldus Knowledge Base Remote access software can be used to control a computer (e.g. where EthoVision is running) from another computer located elsewhere. The hardware license key (if needed, see below) should be plugged into the EthoVision computer, not the remote computer. Microsoft Remote Desktop will not work for this purpose if you are using a hardware license key (aka dongle), although it is fine if you have a software-based license (using an activation code rather than a hardware license key). While using Remote Desktop, your hardware key will not be detected. Other remote access software will work. (Note: this applies to all Noldus products with hardware license keys, not just EthoVision.) More details are provided about using TeamViewer and TightVNC at the end of this document. - TeamViewer https://www.teamviewer.com/  (PREFERRED) - TightVNC https://www.tightvnc.com/download.php - RealVNC https://www.realvnc.com/en/connect/trial/ - DameWare https://www.dameware.com/dameware-remote-everywhere/registration When is this needed? Use remote access to a computer in your lab when you need to use hardware in your lab (e.g. cameras, arenas), when you need a hardware key but cannot take it from the lab (e.g. to allow multiple people in different locations to use it), or when it is unfeasible to take the files (e.g. because of their size). A license is required for: - Creating a new experiment using functionality from any optional module (e.g. multiple arenas, nose and tail tracking, behavior recognition) - Acquiring a new track from camera - Acquiring a track (new or redoing a track) from a video file A hardware license key is not required for analysis of existing tracks. You can simply install EthoVision on an additional computer for this purpose. If you are using EthoVision XT 17 or newer, you have the option of a software-based license instead of a hardware license key. This avoids the issue with Remote Desktop. Contact Noldus support if you are interested in switching from a hardware license key to a software-based license. TeamViewer TeamViewer is easy to use and free for non-commercial purposes. - Download TeamViewer from their site at https://www.teamviewer.com/ - When installing on the EthoVision computer, make sure to select Unattended Access. - Open TeamViewer on the EthoVision computer. - On the General tab under Unattended Access, select Start TeamViewer. - Write down the Partner ID and Password (or take a photo of the screen). - Leave this computer running so you can connect to it. - Install TeamViewer on your remote computer. - Under “Control Remote Computer”, enter the ID from above, then enter the password when prompted. TightVNC TightVNC may require that you connect to the network using a VPN. - Download the installer from https://www.tightvnc.com/download.php, and run it on the pc with EthoVision. - Use the full install to install both the viewer and the server. Use the default install, but set the passwords for security to ensure others cannot access your computer. - Restart the computer and leave it running in order to be able to connect to it. - Install the viewer on the PC you want to work. - Make the connection to the local network where the computer is running. - Run the viewer and type the name or the IP address of the PC you want to connect too. - Type in the password   View original HubSpot article · HubSpot article 190573052066 · Knowledge Base 187958790447 · Language en · Updated 1748132057238 --- ## Activity, Mobility, and Movement: How much is my animal moving around? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/activity-mobility-and-movement-how-much-is-my-animal-moving-around Chapter: Noldus Knowledge Base EthoVision provides many dependent variables to measure different aspects of your animal's behavior. Activity, Mobility, and Movement each provide ways to measure the amount of time the animal was moving around vs the amount of time the animal was stationary. Depending on the settings and the context of the experiment, they can be used to measure sleep (prolonged inactivity) or freezing (brief inactivity), or even to identify possible seizure events (usually a brief bout of intense activity). Activity and Mobility can also be used to measure swimming vs floating in the Porsolt Forced Swim Test. Each of these dependent variables has a continuous measure that reports a value for every sample point, and a state measure that compares that value to a threshold. Activity is a continuous measure, while Activity State is the state measure. Mobility and Mobility State have the same relationship. Movement is a state measure based on the continuous value of Velocity. Mobility Mobility looks at the entire area that is detected as the animal – everything that is showing up in yellow during tracking. It asks what percentage of that area is different (non-overlapping) from one sample to the next. The Mobility could be high either because the animal is moving (e.g. in a straight line), or because the outline of the animal is changing (e.g. the animal is rotating in place so the head and tail are in different places even though the center point might be stationary). Mobility reports a percentage which is the percentage change. Here's how that change is calculated. A(n-1) is the area of the animal in the previous sample point, while A(n) is the area in the current sample point. CA(n) is the calculated changed area. Mobility States then compares that percentage to the thresholds you set in order to categorize mobility as immobile, mobile, or highly mobile and give you the duration and frequency of each state. In the example shown below, the animal is considered Immobile when the mobility is below 4%, mobile from 4-10%, and highly mobile from 10% up. Activity Activity does not care what is detected as the animal. Instead, it looks at the entire arena and asks what percentage of the entire arena is changing. Of course we expect that what is changing is either the animal or directly caused by the animal (e.g. shadows or reflections caused by the animal), but for these purposes we’re just asking what percentage of pixels in the arena are different than in the previous sample. Activity States then compares that percentage to thresholds you set, the same way as Mobility is used to determine Mobility States. When the detection settings are good and the whole body of the animal is being detected (and showing in yellow), Mobility and Activity are equally good and should give very similar results (the values will not be the same but they will show the same differences between treatments etc). Activity does require that it must be enabled in the Experiment Settings and the settings adjusted in the Detection Settings in order for it to be used, whereas Mobility is something you can add post-hoc. When it’s difficult to get good detection settings, and only part of the animal is detected inconsistently, or you are inconsistently picking up shadows and reflections as part of the animal, Activity can be a better choice. Activity can also work in situations where tracking is not possible at all, e.g. you could look at activity in the whole tank when there are too many fish to track individually. To set up Activity, before running any trials and after checking the Activity checkbox in the experiment settings, in the Detection Settings click Activity on the right. You will see these settings: Set the Compression Artifacts Filter on if you are using video files. Set it off if you are acquiring trials directly from a camera. The background noise filter can be helpful if you see a lot of activity all over the arena due to camera noise. You will also need to adjust the activity threshold after changing the background noise filter. Adjust the activity threshold so that you see purple wherever there is movement in the arena, but minimize the amount of purple where there is no movement. It may look something like this:   Movement Movement is the simplest measure. It simply determines whether the center point of the animal's body (or other selected point) was moving faster than a threshold you set. The settings look like this: In this case, as soon as the animal begins moving at least 2.00 cm/s, it is considered moving. When its velocity drops below 1.75 cm/s, it is considered to have stopped ("not moving"). Movement tells you how often the animal was walking around. However, because it only looks at whether that center point was going from one place to another, it won't distinguish between an animal that is completely stationary (e.g. freezing, sleeping) and one that is sitting in place but active (e.g. grooming). Determining Thresholds Mobility State, Activity State, and Movement all depend on determining appropriate thresholds. The optimal threshold depends on your animals, your arena, and your settings, so you will need to examine your data to determine what threshold to use. The easiest way to do this is by using the Integrated Visualization. First add Velocity, Mobility, and/or Activity to your analysis profile – these are the three measures that will be used to determine Movement, Mobility States, and Activity States. Then go to the Integrated Visualization. Here, you will see your video with the track superimposed, and also plots of those three dependent variables. You can zoom in and out by picking the + and – magnifying glasses at the top, then click in the graph to zoom the timeline in and out, or click in the Y-axis to adjust that scale. You can check specific values at any point along the plots by hovering the mouse over those points. Here's an example of Activity and Activity States: For Mobility and Activity, you may find that the plots are very noisy. You can go back to the analysis profile and double-click them to edit the settings, then raise the Averaging Interval to remove some of that noise. That will convert the values to moving averages over the specified number of samples. Here's that same data averaging over 10 samples: Now look at periods with the behavior of interest (e.g. freezing, sleeping, active, seizures -- whatever you want to identify) and find thresholds that distinguish those periods from baseline behavior. Set up Movement, Mobility States, and Activity States accordingly. If you raised the Averaging Interval for Mobility, be sure to set it the same way for Mobility States, and likewise for Activity and Activity States. Then look at the integrated visualization again. Do the states correspond well with your behavior? You can adjust the thresholds up and down as needed. For Activity States, you can also exclude very short intervals (in the Activity States settings), if the behavior you are looking for is not brief (e.g. sleeping). View original HubSpot article · HubSpot article 190267935386 · Knowledge Base 187958790447 · Language en · Updated 1747518065816 --- ## After installation and starting TrackLab Viewer for the first time, it crashes. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/after-installation-and-starting-tracklab-viewer-for-the-first-time-it-crashes Chapter: Noldus Knowledge Base - Make sure you installed ALL three TrackLab components (Viewer, Server and Recorder). - Restart N-Linx. - Restart TrackLab Server. - If the problem persists, re-install all 3 TrackLab components. - If the problem persists, get R&D assistance. View original HubSpot article · HubSpot article 190556076835 · Knowledge Base 187958790447 · Language en · Updated 1748130916649 --- ## After recording for a long time, the TrackLab system becomes non-responsive with high memory and CPU load. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/after-recording-for-a-long-time-the-tracklab-system-becomes-non-responsive-with-high-memory-and-cpu-load Chapter: Noldus Knowledge Base The cause of this problem is variable. - Get the log files "C:\ProgramData\Noldus\TrackLab\2\Log", "C:\ProgramData\Noldus\TrackLab Recorder\2\Log" and "C:\ProgramData\Noldus\TrackLab Server\2\Log" - Get R&D assistance and share the log files. - If R&D finds no issues in the logs: (a) stop recording, reboot the PC and restart recording. This is a temporary solution. For the long-term: (b) recommend the user to apply a time interval of max 1 week for replaying data, viewing and exporting analysis results. Alternatively, (c) the user may opt to reduce the recording session duration (occasionally stopping-restarting recording). Note: raw data export is not affected by this performance bottleneck and can be exported for bigger time windows. - Note: the product roadmap includes hardware merging, i.e. selecting 1 higher performance PC to replace the current TrackLab PC and Sewio server PC. R&D aims to increase data processing performance with this improvement. Ask the Product Manager for more details. View original HubSpot article · HubSpot article 190573052078 · Knowledge Base 187958790447 · Language en · Updated 1748132789624 --- ## An overview of which software version is supported by which operating system URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/an-overview-of-which-software-version-is-supported-by-which-operating-system Chapter: Noldus Knowledge Base The Observer - The Observer 3, 4, 5: Windows 2000, Windows XP Pro (SP3) - The Observer XT 6: Windows XP Pro (SP3) - The Observer XT 7, 8, 9: Windows XP Pro (SP3), Windows Vista 32-bit - The Observer XT 10.0, 10.1: Windows XP Pro SP3, Windows 7 32-bit (SP1) - The Observer XT 10.5: Windows XP Pro SP3, Windows 7 32-bit or 64-bit (SP1) - The Observer XT 11: Windows 7 32-bit or 64-bit (SP1) - The Observer XT 11.5: Windows 7 32-bit or 64-bit (SP1), Windows 8 64-bit - The Observer XT 12: Windows 7 64-bit (SP1), WIndows 8 64-bit - The Observer XT 12.5: Windows 7 64-bit (SP1), Windows 8.1 64-bit - The Observer XT 13, 14: Windows 7 64-bit (SP1), Windows 10 - The Observer XT 14.1, 15, 16: Windows 10 EthoVision - EthoVision 2, 3: Windows 2000, Windows XP Pro 32 (SP3) - EthoVision XT 4: Windows XP Pro 32-bit (SP3) - EthoVision XT 5, 6, 7.0: Windows XP Pro 32-bit (SP3), Windows Vista 32-bit (SP1) - EthoVision XT 7.1, 8: Windows XP Pro 32-bit (SP3), Windows 7 32-bit (SP1) - EthoVision XT 9: Windows 7 32-bit or 64-bit (SP1), Windows 8 64-bit - EthoVision XT 10, 11: Windows 7 64-bit (SP1), Windows 8 64-bit - EthoVision XT 11.5: Windows 7 64-bit Professional (SP1), Windows 8.1 64-bit Professional - EthoVision XT 12, 13, 14: Windows 7 64-bit (SP1), Windows 10 Pro - EthoVision XT 15: Windows 10 Pro, tested version 19H1. - EthoVision XT 16: Windows 10 Pro, tested version 20H2 - EthoVision XT 17.0: Windows 10 Pro tested version 20H2; Windows 11 Pro, tested version 21H2 - EthoVision XT 17.5: Windows 10 Pro, tested version 20H2; Windows 11 Pro, tested version 21H2 CatWalk - CatWalk 7: Windows XP 32-bit (SP3) - CatWalk XT 8: Windows XP 32-bit (SP3), Windows Vista 32-bit (SP1) - CatWalk XT 9: Windows XP 32-bit (SP3) - CatWalk XT 9.1: Windows XP 32-bit (SP3), Windows 7 32-bit or 64-bit (SP1) - CatWalk XT 10, 10.1: Windows 7 32-bit or 64-bit (SP1) - CatWalk XT 10.6: Windows 7 64-bit (SP1), Windows 8.1 64-bit, Windows 10 - CatWalk XT 10.7: Windows 10 Pro, tested version 22H2; Windows 11 Pro, tested version 23H2 DanioScope - DanioScope 1.0, 1.2: Windows 7 64-bit (SP1), Windows 8 64-bit FaceReader - FaceReader 1, 2: Windows XP 32-bit (SP3) - FaceReader 3: Windows XP 32-bit (SP3), Windows Vista 32-bit (SP1) - FaceReader 4: Windows XP 32-bit (SP3), Windows 7 32-bit or 64-bit (SP1) - FaceReader 5: Windows 7 32-bit or 64-bit (SP1) - FaceReader 5.1:  Windows 7 64-bit (SP1), Windows 8 64-bit - FaceReader 6: Windows 7 64-bit (SP1), Windows 8.1 64-bit - FaceReader 7, 8, 9: Windows 7 64-bit (SP1), Windows 10 Media Recorder - Media Recorder 1: Windows XP 32-bit (SP3), Windows 7 32-bit (SP1) - Media Recorder 2: Windows 7 32-bit or 64-bit (SP1) - Media Recorder 2.5, 2.6: Windows 7 64-bit (SP1) - Media Recorder 3: Windows 7 64-bit (SP1), Windows 8.1 64-bit - Media Recorder 4: Windows 7 64-bit (SP1), Windows 10 - Media Recorder 5, 6: Windows 10 UltraVox - UltraVox 2: Windows 2000, Windows XP 32-bit (SP3) - UltraVox 3: Windows 7 64-bit (SP3) - UltraVox 3.1: Windows 7 64-bit (SP3), Windows 8.1 64-bit, Windows 10 - UltraVox 3.2: Windows 7 64-bit (SP3), Windows 10 Viso - Viso 1, 2, 3: Windows 8.1 64-bit - Viso 4, 5, 6, 7, 8, 9, 10: Windows 10 View original HubSpot article · HubSpot article 190556076819 · Knowledge Base 187958790447 · Language en · Updated 1748128292631 --- ## An unexpected power down resulted in inconsistent analysis results/database in TrackLab URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/an-unexpected-power-down-resulted-in-inconsistent-analysis-resultsdatabase-in-tracklab Chapter: Noldus Knowledge Base Problem Prevention: - Especially if unexpected blackouts are known to occur (not uncommon in remote/barn sites), recommend the use of an Uninterruptible Power Supply (UPS). Tell them to connect at least both PC's and the network switch to the UPS. - If there is a planned power outage, stop TrackLab recording before shutting off the PC, and restart recording after power is up again. - If there is an unexpected outage, you want to make sure to keep the Sewio PC downtime as short as possible to keep missing data to a minimum. If the TrackLab system installation went well, the Sewio PC has an automatic reboot setting enabled. This will make sure the PC restarts automatically when power is up again. However, if after the outage the PC was found switched off, assist the customer in enabling this setting in the BIOS settings, by following these instructions. Problem Solution: - Get the TrackLab log files "C:\ProgramData\Noldus\TrackLab\2\Log", "C:\ProgramData\Noldus\TrackLab Recorder\2\Log" and "C:\ProgramData\Noldus\TrackLab Server\2\Log". - Check for the log file entry “Fatal – This can only occur if the server is powered up while recording was ongoing”. If you find it, it confirms the database inconsistencies. Proceed with the next steps.  - If the customer is in the middle of an experiment recording session, proceed AFTER that recording session is finished. - If TrackLab is recording, stop it. - Use the database backup tool to make a backup. - Provide R&D with the backup. - R&D will returns the repaired database version. - Use the database backup tool to restore the repaired database on the customer PC. - TrackLab will now recalculate all analysis results, which may take a couple of hours. Note: - The R&D team is planning a fix to prevent the problem (planned for v2.12 - ask the Product Manager) but for the time being use the above workaround. View original HubSpot article · HubSpot article 190556076826 · Knowledge Base 187958790447 · Language en · Updated 1748129142943 --- ## Basler camera is not detected by EthoVision URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/basler-camera-is-not-detected-by-ethovision Chapter: Noldus Knowledge Base The following troubleshooting steps cover the various causes for a "camera not found" message as shown:   Solution 1: Check the connections on the PC and camera Please see Connecting a Basler camera.   Solution 2: Ensure that the correct Pylon driver is installed After checking your cabling and verifying all looks correct, then the next step would be to make sure that the correct Pylon driver is installed for your version of EthoVision XT. To check, please go to the Start menu and type in “Add or remove programs” and then click “Programs and Features” to get your list of installed programs. (In Windows 10, you can also get here from the Start menu, then click the Settings gear, then click Apps.) In that list, you should see a program named something similar to “Pylon X Camera Software Suite X.X.X.XXXXX”.   Please note: a) the correct version depends on the version of EthoVision XT you are using, and b) the version needs to be what is in the list (i.e., a “newer” version will not necessarily work). EthoVision XT version Pylon Software Suite version 17.0 6.2.0.21487 (and see below) 16.0 5.1.0.12681 15.0 5.1.0.12681 14.0 5.0.9 If you do not have the correct version installed, please un-install any other version (if relevant) by clicking on it and selecting “Uninstall” at the top, download/install the correct version using the links above, then restart your PC.   For Pylon 6.x and above: - Run or double click the downloaded file. - Accept the terms and conditions, then click Next. - Under Profiles, select Custom and click Next. - Under Features, choose GigE Camera Support (for GigE cameras which connect using an ethernet cable) or USB Camera Support (for Basler USB cameras), and... - Make sure to also select Pylon Viewer and DirectShow Support. The camera will not work in EthoVision if you do not select DirectShow during the installation. If you missed this step, uninstall Pylon and reinstall making that selection. - Complete the installation.   Solution 3: Check the IP address settings on the camera(s) and network port(s) Please see Check network settings for a Basler camera.   Solution 4: Turn off your PCs Firewall. If none of the steps above resolve the issue, then the last thing to try is to turn off your PC's Firewall. a) Go to the Start menu and type “Control Panel” b) Click on System and Security and then Windows Defender Firewall c) Click on Turn Windows Defender Firewall on or off on the left side of the screen and turn off all three options, then click OK. View original HubSpot article · HubSpot article 190573052044 · Knowledge Base 187958790447 · Language en · Updated 1748130480831 --- ## Blue screen error message at 53% installation of Media Recorder 4.0 - hardlock.sys fails URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/blue-screen-error-message-at-53-installation-of-media-recorder-40-hardlocksys-fails Chapter: Noldus Knowledge Base This driver of the HASP key is not compatible with Windows 10 resulting in the symptom with the hardlock.sys error every time when you attempt to install MediaRecorder 4.0. The solution is to install an updated HASP driver before installing MR 4.0. This forces the installation to skip the step with the old HASP driver installation, since a newer version was already installed.This driver should resolve the issue: HASP driver 8.13Run or double-click the downloaded file to install the driver. View original HubSpot article · HubSpot article 190573052282 · Knowledge Base 187958790447 · Language en · Updated 1748145383667 --- ## Camera is not detected in CatWalk XT 10.6 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/camera-is-not-detected-in-catwalk-xt-106 Chapter: Noldus Knowledge Base When CatWalk opens, the camera status will be shown in the lower right corner. If it displays "Camera detected: No," the camera has not been detected and it will not be possible to configure the camera or proceed with acquisition. You can, however, proceed with classification or analysis (which do not require the camera). The camera may not be detected if the camera has no power, the camera is still establishing a connection to the PC, the camera is connected to the wrong port, or the configuration is not correct. Basic requirements and reconnecting For the camera to be detected, the camera must be powered on, plugged in correctly, and ready before the CatWalk XT software was opened. Note that it may take up to 2 minutes after powering on the camera before it is ready. If you have corrected the issue, you can go on the menu under Setup to Camera, select your camera (it should be listed as Gevicam), and click Refresh. Closing and reopening the CatWalk XT software should also correct this issue. Camera has no power The CatWalk camera receives power from the Control Unit which is mounted at knee level on the left side of the CatWalk frame. The power switch on the left side of the Control Unit must be turned on, and the power cable for the Control Unit must be plugged in. The green and red lights on the walkway should be on. If your CatWalk has a power switch at the left side of the glass plate, this switch should be turned on at all times (newer CatWalk systems do not have this switch, they only have a switch on the Control Unit). When you turn on the power on the Control Unit, you should see the indicator LEDs on the right side of the Control Unit flashing for a short period of time. Once the Control Unit is on, these LEDs will turn off. So, it is a concern if they never turn on at all, but it is normal if they are off while in use. This picture shows the Control Unit from the back (this is the side facing the wall). The power cable from the camera plugs into "Cam Supply" marked "a" in the picture. The indicator LEDs are on the side. It will take 1-2 minutes for the camera to be recognized after it has been turned on before the CatWalk software will detect it. Closing and restarting the CatWalk software after the camera is ready will resolve the situation. Please note that the CatWalk walkway lights take up to 15 minutes to reach full brightness. The walkway should be turned on at least 15 minutes before it is used to set the detection settings or to acquire any runs. Camera is connected to the wrong port There are two cables connected to the camera. There is a tan cable which ends in a round metal plug, which should be plugged into the Control Unit (in the Cam Supply port labeled "a" in the image above). There is also a network cable which should go to a port on the back of the computer labeled "CatWalk Network". Do not plug the network cable into a port on the Control Unit; these are not network ports and will damage the camera. Computers provided by Noldus will have two network ports. One port is higher and located near the USB ports; do not use this port for the CatWalk camera, it is for use with your local network (if any). The other is lower and in the area with the metal slots, and will be labeled for CatWalk. Plugging the camera into the wrong port will result in it not being connected. When the camera is connected to the PC, there should be a green light where the network cable plugs into the back of the camera (facing the floor). This indicates connectivity to the computer. Camera settings You can test the camera directly. Close CatWalk, then go to the start menu and in the programs list find the Pleora Technologies folder, and then GEV Player listed in it. Click the Select/Connect button. You should see a window displaying a list of your network adapters. One should be labeled as the eBus Interface with a device listed indented beneath it. Select that device, click OK, then click the Play button. If you see an image from the camera, it is likely to have solved the underlying problem. Click Stop, close the GEV Player, and test the camera in CatWalk again. If it is still not working, return to the start menu and Pleora Technologies, then pick Driver Installation Tool. You will see a window like this: There will be one line for each network adapter in the computer (usually two). If the eBus Universal Pro Driver is not already selected for the Intel Gigabit CT Desktop adapter, select "Install eBus Universal Pro Driver" under Action, then click Install. Allow it to complete, then close it and restart the computer. View original HubSpot article · HubSpot article 190573052062 · Knowledge Base 187958790447 · Language en · Updated 1748131893662 --- ## Can a TrackLab 1 customer install a copy at home? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-a-tracklab-1-customer-install-a-copy-at-home Chapter: Noldus Knowledge Base Yes, they can but only for data analysis purposes. Instructions: - The customer installs a TrackLab 1 copy on their PC (make sure the PC meets the system requirements as outlined in the user manual). - After starting the application for the first time, follow the instructions in the interface to request a registration key. - Support receives the request. - Support verifies that the contact person indeed belongs to a registered TrackLab 1 account. - Support generates and provides a registration key within 24 hours to the customer. Note: If you never generated a TrackLab 1 registration key before, ask the R&D team (Ben Loke or Mike Kelia) to provide you with the key generation tool including instructions. View original HubSpot article · HubSpot article 190573052192 · Knowledge Base 187958790447 · Language en · Updated 1748137777675 --- ## Can a TrackLab GPS setup be installed by the customers themselves, with no on-site Noldus services? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-a-tracklab-gps-setup-be-installed-by-the-customers-themselves-with-no-on-site-noldus-services Chapter: Noldus Knowledge Base Yes, GPS system installation by the customer is possible. Unlike a UWB tracking setup, the GPS setup does not require the use of advanced calibration procedures. However, keep in mind that at this stage, there is still some level of online assistance by Operations or R&D required.  - The remote assistance by Operations or R&D is at the moment still required as the GPS system is still relatively new and there are system integration aspects that require attention (e.g. network, LoRa server configuration, tag settings). - The installation mainly consists of (a) installing the LoRa antenna at a high location (e.g. roof, pole), (b) connecting the antenna with the PC, (c) configuring the LoRa server and (d) preparing the GPS tags. View original HubSpot article · HubSpot article 190573052061 · Knowledge Base 187958790447 · Language en · Updated 1748131813227 --- ## Can EthoVision XT output a TTL signal for every video frame captured during a behavioral trial? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-ethovision-xt-output-a-ttl-signal-for-every-video-frame-captured-during-a-behavioral-trial Chapter: Noldus Knowledge Base FAQ and Step-by-Step Guidance Can EthoVision XT send a TTL pulse for every frame captured? - No. EthoVision XT’s I/O Box refreshes at 10 Hz, so it cannot output a TTL pulse for each video frame. The system can send signals at the start and end of tracking but not at frame-level frequency. What alternatives exist to mark frames or achieve high-frequency TTL output? - Use trial control to send TTL pulses at the start and end of each trial. This marks the period when tracking occurs. - Use the Eternal Data Module to send an ON/OFF or TCAP (time code) signal to synchronize with external devices. This requires a custom connection cable that connects to the EthoVision XT PC’s COM port. - If you need a TTL pulse for every video frame, consider using the camera’s frame-sync output (if available) to generate pulses directly from the camera instead of through the I/O box (not officially supported). - Alternatively, use an external microcontroller or signal generator to produce a continuous pulse train at the desired frame rate and align it with EthoVision’s start/end signals during post-processing. How can I synchronize EthoVision XT with external devices at high rates? - Configure EthoVision XT to send TTL pulses via the I/O box at key events (e.g., start and stop of recording). - Use the Eternal Data Module to send an ON/OFF or TCAP (time code) signal to synchronize with external devices. This requires a custom connection cable that connects to the EthoVision XT PC’s COM port. - For higher-frequency synchronization, connect external hardware (such as a camera’s frame output or a microcontroller) to the device you want to synchronize with. - Use EthoVision’s start and end pulses as markers to align your external signals with the recorded video during analysis. What if I still need per-frame synchronization? - Due to hardware limits, EthoVision XT cannot provide per-frame TTL via the I/O box. You may need to integrate the system with equipment that can provide a frame-sync output or consult the manufacturer for hardware upgrades. View original HubSpot article · HubSpot article 194772883748 · Knowledge Base 187958790447 · Language en · Updated 1755627155555 --- ## Can I add or alter zones in my Arena Settings after data acquisition in EthoVision XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-add-or-alter-zones-in-my-arena-settings-after-data-acquisition-in-ethovision-xt Chapter: Noldus Knowledge Base Arena Settings are normally set up before acquiring data in EthoVision XT, but you may decide at a later time point that the Zone(s) you used were not optimal (e.g., not the right size/position) and/or there are new Zone(s) of interest that you’d like to add. How can changes be made to those settings after the trial? Changing Zones After you have used a given Arena Settings to acquire data, certain features will be locked: your background image, calibration scale(s), and Arena(s) drawn. However, your Zone Group(s) and Zone(s) therein will not be locked (please note a few exceptions below). As such, you can alter existing zones (e.g., size, position, etc.), as well as add new Zone(s) to existing Zone Group(s) and/or add new Zone Group(s). You also do not need to re-track those trials and those new Zone(s) will automatically be available in your analyses. Note: If a Zone was used as a condition in your Trial Control Settings (e.g., stop the trial after the animal was in that Zone for 2 seconds), then the Zone Group (and all Zone(s) that Zone is in will be locked and cannot be modified.  In addition, all Hidden Zone(s) will be locked and cannot be modified.  The only way to modify locked Zone(s) would be to clear (or delete) all trials that used those Trial Control Settings and re-run those trials after modifying your Arena Settings.   New Arena Settings Any changes to the zones must be made in the same Arena Settings you used to record the trial. Creating a new Arena Settings profile with different zones will not affect previously-acquired trials.  If you need to apply a new Arena Settings profile (e.g., to change the calibration or the outline of the arena), you will need to Redo the trial from the video files. View original HubSpot article · HubSpot article 190573052075 · Knowledge Base 187958790447 · Language en · Updated 1748132577655 --- ## Can I get certain dependent measures (e.g., "distance moved") by zone in EthoVision XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-get-certain-dependent-measures-eg-distance-moved-by-zone-in-ethovision-xt Chapter: Noldus Knowledge Base It's possible to calculate any dependent variable in your Analysis Profile by zone(s). For example, you can get the “Distance Moved” within each quadrant zone in a Morris Water Maze study. This will reveal how much of the animal's total path length was in each of the quadrants. Solution: Use the “Results per zone” option in the Result(s) container. In your Data Profile, click on the “Settings” button for the Results container(s), check the “Results per zone” button, and check the zone(s) of interest that you would like to have the Dependent Measure(s) of interest in your Analysis Profile for that zone(s). Once finished in the Data Profile, go to your Analysis Profile and add the Dependent Measure(s) of interest (e.g., “Distance moved”). After adding the Dependent Measure(s) of interest in the Analysis Profile, go to Statistics & Charts and you should see the data broken down by zone(s). View original HubSpot article · HubSpot article 190573052255 · Knowledge Base 187958790447 · Language en · Updated 1748142850653 --- ## Can i migrate data from TrackLab 1.x to TrackLab 2? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-migrate-data-from-tracklab-1x-to-tracklab-2 Chapter: Noldus Knowledge Base General guideline: - We do NOT support data migration from TrackLab 1 to TrackLab 2. It is technically possible but since this concerns two architecturally different products, it involves a manual time-consuming (costly) process.    Exception: - If the customer persists or if there are special circumstances, talk to the Product Manager. Ask the customer how many projects and recording days they would like to migrate. The Product Manager will consult with the R&D team and determine IF we can support it and what the cost and delivery time will be. View original HubSpot article · HubSpot article 190573052077 · Knowledge Base 187958790447 · Language en · Updated 1748132729653 --- ## Can i migrate data from TrackLab 2.x to a newer version? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-migrate-data-from-tracklab-2x-to-a-newer-version Chapter: Noldus Knowledge Base - From version 2.0-2.3 to version 2.1-2.4: No, not possible. - From v2.4 upwards: yes, possible. Notes: - Before upgrading, first make a database backup with the Backup tool. Get the tool and user manual at the R&D team. Note: This tool is for use by Support only, not for use by customers. - Use this article to upgrade TrackLab. - Once you install a migration-compatible TrackLab server (version 2.4 upwards), it will automatically detect an already existing database and migrate the data to the new database. - Version 2.12 upwards will contain demo projects for (1) human indoor UWB scenario, (2) animal indoor UWB scenario and the (3) outdoor GPS scenario. During installation, you can choose to install these or not.   View original HubSpot article · HubSpot article 190573052197 · Knowledge Base 187958790447 · Language en · Updated 1748138141664 --- ## Can I share my project with another user that has a different version of The Observer XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-share-my-project-with-another-user-that-has-a-different-version-of-the-observer-xt Chapter: Noldus Knowledge Base Solution 1: If your colleague is using a “newer” (i.e., higher numbered) version of The Observer XT (or the same version), send them a backup of your project. If you are using an “older” (i.e., lower numbered) version of The Observer XT (or the same version), you can simply make and send them a backup of your project.  To do so, open the project of interest and go to File > Make backup.  It will prompt you with a window to ask where you’d like to save the resulting backup (.vpb) file.  After making the backup, you can send the .vpb file to your colleague and after opening their version of The Observer XT, they will go to File > Restore backup, point the software to the .vpb file you sent, and that will upgrade and restore the project on their PC.   Note: If you colleague is restoring a backup/opening a project from an older version of The Observer XT, they will get the following warning message.  Basically, it will upgrade the project to their version of The Observer XT and make a duplicate safety backup of the project in the original version.    Note: If you or your colleague does not see the option to make or restore a backup in the File menu, then you must be using a Coder license key.  To check what kind of license key you have, you can go to Help > About The Observer XT > License Info.  In the window that opens, you will see a “License Number” field (just below the name of the “Registered User”).   If the license number starts with “OC”, that means you are using a coder license key and you need to switch to a full license key after (will start with “OB” in the “License Info” window) in order to make and/or restore backups.  Please note you will need to close the software before unplugging/swapping license keys.  If using a physical hardware key (purple USB key) to access the software, a Coder license key will say “Observer Coder” on it, whereas a full license key will say “Observer XT" on it.   Solution 2: If your colleague is using an “older” (i.e., lower numbered) version of The Observer XT, send them your observation (.odx) file(s). If you are using a “newer” (i.e., higher numbered) version of The Observer XT, then the only way to share your project is to send them you observation (.odx) file(s).   Completed observations should to be exported as individual .odx files via File > Export > Observation Data > The Observer XT > check the “Create separate file per observation” box > OK.  You can then send those .odx file(s) to your colleague.   Once your colleague has those file(s), they can create a new (blank) project in their version of The Observer XT by going to File > New Project.   After creating this project, they will import those .odx files via File > Import > Observational Data and selecting the .odx file(s).  The coding scheme that was used to create those .odx files will be generated automatically for you.   Note: This procedure will work for versions of The Observer XT as low as 10.5.   Note: If your colleague does not see the option to make a New Project (i.e., they only see the “New Project from Template” option) in the File menu, then they must be using a Coder license key and will need to use a full license key instead.   View original HubSpot article · HubSpot article 190573052178 · Knowledge Base 187958790447 · Language en · Updated 1748136998659 --- ## Can I use a webcam with EthoVision? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-use-a-webcam-with-ethovision Chapter: Noldus Knowledge Base EthoVision XT (version 15), has been tested with two webcams, Microsoft LifeCam Studio and Logitech Brio. However, we do not recommend the use of webcams when timing of video frames is important, as they are not very precise and can drop frames. If needed, they can be used for simple tests, e.g., use a webcam to track one subject in an open field, to measure the total distance moved. Do not use webcams for multi-subject tracking, or tracking in multiple arenas, or with Behavior Recognition, or whenever the exact position of the subject’s body points at a specific time is needed. Moreover, test if the webcam still works when other software needed to run during the trials is open (e.g., PowerPoint for stimulus presentation), as other software may attempt to take control of the webcam. Verifying Performance As a general note, if you want to use a camera model other than the ones listed under ‘Cameras supported by EthoVision XT’ in the Help menu, make sure that the timing of the camera is accurate enough for a frame-level video analysis before starting an experiment. To do so, create a live tracking experiment, and carry out a test trial with the video footage of a digital clock for some ten minutes. Make sure you are getting less than 1% Missed Samples or Interpolated Samples during the trial (visible at the bottom of the screen in the acquisition or detection settings). Just before stopping the trial, check that the trial duration shown on your screen does not deviate from that obtained with the clock time. View original HubSpot article · HubSpot article 190271483186 · Knowledge Base 187958790447 · Language en · Updated 1747539537350 --- ## Can I use experiments from old versions of EthoVision in a new version when I upgrade? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-use-experiments-from-old-versions-of-ethovision-in-a-new-version-when-i-upgrade Chapter: Noldus Knowledge Base Existing experiments can be used in the new version (for versions as old as version 4, but not 3 or earlier). The first time you open an experiment from a previous version, it will be updated for the new version. However, note that it will no longer be possible to open those experiments in the old version; you can upgrade experiments but not downgrade them. No experiments will be removed even if you uninstall the prior version of EthoVision. View original HubSpot article · HubSpot article 190573052291 · Knowledge Base 187958790447 · Language en · Updated 1748146540295 --- ## Can i use other Noldus applications on the TrackLab PC? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-use-other-noldus-applications-on-the-tracklab-pc Chapter: Noldus Knowledge Base Guideline: - Recommend customers to, if feasible, use these applications on separate PC’s. - If customer persists, tell them they can install any other application on the TrackLab PC, and that it is OK to use that application while only the TrackLab Recorder and Server are running in the 'background'. However, they should NOT use the application alongside the TrackLab Viewer! Note: - If, after the installation of the other Noldus software, TrackLab or the other software does not run correctly, there may be an N-Linx server conflict. In that case, re-install N-Linx. View original HubSpot article · HubSpot article 190573052185 · Knowledge Base 187958790447 · Language en · Updated 1748137361643 --- ## Can i use TrackLab 2 on the same computer as TrackLab 1? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-i-use-tracklab-2-on-the-same-computer-as-tracklab-1 Chapter: Noldus Knowledge Base - TrackLab 1 and TrackLab 2 can be installed on the same PC, provided the PC meets the specifications required for both applications. - TrackLab 1 can be run with the TrackLab 2 server and recorder running in the background. - TrackLab 1 can not be used alongside the TrackLab 2 Viewer application. - It is not possible however to record track data using the same tracking hardware (be it Sewio or Ubisense). Only one application can be connected with the tracking hardware. View original HubSpot article · HubSpot article 190573052198 · Knowledge Base 187958790447 · Language en · Updated 1748138191665 --- ## Can my customer use their own PC brand/model to run TrackLab? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-my-customer-use-their-own-pc-brandmodel-to-run-tracklab Chapter: Noldus Knowledge Base They prefer a different PC brand and/or model, is that ok? - We only support TrackLab on our own tested and approved PC brand and model. - Exception 1) provided the PC meets the technical specifications, the customer may use their own brand/model at their own risk; performance and non-responsiveness problems will not be supported. - Exception 2) sometimes the customers IT department demands the PC systems to conform their system administrative guidelines which may include the use of a certain PC brand. If this involves a big Sales order you can talk to the Product Manager, in this case it may be possible for the customer to ship a PC to R&D where it can be stress tested to confirm compatibility.  They have the right brand and the specs almost meet the required specifications, is that ok? - No, don't compromise on the specs, or they will face problems with performance or the application becoming non-responsive. If they run into problems, the non-conformity of the specs are likely to complicate problem solving. View original HubSpot article · HubSpot article 190573052204 · Knowledge Base 187958790447 · Language en · Updated 1748138597655 --- ## Can we measure altitude data (z-coordinate) with TrackLab? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-we-measure-altitude-data-z-coordinate-with-tracklab Chapter: Noldus Knowledge Base TrackLab: Currently altitude measurement and export in TrackLab is NOT supported, for both indoor (UWB) and outdoor (UWB or GPS) tracking. There are 2 scenarios that we know certain demand exists for: - Measuring the vertical location of subjects, e.g. the amount of time laying hens spend outside, inside or below their elevated chicken coops. - Using the z-coordinate of neck-mounted tags on cattle, to feed the machine learning algorithm to output behaviors such as eating or posture.   Ask the Product Manager IF and WHEN this functionality is expected (depending product roadmap and Return of Investment).   Sewio Workaround for raw z-axis data: Sewio currently (2021) have a beta version of altitude measurement, based on barometer sensor measurement. Provided the customer has the appropriate hardware, they can measure and export altitude data from Sewio, however, Noldus do not support this and the process requires a tech-savvy person and some manual periodic re-calibration. Notes: - Measurement principle: Sewio uses barometer sensors to measure altitude; one sensor in each tag and one sensor in each anchor. By measuring the difference in altitude between anchor and tag, the system can calculate and visualize the altitude of each individual tag. - Required anchors: Vista Omni or Vista DirectFive, firmware v3 upwards (details). - Required tags: Leonardo iMU 4.7 and Piccolino 2.6, firmwars 3.118 upwards (details). - For more details, see the application note and demo video. - To enable the barometer sensors, see the sensor guide. - To export the z-axis data, ask the R&D team for the Python export tool. Side Note: One could expect it to also be possible to measure altitude data based on triangulation, just like the x-y measurement. Indeed this is possible with Sewio hardware, however, for accurate measurement, this requires placing anchors not only in the horizontal plane, but also in the vertical plane, i.e. high up and low down. In most TrackLab applications this is not practical due to the risk of damage or misalignment of the devices. It would also result in considerable extra hardware cost for the customer. Finally, Sewio claim that although they enable this form of z-axis measurement, they have not thoroughly tested and optimized it and therefore do not support it. Hence, WE also do NOT support this solution. Whenever we support Sewio-based z-axis measurement, it will be barometer based. View original HubSpot article · HubSpot article 190573052076 · Knowledge Base 187958790447 · Language en · Updated 1748132644650 --- ## Can you use different types of Sewio tags in the same TrackLab setup? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/can-you-use-different-types-of-sewio-tags-in-the-same-tracklab-setup Chapter: Noldus Knowledge Base Yes, you can combine any type of Sewio tag (e.g. Leonardo, Piccolino) in the same tracking setup. The tags can even have different settings (e.g. sample rate, sleep mode). View original HubSpot article · HubSpot article 190573052179 · Knowledge Base 187958790447 · Language en · Updated 1748137115637 --- ## Cannot connect to Viso Services or Connection with Viso Services Lost URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/cannot-connect-to-viso-services-or-connection-with-viso-services-lost Chapter: Noldus Knowledge Base If you encounter any errors about Viso Services, for example: - Cannot connect to Viso Services - Connection with Viso Services Lost …make sure that VisoServices is running via the Task Manager. Here is how: 1. Click on Windows Start button and type in Task Manager. Open the Task Manager app. 2. Click on the Services tab. 3. Locate VisoServices in the list. - If VisoServices is Running, stop and restart it by right-clicking on it and select Stop. - After the service stops, right-click on it and select Start. - If VisoServices is Stopped, right-click on it and select Start. 4. Now locate RabbitMQ in the list. - If RabbitMQ is Running, stop and restart it by right-clicking on it and select Stop. After the service stops, right-click on it and select Start. - If RabbitMQ is Stopped: right-click on it and select Start. 5. Now test the issue that created the error and see if it is now resolved. If not, please contact either your local IT or Noldus Support. View original HubSpot article · HubSpot article 195613327641 · Knowledge Base 187958790447 · Language en · Updated 1757088828051 --- ## Cannot retrieve information from Viso Services: Error 20021 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/cannot-retrieve-information-from-viso-services-error-20021 Chapter: Noldus Knowledge Base The is error is caused by Windows firewall blocking the Viso Services. To disable Firewall on all Viso computers: - Open Control Panel > System and Security - Click Windows Defender Firewall - Click Turn Windows Defender Firewall on or off on the left side of the window. - Under Overview, click Windows Firewall Properties - In each network zone, select Turn off Windows Defender Firewall (not recommended) - Click Close View original HubSpot article · HubSpot article 195690691502 · Knowledge Base 187958790447 · Language en · Updated 1757345062421 --- ## CatWalk shows unexpected error and experiment won't open URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/catwalk-shows-unexpected-error-and-experiment-wont-open Chapter: Noldus Knowledge Base Summary  A CatWalk XT experiment would not open. When the experiment first complained that it was created in a previous or newer software version, renaming the version.dat file to version.dat.old resolved the issue. Later, when the message appeared again, the version.dat was renamed to version.dat.old2, and the experiment immediately showed an unexpected error. Renaming or deleting this second file did not help, and attempts to delete corrupt settings files also failed. Other experiments opened correctly, so whether there was a way to salvage their main experiment. There are three possible reasons why CatWalk experiment show the unexpected error. The three FAQs below explain the detail and step by step instructions on how to fix the error FAQ 1 – How to Fix the “Unexpected Error” after renaming version.dat  Why does the error occur after renaming version.dat?  CatWalk XT uses the version.dat file inside each experiment folder to track the software version used to create the experiment. If multiple .old copies exist or the file is missing altogether, the software may throw an unexpected error when opening the experiment. Renaming the file incorrectly or deleting it can break the experiment.  How do I fix the error and open the experiment?  Follow these steps to restore the correct version.dat file and resolve the error:  - Locate the experiment folder  - In Windows Explorer, navigate to the folder where your CatWalk experiment is stored (usually under C:\Users\Public\Documents\Noldus\CatWalk\Experiments or a similar path).  - Revert the filename  - If you see files named version.dat.old or version.dat.old2, rename one of them back to version.dat. There must be only one version.dat file in the folder. Delete any extra .old or .old2 copies after you restore the correct file.  - Use a known‑good version file  - If the original version.dat file is missing or corrupted, copy version.dat from another working CatWalk experiment created with the same software version. Paste it into your problematic experiment’s folder and rename it to version.dat if necessary.  - Remove corrupt settings  - Some users fix unexpected errors by deleting settings files (e.g., Settings_*.xml or ExperimentConfig files). If your experiment still fails to open, try moving these settings files out of the folder (keep backups) and re‑open the experiment. CatWalk will recreate missing settings files.  - Test opening the experiment  - Launch CatWalk XT and attempt to open the experiment. If the error persists, repeat steps 2–4 or contact support for assistance.  By ensuring there is a single, valid version.dat file and removing corrupted settings files, you can usually recover an experiment that reports an unexpected error after renaming the version file.  FAQ 2 – How to Replace a corrupted .cwe file  What is a .cwe file?  In CatWalk XT, .cwe files contain the walkway definition for each experiment. If a .cwe file becomes corrupted (for example, after a failed edit or crash), the experiment may refuse to open or show errors.  How do I replace a corrupted .cwe file?  - Close CatWalk XT  - Go into the folder of the experiment that will not open (normally located here C://Users/Public/Public Documents/Noldus/CatWalk XT/Experiments/).  - Locate the CWE file. This is the MAIN file of your experiment and it is what is preventing the experiment to open for some reason. The restore.btn file is a backup ‘COPY’ of the CWE file.  - Right-click on your CWE file and add ‘OLD’ to the end. For example: Spinal cord injury.cwe - change it to Spinal cord injury.cweold.  - Now rename the restore.btn file to what your CWE file was originally. For example: restore.btn becomes Spinal cord injury.cwe.  - Now try and open the experiment as before. Open CatWalk XT and go File menu/Open. Load in the experiment’s CWE file.  FAQ 3 – Replacing a corrupted Version.dat file: Experiment will not open and error message states it was made with a previous version of CatWalk - Close CatWalk - If the original version.dat file is missing or corrupted, copy the version.dat file from another working CatWalk experiment created with the same software version. Paste it into your problematic experiment’s folder and rename it to version.dat if necessary. - It will ask you if you want to overwrite, click Yes. - Open CatWalk and try loading in your experiment again. It should load in fine now with no errors. Please make a backup of your experiment via File menu/Make Backup. Archive the CWZ file for safe keeping. Backup daily or weekly. These instructions address both the unexpected error caused by renaming version.dat and the procedure for replacing a corrupted .cwe file. Following these steps should help you recover the experiment and resume analysis.  View original HubSpot article · HubSpot article 195293378117 · Knowledge Base 187958790447 · Language en · Updated 1756485006038 --- ## CatWalk XT 10.0, 10.5, or 10.6 does not open URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/catwalk-xt-100-105-or-106-does-not-open Chapter: Noldus Knowledge Base The CatWalk XT 10 software may fail to open or fail to start up if the camera has not connected properly, if you do not have access to necessary files, or if there is a problem with the settings files. CatWalk creates a log file which can be used by Noldus support to identify the specific issue. Camera not connected properly This issue will only occur if the walkway is connected to the computer and powered on. If this is the issue, after shutting off power to the walkway, the software will open correctly. Normally this can be solved by shutting off the walkway, wait 10 seconds, turn the walkway on, and wait one to two minutes before opening the CatWalk software. This resets the camera and resolves most issues. Insufficient access CatWalk may not open if you are logged into the computer with a Guest account or other account with restricted access. It will also not open if the first person to use CatWalk on this computer after its installation had administrative access, but you do not. If this occurs, the easiest resolution is to delete the settings files (see below) and then open CatWalk using a regular (non-administrative) account. The problem will not occur in that case. Opening CatWalk with an administrative account will not cause any problems as long as it was first opened with a regular account. Invalid settings files CatWalk may not open if one of the settings files is corrupted or damaged. The settings files are located in this folder: - C:\ProgramData\Noldus\CatWalk\XT 10.6\Settings\ Note that ProgramData is a hidden folder. If you don’t see it, in Windows 7 or 8 press the Alt key to get the menu, then go to Tools, Folder Options, click the View tab, and then under Hidden Files And Folders select “Show Hidden Files, Folders, and Drives”, then click OK. In Windows 10, click View on the ribbon and check the box to view hidden files. You can selectively remove settings files and try opening CatWalk. Any missing files will be recreated. Removing all of the settings files will resolve this for certain. However any relevant settings will be lost (e.g., if you remove “detectionsettingsprofiles.dat”, you will need to redo the detection settings). So it may be worth your time to remove them selectively to determine which file(s) are the issue. Check the log file There may be a log file which will help us diagnose the problem. If so, it will be in - C:\ProgramData\Noldus\CatWalk\XT 10.6\Log\ Note that ProgramData is a hidden folder. If you don’t see it, in Windows 7 or 8 press the Alt key to get the menu, then go to Tools, Folder Options, click the View tab, and then under Hidden Files And Folders select “Show Hidden Files, Folders, and Drives”, then click OK. In Windows 10, click View on the ribbon and check the box to view hidden files. Send this log file to Noldus support and we can diagnose the problem for you.   View original HubSpot article · HubSpot article 190573052029 · Knowledge Base 187958790447 · Language en · Updated 1748128767387 --- ## CatWalk XT classified footprints are grayed out URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/catwalk-xt-classified-footprints-are-grayed-out Chapter: Noldus Knowledge Base Use of the Data Segmentation Profile (or accidentally selecting it) can result in footprints that have been classified being excluded in the visualizations and statistics. Filtered out results will look like this in the Run Visualizations: And in the Run Statistics:   The “Data Segmentation Profile” is active/too restrictive On the left bottom of the CatWalk window under “Profiles Explorer”, there is a section labeled “Data Segmentation Profile”. By default, the one called “All data” is active (i.e., in blue). If however, the one called “Data Segmentation Profile 1” (or any other except “All data”) is active, it will restrict the data output to footprints during a run within the parameters specified: The Data Segmentation Profile can be very useful if you want to examine the effect of different settings or variation in walking speed. However, it can be a surprise if you've accidentally clicked on it and now don't see any results! To resolve footprints from being grayed out, either change the parameters above to be less restrictive or re-activate the “All data” profile (either by double-clicking it, or right-clicking it and selecting “Set as active”) and that should clear it the issue.   View original HubSpot article · HubSpot article 190556076850 · Knowledge Base 187958790447 · Language en · Updated 1748134128670 --- ## Changing the exposure settings for Basler cameras URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/changing-the-exposure-settings-for-basler-cameras Chapter: Noldus Knowledge Base Exposure is the amount of time the camera spends acquiring a video frame. Raising the exposure permits more light to reach the camera sensor, brightening the image, while lowering the exposure reduces the amount of light, darkening the image.  The image brightness is also affected by the aperture setting on the lens (this is the adjustment ring on the lens marked open-close, turn it to Open to brighten the image), the gain setting of the camera, and the lighting. If the image is too dark, it's usually best to start by opening the aperture on the lens, but increasing the exposure can also be helpful. Also see My image is too dark using a Basler camera which covers exposure but also gain and the aperture setting on the lens. Solution 1. Close your Noldus software (e.g., MediaRecorder or EthoVision XT) on the PC. 2. Start the Basler Pylon Viewer software that comes with the camera.  - NOTE The Basler Pylon Viewer software is installed automatically when you install the camera drivers. The icon will normally be on the desktop. Otherwise, look in the start menu under Basler. 3. Choose Tools > Options and check that the User level is set to Expert or Guru.    4. In the Devices panel, double-click the item Basler under GigE or USB depending on the camera you have.  5. In the Features panel, open the Basler camera item and then double-click Acquisition Controls.  - NOTE If you do not see the Features panel, go on the menu to Window and make sure the Features option is checked  6. Makes sure Exposure mode is set to Timed  7. Make sure Exposure Auto to set to Off.  8. Set Exposure Time (Abs) [us], enter the exposure time you require, in microseconds. Press Tab or click another field to confirm.  - NOTE A higher exposure setting will result in a brighter image, while a lower exposure setting will result in a darker image. However, too-high exposure will result in dropped frames, and too-low exposure may result in an image that flickers or changes rapidly between light and dark.  For non-DanioVision set-ups, this value will typically vary between 8,000 and 25,000 depending on your lighting needs and your Gain setting in Pylon (more on Gain below). You can reduce the value below this range if the image is too bright, but don't exceed 25,000. IR lighting is the exception to the above. When tracking in IR with an NIR GigE camera, you may need an exposure setting around 30,000 in order to brighten up the image enough for tracking in EthoVision. You may need to reduce the frame rate if you use such a high exposure. For DanioVision setup, values should be 4000 (with a camera resolution of 1280x960) or 2000 (with a camera resolution of 640x480).  9. To check that the exposure time is compatible with your frame rate, click the Continuous Shot button on the toolbar.   10. At the bottom of the live video window, locate the frame rate resulting with the new exposure time. This should be the same as the one next to Acquisition Frame Rate (Abs) [Hz]. (Noldus recommends 25 or 30)  11. If the resulting frame rate is lower than Acquisition Frame Rate (Abs) [Hz], then either: a. lower the exposure time (this will darken the image) and instead raise Gain (Raw) (under Analog Control; this will make the video image brighter), b. open the lens diaphragm (aperture) to compensate for this (if not done already), or  c. lower the video resolution.   This is under AOI Controls and can be reduced by lowering the Width and Height. This will help if your exposure setting is close to the limit, but if the exposure is very high, changing the resolution will not solve this on its own.   - NOTE Lowering the resolution will make the image look more “zoomed in”, it will crop the image to the selected resolution. Also, make sure the Center X and Center Y are checked or else the cropped image will be off-center.    d. lower the frame rate. Note that you will also need to use the lower frame rate in EthoVision. If your frame rate selected in EthoVision is too high for your exposure setting, you will see high numbers of Missed Samples or Interpolated Samples in EthoVision, indicating that the camera is not providing the correct number of video frames. Repeat steps until you see the expected framerate. 12. Once finished, stop the Continuous Shot  and open the Configuration Sets item and:    a. select User Set 1 from the Configuration Set Selector, b. click Execute next to User Set Save (the camera settings set in the previous steps are now saved under User Set 1), c. select User Set 1 from the Default Startup Set list, d. close Pylon Viewer.  - NOTE These settings will be used each time you start up your Noldus software.   TIP You can also save different settings for the same camera in User Set 2 and User Set 3. Under Default Startup Set (User Set Default), select which you want Noldus software to use. View original HubSpot article · HubSpot article 190271421083 · Knowledge Base 187958790447 · Language en · Updated 1747519022161 --- ## Check network settings for a Basler camera URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/check-network-settings-for-a-basler-camera Chapter: Noldus Knowledge Base Basler GigE cameras connect to the computer using a network cable, and as such must have network settings configured accordingly. If the camera is not detected, but is connected properly, check the network settings. If you've checked these settings and the camera is not detected, also see Basler camera is not detected by EthoVision. Camera Settings As part of the drivers for the camera, Basler provides the Pylon IP Configurator to check and adjust the settings for the camera. Go to the Start menu and type “Pylon IP Configurator” and open the program. (The Pylon IP Configurator may also appear as an icon on the desktop, or you can find it on the Start menu under Basler.) If it says your camera is “not reachable”, then there is an issue with the compatibility of your camera’s IP address with the network port’s IP address. If you click on the camera that is “not reachable”, you can find the camera’s assigned IP address (and Subnet Mask) on the bottom left.  The following IP addresses (and subnet masks) should be used: Camera 1: 192.168.200.1 (255.255.255.0) Camera 2: 192.168.201.1 (255.255.255.0) Camera 3: 192.168.202.1 (255.255.255.0) Camera 4: 192.168.203.1 (255.255.255.0) NOTE The IP address for each camera is the same except for the third set of numbers underlined above. Also, make sure the Subnet Mask is 255.255.255.0 (not 255.255.0.0). If you need to change a camera’s IP address and/or Subnet Mask (e.g., camera was not provided by Noldus), then do so in the Pylon IP Configurator and click “Save”. After changing and saving the IP address and Subnet Mask, the camera should report that it is “OK”. (Note: do not copy the settings shown in the image below, use Static IP and the IP addresses as listed in the text above.) Network Adapter Settings If the camera is still “not reachable”, then the network port that the camera is plugged into also needs to be changed. To change the network port’s IP address: a) Go to the Start menu and type “Control Panel” b) Go to Network & Internet and then View network status and tasks. c) Click Change adapter settings on the left side of your window. d) Right-click the Local Area Connection and click Properties. If your computer has more than one Local Area Connection, choose Noldus Camera Network #. Write down the number of this connection. NOTE If your network card has 2 or 4 ports, you will need to assign an IP address to EACH port for EACH camera. You will see something like this on your PC (note you will NOT see “Noldus Camera Network” UNLESS you bought the PC from Noldus). Also, if you are unsure what port a camera is connected to, unplug the cable and watch for a red X to appear with the message "Network cable unplugged." When you plug it back in, that red X will go away.   e) Select Internet Protocol Version 4 (TCP/IPv4) and click Properties.  f) Select Use the following IP address and type in the IP address you will assign to this card/port. Network port for Camera 1: 192.168.200.101 (255.255.255.0) Network port for Camera 2: 192.168.201.101 (255.255.255.0) Network port for Camera 3: 192.168.202.101 (255.255.255.0) Network port for Camera 4: 192.168.203.101 (255.255.255.0) (Don't use the IP address shown in the picture, use the addresses listed above.)  When done, click OK and then Close. You may need to restart the computer for all network issues to resolve. NOTE The IP address for each camera’s network port is the same except for the third set of numbers underlined above. Also, the Subnet Mask of 255.255.255.0 should autofill once you click in that field. Lastly, note that the IP address assigned to the network adapter will match the first three numbers of the IP address of the camera, e.g. 192.168.200, but the last number will differ, .101 for the network adapter as shown here whereas it will be .1 for the camera.  View original HubSpot article · HubSpot article 190573052214 · Knowledge Base 187958790447 · Language en · Updated 1748139386675 --- ## Checking your license number URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/checking-your-license-number Chapter: Noldus Knowledge Base To determine the full version number of your software, go on the menu to Help > About. To determine the license number or name of the registered user, from the About window click the User Info or License Info button (depending on which software and version is used). Noldus license numbers associated with hardware license keys (dongles) begin with two letters indicating the software (e.g. EV for EthoVision), followed by the version number (e.g. EV150 is for EthoVision XT 15.0), and then a unique identifying five digit number. Additional letters may indicate add-on modules. Software-based license numbers are randomized and do not provide any information; contact Noldus support if more information is needed about your license. In FaceReader, the license number and name of the registered user are displayed in the About window without clicking User Info or License Info.   View original HubSpot article · HubSpot article 190573052022 · Knowledge Base 187958790447 · Language en · Updated 1748128361375 --- ## Color-marking animals for EthoVision URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/color-marking-animals-for-ethovision Chapter: Noldus Knowledge Base In EthoVision XT there are two methods for tracking animals with color markers: - Color marker tracking (treat marker as center point) — Only the colored marker is tracked, not the whole animal, so nose-point and tail-base tracking is not possible. It is suitable for any species. - Marker assisted tracking — Tracks the animals’ body using the usual contrast methods, and then in addition use the marker to determine the animal’s identity. You can use this method in social interaction tests where you need to track the nose point and tail. In each case, you'll need some kind of colored mark on the animal which can be tracked. Lighting conditions Lighting conditions play an important role in ensuring different colors can be distinguished. - It must be bright enough — Dark or dim conditions can result in low contrast between the animal and the background and therefore tracking might not be optimal. Dim light also makes it difficult to distinguish colors. When it is not possible to use strong illumination in your setup, try using fluorescent marker colors with UV lighting. - It must be even — Lighting should be diffuse, e.g., coming from multiple directions, through a diffuser, or bounced off the ceiling. This keeps colors and contrast consistent throughout the arena. - For optimal color separation, illuminate your setup with lamps that approximate to day-light in color temperature, that is, have a wide spectrum range. General Tips for Markers EthoVision distinguishes markers on the basis of Hue, Saturation, and Brightness. Hue is the color (e.g. red vs blue), saturation is how colorful it is (high saturation is colorful, low saturation is muddy and grayish), and brightness is light vs dark. Some general tips: - Use hues that are widely separated. For example, use red and green, not red and orange. - It may be wise to avoid using red for marking, since it looks like blood. - If the color of your marker is also present elsewhere in the arena, you can get rid of it by setting a minimal marker size in EthoVision, excluding areas with that color from the arena, or use a different colored marker. - Marking animals may stress them, and therefore affect their behavior. A longer-lasting method requires less handling and can be used farther in advance. - If you need to record in dark conditions, using UV illumination with fluorescent markers can provide enough visibility. This is most suitable when you are only tracking the colored marker and not the outline of the animal (i.e., no nose-point and tail-base tracking). - Place the marker where it can be seen by the camera, preferably on the center of the animal's back. A marker on the head of an animal may go out of view when the animal looks down. - Make the mark as round as possible, this will ensure that the relative movement of the center of gravity of the marker is the same in all directions when the edges of the marker change due to posture changes or otherwise.  - Don't make the marker too big if using marker-assisted tracking; the marker may interfere with proper detection of the body contour. For example, make sure that a dark marker on a white animal does not cover the complete width of the animal because it can cause the body to be split in two. Small mammals (and birds) These methods work with many small animals, e.g., mice and rats. Many also work with birds. - Chalk markers ( https://www.chalkink.com/ ) and terracotta markers are each types of non-toxic opaque paint markers which work well even on dark-colored animals. - Livestock markers intended for large animals can also be used on smaller animals. These markers come as paint sticks and spray cans, and are available in many colors including fluorescent ones. The markers are weather-resistant, non-toxic and stay on for one or two days. See links under Large Mammals below. - The fur of rats and mice can be marked with commercial products for dyeing human hair. Dark fur can be bleached (like dark human hair, to make it blonde) before coloring. Hair dyes are available in many bright colors, and provide long-lasting coloration. Schwarzkopf PolyColor Hair color Cream, for example, can be applied to rat’s fur with a cotton swab. - Permanent marker pens present a cheap and easy way to mark small mammals. Take care to make a large and uniform blob. This method may only work for a short period of time as many species may remove the mark by grooming. - It is advised not to mark the animals immediately before starting a test, because handling of the animals might affect their subsequent behavior. If you use a marker that stays on the animal for only a short period of time, habituate the animal to the marking procedure. - Colored ‘jackets’ can be used to color-track mammals with colored fur. Jackets cover most of the cat’s back, and can be provided with velcro strips, so one can place pieces of cloth of different colors to test optimal color combinations. Orange vests may give problems when animals are red-haired, so it should be replaced by either (bright) green, yellow or pink. Large mammals You can use livestock markers to mark large animals such as cows, sheep and pigs. Examples include: https://carmelindustries.com/collections/livestock-markers https://markal.com/pages/all-weather Fish (and amphibians) Fish can be color marked by attaching plastic pearls. This technique has been used successfully in Mediterranean damsel fish (Chromis chromis, size: about 9 cm long). Colored pearls with a diameter of 1 cm can be bought from a toy store. The pearls can be attached under the dorsal fin with blue non-resorbable surgery polyamide mono filament (for example, from B/Braun), using a surgical needle under anaesthesia. The fish can be anesthetized by placing them in a small tank with 2-phenoxy-ethanol (0.3 ml/l for the damsel fish) for five minutes, before attaching the pearl. The bottom and sides of the arena have to be very dark. The pearls do not significantly impair swimming in damsel fish (Source: M. Ylieff, Institut de Zoologie, Université de Liège, Belgium). Visible implant fluorescent elastomer (VIE) tags are produced by North west Marine Technologies (NMT). https://www.nmt.us/visible-implant-elastomer/ VIE material is implanted beneath transparent or translucent tissue (it may become difficult to detect it beneath pigmented tissue). The material is injected as a liquid and soon turns into a pliable, bio-compatible solid. VIE colors are visible under normal lighting conditions and have greatly enhanced visibility under ultra-violet light or with other fluorescence enhancing techniques. You can test which colors work best in your own setup with a color test patch from NMT. (Source: J. Merilä, Evolutionary Biology Centre, Uppsala University, Sweden). VIE tags also work with tadpoles. Reptiles Nail polish (available in many colors) can be used to mark lizards. The mark usually lasts 10 days in small (up to 10 cm) lizards in the field. (Source: M. Massot, Laboratoire d’Ecologie, Université Pierre et Marie Curie, Paris, France). Insects Acrylic paint (for example, Talens Decorfin) can be used to mark insects. The paint can be applied with a fine brush or thread. Hold the insect with forceps until the paint is dry (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands; S. Belmain, Natural Resources Institute, Chatham Maritime, UK). Some species of parasitic wasp develop a colored abdomen when you feed them honey with non-toxic food coloring. The advantage of this method over marking with paint is that you do not have to anesthetize the insects (which may influence their behavior and survival). The method works best in insects with unpigmented abdomens (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands). You can also use visible implant fluorescent elastomer (VIE) tags (see ‘Fish’ above). View original HubSpot article · HubSpot article 190573052209 · Knowledge Base 187958790447 · Language en · Updated 1748139032168 --- ## Configuring or reconfiguring new or existing tags URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/configuring-or-reconfiguring-new-or-existing-tags Chapter: Noldus Knowledge Base Customers frequently order extra tags to track more subjects in their existing tracking setup. Or they might want to replace a defective tag. Tags come with default settings. Sewio delivers the tags to us with Sewio defaults. We deliver the tags to the customer with Noldus defaults that differ slightly from the Sewio defaults. And finally there is the customer that might have reasons to change these defaults, for example to increase the sample rate or sleep mode refresh rate. This article includes instructions for checking and editing the tag settings. Preparation: - Make sure the tags are switched on. For the Leonardo this means press the enclosure for 2 seconds. For the Piccolino, inserting the coin cell battery in the enclosure will switch it on. If there is already a coin cell in it, the enclosure will need to be opened and the switch needs to be pressed for 2 seconds. - Make sure the tags are charged. Select a Tag Configuration Mode: - Wireless configuration using the Android app (NFC). This is the recommended option since it uses NO energy and it does NOT require you to switch the tags on and off to load the settings. Find the instructions below. - Wireless configuration through RTLS Manager. Choose this option if you don't have an Android phone available. Note that this option will use energy from the tag battery. It also requires access to the TrackLab PC. Find the instructions below.   Option 1: Wireless configuration using the Android app (NFC): You can download the 'Sewio Leonardo Configurator' Android app from Google Play. Reading the configuration of your tags  Go to the Sewio Leonardo Configurator home screen and read the tag using the smartphone NFC reader. Make sure the NFC interface on your smartphone is turned on. Try to put the front side of the tag to the NFC "sweet spot" of your smartphone. Doing this for the first time means you may have to maneuver the tag against the back of your phone a bit to find the NFC connection. The tag configuration shows on the screen. To view all the parameters simply scroll down by swiping up. Creating a New or adjust your tag configuration To make a new configuration tap on the "CREATE NEW CONFIGURATION" button. The 'Create Configuration' screen will be shown: Set desired parameters and tap on 'START SENDING' button. The 'Write Configuration' screen appears: Move the front side of the tag to the NFC "sweet spot" of your smartphone and wait until the confirmation message appears >> the phone vibrates, and the MAC address of the tag appears on the screen. It will take about 5 seconds until the new configuration is written to the tag's memory, which is indicated by three fast blinks of the LED diode. You may configure more tags if you stay in the 'Write Configuration' screen. Copying the Configuration of a Tag If you have a tag that you know has the correct configuration, it is also possible to copy that configuration to other tags. Go to the application home screen and read the tag (see section 'Reading the configuration of a tag'). Once the app has read the configuration, tap on the "COPY TAG CONFIGURATION" button and check the values. If desired, you may edit any setting of the configuration. Then proceed to the 'Write Configuration' screen using the "START SENDING" button and apply the configuration to other tags.   Option 2: Instructions for wireless batch-configuration through RTLS Manager: - Sign in to RTLS Studio: https://192.168.225.2 - Go to “RTLS Manager” - Go to “Anchors (Basic)” and then “Summary” - Select one anchor that is going to be used for the configuration process. In general any anchor should do just fine. In case of doubt, pick one that is easily visible in the site. - Configure the anchor to use Blink Profile RF 4 and press “UPDATE” for the particular anchor. A notification should be shown after applying the update. - Follow the steps in this article to reconfigure the tags. Please make sure...: - ...to use the anchor that was selected previously in the previous step. - ...that the new tags are ‘visible’ to the selected anchor. - ...that tags are set to the default RF5 channel. It should be the same for all tags and anchors. - ...to check the tag firmware version. It should be at least version FW 3.120.0 or newer. Normally, new tags should have the latest firmware version already. If necessary, update the firmware. Also check the RTLS Studio version compatibility and if necessary also update RTLS Studio. Please note that only Sewio partners (i.e. Noldus) can download firmware updates from the Sewio partner portal and provide to the customer. - ...that all other tag settings match those of the other tags, unless the customers wants to deviate intentionally. - Go to RTLS Studio/Sensmap to see if the tags show up, by moving the tags in the tracking area. You might have to move to a different area in the tracking area as the anchor that was reconfigured doesn’t participate in the localization anymore. - If all tags are visible, configure the anchor again, to use Blink Profile RF 4 and press “UPDATE” for the particular anchor. A confirmation message should be shown after applying the update. Check if localization works again in all areas of the tracking area by moving a tag around. If the above procedure was not successful, try these troubleshooting steps: - Check if the tag PCB is placed correctly in the enclosure, i.e. with the charging coil facing the flat side of the enclosure. - Check the on/off button on the tag PCB. In rare occasions, the button is touching the enclosure even if no pressure is applied from the outside, unintentionally resulting in an activation-deactivation loop. - Get R&D assistance. - If necessary, start an RMA procedure. Find more details here. View original HubSpot article · HubSpot article 190556076844 · Knowledge Base 187958790447 · Language en · Updated 1748132876849 --- ## Configuring the Epiphan Broadcaster in FaceReader URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/configuring-the-epiphan-broadcaster-in-facereader Chapter: Noldus Knowledge Base In order to stream screen capture with an Epiphan Broadcaster in FaceReader, the screen codec for the Broadcaster must be changed from H.264 to Motion Jpeg. - Connect to the Epiphan admin page with a web browser, by entering the URL http:///admin.  The username is "admin", and the password may be left blank (unless you have configured it otherwise). - Click on the Stream Setup in the menu down the left side of the screen. - At the very top there is a codec setting with a drop down window.  Select Motion JPEG. - Scroll all the way to the bottom of the page and click Apply. - Click on Info and you will see under streaming info the URL to the MJPEG stream:  http:// Restore Backup, then select your file. The project folder and all of its contents will be created, and the project will be opened. The project file has been renamed Normally, the .vop project file should be in a folder with the same name, e.g., you might have a project “Behavior Study” which will have a folder “Behavior Study” containing a project file “Behavior Study.vop”. If you rename the .vop file, and then make a backup, and then restore that backup, The Observer will not find the .vop under the name it expects and you may receive this error. In this case the project folder should still be created and the file names can be corrected there. Backups are normally restored to the default project folder: C:\Users\Public\Documents\Noldus\The Observer XT\Projects\ If you have designated a different folder as the default location for your projects, that is where the backup will be restored to as well. The project database is damaged or corrupted If neither of the above issues apply, the project database may be damaged. The Observer maintains a backup copy of the project database in a file named “restore.btn”. You can rename the files to use that backup copy: - Rename the .vop file (e.g. “Behavior Study.vop.old”). - Rename the restore.btn file to the exact original name of the .vop file including the extension (e.g. “Behavior Study.vop”). - Open the project in The Observer. Note that if Windows is hiding extensions (e.g. the “.vop” part of the project file name), it may prevent you from changing the extensions. In Windows 7 and 8, click the Alt key to show the menu, then go on the menu to Tools/Folder Options, pick the View tab, and uncheck the option “hide extensions for known file types”. In Windows 10, click View on the ribbon and check the option to show file extensions. Restoring the project from the restore.btn file may lose work from your last session with The Observer, but should recover the rest. The restore.btn file will not be present in projects from very old versions of The Observer. In that case, it may be necessary to restore the project from a project backup. Regardless of the version, we recommend making regular backups of your data. You can make a backup of your project from within The Observer by going on the menu to File > Make Backup. Keep a copy of these backups on a separate hard drive, e.g. on a network drive or external drive, so they will be available if the original drive fails. View original HubSpot article · HubSpot article 190556076821 · Knowledge Base 187958790447 · Language en · Updated 1748128540257 --- ## Do we charge customers for TrackLab updates and upgrades? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/do-we-charge-customers-for-tracklab-updates-and-upgrades Chapter: Noldus Knowledge Base General guidelines: - All upgrades from TL1 to TL2 are free of charge. This applies to the software. Any hardware (anchors, tags, etc) of course will have to be paid for. - All point updates (e.g. 2.8 > 2.11) are free, as long as they are performed under NoldusCare. - Future upgrades: upgrades from TrackLab 2 to TrackLab 3 will come at a cost. There will also be optional add-ons. For more information, ask the Product Manager. View original HubSpot article · HubSpot article 190556076866 · Knowledge Base 187958790447 · Language en · Updated 1748138025666 --- ## Do you need a dongle or license key to use TrackLab 2? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/do-you-need-a-dongle-or-license-key-to-use-tracklab-2 Chapter: Noldus Knowledge Base - Version 2.0 - 2.10: No license key nor dongle required. - Version 2.11: This is a custom version (for smartphone and Sodaq GPS tracking) that requires a Software Registration key. - Version 2.12 and up: A Software Registration key is required, but no dongle. View original HubSpot article · HubSpot article 190556076843 · Knowledge Base 187958790447 · Language en · Updated 1748132375672 --- ## Does The Observer XT support H265/Hevc codec? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/does-the-observer-xt-support-h265hevc-codec Chapter: Noldus Knowledge Base The Observer XT does not support the H265/Hevc codec. The only option is to convert your media file(s) into a codec that we do support. Please check the reference manual for the list of supported formats (look under Media Files > Supported Format). View original HubSpot article · HubSpot article 190556076905 · Knowledge Base 187958790447 · Language en · Updated 1748145519706 --- ## Error contacting the license server in The Observer XT 16 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/error-contacting-the-license-server-in-the-observer-xt-16 Chapter: Noldus Knowledge Base If you are using The Observer XT 16 with a software-based license (and not a hardware license key), and receive the following message, please update The Observer XT 16 to the latest version, which you can find in the Downloads area of this site. - Error contacting the license server. Check your internet connection, your firewall or the license server may be offline. If you use a proxy server, you must configure your proxy server settings. Unable to connect to the remote server - URL: https://qlmlicenses.noldus.com:9999/qlmlicenseserver/qlmservice.asmx This message appears if the version of The Observer XT 16 you have installed is 16.0.1201. It was resolved in 16.0.1203. You can check the version of The Observer you have installed by going on the menu to Help > About The Observer. View original HubSpot article · HubSpot article 190573052265 · Knowledge Base 187958790447 · Language en · Updated 1748143522660 --- ## Error E01 on the DanioVision Temperature Control Unit URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/error-e01-on-the-daniovision-temperature-control-unit Chapter: Noldus Knowledge Base Error E01 indicates the temperature sensor is not detected. Most likely it is either unplugged or not fully plugged in. Check that there is a cable that goes from the “Temp” jack on the back of the DanioVision to the “Temp” jack on the back of the Temperature Control Unit. This is connector 5 in the images below. Check that the cable is firmly plugged into the correct port on each device.     View original HubSpot article · HubSpot article 190556076829 · Knowledge Base 187958790447 · Language en · Updated 1748129498237 --- ## Error Messages on the DanioVision Temperature Control Unit URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/error-messages-on-the-daniovision-temperature-control-unit Chapter: Noldus Knowledge Base The DanioVision Temperature Control Unit (TCU) provides two types of error indication. Error codes may flash in the temperature display, and there are blinking LED lights. Temperature Display If an error is present, one or more of the following codes will flash on the temperature display: - E01: The temperature sensor is not detected. Check that the cable is connected to the ports marked "Temp" on the back of the Temperature Control Unit and the DanioVision. For more details, see Error E01 on the DanioVision Temperature Control Unit. - E04: The water temperature is currently more than 0.5 degrees C above the temperature you have set. Depending on the temperature setting, it could take up to 15 minutes for the water to reach the temperature you have set. This error will clear itself once the water has warmed sufficiently. - E05: The water temperature is currently more than 0.5 degrees C below the temperature you have set. As with E04, the error will clear itself once the water has cooled sufficiently. - Ed1: This indicates a system error. Refer to the blinking LED lights to identify the issue. LED Lights The LED lights give the current status. In the case of errors, the error light will blink red quickly between 1 and 6 times, then pause before repeating. Filling/Draining - Orange blinking: System is pumping. In this mode, you can fill or empty the basin of water, or add coolant. - Red continuous: The system has timed out because there has been no flow in the water circulation and/or cooling liquid for more than 10 minutes. If needed, reset the timer by turning the operation switch to Off and then back to Fill/Drain. Operation - Green blinking: Water is being heated or cooled, but has not yet reached the set temperature. - Green continuous: The set temperature has been reached and the system is ready to use. Errors - 1 Red Blink: Insufficient water circulation flow. Make sure there is enough water in the basin and the tubing is clear of air bubbles; add water if necessary. This error will also appear if a hose is blocked or kinked, if the filter is clogged (replacement may be required), or (very rarely) if the pump fails. - 2 Red Blinks: Insufficient flow in the cooling liquid. Check the coolant level and add more if required, and check for signs of leakage in the emergency liquid container. Otherwise, this could be a sign of a flow blockage or pump failure. - 3 Red Blinks: The fan is not spinning, or not spinning at sufficient speed. Check that nothing is obstructing the fan. - 4 Red Blinks: System is overheated. Turn off the system and end the experiment. Coolant can be cooled down by switching the system into Fill/Drain mode. Check for the cause of overheating, for example if the air vents on the TCU are blocked, or if the ambient temperature in the room is very high (higher than 35 deg C). - 5 Red Blinks: An electrical problem has occurred resulting in both heating and cooling being activated simultaneously. Please contact Noldus support. - 6 Red Blinks: There is a problem accessing the SD card mounted within the TCU that is used for logging. Open the TCU and check that the SD card is properly seated, and the cable between the SD card reader and the main board is plugged in at both ends. If that does not resolve the problem, the SD card may be full. Take the SD card out, take it to a computer, and delete the files from it or format it. Then place it back in the TCU. - Red continuous: Temperature is more than 0.5 degrees C above or below the set temperature. The system will heat or cool until the temperature is back in the correct range.   View original HubSpot article · HubSpot article 190573052069 · Knowledge Base 187958790447 · Language en · Updated 1748132284686 --- ## EthoVision will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: Noldus Knowledge Base This error in the installation log file indicates one of the following issues. You do not have the necessary rights to install software Your account does not have the required administrative rights to install software. Check that you do have administrative rights, or log into the computer using an account which does. Depending on how your systems are configured, you might require the assistance of your local IT department for installing software. Windows is currently updating Windows is in the process of installing updates, and the FaceReader installation cannot begin until it is finished. Complete any system updates and try again. Reboot PC after Windows updates complete to ensure no updates are pending. There is a problem with system files Malware or a computer virus has modified system files. Run a scan of the system. View original HubSpot article · HubSpot article 190573052052 · Knowledge Base 187958790447 · Language en · Updated 1748131179071 --- ## EthoVision XT 17 could no longer grab a frame from the video capture device after upgrade from EthoVision 16. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-17-could-no-longer-grab-a-frame-from-the-video-capture-device-after-upgrade-from-ethovision-16 Chapter: Noldus Knowledge Base Upgraded from EthoVision XT 16 to EthoVision XT 17. After the upgrade, the software could no longer grab a frame from the video capture device. They attempted to reinstall the software, but the frame grabber error persisted. The following FAQ offers general troubleshooting steps for frame‑grabber problems. FAQ and step‑by‑step instructions Q1: Why can’t EthoVision XT 17 grab frames after the upgrade? Upgrading EthoVision might expose compatibility issues between the new software version and your camera or frame‑grabber hardware. Drivers that worked with XT 16 may not be supported or may need updates for XT 17. Q2: How do I troubleshoot a frame‑grabber error in EthoVision XT? Follow these steps to identify and resolve frame‑capture issues: - Verify hardware support - Check that your camera or frame‑grabber board is supported by EthoVision XT 17. Consult the hardware compatibility list from the manufacturer and update firmware if necessary. - If you use a third‑party capture card, ensure it is compatible with the newer version of EthoVision. - Update drivers - Visit the camera or frame‑grabber manufacturer’s website to download the latest Windows drivers. - Install drivers as an administrator and reboot your computer to ensure they load correctly. - Check Windows device manager - Open Device Manager and verify that the camera/capture card appears without warning icons. - If the device has a yellow or red icon, uninstall and reinstall its driver. - Reinstall EthoVision - Uninstall EthoVision completely using Add/Remove Programs. - Delete leftover folders in C:\ProgramData\Noldus and C:\Users\\AppData\Local\Noldus to remove old configuration files. - Reboot and reinstall EthoVision XT 17 using administrator privileges. - Configure the camera in EthoVision - Launch EthoVision and create a new experiment. - In the Detection step, select your camera or capture card from the list of available video sources. - Adjust resolution and frame rate settings to match your camera’s capabilities. - Test with another video source - If possible, connect a different camera or use a sample video to see whether EthoVision can grab frames. This helps determine if the problem lies with the camera or with EthoVision itself. - Check system resources - Ensure your PC meets the minimum hardware requirements for EthoVision XT 17 (e.g., sufficient RAM, CPU and GPU capabilities). - Close other programs that might compete for the camera or processing resources. - Contact support - If the issue persists, gather information about your camera model, frame‑grabber board, operating system, and any error messages. - Provide this data to Noldus support for further troubleshooting. They may have firmware or driver updates specific to your hardware. By following these steps, users can systematically identify hardware or software issues that might prevent EthoVision from capturing frames after an upgrade.  View original HubSpot article · HubSpot article 194934578752 · Knowledge Base 187958790447 · Language en · Updated 1755876018748 --- ## EthoVision XT crashes the moment the acquisition is started on a system that also has 3DHistech's CaseViewer installed URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-crashes-the-moment-the-acquisition-is-started-on-a-system-that-also-has-3dhistechs-caseviewer-installed Chapter: Noldus Knowledge Base 3DHistech's CaseViewer contains a codec that is incompatible with EthoVision XT. Uninstalling the 3DHistech software should solve the issue. If it does not please contact your local Noldus support office. View original HubSpot article · HubSpot article 190573052082 · Knowledge Base 187958790447 · Language en · Updated 1748133426673 --- ## EthoVision XT crashes when viewing a GLP log URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-crashes-when-viewing-a-glp-log Chapter: Noldus Knowledge Base This occurs when using Quality Assurance experiments, after you click within the GLP log window or when you click the Close button in the GLP Log window. Do the following: 1. Open the Windows Notepad and enter the following text:     Windows Registry Editor Version 5.00     [HKEY_CURRENT_USER\SOFTWARE\Microsoft\Internet Explorer\Main\FeatureControl\FEATURE_USE_LEGACY_JSCRIPT]     "EthoVision.exe"=dword:00000001 2. Save the file as [file name].reg on the EthoVision XT computer. 3. Double-click the file. Click OK in the message that appears. TIP  Files with extension *.reg are blocked by Windows and mail servers. Do not run REG files stored on network drives. If you need to send a REG file by email, enclose it in a ZIP file. View original HubSpot article · HubSpot article 190556076886 · Knowledge Base 187958790447 · Language en · Updated 1748142168634 --- ## EthoVision XT displayed an “Insufficient License (Id 10073)” error when he attempted to open a previously saved experiment. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-displayed-an-insufficient-license-id-10073-error-when-he-attempted-to-open-a-previously-saved-experiment Chapter: Noldus Knowledge Base EthoVision XT (version unspecified) displayed an “Insufficient License (Id 10073)” error when he attempted to open a previously saved experiment. The license number was correct and asked whether a setting in the experiment needed to be disabled. The FAQ below offers general guidance for resolving insufficient‑license errors in EthoVision. FAQ & Step‑by‑Step Instructions Q: What causes the “Insufficient License (Id 10073)” error? A: This message appears when an experiment uses modules or features that are not included in your license, or when the license key (dongle or network seat) is not detected. It may also arise if the license has been entered incorrectly or the maximum number of licensed users has been exceeded. Q: How do I verify that my license is detected? A: - Check the license key – Ensure the USB license dongle is firmly connected to the computer. If you use a software or network license, make sure your system can reach the license server. - View license details – In EthoVision, go to Help > License Information (or open the Noldus License Manager) to see whether your license is recognised and which modules are enabled. - Test on another PC – Plug the same dongle into another computer running EthoVision; if the license is recognised there, the issue may lie with the original PC’s USB port or drivers. Q: How can I open my experiment if it uses an unlicensed module? A: - Open on a licensed system – If possible, open the experiment on a computer with a full license. Go to the experiment’s Detection Settings or Analysis Options and disable modules not covered by your license (e.g., Social Interaction, Deep Learning, 3‑point tracking, etc.). Save and close the experiment. You should then be able to open it with a more limited license. - Review module usage – Experiments created with specialized modules may require them for subsequent editing. Consult your license documentation or Noldus support to identify which modules are needed. Q: What if the license is correct but the error persists? A: Try these steps: - Update your license drivers – Install the latest HASP (Sentinel) drivers from Noldus to ensure the dongle is detected correctly. - Restart the license server – For network licenses, restart the license service or check whether all seats are in use. Release unused sessions if necessary. - Re‑enter the license key – In the Noldus License Manager, remove the existing license number and re‑enter it carefully. A typographical error can cause an insufficient‑license warning. - Upgrade your license – If your experiment requires modules that your current license does not include, contact Noldus to purchase or activate the necessary modules. Q: Are there any experiment settings that trigger this error? A: Yes. Enabling advanced modules such as Social Interaction, Three‑point tracking, Deep Learning, or Physiology integration without having the corresponding license will cause an insufficient‑license error. Disabling these modules or obtaining the appropriate license will resolve the problem. View original HubSpot article · HubSpot article 194934579998 · Knowledge Base 187958790447 · Language en · Updated 1755877000314 --- ## EthoVision XT does not recognize the dongle when working remotely URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-does-not-recognize-the-dongle-when-working-remotely Chapter: Noldus Knowledge Base Microsoft's Remote Desktop does not support dongles (hardware license keys). To work remotely, we recommend using alternative tools for remote access such as TightVNC, TeamViewer, or Dameware to do so, these do support the use of dongles remotely. Any remote access solution other than Microsoft's Remote Desktop should work.Alternatively, software-based licenses (available starting in EthoVision XT 17) can work in Remote Desktop. Contact support if you would like more information. View original HubSpot article · HubSpot article 190573052284 · Knowledge Base 187958790447 · Language en · Updated 1748145653617 --- ## EthoVision XT error ID 14005 Chart creation failed URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-error-id-14005-chart-creation-failed Chapter: Noldus Knowledge Base This error occurs when you go the Statistics & Charts section of EthoVision XT and the warning message below pops up.  While you will still be able to get your data, this error indicates that the software component for generating the charts under the Groups Statistics & Charts tab is missing/corrupt.       While the warning message suggests reinstalling the EthoVision XT software, the easiest solution is to close the EthoVision XT software, go to your Start menu, type in “Programs and Features” and in the list look to see if a program called “Noldus ChartWrapperControl 2” is present.  If so, please highlight it and click “Uninstall”.  If not present, then move to the next step.       After uninstalling, please close the window above and use MyNoldus to download this file (if the EthoVision XT PC is offline, then simply download the program to a portable storage device and take to the EthoVision XT PC): Chart Wrapper Control 2.0.2 This version is used in EthoVision XT 12, 13, 14, and 15. If you need this component for a different version of EthoVision, please contact support. Double-click or run the downloaded file to install it. Once installed, please reopen EthoVision XT and see if the issue is resolved. View original HubSpot article · HubSpot article 190573052174 · Knowledge Base 187958790447 · Language en · Updated 1748136716628 --- ## EthoVision XT file error Id 10025 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-file-error-id-10025 Chapter: Noldus Knowledge Base This error indicates there was a problem opening the experiment, but could arise for a variety of reasons. If this error occurs, you cannot open the experiment until the underlying cause is resolved. Files missing or out of place A complete EthoVision experiment consists of a folder named for the experiment, containing a variety of files and folders. All of these together constitute the experiment.   Note that file extensions (e.g. “.evxt”) may not be displayed (depending on your Windows settings), and the Restore.btn files will not appear in older versions of EthoVision. This error will occur if the .evxt file (the file that you select to open the experiment) has been moved and is no longer in the location with the rest of the experiment. The .evxt file on its own does not include, for example, any track data. If this is the issue, copy the .evxt file back into the original location. This error may also occur if some of the files in the experiment are missing. This could happen if you moved some of the files out of the experiment folder or deleted them. It could also happen if you ran out of space on the hard drive where the experiment is stored. Check that you are not low on space. Lastly, you will not be able to open the experiment if any of the listed folders are missing. This may also result in an error message indicating “experimental inconsistencies.” You can create these folders as necessary. They may disappear if you use Windows to create a compressed folder of the experiment; Windows will frequently discard empty folders in this case but EthoVision still needs those folders. If the Configuration Files folder is missing, copy it from a working experiment. This folder has a number of subfolders and you'll need all of them. Insufficient access This error may occur if some or all the files of the experiment are not accessible to the current user. This could happen if you are logged in under a different account on the computer, especially when using a network drive. If you can open the experiment from one user account (including from an administrative account) but not from another, the problem is likely one of user access rights. Please consult your local IT department for assistance. Experiment database is damaged This error may occur if the experiment database itself is damaged. This is the .evxt file. Starting in EthoVision XT 8.5, EthoVision automatically creates an extra copy of this file, called “restore.btn”. If after checking the above issues, you still cannot open the experiment, try this procedure. You will likely lose your work from your last session in the experiment, but the remainder will be restored if the .evxt file was the problem.  - In the experiment folder, rename your experiment file (e.g. to “my experiment.evxt.old”) - Rename the file “restore.btn” to the original name of your experiment file (including the .evxt extension, it should have exactly the same name so that it replaces that file) Note that if Windows is hiding extensions (e.g. the “.evxt” part of the experiment file name), it will prevent you from changing the extensions. In Windows 10, click View on the ribbon and check the option to show file extensions. In Windows 7 and 8, click the Alt key to show the menu, then go on the menu to Tools/Folder Options, pick the View tab, and uncheck the option “hide extensions for known file types”.   View original HubSpot article · HubSpot article 190271421082 · Knowledge Base 187958790447 · Language en · Updated 1747539558360 --- ## EthoVision XT file error Id 10034 Experiment cannot be repaired URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-file-error-id-10034-experiment-cannot-be-repaired Chapter: Noldus Knowledge Base This error may state  "Ethovision has detected some experiment inconsistencies." It may result either because necessary files are missing, or the experiment file is damaged. Files missing or out of place The most likely reason for this error is that you do not have the entire experiment's folder with all the necessary components to open that experiment.  If you have just the .evxt file, please note that the .evxt file by itself is not a usable file. You need the entire folder that contained it (which should also be named for the experiment). The .evxt file has an index of all of those files and folders but it does not, for example, include any tracking data. Here's an example of what an entire experiment looks like: As you can see, there is an .evxt file, but also lots of other files/folders. When the .evxt file is in the folder with these other files, it should open properly. Without those files, you will receive an error. Folders lost in a zip file or compressed folder Sometimes when you zip/compress a folder and then restore it in a different location, Windows will omit any empty folders. EthoVision does expect those folders to be present, so if the only thing that is missing are empty folders, it may resolve things if you create them. Note that the External folder has a subfolder "SyncOut", and Configuration Files also has subfolders; it may be easiest to copy these from a working experiment. Preventing files from getting lost Rather than copying the experiment or zipping the experiment folder, use EthoVision to create an experiment backup. In EthoVision, open the original experiment and then go on the menu to File > Make Backup. That will create an .evz file which is an experiment backup. There is an option to omit the media files (i.e. videos) which will make the file much smaller but not interfere with analysis, although if you want to recheck tracking you may want them. Then take that file to the other computer and use File > Restore Backup to create all the required files and folders. Experiment File is Damaged Another possibility is that the experiment file is damaged. However, EthoVision creates a backup of this file. Try the following to use that backup: - In the experiment folder, rename your experiment file (e.g. to “my experiment.evxt.old”) - Rename the file “restore.btn” to the original name of your experiment file. - Note that if Windows is hiding extensions (e.g. the “.evxt” part of the experiment file name), it will prevent you from changing the extensions. In Windows 7 or 8, tap the Alt key to show the menu, then go on the menu to Tools/Folder Options, pick the View tab, and uncheck the option “hide extensions for known file types”. In Windows 10, go on the ribbon to View and check the option to show file name extensions. The extensions will be shown and can be changed. - Reverting to this backup copy of the experiment file may result in losing any changes from your last session, but earlier data should still be present. View original HubSpot article · HubSpot article 190556076852 · Knowledge Base 187958790447 · Language en · Updated 1748134250656 --- ## EthoVision XT is unable to detect the Noldus I/O Box URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-is-unable-to-detect-the-noldus-io-box Chapter: Noldus Knowledge Base EthoVision will report that the USB I/O Box is not connected if the connection is lost or if it is not present when you attempt to start the experiment or test connections. Check the items below to troubleshoot that situation. Connect the I/O Box before starting EthoVision EthoVision will only detect the box if it is connected when EthoVision starts. If you plugged in the I/O Box after starting EthoVision, close EthoVision and then re-open it. Check connections and power supply Other than the connected Noldus or 3rd party hardware (via TTL or SDI ports), there are two main cables. These connections are the same whether you are using the USB IO Box or Mini USB IO Box. - The USB cable that connects the IO box to the computer. If this cable is connected, the USB light on the IO box should be on.  - You should also have a power cable connected, and the power LED light should be on. Without power, the box may sometimes receive enough power over USB to communicate with the computer, but not enough to control any devices.                Is the I/O box detected by the computer? If the box is plugged in (both cables) but it is not detected by EthoVision, check that it is detected by the computer. Go to the start menu and click the gear icon for Settings, then pick Devices. You should see the "Bluetooth & other devices" page listing devices connected to the computer. Under "Other Devices", look for the device “I/OWarrior56”. If this device is not listed, either the driver for the box is not installed or the box is malfunctioning. Is the correct I/O box selected for in your Experiment Settings? You may receive an error stating that the I/O box is not detected if you selected the wrong interface when the experiment was created (e.g., the Mini-USB I/O Box was selected instead of the standard USB I/O box). In this case, EthoVision will look for the wrong box and not find it. The USB-IO Box is labeled USB-IO Box; it has 13 RJ45 ports on the side labeled SDI Control and 12 RJ45 ports on the side labeled TTL Control The Mini USB-IO Box is labeled "mini USB-IO box". It has four RJ45 ports labled TTL Control and one RJ45 port labeled SDI Control. If you've assigned devices to the wrong interface, select that same interface and remove the device assignments, then add them for the correct interface (or create a new experiment). View original HubSpot article · HubSpot article 190556076832 · Knowledge Base 187958790447 · Language en · Updated 1748130617738 --- ## EthoVision XT Resizer error (ID 8359) URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-resizer-error-id-8359 Chapter: Noldus Knowledge Base If, when you try to grab a background image in the Arena Settings, you receive a warning message "Resizer error (Id 8359)", the Resizer component is missing or has been corrupted.     Solution: Reinstall Noldus ResizerFilter It is likely that the issue involves the Noldus ResizerFilter is missing/corrupt, so please download the version from MyNoldus that corresponds to your EthoVision XT version. If unsure of your EthoVision XT version, you can check by going to Help > About EthoVision XT on the menu. Links for recent versions are included in the table below.     EthoVision XT version Noldus Resizer Filter version 16.0, 17.0 Noldus Resizer Filter 13.1.2 14.0, 15.0 Noldus Resizer Filter 13.0.2 12.0, 13.0 Noldus Resizer Filter 12.1.6 View original HubSpot article · HubSpot article 190573052175 · Knowledge Base 187958790447 · Language en · Updated 1748136804619 --- ## EthoVision XT Settings are Locked, Unable to Modify URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-settings-are-locked-unable-to-modify Chapter: Noldus Knowledge Base Once data has been acquired in EthoVision using a specific profile (Arena Settings, Trial Control Settings, or Detection Settings), they become locked from changes (red arrows). This ensures that EthoVision always preserves the settings you used to acquire your data, so it can be checked or replicated.  If you need to make changes, right-click your existing settings profile, and select the option to “duplicate.” The new profile will allow modifications (as it has not be used for data acquisition - green arrow). If your experiment includes multiple profiles (e.g., multiple arena settings), the one highlighted in blue is the one that will be used for the next trial. You can change which one should be used by specifying it either in the Trial List or the Acquisition.   If you are testing certain settings before the actual acquisition process, you can also clear or delete the acquired trials (blue arrow). This will remove the “lock” and allow settings modifications (green arrows). Note that the Experiment Settings will also become locked once trials have been acquired. These settings cannot be duplicated, so if you need to make changes after acquiring data, you will need to create a new experiment. You can create a new copy of an existing experiment either by saving the experiment under a new name (File > Save Experiment As) and remove the trials from the new copy. Alternatively, you can create a New Template Experiment, choose Custom Template, and select your existing experiment as the source; this will copy all of the settings but none of the data, so everything will be unlocked. Note that the Custom Template option can take a while, especially if the original experiment included many trials. View original HubSpot article · HubSpot article 190573052163 · Knowledge Base 187958790447 · Language en · Updated 1748134074660 --- ## EthoVision XT trial duration does not correspond with system time (Id 12015) URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-trial-duration-does-not-correspond-with-system-time-id-12015 Chapter: Noldus Knowledge Base This error message, "Trial duration does not correspond with system time (Id 12015)", indicates that EthoVision sees that the video has been streaming in at a slower rate than expected. The most common cause is that the camera is not delivering frames at the expected rate. This can also result in the trial stopping prematurely if too many consecutive video frames are missing. Otherwise, it may indicate the computer is inadequate or has impaired performance. Frames being skipped To check whether frames are being skipped, check any of the following: - In the Detection Settings, check the Missed Samples or Interpolated Samples count near the bottom of the screen. Both of these should be very close to 0% (and always < 1%). This value will display in red if it is very high. (Note that Interpolated Samples will be displayed only if Dropped Frames Correction is enabled in the Detection Settings, but Missed Samples is always present.) The count of Subject Not Found is not relevant to this issue (although if the subject is not found when your animal is in the arena, it may indicate the detection settings need improvement). - In the Acquisition, the Missed Samples and Interpolated Samples will be displayed the same way. - In the Trial List, check the Missed Samples column. If it is not displayed, click Show/Hide in the upper right corner, pick Variables, and then check the checkbox for Missed Samples (and Interpolated Samples if available). The Trial List permits you to check these values for trials that have already been acquired. If frames are being skipped, the most likely cause is the camera.  Camera skipping frames If the camera is a USB webcam, make sure the camera is plugged into a USB 3 port (which will either be blue or marked SS for SuperSpeed) if possible. Use a port on the computer itself rather than a hub. It may be necessary to reduce the frame rate or resolution (in the experiment settings). If the camera is not plugged into a USB 3 port, avoid using any other high-bandwidth USB devices at the same time; for example, don’t use an external hard drive. In general, USB cameras are not recommended. If the camera is an IP camera (e.g., Axis cameras), for best results the camera should connect directly to the computer, rather than connecting many cameras to a network switch or your local network. If the camera is a Basler GigE camera, it may be necessary to adjust the Exposure setting. Exposure is the amount of time spent acquiring one video frame, so if it is too high, there is not enough time to acquire the next frame, and it will be skipped. For details about changing this setting, see changing the exposure for a Basler camera. A defective ethernet cable can also result in dropped frames for IP and GigE cameras. Replacing the cable is a quick and easy test. For any other type of camera, ensure the camera is set to a fixed frame rate, not a variable frame rate. If exposure can be adjusted, ensure it is not too high. Basler camera using wrong drivers In order to maximize the performance of Basler cameras, the Basler software installs a Basler driver for the network card to replace the Intel driver normally used. But in some cases Windows will switch back and this can cause subpar performance. For more details about correcting this issue, please click here. Computer performance We recommend the use of a workstation-class computer, such as the Dell Precision. The computer should include a dedicated video adapter (GPU) with its own memory, rather than relying on onboard Intel Graphics. Check the Help for your version of EthoVision, or contact Noldus support, if you need assistance. If the experiment is being saved to an external or network drive, check whether the problem is resolved by moving the experiment to the local drive. (Copy the entire experiment folder named for the project to the local drive, not just the .evxt file, or save a copy to the local drive by going on the menu to File/Save Experiment As). Performance may also be improved by adjusting the computer's power settings. For more details, see Windows 10 power-saving settings. Hardware failure This problem can also be caused by a faulty video display card or a failing hard drive. Dell computers provided by Noldus include built-in diagnostics to test the CPU, memory, motherboard, disks, fans, and other components. To access these diagnostics, shut down the computer. Restart the computer and press the F12 key as soon as the Dell logo appears (before Windows opens). You should see a selective start menu with a diagnostics option. Once in the diagnostics, please carefully note any errors. View original HubSpot article · HubSpot article 190573052173 · Knowledge Base 187958790447 · Language en · Updated 1748136658649 --- ## EthoVision XT v18 download from the MyNoldus link, after extracting the ZIP archive, received an error indicating that the folder was empty. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-v18-download-from-the-mynoldus-link-after-extracting-the-zip-archive-received-an-error-indicating-that-the-folder-was-empty Chapter: Noldus Knowledge Base Downloaded EthoVision XT v18 from the MyNoldus link but, after extracting the ZIP archive, received an error indicating that the folder was empty. He tried multiple times and requested a working installation package. Support explained that the error relates to missing Intel Performance Primitives (IPP) runtime libraries (e.g., ippcore‑8.2.dll, ipps‑8.2.dll, ippvx‑8.2.dll) and recommended performing a clean reinstall of EthoVision. FAQ & Step‑by‑Step Instructions Q: Why does the installer say the extracted folder is empty or missing DLLs? A: This can happen if the installation package is run directly from inside a ZIP file or if previous installations left behind incomplete components. EthoVision relies on Intel’s Performance Primitives libraries for video processing; if those DLLs are missing, the installer cannot proceed. Q: How do I cleanly reinstall EthoVision XT v18? A: - Uninstall existing software – Go to Add/Remove Programs in Windows and uninstall anything labeled EthoVision or Noldus. - Remove leftover folders – Delete any remaining Noldus directories from the following locations: C:\ProgramData\Noldus and C:\Users\\AppData\Local\Noldus. - Restart the computer – Reboot to ensure all files are released. - Extract the ZIP file – Download the ZIP archive again if necessary. Use Windows Explorer or a reliable extraction tool to unzip it to a local folder. - Run the installer as administrator – Inside the extracted folder, right‑click exe and select Run as administrator. This will trigger the full set of prerequisite installations, including the IPP components required by EthoVision. - Complete the installation – Follow the on‑screen instructions to install EthoVision XT v18. After installation, launch EthoVision normally. Q: What are Intel IPP libraries and why are they needed? A: Intel Performance Primitives (IPP) are runtime libraries used for image and video processing. EthoVision employs IPP for video handling; if these components fail to register correctly, EthoVision will not start. Running the installer as administrator ensures they are installed. Q: What if the issue persists after a clean reinstall? A: If you still encounter extraction errors or missing DLL messages: - Verify the download – The ZIP file may be corrupted. Download it again using a stable internet connection. - Try a different extraction tool – Use 7‑Zip or another unzip utility to extract the archive. - Request a physical installer – Contact Noldus support to obtain a direct installer package or a new download link. - Check antivirus software – Some security programs may block DLL registration. Temporarily disable them during installation and re‑enable them after completion. View original HubSpot article · HubSpot article 194934580003 · Knowledge Base 187958790447 · Language en · Updated 1755874839041 --- ## EthoVision XT: Animal is not tracked in Hidden Zone URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ethovision-xt-animal-is-not-tracked-in-hidden-zone Chapter: Noldus Knowledge Base Make sure that the Entry Zone is properly linked to the Hidden Zone and not too small Briefly, the purpose of the Entry Zone is to provide a means for the software to know that if the animal is “seen” in the Entry Zone and then disappears, they must be in the Hidden Zone. For each Hidden Zone you create, you are required to create and link at least one Entry Zone. If the animal being tracked accurately in the Arena and therefore tracked accurately in the Entry Zone, but then goes as “missing” once it enters the Hidden Zone, then there must be a problem with the Entry Zone not being properly “linked” to the Hidden Zone and/or the Entry Zone is too small.   First thing to check is that the Entry Zone is properly “linked” to its respective Hidden Zone.  To do so, go to your Arena Settings and right-click on the Entry Zone and select “Link Hidden Zones”.  In the Light-Dark box example below, if one right-clicks the Entry Zone “Door” and selects “Link Hidden Zones”, the following box appears:   Thus, it is important to make sure that it is linked to my Hidden Zone called “Dark Side” by making sure the box is checked.   Please note there’s also an option to “Use the entry zone also as a leaving zone”. By default, the animal is considered to have left the Hidden Zone when it is next detected, that is, when its body point(s) are “not missing”. However, every time an animal pokes its head out, this may be recorded as an exit.  Subsequently, retracting back into the Hidden Zone - without ever really leaving it- would count as entering again. This results in an overestimation of how often the animal enters/exits the Hidden Zone. Therefore, EthoVision XT versions 5.1 and up have the possibility to also use the Entry Zone as leaving zone. The animal is then considered to have left the Hidden Zone when it was first considered to be in a Hidden Zone, and subsequently detected outside of the entry zone. In other words, the exit is counted only when the body point crosses the border between the Entry Zone and the rest of the arena.  It is recommended to use this function if you want to prevent an overestimation of entrances into, and exits from, the Hidden Zone. If the Entry Zone is properly linked to the Hidden Zone, then the most likely other cause of the issue is that the Entry Zone is too small. Keeping in mind that EthoVision must “see” the animal in the Entry Zone before they disappear (i.e., the enter the Hidden Zone), if the Entry Zone is too small and the animal enters the Entry Zone and leaves it into the Hidden Zone before a sample of data is collected by EthoVision, then they will be determined as “missing” and not in the Hidden Zone. This is more likely to happen if your subject is fast (e.g., a bird flying), or if the Entry Zone is too narrow and the animal can enter the Hidden Zone without its center point ever entering the Entry Zone.  Therefore, please make sure that the Entry Zone is big enough and slightly overlaps the Hidden Zone so that from no matter the angle that the animal enters the Entry Zone, it will be “seen” by EthoVision and determined that it is near the Hidden Zone.  If so, once they disappear (i.e., they enter the Hidden Zone), the software will accurately mark them as being in the Hidden Zone and not “missing”. It's normally ok to make the Entry Zone fairly large (although if "Use this entry zone also as leaving zone" is checked, bear in mind the animal won't be tracked until it leaves the Entry Zone). Hidden Zones are for situations where the animal is out of view and impossible to track, so the animal is considered to have entered the Hidden Zone if it was in the Entry Zone and then disappeared. If the animal is detected while it is in the Hidden Zone, it's no longer hidden, and therefore it may be tracked as having left the Hidden Zone. If it subsequently disappears without being in the Entry Zone, it will not be counted as going back into the Hidden Zone. You can address this by making the Entry Zone large enough to cover the Hidden Zone. View original HubSpot article · HubSpot article 190573052025 · Knowledge Base 187958790447 · Language en · Updated 1748128610049 --- ## Export of raw multi-sensor data (e.g. accelerometer, gyroscope, magnetometer, barometer) with TrackLab URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/export-of-raw-multi-sensor-data-eg-accelerometer-gyroscope-magnetometer-barometer-with-tracklab Chapter: Noldus Knowledge Base Export from TrackLab: TrackLab currently only imports location data from the Sewio system. It does not yet import (and thus not export) data from the other tag sensors such as the accelerometer, the gyroscope, the magnetometer or the barometer. Import of, and Machine Learning with, the multi-sensor data is on the product roadmap. Ask the Product Manager for more information. Export directly from the Sewio system: It is possible for the customer to export raw data from the Sewio system: - Note that the sensors must be enabled for each tag, otherwise there is no data recorded even by Sewio. - Ask R&D for the export tool and user manual and share this with the customer. - Note: The solution we aim for on the mid term is to import and machine-learn with the raw data inside TrackLab. Therefore, the intermediate solution for export of other sensor data from Sewio is somewhat technical. The export tool consists of a Python script that docks onto Sewio's Sage application. Further info: The above mentioned raw data export tool is restricted to export of historical data, for use by any TrackLab user. Customers that are tech-savvy and capable of programming can also use other API's to access the raw Sewio data (see overview): - REST API: for export or handling of static information (meta data). - WebSockets API: for export of real-time data (low sample rates).  - UDP API: for export of real-time data (high sample rates)  - SQL Database: for custom statistics creation View original HubSpot article · HubSpot article 190573052188 · Knowledge Base 187958790447 · Language en · Updated 1748137562006 --- ## FaceReader will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/facereader-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: Noldus Knowledge Base This error in the installation log file indicates one of the following issues. You do not have the necessary rights to install software Your account does not have the required administrative rights to install software. Check that you do have administrative rights, or log into the computer using an account which does. Depending on how your systems are configured, you might require the assistance of your local IT department for installing software. Windows is currently updating Windows is in the process of installing updates, and the FaceReader installation cannot begin until it is finished. Complete any system updates and try again. Reboot PC after Windows updates complete to ensure no updates are pending. There is a problem with system files Malware or a computer virus has modified system files. Run a scan of the system. View original HubSpot article · HubSpot article 190556076854 · Knowledge Base 187958790447 · Language en · Updated 1748134404673 --- ## For social proximity analysis in TrackLab, is there a way to relate to which other subject the subject was in proximity? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/for-social-proximity-analysis-in-tracklab-is-there-a-way-to-relate-to-which-other-subject-the-subject-was-in-proximity Chapter: Noldus Knowledge Base Today: Currently, TrackLab only provides a general social behavior indicator, i.e. how much time did a subject spend time in proximity to ANY other subject. There is a workaround available at R&D to get subject identity information but that requires manual post-processing of results (e.g. in Excel) and is feasible only for small groups of subjects. Medium term: On the product roadmap, there is the so-called 'Social Network' analysis which will give a matrix with time and %time spend in proximity, for all subject pairs. A color coding will highlight the 'dominant' pairs in the group. View original HubSpot article · HubSpot article 190556076864 · Knowledge Base 187958790447 · Language en · Updated 1748137716627 --- ## How accurate is location measurement for TrackLab with UWB (Sewio) tracking? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-accurate-is-location-measurement-for-tracklab-with-uwb-sewio-tracking Chapter: Noldus Knowledge Base The accuracy is at least 15cm (6 inch) in all directions, from the measured location. This means that the real location of the tag is within a 30 cm/12 inch diameter circle around the measured location. Of course, our Operations team will always try to maximize accuracy. Sometimes we can achieve an accuracy as high as 5 cm / 2 inch in the center of the tracking area. If this is possible depends on the characteristics of the tracking site: - How good is the 'line of sight' between anchors? - Are there any blocking objects? - Are there any flat-surfaced solid metal objects that may cause reflections? - How good is the line of sight between tags and anchors? In the pre-Sales process, we make sure that the site meets the requirements needed to be able to meet the accuracy claim. This includes the min and max distance between anchors. Any issue that may compromise tracking accuracy is evaluated in the pre-Sales process.  Notes: - There are 2 dimensions of the 'quality of location measurement'; there is accuracy and precision. The picture below illustrates how precision determines the variation (standard deviation) in location measurements for a static tag. The accuracy tells you how far the center of gravity/mean location is away from the real-world point. Both qualities determine how big the accuracy circle is. - By nature of the triangulation-based localization method, the precision will differ across the tracking area. Learn more about the characteristics of UWB tracking precision in this article. In general, the accuracy will be best in the center of the tracking area, and gradually degrade towards the corners. Directly below the anchors, the 15cm accuracy requirement may not be met, due to the intrinsic characteristics of UWB tracking. However, in most cases, the subjects (animal or human) tend to not move all the way into a corner, especially not with the head (where the tag is normally located). - At the moment, our accuracy claim is restricted to the static accuracy, i.e. static location measurement. In case a customer asks, we do not yet have a claim for dynamic and analysis accuracy. Of course this is derived from the static accuracy but you could measure a tag moving across a trajectory with a known distance, and then compare with the measured distance. R&D plans to come up with a claim that for example says the dynamic accuracy/distance moved is +/- x%. - The dynamic accuracy also depends on settings that affect the track smoothing; tag sample rate, tag sleep mode settings, track smoothing and Minimal Distance Moved (MDM) filter in TrackLab. These are adjusted based on the subject type and movement characteristics. - Some customers have also asked how we calibrate the system, and if there is a way for them to periodically re-calibrate the system (as per research procedural requirements). R&D is planning a solution for this. Ask the TrackLab PM for more details. View original HubSpot article · HubSpot article 190573052184 · Knowledge Base 187958790447 · Language en · Updated 1748137305677 --- ## How can I play back and hear ultrasound outside UltraVox XT ? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-can-i-play-back-and-hear-ultrasound-outside-ultravox-xt Chapter: Noldus Knowledge Base Within UltraVox XT you can play back recordings and hear ultrasound. To do so, use the Pitch reduction function.  However, there may be cases when you wish to play back a recording in different software. We recommend to do so in Audacity (downloadable at www.audacityteam.org). 1. Locate your recording (with extension UVD) in the experiment folder. 2. Select the file, press Ctrl+C and then Ctrl+V. A copy of the file appears. Rename that copy to [file name].WAV. 3. Open the WAV file in Audacity. 4. Select Edit > Preferences, then under Tracks choose Spectrograms and under Scale set the frequency range (e.g. 0 to 125000).  5. Choose Spectrogram from the menu that opens when you click the arrow near the file name. 6. Select the whole recording (Ctrl+A). 7. Choose Effect > Pitch and Tempo > Change Pitch.. 8. Under Frequency, enter the change in frequency you require. For example, if the calls are around 60 kHz and you want to hear them, type From 60000 to 10000 Hz. Remember that the upper limit of audible sound is at about 20000 Hz. 9. Click Apply. 10. Click the Play button or press the space bar to play the sound file. You should now hear the calls. If you don’t, choose Edit > Undo Change Pitch and reduce the frequency further. 11. To save the audible sound file, choose File > Export Audio.   View original HubSpot article · HubSpot article 190573052249 · Knowledge Base 187958790447 · Language en · Updated 1748142236620 --- ## How can i remove a tracking site that i do not use anymore? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-can-i-remove-a-tracking-site-that-i-do-not-use-anymore Chapter: Noldus Knowledge Base - Prerequisites: (a) you can only remove sites that contain no data and (b) you need to be logged in as administrator. - Open the menu button in TrackLab Viewer and choose the option "Site Management" (see image below). - In the dialog, select the site you want to discard and click the "remove" button. - If the remove button is disabled, the site is not active anymore. To reactivate the site, proceed with the following steps: - Locate the file "connectionsettings.xml" in this directory: "C:\ProgramData\Noldus\TrackLab Recorder\2\". - Open it by right-clicking it with the mouse and choosing "Open with... Notepad". - Find the line "Sitename" and replace the name (bold in the example) by the name of your site, as listed in the Site Management dialog. - Find the line "Key" and replace the key (bold in the example) by the key of your site, as listed in the Site Management dialog. - Save and close the connection settings file, restart TrackLab Viewer and open the Site Management dialog to remove the site. Remember to repeat the steps to reconnect another site that you want to record data with. View original HubSpot article · HubSpot article 190573052202 · Knowledge Base 187958790447 · Language en · Updated 1748138526655 --- ## How can I remove recordings and data from the TrackLab database? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-can-i-remove-recordings-and-data-from-the-tracklab-database Chapter: Noldus Knowledge Base You may wish to remove recordings from TrackLab if the system is getting slow, if the recordings were only created for test purposes and are no longer needed, or if there is a problem analyzing them. In some cases if TrackLab was closed improperly, you may have recordings that never analyzed properly, and these can interfere with deleting recordings. In all cases when removing data, it's advisable to start by creating a backup of the data. If you have the above issue, you might not be able to do so with the project open. Follow these steps to make a backup even if you have that issue: - Open TrackLab but don't select your project. (In fact, you don't even need to log in, but if you are set to log in automatically that's OK.) - Click the menu button in the upper right (with three parallel horizontal lines), then pick Data Management.  - TrackLab will tell you that you will be logged out, which is fine. You may need the administrative password for the PC. It will do some preparation, stop the services and process, and after a delay should tell you "Datamanagement prepared successfully."  - Click the Create Backup button.  - You should get a message that this was successful (after a delay). Click Close to close that window (this may also take a little time to complete). To remove recordings, without opening your project: - Go back to that menu button and pick Data Management again.  - Click Remove Data.  - You'll see a list of available sessions. Pick the session or sessions you want to remove. (You can select multiple sessions by either clicking the first and then holding down the shift key when clicking the last, or hold the ctrl key while clicking each session to be selected.)  - Click Remove Selected Sessions.  - Close the window. You're now logged out of TrackLab. Log back in and open your project. It may still need to recover analysis data if there were previously any issues, but if you've removed any problem sessions it should complete the process. If you removed sessions in order to resolve an analysis issue, it's a good idea to make another backup at this point.   View original HubSpot article · HubSpot article 190573052270 · Knowledge Base 187958790447 · Language en · Updated 1748143875633 --- ## How can I transport an EthoVision XT experiment from one PC to another? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-can-i-transport-an-ethovision-xt-experiment-from-one-pc-to-another Chapter: Noldus Knowledge Base To transport an EthoVision XT experiment from one PC to another please always use a backup. Load your experiment in EthoVision XT, go to File/Make backup and store the *.evz file to the desired storage medium (USB stick, external hard disk, network location, Internet file exchange service etc.). Including videos is optional but will result in an extremely large file (uncheck if too large). On the new PC start EthoVision XT, go to File/Restore backup and restore to the local drive. View original HubSpot article · HubSpot article 190573052289 · Knowledge Base 187958790447 · Language en · Updated 1748145977526 --- ## How can I use video files in CatWalk XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-can-i-use-video-files-in-catwalk-xt Chapter: Noldus Knowledge Base CatWalk is designed for use with live video from the walkway, but it is possible to use it with video files. Normally this is only for demonstration purposes. The video file must be specified on the command line when CatWalk is opened. This can be achieved most easily by editing a shortcut or by creating a .bat file. Video Files You will need suitable videos. We have three available for download here: https://noldus.sharefile.eu/d-s7e04648930d4f2aa Unzip the downloaded file and put the videos in this folder: C:\Users\Public\Documents\Noldus\CatWalk XT\DemoVideos   Option 1: Create a shortcut Open the folder that contains the CatWalk program.  - In CatWalk XT 10.7, this is normally C:\Program Files\Noldus\CatWalk XT 10 - In previous versions, it is C:\Program Files (x86)\Noldus\CatWalk XT 10 Find CatWalk.exe in the folder. (If Windows is hiding file extensions, there will be three files named CatWalk. It's the one with the Type shown as "Application", with the red CatWalk icon associated.) Right-click this file and pick Send To > Desktop (Create Shortcut).  (In Windows 11, you will first need to pick Show More.) The shortcut will be created on your desktop. Find the new shortcut, rename it as desired, then right-click it and pick Properties. Change the Target to: "C:\Program Files\Noldus\CatWalk XT 10\CatWalk.exe" /videofile "C:\Users\Public\Documents\Noldus\CatWalk XT\DemoVideos\Sample_Video_Rat.avi" /framerate 100 Change the name of the video file shown (e.g., Sample_Video_Rat.avi in this example) to the name of your video.   Also, change Start In to: "C:\Program Files\Noldus\CatWalk XT 10" Then click OK.   Note: if you are using CatWalk XT 10.6 or earlier, "C:\Program Files\" must be changed to "C:\Program Files (x86)\" in both of the above settings. The text shown is correct for CatWalk XT 10.7.   Option 2: Create a .bat file A .bat file is a small text file that contains command line statements. When it is executed (e.g., by double-clicking the .bat file), those statements are executed as if you had typed them at the command line. The easiest way to create a .bat file is to open the folder you want it in (or use the desktop), right-click any open space, and pick New > Text Document. Give it a suitable name, then double-click it to edit (normally in Notepad). Paste the following into the file: "C:\Program Files\Noldus\CatWalk XT 10\CatWalk.exe" /videofile "C:\Users\Public\Documents\Noldus\CatWalk XT\DemoVideos\Sample_Video_Rat.avi" /framerate 100 Replace the name of the video file (Sample_Video_Rat.avi in this example) with the name of the video you want to use. Note: if you are using CatWalk XT 10.6 or earlier, "C:\Program Files\" must be changed to "C:\Program Files (x86)\" in both of the above settings. Save the file and close Notepad. Now you need to change the file type from .txt to .bat. If Windows is hiding those file extensions, you must show them first. In Windows 10, in the file explorer go on the menu to View, then check the checkbox for File Name Extensions. In Windows 11, go on the menu to View > Show > File Name Extensions. Then rename the file so it has a .bat extension instead of .txt. If you need to edit an existing .bat file, you can easily do so. Right-click the file and pick Edit. You can also copy and paste the file so you have different copies linked to different video files.   Using the video When you double-click the shortcut or double-click the .bat file, CatWalk XT will open normally. It will indicate no camera is connected. However when you go to the Detection Settings or Acquisition, it will show the specified video in place of the camera image. This video will repeat endlessly. There is no way to select a different video within the program, to do that you must close CatWalk and open it from a different shortcut or .bat file. Before acquiring a run, you will need to define the walkway (which normally will be the entire video) and calibrate. View original HubSpot article · HubSpot article 190573052089 · Knowledge Base 187958790447 · Language en · Updated 1748133928628 --- ## How do I upgrade my license? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-do-i-upgrade-my-license Chapter: Noldus Knowledge Base Noldus offers two kinds of licenses:  - Hardware license keys (dongles) are USB devices which must be plugged in a USB port on the computer when in use. - Software activation codes are codes that are typed in within the software to activate the license. See the applicable instructions for the type of license you have. Please note that upgrading the license will not upgrade the software. For a new version of the software, you will need to download and install the new software as well. How to upgrade your Hardware Key License (Dongle) To start using the software with a hardware key (USB dongle), please insert the dongle into any free USB slot in your computer. If the software and drivers are successfully installed, then a red LED will light up inside the dongle. You can now start the application. When you purchase a new version of our software or an additional module for your license, or if you received a free upgrade because you have an active NoldusCare contract, the dongle needs to be upgraded to access the new version or functionality. Upgrading a USB dongle is done by entering a code in the software application while your dongle is inserted into the system. The Upgrade code can be found either here on MyNoldus under the licenses tab or by contacting support at Support@noldus.com. Upgrade to a newer version of the software If you are upgrading to a newer software version, first install the new version of software, then enter the upgrade code in that version and not in the old application. Removal of the old application first is preferred in most cases. You will be prompted to enter the code when you open the new software. Note that an upgrade code is required for full version changes, for example from version 17 to 18. Minor updates, such as from 17.0 to 17.1, do not require upgrade codes. You can just keep using your dongle after installing the updated version. Adding a new module to your license If the version is not changed and only a new module is added to your license, then you can proceed in the current installed version of your software. You do not need to install new software. Enter the upgrade code by following these steps: - Insert dongle into a USB port. - Launch the application. - Go on the menu to Help > Upgrade or Help > License > Upgrade. - Enter the code in the indicated boxes below. (Depending on the modules, you may only have a code for Key 1. When this is the case, Key 2 can be left blank.) Note that you do not need to edit the Name or License number. If the code is accepted, the window will close. You can check the current status of the license by going on the menu to Help > About and then click License Info (or the information will already be displayed, depending on which software you are using). How to upgrade your Software Based License A software-based license can be activated as a Fixed or Floating license. - A Fixed license is activated on one computer. It can be used without an internet connection. - A Floating license may be activated on multiple computers, and can be used on any one of them at a time. (Or more than one, if you have multiple licenses sharing an activation code.) Floating licenses always require an internet connection during use. Adding a new module to a Software-Based License When you purchase an extra module with new functionality on your existing license, the following actions are needed to enable the new module on the license. - Floating license (with internet connection): no action needed, the license will upgrade after first startup of the application. - Fixed license (with internet connection): no action needed, the license will upgrade after first startup of the application. - Fixed license (without internet connection): first deactivate the license, by going on the menu to Help > Deactivate License. Pick the offline activation procedure, which will present a QR code to read with your smartphone. Then re-activate the license, again using the offline activation option. Upgrading a Software-Based License to a newer version If you have an active NoldusCare service contract, newer versions of the software will be automatically unlocked for your license. - Floating license (with internet connection): no action needed, just install the latest software version and the license will upgrade after first startup of the application.  - Fixed license (with internet connection): no action needed, just install the latest software version and the license will upgrade after first startup of the application.  - Fixed license (without internet connection): first deactivate the license, by going on the menu to Help > Deactivate License. Pick the offline activation procedure, which will present a QR code to read with your smartphone. Then re-activate the license, again using the offline activation option. View original HubSpot article · HubSpot article 190573052250 · Knowledge Base 187958790447 · Language en · Updated 1748142441668 --- ## How do IR cameras work? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-do-ir-cameras-work Chapter: Noldus Knowledge Base Most cameras have some sensitivity to IR as well as to visible light. Color cameras used colored filters which block IR, and monochrome (black and white) cameras may have IR blocking filters, but these filters may be removable (e.g., a color camera with a monochrome "night mode" will simply move the colored filter out of the way so its sensor will detect everything). A camera designed for IR may have better sensitivity to IR, but the basic functionality is the same.A common misconception is that IR cameras detect heat. Hot objects do emit IR, but at temperatures you will encounter in a behavior lab, that is mid to far infrared (wavelengths of 3000 nm and up) which is not detectable by your camera (even IR cameras typically have sensitivity only up to around 1000 nm). Typical IR illumination is 850 or 940 nm (e.g., 940 nm in the Phenotyper), in the “near IR” range (defined as 700 nm to 3000 nm). To be visible in the near IR range simply based on heat, an object would have to be over 1800 degrees C. It’s possible to detect the heat from living things, but for that you need a thermographic camera and not merely a camera that is sensitive to near IR. Thermographic cameras add expense and typically have low resolution, resulting in a less detailed image, that shows temperature as false color; that's not something normally used for behavior tracking.So, for purposes of behavior research, IR is essentially just a color of light that has the special trait that it is invisible to us and to most animals (including rodents). We add IR illuminators that work just like visible lights, but in this invisible color. Those illuminators may be separate devices, mounted in an observation cubicle, or built into the top of our Phenotyper chambers. In some cases we will add an IR-pass filter which prevents the camera from seeing visible light; only IR is able to pass through the filter and be detected. This permits the camera to give a consistent image even if the ambient lighting is changing (e.g., circadian lighting), but requires that a source of IR illumination is present. You can see that this filter is present because the front of the camera lens will be completely black, as no visible light passes through it.When using IR illumination, all the same considerations as using normal visible light apply: light is shining onto the scene, it is reflected or absorbed by objects in the scene, and whatever is reflected back to the camera becomes part of the image. If there is a shiny surface, IR can produce bright glare, and the relative position of the camera and illuminator may need to be adjusted to get the best possible image. For the most part, dark objects will appear dark and light objects will appear light in the camera image, but there are some exceptions as some objects will absorb more or less light in the IR range than they do in the visible range (just like some objects will absorb more or less red light, and accordingly may appear blue or red).If you are using IR illumination to observe animals on bedding, corncob bedding may appear a bit brighter in IR than it does to the eye, and we find that paper-based bedding often appears darker (although not all brands will appear dark). For light-colored animals it can be advantageous to use very dark bedding. One option is Purina’s Yesterday’s News kitty litter (unscented!)  which appears very dark. View original HubSpot article · HubSpot article 190573052045 · Knowledge Base 187958790447 · Language en · Updated 1748130550920 --- ## How do power outages affect TrackLab operation? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-do-power-outages-affect-tracklab-operation Chapter: Noldus Knowledge Base Power control in TrackLab TrackLab needs a stable power connection to ensure consistent operation. To avoid situations where the power connection can be interrupted, for example, due to an unexpected power cut, we suggest using a UPS (Uninterruptible Power Supply).  Controlled shutdown A shutdown action is 'controlled' when the shutdown is initiated by Windows or by the user. A controlled shutdown is announced by the system before it is executed. The consequences of a controlled shutdown are: - There are no severe consequences if TrackLab is not recording data when the power of the system is switched off. TrackLab will recalculate the analysis data to ensure consistency. In this case, a warning banner appears as seen in the below right image. It means that analysis calculations are ongoing and that not all the analysis data is available. The analysis data will be fully available again when all the calculations have finished. In this case, the below-left banner will show in TrackLab.         - If TrackLab was recording, the recording is interrupted for the time interval that the power was down. The data that is received from the tracking system and not stored yet will be permanently lost. The recording will automatically resume once the PC is powered up again. Simoustainlously will TrackLab start to recalculate the analysis data. It will not be possible to view the analysis data while it is recalculating. While TrackLab is recalculating the analysis date TrackLab will show the upper right image and when finished the upper left. NOTE: It may take a considerable amount of time before the finished banner occurs, especially when TrackLab was recording for a long time before the power failure occurred. Uncontrolled shutdown The consequences of an uncontrolled shutdown include the steps of a controlled shutdown. In addition, it may result in these effects: - Corruption of data storage. It may be that part of the data is not available for analysis results.  - The system does not startup correctly. TrackLab logs each situation as an error in the System Diagnostics window that is available from the top-right menu after login.   The use of a UPS (Uninterruptible Power Supply) prevents uncontrolled shutdowns and their consequences. Hence, using a UPS is highly recommended as often TrackLab cannot fully recover from an uncontrolled shutdown without the involvement of Noldus support.   UPS (Uninterruptible Power Supply) To prevent data loss or corruption in case of power failures, we recommend installing two UPS (Uninterruptible Power Supply) systems. One UPS to protect the TrackLab PC and the second UPS to protect the Sewio server PC.  The purpose of each UPS is twofold:  - Keeps both systems running during short power failures and  - Trigger a controlled shutdown sequence of the system before the UPS is completely depleted.  The latter is of utmost importance for TrackLab and should at all times prevail over the former. Note: that the hibernation mode of Windows must be disabled because TrackLab does not support this. Both UPS systems should have at least the next specifications: - 2 battery-protected grounded AC connectors: (1 PC + 1 monitor) - Type of AC connectors depending on the country of use. - AC plug compatible with the available sockets on site.  - Output power: 350 W (PCs, monitors, anchors, network switch), 600VA.  A theoretic backup time of 10 minutes at 350 W. - Able to graceful shutdown the PC. With these specs, even under the heaviest load (350W per UPS), the UPS can keep the equipment running for about 10 minutes. We recommend checking the battery quality of the UPS regularly to make sure that it can perform its task. Please contact your local UPS specialist for more information. View original HubSpot article · HubSpot article 190573052263 · Knowledge Base 187958790447 · Language en · Updated 1748143383637 --- ## How do software-based and hardware-based licenses compare? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-do-software-based-and-hardware-based-licenses-compare Chapter: Noldus Knowledge Base Traditionally Noldus has used hardware-based licenses for all of its software, requiring the hardware license key (or "dongle") to be plugged in when using the software. Starting with The Observer XT 16, EthoVision XT 17, and FaceReader 9, we now offer a software-based license as an alternative to the hardware key. A software-based license can be used without a dongle. Fixed vs Floating Licenses There are two options for how a software-based license can be used; you can choose between them when you activate the license. - Fixed: A fixed license is activated on a single computer and then does not need any key or internet connection when the software is used. In this case the software can only be used on that one computer, unless you deactivate the license. Activation and deactivation require an internet connection, but normal use does not require a network connection. (EthoVision XT 17 can also be activated using a QR code and a smartphone, although an internet connection is easier.) - Floating: A floating license permits the software to be activated on multiple computers. In this case an internet connection is required at all times, and the software will be usable only if it is not already in use on a different computer. However as soon as the application is closed on one computer, it is available to be used on another. You can switch between the two types of licenses. Just Deactivate the license, then Activate it again using the desired option. Floating licenses provide the most flexibility, but Fixed licenses are convenient when network access is limited or unreliable. Multiple Seats In some cases, a license may permit use on multiple computers at once. Each license is limited to a certain number of seats (determined when the license is purchased, but normally one unless additional seats are purchased). For example, a license with 3 seats may be used on three computers at once. You can use any combination of fixed and floating activations; each fixed activation takes one seat all the time, while floating activations only take a seat when the software is open. So for example, if you have 3 seats, a fixed activation on one computer, and floating activations on several additional computers, you could use those floating licenses on two of those computers at a time. EthoVision XT If you are using EthoVision XT, please note that, just as in previous versions, you do not need any kind of license if you are only doing analysis of already-acquired data. A license is only needed when acquiring tracks (either from a camera or from a video file), or when creating a new experiment that will use functionality from optional modules (e.g. trial control, multiple arenas). The Observer and FaceReader always require a license to use.   View original HubSpot article · HubSpot article 190573052081 · Knowledge Base 187958790447 · Language en · Updated 1748133304693 --- ## How do we handle TrackLab support involving Ubisense hardware? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-do-we-handle-tracklab-support-involving-ubisense-hardware Chapter: Noldus Knowledge Base For Ubisense support, get R&D team assistance and apply an according response time. We stopped selling Ubisense UWB hardware a long time ago (replaced by Sewio) so the amount of support is already small and will become only less over time. Therefore R&D sees no point (no ROI) in transferring the complex and abundant Ubisense system knowledge to Operations/Support. View original HubSpot article · HubSpot article 190573052060 · Knowledge Base 187958790447 · Language en · Updated 1748131749637 --- ## How does the anchor geometry affect tracking precision across the tracking site? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-does-the-anchor-geometry-affect-tracking-precision-across-the-tracking-site Chapter: Noldus Knowledge Base This article discusses tracking precision. View this article to learn about the difference between tracking precision and accuracy. When the accuracy of the TrackLab/Sewio UWB system comes into play, the anchors’ placement geometry has a key role. This article is intended to give insight into how the anchor geometry affects the precision across the tracking site. A general mathematical model for evaluation of localization precision is the Dilution of Precision (DOP) model, which will be used to illustrate how precision is affected in 2 examples: - Square anchor geometry (optimal for tracking precision) - Rectangular anchor geometry, with an aspect ratio of 20:3 (x:y). Note: the anchor placement rules say the aspect ratio must not exceed 3:1. This example merely serves to illustrate how the precision is affected if you ignore these rules. Example 1) SQUARE geometry The below image illustrates how the precision across the tracking area changes, depending the location. The lines connect areas with the same precision. The precision is expressed by the 'gain' factor. Dark blue stands for optimal precision, whereas red indicates poor precision. You can immediately see that precision is generally good in the area encompassed by the anchors. The area below the anchors already shows slightly less precision. Behind the anchors, in the corners (largest distance to furthest anchor) shows the poorest precision.   We can illustrate how this theoretic model translates to a real-world measurement. In the below image, the measured location of 500 consecutive samples are plotted, for 3 tags on different locations within the area enclosed by the anchors. You can see how the plot 'clouds' remains small and compact, indicating a high precision of repeated tag localizations. If we now do the same for 3 locations outside the area enclosed by the anchors, the result looks like below; especially in the corners behind the anchors the plot clouds are bigger where the model predicts poor precision: Here are the conclusions for site design: - If possible, place the anchors around the tracking area. For example, if a livestock pen has surrounding pathways, place the anchors such that they include the pathways in the tracking area. - Apply Areas of Interest inside the area enclosed by the anchors. - Note: in practice, you will se a reduced precision in the corners of the tracking area, also directly below the anchors. Sometimes the anchors can not be placed outside the tracking area, for instance when a livestock pen is directly bordered to walls. You then need to mount the anchors onto the walls and since the anchors need to be mounted at least 30cm from the wall, this will lead to slightly reduced precision below the anchors. However, in most TrackLab applications this will not be a practical problem since the subjects tend to not move all the way into the corners. It is still something to consider in certain situations. Example 2) RECTANGULAR anchor geometry In this example, the anchors on the x-axis are much further apart than the anchors in the direction of the y-axis. The aspect ratio (AR) in this example is 20:3 meters. Remember that this AR goes against the anchor placement rule that says that the anchor AR shall be 3:1 (x:y) at maximum. This example is intended to merely demonstrate what the effect on precision would be should you ignore the rule. The below image again shows the Dilution of Precision model, including 500 location plots of 3 tags each (the black plot clouds). You immediately see how especially the precision on the 'short side' of the tracking area (the y-axis) is compromised. The precision on the x-axis is unaffected. In some use cases where only the precision in x-direction is important, this geometry does not have to pose a problem. For example if you want to know how far up the hallway of a museum a visitor has progressed. In other applications it may be a problem for example if you want to know if a supermarket shopper is in proximity to either left or right side shelves of an aisle. What to do if your customer wants to track subjects in such a narrow area, and a decent precision on the y-axis (short side) is required? You can solve this problem by adding extra anchors and adjusting the geometry, for instance like below (red dots are anchors): View original HubSpot article · HubSpot article 190573052056 · Knowledge Base 187958790447 · Language en · Updated 1748131458684 --- ## How long EthoVision XT would take to analyze a 1‑GB video file and whether the software could run in the background while other applications are used? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-long-ethovision-xt-would-take-to-analyze-a-1gb-video-file-and-whether-the-software-could-run-in-the-background-while-other-applications-are-used Chapter: Noldus Knowledge Base Customer query about how long EthoVision XT would take to analyze a 1‑GB video file and whether the software could run in the background while other applications are used. Resolution – EthoVision analysis speed depends on the computer’s processor, RAM, graphics card, and the video’s resolution and frame rate. EthoVision XT can process video faster than real time on capable hardware, but actual duration varies; testing a sample video on the user’s system is the best way to estimate. It was strongly recommended to close all other programs, including background tasks such as email or antivirus, during analysis. Running other software simultaneously may reduce performance or cause missed samples. FAQ and Step-by-Step Instructions How long does EthoVision XT take to analyze a 1‑GB video? The processing time varies based on several factors: - **Hardware** – Faster CPUs, sufficient RAM and a capable graphics card reduce analysis time. - **Video properties** – High‑resolution or high‑frame‑rate videos require more processing. - **Algorithm settings** – Choosing advanced tracking methods (e.g., deep learning or 3‑point tracking) can increase processing load. To estimate processing time: - Identify your video’s duration, resolution and frame rate. - Run a test analysis on your system with a similar clip and measure how long it takes. - Multiply the result proportionally for longer videos. For example, if a 5‑minute clip takes 3 minutes to analyze, a 60‑minute clip may take about 36 minutes on the same machine. - If processing is slow, consider upgrading hardware or adjusting video resolution or settings. Can I run EthoVision XT analysis in the background while using other applications? It is **not recommended**. EthoVision XT needs uninterrupted access to system resources to avoid missed samples. To ensure smooth analysis: - Close unnecessary programs, including email clients, browsers, antivirus scans and other background services. - Disable automatic updates or scheduled tasks that might run during analysis. - Start the EthoVision analysis and allow it to run without interference. - Once the analysis completes, you can reopen other applications. - Running other software simultaneously may reduce performance or cause errors, especially on systems with limited resources. How can I improve analysis speed? - **Use recommended hardware** – Ensure your PC meets or exceeds the system requirements for EthoVision XT (multi‑core CPU, dedicated GPU, ample RAM). - **Store video files locally** – Process videos from a fast local drive (preferably an SSD) rather than a network location. - **Optimize video resolution** – Avoid unnecessarily high resolutions; downsample videos to a resolution appropriate for your tracking needs. - **Limit background processes** – As noted above, run EthoVision XT as the primary task on the machine. What if my analysis still takes too long? - If processing remains slow even after closing other programs and using adequate hardware, consider contacting Noldus support. Provide details about your hardware specifications, video resolution, frame rate and the version of EthoVision XT you are using. View original HubSpot article · HubSpot article 194772884083 · Knowledge Base 187958790447 · Language en · Updated 1755641511781 --- ## How many GigE cameras can I use on a laptop with EthoVision XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-many-gige-cameras-can-i-use-on-a-laptop-with-ethovision-xt Chapter: Noldus Knowledge Base It's generally recommended to use GigE cameras on a desktop computer with the camera connected to a dedicated Intel gigabit network adapter. This leaves the built-in network adapter available for connecting to your local network and/or the internet. It is possible to use a laptop with a suitable built-in gigabit network adapter with a GigE camera, but the settings will not be suitable for connecting the laptop to a network. You will need to use wifi or a USB network adapter if a network connection is needed. EthoVision XT 12, 13, and 14 were tested and supported on a workstation-class laptop with one Basler GigE camera for recordings up to 10 hours in duration. This scenario was not tested and is not officially supported in EthoVision XT 15 and 16. We do support use of the USB 3.0 Basler acA1920-155um camera on a suitable laptop. On a suitable desktop computer equipped with a four-port network adapter, it's possible to record from up to four GigE cameras simultaneously. View original HubSpot article · HubSpot article 190573052035 · Knowledge Base 187958790447 · Language en · Updated 1748129388500 --- ## How often does the TrackLab-Sodaq GPS tag need to be charged? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-often-does-the-tracklab-sodaq-gps-tag-need-to-be-charged Chapter: Noldus Knowledge Base General guideline: - In conditions of limited sunlight exposure and no sleep mode activated (animal continuously moving), the Sodaq GPS tags will need to be charged approximately every 4 days. - Since battery lifetime can be extended by solar charging and sleep mode activation, it is recommended to periodically check battery charge level in the TrackLab interface (Recording module). This way the customer can learn what the battery discharge characteristics are in their application setting, and base a charge schedule on it. The charge level should be kept above 40%. More details on battery lifetime extension: - The greater the sunlight exposure, the more the battery will be charged through the solar panel. This feature will pay off more in countries and regions closer to the equator and/or clear skies. - The less the animals move about, the more often the 'sleep mode' will kick in. If the animal does not move, this will be detected by an accelerometer sensor, which will put the GPS receiver in sleep mode, thus saving energy. The GPS receiver will switch on again if the accelerometer sensor detects movement.  Mimimum charge level: - For the Sodaq tag to operate correctly, a minimum charge level of 40% must be maintained. From 35% down, tag operation cannot be guaranteed anymore (the tag may stop receiving data and storing to SD).   View original HubSpot article · HubSpot article 190573052186 · Knowledge Base 187958790447 · Language en · Updated 1748137433645 --- ## How to change the frequency on a Sennheiser wireless mic solution and automatic sync with wireless mic URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-to-change-the-frequency-on-a-sennheiser-wireless-mic-solution-and-automatic-sync-with-wireless-mic Chapter: Noldus Knowledge Base Setting the channel and frequency ▷ Select the Tune menu item and call it up by holding down the SET button until the channel selection appears. ▷ Adjust the settings. ▷ Press the jog dial to save your selection.     or ▷ Press the ESC button to cancel the entry without saving the setting. Synchronizing devices You can synchronize new 300-500 G4 series transmitters and receivers via the receiver’s infrared interface. You can adjust the Parameters to be transferred to the transmitter here: “Advanced -> Sync Settings menu item”.  To synchronize the devices: ▷ Switch the transmitter and the receiver on. ▷ Press the SYNC button on the receiver.     Sync appears in the receiver’s display and the blue LED turns blue.    ▷ Hold the infra-red interface of the transmitter in front of the infra-red interface of the receiver.   The parameters are transferred to the transmitter. The blue LED blinks during transmission. When the transfer is complete, a tick appears in the receiver’s display as a confirmation. Then the receiver will return to the current standard display.  To cancel synchronization: ▷ Press the ESC button on the receiver. An X appears in the display. This icon also appears when: • no transmitter is found or the transmitter is not compatible. • no transmitter is found and the synchronization process automatically ends after 30 seconds. View original HubSpot article · HubSpot article 190573052261 · Knowledge Base 187958790447 · Language en · Updated 1748143153695 --- ## How to create a scheduled reboot task URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-to-create-a-scheduled-reboot-task Chapter: Noldus Knowledge Base Rebooting the Viso PCs and cameras is the first thing to do when you encounter any issues. Issues are more likely to occur if the PCs have been powered on for many days. For optimal performance of Viso, the PCs should be rebooted daily. The following steps describe how to automate a daily PC reboot task: - On the Windows Start button, type Task Scheduler and open the Task Scheduler app. - In the Actions pane on the right, select Create Task. - On the General tab, fill in the Name field. e.g. “Nightly Reboot” - Select the radio button Run whether user is logged on or not - Check the box Run with highest privileges. - Click the Triggers tab and click New… - Under Settings, select Daily and set the start time to a convenient time for the server to reboot. Click OK. - Click the Actions tab and click New… - For Action, keep the default selected Start a program. - In the Settings pane, for Program/script: enter C:\Windows\System32\shutdown.exe with the arguments /s /t 0. (Shutdown after a time of zero seconds.) Click OK. - Click OK. - Enter the User name and Password and click OK. - User name: .\Noldus - Password: Noldus123 - If your Viso system is on a domain joined computer, contact your local IT support. Power down AV rack: There is no way to automate a power down of the AV rack (black Noldus Audio Video rack, often in corner/closet). If PCs are rebooted daily and you are still experiencing a Viso issue, please turn the AV rack off for 1 minute then power back on and test the issue. View original HubSpot article · HubSpot article 195616323997 · Knowledge Base 187958790447 · Language en · Updated 1773941369962 --- ## How to merge manual scoring data collected in EthoVision on different computers? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-to-merge-manual-scoring-data-collected-in-ethovision-on-different-computers Chapter: Noldus Knowledge Base How to merge manual scoring data collected on different computers. Manual scoring visualizations were absent for some trials and was concerned that retracking with new settings might erase manual scoring.  FAQ and step‑by‑step instructions How do I merge manual scoring data from multiple computers? - On each PC, export manual scoring data to an Excel file via Export > Manual scoring. - Transfer the Excel files to a single PC. - In Excel, align start/stop times and combine scoring rows into one sheet. Add a source column if needed. - Use the combined dataset for analysis in EthoVision or another program. Why are manual scoring visualizations missing? The software cannot display manual scoring if no behaviors were recorded. For the trials in question, no manual data existed, so the visualizations were empty. Verify that the trial durations are sufficient and rescore if necessary. Will retracking erase manual scoring? Yes. Re‑running detection overwrites manual scoring. Always export the manual scoring data first. After retracking, merge the old manual scoring with the new detection data, ensuring timestamps align. How can I prevent EthoVision from tracking shadows? Reset the background during acquisition by clicking the camera icon in the video window. This forces EthoVision to capture a fresh background frame. Alternatively, briefly switch the room lights off and on to refresh the background. Can I avoid manual scoring entirely? Using updated detection settings and analysis profiles (e.g., nose‑point tracking and appropriate zones) can automate behaviour scoring. Optimise lighting and arena design to improve automatic tracking accuracy. View original HubSpot article · HubSpot article 194934578774 · Knowledge Base 187958790447 · Language en · Updated 1755876419722 --- ## How to re-name a computer with a Viso setup URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-to-re-name-a-computer-with-a-viso-setup Chapter: Noldus Knowledge Base How to re-name a computer with a Viso setup Renaming the computers is a known problem, as there are cases where the computer names are stored: - Rabbitmq has to be reinstalled to work, as it saves the computer name on install and uses it for rabbitmq. - If video file names contain a path like //visorecorder1/media/video1.mp4, the database maintenance tool needs to be used to find the new location of the files (like //aic-congres01/media/video1.mp4) The process can be:  - Stop everything - Make a backup of the database - Uninstall nlinx server - Make the computer renames - Reinstall nlinx server - Start viso and check if video files can be found, if not use the database maintenance tool - Check the live preview of the rooms, it may be needed to recreate the locations View original HubSpot article · HubSpot article 190573052215 · Knowledge Base 187958790447 · Language en · Updated 1748139442705 --- ## How to reboot a Viso Services/Recorder Computer URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-to-reboot-a-viso-servicesrecorder-computer Chapter: Noldus Knowledge Base - Click on the start menu and open Remote Desktop Connection. - In the field labeled Computer, enter the hostname of the Viso Services or Viso Recorder computer. In most installations, this name is Viso-Recorder1. - When prompted for a username and password, enter them. If the computer was supplied by Noldus, the username will usually be Noldus with the password Noldus123. - Now, at the Viso Recorder desktop, reboot the computer from the start menu as normal. View original HubSpot article · HubSpot article 209556431899 · Knowledge Base 187958790447 · Language en · Updated 1773942202794 --- ## How to rename your subjects in TrackLab URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-to-rename-your-subjects-in-tracklab Chapter: Noldus Knowledge Base Subject names can be changed either manually, one by one or by importing new subjects from a file. How to manually rename your subjects Click on a particular subject name in the "subject name" column to enter manually new subject names.  Alternatively, select a known subject name from a drop-down list within a subject name cell. This drop-down menu contains all known subjects names used within TrackLab (all subjects used in any session and site).  If a new subject name is already used for another tag in the opened session the subject cell is outlined in red and the new name is not accepted.  Note: that all manual rename actions only affect the selected session.  Import subject names The import subject names button, located on the right side of the screen, opens a dialogue that allows you to select a file. This file needs to contain the recorded tag MAC addresses assigned to a new subject name. When uploading the file it only applies to the selected session unless the checkbox "to all session" is ticked. If this is the case, the rename actions apply to all existing sessions within the project/experiment.  The name extension of the text file is not restricted although it must contain text. The first line of the file will be ignored as this is seen as header information. All subsequent lines must contain a tag MAC-Id and the subject name to assign to it, separated by a semicolon.  An incorrect format for the mapping file will result in an "incorrect Mapping File" error.  See subject renaming failures for more details about the errors.  Note: Renaming of subjects takes some performance time of the TrackLab software. Especially when larger name files or several sessions are selected. TrackLab does not show any progress indication. You can see when the progress finishes as soon as the new names appear in the Subject-Level variable list. In the meantime, it is not possible to make any adjustments until the progress has finished.  View original HubSpot article · HubSpot article 190556076890 · Knowledge Base 187958790447 · Language en · Updated 1748142646655 --- ## How to setup Deep Learning in EthoVision XT 18? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/how-to-setup-deep-learning-in-ethovision-xt-18 Chapter: Noldus Knowledge Base   Resolution – Deep Learning isn’t a standalone module; it becomes available only when three‑point tracking is selected and, for live tracking, only when the experiment contains fewer than two arenas or subjects. The customer was advised to adjust experiment settings accordingly.  FAQ and Detailed Instructions:  Why can’t I use the Deep Learning option in EthoVision XT?  - Deep Learning doesn’t appear as a separate module. It is available only when you configure your experiment to use three‑point tracking and, for live tracking, when there are less than two arenas and no more than two subjects per arena.  What is three‑point tracking and why is it required?  - Three‑point tracking refers to tracking the animal’s body as three separate points (e.g., nose-point, center, and tail-base). The Deep Learning algorithm relies on this tracking mode for accurate body-point recognition.  Enabling Deep Learning in your experiment:  - Open your experiment in EthoVision XT and go to the Experiment Settings. - Select three‑point tracking – Choose the tracking method that uses three points on the subject’s body. - Confirm the number of arenas – For live tracking, Deep Learning is only available when up to four arenas are configured and either one or two subjects per Arena. - Update the software – Ensure you have a recent version (v18 or later). - Verify hardware – Make sure you have a compatible NVIDIA GPU with up‑to‑date drivers. - Restart and test – After adjusting settings, restart the software and confirm the Deep Learning method appears. Can Deep Learning be used when live tracking in more than one arena?  - Yes. EthoVision XT supports the Deep Learning algorithm in up to four arenas when live tracking.   Can Deep Learning be used when live tracking more than one subject (Social Interaction Module required)?  - Yes. EthoVision XT supports the Deep Learning algorithm for live tracking when only two subjects are tracked in the same arena, in up to 4 arenas.  What if I still cannot enable Deep Learning after following these steps?  - - Confirm three‑point tracking is selected.  - - Ensure your EthoVision license is active (USB license key or software-based license key).  - - Restart EthoVision XT after changing settings.  - - Check GPU drivers and hardware compatibility.  - - If the option is still missing, contact support@noldus.com with your software version, hardware details and experiment configuration.  View original HubSpot article · HubSpot article 194772883628 · Knowledge Base 187958790447 · Language en · Updated 1755622033786 --- ## I can't get my firewire camera working in EthoVision XT 15.0 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/i-cant-get-my-firewire-camera-working-in-ethovision-xt-150 Chapter: Noldus Knowledge Base EthoVision XT 15.0 requires Windows 10, which no longer supports Firewire devices. The most recent version to support Firewire (IEEE-1394) cameras was EthoVision XT 11.0. View original HubSpot article · HubSpot article 190556076902 · Knowledge Base 187958790447 · Language en · Updated 1748145438638 --- ## I cannot find my project’s VOP file. I see a file that looks like it might be it, but I am unsure URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/i-cannot-find-my-projects-vop-file-i-see-a-file-that-looks-like-it-might-be-it-but-i-am-unsure Chapter: Noldus Knowledge Base Solution: Check that the Windows File Explorer is not “hiding” the relevant file information If your project’s folder looks similar to the image below, it is likely that Windows is hiding the file type and file extension information.  You can resolve this issue by going to “View”, checking the “Details” (will display the file type information), and checking the “File name extensions” box (will display the file extension information after the file name).   Please note that the .vop file is not a complete project. This is the file you select to open the project, but don't copy just this file, or create a new copy in this folder. To copy the project, copy the entire folder named for the project, or open the project in The Observer and then use File > Save Project As to create a new copy. View original HubSpot article · HubSpot article 190556076853 · Knowledge Base 187958790447 · Language en · Updated 1748134342660 --- ## I made a backup file but I cannot see the VPB file extension on the end in File Explorer. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/i-made-a-backup-file-but-i-cannot-see-the-vpb-file-extension-on-the-end-in-file-explorer Chapter: Noldus Knowledge Base Backup files in The Observer are expected to have a .vpb extension. However, after making a backup file and saving it to the hard drive, the file extension may not show up in File Explorer. This results because Windows by default hides extensions for known types of files. In order to see all extensions, even for known file types, make the following changes. Windows 7 In File Explorer, tap the Alt key to see the menu, then under Tools pick Folder Options. Click the View tab and uncheck the option "hide extensions for known file types." Windows 10 In File Explorer, select the View menu, then check the box for ‘File name extensions’: View original HubSpot article · HubSpot article 190573052172 · Knowledge Base 187958790447 · Language en · Updated 1748136602630 --- ## If i want to upgrade TrackLab, do i need to upgrade all three components (Viewer, Recorder and Server)? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/if-i-want-to-upgrade-tracklab-do-i-need-to-upgrade-all-three-components-viewer-recorder-and-server Chapter: Noldus Knowledge Base Yes. You need to run all three installers. Please follow the steps in the TrackLab manual on how to update TrackLab. Note: the steps describe the option to create a backup of the dataset. This is only available starting from TrackLab 2.15. View original HubSpot article · HubSpot article 190556076869 · Knowledge Base 187958790447 · Language en · Updated 1748138388671 --- ## Image from my camera is flickering URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/image-from-my-camera-is-flickering Chapter: Noldus Knowledge Base This issue can arise because fluorescent and LED lighting actually flashes very quickly, at a rate dependent on the electrical power frequency. This rate is fast enough that it is imperceptible to human vision. If the camera's frame rate is mismatched with the flicker rate of the lighting, the camera may acquire images at points of high and low brightness, resulting in a flicking image. For example, common power sources are 50 Hz (in Europe and most of Asia) and 60 Hz (in North America), which cause 100 and 120 pulses of light each second, respectively. Solution: Alter the frame rate of the camera in your Noldus software  Under normal lighting conditions in North America, a frame rate of 25 will occasionally result in a flickering image and it can be resolved by increasing the frame rate to 30.  However, you may need to alter the frame rate and check to see the resulting image no longer flickers. This is especially true for dimmable lighting as altering the dim settings will alter the pulses of light each second (e.g., more dim = fewer pulses). EthoVision XT In the Experiment Settings, alter the frame rate for your camera(s) and click on theicon to get a live image to see if the issue is resolved.      If not, you can alter the frame rate and view the resulting image in the Video Settings window that opens after clicking the icon.   NOTE The image will take a few seconds to update after making any changes. Also, these settings will become locked once you have acquired any trials in your experiment. If those trials are not needed (e.g., they were just tests to make sure the settings were ok), you can delete them. Otherwise, you can create a new experiment. To create a new experiment but copy all the settings (but not data) from the original experiment, pick the option to create a New Template Experiment, then Custom Template, and pick your existing experiment as the source. Note this can take a while, especially if the original experiment contained many trials.   MediaRecorder In the Video Settings, alter the frame rate for your camera(s) under the Frame rate column and click Apply to see if the issue is resolved in your live image in MediaRecorder.  If not, repeat the procedure until the flickering no longer appears.   NOTE The image will take a few seconds to update after making any changes. View original HubSpot article · HubSpot article 190271483187 · Knowledge Base 187958790447 · Language en · Updated 1747539506961 --- ## Improving Nose-Tail tracking in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/improving-nose-tail-tracking-in-ethovision-xt Chapter: Noldus Knowledge Base How Nose-Tail Tracking Works EthoVision XT can use two different methods to track the nose and tail: - Contour-based detection looks at the outline of the area detected as the animal to find the correct shape of the nose and tail. - Deep learning uses a trained neural network model to identify the nose and tail of a mouse or rat. This method, available in EthoVision XT 16 and up, uses the image of the animal and can accurately place the nose and tail even outside the yellow detected area of the animal. Deep learning requires a suitable NVIDIA GPU; if that is not present, contour-based detection is required. When deep learning is available, and you are working with rodents, it will generally give the best results. Contour-Based Detection When using contour-based detection, it's important to adjust the detection settings so that the yellow area (which indicates everything detected as the animal) corresponds as closely as possible to the real outline of the animal, since the outline is being used to identify the points. In the Detection Settings, under the method there is a pulldown selection of the algorithm to identify the nose and tail points. The options are: - Any species / Default: This is a general method that works for many animals. If tracking rodents, make sure the tail is detected. (In EthoVision XT 14 and earlier, this was called "Shape-Based / Default".) - Rodents / Default: This method fits a model rodent shape to the detected outline. It is more robust for rodents than the above method because it does not require the nose and tail to be visible. It's a good choice when tracking a single rodent without occlusions or difficult tracking conditions, for example in an open field, water maze, or novel object test. (In EthoVision XT 14 and earlier, this was called "Simple Model / Rodents".) - Rodents / For Occlusions: This method works better than the default method if parts of the animal will be occluded from view, e.g., by bars in a cage or by another animal. It is more computationally demanding however. It works best if the animal's tail is not tracked (you can use the Erosion and Dilation settings to adjust this). (In EthoVision XT 14 and earlier, this was called "Advanced Model / Rodents".) - Adult Fish / For Occlusions: This method is best for adult zebrafish and fish of similar shape, when viewed from above. Make sure the whole body of the fish is detected, including the tail. (In EthoVision XT 14 and earlier, this was called "Advanced Model / Adult Fish".) - Other Species / For Occlusions: This method may work better for other types of animals, or fish from the side. (In EthoVision XT 14 and earlier, this was called "Advanced Model / Other".) Optimizing the "Rodents / For Occlusion" method When using this method (called "Advanced Model / Rodents" in EthoVision XT 14 and earlier), you can improve the results by telling EthoVision the size of your animals. To do so: - In the Detection Settings, first optimize the detection of the animal's body so that the detected area (in yellow) matches the real outline of the animal as closely as possible. - Click the Advanced button next to Subject Size. - In the middle panel of the window that opens, labeled "Modeled Subject Size", the size of the currently-detected animal will be displayed under Current Pixels. You can either copy this value to the Average Pixels by clicking the Grab button, or click on that value and edit it directly. You want the Average Pixels to be a reasonable estimate of the typical size of the animal. (The actual size will vary from frame to frame based on the posture of the animal, but try to set it close to the average.)  - Then, check the checkbox under Fix. This will often improve the accuracy of nose-tail tracking when using this method. If you are tracking multiple animals in the same arena, and EthoVision sometimes identifies them as a single large animal when they are in contact, reducing the Average Pixels value may help. Deep Learning Deep learning will work best when the outline of the animal is visible everywhere in the arena. As always, you will get best results when the lighting is relatively uniform. The animal should be at least 30 pixels in length to provide enough detail. When using deep learning, there are only two new settings in the Detection Settings. There is a checkbox for "Hooded rats" which should be used if your animals are a mixture of black and white rather than a uniform color. There is also a Define button which allows you to specify the Cutout size. Clicking the Define button should show you an image of your animal with a yellow box around it. The yellow box should extend 0.5-1 body lengths beyond the animal in all directions (not including the tail). You can click the Automated button to set it automatically, or adjust it manually with a slider. This tells the model how big to expect your animal to be. General Advice If the center of the animal is tracked accurately, and the nose and tail are tracked accurately most of the time, but there are quite a few nose-tail swaps, the following suggestions can significantly improve tracking of the nose and tail: - When you draw the arena, take care that it is big enough (but not too large that you bring external factors into play like dark or light edges the system may mistake for your animal), also to include when the rat is rearing up the sides. If the rat can stick its nose outside the arena, EthoVision will not be able to detect its nose. - If you have reflections on your side walls, which the system is mistaking for your animal (or merging the animal and its reflection into one big shape), one option can be to lightly sand the walls of the arena, so they are not so shiny. - The contrast setting should be set such that the entire animal is detected. You may find that a higher contrast setting accurately finds the center of the animal but misses the edges. In this case, EthoVision cannot see the outline of the animal, and will have trouble identifying the nose and tail from that outline. Set the contrast to the lowest setting possible that still correctly identifies the animal without much noise in the arena. - For best results the lighting should be even, indirect and diffuse. Please see the manual for details about this. The diagram in the manual about placing lights in relation to a water maze is also applicable here. If the lighting is uneven, the appropriate contrast levels may vary between different areas of the arena. Also, uneven lighting will create shadows which will affect the outline of the animal. - You do not need bright lighting. Opening up the aperture (diaphragm) of your camera a little may improve the contrast without changing the lighting. - For nose-trail tracking it is often best to track at the maximum sample rate (25-30 samples per second), so that the tracker has as much information as possible. - Sometimes, especially if the load on the computer is high, you may get better results tracking from a video file. If you find that is the case, you can use 2-stage tracking (first acquire the video with EthoVision, then track from that video). When you track from video, always use the Detection Determines Speed setting in acquisition.   View original HubSpot article · HubSpot article 190573052221 · Knowledge Base 187958790447 · Language en · Updated 1748139693390 --- ## Installing EthoVision XT 17.5 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/installing-ethovision-xt-175 Chapter: Noldus Knowledge Base System requirements EthoVision XT 17.5 runs with Windows 10 Professional and 11 Pro. Note that it is not designed for use with the Touch features of Windows. If you have EthoVision XT 17.0, this version replaces your current version! However, it won't change or delete your experiments. If you have EthoVision XT 16 or older, this is not a free upgrade. If you have a hardware license key (dongle), you will need to enter an upgrade code before you can use the new version. If you have a NoldusCare contract, the registered user has received an upgrade key, otherwise please contact your sales person to purchase an upgrade. If you have a software-based license, the license will update automatically if you have an active NoldusCare contract; otherwise please contact your sales person to purchase the upgrade. Before you install EthoVision XT If you are a new user of EthoVision XT: You received a software activation key. Please make sure you have this key at hand when you start EthoVision XT.  If you are upgrading from older versions of EthoVision and have a hardware license key (dongle): You received an email with a license upgrade key. Please make sure you have this key at hand when you start EthoVision XT. User rights: To install EthoVision XT, you must have administrator rights. In other words: either you are the system administrator or you are a member of the Windows group Administrators and have been assigned administrator rights. Regional Settings: We recommend not to use a comma as the decimal separator in the Windows regional settings. To open the regional settings, in Windows choose Apps > Windows System > Control Panel. Under Clock, Language and Region click Change date, time or number formats, then click Additional settings. MediaRecorder: If you plan to install MediaRecorder and EthoVision XT on the same PC, first install MediaRecorder, then EthoVision XT. To install EthoVision XT 17.5 Close all other programs before installing EthoVision XT. If you do not already have the installation files (e.g., you may have received a USB drive with the installation files when you purchased your system), they can be downloaded from this site. You will need to login with an account associated with your license. (If you do not have access, please contact support@noldus.com for assisstance. Let us know the license number or the name of the registered user.) To download the files: - Click Downloads at the top of the page. - Under the EthoVision heading, click Versions. - Click "Ethovision XT - Installation Package - 17.5.1718.zip" and then click Download in the panel that appears on the right. Note that this is a large ZIP file, so downloading may take some time. The installation is too large to fit into a single installation file, so it is split into four files, all of which are included in this zip file. Although Windows will allow you to double-click the zip file (showing it as a compressed folder) to see what is inside, you cannot run the installer that way (installation will fail). Instead, you must extract the files in order for the installation to work: - Right-click the zip file (compressed folder) and pick Extract All. - Check the check-box for "Show extracted files when complete". Whether you started with the zip file or had the individual installation files, continue here: - Double-click the file "EthoVision XT 17.5 – Setup – [version number].exe" to begin the installation. - Choose Standard as the Installation type. - Check the boxes for the drivers for the cameras or the encoder board you use. If you have Basler USB 3.0 cameras (connected with a USB cable), choose Basler USB camera driver. If you have GigE Vision cameras (connected with an ethernet cable), choose Basler GigE camera driver or Daheng Galaxy depending on which camera you have. If you have analog cameras (connected with BNC cables), choose Euresys Multicam. This works only with the Picolo Alert encoder board. If installation fails for any reason, the installer will provide a log file. If you send this log file to support@noldus.com, we can diagnose the cause. Opening EthoVision For The First Time When you first open EthoVision, it will look for your license. If you have a hardware license key (dongle): This primarily applies for those upgrading from previous versions of EthoVision. You have a purple USB hardware key which plugs into the computer. It should be labeled with "EthoVision" and the license number. If the hardware license key is for EthoVision XT 17.0 or higher, it will immediately be recognized and EthoVision will open, ready to go. If the hardware license key is for a previous version of EthoVision, you will be prompted for an upgrade key. Enter the key and your hardware license key will be updated. You will only need to enter this key once, and it will be remembered by your hardware license key. If you have a software-based activation code: This applies to most new licenses. You do not have a hardware license key, but do have an activation code. Select Activate software license key. You will have the option to pick a Floating or Fixed license: - Floating – You can activate the license on multiple computers, but use it only on one of those computers at a time (per license seat). An internet connection is required while using EthoVision. - Fixed – This is the option for you if you don’t have an internet connection to the computer you want to acquire the data with. You can activate the fixed license with a one-off internet connection or using a QR code. If you will only be acquiring tracks on one computer (i.e., the one with the cameras), a Fixed license is usually a better option. Note that you can install EthoVision on additional computers without the activation code. When you start EthoVision, you'll pick the option to start in unlicensed analysis mode, and you will have full access to analyze data that has already been acquired. View original HubSpot article · HubSpot article 190556076848 · Knowledge Base 187958790447 · Language en · Updated 1748133987664 --- ## Installing EthoVision XT 18 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/installing-ethovision-xt-18 Chapter: Noldus Knowledge Base System requirements EthoVision XT 18 runs with Windows 11 Pro. Note that it is not designed for use with the Touch features of Windows. It is anticipated that it will work with Windows 10 but this was not fully tested. Installing EthoVision XT 18 will not uninstall any previous version, although you may wish to do so in order to prevent confusion. Uninstalling previous versions will not change or delete your experiments. Experiments from previous versions can be opened in EthoVision XT 18; you will get a message that they will be updated. Once saved in 18, they cannot be opened in previous versions. IIf you have EthoVision XT 17 or older, this is not a free upgrade. If you have a hardware license key (dongle), you will need to enter an upgrade code before you can use the new version. If you have a NoldusCare contract, the registered user has received an upgrade key, otherwise please contact your sales person to purchase an upgrade. If you have a software-based license, the license will update automatically if you have an active NoldusCare contract; otherwise please contact your sales person to purchase the upgrade. Before you install EthoVision XT If you are a new user of EthoVision XT: You received a software activation key. Please make sure you have this key at hand when you start EthoVision XT.  If you are upgrading from older versions of EthoVision and have a hardware license key (dongle): You received an email with a license upgrade key. Please make sure you have this key at hand when you start EthoVision XT. User rights: To install EthoVision XT, you must have administrator rights. In other words: either you are the system administrator or you are a member of the Windows group Administrators and have been assigned administrator rights. Regional Settings: We recommend not to use a comma as the decimal separator in the Windows regional settings. To open the regional settings, in Windows choose Apps > Windows System > Control Panel. Under Clock, Language and Region click Change date, time or number formats, then click Additional settings. MediaRecorder: If you plan to install MediaRecorder and EthoVision XT on the same PC, first install MediaRecorder, then EthoVision XT. To install EthoVision XT 18 Close all other programs before installing EthoVision XT. If you do not already have the installation files (e.g., you may have received a USB drive with the installation files when you purchased your system), they can be downloaded from this site. You will need to login with an account associated with your license. (If you do not have access, please contact support@noldus.com for assistance. Let us know the license number or the name of the registered user.) To download the files: - Click Downloads at the top of the page. - Under the EthoVision heading, click Versions. - Click "EthoVision XT - Installation Package - 18.0.1832" and then click Download in the panel that appears on the right. Note that this is a large ZIP file (5 GB), so downloading may take some time. The installation is too large to fit into a single installation file, so it is split into multiple files, all of which are included in this zip file. Although Windows will allow you to double-click the zip file (showing it as a compressed folder) to see what is inside, you cannot run the installer that way (installation will fail). Instead, you must extract the files in order for the installation to work: - Right-click the zip file (compressed folder) and pick Extract All. - Check the check-box for "Show extracted files when complete". Whether you started with the zip file or had the individual installation files, continue here: - Double-click the file "EthoVision XT - Setup - 18.0.1832.exe" to begin the installation. - Choose Standard as the Installation type. - Check the boxes for the drivers for the cameras or the encoder board you use. If you have Basler USB 3.0 cameras (connected with a USB cable), choose Basler USB camera driver. If you have GigE Vision cameras (connected with an ethernet cable), choose Basler GigE camera driver or Daheng Galaxy depending on which camera you have. If you have analog cameras (connected with BNC cables), choose Euresys Multicam. This works only with the Picolo Alert encoder board. If installation fails for any reason, the installer will provide a log file. If you send this log file to support@noldus.com, we can diagnose the cause. Opening EthoVision For The First Time When you first open EthoVision, it will look for your license. If you have a hardware license key (dongle): This primarily applies for those upgrading from previous versions of EthoVision. You have a purple USB hardware key which plugs into the computer. It should be labeled with "EthoVision" and the license number. If the hardware license key is for EthoVision XT 18.0 or higher, it will immediately be recognized and EthoVision will open, ready to go. If the hardware license key is for a previous version of EthoVision, you will be prompted for an upgrade key. Enter the key and your hardware license key will be updated. You will only need to enter this key once, and it will be remembered by your hardware license key. If you have a software-based activation code: This applies to most new licenses. You do not have a hardware license key, but do have an activation code. Select Activate software license key. You will have the option to pick a Floating or Fixed license: - Floating – You can activate the license on multiple computers, but use it only on one of those computers at a time (per license seat). An internet connection is required while using EthoVision. - Fixed – This is the option for you if you don’t have an internet connection to the computer you want to acquire the data with. You can activate the fixed license with a one-off internet connection or using a QR code. If you will only be acquiring tracks on one computer (i.e., the one with the cameras), a Fixed license is usually a better option. Note that you can install EthoVision on additional computers without the activation code. When you start EthoVision, you'll pick the option to start in unlicensed analysis mode, and you will have full access to analyze data that has already been acquired. View original HubSpot article · HubSpot article 190556076888 · Knowledge Base 187958790447 · Language en · Updated 1748142372668 --- ## Integrate TrackLab/Sewio with a customer network URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/integrate-tracklabsewio-with-a-customer-network Chapter: Noldus Knowledge Base Sometimes a customer requires the TrackLab/Sewio system to be integrated with their network. In order for this to work a couple of steps must be followed to reconfigure both systems. The second part is for the customer to reconfigure their network, which might involve changing security policies, DHCP server, configure routers, VLAN's or firewalls. However this article does not cover customer actions, but they must be aware of the following ports that are used to communicate between the TrackLab and Sewio devices: https://docs.sewio.net/docs/network-architecture-and-required-ports-25593406.html. Also port 123 for NTP time synchronization between the TrackLab and Sewio PC must be allowed on the network. Note: the steps below must be done before integrating with the customer network, otherwise network communication between devices might not be possible. - Request the IP addresses for both the TrackLab and Sewio system from the customer. Note that it is highly recommended to have the customer both IP addresses fixed in their DHCP server - Open a web browser and go to http://192.168.225.2 - Login with username "sewiortls" and password "sensmap" - Make sure the anchors are configured correctly: - Configure them to receive an IP address through DHCP (field: "Ethernet IP mode")      - Continuing the IP configuration of the anchor (scroll to the right). The field "RTLS Server IP Address" must be set to the IP address the Sewio system is going to be assigned by the customer - Press "UPDATE" and wait for the confirmation message. Then press "REBOOT" to restart the anchor and continue with the next anchor. Note : the settings can be changed for all anchors in one go, by specifying the settings in the "All Anchors" section (encircled in green) and press "UPDATE ALL" - The Sewio system by default runs a DHCP server. Discuss with the customer whether this should be disabled or not. If it must be disabled note that the customer must provide an active DHCP server on the network that can be reached by the TrackLab/Sewio system (including the anchors). To disable the DHCP in Sewio, follow the steps below: - Go to RTLS Manager - In the menu on the left open the settings for "DHCP Server" - Click on "STOP" - Click on "DISABLE" - Follow the next steps to make sure TrackLab receives location data from RTLS Studio - Go to "RTLS Manager" - In the menu on the left open the settings for "RTLS Server" - Go to "Server Communication Settings" - Change the value for "Udp Upload Address" to the customer provided IP address of the TrackLab PC - Click "APPLY AND RESTART RTLS SERVER" and wait for the confirmation message - The next step is to reconfigure the network settings of the Sewio PC - Open a command prompt - Type the following command: ssh -o "StrictHostKeyChecking no" noldus@192.168.225.2 and press ENTER - Enter the password "Noldus123" and press ENTER - Next type the command: sudo nano /etc/netplan/50-cloud-init.yaml and press ENTER. Use the arrow keys to move the cursor through the file - For the parameter "dhcp4" change the value to "yes" - The file must look like the contents of the screenshot below. All other information must be removed (or commented using '#') Note 1: the keyword directly below the keyword "ethernets", which is "eno1" in the example and might be different in your specific case (!), must not be changed  Note 2: before continuing verify that the information and formatting of the file is correct. In case of misconfiguration the network connection might be lost. This would mean that physical access to the PC is required to correct the error. - To save the file press and hold the CTRL key and press the O key - Press enter to accept the default name. The file should now be saved - To exit the editor press and hold the CTRL key and press the X key - Type the command: sudo netplan apply. Note that this might lead to loss of network communication as the PC requests a new IP address through DHCP - Now we must reconfigure TrackLab and the TrackLab PC - Go to "C:\ProgramData\Noldus\TrackLab Recorder\2" - Open the file "connectionsettings.xml". Note that you must have administrator privileges to edit and save the file - Find the key "SewioServerAddress" and change the IP address to the customer provided IP address - Save the file - Change the IP settings for the network card that connects with the customer network. Set it to receive an IP address through DHCP. This can be achieved using the regular network settings of Windows - Restart the computer View original HubSpot article · HubSpot article 190573052211 · Knowledge Base 187958790447 · Language en · Updated 1748139163456 --- ## Is it possible to use The Observer XT on an Apple Mac? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/is-it-possible-to-use-the-observer-xt-on-an-apple-mac Chapter: Noldus Knowledge Base The Observer is Windows software. You may be able to use it under Windows emulation, e.g., Parallels, VMware Fusion, or Boot Camp. With Boot Camp, the computer boots as if it was a Windows PC, so you can use any Windows software in a Windows environment. With Parallels and VMware Fusion, Windows software can run in a window on the Mac desktop. We are not able to provide support for these solutions but we know they are being used successfully by some users. View original HubSpot article · HubSpot article 190573052280 · Knowledge Base 187958790447 · Language en · Updated 1748145205264 --- ## Is my hardware license key PC specific, or can I move it from one PC to another as needed? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/is-my-hardware-license-key-pc-specific-or-can-i-move-it-from-one-pc-to-another-as-needed Chapter: Noldus Knowledge Base Your hardware license key (dongle) is not tied to any particular PC and can be moved as needed to any other PC that has your Noldus software installed. Please note this will limit the use of the software to one PC at a time per license key. View original HubSpot article · HubSpot article 190556076898 · Knowledge Base 187958790447 · Language en · Updated 1748144985649 --- ## Is there a third party (freeware) program to convert my videos with? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/is-there-a-third-party-freeware-program-to-convert-my-videos-with Chapter: Noldus Knowledge Base One option is WinFF:Download WinFFAnother free option is Handbrake. When using Handbrake, on the Summary tab, set the format to MP4. On the Video tab, set the codec to H.264, the frame rate to “same as source” and pick the option for “Constant Framerate”. The filename should have the extension .mp4 (not .m4v).Download Handbrake View original HubSpot article · HubSpot article 190556076899 · Knowledge Base 187958790447 · Language en · Updated 1748145054656 --- ## Is there a way to bulk‑rename exported data files by appending a custom label to each file name? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/is-there-a-way-to-bulkrename-exported-data-files-by-appending-a-custom-label-to-each-file-name Chapter: Noldus Knowledge Base FAQ and Step-by-Step Instructions How can I bulk‑rename exported data files in EthoVision XT? There is no built‑in bulk‑rename feature. However, you can: - Add independent variables in the Trial List (e.g., ‘Group’, ‘Phase’). - Assign the desired labels to each trial before exporting. - When you export data, these variables are appended to the file names, effectively labelling each file without manual renaming. - Planning these variables ahead of time is essential because file names cannot be changed automatically after export. Can exported statistical data include detection settings information? No. EthoVision XT does not include detection settings in Excel or CSV exports. To document which detection settings were used: - Save the detection settings profile as a separate file through the detection settings interface. - Alternatively, note down the settings (e.g., frame rate, tracking method, thresholds) in your analysis log. - Store these records with your exported data so you can reference them during analysis. How can I distinguish nose or head over a hole versus full nest box entry in Barnes maze experiments? To differentiate between partial and full entries: - Enable nose‑tail detection so EthoVision XT tracks both the nose and body points. - Define two zones: one small zone covering the hole entrance for nose‑point entries, and another larger zone representing the nest box. - Use variables such as ‘head directed to zone’ or Trial Control transitions to record when the nose enters the hole versus when all three body points enter. Compare these events to see if the animal is investigating or entering. - You can also create separate analysis profiles: one that counts nose entries only, and another that counts full body entries. Hidden zones may help if tracking is difficult. Is there any other way to manage file naming or detection metadata? - Beyond the independent variables workaround, EthoVision XT currently doesn’t support appending custom metadata to file names or including detection settings in exports. Consider keeping a structured notebook or spreadsheet to track these details alongside your exported files. View original HubSpot article · HubSpot article 194772883847 · Knowledge Base 187958790447 · Language en · Updated 1755631796870 --- ## Making screen captures in Windows URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/making-screen-captures-in-windows Chapter: Noldus Knowledge Base Windows provides multiple means to capture images from the screen, either using the Printscreen key or the snipping tool or snip & sketch. Some Noldus software also provides options to save images of your settings or of graphs. Printscreen key (any Windows version) You can copy the contents of the screen to the clipboard by using the Printscreen key, located in the upper right (and typically labeled “PrtScr”). Press the Printscreen key to copy the contents of the screen to the clipboard. Hold down the Alt key when pressing the Printscreen key to copy just the contents of the selected window. Once the image is in the clipboard, you can paste it into other applications, e.g. into Word or PowerPoint. Large images pasted directly into emails may be automatically scaled down, so that is not always effective. You can also use Windows’ Paint. Just go to the start menu and type Paint, select it, and the press ctrl-v to paste the image, then save it. The Snipping Tool (Windows 7, 8, 10) Starting in Windows 7, Windows includes the snipping tool which allows you to capture any section of the screen, annotate it, and save it as an image. Go to the start menu and type “snip” and you’ll see the snipping tool listed. In Windows 10, you’ll also see Snip & Sketch which later replaceed the snipping tool. Click the snipping tool, then click the New button. It will prompt you to click and drag the area you want to snip. The selected area will then appear in the snipping tool where you can add annotations or save it. Snip & Sketch (Windows 10) You can open Snip & Sketch from the start menu (just open the start menu and type "snip" and you'll see it listed), in which case click New to select the area to snip. But you can also skip that step by holding down the Windows logo key and the shift key and pressing the S key (Windows logo key + Shift + S). A tiny menu will appear at the top of the screen to let you choose the shape of the area, but if you ignore it and just click and drag, you will select a rectangular area. After selecting the area, a popup notification will appear in the bottom right corner of the screen. You can now either paste the snip into any document, or click the popup to open the Snip & Sketch tool where you can add annotations or click the disk icon to save it as an image. Noldus software In most software which displays graphs of analysis results, right-click the graph to save the image or copy it to the clipboard. See the documentation for your software for more details. In EthoVision, in the Arena Settings, Trial Control Settings, and Data Profile, look for the camera icon at the top. Click it to save an image of those settings.  This also applies to The Observer in the Data Profile and Visualization. View original HubSpot article · HubSpot article 190278679460 · Knowledge Base 187958790447 · Language en · Updated 1747546342383 --- ## MediaRecorder 6.5.8847 Installation Instructions URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/mediarecorder-658847-installation-instructions Chapter: Noldus Knowledge Base Upgrade notes View Current version: MediaRecorder 6.5.8847 Please note the following important points: - New camera drivers may be available. We recommend to uninstall the old drivers before you install the new ones. Download the drivers we supply on Other downloads tab, since these were tested with MediaRecorder 6.5. Do not download them from the camera manufacturer. - New firmware for the cameras may be available. Check this at the website of the camera manufacturer. We recommend to use the latest firmware. - After upgrading to MediaRecorder 6.5, new settings should be made for the cameras. - The video files that were made with Media Recorder 2.0, or 1.0 were stored in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. Also after upgrading, the videos are stored in this folder. However, if MediaRecorder 6.5 is installed on a computer that did not contain a previous MediaRecorder version, the video files are stored in the folder C:\Users\Public\PublicDocuments\Noldus\MediaRecorder\Video Files. This location can be changed in the main MediaRecorder window. - If you have a previous version of MediaRecorder on a computer with another operating system than the 64-bit versions of Windows 7 or 10, you should either upgrade Windows, or install MediaRecorder on a computer with one of these operating systems. New device MediaRecorder now supports the Basler acA1920-155um professional USB camera. Procedure - Carefully read the above notes, and take a look at the what's new section of the Help. - Download and install the MediaRecorder 6.5 installation file. You can find this file in the 'Version' tab. - Download the MediaRecorder 6.5 Help in the 'Documentation' tab. Read the section Upgrade to MediaRecorder 6.5 for instructions. - Optionally, download and install the new drivers for the cameras and other hardware that you are using on the 'Drivers & Tools' tab. Please only use drivers from this website, as only that version has been tested with MediaRecorder. Find more information on how to upgrade your license in this knowledge base article:  https://my.noldus.com/shared/knowledge-base/answer/282  View original HubSpot article · HubSpot article 193222114204 · Knowledge Base 187958790447 · Language en · Updated 1753289655294 --- ## MediaRecorder will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/mediarecorder-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: Noldus Knowledge Base   This error in the installation log file indicates one of the following issues. You do not have the necessary rights to install software Your account does not have the required administrative rights to install software. Check that you do have administrative rights, or log into the computer using an account which does. Depending on how your systems are configured, you might require the assistance of your local IT department for installing software. Windows is currently updating Windows is in the process of installing updates, and the FaceReader installation cannot begin until it is finished. Complete any system updates and try again. Reboot PC after Windows updates complete to ensure no updates are pending. There is a problem with system files Malware or a computer virus has modified system files. Run a scan of the system. View original HubSpot article · HubSpot article 190573052020 · Knowledge Base 187958790447 · Language en · Updated 1748128023026 --- ## Missing data in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/missing-data-in-ethovision-xt Chapter: Noldus Knowledge Base When the video, camera, or detection settings are not optimal, you may encounter gaps in EthoVision data. Indications of missing data will appear as: - High values for missed samples, interpolated samples, or subject not found. - Gaps in the graphs shown in the integrated visualization. - Gray segments in the track visualization. - Total time spent in the arena may be less than the duration of the trial. - Dashes or asterisks appear in the sample list in the track editor. It's always best to identify the underlying cause so it can be addressed. Missed Samples, Interpolated Samples, and Subject Not Found Counts of these three types of missing data appear at the bottom of the screen in the Detection Settings and Acquisition. Values will appear in red if they are very high (as shown for Subject Not Found here). You can also check them after the fact in the Trial List by clicking Show/Hide in the upper right corner, then pick Variables, and check their respective checkboxes. Missed Samples A missed sample indicates that EthoVision was unable to analyze a given frame from the video.  Tracking live When tracking live, a missed sample often indicates the camera did not provide the expected number of frames. This can occur when there is a poor connection to the camera (e.g., any USB webcam, or a poor quality cable connecting a GigE camera). It can also occur if the Exposure setting is too high for the camera. If you are using a Basler camera, especially in dark conditions, please see Changing the exposure settings for Basler cameras. Missed samples can also occur during very difficult tracking tasks (especially multiple animals, color tracking, and behavior recognition) if the computer is unable to keep up. The following contribute to increased load: - Differencing as the detection method - Color marking as the detection method - Multiple animals per arena - Video pixel smoothing (in the detection settings) set to High. (Settings of low or medium are much less computationally intensive.) - Animals that are large relative to the image - High sample rates. For normal tracking of the nose, center, and tail, it's not necessary to exceed 25-30 samples per second. - Very high resolution video If tracking is too much for EthoVision to keep up with on your computer, you can use the "Save video and track later" option in the acquisition, then pick "Track next saved video file" to track afterwards. Tracking from video files If you are tracking from a video file, check that the DDS checkbox is checked (in the Acquisition, to the right side of the video controls). In this case, EthoVision will track the video at the fastest speed it is able, so there is never a concern about keeping up. With DDS checked, you will only see Missed Samples if the video itself has missing frames, or if the frame timing is erratic. This must be solved in the recording software. If your software (or video converter) has a setting for a fixed frame rate, it should be selected (not a variable frame rate). Interpolated Samples If you have enabled the Dropped Frames Correction (Missing Samples Interpolation) setting in the Detection Settings, when EthoVision encounters a Missed Sample, it will interpolate the results. This does not result in a gap, and is acceptable if the number of interpolated samples is low (<1%), but if the number of interpolated samples is high, it has the same underlying causes as Missed Samples and should be addressed the same way. Subject Not Found This indicates EthoVision was not able to locate the animal within the arena. Any Missed Sample will also result in Subject Not Found, so if you are seeing both, focus on the Missed Samples issues. If you see only Subject Not Found, either the animal was not visible in the arena (e.g., there is no animal, the animal escaped from the arena, or the animal is hidden for example inside a shelter) or the detection settings were not adequate to locate the animal. Adjust the detection settings accordingly. Smoothing and Interpolation If the number of missing data points is low, they can be addressed by either interpolating the missing points or by using track smoothing, which will also fill in short missing segments. Interpolating missing points To interpolate missing points, go to the Track Editor (found under Acquisition) and select the track to interpolate (in the upper left corner). You can either select the entire track (e.g. click the first data point in the sample list, then go to the end of the track and hold down the shift key while clicking the last data point) or use the Auto Select function. For the latter, click Auto Select, pick Missing Samples, then Select All. Once the data points have been selected by either means, click the "Interpolate Selection" button (with the + symbol) or press ctrl-i. Any missing data points will be interpolated based on the last and next known position of the animal. Note that points shown with an asterisk (*) are prior to the start of the track (before the start conditions in the trial control have been met) and cannot be interpolated. Also, because interpolation fills in data between the previous and next known location, it cannot be used at the very start of the trial (where there is no previous location) or at the very end (where there is no next known location). Interpolation must be done separately for each trial. You can undo the interpolation by returning to the track editor, selecting the track, and clicking the Undo All button. Track Smoothing Track Smoothing, which is found in the Track Smoothing Profile (also under Acquisition), averages each data point based on a number of points prior to and subsequent to that point (by default 10 points before and after). It will also fill in small gaps. Track smoothing has the advantage that it can be turned on with a single checkbox for all trials, and can be removed just as easily. To get a sense of the effect of smoothing, compare the trial visualization with and without smoothing. Redoing Trials If the number of missing data points is high, especially if it is due to poor detection settings, it may be preferable to redo the trial from the recorded video (if one was created). Please see Redo a trial in EthoVision XT for more details. View original HubSpot article · HubSpot article 190573052024 · Knowledge Base 187958790447 · Language en · Updated 1748128462137 --- ## Moving or Relocating the CatWalk XT Walkway URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/moving-or-relocating-the-catwalk-xt-walkway Chapter: Noldus Knowledge Base Your CatWalk XT system can be moved if necessary. Disconnect the cables between the walkway and computer. There are two such cables: a network cable from the PC to the camera, and a USB cable from the PC to the Control Unit. Take note of how the network cable is connected: on the PC it connects to the network card, which is normally labeled accordingly, not to the network port higher up near the USB ports. At the walkway end, the network cable goes directly to the camera; do not plug it into the control unit. If you are just moving the system down the hall, you can unlock the wheel casters and simply roll it to the new location. If it needs to be transported to a new facility, see below. Preparing the Walkway OEM packaging will not be necessary. It may be easiest to leave the CatWalk walkway assembled for the relocation, while taking special precautions for the more sensitive components (the glass plate, illuminated ceiling). Be sure to lock the wheel casters to prevent inadvertent movement. It is recommended to remove the camera and Control Unit device from the Walkway, in addition to the cable connections, to better safeguard the transport to the new room or facility. Documentation Please consult the available documentation in MyNoldus, including the Walkway Assembly Instructions, for further information. The assembly documentation shows how the camera and control unit are mounted. NoldusCare Warranty Please note, certain provisions in the NoldusCare Terms and Conditions will disqualify any and all hardware warranties should damage occur during packaging and/or transportation. This will result in needing to purchase replacement components that may become damaged during the moving process.   View original HubSpot article · HubSpot article 190573052248 · Knowledge Base 187958790447 · Language en · Updated 1748142023682 --- ## Moving or Relocating the PhenoTyper Home Cage URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/moving-or-relocating-the-phenotyper-home-cage Chapter: Noldus Knowledge Base How best to prepare the PhenoTyper home cage(s) for relocation depends on the scale of the move – just down the hall to another room, or to another facility possibly far distances apart. Preparing the PhenoTyper OEM packaging will not be necessary. It will be best to disassemble the cage(s) for relocation, while taking special precautions for the more sensitive components (Top Unit, pellet dispensers, lickometers, running wheels, etc.). Each PhenoTyper wall has two screws at the top, and the Top Unit and floor base rest on the top and bottom of the walls, respectively. We recommend taking pictures of all the various connections prior to disassembling the system to aide with the reassembly. Documentation Please consult the available Documentation in MyNoldus, including the PhenoTyper Reference and Service Manuals, for additional information, including assembly instructions. NoldusCare Warranty Please note, certain provisions in the NoldusCare Terms and Conditions will disqualify any and all hardware warranties should damage occur during packaging and/or transportation. This will result in needing to purchase replacement components that may become damaged during the moving process. View original HubSpot article · HubSpot article 190556076885 · Knowledge Base 187958790447 · Language en · Updated 1748142103225 --- ## Multiple error messages in The Observer XT when working from internal harddisk while no errors when working with fast external harddisk URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/multiple-error-messages-in-the-observer-xt-when-working-from-internal-harddisk-while-no-errors-when-working-with-fast-external-harddisk Chapter: Noldus Knowledge Base Especially when importing many datafiles (videos, external data) in can happen that multiple error message pop up. If it works on another HDD, that means there is a problem with the drive itself: ⦁    Check if there is free space enough As a rule of thumb take the size of a similar project including videos and take care that there is at least double the size free on the corresponding harddisk before you start a new project. Please note that mostly videos are the files that take up the most storage space.  ⦁    Check the drive for errors In Windows file explorer select the hard disk drive with a right mouseclick, go to "Properties" then the tab "Tools" then go to "Error checking" and "Check" ⦁    Check if the project folder does not contain unneeded things (do not  copy gb-s of video data to the project folder, that should be saved separately to the video folder) ⦁    Do not save project files on the Desktop! This is a kind of special folder in Windows, you should not store large datasets there. Files saved to desktops as are not as protected as documents you save in your libraries. For example, if you carry out a system restore, they'll be deleted; and that important file you needed is gone with no way of getting it back. ⦁    Do you have admin rights? Can problems be a user rights error? In Windows file explorer select the hard disk drive with a right mouseclick, go to "Properties" then the tab "Secutity" and check that System has all permissions and the user has the necessary permissions.   View original HubSpot article · HubSpot article 190573052219 · Knowledge Base 187958790447 · Language en · Updated 1748139570639 --- ## My camera image is black URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/my-camera-image-is-black Chapter: Noldus Knowledge Base Please ensure the aperture of your lens is sufficiently open (turn the adjustment ring marked "open-close" towards "open") and a light source is present. If nothing changes when turning the rings and the light is on, unscrew the lens to see whether there is any difference without a lens. When using analog cameras try one of the other inputs of your framegrabber board.If your camera has an IR-pass filter (which will look completely black), you also must have a source of IR illumination. View original HubSpot article · HubSpot article 190573052286 · Knowledge Base 187958790447 · Language en · Updated 1748145760644 --- ## My CatWalk XT experiment will not open as it reports that it was made with a previous (or newer) version of the software, but the same version was used. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/my-catwalk-xt-experiment-will-not-open-as-it-reports-that-it-was-made-with-a-previous-or-newer-version-of-the-software-but-the-same-version-was-used Chapter: Noldus Knowledge Base This issue results in the inability to open a CatWalk XT experiment, with a warning message that it was made with a newer version of the software, but the same version was previously used. It may also report an older version was used, but fail to convert the experiment to the new version. The error message may appear as shown:     Solution: the “version.dat” file in your experiment is corrupt and needs to be replaced.   This problem is easily solved, since the version.dat file is present in every experiment and contains no other experiment data. - Locate another experiment that is working. If you don't have any other experiments, open CatWalk XT and click “Create a new experiment” and create a dummy blank experiment. - Open that experiment’s folder location in the Windows File Explorer (C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments by default) - In that folder, right-click on the file “version.dat” and select “Copy”.   - Open the problematic experiment’s folder and right-click on the “version.dat” file, select “Rename” and rename the file “version.dat.old” (it will warn that it may be unusable, so just click “Ok”).  - Then, right-click in the blank space of the experiment’s folder and select “Paste” to paste the “version.dat” file from the working/new experiment.   After doing so, close the File Explorer and CatWalk XT (if open), re-open CatWalk XT and see if the issue is resolved for your problematic experiment. View original HubSpot article · HubSpot article 190573052183 · Knowledge Base 187958790447 · Language en · Updated 1748137234161 --- ## My color Basler camera is monochrome in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/my-color-basler-camera-is-monochrome-in-ethovision-xt Chapter: Noldus Knowledge Base Solution: Change the Color Space to YUY2 in EthoVision XT  In the Experiment Settings, click on theicon to get a live image and to open the Video Settings window.   In the Format tab of the Video Settings window, change the Color Space field to YUY2 and check the resulting live image to see if the issue is resolved.  NOTE The image will take a few seconds to update after making any changes. For experiments where a monochrome image is preferred, use Y800 as the color space instead. View original HubSpot article · HubSpot article 190573052041 · Knowledge Base 187958790447 · Language en · Updated 1748130405532 --- ## My image is too dark using a Basler camera URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/my-image-is-too-dark-using-a-basler-camera Chapter: Noldus Knowledge Base Solution # 1: Open the aperture on the lens more 1. Twist the aperture on the lens to “Open” until the image has the desired brightness in your Noldus software.    Solution # 2: Increase the gain and/or exposure in Pylon 1. Close your Noldus software (e.g., MediaRecorder or EthoVision XT) on the PC. 2. Start the Basler Pylon Viewer software that comes with the camera. It can normally be found as an icon on the desktop. Otherwise, look in the Start menu under Basler. - NOTE The Basler Pylon Viewer software is installed automatically when you install the camera drivers.  3. Choose Tools > Options and check that the User level is set to Expert or Guru.  4. In the Devices panel, double-click the item Basler under GigE or USB depending on the camera you have.  5. In the Features panel, open the Basler camera item and then double-click Analog Controls.  - NOTE If you do not see the Features panel, go to Window and make sure the Features option is checked  6. Increasing the gain: Under Analog Control, increase the Gain (Raw) up to 2. NOTE A higher gain setting will result in a brighter image, while a lower gain setting will result in a darker image. Very high settings may increase the noise or graininess of the image. 7. You can check the resulting changes by clicking the Continuous Shot button on the toolbar.  8. Increasing the exposure: Make sure Exposure Auto to set to Off.  9. Set Exposure Time (Abs) [us], enter the exposure time you require, in microseconds. Press Tab or click another field to confirm.  NOTE A higher exposure setting will result in a brighter image, while a lower exposure setting will result in a darker image. However, too-high exposure will result in dropped frames, and too-low exposure may result in an image that flickers or changes rapidly between light and dark.  For non-DanioVision set-ups, this value will typically vary between 8,000 and 25,000 depending on your lighting needs and your Gain setting in Pylon (more on Gain below).   IR lighting is the exception to the above. When tracking in IR with an NIR GigE camera, you may need an exposure setting around 30,000 in order to brighten up the image enough for tracking in EthoVision. For DanioVision setup, values should be 4000 (with a camera resolution of 1280x960) or 2000 (with a camera resolution of 640x480).  10. To check that any alterations in the gain or exposure is compatible with your frame rate, click the Continuous Shot button on the toolbar.  11. At the bottom of the live video window, locate the frame rate resulting with the new exposure time. This should be the same as the one next to Acquisition Frame Rate (Abs) [Hz]. (Noldus recommends 25 or 30)      12. If the resulting frame rate is lower than Acquisition Frame Rate (Abs) [Hz], then stop the Continuous Shot and either: a. lower the exposure time and adjust the Gain (Raw) instead (see #6 above), b. open the lens diaphragm to compensate for this (if not done already, see the beginning of this article), or  c. lower the video resolution.   This is under AOI Controls and can be reduced by lowering the Width and Height. This will help if the exposure is close to the limit, but not if the exposure is extremely high. -  NOTE Lowering the resolution will make the image look more “zoomed in”.  Also, make sure the Center X and Center Y are checked.     Repeat steps until you see the expected framerate. 13. Once finished with any gain or exposure alterations, stop the Continuous Shot and open the Configuration Sets item and:   a. select User Set 1 from the Configuration Set Selector, b. click Execute next to User Set Save (the camera settings set in the previous steps are now saved under User Set 1), c. select User Set 1 from the Default Startup Set list, d. close Pylon Viewer. - NOTE These settings will be used each time you start up your Noldus software.  TIP You can also save different settings for the same camera in User Set 2 and User Set 3. Under Default Startup Set (User Set Default), select which you want your Noldus software to use. View original HubSpot article · HubSpot article 190556076823 · Knowledge Base 187958790447 · Language en · Updated 1748128694310 --- ## My observation went on too long. How can I manually edit the stop time to lower it? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/my-observation-went-on-too-long-how-can-i-manually-edit-the-stop-time-to-lower-it Chapter: Noldus Knowledge Base You can not edit the stop time of your observation in The Observer XT. However, you can make an interval (in the Data Profile) from the start of your observation to a certain time or behavior in the observation to exclude the last part of the observation from being analyzed. View original HubSpot article · HubSpot article 190573052283 · Knowledge Base 187958790447 · Language en · Updated 1748145587638 --- ## My upgrade code is not recognized URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/my-upgrade-code-is-not-recognized Chapter: Noldus Knowledge Base Upgrade codes are issued for Noldus software using hardware license keys (dongles) when the software is to be updated to a new version or additional modules will be added. Upgrade codes are also used to change the expiration date of the license if you have a loan or rental (purchased software does not expire). If the upgrade key to upgrade your hardware license key (dongle) is not recognized, please check the following items. You will get a warning that you only have a limited number of tries left (although this count will reset the following day). If you do not get this warning, the code was recognized and you are done. Software Version Must Match Upgrade Code Upgrade code for hardware license keys (dongles) are created for specific versions of the software. For example, if you have an upgrade code for EthoVision XT 16, you must have EthoVision XT 16 installed and enter the code in that version. If your upgrade code is for The Observer XT 14.2, it must be entered in The Observer XT 14.2 and not 14.0 or any other version. Once the code has been entered, the hardware license key will also continue to work in older versions, but the code must be initially entered in the new version. So, please download and install the correct version of the software. If you do not see the correct version listed in the downloads section of this site (e.g., for very old versions), please contact Noldus support for assistance. Enter the Code Correctly If at all possible, copy-paste the upgrade code into the software to avoid typos. If you must type it (e.g., the computer is not connected to the internet), please note that the upgrade codes may contain the numerals zero and one but will not include the letters O, I, or L. Depending on the software, upgrade codes may be either 20 alphanumeric characters on a single line, or 20 characters on a first line and 4 additional characters on a second line. Enter the entire code. Check the License Number The upgrade window will show your current license number. If the upgrade code is for a new version of the software, it will not exactly match the new license number, because the first part of the license number reflects the version number. So, for example, if you are upgrading from EthoVision XT 15 to EthoVision XT 16, your current license number will be EV015-00000-AAAAAAAA where EV015 indicates EthoVision XT 15, while the new license number will start EV016 to reflect the new version. The letters at the end encode which optional modules are included in the license, which may also change. The only part of the license number that must match is the middle numeric part (e.g. -00000-). If the middle numeric part does not match, the upgrade code is for a different license key; when in doubt please contact Noldus support. In any case, you do not need to type the new license number, it will be automatically updated after your upgrade code has been entered. Additional Computers After an upgrade code has been entered successfully, the hardware license key stores the new license information. If you move the key to a different computer, you will not need to enter the upgrade code again. View original HubSpot article · HubSpot article 190556076871 · Knowledge Base 187958790447 · Language en · Updated 1748138725668 --- ## My video image is missing/black/white/grayed out in certain places in EthoVision XT (e.g., Arena Settings, Detection Settings, Acquisition, Track Editor, Manual Scoring, Integrated Visualizat URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/my-video-image-is-missingblackwhitegrayed-out-in-certain-places-in-ethovision-xt-eg-arena-settings-detection-settings-acquisition-track-editor-manual-scoring-integrated-visualization-etc Chapter: Noldus Knowledge Base This problem could arise due to the computer using the wrong graphics card (GPU) or an insufficient video driver installed for the GPU. The symptom may look like this:     Solution 1: Change the Graphics Settings on your PC. Directing Windows to use the appropriate graphics card (GPU) may resolve the problem. You can check and change these settings by going to the Start Menu and typing “Graphics Settings”. If you do not see “EthoVision XT” in the list of programs at the bottom, please click “Browse” and navigate to your “EthoVision.exe” file.   Note: If using EthoVision XT version 16 or newer, you will find your “EthoVision.exe” file in C:\Program Files\Noldus\EthoVision XT XX (XX = version number).  If using EthoVision XT version 15 or older, you will find your “EthoVision.exe” file in C:\Program Files (x86)\Noldus\EthoVision XT XX.   Once located, double-click on it to add it to your list.     Once added to your list (or if already there), click on it and select “Options”.     If set to “High performance”, then select “Let Windows decide” and then “Save”.     If set to “Let Windows decide”, then select “High performance” and then “Save”.   Once saved, close the “Graphic preferences” window, re-open your experiment in EthoVision and see if the issue is resolved. If the problem is not solved by choosing "High performance," also try "Power saving." In some cases it will give better results.   Solution 2: Change how your monitor is connected to your computer. This solution is only applicable to desktop computers. Your desktop computer may have ports to connect a monitor in more than one location. If a dedicated graphics card is installed, connecting the monitor to these other ports will bypass that card and use the inferior graphics adapter installed on the motherboard. So, use the ports in the area of the metal slots.   Solution 3: Update the graphics drivers on your computer. In some cases, after Windows has been updated (especially to Windows 10 from an earlier version), no graphics driver is present. Instead, the Microsoft Basic Display Adapter will be used. This is a generic driver included with Windows, but it does not have the required functionality for EthoVision. To see if you're using the Microsoft Basic Display Adapter, right-click the Start button (the Windows logo in the lower left corner of the screen) and pick Device Manager. Click the > symbol next to Display Adapters to expand it. Your computer may have one or two items listed here. If either of them is the "Microsoft Basic Display Adapter", it will need to be replaced with a suitable driver. In some cases you can right-click the display adapter and pick Update Driver; in other cases you may need to visit the website of the manufacturer. For assistance, contact Noldus Support.   View original HubSpot article · HubSpot article 190573052264 · Knowledge Base 187958790447 · Language en · Updated 1748143451677 --- ## No Valid Hardware Key Detected After Installing Noldus Software URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/no-valid-hardware-key-detected-after-installing-noldus-software Chapter: Noldus Knowledge Base Most Noldus software requires a license to operate (e.g., The Observer) or to make all functionality available (e.g., acquisition in EthoVision). A hardware license key (or "dongle") is a USB device that contains the license information. Although it resembles a USB drive, it does not store any files, only the license information. Starting with The Observer XT 16, EthoVision XT 17, Media Recorder 6, and FaceReader 9, your license may be a software-based license with an activation code. In this case, you do not have or need a hardware license key; use the activation code options instead. If you are using a hardware license key and it is not detected, see below. Multiple Noldus Software Licenses If you have access to different Noldus Software licenses (ex: FaceReader, Observer XT, and MediaRecorder), please verify that you have the correct license key plugged in that corresponds to the software you want to access. Each license is specific to only one software package and cannot be used interchangeably. For example, you will have separate license keys for Media Recorder and The Observer, these do not use the same key. You can plug all of these keys into the computer at once. License Key Driver  Seeing a message "No hardware key detected" after installing Noldus software and plugging in the key indicates there was a problem during the installation of the drivers for the license key. It could arise for a variety of reasons, but typically, reinstalling the drivers solves the issue. If the drivers are not functioning, you may also see that the key blinks red when plugged in, but then turns off shortly thereafter. When properly detected, the red light should remain lit. Upgrading the drivers may also be necessary if you are using older versions of our software with Windows 10 or 11. Changes in Windows invalidated the drivers installed with older software. This driver will normally work to resolve both of the issues above: HASP 8.13 Run or double-click the downloaded file to install the driver. If the key is still not detected after installing the driver, please contact Noldus Technical Support. View original HubSpot article · HubSpot article 190573052051 · Knowledge Base 187958790447 · Language en · Updated 1748131122667 --- ## No vocalizations are seen in the UltraVox XT spectrogram URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/no-vocalizations-are-seen-in-the-ultravox-xt-spectrogram Chapter: Noldus Knowledge Base One simple explanation is that the subject did not make vocalizations. However, it may be that the signal is so noisy that the calls do not emerge in the spectrogram. The colors displayed in the spectrogram for one event also depend on the amplitude of the signal in the surrounding interval. The same call may appear or not (or appear less evident) if another, unwanted signal like strong noise (for example, a door being closed) or constant noise from electrical appliances occurs in the interval displayed. To find out whether there is constant noise in the signal - Under View, select Spectrum. - Look at peaks in the spectrum. If necessary, zoom in the spectrum.  Examples: With strong noise at 60 Hz, zoom in the left part of the spectrum.   In another example, after filtering at 20000 Hz, two peaks are visible at 32kHz and 47 kHz.   View original HubSpot article · HubSpot article 190573052256 · Knowledge Base 187958790447 · Language en · Updated 1748142931647 --- ## Noldus software download links URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/noldus-software-download-links Chapter: Noldus Knowledge Base Direct link for downloading the latest version of Noldus software when myNoldus account does now work, By following the links, you can successfully install the software on your Windows PC. - Click the link below to download EthoVision 19:    https://noldus.sharefile.eu/public/share/web-se602fb5062464f0aa4f99d5afbea9fcc This is a zip file and will need to be extracted before installation. Right-click the downloaded file and pick Extract All and save all the files on local computer. In the extracted folder, double-click and Run EthoVision XT - Setup - 19.0.1914. Follow the instructions on your screen. - Click the link below to download EthoVision 18: https://noldus.sharefile.eu/public/share/web-s05a45dd9ddd74dd2bd94eab6fd31675f. This is a zip file and will need to be extracted before installation. Right-click the downloaded file and pick Extract All. In the extracted folder, double-click the file "EthoVision XT - Setup - 18.0.1832.exe" and follow the prompts. - Click the link below to download CatWalk 10.7: https://noldus.sharefile.eu/public/share/web-s801b8b65e49248229503d69c437d7ea7. - Click the link below to download FaceReader 10: https://noldus.sharefile.eu/public/share/web-se253b586f8a94f4aab7d16d0cb912767. - Click the link below to download MediaRecorder 6.5: https://cdn.noldus.com/download/share/software-mediarecorder/0VuIBnkomIZphWqTqmZMko8xROLg6j/MTc1MzkwNjY3Mw%3D%3D - Click the link below to download The Observer XT 17: https://noldus.sharefile.eu/public/share/web-s5a0f01d93d4248f9a701ae2607ba6dbb. View original HubSpot article · HubSpot article 192775752023 · Knowledge Base 187958790447 · Language en · Updated 1783615051509 --- ## Our Basler camera used to give 25 frames per second but now only gives 3.75 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/our-basler-camera-used-to-give-25-frames-per-second-but-now-only-gives-375 Chapter: Noldus Knowledge Base The frame rate may be reduced if: you have a poor connection to the camera (e.g., a bad cable).if the exposure is set too high. Please see Changing the exposure for Basler cameras.if Windows has replaced the Basler driver for the network card with the default driver for that card. Click here for more information. View original HubSpot article · HubSpot article 190573052277 · Knowledge Base 187958790447 · Language en · Updated 1748144901648 --- ## Paw prints are not recognized by the Automatic Footprint Classification Module in CatWalk XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/paw-prints-are-not-recognized-by-the-automatic-footprint-classification-module-in-catwalk-xt Chapter: Noldus Knowledge Base This may happen when a paw print has consistently a low Intensity, below the minimum set in the Classification Settings (which is 100 by default). Prints with very low intensity may indicate that the Detection Settings are not optimal for your animals. You will get more reliable data by adjusting the Detection Settings so the prints are reliably detected. Also, always allow the walkway lights to reach their full brightness before running any trials, which can take up to 15 minutes. Turning on the walkway at least 15 minutes before running your first trial prevents any issue here. Runs acquired immediately after turning on the walkway may be dim. However, for recordings you've already made, you can adjust the Classification Settings to better detect the dim prints. Go on the menu to Setup > Classification Settings. To the "Only assign a label..." option, reduce the value of minimum acceptable Max Intensity. Next, repeat automatic classification. View original HubSpot article · HubSpot article 190573052171 · Knowledge Base 187958790447 · Language en · Updated 1748136497657 --- ## Paw prints look incomplete in the Interactive Footprint Measurements screen in CatWalk XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/paw-prints-look-incomplete-in-the-interactive-footprint-measurements-screen-in-catwalk-xt Chapter: Noldus Knowledge Base When the footprint is shown in the Interactive Footprint Measurements screen, it is enlarged by means of smoothing and anti-aliasing algorithms (See the arrow in image 3 below). Pixels that are outside the border of the footprint rectangle, which contain no data by definition, are “translated” to blue pixels. This may result in effects like that in image 3, especially if the image resolution is low. To get more detail and reduce this effect, raise the camera closer to the walkway. Note that you will need to refocus the camera, define and calibrate the walkway, and redo the detection settings, so it's best to make this change at the beginning of a study. If most of the prints are good, but a few are cropped or lack detail, you can skip the prints that are insufficiently clear. They will be ignored in the analysis if you have not taken any measurements for them. In some cases it can be easier to see the print in actual color, rather than the false color image shown above in image 3. In the Interactive Footprint Measurements screen, right-click the Footprint image and select Switch to ‘Normal Color’ mode. You can switch back by right-clicking again and switch to False Color. View original HubSpot article · HubSpot article 190573052170 · Knowledge Base 187958790447 · Language en · Updated 1748136269656 --- ## Pellet Dispenser indicator light and error troubleshooting URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/pellet-dispenser-indicator-light-and-error-troubleshooting Chapter: Noldus Knowledge Base The Noldus pellet dispenser has an LED light which indicates the status and can be used to identify an error: - Connect power cable/RJ45 cable — single blink - Waiting for command — LED off - Receiving pellet drop command — Single blink - Dropping pellet — Single blink - Error state — Fast blinking - Reset — Double blink - Blocked — LED solid on Dispenser Empty An infrared photobeam detector senses whether a pellet is dropped after a “drop pellet” command has been given (either manually by pushing the blue button on the dispenser or with the USB-IO box and EthoVision XT). When no pellet is detected, the stepper motor moves the carousel within the silo one step further. If, even after a full rotation (15 steps), no falling pellet was detected, the system considers the silo to be empty. The pellet dispenser goes into error mode and the LED at the front of the pellet dispenser blinks continuously. Fill the silo with pellets and press the blue button at the front of the pellet dispenser to reset the device. It is then ready to be used again.  Not Empty, But No Pellet Dispenses If the pellet tube is blocked, the pellet dispenser will go through the same process as above, but pellets remain in the carousel. Remove the carousel (by lifting it off the base) and check whether it is blocked by dropping a pellet into the hole. If it does not come out of the dispenser, the path is blocked. Use a thin, flexible object (e.g., a twist tie or cable tie) to clear the tube. LED Light Stays On The LED indicator will remain on if the infrared photobeam detector sees something remaining in the path. This could be an obstruction as above. If clearing the path does not resolve the problem, the detector may be covered in dust. A pipe cleaner or a can of compressed air can be used to clear the tube. Using dustless pellets should prevent this problem from occurring. View original HubSpot article · HubSpot article 190573052206 · Knowledge Base 187958790447 · Language en · Updated 1748138904633 --- ## Picking the right sample rate in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/picking-the-right-sample-rate-in-ethovision-xt Chapter: Noldus Knowledge Base EthoVision allows you to set both a camera frame rate and a sampling rate: - The camera’s frame rate is set in the Experiment Settings or in step 1 (video sources) if you are creating a new template experiment. In either case, you can check it in the Experiment Settings. The frame rate controls how many video frames will be in the recorded video file. - The sampling rate determines how frequently EthoVision will analyze the video to determine the coordinates of the animal and other parameters. Camera Frame Rate For most purposes, it’s appropriate to set the camera at standard video frame rates. For European video, this is 25 frames per second (fps). For American video, it’s 30 frames per second. Normally, either 25 or 30 fps will work properly regardless of where you are, but in some cases if you have fluorescent lighting the video will appear to flicker if you do not pick the frame rate corresponding to your electrical system. This is because fluorescent lighting is actually blinking at the frequency of your electrical system (50 Hz for Europe, 60 Hz for the US), and it’s better to record video at a matching rate. If you are looking at very fast behaviors, e.g. startle or escape responses in fish, it may be desirable to record at a higher frame rate. The Basler acA1300-60 cameras we typically use support a frame rate as high as 60 fps. You may need to reduce the resolution when using an elevated frame rate. Be sure to check the Missed Samples and (if shown) Interpolated Samples in the Detection Settings and Acquisition. If these are greater than 1%, your system will not be able to track at this speed, but you may be able to select the “save video only and track later” option in the Acquisition. As with other settings in the Experiment Settings, the camera frame rate cannot be changed in an experiment once you have started acquiring data. Sample Rate The sample rate determines how frequently EthoVision will analyze the video. The sample rate can be lower than the frame rate, but it can never be higher – you can’t analyze video frames that don’t exist. Sample Rate is specified in the Detection Settings (if it’s not shown, click Video in the upper right); you will also be prompted to select the sample rate if you set up a new template experiment. The options for the sample rate will be limited based on your camera frame rate. If the camera frame rate is 25 fps, the sample rate options will be 25 samples/sec (every video frame), 12.5 samples/sec (every other video frame), 8.333 samples/sect (every third video frame), etc. We normally recommend: - If tracking just the center point of the animal, the sample rate should be 5-8 samples/sec for rats or 10-15 samples/sec for mice. - If tracking the nose and tail in addition to the center point, the sample rate should be 25-30 samples/sec. The additional detail improves the accuracy. This is required when using the Mouse or Rat Behavior Recognition Module. - Zebrafish: 5-6 samples/sec for adults, 30 or 60 samples/sec for larvae. These settings work well to capture the movement of the animals, without picking up too much noise or wobble which would slightly exaggerate distance moved and other measures, as shown here: If you are looking at Activity and/or Mobility, EthoVision is measuring the amount of change from one sample to the next. The longer the sample, the more change; the shorter the sample, the less change. In some cases picking a high sample rate will make it harder to detect events of interest because there’s simply not enough movement from one sample to the next. Because the sample rate is set in the detection settings, and you can create multiple detection within the same experiment, it is possible to change the sample rate by creating a new detection settings profile. However, data recorded at different sample rates may not be directly comparable and it is not recommended to do so. View original HubSpot article · HubSpot article 190573052058 · Knowledge Base 187958790447 · Language en · Updated 1748131585728 --- ## Play a tone as a stimulus from the EthoVision XT trial control URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/play-a-tone-as-a-stimulus-from-the-ethovision-xt-trial-control Chapter: Noldus Knowledge Base Play a tone as a stimulus from EthoVision XT In general, there are two approaches for creating a sound stimulus during an EthoVision trial. You can either use a sound-producing device that takes a TTL input or you can play a tone over the computer speaker. The latter is only a good choice when there is only a single arena or when sound presentation will be synchronized across all the arenas. Also note when using a computer tone that the volume level will depend on the volume set on the computer, and any other sounds produced by the computer will also be audible on the same speaker. If you are using a PhenoTyper, there is a built-in tone stimulus which can be used instead. Use a TTL device To set up a TTL-controlled sound stimulus, you'll need the Trial & Hardware Control Module and either the USB I/O Box or Mini USB I/O Box. You'll also need a suitable cable to go from the RJ45 connectors on the I/O box to the input on your TTL device. As every device is different, consult Noldus technical support if you need assistance with this, or would like to purchase a cable. In the Experiment Settings of your experiment, check the box for "Use of trial control hardware" (note: if this option is not shown, you do not have the Trial & Hardware Control Module) and then click the Settings button next to it. Select the USB I/O Box or Mini USB I/O Box depending on which device you have. For the TTL port that is connected to your sound device, set the device type to "Custom Hardware." In the Arena Settings, click the Arena-Hardware Mapping button in the lower right corner of the screen. If you have a single arena, each device should show up on its own line. If it's not listed, click the Add Device button to add it. Make sure the device is listed in the column for Arena 1. The Device Name shown here is how it will be displayed in the Trial Control Settings. If you have multiple arenas, each type of device should have its own line. So for example you would have one line for a Tone device, with the individual devices selected in the column for each arena. The Device Name shown here is how they will be displayed in the Trial Control Settings. You can test your device here. Select the device in the column for the appropriate arena, then click the Test button. Select "Output 1 High" and click Test to turn on a device on output 1, and "Output 1 Low" and Test to turn it off. "Output 2 High" and "Output 2 Low" will similarly control a device on the second output for a given TTL port (each TTL port on the I/O box has two outputs). In the Trial Control Settings, add a Hardware Action, select the device, and Output 1 (or 2) High to turn it on, or Output 1 (or 2) Low to turn it off. Insert these events into the trial control settings as appropriate. Use an external command To create a tone using an external command, you'll need these files to create the tone: Beep files Right-click the downloaded file and pick Extract All. Copy/move the three files it contains to this folder:  C:\Users\Public\Documents\Noldus\EthoVision XT (Note: you can use a different folder, but you'll need to edit the "beep.bat" file to specify the correct location in that case.) Edit the file "beep.ps1" if you want to change the frequency (the first number in the file, currently 1500 Hz) or the duration (the second number in the file, currently 1000 msec = 1 sec). Then in the EthoVision trial control settings, add an "External Command" action. Click the ... button, change the file type (in the lower right corner) from "Executables (*.exe)" to "Batch Files (*.bat; *.cmd)", and then select the beep.bat file wherever you put it. You can leave the "Command line options" box blank. In recent versions of EthoVision, you can use the Test button in that box to check that the sound is working.   View original HubSpot article · HubSpot article 190573052220 · Knowledge Base 187958790447 · Language en · Updated 1748139635905 --- ## Playback control buttons are grayed out in The Observer XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/playback-control-buttons-are-grayed-out-in-the-observer-xt Chapter: Noldus Knowledge Base If the video opens but the playback control buttons are greyed out and won't let you play, pause, etc. the video, deleting the customization files may resolve the issue. This will also resolve issues with hidden or missing toolbars, windows, and panels. Close the project and The Observer software, go to the location where the problematic project is located (by default, it is C:\Users\Public\Documents\Noldus\The Observer XT\Projects), find and open the problematic project's folder, and delete the .pos and .pob files in it.   Note that if the extensions (.pos, .pob, vop) are not displayed, in Windows 10 click View on the ribbon and check the checkbox for Show Extensions to see them. This ensures you do not delete the wrong file. Do not delete the .vop file! After that, close the project’s folder, re-open The Observer XT software/your project, and the issue should be resolved. View original HubSpot article · HubSpot article 190573052057 · Knowledge Base 187958790447 · Language en · Updated 1748131509670 --- ## Problems with the toolbar in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/problems-with-the-toolbar-in-ethovision-xt Chapter: Noldus Knowledge Base Problems with the toolbar in EthoVision If the toolbar (menu) is missing, located in the wrong place, or expected buttons are not available, you can reset the customization of these options in the experiment. This will also return the size and positions of all panels to their defaults. Other experiments on the same computer will not be affected. Simply delete the following two files in the experiment folder:  - positions.pos  - PositionsDock.pob View original HubSpot article · HubSpot article 190573052251 · Knowledge Base 187958790447 · Language en · Updated 1748142495647 --- ## Randomizing Events using EthoVision XT Trial Control URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/randomizing-events-using-ethovision-xt-trial-control Chapter: Noldus Knowledge Base EthoVision’s trial control settings allow you to plan out sequences of events during a trial, with specified delays and durations. But sometimes it’s better to vary the delays or sequences unpredictably. One option is simply to create multiple trial control settings profiles, and randomly assign them per trial. This keeps the trial control settings simple and has the advantage that trials with the same order of presentation can be grouped or labeled in the analysis results. However, it’s also possible to vary both the timing and sequences of events within a single trial control settings profile. Random Durations The easiest way to add random variability is by varying the time between different events. Just as you can use a Time condition to add a delay of a fixed duration, you can specify a random duration: Random Events and Sequences If you want to randomly select between different events, e.g. selecting between two different stimuli, it is possible to do so using trial control variables. A variable just stores a numeric value. There is a trial control variable action which you can use to assign a random value to such a variable. Likewise there is a trial control variable condition which you could use to choose between two different paths. (You also have to create the variable. To do so, click the “TC Variables…” button in the settings for any trial control element that uses variables, then click Add and give it a name.) Variables can be used as counters but here we will use one to make a randomized choice. Here's an example of a trial control sub-rule which randomly selects between presenting a noise stimulus (the upper path) and a tone stimulus (the lower path), and then afterwards waits for 5-30 seconds (after which the sub-rule could be made to repeat): The first Action box (“Randomize”) assigns a random value between 0 and 10 to a trial control variable named “Choice.” We then have arrows going to two different conditions in order to pick which events should occur. Two important things to note here: - When you split paths (with diverging arrows), the events on both paths will happen. So, if you only want to pick one of them, there needs to be a condition on each path such that only one condition is true. And it’s important that you don’t ever have a circumstance where neither will ever become true, because EthoVision will potentially wait forever in that case. (It’s ok if neither is true yet if you are waiting for something to happen, e.g. a certain amount of time to pass or the animal to enter a certain zone.) - When the arrows converge again, you need an Operator. This specifies whether EthoVision should wait until A) Any input is true (as here), B) All of the inputs are true, or C) X number of the inputs are true. Random Events and Counting In many cases, although the order of presentation should be randomized, the total number of presentations should be fixed. In this case, we want to make a random selection, but also keep a count of how many times each stimulus was presented. If we’ve reached the maximum number for the selected stimulus, we’ll switch to the other stimulus instead. Here’s an example, using the same random selection of noise vs tone from above, but limiting each to a maximum of 5 presentations. Two additional variables have been created, ToneCount to count the number of tone stimuli and NoiseCount to count the number of noise stimuli: In order to present each stimulus 5 times, the sub-rule should be called to execute the sub-rule a total of 10 times. Five will be tone and five will be noise, but the order will be random. Here’s the remaining part of the trial control settings, which in this example waits 60 seconds and then calls the sub-rule 10 times: View original HubSpot article · HubSpot article 190573052176 · Knowledge Base 187958790447 · Language en · Updated 1748136874643 --- ## Re-use of subject names in TrackLab URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/re-use-of-subject-names-in-tracklab Chapter: Noldus Knowledge Base Typically, in successive sessions, the names of the same subjects are assigned to the same tags. TrackLab easily supports this by the ‘re-use subject names’ option (to the right side of the subject variables list). It is good practice to assign the correct subject names to the tags in the first session and select the re-use option, before starting the next sessions. In the next sessions, tags get assigned to the same subject names as in the previous session(s). For new tags IDs, a subject name remains equal to the assigned tag MAC-ID and is therefore not renamed. View original HubSpot article · HubSpot article 190573052252 · Knowledge Base 187958790447 · Language en · Updated 1748142713675 --- ## Redo a trial in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/redo-a-trial-in-ethovision-xt-bBP Chapter: Noldus Knowledge Base EthoVision XT can be used to track in real-time but sometimes after the trial it will be apparent that the animal was not tracked well, the arena was miscalibrated, or for other reasons the track is not correct. If you recorded a video during the trial, you can retrack that video in the same experiment. Note 1: Retracking is not needed if you simply want to add or change zones for analysis. You can make those changes in the arena settings originally used to acquire the trial. What cannot be changed in the arena settings are the outline of the arena itself (since EthoVision ignored everything outside the arena), the calibration, and any zones used for trial control or hidden zones. Note 2: If the original trial includes imported hardware data collected via trial and hard control module, such as TTL signals, that hardware data is not preserved when you use Clear tracks but re-use the video or Clear tracks but re-use the video reference. If you need to improve tracking while keeping the original hardware data available, keep the original experiment unchanged and retrack the videos in a new experiment instead. 1. Clear and redo a trial If you were tracking live and recorded a video, to redo a trial, in the Acquisition on the right side under Redo Trial click the Select button: 2. Select the trial(s) to redo Pick the trial you want to redo, and pick the option “Clear tracks but re-use the video.” That will clear the track but keep the trial in the trial list with the video that was recorded. You can repeat this for as many trials as required. Note that if your experiment originally used video files rather than a camera, the option here will be "Clear tracks but re-use the video reference." This works the same way, allowing the video to be retracked. Alternatively for experiments working for video, you can simply delete the trial and track the video in a new trial. 3. Track saved video trials You’ll now be able to pick the “Track the next saved video trial” option in the Acquisition and retrack. But before doing so, go to the Trial List and make sure to select the correct detection settings and/or arena settings for that trial. When you do retrack, by default it uses the “DDS” or Detection Determines Speed setting which means that it will track as fast as it is able, which in many cases will be faster than real time. If you have many trials to redo, you can go through and select all of them to redo, then update the trial list to specify the correct detection settings to use for each trial, and then in the acquisition pick the option “Track all saved video trials” and it will run through the entire set one after the other without requiring your attention. Trials which have been cleared but not yet retracked will be marked with a status of "Postponed" in the trial list. This indicates that the trial exists but the track data has not been acquired yet (tracking has been postponed). Create a new experiment Alternatively, sometimes it is easier to simply make a new experiment and use the videos from the original experiment. In that case you can set up the arena settings and detection settings based on those existing videos. To easily create a new experiment with the same settings as the original, create a New Template Experiment, pick the Custom Template option, and select your original experiment as the template. This will copy all the settings but none of the data into the new experiment. Note that this will take a while if you have a lot of data in the original, as the original experiment is copied first and then the data is removed from the new copy. The videos will be available in the Media Files folder of the original experiment. The advantage of creating a new experiment is that you can use those videos when setting up your arena settings and detection settings. View original HubSpot article · HubSpot article 190573052034 · Knowledge Base 187958790447 · Language en · Updated 1775582523586 --- ## Reinstalling the Picolo Alert drivers for EthoVision URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/reinstalling-the-picolo-alert-drivers-for-ethovision Chapter: Noldus Knowledge Base The Picolo Alert is used as the framegrabber card for EthoVision XT 14 and up. This card has four round metal BNC ports directly on the back of the computer, with a small red block of tiny DIP switches next to input 1. The Picolo Diligent looks the same from the outside of the computer, but was used only in much older systems. If your system originally had EthoVision XT 8 or earlier, and was running an older 32-bit version of Windows, it would have had the Diligent, not the Alert, unless you upgraded the card when upgrading to EthoVision XT 14 or 15. The Picolo Diligent will not work with Windows 10 or any 64-bit version of Windows (other Picolo cards do work in these versions). If the card has one wide connector on the back of the computer, with a breakout cable splitting into 6 or 10 short (1’) black cables each with a round metal numbered BNC connector on the end, that is the Picolo U4 or U8, not the Picolo Alert. Reinstall the Picolo U4 or U8 Reinstall the Picolo Diligent When is reinstallation required? If your card is the Picolo Alert but it is not recognized by EthoVision, please follow the directions below to uninstall and reinstall the card. Do not install drivers for other Picolo cards (e.g. do not install the Picolo U4-U8 drivers as they will conflict). Note that this card may also cease operating if the computer has gone into Sleep or Standby mode. This can be resolved by simply shutting down the computer and then restarting it. The computer should be set so that it never goes into Sleep or Standby, and disable Fast Startup, to avoid this issue. If the card is recognized by EthoVision, but the image is all black or all white, the problem is more likely with the camera, cables, or connections. Check that the camera has power and is connected to the computer. Uninstall the Picolo Alert You’ll need to uninstall the card first if drivers were ever previously installed and are not currently working. Uninstall the driver from the Device Manager.  - In Windows 10, right-click the Windows logo in the lower left corner of the screen and then pick Device Manager.  - Click the triangle next to “Euresys capture devices” to expand it. Locate PICOLO Alert PCIe. Right-click on PICOLO Alert PCIe and select Uninstall.          - - If this item is missing from the Device Manager, you can proceed with the next step. Uninstall the driver from the programs list. - In Windows 10, click the Windows logo in the lower left corner of the screen, click the Settings gear, and then click Apps. - Pick Euresys Multicam x.x.x.x (where x.x.x.x is the version number of the drivers installed) and click the Remove button to uninstall.  - If other Euresys or Picolo drivers are installed, remove them too. Install the Picolo Alert - If you uninstalled the drivers as directed above, reboot the computer. - You'll need the file multicam-win10-6.15.1.3573.exe. If you have the installation USB stick for EthoVision, it can be found in the folder \Drivers and tools\Drivers\Euresys MultiCam. Otherwise, it can be downloaded here: Picolo Alert driver - Double-click the downloaded file to install the driver. - Open EthoVision and try it out. EthoVision should detect the card and, assuming you have a camera connected, should be able to get an image from it. If it offers the card as an option for live tracking but you get no image, the drivers and card are ok but there is an issue with the camera or the camera's connection with the card. In that case check the connections.   View original HubSpot article · HubSpot article 190573052088 · Knowledge Base 187958790447 · Language en · Updated 1748133857656 --- ## Reinstalling the Picolo U4 or U8 for EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/reinstalling-the-picolo-u4-or-u8-for-ethovision-xt Chapter: Noldus Knowledge Base The Picolo U4 H.264 and Picolo U8 H.264 were used as the framegrabber card for EthoVision XT versions 8-14 and continue to be supported in 15 (but not in EthoVision XT 16 or up). This card is usable in Windows 7, 8, and 10, including 32-bit and 64-bit versions. The Picolo U4 and U8 have one wide connector on the back of the computer, with a breakout cable that splits into 6 or 10 short (1’) black cables each with a round metal numbered BNC connector on the end. The U4 splits into 6 and the U8 splits into 10 connectors. If your card does not have a breakout cable, and instead has four round metal BNC connectors, it is either the Picolo Alert or Picolo Diligent. Do not use the drivers listed here, see the instructions for your card. Reinstall the Picolo Alert Reinstall the Picolo Diligent When is reinstallation required? If your card is the Picolo U4 or U8 but it is not recognized by EthoVision, please follow the directions below to uninstall and reinstall the card. These two cards use the same drivers, but do not install drivers for other Picolo cards (e.g. do not install the Multicam drivers as they will conflict). Note that this card may also cease operating if the computer has gone into Sleep or Standby mode. This can be resolved by simply shutting down the computer and then restarting it. The computer should be set so that it never goes into Sleep or Standby, and disable Fast Startup, to avoid this issue. If the card is recognized by EthoVision, but the image is all black or all white, the problem is more likely with the camera, cables, or connections. Check that the camera has power and is connected to the computer. Uninstall the Picolo U4 or U8 You’ll need to uninstall the card first if drivers were ever previously installed and are not currently working. It must be uninstalled from both the device manager and the programs list. Uninstall the driver from the Device Manager.  - In Windows 7: Go to the Start menu, select Control Panel, pick Hardware and Sound, then click Device Manager (under Devices and Printers).  - In Windows 10, right-click the Windows logo in the lower left corner of the screen and then pick Device Manager. - In either case, click the + next to Sound, video and game controllers to expand it. Locate PICOLO U4 (or U8) H.264 Device. Right-click on PICOLO U4 H.264 Device and select Uninstall.         - If this item is missing from the Device Manager, you can proceed with the next step. Uninstall the driver from the programs list. - In Windows 7, go to the Start menu, select Control Panel, then pick Uninstall a program. - In Windows 10, click the Windows logo in the lower left corner of the screen, click the Settings gear, and then click Apps. - In either case, locate Euresys Picolo U4-U8-U16 H.264 x.x.x.x (where x.x.x.x is the version number of the drivers installed) and click the Remove button to uninstall.  - If other Euresys or Picolo drivers are installed, remove them too. Install the Picolo U4 or U8 If you uninstalled the drivers as directed above, reboot the computer. If you’ve just installed the card for the first time, the computer should be just starting up. In either case, IGNORE the prompt to install new hardware (click Cancel). - You'll need the file picolo-u4-u8-u16-h264-win-2.5.0.139-ds-driver.exe. If you have the installation USB stick for EthoVision, it can be found in the folder \Drivers and tools\Drivers\Euresys. Otherwise, it can be downloaded here: Picolo U4-U8 driver - Double-click the downloaded file to install the driver. - Open EthoVision and try it out. EthoVision should detect the card and, assuming you have a camera connected, should be able to get an image from it. If it offers the card as an option for live tracking but you get no image, the drivers and card are ok but there is an issue with the camera or the camera's connection with the card. In that case check the connections. View original HubSpot article · HubSpot article 190271421085 · Knowledge Base 187958790447 · Language en · Updated 1747539520154 --- ## Replacement of Sewio hardware URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/replacement-of-sewio-hardware Chapter: Noldus Knowledge Base Every now and then Sewio hardware gets broken and a replacement needs to be provided for a customer. It is important to deliver replacement anchors and tags properly configured so that the customer has minimal effort to restore their system. Anchors Anchors come with the default configuration from the factory. It is important to adjust such settings to match the existing anchors before shipping the replacement to the customer. 1. The firmware of the replacement anchor should be the same as for the other anchors on the system. Below is an example of different anchor firmware. If that is the case update the firmware to the same version.     2. The anchor IP configuration should be the same as for the other anchors at the customer site. It should be either static or DHCP (to acquire an IP address from the DHCP server). In case the "Ethernet IP mode" is set to static please set it to the correct values for the fields "Ethernet IP", "Ethernet Network Mask" and "Ethernet Gateway IP Address".     3. Continuing the IP configuration of the anchor (scroll to the right). The fields "Reports Protocol", "RTLS Server IP Address", "RTLS Server Port", "Sync Server Port" and "TDMA Protocol" must be configured the same as at the customer site. 4. The anchor synchronization protocol should be the same as for the other anchors on the customer system.     5. The sync and blink channel and profile should match the other anchors on the customer system.       Tags 1. The blink channel and profile should match the settings of the anchors (and the settings of other tags). 2. The refresh rate should be the same as for other customers' tags. 3. Tag firmware should be the same as for other customer tags. 4. Tag sleep settings should match the settings of the other customer tags. We recommend the following sleep mode settings.  5. Tag button settings should match the settings of existing tags. 6. The same sensors on the tag should be enabled as for any existing tags in the system. The easiest way is to configure tag(s) using NFC. It is also possible to do that wirelessly but for that, a working RTLS system is needed.  View original HubSpot article · HubSpot article 190573052267 · Knowledge Base 187958790447 · Language en · Updated 1748143645652 --- ## Resizer error when trying to open a video in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/resizer-error-when-trying-to-open-a-video-in-ethovision-xt Chapter: Noldus Knowledge Base Please go to the list of installed programs on your computer and look for the Noldus ResizerFilter. Select it and click Uninstall. Once it is removed look for EthoVision XT in that list, select it, and choose to repair. This will reinstall the filter. View original HubSpot article · HubSpot article 190573052290 · Knowledge Base 187958790447 · Language en · Updated 1748146091655 --- ## Retrieve log files from the Sewio PC URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/retrieve-log-files-from-the-sewio-pc Chapter: Noldus Knowledge Base To be able to diagnose the Sewio system in more detail, several log files are needed. They can be found on the following locations: - /var/log - /home/sewiortls/logs Note that the steps below assume the system is not integrated with a customer network. If it is, substitute correct IP addresses which reflect the customer setup.  - Open an command prompt on the TrackLab PC and execute the command ssh -o "StrictHostKeyChecking no" noldus@192.168.225.2 - Specify Noldus123 for the password and press ENTER - Execute the command zip -9 -r /home/noldus/var_log.zip /var/log/ -x /var/log/journal/\* - Execute the command zip -9 -r /home/noldus/sewio_log.zip /home/sewiortls/logs/ - Transfer both ZIP files to a Windows PC using FileZilla or WinSCP   View original HubSpot article · HubSpot article 190556076895 · Knowledge Base 187958790447 · Language en · Updated 1748143761676 --- ## RTLS Studio not storing location and/or sensor data URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/rtls-studio-not-storing-location-andor-sensor-data Chapter: Noldus Knowledge Base There are several possible scenarios which may result in RTLS Studio stopping the recording of location and/or sensor data. - The Sewio PC ran out of disk space (for the database) - RTLS Studio applications might not be running correctly - Storing of data was disabled for RTLS Server - Upper limits for database constraints have been reached Below the scenarios are worked out in (possible) solutions.   The Sewio PC ran out of disk space (for the database) Verify if there is enough free disk space for the system. This can be done through the following steps: - Open a web browser and go to http://192.168.225.2 - Login with username "sewiortls" and password "sensmap" - Go to the menu and then go to "RTLS Monitor" - - Scroll down to the section "Disk Partitions" - - Verify that there is still enough free disk space (>= 1GB) for "/dev/mapper/sewiortls--vg-root" (red encircled). If not, contact TrackLabSupport2ndLine@Noldus.NL   RTLS Studio applications might not be running correctly Verify that all RTLS Studio applications are running by taking next steps: - In "RTLS Monitor" scroll up to "Sewio Software" - Verify that all applications are "active, running" (red encircled). If not, try restarting the PC. If that didn't solve the problem contact TrackLabSupport2ndLine@Noldus.NL -   Storing of data was disabled for RTLS Server Storing of location and/or sensor data in the database can be enabled/disabled in RTLS Server. Verify it is enabled following next steps: - Go to "RTLS Manager" - In the menu on the left open the settings for "RTLS Server" - Go to "Position Data Output" - Verify that the setting "Store To Db" is enabled. If not, enabled it and press "APPLY AND RESTART RTLS SERVER". Wait for the confirmation message - - Verify that RTLS Studio is storing data again   Upper limits for database constraints have been reached RTLS Studio uses a MySQL database as storage backend. RTLS Studio doesn't do automatic house keeping, which means that the database eventually will run out of free space. This doesn't mean disk space, but rather it reached the upper limit for a constraint. Take the following steps to find out if this is the case: - Go to the menu and then go to "Backup/Restore" - - Go to "RTLS Database" - Verify that the values encircled in red are either smaller than 2147483647 (32-bits signed integer for the old database schema) or smaller than 263 (64-bits signed integer for the new database schema). In case of doubt, contact TrackLabSupport2ndLine@Noldus.NL - - If the values do match either specified upper boundary, press the corresponding button "EMPTY TABLE". Note 1: emptying the table will permanently remove all data in the table and cannot not be accessed anymore. This is however by far the fastest method to cleanup the table. Note 2: using the drop down function of the button allows to specify a time period for data that should be removed. However: - this leads to increased disk space usage - it also puts a lot of pressure on the database as the engine creates a backup of the entire table before removing the data - it can be extremely time consuming (e.g. multiple hours or days) - it could also lead to running in the scenario where there is not enough free disk space left which then would fail emptying the table and one might get stuck in the middle. View original HubSpot article · HubSpot article 190573052212 · Knowledge Base 187958790447 · Language en · Updated 1748139238884 --- ## RTLS Studio reports server time is out of sync with the browser time URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/rtls-studio-reports-server-time-is-out-of-sync-with-the-browser-time Chapter: Noldus Knowledge Base It is important that the system time between the TrackLab and Sewio PC are in sync. It they are not in sync, an error is shown in RTLS Manager that indicates this (see red arrow in the screenshot below). The panel can be found in RTLS Manager in "Summary" for the anchors. By default the TrackLab PC runs a NTP server that is enabled during installation of TrackLab. - Note 1: that it can be re-enabled by executing this Batch file: "\\nit-srv3\Applications\~ Noldus Products\TrackLab\Operations and Services Documentation\Scripts\Enable NTP Server.bat". This script will enable and start the NTP server as well as opening port 123 in the firewall to allow communication with the NTP server - Note 2: that whenever there are changes to settings for time, like time zone changes or enabling/disabling the automatic configuring of time (zone) the Batch script must be executed again The Sewio PC is pre-configured with a NTP client that automatically synchronizes with the NTP server on the TrackLab PC. Sometimes the synchronization gets lost. This can happen due to: - changes in the time (e.g. changes to time zone) - changes to the network configuration (of the customer) - Windows updates - misconfiguration (e.g. incorrect IP addresses configured) - changes to security policies, for example the firewall. Especially when integrating the system with a customer network sometimes can break the functionality because of mentioned reasons. The following steps need to be taken to ensure the time synchronization is working. Note that the steps below assume the system is not integrated with a customer network. If it is, substitute correct IP addresses which reflect the customer setup.   Ensure correct firewall settings are active If the "Public Profile" is assigned to the network card that is connecting to the Sewio network, certain features are automatically limited or prohibited. Like for example opening up the port for the NTP server in the firewall is allowed, but in reality the port is never opened. One must assign the "Private Profile" to the network card for communication to be possible. This can be done by following the next steps: - Open the PowerShell (Windows Start menu -> Powershell) - Type "Get-NetConnectionProfile" and press ENTER. An example of the result, this might be different in the actual setup - - Locate the section that holds the details for the network card that is connected to the Sewio network - Remember the network's name exactly as shown listed by the command ran at step 2 - Type the following command and press ENTER. Where "NetworkName" must be replaced with the actual network name: "Set-NetConnectionProfile -Name "NetworkName" -NetworkCategory Private"   Verify the NTP server is running on the TrackLab PC - Open a command prompt - Type the command netstat -an | find "123" and press ENTER - If the reply looks like the screenshot on the right, the NTP server is running - If the reply is empty, it means the NTP server is not running. Re-enable it by executing the Batch file mention earlier. Note that the executing must be done using administrator privileges, otherwise the script will fail   Verify the NTP client is running on the Sewio PC - Open a command prompt on the TrackLab PC - Type the command ssh -o "StrictHostKeyChecking no" noldus@192.168.225.2 and press ENTER - Specify Noldus123 as password and press ENTER - Specify the command sudo systemctl status systemd-timesyncd. The result should like something like in the screenshot below - If the status is "Not synchronized" or "Idle", execute the Batch file mentioned earlier on the TrackLab PC. It will open the required port in the firewall, just in case it was closed somehow - Now execute the command sudo systemctl restart systemd-timesyncd to force synchronize the NTP client - Execute again the command sudo systemctl status systemd-timesyncd. The result should now look like something in the screenshot in step 4 - If the status is still not something like "Synchronized to time server", set the time zone to match the time zone on the TrackLab PC. Execute the command sudo dpkg-reconfigure tzdata - Go through the menu using the arrow keys and press ENTER to select - After setting the time zone, check the current date/time of the Sewio PC. Execute the command date - If the returned time differs more than 1 minute, execute the command sudo date --set "2023-04-16 14:58:00". Note that actual values for date/time must be used! - Execute the command sudo hwclock --systohc to set the hardware clock to the current date/time - Now again execute the command sudo systemctl restart systemd-timesyncd to force synchronize the NTP client - Execute again the command sudo systemctl status systemd-timesyncd. The result should now look like something in the screenshot in step 4 - If the status is still not something like "Synchronized to time server", contact TrackLab 2nd line support View original HubSpot article · HubSpot article 190573052268 · Knowledge Base 187958790447 · Language en · Updated 1748143705653 --- ## Running out of free memory during acquisition in CatWalk XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/running-out-of-free-memory-during-acquisition-in-catwalk-xt Chapter: Noldus Knowledge Base During acquisition you may see this error message: This indicates there is insufficient free memory to record acquisition data. Possible issues include insufficient RAM memory in the PC, other applications running in the background, excessively long runs, a walkway that is not clean, too much camera noise, and opening the ceiling of the walkway. Rebooting the PC may be helpful in some cases. Solutions to these issues are listed below. Update CatWalk This issue should be resolved by updating to CatWalk XT 10.7, which is available here on MyNoldus. This is a free upgrade if you have CatWalk XT 10.0 or higher. Note that CatWalk XT 10.7 requires the control unit (look for a black box mounted on the CatWalk frame about knee-high, with the power cables plugged into it); if you have an older CatWalk without the control unit, CatWalk XT 10.0 is the newest version of the software that can be used. Contact Noldus if you would like to upgrade your hardware as well. The other items listed below may be helpful if you are not able to upgrade the software to 10.7. Add Memory (RAM) to the PC Windows 10 has gradually shifted the way it uses system memory, prioritizing speed of running processes over memory usage, and the shift to 64-bit applications has also increased memory usage. Consequently, computers that had sufficient RAM may not have enough if they are running Windows 10. We currently recommend 16 GB of RAM. Older computers are likely to have 8 GB or less. If acquisition is being canceled very early in the run, adding additional memory may be required. Note that what is required is RAM, not additional storage space. You will need to add memory (usually DIMMs), not a bigger hard drive. Close Other Applications Any other application running in the background will consume memory. Close any unneeded applications. Browsers are especially likely to use large amounts of memory. Reduce Run Length Longer runs require more memory, and generally do not generate useful data. Generally it should not be necessary to set the maximum run length longer than 10 seconds. With slower rats you may choose to extend it as high as 15 seconds. Clean the Walkway Accumulated dirt and prints on the walkway create noise which takes memory to record, and also reduces the quality of your data and the accuracy of auto classification, which means more work for you. It's recommended that after each trial (when switching from one animal to the next) you clean the walkway and then click the "Snap Background" button. You can clean the walkway with regular glass cleaners or with dilute ethanol. Reduce Noise Aside from a walkway that is not clean, you can get excessive noise (with the same issues as above) if the Camera Gain in the Detection Settings is greater than 20 or if the Green Noise Threshold is too low. If the Camera Gain is above 20, make sure the aperture on the lens is fully open and then check that the Camera Gain is appropriate. Increasing the Green Walkway Light setting can allow a lower Camera Gain. (Normal values for the Green Walkway Light are 16.0 V for rats, 16.5 V for mice, but you can increase it by small amounts to get a noticeable difference.) Set the Green Intensity Threshold to a level where you can clearly make out the prints but do not see noise elsewhere on the walkway. Keep the Ceiling Closed If the walkway ceiling is lifted during acquisition, the entire working area becomes dark and is detected as if it was a giant animal, which requires recording an excessive amount of spurious data. If it's necessary to lift the ceiling during a trial (e.g., because your animal has stopped in the middle of the walkway), click the Stop Acquisition button before lifting the ceiling. You can then start the trial again to acquire more runs if needed. Reboot the Computer Rebooting the computer regularly can free up memory as well. We recommend doing so daily. View original HubSpot article · HubSpot article 190556076872 · Knowledge Base 187958790447 · Language en · Updated 1748138842674 --- ## Selecting an Axis IP camera in FaceReader 6 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/selecting-an-axis-ip-camera-in-facereader-6 Chapter: Noldus Knowledge Base In your project, click the Camera Analysis button to add a new camera analysis. Fill in the settings as follows: - Select Camera: Select "IP Camera" from the drop down menu. - Source URL: See below. - Stream Type: click MJPEG. - Secured: Check the checkbox and fill in the username and password for the camera. For the source URL, insert the camera stream URL which will be: - http://xxx.xxx.xxx.xxx/axis-cgi/mjpg/video.cgi Replace xxx.xxx.xxx.xxx with the IP address of the camera. Noldus typically sets up the first camera as 192.168.200.1, the second camera as 192.168.200.2, etc. Once these settings have been filled in, the video will appear in the preview screen on the left. Check the checkbox for "Use as default camera" if you would like these settings to be used in the future. Click OK to proceed.     View original HubSpot article · HubSpot article 190556076827 · Knowledge Base 187958790447 · Language en · Updated 1748129219971 --- ## Selecting an Axis IP camera in FaceReader 7, 8, or 9 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/selecting-an-axis-ip-camera-in-facereader-7-8-or-9 Chapter: Noldus Knowledge Base To connect an Axis camera to FaceReader 7, 8, or 9: - In the Select Camera window, under Select Camera, choose IP Camera. - Under Source URL, enter the source URL of your camera. For cameras configured by Noldus, this will typically be 192.168.200.1 for the first camera, 192.168.200.2 for the second camera, etc. It should also be labeled on the camera itself. - For Axis IP cameras, enter one of the following (replacing the IP address with the same address from step 2): - http://IP address camera/mjpg/video.mjpg - http://IP address camera/axis-cgi/mjpg/video.cgi - Under Frame rate, select the frame rate (default: 5 fps).  - If your camera is password-protected, select Secured and enter the Username and the Password. - Select MJPEG. - Select Use as Default Camera if you want FaceReader to automatically select the current camera for future camera analyses. The camera view should appear in the Preview image window. View original HubSpot article · HubSpot article 190556076817 · Knowledge Base 187958790447 · Language en · Updated 1748127905738 --- ## Setting up the CatWalk XT 10 walkway: calibration and detection settings URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/setting-up-the-catwalk-xt-10-walkway-calibration-and-detection-settings Chapter: Noldus Knowledge Base Setting up the walkway for use is a three step process: defining the walkway, calibrating, and detection settings. These steps are not difficult but can make a big difference for the quality of data and how much work you will need to do in the classification, so it’s worth getting right. In addition to the initial set-up, you need to: - Define the walkway whenever the camera height or walkway wall positions are changed (e.g., to make a wider or narrower corridor). - Calibrate the walkway whenever the camera height is changed. - Adjust the Detection Settings whenever the lighting in the room is significantly changed, when the camera height is changed, or when switching between different groups of animals with significantly different weights. Defining the walkway This step tells CatWalk which part of the image to look at; it simply defines which part of the walkway is the working area. You will need to define the walkway any time you raise or lower the camera, or if you make the walkway wider or narrower. Go on the menu to Setup/Define Walkway. You will see the full area visible to the camera. Move and resize the white rectangle so that it outlines the working area for runs. During normal use you will only see this area. You may choose not to use the full length as seen by the camera, for example with rats you need to leave enough room at the two ends of the walkway so that when they turn around, their tail is not in the defined area. This is normally not an issue with mice as a smaller section of the walkway is used. In the image, you’ll see the bottom edge of the two corridor walls. The defined walkway should be just within those boundaries. Try to minimize the amount of the black bottom edge of those walls that is within the rectangle. Calibrate the walkway Calibration tells CatWalk the size of the image so that results can be reported in real units (cm) and not pixels. You’ll need to redo the calibration if you move the camera up or down. For the calibration, you will want a calibration sheet. You should have one, but there is also a printable calibration sheet in the manual or you can download it below. It has a rectangle which is 10x20 cm in size. Place it on the walkway, face down, so the rectangle is in view from the camera. Go on the menu to Setup/Calibrate Walkway. If the image is not in focus, adjust the focus on the camera lens. Move and resize the white rectangle on the screen to align with the rectangle on the calibration sheet. Click OK. The calibration is done. Download the printable calibration sheet, US letter sized. Download the printable calibration sheet, A4 sized. Make sure to print the calibration sheet exact size, not scaled!  Detection settings The final setup step is the Detection Settings. In this step, you will set the sensitivity (gain) of the camera so that prints can be detected and distinguished from noise. Redo the detection settings if the lighting is different in the room (e.g. due to different positioning of the computer monitor, different room size, amount of light coming under the door, etc), if the camera has been raised or lowered, or if you are working with significantly lighter or heavier animals. When setting up the detection settings, the room must be dark, with the same lighting you will use during trials. The ceiling on the walkway should be lowered. You will need at least one animal that is approximately the size and weight of your typical subjects. The walkway should be on for at least 15 minutes before you set the detection settings or perform trials (because the lights will gradually brighten during the first 15 minutes). Go on the menu to Setup/Detection Settings. When setting up from scratch, we recommend first using Auto Detection, then making fine adjustments manually. If your lighting is already very similar, you can also skip the Auto Detection. To use Auto Detection, click the Start Auto Detect button. Place your animal on the walkway and allow it to run across (with some encouragement if necessary). After the animal has moved across the image, CatWalk will adjust to recommended settings. In some cases it may require the animal to cross a few times before auto detection is complete. This will usually get you good settings, but you should still check them and you may be able to improve them further. When adjusting manually, your goal is that when the animal runs across the walkway, without stopping, the Maximum Green Intensity (shown in the center) should be in the range 200-205. You can click the Reset Prints button to clear these values to get another reading. If the animal stops in the middle, you will get a higher Maximum Green Intensity reading – don’t worry about that, just click Reset Prints and wait for the animal to cooperate. The reading you want is one in which the animal kept moving all the way across. You can repeat this as many times as necessary. If the Maximum Green Intensity is too high, lower the Camera Gain (this decreases the sensitivity of the camera). If the Maximum Green Intensity is too low, raise the Camera Gain (increasing the sensitivity of the camera). Then wait for the animal to make another run. Repeat until you feel confident you are in the range 200-205. If the Camera Gain is very high (>20), you may get a lot of noise. If you are using CatWalk XT 10.6 (but not earlier versions), you can increase the brightness of the walkway lights (the Green Walkway Light setting) which will allow you to use a lower Camera Gain. The default settings are 16.5 volts for mice and 16.0 for rats. Only small adjustments are needed here, adjust by 0.1 increments. After the Camera Gain is set, adjust the Green Intensity Threshold. A higher value will filter out more noise but if it’s too high, you will lose details around the paw prints. A lower value will get more of each print but if too low will pick up noise that is not part of the prints. Adjust this to remove other noise but still getting a clear image for each print. Then click OK, you are finished.   View original HubSpot article · HubSpot article 190556076841 · Knowledge Base 187958790447 · Language en · Updated 1748132143638 --- ## Some elements of the software appear too small or cropped when using Windows 10 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/some-elements-of-the-software-appear-too-small-or-cropped-when-using-windows-10 Chapter: Noldus Knowledge Base When using high DPI displays in Windows 10, some elements in our software may appear too small or may appear cropped so they cannot be seen clearly. This can be corrected by adjusting the properties of the application: - Right-click the shortcut icon of applications you want to adjust - Select ‘Properties’ (If the icon is in the taskbar, you will have to right-click the second app icon) - Select the ‘Compatibility‘ tab - Select ‘Change high DPI settings‘ at the bottom of the tab - Check ‘Override high DPI scaling behavior‘ at the bottom - Select ‘System (Enhanced)‘ from the drop down - Select ‘OK‘ and then ‘OK‘ again to apply - Launch the application to see the difference View original HubSpot article · HubSpot article 190556076845 · Knowledge Base 187958790447 · Language en · Updated 1748132987654 --- ## Subject renaming in TrackLab URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/subject-renaming-in-tracklab Chapter: Noldus Knowledge Base TrackLab records location data from your subjects by wearable tags. For example, a Sewio UWB tag that is attached to the collar or a cow. Each tag has its own MAC identification number. Inside the TrackLab Software in the Setup - Variables tab, on the SUBJECT-LEVEL page, you find an overview of the presented tags recorded within the selected session.   As seen in the picture in the second column, each tag has a subject name assigned. Initially, the subject names are equal to the tag-IDs. Now with TrackLab version 2.12, it is possible to replace these code names with more suitable subject names. These names are then used throughout TrackLab to identify the subjects.  In TrackLab, each subject name uniquely identifies a real recorded subject. Meaning that: - It is not allowed to assign the same subject name twice in the same session.  - The subject name used in several sessions represents the same subject. Even in case, the sessions belong to different recorded sites.  - Although not commonly used identical subjects can be used by several sites. However, the shown analysis results in TrackLab are always limited to one selected site.    Read how to rename your subjects HERE Read HERE how to re-use subject names.  Continue to this article to read when subject renaming fails.  View original HubSpot article · HubSpot article 190556076889 · Knowledge Base 187958790447 · Language en · Updated 1748142563645 --- ## Suddenly a problem with automatic Detection in Catwalk XT 10.6 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/suddenly-a-problem-with-automatic-detection-in-catwalk-xt-106 Chapter: Noldus Knowledge Base A customer suddenly encountered issues with automatic detection. Finally they discovered that the glass plate was pulled forward on one side of the Catwalk. This probably happened when they wanted to move the Catwalk stand and pulled the glass plate instead of pulling the stand itself! That caused the green light reaching the glass plate insufficiently and unevenly. Customer mentioned: 'This caught my eye because I noticed a difference between left and left in my run and the camera gain was quite high to detect paws.' Now that the glass plate is nicely slid back in, I can see the legs again very nicely. Concluding from this: please advise customers, not to pull the glass plate but instead, pull or push the Catwalk stand itself! View original HubSpot article · HubSpot article 190573052266 · Knowledge Base 187958790447 · Language en · Updated 1748143574042 --- ## Tags are shown at the wrong location in the tracking area, align at straight lines or not visible at all URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tags-are-shown-at-the-wrong-location-in-the-tracking-area-align-at-straight-lines-or-not-visible-at-all-MsP Chapter: Noldus Knowledge Base An example of anchors aligned at a straight line can be seen in the screenshot below:   - In Sensmap Visualization, check if all anchors are at their respective locations. Meaning that they should not be moved or swapped Note: also disconnected anchors are shown - In RTLS Manager/Anchors Summary, check if all anchors are listed and if the status shows they are online. Note 1: disconnected anchors are NOT shown. Match missing anchors with the anchors shown in Sensmap Visualization Note 2: due to a disconnected anchor, anchor restrictions might fail (Sensmap Visualization/RTLS/Anchor Restrictions). Meaning for example that the minimum required anchors to calculate a position might not be reached. A resulting symptom could be that in a specific cell no tags show up - Check the status panel. All should be showing green tick marks and "TDMA protocol" should be showing in green text - If any of the checks at point 1 to 3 failed, visually inspect the cables, connectors and the network switch (do all connector LED's blink as they should?) - Unplug and plug network cables for the anchors on the network switch - Wait 1 or 2 minutes for the anchors to come back up online - Check main points 1 to 3 again. If this did not solve the issue, continue with point 6 - Visually inspect the connectors at the anchor(s) that fails - Unplug and plug the network cable at the failing anchor(s) - Wait 1 or 2 minutes for the anchors to come back up online - Check main points 1 to 3 again. If this did not solve the issue, continue with point 8 - In RTLS Manager/Sync Stability, check in the graph if the values on the y-axis don't exceed a value of "1". In the slave-anchor list, check that there is no packet loss (the number of lost packets must not increase over time). If either NOT ok, proceed with trouble shooting. If this does not solve the problem, proceed as follows:   - Visually inspect the anchors, to see if the housing shows an LED lighting up. If indeed the case, proceed with trouble shooting. If the problem persists, proceed: - Visually inspect the anchors to see if they are misaligned (due to any impact, birds, etc) or if there were any new potentially blocking objects introduced in the tracking area. - If the above did not solve the problem, contact TrackLab 2nd line support This is an example of what a sound sync stability looks like: View original HubSpot article · HubSpot article 190573052187 · Knowledge Base 187958790447 · Language en · Updated 1748137495650 --- ## Taking Viso Locations On/Offline URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/taking-viso-locations-onoffline Chapter: Noldus Knowledge Base Taking a location on and offline can be a good solution if you experience any of the following problems or error messages: - Camera Configuration Problem - Configuration error - Connection with Viso Services lost error - Cannot open a location - Location is offline Here is the procedure:  - Log into Viso with a Technician-level account - Go to Locations and click on Edit Locations. - Expand the Computer Name where you want to take a Location on/offline. - Under the Select for Recording column, select/deselect the checkbox. Allow a minute between selections and select it again to bring the Location online again. - Open the Location and test the issue. . If the error/issue isn’t resolved, please recreate the Location. . If the Location is still Offline after the Location is recreated, antivirus software might be interfering with network traffic. Contact your local IT support to disable any antivirus software or, alternatively, allow an exception for Viso traffic. View original HubSpot article · HubSpot article 195690691628 · Knowledge Base 187958790447 · Language en · Updated 1757347694107 --- ## The Complete_Averages.csv export from FaceReader Online was misaligned URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-complete-averagescsv-export-from-facereader-online-was-misaligned Chapter: Noldus Knowledge Base User reported that the Complete_Averages.csv export from FaceReader Online was misaligned: episode names were scattered across rows instead of staying in the episode column. They needed a corrected data file for their project. Resolution – The misalignment occurs when episode names contain commas or hidden line breaks, which break the CSV structure. The recommended fix is to rename episodes using only letters, numbers, underscores or dashes (no commas or returns), then export the results again as an Excel file. The Excel export keeps the data aligned. If a CSV is still required, open the clean Excel file and save it as CSV or change your system’s list separator before exporting. FAQ and Step-by-Step Instructions Why is my FaceReader Online CSV export misaligned? - The Complete_Averages.csv file can become misaligned when episode names include commas or hidden line breaks. CSV files use commas to separate columns, so commas inside a name cause the episode label to shift into the next column. Hidden line breaks can push data into a new row. How can I fix the misaligned export data? Follow these steps: - In FaceReader Online, locate the episodes that have commas (,) or line breaks in their names. - Rename each episode to use only letters, numbers, underscores (_) or dashes (-). Avoid punctuation and returns. - After renaming, export your results as an Excel file (.xlsx) instead of CSV. The Excel format preserves the columns and keeps episode names in the correct column. - Open the Excel file to verify the data is aligned correctly. - If you still need a CSV, use Excel’s Save As function to save the clean file as .csv. Alternatively, change your system’s list separator to a different character (e.g., semicolon) before exporting to CSV again.   How do I rename episodes in FaceReader Online? - Log in to FaceReader Online and open the project containing your episodes. - Navigate to the episode list or timeline where episode names are defined. - Click on each episode name and edit the text. Remove any commas, line breaks or special characters. Replace spaces with underscores if needed. - Save your changes before exporting. What if I still encounter issues after renaming and exporting? - Make sure there are no hidden characters in the episode names. You can copy the names into a plain text editor to check. - Double‑check that you exported the results as Excel first and verified the alignment. - If problems persist, contact Noldus support with a sample of your data for further assistance. View original HubSpot article · HubSpot article 194772905001 · Knowledge Base 187958790447 · Language en · Updated 1755641141458 --- ## The Observer is not letting me create new projects, only new projects from templates URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-observer-is-not-letting-me-create-new-projects-only-new-projects-from-templates Chapter: Noldus Knowledge Base There are two types of licenses for The Observer: full licenses and coder licenses. Coder licenses are meant only for coding in existing projects; you can also use them to create a new project but only from a template you've already set up. A full license can be used to create new projects. So, if you can only create projects from templates, you have a coder license plugged in. Close The Observer, unplug the coder license, and plug in the full license if you would like to create a new project. View original HubSpot article · HubSpot article 190573052288 · Knowledge Base 187958790447 · Language en · Updated 1748145903647 --- ## The Observer will not install and the installation log file says Access Denied - 0x80070005 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-observer-will-not-install-and-the-installation-log-file-says-access-denied-0x80070005 Chapter: Noldus Knowledge Base   This error in the installation log file indicates one of the following issues. You do not have the necessary rights to install software Your account does not have the required administrative rights to install software. Check that you do have administrative rights, or log into the computer using an account which does. Depending on how your systems are configured, you might require the assistance of your local IT department for installing software. Windows is currently updating Windows is in the process of installing updates, and the FaceReader installation cannot begin until it is finished. Complete any system updates and try again. Reboot PC after Windows updates complete to ensure no updates are pending. There is a problem with system files Malware or a computer virus has modified system files. Run a scan of the system. View original HubSpot article · HubSpot article 190573052165 · Knowledge Base 187958790447 · Language en · Updated 1748134467869 --- ## The Observer XT Error Id 12524 – Event Log Read Failure URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-observer-xt-error-id-12524-event-log-read-failure Chapter: Noldus Knowledge Base The message "Event Log Read Failure" (Id 12524) indicates that the event log files cannot be found. These files are distinct from the project file (the .vop file) and if they have been separated from the rest of the project, this error will occur. Files missing or out of place A complete Observer XT project consists of a folder named for the project, containing a variety of files and subfolders. All of these together constitute the project:   (Note that file extensions (e.g. “.vop”) may be hidden by Windows, and the Restore.btn files will not appear in older versions of The Observer.) The observational data (the event logs) is not stored in the .vop file, it is stored in the Event Data folder, one file per event log. You should have the same number of files in that folder as you have observations. If you move the .vop file, The Observer will create the Event Files folder (and the other folders) but it has no way to recreate the data because it no longer knows where that data is located. When you open an observation created before that move, this results in the Event Log Read Failure error. To solve this, you must locate the original folder that contained the experiment, where the .vop file was located and with the Event Files folder containing the required data files. This folder must have existed at one time, but it may have not been copied and the .vop file was moved without it. Moving/transferring project files If you would like to move a project, move the entire project folder and all of its contents. If you would like to make a new copy, open the project and go to File > ‘Save Project As’ to make a new copy.  To take a project from one computer to another, make a backup of the project by going to File > Make Backup. This will save the entire project as a single file with a .vpb extension. Take that file to the other computer and use the ‘Restore Project’ function to open the project up on the other PC. Doing so will create all the necessary files and folders. Files renamed The name of the project folder, .vop file, and .pos file all match the name of the project. If these names do not match, you may get an error if you make a backup of the project and then try to restore it. View original HubSpot article · HubSpot article 190556076851 · Knowledge Base 187958790447 · Language en · Updated 1748134192649 --- ## The Observer XT will not install and the resulting Log file says Access Denied 0x80070005 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-observer-xt-will-not-install-and-the-resulting-log-file-says-access-denied-0x80070005 Chapter: Noldus Knowledge Base This issue involves a situation where the installation of The Observer XT on your computer fails and the resulting log file says “Error 0x80070005”. Log file says “Error 0x80070005” After installation fails, you may see this error in the log file:      Possible causes when getting this error: - Your account does not have the required administrative rights to install software. Check that you do have administrative rights, or log into the computer using an account which does. Depending on how your systems are configured, you might require the assistance of your local IT department for installing software. - Windows is in the process of installing updates. Complete any system updates and try again. Reboot PC after Windows updates complete. - Malware or a virus has modified system files. Run a scan of the system. - There is an issue installing Microsoft.NET. Try to download and manually install it separately. Then try installing the Noldus software again. View original HubSpot article · HubSpot article 190556076861 · Knowledge Base 187958790447 · Language en · Updated 1748137050291 --- ## The Sewio anchors have stopped operating URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-sewio-anchors-have-stopped-operating Chapter: Noldus Knowledge Base - Open the RTLS Manager we portal. If it is off-line, check if the Sewio PC is switched on and if the cable between the Sewio PC and TrackLab PC is correctly plugged in. If the problem persists: - In RTLS Manager/Anchors Summary, check if all anchors are listed, and if the status shows they are online. If an anchor is missing from the list, proceed with step 4. If the anchor 'status' column indicates they are off-line, proceed with step 3. - In RTLS Manager/Anchor Settings, check if the IP addresses are still correct for each anchor. Normally, the anchors will have a static IP (recommended!) but if it is set to DHCP and the system is connected to the company network, IP addresses may have changed. - In RTLS Manager/Synch Stability, check in the graph if the values on the y-axis don't exceed a value of "2". In the slave-anchor list, check that there is no packet loss (the number of lost packets must not increase over time). If either NOT ok, proceed with trouble shooting. If this does not solve the problem, proceed as follows:   - Visually inspect the anchors, to see if the housing shows an LED lighting up. If indeed the case, proceed with trouble shooting. - Visually inspect the anchors to see if they are misaligned (due to any impact of for example a bird, a door, machine) or if any new big objects were introduced in the tracking area, which can potentially block the line of sight between the master anchor and its slaves. If the problem persists: - Check the cables, connectors and network switch. Are all cables plugged in correctly (try unplugging-plugging)? Is there water or dust ingress? Are all LED's on the switch lighting up? If not, try plugging the connector into a free switch port. Does the network switch have a correct IP rating? Also check the cable between the switch and the Sewio PC. You could optionally use a UTP cable tester (available online for app. $10,-) to test the cable integrity. If the problem persists: - Use the backup tool to make a database backup and get R&D assistance. - See also the anchors FAQ on the Sewio documentation portal. - If none of the above solved the problem, start an RMA process. View original HubSpot article · HubSpot article 190573052021 · Knowledge Base 187958790447 · Language en · Updated 1748128108398 --- ## The subject/tag names in TrackLab have technical numbers (MAC address). Can these be changed into human readable names? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-subjecttag-names-in-tracklab-have-technical-numbers-mac-address-can-these-be-changed-into-human-readable-names-SWo Chapter: Noldus Knowledge Base Yes, from TrackLab version 2.12 up, you can apply custom names in the Variables module. View original HubSpot article · HubSpot article 190556076833 · Knowledge Base 187958790447 · Language en · Updated 1748130774618 --- ## The time stamps from the Sewio REST API export are not from the correct time zone. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-time-stamps-from-the-sewio-rest-api-export-are-not-from-the-correct-time-zone Chapter: Noldus Knowledge Base Tell the customer to use our Sewio Sage export tool (tool + user manual available at R&D) to export historical data. The REST API is primarily designed for export or handling meta data, and we don't have a tool to support it. - Time zones: In Sewio/Sage, time stamps are always stored in UTC/GMT. The customer needs to convert the time stamps to their local time zone themselves. For example, in Excel they can apply a simple cell formula for subtracting or adding a number of hours, without needing to use Excel Visual Basic (VBA).   Example for Time Stamp Conversion: Fine below an example of a formula for conversion of UTC/GMT times to a local time zone that in this example is 5 hours later than UTC/GMT. For more details, see this MicroSoft Tech Community post. View original HubSpot article · HubSpot article 190573052189 · Knowledge Base 187958790447 · Language en · Updated 1748137622157 --- ## The TrackLab customer reports a defective Sodaq-GPS tag with bulging battery. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-tracklab-customer-reports-a-defective-sodaq-gps-tag-with-bulging-battery Chapter: Noldus Knowledge Base 1) Have the customer open the tag enclosure by removing the 4 torx screws... 2) ...and remove the SD card from the SD cardholder by press-and-release... 3) ...take a picture of the SD card (with id number visible)... 4) ...take a picture of the battery. Example of a bulging battery: 5) ...take a picture of the tag sticker (on the enclosure) showing the ID number... Example: 6) Tell the customer to dispose of the tag according local regulations. Do NOT ask the customer to remove the battery to return the rest of the tag, as the battery is firmly glued to the enclosure and applying force can damage the battery which can spark a fire! 7) Start an RMA process. View original HubSpot article · HubSpot article 190573052074 · Knowledge Base 187958790447 · Language en · Updated 1748132517675 --- ## The TrackLab server is disconnected URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/the-tracklab-server-is-disconnected Chapter: Noldus Knowledge Base - Open the Windows Task Manager and verify if TrackLab server is running. If it isn't, start it. If it is not, proceed with the next step: - Verify if the RabbitMQ service is running. If not > start it. - If the status is ‘running’ but the problem persists > stop-and-restart it. - If the problem still persists, re-install N-Linx.   View original HubSpot article · HubSpot article 190573052036 · Knowledge Base 187958790447 · Language en · Updated 1748129567503 --- ## There are no data in my experiment. What happened ? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/there-are-no-data-in-my-experiment-what-happened Chapter: Noldus Knowledge Base When trying to open recordings for analysis, the message opens: This occurs when UltraVox XT looks for recordings that are no longer present in the experiment. This could be for the following reasons: First reason: There are no recordings in the experiment folder. You can check this by opening the folder under Experiments that has the same name as the experiment. There should not be recordings (UVD) and other files. Second reason: The experiment folder still contains recordings, however the software points to another folder which does not contain recordings. This happens when experiments are duplicated not in the proper way, for example by simply copying an entire folder and giving this new folder another name. Do the following: - Close the experiment. - Open the folder of the experiment. - Right-click the file with extension UVX and select Open with Notepad. - Take note of the name on the second line, near Name =. This is the name of the folder where UltraVox XT was looking in. Perhaps this folder was deleted, or moved, with its own recordings. - Try to recover that folder and place it under Experiments. IMPORTANT To make a new copy of an experiment, always use the File > Save As function within UltraVox XT !   View original HubSpot article · HubSpot article 190556076887 · Knowledge Base 187958790447 · Language en · Updated 1748142309654 --- ## There are no rectangles around the paw prints in CatWalk XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/there-are-no-rectangles-around-the-paw-prints-in-catwalk-xt Chapter: Noldus Knowledge Base Too much of the animal is being detected, preventing CatWalk from focusing on the actual prints, or display of the rectangles has been turned off. Too Much Detection If the Camera Gain is high or there is too much ambient light in the room, especially if the Green Intensity Threshold is too low, CatWalk may detect the abdomen or even the complete ventral side of the animal as a paw print. In this case, you'll see parts of the animal showing up in green, as shown here: When this is the case and in the Acquisition Settings the option "Discard incomplete prints at the start and end of a run" is selected, the following happens: as soon as the animal enters the camera view, the ventral side of the body overlaps with the border of the camera image, and, because of the selected option, the whole body (that is, all the prints) is discarded. To prevent this scenario from happening, deselect the option "Discard incomplete prints at the start and end of a run". You can access this setting by going on the menu to Setup > Acquisition Settings. You may also wish to adjust the detection settings if the Camera Gain is too high or the Green Intensity Threshold too low. Display of Rectangles is Turned Off Right-click in the orange (background) part of the image and make sure "Show Rectangles" is checked. View original HubSpot article · HubSpot article 190573052169 · Knowledge Base 187958790447 · Language en · Updated 1748136212644 --- ## There are no subjects visible in TrackLab, there seems to be no incoming data. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/there-are-no-subjects-visible-in-tracklab-there-seems-to-be-no-incoming-data Chapter: Noldus Knowledge Base First do this: - Arrange TeamViewer access. - On the TrackLab PC, try to access the Sewio RTLS portal. If you do NOT succeed, proceed with Scenario 1 below. If you can access the portal, proceed with Scenario 2.   Scenario 1 troubleshooting: NO access to Sewio RTLS - Check if the Sewio PC is switched on. - If the Sewio PC is switched off due to a power outage, ask the customer if they when this happened. Give the customer instructions (see installation manual) to enable the 'automatic reboot' setting in the BIOS settings. This option should be enabled by default (part of the standard system installation procedure) but it may have been forgotten. - If the Sewio PC was switched on, proceed with the next step. - Stop TrackLab recording and reboot both TrackLab PC and Sewio PC. - Get the following TrackLab error log files: "C:\ProgramData\Noldus\TrackLab\2\Log", "C:\ProgramData\Noldus\TrackLab Recorder\2\Log" and "C:\ProgramData\Noldus\TrackLab Server\2\Log". - Check the network cables and connectors. Unplug and re-plug the connectors, check for water or dust ingress. - Check for hostile conditions at the switch and PC; potential temperature, humidity or dust ingress problems? Does the switch have an according grade? - Reboot the network switch. - Check if the Sewio-to-TrackLab network cable length does not exceed 100m. - Check if the IP address is correct (@R&D: instructions). - Check if the correct TrackLab PC Firewall rules are applied (see installation manual). - Get the Windows log files from the TrackLab PC: (a) Type ‘eventvwr’ in the Command Line, (b) Right-click “Application”, (c) Choose “Save All Events As”, (d) Choose “Comma Separated”. - Get the RTLS Studio and Linux OS log files from the Sewio PC. If the network between the TrackLab and Sewio PC is in tact, you can use the command line through the TrackLab PC, as outlined in step 12 (@R&D: instructions for Sewio PC access?). If the network is not in tact, you will need to assist the customer in getting the files. - If the network is defective, run system diagnostics/ping tool on the Sewio PC. Instructions: Enter “ping 192.168.225.2 –t” in the command line. Check the result in the command-line-interface to see if communication was succesful. - If the Ping result is OK but intermittent network problems are suspected, run the system diagnostics for an extended period of time. You can then include timestamp logging which makes it easier to trace when and what happened. Instructions: - Diagnostics for the TrackLab PC: (Windows): Use a PowerShell script like this: "ping.exe -t 192.168.225.2 |Foreach{"{0} - {1}" -f (Get-Date),$_} >> log.txt". - Diagnostics for the Sewio computer (Linux): Try this command: "ping 192.168.225.2 | while read line; do echo `date` - $line; done > log.txt". It will give a similar output. - If the previous did not reveal and fix the problem, get R&D assistance.   Scenario 2 troubleshooting: access to Sewio RTLS is OK - Check in Sewio RTLS Studio/Sensmap if tags are still showing and moving. - Check in RTLS Manager/Tag Summary if the tag status is still updated and if the battery level is adequate. If a tag is 'alive' the 'status' cell is green. - Stop-and-restart TrackLab Recorder, TrackLab Server, N-Linx and RabbitMQ, in the Task Manager on the TrackLab PC. RabbitMQ might be ‘frozen’ which means it cannot be stopped or restarted. In that case, reboot the PC. If that does not help > re-install the N-Linx server. - Check these settings in RTLS Studio/RTLS Manager: (a) Server Communication settings/Udp Upload address: "192.168.225.1", (b) Position data output/Upload via Udp: "YES". - In RTLS Studio/RTLS Monitor, check to see how much CPU resources Sewio is using. If the CPU load is very high (e.g. near 100%): Reboot the Sewio system (as short-term solution) and get R&D assistance for the long-term solution. - If the above did not uncover and solve the problem, proceed: - Check if all tags are still mounted correctly on the subjects. - Check if the Sewio system is still working. - If the Sewio system is not working, in RTLS Studio/RTLS Manager/Anchors Summary, check if all anchors are shown in the anchors summary table. - In RTLS Studio/RTLS Manager/Synchronization Stability, check the communication between the master anchor and its neighboring slave anchors. Make sure the values in the graph remain under value "2", for each of the slave anchors. Also check that there are no (or no increasing) synch packet losses. - Check if any of the anchors was accidentally misplaced. If necessary, optimize anchor alignment for better ‘line of sight’. - If the anchors are detected but the problem persists, ask the customer to reboot the Sewio PC. - If the problem still persists, ask the customer to check the network cables at the anchors (properly plugged? damage?), the network switch (check if the connector LED’s flash) and both PC’s. - If the problem persists > Get R&D assistance. View original HubSpot article · HubSpot article 190573052055 · Knowledge Base 187958790447 · Language en · Updated 1748131384206 --- ## Toolbars in EthoVision have disappeared URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/toolbars-in-ethovision-have-disappeared Chapter: Noldus Knowledge Base EthoVision XT 10 and older The menu bar can be floated out of the EthoVision window by double-clicking it, and after doing that it could be positioned awkwardly. Double-click any blank space in the menu bar to float it, or to dock it back into the window. This will typically reset its position. If it becomes a tall, narrow rectangle which pushes other things over to the right, click and drag the dashed line at the top, dragging it up to the top bar of the EthoVision window and move it around until you see a very wide rectangle appear, then release it.   Alternatively, close EthoVision, go to the Start menu, click Run and then type "regedit" in the box and click OK. This will open the registry editor. In the panel on the left side, click the + signs to open the entries for:  \HKEY_CURRENT_USER\Software\Noldus Information Technology\EthoVision\x\   Note: “x” above equals your version number Indented under "x" will be a number of entries, many of which have names beginning with "Toolbars". Right-click on each of the ones with a "Toolbars" name and pick Delete. Close the registry editor and then open EthoVision. It will recreate those entries with default settings, which should set the menu(s) back to normal. For example, in EthoVision XT 10: EthoVision XT 11 and newer Close EthoVision and go to the location of the problematic experiment’s folder.  By default, it will be located in C:\Users\Public\Documents\Noldus\EthoVision XT\Experiments.  If not located in the default location above and you’re not sure where it is located, re-open your experiment in EthoVision and go to the Experiment Settings. The location of the experiment will be shown at the top. Once the location of the experiment is known, close EthoVision, use the File Explorer to navigate to that location, and open the experiment’s folder.  It should look something similar to the image below (please note there may be slight variations in the appearance depending on your version and the experiment itself): Delete the highlighted files (.pob and .pos files) by either right-clicking on each and selecting “Delete” or highlighting each one and press the “Delete” key on your keyboard. The locations of toolbars in EthoVision are stored in those files so deleting them will reset them to the default positions. Once deleted, close the File Explorer and re-open your experiment in EthoVision to see if the issue is resolved. View original HubSpot article · HubSpot article 190573052068 · Knowledge Base 187958790447 · Language en · Updated 1748132205672 --- ## Tracking from multiple video files (Batch processing) in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracking-from-multiple-video-files-batch-processing-in-ethovision-xt-3pN Chapter: Noldus Knowledge Base Tracking from multiple video files (Batch processing) in EthoVision XT. Applies to: EthoVision XT (9.0 and later) Description of issue:  If you recorded a series of video files outside of EthoVision or want to re-track video files that were recorded with EthoVision earlier you can use the Batch Processing functionality. Solution  Under Experiment Settings, select ‘From video file’ as the Video Source:   The following example experiment has 2 Arena Settings and 2 Detection Settings:   Next, in the Trial List, click on ‘Add Videos’:   Browse to the video files and selected the ones to be added to the Trial List:    If all videos will be tracked using identical Arena Settings, Trial Settings, and Detection Settings, you simply select the desired settings (in blue) in the Experiment Explorer:    However, if these settings vary across video files, you need to select them for each video:   Please note that it is all or nothing:  Either don’t select ANY settings or select one for EACH video. Subsequently, in the Acquisition window, select ‘Track all planned trials’:  View original HubSpot article · HubSpot article 190573052046 · Knowledge Base 187958790447 · Language en · Updated 1748130691618 --- ## TrackLab 2.15 Upgrade Notes URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracklab-215-upgrade-notes Chapter: Noldus Knowledge Base      Current Version number : TrackLab 2.15.  To upgrade  from TrackLab version  2.14.2  - Download the TrackLab 2 Help document in the Documentation tab. - Please read carefully the Update TrackLab procedure as described in the manual. - Download the TrackLab 2.15, TrackLab 2.15 Server, and TrackLab 2.15 Recorder Setup files in the Versions tabs. Do not start the installation yet. - To ensure the safety of previously recorded data follow the procedure  step by step  to install TrackLab and create a  backup of your data  .  To upgrade  from TrackLab version  2.12 or older  - Please contact Noldus Support to arrange an upgrade. - Support will help you to make a database backup before installing the new version. Find more information on how to upgrade your license with a dongle or a software based license. View original HubSpot article · HubSpot article 193222114228 · Knowledge Base 187958790447 · Language en · Updated 1753290797127 --- ## TrackLab crashes when opening or creating a new project URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracklab-crashes-when-opening-or-creating-a-new-project Chapter: Noldus Knowledge Base - Get the following log files: "C:\ProgramData\Noldus\TrackLab\2\Log", "C:\ProgramData\Noldus\TrackLab Recorder\2\Log" and "C:\ProgramData\Noldus\TrackLab Server\2\Log". - Get R&D assistance. View original HubSpot article · HubSpot article 190573052079 · Knowledge Base 187958790447 · Language en · Updated 1748132937688 --- ## TrackLab Remote Support & TeamViewer Usage Guidelines URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracklab-remote-support-teamviewer-usage-guidelines Chapter: Noldus Knowledge Base In order to facilitate easy access for Support and updates installation, the TrackLab R&D team have setup TeamViewer access on almost all customer PC’s. By setting up a TeamViewer connection during the TrackLab installation process, we guarantee a swift response in Support scenarios.  Some customers have granted us free access. Others we can access only after getting the customer consent.  Instructions: - These instructions are for Support personnel only. See also picture below. - If the customer PC has no intranetwork connection (wired or wifi) for instance if the tracking site is at a remote farm, recommend the customer to purchase a 4G or 5G data dongle in order to establish internet-based remote access. It is up to the customer to purchase this dongle, since the appropriate dongle solution depends on local service providers and their network coverage. Of course you can help out by providing an exemplary product link. - For access to customer PC’s, request the R&D team (ask Andrius Zukas or Mike Kelia) to share the “TrackLab Customers” TeamViewer group with you. - Once shared, you can access a TrackLab customer’s PC through your own TeamViewer account. - ATTENTION: open the ‘Properties’ window and view the information in the ‘Description’ field to find details such as the PC password and to see if you are allowed to access the PC freely, or that you need to ask for explicit customer consent each time you access it. Note: scroll the field to see all data. Notes: - If no fixed/personal TeamViewer password has been set on the customers PC, the password will be automatically reset each time the TrackLab PC is rebooted. This can easily happen, for example in case of a power outage or if the customer switches it off when not recording data. Therefore we need to make sure that a permanent password is set. This should be arranged already upon installation, but if not, here are the instructions: In TeamViewer go to: Extras > Options > Security > Personal password and set and confirm the password. Do NOT select the “grant easy access” option as that would enable password-free access. - We currently also use TeamViewer access for the installation of TrackLab updates. Be ensured that the TrackLab team are working to enable customers to install updates themselves, in the near future. - The Sewio PC (Linux) can be accessed through the TrackLab PC. The Sewio RTLS Studio software runs on the Sewio PC but can be accessed through the RTLS Portal on the TrackLab PC. In rare occasions, for instance when certain BIOS settings have to be changed, direct access (or switching on/off) to the Sewio PC may be required. In those cases you may need the customer to help you out. View original HubSpot article · HubSpot article 190573052201 · Knowledge Base 187958790447 · Language en · Updated 1748138460656 --- ## TrackLab shows "Database error, contact Noldus support" URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracklab-shows-database-error-contact-noldus-support Chapter: Noldus Knowledge Base Database error, contact Noldus support! While TrackLab was recording and it suddenly shows a message "Database error, contact Noldus support" in the "Recording Control", next to the Record and Scheduling buttons. This happens when the connection between "TrackLab Recorder" and the "N-Linx Storage Service" (storage engine) is lost.   To solve this please follow the following steps: - Check and make sure that RabbitMQ service is running. If it is not running please start it.                        2. Check and make sure that N-Linx Storage service is running. If it is not running please start it. If it is running try to restart it.                        3. If this did not solve the problem please reboot the TrackLab PC.           4. When the PC boots up check if the error is resolved. Check if the recording is running. If needed start a new recording. View original HubSpot article · HubSpot article 190573052205 · Knowledge Base 187958790447 · Language en · Updated 1748138782657 --- ## TrackLab stopped calculating analysis results for Areas of Interest URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracklab-stopped-calculating-analysis-results-for-areas-of-interest Chapter: Noldus Knowledge Base This can occasionally happen as the result of a bug. Update to version 2.12 which contains the fix. View original HubSpot article · HubSpot article 190573052037 · Knowledge Base 187958790447 · Language en · Updated 1748129642351 --- ## TrackLab subsampling vs sampling frequency URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracklab-subsampling-vs-sampling-frequency Chapter: Noldus Knowledge Base Sampling frequency in TrackLab is defined by the acquisition hardware (e.g. Sewio). This is the frequency at which location samples are produced. This also defines the maximum amount of samples within a given time frame. TrackLab is able to subsample the incoming data to a lower frequency. For example, the tracking hardware produces data at 10 Hz. When the location data stream comes into TrackLab it is subsampled to 1 Hz. This is useful when high-frequency data is not needed to derive analysis results.  The default subsampling frequency starting with TrackLab 2.12 is 1 Hz. This can easily be increased or decreased when needed before a recording is started. See the image below where to change the subsampling frequency.    View original HubSpot article · HubSpot article 190573052260 · Knowledge Base 187958790447 · Language en · Updated 1748143095244 --- ## TrackLab Viewer crashes on application startup (up to version 2.9) URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/tracklab-viewer-crashes-on-application-startup-up-to-version-29 Chapter: Noldus Knowledge Base Install update 2.10 or newer. View original HubSpot article · HubSpot article 190573052196 · Knowledge Base 187958790447 · Language en · Updated 1748138078655 --- ## Troubleshooting air continuing to blow after mouse crosses ladder URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/troubleshooting-air-continuing-to-blow-after-mouse-crosses-ladder Chapter: Noldus Knowledge Base When the ErasmusLadder is working properly, after the mouse has crossed the ladder and moved into the chamber at the end, air should stop blowing on the walkway and the lights should turn off. If air continues to blow and the lights stay on, this indicates one of the ladder rungs is sticking in the pressed position. You can temporarily release the rung by lifting up lightly on that rung, e.g., with the eraser end of a pencil in order to get through the current session. Below, you can download a video where colleagues explain how to find the sticky rung: Download the video To determine which rung is affected, check the LCD display of the ladder. In an upper corner it will give a letter and number, e.g. R5 or G15. R is the front of the ladder (marked with a Red stripe) and G is the back (Green stripe). The numbers are labeled next to the rungs, number 1 is on the right. If the display shows a rung is pressed when the animal has actually left the ladder, that rung is sticking.   To replace the rungs you just need an allen wrench and a replacement rung. Each ErasmusLadder is provided with a number of replacement low and high rungs for just such an occurrence. More can be ordered if needed. Full instructions for the replacement can be found in the help. You can manually test the rungs without an animal. The easiest way is to turn the ladder on, then press down on the rung e.g. with the eraser end of a pencil. The air should turn on right away, and then it should stop right away when you release the rung. However, rungs sometimes stick only when pressed with a certain amount of weight, and manually testing may not give the same results as a mouse. So even if you have manually tested them all, if there’s one that sticks during an actual trial, replace that rung.   View original HubSpot article · HubSpot article 190573052030 · Knowledge Base 187958790447 · Language en · Updated 1748128894855 --- ## UltraVox microphones are not recognized after restarting the computer URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ultravox-microphones-are-not-recognized-after-restarting-the-computer Chapter: Noldus Knowledge Base UltraVox may not recognize the microphones if they have been plugged into different ports, or if the computer went into sleep mode. Solution - Disconnect and reconnect the USB cable of the hub to the same USB port. - In UltraVox XT, open the Experiment Settings, and click the Refresh button. - If you see a cross symbol next to a microphone, click the button in the Microphone column and make sure to reselect the same microphone. The microphones will keep the same microphone name as before. To prevent issues, always plug each microphone into the same USB port every time. View original HubSpot article · HubSpot article 190573052253 · Knowledge Base 187958790447 · Language en · Updated 1748142774550 --- ## UltraVox XT Error Message - Out of Memory URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/ultravox-xt-error-message-out-of-memory Chapter: Noldus Knowledge Base The following error appears: “Error saving calls: Out of memory (A2)”.   The problem occurs when your recording has lots of calls, for example more than 500, and the Overlap (%) value in the Spectrogram settings is high, for example 90%. Increasing Overlap can improve sensitivity for brief events, but it substantially increases the amount of data that must be recorded, as well as slowing down the analysis, as the same data must be reanalyzed for each overlapping SFT frame. Solution -  In the Call Detection screen, under View, click Settings. - Reduce the value of Overlap (%), for example to 70%. Next, click Close. - In the Call Detection screen, click Apply to detect the calls, then save the experiment. View original HubSpot article · HubSpot article 190573052053 · Knowledge Base 187958790447 · Language en · Updated 1748131237386 --- ## Understanding Axis camera LEDs URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/understanding-axis-camera-leds Chapter: Noldus Knowledge Base Understanding camera LEDs When troubleshooting an Axis network camera, the camera LEDs can be a very useful source of information. Different models have different LED setups, but here we’ll use the AXIS P1365 as an example. This model has three LEDs: one for status, one for power and one for network. Each LED can show different colors.  The status LED A steady green light means normal operation. A steady amber light is shown during startup, during a reset to factory defaults or when restoring settings. A slowly flashing red light indicates a failed firmware upgrade. The power LED   - A steady green light means normal operation - The light flashes green/amber during a firmware upgrade. The network LED - Steady green when connected at 100Mb/s. Flashes on network activity. - Steady amber when connected at 10Mb/s. Flashes on network activity. - Unlit when there is no network connection.   View original HubSpot article · HubSpot article 190278724018 · Knowledge Base 187958790447 · Language en · Updated 1747546472103 --- ## Upgrade CatWalk XT 10.7 from version 8 or 9 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/upgrade-catwalk-xt-107-from-version-8-or-9 Chapter: Noldus Knowledge Base To upgrade CatWalk XT 10.7 from version 8 or 9, you need an  Upgrade Key  provided by Noldus after purchasing the upgrade. - Back up all your existing CatWalk data to a secure location. - If upgrading, manually uninstall the existing CatWalk XT drivers for the Ethernet card, as version 10.7 uses new drivers: - Open the  Control Panel  and go to  Programs and Features  . - Uninstall  eBUS Driver Suite [version number]  . - Uninstall  Gevicam [version number]  . - Install CatWalk XT 10.7. - If your license uses a USB hardware key, insert it into a USB port on your CatWalk XT computer. - Start CatWalk XT 10.7. - Enter the Upgrade Key when prompted. If you are upgrading from CatWalk version 7, your computer does not meet the system requirements for CatWalk XT 10.7. Please contact your nearest Noldus support office. Find more information on how to upgrade your license (dongle or a software based license). View original HubSpot article · HubSpot article 193222114113 · Knowledge Base 187958790447 · Language en · Updated 1753284382668 --- ## Upgrade to ErasmusLadder 2.0 URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/upgrade-to-erasmusladder-20 Chapter: Noldus Knowledge Base To upgrade from version 1.x IMPORTANT Installing ErasmusLadder 2.0 overwrites version 1.x. If you run experiments in the old version, complete the experiments in the same version. Use ErasmusLadder 2.0 for the new experiments. 1. Follow the procedure as described in the installation instructions. 2. When you start ErasmusLadder for the first time, a window appears asking to enter the Upgrade key. Enter the code that you received from Noldus. NOTE Experiments saved in ErasmusLadder 2 cannot be opened in ErasmusLadder 1.x. Find more information on how to upgrade your license in this knowlegde base article: https://my.noldus.com/shared/knowledge-base/answer/282 View original HubSpot article · HubSpot article 193237711685 · Knowledge Base 187958790447 · Language en · Updated 1753288447335 --- ## Using the MediaTypeRegistryCleaner URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/using-the-mediatyperegistrycleaner Chapter: Noldus Knowledge Base If video files that previously worked are not working now, especially .mp4 files, there is likely a problem with the codecs installed on the system. Such problems occur most often when other software using video is installed, uninstalled, or updated. You may receive Media File Error (Id 8356) in EthoVision indicating such a problem. There is a tool available which can resolve many such codec problems.  If you have the EthoVision XT 16 or 17 installation USB stick, this tool can be found in the folder \Drivers and tools\Utilities\MediaTypeRegistryCleaner   Otherwise, download this file: https://noldus.sharefile.eu/d-s23c8e2c4233c4e518dcdf773ec402360  If you have downloaded the zip file, unzip the file by right-clicking it and picking Extract All. To use the tool, in the x64 folder, right-click the MediaTypeRegistryCleaner file and pick "Run as administrator" (if you do not have administrative access on your PC, you may need the assistance of your local IT department). Reboot the computer and check whether the issue is resolved. View original HubSpot article · HubSpot article 190573052269 · Knowledge Base 187958790447 · Language en · Updated 1748143817683 --- ## Viso Error 30028 when opening a location URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/viso-error-30028-when-opening-a-location Chapter: Noldus Knowledge Base Ensure a stand-alone video card with 2+ GB RAM. It should also support Direct3D Acceleration. We prefer NVIDIA video cards. View original HubSpot article · HubSpot article 195616950680 · Knowledge Base 187958790447 · Language en · Updated 1757345199137 --- ## Viso rooms are showing offline URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/viso-rooms-are-showing-offline Chapter: Noldus Knowledge Base - Download & Unzip to a folder named Noldus Configuration Do Not Delete on the root of the C:\ Drive Link: Download  - Open a Command prompt with admin rights  - Navigate to win64 folder of unzipped file  cd c:\Noldus Configuration Do Not Delete\nssm-VERSION\nssm\win64  - Start the service manager with this command    - On application tab, browse to the path to the recorder manager   < C:\Program Files\Noldus\Viso Recorder VERSION\VisoRecorderManager.exe>    - In the Service name field put   - Click “Install Service”  - In the start menu, type “Startup” and open Startup Applications.  - Turn off automatic startup for Viso Recorder Manager  - Reboot the computer   View original HubSpot article · HubSpot article 195613710143 · Knowledge Base 187958790447 · Language en · Updated 1757090337530 --- ## Viso troubleshooting the Router URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/viso-troubleshooting-the-router Chapter: Noldus Knowledge Base One of the possible scenarios for Viso unable to reach camera error is because of the network router issue. Here are some simple troubleshooting steps: - Is only one device affected, or are all devices affected? If only one device, the issue is likely not the router. - Is the router plugged in to power? Is the power supply supplying power? - Are indicator lights on the router blinking? - Do Ethernet ports on the router indicate activity and link? - Is the router abnormally warm or hot? - Is the router making noise? - Is the workstation receiving an IP address from the router? - Is the router passing network traffic? - Are other devices on the network reachable? Attempt to ping a device by opening a command prompt and then typing ping HOSTNAME or ping IPADDRESS. Eg. ping noldus-recorder1, ping 192.168.200.100. If none of these steps point to an issue, perform a factory reset on the router and re-enter the configuration. If the issues persist, it may be necessary to replace the router.How to perform a factory reset is dependent on the router manufacturer and model. Please check the Reference Manual for your device to learn how to do a factory reset.Standard Noldus router settings: - IP Address: 192.168.200.250 - DHCP Scope: 192.168.200.50-99 - SSID: Noldus Lab Wifi - Security: WPA2/TKIP - Passphrase: Noldus123 View original HubSpot article · HubSpot article 195690691585 · Knowledge Base 187958790447 · Language en · Updated 1757345886245 --- ## What are the filter settings in Trackab? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-are-the-filter-settings-in-trackab Chapter: Noldus Knowledge Base TrackLab version 2.13 contains three different filter settings TrackLab 2.13 contains three filter settings: - Sample rate - Smoothing window size - Minimum distance moved threshold (MDM) Sample rate This setting specifies the maximum number of data points recorded by TrackLab per second, per tag. If a tag produces more than ‘sample rate’ data points, TrackLab filters out the surplus.  Depending on the configuration of the Sewio system, it can acquire data points with high frequency. This is desired when you are interested in additional sensor data like accelerometer data. In this case, the sample rate filter in TrackLab will limit the amount of location sample data entering TrackLab. The other sensor data (e.g., accelerometer) will remain at the sample rate set for the tags. For cattle, we usually set the sample rate to 1Hz. Higher sample rates put a bigger load on TrackLab’s database and processing while the analysis results do not improve.  In general, tracking smaller subjects requires a higher sample rate. Smoothing window size  To smooth out short-term fluctuations in the coordinates due to noise and rapid movements of the subject, TrackLab re-calculates the position of the tag based on the average coordinates of the data points in an interval around the focal time. This interval is called smoothing window (see below). For example, if the window size is 25 samples, the position of the tag at sample time (t) is calculated as the average of the coordinates of 25 samples centered on the focal sample. Those 25 samples consist of the focal sample, the last 12 samples before t, and the next 12 samples after t. This averaging process smooths out zig-zag paths. The higher the window size value, the smoother the resulting track will be. NOTE: By default, smoothing is enabled with a window size of 9. Minimum distance moved (MDM) threshold This setting filters out raw data which contains minimal displacement between subsequent locations. It removes noise and creates a more realistic estimate of the total distance moved by the subject, particularly when the subject spends significant time sitting or laying. To remove small, random displacements caused by noise in the data, TrackLab calculates first the distance between a sample and the next (AB in the following figure). If the distance is shorter than the threshold distance, the second sample (in the example below, B) is “moved” to the previous (A). Then TrackLab calculates the distance from A to the second next sample (the dotted line AC), etc. until it finds a segment (AD) longer than the threshold distance. Sample D is then kept in the original position. In this example, samples B and C are both set to sample A. TrackLab proceeds with the next segment (DE) etc. up to the end of the track. As a result, the track only shows significant displacements. Very small movements, which in the case of a stationary animal may consist entirely of noise, are filtered out. - A low value of the Minimum Distance Moved threshold does not have a significant effect on the track, especially at high sample rates (e.g. 10 samples/s).  - Select a low value of Minimum Distance Moved threshold in the following cases: (a) when the tracking area is small; (b) when you defined small Areas of Interest; (c) when you analyze proximity with a small value of the ‘In proximity below’ threshold. The value of Minimum Distance Moved should be smaller than the proximity threshold. In combination with Sewio, we advise using a MDM threshold of 0.30 m. In combination with GPS Lora, we advise using a MDM threshold of 1.00m. View original HubSpot article · HubSpot article 190573052262 · Knowledge Base 187958790447 · Language en · Updated 1748143218639 --- ## What are the supported cameras for MediaRecorder 5.0? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-are-the-supported-cameras-for-mediarecorder-50 Chapter: Noldus Knowledge Base Analog Cameras MediaRecorder works with the output of any analog camera used with the Euresys Picolo H.264 or Euresys Picolo Alert video capture card. We specifically tested MediaRecorder with output of the following cameras: - The camera from the PhenoTyper Top Unit (EIA). - The camera from the PhenoTyper Top Unit (CCIR). Maximum supported number of cameras - Euresys Picolo Alert PCIe card - Four cameras or PhenoTyper Top Units. - Euresys Picolo U4 H.264 card – Three cameras or PhenoTyper Top Units. - Euresys Picolo U8 H.264 card. – Six cameras or PhenoTyper Top Units. IP Cameras To use MediaRecorder with IP cameras, the following network requirements apply: - An Intel Pro/1000 CT or Intel Pro/1000 PT (1 Gb) network adapter is installed in the computer with MediaRecorder. - The cables are suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. - We recommend using a dedicated network for the cameras, rather than connecting them to a general use network. Supported IP cameras - Axis P5512 - Axis P5514 - Axis P5515 - Axis P5534 - Axis M1054 - Axis M1065 - Hikvision IP DS-2PT7D20IW-DE USB Cameras - Microsoft LifeCam Studio - Basler acA1920-155um - Logitech BRIO The DanioVision FireWire system The ImagingSource DMK 21AF04 camera that is present in the DanioVision FireWire system (currently discontinued). GigE Vision cameras - Basler GigE cameras AC1300-60gm Screen capture devices Epiphan screen capture devices The Epiphan screen capture devices are hardware devices with which you connect the monitor of the test computer to the computer with MediaRecorder. MediaRecorder supports: - Epiphan DVI2USB 3.0 – A USB 3 device. - Epiphan DVI2PCIe – A frame grabber board that is inserted in a PCI express slot in the recording computer. - Epiphan VGADVI broadcaster. A screen capture device that streams over Ethernet. MediaRecorder screen capture device A software screen capture virtual device that is present if your MediaRecorder license includes the Screen Capture Module. View original HubSpot article · HubSpot article 195251830107 · Knowledge Base 187958790447 · Language en · Updated 1756399615166 --- ## What are the supported video file formats for EthoVision XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-are-the-supported-video-file-formats-for-ethovision-xt Chapter: Noldus Knowledge Base Supported video file formats for EthoVision XT 12, 13, 14, 15, and 16 EthoVision XT supports playback of the following digital video file formats: - MPEG-1. (No longer supported in EthoVision XT 16.) - MPEG-2. This is a collection of formats, not all are supported. - MPEG-4. This is a collection of formats, not all are supported. - MPEG-4 (mp4v) in MP4 container. This is the format of video files you obtain when you record video with EthoVision XT using analog cameras connected to the Picolo Alert board. - MPEG-4 DivX in AVI container. This is the format created by Media Recorder and EthoVision XT with digital cameras.  - H.264 AVC in MPEG container. This is the format created by Media Recorder 2.5 and lower with the Euresys Picolo H.264 board. - H.264 AVC in MP4 container. This is the format that will be created by Media Recorder 4.0 with the Euresys Picolo H.264 board. - H.264 AVC is a type of MPEG-4, which is supported. - DV-AVI. This is uncompressed video from FireWire cameras. We do not recommend this format because of the large file size. Note that DV-AVI is a special case of AVI. In general, EthoVision XT does not support video files of AVI format. The AVI format should not be confused with the *.avi file extension. Some MPEG-4 files have the extension *.avi, but other video formats with *.avi extension may not work.  We cannot guarantee that all MPEG-2, MPEG-4, and H.264 files can be played back in EthoVision XT, only those created using the encoder boards supplied by Noldus and the Media Recorder software.  To play back MPEG-1 and MPEG-2 files, EthoVision XT uses the MainConcept Decoder which is automatically installed when you install EthoVision XT. To play back MPEG-4 files, EthoVision XT uses the standard Windows decoder, which is present on all computers with Windows installed. To play back H.264 files you need decoding software which is installed when you install EthoVision XT. One of the difficulties with digital video files is that the file extension does not indicate what the file type is. For example, the extension *.mpg can mean any one of different type of formats, and an MPEG-4 movie can have the extension *.mpg, *.mpeg or *.avi. Video formats not supported by EthoVision XT - DivX, other than the MPEG-4 DivX created by Media Recorder. - WMV. - Quick Time. - FLV (Flash video, YouTube). - XviD variants of the MPEG-4 format. Testing Other Formats EthoVision may work with other video formats that are not supported. Check that the Missing Samples (and Interpolated Samples if shown), which are shown at the bottom of the screen in the Detection Settings and Acquisition, are less than 1%. These numbers will turn red if the values are high. If the count of Missing or Interpolated Samples is high, this indicates the video is missing many frames or the frame timing is inconsistent and the analysis may be affected. Determining the Format If unsure of your video file type, right-click on your video, select Properties and that will display the video file information.    The resolution (width x height) of your videos must be at least 640 x 480 and no more than 1920 x 1200.   If unsure of the resolution, right-click on your video, select Properties and click the Details tab.  That will display the resolution information.  Converting Videos If you need to convert your video files to a compatible format, we recommend the following inexpensive converter: MP4Converter To change the format it outputs, Under Profile (at the bottom of the screen), go to General Video Format. - Observer and FaceReader: convert to DIVX, XVID, MPEG-1 or MPEG-2. - EthoVision or DanioScope: convert to MPEG-1, MPEG-2 or DIVX. - If converting MTS files, please convert to DIVX or XVID as support has reports from customers that MTS to MPEG-1 and MPEG-2 do not work. They offer a trial period which will enable you to convert the first 3 minutes of a video. This should be enough to test the video in our system to see if it works. If so, you can then purchase the converter to convert all of your videos in their entirety. Handbrake Another conversion option is Handbrake, which is free. In Handbrake, on the Summary tab, set the format to MP4. On the Video tab, set the codec to H.264, the frame rate to “same as source” and pick the option for “Constant Framerate.” View original HubSpot article · HubSpot article 190573052031 · Knowledge Base 187958790447 · Language en · Updated 1748128980947 --- ## What are the supported video formats for FaceReader 8? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-are-the-supported-video-formats-for-facereader-8 Chapter: Noldus Knowledge Base FaceReader 8 supports the following video formats: Container Code Name/Encoder mpg mpg1 MPEG-1 Part 2 mpg mpg2 MPEG-2 mpg H264 H.264/ MPEG-4 vob (DVD) mpg2 MPEG-2 mp4 mp4v MPEG-4 Video mov mp4v MPEG-4 Quicktime avi XVID XviD ISO MPEG-4 avi XVID XviD 1.1.0 Final avi DIB (_RGB)  BI_RGB Raw Bitmap avi DIV3 DivX 3 Low-Motion avi DIV5 DivX 5.x/6.x avi DIVX DivX 4 avi dvsd DVC/DV Video avi DX50 DivX 6.0.0 avi DX50 DivX 5.x avi CRAM Microsoft Video 1 avi cvid Cinepak avi IV32 Indeo 3.x avi MJPG Motion JPEG avi MP42 S-MPEG 4 version 2 avi WMV3 WMP v9 (VC-1 Simple/Main) asf (.wmv) WMV1 WMP v7 asf (.wmv) WMV2 WMP v8 asf (.wmv) WMV3 WMP v9 (VC-1 Simple/Main) asf MP43 S-Mpeg 4 version 3 3gp s263 ITU H.263 video (3GPP)   Notes: - The container is not the same as the file extension. Different containers can have the same file extension. - If you are not sure what the format of your video files is, you can use a program like GSpot to find this out. To download GSpot (free of charge): http://www.headbands.com/gspot View original HubSpot article · HubSpot article 190573052040 · Knowledge Base 187958790447 · Language en · Updated 1748130313280 --- ## What are the supported video formats for FaceReader 9? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-are-the-supported-video-formats-for-facereader-9 Chapter: Noldus Knowledge Base FaceReader 9 supports the following video formats: Container Code Name/Encoder mpg mpg1 MPEG-1 Part 2 mpg mpg2 MPEG-2 mpg H264 H.264/ MPEG-4 mpg H265 H.265/ MPEG-4 vob (DVD) mpg2 MPEG-2 mp4 mp4v MPEG-4 Video mov mp4v MPEG-4 Quicktime avi XVID XviD ISO MPEG-4 avi XVID XviD 1.1.0 Final avi avi DIB (_RGB) DIV3 BI_RGB Raw Bitmap D  ivX 3 Low-Motion avi DIV5 DivX 5.x/6.x avi DIVX DivX 4 avi dvsd DVC/DV Video avi DX50 DivX 6.0.0 avi DX50 DivX 5.x avi CRAM Microsoft Video 1 avi cvid Cinepak avi IV32 Indeo 3.x avi MJPG Motion JPEG avi MP42 S-MPEG 4 version 2 avi WMV3 WMP v9 (VC-1 Simple/Main) asf (.wmv) WMV1 WMP v7 asf (.wmv) WMV2 WMP v8 asf (.wmv) WMV3 WMP v9 (VC-1 Simple/Main) asf MP43 S-Mpeg 4 version 3 3gp s263 ITU H.263 video (3GPP)   Notes The container is not the same as the file extension. Different containers can have the same file extension.  If you are not sure what the format of your video files is, you can use a program like GSpot to find this out.To download GSpot (free of charge): http://www.headbands.com/gspot  Video file extensions in Project wizard  The following video file extensions can be used in combination with the project wizard: - .mpg - .mpeg - .avi - .wmv - .mov - .asf - .3gp - .vob - .mp4 - .mkv - .flv View original HubSpot article · HubSpot article 190276872051 · Knowledge Base 187958790447 · Language en · Updated 1747546194860 --- ## What can I do in EthoVision XT without the hardware license key? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-can-i-do-in-ethovision-xt-without-the-hardware-license-key Chapter: Noldus Knowledge Base EthoVision XT requires a license (hardware dongle or software key) to acquire new tracks from a camera or from video files (including redoing a trial), or to create a new experiment with functionality from an optional module (e.g. multiple arenas, nose-tail tracking, controlling external hardware). A hardware license key is not required to create a new experiment with base functionality (center point of one animal in one arena), use any of the analysis or visualization features, or export data. View original HubSpot article · HubSpot article 190573052279 · Knowledge Base 187958790447 · Language en · Updated 1748145136626 --- ## What exactly do the different colours in the heatmaps in EthoVision XT represent? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-exactly-do-the-different-colours-in-the-heatmaps-in-ethovision-xt-represent Chapter: Noldus Knowledge Base These represent the time spent in that area, where blue is the lowest and red the highest amount of time spent. Starting in EthoVision XT 15, the heatmap includes a legend that indicates the number of seconds for the highest part of the range. If you merge heatmaps (so each one represents multiple trials), the scale is the proportion of time rather than the number of seconds. View original HubSpot article · HubSpot article 190573052287 · Knowledge Base 187958790447 · Language en · Updated 1748145834054 --- ## What is the best way to share my Observer project with another user? Can I simply send the .vop (Observer Project) file? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-is-the-best-way-to-share-my-observer-project-with-another-user-can-i-simply-send-the-vop-observer-project-file Chapter: Noldus Knowledge Base Please note the .vop file is not the project, but rather one component of the project. In the example below, a project is a folder that has many pieces and should look something like this. The .vop file name should match the name of the folder. As such, the .vop file alone will not work for sharing your The Observer XT project with another user and you will need to use one of the solutions below.   Solution 1: If your colleague is using a “newer” (i.e., higher numbered) version of The Observer XT, or the same version, send them a backup of your project. If you are using an “older” (i.e., lower numbered) version of The Observer XT, you can simply make and send them a backup of your project.  To do so, open the project of interest and go to File > Make backup. It will prompt you with a window to ask where you’d like to save the resulting backup (.vpb) file. After making the backup, you can send the .vpb file to your colleague and after opening their version of The Observer XT, they will go to File > Restore backup, point the software to the .vpb file you sent, and that will restore the project on their PC.   Note: If you colleague is restoring a backup/opening a project from an older version of The Observer XT, they will get the following warning message.  Basically, it will upgrade the project to their version of The Observer XT and make a duplicate safety backup of the project in the original version.    Note: If you or your colleague does not see the option to make or restore a backup in the File menu, then you are using a Coder license key.  To check what kind of license key you have, you can go to Help > About The Observer XT > License Info.  In the window that opens, you will see a “License Number” field (just below the name of the “Registered User”).   If the license number starts with “OC”, that means you are using a coder license key and you may need to switch to a full license key after (will start with “OB” in the “License Info” window) in order to make and/or restore backups. Please note you will need to close the software before unplugging/swapping license keys.  If using a physical hardware key (purple USB key) to access the software, a Coder license key will say “Observer Coder” on it, whereas a full license key will say “Observer XT" on it.   Solution 2: If your colleague is using an “older” (i.e., lower numbered) version of The Observer XT, send them your observation (.odx) file(s). If you are using a “newer” (i.e., higher numbered) version of The Observer XT, then the only way to share your project is to send them you observation (.odx) file(s).   Completed observations should to be exported as individual .odx files via File > Export > Observation Data > The Observer XT > check the “Create separate file per observation” box > OK.  You can then send those .odx file(s) to your colleague.   Once your colleague has those file(s), they can create a new (blank) project in their version of The Observer XT by going to File > New Project.   After creating this project, they will import those .odx files via File > Import > Observational Data and selecting the .odx file(s).  The coding scheme that was used to create those .odx files will be generated automatically for you.   Note: This procedure will work for versions of The Observer XT as low as 10.5.   Note: If your colleague does not see the option to make a New Project (i.e., they only see the “New Project from Template” option) in the File menu, then they must be using a Coder license key and will need to use a full license key instead (as discussed above).   View original HubSpot article · HubSpot article 190556076818 · Knowledge Base 187958790447 · Language en · Updated 1748128214040 --- ## What is the difference between RF4 and RF5 channel settings, on the Sewio tags? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-is-the-difference-between-rf4-and-rf5-channel-settings-on-the-sewio-tags Chapter: Noldus Knowledge Base These is a technical setting that influence the channel utilization capacity, battery lifetime and signal robustness. Sewio recommends us to use RF5 which provides better channel utilization (maximum number of tags that can be simultaneously tracked) and battery lifetime, while in our typical applications, its slightly lower signal robustness is adequate. Hence, RF5 is what we use/recommend as default. More detail on UWB channels and profiles in the Sewio documentation. Notes: - Firmware updates will automatically set RF5 (on tags and anchors). You can find the default Leonardo) configuration settings here.  - For new tags, it can happen that despite the RF5 default, the tag is set to RF4, which can be a cause for customers reporting that their new tags are not showing up. This requires changing the tag configuration. There are 2 wireless configuration edit options. For one or a few tags, the quickest and zero-energy-use option is to use a Smartphone app (Android 5+ with NFC, BLE and GPS - click for instructions). However, this requires close access to the tags. If you want to change many tags in one go, without having to get close access to tags, you can edit tags configurations through the Sewio RTLS Manager (instructions) Note that this requires significant battery energy use. View original HubSpot article · HubSpot article 190556076834 · Knowledge Base 187958790447 · Language en · Updated 1748130854644 --- ## What is the purpose is of the tag settings ‘random deviation’, ‘periodical RX value’ and ‘RX duration’? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-is-the-purpose-is-of-the-tag-settings-random-deviation-periodical-rx-value-and-rx-duration Chapter: Noldus Knowledge Base - First ask the customer if their tracking setup has a specific problem that they want to solve. - Tell the customer that these settings are technical settings that in normal operation, must not be changed. - If they want more detail, send them this link, containing an explanations of the function of these settings. View original HubSpot article · HubSpot article 190556076868 · Knowledge Base 187958790447 · Language en · Updated 1748138329654 --- ## What to do if the Tobii Eye Tracker is not found URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/what-to-do-if-the-tobii-eye-tracker-is-not-found Chapter: Noldus Knowledge Base Sometimes, if you open Tobii Pro Lab, the eyetracker isn’t found. After opening a Project you see a red highlighted Eyetracker under the Record tab in Tobii Pro Lab (Figure 1). If you see this, the Tobii eye tracker will not start and it is necessary to re-enable it. Under the Control Panel\All Control Panel Items\Network Connections disable the network for the Tobii.   To do this right-click the Tobii Network and click the option “Disable”, right-click again and choose the option “Enable” after around 30 seconds the Tobii Eye Tracker is found in the Tobii Pro Lab automatically. You can see this, because the Eye Tracker is not red highlighted anymore and you see the type number of the eyetracker as well (Figure 2). View original HubSpot article · HubSpot article 190556076836 · Knowledge Base 187958790447 · Language en · Updated 1748130991624 --- ## What's new in EthoVision XT 17? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/whats-new-in-ethovision-xt-17 Chapter: Noldus Knowledge Base New and improved features in EthoVision XT 17 include: Application Software license. You can purchase EthoVision XT with a software license that makes it easier to use the software without worrying about losing or damaging the hardware key. You can choose to have your license coupled with one computer (named Fixed license) or with multiple computers (Floating license). Video technology EthoVision XT uses new drivers for digital cameras: - For Basler digital cameras, driver version 6.2 (was 5.1). - For Daheng digital cameras, driver version 1.12 (was 1.6). Graphic cards (GPUs) for tracking with Deep learning. A few more graphics cards have been tested that can be used to track your subjects with Deep learning. Make sure that the graphics card is compatible and its software is updated. Tested cards include the NVIDIA Quadro P2000 and P2200, and the NVIDIA T1200. Trial Control Permutation option for Trial Control variables of random type. Imagine your Trial Control procedure includes a variable which produces random values at every repeat of a task. For example, to determine which sliding door must be activated in the current repeat. The Trial Control variable has a extra option, Permutation, which extracts a specific value only when the other values allowed within a range have been extracted in previous repeats. Subrule repeat interval. Up to now you could have the software start a subrule repeat within 24 hours since the start of the previous repeat. Now you can specify a time period up to 99 hours 59 minutes 59 seconds. That is handy when you work with long protocols, for example when you define a task that must be repeated a number of times within a time period of more than 24 hours. Data acquisition Import trials from other experiments. You can import trials from different experiments and analyze them as one data set. Use this function, for example, to merge identical experiments that control groups of PhenoTyper cages or DanioVision chambers.  Show and hide the body points in the Manual Scoring screen. Sometimes when you code events in the Manual Scoring screen you really need to view the nose and tail-base points detected by the software. Now that is possible. Data analysis and visualization Group charts: box plots with dots. When you choose a box-and-whiskers plot for group results, you have the extra option to display the original data points the statistics are based on. Customize tracks. In several parts of the software, like in Detection Settings and in the Integrated Visualization, you can customize the thickness of the tracks and the size of the body points plotted. Headers in the results table. The statistics results table has now headers for the independent variables.  Documentation If you use the Temperature Control Unit with DanioVision, you can find all information about this device in the DanioVision DVOC-0041 - Reference Manual.   The EthoVision XT 17 - Application Manual includes a new chapter about conducting calcium imaging experiments with EthoVision XT combined with Inscopix nVista/nVoke systems. The Quick Start Guide for the Ugo Basile fear conditioning system has been incorporated in the EthoVision XT 17 - Application Manual. To access the manuals, in the start menu look under Apps > Noldus > EthoVision XT 17 Other Documentation. Experiment Templates Track3D experiment templates. Two new templates have been added to the current list: one for a flight chamber and one for a water tank, both designed for experiments where you track subjects in 3D. View original HubSpot article · HubSpot article 190556076846 · Knowledge Base 187958790447 · Language en · Updated 1748133362539 --- ## What's new in FaceReader 10.0? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/whats-new-in-facereader-100 Chapter: Noldus Knowledge Base FaceReader 10.0 brings you a myriad of brand-new features to broaden your emotion analysis research: - Voice emotion detection | Analyze vocal tone to detect emotions even when facial expressions are masked or not yet visible, giving you earlier and more nuanced insights into emotional states.  - Multimodal emotion analysis | Combine facial expression data with voice analysis to improve the accuracy and depth of emotion detection, helping you uncover subtle differences in emotional response, such as those caused by stress or mental health conditions.  - Multi-subject analysis | Analyze facial expressions of up to 8 people in a single video, making it easier to study social dynamics, group interactions, or team-based activities in natural settings or online meetings.  - Webcam eye tracking | Track eye movements and gaze patterns using a standard USB webcam, providing valuable data on visual attention and engagement, ideal for psychology, marketing, and UX research without investing in extra hardware.  - Vital signs monitoring | Measure heart rate, heart rate variability, and breathing rate directly from facial video, allowing you to capture physiological responses in real time without sensors or participant discomfort.  - Consumption behavior detection | Automatically detect eating and drinking actions like sipping or chewing, enabling you to study emotional responses during consumption and understand how mood, product experience, or environment affect behavior. NOTE  | To be able to measure Action Units and Custom Expressions, you need the Action Unit Module . Installation instructions for upgraders from FaceReader 8 or 9 - Complete your existing experiment. It is best not to mix versions in one research project. Because the classifications methods are improved with every release, we recommend to use the same FaceReader version within one project. - If you upgrade an experiment that was created in a previous version into FaceReader 9.1, it cannot be opened in the older version anymore. Therefore, always create a backup of your project first. - Facereader 10 can be installed next to older versions of FaceReader. - Follow the installation instructions for new users (tab 'Installation instructions'). - If you have the Project Analysis Module, use Stimulus Presentation Tool version 5 with FaceReader 10. Find more information on how to upgrade your license with a dongle or a software based license. View original HubSpot article · HubSpot article 193237711712 · Knowledge Base 187958790447 · Language en · Updated 1753289430397 --- ## What's new in The Observer XT 17? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/whats-new-in-the-observer-xt-17 Chapter: Noldus Knowledge Base To make coding visually more attractive and transparent, the encoded behaviors are updated as you score in this new version. Also, you can synchronize behavioral observations with neural data by integrating data from Bitbrain's EEG diadem. Find more information in the section 'Welcome to The Observer XT/What's new in The Observer XT 17' in The Observer XT 17 Help for the new features in The Observer XT 17. Press the F1 key in The Observer XT to open it, or double-click The Observer XT 17 Help icon on the desktop of the computer with The Observer XT. New patch In the latest version of The Observer XT17 (version 17.0.1304), there are several improvements: - Software based licensing will now allow more than 2 videos - Tobii control shows the correct status - Performance improvements for opening and scoring an observation with large/complex coding schemes This patch can be installed over a previous installed The Observer XT 17. Dongle free security system We offer the possibility of software based licenses as an alternative to the hardware key. This allows for a more flexible use of the license and no more lost or damaged dongles. Easily install and activate your software on multiple PCs. Please contact us for details if you are interested. To upgrade from a previous version - When you open a project that was made with a previous version of The Observer XT, the data will be converted to the new version and a backup of the previous version will be created in the current folder. Backup file: C:\Users\Public\Documents\Noldus\The Observer XT\Projects\Name project.vpb - Consult the section Installation/Upgrade to The Observer XT 17 in The Observer XT Help. Also read the notes in this section for compatibility of previous versions with The Observer XT 17. ULog uLog 3.5 is supported with The Observer XT 12.5 or higher. Find more information on how to upgrade your license with a dongle or a software based license. View original HubSpot article · HubSpot article 193222114224 · Knowledge Base 187958790447 · Language en · Updated 1753290369726 --- ## When and how do we update Sewio firmware and software? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/when-and-how-do-we-update-sewio-firmware-and-software Chapter: Noldus Knowledge Base General update guideline: - We will NOT actively push Sewio firmware and software updates to customers (if it ain't broke, don't fix it). - Exception 1: The customer has a reason to want an update. There is no argument against installing firmware and software updates. Tag firmware updates can be done by the customer and involves a fairly simple process using a mobile app (below). Anchor firmware and RTLS Studio software updates must be done (or assisted) by us as it is more technical and involves providing downloads from our Sewio Partner Portal. - Exception 2: R&D sees a need for pushing a firmware upgrade in certain cases, which will then come with clear instructions. Instructions for tag firmware updating ('Leonardo' & 'Personal' tag): - Tag firmware updates can be done using a smartphone app, also by the customer. - Follow the Firmware Update Instructions. - Don't forget to check the RTLS Studio version compatibility. If necessary, update the RTLS Studio version as well (see below). RTLS Studio is backward compatible so updates are only necessary in 'upward' direction. - For anyone interested in the version changes, see the changelog (very technical). Instructions for anchor firmware updating: - Anchor firmware updates can only be downloaded by Sewio partners (that's us), not by our customers. Download the anchor updates through the Sewio Partner Portal. - Find the installed firmware version in RTLS Studio > RTLS Manager > Anchor Summary. - For RTLS Studio 2.2 and lower: follow the instructions. - For RTLS Studio 2.3 and higher: follow the instructions. - For anyone interested in the version changes, see the changelog (very technical). Instructions for software updating (RTLS Studio): - Sewio RTLS Studio software updates can only be downloaded by Sewio partners (that's us), not by our customers. Download the anchor updates through the Sewio Partner Portal.  - Follow the Update Guide. - After the update of the RTLS studio software please empty the cash of the web browser via the history settings. View original HubSpot article · HubSpot article 190573052054 · Knowledge Base 187958790447 · Language en · Updated 1748131300652 --- ## When attempting to upload and play an MP4 video in EthoVision XT on a Mac, the software only displayed a black screen URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/when-attempting-to-upload-and-play-an-mp4-video-in-ethovision-xt-on-a-mac-the-software-only-displayed-a-black-screen Chapter: Noldus Knowledge Base When attempting to upload and play an MP4 video in EthoVision XT on a Mac, the software only displayed a black screen.  FAQ – Resolving the Video Display Issue in EthoVision XT Q: Why do my MP4 videos show only a black screen in EthoVision XT on macOS? A: EthoVision XT is not supported on macOS. This incompatibility is the main cause of the black screen. The software is designed to run on Windows. Step-by-step instructions - Switch to a Supported Operating System - Install and run EthoVision XT on a Windows PC. - macOS is not officially supported and may cause playback issues. - Check Video Playback on Windows - Update graphics drivers to the latest version. - If using a laptop with an external monitor, make sure EthoVision is configured to use the correct display and graphics adapter. - Ensure your system meets EthoVision XT’s hardware specifications. - Verify Video Format - EthoVision XT supports standard MP4 files (commonly H.264 encoded). - If playback still fails, convert the video to a supported format/codec (e.g., H.264 MP4) using a trusted video converter. - Maintain Video Confidentiality - All troubleshooting can be done locally on your machine. - You do not need to share or upload your video files, ensuring sensitive data stays confidential. Following these steps should resolve the black screen issue and allow videos to play properly in EthoVision XT.   View original HubSpot article · HubSpot article 194934580028 · Knowledge Base 187958790447 · Language en · Updated 1755876911770 --- ## When charging the tags, the charging pad status LED starts flashing red after some time. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/when-charging-the-tags-the-charging-pad-status-led-starts-flashing-red-after-some-time Chapter: Noldus Knowledge Base First: - Check that the customer uses a Qi-compatible charging pad.  - If the charger is a Samsung EP-P3105, send them the User Manual [link] to verify the LED blinking status. A flashing red LED means ‘not charging properly due to a general error’. Recommend this: - Charging in a ventilated, cool room. High temperatures can be a problem if the charger and/or tag turn hot. If charging in a ventilated, cool room is not possible, you may recommend a workaround by placing a timer between mains and the charger, and apply cooldown intervals. - Not to place the pad on a metal surface. - If multiple chargers are used, to leave 20-30cm space between charging pads. If still no success, check the tag status: - Use an anti-static mat when opening tag enclosures. - Check if the tag electronic board is placed correctly in the enclosure: The charging coil should face the flat side of the enclosure. This way the charging coil is closest to the tag outside and charging should proceed without problems. - Check if the tag enclosures are not deformed. - Check if the on/off button on the tag electronics board does not touch the enclosure. The button should be slightly tapered. - If all of the above was unsuccessful: RMA. View original HubSpot article · HubSpot article 190573052059 · Knowledge Base 187958790447 · Language en · Updated 1748131678543 --- ## When should I use "Activity Analysis" in EthoVision XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/when-should-i-use-activity-analysis-in-ethovision-xt Chapter: Noldus Knowledge Base If you have EthoVision XT 9 or newer, you will see an option to add Activity Analysis in the Experiment Settings. This is an optional feature that does not track the subject(s) per se, but rather tracks pixel changes across the entire arena. It is intended to be used when the researcher in interested in freezing or inactivity, such as fear conditioning, tail suspension, Porsolt forced swim test, sleeping, etc. This must also be configured in your Detection Settings.See here for more information. View original HubSpot article · HubSpot article 190573052285 · Knowledge Base 187958790447 · Language en · Updated 1748145713679 --- ## When using the Baby model of FaceReader 9 the automatic analysis did not detect any negative valences across the whole dataset. URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/when-using-the-baby-model-of-facereader-9-the-automatic-analysis-did-not-detect-any-negative-valences-across-the-whole-dataset Chapter: Noldus Knowledge Base When using the Baby model in the first release of FaceReader 9, the automatic analysis did not detect any negative valences across the whole dataset. This resulted in a misclassification of negative and very negative affect as positive valence. Fortunately the video does not need to be re-analyzed. This is because the valence can be calculated directly from the action units. This issue has now been fixed in FaceReader 9.0.17 which can be downloaded via MyNoldus. View original HubSpot article · HubSpot article 190573052207 · Knowledge Base 187958790447 · Language en · Updated 1748138974363 --- ## Where can I find license info in MyNoldus? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/where-can-i-find-license-info-in-mynoldus Chapter: Noldus Knowledge Base You can find all info on the licenses linked to you or your team by clicking on your name in the upper right corner of MyNoldus. Now click on Licenses and Contracts in the dropdown list and the information will be shown to you.This information is available only to the registered user of the license(s). Others will have access to MyNoldus including downloads, but will not see the license information. View original HubSpot article · HubSpot article 190556076906 · Knowledge Base 187958790447 · Language en · Updated 1748146041634 --- ## Where can i find technical information on UWB tracking hardware from Sewio? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/where-can-i-find-technical-information-on-uwb-tracking-hardware-from-sewio Chapter: Noldus Knowledge Base The TrackLab team will share the most essential topics on this MyNoldus platform. This information is restricted to the Sewio hardware that we use in TrackLab setups. Find more detailed information on the Sewio documentation portal. View original HubSpot article · HubSpot article 190573052073 · Knowledge Base 187958790447 · Language en · Updated 1748132436656 --- ## Which UWB tag sleep mode settings do we recommend? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/which-uwb-tag-sleep-mode-settings-do-we-recommend Chapter: Noldus Knowledge Base The 'sleep mode' allows for reducing tag battery energy expenditure. It kicks in when the subject is not moving which will put the tag in sleep mode. It will 'awake' again if the accelerometer sensor on the tag detects movement again. We recommend the following defaults: - Sleep mode enabled. - Sleep threshold set to “low” (the tag will go to ‘sleep’ fast). - Sleep refresh rate set to 5000ms. In TrackLab, a tag that is not detected for 30 seconds will becomes unvisible. By setting the 'Sleep Refresh Rate' to 5 seconds, the tag will always remain visible, and you can still save a lot of energy. Notes: - We are still in the process of gaining experience with the effect of the sleep mode, depending the typical animal type or human movement behavior patterns. - The Sewio default settings deviate from our recommended settings. It has the sleep refresh rate set to ‘0’. - Do not use a "sleep refresh rate" of 30000 ms or higher. That would result in the tag becoming invisible in TrackLab. - The sleep mode does not affect the result of most analysis parameters. The R&D team are performing investigations to rule out possible small implications. - For more details, see the Sewio documentation on Tag Settings.   View original HubSpot article · HubSpot article 190573052180 · Knowledge Base 187958790447 · Language en · Updated 1748137172609 --- ## Why are my trials ending at an exact time (e.g., 10 minutes) even though my Trial Control Settings are set for longer? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/why-are-my-trials-ending-at-an-exact-time-eg-10-minutes-even-though-my-trial-control-settings-are-set-for-longer Chapter: Noldus Knowledge Base Solution: Uncheck the “Maximum Trial Duration” box in the Trial Control Settings. If you are not getting any warning message when the trial ends (such as the error message “Trial duration does not correspond with system time”), then the likely issue is that you have the “Maximum Trial Duration” box checked in the Trial Control Settings. The purpose of that box is to end the trial independent of anything in the Trial Control Settings so that a trial does not exceed a certain amount of time that would be beyond the limits of what is expected.  Given its independence from any condition in the Trial Control Settings, a clock for the specified time will start once the “Start trial” button is clicked in Acquisition and the trial will end once the time is reached.   Note: Any Trial Control Settings that have been used to acquire trials will be “locked” and cannot be altered.  Thus, if you would like to run more trials in the same experiment with the same Trial Control Setting, but with the “Maximum Trial Duration” box unchecked, right-click on the Trial Control Settings you used and select “Duplicate”.  That will make an exact “unlocked” copy.  You can then uncheck that box and then use those Trial Control Settings for any future trials.   View original HubSpot article · HubSpot article 190573052063 · Knowledge Base 187958790447 · Language en · Updated 1748132003661 --- ## Why can't I start acquisition in EthoVision XT? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/why-cant-i-start-acquisition-in-ethovision-xt Chapter: Noldus Knowledge Base Acquisition cannot be started if the license is not present, there are no planned trials in the trial list, or if the settings are incomplete. License Not Present Acquisition requires a license, either in the form of a hardware license key (any version) or a software-based license (only in EthoVision XT 16 or newer). If using a hardware license key, it must be plugged in and detected. Without the key, you can open EthoVision but you will receive a warning that "no valid hardware key is detected." Clicking through that warning will permit you to open EthoVision and use any of the analysis features, but not acquire new trials (whether live or from video). If the hardware license key is plugged in but you still get the message "no valid hardware key is detected", please download this file: HASP 8.13 Run or double-click the downloaded file to install the driver. No Planned Trials In Trial List The Start Trial button will only appear if there are planned trials in the trial list. You can add trials either by going to the Trial List and clicking the Add Trials button, or click the Add Trial button in Acquisition (it looks like a + sign, right next to the Start Trial button). Trial List Incomplete If you have selected the option to Track all planned trials in the acquisition, and are tracking from video files, a video file must be specified for every trial listed in the trial list. Either fill in a video for each trial, remove the trials with no video, or in the acquisition switch to Track next planned trial. Settings Are Incomplete Trials cannot be started if the arena settings, detection settings, or trial control settings are incomplete or invalid. If you are working from video files, acquisition cannot begin if no video is selected, or if the selected video has been moved or deleted. In the acquisition, click the ... button next to Video to select a new video. You can check the arena settings by opening the arena settings and clicking Validate Setup. If there are any issues, a popup message will notify you. In the Trial Control Settings, check that there is a path, following the arrows, from the Rule Begin to the Rule End box. If you cannot reach the Rule End box by following the arrows, the settings are not complete. You can add arrows if needed by clicking and dragging from the center of one box to the center of the next. If you are using the Behavior Recognition Module, make sure that you have completed the Behavior Recognition settings in the Detection Settings. View original HubSpot article · HubSpot article 190573052080 · Knowledge Base 187958790447 · Language en · Updated 1748133242687 --- ## Why did i loose TeamViewer access to the customer PC? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/why-did-i-loose-teamviewer-access-to-the-customer-pc Chapter: Noldus Knowledge Base Possible causes: - The customer has changed the password. - The customer rebooted the PC. By default, TeamViewer resets the password when the PC is rebooted. Solution: - Ask the customer to set a 'permanent password' and to share it with you. - Instructions for setting a permanent password: (a) Open the main window of the remote TeamViewer client, (b) go to "Extras > Options > Security > Personal password" and (c) Enter a password of your (=customer) choice, enter it once again to confirm it and (d) click on "OK" at the bottom of the window to save your choices. View original HubSpot article · HubSpot article 190556076865 · Knowledge Base 187958790447 · Language en · Updated 1748137890694 --- ## Why didn't my upgrade code work? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/why-didnt-my-upgrade-code-work Chapter: Noldus Knowledge Base Upgrade codes are created for a specific version of the software, and must be entered in that version (e.g. The Observer XT 14.1). If you have a different version, please install the correct version or contact Noldus for a new code.If possible, copy and paste the code. If you are typing it in, please note that upgrade codes never contain the letters O, I, or L, but they may contain the numeric digits zero and one. View original HubSpot article · HubSpot article 190556076901 · Knowledge Base 187958790447 · Language en · Updated 1748145317653 --- ## Why is the sum/total of the cumulative time for all of my zones greater than the trial time? URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/why-is-the-sumtotal-of-the-cumulative-time-for-all-of-my-zones-greater-than-the-trial-time Chapter: Noldus Knowledge Base The most common reasons for zones not adding up to the total trial time are: - The subject was not tracked for the entire trial, so there are periods when it was not counted in any zone. - The zones do not cover the entire arena so the animal was sometimes not in any zone, or the zones overlap, so the animal was sometimes in more than one zone at a time. - Use of the "Zone exit threshold" permitted the animal to be counted in multiple zones at once. Each of these possibilities are described in detail below. The subject was not tracked for the entire trial If the animal disappears from view or the detection settings are not adequate to detect the animal, there may be samples during which the animal's location was not known. If the animal's location was unknown for just a sample or two, it will continue to be counted in the zone it was last seen in. However, if it is missing for three or more consecutive samples, it will not be counted in any zones until it is detected again. During a trial, the number of samples during which the animal was not detected is displayed as "Subject not found." Normally this value should be very low: You can also check the number of such samples in the Trial List. If the Subject Not Found column is not displayed, click Show/Hide in the upper right corner, then Variables, and check the checkbox for Subject Not Found. If the number of such samples is very high, it may be best to improve the detection settings and retrack from the video (if one was recorded). If it is small but you wish it to be zero, you can either interpolate the missing samples in the Track Editor, or in many cases enabling the Track Smoothing option in the Track Smoothing Profile will fill in these samples (as long as the number of consecutive missing points is small). For more information about missing samples, see Missing data in EthoVision XT. If there are areas where the animal is expected to disappear from view (e.g., an opaque shelter), use Hidden Zones so that EthoVision knows to count the animal as being in that hidden zone rather than marking it as missing.   The zones do not cover the entire arena, or zones overlap The simplest and cleanest way to set up zones is to use the various drawing tools to divide the arena into zones, labeling each space: In this example, lines have been drawn across the arena to divide it into four separate quadrants. Every point is in one of the four zones. If you use the drawing tools to draw a closed shape (e.g., a rectangle or circle), and "Auto-Label Zone" is selected, EthoVision will prompt you to label that space as a zone. But you can also label spaces outside of those shapes. Any line or shape simply divides the space, and each resulting section can be a zone. You do not need to draw a new shape for each zone. For example, here we have drawn a rectangle encompassing half the arena and added a second zone label (using the Add Zone Label button) to label the rest: While you could draw two separate rectangles, if their edges are not perfectly aligned, you may create a space between them which is not part of either zone. Therefore the time spent in the two zones may not add up to the duration of the entire trial. In both of the above examples, all the zones were included in a single Zone Group. You can think of a zone group as a single piece of paper upon which you draw zones. Any lines or shapes divide up that space and the resulting areas can be labeled as zones. Sometimes, though, it is desirable to have zones which overlap. For example, you might wish to have center and perimeter zones, and also have quadrants. To permit this, you can use multiple zone groups. Just as if they were separate pieces of paper, lines drawn in different zone groups do not divide the space for the other zone groups. It can sometimes be confusing to tell which zone group you are working on or which lines divide which zones. In order to see the zones more clearly, uncheck the View checkbox in the list of zones on the right for any zone group you are not presently working on. This will show only the items you have checked so you can clearly see what is going on. If there are any discrepancies in the results between the zone you think the animal should be in vs. how they are being counted, check each zone group individually this way. The issue will often be obvious as soon as you hide the other zone groups. Sometimes zone groups are misused, especially in older versions of EthoVision in which the option to add zone groups was more prominent. Here's an example of how that looks, where a separate zone group was added for each zone. Because the zones are in different zone groups, two separate circles were drawn, one for the center zone and one for the perimeter zone. If these circles are not exactly the same, you may either get a gap between the two zones (in this example, there is a gap shown in orange) or the two zones may overlap. In either case, the time in the two zones will not add up to the total time in the arena. This could have been avoided by putting both zones in the same zone group, so the exact same circle could have been used to define both of them, ensuring a perfect match.   The “Zone exit threshold” permitted the animal to be counted in multiple zones at once If you are using EthoVision XT version 12 or higher, there is an option in your “In Zone” dependent variable to include a buffer for your “zone exit threshold”.      The purpose of this is to allow a buffer zone on a zone’s edge so that small body movements aren’t counted as an undesired zone exit and subsequent re-entry.   For example, in the circular zone below, if the “zone exit threshold” is set to 0.00 cm (upper diagram), then the movement of the body point indicated by the line will be counted as two zone visits.  However, if the “zone exit threshold” is set to something higher (e.g., 0.5 cm; lower diagram), then the small body point exit and re-entry will not be counted and the event will only be counted as one zone visit.  Note that the threshold only applies to zone exits and leaves zone entry conditions unaffected. If you have the “zone exit threshold” set to something greater than 0.00 cm, then a body point just outside a zone will be counted as being in that zone and the immediate adjacent zone at the same time.  For example, in a Morris Water Maze experiment with four quadrants where the “zone exit threshold” is set to 1 cm, the center point of an animal leaving the NE quadrant and entering the NW quadrant will be counted as being in both quadrants at the same time until the animal is more than 1 cm from the edge of the NE quadrant.  As such, the sum/total of the cumulative duration for all four quadrants will be greater than the trial time because the zones are no longer mutually exclusive.  Setting the “Zone exit threshold” to 0.00 cm will resolve this issue.   View original HubSpot article · HubSpot article 190573052257 · Knowledge Base 187958790447 · Language en · Updated 1748143010627 --- ## Why runs that seemed to meet the defined criteria in CatWalk XT were being marked as non‑compliant URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/why-runs-that-seemed-to-meet-the-defined-criteria-in-catwalk-xt-were-being-marked-as-noncompliant Chapter: Noldus Knowledge Base Resolution: Compliant runs must satisfy all run criteria (duration between minimum and maximum, speed variation within range if enabled). Runs become non‑compliant if any criterion is not met. Users should start the acquisition once, place the animal on the walkway, and allow the system to automatically acquire runs. Manually stopping a run causes it to be marked ‘user aborted,’ making it non‑compliant if the option to discard aborted runs is selected. If runs exceed the maximum duration, adjust walkway definition, background image and camera gain (6–20) to avoid mis‑detection. Don’t include dark areas in the walkway, snap a new background, and adjust gain if noise causes false detections. FAQ and Step-by-Step Instructions What makes a run ‘compliant’ in CatWalk XT? - The run duration is longer than the minimum and shorter than the maximum specified in your run criteria. - If speed variation checking is enabled, the variation must be within the allowed range. - The run is not manually aborted by the user. Why are some runs marked as non‑compliant even when they look correct? - Manual stop – If you press the stop record button, the run is saved but marked ‘user aborted’ and may be non‑compliant depending on your settings. - Maximum duration exceeded – This can happen if the system still detects something in the walkway after the animal has left; adjust the walkway definition and detection settings. Do I need to manually start and stop each run? No. Follow these steps for proper acquisition: - Start the acquisition once, then place the animal on the walkway. - CatWalk XT automatically detects when the animal enters the field of view and records the run. - Allow the system to stop automatically when the animal leaves. Avoid stopping manually unless necessary. - Repeat for each crossing; the system will acquire individual runs without manual intervention. How can I prevent false detection or non‑compliance? -  **Check walkway definition** – Make sure only the walkway surface is defined; exclude dark areas like walls or edges. -  **Snap a new background** – If the background image has changed, use the ‘Snap Background’ button to update it. -  **Adjust camera gain** – Keep gain between 6 and 20. High gain introduces noise; open the camera aperture and redo detection settings if necessary. -  **Let the system manage the run** – Avoid manually stopping runs to ensure they are recorded and evaluated automatically. When should I contact support? - If you have checked the walkway definition, background and camera settings and runs are still incorrectly labelled, contact technical support with details of your settings and a sample video for further assistance. View original HubSpot article · HubSpot article 194772878931 · Knowledge Base 187958790447 · Language en · Updated 1755629992871 --- ## Will deactivating the license on the old computer delete experiments or projects saved on that machine URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/will-deactivating-the-license-on-the-old-computer-delete-experiments-or-projects-saved-on-that-machine Chapter: Noldus Knowledge Base FAQ and Step-by-Step Instructions Will my EthoVision XT experiments be deleted when I deactivate my license on the current PC? - No. Deactivating the license only removes the permission to run EthoVision XT. It does not delete experiments or transfer them; your data remains on the old PC. How do I move my EthoVision XT license to a new computer? - On the old PC, open EthoVision XT’s Help menu, and chose the option to deactivate the software license. - Download and install EthoVision XT on the new PC. - Launch EthoVision XT on the new PC and activate the license using your software activation code (license number). - If needed, copy your experiment project folders from the old PC to the new PC via an external drive or network share. - The old PC can still open and analyze experiment data without an active license for post-acquisition analysis. How do I back up my experiment data? - Copy your complete experiment project folder to an external drive or network share. Be sure that all contents are copied and move over successfully when doing so. - Alternatively, create a Project Backup by going to the File menu and choosing ‘Make a Backup…’. This will create a zipped .EVZ file that makes the project easier to move. Note, the backup file needs to be restored before being able to access the experiment again. Can I run EthoVision XT on multiple computers simultaneously with one software-based license? - Unless your software-based license includes multiple seats, an access code would be considered single-use. You must deactivate it on one computer before activating it on another. Only one active instance is permitted at a time. View original HubSpot article · HubSpot article 194772883781 · Knowledge Base 187958790447 · Language en · Updated 1755626280863 --- ## Windows 10 power settings for EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/windows-10-power-settings-for-ethovision-xt Chapter: Noldus Knowledge Base With default Windows settings, Windows may shut down during long unattended recordings (e.g. going into sleep or standby mode), and when the computer is turned off it may go into sleep/standby instead of turning off, which allows memory issues to accumulate rather than cleaning the slate for a new session. Some hardware may not restart properly after sleep/standy, especially Picolo framegrabbers for video capture from analog cameras. The settings listed below will prevent all of these issues and improve performance. Note that these changes will require an administrative password for the computer. - Go to the Start menu, click the Settings gear, then pick System: - Click “Power & Sleep” on the left: - Click “Additional power settings” on the right: - This will display “Choose or customize a power plan.” Click “Choose what the power buttons do” on the left: - You will see the following settings. Click “Change settings that are currently unavailable” at the top. You will be prompted for an administrative password. - Pick “Shut Down” (or “Do nothing”) options rather than “Sleep”, and uncheck the Sleep and Hibernate checkboxes.  - Uncheck the “Turn on fast startup” option. - Click Save Changes. You will return to the “Choose or customize a power plan” page.  - Click “Change plan settings” next to the selected power plan. For any computer that will be recording unattended, change the “Put the computer to sleep” option to “Never.” - Then click “Change advanced power settings.” You will see this window with a variety of options. Click the + sign next to any option to expand it. - Under “Hard disk”, under “Turn off hard disk” click the time highlighted in blue (if it is not already set to “Never”) and enter 0 (this indicates “Never”). - Then click OK to exit. View original HubSpot article · HubSpot article 190573052084 · Knowledge Base 187958790447 · Language en · Updated 1748133555565 --- ## Working temperature of an Axis M1145-L URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/working-temperature-of-an-axis-m1145-l Chapter: Noldus Knowledge Base The temperature working range of the cameras The Axis M1145-L network camera can be used in the following operating conditions: - 0 °C to 50 °C (32 °F to 122 °F) - Humidity 20-80% RH (non-condensing) View original HubSpot article · HubSpot article 190556076870 · Knowledge Base 187958790447 · Language en · Updated 1748138667649 --- ## Z-axis compensation not in effect in Sewio (RTLS Studio), actual height values are generated URL: https://noldus.com/shared/resources/book/noldus-customer-agent-data/chapter/noldus-knowledge-base/page/z-axis-compensation-not-in-effect-in-sewio-rtls-studio-actual-height-values-are-generated Chapter: Noldus Knowledge Base RTLS Studio still generates actual height values for the Z-coordinate, even though Z-axis compensation is set. This is likely due to the parameter "Set Boundaries According To Anchors" being set to "No". Set it to "Yes" instead to solve the issue. View original HubSpot article · HubSpot article 190573052210 · Knowledge Base 187958790447 · Language en · Updated 1748139100677 --- ## CatWalk Parameters Biological Significance - - Affected Hind Paw (31%) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-parameters-biological-significance-affected-hind-paw-31 Chapter: CatWalk XT - Affected Hind Paw (31%): Ferland et al. (2011) Pharmacology, Biochemistry and Behavior 97: 603–610; Pinho et al. (2011) The Journal of Pain, 12(2): 194-204; Angeby-Möller et al. (2008), Journal of Neuroscience Methods 174: 1–9 - Related to the Severity of SCI: Hamers et al. (2006), Journal of Neurotrauma, 23: 537-548; Kloos et al. (2005), Experimental Neurology, 191: 251-265 - Affected Hind Paw (SFI): Costa et al. (2009). International Review of Neurobiology, 87: 127-139; Bozkurt et al. (2011), Behavioural Brain Research, 219: 55-62 - For Ataxic Animals: Cendelin et al. (2010), Behavioural Brain Research, 210: 8–15 - For Girdle Paws in Treated Animals: Encarnacion et al. (2011), Journal of Neuroscience Methods, 196: 247-257 - For Transgenic HD Animals: Vandenputte et al. (2010), BMC Neuroscience, 11: 92-103; Westin et al. (2012), Behavioural Brain Research, 226: 519–528 Source: CatWalk Parameters Biological Significance, Noldus Information Technology --- ## CatWalk XT - Analyze Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-analyze-data Chapter: CatWalk XT 7 - Analyze Data In a Data Segmentation profile you can select a part of a classified run with a specific average speed range and speed variation. In a Parameter profile you can select specific parameters for analysis and export. You can view the run, 3D and 2D Footprint Intensities, and Footfall Patterns. Here you can view the tables with calculated statistics. Here you can view run statistics grouped by treatment group and time point, and their corresponding charts. A list of research areas where CatWalk XT is an important tool, with special focus on the analysis parameters used by researchers. 7 - Analyze Data 7.1 Select The Data Using a Data Segmentation profile, you can select one part from each classified run that complies with three criteria (the minimum number of consecutive steps with a specific speed range and maximum allowed speed variation). This is useful, for example, if you have a run in which the animal briefly stopped at the beginning of a run but then continued to walk normally. You can automatically select only the 'good' part of the run for analysis and export with a Data Segmentation profile. Data Segmentation Profiles Default data segmentation profile The default Data Segmentation profile is labeled All Data. It cannot be deleted. Procedure - Do one of the following: In the Profiles Explorer, right-click Data Segmentation Profiles and select Add New Profile. Choose Profiles > Data Segmentation Profile > New. 2. Enter the name of the new profile and click OK. 3. In the Profile window, under Select Data, you can set the following: Minimum number of consecutive steps per run - Only the part of the run with the minimum number of consecutive steps which complies with the next two parameters is selected. We advise you to use at least 10 consecutive steps. See also what speed or variation should i choose? on page 95. Average speed should range from (in distance unit/second) - Only the part of the run within the set speed range is selected. The Average Speed is based on the Body Speed of selected steps in a run. The Body Speed for each step cycle is calculated by dividing the distance that animal's body has traveled from one initial contact to the next by the time it took to travel that distance. The Average Speed is different from the Run Average Speed (shown in the Acquisition and Classification screens), which is the average speed of the animal's body during the whole recorded run. Maximum allowed speed variation (in percent) - Only the steps in a run within the set maximum allowed speed variation are selected. 7 - Analyze Data Example - The Average Speed of a run is 22.0 cm/s. The speed of a step cycle of the left front paw in this run is 29.07 cm/sec. The variation then is: ([29.07-22.0] / 22.0) * 100% = 32.1%. Exclude non-compliant runs - When you select this option, runs not compliant with the run criteria in the Experiment Settings are excluded from the data selection. Exclude partially classified runs - When you select this option, runs which have not been completely classified are excluded from the data selection. Selected Data Overview tab Shows the result of your data segmentation. The sheet (on the left) shows, per treatment group and time point, the number of Selected Animals / Runs / Steps, the Total number of Animals / Runs / Steps in the experiment and the Percentage of selected Animals / Runs / Steps. You can choose whether you want to see the selected Animals, Runs or Steps by selecting the corresponding option at the bottom. The chart (on the right) is a graphical representation of the selected data. You can choose whether you want time points or treatment groups displayed on the X-axis, by selecting the corresponding option at the bottom. Figure 7.1 Part of the Data Segmentation Profile window. In this example, the Selected Data Overview sheet shows the selected Steps. On the right is the graphical representation of the selection. 7 - Analyze Data Complete Data Overview tab In the matrix on the left, the average speed intervals (1 to 10 cm/sec, 1 to 20 cm, 1 to 30 cm/ sec, etc, with centimeters as distance unit) are displayed on rows. The speed variation is displayed in 10%-intervals on columns. Each cell in the matrix shows the resulting number of steps for a specific combination of Average Speed and Maximum Variation in speed based on the Minimum number of consecutive steps you selected. In the Complete Data Overview, you can only change the Minimum number of consecutive steps per run. If you do this, you need to click the Calculate Complete Data Overview button at the bottom to re-calculate the number of selected steps. The 3D-chart shows: On the X-axis: the Average speed range intervals. On the Y-axis, the Maximum allowed speed variation intervals. On the Z-axis, the resulting number of steps per speed / speed variation interval. Figure 7.2 The 3D-chart in the Complete Data Overview tab of a Data Segmentation profile. In this example, the majority of the steps in the runs of this experiment have an Average Speed > 40 cm/s and a Maximum speed variation > 90%. 7 - Analyze Data What Speed Or Variation Should I Choose? Minimum number of consecutive steps per run - We recommend to select at least 10 consecutive steps. This generally corresponds to 1 step cycle for each paw (that is, each paw is placed twice on the glass plate). If you select a lower number, a paw might have been placed only once, which means that for this paw some parameters (for example, Swing or Stride Length) cannot be calculated. Average speed should range from ... to ... ([Distance unit]/second) - In the Complete Data Overview tab, the 3D-chart (see Figure 7.2) shows the number of steps in the different Average Speed intervals; this helps you in determining the Average Speed range for your data. Select the widest average speed range possible for your runs if the Average Speed is different for different treatment groups (for example, the experimental animals are on average slower than the control animals). In the 3D-chart in the Complete Data Overview tab, steps with a maximum speed higher than 120 cm/sec (or an equivalent speed in a different Distance unit) are not displayed. However, you can select a maximum average speed of up to 300 cm/sec. Maximum allowed speed variation (percent) - By selecting a low or high speed variation, you allow, respectively, small and large differences in average speed for a run. Example - You have a run with an Average Speed of 25 cm/sec. You have set the Maximum allowed speed variation to 20 percent. The variation is calculated as follows: ([Step speed - Average Speed] / Average Speed) * 100 = speed variation (%). With the values in this example, this means that the step speed can range between 20 and 30 cm/ sec. If you set the Maximum allowed speed variation to 60 percent, the step speed can range between 10 and 40 cm/sec. Check The Data After Segmentation While data segmentation is a powerful tool to remove outliers and generate more homogeneous samples which facilitate analysis, is not free of risks. The following figure shows a typical CatWalk XT visualization of paw prints. The subject under study makes a small jump (indicated with the arrow in the Timing view). This jump is typical of the studied phenotype, and should be in the data. However, data segmentation may remove significant part of interesting data because based on increased variation in speed or a number of consecutive regular steps. 7 - Analyze Data Thus, always check the data resulting from data segmentation before running the analysis. 7.2 Select The Analysis Parameters You can select specific parameters with Parameter profiles. Only selected parameters from the Paw Statistics (see page 106) and Phase Lags (see page 123 and page 126) are displayed in the Run Statistics and in the Group Statistics and Charts, and exported to an Excel file. The default Parameter profile is labeled All Parameters and cannot be edited nor deleted. 1. To create a new Parameter profile, do one of the following: In the Profiles Explorer, right-click Parameter Profiles and select Add New Profile. Choose Profiles > Parameter Profile > New. 2. Type in the name of the Parameter profile and click OK. 3. In the Parameter profile window, you can select or de-select the following: Paws - Select the paws for which you want to display/export the Paw Statistics Parameters. Parameters - Select the Paw Statistics Parameters you want to display/export. Phase Dispersions - Select the paw combinations (Diagonal, Girdle, Ipsilateral) for which you want to calculate Phase Dispersions (see page 123). Couplings - Select the paw combinations (Diagonal, Girdle, Ipsilateral) for which you want to calculate Couplings (page 126). 4. Click OK to make this new Parameter profile active. 7 - Analyze Data 7.3 Visualize The Runs Procedure Open the Visualization screen In the Experiment Tasks window, select View Run Visualizations. Choose Analyze > View Run Visualizations. In the Experiment Explorer: - Right-click a trial and select View Run Visualizations. This option is only available, when the trial contains one or more (partially) classified runs. - Right-click a Run and select View Run Visualizations. This option is only available when the run has been (partially) classified. You can export the Visualizations. See export the run visualizations on page 160. Visualize a run - Under Trial & Run Selection, select a trial and one of the runs in that trial, or click the Previous/Next button to navigate between trials and runs. - Replay the run (as described in Review the runs during classification on page 78). - Under Visualizations, you can view: 3D Footprint Intensities (see below). 2D Footprint Intensities (see page 99). Footfall Patterns (see page 100). Paws which have not been selected in the currently active Data Segmentation profile, are displayed in gray in the Video window and are not displayed in any of the Visualizations (3D/ 2D Footprint Intensities, Footfall Patterns). You can select another Data Segmentation profile by right-clicking it and selecting Set as Active. 3d Footprint Intensities Click on the 3D Footprint Intensities tab. The 3D Footprint Intensities tab plots the print intensities of the 4 paws for each individual video frame in which the paws has contact with the glass plate in a 3D-chart. The intensities 7 - Analyze Data range from 0 to 255. The color range used in the 3D-chart is the same as is used in the False Color mode of the footprints in the Classification print view (see page 79). A 3D chart can be rotated in all directions: click a chart, keep the mouse button pressed and drag to rotate the chart. To reset all charts to the original orientation, open another item in the experiment (for example the Trial List) and re-open the Visualization. Figure 7.3 The 3D Footprint Intensities charts. In this example, the Video window shows two paws, right hind (RH) and left front (LF) in gray, which means that these paws were not selected in the current Data Segmentation profile. As a result, these paws are not displayed in the 3D chart. 7 - Analyze Data 2d Footprint Intensities Click on the 2D Footprint Intensities tab. The 2D Footprint Intensities tab plots the print intensities of each paw print in a single image. The solid red line represents the maximum intensity in a frame, the filled, colored area under the red line represents the mean intensity of the paw (see Figure 7.4). The 2D Footprint Intensities plot displays the prints from left to right irrespective of the animal's actual walking direction. When you right-click the 2D Footprint Intensities plot, you can select on of two options: Save to File. This saves the 2D Footprint Intensities plot to an image file (*.png). Copy to Clipboard. This copies the 2D Footprint Intensities plot to the clipboard. Figure 7.4 The 2D Footprint Intensities. The position of the vertical, dotted hairline corresponds to the position of the animal in the Video window. Left: All steps are selected (Default data profile). Right: Some steps have been excluded in the current Data Segmentation profile and are, therefore, not displayed in the 2D chart. 7 - Analyze Data Footfall Patterns Click the Footfall Patterns tab. The Footfall Patterns diagram shows the order in which the paws (represented by colored dots) were placed on the glass plate. The Footfall Patterns are displayed from left to right, irrespective of the animal's actual walking direction. The colors of the dots indicate the following: Orange - Not taken into account Orange dots indicate paw placements that are not taken into account when determining a footfall pattern. This often occurs to the first and last paw prints. example In the figure below, the first paw placement, LF, occurs again within a 4-paw sequence (see the fourth dot in the run). A pattern like LF-LH-RF-LF is clearly not a footfall pattern. Therefore, the LF paw placement is ignored and the software starts looking for patterns from the next paw placement. In this case, the next paw placement is LH, which is followed by RF-LF-RH. Together, they form a recognized footfall pattern, indicated with CA. Figure 7.5 The Footfall Patterns diagram (bottom). The dots with the dotted circles correspond to the paws displayed in the Video window (top). 7 - Analyze Data Similarly, paw placements at the end of the run can be excluded. After the last valid pattern LH-RF-LF-RH has been found (see the last CA in the run), three paw placements are left: RF, LH and RH. They form an incomplete pattern, which is excluded from the results. Blue - Start of a pattern Paws at the begin of a recognized footfall pattern. It is always followed by three green dots. Green - Part of a pattern Paws that are at the second, third and fourth place in a recognized footfall pattern. Purple - Not part of a pattern These paw placements are determined as not being part of a footfall pattern. They are usually in the middle of the run, between two valid patterns. In the following example, the paw LF is repeated within a sequence of 4 paw placements (the first and the fourth are indicated with arrows). The sequence LF-LH-RF-LF, indicated with the dotted line rectangle, is not recognized as a valid pattern. So the paw placement LF is marked with a Not part of a pattern dot and the software resumes searching from the next paw placement, in this case LH, which is detected as the start of a CA pattern (LH-RF-LF-RH). 7 - Analyze Data How Footfall patterns are labeled Consider a generic footfall pattern found in a run, like LH-RF-LF-RH in the figure below. The starting paw placement LH is marked with a blue dot. Now imagine that this pattern LH-RF-LF-RH is repeated immediately after the first one: LH-RF-LF-RH-LH-RF-LF-RH. Now we can recognize more patterns, for example: If you start from the second placement, RF: RF-LF-RH-LH; If you start from the third placement, LF: LF-RH-LH-RF; If you start from the fourth placement, RH: RH-LH-RF-LF; 7 - Analyze Data etc. This "family" of patterns is marked with the label CA (Cruciate A). The grouping of patterns into "families" is also the reason why Catwalk XT reports only 6 patterns (CA, CB, AA, AB, RA, RB) out of a total of 24 possible combinations. This makes classification independent on which paw comes first in the beginning of a run. The predefined footfall pattern labels are (note that any of the paw prints within a sequence can be the starting point, marked with the blue dot): For Cruciate patterns: - CA, for the paw sequence RF-LF-RH-LH. - CB, for LF-RF-LH-RH. For Alternate patterns: - AA, for RF-RH-LF-LH. - AB, for LF-RH-RF-LH. For Rotate patterns: - RA, for RF-LF-LH-RH. - RB, for LF-RF-RH-LH. When initial contact of two paws coincides in a frame, the paw with the largest surface area in this frame is considered to have been placed first. In the unlikely event that the surface areas of these paws are equal, the following order of placement is used: LF-LH-RF-RH. Paws that are currently visible in the Video window are marked with a dotted circle in the Footfall Patterns diagram (see Figure 7.5). Export the visualizations Right-click the Footfall Patterns diagram and choose one of the two options: Save to File. This saves the Footfall Patterns diagram to an image file (*.png). Copy to Clipboard. This copies the Footfall Patterns diagram to the clipboard. See also The Regularity Index (%) on page 116. All statistics of Step sequence on page 115. 7 - Analyze Data 7.4 Run Statistics Procedure - Do one of the following: Choose Analyze > View Run Statistics. In the Experiment Explorer, right-click a trial/run and select View Run Statistics. This option is only available, when the trial contains one or more (partially) classified runs. - If you want to see the Run Statistics of another trial or run, under Trial & Run Selection, select a trial and a run, or click the Previous/Next button to navigate to that trial and run. Under Views, the Print View and the Timing View of the selected run are displayed. 3. Under Statistics, click on one of the tabs to view the corresponding parameter sheet and their statistics. All tabs and their parameters are described below. Notes All sheets contain calibrated values, displayed in the Distance Unit selected in the Preferences. By right-clicking individual sheets you can either copy them to the clipboard or export them to Excel. You can export statistics of separate runs (Run Statistics, page 153), grouped per trial (Trial Statistics, page 156) and grouped per experimental group (Group Statistics, page 159). Paw prints displayed in gray are excluded from analysis based on the settings in the Data Segmentation profile currently active. To include all paw prints in the analysis, select the All Data Segmentation profile (page 92). Summary The Summary sheet shows a summary for the following parameters categories: Paw Statistics - The mean and standard deviation (SD) are given for each paw, for the girdle paws (RF-LF and RH-LH) and for the ratio of the girdle paws (RF/LF, LF/RF, RH/LH and LH/RH). See Paw Statistics sheet (page 106) for more details. Step sequence - The total duration of all runs and the total number of categorized footfall patterns are given. For each footfall pattern category the percentage of the total 7 - Analyze Data number of categorized footfall patterns is given. Finally, the Regularity Index is shown, based on all categorized footfall patterns. See Step sequence sheet (page 115) for more details. Base of support - These are the mean values for the front paws and the hind paws. See Base of Support sheet (page 118) for more details. Print positions - These are the mean values for the right paws and the left paws. See Print positions sheet (page 122) for more details. Support - These are the relative duration of contact with the glass plate of all paw combinations. See Support sheet (page 127) for more details. Phase Dispersions - The Mean, AD (Angular deviation), SD (Circular Standard Deviation) and R for all pairs are given, together with the number of Mismatches and occurrences of Anchor-No-Target (ANT), Anchor-Multiple-Targets (AMT) and Target-No-Anchor (TNA). Note that the results are circular statistics. See phase dispersions (page 123) for details. Couplings - The same statistics are given as for Phase dispersions. See Couplings sheet (page 126) for more details. General The General sheet displays the following variables: Name - The name of the run. Start Time - The date and time the run was acquired. Run Duration - The duration of the recorded run. Run Average Speed - The average speed of the recorded run. This is the speed of the animal's body in the recorded run. Run Maximum Variation - The maximum variation in walking speed in the recorded run. Frame Rate - The frame rate of the camera. This is always 100 frames per second (fps). Camera Gain - The value of the Camera Gain from the Detection Settings. Green Intensity Threshold - The value of the Green Intensity Threshold from the Detection Settings. X-Unit (mm/pixel) - The horizontal size of a single pixel. Y-Unit (mm/pixel) - The vertical size of a single pixel. Walkway Length - The length of the defined walkway. Walkway Width - The width of the defined walkway. 7 - Analyze Data Paw Statistics The Paw Statistics sheet displays parameters that are based on individual paw prints. Choose Analyze > View Run Statistics and under Statistics click Paw Statistics. Which paws/parameters are displayed in this sheet depends on the selection in the currently active Parameter profile (displayed in blue and bold in the Experiment Explorer). In the Paw Statistics sheet, when you click one of the paw rows: The Print View highlights the corresponding print. The Timing View shows the corresponding Stand. The Sub Prints View shows the individual prints of the Stand. Paw The Paw label based on the current classification. Initial Contact At (s) Initial Contact At (s) is the time in seconds since the start of the run at which a paw makes contact with the glass plate. Stand (s) (or Stance) (s) Stand (s) or Stance phase is the duration in seconds of contact of a paw with the glass plate. Kloos et al. (2005) (Exp. Neurol. 191: 251-265) showed that rats with a moderate spinal cord injury showed an increase in stand duration of the hind legs compared to pre-operative values. See Application examples > spinal cord injury (page 136). Stand Index Stand Index is a measure for the speed at which the paw loses contact with the glass plate. 7 - Analyze Data The formula for Stand Index is: where: a is derived from y = ax + b, that describes a straight line fitted through the values of Print area between the time of maximum contact and the 90% percentile of the stance duration. The value a should be interpreted as "change in print area per video frame". X0 is the max contact area. frame rate is the camera frame rate (usually 100 frames per second). This correction allows to compare results obtained with different frame rates. Stand Index is therefore a function of the change in print area per second. It is always negative because it describes the decrease in print area as shown in the next figure. The more negative the value, the steeper the slope of the line that describes the reduction in the Print area. This means that the subject lifts its paw more quickly. notes Index should only be used for smoothly moving animals. The formula of Stand Index includes a/X0 to correct for differences in Print area between paws, subjects etc. Stand Index X 0 - frame rate 7 - Analyze Data Stand Index is only calculated when Stand consists of at least 5 frames and there are at least 3 data points between t(Max area) and the 90% percentile. Stand Index is not calculated when two stances were combined (see page 76) and the Max Contact area was in the first stance. If the 90th percentile of the time interval does not correspond to a video frame, the software interpolates the Print area between the two video frames that include that time. Max Contact At (s) Max Contact At (s) is the time in seconds since the start of the run that a paw makes maximum contact with the glass plate. It can be regarded as the point at which the braking phase turns into the propulsion phase during Stand. Max Contact At (%) Max Contact At (%) is Max Contact At (s) relative to Stand of a paw. The formula for Max Contact At (%) is: Max Contact At (%) is used in research on spinal cord injury. For example, Hamers et al. (2001) found an increase in Max Contact At (%) for both front and hind paws in rats. This increase was more marked following a contusion injury compared to a transection injury. Max Contact Area Max Contact Area is the maximum area of a paw that comes into contact with the glass plate. In other words, it is the Print Area at Max Contact at (s). Max Contact Max Intensity This is the maximum intensity at the time of maximum contact of a paw. Intensity ranges from 0 to 255. The intensity of a print depends on the degree of contact between a paw and the glass plate and increases with increasing weight. Therefore, Intensity is a measure of weight put on the glass plate. The parameter is extracted from the print at maximum contact and finding the pixels of highest intensity: Max Contact At Max Contact at (s) - Initial Contact Stand - ·· 7 - Analyze Data The Intensity parameter is used to assess the effects of neuropathic pain, including mechanical allodynia (Vrinten and Hamers, 2003). Vrinten and Hamers found that after a chronic constriction injury, which causes neuropathic pain, Intensity was reduced two weeks after surgery and gradually returned to pre-operative values. This change in Intensity showed a high degree of correlation with Von Frey thresholds. Max Contact Mean Intensity This is the mean Intensity of a paw print at Max Contact. Intensity ranges from 0 to 255. See also Mac Contact Max Intensity. X position X is the position of the center of the paw print at Max Contact in the horizontal (walking) direction. X is the distance in the Distance Unit from the left side of the walkway to the center of the print. 7 - Analyze Data Y position Y is the position of the center of the paw print at Max Contact in vertical direction. Y is the distance in the Distance Unit from the top of the walkway to the center of the print. Print Length Print length is the length (horizontal direction) of the complete print. It is displayed in the Distance Unit selected in the Preferences (see page 44). The complete print is the sum of all contacts with the glass plate, as if the animal's paw would have been inked. Print Width Print Width is the width (vertical direction) of the complete paw print. It is displayed in the Distance Unit you selected in the Preferences. Print Area Print area is the surface area of the complete print (indicated by the hashed area in the figure below). The print area is by definition at least as large as the Max Contact Area. It is displayed in the Distance Unit squared, where Distance Unit can be selected in the Preferences. 7 - Analyze Data Max Intensity At (s) Max Intensity At (s) is the time in seconds since the start of the run that the maximum Intensity is measured. Max Intensity At (%) Max Intensity At (%) is the same as Max Intensity At (s), expressed in percentage of the duration of Stance phase (Stand). For example: The formula for Max Intensity At (%) is: Max Intensity at Max Intensity At (s) - Initial Contact Stand - 100% 7 - Analyze Data Max Intensity Max Intensity is the maximum intensity of the complete paw print, which is obtained by summing up the pixels of all the paw prints detected in the stance phase. Min Intensity Min Intensity is the minimum intensity of the complete paw print (see the figure above). Mean intensity Mean intensity is the mean intensity of the complete paw print (see in the figure above). Mean Intensity of the 15 Most Intense Pixels This is the mean Intensity of the 15 pixels of a paw with the highest intensity. Swing (s) Swing (s) or Swing Phase is the duration in seconds of no contact of a paw with the glass plate. Swing Speed Swing Speed is the speed (Distance Unit/second) of the paw during Swing. The formula of Swing Speed is: Stride Length Stride Length is the distance (in Distance Units) between successive placements of the same paw. Swing Speed Stride Length Swing - 7 - Analyze Data It is obtain by calculating the beeline distance between the center of the paw print of two consecutive placements of the same paw during Max contact. So it is not the difference in the X-coordinates of the two paw print centers. The Stride Length is the length of the segment in the figure below. Step Cycle (s) Step Cycle is the time in seconds between two consecutive Initial Contacts of the same paw: The figure below shows an example of Step Cycle, Stand and Swing for a Right Front paw. Duty Cycle (%) Duty Cycle (%) expressed Stand as a percentage of Step Cycle: Toe Spread For more information on (Intermediate) Toe Spread, Manual Print Length and Paw Angle, see also page 86. Toe Spread is the distance (in Distance Units) between the center of the first and fifth toe of a hind paw. Step Cycle Stand + Swing Duty Cycle Stand Stand + Swing - 100% 7 - Analyze Data Intermediate Toe Spread Intermediate Toe Spread is the distance (in Distance Units) between the center of the second and fourth toe of a hind paw (see also page 86). Manual Print Length Manual Print Length is the distance (in Distance Units) between the center of the third toe and the heel of a paw. Paw Angle Body Axis Paw Angle Body Axis is the smallest angle (in degrees) between the Manual Print Length line and the line representing the orientation of the body axis. Paw Angle Movement Vector Paw Angle Movement Vector is the smallest angle (in degrees) between the Manual Print Length line and the line representing the direction of movement of the animal's body. Single Stance Single Stance is the duration (in seconds) of ground contact for a single hind paw (Coulthard et al., 2002, 2003). It is used for gait analysis in pain models. In CatWalk XT, Single Stance is the part in the step cycle of a hind paw where the contralateral hind paw does not touch the glass plate (see '3' in Figure 7.6). Initial Dual Stance Dual Stance is the duration (in seconds) of ground contact for both hind paws simultaneously (Coulthard et al., 2002, 2003). Dual Stance is used for gait analysis in pain models. In CatWalk XT, a distinction is made between Initial Dual Stance and Terminal Dual Stance. Initial Dual Stance is the first time in a step cycle of a hind paw that the contralateral hind paw also makes contact with the glass plate (see '2' in Figure 7.6). Terminal Dual Stance In CatWalk XT, Terminal Dual Stance is the second step in a step cycle of a hind paw that the contralateral hind paw also makes contact with the glass plate (see '4' in Figure 7.6). 7 - Analyze Data Single and Dual Stance values are only calculated if the contralateral hind paw has been placed on the glass plate before and after a step cycle of the other hind paw. Please note that the Terminal Dual Stance for a hind paw is the Initial Dual Stance for the successive step cycle of the contralateral paw. Body Speed The Body Speed of a step cycle of a specific paw is calculated by dividing the distance that the animal's body traveled from one initial contact of that paw to the next by the time to travel that distance. Body Speed Variation Body Speed Variation (%) is calculated by dividing the absolute difference between the Body speed and the Average Speed of a run by the Average Speed. Step Sequence The Step Sequence sheet contains information on the order in which the four paws are placed. The following parameters are displayed in the Step Sequence sheet. Choose Analyze > View Run Statistics and under Statistics click Step Sequence. Figure 7.6 Timing View with a graphical depiction of Single and Dual Stance. 1: Step cycle of the right hind paw RH. 2: Initial Dual Stance of RH, which lasts as long as the contralateral paw, LH, makes contact with the glass plate. Note that from the point of view of LH, 2 is a Terminal Dual Stance. 3: Single Stance of RH. 4: Terminal Dual Stance of RH. Note that from the point of view of LH, 4 is an Initial Dual Stance. 7 - Analyze Data Step sequence The Step Sequence lists the order in which the paws were placed on the glass plate. This order determines the footfall pattern that can assigned. Codes Each Code corresponds to a particular paw: 1 = Left Hind (LH), 2 = Left Front (LF), 3 = Right Hind (RH), 4 = Right Front (RF). The Codes are used to create the Footfall Patterns diagram (see page 100). Patterns This row contains the abbreviations of the assigned footfall patterns (see also Figure 7.6). The colors of the cells correspond to those in the Footfall Patterns diagram (page 100). Normal Patterns This is the number of Step Cycles that fall within one of the footfall pattern categories (see Figure 7.6 on page 115). Accounted Steps This is the number of steps that was taken into account to determine the footfall patterns. Regularity Index (%) The Regularity Index expresses the number of normal step sequence patterns relative to the total number of paw placements. The formula of Regularity Index is: where NSSP is the number of normal step sequence patterns and PP the total number of paw placements (see Figure 7.7). Regularity Index NSSP x 4 PP - 100% 7 - Analyze Data The Regularity Index does not tell whether the subject walks with the same pattern. If the footfall pattern changes during a run (for example, from AA to AB), the Regularity Index is not affected. The Regularity Index (RI) is used in research on spinal cord injury. It is a fractional measure of inter-paw coordination. In healthy, fully coordinated animals its value is 100%. For example, one week after rats were subjected to a transection injury, the RI decreased from 100% (pre- treatment) to approximately 80%. The RI again increased to 90% after 4 weeks (Hamers et al., 2001; see Figure 7.7). Additional visualizations In the Step Sequence sheet, when you click a Code or a colored cell, the following occurs: The Print View highlights the corresponding print. The Timing View highlights the start and end time of the stand of that paw. Figure 7.7 A Footfall Patterns diagram. In this example, there are six normal footfall patterns (NSSP). Each patterns begins with a blue dot (in the legend: Start of a pattern) and is followed by three dots. The first paw print and the last three are not taken into account (see page 100 for why that is the case). The number of accounted steps (PP) is 6 * 4 = 24. Therefore, the Regularity Index is (6 * 4)/24 * 100% = 100%. To create footfall pattern diagrams, select Analyze > View Run Visualizations and under Visualizations click the Footfall Patterns tab. See also footfall patterns on page 100. 7 - Analyze Data The Sub Print View shows the individual prints of the Stand. The time between two subsequent prints is 1/100 s. See also Footfall patterns on page 100. Base Of Support Base of Support is the average distance between either the front paws or the hind paws, measured along the y axis. Choose Analyze > View Run Statistics and under Statistics click Base of Support. 7 - Analyze Data In the Base of Support sheet the following variables/parameters are displayed: Paw - The label of the paw. N - The number of times each paw was placed. Mean (in Distance Unit) - The mean value for the Y position for each paw. SEM (%) - This is the Standard Error of the Mean, expressed as a percentage of the mean Base of Support. At the bottom: Paws - Front paws or Hind paws. N - The total number of times the paw combinations were placed. Base of Support ([Distance Unit]) - The mean distance between either front paws or hind paws. The Base of Support is calculated as follows: The Base of Support parameter is used in research on spinal cord injury. It has been found that as a result of trauma to the spinal cord (either as a result of a transection or contusion), the Base of Support of the front paws is unaffected, but that of the hind paws showed an increase (Hamers et al., 2001). Other Statistics In the Other Statistics sheet, the following parameters are displayed: Duration This is the duration of the run based on the selected steps in the data selection (see Select the data on page 92). The Duration is different from the Run Duration which the duration of the recorded run. Average Speed This is the average speed of the selected steps in the data selection (see Select the data on page 92). The Average Speed is expressed in Distance Units per second. Base of Support Front paws YRF YLF Base of Support Hind paws YRH YLH 7 - Analyze Data Maximum Variation (%) This is the Maximum Variation in average speed of the selected steps in the data selection. Cadence The Cadence is expressed in steps per second: where steps is the total number of selected steps. The selected steps include the yellow, unaccounted steps in the Footfall Patterns diagram (see page 100), but the steps that are not selected in the current Data Segmentation profile (page 92) are not included. Number of steps This is the total number of selected steps in this run. Steps that are not selected in the current Data Segmentation profile are not included. Sciatic Functional Index The Sciatic Functional Index (SFI) is a measure for the functional recovery of the sciatic nerve which innervates the hind paws. Therefore, the SFI is only relevant for hind paws. The SFI is calculated differently for rats and mice. The formula used for the calculation of the SFI for rats (Bain et al., 1989): where PL is Manual Print Length, TS is Toe Spread, ITS is Intermediate Toe Spread and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. The formula used for the calculation of the SFI for mice (Inserra et al., 1998): note Although ITS is not in the formula above, you need to measure the ITS in mice in order to have the SFI calculated! Cadence steps - 1 Initial contact last Stand Initial contact first Stand - SFI 38.3 PLE PLN PLN - 109.5 TSE TSN TSN - 13.3 ITSE ITSN ITSN - 8.8 SFI 118.9 TSE TSN TSN - 51.2 PLE PLN PLN - 7.5 7 - Analyze Data Posterior Tibial Functional Index The Tibial Functional Index (TFI) is a measure for the functional recovery of the tibial nerve which is a branch of the sciatic nerve. The formula used for the calculation of the TFI for rats (Bain et al., 1989): where PL is Manual Print Length, TS is Toe Spread, ITS is Intermediate Toe Spread and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. The formula used for the calculation of the TFI for mice (Inserra et al., 1998): Peroneal Functional Index The Peroneal Functional Index (PFI) is a measure for the functional recovery of the peroneal nerve which innervates the hind paws. The formula used for the calculation of the PFI for rats (Bain et al., 1989): where PL is Manual Print Length, TS is Toe Spread, and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. The formula used for the calculation of the PFI for mice (Inserra et al., 1998): where TS is Toe Spread and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. TFI 37.2 PLE PLN PLN - 104.4 TSE TSN TSN - 45.6 ITSE ITSN ITSN - 8.8 TFI 109.9 PLE PLN PLN - 7.2 PFI 174.9 PLE PLN PLN - 80.3 TSE TSN TSN - 13.4 PFI 191.1 TSE TSN TSN - 9.86 7 - Analyze Data Print Print displays all non-paw prints (Right Hip, Right Knee, Left Hip, Left Knee, Nose, Abdomen, Tail, Genitalia). For each print is given: Number of Contacts - With the glass plate. Total Duration - Of contact with the glass plate. % - Total Duration of contact with the glass plate expressed as a percentage of the total Duration (time between first selected print and last selected print of the run). Print Positions Print Positions is the distance between the position of the hind paw and the position of the previously placed front paw on the same side of the body (ipsilateral) and in the same Step Cycle. A positive value of Print positions indicates that the hind paw is placed behind the front paw. A negative value of Print Positions indicates that the hind paw is placed in front of the front paw. The Print Positions sheet shows the distance (in the selected Distance Units) for the right and left front paws and their respective ipsilateral hind paws. Calculation of Print Positions is based on the X-coordinates of the centers of ipsilateral paws at Max Contact. Walking direction from left to right Walking direction from right to left where FP is one of the front paws and HP is one the hind paws. The last front paw does not have a Step Cycle (and therefore no Print Position) but if the corresponding hind paw starts within the Stance of the front paw, this combination is also used for calculating the Print Position. Print Positions XFP(Max Contact) XHP(Max Contact) Print Positions XHP(Max Contact XFP(Max Contact) 7 - Analyze Data In the Print Positions sheet, when you click one of the front paw rows: The Print View highlights the ipsilateral paws. The Timing View shows the Stand of both ipsilateral paws. Phase Dispersions The Phase Dispersions parameter describes the temporal relationship between placement of two paws within a Step Cycle. It is used as a measure of inter-paw coordination. Calculation Phase Dispersions is the moment of Initial Contact of a target paw expressed as a percentage of the Step Cycle time of an anchor paw. Phase Dispersions range from -50 to 75% (see Figure 7.8 for a graphical depiction of Phase Dispersions). The formula for Phase Dispersions is: where IC is initial Contact. A positive Phase Dispersions value indicates that initial contact of the target paw occurred after that of the anchor paw. A negative Phase Dispersions value indicates that the target paw preceded the anchor paw. Phase Dispersions can be computed for a total of 12 pairs. However, interchanging target and anchor does not have a large effect since their Phase Dispersions values are normally strongly correlated, so only 6 pairs of paws are displayed. Within diagonal pairs (RF-LH, LF- RH) and ipsilateral pairs (RF-RH, LF-LH), the anchor is always one of the front paws. Within girdle pairs (LF-RF, LH-RH), the anchor paw is always one of the left paws. Which paws/parameters are displayed in the Phase Dispersions sheet depends on the selection in the currently active Parameter profile (displayed in bold and blue in the Experiment Explorer). Phase Dispersions ICtargetm ICanchorn Step cycleanchor - 100% 7 - Analyze Data Statistics The following statistics are displayed in the Phase Dispersions sheet for the various paw combinations: Value - This column shows the Phase Dispersions values. An empty cell indicates that Phase Dispersions could not be calculated (see Peculiarities below). Anchor start (A-start) - Initial Contact of the anchor paw. An empty cell indicates that Phase Dispersions could not be calculated (see Peculiarities below). Anchor duration (A-duration) - The duration of Step Cycle of the anchor paw. Figure 7.8 Diagram for the right front paw (RF) and hind paw (RH). Stand for each paw is depicted by a black bar, Swing is shown as a white bar. Initial contact is the point of transition from the white to black bar and also indicated by a vertical, dotted lines. A Step Cycle runs from Initial Contact to the next Initial Contact of that paw which is 0.44 s in (A) and 0.28 s in (B) for the anchor paw. Phase Dispersions is calculated by measuring the timing between Initial Contacts of a paw pair (RF - RH) and expressing it as a percentage of the Step Cycle time of the anchor paw (RF). (A) Initial Contact of the RH, the target paw, occurs 0.22 s after that of the anchor paw (RF), resulting in a Phase Dispersions value of 50% (0.22/0.44 * 100). (B) In this example, the Phase Dispersions value exceeds 75% with the first anchor (0.22/ 0.28 * 100 = 78.6). In such a case the target is assigned to the next anchor resulting in a Phase Dispersions value of -25% (-0.06/0.24 * 100) (Taken from Kloos et al., 2005). 7 - Analyze Data Target start (T-start) - Initial Contact of the target paw. Peculiarities - Displays the abbreviations for a number of potential error conditions that can occur: - ANT - Anchor but no valid target. This is not considered an error with the placement of the first anchor paw, when the target has not been placed yet. - AMT - Anchor with multiple targets. This occurs when the target paw is placed more often than the anchor paw. - TNA - Target no anchor. This is not considered to be an error with the placement of the last target, when the anchor is not placed on the glass plate anymore. Mismatches - This row displays the number of Peculiarities that occurred. Cstat Mean / AD / SD / R - Phase Dispersions and Couplings are more correctly described as a circular variable where a value of 0% (that is, the Target paw starting exactly at the same time as the Anchor paw) is equivalent to a value of 100% (that is, the Target paw starting at the end of the previous step cycle of the Anchor paw). In order to generate meaningful averages, special procedures are followed (see Circular Distributions on page 176). The values derived in this way are labeled as CStat. Mean is the circular mean, expressed as percentage. For Phase Dispersions, it ranges between -50% and +50%. For Couplings, it ranges between 0% and 100%. AD is the Angular Deviation, expressed as percentage. AD is the same as the Standard Deviation in CatWalk 10.6 and earlier versions. See page 179. SD is the circular Standard Deviation, expressed as percentage. AD and SD are measures of spread and are calculated with similar formulas. See page 179. R is the length of the vector that represents the mean direction, that is, the mean percentage projected on a circle. It measures the degree of concentration of values around the mean, and is therefore a measure of directedness. R is dimensionless and ranges between 0 (no dominant direction) and 1 (full directedness). In the Phase Dispersions sheet, when you click a row with a target and an anchor pair: The Print View highlights both the target and the anchor paw. The Timing View graphically displays the interval between Initial Contact of the anchor and target paw and the Anchor Duration. Notes The values of Phase Dispersions are, by definition, limited in the range -50% to +75% (see Figure 7.8 on page 124). Values between 50% and 75% are equivalent to those between - 50 and -25. Therefore, if the average is greater than 50%, it is expressed as the complementary (negative) value. For example, if the points are around 52%, the CStat Mean reported by CatWalk is -48. 7 - Analyze Data If you are not familiar with circular statistics, take a look at the Excel sheet Calculate Circular Statistics of Phase Dispersions and Couplings.xlsx in the CatWalk XT documentation folder. See page 180. Applications Kloos et al. (2005) use the Phase Dispersions parameter to study the effect of locomotor and sensory recovery from spinal cord injury (SCI) on inter-paw coordination in rats. In normal animals, for the diagonal paw pairs RF-LH, LF-RH) the target paw typically moves synchronously with the anchor so the Initial Contacts occur simultaneously resulting in a Phase Dispersions value of 0%. Girdle pairs (RF-LF, RH-LH) usually yield a Phase Dispersions value of 50% when walking at a moderate speed. Kloos et al. found that depending on the severity of SCI recovery of inter-paw coordination followed different patterns. See also Application examples on page 135. Couplings Couplings describe the temporal relationship between placement of two paws within a step cycle. It is used as a measure of inter-paw coordination. In the Couplings sheet, Couplings values are displayed for all 12 pairs of paws. Calculation Couplings are computed the same way as Phase dispersions. However, in the case of Couplings a target can never precede an anchor. Therefore, the value of Couplings ranges between 0 and 100%. 7 - Analyze Data Assuming that the step cycle is constant, Phase Dispersions and Couplings are related to each other. In the following example, if the Phase Dispersion value of a single Anchor-Target pair A-B is - 20% of the step cycle of A (B occurring earlier than A), for Couplings the value is +80% because the previous paw B is taken as an anchor. Statistics For a description of the statistics displayed in the Couplings sheet, see phase dispersions on page 124. The main difference between Couplings and Phase Dispersions is that the average of Couplings is always positive in the range 0% - 100%, while the average of Phase Dispersions is in the range -50% to 50%. Notes If you are not familiar with circular statistics, take a look at the Excel sheet Calculate Circular Statistics of Phase Dispersions and Couplings.xlsx in the CatWalk XT documentation folder. See page 180. See also Circular Distributions on page 176. Support The Support sheet shows the following parameters: Start Time - Displays the start time of the different sections. A section is a time segment in which the same paws make contact with the glass plate. A section starts every time a paw is placed on the glass plate or lifted from the glass plate. Duration - Duration of a section. Support Formula - This is the number of paws that are simultaneously on the glass plate in a section. The Support Formula starts at Initial Contact of the left hind paw after all paws have been placed on the glass plate once. A new Support Formula row is started with the next Step Cycle of left hind. 7 - Analyze Data Footfall Formula - Contains information about which paws are touching the glass plate during each section. For an explanation of the Footfall Formula notation see page 174. Standing on % - This parameter displays the relative duration of simultaneous contact with the glass plate of all combinations of paws. The combinations are: zero paws, a single paw, diagonal pair of paws (RF-LH or LF-RH), lateral paws (RF-RH or LF-LH), girdle paws (RF-LF or RH-LH), three paws and four paws. When you click a Support Formula, the Print View highlights all paws in the section that touch the glass plate, and the Timing View graphically displays the section interval. 7 - Analyze Data 7.5 Group Statistics And Charts With Group statistics, you can calculate the statistics of parameters, grouped per treatment group*time point combination, and view the corresponding charts. Procedure - Make sure you have selected the right Data Segmentation profile and Parameter profile. Data not selected in these profiles are not included in the results. - Choose Analyze > View Group Statistics and Charts. - Under Numerical Results, click a category tab to display the results. - Under Graphical Results, click a category to view the corresponding parameter charts. See chart settings on page 130. - To export group statistics and charts, see page 159. Notes If the tab for a parameter contains no results, it means that it is not selected in the currently active Parameter profile. To select another Parameter profile, in the Profiles Explorer, right-click a Parameter profile and select Set as Active. See also Select the analysis parameters on page 96. If your experiment contains one or more runs with missing or corrupt data you get an error message when you try to open the group statistics and charts. In the Experiment Explorer, delete the runs listed in the error message (right-click a run and select Delete. See also page 150). Statistics Available To calculate group statistics, CatWalk XT uses the values of trial statistics. example The experimental group Control includes 10 trials for 10 subjects recorded at time point Day 1. The group mean of Print Length for Control - Day 1 is calculated by averaging the 10 per-trial values of Print Length for that group. You can find the per-trial values in the Trial Statistics export file (page 156). The following statistics are available: N - The number of trials in that treatment grouptime point combination. 7 - Analyze Data Mean (for all parameters but Phase Dispersions and Couplings), the arithmetic mean of the parameter for that treatment grouptime point combination. CStat Mean (only for Phase Dispersions and Couplings) - The circular mean of phase lags (CStat) for that treatment group*time point combination. See the circular group mean on page 176. note Values like -49% and +51% may look different in a column chart. However, in the circular domain they are very similar. See page 176. CStat R (only for Phase Dispersions and Couplings) - The length of the vector representing the average phase lag for a treatment grouptime point combination. SEM (for all parameters but Phase Dispersions and Couplings) - The Standard Error of the Mean of the parameter. CStat AD (only for Phase Dispersions and Couplings) - The angular deviation of the individual phase lags for a treatment grouptime point combination. CStat SD (only for Phase Dispersions and Couplings) - The circular standard deviation of the individual phase lags for a treatment group*time point combination. See measures of spread around the mean on page 179. Chart Settings In the Group Statistics & Charts screen, under Graphical Results, click In the Chart Settings window, the following settings are available: Chart Type Bar Chart - This chart shows the mean value of the parameter as colored bar and the standard error as error bar. Five Number Summary Chart - A box-whisker chart showing the sample minimum, lower quartile, median, upper quartile and sample maximum. This chart can be made when at least 4 trials (therefore N≥ 4) are available for that data series. This chart type is not displayed for Phase Dispersions and Couplings. Horizontal axis Time Points - Displays the time points on the horizontal axis. Treatment Groups - Displays the treatment groups on the horizontal axis. 7 - Analyze Data Data Series Data Series are displayed in the chart legend. You have the same options as under Horizontal axis. If you change the option under Horizontal axis, the option under Data Series changes automatically and vice versa. Title font size Select the size in pixels of the font for the chart title (range: 6 - 14). Bar Chart / Five Number Summary Chart Chart width - The width of the chart in pixels (including the legend). Chart height - The width of the chart in pixels (including the title). 7 - Analyze Data Bar width (%) - The percentage of the space available for that data series occupied by the bar (see the figure on the right). Gap - The gap between bars (in pixels). Whisker width (%) - The with of the whisker relative to the bar width. Circular charts Chart size - The width and the height of the chart in pixels, including the title and the legend. Range: 100-1000. Include datapoints - Select this option if you want to have the per-trial values of variables displayed on the circle. Those data points are used to calculate the group average, which is represented by the vector. note Data points may overlap on the circle. In that case you see fewer dots than the actual number of trials in that group. However, the statistics are based on all trials in each group. Split charts by - Select which criterion you want to produce different charts. Treatment Groups. For example, two treatment groups results in two charts per variable, one for Control and one for Treated. The time points appear in the legend. Time Points. For example, three time points (d1, d5, d10) results in three charts per variable. The treatment groups appear in the legend. Time Points and Treatment Groups. This option creates as many charts as those created with the two option above, taken together. For example, with three time points and two treatment groups, for the variable Phase Dispersions RF->LH: 7 - Analyze Data The first three charts are based on the three time points. The legend shows the groups of subjects. The other two charts show the same data the other way round: one chart for each group of subjects, with the legend showing the three time points. Note If a chart is empty, it could be that a five number summary chart is selected, and for that parameter less than four trials are available. To solve this, in the Chart Settings window select Bar chart next to Chart type. To optimize the space needed for charts, reduce the font size for the title, and in the Experiment settings shorten the name of the categories under Treatment Groups and Time Points. That makes the legend smaller. Interpreting The Circular Charts Circular charts represent the average (group) values of Phase Dispersions and Couplings. Vector orientation The angle formed by the vector represents the average CStat Mean of an experimental group*time point combination, expressed in percentage and plotted on a polar coordinate system. Vector length The length of the vector represents the value CStat R for an experimental group*time point combination. It ranges between 0 and 1 and reflects the degree of certainty of the average. The lower the dispersion of the single data points around the average, the longer the vector. 7 - Analyze Data Data points If you selected Include datapoints in the Chart Settings (page 130), each dot represents one of the values of Phase Dispersion/Couplings that contribute to the mean. The value N in the table indicates the number of points. However, mind that if one value occurs multiple times, the dot overlap. Circular scale The scale of these charts reflects the different definition of the two parameters: -50% to +50% for Phase Dispersions, and o% to 100% for Couplings. For details, see phase dispersions on page 123 and couplings on page 126. Note that for a specific pair Anchor-Target: A value of -50% in a Phase Dispersion chart corresponds to a value of +50% in a Couplings chart. A value of -25% in a Phase Dispersions chart corresponds to a value of +75% in a Couplings chart. However, in practice the average values of Phase Dispersions and Coupling do not always correspond precisely. This is because some values of Phase Dispersions are not calculated when they exceed the limits stated in their definition; for example when a target occurs at more than 75% of the anchor step cycle (see phase dispersions on page 123); however those values are calculated as Couplings. You can check this in the Run Statistics by comparing the tabs Phase Dispersions and Couplings. The two averages, therefore, are not calculated using the same values. Circular charts options See chart settings on page 130. 7 - Analyze Data 7.6 Application Examples This list of applications is not exhaustive. For more applications and publications, please search Google Scholar. CNS-related changes Spinal cord injury (CatWalk comes from this field of research) - page 136 Neuropathic pain - page 137 Ischemia / stroke - page 138 Amyotrophic Lateral Sclerosis (ALS) - page 139 Parkinson's disease models - page 141 Cerebellar ataxia - page 139 Motor coordination (cerebellar cortex) - page 140 PNS-related changes Sciatic nerve injury - page 142 Skeletal and /or musculature changes Arthritis - page 143 Genetic / toxic Huntington's disease - page 144 Refsum disease - page 144 Charcot-Marie-Tooth (CMT) - page 144 Leigh disease - page 145 7 - Analyze Data Spinal Cord Injury References Cao, Y., Shumsky, J.S., Sabol, M.A., Kushner, R.A., Strittmatter, S., Hamers, F.P.T., Lee, D.H.S., Rabacchi, S.A. & Murray, M. 2008. Nogo-66 receptor antagonist peptide (NEP1-40) administration promotes functional recovery and axonal growth after lateral funiculus injury in the adult rat. Neurorehabilitation and Neural Repair 22: 262-278. doi:10.1177/ 1545968307308550 Hamers, F.P.T., Koopmans, G.C. & Joosten, E.A.J. 2006. CatWalk-Assisted Gait Analysis in the Assessment of Spinal Cord Injury. Journal of Neurotrauma 23: 537-548. Hou, J., Nelson, R., Nissim, N., Parmer, R., Thompson, F.J. & Bose, P. 2014. Effect of combined treadmill training and magnetic stimulation on spasticity and gait impairments following cervical spinal cord injury (C-SCI). Journal of Neurotrauma 31: 1088-1106. doi: 10.1089/neu.2013.3096. Kloos, A.D., Fisher, L.C., Detloff, M.R., Hassenzahl, D.L. & Basso D.M. 2005. Stepwise motor and all-or-none sensory recovery is associated with nonlinear sparing after incremental Result Parameters affected References Depending on the severity of SCI, the gait becomes less stable and less coordinated. The animal tries to stabilize the body Base of Support, Intensity, Stand, Phase dispersions depending on severity of SCI Hamers et al. 2006 Kloos et al. 2005 After lateral funiculus injury, gait analysis showed recovery in animals treated with compound Stride Length, Regularity Index, Base Of Support, Run Duration Cao et al. 2008 Effect of locomotor training and/or magnetic stimulation on gait impairments after cervical spinal cord injury Phase Dispersions, Average Speed, Print Area, Stand Index Hou et al. 2014 CatWalk XT analysis and especially its static parameters found highly useful in assessing spontaneous recovery of hindlimb function after severe thoracic spinal cord injury Max intensity, Mean intensity, Max intensity at%, Max contact mean intensity Zheng et al. 2023 7 - Analyze Data spinal cord injury in rats. Experimental Neurology 191: 251-265. doi: 10.1016/ j.expneurol.2004.09.016. Zheng, G., Zhang, H., Tail, M., Wang, H., Walter, J., Skutella, T., Unterberg, A., Zweckberger, K., Younsi, A. 2023. Assessment of hindlimb motor recovery after severe thoracic spinal cord injury in rats: Classification of CatWalk XT® gait analysis parameters. Neural Regen. Res. 18: 1084. Neuropathic Pain References Hestehave, S., Abelson, K.S.P., Brønnum Pedersen, T. et al. 2020. The influence of rat strain on the development of neuropathic pain and comorbid anxio-depressive behaviour after nerve injury. Scientific Reports 10: 20981 (2020). https://doi.org/10.1038/s41598-020- 77640-8 Moon, E.S., Karadimas, S.K., Yu, W.-R., Austin, J.W. & Fehlings, M.G. 2014. Riluzole attenuates neuropathic pain and enhances functional recovery in a rodent model of cervical spondylotic myelopathy. Neurobiology of Disease 62: 394-406. doi: 10.1016/ j.nbd.2013.10.020. Result Parameters affected References Rats with a chronic constriction injury of the sciatic nerve, a model of neuropathic pain, minimize contact with the affected paw during locomotion Print Area, Intensity, Duty Cycle. Regularity Index unchanged Vrinten & Hamers 2003 Drug treatment (riluzole) attenuates neuropathic pain and enhances functional recovery in a rat model of cervical spondylotic myelopathy Swing Duration, Swing speed, Mean Intensity Moon et al. 2014 All rat strains displayed similar SNI- specific postural changes with pronation of the affected paw Contact area, Swing duration, Duty cycle, Run speed Hestehave et al. 2020 7 - Analyze Data Vrinten, D.H. & Hamers, F.F. 2003. 'CatWalk' automated quantitative gait analysis as a novel method to assess mechanical allodynia in the rat; a comparison with von Frey testing. Pain 102: 203-209. Ischemia / Stroke References Encarnacion, A., Horie, N., Keren-Gill, H., Bliss, T.M., Steinberg, G.K. & Shamloo, M. 2011. Long-term behavioral assessment of function in an experimental model for ischemic stroke. Journal of Neuroscience Methods 196: 247-257. doi:10.1016/j.jneumeth.2011.01.010. Madinier, A., Quattromani, M.J., Sjölund, C., Ruscher, K. & Wieloch, T. 2014. Enriched housing enhances recovery of limb placement ability and reduces aggrecan-containing perineuronal nets in the rat somatosensory cortex after experimental stroke. PLoS ONE 9: e93121. doi:10.1371/journal.pone.0093121 Qin, L., Jing, D., Parauda, S., Carmel, J., Ratan, R.R., Lee, F.S., Cho, S. 2014. An Adaptive Role for BDNF Val66Met Polymorphism in Motor Recovery in Chronic Stroke. Journal of Neuroscience 34: 2493-2502. doi: 10.1523/JNEUROSCI.4140-13.2014 Result Parameters affected References Long-term functional deficit after middle cerebral artery occlusion Swing Speed, Intensity, Duty Cycle, Phase Dispersions Encarnacion et al. 2011. After photothrombosis lesion, gait is affected in various ways Average Speed Cadence, Stand and Swing Duration, Support, Maximum Contact Area, Max intensity at Max Contact, Couplings Madinier et al. 2014 Gait analysis reveals impairments in the limbs of both sides after right middle cerebral artery occlusion, and suggests involvement of the contralesional left hemisphere in recovery Regularity Index, Maximum Contact Area, Mean Intensity, Stride Length, Swing speed Qin et al. 2014 7 - Analyze Data Amyotrophic Lateral Sclerosis (als) References Mead, R.J., Bennett, E.J., Kennerley, A.J., Sharp, P., Sunyach, C., Kasher, P., Berwick, J., Pettmann, B., Battaglia, G., Azzouz, M., Grierson, A., Shaw P.J. 2011. Optimised and rapid pre-clinical screening in the SOD1G93A transgenic mouse model of amyotrophic lateral sclerosis (ALS). PLoS ONE 6: e23244. doi: 10.1371/journal.pone.0023244 Sun, H., Hou, Z., Yang, H., Meng, M., Li, P., Zou, Q., Yang, L., Chen, Y., Chai, H., Zhong, H., Zhuyun Yang, Z., Zhao, J., Lai, L., Jiang, X., Xiao Z. 2014. Multiple systemic transplantations of human amniotic mesenchymal stem cells exert therapeutic effects in an ALS mouse model. Cell Tissue Research 357: 571. doi:10.1007/s00441-014-1903-z Vergouts, M., Marinangeli, C., Ingelbrecht, C., Genard, G., Schakman, O., Sternotte, A., Calas, A.-G., Hermans, E. 2015. Early ALS-type gait abnormalities in AMP-dependent protein kinase-deficient mice suggest a role for this metabolic sensor in early stages of the disease. Metabolic Brain Disease 30: 1369. doi:10.1007/s11011-015-9706-9 Cerebellar Ataxia Result Parameters affected References Gait parameters describe decline in motor function in a transgenic mouse model of ALS Stand, Stride Length, Duty Cycle, Support on diagonal limbs, Support on 3 limbs Mead et al. 2011 Stem cell treatment improves motor function Stride Length (hindlimbs) Sun et al. 2014 Altered gait in mouse with ALS-related gene n. a. Vergouts et al. 20015 Result Parameters affected References Impaired gait in general as a result of neurological deficits Swing Duration, Stand Duration, Regularity Index Cendelín et al. 2010 7 - Analyze Data References Cendelín, J., Voller, J., Vožeh, F. 2010. Ataxic gait analysis in a mouse model of the olivocerebellar degeneration. Behavioural Brain Research 210: 8-15. doi:10.1016/ j.bbr.2010.01.035. Salvi, J., Bertaso, F., Mausset-Bonnefont, A.-L., Metz, A., Lemmers, C., Ango, F., Fagni, L., Lory, P., Mezghrani, A. 2014. RNAi silencing of P/Q-type calcium channels in Purkinje neurons of adult mouse leads to episodic ataxia type 2. Neurobiology of Disease 68: 47-56, doi: 10.1016/j.nbd.2014.04.005. Kyriakou, E.I., van der Kieft, J.G., de Heer, R.C., Spink, A., Nguyen, H.P., Homberg, J.R., van der Harst, J.E. 2015. Automated quantitative analysis to assess motor function in different rat models of impaired coordination and ataxia, Journal of Neuroscience Methods 268: 171-181. doi: 10.1016/j.jneumeth.2015.12.001 Motor Coordination (cerebellar Cortex) Motor abnormalities measured after suppression of the P/Q-type calcium channels in Purkinje neurons Print Area, Stand, Duty Cycle, Stride Length Salvi et al. 2014 Static and dynamic parameters showed significant differences in three rat models of impaired coordination and ataxia Average Speed, Swing Speed, Stride Length, Phase Dispersions Kyriakou et al. 2016 Result Parameters affected References Reduced motor coordination in mice lacking chloride calcium-gated chloride channels in Purkinje cells Run Speed, Stride Length, Duty Cycle, Swing Speed, Stand, Print Positions, Base of Support, Footfall Patterns, Support on three paws %, Support on diagonal paws, Phase Dispersion variability Neureither et al. 2017 Deterioration of motor performance correlates with the demise of Purkinje cell axons in the cerebellum Stride Length, Stand Duration, Swing Duration, Print Positions Verheijden et al. 2013 7 - Analyze Data References Neureither, F., Ziegler, K., Pitzer, C., Frings, S., Möhrlen, F. 2017. Impaired Motor Coordination and Learning in Mice Lacking Anoctamin 2 Calcium-Gated Chloride Channels. Cerebellum (Online). doi:10.1007/s12311-017-0867-4. Verheijden, S., Bottelbergs, A., Krysko, O., Krysko, D.V., Beckers, L., De Munter, S., Van Veldhoven, P.P., Wyns, S., Kulik, W., Nave, K.-A., Ramer, M.S., Carmeliet, P., Kassmann, C.M. & Baes, M. 2013. Peroxisomal multifunctional protein-2 deficiency causes neuroinflammation and degeneration of Purkinje cells independent of very long chain fatty acid accumulation, Neurobiology of Disease 58: 258-269. doi: 10.1016/ j.nbd.2013.06.006. Parkinson's Disease Models Result Parameters affected References Treatment improved motor functions as measured with CatWalk XT Run Average Speed, Regularity Index, Print Area, Swing Speed, Stride Length, Print Positions Tatenhorst et al. 2016 Treatment improves speed of locomotion but impairs forelimb movement Run Duration, Base of Support, Maximum Contact Area, Maximum Intensity, Swing Duration, Swing Speed Vlamings et al. 2016 Behavioral deficits efficiently measured in rat Parkinson models Mean Intensity, Maximum Contact Area (forepaws) Vandeputte et al. 2010 Swaying pattern during locomotion was quantified in rodent models Paw statistics X position and Y position Timotius et al. 2018 Detection of motor deficiencies in a Medial Forebrain Bundle 6-OHDA lesion model of Parkinson's disease Stride Length, Print Position, Step Cycle, Swing phase of the step cycle, Stand index, Phase Dispersion, Print Length, Print Area Boix et al 2018 7 - Analyze Data References Boix, J., von Hieber, D., Connor, B. 2018. Gait analysis for early detection of motor symptoms in the 6-OHDA rat model of Parkinson's disease. Frontiers in Behavioral Neuroscience 12: 39. Tatenhorst, L., Eckermann, K., Dambeck, V., Fonseca-Ornelas, L., Walle, H., Lopes da Fonseca, T., Koch, J.C., Becker, S., Tönges, L., Bähr, M., Outeiro, T.F., Zweckstetter, M. & Lingor, P. 2016. Fasudil attenuates aggregation of -synuclein in models of Parkinson's disease. Acta Neuropathologica Communications 4: 39. doi: 10.1186/s40478-016-0310-y Timotius, I.K., Canneva, F., Minakaki, G., Pasluosta, C., Moceri, S., Casadei, N., Riess, O., Winkler, J., Klucken, J., von Hörsten, S., & Eskofier, B. 2018. Dynamic footprint based locomotion sway assessment in -synucleinopathic mice using Fast Fourier Transform and Low Pass Filter. Journal of Neuroscience Methods 296: 1-11. doi: 10.1016/ j.jneumeth.2017.12.004. Vandeputte, C., Taymans, J.-M., Casteels, C., Coun, F., Ni, Y., Van Laere, K., & Baekelandt, V., 2010. Automated quantitative gait analysis in animal models of movement disorders. BMC Neuroscience 11: 92. doi: 10.1186/1471-2202-11-92 Vlamings, R., Visser-Vandewalle, V., Koopmans, G., Joosten, E.A.J., Kozan, R., Kaplan, S., Steinbusch, H.W.M., Temel, Y. 2007. High frequency stimulation of the subthalamic nucleus improves speed of locomotion but impairs forelimb movement in Parkinsonian rats. Neuroscience 148: 815-823. doi:10.1016/j.neuroscience.2007.06.043. Sciatic Nerve Injury Result Parameters affected References CatWalk gait analysis suitable for the measurement of behavioural recovery after complete rat sciatic nerve injury Paw Print Intensities, Couplings Bozkurt et al. 2008 A review of the most important gait kinematic measures that can be gathered with automated gait analysis systems Costa et al. 2011 7 - Analyze Data References Bozkurt, A., Deumens, R., Scheffel, J., O'Dey, D.M., Weis, J., Joosten, E.A., Führmann, T., Brook, G.A. & Pallua, N. 2008. CatWalk gait analysis in assessment of functional recovery after sciatic nerve injury, Journal of Neuroscience Methods 173: 91-98. doi: 10.1016/ j.jneumeth.2008.05.020. Costa, L.M., Simões, M.J., Maurício, A.C. & Varejão, A.S.P. 2009. Chapter 7 Methods and Protocols in Peripheral Nerve Regeneration Experimental Research: Part IV - Kinematic gait analysis to quantify peripheral nerve regeneration in the rat. International Review of Neurobiology 87: 127-139. doi: 10.1016/S0074-7742(09)87007-4. Deumens, R., Jaken, R.J.P., Marcus, M.A.E. & Joosten, E.A.J. 2007. The CatWalk gait analysis in assessment of both dynamic and static gait changes after adult rat sciatic nerve resection. Journal of Neuroscience Methods 164: 120-130. doi: 10.1016/ j.jneumeth.2007.04.009. Arthritis Monoarthritis Möller, K.Ä., Berge, O.-G., Hamers, F.P.T. 2008. Using the CatWalk method to assess weight-bearing and pain behaviour in walking rats with ankle joint monoarthritis induced by carrageenan: Effects of morphine and rofecoxib. Journal of Neuroscience Methods 174: 1-9. doi: 10.1016/j.jneumeth.2008.06.017. Parameters affected: Print Area, Mean Intensity (as a measure of weight load), Duty Cycle, Regularity Index (all decreased in treated animals). Osteoarthritis Ferreira-Gomes, J., Adaes, S. & Castro-Lopes, J.M. 2008. Assessment of movement-evoked pain in osteoarthritis by the knee-bend and CatWalk tests: a clinically relevant study. The Journal of Pain 9: 945-954. Parameters affected: Total Intensity (this was calculated outside CatWalk). CatWalk gait analysis detects a large set of both dynamic and static gait changes after neurotmesis (complete nerve transection) Base of Support, Print Length, Print Width, Stride Length, Maximum Area, Mean Intensity, Stand Duration, Swing Duration, % of normal step sequence patterns, Phase Dispersion (girdles and ipsilateral left side) Deumens et al. 2007 7 - Analyze Data Ishikawa, G., Nagakura, Y., Takeshita, N., Shimizu, Y. 2014. Efficacy of drugs with different mechanisms of action in relieving spontaneous pain at rest and during movement in a rat model of osteoarthritis. European Journal of Pharmacology 738: 111-117. doi: 10.1016/ j.ejphar.2014.05.048. Parameters affected: Maximum Contact Area, Swing Speed. Qin, J., Chow, S.K.-H., Guo, A., Wong, W.-N., Leung, K.-S., Cheung, W.-H. 2014. Low magnitude high frequency vibration accelerated cartilage degeneration but improved epiphyseal bone formation in anterior cruciate ligament transect induced osteoarthritis rat model. Osteoarthritis and Cartilage 22: 1061-1067. doi: 10.1016/j.joca.2014.05.004. Parameters affected: Duty Cycle, Regularity Index. Genetic/toxic Huntington's disease Vandeputte, C., Taymans, J.-M., Casteels, C., Coun, F., Ni, Y., Van Laere, K., & Baekelandt, V., 2010. Automated quantitative gait analysis in animal models of movement disorders. BMC Neuroscience 11: 92. doi: 10.1186/1471-2202-11-92. Parameters affected: Swing speed, Stand. Refsum disease Ferdinandusse, S., Zomer, A.W.M., Komen, J.C., van den Brink, C.E., Thanos, M., Hamers, F.P.T., Wanders, R.J.A., van der Saag, P.T., Poll-The, B.T. & Brites, P. 2008. Ataxia with loss of Purkinje cells in a mouse model for Refsum disease. PNAS 105: 17712-17717. doi:10.1073/ pnas.0806066105 Unsteady gait with strongly reduced paw print area for both fore- and hindpaws and reduced base of support for the hindpaws. Parameters affected: Print area, Toe Spread of intermediate toes, Base of Support. Lucas, E.K., Reid, C.S., McMeekin, L.J., Dougherty, S.E., Floyd, C.L., Cowell, R.M. 2014. Cerebellar transcriptional alterations with Purkinje cell dysfunction and loss in mice lacking PGC-1. Frontiers in Cellular Neuroscience 8: 441. doi:10.3389/fncel.2014.00441. Parameters affected: Print Area, Swing speed, Stand Index, Regularity Index. Charcot-Marie-Tooth (CMT) Villalón, E., Dale, J.N., Jones, M., Shen, H. & Garcia, M.L. 2015. Exacerbation of Charcot- Marie-Tooth type 2E neuropathy following traumatic nerve injury. Brain Research 1627: 143-153. doi: 10.1016/j.brainres.2015.09.024. 7 - Analyze Data Parameters affected: Print Length and Width, Max Contact Area, Max Intensity, Max Contact at (%), all decreased. Couplings involving the affected limb (LH) decreased or increased depending on the coupling combination. Dale, J.M., Villalon, E., Shannon, S.G., Barry, D. M., Markey, R.M., Garcia, V.B. and Garcia, M.L. 2012. Expressing hNF-LE397K results in abnormal gaiting in a transgenic model of CMT2E. Genes, Brain and Behavior 11: 360-365. doi:10.1111/j.1601-183X.2012.00771.x Parameters affected: Stride Length, Regularity Index, Stand Index (all decreased). Couplings and Phase dispersions increased or decreased depending on which combination was considered. Leigh disease de Haas, R., Russel,F.G., & Smeitink, J.A. 2016. Gait analysis in a mouse model resembling Leigh disease. Behav Brain Res, 296: 191-198. See also Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - Appendices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-appendices Chapter: CatWalk XT Describes the Support Formula and Footfall Formula. Describes the computation of descriptive statistics for circular distributions of data such as phase lags during locomotion. Written by Dr. Frank Hamers. A - Install the Ethernet card for the camera A Install The Ethernet Card For The Camera Main Steps Prerequisites You need a 1-Gb (gigabit) Ethernet network interface card (desktop computers only). Contact your Noldus representative if you need to purchase such card or you are not sure whether your card is compatible. Procedure Follow the instructions in this section when you install CatWalk XT on a new computer, and you want to acquire data with that computer. 1. Install the Ethernet network interface card in your CatWalk XT computer (see below). 2. Install the Ethernet network interface card driver software (see page 165). Notes If you purchased the computer from Noldus, the steps above are already done. You can skip this section. In all other cases: You must first install the Ethernet card, then the CatWalk XT software! The Ethernet card is necessary when you acquire runs - that is when the software records the video through the Ethernet connection. You do not need to install the Ethernet card if you use CatWalk XT to classify and analyze runs previously acquired on a different computer. Install The Ethernet Card tip Watch the video of the installation of the Ethernet card. On the CatWalk XT installation disc open the folder ...\Videos\Installation Instructions\ and double-click installation_ instructionscatwalkxt.exe. 1. Turn off your computer and all connected peripherals, such as the monitor and printer. 2. Unplug the computer and its peripherals. 3. Remove the PC's case according to the instructions provided in its user manual. When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground A - Install the Ethernet card for the camera yourself by putting on an earthing wristlet, and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. 4. Select a free PCIe expansion slot and remove the corresponding extension cover making sure that the screw is put aside safely. 5. Unpack the Ethernet card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. 6. Fix the card to the chassis using the screw retained earlier and re-fit the computer's cover. PCIe card slots are marked on the motherboard, for example SLOT3-PCIe2x1. If possible, choose the PCIe slot with highest performance. This is estimated by the version number (for example PCIe2x1 is version 2); the higher the version number, the higher the performance. Install The Ethernet Card Driver The driver for the Ethernet card is installed automatically when you install the CatWalk XT software. In case you need to uninstall the driver, in the Control Panel, choose Programs and Features, and uninstall eBUS Runtime 64-bit. To re-install the driver, start the file CatWalk XT - Setup - [version number].exe. Select Repair and click Next. Notes You can download the setup file from my.noldus.com. The eBus Runtime software includes two drivers, one for Ethernet connections and one for USB3 Vision connections. CatWalk XT uses only the driver for Ethernet connection, the Universal Pro Driver for Ethernet. A - Install the Ethernet card for the camera important After turning on the CatWalk system and the CatWalk computer, it can take a couple of minutes for the camera to be detected (indicated by the Acquiring network icon in the task bar). Please do not start CatWalk before the camera has been detected. B - Troubleshooting B Troubleshooting See the following main topics: general issues (below) paw prints (page 169) data analysis and export (page 173). General Issues CatWalk XT crashes Please send our Support department the log file which contains all the information needed for us to find the cause of the crash. The log file is located in the following folder: C:\ProgramData\Noldus\CatWalk\XT 10.7\Log\CatWalk XT.log. CatWalk XT does not start anymore If you start CatWalk XT for the first time on a computer with multiple user accounts as the administrator, other standard users are not able to use CatWalk XT anymore. This is because the configuration files, which are created the first time you start CatWalk XT, can in this case only be accessed by the administrator and not by other users. To solve this, the administrator should delete all files and folders from C:\ProgramData\Noldus\CatWalk\XT 10.7. After this, only standard users should start CatWalk XT. An error message appears during conversion of an old experiment When opening experiments saved in older CatWalk XT versions, you may get a message like "An error occurred during the conversion of experiment [experiment name]". Do the following: 1. Click OK and Cancel and close CatWalk XT. 2. In Windows Explorer, go to the CatWalk Experiments folder and delete the complete [experiment name] folder which contains the experiment you wanted to convert. Do not try to open the *.cwe file from the [experiment name] folder! 3. In CatWalk XT, restore the backup file that was created when you opened the experiment (step 3 in Open a CatWalk XT 8/9/10.0/10.5/10.6 experiment on page 147). B - Troubleshooting Possible causes for a conversion error are: The disk to which you try to save the experiment is full. You do not have write permission for the CatWalk Experiment folder. There is an error in the Experiment or Experiment folder. In this case, send the backup file An error message appears when opening a run If you get a message "An error occurred while loading the data of run Run#", it means the run is corrupt. We advise you to delete this run. To delete a run, do one of the following: In the Experiment Explorer, right-click a run and select Delete. Open the Acquisition screen, select the corresponding trial and select Live video in the View list. Click one or more runs in the Acquired Runs list and click the Delete Run(s) button. The camera is not detected If the camera is not detected by CatWalk XT, wait some time. After starting up the computer and CatWalk XT, it sometimes takes about a minute before the Ethernet card detects the camera indicated by the 'connecting to network' icon in the Windows task bar. If you do not see the live camera image, it is likely that the driver is not installed or not installed properly. See install the ethernet card driver on page 165. CatWalk led lights not bright This may happen when you turn on the CatWalk Control Unit and the walkway switch is still turned off. Turn off the Control Unit by unplugging the power plug, set the walkway switch to ON and turn on the Control Unit again. Camera gain reached minimum value In the Detection Settings, you might get the message that the Camera Gain reached its minimum value of 6 during auto-detection. This can occur when you use a heavy animal (for example, >300 gr.) for auto-detection. In this case, increase the intensity of the Green Walkway Light by 0.25 and run the auto-detection again. Repeat these steps until the Camera Gain reaches a value higher than 10. A run does not stop after the animal leaves the walkway The background image may no longer be valid. Always grab a new background image after cleaning the walkway or moving the corridor walls. B - Troubleshooting Paw Prints The paw prints are shown in gray When paw prints are shown in gray, it means that they are not selected in the currently active Data Segmentation profile. This also means that those prints are excluded from analysis. To include those prints, use the default Data Segmentation profile All Data, or modify the one currently selected. See Select the data on page 92. There are no rectangles around the paw prints This can happen when, due to a high Camera Gain value or high light intensity in the room where CatWalk is set up, the abdomen or even the complete ventral side of the animal is detected as a paw print (that is, lights up in green in the video window in CatWalk. See the figure below for an example). When this is the case AND in the Acquisition Settings the option Discard incomplete prints at the start and end of a run is selected, the following happens: as soon as the animal enters the camera view, the ventral side of the body overlaps with the border of the camera image, and, because of the selected option, the whole body (that is, all the prints) is discarded. To prevent this from happening, deselect the option Discard incomplete prints at the start and end of a run. The mark UN does not appear during classification Choose Setup > Classification Settings. In the window that opens, de-select both options. B - Troubleshooting The paw prints look faint, or irregular. This may have multiple causes: (a) the camera gain is too low, (b) the walkway lights are too dim, or (c) the green intensity threshold is too high. 1. In the classification screen, click the Adjust the Green Intensity Threshold button. De- select Show filtered out signals. When you move the slider to the right, the prints should shrink and then disappear. When you move the slider to the left, more and more of the prints should appear in green. Change this setting until the prints look good. However this change only affects that run. If that solves the issue, in the Detection Settings, make the same change to the green intensity threshold there to apply to all future runs. 2. If the previous step does not help, the issue may lie in the camera gain or the lights. Go to the Detection Settings (Setup > Detection Settings). Set the Green Intensity Threshold fairly low, for example 0.05. With an animal running across the walkway, look at the value in the middle for Maximum Green Intensity. During a run, this value should be around 200-205. If the animal stops, or walks more times in the same place, the value increases. Click the Reset Prints button to clear that value and try again. If the Maximum Green Intensity is much lower than about 200, raise the Camera Gain. If you raise the Camera Gain to 20 or higher and the maximum green intensity is still too low, also raise the Green Walkway Light setting (only a little bit at a time). Keep clicking Reset Prints while the animal runs back and forth to get new measures. Avoid having the camera gain above 20 as it produces more noise. 3. Once the Camera Gain is set, with a low Green Intensity Threshold you will probably also have a lot of other noise in the image. Now start adjusting that threshold value. You want to get nice clean images of the prints but no green noise anywhere else. If you raise the Green Intensity Threshold too high, you'll start losing the prints themselves. Play with this setting till the prints look good. A paw print is not recognized by the Automatic Footprint Classification This may happen when a paw print has consistently a low value of Max Intensity, and this value is lower then the minimum set in the Classification Settings. Choose Setup > Classification Settings. Next to Only assign a label..., reduce the value of minimum acceptable Max Intensity. Next, repeat automatic classification. B - Troubleshooting The Automatic Footprint Classification does not seem to work well This may occur in two cases: (a) when prints are too light, because the gain in the detection settings is too low, or the noise threshold is too high, or (b) when there is too much noise that confuses the system, because the gain is too high or the noise threshold too low. Especially in the case where there is too much noise, you can adjust the noise threshold in the classification. Click the button Adjust the Green Intensity Threshold and use the slider to raise or lower the threshold. A lower threshold will show more of the prints and noise, while a higher threshold will remove more of them. Your goal is to have only the prints left, as complete as possible, but no noise. The closer you get to that situation, the better a job auto classification will do. If you consistently need to adjust the noise threshold, it's best to do so in the Detection Settings. That is also the only place you can adjust the camera Gain (sensitivity). The Gain can only be adjusted for future trials, not for those which have already been acquired. Paw prints look incomplete in the Interactive Footprint Measurements screen See the arrow in 3 in Figure A.1. When the footprint is shown in the Interactive Footprint Measurements screen, it is enlarged by means of smoothing and anti-aliasing algorithms. Pixels that are outside the border of the footprint rectangle, which contain no data by definition, are "translated" to blue pixels. This may result in effects like that in 3, especially if the image resolution is low. To reduce this effect, place the camera closer to the walkway. Tip: In the Interactive Footprint Measurements screen, right-click the Footprint image and select Switch to 'Normal Color' mode. That way the artifact is less evident. Figure A.1 This scheme shows how the footprint in the IFM may look incomplete. 1 - Original footprint as displayed in the Classification screen. This corresponds to the original pixels used for analysis. 2 - The same image, zoomed in, not resized. 3 - Image in the IFM screen, after resizing. B - Troubleshooting I want to include non-compliant runs in my data set In the lower-left corner, under Data Segmentation Profiles, double-click All Data. In the window that opens, make sure that the two check boxes at the top are not selected. Then click OK and run analysis. How can I separate two paw prints that are near each other? When two paw prints are very near each other, drawing a box around one of the prints is likely to include parts of the other print. 1. Draw a box that only covers (part of) the first paw print, and select Add Print. If a box is already defined around both paw prints, remove that box (right-click and select Remove Print). 2. Draw more boxes for the remaining parts of the paw print, but try not to include the second paw print. Keep selecting Add Print. Each box is now labeled as UN. 3. Draw a larger box around all the boxes and select the paw print you want. 4. Repeat the steps for the other paw print. B - Troubleshooting The Automatic detection of paw prints does not work anymore This could be caused by the glass plate that is not longer in its place. In that case illumination is no longer uniform, that is, only the left or right parts of the catwalk the paw prints are found. Check that it has not been pulled or pushed during transport of the system, and that both the left and right sides of the walkway are equally visible. If you move the system to another location, always do this by pushing/pulling the whole CatWalk stand, not the glass plate! Data Analysis And Export The group means do not correspond to what I calculate using the exported data This occurs because of the way the group means are calculated. In CatWalk XT, the group mean of a variable is calculated by taking the means of the trials that corresponds to that group. So if a group contains 10 trials, the mean is calculated over the 10 trial averages, irrespective of the "weight" of each trial, that is, of how many runs each trial contains. If you consider the single runs, the overall mean value for that group differ from that given by CatWalk XT. The circular charts look distorted when exported When being exported to image files, the circular charts may look stretched or squeezed. To solve this, click the Chart Settings button and select the same value of Chart width, Chart height and Chart size (the latter under Circular charts). Next, export the charts again. C - Gait formulas C Gait Formulas A gait formula starts at Initial Contact (IC) of the left hind paw after all paws have been placed at least once. The Step Cycle then runs until the next IC of the left hind paw. In the Support tab of the Run Statistics, each Step Cycle is put on a separate row. Support Formula During each Step Cycle paws are subsequently raised and placed, leading to different numbers of paws on the ground. The Step Cycle can be subdivided in a number (often 8) of subsequent sections during which different numbers of paws are touching the ground. The Support formula just provides the number of paws on the ground during each section, in the following way: 2 - 3 - 2 - 3 - 2 - 3 - 2 - 3 or 4 - 3 - 2 - 3 - 4 - 3 - 2 - 3 or 1 - 2 - 1 - 2 - 1 - 2 - 1 - 2 Note that the Support formula does not describe which paws are on the ground, nor how long each section is (in relation to the total Step Cycle). Footfall Formula The Footfall formula supplies some of the information which is missing in the Support formula, namely information on which paws are touching the floor during each section, but without information about the relative length of these sections. The Footfall formula can be notated in several graphical ways, but use an alphanumeric notation in the CatWalk program, as follows: 0 No paw touching the ground I One paw touching the ground ILH left hind paw on the ground ILF left front paw on the ground C - Gait formulas IRF right front paw on the ground IRH right hind paw on the ground II Two paws touching the ground IIG Girdle pairs IIGF front paws on the ground IIGH hind paws on the ground IIL Ipsilateral pairs IILL Left side on the ground IILR Right side on the ground IID Diagonal pairs IIDL Left front paw and right hind paw on the ground IIDR Right front paw and left hind paw on the ground III One paw off the ground IIILH Left hind paw off the ground IIILF Left front paw off the ground IIIRF Right front paw off the ground IIIRH Right hind paw off the ground IV Four paws on the ground A possible footfall formula is then as follows: IIILF - IIDR - IIIRH - IILL - IIIRF - IIDL - IIILH - IILR These labels allow us to refer to specific combinations of placed paws and to assign durations (relative to that of the total Step Cycle) to them for further analysis. Especially interesting is the total duration spent in I's combined, and the total in IIG's and/or IIL's combined, as these are unstable (mass-midpoint of the animal is far from the point(s) of support). D - Circular Distributions D Circular Distributions This appendix describes the computation of descriptive statistics for circular distributions of data such as phase lags during locomotion. It provides a very short summary of chapter 26 from Biostatistical Analysis by Zar (1998). Special statistical tests are available for circular distributions. See Zar (1998), Chapter 27. tip Open the Excel file Calculate Circular Statistics of Phase Dispersions and Couplings.xlsx that you can find under C:\Program Files\Noldus\CatWalk XT 10\Documentation. Enter the values of Phase Dispersions and Couplings obtained in runs or trials and see how the main statistics are computed. The Circular Mean If we have a sample consisting of phase lags (periodic on the range 0-100), denoted as through , then the mean of these phase lags, , is to be an estimate of the average phase lag angle in the sampled population . To compute the sample mean phase lag, we first consider the rectangular coordinates of the mean phase lag: and Then the quantity is computed. This is the length of the mean vector, which will be discussed later. (E.1) (E.2) (E.3) a1 an D - Circular Distributions The value of a is determined as the angle having the following cosine and sine: and It is also true that Therefore, the Circular Mean (CStat Mean (%) in CatWalk XT) is Interpreting The Mean And R CatWalk XT reports the CStat Mean in percentage of the step cycle duration. For Phase Dispersions, it ranges from -50 % to +50 %. For Couplings, it ranges from 0 % to 100 %. The value R ranges from 0 and 1. Both CStat Mean and R are important: we can interpret them as a vector with length R and direction . The vector starts at the midpoint of a circle with a radius of 1.00 and ends at the mass midpoint of the phase lag values that are positioned at the circle itself. In the next figure, you find an example of the average of two values of Phase Dispersions, here represented as dots on a circle. X and Y are the average x- and y- coordinates of the dots in a 2D space. The angle formed by the vector is halfway between the two dots. The length of the vector describes the dispersion of the dots around the mean. (E.4) (E.5) (E.6) (E.7) D - Circular Distributions Now imagine to add a few more dots between the two existing ones. The more dots you add, the more the average coordinates X,Y will get closer to the circle. This means that the vector length R will increase. The greater R, the better the direction of the vector is defined, because the data points agree with each other (see the next figure, left). However, if you place points at other locations, far from each other, (right), the length of the vector is reduced, and R is low. Consequently, the value of the mean is a bad measure for the average Phase Dispersion because it represents a group of very different locations on the percentages circle. In other words, R helps you quantify the credibility of the average. When contrasting Phase Dispersions between two experimental groups, you may find a significant difference in R, not in CStat Mean. This means that the two groups do not differ in the average timing of one paw (target, T) relative to the other (anchor, A). However, the higher value of R in one of the two groups indicates lower between-subject variability in the temporal position of T relative to A (see the figure above, left) than in the other group (see the figure above, right). We can visualize this difference in the following way. The subjects in the group with higher R walk more uniformly (see the next figure, top) than those in the group with a low R (see the next figure, bottom), although the average position of T relative to A is not different between the two groups. D - Circular Distributions Measures Of Spread Around The Mean Angular Deviation The vector length R is used to compute the Angular Deviation (CStat AD in CatWalk XT), which is defined as follows: The Angular deviation ranges from a minimum of 0 when R = 1, to a maximum of 22.508 ) when R = 0. note The Angular Deviation CStat AD is the same as the CStat Standard Deviation in CatWalk XT 10.6 and earlier versions. Make sure this does not generate confusion when examining old experiments. Circular Standard Deviation An alternative measure which ranges from 0 to , the Circular standard deviation (CStat SD in CatWalk XT), is defined as follows: (E.8) (E.9) 100/22 D - Circular Distributions The Circular standard deviation s0 ranges from 0 to , therefore it more closely resembles the standard deviation on a linear scale. However, it is reasonable to assume that circular have a limited spread; in that case Angular Deviation may be a better option. note The Circular Standard Deviation CStat SD is not the same as the CStat Standard Deviation in CatWalk XT 10.6 and earlier versions. Make sure this does not generate confusion when examining old experiments. Note that Angular Deviation and Circular Standard Deviation tend to converge as the data cluster around the mean. The Circular Group Mean When calculating Group statistics (Analyze > View Group Statistics and Charts), the group mean CStat Mean is calculated with the same formulas as for the mean of single values of Phase Dispersions and Couplings (see page 176). example A group includes three trials. The per-trial averages of Couplings are 5 %, 95 % and 100 %. The circular mean provided by CatWalk XT is 0 % (that is the same as 100 %). Using the arithmetic mean would result in a value (66,67 %) far from the original ones. The Excel Sheet "calculate Circular Statistics" If you are not familiar with circular statistics, you can practice with the Excel sheet Calculate Circular Statistics for Phase Dispersions and Couplings.xlsx, which you can find in the same folder as this manual: C:\Program Files\Noldus\CatWalk XT 10\Documentation 1. Open the Excel file. 2. Enter the values of Phase Dispersions or Couplings, for example those displayed in CatWalk XT for a specific run. D - Circular Distributions 3. Explore the formulas that lead to the main results: CStat Mean (%), CStat Angular Deviation (%) and CStat Standard Deviation (%). 4. Enter one or more values in the Values (%) column, to see the effect on the statistics and on the orientation of the vector in the chart that is shown on the right. Notes If CStat Mean is negative, and you prefer to have positive values, locate the Complementary Mean (%). Do this especially when you enter the values of Couplings. For example, if the CStat Mean (%) is -25 %, the complementary mean valid in the range for Couplings (0-100 %) is 75 %. The formulas for calculating circular statistics are protected and cannot be changed. There may be small differences between the statistics given by CatWalk XT and those in the Excel sheet. In general they do not exceed 0.01% and are the effect of rounding of cell values. You can increase the number of decimals in CatWalk XT (File > Preferences > Number of Decimals) to better locate those differences. Confidence Limits For The Population Mean CatWalk XT does not calculate the confidence limits for the mean. You can calculate the confidence limits as: ā ± d (E.10) where d is defined as follows (if n > 8). For , and (E.11) 0.9 2a 1 / 2n D - Circular Distributions and for where R = nr, and the significance level. Critical values for the distribution with 1 degree of freedom ( ) are given in table D.1. Table D.1. Critical values for the 2 distribution with v=1 (Zar 1998, table B.1). (E.12) Confidence interval 0.999 0.001 10.282 0.995 0.005 7.879 0.990 0.010 6.635 0.975 0.025 5.024 0.950 0.050 3.841 0.900 0.100 2.706 0.750 0.250 1.323 0.500 0.500 0.455 0.9 a 1 E - Protocol for training and testing using the Noldus goal box E Protocol For Training And Testing Using The Noldus Goal Box F - References F References For a complete and up-to-date list CatWalk XT publications, see our web page See also Application examples on page 135. Bain JR, Mackinnon SE, Hunter RT (1989). Functional evaluation of complete sciatic, peroneal, and posterior tibial nerve lesions in the rat. Plast Reconstr Surg 83: 129-136. Coulthard P, Pleuvry BJ, Brewster M, Wilson KL, Macfarlane TV (2002). Gait analysis as an objective measure in a chronic pain model. J Neurosci Methods 116: 197- 213. Coulthard P, Simjee SU, Pleuvry BJ (2003). Gait analysis as a correlate of pain induced by carrageenan intraplantar injection. J Neurosci Methods 128: 95-102. Hamers FPT, Lankhorst, AJ, Van Laar, TJ, Veldhuis, WB, Gispen WH (2001). Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries. J Neurotrauma 18: 187- 201. Hamers FPT, Koopmans GC, Joosten EAJ. (2006) CatWalk assisted gait analysis in the assessment of spinal cord injury. J Neurotrauma 24: 537-548. Hildebrand M (1976). Analysis of tetrapod gaits: general considerations and symmetrical gaits. In: Herman RM, Grillner S, Stein PSG, Stuart DG, Neural control of locomotion, Plenum, NY. Inserra MM, Bloch DA, Terris, DJ (1998). Functional indices for sciatic, peroneal, and posterior tibial nerve lesions in the mouse. Microsurgery 18: 119-124. Kloos AD, Fisher LC, Detloff MR, Hassenzahl DL, Basso DM (2005). Stepwise motor and all-or- none sensory recovery is associated with nonlinear sparing after incremental spinal cord injury in rats. Exp Neurol 191: 251-265. Koopmans GC, Honig WMM, Hamers FPT, Steinbusch HWM, Joosten EAJ (2005). The assessment of locomotor behavior in spinal cord injured rats; the importance of objective analysis of locomotion. J Neurotrauma 22: 214-225. Vrinten DH, Hamers FPT (2003). 'CatWalk' automated quantitative gait analysis as a novel method to assess mechanical allodynia in the rat; a comparison with von Frey testing. Pain 102: 203-209. Zar JH (1998). Biostatistical Analysis, 4th edition. Prentice Hall: NJ. G - History of CatWalk G History Of CatWalk (Text by Frank Hamers, MD, PhD - October 24, 2005) CatWalk was developed by Dr. Frank Hamers (Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, The Netherlands) as a research tool for his work on functional recovery from spinal cord contusion injury in the rat. Development started in the summer of 1996, after he had spent a month at the lab of Dr. Michael Beattie and Jacqueline Bresnahan at OSU (Columbus, OH) to gain experience with the newly developed Basso- Beattie-Bresnahan locomotor rating scale (BBB-test), a very sensitive and reproducible open- field test for assessment of locomotor recovery in this animal model. An important landmark in the BBB-test is the return of FL-HL coordination, something which may be difficult to see with the naked eye. The definition used in the BBB-score is an operational one as it is impossible to follow all four paws at the same time: even with two observers (the recommended setup for BBB-testing) each observer only sees at most three paws at the same time. Several months earlier, Frank Hamers had read some papers written by Kenneth Clarke (University of Sheffield, UK) who used a special walkway which enables evaluation of the presence of paw-floor contact with unprecedented detail for his own research on gait development in rat puppies. Frank Hamers believed that such a walkway might be used to enable better evaluation of FL-HL coordination in spinal cord lesioned animals and back in Utrecht a prototype of the walkway was built: it behaved as expected. The first full-featured walkway was built in a weekend by Jan Brakkee, the chief biotechnician in the regeneration group and several other have been built by the author himself after that. Frank Hamers had well-developed software engineering skills - in fact, since he enrolled in the lab as a PhD student in 1988 he largely automated data acquisition in the whole of the regeneration group - and as such he set out to write a simple videotaping program to capture animals crossing the walkway. This was the prototypical CatWalk program which eventually evolved into the program such as it is now. This evolution was driven by Frank Hamers' own research questions, and those of his collaborators using the system, the more as regeneration research was banned from the Pharmacology & Anatomy lab shortly after 2001. For instance, assessment of coordination is just one of the many things that the program can be used for and its ability to assess FL-HL coordination in an unbiased way has only recently been combined with the BBB-test by Guido Koopmans, a former PhD student in Bert Joosten's lab at Maastricht University. The first meaningful results with the system were presented at the Annual Neurotrauma Symposium in Miami Beach in November 1999. The second and third systems were set up by Frank Hamers at Jacqui Bresnahan's lab at OSU and at Barbara Bregman's lab at Georgetown University in September 2000, followed almost immediately by a system in Joost Verhaagen's lab at the Netherlands Institute for Brain Research in Amsterdam. Since then, the number of installed systems has greatly expanded and the value of the system in many different nervous system lesion models and others becomes increasingly more clear. G - History of CatWalk Acknowledgments (Text by Frank Hamers, MD, PhD - October 24, 2005) The CatWalk system would not have been possible without Dr Willem Hendrik Gispen, the leading force behind nerve regeneration research in Utrecht and originally my PhD thesis advisor. During his tenure as scientific director of the Department of Pharmacology & Anatomy and that of the Rudolf Magnus Institute of Neuroscience -which was his creation- he inspired clinical and basic scientists to collaborate on the most difficult problems in (clinical) neurosciences. After completion of my PhD thesis on cisplatin neuropathy he offered me a position in his staff and as such I eventually started spinal cord research: In 1996 I visited the Beattie/Bresnahan lab at OSU to learn the BBB-score, and I returned with the idea to further objectify assessment of FL-HL coordination in this test. In this I was fully supported by Willem Hendrik Gispen. Jan Brakkee spent a weekend in his workshop at home to build a walkway. All (PhD) students helped in testing, and it was together with Dr Alex Lankhorst that I published the first validation studies. Dr Tinna Ängeby-Möller from AstraZeneca Pain Research in Sweden was the first one with the idea to use this device for quantification of pain. Drs Dorien Vrinten and Tineke Vogelaar have been most appreciated collaborators on the pain and peripheral nerve regeneration studies. On the other side of the ocean, Drs Jacqueline Bresnahan and Michael Beattie have been my strongest supporters ever since they got a demonstration of the walkway's abilities. Implementation of the phase lag parameters was driven by Dr Michelle Basso. Their continuing input in and promotion of the system are very much appreciated. Dr Joost Verhaagen, like Drs Beattie and Bresnahan in the US, has been one of my staunchest supporters in Europe, and I hope that I can continue the very rewarding collaboration with members of his lab on problems related to nerve regeneration. My foremost collaborator in the last three years has been Dr Bert Joosten. After his move from Utrecht to Maastricht he needed to start his own behavioural research and he decided to set up a CatWalk system as well. In Maastricht he also entered the pain field, and all his students use CatWalk, either for SCI or for pain, and they generate lots of data, questions and discussion. And it was Guido Koopmans (2005), one of Bert's PhD students, who eventually showed that CatWalk can be used to more reliably assess FL-HL coordination than open-field testing, enabling one to observe otherwise missed treatment effects. But my most important supporter over the years has been my wife, Ingeborg, who did not complain when I worked at the program in the evenings and weekends, and who fully supported my regular lab and conference-visits abroad, despite her own demanding job and the doubled household/childcare obligations with me abroad. 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Other than set out in Section 6.1, no warranties are expressed or implied with respect Software or any element thereof, including without limitation its quality, performance, I - End-User License Agreement accuracy, merchantability or suitability or fitness for any purpose, whether or not that purpose has been communicated by End-User to Noldus. The Software is a general product developed by Noldus for a wide range of solutions, requirements and situations and End- User is responsible for purchasing the Software required for his needs. Noldus explicitly does not warrant that the Software shall be entirely without error or fault nor that it will operate without interruption. End-User agrees that such errors, faults or interruptions shall not be deemed material and cause to terminate this EULA. 6.3. The warranty by Noldus set out in Section 6.1 applies only to the first installation of the Software and will not apply, resume or renew upon delivery or installation of any subsequent update or upgrade to the Software, alteration in the number of EULA's granted for use of the Software, or any other extensions, upgrades or alterations to the Software where the Software has previously been delivered to or installed by the End-User. 6.4. The warranty by Noldus set out in Section 6.1 shall further not apply to Software that is licensed or otherwise made available at no cost, or Software that is designated as 'prototype', 'alpha' or 'beta' code, all of which are provided 'as is' and without warranty, representation or liability. 6.5 Upon receipt of an End-User's written notice of the Software not conforming to the Specifications during the Warranty Period, Noldus shall at its option and in its sole discretion (i) assist the Customer in correcting or replacing the non-conforming Software or, (ii) terminate the EULA immediately and refund the purchase price paid by the End-User. The remedies described above shall be End-User's sole and exclusive remedies. Upon expiration of the Warranty Period, Noldus shall have no obligation to provide such remedies. 6.6 Noldus and Authorized Partners, are not responsible for maintaining or supporting use of the Software or obligated to provide any updates, fixes or support to the Software unless otherwise expressly agreed in writing between End-User and Noldus or the Authorized Partners. 7. USE LIMITATION; LIABILITY; INDEMNIFICATION 7.1. End-User acknowledges that the Software is intended for research or training purposes only and agrees not to use the Software for diagnosis or treatment of disease in human subjects. End-User agrees not to use the Software in any application where the failure, malfunction or inaccuracy of the Software carries the risk of death or bodily injury. 7.2. Noldus Software shall not be used for collection of biometric data from human subjects without prior informed consent from the person whose data is being captured. 7.3. Noldus does not allow the use of its Software for the following applications: a. Active defense, i.e. embedding Noldus Software in a weapon system. b. Biometric data collection in criminal, security-related or similar investigations or procedures. c. Surveillance of people in public spaces for security purposes. I - End-User License Agreement d. Any other use that may potentially violate fundamental human rights (https://www.un.org/en/about-us/universal-declaration-of-human-rights). 7.4. If Noldus notices that its Software is used for applications that it does not approve, this may lead to discontinuation of customer support and termination of the EULA. 7.5. To the fullest extent permitted by law, and not withstanding any other provision of this EULA to the contrary: a. In no event will Noldus or the Authorized Partners be liable to the End-User for Indirect Losses or for special, incidental, consequential, exemplary, enhanced, or punitive damages, including without limitation, any damages resulting from interruption of business, loss of use, loss of profits or revenue, or loss of business, arising out of or in connection with this EULA, the Software, or the performance of Noldus, the Authorized Partners, or third parties engaged by Noldus in the performance of this EULA, regardless of whether Noldus, the Authorized Partners, End-User, or any other person or entity has been advised of (or could have reasonably foreseen) the possibility of such damages or Indirect Losses. If, despite the provisions in this EULA, liability exists anyway, only direct damage will be eligible for reimbursement. 7.6. Noldus' and Authorized Partners' liability shall also be excluded, and Noldus and the Authorized Partners shall not have any liability under this EULA in the event of: a. End-User's use of the Software other than in accordance with Section 7.1; b. in the event of direct and indirect consequences of the End-User's failing to adhere strictly to the user documentation provided or made available by Noldus or the Authorized Partner; or c. any loss of or damage to files or data howsoever caused. 7.7. A liability claim will be unenforceable and lapse unless Noldus or the Authorized Partner receives a written notice thereof no later than 6 months after the discovery of an event or circumstance that gives or may give rise to that claim. 7.8. Noldus will hold harmless, defend, and indemnify End-User from and against all losses, damages, claims, liabilities, and expenses incurred by End-User that arise out of, relate to, or are caused by any third party claim that End-User's use of the Software, pursuant to the terms of the this EULA, infringes the intellectual property rights of such third party. If such a claim is made or appears likely to be made, Noldus, at its option, will have the right to either (i) procure for the End-User the right to continue to use the Software, (ii) modify or replace the Software so that it is no longer infringing (in a manner that substantially retains its functionality and quality), or (iii) require End-User to terminate the use of and return the Software and refund a pro rata portion, if any, of the amount paid by End-User to Noldus for the infringing Software. Notwithstanding the foregoing, Noldus will have no liability to End- User if the infringement results from use of the Software in combination with software not provided by Noldus or from modifications made by Noldus to conform to specifications provided by End-User. The indemnification obligations in this section are subject to: (i) End- I - End-User License Agreement User giving Noldus prompt written notice of any claim (provided that End-User's failure to provide prompt written notice will only relieve Noldus of its obligations under this Section to the extent such failure materially limits or prejudices Noldus' ability to defend or settle such claim); (ii) the transfer of sole control of the defense and any related settlement negotiations to Noldus; and (iii) End-User's cooperation, at Noldus' expense, in the defense of such claim. THIS SECTION STATES END-USER'S SOLE AND EXCLUSIVE REMEDIES FOR THIRD PARTY INTELLECTUAL PROPERTY INFRINGEMENT CLAIMS. 7.9. End-User shall indemnify and hold harmless Noldus, the Authorized Partners, and the third parties engaged by Noldus from and against any and all losses (including Indirect Losses and special, incidental, consequential, exemplary, enhanced, or punitive damages) arising out of or caused by (i) any failure in the performance of the obligations of the End- User under the law, this EULA, or Noldus' General Terms and Conditions, or (ii) any and all third party claims on any grounds whatsoever, directly or indirectly related to the End-User's use of the Software, the contents thereof, or any results or materials generated by the Software. 7.10. THE LIMITATION OF LIABILITY PROVISIONS SET FORTH IN THIS SECTION 7 SHALL APPLY EVEN IF END-USER'S REMEDIES UNDER THIS EULA FAIL OF THEIR ESSENTIAL PURPOSE. 7.11. Noldus and End-User acknowledge and agree that the parties entered into this EULA in reliance upon the limitations of liability set forth in this Section 7, that the same reflect an allocation of risk between the parties (including the risk that a contract remedy may fail of its essential purpose and cause consequential loss), and that the same form an essential basis of the bargain between the parties. 8. MISCELLANEOUS 8.1. Parties may communicate with each other by electronic mail. Parties recognize the risks associated with electronic mail and declare that they shall not hold each other liable for any damage incurred by either of them as a result of the use of electronic mail. If a Party is in doubt as to the content of an electronic message received, the content of the message originating with the sender shall be decisive. 8.2. The invalidity or unenforceability of any provision this EULA shall not affect or limit the validity or enforceability of any other provisions thereof. Any such invalid or unenforceable provision shall be deemed to be substituted by a provision that is considered to be valid and enforceable. The interpretation of the substituting provision shall be as close as possible to the economic, legal and commercial objectives of the severed provision. 8.3. Failure by Noldus or the Authorized Partner to enforce any of its rights under the EULA shall not constitute a waiver of such rights thereunder and shall not relieve End-User of its obligation to comply with such provisions. No waiver or amendment of any provisions therein shall be effective unless signed in writing by a Noldus representative. Any such written waiver shall only be applicable to the specific instance to which it relates and shall not be deemed to be a continuing or future waiver. I - End-User License Agreement 8.4. Amendments or changes to this EULA can only be agreed upon in writing between the Parties. 8.5. The EULA shall be binding upon the Parties thereto, their legal representatives, successors and assigns. End-User shall not assign any right or obligation arising out of this EULA without the prior written consent of Noldus. Any attempt by End-User to assign or delegate any obligation hereunder shall be deemed null and void. 9. GOVERNING LAW: END-USERS USA OR CANADA 9.1. If End-User is a legal entity and its principal place of business is located in the United States of America or Canada, or if End-User is an individual whose primary residence is located in the United States of America or Canada: a. This EULA is exclusively governed by the laws of the Commonwealth of Virginia and the applicable federal laws of the United States of America, without regard to the conflicts of law provisions of any jurisdiction. Without limiting the previous sentence, End-User and Noldus expressly agree: (i) that the Virginia Uniform Computer Information Transactions Act, Virginia Code §§ 59.1-501.1 et seq. ("UCITA"), and the United Nations Convention on Contracts for the International Sale of Goods ("CISG") are expressly excluded from this EULA, (ii) that any and all terms contained in UCITA or CISG will have no force or effect on any portion of this EULA, and (iii) that UCITA and CISG do not apply to this EULA or the Software. b. Any and all claims and disputes arising out of or in connection with this EULA, the Software, or the performance or non-performance by either party of any of its obligations under this EULA, which End-User and Noldus cannot resolve amicably within a reasonable period of time, will be commenced and maintained only in a state or federal court of competent subject matter jurisdiction situated or located in the United States of America. Noldus and End-User consent to the exclusive personal jurisdiction of and venue in any such court. c. To the extent permitted by law: End-User must commence or file any claim or action arising out of or relating to this EULA or the Software within six months after the cause of action accrues, otherwise, such claim or cause of action is permanently barred. To the extent permitted by law, End-User expressly waives the right to commence or file any such claim or action under any longer statute of limitations. 10. GOVERNING LAW: END-USERS OTHER COUNTRIES 10.1. If End-User is a legal entity and its principal place of business is located in any country other than the United States of America or Canada, or if End-User is an individual whose primary residence is located in any country other than the United States of America or Canada: a. This EULA is exclusively governed by the laws of The Netherlands. The United National Convention for Contracts on the International Sale of Goods is expressly excluded. I - End-User License Agreement b. Any disputes arising out or in connection with this EULA that cannot be solved amicably within a reasonable period of time will be submitted to the competent court in Arnhem, The Netherlands, for any dispute with End-Users having their principal place of business in the European Union. In the event that an End-User has its principal place of business outside the European Union, the United States of America or Canada, any dispute shall be finally settled in accordance with the Arbitration Rules of the Netherlands Arbitration Institute. Location shall be Arnhem, The Netherlands. The arbitration procedure shall be conducted by one (1) arbiter in the English language. J - Acknowledgments and Copyright notices J Acknowledgments And Copyright Notices CatWalk™ is a trademark of Noldus Information Technology BV. CatWalk XT would not be what it is without the use of third-party software. This page lists software libraries and other software products used in CatWalk XT and where you can find license and compliance information and/or acknowledgments for that product. Boost Open source (Boost community) software library, C++ templates. Link/License: Boost software license http://www.boost.org/users/license.html FFmpeg Cross-platform solution to record, convert and stream audio and video https://ffmpeg.org Noldus IT does not own FFmpeg or any component thereof. GNU Lesser General Public License (LGPL) version 2.1 https://ffmpeg.org/legal.html HASP Library for software protection. EULA https://supportportal.gemalto.com/ csm?id=kbarticleview&syskbid=f8ad2d43db19ff04d298728dae96195d&sysparm_articl e=KB0018933 Thales Group https://cpl.thalesgroup.com/ OpenCV 4.7.0 Software library for various computer vision problems http://www.intel.com/content/www/us/en/research/intel-research.html Apache License 2.0 https://github.com/opencv/opencv/blob/master/LICENSE J - Acknowledgments and Copyright notices OpenCvSharp OpenCV wrapper for .NET https://github.com/shimat/opencvsharp Apache License 2.0 https://github.com/shimat/opencvsharp/blob/master/LICENSE Wix Toolset Tools to author software installers http://wixtoolset.org/ .NET Foundation https://dotnetfoundation.org/ Microsoft Reciprocal License (MS-RL) https://opensource.org/license/ms-rl-html/ Index - Numerics 2D Footprint Intensities - 99 exporting to video - 161 3D Footprint Intensities - 97 exporting to video - 161 3D-chart overview of complete data - 95 - A Abdomen label - 74, 122 Abort runs - 53 About CatWalk XT - 13 Accounted Steps - 116 Acquire data see Data Acquisition Acquired Runs list - 60 Acquisition Settings background image - 53 run settings - 53 sound feedback - 54 specifying - 53 Acquisition Status - 64 Activating data segmentation profiles - 151 parameter profile - 151 Active run, exporting - 152 Adding an incomplete print - 77 data segmentation profile - 92 experiment setup profiles - 43 parameter profile - 96 prints - 77 time points - 38 treatment groups - 38 trials - 41 Add-on module - 19 Adjusting the Green Intensity Threshold after acquisition - 67 All runs from active trial, exporting - 152 Alternate Footfall Pattern - 103 AMT - 125 Amyotrophic lateral sclerosis - 139 Analyzing Data - 91 run statistics - 104 visualization - 97 Anchor - 124 Anchor start - 124 Angular Deviation - 179 Animal ID - 41 Animal training - 47 Animal Type - 37, 148 ANT - 125 Applications of CatWalk - 10 Arthritis - 143 Assembly Instructions - 16 Assigning labels manual - 73 speeding up - 75 Asterisk - 65 Auto Save - 44 Automatic Footprint Classification requirements - 70 scenarios for classification - 67 Average Speed in data selection - 95 of a recorded run - 60 Index of selected steps - 92 Average speed - 119 Average speed interval - 94 Average speed should range from - 92 AVI, uncompressed - 161, 162 - B Background Image - 53 Backup - 13, 149 Backup file - 149 Bar Chart - 130 Bar width - 132 Base of Support - 119 Base of Support sheet - 118 Beep see sound feedback Body Axis - 88 Body Speed - 92, 115 Body Speed Variation - 115 Busy/alive light - 33 - C Cadence - 120 Calibrating the walkway - 36 Calibration x-unit - 105 y-unit - 105 Camera - 9, 35, 48 Camera connection lost - 62 Camera Gain - 51 Camera position - 35, 57 Carrying out data acquisition - 58 CatWalk 7.x - 147 CatWalk error - 83 CatWalk history - 185 CatWalk XT 8/9 experiment converting - 147, 148 opening - 147 Cerebellar ataxia - 139 Charcot-Marie-Tooth disease - 144 Chart height - 131 Chart size (circular) - 132 Chart type - 130 Chart width - 131 Charts - 129 chart type - 130 exporting - 159 Charts settings - 130 Circular charts - 132, 133 Circular distributions - 176 Circular group mean - 180 Circular mean - 176 Circular scale - 134 Circular Standard Deviation - 179 Classification error detection - 84 Classification scenarios - 67 Classification Settings - 71 only assign a label when the Max Intensity is higher than - 71 reset all assigned labels when applying the AFC - 71 Classification Status - 90 Classifying prints - 67 Classifying Runs graphical results - 79 numerical results - 81 zooming in / out - 75 Classifying toes see Interactive Footprint Measurements - 86 Cleaning the glass plate - 57 Clipboard copy to - 81, 99, 103 Clipboard copy to - 80 Codes - 116 Color preferences - 45 Colorized mode - 80 Combining stances - 76 Complete Data Overview - 94 Index Complete print - 110 Completely classified - 90 Compliant/Non-compliant - 60 Computer requirements - 16 Confidence limits - 181 Configuring Detection Settings - 48 Control Unit - 33 firmware upgrade - 33 turning on/off - 33 Conversion error - 148 Converting a CatWalk XT 8/9 experiment - 147 Copying text in the trial list - 42 Copyright notices - 198 Correcting catwalk error - 83 interactive footprint measurements errors - labeling error - 82 Corridor position - 57 Couplings - 126 parameter profile - 96 Couplings sheet - 126 Creating an experiment - 147 backup file - 149 data segmentation profiles - 150 experiment setup profiles - 43 parameter profile - 150 Cruciate Footfall Pattern - 103 CStat AD - 125, 130, 179 CStat Mean - 125, 130, 133 CStat R - 125, 130 CStat SD - 125, 130, 179 Current Green Intensity Threshold - 68 CWE file - 147 CWZ file - 149 - D Data Acquisition - 56 snap background - 58 status message - 62 Data points in circular chart - 134 Data Segmentation see Selecting Data - 92 Data Segmentation Profile - 92 activating - 151 adding - 92 creating - 150 duplicating - 151 opening - 151 Data selection see Selecting Data - 92 Data series - 131 Default settings for Detection Settings - Defining the layout of the walkway - 35 Defining the Trial List - 41 Deleting data segmentation profiles - 151 experiment setup profiles - 44 parameter profile - 151 run - 150 runs - 63 time points - 38 treatment groups - 39 trial - 150 trials - 42 Detection Settings camera gain - 51 configuring - 48 frames before delta - 51 green intensity threshold - 51 intensity minimum - 51 manual - 51 maximum intensity - 51 maximum range from - 51 minimum intensity - 51 range - 52 Detection Settings Profiles - 48 default values - 49 for mice - 49 for rats - 49 Discard aborted runs - 53 incomplete prints - 54 non-compliant runs - 54 Index Distance Units - 44 Dongle see hardware key Drivers - 164 Duplicating data segmentation profiles - 151 experiment setup profiles - 43 parameter profile - 151 Duty Cycle (%) - 113 - E End-User License Agreement - 189 Excel - 104, 152, 154, 155, 157, 158, 159, 160 Exclude non-compliant runs - 93 Exclude partially classified runs - 93 Experiment - 36 backup and restore - 149 creating - 36, 147 opening - 147 saving - 148 Experiment Explorer data selection status of trials and runs - 65 Experiment Settings animal type - 37 specifying - 37 time points - 38 treatment groups - 38 Experiment Setup Profiles adding - 43 deleting - 44 duplicating - 43 opening - 43 renaming - 43 Export active trial - 157 Export all runs from active trial - 154 Export all runs from all trials - 154 Export all trials - 157 Export file group statistics - 160 run statistics - 155 trial statistics - 158 Exporting 2D visualizations to video - 161 3D visualizations to video - 161 all runs from active trial - 152 camera gain - 155, 159 charts - 159 footfall patterns to video - 161 green intensity threshold - 155, 159 max intensity - 153 mean intensity - 153 means - 155, 157 min intensity - 153 print area - 153 print length - 153 print width - 153 run data - 152 run data export file - 152 run statistics - 153 run video - 161 standard deviation - 155, 157 trial statistics - 156 visualizations to video - 160 x-unit - 155, 159 y-unit - 155, 159 Exporting active run - 152 Exporting Data - 152 - F False Color mode - 80 Filtering out signals - 68 Firmware of Control Unit - 33, 34 Five Number Summary Chart - 130 Font size - 131 Footfall Formula - 128, 174 Footfall Patterns - 100, 116 alternate - 103 cruciate - 103 exporting to video - 161 labels - 103 rotate - 103 Footprint Intensities 2D chart - 99 3D chart - 97 Frame rate - 105 Frames before delta - 51 - G Gait formulas - 174 Index General sheet - 105 camera gain - 105 frame rate - 105 green intensity threshold - 105 x-unit - 105 y-unit - 105 Genitalia label - 74, 122 Glass plate cleaning - 57 Goal box - 47, 48, 57 Graphical Results - 79 print view - 79 timing view - 80 Graphs see Charts Gray paw prints - 97, 104 Green Intensity Threshold adjusting after acquisition - 67 classification - 67 detection settings - 51 effect on run statistics - 69 Green Walkway Light adjusting intensity - 52 Group charts - 130 Group statistics - 129 - H Hardware key - 17, 20 Heels not visible - 88 Help topics - 13 Hip label - 74, 122 History of CatWalk - 185 Horizontal axis - 130 Huntington's disease - 144 - I IFM see Interactive Footprint Measurements Independent variable see Treatment Groups see Trial List Initial Contact At (s) - 106 Initial Dual Stance - 114 Installation of software - 17 Intensity adjusting the green walkway light - 52 adjusting the red ceiling light - 52 Intensity minimum - 51 Interactive Footprint Measurements - 37, body axis - 88 correcting errors - 89 intermediate toe spread - 88 manual print length - 88 paw angle body axis - 88 paw angle movement vector - 88 toe spread - 87 Intermediate Toe Spread - 88, 114 Interval average speed - 94 speed variation - 94 Ischemia - 138 - J Junk labeling - 77 removing - 77 - K Knee label - 74, 122 - L Labeling error - 82 Labeling Junk - 77 Labeling non-paw prints - 67, 74 Labels - 74 exporting - 162 of footfall patterns - 103 show/hide - 79 Left and right determining - 73 Length of defined walkway - 159 License Agreement - 189 License Info - 13, 19 Light conditions - 48, 51 Index - M Manual Detection Settings - 51 Manual Print Length - 88, 114 Max Contact Area - 108 Max Contact at - 76 Max Contact At (%) - 108 Max Contact At (s) - 108 Max Intensity - 108, 112 Max Intensity at (%) - 111 Max Intensity at (s) - 111 Maximum allowed speed variation - 92 Maximum allowed speed variation in data selection - 95 Maximum Intensity - 51 Maximum number of runs - 40 Maximum range from - 51 Maximum run duration - 40 Maximum run recording - 61 Maximum Variation (%) - 120 Maximum variation of a recorded run - Mean exporting - 157 Mean (circular) - 125, 176 Mean Intensity - 109 Mean intensity - 112 Mean Intensity of the 15 Most Intense Pixels - 112 Mean of mean phase lags - 130 Mean speed see average speed Mean, exporting - 155 Mechanical allodynia - 109 Min Intensity - 112 Minimum number of compliant runs to acquire - 40 Minimum number of consecutive steps per run - 92 Minimum run duration - 40 Monoarthritis - 143 Motor coordination - 140 Mouse - 37 - N N - 119, 129 Neuropathic pain - 109, 137 Noldus Support - 13 Non-compliant - 60 Non-compliant runs, discard - 54 Normal Color mode - 80 Normal Patterns - 116 Nose label - 74, 122 Number of selected animals - 93 selected runs - 93 selected steps - 93 Number of steps - 120 Numerical Results - 81 image - 81 initial contact (s) - 81 max contact area - 81 max contact at (s) - 81 max intensity - 82 mean intensity - 82 print - 81 print area - 82 print length - 82 print width - 82 stand (s) - 81 - O Only assign a label when the Max Intensity is higher than - 71 Opening a run - 150 a trial - 150 an experiment - 147 backup file - 149 catwalk xt 8/9 experiment - 147 data segmentation profiles - 151 experiment setup profiles - 43 parameter profile - 151 Index Operating system - 16 Original Green Intensity Threshold adjusting green intensity threshold - 68 Osteoarthritis - 143 Other Statistics sheet - 119 average speed - 119 cadence - 120 maximum variation (%) - 120 number of steps - 120 other prints - 122 Peroneal functional index - 121 Sciatic functional index - 120 Tibial functional index - 121 Overlay Text exporting - 162 show/hide - 79 - P Pain research - 109, 114 Parameter Profile - 96 activating - 151 adding - 96 creating - 150 deleting - 151 duplicating - 151 opening - 151 renaming - 151 Parameter selection see Selecting Parameters Parkinson's disease - 141 Partially classified - 90 Pasting text in the trial list - 42 Paw Angle Body Axis - 88, 114 Paw Angle Movement Vector - 88, 114 Paw print labels - 74 Paw Statistics - 106 body speed - 115 body speed variation - 115 duty cycle (%) - 113 initial contact at (s) - 106 initial dual stance - 114 intermediate toe spread - 114 manual print length - 114 max contact area - 108 max contact at (%) - 108 max contact at (s) - 108 max intensity - 108, 112 max intensity at (%) - 111 max intensity at (s) - 111 mean intensity - 109, 112 mean intensity of the 15 most intense pixels - min intensity - 112 paw - 106 paw angle body axis - 114 paw angle movement vector - 114 print area - 110 print length - 110 print width - 110 single stance - 114 stand - 106 stand index - 106 step cycle - 113 stride length - 112 swing - 112 swing speed - 112 terminal dual stance - 114 toe spread - 113 x - 109 y - 110 Paws parameter profile - 96 PC report - 14 Peculiarities - 125 Peroneal Functional Index - 86, 121 formula for mice - 121 formula for rats - 121 Phase Dispersions - 123 anchor duration - 124 anchor start - 124 Cstat - 125 parameter profile - 96 peculiarities - 125 target start - 125 value - 124 variability - 140 Phase Dispersions sheet - 123 Playback speed see Speed Playing back runs see Reviewing Runs Power light - 33 Preferences colors - 45 Index setting - 44 Preparing Data Acquisition - 46 Preparing the walkway - 57 Principle of operation - 9 Print Area - 110 Print Length - 110 Print Positions - 122 Print Positions sheet - 122 Print Width - 110 Prints adding - 77 discard incomplete prints - 54 - R Rat - 37 Ready for acquisition - 61 Recording Run - 62 Rectangles exporting - 162 show/hide - 79 Red Ceiling Light adjusting intensity - 52 Red light - 48 References - 184 Refsum disease - 144 Removing junk prints - 77 Renaming data segmentation profiles - 151 experiment setup profiles - 43 parameter profile - 151 Requirements for automatic classification - 70 Reset all assigned labels when applying the AFC - 71 Restore - 13, 149 Reviewing Runs - 62, 78 graphical results - 79 numerical results - 81 video window - 78 Rotate Footfall Pattern - 103 Run Average Speed - 60, 105 Run Average Speed vs Average Speed - 92 Run Criteria - 39 maximum run duration - 40 minimum number of compliant runs to ac- quire - 40 minimum run duration - 40 use maximum allowed speed variation - 40 Run Data, exporting - 152 Run Duration - 60, 105 Run Maximum Variation - 60, 105 Run Settings - 53 auto abort runs... - 53 discard aborted runs - 53 discard incomplete prints - 54 discard non-compliant runs - 54 Run Statistics - 104 exporting - 153 general sheet - 105 grouped - 129 paw statistics sheet - 106 step sequence sheet - 115 summary sheet - 104 Run Video, exporting - 161 Run Visualizations, exporting - 160 Running speed see speed Runs acquired runs list - 60 auto-abort - 53 classification status - 90 completely classified - 90 compliant - 60 corrupt - 150 deleting - 63, 150 discard in run settings - 53 maximum number to acquire - 40 non-compliant - 60 opening - 150 partially classified - 90 playing back - 62 reviewing - 62, 78 visualization - 97 - S Sample experiments - 12 Index Sample size - 129 Saving an experiment - 148 Saving Preferences - 149 Saving Settings - 149 Sciatic Functional Index - 37, 86, 120 formula for mice - 120 formula for rats - 120 settings - 89 Sciatic nerve injury - 142 Selected Animals, number of - 93 Selected Data Overview - 93 Selected Runs, number of - 93 Selected Steps, number of - 93 Selecting Data - 92 average speed should range from - 92, 95 maximum allowed speed variation - 92, 95 minimum number of consecutive steps per run - 92, 95 overview of complete data - 94 overview of selected data - 93 parameter profile - 96 Selecting data trial and run status in project explorer - 64 Selecting Parameters - 96 Selecting the camera - 35 SEM - 130 Setting Preferences - 44 Setting up an experiment - 32 Setting up the walkway - 34 Show All Prints - 80, 81 Show filtered out signals - 68 Show Labels - 80 Show Rectangles - 80 Single Stance - 114 Sorting the Trial List - 42 Sound Feedback - 54 Specifying Acquisition Settings - 53 Specifying Experiment Settings - 37 Speed average - 119 average run speed - 60 maximum variation - 60, 120 playback - 62, 78 swing speed - 112 Speed variation interval - 94 Spinal cord injury - 106, 108, 117, 119, 126, 136 Stance combine with previous or next - 76 see also Stand Stand - 106 Stand Index - 106 combining stances - 76 Standard Deviation exporting - 155, 157 Standard error - 119, 130 Standing on % - 128 Start Acquisition - 59 Starting up CatWalk XT - 33 Step Cycle - 113 Step sequence - 116 Step Sequence sheet - 115 codes - 116 footfall patterns - 116 normal patterns - 116 step sequence - 116 Stop Acquisition - 59 Stride Length - 112 Stroke - 138 Summary sheet - 104 base of support - 105 couplings - 105 paw statistics - 104 phase dispersions - 105 print positions - 105 step sequence - 104 support - 105 Summary statistics - 104 Support Formula - 127 Support formula - 174 Support sheet - 127 footfall formula - 128 standing on % - 128 support formula - 127 Swing - 112 Index Swing Speed - 112 Switch to 'Normal/False Color' mode - 80 System Variables acquisition status - 41 classification status - 42 compliant runs - 42 total runs - 41 - T Tail label - 74, 122 Target - 125 start - 125 Technical Support - 14 Terminal Dual Stance - 114 Tibial Functional Index - 86, 121 formula for mice - 121 formula for rats - 121 Time and frame information - 79 exporting - 162 Time Point in data selection - 93 Time Points - 38, 41 adding - 38 deleting - 38 TNA - 125 Toe classification see Interactive Footprint Measurements Toe Spread - 87, 113 Training animals - 47 Treatment Group in data selection - 93 Treatment Groups - 38 adding - 38 deleting - 39 Trial List animal - 41 copying text - 42 defining - 41 sorting - 42 time point - 41 Trial Selection - 58 Trials adding multiple trials - 41 classification status - 90 completely classified - 90 deleting - 42, 150 opening - 150 partially classified - 90 Troubleshooting - 167 Tutorial videos - 13 - U Uncompressed AVI export - 161, 162 Units see distance units Upgrade key - 13 Upgrading - 17 USB cable - 33 Use maximum allowed speed variation - User rights - 16 - V Variability of phase dispersions - 140 Vector length - 133 Vector orientation - 133 Velocity see speed Video exporting - 161 Video frame rate - 105 Video window - 78 Visualization 2D footprint intensities - 99 2d footprint intensities - 99 3D footprint intensities - 97 3d footprint intensities - 97 exporting - 160 footfall patterns - 100 Visualizing data - 97 - W Waiting for animal to leave the walkway Index - 62 Waiting for background snapshot of empty walkway to be taken - 61 Waiting for run to start - 62 Walking Direction - 60 Walkway calibrating - 36 defining the layout - 35 preparing - 57 Walkway Length - 159 Warm up of the CatWalk system - 33 What's new in CatWalk XT - 11 Width of defined walkway - 159 Wildcard - 65 Windows 10 - 16 Windows 11 - 16 - X X - 109 X-Unit - 105 - Y Y - 110 Y-Unit - 105 - Z Zooming in / out - 75 Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - Carry out Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-carry-out-data-acquisition Chapter: CatWalk XT 5 - Carry out Data Acquisition 5.1 Prepare the walkway........................................................................... Make sure the walkway is clean, the corridor is put in place and the illuminated ceiling is lowered. 5.2 Carry out data acquisition................................................................... During acquisition an animal crosses the walkway and these runs are recorded. After acquisition you can play back runs for inspection and if necessary delete runs. In the Experiment Explorer, small Acquisition Status symbols allow you to check the Acquisition Status of trials and runs. 5 - Carry out Data Acquisition 5.1 Prepare The Walkway Before you acquire data you need to make sure that: The glass plate is clean Lift the corridor. Use a soft cloth or tissue to remove droppings, urine or other dirt from the glass plate. You can use a propriety glass-cleaning fluid to further clean the glass plate. Experience from CatWalk users has shown that also water with some vinegar added or a70% alcohol solution are also effective in cleaning the glass plate. The camera is at the correct position The distance of the camera to the glass plate determines how much of the walkway is visible. In order to get 5-6 step cycles per run, you should see about 45 cm of the walkway for mice and about 70 cm for rats. Try this out with one or two animals to make sure you get the appropriate camera position. If you change the position of the camera, you need to redefine the walkway and re- calibrate the walkway (see Set up the walkway). Also make sure to focus the camera. The corridor is put in place Make sure the middle of the corridor is positioned in the middle of the glass plate. Adjust the width of the corridor to match the animal's size. The illuminated ceiling is lowered When you did not install the diffusion plate on top of the corridor walls, it is useful to leave a gap between the top of the corridor and the illuminated ceiling so you can put an animal into the corridor from the top. When you adjust the vertical position of the illuminated ceiling, always check in the Define Walkway window that the red LED lights of the illuminated ceiling completely cover the defined area. Optionally, you can use the Noldus goal box to let the animal run towards its home cage. 5 - Carry out Data Acquisition 5.2 Carry Out Data Acquisition After you have prepared the walkway (see above), you are ready to start data acquisition. During acquisition, CatWalk XT uses the run criteria you have specified in the Experiment Settings (see page 39). Procedure Start data acquisition - Do one of the following: In the Experiment Tasks window, click Open Acquisition. Choose Acquire > Open Acquisition. In the Experiment Explorer, under Acquisition, right-click a trial and select Acquire Runs. - Under Trial Selection, select a trial from the list (see the figure below). When you have not defined one or more trials in the Trial List, select Create new trial from the list or go to the Trial List (see page 41) to define trials. Lower the illuminated ceiling gently; if you do this too roughly, it can make the corridor walls shake which can accidentally set off acquisition after you have clicked the Start Acquisition button. Do not lift the illuminated ceiling after you have clicked the Start Acquisition button; this results in the acquisition of a lot of data and a high processing load. - Click the Snap Background button to snap a background image of the empty, clean walkway. You cannot start acquisition before you have snapped a background image (see Acquisition Status on page 61). You can view the background image in the Acquisition Settings: Choose Setup > Acquisition Settings and click the View Background Image button. 5 - Carry out Data Acquisition - Click Start Acquisition or press Page-Up. The Status changes to 'waiting for run to start'. - Put the animal into the corridor from the side. Acquisition starts automatically as soon as the animal's contour is detected. The Status changes to 'recording Run#'. As soon as the animal disappears from view, the Status changes to 'waiting for run to start'. - If you have specified in the run criteria of the Experiment Settings to acquire more than 1 compliant run, now take the animal out of the corridor and put it back in on the other side or let it turn around for the next run (step 5). Stop data acquisition - You can manually stop data acquisition by clicking the Stop Acquisition button or by pressing Page-Down. - Acquisition stops automatically as soon as the set number of compliant runs (run criteria on page 39) has been acquired. See also page 61. What next? When the set number of compliant runs has been acquired, the Acquisition Finished Tasks window opens (see Figure 5.2). You can now select: Acquire Next Trial - This is the trial that is listed next in the Trial List. Acquire New Trial - This creates a new trial that you can acquire. Classify Runs - This takes you to the Classification window where you can classify acquired runs. Figure 5.1 Part of the Acquisition screen. The background has been snapped and the Start Acquisition button has been clicked; acquisition starts when the animal is detected. 5 - Carry out Data Acquisition Review Runs - To inspect acquired runs (see below). Notes Acquired Run list The Acquired Runs list (see Figure 5.3) shows the acquired runs with the following variables: Run - The run number. Start - The start data and time of the run. Duration - The total duration of the run. Compliant - A run is marked compliant or non-compliant with the run criteria. When you hover over the non-compliant icon, information is displayed about why the run is non- compliant with the run criteria. The run criteria become read-only when you have acquired a run. Direction - The walking direction of the animal. If the animal turns around the Direction cannot be determined. Run Average Speed - The speed of the recorded run. Run Maximum Variation - The maximum variation in running speed (see the run criteria) of the recorded run. Figure 5.2 The Acquisition Finished Tasks window. 5 - Carry out Data Acquisition Camera Gain - The Camera Gain value from the Detection Settings (see Configure the detection settings on page 48). Green Intensity Threshold - The Green Intensity Threshold value from the Detection Settings. Depending on your Run Settings in the Acquisition Settings, runs that are aborted or do not meet the run criteria are kept or discarded. A run stops automatically... When the run duration exceeds the maximum set in the run settings (page 53). In any case when run duration exceeds 60 seconds. This is indicated for that run in the Acquired Runs list. Acquisition stops automatically... When the set number of compliant runs (run criteria on page 39) has been acquired. When not enough internal memory is available. This can occur, for example, when you acquire a number of long runs (20-30 seconds) in a row, with short time between runs. In this case, CatWalk XT needs to both process and acquire (long) runs, which can cause the internal memory to 'overflow'. Acquisition Status The Status during acquisition can be: Waiting for background snapshot of empty walkway to be taken - Press the Snap Background button. You can view the snapped Background in the Acquisition Settings (see page 53). Ready for acquisition - Then press the Start Acquisition button. Figure 5.3 Part of the Acquired Runs list. In this example, two consecutive runs were acquired that both are compliant with the set run criteria. 5 - Carry out Data Acquisition Waiting for run to start - Recording starts automatically as soon as the animal appears in the video image. Recording Run[#] - A run is recorded and acquisition stops automatically as soon as the animal has completely disappeared from the video image. Camera connection lost, trying to restore the connection... - If the connection is lost, acquisition is stopped. Acquisition can only be resumed after the connection has been restored. Waiting for animal to leave the walkway - This status message is shown in the following cases: - The Maximum run duration (see page 39) has been exceeded while the animal is still on the walkway. - The animal has left the walkway but has left some faeces or urine so the run has not been stopped. 5.3 Acquired Runs Review The Runs Review a run - Under Video, from the View list, select a run. - To replay a run, press the Play button (see Figure 5.4 for a description of the playback buttons). Options Select a playback speed from the list. When you press the Pause button, the video pauses at its current position. You can move the video forward or backward one frame, by using the Play-forward-one- frame or Play-backward-one-frame button. You can keep them pressed to move through the run frame by frame. Note that the time between two subsequent frames is 1/100 s. When you press the Stop button, the video jumps to the beginning. When the run is paused or stopped, you can scroll through the video using the slider. 5 - Carry out Data Acquisition A run plays continuously, unless you turn off the Repeat button. Delete Runs important Deleting runs cannot be undone. We recommend to make a backup of your experiment (see page 149) before deleting runs. Delete a single run - Select the run you want to delete in the Acquired Runs list at the bottom of the screen. The currently active run (indicated in bold and blue in the Experiment Explorer) cannot be deleted. From the View list, select Live video to 'in-activate' the run. - Click the Delete Run(s) button. Alternatively, right-click an 'inactive' run in the Experiment Explorer and select Delete. Delete multiple runs - Select the runs you want to delete in the Acquired Runs list at the bottom of the screen: The currently active run (indicated in bold and blue in the Experiment Explorer) cannot be deleted. From the View list, select Live video to 'in-activate' all runs. To select multiple, consecutive runs, click the first run you want to delete, press and hold the Shift key and click the last run you want to delete. To delete multiple, individual runs, press and hold the Ctrl key and click the runs you want to delete. - Click the Delete Run(s) button. When you next acquire an additional run in this trial, the run number continues from the previous number of acquired runs. For example, you have three runs (Run1, Run2, Run3) in the list and you delete Run3. When you next acquire a new run, this run is labeled Run4. Figure 5.4 The playback control buttons. From left to right: Play button / Pause button, Stop button, Repeat button, Playback speed list, Play-back-one-frame button, Play-forward-one-frame button, Slider. 5 - Carry out Data Acquisition 5.4 Acquisition Status Icons In the Experiment Explorer, the following symbols allow you to check the Acquisition status of trials and runs. Trials Runs Data selection status For each trial and run it is also indicated whether it contains steps which are included in the currently active Data Segmentation profile (see Select the data on page 92): Trial - The number of runs within the trial that contain steps which are included in the data selection is indicated behind the trial. The figure below shows an example of a trial Trial# Green check mark For this trial the minimum number of compliant runs (as set in the Experiment Settings, see page 39) have been acquired. Trial# Orange check mark For this trial the minimum number of compliant runs have NOT been acquired. Run# Green round icon This run meets the run criteria set in the Experiment Settings. Run# Orange round icon This run does NOT meet the run criteria. 5 - Carry out Data Acquisition with 3 runs which all contain steps included in the currently active Data Segmentation profile. Run - An asterisk (*) behind a run indicates that the run contains steps which are included in the data selection. What next? You can acquire another run for the current trial by selecting Live video from the View list under Video. You can acquire runs for another trial; go to step 2 on page 58. You can continue to Classification (see Classify Runs on page 66). Click >> Classify Runs in the bottom-right corner or choose Acquire > Classify Runs. Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - Classify Runs URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-classify-runs Chapter: CatWalk XT 6 - Classify Runs CatWalk XT can automatically assign labels to paw prints, but also to other body parts, such as, hip, knee, nose, abdomen, tail and genitalia. You can also carry out manual classification. 6.2 Review the runs during classification................................................. You can inspect the labels that have been assigned. This might be necessary when you, for example, accidently have switched the left and right side of the body. Also, sometimes CatWalk XT is not able to automatically classify all paw prints or classifies some prints incorrectly. If you have the Interactive Footprint Measurements module, you can determine Toe Spread, Print Length and Paw Angle. CatWalk uses Toe Spread and Print Length to calculate the Sciatic Functional Index. In the Experiment Explorer, small classification status symbols allow you to check the Classification Status of trials and runs. 6 - Classify Runs 6.1 Classify The Paw Prints Classification Screen Do one of the following: In the Experiment Tasks window, click Classify Runs. Choose Acquire > Classify Runs. In the Experiment Explorer: right-click a trial (containing runs) and select Classify Runs. right-click a run and select Classify. double-click a run. Before you start classifying paws, first check the quality of the detected paw prints by playing back the runs. If necessary, you can adjust the Green Intensity Threshold (see below) to increase the quality of the paw prints or to remove noise If you use the Automatic Footprint Classification module, there are two main classification scenarios: You only want to label paw prints - Use automatic classification (see page 69) to let CatWalk label the paw prints. Next, use manual classification (see page 73) to label paw prints that CatWalk was not able to classify automatically. You want to label both paw and non-paw prints - First, manually label (see page 73) the non-paw prints. Next, use automatic classification (see below) to let CatWalk label the paw prints. Adjust The Green Intensity Threshold The Green Intensity Threshold is set in the Detection Settings before acquisition. The Green Intensity Threshold is the minimum pixel intensity that is detected by CatWalk. All pixels below the minimum Green Intensity are not processed by CatWalk. In CatWalk XT 10, you have the possibility to increase or decrease the Green Intensity Threshold of a run before classification of the paws, so after you acquired the runs. When do I need to adjust the Green Intensity Threshold? You can adjust the Green Intensity Threshold in the Classification screen when you see that the Green Intensity Threshold set in the Detection Settings is either too low or too high. When the Green Intensity Threshold is too low, a lot of noise shows up (for example, part of the animal's body). When the Green Intensity Threshold is too high, the paws are not 6 - Classify Runs detected completely (for example, toes are missing or part of the sole). See Figure 6.1 for an example of a too low Green Intensity Threshold which is increased before classification. To adjust the Green Intensity Threshold: 1. In the Classification screen, under Video, click the Adjust the Green Intensity Threshold button on the right. The Adjust the Green Intensity Threshold window (see Figure 6.2) shows the following: Video window - with prints displayed based on the Current Green Intensity Threshold which initially is the same as the Original Green Intensity Threshold that was set in the Detection Settings. Original Green Intensity Threshold - this is the value you set in the Detection Settings. Current Green Intensity Threshold - this is the current value you can set here. Show filtered out signals - when you select this option, the prints which are filtered out with the Current Green Intensity Threshold value are displayed in red. 2. To adjust the Green Intensity Threshold, move the slider to the desired value. Depending on whether you increase or decrease the Green Intensity Threshold, prints disappear or appear, respectively. When you adjust the Green Intensity Threshold of a run recorded with a previous version of CatWalk XT, the lowest possible value for the Green Intensity Threshold is the value with which the run was acquired. Figure 6.1 Example of the result of adjusting the Green Intensity Threshold. The top picture shows the result of automatic classification with a Green Intensity Threshold of 0.10 which was set in the Detection Settings; in this video frame you see that a lot of noise is included in the paw print LH. The bottom picture shows the same frame but classified with a Green Intensity Threshold of 0.30. The noise is now excluded from the paw print. 6 - Classify Runs Clicking left or right of the slider on the slider bar moves the slider in steps of 5. 3. When the Current Green Intensity Threshold has the desired value, click OK. The run is now processed with the new Green Intensity Threshold value. Depending on the length of the run and the set Green Intensity Threshold, this can take a few seconds. 4. You can now classify the run (see below) with the new Green Intensity Threshold value. Please note that changing the Green Intensity Threshold affects the Run Statistics. Therefore, we recommend to use the same Green Intensity Thresholds for all runs within one experiment to be able to compare the results between runs. Automatic Classification You need the Automatic Classification module to be able to classify paw prints automatically. With the base version of CatWalk XT 10, you can only assign labels manually. The Automatic Footprint Classification (AFC) module uses the body contour of the animal to determine the position of the paw prints. Performance of Automatic Classification We cannot guarantee that Automatic Footprint Classification will work in all situations. Tests have shown that the AFC module gives good results when used with an animal which is walking with a normal gait across a clean glass plate. Figure 6.2 The Adjust Green Intensity Threshold window. In this example, the original Green Intensity Threshold value of 0.10 has been increased to the Current Green Intensity Threshold value of 0.30. The Print View shows the filtered out prints in red because the option Show filtered out signals is selected. 6 - Classify Runs The AFC module is likely to function less well when the glass plate is dirty (which results in a lot of background noise in the video image) or when the animal touches the glass plate with other parts of the body than the paws. How to improve Automatic Classification For the AFC module, a number of ground rules apply: Try to avoid background noise as much as possible. To do this, make sure the ambient light is dimmed as much as possible and the glass plate is clean before you start acquisition. If you still see a lot of noise in the video image, you might need to re-configure the Detection Settings. Remove junk prints. If you already acquired runs that contain a lot of noise, increase the Green Intensity Threshold before classification (see adjust the green intensity threshold on page 67). If after this, there is still some noise prints left, manually label these prints as Junk and remove them (see I want to permanently remove prints labeled as Junk on page 77). The animal should walk in a straight line and in one direction. If the animal turns around during a run, AFC does not work. You can facilitate straight runs by putting the corridor walls together as close as possible without restricting the animal in crossing the walkway. The animal should not rear during a run You can prevent this from happening by installing the diffusion plate on top of the corridor walls. The animal should only make contact with the glass plate with its paws. If other body parts than the paws make contact with the glass plate, manually label these prints before you run the AFC. The corridor should be positioned in the middle of the glass plate. Make sure that the corridor is centered over the camera, in such a way that the animal, on average, walks along the middle line of the video image. For example: 6 - Classify Runs Try to minimize the area of the video image covered by the corridor walls, which may interfere with detection of the body contour. The following picture shows one of the walls covering a significant part of the walkway: Classification Settings Choose Setup > Classification Settings. In the Classification Settings window, you can select the following: Reset all assigned labels when applying the AFC - Do NOT select this option in case you already have manually labeled (part of) this run and want to keep these labels. Only assign a label when the Max Intensity is higher than... - Noise (for example, dirt on the glass plate) has a much lower Max Intensity than paw prints. By selecting this option with the default value of 100 you ignore most of the noise prints. See Figure 6.3 for an example of the result of automatic classification when you do NOT select this option. Procedure - Under Trial & Run Selection, select a trial and one of the runs in that trial, or click the Previous/Next button to navigate to the trial and run you want to classify. The trials in the trial list contain animal ID, time point, acquisition status and classification status. The runs in the run list include compliant/non-compliant status and classification status. 2. Click the Auto Classify button to automatically classify the complete run. 6 - Classify Runs What next? If the AFC module classified the complete run, the Classification Finished Tasks window appears. To continue, select one of the options in this window. If some prints could not be classified by the AFC module, the video automatically jumps to the first frame with an unlabeled print. Continue manually labeling the unlabeled prints (see page 73). Review the run (see page 78) and, if necessary, correct errors (see page 82). Figure 6.3 Example of automatic classification with not selecting the option Only assign a label when the Max Intensity is higher than.... The arrow in the video image at the top indicates a noise print that has been incorrectly assigned label 'Left Hind'. The arrow in the Numerical Results sheet indicates the Max Intensity value of 85 of this print. Selecting the 'Only assign a label... with the default value of 100' would have ignored this print. 6 - Classify Runs Manual Classification - Under Trial & Run Selection, select a trial and one of the runs in that trial, or click the Previous/Next button to navigate to the trial and run you want to classify. The associated video opens with the video frame that contains the first unlabeled print (see Figure 6.4). 2. Do one of the following: Continue at the next step to start assigning labels. Move the video to a new position by using the playback buttons (see page 78 how to move through the video). Optionally, zoom in to get a better view of the prints (see page 75 how to zoom in and out in the Video window). Figure 6.5 below helps you in determining what is left and what is right. 3. To label a print, do the following: Figure 6.4 The first video frame in a run with unlabeled prints. The print is automatically marked with a white rectangle and a white 'UN' label. The overlay text (hidden in this example) displays the run number, current frame number and total number of frames. Figure 6.5 Paw positions in relation to walking direction. When the animal walks from left to right (picture on the left), the upper side in the video image is the right side of the animal, the lower side if the left. When the animal walks from right to left (picture on the right), the upper side in the video image is the left side of the animal, the lower side if the right. 6 - Classify Runs Using the mouse, select a rectangle or draw a larger box around one of the white rectangles and release the mouse button. Select a label from the menu. Assign a label to other unlabeled prints in this frame until there are no unlabeled prints left or you have labeled all relevant prints in this frame. The labeled print appears under Results, both in the Print View and Timing View of the Graphical tab and in the Numerical tab (see Figure 6.6). The following labels can be used: Paws - RF = Right Front, RH = Right Hind, LF = Left Front, LH = Left Hind, Hip and Knee - RM = Right Hip, RK = Right Knee, LM = Left Hip, LK = Left Knee. Other body parts - NO = Nose, AB = Abdomen, TA = Tail, GT = Genitalia. 4. The video now automatically moves to the next frame with unlabeled prints that do not overlap with already labeled prints. You can now do the one of the following: Repeat the procedure described in step 3 above. Figure 6.6 The Graphical tab (left) and the part of the Numerical tab (right) of the Results sheet. 6 - Classify Runs Click the Jump to next unlabeled print button or Jump to previous unlabeled print button to go to a, next or previous, specific unlabeled print and repeat the procedure described in step 3 above. You can speed up labeling prints by doing the following: draw a box around both labeled prints and unlabeled prints that belong to the same paw (see Figure 6.7). The unlabeled prints are now automatically assigned the same label. 5. Continue until you have labeled all relevant prints in the run. What next? If you labeled the complete run, the Classification Finished Tasks window appears. To continue, select one of the options in this window. You can speed up labeling prints by doing the following: draw a box around both labeled prints and unlabeled prints that belong to the same paw (see Figure 6.7). The unlabeled prints are now automatically assigned the same label. Zoom In/out In The Video Window During classification, to get a better view of the paw prints, zoom in in the Video window. The available zoom factors are: 1x, 2x, 3x, 4x and 5x. To zoom, do one of the following: Click the Zoom in button or the Zoom out button. To zoom in, click Ctrl-'+' (numeric keyboard), to zoom out, click Ctrl-'-' (numeric button). To jump to the normal view, click Ctrl-'0' ('zero' on the numeric keyboard). Figure 6.7 Example of how labeling is speeded up by drawing a box around both an unlabeled print and a labeled print. RF is the right front paw. 6 - Classify Runs Combine Stances Occasionally, it can occur that a print in a frame is not detected. As a result, the stance (that is, contact of a paw with the glass plate during one paw placement) of a specific paw is subdivided into two separate stances (see Figure 6.8). In CatWalk XT 10, these separated stances can now be manually combined. tip If you have a lot of these subdivided stances, it might be that your Green Intensity Threshold was set too high. Try to decrease the Green Intensity Threshold (see page 67) before proceeding with combining stances below. Procedure To combine two stances, Right-click on the first stance and select Combine with next. As a result, the stances are combined and the new stance is now considered to be a single stance, in the Visualization and also in the Run Statistics. important CatWalk is not able to calculate the Stand Index (see page 106) for the new stance when the Max C0ntact at point is in the first stance. Figure 6.8 Part of the Timing view with an example of a subdivided stance. The second placement of the Right Hind paw is subdivided into two stances indicated by the gap. 6 - Classify Runs Label Junk When a print is displayed of which you are sure that it is not part of the animal's body (for example, a dropping, or dirt from the animal's body) or it is irrelevant, you can label it as Junk. You do this exactly the same way as assigning one of the other labels. Prints labeled as Junk are not displayed in the Print View and Timing View. If you have a lot of noise prints, it might be better to first increase the Green Intensity Threshold (see adjust the green intensity threshold on page 67). I have a lot of prints that are Junk In case a frame contains a lot of junk, you can do the following to speed up labeling: 1. Label all relevant prints in the frame. 2. Click the UN = Junk button (alternatively, press the ''~" key or the "-" (en dash) key on your keyboard to label all remaining prints in the frame as Junk. I want to permanently remove prints labeled as Junk When you have labeled print as Junk, they still appear in the Video window when you replay a run. When you do not want Junk to be displayed, you can permanently remove prints labeled as Junk: 1. First, carry out the two steps described under I have a lot of prints that are Junk above. 2. Next, click the Remove All Junk Prints button. Removing all Junk prints cannot be undone. The only way to get prints back is to, in each frame from which a Junk print was removed, manually add a print (see below). Add Paw Prints You might want to add a print when there is no rectangle around a print (therefore, the print cannot be labeled) whose intensity exceeds the Green Intensity Threshold (see under manual detection on page 51). This can occur in the following situations: You have manually removed a print labeled as Junk ("label junk" on page 77). In the Acquisition Settings, you selected the option Discard incomplete prints at the start and end of a run (see page 53). As a result, no rectangle is drawn around the print. Procedure To add a print do the following: 1. Draw a box around the print. 6 - Classify Runs 2. From the menu, select Add Print. 6.2 Review The Runs During Classification You can review runs using the: Video window - You can move through the video and inspect the assigned labels. Graphical Results - With the labeled prints and the time-based gait diagram. Numerical Results - This sheet displays a number of basic parameters for each print. Video Window Review a run - Under Trial & Run Selection, select a (partially) classified trial and a (partially) classified run. - To replay a run, press the Play button: You can selected a playback speed from the list. When you press the Pause button, the video pauses at its current position. You can move the video forward or backward one frame, by using Play-forward-one- frame or Play-back-one-frame button, respectively. When you press the Stop button, the video jumps to the beginning. When the run is paused or stopped, you can scroll through the video using the slider. A run plays continuously, unless you turn off the Repeat button. Figure 6.9 The playback control buttons. From left to right: Play button / Pause button, Stop button, Repeat button, Playback speed list, Play-back-one- frame button, Play-forward-one-frame button, Slider. 6 - Classify Runs When you right-click the Video window, a menu appears in which you can select the following: Show Labels - When not selected, the labels are hidden. Show Rectangles - When not selected, the rectangles are hidden. Show Overlay Text - The Overlay Text situated at the top-left corner displays the run number, the time of the current video frame, the current frame number and the total number of frames. When not selected, the Overlay Text is hidden. Hiding labels, rectangles and overlay text might be useful, to get a better view of the prints. Graphical Results The Graphical Results contains two views. Print View The Print View displays the paw prints and other prints. During labeling the Print View is constantly updated. The prints in the Print View are displayed in the same direction as in the Video window. During playback of the run, paw prints and their labels visible in the Video window, are highlighted in yellow (or another color that you can select in the Preferences; see page 45). Print View options Right-click the Print View to access a number of options: Figure 6.10 The Print View options. 6 - Classify Runs Switch to 'Normal Color' mode - Choose this option to display the prints in green of variable intensity, on a black background. Switch to False Color' mode - Choose this option to display the prints with a color gradient indicating different print intensities (from green = low intensity, to red = high intensity), on a blue background. False Color mode is the default mode; if you do not see this option, it means that the Print View is in that mode. Switch to 'Colorized' mode - Choose this option to display the prints in the colors selected in the Color preferences (see colors on page 45), on a black background. Show All Prints - When not selected, only the prints that are visible in the current frame in the Video window are shown in the Print View. Show Labels - When not selected, all labels are hidden. Show Rectangles - When not selected, all rectangles are hidden. Save to File... - To save the Print View, as displayed on the screen, to an image file (*.png). Copy to Clipboard - To copy the Print View, as displayed on the screen, to the clipboard. tips You can hide the Print View by clicking the title bar. You can jump to the first frame of a specific print by clicking the print in the Print View (indicated by the mouse pointer becoming a hand when hovering over a print). if you do not see a color mode option, it means that the Print View is already in that mode. Timing View The Timing View displays the time-based gait diagram of a run. It also displays the contact with the glass plate of other body parts that you have labeled. 6 - Classify Runs The Timing View displays the prints from left to right, irrespective of the animal's actual direction of movement. The bars in the Timing View represent the duration of contact with the glass plate (stance or stand) of a paw or other body part. The intervals between bars represent the time a paw was not touching the glass plate (Swing; see page 112). The vertical, red dotted hairline corresponds to the position of the run in the Video window. When you right-click the Timing View, a menu appears with the following options: Show all prints - When not selected, only the four paw prints are shown. Save to File... - This saves the Timing View, as displayed on the screen, to an image file (*.png). Copy to Clipboard - This copies the Timing View, as displayed on the screen, to the clipboard. tips You can hide the Timing View by clicking the title bar. You can jump to the first video frame of a specific print by clicking the corresponding bar in the Timing View (indicated by the mouse pointer becoming a hand when hovering over a bar). Numerical Results The Numerical Results sheet contains for each labeled print: Print - The full label of the print. Image - A picture of the full print. A larger version of this picture and other full paw prints from the current video frame are also displayed next to the Video window. You can use these pictures to detect possible classification errors (see also Correct errors on page 82). Initial Contact (s) - The time in seconds since the start of the run that the print first makes contact with the glass plate. Stand (s) - The duration of contact with the glass plate of the print. Max Contact At (s) - The time in seconds since the start of the run that the largest part of the print makes contact with the glass plate. Max contact area (Distance Unit2) - The surface area of the print at Max contact expressed in the Distance Unit you selected in the Preferences. 6 - Classify Runs Max intensity - The print's maximum intensity. Mean intensity - The print's mean intensity. Print Length (Distance Unit) - This is the length (horizontal direction) of the complete print expressed in the Distance Unit you selected in the Preferences. See also paw statistics on page 106. Print Width (Distance Unit) - This is the width (vertical direction) of the complete print expressed in the Distance Unit you selected in the Preferences. See also paw statistics on page 106. Print Area (Distance Unit2) - This is the surface area of the complete paw print expressed in the Distance Unit you selected in the Preferences. See also paw statistics on page 106. When you click a row in the Numerical Results table, the video jumps to the corresponding frame. When you play back the run, a blue hairline indicates the position of the run in the Video window. 6.3 Correct Errors The following errors can occur: Labeling error - A print is assigned an incorrect label. For example, left and right are swapped or the animal's nose touching the glass plate is labeled as one of the front paws. See below for how to correct a labeling error. CatWalk error - When an already labeled print overlaps with an subsequent unlabeled print, CatWalk automatically assigns the same label to the unlabeled print. This results in two different paws with the same label. See page 83 for how to correct a CatWalk error. Print error - Two prints that are not part of the same paw are included in the same rectangle. This can occur, for example, when noise or another part of an animal's body is included in the rectangle around a paw print. See page 85 for how to correct a Print error. Labeling Error In some cases during labeling, a wrong label was assigned to a print. 6 - Classify Runs The Graphical Results tab (see also page 79) can help you in detecting errors. For example, when a print was labeled as Right Front while it should have been Left Front, this becomes visible in the Timing View (see Figure 6.11). To correct a labeling error (the error shown in Figure 6.11 is used as an example), do the following: 1. Click the incorrectly labeled print in the Timing View to jump to the first frame of the corresponding print in the video image (see Figure 6.11). 2. Draw a box around the incorrectly labeled print and from the menu select Reset. 3. Now draw a box around the unlabeled print and select the correct label or draw a larger box around the unlabeled print and the labeled prints it belongs to (see also Figure 6.7 on page 75). Catwalk Error A CatWalk error occurs when the same label is assigned to two different paws visible in the same frame. For example, when a paw is placed on the glass plate at the same position as a previous other paw (see Figure 6.12 for an example). Figure 6.11 The Timing View and part of the Video window. The Timing View shows a long stance (indicated by the hand pointer) for Right Front which should partly have been Left Front. The arrow in the Video window points at the print that was incorrectly labeled Right Front. Figure 6.12 An example of a CatWalk error. In this case the Right Hind paw is placed at the same position as the previous Right Front paw; because they partly overlap, the print indicated by the arrow is automatically assigned label RF, while in fact it is RH. 6 - Classify Runs A CatWalk error is automatically detected by the program and is displayed in a list in the Video section. To correct a CatWalk error: 1. Select an error from the error list (see Figure 6.13). 2. Click the rectangle of the incorrectly labeled print and from the menu select Reset. As a result, the print is reset and the print is now unlabeled. 3. Now assign the correct label to the appropriate print. Figure 6.13 Part of the Video section with the CatWalk error list (indicated by the red rectangle). Figure 6.14 Example of resetting a wrong print (indicated by the yellow rectangle). 6 - Classify Runs The relabeled print now has the correct label (see Figure 6.15) and the error is removed from the error list. 4. If necessary, repeat steps 1 to 3 for the other errors. Print Error A Print error occurs when noise prints or another part of an animal's body is included in the rectangle around a paw print (see Figure 6.16 below). You might be able to prevent Print errors by increasing the Green Intensity Threshold (see adjust the green intensity threshold on page 67). To correct a Print error, do the following: 1. Right-click the rectangle and select Remove Print. 2. If necessary, scroll back to the frame in which you removed the print. Figure 6.15 Example of a corrected CatWalk error. The arrow indicates the print that has been corrected. Figure 6.16 Example of a Print error. When an animal's abdomen touches the glass plate, part of the abdomen can be included in the rectangle of one of the hind paws (in this example, the right hind paw). 6 - Classify Runs 3. Draw a box around the paw print and, from the menu, select Add Print. 4. Assign the correct label to the print. 6.4 Classify Toes Interactive Footprint Measurements Classification of toes is done in the Interactive Footprints Measurements. Toe classification of the hind paws (by measuring the Toe Spread, Intermediate Toe Spread and Print Length) can be used to calculate the Sciatic Functional Index, Peroneal Functional Index and Tibial Functional Index. The Sciatic Functional Index is commonly used as a tool for the evaluation of the recovery of the sciatic nerve. You first need to label a paw print before you can classify its toes. You need the Interactive Footprint Measurements module to be able to classify toes. Choose Acquire > Interactive Footprint Measurements. In the Interactive Footprint Measurements, you can measure the following: Toe Spread - This is the distance between the first and fifth toe of a hind paw. Intermediate Toe Spread - This is the distance between the second and fourth toe of a hind paw. Manual Print Length - This is the distance between the third toe and the heel of a hind paw. 6 - Classify Runs This parameter is different from Print Length which is length (in the horizontal direction) of the complete print (see page 110). Paw Angle Body Axis - This is the angle of the paw relative to the orientation of the body axis of the animal. Paw Angle Movement Vector - This is the angle of the paw relative to the direction of movement of the animal. The Movement Vector is a more accurate measure of the actual walking direction of the animal. The Movement Vector is calculated by performing linear regression of the center- of-gravity of the body contour in the current frame and in the three preceding frames. Procedure - Choose Acquire > Interactive Footprint Measurements. - Under Trial Run Selection, select a classified trial and run from the list, or click the Previous/Next buttons to navigate to the trial and run you want to measure. 3. Under Footprint Type Selection, select the paw prints you want to display. By default, both hind paws are selected. 4. Click the paw you want to classify. The Footprint view displays a zoomed-in picture of the complete paw. The paw print consists of all frames of that paw whereas the Body Axis view only shows the frame at Max Contact; therefore, the paw prints can be different. Note - In some cases the paw print may look incomplete; see page 171. The Body Axis view shows the frame with the Max Contact (see page 108) of the corresponding paw with the body contour and body axis of the animal. It also shows the Movement Vector as a red arrow. 5. In the Footprint view, you can measure the following parameters: Toe Spread - This is the distance between the first and fifth toe of the hind paw (see Figure 6.17). To measure Toe Spread, click as close as possible to the center of the first toe, move the mouse cursor as close as possible to the center of the fifth toe and click, and next select Toe Spread from the menu. 6 - Classify Runs Intermediate Toe Spread - This is the distance between the second and fourth toe of a hind paw (see Figure 6.17). To measure the Intermediate Toe Spread, click as close as possible to the center of the second toe, move the mouse cursor as close as possible to the center of the fourth toe and click, and next select Intermediate Toe Spread. Manual Print Length - This is the distance between the center of the third toe and the heel of a hind paw (see Figure 6.17). To measure Print Length, click as close as possible to the center of the third toe, move the cursor as close as possible to the heel of the paw print and click, and next select Print Length from the menu. If your animals do not show the heels in the Footprint view, draw the line from the third toe to between the proximal pads because that is in the direction of the heel, and stop where the print ends. Be consistent with this definition across the animals. When you next measure the third parameter, it is automatically assigned the remaining label. Paw Angle Body Axis - This is the smallest angle between the Print Length line and the white line representing the body axis of the animal as displayed in the Body Axis view. Paw Angle Movement Vector - This is the smallest angle between the Print Length line and the red line representing the direction of movement of the animal as displayed in the Body Axis view. 6. Under Parameters, select Show parameter values to display the values of the parameters. Figure 6.17 Example of the result of classification of a toe. The Footprint view shows the measurements for Toe Spread (TS), Intermediate Toe Spread (ITS) and Print Length (PL). The Body Axis view displays the paw at Max Contact, the body axis (long, white line) and the Movement Vector (short, red line). Under Parameters, the measured parameter values are shown. 6 - Classify Runs 7. Optionally, in the Body Axis view, you can change the orientation of the body axis by moving one of the sides of the body axis line to a new position. When you do this, the Paw Angle Body Axis, displayed under Parameters, is instantly updated. 8. Go back to step 4 above to proceed with the next paw and repeat steps 4-6 for all paws you want to classify. 9. Under Functional Index Settings, select the experimental paw from the list for calculation of the Sciatic Functional Index (see page 120). 10.Click OK when you are finished with classifying toes for the current run. In the top view with all the paw prints, a print with classified toes has a green border, a print with unclassified toes has a white border. Correct Measurements Remove a measurement In the Footprint view, click a line and select Remove. Move a line Both in the Footprint and Body Axis view, click on one of the end points and drag it to the new position. 6 - Classify Runs 6.5 Classification Status Icons In the Experiment Explorer, the following symbols allow you to check the classification status of trials and runs: Trials The check mark at the top indicates whether the trial is compliant. The check mark at the bottom indicates whether the trial contains classified runs. Runs The check mark at the bottom indicates whether the run has been classified. Trial# Orange check mark below the 'compliant' trial check mark Not all runs in this trial were (completely) classified. Trial# Green check mark below the 'non-compliant' trial check mark All runs in this trial were completely classified. Trial# One green check mark This trial has both been completely acquired and classified. Run# Orange check mark below the green 'compliant' check mark The run has been partially classified. Run# Green check mark below the green 'compliant' check mark The run has been completely classified. Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - File and Profile Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-file-and-profile-management Chapter: CatWalk XT 8.1 CatWalk Experiments Create a New Experiment - Do one of the following: - In the Application Startup Tasks window, select Create a new experiment. - Choose File > New Experiment. - Click the New Experiment icon in the tool bar. - Select an Experiment Setup profile from the Setup Profile list. - Enter the Name for your experiment. - Accept the default location or browse to a new location. Optionally, you can add a Description and enter a name in the Created by field. The default experiment folder is C:\Users\Public\(Public) Documents\Noldus\CatWalk XT\Experiments. - Click Create experiment. The experiment (*.cwe) is stored in a folder with the same name as the experiment. Open a CatWalk XT 10.7 Experiment - To open an experiment, do one of the following: - In the Acquisition Startup Tasks window, click an existing experiment listed under Open an existing experiment or click Open another.... - Choose File > Open Experiment (Ctrl+O) or click the Open Experiment icon. - Double-click the experiment folder, select the *.cwe file and click Open. Open a CatWalk XT 8/9/10.0/10.5/10.6 Experiment When you open an old experiment, it is converted to a CatWalk XT 10.7 experiment. Once the experiment is converted, it cannot be opened anymore in the previous version. It is not possible to open or import experiments from CatWalk 7.x or earlier. Before opening a CatWalk XT 8/9/10.0/10.5/10.6 experiment in CatWalk XT 10.7, you are required to make a backup of the experiment that can still be opened in the previous version. Make sure to store backups in a safe location. We strongly recommend that you backup your experiments every day, and, for irreplaceable data, more often. - Choose File > Open Experiment. - In the window that appears, click Yes. - In the Backup Experiment window, you can enter the name and folder for the experiment backup. The file name for the backup contains the current date and time. Click Backup to create a backup copy of the experiment and then click OK. - If you convert a CatWalk XT 8 experiment, you can select Rat or Mouse in the Animal Type window. Selection of the type of animal is important for Automatic Footprint Classification and for calculation of the Sciatic, Tibial and Peroneal Functional Index (for rat and mouse different Automatic Footprint Classification algorithms and different FI formulas are used). You can also later select the animal type in the Experiment Settings if you are not sure at this point which animal type you should select. - Click OK to start the conversion. When conversion is completed, the Open Experiment Tasks window opens. Select one of the options to continue or close the window. Errors During Conversion If an error occurs during conversion, you get an error message "An error occurred during the conversion of experiment [experiment name]". Now do the following: - Click OK and Cancel and close CatWalk XT. - In Windows Explorer, go to the CatWalk Experiments folder and delete the complete [experiment name] folder which contains the experiment you wanted to convert. Do not try to open the *.cwe file from the [experiment name] folder. - Open CatWalk and restore the backup file that was created in step 3 of the conversion procedure above. Possible causes for a conversion error are: - The disk to which you try to save the experiment is full. - You do not have write permission for the CatWalk Experiment folder. - There is an error in the Experiment or Experiment folder. In this case, send the backup file to our Support department (via www.noldus.com/support). Save an Experiment Choose File > Save Experiment or press Ctrl+S, or click the Save icon in the tool bar. When you save an experiment, all trials and runs are saved. Settings (such as walkway settings, Preferences, Detection Settings, Acquisition Settings and profiles) are only saved when you save and exit the experiment. By default, Auto Save is active and the experiment is automatically saved at 5-minute intervals. Create a Backup of the Current Experiment - Choose File > Make Backup or click the Make Backup icon in the tool bar. - Accept the default File name and Folder or change these. Before clicking Backup, you can click Open Output Folder so Windows Explorer opens the folder in which the backup (*.cwz) file is saved. - Click Backup. A message appears when the backup file was successfully created. Restore a CatWalk XT Backup (*.cwz) File - Choose File > Restore Backup or click the Restore Backup icon in the tool bar. When you first start CatWalk XT, you can also select Restore Backup in the Application Startup Tasks window. - Locate the backup file (*.cwz) and click Open. - Accept the default CatWalk XT Experiment folder or browse to another folder in which you want to restore the experiment. - Click OK. If you open a CatWalk XT 8/9/10.0/10.5/10.6 backup (*.cwz) file, the experiment is converted to CatWalk XT 10.7. 8.2 Trials and Runs Open a Trial or Run To open a trial/run, in the Experiment Explorer, right-click a trial or run and select Acquire, Classify, Visualize or View Run Statistics. If you get a message "An error occurred while loading the data of run 'Run#'", it means the run is corrupt. Delete this run as described below. Delete a Trial or Run You cannot delete an active trial/run (shown in bold and blue in the Experiment Explorer). If you want to delete trials/runs, you must do this in CatWalk. If you delete trials/runs in the experiments folder in Windows Explorer, this makes your experiment corrupt. To delete a trial, do one of the following: - In the Experiment Explorer, right-click a trial and select Delete. - Open the Trial List, select one or more trials and click the Delete Trial(s) button at the bottom. To delete a run, do one of the following: - In the Experiment Explorer, right-click a run and select Delete. - Open the Acquisition screen, select the corresponding trial and select Live video in the View list. Click one or more runs in the Acquired Runs list and click the Delete Run(s) button. 8.3 Profiles This section applies to Experiment Setup profiles, Detection Settings profiles, Data Segmentation profiles and Parameter profiles. Create a Profile - Do one of the following: - In the Experiment Explorer, right-click Experiment Setup Profiles, Detection Settings Profile, Data Segmentation Profiles or Parameter Profiles, and select Add New Profile. - Choose Profiles > Experiment Setup Profile, Detection Settings Profile, Data Segmentation Profile or Parameter Profile > New. - Enter the name of the new profile and click OK. Open a Profile Do one of the following: - In the Experiment Explorer, right-click a profile and select Open. - Choose Profiles > Experiment Setup Profiles, Detection Settings Profile, Data Segmentation Profiles or Parameter Profile > Open, select a profile from the list and click OK. Rename a Profile You cannot rename the All Data Segmentation profile and the default All Parameters Parameter profile. - In the Experiment Explorer, right-click a profile and select Rename. - Type the new name and press Enter. Duplicate a Profile - In the Experiment Explorer, right-click a profile and select Duplicate. - Type the new name and click OK. Activate a Profile To activate a profile, in the Experiment Explorer, right-click a profile and select Set as Active. Delete a Profile You cannot delete an active profile. You can also not delete the default profile. To delete a profile, do one of the following: - In the Experiment Explorer, right-click a profile and select Delete. - Choose Profiles > Experiment Setup Profile, Detection Settings Profile, Data Segmentation Profile or Parameter Profile > Delete, select a profile from the list and click OK. When you delete all Detection Settings profiles, a new default Detection Settings profile is created automatically with default settings. 8.4 Export Data and Results Export the Run Data To export the raw print information for each video frame of a run. Each row corresponds to one video frame (100 per second). If your experiment contains one or more runs with missing or corrupt data you get an error message when you try to export run data. Delete the runs listed in the error message and then export run data. - In the Visualization or Run Statistics screen, under Trial & Run Selection, select a trial and a run. - Choose File > Export > Run Data. - In the Export Run Data window, you can export run data for: - Active run (Run#) - This exports raw data from one run to an Excel file. - All runs from active trial (Trial#) - This exports raw data from all runs in Trial# to an Excel file; each run is saved in a separate sheet. Under Output, choose the File name and export Folder. - First, click Open Output Folder and then Export. The Run Data Export File The Run Data export file is an Excel file containing the following columns: - Experiment - Contains the experiment name. - Group - The name of the treatment group. - Animal - The animal ID. - Time Point - The time point of acquisition of the run. - Trial - The trial ID. - Run - The run ID. - Frame - The frame number. - Time - The time stamp of the frame. For each paw print the following parameters are displayed for each frame: - X - The X-coordinate of the center-point of the surrounding print rectangle. - Y - The Y-coordinate of the center-point of the surrounding print rectangle. - PrintLength - The length (in X-direction) of the surrounding print rectangle given in the Distance Unit selected in the Preferences. - PrintWidth - The width (in Y-direction) of the surrounding print rectangle given in the Distance Unit selected in the Preferences. - PrintArea - The size of the print (including all pixels with an intensity value greater than zero). - MinIntensity - The minimum intensity found in the print (intensity values of zero excluded). - MaxIntensity - The maximum intensity found in the print. - MeanIntensity - The mean intensity found in the print (intensity values of zero excluded). Export the Run Statistics To export the values displayed in the Summary sheet of the Run Statistics screen. Each run is represented by a single row in the export file. You can select the parameters to be exported. If your experiment contains one or more runs with missing or corrupt data you get an error message when you try to export Run Statistics. Delete the runs listed in the error message and then export Run Statistics. Export Run Statistics for the Current Run Choose Analyze > View Run Statistics, select a run, then right-click the sheet you want to export and select Export Sheet to Excel. Export Statistics for Multiple Runs - Choose Analyze > View Run Statistics, then under Trial & Run Selection, select a trial. - Choose File > Export > Run Statistics. - In the Export Run Statistics window, under Select data choose: - Export all runs from active trial (Trial#) - This exports the statistics from all runs in Trial#. Each run is represented by a row in the Excel export file. - Export all runs from all trials - This exports the statistics from all runs of all trials in the current experiment. Each run is represented by a row in the Excel export file. The number of trials and runs in the current selection are shown under the Select data options. - Under Parameters, select the parameter categories you require. - Under Statistics, select to export the Mean and/or the Standard Deviation for each statistic from the parameter categories. - Under Output, choose the File name and export Folder. - First, click Open Output Folder and then Export. The Run Statistics Export File This is an Excel file containing the following columns: - Experiment - Contains the experiment name. - Group - The name of the treatment group. - Group_Type - Group_Description - Animal - The animal ID. - Time_Point - The time point of acquisition of the run. - Time_Point_Description - Trial - The trial ID. - Trial_Description - Run - The Run ID. - Run_Description - Run_Duration - The duration of the recorded run. - Run_Average_Speed - The average speed of the animal in the recorded run. - Run_Maximum_Variation - The maximum variation in walking speed of the animal in the recorded run. - Camera_Gain - The Camera Gain value that was used during acquisition. - Green_Intensity_Threshold - The Green Intensity Threshold value that was used during acquisition. - X-Unit - The width of a single pixel as determined during calibration. - Y-Unit - The height of a single pixel as determined during calibration. - Walkway_Length - The length of the defined walkway. - Walkway_Width - The width of the defined walkway. In the subsequent columns, for each paw print the selected statistics are displayed. Note: A parameter that was not measured is indicated with an empty cell. Export the Trial Statistics To export the combined parameters of runs within a trial. Each trial is represented by a single row in the export file. You can select the parameters to be exported. If your experiment contains one or more runs with missing or corrupt data you get an error message when you try to export Trial Statistics. Delete the runs listed in the error message and then export Trial Statistics. Note: A parameter that was not measured is indicated with an empty cell in the export file. - In the Run Statistics window, under Trial & Run Selection, select a trial. - Choose File > Export > Trial Statistics. - In the Export Trial Statistics window, under Select data, choose: - Export active trial (Trial#) - This exports the combined parameters of runs within this trial. - Export all trials - This exports the combined parameters of all trials. Each trial is represented by a single row in the export file. Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - Gait Analysis White Paper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-gait-analysis-white-paper Chapter: CatWalk XT Gait Analysis with CatWalk XT Gait is an important behavioral endpoint in research on any disorder or disease affecting the movement or gait of animals. Traditionally, gait analysis was done by inking the animal's paw and letting it run across a piece of paper. This way only a limited number of gait characteristics could be measured. Nowadays, more sophisticated and automated systems are available for detailed analysis of a large number of gait parameters. The CatWalk XT system is one of them. How Does CatWalk XT Work? CatWalk XT is a semi-automated gait analysis system for rodents. The heart of the CatWalk XT system is a walkway with a corridor on a glass plate through which a rat or mouse walks from one side of the walkway to the other. Green light sent into this glass plate is able to escape only at those areas where the animal's paws make contact with the glass plate; as a result, the light is scattered and paw prints are visible. These are captured by a high speed video camera that is positioned underneath the walkway. Each pixel recorded has a certain brightness, allowing CatWalk XT to detect intensity differences between an animal's paws. CatWalk XT also measures many other parameters related to paws, and related to the spatial and temporal relationship between paws. The CatWalk XT illuminated ceiling contains red light. This allows you to see the animal's body contour in the recordings, which facilitates correct classification of the paws (e.g., left front/hind, right front/hind). The goal box on the right side can hold, for example, the animal's home cage. This makes it more attractive for the animal to cross the walkway and facilitates the acquisition of high-quality runs. Experiment Settings In the Experiment Settings you can predefine Time Points (e.g., Day 0, Day 7) and Treatment Groups (e.g., Control, Experimental, Sham). You can also set Run Criteria (minimum and maximum duration, maximum allowed variation in running speed) to check the quality of your runs during acquisition of data. A run is an animal's crossing of the walkway from one side to the other. In the Experiment Settings, you can also define how many runs per animal you want to acquire in one trial that meet the Run Criteria. In Data Acquisition, CatWalk XT will then automatically keep acquiring runs until the minimum number of compliant runs have been recorded. Trial List In the Trial List you can define Trials that you want to acquire. A Trial corresponds to an animal from one of the Treatment Groups at a particular Time Point. A Trial consists of one or more runs. Training Animals Before you start acquiring runs, you can train the animals to cross the walkway without interruptions or hitches and to enter the goal box, so all animals start from a similar baseline. This is important in order to be able, during an experiment, to compare different runs and pick up gait abnormalities that are the result of effects of treatment rather than differences in quality of runs. Training of the animals can be started before treatment. Detection Settings Configuring the Detection Settings is an important step in a CatWalk XT experiment, because light conditions and the type of animals you use may vary between labs and between experiments. The Detection Settings allows the software to adapt so that the program can distinguish between paw prints and background noise in any situation. CatWalk XT can automatically set the optimal values for Camera Gain and Intensity Threshold based on your lab conditions and your animals. After automatic configuration of the Detection Settings you have the option to manually fine-tune the settings to get even better paw prints. This is especially important if you also want to detect the animal's toes. Preparing the Walkway A clean glass plate will make sure your prints are clean. The spring-operated corridor opens up easily, so you can clean the glass plate using some proprietary glass-cleaning fluid. The width of the corridor can also be adjusted to the size of the animal; if the corridor is too wide, the animal might meander too much, and if the corridor is too narrow, a normal gait of the animal might be hampered. Carrying Out Data Acquisition You manually start acquisition, put the animal on the walkway on the left side, and then CatWalk XT automatically keeps acquiring runs until the required number of runs (as set in the Run Criteria) has been recorded. Paw Print Classification Classification of runs means assigning the correct label (left front/hind, right front/hind) to paw prints. Optionally, before classification, you have the possibility to slightly adjust the Detection Settings to improve the quality of your paw prints. With the Automatic Footprint Classification module, CatWalk XT automatically labels paws. Optionally, you can manually label paws that have not been labeled automatically, or you can label other prints than paw prints (for example, nose, tail, or abdomen). You can install the CatWalk XT software on any computer and classify runs without the hardware key. The hardware key is only required for data acquisition. Toe Classification Classification of toes is done with the Interactive Footprints Measurements Module and comes after classification of paw prints. Toe classification of the hind paws (by measuring the Toe Spread, Intermediate Toe Spread, and Print Length) can be used to calculate the Sciatic Functional Index, Peroneal Functional Index, and Tibial Functional Index. These indexes are commonly used as a tool for the evaluation of the recovery of the sciatic nerve and its branches. Additionally, CatWalk XT automatically calculates the Paw Angle, which is the angle at which the paw is placed relative to the body. Run Visualizations After you have finished classifying prints, you can visually inspect your runs by displaying 2D and 3D pictures of the paw prints. These visualizations can be exported as pictures or video so you can use them in presentations. Run Statistics Once a run and its prints have been classified, all CatWalk XT parameters are automatically calculated and can be viewed in the Run Statistics window. The Run Statistics provide a large number of gait parameters that fall into three main categories: - Parameters related to individual paw prints: for example, Print Intensity, Print Area, and Contact Area. - Parameters that describe spatial relationships between paws: for example, Stride Length, Regularity Index, and Base of Support. - Parameters that describe temporal relationships between paws: for example, Stand, Swing, and Phase Dispersions. Individual Paw Prints Print Intensity — CatWalk XT provides a number of intensity parameters that are related to how much weight the animal put on each paw. You get the minimum, maximum, and mean intensity of a paw print, but also information about the weight bearing when the largest area of the paw was in contact with the glass plate. This gives you detailed information about whether the animal avoids putting weight on one or more paws as a result of, for example, pain. Print Area — This is the surface area of the complete print (including the toes), as if it were an inked print. The Contact Area is the surface area of the paw at the moment of maximum contact with the glass plate. Furthermore, CatWalk XT provides information about at which time point during the whole contact of a paw with the glass plate the maximum contact is reached. Spatial Relationships Between Paw Prints Stride Length is the distance between successive placements of the same paw and therefore measures the step size of a paw. Regularity Index is an indicator of how normal an animal walks. CatWalk XT recognizes a number of walking or footfall patterns. If an irregular placement of a paw breaks a pattern, this paw cannot be assigned to one of the footfall patterns. As a result, the Regularity Index decreases. Base of Support is a measure of how wide either the front paws or the hind paws are placed apart during walking. Base of Support is an important parameter in spinal cord injury research; because injured animals have problems keeping their balance, they put their hind paws further apart, which is reflected in an increased Base of Support in CatWalk XT. Temporal Relationships Between Paw Prints Stand and Swing are parameters that reflect the temporal aspects of an animal's gait. Stand is the duration of contact with the glass plate of a paw, whereas Swing is the time the paw is in the air in between steps. By looking at the Stand and Swing of all four paws you can get a good idea of how a decrease in Stand of one paw is compensated by an increase in Stand of another paw. Phase Dispersions is an interesting parameter that is an indicator of inter-paw coordination. It describes the temporal relationship between the placement of a target paw relative to an anchor paw. Parameter Charts In the Run Statistics, all parameters and their values are shown in tables. To visually inspect your data or to easily create graphs, CatWalk XT comes with the Parameter Charts module. In this module, bar charts are created for all paw parameters for all classified trials in each combination of Treatment Group and Time Point. This way you can very quickly visually inspect possible differences between Treatment Groups and/or Time Points for paw statistics. You can format the charts to your own needs and export them individually or all at once. Data Export CatWalk XT offers the possibility to export a variety of different data types. You can export the Run Statistics, either as raw data or at run/trial level, to Excel. You can also export the recorded run or the Run Visualizations to a video file for playback in a presentation. Source: White paper Gait CatWalk, Noldus Information Technology --- ## CatWalk XT - Getting the Perfect Runs URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-getting-the-perfect-runs Chapter: CatWalk XT Getting the Perfect Runs CatWalk™ XT is a gait analysis system based on the voluntary movement of rats or mice across a corridor, over a glass plate. Generally, animals quickly learn to cross in a consistent manner, especially rats. However, familiarizing them with the system before you start your experiment makes your job a lot easier. So how do you familiarize and motivate your rats? Kristina Ängeby Möller has a lot of experience with pain research and gait analysis in rats, and shares some tips and tricks. Five Tips for Getting the Perfect Run 1. Get Rid of Stress Perhaps the most important factor is to reduce the level of stress as much as possible. Stress will influence the testing but also the results. CatWalk XT helps by providing a relatively dark and safe environment in which the animals can freely move. Stress relief starts with the care in the animal facility. It is vital to understand where rats come from – they are a prey species that mainly live underground and away from light. They are sensitive to threats from possible predators, including humans. As a researcher, you should always behave in a calm manner, habituate the rats to human handling, and never hold them too tightly. Also, never pick a rat up by the tail – it is one of the most sensitive parts of its body. Rats have good hearing, so refrain from making any sudden sounds, especially sounds that are similar to squeaks from rats in distress. Having some background sound in the animal facility and in the experimental room, such as music from a radio, is an advantage. 2. Friends Are the Best Motivators There are different kinds of stimuli one might consider, but a social one – using cage mates as a motivator – seems to work best. Recent versions of CatWalk XT are shipped including a goal box. If you are working with a previous version, try to acquire one. It really helps a lot to place all rats from a holding cage in the goal box and habituate them; five minutes is enough the first time, which can then be reduced to one to two minutes. Once a rat has crossed the walkway and discovered that there is an exit, it will remember that, and returning to its cage mates is really all the motivation rats need to want to cross. 3. Why Food Does Not Work Additional attempts to motivate rats with rewards, like food, will not further improve their performance. In the context of a new surrounding, this is not something rats will even willingly try, as it may be threatening to their health. Rats are one of the most successful species that have spread across the globe and are very clever; they usually avoid trying anything new unless they can assess the risk and gain from the consequences. 4. Don't Force Them Never try to make the rats walk by using sounds to startle them, by pushing them forward, or by any other technique. The more you try that, the more stressed they will get and the less they will want to walk. Instead, once you put them into the walkway, try to stay as silent and unnoticeable as possible. A recommended limit is 20 minutes of waiting for a rat to cross, but that situation rarely arises – occurring with only about one in two or three hundred rats. 5. Don't Look Down on Them Do not look down on the rats, or do anything else from above. This will intimidate the rat tremendously, as it will likely interpret your presence as something threatening. The best approach is to keep the walkway covered by a ceiling during the experiment, which is automatically the case in recent CatWalk XT versions. When a rat has become accustomed to crossing the walkway, it can then accept being lifted from it, observed, and exposed to many other distractions. About the Author Kristina Ängeby Möller has been setting up and validating in vivo behavioral models in the mouse, rat, and guinea pig for more than 35 years at AstraZeneca R&D Södertälje, R&D CNS Research Orion Corporation Orion Pharma Turku, and Karolinska Institutet. Models include stereotypic behaviors, catalepsy, monoarthritis, and neuropathy. Endpoints include spontaneous behavior, thermal and mechanical sensitivity, and gait analysis. Department of Physiology and Pharmacology, von Eulers väg 8, Karolinska Institutet, 171 77 Stockholm, Sweden. E-mail: kristina.angeby.moller@ki.se Publications - Ängeby Möller, K.; Aulin, C.; Baharpoor, A.; Svensson, C. (2020). Pain behaviour assessments by gait and weight bearing in surgically induced osteoarthritis and inflammatory arthritis. Physiology & Behavior, 225, 113079. - Ängeby Möller, K.; Svärd, H.; Suominen, A.; Immonen, J.; Holappa, J.; Stenfors, C. (2017). Gait analysis and weight bearing in pre-clinical joint pain research. Journal of Neuroscience Methods, 300, 92–102. - Ängeby Möller, K.; Berge, O.-G.; Finn, A.; Stenfors, C.; Svensson, C.I. (2015). Using gait analysis to assess weight bearing in rats with Freund's complete adjuvant-induced monoarthritis to improve predictivity: Interfering with the cyclooxygenase and nerve growth factor pathways. European Journal of Pharmacology, 756, 75–84. - Finn, A.; Ängeby Möller, K.; Gustafsson, C.; Abdelmoaty, S.; Nordahl, G.; Ferm, M.; Svensson, C. (2014). Influence of model and matrix on cytokine profile in rat and human. Rheumatology, 53, 2297–2305. - Ängeby Möller, K.; Kinert, S.; Størkson, R.; Berge, O.-G. (2012). Gait analysis in rats with single joint inflammation: Influence of experimental factors. PLoS ONE, 7, e46129. - Ängeby Möller, K.; Berge, O.-G.; Hamers, F.P. (2008). Using the CatWalk method to assess weight-bearing and pain behaviour in walking rats with ankle joint monoarthritis induced by carrageenan: Effects of morphine and rofecoxib. Journal of Neuroscience Methods, 174, 1–9. Source: White paper perfect runs, Noldus Information Technology --- ## CatWalk XT - Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-installation Chapter: CatWalk XT 2 - Installation 2.1 Install the CatWalk XT software ......................................................... See this section to install the CatWalk XT software. To assemble the CatWalk system, see the CatWalk Assembly Instructions on the CatWalk XT installation disc. To install the Ethernet interface board for the CatWalk XT camera, see page 164. 2.2 Your CatWalk license........................................................................... The hardware key contains your current license of CatWalk XT and determines which software functionalities you can use. 2.3 License activation ................................................................................ See this section to activate (or deactivate) your software license, and learn about the types of licenses of CatWalk XT. 2 - Installation 2.1 Install The CatWalk XT Software If you ordered a new computer from Noldus Information Technology when you purchased CatWalk XT, all the necessary software and hardware is already installed and tested. In that case, you only need to assemble and set up the CatWalk system. See the CatWalk XT Assembly Instructions which you can find on the CatWalk XT installation package and in a printed version that came with the system. To install the Ethernet card, see Appendix A Install the Ethernet card for the camera on page 164. Before You Install Administrator rights To be able to install the CatWalk software you must have administrator rights, that is, either you are the system administrator or you have been assigned administrator rights. Windows Power Users cannot install CatWalk XT. Do not run CatWalk XT for the first time as an administrator on a computer with multiple user accounts, because other, standard, users then are not able to run CatWalk XT. Operating systems: Windows 10 Pro, version 22H2 or later. Please do first a Windows Update to install a compatible Windows 10 version, then install CatWalk XT. See https://learn.microsoft.com/en-us/lifecycle/products/windows-10-home-and-pro Windows 11 Pro. Computer CatWalk XT 10.7 has been tested on a Dell Precision T3660. - Processor: Intel Core i7-11700, 16 MB Cache, 8 Core, 2.5 GHz to 4.9 GHz. - Memory: 16GB DDR5. The RAM minimum requirement for CatWalk XT is 16 GB. - First hard disk: M.2 256GB PCIe NVMe SSD. - Second hard disk: 3,5 inch 1 TB SATA (7200 rpm). - Graphics card: NVIDIA Quadro T1000, 4GB. 2 - Installation Ethernet network interface You need a 1-Gb (gigabit) Ethernet network interface card for connecting the digital camera to the CatWalk XT computer. If you purchased the CatWalk XT computer from Noldus, the card is already installed and configured. Experiments from previous versions of CatWalk XT If you have old experiments, first back up all your data to a secure location. Experiments are stored by default in the folder: C:\Users\Public(Public) Documents\Noldus\CatWalk XT\ Experiments). Please copy the complete folder of an experiment when transferring it to another folder on the same computer or to another computer. License Agreement See page page 189. Install Catwalk Xt note Make sure you first install CatWalk XT before you connect the Control Unit to the CatWalk XT computer. First install the CatWalk XT software and then connect the hardware key to your computer, not the other way around! If you upgrade from previous versions From CatWalk XT 8.x / 9.x - CatWalk XT 10.7 is installed alongside CatWalk 8.x / 9.x. Experiments from CatWalk XT 8.x / 9.x are automatically converted to CatWalk XT 10.7 after opening them, and cannot be opened in the previous CatWalk XT version. From CatWalk XT 10.x - CatWalk XT 10.7 replaces CatWalk XT 10.x. Experiments from CatWalk XT 10.x are automatically converted to CatWalk XT 10.7 when you open them. Important - before you install CatWalk XT 10.7 If you have CatWalk XT 10.6, we advise you to update the firmware of the Control Unit (Help > Upgrade Control Unit Firmware). See the CatWalk XT 10.6 - Reference Manual. 2 - Installation Install CatWalk XT - Download the CatWalk XT installation files from my.noldus.com. - Double-click the file CatWalk XT - Setup - [version number].exe. - In the Welcome screen of the CatWalk XT, under Installation type, select Standard. - optional Choose Custom if you want to install the software on a location other than the default one, or if you want to specify another default location for your experiments (see below) or if you want to specify which shortcuts to add to your desktop. Click Next. - Read the End-User License Agreement, select I agree and click Install. - Click Close when the message Installation complete appears. Notes During the installation of CatWalk XT 10.7, the computer restarts automatically. Please wait until the installation is complete. Installation of the drivers for the Ethernet card is included in this installation. You do not have to take further action. If installation fails Try removing the eBUS SDK driver and CatWalk XT 10.6 from the Windows Control Panel. The eBUS SDK driver was installed with CatWalk XT 10.6. Next, install CatWalk XT 10.7 which includes a 64-bit version of the driver (eBUS Runtime 64-bit). Standard file locations Installation location: C:\Program Files\Noldus\CatWalk XT 10. Experiments location: C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments. Uninstall CatWalk XT To remove CatWalk XT from your computer, do the following: 1. Click the Windows Start button and type "Programs" in the Search field. Choose Add or remove programs. Or open the Control Panel and choose Programs and Features. 2. In the Programs/Apps and Features window, select CatWalk XT 10 and click Uninstall. 2 - Installation Upgrade Catwalk Xt Prerequisites You have a CatWalk XT license and purchased an upgrade. You received an Upgrade Key from Noldus, either on the Welcome letter or by e-mail. If your license is on a USB hardware key, insert that key in a USB port of your CatWalk XT computer. Procedure - Download and install the newest CatWalk XT version from MyNoldus.com. note You do not need to uninstall previous CatWalk XT versions. - After installation is complete, start CatWalk XT. - In the window that opens, choose Activate software license key. - Choose whether to activate online or offline. For details, see page 23. - Enter the Upgrade Key that you received from Noldus. Note If your license is stored on a hardware key, you need to upgrade the license on that key. Make sure that the hardware key is pugged in the computer and the red LED on the key is on. After starting the newest CatWalk XT version, enter the Upgrade Key. 2.2 Your CatWalk License Types Of Catwalk Xt License Your CatWalk XT license is stored on a hardware key (also known as dongle) or in a software form (software license key). In all cases, to know which add-on module you have, choose Help About CatWalk XT, then click the License Info button. Enabled modules are marked with . 2 - Installation License on a hardware key Your CatWalk XT software comes with a hardware key, which determines which functionalities are available. This is a very important piece of equipment, as it is your license and will not be replaced free of charge. Please keep this in mind and make sure that you do not lose the key! You will need to pay for a new license if you do so. The driver for the hardware key is installed automatically when you install CatWalk XT. To make sure that the driver is installed, in the Windows Control Panel open Programs and Features. If the driver is installed, you should see an item named Sentinel Runtime (version 8.11). To reinstall the driver of the hardware key, run the installation of CatWalk XT 10 and select Repair. First install the CatWalk XT software and then connect the hardware key to your computer, not the other way around! Your CatWalk XT software can only acquire data if the hardware key is plugged in your computer. If the hardware key is not plugged in, you can open existing experiments, analyze data and classify runs. In order to use the full functionality of CatWalk XT on two computers, you must move the hardware key from one computer to the other. If the hardware key is not plugged in your PC or the software license is not activated, you can still start CatWalk XT and work in unlicensed analysis mode. This means that you can analyze and visualize previously-recorded data, but cannot acquire more data. See catwalk xt in analysis mode on page 30. 2 - Installation Upgrade the hardware key When you upgrade from a previous version and start CatWalk XT for the first time, the system automatically detects the hardware key and asks you to type the Upgrade Key in the Upgrade Key window box. This number is normally sent to you by e-mail or in your welcome letter. See also upgrade catwalk xt on page 19. Software license key A software license key allows you to use CatWalk XT without a hardware key plugged in your computer. important Your software license key is coupled to the hardware of your computer; not to a specific user or user group name. A software license can be of two types: Fixed. This type of license is meant to be used on a specific computer. The fixed license is associated with that computer. This association is registered on the Noldus Server. In order to re-use a fixed license on another computer, you must first deactivate that license on the computer where it is currently active. See deactivate a catwalk xt license on page 26. Floating. This type of license is meant for when you want to use CatWalk XT to acquire runs on two or more computers (though not simultaneously). 2 - Installation - If you acquire runs on the same computer in the lab and you want to analyze/visualize data on your computer in the office, a floating license is not needed. You can activate a fixed license on your lab's computer to acquire the data, while using CatWalk XT in unlicensed analysis mode in your office (see page 30). - With one floating license you can work on one computer at a time. Make sure that CatWalk XT is closed on the computers other than the one you are using at that time. - important In order to work with a floating license, your CatWalk XT computer must be connected to the internet. When you close CatWalk XT on one computer with a floating license, the license is automatically deactivated, at the condition that the computer is connected to the Noldus Server. At that point you can use CatWalk XT on another computer. See also The End-User License Agreement on page 189. The Acknowledgments and Copyright notices on page 198. Alternatively, the documents stored in the following location: C:\Program Files\Noldus\CatWalk XT 10\Documentation \Legal. 2 - Installation 2.3 License Activation Choose what applies: activate your catwalk xt license on page 23 deactivate a catwalk xt license on page 26 turn a floating license to a fixed license on page 28 turn a fixed license to a floating license on page 29 duration of the catwalk xt license on page 29 See also catwalk xt in analysis mode on page 30 Activate Your Catwalk Xt License Aim To activate a CatWalk XT license after purchase. Note that you do not need to follow this procedure if your license is on a USB hardware key. Background information When you start CatWalk XT, the software checks that your license is valid. The license may be stored in your hardware key (dongle), in your CatWalk XT computer (Fixed license) or in the Noldus server (Floating license). See types of catwalk xt license on page 19. If no valid license is found, you can activate your license by following the procedure below. Important terms Activation key. An activation key is provided by Noldus to activate your license. You find an activation key on a letter or e-mail sent to you. Computer key. A Computer key comes into play when you activate your license offline (see below), This is a key that identifies the computer that you are using during activation. License key. A license key is the unique piece of information that you obtain after you activate the license. You can find this key in CatWalk XT, by choosing Help > About CatWalk XT > License Info. Prerequisites You have installed CatWalk XT (page 17). 2 - Installation You have received a License Activation Key from Noldus. What do you want to do? Activate a fixed license (below). Do this when you want to work with CatWalk XT on one computer only. Activate a floating license (page 25). Do so if you plan to use this license on different computers at different times. If you have two or more floating licenses instead of one, you can use CatWalk XT on multiple computers simultaneously. Activate a fixed license - Start CatWalk XT. In the window that appears, choose Activate software license key. - Choose Fixed - On this computer only and click OK. - Enter or copy the Activation Key that you received from Noldus. - Select one of the options depending if your CatWalk XT computer is connected to the internet. - Activate Online. Do so if your computer is connected to the internet. Next, click OK. A message appears that the license has been activated. - Activate Offline. If your computer is not connected to the internet, you need a smartphone connected to the internet, which can scan a QR-code. 2 - Installation note The Activate Offline option is not available if you have purchased a time-limited license or received a license for a free trial. See duration of the catwalk xt license page 29 a. To obtain the Computer Key, scan the QR code with a smartphone. b. If the QR code is recognized, a web page of the Noldus License Manager opens that shows the required Computer Key (see below). c. Enter this key in the Computer Key field in the CatWalk XT License activation window and click OK. Activate a floating license Choose a floating license if you want to use CatWalk XT on different computers (though not simultaneously). With two or more floating licenses, you can work with CatWalk XT on different computers (and CatWalk XT systems) simultaneously. important You can only activate and use a floating license when your CatWalk XT computers are connected to the internet. So make sure that your CatWalk XT computer in the lab is always connected. 2 - Installation 1. Start CatWalk XT on one of the computers. In the window that appears, choose Activate software license key. 2. Choose Floating - On multiple computers and click OK. 3. Under Activate floating license, enter or copy the Activation Key that you received from Noldus. Next, click OK. 4. The license is activated. You can start using CatWalk XT. 5. Repeat the procedure on the other computers. Notes You cannot activate a term license after the expiration date. If activation fails: - Try once again and make sure that you enter the correct Activation Key and Computer Key, including capital letters and dashes. - Contact Noldus to obtain a valid Activation Key. If your license is not activated, you can still start CatWalk XT and work in unlicensed analysis mode (see page 30). Deactivate A Catwalk Xt License Aim To deactivate a software license, either to end the license agreement or to transfer the license to another computer. 2 - Installation example You have purchased a new computer and you would like to transfer your CatWalk XT license from the old to the new computer. Prerequisites CatWalk XT is running with a software license (no hardware key). The CatWalk XT computer is connected to the internet, or you have a smartphone connected to the internet. What do you want to do? Deactivate a fixed license (see below). Deactivate a floating license (see page 28). See types of catwalk xt license on page 28. Deactivate a fixed license - In CatWalk XT, choose Help > Deactivate License. - Choose Fixed - On this computer only and click OK. - Select one of the options depending if your CatWalk XT computer is connected to the internet. - Deactivate online. Do this if your CatWalk XT computer is connected to the internet. Select this option and click OK. - Deactivate offline. If your computer is not connected to the internet, you need a smartphone connected to the internet, which can scan a QR-code. a. Select this option, and click OK. b. A QR code appears on the screen. c. Scan this code using a smartphone and follow the link within 24 hours. d. Click Deactivate on the screen that appears in your browser. - CatWalk XT shows a message that the license has been deactivated and closes. Note: If your smartphone is not connected to the internet, leave the link open, go to a place where your smartphone is connected to the internet and open the linked page. When you click Deactivate offline, your license is deactivated on your computer, but not yet on the Noldus Server. For this second step you must scan the QR code, follow the associated link and click Deactivate on a web browser of your smartphone. Do this within 24 hours. 2 - Installation Deactivate a floating license Deactivate a floating license when you need to transfer that license to another computer. Note that, when you have floating licenses, in order to be able to work on one computer you just need to close CatWalk XT on the other computer(s). You do not need to deactivate the license on the other computer(s). 1. Make sure that the CatWalk XT computer is connected to the internet. 2. In CatWalk XT, choose Help > Deactivate License. 3. A message appears: License successfully deactivated. CatWalk XT will close now. 4. You can now activate that floating license on another computer. See activate your catwalk xt license on page 23 and choose to activate a floating license. See also activate your catwalk xt license on page 23. types of catwalk xt license on page 28. Turn A Floating License To A Fixed License Aim You may want to turn a floating license to a fixed license so you can use CatWalk XT on a computer without internet connection. Prerequisites You have a CatWalk XT floating license. You have an Activation Key for your floating license. Procedure - Open CatWalk XT and deactivate the floating license. Here you need an internet connection. See Deactivate a floating license on page 28. - After deactivation of the license, CatWalk XT closes. - Start CatWalk XT on the computer where you want to have the fixed license. - Choose Activate software license key, then Fixed - On this computer only. Follow the instructions under Activate a fixed license on page 24. See also types of catwalk xt license on page 19. 2 - Installation Turn A Fixed License To A Floating License Aim You may want to turn a fixed license to a floating license because you want to use CatWalk XT on multiple computers (not simultaneously). note If you purchased multiple floating licenses, you can work on multiple computers simultaneously, because a license will be active in each computer. Prerequisites You have a CatWalk XT fixed license. You need to have the Activation Key for your floating license. Procedure - Open CatWalk XT and deactivate the fixed license. See Deactivate a fixed license on page 27. - After deactivation of the license, CatWalk XT closes. - Start CatWalk XT on the computer where you want to activate the floating license. Here you need an internet connection. - Choose Activate software license key, then Floating - On multiple computers. Follow the instructions under Activate a floating license on page 25. note If you choose to deactivate offline, first click OK, then scan the QR code that appears. Follow the link and click/tap Deactivate. See also types of catwalk xt license on page 19. Duration Of The Catwalk Xt License An CatWalk XT license can be: Perpetual license This is the most common license. You purchase a copy of CatWalk XT on a one-time basis and can use the software forever. Time-limited license This license is generally valid for a period of six or twelve months. 2 - Installation A time-limited license can only be activated online. See activate your catwalk xt license on page 23. See also types of catwalk xt license on page 19. activate your catwalk xt license on page 23. Catwalk Xt In Analysis Mode Aim To carry out analysis and visualization of already-existing track data in CatWalk XT without a license. Background information An CatWalk XT license is needed whenever you acquire new data and record video. So it is important to activate a license on the computer that you use to collect data. However, you can also install the CatWalk XT software on other computers without a license. example After collecting gait data in your lab with a CatWalk XT license, copy the CatWalk XT experiment to your laptop where you have installed CatWalk XT without a license. There you can visualize and analyze your data. Procedure - If you have not done so yet, install CatWalk XT (see page 17) - Start CatWalk XT. - If CatWalk XT does not find a valid license, a window opens with the message No License key found. - Choose Start in unlicensed analysis mode. What you can do with CatWalk XT in analysis mode CatWalk XT in unlicensed analysis mode offers all the functions necessary to refine analysis and produce results. Open existing experiments. Edit the values of independent variables in the Trial List. Classify runs and adjust the Classification Settings. Create new Data profiles and select data. 2 - Installation Create new Parameter profiles and select parameters. Use all the analysis functions under the Analyze menu. Export videos, visualizations, run data, all statistics and charts. Make a backup of your experiment and restore experiments from backup files. See also License activation on page 23. Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-introduction Chapter: CatWalk XT 1 - Introduction 1.1 An introduction to CatWalk XT........................................................... How the CatWalk system works and what it does. 1.2 What's new in CatWalk XT.................................................................. What's new in CatWalk XT compared with previous versions. 1.3 Additional information........................................................................ Lists the CatWalk XT documentation, and additional help and information resources. 1 - Introduction 1.1 An Introduction To CatWalk XT This section gives a general overview of what the CatWalk program does. We recommend that all first-time users of CatWalk read this section. For information on the history of the CatWalk system, see page 174. Principle Of Operation The heart of CatWalk system consists of an enclosed walkway on a glass plate that is traversed by a rat or mouse from one side of the walkway to the other. Green light enters at the long edge of the plate and is completely internally reflected. Light is able to escape only at those areas where the animal's paws make contact with the glass plate; as a result, the light is scattered. Thanks to our Illuminated Footprints™ technology, paws are captured by a high speed video camera that is positioned underneath the walkway. The video camera transforms each scene (the area in front of the lens) into a digital image (an image composed Figure 1.1 The CatWalk system. In the inset, a rat on the walkway. 1 - Introduction of discrete pixels of digital brightness values). The digital images are transferred to the computer through an Ethernet connection. The brightness of a pixel depends on the amount of light received from such an area by the camera. The Illuminated Footprints™ technology enables intensity differences to be detected between animals' paws. Paw Detection In order to be able to classify paw prints in the video, you first need to set the CatWalk program to distinguish between paw prints and background noise. For this you can adjust the Camera Gain and Green Intensity Threshold to set the Maximum and Minimum Green Intensity, respectively, of the pixels that comprise a paw print. Classifying runs The video images with paw prints are used in the footprint classification. You assign labels (for example, right hind paw, left front paw) manually or automatically to illuminated paw prints in each video image. You can also determine (Intermediate) Toe Spread, Print Length and Paw Angle with the interactive footprint measurements module. Once classification is done, the CatWalk software automatically calculates a wide number of parameters in each of the following categories: Parameters related to individual footprints: for example, initial contact of each placement of a paw, the duration of contact of a paw print with the glass plate, the width and length of a complete paw print, the intensity of a paw, the time the animal stands on a single hind paw or both hind paws, etc. Parameters related to the position of footprints: for example, stride length, base-of- support, relative print positions. Parameters related to time-based relationships between footprints: for example, footfall patterns, phase dispersions, support formulas. The Sciatic Functional Index which is commonly used as a tool for the evaluation of the recovery of the sciatic nerve. For a detailed description of all parameters calculated by the CatWalk program, see Analyze Data on page 91. Applications See Application examples on page 135. 1 - Introduction 1.2 What's New In CatWalk XT For Users Of Catwalk 10.6 CatWalk Control Unit The CatWalk Control Unit is now connected to the PC through a USB cable with connectors of type B and C. Installation procedure The software installation procedure has been greatly simplified. You no longer have to install and configure the Ethernet card drivers and the camera drivers separately. The new CatWalk XT installation wizard does that for you. Software License Key You can purchase CatWalk XT with a software license that makes it easier to use the software without worrying to lose or damage the hardware key. You can choose to have your license coupled with one computer (named Fixed license) or with multiple computers (Floating license). See Your CatWalk license on page 19 and License activation on page 23. Data analysis: Phase Dispersions and Couplings In the Phase Dispersions and Couplings analysis sheets, the Normal Mean has been removed from both sheets because of its problematic interpretation. A bug was fixed that caused the average CStat Mean of Phase Dispersions to fall outside the range allowed (-50 % to 75 %). See phase dispersions on page 123. In the Phase Dispersions and Couplings analysis sheets, the CStat Mean is reported within the following ranges: - For Phase Dispersions: -50 % to 50 %. Note that a value of 55 % is the same as -45 % in the circular statistics domain. - For Couplings: 0 % to 100 %. To measure the spread of data around a mean, two statistics are offered: the Angular Deviation (which is the same as the Standard Deviation in CatWalk XT 10.6 and earlier) and the Circular Standard Deviation (new in CatWalk 10.7). For the difference between the two statistics, see page 179. If the average CStat Mean of Phase Dispersions is higher than 50%, it is reported as its complementary (negative) value. For example, the values of Phase Dispersions 50, 55 and 60 would give CStat Mean = 55 %, but CatWalk XT 10.7 reports CStat Mean = -45 %, which is the complementary negative value of 55% in the circular statistics domain. 1 - Introduction Excel sheet for calculating circular statistics An Excel sheet has been added to your documentation that provides formulas for computing circular statistics. See page 180. Circular charts for Phase Dispersions and Couplings Phase dispersions and Couplings are expressed with circular statistics. Circular charts are ideal to visualize that kind of data. To facilitate interpretation of the results for those two groups of CatWalk parameters, in the Group statistics and charts screen the bar charts have been replaced by circular charts. See interpreting the circular charts on page 133. New colors in data visualization The colors of many charts, for example, that of footfall patterns and the timing view, have been adjusted in order to improve their accessibility to users with color vision deficiency. 1.3 Additional Information Documentation CatWalk XT comes with the following documentation: describes how to use the CatWalk XT system, and how to install the software and the hardware on the computer. If you purchased the CatWalk XT computer from Noldus Information Technology, all hardware and software on this computer already has been installed and tested. CatWalk XT 10.7 - Assembly Instructions.pdf. This document describes how to assemble the CatWalk system and the goal box. CatWalk XT 10.7 Quick Start Guide.pdf. This document describes how to set up, carry out and analyze an experiment with CatWalk XT. Sample Experiments The CatWalk XT software includes three sample experiments, which contain data collected in real experiments carried out with mice and rats. Sample experiments are a good way to start understanding gait analysis in CatWalk XT if this is the first time you operate the software. To open a sample experiment: 1 - Introduction 1. In CatWalk XT, choose Restore backup in the start screen or choose File > Restore Backup. 2. Browse to C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments\Backups. 3. Select one of the files with extension CWZ and click Open. 4. Select where to save the experiment. By default, experiments are saved in C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments. The Help Menu The Help menu in the CatWalk XT program contains the following options: Help Topics - Displays the PDF of the CatWalk XT Reference Manual (F1). Tutorial videos - Opens a folder on your PC where the tutorials are stored. Noldus Online - If your computer is connected to the internet, choose this option and click one of the following items: - The CatWalk XT Home Page for general information on CatWalk and relevant publications. - Customer Support then click Support to contact the Help desk. - Knowledgebase then click Resources to search through dozens of entries in a database of questions submitted by our customers with answers by our support staff. - Report an issue to fill a form about an issue you encountered when using Catwalk XT. Deactivate License - If you have a software license, you can choose to move a license from one computer to another. Select Deactivate License on a PC in order to be able to activate the same license on another PC. See License activation on page 23. Upgrade License - If you already are a CatWalk user (XT 8/9) and you have purchased the latest version of CatWalk, choose this option to type in the new Upgrade Key number that you have received from Noldus. Enter this number in the newest software version, not the old one. If you have CatWalk XT 10.0 or 10.5, you do not need to purchase a new license. About CatWalk XT - Contains information about your copy of CatWalk XT. Click the License Info button to see the name of the d user and the license number of your software. 1 - Introduction Noldus Help Desk If you have any problems, questions, remarks or comments, please let us know. You can contact us at our support page: my.noldus.com We offer 24 hour support by help desks in various time zones. Before you contact Technical Support, please have the following information available. To find this information, go to the Help menu and select About CatWalk XT: The version number of your copy of CatWalk XT. The name of the registered user and the license number (Help > About CatWalk XT > License Info). Other contact information Make a PC report for the Help desk This section is needed if the Noldus Help desk asks you to send them a PC report for the CatWalk XT computer. 1. Download the utility from the Help desk and copy it to the CatWalk XT computer. 2. Double-click on the file siw64.exe. 3. Choose File > Create Report File > HTML Report and save the file to your desktop. 4. Send the HTML file as an e-mail attachment to the Help desk. Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - Prepare Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-prepare-data-acquisition Chapter: CatWalk XT 4 - Prepare Data Acquisition 4.1 Train the animals................................................................................. Before you start acquisition, it is recommended to train the animals to cross the glass plate. This results in better data. With the Detection Settings the CatWalk system distinguishes the paw prints from the background. 4.3 Specify the acquisition settings .......................................................... In the Acquisition Settings, you can view the snapped Background Image, specify how CatWalk should treat acquired runs and set the Sound feedback. 4 - Prepare Data Acquisition 4.1 Train The Animals Training Protocol Before you start acquiring runs, animals need to learn to cross the walkway without interruptions or hitches so all animals start from a similar baseline. This is important in order to be able, during an experiment, to compare different runs and pick up gait abnormalities that are the result of effects of treatment rather than differences in quality of runs. Below you find a description of a training procedure that you can adapt to suit your experimental setup: 1. Habituate the animal to the CatWalk system by placing it in the corridor for 1 minute on a number of consecutive days until it freely explores the walkway. Make sure the corridor walls are together as close as possible so the animal is still able to comfortably walk in between the walls but is not able to meander too much from side to side. 2. One week prior to treatment, train the animals to run across the glass plate with a minimum of three runs per day. You can condition the animals to run by signaling the availability of a food pellet at the other end of the walkway using a conspicuous auditory or visual cue placing food pellets. If necessary, subject the animals to mild food restriction or deprivation. You can use all sorts of incentives to facilitate runs across the walkway. You can use normal food pellets but also special rodent sweets or candy. Using the special goal box animal crossing the walkway. 3. The training criterion could then be that the animal crosses the walkway without any interruptions or hitches, in three consecutive runs. The time it takes for the average animal to cross the glass plate can be used as a basis for the run criteria (see page 39). Tips From Catwalk Xt Users Training animals in a different environment Some users find it more convenient to train an animal to cross a certain distance, similar to the length of the walkway, in another apparatus than the CatWalk system. For example, you can start training an animal to run from one side of an open field to the other. Once it has learnt to run this distance, you can let it run on the walkway. 4 - Prepare Data Acquisition Using home cage mates If you use the goal box, let all animals from a home cage habituate together in the goal box. For example, the first time for five minutes, the next time for two-three minutes. In that case you must make sure that only one rat crosses the walkway and the others stay in the goal box, for example using a sliding door between the walkway and the goal box entrance. When the animal approaches the goal box, open the sliding door and close it carefully to avoid pinching the animals' tail after it has entered that cage. How long should you wait? Let the animal find its own way to the other end of the walkway, without trying to force it in any way. Wait up to for example 15-20 minutes. Experience shows that patience produces good results. 4.2 Configure The Detection Settings Introduction To Detection Settings Detection settings and profiles The aim of the Detection Settings is to achieve an optimal intensity range for the paw prints and to filter out background noise. This is done by putting an animal of average weight on the walkway and then adjusting the Camera Gain and Green Intensity Threshold. Optionally, you can adjust the voltage (intensity) of the green and red lights in, respectively, the walkway and the illuminated ceiling. CatWalk provides quantitative feedback in order to define an optimal range between the minimum and maximum print intensity. Make sure to turn the lights off before configuring the Detection Settings. Alternatively, you can work under red light conditions. Make sure you avoid the red ambient light from shining directly into the camera. Make sure you completely open the camera's aperture and you focus the camera. Detection Settings are stored in a Detection Settings profile. You can create multiple Detection Settings profiles of which one is active during acquisition (see also Profiles on page 150). When you start up CatWalk XT for the first time, two Detection Settings profiles are present: Rats and Mice. 4 - Prepare Data Acquisition You can configure Detection Settings both automatically and manually. We recommend to first carry out auto detection and then manually fine-tune the settings (see below). Basic procedure - Carry out auto detection (see page 49) to get optimal values for Camera Gain and Green Intensity Threshold. - Adjust the Camera Gain and Green Intensity Threshold to further optimize detection (see manual detection on page 51). - If necessary, adjust the Green Walkway Light and/or Red Ceiling Light to further increase the quality of the paw prints (see Adjust the intensity of the Green Walkway Light and/or the Red Ceiling Light on page 52). Auto Detection - First, put an animal on the walkway. Make sure the illuminated ceiling is lowered. - In the Profiles Explorer, double-click the Detection Settings profile you want to use: Mice or Rats. The difference between the Mice and Rats Detection Settings profile is the default intensity of the Green Walkway Light (Mice: 16.5 Volts, Rats: 16.0 Volts). For both Mice and Rats, the default value for Camera Gain is 20, for Green Intensity Threshold is 0.10 and for Red Ceiling Light is 17.7 Volts. Figure 4.1 shows the initial values for Camera Gain and Green Intensity Threshold under Detection Settings, and Maximum and Minimum Green Intensity under Results, before the start of Auto Detection. 4 - Prepare Data Acquisition - Click the Reset Prints button and then the Start Auto Detect button. The program now automatically adjusts both Camera Gain and Green Intensity Threshold in consecutive steps to achieve the optimal range. Adjustment of the Camera Gain results in a value for Maximum Green Intensity between 197 and 203 based on the prints in the Print view. Adjustment of the Green Intensity Threshold ensures that prints that do not contain pixels with an intensity above the Minimum Green Intensity are removed from the Print view. It is important in this step that the animal walks through the camera view a number of times for proper determining of the detection settings. If the animal just sits still, the detection settings might not work for a moving animal. - When Auto Detection is finished successfully, a message appears. - You can now do the following: You can accept the settings and proceed to Acquisition Settings (see page 53). You can manually adjust the Camera Gain and Green Intensity Threshold to tweak the quality of the paw prints (see manual detection on page 51). Furthermore, you can adjust the intensity of the Green Walkway Light and/or Red Ceiling Light (see Figure 4.1 Part of the Detection Settings window. This example shows the default values under Detection Settings and Auto Detection Settings before auto detection. 4 - Prepare Data Acquisition page 52). This might be useful if you work with either very heavy or very light animals and the default settings in the Detection Settings profiles Rats and Mice do not result in optimal detection of the paws. Also, decreasing the intensity of the Red Ceiling Lights might result in better detection of toes for use with the Interactive Footprint Measurements. Auto Detection Settings Under Auto Detection Settings you can set the following: Maximum range from - The Camera Gain is automatically adjusted until the Maximum Green Intensity (displayed under Results) reaches a value within this range. The default range is between 197 and 203. Frames before delta - This parameter determines how many video frames with prints should be detected before the Camera Gain is auto adjusted. A print should contain at least one pixel with an intensity above the Intensity Minimum value. The default number of frames is 5. Note: the frame rate of the CatWalk camera is 100 frames per second. Intensity Minimum - This is the minimum value for the intensity. Each print should contain at least one pixel with an intensity above the Intensity Minimum. The default value is 85. Prints caused by background noise (such as, other light sources than the green LEDS, dirt) that do not contain a single pixel with an intensity above 85 are automatically removed by an increase of the Green Intensity Threshold. Manual Detection - First, put an animal on the walkway. Make sure the illuminated ceiling is lowered. - Choose Setup > Detection Settings. As soon as the Detection Settings window opens, the Print view shows the animal's cumulative prints. Under Results, the Maximum and Minimum Green Intensity of all prints shown in the Print view are displayed, based on the current settings of the Camera Gain and Green Intensity Threshold shown under Detection Settings. The Camera Gain (dB) determines the Maximum Green Intensity, the Green Intensity Threshold determines the Minimum Green Intensity. - Under Detection Settings, adjust the Camera Gain until the Maximum Green Intensity value for these prints is approximately 203. The absolute maximum intensity for prints is 255. 4 - Prepare Data Acquisition As a result, under Results, the Maximum and Minimum Green Intensity, and Range are changed, based on the current values for Camera Gain and Green Intensity Threshold. Each time you adjust Camera Gain, the prints in the Prints view are reset. - If necessary, increase the Green Intensity Threshold to remove noise, that is, prints in the Print View that are not paws. As a result, in the Print view, the noise is filtered out and under Results, the Minimum Green Intensity and Range both change. - Click OK when you are done. Adjust the intensity of the Green Walkway Light and/or the Red Ceiling Light Adjust the intensity of the Green Walkway Light when the Camera Gain reaches its maximum or minimum value; this can occur if, respectively, the animal's paws exert too little pressure on the glass plate or if there is too much background noise. You get an error message if this happens. For example, with a large, heavy rat, the Camera Gain can drop below the minimum value of 6. In that case, decrease the Green Walkway Light intensity from the default 16.0 to 15.5. Next, re-do auto detection (see page 49). If detection of the toes is important (for example, if you want classify toes in the Interactive Footprint Measurements to calculate the Sciatic Functional Index), make sure to check whether manually adjusting the intensity of the Green Walkway Light (in steps of 0.25) might result in even better detection of the toes, especially for light-weighted animals. Also, reducing the intensity of the Red Ceiling Light might increase the detection of the toes (see Figure 4.2 for an example of what the optimal intensity of the Red Ceiling Light should look like). Figure 4.2 Two examples of Red Ceiling Light intensities. In the top picture, the intensity is too low. As a result, the animal is only detected when it already has entered the walkway. Furthermore, the body contour is not fully visible which results in poor performance of the automatic classification. The bottom picture shows an example of optimal intensity of the Red Ceiling Light. 4 - Prepare Data Acquisition We recommend to adjust the intensity of the Green Walkway Light and/or the Red Ceiling Light after determining the optimal values for Camera Gain and Green Intensity Threshold. As a rule of thumb, the optimal value for Camera Gain ranges between 10 and 20 dB. If the value of Camera Gain is far outside this range (for example, 6 or 35), adjust the intensity of the Green Walkway Light and re-do auto-detection until the Camera Gain is within the optimal range (10 - 20 dB). 4.3 Specify The Acquisition Settings Choose Setup > Acquisition Settings. Background Image When you have snapped a Background Image before acquisition (indicated by a check mark icon; see page 58), you can view it by clicking the View Background Image button. When the Background Image does not cover the area of interest of the walkway, you should (re-)define the walkway. Run Settings You can specify the following settings: Auto abort runs when the duration exceeds ... seconds - When selected, this option automatically stops acquisition when the set time is exceeded. The Auto abort run... option is different from the Maximum run duration in the run criteria (see page 39). When the animal exceeds the Maximum run duration, the run is marked 'non-compliant' but acquisition is not aborted. CatWalk XT stops recording automatically when the run duration reaches 60 seconds. Runs longer than 60 seconds generate so much data that it can impede the computer's performance. Discard auto aborted runs - When selected, CatWalk automatically deletes runs that exceed the time set in the Auto abort runs... option. Discard user aborted runs - When selected, runs that are stopped by the user are deleted. 4 - Prepare Data Acquisition When this option is not selected, when you manually stop acquisition during a run, the run is saved. Discard runs not compliant with the Run Criteria - When selected, runs that do not meet the run criteria (see page 39) are automatically deleted. Discard incomplete prints at the start and end of a run - When selected, paw prints or part of paw prints on the border of the walkway are not included in the classification (that is, CatWalk draws no rectangle around the print). Including incomplete prints in the analysis affects parameters, such as, Print Area or Max Contact Area. Please note that if a paw print consists of sub-prints (for example, toes), the sub-prints that are not on the border of the walkway are not discarded. As a result, sub-prints that are not on the border are included in the classification, sub-prints on the border are not (see Figure 4.4 for an example). To discard the complete print, select all labeled sub- prints and label them as Junk. Sound Feedback It might be useful to get auditory feedback (system beep) on the status of acquisition, especially when you are not able to view the runs on the monitor. You can select the following: Run start (1 beep) - When selected, you get one system beep when acquisition starts. Run stop (2 beeps) - When selected, you get two system beeps when acquisition stops. Figure 4.3 Example of the result of selecting the option "Discard incomplete prints at the start and end of a run" in Classification. A paw print directly on the border of the walkway is not included for classification (CatWalk draws no rectangle around the print) and therefore available for labeling. Figure 4.4 Example of a paw print of which a sub-print (on the border of the defined walkway) is not included in the classification and another one (labeled RH) is included in the classification. To exclude the labeled sub-print, reset the label and label the print as Junk. 4 - Prepare Data Acquisition Error (e.g. camera connection lost, 3 beeps) - When selected, you get 3 system beeps if an error occurs. Turn Sound Feedback off when you suspect it might disturb the animals. Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT - Set up an Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-set-up-an-experiment Chapter: CatWalk XT 3 - Set up an Experiment 3.1 Start CatWalk XT ................................................................................. Turning on the CatWalk system and starting CatWalk XT. 3.2 Set up the walkway ............................................................................. Define the layout of the walkway and calibrating the walkway. 3.4 Specify the experiment settings ......................................................... Define your treatment groups and run criteria. 3.5 Define the Trial List.............................................................................. In the Trial List you can enter variables for the trials you plan to acquire. 3.6 Experiment setup profiles................................................................... Save the current experiment settings, time points, treatment groups and Trial List to a profile that you can apply to future experiments. Select the Distance Units and number of decimals to be displayed. In the Preferences you can also set the program Folders, the Auto Save interval and the colors in which paws and other prints are displayed. 3 - Set up an Experiment 3.1 Start CatWalk XT Turn On The Catwalk System Prerequisites If you upgrade from CatWalk XT 8/9, you need the CatWalk Control Unit. Contact your nearest Noldus representative for information. If you upgrade from CatWalk XT 10.0, you need to upgrade the firmware of the Control Unit. Contact the Noldus Help desk (see page 14). See the CatWalk XT Assembly Instructions on the installation disc to install the CatWalk system and the Control Unit. Procedure - Check that the on-off switch of the walkway (located on the left side) is turned On. The Control Unit must be connected to the camera, walkway and illuminated ceiling (if this not the case, see the Assembly Instructions for details). The Control Unit must also be connected to the CatWalk XT computer via a USB cable if you want to acquire data. Make sure the Control Unit is not connected to the mains socket yet! - Now connect the Control Unit to the mains socket, and on the Control Unit, turn the switch on. The red lights busy/alive and power on the Control Unit turn on, and the busy alive lights starts flashing. When the Control Unit is finished configuring the LED lights, both red lights turn off. The green and red LED lights of the CatWalk system flash until the correct intensity levels are reached. - Make sure you turn on the CatWalk system at least 15 minutes before you start using CatWalk. 3 - Set up an Experiment - To turn off the CatWalk system, turn the switch off on the Control Unit. Start Catwalk Xt After turning on the CatWalk system, it can take a couple of minutes for the camera to be detected. This is indicated by the Acquiring network icon in the Windows task bar. Note that the yellow triangle does not mean that something went wrong. It means that the PC has not found a network. However, the camera has been detected. Do not start CatWalk XT before this icon appears. To start CatWalk XT, double-click the CatWalk XT icon on the desktop. After starting CatWalk XT, you may get a message that the firmware of the Control Unit needs to be upgraded. Contact the Noldus Help desk (page 14). 3.2 Set Up The Walkway Setting up the walkway involves: Defining the layout of the walkway - In this step you outline the area of the walkway that you want to record, that is the area inside the corridor. Calibrating the walkway - This is done so CatWalk can convert pixels to real-life dimensions. 3 - Set up an Experiment Define The Layout Of The Walkway - Do one of the following: In the Application Startup Tasks window, select Setup the walkway and then click Define the layout of the walkway. Choose Setup > Define Walkway. Click the Define Walkway icon in the tool bar In the Define Walkway window, you see the full camera image. If you do not see an image, open the camera's aperture. Make sure the camera is in focus. If you do not see a camera image, close the Application Startup Tasks window and choose Setup > Camera. In the Camera Selection window, click the Refresh button, select the Gevicam camera in the Camera field and click OK. 2. Adjust the camera's vertical position to the match the type of animal you are using. You should get 5-6 step cycles per run. This corresponds to about 45 cm on the walkway for mice and 70 cm for rats. 3. Position the mouse pointer over the rectangle so it becomes a four-headed arrow; drag the rectangle to the top-left corner of the area of the walkway you want to outline (see the arrow on the left in the figure below). 4. Next, position the mouse pointer at the bottom-right corner of the rectangle so the pointer becomes a resize pointer. Drag the bottom-right corner of the rectangle to the bottom-right corner of the area of interest on the walkway (see the arrow on the right in the figure below). Make sure that all sides of the rectangle are visible within the camera view. 5. Click OK. Figure 3.1 The walkway and the corridor in the CatWalk system. 3 - Set up an Experiment Calibrate The Walkway - Do one of the following: In the Application Startup Tasks window, click Setup the walkway and then Calibrate the walkway. Choose Setup > Calibrate Walkway. Click the Calibrate Walkway icon in the tool bar. - Put the Calibration sheet in the middle of the glass plate. If necessary, put the camera in focus using the text on the Calibration sheet. The Calibration sheet is enclosed in the CatWalk box with the assembly instructions. If you do not find it, on the CatWalk XT installation disc open the Documentation folder and print the Calibration sheet PDF file that matches your page size settings. - Move and resize the white rectangle to match the 20 x 10 cm rectangle on the calibration sheet. If you use another shape with known dimensions to calibrate the walkway, type in the Width and Height at the bottom of the Calibrate Walkway window and select the appropriate Unit. 4. Click OK. For an experiment, with a specific setup of your CatWalk system, you only need to set up the walkway once, unless something changes to the hardware setup of the system (for example, the camera was moved or the width of the corridor was changed). When you close an experiment, the layout of the walkway and the calibration are stored within the application. Next time you open CatWalk, the Application Startup Tasks window shows the last date/ time the walkway was defined and calibrated. 3.3 Create A New Experiment - To create a new experiment, do one of the following: In the Application Startup Tasks window, click Create a new experiment. Choose File > New Experiment or press Ctrl+N. Click the New Experiment icon in the tool bar - In the New Experiment window, enter the Name of the experiment. The name cannot contain any of the following characters: /:*?\"<>|'&.; . - Select a Setup profile from the list. See Experiment setup profiles on page 43 for more information. 3 - Set up an Experiment - Optionally, browse to the location where you want to save your experiment. important Do not save your experiment to a USB stick because this might result in a corrupt experiment. - Optionally, add a Description and edit the name in the Created by field. - Click the Create experiment button. 3.4 Specify The Experiment Settings Experiment Settings Screen In the Experiment Settings screen, you define the animal type, time points, treatment groups and the run criteria. These variables and values stay constant throughout the experiment, but potentially affect the outcome of the experiment. Open the Experiment Settings screen Do one of the following: Choose Setup > Experiment Settings In the Experiment Tasks window, click Experiment Settings. Click the Experiment Settings icon in the tool bar In the Experiment Explorer, under Setup, double-click Experiment Settings. Animal Type As Animal Type you can select Rat or Mouse. The Automatic Footprint Classification (AFC) module uses a different algorithm depending on whether you select Rat or Mouse. Furthermore, the Sciatic Functional Index, which is only available if you have the Interactive Footprint Measurements (IFM) module, is calculated differently for rats and mice. When you do not have the AFC or IFM module, it does not matter which Animal Type you choose. However, when you later want to use the AFC and/or IFM module in the same experiment, you should then select the correct Animal Type. For the IFM module, make sure in the Detection Settings that the animals' toes are detected properly! 3 - Set up an Experiment Time Points Under Time Points, define the time points at which you carry out data acquisition. Use time points to distinguish between trials of the same animal. Add time points - Click the Add Time Point button once to add one time point, or more than once to add multiple time points. - Click the name to type in the name for a time point. - Optional: Add a Description for a time point. Click the cell under Fill Style and change the color in which the time point is displayed in the Group statistics and charts screen. - Repeat the previous steps to add additional time points. Delete Time Points - Click on a time point name. To select multiple items, click them while holding the Ctrl key. - Click the Delete Time Point(s) button and click Yes. Treatment Groups Under Treatment Groups, predefine your groups. Add treatment groups - Click the Add Group button. - In the new row of the table, from the list in the Type column select one of the predefined types (Undefined, Experimental, Control and Sham). - In the Name column, type the name of the Treatment Group. Change the Name of a group to reflect the type of treatment group, because the Name of the treatment group is used in the analysis (see Figure 3.2). 3 - Set up an Experiment - Optional: Add a Description for that group. This description is also exported to an export file with the statistics and can be used as an independent variable. Click the cell under Fill Style and change the color in which the treatment group is displayed in the Group statistics and charts screen. Delete groups - Click in the row of the groups you want to remove. You can select multiple groups by clicking rows while holding the Ctrl key. - Click the Delete Group(s) button and click Yes. Copy and paste values from one cell to another - Select the contents of the cell. - Right-click the cell and select Copy. - Select the cell in which you want to paste. - Right-click this cell and select Paste or press Ctrl+V. Run Criteria Define run criteria to automatically check the quality of your runs in terms of mean running speed and variation in running speed. This automatic check is useful because it enables you to compare runs within and between animals. In order to achieve this, animals should be Figure 3.2 The Treatment Groups table in the Experiment Settings screen. In this example, two groups have been defined. 3 - Set up an Experiment trained to cross the glass plate before they are eventually tested (see Train the animals on page 47). Under Run Criteria you can set the following criteria: Minimum run duration - When the animal is slower than this Minimum run duration, the run is marked 'non-compliant'. Maximum run duration - When the animal exceeds the Maximum run duration, the run is marked 'non-compliant'. This does not stop data acquisition of this and the next runs. If you want to automatically abort data acquisition after a specific time, do this in the Acquisition Settings (page 53). Minimum number of compliant runs to acquire - Data Acquisition continues until this number of runs that meet the other three criteria (Minimum and Maximum run duration and Maximum allowed speed variation) has been acquired. The maximum number of runs (compliant + non-compliant) to acquire per trial is '100'. Use maximum allowed speed variation - With this criterion you can check whether the animal walked very slowly during part of the run, and then extremely fast during another part. When this happens, the run can still meet the Minimum and Maximum run duration criteria, but the variation in speed would be too high. The speed variation is calculated as follows: the run is divided into 5 intervals with equal duration. For each interval, the average speed is calculated and this speed is expressed as the percentage difference, from the average speed of the total run. For example, an animal starts very slowly and its speed in the first interval is 5 cm/s. After that, it speeds up, resulting in an average speed of the total run of 20 cm/s. The speed variation is: ([absolute difference (5-20)] / 20) * 100 = 75% (expressed as a whole number). By default, Use maximum allowed speed variation is not selected. The run criteria become read-only when you have acquired a run. What next? Click >> Trial List in the bottom-right corner. Figure 3.3 The Run Criteria in the Experiment Settings screen. 3 - Set up an Experiment 3.5 Define The Trial List The Trial List In the Trial List you can enter a number of variables for the trials you plan to acquire. Open the trial list Do one of the following: Choose Setup > Trial List. Click the Trial List icon In the Experiment Tasks window, select Open Trial List. In the Experiment Explorer, under Setup, double-click Trial List. Add trials - Click the Add Trial(s) button. - In the Add Trial(s) window, enter the Number of Trials you want to add for each time point and treatment group you defined in the Experiment Settings and click Add. We advice you not to add more than 500 trials per experiment. Repeat this step for each time point * treatment group combination. - If necessary, re-assign a treatment group to a trial/animal by selecting a treatment group from the list. - You can now define the following User Variables: Animal - Click a cell in the Animal ID column to change the animal ID. Time Point - Select a time point from the predefined list in the Time Point column (see time points on page 38 for details). Optionally, you can enter a Description. This description is also exported to an export file with the statistics and can be used as an independent variable. The Trial name Trial0001, Trial0002, etc. is used as an ID to identify individual trials. Therefore, trial names must be unique. You can edit trial names. System variables The Trial List also displays the following system variables for each trial: Acquisition Status - The shows the Acquisition Status of a trial. The status can be Planned, Partially acquired, Acquired. Total Runs - This shows the number of acquired runs. 3 - Set up an Experiment Compliant Runs - This shows the number of acquired runs that meet the run criteria (see page 39). Classification status - This shows Classification Status of the acquired runs of a trial. The status can be Not classified, Partially classified, Classified. Delete a trial Do one of the following: In the Trial List, select the trial you want to delete and click the Delete Trial(s) button. tip You can select multiple trials: select the first trial you want to remove, press and hold the Shift key and select the last trial you want to remove. if you want to select multiple, individual trials, press and hold the Ctrl key and select the trials. In the Experiment Explorer, right-click a trial and select Delete. important Deleting a trial cannot be undone. It is not possible to delete an 'active' trial. Sort the trial list You can sort each column of the Trial List by clicking its column header. Although you can sort the Trial List and/or edit trial names, in Acquisition, the order of trials is always the original order when the Trial List was created. Copy and paste contents in the trial list - Select the contents of the cell, then right-click and select Copy (Ctrl+C). - Click the cell where you want to paste the text, right-click and select Paste or press Ctrl+V. Note that you cannot copy and paste multiple cells from Excel. Figure 3.4 The Trial List. In this example, six trials have been defined for six different animals from three different treatment groups. 3 - Set up an Experiment 3.6 Experiment Setup Profiles You can save the current Experiment Settings, time points, treatment groups and Trial List to an Experiment Setup profile. You can have multiple Experiment Setup profiles. When you create a new experiment, you select an Experiment Setup profile, so those settings are copied to the new experiment without the trials. Add an Experiment Setup profile To create a new Experiment Setup profile that contains the current Experiment Settings and Trial List: 1. Do one of the following: In the Profiles Explorer, right-click Experiment Setup Profiles and select Add New Profile. Choose Profiles > Experiment Setup Profile > New. 2. Select 'Create an Experiment Setup Profile...from the current experiment'. When you select Create a blank Experiment Setup Profile, an Experiment Setup profile is created with default experiment settings and no time points, treatment groups or trials. 3. Enter a name and click Add. 4. If necessary, make adjustments and click OK to store the profile. Open an Experiment Setup profile Do one of the following: In the Profiles Explorer, right-click an Experiment Setup profile and select Open. Choose Profiles > Experiment Setup Profile > Open. Next, select a profile from the list and click Open. Duplicate an Experiment Setup profile - In the Profiles Explorer, right-click an Experiment Setup profile and select Duplicate. - Enter a name and click OK. Rename an Experiment Setup profile - In the Profiles Explorer, right-click an Experiment Setup profile and select Rename. - Type in a name and press Enter. 3 - Set up an Experiment Delete an Experiment Setup profile Do one of the following: In the Profiles Explorer, right-click an Experiment Setup profile, select Delete and click Yes. Choose Profiles > Experiment Setup Profile > Delete. Next, select a profile from the list and click Delete. 3.7 Set Your Preferences Procedure - Choose File > Preferences or click the Preferences icon on the tool bar - Click the tab that applies and make the necessary changes. General - Choose the Distance Unit (Millimeters, Centimeters, or Inches) and the Number of Decimals shown for Numbers, Times and Percentages. Folders and Auto Save - Optionally, change the default location of the new experiments, new backup files and the export folder. Here you can also turn on/turn off Auto Save and set the auto save interval. Colors - You can choose the colors in which paws and other body parts are displayed in the Print and Timing View. For more details, see the below. Note that the default colors have changed in CatWalk XT 10.7 to make them better distinguishable to most users. Messages - We recommend to keep the option Regularly prompt for backup selected; every 10th time you save an experiment, a message appears reminding you to back up your experiment. 3. Click OK to apply the new preferences. 3 - Set up an Experiment Colors Paws / Limbs / Other Select the colors that are used in the Timing View for Paws, Limbs and Other body parts. To change a color, click it and select a new color. Classification Select the colors of the rectangles and associated labels in the Print View. You can do this for Labeled, Unlabeled, Selected and Junk prints. To change a color, click it and select a new color. Use individual colors for labeled prints When you select this option, the labeled prints are displayed in the colors selected under Paws. When the option is not selected, all labeled prints are displayed in green. Source: CatWalk XT 10.7 - Reference Manual --- ## CatWalk XT 10.7 - Technical Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-107-technical-specifications Chapter: CatWalk XT CatWalk XT10 Technical Specifications CatWalk™ XT is an easy-to-use and highly sensitive tool for the detailed assessment of gait changes in laboratory rodents. CatWalk is a plug-and-play system and consists of the following components: - The walkway: consists of a hardened glass plate, a spring-operated corridor, an illuminated ceiling, a control unit, and a goal box. - A 100 frames per second (fps) high-speed color camera that records the footfalls and body contour. - The CatWalk XT software, version 10, for the recording and analysis of the footprints and gait of rodents traversing the walkway. - Top-of-the-line computer equipment for running the software. Part 1 - Hardware The Walkway The CatWalk XT walkway consists of a scratch-resistant hardened glass plate that is essential for the detection of the footprints and outline of an animal. Usually, a rodent walks from left to right, toward the goal box located on the right side while being constrained in its lateral movement by a corridor. It thus facilitates the recording of footprints and limits unwanted behaviors to elicit uniform runs. Since the paws are detected by the light they reflect, it is best to record in a low-light environment. However, a dim red indirect light source can be used to illuminate the environment. The dimensions of the walkway are 130 x 68 x 152 cm (51.2" x 26.8" x 59.8"). Illuminated Footprints Technology The Illuminated Footprints™ technology is based on total internal reflection. Green LED light is injected into the glass plate from the side and is completely internally reflected, except for those areas where the animal makes contact with the glass plate. At points of contact, typically the animal's paws, light escapes and is reflected toward the camera. The high-speed color camera (100 Hz) positioned underneath the glass plate captures the illuminated paws, and their position in space and time is determined by the CatWalk XT software. The Illuminated Footprints™ technology assures that the actual footprints of the rodent can be captured with a high-speed video camera while the rodent traverses the walkway. This ensures maximal spatial and temporal resolution and is why CatWalk XT is able to produce such high-quality data. The captured video is processed by the CatWalk XT software. Based on the timing, dimensions, position, dynamics, and intensity of each footfall, numerous parameters are calculated for qualitative and quantitative analysis of footfalls and gait. The Glass Plate The glass plate is made of clear, hardened, scratch-resistant safety glass with polished edges. This type of glass is less contaminated than standard glass to ensure evenly distributed lighting conditions along the length and width of the walkway. Each plate is hand-selected for clarity and the absence of blemishes or inclusions introduced during the manufacturing process. A replacement glass plate can be ordered from the Noldus website when necessary. Dimensions of the glass plate are 130 x 20 x 0.5 cm (51.2" x 7.9" x 0.2"). Spring-Operated Corridor The corridor consists of two matted black walls to limit and direct an animal's movement over the glass plate. The width of the corridor can be adjusted, making the system suitable for both mice and rats. The left edges are bent outwards so animals can be easily inserted. On top of the corridor walls, an extra diffusion plate is mounted to provide stability and prevent animals from peeking over the corridor. If necessary, the diffusion plate can be removed to allow, for instance, tethered animals to traverse the walkway. For cleaning purposes and to remove a rodent from the glass plate, the corridor can be effortlessly lifted with just two fingers due to the spring-operated lifting mechanism situated at the back of the corridor. Goal Box The goal box is located at the right end of the corridor. It consists of a platform with a hole in the middle. On this platform, a lightweight box can be positioned that covers the hole and has an opening at the side of the corridor to allow entry from the corridor. This box can easily be lifted with one hand for access to an animal inside. Once inside the box, the animal has the option to jump through the hole into its home cage located below. The goal box design accommodates the most commonly used rack-based cages, and various inserts are provided for a precise fit. Illuminated Ceiling The illuminated ceiling on top of the walkway creates a red background so that the contour of the animal can be visualized. This contour is used to determine the position of the illuminated paw relative to the body contour and assign its identity. Furthermore, it is used to detect the position of the animal so a trial can be started and stopped, or the speed of the animal can be determined. Power Supply The 24V power supply unit can be operated worldwide using mains voltage from 100 to 240V AC and 50 to 60 Hz. CatWalk XT Control Unit The CatWalk XT Control Unit takes power from the power supply and distributes it to the camera, green LED rail, and illuminated ceiling. The voltages to the green and red light rails can be controlled by the CatWalk software via a USB connection. Camera and Mount The high-speed color camera (100 fps) captures video of the animal traversing the CatWalk. The time limit for capturing a run is determined by numerous factors, such as image light noise level and computer memory. The camera is connected via a CAT-6 UTP cable to a network card inside the computer running the CatWalk XT software. To view a smaller or larger portion of the glass plate, the camera can be moved up or down on the slider. Having approximately 60 cm of the glass plate in view results in capturing approximately five to six strides of gait in rats. Decreasing the distance between the camera and the glass plate to approximately 35 cm in view allows you to acquire the same number of strides for a mouse while increasing image resolution and light sensitivity. Part 2 - Software Navigation Startup When you start the CatWalk XT software, a task dialogue will appear that guides you through the application. The dialogue allows you to easily navigate to relevant parts of the software that are often accessed when starting up CatWalk XT. Task Dialogue Further task dialogue windows will guide you through the application and offer functions depending on the position in the workflow. Menu Bar The menu bar located at the top of the user interface allows you to navigate anywhere in the application, independent of the task dialogues. Experiment Explorer The left pane of the user interface displays the experiment explorer, which contains the workflow from top to bottom. Double-clicking allows you to quickly jump to different positions in the workflow. It also shows the acquired trials and runs and their status, including selection by the data segmentation profile, classification, and whether a run is compliant with the run criteria. Quick Links The bottom of the user interface offers links to the previous and subsequent phases in the workflow. Setup Define and Calibrate the Walkway In this part of the software, the camera view needs to be cropped to omit all redundant parts in the video image. The image also needs to be calibrated to match real-world dimensions. Detection Settings The detection settings allow you to define the optimal intensity range for footprint detection and for filtering out background noise. The detection settings dialogue includes an auto-detection function that suggests optimal detection settings, from which you can fine-tune detections by adjusting the camera gain, intensity threshold, and green and red light intensity. Experiment Settings In the experiment settings, you can define experiment groups and time points, which can later be used as independent variables in data selection and analysis. Run criteria can also be defined to set thresholds for run duration and speed variation. These criteria become read-only for the entire experiment once the first run is acquired. Runs that comply with these criteria are labeled accordingly, while runs that do not comply are not discarded and can still be used for data segmentation. The minimum number of runs required to comply with these criteria can also be set in this dialogue. On average, three compliant runs per animal per time point are necessary when using five or six gait cycles per paw per run. When using fewer gait cycles per run due to time limitations or motivational issues, more than three compliant runs are advised to ensure enough repeated measures are taken. Trial List The trial list allows you to automatically build a list of trials to acquire for each time point and treatment group. A trial is a unique identifier that contains the treatment group, time points, animal ID, and several runs. A trial is finished when the number of compliant runs set in the run criteria is acquired. Acquisition Settings The acquisition settings dialogue allows you to set several standard operations regarding runs. For instance, you can determine after what duration runs should be automatically aborted. The default is set at 10 seconds. Acquisition Trial Selection Prior to acquisition, the trial that matches the animal being tested must be selected. Alternatively, a new trial can be created for the animal. In the experiment explorer, you can see how many runs have been performed in each trial and how many of them are labeled compliant. Run Acquisition Before starting a run, you need to refresh the background for optimal detection fidelity. After the animal is placed on the walkway, its image is captured automatically during the entire time it is in view, until it either leaves the camera's view or the maximum run duration is exceeded. Feedback is provided after each run regarding the run's compliance with the defined run criteria. Run Footprint Classification Manual Footprint Classification The software automatically identifies the parts of the animal that have made contact with the glass plate, which are typically the animal's footprints. The footprints can then be labeled manually through a click-and-select function. Once a footprint is manually labeled, the software automatically jumps to the next unlabeled print. Recognition of the footprints is facilitated by dragging the video slider back and forth or by zooming into the video image. The Automatic Footprint Classification Module With Automatic Footprint Classification™, the classification of each print is performed automatically by the built-in classification algorithm. Atypical prints are automatically highlighted for manual classification, and any labeling conflicts are automatically detected. These conflicts can be accessed via a dropdown menu. Once labeling is completed, both qualitative and quantitative data are automatically generated by the software. Adjusting the Intensity Threshold In the Adjust Intensity Threshold dialogue, you can change the intensity threshold set in the detection settings. This change applies only to the selected run, whereas the value set in the detection settings is applied to all runs yet to be acquired. Changing the intensity threshold may be necessary for individual runs when there is a large variation in background noise between runs, trials, or time points. Please revisit the detection settings when this is the case. Source: Technical specs - CW XT 10.7, Noldus Information Technology --- ## CatWalk XT 11 - Analyze Data - 2D Footprint Intensities URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-2d-footprint-intensities Chapter: CatWalk XT 2D Footprint Intensities Click on the 2D Footprint Intensities tab. The 2D Footprint Intensities tab plots the print intensities of each paw print in a single image. The solid red line represents the maximum intensity in a frame, the filled, colored area under the red line represents the mean intensity of the paw. The 2D Footprint Intensities plot displays the prints from left to right irrespective of the animal's actual walking direction. When you right-click the 2D Footprint Intensities plot, you can select one of two options: - Save to File. This saves the 2D Footprint Intensities plot to an image file (*.png). - Copy to Clipboard. This copies the 2D Footprint Intensities plot to the clipboard. Footfall Patterns Click the Footfall Patterns tab. The Footfall Patterns diagram shows the order in which the paws (represented by colored dots) were placed on the glass plate. The Footfall Patterns are displayed from left to right, irrespective of the animal's actual walking direction. The colors of the dots indicate the following: Orange - Not Taken into Account Orange dots indicate paw placements that are not taken into account when determining a footfall pattern. This often occurs to the first and last paw prints. In the example below, the first paw placement, LF, occurs again within a 4-paw sequence (see the fourth dot in the run). A pattern like LF-LH-RF-LF is clearly not a footfall pattern. Therefore, the LF paw placement is ignored and the software starts looking for patterns from the next paw placement. In this case, the next paw placement is LH, which is followed by RF-LF-RH. Together, they form a recognized footfall pattern, indicated with CA. Similarly, paw placements at the end of the run can be excluded. After the last valid pattern LH-RF-LF-RH has been found (see the last CA in the run), three paw placements are left: RF, LH and RH. They form an incomplete pattern, which is excluded from the results. Blue - Start of a Pattern Paws at the beginning of a recognized footfall pattern. It is always followed by three green dots. Green - Part of a Pattern Paws that are at the second, third and fourth place in a recognized footfall pattern. Purple - Not Part of a Pattern These paw placements are determined as not being part of a footfall pattern. They are usually in the middle of the run, between two valid patterns. In the following example, the paw LF is repeated within a sequence of 4 paw placements. The sequence LF-LH-RF-LF is not recognized as a valid pattern. So the paw placement LF is marked with a Not Part of a Pattern dot and the software resumes searching from the next paw placement, in this case LH, which is detected as the start of a CA pattern (LH-RF-LF-RH). How Footfall Patterns Are Labeled Consider a generic footfall pattern found in a run, like LH-RF-LF-RH. The starting paw placement LH is marked with a blue dot. If this pattern LH-RF-LF-RH is repeated immediately after the first one (LH-RF-LF-RH-LH-RF-LF-RH), additional patterns can be recognized: - Starting from the second placement, RF: RF-LF-RH-LH - Starting from the third placement, LF: LF-RH-LH-RF - Starting from the fourth placement, RH: RH-LH-RF-LF This "family" of patterns is marked with the label CA (Cruciate A). The grouping of patterns into "families" is also the reason why CatWalk XT reports only 6 patterns (CA, CB, AA, AB, RA, RB) out of a total of 24 possible combinations. This makes classification independent of which paw comes first at the beginning of a run. The predefined footfall pattern labels are (note that any of the paw prints within a sequence can be the starting point, marked with the blue dot): - Cruciate Patterns: - CA, for the paw sequence RF-LF-RH-LH - CB, for LF-RF-LH-RH - Alternate Patterns: - AA, for RF-RH-LF-LH - AB, for LF-RH-RF-LH - Rotate Patterns: - RA, for RF-LF-LH-RH - RB, for LF-RF-RH-LH When initial contact of two paws coincides in a frame, the paw with the largest surface area in that frame is considered to have been placed first. In the unlikely event that the surface areas of these paws are equal, the following order of placement is used: LF-LH-RF-RH. Paws that are currently visible in the Video window are marked with a dotted circle in the Footfall Patterns diagram. Export the Visualizations Right-click the Footfall Patterns diagram and choose one of the two options: - Save to File. This saves the Footfall Patterns diagram to an image file (*.png). - Copy to Clipboard. This copies the Footfall Patterns diagram to the clipboard. --- ## CatWalk XT 11 - Analyze Data - Analyze Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-analyze-data Chapter: CatWalk XT Analyze Data 7.1 Select the Data Using a Data Segmentation profile, you can select one part from each classified run that complies with three criteria (the minimum number of consecutive steps with a specific speed range and maximum allowed speed variation). This is useful, for example, if you have a run in which the animal briefly stopped at the beginning of a run but then continued to walk normally. You can automatically select only the 'good' part of the run for analysis and export with a Data Segmentation profile. Default Data Segmentation Profile The default Data Segmentation profile is labeled All Data. It cannot be deleted. Procedure - Do one of the following: - In the Profiles Explorer, right-click Data Segmentation Profiles and select Add New Profile. - Choose Profiles > Data Segmentation Profile > New. - Enter the name of the new profile and click OK. - In the Profile window, under Select Data, you can set the following: - Minimum number of consecutive steps per run – Only the part of the run with the minimum number of consecutive steps which complies with the next two parameters is selected. We advise you to use at least 10 consecutive steps. - Average speed should range from (in distance unit/second) – Only the part of the run within the set speed range is selected. The Average Speed is based on the Body Speed of selected steps in a run. The Body Speed for each step cycle is calculated by dividing the distance that the animal's body has traveled from one initial contact to the next by the time it took to travel that distance. The Average Speed is different from the Run Average Speed (shown in the Acquisition and Classification screens), which is the average speed of the animal's body during the whole recorded run. - Maximum allowed speed variation (in percent) – Only the steps in a run within the set maximum allowed speed variation are selected. Example: The Average Speed of a run is 22.0 cm/s. The speed of a step cycle of the left front paw in this run is 29.07 cm/sec. The variation then is: ([29.07 - 22.0] / 22.0) * 100% = 32.1%. - Exclude non-compliant runs – When you select this option, runs not compliant with the run criteria in the Experiment Settings are excluded from the data selection. - Exclude partially classified runs – When you select this option, runs which have not been completely classified are excluded from the data selection. Selected Data Overview Tab Shows the result of your data segmentation. The sheet on the left shows, per treatment group and time point, the number of Selected Animals / Runs / Steps, the Total number of Animals / Runs / Steps in the experiment, and the Percentage of selected Animals / Runs / Steps. You can choose whether you want to see the selected Animals, Runs, or Steps by selecting the corresponding option at the bottom. The chart on the right is a graphical representation of the selected data. You can choose whether you want time points or treatment groups displayed on the X-axis by selecting the corresponding option at the bottom. Complete Data Overview Tab In the matrix on the left, the average speed intervals (1 to 10 cm/sec, 1 to 20 cm/sec, 1 to 30 cm/sec, etc., with centimeters as distance unit) are displayed on rows. The speed variation is displayed in 10% intervals on columns. Each cell in the matrix shows the resulting number of steps for a specific combination of Average Speed and Maximum Variation in speed based on the Minimum number of consecutive steps you selected. In the Complete Data Overview, you can only change the Minimum number of consecutive steps per run. If you do this, you need to click the Calculate Complete Data Overview button at the bottom to re-calculate the number of selected steps. The 3D chart shows: - On the X-axis: the Average speed range intervals. - On the Y-axis: the Maximum allowed speed variation intervals. - On the Z-axis: the resulting number of steps per speed / speed variation interval. What Speed or Variation Should I Choose? - Minimum number of consecutive steps per run – We recommend selecting at least 10 consecutive steps. This generally corresponds to 1 step cycle for each paw (that is, each paw is placed twice on the glass plate). If you select a lower number, a paw might have been placed only once, which means that for this paw some parameters (for example, Swing or Stride Length) cannot be calculated. - Average speed should range from ... to ... ([Distance unit]/second) – In the Complete Data Overview tab, the 3D chart shows the number of steps in the different Average Speed intervals; this helps you in determining the Average Speed range for your data. Select the widest average speed range possible for your runs if the Average Speed is different for different treatment groups (for example, the experimental animals are on average slower than the control animals). Steps with a maximum speed higher than 120 cm/sec (or an equivalent speed in a different distance unit) are not displayed in the 3D chart. However, you can select a maximum average speed of up to 300 cm/sec. - Maximum allowed speed variation (percent) – By selecting a low or high speed variation, you allow respectively small and large differences in average speed for a run. Example: You have a run with an Average Speed of 25 cm/sec. You have set the Maximum allowed speed variation to 20 percent. The variation is calculated as follows: ([Step speed - Average Speed] / Average Speed) * 100 = speed variation (%). With these values, the step speed can range between 20 and 30 cm/sec. If you set the Maximum allowed speed variation to 60 percent, the step speed can range between 10 and 40 cm/sec. Check the Data After Segmentation While data segmentation is a powerful tool to remove outliers and generate more homogeneous samples which facilitate analysis, it is not free of risks. A subject under study may make a small jump that is typical of the studied phenotype and should remain in the data; however, data segmentation may remove a significant part of interesting data based on increased variation in speed or the number of consecutive regular steps. Always check the data resulting from data segmentation before running the analysis. 7.2 Select the Analysis Parameters You can select specific parameters with Parameter profiles. Only selected parameters from the Paw Statistics and Phase Lags are displayed in the Run Statistics and in the Group Statistics and Charts, and exported to an Excel file. The default Parameter profile is labeled All Parameters and cannot be edited or deleted. - To create a new Parameter profile, do one of the following: - In the Profiles Explorer, right-click Parameter Profiles and select Add New Profile. - Choose Profiles > Parameter Profile > New. - Type in the name of the Parameter profile and click OK. - In the Parameter profile window, you can select or de-select the following: - Paws – Select the paws for which you want to display or export the Paw Statistics Parameters. - Parameters – Select the Paw Statistics Parameters you want to display or export. - Phase Dispersions – Select the paw combinations (Diagonal, Girdle, Ipsilateral) for which you want to calculate Phase Dispersions. - Couplings – Select the paw combinations (Diagonal, Girdle, Ipsilateral) for which you want to calculate Couplings. - Click OK to make the new Parameter profile active. 7.3 Visualize the Runs Procedure: Open the Visualization Screen - In the Experiment Tasks window, select View Run Visualizations. - Choose Analyze > View Run Visualizations. - In the Experiment Explorer, right-click a trial and select View Run Visualizations (only available when the trial contains one or more partially classified runs), or right-click a run and select View Run Visualizations (only available when the run has been partially or fully classified). You can export the Visualizations. See Export the Run Visualizations for details. Visualize a Run - Under Trial & Run Selection, select a trial and one of the runs in that trial, or click the Previous/Next button to navigate between trials and runs. - Replay the run as described in Review the Runs During Classification. - Under Visualizations, you can view: - 3D Footprint Intensities - 2D Footprint Intensities - Footfall Patterns Paws which have not been selected in the currently active Data Segmentation profile are displayed in gray in the Video window and are not displayed in any of the Visualizations (3D/2D Footprint Intensities, Footfall Patterns). You can select another Data Segmentation profile by right-clicking it and selecting Set as Active. 3D Footprint Intensities Click on the 3D Footprint Intensities tab. The 3D Footprint Intensities tab plots the print intensities of the 4 paws for each individual video frame in which the paw has contact with the glass plate in a 3D chart. The intensities range from 0 to 255. The color range used in the 3D chart is the same as is used in the False Color mode of the footprints in the Classification print view. A 3D chart can be rotated in all directions: click a chart, keep the mouse button pressed, and drag to rotate the chart. To reset all charts to the original orientation, open another item in the experiment (for example the Trial List) and re-open the Visualization. --- ## CatWalk XT 11 - Analyze Data - Analyze Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-analyze-data-fxO Chapter: CatWalk XT Analyze Data Sub Print View The Sub Print View shows the individual prints of the Stand. The time between two subsequent prints is 1/100 s. Base of Support Base of Support is the average distance between either the front paws or the hind paws, measured along the y axis. Choose Analyze > View Run Statistics and under Statistics click Base of Support. In the Base of Support sheet the following variables/parameters are displayed: - Paw – The label of the paw. - N – The number of times each paw was placed. - Mean (in Distance Unit) – The mean value for the Y position for each paw. - SEM (%) – This is the Standard Error of the Mean, expressed as a percentage of the mean Base of Support. At the bottom: - Paws – Front paws or Hind paws. - N – The total number of times the paw combinations were placed. - Base of Support ([Distance Unit]) – The mean distance between either front paws or hind paws. The Base of Support is calculated as follows: - Base of Support Front paws = |YRF − YLF| - Base of Support Hind paws = |YRH − YLH| The Base of Support parameter is used in research on spinal cord injury. It has been found that as a result of trauma to the spinal cord (either as a result of a transection or contusion), the Base of Support of the front paws is unaffected, but that of the hind paws showed an increase (Hamers et al., 2001). Other Statistics In the Other Statistics sheet, the following parameters are displayed: Duration This is the duration of the run based on the selected steps in the data selection. The Duration is different from the Run Duration, which is the duration of the recorded run. Average Speed This is the average speed of the selected steps in the data selection. The Average Speed is expressed in Distance Units per second. Maximum Variation (%) This is the Maximum Variation in average speed of the selected steps in the data selection. Cadence The Cadence is expressed in steps per second: Cadence = (# steps − 1) / (Initial Contact last Stand − Initial Contact first Stand) The selected steps include the yellow, unaccounted steps in the Footfall Patterns diagram, but the steps that are not selected in the current Data Segmentation profile are not included. Number of Steps This is the total number of selected steps in this run. Steps that are not selected in the current Data Segmentation profile are not included. Sciatic Functional Index The Sciatic Functional Index (SFI) is a measure for the functional recovery of the sciatic nerve which innervates the hind paws. Therefore, the SFI is only relevant for hind paws. The SFI is calculated differently for rats and mice. The formula used for the calculation of the SFI for rats (Bain et al., 1989): SFI = −38.3 × ((PLE − PLN) / PLN) + 109.5 × ((TSE − TSN) / TSN) + 13.3 × ((ITSE − ITSN) / ITSN) − 8.8 where PL is Manual Print Length, TS is Toe Spread, ITS is Intermediate Toe Spread, and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. The formula used for the calculation of the SFI for mice (Inserra et al., 1998): SFI = 118.9 × ((TSE − TSN) / TSN) − 51.2 × ((PLE − PLN) / PLN) − 7.5 Note: Although ITS is not in the formula above, you need to measure the ITS in mice in order to have the SFI calculated. Posterior Tibial Functional Index The Tibial Functional Index (TFI) is a measure for the functional recovery of the tibial nerve, which is a branch of the sciatic nerve. The formula used for the calculation of the TFI for rats (Bain et al., 1989): TFI = −37.2 × ((PLE − PLN) / PLN) + 104.4 × ((TSE − TSN) / TSN) + 45.6 × ((ITSE − ITSN) / ITSN) − 8.8 where PL is Manual Print Length, TS is Toe Spread, ITS is Intermediate Toe Spread, and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. The formula used for the calculation of the TFI for mice (Inserra et al., 1998): TFI = −109.9 × ((PLE − PLN) / PLN) − 7.2 Peroneal Functional Index The Peroneal Functional Index (PFI) is a measure for the functional recovery of the peroneal nerve which innervates the hind paws. The formula used for the calculation of the PFI for rats (Bain et al., 1989): PFI = 174.9 × ((PLE − PLN) / PLN) + 80.3 × ((TSE − TSN) / TSN) − 13.4 where PL is Manual Print Length, TS is Toe Spread, and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. The formula used for the calculation of the PFI for mice (Inserra et al., 1998): PFI = 191.1 × ((TSE − TSN) / TSN) − 9.86 where TS is Toe Spread and the subscripts E and N indicate the Experimental and Normal contralateral hind paws, respectively. Print Print displays all non-paw prints (Right Hip, Right Knee, Left Hip, Left Knee, Nose, Abdomen, Tail, Genitalia). For each print the following is given: - Number of Contacts – With the glass plate. - Total Duration – Of contact with the glass plate. - % – Total Duration of contact with the glass plate expressed as a percentage of the total Duration (time between first selected print and last selected print of the run). Print Positions Print Positions is the distance between the position of the hind paw and the position of the previously placed front paw on the same side of the body (ipsilateral) and in the same Step Cycle. - A positive value of Print Positions indicates that the hind paw is placed behind the front paw. - A negative value of Print Positions indicates that the hind paw is placed in front of the front paw. The Print Positions sheet shows the distance (in the selected Distance Units) for the right and left front paws and their respective ipsilateral hind paws. Calculation of Print Positions is based on the X-coordinates of the centers of ipsilateral paws at Max Contact. - Walking direction from left to right: Print Positions = XFP(Max Contact) − XHP(Max Contact) - Walking direction from right to left: Print Positions = XHP(Max Contact) − XFP(Max Contact) where FP is one of the front paws and HP is one of the hind paws. The last front paw does not have a Step Cycle (and therefore no Print Position), but if the corresponding hind paw starts within the Stance of the front paw, this combination is also used for calculating the Print Position. In the Print Positions sheet, when you click one of the front paw rows: - The Print View highlights the ipsilateral paws. - The Timing View shows the Stand of both ipsilateral paws. Phase Dispersions The Phase Dispersions parameter describes the temporal relationship between placement of two paws within a Step Cycle. It is used as a measure of inter-paw coordination. Calculation Phase Dispersions is the moment of Initial Contact of a target paw expressed as a percentage of the Step Cycle time of an anchor paw. Phase Dispersions range from −50 to 75%. The formula for Phase Dispersions is: Phase Dispersions = ((ICtarget(m) − ICanchor(n)) / Step Cycle anchor) × 100% where IC is Initial Contact. A positive Phase Dispersions value indicates that initial contact of the target paw occurred after that of the anchor paw. A negative Phase Dispersions value indicates that the target paw preceded the anchor paw. Phase Dispersions can be computed for a total of 12 pairs. However, interchanging target and anchor does not have a large effect since their Phase Dispersions values are normally strongly correlated, so only 6 pairs of paws are displayed. Within diagonal pairs (RF-LH, LF-RH) and ipsilateral pairs (RF-RH, LF-LH), the anchor is always one of the front paws. Within girdle pairs (LF-RF, LH-RH), the anchor paw is always one of the left paws. Which paws/parameters are displayed in the Phase Dispersions sheet depends on the selection in the currently active Parameter profile (displayed in bold and blue in the Experiment Explorer). Statistics The following statistics are displayed in the Phase Dispersions sheet for the various paw combinations: - Value – This column shows the Phase Dispersions values. An empty cell indicates that Phase Dispersions could not be calculated. - Anchor Start (A-Start) – Initial Contact of the anchor paw. An empty cell indicates that Phase Dispersions could not be calculated. - Anchor Duration (A-Duration) – The duration of Step Cycle of the anchor paw. Stand for each paw is depicted by a black bar and Swing is shown as a white bar. Initial Contact is the point of transition from the white to black bar. A Step Cycle runs from Initial Contact to the next Initial Contact of that paw. Phase Dispersions is calculated by measuring the timing between Initial Contacts of a paw pair (RF–RH) and expressing it as a percentage of the Step Cycle time of the anchor paw (RF). For example, if Initial Contact of the RH (target paw) occurs 0.22 s after that of the anchor paw (RF) and the Step Cycle is 0.44 s, the resulting Phase Dispersions value is 50% (0.22/0.44 × 100). If the Phase Dispersions value exceeds 75% with the first anchor, the target is assigned to the next anchor (Kloos et al., 2005). --- ## CatWalk XT 11 - Analyze Data - Analyze Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-analyze-data-DHI Chapter: CatWalk XT Analyze Data Phase Dispersions Parameters - Target Start (T-Start) – Initial Contact of the target paw. - Peculiarities – Displays the abbreviations for a number of potential error conditions that can occur: - ANT – Anchor but no valid target. This is not considered an error with the placement of the first anchor paw, when the target has not been placed yet. - AMT – Anchor with multiple targets. This occurs when the target paw is placed more often than the anchor paw. - TNA – Target no anchor. This is not considered to be an error with the placement of the last target, when the anchor is not placed on the glass plate anymore. - Mismatches – This row displays the number of Peculiarities that occurred. - CStat Mean / AD / SD / R – Phase Dispersions and Couplings are more correctly described as a circular variable where a value of 0% (that is, the Target paw starting exactly at the same time as the Anchor paw) is equivalent to a value of 100% (that is, the Target paw starting at the end of the previous step cycle of the Anchor paw). In order to generate meaningful averages, special procedures are followed. The values derived in this way are labeled as CStat. - Mean is the circular mean, expressed as percentage. For Phase Dispersions, it ranges between -50% and +50%. For Couplings, it ranges between 0% and 100%. - AD is the Angular Deviation, expressed as percentage. AD is the same as the Standard Deviation in CatWalk 10.6 and earlier versions. - SD is the circular Standard Deviation, expressed as percentage. AD and SD are measures of spread and are calculated with similar formulas. - R is the length of the vector that represents the mean direction, that is, the mean percentage projected on a circle. It measures the degree of concentration of values around the mean, and is therefore a measure of directedness. R is dimensionless and ranges between 0 (no dominant direction) and 1 (full directedness). In the Phase Dispersions sheet, when you click a row with a target and an anchor pair, the Print View highlights both the target and the anchor paw, and the Timing View graphically displays the interval between Initial Contact of the anchor and target paw and the Anchor Duration. Notes on Phase Dispersions The values of Phase Dispersions are, by definition, limited in the range -50% to +75%. Values between 50% and 75% are equivalent to those between -50% and -25%. Therefore, if the average is greater than 50%, it is expressed as the complementary (negative) value. For example, if the points are around 52%, the CStat Mean reported by CatWalk is -48. If you are not familiar with circular statistics, take a look at the Excel sheet Calculate Circular Statistics of Phase Dispersions and Couplings.xlsx in the CatWalk XT documentation folder. Applications Kloos et al. (2005) use the Phase Dispersions parameter to study the effect of locomotor and sensory recovery from spinal cord injury (SCI) on inter-paw coordination in rats. In normal animals, for the diagonal paw pairs (RF-LH, LF-RH) the target paw typically moves synchronously with the anchor so the Initial Contacts occur simultaneously, resulting in a Phase Dispersions value of 0%. Girdle pairs (RF-LF, RH-LH) usually yield a Phase Dispersions value of 50% when walking at a moderate speed. Kloos et al. found that depending on the severity of SCI, recovery of inter-paw coordination followed different patterns. Couplings Couplings describe the temporal relationship between placement of two paws within a step cycle. It is used as a measure of inter-paw coordination. In the Couplings sheet, Couplings values are displayed for all 12 pairs of paws. Calculation Couplings are computed the same way as Phase Dispersions. However, in the case of Couplings a target can never precede an anchor. Therefore, the value of Couplings ranges between 0 and 100%. Assuming that the step cycle is constant, Phase Dispersions and Couplings are related to each other. For example, if the Phase Dispersion value of a single Anchor-Target pair A-B is -20% of the step cycle of A (B occurring earlier than A), for Couplings the value is +80% because the previous paw B is taken as an anchor. Statistics For a description of the statistics displayed in the Couplings sheet, see the Phase Dispersions section. The main difference between Couplings and Phase Dispersions is that the average of Couplings is always positive in the range 0%–100%, while the average of Phase Dispersions is in the range -50% to 50%. Notes on Couplings If you are not familiar with circular statistics, take a look at the Excel sheet Calculate Circular Statistics of Phase Dispersions and Couplings.xlsx in the CatWalk XT documentation folder. See also the Circular Distributions section. Support The Support sheet shows the following parameters: - Start Time – Displays the start time of the different sections. A section is a time segment in which the same paws make contact with the glass plate. A section starts every time a paw is placed on the glass plate or lifted from the glass plate. - Duration – Duration of a section. - Support Formula – This is the number of paws that are simultaneously on the glass plate in a section. The Support Formula starts at Initial Contact of the left hind paw after all paws have been placed on the glass plate once. A new Support Formula row is started with the next Step Cycle of left hind. - Footfall Formula – Contains information about which paws are touching the glass plate during each section. - Standing On % – This parameter displays the relative duration of simultaneous contact with the glass plate of all combinations of paws. The combinations are: zero paws, a single paw, diagonal pair of paws (RF-LH or LF-RH), lateral paws (RF-RH or LF-LH), girdle paws (RF-LF or RH-LH), three paws, and four paws. When you click a Support Formula, the Print View highlights all paws in the section that touch the glass plate, and the Timing View graphically displays the section interval. --- ## CatWalk XT 11 - Analyze Data - Genetic/Toxic Models URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-genetictoxic-models Chapter: CatWalk XT Genetic/Toxic Models Huntington's Disease Vandeputte, C., Taymans, J.-M., Casteels, C., Coun, F., Ni, Y., Van Laere, K., Baekelandt, V. 2010. Automated quantitative gait analysis in animal models of movement disorders. BMC Neuroscience 11: 92. doi: 10.1186/1471-2202-11-92. Parameters affected: Swing Speed, Stand. Refsum Disease - Ferdinandusse, S., Zomer, A.W.M., Komen, J.C., van den Brink, C.E., Thanos, M., Hamers, F.P.T., Wanders, R.J.A., van der Saag, P.T., Poll-The, B.T., Brites, P. 2008. Ataxia with loss of Purkinje cells in a mouse model for Refsum disease. PNAS 105: 17712–17717. doi: 10.1073/pnas.0806066105. Parameters affected: Print Area, Toe Spread of intermediate toes, Base of Support. Unsteady gait with strongly reduced paw print area for both fore- and hindpaws and reduced base of support for the hindpaws. - Lucas, E.K., Reid, C.S., McMeekin, L.J., Dougherty, S.E., Floyd, C.L., Cowell, R.M. 2014. Cerebellar transcriptional alterations with Purkinje cell dysfunction and loss in mice lacking PGC-1α. Frontiers in Cellular Neuroscience 8: 441. doi: 10.3389/fncel.2014.00441. Parameters affected: Print Area, Swing Speed, Stand Index, Regularity Index. Charcot-Marie-Tooth (CMT) Villalón, E., Dale, J.N., Jones, M., Shen, H., Garcia, M.L. 2015. Exacerbation of Charcot-Marie-Tooth type 2E neuropathy following traumatic nerve injury. Brain Research 1627: 143–153. doi: 10.1016/j.brainres.2015.09.024. Parameters Affected Print Length and Width, Max Contact Area, Max Intensity, Max Contact at (%), all decreased. Couplings involving the affected limb (LH) decreased or increased depending on the coupling combination. References - Dale, J.M., Villalon, E., Shannon, S.G., Barry, D.M., Markey, R.M., Garcia, V.B. and Garcia, M.L. 2012. Expressing hNF-LE397K results in abnormal gaiting in a transgenic model of CMT2E. Genes, Brain and Behavior 11: 360–365. doi:10.1111/j.1601-183X.2012.00771.x - Parameters affected: Stride Length, Regularity Index, Stand Index (all decreased). Couplings and Phase dispersions increased or decreased depending on which combination was considered. Leigh Disease - de Haas, R., Russel, F.G., & Smeitink, J.A. 2016. Gait analysis in a mouse model resembling Leigh disease. Behav Brain Res, 296: 191–198. Source: CatWalk XT 11.0 Reference Manual - Analyze Data, Noldus Information Technology --- ## CatWalk XT 11 - Analyze Data - Group Statistics and Charts URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-group-statistics-and-charts Chapter: CatWalk XT Group Statistics and Charts With Group Statistics, you can calculate the statistics of parameters, grouped per treatment group × time point combination, and view the corresponding charts. Procedure - Make sure you have selected the right Data Segmentation profile and Parameter profile. Data not selected in these profiles are not included in the results. - Choose Analyze > View Group Statistics and Charts. - Under Numerical Results, click a category tab to display the results. - Under Graphical Results, click a category to view the corresponding parameter charts. - To export group statistics and charts, see the Export section. Notes - If the tab for a parameter contains no results, it means that it is not selected in the currently active Parameter profile. To select another Parameter profile, in the Profiles Explorer, right-click a Parameter profile and select Set as Active. - If your experiment contains one or more runs with missing or corrupt data, you get an error message when you try to open the group statistics and charts. In the Experiment Explorer, delete the runs listed in the error message by right-clicking a run and selecting Delete. Statistics Available To calculate group statistics, CatWalk XT uses the values of trial statistics. For example, the experimental group Control includes 10 trials for 10 subjects recorded at time point Day 1. The group mean of Print Length for Control - Day 1 is calculated by averaging the 10 per-trial values of Print Length for that group. You can find the per-trial values in the Trial Statistics export file. The following statistics are available: - N – The number of trials in that treatment group × time point combination. - Mean (for all parameters except Phase Dispersions and Couplings) – The arithmetic mean of the parameter for that treatment group × time point combination. - CStat Mean (only for Phase Dispersions and Couplings) – The circular mean of phase lags (CStat) for that treatment group × time point combination. Note that values like -49% and +51% may look different in a column chart, but in the circular domain they are very similar. - CStat R (only for Phase Dispersions and Couplings) – The length of the vector representing the average phase lag for a treatment group × time point combination. - SEM (for all parameters except Phase Dispersions and Couplings) – The Standard Error of the Mean of the parameter. - CStat AD (only for Phase Dispersions and Couplings) – The angular deviation of the individual phase lags for a treatment group × time point combination. - CStat SD (only for Phase Dispersions and Couplings) – The circular standard deviation of the individual phase lags for a treatment group × time point combination. Chart Settings In the Group Statistics & Charts screen, under Graphical Results, open the Chart Settings window. The following settings are available: Chart Type - Bar Chart – Shows the mean value of the parameter as a colored bar and the standard error as an error bar. - Five Number Summary Chart – A box-whisker chart showing the sample minimum, lower quartile, median, upper quartile, and sample maximum. This chart can be made when at least 4 trials (N ≥ 4) are available for that data series. This chart type is not displayed for Phase Dispersions and Couplings. Horizontal Axis - Time Points – Displays the time points on the horizontal axis. - Treatment Groups – Displays the treatment groups on the horizontal axis. Data Series Data Series are displayed in the chart legend. You have the same options as under Horizontal Axis. If you change the option under Horizontal Axis, the option under Data Series changes automatically and vice versa. Title Font Size Select the size in pixels of the font for the chart title (range: 6–14). Bar Chart / Five Number Summary Chart - Chart Width – The width of the chart in pixels (including the legend). - Chart Height – The height of the chart in pixels (including the title). Bar Chart Settings - Bar width (%) — The percentage of the space available for that data series occupied by the bar. - Gap — The gap between bars (in pixels). - Whisker width (%) — The width of the whisker relative to the bar width. Circular Charts - Chart size — The width and the height of the chart in pixels, including the title and the legend. Range: 100–1000. - Include datapoints — Select this option if you want to have the per-trial values of variables displayed on the circle. Those data points are used to calculate the group average, which is represented by the vector. Note: Data points may overlap on the circle. In that case you see fewer dots than the actual number of trials in that group. However, the statistics are based on all trials in each group. - Split charts by — Select which criterion you want to produce different charts: - Treatment Groups. For example, two treatment groups results in two charts per variable, one for Control and one for Treated. The time points appear in the legend. - Time Points. For example, three time points (d1, d5, d10) results in three charts per variable. The treatment groups appear in the legend. - Time Points and Treatment Groups. This option creates as many charts as those created with the two options above, taken together. For example, with three time points and two treatment groups, for the variable Phase Dispersions RF->LH: the first three charts are based on the three time points and the legend shows the groups of subjects. The other two charts show the same data the other way round: one chart for each group of subjects, with the legend showing the three time points. If a chart is empty, it could be that a five number summary chart is selected, and for that parameter less than four trials are available. To solve this, in the Chart Settings window select Bar chart next to Chart type. To optimize the space needed for charts, reduce the font size for the title, and in the Experiment settings shorten the name of the categories under Treatment Groups and Time Points. That makes the legend smaller. --- ## CatWalk XT 11 - Analyze Data - Interpreting the Circular Charts URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-interpreting-the-circular-charts Chapter: CatWalk XT Interpreting the Circular Charts Circular charts represent the average (group) values of Phase Dispersions and Couplings. Vector Orientation The angle formed by the vector represents the average CStat Mean of an experimental group × time point combination, expressed in percentage and plotted on a polar coordinate system. Vector Length The length of the vector represents the value CStat R for an experimental group × time point combination. It ranges between 0 and 1 and reflects the degree of certainty of the average. The lower the dispersion of the single data points around the average, the longer the vector. Data Points If you selected Include datapoints in the Chart Settings, each dot represents one of the values of Phase Dispersion/Couplings that contribute to the mean. The value N in the table indicates the number of points. However, if one value occurs multiple times, the dots overlap. Circular Scale The scale of these charts reflects the different definition of the two parameters: -50% to +50% for Phase Dispersions, and 0% to 100% for Couplings. Note that for a specific pair Anchor–Target: - A value of -50% in a Phase Dispersion chart corresponds to a value of +50% in a Couplings chart. - A value of -25% in a Phase Dispersions chart corresponds to a value of +75% in a Couplings chart. However, in practice the average values of Phase Dispersions and Coupling do not always correspond precisely. This is because some values of Phase Dispersions are not calculated when they exceed the limits stated in their definition; for example when a target occurs at more than 75% of the anchor step cycle. However, those values are calculated as Couplings. You can check this in the Run Statistics by comparing the tabs Phase Dispersions and Couplings. The two averages, therefore, are not calculated using the same values. Application Examples This list of applications is not exhaustive. For more applications and publications, please search Google Scholar. CNS-Related Changes - Spinal cord injury - Neuropathic pain - Ischemia / stroke - Amyotrophic Lateral Sclerosis (ALS) - Parkinson's disease models - Cerebellar ataxia - Motor coordination (cerebellar cortex) PNS-Related Changes - Sciatic nerve injury Skeletal and/or Musculature Changes - Arthritis Genetic / Toxic - Huntington's disease - Refsum disease - Charcot-Marie-Tooth (CMT) - Leigh disease Spinal Cord Injury The following table summarizes results, parameters affected, and references for spinal cord injury research using CatWalk XT. - Depending on the severity of SCI, the gait becomes less stable and less coordinated. The animal tries to stabilize the body. Parameters affected: Base of Support, Intensity, Stand, Phase Dispersions depending on severity of SCI. (Hamers et al. 2006; Kloos et al. 2005) - After lateral funiculus injury, gait analysis showed recovery in animals treated with compound. Parameters affected: Stride Length, Regularity Index, Base of Support, Run Duration. (Cao et al. 2008) - Effect of locomotor training and/or magnetic stimulation on gait impairments after cervical spinal cord injury. Parameters affected: Phase Dispersions, Average Speed, Print Area, Stand Index. (Hou et al. 2014) - CatWalk XT analysis and especially its static parameters found highly useful in assessing spontaneous recovery of hindlimb function after severe thoracic spinal cord injury. Parameters affected: Max Intensity, Mean Intensity, Max Intensity at%, Max Contact Mean Intensity. (Zheng et al. 2023) References - Cao, Y., Shumsky, J.S., Sabol, M.A., Kushner, R.A., Strittmatter, S., Hamers, F.P.T., Lee, D.H.S., Rabacchi, S.A. & Murray, M. 2008. Nogo-66 receptor antagonist peptide (NEP1-40) administration promotes functional recovery and axonal growth after lateral funiculus injury in the adult rat. Neurorehabilitation and Neural Repair 22: 262–278. doi:10.1177/1545968307308550 - Hamers, F.P.T., Koopmans, G.C. & Joosten, E.A.J. 2006. CatWalk-assisted gait analysis in the assessment of spinal cord injury. Journal of Neurotrauma 23: 537–548. - Hou, J., Nelson, R., Nissim, N., Parmer, R., Thompson, F.J. & Bose, P. 2014. Effect of combined treadmill training and magnetic stimulation on spasticity and gait impairments following cervical spinal cord injury (C-SCI). Journal of Neurotrauma 31: 1088–1106. doi:10.1089/neu.2013.3096 - Kloos, A.D., Fisher, L.C., Detloff, M.R., Hassenzahl, D.L. & Basso, D.M. 2005. Stepwise motor and all-or-none sensory recovery is associated with nonlinear sparing after incremental spinal cord injury in rats. Experimental Neurology 191: 251–265. doi:10.1016/j.expneurol.2004.09.016 - Zheng, G., Zhang, H., Tail, M., Wang, H., Walter, J., Skutella, T., Unterberg, A., Zweckberger, K., Younsi, A. 2023. Assessment of hindlimb motor recovery after severe thoracic spinal cord injury in rats: Classification of CatWalk XT® gait analysis parameters. Neural Regen. Res. 18: 1084. Neuropathic Pain - Rats with a chronic constriction injury of the sciatic nerve, a model of neuropathic pain, minimize contact with the affected paw during locomotion. Parameters affected: Print Area, Intensity, Duty Cycle; Regularity Index unchanged. (Vrinten & Hamers 2003) - Drug treatment (riluzole) attenuates neuropathic pain and enhances functional recovery in a rat model of cervical spondylotic myelopathy. Parameters affected: Swing Duration, Swing Speed, Mean Intensity. (Moon et al. 2014) - All rat strains displayed similar SNI-specific postural changes with pronation of the affected paw. Parameters affected: Contact Area, Swing Duration, Duty Cycle, Run Speed. (Hestehave et al. 2020) References - Hestehave, S., Abelson, K.S.P., Brønnum Pedersen, T. et al. 2020. The influence of rat strain on the development of neuropathic pain and comorbid anxio-depressive behaviour after nerve injury. Scientific Reports 10: 20981. https://doi.org/10.1038/s41598-020-77640-8 - Moon, E.S., Karadimas, S.K., Yu, W.-R., Austin, J.W. & Fehlings, M.G. 2014. Riluzole attenuates neuropathic pain and enhances functional recovery in a rodent model of cervical spondylotic myelopathy. Neurobiology of Disease 62: 394–406. doi:10.1016/j.nbd.2013.10.020 - Vrinten, D.H. & Hamers, F.F. 2003. 'CatWalk' automated quantitative gait analysis as a novel method to assess mechanical allodynia in the rat; a comparison with von Frey testing. Pain 102: 203–209. --- ## CatWalk XT 11 - Analyze Data - Ischemia / Stroke URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-ischemia-stroke Chapter: CatWalk XT Ischemia / Stroke - Long-term functional deficit after middle cerebral artery occlusion. Parameters affected: Swing Speed, Intensity, Duty Cycle, Phase Dispersions. (Encarnacion et al. 2011) - After photothrombosis lesion, gait is affected in various ways. Parameters affected: Average Speed, Cadence, Stand and Swing Duration, Support, Maximum Contact Area, Max Intensity at Max Contact, Couplings. (Madinier et al. 2014) - Gait analysis reveals impairments in the limbs of both sides after right middle cerebral artery occlusion, and suggests involvement of the contralesional left hemisphere in recovery. Parameters affected: Regularity Index, Maximum Contact Area, Mean Intensity, Stride Length, Swing Speed. (Qin et al. 2014) References - Encarnacion, A., Horie, N., Keren-Gill, H., Bliss, T.M., Steinberg, G.K. & Shamloo, M. 2011. Long-term behavioral assessment of function in an experimental model for ischemic stroke. Journal of Neuroscience Methods 196: 247–257. doi:10.1016/j.jneumeth.2011.01.010 - Madinier, A., Quattromani, M.J., Sjölund, C., Ruscher, K. & Wieloch, T. 2014. Enriched housing enhances recovery of limb placement ability and reduces aggrecan-containing perineuronal nets in the rat somatosensory cortex after experimental stroke. PLoS ONE 9: e93121. doi:10.1371/journal.pone.0093121 - Qin, L., Jing, D., Parauda, S., Carmel, J., Ratan, R.R., Lee, F.S., Cho, S. 2014. An adaptive role for BDNF Val66Met polymorphism in motor recovery in chronic stroke. Journal of Neuroscience 34: 2493–2502. doi:10.1523/JNEUROSCI.4140-13.2014 Amyotrophic Lateral Sclerosis (ALS) Results Summary ResultParameters AffectedReferences Gait parameters describe decline in motor function in a transgenic mouse model of ALSStand, Stride Length, Duty Cycle, Support on diagonal limbs, Support on 3 limbsMead et al. 2011 Stem cell treatment improves motor functionStride Length (hindlimbs)Sun et al. 2014 Altered gait in mouse with ALS-related genen.a.Vergouts et al. 2015 References - Mead, R.J., Bennett, E.J., Kennerley, A.J., Sharp, P., Sunyach, C., Kasher, P., Berwick, J., Pettmann, B., Battaglia, G., Azzouz, M., Grierson, A., Shaw P.J. 2011. Optimised and rapid pre-clinical screening in the SOD1G93A transgenic mouse model of amyotrophic lateral sclerosis (ALS). PLoS ONE 6: e23244. doi: 10.1371/journal.pone.0023244 - Sun, H., Hou, Z., Yang, H., Meng, M., Li, P., Zou, Q., Yang, L., Chen, Y., Chai, H., Zhong, H., Zhuyun Yang, Z., Zhao, J., Lai, L., Jiang, X., Xiao Z. 2014. Multiple systemic transplantations of human amniotic mesenchymal stem cells exert therapeutic effects in an ALS mouse model. Cell Tissue Research 357: 571. doi: 10.1007/s00441-014-1903-z - Vergouts, M., Marinangeli, C., Ingelbrecht, C., Genard, G., Schakman, O., Sternotte, A., Calas, A.-G., Hermans, E. 2015. Early ALS-type gait abnormalities in AMP-dependent protein kinase-deficient mice suggest a role for this metabolic sensor in early stages of the disease. Metabolic Brain Disease 30: 1369. doi: 10.1007/s11011-015-9706-9 Cerebellar Ataxia Results Summary ResultParameters AffectedReferences Impaired gait in general as a result of neurological deficitsSwing Duration, Stand Duration, Regularity IndexCendelín et al. 2010 Motor abnormalities measured after suppression of the P/Q-type calcium channels in Purkinje neuronsPrint Area, Stand, Duty Cycle, Stride LengthSalvi et al. 2014 Static and dynamic parameters showed significant differences in three rat models of impaired coordination and ataxiaAverage Speed, Swing Speed, Stride Length, Phase DispersionsKyriakou et al. 2016 References - Cendelín, J., Voller, J., Vožeh, F. 2010. Ataxic gait analysis in a mouse model of the olivocerebellar degeneration. Behavioural Brain Research 210: 8–15. doi: 10.1016/j.bbr.2010.01.035 - Salvi, J., Bertaso, F., Mausset-Bonnefont, A.-L., Metz, A., Lemmers, C., Ango, F., Fagni, L., Lory, P., Mezghrani, A. 2014. RNAi silencing of P/Q-type calcium channels in Purkinje neurons of adult mouse leads to episodic ataxia type 2. Neurobiology of Disease 68: 47–56. doi: 10.1016/j.nbd.2014.04.005 - Kyriakou, E.I., van der Kieft, J.G., de Heer, R.C., Spink, A., Nguyen, H.P., Homberg, J.R., van der Harst, J.E. 2015. Automated quantitative analysis to assess motor function in different rat models of impaired coordination and ataxia. Journal of Neuroscience Methods 268: 171–181. doi: 10.1016/j.jneumeth.2015.12.001 Motor Coordination (Cerebellar Cortex) Results Summary ResultParameters AffectedReferences Reduced motor coordination in mice lacking chloride calcium-gated chloride channels in Purkinje cellsRun Speed, Stride Length, Duty Cycle, Swing Speed, Stand, Print Positions, Base of Support, Footfall Patterns, Support on three paws %, Support on diagonal paws, Phase Dispersion variabilityNeureither et al. 2017 Deterioration of motor performance correlates with the demise of Purkinje cell axons in the cerebellumStride Length, Stand Duration, Swing Duration, Print PositionsVerheijden et al. 2013 References - Neureither, F., Ziegler, K., Pitzer, C., Frings, S., Möhrlen, F. 2017. Impaired motor coordination and learning in mice lacking Anoctamin 2 calcium-gated chloride channels. Cerebellum (Online). doi: 10.1007/s12311-017-0867-4 - Verheijden, S., Bottelbergs, A., Krysko, O., Krysko, D.V., Beckers, L., De Munter, S., Van Veldhoven, P.P., Wyns, S., Kulik, W., Nave, K.-A., Ramer, M.S., Carmeliet, P., Kassmann, C.M., Baes, M. 2013. Peroxisomal multifunctional protein-2 deficiency causes neuroinflammation and degeneration of Purkinje cells independent of very long chain fatty acid accumulation. Neurobiology of Disease 58: 258–269. doi: 10.1016/j.nbd.2013.06.006 --- ## CatWalk XT 11 - Analyze Data - Parkinson's Disease Models URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-parkinsons-disease-models Chapter: CatWalk XT Parkinson's Disease Models Results Summary ResultParameters AffectedReferences Treatment improved motor functions as measured with CatWalk XTRun Average Speed, Regularity Index, Print Area, Swing Speed, Stride Length, Print PositionsTatenhorst et al. 2016 Treatment improves speed of locomotion but impairs forelimb movementRun Duration, Base of Support, Maximum Contact Area, Maximum Intensity, Swing Duration, Swing SpeedVlamings et al. 2016 Behavioral deficits efficiently measured in rat Parkinson modelsMean Intensity, Maximum Contact Area (forepaws)Vandeputte et al. 2010 Swaying pattern during locomotion was quantified in rodent modelsPaw statistics X position and Y positionTimotius et al. 2018 Detection of motor deficiencies in a Medial Forebrain Bundle 6-OHDA lesion model of Parkinson's diseaseStride Length, Print Position, Step Cycle, Swing phase of the step cycle, Stand index, Phase Dispersion, Print Length, Print AreaBoix et al. 2018 References - Boix, J., von Hieber, D., Connor, B. 2018. Gait analysis for early detection of motor symptoms in the 6-OHDA rat model of Parkinson's disease. Frontiers in Behavioral Neuroscience 12: 39. - Tatenhorst, L., Eckermann, K., Dambeck, V., Fonseca-Ornelas, L., Walle, H., Lopes da Fonseca, T., Koch, J.C., Becker, S., Tönges, L., Bähr, M., Outeiro, T.F., Zweckstetter, M., Lingor, P. 2016. Fasudil attenuates aggregation of α-synuclein in models of Parkinson's disease. Acta Neuropathologica Communications 4: 39. doi: 10.1186/s40478-016-0310-y - Timotius, I.K., Canneva, F., Minakaki, G., Pasluosta, C., Moceri, S., Casadei, N., Riess, O., Winkler, J., Klucken, J., von Hörsten, S., Eskofier, B. 2018. Dynamic footprint based locomotion sway assessment in α-synucleinopathic mice using Fast Fourier Transform and Low Pass Filter. Journal of Neuroscience Methods 296: 1–11. doi: 10.1016/j.jneumeth.2017.12.004 - Vandeputte, C., Taymans, J.-M., Casteels, C., Coun, F., Ni, Y., Van Laere, K., Baekelandt, V. 2010. Automated quantitative gait analysis in animal models of movement disorders. BMC Neuroscience 11: 92. doi: 10.1186/1471-2202-11-92 - Vlamings, R., Visser-Vandewalle, V., Koopmans, G., Joosten, E.A.J., Kozan, R., Kaplan, S., Steinbusch, H.W.M., Temel, Y. 2007. High frequency stimulation of the subthalamic nucleus improves speed of locomotion but impairs forelimb movement in Parkinsonian rats. Neuroscience 148: 815–823. doi: 10.1016/j.neuroscience.2007.06.043 Sciatic Nerve Injury Results Summary ResultParameters AffectedReferences CatWalk gait analysis suitable for the measurement of behavioural recovery after complete rat sciatic nerve injuryPaw Print Intensities, CouplingsBozkurt et al. 2008 A review of the most important gait kinematic measures that can be gathered with automated gait analysis systems—Costa et al. 2011 CatWalk gait analysis detects a large set of both dynamic and static gait changes after neurotmesis (complete nerve transection)Base of Support, Print Length, Print Width, Stride Length, Maximum Area, Mean Intensity, Stand Duration, Swing Duration, % of normal step sequence patterns, Phase Dispersion (girdles and ipsilateral left side)Deumens et al. 2007 References - Bozkurt, A., Deumens, R., Scheffel, J., O'Dey, D.M., Weis, J., Joosten, E.A., Führmann, T., Brook, G.A., Pallua, N. 2008. CatWalk gait analysis in assessment of functional recovery after sciatic nerve injury. Journal of Neuroscience Methods 173: 91–98. doi: 10.1016/j.jneumeth.2008.05.020 - Costa, L.M., Simões, M.J., Maurício, A.C., Varejão, A.S.P. 2009. Chapter 7: Methods and protocols in peripheral nerve regeneration experimental research: Part IV — Kinematic gait analysis to quantify peripheral nerve regeneration in the rat. International Review of Neurobiology 87: 127–139. doi: 10.1016/S0074-7742(09)87007-4 - Deumens, R., Jaken, R.J.P., Marcus, M.A.E., Joosten, E.A.J. 2007. The CatWalk gait analysis in assessment of both dynamic and static gait changes after adult rat sciatic nerve resection. Journal of Neuroscience Methods 164: 120–130. doi: 10.1016/j.jneumeth.2007.04.009 Arthritis Monoarthritis Möller, K.Ä., Berge, O.-G., Hamers, F.P.T. 2008. Using the CatWalk method to assess weight-bearing and pain behaviour in walking rats with ankle joint monoarthritis induced by carrageenan: Effects of morphine and rofecoxib. Journal of Neuroscience Methods 174: 1–9. doi: 10.1016/j.jneumeth.2008.06.017. Parameters affected: Print Area, Mean Intensity (as a measure of weight load), Duty Cycle, Regularity Index (all decreased in treated animals). Osteoarthritis - Ferreira-Gomes, J., Adaes, S., Castro-Lopes, J.M. 2008. Assessment of movement-evoked pain in osteoarthritis by the knee-bend and CatWalk tests: a clinically relevant study. The Journal of Pain 9: 945–954. Parameters affected: Total Intensity (calculated outside CatWalk). - Ishikawa, G., Nagakura, Y., Takeshita, N., Shimizu, Y. 2014. Efficacy of drugs with different mechanisms of action in relieving spontaneous pain at rest and during movement in a rat model of osteoarthritis. European Journal of Pharmacology 738: 111–117. doi: 10.1016/j.ejphar.2014.05.048. Parameters affected: Maximum Contact Area, Swing Speed. - Qin, J., Chow, S.K.-H., Guo, A., Wong, W.-N., Leung, K.-S., Cheung, W.-H. 2014. Low magnitude high frequency vibration accelerated cartilage degeneration but improved epiphyseal bone formation in anterior cruciate ligament transect induced osteoarthritis rat model. Osteoarthritis and Cartilage 22: 1061–1067. doi: 10.1016/j.joca.2014.05.004. Parameters affected: Duty Cycle, Regularity Index. --- ## CatWalk XT 11 - Analyze Data - Run Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-run-statistics Chapter: CatWalk XT Run Statistics Procedure - Do one of the following: - Choose Analyze > View Run Statistics. - In the Experiment Explorer, right-click a trial/run and select View Run Statistics. This option is only available when the trial contains one or more (partially) classified runs. - If you want to see the Run Statistics of another trial or run, under Trial & Run Selection, select a trial and a run, or click the Previous/Next button to navigate to that trial and run. - Under Statistics, click on one of the tabs to view the corresponding parameter sheet and their statistics. All tabs and their parameters are described below. Notes - All sheets contain calibrated values, displayed in the Distance Unit selected in the Preferences. - By right-clicking individual sheets you can either copy them to the clipboard or export them to Excel. - You can export statistics of separate runs (Run Statistics), grouped per trial (Trial Statistics) and grouped per experimental group (Group Statistics). - Paw prints displayed in gray are excluded from analysis based on the settings in the Data Segmentation profile currently active. To include all paw prints in the analysis, select the All Data Segmentation profile. Summary The Summary sheet shows a summary for the following parameter categories: - Paw Statistics – The mean and standard deviation (SD) are given for each paw, for the girdle paws (RF-LF and RH-LH) and for the ratio of the girdle paws (RF/LF, LF/RF, RH/LH and LH/RH). See the Paw Statistics sheet for more details. - Step Sequence – The total duration of all runs and the total number of categorized footfall patterns are given. For each footfall pattern category the percentage of the total number of categorized footfall patterns is given. Finally, the Regularity Index is shown, based on all categorized footfall patterns. See the Step Sequence sheet for more details. - Base of Support – These are the mean values for the front paws and the hind paws. See the Base of Support sheet for more details. - Print Positions – These are the mean values for the right paws and the left paws. See the Print Positions sheet for more details. - Support – These are the relative duration of contact with the glass plate of all paw combinations. See the Support sheet for more details. - Phase Dispersions – The Mean, AD (Angular Deviation), SD (Circular Standard Deviation) and R for all pairs are given, together with the number of Mismatches and occurrences of Anchor-No-Target (ANT), Anchor-Multiple-Targets (AMT) and Target-No-Anchor (TNA). Note that the results are circular statistics. See the Phase Dispersions sheet for details. - Couplings – The same statistics are given as for Phase Dispersions. See the Couplings sheet for more details. General The General sheet displays the following variables: - Name – The name of the run. - Start Time – The date and time the run was acquired. - Run Duration – The duration of the recorded run. - Run Average Speed – The average speed of the recorded run. This is the speed of the animal's body in the recorded run. - Run Maximum Variation – The maximum variation in walking speed in the recorded run. - Frame Rate – The frame rate of the camera. This is always 100 frames per second (fps). - Camera Gain – The value of the Camera Gain from the Detection Settings. - Green Intensity Threshold – The value of the Green Intensity Threshold from the Detection Settings. - X-Unit (mm/pixel) – The horizontal size of a single pixel. - Y-Unit (mm/pixel) – The vertical size of a single pixel. - Walkway Length – The length of the defined walkway. - Walkway Width – The width of the defined walkway. Paw Statistics The Paw Statistics sheet displays parameters that are based on individual paw prints. Choose Analyze > View Run Statistics and under Statistics click Paw Statistics. Which paws and parameters are displayed in this sheet depends on the selection in the currently active Parameter profile (displayed in blue and bold in the Experiment Explorer). In the Paw Statistics sheet, when you click one of the paw rows: - The Print View highlights the corresponding print. - The Timing View shows the corresponding Stand. - The Sub Prints View shows the individual prints of the Stand. Paw The Paw label based on the current classification. Initial Contact At (s) Initial Contact At (s) is the time in seconds since the start of the run at which a paw makes contact with the glass plate. Stand (s) / Stance (s) Stand (s) or Stance phase is the duration in seconds of contact of a paw with the glass plate. Kloos et al. (2005) (Exp. Neurol. 191: 251-265) showed that rats with a moderate spinal cord injury showed an increase in stand duration of the hind legs compared to pre-operative values. Stand Index Stand Index is a measure for the speed at which the paw loses contact with the glass plate. The formula for Stand Index is: Stand Index = (a / X0) × frame rate Where: - a is derived from y = ax + b, which describes a straight line fitted through the values of Print Area between the time of maximum contact and the 90th percentile of the stance duration. The value a should be interpreted as "change in print area per video frame." - X0 is the maximum contact area. - frame rate is the camera frame rate (usually 100 frames per second). This correction allows comparison of results obtained with different frame rates. Stand Index is therefore a function of the change in print area per second. It is always negative because it describes the decrease in print area over time. The more negative the value, the steeper the slope of the line that describes the reduction in print area, meaning that the subject lifts its paw more quickly. Notes - Stand Index should only be used for smoothly moving animals. - The formula of Stand Index includes a/X0 to correct for differences in Print Area between paws, subjects, etc. --- ## CatWalk XT 11 - Analyze Data - Stance Parameters URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-stance-parameters Chapter: CatWalk XT Stance Parameters Single Stance Single Stance is the duration (in seconds) of ground contact for a single hind paw (Coulthard et al., 2002, 2003). It is used for gait analysis in pain models. In CatWalk XT, Single Stance is the part in the step cycle of a hind paw where the contralateral hind paw does not touch the glass plate. Initial Dual Stance Dual Stance is the duration (in seconds) of ground contact for both hind paws simultaneously (Coulthard et al., 2002, 2003). Dual Stance is used for gait analysis in pain models. In CatWalk XT, a distinction is made between Initial Dual Stance and Terminal Dual Stance. Initial Dual Stance is the first time in a step cycle of a hind paw that the contralateral hind paw also makes contact with the glass plate. Terminal Dual Stance Terminal Dual Stance is the second time in a step cycle of a hind paw that the contralateral hind paw also makes contact with the glass plate. Note that the Terminal Dual Stance for a hind paw is the Initial Dual Stance for the successive step cycle of the contralateral paw. Single and Dual Stance values are only calculated if the contralateral hind paw has been placed on the glass plate before and after a step cycle of the other hind paw. Body Speed Parameters Body Speed The Body Speed of a step cycle of a specific paw is calculated by dividing the distance that the animal's body traveled from one initial contact of that paw to the next by the time to travel that distance. Body Speed Variation Body Speed Variation (%) is calculated by dividing the absolute difference between the Body Speed and the Average Speed of a run by the Average Speed. Step Sequence The Step Sequence sheet contains information on the order in which the four paws are placed. To view it, choose Analyze > View Run Statistics and under Statistics click Step Sequence. Step Sequence The Step Sequence lists the order in which the paws were placed on the glass plate. This order determines the footfall pattern that can be assigned. Codes Each Code corresponds to a particular paw: - 1 = Left Hind (LH) - 2 = Left Front (LF) - 3 = Right Hind (RH) - 4 = Right Front (RF) The Codes are used to create the Footfall Patterns diagram. Patterns This row contains the abbreviations of the assigned footfall patterns. The colors of the cells correspond to those in the Footfall Patterns diagram. Normal Patterns This is the number of Step Cycles that fall within one of the footfall pattern categories. Accounted Steps This is the number of steps that was taken into account to determine the footfall patterns. Regularity Index (%) The Regularity Index expresses the number of normal step sequence patterns relative to the total number of paw placements. The formula is: Regularity Index = (NSSP × 4 / PP) × 100% where NSSP is the number of normal step sequence patterns and PP is the total number of paw placements. The Regularity Index does not indicate whether the subject walks with the same pattern throughout. If the footfall pattern changes during a run (for example, from AA to AB), the Regularity Index is not affected. The Regularity Index (RI) is used in research on spinal cord injury. It is a fractional measure of inter-paw coordination. In healthy, fully coordinated animals its value is 100%. For example, one week after rats were subjected to a transection injury, the RI decreased from 100% (pre-treatment) to approximately 80%, and increased again to 90% after 4 weeks (Hamers et al., 2001). Additional Visualizations In the Step Sequence sheet, when you click a Code or a colored cell, the following occurs: - The Print View highlights the corresponding print. - The Timing View highlights the start and end time of the stand of that paw. To create footfall pattern diagrams, select Analyze > View Run Visualizations and under Visualizations click the Footfall Patterns tab. --- ## CatWalk XT 11 - Analyze Data - Stand Index Calculation Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-analyze-data-stand-index-calculation-notes Chapter: CatWalk XT Stand Index Calculation Notes - Stand Index is only calculated when Stand consists of at least 5 frames and there are at least 3 data points between t(Max area) and the 90th percentile. - Stand Index is not calculated when two stances were combined and the Max Contact area was in the first stance. - If the 90th percentile of the time interval does not correspond to a video frame, the software interpolates the Print area between the two video frames that include that time. Paw Contact Parameters Max Contact At (s) Max Contact At (s) is the time in seconds since the start of the run that a paw makes maximum contact with the glass plate. It can be regarded as the point at which the braking phase turns into the propulsion phase during Stand. Max Contact At (%) Max Contact At (%) is Max Contact At (s) relative to Stand of a paw. The formula is: Max Contact At (%) = ((Max Contact At (s) − Initial Contact) / Stand) × 100 Max Contact At (%) is used in research on spinal cord injury. For example, Hamers et al. (2001) found an increase in Max Contact At (%) for both front and hind paws in rats. This increase was more marked following a contusion injury compared to a transection injury. Max Contact Area Max Contact Area is the maximum area of a paw that comes into contact with the glass plate. In other words, it is the Print Area at Max Contact At (s). Max Contact Max Intensity This is the maximum intensity at the time of maximum contact of a paw. Intensity ranges from 0 to 255. The intensity of a print depends on the degree of contact between a paw and the glass plate and increases with increasing weight. Therefore, Intensity is a measure of weight put on the glass plate. The parameter is extracted from the print at maximum contact by finding the pixels of highest intensity. The Intensity parameter is used to assess the effects of neuropathic pain, including mechanical allodynia (Vrinten and Hamers, 2003). Vrinten and Hamers found that after a chronic constriction injury, which causes neuropathic pain, Intensity was reduced two weeks after surgery and gradually returned to pre-operative values. This change in Intensity showed a high degree of correlation with Von Frey thresholds. Max Contact Mean Intensity This is the mean Intensity of a paw print at Max Contact. Intensity ranges from 0 to 255. See also Max Contact Max Intensity. X Position X is the position of the center of the paw print at Max Contact in the horizontal (walking) direction. X is the distance in the Distance Unit from the left side of the walkway to the center of the print. Y Position Y is the position of the center of the paw print at Max Contact in the vertical direction. Y is the distance in the Distance Unit from the top of the walkway to the center of the print. Print Dimensions Print Length Print Length is the length (horizontal direction) of the complete print. It is displayed in the Distance Unit selected in the Preferences. The complete print is the sum of all contacts with the glass plate, as if the animal's paw would have been inked. Print Width Print Width is the width (vertical direction) of the complete paw print. It is displayed in the Distance Unit selected in the Preferences. Print Area Print Area is the surface area of the complete print. The print area is by definition at least as large as the Max Contact Area. It is displayed in the Distance Unit squared, where Distance Unit can be selected in the Preferences. Intensity Parameters Max Intensity At (s) Max Intensity At (s) is the time in seconds since the start of the run that the maximum Intensity is measured. Max Intensity At (%) Max Intensity At (%) is the same as Max Intensity At (s), expressed as a percentage of the duration of the Stance phase (Stand). The formula is: Max Intensity At (%) = ((Max Intensity At (s) − Initial Contact) / Stand) × 100% Max Intensity Max Intensity is the maximum intensity of the complete paw print, which is obtained by summing up the pixels of all the paw prints detected in the stance phase. Min Intensity Min Intensity is the minimum intensity of the complete paw print. Mean Intensity Mean Intensity is the mean intensity of the complete paw print. Mean Intensity of the 15 Most Intense Pixels This is the mean Intensity of the 15 pixels of a paw with the highest intensity. Swing and Stride Parameters Swing (s) Swing (s), or Swing Phase, is the duration in seconds of no contact of a paw with the glass plate. Swing Speed Swing Speed is the speed (Distance Unit/second) of the paw during Swing. The formula is: Swing Speed = Stride Length / Swing Stride Length Stride Length is the distance (in Distance Units) between successive placements of the same paw. It is obtained by calculating the beeline distance between the center of the paw print of two consecutive placements of the same paw during Max Contact. It is not the difference in the X-coordinates of the two paw print centers. Step Cycle (s) Step Cycle is the time in seconds between two consecutive Initial Contacts of the same paw: Step Cycle = Stand + Swing Duty Cycle (%) Duty Cycle (%) expresses Stand as a percentage of Step Cycle: Duty Cycle = (Stand / (Stand + Swing)) × 100% Toe and Paw Measurements For more information on Toe Spread, Intermediate Toe Spread, Manual Print Length, and Paw Angle, refer to the Manual Measurements section. Toe Spread Toe Spread is the distance (in Distance Units) between the center of the first and fifth toe of a hind paw. Intermediate Toe Spread Intermediate Toe Spread is the distance (in Distance Units) between the center of the second and fourth toe of a hind paw. Manual Print Length Manual Print Length is the distance (in Distance Units) between the center of the third toe and the heel of a paw. Paw Angle Body Axis Paw Angle Body Axis is the smallest angle (in degrees) between the Manual Print Length line and the line representing the orientation of the body axis. Paw Angle Movement Vector Paw Angle Movement Vector is the smallest angle (in degrees) between the Manual Print Length line and the line representing the direction of movement of the animal's body. --- ## CatWalk XT 11 - Appendices - Acknowledgments and Copyright Notices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-acknowledgments-and-copyright-notices Chapter: CatWalk XT Acknowledgments and Copyright Notices CatWalk™ is a trademark of Noldus Information Technology BV. CatWalk XT would not be what it is without the use of third-party software. This page lists software libraries and other software products used in CatWalk XT and where you can find license and compliance information and/or acknowledgments for that product. Boost Open source (Boost community) software library, C++ templates. - License: Boost Software License - Link: http://www.boost.org/users/license.html FFmpeg Cross-platform solution to record, convert and stream audio and video. - Link: https://ffmpeg.org - Noldus IT does not own FFmpeg or any component thereof. - License: GNU Lesser General Public License (LGPL) version 2.1 - License details: https://ffmpeg.org/legal.html HASP Library for software protection. - License: EULA - Link: https://supportportal.gemalto.com/ - Vendor: Thales Group OpenCV 4.7.0 Software library for various computer vision problems. - Link: http://www.intel.com/content/www/us/en/research/intel-research.html - License: Apache License 2.0 - License details: https://github.com/opencv/opencv/blob/master/LICENSE OpenCvSharp OpenCV wrapper for .NET. - Link: https://github.com/shimat/opencvsharp - License: Apache License 2.0 - License details: https://github.com/shimat/opencvsharp/blob/master/LICENSE Wix Toolset Tools to author software installers. - Link: http://wixtoolset.org/ - Foundation: .NET Foundation - License: Microsoft Reciprocal License (MS-RL) - License details: https://opensource.org/license/ms-rl-html/ Source: CatWalk XT 11.0 Reference Manual - Appendices, Noldus Information Technology --- ## CatWalk XT 11 - Appendices - Appendices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-appendices Chapter: CatWalk XT Appendices Contents - A – Install the Ethernet Card for the Camera - B – Troubleshooting - C – Gait Formulas: Describes the Support Formula and Footfall Formula. - D – Circular Distributions: Describes the computation of descriptive statistics for circular distributions of data such as phase lags during locomotion. - E – Protocol for Training and Testing Using the Noldus Goal Box - F – References - G – History of CatWalk: Written by Dr. Frank Hamers. - H – Declaration of Conformity - I – End-User License Agreement - J – Acknowledgments and Copyright Notices A – Install the Ethernet Card for the Camera Prerequisites You need a 10-Gb (gigabit) Ethernet network interface card (desktop computers only). Contact your Noldus representative if you need to purchase such a card or you are not sure whether your card is compatible. Procedure Follow the instructions in this section when you install CatWalk XT on a new computer and you want to acquire data with that computer. - Install the Ethernet network interface card in your CatWalk XT computer (see below). - Install the Ethernet network interface card driver software. Notes: - If you purchased the computer from Noldus, the steps above are already done. You can skip this section. - In all other cases, you must first install the Ethernet card, then the CatWalk XT software. - The Ethernet card is necessary when you acquire runs — that is, when the software records the video through the Ethernet connection. You do not need to install the Ethernet card if you use CatWalk XT to classify and analyze runs previously acquired on a different computer. Install the Ethernet Card Tip: Watch the video of the installation of the Ethernet card. On the CatWalk XT installation disc, open the folder ...\Videos\Installation Instructions\ and double-click installation_instructions_catwalk_xt.exe. - Turn off your computer and all connected peripherals, such as the monitor and printer. - Unplug the computer and its peripherals. - Remove the PC's case according to the instructions provided in its user manual. When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Select a free PCIe expansion slot and remove the corresponding extension cover, making sure that the screw is put aside safely. - Unpack the Ethernet card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. - Fix the card to the chassis using the screw retained earlier and re-fit the computer's cover. PCIe card slots are marked on the motherboard, for example SLOT3-PCIe2x1. If possible, choose the PCIe slot with the highest performance. This is estimated by the version number (for example, PCIe2x1 is version 2); the higher the version number, the higher the performance. Install the Ethernet Card Driver The driver for the Ethernet card is installed automatically when you install the CatWalk XT software. Notes: - You can download the setup file from my.noldus.com. - Important: After turning on the CatWalk system and the CatWalk computer, it can take a couple of minutes for the camera to be detected (indicated by the Acquiring Network icon in the task bar). Please do not start CatWalk before the camera has been detected. --- ## CatWalk XT 11 - Appendices - Appendices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-appendices-IAg Chapter: CatWalk XT Appendices A - Install the Ethernet Card for the Camera Prerequisites You need a 10-Gb (gigabit) Ethernet network interface card (desktop computers only). Contact your Noldus representative if you need to purchase such a card or you are not sure whether your card is compatible. Procedure Follow the instructions in this section when you install CatWalk XT on a new computer, and you want to acquire data with that computer. - Install the Ethernet network interface card in your CatWalk XT computer. - Install the Ethernet network interface card driver software. Notes: - If you purchased the computer from Noldus, the steps above are already done. You can skip this section. - In all other cases, you must first install the Ethernet card, then the CatWalk XT software. - The Ethernet card is necessary when you acquire runs — that is, when the software records the video through the Ethernet connection. You do not need to install the Ethernet card if you use CatWalk XT to classify and analyze runs previously acquired on a different computer. Install the Ethernet Card Tip: Watch the video of the installation of the Ethernet card. On the CatWalk XT installation disc, open the folder ...\Videos\Installation Instructions\ and double-click installation_instructions_catwalk_xt.exe. - Turn off your computer and all connected peripherals, such as the monitor and printer. - Unplug the computer and its peripherals. - Remove the PC's case according to the instructions provided in its user manual. When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Select a free PCIe expansion slot and remove the corresponding extension cover, making sure that the screw is put aside safely. - Unpack the Ethernet card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. - Fix the card to the chassis using the screw retained earlier and re-fit the computer's cover. PCIe card slots are marked on the motherboard, for example SLOT3-PCIe2x1. If possible, choose the PCIe slot with the highest performance. This is estimated by the version number (for example, PCIe2x1 is version 2); the higher the version number, the higher the performance. Install the Ethernet Card Driver The driver for the Ethernet card is installed automatically when you install the CatWalk XT software. Notes: - You can download the setup file from my.noldus.com. - Important: After turning on the CatWalk system and the CatWalk computer, it can take a couple of minutes for the camera to be detected (indicated by the Acquiring Network icon in the task bar). Please do not start CatWalk before the camera has been detected. --- ## CatWalk XT 11 - Appendices - B - Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-b-troubleshooting-zDg Chapter: CatWalk XT B - Troubleshooting See the following main topics: - General issues - Paw prints - Data analysis and export General Issues CatWalk XT Crashes Please send our Support department the log file which contains all the information needed for us to find the cause of the crash. The log file is located in the following folder: C:\ProgramData\Noldus\CatWalk\XT 10.7\Log\CatWalk XT.log CatWalk XT Does Not Start Anymore If you start CatWalk XT for the first time on a computer with multiple user accounts as the administrator, other standard users are not able to use CatWalk XT anymore. This is because the configuration files, which are created the first time you start CatWalk XT, can in this case only be accessed by the administrator and not by other users. To solve this, the administrator should delete all files and folders from C:\ProgramData\Noldus\CatWalk\XT 10.7. After this, only standard users should start CatWalk XT. An Error Message Appears During Conversion of an Old Experiment When opening experiments saved in older CatWalk XT versions, you may get a message like "An error occurred during the conversion of experiment [experiment name]". Do the following: - Click OK and Cancel and close CatWalk XT. - In Windows Explorer, go to the CatWalk Experiments folder and delete the complete [experiment name] folder which contains the experiment you wanted to convert. Do not try to open the *.cwe file from the [experiment name] folder. - In CatWalk XT, restore the backup file that was created when you opened the experiment. Possible causes for a conversion error are: - The disk to which you try to save the experiment is full. - You do not have write permission for the CatWalk Experiment folder. - There is an error in the experiment or experiment folder. In this case, send the backup file to our Support department. An Error Message Appears When Opening a Run If you get a message "An error occurred while loading the data of run Run#", it means the run is corrupt. We advise you to delete this run. To delete a run, do one of the following: - In the Experiment Explorer, right-click a run and select Delete. - Open the Acquisition screen, select the corresponding trial and select Live Video in the View list. Click one or more runs in the Acquired Runs list and click the Delete Run(s) button. The Camera Is Not Detected If the camera is not detected by CatWalk XT, wait some time. After starting up the computer and CatWalk XT, it sometimes takes about a minute before the Ethernet card detects the camera, indicated by the 'Connecting to Network' icon in the Windows task bar. If you do not see the live camera image, it is likely that the driver is not installed or not installed properly. See the Install the Ethernet Card Driver section above. CatWalk LED Lights Not Bright This may happen when you turn on the CatWalk Control Unit and the walkway switch is still turned off. Turn off the Control Unit by unplugging the power plug, set the walkway switch to ON, and turn on the Control Unit again. Camera Gain Reached Minimum Value In the Detection Settings, you might get the message that the Camera Gain reached its minimum value of 6 during auto-detection. This can occur when you use a heavy animal (for example, greater than 300 g) for auto-detection. In this case, increase the intensity of the Green Walkway Light by 0.25 and run the auto-detection again. Repeat these steps until the Camera Gain reaches a value higher than 10. A Run Does Not Stop After the Animal Leaves the Walkway The background image may no longer be valid. Always grab a new background image after cleaning the walkway or moving the corridor walls. Paw Prints The Paw Prints Are Shown in Gray When paw prints are shown in gray, it means that they are not selected in the currently active Data Segmentation profile. This also means that those prints are excluded from analysis. To include those prints, use the default Data Segmentation profile All Data, or modify the one currently selected. See Select the Data for details. There Are No Rectangles Around the Paw Prints This can happen when, due to a high Camera Gain value or high light intensity in the room where CatWalk is set up, the abdomen or even the complete ventral side of the animal is detected as a paw print (that is, it lights up in green in the video window in CatWalk). When this is the case and the option Discard Incomplete Prints at the Start and End of a Run is selected in the Acquisition Settings, the following happens: as soon as the animal enters the camera view, the ventral side of the body overlaps with the border of the camera image, and because of the selected option, the whole body (that is, all the prints) is discarded. To prevent this from happening, deselect the option Discard Incomplete Prints at the Start and End of a Run. The Mark UN Does Not Appear During Classification Choose Setup > Classification Settings. In the window that opens, deselect both options. --- ## CatWalk XT 11 - Appendices - B – Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-b-troubleshooting Chapter: CatWalk XT B – Troubleshooting See the following main topics: - General Issues (below) - Paw Prints - Data Analysis and Export General Issues CatWalk XT Crashes Please send our Support department the log file which contains all the information needed for us to find the cause of the crash. The log file is located in the following folder: C:\ProgramData\Noldus\CatWalk\XT 10.7\Log\CatWalk XT.log CatWalk XT Does Not Start Anymore If you start CatWalk XT for the first time on a computer with multiple user accounts as the administrator, other standard users are not able to use CatWalk XT anymore. This is because the configuration files, which are created the first time you start CatWalk XT, can in this case only be accessed by the administrator and not by other users. To solve this, the administrator should delete all files and folders from C:\ProgramData\Noldus\CatWalk\XT 10.7. After this, only standard users should start CatWalk XT. An Error Message Appears During Conversion of an Old Experiment When opening experiments saved in older CatWalk XT versions, you may get a message such as "An error occurred during the conversion of experiment [experiment name]." Do the following: - Click OK and Cancel and close CatWalk XT. - In Windows Explorer, go to the CatWalk Experiments folder and delete the complete [experiment name] folder which contains the experiment you wanted to convert. Do not try to open the *.cwe file from the [experiment name] folder. - In CatWalk XT, restore the backup file that was created when you opened the experiment. Possible causes for a conversion error are: - The disk to which you try to save the experiment is full. - You do not have write permission for the CatWalk Experiment folder. - There is an error in the experiment or experiment folder. In this case, send the backup file to our Support department. An Error Message Appears When Opening a Run If you get a message "An error occurred while loading the data of run Run#", it means the run is corrupt. We advise you to delete this run. To delete a run, do one of the following: - In the Experiment Explorer, right-click a run and select Delete. - Open the Acquisition screen, select the corresponding trial, and select Live Video in the View list. Click one or more runs in the Acquired Runs list and click the Delete Run(s) button. The Camera Is Not Detected If the camera is not detected by CatWalk XT, wait some time. After starting up the computer and CatWalk XT, it sometimes takes about a minute before the Ethernet card detects the camera, indicated by the 'Connecting to Network' icon in the Windows task bar. If you do not see the live camera image, it is likely that the driver is not installed or not installed properly. See the Install the Ethernet Card Driver section above. CatWalk LED Lights Not Bright This may happen when you turn on the CatWalk Control Unit and the walkway switch is still turned off. Turn off the Control Unit by unplugging the power plug, set the walkway switch to ON, and turn on the Control Unit again. Camera Gain Reached Minimum Value In the Detection Settings, you might get the message that the Camera Gain reached its minimum value of 6 during auto-detection. This can occur when you use a heavy animal (for example, greater than 300 g) for auto-detection. In this case, increase the intensity of the Green Walkway Light by 0.25 and run the auto-detection again. Repeat these steps until the Camera Gain reaches a value higher than 10. A Run Does Not Stop After the Animal Leaves the Walkway The background image may no longer be valid. Always grab a new background image after cleaning the walkway or moving the corridor walls. Paw Prints The Paw Prints Are Shown in Gray When paw prints are shown in gray, it means that they are not selected in the currently active Data Segmentation profile. This also means that those prints are excluded from analysis. To include those prints, use the default Data Segmentation profile All Data, or modify the one currently selected. See Select the Data. There Are No Rectangles Around the Paw Prints This can happen when, due to a high Camera Gain value or high light intensity in the room where CatWalk is set up, the abdomen or even the complete ventral side of the animal is detected as a paw print (that is, it lights up in green in the video window in CatWalk). When this is the case and the option Discard Incomplete Prints at the Start and End of a Run is selected in the Acquisition Settings, the following happens: as soon as the animal enters the camera view, the ventral side of the body overlaps with the border of the camera image, and because of the selected option, the whole body (that is, all the prints) is discarded. To prevent this from happening, deselect the option Discard Incomplete Prints at the Start and End of a Run. The Mark UN Does Not Appear During Classification Choose Setup > Classification Settings. In the window that opens, deselect both options. --- ## CatWalk XT 11 - Appendices - Circular Distributions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-circular-distributions Chapter: CatWalk XT Circular Distributions Vector Length and Mean Direction Imagine adding a few more dots between two existing ones on a circle. The more dots you add, the more the average coordinates X,Y will get closer to the circle. This means that the vector length R will increase. The greater R, the better the direction of the vector is defined, because the data points agree with each other. However, if you place points at other locations far from each other, the length of the vector is reduced and R is low. Consequently, the value of the mean is a poor measure for the average Phase Dispersion because it represents a group of very different locations on the percentages circle. In other words, R helps you quantify the credibility of the average. When contrasting Phase Dispersions between two experimental groups, you may find a significant difference in R, not in CStat Mean. This means that the two groups do not differ in the average timing of one paw (target, T) relative to the other (anchor, A). However, the higher value of R in one of the two groups indicates lower between-subject variability in the temporal position of T relative to A than in the other group. Subjects in the group with higher R walk more uniformly than those in the group with a low R, although the average position of T relative to A is not different between the two groups. Measures of Spread Around the Mean Angular Deviation The vector length R is used to compute the Angular Deviation (CStat AD in CatWalk XT). The Angular Deviation ranges from a minimum of 0 when R = 1, to a maximum of 22.508 (100/2π) when R = 0. Note: The Angular Deviation CStat AD is the same as the CStat Standard Deviation in CatWalk XT 10.6 and earlier versions. Make sure this does not generate confusion when examining old experiments. Circular Standard Deviation An alternative measure, the Circular Standard Deviation (CStat SD in CatWalk XT), ranges from 0 to infinity and is defined by formulas E.8 and E.9. The Circular Standard Deviation s0 more closely resembles the standard deviation on a linear scale. However, it is reasonable to assume that circular data have a limited spread; in that case Angular Deviation may be a better option. Note: The Circular Standard Deviation CStat SD is not the same as the CStat Standard Deviation in CatWalk XT 10.6 and earlier versions. Make sure this does not generate confusion when examining old experiments. Note that Angular Deviation and Circular Standard Deviation tend to converge as the data cluster around the mean. The Circular Group Mean When calculating group statistics (Analyze > View Group Statistics and Charts), the group mean CStat Mean is calculated with the same formulas as for the mean of single values of Phase Dispersions and Couplings. Example: A group includes three trials. The per-trial averages of Couplings are 5%, 95%, and 100%. The circular mean provided by CatWalk XT is 0% (which is the same as 100%). Using the arithmetic mean would result in a value (66.67%) far from the original ones. The Excel Sheet "Calculate Circular Statistics" If you are not familiar with circular statistics, you can practice with the Excel sheet Calculate Circular Statistics for Phase Dispersions and Couplings.xlsx, which you can find in the same folder as this manual: C:\Program Files\Noldus\CatWalk XT 10\Documentation - Open the Excel file. - Enter the values of Phase Dispersions or Couplings, for example those displayed in CatWalk XT for a specific run. - Explore the formulas that lead to the main results: CStat Mean (%), CStat Angular Deviation (%), and CStat Standard Deviation (%). - Enter one or more values in the Values (%) column to see the effect on the statistics and on the orientation of the vector in the chart shown on the right. Notes: - If CStat Mean is negative and you prefer positive values, locate the Complementary Mean (%). Do this especially when entering values of Couplings. For example, if the CStat Mean (%) is -25%, the complementary mean valid in the range for Couplings (0–100%) is 75%. - The formulas for calculating circular statistics are protected and cannot be changed. - There may be small differences between the statistics given by CatWalk XT and those in the Excel sheet. In general they do not exceed 0.01% and are the effect of rounding of cell values. You can increase the number of decimals in CatWalk XT (File > Preferences > Number of Decimals) to better locate those differences. Confidence Limits for the Population Mean CatWalk XT does not calculate the confidence limits for the mean. You can calculate the confidence limits as ā ± d (E.10), where d is defined as follows (if n > 8). For r ≤ 0.9 (E.11), and for r ≥ 0.9 (E.12), where R = nr and α is the significance level. Critical values for the χ² distribution with 1 degree of freedom are given in the table below. Critical Values for the χ² Distribution with v=1 (Zar 1998, Table B.1) Confidence Intervalαχ² 0.9990.00110.282 0.9950.0057.879 0.9900.0106.635 0.9750.0255.024 0.9500.0503.841 0.9000.1002.706 0.7500.2501.323 0.5000.5000.455 --- ## CatWalk XT 11 - Appendices - Circular Distributions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-circular-distributions-wEy Chapter: CatWalk XT Circular Distributions Vector Length and Mean Direction Imagine adding a few more dots between two existing ones on a circle. The more dots you add, the more the average coordinates X,Y will get closer to the circle. This means that the vector length R will increase. The greater R, the better the direction of the vector is defined, because the data points agree with each other. However, if you place points at other locations far from each other, the length of the vector is reduced, and R is low. Consequently, the value of the mean is a bad measure for the average Phase Dispersion because it represents a group of very different locations on the percentages circle. In other words, R helps you quantify the credibility of the average. When contrasting Phase Dispersions between two experimental groups, you may find a significant difference in R, not in CStat Mean. This means that the two groups do not differ in the average timing of one paw (target, T) relative to the other (anchor, A). However, the higher value of R in one of the two groups indicates lower between-subject variability in the temporal position of T relative to A than in the other group. The subjects in the group with higher R walk more uniformly than those in the group with a low R, although the average position of T relative to A is not different between the two groups. Measures of Spread Around the Mean Angular Deviation The vector length R is used to compute the Angular Deviation (CStat AD in CatWalk XT). The Angular Deviation ranges from a minimum of 0 when R = 1, to a maximum of 22.508 (100/2π) when R = 0. Note: The Angular Deviation CStat AD is the same as the CStat Standard Deviation in CatWalk XT 10.6 and earlier versions. Make sure this does not generate confusion when examining old experiments. Circular Standard Deviation An alternative measure, the Circular Standard Deviation (CStat SD in CatWalk XT), ranges from 0 to ∞. The Circular Standard Deviation s0 ranges from 0 to ∞, and therefore more closely resembles the standard deviation on a linear scale. However, it is reasonable to assume that circular data have a limited spread; in that case Angular Deviation may be a better option. Note: The Circular Standard Deviation CStat SD is not the same as the CStat Standard Deviation in CatWalk XT 10.6 and earlier versions. Make sure this does not generate confusion when examining old experiments. Note that Angular Deviation and Circular Standard Deviation tend to converge as the data cluster around the mean. The Circular Group Mean When calculating group statistics (Analyze > View Group Statistics and Charts), the group mean CStat Mean is calculated with the same formulas as for the mean of single values of Phase Dispersions and Couplings. Example: A group includes three trials. The per-trial averages of Couplings are 5%, 95%, and 100%. The circular mean provided by CatWalk XT is 0% (that is the same as 100%). Using the arithmetic mean would result in a value (66.67%) far from the original ones. The Excel Sheet "Calculate Circular Statistics" If you are not familiar with circular statistics, you can practice with the Excel sheet Calculate Circular Statistics for Phase Dispersions and Couplings.xlsx, which you can find in the same folder as this manual: C:\Program Files\Noldus\CatWalk XT 10\Documentation - Open the Excel file. - Enter the values of Phase Dispersions or Couplings, for example those displayed in CatWalk XT for a specific run. - Explore the formulas that lead to the main results: CStat Mean (%), CStat Angular Deviation (%), and CStat Standard Deviation (%). - Enter one or more values in the Values (%) column to see the effect on the statistics and on the orientation of the vector in the chart shown on the right. Notes: - If CStat Mean is negative and you prefer positive values, locate the Complementary Mean (%). Do this especially when you enter the values of Couplings. For example, if the CStat Mean (%) is -25%, the complementary mean valid in the range for Couplings (0–100%) is 75%. - The formulas for calculating circular statistics are protected and cannot be changed. - There may be small differences between the statistics given by CatWalk XT and those in the Excel sheet. In general they do not exceed 0.01% and are the effect of rounding of cell values. You can increase the number of decimals in CatWalk XT (File > Preferences > Number of Decimals) to better locate those differences. Confidence Limits for the Population Mean CatWalk XT does not calculate the confidence limits for the mean. You can calculate the confidence limits as: ā ± d where d is defined as follows (if n > 8). For r ≤ 0.9: d is calculated using the formula based on χ²(α,1) and the mean resultant length r. For r ≥ 0.9: d is calculated using R = nr, where R is the resultant length, n is the sample size, and α is the significance level. Critical values for the χ² distribution with 1 degree of freedom are given in the table below. Confidence Interval α χ² 0.9990.00110.282 0.9950.0057.879 0.9900.0106.635 0.9750.0255.024 0.9500.0503.841 0.9000.1002.706 0.7500.2501.323 0.5000.5000.455 --- ## CatWalk XT 11 - Appendices - End-User License Agreement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-end-user-license-agreement Chapter: CatWalk XT End-User License Agreement Important – Read Carefully. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading or using the Software (as defined below). By checking the "accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions of this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions Terms used in this EULA but not otherwise defined shall have the meaning assigned to them below: - 1.1. Authorized Partner: The individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. - 1.2. End-User: The individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3. EULA: This End-User License Agreement. - 1.4. Indirect Losses: Any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5. 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If the Software is an upgrade, any transfer must include all prior versions of the Software. - Noldus reserves the right to levy an administrative charge upon the End-User and/or the new End-User in relation to transfer of the Software to an End-User. 4.2. Any attempted transfer without prior written permission from Noldus shall constitute a material breach of this Agreement and shall be deemed null and void. 5. Term And Termination - 5.1. The EULA shall enter into force on the date of acceptance by the End-User and continue until terminated in accordance with this Section 5. - 5.2. If the Software is licensed on a subscription basis, the EULA shall continue until the end of the current subscription period. - 5.3. Noldus is entitled to terminate the EULA immediately upon prior written notice upon: - The breach of any material provision of this Agreement by the End-User if (i) such breach is not curable or (ii) if curable, the End-User has not cured such breach within a 30 (thirty) day period following receipt of a written notice by Noldus substantiating such breach. --- ## CatWalk XT 11 - Appendices - End-User License Agreement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-end-user-license-agreement-18Q Chapter: CatWalk XT End-User License Agreement Section 7 (Continued) User giving Noldus prompt written notice of any claim (provided that End-User's failure to provide prompt written notice will only relieve Noldus of its obligations under this Section to the extent such failure materially limits or prejudices Noldus' ability to defend or settle such claim); (ii) the transfer of sole control of the defense and any related settlement negotiations to Noldus; and (iii) End-User's cooperation, at Noldus' expense, in the defense of such claim. 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The United Nations Convention for Contracts on the International Sale of Goods is expressly excluded. - Any disputes arising out of or in connection with this EULA that cannot be solved amicably within a reasonable period of time will be submitted to the competent court in Arnhem, The Netherlands, for any dispute with End-Users having their principal place of business in the European Union. In the event that an End-User has its principal place of business outside the European Union, the United States of America or Canada, any dispute shall be finally settled in accordance with the Arbitration Rules of the Netherlands Arbitration Institute. Location shall be Arnhem, The Netherlands. The arbitration procedure shall be conducted by one (1) arbiter in the English language. --- ## CatWalk XT 11 - Appendices - End-User License Agreement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-end-user-license-agreement-NXK Chapter: CatWalk XT End-User License Agreement 5. Termination (Continued) 5.4. Upon termination of the EULA, the End-User shall immediately discontinue the use of the Software and remove the software from all computers, destroy all (partial) copies of the Software from all storage media and return the documentation and materials relating to the Software to Noldus or its Authorized Partner. 5.5. Termination of this Agreement does not remove or reduce End-User's obligation to pay any outstanding license fees or other monies, all of which shall be due for payment immediately on termination of the EULA. 5.6. The following provisions shall survive termination of this EULA: Sections 3, 7, 9, 10 and this Section 5.6. In addition, any other provisions which are required to interpret and enforce the Parties' rights and obligations under the EULA shall also survive any termination or expiration of this EULA, but only to the extent required for the full observation and performance of the EULA. 6. Warranty 6.1. 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Upon receipt of an End-User's written notice of the Software not conforming to the Specifications during the Warranty Period, Noldus shall at its option and in its sole discretion (i) assist the Customer in correcting or replacing the non-conforming Software or, (ii) terminate the EULA immediately and refund the purchase price paid by the End-User. The remedies described above shall be End-User's sole and exclusive remedies. Upon expiration of the Warranty Period, Noldus shall have no obligation to provide such remedies. 6.6. Noldus and Authorized Partners are not responsible for maintaining or supporting use of the Software or obligated to provide any updates, fixes or support to the Software unless otherwise expressly agreed in writing between End-User and Noldus or the Authorized Partners. 7. Use Limitation; Liability; Indemnification 7.1. 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Noldus' and Authorized Partners' liability shall also be excluded, and Noldus and the Authorized Partners shall not have any liability under this EULA in the event of: - End-User's use of the Software other than in accordance with Section 7.1. - Direct and indirect consequences of the End-User's failing to adhere strictly to the user documentation provided or made available by Noldus or the Authorized Partner. - Any loss of or damage to files or data howsoever caused. 7.7. A liability claim will be unenforceable and lapse unless Noldus or the Authorized Partner receives a written notice thereof no later than 6 months after the discovery of an event or circumstance that gives or may give rise to that claim. 7.8. Noldus will hold harmless, defend, and indemnify End-User from and against all losses, damages, claims, liabilities, and expenses incurred by End-User that arise out of, relate to, or are caused by any third party claim that End-User's use of the Software, pursuant to the terms of this EULA, infringes the intellectual property rights of such third party. If such a claim is made or appears likely to be made, Noldus, at its option, will have the right to either (i) procure for the End-User the right to continue to use the Software, (ii) modify or replace the Software so that it is no longer infringing (in a manner that substantially retains its functionality and quality), or (iii) require End-User to terminate the use of and return the Software and refund a pro rata portion, if any, of the amount paid by End-User to Noldus for the infringing Software. Notwithstanding the foregoing, Noldus will have no liability to End-User if the infringement results from use of the Software in combination with software not provided by Noldus or from modifications made by Noldus to conform to specifications provided by End-User. The indemnification obligations in this section are subject to: (i) End-User providing Noldus with prompt written notice of the claim. --- ## CatWalk XT 11 - Appendices - Gait Formulas URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-gait-formulas-tHa Chapter: CatWalk XT Gait Formulas A gait formula starts at Initial Contact (IC) of the left hind paw after all paws have been placed at least once. The Step Cycle then runs until the next IC of the left hind paw. In the Support tab of the Run Statistics, each Step Cycle is put on a separate row. Support Formula During each Step Cycle paws are subsequently raised and placed, leading to different numbers of paws on the ground. The Step Cycle can be subdivided into a number (often 8) of subsequent sections during which different numbers of paws are touching the ground. The Support formula provides the number of paws on the ground during each section, for example: - 2 — 3 — 2 — 3 — 2 — 3 — 2 — 3 - 4 — 3 — 2 — 3 — 4 — 3 — 2 — 3 - 1 — 2 — 1 — 2 — 1 — 2 — 1 — 2 Note that the Support formula does not describe which paws are on the ground, nor how long each section is in relation to the total Step Cycle. Footfall Formula The Footfall formula supplies some of the information which is missing in the Support formula, namely information on which paws are touching the floor during each section, but without information about the relative length of these sections. The Footfall formula uses an alphanumeric notation in CatWalk, as follows: - 0 — No paw touching the ground - I — One paw touching the ground - ILH — Left hind paw on the ground - ILF — Left front paw on the ground - IRF — Right front paw on the ground - IRH — Right hind paw on the ground - II — Two paws touching the ground - IIG — Girdle pairs - IIGF — Front paws on the ground - IIGH — Hind paws on the ground - IIL — Ipsilateral pairs - IILL — Left side on the ground - IILR — Right side on the ground - IID — Diagonal pairs - IIDL — Left front paw and right hind paw on the ground - IIDR — Right front paw and left hind paw on the ground - III — One paw off the ground - IIILH — Left hind paw off the ground - IIILF — Left front paw off the ground - IIIRF — Right front paw off the ground - IIIRH — Right hind paw off the ground - IV — Four paws on the ground A possible footfall formula is then as follows: IIILF - IIDR - IIIRH - IILL - IIIRF - IIDL - IIILH - IILR These labels allow us to refer to specific combinations of placed paws and to assign durations (relative to that of the total Step Cycle) to them for further analysis. Especially interesting is the total duration spent in I's combined, and the total in IIG's and/or IIL's combined, as these are unstable (the mass-midpoint of the animal is far from the point(s) of support). Circular Distributions This section describes the computation of descriptive statistics for circular distributions of data such as phase lags during locomotion. It provides a very short summary of chapter 26 from Biostatistical Analysis by Zar (1998). Special statistical tests are available for circular distributions; see Zar (1998), Chapter 27. Tip: Open the Excel file Calculate Circular Statistics of Phase Dispersions and Couplings.xlsx, found under C:\Program Files\Noldus\CatWalk XT 10\Documentation. Enter the values of Phase Dispersions and Couplings obtained in runs or trials to see how the main statistics are computed. The Circular Mean If we have a sample consisting of phase lags (periodic on the range 0–100), the mean of these phase lags is an estimate of the average phase lag angle in the sampled population. To compute the sample mean phase lag, we first consider the rectangular coordinates of the mean phase lag, then compute the length of the mean vector R. The Circular Mean (CStat Mean (%) in CatWalk XT) is derived from the cosine and sine of the resulting angle. Interpreting the Mean and R CatWalk XT reports the CStat Mean as a percentage of the step cycle duration. For Phase Dispersions, it ranges from -50% to +50%. For Couplings, it ranges from 0% to 100%. The value R ranges from 0 to 1. Both CStat Mean and R are important: they can be interpreted as a vector with length R and a direction equal to the mean angle. The vector starts at the midpoint of a circle with a radius of 1.00 and ends at the mass midpoint of the phase lag values positioned on the circle itself. - X and Y are the average x- and y-coordinates of the data points in a 2D space. - The angle formed by the vector is halfway between the two data points. - The length of the vector describes the dispersion of the data points around the mean. --- ## CatWalk XT 11 - Appendices - Gait Formulas URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-gait-formulas Chapter: CatWalk XT Gait Formulas A gait formula starts at Initial Contact (IC) of the left hind paw after all paws have been placed at least once. The Step Cycle then runs until the next IC of the left hind paw. In the Support tab of the Run Statistics, each Step Cycle is put on a separate row. Support Formula During each Step Cycle paws are subsequently raised and placed, leading to different numbers of paws on the ground. The Step Cycle can be subdivided in a number (often 8) of subsequent sections during which different numbers of paws are touching the ground. The Support formula provides the number of paws on the ground during each section, for example: - 2 — 3 — 2 — 3 — 2 — 3 — 2 — 3 - 4 — 3 — 2 — 3 — 4 — 3 — 2 — 3 - 1 — 2 — 1 — 2 — 1 — 2 — 1 — 2 Note that the Support formula does not describe which paws are on the ground, nor how long each section is in relation to the total Step Cycle. Footfall Formula The Footfall formula supplies some of the information which is missing in the Support formula, namely information on which paws are touching the floor during each section, but without information about the relative length of these sections. The Footfall formula uses an alphanumeric notation in the CatWalk program, as follows: - 0 — No paw touching the ground - I — One paw touching the ground - ILH — Left hind paw on the ground - ILF — Left front paw on the ground - IRF — Right front paw on the ground - IRH — Right hind paw on the ground - II — Two paws touching the ground - IIG — Girdle pairs - IIGF — Front paws on the ground - IIGH — Hind paws on the ground - IIL — Ipsilateral pairs - IILL — Left side on the ground - IILR — Right side on the ground - IID — Diagonal pairs - IIDL — Left front paw and right hind paw on the ground - IIDR — Right front paw and left hind paw on the ground - III — One paw off the ground - IIILH — Left hind paw off the ground - IIILF — Left front paw off the ground - IIIRF — Right front paw off the ground - IIIRH — Right hind paw off the ground - IV — Four paws on the ground A possible footfall formula is then as follows: IIILF - IIDR - IIIRH - IILL - IIIRF - IIDL - IIILH - IILR These labels allow us to refer to specific combinations of placed paws and to assign durations (relative to that of the total Step Cycle) to them for further analysis. Especially interesting is the total duration spent in I's combined, and the total in IIG's and/or IIL's combined, as these are unstable (the mass-midpoint of the animal is far from the point or points of support). Circular Distributions This appendix describes the computation of descriptive statistics for circular distributions of data such as phase lags during locomotion. It provides a very short summary of chapter 26 from Biostatistical Analysis by Zar (1998). Special statistical tests are available for circular distributions; see Zar (1998), Chapter 27. Tip: Open the Excel file Calculate Circular Statistics of Phase Dispersions and Couplings.xlsx, which can be found under C:\Program Files\Noldus\CatWalk XT 10\Documentation. Enter the values of Phase Dispersions and Couplings obtained in runs or trials to see how the main statistics are computed. The Circular Mean If we have a sample consisting of phase lags (periodic on the range 0–100), the mean of these phase lags is an estimate of the average phase lag angle in the sampled population. To compute the sample mean phase lag, we first consider the rectangular coordinates of the mean phase lag, then compute the length of the mean vector R. The Circular Mean (CStat Mean (%) in CatWalk XT) is derived from the angle having the corresponding cosine and sine values. Interpreting the Mean and R CatWalk XT reports the CStat Mean in percentage of the step cycle duration. For Phase Dispersions, it ranges from -50% to +50%. For Couplings, it ranges from 0% to 100%. The value R ranges from 0 to 1. Both CStat Mean and R are important: they can be interpreted as a vector with length R and a direction corresponding to the mean. The vector starts at the midpoint of a circle with a radius of 1.00 and ends at the mass midpoint of the phase lag values that are positioned on the circle itself. - X and Y are the average x- and y-coordinates of the data points in a 2D space. - The angle formed by the vector is halfway between the two data points. - The length of the vector describes the dispersion of the data points around the mean. --- ## CatWalk XT 11 - Appendices - History Of CatWalk URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-history-of-catwalk-WYY Chapter: CatWalk XT History Of CatWalk Acknowledgments Text by Frank Hamers, MD, PhD – October 24, 2005 The CatWalk system would not have been possible without Dr Willem Hendrik Gispen, the leading force behind nerve regeneration research in Utrecht and originally my PhD thesis advisor. During his tenure as scientific director of the Department of Pharmacology & Anatomy and that of the Rudolf Magnus Institute of Neuroscience — which was his creation — he inspired clinical and basic scientists to collaborate on the most difficult problems in clinical neurosciences. After completion of my PhD thesis on cisplatin neuropathy he offered me a position in his staff and as such I eventually started spinal cord research. In 1996 I visited the Beattie/Bresnahan lab at OSU to learn the BBB-score, and I returned with the idea to further objectify assessment of FL-HL coordination in this test. In this I was fully supported by Willem Hendrik Gispen. Jan Brakkee spent a weekend in his workshop at home to build a walkway. All PhD students helped in testing, and it was together with Dr Alex Lankhorst that I published the first validation studies. Dr Tinna Ängeby-Möller from AstraZeneca Pain Research in Sweden was the first one with the idea to use this device for quantification of pain. Drs Dorien Vrinten and Tineke Vogelaar have been most appreciated collaborators on the pain and peripheral nerve regeneration studies. On the other side of the ocean, Drs Jacqueline Bresnahan and Michael Beattie have been my strongest supporters ever since they got a demonstration of the walkway's abilities. Implementation of the phase lag parameters was driven by Dr Michelle Basso. Their continuing input in and promotion of the system are very much appreciated. Dr Joost Verhaagen, like Drs Beattie and Bresnahan in the US, has been one of my staunchest supporters in Europe, and I hope that I can continue the very rewarding collaboration with members of his lab on problems related to nerve regeneration. My foremost collaborator in the last three years has been Dr Bert Joosten. After his move from Utrecht to Maastricht he needed to start his own behavioural research and he decided to set up a CatWalk system as well. In Maastricht he also entered the pain field, and all his students use CatWalk, either for SCI or for pain, and they generate lots of data, questions and discussion. It was Guido Koopmans (2005), one of Bert's PhD students, who eventually showed that CatWalk can be used to more reliably assess FL-HL coordination than open-field testing, enabling one to observe otherwise missed treatment effects. But my most important supporter over the years has been my wife, Ingeborg, who did not complain when I worked at the program in the evenings and weekends, and who fully supported my regular lab and conference visits abroad, despite her own demanding job and the doubled household and childcare obligations with me abroad. --- ## CatWalk XT 11 - Appendices - History of CatWalk URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-history-of-catwalk Chapter: CatWalk XT History of CatWalk Acknowledgments Text by Frank Hamers, MD, PhD – October 24, 2005 The CatWalk system would not have been possible without Dr Willem Hendrik Gispen, the leading force behind nerve regeneration research in Utrecht and originally my PhD thesis advisor. During his tenure as scientific director of the Department of Pharmacology & Anatomy and that of the Rudolf Magnus Institute of Neuroscience – which was his creation – he inspired clinical and basic scientists to collaborate on the most difficult problems in (clinical) neurosciences. After completion of my PhD thesis on cisplatin neuropathy he offered me a position in his staff and as such I eventually started spinal cord research: In 1996 I visited the Beattie/Bresnahan lab at OSU to learn the BBB-score, and I returned with the idea to further objectify assessment of FL-HL coordination in this test. In this I was fully supported by Willem Hendrik Gispen. Jan Brakkee spent a weekend in his workshop at home to build a walkway. All (PhD) students helped in testing, and it was together with Dr Alex Lankhorst that I published the first validation studies. Dr Tinna Ängeby-Möller from AstraZeneca Pain Research in Sweden was the first one with the idea to use this device for quantification of pain. Drs Dorien Vrinten and Tineke Vogelaar have been most appreciated collaborators on the pain and peripheral nerve regeneration studies. On the other side of the ocean, Drs Jacqueline Bresnahan and Michael Beattie have been my strongest supporters ever since they got a demonstration of the walkway's abilities. Implementation of the phase lag parameters was driven by Dr Michelle Basso. Their continuing input in and promotion of the system are very much appreciated. Dr Joost Verhaagen, like Drs Beattie and Bresnahan in the US, has been one of my staunchest supporters in Europe, and I hope that I can continue the very rewarding collaboration with members of his lab on problems related to nerve regeneration. My foremost collaborator in the last three years has been Dr Bert Joosten. After his move from Utrecht to Maastricht he needed to start his own behavioural research and he decided to set up a CatWalk system as well. Source: CatWalk XT 11.0 Reference Manual - Appendices, Noldus Information Technology --- ## CatWalk XT 11 - Appendices - References URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-references-sv0 Chapter: CatWalk XT References - Bain JR, Mackinnon SE, Hunter RT (1989). Functional evaluation of complete sciatic, peroneal, and posterior tibial nerve lesions in the rat. Plast Reconstr Surg 83: 129–136. - Coulthard P, Pleuvry BJ, Brewster M, Wilson KL, Macfarlane TV (2002). Gait analysis as an objective measure in a chronic pain model. J Neurosci Methods 116: 197–213. - Coulthard P, Simjee SU, Pleuvry BJ (2003). Gait analysis as a correlate of pain induced by carrageenan intraplantar injection. J Neurosci Methods 128: 95–102. - Hamers FPT, Lankhorst AJ, Van Laar TJ, Veldhuis WB, Gispen WH (2001). Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries. J Neurotrauma 18: 187–201. - Hamers FPT, Koopmans GC, Joosten EAJ (2006). CatWalk assisted gait analysis in the assessment of spinal cord injury. J Neurotrauma 24: 537–548. - Hildebrand M (1976). Analysis of tetrapod gaits: general considerations and symmetrical gaits. In: Herman RM, Grillner S, Stein PSG, Stuart DG, Neural Control of Locomotion, Plenum, NY. - Inserra MM, Bloch DA, Terris DJ (1998). Functional indices for sciatic, peroneal, and posterior tibial nerve lesions in the mouse. Microsurgery 18: 119–124. - Kloos AD, Fisher LC, Detloff MR, Hassenzahl DL, Basso DM (2005). Stepwise motor and all-or-none sensory recovery is associated with nonlinear sparing after incremental spinal cord injury in rats. Exp Neurol 191: 251–265. - Koopmans GC, Honig WMM, Hamers FPT, Steinbusch HWM, Joosten EAJ (2005). The assessment of locomotor behavior in spinal cord injured rats; the importance of objective analysis of locomotion. J Neurotrauma 22: 214–225. - Vrinten DH, Hamers FPT (2003). 'CatWalk' automated quantitative gait analysis as a novel method to assess mechanical allodynia in the rat; a comparison with von Frey testing. Pain 102: 203–209. - Zar JH (1998). Biostatistical Analysis, 4th edition. Prentice Hall: NJ. History of CatWalk Text by Frank Hamers, MD, PhD — October 24, 2005 CatWalk was developed by Dr. Frank Hamers (Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, The Netherlands) as a research tool for his work on functional recovery from spinal cord contusion injury in the rat. Development started in the summer of 1996, after he had spent a month at the lab of Dr. Michael Beattie and Jacqueline Bresnahan at OSU (Columbus, OH) to gain experience with the newly developed Basso-Beattie-Bresnahan locomotor rating scale (BBB-test), a very sensitive and reproducible open-field test for assessment of locomotor recovery in this animal model. An important landmark in the BBB-test is the return of FL-HL coordination, something which may be difficult to see with the naked eye. The definition used in the BBB-score is an operational one, as it is impossible to follow all four paws at the same time: even with two observers (the recommended setup for BBB-testing) each observer only sees at most three paws at the same time. Several months earlier, Frank Hamers had read some papers written by Kenneth Clarke (University of Sheffield, UK) who used a special walkway enabling evaluation of paw-floor contact with unprecedented detail for his own research on gait development in rat puppies. Frank Hamers believed that such a walkway might be used to enable better evaluation of FL-HL coordination in spinal cord lesioned animals, and back in Utrecht a prototype of the walkway was built: it behaved as expected. The first full-featured walkway was built in a weekend by Jan Brakkee, the chief biotechnician in the regeneration group, and several others have been built by the author himself after that. Frank Hamers had well-developed software engineering skills — in fact, since he enrolled in the lab as a PhD student in 1988 he largely automated data acquisition in the whole of the regeneration group — and as such he set out to write a simple videotaping program to capture animals crossing the walkway. This was the prototypical CatWalk program which eventually evolved into the program as it is now. This evolution was driven by Frank Hamers' own research questions and those of his collaborators using the system, the more so as regeneration research was banned from the Pharmacology & Anatomy lab shortly after 2001. For instance, assessment of coordination is just one of the many things that the program can be used for, and its ability to assess FL-HL coordination in an unbiased way has only recently been combined with the BBB-test by Guido Koopmans, a former PhD student in Bert Joosten's lab at Maastricht University. The first meaningful results with the system were presented at the Annual Neurotrauma Symposium in Miami Beach in November 1999. The second and third systems were set up by Frank Hamers at Jacqui Bresnahan's lab at OSU and at Barbara Bregman's lab at Georgetown University in September 2000, followed almost immediately by a system in Joost Verhaagen's lab at the Netherlands Institute for Brain Research in Amsterdam. Since then, the number of installed systems has greatly expanded and the value of the system in many different nervous system lesion models and others has become increasingly more clear. --- ## CatWalk XT 11 - Appendices - References URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-references Chapter: CatWalk XT References - Bain JR, Mackinnon SE, Hunter RT (1989). Functional evaluation of complete sciatic, peroneal, and posterior tibial nerve lesions in the rat. Plast Reconstr Surg 83: 129–136. - Coulthard P, Pleuvry BJ, Brewster M, Wilson KL, Macfarlane TV (2002). Gait analysis as an objective measure in a chronic pain model. J Neurosci Methods 116: 197–213. - Coulthard P, Simjee SU, Pleuvry BJ (2003). Gait analysis as a correlate of pain induced by carrageenan intraplantar injection. J Neurosci Methods 128: 95–102. - Hamers FPT, Lankhorst AJ, Van Laar TJ, Veldhuis WB, Gispen WH (2001). Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries. J Neurotrauma 18: 187–201. - Hamers FPT, Koopmans GC, Joosten EAJ (2006). CatWalk assisted gait analysis in the assessment of spinal cord injury. J Neurotrauma 24: 537–548. - Hildebrand M (1976). Analysis of tetrapod gaits: general considerations and symmetrical gaits. In: Herman RM, Grillner S, Stein PSG, Stuart DG, Neural Control of Locomotion. Plenum, NY. - Inserra MM, Bloch DA, Terris DJ (1998). Functional indices for sciatic, peroneal, and posterior tibial nerve lesions in the mouse. Microsurgery 18: 119–124. - Kloos AD, Fisher LC, Detloff MR, Hassenzahl DL, Basso DM (2005). Stepwise motor and all-or-none sensory recovery is associated with nonlinear sparing after incremental spinal cord injury in rats. Exp Neurol 191: 251–265. - Koopmans GC, Honig WMM, Hamers FPT, Steinbusch HWM, Joosten EAJ (2005). The assessment of locomotor behavior in spinal cord injured rats; the importance of objective analysis of locomotion. J Neurotrauma 22: 214–225. - Vrinten DH, Hamers FPT (2003). CatWalk automated quantitative gait analysis as a novel method to assess mechanical allodynia in the rat; a comparison with von Frey testing. Pain 102: 203–209. - Zar JH (1998). Biostatistical Analysis, 4th edition. Prentice Hall: NJ. History of CatWalk (Text by Frank Hamers, MD, PhD — October 24, 2005) CatWalk was developed by Dr. Frank Hamers (Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, The Netherlands) as a research tool for his work on functional recovery from spinal cord contusion injury in the rat. Development started in the summer of 1996, after he had spent a month at the lab of Dr. Michael Beattie and Jacqueline Bresnahan at OSU (Columbus, OH) to gain experience with the newly developed Basso-Beattie-Bresnahan locomotor rating scale (BBB-test), a very sensitive and reproducible open-field test for assessment of locomotor recovery in this animal model. An important landmark in the BBB-test is the return of FL-HL coordination, something which may be difficult to see with the naked eye. The definition used in the BBB-score is an operational one, as it is impossible to follow all four paws at the same time: even with two observers (the recommended setup for BBB-testing) each observer only sees at most three paws at the same time. Several months earlier, Frank Hamers had read some papers written by Kenneth Clarke (University of Sheffield, UK) who used a special walkway enabling evaluation of paw-floor contact with unprecedented detail for his research on gait development in rat puppies. Frank Hamers believed that such a walkway might be used to enable better evaluation of FL-HL coordination in spinal cord lesioned animals, and back in Utrecht a prototype of the walkway was built: it behaved as expected. The first full-featured walkway was built in a weekend by Jan Brakkee, the chief biotechnician in the regeneration group, and several others have been built by the author himself since then. Frank Hamers had well-developed software engineering skills — in fact, since he enrolled in the lab as a PhD student in 1988 he largely automated data acquisition across the whole of the regeneration group — and as such he set out to write a simple videotaping program to capture animals crossing the walkway. This was the prototypical CatWalk program which eventually evolved into the program as it exists today. This evolution was driven by Frank Hamers' own research questions and those of his collaborators using the system, the more so as regeneration research was banned from the Pharmacology & Anatomy lab shortly after 2001. For instance, assessment of coordination is just one of the many things that the program can be used for, and its ability to assess FL-HL coordination in an unbiased way has only recently been combined with the BBB-test by Guido Koopmans, a former PhD student in Bert Joosten's lab at Maastricht University. The first meaningful results with the system were presented at the Annual Neurotrauma Symposium in Miami Beach in November 1999. The second and third systems were set up by Frank Hamers at Jacqui Bresnahan's lab at OSU and at Barbara Bregman's lab at Georgetown University in September 2000, followed almost immediately by a system in Joost Verhaagen's lab at the Netherlands Institute for Brain Research in Amsterdam. Since then, the number of installed systems has greatly expanded and the value of the system in many different nervous system lesion models and others has become increasingly clear. --- ## CatWalk XT 11 - Appendices - Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-troubleshooting-eww Chapter: CatWalk XT Troubleshooting The Paw Prints Look Faint, or Irregular This may have multiple causes: (a) the camera gain is too low, (b) the walkway lights are too dim, or (c) the green intensity threshold is too high. - In the classification screen, click the Adjust the Green Intensity Threshold button. Deselect Show Filtered Out Signals. When you move the slider to the right, the prints should shrink and then disappear. When you move the slider to the left, more and more of the prints should appear in green. Change this setting until the prints look good. However this change only affects that run. If that solves the issue, in the Detection Settings, make the same change to the green intensity threshold there to apply to all future runs. - If the previous step does not help, the issue may lie in the camera gain or the lights. Go to the Detection Settings (Setup > Detection Settings). Set the Green Intensity Threshold fairly low, for example 0.05. With an animal running across the walkway, look at the value in the middle for Maximum Green Intensity. During a run, this value should be around 200–205. If the animal stops, or walks more times in the same place, the value increases. Click the Reset Prints button to clear that value and try again. If the Maximum Green Intensity is much lower than about 200, raise the Camera Gain. If you raise the Camera Gain to 20 or higher and the maximum green intensity is still too low, also raise the Green Walkway Light setting (only a little bit at a time). Keep clicking Reset Prints while the animal runs back and forth to get new measures. Avoid having the camera gain above 20 as it produces more noise. - Once the Camera Gain is set, with a low Green Intensity Threshold you will probably also have a lot of other noise in the image. Now start adjusting that threshold value. You want to get nice clean images of the prints but no green noise anywhere else. If you raise the Green Intensity Threshold too high, you'll start losing the prints themselves. Play with this setting till the prints look good. A Paw Print Is Not Recognized by the Automatic Footprint Classification This may happen when a paw print has consistently a low value of Max Intensity, and this value is lower than the minimum set in the Classification Settings. Choose Setup > Classification Settings. Next to Only Assign a Label..., reduce the value of minimum acceptable Max Intensity. Next, repeat automatic classification. The Automatic Footprint Classification Does Not Seem to Work Well This may occur in two cases: (a) when prints are too light, because the gain in the detection settings is too low, or the noise threshold is too high, or (b) when there is too much noise that confuses the system, because the gain is too high or the noise threshold too low. Especially in the case where there is too much noise, you can adjust the noise threshold in the classification. Click the button Adjust the Green Intensity Threshold and use the slider to raise or lower the threshold. A lower threshold will show more of the prints and noise, while a higher threshold will remove more of them. Your goal is to have only the prints left, as complete as possible, but no noise. The closer you get to that situation, the better a job auto classification will do. If you consistently need to adjust the noise threshold, it's best to do so in the Detection Settings. That is also the only place you can adjust the camera Gain (sensitivity). The Gain can only be adjusted for future trials, not for those which have already been acquired. Paw Prints Look Incomplete in the Interactive Footprint Measurements Screen When the footprint is shown in the Interactive Footprint Measurements screen, it is enlarged by means of smoothing and anti-aliasing algorithms. Pixels that are outside the border of the footprint rectangle, which contain no data by definition, are "translated" to blue pixels. This may result in incomplete-looking images, especially if the image resolution is low. To reduce this effect, place the camera closer to the walkway. Tip: In the Interactive Footprint Measurements screen, right-click the footprint image and select Switch to 'Normal Color' Mode. That way the artifact is less evident. I Want to Include Non-Compliant Runs in My Data Set In the lower-left corner, under Data Segmentation Profiles, double-click All Data. In the window that opens, make sure that the two check boxes at the top are not selected. Then click OK and run analysis. How Can I Separate Two Paw Prints That Are Near Each Other? When two paw prints are very near each other, drawing a box around one of the prints is likely to include parts of the other print. - Draw a box that only covers (part of) the first paw print, and select Add Print. If a box is already defined around both paw prints, remove that box (right-click and select Remove Print). - Draw more boxes for the remaining parts of the paw print, but try not to include the second paw print. Keep selecting Add Print. Each box is now labeled as UN. - Draw a larger box around all the boxes and select the paw print you want. - Repeat the steps for the other paw print. The Automatic Detection of Paw Prints Does Not Work Anymore This could be caused by the glass plate no longer being in its place. In that case illumination is no longer uniform; that is, paw prints are found only on the left or right parts of the catwalk. Check that the glass plate has not been pulled or pushed during transport of the system, and that both the left and right sides of the walkway are equally visible. If you move the system to another location, always do this by pushing/pulling the whole CatWalk stand, not the glass plate. Data Analysis and Export The Group Means Do Not Correspond to What I Calculate Using the Exported Data This occurs because of the way the group means are calculated. In CatWalk XT, the group mean of a variable is calculated by taking the means of the trials that correspond to that group. So if a group contains 10 trials, the mean is calculated over the 10 trial averages, irrespective of the "weight" of each trial, that is, of how many runs each trial contains. If you consider the single runs, the overall mean value for that group will differ from that given by CatWalk XT. The Circular Charts Look Distorted When Exported When being exported to image files, the circular charts may look stretched or squeezed. To solve this, click the Chart Settings button and select the same value of Chart Width, Chart Height, and Chart Size (the latter under Circular Charts). Then export the charts again. --- ## CatWalk XT 11 - Appendices - Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-appendices-troubleshooting Chapter: CatWalk XT Troubleshooting The Paw Prints Look Faint, or Irregular This may have multiple causes: (a) the camera gain is too low, (b) the walkway lights are too dim, or (c) the green intensity threshold is too high. - In the classification screen, click the Adjust the Green Intensity Threshold button. Deselect Show filtered out signals. When you move the slider to the right, the prints should shrink and then disappear. When you move the slider to the left, more and more of the prints should appear in green. Change this setting until the prints look good. However this change only affects that run. If that solves the issue, in the Detection Settings, make the same change to the green intensity threshold there to apply to all future runs. - If the previous step does not help, the issue may lie in the camera gain or the lights. Go to the Detection Settings (Setup > Detection Settings). Set the Green Intensity Threshold fairly low, for example 0.05. With an animal running across the walkway, look at the value in the middle for Maximum Green Intensity. During a run, this value should be around 200–205. If the animal stops, or walks more times in the same place, the value increases. Click the Reset Prints button to clear that value and try again. If the Maximum Green Intensity is much lower than about 200, raise the Camera Gain. If you raise the Camera Gain to 20 or higher and the maximum green intensity is still too low, also raise the Green Walkway Light setting (only a little bit at a time). Keep clicking Reset Prints while the animal runs back and forth to get new measures. Avoid having the camera gain above 20 as it produces more noise. - Once the Camera Gain is set, with a low Green Intensity Threshold you will probably also have a lot of other noise in the image. Now start adjusting that threshold value. You want to get nice clean images of the prints but no green noise anywhere else. If you raise the Green Intensity Threshold too high, you'll start losing the prints themselves. Play with this setting till the prints look good. A Paw Print Is Not Recognized by the Automatic Footprint Classification This may happen when a paw print has consistently a low value of Max Intensity, and this value is lower than the minimum set in the Classification Settings. Choose Setup > Classification Settings. Next to Only assign a label..., reduce the value of minimum acceptable Max Intensity. Next, repeat automatic classification. The Automatic Footprint Classification Does Not Seem to Work Well This may occur in two cases: (a) when prints are too light, because the gain in the detection settings is too low or the noise threshold is too high, or (b) when there is too much noise that confuses the system, because the gain is too high or the noise threshold too low. Especially in the case where there is too much noise, you can adjust the noise threshold in the classification. Click the button Adjust the Green Intensity Threshold and use the slider to raise or lower the threshold. A lower threshold will show more of the prints and noise, while a higher threshold will remove more of them. Your goal is to have only the prints left, as complete as possible, but no noise. The closer you get to that situation, the better a job auto classification will do. If you consistently need to adjust the noise threshold, it is best to do so in the Detection Settings. That is also the only place you can adjust the camera Gain (sensitivity). The Gain can only be adjusted for future trials, not for those which have already been acquired. Paw Prints Look Incomplete in the Interactive Footprint Measurements Screen When the footprint is shown in the Interactive Footprint Measurements screen, it is enlarged by means of smoothing and anti-aliasing algorithms. Pixels that are outside the border of the footprint rectangle, which contain no data by definition, are translated to blue pixels. This may result in incomplete-looking images, especially if the image resolution is low. To reduce this effect, place the camera closer to the walkway. Tip: In the Interactive Footprint Measurements screen, right-click the Footprint image and select Switch to 'Normal Color' mode. That way the artifact is less evident. I Want to Include Non-Compliant Runs in My Data Set In the lower-left corner, under Data Segmentation Profiles, double-click All Data. In the window that opens, make sure that the two check boxes at the top are not selected. Then click OK and run analysis. How Can I Separate Two Paw Prints That Are Near Each Other? When two paw prints are very near each other, drawing a box around one of the prints is likely to include parts of the other print. - Draw a box that only covers (part of) the first paw print, and select Add Print. If a box is already defined around both paw prints, remove that box (right-click and select Remove Print). - Draw more boxes for the remaining parts of the paw print, but try not to include the second paw print. Keep selecting Add Print. Each box is now labeled as UN. - Draw a larger box around all the boxes and select the paw print you want. - Repeat the steps for the other paw print. The Automatic Detection of Paw Prints Does Not Work Anymore This could be caused by the glass plate no longer being in its place. In that case illumination is no longer uniform, and only the left or right parts of the catwalk paw prints are found. Check that it has not been pulled or pushed during transport of the system, and that both the left and right sides of the walkway are equally visible. If you move the system to another location, always do this by pushing or pulling the whole CatWalk stand, not the glass plate. Data Analysis and Export The Group Means Do Not Correspond to What I Calculate Using the Exported Data This occurs because of the way the group means are calculated. In CatWalk XT, the group mean of a variable is calculated by taking the means of the trials that correspond to that group. So if a group contains 10 trials, the mean is calculated over the 10 trial averages, irrespective of the weight of each trial, that is, of how many runs each trial contains. If you consider the single runs, the overall mean value for that group will differ from that given by CatWalk XT. The Circular Charts Look Distorted When Exported When being exported to image files, the circular charts may look stretched or squeezed. To solve this, click the Chart Settings button and select the same value of Chart width, Chart height, and Chart size (the latter under Circular charts). Next, export the charts again. --- ## CatWalk XT 11 - Assembly - Assemble The Catwalk System URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-assembly-assemble-the-catwalk-system Chapter: CatWalk XT Phase 1 - The CatWalk Stand End result (shown in black) - Take the base frame from the box with the CatWalk stand (the widest box) and place it on the floor. - Put the brake on the caster wheels by putting the pedal in the 'down' position. - Using one of the hexagonal keys, unscrew two sliding nuts (a in the picture below) from each of the support angles and leave the other two nuts attached. - Slide two sliding nuts into the profile on both short sides of the base frame. Tip: To estimate the position of the sliding nuts, place one of the ground plates on top of the base frame. The two nuts should be visible. Make sure the cut-out corner is at the back of the frame. - Attach the support angle loosely to the base frame; you should still be able to slide the support angle (indicated by the horizontal arrows in the picture below). Unscrew the other two sliding nuts as much as possible but make sure they stay attached to the bolts (indicated by the circle). Repeat this on the opposite side of the base frame. - Attach one of the profiles (with the small and large support angle) to the support angle on the base frame by sliding the profile over the unscrewed sliding nuts until the profile rests on the base frame. Make sure that: - The support angle in the middle of the vertical profile points inwards. - The small support angle at the top points forward. Now firmly attach the standing profile to the support angle on the base frame by tightening the bolts on the support angle. - Unscrew the sliding nuts of the support angle in the middle of the profile you just attached to the base frame, but make sure the nuts stay attached to the bolts. - Slide the profile (with the hole in the middle) over the nuts of the support angle on the standing profile. The hole in the middle should be facing forward. - Take the other profile (with the small and large support angle) and unscrew the sliding nuts of the support angle in the middle of the profile (as in step 6 above). Make sure the nuts stay attached to the bolts. Next, slide the horizontal profile over the unscrewed nuts of the support angle. - Slide the profile over the nuts of the support angle on the base frame until this vertical profile rests on the base frame. Now firmly attach the standing profile to the support angle on the base frame by tightening the bolts on the support angle. - Remove the protective plastic from the two black ground plates. Lay down each plate with the slit around the support angle and standing profile. Make sure the cut-out corner is at the back of the base frame. Move the support angle and standing profile so the base plates are aligned with the base frame on both sides. The standing profile should be positioned so that there is a small gap at the side of the support angle so the protection cap fits there. - Now firmly attach the support angles at the bottom of the base frame (see 1 in the picture below). Also, firmly attach the horizontal profile to the support angles on the vertical profiles (see 2 in the picture below). - Slightly unscrew the bolts from the small support angles on both standing profiles and slide the small support angles out of the profiles. These small support angles will be attached to the walkway (see step 19). - Loosely attach two sliding nuts to both fixation plates. Slide the sliding nuts into the standing profile at the front side. Repeat on the standing profile on the other side. Slide the fixation plates downwards until they are positioned just above the horizontal profile. - Insert the other sliding nuts into the horizontal profile. Make sure the sliding nuts are positioned with the holes facing outwards. Slide the fixation plate further downwards and firmly attach the fixation plate to the standing and horizontal profile. Phase 2 - Attach the Walkway to the Stand End result (shown in black) - Open the box with the walkway and take out the walkway with glass plate. Carefully put the walkway on its side so the bottom-side is facing you. - Take the small support angles you removed from the standing profiles in step 12. Unscrew both nuts as much as possible but make sure they stay attached to the bolts. - From the right side of the walkway, slide one support angle into the bottom of the walkway profile. Slide the support angle all the way to the left side of the walkway profile so it is aligned with the small profile supporting the glass plate. - Now open the third box and take out the camera profile. Unscrew the nut from the bolt until it is almost loose. Slide the camera profile into the bottom of the walkway profile until it is in the middle of the walkway. Tighten the bolt a bit but make sure you are still able to move the camera profile sideways. - Slide the other small support angle into the bottom of the walkway profile until it is aligned with the profile supporting the glass plate on the right side. - For this step you need a second person. Lift the walkway with the two support angles and the camera profile. Slide the nuts on the small support angles on either side into the standing profiles. Important: Check the following: - That the camera profile is horizontally centered (this is where the ground plates meet on the base frame). - That the glass plate is perfectly horizontal. Check this with the spirit level. - When you are sure that the glass plate is horizontal, tighten the bolt on the camera profile and the four bolts on both support angles so the walkway is firmly attached to the stand. Important: To make the camera profile more stable: attach the camera profile to the horizontal profile using a small support angle. Insert two sliding nuts in both profiles, and fix the support angle to both of them (back view). - Remove the black ceiling support fixation plates from the profiles of the illuminated ceiling; unscrew the two bolts and remove them from the plate. Unscrew the other two bolts but make sure they stay attached to the nuts. Slide the nuts of the ceiling support fixation plate into the vertical profile at the back of the stand. Slide the fixation plate all the way down until it rests on the horizontal profile in the middle. Repeat on the other side. - Take the profile with the two sliding bolts. Attach the profile to the stand by inserting the bolts into the holes on top of the standing profiles. Loosely fix the bolt on one side through the hole in the profile sitting on the stand. Next, fix the bolt on the other side; if necessary, slightly move the horizontal profile to align the bolt and the hole in the profile. Note: This profile must be aligned with the walkway profile. Phase 3 - Install the Illuminated Ceiling and Corridor End result (shown in black) Install the Spring-Operated Corridor - Take the ceiling support profiles. Unscrew the nut from the support angle (indicated by b in the picture below) but make sure it stays attached to the bolt. - Remove the protective cap from the right side of the profile with the sliding bolts. Insert both illuminated ceiling profiles into the horizontal profile. Make sure the supports at the top are pointing outwards. Align both illuminated ceiling profiles with the standing profiles of the stand. Do not yet fix the illuminated ceiling profiles to the stand; you still need to be able to slightly move them when attaching the illuminated ceiling. - Attach a washer (a) and a spacer (b) to both supporting rods of the ceiling profile. - Take the corridor lift mechanism, the two corridor walls and the corridor holders. Remove the plastic nuts (indicated by a), serrated washers (b) and one screw (c) from both corridor holders. Attach the walls to the holders with the nuts, washers and screw in the same order. Screw the ends of the corridor holders into the corridor lift mechanism. The CatWalk XT logo on one of the corridor walls should be on the outside and the curved ends of both corridor walls should be facing outwards. - Loosely attach two bolts, washers and sliding nuts to the two corridor protection plates. Make sure the sliding nut is positioned with the widest part at the bottom. Insert the nuts into the upper side of the stand. Do not fix them to the profile yet. - This step is easier with two persons. Important: Please be careful when moving the corridor lift mechanism not to get your fingers caught between the hinges. Take the corridor lift mechanism with corridor. Place the corridor on the glass plate so it is centered; the beam of the corridor lift mechanism should be on the side of the corridor walls while the hinge of the corridor lift mechanism should be on the other side of the protection plates. If necessary, move the protection plates sideways so the supports on the hinges fit in the gap of the protection plates. - If the corridor is in the right position (centered with the glass plate), tighten the bolts indicated by the arrows in the picture below until the corridor lift mechanism is firmly attached. Now carefully lift the corridor to its up position. Important: Be careful not to get your fingers caught between the hinges. - Remove the sliding nuts from the bolts attached to the springs. Slide the nuts into the top of the profile and screw the bolt loosely into the nuts. Slide the bolt and nut outwards so the spring is under some tension. First tighten the screw with your hand and then firmly tighten it with one of the hexagonal keys. Important: It is very important that the springs are firmly attached, otherwise they might come loose when you lift the corridor. With the springs firmly attached, lower the corridor to its 'down' position. The corridor should move slowly to its 'down' position even without you holding it. If lowering the corridor goes too fast, lift the corridor to its 'up' position and make the springs a bit more tense. Note: The corridor must touch the glass plate at both sides for stability. If this does not happen, it may be that the magnets on the lift mechanism touch each other before the corridor is all the way down. It may then be necessary to adjust the magnets' position. Role of the Magnets The corridor lift mechanism is provided with magnets. When you move the corridor to the "down" position, the magnets ensure that the corridor lies parallel to the walkway. Adjust the Magnets' Position Sometimes when the corridor is lowered it does not touch the glass plate at one or both ends. To adjust the magnets' position: - Lift the corridor. - Remove the protection plates (if already mounted). - Because you need some space to adjust the magnets, move the corridor wall that is closest to the lift mechanism further away. To do so, loosen the plastic nuts and washers. - Loosen the bolts of the magnets on both sides using a hexagonal key (1–2 turns is enough). - Push the corridor lift mechanism all the way down until the corridor wall touches the glass plate by placing a finger on the lift mechanism and gently pressing it down. - At this point the magnets should be sticking together. Keep the corridor down, and tighten the bolts of the magnets. - Lift the corridor, then lower it again and check that it touches the glass plate. - When the corridor is positioned correctly, put the protection plates back and adjust the corridor walls to their original position. Optionally, install the diffusion plate by screwing it into the upper side of the corridor walls. Start with the screw at the straight (right-hand) end of the corridor wall and then continue towards the other, bent end. Make sure that when lifting the corridor, the lift mechanism does not touch the fixation plates. If necessary, slightly unscrew the bolts on the support angles and adjust the height of the walkway. Install the Illuminated Ceiling - This step requires two persons. Lift the illuminated ceiling and insert one of the supporting rods into the hole in the hinge of the illuminated ceiling on one side of the stand. Next, do this on the other side by moving the ceiling support slightly inwards and then outwards to insert the supporting rod into the hole of the other hinge. - Now firmly attach the ceiling support profiles, aligned with the standing profiles, to the stand. On both sides, move the ceiling support fixation plates upwards and firmly attach them both to the stand and the ceiling support profiles. Phase 4 - Install the Support Profiles and the Camera End result (shown in black) - Remove the sliding nuts from both support profiles. - Insert the nut into the base frame in the gap in the ground plate. Attach the support profile to the stand. You need to turn the head of the support profile to be able to do this. Do not fix the support profile yet. - Insert a sliding nut into the ceiling support profile and firmly attach the support profile to the ceiling support profile. Also, firmly attach the other side of the support profile to the stand. - Attach the camera to the camera holder using the small screws and serrated washer rings (the washers go between the screws and the holder). Note the position of the power and network connection on the camera. Make sure that the camera is attached to the outer side of the camera holder. Attach the camera holder to the camera profile with the two plastic nuts. Phase 5 - Install the Control Unit End result (shown in black) - Loosely attach three sliding nuts, bolts and washer rings to the control unit: one on the left side and two on the right. Next, attach the control unit to the stand. - Attach the metal plug of the camera cable to the cam supply connector (a) on the control unit and the white plug to the camera. When inserting the metal plug into the connector, make sure the small gap on the plug is aligned with the release mechanism on the connector. The plug is fully inserted when you hear a click. To release the plug, push the release mechanism and pull the plug. - Attach the plug of the power supply to the 24V in connector (c). Do not yet connect the power supply to the mains socket. - Take the LED cable with three connectors. Attach the single metal plug of the LED cable to the LED supply connector (b) on the control unit. On the other side, attach the metal plug to the illuminated ceiling and the black plastic plug to the black box attached to the walkway. - Use the 5-m USB cable to connect the Control Unit to the CatWalk XT computer. Important: You can only connect one Control Unit to a CatWalk XT computer. - Connect the camera to the Basler 10GigE Network interface card in the CatWalk PC with the network cable. - Optionally, install the plastic protection caps on the support angles using the small rubber mallet. Turn On the CatWalk System - Make sure all cables are connected. - Connect the power supply to the mains socket and switch on the Control Unit. - The red Power and Busy/alive lights on the Control Unit turn on. The LEDs in the illuminated ceiling and glass plate turn on and the control unit sets the right lighting levels for the LEDs, indicated by the blinking of the Busy/alive light. When the right lighting levels are set, the Power and Busy/alive lights turn off. Important: Wait at least 15 minutes before using the CatWalk system. Important: When connected correctly, all LEDs of the Control Unit are switched off. Source: CatWalk XT 11.0 Assembly Instructions, Noldus Information Technology --- ## CatWalk XT 11 - Assembly - Assembly Instructions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-assembly-assembly-instructions Chapter: CatWalk XT CatWalk System - Overview Pictures Front View Back View Cable Connections - Front Important: Do not connect the TTL control inputs of the CatWalk Control Unit to the PC! Cable Connections - Back Note: The CatWalk computer provided by Noldus has a USB port of type C for connecting the CatWalk system. Dimensions Use the figure below to plan the room available in your laboratory (computer and table are not shown here). Without the goal box, the length of the system is 130 cm (51 3/16"). General Information Components of the CatWalk System - Mechanics – CatWalk stand, walkway, spring-operated corridor, camera profile, support for the illuminated ceiling, illuminated ceiling. - Hardware – Ethernet card, digital camera, network cable, power supply. See also Parts List. Location The room in which the CatWalk system is set up should be darkened (± 1 Lux) to ensure the optimal signal-to-noise ratio. Alternatively, you can also operate CatWalk under red light conditions. Make sure the red light does not shine directly into the camera. How Many People? Two persons are needed for some crucial steps. Tools You Need - CatWalk assembly tools: 4 hexagonal (Allen) keys of 3, 4, 5 and 6 mm, a small Philips head screwdriver and a spirit level, which are included with the CatWalk system. - A small rubber mallet (hammer), not included. Important: First read the CatWalk System - Overview Pictures section for an overview of the complete CatWalk system with labels for the major parts. See also Parts List. Be careful when handling CatWalk parts. Noldus Information Technology cannot be held responsible for any injuries acquired during installation. Please read each step carefully before carrying it out! Source: CatWalk XT 11.0 Assembly Instructions, Noldus Information Technology --- ## CatWalk XT 11 - Assembly - Install The Goal Box URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-assembly-install-the-goal-box Chapter: CatWalk XT Install the Goal Box The goal box is an optional addition to the CatWalk system which can facilitate getting an animal to cross the walkway during training and testing. See the CatWalk XT Help for an example of a protocol for training and testing of rats. To attach the goal box, you need three sets of hexagonal bolts and sliding nuts. The longest and medium bolts can be found in the plastic bag inside the goal box packaging. Step 1: Prepare the Walkway Before installing the goal box, first take all parts from the box. Remove the plastic strip from the right side of the walkway profile. Insert the sliding nut in the left side of the glass plate profile. On the other side, the goal box support beam will be attached to the side of the walkway profile. Step 2: Attach the Support Beam Attach the goal box support beam to the walkway using two hexagonal bolts. For this step you need the two medium bolts. First attach the bolt on the right side. Next, align the sliding nut in the glass plate profile with the hole in the support beam and attach the bolt. Step 3: Attach the Bottom Support Insert two sliding nuts into the standing profile of the CatWalk stand. When you insert the first nut, use the small screwdriver to prevent the nut from falling down to the bottom of the profile. Insert the second nut above the first one. Loosely attach the bottom support to the CatWalk stand so that you are still able to slide it up and down. Use short bolts in this step. Step 4: Attach the Goal Box Remove the plastic nuts from the support connected to the walkway. Make sure that you use the longest bolts available in this step. Attach the goal box to the support. Step 5: Level the Goal Box Loosely fix the plastic nuts. Slide the triangular bottom support upwards until it touches the bottom of the goal box and the goal box is level. Before tightening the plastic nuts, make sure the goal box is shifted as far as possible towards the glass plate. Step 6: Fit the Lid and Inserts Put the goal box lid on top of the goal box. Make sure the bumpers are outside the lid. Depending on the height of the cage you want to keep in the goal box, insert the appropriate number of inserts into the goal box. Parts List The CatWalk system (excluding the computer and its accessories) comes in three separate boxes: one box contains the CatWalk stand, one box contains the walkway, and the third box contains the illuminated ceiling. CatWalk System - Base frame with 2 swivel wheels and 2 regular wheels. - Two large support angles with 4 bolts, 4 sliding nuts, and 4 washers attached to each support angle. - Two profiles with one large and one small support angle each. See the standing profile illustration for reference. - One profile with a hole in the middle (horizontal profile) and one profile with two sliding bolts. - Two black ground plates. - Two fixation plates for the stand with four sliding nuts, bolts, and washer rings each. - Walkway with glass plate and green LED lights located inside the profile. On the left side of the walkway is a box with a connector. Note: The length of the standing profiles may differ from that represented in these instructions. However, this does not affect the assembling procedure. Illuminated Ceiling - Two profiles for the illuminated ceiling, each with a support at the top, a small support angle in the middle, and a ceiling support fixation plate at the bottom. - Illuminated ceiling. - Two spacers and washers for the attachment of the illuminated ceiling. Corridor and Camera Components - Corridor lift mechanism for the spring-operated corridor. - Two protection plates for the corridor lift mechanism. - Four sliding nuts, bolts, and washer rings for the protection plates. - Camera profile with a small support angle at the top, two plastic nuts, and a ruler at the front. - Two support profiles. - Camera holder with two small screws and serrated washers. - Camera and lens (in separate boxes). - Two black corridor walls and one white diffusion plate. - Eight screws for the diffusion plate. - Two corridor holders. Control Unit and Accessories - Six black protection caps to put on the open sides of the support angles. - The CatWalk XT Control Unit. - Three sliding nuts, bolts, and washer rings to attach the control unit to the stand. - Power supply and cables for the control unit, including a camera cable and an LED cable for the green LEDs in the glass plate and the red LEDs in the illuminated ceiling. - USB cable (5 m). - Network cable (10 m). - CatWalk assembly tools: 4 hexagonal (Allen) keys of 3, 4, 5, and 6 mm, a small Phillips head screwdriver, and a spirit level. Goal Box - If you purchased the CatWalk Goal Box, it can be found in a box labeled Goal Box [serial number] (perspex home cage not included). - A separate bag with bolts, spacers, and sliding nuts can be found in the same box. Source: CatWalk XT 11.0 Assembly Instructions, Noldus Information Technology --- ## CatWalk XT 11 - Carry Out Data Acquisition - 5.2 Carry Out Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-carry-out-data-acquisition-52-carry-out-data-acquisition Chapter: CatWalk XT 5.2 Carry Out Data Acquisition After you have prepared the walkway, you are ready to start data acquisition. During acquisition, CatWalk XT uses the run criteria you have specified in the Experiment Settings. Start Data Acquisition - Do one of the following: - In the Experiment Tasks window, click Open Acquisition. - Choose Acquire > Open Acquisition. - In the Experiment Explorer, under Acquisition, right-click a trial and select Acquire Runs. - Under Trial Selection, select a trial from the list. When you have not defined one or more trials in the Trial List, select Create New Trial from the list or go to the Trial List to define trials. Lower the illuminated ceiling gently; if you do this too roughly, it can make the corridor walls shake which can accidentally set off acquisition after you have clicked the Start Acquisition button. Do not lift the illuminated ceiling after you have clicked the Start Acquisition button, as this results in the acquisition of a lot of data and a high processing load. - Click the Snap Background button to snap a background image of the empty, clean walkway. You cannot start acquisition before you have snapped a background image. You can view the background image in the Acquisition Settings by choosing Setup > Acquisition Settings and clicking the View Background Image button. - Click Start Acquisition or press Page Up. The status changes to Waiting for run to start. - Optionally, check the walkway by pressing Validate Walkway. A dialog showing the full walkway appears, indicating where the corridor walls are detected. If the corridor walls are not parallel to the walkway or to each other, a warning appears. If everything is acceptable, a green message Walkway looks good appears. - Put the animal into the corridor from the side. Acquisition starts automatically as soon as the animal's contour is detected. The status changes to Recording Run#. As soon as the animal disappears from view, the status changes to Waiting for run to start. - If you have specified in the run criteria of the Experiment Settings to acquire more than one compliant run, take the animal out of the corridor and put it back in on the other side, or let it turn around for the next run. Stop Data Acquisition - You can manually stop data acquisition by clicking the Stop Acquisition button or by pressing Page Down. - Acquisition stops automatically as soon as the set number of compliant runs has been acquired. What Next? When the set number of compliant runs has been acquired, the Acquisition Finished Tasks window opens. You can now select: - Acquire Next Trial – This is the trial listed next in the Trial List. - Acquire New Trial – This creates a new trial that you can acquire. - Classify Runs – This takes you to the Classification window where you can classify acquired runs. - Review Runs – To inspect acquired runs. Acquired Run List The Acquired Runs list shows the acquired runs with the following variables: - Run – The run number. - Start – The start date and time of the run. - Duration – The total duration of the run. - Compliant – A run is marked compliant or non-compliant with the run criteria. When you hover over the non-compliant icon, information is displayed about why the run is non-compliant. The run criteria become read-only when you have acquired a run. - Direction – The walking direction of the animal. If the animal turns around, the direction cannot be determined. - Run Average Speed – The speed of the recorded run. - Run Maximum Variation – The maximum variation in running speed of the recorded run. - Camera Gain – The Camera Gain value from the Detection Settings. - Green Intensity Threshold – The Green Intensity Threshold value from the Detection Settings. Depending on your Run Settings in the Acquisition Settings, runs that are aborted or do not meet the run criteria are kept or discarded. A run stops automatically: - When the run duration exceeds the maximum set in the run settings. - In any case when run duration exceeds 60 seconds. This is indicated for that run in the Acquired Runs list. Acquisition stops automatically: - When the set number of compliant runs has been acquired. - When not enough internal memory is available. This can occur, for example, when you acquire a number of long runs (20–30 seconds) in a row with short time between runs. In this case, CatWalk XT needs to both process and acquire long runs, which can cause the internal memory to overflow. Acquisition Status The status during acquisition can be: - Waiting for background snapshot of empty walkway to be taken – Press the Snap Background button. You can view the snapped background in the Acquisition Settings. - Ready for acquisition – Press the Start Acquisition button. - Waiting for run to start – Recording starts automatically as soon as the animal appears in the video image. - Recording Run[#] – A run is being recorded and acquisition stops automatically as soon as the animal has completely disappeared from the video image. - Camera connection lost, trying to restore the connection – If the connection is lost, acquisition is stopped. Acquisition can only be resumed after the connection has been restored. - Waiting for animal to leave the walkway – This status message is shown in the following cases: - The maximum run duration has been exceeded while the animal is still on the walkway. - The animal has left the walkway but has left some faeces or urine so the run has not been stopped. --- ## CatWalk XT 11 - Carry Out Data Acquisition - 5.3 Acquired Runs URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-carry-out-data-acquisition-53-acquired-runs Chapter: CatWalk XT 5.3 Acquired Runs Review a Run - Under Video, from the View list, select a run. - To replay a run, press the Play button. Options: - Select a playback speed from the list. - When you press the Pause button, the video pauses at its current position. - You can move the video forward or backward one frame by using the Play Forward One Frame or Play Backward One Frame button. You can keep them pressed to move through the run frame by frame. Note that the time between two subsequent frames is 1/100 second. - When you press the Stop button, the video jumps to the beginning. - When the run is paused or stopped, you can scroll through the video using the slider. - A run plays continuously unless you turn off the Repeat button. Delete Runs Important: Deleting runs cannot be undone. We recommend making a backup of your experiment before deleting runs. Delete a Single Run - Select the run you want to delete in the Acquired Runs list at the bottom of the screen. The currently active run (indicated in bold and blue in the Experiment Explorer) cannot be deleted. From the View list, select Live Video to deactivate the run. - Click the Delete Run(s) button. Alternatively, right-click an inactive run in the Experiment Explorer and select Delete. Delete Multiple Runs - Select the runs you want to delete in the Acquired Runs list at the bottom of the screen. The currently active run (indicated in bold and blue in the Experiment Explorer) cannot be deleted. From the View list, select Live Video to deactivate all runs. - To select multiple consecutive runs, click the first run you want to delete, press and hold the Shift key, and click the last run you want to delete. - To select multiple individual runs, press and hold the Ctrl key and click the runs you want to delete. - Click the Delete Run(s) button. When you next acquire an additional run in this trial, the run number continues from the previous number of acquired runs. For example, if you have three runs (Run 1, Run 2, Run 3) and you delete Run 3, the next acquired run will be labeled Run 4. 5.4 Acquisition Status Icons In the Experiment Explorer, small Acquisition Status symbols allow you to check the acquisition status of trials and runs. Acquisition Status Icons In the Experiment Explorer, the following symbols allow you to check the acquisition status of trials and runs. Trials - Green Check Mark – Trial#: The minimum number of compliant runs (as set in the Experiment Settings) have been acquired for this trial. - Orange Check Mark – Trial#: The minimum number of compliant runs have not been acquired for this trial. Runs - Green Round Icon – Run#: This run meets the run criteria set in the Experiment Settings. - Orange Round Icon – Run#: This run does not meet the run criteria. Data Selection Status For each trial and run it is also indicated whether it contains steps which are included in the currently active Data Segmentation profile. - Trial: The number of runs within the trial that contain steps included in the current data selection is shown behind the trial name. For example, a trial may show 3 runs which all contain steps included in the currently active Data Segmentation profile. - Run: An asterisk (*) behind a run indicates that the run contains steps which are included in the data selection. What Next? - You can acquire another run for the current trial by selecting Live Video from the View list under Video. - You can acquire runs for another trial by returning to the trial selection step. - You can continue to classification by clicking Classify Runs in the bottom-right corner or by choosing Acquire > Classify Runs. Source: CatWalk XT 11.0 Reference Manual - Carry Out Data Acquisition, Noldus Information Technology --- ## CatWalk XT 11 - Carry Out Data Acquisition - Carry Out Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-carry-out-data-acquisition-carry-out-data-acquisition Chapter: CatWalk XT Carry Out Data Acquisition 5.1 Prepare the Walkway Before you acquire data you need to make sure that: The Glass Plate Is Clean Lift the corridor. Use a soft cloth or tissue to remove droppings, urine or other dirt from the glass plate. You can use a proprietary glass-cleaning fluid to further clean the glass plate. Experience from CatWalk users has shown that water with some vinegar added or a 70% alcohol solution are also effective in cleaning the glass plate. The Camera Is at the Correct Position The distance of the camera to the glass plate determines how much of the walkway is visible. In order to get 5-6 step cycles per run, you should see about 45 cm of the walkway for mice and about 70 cm for rats. Try this out with one or two animals to make sure you get the appropriate camera position. If you change the position of the camera, you need to redefine the walkway and re-calibrate the walkway (see Set Up the Walkway). Also make sure to focus the camera. The Corridor Is Put in Place Make sure the middle of the corridor is positioned in the middle of the glass plate. Adjust the width of the corridor to match the animal's size. The Illuminated Ceiling Is Lowered When you did not install the diffusion plate on top of the corridor walls, it is useful to leave a gap between the top of the corridor and the illuminated ceiling so you can put an animal into the corridor from the top. When you adjust the vertical position of the illuminated ceiling, always check in the Define Walkway window that the red LED lights of the illuminated ceiling completely cover the defined area. --- ## CatWalk XT 11 - Classify Runs - Classify Runs URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-classify-runs-classify-runs Chapter: CatWalk XT Classify Runs 6.1 Classify the Paw Prints To open the classification screen, do one of the following: - In the Experiment Tasks window, click Classify Runs. - Choose Acquire > Classify Runs. - In the Experiment Explorer: - Right-click a trial (containing runs) and select Classify Runs. - Right-click a run and select Classify. - Double-click a run. Before you start classifying paws, first check the quality of the detected paw prints by playing back the runs. If necessary, you can adjust the Green Intensity Threshold to increase the quality of the paw prints or to remove noise. If you use the Automatic Footprint Classification module, there are two main classification scenarios: - You only want to label paw prints – Use automatic classification to let CatWalk label the paw prints. Next, use manual classification to label paw prints that CatWalk was not able to classify automatically. - You want to label both paw and non-paw prints – First, manually label the non-paw prints. Next, use automatic classification to let CatWalk label the paw prints. Adjust the Green Intensity Threshold The Green Intensity Threshold is set in the Detection Settings before acquisition. It is the minimum pixel intensity detected by CatWalk; all pixels below this minimum are not processed. In CatWalk XT 11, you can increase or decrease the Green Intensity Threshold of a run before classification, after acquisition. You may need to adjust the Green Intensity Threshold when the value set in Detection Settings is either too low or too high. When it is too low, a lot of noise appears (for example, part of the animal's body). When it is too high, paws are not detected completely (for example, toes or parts of the sole are missing). To adjust the Green Intensity Threshold: - In the Classification screen, under Video, click the Adjust the Green Intensity Threshold button on the right. The Adjust the Green Intensity Threshold window appears and shows the following: - Video window – Displays prints based on the Current Green Intensity Threshold, which initially matches the Original Green Intensity Threshold set in Detection Settings. - Original Green Intensity Threshold – The value set in Detection Settings. - Current Green Intensity Threshold – The value you can adjust here. - Show filtered out signals – When selected, prints filtered out by the Current Green Intensity Threshold value are displayed in red. - Move the slider to the desired value. Increasing the threshold removes prints; decreasing it adds prints. Clicking to the left or right of the slider on the slider bar moves it in steps of 5. When adjusting the threshold for a run recorded with a previous version of CatWalk XT, the lowest possible value is the value with which the run was originally acquired. - When the Current Green Intensity Threshold has the desired value, click OK. The run is processed with the new value, which may take a few seconds depending on run length and the threshold set. - You can now classify the run with the new Green Intensity Threshold value. Please note that changing the Green Intensity Threshold affects Run Statistics. We recommend using the same Green Intensity Threshold for all runs within one experiment to ensure results can be compared between runs. Automatic Classification You need the Automatic Classification module to classify paw prints automatically. With the base version of CatWalk XT 10, labels can only be assigned manually. The Automatic Footprint Classification (AFC) module uses the body contour of the animal to determine the position of the paw prints. Performance of Automatic Classification Automatic Footprint Classification cannot be guaranteed to work in all situations. Tests have shown that the AFC module gives good results when used with an animal walking with a normal gait across a clean glass plate. It is likely to function less well when the glass plate is dirty, resulting in background noise, or when the animal touches the glass plate with body parts other than the paws. How to Improve Automatic Classification The following ground rules apply for the AFC module: - Minimize background noise. Dim ambient light as much as possible and ensure the glass plate is clean before acquisition. If noise persists in the video image, reconfigure the Detection Settings. - Remove junk prints. If acquired runs contain a lot of noise, increase the Green Intensity Threshold before classification. If noise prints remain, manually label them as Junk and remove them. - The animal should walk in a straight line and in one direction. If the animal turns around during a run, AFC will not work. Place corridor walls as close together as possible without restricting the animal, to encourage straight runs. - The animal should not rear during a run. Install the diffusion plate on top of the corridor walls to help prevent this. - The animal should only make contact with the glass plate with its paws. If other body parts contact the glass plate, manually label those prints before running the AFC. - The corridor should be positioned in the middle of the glass plate. Center the corridor over the camera so that the animal, on average, walks along the middle line of the video image. - Minimize the area of the video image covered by corridor walls, as walls may interfere with detection of the body contour. Classification Settings Choose Setup > Classification Settings. In the Classification Settings window, you can select the following options: - Reset all assigned labels when applying the AFC – Do not select this option if you have already manually labeled part of a run and want to keep those labels. - Only assign a label when the Max Intensity is higher than... – Noise such as dirt on the glass plate has a much lower Max Intensity than paw prints. Selecting this option with the default value of 100 causes most noise prints to be ignored. Automatic Classification Procedure - Under Trial & Run Selection, select a trial and one of the runs in that trial, or click the Previous/Next button to navigate to the trial and run you want to classify. The trial list displays animal ID, time point, acquisition status, and classification status. The run list displays compliant/non-compliant status and classification status. - Click the Auto Classify button to automatically classify the complete run. After automatic classification, do one of the following: - If the AFC module classified the complete run, the Classification Finished Tasks window appears. Select one of the options in this window to continue. - If some prints could not be classified, the video automatically jumps to the first frame with an unlabeled print. Continue manually labeling the unlabeled prints. - Review the run and, if necessary, correct any errors. --- ## CatWalk XT 11 - Classify Runs - Classify Toes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-classify-runs-classify-toes Chapter: CatWalk XT Classify Toes Interactive Footprint Measurements Classification of toes is done in the Interactive Footprint Measurements. Toe classification of the hind paws (by measuring the Toe Spread, Intermediate Toe Spread, and Print Length) can be used to calculate the Sciatic Functional Index, Peroneal Functional Index, and Tibial Functional Index. The Sciatic Functional Index is commonly used as a tool for the evaluation of the recovery of the sciatic nerve. You first need to label a paw print before you can classify its toes. You need the Interactive Footprint Measurements module to be able to classify toes. Choose Acquire > Interactive Footprint Measurements. In the Interactive Footprint Measurements, you can measure the following: - Toe Spread – This is the distance between the first and fifth toe of a hind paw. - Intermediate Toe Spread – This is the distance between the second and fourth toe of a hind paw. - Manual Print Length – This is the distance between the third toe and the heel of a hind paw. This parameter is different from Print Length, which is the length (in the horizontal direction) of the complete print. - Paw Angle Body Axis – This is the angle of the paw relative to the orientation of the body axis of the animal. - Paw Angle Movement Vector – This is the angle of the paw relative to the direction of movement of the animal. The Movement Vector is a more accurate measure of the actual walking direction of the animal. The Movement Vector is calculated by performing linear regression of the center-of-gravity of the body contour in the current frame and in the three preceding frames. Procedure - Choose Acquire > Interactive Footprint Measurements. - Under Trial Run Selection, select a classified trial and run from the list, or click the Previous/Next buttons to navigate to the trial and run you want to measure. - Under Footprint Type Selection, select the paw prints you want to display. By default, both hind paws are selected. - Click the paw you want to classify. The Footprint view displays a zoomed-in picture of the complete paw. The paw print consists of all frames of that paw, whereas the Body Axis view only shows the frame at Max Contact; therefore, the paw prints can be different. The Body Axis view shows the frame with the Max Contact of the corresponding paw with the body contour and body axis of the animal. It also shows the Movement Vector as a red arrow. - In the Footprint view, you can measure the following parameters: - Toe Spread – This is the distance between the first and fifth toe of the hind paw. To measure Toe Spread, click as close as possible to the center of the first toe, move the mouse cursor as close as possible to the center of the fifth toe and click, and next select Toe Spread from the menu. - Intermediate Toe Spread – This is the distance between the second and fourth toe of a hind paw. To measure the Intermediate Toe Spread, click as close as possible to the center of the second toe, move the mouse cursor as close as possible to the center of the fourth toe and click, and next select Intermediate Toe Spread. - Manual Print Length – This is the distance between the center of the third toe and the heel of a hind paw. To measure Print Length, click as close as possible to the center of the third toe, move the cursor as close as possible to the heel of the paw print and click, and next select Print Length from the menu. If your animals do not show the heels in the Footprint view, draw the line from the third toe to between the proximal pads because that is in the direction of the heel, and stop where the print ends. Be consistent with this definition across the animals. When you next measure the third parameter, it is automatically assigned the remaining label. - Paw Angle Body Axis – This is the smallest angle between the Print Length line and the white line representing the body axis of the animal as displayed in the Body Axis view. Classify Runs Paw Angle Movement Vector The Paw Angle Movement Vector is the smallest angle between the Print Length line and the red line representing the direction of movement of the animal as displayed in the Body Axis view. Classifying Paws and Toes - Under Parameters, select Show parameter values to display the values of the parameters. - Optionally, in the Body Axis view, you can change the orientation of the body axis by moving one of the sides of the body axis line to a new position. When you do this, the Paw Angle Body Axis, displayed under Parameters, is instantly updated. - Go back to the previous step to proceed with the next paw and repeat the steps for all paws you want to classify. - Under Functional Index Settings, select the experimental paw from the list for calculation of the Sciatic Functional Index. - Click OK when you are finished with classifying toes for the current run. In the top view with all the paw prints, a print with classified toes has a green border, and a print with unclassified toes has a white border. Correct Measurements Remove a Measurement In the Footprint view, click a line and select Remove. Move a Line Both in the Footprint and Body Axis view, click on one of the end points and drag it to the new position. Classification Status Icons In the Experiment Explorer, the following symbols allow you to check the classification status of trials and runs. Trials The check mark at the top indicates whether the trial is compliant. The check mark at the bottom indicates whether the trial contains classified runs. Runs The check mark at the bottom indicates whether the run has been classified. - Orange check mark below the compliant trial check mark: Not all runs in this trial were completely classified. - Green check mark below the non-compliant trial check mark: All runs in this trial were completely classified. - One green check mark: This trial has both been completely acquired and classified. - Orange check mark below the green compliant check mark (Run): The run has been partially classified. - Green check mark below the green compliant check mark (Run): The run has been completely classified. Source: CatWalk XT 11.0 Reference Manual - Classify Runs, Noldus Information Technology --- ## CatWalk XT 11 - Classify Runs - Manual Classification URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-classify-runs-manual-classification Chapter: CatWalk XT Manual Classification - Under Trial & Run Selection, select a trial and one of the runs in that trial, or click the Previous/Next button to navigate to the trial and run you want to classify. The associated video opens with the video frame that contains the first unlabeled print. - Do one of the following: - Continue at the next step to start assigning labels. - Move the video to a new position by using the playback buttons (see page 87 for how to move through the video). - Optionally, zoom in to get a better view of the prints (see page 84 for how to zoom in and out in the Video window). - To label a print, do the following: - Using the mouse, select a rectangle or draw a larger box around one of the white rectangles and release the mouse button. - Select a label from the menu. - Assign a label to other unlabeled prints in this frame until there are no unlabeled prints left or you have labeled all relevant prints in this frame. The labeled print appears under Results, both in the Print View and Timing View of the Graphical tab and in the Numerical tab. The following labels can be used: - Paws: RF = Right Front, RH = Right Hind, LF = Left Front, LH = Left Hind - Hip and Knee: RM = Right Hip, RK = Right Knee, LM = Left Hip, LK = Left Knee - Other body parts: NO = Nose, AB = Abdomen, TA = Tail, GT = Genitalia - The video now automatically moves to the next frame with unlabeled prints that do not overlap with already labeled prints. You can now do one of the following: - Repeat the procedure described in step 3 above. - Click the Jump to Next Unlabeled Print button or the Jump to Previous Unlabeled Print button to go to a next or previous specific unlabeled print and repeat the procedure described in step 3 above. You can speed up labeling prints by drawing a box around both labeled prints and unlabeled prints that belong to the same paw. The unlabeled prints are automatically assigned the same label. - Continue until you have labeled all relevant prints in the run. If you labeled the complete run, the Classification Finished Tasks window appears. To continue, select one of the options in this window. Zoom In/Out in the Video Window During classification, you can zoom in in the Video window to get a better view of the paw prints. The available zoom factors are: 1x, 2x, 3x, 4x, and 5x. To zoom, do one of the following: - Click the Zoom In button or the Zoom Out button. - To zoom in, press Ctrl+'+' (numeric keyboard); to zoom out, press Ctrl+'-' (numeric keyboard). - To jump to the normal view, press Ctrl+'0' (zero on the numeric keyboard). Combine Stances Occasionally, a print in a frame may not be detected. As a result, the stance (that is, contact of a paw with the glass plate during one paw placement) of a specific paw is subdivided into two separate stances. These separated stances can be manually combined. If you have a lot of subdivided stances, it might be that your Green Intensity Threshold was set too high. Try decreasing the Green Intensity Threshold before proceeding with combining stances. Procedure To combine two stances, right-click on the first stance and select Combine with Next. The stances are combined and the new stance is considered to be a single stance in both the Visualization and the Run Statistics. CatWalk is not able to calculate the Stand Index for the new stance when the Max Contact point is in the first stance. The menu also provides an option to exclude a stance from analysis. This option is used to mark the stance as junk. Label Junk When a print is displayed that you are sure is not part of the animal's body (for example, a dropping or dirt from the animal's body) or is irrelevant, you can label it as Junk. You do this in exactly the same way as assigning one of the other labels. Prints labeled as Junk are not displayed in the Print View and Timing View. If you have a lot of noise prints, it might be better to first increase the Green Intensity Threshold. I Have a Lot of Prints That Are Junk In cases where a frame contains a lot of junk, you can do the following to speed up labeling: - Label all relevant prints in the frame. - Click the UN = Junk button (alternatively, press the '~' key or the '-' (en dash) key on your keyboard) to label all remaining prints in the frame as Junk. I Want to Permanently Remove Prints Labeled as Junk When you have labeled prints as Junk, they still appear in the Video window when you replay a run. If you do not want Junk prints to be displayed, you can permanently remove them: - Carry out the two steps described under I Have a Lot of Prints That Are Junk above. - Click the Remove All Junk Prints button. Removing all Junk prints cannot be undone. The only way to restore prints is to manually add a print in each frame from which a Junk print was removed. Add Paw Prints You may want to add a print when there is no rectangle around a print whose intensity exceeds the Green Intensity Threshold. This can occur in the following situations: - You have manually removed a print labeled as Junk. - In the Acquisition Settings, you selected the option Discard Incomplete Prints at the Start and End of a Run, which results in no rectangle being drawn around the print. Procedure - Draw a box around the print. - From the menu, select Add Print. --- ## CatWalk XT 11 - Classify Runs - Numerical Results URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-classify-runs-numerical-results Chapter: CatWalk XT Numerical Results The Numerical Results sheet contains for each labeled print: - Print – The full label of the print. - Image – A picture of the full print. A larger version of this picture and other full paw prints from the current video frame are also displayed next to the Video window. You can use these pictures to detect possible classification errors. - Initial Contact (s) – The time in seconds since the start of the run that the print first makes contact with the glass plate. - Stand (s) – The duration of contact with the glass plate of the print. - Max Contact At (s) – The time in seconds since the start of the run that the largest part of the print makes contact with the glass plate. - Max Contact Area (Distance Unit²) – The surface area of the print at Max Contact expressed in the Distance Unit you selected in the Preferences. - Max Intensity – The print's maximum intensity. - Mean Intensity – The print's mean intensity. - Print Length (Distance Unit) – This is the length (horizontal direction) of the complete print expressed in the Distance Unit you selected in the Preferences. - Print Width (Distance Unit) – This is the width (vertical direction) of the complete print expressed in the Distance Unit you selected in the Preferences. - Print Area (Distance Unit²) – This is the surface area of the complete paw print expressed in the Distance Unit you selected in the Preferences. When you click a row in the Numerical Results table, the video jumps to the corresponding frame. When you play back the run, a blue hairline indicates the position of the run in the Video window. Correct Errors The following errors can occur: - Labeling Error – A print is assigned an incorrect label. For example, left and right are swapped or the animal's nose touching the glass plate is labeled as one of the front paws. - CatWalk Error – When an already labeled print overlaps with a subsequent unlabeled print, CatWalk automatically assigns the same label to the unlabeled print. This results in two different paws with the same label. - Print Error – Two prints that are not part of the same paw are included in the same rectangle. This can occur, for example, when noise or another part of an animal's body is included in the rectangle around a paw print. Labeling Error In some cases during labeling, a wrong label was assigned to a print. The Graphical Results tab can help you in detecting errors. For example, when a print was labeled as Right Front while it should have been Left Front, this becomes visible in the Timing View. To correct a labeling error, do the following: - Click the incorrectly labeled print in the Timing View to jump to the first frame of the corresponding print in the video image. - Draw a box around the incorrectly labeled print and from the menu select Reset. - Now draw a box around the unlabeled print and select the correct label, or draw a larger box around the unlabeled print and the labeled prints it belongs to. CatWalk Error A CatWalk error occurs when the same label is assigned to two different paws visible in the same frame. For example, when a paw is placed on the glass plate at the same position as a previous other paw. A CatWalk error is automatically detected by the program and is displayed in a list in the Video section. To correct a CatWalk error: - Select an error from the error list. - Click the rectangle of the incorrectly labeled print and from the menu select Reset. As a result, the print is reset and is now unlabeled. - Now assign the correct label to the appropriate print. The relabeled print now has the correct label and the error is removed from the error list. - If necessary, repeat steps 1 to 3 for the other errors. Print Error A Print error occurs when noise prints or another part of an animal's body is included in the rectangle around a paw print. For example, when an animal's abdomen touches the glass plate, part of the abdomen can be included in the rectangle of one of the hind paws. You might be able to prevent Print errors by increasing the Green Intensity Threshold. To correct a Print error, do the following: - Right-click the rectangle and select Remove Print. - If necessary, scroll back to the frame in which you removed the print. - Draw a box around the paw print and, from the menu, select Add Print. - Assign the correct label to the print. --- ## CatWalk XT 11 - Classify Runs - Review the Runs During Classification URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-classify-runs-review-the-runs-during-classification Chapter: CatWalk XT Review the Runs During Classification You can review runs using the following: - Video window: move through the video and inspect the assigned labels. - Graphical Results: view labeled prints and the time-based gait diagram. - Numerical Results: view a number of basic parameters for each print. Video Window Review a Run - Under Trial & Run Selection, select a (partially) classified trial and a (partially) classified run. - To replay a run, press the Play button: - You can select a playback speed from the list. - When you press the Pause button, the video pauses at its current position. - You can move the video forward or backward one frame using the Play-Forward-One-Frame or Play-Back-One-Frame button, respectively. - When you press the Stop button, the video jumps to the beginning. - When the run is paused or stopped, you can scroll through the video using the slider. - A run plays continuously unless you turn off the Repeat button. When you right-click the Video window, a menu appears with the following options: - Show Labels: when not selected, the labels are hidden. - Show Rectangles: when not selected, the rectangles are hidden. - Show Overlay Text: the overlay text at the top-left corner displays the run number, the time of the current video frame, the current frame number, and the total number of frames. When not selected, the overlay text is hidden. Hiding labels, rectangles, and overlay text may be useful to get a better view of the prints. Graphical Results The Graphical Results contains two views. Print View The Print View displays the paw prints and other prints. During labeling, the Print View is constantly updated. The prints are displayed in the same direction as in the Video window. During playback of the run, paw prints and their labels visible in the Video window are highlighted in yellow (or another color that you can select in the Preferences). Print View Options Right-click the Print View to access the following options: - Switch to Normal Color Mode: displays the prints in green of variable intensity on a black background. - Switch to False Color Mode: displays the prints with a color gradient indicating different print intensities (from green = low intensity, to red = high intensity) on a blue background. False Color mode is the default mode. - Switch to Colorized Mode: displays the prints in the colors selected in the Color preferences on a black background. - Show All Prints: when not selected, only the prints visible in the current frame in the Video window are shown in the Print View. - Show Labels: when not selected, all labels are hidden. - Show Rectangles: when not selected, all rectangles are hidden. - Save to File: saves the Print View, as displayed on screen, to an image file (*.png). Copy to Clipboard and Print View Tips To copy the Print View, as displayed on the screen, to the clipboard, use the Copy to Clipboard option. - You can hide the Print View by clicking the title bar. - You can jump to the first frame of a specific print by clicking the print in the Print View (indicated by the mouse pointer becoming a hand when hovering over a print). - If you do not see a color mode option, it means that the Print View is already in that mode. Timing View The Timing View displays the time-based gait diagram of a run. It also displays the contact with the glass plate of other body parts that you have labeled. The Timing View displays the prints from left to right, irrespective of the animal's actual direction of movement. The bars in the Timing View represent the duration of contact with the glass plate (stance or stand) of a paw or other body part. The intervals between bars represent the time a paw was not touching the glass plate (Swing). The vertical, red dotted hairline corresponds to the position of the run in the Video window. When you right-click the Timing View, a menu appears with the following options: - Show All Prints – When not selected, only the four paw prints are shown. - Save to File... – This saves the Timing View, as displayed on the screen, to an image file (*.png). - Copy to Clipboard – This copies the Timing View, as displayed on the screen, to the clipboard. - You can hide the Timing View by clicking the title bar. - You can jump to the first video frame of a specific print by clicking the corresponding bar in the Timing View (indicated by the mouse pointer becoming a hand when hovering over a bar). --- ## CatWalk XT 11 - Classify The Runs URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-classify-the-runs Chapter: CatWalk XT Classify the Runs To open the Classification screen, do one of the following: - From a Tasks window, select Classify Runs. - Choose Acquire > Classify Runs. - In the Experiment Explorer, right-click a trial or run and select Classify. Classification Settings If your license of CatWalk XT includes the Automatic Footprint Classification (AFC) module, you can specify Classification Settings: - Choose Setup > Classification Settings. - In the Classification Settings window, you can select: - Reset all assigned labels when applying the AFC – When selected, all labels that you already have assigned manually are reset when you click the Auto Classify button. - Only assign a label when the max Intensity is higher than – When selected, prints below the specified pixel intensity threshold are not labeled during automatic classification. Adjust the Green Intensity Threshold The Green Intensity Threshold is set in the Detection Settings before acquisition. The Green Intensity Threshold is the minimum pixel intensity that is detected by CatWalk. All pixels below the minimum intensity are not processed by CatWalk XT. You can increase or decrease the Green Intensity Threshold of a run before classification of the paws, after you have acquired the runs. This can be useful when the Green Intensity Threshold was set too high or too low in the Detection Settings. To adjust the Green Intensity Threshold: - In the Classification screen, under Video, click the Adjust the Green Intensity Threshold button on the right. - To adjust the Green Intensity Threshold, move the slider to the desired value. Depending on whether you increase or decrease the Green Intensity Threshold, prints disappear or appear, respectively. - When you adjust the Green Intensity Threshold of a run recorded with a previous version of CatWalk XT, the lowest possible value for the Green Intensity Threshold is the value with which the run was acquired. - Clicking left or right of the slider on the slider bar moves the slider in steps of 5. - When the Current Green Intensity Threshold has the desired value, click OK. The run is now processed with the new Green Intensity Threshold value. Depending on the length of the run and the set Green Intensity Threshold, this can take a few seconds. Classify the Paw Prints You can classify paw prints manually and/or automatically. For automatic classification you need the Automatic Footprint Classification (AFC) module, which is available as an add-on to the base version of CatWalk XT. If you use CatWalk XT with the AFC module, there are two main scenarios: - You only want to classify paw prints – You first run the AFC module (see Automatic Classification below) and next manually label prints that have not been classified (see Manual Classification below). - You want to label both paw and non-paw prints (such as the knee, the hip or the nose) – First, classify the non-paw prints manually (see Manual Classification below) and next let the AFC module label the paw prints (see Automatic Classification below). If this second scenario applies to you, in the Classification Settings the option Reset all assigned labels when applying the AFC must NOT be selected. Automatic Classification - Select a trial/run by doing one of the following: - Under Trial & Run Selection, select a trial and a run from the corresponding lists. - In the Experiment Explorer, right-click a run and select Classify. The corresponding video jumps to the first frame with an unlabeled print (indicated by the label UN). Check that you have selected the correct classification settings. - Click the Auto Classify button. - Review the run and, if necessary, manually classify unlabeled prints and correct errors (see below). Manual Classification - Select a trial/run as described in step 1 of Automatic Classification above. - To label a print, using the mouse, select a rectangle or draw a larger box around one or more of the rectangles that surround a print and release the mouse button. - From the menu, select the appropriate label. As a result, the rectangle around the print becomes green and the new label appears. Repeat steps 2 and 3 until all prints in the frame have been labeled. As a result, CatWalk XT automatically moves to the next frame containing unlabeled prints that do not overlap with already labeled prints. - Repeat steps 2 and 3 until you are finished labeling prints. You can speed up labeling prints by drawing a box around both unlabeled prints and labeled prints that both belong to the same paw. The unlabeled prints are automatically assigned the same label. You can label all remaining prints in a frame as Junk by either clicking the UN=Junk button or by pressing the ~ key or - key (minus sign) on your keyboard. You can zoom in/out the Video window for easier labeling of the paws. Press the Zoom in icon or Ctrl+'+' to zoom in, press the Zoom out icon or Ctrl+'-' to zoom out, and Ctrl+'0' to reset the zoom factor. Combine Two Stances in One Occasionally, a paw print in a video frame is not detected. As a result, the stance (that is, contact of a paw with the glass plate during one paw placement) of a specific paw is subdivided into two separate stances. In CatWalk XT, these separated stances can be manually combined. Tip: If you have a lot of these subdivided stances, it might be that your Green Intensity Threshold was set too high in the Detection Settings. Try to decrease the Green Intensity Threshold before proceeding with combining stances. To combine two stances, right-click on the first stance and select Combine with Next. As a result, the stances are combined and the new stance is now considered to be a single stance, in the Visualization and also in the Run Statistics. Correct Errors To Jump to a Print You can quickly jump to an incorrectly labeled print by doing one of the following: - In the error list, select an automatically detected error. - In the Print View, click the boxed print. - In the Timing View, click the corresponding bar. The video automatically jumps to the first frame of the corresponding print. Relabel a Print - Draw a box around a labeled print, release the mouse button and select Reset. - Draw a box around the now unlabeled print, release the mouse button and select the appropriate label. Relabel a Complete Frame - Click the Reset Frame button. This not only resets the current frame but also the subsequent frames of the current paw prints. - Repeat steps 2 and 3 as described in Manual Classification above until all paw prints have been labeled. Relabel a Complete Run - Click the Reset Run button. - Repeat steps 2 and 3 as described in Classify the Runs above (either manually or automatically) until the run has been labeled. Remove or Add a Print It might be necessary to remove or add a paw print in the following situations: - A hind paw is placed very close to the ipsilateral front paw which has not been completely lifted yet; as a result, CatWalk XT draws one rectangle around the front paw print and the hind paw print while in fact there should be two separate rectangles (one for the front paw and one for the hind paw). - The Green Intensity Threshold in the Detection Settings is set too low and/or the animal touches the glass plate with its abdomen. As a result, the animal's abdomen is added to the print of the hind paws. To correct a situation where prints are incorrectly combined, do the following: - Right-click the rectangle and select Remove Print. Continue to do this for all consecutive frames in which prints are incorrectly included in the same rectangle. - Go back to the first frame in which you removed a print, draw a box just around one of the paws and select Add Print. Do this for all paw prints in this frame. - If all prints have been labeled in the run, the Classification Finished Tasks window might appear. To prevent this window from appearing every time you add a print, select the option Don't show this dialog again during this run's classification session at the bottom of the window. - If the newly added print overlaps with an already labeled print, the same label is automatically assigned to the new print. Otherwise, you need to manually assign a label to the print (see Manual Classification above). - Continue until all prints have been added. Classify the Toes You can classify toes with the Interactive Footprint Measurements add-on module. Toe classification of the hind paws is done by measuring the Toe Spread, Intermediate Toe Spread and Print Length and can be used to calculate the Sciatic Functional Index (SFI). The SFI is commonly used as a tool for the evaluation of the recovery of the sciatic nerve. - Note: You first need to label a paw print before you can classify its toes. - Note: You need the Interactive Footprint Measurements module to be able to classify toes. The following measurements are used in Interactive Footprint Measurements: - Toe Spread – The distance between the first and fifth toe of a hind paw. - Intermediate Toe Spread – The distance between the second and fourth toe of a hind paw. - Print Length – The distance between the third toe and the heel of a hind paw. To classify the toes: - Choose Acquire > Interactive Footprint Measurements. - In the Classification screen, select a classified trial and run from the list, or click the Previous/Next buttons to navigate to the trial and run you require. - Under Footprint Type Selection, select the paws of which you want to classify the toes. - Select the paw print that you want to classify. - In the large Footprint view: - To measure the Toe Spread, click as close as possible to the center of the first toe, move the mouse cursor as close as possible to the center of the fifth toe and click, and next select Toe Spread from the menu. - To measure the Intermediate Toe Spread, click as close as possible to the center of the second toe, move the mouse cursor as close as possible to the center of the fourth toe and click, and next select Intermediate Toe Spread from the menu. - To measure the Print Length, click as close as possible to the center of the second toe, move the cursor as close as possible to the heel of the paw print and click, and next select Print Length from the menu. When you have done two measurements, the third measurement is automatically assigned the remaining label. To remove a line, position the mouse cursor on the line so the cursor becomes a hand icon, click and select Remove. Under Parameters, select the Show parameter values option to display the values. - Under Functional Index Settings at the bottom, select the experimental paw from the list. Viewing Results In the Classification screen, you can view the graphical and numerical results during classification of runs. Graphical Results - Print View – This view displays the paw prints and prints of other body parts. - Timing View – This view displays the time-based gait diagram. The colored bars represent contact with the glass plate of the paws or other body parts. The gait diagram is displayed from left to right, irrespective of the animal's direction of movement. You can quickly jump to the first frame of a print by clicking the corresponding print in either the Print View or Timing View. Tip: Right-click the Print View and choose one of the options to view the footprints in different colors. For example, choose Switch to 'Colorized' mode to display the prints in the preferred colors (File > Preferences > Colors). Numerical Results The numerical results sheet displays a number of basic CatWalk XT parameters for each paw print. When you click on a row in the sheet, the video jumps to the first frame of the corresponding print. The images of complete paw prints are shown in the numerical results sheet; a larger version of these images is displayed next to the Video window. Source: CatWalk XT 11.0 Quick Start Guide, Noldus Information Technology --- ## CatWalk XT 11 - Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-data-acquisition Chapter: CatWalk XT Data Acquisition Acquisition Procedure After snapping a background image of the empty walkway, the user clicks Start Acquisition. CatWalk automatically detects when the animal enters the camera view and begins recording. A run stops automatically when the animal leaves the field of view. Acquired Runs List For each run, the following variables are displayed: - Run number - Start date and time - Duration - Compliance status (with reason if non-compliant) - Walking direction - Run average speed - Run maximum speed variation - Camera gain - Green intensity threshold Acquisition Settings - Auto-Abort — Runs can be automatically aborted if they exceed a set duration. Runs are always stopped at 60 seconds maximum. - Discard Options — Separately configure whether auto-aborted runs, user-aborted runs, non-compliant runs, and incomplete prints at walkway borders are discarded automatically. - Sound Feedback — Auditory beeps (1 = run started, 2 = run stopped, 3 = error) can be enabled or disabled. Run Classification Paw Print Classification - Manual Classification — Users draw boxes around prints and assign labels: Right Front (RF), Left Front (LF), Right Hind (RH), Left Hind (LH), Right Hip (RM), Right Knee (RK), Left Hip (LM), Left Knee (LK), Nose (NO), Abdomen (AB), Tail (TA), Genitalia (GT). Grouping boxes around labeled and unlabeled prints of the same paw speeds up labeling. - Automatic Footprint Classification (AFC) — Optional add-on module. Uses the body contour of the animal to automatically assign paw labels. AFC works best with a clean glass plate, straight uninterrupted runs, and an animal that contacts the glass only with its paws. Manual pre-labeling of non-paw prints before running AFC is recommended. A minimum Max Intensity threshold can be set to filter noise. - Green Intensity Threshold (Per Run) — Can be adjusted before classification to fine-tune paw detection without affecting other runs. Error Correction - Labeling Errors — Reset and re-assign labels using the Print View or Timing View as guides. - CatWalk Errors — Detected automatically when the same label is assigned to two paws in the same frame. Listed in the Video section for correction. - Print Errors — Noise or non-paw body parts included in a paw rectangle can be corrected by removing and re-adding prints. - Combine Stances — Two sub-divided stances of the same paw can be manually combined. Classification Views - Print View — Displays all paw prints in 2D. Available in Normal Color, False Color (intensity gradient green–red), and Colorized modes. Prints can be shown all-at-once or per frame. - Timing View — Time-based gait diagram. Bars represent stance duration per paw; gaps represent swing. Clicking a bar jumps to the corresponding video frame. - Numerical Results — Per-print table with initial contact time, stand duration, max contact time and area, max and mean intensity, print length, width and area. Interactive Footprint Measurements This optional Interactive Footprint Measurement (IFM) module is used for detailed toe measurements on hind paws to calculate functional nerve recovery indices. - Toe Spread (TS) — Distance between the centre of the first and fifth toe. - Intermediate Toe Spread (ITS) — Distance between the centre of the second and fourth toe. - Manual Print Length (PL) — Distance from the centre of the third toe to the heel. - Paw Angle Body Axis — Smallest angle between the Print Length line and the body axis. - Paw Angle Movement Vector — Smallest angle between the Print Length line and the calculated movement direction (linear regression over four consecutive body-contour positions). Data Selection Data Segmentation Profiles A Data Segmentation profile selects the portion of each classified run that meets three criteria: minimum number of consecutive steps, average speed range, and maximum allowed speed variation. Multiple profiles can be created and saved; the default All Data profile includes all classified steps. - Minimum Number of Consecutive Steps — Recommended ≥ 10 (ensures each paw is placed at least twice, enabling calculation of stride-based parameters). - Average Speed Range — Set in distance units per second. - Maximum Allowed Speed Variation — Expressed as percentage deviation from run average speed. - Options to exclude non-compliant runs and/or partially classified runs. The Selected Data Overview shows the proportion of animals, runs, and steps selected per group and time point. Parameter Profiles Parameter profiles allow selection of specific paws and parameters for display in Run Statistics, Group Statistics, and export files. The default All Parameters profile cannot be edited or deleted. Temporal - Contact - Initial Contact At (s) — Time since run start when a paw first contacts the glass plate. - Stand / Stance (s) — Duration of contact of a paw with the glass plate. - Stand Index — Rate at which the paw loses contact with the glass plate (negative value; more negative = faster lift). Requires ≥ 5 frames of stance. - Max Contact At (s) — Time since run start at which the paw reaches maximum contact area (transition from braking to propulsion phase). - Max Contact At (%) — Max Contact At expressed as a percentage of stance duration. Spatial - Contact Area and Intensity - Max Contact Area — Surface area of the paw print at Max Contact At. - Max Contact Max Intensity — Maximum pixel intensity of the print at Max Contact (range 0–255; proxy for weight-bearing). - Max Contact Mean Intensity — Mean pixel intensity of the print at Max Contact. - X Position — Horizontal position of the paw print centre at Max Contact. - Y Position — Vertical position of the paw print centre at Max Contact. - Print Length — Length (horizontal / walking direction) of the complete print. - Print Width — Width (perpendicular to walking direction) of the complete print. - Print Area — Surface area of the complete print (all stance frames combined; ≥ Max Contact Area). Temporal - Intensity - Max Intensity At (s) — Time since run start at which maximum print intensity occurs. - Max Intensity At (%) — Max Intensity At expressed as a percentage of stance duration. - Max Intensity — Maximum intensity of the complete paw print across all stance frames. - Min Intensity — Minimum intensity of the complete paw print. - Mean Intensity — Mean intensity of the complete paw print. - Mean Intensity of 15 Most Intense Pixels — Mean intensity of the 15 highest-intensity pixels of the print. Swing and Stride - Swing (s) — Duration of no contact with the glass plate between two stances. - Swing Speed — Speed of the paw during swing (Stride Length / Swing). - Stride Length — Distance between successive placements of the same paw (centre-to-centre at Max Contact). - Step Cycle (s) — Time between two consecutive Initial Contacts of the same paw (Stand + Swing). - Duty Cycle (%) — Stand expressed as a percentage of Step Cycle. Source: CatWalk XT 11.0 Technical Specifications, Noldus Information Technology --- ## CatWalk XT 11 - Export Data, Results And Video URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-export-data-results-and-video Chapter: CatWalk XT Export Data, Results and Video Tip: To easily find your export files, in the Export window click Open Output Folder, then click Export. Export Run Data Export the raw print information for each frame of one or more runs. - Choose Analyze > View Run Statistics. Under Trial & Run Selection, select a trial and a (partly) classified run. - Choose File > Export > Run Data. - Select the run(s) you want to export, and choose the export file name and folder. Export Run Statistics Export the parameters displayed in the Summary sheet of the Run Statistics screen. Each run is represented by a single row in the export file. - Choose Analyze > View Run Statistics. Under Trial & Run Selection, select a trial and a run. - Choose File > Export > Run Statistics. - Select the runs, parameters and statistics you want to export, and choose the export file name and folder. Export Trial Statistics Export the combined parameters of runs within a trial. Each trial is represented by a single row in the export file. - Choose Analyze > View Run Statistics. Under Trial & Run Selection, select a trial. - Choose File > Export > Trial Statistics. - Select the trials, parameters and statistics you want to export, and choose the file name and folder. Export Group Statistics Exports the results per treatment group × time point combination, and corresponding charts. - Choose Analyze > View Group Statistics and Charts. - Choose File > Export > Group Statistics or click the export button. - Choose the export file name and folder. Export the Group Charts - Choose Analyze > View Group Statistics and Charts. - Choose File > Export > Charts to export all charts to a PDF file, or right-click a chart and select Save to File. - Choose the export file name and folder. Export Run Visualizations Export a video of one or more run visualizations. - Choose Analyze > View Run Visualizations, then File > Export > Run Visualizations. - Select the visualizations you want to export. Under Output, select the playback speed of the exported video. Export a Run Video - Choose Acquire > Classify Runs, then File > Export > Run Video. - Select whether you want to export labels, rectangles, time and frame information. - Under Output, select the playback speed of the exported video. Source: CatWalk XT 11.0 Quick Start Guide, Noldus Information Technology --- ## CatWalk XT 11 - File and Profile Management - 8.3 Profiles URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-file-and-profile-management-83-profiles Chapter: CatWalk XT 8.3 Profiles This section applies to Experiment Setup profiles, Detection Settings profiles, Data Segmentation profiles and Parameter profiles. Create a Profile - Do one of the following: - In the Experiment Explorer, right-click Experiment Setup Profiles, Detection Settings Profile, Data Segmentation Profiles or Parameter Profiles, and select Add New Profile. - Choose Profiles > Experiment Setup Profile, Detection Settings Profile, Data Segmentation Profile or Parameter Profile > New. - Enter the name of the new profile and click OK. Open a Profile Do one of the following: - In the Experiment Explorer, right-click a profile and select Open. - Choose Profiles > Experiment Setup Profiles, Detection Settings Profile, Data Segmentation Profiles or Parameter Profile > Open, select a profile from the list and click OK. Rename a Profile You cannot rename the All Data Segmentation profile and the default All Parameters Parameter profile. - In the Experiment Explorer, right-click a profile and select Rename. - Type the new name and press Enter. Duplicate a Profile - In the Experiment Explorer, right-click a profile and select Duplicate. - Type the new name and click OK. Activate a Profile To activate a profile, in the Experiment Explorer, right-click a profile and select Set as Active. Delete a Profile You cannot delete an active profile. You also cannot delete the default profile. To delete a profile, do one of the following: - In the Experiment Explorer, right-click a profile and select Delete. - Choose Profiles > Experiment Setup Profile, Detection Settings Profile, Data Segmentation Profile or Parameter Profile > Delete, select a profile from the list and click OK. When you delete all Detection Settings profiles, a new default Detection Settings profile is created automatically with default settings. 8.4 Export Data and Results Export the Run Data The purpose of this export is to export the raw print information for each video frame of a run. Each row corresponds to one video frame (100 per second). If your experiment contains one or more runs with missing or corrupt data, you get an error message when you try to export run data. Delete the runs listed in the error message and then export run data. - In the Visualization or Run Statistics screen, under Trial & Run Selection, select a trial and a run. - Choose File > Export > Run Data. - In the Export Run Data window, you can export run data for: - Active run (Run#) – This exports raw data from one run to an Excel file. - All runs from active trial (Trial#) – This exports raw data from all runs in Trial# to an Excel file; each run is saved in a separate sheet. Under Output, choose the File name and export Folder. - Click Open Output Folder and then Export. --- ## CatWalk XT 11 - File and Profile Management - File and Profile Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-file-and-profile-management-file-and-profile-management-Yev Chapter: CatWalk XT File and Profile Management Procedure - In the Classification or Run Visualizations screen, under Trial & Run Selection, select a trial and a run. - Choose File > Export and Run Video. - In the Export Run Video window, select to export: - Labels – When selected, the labels for all prints are exported. - Rectangles – When selected, the rectangles around prints are exported. - Time and Frame Information – When selected, the overlay text showing the run number, time and frames is exported. - Under Output, select a playback Speed, File name and export Folder. - First, click Open Output Folder and then Export. The run video is exported in uncompressed AVI format and plays back at the selected speed. You do not need a codec to play the run video. Source: CatWalk XT 11.0 Reference Manual - File and Profile Management, Noldus Information Technology --- ## CatWalk XT 11 - File and Profile Management - File and Profile Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-file-and-profile-management-file-and-profile-management-fkY Chapter: CatWalk XT File and Profile Management Run Data Parameters For each frame, the following parameters are displayed: - Experiment – Contains the experiment name. - Group – The name of the treatment group. - Animal – The animal ID. - Time Point – The time point of acquisition of the run. - Trial – The trial ID. - Run – The run ID. - Frame – The frame number. - Time – The time stamp of the frame. For each paw print the following parameters are displayed for each frame: - X – The X-coordinate of the center-point of the surrounding print rectangle. - Y – The Y-coordinate of the center-point of the surrounding print rectangle. - PrintLength – The length (in X-direction) of the surrounding print rectangle given in the Distance Unit selected in the Preferences. - PrintWidth – The width (in Y-direction) of the surrounding print rectangle given in the Distance Unit selected in the Preferences. - PrintArea – The size of the print (including all pixels with an intensity value greater than zero). - MinIntensity – The minimum intensity found in the print (intensity values of zero excluded). - MaxIntensity – The maximum intensity found in the print. - MeanIntensity – The mean intensity found in the print (intensity values of zero excluded). Export the Run Statistics Aim To export the values displayed in the Summary sheet of the Run Statistics screen. Each run is represented by a single row in the export file. You can select the parameters to be exported. Note: If your experiment contains one or more runs with missing or corrupt data you get an error message when you try to export Run Statistics. Delete the runs listed in the error message and then export Run Statistics. Export Run Statistics for the Current Run Choose Analyze > View Run Statistics, select a run, then right-click the sheet you want to export and select Export Sheet to Excel. Export Statistics for Multiple Runs - Choose Analyze > View Run Statistics, then under Trial & Run Selection, select a trial. - Choose File > Export > Run Statistics. - In the Export Run Statistics window, under Select Data choose: - Export All Runs from Active Trial (Trial#) – This exports the statistics from all runs in Trial#. Each run is represented by a row in the Excel export file. - Export All Runs from All Trials – This exports the statistics from all runs of all trials in the current experiment. Each run is represented by a row in the Excel export file. The number of trials and runs in the current selection are shown under the Select Data options. - Under Parameters, select the parameter categories you require. For a description of the categories and their statistics, see the Parameters section. - Under Statistics, select to export the Mean and/or the Standard Deviation for each statistic from the parameter categories. - Under Output, choose the File name and export Folder. - First, click Open Output Folder and then Export. The Run Statistics Export File This is an Excel file containing the following columns: - Experiment – Contains the experiment name. - Group – The name of the treatment group. - Group_Type - Group_Description - Animal – The animal ID. - Time_Point – The time point of acquisition of the run. - Time_Point_Description - Trial – The trial ID. - Trial_Description - Run – The run ID. - Run_Description - Run_Duration – The duration of the recorded run. - Run_Average_Speed – The average speed of the animal in the recorded run. - Run_Maximum_Variation – The maximum variation in walking speed of the animal in the recorded run. - Camera_Gain – The Camera Gain value that was used during acquisition. - Green_Intensity_Threshold – The Green Intensity Threshold value that was used during acquisition. - X-Unit – The width of a single pixel as determined during calibration. - Y-Unit – The height of a single pixel as determined during calibration. - Walkway_Length – The length of the defined walkway. - Walkway_Width – The width of the defined walkway. In the subsequent columns, for each paw print the selected statistics are displayed. Note: A parameter that was not measured is indicated with an empty cell. Export the Trial Statistics Aim To export the combined parameters of runs within a trial. Each trial is represented by a single row in the export file. You can select the parameters to be exported. Note: If your experiment contains one or more runs with missing or corrupt data you get an error message when you try to export Trial Statistics. Delete the runs listed in the error message and then export Trial Statistics. Note: A parameter that was not measured is indicated with an empty cell in the export file. Procedure - In the Run Statistics window, under Trial & Run Selection, select a trial. - Choose File > Export > Trial Statistics. - In the Export Trial Statistics window, under Select Data, choose: - Export Active Trial (Trial#) – This exports the combined parameters of runs within this trial. - Export All Trials – This exports the combined parameters of all trials. Each trial is represented by a single row in the Excel export file. The number of trials and runs in the current selection are shown under the Select Data options. - Under Parameters, select the parameter categories you require. For a description of the categories and their statistics, see the Parameters section. - Under Statistics, select to export the Mean and/or the Standard Deviation for each statistic from the parameter categories. - Under Output, choose the File name and export Folder. - First, click Open Output Folder and then Export. How Trial Statistics Are Calculated Trial Statistics are calculated based on all individual paw prints in all the runs of a trial (provided that they are selected for analysis). It is like all runs in a trial are combined in one long run, and then statistics are calculated. Therefore, Trial Statistics are not a simple average of the values reported in the Run Statistics export sheet. Example 1 – Print Length: To calculate the trial statistic Print Length for the Right Front paw, the Print Length values of all selected Right Front paw prints in that trial are summed up and the result divided by the total number of Right Front paw prints in that trial. Example 2 – Phase Dispersions: A trial consists of five runs. The run statistics for Phase Dispersions RF->LH are -8.064102564, -2.961685824, -9.991397491, -4.797619048, and -4.114787182. These values are found in the export file of run statistics. The arithmetic mean of these values is -5.9859. However, CatWalk XT reports a slightly different value, -6.0385, as the average for that trial. The reason for this is that the five run values do not have equal weight. Runs 1 and 2 are based on three steps, whereas runs 3 to 5 are based on four steps. CatWalk XT calculates the average by taking the Phase Dispersions values for each step included in the selected runs. Therefore, a run of four steps contributes to the average more than a run of three steps, resulting in a trial average for Phase Dispersion of -6.0385 rather than the arithmetic mean of the per-run averages. The Trial Statistics Export File This is an Excel file containing the following columns: - Experiment – Contains the experiment name. - Group – The name of the treatment group. - Group_Type - Group_Description - Animal – The animal ID. - Time_Point – The time point of acquisition of the run. - Time_Point_Description - Trial – The trial ID. - Trial_Description - NumberOfRunsUsedForCalculatingTrialStatistics – The number of exported runs based on the selection chosen in the Export Trial Statistics window. - Run_Duration_Mean – The mean run duration of all recorded runs in this trial. - Run_Average_Speed_Mean – The average speed of the animal in this trial. - Run_Maximum_Variation_Mean – The average maximum variation in walking speed of the animal in this trial. - Camera_Gain – The Camera Gain value that was used during acquisition. - Green_Intensity_Threshold – The Green Intensity Threshold value that was used during acquisition. - X-Unit – The width of a single pixel as determined during calibration. - Y-Unit – The height of a single pixel as determined during calibration. - Walkway_Length – The length of the defined walkway. - Walkway_Width – The width of the defined walkway. In the subsequent columns, for each paw print the selected statistics are displayed. Export the Group Statistics and Charts Aim To export the statistics of parameters calculated per treatment group and time point combination to Excel, and one or more parameter charts. Note: If your experiment contains one or more runs with missing or corrupt data you get an error message when you try to open the Group Statistics and Charts. Delete the runs listed in the error message first. Note: A parameter that was not measured is indicated with an empty cell. Export Group Statistics for One Parameter Category Choose Analyze > View Group Statistics and Charts, right-click the sheet you want to export, and select Export Sheet to Excel. Export All Group Statistics - Do one of the following: - Choose Analyze > View Group Statistics and Charts, then click the Export button. - Choose File > Export > Group Statistics. - Choose a file name (default: [experiment name]_Group Statistics) and destination folder. The Group Statistics Export File This is an Excel file with one sheet for each group of parameters (Paw Statistics, Phase Dispersions, etc.). Each sheet contains the following columns: - Time Point – The name of the time point. - Treatment Group – The name of the treatment group. In the subsequent columns, the selected statistics are displayed. Export a Chart Right-click the chart you want to export and select Save to File or Copy to Clipboard. - With the Save to File option, the chart is saved as a PNG image. - If you choose Copy to Clipboard, paste the chart in the destination program. Export All Charts - Choose File > Export and Charts. - Choose a file name (default: [experiment name]_Charts.pdf) and destination folder. - Click Open Output Folder to access the folder where the file will be saved. - Click Export. The file is saved as PDF and contains all charts in the Graphical Results. Export the Run Visualizations Aim To export the video, 3D/2D Footprint Intensities, or Footfall Patterns of the current run to a video file. Procedure - In the Run Visualizations screen, select a trial and a run. - Choose File > Export > Run Visualizations. - Select the Visualizations (Video, 3D/2D Footprint Intensities, Footfall Patterns) you want to export. - Under Output, select a playback Speed, File name, and export Folder. - First, click Open Output Folder and then Export. The Run Visualizations file is exported in uncompressed AVI format and plays back at the selected speed. You do not need a codec to play the Run Visualizations video. Export the Run Video Aim To export the video of the current run. --- ## CatWalk XT 11 - File and Profile Management - File and Profile Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-file-and-profile-management-file-and-profile-management Chapter: CatWalk XT File and Profile Management 8.1 CatWalk Experiments Create a New Experiment - Do one of the following: - In the Application Startup Tasks window, select Create a new experiment. - Choose File > New Experiment. - Click the New Experiment icon in the tool bar. - Select an Experiment Setup profile from the Setup Profile list. - Enter the Name for your experiment. - Accept the default location or browse to a new location. Optionally, you can add a Description and enter a name in the Created by field. The default experiment folder is C:\Users\Public\(Public) Documents\Noldus\CatWalk XT\Experiments. - Click Create experiment. The experiment (*.cwe) is stored in a folder with the same name as the experiment. Open a CatWalk XT 11.0 Experiment - To open an experiment, do one of the following: - In the Acquisition Startup Tasks window, click an existing experiment listed under Open an existing experiment or click Open another... - Choose File > Open Experiment (Ctrl+O) or click the Open Experiment icon. - Double-click the experiment folder, select the *.cwe file and click Open. Open a CatWalk XT 8/9/10.0/10.5/10.6/10.7 Experiment When you open an old experiment, it is converted to a CatWalk XT 11.0 experiment. Once the experiment is converted, it cannot be opened anymore in the previous version. It is not possible to open or import experiments from CatWalk 7.x or earlier. Before opening a CatWalk XT 8/9/10.0/10.5/10.6/10.7 experiment in CatWalk XT 11.0, you are required to make a backup of the experiment that can still be opened in the previous version. Make sure to store backups in a safe location. We strongly recommend that you backup your experiments every day, and, for irreplaceable data, more often. - Choose File > Open Experiment. - In the window that appears, click Yes. - In the Backup Experiment window, you can enter the name and folder for the experiment backup. The file name for the backup contains the current date and time. Click Backup to create a backup copy of the experiment and then click OK. - If you convert a CatWalk XT 8 experiment, you can select Rat or Mouse in the Animal Type window. Selection of the type of animal is important for Automatic Footprint Classification and for calculation of the Sciatic, Tibial and Peroneal Functional Index (for rat and mouse different Automatic Footprint Classification algorithms and different FI formulas are used). You can also later select the animal type in the Experiment Settings if you are not sure at this point which animal type you should select. - Click OK to start the conversion. When conversion is completed, the Open Experiment Tasks window opens. Select one of the options to continue or close the window. Errors During Conversion If an error occurs during conversion, you get an error message "An error occurred during the conversion of experiment [experiment name]". Do the following: - Click OK and Cancel and close CatWalk XT. - In Windows Explorer, go to the CatWalk Experiments folder and delete the complete [experiment name] folder which contains the experiment you wanted to convert. Do not try to open the *.cwe file from the [experiment name] folder. - Open CatWalk and restore the backup file that was created in step 3 above. Possible causes for a conversion error are: - The disk to which you try to save the experiment is full. - You do not have write permission for the CatWalk Experiment folder. - There is an error in the experiment or experiment folder. In this case, send the backup file to our Support department. Save an Experiment Choose File > Save Experiment or press Ctrl+S, or click the Save icon in the tool bar. When you save an experiment, all trials and runs are saved. Settings such as walkway settings, Preferences, Detection Settings, Acquisition Settings and profiles are only saved when you save and exit the experiment. By default, Auto Save is active and the experiment is automatically saved at 5-minute intervals. Create a Backup of the Current Experiment - Choose File > Make Backup or click the Make Backup icon in the tool bar. - Accept the default File name and Folder or change these. Before clicking Backup, you can click Open Output Folder so Windows Explorer opens the folder in which the backup (*.cwz) file is saved. - Click Backup. A message appears when the backup file was successfully created. Restore a CatWalk XT Backup (*.cwz) File - Choose File > Restore Backup or click the Restore Backup icon in the tool bar. When you first start CatWalk XT, you can also select Restore Backup in the Application Startup Tasks window. - Locate the backup file (*.cwz) and click Open. - Accept the default CatWalk XT Experiment folder or browse to another folder in which you want to restore the experiment. - Click OK. If you open a CatWalk XT 8/9/10.0/10.5/10.6/10.7 backup (*.cwz) file, the experiment is converted to CatWalk XT 11.0. 8.2 Trials & Runs Open a Trial or Run To open a trial or run, in the Experiment Explorer, right-click a trial or run and select Acquire, Classify, Visualize or View Run Statistics. If you get a message "An error occurred while loading the data of run 'Run#'", it means the run is corrupt. We advise you to delete this run. Delete a Trial or Run You cannot delete an active trial or run (shown in bold and blue in the Experiment Explorer). If you want to delete trials or runs, you must do this in CatWalk. If you delete trials or runs in the experiments folder in Windows Explorer, this makes your experiment corrupt. To delete a trial, do one of the following: - In the Experiment Explorer, right-click a trial and select Delete. - Open the Trial List, select one or more trials and click the Delete Trial(s) button at the bottom. To delete a run, do one of the following: - In the Experiment Explorer, right-click a run and select Delete. - Open the Acquisition screen, select the corresponding trial and select Live video in the View list. Click one or more runs in the Acquired Runs list and click the Delete Run(s) button. --- ## CatWalk XT 11 - Hardware Installation Guide URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-hardware-installation-guide Chapter: CatWalk XT Verify Package Contents Check that all components are present before starting your installation. Verify that the following components are present in your upgrade kit. Component Article Number Basler a2A1920-165g5cBAS camera XCCW-0001 6mm wide-angle low-distortion lens XCCW-0004 Basler 10GigE interface card, 1 port XCCW-0002 5m GigE Cat6a RJ45 cable XCCW-0003 Camera heat sink XCCW-0005 Camera mounting bracket — If any component is missing or damaged, contact your Noldus account manager before proceeding with the installation. Install the 10GigE Interface Card The 10GigE interface card must be installed in your PC before connecting the camera. Follow these steps carefully. - Turn off your computer and disconnect the power cable. Also turn off all connected peripherals. - Remove the PC's side panel according to your PC's user manual. - Select a free PCIe expansion slot and remove the corresponding slot cover. Different PCIe slots offer different bandwidth. When possible, choose the slot that gives maximum performance. The card has a 1x connector so values are per lane: - PCIe v2.x: 500 MB/s - PCIe v3.0: ~1 GB/s - PCIe v4.0: ~2 GB/s - PCIe v5.0: ~4 GB/s - Unpack the Ethernet board and carefully place it into the selected PCIe slot. Press gently but firmly into position. Important — Static Electricity: Electronic components can be damaged by static electricity. Ensure you are grounded before handling the card. Use an earthing wristlet clipped to the PC's metal frame, or hold the frame with one hand while handling the board. - Fix the card to the chassis with the retaining screw and re-fit the computer's side panel. - Reconnect power and start your computer. Windows will automatically detect the new network adapter. Verify Network Adapter Settings - Open Windows Device Manager. - Under Network Adapters, locate your new Ethernet board, right-click and select Properties. - Go to the Power Management tab and ensure Allow the computer to turn off this device to save power is not selected. Connect the Camera The new CatWalk Basler camera comes with a heat sink pre-installed to prevent overheating during operation. Connect the Network Cable - Connect one end of the GigE Cat6a network cable to the camera. Make sure you securely tighten the screws to attach the network plug. - Connect the other end of the network cable to the 10GigE port on your PC. Connect the Power Cable - Attach the power cable to the camera. Carefully align the pins on the connector to the power input on the camera. - Connect the other end of the power cable to the CatWalk control unit. Mount the Camera Attach the camera to the CatWalk using the mounting bracket. Adjust the camera position to your needs. Ensure the camera is positioned centrally above the walkway and that the lens has a clear, unobstructed view of the entire glass plate. Install the Software Once all the hardware components have been installed you are ready to download the CatWalk 11 software. - Go to my.noldus.com. - Log into your Noldus account to download the latest version. - Install the software following the on-screen instructions. - Proceed with the walkway setup in the CatWalk software. Walkway setup for CatWalk 11 has been made significantly easier with the new NoldusCalibrationCard. Follow the steps inside the software to consistently focus the camera and calibrate and define your walkway. If you have NoldusCare you can access the Noldus Academy. The Academy includes videos explaining both the installation of the camera as well as the calibration and focus process in depth. Need Help? Contact your Noldus account manager or visit www.noldus.com/support. Contact Information - International Headquarters Noldus Information Technology bv Wageningen, The Netherlands Phone: +31-317-473300 Email: contact@noldus.com - North American Headquarters Noldus Information Technology Inc. Leesburg, VA, USA Phone: +1-703-771-0440 Toll-free: 1-800-355-9541 Email: info@noldus.com Due to our policy of continuous product improvement, information in this document is subject to change without notice. EthoVision is a registered trademark of Noldus Information Technology bv. © 2025 Noldus Information Technology bv. All rights reserved. Source: CatWalk XT 11.0 Hardware Installation Guide, Noldus Information Technology --- ## CatWalk XT 11 - Installation - 2.2 Your CatWalk License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-installation-22-your-catwalk-license Chapter: CatWalk XT 2.2 Your CatWalk License Types of CatWalk XT License Your CatWalk XT license is stored on a hardware key (also known as a dongle) or in a software form (software license key). In all cases, to know which add-on module you have, choose Help > About CatWalk XT, then click the License Info button. Enabled modules are marked with a checkmark. License on a Hardware Key Your CatWalk XT software comes with a hardware key, which determines which functionalities are available. This is a very important piece of equipment, as it is your license and will not be replaced free of charge. Please keep this in mind and make sure that you do not lose the key. You will need to pay for a new license if you do so. - The driver for the hardware key is installed automatically when you install CatWalk XT. To make sure that the driver is installed, open Programs and Features in the Windows Control Panel. If the driver is installed, you should see an item named Sentinel Runtime (version 8.11). - To reinstall the driver of the hardware key, run the installation of CatWalk XT 11 and select Repair. - First install the CatWalk XT software and then connect the hardware key to your computer, not the other way around. - Your CatWalk XT software can only acquire data if the hardware key is plugged into your computer. If the hardware key is not plugged in, you can open existing experiments, analyze data, and classify runs. - In order to use the full functionality of CatWalk XT on two computers, you must move the hardware key from one computer to the other. - If the hardware key is not plugged into your PC or the software license is not activated, you can still start CatWalk XT and work in unlicensed analysis mode. This means that you can analyze and visualize previously-recorded data, but cannot acquire more data. Upgrade the Hardware Key When you upgrade from a previous version and start CatWalk XT for the first time, the system automatically detects the hardware key and asks you to type the Upgrade Key in the Upgrade Key window box. This number is normally sent to you by email or in your welcome letter. Software License Key A software license key allows you to use CatWalk XT without a hardware key plugged into your computer. Your software license key is coupled to the hardware of your computer, not to a specific user or user group name. A software license can be of two types: - Fixed. This type of license is meant to be used on a specific computer. The fixed license is associated with that computer, and this association is registered on the Noldus Server. In order to re-use a fixed license on another computer, you must first deactivate that license on the computer where it is currently active. - Floating. This type of license is meant for when you want to use CatWalk XT to acquire runs on two or more computers, though not simultaneously. - If you acquire runs on the same computer in the lab and want to analyze or visualize data on your office computer, a floating license is not needed. You can activate a fixed license on your lab computer to acquire data, while using CatWalk XT in unlicensed analysis mode in your office. - With one floating license you can work on one computer at a time. Make sure that CatWalk XT is closed on all computers other than the one you are currently using. - In order to work with a floating license, your CatWalk XT computer must be connected to the internet. When you close CatWalk XT on one computer with a floating license, the license is automatically deactivated, provided the computer is connected to the Noldus Server. At that point you can use CatWalk XT on another computer. See Also - The End-User License Agreement. - The Acknowledgments and Copyright Notices. - Legal documents stored at: C:\Program Files\Noldus\CatWalk XT 11.0\Documentation\Legal --- ## CatWalk XT 11 - Installation - Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-installation-installation Chapter: CatWalk XT Installation 2.1 Install The CatWalk XT Software If you ordered a new computer from Noldus Information Technology when you purchased CatWalk XT, all the necessary software and hardware is already installed and tested. In that case, you only need to assemble and set up the CatWalk system. See the CatWalk XT Assembly Instructions which you can find on the CatWalk XT installation package and in a printed version that came with the system. To install the Ethernet card, see Appendix A: Install the Ethernet Card for the Camera. Before You Install Administrator Rights To be able to install the CatWalk software you must have administrator rights, that is, either you are the system administrator or you have been assigned administrator rights. Windows Power Users cannot install CatWalk XT. Do not run CatWalk XT for the first time as an administrator on a computer with multiple user accounts, because other, standard, users then are not able to run CatWalk XT. Operating Systems - Windows 10 Pro, version 22H2 or later. Please first do a Windows Update to install a compatible Windows 10 version, then install CatWalk XT. See https://learn.microsoft.com/en-us/lifecycle/products/windows-10-home-and-pro - Windows 11 Pro. Computer Requirements CatWalk XT 11.0 has been tested on a Dell Precision T3660. - Processor: Intel Core i7-11700, 16 MB Cache, 8 Core, 2.5 GHz to 4.9 GHz. - Memory: 16 GB DDR5. The RAM minimum requirement for CatWalk XT is 16 GB. - First hard disk: M.2 256 GB PCIe NVMe SSD. - Second hard disk: 3.5 inch 1 TB SATA (7200 rpm). - Graphics card: NVIDIA Quadro T1000, 4 GB. USB-C Port In order to connect the CatWalk Control Unit, the PC must have one USB-C port. Ethernet Network Interface You need a 10-Gb (gigabit) Ethernet network interface card for connecting the digital camera to the CatWalk XT computer. If you purchased the CatWalk XT computer from Noldus, the card is already installed and configured. If you use a different PC, see Appendix A: Install the Ethernet Card for the Camera. Experiments From Previous Versions of CatWalk XT If you have old experiments, first back up all your data to a secure location. Experiments are stored by default in the folder: C:\Users\Public\(Public) Documents\Noldus\CatWalk XT\Experiments. Please copy the complete folder of an experiment when transferring it to another folder on the same computer or to another computer. Install CatWalk XT Make sure you first install CatWalk XT before you connect the Control Unit to the CatWalk XT computer. First install the CatWalk XT software and then connect the hardware key to your computer, not the other way around. If You Upgrade From Previous Versions - From CatWalk XT 8.x / 9.x: CatWalk XT 11.0 is installed alongside CatWalk 8.x / 9.x. Experiments from CatWalk XT 8.x / 9.x are automatically converted to CatWalk XT 11.0 after opening them, and cannot be opened in the previous CatWalk XT version. - From CatWalk XT 10.x: CatWalk XT 11.0 replaces CatWalk XT 10.x. Experiments from CatWalk XT 10.x are automatically converted to CatWalk XT 11.0 when you open them. Experiments that are recorded with any version before 11.0 can only be analyzed. No additional acquisition is possible. If you have CatWalk XT 10.6, we advise you to update the firmware of the Control Unit (Help > Upgrade Control Unit Firmware) before installing CatWalk XT 11.0. See the CatWalk XT 10.6 Reference Manual. Installation Procedure - Download the CatWalk XT installation files from my.noldus.com. - Double-click the file CatWalk XT - Setup - [version number].exe. - In the Welcome screen of CatWalk XT, under Installation Type, select Standard. Optionally, choose Custom if you want to install the software in a location other than the default, specify another default location for your experiments, or specify which shortcuts to add to your desktop. Click Next. - Read the End-User License Agreement, select I Agree, and click Install. - Click Close when the message "Installation Complete" appears. Installation Notes - During the installation of CatWalk XT 11.0, the computer may restart automatically. Please wait until the installation is complete. - Installation of the drivers for the Ethernet card is included in this installation. You do not have to take further action. - The Basler camera software to control the camera (Pylon Runtime) is included in the installer. When this installer starts as part of the CatWalk installation, accept the license and install it. When it is done, click Finish. The CatWalk installer will then continue. If Installation Fails Use the Windows Control Panel to uninstall the following programs if they are present on your PC: - Any previous CatWalk version. - The eBUS SDK drivers (eBUS Runtime 64-bit). - Microsoft Visual C++ 2015-2022 Redistributable - 14.40.xxx. Standard File Locations - Installation location: C:\Program Files\Noldus\CatWalk XT 11 - Experiments location: C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments Uninstall CatWalk XT To remove CatWalk XT from your computer, do the following: - Click the Windows Start button and type "Programs" in the Search field. Choose Add or Remove Programs. Alternatively, open the Control Panel and choose Programs and Features. - In the Programs/Apps and Features window, select CatWalk XT 11 and click Uninstall. Upgrade CatWalk XT Prerequisites - You have a CatWalk XT license and have purchased an upgrade. - You received an Upgrade Key from Noldus, either in the Welcome letter or by email. - If your license is on a USB hardware key, insert that key into a USB port of your CatWalk XT computer. Upgrade Procedure - Download and install the newest CatWalk XT version from MyNoldus.com. You do not need to uninstall previous CatWalk XT versions. - After installation is complete, start CatWalk XT. - In the window that opens, choose Activate Software License Key. - Choose whether to activate online or offline. - Enter the Upgrade Key that you received from Noldus. If your license is stored on a hardware key, you need to upgrade the license on that key. Make sure that the hardware key is plugged into the computer and the red LED on the key is on. After starting the newest CatWalk XT version, enter the Upgrade Key. --- ## CatWalk XT 11 - Installation - License Activation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-installation-license-activation Chapter: CatWalk XT License Activation Choose what applies: - Activate your CatWalk XT license - Deactivate a CatWalk XT license - Turn a floating license to a fixed license - Turn a fixed license to a floating license - Duration of the CatWalk XT license Activate Your CatWalk XT License Aim To activate a CatWalk XT license after purchase. Note that you do not need to follow this procedure if your license is on a USB hardware key. Background Information When you start CatWalk XT, the software checks that your license is valid. The license may be stored in your hardware key (dongle), in your CatWalk XT computer (Fixed license) or in the Noldus server (Floating license). If no valid license is found, you can activate your license by following the procedure below. Important Terms - Activation key. An activation key is provided by Noldus to activate your license. You find an activation key on a letter or email sent to you. - Computer key. A computer key comes into play when you activate your license offline. This is a key that identifies the computer that you are using during activation. - License key. A license key is the unique piece of information that you obtain after you activate the license. You can find this key in CatWalk XT by choosing Help > About CatWalk XT > License Info. Prerequisites - You have installed CatWalk XT. - You have received a License Activation Key from Noldus. What Do You Want to Do? - Activate a fixed license (see below). Do this when you want to work with CatWalk XT on one computer only. - Activate a floating license (see below). Do so if you plan to use this license on different computers at different times. If you have two or more floating licenses instead of one, you can use CatWalk XT on multiple computers simultaneously. Activate a Fixed License - Start CatWalk XT. In the window that appears, choose Activate software license key. - Choose Fixed - On this computer only and click OK. - Enter or copy the Activation Key that you received from Noldus. - Select one of the following options depending on whether your CatWalk XT computer is connected to the internet: - Activate Online. Do so if your computer is connected to the internet. Next, click OK. A message appears that the license has been activated. - Activate Offline. If your computer is not connected to the internet, you need a smartphone connected to the internet that can scan a QR code. Note that the Activate Offline option is not available if you have purchased a time-limited license or received a license for a free trial. - To obtain the Computer Key, scan the QR code with a smartphone. - If the QR code is recognized, a web page of the Noldus License Manager opens that shows the required Computer Key. - Enter this key in the Computer Key field in the CatWalk XT License Activation window and click OK. Activate a Floating License Choose a floating license if you want to use CatWalk XT on different computers (though not simultaneously). With two or more floating licenses, you can work with CatWalk XT on different computers and CatWalk XT systems simultaneously. Important: You can only activate and use a floating license when your CatWalk XT computers are connected to the internet. Make sure that your CatWalk XT computer in the lab is always connected. - Start CatWalk XT on one of the computers. In the window that appears, choose Activate software license key. - Choose Floating - On multiple computers and click OK. - Under Activate floating license, enter or copy the Activation Key that you received from Noldus. Next, click OK. - The license is activated. You can start using CatWalk XT. - Repeat the procedure on the other computers. Notes - You cannot activate a term license after the expiration date. - If activation fails: - Try once again and make sure that you enter the correct Activation Key and Computer Key, including capital letters and dashes. - Contact Noldus to obtain a valid Activation Key. - If your license is not activated, you can still start CatWalk XT and work in unlicensed analysis mode. Deactivate a CatWalk XT License Aim To deactivate a software license, either to end the license agreement or to transfer the license to another computer. Example: You have purchased a new computer and you would like to transfer your CatWalk XT license from the old computer to the new computer. Prerequisites - CatWalk XT is running with a software license (no hardware key). - The CatWalk XT computer is connected to the internet, or you have a smartphone connected to the internet. What Do You Want to Do? - Deactivate a fixed license (see below). - Deactivate a floating license (see below). Deactivate a Fixed License - In CatWalk XT, choose Help > Deactivate License. - Choose Fixed - On this computer only and click OK. - Select one of the following options depending on whether your CatWalk XT computer is connected to the internet: - Deactivate online. Do this if your CatWalk XT computer is connected to the internet. Select this option and click OK. - Deactivate offline. If your computer is not connected to the internet, you need a smartphone connected to the internet that can scan a QR code. - Select this option and click OK. - A QR code appears on the screen. - Scan this code using a smartphone and follow the link within 24 hours. - Click Deactivate on the screen that appears in your browser. - CatWalk XT shows a message that the license has been deactivated and closes. Notes - If your smartphone is not connected to the internet, leave the link open, go to a place where your smartphone is connected to the internet, and open the linked page. - When you click Deactivate offline, your license is deactivated on your computer but not yet on the Noldus server. For this second step you must scan the QR code, follow the associated link, and click Deactivate in a web browser on your smartphone. Do this within 24 hours. Deactivate a Floating License Deactivate a floating license when you need to transfer that license to another computer. Note that when you have floating licenses, in order to be able to work on one computer you just need to close CatWalk XT on the other computer(s). You do not need to deactivate the license on the other computer(s). - Make sure that the CatWalk XT computer is connected to the internet. - In CatWalk XT, choose Help > Deactivate License. - A message appears: License successfully deactivated. CatWalk XT will close now. - You can now activate that floating license on another computer. Choose to activate a floating license as described in the Activate Your CatWalk XT License section above. Turn a Floating License to a Fixed License Aim You may want to turn a floating license to a fixed license so you can use CatWalk XT on a computer without an internet connection. Prerequisites - You have a CatWalk XT floating license. - You have an Activation Key for your floating license. Procedure - Open CatWalk XT and deactivate the floating license. An internet connection is required for this step. See Deactivate a Floating License above. - After deactivation of the license, CatWalk XT closes. - Start CatWalk XT on the computer where you want to have the fixed license. - Choose Activate software license key, then Fixed - On this computer only. Follow the instructions under Activate a Fixed License above. Turn a Fixed License to a Floating License Aim You may want to turn a fixed license to a floating license because you want to use CatWalk XT on multiple computers (not simultaneously). If you purchased multiple floating licenses, you can work on multiple computers simultaneously because a license will be active on each computer. Prerequisites - You have a CatWalk XT fixed license. - You need to have the Activation Key for your floating license. Procedure - Open CatWalk XT and deactivate the fixed license. See Deactivate a Fixed License above. - After deactivation of the license, CatWalk XT closes. - Start CatWalk XT on the computer where you want to activate the floating license. An internet connection is required for this step. - Choose Activate software license key, then Floating - On multiple computers. Follow the instructions under Activate a Floating License above. Note: If you choose to deactivate offline, first click OK, then scan the QR code that appears. Follow the link and click or tap Deactivate. Duration of the CatWalk XT License A CatWalk XT license can be one of the following types: - Perpetual license. This is the most common license. You purchase a copy of CatWalk XT on a one-time basis and can use the software forever. - Time-limited license. This license is generally valid for a period of six or twelve months. A time-limited license can only be activated online. CatWalk XT in Analysis Mode Aim To carry out analysis and visualization of already-existing track data in CatWalk XT without a license. Background Information A CatWalk XT license is needed whenever you acquire new data and record video. It is therefore important to activate a license on the computer that you use to collect data. However, you can also install the CatWalk XT software on other computers without a license. Example: After collecting gait data in your lab with a CatWalk XT license, copy the CatWalk XT experiment to your laptop where you have installed CatWalk XT without a license. There you can visualize and analyze your data. Procedure - If you have not done so yet, install CatWalk XT. - Start CatWalk XT. - If CatWalk XT does not find a valid license, a window opens with the message: No License key found. - Choose Start in unlicensed analysis mode. What You Can Do with CatWalk XT in Analysis Mode CatWalk XT in unlicensed analysis mode offers all the functions necessary to refine analysis and produce results: - Open existing experiments. - Edit the values of independent variables in the Trial List. - Classify runs and adjust the Classification Settings. - Create new Data profiles and select data. - Create new Parameter profiles and select parameters. - Use all the analysis functions under the Analyze menu. - Export videos, visualizations, run data, all statistics, and charts. - Make a backup of your experiment and restore experiments from backup files. Source: CatWalk XT 11.0 Reference Manual - Installation, Noldus Information Technology --- ## CatWalk XT 11 - Introduction - Additional Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-introduction-additional-information Chapter: CatWalk XT Additional Information Documentation CatWalk XT comes with the following documentation: - CatWalk XT 11.0 - Reference Manual.pdf (the current document). This document describes how to use the CatWalk XT system, and how to install the software and the hardware on the computer. If you purchased the CatWalk XT computer from Noldus Information Technology, all hardware and software on this computer already has been installed and tested. - CatWalk XT 11.0 - Assembly Instructions.pdf. This document describes how to assemble the CatWalk system and the goal box. - CatWalk XT 11.0 Quick Start Guide.pdf. This document describes how to set up, carry out and analyze an experiment with CatWalk XT. Sample Experiments The CatWalk XT software includes three sample experiments, which contain data collected in real experiments carried out with mice and rats. Sample experiments are a good way to start understanding gait analysis in CatWalk XT if this is the first time you operate the software. To open a sample experiment: - In CatWalk XT, choose Restore Backup in the start screen or choose File > Restore Backup. - Browse to C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments\Backups. - Select one of the files with extension CWZ and click Open. - Select where to save the experiment. By default, experiments are saved in C:\Users\Public\Documents\Noldus\CatWalk XT\Experiments. Note that the sample experiments are recorded with older versions than CatWalk XT 11.0 and therefore are recorded with the old low resolution camera (640 x 480 pixels instead of 1920 x 1216 pixels). The Help Menu The Help menu in the CatWalk XT program contains the following options: - Help Topics — Displays the PDF of the CatWalk XT Reference Manual (F1). - Tutorial Videos — Opens a folder on your PC where the tutorials are stored. - Noldus Online — If your computer is connected to the internet, choose this option and click one of the following items: - The CatWalk XT Home Page for general information on CatWalk and relevant publications. - Customer Support, then click Support to contact the Help desk. - Knowledgebase, then click Resources to search through dozens of entries in a database of questions submitted by our customers with answers by our support staff. - Report an Issue to fill a form about an issue you encountered when using CatWalk XT. - Deactivate License — If you have a software license, you can choose to move a license from one computer to another. Select Deactivate License on a PC in order to be able to activate the same license on another PC. Introduction Upgrade License If you already are a CatWalk user (XT 8/9) and you have purchased the latest version of CatWalk, choose this option to type in the new Upgrade Key number that you have received from Noldus. Enter this number in the newest software version, not the old one. If you have CatWalk XT 10.0 or 10.5, you do not need to purchase a new license. About CatWalk XT Contains information about your copy of CatWalk XT. Click the License Info button to see the name of the registered user and the license number of your software. Noldus Help Desk If you have any problems, questions, remarks or comments, please let us know. You can contact us at our support page: my.noldus.com We offer 24 hour support by help desks in various time zones. Before you contact Technical Support, please have the following information available. To find this information, go to the Help menu and select About CatWalk XT: - The version number of your copy of CatWalk XT. - The name of the registered user and the license number (Help > About CatWalk XT > License Info). Make A PC Report For The Help Desk This section is needed if the Noldus Help desk asks you to send them a PC report for the CatWalk XT computer. - Download the utility from the Help desk and copy it to the CatWalk XT computer. - Double-click on the file siw64.exe. - Choose File > Create Report File > HTML Report and save the file to your desktop. - Send the HTML file as an e-mail attachment to the Help desk. Source: CatWalk XT 11.0 Reference Manual - Introduction, Noldus Information Technology --- ## CatWalk XT 11 - Introduction - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-introduction-introduction Chapter: CatWalk XT Introduction 1.1 An Introduction to CatWalk XT This section gives a general overview of what the CatWalk program does. We recommend that all first-time users of CatWalk read this section. Principle of Operation The heart of the CatWalk system consists of an enclosed walkway on a glass plate that is traversed by a rat or mouse from one side of the walkway to the other. Green light enters at the long edge of the plate and is completely internally reflected. Light is able to escape only at those areas where the animal's paws make contact with the glass plate; as a result, the light is scattered. Thanks to our Illuminated Footprints™ technology, paws are captured by a high speed video camera that is positioned underneath the walkway. The video camera transforms each scene (the area in front of the lens) into a digital image composed of discrete pixels of digital brightness values. The digital images are transferred to the computer through an Ethernet connection. The brightness of a pixel depends on the amount of light received from such an area by the camera. The Illuminated Footprints™ technology enables intensity differences to be detected between animals' paws. Paw Detection In order to be able to classify paw prints in the video, you first need to set the CatWalk program to distinguish between paw prints and background noise. For this you can adjust the Camera Gain and Green Intensity Threshold to set the Maximum and Minimum Green Intensity, respectively, of the pixels that comprise a paw print. Classifying Runs The video images with paw prints are used in the footprint classification. You assign labels (for example, right hind paw, left front paw) manually or automatically to illuminated paw prints in each video image. You can also determine (Intermediate) Toe Spread, Print Length and Paw Angle with the interactive footprint measurements module. Once classification is done, the CatWalk software automatically calculates a wide number of parameters in each of the following categories: - Parameters related to individual footprints: for example, initial contact of each placement of a paw, the duration of contact of a paw print with the glass plate, the width and length of a complete paw print, the intensity of a paw, the time the animal stands on a single hind paw or both hind paws, etc. - Parameters related to the position of footprints: for example, stride length, base-of-support, relative print positions. - Parameters related to time-based relationships between footprints: for example, footfall patterns, phase dispersions, support formulas. - The Sciatic Functional Index, which is commonly used as a tool for the evaluation of the recovery of the sciatic nerve. --- ## CatWalk XT 11 - Introduction - What's New in CatWalk XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-introduction-whats-new-in-catwalk-xt Chapter: CatWalk XT What's New in CatWalk XT New in CatWalk 11.0 This section describes new features compared to version 10.7. Hardware Changes: - CatWalk 11.0 uses a new camera system with a resolution of 1920 x 1216 pixels instead of 640 x 480. - The Basler camera is pre-configured to process the middle part of the camera images automatically. - The installed interface card now has 10 Gig capacity instead of 1 Gig. - Pleora Ebus drivers are no longer installed. Basler Pylon Runtime is used instead. Setup Changes: - The setup of the camera is improved. Focusing, calibration and definition of the walkway are easier and more reliable. A dedicated calibration card is included and is used instead of the calibration sheets. - Focus support: the camera can be focused to get sharp images easily and correctly. - Automatic WalkWay calibration: the WalkWay can be calibrated correctly and automatically without any effort. - Automatic WalkWay definition: the WalkWay is detected automatically. - CatWalk 11.0 does not support making new recordings on experiments created with previous versions. Data coming from different camera systems cannot be analyzed and compared reliably. Functional Changes: - Units for all parameters in Excel export and in the interface. - User preferred precision in export. - Meta data added to Excel export files and chart PDF files. - Body axis color adapted for better visibility. - Validate WalkWay on demand. New in CatWalk 10.7 This section describes the functionality that was released in CatWalk XT 10.7. It is only relevant for users that have used CatWalk 10.6 and/or older versions. CatWalk Control Unit: The CatWalk Control Unit is now connected to the PC through a USB cable with connectors of type B and C. Your CatWalk XT computer must have a USB-C connector in order to connect it to the Control Unit. Installation Procedure: The software installation procedure has been greatly simplified. You no longer have to install and configure the Ethernet card drivers and the camera drivers separately. The new CatWalk XT installation wizard does that for you. Software License Key: You can purchase CatWalk XT with a software license that makes it easier to use the software without worrying about losing or damaging the hardware key. You can choose to have your license coupled with one computer (named Fixed license) or with multiple computers (Floating license). Data Analysis: Phase Dispersions and Couplings: - In the Phase Dispersions and Couplings analysis sheets, the Normal Mean has been removed from both sheets because of its problematic interpretation. - A bug was fixed that caused the average CStat Mean of Phase Dispersions to fall outside the allowed range (-50% to 75%). - In the Phase Dispersions and Couplings analysis sheets, the CStat Mean is reported within the following ranges: - For Phase Dispersions: -50% to 50%. Note that a value of 55% is the same as -45% in the circular statistics domain. - For Couplings: 0% to 100%. - To measure the spread of data around a mean, two statistics are offered: the Angular Deviation (which is the same as the Standard Deviation in CatWalk XT 10.6 and earlier) and the Circular Standard Deviation (new in CatWalk 10.7). - If the average CStat Mean of Phase Dispersions is higher than 50%, it is reported as its complementary (negative) value. For example, the values of Phase Dispersions 50, 55 and 60 would give CStat Mean = 55%, but CatWalk XT 10.7 reports CStat Mean = -45%, which is the complementary negative value of 55% in the circular statistics domain. Excel Sheet for Calculating Circular Statistics: An Excel sheet has been added to your documentation that provides formulas for computing circular statistics. Circular Charts for Phase Dispersions and Couplings: Phase Dispersions and Couplings are expressed with circular statistics. Circular charts are ideal to visualize that kind of data. To facilitate interpretation of the results for those two groups of CatWalk parameters, in the Group Statistics and Charts screen the bar charts have been replaced by circular charts. New Colors in Data Visualization: The colors of many charts, for example those of footfall patterns and the timing view, have been adjusted in order to improve their accessibility to users with color vision deficiency. --- ## CatWalk XT 11 - Prepare Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-prepare-data-acquisition Chapter: CatWalk XT Prepare Data Acquisition Preparing Data Acquisition involves specifying: - Detection settings – To distinguish between paw prints and background noise. See below. - Acquisition settings – To specify settings for acquired runs. See the Acquisition Settings section. Detection Settings The aim of the Detection Settings is to achieve an optimal intensity range for the paw prints and to filter out background noise. This is done by putting an animal of average weight on the walkway and then adjusting the Camera Gain and Green Intensity Threshold. Additionally, you can adjust the intensity of the Green Walkway Light and/or Red Ceiling Light. You can have multiple Detection Settings Profiles, for example, one for mice and one for rats. Note: Please make sure you turn the lights off before configuring the Detection Settings or turn on red ambient lighting. To configure the Detection Settings: - First, put an animal on the walkway and make sure that it stays within the camera view. Also make sure the illuminated ceiling is lowered. - In the Detection Settings window, click the Reset Prints button to 'clean' the Prints view. - Click the Start Auto Detect button. The program now automatically adjusts both Camera Gain and Green Intensity Threshold in consecutive steps to achieve the optimal range. Adjustment of the Camera Gain results in a value for Maximum Green Intensity between 197 and 203 based on the prints in the Print view. Adjustment of the Green Intensity Threshold ensures that prints that do not contain pixels with an intensity above the Minimum Green Intensity are removed from the Print view. - When Auto Detection is finished successfully, a message appears. If detection of the toes is important (if you want to classify toes in the Interactive Footprints Measurement to calculate the Sciatic Functional Index), check whether manually adjusting the Camera Gain and Green Intensity Threshold might result in even better detection of the toes. - Optionally, increase the intensity of the Green Walkway Light and/or decrease the intensity of the Red Ceiling Light (with steps of 0.1) to further optimize detection of paws. Now re-do auto detection (step 1). As a rule of thumb, the Camera Gain value should be between 5 and 12 dB. - Click OK when you are done. Acquisition Settings Choose Setup > Acquisition Settings. In the Acquisition Settings, you can set the following: Background Image Here you can view the Background Image that you snap in the Acquisition pane. Run Settings - Auto abort runs when the duration exceeds ... seconds – When you select this option, data acquisition is automatically stopped when a run exceeds the set number of seconds. This option is different from the Maximum run duration in the Experiment Settings. When an animal exceeds the Maximum run duration, acquisition is not aborted but the run labeled 'non-compliant'. - Discard auto aborted runs – When you select this option, runs that are automatically aborted are removed. - Discard user aborted runs – When you select this option, runs for which acquisition was manually stopped are removed. - Discard runs not compliant with the Run Criteria – When you select this option, runs that do not comply with the Run criteria are automatically removed. - Discard incomplete prints at the start and end of a run – An incomplete print can result from a paw that is put on the edge of the defined walkway, either at the start or end of a run. This can result in incorrect data: for example, the calculated print area of such a paw underestimates the actual print area. When you select this option, incomplete prints are not included in the classification. See the section Run Settings in the CatWalk XT 11.0 Reference Manual for more details. Sound Feedback - Run start (1 beep) – When selected, you get one system beep when acquisition starts. - Run stop (2 beeps) – When selected, you get two system beeps when acquisition stops. - Error (3 beeps) – When selected, you get three system beeps when an error occurs (for example, if the camera connection gets lost). When you are finished with the Acquisition Settings, click OK. Proceed to Acquisition by clicking >> Open Acquisition at the bottom-right corner of the screen or choose Acquire menu > Open Acquisition. Acquire the Data We recommend that you acquire the data with the lights in the test room turned off, or under ambient red light conditions. Make sure that the red light is not situated straight above the camera. Also make sure the illuminated ceiling is lowered. To carry out Data Acquisition, do the following: - Under Trial Selection, select an existing trial or create a new trial. You can also select a specific trial in the Experiment Explorer; right-click a trial and select Acquire Runs. - In the Video section, click the Snap Background button to snap an image of the empty walkway. - Optionally, the walkway can be checked if it is still OK. If, for example, the side walls are moved, the walkway detection should be redone. See setting up the walkway. - Click the Start Acquisition button (or press Page Up). - Put the animal on the walkway (ensure it is not in the camera view). To do this, put the animal in from the side. Recording a run starts automatically as soon as the animal's body contour is detected in the camera image. Recording a run stops automatically when the animal has completely disappeared from the camera image. - Data Acquisition stops: - Automatically, when the minimum number of compliant runs (as set in the Experiment Settings) has been acquired. - When you click the Stop Acquisition button (or press Page Down). - What do you want to do next? - Acquire the next trial – Select Acquire Next Trial in the Acquisition Finished Tasks window and go back to step 1 above. - Create and acquire a new trial – Select Acquire New Trial in the Acquisition Finished Tasks window or select create a new trial from the list under Trial Selection. - Classify runs – Select Classify Runs in the Acquisition Finished Tasks window or click >> Classify Runs at the bottom-right of the Acquisition screen. - Review runs – Select Review Runs in the Acquisition Finished Tasks window and under Video, select a run from the View list. - Remove runs – Close the Acquisition Finished Tasks window, click a run in the list with Acquired Runs and click the Remove Run(s) button at the bottom. Alternatively, in the Experiment Explorer, right-click a run and select Remove. Source: CatWalk XT 11.0 Quick Start Guide, Noldus Information Technology --- ## CatWalk XT 11 - Prepare Data Acquisition - 4.2 Configure the Detection Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-prepare-data-acquisition-42-configure-the-detection-settings Chapter: CatWalk XT 4.2 Configure the Detection Settings Introduction to Detection Settings The aim of the Detection Settings is to achieve an optimal intensity range for the paw prints and to filter out background noise. This is done by putting an animal of average weight on the walkway and then adjusting the Camera Gain and Green Intensity Threshold. Optionally, you can adjust the voltage (intensity) of the green and red lights in, respectively, the walkway and the illuminated ceiling. CatWalk provides quantitative feedback in order to define an optimal range between the minimum and maximum print intensity. Make sure to turn the lights off before configuring the Detection Settings. Alternatively, you can work under red light conditions. Make sure you avoid the red ambient light from shining directly into the camera. Make sure you completely open the camera's aperture and you focus the camera. Detection Settings are stored in a Detection Settings profile. You can create multiple Detection Settings profiles of which one is active during acquisition. When you start up CatWalk XT for the first time, two Detection Settings profiles are present: Rats and Mice. You can configure Detection Settings both automatically and manually. We recommend to first carry out auto detection and then manually fine-tune the settings. Basic Procedure - Carry out auto detection to get optimal values for Camera Gain and Green Intensity Threshold. - Adjust the Camera Gain and Green Intensity Threshold to further optimize detection. - If necessary, adjust the Green Walkway Light and/or Red Ceiling Light to further increase the quality of the paw prints. Auto Detection - First, put an animal on the walkway. Make sure the illuminated ceiling is lowered. - In the Profiles Explorer, double-click the Detection Settings profile you want to use: Mice or Rats. The difference between the Mice and Rats Detection Settings profile is the default intensity of the Green Walkway Light (Mice: 16.5 Volts, Rats: 16.0 Volts). For both Mice and Rats, the default value for Camera Gain is 20, for Green Intensity Threshold is 0.10 and for Red Ceiling Light is 17.7 Volts. - Click the Reset Prints button and then the Start Auto Detect button. The program now automatically adjusts both Camera Gain and Green Intensity Threshold in consecutive steps to achieve the optimal range. Adjustment of the Camera Gain results in a value for Maximum Green Intensity between 197 and 203 based on the prints in the Print view. Adjustment of the Green Intensity Threshold ensures that prints that do not contain pixels with an intensity above the Minimum Green Intensity are removed from the Print view. It is important in this step that the animal walks through the camera view a number of times for proper determining of the detection settings. If the animal just sits still, the detection settings might not work for a moving animal. - When Auto Detection is finished successfully, a message appears. - You can now do the following: - Accept the settings and proceed to Acquisition Settings. - Manually adjust the Camera Gain and Green Intensity Threshold to tweak the quality of the paw prints. Furthermore, you can adjust the intensity of the Green Walkway Light and/or Red Ceiling Light. This might be useful if you work with either very heavy or very light animals and the default settings in the Detection Settings profiles Rats and Mice do not result in optimal detection of the paws. Also, decreasing the intensity of the Red Ceiling Lights might result in better detection of toes for use with the Interactive Footprint Measurements. Auto Detection Settings Under Auto Detection Settings you can set the following: - Maximum Range From – The Camera Gain is automatically adjusted until the Maximum Green Intensity (displayed under Results) reaches a value within this range. The default range is between 197 and 203. - Frames Before Delta – This parameter determines how many video frames with prints should be detected before the Camera Gain is auto adjusted. A print should contain at least one pixel with an intensity above the Intensity Minimum value. The default number of frames is 5. Note: the frame rate of the CatWalk camera is 100 frames per second. - Intensity Minimum – This is the minimum value for the intensity. Each print should contain at least one pixel with an intensity above the Intensity Minimum. The default value is 85. Prints caused by background noise (such as other light sources than the green LEDs, or dirt) that do not contain a single pixel with an intensity above 85 are automatically removed by an increase of the Green Intensity Threshold. Manual Detection - First, put an animal on the walkway. Make sure the illuminated ceiling is lowered. - Choose Setup > Detection Settings. As soon as the Detection Settings window opens, the Print view shows the animal's cumulative prints. Under Results, the Maximum and Minimum Green Intensity of all prints shown in the Print view are displayed, based on the current settings of the Camera Gain and Green Intensity Threshold shown under Detection Settings. The Camera Gain (dB) determines the Maximum Green Intensity; the Green Intensity Threshold determines the Minimum Green Intensity. - Under Detection Settings, adjust the Camera Gain until the Maximum Green Intensity value for these prints is approximately 203. The absolute maximum intensity for prints is 255. --- ## CatWalk XT 11 - Prepare Data Acquisition - Prepare Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-prepare-data-acquisition-prepare-data-acquisition Chapter: CatWalk XT Prepare Data Acquisition 4.1 Train the Animals Before you start acquiring runs, animals need to learn to cross the walkway without interruptions or hitches so all animals start from a similar baseline. This is important in order to be able, during an experiment, to compare different runs and pick up gait abnormalities that are the result of effects of treatment rather than differences in quality of runs. Below you find a description of a training procedure that you can adapt to suit your experimental setup: - Habituate the animal to the CatWalk system by placing it in the corridor for 1 minute on a number of consecutive days until it freely explores the walkway. Make sure the corridor walls are together as close as possible so the animal is still able to comfortably walk in between the walls but is not able to meander too much from side to side. - One week prior to treatment, train the animals to run across the glass plate with a minimum of three runs per day. You can condition the animals to run by signaling the availability of a food pellet at the other end of the walkway using a conspicuous auditory or visual cue placing food pellets. If necessary, subject the animals to mild food restriction or deprivation. - The training criterion could then be that the animal crosses the walkway without any interruptions or hitches, in three consecutive runs. You can use all sorts of incentives to facilitate runs across the walkway. You can use normal food pellets but also special rodent sweets or candy. Using the special goal box also facilitates the animal crossing the walkway. The time it takes for the average animal to cross the glass plate can be used as a basis for the run criteria. Tips From CatWalk XT Users Training Animals in a Different Environment Some users find it more convenient to train an animal to cross a certain distance, similar to the length of the walkway, in another apparatus than the CatWalk system. For example, you can start training an animal to run from one side of an open field to the other. Once it has learnt to run this distance, you can let it run on the walkway. Using Home Cage Mates If you use the goal box, let all animals from a home cage habituate together in the goal box. For example, the first time for five minutes, the next time for two-three minutes. In that case you must make sure that only one rat crosses the walkway and the others stay in the goal box, for example using a sliding door between the walkway and the goal box entrance. When the animal approaches the goal box, open the sliding door and close it carefully to avoid pinching the animals' tail after it has entered that cage. How Long Should You Wait? Let the animal find its own way to the other end of the walkway, without trying to force it in any way. Wait up to for example 15-20 minutes. Experience shows that patience produces good results. --- ## CatWalk XT 11 - Prepare Data Acquisition - Prepare Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-prepare-data-acquisition-prepare-data-acquisition-nsN Chapter: CatWalk XT Prepare Data Acquisition Adjusting Camera Gain and Green Intensity Threshold As a result, under Results, the Maximum and Minimum Green Intensity, and Range are changed, based on the current values for Camera Gain and Green Intensity Threshold. Each time you adjust Camera Gain, the prints in the Prints view are reset. - If necessary, increase the Green Intensity Threshold to remove noise, that is, prints in the Print View that are not paws. As a result, in the Print view, the noise is filtered out and under Results, the Minimum Green Intensity and Range both change. - Click OK when you are done. Adjusting the Intensity of the Green Walkway Light and/or the Red Ceiling Light Adjust the intensity of the Green Walkway Light when the Camera Gain reaches its maximum or minimum value; this can occur if, respectively, the animal's paws exert too little pressure on the glass plate or if there is too much background noise. You get an error message if this happens. For example, with a large, heavy rat, the Camera Gain can drop below the minimum value of 6. In that case, decrease the Green Walkway Light intensity from the default 16.0 to 15.5. Next, re-do auto detection. If detection of the toes is important (for example, if you want to classify toes in the Interactive Footprint Measurements to calculate the Sciatic Functional Index), make sure to check whether manually adjusting the intensity of the Green Walkway Light (in steps of 0.25) might result in even better detection of the toes, especially for light-weighted animals. Also, reducing the intensity of the Red Ceiling Light might increase the detection of the toes. In the optimal example, the animal and its full body contour are clearly visible upon entering the walkway. If the Red Ceiling Light intensity is too low, the animal is only detected when it has already entered the walkway and the body contour is not fully visible, which results in poor performance of the automatic classification. We recommend adjusting the intensity of the Green Walkway Light and/or the Red Ceiling Light after determining the optimal values for Camera Gain and Green Intensity Threshold. As a rule of thumb, the optimal value for Camera Gain ranges between 5 and 12 dB. If the value of Camera Gain is far outside this range (for example, 3 or 25), adjust the intensity of the Green Walkway Light and re-do auto-detection until the Camera Gain is within the optimal range (5–12 dB). Specifying the Acquisition Settings Choose Setup > Acquisition Settings. When you have snapped a Background Image before acquisition (indicated by a check mark icon), you can view it by clicking the View Background Image button. When the Background Image does not cover the area of interest of the walkway, you should (re-)define the walkway. Run Settings You can specify the following settings: - Auto Abort Runs When the Duration Exceeds ... Seconds – When selected, this option automatically stops acquisition when the set time is exceeded. The Auto Abort Run option is different from the Maximum Run Duration in the run criteria. When the animal exceeds the Maximum Run Duration, the run is marked non-compliant but acquisition is not aborted. CatWalk XT stops recording automatically when the run duration reaches 60 seconds. Runs longer than 60 seconds generate so much data that it can impede the computer's performance. - Discard Auto Aborted Runs – When selected, CatWalk automatically deletes runs that exceed the time set in the Auto Abort Runs option. - Discard User Aborted Runs – When selected, runs that are stopped by the user are deleted. When this option is not selected and you manually stop acquisition during a run, the run is saved. - Discard Runs Not Compliant with the Run Criteria – When selected, runs that do not meet the run criteria are automatically deleted. - Discard Incomplete Prints at the Start and End of a Run – When selected, paw prints or parts of paw prints on the border of the walkway are not included in the classification (that is, CatWalk draws no rectangle around the print). Including incomplete prints in the analysis affects parameters such as Print Area or Max Contact Area. Please note that if a paw print consists of sub-prints (for example, toes), the sub-prints that are not on the border of the walkway are not discarded. As a result, sub-prints that are not on the border are included in the classification while sub-prints on the border are not. To discard the complete print, select all labeled sub-prints and label them as Junk. Sound Feedback It might be useful to get auditory feedback (system beep) on the status of acquisition, especially when you are not able to view the runs on the monitor. You can select the following: - Run Start (1 Beep) – When selected, you get one system beep when acquisition starts. - Run Stop (2 Beeps) – When selected, you get two system beeps when acquisition stops. - Error (3 Beeps) – When selected, you get three system beeps if an error occurs, such as a lost camera connection. Turn Sound Feedback off when you suspect it might disturb the animals. Source: CatWalk XT 11.0 Reference Manual - Prepare Data Acquisition, Noldus Information Technology --- ## CatWalk XT 11 - Select The Data For Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-select-the-data-for-analysis Chapter: CatWalk XT Select the Data for Analysis Data Segmentation Profiles Using a Data Segmentation Profile, you can select one part from each run which complies with three parameters (minimum number of consecutive steps, range of desired speed, maximum allowed speed variation). This is useful, for example, if you have a run in which the animal briefly stopped at the beginning of a run but then continued to walk normally. With a Data Segmentation Profile, select only the 'good' part of the run for analysis and export. - Choose Profiles > Data Segmentation Profile > New. - Under Parameters, you can set the following: - Minimum number of consecutive steps per run – Only the part of the run with the minimum number of consecutive steps which complies with the next two parameters is selected. We advise you to use at least 12 consecutive steps. - Average speed should range from (in distance unit/second) – Only the part of the run which complies with the set speed range is selected. - Maximum allowed speed variation (in percent) – Only the part of the run which complies with the maximum allowed speed variation is selected. Note: All profiles in CatWalk XT are used for all experiments stored on your computer. If you make a change in a profile, this change is applied to all experiments that you open afterwards. Selected Data Overview Tab The results of your data segmentation are shown under Results: The Selected Data Overview sheet shows, per Treatment Group and Time Point, the number of Selected Animals / Runs / Steps, the Total number of Animals / Runs / Steps in the experiment, and the Percentage of selected Animals / Runs / Steps. You can choose whether you want to see the selected Animals, Runs, or Steps by selecting the corresponding option at the bottom. The chart on the right is a graphical representation of the selected data. You can choose whether you want Time Points or Treatment Groups displayed on the x-axis by selecting the corresponding option at the bottom. The number of Selected Steps and Total Steps per Treatment Group for each Time Point are also displayed in the bar chart on the right. Complete Data Overview Tab In the matrix, the average speed intervals (1 to 10 cm/sec, 1 to 20 cm/sec, 1 to 30 cm/sec, etc.) are displayed on rows. The speed variation is displayed in 10% intervals on columns. Each cell in the matrix shows the resulting number of steps for a specific combination of average speed and speed variation. The 3D chart shows a graphical representation of the data in the matrix. Select the Analysis Parameters Parameter Profiles In a Parameter Profile, you specify which parameters you want to calculate. You can create multiple Parameter Profiles to produce results tables with specific parameters. To create a Parameter Profile: - Do one of the following: - Choose Profiles > Parameter Profile > New. - In the Profiles Explorer, right-click Parameter Profiles and select Add New Profile. Enter a name for the new Parameter Profile. - Select Paws, Paw combinations for Phase Dispersions and Couplings, and the Parameters you want to display and export. - Click OK. The newly created Parameter Profile is added in the Profiles Explorer and set to active. Notes: - The selection in a Parameter Profile affects the Paw Statistics, Phase Dispersions, and Couplings result tables. - Only parameters selected in the active Parameter Profile are analyzed and exported. - All profiles in CatWalk XT are used for all experiments stored on your computer. If you make a change in a profile, this change is applied to all experiments that you open afterwards. Tip: If you have multiple Parameter Profiles, you can make a specific one active by right-clicking a Parameter Profile and selecting Set as Active. The currently active Parameter Profile is displayed in bold and blue in the Experiment Explorer. Analyze the Data Visualization - Choose Analyze > View Run Visualizations. - Under Trial & Run Selection, select a trial and run from the list. - Under Video, select a playback speed from the list and play back the run by pressing the play button or by moving the slider. - Under Visualizations, click the tab: - 3D Footprint Intensities – To display the print intensities for each individual frame of a stance for all paws. The 3D charts can be rotated in all directions. - 2D Footprint Intensities – To view the print intensities of the paws. The red line represents the maximum intensity found in the frame. The colored area under the red line represents the mean intensity in the frame. - Footfall Patterns – To view the order in which the paws were placed on the glass plate. Paw prints which are not selected in the currently active Data Segmentation Profile are displayed in gray in the video window and are not displayed in the Visualizations. Run Statistics - Choose Analyze > View Run Statistics. - Under Trial & Run Selection, select a trial and run. - Under Statistics, click on one of the tabs to see the analysis results sheet of the corresponding parameter(s). Which parameters you see in the Paw Statistics sheet and Phase Dispersions/Couplings sheet depends on the data selection you made in the currently active Parameter Profile. For some results sheets, click in the cells to view more details under Views. Paw prints that are not selected in the currently active Data Segmentation Profile are displayed in gray. For these non-selected prints, no run statistics are calculated. Group Statistics and Charts You can calculate the statistics of all parameters, grouped per treatment group and time point, and view the corresponding charts. - Make sure you have selected the right Data Segmentation Profile and Parameter Profile. - Choose Analyze > View Group Statistics and Charts. - Under Numerical Results, click a category to display the results. - Under Graphical Results, click a category to view the corresponding parameter charts. To customize your charts, under Graphical Results, click the customize icon. Source: CatWalk XT 11.0 Quick Start Guide, Noldus Information Technology --- ## CatWalk XT 11 - Set Up an Experiment - Define the Trial List URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-define-the-trial-list-lsX Chapter: CatWalk XT Define the Trial List In the Trial List you can enter a number of variables for the trials you plan to acquire. Open the Trial List Do one of the following: - Choose Setup > Trial List. - Click the Trial List icon. - In the Experiment Tasks window, select Open Trial List. - In the Experiment Explorer, under Setup, double-click Trial List. Add Trials - Click the Add Trial(s) button. - In the Add Trial(s) window, enter the Number of Trials you want to add for each time point and treatment group you defined in the Experiment Settings and click Add. We advise you not to add more than 500 trials per experiment. Repeat this step for each time point and treatment group combination. - If necessary, re-assign a treatment group to a trial or animal by selecting a treatment group from the list. - You can now define the following user variables: - Animal – Click a cell in the Animal ID column to change the animal ID. - Time Point – Select a time point from the predefined list in the Time Point column. - Description – Optionally, you can enter a Description. This description is also exported to an export file with the statistics and can be used as an independent variable. The Trial name Trial0001, Trial0002, etc. is used as an ID to identify individual trials. Therefore, trial names must be unique. You can edit trial names. System Variables The Trial List also displays the following system variables for each trial: - Acquisition Status – Shows the acquisition status of a trial. The status can be Planned, Partially Acquired, or Acquired. - Total Runs – Shows the number of acquired runs. - Compliant Runs – Shows the number of acquired runs that meet the run criteria. - Classification Status – Shows the classification status of the acquired runs of a trial. The status can be Not Classified, Partially Classified, or Classified. Delete a Trial Do one of the following: - In the Trial List, select the trial you want to delete and click the Delete Trial(s) button. You can select multiple trials by selecting the first trial, pressing and holding the Shift key, and selecting the last trial. To select multiple individual trials, press and hold the Ctrl key and select the trials. - In the Experiment Explorer, right-click a trial and select Delete. Deleting a trial cannot be undone. It is not possible to delete an active trial. Sort the Trial List You can sort each column of the Trial List by clicking its column header. Although you can sort the Trial List and/or edit trial names, in Acquisition the order of trials is always the original order when the Trial List was created. Copy and Paste Contents in the Trial List - Select the contents of the cell, then right-click and select Copy (Ctrl+C). - Click the cell where you want to paste the text, right-click and select Paste, or press Ctrl+V. Note that you cannot copy and paste multiple cells from Excel. Experiment Setup Profiles You can save the current Experiment Settings, time points, treatment groups, and Trial List to an Experiment Setup profile. You can have multiple Experiment Setup profiles. When you create a new experiment, you select an Experiment Setup profile so those settings are copied to the new experiment without the trials. Add an Experiment Setup Profile To create a new Experiment Setup profile that contains the current Experiment Settings and Trial List: - Do one of the following: - In the Profiles Explorer, right-click Experiment Setup Profiles and select Add New Profile. - Choose Profiles > Experiment Setup Profile > New. - Select Create an Experiment Setup Profile from the current experiment. When you select Create a Blank Experiment Setup Profile, an Experiment Setup profile is created with default experiment settings and no time points, treatment groups, or trials. - Enter a name and click Add. - If necessary, make adjustments and click OK to store the profile. Open an Experiment Setup Profile Do one of the following: - In the Profiles Explorer, right-click an Experiment Setup profile and select Open. - Choose Profiles > Experiment Setup Profile > Open, then select a profile from the list and click Open. Duplicate an Experiment Setup Profile - In the Profiles Explorer, right-click an Experiment Setup profile and select Duplicate. - Enter a name and click OK. Rename an Experiment Setup Profile - In the Profiles Explorer, right-click an Experiment Setup profile and select Rename. - Type in a name and press Enter. Delete an Experiment Setup Profile Do one of the following: - In the Profiles Explorer, right-click an Experiment Setup profile, select Delete, and click Yes. - Choose Profiles > Experiment Setup Profile > Delete, then select a profile from the list and click Delete. Set Your Preferences - Choose File > Preferences, or click the Preferences icon on the toolbar. - Click the tab that applies and make the necessary changes: - General – Choose the Distance Unit (Millimeters, Centimeters, or Inches) and the Number of Decimals shown for Numbers, Times, and Percentages. - Folders and Auto Save – Optionally, change the default location of new experiments, new backup files, and the export folder. Here you can also turn Auto Save on or off and set the auto save interval. - Colors – Choose the colors in which paws and other body parts are displayed in the Print and Timing View. --- ## CatWalk XT 11 - Set Up an Experiment - Define the Trial List URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-define-the-trial-list Chapter: CatWalk XT Define the Trial List In the Trial List you can enter a number of variables for the trials you plan to acquire. Open the Trial List Do one of the following: - Choose Setup > Trial List. - Click the Trial List icon. - In the Experiment Tasks window, select Open Trial List. - In the Experiment Explorer, under Setup, double-click Trial List. Add Trials - Click the Add Trial(s) button. - In the Add Trial(s) window, enter the Number of Trials you want to add for each time point and treatment group you defined in the Experiment Settings and click Add. It is advised not to add more than 500 trials per experiment. Repeat this step for each time point and treatment group combination. - If necessary, re-assign a treatment group to a trial or animal by selecting a treatment group from the list. - You can now define the following user variables: - Animal – Click a cell in the Animal ID column to change the animal ID. - Time Point – Select a time point from the predefined list in the Time Point column. - Description – Optionally, enter a description. This description is also exported to an export file with the statistics and can be used as an independent variable. The trial name (Trial0001, Trial0002, etc.) is used as an ID to identify individual trials. Trial names must be unique. You can edit trial names. System Variables The Trial List also displays the following system variables for each trial: - Acquisition Status – Shows the acquisition status of a trial. The status can be Planned, Partially Acquired, or Acquired. - Total Runs – Shows the number of acquired runs. - Compliant Runs – Shows the number of acquired runs that meet the run criteria. - Classification Status – Shows the classification status of the acquired runs of a trial. The status can be Not Classified, Partially Classified, or Classified. Delete a Trial Do one of the following: - In the Trial List, select the trial you want to delete and click the Delete Trial(s) button. You can select multiple trials by selecting the first trial, pressing and holding the Shift key, and selecting the last trial. To select multiple individual trials, press and hold the Ctrl key and select the trials. - In the Experiment Explorer, right-click a trial and select Delete. Deleting a trial cannot be undone. It is not possible to delete an active trial. Sort the Trial List You can sort each column of the Trial List by clicking its column header. Although you can sort the Trial List and edit trial names, in Acquisition the order of trials is always the original order in which the Trial List was created. Copy and Paste Contents in the Trial List - Select the contents of the cell, then right-click and select Copy (Ctrl+C). - Click the cell where you want to paste the text, right-click and select Paste, or press Ctrl+V. Note that you cannot copy and paste multiple cells from Excel. Experiment Setup Profiles You can save the current Experiment Settings, time points, treatment groups, and Trial List to an Experiment Setup profile. You can have multiple Experiment Setup profiles. When you create a new experiment, you select an Experiment Setup profile so that those settings are copied to the new experiment without the trials. Add an Experiment Setup Profile - Do one of the following: - In the Profiles Explorer, right-click Experiment Setup Profiles and select Add New Profile. - Choose Profiles > Experiment Setup Profile > New. - Select "Create an Experiment Setup Profile from the current experiment." When you select "Create a Blank Experiment Setup Profile," a profile is created with default experiment settings and no time points, treatment groups, or trials. - Enter a name and click Add. - If necessary, make adjustments and click OK to store the profile. Open an Experiment Setup Profile Do one of the following: - In the Profiles Explorer, right-click an Experiment Setup profile and select Open. - Choose Profiles > Experiment Setup Profile > Open. Next, select a profile from the list and click Open. Duplicate an Experiment Setup Profile - In the Profiles Explorer, right-click an Experiment Setup profile and select Duplicate. - Enter a name and click OK. Rename an Experiment Setup Profile - In the Profiles Explorer, right-click an Experiment Setup profile and select Rename. - Type in a name and press Enter. Delete an Experiment Setup Profile Do one of the following: - In the Profiles Explorer, right-click an Experiment Setup profile, select Delete, and click Yes. - Choose Profiles > Experiment Setup Profile > Delete. Next, select a profile from the list and click Delete. Set Your Preferences - Choose File > Preferences or click the Preferences icon on the toolbar. - Click the tab that applies and make the necessary changes: - General – Choose the Distance Unit (Millimeters, Centimeters, or Inches) and the Number of Decimals shown for Numbers, Times, and Percentages. - Folders and Auto Save – Optionally, change the default location of new experiments, new backup files, and the export folder. Here you can also turn Auto Save on or off and set the auto save interval. - Colors – Choose the colors in which paws and other body parts are displayed in the Print and Timing View. --- ## CatWalk XT 11 - Set Up an Experiment - Open the Experiment Settings Screen URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-open-the-experiment-settings-screen-bdQ Chapter: CatWalk XT Open the Experiment Settings Screen Do one of the following: - Choose Setup > Experiment Settings. - In the Experiment Tasks window, click Experiment Settings. - Click the Experiment Settings icon in the toolbar. - In the Experiment Explorer, under Setup, double-click Experiment Settings. Animal Type As Animal Type you can select Rat or Mouse. The Automatic Footprint Classification (AFC) module uses a different algorithm depending on whether you select Rat or Mouse. Furthermore, the Sciatic Functional Index, which is only available if you have the Interactive Footprint Measurements (IFM) module, is calculated differently for rats and mice. When you do not have the AFC or IFM module, it does not matter which Animal Type you choose. However, when you later want to use the AFC and/or IFM module in the same experiment, you should select the correct Animal Type. For the IFM module, make sure in the Detection Settings that the animals' toes are detected properly. Time Points Under Time Points, define the time points at which you carry out data acquisition. Use time points to distinguish between trials of the same animal. Add Time Points - Click the Add Time Point button once to add one time point, or more than once to add multiple time points. - Click the name to type in the name for a time point. - Optionally: - Add a Description for a time point. - Click the cell under Fill Style and change the color in which the time point is displayed in the Group Statistics and Charts screen. - Repeat the previous steps to add additional time points. Delete Time Points - Click on a time point name. To select multiple items, click them while holding the Ctrl key. - Click the Delete Time Point(s) button and click Yes. Treatment Groups Under Treatment Groups, predefine your groups. Add Treatment Groups - Click the Add Group button. - In the new row of the table, from the list in the Type column select one of the predefined types (Undefined, Experimental, Control, and Sham). - In the Name column, type the name of the Treatment Group. Change the Name of a group to reflect the type of treatment group, because the Name of the treatment group is used in the analysis. - Optionally: - Add a Description for that group. This description is also exported to an export file with the statistics and can be used as an independent variable. - Click the cell under Fill Style and change the color in which the treatment group is displayed in the Group Statistics and Charts screen. Delete Groups - Click in the row of the groups you want to remove. You can select multiple groups by clicking rows while holding the Ctrl key. - Click the Delete Group(s) button and click Yes. Copy and Paste Values from One Cell to Another - Select the contents of the cell. - Right-click the cell and select Copy. - Select the cell in which you want to paste. - Right-click this cell and select Paste, or press Ctrl+V. Run Criteria Define run criteria to automatically check the quality of your runs in terms of mean running speed and variation in running speed. This automatic check is useful because it enables you to compare runs within and between animals. In order to achieve this, animals should be trained to cross the glass plate before they are eventually tested. Under Run Criteria you can set the following criteria: - Minimum Run Duration – When the animal is slower than this Minimum Run Duration, the run is marked non-compliant. - Maximum Run Duration – When the animal exceeds the Maximum Run Duration, the run is marked non-compliant. This does not stop data acquisition of this and the next runs. If you want to automatically abort data acquisition after a specific time, do this in the Acquisition Settings. - Minimum Number of Compliant Runs to Acquire – Data acquisition continues until this number of runs that meet the other three criteria (Minimum and Maximum Run Duration and Maximum Allowed Speed Variation) has been acquired. The maximum number of runs (compliant and non-compliant) to acquire per trial is 100. - Use Maximum Allowed Speed Variation – With this criterion you can check whether the animal walked very slowly during part of the run and then extremely fast during another part. When this happens, the run can still meet the Minimum and Maximum Run Duration criteria, but the variation in speed would be too high. The speed variation is calculated as follows: the run is divided into 5 intervals with equal duration. For each interval, the average speed is calculated and this speed is expressed as the percentage difference from the average speed of the total run. For example, an animal starts very slowly and its speed in the first interval is 5 cm/s. After that, it speeds up, resulting in an average speed of the total run of 20 cm/s. The speed variation is: ([absolute difference (5-20)] / 20) × 100 = 75% (expressed as a whole number). By default, Use Maximum Allowed Speed Variation is not selected. The run criteria become read-only when you have acquired a run. --- ## CatWalk XT 11 - Set Up an Experiment - Open the Experiment Settings Screen URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-open-the-experiment-settings-screen Chapter: CatWalk XT Open the Experiment Settings Screen Do one of the following: - Choose Setup > Experiment Settings. - In the Experiment Tasks window, click Experiment Settings. - Click the Experiment Settings icon in the toolbar. - In the Experiment Explorer, under Setup, double-click Experiment Settings. Animal Type As Animal Type you can select Rat or Mouse. The Automatic Footprint Classification (AFC) module uses a different algorithm depending on whether you select Rat or Mouse. Furthermore, the Sciatic Functional Index, which is only available if you have the Interactive Footprint Measurements (IFM) module, is calculated differently for rats and mice. When you do not have the AFC or IFM module, it does not matter which Animal Type you choose. However, when you later want to use the AFC and/or IFM module in the same experiment, you should select the correct Animal Type. For the IFM module, make sure in the Detection Settings that the animals' toes are detected properly. Time Points Under Time Points, define the time points at which you carry out data acquisition. Use time points to distinguish between trials of the same animal. Add Time Points - Click the Add Time Point button once to add one time point, or more than once to add multiple time points. - Click the name to type in the name for a time point. - Optionally: - Add a Description for a time point. - Click the cell under Fill Style and change the color in which the time point is displayed in the Group Statistics and Charts screen. - Repeat the previous steps to add additional time points. Delete Time Points - Click on a time point name. To select multiple items, click them while holding the Ctrl key. - Click the Delete Time Point(s) button and click Yes. Treatment Groups Under Treatment Groups, predefine your groups. Add Treatment Groups - Click the Add Group button. - In the new row of the table, from the list in the Type column select one of the predefined types: Undefined, Experimental, Control, or Sham. - In the Name column, type the name of the Treatment Group. Change the name to reflect the type of treatment group, because the Name of the treatment group is used in the analysis. - Optionally: - Add a Description for that group. This description is also exported to an export file with the statistics and can be used as an independent variable. - Click the cell under Fill Style and change the color in which the treatment group is displayed in the Group Statistics and Charts screen. Delete Groups - Click in the row of the groups you want to remove. You can select multiple groups by clicking rows while holding the Ctrl key. - Click the Delete Group(s) button and click Yes. Copy and Paste Values from One Cell to Another - Select the contents of the cell. - Right-click the cell and select Copy. - Select the cell in which you want to paste. - Right-click this cell and select Paste, or press Ctrl+V. Run Criteria Define run criteria to automatically check the quality of your runs in terms of mean running speed and variation in running speed. This automatic check enables you to compare runs within and between animals. In order to achieve this, animals should be trained to cross the glass plate before they are eventually tested. Under Run Criteria you can set the following criteria: - Minimum Run Duration – When the animal is slower than this minimum run duration, the run is marked non-compliant. - Maximum Run Duration – When the animal exceeds the maximum run duration, the run is marked non-compliant. Note that this does not stop data acquisition of this and the next runs. If you want to automatically abort data acquisition after a specific time, do this in the Acquisition Settings. - Minimum Number of Compliant Runs to Acquire – Data acquisition continues until this number of runs that meet the other three criteria (Minimum and Maximum Run Duration and Maximum Allowed Speed Variation) has been acquired. The maximum number of runs (compliant and non-compliant) to acquire per trial is 100. - Use Maximum Allowed Speed Variation – With this criterion you can check whether the animal walked very slowly during part of the run and then extremely fast during another part. When this happens, the run can still meet the Minimum and Maximum Run Duration criteria, but the variation in speed would be too high. The speed variation is calculated by dividing the run into 5 intervals of equal duration, calculating the average speed for each interval, and expressing that speed as the percentage difference from the average speed of the total run. For example, if an animal starts at 5 cm/s and the average speed of the total run is 20 cm/s, the speed variation is ([absolute difference (5–20)] / 20) × 100 = 75%. By default, Use Maximum Allowed Speed Variation is not selected. The run criteria become read-only once you have acquired a run. --- ## CatWalk XT 11 - Set Up an Experiment - Set Up an Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-set-up-an-experiment Chapter: CatWalk XT Set Up an Experiment 3.1 Start CatWalk XT Turn On the CatWalk System Prerequisites - If you upgrade from CatWalk XT 8/9, you need the CatWalk Control Unit. Contact your nearest Noldus representative for information. - If you upgrade from CatWalk XT 10.0, you need to upgrade the firmware of the Control Unit. Contact the Noldus Help desk. - See the CatWalk XT Assembly Instructions on the installation disc to install the CatWalk system and the Control Unit. Procedure - Check that the on-off switch of the walkway (located on the left side) is turned on. The Control Unit must be connected to the camera, walkway and illuminated ceiling. The Control Unit must also be connected to the CatWalk XT computer via a USB cable if you want to acquire data. For this, your computer must have a USB-C port. Make sure the Control Unit is not connected to the mains socket yet. - Connect the Control Unit to the mains socket, and on the Control Unit, turn the switch on. The red lights busy/alive and power on the Control Unit turn on, and the busy/alive light starts flashing. When the Control Unit is finished configuring the LED lights, both red lights turn off. The green and red LED lights of the CatWalk system flash until the correct intensity levels are reached. - Make sure you turn on the CatWalk system at least 15 minutes before you start using CatWalk. - To turn off the CatWalk system, turn the switch off on the Control Unit. Start CatWalk XT After turning on the CatWalk system, it can take a couple of minutes for the camera to be detected. This is indicated by the Acquiring Network icon in the Windows task bar. Note that the yellow triangle does not mean that something went wrong — it means that the PC has not found a network; however, the camera has been detected. Do not start CatWalk XT before this icon appears. To start CatWalk XT, double-click the CatWalk XT icon on the desktop. After starting CatWalk XT, you may get a message that the firmware of the Control Unit needs to be upgraded. Contact the Noldus Help desk. 3.2 Set Up the Walkway This section describes how to configure the software to ensure that recordings will have high quality. Make sure that the camera is in the correct vertical position before proceeding. Setting up the walkway involves these three steps: - Focusing the lens of the camera. - Calibrating the walkway so that CatWalk can convert pixels to real-life dimensions. - Defining the layout of the walkway by outlining the area inside the corridor that you want to record. For the first two steps, a dedicated tool is used: the calibration card. It must be placed in the walkway, separated from the corridor walls and positioned somewhere in the middle of the glass plate. All three functionalities can be accessed via the Setup menu or the Setup Walkway Tasks. Focus Assist The camera lens has two rings that can be turned: the aperture, which controls brightness, and the focus ring, which controls sharpness. Before focusing, make sure: - The aperture of the lens is fully opened so that the image appears bright and cannot be made brighter. - The calibration card is placed somewhere in the middle of the walkway. - You can see the PC screen when the camera is being focused. To start the Focus Assist, do one of the following: - In the Application Startup Tasks window, click Setup the Walkway and then Focus Assist. - Choose Setup > Focus Assist. - Click the Focus Assist icon in the toolbar. The top image shown is the original image from the camera. The bottom image shows only the sharp parts of the original image and is therefore a good indication of overall sharpness — the more white it shows, the sharper the image is. The crop buttons can be used to crop or uncrop the images. They have no effect on the reported values, colors, or sharpness indicator. The sharpness indicator shows the percentage of the maximum reachable sharpness. If the focusing procedure was disturbed in some way, it may be impossible to get the indicator to reach nearly 100%. In this case, the procedure must be redone: turn the focus ring slightly out of focus, close the dialog, then reopen it and repeat the procedure. Calibrate the Walkway After focusing the camera correctly, the walkway must be calibrated. Keep the calibration card in the same position in the walkway as it was used to focus the lens. To start the calibration, do one of the following: - In the Application Startup Tasks window, click Setup the Walkway and then Calibrate the Walkway. - Choose Setup > Calibrate Walkway. - Click the Calibrate Walkway icon in the toolbar. - Click Next in the Focus Assist dialog. In the Calibrate Walkway window, click Auto Calibration. If no error warning occurs, the calibration is created automatically. Press OK to save it, or Next/Previous to go to the next or previous step of the setup. Note that pressing Next or Previous also saves the calibration. Pressing Cancel discards the changes. If an error is shown: - Make sure that the calibration card is in the center of the walkway and is the only object on the walkway. - Make sure the red light is working correctly. - Make sure the camera lens aperture is fully opened. - The calibration can be set manually, but it is highly recommended not to do so. In general, if auto calibration fails, something is wrong with the setup. A message appears indicating what is wrong and how to fix it. Define the Layout of the Walkway To define the walkway layout, do one of the following: - In the Application Startup Tasks window, select Setup the Walkway and then click Define the Layout of the Walkway. - Choose Setup > Define Walkway. - Click the Define Walkway icon in the toolbar. - Click Next in the Calibrate Walkway dialog. In the Define Walkway window, you see the full camera image. If you do not see an image, open the camera's aperture and make sure the camera is focused correctly. - Press Detect Walkway. When no errors are reported, the walkway sides are found and a walkway covering 70% of the length of the walkway is defined automatically. You can make the walkway rectangle longer and reposition it. In general, moving or enlarging vertically should not be needed. If walkway detection fails, a message is shown. Failure of detection can be caused by other objects on the walkway, sub-optimal lighting conditions, or side walls of the corridor that are not aligned with the camera or with each other. These errors must be fixed before proceeding. - If desired, the walkway definition can be changed manually. Position the mouse pointer over the rectangle so it becomes a four-headed arrow, then drag the rectangle to the top-left corner of the area you want to outline. - Position the mouse pointer at the bottom-right corner of the rectangle so the pointer becomes a resize pointer. Drag the bottom-right corner to the bottom-right corner of the area of interest on the walkway. Make sure that all sides of the rectangle are visible within the camera view. Press OK to save the changes or Cancel to discard them. General Remarks on Setup When all three parts of the setup are successfully completed, the setup is correct: the camera is focused, the walkway is calibrated, and the walkway definition is specified. For an experiment with a specific hardware configuration, you only need to set up the walkway once, unless something changes to the hardware setup (for example, the camera was moved or the width of the corridor was changed). When you close an experiment, the layout of the walkway and the calibration are stored within the application. The next time you open CatWalk, the Application Startup Tasks window shows the last date and time the walkway was defined and calibrated. In the walkway calibration and definition dialogs, buttons for Previous and Next are available. When pressed, the changes are stored. After setting up the walkway, the side walls can still move slightly during normal use. Opening and closing the red light cover, or accidentally touching the side walls, can relocate them. When data acquisition is started, an additional check for the walkway is offered. Create a New Experiment - To create a new experiment, do one of the following: - In the Application Startup Tasks window, click Create a New Experiment. - Choose File > New Experiment or press Ctrl+N. - Click the New Experiment icon in the toolbar. - In the New Experiment window, enter the name of the experiment. The name cannot contain any of the following characters: / : * ? \ " < > | ' & . ; - Select a Setup Profile from the list. - Optionally, browse to the location where you want to save your experiment. Do not save your experiment to a USB stick, as this might result in a corrupt experiment. - Optionally, add a description and edit the name in the Created By field. - Click the Create Experiment button. 3.3 Specify the Experiment Settings Experiment Settings Screen In the Experiment Settings screen, you define the animal type, time points, treatment groups, and run criteria. These variables and values remain constant throughout the experiment but can potentially affect the outcome of the experiment. --- ## CatWalk XT 11 - Set Up an Experiment - Set Up an Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-set-up-an-experiment-AzA Chapter: CatWalk XT Set Up an Experiment 3.1 Start CatWalk XT Turn On the CatWalk System Prerequisites - If you upgrade from CatWalk XT 8/9, you need the CatWalk Control Unit. Contact your nearest Noldus representative for information. - If you upgrade from CatWalk XT 10.0, you need to upgrade the firmware of the Control Unit. Contact the Noldus Help desk. - See the CatWalk XT Assembly Instructions on the installation disc to install the CatWalk system and the Control Unit. Procedure - Check that the on-off switch of the walkway (located on the left side) is turned On. The Control Unit must be connected to the camera, walkway and illuminated ceiling. The Control Unit must also be connected to the CatWalk XT computer via a USB cable if you want to acquire data. For this, your computer must have a USB-C port. Make sure the Control Unit is not connected to the mains socket yet. - Connect the Control Unit to the mains socket, and on the Control Unit, turn the switch on. The red lights busy/alive and power on the Control Unit turn on, and the busy/alive light starts flashing. When the Control Unit is finished configuring the LED lights, both red lights turn off. The green and red LED lights of the CatWalk system flash until the correct intensity levels are reached. - Make sure you turn on the CatWalk system at least 15 minutes before you start using CatWalk. - To turn off the CatWalk system, turn the switch off on the Control Unit. Start CatWalk XT After turning on the CatWalk system, it can take a couple of minutes for the camera to be detected. This is indicated by the Acquiring network icon in the Windows task bar. Note that the yellow triangle does not mean that something went wrong. It means that the PC has not found a network; however, the camera has been detected. Do not start CatWalk XT before this icon appears. To start CatWalk XT, double-click the CatWalk XT icon on the desktop. After starting CatWalk XT, you may get a message that the firmware of the Control Unit needs to be upgraded. Contact the Noldus Help desk. 3.2 Set Up the Walkway Note: This section describes how to configure the software to make sure that recordings will have high quality. Make sure that the camera is in the correct vertical position first. See "Prepare the Walkway." Setting up the walkway involves these three steps: - Focusing the lens of the camera. - Calibrating the walkway – This is done so CatWalk can convert pixels to real-life dimensions. - Defining the layout of the walkway – In this step you outline the area of the walkway that you want to record, that is the area inside the corridor. For the first two steps, a dedicated tool is used: the calibration card. It must be placed in the walkway, separated from the corridor walls and somewhere in the middle of the glass plate. All three functionalities can be accessed by the Setup menu or by the Setup Walkway Tasks. Focus Assist The camera lens has two rings that can be turned: the aperture, which controls brightness, and the focus ring, which controls sharpness. Before focusing, make sure: - The aperture of the lens is fully opened. The image appears bright and it cannot be made brighter. - The calibration card is placed somewhere in the middle of the walkway. - You can see the PC screen when the camera is being focused. To start the Focus Assist, do one of the following: - In the Application Startup Tasks window, click Setup the walkway and then Focus Assist. - Choose Setup > Focus Assist. - Click the Focus Assist icon in the tool bar. The top image is the original image from the camera. The bottom image only shows sharp parts of the original image and therefore is a good indication of the overall sharpness. The more white it shows, the sharper the image is. The crop buttons can be used to crop or uncrop the images. They have no effect on the reported values, colors, and sharpness indicator. The sharpness indicator shows the percentage of the maximum reachable sharpness. If the focusing procedure was disturbed in some way, it may be impossible to get the indicator to reach nearly 100%. The procedure must be redone in this case. Turn the focus ring a bit out of focus and close the dialog, then reopen it and repeat the procedure. Calibrate the Walkway After focusing the camera correctly, the walkway must be calibrated. Keep the calibration card in the same position in the walkway as it was used to focus the lens. To start the calibration, do one of the following: - In the Application Startup Tasks window, click Setup the walkway and then Calibrate the walkway. - Choose Setup > Calibrate Walkway. - Click the Calibrate Walkway icon in the tool bar. - Click Next in the Focus Assist dialog. In the Calibrate Walkway window, click Auto Calibration. If no error warning occurs, the calibration is created automatically. Press OK to save it, or Next/Prev to go to the next or previous step of the setup. Note that on Next/Prev the calibration is saved as well. On Cancel the changes are not saved. If an error is shown: - Make sure that the calibration card is in the center of the walkway and is the only object on the walkway. - Make sure the red light is working correctly. - Make sure the camera lens aperture is fully opened. - The calibration can be set manually as well, but it is highly recommended not to do so. In general, if auto calibration fails, something is wrong with the setup. A message appears indicating what is wrong and how to fix it. Define the Layout of the Walkway Do one of the following: - In the Application Startup Tasks window, select Setup the walkway and then click Define the layout of the walkway. - Choose Setup > Define Walkway. - Click the Define Walkway icon in the tool bar. - Click Next in the Calibrate Walkway dialog. In the Define Walkway window, you see the full camera image. If you do not see an image, open the camera's aperture. Make sure the camera is focused correctly. - Press Detect Walkway. When no errors are reported, the walkway sides are found and a walkway that covers 70% of the length of the walkway is defined automatically. You can make the walkway rectangle longer and reposition it. In general, moving or enlarging vertically should not be needed. If the walkway detection fails, a message is shown. It is highly recommended to make sure that the detection is successful so no vertical changes are needed. Failure of detection can be caused by other objects on the walkway, sub-optimal lighting conditions, or side walls of the corridor that are not aligned with the camera or with each other. If these errors are found, they must be fixed. - If desired, the walkway definition can be changed manually. Position the mouse pointer over the rectangle so it becomes a four-headed arrow; drag the rectangle to the top-left corner of the area of the walkway you want to outline. - Next, position the mouse pointer at the bottom-right corner of the rectangle so the pointer becomes a resize pointer. Drag the bottom-right corner of the rectangle to the bottom-right corner of the area of interest on the walkway. Make sure that all sides of the rectangle are visible within the camera view. Press OK to save the changes or Cancel to ignore the changes. General Remarks on Setup When all three parts of the setup are successfully completed, the setup is correct. The camera is focused, the walkway is calibrated, and the walkway definition is specified. For an experiment with a specific setup of your CatWalk system, you only need to set up the walkway once, unless something changes to the hardware setup of the system (for example, the camera was moved or the width of the corridor was changed). When you close an experiment, the layout of the walkway and the calibration are stored within the application. Next time you open CatWalk, the Application Startup Tasks window shows the last date and time the walkway was defined and calibrated. In the walkway calibration and definition dialogs, buttons for Previous and Next are offered. When pressed, the changes are stored. After setting up the walkway, the side walls can still be moved slightly even when CatWalk is used normally. Opening and closing the red light cover, or accidentally touching the side walls can relocate them. When data acquisition is started, an additional check for the walkway is offered. See Carry Out Data Acquisition for details. 3.3 Create a New Experiment - To create a new experiment, do one of the following: - In the Application Startup Tasks window, click Create a new experiment. - Choose File > New Experiment or press Ctrl+N. - Click the New Experiment icon in the tool bar. - In the New Experiment window, enter the Name of the experiment. The name cannot contain any of the following characters: / : * ? \ " < > | ' & . ; - Select a Setup profile from the list. See Experiment Setup Profiles for more information. - Optionally, browse to the location where you want to save your experiment. Do not save your experiment to a USB stick because this might result in a corrupt experiment. - Optionally, add a Description and edit the name in the Created By field. - Click the Create Experiment button. 3.4 Specify the Experiment Settings Experiment Settings Screen In the Experiment Settings screen, you define the animal type, time points, treatment groups, and the run criteria. These variables and values stay constant throughout the experiment, but potentially affect the outcome of the experiment. --- ## CatWalk XT 11 - Set Up an Experiment - Set Up an Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-set-up-an-experiment-wAL Chapter: CatWalk XT Set Up an Experiment Application Preferences Colors have changed in CatWalk XT 11.0 to make them better distinguishable to most users. - Messages – We recommend to keep the option Regularly prompt for backup selected; every 10th time you save an experiment, a message appears reminding you to back up your experiment. Click OK to apply the new preferences. Colors Paws / Limbs / Other Select the colors that are used in the Timing View for Paws, Limbs and Other body parts. To change a color, click it and select a new color. Classification Select the colors of the rectangles and associated labels in the Print View. You can do this for Labeled, Unlabeled, Selected and Junk prints. To change a color, click it and select a new color. - Use individual colors for labeled prints – When you select this option, the labeled prints are displayed in the colors selected under Paws. When the option is not selected, all labeled prints are displayed in green. Source: CatWalk XT 11.0 Reference Manual - Set Up an Experiment, Noldus Information Technology --- ## CatWalk XT 11 - Set Up an Experiment - Set Up an Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-an-experiment-set-up-an-experiment-I0S Chapter: CatWalk XT Set Up an Experiment Preferences Overview Colors have changed in CatWalk XT 11.0 to make them better distinguishable to most users. - Messages – We recommend keeping the option Regularly prompt for backup selected; every 10th time you save an experiment, a message appears reminding you to back up your experiment. Click OK to apply the new preferences. Colors Paws / Limbs / Other Select the colors that are used in the Timing View for Paws, Limbs, and Other body parts. To change a color, click it and select a new color. Classification Select the colors of the rectangles and associated labels in the Print View. You can do this for Labeled, Unlabeled, Selected, and Junk prints. To change a color, click it and select a new color. - Use individual colors for labeled prints – When you select this option, the labeled prints are displayed in the colors selected under Paws. When the option is not selected, all labeled prints are displayed in green. Source: CatWalk XT 11.0 Reference Manual - Set Up an Experiment, Noldus Information Technology --- ## CatWalk XT 11 - Set Up Your Catwalk Xt Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-set-up-your-catwalk-xt-experiment Chapter: CatWalk XT Setting Up Your CatWalk XT Experiment Setting up an experiment involves the following steps: - Setting up the walkway - Creating a new experiment - Specifying experiment settings - Defining the trial list Setting Up the Walkway - For focusing the camera and calibration of the walkway, a calibration card is supplied. The card must be placed in the center of the walkway, separated from both corridor walls. - When you first start CatWalk XT, the Application Startup Tasks window appears. - Click Set up the Walkway. - The Setup Walkway Tasks dialog appears. - Click Focus Walkway. Follow the instructions shown on click Show Instructions. Make sure the aperture is fully opened (brightness is maximal) and focus of the camera is optimal. When finished, the green bar should be (nearly) 100%. Press Next: Calibration. - In the Calibrate Walkway window, a rectangle is displayed that represents the scale factors on the two axes. Click Auto Calibrate. The white rectangle will be automatically located in the correct location and will have the correct size. If auto calibration fails, a warning with instructions appears. If the calibration is OK, press Next: Define Walkway (OK) to proceed to the next step. The changes are stored. - In the Setup Walkway Tasks window, click Define the Layout of the Walkway. The Define Walkway dialog opens. Remove the calibration card or make sure it is not close to the walls and is in the center of the walkway. Press Detect Walkway. If successfully detected, the white rectangle will cover about 80% of the walkway and will be perfectly aligned with the side walls. If it is not detected automatically, a warning describes what is wrong. The walkway sides must be aligned with the camera image and must be parallel. If walkway detection was successful, make the white rectangle longer or shorter to define the area of the glass plate in which you want to record the paw prints of the animal. It should not be necessary to change the height of the white rectangle. Creating a New Experiment - To create a new experiment, in the Application Startup Tasks window, click Create a New Experiment or choose File > New Experiment. - Select a Setup Profile from the list. - Enter the name for your experiment, accept the default location or browse to a new location, and click the Create Experiment button. Specifying the Main Experiment Settings You can save the current Experiment Settings, Time Points, Treatment Groups, and Trial List to an Experiment Setup Profile. You can select an Experiment Setup Profile when you create a new experiment, so the experiment settings are copied to the new experiment. - Choose Setup > Experiment Settings, or in the New Experiment Tasks window, click Experiment Settings. - Define the time points: Time points are categories that represent predefined points in time relative to the administration of the treatment or any other event important in your study. Each animal is tested at those time points. For example, Pre-treatment, Day 1, Day 3, and Day 5. Under Time Points, click the Add Time Point button to add one or more time points. - Define the animal type: Choose the Animal Type (Rat or Mouse). The Automatic Footprint Classification module uses a different algorithm depending on whether you select Rat or Mouse. The Sciatic Functional Index is also calculated differently for rats and mice. - Define the treatment groups: - Under Treatment Groups, click Add Group to add one or more treatment groups. - In the Type column, select the type of treatment group from the list (Undefined, Experimental, Sham, or Control). - Optionally, in the Name column, change the name of the treatment group. - Optionally, enter a Description for that group. This information is also shown in the export file of both the Run and Trial Statistics. - Define the run criteria: Under Run Criteria, ensure that all runs are executed at approximately the same speed. Specify the following run criteria: - Minimum Run Duration – If it takes the animal less time than the set value, the run is labeled non-compliant. - Maximum Run Duration – If the animal exceeds the set value, the run is labeled non-compliant. - Minimum Number of Compliant Runs to Acquire – Data acquisition stops automatically when this criterion is met during a trial. - Use Maximum Allowed Speed Variation – When selected, if the animal exceeds the set value, the run is labeled non-compliant. - Proceed to the Trial List by clicking >> Trial List at the bottom-right of the screen, or choose Setup > Trial List. Defining the Trial List In the Trial List you add trials and animals for which you want to acquire runs. - Click the Add Trial(s) button at the bottom-left of the Trial List screen. - In the Add Trial(s) window, enter the Number of Trials you want to add for each treatment group defined in the Experiment Settings and click Add. - Click in a cell of the Trial or Animal column to change a label. Click in a cell of the Time Point column to add a time point (day, week, etc.). - If necessary, re-assign a Treatment Group to a trial or animal by selecting a treatment group from the list. - To proceed to Detection Settings, choose Setup > Detection Settings. To delete trials from the Trial List, click the row with the trial or animal you want to delete, and click the Delete Trial(s) button. Experiment Setup Profile You can save the current Experiment Settings and the Trial List in an Experiment Setup Profile, so you can re-use it when creating another experiment. - Choose Profiles > Experiment Setup Profile > New. - Select Create an Experiment Setup Profile from the current experiment. - Enter a name and click Add. - If necessary, make adjustments and click OK to store the profile. - When creating a new experiment, select that Experiment Setup Profile. Source: CatWalk XT 11.0 Quick Start Guide, Noldus Information Technology --- ## CatWalk XT 11 - Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-specifications Chapter: CatWalk XT System Configurations & Licensing CatWalk 11.0 is available with either a hardware key (USB dongle) or a software license. Software licenses offer two modes: License Types - Fixed License — Tied to a single computer. Deactivation required before transferring to another machine. May be activated online or offline (via QR code). - Floating License — Usable on multiple computers sequentially (not simultaneously). Requires internet connection on the acquisition computer. Multiple floating licenses allow simultaneous use. - Perpetual License — One-time purchase; software may be used indefinitely. - Time-Limited License — Valid for a defined period (typically 6 or 12 months). Online activation only. Analysis Mode CatWalk can be installed on additional computers without a license. In unlicensed analysis mode, users can open experiments, classify runs, create data and parameter profiles, run all analysis functions, and export all data and statistics. New data acquisition is not possible without a valid license. Data Management Experimental Setup - Animal Type — Select Rat or Mouse. Determines the Automatic Footprint Classification algorithm and the Sciatic, Tibial, and Peroneal Functional Index formulas. - Time Points — Define and label the time points at which data are acquired, with optional colour coding for group statistics. - Treatment Groups — Define groups with type (Undefined, Experimental, Control, Sham), name, description, and display colour. - Run Criteria — Set minimum and maximum run duration, minimum number of compliant runs to acquire, and an optional maximum allowed speed variation threshold. Runs not meeting criteria are marked non-compliant; acquisition continues until the required number of compliant runs is reached. - Trial List — Pre-plan trials with animal ID, time point, group assignment, and optional description. Trial names are unique identifiers. The list shows acquisition status, total runs, compliant runs, and classification status for each trial. File Management - Experiment Setup Profiles — Save and reuse a set of experiment settings (time points, treatment groups, trial structure) across new experiments. - Preferences — Distance unit (millimetres, centimetres, or inches), decimal precision for numbers, times and percentages; folder locations; auto-save interval; paw display colours. - Experiment Files — Stored as *.cwe files within a named experiment folder. - Backup and Restore — Experiments can be backed up to *.cwz archives and restored from them. Auto-save at configurable intervals (default: every 5 minutes). - Backward Compatibility — CatWalk 11 opens and converts experiments from versions 8.x, 9.x, 10.x. Experiments from versions prior to 11 are read-only (analysis only; no new acquisition). Experiments from versions 7.x or earlier cannot be opened. Walkway Setup Setup Workflow Setting up the walkway involves three sequential steps, each supported by a dedicated tool: - Focus Assist — Interactive tool to focus the camera lens. A sharpness indicator (percentage of maximum reachable sharpness) guides the user. A bottom-image view highlights sharp areas for real-time feedback. - Automatic Walkway Calibration — After focusing, a dedicated calibration card placed in the walkway is detected automatically. Calibration converts pixel dimensions to real-world units (mm/pixel). Manual calibration is possible but not recommended. - Automatic Walkway Definition — The software automatically detects the corridor walls and defines a walkway rectangle covering 70% of the walkway length. The walkway can be resized and repositioned manually. A Validate Walkway function checks corridor-wall alignment at the start of each acquisition session. Once set up, the walkway configuration is retained across sessions. Re-setup is only required if hardware is changed (e.g., camera position, corridor width). Detection Settings - Auto Detection — With an animal on the walkway, CatWalk automatically adjusts Camera Gain and Green Intensity Threshold to achieve optimal paw-print intensity (target: Maximum Green Intensity 197–203). Default Detection Settings profiles for Rats and Mice are provided. - Manual Detection — Camera Gain and Green Intensity Threshold can be fine-tuned manually. The intensity of the Green Walkway Light and Red Ceiling Light can also be adjusted. - Camera Gain — Controls Maximum Green Intensity of detected prints. Optimal range: 5–12 dB. - Green Intensity Threshold — Sets the minimum pixel intensity for paw detection. Removes background noise. Can also be adjusted per run in the Classification screen before classification. Source: CatWalk XT 11.0 Technical Specifications, Noldus Information Technology --- ## CatWalk XT 11 - Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-variables Chapter: CatWalk XT Paw Statistics Body Dynamics - Initial Contact At (s): Body Speed - Stand / Stance (s): Body Speed Variation (%) - Single Stance: Duration during which only one hind paw contacts the glass plate (contralateral hind paw off ground). - Initial Dual Stance: First period in a hind-paw step cycle during which both hind paws simultaneously contact the glass. - Terminal Dual Stance: Second period in a hind-paw step cycle during which both hind paws simultaneously contact the glass. Interactive Hind Paw Footprint Measurement (Module) - Max Intensity At (s): Time since run start at which maximum print intensity occurs. - Max Intensity At (%): Max Intensity At expressed as a percentage of stance duration. - Max Intensity: Time since run start at which maximum print intensity occurs. - Min Intensity: Max Intensity At expressed as a percentage of stance duration. - Mean Intensity: Time since run start at which maximum print intensity occurs. - Mean Intensity of 15 Most Intense Pixels: Mean intensity of the 15 highest-intensity pixels of the print. Step Sequence and Footfall Patterns - Regularity Index (%): Number of Normal Step Sequence Patterns (NSSP) × 4 / Total paw placements × 100%. A value of 100% indicates fully coordinated gait. Used in spinal cord injury research. - Footfall Patterns: Six recognised pattern families: Cruciate A (CA), Cruciate B (CB), Alternate A (AA), Alternate B (AB), Rotate A (RA), Rotate B (RB). Labelling is independent of which paw starts the run. - Normal Patterns: Count of step cycles falling within one of the six recognised footfall pattern categories. - Accounted Steps: Total number of steps used to determine footfall patterns. Base of Support - Base of Support — Front Paws: Mean Y-axis distance between the centres of the two front paws at Max Contact. - Base of Support — Hind Paws: Mean Y-axis distance between the centres of the two hind paws at Max Contact. Print Positions - Print Positions: Distance between the ipsilateral front and hind paw in the same step cycle (X-axis at Max Contact). Positive = hind paw behind front paw; negative = hind paw in front of front paw. Other Statistics - Duration: Duration of the run based on selected steps (Data Segmentation profile). - Average Speed: Average speed of selected steps (distance units/second). - Maximum Variation (%): Maximum variation in average speed within the selected steps. - Cadence: Steps per second, calculated from Initial Contact of the first to last selected step. - Number of Steps: Total number of selected steps. - Sciatic Functional Index (SFI): Functional recovery measure for the sciatic nerve. Uses Manual Print Length, Toe Spread, and Intermediate Toe Spread for experimental vs. normal contralateral hind paw. Calculated separately for rats (Bain 1989) and mice (Inserra 1998). Requires IFM module. - Posterior Tibial Functional Index (TFI): Recovery measure for the tibial nerve branch. Same inputs as SFI. Requires IFM module. - Peroneal Functional Index (PFI): Recovery measure for the peroneal nerve branch. Uses Print Length and Toe Spread. Requires IFM module. Phase Dispersions Phase Dispersions describe the temporal relationship between the placement of two paws within a step cycle, expressed as a percentage of the anchor paw's step cycle time. Six paw-pair combinations are reported. Range: −50% to +50% (CStat Mean). Values are circular statistics. Paw Pair Combinations - Diagonal Pairs: RF–LH and LF–RH (anchor = front paw). - Girdle Pairs: LF–RF and LH–RH (anchor = left paw). - Ipsilateral Pairs: RF–RH and LF–LH (anchor = front paw). Phase Dispersion Statistics - CStat Mean (%): Circular mean of phase dispersions (range −50% to +50%). - AD (Angular Deviation): Measure of spread around the mean (equivalent to Standard Deviation in CatWalk ≤ 10.6). - SD (Circular Standard Deviation): Alternative spread measure; ranges from 0 to ∞. - R: Length of the mean vector (0–1); higher R = greater consistency of inter-paw timing across step cycles. - Mismatches: Count of ANT (anchor, no target), AMT (anchor, multiple targets), and TNA (target, no anchor) occurrences. Couplings Couplings are computed the same way as Phase Dispersions but a target can never precede its anchor; values range from 0% to 100% (CStat Mean). Twelve paw-pair combinations are reported. The same statistics (CStat Mean, AD, SD, R, Mismatches) are available as for Phase Dispersions. Support and Footfall Formulas - Support Formula: Number of paws simultaneously on the glass plate in each section of a step cycle (e.g., 2–3–2–3–2–3–2–3). - Footfall Formula: Alphanumeric notation indicating which specific paws are on the glass plate during each section. - Standing On (%): Relative duration of simultaneous contact for all combinations: zero, single, diagonal, lateral, girdle, three, and four paws. Group Statistics Group statistics aggregate per-trial values by treatment group and time point combination. Available statistics: N, Mean (arithmetic or circular), SEM, CStat Mean, CStat R, CStat AD, CStat SD. Charts: Bar chart (mean ± SEM) or Five Number Summary (box-whisker, minimum 4 trials required). Circular charts for Phase Dispersions and Couplings. Charts can be split by treatment group, time point, or both. Research Applications CatWalk has been validated and applied extensively across a wide range of preclinical research areas. The following disease models and research areas have been studied using CatWalk gait parameters. Research Area Commonly Affected Parameters Spinal Cord Injury Base of Support, Intensity, Stand, Phase Dispersions, Regularity Index, Stride Length Neuropathic Pain Print Area, Intensity, Duty Cycle, Swing Duration, Swing Speed Ischemia / Stroke Swing Speed, Intensity, Duty Cycle, Phase Dispersions, Regularity Index, Stride Length Amyotrophic Lateral Sclerosis Stand, Stride Length, Duty Cycle, Support on diagonal and 3 limbs Cerebellar Ataxia Swing & Stand Duration, Regularity Index, Print Area, Stride Length, Phase Dispersion Motor Coordination (Cerebellar Cortex) Stride Length, Duty Cycle, Swing Speed, Phase Dispersions, Support Formulas Parkinson's Disease Models Average Speed, Regularity Index, Print Area, Swing Speed, Stride Length, Stand Index Sciatic Nerve Injury SFI, Paw Print Intensities, Couplings, Base of Support, Stride Length Arthritis (Mono- and Osteoarthritis) Print Area, Mean Intensity, Duty Cycle, Regularity Index Huntington's Disease Swing Speed, Stand Charcot-Marie-Tooth Disease Print Length/Width, Max Contact Area, Max Intensity, Couplings Genetic / Toxic Models (Refsum, Leigh) Print Area, Swing Speed, Stride Length, Stand Index, Regularity Index Source: CatWalk XT 11.0 Technical Specifications, Noldus Information Technology --- ## CatWalk XT 11 - Version 11.0 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-version-110 Chapter: CatWalk XT Install CatWalk XT And Activate Your License Install CatWalk XT - Browse to https://my.noldus.com. Log in or register using the registration code on your welcome letter. - Click Downloads and under CatWalk XT download the latest version. - Double-click the file CatWalk XT - Setup - [version number].exe. Notes - During installation, the computer restarts automatically. Please wait until installation is complete. - In most cases, the camera and the walkway have been installed at your site by Noldus. For details about how to connect and start up the system, see the CatWalk XT 11.0 - Reference Manual (press F1 in the software). Activate Your License With A USB Hardware Key If you have a hardware key, insert it into a USB port of the computer and start CatWalk XT. If you upgrade from a previous CatWalk XT version, start CatWalk XT and enter the Upgrade key in the window that opens. With A Software License Key If you received a software license key, start CatWalk XT and activate your license. Choose between a Floating license or a Fixed license. - Floating — A Floating license allows you to be flexible on which computer you use CatWalk XT to acquire data. For this license your computers must be connected to the internet. - Fixed — A Fixed license is linked to one computer. To activate your license, your computer must have an internet connection, or you must have a smartphone with an internet connection. If you want to use CatWalk XT to analyze existing data, not acquire new data, you can run it on that PC in Analysis mode, which does not require a license. Source: CatWalk XT 11.0 Quick Start Guide, Noldus Information Technology --- ## CatWalk XT 11 - Visualizations URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-visualizations Chapter: CatWalk XT Visualizations - 3D Footprint Intensities — Plots paw print intensity values (0–255) per video frame as a rotating 3D chart. Uses the same false-colour scale as the Classification Print View. - 2D Footprint Intensities — Plots maximum and mean intensity for each paw print over time in a 2D chart. A vertical hairline marks the current video position. - Footfall Patterns Diagram — Graphical representation of the order in which paws were placed. Dots are colour-coded: blue = start of pattern, green = within pattern, orange = not counted, purple = not part of a recognised pattern. Export Types - Run Data — Format: Excel (.xlsx). Raw print data per video frame (100 frames/s): X/Y position, print dimensions, min/max/mean intensity — per paw, per frame. - Run Statistics — Format: Excel (.xlsx). Summary statistics per run (one row per run). Selectable parameter categories and statistics (mean, SD). - Trial Statistics — Format: Excel (.xlsx). Combined statistics across all runs in a trial (one row per trial). Weighted averages. - Group Statistics — Format: Excel (.xlsx). Statistics per treatment group × time point combination (one sheet per parameter group). - Group Charts — Format: PDF. All charts in Graphical Results exported to a single PDF file. Individual charts: PNG. - Run Visualizations — Format: AVI (uncompressed). 3D/2D Footprint Intensities and Footfall Patterns exported as video at selectable playback speed. No codec required. - Run Video — Format: AVI (uncompressed). Raw run video with optional overlay of labels, rectangles, and time/frame information. Output and Export Export Formats All exports include metadata columns: Experiment, Group, Group Type, Group Description, Animal ID, Time Point, Trial, Run, walkway dimensions, pixel calibration values, Camera Gain, and Green Intensity Threshold. Units are included in all parameter labels as of CatWalk 11. Hardware and System Requirements Minimum Set-Up - CatWalk 11 software with valid license - CatWalk system hardware (walkway, glass plate, green LED illumination, illuminated ceiling with red LEDs, CatWalk Control Unit) - Basler high-speed camera (1920 × 1216 pixels, pre-configured) - Computer with USB-C port (for Control Unit connection) and 10 Gb Ethernet PCIe card (for camera connection) Optional Components - Goal box (to motivate the animal to cross the walkway) - Noldus goal box with sliding door - Diffusion plate (fits on top of corridor walls to prevent rearing) - Calibration card (included with CatWalk 11) Camera Specifications - Type: GigE - Brand / Model: Basler (10 GigE) - Interface: Basler Pylon Runtime - Connection: 10 Gb Ethernet PCIe card - Frame Rate: 100 fps CatWalk Control Unit - Connected to the walkway, camera, and illuminated ceiling. - Connected to the CatWalk computer via USB-C cable (requires a USB-C port on the computer). - Controls green walkway LED light (adjustable voltage) and red ceiling LED light (adjustable voltage). - Firmware upgradeable from within CatWalk software. System Requirements Operating System - Windows 10 Pro, version 22H2 or later - Windows 11 Pro Administrator rights required for installation. Do not run CatWalk for the first time as an administrator on a multi-user computer. Recommended Computer Configuration - Tested System: Dell Precision T3660 - Processor (CPU): Intel Core i7-11700, 8-core, 2.5–4.9 GHz, 16 MB cache - Memory (RAM): 16 GB DDR5 (minimum requirement) - Primary Hard Disk: M.2 256 GB PCIe NVMe SSD - Secondary Hard Disk: 3.5-inch 1 TB SATA (7200 rpm) for experiment storage - Graphics Card (GPU): NVIDIA Quadro T1000, 4 GB - USB Port: USB-C (required for Control Unit connection) - Network Interface: 10 Gb Ethernet PCIe card (required for camera connection; included if ordering computer from Noldus) Camera Connection - A dedicated 10 Gb (gigabit) Ethernet PCIe network interface card is required for connecting the digital camera. - Driver installation is included in the CatWalk 11 installer. - Basler Pylon Runtime is included in the CatWalk 11 installer (replaces the legacy Pleora eBUS driver of previous versions). - After starting the computer and turning on the Control Unit, allow approximately 1–2 minutes for the camera to be detected. Help Features - PDF Reference Manual — The complete CatWalk 11.0 Reference Manual is accessible from the Help menu (F1). - Tutorial Videos — Video tutorials are installed on the computer and accessible from the Help menu. - Quick Start Guide — Step-by-step guide for setting up, acquiring, and analysing a first experiment. - Assembly Instructions — Separate document for assembling the CatWalk hardware and goal box. - Sample Experiments — Three sample experiments (with mouse and rat data) are provided. Accessible via File > Restore Backup. - Noldus Help Desk — 24-hour support across multiple time zones. Contact via my.noldus.com. PC report utility available on request. - Online Knowledge Base — Searchable database of customer questions and support answers at my.noldus.com. Supported by an online chatbot to help answer frequently asked questions. Source: CatWalk XT 11.0 Technical Specifications, Noldus Information Technology --- ## CatWalk XT 11 - Walkway - Setting Up Your Walkway URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/catwalk-xt/page/catwalk-xt-11-walkway-setting-up-your-walkway Chapter: CatWalk XT Walkway Setup Place the Noldus Calibration Card on the glass plate of the CatWalk. In the software, select Set up the Walkway. Indicate what you would like to set up. If you have installed the camera for the first time, or have moved the camera position, start with Focus Assist. Ensure proper lighting and make sure the camera is properly focused for your experimental conditions. Acquisition Turn off the room lights to create the same light conditions you will be using for acquisition of your actual experiments. Also don't forget to lower the corridor walls and close the CatWalk ceiling. Replicate your actual experiment conditions as closely as possible during setup for optimal results. This includes room lighting, walkway position, and ceiling state. Click the Show Instructions button to display the required steps for focusing the camera. Check that the aperture on the camera lens is completely open to get the brightest image possible. Using the focus ring on the lens, turn the lens fully out of focus. Once the lens is out of focus, click the Reset button. Focusing the Camera Refocus the camera by using the focus ring on the lens. You don't have to focus on the calibration card in the camera view, simply keep an eye on the sharpness indication bar. Once it turns green, the focusing process is finished. The bar doesn't need to be full; green is enough. Calibrating the Walkway Proceed with the walkway calibration step by pressing Calibrate the Walkway. Then click the Auto Calibration button. The calibration rectangle automatically moves to the calibration card, which finishes the calibration step. Important: Ensure the calibration card is fully visible in the camera view and positioned flat on the glass plate for accurate calibration results. Defining the Walkway Layout Proceed to Define the Layout of the Walkway. The CatWalk software checks whether both corridor walls are straight and aligned after clicking the Detect Walkway button. If the walls are not properly aligned, you will receive a notification. In this case, straighten and align the walls and click the Detect Walkway button again. - Tip: You can optionally enlarge the walkway to increase the captured area. This may be useful for studies that require a wider field of view. Your setup is now complete. Click OK and then Close to return to the CatWalk overview window. Your walkway is now set up and ready for data acquisition. Source: CatWalk XT 11.0 Walkway Setup Guide, Noldus Information Technology --- ## DanioScope 1 - Morphology and Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-1-morphology-and-analysis Chapter: DanioVision Morphology Aim: To measure body parts and organs. Typical measurements are body length, eye area, and pericardial area. Procedure: - Choose Acquisition > Morphology and click Add Images or Add Images From Video to load your images. - Use a Calibration profile to apply the same scale to multiple images. To create a new Calibration profile, click the Calibration Profiles button. Click Add and choose a picture containing an object of known size, for instance a stage micrometer. This picture must be obtained with the same lens and zoom level as the pictures of the embryos. Next, draw a line that connects the two extremes of the object, enter a value for Known distance and click OK. - Select the Calibration profile you want to use. - Draw the measurement line/shape for Body Length, Eye Size or Pericardial Area. For other measurements like the number of somites, enter or select the appropriate value. For more information, see Morphology in the DanioScope Help. Calculate Statistics Trial Statistics Choose Analysis > Trial Statistics to get statistics per subject. You can calculate statistics like Burst Activity and Burst Count for Activity, Beats per second or Beats per minute for Cardiology. Group Statistics Choose Analysis > Group Statistics and Charts to calculate average values of the statistics per group. Define groups based on the values of the independent variables in your experiment. Click the Comparison Settings button to compare different types of measurements, for example, Burst Count with BPM (beats per minute). Click the Comparison tab to view the corresponding statistics and charts. Other Options - Choose Analysis > Data Selection to filter data based on the values of the independent variables. For example, to analyze only subjects with Time point = 48 hpf. Select the check box under Filter for the independent variable of your choice. - Choose Analysis > Visualizations to view activity plots for the subjects in your videos, the activity in the heart area or the flow in an artery or gut. For more information, see Data analysis in the DanioScope Help. Export Data and Results To Export the Trial Statistics or the Group Statistics Choose the option you require under Analysis. Click the Export Statistics button. Select the export format and click Export. To Export the Raw Activity Data For Activity, Cardiology and Flow you can also export the raw data recorded at each video frame. In the Trial Statistics screen, click the Export Raw Data button. To Back Up an Entire Experiment Use the backup function to keep your data safe in another location. Make a backup of your experiments on a regular basis, at least once a day. - Choose File > Make Backup. Give the backup file a name and choose a destination. - Copy the backup file (with extension *.dsz) to the other computer, together with the video and image files. - To restore an experiment from a backup file and open it with DanioScope on the other computer, choose File > Restore Backup. Choose the backup file and select the folder where you want to store the experiment. For More Information DanioScope Help In DanioScope, choose Help > Help Topics or press F1. Or, on the Windows Apps screen, under Noldus choose DanioScope 1 Help. Help Desk If you have any problems, questions, remarks or comments, please let us know. You can contact us via our website (www.noldus.com/helpdesk) and fill out a Support Request Form (preferred), or phone. We offer 24-hour support via several help desks in different time zones. Please have the following information available when you contact the help desk: - The version number of your copy of the software. - The name of the registered user and the license number of your copy of the software (choose Help > About DanioScope > User Info). For other contact information, browse to www.noldus.com and choose About Noldus then Contact. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## DanioScope 1 - Quick Start Guide URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-1-quick-start-guide Chapter: DanioVision Install DanioScope Make sure that the USB hardware key is not plugged in your computer before installing the software. - Insert the DanioScope Installation USB stick into one of your computer's USB ports. - Browse to the USB stick contents and double-click Setup.exe. - In the Welcome screen, click Next>. - Read the license agreement and select I accept, then click Next>. - Click Install. - Click Finish to complete installation. To Start DanioScope - Before you start DanioScope, insert your license key into a USB port of your computer. - To start DanioScope, on the Apps screen under Noldus choose DanioScope. Your First DanioScope Experiment Create a New Experiment To create an experiment from scratch, choose File > New. Give a name you want to give to the experiment, and click Create. - To create an experiment from a pre-existing template, choose File > New from Template. Select a template from the Template list. - The default location is C:\Users\Public\Documents\Noldus\DanioScope\Experiments. To change the location for all the next experiments, choose File > Preferences. The Experiment's Basic Properties Measurements Choose Setup > Experiment Settings. Choose the measurements you want to take: - Activity — To measure activity bursts of the embryo. - Cardiology — To measure heart rate. - Flow — To measure fluid movement rate in blood vessels or the gut. - Morphology — To measure body parts and organs. Click the Add button to define additional measurements. Independent Variables You can associate your measurements with one or more variables important for analysis, named independent variables. Choose Setup > Independent Variables. Two variables, Compound and Time Point, are predefined. Choose which variable you want to associate with measurements. Click Values to edit the possible variable values. To add a new variable, click the Add Variable button. Record Media Files - We advise to name video and image files in such a way they suggest which subject(s) and time points are recorded. This may be very useful when copying files from one computer to another. - Test the format of your video before recording videos of your experiment. To test a video format, in the Acquisition screen load the video file and play it back. For the list of supported formats, see the Questions and Answers in the DanioScope Help. - Automatic detection of embryos is only possible when the video is not distorted relative to the original aspect ratio of the camera image. If the aspect ratio of the video file is distorted, convert the video file to one of the formats compatible with DanioScope, and make sure to adjust the video aspect ratio. Activity Aim To record and analyze bursts of movement in zebrafish embryos. Procedure - Choose Acquisition > Activity. - Click the Add Videos button and load one or more video files. - Select a video file and position the video to the first frame where you want to start measuring. - Click the Detect Embryos button. - Select the values of the independent variables that apply for that video. Each detected embryo is marked with a circle and a code Sn / M1 (Subject/Measurement), where n is a progressive number. - Click the > button and repeat the procedure for the next video file. - Click the Acquire All button. To Check Activity Data Click one of the rows in the results table and click the Activity Settings button. In the window that appears, play the video and check that the Activity (%) peaks correspond to the actual behavior of the embryos. If necessary, adjust the Activity onset and Activity offset settings and click Apply. - If DanioScope cannot find the embryos, you can define them manually. For details, see Add a measurement in the DanioScope Help. - If an embryo shows spatial displacement in the video, for more accurate measurement of activity, you can only analyze the part of the video where the embryo stays in the same place. For this and other tips, see Questions and Answers in the DanioScope Help. Cardiology Aim To analyze the heart area in zebrafish larvae, and estimate the heart rate. Procedure - Choose Acquisition > Cardiology. - Click the Add Videos button and load one or more video files. - Select one of the video files in the list. - Choose one of the drawing tools and draw a shape around the heart of one of the subjects. - Enter the number of subjects in the current video and click Add. - Place a heart area over each heart in the image. Repeat the procedure for other videos. - Click the Acquire All button. For more information, see Cardiology in the DanioScope Help. Flow Aim To estimate flow of fluids in specific areas of interest, like a blood vessel or a gut section. Note: Flow does not give results in physical units like l/s. Procedure - Choose Acquisition > Flow. - Click the Add Videos button and load one or more video files. - Select one of the video files in the list. - Choose a drawing tool and draw a shape over the blood vessel or gut in such a way that it fits exactly inside the vessel/gut section. - Release the mouse button and assign the shape to an existing subject S01, S02, etc., or add a new subject if you have drawn the shape on another larva in the image. - Repeat steps 4-5 for other areas, subjects and videos. - Click the Acquire All button. For more information, see Flow in the DanioScope Help. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## DanioScope 1.1 - Activity - Activity URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-activity-activity Chapter: DanioVision Activity Aim To detect and quantify activity bursts in embryos. To Open the Activity Screen Choose Acquisition > Activity. Main Steps - Load the video files and detect embryos automatically. - Acquire activity data. - Adjust the Activity settings to detect activity bursts. - View the Activity statistics. See Also - What is Activity? - Which video and image formats are supported? Detect Embryos Automatically Aim To let DanioScope find the embryos in your video file, so their activity can be analyzed. Important: Automatic detection of embryos for Activity analysis is only possible when the video is not distorted relative to the original aspect ratio of the camera image. If the video aspect ratio appears distorted, convert the video to a compatible format and adjust the video aspect ratio. Make sure that the video image has good contrast and the embryos are in focus. If automatic detection does not work, indicate the embryos manually. See Add a Measurement. To Detect the Embryos Automatically - To open the Activity screen, choose Acquisition > Activity. - Add videos by clicking the Add Video(s) button. To select multiple files, hold the Ctrl key down and click each file name. - Select the video you want to use first. - Using the playback controls, position the video to the point where you want to start measuring (if the first part of the video is not interesting), or leave it as it is to detect embryos from the first video frame. - Click the Detect Embryos button. - If detection works well, a circle appears around each detected embryo. If you have defined independent variables, the Independent Variables Values window appears on top. - If all subjects in the video have the same independent variable values (for example, when all embryos are 18 hours post fertilization (hpf)), then select this value from the corresponding list. If the subjects are of different type, for example one is wild type and another is mutant, you can later assign the values per subject. See Edit the Independent Variable Values. - Click OK. Each detected embryo is marked with a code Sn / M1, where n is a progressive number. M1 means measurement 1. - Some overlap between circles can be accepted for good data acquisition. Click the > button next to Detect Embryos, and repeat the procedure for the next video file. - When ready, acquire activity data. Notes - If an embryo is not detected, you can draw the contour of the embryo. See Add a Measurement. - The video is analyzed up to its end. If a subject changes position significantly throughout the video, you must specify the stop time for the measurement (see To Set a Stop Time for a Measurement). Optionally, specify the new location as a new measurement (see To Add a New Measurement for the Same Subject). - Below the video window, the detected subjects are listed. Drag the handle between the two windows to view all subjects. See Also - Add a Measurement - Acquire Activity Data Acquire Activity Data To Acquire Activity Data - Make sure that all embryos are detected correctly in the video fragments you are interested in. - To acquire data for the current video, click the Acquire button. To acquire data for all videos where subjects have been defined, click Acquire All. - At the end of acquisition the Status column in the video list says Acquired. - Click the Activity Settings button and check that the Activity (%) peaks correspond to the actual behavior of the embryos. See the next section, Activity Settings. Notes - If you resize a shape after acquisition, the activity statistics for that measurement are cleared and the Status column says Next: Acquire. Click Acquire to acquire the data. --- ## DanioScope 1.1 - Activity - Activity Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-activity-activity-settings Chapter: DanioVision Activity Settings What Is Activity? To detect embryo movements, DanioScope looks at the pixels within the shape around the embryo that change their gray scale value with time. At a given time, a pixel's gray scale value can range between 0 (pure black) and 255 (pure white). Activity is defined as the proportion of pixels within the area of interest (embryo for Activity, heart area for Cardiology, and gut section for Flow) of video frame n, that change in gray scale value relative to the same area in the previous frame (n-1). Activity is expressed as the percentage of the changed pixels in the area of interest. A value of zero means that none of the pixels within the area of interest changed their gray scale value, like in a still image. A value of 100 means that all pixels in the area of interest have changed their value from frame n-1 to frame n. Activity Onset and Offset In any video file there is always a small proportion of pixels that change with time, even when the animal is not active. You must specify a minimum amount of pixel change, called Activity onset, above which the subject is scored as active. Furthermore, you must specify an Activity offset. When Activity (%) goes below the Activity offset value, the subject is scored as not active. This ends the time fragment scored as an activity burst (highlighted in red). To refine detection of activity bursts, you have two extra options: the minimum time between peaks and the minimum peak duration. To Adjust the Activity Settings - Select the video you want to analyze. - Click the Activity Settings button. The Activity Settings window opens. - The first subject/measurement S01/M1 is highlighted in the Subject/Measurement list, and in the video image. - Check that the peaks marked in red in the Activity plot correspond to true activity bursts. Use the playback controls to control the video. Zoom in the Activity plot if necessary. See Zoom In/Out. - To check for false negatives (the animal moves, but activity is not detected): position the video where activity bursts occur for that subject. Check in the Activity plot that the activity peak is highlighted in red. If that is not the case, reduce the Activity onset until the peak is highlighted. - To check for false positives (activity is detected, but the subject does not move): position the hairline in the Activity plot where an activity peak is highlighted in red. Check in the video that this corresponds to a true burst of activity. If that is not the case, increase the Activity onset until the peak is no longer highlighted. - Check the duration of single activity bursts. The Activity onset (green line) determines when the increase in activity is scored as the start of the activity burst (marked by the left side of the red rectangle). The Activity offset (orange line) determines when the decrease in activity is scored as the end of the activity burst (marked by the right side of the red rectangle). In most cases activity increases with a steep line and decreases more slowly. Therefore it makes sense to have Activity onset higher than Activity offset. If you want to capture most of the slow decrease in activity and include it in the burst duration, enter a lower Activity offset. Important: The left side of the red rectangle marks the first video frame when activity becomes higher than the onset. Similarly, the right side marks the first video frame when activity becomes lower than the offset. The start and stop times of the activity burst are based on the time stamps of those video frames. However, because the activity line shown in the plot is a linear interpolation between the actual (discrete) values of activity, a small difference may appear between the time that the line crosses the onset/offset and the true time of onset and offset (the sides of the red rectangle). - Check the time between single activity peaks. Check the distance between single peaks. If two adjacent peaks are counted as two bursts and you want them to be counted as one, increase the Min. Inter Peaks Interval. If two peaks are counted as one and you want them to be counted separately, reduce the Min. Inter Peaks Interval. - Set the minimum peak duration. Zoom in the activity plot (see Zoom In/Out) and check the duration of single peaks. If a short peak is detected as a separate burst and you want to exclude it from analysis, increase the Min Peak Duration. - Select another subject/measurement from the list and repeat steps 4 to 7. Try to find a value of Activity onset and offset that eliminates or minimizes the detection errors. - Click Apply to apply the new threshold to all measurements. After clicking Apply, the activity statistics are updated. - Check that the new thresholds also work well for other videos. Notes - Important: The new activity settings are used for all activity measurements in the experiment, including those already acquired. - The Activity Settings button is only available after acquiring data from that video. Activity Statistics In the list below the video window you find the activity statistics per subject and measurement for that video file. Note The video frame corresponding to the Stop time is not analyzed. Video is analyzed from Start to Stop (included). See Also - Trial Statistics - Group Statistics and Charts - Export Statistics - Export Raw Data Source: DanioScope 1.1 Reference Manual - Activity, Noldus Information Technology --- ## DanioScope 1.1 - Cardiology URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-cardiology Chapter: DanioVision Cardiology Aim In DanioScope, Cardiology analyzes video images of one or more subjects and estimates the heart beat rate. To Open the Cardiology Screen Choose Acquisition > Cardiology. Main Steps - Load the video files and draw the heart areas. - Acquire cardiology data. See Also - Which video and image formats are supported? Draw the Heart Areas To Load Video Files - Click the Add Video(s) button. - Select one or more video files, and click Open. To select multiple files, hold the Ctrl key down and click each file name. - The list of loaded video files appears. The video window shows the first video in the list. Tip: To select and open another video for preview, select the corresponding check box. To Draw the Heart Areas - Select one of the video files in the list. - Using the playback controls, position the video to the first frame, or, if the first part of the video is not interesting, to the point where you want to start measurements. An interval of 10 to 15 seconds is usually enough to accurately measure heart rate. - Click one of the drawing tools, and draw a shape around the heart of the first subject in the image. - Assign the shape to an existing subject or select Add Subjects. - If you selected Draw template shapes for all subjects in the Add Subjects window, all shapes are copied at the top of the video window. Move each shape to the corresponding heart. - Click a shape and drag its handles to resize and adapt it to the hearts. Play the video for a clear view of the heart movements. The shapes do not need to have exactly the same area. - Click the > button above the video window and repeat the procedure for the next video file. The Status column tells you which step is next for each video file. Notes - For Cardiology, the measurement of heart rate is based on the frequency of the peaks in Activity (%) in the heart area, not on the absolute values of Activity (%), which are affected by the size and shape of the heart area. This means that, if you are interested in heart rate only, the heart areas do not need to have exactly the same size. However, if you are interested in the absolute values of Activity (%) to compare different individuals, draw the areas in such a way that it only includes the heart. Next Steps - The video is analyzed up to its end. If a subject changes position significantly throughout the video, you must specify the stop time for the measurement (see To Set a Stop Time for a Measurement). Optionally, specify the new location as a new measurement (see Add a Measurement). Acquire Cardiology Data To Acquire Cardiology Data - Make sure that all heart areas are in the correct place. - To acquire data for the current video, click the Acquire button. To acquire data for all videos where subjects have been defined, click Acquire All. At the end of acquisition the Status column in the video list says Acquired. Notes - If you resize a shape after acquisition, the cardiology statistics for that measurement are cleared and the Status column says Next: Acquire. Click Acquire to acquire the data. - Cardiology data are essentially pixel activity data, measured for the heart area only, not the whole embryo. See Also - Cardiology Statistics Cardiology Statistics In the list below the video window you find the cardiology statistics per subject and measurement: BPS (beats per second) and BPM (beats per minute). If values of BPS are very low, they may result from artifacts in the video image (for example flickering). Make sure that your video does not contain such artifacts. Note The video frame corresponding to the Stop time is not analyzed. Video is analyzed from Start to Stop (included). See Also - Trial Statistics - Group Statistics and Charts - Export Statistics - Export Raw Data Source: DanioScope 1.1 Reference Manual - Cardiology, Noldus Information Technology --- ## DanioScope 1.1 - Data Analysis - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-data-analysis-data-analysis Chapter: DanioVision Data Analysis Visualize Data To open the Visualizations screen, choose Analysis > Visualizations, then click one of the tabs: Activity, Cardiology, or Flow. Note: Only the subjects selected are visualized. See Analyze a Selection of Data. Each row represents a measurement. If a subject is measured two or more times in the same video, data of that subject appears in a corresponding number of rows (see the column Measurement). The thumbnail shows a snapshot of the first video frame of the measurement with the area of interest highlighted in yellow. Activity Plot This is the time plot of activity (%) for Activity, Cardiology, and Flow. See How DanioScope Analyzes Video Images and Activity Settings. Power Spectrum Plot This is shown in the Cardiology tab. It describes how the activity signal is distributed over frequencies. The highest peak in the plot represents the dominant frequency, which is the heart rate in beats per minute. Notes: - A power spectrum is obtained by applying Discrete Fourier Transformation (DFT) to the samples in the activity signal. - Important: Because the duration of the video is finite, there is a fixed limit to the frequency resolution (that is, the lowest frequency difference that can be detected), equal to 1/(video duration). For a 10-second video, this limit is 1/10 = 0.1 Hz. Therefore, when the dominant frequency in BPS reported for a 10-second video is 2.37 BPS, this actually means that the dominant frequency lies in the interval 2.32–2.42 BPS. - If the dominant frequency is close to 0, it may result from artifacts in the video image (for example, flickering). Make sure that your video does not contain such artifacts. - Tip: You can hide the Activity plot and/or the Power Spectrum plot by deselecting the check boxes at the top of the screen. - Video is analyzed from the Start time to the Stop time defined in the Acquisition screen. Play Back Video and Plots Use playback to review a measurement in detail. Video is played back together with the activity plot. - Choose Analysis > Visualizations. Click one of the tabs: Activity, Cardiology, or Flow. - Click on the thumbnail for a measurement, or click one of the plots. - In the window that opens, click the buttons below the video or use the slider to play through or move through the video. Data for that subject and measurement (highlighted in the video) are plotted together with the original video: - For Activity: Activity Plot. The onset and offset activity thresholds for activity burst detection are also shown in the plot. - For Cardiology: Activity Plot and Power Spectrum Plot. - For Flow: Activity Plot. Play the video frame-by-frame backward and forward with the corresponding buttons. Click the Loop button to play the video back repeatedly. To Zoom In or Out a Plot Drag around the area of the plot you want to zoom in. Always drag from left to right. To view the whole measurement, click and drag from right to left. Notes: - Tip: If you want to analyze activity peaks in detail, export the raw data. - When you play the video, the hairline in the plot moves synchronously. - The timeline of the plot represents the duration of the measurement, while the timeline of the video image represents the entire duration of the video. If your measurement is based on part of the video, when the video plays back you may see the hairline on the timeline of the video rather than on the plot. The same happens when you zoom in on a plot. - To enlarge or reduce the video image, click the buttons at the upper-right corner of the video window. - If you zoom in and play the video back, the hairline moves outside the selected time. Zoom out to view the rest of the timeline. Export Plots Do one of the following: - To export the plot to a file, right-click a plot and select Save to File. Available format: Portable Network Graphics (*.png). - To copy the plot to another program, right-click it and select Copy to Clipboard, then paste it into the other program. Trial Statistics Trial statistics summarize measurements for each subject. Choose Analysis > Trial Statistics. The Trial Statistics screen opens with results divided into pages for Activity, Cardiology, Flow, and Morphology. Each row in a table represents one subject. Trial statistics shows the mean and the standard error for each variable. N is the number of measurements per subject. Note: Only the data selected is used in the analysis. Activity - Burst Activity (%). The percentage of the measurement duration the subject was scored as Active. - Inactivity (%). Equals 100% minus Burst Activity (%). - Total Burst Duration (s). The total duration of all instances when the subject was scored as Active, in seconds. - Mean Burst Duration (s). The average duration of all instances when the subject was scored as Active, in seconds. - Inactivity Duration (s). The total duration of the measurement minus the Total Burst Duration, in seconds. - Burst Count. The number of times the subject was scored as Active. - Burst Count / Minute. Equals Burst Count divided by the measurement duration, expressed as number per minute. Note that the measurement duration may not be the same as the length of the video, depending on the Start/Stop times of the measurement. Cardiology - BPS. The heart rate in number of beats per second. - BPM. The heart rate in number of beats per minute. Notes: - Because the duration of the video is finite, there is a fixed limit to the frequency resolution (that is, the lowest frequency difference that can be detected), equal to 1/(video duration). For a 10-second video, this limit is 1/10 = 0.1 Hz. Therefore, when the dominant frequency reported for a 10-second video is 2.37 BPS, this actually means that the dominant frequency lies in the interval 2.32–2.42 BPS. - If values of BPS are very low, they may result from artifacts in the video image (for example, flickering). Make sure that your video does not contain such artifacts. Flow - Flow Activity (%). The percentage of pixels within the area of interest which changed in gray scale value between subsequent frames in the video. Morphology The Morphology page shows the statistics for the measurements defined in the Experiment Settings. - Body Length (mm) - Eye Size (mm²) - Pericardial Area (mm²) - Somites. The number of somites observed in the image. - Tail Detachment. With possible values: Positive and Negative. - Body Curvature. With possible values: Dorsal, Ventral, and Straight. Notes: - means that the measurement was not taken for that image. - Only measurements taken on calibrated images are included in Trial Statistics. - Make sure that all images have been associated with a calibration profile. In the Morphology screen, check the Calibration Profile column. - If you measure Body Length with a polyline, Body Length is the total length of the segments that the polyline is made of. Group Statistics and Charts Group Statistics summarize measurements per group, where a group is defined based on the independent variables. Choose Analysis > Group Statistics and Charts. Group Statistics gives you the average and standard error of the statistics calculated in Trial Statistics, averaged per group. Groups can only be defined based on the independent variables currently in the experiment. The charts visualize the group statistics with column bars. Scroll the horizontal bar to view all charts. To Define Groups - Click the Group Settings button. - In the Group Settings window, select the independent variables you want to use to create groups, and how they are sorted. The values of the first variable appear on the x-axis of each chart. The values of the second variable appear in the series (indicated by the legend). - Click OK and then click the tab of your choice. Notes: - In the Group Statistics and Charts, N is the number of different subjects in that group, regardless of how many measurements are taken for each subject. If ten subjects are measured two times each, N is equal to 10. - Important for Morphology: Make sure that all images taken with the same camera lens have the corresponding calibration profile. If not, group statistics may be incorrect. Only measurements taken on calibrated images are included in Group Statistics and Charts. - To define additional independent variables, see Independent Variables. - To assign the values of the new independent variable to subjects and measurements, do this in the measurement list of the corresponding screen (Activity, Cardiology, Flow, or Morphology). - Click Swap IVs to exchange the independent variable between the x-axis and series. To Compare Different Types of Measurements To compare, for example, Burst Count per Minute with heart rate (BPS) in the same table: - Click the Comparison Settings button. - In the Comparison Settings window, select the measurements you want to compare. - Click OK and then click the Comparison tab for both the statistics and the charts. To Export Group Charts Do one of the following: - To export the chart to a file, right-click a chart and select Save to File. Available format: Portable Network Graphics (*.png). - To copy the chart to another program, right-click it and select Copy to Clipboard, then paste it into the other program. Analyze a Selection of Data Data selection is optional. You can use it to select the measurements associated with certain values of the independent variables. When visualizing data or calculating statistics, only the measurements specified in the data selection are used. To select data, choose Analysis > Data Selection. In the Data Selection screen you can filter measurements for Activity, Cardiology, Flow, and Morphology separately. At the bottom of each of the four tables you can see how many of the measured subjects are currently selected. To Select Measurements for Analysis - Select the check box under Filter for the independent variable of your choice. A window appears showing the independent variable values which you defined. - Select the values of your choice and click OK. The number of measured subjects in your selection is updated accordingly. - Repeat the steps above to refine your data selection based on other independent variables. - Choose one of the analysis options from the Analyze menu. To Apply a Filter to All Measurement Types Select the option "Apply changes in selected values of shared Independent Variables to all measurements" at the top of the Data Selection screen. For instance, if you tested three groups of larvae (Control, Concentrate 1, and Concentrate 2) and you only select Control for Cardiology, this selection will also apply to the other measurements (for instance, Morphology). --- ## DanioScope 1.1 - Data Analysis - Export Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-data-analysis-export-statistics Chapter: DanioVision Export Statistics To export Trial Statistics or Group Statistics: - Choose Analysis > Trial Statistics or Analysis > Group Statistics & Charts depending on the type of statistics you want to export. - Click the tab for the type of measurements you want to export (e.g. Activity). - Click Export Statistics. - Enter a name for your results file, or accept the default name. - Choose the export format, Excel (*.xlsx) or Text (*.txt). - Click Browse to select the export location, or accept the default location C:\Users\Public\Documents\Noldus\DanioScope\Export. - Click Export. Notes - The default export file name is: [experiment name] - [statistic type] - [measurement type], where statistic type is Trial Statistics or Group Statistics, and measurement type is Activity, Cardiology, Flow, or Morphology. - To change the default export folder, or the default text field delimiter, choose File > Preferences. See Also - Export Group Charts Export Raw Data To export the pixel activity data calculated for each video frame. This applies to Activity, Cardiology, and Flow. To export raw activity data: - Choose Analysis > Trial Statistics. - Click the tab for the type of measurements you want to export (e.g. Activity). - Click Export Raw Data. - Enter a name for your export file, or accept the default name. - Choose the export format, Excel (*.xlsx) or Text (*.txt). - Click Browse to select the export location, or accept the default location C:\Users\Public\Documents\Noldus\DanioScope\Export. - Click Export. Notes - Export is applied to the type of measurement currently open. To export data of another type, click the corresponding tab. - For Excel export files: DanioScope exports one file at a time. The Excel file contains one tab for each video. The default export file name is: [experiment name] - Raw Data - [measurement type (Activity, Cardiology, or Flow)]. - For text export files: DanioScope exports one file per video. The column separator is semicolon (;). The default export file name is: [experiment name] - Raw Data - [measurement type (Activity, Cardiology, or Flow)] - [video file name]. - In the export file, each column contains data for a subject and measurement combination. Example of Export File Cardiology - Excel: - A. Time stamps. - B. Activity (%) of the heart area of subject 6, measurement 1. See Also - Export Statistics Source: DanioScope 1.1 Reference Manual - Data Analysis, Noldus Information Technology --- ## DanioScope 1.1 - Flow URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-flow Chapter: DanioVision Flow Aim To obtain a relative measure of body fluid movements in a section of a blood vessel or the gut. To Open the Flow Screen Choose Acquisition > Flow. Notes - In DanioScope, Flow measures the percentage of the area of interest that changes its gray scale value per video frame. The higher the flow rate in a gut or blood vessel, the higher this percentage. Note that Flow does not measure flow rate in physical units (like volume or mass per time unit). - Important: Make sure that the video is in focus. If the image is not in focus, Flow is generally underestimated. - Important: Flow also depends on the size of the area of interest. Be careful when comparing different measurements or subjects. Make sure that the Flow areas only cover the section of the blood vessel or gut, and not other body parts. Main Steps - Draw the flow areas. - Acquire flow data. Draw the Flow Areas To Load Video Files - Click the Add Video(s) button. - Select one or more video files, and click Open. To select multiple files, hold the Ctrl key down and click each file name. - The list of loaded video files appears. The video window shows the first video in the list. Tip: To select another video for preview, select the check box near its name. To Draw the Flow Areas - Select one of the video files in the list. - Click one of the drawing tools and draw a shape over the area of interest of a subject. Make sure that the shape includes the entire section of the blood vessel or gut, not other areas. If the shape includes areas in which there is no flow, Flow statistics will be underestimated. For details about drawing shapes, see Add a Measurement. - Select an existing subject to assign the shape to it, or select Add Subjects. - For multiple subjects: if you selected Draw template shapes for all subjects, all shapes are copied at the top of the video window. Move each shape to the corresponding vessel or gut section. - Click a shape and drag the handles to resize and adapt it to the vessel or gut section. Play the video for a clear view of the flow in those regions. Tip: To better compare flow measurements between subjects, draw Flow shapes of equal size and shape. For this purpose, use the Duplicate function. Right-click a shape and select Duplicate. In the context menu that appears, select an existing subject to assign the shape to it, or select Add Subject. - Repeat the entire procedure for each video file to analyze. Tip: The Status column tells you which step is next for each video file. Next Steps - The video is analyzed up to its end. If a subject changes position significantly throughout the video, you must specify the stop time for the measurement (see To Set a Stop Time for a Measurement). Optionally, specify the new location as a new measurement (see To Add a New Measurement for the Same Subject). - Acquire flow data. Acquire Flow Data To Acquire Flow Data - Make sure that all flow areas in your videos are marked, and in the correct video fragments. - To acquire data for the current video, click the Acquire button. To acquire data for all videos where subjects have been defined, click Acquire All. - At the end of acquisition the Status column in the video list says Acquired. Notes - If you resize a shape after acquisition, the flow statistics for that measurement are cleared and the Status column says Next: Acquire. Click Acquire to acquire the data. Flow Statistics In the list below the video window you find the flow statistics per subject and measurement: Flow Activity (%). Notes - The video frame corresponding to the Stop time is not analyzed. Video is analyzed from Start to Stop (included). See Also - Trial Statistics - Group Statistics and Charts - Export Statistics - Export Raw Data Source: DanioScope 1.1 Reference Manual - Flow, Noldus Information Technology --- ## DanioScope 1.1 - Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-installation Chapter: DanioVision Install DanioScope System Requirements Operating System - Windows 10 Professional, 64 bit. - Windows 7 Professional, 64 bit, Service Pack 1. To check that a Windows 7 computer has Service Pack 1 installed, choose Control Panel > System and Security > System. Under Windows edition you can see whether Service Pack 1 is installed. Computer DanioScope has been tested with a Dell Precision™ T5810 PC, and a Dell Precision™ 7510 mobile workstation. Dell Precision™ T5810 PC - Processor: E5-1620 v3 (Xeon 3.50 GHz 4-core). - Internal memory: 8 GB. - Graphics card: NVIDIA Quadro K620, 2 GB DDR3 memory. - Hard disk: 500 MB free space for program installation. Allow enough hard disk space for storing video and image files. Dell Precision™ 7510 Mobile Workstation - Processor: 6820HQ (i7 2.70GHz 4-core). - Internal memory: 8 GB. - Graphics card: Nvidia Quadro M1000M, 2 GB GDDR5 memory. - Hard disk: 500 MB free space for program installation. Allow enough hard disk space for storing video and image files. See also: Which video and image formats are supported? Install DanioScope Important: Make sure that the USB hardware key is not plugged in to your computer before installing the software. To install DanioScope: - Insert the DanioScope Installation USB stick into one of your computer's USB ports. Browse to the USB stick contents and double-click Setup.exe. - In the Welcome screen, click Next>. - Read the license agreement and select I accept, then click Next>. - Click Install. - When the Install Shield Wizard Completed screen appears, click Finish. To start DanioScope: - Insert the DanioScope hardware key in one of the USB ports of your computer. - Double-click the DanioScope icon on your desktop, or choose Apps > Noldus > DanioScope. Notes: - The DanioScope program folder is by default C:\Program Files (x86)\Noldus\DanioScope 1. - The DanioScope data folder is C:\Users\Public\Documents\Noldus\DanioScope\Experiments. See also: Change the default data folders License Agreement License Noldus Information Technology b.v. ('Noldus') grants you a non-exclusive license to use the software and accompanying documentation (collectively called the 'Software' in this agreement) in accordance with the following terms. Noldus retains title and all ownership rights to the Software. Noldus will allow you to make back-up copies of the Software, always including copyright notices, provided that these copies are only for your own use. Noldus grants you the right to transfer this license and the Software to another party, provided that (a) the other party accepts all terms of this agreement, (b) all copies of the software are transferred and you discontinue use of the Software after transferring, (c) Noldus is promptly notified of the license number of the Software and the name and address of the other party, and (d) Noldus is not required to supply new media. You may not sublicense, assign or transfer the license or the Software except as expressly provided in this agreement. Any attempt otherwise to sublicense, assign or transfer any of the rights, duties or obligations hereunder is void. Term and Termination Failure to comply with any of these terms will terminate this agreement and your right to use the Software. You may also choose to terminate the agreement at any time. Upon termination of this agreement, you must immediately destroy the Software and all copies of it. Limited Warranty Noldus warrants that the media on which the Software is furnished are free of defects in workmanship and material under normal use, and that the Software will perform substantially in accordance with the specifications set forth in the documentation provided with the Software, for a period of ninety (90) days from the date of purchase by you. During the 90-day warranty period, if the Software does not perform as warranted, Noldus at its sole option will (a) provide, without charge, a replacement of the media, (b) provide, without charge, corrected Software, (c) replace, without charge, Software with a functionally similar program, or (d) refund the fees paid for licensing the Software. These are your sole and exclusive remedies for any breach of warranty. Do not return any product until you have called Noldus or its supplier and obtained a return authorization number. Disclaimer Software is licensed 'as is' without warranty as to its performance. Except for the limited warranty provided above, there are no warranties expressed or implied, including but not limited to implied warranties of merchantability or fitness for a particular purpose, and all such warranties are expressly disclaimed. In no event shall Noldus or its suppliers be responsible for any indirect or consequential damage or lost profits, even if Noldus and its suppliers had been advised of the possibility of such damage. Miscellaneous The Software and accompanying documentation are protected by both Dutch copyright law and international copyright treaty provisions. This agreement will be governed by the laws of The Netherlands. Other Software - HASP is a trademark of Gemalto N.V., Amsterdam, The Netherlands. Source: DanioScope 1.1 Reference Manual - Installation, Noldus Information Technology --- ## DanioScope 1.1 - Morphology URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-morphology Chapter: DanioVision Morphology Aim In DanioScope, Morphology measures body parts and organs. Typical measurements are Body length, eye area, pericardial area. You can also define additional measurements. To Open the Morphology Screen Choose Acquisition > Morphology. The Morphology module works with image files or video files. Main Steps - Add images for Morphology. - Calibrate the images for Morphology. - Measure organs in Morphology. Note: Only calibrated images are used in the statistics calculation. Add Images for Morphology To Add Images from Image Files - Click the Add Images button and load the files you require (*.bmp, *.jpg, *.png). - The list of loaded images appears under Morphology. The video window on the right shows the last loaded image. - Optional: Enter text for a Description of an image (last column of the list). To Add Images from Video Files - Click the Add Images from Video button. - Select a video file. - In the Add Video Images from Video window, play the video to the point where a good image is suitable for measurements. - Click Grab Image. Repeat this step to add more images from the same video. Each new image is appended to the measurement list with the name [video file name]1, 2, ... - Click Browse to select another video file and add more images. Tip: To select another image for preview, select the check box near its name. To remove an image, click the corresponding row and click Remove Images. Calibrate the Images for Morphology To Calibrate Images For each image, select the correct Calibration Profile from the list. Use a calibration profile to apply the same scale to multiple images. If you do not calibrate the images, length and area measurements will be in pixels and pixels², respectively. To Create a New Calibration Profile To create a calibration profile, use a picture containing an object of known size, like a stage micrometer. - Click the Calibration Profiles button. - Click Add and select an appropriate picture of format *.bmp, *.jpg, or *.png. - Enter a name for the new Calibration Profile, and click OK. - In the picture that opens, drag the arrow line to the extremes of the object of known size. Zoom in the image and choose another color for the arrow line if necessary. - Enter the Known distance of the object (in m). - Enter the Pixel aspect ratio or leave the default value (1.00). For information on the pixel aspect ratio of your images, see the documentation of the image acquisition software or hardware. Tip: Most video cameras and microscopes have a pixel aspect ratio equal to 1. When the pixel aspect ratio is unknown, you can use free software like ImageJ to analyze your images. Alternatively, make a picture with an object of known size in both dimensions X and Y. Create a new calibration profile, and draw a line first over X and then over Y. Take note of the Distance in pixels (Px and Py). The aspect ratio is (Px/X) / (Py/Y). The X Scale and Y Scale values are updated according to the values you have entered. - Click OK. In the Morphology screen, select the calibration profile for the images it applies to. Note: Only images associated with a calibration profile are used in the statistics calculation. Measure Organs in Morphology - Select the image in which you want to make measurements. - Zoom in or out when needed to have a complete view of the organ to measure. - Choose one of the drawing tools. The available tools depend on what Morphology measurements are defined in the Experiment Settings. - Draw the shape over the organ you want to measure. When drawing a polygon and the Body Length open polyline, click once to add a new vertex. To confirm the shape: - For the Body Length simple line and ovals, release the mouse button. - For the polygons, double-click the first vertex. This closes the polygon. - For the Body Length open polyline, double-click the last vertex. - Assign the shape to an existing subject or select Add Subjects. - For multiple subjects: If you selected Draw template shapes for all subjects, all shapes are copied at the top of the video window. Move each shape to the corresponding subject, otherwise draw new shapes and assign them to the remaining subjects. - Click a shape and drag its handles to resize and adapt it to the body or organ to measure. - For measurements that require direct observation, enter or select the value in the corresponding column of the measurement list: - Somites: The number of somites of that subject. - Tail Detachment: Select the value that applies (Positive, Negative). - Body Curvature: Select the value that applies (Dorsal, Ventral, Straight). - Repeat the procedure from step 3 to add more measurement shapes. - Repeat the entire procedure for each image file to analyze. The Calibration Profile column tells you which calibration profile is used. Images marked with Not specified are not included in the analysis. The Status column tells you which image file has been calibrated and contains measurements. Morphology Statistics Morphology measurements are immediately available in the list below the image window. Note: The Status column says Partially measured when not all variables defined under Morphology Measurements are measured or entered. See Also - Trial statistics - Group statistics and charts - Export statistics Source: DanioScope 1.1 Reference Manual - Morphology, Noldus Information Technology --- ## DanioScope 1.1 - Questions and Answers - Add a Measurement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-questions-and-answers-add-a-measurement Chapter: DanioVision Add a Measurement Prerequisites Choose the option you require from the Acquisition menu. To Add a Measurement - At the top of the video window, choose a drawing tool. - Draw a shape around the body part of interest. To enlarge the image, use the Zoom In button. When drawing a polygon, click once to add a new vertex. When ready, release the mouse button (for a rectangle or oval) or double-click the first vertex (for a polygon). The next steps depend on whether subjects are already defined. To Add a Measurement When No Subject Is Defined Yet - If no subject is defined yet for that video/image, the Add Subjects window appears. Enter the Number of subjects to measure in the video/image. The new area of interest will be assigned to S1/M1. If the video/image contains one subject, leave 1. - Optionally, select the Independent Variable Values for this group of subjects. If subjects must be assigned to different values (e.g. some Control and some Concentrate 1), do this in the list under the video window. - Select Draw template shapes for all subjects to create multiple copies of the shape you have just drawn. You can later move and edit each shape to adapt it to the corresponding area of interest. If you leave the option not selected, DanioScope adds the subjects to your list but does not create more shapes. - Click Add. To Add a Measurement When One or More Subjects Are Already Defined - A context menu appears, listing the subject names. If the new area of interest refers to a subject already defined, select that subject. The new area will be marked as a new measurement for that subject (for example, S01/M2). If the new area of interest refers to a new, undefined subject, select Add subject from the context menu. - Enter 1 or a higher number, depending on how many subjects are still undefined, and optionally specify the values of the independent variables for those subjects (you can also do that later on). Next, click Add. The shape is marked as a new measurement for the first of the added subjects (for example, S04/M1). To Adjust the Area of Interest If necessary, drag the shape handles to move and resize it so that it matches the contour of the subject/body part as much as possible. For Activity, a little overlap between the circles is acceptable. Important: If you resize a shape after acquisition, the statistics for that measurement are cleared and the Status column says Next: Acquire. Click Acquire to acquire the data. Delete a Shape (Measurement or Subject) Do one of the following: Delete a Shape on the Video Image Right-click a shape and select Delete Measurement. Select Delete Subject if you want to delete the subject the shape belongs to. This means that all measurements and shapes for that subject are removed. Deleting a shape also means removing the measurement in the list. The subject is deleted from the list only if you choose Delete Subject. Delete a Row in the Measurement List Right-click the row in the list under the video window and select: - Delete Measurement. The measurement row is deleted. If that row is the only one for a subject, it is cleared (the cells Measurement Start, Stop and Duration are blank), but not deleted. - Delete Subject. All rows for that subject are deleted. The shapes are removed from the video window according to the option chosen. To select multiple shapes/measurement rows, hold the Ctrl key down and click each shape. To select all measurement rows, click the top row, hold down the Shift key and click the last row. Add a New Subject You add a subject by drawing a new shape and selecting Add Subjects. See Add a Measurement. Edit the Independent Variable Values Aim To assign values of independent variables like Time Point and Compound to different subjects and measurements. You can then use those values to group subjects and measurements in Group Statistics and charts. If subjects in the same video have different values of an independent variable, you can set those values for each subject. To Assign a Value to One Subject/Measurement Do one of the following: - In the measurement list under the video window, locate the independent variable column. Select the appropriate value for a subject. - In the video window, right-click the subject/measurement you want to edit and choose Edit Variable Values. In the window that appears, select the appropriate value for that subject/measurement. To Assign a Value to Multiple Subjects/Measurements Do one of the following: - In the video window, hold Ctrl or Shift down and click each subject/measurement you want to edit. When ready, choose Edit Variable Values. In the window that appears, choose the appropriate value and click OK. - In the measurement list under the video window, select the rows for subjects and measurements you want to edit. To select adjacent rows, hold Shift down and click the first and the last row. To select non-adjacent rows, hold Ctrl down and click each row. Next, right-click anywhere in the rows and select Edit Variable Values. In the window that appears, choose the appropriate value and click OK. For both methods, the value of the independent variable chosen is applied to all subjects/measurements selected. Duplicate a Shape To make an exact duplicate of a shape (recommended when comparing Flow measurements), right-click a shape and select Duplicate. In the context menu that appears, select an existing subject to assign the shape to it or select Add Subjects. If you select an existing subject with n measurements, the shape receives the same subject code and a new measurement code (n+1). Edit a Shape - To move one of the ends of a line, select the line and drag the corresponding white square. - To reposition the vertex of a polygon or open polyline, hover the mouse on the shape; when a four-arrows cursor appears, click once. Drag the white square at the vertex you require. - To move an entire line or other shape, click in the middle of the line or shape and drag it to the new position. --- ## DanioScope 1.1 - Questions and Answers - Change the Shapes' Color URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-questions-and-answers-change-the-shapes-color Chapter: DanioVision Change the Shapes' Color To choose a new color for all shapes in your video/image, click the Set Shape Color button above the video window and select the color of your choice. - You can specify a color for Activity, Cardiology, Flow and Morphology. The color is applied to all video/image files currently loaded for that function. - You cannot apply colors to individual shapes or video/image files. Zoom In/Out To enlarge or reduce the video/image size, click the Zoom In or Zoom Out button above the video window respectively. Zoom range: 20–180%. - When you resize the DanioScope window, the video/image zoom level is adjusted to fit the whole image to the new size. - You can also zoom in on a plot in the Visualizations screen. See also Play Back Video and Plots. Remove Results for a Video or Subject You can remove the results for a video or subject without removing the video itself from the experiment. - From the Acquisition menu, choose the type of measurement. In the measurement list, for the video or subject you want to remove (for example, Cardiology1), select from one of the independent variables. - Choose Analysis > Data Selection. Click the Filter box next to the independent variable you have chosen, and for the appropriate measurement type, deselect . - Choose Analysis > Trial Statistics or Group Statistics and Charts. The video/subject which you wanted to remove is not listed in the results. Error Messages Video or Image Missing When a video file or an image file is missing, DanioScope shows a message "At least one video (image) file is missing". The missing file name is displayed on a red background. Hover the mouse over the file name to view the folder path where DanioScope expects the file to be located. - Locate or copy the missing video/image files to the PC. - Click the Relink Videos or the Relink Images button. - In the Browse For Folder window, select the folder containing the missing videos/images. Video Error (DanioScope Could Not Analyze the Video) In the Acquisition screen, and for Activity, Cardiology and Flow, after clicking Acquire or Acquire All, the Status column shows Video error. An error message also appears at the top. The video error occurs in the following cases: - When a video file contains errors. - When the segment of video defined by the measurement contains more than 5% of missing video frames. - When the segment of video defined by the measurement contains at least 0.1 seconds of consecutive missing video frames. In such cases DanioScope cannot calculate the Activity parameters reliably. Please check the video-recording device or software, then redo the video recording. In the measurement list, the Video error message may appear for one measurement but not another in the same video, depending on whether missing frames are found in the corresponding segment of video. In that case the video is marked with Partially acquired. See also: Video Image Quality. For More Information Help Desk If you have any problems, questions, remarks or comments, please contact the help desk. In DanioScope, choose Help > Noldus Online > Contact Help Desk and fill out a Support Request Form (preferred), or phone. 24-hour support is available via several help desks in different time zones. Please have the following information available when you contact the help desk: - The version number of your copy of the software. - The name of the registered user and the license number of your copy of the software (choose Help > About DanioScope > User Info). NoldusCare Your license of DanioScope comes with a one-year NoldusCare service, which includes free technical support and other advantages. With NoldusCare you make sure that you work with the latest version of your software, based on input from our worldwide customer base. Updates, upgrades and new releases are available for free, as well as update meetings where you can discuss new features with a Noldus consultant. Source: DanioScope 1.1 Reference Manual - Questions and Answers, Noldus Information Technology --- ## DanioScope 1.1 - Questions and Answers - Create a Copy of Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-questions-and-answers-create-a-copy-of-data Chapter: DanioVision Create a Copy of Data Aim With the Backup function you can create backup copies of experiments to store data in a safe location. Important: A backup of the experiment does not contain video and images. Do not forget to create backup copies of these as well. To Back Up an Experiment - Open the experiment you want to create a copy of, and choose File > Make Backup. Enter a File name. Choose a Folder. The default folder is C:\Users\Public\Documents\Noldus\DanioScope\Experiments\Backups. Click Backup. - Copy the backup file (with extension *.dsz) to the location you require. If you want to open the experiment on another PC, make sure to copy the video and images together with the *.dsz file. - To restore an experiment from a backup file and open it in the new location, choose File > Restore Backup. Choose the backup file and select the folder where you want to store the experiment. If DanioScope does not find the videos/images, click Relink Videos/Images and select the folder where you copied your videos/images. Notes - Important: Make a backup of your experiments on a regular basis, at least once a day. - The default name of the backup file is [experiment name] - [date] [time].dsz. - To change the default backup folder, choose File > Preferences. - Click Open Output Folder in the Backup Experiment window to check which backup files are saved there. Copy Settings from One Experiment to Another Aim With the Template function you can save settings like morphology measurements and independent variables to a template, and apply those settings when creating new experiments. To Save an Experiment as a Template A template is an experiment with predefined settings, but no video or data. You can use a template to create new experiments with the same settings and properties without having to re-define them. When you save an experiment as a template, the template stores the following: - The Measurements selected in the Experiment Settings. - The list of Morphology Measurements. - The list of Independent Variables. - The Activity Settings. - Calibration Profiles. To save an experiment as a template, open that experiment and choose File > Save as Template. Enter a name and click OK. To make an experiment based on a template, choose File > New from Template. Manage Your Templates - To rename or delete a template, choose File > Manage Templates, select the template and click Rename or Delete. - To specify a template as a default, choose File > Manage Templates, select the template and click Set as Default. That template is selected when you create an experiment from a template. The Standard Template The standard template has the following settings: - Measurements: Choose Setup > Experiment Settings to view the default measurements. - Independent Variables: Choose Setup > Independent Variables. How to Deal with Embryo Movements in Space Depending on your medium, embryos might float to another location during the experiment. When this happens, you can redefine the position of the embryo and measure activity at this area for the selected duration of the video. Example In this example, the subject S01 stays in the same place between time A and B (the arrow represents time), then from time B to C it moves to the right of the image. From time C, it stays in the same position up to the end of the video. For accurate activity quantification, the yellow circle must overlap with the chorion. Therefore, the measurement S01/M1 must be defined from frame A to B. You can do this by setting the stop time to time B. See To Set a Stop Time for a Measurement below. Since the embryo does not displace from time C to the end of the video, you could add a second measurement that goes from time C to the end of the video. Note, however, that if you work with large samples, occasional floats may be ignored. You can minimize the amount of manual editing and keep your margin of error low. To Set a Stop Time for a Measurement - Position the video to the last frame where the subject remains in the initial position. - Click that subject's name in the subject list, and click the button under Stop. The Stop time changes to the current video time for that subject. The Duration of the video fragment to analyze changes accordingly. - To check that DanioScope does not analyze the frames after the Stop time for that subject, play the video a few frames forward. The shape for that subject should disappear. - If you want to analyze the video fragment after the subject has moved to its new position, see below. Note: Video is analyzed from Start to Stop (included). To Add a New Measurement for the Same Subject - Position the video to the frame where the subject has reached its new position (time C in the picture above). - Draw a shape around the subject/organ. - In the context menu, select the subject you require. - A new row is appended to the list, under the subject, and marked in the Measurement column with M2 (or M3, and so on, depending on how many measurements are defined for that subject). The new measurement has a Start time, a Stop time and a Duration. Note: Video is analyzed from Start to Stop (included). --- ## DanioScope 1.1 - Questions and Answers - Questions and Answers URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-questions-and-answers-questions-and-answers Chapter: DanioVision Questions and Answers General - How DanioScope analyzes video images - Change the default data folders - Which video and image formats are supported? - Create a copy of data - Copy settings from one experiment to another Embryo Detection - How to deal with embryo movements in space Measurements and Shapes - Add a measurement - Delete a shape (measurement or subject) - Add a new subject - Duplicate a shape - Change the shapes' color - Zoom in/out - Edit the independent variable values Analysis Results - Remove results for a video or subject See Also - Error messages - For more information How DanioScope Analyzes Video Images Pixel Change in the Area of Interest For Activity, Cardiology and Flow measurements, DanioScope analyzes the change in gray scale values of each pixel in the areas of interest (for example, in the case of Cardiology, the heart area). A pixel is the fundamental unit of a digital video or still image. Its gray scale value varies from 0 (pure black) to 255 (pure white). For each video frame n, a value of Activity (%) is calculated. This is the percentage of pixels in the area of interest that change their gray scale value relative to the previous frame (n-1), is the value of Activity (%) for frame n. Example In the example below, two pixels are considered within the embryo area (for Activity). One pixel (top) changes between two video frames. The other (bottom) does not. Suppose that the embryo area defined by the yellow circle is 1000 pixels. If the number of pixels that change their gray scale value from video frame n-1 to video frame n is 450, then Activity (%) for frame n is 45%. For Activity, Cardiology and Flow, the output parameters are based on the temporal change of Activity (%). See a few examples in Visualize Data. Missing Video Frames What Are Missing Video Frames? When recording digital video, the recording hardware and software may not take all information it is given. This may happen when recording high resolution video at high frame rates. In such cases one or more video frames may be "dropped", or "missing". Whether a video file contains missing video frames also depends on the recording setup. If video contains consecutive missing frames for less than 0.1 s, DanioScope linearly interpolates the values of Activity (%) from the known values of the neighboring frames. The measurement is marked as Acquired. Example of How DanioScope Deals with Missing Frames A measurement is defined in part of a video which contains two consecutive missing frames. Two missing frames for a video of 25 frames per second are equal to 2 x 0.04 = 0.08 s. The adjacent (valid) video frames are analyzed and their Activity (%) values are 10 and 30, respectively. The interpolated values of activity for the two missing frames are 17 and 23, respectively. Note, however, that if the same measurement included 4 or more consecutive missing frames, it would not be analyzed and Video error would appear under Status in the Measurement list. Notes - If you analyze video from time 0.00 (first video frame), the value of Activity (%) at that time is unknown. This is because at that time there is no previous frame as a reference. - If you analyze video from a non-zero time, the value of activity at that time is known, because there is always a previous frame. - If you analyze video from time t1 to t2, activity is calculated for all frames, including t1 (unless t1 = 0) and t2. Change the Default Data Folders To change the default location for data, export and backup files, choose File > Preferences. Select a new folder: - To change the location of future experiments, click Browse next to Experiments. - To change the export folder, click Browse next to Export. - To change the default backup folder, click Browse next to Backups. Which Video and Image Formats Are Supported? Video Formats (for All Functions) - MPEG-1 - MPEG-2 — This is a collection of formats; not all are supported. - MPEG-4 — This is a collection of formats; not all are supported. - H.264 AVC — This is a type of MPEG-4, which is supported. - DV-AVI — This is uncompressed video from FireWire cameras. This format is not recommended because of the large file size. Note that DV-AVI is a special case of AVI. In general, DanioScope does not support AVI files. Also, the AVI format should not be confused with the *.avi file extension. Some MPEG-4 files have the extension *.avi, which DanioScope does support. - QuickTime — Container file format developed by Apple. QuickTime video is usually stored in files with MOV extension, and commonly uses the MPEG-4 codec for compression. - Windows Media Video — With file extension *.wmv. Notes - File extensions supported are: avi, mpg, mpeg, mp4, mov, wmv. - Video files made with Media Recorder are supported. - Flash video files (*.flv) are not supported. - Important: Test a specific format before recording all the videos for your experiment. To test a video format, in the Acquisition screen load the video file and play it back. Define one or more measurements, acquire data and check that error messages are not given. See Error Messages. - Automatic detection of embryos for Activity analysis is only possible when the video is not distorted relative to the original aspect ratio of the camera image. If that is the case, convert the video to a compatible format and adjust the video aspect ratio. Image Formats (for Morphology) - JPEG — With file extension *.jpg. - Bitmap — With file extension *.bmp. - Portable Network Graphics — With file extension *.png. --- ## DanioScope 1.1 - Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-setup Chapter: DanioVision Setup Experiment Settings To access the Experiment Settings, choose Setup > Experiment Settings. In the Experiment Settings screen you find: - Location – The location where your experiment is saved. - Description (optional) – Enter information about your experiment such as the kind of test that you perform, the date video was recorded, the name of the researchers, etc. You can edit the description at any time. - Measurements – DanioScope offers four types of measurements. Choose one or more of the following: - Activity. To measure activity bursts. - Cardiology. To measure heart rate. - Flow. To measure fluid movement rate in a blood vessel or the gut. - Morphology. To measure body parts and organs. If necessary, edit the list of Morphology Measurements. What you select under Measurements determines what items are listed under Acquisition in the Experiment Explorer. To enter text you can use a wide range of Unicode characters. For details, see: http://en.wikipedia.org/wiki/Plane_(Unicode)#Basic_Multilingual_Plane. Morphology Measurements To access the Morphology Measurements, in the Experiment Settings, under Measurements select Morphology. The list contains predefined measurements when you create a new experiment from scratch or from the Standard Template: - Body Length (in m). Measured as you draw the line Body Length. - Eye Size (in m²). Measured as you draw the area of interest Eye Area. - Pericardial Area (in m²). Measured as you draw the area of interest Pericardial Area. The remaining variables are for direct observation (not detected automatically): - Somites. The observed number of somites. - Tail Detachment. With possible values Positive and Negative. - Body Curvature. With possible values Dorsal, Ventral, and Straight. To Add a Measurement Variable - Click the Add button. - Next to Name, enter a short name for the variable (default: Variable). - From the Type list, select the type of the new variable: - Area. To measure the area of a surface in the subject. - Length. To measure the length of a body part or organ. - Classifier. To assign a body part to a category. - Number. To record the number of repeated structures. If you select Classifier, click Add to enter a new value. To delete a value, select the corresponding row and click Delete. To edit a value, select the corresponding row and click Rename. - Next to Description, enter a description of what you want to measure. To Edit an Existing Measurement If you want to change the name, type, or description of a morphology measurement, double-click the row of that measurement or select the row and click the Edit button. Make the necessary changes and click OK. To Delete a Measurement Select the row of that measurement and click the Delete button. Independent Variables To access the Independent Variables, choose Setup > Independent Variables. Independent variables are variables that potentially influence the outcome of your experiment. You can assign values of independent variables to each subject; for example the level of the experimental treatment or the age of the embryo. You can use the independent variables as grouping factors. Default Independent Variables For experiments created from scratch (File > New) or from the Standard Template (File > New from Template), two independent variables are defined: - Compound, with 3 possible values (levels): Control, Concentrate 1, and Concentrate 2. - Time point, with possible values 24 hours post fertilization (hpf), 48 hpf, 72 hpf, 96 hpf, 120 hpf, and 144 hpf. Please note the following: - Each subject can be associated with a combination of values of the independent variables. For example, Subject 1 is assigned to Control and 48 hpf; Subject 2 is assigned to Concentrate 1 and 48 hpf. - If a subject is measured in multiple sessions in a video (called measurements M1, M2, etc.), all measurements within that video are associated with the same values of the independent variables. - For each independent variable, specify which function that variable is used for. Select one or more of the functions available (Activity, Cardiology, Flow, and Morphology). - Values of independent variables, including numbers, are always exported as text. To Add an Independent Variable - Click the Add Variable button. - In the Add Variable window, enter the name of the new variable. - Click the Add button and enter the name of a value (level of the factor). Repeat this step for each possible value. - When ready, click OK. - A new row is appended to the list. Select for which type of measurements the new variable is used. - Optional: Click the cell under Description and enter any useful information about that variable. To Edit an Existing Independent Variable - To edit the name of a variable, double-click the name under Independent Variables and enter the name you require. - To add or remove values of a variable, for example to replace Dose 1 with 0.01 mg or add Dose 3, click the button under Values. In the Edit Values window that appears: - To modify a value, select that value and click Rename. - To add a value, click Add and enter the value you require. - To delete a value, select that value and click Delete. To Remove an Independent Variable Select a variable name and click the Delete Variable(s) button. To select multiple variables, hold the Ctrl key down and click each variable row. Source: DanioScope 1.1 Reference Manual - Setup, Noldus Information Technology --- ## DanioScope 1.1 - Welcome to DanioScope - Managing Experiments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-welcome-to-danioscope-managing-experiments Chapter: DanioVision Managing Experiments To change the default location for experiments, see Change the Default Data Folders. To delete an experiment, delete the corresponding folder using Windows. When an experiment is opened on your screen, you can control the experiment from the panel at the left hand side, called the Experiment Explorer, or from the window in the middle of the screen. An experiment created with File > New and an experiment created from the Standard Template has by default six morphology measurements and two independent variables. See Also - Questions and Answers - The Standard Template Source: DanioScope 1.1 Reference Manual - Welcome to DanioScope, Noldus Information Technology --- ## DanioScope 1.1 - Welcome to DanioScope - Welcome to DanioScope URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-welcome-to-danioscope-welcome-to-danioscope Chapter: DanioVision Welcome to DanioScope About DanioScope What Is DanioScope? DanioScope is video- and image-based software for high throughput screening of behavior, cardiology, physiology and morphology of embryos and larvae of zebrafish (and other species). Applications DanioScope offers four main functions for image-based screening of subjects in toxicological, pharmacological and safety pharmacological studies: Activity In zebrafish embryos, movements such as tail flicks, coilings, and convulsive behavior start as early as 17 hours post fertilization (hpf), and are important measurements in toxicology and pharmacology because they reflect the development of the nervous system and are highly susceptible to pharmacological manipulation. DanioScope automatically recognizes the embryos and selects each embryo (in chorion) as a zone of interest in which the activity is recorded. Output: - Burst activity. Percentage of time that the embryo was moving. - Inactivity. Percentage of time of inactivity (100% - Burst activity). - Burst duration. Total and average time spent active (sum and average of all movement durations, respectively). - Inactivity duration. Total time spent inactive. - Burst count. Number of times the embryo moved. - Burst count / per minute. Number of movements per minute. - Activity plot. Cardiology (Mainly for Larvae) In DanioScope, select one or more video files showing one or more larvae each. Then indicate the heart area by drawing a rectangle around it for each larva. Within the area(s) of interest, activity is automatically monitored and heart rate is measured. Output: - BPS. Mean and standard deviation of the number of beats per second. - BPM. Mean and standard deviation of the number of beats per minute. - Heart activity plot. - Power spectrum plot. Flow (Mainly for Larvae) In addition to heartbeat measurements, blood flow is another useful parameter in toxicology and other research areas. Malfunctioning of the heart might not always show in the blood flow measurements, and vice versa, depending on the cause, and so researchers often measure both. DanioScope uses video analysis to estimate the flow in blood vessels and in the gut. Select a part of the blood vessel or the gut, from wall to wall, in your video image. Flow is estimated by the temporal changes in activity on a frame-by-frame basis. Output: - Flow activity (%). Mean percentage of activity in the area of interest. Note that Flow does not produce statistics in physical units like ml/s. - Activity plot. Morphology (Mainly for Larvae) Besides dynamic measurements, DanioScope also allows you to easily monitor the morphology of your subjects. You can upload images or take snapshots from videos to monitor changes in morphology. With intuitive drawing tools you can define distances or areas you are interested in, and after calibration DanioScope measures lengths and surfaces automatically. Output: - Measurements of body parts and organs, such as body length, tail length, eye area, pericardial area. Additional measurements can be entered after direct observation (e.g. number of somites). Study Species DanioScope has been developed specifically to study zebrafish embryos and larvae, but it may be extended to other fish species. For some of the analysis functions, there may be limitations. For Activity, the subject must be transparent enough to allow the software to detect the contour of the chorion automatically. If the chorion is hairy, automatic detection may not work all times. In such cases you can manually draw the contour of the chorion. Key Features Experiment Management Organize your videos, images and data in experiments. An experiment refers to a specific data set, an experimental setup or a research question. Data can be organized in relation to a number of user-defined factors, called independent variables, like genotype, test concentration, etc. Throughput DanioScope can analyze multiple subjects in one video. Analysis DanioScope provides descriptive statistics and charts, for each subject and for groups based on the independent variables. It also allows you to view results from different measurements in the same sheet (for example, to compare heart rates with pericardial areas). Practical Work When working with video files, you can analyze only the part of the video where the subjects do not move. Therefore, there is no need to immobilize the larvae. --- ## DanioScope 1.1 - Welcome to DanioScope - Workflow URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/danioscope-11-welcome-to-danioscope-workflow Chapter: DanioVision Workflow Record Media Files Record video and/or images of one or more subjects to digital media files of compatible format. Video image quality is very important for automatic detection of embryos (see Video Image Quality). If automatic detection does not work, draw manually the contour of the embryo. Give your media files unique names, in such a way they suggest which subjects and time points are recorded. This is handy when copying files from one computer to another. Setup Experiment Settings. Choose which type of measurement you want to carry out: Activity, Cardiology, Flow and Morphology. For Morphology, define the measurements you want to take; for example the Body length. Independent Variables. Define for example the experimental groups Control, Concentrate 1, and Concentrate 2, or variables that mark subjects, for example Batch number. You can use independent variables to make analysis groups. Acquisition Load the videos you want to use (or pictures, in the case of Morphology), define the areas of interest or, in the case of Activity, let the program detect them for you. For Activity, Cardiology and Flow, click Acquire. For Morphology, calibrate the pictures according to your camera setup and take the measurements. Analysis Data Selection (optional). Select measurements based on the values of your Independent Variables. By default, all subjects and measurements are selected for analysis. Visualizations. Visualize data for inspection. For example, plot the power spectrum for cardiology measurements. Replay the video and data together. Trial Statistics. Let DanioScope calculate the statistics of your measurements. For example, the average activity level or average heart rate of each subject. Group Statistics and Charts. Let DanioScope calculate statistics averaged over the subjects in a group. For example, the average heart rates for the three groups Control, Concentrate 1 and Concentrate 2. Summary statistics are accompanied with charts. Result Export Export the results table to text or Excel format. You can export both Trial statistics and Group statistics. For Activity, Cardiology and Flow you can also export the raw data to other software to analyze short-time changes in detail. Video Image Quality Please read the following recommendations carefully. Video and Image Files - Make sure that the video or still image has good contrast and focus. - Check that the image aspect ratio is not distorted relative to that of the source camera. When you load the video files in DanioScope, the chorion should be circular, not egg-like. If the image is distorted, convert the video to adjust the aspect ratio. The aspect ratio of an image describes the proportional relationship between its width and its height. It is commonly expressed as two numbers separated by a colon, for example 4:3 like in still camera images or standard television, or 16:9 like in high-definition television. - DanioScope may not analyze video when it contains missing frames. To reduce the probability that your video contains missed frames, keep a video frame rate just enough to give you the information you need, not higher. One of the causes of missing frames is the shutter (exposure) time in the camera that is too high to be compatible with the frame rate. In that case the camera must keep the shutter open for a long time, and does not have the time necessary to read each video frame at the expected rate. See the documentation that comes with the camera for how to adjust the exposure settings. Test Environment - Embryos should be on a uniform background. Always place embryos in a Petri dish. - Make sure the substance that holds the embryo (for example, agar) does not contain air bubbles or other irregularities. Subjects - In order for DanioScope to detect the position of the embryo automatically, subjects must be transparent enough. This is typically the case of zebrafish embryos. - If the chorion is hairy, automatic detection may not work all times. What's New in DanioScope 1.1? Supported Video Formats You can now analyze video in QuickTime format, with MOV file extension, and Windows Media Video, with WMV file extension. Data Management Independent Variables You can now enter the values of independent variables more easily: - Directly in the video image. Right-click the subject shape and select Edit Variable Values. Hold Ctrl or Shift down to select multiple shapes. - In the Measurement list, hold Shift or Ctrl down and click the rows for which you want to edit the values. Next, choose the value you want to assign to those measurements. Export Raw Data You can now export raw data, where data are written for each video frame analyzed. You can export raw data to text or Excel. Your First DanioScope Experiment Background In DanioScope, an experiment is a collection of video files, data and results related to specific research questions. Each experiment is saved separately on your computer. To Create an Experiment - To create an experiment from scratch, choose File > New. To create an experiment from a preexisting template, choose File > New from Template. - Next to Name, enter the name you want to give to the experiment. The experiment is saved in C:\Users\Public\Documents\Noldus\DanioScope\Experiments. To select another location, click Browse. - If you have chosen New from Template in step 1, select a template from the Template list. Default is Standard Template. - Click Create. Notes - You cannot exchange data between different DanioScope experiments. Make sure that each experiment contains all the video files and results that you want to use for a specific research project. - To open an existing experiment, choose File > Open. - Each experiment is saved to a file with extension *.dse, located in a folder with the same name as the experiment. The folder contains two default sub-folders, Settings and Data. --- ## DanioVision - 1 What is DanioVision? URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-1-what-is-daniovision Chapter: DanioVision 1 What Is DanioVision? Daniovision DanioVision™ is a system for high throughput tracking of zebrafish larvae in multi-well plates. It consists of: The DanioVision Observation Chamber (DVOC-0041) See Figure 1. This chamber contains a transparent holder with backlight that fits an ANSI SBS compatible multi-well microtiter plate, infrared (IR) and white light sources (underneath the microtiter plate), and a Gigabit Ethernet (GigE Vision) video camera. The optical design provides a stable and undistorted top view of each well and a controlled and constant environment within the observation chamber. For technical specifications and for cleaning instructions, see System specifications. tip You find your DanioVision' version number on the label at the back of the chamber. Figure 1 The DanioVision Observation Chamber DVOC-0041. EthoVision® XT Video-tracking software with the Multiple Arenas Module and Trial & Hardware Control Module. Using Trial & Hardware Control, you can adjust the white light stepwise based on time or behavior of your fish. You have the option to connect external devices, such as sound or shock generators. note DanioVision DVOC-0041 works with EthoVision XT 10.1 or newer. Daniovision Add-ons DanioVision Temperature Control Unit With the DanioVision Temperature Control Unit you can set up a water flow at constant temperature underneath the well-plate. For details, see the Reference Manual - DanioVision Temperature Control Unit DV- TCU.pdf, which you can download from the Noldus website (see page 10). DanioVision Tapping Device With the DanioVision Tapping Device you can trigger a startle response in zebrafish. For details, see The DanioVision Tapping Device in this manual. DanioVision Toplight Unit With this add-on you can generate top-down light stimuli in your experiments. Four types of light are available: white, red, blue and green. For details, see The DanioVision Toplight Unit in this manual. DanioVision with Optogenetics DanioVision can be provided with one to three LEDs that illuminate the well plates based on your Trial Control protocol. The Optogenetics add- on allows to accurately control and time the application of optogenetic stimulation to up to 96 individuals simultaneously (one for each well in a 96-well plate). For details, see The DanioVision Optogenetics add-on on page 88. Custom solutions As research evolves, so do research needs. If you are interested in a custom solution, don't hesitate to contact us! A few recent examples of custom solutions: Light-Dark Grid. Commonly used to investigate anxiety behavior in zebrafish. The grid is placed underneath the well plate (available for 6, 12, 24, 48 or 96 wells) and creates a dark and light half in each well. The grid is IR light translucent, leaving the tracking of the zebrafish unaffected. High-speed camera. DanioVision is equipped with a camera capable of 1000 frames per second. The aim is to measure the startle response of larvae to a stimulus during a Pre-Pulse Inhibition test (Burgess and Granato 2007). Split basin. The DanioVision basin has been modified so that it receives water at two different temperatures. The aim of this solution is to measure temperature preference in zebrafish larvae. Ultraviolet Toplight Unit. This is a modification of the Toplight unit (see the previous page), which shines UV light. Light intensity is controlled by EthoVision XT. Turbo-cooling TCU. This is a modified Temperature Control Unit which keeps water at a constant temperature of 12° in a room where temperature is about 25°. For More Information Manuals For more information, see The EthoVision XT Help (press F1 in the EthoVision XT). The Reference Manual - Trial and Hardware Control in EthoVision XT. You can find this manual under Noldus > EthoVision XT 16 Other Documentation. The Reference Manual - DanioVision Temperature Control Unit DV- TCU. You can find this manual on the Noldus website (my.noldus.com). Note that you have to log in to access the downloads page. You can also find other manuals on the EthoVision XT installation USB stick. Sample experiments EthoVision XT download page you can find sample experiments that make use of DanioVision. Browse to my.noldus.com, there under Downloads choose Sample projects, then EthoVision XT. Experiment templates EthoVision XT contains templates that help you setting up an experiment with arenas, analysis profiles and other elements already defined. See create a daniovision experiment on page 41. References See our web page of selected publications: Support center If after reading this manual you still have questions, please contact our Support center at my.noldus.com. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 10 The DanioVision Tapping Device URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-10-the-daniovision-tapping-device Chapter: DanioVision 10 The DanioVision Tapping Device Introduction Larval stage zebrafish display a robust startle response, which is mediated by neural pathways similar to that in higher vertebrates. With the DanioVision Tapping Device you can evoke a startle response in zebrafish larvae. How the Tapping Device works The DanioVision Tapping Device is based on an electromagnetically inductive coil wound around a metal core. The core is made of two parts, a fixed one and a plunger connected to a push pin. When a current flows in the Tapping Device, magnetic force is created between the plunger and the core, causing the plunger and the push pin to quickly move forward (as indicated by the blue arrow in the picture). The pushpin hits a metal plate attached to the basin in which the well plate is kept. When deactivated, a spring makes the plunger resume its position. How you control the Tapping Device With the Trial and Hardware Control module of EthoVision XT you can plan when to activate the Tapping Device during a trial. For example, activate the Tapping Device 10 times at intervals of two minutes. Noldus test results: a summary In both light and dark conditions, the Tapping Device is capable of inducing a startle response in animals of 3 dpf and older. It is in principle possible to design experiments where the animals are subject to stimuli of different intensity. You can set the tap intensity in EthoVision XT (page 76). There is no evidence that the startle response measured by EthoVision XT depends on light conditions and location of the subject in the well plate. See also the white paper Using the DanioVision Tapping Device, which you can download from our web site. important We advise you not to compare the results between two DanioVision Observation Chambers provided with the Tapping Device. Slight differences in the position of the Tapping Device may result in differences in the actual stimulus intensity, all else being equal! Install The Daniovision Tapping Device If you order the Tapping Device together with a DanioVision Observation Chamber, the Tapping Device is already installed. In all other cases: 1. Open the lid of the DanioVision Observation chamber, and remove the bench plate (see also page 116). 2. Remove the two bolts from the aluminium plate at the bottom of the chamber as indicated in the figure below. Make sure that the backlight box does not move. tip Use a pencil to mark the exact position of the backlight box on the frame so that you can place it in that position if it accidentally moves. 3. Put the metal frame of the Tapping Device over the aluminium profiles, and fix the bolts with the supplied spring washers. Use both the already connected spring washers and the new ones. 4. Connect cables as indicated here. The cable with a 4-pin white connector comes from the Tapping Device. b The flat cable with a blue connector comes from the bottom of the DanioVision chamber. Raise the metal hooks, insert the connector, then lower the hooks to fix the connector. The cable with 2-pin connector comes from the bottom of the DanioVision chamber. 5. Attach the control box to the aluminium profile at the front side of the observation chamber. Insert the screw in one of the hole at the sides of the control box. b Attach the spacers and the sliding nuts to the screw. Insert the sliding nuts into the profile, and turn the screw. 6. Put the bench plate back into place and fix the four screws. Set Up The Tapping Device In Ethovision Xt Make sure that the DanioVision Observation Chamber is connected to your EthoVision XT computer. Experiment Settings Under Trial Control hardware, click Settings. In the Hardware Interface window, select DanioVision DVOC-004x/T. Arena settings note If you created an experiment with a pre-defined template and selected an arena template for DanioVision with the Tapping device (DanioVision DVOC 004x/T), the Tapping Stimulus has been assigned automatically to the arenas. The steps below are then not necessary. 1. In the Arena Settings pane click Arena - Hardware Mapping and then click the Arena - Hardware Mapping button. 2. Click Add device. Under Device type, select Tapping Stimulus. Under Arena 1 select Tapping Stimulus. 3. To test the Tapping Device, select the cell under Arena 1 and click Test. Trial and Hardware Control Settings - Open the Trial Control Settings containing the protocol in which you want to insert the Tapping Stimulus. Under Actions - Hardware click the button next to Tapping Stimulus. 2. In the Hardware Action window specify the Intensity level (1-8). Click Test to get an impression of the tap intensity. 3. Click OK and insert the Action box in your Trial Control protocol. 4. Test the protocol before carrying out the real trials. important Allow at least 300 milliseconds between two consecutive tapping events. To do so, place a Time condition box that specifies this time between two Tapping Stimulus Action boxes. Analyze The Response To The Tapping Stimulus You can analyze the startle response by looking at dependent variables like Activity, Distance moved, or Acceleration (state) immediately before and after the administration of the stimulus. In the following example, we examine the Total Distance moved in the 1-second periods immediately before and after the tapping stimulus command was given. We expect that the total distance moved increased from "before" (assumed to be a baseline) to "after". The stimulus command was given at exactly 1 minute after the start of the trial. 1. In the Data profile define two Nesting time intervals, one from 00:59.00 to 01:00.00, the other from 01:00.00 to 1:01.00. Each of the resulting Nest box is connected to a separate Results box. 2. In the Analysis profile define Distance moved. The following picture shows the Distance moved plotted in Integrated Visualization. Figure 14 An example of per-sample distance moved plotted against time for two subjects, and in the 1-s period before (59 s - 60 s) and after triggering the Tapping Device (60 s - 61 s). The hairline indicates the time that the stimulus was administered. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 11 The DanioVision Toplight Unit URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-11-the-daniovision-toplight-unit Chapter: DanioVision 11 The DanioVision Toplight Unit This manual explains the setup and operation of the DanioVision Toplight (type DVTL-0020) for the DanioVision Observation Chamber DVOC-0041. note The DanioVision Toplight Unit is an add-on to DanioVision; it does not come with a standard DanioVision system. For the specifications, see daniovision toplight unit on page 135. Connect The Toplight Unit Components DanioVision Observation Chamber with built-in Toplight Unit. Desktop power supply, TTL-to-28V interface and cabling (see the figure below). Operation With this setup, two of the LED colors, or the white light can be switched on and off from EthoVision XT. The TTL-to-28V interfaces enable switching the power from the desktop power supply. note Whenever you would like to use all three colors (R-G-B) within one experiment you'll need a second TTL-to-28V interface. important The LEDs get hot during operation. Please let the ceiling light cool down before touching it important Do not exceed the maximum specified voltage for each color as doing so may damage the LEDs Setup for the white light - Desktop adjustable supply set to max 18 V for white light. - TTL cable to free TTL port on the DanioVision Observation Chamber's (DVOC) back panel. - White light cable plugged in. - Top light cable from the DVOC's back panel. - Main LED power cable. Connect the components The LED power cable (coming from the back of the DVOC) has 4 connectors, one for each LED color. The connectors belonging to the appropriate colors should be connected to the TTL-to-28V interface on outputs 1 and 2. The TTL network cable (green) should be connected between the TTL- to-28V interface and port 1 on the DVOC (see the next figure). A main power cable connects the desktop power supply to the input of the TTL-28V interface. 1. USB cable to EthoVision XT computer. 2. TTL cable running to TTL-to-28V interface. 3. LED power cable. Operate The Power Supply On the power supply the voltage can be set which determines the amount of light that the LEDs emit. The voltage may not exceed the maximum voltage for each LED color. This is 24V for the Red, Green and Blue LEDs and 18V for the white LEDs. important Higher voltages may damage the LEDs. Before connecting to the mains outlet, check that the mains voltage matches the voltage setting of the power supply. To power up, press the power button. To adjust the voltage Turn the Voltage knobs for coarse and fine adjustments. Or when in presence of one knob, press once for coarse adjustments, and press once more for fine adjustment. The actual output voltage can be read from the display. Both "Current" knobs can be used to set a current limiting value (maximum current). This feature is not needed; just set to the maximum level (turn full clockwise). If not set properly, the supply may come in Constant Current mode (CC) and limit the output voltage. It is good practice to first set your desired voltage before actually connect the main LED power cable to the supply. For more information, see the supply manual. Change The Lights Two switch between red, green and blue To change between colors, simply unplug the current connector of the LED power cable from the TTL-to-28V interface and plug in the correct one. Each connector is labeled. To switch between white and colors If you want to switch from RGB to white light (or vice versa), turn the complete unit in order to have the right LEDs facing down towards the well plate. The RGB LEDs and white LEDs are mounted on the opposite sides of the same plate and can be identified by the label white and rgb attached. 1. Cover the lens bracket with some protective material. 2. Untighten both left and right round black knobs to enable the unit sliding down a few centimeter, just below the camera. 3. Pull the unit out and turn it upside down (facing the preferred LED's down). important Be careful not to twist the cable at the back. Unplug temporarily both connectors to prevent this from happening. 4. Insert the unit and slide it up again. 5. Tighten both round knobs. Configure Ethovision Xt To Control The Top Lights - Start EthoVision XT and create a new experiment using a template (File > New from template). During the guided setup, choose Live Tracking, Zebrafish larvae, DanioVision [with the type of well plate you use]. 2. Choose Setup > Experiment Settings. Under Trial Control Hardware, select Use of Trial Control Hardware and choose the options as in the figure below. Choose the TTL port of the DVOC that you connected (see above). You can rename Device ID to something like "Ceiling Light". 3. Choose Setup > Arena Settings. After calibrating and drawing the arenas, click Arena Hardware Mapping. Click Add device and follow the picture below. You can rename the text under Device name to something like "Ceiling Light". Under A1 select the device. Then Click OK. 4. To test the light, select Output 1 High or Output 2 High from the Command menu and click the Test button. To turn them off, select Output 1 Low or Output 2 Low. Program The Top Lights In Ethovision Xt Choose Setup > Trial Control Settings. Example: After 1 minute during the trial, switch the light on, then after 10 seconds switch it off. Under Conditions, choose Time to create a time condition (e.g. Wait 1 minute, Wait 10 seconds). Under Actions, choose Custom Hardware to define commands (Switch on/off). This can be done for both output 1 and output 2. Remember to connect all boxes with the start-stop procedure. Create routines With the Subrule function you can create routines, to switch on and off the lights in repeated sequences. For more information, see the Reference Manual - Trial and Hardware Control in EthoVision XT. Also adjust the Detection Settings (Setup > Detection Settings) before running the trials. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 12 The DanioVision Optogenetics add-on URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-12-the-daniovision-optogenetics-add-on Chapter: DanioVision 12 The DanioVision Optogenetics Add-on Introduction Optogenetics allow scientists to control the activity of specific neurons and study their downstream influence on a variety of biological processes, including behavior. In rodent studies, this technique requires optical fiber implantation. When working with zebrafish larvae, mostly transparent, fiber optics are not needed Light simply needs to shine in the right direction, making it easy to assess the effect of stimulation of specific, light-sensitive neurons on the behavior of the fish. By inserting light-sensitive receptor proteins into neurons in vivo, it is possible to make those neurons sensitive to activation by light of specific wavelengths. In zebrafish studies, the light-sensitive receptor protein halorhodopsin (NpHR) has successfully been used to inhibit swimming behavior in zebrafish larvae (Arrenberg et al. 2009). Other research showed that channelrhodopsin-2 (ChR2) activation induced backward swimming in a sparse transgene expression line (Zhu et al. 2009). Optogenetics add-on Application of optogenetic stimulation in zebrafish larvae requires the correct wavelength (i.e., color) of light. When using the DanioVision Observation Chamber, the Optogenetics Add-on provides a way to accurately control and precisely time the application of optogenetic stimulation to up to 96 individuals simultaneously (working with 96 well plates). The Optogenetics add-on for DanioVision is an optogenetic LED light source based on the Prizmatix Modular LED system. It consists of one, two or three LED wavelengths. The Optogenetics add-on can be programmed and controlled using the EthoVision XT software included with your DanioVision system. You can set user-defined time conditions for the optogenetic stimulation. In comparison to manual control, this offers far better temporal precision and adds efficiency to longitudinal studies. References Arrenberg, A.B., Del Bene, F., Baier, H. 2009. Optical control of zebrafish behavior with halorhodopsin. PNAS 106: 17968-17973. Zhu, P., Narita, Y., Bundschuh, S.T., Fajardo, O., Scharer, Y.P., Chattopadhyaya, B., Bouldoires, E.A., Stepien, A.E., Desseroth, K., Arber, S., Sprengel, R., Rijli, F.M., Friedrich, R.W. 2009. Optogenetic dissection of neuronal circuits in zebrafish using viral gene transfer and the Tet system. Frontiers in Neural Circuits 3: 21. Sample experiment Your DanioVision system comes with an EthoVision XT sample experiment: DVOCOptogeneticsDemo_Recommended.evxt. It contains examples of Trial Control rules for triggering pulse sequences in one up to three Pulsers. Additional manuals For connecting hardware Prizmatix UHP-T LED Illuminator User Manual.pdf For programming the Pulser Prizmatix Pulser User Manual.pdf For connecting the DanioVision Temperature Control Unit Reference Manual - DanioVision Temperature Control Unit DV- TCU.pdf Install The Dichroic Mirror In Daniovision When you receive the DanioVision Observation Chamber DVOC-004x with the Optogenetics add-on, the LEDs are already mounted so you only have to connect the cables (see the next section). However, the dichroic mirror comes in a separate box to prevent damage during shipping. This section explains how to install it. Please follow the instructions below. note The function of the dichroic mirror is to direct the color light beams to the well plate, and at the same time allow light to reach the camera, so you can film and track the fish during the test. 1. Locate the box containing the mirror. important Please wear the supplied gloves to avoid damaging or dirtying the mirror. Avoid touching the mirror surface and only hold its edges. 2. Locate the arrow on one side of the mirror. Once the mirror is mounted, this arrow should be at the top of the mirror and point towards the light source, that is, the backside of the Daniovision chamber. 3. Attach the mirror (see the next picture). Slide the mirror upwards along the brackets as indicated by the arrows. 4. Position the mirror just above the mark on the right-hand bracket (see the picture below, 1). When the mirror is in that position, carefully tighten the screw on the left to fix the mirror (2). Do not apply any force as this may damage the mirror. 5. The mirror is now ready to use. See the next sections. important The LED is extremely powerful and may cause eye injury when looking directly into the light source. For testing, we recommend to set the LED intensity to low. The Pulser Software Please skip this section if you do not use the Pulser/PulserPlus devices. Follow the procedure below if you use one or more Pulser/PulserPlus devices. To control multiple devices, multiple instances of the Pulser software must be running on the EthoVision XT computer. important Do not connect the Pulser/PulserPlus device to the computer until the software setup process is complete. Install the Pulser software once - Copy the installation files and folders to your computer's hard drive. - Run the setup.exe file and follow the instructions as they appear on the screen. Next, restart the computer to complete the software installation. - Open the folder where the software has been installed (default: C:\Program Files (x86)\Prizmatix Pulser Plus 3.1) and make a shortcut to the EXE file. Give the shortcut a name that is easily recognized, like Pulser A or the name of the first LED. - To install or update the Pulser/PulserPlus drivers, see the Pulser/ PulserPlus User Manual. Install multiple instances of the Pulser software To control two or three LEDs independently using the dedicated Pulser/ PulserPlus devices, install one instance of the Pulser software for each Pulser/PulserPlus. 1. Install the first instance of the Pulser software (see above). 2. Browse to the folder C:\Program Files (x86) and copy the entire folder Prizmatix Pulser Plus 3.1. 3. Paste the folder in the same location C:\Program Files (x86). Rename the folder to ... Prizmatix Pulser Plus 3.1 PulserB. 4. Open the new folder and make a shortcut for the EXE file that you find there. Place the shortcut on your desktop. Name it like Pulser B or the name of the second LED. 5. If you have a third LED, repeat the steps above from 2 to 4 to create a new folder which will contain a third instance of the Pulser software. Make a shortcut to the new EXE file and rename it to e.g. Pulser C. 6. You should at this point have a folder structure like the following: and three shortcuts on your desktop. The Led Controller To control the LED manually: - Turn on the main power (see 1 in the figure above). - Set the switch near TTL (5) to Int. - Set the switch near Ain (6) to Int. - To turn the LED on, flip the switch (2) on. To control the LED from EthoVision XT (through TTL) - Turn on the main power (see 1 in the figure above). - Set the switch near TTL (5) to Ext. - Set the switch near Ain (6) to Int. - To turn the LED on, flip the switch (2) on. - Connect the TTL cable with BNC connector from the pulser (or the USB-IO box, depending on the setup) to the connector TTL on the back panel of the LED controller (4). - In EthoVision XT you can now give the "high" command. See page 100 or 101 depending on the setup. Other controls Power adjustment dial (3). Analog input (Ain) connector (7). LED control cable connector (8). LED current cable connector (9). DC power jack (10). Configuration 1 - Without The Pulser Connection diagram In the following example, EthoVision XT controls three LED controllers through the TTL ports in the DanioVision Observation Chamber. Note that each port contains two lines, with connectors white (Line 1) or red (Line 2). Each line controls one LED controller. Define the pulse sequence To define a pulse sequence, use actions and conditions in the EthoVision XT's Trial Control Settings. For example a 1-s pulse of light in the first LED can be defined as: Action Light On on port 1 > Time Condition (1 second) > Action Light Off on port 1. For information about creating pulse sequences in EthoVision XT, see the Chapter Optogenetics experiments in the Application Manual - EthoVision XT, which you can find on the EthoVision XT computer under Noldus > EthoVision XT Other Documentation. USB ports You need one USB port on the EthoVision XT computer, to control DanioVision. TTL ports When using one LED, you can use the TTL-port 2 of DanioVision. Use the white connector at the other end of the cable to connect the LED controller. When using two or three LEDs, you can control two LEDs with one TTL port. Use TTL-port 2 for LED 1 and 2, and TTL-port 3 for LED 3. Remember that the white connector at the other end of the cable means Line 1, and the red connector means Line 2. Configuration 2 - With Pulsers Connection diagram USB ports On the EthoVision XT computer, you need: One USB port, to connect DanioVision (see page 17) Additional USB ports, one for each Pulser (see page 97). Connect the USB port of each Pulser to a USB port of your computer. TTL ports When using one Pulser, you can use the TTL-port 2 of DanioVision. Use the white connector at the other end of the cable to connect the Pulser. When using two or three Pulsers, you can control two Pulsers with one TTL port. Use the DanioVision TTL-port 2 for Pulser A and B, and TTL-port 3 for Pulser C. Connect the other end of the cable to the Trigger In port of each Pulser. Remember that the white connector at the other end of the cable means Line 1, and the red connector means Line 2. Experiment Settings Choose Setup > Experiment Settings > Click Settings next to Use of Trial Control hardware. Then follow the section below that applies to choose the port numbers in the Device Configuration window. tip Open the sample experiment DVOCOptogeneticsDemo_ Recommended.evxt. This is a live tracking experiment where basic settings in Experiment Settings and Trial Control are already selected for when you work with three pulsers. Configuration 1 - without Pulser Each LED controller is connected directly to one TTL port of DanioVision. If for example you have three LEDs, choose Port 2 for the first two LEDs, and Port 3 for the third one. See the corresponding scheme on page 95. Configuration 2 - with Pulser Each Pulser is connected to one TTL port of DanioVision. If for example you have three Pulsers, choose Port 2 for the first two Pulsers, and Port 3 for the third one. See the corresponding scheme on page 97. Under Device ID, give each port a name that can be easily recognized. Arena - Hardware Mapping Choose Setup > Arena Settings. Draw the arenas (see this manual). When the arenas are ready, click the Arena - Hardware Mapping button and make sure that the devices are selected under Arena 1 (A1). The figure below refers to a configuration with three Pulsers. Trial Control (no Pulser) important Before you follow this section, make sure that (1) the dichroic mirror is installed in the DanioVision chamber (page 90), and (2) all components are connected (page 95) and powered up, and (3) that the LED controller is set to TTL control (page 93). When the LED is controlled directly from EthoVision XT, activation occurs in Trial Control, using the Action boxes. The duration of the light pulse is determined by a Time condition placed between the Action Output 1 High and Output 1 Low. In the example below, LED 1 (Device D in the Arena - Hardware mapping window; see above) is activated with a TTL signal Output 1 High and after 0.5 it is deactivated with a TTL signal Output 1 Low. The LED Controller must be connected to DanioVision through TTL Port 1 - Line 1 (see page 95). Use Output 2 High/Low commands to control the other LED controller connected to the same DanioVision TTL port. Make sure that the Int-Ext switch near TTL on the LED controller is set to Ext! Trial Control (with Pulsers) important Before you follow this section, make sure that (1) the dichroic mirror is installed in the DanioVision chamber (page 90), (2) all components are connected (page 97) and powered up, and (3) that the LED controller is set to TTL control (page 93). Procedure - Open all the instances of the Pulser software by clicking on the desktop shortcuts Pulser A, Pulser B, and Pulser C. Each instance controls one pulser. 2. For each instance of the software, next to Select COM port, choose the correct COM port for the corresponding Pulser. These can be found on the pulser or on the connection diagram. 3. Next to Select Operation Mode, choose one of the following: When testing the Pulser, choose (0) Execute pulse sequence after START. By pressing the Start Sequence button, the LED flashes the configured sequence. When running the actual trials, choose (3) Execute pulse sequence after trigger HIGH, then stop when LOW. If you now click the Start Sequence button, the Pulser waits for a TTL trigger to start the sequence. 4. Enter the other settings in the dialog to control the pulse duration and the time between pulses. For details, see the Prizmatix Pulser/ PulserPlus User Manual. 5. Start EthoVision and open the example experiment: DVOCOptogeneticsdemo_recommended.evxt In the Trial Control Settings you find predefined routines (called subrules) to control three Pulsers. The main procedure (top row) has been configured to consecutively trigger the three Pulsers using the corresponding subrules. Make sure the pulsers all have the correct COM port, are all in mode 3 and the start sequence button has been pressed. See also configure the com port for each pulser on page 103. Here below you find the basic actions to control the triggering of the Pulsers. For more information, see also the Chapter Optogenetics experiments in the Application Manual - EthoVision XT, which you can find in Start > Noldus > EthoVision XT Other Documentation. Basic subrule A basic set of instructions in a subrule activates the Pulser a number of times, as specified in the Subrule Reference box. The boxes within the subrule specify an action to trigger the pulse sequence (Send a signal High to a device through line 1 or 2), a Time (wait a number of seconds) and a second action which stops the pulse sequence (Send signal Low to a device through line 1 or 2). In the following example, the subrule triggers the sequence in the Pulser A through Output Line 1, for 5 seconds. The name of the device selected next to Custom Hardware is 570 +520 nm, because it control two Pulsers, one for a LED of 570 nm (through Output Line 1) and one for a LED of 520 nm (through Output Line 2). You find the name 570 +520 nm in the Arena - Hardware Mapping window of the Arena Settings in the demo experiment. In practice, the subrule would look like the following: Make sure that the Int-Ext switch near TTL on the LED controller is set to Ext! Configure The Com Port For Each Pulser Aim To configure the COM port in such a way the Pulser/PulserPlus accepts commands from EthoVision XT. Procedure - Connect the Pulser/PulserPlus to the PC using the USB cable with type-A to type-B connectors. - In the Control Panel, open the Device Manager. - Under Ports (COM & LPT), right-click USB Serial Port and select Properties. - Click the Port Settings tab. - Make sure that the parameters are as below, then click OK. - Take note of the port number (in the example above it is COM3). - Repeat the procedure for each Pulser/PulserPlus. Notes The COM port number is retained in the Pulser, so if you disconnect the Pulsers and reconnect them, you do not have to assign the COM ports again. tip To know which COM port is assigned to which Pulser/PulserPlus device, disconnect the USB cable from one Pulser/Pulser Plus. Then, re-connect it. The item that appears under Ports (COM & LPT) indicates the COM port. tip To change the COM port for a specific Pulser, in the Control Panel, open the Device Manager. Under Ports (COM & LPT), right- click the COM port, select Properties, Port Settings, then Advanced. From the COM Port Number list select the COM port among those available. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 13 Data preparation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-13-data-preparation Chapter: DanioVision 13 Data Preparation Smooth The Tracks Track Smoothing profiles in the template experiment No Smoothing. Smoothing filters are not activated. MDM 0.2 mm - With this Minimal Distance Moved filter, you can reduce the effect of 'jitter' on the Distance moved variable. Applying this filter is recommended, however, it results in longer calculation times in the analysis. Change these settings for your setup, if necessary. More options Use the Maximum Distance Moved filter to remove outliers in the track, due to erratic detection of objects within the arena. when the margin of the well is sometimes detected as the fish. For more information on smoothing data, see Smooth the Tracks in the EthoVision XT Help. Select Data Data profiles in the template experiment All Data. With this Data profile you analyze all tracks separately. Treated vs. Control - The data are split for analysis based on the two values of the user-defined variable Treatment: Treated and Control. Analyze dark vs. light periods In this example, the researcher wants to analyze the data in different light and dark periods, determined by the activation of the white light. In the Data profile, the function Trial Control State under Nesting is used to create intervals corresponding to the state of the white light. 1. Choose Analysis > Data Profile > New. Give the new Data profile a name and click OK. 2. In the Components pane, under Nesting, click the button next to Trial Control State. 3. Select the period you are interested in, using the Trial Control actions. For example From Light On To Light Off (depending on what name the Light On/Off actions have in the Trial Control Settings). 4. Insert the Nest box in the Data profile sequence. 5. If you want to analyze different periods and have the results in the same table, create more Results boxes as shown in the picture below. To add a Result box, in the Components pane click the button next to Result. In each sequence, add a Nest box that specifies a different Trial Control State. 6. Choose the dependent variables and run analysis (see page 113). tip See also the sample experiment DanioVision with 96 wells XT which you can download from our web site. There you can find the Data profile mentioned here. Analyze data excluding periods of inactivity In this example we want to exclude the interval in which a larva was not moving. 1. Choose Analysis > Data Profile > New. Give the new Data profile a a name and click OK. 2. In the Components pane, under Nesting, click the button next to Movement. 3. In the Movement tab, you can set the following: Averaging interval (range 1 - 1000) - This is the number of samples across which changes in speed are calculated to determine whether the subject is moving or not. In order to reduce the sensitivity of the Movement variable to brief changes in velocity, the velocity data can be smoothed by taking the running average of the last n samples. Enter the averaging interval n or leave 1 if you do not want to smooth the velocity data. Start velocity - The velocity above which the subject is considered to be moving. Stop velocity - The velocity below which displacements of the subject's body points are no longer attributed to locomotion but to system noise, body wobble or pivoting on the spot. 4. Under Calculate nesting for, select Not moving. 5. Click OK. Insert the Nest box in the appropriate position between the Start and the Result box. 6. Choose the dependent variables and run analysis (see page 113). For more information on the Nesting functions, see Analyze Track Segments in the EthoVision XT Help. Analyze the intervals around the onset of the white light In this example, we want to analyze two intervals: From 5 seconds before the onset of the White light stimulus, to the onset of the stimulus. From the onset of the White light stimulus, to 5 seconds after the onset of the stimulus. The aim is to compare activity, speed and other parameters between the two intervals. 1. Choose Analysis > Data Profile > New. Give the new Data profile a a name and click OK. 2. In the Components pane, under Nesting, click the button next to Free interval. 3. Do the following: Under Start criterion, select Trial Control. Choose the options as in the picture below. Under Stop criterion, select Time. Next to Elapsed time leave 0:00:00.000 after start event selected. note "Start event" here refers to the White light selected under Interval start. Click OK and insert the Nest box in the sequence. 4. To create the second interval, choose first Result under Common elements. Click the middle of the Start box and drag to the Result 2 box; this will connect the two boxes. 5. Repeat the steps 2-3 to create a new Nest box, this time for the interval "from White light to 5-s after that". In the settings, choose the criteria for the second interval: from "Trial Control - 0 seconds before Action: Light on" to "Time - Elapsed time 5 seconds after start event". Click OK and insert the Nest box in the sequence. 6. Choose the dependent variables and run analysis (see page 113). tip Click Settings in the Result boxes and rename them, to for example "5-s Before white light" and "5-s after white light". Those names will be shown in your results. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 14 Analyze data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-14-analyze-data Chapter: DanioVision 14 Analyze Data Analysis Profiles And Options Analysis Profiles in the template experiment Distance, Time & Movement - Contains the dependent variables Distance moved, Velocity and Movement. Path Shape - Contains the dependent variables Heading, Turn angle, Angular velocity and Meander. Rotation - Contains two instances of the dependent variable Rotation, to count the number of clockwise and counterclockwise rotations. For more information on these and other dependent variables, see Dependent Variables in Detail in the EthoVision XT Help. Also see Analysis of Trial Control data in the Reference Manual - Trial and Hardware Control in EthoVision XT. Analyze intervals Make sure you have defined a Data profile which specifies the intervals you are interested in (see page 106). Next, in the Analysis profile choose your variables (e.g. Distance moved). Then visualize the data (see an example in Figure 15) and run analysis (see page 115). Activity analysis You can also use the dependent variable Activity state. This variable is only available when you selected Activity analysis in the Experiment Settings (see page 46 and page 66). With Activity state you can calculate how long and how frequent your subject has been in different activity states. These states depend on the total pixel change within the arena between a sample and the previous sample. It is important that all defined arenas have exactly the same size. The number of states (two to four) and their thresholds are user- defined. Analyze convulsions To analyze convulsions, you can use several variables, such as Velocity, Activity and Mobility. If you use Mobility, start with setting a High Mobility Threshold to a high value like 95%, and an averaging interval of 2. Compare the scores of Highly Mobile with those of convulsions obtained manually. Figure 15 Example of visualization of data after nesting over a Trial Control State. Here the samples of Arena 1 are displayed in full color when the white light was on. Only those samples are subject to analysis. The first plot is of the variable Trial Control State (defined as: From Light on to Light off; it illustrates the effect of nesting), and the second is of Distance moved defined in the Analysis profile. Calculate The Statistics The instructions below describe the general procedure of selecting a dependent variable and calculating statistics for that variable. 1. Choose Analysis > Analysis Profile. In the Analysis Profiles window, select New and type a name for the new profile, then click OK. 2. Click the Add button next to the dependent variable you want to use for analysis (for an overview, see Dependent Variables in Detail in the EthoVision XT Help). 3. In the window that appears, select the properties of the dependent variable. In the Trial Statistics tab, choose the statistics you want to calculate per trial for that variable. If you run multiple trials, select additional statistics in the Group Statistics tab. 4. Repeat steps 2-3 to add more dependent variables. 5. Choose Analysis > Results > Statistics & Charts. Choose the Data Profile from the list on the tool bar and click the Calculate button. 6. The results appears on the screen. The Trial Statistics tab shows the statistics per trial. The Group Statistics & Charts tab shows the statistics and charts from the summarized results of all trials. See Calculate Statistics in the EthoVision XT Help for how to read and customize your results. 7. optional Click the Layout button to modify the layout of the results table. Batch calculations It is also possible to carry out multiple analyses with different filters, data profiles and analysis profiles. To do so click the Batch button. Make your selection from the lists under Select the profile combinations to calculate and click Add. When done, click Calculate. To view a specific analysis result, select the options from the lists on the toolbar. For more information on batch statistics calculation, see Batch statistics calculation in the EthoVision XT Help. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 2 What’s new in DanioVision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-2-whats-new-in-daniovision Chapter: DanioVision 2 What's New In DanioVision Daniovision Observation Chamber For users of DanioVision DVOC-0040 The white light LED array has been improved. The White light can be set to higher intensity. For users of DanioVision DVOC-0030 The housing has been completely redesigned. You open the observation chamber by tilting the lid along the top side. This way you have easier access to the camera and opening/closing the lid produces less vibration. note The DanioVision Observation Chamber is designed to block light from the outside. However, it cannot be guaranteed that it is completely dark inside the Chamber. For experiments that require absolute darkness (like experiments with day-night rhythms), place the DVOC in a dark room. The housing is now larger to create more space for accessing the video camera or adding devices. For this purpose, the housing can be disassembled more easily than before. For the instructions see page 116. The basin has been redesigned. It has now a more flexible retainer that can hold a wider range of well plates. DanioVision can now work with ANSI, SBS compatible micro plates (L =127.76± 0.5 mm, W=85.48 ± 0.5 mm) with a maximum height of 27 mm, and with Petri dishes with a diameter up to 90 mm. To place small well plates and petri dishes, slide the bridge to a new position in such a way that the well plate/petri dish is in the middle of the camera view (left). For details see place well plates and petri dishes on page 37. The mechanism for moving the Fresnel lens located above the well plate has been improved. You can now move the lens all the way out of the camera view when you need to place containers higher than 27 mm. Communication between DanioVision and EthoVision XT has improved via a new version of the hardware interface software. See install ethovision xt on page 22. All four TTL lines TTL 1 to TTL 4 are available for communication with external devices. For connecting custom hardware, additional expansion connectors Expansion 1 and 2 are available. See Figure 3 on page 15. Figure 2 Positioning a well plate (left) and a petri dish (right). The White Light is now dimmable at very low intensity, without the need to operate the Low light switch located behind the camera. The DanioVision Tapping Device has been designed to provide DanioVision with a reliable device which evokes a startle response in zebrafish larvae. See The DanioVision Tapping Device on page 72. note The DanioVision Tapping Device is a separate add-on to the DanioVision system. For users of DanioVision DVOC-002x The DanioVision camera is now a Gigabit Ethernet (GigE) digital camera connected to the EthoVision XT computer through a 1-Gb Ethernet card. With a GigE camera, tracking can be done with a higher sample rate and higher resolution. The intensity of the infrared LED back-lighting has been increased. This results in a more even distribution of back-lighting over the well-plate and a higher contrast between animals and the background. Therefore, it is easier to configure the detection settings and detection is better. It is possible to use very low light levels for the DanioVision White Light in addition to the default, standard White Light levels. The standard White light levels range from ±20 to ±10000 lux. The low White light levels range from 0 to ±20 lux. The anti-condensation mechanism can now be easily switched on and off, or set to automatic. The anti-condensation mechanism prevents the lens from condensing during an experiment. Ethovision Xt Here the main additions relevant to DanioVision are listed. For a complete list of the new features, see the EthoVision XT Help "What's new" section. For users of EthoVision XT 15 Improved Subject Contour filter. In the Detection Settings, a second Erosion filter is added to the Subject Contour settings. This filter is added after the pre-existing Erosion and Dilation, and improves detection in some difficult situations. For more information, see Advanced detection settings: Subject contour in the EthoVision XT Help. Trial Control variable in the analysis. In the Analysis profile you can now select the Trial Control variables used in the Trial Control protocols. This way you can analyze or visualize its values just like the other dependent variables. You can also visualize a Trial Control variable in the Integrated Visualization for testing purposes. For example, to check that a variable gets the expected value at a specific time in the trial. note The Deep learning functionality in EthoVision XT 16 is not designed specifically to track fish larvae. In DanioVision experiments, always choose Contour-based as the body point detection technique. For users of EthoVision XT 14 Heatmaps are plotted together with a time scale. This helps you quantify the time that the subjects spend in specific locations. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 3 Set up DanioVision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-3-set-up-daniovision Chapter: DanioVision 3 Set Up DanioVision Connections The back panel of the DanioVision Observation Chamber contains the following connections (see Figure 3 below): 1. Expansion 1. You can optionally use this connector to set up to 4 TTL out lines, to control external devices. For details, see page 127. 2. Temp. Connector for the temperature sensor. Use this in combination with the DanioVision Temperature Control Unit (TCU). 3. Cable grommet. If you install additional hardware inside the observation chamber, puncture the rubber membrane to let the cables pass through. For example, to connect the sensor of a digital thermometer placed in the water basin to a digital display outside the DanioVision Observation Chamber. 4. Gigabit Ethernet (GigE) camera connector. Use this output to connect the DanioVision camera to the EthoVision XT computer. Figure 3 The back panel of the DanioVision Observation Chamber. See text for explanation. The label with the CE marking contains the product version. 5. Expansion 2. This is a RJ45 type, 8-pin feed through connection. You can use it to connect future internal add-on hardware to get external signals in the DanioVision Observation Chamber. 6. Connector for water flow (see page 18 for details). 7. TTL1 to TTL4. You can optionally use these TTL input/output connections to control external devices such as a sound or shock generator, or the DanioVision Temperature Control Unit. 8. USB port (type Standard-B) to connect the DanioVision Observation Chamber to the EthoVision XT computer. 9. Connection for the 24 V power supply. 10.Connectors for water flow (see page 18 for details). Connect Daniovision Make sure the DanioVision Observation Chamber is placed on a level surface! Power Connect the DanioVision Observation Chamber's 24 V socket (9 in Figure 3) to the power supply using the power cable and adaptor. Video Use the Ethernet cable with the large round connector to connect the digital video output of the DanioVision Observation Chamber (4 in Figure 3) to the Ethernet port labeled DanioVision camera on the EthoVision XT computer. The DanioVision camera must be connected to a 1-Gb Ethernet card. See page 23 for how to install this card on your computer. If you have purchased a PC from Noldus together with DanioVision, this card is already installed. Contact Noldus if you need a new Ethernet card for the DanioVision camera. White Light, Tapping Device, and other hardware Use the USB cable that comes with DanioVision to connect the USB port of the DanioVision Observation Chamber (8 in Figure 3) to a USB port on the EthoVision XT computer. Do this only if: You want to control the White Light or the Tapping Device in the DanioVision Observation Chamber during data acquisition in EthoVision XT. You have the DanioVision Temperature Control Unit and you want EthoVision XT to take action if the water temperature gets too low or too high. You want to control any custom hardware connected to the DanioVision Mini USB-IO box. Figure 4 Basic connections between the EthoVision XT computer and the DanioVision Observation Chamber. For controlling other devices like the Toplight Unit and the Temperature Control Unit, see the corresponding sections. Set Up A Water-flow System If you require a temperature-controlled water flow underneath the well plate, the Noldus DVTCU Temperature Control Unit is the preferred method. The back panel of the DanioVision Observation Chamber contains three connections for controlling the water flow (see Figure 6): a water inlet (marked in green), a water outlet (marked in yellow) and a water overflow (marked in red). Figure 5 The DanioVision DVTCU Temperature Control Unit. Figure 6 The back panel of the DanioVision Observation Chamber, with the numbers indicating the connections of the water-flow system: 1 - water inlet; 2 - water outlet; 3 - water overflow. Connect the DanioVision Observation Chamber to the DVTCU using the tubes that match the color of the connectors. Please see the Reference Manual - DanioVision Temperature Control Unit DV-TCU for the complete instructions. Suggested temperature For Danio larvae, the temperature of the water flowing through the system is usually 28 degrees Celsius. You can set a different temperature when needed. Figure 7 Tube connections between the DanioVision Observation Chamber and the DanioVision Temperature Control Unit. Color dots represents colors on the tubes. Arrows indicate the water circulation. Light And Switches Main switch The main switch is located on the front panel. After you switch on DanioVision, wait at least 15 minutes for it to 'start up' and to avoid condensation in the system. Internal LED light The DanioVision Observation Chamber is equipped with a LED light to illuminate the inside of the chamber while you set up your experiment. Operate the Light switch at the left of the camera to turn the light on and off. Anti-Moisture switch This switch is located at the right of the camera. Operate this switch to adjust the anti-condensation mechanism (page 35). Low light switch This switch is located on the Mini USB-IO box, behind the camera at the back of the observation chamber. When the switch is set to H (default), the standard light levels are activated, from ±20 to ±10000 lux. Set this switch to L to allow very low light intensities, from 0 to ±20 lux. For details, see page 36. Install Ethovision Xt If you have purchased the DanioVision Observation Chamber including a computer from Noldus Information Technology, all software has been installed and tested. You can skip this section. See Set up EthoVision XT on page 41 If you use your own computer (or a computer you bought from Noldus IT in the past; in that case, make sure it meets the EthoVision XT system requirements), see below. EthoVision XT 16 is supported with Windows 10 Pro, 64 bit. For more information about system requirements, press F1 in EthoVision XT. Mini USB-IO box drivers The Mini USB-IO box is the embedded electronics unit that communicates with EthoVision XT. The Mini USB-IO box makes it possible for EthoVision XT to control for example the white light stimulus. Before installing EthoVision XT, remove older versions of the drivers for the Mini USB-IO box. To do so: 1. In the Windows Control Panel select Programs and features. 2. Click each of the items whose name begins with Noldus_Hardware Interface.. and click Uninstall. 3. Insert the EthoVision XT Installation USB stick into your computer and follow the instructions to install EthoVision XT. When you install EthoVision XT, the drivers of the Noldus Mini USB-IO Box are automatically installed. important When you open an experiment from EthoVision XT 12 or lower, a warning appears, informing you that you cannot open upgraded experiments in the old version of the software anymore. Make a backup of your DanioVision experiment in the older version of EthoVision XT before opening it in EthoVision XT. To make a backup, choose File > Make Backup. important If you uninstalled the older version of EthoVision XT, you cannot use the Backup function. Instead, make a copy of your experiment using Windows Explorer before you open it in the newer EthoVision XT version. Always copy the complete experiment folder and not only the *.evxt file otherwise your experiment does not open. For more information See Installation in the EthoVision XT Help for instructions on how to install EthoVision XT. For more information on the Mini USB-IO box, see the Reference Manual - Trial and Hardware Control in EthoVision XT, which you can find on your EthoVision XT computer, under Noldus > EthoVision XT 16 Other Documentation. Install The Network Card For The Daniovision Camera DanioVision works with a Basler Gigabit Ethernet (GigE) video camera, connected via an Intel PRO/1000 CT 1-Gb Ethernet card installed on your computer. If you ordered a computer from Noldus Information Technology when you purchased DanioVision, it came with that Ethernet card. The card has already been installed and tested. In that case, skip the sections below and continue with Chapter 4 on page 32. If you bought your computer somewhere else, you will have to install the Ethernet card yourself. This involves a few steps (see below). Figure 8 The Intel PRO/1000 CT Ethernet card. Step 1. Insert the Ethernet card in the DanioVision computer - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's casing according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. When possible, choose the slot that gives maximum performance. To estimate performance, take note of the slot version (2, 3, etc.) and compare it with the following values: PCIe v1.x: 250 MB/s PCIe v2.x: 500 MB/s PCIe v3.0: ~1 GB/s PCIe v4.0: ~2GB/s PCIe v5.0: ~ 4GB/s Note that values are given per lane; they should not be multiplied by the number of lanes in a slot (e.g. x4) since the card has a 1x connector). For example, SLOT1-PCIe3x4 means version 3.0, with four lanes. important Do not insert the PCIe board in the blue or white slots. - Unpack the Ethernet card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet, and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Fix the card to the chassis and re-fit the computer's cover. For more information about installing the camera and the Ethernet board, see Camera Installation in the EthoVision XT Help. Step 2. Install the camera drivers - Insert the EthoVision XT installation USB stick into your computer. - Double-click EthoVision XT Setup.exe. If you have already installed EthoVision XT, select Modify. - Under Drivers and tools, select Basler GigE camera driver. - Continue with installation. Under Profile, select Camera User, then click Next. - Under Interfaces, select GigE, then click Next. - Connect the DanioVision camera to the port of the Ethernet card using a network cable (see D in Figure 3 on page 15). Step 3. Assign the IP address to the Ethernet card tip Watch the video tutorial Set Up the Camera. In EthoVision XT, choose Help > Video Tutorial. 1. In Windows (here version 10), search for Network Connections. 2. Right-click the Local Area Connection and click Properties. If your computer has more than one Local Area Connection, choose Basler GigE Vision Adapter. Write down the number of this connection. 3. Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. 4. Select the options: Use the following IP address and Use the following DNS server addresses and fill in the details as shown in the next figure. Also select the checkbox Validate settings upon exit. When done, click OK and then Close. Step 4. Set the IP address of the DanioVision camera tip Watch the video tutorial Set Up the Camera. In EthoVision XT, choose Help > Video Tutorial. 1. In Windows, search for IP Configurator and start this application. 2. Select the camera. 3. Fill in the details in the IP Address and Subnet Mask fields under Static IP Address as shown in the figure below. 4. Click Save and then Close. 5. Follow the instructions below to configure the DanioVision camera. Configure The Daniovision Camera Camera settings The DanioVision camera that you received is already configured according to your setup. Noldus created three main settings profiles, called User Sets, stored in the Pylon Viewer software which controls the camera: User Set 1, User Set 2 and User Set 3. Only one User Set can be active at a time. For each video resolution, you must use different camera settings and in some cases a different camera lens. For example, the video resolution determines the maximum frame rate. The higher the required resolution (in number of pixels), the lower the maximum frame rate (in frames per second). The three User Sets are specific for a combination of video resolution and frame rate (Table 1). Which User Set is currently selected? Make sure that EthoVision XT is closed. Start the Basler Pylon Viewer software and in the Features panel (for details, see the procedure in the next pages), under Configuration Sets, look for the item Default Startup Set. This is the User Set that contains the current settings. Always check that the settings in Pylon Viewer for a particular User Set correspond to those in the table! Note EthoVision XT reads the settings from the camera driver software. For a specific EthoVision XT experiment you can override the values of video resolution and frame rate values that are stored in the driver, not other settings; see page 45. The maximum frame rates have been measured with a 96 well plate setup. Other values may be optimal in other setups. 1 User Set 1 is the default User Set in most applications. User Set 2 is pre- selected if you purchased a 12-mm lens. User Set 3 is pre-selected if you purchased a 8-m lens. 2 For User Set 2, Binning mode must be Summing. For other User Sets either option has no effect with binning equal to 1. Table 1 Overview of predefined User Sets in the camera driver software and associated video frame rate, video size and required camera lens. Resolution and maximum frame rate 1280 x 960, 30 fps 640 x 480, 60 fps 800 x 600, 60 fps Camera lens 12 mm 12 mm 8 mm + 0.5 mm spacer ring Settings in Pylon Viewer User Set1 User Set 1 User Set 2 User Set 3 Pixel Format Mono 8 Mono 8 Mono 8 Analog Gain Center X and Center Y Horizontal binning, Vertical binning2 1, 1 2, 2 1, 1 Exposure TIme (Abs) in microseconds 3 4000 2000 4000 Settings in EthoVision XT Resolution 1280 x 960 640 x 480 800 x 600 Frame rate (fps) Color space Y800 Y800 Y800 3 For all User Sets: Enable Acquisition Frame Rate must be selected. Adjust the camera settings in EthoVision XT In EthoVision XT, choose Setup > Experiment Settings and click the camera button. Adjust the settings according to the table on the previous page. For details, see Adjust camera Settings in EthoVision XT in the EthoVision XT Help. Adjust the camera settings in Pylon Viewer You can also adjust the camera settings directly in the camera software Pylon Viewer. Adjust the settings according to the configuration you want to use in Table - First, choose a video resolution and frame rate combination, then mount the recommended camera lens, and next make the appropriate settings in Pylon Viewer. Finally, adjust the appropriate settings in EthoVision XT. For more information about Pylon Viewer, see the Configure the digital camera in the EthoVision XT Help. Pixel format (column B inTable 1). Analog gain (column C in Table 1). Center X and Center Y options (column D in Table 1). Horizontal and Vertical binning (column E in Table 1). Acquisition frame rate and Exposure time (column F in Table 1). tip To preview the camera image, click the Continuous Shot button on the toolbar. tip You can increase the Analog gain to 2 if you need a brighter camera image. However, the image noise will also increase, which may influence tracking. To save the settings, click the Stop button and open the Configuration Sets item. From the Configuration Set Selector list, select the User Set you want to save the settings to. Next to User Set Save, click Execute. Select the User Set you want to use at a daily basis. From the Default Startup Set list, select the User Set of your choice. Camera view Check that the camera view is correct by placing a wellplate in the DanioVision Observation Chamber. Make sure that: The well plate is in the middle of the field of view, not rotated or skewed. If not, see page 125. The well plate is in focus. If not, operate the focus ring of the camera lens. Fixation screws of all rings on the lens are tightened. The aperture is chosen such that the image appears slightly overexposed. With water in the well plate, the image is fine. When you create an EthoVision XT experiment, check that the video Resolution, Video frame rate and Color space are as in Table 1 (page 29) for the User Set you want to use. See the next chapter and also Fine camera adjustments on page 122. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 4 Check the DanioVision system URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-4-check-the-daniovision-system Chapter: DanioVision 4 Check The DanioVision System Before you start setting up EthoVision XT, you need to check the following: Camera The camera lens should have the correct aperture and must be in focus. See page 33 The camera is correctly configured. See page 28 Anti-condensation mechanism You need to do this depending on the temperature inside the DanioVision chamber and the desired water temperature around the well-plate. See page 35 White Light stimulus You need to do this when you want to use very low intensities for the DanioVision White Light. See page 36 Well plates and Petri dishes The well plate or Petri dish must be inserted correctly. See page 37 Always control evaporation in the basin and in the well plate, especially when you carry out long trials (> 1 day). See page 40 Check The Camera Lens Although the camera and lens are set up before shipment, the settings of the lens can shift during transport. Before you start to work with the DanioVision system, please check that the lens is set up correctly by doing the following: 1. The lens you use depends on the video resolution and frame rate you want to use. See the table on page 29. 2. Insert a well plate (o petri dish) in the basin. 3. Create a new EthoVision XT experiment (see create a daniovision experiment on page 41) and open the Arena Settings to see the camera image. When water is not present in the basin, the image of the well plate should look overexposed, like the following: 4. Check the focus (see Figure 9). If the camera image is not in focus, loosen the screw, adjust the focus and tighten the screw. The camera should be focused on the animals. The distance between animals and camera does not change much between types of well-plate and water level in the wells, however it is always a good idea to check the image before an experiment and adjust the focus until it is optimized. 5. Check the aperture (see Figure 9). The aperture has been adjusted in such a way that when the basin is filled with water, the video image is optimal for tracking (see example of a good video image on page 126). However, in the Detection Settings (page 64) check that detection of the larvae is good. If necessary, adjust the aperture to get a better contrast between larvae and background. 6. Make sure the camera is correctly configured (see page 28). Notes The more the aperture is closed, the larger the depth of field, which means that an object is 'sharp' at different distances from the lens. This is especially relevant when you work with a zoom lens and zoom in to focus on a smaller region of a well plate. On the other hand, closing the aperture decreases the contrast between animals and the background. Adjust the aperture until the image is optimized. Figure 9 The 12-mm standard camera lens (left) and the 8-mm camera lens (right). The 8-mm lens has a spacer ring (already installed if you purchased this lens from Noldus). See also Table 1 on page 29 for which camera settings apply to which lens. Configure The Anti-condensation Mechanism Anti-condensation switch The DanioVision Observation Chamber is equipped with an anti- condensation mechanism to prevent water droplets forming on the lens during an experiment. A temperature sensor inside the DanioVision Observation Chamber checks whether the anti- condensation mechanism should be switched on or off when it is set to Auto mode. Besides the Auto mode, you can also permanently switch the anti-condensation mechanism On or Off. The switch to set the anti- condensation mode is located behind the camera, at the right side. Auto Default and recommended when the DanioVision TCU is not used. The anti-condensation mechanism is automatically switched on when the air temperature inside the chamber drops below 28 °C (82.4 °F) to Figure 10 Position of the anti-condensation switch (labeled: Anti-Moisture) inside the DanioVision Observation Chamber. prevent condensation on the lens. When the air temperature inside the chamber exceeds 28 °C, the anti-condensation mechanism is automatically turned off to prevent heating of the water in the wells. The value of 28 °C is a default setting of the embedded controller. note If you use the DanioVision TCU, follow the instructions on the Reference Manual - DanioVision Temperature Control Unit DV-TCU, and set the switch to either On or Off. Off The anti-condensation mechanism is permanently turned off. Use this mode when the air temperature inside the chamber is equal to or higher than the actual water temperature of the basin/well plate water (in most cases 28 °C). You can use this option in combination with the DanioVision TCU. On The anti-condensation mechanism is permanently turned on. Use this mode when the air temperature inside the chamber is lower than the water temperature in the wells. You can use this option in combination with the DanioVision TCU. Configure The Daniovision White Light In the DanioVision Observation Chamber it is possible to use very low light levels for the DanioVision White Light in addition to the default, standard white light levels. The standard light levels range from ±20 lux to ±10000 lux. The low light levels range from 0 to ± 20 lux. Both standard and low light can be controlled in the same way by EthoVision XT's Trial and Hardware Control. 1. Locate the switch, behind the camera, at the bottom-left of the black mini USB-IO Box. 2. Set the intensity of the White light. Right position H, standard high light level. Left position L, low light level. Place Well Plates And Petri Dishes Well plates (ANSI standard) - Put the back of the well plate against the bridge and place it on the basin floor. - Tilt the front of the well plate down to the floor. This way the water in the basin pushes the air from underneath the well plate. Make sure the well plate is accommodated correctly between the metal springs at the front and at the right side. tip Drill a few holes on the sides of the well plate to allow air to escape when placing the well plate. Well plates (non-ANSI standard) For smaller or larger well plates, place the bridge in a different position. The default position (ANSI standard) corresponds to the second hole on the side walls of the basin, when counting from the inner side of the observation chamber. 1. Remove the screws as indicated in the picture. 2. Slide the bridge by one or more positions. Check the video image in EthoVision XT, and make sure that the well plate is centered in the camera view. 3. Fix the screws in the corresponding holes. Petri dishes - Put the Petri dish against the 90º angle of the bridge. - If necessary, remove the screws of the bridge (see above) and slide the bridge of a few positions until the dish is centered in the camera view. With DanioVision you can use Petri dish of diameter up to 90 mm. We recommend not to let water flow in the basin when using Petri dishes. Water may flow underneath the bottom of the dish, making it shift from its original position during a trial. Control Evaporation Wells on the sides of the well plate tend to show a higher rate of evaporation than wells in the center. Also, wells at the front have a higher evaporation rate than those at the back. Our recommendations In long experiments (> 24 h), evaporation may occur for both the wells in the plate and the basin. Wells: Check the wells every 24 hours and if necessary, refill them. Basin: Refill the basin every 2-3 days using the Basin Refill tool. For details, see the Reference Manual - Temperature Control Unit DV- TCU. The environmental conditions (temperature, relative humidity and air flow) and experimental conditions (lens heater on/off, White light intensity) influence the rate of evaporation (and condensation) of water from the basin and well plate. If you plan to carry out long experiments, always test evaporation at your environmental and experimental conditions, and plan refills to make sure that water drop never reaches a critical value. tip You can use a special syringe to refill the basin without having to open the DanioVision Observation Chamber. Contact Noldus for more information. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 5 Set up EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-5-set-up-ethovision-xt Chapter: DanioVision 5 Set Up EthoVision XT Prerequisites Before you can start working with the DanioVision system, you need to connect the DanioVision Observation Chamber to the EthoVision XT computer (see page 15) and, optionally, set up the water-flow system (see page 18). After you have turned on the DanioVision Observation Chamber with the switch on the front panel, wait at least 15 minutes for the DanioVision chamber to 'start up'. Also make sure to remove the lens cap from the camera. Assign treatments to wells To prevent systematic errors as a result of potential variation in temperature, light intensity or other unknown variable across a well- plate, it is recommended to either assign larvae from different treatments randomly to the wells or make sure that wells containing different treatments (that is, different solutions or different concentrations of the same solution) are evenly distributed across the well-plate (so, for example, one type of solution is not only put in the center wells). Create A Daniovision Experiment Preferred method With this method, All arenas are created automatically, but need to be manually adjusted, using the Arrange Arenas option. Unnecessary functionality like manual scoring is removed from the interface and detection settings are optimized for DanioVision. If you select a template which contains more arenas than needed, you can exclude the unused arenas with Data selection (see page 106). After you have followed the steps below to create the new experiment, you must still check/adjust Experiment Settings, Arena Settings and Detection Settings before you can track any animal correctly. 1. Do one of the following: In the EthoVision XT Startup window, under New experiment, click New from template. Choose File > New from Template. 2. In the Select a template option window, click Apply a pre-defined template. Next, follow the instructions in the guided setup as described below. 3. Which video source will you use? Select the option Live tracking (and saving video files), click the Sources button and select the Basler camera. Click Next >. 4. Which subjects will you track? Select Fish and then Zebrafish larvae from the list. Click Next >. 5. How is the arena configured? Select an Arena template from the list, then click Next >. DanioVision DVOC 004x, 24 round wells. DanioVision DVOC 004x, 48 round wells. DanioVision DVOC 004x, 48 square wells. DanioVision DVOC 004x, 96 round wells. DanioVision DVOC 004x, 96 round wells. **DanioVision DVOC 004x/T, 24 round wells. *** DanioVision DVOC 004x/T, 48 round wells. DanioVision DVOC 004x/T, 48 square wells. DanioVision DVOC 004x/T, 96 round wells. DanioVision DVOC 004x/T, 96 round wells. *) Select one of the options with /T when you have installed the DanioVision Tapping Device and you want to use it in this experiment. For details see page 72. tip To know which DVOC version you have, see the serial number on the label located on the back panel. Open field, round. Open field, square. Well plate, round wells - Select this option if you have a different number of round wells. Well plate, square wells - Select this option if you have a different number of square wells. note Arena templates are also present for older DanioVision DVOC versions: DanioVision DVOC 001x -003x. note If you selected a template for an older DanioVision version, it is possible that the DanioVision detection settings method does not give optimal detection of the larvae with images from your camera. If that is the case, use another detection method in the Advanced section of the Detection Settings pane. Consult the DanioVision manual that came with your setup, or see Configure Detection Settings in the EthoVision XT Help. 6. Initialize template experiment. Check here that all settings are correct and, if so, click Finish. 7. Enter the name of the experiment and click OK. The EthoVision XT Overview window opens. 8. Follow all the next steps: Experiment Settings. See page 45. Arena Settings. See page 49. Trial Control Settings. See page 57. Detection Settings. See page 64. Other ways to create a DanioVision experiment No matter which method you choose, when you create a DanioVision experiment unnecessary functionality like the Manual Scoring Settings is removed from the interface and detection settings are optimized for DanioVision. File > New from Template > Apply a custom template. Choose this method to create an experiment based on an existing one. For example when you want to replicate an experiment with the same number of arenas, the same trial control procedures, etc. For details, see Create a new experiment based on an existing experiment in the EthoVision XT Help. File > New and in the window that appears select the option DanioVision experiment. In the Experiment Settings, next to Number of Arenas enter the number of wells. With this option you have to draw the arenas manually. For more information on creating an experiment manually, see Set Up an Experiment in the EthoVision XT Help. Instead, we advise to create an experiment with a predefined template (first method), because all arenas are then defined automatically. Experiment Settings Choose Setup > Experiment Settings. Video Source - Under Video source, click the Video icon on the right side of the row of your camera. - In the Video Settings window that appears, click the Formats tab and select the Resolution and Frame rate. Default resolution is 1280 x 960 at 30 frames/s. If you create an experiment based on a template with the Tapping Device, set the frame rate to 60 fps and reduce the resolution according to your setup (see the table on page 29). See also the guidelines in columns G, H and I in Table 1 on page 29. From the Color space list, choose Y800. This is the color space for a monochrome video image. The other options, suitable for color images, do not apply to DanioVision. Tracked Features Specify whether you want to track the center point of the fish (default) or the center point, the nose point and the tail base. Choose the latter option only if you track fish in a close-up image. Body Point Detection Technique The Contour-based technique is selected. The option Deep learning is not available for fish tracking. Analysis Options If you are interested in how long and how frequent your subjects have been active vs. inactive, under Analysis Options select Activity analysis. Make sure you also adjust the Activity settings in the Detection Settings (see page 66). For more information about setting up an experiment, see Set Up an Experiment in the EthoVision XT Help. Use Of Trial Control Hardware Follow this section if you use stimulus devices like the white/color lights and the tapping stimulus device. 1. In the Experiment Settings, under Trial Control Hardware, make sure that Use of Trial Control hardware is selected and click the Settings button. 2. In the Hardware Interface window that opens, choose the type of system you have. If you have DanioVision DVOC-0041: Choose DanioVision DVOC-004x/T if you use the Tapping Device in this experiment. In all other cases choose DanioVision DVOC-004x. The other options DanioVision DVOC-001x - 003x are meant for older versions of the DanioVision Observation Chamber. note The option Mini USB-IO Box only applies when you use a Mini USB-IO box instead of DanioVision DVOC. 3. In the Device Configuration window, under Device features, the hardware devices activated for this experiment are listed. 4. optional The default status of the DanioVision White Light Stimulus if Light off. This means that, when you start a trial, the white light is switched off. To use the white light as a stimulus, program its activation with Trial Control. If, however, you want to use the white light as a default lighting condition, and use the darkness as a stimulus, do the following: Click the White Light Default button. b Under Default device state, select Light on. Choose a percentage of intensity (0-100) and click OK. Then in the Trial Control procedure you can program when to switch the light off. See Trial Control Settings on page 57. 5. optional If you connect additional hardware, under Plug-in devices, select the devices in the corresponding rows for TTL Port 1-4, or Expansion 1 / Port 1-4 depending on which port on the DanioVision back panel you use. 6. Click OK. 7. optional If you set the default state of the White Light Stimulus to Light on, open the Trial Control Settings. This will confirm your selection. Notes The Tapping Stimulus is listed under Device features when you select DanioVision DVOC-004x/T in step 2. If you upgraded from an older version of EthoVision XT, and you use an experiment created in the older version as a template for a new one, the DanioVision detection method is not available. Therefore, we recommend to create a new experiment with the newest version, and use this as a template (File > New From Template > Use a custom template). If you upgraded an experiment from an older EthoVision XT version, do not change the Trial Control Hardware Settings in the Experiment Settings. Leave Noldus Mini USB-IO Box selected in the Hardware Interface window. Otherwise the Trial Control rules, for example to control the white light, may not work. When you change the default state of the White Light Stimulus to Light on, note that the white light is only switched on in one of the following cases: When you open the Trial Control screen. When you open the Arena - Hardware Mapping window. When you start a trial. For more information on Trial and Hardware Control, see the Reference Manual - Trial and Hardware Control in EthoVision XT. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 6 Arena Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-6-arena-settings Chapter: DanioVision 6 Arena Settings Define The Arenas Choose Setup > Arena Settings > Arena Settings 1. To define the arenas automatically Follow these instructions if your experiment was created for well plates with 6, 12, 24, 48 or 96 round wells, or 96 square wells, and this is the first new Arena Settings in your experiment. In other cases, go to To define the arenas manually on page 52. tip Use well plates with no notches between wells. These result in better well detection. Also make sure that the borders of all wells are within the camera image. 1. In the Grab Background Image window, click the Grab button to grab a background image of an empty well-plate from the camera image. 2. If EthoVision XT can detect the wells, the outline of the arenas are displayed over the background image. A message appears asking whether the arenas overlap with the wells in the image. 3. Do one of the following: If there is good overlap like in the picture below, click Yes. If needed, you can always make small adjustments using the Arrange Arenas function (see page 53). If the arenas clearly do not overlap with the wells, or arenas overlap with each other, click No. The Arrange Arenas window appears automatically. See arrange the arenas on page 53 for details. 4. Click the 1. Draw Scale to Calibrate button. Draw a line over the entire well-plate. Next, enter its size. Do this horizontally as well as vertically. 5. Click Validate Setup to validate the Arena Settings. Common errors are overlapping arenas, or zones falling outside an arena. If the setup is valid, continue with the instructions below. Notes Arenas are marked with labels A1, A2, ..., B1, B2, ... according to your well plate (letters indicate rows; numbers indicate columns) Automatic detection of the wells in the video image has been tested with the DVOC-0040 and DVOC-0041. Success of automatic detection much depends on image contrast, focus, and distortion, and therefore we cannot guarantee it will work in all situations and with video made with previous DanioVision versions. Automatic detection also does not work if water is not present in the well plate. If automatic detection of the wells does not work, it could be due to the well plate being not centered in the video image. See Fine camera adjustments on page 122. When the well plate image is optimal and centered, and still EthoVision XT shows the message Well plate detection failed, click OK and proceed with To define the arenas manually on page 52. To start automatic well plate detection, click the Well plate detection button at the bottom of the Arenas and Zones section of the Arena Settings pane. To define the arenas manually The following instructions apply when the automatic well plate detection does not work properly. In that case you must define one arena and then make duplicates. If you used a predefined template to set up your experiments, go to arrange the arenas on page 53. 1. Click the 1. Draw Scale to Calibrate button, draw a line over the entire well-plate and enter its size. Do this horizontally as well as vertically. 2. If the current arenas are of shape different from that of the wells, select all arenas and press Delete. 3. Click 2. Select Shape and Draw Arena and use one of the shapes to create the first, top-left, arena. Make sure the label of the first arena (for example A1) points to the inside of the drawn arena. 4. Click the outline of the arena or its label and then click the 4. Copy Arena button. In the window that appears select All other arenas. Select the number of rows and click OK. 5. Make sure the predefined arenas cover the wells. If you need to adjust the arena size and position, see arrange the arenas on page 53. Arrange The Arenas - in the Arena Settings window, click the 5. Arrange Arenas button. In the Arrange Arenas window, do the following: - To move all arenas: Under 1. Move Grid To move up/down: Click the first slider. Move it the right (to move the arenas down) or left (to the arenas move up). To move to the right/left: Click the second slider. Move it the right (to move arenas to the right) or left (to move them to the left). You can also click the up/down arrow buttons of the corresponding box or enter a number in the box. - To scale all arenas: Under 2. Scale Arenas Resize all shapes by using the sliders, by pressing the up/down arrows of the corresponding box or by entering a number in a box. To increase the height of all arenas, use the first slider. To increase the width of all arenas, use the second slider By default the option Keep proportions is not selected. Then you can resize the height and width of all shapes separately. If you select Keep proportions, you can change either the height, or the width while keeping the aspect ratio. 4. To rotate all arenas: Under 3. Rotate Grid Optionally, rotate all shapes. This is only necessary if the well-plate is not positioned straight. The shapes rotate around the center of gravity of Arena 1. 5. To change the space between arenas: Under 4. Arena Spacing Change the space between the shapes. By default, the option Keep proportions is not selected. Then you can change the space between the shapes separately in the vertical and horizontal direction (relative to the first row and first column, respectively). If you select Keep proportions, change the spacing in either the horizontal or vertical direction while keeping the aspect ratio. tip First position the upper left arena in the desired position and make desired size (use scale). Next adjust arena spacing so all arenas are correctly positioned. See Using the Multiple Arena Setup in the EthoVision XT Help for information on setting up multiple arenas. 6. Click Validate Setup to validate the Arena Settings. Common errors are overlapping arenas, or zones falling outside an arena. If the setup is valid, continue with the instructions below. To edit a single arena Click the row in the Arena Settings pane for that arena. The corresponding arena is highlighted. For details on editing shapes, in the EthoVision XT Help see Arena Settings > Work with shapes. Assign The Stimuli To The Arenas Follow this procedure if you want to apply stimuli during a trial, for example a light pulse or a tapping stimulus. important If you created an experiment with a pre-defined template and selected the correct DanioVision arena template, the White Light, or Tapping Stimulus has been assigned automatically to the arenas. The steps below are then not necessary. 1. At the bottom of the Arena Settings pane, click the Arena - Hardware Mapping button. 2. In the Arena - Hardware Mapping window, do one or both depending on what you want to use: Click Add device. Under Arena 1, select White Light Stimulus. Click Add device. Under Arena 1, select Tapping Stimulus. The devices White Light Stimulus and Tapping Stimulus only need to be assigned to Arena 1. They are in fact applied to all arenas. 3. Click OK. For more information See also Test the hardware devices in the Reference Manual - Trial and Hardware Control in EthoVision XT. To set up the Tapping Device, see also The DanioVision Tapping Device on page 72. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 7 Trial Control Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-7-trial-control-settings Chapter: DanioVision 7 Trial Control Settings Choose Setup > Trial Control Settings > Default or White Light Routine. The template experiment contains two examples of trial control settings: Default - The default Trial Control Start-Stop rule. Use these settings to start and stop tracking manually. White Light routine. Use these settings when you want to provide a light stimulus during the trial. Ten minutes after the start of the trial, the DanioVision white light immediately turns on to 100% intensity for 10 minutes, then the white light immediately turns off for 10 minutes. This sequence of actions is repeated twice, using a sub-rule, after which the trial stops. For using the White Light, see below. For using the Tapping Device, see page 72. Maximum trial duration (recommended) If you record video: 60 minutes. Without recording video: 72 hours. Set the duration of your trials in the Maximum Trial Duration pane or in the Start-Stop trial rule, by placing a Time condition immediately before the Stop track action box. Create Your Own Trial Control Procedure You can adjust these trial control settings to your own needs. The procedure below describes how to define Trial Control Settings from scratch. For more information on Trial Control Settings: Trial Control in the EthoVision XT Help. The Reference Manual - Trial and Hardware Control in EthoVision XT, which you can find under Noldus > EthoVision XT 16 Other Documentation. With the Trial Control Settings you can control the DanioVision White Light. Example: After a 24-hour dark period in the DanioVision Observation Chamber, you want to expose your animals to alternating periods with the white light on and off, in which the light-on periods also vary in intensity. This schedule is shown in the figure below. To program this schedule: 1. To open the Trial Control, in the Experiment Explorer, right-click Trial Control Settings, select New, enter a name and click OK. The Trial Control screen opens with the default Start-Stop trial control rule. 2. Click the Condition Time box with "Infinite time" and press Delete. 3. In the Components pane, under Actions - Hardware, click the button in the Add column next to White Light Stimulus. Select Create a new action. 4. In the Hardware Action window, set the following: Action name. Enter a description of the action, for example "Light on 100%". Action to perform. Select Light on from the list. Intensity level. Select the maximum intensity level of the light, in percentage (0 - 100%) or in Steps (0-4096). See some reference values on page 131. Fade duration. For example, with Intensity level of 50% and a Fade duration of 2 seconds, the white light gradually turns on until 50% of its maximum intensity in 2 seconds time. 5. Click OK and insert the Action box in the sequence. 6. In the Components pane, under Conditions, click the button next to Time. Click Create a new action and click OK. In the Time condition window, you can set the following: Condition name. For example, enter 'Wait 15 mins'. Condition is met. For the option After a time of, enter '15 mins'. 7. Click OK and insert the Condition box in the sequence. 8. Repeat steps 3-6 to complete the Trial Control rule example described on page 59: Add an Hardware Action box with White Light - Off and a Condition Time box with "After 10 mins". Figure 11 This combination of Action and Condition box turns the White Light on at 100% intensity and keeps it on for 15 minutes. Add an Hardware Action box with White Light - On 50% and a Condition Time box with "After 10 mins". Add an Hardware Action box with White Light - Off and a Condition Time box with "After 10 mins". Add an Hardware Action box with White Light - On 100% and a Condition Time box with "After 15 mins". tip Combinations of Action and Condition boxes that are repeated in a sequence can be replaced with a sub-rule. This is especially handy when the entire sequence is repeated multiple times during a trial. For example: [White Light - On - 100%] > [After 10 min] > [White Light - Off] > [After 10 min]... For more information on using sub-rules, see also the Reference Manual - Trial and Hardware Control in EthoVision XT. 9. Insert all the boxes in the correct order into the sequence and make sure you connect all boxes (see Figure 12 and Figure 13 on the next page for an example). Figure 12 Example of Trial Control Settings. This is the first half of the Start-Stop Trial rule. In this example of Trial Control Settings, the repeated combination of Action box 'Light off - 0' and Condition box 'Wait 10 mins' to turn the White Light off for 10 minutes, has been replaced by a Sub-rule (see also the Figure on the previous page). Notes Click Test in the Hardware Action window to test the hardware action. Click Reset to reset all Hardware Action windows in your Trial Control procedure to their default values (for example a White Light action is set to off; however if you set the default White light to on (page 47), then after clicking Reset the White light switches on. To analyze data in the light or dark period, create first a Data profile that specifies that period using Trial Control State (see page 107). Then, calculate the statistics. Use an external command If you want to use an external command, for instance to play a sound during the trial, the command is executed for each arena. For example, the command to play the sound is repeated 96 times for a 96 arena experiment. To prevent this from happening, put a condition before the External command box, which will only become true for one of the arenas, for example Arena 1. In the Arena Settings, create a zone in Figure 13 Continued from Figure 12. This is the second half of the Start-Stop Trial rule. The Sub-rule is called a second time by the Reference box Light off (2). Arena 1 and call it "Zone 1A". Make the zone as large as the arena. In the Trial Control Settings, make a condition like "Is subject in Zone A?", followed by the external command. Make sure that the sequence does not interfere with the rest of the Trial Control rule, like in the following example. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 8 Detection Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-8-detection-settings Chapter: DanioVision 8 Detection Settings What do you want to do? Track one subject per well/enclosure. See below. Track two or more subjects in the same enclosure. See page 67. Use Activity. See page 66. One Subject Per Enclosure Choose Setup > Detection Settings > Detection Settings 1. The template experiment contains a Detection Settings profile with DanioVision selected as method. important If you have upgraded EthoVision XT to version 15 while you have a DanioVision system older than the DVOC-0040, it is possible that the DanioVision detection settings method does not give optimal detection of the larvae with images from your camera. If that is the case, use another detection method in the Advanced section of the Detection Settings pane. For details, see the EthoVision XT Help. 1. Click the Auto-detect button. important Use the Auto-detect button every time you change a well-plate. 2. The Auto-detect window with a timer appears. Wait until it has disappeared. All larvae should now be detected well. If not, do one or more of the following: Open the Advanced section and move the Sensitivity slider. Moving the slider to the left results in detecting more of the body of the larvae, but also more noise. Moving the slider to the right results in detecting less noise, but also gives less good detection of the larvae. If you see erratic tracks like that in the picture below (right), it means that small groups of pixels at the border of the well are sometimes detected as the larva. Move the Sensitivity slider to the right. If some larvae are not detected while they are in the corner or border of a well, check that the arenas are drawn well. Click the Show/Hide button on the toolbar and select Arena Features and then select the check box in front of Arenas. Check that the arenas cover the entire wells. In the picture below, the arena on the right does not cover the left margin of the well. Theref0re, the larva is not detected when swimming in that region. Try to maximize the contrast by opening the aperture of the camera lens (See "check the camera lens" on page 33.) However, make sure the light intensity is equal for all wells (that is, the center and outer wells). Certain compounds dissolved in the water can affect the pigmentation in the larvae, thereby decreasing the contrast of the animal and making detection of the animal more difficult. Make sure that EthoVision XT can still detect all animals after treatment. 3. If detection remains unsatisfactory, adjust the Advanced Detection Settings. The Dynamic subtraction method may give better results. For an explanation of the options, see Configure Detection Settings in the EthoVision XT Help. Activity Analysis Use Activity to quantify overall activity of your subjects. In the Experiment Settings (see page 46) select Activity analysis. In the Detection Settings pane, open the Activity section. Activity is shown by purple pixels in the video window. Set the Activity threshold in such a way that movements of the animals are detected and some noise is left. For more information on activity, see Activity settings in the EthoVision XT Help. Also watch the video tutorial on Activity analysis. For more general information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Multiple Subjects In The Same Enclosure Prerequisites: in the Experiment Settings, Number of Subjects is set to 2 or higher. 1. Choose Setup > Detection Settings > Detection Settings 1. 2. Click Automated Setup and draw a rectangle around each subject. 3. Under Method, select Advanced Model / Adult Fish or Advanced Model / Other if the first does not give the expected results when tracking fish larvae. note The Advanced Model /Other method is not based on a modeled fish shape. With this method you cannot track the fish snout and tail. It is only available if the experiment is set to Center- point detection only. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - 9 Acquire data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-9-acquire-data Chapter: DanioVision 9 Acquire Data There are three ways of acquiring data with your DanioVision system. For every option it is possible run single trials, but it is also possible to carry out batch acquisition. acquire data live (page 69). The larvae are tracked as they move in their wells. acquire data live and record video simultaneously (page 70). The larvae are tracked as they move in their wells while at the same time a video is recorded. This gives you to opportunity to redo the tracking if necessary, either per trial or using batch acquisition. record video, then acquire data (page 71). You record a video first and then track the subjects offline from the video. Please note that if you only record video with EthoVision XT, Trial Control is not applied. So, for example, the white light is not switched on and off, if you only record video. Before you start acquiring data, make sure you have carried out all the necessary checks of the system (see page 32). Notes The DanioVision Observation Chamber is designed to block light from the outside. However, it cannot be guaranteed that it is completely dark inside the chamber. For experiments that require absolute darkness, place the DVOC in a dark room. important In long experiments, evaporation may occur for both the wells in the plate and the basin. Check the wells every 24 hours and if necessary, refill them. Refill the basin every 2-3 days using the Basin Refill tool. For details, see the Reference Manual - DanioVision Temperature Control Unit DV-TCU. Please read the section in the next pages that applies to your setup. For more information, see Acquire Data in the EthoVision XT Help. Acquire Data Live - Make sure the camera is connected to the EthoVision XT computer and that Live tracking is selected as Video Source in the Experiment Settings. 2. Optionally, plan your trials in the Trial list and select the Arena settings, Detection settings and Trial control settings for each trial. 3. Choose Acquisition > Open Acquisition. 4. If no trials are planned, click the New trial button in the Playback Control window or press Ctrl+F3. 5. In the Acquisition Settings pane, select whether you want to track only the next planned trial or whether you want to track all planned trials without having to start the next trial manually. If you want to track all planned trials, specify the inter-trial interval. Enter a time long enough to be able to change well plates. When you change the well plate between trials, you can start the next trial without waiting that the inter-trial interval is reached. To do this, click the Skip remaining interval button in the Playback Control window. 6. Select whether you automatically want to start the analysis after the tracks are acquired. If that is the case, first define your dependent variables in an Analysis Profile (see Analyze data on page 113). Optionally, first make a Track Smoothing profile and a Data profile to make a selection out of your data. 7. Select whether you want to use the Track smoothing profile, Data profile, and Analysis profile that are highlighted in blue in the Experiment Explorer for analysis, or that you want to run analyses for all possible profile combinations. In the latter case, first delete all profiles you do not need for analysis. If you want to carry out analyses for only a selection of profiles, deselect the check box Auto- start analysis and carry out batch analysis after acquisition (see step 5 on page 115). 8. Put the well-plate into the DanioVision chamber. 9. Click the Auto-detect button. A Re-initialize window with a timer appears. Wait until it disappears. important Use the Auto-detect button every time you change a well-plate. 10.To start the trial, click the Start trial button in the Playback Control window (or press Ctrl+F5). 11. To stop the trials, wait until Trial Control automatically stops the trials. To stop acquisition manually click the Stop trial button in the Playback Control window (or press Ctrl+F6). If you stop the trials manually, automatic analysis does not start. Also, for batch analysis, the next trials are not started if you stop a trial manually. note The recommended maximum trial duration when acquiring live without recording video is 72 hours (3 days). Acquire Data Live And Record Video Simultaneously To save video when doing tracking, follow the procedure above, with the difference that in step 4 you select the check box Save video in the Acquisition Settings pane. If you realize tracking was not optimal, you can re-do tracking from the acquired video. note The recommended maximum trial duration when acquiring live and recording video simultaneously is 60 minutes. Longer trials produce video files of excessive size, more difficult to manage. Furthermore, if one large video gets corrupted then you lose more data. Record Video, Then Acquire Data If you use the option Save video only, track later, Trial Control is not applied so you cannot control the white light of the DanioVision Chamber with EthoVision XT. To save video when doing tracking, follow the procedure on page 69, with the difference that in step 4 you select Save video only, track later in the Acquisition Settings pane. Also make sure that the trial is time limited, either with a time condition in the Trial Control start-stop rule, or with a Maximum Trial duration setting (page 58). Next, you can acquire data using batch acquisition. Plan your trials in the Trial list and specify the video and optionally Arena Settings, Trial Control Settings and Detection Settings for each trial. note The recommended maximum trial duration when recording video is 60 minutes. Longer video recordings produce files of excessive size, more difficult to manage. Furthermore, if one large video gets corrupted then you lose more data. Drain And Clean The System At the end of the experiment, we recommend to remove all the water from the basin and the tubes. If you use the Temperature Control Unit, DV-TCU, set it to Fill/Drain and follow the instructions in the manual Reference Manual - DanioVision Temperature Control Unit DV-TCU.pdf. To prevent the growth of algae in the system: Always drain the system after use. Do not expose the system and the tubes to sunlight. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - A Open the DanioVision casing URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-a-open-the-daniovision-casing Chapter: DanioVision A - Open the DanioVision casing Open The DanioVision Casing Tools You Need A Phillips or (preferably) a Pozidrive screwdriver, size 2. Do not use electric screwdrivers! Bench Plate Remove the bench plate, for example, to install the Tapping Device and other, custom hardware you want to place inside the DanioVision Observation Chamber. Also when opening the top casing (page 117) it is handy to first remove the bench plate. 1. Remove the four screws as indicated in the picture below. 2. Remove the bench plate. A - Open the DanioVision casing Top Casing Remove the top casing, for example, when you need to replace the camera. 1. optional Remove the bench plate first (page 116), this makes the following steps easier. 2. Remove the eight screws as indicated in the picture below. Note that the screws located more internally are shorter than the others. These are attached to the aluminium frame. A - Open the DanioVision casing 3. Close the lid and lift the top casing. 4. When putting the top casing back in place, make sure that you insert the sides into the bottom casing as indicated in the picture below. Then, tighten all the screws. A - Open the DanioVision casing Sides And Back Casing Remove the sides and back casing to access the connector box, wirings and internal tubings. In most cases you do not need to do so. 1. Follow the instructions on page 117 to remove the top casing. 2. Put the DanioVision Observation Chamber just over at the edge of the table and remove the three screws from the bottom plate. Repeat this step for the other side. A - Open the DanioVision casing 3. Remove the two screws at the back as indicated in the picture below. 4. You can now lift the casing. A - Open the DanioVision casing Connector Panel To remove the connector panel at the back of the observation chamber, remove the four screws as indicated in the picture below. Adjusting Lid Friction You can adjust the friction of the Observation chamber lid. If the lid falls down easily or opens with much friction, it can be adjusted by loosening or tightening the three screws per hinge. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - B Fine camera adjustments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-b-fine-camera-adjustments Chapter: DanioVision B - Fine camera adjustments Fine Camera Adjustments Each DanioVision system is thoroughly checked and set to its optimal configuration. However, transport and handling of the system may sometimes cause slight changes in the camera position relative to the well plate, resulting in a sub-optimal video image. This section helps you restore the original settings. To open the DanioVision casing, see page 116. Centering The Well Plate Horizontally If the well plate is not centered horizontally: 1. Loosen the washer located behind the camera bracket, under the camera profile. B - Fine camera adjustments 2. Turn the camera in the direction required until the well plate is in the middle of the camera view. 3. Tighten the washer to fix the camera in the new position. Centering The Well Plate Vertically If the camera is rotated forward or backward in its vertical plane, the video image may look like this: 1. Loosen the two bolts at the sides of the camera profile. B - Fine camera adjustments 2. Rotate the camera bracket forward or backward until the well plate is centered vertically in the video image. 3. Tighten the bolts. B - Fine camera adjustments If The Well Plate Looks Rotated If the margin of the well parallel is not parallel to the margin of the video image: 1. Open the DanioVision Observation Chamber and locate one of the bolts at the side of the camera profile (either left or right): 2. Loose the bolt using a 3-mm Allen key. 3. Gently move the camera bracket forward or backward until the well plate is in the correct orientation. When ready, tighten the bolt. B - Fine camera adjustments Example Of A Good Video Image Check that the well plate fills the video image as much as possible, with the letters A-H and numbers 1-8 well visible. Set the camera lens to maximum aperture. The image is overexposed when no water is present. Below an example of a good video image when water is present: Tighten the three screws on the camera lens once the image is optimized. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - C Additional hardware URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-c-additional-hardware Chapter: DanioVision C - Additional hardware Additional Hardware DanioVision offers additional connectors to attach and control custom hardware. These are Expansion 1 and Expansion 2 located on the back panel. Expansion 1 Expansion 1 is a female 25-pin DB connector. It provides four additional TTL out lines to control external hardware and input/output lines to trigger the DanioVision camera (for example at a specific event). Numbers in black indicate pins currently available. Pin number Description TTL-out port 1 TTL-out port 2 TTL-out port 3 C - Additional hardware TTL-out ports are open collector outputs with a common emitter on pin 9 and 10. Voltage range 0 to 5 V. Specify the custom hardware in the corresponding row of the Device Configuration window. For details, see experiment settings. For more technical details and how to use these connections, contact Noldus Information Technology. TTL-out port 4 5 - 8 Not available Common emitter for TTL-out ports Common emitter for TTL-out ports I/O output camera 12-21 Not available GND I/O camera I/O input camera 24-25 Not available C - Additional hardware Expansion 2 Expansion 2 is a 8-pin modular RJ45 feed through connector. You can use it to connect internal add-on hardware and get external signals in the DanioVision Observation Chamber. Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - D System specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-d-system-specifications Chapter: DanioVision D - System specifications System Specifications Daniovision Dvoc-0041 Power supply Power requirements: 24 Volt DC, 2.0Amp (max) Mains adapter: input 100-240 Volt AC, output 24 Volt DC, 3.0Amp Camera Brand, type: Basler acA1300-60gm Interface: Gigabit Ethernet (RJ45 connector, CAT5e or higher) Sensor: 1/1.8" Progressive Scan CMOS, monochrome Max. resolution: 1280 x 1024 Max. frame rate: 60 fps Lens 12 mm Megapixel, C-mount, F1.4, includes IR pass filter Optional lens: 8 mm Megapixel, C-mount, F1.4, includes IR pass filter Video performance (H x V pixels) Default: 1280 x 960 at 30 fps (in combination with 12 mm lens) Optional: 640 x 480 at 60 fps (in combination with 12 mm lens) 800 x 600 at 60 fps (in combination with 8 mm lens) Maximum frame rates as measured in 96 well plate setup. Backlight unit Combined infrared (IR) and white light array Infrared wavelength (typical): 950 nm D - System specifications According to published research, zebrafish are sensitive to infrared light, though not above 910 nm. See Shcherbakov et al. 2013, PLoS ONE 8(5): e64429. The IR light provided by DanioVision is therefore unlikely to affect the fish's behavior. White light color temperature (typical): 5500ºK White light level controllable via USB (EthoVision XT). Intensity range: 0 to ±10000 lux (light level measured directly at the bottom of the water basin). With the standard White Light settings, the light intensities of the white light are approximately: note If you set the Low Light switch to L (low), the highest light level (100%) is around 20 lux. See configure the daniovision white light on page 36 for more information. note Light intensity in DVOC-0041 can be set higher than in DVOC- - Here the reference values if you have DVOC-0040: You may want to replicate light conditions that you set in DanioVision DVOC-0040 in a new experiment with DanioVision DVOC-0041. For example, if you set light intensity to 50% in Percentage Steps Intensity (lux) 1000 2500 2100 5300 3000 8000 4095 10500 Percentage Steps Intensity (lux) 1% 25% 1025 1450 50% 2050 2950 75% 3000 4400 100% 4096 5450 D - System specifications DanioVision DVOC-0040, this gave 2950 lux. The percentage to be set in DanioVision DVOC-0041 is (2950/5300)*50 = approx. 28%. Multi basin Water inlet, water outlet and overflow Basin size 158 x 132 mm Supports ANSI, SBS compatible micro plates (L =127.76± 0.5 mm (5 1/32" ± 1/64"), W=85.48 ± 0.5 mm (3 23/64" ± 1/64") with maximum height of 27mm (1 1/16") Supports Petri dishes up to 90 mm in diameter Temperature sensor supporting the use of Noldus DVTCU (Temperature Control Unit) Water connections Water inlet/outlet: tube fitting 8 mm Water overflow: tube fitting 10 mm Tubes included 1.5 m Clear PVC Hose, 8 mm OD, 5 mm ID for water inlet (green color marked) 1.5 m Clear PVC Hose, 8 mm OD, 5 mm ID for water outlet (yellow color marked) 1.5 m Clear PVC Hose, 10 mm OD, 8 mm ID for water overflow (red color marked) PC interface USB-2 compatible External I/O TTL input/output (4x modular RJ45 connector): 4 x 2 TTL input 4 x 2 TTL output D - System specifications TTL expansion port 1: 4 x TTL output (open collector output) 1 x input camera 1 x output camera TTL expansion port 2 (1x modular RJ45 connector: System start-up time (cold start) ~ 15 minutes Dimensions 61 x 32 x 46 cm (24 1/64" x 12 19/32" x 18 7/64") (h x w x d) in closed position Door opening 36 x 29 cm (14 11/64" x 11 27/64") (h x w) Weight 15 kg excluding power supply, external tubes and cables Cleaning the DanioVision Observation Chamber We recommend to use a propriety glass-cleaning fluid to clean the outside of the DanioVision Observation Chamber. Declaration of conformity See page 136. D - System specifications Daniovision Tapping Device Power Power requirements: 24 Volt DC, 0.4Amp (max) Features Controlled from EthoVision XT 10.1 or later with selectable stimulus intensity (1-8) Delivers a discrete 'tap' to the well plate holder Maximum tapping rate of ±3 taps per second Connectors Molex 2 pin - Power (24V) Molex 4 pin - From Tapping Device to control box Multi connector (blue) - For TTL control signal Dimensions Tapping Device (including aluminum bracket): 6 x 24 x 7.5 cm (2 23/64" x 9 29/64" x 2 61/64") (h x w x d) Control box: 2.5 x 10 x 6.5 cm (63/64" x 3 15/16" x 2 9/16") (h x w x d) Weight ~ 300g (Tapping Device, bracket, control box) If not pre-assembled in the DVOC-0041, the package includes mounting material Compatible DanioVision Chambers DVOC-0040, DVOC-0041 D - System specifications Daniovision Toplight Unit White light 30.000 lux at 25cm distance (well plate), 1584 lm Color temperature 4000K Array of 408 LED's Max. voltage 18 Volt Red light 192 lm, wavelength 623 nm Array of 252 RGB LED's Max. voltage 24 Volt Green light 384 lm, wavelength 525 nm Array of 252 RGB LED's Max. voltage 24 Volt Blue light 240 lm, wavelength 470 nm Array of 252 RGB LED's Max. voltage 24 Volt Unit Dimensions 270 x 220 x 30mm (10 5/8" x 8 21/32" x 1 3/16") D - System specifications Declaration Of Conformity D - System specifications Source: Reference Manual - DanioVision DVOC-0041 --- ## DanioVision - DVTCU Basin Refill Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvtcu-basin-refill-procedure-aEA Chapter: DanioVision Temperature Control Unit Basin Refill The Basin Refill Tool During long-lasting DanioVision experiments, evaporation of water out of the basin could be an issue. You can compensate for evaporation by refilling the basin without opening the DanioVision Observation Chamber (DVOC-0040). The Basin Refill Tool (DVBR-0010) allows you to refill the basin without opening the DanioVision Chamber during an experiment. It is provided standard with the DanioVision Temperature Control Unit (DVTCU). It is possible to fill/refill the basin directly (see Chapters 3 and 4 in the Temperature Control Unit – DanioVision User Manual). However, this is not practical when an experiment is running. Only use the Basin Refill Tool in combination with the DanioVision Temperature Control Unit (DVTCU). Setting Up the Basin Refill Tool You must install the Basin Refill Tool before starting the experiment. - Make sure your DanioVision basin is empty. To do so, follow the instructions in the section Draining the DanioVision System in Chapter 4 of the Temperature Control Unit – DanioVision User Manual. - Disconnect the tube marked in green between the DanioVision Chamber and the TCU (when applicable). - Connect the ends of the tubes of the Basin Refill Tool to the corresponding green-marked inlets at the back of the DanioVision Observation Chamber and the Temperature Control Unit. - Make sure the faucet is closed (Off position). - Fill the syringe with basin liquid, and connect it to the short faucet tube. - Fill the basin circuit (see Chapter 3 of the Temperature Control Unit – DanioVision User Manual). Tip: While the basin circuit is being filled, insert a few ml of liquid from the syringe in order to prevent air bubbles from getting into the circuit. - Start the experiment as usual. How to Use the Basin Refill How much liquid to insert via the syringe depends on the level of evaporation and the duration of the experiment. Add liquid into the basin circuit whenever needed. During refill, do not switch off the Temperature Control Unit. - Open the faucet (On position). - Make sure you can see the overflow outlet of the DanioVision Chamber (red marked tube). - Gently push the syringe to insert liquid. - Carefully watch the overflow tube. Whenever the liquid comes out, stop pushing the syringe. Notes: - Overflow is a good indication of a 100% filled basin; however, it may lag on filling. - The DVTCU will compensate for any temperature fluctuation due to the refill. However, make sure that the liquid temperature in the syringe is not too far from the desired basin temperature. To refill the syringe: - Make sure the faucet is closed (Off position). - Disconnect the syringe. - Fill the syringe with basin liquid. - Make sure no air is present in the syringe. - Connect the syringe back to the faucet tube. For More Information For more extensive information on the DanioVision Temperature Control Unit, see the Temperature Control Unit – DanioVision User Manual, which you can find on our website at www.noldus.com/downloads. Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## DanioVision - DVTCU Basin Refill Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvtcu-basin-refill-procedure Chapter: DanioVision Temperature Control Unit Basin Refill The Basin Refill Tool During long-lasting DanioVision experiments, evaporation of water out of the basin could be an issue. You can compensate for evaporation by refilling the basin without opening the DanioVision Observation Chamber (DVOC-0040). The Basin Refill Tool (DVBR-0010) allows you to refill the basin without opening the DanioVision Chamber during an experiment. It is provided standard with the DanioVision Temperature Control Unit (DVTCU). It is possible to fill/refill the basin directly (see Chapters 3 and 4 in the Temperature Control Unit – DanioVision User Manual). However, this is not practical when an experiment is running. Only use the Basin Refill Tool in combination with the DanioVision Temperature Control Unit (DVTCU). Setting Up the Basin Refill Tool You must install the Basin Refill Tool before starting the experiment. - Make sure your DanioVision basin is empty. To do so, follow the instructions in the section Draining the DanioVision System in Chapter 4 of the Temperature Control Unit – DanioVision User Manual. - Disconnect the tube marked in green between the DanioVision Chamber and the TCU (when applicable). - Connect the ends of the tubes of the Basin Refill Tool to the corresponding green-marked inlets at the back of the DanioVision Observation Chamber and the Temperature Control Unit. - Make sure the faucet is closed (Off position). - Fill the syringe with basin liquid, and connect it to the short faucet tube. - Fill the basin circuit (see Chapter 3 of the Temperature Control Unit – DanioVision User Manual). - Start the experiment as usual. Tip: While the basin circuit is being filled, insert a few ml of liquid from the syringe in order to prevent air bubbles from getting into the circuit. How to Use the Basin Refill How much liquid to insert via the syringe depends on the level of evaporation and the duration of the experiment. Add liquid into the basin circuit whenever needed. During refill, do not switch off the Temperature Control Unit. - Open the faucet (On position). - Make sure you can see the overflow outlet of the DanioVision Chamber (red marked tube). - Gently push the syringe to insert liquid. - Carefully watch the overflow tube. Whenever the liquid comes out, stop pushing the syringe. - Overflow is a good indication of a 100% filled basin; however, it may lag on filling. - The DVTCU will compensate for any temperature fluctuation due to the refill. However, make sure that the liquid temperature in the syringe is not too far from the desired basin temperature. To refill the syringe: - Make sure the faucet is closed (Off position). - Disconnect the syringe. - Fill the syringe with basin liquid. - Make sure no air is present in the syringe. - Connect the syringe back to the faucet tube. For More Information For more extensive information on the DanioVision Temperature Control Unit, see the Temperature Control Unit – DanioVision User Manual, which you can find on our website at www.noldus.com/downloads. Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## DanioVision - Solenoid Startle Response in Zebrafish Larvae URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-solenoid-startle-response-in-zebrafish-larvae Chapter: DanioVision 1. Introduction Larval stage zebrafish display a robust startle response, which is mediated by neural pathways similar to that in higher vertebrates. Noldus Information Technology has developed the DanioVision Tapping Device DVTD-0010 that works as a startle stimulus for zebrafish larvae, to be used in combination with the DanioVision Observation Chamber and the EthoVision XT software. In this system, a single mechanical impulse is given to the well plate holder which startles the zebrafish larvae. Here we demonstrate the capability of this solution by listing a number of test results. Questions Addressed - Can the DanioVision Tapping Device trigger a startle response in zebrafish larvae? - Does the startle response differ between larvae in light and dark conditions? - At what age of the larvae can the DanioVision Tapping Device evoke a startle response? - Does the response differ between larvae located in different areas of the well plate? 2. Methods DanioVision and the Tapping Device We used a DanioVision Observation Chamber (DVOC-0040/T) connected to a Temperature Control Unit (DVTCU) that kept the water at 28°. The Tapping Device is located inside the DanioVision chamber, in such a way that when activated it would hit a metal plate connected to the DanioVision well plate holder. The larvae were filmed using a digital camera with a video resolution of 640 x 480 pixels, and a frame rate of 60 fps. How the DanioVision Tapping Device Works The DanioVision Tapping Device is based on a solenoid, an electromagnetically inductive coil wound around a metal core. The core is made of two parts, a fixed one and a plunger connected to a push pin. When a current flows in the solenoid, a magnetic force is created between the plunger and the core, causing the plunger and the push pin to quickly move forward. The pushpin hits a metal plate attached to the basin in which the well plate is kept. When deactivated, a spring makes the plunger resume its position. EthoVision XT and Test Protocols We used EthoVision XT 10.1 on a Dell Precision workstation. The Trial Control procedures of EthoVision XT controlled the timing of the stimulus. In most cases the stimulus was given repeatedly at regular intervals of 1 minute, with a rest period of 5–10 minutes between stimuli of different intensity. In other tests, the intensity of the stimulus was constant in each trial. The stimulus intensity can be adjusted in the Trial Control procedures of EthoVision XT, on a scale from 1 to 8. Additional tests using an accelerometer placed on an empty well plate showed that higher stimulus intensities resulted in higher accelerations. Tests were carried out on 2 to 9 dpf larvae, with different genotypes (wild type and genetically modified) and subject to different experimental treatments. In the Trial Control procedures, the Tapping Device and the White Light stimuli could be combined and programmed. In general, tests were carried out in two different lighting conditions: either with full light (with the intensity of the DanioVision White Light set to 100%) or in darkness. Data Analysis To analyze the startle response we used the distance moved by the center point of each subject. We compared the 1-second periods immediately before and after administering the stimuli, respectively. Most of the results reported here are from control, wild-type animals. 3. Results Startle Response In all test conditions, zebrafish larvae reacted to the DanioVision Tapping Device. We found a significant increase in the subject's distance moved in the 1-second period after stimulus administration compared with the previous 1-second period (paired one-tailed t-tests, n=96; always P<0.001). Although significant variation in the data was due to between-subject differences, the response was consistent across systems and laboratories. A startle response could be detected independent of the animals' baseline. Effect of Lighting Conditions Zebrafish larvae were generally less active in dark conditions, but showed similar responses as when they were exposed to the DanioVision white light. The difference in response was not significant (ANOVA, P >0.5). Effect of Subject Age Tests conducted in different laboratories on larvae of age 2, 3, 6 and 9 dpf showed that the startle response can be detected from the age of 3 to 9 dpf, and for all stimulus intensities. Tests carried out on 5 and 6 dpf larvae showed no significant difference in the degree of response between day 5 and 6 (ANOVA, P >0.5). Effect of Position in the Well Plate We tested whether the degree of the startle response differed between animals in different positions of a 96- or 48-well plate. We analyzed the distance moved before and after stimulus administration between animals in the top vs. bottom rows, and between animals in the left vs. right columns. The degree of response did not differ between groups in any of the tests (P >0.05). We conclude that there is no evidence that the Tapping Device stimulus results in differential responses at various distances from the stimulus source. 4. Conclusions - For all Tapping Device stimulus intensities, in both light and dark conditions, the DanioVision Tapping Device is capable of inducing a startle response in animals of 3 dpf and older. - It is in principle possible to design experiments where the animals are subject to stimuli of different intensity. - There is no evidence that the startle response measured by EthoVision XT depends on light conditions or the position of the subject in the well plate. 5. Acknowledgments We acknowledge the kind collaboration of the following researchers and their groups: - Dr. Stefan Spulber, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden - Dr. Edor Kabashi, Institut du Cerveau et de la Moelle, Paris, France - Dr. Hiroko Nakatani, URM INSERM 788, Le Kremlin-Bicêtre, France Sjors Coenders is Senior Solution Engineer and Fabrizio Grieco is Behavioral Research Consultant at Noldus Information Technology. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## DanioVision - TCU Conversion Manual URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-conversion-manual Chapter: DanioVision DanioVision Observation Chamber Conversion Manual Introduction This Conversion Manual describes how to convert your current DanioVision Observation Chamber to work with the new Temperature Control Unit. Please make sure to carefully follow the steps described below. Converting the DanioVision Observation Chamber What Do I Need? To carry out the conversion, the conversion kit comes with the following parts and tools: - New basin with temperature sensor. - Three color-coded tubes. - Tube connectors. - Torx bit. - Small Philips head screwdriver. - Hexagonal key (2 mm). - PTFE tape (0.1 mm, pressure class 0.2). Additionally, you need the following tools and parts: - Large Philips head screwdriver. - Pliers. - Grip for torx bit. - Socket wrenches (no. 14, 11, 10). - Vaseline. The conversion of the DanioVision Observation Chamber must be carried out by a technically skilled person. If, during the conversion, you have any questions, please contact the Noldus Help Desk (www.noldus.com/help-desk). Carrying Out the Conversion - Place the DanioVision Observation Chamber on a flat, stable table with enough space to move it around, or for yourself to move around the table. Removing the Green Lid (Steps 2–4) - Raise the lid to the upper position. - Remove the 6 screws (3 screws on each side) in the rail with the small Philips head screwdriver. It might be easier to put the Observation Chamber on its side to reach the bottom screws. Make sure not to lose the screws because you need them to re-assemble the chamber. - Lift the lid and slightly tilt it forwards to remove it from the Observation Chamber. Removing the White Casing (Steps 5–12) - Remove the plastic cover from the back panel by unscrewing the 4 screws with the small Philips head screwdriver. - Gently and carefully put the DanioVision Observation Chamber on its side. Unscrew the 9 torx screws using the torx screwdriver. - Put the DanioVision Observation Chamber upright or keep it on its side. Remove 4 screws with the small Philips head screwdriver from the inside frame: there are 2 screws on either side. - Before removing the white casing, lift the lens to the up position. - Do not yet completely remove the white casing, but lift it (slightly pull apart both sides) on both sides until it is about 20 centimeters off the bottom. - Disconnect the molex connector at the front. - Lift the back of the DanioVision Observation Chamber and disconnect the 3 tubes on the inside with the pliers from the connectors. - Lift the white casing to remove it from the system. Disconnecting the Interface Box (Steps 13–15) The steps below describe how to disconnect the interface box; this is necessary for the placement of the new basin. - At the back of the DanioVision Observation Chamber, mark the position of the interface box. - Unscrew the 2 screws (one on each side) of the interface box. - Remove the interface box from the base of the Observation Chamber. Replacing the Basin (Steps 16–21) - Unscrew the 6 hexagonal screws (3 on each side) from the basin. - Remove the basin from the chamber. - Remove the two clamps from the old basin and install them on the new basin with the large Philips head screwdriver. - Insert the new basin into the Observation Chamber from the back side. - Use the 6 hexagonal screws from the old basin (see step 16) to fix the new basin to the base of the DanioVision Observation Chamber. - Put the interface box back in place using the marking from step 13 and fix it to the bottom plate with the two screws. Modifying the White Casing (Steps 22–28) - Put the white casing upside down. - Remove the tube connector with the green sticker from the inside of the casing with a socket wrench. - Remove the tube connector with the red sticker. - Remove the old PTFE tape and apply new PTFE tape to the thread of the biggest connector (the smaller connector is not re-used). Do the same for the new blue connector. - Screw the blue connector into the hole with the red sticker and the grey connector into the hole with the green sticker. - Punch out the rubber of the hole next to the connector with the green sticker. If necessary, use scissors or a sharp knife to remove the rubber. - Put the white casing on the table surface. Take the plug that is connected to the temperature sensor of the new basin and lead it from underneath the casing to the hole made in the previous step. Firmly push the plug through the hole. The plug of the temperature sensor and the wire should come out on the other side of the casing. Reassembling the Chamber (Steps 29–37) - Slide the white casing back onto the Observation Chamber frame. Make sure not to slide it all the way to the bottom of the frame. - Reconnect the molex connector at the front. - At the back of the chamber, reconnect the tubes as follows: - Connect the large tube (10 mm) to the left connector on the inside using the pliers. Before connecting the tube, lubricate the connector with some Vaseline. This connector is for the water overflow. - Connect the small tube (8 mm) to the connector next to the one connected in the previous step using the pliers. Before connecting the tube, lubricate the connector with some Vaseline. This connector is for the water outlet. - Connect the other small tube (8 mm) to the remaining connector on the right using the pliers. Before connecting the tube, lubricate the connector with some Vaseline. This connector is for the water inlet. Make sure to slide each tube far enough onto its connector. - Lower the casing onto the bottom of the frame. - Attach the white casing to the frame with the 4 screws from step 7. - Attach the bottom plate to the frame with the 9 torx screws from step 6. - Slide the green lid back onto the frame (see also step 4). Make sure the outer rail on both sides is sticking out of the white casing to be able to attach the green lid to the rails. If the rails have slid down, use a small screwdriver to push them up. It may be helpful to put the chamber on its side and then place and tighten the screws. - Attach the plastic cover to the back panel (see also step 5). - At the back of the chamber, screw the new outer connectors to the inputs/outputs as follows: - Connector 1 (red): water overflow. - Connector 2 (yellow): water output. - Connector 3 (green): water input. You can now connect the DanioVision Temperature Control Unit to the Observation Chamber. See the Temperature Control Unit – DanioVision User Manual for instructions on how to do this. Source: DanioVision Conversion Manual TCU, Noldus Information Technology --- ## DanioVision - Technical Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-technical-specifications Chapter: DanioVision DanioVision Technical Specifications DanioVision™ is a complete system for the tracking of zebrafish larvae, insect larvae, and other very small animals in a multi-well plate. The system consists of: - The DanioVision Observation Chamber - The Temperature Control Unit (optional) - The Tapping Device (optional device for sound/vibration stimulus) - Computer - EthoVision® XT video tracking software (pre-installed) Observation Chamber Main Features The Observation Chamber provides a controlled environment for testing. It features: - An infrared (IR) sensitive high-speed GigE digital camera - An IR and white light backlit basin with plate/dish holder - An innovative optical design to prevent image distortion - Connections for additional stimuli (such as Tapping Device) - In- and outflow connections for the flow-through of water in the basin Dimensions Closed position: 61 x 32 x 49 cm (24" x 12.6" x 19.3") Door opening: 35 x 29 cm (13.8" x 11.4") Power Requirements 24 V DC, 2.0 A (max) Mains adapter input: 100–240 V AC. Output: 24 V DC, 3.0 A. PC Interface USB-2 compatible Weight 15 kg (excluding power supply, external tubes, and cables) Camera The DanioVision Observation Chamber includes a GigE digital camera with an IR lens. - Basler acA1300-60gm - Gigabit Ethernet (RJ45 connector, CAT5e or higher) - 1/1.8" Progressive Scan CMOS, monochrome - 8 mm (default) or 12 mm (optional) lens, F1.4, IR pass filter Video performance options: - 800 x 600 at 60 fps (8 mm lens) — default - 640 x 480 at 60 fps (12 mm lens) — optional - 1280 x 960 at 30 fps (12 mm lens) — optional Basin The backlit water basin allows for the inflow, outflow, and overflow of water and holds several multi-well plates, petri dishes, and other small containers. Basin dimensions: 15.8 x 13.2 cm (6.2" x 5.2") Microplate Holder - Compatibility: ANSI and SBS compatible - Dimensions: 127.76 x 85.48 x ±0.50 mm - Maximum height: 27 mm Water Connections - Inlet/outlet: tube fitting 8 mm - Overflow: tube fitting 10 mm - Inlet tube: 1.5 m clear PVC hose, 8 mm OD, 5 mm ID (marked green) - Outlet tube: 1.5 m clear PVC hose, 8 mm OD, 5 mm ID (marked yellow) - Overflow tube: 1.5 m clear PVC hose, 10 mm OD, 8 mm ID (marked red) Lights The backlight unit of the basin combines an IR and white light array. The IR light (near infrared at ~950 nm) is invisible and used for tracking only. It is permanently turned on at a constant level to enable accurate detection and tracking of the animals. The visible white light is meant to be used as a stimulus (light pulse) or to mimic daylight conditions. Changes in white light will not be picked up by the camera. The white light has a color temperature (Tc/°K) of ~5500 and an intensity ranging from a minimum of ~0 lux to a maximum of ~5000 lux. You can program EthoVision XT to turn the light on or off, or to build up or decrease the white light gradient. White light levels are measured directly on the bottom of the water basin. For more information on how to use and change the white light settings in your experiment, please refer to the EthoVision XT user manual. External Input/Output You can connect several stimulus devices to the DanioVision system using TTL connections: - TTL input/output (4x module RJ45 connector): - 4 x 2 TTL input - 4 x 2 TTL output - TTL expansion port 1: - 4 x TTL output (open collector output) - 1 x input camera - 1 x output camera - TTL expansion port 2 (1 x modular RJ45 connector): - 8 pin feed through Temperature Control Unit The Temperature Control Unit is connected to the DanioVision Observation Chamber to control the temperature of the water in the basin that holds the well plate. The temperature is measured at the base of the basin. Mechanical - Dimensions: 460 x 210 x 280 mm - Weight: 7 kg - Hose connectors: 8 mm outer diameter tube Electrical - Operating voltage: 24 V DC - TTL port specifications: 2 input (max 5 V), 2 output (max 5 V, open collector) Operational - Temperature accuracy: ±0.5 °C / 0.9 °F - Temperature set point range: 15–40 °C / 59–104 °F (depending on ambient temperature) - Maximum heating capacity: 10 °C / 18 °F above ambient temperature - Maximum cooling capacity: 2.5 °C / 4.5 °F below ambient temperature - Permissible water temperature range: 5–50 °C / 41–122 °F - Water capacity: approximately 350 ml - Pump water flow rate: approximately 310 ml/min - Permissible height difference: Temperature Control Unit must be at the same height as or a maximum of 1.3 m lower than the DanioVision chamber Tapping Device The Tapping Device produces a tap at the basin causing a vibration that can be used to evoke a startle response. The tap can be set to a specific force (1–8) with a maximum tapping rate of 3 taps per second, and is programmable with EthoVision XT software. Specifications - Dimensions (including bracket): 6 x 24 x 7.5 cm (2.4" x 9.4" x 3") - Dimensions of electronics housing: 2.5 x 10 x 6.5 cm (1" x 3.9" x 2.6") - Weight: 300 g - Power requirements: 24 V DC, 0.4 A (max) Connectors - Molex 1 pin — Power (24 V) - Molex 4 pin — Tapping device to electronics - Blue multi connector — TTL control signal Source: Technical specifications - DanioVision, Noldus Information Technology --- ## DanioVision - Temperature Control Unit in a Nutshell URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-temperature-control-unit-in-a-nutshell Chapter: DanioVision DanioVision Temperature Control Unit in a Nutshell Connecting the DanioVision System - Connect the color-coded tubes to connectors with the same color on both the Temperature Control Unit and the Observation Chamber. - Make sure that both the Drain tube in the DanioVision Temperature Control Unit (blue color code) and the Overflow tube in the DanioVision Observation Chamber (red color code) end in a sink or container. - Connect the cable with cinch plugs on both ends to the temperature sensor connectors on both the Temperature Control Unit and the Observation Chamber. - Optionally, connect the network cable to the TTL port on the DanioVision Temperature Control Unit and one of the TTL ports 1 to 4 on the Observation Chamber. This allows you to log "low" and "high" temperature alarm messages and use them in the Trial Control in EthoVision XT, for example to stop tracking when the temperature is too low. Setting Up the Temperature Control Unit Before you start using the system for the first time, we recommend first flushing the system. Fill and drain the system with demineralized or distilled water. To do this, first fill the system with water, then drain the system. See below for how to fill the system and the draining section for how to drain the system. To set up the DanioVision Temperature Control Unit and the Observation Chamber: - Turn on the DanioVision Observation Chamber at least 15 minutes before you start EthoVision XT. - Locate the switch inside the chamber at the right of the camera, and set the anti-condensation mode to: - On when the room temperature is lower than the desired water temperature. - Off when the room temperature is higher than the desired water temperature. - On the DanioVision Temperature Control Unit, set the Operation switch to Fill/Drain and turn the Drain tap completely to Closed. - Slowly start pouring demineralized or distilled water into the basin of the Observation Chamber. If necessary, repeat this until the basin and all tubes are filled. The water level in the basin should be just below the indicated edge. Close the Observation Chamber when done. - To set the desired water temperature, set the Operation switch to On. - Hold the Set button for about 1 second; the display shows the set temperature. - Use the arrow keys to set the desired water temperature and press Set. - Wait until the set temperature has been reached. This takes on average 10 minutes. After that, the system turns to Ready. Using the Temperature Control Unit - Insert a well plate into the basin. To prevent air getting trapped underneath the well plate, put the back of the well plate against the shaped wall and place it on the basin floor, then tilt the front of the well plate down to the floor. As you do this, water flows into the overflow part of the basin. - Lower the lens and close the DanioVision Observation Chamber. - Carry out an experiment as usual. Draining the DanioVision System After you have carried out an experiment, remove all the water from the system by draining it. This prevents contamination of the system. Before you drain the system, make sure that both the Drain tube in the DanioVision Temperature Control Unit (blue color code) and the Overflow tube in the DanioVision Observation Chamber (red color code) end in a sink or container. - Set the Operation switch to Fill/Drain and turn the Drain tap to Open. - When the basin is empty, turn the Drain tap to Closed to remove all remaining water from the tubes and let it flow into the basin. - Turn the Drain tap to Open again to completely drain the DanioVision Observation Chamber. For More Information For more extensive information on the Temperature Control Unit, see the Temperature Control Unit – DanioVision User Manual. For information on how to use the DanioVision system, see the DanioVision DVOC-0040 User Manual. You can download all documentation from www.noldus.com/downloads. Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## DanioVision - TopLight Unit Integration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-toplight-unit-integration Chapter: DanioVision Integrating the Top Light Unit into DVOC-0050 This document explains how to integrate a top light unit into the DanioVision DVOC-0050. Top Light Unit Set The top light unit set comes with all parts needed to integrate it into a DVOC-0050. - Unit with RGB and white LEDs, plus 2 black 8mm mounting screws - 2 black angle brackets with T-slot nut and 6mm screws - 2 plastic "stop" pieces - Hex key tool Mounting Mounting the top light unit into the DanioVision DVOC-0050 is not complicated with basic technical skills. Follow the steps below. - Remove any remaining protective cover from the acrylic diffuser plates on both sides of the unit. - Cover the lens bracket inside the DVOC with some protective material to prevent scratching while mounting the top light unit. - Insert the black plastic "stop" into the profile slot and place the T-slot nut above it. - Fasten both angle brackets at a height of approximately 21 cm, measured from the basin bottom. - Position the light unit on top of both brackets and fasten it with both black screws from below. - Slide the unit upwards to reposition it. You may need to loosen both the left and right bracket screws into the profile nuts. Having someone hold the unit in position during this step is recommended. - Slightly fasten both screws so that the unit can still be slid upwards. - Gently slide the whole unit upwards until it is approximately 22 to 23 cm from the basin bottom. - Tighten both screws firmly to secure the unit in position. Ensure the unit is as level as possible and adjust if necessary. Power Connection In the DVOC-0050, the power cables for the top light are pre-installed and ready to be connected. Loosen the cable and connect it to the back of the top light unit. Unit Turning To switch the function from RGB to white light, or vice versa, the complete unit must be turned so that the correct LEDs face down toward the well plate. The RGB LEDs and white LEDs are mounted on opposite sides of the same aluminum base plate and can be identified by the labels "White" and "RGB" attached to the unit. - Cover the lens bracket with protective material as before. - Loosen both T-slot screws to allow the unit to move down a few centimeters. - Tighten both screws to hold this position and prevent the unit from falling. - Unscrew both the left and right screws from the aluminum LED base plate. - Remove the unit and turn it so that the preferred LEDs now face downward. Take care not to twist the cable at the back. You may temporarily unplug both connectors to avoid twisting. - Fasten both screws back into the base plate. - Loosen both T-slot screws to allow the unit to slide back up to the original height. - Tighten both screws firmly to secure the unit in its final position. Source: TopLight Integration, Noldus Information Technology --- ## DanioVision - TopLight User Manual URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-toplight-user-manual Chapter: DanioVision User Manual: DVOC Top Light DVTL-002x This manual explains the setup and operation of the custom red, blue, green (RGB) and white top lighting in the DVOC-0040 / DVOC-0041. Connecting the Components The setup consists of a DanioVision Observation Chamber with built-in custom top light, a desktop power supply, a TTL-to-28V interface, and cabling. With this setup, two of the LED colors, or the white light, can be switched on and off from EthoVision. The TTL-to-28V interfaces enable switching the power from the desktop power supply. If you would like to use all three colors (R-G-B) within one experiment, you will need a second TTL-to-28V interface. The LED power cable (coming from the back of the DVOC) has four connectors, one for each LED color. The connectors belonging to the appropriate colors should be connected to the TTL-to-28V interface on outputs 1 and 2. The TTL network cable (green) should be connected between the TTL-to-28V interface and port 1 on the DVOC. A main power cable connects the desktop power supply to the input of the TTL-to-28V interface. Operating the Power Supply Supply version: PeakTech 6225A. Prior to connection to a mains outlet, check that the mains voltage corresponds with the voltage setting of the supply. On the power supply, the voltage can be set to determine the amount of light that the LEDs emit. The voltage must not exceed the maximum voltage for each LED color: - Red, Green, and Blue LEDs: maximum 24V - White LEDs: maximum 18V Note that higher voltages may damage the LEDs. To operate the power supply: - Power up using the power switch on the back. - Adjust the voltage by turning the Voltage knob. Press the knob to switch between coarse and fine adjustment. - Read the actual output voltage from the display. - Set the Current knob to its maximum level (turn fully clockwise). This knob sets a current-limiting value and is not needed for this application. If not set correctly, the supply may enter Constant Current (CC) mode and limit the output voltage. - After setting the desired values, switch the actual voltage output on using pushbutton 8 on the front. It is good practice to set your desired voltage before connecting the main LED power cable to the supply. Refer to the supply manual for further details. Changing Between Red, Green, and Blue To change between colors, unplug the current connector of the LED power cable from the TTL-to-28V interface and plug in the correct one. Each connector is labelled with its corresponding color. Changing Between Color and White Light To switch between RGB and white light, the unit must be turned so that the correct LEDs face downward toward the well plate. The RGB LEDs and white LEDs are mounted on opposite sides of the same aluminum base plate, identified by the labels "White" and "RGB". - Cover the lens bracket with protective material. - Loosen both the left and right round black knobs to allow the unit to slide down a few centimeters, just below the camera. - Pull the unit out and turn it upside down so that the preferred LEDs face downward. Be careful not to twist the cable at the back. You may temporarily unplug both connectors to prevent twisting. - Insert the unit and slide it back up. - Tighten both round knobs. Settings in EthoVision XT for Switching Light On/Off Start EthoVision XT and create a new experiment using a template via File > New from Template. During the guided setup, choose Live Tracking, Zebrafish Larvae, and DanioVision with the type of well plate you are using. Configuring Trial Control Hardware - Choose Setup > Experiment Settings. - Under Trial Control Hardware, select Use of Trial Control Hardware. - Choose the options as shown in the reference figure and select the TTL port that you connected. - You can rename the Device ID to something descriptive, such as "Ceiling Light". Configuring Arena Hardware Mapping - Choose Setup > Arena Settings. - After calibrating and drawing the arenas, click Arena Hardware Mapping. - Click Add Device and follow the on-screen instructions. You can rename the device to something like "Ceiling Light". - Under A1, select the device, then click OK. Testing the Light To test the light, select Output 1 High or Output 2 High from the dropdown menu and click the Test button. To turn the outputs off, select Output 1 Low or Output 2 Low. Programming the Light During Trials in EthoVision XT Choose Setup > Trial Control Settings. The following is an example protocol: after 1 minute during the trial, switch the light on, then after 10 seconds switch it off. - Use Conditions > Time to create time conditions (e.g., Wait 1 minute, Wait 10 seconds). - Use Actions > Custom Hardware to define commands (switch on/off) for output 1 and output 2. - Connect all boxes with the start-stop procedure. - Use the Subrule function to create repeating routines (e.g., switch on-off-on). Also adjust the Detection Settings via Setup > Detection Settings before running trials. For more information, refer to the following resources: - The DanioVision DVOC-0040 User Manual - The Trial and Hardware Control – EthoVision XT 11.5 Reference Manual - Chapter 5: Subrules - Chapter 7: Controlling Hardware Devices Tips - The LEDs get hot during operation. Allow the ceiling light to cool down before touching it. - Do not exceed the maximum specified voltage for each color, as doing so may damage the LEDs. Specifications White Light - Illuminance: >30,000 lux at 25 cm distance (well plate) - Luminous flux: 1,584 lm - Color temperature: 4,000K - Array of 408 LEDs - Maximum voltage: 18V Red Light - Luminous flux: 192 lm - Wavelength: 623 nm - Array of 252 RGB LEDs - Maximum voltage: 24V Green Light - Luminous flux: 384 lm - Wavelength: 525 nm - Array of 252 RGB LEDs - Maximum voltage: 24V Blue Light - Luminous flux: 240 lm - Wavelength: 470 nm - Array of 252 RGB LEDs - Maximum voltage: 24V Unit Dimensions - 270 x 220 x 30 mm Source: TopLight User Manual, Noldus Information Technology --- ## DanioVision - Water Pump Fix Technical Note URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-water-pump-fix-technical-note Chapter: DanioVision Why This Technical Note? This section contains instructions for installing the water pump fix in the DanioVision Temperature Control Unit (DVTCU). You need to do this only when, on a regular basis, a flow error of the basin circuit occurs. This error is indicated by one blink of the Error LED. Contents of the Water Pump Fix Kit - 1x printed circuit board with electronics - 1x connection cable for connecting the pump fix board with the main board - 2x spacer with pre-assembled nuts - 1x washer - 1x screwdriver How to Install the Water Pump Fix A - Opening the DanioVision Temperature Control Unit - Before installing the pump fix, make sure that the DanioVision Temperature Control Unit (DVTCU) is drained, disconnected from water hoses and from the power supply. - Put the DVTCU in front of you. Using the washer that comes with the pump fix kit, remove the front screw. - Place the DVTCU in front of you, with the lid on your right hand side. - Remove the two screws at the top of the side wall. - Put the DVTCU just over the edge of the table and remove the three remaining screws from the bottom of the side wall. - Gently pull the side wall towards you to remove it. B - Attaching the Pump Fix Board - Remove two screws at the right side of the main board. Keep the screws aside for later use. - Insert the spacers into both holes. Hand tighten the spacers to prevent overtightening. - Put the pump fix board in place. - Fasten the pump fix board on the spacers using the screws that you removed from the main board (step B1). C - Connecting the Pump Fix Board to the Main Board - Unplug the white connector marked J6 from the main board and connect it to the connector J6 on the pump fix board. - Unplug the white connector marked J2 from the right side of the main board and connect it to the connector J4 on the pump fix board. - Take the wire with a 2-pin connector from the pump fix board, and connect it to the connector J6 of the main board. - Take the wire with a 4-pin connector from the pump fix board, and connect it to the connector J2 of the main board. - Unplug the connector J9 from the main board and connect it to connector J3 on the pump fix board. - Plug the connection cable (consisting of three wires: black, yellow, and red) into the connector J9 of the main board and into the connector J2 of the pump fix board. D - Closing the DanioVision Temperature Control Unit - Put the side wall of the DVTCU back in place. - Tighten the two screws at the top of the side wall, as well as the three screws at the bottom. - Close the lid of the DVTCU. Make sure that the cables are not caught between the lid and the side walls. - Put the plastic screw back in place and tighten it. Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## DanioVision DVOC-0021 - Service Manual URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0021-service-manual Chapter: DanioVision Introduction This DanioVision Service Manual describes how to install EthoVision XT, additional drivers and hardware. If you have purchased the DanioVision Observation Chamber including a computer from Noldus Information Technology, all hardware and software has been installed and tested. In this case you do not need most of the information in this document. This DanioVision Service Manual describes how to: - Install EthoVision XT – You need this information if you use your own computer or an older computer you bought from Noldus IT. In both cases, make sure the computer meets the EthoVision XT 8 system requirements. - Install drivers for the FireWire camera – You need this information if you use your own computer or an older computer you bought from Noldus IT. In both cases, make sure the computer meets the EthoVision XT 8 system requirements. - Configure the anti-condensation mechanism – You need this information when you want to configure the settings of the anti-condensation mechanism for the lens. - Configure the DanioVision White Light – You need this information when you want to use very low intensities for the DanioVision White Light. - Install the spacer for the FireWire camera – You need this information if you want to fully zoom in to 2 x 2 wells. Installing EthoVision XT If you have purchased the DanioVision Observation Chamber including a computer from Noldus Information Technology, all software has been installed and tested. If you use your own computer, or a computer you bought from Noldus IT in the past, make sure it meets the EthoVision XT 8 system requirements before proceeding. During installation of EthoVision XT 8, make sure you select the Noldus Mini USB IO-Box. See the "Mini USB IO-Box - Technical Note" on the EthoVision XT installation disk for instructions on how to install the drivers for the Mini USB IO-Box. If you use a computer on which the Noldus USB IO-Box has been installed, you first need to de-install the drivers for the USB IO-Box via the Control Panel before you can install the drivers for the Mini USB IO-Box. Installing Drivers for the FireWire Camera You can find the drivers for the FireWire camera on the EthoVision XT 8 installation disk. If you do not have the EthoVision XT 8 installation disk, please contact the Support department at Support@noldus.nl for the drivers. Before you install the drivers, make sure the FireWire camera is connected to the EthoVision computer. To install the drivers: - On the EthoVision XT 8 installation disk, browse to the folder ...\Drivers\Imaging Source\4.1.1.4\. - Double-click drvinstaller.exe to start the installation. - Follow the instructions in the Driver Installation Wizard. Configuring the Anti-Condensation Mechanism The DanioVision Observation Chamber is equipped with an anti-condensation mechanism to prevent the lens from condensing during an experiment. This mechanism can be set to three modes using a switch located just below and to the right of the camera inside the chamber. The following modes are available: - Auto (default and recommended) – The anti-condensation mechanism is automatically switched on when the air temperature inside the chamber drops below 28°C (82.4°F), to prevent condensation on the lens. When the air temperature inside the chamber exceeds 28°C, the anti-condensation mechanism is automatically turned off to prevent heating the water in the wells. The value of 28°C is the default setting of the embedded controller. - Off – The anti-condensation mechanism is permanently turned off. Use this mode when the air temperature inside the chamber is equal to the desired water temperature in the wells (28°C). - On – The anti-condensation mechanism is permanently turned on. Use this mode when the air temperature inside the chamber is lower than the water temperature in the wells. Use this in combination with a temperature-controlled water circulation to keep the water in the wells at the desired level for experiments that last several hours. TTL port 2 on the back panel of the DanioVision Observation Chamber is reserved for future use and is therefore no longer available as a TTL I/O port. TTL ports 3 and 4 can still be used. Configuring the DanioVision White Light In the current version of the DanioVision Observation Chamber (DVOC-0021 FireWire), it is possible to use very low light levels for the DanioVision White Light in addition to the default standard white light levels. Both standard and low light are controlled in the same way by EthoVision's Trial and Hardware Control. You can set the light level between 0 and 100% and also specify the fade duration. The standard white light levels range from approximately 150 Lux to over 4000 Lux. The low light maximum intensity value is 1 Lux. There is a switch inside the DanioVision Observation Chamber, located at the bottom-left of the black mini USB IO-Box, with which you can set the White Light level: - H – This is the standard, high light level. - L – This is the low light level. Installing the Spacer for the FireWire Camera You need to install the spacer between the zoom lens and the FireWire camera if you want to be able to zoom in to four (2 x 2) wells. Do not use the spacer if you want to be able to view the complete well plate with all 96 wells. If you indicated in advance that you want to zoom in to four wells, the spacer will already be installed on the zoom lens. To install the spacer: - Inside the DanioVision Observation Chamber, unscrew the lens from the camera. - Screw the spacer onto the lens. - Screw the lens, now including the spacer, back onto the camera. Source: DanioVision DVOC-0021 Service, Noldus Information Technology --- ## DanioVision DVOC-0041 - Acquire Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-acquire-data Chapter: DanioVision Acquire Data There are three ways of acquiring data with your DanioVision system. For every option it is possible to run single trials, but it is also possible to carry out batch acquisition. - Acquire data live. The larvae are tracked as they move in their wells. - Acquire data live and record video simultaneously. The larvae are tracked as they move in their wells while at the same time a video is recorded. This gives you the opportunity to redo the tracking if necessary, either per trial or using batch acquisition. - Record video, then acquire data. You record a video first and then track the subjects offline from the video. Please note that if you only record video with EthoVision XT, Trial Control is not applied. So, for example, the white light is not switched on and off if you only record video. Before you start acquiring data, make sure you have carried out all the necessary checks of the system. Note: The DanioVision Observation Chamber is designed to block light from the outside. However, it cannot be guaranteed that it is completely dark inside the chamber. For experiments that require absolute darkness, place the DVOC in a dark room. Important: In long experiments, evaporation may occur for both the wells in the plate and the basin. Check the wells every 24 hours and if necessary, refill them. Refill the basin every 2-3 days using the Basin Refill tool. For details, see the Reference Manual - DanioVision Temperature Control Unit DV-TCU. For more information, see Acquire Data in the EthoVision XT Help. Acquire Data Live - Make sure the camera is connected to the EthoVision XT computer and that Live tracking is selected as Video Source in the Experiment Settings. - Optionally, plan your trials in the Trial list and select the Arena settings, Detection settings and Trial control settings for each trial. - Choose Acquisition > Open Acquisition. - If no trials are planned, click the New trial button in the Playback Control window or press Ctrl+F3. - In the Acquisition Settings pane, select whether you want to track only the next planned trial or whether you want to track all planned trials without having to start the next trial manually. If you want to track all planned trials, specify the inter-trial interval. Enter a time long enough to be able to change well plates. When you change the well plate between trials, you can start the next trial without waiting for the inter-trial interval to be reached by clicking the Skip remaining interval button in the Playback Control window. - Select whether you automatically want to start the analysis after the tracks are acquired. If that is the case, first define your dependent variables in an Analysis Profile. Optionally, first make a Track Smoothing profile and a Data profile to make a selection out of your data. - Select whether you want to use the Track smoothing profile, Data profile, and Analysis profile that are highlighted in blue in the Experiment Explorer for analysis, or whether you want to run analyses for all possible profile combinations. In the latter case, first delete all profiles you do not need for analysis. If you want to carry out analyses for only a selection of profiles, deselect the check box Auto-start analysis and carry out batch analysis after acquisition. - Put the well-plate into the DanioVision chamber. - Click the Auto-detect button. A Re-initialize window with a timer appears. Wait until it disappears. Important: Use the Auto-detect button every time you change a well-plate. - To start the trial, click the Start trial button in the Playback Control window or press Ctrl+F5. - To stop the trials, wait until Trial Control automatically stops the trials. To stop acquisition manually, click the Stop trial button in the Playback Control window or press Ctrl+F6. If you stop the trials manually, automatic analysis does not start. Also, for batch analysis, the next trials are not started if you stop a trial manually. Note: The recommended maximum trial duration when acquiring live without recording video is 72 hours (3 days). Acquire Data Live and Record Video Simultaneously To save video when doing tracking, follow the procedure above, with the difference that in step 4 you select the check box Save video in the Acquisition Settings pane. If you realize tracking was not optimal, you can redo tracking from the acquired video. Note: The recommended maximum trial duration when acquiring live and recording video simultaneously is 60 minutes. Longer trials produce video files of excessive size, which are more difficult to manage. Furthermore, if one large video gets corrupted then you lose more data. Record Video, Then Acquire Data If you use the option Save video only, track later, Trial Control is not applied, so you cannot control the white light of the DanioVision Chamber with EthoVision XT. To save video when doing tracking, follow the procedure above, with the difference that in step 4 you select Save video only, track later in the Acquisition Settings pane. Also make sure that the trial is time limited, either with a time condition in the Trial Control start-stop rule, or with a Maximum Trial duration setting. Next, you can acquire data using batch acquisition. Plan your trials in the Trial list and specify the video and optionally Arena Settings, Trial Control Settings and Detection Settings for each trial. Note: The recommended maximum trial duration when recording video is 60 minutes. Longer video recordings produce files of excessive size, which are more difficult to manage. Furthermore, if one large video gets corrupted then you lose more data. Drain and Clean the System At the end of the experiment, we recommend removing all the water from the basin and the tubes. If you use the Temperature Control Unit, DV-TCU, set it to Fill/Drain and follow the instructions in the Reference Manual - DanioVision Temperature Control Unit DV-TCU. To prevent the growth of algae in the system: - Always drain the system after use. - Do not expose the system and the tubes to sunlight. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Add-On URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-add-on Chapter: DanioVision Introduction Optogenetics allow scientists to control the activity of specific neurons and study their downstream influence on a variety of biological processes, including behavior. In rodent studies, this technique requires optical fiber implantation. When working with zebrafish larvae, mostly transparent, fiber optics are not needed. Light simply needs to shine in the right direction, making it easy to assess the effect of stimulation of specific, light-sensitive neurons on the behavior of the fish. By inserting light-sensitive receptor proteins into neurons in vivo, it is possible to make those neurons sensitive to activation by light of specific wavelengths. In zebrafish studies, the light-sensitive receptor protein halorhodopsin (NpHR) has successfully been used to inhibit swimming behavior in zebrafish larvae (Arrenberg et al. 2009). Other research showed that channelrhodopsin-2 (ChR2) activation induced backward swimming in a sparse transgene expression line (Zhu et al. 2009). Optogenetics Add-On Application of optogenetic stimulation in zebrafish larvae requires the correct wavelength (i.e., color) of light. When using the DanioVision Observation Chamber, the Optogenetics Add-on provides a way to accurately control and precisely time the application of optogenetic stimulation to up to 96 individuals simultaneously (working with 96 well plates). The Optogenetics Add-on for DanioVision is an optogenetic LED light source based on the Prizmatix Modular LED system. It consists of one, two or three LED wavelengths. The Optogenetics Add-on can be programmed and controlled using the EthoVision XT software included with your DanioVision system. You can set user-defined time conditions for the optogenetic stimulation. In comparison to manual control, this offers far better temporal precision and adds efficiency to longitudinal studies. References - Arrenberg, A.B., Del Bene, F., Baier, H. 2009. Optical control of zebrafish behavior with halorhodopsin. PNAS: 17968–17973. - Zhu, P., Narita, Y., Bundschuh, S.T., Fajardo, O., Scharer, Y.P., Chattopadhyaya, B., Bouldoires, E.A., Stepien, A.E., Desseroth, K., Arber, S., Sprengel, R., Rijli, F.M., Friedrich, R.W. 2009. Optogenetic dissection of neuronal circuits in zebrafish using viral gene transfer and the Tet system. Frontiers in Neural Circuits: 21. Sample Experiment Your DanioVision system comes with an EthoVision XT sample experiment: DVOC_Optogenetics_Demo_Recommended.evxt. It contains examples of Trial Control rules for triggering pulse sequences in one up to three Pulsers. Additional Manuals - For connecting hardware: Prizmatix UHP-T LED Illuminator User Manual.pdf - For programming the Pulser: Prizmatix Pulser User Manual.pdf - For connecting the DanioVision Temperature Control Unit: Reference Manual - DanioVision Temperature Control Unit DV-TCU.pdf Install the Dichroic Mirror in DanioVision When you receive the DanioVision Observation Chamber DVOC-004x with the Optogenetics Add-on, the LEDs are already mounted so you only have to connect the cables. However, the dichroic mirror comes in a separate box to prevent damage during shipping. This section explains how to install it. Note: The function of the dichroic mirror is to direct the color light beams to the well plate, and at the same time allow light to reach the camera, so you can film and track the fish during the test. - Locate the box containing the mirror. Important: Please wear the supplied gloves to avoid damaging or dirtying the mirror. Avoid touching the mirror surface and only hold its edges. - Locate the arrow on one side of the mirror. Once the mirror is mounted, this arrow should be at the top of the mirror and point towards the light source, that is, the backside of the DanioVision chamber. - Attach the mirror. Slide the mirror upwards along the brackets as indicated by the arrows. - Position the mirror just above the mark on the right-hand bracket. When the mirror is in that position, carefully tighten the screw on the left to fix the mirror. Do not apply any force as this may damage the mirror. - The mirror is now ready to use. Important: The LED is extremely powerful and may cause eye injury when looking directly into the light source. For testing, we recommend setting the LED intensity to low. The Pulser Software Please skip this section if you do not use the Pulser/PulserPlus devices. Follow the procedure below if you use one or more Pulser/PulserPlus devices. To control multiple devices, multiple instances of the Pulser software must be running on the EthoVision XT computer. Important: Do not connect the Pulser/PulserPlus device to the computer until the software setup process is complete. Install the Pulser Software Once - Copy the installation files and folders to your computer's hard drive. - Run the setup.exe file and follow the instructions as they appear on the screen. Next, restart the computer to complete the software installation. - Open the folder where the software has been installed (default: C:\Program Files (x86)\Prizmatix Pulser Plus 3.1) and make a shortcut to the EXE file. Give the shortcut a name that is easily recognized, like Pulser A or the name of the first LED. - To install or update the Pulser/PulserPlus drivers, see the Pulser/PulserPlus User Manual. Install Multiple Instances of the Pulser Software To control two or three LEDs independently using the dedicated Pulser/PulserPlus devices, install one instance of the Pulser software for each Pulser/PulserPlus. - Install the first instance of the Pulser software (see above). - Browse to the folder C:\Program Files (x86) and copy the entire folder Prizmatix Pulser Plus 3.1. - Paste the folder in the same location C:\Program Files (x86). Rename the folder to Prizmatix Pulser Plus 3.1 PulserB. - Open the new folder and make a shortcut for the EXE file that you find there. Place the shortcut on your desktop. Name it like Pulser B or the name of the second LED. - If you have a third LED, repeat steps 2 to 4 above to create a new folder which will contain a third instance of the Pulser software. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Add-On (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-add-on-continued Chapter: DanioVision Setting Up the LED Controller Shortcut Make a shortcut to the new EXE file and rename it to e.g. Pulser C. You should at this point have a folder structure and three shortcuts on your desktop. The LED Controller Controlling the LED Manually - Turn on the main power. - Set the switch near TTL to Int. - Set the switch near Ain to Int. - To turn the LED on, flip the switch on. Controlling the LED from EthoVision XT (Through TTL) - Turn on the main power. - Set the switch near TTL to Ext. - Set the switch near Ain to Int. - To turn the LED on, flip the switch on. - Connect the TTL cable with BNC connector from the pulser (or the USB-IO box, depending on the setup) to the connector TTL on the back panel of the LED controller. - In EthoVision XT you can now give the High command. Other Controls - Power Adjustment Dial - Analog Input (Ain) Connector - LED Control Cable Connector - LED Current Cable Connector - DC Power Jack Configuration 1 - Without the Pulser Connection Diagram In the following example, EthoVision XT controls three LED controllers through the TTL ports in the DanioVision Observation Chamber. Note that each port contains two lines, with connectors white (Line 1) or red (Line 2). Each line controls one LED controller. Defining the Pulse Sequence To define a pulse sequence, use actions and conditions in EthoVision XT's Trial Control Settings. For example, a 1-second pulse of light in the first LED can be defined as: Action Light On on port 1 > Time Condition (1 second) > Action Light Off on port 1. For information about creating pulse sequences in EthoVision XT, see the chapter Optogenetics Experiments in the Application Manual - EthoVision XT, which you can find on the EthoVision XT computer under Noldus > EthoVision XT Other Documentation. USB Ports You need one USB port on the EthoVision XT computer to control DanioVision. TTL Ports - When using one LED, you can use TTL-port 2 of DanioVision. Use the white connector at the other end of the cable to connect the LED controller. - When using two or three LEDs, you can control two LEDs with one TTL port. Use TTL-port 2 for LED 1 and 2, and TTL-port 3 for LED 3. The white connector means Line 1, and the red connector means Line 2. Configuration 2 - With Pulsers Connection Diagram USB Ports On the EthoVision XT computer, you need: - One USB port to connect DanioVision. - Additional USB ports, one for each Pulser. Connect the USB port of each Pulser to a USB port of your computer. TTL Ports - When using one Pulser, you can use TTL-port 2 of DanioVision. Use the white connector at the other end of the cable to connect the Pulser. - When using two or three Pulsers, you can control two Pulsers with one TTL port. Use DanioVision TTL-port 2 for Pulser A and B, and TTL-port 3 for Pulser C. Connect the other end of the cable to the Trigger In port of each Pulser. The white connector means Line 1, and the red connector means Line 2. Experiment Settings Choose Setup > Experiment Settings and click Settings next to Use of Trial Control Hardware. Then follow the section below that applies to choose the port numbers in the Device Configuration window. Tip: Open the sample experiment DVOC_Optogenetics_Demo_Recommended.evxt. This is a live tracking experiment where basic settings in Experiment Settings and Trial Control are already selected for when you work with three pulsers. Configuration 1 - Without Pulser Each LED controller is connected directly to one TTL port of DanioVision. If you have three LEDs, choose Port 2 for the first two LEDs, and Port 3 for the third one. Configuration 2 - With Pulser Each Pulser is connected to one TTL port of DanioVision. If you have three Pulsers, choose Port 2 for the first two Pulsers, and Port 3 for the third one. Under Device ID, give each port a name that can be easily recognized. Arena - Hardware Mapping Choose Setup > Arena Settings. Draw the arenas as described in this manual. When the arenas are ready, click the Arena - Hardware Mapping button and make sure that the devices are selected under Arena 1 (A1). Trial Control (No Pulser) Important: Before following this section, make sure that (1) the dichroic mirror is installed in the DanioVision chamber, (2) all components are connected and powered up, and (3) the LED controller is set to TTL control. When the LED is controlled directly from EthoVision XT, activation occurs in Trial Control using the Action boxes. The duration of the light pulse is determined by a Time condition placed between the Action Output 1 High and Output 1 Low. In the example below, LED 1 is activated with a TTL signal Output 1 High and after 0.5 seconds it is deactivated with a TTL signal Output 1 Low. The LED controller must be connected to DanioVision through TTL Port 1 - Line 1. Use Output 2 High/Low commands to control the other LED controller connected to the same DanioVision TTL port. Important: Make sure that the Int-Ext switch near TTL on the LED controller is set to Ext. Trial Control (With Pulsers) Important: Before following this section, make sure that (1) the dichroic mirror is installed in the DanioVision chamber, (2) all components are connected and powered up, and (3) the LED controller is set to TTL control. Procedure - Open all instances of the Pulser software by clicking on the desktop shortcuts Pulser A, Pulser B, and Pulser C. Each instance controls one pulser. - For each instance of the software, next to Select COM Port, choose the correct COM port for the corresponding Pulser. These can be found on the pulser or on the connection diagram. - Next to Select Operation Mode, choose one of the following options. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Add-On (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-add-on-continued-3hF Chapter: DanioVision Pulser Configuration and Operation Testing and Running the Pulser When testing the Pulser, choose (0) Execute pulse sequence after START. By pressing the Start Sequence button, the LED flashes the configured sequence. When running the actual trials, choose (3) Execute pulse sequence after trigger HIGH, then stop when LOW. If you click the Start Sequence button, the Pulser waits for a TTL trigger to start the sequence. - Enter the other settings in the dialog to control the pulse duration and the time between pulses. For details, see the Prizmatix Pulser/PulserPlus User Manual. - Start EthoVision and open the example experiment: DVOC_Optogenetics_demo_recommended.evxt In the Trial Control Settings you find predefined routines (called subrules) to control three Pulsers. The main procedure (top row) has been configured to consecutively trigger the three Pulsers using the corresponding subrules. Make sure the Pulsers all have the correct COM port, are all in the correct mode, and the Start Sequence button has been pressed. For more information, see the chapter Optogenetics Experiments in the Application Manual - EthoVision XT, which you can find in Start > Noldus > EthoVision XT Other Documentation. Basic Subrule A basic set of instructions in a subrule activates the Pulser a number of times, as specified in the Subrule Reference box. The boxes within the subrule specify: - An action to trigger the pulse sequence (Send a signal High to a device through line 1 or 2) - A Time value (wait a number of seconds) - A second action which stops the pulse sequence (Send signal Low to a device through line 1 or 2) In the following example, the subrule triggers the sequence in Pulser A through Output Line 1 for 5 seconds. The name of the device selected next to Custom Hardware is 570 +520 nm, because it controls two Pulsers — one for an LED of 570 nm (through Output Line 1) and one for an LED of 520 nm (through Output Line 2). The name +520 nm can be found in the Arena - Hardware Mapping window of the Arena Settings in the demo experiment. Note: Make sure that the Int-Ext switch near TTL on the LED controller is set to Ext. Configure the COM Port for Each Pulser Aim To configure the COM port so that the Pulser/PulserPlus accepts commands from EthoVision XT. Procedure - Connect the Pulser/PulserPlus to the PC using the USB cable with type-A to type-B connectors. - In the Control Panel, open the Device Manager. - Under Ports (COM & LPT), right-click USB Serial Port and select Properties. - Click the Port Settings tab. - Verify that the parameters are correct, then click OK. - Take note of the port number (for example, COM3). - Repeat the procedure for each Pulser/PulserPlus. Notes The COM port number is retained in the Pulser, so if you disconnect the Pulsers and reconnect them, you do not have to assign the COM ports again. - Tip: To identify which COM port is assigned to which Pulser/PulserPlus device, disconnect the USB cable from one Pulser/PulserPlus, then reconnect it. The item that appears under Ports (COM & LPT) indicates the assigned COM port. - Tip: To change the COM port for a specific Pulser, open the Device Manager from the Control Panel. Under Ports (COM & LPT), right-click the COM port, select Properties, then Port Settings, then Advanced. From the COM Port Number list, select the desired COM port from those available. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Analyze Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-analyze-data Chapter: DanioVision Analysis Profiles and Options Analysis Profiles in the Template Experiment The following analysis profiles are available in the template experiment: - Distance, Time & Movement - Contains the dependent variables Distance moved, Velocity and Movement. - Path Shape - Contains the dependent variables Heading, Turn angle, Angular velocity and Meander. - Rotation - Contains two instances of the dependent variable Rotation, to count the number of clockwise and counterclockwise rotations. For more information on these and other dependent variables, see Dependent Variables in Detail in the EthoVision XT Help. Also see Analysis of Trial Control data in the Reference Manual - Trial and Hardware Control in EthoVision XT. Analyze Intervals Make sure you have defined a Data profile which specifies the intervals you are interested in. Next, in the Analysis profile choose your variables (e.g. Distance moved). Then visualize the data and run analysis. Activity Analysis You can also use the dependent variable Activity state. This variable is only available when you selected Activity analysis in the Experiment Settings. With Activity state you can calculate how long and how frequent your subject has been in different activity states. These states depend on the total pixel change within the arena between a sample and the previous sample. It is important that all defined arenas have exactly the same size. The number of states (two to four) and their thresholds are user-defined. Analyze Convulsions To analyze convulsions, you can use several variables, such as Velocity, Activity and Mobility. If you use Mobility, start with setting a High Mobility Threshold to a high value like 95%, and an averaging interval of 2. Compare the scores of Highly Mobile with those of convulsions obtained manually. Calculate the Statistics The instructions below describe the general procedure of selecting a dependent variable and calculating statistics for that variable. - Choose Analysis > Analysis Profile. In the Analysis Profiles window, select New and type a name for the new profile, then click OK. - Click the Add button next to the dependent variable you want to use for analysis (for an overview, see Dependent Variables in Detail in the EthoVision XT Help). - In the window that appears, select the properties of the dependent variable. In the Trial Statistics tab, choose the statistics you want to calculate per trial for that variable. If you run multiple trials, select additional statistics in the Group Statistics tab. - Repeat steps 2-3 to add more dependent variables. - Choose Analysis > Results > Statistics & Charts. Choose the Data Profile from the list on the tool bar and click the Calculate button. - The results appear on the screen. The Trial Statistics tab shows the statistics per trial. The Group Statistics & Charts tab shows the statistics and charts from the summarized results of all trials. See Calculate Statistics in the EthoVision XT Help for how to read and customize your results. - Optional: Click the Layout button to modify the layout of the results table. Batch Calculations It is also possible to carry out multiple analyses with different filters, data profiles and analysis profiles. To do so click the Batch button. Make your selection from the lists under Select the profile combinations to calculate and click Add. When done, click Calculate. To view a specific analysis result, select the options from the lists on the toolbar. For more information on batch statistics calculation, see Batch statistics calculation in the EthoVision XT Help. Open the DanioVision Casing Tools You Need A Phillips or (preferably) a Pozidrive screwdriver, size 2. Do not use electric screwdrivers. Bench Plate Remove the bench plate, for example, to install the Tapping Device and other custom hardware you want to place inside the DanioVision Observation Chamber. Also when opening the top casing it is handy to first remove the bench plate. - Remove the four screws as indicated in the picture below. - Remove the bench plate. Top Casing Remove the top casing, for example, when you need to replace the camera. - Optional: Remove the bench plate first, as this makes the following steps easier. - Remove the eight screws as indicated in the picture below. Note that the screws located more internally are shorter than the others. These are attached to the aluminium frame. - Close the lid and lift the top casing. - When putting the top casing back in place, make sure that you insert the sides into the bottom casing as indicated in the picture below. Then, tighten all the screws. Sides and Back Casing Remove the sides and back casing to access the connector box, wirings and internal tubings. In most cases you do not need to do so. - Follow the instructions to remove the top casing. - Put the DanioVision Observation Chamber just over the edge of the table and remove the three screws from the bottom plate. Repeat this step for the other side. - Remove the two screws at the back as indicated in the picture below. - You can now lift the casing. Connector Panel To remove the connector panel at the back of the observation chamber, remove the four screws as indicated in the picture below. Adjusting Lid Friction You can adjust the friction of the Observation chamber lid. If the lid falls down easily or opens with much friction, it can be adjusted by loosening or tightening the three screws per hinge. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Arena Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-arena-settings Chapter: DanioVision Define the Arenas Choose Setup > Arena Settings > Arena Settings 1. To Define the Arenas Automatically Follow these instructions if your experiment was created for well plates with 6, 12, 24, 48 or 96 round wells, or 96 square wells, and this is the first new Arena Settings in your experiment. In other cases, go to To Define the Arenas Manually. Tip: Use well plates with no notches between wells. These result in better well detection. Also make sure that the borders of all wells are within the camera image. - In the Grab Background Image window, click the Grab button to grab a background image of an empty well-plate from the camera image. - If EthoVision XT can detect the wells, the outline of the arenas are displayed over the background image. A message appears asking whether the arenas overlap with the wells in the image. - Do one of the following: - If there is good overlap, click Yes. If needed, you can always make small adjustments using the Arrange Arenas function. - If the arenas clearly do not overlap with the wells, or arenas overlap with each other, click No. The Arrange Arenas window appears automatically. See Arrange the Arenas for details. - Click the 1. Draw Scale to Calibrate button. Draw a line over the entire well-plate. Next, enter its size. Do this horizontally as well as vertically. - Click Validate Setup to validate the Arena Settings. Common errors are overlapping arenas, or zones falling outside an arena. If the setup is valid, continue with the instructions below. Notes - Arenas are marked with labels A1, A2, ..., B1, B2, ... according to your well plate (letters indicate rows; numbers indicate columns). - Automatic detection of the wells in the video image has been tested with the DVOC-0040 and DVOC-0041. Success of automatic detection much depends on image contrast, focus, and distortion, and therefore we cannot guarantee it will work in all situations and with video made with previous DanioVision versions. Automatic detection also does not work if water is not present in the well plate. - If automatic detection of the wells does not work, it could be due to the well plate being not centered in the video image. See Fine Camera Adjustments. - When the well plate image is optimal and centered, and EthoVision XT still shows the message Well plate detection failed, click OK and proceed with To Define the Arenas Manually. - To start automatic well plate detection, click the Well plate detection button at the bottom of the Arenas and Zones section of the Arena Settings pane. To Define the Arenas Manually The following instructions apply when the automatic well plate detection does not work properly. In that case you must define one arena and then make duplicates. If you used a predefined template to set up your experiments, go to Arrange the Arenas. - Click the 1. Draw Scale to Calibrate button, draw a line over the entire well-plate and enter its size. Do this horizontally as well as vertically. - If the current arenas are of a shape different from that of the wells, select all arenas and press Delete. - Click 2. Select Shape and Draw Arena and use one of the shapes to create the first, top-left, arena. Make sure the label of the first arena (for example A1) points to the inside of the drawn arena. - Click the outline of the arena or its label and then click the 4. Copy Arena button. In the window that appears, select All other arenas. Select the number of rows and click OK. - Make sure the predefined arenas cover the wells. If you need to adjust the arena size and position, see Arrange the Arenas. Arrange the Arenas - In the Arena Settings window, click the 5. Arrange Arenas button. In the Arrange Arenas window, do the following: - To move all arenas: Under 1. Move Grid: - To move up/down: Click the first slider. Move it to the right (to move the arenas down) or left (to move the arenas up). - To move right/left: Click the second slider. Move it to the right (to move arenas to the right) or left (to move them to the left). - You can also click the up/down arrow buttons of the corresponding box or enter a number in the box. - To scale all arenas: Under 2. Scale Arenas: - Resize all shapes by using the sliders, by pressing the up/down arrows of the corresponding box, or by entering a number in a box. - To increase the height of all arenas, use the first slider. To increase the width of all arenas, use the second slider. - By default, Keep proportions is not selected, allowing you to resize height and width separately. If you select Keep proportions, you can change either the height or the width while maintaining the aspect ratio. - To rotate all arenas: Under 3. Rotate Grid: - Optionally, rotate all shapes. This is only necessary if the well-plate is not positioned straight. The shapes rotate around the center of gravity of Arena 1. - To change the space between arenas: Under 4. Arena Spacing: - Change the space between the shapes. - By default, Keep proportions is not selected, allowing you to change the space between shapes separately in the vertical and horizontal direction. If you select Keep proportions, change the spacing in either the horizontal or vertical direction while maintaining the aspect ratio. - Click Validate Setup to validate the Arena Settings. Common errors are overlapping arenas, or zones falling outside an arena. If the setup is valid, continue with the instructions below. Tip: First position the upper left arena in the desired position and set the desired size using the scale controls. Next, adjust arena spacing so all arenas are correctly positioned. See Using the Multiple Arena Setup in the EthoVision XT Help for information on setting up multiple arenas. To Edit a Single Arena Click the row in the Arena Settings pane for that arena. The corresponding arena is highlighted. For details on editing shapes, in the EthoVision XT Help see Arena Settings > Work with Shapes. Assign the Stimuli to the Arenas Follow this procedure if you want to apply stimuli during a trial, for example a light pulse or a tapping stimulus. Important: If you created an experiment with a pre-defined template and selected the correct DanioVision arena template, the White Light settings will be pre-configured. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Arena Settings (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-arena-settings-continued Chapter: DanioVision Arena Settings (Continued) or Tapping Stimulus has been assigned automatically to the arenas. The steps below are then not necessary. Arena Settings - At the bottom of the Arena Settings pane, click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, do one or both depending on what you want to use: - Click Add device. Under Arena 1, select White Light Stimulus. - Click Add device. Under Arena 1, select Tapping Stimulus. The devices White Light Stimulus and Tapping Stimulus only need to be assigned to Arena 1. They are in fact applied to all arenas. - Click OK. For More Information See also Test the hardware devices in the Reference Manual - Trial and Hardware Control in EthoVision XT. To set up the Tapping Device, see also The DanioVision Tapping Device on page 72. Trial Control Settings Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Check The Daniovision System URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-check-the-daniovision-system Chapter: DanioVision Check the DanioVision System Before you start setting up EthoVision XT, you need to check the following: - Camera: The camera lens should have the correct aperture and must be in focus. The camera must also be correctly configured. - Anti-Condensation Mechanism: You need to do this depending on the temperature inside the DanioVision chamber and the desired water temperature around the well-plate. - White Light Stimulus: You need to do this when you want to use very low intensities for the DanioVision White Light. - Well Plates and Petri Dishes: The well plate or Petri dish must be inserted correctly. Always control evaporation in the basin and in the well plate, especially when you carry out long trials (greater than 1 day). Check the Camera Lens Although the camera and lens are set up before shipment, the settings of the lens can shift during transport. Before you start to work with the DanioVision system, please check that the lens is set up correctly by doing the following: - The lens you use depends on the video resolution and frame rate you want to use. - Insert a well plate or Petri dish in the basin. - Create a new EthoVision XT experiment and open the Arena Settings to see the camera image. When water is not present in the basin, the image of the well plate should look overexposed. - Check the focus. If the camera image is not in focus, loosen the screw, adjust the focus, and tighten the screw. The camera should be focused on the animals. The distance between animals and camera does not change much between types of well-plate and water level in the wells; however, it is always a good idea to check the image before an experiment and adjust the focus until it is optimized. - Check the aperture. The aperture has been adjusted so that when the basin is filled with water, the video image is optimal for tracking. In the Detection Settings, check that detection of the larvae is good. If necessary, adjust the aperture to get a better contrast between larvae and background. - Make sure the camera is correctly configured. Note: The more the aperture is closed, the larger the depth of field, which means that an object is sharp at different distances from the lens. This is especially relevant when you work with a zoom lens and zoom in to focus on a smaller region of a well plate. On the other hand, closing the aperture decreases the contrast between animals and the background. Adjust the aperture until the image is optimized. Configure the Anti-Condensation Mechanism The DanioVision Observation Chamber is equipped with an anti-condensation mechanism to prevent water droplets forming on the lens during an experiment. A temperature sensor inside the DanioVision Observation Chamber checks whether the anti-condensation mechanism should be switched on or off when it is set to Auto mode. Besides Auto mode, you can also permanently switch the anti-condensation mechanism on or off. The switch to set the anti-condensation mode is located behind the camera, at the right side. - Auto: Default and recommended when the DanioVision TCU is not used. The anti-condensation mechanism is automatically switched on when the air temperature inside the chamber drops below 28 °C (82.4 °F) to prevent condensation on the lens. When the air temperature inside the chamber exceeds 28 °C, the anti-condensation mechanism is automatically turned off to prevent heating of the water in the wells. The value of 28 °C is a default setting of the embedded controller. - Off: The anti-condensation mechanism is permanently turned off. Use this mode when the air temperature inside the chamber is equal to or higher than the actual water temperature of the basin or well plate water (in most cases 28 °C). You can use this option in combination with the DanioVision TCU. - On: The anti-condensation mechanism is permanently turned on. Use this mode when the air temperature inside the chamber is lower than the water temperature in the wells. You can use this option in combination with the DanioVision TCU. Note: If you use the DanioVision TCU, follow the instructions in the Reference Manual - DanioVision Temperature Control Unit DV-TCU, and set the switch to either On or Off. Configure the DanioVision White Light In the DanioVision Observation Chamber it is possible to use very low light levels for the DanioVision White Light in addition to the default, standard white light levels. The standard light levels range from approximately 20 lux to approximately 10000 lux. The low light levels range from 0 to approximately 20 lux. Both standard and low light can be controlled in the same way by EthoVision XT's Trial and Hardware Control. - Locate the switch behind the camera, at the bottom-left of the black mini USB-IO Box. - Set the intensity of the White Light: - Right position (H): Standard high light level. - Left position (L): Low light level. Place Well Plates and Petri Dishes Well Plates (ANSI Standard) - Put the back of the well plate against the bridge and place it on the basin floor. - Tilt the front of the well plate down to the floor. This way the water in the basin pushes the air from underneath the well plate. Make sure the well plate is accommodated correctly between the metal springs at the front and at the right side. Tip: Drill a few holes on the sides of the well plate to allow air to escape when placing the well plate. Well Plates (Non-ANSI Standard) For smaller or larger well plates, place the bridge in a different position. The default position (ANSI standard) corresponds to the second hole on the side walls of the basin, when counting from the inner side of the observation chamber. - Remove the screws as indicated in the picture. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Check The Daniovision System (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-check-the-daniovision-system-continued Chapter: DanioVision Check the DanioVision System (Continued) Adjusting the Bridge for Well Plates - Slide the bridge by one or more positions. Check the video image in EthoVision XT, and make sure that the well plate is centered in the camera view. - Fix the screws in the corresponding holes. Petri Dishes - Put the Petri dish against the 90º angle of the bridge. - If necessary, remove the screws of the bridge and slide the bridge a few positions until the dish is centered in the camera view. With DanioVision you can use Petri dishes of diameter up to 90 mm. We recommend not letting water flow in the basin when using Petri dishes. Water may flow underneath the bottom of the dish, making it shift from its original position during a trial. Control Evaporation Wells on the sides of the well plate tend to show a higher rate of evaporation than wells in the center. Also, wells at the front have a higher evaporation rate than those at the back. Our Recommendations In long experiments (greater than 24 hours), evaporation may occur for both the wells in the plate and the basin. - Wells: Check the wells every 24 hours and, if necessary, refill them. - Basin: Refill the basin every 2–3 days using the Basin Refill tool. For details, see the Reference Manual - Temperature Control Unit DV-TCU. The environmental conditions (temperature, relative humidity, and air flow) and experimental conditions (lens heater on/off, white light intensity) influence the rate of evaporation and condensation of water from the basin and well plate. If you plan to carry out long experiments, always test evaporation at your environmental and experimental conditions, and plan refills to make sure that the water level never reaches a critical value. Tip: You can use a special syringe to refill the basin without having to open the DanioVision Observation Chamber. Contact Noldus for more information. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Data Preparation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-data-preparation Chapter: DanioVision Data Preparation Smooth the Tracks Track Smoothing profiles in the template experiment: - No Smoothing – Smoothing filters are not activated. - MDM 0.2 mm – With this Minimal Distance Moved filter, you can reduce the effect of 'jitter' on the Distance moved variable. Applying this filter is recommended, however, it results in longer calculation times in the analysis. Change these settings for your setup, if necessary. More Options Use the Maximum Distance Moved filter to remove outliers in the track, due to erratic detection of objects within the arena, when the margin of the well is sometimes detected as the fish. For more information on smoothing data, see Smooth the Tracks in the EthoVision XT Help. Select Data Data profiles in the template experiment: - All Data – With this Data profile you analyze all tracks separately. - Treated vs. Control – The data are split for analysis based on the two values of the user-defined variable Treatment: Treated and Control. Analyze Dark vs. Light Periods In this example, the researcher wants to analyze the data in different light and dark periods, determined by the activation of the white light. In the Data profile, the function Trial Control State under Nesting is used to create intervals corresponding to the state of the white light. - Choose Analysis > Data Profile > New. Give the new Data profile a name and click OK. - In the Components pane, under Nesting, click the button next to Trial Control State. - Select the period you are interested in, using the Trial Control actions. For example From Light On To Light Off (depending on what name the Light On/Off actions have in the Trial Control Settings). - Insert the Nest box in the Data profile sequence. - If you want to analyze different periods and have the results in the same table, create more Results boxes. To add a Result box, in the Components pane click the button next to Result. In each sequence, add a Nest box that specifies a different Trial Control State. - Choose the dependent variables and run analysis. Tip: See also the sample experiment DanioVision with 96 wells XT which you can download from our web site. There you can find the Data profile mentioned here. Analyze Data Excluding Periods of Inactivity In this example we want to exclude the interval in which a larva was not moving. - Choose Analysis > Data Profile > New. Give the new Data profile a name and click OK. - In the Components pane, under Nesting, click the button next to Movement. - In the Movement tab, you can set the following: - Averaging interval (range 1–1000) – This is the number of samples across which changes in speed are calculated to determine whether the subject is moving or not. In order to reduce the sensitivity of the Movement variable to brief changes in velocity, the velocity data can be smoothed by taking the running average of the last n samples. Enter the averaging interval n or leave 1 if you do not want to smooth the velocity data. - Start velocity – The velocity above which the subject is considered to be moving. - Stop velocity – The velocity below which displacements of the subject's body points are no longer attributed to locomotion but to system noise, body wobble or pivoting on the spot. - Under Calculate nesting for, select Not moving. - Click OK. Insert the Nest box in the appropriate position between the Start and the Result box. - Choose the dependent variables and run analysis. For more information on the Nesting functions, see Analyze Track Segments in the EthoVision XT Help. Analyze the Intervals Around the Onset of the White Light In this example, we want to analyze two intervals: - From 5 seconds before the onset of the White light stimulus, to the onset of the stimulus. - From the onset of the White light stimulus, to 5 seconds after the onset of the stimulus. The aim is to compare activity, speed and other parameters between the two intervals. - Choose Analysis > Data Profile > New. Give the new Data profile a name and click OK. - In the Components pane, under Nesting, click the button next to Free interval. - Do the following: - Under Start criterion, select Trial Control and choose the appropriate options. - Under Stop criterion, select Time. Next to Elapsed time, leave 0:00:00.000 after start event selected. Note: "Start event" here refers to the White light selected under Interval start. Click OK and insert the Nest box in the sequence. - To create the second interval, choose Result under Common elements. Click the middle of the Start box and drag to the Result 2 box to connect the two boxes. - Repeat steps 2–3 to create a new Nest box, this time for the interval "from White light to 5 seconds after that". In the settings, choose the criteria for the second interval: from Trial Control – 0 seconds before Action: Light on to Time – Elapsed time 5 seconds after start event. Click OK and insert the Nest box in the sequence. - Choose the dependent variables and run analysis. Tip: Click Settings in the Result boxes and rename them, for example to "5-s Before White Light" and "5-s After White Light". Those names will be shown in your results. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Detection Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-detection-settings Chapter: DanioVision Detection Settings What Do You Want to Do? - Track one subject per well/enclosure. See below. - Track two or more subjects in the same enclosure. See page 67. - Use Activity. See page 66. One Subject Per Enclosure Choose Setup > Detection Settings > Detection Settings 1. The template experiment contains a Detection Settings profile with DanioVision selected as method. Important: If you have upgraded EthoVision XT to version 15 while you have a DanioVision system older than the DVOC-0040, it is possible that the DanioVision detection settings method does not give optimal detection of the larvae with images from your camera. If that is the case, use another detection method in the Advanced section of the Detection Settings pane. For details, see the EthoVision XT Help. - Click the Auto-detect button. Important: Use the Auto-detect button every time you change a well-plate. - The Auto-detect window with a timer appears. Wait until it has disappeared. All larvae should now be detected well. If not, do one or more of the following: - Open the Advanced section and move the Sensitivity slider. Moving the slider to the left results in detecting more of the body of the larvae, but also more noise. Moving the slider to the right results in detecting less noise, but also gives less good detection of the larvae. If you see erratic tracks, it means that small groups of pixels at the border of the well are sometimes detected as the larva. Move the Sensitivity slider to the right. - If some larvae are not detected while they are in the corner or border of a well, check that the arenas are drawn well. Click the Show/Hide button on the toolbar and select Arena Features, then select the check box in front of Arenas. Check that the arenas cover the entire wells. - Try to maximize the contrast by opening the aperture of the camera lens (see "Check the Camera Lens" on page 33). However, make sure the light intensity is equal for all wells (that is, the center and outer wells). - Certain compounds dissolved in the water can affect the pigmentation in the larvae, thereby decreasing the contrast of the animal and making detection more difficult. Make sure that EthoVision XT can still detect all animals after treatment. - If detection remains unsatisfactory, adjust the Advanced Detection Settings. The Dynamic subtraction method may give better results. For an explanation of the options, see Configure Detection Settings in the EthoVision XT Help. Activity Analysis Use Activity to quantify overall activity of your subjects. In the Experiment Settings (see page 46) select Activity analysis. In the Detection Settings pane, open the Activity section. Activity is shown by purple pixels in the video window. Set the Activity threshold in such a way that movements of the animals are detected and some noise is left. For more information on activity, see Activity Settings in the EthoVision XT Help. Also watch the video tutorial on Activity analysis. For more general information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Multiple Subjects in the Same Enclosure Prerequisites: In the Experiment Settings, Number of Subjects is set to 2 or higher. - Choose Setup > Detection Settings > Detection Settings 1. - Click Automated Setup and draw a rectangle around each subject. - Under Method, select Advanced Model / Adult Fish or Advanced Model / Other if the first does not give the expected results when tracking fish larvae. Note: The Advanced Model / Other method is not based on a modeled fish shape. With this method you cannot track the fish snout and tail. It is only available if the experiment is set to Center-point detection only. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Fine Camera Adjustments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-fine-camera-adjustments Chapter: DanioVision Fine Camera Adjustments Each DanioVision system is thoroughly checked and set to its optimal configuration. However, transport and handling of the system may sometimes cause slight changes in the camera position relative to the well plate, resulting in a sub-optimal video image. This section helps you restore the original settings. Centering the Well Plate Horizontally If the well plate is not centered horizontally: - Loosen the washer located behind the camera bracket, under the camera profile. - Turn the camera in the direction required until the well plate is in the middle of the camera view. - Tighten the washer to fix the camera in the new position. Centering the Well Plate Vertically If the camera is rotated forward or backward in its vertical plane, the video image may appear incorrectly centered. - Loosen the two bolts at the sides of the camera profile. - Rotate the camera bracket forward or backward until the well plate is centered vertically in the video image. - Tighten the bolts. If the Well Plate Looks Rotated If the margin of the well plate is not parallel to the margin of the video image: - Open the DanioVision Observation Chamber and locate one of the bolts at the side of the camera profile (either left or right). - Loosen the bolt using a 3-mm Allen key. - Gently move the camera bracket forward or backward until the well plate is in the correct orientation. When ready, tighten the bolt. Example of a Good Video Image Check that the well plate fills the video image as much as possible, with the letters A–H and numbers 1–8 well visible. Set the camera lens to maximum aperture. The image is overexposed when no water is present. Below is an example of a good video image when water is present. Tighten the three screws on the camera lens once the image is optimized. Additional Hardware DanioVision offers additional connectors to attach and control custom hardware. These are Expansion 1 and Expansion 2, located on the back panel. Expansion 1 Expansion 1 is a female 25-pin DB connector. It provides four additional TTL out lines to control external hardware and input/output lines to trigger the DanioVision camera (for example, at a specific event). TTL-out ports are open collector outputs with a common emitter on pin 9 and 10. Voltage range 0 to 5 V. Specify the custom hardware in the corresponding row of the Device Configuration window. For details, see experiment settings. For more technical details and how to use these connections, contact Noldus Information Technology. - Pin 1: TTL-out port 1 - Pin 2: TTL-out port 2 - Pin 3: TTL-out port 3 - Pin 4: TTL-out port 4 - Pins 5–8: Not available - Pin 9: Common emitter for TTL-out ports - Pin 10: Common emitter for TTL-out ports - Pin 11: I/O output camera - Pins 12–21: Not available - Pin 22: GND I/O camera - Pin 23: I/O input camera - Pins 24–25: Not available Expansion 2 Expansion 2 is an 8-pin modular RJ45 feed-through connector. You can use it to connect internal add-on hardware and receive external signals in the DanioVision Observation Chamber. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Service Manual URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-service-manual Chapter: DanioVision Introduction This DanioVision Service Manual describes how to install EthoVision XT, additional drivers and hardware. If you have purchased the DanioVision Observation Chamber including a computer from Noldus Information Technology, all hardware and software has been installed and tested. In this case you do not need most of the information in this document. This DanioVision Service Manual describes how to: - Install EthoVision XT – You need this information if you use your own computer or an 'old' computer you bought from Noldus IT. In both cases, make sure the computer meets the EthoVision XT 8 system requirements. - Configure the Anti-Condensation Mechanism – You need this information when you want to configure the settings of the anti-condensation mechanism for the lens. - Configure the DanioVision White Light – You need this information when you want to use very low intensities for the DanioVision White Light. Installing EthoVision XT If you have purchased the DanioVision Observation Chamber including a computer from Noldus Information Technology, all software has been installed and tested. If you use your own computer (or a computer you bought from Noldus IT in the past), make sure it meets the EthoVision XT 8 system requirements before proceeding. During installation of EthoVision XT 8, make sure you select the Noldus Mini USB IO-Box. See the "Mini USB IO-box - Technical Note" on the EthoVision XT installation disk for instructions on how to install the drivers for the Mini USB IO-Box. If you use a computer on which the Noldus USB IO-Box has been installed, you first need to de-install the drivers for the USB IO-Box (via the Control Panel), before you can install the drivers for the Mini USB IO-Box. Configuring the Anti-Condensation Mechanism The DanioVision Observation Chamber is equipped with an anti-condensation mechanism to prevent the lens from condensing during an experiment. This anti-condensation can be set to three modes using a switch inside the chamber, located just below and to the right of the camera. The following modes are available: - Auto (Default and Recommended) – The anti-condensation mechanism is automatically switched on when the air temperature inside the chamber drops below 28°C (82.4°F), to prevent condensation on the lens. When the air temperature inside the chamber exceeds 28°C, the anti-condensation mechanism is automatically turned off to prevent heating the water in the wells. The value of 28°C is the default setting of the embedded controller. - Off – The anti-condensation mechanism is permanently turned off. Use this mode when the air temperature inside the chamber is equal to the desired water temperature in the wells (28°C). - On – The anti-condensation mechanism is permanently turned on. Use this mode when the air temperature inside the chamber is lower than the water temperature in the wells. Use this in combination with a temperature-controlled water circulation to keep the water in the well at the desired level for experiments that last several hours. TTL port 2 on the back panel of the DanioVision Observation Chamber is reserved for future use (controlling/displaying DanioVision's anti-condensation mechanism) and is therefore no longer available as a TTL I/O port. TTL port 3 and 4 can still be used. Configuring the DanioVision White Light In the current version of the DanioVision Observation Chamber (DVOC-0011 Analog), it is possible to use very low light levels for the DanioVision White Light in addition to the default, standard white light levels. Both standard and low light are controlled in the same way by EthoVision's Trial and Hardware Control: you can set the light level between 0 and 100% and also specify the Fade duration. The standard white light levels range from approximately 150 Lux to over 4000 Lux. The low light maximum intensity value is 1 Lux. There is a switch inside the DanioVision Observation Chamber (at the bottom-left of the black mini USB IO-Box) with which you can set the White Light level: - H – This is the standard, high light level (right position). - L – This is the low light level (left position). Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## DanioVision DVOC-0041 - Set Up Daniovision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-set-up-daniovision Chapter: DanioVision Connections The back panel of the DanioVision Observation Chamber contains the following connections (see Figure 3 below): - Expansion 1. You can optionally use this connector to set up to 4 TTL out lines, to control external devices. - Temp. Connector for the temperature sensor. Use this in combination with the DanioVision Temperature Control Unit (TCU). - Cable Grommet. If you install additional hardware inside the observation chamber, puncture the rubber membrane to let the cables pass through. For example, to connect the sensor of a digital thermometer placed in the water basin to a digital display outside the DanioVision Observation Chamber. - Gigabit Ethernet (GigE) Camera Connector. Use this output to connect the DanioVision camera to the EthoVision XT computer. - Expansion 2. This is a RJ45 type, 8-pin feed through connection. You can use it to connect future internal add-on hardware to get external signals in the DanioVision Observation Chamber. - Connector for Water Flow. See the water-flow system section for details. - TTL1 to TTL4. You can optionally use these TTL input/output connections to control external devices such as a sound or shock generator, or the DanioVision Temperature Control Unit. - USB Port (type Standard-B) to connect the DanioVision Observation Chamber to the EthoVision XT computer. - Connection for the 24 V Power Supply. - Connectors for Water Flow. See the water-flow system section for details. Connect DanioVision Make sure the DanioVision Observation Chamber is placed on a level surface. Power Connect the DanioVision Observation Chamber's 24 V socket to the power supply using the power cable and adaptor. Video Use the Ethernet cable with the large round connector to connect the digital video output of the DanioVision Observation Chamber to the Ethernet port labeled DanioVision camera on the EthoVision XT computer. The DanioVision camera must be connected to a 1-Gb Ethernet card. If you have purchased a PC from Noldus together with DanioVision, this card is already installed. Contact Noldus if you need a new Ethernet card for the DanioVision camera. White Light, Tapping Device, and Other Hardware Use the USB cable that comes with DanioVision to connect the USB port of the DanioVision Observation Chamber to a USB port on the EthoVision XT computer. Do this only if: - You want to control the White Light or the Tapping Device in the DanioVision Observation Chamber during data acquisition in EthoVision XT. - You have the DanioVision Temperature Control Unit and you want EthoVision XT to take action if the water temperature gets too low or too high. - You want to control any custom hardware connected to the DanioVision Mini USB-IO box. Set Up a Water-Flow System If you require a temperature-controlled water flow underneath the well plate, the Noldus DVTCU Temperature Control Unit is the preferred method. The back panel of the DanioVision Observation Chamber contains three connections for controlling the water flow: a water inlet (marked in green), a water outlet (marked in yellow), and a water overflow (marked in red). Connect the DanioVision Observation Chamber to the DVTCU using the tubes that match the color of the connectors. Please see the Reference Manual - DanioVision Temperature Control Unit DV-TCU for the complete instructions. Suggested Temperature For Danio larvae, the temperature of the water flowing through the system is usually 28 degrees Celsius. You can set a different temperature when needed. Light and Switches Main Switch The main switch is located on the front panel. After you switch on DanioVision, wait at least 15 minutes for it to start up and to avoid condensation in the system. Internal LED Light The DanioVision Observation Chamber is equipped with a LED light to illuminate the inside of the chamber while you set up your experiment. Operate the Light switch at the left of the camera to turn the light on and off. Anti-Moisture Switch This switch is located at the right of the camera. Operate this switch to adjust the anti-condensation mechanism. Low Light Switch This switch is located on the Mini USB-IO box, behind the camera at the back of the observation chamber. - When the switch is set to H (default), the standard light levels are activated, from approximately 20 to 10000 lux. - Set this switch to L to allow very low light intensities, from 0 to approximately 20 lux. Install EthoVision XT If you have purchased the DanioVision Observation Chamber including a computer from Noldus Information Technology, all software has been installed and tested. You can skip this section and proceed to Set Up EthoVision XT. If you use your own computer, make sure it meets the EthoVision XT system requirements. EthoVision XT 16 is supported with Windows 10 Pro, 64 bit. For more information about system requirements, press F1 in EthoVision XT. Mini USB-IO Box Drivers The Mini USB-IO box is the embedded electronics unit that communicates with EthoVision XT. The Mini USB-IO box makes it possible for EthoVision XT to control hardware such as the white light stimulus. Before installing EthoVision XT, remove older versions of the drivers for the Mini USB-IO box. To do so: - In the Windows Control Panel, select Programs and Features. - Click each of the items whose name begins with Noldus_Hardware_Assistant. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Set Up Daniovision (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-set-up-daniovision-continued Chapter: DanioVision Set Up DanioVision (Continued) Installing EthoVision XT - Navigate to Interface and click Uninstall. - Insert the EthoVision XT Installation USB stick into your computer and follow the instructions to install EthoVision XT. When you install EthoVision XT, the drivers of the Noldus Mini USB-IO Box are automatically installed. Important: When you open an experiment from EthoVision XT 12 or lower, a warning appears, informing you that you cannot open upgraded experiments in the old version of the software anymore. Make a backup of your DanioVision experiment in the older version of EthoVision XT before opening it in EthoVision XT. To make a backup, choose File > Make Backup. Important: If you uninstalled the older version of EthoVision XT, you cannot use the Backup function. Instead, make a copy of your experiment using Windows Explorer before you open it in the newer EthoVision XT version. Always copy the complete experiment folder and not only the *.evxt file, otherwise your experiment will not open. For More Information See Installation in the EthoVision XT Help for instructions on how to install EthoVision XT. For more information on the Mini USB-IO box, see the Reference Manual - Trial and Hardware Control in EthoVision XT, which you can find on your EthoVision XT computer, under Noldus > EthoVision XT 16 Other Documentation. Install the Network Card for the DanioVision Camera DanioVision works with a Basler Gigabit Ethernet (GigE) video camera, connected via an Intel PRO/1000 CT 1-Gb Ethernet card installed on your computer. If you ordered a computer from Noldus Information Technology when you purchased DanioVision, it came with that Ethernet card already installed and tested. In that case, skip the sections below and continue with Chapter 4. If you bought your computer elsewhere, you will need to install the Ethernet card yourself. Step 1: Insert the Ethernet Card in the DanioVision Computer - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's casing according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot and remove the corresponding extension cover. When possible, choose the slot that gives maximum performance. To estimate performance, take note of the slot version and compare it with the following values: - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: ~1 GB/s - PCIe v4.0: ~2 GB/s - PCIe v5.0: ~4 GB/s Note that values are given per lane and should not be multiplied by the number of lanes in a slot (e.g. x4), since the card has a 1x connector. For example, SLOT1-PCIe3x4 means version 3.0 with four lanes. Important: Do not insert the PCIe board in the blue or white slots. - Unpack the Ethernet card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. Warning: When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Fix the card to the chassis and re-fit the computer's cover. For more information about installing the camera and the Ethernet board, see Camera Installation in the EthoVision XT Help. Step 2: Install the Camera Drivers - Insert the EthoVision XT installation USB stick into your computer. - Double-click EthoVision XT Setup.exe. If you have already installed EthoVision XT, select Modify. - Under Drivers and Tools, select Basler GigE Camera Driver. - Continue with installation. Under Profile, select Camera User, then click Next. - Under Interfaces, select GigE, then click Next. - Connect the DanioVision camera to the port of the Ethernet card using a network cable. Step 3: Assign the IP Address to the Ethernet Card Tip: Watch the video tutorial Set Up the Camera. In EthoVision XT, choose Help > Video Tutorial. - In Windows, search for Network Connections. - Right-click the Local Area Connection and click Properties. If your computer has more than one Local Area Connection, choose Basler GigE Vision Adapter. Write down the number of this connection. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Select the options Use the Following IP Address and Use the Following DNS Server Addresses and fill in the required details. Also select the checkbox Validate Settings Upon Exit. When done, click OK and then Close. Step 4: Set the IP Address of the DanioVision Camera Tip: Watch the video tutorial Set Up the Camera. In EthoVision XT, choose Help > Video Tutorial. - In Windows, search for IP Configurator and start the application. - Select the camera. - Fill in the details in the IP Address and Subnet Mask fields under Static IP Address. - Click Save and then Close. - Follow the instructions below to configure the DanioVision camera. Configure the DanioVision Camera Camera Settings The DanioVision camera that you received is already configured according to your setup. Noldus created three main settings profiles, called User Sets, stored in the Pylon Viewer software which controls the camera: User Set 1, User Set 2, and User Set 3. Only one User Set can be active at a time. For each video resolution, you must use different camera settings and in some cases a different camera lens. For example, the video resolution determines the maximum frame rate. The higher the required resolution (in number of pixels), the lower the maximum frame rate (in frames per second). The three User Sets are specific for a combination of video resolution and frame rate. Which User Set Is Currently Selected? Make sure that EthoVision XT is closed. Start the Basler Pylon Viewer software and navigate to the Features panel for further configuration details. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Set Up Daniovision (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-set-up-daniovision-continued-rCg Chapter: DanioVision Set Up DanioVision (Continued) Under Configuration Sets, look for the item Default Startup Set. This is the User Set that contains the current settings. Always check that the settings in Pylon Viewer for a particular User Set correspond to those in the table. Note: EthoVision XT reads the settings from the camera driver software. For a specific EthoVision XT experiment you can override the values of video resolution and frame rate values that are stored in the driver, not other settings. The maximum frame rates have been measured with a 96 well plate setup. Other values may be optimal in other setups. User Set 1 is the default User Set in most applications. User Set 2 is pre-selected if you purchased a 12-mm lens. User Set 3 is pre-selected if you purchased an 8-mm lens. For User Set 2, Binning mode must be Summing. For other User Sets either option has no effect with binning equal to 1. Overview of Predefined User Sets The following table summarizes the predefined User Sets in the camera driver software and their associated video frame rate, video size, and required camera lens. Setting User Set 1 User Set 2 User Set 3 A - User Set User Set 1 User Set 2 User Set 3 B - Pixel Format Mono 8 Mono 8 Mono 8 C - Analog Gain — — — D - Center X and Center Y — — — E - Horizontal Binning, Vertical Binning 1, 1 2, 2 1, 1 F - Exposure Time (Abs) in microseconds — — — G - Resolution 1280 x 960 640 x 480 800 x 600 H - Frame Rate (fps) 30 fps 60 fps 60 fps I - Color Space Y800 Y800 Y800 Camera Lens 12 mm 12 mm 8 mm + 0.5 mm spacer ring For all User Sets: Enable Acquisition Frame Rate must be selected. Adjust the Camera Settings in EthoVision XT In EthoVision XT, choose Setup > Experiment Settings and click the camera button. Adjust the settings according to the table above. For details, see Adjust Camera Settings in EthoVision XT in the EthoVision XT Help. Adjust the Camera Settings in Pylon Viewer You can also adjust the camera settings directly in the camera software Pylon Viewer. Adjust the settings according to the configuration you want to use. First, choose a video resolution and frame rate combination, then mount the recommended camera lens, and next make the appropriate settings in Pylon Viewer. Finally, adjust the appropriate settings in EthoVision XT. For more information about Pylon Viewer, see Configure the Digital Camera in the EthoVision XT Help. Adjust the following settings in Pylon Viewer: - Pixel Format (column B in Table 1) - Analog Gain (column C in Table 1) - Center X and Center Y options (column D in Table 1) - Horizontal and Vertical Binning (column E in Table 1) - Acquisition Frame Rate and Exposure Time (column F in Table 1) Tip: To preview the camera image, click the Continuous Shot button on the toolbar. Tip: You can increase the Analog Gain if you need a brighter camera image. However, the image noise will also increase, which may influence tracking. To save the settings, click the Stop button and open the Configuration Sets item. From the Configuration Set Selector list, select the User Set you want to save the settings to. Next to User Set Save, click Execute. Select the User Set you want to use on a daily basis. From the Default Startup Set list, select the User Set of your choice. Camera View Check that the camera view is correct by placing a well plate in the DanioVision Observation Chamber. Make sure that: - The well plate is in the middle of the field of view, not rotated or skewed. - The well plate is in focus. If not, operate the focus ring of the camera lens. - Fixation screws of all rings on the lens are tightened. - The aperture is chosen such that the image appears slightly overexposed. With water in the well plate, the image is fine. When you create an EthoVision XT experiment, check that the Video Resolution, Video Frame Rate, and Color Space match the values in Table 1 for the User Set you want to use. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Set Up Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-set-up-ethovision-xt Chapter: DanioVision Prerequisites Before you can start working with the DanioVision system, you need to connect the DanioVision Observation Chamber to the EthoVision XT computer and, optionally, set up the water-flow system. After you have turned on the DanioVision Observation Chamber with the switch on the front panel, wait at least 15 minutes for the DanioVision chamber to 'start up'. Also make sure to remove the lens cap from the camera. Assign Treatments To Wells To prevent systematic errors as a result of potential variation in temperature, light intensity or other unknown variable across a well-plate, it is recommended to either assign larvae from different treatments randomly to the wells or make sure that wells containing different treatments (that is, different solutions or different concentrations of the same solution) are evenly distributed across the well-plate (so, for example, one type of solution is not only put in the center wells). Create A DanioVision Experiment Preferred Method With this method, all arenas are created automatically, but need to be manually adjusted, using the Arrange Arenas option. Unnecessary functionality like manual scoring is removed from the interface and detection settings are optimized for DanioVision. If you select a template which contains more arenas than needed, you can exclude the unused arenas with Data Selection. After you have followed the steps below to create the new experiment, you must still check/adjust Experiment Settings, Arena Settings and Detection Settings before you can track any animal correctly. - Do one of the following: - In the EthoVision XT Startup window, under New experiment, click New from template. - Choose File > New from Template. - In the Select a template option window, click Apply a pre-defined template. Next, follow the instructions in the guided setup as described below. - Which video source will you use? Select the option Live tracking (and saving video files), click the Sources button and select the Basler camera. Click Next >. - Which subjects will you track? Select Fish and then Zebrafish larvae from the list. Click Next >. - How is the arena configured? Select an Arena template from the list, then click Next >. - DanioVision DVOC 004x, 24 round wells - DanioVision DVOC 004x, 48 round wells - DanioVision DVOC 004x, 48 square wells - DanioVision DVOC 004x, 96 round wells - DanioVision DVOC 004x/T, 24 round wells * - DanioVision DVOC 004x/T, 48 round wells - DanioVision DVOC 004x/T, 48 square wells - DanioVision DVOC 004x/T, 96 round wells - Open field, round - Open field, square - Well plate, round wells — Select this option if you have a different number of round wells - Well plate, square wells — Select this option if you have a different number of square wells * Select one of the options with /T when you have installed the DanioVision Tapping Device and you want to use it in this experiment. Tip: To know which DVOC version you have, see the serial number on the label located on the back panel. Note: Arena templates are also present for older DanioVision DVOC versions: DanioVision DVOC 001x–003x. Note: If you selected a template for an older DanioVision version, it is possible that the DanioVision detection settings method does not give optimal detection of the larvae with images from your camera. If that is the case, use another detection method in the Advanced section of the Detection Settings pane. Consult the DanioVision manual that came with your setup, or see Configure Detection Settings in the EthoVision XT Help. - Initialize template experiment. Check here that all settings are correct and, if so, click Finish. - Enter the name of the experiment and click OK. The EthoVision XT Overview window opens. - Follow all the next steps: - Experiment Settings - Arena Settings - Trial Control Settings - Detection Settings Other Ways To Create A DanioVision Experiment No matter which method you choose, when you create a DanioVision experiment unnecessary functionality like the Manual Scoring Settings is removed from the interface and detection settings are optimized for DanioVision. - File > New from Template > Apply a custom template — Choose this method to create an experiment based on an existing one. For example, when you want to replicate an experiment with the same number of arenas, the same trial control procedures, etc. See Create a new experiment based on an existing experiment in the EthoVision XT Help. - File > New — In the window that appears, select the option DanioVision experiment. In the Experiment Settings, next to Number of Arenas, enter the number of wells. With this option you have to draw the arenas manually. For more information on creating an experiment manually, see Set Up an Experiment in the EthoVision XT Help. We advise creating an experiment with a predefined template (first method), because all arenas are then defined automatically. Experiment Settings Choose Setup > Experiment Settings. Video Source - Under Video source, click the Video icon on the right side of the row of your camera. - In the Video Settings window that appears, click the Formats tab and select the Resolution and Frame rate. Default resolution is 1280 x 960 at 25 frames/s. If you create an experiment based on a template with the Tapping Device, set the frame rate to 60 fps and reduce the resolution according to your setup. From the Color space list, choose Y800. This is the color space for a monochrome video image. The other options, suitable for color images, do not apply to DanioVision. Tracked Features Specify whether you want to track the center point of the fish (default) or the center point, the nose point and the tail base. Choose the latter option only if you track fish in a close-up image. Body Point Detection Technique The Contour-based technique is selected. The option Deep learning is not available for fish tracking. Analysis Options Specify whether you are interested in how long and how frequently your subjects have visited defined zones. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Set Up Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-set-up-ethovision-xt-continued Chapter: DanioVision Set Up EthoVision XT (Continued) To track whether subjects have been active vs. inactive, under Analysis Options select Activity analysis. Make sure you also adjust the Activity settings in the Detection Settings. For more information about setting up an experiment, see Set Up an Experiment in the EthoVision XT Help. Use of Trial Control Hardware Follow this section if you use stimulus devices like the white/color lights and the tapping stimulus device. - In the Experiment Settings, under Trial Control Hardware, make sure that Use of Trial Control hardware is selected and click the Settings button. - In the Hardware Interface window that opens, choose the type of system you have. If you have DanioVision DVOC-0041: - Choose DanioVision DVOC-004x/T if you use the Tapping Device in this experiment. - In all other cases choose DanioVision DVOC-004x. The other options DanioVision DVOC-001x - 003x are meant for older versions of the DanioVision Observation Chamber. Note: The option Mini USB-IO Box only applies when you use a Mini USB-IO box instead of DanioVision DVOC. - In the Device Configuration window, under Device features, the hardware devices activated for this experiment are listed. - Optional: The default status of the DanioVision White Light Stimulus is Light off. This means that when you start a trial, the white light is switched off. To use the white light as a stimulus, program its activation with Trial Control. If, however, you want to use the white light as a default lighting condition and use the darkness as a stimulus, do the following: - Click the White Light Default button. - Under Default device state, select Light on. - Choose a percentage of intensity (0–100) and click OK. Then in the Trial Control procedure you can program when to switch the light off. See Trial Control Settings for more information. - Optional: If you connect additional hardware, under Plug-in devices, select the devices in the corresponding rows for TTL Port 1–4, or Expansion 1 / Port 1–4 depending on which port on the DanioVision back panel you use. - Click OK. - Optional: If you set the default state of the White Light Stimulus to Light on, open the Trial Control Settings. This will confirm your selection. Notes - The Tapping Stimulus is listed under Device features when you select DanioVision DVOC-004x/T in step 2. - If you upgraded from an older version of EthoVision XT and you use an experiment created in the older version as a template for a new one, the DanioVision detection method is not available. Therefore, it is recommended to create a new experiment with the newest version and use this as a template (File > New From Template > Use a custom template). - If you upgraded an experiment from an older EthoVision XT version, do not change the Trial Control Hardware Settings in the Experiment Settings. Leave Noldus Mini USB-IO Box selected in the Hardware Interface window. Otherwise the Trial Control rules, for example to control the white light, may not work. - When you change the default state of the White Light Stimulus to Light on, note that the white light is only switched on in one of the following cases: - When you open the Trial Control screen. - When you open the Arena - Hardware Mapping window. - When you start a trial. For more information on Trial and Hardware Control, see the Reference Manual - Trial and Hardware Control in EthoVision XT. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - System Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-system-specifications Chapter: DanioVision System Specifications DanioVision DVOC-0041 Power Supply - Power requirements: 24 Volt DC, 2.0 Amp (max) - Mains adapter: Input 100–240 Volt AC, output 24 Volt DC, 3.0 Amp Camera - Brand, type: Basler acA1300-60gm - Interface: Gigabit Ethernet (RJ45 connector, CAT5e or higher) - Sensor: 1/1.8" Progressive Scan CMOS, monochrome - Max. resolution: 1280 x 1024 - Max. frame rate: 60 fps Lens - Standard lens: 12 mm Megapixel, C-mount, F1.4, includes IR pass filter - Optional lens: 8 mm Megapixel, C-mount, F1.4, includes IR pass filter Video Performance (H x V Pixels) - Default: 1280 x 960 at 30 fps (in combination with 12 mm lens) - Optional: - 640 x 480 at 60 fps (in combination with 12 mm lens) - 800 x 600 at 60 fps (in combination with 8 mm lens) Maximum frame rates as measured in 96 well plate setup. Backlight Unit - Type: Combined infrared (IR) and white light array - Infrared wavelength (typical): 950 nm - White light color temperature (typical): 5500 ºK - White light intensity range: 0 to ±10,000 lux (measured directly at the bottom of the water basin) White light level is controllable via USB (EthoVision XT). According to published research, zebrafish are sensitive to infrared light, though not above 910 nm. See Shcherbakov et al. 2013, PLoS ONE (5): e64429. The IR light provided by DanioVision is therefore unlikely to affect the fish's behavior. Note: If you set the Low Light switch to L (low), the highest light level (100%) is around 20 lux. Note: Light intensity in DVOC-0041 can be set higher than in DVOC-0040. You may want to replicate light conditions set in DanioVision DVOC-0040 in a new experiment with DanioVision DVOC-0041. For example, if you set light intensity to 50% in DanioVision DVOC-0040, this gave 2950 lux. The equivalent percentage to set in DanioVision DVOC-0041 is (2950/5300) x 50 = approximately 28%. Multi Basin - Water inlet, water outlet, and overflow - Basin size: 158 x 132 mm - Supports ANSI/SBS compatible micro plates (L = 127.76 ± 0.5 mm (5 1/32" ± 1/64"), W = 85.48 ± 0.5 mm (3 23/64" ± 1/64")) with maximum height of 27 mm (1 1/16") - Supports Petri dishes up to 90 mm in diameter - Temperature sensor supporting the use of Noldus DVTCU (Temperature Control Unit) Water Connections - Water inlet/outlet: Tube fitting 8 mm - Water overflow: Tube fitting 10 mm Tubes Included - 1.5 m Clear PVC Hose, 8 mm OD, 5 mm ID — water inlet (green color marked) - 1.5 m Clear PVC Hose, 8 mm OD, 5 mm ID — water outlet (yellow color marked) - 1.5 m Clear PVC Hose, 10 mm OD, 8 mm ID — water overflow (red color marked) PC Interface - Interface: USB-2 compatible External I/O - TTL input/output (4x modular RJ45 connector): - 4 x 2 TTL input - 4 x 2 TTL output - TTL expansion port 1: - 4 x TTL output (open collector output) - 1 x input camera - 1 x output camera - TTL expansion port 2 (1x modular RJ45 connector): - 8-pin feed through System Start-Up Time - Cold start: ~15 minutes Dimensions - Closed position: 61 x 32 x 46 cm (24 1/64" x 12 19/32" x 18 7/64") (h x w x d) - Door opening: 36 x 29 cm (14 11/64" x 11 27/64") (h x w) Weight - 15 kg excluding power supply, external tubes, and cables Cleaning the DanioVision Observation Chamber We recommend using a proprietary glass-cleaning fluid to clean the outside of the DanioVision Observation Chamber. Declaration of Conformity See the Declaration of Conformity documentation included with your unit. DanioVision Tapping Device Power - Power requirements: 24 Volt DC, 0.4 Amp (max) Features - Controlled from EthoVision XT 10.1 or later with selectable stimulus intensity (1–8) - Delivers a discrete 'tap' to the well plate holder - Maximum tapping rate of ±3 taps per second Connectors - Molex 2 pin — Power (24V) - Molex 4 pin — From Tapping Device to control box - Multi connector (blue) — For TTL control signal Dimensions - Tapping Device (including aluminum bracket): 6 x 24 x 7.5 cm (2 23/64" x 9 29/64" x 2 61/64") (h x w x d) - Control box: 2.5 x 10 x 6.5 cm (63/64" x 3 15/16" x 2 9/16") (h x w x d) Weight - ~300 g (Tapping Device, bracket, and control box) Compatible DanioVision Chambers - DVOC-0040 - DVOC-0041 If not pre-assembled in the DVOC-0041, the package includes mounting material. DanioVision Toplight Unit White Light - Intensity: >30,000 lux at 25 cm distance (well plate), 1584 lm - Color temperature: 4000 K - Array: 408 LEDs - Max. voltage: 18 Volt Red Light - Luminous flux: 192 lm - Wavelength: 623 nm - Array: 252 RGB LEDs - Max. voltage: 24 Volt Green Light - Luminous flux: 384 lm - Wavelength: 525 nm - Array: 252 RGB LEDs - Max. voltage: 24 Volt Blue Light - Luminous flux: 240 lm - Wavelength: 470 nm - Array: 252 RGB LEDs - Max. voltage: 24 Volt Unit Dimensions - 270 x 220 x 30 mm Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - The Daniovision Tapping Device URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-the-daniovision-tapping-device Chapter: DanioVision Introduction Larval stage zebrafish display a robust startle response, which is mediated by neural pathways similar to that in higher vertebrates. With the DanioVision Tapping Device you can evoke a startle response in zebrafish larvae. How the Tapping Device Works The DanioVision Tapping Device is based on an electromagnetically inductive coil wound around a metal core. The core is made of two parts, a fixed one and a plunger connected to a push pin. When a current flows in the Tapping Device, magnetic force is created between the plunger and the core, causing the plunger and the push pin to quickly move forward. The pushpin hits a metal plate attached to the basin in which the well plate is kept. When deactivated, a spring makes the plunger resume its position. How You Control the Tapping Device With the Trial and Hardware Control module of EthoVision XT you can plan when to activate the Tapping Device during a trial. For example, activate the Tapping Device 10 times at intervals of two minutes. Noldus Test Results: A Summary - In both light and dark conditions, the Tapping Device is capable of inducing a startle response in animals of 3 dpf and older. - It is in principle possible to design experiments where the animals are subject to stimuli of different intensity. You can set the tap intensity in EthoVision XT. - There is no evidence that the startle response measured by EthoVision XT depends on light conditions and location of the subject in the well plate. See also the white paper Using the DanioVision Tapping Device, which you can download from our web site. Important: We advise you not to compare the results between two DanioVision Observation Chambers provided with the Tapping Device. Slight differences in the position of the Tapping Device may result in differences in the actual stimulus intensity, all else being equal. Install the DanioVision Tapping Device If you order the Tapping Device together with a DanioVision Observation Chamber, the Tapping Device is already installed. In all other cases: - Open the lid of the DanioVision Observation Chamber, and remove the bench plate. - Remove the two bolts from the aluminium plate at the bottom of the chamber. Make sure that the backlight box does not move. Tip: Use a pencil to mark the exact position of the backlight box on the frame so that you can place it in that position if it accidentally moves. - Put the metal frame of the Tapping Device over the aluminium profiles, and fix the bolts with the supplied spring washers. Use both the already connected spring washers and the new ones. - Connect cables as indicated: - a — The cable with a 4-pin white connector comes from the Tapping Device. - b — The flat cable with a blue connector comes from the bottom of the DanioVision chamber. Raise the metal hooks, insert the connector, then lower the hooks to fix the connector. - c — The cable with 2-pin connector comes from the bottom of the DanioVision chamber. - Attach the control box to the aluminium profile at the front side of the observation chamber. - a — Insert the screw in one of the holes at the sides of the control box. - b — Attach the spacers and the sliding nuts to the screw. - c — Insert the sliding nuts into the profile, and turn the screw. - Put the bench plate back into place and fix the four screws. Set Up the Tapping Device in EthoVision XT Make sure that the DanioVision Observation Chamber is connected to your EthoVision XT computer. Experiment Settings Under Trial Control Hardware, click Settings. In the Hardware Interface window, select DanioVision DVOC-004x/T. Arena Settings Note: If you created an experiment with a pre-defined template and selected an arena template for DanioVision with the Tapping Device (DanioVision DVOC 004x/T), the Tapping Stimulus has been assigned automatically to the arenas. The steps below are then not necessary. - In the Arena Settings pane click Arena - Hardware Mapping and then click the Arena - Hardware Mapping button. - Click Add Device. Under Device Type, select Tapping Stimulus. Under Arena 1 select Tapping Stimulus. - To test the Tapping Device, select the cell under Arena 1 and click Test. Trial and Hardware Control Settings - Open the Trial Control Settings containing the protocol in which you want to insert the Tapping Stimulus. Under Actions - Hardware click the button next to Tapping Stimulus. - In the Hardware Action window specify the Intensity Level (1–8). Click Test to get an impression of the tap intensity. - Click OK and insert the Action box in your Trial Control protocol. - Test the protocol before carrying out the real trials. Important: Allow at least 300 milliseconds between two consecutive tapping events. To do so, place a Time Condition box that specifies this time between two Tapping Stimulus Action boxes. Analyze the Response to the Tapping Stimulus You can analyze the startle response by looking at dependent variables like Activity, Distance Moved, or Acceleration (State) immediately before and after the administration of the stimulus. In the following example, we examine the Total Distance Moved in the 1-second periods immediately before and after the tapping stimulus command was given. We expect that the total distance moved increased from "before" (assumed to be a baseline) to "after". The stimulus command was given at exactly 1 minute after the start of the trial. - In the Data profile define two Nesting time intervals, one from 00:59.00 to 01:00.00, the other from 01:00.00 to 01:01.00. Each of the resulting Nest boxes is connected to a separate Results box. - In the Analysis profile define Distance Moved. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - The Daniovision Toplight Unit URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-the-daniovision-toplight-unit Chapter: DanioVision The DanioVision Toplight Unit This manual explains the setup and operation of the DanioVision Toplight (type DVTL-0020) for the DanioVision Observation Chamber DVOC-0041. Note: The DanioVision Toplight Unit is an add-on to DanioVision; it does not come with a standard DanioVision system. For the specifications, see the DanioVision Toplight Unit specifications section. Connect the Toplight Unit Components - DanioVision Observation Chamber with built-in Toplight Unit. - Desktop power supply, TTL-to-28V interface and cabling. Operation With this setup, two of the LED colors, or the white light can be switched on and off from EthoVision XT. The TTL-to-28V interfaces enable switching the power from the desktop power supply. Note: Whenever you would like to use all three colors (R-G-B) within one experiment you will need a second TTL-to-28V interface. Important: The LEDs get hot during operation. Please let the ceiling light cool down before touching it. Important: Do not exceed the maximum specified voltage for each color as doing so may damage the LEDs. Setup for the White Light - Desktop adjustable supply set to max 18 V for white light. - TTL cable to free TTL port on the DanioVision Observation Chamber's (DVOC) back panel. - White light cable plugged in. - Top light cable from the DVOC's back panel. - Main LED power cable. Connect the Components The LED power cable (coming from the back of the DVOC) has 4 connectors, one for each LED color. The connectors belonging to the appropriate colors should be connected to the TTL-to-28V interface on outputs 1 and 2. The TTL network cable (green) should be connected between the TTL-to-28V interface and port 1 on the DVOC. A main power cable connects the desktop power supply to the input of the TTL-28V interface. - USB cable to EthoVision XT computer. - TTL cable running to TTL-to-28V interface. - LED power cable. Operate the Power Supply On the power supply the voltage can be set which determines the amount of light that the LEDs emit. The voltage may not exceed the maximum voltage for each LED color. This is 24V for the Red, Green and Blue LEDs and 18V for the white LEDs. Important: Higher voltages may damage the LEDs. Before connecting to the mains outlet, check that the mains voltage matches the voltage setting of the power supply. To power up, press the power button. To Adjust the Voltage Turn the Voltage knobs for coarse and fine adjustments. Or when in presence of one knob, press once for coarse adjustments, and press once more for fine adjustment. The actual output voltage can be read from the display. Both Current knobs can be used to set a current limiting value (maximum current). This feature is not needed; just set to the maximum level (turn full clockwise). If not set properly, the supply may come in Constant Current mode (CC) and limit the output voltage. It is good practice to first set your desired voltage before actually connecting the main LED power cable to the supply. For more information, see the supply manual. Change the Lights To Switch Between Red, Green and Blue To change between colors, simply unplug the current connector of the LED power cable from the TTL-to-28V interface and plug in the correct one. Each connector is labeled. To Switch Between White and Colors If you want to switch from RGB to white light (or vice versa), turn the complete unit in order to have the right LEDs facing down towards the well plate. The RGB LEDs and white LEDs are mounted on the opposite sides of the same plate and can be identified by the labels white and rgb. - Cover the lens bracket with some protective material. - Untighten both left and right round black knobs to enable the unit sliding down a few centimeters, just below the camera. - Pull the unit out and turn it upside down (facing the preferred LEDs down). Important: Be careful not to twist the cable at the back. Unplug both connectors temporarily to prevent this from happening. - Insert the unit and slide it up again. - Tighten both round knobs. Configure EthoVision XT to Control the Top Lights - Start EthoVision XT and create a new experiment using a template (File > New from Template). During the guided setup, choose Live Tracking, Zebrafish Larvae, DanioVision [with the type of well plate you use]. - Choose Setup > Experiment Settings. Under Trial Control Hardware, select Use of Trial Control Hardware and choose the appropriate options. Choose the TTL port of the DVOC that you connected. You can rename Device ID to something like "Ceiling Light". - Choose Setup > Arena Settings. After calibrating and drawing the arenas, click Arena Hardware Mapping. Click Add Device and follow the on-screen instructions. You can rename the text under Device Name to something like "Ceiling Light". Under A1, select the device, then click OK. - To test the light, select Output 1 High or Output 2 High from the Command menu and click the Test button. To turn them off, select Output 1 Low or Output 2 Low. Program the Top Lights in EthoVision XT Choose Setup > Trial Control Settings. Example: After 1 minute during the trial, switch the light on, then after 10 seconds switch it off. - Under Conditions, choose Time to create a time condition (e.g. Wait 1 minute, Wait 10 seconds). - Under Actions, choose Custom Hardware to define commands (Switch on/off). This can be done for both output 1 and output 2. - Remember to connect all boxes with the start-stop procedure. Create Routines With the Subrule function you can create routines to switch the lights on and off in repeated sequences. For more information, see the Reference Manual - Trial and Hardware Control in EthoVision XT. Also adjust the Detection Settings (Setup > Detection Settings) before running the trials. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Trial Control Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-trial-control-settings Chapter: DanioVision Trial Control Settings Choose Setup > Trial Control Settings > Default or White Light Routine. The template experiment contains two examples of trial control settings: - Default - The default Trial Control Start-Stop rule. Use these settings to start and stop tracking manually. - White Light Routine - Use these settings when you want to provide a light stimulus during the trial. Ten minutes after the start of the trial, the DanioVision white light immediately turns on to 100% intensity for 10 minutes, then the white light immediately turns off for 10 minutes. This sequence of actions is repeated twice, using a sub-rule, after which the trial stops. Maximum Trial Duration (Recommended) - If you record video: 60 minutes. - Without recording video: 72 hours. Set the duration of your trials in the Maximum Trial Duration pane or in the Start-Stop trial rule, by placing a Time condition immediately before the Stop track action box. Create Your Own Trial Control Procedure You can adjust these trial control settings to your own needs. The procedure below describes how to define Trial Control Settings from scratch. For more information on Trial Control Settings: - Trial Control in the EthoVision XT Help. - The Reference Manual - Trial and Hardware Control in EthoVision XT, which you can find under Noldus > EthoVision XT 16 Other Documentation. Controlling the DanioVision White Light With the Trial Control Settings you can control the DanioVision White Light. Example: After a 24-hour dark period in the DanioVision Observation Chamber, you want to expose your animals to alternating periods with the white light on and off, in which the light-on periods also vary in intensity. To program this schedule: - To open the Trial Control, in the Experiment Explorer, right-click Trial Control Settings, select New, enter a name and click OK. The Trial Control screen opens with the default Start-Stop trial control rule. - Click the Condition Time box with "Infinite time" and press Delete. - In the Components pane, under Actions - Hardware, click the button in the Add column next to White Light Stimulus. Select Create a new action. - In the Hardware Action window, set the following: - Action name - Enter a description of the action, for example "Light on 100%". - Action to perform - Select Light on from the list. - Intensity level - Select the maximum intensity level of the light, in percentage (0-100%) or in Steps. - Fade duration - For example, with an Intensity level of 50% and a Fade duration of 2 seconds, the white light gradually turns on until 50% of its maximum intensity in 2 seconds time. - Click OK and insert the Action box in the sequence. - In the Components pane, under Conditions, click the button next to Time. Click Create a new action and click OK. In the Time condition window, you can set the following: - Condition name - For example, enter "Wait 15 mins". - Condition is met - For the option After a time of, enter "15 mins". - Click OK and insert the Condition box in the sequence. - Repeat steps 3-6 to complete the Trial Control rule: - Add a Hardware Action box with White Light - Off and a Condition Time box with "After 10 mins". - Add a Hardware Action box with White Light - On 50% and a Condition Time box with "After 10 mins". - Add a Hardware Action box with White Light - Off and a Condition Time box with "After 10 mins". - Add a Hardware Action box with White Light - On 100% and a Condition Time box with "After 15 mins". - Insert all the boxes in the correct order into the sequence and make sure you connect all boxes. Tip: Combinations of Action and Condition boxes that are repeated in a sequence can be replaced with a sub-rule. This is especially handy when the entire sequence is repeated multiple times during a trial. For example: [White Light - On - 100%] > [After 10 min] > [White Light - Off] > [After 10 min]. For more information on using sub-rules, see the Reference Manual - Trial and Hardware Control in EthoVision XT. Notes - Click Test in the Hardware Action window to test the hardware action. - Click Reset to reset all Hardware Action windows in your Trial Control procedure to their default values. For example, a White Light action is set to off by default; however, if you set the default White Light to on, then after clicking Reset the White Light switches on. - To analyze data in the light or dark period, first create a Data Profile that specifies that period using Trial Control State, then calculate the statistics. Use an External Command If you want to use an external command, for instance to play a sound during the trial, the command is executed for each arena. For example, the command to play the sound is repeated 96 times for a 96-arena experiment. To prevent this from happening, put a condition before the External command box which will only become true for one of the arenas, for example Arena 1. In the Arena Settings, create a zone in Arena 1 and call it "Zone 1A". Make the zone as large as the arena. In the Trial Control Settings, make a condition such as "Is subject in Zone A?", followed by the external command. Make sure that the sequence does not interfere with the rest of the Trial Control rule. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - Version Dvoc-0041 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-version-dvoc-0041 Chapter: DanioVision What Is DanioVision? Information in this document is subject to change without notice and does not represent a commitment on the part of Noldus Information Technology BV. The software described in this document is furnished under a license agreement. The software may be used or copied only in accordance with the terms of the agreement. Copyright © 2021 Noldus Information Technology BV. All rights reserved. No part of this publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any other language in whole or in part, in any form or by any means, without the written permission of Noldus Information Technology BV. EthoVision is a registered trademark and DanioVision is a trademark of Noldus Information Technology BV. Version: DVOC-0041 Date: March 2, 2021 For: EthoVision XT version 16 Noldus Information Technology BV International Headquarters Wageningen, The Netherlands Telephone: +31-317-473300 E-mail: info@noldus.nl Contents - What Is DanioVision? - DanioVision - DanioVision Add-Ons - For More Information - What's New in DanioVision - DanioVision Observation Chamber - EthoVision XT - Set Up DanioVision - Connections - Connect DanioVision - Set Up a Water-Flow System - Light and Switches - Install EthoVision XT - Install the Network Card for the DanioVision Camera - Configure the DanioVision Camera - Check the DanioVision System - Check the Camera Lens - Configure the Anti-Condensation Mechanism - Configure the DanioVision White Light - Place Well Plates and Petri Dishes - Control Evaporation - Set Up EthoVision XT - Prerequisites - Create a DanioVision Experiment - Experiment Settings - Use of Trial Control Hardware - Arena Settings - Define the Arenas - Arrange the Arenas - Assign the Stimuli to the Arenas - Trial Control Settings - Create Your Own Trial Control Procedure - Detection Settings - One Subject Per Enclosure - Activity Analysis - Multiple Subjects in the Same Enclosure - Acquire Data - Acquire Data Live - Acquire Data Live and Record Video Simultaneously - Record Video, Then Acquire Data - Drain and Clean the System - The DanioVision Tapping Device - Introduction - Install the DanioVision Tapping Device - Set Up the Tapping Device in EthoVision XT - Analyze the Response to the Tapping Stimulus - The DanioVision Toplight Unit - Connect the Toplight Unit - Operate the Power Supply - Change the Lights - Configure EthoVision XT to Control the Top Lights - Program the Top Lights in EthoVision XT - The DanioVision Optogenetics Add-On - Introduction - Install the Dichroic Mirror in DanioVision - The Pulser Software - The LED Controller - Configuration 1 - Without the Pulser - Configuration 2 - With Pulsers - Experiment Settings - Arena - Hardware Mapping - Trial Control (No Pulser) - Trial Control (With Pulsers) - Configure the COM Port for Each Pulser - Data Preparation - Smooth the Tracks - Select Data - Analyze Data - Analysis Profiles and Options - Calculate the Statistics - Appendix A: Open the DanioVision Casing - Tools You Need - Bench Plate - Top Casing - Sides and Back Casing - Connector Panel - Adjusting Lid Friction - Appendix B: Fine Camera Adjustments - Centering the Well Plate Horizontally - Centering the Well Plate Vertically - If the Well Plate Looks Rotated - Example of a Good Video Image - Appendix C: Additional Hardware - Expansion 1 - Expansion 2 - Appendix D: System Specifications - DanioVision DVOC-0041 - DanioVision Tapping Device - DanioVision Toplight Unit - Declaration of Conformity Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - What Is Daniovision? URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-what-is-daniovision Chapter: DanioVision What Is DanioVision? DanioVision™ is a system for high throughput tracking of zebrafish larvae in multi-well plates. It consists of: The DanioVision Observation Chamber (DVOC-0041) This chamber contains a transparent holder with backlight that fits an ANSI SBS compatible multi-well microtiter plate, infrared (IR) and white light sources (underneath the microtiter plate), and a Gigabit Ethernet (GigE Vision) video camera. The optical design provides a stable and undistorted top view of each well and a controlled and constant environment within the observation chamber. For technical specifications and for cleaning instructions, see System Specifications. Tip: You can find your DanioVision version number on the label at the back of the chamber. EthoVision® XT Video-tracking software with the Multiple Arenas Module and Trial & Hardware Control Module. Using Trial & Hardware Control, you can adjust the white light stepwise based on time or behavior of your fish. You have the option to connect external devices, such as sound or shock generators. Note: DanioVision DVOC-0041 works with EthoVision XT 10.1 or newer. DanioVision Add-Ons DanioVision Temperature Control Unit With the DanioVision Temperature Control Unit you can set up a water flow at constant temperature underneath the well-plate. For details, see the Reference Manual - DanioVision Temperature Control Unit DV-TCU, which you can download from the Noldus website. DanioVision Tapping Device With the DanioVision Tapping Device you can trigger a startle response in zebrafish. For details, see The DanioVision Tapping Device in this manual. DanioVision Toplight Unit With this add-on you can generate top-down light stimuli in your experiments. Four types of light are available: white, red, blue, and green. For details, see The DanioVision Toplight Unit in this manual. DanioVision with Optogenetics DanioVision can be provided with one to three LEDs that illuminate the well plates based on your Trial Control protocol. The Optogenetics add-on allows you to accurately control and time the application of optogenetic stimulation to up to 96 individuals simultaneously (one for each well in a 96-well plate). For details, see The DanioVision Optogenetics Add-On. Custom Solutions As research evolves, so do research needs. If you are interested in a custom solution, don't hesitate to contact us. A few recent examples of custom solutions include: - Light-Dark Grid: Commonly used to investigate anxiety behavior in zebrafish. The grid is placed underneath the well plate (available for 6, 12, 24, 48, or 96 wells) and creates a dark and light half in each well. The grid is IR light translucent, leaving the tracking of the zebrafish unaffected. - High-Speed Camera: DanioVision is equipped with a camera capable of 1000 frames per second. The aim is to measure the startle response of larvae to a stimulus during a Pre-Pulse Inhibition test. - Split Basin: The DanioVision basin has been modified so that it receives water at two different temperatures. The aim of this solution is to measure temperature preference in zebrafish larvae. - Ultraviolet Toplight Unit: A modification of the Toplight Unit that shines UV light. Light intensity is controlled by EthoVision XT. - Turbo-Cooling TCU: A modified Temperature Control Unit which keeps water at a constant temperature of 12° in a room where temperature is about 25°. For More Information Manuals - The EthoVision XT Help (press F1 in EthoVision XT). - The Reference Manual - Trial and Hardware Control in EthoVision XT. You can find this manual under Noldus > EthoVision XT 16 Other Documentation. - The Reference Manual - DanioVision Temperature Control Unit DV-TCU. You can find this manual on the Noldus website at my.noldus.com. Note that you have to log in to access the downloads page. - Additional manuals are available on the EthoVision XT installation USB stick. Sample Experiments On the EthoVision XT download page you can find sample experiments that make use of DanioVision. Browse to my.noldus.com, then under Downloads choose Sample Projects, then EthoVision XT. Experiment Templates EthoVision XT contains templates that help you set up an experiment with arenas, analysis profiles, and other elements already defined. See Create a DanioVision Experiment for more details. References See the Noldus web page of selected publications for relevant references. Support Center If after reading this manual you still have questions, please contact the Support Center at my.noldus.com. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0041 - What’S New In Daniovision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0041-whats-new-in-daniovision Chapter: DanioVision What's New in DanioVision DanioVision Observation Chamber For Users of DanioVision DVOC-0040 The white light LED array has been improved. The white light can be set to higher intensity. For Users of DanioVision DVOC-0030 The housing has been completely redesigned. You open the observation chamber by tilting the lid along the top side. This way you have easier access to the camera and opening/closing the lid produces less vibration. Note: The DanioVision Observation Chamber is designed to block light from the outside. However, it cannot be guaranteed that it is completely dark inside the chamber. For experiments that require absolute darkness (like experiments with day-night rhythms), place the DVOC in a dark room. The housing is now larger to create more space for accessing the video camera or adding devices. For this purpose, the housing can be disassembled more easily than before. The basin has been redesigned. It has now a more flexible retainer that can hold a wider range of well plates. DanioVision can now work with ANSI, SBS compatible micro plates (L = 127.76 ± 0.5 mm, W = 85.48 ± 0.5 mm) with a maximum height of 27 mm, and with Petri dishes with a diameter up to 90 mm. To place small well plates and Petri dishes, slide the bridge to a new position in such a way that the well plate/Petri dish is in the middle of the camera view. The mechanism for moving the Fresnel lens located above the well plate has been improved. You can now move the lens all the way out of the camera view when you need to place containers higher than 27 mm. Communication between DanioVision and EthoVision XT has improved via a new version of the hardware interface software. All four TTL lines TTL 1 to TTL 4 are available for communication with external devices. For connecting custom hardware, additional expansion connectors are available. The white light is now dimmable at very low intensity, without the need to operate the low light switch located behind the camera. The DanioVision Tapping Device has been designed to provide DanioVision with a reliable device which evokes a startle response in zebrafish larvae. Note: The DanioVision Tapping Device is a separate add-on to the DanioVision system. For Users of DanioVision DVOC-002x - The DanioVision camera is now a Gigabit Ethernet (GigE) digital camera connected to the EthoVision XT computer through a 1-Gb Ethernet card. With a GigE camera, tracking can be done with a higher sample rate and higher resolution. - The intensity of the infrared LED back-lighting has been increased. This results in a more even distribution of back-lighting over the well plate and a higher contrast between animals and the background, making it easier to configure the detection settings. - It is possible to use very low light levels for the DanioVision white light in addition to the default, standard white light levels. The standard white light levels range from ± 20 to ± 10000 lux. The low white light levels range from 0 to ± 20 lux. - The anti-condensation mechanism can now be easily switched on and off, or set to automatic. The anti-condensation mechanism prevents the lens from condensing during an experiment. EthoVision XT The following lists the main additions relevant to DanioVision. For a complete list of new features, see the EthoVision XT Help "What's New" section. For Users of EthoVision XT 15 - Improved Subject Contour Filter: In the Detection Settings, a second Erosion filter is added to the Subject Contour settings. This filter is added after the pre-existing Erosion and Dilation, and improves detection in some difficult situations. For more information, see Advanced Detection Settings: Subject Contour in the EthoVision XT Help. - Trial Control Variable in the Analysis: In the Analysis profile you can now select the Trial Control variables used in the Trial Control protocols. This allows you to analyze or visualize its values just like other dependent variables. You can also visualize a Trial Control variable in the Integrated Visualization for testing purposes, for example, to check that a variable gets the expected value at a specific time in the trial. Note: The deep learning functionality in EthoVision XT 16 is not designed specifically to track fish larvae. In DanioVision experiments, always choose Contour-based as the body point detection technique. For Users of EthoVision XT 14 - Heatmaps with Time Scale: Heatmaps are plotted together with a time scale. This helps you quantify the time that subjects spend in specific locations. Source: DanioVision DVOC-0041 Reference Manual, Noldus Information Technology --- ## DanioVision DVOC-0050 - Acquire Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-acquire-data Chapter: DanioVision Acquire Data There are three ways of acquiring data with your DanioVision system. For every option it is possible to run single trials, but it is also possible to carry out batch acquisition. - Acquire data live. The larvae are tracked as they move in their wells. - Acquire data live and record video simultaneously. The larvae are tracked as they move in their wells while at the same time a video is recorded. This gives you the opportunity to redo the tracking if necessary, either per trial or using batch acquisition. - Record video, then acquire data. You record a video first and then track the subjects offline from the video. Please note that if you only record video with EthoVision XT, Trial Control is not applied. So, for example, the white light is not switched on and off if you only record video. Before you start acquiring data, make sure you have carried out all the necessary checks of the system. Notes: - The DanioVision Observation Chamber is designed to block light from the outside. However, it cannot be guaranteed that it is completely dark inside the chamber. For experiments that require absolute darkness, place the DVOC in a dark room. - Important: In long experiments, evaporation may occur for both the wells in the plate and the basin. Check the wells every 24 hours and if necessary, refill them. Refill the basin every 2–3 days using the Basin Refill tool. Acquire Data Live - Make sure the camera is connected to the EthoVision XT computer and that Live tracking is selected as Video Source in the Experiment Settings. - Optionally, plan your trials in the Trial list and select the Arena settings, Detection settings, and Trial Control settings for each trial. - Choose Acquisition > Open Acquisition. - If no trials are planned, click the New trial button in the Playback Control window or press Ctrl+F3. - In the Acquisition Settings pane, select whether you want to track only the next planned trial or whether you want to track all planned trials without having to start the next trial manually. If you want to track all planned trials, specify the inter-trial interval. Enter a time long enough to be able to change well plates. When you change the well plate between trials, you can start the next trial without waiting for the inter-trial interval to be reached by clicking the Skip remaining interval button in the Playback Control window. - Select whether you automatically want to start the analysis after the tracks are acquired. If that is the case, first define your dependent variables in an Analysis Profile. Optionally, first make a Track Smoothing profile and a Data profile to make a selection out of your data. - Select whether you want to use the Track Smoothing profile, Data profile, and Analysis profile that are highlighted in blue in the Experiment Explorer for analysis, or whether you want to run analyses for all possible profile combinations. In the latter case, first delete all profiles you do not need for analysis. If you want to carry out analyses for only a selection of profiles, deselect the check box Auto-start analysis and carry out batch analysis after acquisition. - Put the well plate into the DanioVision chamber. - Click the Auto-detect button. A Re-initialize window with a timer appears. Wait until it disappears. Important: Use the Auto-detect button every time you change a well plate. - To start the trial, click the Start trial button in the Playback Control window or press Ctrl+F5. - To stop the trials, wait until Trial Control automatically stops the trials. To stop acquisition manually, click the Stop trial button in the Playback Control window or press Ctrl+F6. If you stop the trials manually, automatic analysis does not start. Also, for batch analysis, the next trials are not started if you stop a trial manually. Note: The recommended maximum trial duration when acquiring live without recording video is 72 hours (3 days). Acquire Data Live and Record Video Simultaneously To save video when doing tracking, follow the procedure above, with the difference that you select the check box Save video in the Acquisition Settings pane. If you realize tracking was not optimal, you can redo tracking from the acquired video. Note: The recommended maximum trial duration when acquiring live and recording video simultaneously is 60 minutes. Longer trials produce video files of excessive size that are more difficult to manage. Furthermore, if one large video gets corrupted then you lose more data. Record Video, Then Acquire Data If you use the option Save video only, track later, Trial Control is not applied, so you cannot control the white light of the DanioVision Chamber with EthoVision XT. To save video when doing tracking, follow the procedure for acquiring data live, with the difference that you select Save video only, track later in the Acquisition Settings pane. Also make sure that the trial is time limited, either with a time condition in the Trial Control start-stop rule or with a Maximum Trial Duration setting. Next, you can acquire data using batch acquisition. Plan your trials in the Trial list and specify the video and optionally Arena Settings, Trial Control Settings, and Detection Settings for each trial. Note: The recommended maximum trial duration when recording video is 60 minutes. Longer video recordings produce files of excessive size that are more difficult to manage. Furthermore, if one large video gets corrupted then you lose more data. Drain and Clean the System At the end of the experiment, we recommend removing all the water from the basin and the tubes. If you use the Temperature Control Unit (DV-TCU), set it to Fill/Drain and follow the instructions in the relevant section of this guide. To prevent the growth of algae in the system: - Always drain the system after use. - Do not expose the system and the tubes to sunlight. Source: DanioVision DVOC-0050 Reference Manual - Acquire Data, Noldus Information Technology --- ## DanioVision DVOC-0050 - Analyze Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-analyze-data Chapter: DanioVision Analyze DanioVision Data Analysis Profiles and Options Analysis Profiles in the Template Experiment - Distance, Time & Movement - Contains the dependent variables Distance moved, Velocity and Movement. - Path Shape - Contains the dependent variables Heading, Turn angle, Angular velocity and Meander. - Rotation - Contains two instances of the dependent variable Rotation, to count the number of clockwise and counterclockwise rotations. For more information on these and other dependent variables, see Dependent Variables in Detail in the EthoVision XT Help. Also see the chapter Analysis of Trial Control data in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Analyze Intervals Make sure you have defined a Data profile which specifies the intervals you are interested in. Next, in the Analysis profile choose your variables (e.g. Distance moved). Then visualize the data and run analysis. Activity Analysis You can also use the dependent variable Activity state. This variable is only available when you selected Activity analysis in the Experiment Settings. With Activity state you can calculate how long and how frequent your subject has been in different activity states. These states depend on the total pixel change within the arena between a sample and the previous sample. It is important that all defined arenas have exactly the same size. The number of states (two to four) and their thresholds are user-defined. Analyze Convulsions To analyze convulsions, you can use several variables, such as Velocity, Movement, Activity and Mobility. Method 1 - With Movement In this example, seizures are frequently characterized by fast zig-zag movements that last up to two seconds. To discriminate between seizure and no seizure, we use Movement, a variable based on the current (smoothed) velocity of the fish. - Create an instance of Movement that is active when the velocity exceeds a specific threshold value. To get an idea of what the threshold should be, plot the values of velocity with an averaging interval of 5. Play the video until a seizure occurs in one of the wells, and look at the values of velocity for that subject. In this example, velocity is higher than 15 mm/s. Check this in other wells and in a few videos and try to find an optimal cut-off value. - Create a Free interval that has the following settings: - Start Criterion: Dependent Variable; Select Variable: Movement. Set Movement with a Start velocity threshold around 1.5 cm/s and a Stop velocity threshold a bit lower (say 1.3 cm/s). Select Statistic: Current Duration of Moving and choose a value like >= 0.5 s. This way you filter out short swim bursts that are less likely to be seizures. - Stop Criterion: same as above, with the difference that you select Current Duration of Not Moving >= 0.5 s. The free interval ends when the fish has been Not Moving for half a second. - The resulting free interval captures the period of time when the velocity of the subject is higher than the threshold value. Tip: To exclude sudden changes in velocity in the middle of a seizure, use an Averaging interval when defining Movement. - Calculate the necessary statistics, like the average duration of the seizures, the number of occurrences, etc. Method 2 - With Mobility Create a Mobility variable in your Analysis profile. Start with setting a High Mobility Threshold to a high value like 95%, and an averaging interval of 2. Similar to Movement, Mobility should only capture the periods of time when the subject is very active because of the seizure, excluding normal swimming activity. Compare the scores of Highly Mobile with those of convulsions obtained manually. Adjust the mobility thresholds until they match. Heatmaps To create a heatmap of the subjects' position, choose Analysis > Results > Plot Heatmaps. Choose the Data profile from the list on the toolbar to create a heatmap based on the data selected. Notes: - There is one scale for all the wells in the well plate. You cannot create separate scales for each well, unless you select single wells in the Data profiles (one well for each Results box). - For DanioVision experiments, the Group Means button is not available. - For more information on heatmaps, open the EthoVision XT Help and browse to Visualize data > Plot heatmaps. Calculate the Statistics Procedure - Choose Analysis > Analysis Profile > New. - Add the dependent variables of your interest. For an overview, see Dependent Variables in Detail in the EthoVision XT Help. - In the Trial Statistics tab, choose the statistics you want to calculate per trial for that variable. If you created groups of tracks in the Data profile, select additional statistics in the Group Statistics tab. - Repeat steps 2-3 to add more dependent variables. - Choose Analysis > Results > Statistics & Charts. Choose the Data Profile from the list on the toolbar and click the Calculate button. - The results appear on the screen. The Trial Statistics tab shows the statistics per trial. The Group Statistics & Charts tab shows the statistics and charts from the summarized results of all trials. See Calculate Statistics in the EthoVision XT Help for details. - Optional: Click the Layout button and change the layout of the results table. Batch Calculations It is also possible to carry out multiple analyses with different filters, data profiles and analysis profiles. To do so, click the Batch button. Make your selection from the lists under Select the profile combinations to calculate and click Add. When done, click Calculate. To view a specific analysis result, select the options from the lists on the toolbar. For more information on batch statistics calculation, see Batch statistics calculation in the EthoVision XT Help. Source: DanioVision DVOC-0050 Reference Manual - Analyze Data, Noldus Information Technology --- ## DanioVision DVOC-0050 - Appendices - Opening The DanioVision Casing URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-appendices-opening-the-daniovision-casing Chapter: DanioVision Opening The DanioVision Casing Tools You Need A Phillips or (preferably) a Pozidrive screwdriver, size 2. Do not use electric screwdrivers. Removing The Bench Plate Remove the bench plate, for example, to install the Tapping Device and other custom hardware you want to place inside the DanioVision Observation Chamber. It is also helpful to remove the bench plate before opening the top casing. - Remove the four screws as indicated in the picture. - Remove the bench plate. Removing The Top Casing Remove the top casing, for example, when you need to replace the camera. - Optionally, remove the bench plate first, as this makes the following steps easier. - Remove the eight screws as indicated in the picture. Note that the screws located more internally are shorter than the others. Take note of which screw goes to which hole for when you put everything back in place. - Close the lid and lift the top casing. - When putting the top casing back in place, make sure that you insert the sides into the bottom casing as indicated in the picture. - Tighten all the screws. Removing The Sides And Back Casing Remove the sides and back casing to access the connector box, wirings, and internal tubings. In most cases you do not need to do so. - Remove the top casing as described in the previous section. - Place the DanioVision Observation Chamber just over the edge of the table and remove the three screws from the bottom plate nearest to the side of the chamber. Do not remove the other screws. - Repeat the previous step for the other side. - Remove the two screws at the back as indicated in the picture. - You can now lift the casing. Removing The Connector Panel To remove the connector panel at the back of the observation chamber, remove the four screws as indicated in the picture. Adjusting The Lid Friction You can adjust the friction of the observation chamber lid. If the lid falls down easily or opens with much friction, loosen or tighten the three screws per hinge, respectively. Fine Camera Adjustments Each DanioVision system is thoroughly checked and set to its optimal configuration. However, transport and handling of the system may sometimes cause slight changes in the camera position relative to the well plate, resulting in a sub-optimal video image. This section helps you restore the original settings. Centering The Well Plate Horizontally Follow these steps if the well plate is not centered horizontally: - Loosen the washer located behind the camera bracket, under the camera profile. - Turn the camera in the direction required until the well plate is in the middle of the camera view. - Tighten the washer to fix the camera in the new position. Centering The Well Plate Vertically If the camera is rotated forward or backward in its vertical plane, the video image may appear off-center vertically. - Loosen the two bolts at the sides of the camera profile. - Rotate the camera bracket forward or backward until the well plate is centered vertically in the video image. - Tighten the bolts. Correcting A Rotated Well Plate Follow the steps below if the margin of the well plate is not parallel to the margin of the video image: - Open the DanioVision Observation Chamber and locate one of the bolts at the side of the camera profile (either left or right). - Loosen the bolt using a 3-mm Allen key. - Gently move the camera bracket forward or backward until the well plate is in the correct orientation. When ready, tighten the bolt. Example Of A Good Video Image Check that the well plate fills the video image as much as possible, with the letters A–H and numbers 1–8 clearly visible. Set the camera lens to maximum aperture. The image is overexposed when no water is present. Tighten the three screws on the camera lens once the image is optimized. --- ## DanioVision DVOC-0050 - Appendices - System Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-appendices-system-specifications Chapter: DanioVision System Specifications DanioVision DVOC-0050 Dimensions - 61 x 32 x 46 cm (24 1/64" x 12 19/32" x 18 7/64") (H x W x D) in closed position - Door opening: 36 x 29 cm (14 11/64" x 11 27/64") (H x W) Weight - 15 kg excluding power supply, external tubes, and cables Power Supply - Power requirements: 24 Volt DC, 4.0 A (max) - Mains adapter: input 100–240 Volt AC, output 24 Volt DC, 4.0 A Camera - Brand and type: Basler acA1300-60gm - Interface: Gigabit Ethernet (RJ45 connector, CAT5e or higher) - Sensor: 1/1.8" Progressive Scan CMOS, monochrome - Maximum resolution: 1280 x 1024 - Maximum frame rate: 60 fps Lens - 12 mm 2 Megapixel, C-mount, F1.4, includes IR pass filter - Optional lens: 8 mm 2 Megapixel, C-mount, F1.4, includes IR pass filter. Note: this lens requires a 0.5 mm spacer ring. Video Performance (H x V Pixels) - Default: 1280 x 960 at 30 fps (in combination with 12 mm lens) - Optional: 640 x 480 at 60 fps (in combination with 12 mm lens) - Optional: 800 x 600 at 60 fps (in combination with 8 mm lens) Maximum frame rates as measured in a 96 well plate setup. Backlight Unit - Combined infrared (IR) and white light (White Light Stimulus) array - Infrared wavelength (typical): 950 nm. According to published research, zebrafish are sensitive to infrared light, though not above 910 nm (see Shcherbakov et al. 2013, PLoS ONE 8(5): e64429). The IR light provided by DanioVision is therefore unlikely to affect the fish's behavior. - White light color temperature (typical): 5500 ºK - White light level controllable with EthoVision XT. Intensity range: standard levels 0 to approximately 10,000 lux; low light levels (Low Light switch set to L): 0 to about 20 lux. Light level measured directly at the bottom of the water basin. Multi Basin - Water inlet, water outlet, and overflow - Basin size: 158 x 132 mm (6 7/32" x 5 13/64") - Supports ANSI/SBS compatible micro plates (L = 127.76 ± 0.5 mm, W = 85.48 ± 0.5 mm) with a maximum height of 27 mm (1 1/16") - Supports Petri dishes up to 90 mm (3 35/64") in diameter - Temperature sensor supporting the use of the Noldus DVTCU Temperature Control Unit Water Connections - Water inlet/outlet: tube fitting 8 mm - Water overflow: tube fitting 10 mm Tubes Included - 1.5 m clear PVC hose, 8 mm OD, 5 mm ID for water inlet (green color marked) - 1.5 m clear PVC hose, 8 mm OD, 5 mm ID for water outlet (yellow color marked) - 1.5 m clear PVC hose, 10 mm OD, 8 mm ID for water overflow (red color marked) PC Interface - Ethernet External I/O - TTL input/output (2x modular RJ45 connector): 2x 2 TTL input, 2x 2 TTL output - TTL Trigger Out (2x BNC connector): 2x TTL output System Start-Up Time (Cold Start) - Approximately 15 minutes Cleaning The DanioVision Observation Chamber - Outside of the chamber: use a proprietary glass-cleaning fluid or a detergent solution. - Inside parts (Fresnel lens, lens heater, etc.): use only a damp microfiber cloth with a mild detergent solution in warm or lukewarm water. Ensure the cloth is just damp and leaves no droplets on the surface. DanioVision Temperature Control Unit (TCU) Dimensions - 460 x 210 x 280 mm / 18.11" x 8.26" x 11.02" (L x W x H) - Hose connectors: 8 mm outer diameter tube Weight - 7 kg / 15.43 lb Electrical - Operating voltage: 24 V DC - Power consumption (average / maximum): 40 / 120 W - TTL port specs: 2 input / 2 output, max. 5 V / max. 5 V, open collector Operational - Temperature accuracy: ± 0.5 °C / ± 0.9 °F - Temperature set point range: 15–40 °C / 59–104 °F - Maximum heating capacity: at least 10 °C / 18 °F above ambient temperature (within the temperature set point range 15–40 °C / 59–104 °F) - Maximum cooling capacity: 2.5 °C / 4.5 °F below ambient temperature (within the temperature set point range 15–40 °C / 59–104 °F) - Permissible water temperature range: 5–50 °C / 41–122 °F - Water capacity: approximately 350 ml / 11.83 oz - Pump flow rate – water: approximately 310 ml per min / 10.48 oz per min - Water filter type: 20 μm pore size, 1 inch diameter - Cooling liquid capacity: approximately 250 ml / 8.45 oz - Cooling liquid type: colored, anti-corrosive, anti-algae, PC-type cooling liquid - Pump flow rate – cooling liquid: approximately 1650 ml per min / 55.79 oz per min - Maximum height difference between DVOC and TCU: 1.3 m / 4.26 ft. Important: do not place the Temperature Control Unit higher than the Observation Chamber. - Noise level: average over all frequencies less than 35 dB; maximum peak of approximately 48 dB around 160 Hz Environmental Conditions - Permissible ambient temperature range: operating 10–35 °C / 50–95 °F; storage 5–65 °C / 41–149 °F - Permissible relative humidity: 20%–80% (non-condensing) DanioVision Tapping Device Dimensions - Tapping Device (including aluminum bracket): 6 x 24 x 7.5 cm / 2 23/64" x 9 29/64" x 2 61/64" (H x W x D) - Control box: 2.5 x 10 x 6.5 cm / 63/64" x 3 15/16" x 2 9/16" (H x W x D) Weight - Approximately 300 g (Tapping Device, bracket, and control box) - If not pre-assembled in the DVOC-0050, the package includes mounting material Power - Power requirements: 24 V DC, 0.4 A (max) Features - Controlled from EthoVision XT 10.1 or later with selectable stimulus intensity (1–8) - Delivers a discrete tap to the well plate holder - Maximum tapping rate of approximately 3 taps per second Connectors - Molex 2 pin – Power (24 V) - Molex 4 pin – From Tapping Device to control box - Multi connector (blue) – For TTL control signal Compatible DanioVision Chambers - DVOC-004x, DVOC-0050 DanioVision Toplight Unit Dimensions - 270 x 220 x 30 mm / 10 5/8" x 8 21/32" x 1 3/16" White Light - Greater than 30,000 lux at 25 cm distance (well plate), 1584 lm - Color temperature: 4000 °K - Array of 408 LEDs - Maximum voltage: 18 V Red Light - 192 lm, wavelength 623 nm - Array of 252 RGB LEDs - Maximum voltage: 24 V Green Light - 384 lm, wavelength 525 nm - Array of 252 RGB LEDs - Maximum voltage: 24 V Blue Light - 240 lm, wavelength 470 nm - Array of 252 RGB LEDs - Maximum voltage: 24 V Source: DanioVision DVOC-0050 Reference Manual - Appendices, Noldus Information Technology --- ## DanioVision DVOC-0050 - Arena Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-arena-settings Chapter: DanioVision Arena Settings Define the Arenas Automatically Follow these instructions if your experiment was created for well plates with 6, 12, 24, 48 or 96 round wells, or 96 square wells, and this is the first new Arena Settings in your experiment. In other cases, see Define the Arenas Manually. Tip: Use well plates with no notches between wells. These result in better well detection. Also make sure that the borders of all wells are within the camera image. - Place the well plate with water in the DanioVision chamber. - Choose Setup > Arena Settings > Arena Settings 1. - In the Grab Background Image window, click the Grab button to grab a background image of an empty well plate from the camera image. - If EthoVision XT can detect the wells, the outline of the arenas are displayed over the background image. A message appears asking whether the arenas overlap with the wells in the image. - Do one of the following: - If there is good overlap, click Yes. If needed, you can always make small adjustments using the Arrange Arenas function. - If the arenas clearly do not overlap with the wells, or arenas overlap with each other, click No. The Arrange Arenas window appears automatically. See Arrange the Arenas for details. - Click the 1. Draw Scale to Calibrate button. Draw a line over the entire well plate. Next, enter its size. Do this horizontally as well as vertically. - Click Validate Setup to validate the Arena Settings. Common errors are overlapping arenas, or zones falling outside an arena. If the setup is valid, continue with the instructions below. Notes: - Arenas are marked with labels A1, A2,... B1, B2,... according to your well plate (letters indicate rows; numbers indicate columns). - Success of automatic detection depends greatly on image contrast, focus, and distortion. Therefore, automatic detection cannot be guaranteed to work in all situations or with video made with DanioVision versions earlier than DVOC-0040. Automatic detection also does not work if water is not present in the well plate. - If automatic detection of the wells does not work, it could be due to the well plate not being centered in the video image, with some wells not visible or only partially visible. See Fine Camera Adjustments for guidance. - When the well plate image is optimal and centered and EthoVision XT still shows the message "Well plate detection failed," click OK and proceed with Define the Arenas Manually. - To start automatic well plate detection, click the Well Plate Detection button at the bottom of the Arenas and Zones section of the Arena Settings pane. Define the Arenas Manually The following instructions apply when the automatic well plate detection does not work properly. In that case you must define one arena and then make duplicates. If you used a predefined template to set up your experiment, go to Arrange the Arenas. - Click the 1. Draw Scale to Calibrate button, draw a line over the entire well plate and enter its size. Do this horizontally as well as vertically. - If the current arenas are of a shape different from that of the wells, select all arenas and press Delete. - Click 2. Select Shape and Draw Arena and use one of the shapes to create the first, top-left, arena. Make sure the label of the first arena (for example A1) points to the inside of the drawn arena. - Click the outline of the arena or its label and then click the 4. Copy Arena button. In the window that appears, select All Other Arenas, select the number of rows, and click OK. - Make sure the predefined arenas cover the wells. If you need to adjust the arena size and position, see Arrange the Arenas. Arrange the Arenas Use the Arrange Arenas function to move, re-scale, and rotate all arenas simultaneously. - In the Arena Settings window, click the 5. Arrange Arenas button to open the Arrange Arenas window. - To move all arenas, use the controls under 1. Move Grid: - To move up or down: Click the first slider and move it right (to move arenas down) or left (to move arenas up). - To move right or left: Click the second slider and move it right (to move arenas right) or left (to move arenas left). - You can also click the up/down arrow buttons of the corresponding box or enter a number in the box. - To scale all arenas, use the controls under 2. Scale Arenas: - Resize all shapes using the sliders, by pressing the up/down arrows of the corresponding box, or by entering a number in a box. - To increase the height of all arenas, use the first slider. To increase the width of all arenas, use the second slider. - By default, Keep Proportions is not selected, allowing you to resize height and width separately. If you select Keep Proportions, changing either the height or width will maintain the aspect ratio. - To rotate all arenas, use the controls under 3. Rotate Grid: - Optionally rotate all shapes. This is only necessary if the well plate is not positioned straight. The shapes rotate around the center of gravity of Arena 1. - To change the space between arenas, use the controls under 4. Arena Spacing: - By default, Keep Proportions is not selected, allowing you to change the space between shapes separately in the vertical and horizontal direction. If you select Keep Proportions, changing the spacing in either direction will maintain the aspect ratio. - Click Validate Setup to validate the Arena Settings. Common errors are overlapping arenas, or zones falling outside an arena. If the setup is valid, continue with the instructions below. Tip: First position the upper-left arena in the desired position and set the desired size using Scale. Next, adjust arena spacing so all arenas are correctly positioned. See Using the Multiple Arena Setup in the EthoVision XT Help for more information on setting up multiple arenas. Edit a Single Arena Click the row in the Arena Settings pane for the arena you want to edit. The corresponding arena is highlighted. Click the handles to move or resize the polygon. For details on editing shapes, see Arena Settings > Work with Shapes in the EthoVision XT Help. Assign the Stimuli to the Arenas Use this procedure to apply stimuli during a trial, such as a light pulse or a tapping stimulus. If you created an experiment with a pre-defined template and selected the correct DanioVision arena template, the White Light Stimulus and the Tapping Stimulus have been assigned automatically to the arenas and the steps below are not necessary. Prerequisite: You have declared the port connections in the trial control hardware settings. - At the bottom of the Arena Settings pane, click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, do the following: - Click Add Device. - Locate the new row added to the list. - Under Arena 1, select the device you want to add, for example White Light Stimulus or Tapping Stimulus. - Repeat steps a through c for each additional device. - Click OK. Note that devices only need to be assigned to Arena 1, as they are applied to all arenas. To test a device: Select the corresponding row in the Arena - Hardware Mapping window and click the Test button. See also Test the Hardware Devices in the EthoVision XT 18 Trial and Hardware Control Reference Manual. For more information: - About the Tapping Stimulus: see The DanioVision Tapping Device. - About the TopLight Unit: see The DanioVision Toplight Unit. - About the Optogenetics add-on: see The DanioVision Optogenetics Add-on. Source: DanioVision DVOC-0050 Reference Manual - Arena Settings, Noldus Information Technology --- ## DanioVision DVOC-0050 - Check the System - Check the DanioVision System URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-check-the-system-check-the-daniovision-system Chapter: DanioVision Check the DanioVision System Before you start setting up EthoVision XT, you need to check the following: - Camera: The camera lens should have the correct aperture and must be in focus. The camera must also be correctly configured. - Anti-Condensation Mechanism: You need to configure this depending on the temperature inside the DanioVision chamber and the desired water temperature around the well plate. - White Light Stimulus: Configure this when you want to use very low intensities for the DanioVision White Light. - Well Plates and Petri Dishes: The well plate or Petri dish must be inserted correctly. Always control evaporation in the basin and in the well plate, especially when carrying out long trials (more than 1 day). Check the Camera Lens Although the camera and lens are set up before shipment, the settings of the lens can shift during transport. Before you start to work with the DanioVision system, check that the lens is set up correctly by doing the following: - The lens you use depends on the video resolution and frame rate you want to use. - Insert a well plate or Petri dish in the basin. - Create a new EthoVision XT experiment and open the Arena Settings to see the camera image. When water is not present in the basin, the image of the well plate should look overexposed. - Check the focus. If the camera image is not in focus, loosen the screw, adjust the focus, and tighten the screw. The camera should be focused on the animals. The distance between animals and camera does not change much between types of well plate and water level in the wells; however, it is always a good idea to check the image before an experiment and adjust the focus until it is optimized. - Check the aperture ring. The aperture has been adjusted so that when the basin is filled with water, the video image is optimal for tracking. In the Detection Settings, always check that detection of the larvae is good. If necessary, adjust the aperture to get a better contrast between the larvae and the background. - Make sure the camera is correctly configured. The more the lens aperture is set toward C (Close), the larger the depth of field is. This means that the subject looks sharp across a wider range of distances from the lens. This is especially relevant when working with a zoom lens and zooming in to focus on a smaller region of a well plate. If the aperture is set to O (Open), the subject may look sharp only at a certain water depth. Closing the aperture has the disadvantage of decreasing the contrast between the subject and the background. Adjust the aperture until the image is optimized. Configure the Anti-Condensation Mechanism The Anti-Moisture switch is located behind the camera, on the left side. The DanioVision Observation Chamber is equipped with an anti-condensation mechanism to prevent water droplets from forming on the lens during an experiment. A temperature sensor inside the chamber checks whether the mechanism should be switched on or off when set to Auto mode. Besides Auto mode, you can also permanently switch the mechanism On or Off. Auto Mode This is the default and recommended setting when the DanioVision TCU is not used. The anti-condensation mechanism is automatically switched on when the air temperature inside the chamber drops below 28 °C (82.4 °F) to prevent condensation on the lens. When the air temperature exceeds 28 °C, the mechanism is automatically turned off to prevent heating of the water in the wells. The value of 28 °C is a default setting of the embedded controller. If you use the DanioVision TCU, follow the instructions in the DanioVision Temperature Control Unit section and set the switch to either On or Off. Off The anti-condensation mechanism is permanently turned off. Use this mode when the air temperature inside the chamber is equal to or higher than the actual water temperature of the basin or well plate (in most cases 28 °C). This option can be used in combination with the DanioVision TCU. On The anti-condensation mechanism is permanently turned on. Use this mode when the air temperature inside the chamber is lower than the water temperature in the wells. This option can be used in combination with the DanioVision TCU. Configure the DanioVision White Bottom Light Light Intensities in DanioVision DVOC-0050 In DanioVision DVOC-0050, the White Bottom Light levels are fully adjustable in the EthoVision XT Trial Control Settings using the Action box for the White Light. Light Intensities in DanioVision DVOC-0041 The intensities of the White Light in DanioVision DVOC-0041 are the same as those of the White Bottom Light in DanioVision DVOC-0050: - 5% (Step 207): 139 lux - 25% (Step 1000): 2500 lux - 50% (Step 2100): 5300 lux - 75% (Step 3000): 8000 lux - 100% (Step 4095): 10500 lux Light Intensities in DanioVision DVOC-0040 The reference values of the intensity of White Light in DVOC-0040 are as follows: - 1% (Step 40): 70 lux - 25% (Step 1025): 1450 lux - 50% (Step 2050): 2950 lux - 75% (Step 3000): 4400 lux - 100% (Step 4096): 5450 lux You may want to replicate light conditions set in DanioVision DVOC-0040 in a new experiment with DanioVision DVOC-0050. For example, if you set light intensity to 50% in DanioVision DVOC-0040, this gave 2950 lux. The equivalent percentage in DanioVision DVOC-0050 would be (2950 / 5300) × 50 = approximately 28%. To find the percentage P50 to set in DanioVision DVOC-0050, based on the percentage and intensity used in DanioVision DVOC-0040 (P40 and Lux40 respectively), use the following formula: P50 = (Lux40 / Lux50) × P40 Where Lux50 is the intensity in lux in DanioVision DVOC-0050 corresponding to the percentage set in DVOC-0040. --- ## DanioVision DVOC-0050 - Check the System - Well Plates and Petri Dishes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-check-the-system-well-plates-and-petri-dishes Chapter: DanioVision Well Plates and Petri Dishes Well Plates (ANSI Standard) - Put the back of the well plate against the bridge and place it on the basin floor. - Tilt the front of the well plate down to the floor so that the water in the basin pushes the air from underneath the well plate. Make sure the well plate is accommodated correctly between the metal springs at the front and at the right side. Tip: Drill a few holes on the sides of the well plate to allow air to escape when placing the well plate. Well Plates (Non-ANSI Standard) For smaller or larger well plates, place the bridge in a different position. The default position (ANSI standard) corresponds to the second hole on the side walls of the basin, counting from the inner side of the observation chamber. - Remove the screws as indicated in the picture. - Slide the bridge by one or more positions. Check the video image in EthoVision XT and make sure that the well plate is centered in the camera view. - Fix the screws in the corresponding holes. Petri Dishes - Put the Petri dish against the 90° angle of the bridge. - If necessary, remove the screws of the bridge and slide the bridge a few positions until the dish is centered in the camera view. With DanioVision you can use Petri dishes with a diameter of up to 90 mm. It is recommended not to let water flow into the basin when using Petri dishes, as water may flow underneath the bottom of the dish and cause it to shift from its original position during a trial. Control Evaporation Wells on the sides of the well plate tend to show a higher rate of evaporation than wells in the center. Wells at the front also have a higher evaporation rate than those at the back. In long experiments (more than 24 hours), evaporation may occur in both the wells and the basin. The following steps are recommended: - Wells: Check the wells every 24 hours and refill them if necessary. - Basin: Refill the basin every 2 to 3 days using the Basin Refill tool. Environmental conditions (temperature, relative humidity, and air flow) and experimental conditions (lens heater on or off, White Light intensity) influence the rate of evaporation and condensation of water from the basin and well plate. If you plan to carry out long experiments, always test evaporation under your environmental and experimental conditions, and plan refills to ensure that the water level never drops to a critical value. Source: DanioVision DVOC-0050 Reference Manual - Check the System, Noldus Information Technology --- ## DanioVision DVOC-0050 - Data Preparation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-data-preparation Chapter: DanioVision Data Preparation Track Smoothing Track Smoothing profiles are available in the template experiment: - No Smoothing – Smoothing filters are not activated. - MDM 0.2 mm – With this Minimal Distance Moved filter, you can reduce the effect of 'jitter' on the Distance Moved variable. Applying this filter is recommended, however, it results in longer calculation times in the analysis. Change these settings for your setup, if necessary. More Options Use the Maximum Distance Moved filter to remove outliers in the track, due to erratic detection of objects within the arena, such as when the margin of the well is sometimes detected as the fish. For more information on smoothing data, see Smooth the Tracks in the EthoVision XT Help. Select Data Data profiles available in the template experiment: - All Data – With this Data profile you analyze all tracks separately. - Treated vs. Control – The data are split for analysis based on the two values of the user-defined variable Treatment: Treated and Control. This Data profile assumes that you have assigned a label (either Control or Treated) to each of your trials or arenas (wells). Analyze Dark vs. Light Periods In this example, the researcher wants to analyze the data in different light and dark periods, determined by the activation of the white light. In the Data profile, the function Trial Control State under Nesting is used to create intervals corresponding to the state of the white light. - Choose Analysis > Data Profile > New. Give the new Data profile a name and click OK. - In the Components pane, under Nesting, click the button next to Trial Control State. - Select the period you are interested in using the Trial Control actions. For example, From Light On To Light Off (depending on what name the Light On/Off actions have in the Trial Control Settings). - Insert the Nest box in the Data profile sequence. - If you want to analyze different periods and have the results in the same table, create more Results boxes. To add a Result box, in the Components pane click the button next to Result. In each sequence, add a Nest box that specifies a different Trial Control State. - Choose the dependent variables and run analysis. Tip: See also the sample experiment DanioVision with 96 wells XT, which you can download from our website. There you can find the Data profile mentioned here. Analyze Data Excluding Periods of Inactivity In this example we want to exclude the interval in which a larva was not moving. - Choose Analysis > Data Profile > New. Give the new Data profile a name and click OK. - In the Components pane, under Nesting, click the button next to Movement. - In the Movement tab, you can set the following: - Averaging interval (range 1–1000) – This is the number of samples across which changes in speed are calculated to determine whether the subject is moving or not. In order to reduce the sensitivity of the Movement variable to brief changes in velocity, the velocity data can be smoothed by taking the running average of the last n samples. Enter the averaging interval n, or leave 1 if you do not want to smooth the velocity data. - Start velocity – The velocity above which the subject is considered to be moving. - Stop velocity – The velocity below which displacements of the subject's body points are no longer attributed to locomotion but to system noise, body wobble, or pivoting on the spot. - Under Calculate nesting for, select Not moving. - Click OK. Insert the Nest box in the appropriate position between the Start and the Result box. - Choose the dependent variables and run analysis. For more information on the Nesting functions, see Analyze Track Segments in the EthoVision XT Help. Analyze the Intervals Around the Onset of the White Light In this example, we want to analyze two intervals: - From 5 seconds before the onset of the White light stimulus, to the onset of the stimulus. - From the onset of the White light stimulus, to 5 seconds after the onset of the stimulus. The aim is to compare activity, speed, and other parameters between the two intervals. - Choose Analysis > Data Profile > New. Give the new Data profile a name and click OK. - In the Components pane, under Nesting, click the button next to Free interval. - Do the following: - Under Start criterion, select Trial Control. Choose the appropriate options for your light stimulus action. - Under Stop criterion, select Time. Next to Elapsed time, leave 0:00:00.000 after start event selected. Note: The term start event refers to the White light selected under Interval start. Click OK and insert the Nest box in the sequence. - To create the second interval, choose Result under Common elements. Click the middle of the Start box and drag to the Result 2 box to connect the two boxes. - Repeat steps 2–3 to create a new Nest box for the interval "from White light to 5 seconds after that". In the settings, choose the criteria for the second interval: from Trial Control – 0 seconds before Action: Light On to Time – Elapsed time 5 seconds after start event. Click OK and insert the Nest box in the sequence. - Choose the dependent variables and run analysis. Tip: Click Settings in the Result boxes and rename them, for example to 5-s Before White Light and 5-s After White Light. Those names will be displayed as headers in your results. Source: DanioVision DVOC-0050 Reference Manual - Data Preparation, Noldus Information Technology --- ## DanioVision DVOC-0050 - Detection Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-detection-settings Chapter: DanioVision Detection Settings What Do You Want to Do? - Track one subject per well/enclosure. See below. - Track two or more subjects in the same enclosure. See the Multiple Subjects in the Same Enclosure section. - Use Activity. See the Activity Analysis section. One Subject Per Enclosure Choose Setup > Detection Settings > Detection Settings 1. The DanioVision Detection Method The template experiment contains a Detection Settings profile with DanioVision selected as method. The DanioVision detection method is optimized for detecting small dark objects over a white/gray background, like in DanioVision experiments. The difference with other methods is that DanioVision detects the subject based on the level of contrast within the well where the subject is. You can view this method as Dynamic Subtraction applied to each well independently. This method should detect all subjects even when there are differences in lighting between wells. This method does use a reference image, just like Dynamic Subtraction, however you do not have to choose one. The software does that for you by taking the first video frame available. After comparing the reference image with the current video image, DanioVision selects the pixels within the well that are more likely to be part of the subject. How "choosy" the software is depends on the Sensitivity. With a low value of Sensitivity the software considers pixels over a wider range of grey values as candidates. With high values, it picks pixels over a narrow range of grey values. If some subjects are completely still, the software may not find them. If that occurs, gently tap the well plate to make the animals move. Once all the subjects are detected, adjust your settings. Important: If you have upgraded EthoVision XT to version 18 while you have a DanioVision system older than DVOC-0040, the DanioVision method does not give optimal detection of the larvae with images from your camera. If that is the case, adjust the Sensitivity (see below) or use another detection method in the Advanced section of the Detection Settings pane. For details, see the EthoVision XT Help. Procedure - Place the well plate with the larvae in the DanioVision chamber and close the chamber door. - Click the Auto-detect button. Use the Auto-detect button every time you change a well plate. - The Auto-detect window with a timer appears. Wait until it has disappeared. All larvae should be detected. What If Some Larvae Are Not Detected or the Software Tracks Noise? Do one or more of the following: - Open the Advanced section and under Method move the Sensitivity slider. Moving the slider to the left results in detecting more of the body of the larvae, but also more noise. Moving the slider to the right results in detecting less noise, but also gives less accurate detection of the larvae. - If you see erratic tracks and spikes, it means that small groups of pixels at the border of the well are sometimes detected as the larva, and there is too much noise (orange pixels). Move the Sensitivity slider to the right. - If some larvae are not detected while they are in the corner or border of a well, check that the arenas are drawn correctly. Click the Show/Hide button on the toolbar, select Arena Features, and then select the check box in front of Arenas. Check that the arenas cover the entire wells. The subject is not detected when it swims in a region not covered by the arena. - Try to maximize the contrast by opening the aperture of the camera lens. However, make sure the light intensity is equal for all wells (that is, the center and outer wells). - Certain compounds dissolved in the water can affect the pigmentation in the larvae, thereby decreasing contrast and making detection more difficult. Make sure that EthoVision XT can still detect all animals after treatment. If detection remains unsatisfactory: - It could be that the software tracks other objects outside the well. Restrict the arenas only to the part where the larvae swim. - Try the Dynamic Subtraction method. For an explanation of the options, see Configure Detection Settings in the EthoVision XT Help. Notes - The Dynamic Subtraction method may also work fine with zebrafish larvae. - If your experiment is set to track three body points (snout, center, and tail), you can choose the Adult Fish/For Occlusions method. - If the experiment is set to center-point detection only, choose either DanioVision or Dynamic Subtraction, with the Other Species method to track the center point of the subjects. Activity Analysis Use Activity to quantify overall activity of your subjects. In the Experiment Settings, select Activity Analysis. In the Detection Settings pane, open the Activity section. Activity is shown by purple pixels in the video window. Set the Activity threshold so that movements of the animals are detected and some noise is left. For more information on activity, see Activity Settings in the EthoVision XT Help. Also watch the video tutorial on Activity Analysis. For more general information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Multiple Subjects in the Same Enclosure Prerequisites In the Experiment Settings, Number of Subjects must be set to 2 or higher. Procedure - Choose Setup > Detection Settings > Detection Settings 1. - Click Automated Setup. One subject is detected per well. Play the video to check detection. - Click Advanced, then Method, and select DanioVision. Note that subjects are not individually marked, so identity swaps do occur. Source: DanioVision DVOC-0050 Reference Manual - Detection Settings, Noldus Information Technology --- ## DanioVision DVOC-0050 - Optogenetics Add-on - The DanioVision Optogenetics Add-On URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-optogenetics-add-on-the-daniovision-optogenetics-add-on Chapter: DanioVision The DanioVision Optogenetics Add-On Introduction Optogenetics allow scientists to control the activity of specific neurons and study their downstream influence on a variety of biological processes, including behavior. In rodent behavioral studies, this technique requires optical fiber implantation. When working with zebrafish larvae, mostly transparent, fiber optics are not needed - light simply needs to shine in the right direction, making it easy to assess the effect of stimulation of specific, light-sensitive neurons on the behavior of the fish. By inserting light-sensitive receptor proteins into neurons in vivo, it is possible to make those neurons sensitive to activation by light of specific wavelengths. In zebrafish studies, the light-sensitive receptor protein halorhodopsin (NpHR) has successfully been used to inhibit swimming behavior in zebrafish larvae (Arrenberg et al. 2009). Other research showed that channelrhodopsin-2 (ChR2) activation induced backward swimming in a sparse transgene expression line (Zhu et al. 2009). Optogenetics Add-On Application of optogenetic stimulation in zebrafish larvae requires the correct wavelength (i.e., color) of light. When using the DanioVision Observation Chamber, the Optogenetics Add-on provides a way to accurately control and precisely time the application of optogenetic stimulation to up to 96 individuals simultaneously (working with 96 well plates). The Optogenetics Add-on for DanioVision is an optogenetic LED light source based on the Prizmatix Modular LED system. It consists of one, two or three LED wavelengths. The Optogenetics Add-on can be programmed and controlled using the EthoVision XT software included with your DanioVision system. You can set user-defined time conditions for the optogenetic stimulation. In comparison to manual control, this offers far better temporal precision and adds efficiency to longitudinal studies. References - Arrenberg, A.B., Del Bene, F., Baier, H. 2009. Optical control of zebrafish behavior with halorhodopsin. PNAS 106: 17968-17973. - Zhu, P., Narita, Y., Bundschuh, S.T., Fajardo, O., Scharer, Y.P., Chattopadhyaya, B., Bouldoires, E.A., Stepien, A.E., Desseroth, K., Arber, S., Sprengel, R., Rijli, F.M., Friedrich, R.W. 2009. Optogenetic dissection of neuronal circuits in zebrafish using viral gene transfer and the Tet system. Frontiers in Neural Circuits 3: 21. Sample Experiment Your DanioVision system comes with an EthoVision XT sample experiment: DVOC_Optogenetics_Demo_Recommended.evxt. It contains examples of Trial Control rules for triggering pulse sequences in one up to three Pulsers. Additional Manuals - For connecting the hardware: Prizmatix UHP-T LED Illuminator User Manual.pdf. - For programming the Pulser: Prizmatix Pulser User Manual.pdf. - For connecting the DanioVision Temperature Control Unit: This manual, page 80. Install the Dichroic Mirror in DanioVision If you purchase the DanioVision Observation Chamber DVOC-0050 with the Optogenetics Add-on, the LEDs are already mounted so you only have to connect the cables (see the next section). However, the dichroic mirror comes in a separate box to prevent damage during shipping. This section explains how to install it. Please follow the instructions below. Note: The function of the dichroic mirror is to direct the color light beams to the well plate, and at the same time allow light to reach the camera, so you can film and track the fish during the test. - Locate the box containing the mirror. Wear the supplied gloves to avoid damaging or dirtying the mirror. Avoid touching the mirror surface and only hold its edges. - Locate the arrow on one side of the mirror. Once the mirror is mounted, this arrow should be at the top of the mirror and point towards the light source, that is, the backside of the DanioVision chamber. - Attach the mirror. Slide the mirror upwards along the brackets as indicated by the arrows. - Position the mirror just above the mark on the right-hand bracket. When the mirror is in that position, carefully tighten the screw on the left to fix the mirror. Do not apply any force as this may damage the mirror. - The mirror is now ready to use. See the next sections. Important: The LED is extremely powerful and may cause eye injury when looking directly into the light source. For testing, we recommend setting the LED intensity to low. The Pulser Software Please skip this section if you do not use the Pulser/PulserPlus devices. Follow the procedure below if you use one or more Pulser/PulserPlus devices. To control multiple devices, multiple instances of the Pulser software must be running on the EthoVision XT computer. Important: Do not connect the Pulser/PulserPlus device to the computer until the software setup process is complete. Install the Pulser Software Once - Copy the installation files and folders to your computer's hard drive. - Run the setup.exe file and follow the instructions as they appear on the screen. Next, restart the computer to complete the software installation. - Open the folder where the software has been installed (default: C:\Program Files (x86)\Prizmatix Pulser Plus 3.2.1) and make a shortcut to the EXE file. Give the shortcut a name that is easily recognized, like Pulser A or the name of the first LED. - To install or update the Pulser/PulserPlus drivers, see the Pulser/PulserPlus User Manual. Install Multiple Instances of the Pulser Software To control two or three LEDs independently using the dedicated Pulser/PulserPlus devices, install one instance of the Pulser software for each Pulser/PulserPlus. - Install the first instance of the Pulser software (see above). - Browse to the folder C:\Program Files (x86) and copy the entire folder Prizmatix Pulser Plus 3.2.1. - Paste the folder in the same location C:\Program Files (x86). Rename the folder to Prizmatix Pulser Plus 3.2.1 PulserB. - Open the new folder and make a shortcut for the EXE file that you find there. Place the shortcut on your desktop. Name it like Pulser B or the name of the second LED. - If you have a third LED, repeat steps 2 to 4 to create a new folder which will contain a third instance of the Pulser software. Make a shortcut to the new EXE file and rename it to e.g. Pulser C. - You should at this point have the appropriate folder structure and three shortcuts on your desktop. LED Controller UHPTLCC This device has a switch in the middle of the front panel. Basic Connections - Make sure the power switch (1) is set to Off. - Connect the 12VDC connector (10) to the power outlet through its power cable and adapter. - Connect the LED cables (LED Control cable and LED Current cable) that come from the DanioVision system to the two LED connectors (8 and 9, respectively). To Control the LED Manually - Set the switch near TTL (5) to Int. - Set the switch near Ain (6) to Int. - Turn on the main power (see 1 in the figure above). - To turn the LED on, flip the switch (2) on. To Control the LED from EthoVision XT Through TTL - Set the switch near TTL (5) to Ext. - Set the switch near Ain (6) to Int. - Turn on the main power (see 1 in the figure above). - To turn the LED on, flip the switch (2) on. - Connect the TTL cable with BNC connector from the pulser (or the back of the DanioVision chamber, depending on the setup) to the TTL connector on the back panel of the LED controller (4). - In EthoVision XT you can now give the "high" command using the Trial Control actions. See page 157 or 159 depending on the setup. Other Controls - Power adjustment dial (3). - Analog input (Ain) connector (7). LED Controller UHPTLCC-02 This device does not have a switch in the middle of the front panel. Basic Connections - Make sure the power switch (9) is set to Off (O). - Connect the 12VDC connector to the power outlet through the power cable and adapter. - Connect the LED cables (LED Current cable and LED Control cable) that come from the DanioVision system to the two LED connectors (7 and 8, respectively). To Control the LED Manually - Set the switch near TTL (4) to Int. - Set the switch near Ain (5) to Int. - Turn on the main power (9). - To turn the LED on and off, press the button (1). To Control the LED from EthoVision XT Through TTL - Set the switch near TTL (4) to Ext. - Set the switch near Ain (5) to Int. - Turn on the main power (9). - Do one of the following, depending on whether you work with Pulsers or not: - If you do not use the Pulsers, connect the TTL-In of each LED controller to the connectors at the back of DanioVision: Trigger Out 1 for LED Controller 1, Trigger Out 2 for LED Controller 2, and TTL A (or B) for LED Controller 3. For this latter connection you need a special cable with an 8-pin connector at one end and a BNC connector at the other end. See Configuration 2 - With the Pulsers on page 149. - If you use the Pulsers, connect the Trigger In of each Pulser to the connectors at the back of DanioVision: Trigger Out 1 for Pulser A, Trigger Out 2 for Pulser 2, and TTL A (or B) for Pulser C. For this latter connection you need a special cable with an 8-pin connector at one end and a BNC connector at the other end. See Configuration 2 - With the Pulsers on page 151. - In EthoVision XT you can now trigger the LED controllers or the Pulsers using the Trial Control actions. See page 157 or 159 depending on the setup. Other Controls - Power adjustment dial (2). - Analog input (Ain) connector (6). Configuration 1 - Without the Pulsers In the following example, EthoVision XT controls three LED controllers through the TTL ports in the DanioVision Observation Chamber. EthoVision XT Connections - One Ethernet connection to control the DanioVision and Optogenetics hardware devices. - One Ethernet connection for the DanioVision camera. See page 14. Next Steps - Experiment settings on page 153. - Arena settings on page 154. - Trial control (without the Pulsers) on page 157. For information about creating pulse sequences in EthoVision XT, see the chapter Optogenetics Experiments in the EthoVision XT 18 Application Manual. To open this manual, from the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 Other Documentation. Configuration 2 - With the Pulsers --- ## DanioVision DVOC-0050 - Optogenetics Add-on - Trial Control (Without the Pulsers) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-optogenetics-add-on-trial-control-without-the-pulsers Chapter: DanioVision Trial Control (Without the Pulsers) Prerequisites - The dichroic mirror is installed. - All components are connected and powered up. - The LED controllers are set to TTL control. Procedure To control the LED directly from EthoVision XT, program the Trial Control rule using Action boxes. The duration of the light pulse is determined by a Time condition placed between the Action Output 1/2 High and Output 1/2 Low. In the example below, LED 1 (named Device D in the Arena - Hardware Mapping window) is activated with a TTL signal Output 1 High and after 0.5 seconds it is deactivated with a TTL signal Output 1 Low. The sequence Action - Time Condition - Action has been placed within a subrule so that it can be repeated a number of times. Notes - Use Output 2 High/Low commands to control the LED controller connected to the DanioVision Trigger Out 2 port. - Make sure that the Int-Ext switch near TTL on the LED controllers is set to Ext. Trial Control (With the Pulsers) Prerequisites - The dichroic mirror is installed. - All components are connected and powered up. - The LED controllers are set to TTL - Ext control. Procedure - Open all instances of the Pulser software by clicking on the desktop shortcuts Pulser A, Pulser B, and Pulser C. Each instance controls one Pulser. - For each instance of the software, next to Select COM Port, choose the correct COM port for the corresponding Pulser. These can be found on the Pulser or on the connection diagram. - Next to Select Operation Mode, choose one of the following: - When testing the Pulser, choose (0) Execute Pulse Sequence After START. By pressing the Start Sequence button, the LED flashes the configured sequence. - When running the actual trials, choose (3) Execute Pulse Sequence After Trigger HIGH, Then Stop When LOW. If you now click the Start Sequence button, the Pulser waits for a TTL trigger from EthoVision XT to start the sequence. - Enter the other settings in the dialog to control the pulse duration and the time between pulses. For details, see the Prizmatix Pulser/PulserPlus User Manual. - Start EthoVision and open the example experiment: DVOC_Optogenetics_demo_recommended.evxt. - In the Trial Control Settings, you find predefined routines (called subrules) to control three Pulsers. The main procedure (top row) has been configured to consecutively trigger the three Pulsers using the corresponding subrules. Make sure that: - The Pulsers all have the correct COM port. - The Pulsers are all in mode 3. - The Start Sequence button has been pressed. For more information, see the chapter Optogenetics Experiments in the EthoVision XT 18 Application Manual. Basic Subrule A set of instructions within a subrule activates the Pulser a number of times, as specified in the Subrule Reference box. The three boxes within the subrule specify: - An action that triggers the pulse sequence (send a High signal to a device through line Output 1 or Output 2). - A Time condition to wait a number of seconds. - An action that stops the pulse sequence (send a Low signal to a device through line Output 1 or Output 2). In the following example, the subrule triggers the sequence in Pulser A through the Output 1 line, for 5 seconds. Notes - The name of the device selected next to Optogenetics has been renamed to 570 +520 nm in the Arena - Hardware Mapping window. This is because it controls two Pulsers: one for a LED of 570 nm through line Output 1 (from the Trigger Out 1 port in DanioVision) and one for a LED of 520 nm through line Output 2 (from the Trigger Out 2 port in DanioVision). In this example we operate the first Pulser only, using the command Output 1 High. - You find the name 570 +520 nm in the Arena - Hardware Mapping window of the Arena Settings in the demo experiment. - Do not forget to set the Int-Ext switch located near TTL on the LED controller to Ext. Acquire the Data To acquire the data, choose Acquisition > Open Acquisition. Important Things to Check - Make sure that the green light of the button on the LED controller is switched on. - Make sure that the Pulser software is open on your screen. There must be one instance of Pulser software for each Pulser. If you work with two Pulsers simultaneously, two Pulser software windows must be open. - Check that each instance of the Pulser software indicates that a COM port is selected (COM3, COM4, etc.) and shows the message "Prizmatix Pulser is connected." - If you use the Pulser in trigger mode, in the Pulser software check that the Operating Mode is set to (3) Execute Sequence After Trigger HIGH, Then Stop When LOW. Next, click the button Start Sequence. Now the Pulser is listening to the trigger signal. Start the Trial To start the trial, click the Start Trial button. The optogenetics setup will be activated according to the Trial Control protocol that is active at that time. Configure the COM Port for Each Pulser Aim To configure the COM port in such a way the Pulser/PulserPlus accepts commands from EthoVision XT. Procedure - Connect the Pulser/PulserPlus to the PC using the USB cable with type-A to type-B connectors. - In the Control Panel, open the Device Manager. - Under Ports (COM & LPT), right-click USB Serial Port and select Properties. - Click the Port Settings tab. - Make sure that the parameters are as below, then click OK. - Take note of the port number (in the example above it is COM3). - Repeat the procedure for each Pulser/PulserPlus. Notes - The COM port number is retained in the Pulser, so if you disconnect the Pulsers and reconnect them, you do not have to assign the COM ports again. - To know which COM port is assigned to which Pulser/PulserPlus device, disconnect the USB cable from one Pulser/PulserPlus. Then, re-connect it. The item that appears under Ports (COM & LPT) indicates the COM port. - To change the COM port for a specific Pulser, in the Control Panel, open the Device Manager. Under Ports (COM & LPT), right-click the COM port, select Properties, Port Settings, then Advanced. From the COM Port Number list select the COM port among those available. Source: DanioVision DVOC-0050 Reference Manual - Optogenetics Add-on, Noldus Information Technology --- ## DanioVision DVOC-0050 - Optogenetics Add-on - TTL Lines URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-optogenetics-add-on-ttl-lines Chapter: DanioVision TTL Lines - If you use one Pulser, use the DanioVision Trigger Out 1 port to connect the Pulser. - If you use two Pulsers, use the DanioVision Trigger Out 1 port and the Trigger Out 2 port to connect Pulsers A and B, respectively. - If you use three Pulsers: - Use the DanioVision Trigger Out 1 port for Pulser A. - Use the DanioVision Trigger Out 2 port for Pulser B. - Use the DanioVision TTL A port (if it is not connected to the Temperature Control Unit) or the TTL B port for Pulser C. For the TTL A/B connection you need a special cable with an 8-pin connector at one end and a BNC connector at the other end. EthoVision XT Connections - One Ethernet connection for controlling the DanioVision and Optogenetics hardware devices. - One Ethernet connection for the DanioVision camera. Next Steps - Experiment settings - Arena settings - Trial control (with the Pulsers) For information about creating pulse sequences in EthoVision XT, see the chapter Optogenetics Experiments in the EthoVision XT 18 Application Manual. To open this manual, from the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 Other Documentation. Experiment Settings - Choose Setup > Experiment Settings. - Click Settings next to Use of Trial Control Hardware. - Choose the DanioVision DVOC-0050/TCP. Then follow the section below that applies to choose the port numbers in the Device Configuration window. Tip: Open the sample experiment DVOC_Optogenetics_Demo_Recommended.evxt. This is a live tracking experiment where basic settings in Experiment Settings and Trial Control are already selected for when you work with three Pulsers. Configuration Without Pulsers In this example with three LED controllers, we use the connectors Trigger Out 1, Trigger Out 2, and TTL B because TTL A is connected to the DanioVision TCU. - Trigger Out 1 and Trigger Out 2 are connected to LED controllers 1 and 2. Select Optogenetics next to Trigger Out. - TTL Port B is connected to LED controller 3. Select Custom Hardware under Device Type. Configuration With Pulsers In this example with three Pulsers, we use the connectors Trigger Out 1, Trigger Out 2, and TTL B because TTL A is connected to the DanioVision TCU. - Trigger Out 1 and Trigger Out 2 are connected to Pulser A and Pulser B, respectively. Select Optogenetics next to Trigger Out. - TTL Port B is connected to Pulser C. Select Custom Hardware under Device Type. Arena Settings Declare the Optogenetics Setup The figures below refer to a configuration with three Pulsers. - Choose Setup > Arena Settings. Draw and calibrate the arenas. - Click the Arena - Hardware Mapping button. - Click Add Device. - In the new row, under Device Type select Optogenetics (for Pulser A and B, or LED controllers 1 and 2). - Click Add Device. - In the new row, under Device Type select Custom Hardware (for Pulser C, or LED controller 3). Tip: Rename Device Name to the actual name of the controlled devices, for example Pulsers A and B and Pulser C for the two rows, respectively. If you work only with LED controllers, type in for example LED 1 and 2, and LED 3, respectively. - Make sure that the devices are selected under A1/Arena 1. Test the Triggering Action on the LED Controllers - In EthoVision XT, open the Arena - Hardware Mapping window. - Click the row for the pulser you want to test (either LED 1 and 2 or LED 3). - Click the Test button. - In the window that appears: - If you have selected LED 1 and 2, select Output 1 High to trigger the LED connected to Trigger Out 1 on the DanioVision's back panel (this is usually LED 1), or select Output 2 High to trigger the LED connected to Trigger Out 2 (this is usually LED 2). - If you have selected LED 3, select Output 1 High to trigger the LED. - Click Test. At this point the LED switches on. If it does not, do the following: - Check carefully the cabling. - Check that the green button on the LED controller is turned on. Test the Triggering Action on the Pulsers - Important: Make sure that in the Pulser software the correct COM port is selected and that the operating mode is set to (3) Execute Sequence After Trigger HIGH, Then Stop When LOW. - Click the button Start Sequence. Now the Pulser is listening to the trigger signal. - In EthoVision XT, open the Arena - Hardware Mapping window. - Click the row for the Pulser you want to test (either Pulser A and B or Pulser C). - Click the Test button. - In the window that appears, select Output 1 High or Output 2 High, depending on which Pulser you want to test: - If you have selected Pulser A and B, select Output 1 High to trigger the Pulser connected to Trigger Out 1 on the DanioVision's back panel (this is usually Pulser A), or select Output 2 High to trigger the Pulser connected to Trigger Out 2 (this is usually Pulser B). - If you have selected Pulser C, select Output 1 High to trigger the Pulser. - Click Test. At this point the LED connected to that Pulser is activated following the sequence defined in the Pulser software. If it is not, do the following: - Check carefully the cabling. - Check that the Start Sequence button was pressed. - Check that the green button on the LED controller is turned on. --- ## DanioVision DVOC-0050 - Set Up DanioVision - Configure the DanioVision Camera URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-set-up-daniovision-configure-the-daniovision-camera Chapter: DanioVision Configure the DanioVision Camera Camera Settings The DanioVision camera that you received is already configured according to your setup. Noldus created three main settings profiles, called User Sets, stored in the Pylon Viewer software which controls the camera: User Set 1, User Set 2, and User Set 3. Only one User Set can be active at a time. For each video resolution, you must use different camera settings and in some cases a different camera lens. For example, the video resolution determines the maximum frame rate. The higher the required resolution (in number of pixels), the lower the maximum frame rate (in frames per second). The three User Sets are specific for a combination of video resolution and frame rate. Note: Pylon Viewer is installed when you install the camera driver software. For more information about Pylon Viewer, see Configure the Digital Camera in the EthoVision XT Help. The predefined User Sets and their associated settings are as follows: - User Set 1 is default for most applications, used with a 12 mm lens at 1280 x 960 resolution and 30 fps. - User Set 2 is pre-selected if you purchased a 12 mm lens and work with a high frame rate (640 x 480 at 60 fps). Binning mode must be set to Summing for User Set 2. - User Set 3 is pre-selected if you purchased an 8 mm lens with a 0.5 mm spacer ring (800 x 600 at 60 fps). For all User Sets, Enable Acquisition Frame Rate must be selected. For User Sets other than User Set 2, either binning option has no effect when binning is equal to 1. Which User Set Is Currently Selected? Make sure that EthoVision XT is closed. Start the Basler Pylon Viewer software and in the Features panel, under Configuration Sets, look for the item Default Startup Set. This is the User Set that contains the current settings. Always check that the settings in Pylon Viewer for a particular User Set correspond to those in the table. Note: EthoVision XT reads the settings from the camera driver software. For a specific EthoVision XT experiment you can override the values of video resolution and frame rate stored in the driver, but not other settings. The maximum frame rates have been measured with a 96-well plate setup; other values may be optimal in other setups. Adjust the Camera Settings in EthoVision XT In EthoVision XT, choose Setup > Experiment Settings and click the camera button. Adjust the settings according to your chosen User Set configuration. For details, see Adjust Camera Settings in EthoVision XT in the EthoVision XT Help. Adjust the Camera Settings in Pylon Viewer You can also adjust the camera settings directly in the camera software Pylon Viewer. First choose a video resolution and frame rate combination, then mount the recommended camera lens, make the appropriate settings in Pylon Viewer, and finally adjust the appropriate settings in EthoVision XT. The following settings should be configured: - Pixel format - Analog gain - Center X and Center Y options - Horizontal and vertical binning - Acquisition frame rate and exposure time Tip: To preview the camera image, click the Continuous Shot button on the toolbar. Tip: You can increase the Analog gain to 2 or higher if you need a brighter image. However, the image noise will also increase, which may influence tracking. To save the settings, click the Stop button and open the Configuration Sets item. From the Configuration Set Selector list, select the User Set you want to save the settings to. Next to User Set Save, click Execute. Then from the Default Startup Set list, select the User Set you want to use on a daily basis. For more information about Pylon Viewer, see Configure the Digital Camera in the EthoVision XT Help. Camera View Check that the camera view is correct by placing a well plate in the DanioVision Observation Chamber. Make sure that: - The well plate is in the middle of the field of view, not rotated or skewed. - The well plate is in focus. If not, operate the focus ring of the camera lens. - Fixation screws of all rings on the lens are tightened. - The aperture is chosen such that the image appears slightly overexposed. With water in the well plate, the image is fine. When you create an EthoVision XT experiment, check that the video resolution, video frame rate, and color space match the settings for the User Set you want to use. Source: DanioVision DVOC-0050 Reference Manual - Set Up DanioVision, Noldus Information Technology --- ## DanioVision DVOC-0050 - Set Up DanioVision - Set Up DanioVision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-set-up-daniovision-set-up-daniovision Chapter: DanioVision Set Up DanioVision Connections - Temp out. Connector for the temperature sensor. Use this in combination with the DanioVision Temperature Control Unit (TCU). - TTL A and B. Use those ports to control external devices such as a speaker or an additional light source different from the available add-ons. Each TTL port contains two input lines (Input 1 and Input 2) and two output lines (Output 1 and Output 2). Which line you want to use must be specified in EthoVision XT (Trial Control Settings). - Trigger Out 1 and 2. BNC connectors for output TTL signals. Use those connectors to trigger the Prizmatix Pulser or the Prizmatics LED controller in Optogenetics experiments. If you work with three Pulsers or LED controllers, use one of the TTL connectors for the third device. For this you need a special cable from TTL and the BNC connectors of the Pulser/LED controller. - Ethernet port for controlling DanioVision from the EthoVision XT computer. - Ethernet port for the DanioVision camera. - Connector for water inlet. - 24 VOLT connector for the power supply. - Connector for water outlet. - Connector for water overflow. Connect DanioVision Video Use the Ethernet cable with the large round connector to connect the digital video output of the DanioVision Observation Chamber to the Ethernet port labeled DanioVision camera on the EthoVision XT computer. The DanioVision camera must be connected to a 1-Gb Ethernet interface board. Note that the port on the Ethernet must be given a compatible IP address, for example 192.168.1.51. If you have purchased a PC from Noldus together with DanioVision, this card is already installed and the correct IP is assigned. Contact Noldus if you need a new Ethernet card for the DanioVision camera. Ethernet To control the White Bottom Light, the Tapping Device, and other hardware, connect the Ethernet port of the DanioVision Observation Chamber to an Ethernet port on the EthoVision XT computer using the network cable with connectors of type RJ45 that comes with DanioVision. If you have purchased the computer from Noldus when you purchased DanioVision DVOC-0050, an Ethernet interface board with multiple Ethernet ports is already installed on that computer. In all other cases, we advise installing a dedicated Ethernet interface board with 2+ ports, so you can use the on-board Ethernet port to connect to the internet. IP Addresses of the Ethernet Ports The two Ethernet ports on the PC must be given different IP addresses: - Ethernet port connected to the Ethernet connector in DanioVision (number 4 on the back panel): 192.168.20.1 - Ethernet port connected to the DanioVision camera (number 5 on the back panel): 192.168.1.51 Power Connect the DanioVision Observation Chamber's 24 VOLT socket to the power supply using the power cable and adapter. Set Up a Water-Flow System If you require a temperature-controlled water flow underneath the well plate, the Noldus DVTCU Temperature Control Unit is the preferred method. The back panel of the DanioVision Observation Chamber contains three connections for controlling the water flow: a water inlet (marked in green), a water outlet (marked in yellow), and a water overflow (marked in red). Connect the DanioVision Observation Chamber to the DanioVision Temperature Control Unit using the tubes that match the color of the connectors. Suggested Temperature For Danio larvae, the temperature of the water flowing through the system is usually 28 degrees Celsius. You can set a different temperature when needed. Lights and Switches Main Switch The main switch is located on the front panel. After you switch on DanioVision, wait at least 15 minutes for it to start up and to avoid condensation in the system. Working Light The DanioVision Observation Chamber is equipped with an LED light to illuminate the inside of the chamber while you set up your experiment. This light should not be used during experiments. Operate the light switch at the left of the camera to turn the light on and off. Button for the White Bottom Light This button is located on the metal frame at the right side of the camera. Press the button to switch the White Bottom Light on. Press more times to adjust its intensity. Once the maximal intensity is reached, press once to switch the light off. Operate this button for example to have more background light when you check the larvae. - To have the White Bottom Light switched on by default during your trials, see the Trial Settings section. - For examples of how to use the White Bottom Light in your experiments, see the Experiments section. Anti-Moisture Switch This switch is located on the metal frame, at the left of the camera. Operate this switch to adjust the anti-condensation mechanism. Install EthoVision XT Before You Start - If you have purchased the DanioVision Observation Chamber including a computer from Noldus Information Technology, all software has been installed and tested. You can skip this section and proceed to Set Up EthoVision XT. - If you use your own computer, or a computer you bought from Noldus IT in the past, make sure it meets the EthoVision XT system requirements. For information about system requirements, press F1 in EthoVision XT. Install EthoVision XT - If you do not have the EthoVision XT installation files, browse to the MyNoldus portal at https://my.noldus.com/download/latest/ethovision-xt. Log in or register (if you are a new user you can use the registration code found on the Welcome letter). Click Versions and download the EthoVision XT Installation Package [version number].zip. Save the zip file on your PC. If you store the zip file on a network drive, copy it to your PC before the next step. - Unzip and extract the files on your computer. - Double-click EthoVision XT - Setup - [version number].exe. - Continue installation choosing the interface language and the type of installation (Standard). Then click Next. - Accept the default Application location and Experiments location. - Under Drivers and Tools, select the Basler GigE camera driver. - Complete installation and click Close. Upgrading Old Experiments When you open an experiment from EthoVision XT 12 or earlier, a warning appears informing you that you cannot open upgraded experiments in the old version of the software anymore. Do one of the following: - If the older EthoVision XT version is still on the PC, make a backup of your DanioVision experiment in that version before opening it in EthoVision XT. To make a backup, choose File > Make Backup. - If the older version is no longer on the PC, you cannot use the Backup function. Instead, make a copy of your experiment using Windows Explorer before you open it in the newer EthoVision XT version. Always copy the complete experiment folder and not only the *.evxt file, otherwise your experiment will not open. Keep the original experiment as a backup. For More Information See the Installation section in the EthoVision XT Help for more details about installing EthoVision XT. Drivers and Additional Software Camera Driver Software If, for any reason, you need to re-install the driver software of the DanioVision camera, do the following: - Double-click the file EthoVision XT 18 - Setup [version number].exe and choose Modify. - Under Drivers and Tools, select to install the Basler GigE Camera driver and follow the instructions on the screen. If you do not have the installation files, download the EthoVision XT Installation Package from the MyNoldus portal. Installing the Camera Driver Software from the Installation File You can download the single installation file for the Basler camera driver. If you choose this route you must select the custom setup as described below. Follow the instructions carefully. - After login, choose Downloads > EthoVision XT > Drivers and Tools and under Drivers for the current version download Basler Pylon Camera Driver - Noldus - [latest version]. Extract its content and copy everything to the local disk. - Double-click Basler_pylon_[version number].exe. Accept the Terms and Conditions, then click Next. - Under Profiles, select Custom and click Next. - Under Features, choose GigE Camera Support. This applies to the DanioVision camera. Make sure to select pylon Viewer and DirectShow Support. - Complete the installation. For more information, open the EthoVision XT Help and browse the Camera Installation chapter. DanioVision Hardware Interface Software The hardware interface software for DanioVision DVOC-0050 is installed automatically when you install EthoVision XT. - To de-install this software, open the Windows Control Panel, select Programs and Features, click Noldus HardwareInterface DanioVision - x64 Package - 1, and select Uninstall. - To re-install the DanioVision interface software, run installation of EthoVision and select Repair. Note: Older versions of DanioVision are controlled by the Noldus HardwareInterface IoBox x64 Package 5. You can uninstall that software provided that you are sure you no longer use older versions of DanioVision and any version of the USB-IO box in combination with EthoVision XT. Install the Network Interface Board If you ordered a computer from Noldus Information Technology when you purchased DanioVision, it came with the card already installed and tested. You can skip the instructions below and continue with the Check the DanioVision System section. If you bought your computer somewhere else, you have to install the Ethernet card yourself. Type of Ethernet Interface Board In order to use DanioVision, you need to have a 1-Gb Ethernet interface board (also named Network Interface Card, NIC) installed on the EthoVision XT computer. For DanioVision DVOC-0050, you need an Ethernet board with at least two ports: one for the DanioVision camera and one for controlling the various devices inside DanioVision. Step 1: Insert the Ethernet Card in the DanioVision Computer - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's casing according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. --- ## DanioVision DVOC-0050 - Set Up DanioVision - Set Up DanioVision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-set-up-daniovision-set-up-daniovision-tju Chapter: DanioVision Set Up DanioVision PCIe Slot Performance When possible, choose the slot that gives maximum performance. To estimate performance, take note of the slot version (2, 3, etc.) and compare it with the following values: - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: ~1 GB/s - PCIe v4.0: ~2 GB/s - PCIe v5.0: ~4 GB/s - PCIe v6.0: ~8 GB/s Note that values are given per lane; they should not be multiplied by the number of lanes in a slot (e.g. x4) since the card has a 1x connector (that is, one lane). For example, SLOT1-PCIe3x4 means version 3.0 with four lanes. Important: Do not insert the PCIe board in the blue or white slots. Step 1: Install the Ethernet Card - Unpack the Ethernet card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. - When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Fix the card to the chassis and re-fit the computer's cover. For more information about installing the camera and the Ethernet board, see Camera Installation in the EthoVision XT Help. Step 2: Install the Camera Driver The camera driver is already installed when you installed EthoVision XT, provided that during installation under Drivers and Tools you selected Basler GigE camera driver. If you have not done so, follow the instructions below. - Download the camera driver software from my.noldus.com. Log in or register, then choose Downloads > EthoVision XT > Drivers and Tools. Under the EthoVision XT version that applies, download the Basler Pylon Camera Driver - Noldus - [version number]. - Double-click Basler_pylon_[version number].exe. Accept the Terms and Conditions, then click Next. - Under Profiles, select Custom and click Next. - Under Features, choose GigE Camera Support. Also select pylon Viewer and DirectShow Support. - Complete the installation. - Connect an Ethernet port on your computer to the Ethernet port of DanioVision using a network cable. Step 3: Assign the IP Address to the Ethernet Card Tip: Watch the video tutorial Set Up the Camera. In EthoVision XT, choose Help > Video Tutorial. For DanioVision DVOC-0050: Repeat this procedure two times — once for the port of the Ethernet board for connecting the camera, and once for the other connection. - In Windows (version 10), search for Network Connections. - Right-click the Local Area Connection and click Properties. If your computer has more than one Local Area Connection, choose Basler GigE Vision Adapter. Write down the number of this connection. Tip: To identify which port each item refers to, disconnect the cable from that port and check where the Disconnected symbol appears. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Select the options Use the following IP address and Use the following DNS server addresses, and fill in the details as follows: - Ethernet port connected to the DanioVision camera: 192.168.1.51 - Ethernet port connected to the Ethernet connector in DanioVision: 192.168.20.1 - Also select the checkbox Validate settings upon exit. When done, click OK and then Close. Step 4: Set the IP Address of the DanioVision Camera Tip: Watch the video tutorial Set Up the Camera. In EthoVision XT, choose Help > Video Tutorial. - In Windows, search for IP Configurator and start this application. - Select the camera. - Fill in the details in the IP Address and Subnet Mask fields under Static IP Address. - Click Save and then Close. - Follow the instructions below to configure the DanioVision camera. For more information about setting IP addresses, see Install GigE Cameras in the EthoVision XT Help. Step 5: The IP Address of the DanioVision Chamber The IP address of DanioVision DVOC-0050 is 192.168.20.50 and is set at production. Please make sure the IP address that you set on the Ethernet port of the PC connected to the Ethernet connector of DanioVision matches that IP address — that is, the first three numbers must be the same: - Ethernet port on DanioVision: 192.168.20.50 (preset) - Ethernet port on PC: 192.168.20.1 --- ## DanioVision DVOC-0050 - Set Up EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-set-up-ethovision-xt Chapter: DanioVision Set Up EthoVision XT Prerequisites Connect the DanioVision Observation Chamber to the EthoVision XT computer. Optionally, set up the water-flow system. Turn on the DanioVision Observation Chamber with the switch on the front panel. Wait at least 15 minutes for the DanioVision chamber to start up. Make sure to remove the lens cap from the camera. Assign Treatments to Wells To prevent systematic errors as a result of potential variation in temperature, light intensity or other unknown variables across a well-plate, it is recommended to either assign larvae from different treatments randomly to the wells or make sure that wells containing different treatments (that is, different solutions or different concentrations of the same solution) are evenly distributed across the well-plate. For example, one type of solution should not be placed only in the center wells. Create a DanioVision Experiment Preferred Method With this method, all arenas are created automatically but need to be manually adjusted using the Arrange Arenas option. Unnecessary functionality like manual scoring is removed from the interface and detection settings are optimized for DanioVision. - In the EthoVision XT Startup window, under New Experiment, click New from Template, or choose File > New from Template. - In the Select a Template option window, click Apply a Pre-Defined Template. Next, follow the instructions described below. - Which video source will you use? Select the option Live Tracking (and Saving Video Files), click the Sources button and select the Basler camera. Click Next. - Which subjects will you track? Select Fish and then Zebrafish Larvae from the list. Click Next. - How is the arena configured? Select an Arena template from the list, then click Next. - Select one of the Well Plate or Open Field templates if you have a number of wells other than those listed in the other templates. - Arena templates are also present for older DanioVision DVOC versions: DVOC 001x to DVOC 004x. - To know which DanioVision version you have, see the code DVOC-00xx on the label located on the back panel of the DanioVision chamber. - Initialize the template experiment. Check that all settings are correct and, if so, click Finish. - Enter the name of the experiment and click OK. The EthoVision XT Overview window opens. - Follow all the next steps: - Experiment Settings - Arena Settings - Trial Control Settings - Detection Settings Notes: - If you select a template which contains more arenas than needed, you can exclude the unused arenas with Data Selection. - If you select a template for a DanioVision 1–3 version, it is possible that the DanioVision detection method does not give optimal detection of the larvae with images from your camera. If that is the case, try changing the Sensitivity or use another detection method in the Advanced section of the Detection Settings pane. See also Configure Detection Settings in the EthoVision XT Help. - You can also create an experiment based on a previous experiment — for example, when you want to replicate an experiment with the same number of arenas and the same trial control procedures. Choose File > New from Template > Apply a Custom Template. For details, see Create a New Experiment Based on an Existing Experiment in the EthoVision XT Help. - You can also create a DanioVision experiment with no predefined settings. With this option you must draw the arenas and arrange them manually. Choose File > New and in the window that appears select the option DanioVision Experiment. In the Experiment Settings, next to Number of Arenas, enter the number of wells. Creating an experiment with a predefined template is advised because the arenas are defined automatically. For more information on creating an experiment manually, see Set Up an Experiment in the EthoVision XT Help. - No matter which method you choose, when you create a DanioVision experiment, unnecessary functionality like Manual Scoring Settings is removed from the interface and detection settings are optimized for DanioVision. Experiment Settings Choose Setup > Experiment Settings. Video Source - Under Video Source, click the Video icon on the right side of the row of your camera. - In the Video Settings window that appears, click the Formats tab and select the Resolution and Frame Rate. The default resolution is 1280 x 960 at 30 frames per second. If you create an experiment based on a template with the Tapping Device, set the frame rate to 60 fps and reduce the resolution according to your setup. From the Color Space list, choose Y800. This is the color space for a monochrome video image. The other options, suitable for color images, do not apply to DanioVision. Tracked Features Specify whether you want to track the center point of the fish (default) or the center point, the nose point, and the tail base. Choose the latter option only if you are tracking fish in a close-up image. Body Point Detection Technique The Contour-based technique is selected. The Deep Learning option is not available in DanioVision experiments. Analysis Options If you are interested in how long and how frequently your subjects have been active versus inactive, select Activity Analysis under Analysis Options. Make sure you also adjust the Activity settings in the Detection Settings. For more information about setting up an experiment, see Set Up an Experiment in the EthoVision XT Help. Use of Trial Control Hardware Follow this section if you use stimulus devices like the white/color lights and the tapping stimulus device. - In the Experiment Settings, under Trial Control Hardware, make sure that Use of Trial Control Hardware is selected and click the Settings button. - In the Hardware Interface window that opens, choose the type of system you have. If you have DanioVision DVOC-0050, choose DanioVision DVOC-005x/TCP. The other options (DanioVision DVOC-001x – 004x), if present, are meant for older versions of the DanioVision Observation Chamber. - In the Device Configuration window, under Device Features, the hardware devices activated for this experiment are listed. - Optionally, the default status of the DanioVision White Bottom Light is Light Off. This means that when you start a trial, the White Bottom Light is switched off. To use the White Bottom Light as a stimulus, program its activation with Trial Control. If, however, you want to use the White Bottom Light as a default lighting condition and use darkness as a stimulus, do the following: - Click the White Light Default button. - Under Default Device State, select Light On. - Choose a percentage of intensity (0–100) and click OK. Then in the Trial Control procedure you can program when to switch the light off. - Optionally, if you connect additional hardware, under Plug-in Devices, select the Device Type in the corresponding rows depending on which ports on the DanioVision back panel you use to connect those devices. - TTL Port A / TTL Port B: For example, if the DanioVision Temperature Control Unit is connected to the DanioVision chamber through TTL Port A, choose DanioVision TC (DVTCU-001x) from the list next to TTL Port A. If you connect other devices, choose Custom Hardware. - Trigger Out: If you connected the Optogenetics triggering devices or LED controllers to the DanioVision chamber through the Trigger Out BNC connectors, choose Optogenetics from the list next to Trigger Out. If you connected other devices through the BNC connectors, choose Custom Hardware. - Optionally, edit the name in the Device ID field. - Click OK. - Optionally, if you set the default state of the White Bottom Light to Light On, open the Trial Control Settings. This will confirm your selection. From that moment on, the White Bottom Light switches on at the start of the trial. Notes: - If you upgraded an experiment from an older EthoVision XT version, do not change the Trial Control Hardware Settings in the Experiment Settings. For example, if you see Noldus Mini USB-IO Box selected in the Hardware Interface window, leave it as is. Otherwise the Trial Control rules — for example, to control the white light — may not work. - When you change the default state of the White Light Stimulus to Light On, the white light is only switched on in one of the following cases: - When you open the Trial Control screen. - When you open the Arena – Hardware Mapping window. - When you start a trial. - For more information on Trial and Hardware Control, see the EthoVision XT – Trial and Hardware Control – Reference Manual. IP Settings To ensure communication between DanioVision DVOC-0050 and EthoVision XT, the IP address of the Ethernet port on your computer connected to DanioVision must be configured correctly. DanioVision DVOC-0050 is connected to your computer through the Ethernet port at the back of the chamber labeled Ethernet. This port has a specific, unique IP address: 192.168.20.50. If you purchased the computer from Noldus, the IP address is already set and you can skip this section. Otherwise, follow the instructions below. - In the Experiment Settings, under Trial Control Hardware, make sure that Use of Trial Control Hardware is selected and click the Settings button. - In the Hardware Interface window that opens, choose DanioVision DVOC-005x/TCP. - In the DanioVision Configuration window, click Settings and verify that the IP address is 192.168.20.50. - Open the Network and Sharing Center in Windows. In the Windows Search field, type Control. Under Best Match, click Control Panel, then Network and Sharing Center, then click Change Adapter Settings at the top-left corner of the window. - Open the adapter settings and locate the item that corresponds to the port on your PC connected to the Ethernet connector on the back panel of DanioVision. To identify which port each item refers to, disconnect the cable from that port and check where the Disconnected symbol appears. - Set the IP address, for example 192.168.20.1, and assign the IP address to the Ethernet card. Notes: - If the DanioVision Configuration window shows the message Not Connected to DanioVision, do the following: - Make sure that the DanioVision chamber is switched on. Check the green LED light on the front panel. - Check the cables between the computer and DanioVision. - Make sure that the IP addresses of the Ethernet ports on the computer match those in DanioVision. - Click Refresh. Source: DanioVision DVOC-0050 Reference Manual - Set Up EthoVision XT, Noldus Information Technology --- ## DanioVision DVOC-0050 - Tapping Device URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-tapping-device Chapter: DanioVision The DanioVision Tapping Device Introduction Larval stage zebrafish display a robust startle response, which is mediated by neural pathways similar to that in higher vertebrates. With the DanioVision Tapping Device you can evoke a startle response in zebrafish larvae. How the Tapping Device Works The DanioVision Tapping Device is based on an electromagnetically inductive coil wound around a metal core. The core is made of two parts, a fixed one and a plunger connected to a push pin. When a current flows in the Tapping Device, magnetic force is created between the plunger and the core, causing the plunger and the push pin to quickly move forward. The pushpin hits a metal plate attached to the basin in which the well plate is kept. When deactivated, a spring makes the plunger resume its position. Controlling the Tapping Device With the Trial and Hardware Control module of EthoVision XT you can plan when to activate the Tapping Device during a trial. For example, activate the Tapping Device 10 times at intervals of two minutes. Noldus Test Results: A Summary - In both light and dark conditions, the Tapping Device is capable of inducing a startle response in animals of 3 dpf and older. - It is in principle possible to design experiments where the animals are subject to stimuli of different intensity. You can set the tap intensity in EthoVision XT. - There is no evidence that the startle response measured by EthoVision XT depends on light conditions and location of the subject in the well plate. Important: We advise you not to compare the results between two DanioVision Observation Chambers provided with the Tapping Device. Slight differences in the position of the Tapping Device may result in differences in the actual stimulus intensity, all else being equal. Install the DanioVision Tapping Device If you order the Tapping Device together with a DanioVision Observation Chamber, the Tapping Device is already installed. In all other cases: - Open the lid of the DanioVision Observation Chamber, and remove the bench plate. - Remove the two bolts from the aluminium plate at the bottom of the chamber. Make sure that the backlight box does not move. Tip: Use a pencil to mark the exact position of the backlight box on the frame so that you can place it in that position if it accidentally moves. - Put the metal frame of the Tapping Device over the aluminium profiles, and fix the bolts with the supplied spring washers. Use both the already connected spring washers and the new ones. - Connect cables as indicated: - The cable with a 4-pin white connector comes from the Tapping Device. - The flat cable with a blue connector comes from the bottom of the DanioVision chamber. Raise the metal hooks, insert the connector, then lower the hooks to fix the connector. - The cable with a 2-pin connector comes from the bottom of the DanioVision chamber. - Attach the control box to the aluminium profile at the front side of the observation chamber: - Insert the screw in one of the holes at the sides of the control box. - Attach the spacers and the sliding nuts to the screw. - Insert the sliding nuts into the profile, and turn the screw. - Put the bench plate back into place and fix the four screws. Set Up the Tapping Device in EthoVision XT Make sure that the DanioVision Observation Chamber is connected to your EthoVision XT computer. Experiment Settings - Under Trial Control Hardware select Use of Trial Control Hardware, then click Settings. - In the Hardware Interface window, select DanioVision DVOC-0050/TPC. Tip: You can find your DanioVision version number on the label at the back of the chamber. - When needed, adjust the default light settings for the White Bottom Light. Make sure the message at the bottom of the Hardware Interface window reads Connected. Click Refresh when necessary. - Click OK and go to the next section. Arena Settings Note: If you created an experiment with a pre-defined template and selected an arena template for DanioVision with the Tapping Device (DanioVision DVOC 00xx/T, xx wells), the Tapping Stimulus has been assigned automatically to the arenas. You can skip the steps below and go to the next section. - Open the Arena Settings you want to use. - In the Arena Settings pane click Arena - Hardware Mapping and then click the Arena - Hardware Mapping button. - Click Add Device. - In the new row that appears, under Device Type, select Tapping Stimulus. - Under A1 or Arena 1 (depending on how the arenas are named), select Tapping Stimulus. - To test the Tapping Device, select the cell under A1/Arena 1 and click Test. Trial Control Settings - Open the Trial Control Settings containing the protocol in which you want to insert the Tapping Stimulus. Under Actions - Hardware click the button next to Tapping Stimulus. - In the Hardware Action window: - Enter the Action Name. - Specify the Intensity (0% to 100%). - Click Test to get an impression of the tap intensity. - When ready, click OK. - Insert the Action box in your Trial Control protocol. - Insert Condition boxes and, when required, Sub-rules to create routines. Test the protocol before carrying out the real trials. Important: Allow at least 300 milliseconds between two consecutive tapping events. To do so, place a Time Condition box that specifies this time (> 0.3 sec) between two Tapping Stimulus Action boxes. Note: If the Tapping Device does not respond to the test action, for example after it has not been in use for a long time, open the bench plate and use a screwdriver to gently push the pushpin back, then release it so that it hits the metal plate, as if it was activated. Do this a few times and then test the action again. Also check the connections inside. Tapping Stimulus Routine If you have created an experiment from a DanioVision template with the Tapping Stimulus Device (DVOC-0050_T), you can find an example of a routine with the Tapping Stimulus under Trial Control Settings. Analyze the Response to the Tapping Stimulus Aim You can analyze the startle response by looking at dependent variables like Activity, Distance Moved, or Acceleration (state) immediately before and after the administration of the stimulus. Example We examine the Total Distance Moved in two intervals: (1) a 5-second interval immediately before the tapping stimulus command, used as a baseline, and (2) a 1-second interval after the tapping stimulus command. We expect that the total distance moved increased from "before" (assumed to be a baseline) to "after". Procedure - Open or create a Data Profile. - Interval "before": In the Data Profile, under Nesting click the button next to Free Interval. Define an interval from 5 seconds before the action "Tapping Stimulus" was active to 0 seconds after the action "Tapping Stimulus" was active. - Interval "after": In the Data Profile, under Nesting click the button next to Free Interval. Define an interval from 0 seconds before the action "Tapping Stimulus" was active to 1 second after the action "Tapping Stimulus" was active. - Click the button under Common Elements, next to Result. Place the Result box under the existing one. Each of the resulting Nest boxes is connected to a separate Results box. - In the Analysis Profile define Distance Moved. - Choose Analysis > Results > Statistics and Charts. Source: DanioVision DVOC-0050 Reference Manual - Tapping Device, Noldus Information Technology --- ## DanioVision DVOC-0050 - Temperature Control Unit - Feedback and Error Messages URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-temperature-control-unit-feedback-and-error-messages Chapter: DanioVision Feedback and Error Messages The DanioVision Temperature Control Unit gives feedback about its status with four LED lights and error codes on the temperature display. LED Indicators - Filling/Draining – Orange blinking: System is pumping. The system can be filled with water, water can be drained from the basin, or cooling liquid can be filled. - Filling/Draining – Red continuous: Time out. There has been no flow in the water circulation and/or the cooling liquid circulation for more than 10 minutes. Reset the system by turning the Operation switch to Off and then back to Fill/Drain. - Heating/Cooling – Green blinking: The water is being heated or cooled to the set temperature. Wait; no action needed. - Ready – Green continuous: The set temperature has been reached and the system is ready to be used. An experiment can be started. - Error – Red, 1 blink repeatedly: Insufficient flow in the water circulation. Look for the source of the problem. This may be: - Low water level in the basin due to evaporation or leakage. In this case, fill the system. - Flow blockage somewhere in the system or filter clogged. Replace the filter or contact Noldus. - Pump failure. The Fill/Drain mode can be used to localize the problem. Reset the system by setting the Operation switch to Off and then to Fill/Drain. - Error – Red, 2 blinks repeatedly: Insufficient flow in the cooling liquid circulation. Look for the source of the problem. This may be: - Low cooling liquid level in the pump reservoir. Check if the liquid level is above the indication. If not, refill cooling liquid and check for signs of leakage in the emergency liquid container. - Flow blockage somewhere in the system. - Pump failure. The Fill/Drain mode can be used to localize the problem. Reset the system by setting the Operation switch to Off and then to Fill/Drain. - Error – Red, 3 blinks repeatedly: The fan is not spinning, or not spinning at sufficient speed. Check if there is anything blocking the fan. If this is not the case, please contact Noldus support. - Error – Red, 4 blinks repeatedly: System is overheated. Turn off the system and end the experiment. Cooling liquid can be cooled down by switching the Operation switch to Fill/Drain. Search for the possible cause of the overheating: - Air vents of the Temperature Control Unit might be blocked so the radiator cannot dissipate heat. Make sure air vents are free. - System is used in environmental conditions that have not been tested, for example, room temperature above 35°C. - Error – Red, 5 blinks repeatedly: Heating and cooling have been activated simultaneously. An electrical problem has occurred. Please contact Noldus support. - Error – Red, 6 blinks repeatedly: A problem with the data logger has occurred. Open the TCU and take the SD card out. - If it is locked, unlock it. - Check that it has a minimum capacity of 4 GB. Put the SD card back in the TCU. If the error persists, take the card out and format it (FAT32). Leave the card empty; do not copy the old files to the newly formatted card. Put the SD card back in the TCU and restart the TCU. - Error – Red continuous: A temperature deviation larger than 0.5°C above or below the set temperature has been detected. Water conditioning will continue to try to resolve the situation. Once resolved, the status returns to 'Ready'. Depending on your protocol you can choose to continue or abort the experiment. Temperature Display Codes - Code 1: The water is being heated to the set temperature. - Code 2: The water is being cooled to the set temperature. - Code 3: The current water temperature is at least 0.5°C below the set temperature. It is shown together with temperature alarm code E05. In normal conditions, when code 3 is shown, code 1 is also shown and the red Error LED (continuous) is on. - Code 4: The current water temperature is at least 0.5°C above the set temperature. It is shown together with temperature alarm code E04. In normal conditions, when code 4 is shown, code 2 is also shown and the red Error LED (continuous) is on. - Error mode: This is a system setting indicator, which blinks when the TCU is in heating/cooling mode. No action need be taken. Error Codes - LCD is off: A possible reason is that one of the flat cables coming from the LCD display is not properly connected. Open the DV-TCU, locate the multi-color flat cable (3rd to the right of the SD card), disconnect it and connect it again. - E01: The temperature sensor is not detected. Please connect the temperature sensor cable (with cinch-plugs on both ends). - E04: 'Too high' temperature alarm. The measured temperature is 0.5°C higher than the set temperature. Depending on your protocol you can choose to continue or abort the experiment. Please note that this error also occurs while the system is heating/cooling before the start of the experiment; the system continues to heat/cool to try to resolve the error. Error Codes Error Code Explanation What to Do E05 'Too low' temperature alarm. The measured temperature is 0.5 °C lower than the set temperature. Depending on your protocol you can choose to continue or abort the experiment. Please note that this error also occurs while the system is heating/cooling before the start of the experiment. Ed1 System error. See the Status = Error section for further guidance. nO Another display has been selected accidentally. - Press the up or down arrow until the code b1 appears on the display. - Press the Set button for three seconds to confirm. Source: DanioVision DVOC-0050 Reference Manual - Temperature Control Unit, Noldus Information Technology --- ## DanioVision DVOC-0050 - Temperature Control Unit - The DanioVision Temperature Control Unit URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-temperature-control-unit-the-daniovision-temperature-control-unit-88h Chapter: DanioVision The DanioVision Temperature Control Unit Connect the Network Cable Connect the network cable between one of the TTL ports on the back panel of the DanioVision Observation Chamber and the TTL port on the back panel of the DanioVision Temperature Control Unit. Note: If you have the DanioVision Observation Chamber DVOC-0030 or older, connect the TTL port of the Temperature Control Unit to TTL ports 3 or 4 on the Observation Chamber. Do not use TTL port 2! Define the Temperature Alarm in EthoVision XT - In EthoVision XT, create a DanioVision experiment. - In the Experiment Settings, under Trial Control Hardware, click the Settings button. Select the version number of your DanioVision Observation Chamber and click OK. - In the Device Configuration window, under Plug-in devices, choose the TTL port that you used to connect the Temperature Control Unit. Under Device Type, select DanioVision TCU (DVTCU-001x). Under Device ID, type in a name or accept the default name DanioVision TCU (DVTCU-001x) 1. Next, click OK. - Choose Setup > Arena Settings > Open and choose the Arena Settings you use in the experiment. In the Arena Settings window, click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, click the Add Device button. - In the new row that appears, under Device Type select DanioVision TCU (DVTCU-001x). Under Device Name enter a name, for example "TCU Temp Alarm". In the column A1 (or Arena 1, depending on how the first arena is named), select the Device ID that you defined above. - Click OK. EthoVision XT is now ready to log the alarm signals from the TCU. Possible Alarm Signals The following TTL signals are sent to EthoVision XT and can be used as usual in the Trial Control Settings and Analysis Profiles: - When the current water temperature is within the normal temperature range, that is, a temperature that deviates by less than 0.5 °C from the set temperature [Tset - 0.5°C ≤ Tcurrent ≤ Tset + 0.5°C], no alarm is given. Both Low Temp Error State and High Temp Error State are false. - When the current water temperature is more than 0.5 °C lower than the set temperature (Tcurrent < Tset - 0.5°C), a low-temperature alarm is given and Low Temp Error State becomes true. - When the actual water temperature is more than 0.5 °C higher than the set temperature (Tcurrent > Tset + 0.5°C), a high-temperature alarm is given and High Temp Error State becomes true. - When you turn off the Temperature Control Unit or unplug the network cable from the TTL port, both Low Temp Error State and High Temp Error State become true. Note: During a temperature alarm, the TCU tries to bring the temperature back to the normal range, so you do not need to take any particular action. Program the Temperature Alarm Use a temperature alarm in the Trial Control Settings, for example to stop tracking or start an external program when a temperature alarm occurs. The following steps describe how to program the alarm based on the water temperature. Note: During a temperature alarm, the TCU tries to bring the temperature back to the normal range, so you do not need to take any particular action with Trial Control. - Prerequisite: You have defined the temperature alarm in EthoVision XT. - Choose Setup > Trial Control Settings > Open (an existing profile) or New to create a new profile. - In the Trial Control Settings, under Conditions, click the button next to DanioVision TCU (DVTCU-001x). - The Hardware Condition window appears. In the Condition Name field, enter a name for the condition; for example, "TCU Low Temp Alarm". - From the DanioVision TCU list, select the device name that you defined in the Arena - Hardware Mapping window. The name listed next to DanioVision TCU could be Device A, Device B, etc., or for example "TCU Temp Alarm", depending on whether you edited the device name in the Arena - Hardware Mapping window. - Choose one of the following: - To take an action when an alarm occurs, next to Signal to Check choose either Low Temp Error State? or High Temp Error State? depending on the alarm you want to use. Then next to Signal Value select true. - To take an action when the number of temperature alarms reaches a certain value, next to Signal to Check choose either Low Temp Errors or High Temp Errors and select the threshold of alarm errors. - Insert the condition box in the Trial Control rule. Where to place the condition depends on what you want to happen. For example, if you want EthoVision to stop tracking when the condition is met, place the condition box immediately before the Action - Stop Track box. For more information about working with conditions and actions, see Trial Control in the EthoVision XT Help and the EthoVision XT Trial and Hardware Control Reference Manual. The Temperature Alarm in Data Analysis You may want to visualize alarm events in the Integrated Visualization. This way you can review your trials and see if something has changed in the behavior of the larvae during or after those alarm events. - In an Analysis Profile, under Hardware, click the button next to Hardware State. - Next to Device Type, choose DanioVision TCU (DVTCU-001x). - Next to Device, choose the name given in the Arena - Hardware Mapping window (for example, "TCU Temp Alarm"). - Next to Signal, choose one of the following: - To visualize or calculate the duration of the time that the system was in temperature error state during the trial, select Low Temp Error State for a low-temperature alarm, or High Temp Error State for a high-temperature alarm. Next to Value select true. Select false if you want to visualize or calculate the time that there was no temperature alarm. - To visualize or calculate the duration of the time when the system had more or less than a certain number of temperature error alarms, choose Low Temp Errors or High Temp Errors. Choose whether the number of errors was higher, lower, or equal to a threshold value. Keep the option Cumulative selected. - In the Trial Statistics tab, select the statistic you want and click OK. - Optional: Right-click the row Hardware State and select Rename. Enter a custom name; for example, "Hardware State Low Temp Alarm". - Choose Analysis > Results > Plot Integrated Data. The Temperature Alarm in the Hardware Log To export the hardware log that contains the TCU alarm events, do the following: - Choose Analysis > Export > Raw Data. - In the Raw Data Export window, make sure to select the Hardware Log check box. - Click Start Export to export the data. Carry Out an Experiment Before You Start If you want to log temperature errors, configure EthoVision XT beforehand. See the Temperature Alarm (Optional) section for details. Procedure - Set the water temperature by following the procedure described in the Normal Use with Set Water Temperature section. - Wait until the temperature has reached the set value and no error codes appear on the LCD screen of the TCU. - Insert a well plate with the larvae into the basin. To prevent air getting trapped underneath the well plate, put the back of the well plate against the wall with the shape of "∧" and place it on the basin floor, then tilt the front of the well plate down to the basin floor. As you do this, water flows into the overflow part of the basin. - Lower the Fresnel lens over the well plate and close the DanioVision Observation Chamber. You can now carry out a DanioVision experiment as usual. - If necessary, grab a background image, define the arenas, and define the Detection Settings. See also the EthoVision XT Help. - Choose Acquisition > Open Acquisition. Start the trial. - At the end of the experiment, follow the procedure in the Drain the System section. Draining prevents contamination from building up inside the system. Before you drain the system, make sure the drain tube with blue connector ends in a sink or container. View the Temperature Alarms During the Trial - On the Temperature Control Unit: If an error occurs in the Temperature Control Unit, an error message appears on the display. See the Feedback and Error Messages section for an explanation. - On the EthoVision XT Screen: - Choose Show/Hide > Show Dependent Variable. - From the Select Hardware list, choose Hardware State. Click OK. - Next to Device Type choose DanioVision TCU (DVTCU-001x). Choose the signal you want to display. Click the Statistics tab and choose the statistics of that signal that you want to display. Tip: Choose Current to display whether a temperature alarm is occurring. - During acquisition, in the Analysis Results and Scoring pane click the Dependent Variables tab. There you can view the alarm state under the arena A1. Here, true means error state. Refill the Basin During Long Experiments The Basin Refill Tool During prolonged DanioVision experiments, evaporation of water out of the basin could be an issue. You can compensate for evaporation by refilling the basin without opening the DanioVision Chamber. The Basin Refill Tool (DVBR-0010) allows you to refill the basin without opening the DanioVision Chamber during an experiment. It is provided standard with the DanioVision Temperature Control Unit (DVTCU). Important: It is possible to fill or refill the basin directly by pouring water into the basin; however, this is not practical when an experiment is running. Only use the Basin Refill Tool in combination with the DanioVision Temperature Control Unit (DVTCU). Set Up the Basin Refill Tool Complete these steps before starting the experiment. - Make sure your DanioVision basin is empty by following the instructions in the Drain the System section. - Disconnect the tube marked in green between the DanioVision Chamber and the Temperature Control Unit (when applicable). - Connect the ends of the tubes of the Basin Refill Tool to the corresponding green-marked inlets at the back of the DanioVision Observation Chamber and the Temperature Control Unit. - Make sure the faucet of the Temperature Control Unit is closed (Off position). - Fill the syringe with basin liquid, and connect it to the short faucet tube. - Fill the basin circuit. Tip: While the basin circuit is being filled, insert a few ml of liquid from the syringe in order to prevent air bubbles from getting into the circuit. - Start the experiment as usual. --- ## DanioVision DVOC-0050 - Temperature Control Unit - The DanioVision Temperature Control Unit URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-temperature-control-unit-the-daniovision-temperature-control-unit Chapter: DanioVision The DanioVision Temperature Control Unit Introduction The Temperature Control Unit DVTCU-001x allows you to set up a temperature-controlled water flow underneath the well plate in the DanioVision Observation Chamber. The result is a constant temperature in the well-plate throughout an experiment. If you purchase the Temperature Control Unit, you get all the accessories necessary to work with the DanioVision system. Note: DanioVision users with a DanioVision Observation Chamber purchased before 25 January 2013 must upgrade their DanioVision Observation Chamber in order to be able to work with the Temperature Control Unit. Please contact your Noldus sales representative for more information. Workflow - Connect the DanioVision TCU. See below. - Set up the DanioVision TCU. See the Setup section. - Temperature alarm (optional). See the Temperature Alarm section. - Carry out an experiment. See the Experiment section. Important: After the experiment, drain the DanioVision Observation Chamber and the DanioVision Temperature Control Unit. Also keep the tubing far from sunlight to prevent algae growth inside the tubing. See Drain the System. Connect the DanioVision TCU Important: If you use a DanioVision system of version DVOC-0020/-0021, you need to upgrade your DanioVision Observation Chamber to be able to connect the Temperature Control Unit. Contact your nearest Noldus office for more information. Important: Make sure you place the DanioVision Temperature Control Unit at the same level as the DanioVision Observation Chamber. If that is not possible, place the DanioVision Temperature Control Unit at no more than 1.3 m below the DanioVision Observation Chamber. Accessories The Temperature Control Unit includes: - A 1.5 m color-coded drain tube. Note: For connecting the DanioVision Temperature Control Unit, you also need the color-coded tubes that come with the DanioVision Observation Chamber DVOC-0050. - A cable for the temperature sensor with a cinch-plug on both ends. - A 3-m network (UTP) cable to connect the TTL ports on the Temperature Control Unit and the DanioVision Observation Chamber. - A bottle of liquid coolant and a funnel to fill up the coolant. - The Basin Refill Tool, for filling the DanioVision basin with liquid without opening the DanioVision Observation Chamber. - A power adapter GST120A24 and a power cord. Connection Procedure Connect the tubes between DanioVision and the TCU as follows: - Connect the tube with the green color code to the connectors with the green ring on both the DanioVision Temperature Control Unit and the Observation Chamber. This is the tube through which water flows into the DanioVision Observation Chamber. - Connect the tube with the yellow color code to the connectors with the yellow ring on both the DanioVision Temperature Control Unit and the Observation Chamber. This is the tube through which water flows out of the DanioVision Observation Chamber. - Connect the tube with the blue color code to the connector with the blue ring on the DanioVision Temperature Control Unit. This is the tube to drain the DanioVision system. Make sure this tube ends in a sink or container. - Connect the tube with the red color code to the connector with the red ring on the DanioVision Observation Chamber. This is the tube for the water overflow of the Observation Chamber. Important: Make sure that the tubes with red and blue color codes end in a sink or container. The tubes run obliquely downwards so that water flows spontaneously to the sink or container. - Connect the cable with the cinch-plugs to the temperature-sensor connectors on both the DanioVision Temperature Control Unit and Observation Chamber. - Optionally, connect the network cable between the TTL port on the DanioVision Temperature Control Unit and one TTL port on the Observation Chamber. This allows you to log temperature error messages and potentially use these in trial and hardware control in EthoVision XT. Important: If you have the DanioVision Observation Chamber version DVOC-0030 or older, you cannot use TTL2, because this port is used by the temperature sensor for the lens heater inside the observation chamber. - Connect the DanioVision Temperature Control Unit to the mains socket. - Connect the DanioVision Observation Chamber to the EthoVision XT computer. Set Up the DanioVision TCU Fill and Drain Cycle Before you start using the system, it is good to make sure that the whole water circuit is clean. For these steps you need demineralized or distilled water, and a water container or sink. Important: Always drain the system at the end of the experiments. Fill the System - Turn on the DanioVision Observation Chamber. On the DanioVision Temperature Control Unit, switch the Operation mode to Fill/Drain. - Turn the Drain tap completely to Closed. Water will flow as depicted in the connection diagram. - Slowly start pouring water into the basin of the DanioVision Observation Chamber. Important: Stop adding water when the water level reaches the edge of the basin. As a result, the water starts flowing through the tubes. Pour more water a few times, until all bubbles in the tubes have gone and the basin is completely filled. Drain the System - Keep the Operation switch to Fill/Drain and turn the Drain tap to Open. Water will flow out through the drain. - When the basin is empty, turn the Drain tap to Closed to remove all remaining water from the tubes and let it flow into the basin. - Turn the Drain tap to Open again, to completely drain the DanioVision Observation Chamber. Normal Use with Set Water Temperature - Turn on the DanioVision Observation Chamber. Important: After you turned on the Observation Chamber, wait at least 15 minutes before you start an experiment in EthoVision XT. - Open the DanioVision Observation Chamber and locate the Anti-Moisture switch inside the chamber. Set the switch in one of the two modes: - On: Choose this when the room temperature is lower than the desired water temperature. - Off: Choose this when the room temperature is higher than the desired water temperature. - On the DanioVision Temperature Control Unit, switch the Operation mode to Fill/Drain. - Turn the Drain tap completely to Closed. Water will flow as depicted in the connection diagram. - Slowly start pouring water into the basin of the DanioVision Observation Chamber. Important: Stop adding water when the water level reaches the edge of the basin. We strongly recommend using demineralized or distilled water to minimize contamination of the system and the accumulation of calcium and salt. As a result, the water starts flowing through the tubes. Pour more water a few times, until all bubbles in the tubes have gone and the basin is completely filled. - Close the DanioVision Observation Chamber before you set the desired temperature in the next steps. - Set the Operation switch to On. - Next to the temperature display, hold the Set button for about 1 second; the display flashes showing the currently set temperature. - Use the arrow keys to set the desired temperature. - Confirm by pressing the Set button once. Important: If the difference between the actual and set water temperature is more than 0.5 °Celsius / 0.9 °Fahrenheit, an error code appears. This error message disappears as soon as the water temperature is within a 0.5 °C / 0.9 °F range of the set value again. - Wait until the set temperature has been reached. This takes on average 10 minutes, depending on the set temperature and the temperature in the room. During this process, the status indicated by the LED lights at the front is on Heating / Cooling. Once the temperature is stable at the set value, the status changes to Ready. The DanioVision Temperature Control Unit is now ready to start an experiment. Make sure that the DanioVision Observation Chamber has been on for at least 15 minutes. Displaying Celsius or Fahrenheit You can choose to display the temperature in °Celsius or °Fahrenheit. To set the display, do the following: - Set the Operation switch to On. - Keep the Prg and Set button both pressed until the entry code 0 appears on the temperature display. - Use the arrow keys to change the entry code to 77 and press Set. Program c0 appears on the display. - Use the arrow keys to go to program c18 and press Set. - Use the arrow keys to set the temperature unit to Celsius = 0 or Fahrenheit = 1 and press Set to confirm. - Keep the Prg button pressed until you exit the program mode. Temperature Alarm (Optional) The temperature alarm allows you to log high and low temperature alarms in EthoVision XT. You can use the temperature alarm: - In the Trial Control Settings, for example to stop the trial if the temperature alarm lasts for more than a certain time. - In the Analysis profiles, to visualize when an alarm occurred together with the data. - As a hardware log, which you can export. Note: A temperature alarm should not happen if the TCU is in status "Ready". An alarm is therefore an unusual event in normal conditions. If the TCU is still in "Heating" or "Cooling" status, it is normal that a couple of temperature alarms occur. --- ## DanioVision DVOC-0050 - Temperature Control Unit - Using the Basin Refill URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-temperature-control-unit-using-the-basin-refill Chapter: DanioVision Using the Basin Refill How much liquid to insert via the syringe depends on the level of evaporation and the duration of the experiment. Add liquid into the basin circuit whenever needed. During refill, do not switch off the Temperature Control Unit. - Open the faucet (On position). - Make sure you can see the overflow outlet of the DanioVision Chamber (red marked tube). - Gently push the syringe to insert liquid. - Carefully watch the overflow tube. Whenever the liquid comes, stop pushing the syringe. Notes: - Overflow is a good indication for a 100% filled basin, however it may lag on filling. - The DVTCU will, whenever it occurs, compensate any temperature fluctuation due to the refill. However, make sure that the liquid temperature in the syringe is not too far from the desired basin temperature. To Refill the Syringe - Make sure the faucet is closed (Off position). - Disconnect the syringe. - Fill the syringe with basin liquid. - Make sure no air is present in the syringe. - Connect the syringe back to the faucet tube. Maintenance and Support Replace the Filter The filter inside the DanioVision Temperature Control Unit is a particle filter with a pore size of 20 μm. The filter does not remove bacteria and/or yeast. The filter can get blocked after you have used the system for a longer period of time. When this happens, you will get an 'insufficient-flow' error message. Please first check the error table. Contact Noldus IT to order a new filter. Before replacing the filter, drain the system. - Make sure to use demineralized or distilled water to prevent small particles (greater than 20 μm) from blocking the filter. - Open the lid of the Temperature Control Unit by unscrewing the white plastic screw at the front of the unit. You can use a small screwdriver or a coin to do this. - Remove the left side panel by unscrewing the two screws at the top and three screws at the bottom of the side panel. - Lift the filter from the clamp and disconnect the tubes at both ends from the filter. - Insert the new filter, connect the tubes and push the filter back into the clamp. Make sure the small black arrow on the filter points in the correct direction as indicated in the figure. - Put the side panel back in place and close the lid of the Temperature Control Unit. Replace the Liquid Coolant - Open the lid of the Temperature Control Unit by loosening the plastic screw at the front of the unit. - Remove the left side panel by unscrewing the screws at the top of the side panel. - Locate the cap on top of the reservoir for the liquid coolant. This differs slightly between TCU versions. - Unscrew the cap using, for example, a small coin. - Use the funnel to fill the reservoir with the liquid coolant. It is recommended to fill it to the maximum level. After refilling the liquid coolant, turn the Operation switch to Fill/Drain to make sure the tubes inside the Temperature Control Unit are also filled with liquid coolant. As a result, the level of coolant in the reservoir might drop a bit. Add more coolant so it reaches the Max level. - Screw the cap back on the reservoir. - Put the side panel back in place and close the lid of the Temperature Control Unit. Make sure to regularly check that the level of coolant does not drop below the Min indication on the front of the Temperature Control Unit. If the level is too low, refill the coolant. Wear and Tear All Noldus hardware is sold with a two-year guarantee. That means that if it breaks within two years of the delivery date, it will be repaired or replaced at Noldus' expense. Please see the document 'Noldus guarantee' to see what is covered by the guarantee. Wear and tear caused by regular, normal use of the DanioVision Temperature Control Unit is not covered by the guarantee. Below are some recommendations about environmental conditions and cleaning of the Temperature Control Unit. Environmental Conditions See the specifications under Environmental Conditions in the specifications section. Cleaning the TCU To clean the DanioVision Temperature Control Unit, use a damp cloth. Do not use chemicals or soap to wash the Temperature Control Unit. Make sure that no liquid gets into the Temperature Control Unit. Keeping the Tubing Clean It is very important that the tubes are kept as dry as possible when not using the DanioVision and the TCU. To prevent the growth of algae in the tubing, do the following: - Always fill the system with demineralized water, and drain it after the end of an experiment. - Keep all units and the tubes away from sunlight. Technical Support If after reading this manual you still have questions, please contact our help desk at my.noldus.com. Event Data Logger If you purchased a DanioVision Temperature Control Unit after November 2016, it is equipped with a board and a compact SD card that records performance data during functioning. If you encounter problems when using the Temperature Control Unit, the Noldus Help Desk may ask you to send the files stored in the card. In that case, the Noldus Help Desk will send you instructions for how to do that. --- ## DanioVision DVOC-0050 - Toplight Unit - Program the Top Lights in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-toplight-unit-program-the-top-lights-in-ethovision-xt Chapter: DanioVision Program the Top Lights in EthoVision XT Choose Setup > Trial Control Settings. Example: Program your Trial Control Settings so that the White/RGB Top Light is switched on one minute after the start of the trial, and switches off after 10 seconds. - Under Conditions, choose Time to create time conditions: - One Time condition to Wait 1 minute - One Time condition to Wait 10 seconds - Under Actions, choose White Top Light / RGB Top Light and define the actions: - One action to switch the White Top Light on - One action to switch the Top Light off. This can be done for both Output 1 and Output 2 in the Hardware Action boxes. - Remember to connect all boxes between the Start Track action box and the Stop Track action box. Create a Routine for the Top Light With the Subrule function of the Trial Control Settings you can create routines in order to have the switch on/off sequence repeated multiple times. For more information, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Also adjust the Detection Settings (Setup > Detection Settings) before running the trials. Protocols with Multi-Color Light Stimuli You can create a protocol that presents Top Light stimuli of different light colors within the same trial. To do so: - Install the RGB Top Light. Make sure that the RGB side is facing down. See Switch Between White and Colors above. - In the Trial Control Settings, create multiple Action boxes. In each of them, specify the dominant color and intensity. - Insert the Action boxes in the Trial Control Settings procedure. Insert Time Condition boxes between subsequent Action boxes. Source: DanioVision DVOC-0050 Reference Manual - Toplight Unit, Noldus Information Technology --- ## DanioVision DVOC-0050 - Toplight Unit - The DanioVision Toplight Unit URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-toplight-unit-the-daniovision-toplight-unit Chapter: DanioVision The DanioVision Toplight Unit This chapter explains the setup and operation of the DanioVision Toplight DVTL-0020 for the DanioVision Observation Chamber DVOC-0050. With the TopLight Unit you can administer a light stimulus of specific color, intensity and duration above the well plate: - White - Pure colors: Red, Green and Blue - A mix of the three basic RGB colors Note: The DanioVision Toplight Unit is an add-on to DanioVision; it does not come with a standard DanioVision system. Install the Toplight Unit If you ordered a TopLight Unit with a new DanioVision DVOC-0050, it is already integrated in the chamber. You can skip this section. - Unpack the TopLight Unit. - Cover the lens bracket with some protective material. - If that has not been done yet: - Insert one of the black "stops" into the middle vertical profile, as shown in the image below. - Insert one sliding nut just above the "stop". Do that at both sides of the DanioVision chamber. - Attach the black knobs to each sliding nut. - Connect the White Light side of the TopLight Unit using the predefined black-white cable inside the chamber. - Connect the RGB side of the TopLight Unit using the predefined, multicolor cable inside the chamber. - Turn the TopLight Unit in such a way that the LED color that you want to use (white vs. RGB) is facing down. - Slide the TopLight Unit so that the thread of the black knobs is inserted in the side brackets, as shown in the next figure. - Untighten both left and right black knobs to enable the unit sliding up and down. - Slide the TopLight Unit up, until it is at the level of the lens. - Make sure that the TopLight Unit is kept horizontal. - Tighten the black knobs. Switch Between Lights (DVOC-0050) Switch Between Red, Green and Blue If you have DanioVision DVOC-0050 you can create all combinations of the three basic colors using the Trial Control Settings. You do not need to exchange cable connectors. See Trial Control Settings in the section Set Up the Toplight Unit in EthoVision XT below. Switch Between White and Colors If you want to switch from RGB to white light (or vice versa), turn the entire TopLight Unit in order to have the right LEDs facing down towards the well plate. The RGB LEDs and white LEDs are mounted on the opposite sides of the same plate and can be identified by the label white and rgb attached. - Cover the lens bracket with some protective material. - Untighten both left and right round black knobs as shown in the next figure. - Slide the TopLight Unit down a few centimeters, just below the camera. - Pull the unit out and turn it upside down, facing the preferred LEDs down. Important: Be careful not to twist the cable at the back. Unplug both connectors temporarily to prevent this from happening. - Insert the unit and slide it up again. - Tighten both black knobs. Set Up the Toplight Unit in EthoVision XT Experiment Settings - Start EthoVision XT and create a new experiment using a template (File > New from Template). - Choose Setup > Experiment Settings. - Under Trial Control Hardware, select Use of Trial Control Hardware, then click Settings. - In the Hardware Interface window, select DanioVision DVOC-0050/TPC, then click OK. - When needed, adjust the default light settings for the White Light Stimulus. Make sure the message shown in the bottom-left corner reads Connected. Click Refresh when necessary. - Click OK and proceed to the next section. Arena Settings - Open the Arena Settings that you want to use. Calibrate and draw the arenas. - In the Arena Settings pane, click Arena - Hardware Mapping and then click the Arena - Hardware Mapping button. - If White Top Light / RGB Top Light is already listed in the table, skip the steps below. Otherwise, click Add Device. - In the row that appears, under Device Type, select either White Top Light or RGB Top Light. - Under A1 or Arena 1 (depending on how the arenas are named), select the corresponding device. - To test the device, select the cell under A1/Arena 1 and click Test. Trial Control Settings - Make sure you have completed the procedures described above under Experiment Settings and Arena Settings. - Open the Trial Control Settings for the protocol you want to use to control the TopLight Unit. - Under Actions - Hardware, click the button next to White Top Light / RGB Top Light. Note: Whether White Top Light or RGB Top Light is available depends on what is selected in the Arena - Hardware Mapping window. - In the Hardware Action window, specify: - The Action Name (optional) - The Action to perform (Light On or Light Off) - For the White TopLight, the Intensity Level (%) - For the RGB TopLight, the three Color Intensity options to combine the three basic colors. For example, to create a strong pure red light, enter 100% for Red Color Intensity and 0% for the other two color intensities. - The Fade Duration (in ms to hours) - Click Test to ensure that the light intensity is suitable for your protocol. - Click OK and insert the Action box in your Trial Control protocol. Test the protocol before carrying out the real trials. --- ## DanioVision DVOC-0050 - Trial Control Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-trial-control-settings Chapter: DanioVision Trial Control Settings Default Trial Control Settings Choose Setup > Trial Control Settings > Default or White Light Routine. Depending on which template you used to create your experiment, you will find two or three examples of trial control settings: - Default – The default Trial Control Start-Stop rule. Use these settings to start and stop tracking manually. - White Light Routine – Use these settings when you want to provide a light stimulus during the trial. Ten minutes after the start of the trial, the DanioVision white light immediately turns on to 100% intensity for 10 minutes, then the white light immediately turns off for 10 minutes. This sequence of actions is repeated twice, using a sub-rule, after which the trial stops. - Tapping Stimulus Routine – These settings contain a routine to produce a recurrent Tapping stimulus. Maximum Trial Duration (Recommended) - If you record video: 60 minutes. - Without recording video: 72 hours. You can in principle record video for more than one hour, however consider that DanioVision creates high quality video files, which occupy a large disk space. Depending on the frame rate and resolution, one hour of recording may require more than 1 GB. Set the duration of your trials in the Maximum Trial Duration pane or in the Start-Stop trial rule, by placing a Time condition immediately before the Stop Track action box. Tested Configuration - Camera video resolution: 1280 x 1024 - Operating system: Windows 11 Pro, 24H2 - Software: EthoVision XT 18.0 - Experiment: DanioVision with 96 wells - Trial Control: Two sub-rules, one for the Tapping device and one for the White Light. One action every five minutes, for 30 minutes total per device type. Total duration of the test: two hours. Create Your Own Trial Control Procedure Aim You can adjust these trial control settings to your own needs. The procedure below describes how to define Trial Control Settings from scratch. Example A researcher wants to expose the larvae to alternating periods with the white light on and off, in which the light-on periods also vary in intensity. To program this schedule: - To open the Trial Control, in the Experiment Explorer, right-click Trial Control Settings, select New, enter a name and click OK. The Trial Control screen opens with the default Start-Stop trial control rule. - Click the Condition box with Infinite Time and press Delete. - In the Components pane, under Actions – Hardware, click the button in the Add column next to White Light Stimulus. Select Create a New Action. - In the Hardware Action window, set the following: - Action name – Enter a description of the action, for example "Light on 100%". - Action to perform – Select Light On from the list. - Intensity level – Select the maximum intensity level of the light, in percentage (0–100%) or in Steps (0–4096). With the standard White Light settings, the light intensities of the white light are approximately: - 5% = 207 Steps = 139 lux - 25% = 1000 Steps = 2500 lux - 50% = 2100 Steps = 5300 lux - 75% = 3000 Steps = 8000 lux - 100% = 4095 Steps = 10500 lux - Fade duration – For example, with an Intensity Level of 50% and a Fade Duration of 2 seconds, the white light gradually turns on until 50% of its maximum intensity in 2 seconds. Note: if your experiment was created from a template of EthoVision XT 17.0 or an earlier version, you could only set the fade duration in seconds. In experiments created from templates in EthoVision XT 17.5 and later versions, you can set the fade duration in milliseconds, seconds, minutes, and hours (up to 24 hours). - Click OK and insert the Action box in the sequence. - In the Components pane, under Conditions, click the button next to Time. Click Create a New Action and click OK. In the Time Condition window, you can set the following: - Condition name – For example, enter "Wait 15 mins". - Condition is met – For the option After a Time Of, enter "15 mins". - Click OK and insert the Condition box in the sequence. - Repeat steps 3–6 to complete the Trial Control rule: - Add a Hardware Action box with White Bottom Light – Off and a Condition Time box with "After 10 mins". - Add a Hardware Action box with White Bottom Light – On 50% and a Condition Time box with "After 10 mins". - Add a Hardware Action box with White Bottom Light – Off and a Condition Time box with "After 10 mins". - Add a Hardware Action box with White Bottom Light – On 100% and a Condition Time box with "After 15 mins". - Insert all the boxes in the correct order into the sequence and make sure you connect all boxes. To connect boxes, drag the mouse from the middle of one to the middle of the other. Tip: Combinations of Action and Condition boxes that are repeated in a sequence can be replaced with a sub-rule. This is especially useful when the entire sequence is repeated multiple times during a trial. For example: [White Bottom Light – On – 100%] > [After 10 min] > [White Bottom Light – Off] > [After 10 min]. For more information on using sub-rules, see the EthoVision XT 18 – Trial and Hardware Control – Reference Manual. Notes - Click Test in the Hardware Action window to test the hardware action. - Click Reset to reset all Hardware Action windows in your Trial Control procedure to their default values. For example, a White Bottom Light action is set to off by default; however, if you set the default White Bottom Light to on, then after clicking Reset the white light switches on. - To analyze data in the light or dark period, first create a Data Profile that specifies that period using Trial Control State, then calculate the statistics. - For more information on Trial Control Settings, see Trial Control in the EthoVision XT Help and the EthoVision XT 18 – Trial and Hardware Control – Reference Manual. To open this manual, from the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 Other Documentation. Use an External Command Examples of external commands include: - Play a sound during the trial. - Start a batch file that triggers the presentation of a visual stimulus (e.g. a looming object) during the trial. When you work with multiple arenas, the command is executed for each arena. For example, the command to play a sound is repeated 96 times for a 96-arena experiment. To prevent this, use one of the following methods: Method 1 – Condition in Arena 1 - In the Arena Settings, create a zone in Arena 1 and call it "Zone 1A". Make the zone as large as the arena. - In the Trial Control Settings, make a condition such as "Is subject in Zone 1A?", followed by the external command. - Insert a condition before the External Command box that will only become true for one of the arenas, for example Arena 1. - Make sure that the sequence does not interfere with the rest of the Trial Control rule. Place the Condition box and the External Command Action box in a separate branch so that the execution of the external command does not influence the other actions in your trial control procedure. Method 2 – Condition Specified in a Batch File The Trial Control actions are by default executed for each arena independently, meaning an action would be executed as many times as the number of arenas. When using a batch file, it is possible to use an IF condition to execute a command only for a specific arena name, so the action is executed once for all arenas. Suppose you want to execute the following command, which triggers the presentation of an image stimulus on a monitor: D:\Software\Frameless\Frameless.exe "D:\Images\Dot.jpg" mon=2 fullscreen=yes duration=00:00:02 - Create a text file with the following code: - @echo off - echo %1 - IF %1=="Arena 1" ( D:\Software\Frameless\Frameless.exe "D:\Images\Dot.jpg" mon=2 fullscreen=yes duration=00:00:02 ) Make sure that the arena name in the code matches exactly the name defined in the Arena Settings, including spaces. For example, if the name of the first arena in a DanioVision experiment is A1, enter A1 in the batch file. Save the file with the extension .bat, for example ShowImage.bat. - In the Trial Control Settings, create an External Command and next to Select Program to Run, select the batch file. - Next to Command Line Options, enter "%an%" (including the quotes). This makes EthoVision XT listen to the arena name and execute the command only for the arena specified in the batch file. - Arrange the External Command in your Trial Control procedure. In this example it has been placed in a sub-rule. The stimulus is presented once every 10 seconds, regardless of how many arenas are in the experiment. Source: DanioVision DVOC-0050 Reference Manual - Trial Control Settings, Noldus Information Technology --- ## DanioVision DVOC-0050 - What is DanioVision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-what-is-daniovision Chapter: DanioVision What Is DanioVision? DanioVision™ is a system for high throughput tracking of zebrafish larvae in multi-well plates. It consists of: The DanioVision Observation Chamber (DVOC-0050) This chamber contains a transparent holder with backlight that fits an ANSI SBS compatible multi-well microtiter plate, infrared (IR) and white light sources underneath the microtiter plate, and a Gigabit Ethernet (GigE Vision) video camera. The optical design provides a stable and undistorted top view of each well and a controlled and constant environment within the observation chamber. EthoVision XT Video-tracking software with the Multiple Arenas Module and Trial & Hardware Control Module. With this module you can adjust the white light stepwise based on time or behavior of your fish. You have the option to connect external devices, such as sound or shock generators. Note that DanioVision DVOC-0050 works with EthoVision XT 18 and newer, and with an Ethernet connection (RJ45 port) to the EthoVision XT computer. DanioVision Add-Ons DanioVision Temperature Control Unit With the DanioVision Temperature Control Unit you can set up a water flow at constant temperature underneath the well-plate. DanioVision Tapping Device With the DanioVision Tapping Device you can trigger a startle response in zebrafish. DanioVision Toplight Unit With this add-on you can generate top-down light stimuli in your experiments. Four types of light are available: white, red, blue and green. DanioVision with Optogenetics DanioVision can be provided with one to three LEDs that illuminate the well plates based on your Trial Control protocol. The Optogenetics add-on allows you to accurately control and time the application of optogenetic stimulation to up to 96 individuals simultaneously (one for each well in a 96-well plate). Custom Solutions As research evolves, so do research needs. If you are interested in a custom solution, don't hesitate to contact us. A few examples of recent custom solutions: - Light-Dark Grid. Commonly used to investigate anxiety behavior in zebrafish. The grid is placed underneath the well plate (available for 6, 12, 24, 48 or 96 wells) and creates a dark and light half in each well. The grid is IR light translucent, leaving the tracking of the zebrafish unaffected. - High-Speed Camera. DanioVision is equipped with a camera capable of 1000 frames per second. The aim is to measure the startle response of larvae to a stimulus during a Pre-Pulse Inhibition test (Burgess and Granato 2007). - Split Basin. The DanioVision basin has been modified so that it receives water at two different temperatures. The aim of this solution is to measure temperature preference in zebrafish larvae. - Ultraviolet Toplight Unit. This is a modification of the Toplight unit which shines UV light. Light intensity is controlled by EthoVision XT. - Turbo-Cooling TCU. This is a modified Temperature Control Unit which keeps water at a constant temperature of 12° in a room where temperature is about 25°. For More Information Manuals - The EthoVision XT Help (press F1 in EthoVision XT). - The EthoVision XT - Trial and Hardware Control - Reference Manual. To open this and other manuals, from the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 Other Documentation. Sample Experiments On the EthoVision XT downloads page you can find two sample experiments that make use of DanioVision. Once you have downloaded a sample experiment file (*.evz), you can open it in EthoVision XT via File > Restore Backup. Experiment Templates EthoVision XT contains templates that help you set up an experiment with arenas, analysis profiles and other elements already defined. Support Center If after reading this manual you still have questions, please contact our Support Center at my.noldus.com. Source: DanioVision DVOC-0050 Reference Manual - What is DanioVision, Noldus Information Technology --- ## DanioVision DVOC-0050 - Whats New URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-dvoc-0050-whats-new Chapter: DanioVision What's New in DanioVision DanioVision Observation Chamber The interface of DanioVision DVOC-0050 has been completely redesigned. Communication with the EthoVision XT computer goes through Ethernet. There are pre-defined communication lines for the White Bottom Light, the TopLight Unit, the Tapping Stimulus, the DanioVision Temperature Control Unit DVOC-TCU and the Optogenetics setup. - Two BNC connectors are reserved for the Optogenetics setup. - Two TTL ports are available for additional hardware control. Each port includes two input lines and two output lines. - There is a new physical connection for communication with the temperature sensor in the Temperature Control Unit. - You can switch on the White Bottom Light manually. To do so, operate the button at the right side of the camera. EthoVision XT Because the hardware components have changed, the software interface for controlling DanioVision has changed. You can find it in the EthoVision XT Experiment Settings. Choose Setup > Experiment Settings, select Use of Trial Control Hardware. Click Settings and choose DanioVision DVOC-0050/TCP. - The White Light Stimulus is now called White Bottom Light. - The Tapping Stimulus stays as is. - The TopLight Unit has now specific names: White Top Light and RGB Top Light, for white and multi-color LED arrays, respectively. - When programming the White Bottom Light on/off actions, you can set the fade duration in milliseconds, seconds, minutes, and hours (maximum 24 hours). To know more about the new features in EthoVision XT, see the topic What's New in EthoVision XT in the EthoVision XT Help. Source: DanioVision DVOC-0050 Reference Manual - Whats New, Noldus Information Technology --- ## DanioVision TCU - Additional Options URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-additional-options Chapter: DanioVision Configure the Temperature Alarms in EthoVision XT Aim To log the high and low temperature alarm in EthoVision XT. You can use the temperature alarm: - In the Trial Control Settings, for example to stop the trial if the temperature alarm lasts for more than a certain time. - In the Analysis Profiles, to visualize when an alarm occurred together with the data. - As a hardware log that you can export. Note: A temperature alarm should not happen if the TCU is in status "Ready". An alarm is therefore an unusual event in normal conditions. If the TCU is still in "Heating" or "Cooling" status, it is normal that a couple of temperature alarms occur. Cable Connections Connect the network cable to the TTL port in the DanioVision Temperature Control Unit and one of the TTL ports in the Observation Chamber. Important: If you have the DanioVision Observation Chamber DVOC-0030 or older, connect the TTL port of the Temperature Control Unit to TTL ports 3 or 4 on the Observation Chamber. Do not use TTL port 2. To Define the Temperature Alarm in EthoVision XT - In EthoVision XT, create a DanioVision experiment. For details, see the Reference Manual - DanioVision Observation Chamber DVOC-0041 or the EthoVision XT Help. - In the Experiment Settings, under Trial Control Hardware, click the Settings button. Select the version number of your DanioVision Observation Chamber (usually DVOC-004x or DVOC-004x/T if you have the DanioVision Tapping Device) and click OK. - In the Device Configuration window, under Plug-in devices, choose the TTL port that you used to connect the Temperature Control Unit. Under Device type select DanioVision TCU (DVTCU-001x). Under Device ID type in a name or accept the default name DanioVision TCU (DVTCU-001x) 1. Click OK. - Choose Setup > Arena Settings > Open and choose the Arena Settings you use in the experiment. In the Arena Settings window, click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, click the Add device button. Under Device type select DanioVision TCU (DVTCU-001x). Under Device name enter a name, for example TCU Temp alarm. In the column A1 select the Device ID that you defined above. - Click OK. EthoVision XT is now ready to log the alarm signals from the TCU. Possible Alarm Signals The following TTL signals are sent to EthoVision XT and can be used in the Trial Control Settings and Analysis Profiles: - When the current water temperature is within the normal temperature range (deviates by less than 0.5 °C from the set temperature), no alarm is given. Both Low temp error state and High temp error state are false. - When the current water temperature is more than 0.5 °C lower than the set temperature (Tcurrent < Tset - 0.5 °C), a low-temperature alarm is given and Low temp error state becomes true. - When the actual water temperature is more than 0.5 °C higher than the set temperature (Tcurrent > Tset + 0.5 °C), a high-temperature alarm is given and High temp error state becomes true. - When you turn off the Temperature Control Unit or unplug the network cable from the TTL port, both Low temp error state and High temp error state become true. Note: During a temperature alarm, the TCU tries to bring the temperature back to the normal range, so you do not need to take any particular action. Use the Temperature Alarms in EthoVision XT In Trial Control Settings Use a temperature alarm in the Trial Control Settings, for example, to stop tracking or start an external program when a temperature alarm occurs. Note: During a temperature alarm, the TCU tries to bring the temperature back to the normal range, so you do not need to take any particular action with Trial Control. Prerequisite: You have defined the temperature alarm in EthoVision XT. - Choose Setup > Trial Control Settings > Open (an existing profile) or New to create a new profile. - In the Trial Control Settings, under Conditions, click the button next to DanioVision TCU (DVTCU-001x). - The Hardware Condition window appears. In the Condition name field, enter a name for the condition (for example, TCU Low Temp alarm). - From the DanioVision TCU list, select the device name that you defined in the Arena - Hardware Mapping window (for example, TCU Temp alarm). - Choose the following, depending on when an action should be taken: - To take an action when an alarm occurs, next to Signal to check choose either Low temp error state? or High temp error state? depending on the alarm you want to use. Then next to Signal value select true. - To take an action when the number of temperature alarms reaches a certain value, next to Signal to check choose either Low temp errors or High temp errors and select the threshold of alarm errors. - Insert the condition box in the Trial Control rule. For more information, see the EthoVision XT Help and the Reference Manual - Trial and Hardware Control in EthoVision XT. In the Analysis Profile In an Analysis Profile, you can define a temperature alarm variable, for example to visualize alarm events in the Integrated Visualization. This way you can review your trials and see if something has changed in the behavior of the larvae during those alarms. - In an Analysis Profile, under Hardware, click the button next to Hardware state. - Next to Device type choose DanioVision TCU (DVTCU-001x). - Next to Device choose the name given in the Arena - Hardware Mapping window (for example, TCU Temp alarm). - Next to Signal: - To visualize or calculate the duration of the time that the system was in temperature error state during the trial, select Low temp error state for a low-temperature alarm, or High temp error state for a high-temperature alarm. Next to Value select true. Select false if you want to visualize or calculate the time that there was no temperature alarm. - To visualize or calculate the duration of the time when the system had more or less than a certain number of temperature error alarms, choose Low temp errors or High temp errors. Choose whether the number of errors was higher, lower, or equal to a threshold value. Keep the option Cumulative selected. - In the Trial Statistics tab, select the statistic you want and click OK. Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## DanioVision TCU - Additional Options (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-additional-options-continued Chapter: DanioVision Additional Options The figure below shows part of the Integrated Visualization windows of a trial in which first a low-temperature alarm occurred, and after that a high-temperature alarm. - Optional: Right-click the row Hardware state and select Rename. Enter a custom name (for example "Hardware state Low Temp alarm"). In a Hardware Log Do the following to export the Hardware log containing the TCU alarm events. - Choose Analysis > Export > Raw Data. - In the Raw Data Export window, make sure to select the Hardware log check box. - Click Start Export to export the data. Carry Out an Experiment Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## DanioVision TCU - Carry Out An Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-carry-out-an-experiment Chapter: DanioVision Carry Out an Experiment If you want to log temperature errors, configure EthoVision XT beforehand. See Configure the Temperature Alarms in EthoVision XT for details. Procedure - Follow the procedure Normal Use with Set Water Temperature. - Wait until the temperature has reached the set value and no error codes appear on the LCD screen of the TCU. - Insert a well plate with the larvae into the basin. To prevent air getting trapped underneath the well plate, put the back of the well plate against the wall and place it on the basin floor, then tilt the front of the well plate down to the basin floor. As you do this, water flows into the overflow part of the basin. - Lower the Fresnel lens over the well plate and close the DanioVision Observation Chamber. You can now carry out a DanioVision experiment as usual. - If necessary, grab a background image and define the arenas. Next, if necessary, define the Detection Settings. For more information, see the Reference Manual - DanioVision DVOC-0041 and the EthoVision XT Help. - Choose Acquisition > Open Acquisition. Start the trial. - At the end of the experiment, follow the procedure Drain the System. Draining prevents contamination from building up inside the system. Before you drain the system, make sure the drain tube with blue connector ends in a sink or container. Visualize the Temperature Alarms During the Trial On the Temperature Control Unit If an error occurs in the Temperature Control Unit, an error message appears on the display. See Feedback and Error Messages for an explanation. On the EthoVision XT Screen - Choose Show/Hide > Show Dependent Variable. - From the Select Hardware list, choose Hardware State. Click OK. - Next to Device Type, choose DanioVision TCT (DVTCU-001x). Choose the signal you want to display. Click the Statistics tab and choose the statistics of that signal that you want to display. Choose Current to display whether a temperature alarm is occurring. - During acquisition, in the Analysis Results and Scoring pane click the Dependent Variables tab. There you can view the alarm state (under arena A1). Here, true means error state. Refill the Basin During Long Experiments The Basin Refill Tool During long-lasting DanioVision experiments, evaporation of water out of the basin could be an issue. You can compensate for evaporation by refilling the basin without opening the DanioVision Observation Chamber (DVOC-0040). The Basin Refill Tool (DVBR-0010) allows you to refill the basin without opening the DanioVision Chamber during an experiment. It is provided standard with the DanioVision Temperature Control Unit (DVTCU). Important: It is possible to fill or refill the basin directly (see Chapters 3 and 4 in this manual). However, this is not practical when an experiment is running. Only use the Basin Refill Tool in combination with the DanioVision Temperature Control Unit (DVTCU). To Set Up the Basin Refill Tool You must install the Basin Refill Tool before starting the experiment. - Make sure your DanioVision basin is empty. To do so, follow the instructions in Drain the System. - Disconnect the tube marked in green between the DanioVision Chamber and the TCU (when applicable). - Connect the ends of the tubes of the Basin Refill Tool to the corresponding green-marked inlets at the back of the DanioVision Observation Chamber and the Temperature Control Unit. - Make sure the faucet is closed (Off position). - Fill the syringe with basin liquid, and connect it to the short faucet tube. - Fill the basin circuit. While the basin circuit is being filled, insert a few ml of liquid from the syringe in order to prevent air bubbles from getting into the circuit. - Start the experiment as usual. To Use the Basin Refill How much liquid to insert via the syringe depends on the level of evaporation and the duration of the experiment. Add liquid into the basin circuit whenever needed. Important: During refill, do not switch off the Temperature Control Unit. - Open the faucet (On position). - Make sure you can see the overflow outlet of the DanioVision Chamber (red marked tube). - Gently push the syringe to insert liquid. - Carefully watch the overflow tube. Whenever the liquid comes, stop pushing the syringe. - Overflow is a good indication for a 100% filled basin, however it may lag on filling. - The DVTCU will, whenever it occurs, compensate for any temperature fluctuation due to the refill. However, make sure that the liquid temperature in the syringe is not too far from the desired basin temperature. To Refill the Syringe - Make sure the faucet is closed (Off position). - Disconnect the syringe. - Fill the syringe with basin liquid. - Make sure no air is present in the syringe. - Connect the syringe back to the faucet tube. Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## DanioVision TCU - Feedback And Error Messages URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-feedback-and-error-messages Chapter: DanioVision Feedback and Error Messages The DanioVision Temperature Control Unit gives feedback about its status with four LED lights and error codes on the temperature display. LED Indicators Status LED Explanation User Action Filling / Draining Orange – blinking System is pumping. - The system can be filled with water. - Water can be drained from the basin. - Cooling liquid can be filled. Filling / Draining Red – continuous Time out. There has been no flow in the water circulation and/or the cooling liquid circulation for more than 10 minutes. Reset the system by turning the Operation switch to Off and then back to Fill/Drain. Heating / Cooling Green – blinking The water is being heated/cooled to the set temperature. Wait. No action needed. Ready Green – continuous The set temperature has been reached and the system is ready to be used. The Temperature Control Unit is ready to be used and an experiment can be started. Error Red – 1 blink – repeatedly Insufficient flow in the water circulation. Look for the source of the problem. This may be: - Low water level in the basin (due to evaporation or leakage). If so, fill the system. - Flow blockage somewhere in the system or filter clogged. Contact Noldus to replace the filter. - Pump failure. The Fill/Drain mode can be used to localize the problem. Reset the system by setting the Operation switch to Off and then to Fill/Drain. Error Red – 2 blinks – repeatedly Insufficient flow in the cooling liquid circulation. Look for the source of the problem. This may be: - Low cooling liquid level in the pump reservoir. Check if the liquid level is above the indication. If not, refill cooling liquid and check for signs of leakage in the emergency liquid container. - Flow blockage somewhere in the system. - Pump failure. The Fill/Drain mode can be used to localize the problem. Reset the system by setting the Operation switch to Off and then to Fill/Drain. Error Red – 3 blinks – repeatedly The fan is not spinning, or not spinning at sufficient speed. Check if there is anything blocking the fan. If this is not the case, please contact Noldus support. Error Red – 4 blinks – repeatedly System is overheated. Turn off the system and end the experiment. Cooling liquid can be cooled down by switching the Operation switch to Fill/Drain. Search for the possible cause of the overheating: - Air vents of the Temperature Control Unit might be blocked so the radiator cannot get rid of its heat. Make sure air vents are free. - System is used in environmental conditions that have not been tested, for example, room temperature above 35°C. Error Red – 5 blinks – repeatedly Heating and cooling have been activated simultaneously. An electrical problem has occurred. Please contact Noldus support. Error Red – 6 blinks – repeatedly A problem with the data logger has occurred. - Open the TCU and take the SD card out. - If it is locked, unlock it. - Check that it has a minimum capacity of 4 GB. - Put the SD card back in the TCU. - If the error persists, take the card out and format it (FAT32). Leave the card empty; do not copy the old files to the newly-formatted card. - Put the SD card back in the TCU and restart the TCU. Error Red – continuous A temperature deviation larger than 0.5°C above or below the set temperature has been detected. Water conditioning will continue to try to resolve the situation. Once resolved, the status of the system returns to 'Ready'. Depending on your protocol you can choose to continue or to abort the experiment. Temperature Display Status Codes - The water is being heated to the set temperature. - The water is being cooled to the set temperature. - The current water temperature is at least 0.5°C below the set temperature. Shown together with temperature alarm code E05. The red Error LED (continuous) is on. - The current water temperature is at least 0.5°C above the set temperature. Shown together with temperature alarm code E04. The red Error LED (continuous) is on. - Error mode indicator. - This is a system setting indicator, which blinks when the TCU is in heating/cooling mode. No action need be taken. - LCD is off: A possible reason is that one of the flat cables coming from the LCD display is not properly connected. Open the DV-TCU, locate the multi-color flat cable (3rd to the right of the SD card), disconnect it and connect it again. Error Codes Error Code Explanation User Action E01 The temperature sensor is not detected. Please connect the temperature sensor cable (with cinch-plugs on both ends). E04 'Too high' temperature alarm. The measured temperature is 0.5°C higher than the set temperature. Depending on your protocol you can choose to continue or abort the experiment. Note that this error also occurs while the system is heating/cooling before the start of the experiment; the system continues to heat/cool to try to resolve the error. E05 'Too low' temperature alarm. The measured temperature is 0.5°C lower than the set temperature. Depending on your protocol you can choose to continue or abort the experiment. Note that this error also occurs while the system is heating/cooling before the start of the experiment. Ed1 System error. See the Error status entry in the LED Indicators section above. Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## DanioVision TCU - For Daniovision Dvoc-0041 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-for-daniovision-dvoc-0041 Chapter: DanioVision Introduction The combination of the DanioVision Observation Chamber and the Temperature Control Unit allows you to set up a temperature-controlled water flow underneath the well plate in the DanioVision Observation Chamber. The result is a constant temperature in the well-plate throughout an experiment. If you are a new DanioVision user, you get a new DanioVision Observation Chamber, the Temperature Control Unit and all accessories necessary to work with the DanioVision system. DanioVision users with a DanioVision Observation Chamber purchased before 25 January 2013 must upgrade their DanioVision Observation Chamber in order to be able to work with the Temperature Control Unit. Please contact your Noldus sales representative for more information. Workflow Working with the DanioVision Temperature Control Unit involves the following steps: - Set Up Connections: Connect the DanioVision Temperature Control Unit and the Observation Chamber. See page 5. - Set Up EthoVision XT: Set up the DanioVision Temperature Control Unit. See page 9. - Configure Temperature Alarms (Optional): Configure the temperature alarms in EthoVision XT. See page 15. - Carry Out an Experiment: Acquire data with the DanioVision Observation Chamber and the DanioVision Temperature Control Unit. See page 15. Important: After the experiment, drain the DanioVision Observation Chamber and the DanioVision Temperature Control Unit. Also keep the tubing far from sunlight to prevent algae growth inside the tubing. See Drain the System on page 10. Other Documentation - Reference Manual - DanioVision Observation Chamber DVOC-0041: To open this manual, in the Apps screen choose Noldus > EthoVision XT Other Documentation. - EthoVision XT Help: To open the Help, press F1 in EthoVision XT. You can download all documentation from www.noldus.com/downloads. Note that you must register and log in to access this page. Connect the DanioVision Temperature Control Unit and the DanioVision Observation Chamber Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## DanioVision TCU - Maintenance And Support URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-maintenance-and-support Chapter: DanioVision Maintenance and Support Replace the Filter The filter inside the DanioVision Temperature Control Unit is a particle filter with a pore size of 20 µm. The filter does not remove bacteria and/or yeast. Tip: The filter can get blocked after you have used the system for a longer period of time. When this happens, you will get an 'insufficient-flow' error message. Please first check the error table. Contact Noldus IT to order a new filter. Important: Before replacing the filter, drain the system. Make sure to use demineralized or distilled water to prevent small particles (> 20 µm) from blocking the filter. - Open the lid of the Temperature Control Unit by unscrewing the white, plastic screw at the front of the unit. You can use a small screwdriver or a coin to do this. - Remove the left side panel by unscrewing the two screws at the top and three screws at the bottom of the side panel. - Lift the filter from the clamp and disconnect the tubes at both ends from the filter. - Insert the new filter, connect the tubes and push the filter back into the clamp. Make sure the small black arrow on the filter points in the correct direction as shown in the figure. - Put the side panel back in place and close the lid of the Temperature Control Unit. Replace the Liquid Coolant - Open the lid of the Temperature Control Unit by loosening the plastic screw at the front of the unit. - Remove the left side panel by unscrewing the screws at the top of the side panel. - Locate the cap on top of the reservoir for the liquid coolant. This differs slightly between TCU versions. - Unscrew the cap using, for example, a small coin. - Use the funnel to fill the reservoir with the liquid coolant. We recommend filling it to the maximum level. After refilling the liquid coolant, turn the Operation switch to Fill/Drain to make sure the tubes inside the Temperature Control Unit are also filled with liquid coolant. As a result, the level of coolant in the reservoir might drop a bit. Add more coolant so it reaches the Max level. - Screw the cap back on the reservoir. - Put the side panel back in place and close the lid of the Temperature Control Unit. Make sure to regularly check that the level of coolant does not drop below the Min indication on the front of the Temperature Control Unit. If the level is too low, refill the coolant. Please contact Noldus IT if you want to purchase a new bottle of liquid coolant. Wear and Tear All Noldus hardware is sold with a two-year guarantee. That means that if it breaks within two years of the delivery date, it will be repaired or replaced at Noldus' expense. Please see the document 'Noldus guarantee' to see what is covered by the guarantee. Wear and tear caused by regular, normal use of the DanioVision Temperature Control Unit is not covered by the guarantee. Below are some recommendations about environmental conditions and cleaning of the Temperature Control Unit. Environmental Conditions See the Technical Specifications section, under Environmental Conditions. Cleaning To clean the DanioVision Temperature Control Unit, please use a damp cloth. Please do not use chemicals or soap to wash the Temperature Control Unit. Make sure that no liquid gets into the Temperature Control Unit. Keeping the Tubing Clean It is very important that the tubes are kept as dry as possible when not using the DanioVision and the TCU. To prevent the growth of algae in the tubing, do the following: - Always fill the system with demineralized water, and drain it after the end of an experiment. - Keep all units and the tubes far from sunlight. Technical Support Help Desk If after reading this manual you still have questions, please contact our help desk. Event Data Logger If you purchased a DanioVision Temperature Control Unit after November 2016, this is equipped with a board and a compact SD card that records performance data during functioning. If you encounter problems when using the Temperature Control Unit, the Noldus Help Desk may ask you to send the files stored in the card. In that case, the Noldus Help Desk will send you the instructions for how to do that. Technical Specifications Mechanical - Dimensions (mm / inch): 460 x 210 x 280 / 18.11 x 8.26 x 11.02 (L x W x H) - Weight (kg / pound): 7 / 15.43 - Hose Connectors: 8 mm outer diameter tube Electrical - Operating Voltage (volt-DC): See documentation - Power Consumption (W) Average / Maximum: 40 / 120 - TTL Port Specs: 2 input / 2 output; Max. 5 Volt / Max. 5 Volt, open collector Operational - Temperature Accuracy (°C / °F): ± 0.5 °C / ± 0.9 °F - Temperature Set Point Range (°C / °F): 15 - 40 °C / 59 - 104 °F - Maximum Heating Capacity (°C / °F): At least 10 °C / 18 °F above ambient temperature (within the temperature set point range 15–40 °C / 59–104 °F) - Maximum Cooling Capacity (°C / °F): 2.5 °C / 4.5 °F below ambient temperature (within the temperature set point range 15–40 °C / 59–104 °F) - Permissible Water Temperature Range (°C / °F): 5 - 50 °C / 41 - 122 °F - Water Capacity (ml / oz): ± 350 / ± 11.83 - Pump Flow Rate – Water (ml per min / oz per min): ± 310 / ± 10.48 - Water Filter Type: 20 µm pore size, 1 inch diameter - Cooling Liquid Capacity (ml / oz): ± 250 / ± 8.45 - Cooling Liquid Type: Colored, anti-corrosive, anti-algae, PC-type cooling liquid - Pump Flow Rate – Cooling Liquid (ml per min / oz per min): ± 1650 / ± 55.79 - Maximum Height Difference Between DanioVision Observation Chamber and Temperature Control Unit (m / ft): 1.3 / 4.26. Do not place the Temperature Control Unit higher than the Observation Chamber. - Noise Level (dB): Average over all frequencies <35 dB. Max. peak of ± 48 dB around 160 Hz. Environmental Conditions - Permissible Ambient Temperature Range – Operating (°C / °F): 10 - 35 °C / 50 - 95 °F - Permissible Ambient Temperature Range – Storage (°C / °F): 5 - 65 °C / 41 - 149 °F - Permissible Relative Humidity (%): 20 - 80 (non-condensing) Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## DanioVision TCU - Service Manual URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-service-manual Chapter: DanioVision Introduction The combination of the DanioVision Observation Chamber and the Temperature Control Unit allows you to set up a temperature-controlled water flow underneath the well-plate in the DanioVision Observation Chamber. The result is a constant temperature in the well-plates throughout an experiment. User Documentation The DanioVision Temperature Control Unit has the following documentation: - DanioVision Temperature Control Unit Service Manual (current document): This document contains technical background information about the Temperature Control Unit. It also describes how to replace certain parts and how to maintain the system. - DanioVision Temperature Control Unit User Manual: This document describes how to work with the DanioVision Temperature Control Unit. - DanioVision Temperature Control Unit Nutshell Documents: These 2-page documents serve as a quick start for the DanioVision Temperature Control Unit. Replacing the Filter The filter inside the DanioVision Temperature Control Unit is a particle filter with a pore size of 20 μm. The filter does not remove bacteria and/or yeast. To replace the filter, do the following: - Open the lid of the Temperature Control Unit by unscrewing the white, plastic screw at the front of the unit. You can use a small screwdriver or a coin to do this. Note: The filter can get blocked after you have used the system for a longer period of time. When this happens, you will get an 'insufficient-flow' error message. Please first check the error table in the Temperature Control Unit - DanioVision User Manual. Contact Noldus IT if you need a new filter. Important: Before replacing the filter, make sure to completely drain the system (see the DanioVision Temperature Control Unit - User Manual for instructions on how to do this). - Remove the left side panel by unscrewing the 2 screws at the top and three screws at the bottom of the side panel (indicated in the figure below). - Lift the filter from the clamp and disconnect the tubes at both ends from the filter. - Insert the new filter, connect the tubes and push the filter back into the clamp. Make sure the little black arrow on the filter points in the direction as shown in the figure above. - Put the side panel back in place and close the lid of the Temperature Control Unit. Replacing the Liquid Coolant - Open the lid of the Temperature Control Unit by loosening the plastic screw at the front of the unit. - Remove the left side panel by unscrewing the screws at the top of the side panel. - Unscrew the cap (this can be done with a small coin) on top of the reservoir for the liquid coolant (indicated in the figure below). - Use the funnel to fill the reservoir with the liquid coolant. Recommendation: Fill the reservoir to the Max level. - Screw the cap back on the reservoir. - Put the side panel back in place and close the lid of the Temperature Control Unit. Note: After refilling the liquid coolant, turn the Operation switch to Fill/Drain to make sure the tubes inside the Temperature Control Unit are also filled with liquid coolant. As a result, the level of coolant in the reservoir might drop a bit. Add more coolant so it reaches the Max level. Technical Specifications The table below shows the technical specifications of the DanioVision Temperature Control Unit. Mechanical - Dimensions (mm / inch): 460 x 210 x 280 / 18.11 x 8.26 x 11.02 (L x W x H) - Weight (kg / pound): 7 / 15.43 - Hose Connectors: 8 mm outer diameter tube Electrical - Operating Voltage (volt-DC): 24 - Power Consumption (W) — Average / Maximum: 40 / 120 - TTL Port Specs — 2 Input / 2 Output: Max. 5 Volt / Max. 5 Volt, open collector Operational - Temperature Accuracy (°C / °F): ± 0.5 °C / ± 0.9 °F - Temperature Set Point Range (°C / °F): 15 - 40 °C / 59 - 104 °F - Maximum Heating Capacity (°C / °F): At least 10 °C / 18 °F above ambient temperature - Maximum Cooling Capacity (°C / °F): 2.5 °C / 4.5 °F below ambient temperature - Permissible Water Temperature Range (°C / °F): 5 - 50 °C / 41 - 122 °F - Water Capacity (ml / ounces): ± 350 / ± 11.83 - Pump Flow Rate – Water (ml/min): ± 310 / ± 10.48 - Water Filter Type: 20 μm pore size, 1 inch diameter - Cooling Liquid Capacity (ml): ± 250 / ± 8.45 - Cooling Liquid Type: Colored, anti-corrosive, anti-algae, PC-type cooling liquid - Pump Flow Rate – Cooling Liquid (ml/min): ± 1650 / ± 55.79 Wear and Tear All Noldus hardware is sold with a two-year guarantee. That means that if it breaks within two years of the delivery date, it will be repaired or replaced at Noldus' expense. Wear and tear caused by regular, normal use of the DanioVision Temperature Control Unit is not covered by the guarantee. Below are some recommendations about environmental conditions and cleaning of the Temperature Control Unit. Environmental Conditions The recommended environmental conditions for the use of the Temperature Control Unit are described below. Operational - Maximum Height Difference Between DanioVision Observation Chamber and Temperature Control Unit (m / ft): 1.3 / 4.26. Do not place the Temperature Control Unit higher than the Observation Chamber. - Noise Level (dB): Average over all frequencies <35 dB. Max. peak of ± 48 dB around 160 Hz. Environmental Limits - Permissible Ambient Temperature Range — Operating (°C / °F): 10 - 35 °C / 50 - 95 °F - Permissible Ambient Temperature Range — Storage (°C / °F): 5 - 65 °C / 41 - 149 °F - Permissible Relative Humidity (%): 20 - 80 (non-condensing) Please see the document Noldus Guarantee to see what is covered by the guarantee. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## DanioVision TCU - Service Manual - Cleaning URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-service-manual-cleaning Chapter: DanioVision Cleaning To clean the DanioVision Temperature Control Unit, please use a damp cloth. Please do not use chemicals or soap to wash the Temperature Control Unit. Make sure that no liquid penetrates the inside of the Temperature Control Unit. Replacement of Components Filter Make sure to use demineralized or distilled water to prevent small particles (> 20 μm) from blocking the filter. - Please contact Noldus IT if you want to purchase a replacement filter. - Please see "Replacing the Filter" for instructions on how to replace the filter. Liquid Coolant Make sure to regularly check that the level of coolant does not drop below the Min indication on the front of the Temperature Control Unit. If the level is too low, refill the coolant. - Please contact Noldus IT if you want to purchase a new bottle of liquid coolant. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## DanioVision TCU - Set Up The Daniovision Temperature Control Unit URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-set-up-the-daniovision-temperature-control-unit Chapter: DanioVision Fill and Drain Cycle Before you start using the system, it is good to make sure that the whole water circuit is clean. Important: Always drain the system at the end of the experiments. What You Need Demineralized or distilled water, and a water container or sink. 1 - Fill the System - Turn on the DanioVision Observation Chamber. On the DanioVision Temperature Control Unit, switch the Operation mode to Fill/Drain. - Turn the Drain tap completely to Closed. Water will flow as depicted in the scheme. - Slowly start pouring water into the basin of the DanioVision Observation Chamber. Important: Stop adding water when the water level reaches the edge of the basin indicated in the figure. As a result, the water starts flowing through the tubes. Pour more water a few times, until all bubbles in the tubes have gone and the basin is completely filled. 2 - Drain the System - Keep the Operation switch to Fill/Drain and turn the Drain tap to Open. Water will flow as depicted in the scheme. - When the basin is empty, turn the Drain tap to Closed to remove all remaining water from the tubes and let it flow into the basin. - Turn the Drain tap to Open again, to completely drain the DanioVision Observation Chamber. Normal Use with Set Water Temperature - Turn on the DanioVision Observation Chamber. Important: After you turned on the Observation Chamber, wait at least 15 minutes before you start an experiment in EthoVision XT. - Open the DanioVision Observation Chamber, and locate the Anti-Moisture switch inside the chamber, at the right of the camera. Set the switch in one of the two modes: - On: Choose this when the room temperature is lower than the desired water temperature. - Off: Choose this when the room temperature is higher than the desired water temperature. - On the DanioVision Temperature Control Unit, switch the Operation mode to Fill/Drain. - Turn the Drain tap completely to Closed. Water will flow as depicted in the scheme. - Slowly start pouring water into the basin of the DanioVision Observation Chamber. Important: Stop adding water when the water level reaches the edge of the basin indicated in the figure. Important: We strongly recommend using demineralized or distilled water to minimize contamination of the system and the accumulation of calcium and salt. As a result, the water starts flowing through the tubes. Pour more water a few times, until all bubbles in the tubes have gone and the basin is completely filled. - Close the DanioVision Observation Chamber before you set the desired temperature in the next steps. - Set the Operation switch to On. - Next to the temperature display, hold the Set button for about 1 second; the display flashes displaying the currently set temperature. - Use the arrow keys to set the desired temperature. - Confirm by pressing the Set button once. Important: If the difference between the actual and set water temperature is more than 0.5 °Celsius / 0.9 °Fahrenheit, an error code appears. This error message disappears as soon as the water temperature is within a 0.5 °C / 0.9 °F range of the set value again. - Wait until the set temperature has been reached. This takes on average 10 minutes, depending on the set temperature and the temperature in the room. During this process, the status indicated by the LED lights at the front is on Heating / Cooling. Once the temperature is stable at the set value, the status changes to Ready. The DanioVision Temperature Control Unit is now ready to start an experiment. Make sure that the DanioVision Observation Chamber has been on for at least 15 minutes. Displaying Celsius or Fahrenheit You can choose to display the temperature in °Celsius or °Fahrenheit. To set the display unit, do the following: - Set the Operation switch to On. - Keep the Prg and Set buttons both pressed until the entry code appears on the temperature display. - Use the arrow keys to change the entry code and press Set. Program c0 appears on the display. - Use the arrow keys to go to program c18 and press Set. - Use the arrow keys to set the temperature unit to Celsius or Fahrenheit and press Set to confirm. - Keep the Prg button pressed until you exit the program mode. Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## DanioVision TCU - The Daniovision Observation Chamber URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/daniovision-tcu-the-daniovision-observation-chamber Chapter: DanioVision The DanioVision Observation Chamber Important: If you are a user of a DanioVision system with version number DVOC-0020/-0021, you need to upgrade your DanioVision Observation Chamber to be able to connect the Temperature Control Unit. Contact your nearest Noldus office for more information. Accessories The DanioVision Temperature Control Unit comes with the following parts: - A 1.5 m color-coded drain tube. - A cable for the temperature sensor with a cinch-plug on both ends. - A 3-m network (UTP) cable to connect the TTL ports on the Temperature Control Unit and the DanioVision Observation Chamber. - Liquid coolant and a funnel to fill up the coolant. - The Basin Refill Tool, for filling the DanioVision basin with liquid without opening the DanioVision Observation Chamber. - A power adapter GS120A24 and a power cord. Note: For connecting the DanioVision Temperature Control Unit, you also need the color-coded tubes that come with the DanioVision Observation Chamber DVOC-0041. Connect the DanioVision Temperature Control Unit and the DanioVision Observation Chamber Basic Connection Scheme Important: Make sure you place the DanioVision Temperature Control Unit at the same level as the DanioVision Observation Chamber. If that is not possible, place the DanioVision Temperature Control Unit at no more than 1.3 m below the DanioVision Observation Chamber. Procedure - Connect the tube with the green color code to the connectors with the green ring on both the DanioVision Temperature Control Unit and the Observation Chamber. This is the tube through which water flows into the DanioVision Observation Chamber. - Connect the tube with the yellow color code to the connectors with the yellow ring on both the DanioVision Temperature Control Unit and the Observation Chamber. This is the tube through which water flows out of the DanioVision Observation Chamber. - Connect the tube with the blue color code to the connector with the blue ring on the DanioVision Temperature Control Unit. This is the tube to drain the DanioVision system. Make sure this tube ends in a sink or container. - Connect the tube with the red color code to the connector with the red ring on the DanioVision Observation Chamber. This is the tube for the water overflow of the Observation Chamber. Important: Make sure that the tubes with red and blue color codes end in a sink or container, and are slanted downwards so that water flows spontaneously. - Connect the cable with the cinch-plugs to the temperature-sensor connectors on both the DanioVision Temperature Control Unit and Observation Chamber. - Optionally, connect the network cable to the TTL port on the DanioVision Temperature Control Unit and TTL port 1 on the Observation Chamber. This allows you to log temperature error messages and potentially use these in trial and hardware control in EthoVision XT. Important: If you have the DanioVision Observation Chamber version DVOC-0030 or older, you cannot use TTL2, because this port is used by the temperature sensor for the lens heater inside the observation chamber. - Connect the DanioVision Temperature Control Unit to the mains socket. - Connect the DanioVision Observation Chamber to the EthoVision XT computer. For details, see the Reference Manual - DanioVision Observation Chamber DVOC-0041. Set Up the DanioVision Temperature Control Unit Source: DanioVision TCU Reference Manual, Noldus Information Technology --- ## Zebrafish Epilepsy Research - Future Directions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/zebrafish-epilepsy-research-future-directions Chapter: DanioVision Future Directions The integration of CRISPR/Cas9 technology for generating zebrafish models of epilepsy in F0, combined with the advanced behavioral analysis capabilities of the EthoVision XT system and a deep multiparametric analysis represents a powerful approach for phenotyping different genetic epilepsy genes, define a behavioral fingerprint, and for the discovery of novel therapeutic interventions. Future research will benefit from the continuous refinement of behavioral assays and the development of more sophisticated zebrafish models, opening new avenues for the treatment and management of epilepsy. About Noldus Noldus Information Technology is a global leader in the development of software and hardware solutions for behavioral research. With a commitment to innovation and quality, Noldus provides researchers with the tools they need to advance our understanding of behavior and its underlying mechanisms. This extended white paper provides a detailed overview of the application and impact of multiparametric behavioral analysis in zebrafish models for epilepsy research, highlighting the capabilities of the Noldus EthoVision XT system in advancing the field. Besides EthoVision XT, Noldus offers a wide variety of tools to enhance zebrafish research. DanioVision is the ideal system for observing zebrafish larvae. The Observation chamber provides a controlled testing environment that can facilitate a multi-well plate or other small containers that hold larvae. With its high-speed digital camera minute changes in movement can be tracked and analyzed using EthoVision XT. If even more detail is needed for your research, DanioScope is a non-invasive software tool that can measure morphological parameters like heartbeat, eye size, body length, blood flow and gut activity. Furthermore, DanioScope is also able to automatically detect behaviors such as tail coiling and convulsions. Lastly, besides tools, Noldus offers various services to their customers. Our expert trainers and consultants can help you transform data into meaningful insights and provide around-the-clock support. We also offer on-demand training courses and webinars to help you further develop your knowledge and skills on zebrafish behavioral studies. References - Turrini, L.; Sorelli, M.; De Vito, G.; Credi, C.; Tiso, N.; Vanzi, F.; Pavone, F.S. Multimodal Characterization of Seizures in Zebrafish Larvae. Biomedicines 2022, 10, 951, doi:10.3390/biomedicines10050951. - Thijs, R.D.; Surges, R.; O'Brien, T.J.; Sander, J.W. Epilepsy in Adults. The Lancet 2019, 689–701, doi:10.1016/S0140-6736(18)32596-0. - Fisher, R.S.; Acharya, J.N.; Baumer, F.M.; French, J.A.; Parisi, P.; Solodar, J.H.; Szaflarski, J.P.; Thio, L.L.; Tolchin, B.; Wilkins, A.J.; et al. Visually Sensitive Seizures: An Updated Review by the Epilepsy Foundation. Epilepsia, 739–768, doi:10.1111/epi.17175. - Miguel Sanz, C.; Martinez Navarro, M.; Caballero Diaz, D.; Sanchez-Elexpuru, G.; Di Donato, V. Toward the Use of Novel Alternative Methods in Epilepsy Modeling and Drug Discovery. Front. Neurol. 2023, 14, 1213969, doi:10.3389/fneur.2023.1213969. - Locubiche, S.; Ordóñez, V.; Abad, E.; Scotto Di Mase, M.; Di Donato, V.; De Santis, F. A Zebrafish-Based Platform for High-Throughput Epilepsy Modeling and Drug Screening in F0. Int. J. Mol. Sci. 2024, 25, 2991, doi:10.3390/ijms25052991. - Patton, E.E.; Zon, L.I.; Langenau, D.M. Zebrafish Disease Models in Drug Discovery: From Preclinical Modelling to Clinical Trials. Nat. Rev. Drug Discov. 2021, 611–628, doi:10.1038/s41573-021-00210-8. - Cully, M. Zebrafish Earn Their Drug Discovery Stripes. Nat. Rev. Drug Discov. 2019, 811–813, doi:10.1038/d41573-019-00165-x. - Rubbini, D.; Cornet, C.; Terriente, J.; Di Donato, V. CRISPR Meets Zebrafish: Accelerating the Discovery of New Therapeutic Targets. SLAS Discov., 552–567, doi:10.1177/2472555220926920. - Baraban, S.C.; Dinday, M.T.; Hortopan, G.A. Drug Screening in Scn1a Zebrafish Mutant Identifies Clemizole as a Potential Dravet Syndrome Treatment. Nat. Commun. 2013, 2410, doi:10.1038/ncomms3410. - Kawahara, G.; Karpf, J.A.; Myers, J.A.; Alexander, M.S.; Guyon, J.R.; Kunkel, L.M. Drug Screening in a Zebrafish Model of Duchenne Muscular Dystrophy. Proc. Natl. Acad. Sci. 2011, 5331–5336, doi:10.1073/pnas.1102116108. - Burger, A.; Lindsay, H.; Felker, A.; Hess, C.; Anders, C.; Chiavacci, E.; Zaugg, J.; Weber, L.M.; Catena, R.; Jinek, M.; et al. Maximizing Mutagenesis with Solubilized CRISPR-Cas9 Ribonucleoprotein Complexes. Development, dev.134809, doi:10.1242/dev.134809. - Cornet, C.; Di Donato, V.; Terriente, J. Combining Zebrafish and CRISPR/Cas9: Toward a More Efficient Drug Discovery Pipeline. Front. Pharmacol., 703, doi:10.3389/fphar.2018.00703. - Devinsky, O.; Vezzani, A.; O'Brien, T.J.; Jette, N.; Scheffer, I.E.; De Curtis, M.; Perucca, P. Epilepsy. Nat. Rev. Dis. Primer 2018, 18024, doi:10.1038/nrdp.2018.24. - Fisher, R.S.; Cross, H.; D'Souza, C.; French, J.A.; Haut, S.; Higurashi, N.; Hirsch, E.; Jansen, F.E.; Peltola, J.; Moshé, S.L.; et al. 2017 International League Against Epilepsy Classifications of Seizures and Epilepsy Are Steps in the Right Direction. Epilepsia 2019, 1040–1044, doi:10.1111/epi.15052. - Charu C. Aggarwal. Outlier Analysis, 2nd ed.; Springer Cham, 2017; ISBN 978-3-319-47577-6. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## Zebrafish Epilepsy Research - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/zebrafish-epilepsy-research-introduction Chapter: DanioVision Introduction Epilepsy encompasses a spectrum of neurological disorders characterized by epileptic seizures, arising from excessive neuronal activity in the brain. The development of accurate, high-throughput models for epilepsy research is crucial for the elucidation of the underlying genetic and molecular mechanisms and for the identification of potential therapeutic targets. Zebrafish (Danio rerio) have emerged as a premier model organism in neuroscience research, including epilepsy studies, due to their genetic manipulability, translational potential, and the feasibility of large-scale phenotypic screenings. What Is Epilepsy? Epilepsy is one of the most common neurological disorders, with over 70 million people diagnosed worldwide. This disorder is characterized by the appearance of seizures, a consequence of an imbalance between excitatory and inhibitory circuits, causing both cognitive and psychological impairment and increasing the risk of early death. The etiology underlying this disease is variable, genetic mutations being one of the most important causes. Many pediatric epilepsy patients present frequent seizures, events that damage and alter their quality of life. Seizures can be provoked by various sensory inputs. When they are produced in response to light, color, or patterns, it is considered photosensitive epilepsy. Photosensitivity occurs in several epileptic syndromes, being particularly prevalent in genetic generalized epilepsies. Moreover, several epilepsies are resistant to the treatments currently available, demonstrating the ongoing need to test novel anti-seizure medications (ASM). Zebrafish Knock-Out Model In this study, we aimed to establish a workflow allowing scientists to use somatic knock-out zebrafish larvae to analyze the function of genes involved in the pathogenesis of neurodevelopmental disorders. This was motivated by the advantages that the zebrafish model provides and the necessity of expanding the toolbox for modeling epilepsy in order to streamline the discovery of novel ASMs. Our objective is to develop a zebrafish-based comprehensive platform enabling the functional validation of common and de novo rare loss-of-function mutations in a high-throughput fashion. As proof of principle, we knocked out a group of six genes associated with childhood epilepsy and characterized their loss-of-function phenotype through a multiparametric analysis using Noldus tools. Through our approach, we introduce a novel integrated method for high-throughput epilepsy mutant generation, behavioral characterization and ASM testing. Epilepsy Research Zebrafish offer several advantages for modeling human diseases, like epilepsy. Their transparent embryos and larvae provide a unique window into the brain's internal processes, allowing for direct observation of neuronal activity and drug effects in vivo. Additionally, the rapid development and high fecundity of zebrafish facilitate large-scale genetic screenings and drug discovery efforts. The genetic and physiological homologies between zebrafish and humans further underscore the relevance of this model to human epilepsy research. Zebrafish larvae have been used to model various forms of epilepsy, including both genetic and chemically induced forms of the disorder. Researchers can use a variety of techniques to induce seizures in the larvae, such as administering convulsant drugs or exposing them to specific light stimuli, and then study the underlying neural mechanisms that drive the seizures. Zebrafish Genetics The advent of CRISPR/Cas9 gene-editing technology has revolutionized zebrafish research, enabling precise manipulation of the zebrafish genome to model human genetic diseases. By inducing targeted mutations in genes related with childhood epilepsy, we could generate zebrafish models in F0 that recapitulate the molecular and phenotypic characteristics of some human epileptic disorders, specifically light-induced seizures. The constant improvements in CRISPR/Cas9-induced gene disruption have allowed us to generate de-facto mutants of genes of interest in just a few days of development, enabling genetic target validation and compound treatment in a timely manner. This approach allows for the functional analysis of several epilepsy-associated genes and, importantly, the identification of novel potential pharmacological treatments. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## Zebrafish Epilepsy Research - Tracking with EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/daniovision/page/zebrafish-epilepsy-research-tracking-with-ethovision-xt Chapter: DanioVision With EthoVision XT Behavioral phenotyping is a cornerstone of epilepsy research in zebrafish models. EthoVision® XT offers an advanced platform for the automated tracking and analysis of zebrafish behavior across multiple parameters. The accurate detection and tracking of the zebrafish larvae in all the different possible setups allow for a detailed analysis of locomotor activity, obtaining data of multiple parameters related to seizure-like behavior. First, the cumulative percentage of variance of different variables was assessed, unveiling that only 2 principal components (PC) already explain about 80% of the total variance of the sample. Considering a wide range of behavioral parameters, a principal component analysis (PCA) based on two PCs was performed, selecting the key kinematic measurements related with an epileptic-like behavior that can also be considered a high activity behavior regarding the locomotor parameters. Of all the considered parameters, only seven were considered key variables with higher projection and contribution (cos2 > 0.75). These key variables are associated with a modification of the larval position or orientation in the space and include: - Maximum velocity (mm/s) - Number of angle turns - Maximum acceleration (mm/s²) - Mobility in the arena (%) - Cumulative duration (s) of three different mobility states: immobile, mobile, and highly mobile Capturing High Phenotypic Variability Epilepsy is characterized by a high phenotypic heterogeneity, ranging from normal phenotypes to simple febrile seizures and severe epileptic encephalopathies. This heterogeneity highlights the need to have a specialized system and to develop an analysis that allows a statistical distinction of non-epileptic and epileptic-like behavior. To this end, the behavior of multiple crispants of genes related with different childhood epilepsies were analyzed. Considering the previously selected variables, a total sample of 563 larvae and 2209 events related with light-induced epileptic stimuli were analyzed, and the childhood epilepsy genes crispants activity was shown to be different to the behavior of the used controls (scramble). Within this plot, despite the high dispersion of the different measurements — related with the high heterogeneity of the epileptic manifestations — the scramble observations clustered in the center of the PC plot, showing non-epileptic phenotypes, while different observations remote to these positions, corresponding to crispants observations, were potential outliers that could be defining an epileptic-like fingerprint. Behavioral Fingerprint Analyzed larvae could be classified in different groups depending on their activity level, and it was speculated that the crispants of genes having a positive association with photosensitive epilepsy would have an increased representation in the more active group. To explore this possibility, the Mahalanobis distance (MD) of all the observations was measured to evaluate how each flash response differs from the average of the entire population. MD measures the distance between a sample point and the distribution of all the sample points, and it is defined by two parameters: - Distance Magnitude: The numerical MD value - P-Value: A statistical measurement to validate the hypothesis (outliers considered with p-value ≤ 0.05) Two regions of activity were distinguished and classified within the population: - Low Activity Region: MD < 2.5 and p-value > 0.1, corresponding to a non-epileptic phenotype - High Activity Region: MD > 2.5 and p-value < 0.1, corresponding to an epileptic-like phenotype This observation suggests that larvae with increased photosensitivity are prone to display a highly aberrant behavior in response to exposure to flashes of light, constituting a population of outliers distinguished by their higher motor activity. These extreme behaviors are assumed to correspond to epileptic-like seizures characterized by aberrant and excessive movements. Transferring these observations of the two differentiated groups back to the PC plot reveals that most of the observations corresponding to an epileptic-like phenotype overlap with the crispants of childhood epilepsy genes. Therefore, the study demonstrated the efficacy of the EthoVision XT software and the precision of the Noldus equipment in defining a fingerprint for mild and severe childhood epilepsy genes that present a photosensitive epileptic-like behavior through an exhaustive analysis of key parameters detected, tracked, and analyzed, even though it is known to be a highly heterogeneous condition. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## Conduct Maze Integration with EthoVision - 1. Conduct Maze Software Install URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/conduct-maze-integration-with-ethovision-1-conduct-maze-software-install Chapter: EthoVision XT Conduct Maze Software Install Maze Engineers software ConductMaze is a light-weight adapter to EthoVision to control the execution of automated mazes (T-, Y-, 8 arm, 12 arm and 16 arm maze, etc.) or apparatuses (shocker, fear conditioning, etc.) - The software adapter can be deployed in a folder on the same machine where EthoVision software is running. For example, the folder can be C:\appConductMaze\bin. - The executable ConductMazeUI.exe is a light-weight Windows UI application that needs to start before experiments with an automated maze or apparatus. The application accepts commands from EthoVision and controls the execution of the commands. The folder contains the following executables and dlls: - ConductMazeUI.exe — Conduct maze adapter running on EthoVision machine - ConductMazeUI.exe.config — The executable configuration file - ConductMazeLib.dll — A Maze Conduct library dll - CoreAudio.dll — A Maze Conduct library dll - EthoVisionSimulator.exe — An EthoVision simulator for testing without actually invoking EthoVision - galasoft.mvvmlight.dll — A Maze Conduct library dll - MazeController.exe — The executable to be invoked by EthoVision Once ConductMazeUI starts, it connects to the maze via a comport and is ready to accept commands from EthoVision. USB to 232 Driver Install USB to 232 driver installation on the software machine is required. The driver is included in the cable box. Start ConductMazeUI - Step 1: Choose a Maze or Apparatus Type The user must choose a maze type in the ConductMazeUI.exe.config file: - - - - - - - - - - - - - - - - R-Maze represents the Radial 8 arm maze, D-Maze represents the Dodecagon 12 arm maze, H-Maze represents the 16 arm maze, and R-MazeX4 represents the 8 arm maze with 4 extra doors (to partition the maze into T and Y). - Step 2: Choose the Comport When the micro-controller is connected to your computer, a port is created as shown in the Device Manager. If the device is not shown in the Ports section, it will appear in a different section. This means the computer could not find the driver for the hardware device. In this case, you will need to install the driver (small disc included in the UNITEK box) which is included in shipping. - Step 3: Start ConductMazeUI Double-click on ConductMazeUI.exe. The main window will appear. - Step 4: Connect to Comport Once your computer recognizes the hardware, choose the comport that matches the one shown in the Device Manager, then click the Connect button. Experiment Setup in EthoVision In EthoVision, create an External Command Action with a name. In the Select program to run field, choose MazeController.exe and in the Command line options field, add open command(s) such as D10. The options represent an action to open a door, close a door, dispense a pellet, or a combo action. The following examples show some user configuration setups: - Example 1: MazeController.exe D10 — Sends a command to open Door 1 - Example 2: MazeController.exe D11 — Sends a command to close Door 1 - Example 3: MazeController.exe D10;D20;D30 — Sends a combo action to open Door 1, Door 2, and Door 3 In general, certain condition(s) are required to open a door, close a door, or dispense a pellet. Simple Commands 8 Arm Maze (R-Maze — old version): - Open doors: D10, D20, D30, D40, D50, D60, D70, D80 - Close doors: D11, D21, D31, D41, D51, D61, D71, D81 - Dispense a pellet: FT01, FT02, FT03, FT04, FT05, FT06, FT07, FT08 8 Arm Maze with 4 Extra Doors (R-MazeX4): - Open doors: D010, D020, D030, D040, D050, D060, D070, D080, DX10, DX30, DX60, DX70 - Close doors: D011, D021, D031, D041, D051, D061, D071, D081, DX11, DX31, DX61, DX71 8 Arm Maze (R-MazeV2 — current version): - Open doors: D010, D020, D030, D040, D050, D060, D070, D080 - Close doors: D011, D021, D031, D041, D051, D061, D071, D081 - Deliver reward (pellet or water): FT01, FT02, FT03, FT04, FT05, FT06, FT07, FT08 12 Arm Maze (D-Maze): - Open doors: D010, D020, D030, D040, D050, D060, D070, D080, D090, D100, D110, D120 - Close doors: D011, D021, D031, D041, D051, D061, D071, D081, D091, D101, D111, D121 - Dispense a pellet: FT01 through FT12 16 Arm Maze (H-Maze): - Open doors: D010, D020, D030, D040, D050, D060, D070, D080, D090, D100, D110, D120, D130, D140, D150, D160 - Close doors: D011, D021, D031, D041, D051, D061, D071, D081, D091, D101, D111, D121, D131, D141, D151, D161 - Dispense a pellet: FT01 through FT16 T-Maze 3D (3 Door T-Maze): - Open doors: D10, D20, D30 - Close doors: D11, D21, D31 Y-Maze: - Open doors: D10, D20, D30 - Close doors: D11, D21, D31 Shocker: - Start shocker: T=600;D=2;N=100;I=0.5 - T — Total time in seconds - D — Shock pulse duration in seconds - N — Number of shocks - I — Shock current in mA (0–4.0) To terminate the shock session, click the Send button in the lower right corner. Additional information is available in the ConductMazeUI help menu. R-Maze Reward Type For R-MazeV2, the reward can be pellet or water. When the application is launched, an 8 Arm Reward tab appears. By default, the reward type is set to Pellet, corresponding to the pellet dispensers. If you use a lick-o-meter device, select a reward type of Water. The commands from EthoVision to deliver reward (pellet or water) are the same: - Deliver reward (pellet or water): FT01, FT02, FT03, FT04, FT05, FT06, FT07, FT08 Automation Status on ConductMaze When the experiment runs, the External Command Action is invoked and the command is sent to ConductMazeUI. On the left panel of ConductMazeUI, the command from EthoVision is logged. On the right panel, the command execution status is logged. ConductMazeUI can be minimized if you do not need to monitor the status. ConductMazeUI also provides functionality for users to send manual commands to the automated radial arm maze for testing purposes. Source: Conduct Maze Integration with EthoVision, Noldus Information Technology --- ## Conduct Maze Integration with EthoVision - 13. Operant (Tier 2 Nose Poke) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/conduct-maze-integration-with-ethovision-13-operant-tier-2-nose-poke Chapter: EthoVision XT Operant (Tier 2 Nose Poke) Operant Chamber Commands Type Action Command Examples Tone Start t=1 type tone v=1-100 volume d=1-360 duration in seconds f=200-18000 frequency t=1,v=50,d=5,f=1000 Tone Stop t=1 type tone v=0 stop t=1,v=0 Cue Lights Start t=2 type cue light c=1,2 with 1 left panel, 2 right panel v=1 start d=1-360 duration in seconds t=2,c=1,v=1,d=5 t=2,c=2,v=1,d=5 Cue Lights Stop t=2 type cue light c=1,2 with 1 left panel, 2 right panel v=0 stop t=2,c=1,v=0 t=2,c=2,v=0 House Lights Start t=3 type house light v=0-100 light level d=1-7200 duration in seconds t=3,v=50,d=60 House Lights Stop t=3 type house light v=0 stop t=3,v=0 Pellets Start t=4 type pellet c=1,2 with 1 left panel, 2 right panel v=1 deliver one pellet t=4,c=1,v=1 t=4,c=2,v=1 Sound Start t=5 type tone v=1-100 volume d=1-360 duration in seconds t=5,v=50,d=5 Sound Stop t=5 type tone v=0 stop t=5,v=0 Manual Control Window In addition to the normal functions of receiving and executing commands from Ethovision, the ConductMaze adapter software provides a manual control panel. - It can be used to test controls - It can be used for manual controls like closing the door - It shows the control states as a dashboard during the protocol run T-Maze (Plus Two Cue Lights on Goal Arms) T-Maze Commands Type Action Command Examples Door Open t=1 type Door d=1,2,3,4,5,6,7 doors v=1 open t=1,d=1,v=1 t=1,d=7,v=1 Door Close t=1 type Door d=1,2,3,4,5,6,7 doors v=0 close t=1,d=1,v=0 t=1,d=7,v=0 Liquid Reward Deliver t=2 type liquid c=1,2 with 1 left arm, 2 right arm v=1,2,3,4,5,6,7,8,9,10 drops t=2,c=1,v=1 t=2,c=2,v=2 Cue Lights Start t=3 type cue light c=1,2 with 1 left arm, 2 right arm v=1,…,100 light intensity, 0 = off t=3,c=1,v=50 t=3,c=2,v=100 Cue Lights Stop t=3 type cue light c=1,2 with 1 left arm, 2 right arm v=0 t=3,c=1,v=0 t=3,c=2,v=0 Y-MazeV2 (Plus Two Cue Lights, Two Speakers, Two Nose Pokes on Goal Arms) Y-Maze Commands from Noldus EthoVision Type Action Command Examples Tone Start t=1 type tone c=1,2 (1 left arm, 2 right arm) v=1-100 volume d=1-360 duration in seconds f=200-18000 frequency t=1,c=1,v=50,d=5,f=1000 t=1,c=2,v=50,d=5,f=1000 Tone Stop t=1 type tone c=1,2 v=0 stop t=1,c=1,v=0 t=1,c=2,v=0 Cue Lights Start t=2 type cue light c=1,2 v=1 x=R-G-B d=1-360 duration in seconds t=2,c=1,v=1,x=0-255-0,d=5 t=2,c=2,v=1,x=0-0-255,d=5 Cue Lights Stop t=2 type cue light c=1,2 v=0 stop t=2,c=1,v=0 t=2,c=2,v=0 Custom Sound Start t=5 type custom sound c=1,2 v=1-100 volume d=1-360 duration in seconds t=5,c=1,v=50,d=5 Custom Sound Stop t=5 type tone c=1,2 v=0 stop t=5,c=1,v=0 Doors Open t=7 type door c=1,2 v=1 open t=7,c=1,v=1 Doors Close t=7 type door c=1,2 v=0 close t=7,c=1,v=0 Pellets Start t=8 type pellet c=1,2 v=1 t=8,c=2,v=1 Protocol Setup for Events (Nose Pokes and Reward Pokes) This version allows the user to set up actions for events (nose pokes and reward pokes). On the Ymaze Config tab, click Add on the Config line to create a config, then click Add on the Event Actions line to add event actions. Ymaze Result The results are saved in the Ymaze Result tab. Empathy Essay Empathy-Maze Commands from Noldus EthoVision Type Action Command Examples Shock Start c=1,2,0 (1 left chamber, 2 right chamber, 0 both chambers) v=1-100 volume d=1-360 duration in seconds f=200-18000 frequency i=0.1–4.0 shock current level (mA) c=1,v=50,d=5,f=1000,i=0.5 c=2,v=50,d=5,f=1000,i=0.4 Shock Stop t=0 Empathy Result Once the adapter receives the command, a random shock schedule is generated based on the algorithm described in Random Shock Methods.pdf. The shock schedule is then executed. There are two ways to stop the shock execution: - Send a stop command from video tracking - Go to the Command Execution tab, choose command t=0, and click the Send button Save Shock Schedule There is no result output for the empathy test; behavior is captured and analyzed with video. To save the shock schedule, the grid data can be copied and pasted to a spreadsheet. - To select the entire grid, select the first row and first column cell, hold the Shift key, then select the last row and last column cell. The entire grid data should be selected (highlighted in light blue). Release the Shift key after selection. - Press Ctrl + C to copy the data to the clipboard. - Go to a spreadsheet page and press Ctrl + V to paste the data. The grid data along with headers will be pasted into the spreadsheet. Manual Commands For testing purposes, the software allows the user to send a shock command (a connection must be established). Source: Conduct Maze Integration with EthoVision, Noldus Information Technology --- ## Conduct Maze Integration with EthoVision - 6. Ethovision Simulator For Testing URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/conduct-maze-integration-with-ethovision-6-ethovision-simulator-for-testing Chapter: EthoVision XT EthoVision Simulator for Testing For testing purpose, the executable EthoVisionSimulator.exe can be invoked to generate commands to ConductMaze software. Shocker Execution Result Window For shocker, the Execution Result tab is shown. The grid shows the random shock schedules and execution progress. For the random shock generation algorithm, please see Random Shock Methods.pdf. If the user chooses to terminate a shock session before it runs to completion, the user can click on Send button as shown below. Fear Conditioning Fear Conditioning Commands Tone – Start - c=1, 2, 3, 4 chamber ID - t=1 type tone - v=1,…,100 volume - d=1, 2,…,n tone play duration in seconds - f=20,…,18000 tone frequency - Example: c=1,t=1,v=50,d=5,f=1000 Tone – Stop - c=1, 2, 3, 4 chamber ID - t=1 type tone - v=0 stop - Example: c=1,t=1,v=0 Shock – Start - c=1, 2, 3, 4 chamber ID - s=0,1 left or right - t=5 type shock - v=1 start - d=1, 2, …, n duration in seconds - m=0.1 - 4.0 current level in mA, step 0.1 - Example: c=1,s=0,t=5,v=1,d=5,m=0.4 Shock – Stop - c=1, 2, 3, 4 chamber ID - s=0,1 left or right - t=5 type shock - v=0 stop - Example: c=1,s=0,t=5,v=0 Manual Control Window In addition to the normal functions of receiving and executing commands from Ethovision, the ConductMaze adapter software provides a manual control panel. It can be used to stop shock in case the user chooses to quickly stop shock. It can also be used for testing. Labyrinth Maze Labyrinth Door Commands Open Doors Commands: - Row0: R01Y, R02Y, R03Y, R04Y, R05Y - Row1: R11Y, R12Y, R13Y, R14Y, R15Y - Row2: R21Y, R22Y, R23Y, R24Y, R25Y - Row3: R31Y, R32Y, R33Y, R34Y, R35Y - Row4: R41Y, R42Y, R43Y, R44Y, R45Y - Row5: R51Y, R52Y, R53Y, R54Y, R55Y - Col0: C10Y, C20Y, C30Y, C40Y, C50Y - Col1: C11Y, C21Y, C31Y, C41Y, C51Y - Col2: C12Y, C22Y, C32Y, C42Y, C52Y - Col3: C13Y, C23Y, C33Y, C43Y, C53Y - Col4: C14Y, C24Y, C34Y, C44Y, C54Y - Col5: C15Y, C25Y, C35Y, C45Y, C55Y Close Doors Commands: - Row0: R01X, R02X, R03X, R04X, R05X - Row1: R11X, R12X, R13X, R14X, R15X - Row2: R21X, R22X, R23X, R24X, R25X - Row3: R31X, R32X, R33X, R34X, R35X - Row4: R41X, R42X, R43X, R44X, R45X - Row5: R51X, R52X, R53X, R54X, R55X - Col0: C10X, C20X, C30X, C40X, C50X - Col1: C11X, C21X, C31X, C41X, C51X - Col2: C12X, C22X, C32X, C42X, C52X - Col3: C13X, C23X, C33X, C43X, C53X - Col4: C14X, C24X, C34X, C44X, C54X - Col5: C15X, C25X, C35X, C45X, C55X Group Commands: - Row open: R0_Open, R1_Open, R2_Open, R3_Open, R4_Open, R5_Open - Col open: C0_Open, C1_Open, C2_Open, C3_Open, C4_Open, C5_Open - Row close: R0_Close, R1_Close, R2_Close, R3_Close, R4_Close, R5_Close - Col close: C0_Close, C1_Close, C2_Close, C3_Close, C4_Close, C5_Close - All_Close, All_Open Labyrinth Maze with Two Pellet Dispensers Dispense a pellet: FT01, FT02 Active Passive Avoidance Active Passive Avoidance Commands Tone – Start - c=1, 2 chamber ID (left and right) - t=1 type tone - v=1, …, 100 volume level - d=1, 2,…,n tone play duration in seconds - f=20,…,18000 tone frequency - Examples: c=1,t=1,v=50,d=5,f=1000   c=2,t=1,v=80,d=10,f=1000 Tone – Stop - c=1, 2 chamber ID - t=1 type tone - v=0 stop - Example: c=1,t=1,v=0 Light – Start - c=1, 2 chamber ID (left and right) - t=2 type light - v=0, …, 100 light level - d=1, 2,…,n duration in seconds Light – Stop - Example: c=1,t=2,v=0 Shock – Start - c=1, 2 chamber ID (left and right) - t=5 type shock - v=1 start - d=1, 2, …, n duration in seconds - m=0.1 - 4.0 current level in mA, step 0.1 - Example: c=1,t=5,v=1,d=5,m=0.4 Shock – Stop - c=1, 2 chamber ID (left and right) - t=5 type shock - v=0 stop - Example: c=1,t=5,v=0 Door – Open - c=0 central area - t=4 type door - v=1 open - Example: c=0,t=4,v=1 Door – Close - c=0 - t=4 type door - v=0 close - Example: c=0,t=4,v=0 Manual Control Window In addition to the normal functions of receiving and executing commands from Ethovision, the ConductMaze adapter software provides a manual control panel. It can be used to stop shock in case the user chooses to quickly stop shock. It can also be used for testing. Comports Two comports are used for active and passive avoidance shuttle box, one for chamber light, tone, and door and the other for shocker. Make sure both comports are connected. IDED Chamber IDED Chamber Commands Cue Lights – Start - c=1, 2 chamber ID (left and right) - x=1,2 location (front and back) - t=1 type cue light - y=1,2,3 color R, G, B - v=1 start - Examples: c=1,x=1,t=1,y=1,v=1   c=2,x=1,t=1,y=3,v=1 Cue Lights – Stop - c=1, 2 chamber ID - x=1,2 location - t=1 type cue light - v=0 stop - Examples: c=1,x=1,t=1,v=0   c=2,x=1,t=1,v=0 House Lights – Start - c=1, 2 chamber ID (left and right) - t=2 type house light - v=0, …, 100 light level - Examples: c=1,t=2,v=50   c=2,t=2,v=60 House Lights – Stop - Examples: c=1,t=2,v=0   c=2,t=2,v=0 Pellets – Start - c=1, 2 chamber ID (left and right) - t=3 type pellet - v=1 start - Example: c=1,t=3,v=1 Scents – Start - c=1, 2 chamber ID (left and right) - t=4 type scent - v=1 start - Examples: c=1,t=4,v=1   c=2,t=4,v=1 Scents – Stop - c=1, 2 chamber ID (left and right) - t=4 type scent - v=0 stop - Examples: c=1,t=4,v=1   c=2,t=4,v=0 Door – Open - c=0 central area - t=5 type door - v=1 open - Example: c=0,t=5,v=1 Door – Close - c=0 - t=5 type door - v=0 close - Example: c=0,t=5,v=0 Manual Control Window In addition to the normal functions of receiving and executing commands from Ethovision, the ConductMaze adapter software provides a manual control panel. - It can be used to test controls - It can be used for manual controls like closing the door - It shows the control states as a dashboard during the protocol run Active Place Avoidance (Circular) Active Place Avoidance Commands Shock – Start - t=4 type shock - v=1 start - d=1-60 duration in seconds - m=0.1 - 4.0 current level in mA, step 0.1 - Example: t=4,v=1,d=5,m=0.4 Shock – Stop - t=4 type shock - v=0 stop - Example: t=4,v=0 Rotate – Start - t=2 type rotate - v=1 start - s=4-100 speed in rounds/second - c=0 or 1 direction; 0 = counter-clockwise, 1 = clockwise - Example: t=2,v=1,s=20,c=0 Rotate – Stop - t=2 type rotate - v=0 stop - Example: t=2,v=0 Manual Control Window In addition to the normal functions of receiving and executing commands from Ethovision, the ConductMaze adapter software provides a manual control panel. - It can be used to test controls - It can be used for manual controls like closing the door - It shows the control states as a dashboard during the protocol run Source: Conduct Maze Integration with EthoVision, Noldus Information Technology --- ## EthoVision XT - 1 Introduction to Trial Control URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-1-introduction-to-trial-control Chapter: EthoVision XT 1 - Introduction to Trial Control Introduction To Trial Control This Manual This manual is meant for all users of EthoVision XT: For users of the Base version. You can find extensive information on the Trial Control conditions (see page 67) and analysis of Trial Control data (see page 168). This information is not present in the EthoVision XT Help. For users of the Base version plus the Trial and Hardware Control module. You find all the information you need in this guide. If you use EthoVision XT in combination with hardware devices, you can find the relevant information in Section 7 (page 104). EthoVision XT Help For extensive information on EthoVision XT or for troubleshooting, see the EthoVision XT Help. In EthoVision XT, choose Help > EthoVision XT Help or press F1. Other documentation From the Windows Start menu choose All Apps > Noldus > EthoVision XT 17 Other documentation. There you find: EthoVision XT 17 - Application Manual for information on common tests including conditioning tests that make use of sub-rules in the Trial Control Settings. PhenoTyper - EthoVision XT 17 - Reference Manual for information on PhenoTyper and how to connect it to EthoVision XT. PhenoTyper - EthoVision XT 17 - Service Manual for information about PhenoTyper and devices such as the Noldus Pellet dispenser, the Noldus L5ickometer and PhenoWheel. DanioVision DVOC-0041 - Reference Manual if you use Trial Control with the DanioVision Observation Chamber. Why Use Trial And Hardware Control? Trial Control allows you to automate your experiment. For example: You want to set a maximum duration for your trials. See page 41. 1 - Introduction to Trial Control You want to automate the start and/or stop of data acquisition. For example: Start recording when the rat is first detected in the open field. Stop recording when the rat has reached the platform in the Morris water maze. Start recording at exactly 12:30:00. Stop recording after the animal has been in the closed arms of the plus maze for 5 minutes. See page 47 and also page 23 for general information. You want to automate conditioning schedules, or operate hardware devices. For example: When the animal presses a lever, have the food dispenser drop a food pellet. When the animal leaves the shelter, use an External Command action to start a recording with Media Recorder. When the animal enters the shelter, turn on a light. Close the door of a radial maze when the animal has exited that arm. See page 23 for general information and page 55 for making sub-rules. To use Trial and Hardware Control - Open the Trial Control screen (see page 16). - Define the conditions that, when met during your trial, trigger specific actions. Organize conditions and actions in sequences (see page 23). - Before starting data acquisition, you make sure that those Trial Control Settings are active. For information on how to manage Trial Control Settings, see also Settings and profiles, under File management in the EthoVision XT Help. Conditions And Actions A Condition is a statement that EthoVision evaluates. An Action is a command executed on a variable or a hardware device. You can therefore control your experiment by linking conditions with actions. example 1 In a Morris water maze test, stop tracking when the rat reaches the platform (provided that the platform has been defined as a zone). Stop tracking is the action and Rat on the platform is the condition. example 2 In a Fixed Ratio schedule, have EthoVision send a command to drop a pellet when the mouse has been detected in the Trigger zone. Drop one pellet is the action and Mouse in the Trigger zone is the condition. 1 - Introduction to Trial Control You define and link conditions with actions in a graphical form. Example 2 can be represented with the following: For more information on conditions, see page 26 and page 67 For more information on actions, see page 27. You can copy, move, connect and delete Trial Control elements such as actions and conditions. For how to do so, see the EthoVision XT Help. Trial Control Rules A Trial Control rule is a set of conditions and actions organized in a logic sequence. It can be viewed as a set of instructions executed during a trial. There are two types of Trial Control rules: Start-Stop trial rule. For starting and stopping data acquisition. This rule cannot be repeated or deleted. For details, see page 47. Sub-rules (available only in EthoVision XT with the Trial and Hardware Control Module, see page 14). Subroutines of the Start-Stop trial rule, which are meant to carry out specific actions. Sub-rules can start at specific times and be repeated according to conditions specified in a Sub-rule reference. For details, see page 55. Figure 1 A condition is followed by an action. The condition checks that the animal is in the zone named "Trigger zone". The action "Drop a pellet" is taken when the condition is met. Figure 2 Schematic representation of a generic sub-rule. 1 - Introduction to Trial Control How Trial Control Instructions Are Executed The instructions contained in the Trial Control Settings are carried out from the moment you start a trial, to the moment the trial is stopped. Only the instructions in the Trial Control Settings currently active (that is, highlighted in blue in the Experiment Explorer) are carried out. The program evaluates the Trial Control sequence at each sample time. The rate at which this happens depends on your chosen sample rate, not on the video frame rate. For the Start-Stop trial rule and each active sub-rule, the program remembers which Trial Control boxes were evaluated (active) in the previous sample. Depending on the type of this box: For a Condition box. EthoVision XT waits until the condition is met. When this happens (condition becomes true - see 3 in Figure 3), the program passes control to the next box in the sequence. The condition becomes then inactive (see 4 in the same figure). For an Action box. EthoVision XT carries out the action (see 4 in Figure 3), and passes control to the next box, which becomes active. Then, the Action box becomes inactive (see 5). For a Sub-rule Begin box. Control is passed to the box that follows. The Sub-rule Begin box becomes inactive. For a Sub-rule End box. This marks the end of a sub-rule. The sub-rule becomes inactive. Control is passed to the Reference box that had called that sub-rule. This Reference checks whether the sub-rule must be repeated. If this is not the case, control is passed to the box following the Reference box. For a Reference box. Control is passed to the Sub-rule Begin box. The Reference box makes the sub-rule active. The Reference box stays active until the last sub-rule repeat is completed. Next, the Reference box makes the sub-rule inactive and passes control to the box that follows. Next, the Reference box becomes inactive. The events marked in italics above are those you can define in the Analysis profile and analyze or visualize in a chart (see page 168). When a box becomes active, the previous one becomes inactive. 1 - Introduction to Trial Control Figure 3 Schematic representation of how Trial Control Instructions are executed. The scheme shows an example of a Start-Stop trial rule (see page 47). 1 - Tracking starts, either manually or because a previous condition has been met. 2 - Control passes to a Condition box (for example "Is mouse on top of Shelter?"), which becomes active. The condition is evaluated. 4 - Control passes to the next box. In this case, it is an Action. Actions are taken immediately (but see the note below on actions on hardware devices). For clarity, step 3 and 4 have been placed separately. In reality, when a condition becomes true it also becomes inactive at the same sample time, and control passes to the next box. Hatched outlines - Condition box becomes active. Dark outlines - Condition becomes true or Action is taken. Pale outlines - Box becomes inactive. 1 - Introduction to Trial Control When plotted against time (see page 168), events like those in Figure 3 look like as follows: Evaluation of Trial Control boxes Boxes combined in parallel using operators (see page 34) are evaluated at about the same time, in random order. This means that you cannot establish which condition is evaluated/which action is taken first. When your trial control is complex, for example when it includes sub-rules or conditions combined with operators, it is possible that two or more Trial Control boxes are evaluated at the same sample time. When a condition based on a dependent variable is evaluated (and therefore may or may not be met) also depends on the statistic used. See page 78 for details. If two or more boxes are evaluated at the same time, an action on a hardware device is taken only after all active boxes that must be evaluated have been evaluated. If the next box to be evaluated contains a condition that is fulfilled immediately, the program passes control to the next box. Therefore, within one sample time the program can pass control to two or more boxes to the right. Figure 4 Time plot of the events of Trial Control represented in Figure 3. The time that the animal is in the zone "Top of Shelter" is indicated by a horizontal bar. When tracking starts, the Action "Start track" becomes active (1st line) and immediately inactive (2nd line) as control passes to the next box. The condition "On top of Shelter?" becomes active (3rd line; see 2 in Figure 3) and immediately false (4th line) since the animal is not in that zone. When the animal enters the zone, the condition becomes true (5th line), and becomes immediately inactive (6th line) as control passes to the next box (see 4 in Figure 3). The action becomes active (7th line) and immediately inactive (8th line) as the command "drop a pellet" is sent to the pellet dispenser. 1 - Introduction to Trial Control When you stop the trial or the Maximum trial duration has been reached, all Trial Control boxes are deactivated. When the Rule End box of the Start/Stop trial rule is evaluated for an arena, data recording stops for that arena. From that moment, Trial Control is deactivated for that arena, even in those sub-rules that were ongoing in the meantime (see also the next page). A trial stops when trial control is deactivated in all arenas. Actions on hardware devices. A command is sent to a device after all boxes that must be evaluated have been evaluated. However, it may take some time for the outcome to be seen. For example, when a pellet dispenser is almost empty it may take a few seconds before a pellet is released. important When two or more actions on hardware devices follow each other, it is possible that they are evaluated at the same sample time. This happens because the computer is fast enough to analyze multiple Trial Control boxes in the sample interval. To make sure that actions are taken in the correct sequence and do not interfere with each other, add a Time condition (see page 142) between the action boxes, so after the first action is carried out EthoVision XT waits for a short time (for example, 0.1 s) before carrying out the next one. Sub-rules. A sub-rule is completed when the Rule End box has been evaluated, or when it is interrupted (see page 61 for more information). If two or more sub-rules are evaluated at the same time, it is not possible to establish which sub-rule is evaluated first at a specific sample. Trial Control in multiple arenas If your experimental setup includes two or more arenas, Trial Control is applied to each arena separately. This means that, if a condition is met in one arena, EthoVision XT takes the corresponding action in that arena, not the others. example See Figure 5. The setup includes four cages, each defined as an arena. A Trial Control In zone condition (see page 84) has been defined so that tracking starts when the animal is first detected in the arena. When you first put an animal in Arena 2, the condition is met in this arena and tracking starts for that arena. When you release the second animal in Arena 4, 2 seconds later, tracking in that arena starts 2 seconds later than in Arena 2. 1 - Introduction to Trial Control The advantage of Trial Control in multiple arenas is that you can put one animal at a time into the arenas, and EthoVision XT will start tracking in each arena at the appropriate moment. If your setup includes multiple arenas, you cannot define a condition/action specific to one arena. This means that the zones and hardware devices specified in the condition/action must be present in all arenas, and have the same name. If a zone or hardware device is not present in an arena, and a condition is based on that zone or device, Trial Control cannot progress for that arena. Therefore, tracking does not stop unless you set a maximum trial duration or tracking reaches the end of the video. Trial Control executes the instructions for each arena separately, however one cannot establish which arena is evaluated first at a specific sample time. Your Ethovision License And Trial Control Your EthoVision XT license determines which type of Trial Control you can set up. EthoVision XT Base license. You can define a rule to start and stop data recording (Start- Stop trial rule; see page 47), not sub-rules. You can also use an External command action. You cannot control hardware devices. EthoVision XT Base + Trial and Hardware Control Module. You can define a Start/Stop trial rule (see page 47), and in addition sub-rules (see page 55) that serve as subroutines of the Start-Stop trial rule. Moreover, you can control hardware devices. To acquire data in an experiment created with the Trial and Hardware Control Module, you must have a license that includes this module. Figure 5 Trial Control in multiple arenas. The time values displayed on the monitor are the time elapsed since the start of tracking in a particular arena. Tracking started earlier in Arena 2 than in Arena 4 (see text), therefore at any time the Elapsed time (duration of tracking) is longer in Arena 2 than in Arena 4. 1 - Introduction to Trial Control For more information on your EthoVision XT license, see the EthoVision XT Help. Analysis Of Trial Control Data The Trial Control function also allows you to easily analyze events that occurred during the trial. For example, in a conditioning experiment: Number of rewards. Calculate the number of pellets dropped during a trial. Latency between action and reward. Calculate the time interval between the time the animal pressed the lever and the time the animal approached the pellet dispenser. Number of failures. Calculate the number of times the animal approached the lever during the period between 'dropping the pellet' and 'animal approaching the pellet dispenser'. That is, how many times the animal pressed the lever when a reward was already available. You analyze Trial Control data the same way as for the behavioral variables. In the Experiment Explorer, open an Analysis profile, and specify the data you want to analyze (Trial Control event for point events, Trial Control state for time intervals between two events). For the detailed procedure, see page 168. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 10 User-defined hardware devices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-10-user-defined-hardware-devices Chapter: EthoVision XT 10 - User-defined hardware devices User-defined Hardware Devices User-defined Device Types Device types like the PhenoTyper's Top Unit Interface, the Lickometer and the Pellet dispenser are pre-defined in EthoVision XT as default device types, so when you use such devices you do not have to define their properties. In the case you want to use a new device type or a device with parameters different from those set in Noldus devices, you can create a User-defined device type. For example: You want to sample the Lickometer at a rate different from the default one, that is one sample every two seconds. To do so, create a new Lickometer device type, where the only difference between the existing Lickometer and the new device type is the value for the sampling interval. Add a "Trapdoor" device type by duplicating the existing Custom Device, and by replacing the various command- and signal texts. For instance: replace Output 1 High with Door 1 open. This section instructs how to make simple changes to an existing device. For more complex changes, the Noldus HardwareInterface USB-IO box software and maybe even EthoVision XT itself may need to be changed. Contact Noldus Technical support for wishes and ideas. In order to carry out the procedure below, you need some experience with computers and xml language. In A Nutshell When you install EthoVision XT, the following file: DeviceTypesNoldus.xml is copied to the following folders (henceforth named ProgramData folder): C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface Iobox{version number} and C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface MiniIobox{version number} Two files are present in this folder: DeviceTypesNoldusChCh.xml and DeviceTypesNoldusEnUs.xml. The first is used with the Chinese version of EthoVision XT, the second with the English version. 10 - User-defined hardware devices The XML file contains all the details of the types of hardware devices that you can control with EthoVision XT with the USB-IO box and the Mini USB-IO box. You can edit this file for small changes in the hardware devices, for example if you want to change the frequency a PhenoWheel counter is read out. You can also define custom devices and create a file DeviceTypesUser.xml. If you do so, make sure the file DeviceTypesUser.xml and DeviceTypesNoldus[language version].xml do not contain settings for the same device. When you create an experiment, EthoVision XT copies these files to your experiment folder, under Configuration Files\Add-ins\Hardware{dll serial number}. The dll serial number depends on the type of USB-IO box and its version. See in Table 3.1 which serial number belongs to which device and version. tip To find out which version of the driver is installed on your computer, see the Programs and Features list on the Control Panel. Every time that you open the experiment, EthoVision XT reads the files in the experiment folder, not the ones in the ProgramData folder, and does not change them. Therefore: If you edit the files in the ProgramData folder, the new device types will be available to all your new experiments. If you edit the files in a specific experiment folder, the new device types will only be available to that experiment. When you make a backup of the experiment, the device type files are also copied, so the new devices can be recognized on other computers where you restore the experiment from the backup. important Always make a backup of the ProgramData folder before you edit the file DeviceTypesNoldus[language version].xml. Table 3.1 The dll serial numbers for the different versions of the USB-IO box and the Mini USB-IO box. Serial Number USB-IO Box Mini USB-IO Box {A8DA8F3E-7EA3-4629-8327-9D21C90FB3ED} {0308106B-1EBE-4620-B00D-396ABEBBC219} {33DF79E0-53C2-44C6-BA2F-A24C4C702615} {F9AAD805-B910-4FEC-AC2F-31DED85324B2} {C183DC50-0CAB-4E67-905E-9D45D8213BD2} {B1336ED5-DE91-4C40-A59D-6A2D131C4F9B} 10 - User-defined hardware devices Undo the changes in the device type files If you want to undo the changes made and return to the original situation, proceed as follows: 1. Close EthoVision XT. 2. Remove or rename the file DeviceTypesUser.xml in the ProgramData folder. 3. Copy the files from the backup of the ProgramData folder to the ProgramData folder. 4. optional Run installation of EthoVision XT and select Repair. Browse to my.noldus.com if you need to download the EthoVision XT installation files. Any experiments that you have created which refer to the user devices can still be analyzed and continued. To remove every trace of your user devices, you must also delete these experiments (and if you made experiment backups, delete these too) by removing them from the Experiments folder. Define A New Device Type important Before making changes to files in the "ProgramData" folder, make a backup of this folder, so you can recover the files if anything goes wrong. The "ProgramData" folder contains other information important to EthoVision XT. If the files in this folder get corrupted or deleted, you can restore EthoVision XT by re-running installation of EthoVision XT and selecting Repair. To define a new device type - Make the necessary changes to the DeviceTypesUser.xml file in the "ProgramData" folder as described below. Use the program XML Notepad that you can download from www.microsoft.com/downloads. to edit a device type file. Other editors could add undesired characters that may not be read in EthoVision XT. - For changes to standard Noldus device types, edit the file DeviceTypesUser.xml. Note: You can in fact make the changes to the file DeviceTypesNoldus[language version].xml {DF396575-4883-47C4-9124-8DE30AE1E4C6} {2EDFF151-DF50-486E-887F-55AD41457A5B} {83BF6F4E-D35B-489A-9F5E-703C4EE9453B} {93C9527C-8B2F-4530-9370-7CA330856D15} 10 - User-defined hardware devices but these changes will be overwritten when EthoVision XT is subsequently re- installed, repaired or a new version installed. - For the other types, also edit file DeviceTypesUser.xml. - Make sure that the file DeviceTypesUser.xml is stored in the appropriate folder under C:\Program Data\Noldus\Components\EthoVision\Noldus HardwareInterface Iobox\5 or C:\Program Data\Noldus\Components\EthoVision\Noldus HardwareInterface Mini Iobox\5 - Start EthoVision XT, create a new experiment and test the devices. - If EthoVision XT crashes, or does not behave as expected: Delete the created (failed) experiments. Make corrections to the file DeviceTypesUser.xml in the ProgramData folder specified above. Go to step 2. - When everything works fine, create a new experiment and use the changed or new device types. note If you use the Quality Assurance module: The change to the device type file is not recorded in the GLP log. Sample File On the download page of EthoVision XT you can download two sample files. 1. Browse to my.noldus.com (you must log in or register first to access this site). 2. Choose Downloads > EthoVision XT. Download EthoVision XT - Full installation disc [version number]. Unzip the file and locate the folder Drivers ant Tools > IoBox MiniIoBox Devices. There you find the file User defined device types.zip. 3. Unzip the file User defined device types.zip and save the files on your computer. DeviceTypesUser - Example.xml (see below). DeviceTypesUser Pheno Wheel (30).xml (see page 161). 10 - User-defined hardware devices DeviceTypesUser - Example.xml The file DeviceTypeUser - Example.xml specifies several devices. Figure 41 Part of the sample file DeviceTypeUser-Example.xml. The top part specifies the PhenoTyper White spot commands. 10 - User-defined hardware devices DeviceTypesUser - Example.xml (continued) Figure 42 Part of the sample file DeviceTypeUser - Example.xml. The bottom part specifies the counter of the RunningWheel. 10 - User-defined hardware devices DeviceTypesUser Pheno Wheel (30).xml For a running wheel, with reading interval of 30 s instead of 60 s as in the standard Noldus running wheel, you need a file like this: Rename the file to DeviceTypesUser.xml. Figure 43 An XML file that specifies a device type for a running wheel with reading interval of 30 s instead of 60. Note the device type ID (10006), name (PhenoWheel (30)) and the custom sample frequency (30). 10 - User-defined hardware devices When you restart EthoVision XT, the new device types are then shown, for example in the Arena-Hardware Mapping window that you access in the Arena Settings. Predefined Ids For both devices and connectors, IDs must be unique. IDs from 0 to 9999 are for Noldus device (and connector) types. IDs above 10000 are reserved for device (and connector) types that you may want to add. If you create a device type based on a Noldus device type (for example a Lickometer), always use an ID above 10000. Figure 44 Arena-Hardware Mapping window showing the new device type PhenoWheel (30) in the first column of the table. Device type ID Name Top Unit (Standard) Top Unit (Neuro-Bsik) Pellet Dispenser (PTPD-001x) Lickometer (PTLM-001x) TTL Port Tester (PTTB-001x) Custom Hardware PhenoWheel 10 - User-defined hardware devices Xml File Entries Not all of the entries below always apply to each signal, command, etc. If you make edits in a device type file, beware that besides editing the data below you might have to change some numbers that the boost::serialize normally creates itself (vector counts, for example). NCHiIobConnectorTypes Devices can be connected to the USB IO box (or mini IO box) via a connector. There can be more than one connector type in the setup. Following are the properties of the collection of connectors (m_vecConnectorType): Following are properties of each connector: NCHiIobConnectorType USB-IO box monitor Beam Controller (PTBC-0010) Activity Wheel Counter (ENV-042) Activity Wheel Brake (ENV-042) Backlight Unit White Light Top Unit Tester (PTTB-002x) Pellet Receptacle (PTPR-001x) Connector type ID Connector type name Top Unit Interface (PTTI-001x). Note that the Top Unit Standard and Special both use this type of connector. Count Indicates the number of connectors Item_version Indicates the version of the connectors HiIob::ConnectorTypeId m_iId Every connector type must have a unique id. g_ConnectorTypeIdInvalid(-1l): invalid value Item_version Indicates the version of the connectors nstring m_strName name of the connector 10 - User-defined hardware devices NCHiIobDeviceTypes Devices can be connected to the USB-IO box directly (e.g., not via a connector). Following are the properties of the collection of device types (m_vecDeviceType): Following are properties of each device type: NCHiIobDeviceType HiIob::ePortTypes m_ePortType ePrtUndefined(-1): undefined ePrtSD(0): simple device port ePrtCD(1): complex device port int m_iNrPorts number of ports used by the connector int m_iOffsetPin pin offset for the device connected via the connector Count Indicates the number of device types Item_version Indicates the version of the device types HiIob::DeviceTypeId m_iDeviceTypeId Every device type must have a unique id. g_DeviceTypeIdInvalid(-1l): invalid value nstring m_strDeviceTypeName name of device type, showing up in the UI of port- device mapping dialog (hwdll) and various places in EthoVision XT (for example: ATC, test dialog, etc). int m_MaxFrequency Most device types are read every read cycle and have m_MaxFrequency = 0. So called "slow device types" (e.g., Lickometer) are not read every read cycle but with the slower frequency MaxFrequency (in seconds). Use integer values only. HiIob::ePortTypes m_ePortType ePrtUndefined(-1): undefined ePrtSD(0): simple device port ePrtCD(1): complex device port HiIob::ConnectorTypeId m_iConnectorTypeId Every connector type must have a unique id. Most device types do not use a connector and have value. g_ConnectorTypeIdInvalid(-11): invalid value Currently the only connector type is the top unit connector, used with the top unit. 10 - User-defined hardware devices NCHiIobSignal Each device type can have more than one signals. Following are the properties of the collection of signals (m_vecSignal): Following are properties of each signal: Count Indicates the number of signals Item_version Indicates the version of the device type signals HiIob::SignalId m_iId Every signal must have a unique (within device type) id. g_SignalIdInvalid(-11): invalid value nstring m_strName Name of signal, showing up in the interface of Device configuration window and other places, for example: The test window in Trial Control). HiIob::eSignalSource m_eSignalSource eSrcUndefined(-1): undefined eSrcInput(0): signal comes from the hardware eSrcOutput(1): signal is created in the software and is related to an output state. E.g.: there are outputs "White spot off" and "White spot on", for these outputs "Is white spot on" is a output state that is treated as an (artificial, because not coming from the hardware) input. HiIob::eSignalHwType m_eSignalHwType eShtUndefined(-1): undefined eShtPin(0): uses pins (most device types) eShtBytes(1): uses direct bytes reading (e.g.: lickometer) long m_iPin the pin used by the signal. Only relevant if eSignalHwType = eShtPin. int m_iNrBytes the number of bytes used for reading the signal. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. int m_iIndexFirstByte least significant byte. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. int m_iIndexLastByte most significant byte. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. 10 - User-defined hardware devices HiIob::eStateEventType m_eStateEventType eSetUndefined(-1): undefined eSetL(0): signal is based on Low state eSetH(1): signal is based on High state eSetL2H(2): signal is based on transitions from Low to High eSetH2L(3): signal is based on transitions from High to Low Only relevant if eSignalHwType = eShtPin bool m_bHighInit initial value for the signal. True if High, false if Low. Only relevant if m_eSignalSource = eSrcInput and eSignalHwType = eShtPin. bool m_bTotalsSinceLastCall true if signal returns a value (via the hwdll COM interface) that represents a total since the last call. EAdinsIdtHiValueType m_eValueType The type of the value the signal returns (via the hwdll COM interface) One of the values: eAdinsIdtHiVtUndefined(-1) eAdinsIdtHiVtBool(0) eAdinsIdtHiVtLongLong(1)eAdinsIdtHiVtDouble(2) eAdinsIdtHiVtDuration(3) This value is used by EthoVision XT: Trial Control and logging bool m_bHasValueDefault true if the signal has a default value. Indicates how the value of the signal has to be treated by the EXPORTED hardware log in VTS: If true: only the values not equal to the default value are logged If false: only changes in the values are logged (default value is not used) NCHiIobValue m_valueDefault Default value for the signal. Only relevant if m_bHasValueDefault = true; HiIob::eValueType m_eTypeValueDefault Default value type for the signal (see m_eValueType) for the values. 10 - User-defined hardware devices NCHiIobCommand Each device type can have more than one commands. Following are the properties of the collection of commands (m_vecCommand): Following are properties of each command: bool m_bValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtBool. LONGLONG m_lValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtLongLong. double m_dbValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtDouble. Count Indicates the number of commands Item_version Indicates the version of the device type commands HiIob::CommandId m_iId Every command must have a unique (within device type) id. g_CommandIdInvalid(-11): invalid value nstring m_strName name of command, showing up in the UI of port- device mapping dialog (hwdll) and various places in EthoVision XT (for example: Trial Control boxes, test dialog, etc). bool m_bIsDefaultCommand true if command is default command. Default commands are called before start sampler (start of a trial) and after stop sampler (end of a trial). long m_iPin the pin used by the command (if any). bool m_bHigh true if command corresponds to a High bit value, true if command corresponds to a Low bit value int m_iDuration duration in milliseconds. After writing this command a new command is scheduled to be written the given duration time later (only if duration > 0). If the original command was High, the scheduled command is Low and vice versa. Used for the pellet feeder to reset. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 11 Analysis of Trial Control data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-11-analysis-of-trial-control-data Chapter: EthoVision XT 11 - Analysis of Trial Control data Analysis Of Trial Control Data What Do You Want To Do? Trial Control data are analyzed as Dependent variables. Choose your dependent variables in the Analysis Profile. Analyze events that occurred during the trial How many times a condition became true? How many times the food reward was given? What is the latency of the first reward? To answer these questions, we consider the events associated with single Trial Control boxes. See trial control events on page 170. Analyze the time defined by two events How much time elapsed from the moment the cue light switched on to when the subject entered the reward zone? See trial control states page 172 A special case in this category is the analysis of learning. Did the time between the event Light on and the event Subject in reward zone decrease during the test? See page 176 Analyze the data within the time between two events How many times a certain behavior occurred when the stimulus light was on? What was the speed of the subject between event A and event B? To answer such questions, use the Nest function to define the time segments within which the event or behavior of interest occurred. See data within trial control states on page 177. Analyze Trial Control variables (e.g. counters) A Trial Control variable (for details see page 28) has been defined in the Trial Control procedure. Its value is increased every time the subject makes a correct choice. To analyze the performance of the subjects, we calculate the maximum value of the variable, and visualize when the maximum value occurred. See trial control variables on page 178. Analyze the commands sent to the hardware devices How many times did EthoVision XT send a command to a pellet dispenser to drop one pellet? hardware command on See page 178. 11 - Analysis of Trial Control data Analyze variables associated with hardware devices For example, analyze the data from the Lickometer. For hardware devices, there are continuous variable and state variables. See hardware continuous variable on page 179 and hardware state variable on page 181. Notes For more general information on analysis variables, see Dependent variables in the EthoVision XT Help. To visualize Trial Control data, from the Analyze menu, select Results and then Plot Integrated Data (see the EthoVision XT Help). You find an example of visualization of Trial Control data on page 42. To export Trial Control data, see page 185. Trial statistics of Duration and Latency can only be a multiple of the sample interval (=1/ sample rate). For example, a condition like Subject in zone A for >= 3 s is met when the time elapsed from its activation exceeds 3 s. If the sample rate is 12.5 frames/s (thus the sample interval is 1/12.5= 0.08 s), the condition is met at the first multiple of 0.08 greater than 3 s, that is 3.04 s. For this reason, the latency of the event Condition becomes true is 3.04 s. 11 - Analysis of Trial Control data Trial Control Events If you are interested in the rate of events like the number of times the lever was pressed, or the number of pellets dropped, or the latency of an action, use the Trial Control event function in the Analysis profile. 1. In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. 2. In the Dependent Variables pane, under Trial Control, double-click Trial Control event or drag it to the middle of the screen, or click the button next to it. 3. The Trial Control event window appears. Under Event, from the Element list select the element to be analyzed. For example, if you want to analyze the hardware-base action "Drop pellet" locate this among Action: Drop pellet and select it. 4. From the Event list, select the event for the element selected. The options available depend on what you have chosen as Element (see Possible states of Trial Control elements on page 171). 5. Click the Trial Statistics tab and select the statistic you want to analyze. 6. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. 7. Click Add. The new Trial Control event appears in the list of Selected Dependent Variables. 8. Choose the option you require: To calculate statistics of the selected events, choose Analyze > Results > Statistics & Charts. (see Calculate Statistics in the EthoVision XT Help). To visualize the events, choose Analysis > Results > Plot Integrated Data (see Visualize Data in the EthoVision XT Help). Notes If one or more other instances of Trial Control event are listed under Selected Dependent Variables in the main window, the Trial Control event name is followed by a progressive number (1, 2, 3...). The Element list contains the Trial Control elements defined in all your Trial Control Settings. For each element, the list shows the name of the corresponding Trial Control box. Choose Latency to first to analyze the time of the first instance of the event defined since the start of tracking. Choose Latency to last to analyze the time from the start of data recording to the last instance of the event defined. 11 - Analysis of Trial Control data For calculating frequency and latency of the subject's behavior, choose the appropriate Dependent Variable (see Dependent variables in detail in the EthoVision XT Help). Possible events of Trial Control elements Becomes active (for Start-stop trial rule begin, sub-rule begin, conditions, actions, references and operators). Marks the time that the trial starts (for the Start-stop trial rule begin) or the element becomes active (in all other cases). This is the time when control passes from the previous box in the Trial Control sequence. See the Notes below for the difference between Becomes active and Becomes true. Becomes true (for conditions and operators). Marks the time that a condition is met. Choose this option for example to analyze the instances when the condition In zone A was met. Becomes false (for conditions and operators). Marks the time that a condition is not met. Choose this option for example to analyze the instances when the condition In zone A was not met. Becomes inactive (for Start-stop trial rule end, sub-rule end, conditions, actions, references and operators). Marks the time that the element becomes inactive, that is, when control passes to the next box in the Trial Control sequence. In practice, this is the time a condition becomes true or an action is taken. For the Start-Stop trial rule end, this is the time that the trial stops. Makes sub-rule active (for sub-rule references). Marks the time that a reference to a sub- rule triggers the sub-rule. This is the time that one of the Start conditions set in the Reference box (see page 60) becomes true. Makes sub-rule inactive (for sub-rule references). Marks the time that the last repeat of a sub-rule planned for a specific Start condition is completed. Notes For a condition like Is the subject in zone A?, choose Becomes true to consider the moment when the condition is met. Choose Becomes inactive when you want to consider the time that a condition could be met (no matter whether or not the subject is in zone A). Becomes active/inactive are especially used when analyzing intervals (see below). 11 - Analysis of Trial Control data Trial Control States If you are interested in the time interval between two events, for example from the Action "cue light on" to the Condition "subject on shelter" being met, use the Trial Control state function in the Analysis profile. 1. In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. 2. In the Dependent Variables pane, under Trial Control, click Trial Control state or drag it to the middle of the screen, or click the button next to it. The Trial Control State window appears (see below). 3. Next to From, from the Element list select the Trial Control element that makes the criterion for the start of the interval. From the Event list, select the event that makes the start of the interval (see the previous page for information on the events available for a specific element). 4. Next to To, from the Element list select the Trial Control element that makes the criterion for the end of the interval. From the Event list, select the event that makes the end of the interval. The event that marks the end of the interval may occur multiple times. Therefore, choose which occurrence (from 1th to 9th) should be used. 1th is the first occurrence of the event selected under To available after each occurrence of the event selected under From. See an example in Figure 46. Figure 45 The Trial Control State window. 11 - Analysis of Trial Control data 5. Select Ignore last interval if incomplete to ignore the interval when the Trial Control event that defines the end of the state is not found. If you do not select this option, and the end criterion is not met, EthoVision XT defines an interval up to the end of the track. 6. An interval may occur several times in a trial. If your want to have statistics for each occurrence, select the Calculate statistics per interval option. Next to For consecutive intervals, choose the range of occurrences of the intervals you want to have in the results. example If the interval from Light On (cue) to Mouse on Shelter (response) occurs 10 times and you want to have the first four occurrences displayed in your table, select 1 to 4. If you want to have all occurrences displayed, select 1 to 10. If you do not know exactly how many instances of the state interval the tracks contain, enter a number reasonably high (for example 50 or 100) so you make sure analysis is carried out on all instances. note If you do not select this option, the multiple occurrences are considered as one interval. Click the Trial Statistics tab and select the statistic you want to analyze. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Click Add. The new Trial Control state appears in the list of Selected Dependent Variables. Figure 46 An example of time intervals defined with in Trial Control data. In a conditioning test, it is required to teach the subject to sit on the shelter after a cue stimulus is given, in order to get a reward. An interval is defined from when the cue light switches on to when the subject is found on top of the shelter. Solid bars represent the time that the subject is on the shelter (condition met). A - Interval from "Cue light On" to 1st occurrence of "subject on shelter", B - Interval from "Cue light On" to 2nd occurrence of "subject on shelter". 11 - Analysis of Trial Control data 7. Choose the option you require: To calculate statistics of the selected intervals, from the Analysis menu, select Results and then Statistics & Charts. The analysis window that appears has the tab Trial Statistics for the analysis results per trial and Group Statistics for the statistics and charts from the summarized results over different trials. If you have different filters, data profiles, or analysis profiles make your selection on the toolbar. Click Calculate. (see Calculate Statistics in the EthoVision XT Help). To visualize the intervals, choose Analyze > Results > Plot Integrated Data (see Plot integrated data in the EthoVision XT Help). Notes If one or more other instances of Trial Control state are listed under Selected Dependent Variables in the main window, the Trial Control state name is followed by a progressive number (1, 2, 3...). We advise you to rename the trial control state (right-click the name and select Rename). The Element list contains the Trial Control elements defined in all your Trial Control Settings. For each element, the list shows the Name of the corresponding Trial Control box. Choose Becomes active instead of Becomes true when you want the interval to be based on a condition from the moment it could have been met, no matter when it was met actually. See example 1 on page 176. If you define an interval by choosing the same event under From and To, the instance of the event marking the end of the interval is not used as a starting point for the next occurrence of the interval. For example, you have a sequence of four actions of the same type: A1, ..., A2, ..., A3, ..., A4. Selecting a trial control state From A To A results in analyzing the time between A1 and A2, and between A3 and A4. For Trial Control states based on Conditions: The sample time at which a Trial Control state starts (or ends) also depends on the statistic used in the condition in the Trial Control rule. - If you use Current to define the condition (for example, "when Current In zone= true"), the Trial Control state starts (or stops) at the expected sample time. For example, when the animal actually enters the zone (and thus Current= true for that sample). - If you use any other statistic to define the condition (for example, "when Frequency of In zone >= 1): When the condition becomes true after the condition box is activated (see Figure 3 on page 11 for an explanation of the terms true and active), the Trial Control State starts (or stops) at the expected sample time (see A in Figure 47). 11 - Analysis of Trial Control data When the condition is already true when the condition box is activated (for example, a condition "Frequency of In zone =1" is activated when the animal is already in the zone), such statistic is only evaluated at the next sample (or in the second next sample, in the case of Heading). In that case, the Trial Control state starts (or stops) one sample (or two) later than expected from the condition (see B in Figure 47). However, for the consecutive frequencies of In zone =2, 3, etc, the condition is already active by definition; therefore the Trial Control State starts at the expected time, when the condition becomes true. Figure 47 In this example, a Trial Control condition has been defined in the Trial Control Settings, which checks that the Frequency of In zone is >=1 for the Center of the open field. A Trial Control state has been defined in the Analysis profile, which starts when the condition "Frequency of In zone >=1" is true. A1 - The animal enters the Center zone (and therefore the condition becomes true) after the condition is activated. The Frequency statistic is evaluated at the same sample time. A2 - Plot of the variables "In zone" for the Center and the Trial Control state. The Trial Control state starts at the expected sample time, that is, when the animal actually enters the zone. B1 - The animal is already in the zone when the condition is activated. Therefore, the condition becomes true at the same time that it is activated, but the Frequency statistic is evaluated at the next sample (here, sample rate = 5/s, thus after 0.2 s). B2 - Same plot as A2; Here, the Trial Control state starts o.2 s after the In zone state. 11 - Analysis of Trial Control data If you de-select Calculate statistics per interval, the Cumulative duration statistic is the total duration of the intervals in that trial. If you want to know how many occurrences of the intervals a specific trial contains, follow the procedure above making sure that Calculate statistics per interval is not selected, and Frequency is selected under Trial Statistics. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Next, run the analysis. The table shows the number of intervals under Frequency for that dependent variable. The occurrences are counted if the From condition is met. If the trial ends before the To condition is met, the interval is still counted in the Frequency. Examples of Trial Control states example 1 In a conditioning test, it is required that the subject must go to zone A in order to receive a reward. The researcher wants to know the time from the moment the subject could have responded (Condition Subject in zone A becomes active) to the moment the subject eats the reward (Condition Subject in feeder zone becomes true). The Trial Control sequence is as follows: Rule Begin Condition - In zone A Action - Drop a food item Condition - In Feeder zone Rule End. In the Analysis profile, click Trial Control state and select: From - Element Condition: In Zone A, Event= becomes active, To - 1st occurrence of Element Condition: In Feeder zone, Event= becomes true. In the Trial Statistics tab, make sure that Cumulative duration is selected. example 2 In a variant of the experiment above, the researcher wants to know the time that it takes the mouse to get the pellet after being in the zone A. Here we assume that if the animal enters zone A, then gets out and subsequently gets back in it before collecting the food item, one wants to analyze from the first instance that the mouse went in zone A. In the Analysis Profile, click Trial Control state and select: From - Element Condition: In Shelter zone, Event= becomes true (because one wants to analyze the time from when the condition is met). To - 1st occurrence of Element Condition: In Feeder zone, Event= becomes true. In the Trial Statistics tab, make sure that Cumulative duration is selected. Analyze learning behavior When a sequence like Cue stimulus Subject's action Reward is repeated a number of times, you may want to know whether there is a trend of decreasing/increasing duration of 11 - Analysis of Trial Control data intervals from one component of the sequence to the next. For example, is the time from the cue stimulus to the subject's lever press decreasing during a 30-minutes test? To analyze learning behavior, follow the procedure on page 172, and make sure that: In the Trial Control State Interval tab, select the Calculate statistics per interval option. Next to For consecutive intervals, select which occurrences of the interval you want to analyze. In the Trial Statistics tab, make sure that Cumulative duration is selected. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Calculate the statistics, and export the results (see Calculate Statistics in the EthoVision XT Help). Data Within Trial Control States If you want to calculate statistics on or visualize data within intervals defined by Trial Control events, then you must first define those intervals as Nesting intervals in the Data Profile. 1. In the Experiment Explorer, right-click Data Profiles and select New, or click one of the existing profiles. 2. In the Components pane, under Nesting, double-click Trial Control state or drag it to the middle of the screen, or click the button next to it. 3. The Trial Control state window appears. Define the interval as described in steps 3 to 5 of the procedure on page 172 (the options are the same, only the Statistics tab is not present). 4. Click OK. The Nest box appears on the screen. Insert this box between the Start and the Result box. 5. In the Experiment Explorer, right-click Analysis Profiles and select New, or click one of the existing profiles. 6. Define the dependent variables you want to analyze and run analysis or visualize the data. Notes If the interval specified in step 3 above occurs in multiple instances, the program considers the total time line included in those intervals to calculate durations, frequencies etc. If your experiment includes multiple subjects per arena, the Nesting over Subjects group of options is also available. Select Trial Control state under Nesting over Subjects if you want to define an interval based on what one or more of the subjects do during the trial. 11 - Analysis of Trial Control data For example, to define an interval that goes from the action "Cue light on" when activated, to the condition "Subject 1 in zone A" when it becomes true. Click the Actors tab and select the subject that the condition refers to. Analysis will be done for all the subjects, in the interval defined by Subject 1. Note that conditions can be met by specific subjects, while actions cannot be triggered by specific subjects. However, they can be triggered indirectly, when an action follows a condition met by that subject. For information on Nesting, see Analyze Track Segments in the EthoVision XT Help. Trial Control Variables You can analyze and visualize the values of the Trial Control variables defined in the Trial Control Settings. Use this function also for testing purposes. For example, to check that a Trial Control variable receives the value expected at a specific time. 1. In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. 2. Click the Add button next to Trial Control variable and choose a variable from the list. 3. Calculate the statistics or plot the variable with the Integrated Visualization. For more information, see the EthoVision XT Help. Hardware Command A Hardware command is a command given by the EthoVision software to your hardware device. You can define when and what hardware commands are sent as Actions in your Trial Control settings. For instance, you can have EthoVision send a command to your pellet dispenser to drop a pellet after the mouse has been detected in the Trigger zone. For more information about programming Trial Control see Chapter 3. How to add a Hardware command to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware command. 11 - Analysis of Trial Control data The Hardware command window opens. - From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze how many Drop pellet commands EthoVision gave to your pellet dispenser, select Pellet Dispenser (PTPD-001x). - In the Device list, the name of the hardware device will appear as you defined it when you assigned the device to the arena (see page 113). - From the Command list, select which command you want to analyze. For instance, for the Phenotyper's Top Unit, you can select White spot on, White spot off, Yellow light on, Yellow light off, Sound on or Sound off. For other hardware devices (Pellet Dispenser, Lickometer) there is only one option. - Click the Trial Statistics tab to choose the statistics for the dependent variable. Next, click Add. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. See Calculate Statistics in the EthoVision XT Help details. Application By selecting Hardware command as Dependent Variable, you can calculate the frequency of the commands the EthoVision software gives to your hardware device. In addition, you can calculate the latency to the first command and the latency to the last. You can also visualize Hardware commands. This enables you to check whether your Trial Control settings do what you expect them to do. For example, visualize the Hardware command Drop pellet for your pellet dispenser and plot it in the integrated visualization together with the video to check how often the command was given and when. Hardware commands appear as Point events in your plot, that is, as events with no duration (see the upper panel in Figure 48 for an example). Hardware Continuous Variable After EthoVision XT has started tracking, connected hardware devices start sending signals to the EthoVision computer. You can analyze these signals by adding Hardware continuous variables to your analysis profile. You can calculate/ visualize, for instance, the number of pellets dropped by your pellet dispenser (see Figure 48 for an example) or the duration of licks at the lickometer. How to add a Hardware continuous variable to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware continuous. 11 - Analysis of Trial Control data - The Hardware continuous variable window opens. From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze how many pellets your pellet dispenser dropped, select Pellet Dispenser (PTPD-001x). - In the Device list the name of the hardware device will appear as you defined it when you assigned the device to the arena (see page 113). - From the Signal list, select which signal you want to analyze. For instance, for the pellet dispenser you can select Number of drops. - Click the Trial Statistics tab to choose the statistics for the dependent variable. If you want summarized statistics over all trials, or the groups of trials defined in your Data Profile, click the Group Statistics tab and select additional statistics. Next, click Add. For details, see Calculate Statistics in the EthoVision XT Help. An example of a visualization of a hardware continuous variable is shown below. Application By selecting Hardware continuous variable as Dependent Variable, you can calculate, for instance, how many pellets your pellet dispenser dropped or how long your mouse has been drinking from its water bottle. You can also calculate the frequency drinking from the bottle took place. But often many of these drinking occurrences together form a single drinking bout. Analyzing such bouts is not possible in the current version of EthoVision XT. This means that to calculate how often such bouts occurred, you have to export the data to a Hardware log and analyze this in an external program like Excel. Note Devices such as the Lickometer and PhenoWheel send data to EthoVision XT at fixed times, every two seconds for the Lickometer and every 60 seconds for PhenoWheel. At each sample time, EthoVision XT reads the data since the last reading event: For the Lickometer, number and duration of licks. 11 - Analysis of Trial Control data For PhenoWheel: number of rotations. The reading events are not in sync with the trial start and stop. This means that (see the figure below for an example with the Lickometer): The data of the first reading event after the trial start also include some time before the trial start (< 2 s for Lickometer, < 60 s for PhenoWheel). This time is included in the results (figure below, left). The data between the last reading event and the stop of the trial are not included in the results (figure below, right). This time is again < 2 s for Lickometer, < 60 s for PhenoWheel, depending on when the trial stopped. In most cases the two discrepancies have no effect on your data when the trial lasts at least a few minutes or hours, like in typical PhenoTyper tests. tip If you want the devices to have another sampling rate, contact Noldus. Hardware State Variable A variable based on a Hardware continuous variable. You can, for example, define a Hardware state variable Number of dropped pellets is equal to or greater than 1 and calculate, for instance, the duration of this interval. 11 - Analysis of Trial Control data How to add a Hardware state variable to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware state. - The Hardware state variable window opens. From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze the signal from your pellet dispenser, select Pellet Dispenser (PTPD-001x). - In the Device list the name of the hardware device will appear as you defined it when you assigned the device to the arena (see page 113). - From the Signal list, select which signal you want to analyze. For instance, for the pellet dispenser you can select Number of drops or In error state. - Set the appropriate Value (threshold) or select the value you are interested in. For instance, for Number of drops set a threshold of equal to or greater than 1, for In error state select true of false. Cumulative value. Select this option to calculate/visualize the cumulative value of the signal. See Figure 48 for an example of the effect of selecting this option. - Click the Trial Statistics tab to choose the statistics for the dependent variable. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Next, click Add. For details, see Calculate Statistics in the EthoVision XT Help. 11 - Analysis of Trial Control data Application You can use Hardware state variables to analyze, for instance, how long a light was on. You can also use Hardware state variables to analyze learning behavior. For instance, when training an animal you may want to know how long it takes before it completes a task (and receives a food pellet). For this purpose, you can calculate the statistic 'Latency to first' for the Hardware state variable 'Number of drops greater than or equal to 1'. For naive animals the latency will be high at the start of the training and will decrease as the animals learn the task in subsequent trials. Please note that the following question requires a different procedure: What was the average time between "light on" and "lever press" in a learning experiment? It is not possible to define a variable based on two separate hardware events. To answer this question, define a Free interval using hardware events. For more information, see Free interval in the EthoVision XT Help. Figure 48 From top to bottom: Integrated visualization of four Dependent Variables 'Hardware command', 'Hardware continuous variable', 'Hardware state variable' with the option 'cumulative value' selected and 'Hardware state variable' with the option 'cumulative value' not selected. In this learning experiment a rat received a pellet when it climbed on top of its shelter. The rat did this two times and EthoVision two times gave a command to the pellet dispenser to drop a pellet (see the plot at the top). The pellet dispenser dropped a pellet after each command and sent a signal to the EthoVision software (two times) (second plot). For plots 3 and 4, the state variable 'Number of drops is equal to or greater than 1' is visualized. In plot 3 the option 'cumulative value' was selected, in panel 4 this option was not selected. The duration of one occurrence of the state variable in panel 4 is one sample (0.04 seconds if the sample rate is 25 frames/ second). 11 - Analysis of Trial Control data Free Intervals Based On Trial Control And Hardware Data Free intervals are the most flexible solution to analyze slices of time which go from an event, or time, to another event or time. You can use them in the Analysis profile and in the Data profile. example In a DanioVision experiment, analyze the speed of the subjects in the 5-s time interval before the onset of the light stimulus; and in a second interval, in the 5-s time interval after the onset of the light stimulus. Because you want to analyze the speed within the intervals, define those intervals Free intervals in the Data profile. How to add a Free interval to an Analysis profile In the Analysis profile, under Custom Variables, click the Add button next to Free interval. For more information, see Dependent variables in Detail > Custom Variables in the EthoVision XT Help. How to add a Free interval to a Data profile In the Data profile, under Nesting, click the Add button next to Free interval. For more information, see Analyze Track Segments > Nesting over a free interval in the EthoVision XT Help. The Analysis Results To calculate the statistics - Click Statistics & Charts in the Project Explorer. The analysis window that appears has the tab Trial Statistics for the analysis results per trial and Group Statistics & Charts with statistics and charts from the summarized results over different trials. - If you have different filters, data profiles, or analysis profiles make your selection on the toolbar. - Click Calculate. - optional Click the Layout button to modify the layout of the results table. Batch analysis To run different analyses with different combinations of these filters, do the following: 1. Click Batch. 2. Select the profiles from the lists and click Add. 11 - Analysis of Trial Control data 3. Repeat step 2 for other combinations. 4. Click Calculate. 5. Select the combination of profiles from the lists on the toolbar to view the results. Export Trial Control Data You can export Trial Control data just like the other dependent variables. 1. Choose Analysis > Export > Raw Data. 2. Select the following: Track & dependent variables. To export events and intervals defined in the Analysis profile. For example, actions and conditions and intervals in between (see page 168). This option also includes hardware-based actions and conditions, not the actual communication signals. Hardware log. To export the communication signals between EthoVision XT and the hardware device (see below). 3. Click Start Export. Exported raw data file In the exported raw data file, each Trial Control event or Trial Control state defined in the Analysis Profile is stored in a column. A Trial Control event is exported as 1 (one) in the row corresponding to the time when the event occurs. In the other rows, it is exported as 0 (zero). Figure 49 An example of Track data export file that includes a Trial Control event "Drop pellet" and a Trial Control state "From Light On to Drop Pellet". The arrows mark the event and the start/stop of the state. To export such data, define them first in the Analysis profile. For clarity, other columns have been hidden. 11 - Analysis of Trial Control data A Trial Control state interval is exported as 1 (one) in the rows corresponding to the time included in the interval. If the interval occurs in multiple instances during the trial, you will see multiple segments of 1. For more information about exporting track data, see Export tracks in the EthoVision XT Help. Hardware log file When you select Hardware log in the export screen, hardware events are exported to a separate file. The data are organized in columns as follows (see Figure 50): Time is the time when the signal value is read or the action is taken. Note: This is the time elapsed since the start of the trial, not the start of tracking (see a note below). For lickometers, values are updated about every 2 s. Device ID is the name of the physical device that the event refers to. Command/Signal is the type of data (Command, or Signal). Name is the name of the command or signal. Value is the value of the signal at that time. Each row of the file contains one of the two: Rows marked with Signal. The value of the signal since the last time the device was read (for example, the number of licks or the duration of licks since the last reading). Duration of licks is expressed in milliseconds. Rows marked with Command. The command (for example, Drop pellet). The hardware log file is one per trial, no matter how many arenas and devices are used. If you re-do a trial, the log files recorded with the previous instance of the trial are deleted. In order to be logged, hardware devices must be connected to the computer and configured in EthoVision XT (see page 109). Notice that the Time in the Hardware log file is the time since the start of the trial, while the time in the Track data file is the time since the start of tracking (see page 49). example If you have defined a command like Drop pellet as a Trial control event (see page 168), to find a specific Drop pellet event in the data file, take note of the Time in the Hardware log file for that event and locate that time in the Time trial column in the Track data file. For Pellet dispensers. Number of drops is the feedback signal sent by the device to EthoVision. Usually it is recorded 0.04 s after the actual Drop pellet command. 11 - Analysis of Trial Control data Choose Hardware log if you want to export communication data between EthoVision and the hardware device, even when the device was not used during the trial. If you select both Track data and Hardware log, data are exported in separate files when choosing the Text format, and in one file when choosing the Excel format. In the Excel file, Track data and Hardware log data are in stored in separate sheets. Figure 50 An example of Hardware log export file for an experiment with two pellet dispensers. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 12 Apply different protocols to different arenas URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-12-apply-different-protocols-to-different-arenas Chapter: EthoVision XT 12 - Apply different protocols to different arenas Apply Different Protocols To Different Arenas Introduction This document is intended for EthoVision users who record data in with multiple arenas simultaneously, and want to apply different Trial Control protocols to different arenas. example The camera points at two separate arenas, each with one animal. In arena 1, provide a foot shock 30 seconds from the start of the trial. In arena 2, provide a foot shock at a randomly chosen time between 0 and 90 seconds from the start. Multiple arenas in your EthoVision experiment If you work with multiple arenas within an experiment, each arena is treated as an independent replicate. In most cases, you want to apply the same Trial Control protocol to all the arenas. Imagine that you create a Trial Control protocol that stop tracking when the subject has moved a certain distance. You define one Trial Control Settings profile and apply that profile for your trial. Because subjects differ in their behavior, tracking will stop at different times for each of those arenas. That is because EthoVision XT uses multiple copies of the same Trial Control Settings, one for each arena. Figure 51 Four arenas in the same camera view. Each arena is an independent replicate. The protocol defined in the Trial Control Settings is applied to each arena independently. 12 - Apply different protocols to different arenas Same protocol, but independent processes The Trial Control Settings are applied to each arena independently. Suppose that the protocol is "After starting the trial, switch on a light when the animal enters the zone named Food zone". A light device has been installed on top of both arenas, and a zone named "Food zone" has been defined in the Arena Settings for both arenas. If the animal in Arena 1 enters its Food zone, the corresponding light will be switched on. However, the light on top of Arena 2 won't be activated, unless the animal in Arena 2 enters its own Food zone too (see Figure 53). Although the protocol is the same, it is applied in two copies, one for each arena. This can be represented on a time line: To implement this, select the different physical devices (Light 1 for Arena 1, Light 2 for Arena 2 etc.) on the same line in the Arena - Hardware Mapping window (Arena Settings). This way Figure 52 A simple trial control protocol. When the center point of the subject is detected in the "Food zone", EthoVision sends a command to switch on a light in that arena. Figure 53 Time line of a trial with the same trial control protocol active in two arenas. The circle represents the Food zone. 12 - Apply different protocols to different arenas different arenas refer to the same generic Device name (e.g. "Light"). This "generic" name is then used in the instructions of the Trial Control protocol. Another typical example is the PhenoTyper setup, where the same protocol is applied to a group of 4 or more cages. Conditions and actions are processed independently for each cage. But what if Arena 2 needs a completely different protocol than Arena 1? See the next section. Different protocols in different arenas In some cases two or more arenas may need different protocols. For example, your camera view includes three arenas. In Arena 1, a light (Light 1) is switched on at a specific time, for example at one minute after start. In Arena 2, the light (Light 2) is switched on at a moment randomly chosen between 30 s and 2 minutes (because this event is randomly based, it will differ among the animals tested in Arena 2). Arena 3 is then used as a control, with no light stimuli presented. For all arenas, the trial lasts 3 minutes. If we based the Trial Control procedure on an Arena - Hardware Mapping like the one in Figure 54, the two light devices Light 1 and Light 2 would be represented by the same Device name. When using this name in a Trial Control instruction, for example "switch a light using the Device name = Light), that instruction would be executed for both arenas. As a result, the light would be switched on in both arenas twice, one at 1 minute, and a second at a random time between 30 s and 2 minutes. Also if the action is depending on the animal's behavior (for example, "Switch on the light when the animal is in the Food zone"), this command would be executed in both arenas, producing obviously false results. The solution to this problem is to map devices in a different way, by specifying one physical device in each row in the Arena - Hardware Mapping window. Figure 54 In order for the same protocol to be applied to different arenas, the different physical devices specified under Arena 1 and Arena 2 (see the arrows) must refer to the same Device name (e.g. Light). 12 - Apply different protocols to different arenas Simple Case: Two Arenas To illustrate the concept, we assume that we work with two arenas, and one animal in each arena. The animals are subject to two different treatment protocols. Experiment Settings - Connect all hardware devices to the EthoVision XT computer, via the appropriate port in the Noldus USB-IO box. - In the Experiment Settings, under Trial Control Hardware click Settings. - Choose Noldus USB-IO box. - In the Device Configuration window, assign a hardware device to a port of the USB IO box (or Mini USB IO box), as you normally do. Here Device ID is the name of each physical device. For example, Light 1 will be installed in Arena 1, Light 2 in Arena 2, etc. Figure 55 Schematic representation of the treatments in two arenas. 12 - Apply different protocols to different arenas Arena Settings - In the Arena Settings, define and calibrate the arenas as usual. Next, click the Arena - Hardware Mapping button in the Arena Settings window. - In the Arena - Hardware Mapping window, click Add device two or more times to create multiple rows, one row for each physical device that has to work independently. - For each arena, assign a device in a different row. Make sure that the other cells of the row show . Figure 56 Adding devices to the Arena - Hardware Mapping window, Figure 57 First row: The physical device Light 1 is assigned to Arena 1 with the generic name "Light Arena 1". Second row: The physical device Light 2 is assigned to Arena 2 with the generic name "Light Arena 2". 12 - Apply different protocols to different arenas Define the protocols Make a sketch of the events in each arena. Draw a time line for each arena. On the time line, write down the events that should occur, and their duration. This will help creating the Trial Control protocols. Trial Control Settings There may be parts of the protocol shared between arenas. In the example of Figure 59, the first 30 seconds after the start of the trial are the same for the two arenas. Therefore, one condition box after the Start track box will suffice. Figure 58 Make a sketch of your protocols on different time lines. Figure 59 A condition box that waits 30 seconds for both arenas. 12 - Apply different protocols to different arenas The sequence of instructions for the two treatments must originate from the same point (so they will start at the same time) and proceed in parallel. Note that the two branches do not have to end back into the main start-stop sequence. However, you must make sure that the trial does not stop before the two branches have been processed. In this example, we have set the trial to stop after 2 minutes. Therefore, a Time box has been added to the Start-stop sequence that waits 90 s to complete the trial (30 s of the first box + 90s = 120 s) Sequence for Arena 1 - According to the protocol, for Arena 1 the light must be switched on immediately after the 30 s period, then 2 s later it must be switched off. This can be programmed with two hardware actions (ON and OFF) and a Time condition in between. The actions must specify the device Light Arena 1. Figure 60 After a 30-s period, two procedures are activated, one for each arena. Figure 61 Instruction sequence for switching on a light in Arena 1 for two seconds. 12 - Apply different protocols to different arenas Sequence for Arena 2 - According to the protocol, for Arena 2 the light must be switched on at a time randomly chosen between 0 and 90 s. This can be programmed with a time condition that determines the random time, followed by a sequence similar to that for Arena 1. The actions must specify the device Light Arena 2. The Random time condition defines a time between 0 and 88 seconds, to make sure that the 2-seconds light flash is always given in its entire duration within 90 seconds. Repeat a sequence within the trial In most cases, a sequence of actions is repeated a number of times, or until a condition is met. If you want the two sequences described above to be repeated, you must use the Sub- rule function in Trial Control. Figure 62 Instruction sequence for switching on a light in Arena 2 for two seconds. The first box defines a random time chosen between 0 and 90 s. Figure 63 Setting two protocols to be repeated a number of times. Note that the two branching sequences are connected at their end to the stop box of the sub-rule through an operator. Only when the two sequences are processed, control is passed for a new start of the sub-rule. How repeats start is specified in the Sub-rule Reference settings (click Settings in the Reference box). 12 - Apply different protocols to different arenas The Sub-rule settings ensure that the sub-rule is repeated 10 times, and the time between the start of 2 successive repeats is 2 minutes. For more information on how to use Sub-rules, see Sub-rules on page 55. Advanced Case: Six Arenas In this use case, we plan to record data in six arenas, with one animal per arena. This use case is considered advanced for several reasons: Each treatment (odor stimulus and a subsequent foot shock) is duplicated in two arenas. This example shows that even when two of a number of arenas share the same protocol, each arena must have its own trial control procedure with unique Device names defined. Together with two treatments that require different protocols, a third group (control) is added that requires no foot shock. Control animals are recorded simultaneously with the other animals. All animals share part of the protocol. They all receive an odor stimulus by means of an olfactometer. Therefore, part of the Trial Control procedure must work for all arenas. Experiment Settings - Connect all hardware devices to the EthoVision XT computer, via the appropriate port in the Noldus USB-IO box. - In the Experiment Settings, select the Number of arenas. - Under Trial Control Hardware click Settings. - Select Noldus USB-IO box. Figure 64 Schematic representation of the treatments in six arenas. Arenas 1-2, 2-3 and 4- 5 share the same treatment. 12 - Apply different protocols to different arenas 5. In the Device Configuration window, assign a hardware device to a port of the USB IO box (or Mini USB IO box). Here Device ID represents a name for each physical device. For example, Shocker 1 will be installed in Arena 1, Shocker 2 in Arena 2, etc. Since the olfactometers work the same way in all arenas, they can be connected to the same port of the USB IO box. Therefore, you need 4 ports for the shock generators (Arenas 1 to 4) and one port for the olfactometer. Arena Settings - In the Arena Settings, define and calibrate the arenas as usual. Next, click the Arena - Hardware Mapping button in the Arena Settings window. - In the Arena - Hardware Mapping window, click Add device two or more times to create multiple rows, one row for each physical device that has to work independently. In this case, 5 rows. - For each arena, assign a device in a different row. Make sure that the other cells of the row show . Note that: Although Arena 1 and 2 and Arena 3 and 4 share the same treatment, they must be linked to different Device names. This to avoid that any command given to for Figure 65 The Arena - Hardware Mapping window. In the first four rows, a physical device is assigned to one arena; for example Shocker 2 in Arena 2. The name "Shocker 2" in the Device name column will be used in the Trial Control instructions. In the last row, the olfactometer is selected for all arenas, using the Device name "Olfactometer". This name will be used in Trial Control. 12 - Apply different protocols to different arenas example the shocker in Arena 3 does not go to Arena 4. In principle we could use the same command (and thereby the same Device name) for Arena 1 and 2 because the shock is given at the same time, but to keep this case more general we leave them separate. The arenas with no shock treatment (Arenas 5 and 6) have no shocker device selected. The olfactometer is used in all arenas, and at the same time. This means that the command to activate/deactivate the olfactometer can be represented by one Device name in Trial Control (see the last row in the table above). Therefore, the same Device name is assigned to all arenas. Define the protocols Make a sketch of the events in each arena. Draw a time line for each arena. On the time line, write down the events that should occur, and their duration. This will help creating the Trial Control protocols. Figure 66 Make a sketch of your protocols on different time lines. 12 - Apply different protocols to different arenas Trial Control Settings Sequence for Arena 1 and 2 - Note that only the sequences for Arena 1 and 2 are connected to the Stop trial box. There is no need to connect the sequences for Arena 3 and 4 and the sequence for the olfactometers to the Stop Trial box, because these instructions proceed in parallel with those for Arena 1 and 2. The track duration is the same for all arenas. Figure 67 Overview of the Trial Control Settings. Indicated are the parts of the procedure applied to specific arenas. The total length of the trial is 4 minutes and 30 seconds. Figure 68 The trial control sequence for controlling a foot shocker at 28 s from the start, in both Arena 1 and Arena 2. The shock ends at 28+2 = 30 s from the start. 12 - Apply different protocols to different arenas Sequence for Arena 3 and 4 - Figure 69 The trial control sequence for controlling a foot shocker at a time randomly chosen within a 90-s period. In order to center the 90-s period for the random shock in the 4-min period after the offset of the odor (see Figure 66), a 75-s condition has been added (75+90+75 = 240 s = 4 minutes). Note that the 30-s Condition box and the two 75-s conditions could be replaced by one 105-s Condition box, connected to both Random time conditions. In this picture the 105-s time has been kept split in two parts (30 s +75 s) to visually match the sequences for the other arenas. 12 - Apply different protocols to different arenas Repeat the sequence within the trial If you want the sequences described above to be repeated a number of times within a trial, you must use the Sub-rule function in Trial Control. Here, the sub-rule is repeated 10 times. Note that the end box of the sub-rule is connected to the sequence for Arena 1 and 2. This sets the duration of the repeats (30 min. with odor stimulus + 4 minutes), and the trial as a whole. For more information on how to use Sub-rules, see Sub-rules on page 55. Figure 70 A sub-rule has been added to repeat the protocol a number of times in the same trial. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 2 The Trial Control screen URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-2-the-trial-control-screen Chapter: EthoVision XT The Trial Control Screen To access the Trial Control screen, in the Experiment Explorer, click Trial Control Settings 1 in the Trial Control Settings folder, or from the Setup menu, select Trial Control Settings, then click Open and select Trial Control Settings 1. The Trial Control screen appears, showing the default Trial Control settings. To access the Trial Control screen, you can also create a new Trial Control Settings, or open one other than Trial Control Settings 1. The Components pane, listing the conditions on which you can base your actions and the operators which you can use to combine conditions. See the next page. The Trial Control window, showing the Trial Control Settings that are active. It contains a sequence of boxes connected by arrows. See page 19. The Maximum Trial Duration pane that allows you to define a maximum duration for all trials. See page 21. You can show/hide the Components pane and the Maximum Trial Duration pane by clicking the Show/Hide button on the components tool bar and selecting/deselecting the corresponding option in the menu. Figure 6 The Trial Control Settings screen. A - Components pane, B - Maximum Trial Duration pane, C - Trial Control window. The Components Pane With the Components pane you choose the blocks that build up your trial control rules. Expand the list by clicking the More button. Not all the components listed below may be available on your screen, depending on what EthoVision XT license you have on your computer (see page 14). Figure 7 The Components pane for Trial Control, with its main groups Conditions, Actions and Structures. Under Conditions and Actions, you see examples of hardware devices controlled by EthoVision XT: a Pellet dispenser and a PhenoTyper Top Unit. Conditions Time. See page 67. Time interval. See page 69. Trial Control variable. See page 71. Dependent variables. To define a condition based on a variable that describe the animal's behavior, for example velocity, presence in a zone, movement etc. See page 72. note You cannot define a condition based on behaviors scored manually, behaviors detected automatically with Behavior Recognition, Activity state, Acceleration state and Free intervals. Hardware. To define a condition based on the state of a hardware device. See page 79. If devices are not listed, you must first configure EthoVision XT in such a way it recognizes the devices. See page 104. Actions Trial Control variable. See page 28. External command. See page 31. Hardware. See page 117. Structures Sub-rule. To define a subroutine that can be called from a specific point of the Trial Control sequence. See page 55. Operator. To combine two or more conditions in such a way that an action is taken when All, Any or N of All conditions are met. See page 34. Reference. To insert a call to a sub-rule within a sequence of instructions. See page 57. To define a sub-rule, condition, action or operator Do one of the following: Double-click its name. Click the button next to it. Drag the name from the Components pane to the middle of the screen. A new Trial Control box appears in the top-left corner of the Trial Control window. Insert the new box in the sequence of boxes. For the complete procedure for programming Trial Control, see page 23. The Trial Control Window The Trial Control window contains the sequences of instructions (rules) currently present in the Trial Control Settings. When you create a new Trial Control Settings profile, the Trial Control window contains the default Start-Stop trial rule, consisting of six boxes connected by arrows (see page 47). You can then define: Your own conditions that determine the start and stop of data acquisition. If your EthoVision license includes Advanced Trial Control (see page 14): Additional sub-rules, that is, sequences of actions and conditions that work like subroutines in a program. They can be called from another point in the Trial Control sequence. Control hardware devices, like a food dispenser or a door. For details on how to move, copy, connect and delete Trial Control boxes, see the EthoVision XT Help. Grid The trial control boxes automatically snap to a grid. You can change this by clicking the Show/Hide button on the component tool bar and selecting/deselecting the two Grid options (Snap to Grid and Show Grid). Zoom The component tool bar of the Trial Control Settings shows three zoom icons: Zoom in. You can keep zooming in until all trial control boxes fit in the window. Zoom out. Zoom to fit. Clicking this button fits all trial control boxes into the window. The Trial Control window is 'dynamic': this means that it expands when you move trial control boxes to the right. In this case, you can navigate 'from left to right' in the Trial Control Figure 8 The Trial Control window. By default, it contains the Start-Stop trial rule. window by using the scroll bar at the bottom. Use the Zoom to fit button in the component tool bar to make all trial control boxes visible. Trial Control in special cases If you selected Activity analysis in the Experiment Settings, the first condition box is removed from the default Start-Stop rule. To carry out tracking and activity analysis simultaneously, and start tracking when your subject is detected in the arena for a specific time, insert a new In Zone condition box in the Start-Stop rule. For more information on Activity analysis, see the EthoVision XT Help. If you selected Behavior recognition in the Experiment Settings, the default Trial control rule also contains a Time condition box (3 seconds). This means that tracking starts 3 seconds after starting the trial. If you selected both Activity analysis and Behavior recognition in the Experiment settings, the same trial control rule is used as for only Behavior recognition. For more information, see Behavior recognition in the EthoVision XT Help. To export Trial Control Settings You can export an image of the Trial Control Settings: 1. Click the Export image button on the tool bar 2. Select a location to save the image to, type in the File name or accept the default one and select an image type from the Save as type list. 3. Click Save. The complete Trial Control window is exported, irrespective of the zoom factor. Maximum Trial Duration Pane Aim To define a maximum duration of the trial. This prevents EthoVision XT from waiting indefinitely that the condition to stop the trial (see page 47) is met. example In a novel object test, in the Start-Stop Trial rule you have defined a condition 'stop the track when the mouse enters the zone with the familiar object'. it may happen that the mouse completely ignores the familiar object and only pays attention to the novel object. To prevent that EthoVision never stops tracking, set a maximum trial duration. To access this option In the Trial Control Settings screen, locate the Maximum Trial Duration pane, right below the Components pane. If you do not see it, click the Show/Hide button on the tool bar and select Maximum trial duration. Notes Instead of using a Maximum trial duration, you can also define a condition based on time and place it immediately before the Stop track box (see page 47). However, there are two important differences: If you use the maximum trial duration, the program counts the time from the start of the trial (this is indicated by the Start-Stop trial box). Instead, a condition placed immediately before the Stop track box considers the time from the start of data recording (this is indicated by the Start track box). The two starting points may not be the same if you have a condition between Start-Stop trial and Start track that makes data recording start some time later than the trial. With a multi-arena setup, a maximum trial duration stops the trial (and thus data recording) in all the arenas simultaneously, even when data recording had started at different times. Instead, a time condition placed between the Start track and the Stop track box stops data recording in one arena when the condition is met in that arena. This means that you can have data recording stop at different times in different arenas. example You set to start data recording when the animal is detected for the first time in its arena. For this purpose, you make an In zone -based condition. Next, you define a 5- minutes Time condition, and place it immediately before the Stop track box. It the animals are detected for the first time at different times in different arenas, data recording stops at different times too, because of the 5-minutes interval set for all arenas. The trial ends when the recording stops in the last arena. The Maximum trial duration is not applied when you record video with the option Save video only, track later. You must stop video recording manually. When you track from the resulting video file, the Maximum trial duration is applied. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 3 Program Trial Control URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-3-program-trial-control Chapter: EthoVision XT 3 - Program Trial Control Program Trial Control If you just want record data for a specific time, you can do so by setting the maximum trial duration (page 21). If you want to start and stop data recording in relation to a few simple conditions (for example, start recording when the animal is detected in the water maze, and stop when the animal reaches the platform), define the Start/Stop trial rule (page 47). In other cases, see below. Procedure - Before defining Trial Control in the program, it is helpful to draw your experimental procedure as a flow diagram, where each block represents an action or a condition which, when met, triggers other actions or conditions. The logical order in the example below reads from left to right. - From the Setup menu, select Trial Control Settings, select New, enter a name of the new Trial Control Settings or accept the suggested one, and click OK. The default Start/Stop trial rule appears on the screen. - Build the Trial Control sequence outlined in step 1, using the components available. To define a Condition or an Action, click one of the buttons under Conditions or Actions. Insert the box in the appropriate place in the sequence. For conditions See page 26 and page 67 For actions on hardware devices See page 117 For actions on Trial Control variables See page 28 To define a set of actions and conditions to be repeated (Sub-rule), under Structures click the button next to Sub-rule (see page 55). Figure 9 An example of flow diagram representing the control of an operant conditioning test. The sequence is assumed to be repeated a number of times. 3 - Program Trial Control To define the command that calls a sub-rule, under Structures, click the button next to Reference. Insert the box in the appropriate place in the sequence (see page 57). - Test the Trial Control sequence (see page 42). - To apply Trial Control to your trials, before starting data acquisition make sure that the Trial Control Settings are highlighted in blue in the Experiment Explorer (see page 45). Notes When you create a new Trial Control element (action, condition, sub-rule or reference) and another of the same type has already been defined in this or other Trial Control Settings, a message appears asking you whether you want to create a new element or make a copy of the existing control. For more information, see page 36. A Trial Control variable is a variable that you can define to control your trials. For example, a counter variable that is incremented every time a specific event occurs. You can then define conditions and actions based on this variable. For more information, see page 28. If the experimental protocol is very complex, like in the case of a multiple-day recording session, it is handy to split the procedure in main blocks; then, for each block specify the basic actions and conditions, and whether the logical sequence should be repeated. This helps you identifying the main building blocks of your Trial Control logic, which will translate into Sub-rules. If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings (see Activity analysis in the EthoVision XT Help), the Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. This makes the rule invalid. Redesign your Trial Control rule and connect the arrows between the boxes. example A trial is to be run for a few days. On day 5 after the start, during the dark phase, an operant conditioning session must be repeated 10 times. On day 6, the same sequence must be carried out just once. If you choose to record video with EthoVision XT by selecting the option Save video only, track later in the Acquisition screen, Trial Control is applied when you do tracking, not when you record video. To start and stop video recording, do so manually. 3 - Program Trial Control Procedures that must be repeated or represent a specific task must be defined as Sub-rules (see page 55). Sub-rules can be called at specific times or under specific conditions. In the main Start-Stop diagram, draw a block that calls each sub-rule. See also the Main cases on page 38 for examples of logical blocks combined for a specific function. Figure 10 An example of a block diagram representing a multi-day conditioning schedule. Figure 11 An example of a block diagram with the main Start-Stop procedure (top) and two subroutines (sub-rules). 3 - Program Trial Control Conditions A Condition is a statement that EthoVision checks during the trial. When the Condition is met (True), the program evaluates the next Trial Control element (another condition, an action or a reference to a sub-rule). example Conditions are indicated in italics: When the rat reaches the platform, stop tracking. When the mouse is around the novel object, switch on the light. When the animal presses the lever, drop a pellet. To define a condition - In the Components pane, under Conditions, locate the type of condition you want to define. - Double-click the condition name or click the button next to it. - If the Add a condition window appears, it means that there is at least one condition of the same type in your experiment. You are asked to choose between creating a new condition, or re-use an existing one (see page 36). Choose the option you require and click OK. If this window does not appear, skip this step. - Next to Condition name, type in the name you want to give to the condition, or accept the default name. - Specify the condition properties (for details see page 67). - Enter a Comment (optional), then click OK. - Insert the condition box in the sequence. If the condition is complex (for example, Stop the trial either if the rat has reached the platform or it has been swimming for 60 seconds), then you must define separate conditions and combine them (see page 34). important If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings (see the EthoVision XT Help), the Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. This makes the rule invalid. Redesign your Trial Control rule and connect the arrows between the boxes. See also Main cases on page 38, and a detailed overview on page 67. 3 - Program Trial Control Actions An Action is a command that EthoVision carries out during acquisition and that influences the trial. example Actions are indicated in italics: When the animal is detected in the arena, start tracking. This is an example of system actions (start tracking and stop tracking). When the animal enters the maze's left arm, do C= C+1. This is an example of actions on a Trial Control variable. See page 28. When the animal is found on the shelter, drop a pellet. This is an example of actions on hardware devices. See page 117. When the animal leaves the shelter, play a sound or present a visual stimulus. Or, when you start tracking, also start ultrasound recording with UltraVox XT. Those are examples of actions based on an external command. See page 31. To define an action - In the Components pane, under Actions, locate the type of action you want to define: Trial Control variable for an action on a Trial Control variable. The device type name for actions on a Hardware device. External command to start an external program or run a batch file. - Double-click the action name or click the button next to it. - If the Add an action window appears, it means that there is at least one action of the same type in your experiment. You are asked to choose between creating a new action, or re-use an existing one (see page 36). Choose the option you require and click OK. If this window does not appear, skip this step. - Next to Action name, type in the name you want to give to the action, or accept the default name. - Specify the action properties: See page 28 for actions on Trial Control variables. See page 31 for actions on External commands. See page 117 for actions on Hardware devices. - Enter a Comment (optional), then click OK. - Insert the action box in the sequence. You cannot create additional actions of type Start track and Stop track, nor can you delete the existing ones. For an overview of frequent actions, see also page 38. 3 - Program Trial Control Trial Control Variables You can define variables to be temporarily stored during a trial, that you can use to influence the control of the experiment. example 1 Variable as a marker. The variable Phase has been defined to specify the various phases of a trial (Phase = 1 means Conditioning; 2 Testing, etc.). The researcher can then program EthoVision to follow specific Trial Control sequences according to the current value of Phase. example 2 Variable as a counter. A researcher has defined the variable SR (successful response) to count the number of times the subject responds correctly to a stimulus. To increment the value of SR after a correct response, specify the formula SR= SR+1. To define a Trial Control variable - In the Components pane, click the button next to Trial Control variable under Conditions or Actions. Next, click the TC Variables button. - The Trial Control Variables window lists the variables currently in the experiment (also those defined in other Trial Control Settings). To add a new variable, click Add variable. - A new row is appended to the table. Under Name, type in the name you want to give to the variable. Under Initial Value, enter the value of this variable at the start of the trial (default: 0). - Click OK. In the TC-variable action/condition window, define the action or condition you require. Click Cancel if you do not want to create a condition or action based on this variable at this point. To delete a variable, click the variable name in the Trial Control Variables window and click the Delete variable button. To rename a variable, click the variable name in the Trial Control Variables window and edit this name. The variable name cannot contain blank spaces. The default name of a new trial control variable is VarN, where N is a progressive number. Actions on a Trial Control variable To assign a new value to a variable in Trial Control, define a Variable action in your Trial Control rule. 1. In the Components pane, under Actions, click the button next to Trial Control variable. 2. If the Add an action window appears, it means that there is at least one action of the same type in your experiment. You are asked to choose between creating a new action, or re-use an existing one (see page 36). If this window does not appear, skip this step. 3 - Program Trial Control 3. Next to Action Name, enter the name of the action (for example, Increment Counter) or accept the default name. 4. Under Action to perform, select the variable from the list. You can also create the variable by clicking the TC Variables button if you have not yet done so. 5. Next to the "=" symbol, do one of the following: To assign the same value of another variable (for example A = B), select the other variable (B) from the second list. To enter a formula, click the double-arrow button. Select the operator from the list and specify the formula in the second and third lists. For example, A= A + 1. To assign a random value, select Random from the second list, and enter the Minimum and Maximum limits (only integer numbers 1 up to 999) in which the random value must lay. When you select Random, the Permutation option also appears. See below for details. 6. Enter a Comment (optional), then click OK. 7. Insert the resulting Action box in the Trial Control rule. Random values and the Permutation option When programming Variable ratio schedules, it is a good idea to use the Random option. Define a random variable R that specifies the number of rewards to be provided. Insert the resulting box in a sub-rule (see page 55). Every time the sub-rule is repeated, the variable R gets a new value. Make sure that the food dispenser is activated as many times as specified by R during that repeat. You can do this by calling a second subrule that activates the food dispenser (Action "drop pellet" followed by a time condition that waits for a short time interval like a few seconds). This second subrule is repeated as many times as specified by the value of R. You cannot combine Random with a formula (for example, to compute A= Random+1). The equivalent solution is the following: define first an action B= Random, and then one more action A= B+1. Place the two boxes in sequence. Select the Permutation option to generate a value in such a way that all n values within the specified range occur once before a value is generated again. For example, if you specify 1 as Minimum and 5 as Maximum (n = 5), the value 1 will be generated only when all five values in the range are generated in previous repeats of the action. In the following example, the Action is inserted in a subrule that is repeated a number of times at regular intervals. In the first five repeats, the numbers are generated in the following sequence: 5, 4, 2, 3, 1 (see the next image). A new value 5 can only occur at the 6th repeat (indicated with the arrow) or later, after all the numbers within the range 1-5 have been generated. 3 - Program Trial Control Use the Permutation option to create sequences of unique numbers, for example to define which door of a maze must be opened in a pseudo-random sequence. Notes If your setup includes multiple arenas, each arena receives an instance of the variable. Thus, a variable can have different values in different arenas. You can define several instances of variable-based actions and conditions in the same Trial Control profile. Such instances may well become active at the same time. Make sure that they do not interfere with each other. For example, two actions on the same variable are carried out in two different sub-rules (see page 55): If the actions A=1 and A=2 are evaluated at the same sample time, the value of the variable A after the actions are executed depends on the order of the Reference boxes those sub-rules refer to. If the reference to Sub-rule 1 comes first, A=1 is executed first. If references are placed in parallel, the order is undefined. In the Visualization, you can check which action is executed first (see page 42). 3 - Program Trial Control To analyze the values of a Trial Control variable, or visualize its values plotted against time, also for testing purposes, in the Analysis profile choose Trial Control variable. External Commands Actions based on an External command - In the Components pane, under Actions, click the button next to External command. - Next to Action Name, enter a name for the (for example Play sound) or accept the default name. Click the Information button to get additional information about defining an External command. - Under Actions to perform, select which file you want to run by clicking the ellipsis button. - Next, select one of the file types from the list: Executables (.exe). Batch Files (.bat, .cmd). All Files (.*). - Locate the file and click Open. - Optionally, enter a Command line option. - To test the command, click the Test button. Example 1 - Trigger Media Recorder to record video You carry out live tracking during a 24-hour period and you want to record video with Media Recorder, but only when the animal is not in the shelter (defined as a Hidden Zone, where it spends most of its time). note For this configuration you need an analog camera. You must split the video signal from the cameras (using a BNC T-splitter connector) and send it to two BNC connectors of the Picolo Alert encoder board: one for tracking in EthoVision XT and the other for Media Recorder. In order for the board to receive correctly the two signals, you need to adjust the dip switches on the encoder board: usually On for the first input and Off for the second input. 1. First, create an External command box to start Media Recorder. Choose Executables (*.exe) and select MRCmd.exe as the application to run. As a Command line option, enter /E to specify that the external command launches Media Recorder. 3 - Program Trial Control 2. Next, insert a Condition Out of shelter and combine this with a Time condition to make sure that Media Recorder is launched before recording starts (see Figure 12 for an example). 3. At the right of the Operator box insert a second External command box, this time to start video recording: select MRCmd.exe as the executable to run and enter /R as a Command line option to start recording (see the last box in the figure below). 4. Similarly, you can have EthoVision XT stop recording (Command line option: /S) when the subject enters the shelter again (not shown here). note There may be a delay between the command Start Recording and the moment Media Recorder actually starts recording. Run a test recording to measure that delay. Example 2 - Trigger UltraVox XT to record ultrasound In this scenario, you plan to video-track mice with EthoVision XT and, at the same time, record their ultrasonic vocalizations with UltraVox XT. For ease of use you want to start and stop recording from one place - EthoVision XT. Define an External command action based on the batch file SUV.bat (see 1 in the figure below). This file is located in C:\ProgramData\Noldus\Common\Tools\UltraVox XT 3 Control. Note that you need to edit this batch file depending on your computer name or IP address. In the figure below, Condition 2 determines the duration of the recording. Action 3 stops recording in UltraVox XT. Figure 12 Example of the External command action to start a recording with Media Recorder when the animal leaves a shelter. The left Start MR action box starts up Media Recorder. The Start Recording action box on the right starts the recording when both the Out of Shelter and Time(1) conditions are true, that is, the center-point of the animal has left the shelter at least 5 seconds after Media Recorder was started. 3 - Program Trial Control Furthermore you must set UltraVox XT to automatic start/stop recording. For more information, see Control UltraVox XT from other software in the UltraVox XT 3 Help. Example 3 - Run a batch file You want to play a sound during your trials. You can do this by running a batch file (*.bat or *.cmd) using an External command action in EthoVision. In the figure below, an action has been defined with the batch file Play sound.bat. The batch file Play sound.bat starts Windows Media Player and plays the sound file Stimulus_sound.wav. Its content is: start "%ProgramFiles%\Windows Media Player\wmplayer.exe" D:\temp\Stimulus_sound.wav Arena and Trial names. When using a batch file, you can use the command line options %an% and %tn% to send information about the Arena and the Trial name in command lines from the Trial Control rule. For example, during a batch acquisition of trials you could send the trial name information to an external program, which starts a procedure when trial name (%tn%) becomes Trial 10. In the following example, a batch file has been created to display the current Trial name and Arena name in the DOS window (one for each arena, in the case of multiple arenas). Echo %1 and Echo %2 listen to the values of %an% and %tn% in the order specified in the command line options. The DOS window is set to close 5 seconds later: echo %1 echo %2 PING 1.1.1.1 -n 1 -w 5000 >NUL 3 - Program Trial Control In the External command Action window, specify the name and location of the batch file, and enter the command line options %an% %tn% (lower case only; parameters must be separated by space). important Contrary to what worked in EthoVision XT 12 and older, %an% %tn% are not written with quotes. For example %tn% becomes Trial 1, not "Trial 1". Operators Aim The Operators help you combine actions, conditions and sub-rules in various ways. examples When at least one of the two conditions A and B is met, then do … . This is an example of conditions combined by an operator of the "Any" type (OR logic). When two conditions are met at the same time, then do … . This is an example of conditions combined by an operator of the "All" type (AND logic). When at least/at most/exactly 4 of 8 conditions are met, then do … This is an example of conditions combined by an operator of the "N of All " type. Procedure - Define the conditions/actions/rules that you want to combine. Place them in your Trial Control sequence as parallel branches as in the figure below. 3 - Program Trial Control - In the Components pane, under Structures, double-click Operator or click the button next to it. - If the Add an operator window appears, it means that there is at least one operator of the same type in your experiment. You are asked to choose between creating a new operator, or re-use an existing one. If this window does not appear, skip this step. Create a new operator. A new operator is created. Re-use an existing operator. Select the name of the operator already present in your experiment. See page 36 for more information. Click OK. The Operator window appears. - Under Name, enter the Operator name or accept the default name Operator (n), where n is a progressive number. - Under Operator triggers when, select the option that applies: Any (at least one) of the inputs is 'true'. All inputs are simultaneously 'true'. N of All inputs are simultaneously 'true'. Where 'true' means a condition met, an action carried out, or a sub-rule finished (depending on the elements you want to combine). If you choose the third option, specify how many inputs must be 'true': = (exactly equal to), not= (not equal to), >= (at least), <= (a maximum of), etc. Specify the number in the box. - Enter a Comment (optional) to describe this operator, and click OK. - A new Operator box appears in the Trial Control. Place the box right of the elements defined in step 1, and connect each element to the operator box. 3 - Program Trial Control - Connect the operator to the next element in Trial Control sequence. Notes Names of operators must be unique in your experiment. You cannot define two operators with the same Operator name, even if these are defined in two different Trial Control Settings. An Operator can also have just one input box. In that case the operator is of no use, because control passes immediately to the next box as soon as the input condition becomes true or the input action is carried out. EthoVision informs you about this. Operators can also combine sequences of elements. For example: Sequence 1 - When the animal presses a lever (Condition), then drop a food item (Action). Sequence 2 - Time= 5 minutes (Condition; this equals to waiting 5 minutes). If you want the program to take an action when either sequence has been completed, combine the two sequences with an "Any" operator. Re-use Trial Control Elements The elements of Trial Control (conditions, actions, operators, sub-rules and sub-rule references) that you have defined in other Trial Control Settings can be duplicated and re- used in the current Trial Control Settings to reduce your time spent editing. To re-use all the elements defined in your current Trial Control Settings profile, make a copy of it: right-click the profile in the Experiment Explorer and select Duplicate. To re-use a Trial Control element - Click the button next to the category of element that you want to re-use. - The Add window appears. Select Reuse an existing condition/ action/ sub-rule/ reference. This window does not appear when the experiment contains only one Trial Control Settings profile, or the experiment contains more Trial Control Settings profiles but none of them contains an element of the same type as that you have chosen. - Select the name of the existing element from the list next to the option. The second list shows the Trial Control Settings profile that contains that element. If the element is present in multiple Trial Control Settings, choose the appropriate one from the list. - Click OK. 3 - Program Trial Control - A window appears for the type of element chosen. The Name and settings specified here are the same as in the element chosen in step 3. To create an identical copy of the element, click OK and go to step 7. In all other cases, edit the settings and click OK, then go to step 6. - If you have changed any property of the new element (including name and comment), a window appears showing two options: Apply the new settings only in the current Trial Control profile. Apply the new settings in all writable Trial Control profiles. The program asks you whether you want to apply the properties only to the new copy, or to extend those changes to the original elements in all Trial Control Settings that are writable (that means, not locked after acquisition). Choose the option you require and click OK. - Insert the resulting box in the Trial Control sequence. Notes If you choose the option Apply the new settings in all writable trial control profiles, changes are not made in those profiles made read-only after data acquisition. The program does not ask you whether you want to re-use the Trial Control element if no element of the same type has been defined in the other Trial Control Settings. You cannot re-use a Trial Control element from the same Trial Control Settings. This is because the Trial Control elements must be unique in order for correct analysis to be done. 3 - Program Trial Control Frequently-occurring Cases Have an action taken when a condition is met example A food pellet is dropped (Action) when the mouse is detected in the zone that marks the top of the shelter (Condition). The condition must precede the action. In the example above, the condition is based on a zone. The action is performed on the Pellet dispenser. Have two actions taken at the same time example In a radial maze experiment, make sure that the device Door 1 opens at the same time when Door 2 closes. Define two action boxes, one for each door device. Next, do one of the following: Place the two action boxes in parallel, and combine them with an All operator (see page 34). Place the two action boxes one after the other. The time between the two actions is negligible. Specify a time interval between actions/conditions example Wait one minute between the action Cue Light On and the action Drop one pellet. Insert a Time condition box between the two existing boxes (see also the next case). Make multiple instances of an action example In a conditioning experiment, drop two food pellets in sequence. The two actions are placed in a linear sequence. If the action is performed on a hardware device, insert a Time condition between the two action boxes, for example wait 10 s before proceeding to the second action. If you do not do this, EthoVision XT interprets the twin actions as one. In the example above, it would deliver one food pellet only. 3 - Program Trial Control If the pellet dispenser is almost empty, it may take up to 30 seconds to deliver a pellet. make sure that the time specified in the Time condition exceeds the time that it takes the action to be carried out. Another possible solution is to place a condition based on hardware between the two actions, that checks that the Number of pellet drops is >=1 before taking the next Drop pellet action. Have a sequence of conditions and actions repeated example Make sure that the sequence Mouse on Shelter --> Drop one pellet on page 38 is repeated every time the animal is found on the shelter. Define a Sub-rule (see page 55) and insert the sequence of conditions and actions in it. Next, create a Reference to that sub-rule, and specify when and how many times the sequence must be repeated (see page 57). Give a reward after multiple instances of the subject's action example In a Fixed Ratio schedule, it is required that the animal has to press the lever three times (Action) before getting a reward. Define a Trial Control variable C that counts the number of lever presses. The action C=C+1 is triggered every time the condition Lever pressed is met. Define a Sub-rule that includes the sequence Condition Lever pressed Action C=C+1. Define a Reference for that sub-rule, and specify that the sub-rule must be repeated until C reaches the value required 3. Place the Action box for Drop a pellet immediately after the sub-rule's Reference box. For more information: On Trial Control variables. See page 28. On sub-rules and references to sub-rules. See page 55 and page 57. 3 - Program Trial Control Have an action taken when a condition is met within a specific time example Have EthoVision XT drop a food pellet when the animal visits zone A within 1 minute from the release of a light stimulus. Define the main condition (in the example above, animal in zone A. Specify that the Current value of In zone must be true. Define the action that must be taken (Drop a pellet). Define the accompanying Time condition (Wait one minute). Place the main condition followed by the action. Place those two boxes in parallel with the Time condition, using an operator of "Any" type. With such a sequence, the food pellet is dropped as soon as the animal is found in zone A. If the animal does not go to zone A, one minute after the light was switched on the Time condition is met, and the operator becomes active. Therefore, control passes to the box following the operator, and the In zone condition is no longer evaluated. With this solution, the action Drop a pellet is not taken when the animal enters zone A more than one minute after the light has been switched on. important If you combine the two conditions above with an operator of All type, the program may wait indefinitely until both conditions are met. Have different actions taken according to different conditions example A T-maze is provided with two doors, one in the middle of arm A and one in the middle of arm B. It is required that door A is opened when the animal enters arm A, and door B when the animal enters arm B. Define two conditions, one for arm A and one for arm B. For both conditions, specify that the Current value of In zone must be true. 3 - Program Trial Control Define two actions, one for opening door A and one for opening door B. Connect each condition to the corresponding action. Next, connect the resulting sequences through an operator of the "Any" type. Define phases in a trial example It is required that tracking occurs in different phases of a trial, for example, Baseline, Conditioning, and Testing. In each phase, different trial control rules must be applied. For each phase, define a Sub-rule (see page 55) with its actions and conditions. Specify when the sub-rule must start. For each sub-rule, define a Sub-rule reference and insert it in the Start/Stop rule. Make sure that the references are in the order specified in your experimental protocol. 3 - Program Trial Control Test The Trial Control Sequence It is not easy to make a complex Trial Control sequence work right the first time. To check that Trial Control works as expected, follow this procedure: 1. Make sure that the Trial Control Settings that you want to test are highlighted in blue in the Experiment Explorer. Otherwise, click the Trial Control Settings you want to test. 2. Open the Acquisition menu (Choose Acquisition > Open Acquisition. 3. Click Show/Hide and choose Show Dependent Variable. Choose Trial Control Event for simple events like Action Drop a pellet becomes active, or Condition Subject in zone A becomes true. Choose Trial Control State to select the time between events occurred during the trial. for example From Action Light On To Condition In Trigger zone True. This will show the time interval from when the light switches on to when the animal enters the Trigger zone. 4. Start a trial. Watch the Trial Control Events or States in the Analysis Results and Scoring Pane at the bottom of your screen. 5. Create an Analysis profile and use the Trial Control event /state/variable and other dependent variables to specify the events you want to visualize. See page 168 for details. 6. To visualize the trial, choose Analysis > Results > Plot Integrated Data. Trial Control data are visualized as vertical segments (for events, with no duration) or horizontal bars (for states, with a duration) along the time line. Examine the data and check that EthoVision XT has responded as expected. Figure 13 Visualizing Trial Control data. Top: Dependent variable In zone "On Shelter". Middle: Trial Control event that marks the time when the Zone transition condition is met. Bottom: Trial Control event that marks the time when a food pellet is dropped. 3 - Program Trial Control 7. You can also check when exactly a condition becomes active or true, or when a command is given by looking at the Trial Control Events pane at the bottom-right corner of your screen. Select an Arena name from the list to visualize the sequence of Trial Control for that arena. Play the track. The red hairline moves along the sequence and shows at what point Trial Control is. Play the track frame-by-frame to see when exactly a condition becomes true, or a command becomes active. In the following example, a Trial Control sequence is defined: Condition: In trigger zone Action: Drop pellet Condition: In feeder zone. Play the track until the cursor gets between Condition: In trigger zone - becomes false and Condition: In trigger zone - becomes true. This is the time when the condition is activated and the program waits until the animal enters the trigger zone. At 15.48 s the condition becomes true. The program executes the instructions that follow (Action: Drop pellet) and positions at the next condition (In feeder zone) until that becomes true too. 8. Make the necessary corrections to the Trial Control rules and start again from step 2. Figure 14 The Trial Control Events pane. 3 - Program Trial Control Notes For a clear overview of the Trial Control events occurring during a trial, for each Trial Control box (except the Rule End box) define three dependent variables (step 3 above): Trial Control event - under Element, choose which box to test, and under Event, choose becomes active. This marks the time when an action is taken, a condition is evaluated, or a sub-rule is activated. Trial Control event - under Element, choose which box to test, and under Event, choose becomes inactive. This marks the time immediately after an action is taken (this is usually not distinguishable from the time the action is taken), a condition is met, or a sub-rule is completed. Trial Control state - Select From when the box becomes active To when the box becomes inactive. This will display a colored bar that marks the time that the box is activated up to when it is deactivated. Define also one or more a In zone dependent variable to monitor the position of the animal. Once you have carried out a trial, the Trial Control Settings used for that trial are locked. To edit them, either delete the trial acquired in step 2 or make a copy of the Trial Control Settings (right-click the Trial Control Settings in the Experiment Explorer and select Duplicate). To check at what time an action is taken or a condition is met, you can also export the Trial Control events specified in step 2 and the Hardware log data (see page 185). You can also test your Trial Control Settings by providing visual/audible feedback during the trial. Define an action box that calls up some feedback once the program has reached a specific point in the Trial Control sequence. Insert this box immediately right to the condition/action/rule reference box that you want to test. To test hardware devices, see page 115. 3 - Program Trial Control Apply Trial Control To Your Trials To apply Trial Control to your trials, make sure that the Trial Control Settings profile containing that logic is highlighted in blue in the Experiment Explorer. Test your setup thoroughly before carrying out the actual trials (see page 42). For setups with multiple arenas Trial Control is applied to each arena independently. Locked Trial Control Settings When a Trial Control Settings profile is used for acquiring at least one trial, it becomes locked. Locked settings are indicated by a lock symbol in the Experiment Explorer, and cannot be edited. To edit a locked Trial Control Settings profile, make a copy of it and edit this copy. Track from pre-recorded video files When you track from video files, Trial Control checks conditions using video time instead of the real time. Conditions based on time. If you select the Detection Determines Speed option, Trial Control is carried out at the speed set by EthoVision in order not to skip video images). This results in the video playing faster or slower than normal (1x), depending on the processor load necessary to detect subjects. For example, if detection requires little processor work, the program tracks the subject faster than normal. A time condition (for example, 60 s) is therefore met earlier than at real time. Using Clock time. If you define a condition based on clock time, or schedule a sub-rule with Clock time, this is translated into the video start time, that is, the date and time the video file used for tracking was created. example 1 You set a Time condition to start tracking After clock time 11:30. The video file was created on March 6, 2008 at 11:00. once you start the trial, the condition is met half an hour later in the video. If you had set to start tracking After clock time 10:30, tracking would start immediately after starting the trial. example 2 You set a sub-rule to start at 10:00 (1st day). The video file was created on March 6, 2008 at 11:00. Once you start the trial, the sub-rule never starts, because the planned start occurs before the initial time of the video. To make a sub-rule start when tracking from that video, set the start time between 11:00 and the video end time. 3 - Program Trial Control Record video, then track the subject You can choose to record video first and then acquire data from the resulting video file. You do this by selecting Save video only, track later in the Acquisition screen. When recording video, Trial Control is turned off. You get an appropriate message when selecting the option Save video only, track later. When you track from the video recorded in the previous stage, Trial Control for Start- Stop is activated, but you cannot control hardware devices. Re-do a trial For video files recorded with EthoVision, you can re-do the corresponding trial (see 'Redo trials' in the EthoVision XT Help). However, if you re-do a trial the Trial Control log files recorded with the previous instance of the trial are deleted. Stop a trial When you stop the trial, all rules active in the Trial Control Settings are ended immediately, and hardware devices are reset. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 4 The Start-Stop trial rule URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-4-the-start-stop-trial-rule Chapter: EthoVision XT The Start-Stop Trial Rule The Start-Stop trial rule is displayed on your screen when you create or open Trial Control Settings. It can be recognized by the first box with a green circle: With this rule, you control the start and stop of data acquisition (tracking). You can only modify the initial Start-Stop trial rule. You cannot: Delete the Start-Stop trial rule, including the Rule Begin, Rule End, Start track and Stop track boxes. Define an additional Start-Stop trial rule. The Default Start-stop Trial Rule The default Start-Stop trial rule is a sequence of six boxes (but see a few exceptions, page 48): Rule Begin - Start-Stop trial. Activated when you start the trial (from the Acquisition menu, select Start Trial, or click the Start Trial button, or press Ctrl+F5). Once you start the trial, control passes to the next box. Condition - In Zone - Cumulative duration >= 1 s. This is the default Start track condition. It is fulfilled when center point of the subject (or of any subjects, in the case of an arena with multiple subjects) has been detected in the arena for 1 second after you started the trial. If you start the trial and the animal is not detected yet, the program waits until it detects the animal for 1 second, then it starts tracking. Figure 15 The default Start-Stop trial rule is a sequence of six boxes: Action - Start track. Activated when the condition on its left side is met. Once this box is activated, data recording (tracking) starts. If the condition placed between the Start-Stop trial box and this box is not met immediately, tracking starts later than the time you start the trial. Condition - Time - Infinite time (condition never met). This is the default Stop track condition. This condition is never met. The trial stops when you give the Stop command or the time exceeds the maximum trial duration (when this has been set). important Always keep a Condition box that determines when the track is stopped right before the Stop track Action box, otherwise the trail stops immediately after you start the trial. Action - Stop track. Marks the end of all tracks (and trial). Rule End - Start-Stop trial. This box is just the delimiter of the rule, it does not take any action. The Start-stop trial rule in special cases Multiple arenas. When working with multiple arenas, the rule is applied separately for each arena. This means that tracking can start at different times in different arenas in the same trial, depending on when the condition placed immediately before the Start track box is met in a specific arena. See also a note about multiple open fields on page 52. DanioVision and Activity analysis. If you selected Activity analysis in the Experiment Settings, or created a DanioVision experiment, there is no box between the Start-stop trial and the Start track box. This means that tracking starts immediately when you click the Start trial button. For more information on Activity analysis, see Activity analysis in the EthoVision XT Help, or the DanioVision DVOC-0041 - Reference Manual. Behavior recognition. If you selected Behavior recognition in the Experiment Settings the default Trial control rule contains a Time condition box set to 3 seconds. This means that tracking starts 3 seconds after starting the trial. This is done because the Behavior recognition algorithm needs 3 seconds of video images to make the first classification of behavior. With this condition you make sure that your track contains Behavior recognition data since the first sample. If you selected both Activity analysis and Behavior recognition in the Experiment Settings, the Trial Control Rule is the same as when you selected Behavior recognition only. For more information on Behavior recognition, see Behavior recognition in the EthoVision XT Help. An important distinction: Trial vs. track Trial. A Trial can be viewed as a container for the data collected in one recording session. It starts when you give the Start command in acquisition and stops when the tracks for all arenas and subjects have stopped. Track. A Track corresponds to the actual recording of a subject's position and behavior. The start of a track may or may not coincide with the start of the trial. This depends on your Trial Control Settings. If you use the default Trial Control Settings, the track starts 1 second after the animal has been detected in the arena and stops when you stop the trial. A Trial may contain one or more tracks. For example, if you track two subjects simultaneously, each trial includes two tracks, one per subject. Similarly, if your setup contains four arenas with two subjects each, each trial includes 4 arenas x 2 subjects = 8 tracks. In a multiple-arena setup, the end of a track does not necessarily mean the end of the trial. The trial ends when all tracks come to an end. Customize The Start-stop Trial Rule Modify the Start track condition The default Start track condition is an In zone condition. To modify that condition, click the Settings button. In the window that appears, click Settings and specify the zone in which the animal should/should not be in order for the program to start tracking. (for details on In zone conditions, see page 86). To use another condition (for example: start recording exactly 1 minute after starting the trial), delete first the current condition (click that box and press Delete) and insert the new one. For an overview of conditions, see page 26 and page 67. To start recording as soon as you start the trial, delete the Start track condition. Click the box immediately before the Start track box and press Delete. Modify the Stop track condition The default Stop track condition is a Time condition. To modify that condition, click the Settings button, and choose the option you require (for details on Time conditions, see page 67). To use another condition, delete first the current condition (click that box and press Delete) and insert the new one. For an overview of conditions, see page 26 and page 67. If you want to stop tracking when a specific time has elapsed, see page 21. important Keep at least one condition between Start track and Stop track. If you do not do this, tracking stops immediately after tracking starts, resulting in no data. important If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings (see Activity analysis in the EthoVision XT Help), the Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. This makes the rule invalid. Redesign your Trial Control rule and connect the arrows between the boxes. Call a sub-rule Sub-rules are subroutines of the Start-Stop trial rule (see page 55). You can program EthoVision XT in such a way that a subset of Trial control actions and conditions is called from a specific point in the Start-Stop trial rule. When this subset of instructions is finished (or repeated a number of times), the program resumes following the instructions of the Start-Stop trial rule. 1. Define a sub-rule (for details see page 55). 2. In the Components pane, under Structures, click the button next to Sub-rule reference. Enter a name for the reference, and select the sub-rule you have defined in step 1 above. 3. Insert the reference box in the correct place in the Start-Stop trial rule. For more information on sub-rules, see page 55. For more information on sub-rule references, see page 57. You cannot define a sub-rule reference without defining the sub-rule first. Examples Of Start-stop Trial Rules Start data recording at a specific time You want to start recording at a time you are not in the lab, for example at 23:00 h. Delete the default Start track condition (see page 49). Define a Time condition (see page 67). Select At clock time and enter 23:00:00. Click OK and place the resulting box before the Start track box. Before leaving the lab, click the Start trial button to start the trial. The program waits till 23:00 to start data recording. For a similar example, see Examples of Start-Stop trial rules in the EthoVision XT Help. Stop data recording after the maximum time has elapsed Click Settings in the Condition box immediately before the Stop track box. Select After and enter the maximum time. note Instead of using a Time condition, you can also use the Maximum trial duration option (see page 21). Water maze: Stop the trial when the animal has found the platform In the Arena Settings, make sure that the platform has been defined as zone. In the Trial Control Settings, delete the default Stop track condition (see page 49). Next, define a In Zone condition (see page 86). If you want the program to stop recording as soon as the animal is over the platform, select Frequency as Statistic and choose >= 1. Click Settings and select the platform zone. Sometimes the animal swims over the platform, but it does not stop there. In such cases the program would stop recording while the animal has not "found" the platform. Instead of selecting Frequency, choose Current duration and the minimum time the animal must stay on the platform (for example, 3 seconds). Click Settings and select the platform zone. Click OK and place the resulting box before the Stop track box. Water maze: Stop the trial either when the rat has found the platform, or when it has been swimming in the water maze for 60 seconds The Arena Settings and the condition In platform zone are similar to those in the example above. The condition subject swimming for 60 s can be translated to Time >= 60 s. The track stops when either condition is met. The two conditions are combined with OR logic (see Figure 16). This solution results in tracks of different duration: less than 60 s for the animals that found the platform, and 60 s for the others. tip Instead of two Condition boxes in the example above, you can also define the In zone condition box and set a Maximum Trial duration (see page 21). Multiple open fields (multiple arenas): Starting tracking when the subject is released in the open field. Tracking starts independently in each open field. In this setup, four open fields are treated as separate arenas. You want to start acquisition when the animal is detected in the open field independent of what happens in other arenas. This can be achieved by using the default Start-Stop trial rule. As soon as an the subject is detected in an arena, tracking starts for that arena, not the others. This way you do not have to release all the animals at the same time. Conditioning test: Stop the trial when the conditioning task has been repeated N times. For example, when the animal has obtained 25 rewards. 1. Create a new sub-rule (see page 55) containing the instructions for the testing session. Sub-rule Begin Condition Is subject on top of the shelter? Action Drop a pellet Sub-rule End. Figure 16 Example of a Start-Stop trial rule for a water maze. The trial stops when the animal has been in the platform zone for at least 3 s without break, or the time since the start of tracking is 60 s. A - In zone condition that specifies that the animal must be for at least 3 seconds over the Platform zone. Select Current duration >=3s. B - Time condition that specifies a time of 60 s since the track started. C - "Any" operator box. Since the sub-rule is restarted immediately after the pellet has been dropped, it is possible that the animal is still on the top of the shelter, and a new pellet is dropped before the animal eats the previous one. Therefore, you must make sure that the sub- rule ends when the animal has visited the reward zone, so the sub-rule can be repeated from that moment onward. You can do this by defining a condition "In Feeder zone" that is met when the animal has been in the Feeder zone for at least 1 s without break (Current duration >=1 s). Place this box to the left of Rule End. 2. Create a Reference to the sub-rule (see page 57) and specify to have the sub-rule repeated 25 times. Place the resulting box at the left side of the Stop track box. Eight-arm radial maze: Stop the trial when the subject has been in four arms within 10 minutes. Combine eight conditions, one for each arm. At least four conditions must be met, no matter which arm the animal visits. 1. Create an In zone condition (see page 86) and specify that the Frequency for Arm 1 must be >=1. That is, the animal must have visited Arm 1 at least once. Do the same for each of the other arms. 2. Connect the resulting eight condition boxes in parallel using the N of All operator (see Figure 17). 3. Set the Maximum trial duration (see page 21) to 10 minutes to stop tracking in the case the animal fails to visit four arms in the meantime. For more information on operators of type N of All, see page 34. important The frequency of In zone can become high very easily when the animal walks along the edge of a zone. This may result in the condition being met sooner than expected. If that happens, increase the Zone exit threshold. If that does not help, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track. Figure 17 A Trial Control sequence for an eight-arm radial maze. The trial must stop when the animal has visited four of the arms at least once. zone for that arm is greater than or equal to 1. A - Operator that checks that at least four of the eight conditions are met. B- Stop track box. When four conditions are met, the trial is stopped. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 5 Sub-rules URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-5-sub-rules Chapter: EthoVision XT 5 - Sub-rules Sub-rules Use Sub-rules A sub-rule is a sequence of actions and conditions separated from the Start-Stop trial rule. You can view a sub-rule like a subroutine in a larger program, where the program is your Trial Control. You can have the sub-rule start at specific times or under specific conditions. Each criterion defined is a Start condition of the sub-rule. A sub-rule can be repeated, that is, when EthoVision finishes executing the instructions contained in the sub-rule, the program can start the sub-rule again from the beginning, for a specified number of times or until a condition is met. You can also have the same sub-rule called from different points of the Trial Control sequence. To do so, define multiple References to the same sub-rule (see page 57). Why use a sub-rule? A sub-rule is necessary when your trials involve repetition of tasks. For example, when the animal has to press a lever to obtain a reward, and you want to repeat that 50 times. This is not feasible within the Start-Stop trial rule. A sub-rule is also handy when your Trial Control logic is very complex, because it helps you have a clear overview of the phases within your trial. For example, different tasks within a trial can be kept separated and managed more easily. Figure 18 Schematic representation of the functioning of a Sub-rule along the time line. You can specify a sub-rule to start at specific Start conditions (for example: Start at 12:00). For each start condition, a sub- rule can be repeated one or more times (black bars). The white bars represent the time from the start condition to the last repeat. Note that sub-rule repeats can vary in duration, for example when the behavior of the subject determines when a condition defined in the sub-rule is met. Also note that a sub- rule repeat can only start at least one sample after the end of the previous repeat. 5 - Sub-rules Create A Sub-rule - In the Components pane, under Structures, double-click Sub-rule, or click the button next to it. - If the Add a sub-rule window appears, choose one of the following: Create a new sub-rule. This creates a new sub-rule. You will be asked to enter a unique name for this sub-rule. Reuse an existing sub-rule. Choose this option if you want to re-use an existing sub- rule. Select the existing sub-rule and, if necessary, the Trial Control Settings where it is stored. Note: You only copy the sub-rule name, the Rule Begin and the Rule End boxes, not the actions and conditions inside the existing sub-rule. See page 36 for re-using Trial Control elements. - Under Name, enter a name for the sub-rule. The default name is Sub-rule (n) where n is a progressive number. - Under Comment, enter a description of the sub-rule (optional). - Click OK. The sub-rule is displayed on your Trial Control screen. It consists of a Rule begin box and a Rule end box. - Complete the sub-rule by inserting the appropriate conditions and actions between the Rule Begin and Rule End boxes (see page 23). - Define a reference to this sub-rule (see the next section). Notes Sub-rule names. Names of sub-rules must be unique in your Trial Control Settings. You cannot define two sub-rules with the same Name, even if these are defined in two different Trial Control Settings. However, you can create a sub-rule with the same name of an existing sub-rule stored in other Trial Control Settings by Re-using it (see below). Re-using a sub-rule. If you choose to re-use a sub-rule and then change any property of this copy (Name or Comment), a window appears with the message Define the scope of your changes. The program asks you whether you want to apply the properties only to the newly-created sub-rule, or to the sub-rules with the same name in all Trial Control 5 - Sub-rules Settings. Choose the option you require and click OK. See also page 36 for information on re-using elements in Trial Control. Deleting a sub-rule. You cannot delete a sub-rule if at least one reference to that sub-rule is present in the Trial Control. You must first delete its reference. If you create a sub-rule without a valid reference, you can still acquire data but EthoVision informs you that trial control may not work as expected. Create A Reference To A Sub-rule A Reference calls the instructions contained in an existing sub-rule. 1. Make sure that the sub-rule has been defined in the Trial Control screen. 2. In the Components pane, under Structures, double-click Reference or click the button next to it. If the Add a reference window appears, choose one of the following, then click OK. Create a new reference. To create a new reference to a sub-rule. Reuse an existing reference. Choose this option if you want to make a copy of an existing reference. Select that reference and, if necessary, the Trial Control Settings where it is stored. For details on re-using elements, see page 36. 3. The Sub-rule Reference window appears. Under Name, enter a name for the reference. The default name is Reference (n), where n is a progressive number. 4. Under Reference, from the Reference to sub-rule list select the sub-rule you have defined in step 1 above. 5. Under Schedule, the Start conditions box shows Without delay. This means that, by default, the sub-rule starts as soon as the reference box becomes active. You can define one or more start conditions. Once the sub-rule starts according to Start condition, you can have it be repeated one or more times (see the picture under point 2 on page 49). Click the Add button to add a Start condition. The Add Start Condition window appears. 6. From the Select type list, select one of the following: Without delay. To start the subrule as soon as the reference is activated. 5 - Sub-rules Delay (default). To start a specific time after the reference becomes active. Enter this time in the Delay field. Clock Time. To start at a specific day and time. Trial Control variable. To start when a Trial Control variable gets a specific value. For details, see sub-rule start conditions on page 60. 7. Repeat steps 5-6 to add more start conditions. If you want to delete a start condition, select this and click the Delete button. 8. Under Stop conditions, select one of the options to specify whether you want the sub-rule to be repeated once or more times (see Sub-rule stop conditions on page 61). 9. If you select to repeat the sub-rule, the Repeat interval option becomes available. Select: Stop to Start (default). To keep a constant time between the stop of a repeat and the start of the next repeat. Start to start. To keep a constant time between the start of successive repeats. For example, start repeats at every hour. Enter this time in the corresponding box (hh:mm:ss). 10.Select one of the options to specify what to do when a new start condition becomes true and a previous repeat is still ongoing. For details, see 'Options for starting a new repeat' on page 62. 11. Under Comment, enter a description of the sub-rule reference (optional). 12. Click OK. The reference box is displayed on your Trial Control screen. 13. Insert the reference box in the appropriate place in the Trial Control sequence (this can be either the Start-Stop trial rule, or another sub-rule). See also page 63. Notes If you want the sub-rule not to start immediately as its Reference becomes active, select Without delay and click the Delete button. If you accept the default options (Without delay in the Start conditions box and one repeat), the sub-rule starts immediately and is repeated just once. You cannot edit a condition that you have added to the Start conditions box. Delete first the condition (select the condition and click the Delete button), then click Add to add a new condition. The Start conditions are listed in the following order: Without delay, Delay, Clock Time, Trial Control variable. Stop to Start of a repeat. There is always at least 1 sample difference between the time that the Rule End box is evaluated and the time that the Rule Begin box is evaluated for 5 - Sub-rules the start of a new repeat. This means that a new repeat can never start exactly at the same time as the end of a repeat. Reference names. Names of sub-rule references must be unique in your experiment, unless you have re-used an existing reference. You cannot define two sub-rule references with the same Name, even when these are defined in two different Trial Control Settings. This is because analysis of Trial Control data (see page 168) is based on names of elements (sub-rules, references, actions and conditions). Elements with the same name would give ambiguous results. Re-using a sub-rule reference. If you choose to create a copy of a sub-rule reference and then change any property of this copy (Name, Reference options, or Comment), a window appears with a message Define the scope of your changes. The program asks you whether you want to apply the properties only to the newly-created reference, or to the references with the same name in all Trial Control Settings. Choose the option you require and click OK. If you re-use a Reference that is stored in another Trial Control profile, and this profile is locked after data acquisition, changing any of the Reference settings will not affect the Reference in the locked profile. Modifying a sub-rule reference. To modify a sub-rule reference, click Settings button in the reference box. Multiple references to one sub-rule. You can define multiple references to the same sub- rule, and place the corresponding Reference boxes in the same Trial Control sequence. In the case they are activated at the same time, the program executes the sub-rule in two parallel instances. Such instances are independent, however they can interfere with each other if they both contain actions on a Trial Control variable (see an example on page 30) or on hardware devices. Endless loop - EthoVision XT prevents the occurrence of an endless loop in the Trial Control, which would make EthoVision XT unresponsive. When in a Sub-rule Reference box the number of repeats is not set to a fixed value and the Sub-rule has a 0-second duration, this Sub-rule is evaluated endlessly from the Sub-rule Reference box. To prevent this, in EthoVision XT a Sub-rule is evaluated only once per sample from the Reference box. Sub-rules that are empty, only contain a Trial control variable Action box or Hardware Action boxes, are 0-second Sub-rules. With a 0-second Sub-rule, the Sub- rule Reference box never becomes inactive and, therefore, the Stop track Action box and Rule End box are never reached. In this case, the trial is stopped when you click the Stop trial button (for Live and offline tracking) or when the end of the video file is reached (for offline tracking). 5 - Sub-rules Sub-rule Start Conditions To access those options, click Add in the sub-rule's Reference window. Without delay Choose this option to start the sub-rule as soon as the sub-rule reference becomes active. Clock Time Choose this option to start the sub-rule at specific times of the day. Select trial day. Select the day from the start of the trial that the sub-rule should start. 1st trial day= the same day that the trial starts. Set time (hh:mm:ss). Enter the time of the day that the sub-rule should start. example If you want to start the sub-rule at 12:00 h of the fifth day of the trial, select 5th day and enter 12:00:00. Delay Choose this option to start the sub-rule with a specific delay from the moment that the Reference box becomes active. example if you want to start the sub-rule one hour after the start of tracking, enter 01:00:00. Place the Reference box immediately to the right of the Start track box. The time that the Reference becomes active is essentially the time that the previous box in the sequence becomes inactive (a condition being met, or an action being taken). See page 10 for more information on how Trial Control instructions are executed. Trial Control variable Choose this option to start the sub-rule when a Trial Control variable gets a certain value for the first time since the Reference becomes active. 1. Click the Edit TC-variable button. The TC-variable condition window appears. 5 - Sub-rules 2. From the first list, select the Trial Control variable. If you need to create a new variable, click TC Variables (see page 28). 3. Select the comparison operator (=, >, etc.) from the second list. 4. Do one of the following: If you want to compare the Trial Control Variable with another variable, select that variable from the third list. If you want to compare the Trial Control variable with a numerical value, enter this value in the third list. If you want to compare a Trial Control variable with a formula, click the double-arrow button and select the operator, then the variable and/or values to complete the formula. example You have defined the variable Phase which can have one of three values 1, 2 and 3 during the trial. You want to start a sub-rule when the current value of Phase is 2. Select Phase = 2. If your variable is of the type true/false, and switches between true and false several times, the sub-rule starts only the first time that the variable gets the value required since the activation of the Reference. For more information on Trial Control variables, see page 28. Sub-rule Stop Conditions Execute sub-rule once per start condition (default) The sub-rule is executed once when one of the Start conditions is met. Repeat indefinitely (no scheduled stop) The sub-rule is repeated until trial the trial stops (see page 63 for how this can happen). Repeat per start condition The sub-rule is repeated a number of times, or until a condition is met. 5 - Sub-rules For a number of times. To have the sub-rule repeated a fixed number of times for that start condition. Enter this number in the box (default= 2). For a duration of (hh:mm:ss). To have the sub-rule repeated for a specific time period beginning from the corresponding start condition. Enter this time in the box. The maximum time allowed is 99 h 59 min 59 sec. Choose this option if you want that a task is repeated for some time, mo matter how many times in that period. If you choose this option, when the time elapsed since the start condition exceeds the time set here, the ongoing repeat will continue till its end, but no new repeat will start. Until Trial Control variable. To have the sub-rule repeated until a Trial Control variable (see page 28) gets a certain value. Click Edit, specify the variable, its value and click OK. For example, repeat the sub-rule until the variable Count reaches 100. Specify Count <= 100. If you select two or more Repeat per start condition options, no more new repeats are started as soon as any of the conditions is fulfilled. A sub-rule is completed when the last repeat for the planned Start condition is ended. See also the note on Endless loops page 59. Options for starting a new repeat Do not start new repeat when there is still a repeat ongoing. A new repeat is not started. A new repeat will start at the planned time, after the ongoing repeat has been completed. Delay new repeat till ongoing repeat finishes. The repeat starts as soon as the ongoing repeat finishes. Terminate ongoing repeat and start new one. The ongoing repeat is ended no matter at which point it is, and a new repeat is started. example A sub-rule is planned to start every 10 minutes. The first Start condition is set to 12:00 h, the second to 12:20 h etc. Suppose that at 12:10, a repeat has not been completed yet, and it will be completed at 12:15. When selecting the first option above, the repeat planned at 12:10 is not started. The program will start the next planned repeat, at 12:20, provided that the first repeat has been completed. When selecting the second option, the repeat of 12:10 starts at 12:15 when the first repeat has been completed. 5 - Sub-rules When selecting the third option, the repeat of 12:10 starts at the planned time. The repeat of 12:00 is forcibly terminated. If Trial Control switches on a light or sound device at the time the repeat is aborted, that device stays on until a switch off command is encountered in the next repeat (or another ongoing sub-rule). Place The Sub-rule Reference In The Trial Control Sequence The position of sub-rule's Reference box influences progress in the Trial Control sequence. Consider the difference between the following two cases: Reference box in the linear sequence. Control can only progress when the Reference box becomes inactive. This occurs when the last repeat of the sub-rule has been completed. Reference box -n a dead branch of the sequence. When the sub-rule's Reference box becomes active, the box placed in parallel becomes active too. Thus, control moves forward independent of whether the sub-rule has been completed. For more information on activation of Trial Control boxes, see page 10. End A Sub-rule A sub-rule is normally ended when the last repeat (see page 57) is completed. However, it can also be forcibly interrupted in the following cases: When the maximum trial duration has been reached. When you stop the trial manually. 5 - Sub-rules When a condition passes control to the next box in the sequence. Consider the following case, where the Reference box is combined with a Condition box through an operator of the Any type. When the Condition is met, the Any operator applies the OR logic, and passes control to the next box. The sub-rule is interrupted. When the Reference box is placed on a dead end of Trial Control sequence. Consider the following example: The right-hand side of the Reference box is not connected to any box of the Start-Stop trial rule. Therefore, the Reference box poses no limit to control that passes through the boxes in the Start-Stop Trial rule up to the Stop box. Depending on the instructions specified in the Start-Stop Trial rule, the trial may stop before the last repeat of the sub- rule is completed. Figure 19 Example of a sub-rule that is forcibly interrupted when a condition is met. Figure 20 Example of a sub-rule that does not interrupt the Start- Stop Trial rule. 5 - Sub-rules When the last repeat of the sub-rule is ended, the corresponding Reference box becomes inactive. See also the note about Endless loops on page 59. Call A Sub-rule From Another Sub-rule Within a sub-rule, you can define a reference that calls another sub-rule. Why insert a sub-rule within another sub-rule?. Suppose that your Trial Control is made of four sub-rules that have at least some instructions in common. For example, sub-rules that start at different times, but include the instructions to have the program make a light flash. In such a case, you can define the instructions for the light flash in a separate sub-rule, and then in each of the four sub-rules insert a reference to this sub-rule. 1. Define the sub-rule that should contain the reference to another sub-rule (see page 55). 2. Define the sub-rule that should be called by the first one, and its own reference (see page 57). 3. Insert the Reference box of the second sub-rule in the sequence of the first sub-rule. Example of calling a sub-rule from another sub-rule Sub-rule 1 counts the number of times the animal enters the shelter via a particular route. When the animal does so (Condition A in Figure 21), a Reference box (B) calls Sub-rule 2. Figure 21 An example of sub-rule called from another sub-rule. Sub-rule 1 (top) calls Sub-rule 2 (bottom) when the mouse enters the shelter via a particular entry. A - Zone transition condition "Mouse enters the shelter via Entry zone 1" is met (A). B - Reference to Sub-rule 2. C - Action "Light on", followed by a Time condition "0.5 s" and an action "Light off". 5 - Sub-rules Sub-rule 2 is a sub-rule defined to switch a light on for 0.5 seconds (see C for details). As soon as Sub-rule 2 is completed, control is taken back to Sub-rule 1 where the remaining instructions are executed. Notes You can call sub-rules in up to 4 levels of existing sub-rules: for example, you can define the Start-Stop trial rule calling Sub-rule 1, which on its turn calls Sub-rule 2, which on its turn calls Sub-rule 3 etc, but you cannot have Sub-rule 4 calling Sub-rule 5. EthoVision XT informs you when you try to create more than 4 levels of sub-rules. If a sub-rule includes the reference to another sub-rule, it cannot be completed until the sub-rule that is called within it has been completed. You cannot create circular references amongst sub-rules. For example: Insert a reference in the sub-rule that this reference calls. In Sub-rule 1, insert a reference to Sub-rule 2, which on its turn contains a reference to Sub-rule 1. EthoVision XT informs you when you try to create a circular reference. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 6 Conditions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-6-conditions Chapter: EthoVision XT 6 - Conditions Conditions A condition can be based: On Time (see below) or a Time interval (see page 69). On a Trial Control variable (see page 71). On a Dependent variable like Distance moved, In zone, Mobility, etc. (see page 72). A combination of dependent variables, like "is the subject moving above a certain speed and is it in a certain zone?" (See page 101. On a Manually-scored behavior (see page 78). On a Hardware device (see page 79). Conditions Based On Time With a Time condition, some time must elapse before the next Trial Control box is evaluated. 1. In the Components pane, under Conditions, double-click Time or click the button next to it. The Time condition window opens. 2. Under Name, enter a Condition Name. 3. Select one of the following options: After. To have an action been taken some time after the condition becomes active. For the meaning of condition becoming active, see page 11. example Start tracking after two seconds. After a random time. To have an action been taken with a delay chosen randomly between two time limits. Enter the lower and higher limits and choose the time unit (seconds, minutes or hours). The random value is counted from the moment the condition becomes active. 6 - Conditions Choose this option when programming rewards in a variable interval schedule. example When a random time between 10 and 30 seconds has elapsed (condition), drop a food item (action). At clock time. To have an action been taken at an absolute time (hh:mm:ss). example At 12:00 AM (condition), start tracking (action). note If you want start tracking at 12:00 AM of the next day, and you click Start Trial in the afternoon of the current day, EthoVision XT starts tracking immediately because it sees that the condition 12:00 AM has been met already. For how to solve this, see the topic Start and stop the trial at specific clock times in the EthoVision XT Help. Infinite time (condition never met). To wait indefinitely (see the note below). 4. Insert a Comment (optional) and click OK. 5. The Condition box appears in the upper-left corner of the Trial Control screen. Insert it in the appropriate position in the Trial Control sequence. For information on how to insert a Trial Control box, see the EthoVision XT Help. Notes If you want to stop a trial after a specific time has been reached, see page 21. If you track from video files, see the note Tracking from video files under apply trial control to your trials on page 45. Figure 22 The Time condition window. 6 - Conditions The format for clock time is hh:mm:ss where: hh = hours, 24-hour format with leading zero, mm = minutes with leading zero, ss = seconds with leading zero. If you choose clock times, be aware of changeover between wintertime to summertime and vice versa. For example, the time 02:30:00 is encountered twice on the day of onset of wintertime, or never on the day of onset of summertime. The Infinite time option is handy in the following cases: When you want to stop tracking manually. Place the resulting box immediately to the left of the Stop track box. When two sequences have been placed in parallel, and you want the program to take further actions when Sequence 1 has been completed, independent of Sequence 2. Place a Time condition with the Infinite time option immediately to the right of Sequence 2. Combine Sequence 1 and the Time box with an Any operator (see page 34). important If you combine an Infinite time condition with an All operator, the program does not go further in the Trial Control rule, as it waits forever for the condition to be met! Conditions Based On A Time Interval A Time interval condition makes sense when it is combined with another condition. For example: Take an action when the animal is found in Zone A (In zone condition) between 5 and 10 minutes (interval condition). 1. In the Components pane, double-click Time interval or click the button next to it. The Time interval Condition window opens (see Figure 23). 2. Under Name, enter a Condition Name. 3. Condition is met: Between. Define an interval between two time points (x and y seconds, minutes or hours). Enter the time values and choose the time units. Note: The time points are counted from the time that the condition box becomes active, not from the start of the trial or tracking. For the meaning of active, see page 11. Between clock times. Define an interval between two absolute time points, e.g., in the previous example, stop the track when the rat is in quadrant A between 12:00:30 and 6 - Conditions 12:01:00. The time format is hh:mm:ss where hh = hours, 24-hour format with leading zero, mm = minutes with leading zero, ss = seconds with leading zero. 4. Insert a Comment (optional) and click OK. 5. The Condition box appears in the upper-left corner of the Trial Control screen. Insert it in the appropriate position in the Trial Control sequence. For how to do this, see the EthoVision XT Help. Notes Combining Time interval and Zone conditions. In a conditioning experiment, the researcher wants to drop a food reward when the animal is found on its shelter some time between 30 s and 60 s from the previous action (for instance, a cue light being switched on). To do this, a Time interval condition must be defined that specifies the interval between 30 s and 60 s. This condition must be met at the same time as the condition "subject on shelter" in order to drop a food pellet. Therefore, the two condition boxes must be placed in parallel with an operator of type All. Be aware when using Time interval conditions combined with operators or type All. If the animal enters a zone after the upper time limit, the condition is never met, thus Trial Control does not progress. Figure 23 The Time interval condition window. 6 - Conditions Conditions Based On A Trial Control Variable A condition based on a Trial Control variable is essentially the comparison between a Trial Control variable and a value, another variable or a formula at the time the condition becomes active and is evaluated (for the meaning of becomes active, see page 11). 1. In the Components pane, under Conditions, double-click Trial Control variable or click the button next to it. tip If you do not see Trial Control Variable, click the More button. 2. In the Trial Control Condition window, under Name, enter a Condition Name. 3. Under Condition is met when, select the Trial Control variable from the first list. If the variable has not been defined yet, define it first by clicking Variables (see page 28). 4. Select the comparison operator (=, >, etc) from the second list. 5. Do one of the following: To compare the Trial Control Variable with another variable, or a numerical value, select that variable/value from the third list. To compare a Trial Control variable with a formula, click the double-arrow button and select the operator, then complete the formula in the next list. For example: important Be careful using the operator "=". The comparison only takes place when the condition box becomes active. If the variable is updated in other boxes, then it may be so that this condition box is activated too early or too late. For example, if the condition is met when A= 4 and an Action box set the value to A= 5 before the condition box is activated, then the condition is never met. Rather use ">=" or "<=". 6. Insert a Comment (optional) and click OK. 7. Insert the Condition box in the appropriate position in the rule. For information on how to insert a Trial Control box, see the EthoVision XT Help. 6 - Conditions Conditions Based On A Dependent Variable - In the Components pane, under Conditions, double-click the name or click the button next to the dependent variable the condition is based on. For details about dependent variables, see page 84. tip If you do not see the variable name, click the More button. note The following variables are not available for creating conditions: Acceleration state, Activity state, behaviors scored with Behavior recognition. - In the condition window, under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). - Under Condition is met when, from the Statistic list choose the statistic on which the condition is based. See 'Selecting the Statistic' below. - Click the Settings button. A window opens with the variable properties. For the corresponding variable, see also page 84. If you track multiple subjects in one arena, see also Selecting the subjects on page 75. When finished, click OK in the variable window. - From the list next to is:, choose the comparison >=, =, or <=, to specify whether the statistic must be greater than, equal to, or smaller than a value x. Enter this value in the box. If you have chosen Current as a Statistic (step 3) for a discrete variable, choose between true and false. True means that the current state must be the one chosen in Settings, False means that the current state must not be the one chosen in Settings. - Click OK. Insert the Condition box in the appropriate position in the rule. For information on how to do this, see the EthoVision XT Help. The Body Points tab in the variable properties window is only available if your experiment is set to Nose-point, center-point and tail-base detection. Select the statistic Current. The value of the variable in the current sample. 6 - Conditions For example, if a condition based on Velocity is evaluated at sample n, Current is the velocity calculated for sample n. If you rather want to base the condition on the average velocity from the time of activation of the condition to the current time, choose Mean. The remaining statistics below are based on the values of the variable from the time the condition becomes active (see page 11 for what active means). Total. The total value of the variable (only for continuous variables like Distance or Velocity). This is the sum of all values of the variable up to that time. Mean. The mean value of the variable (only for continuous variables like Distance or Velocity) up to that time. Statistics like Minimum, Maximum, Standard error, Standard deviation and Variance are normally less obvious to use in a condition. For example, if you select Standard error for Distance moved, the program calculates the standard error of all distance values calculated between consecutive samples of the track up to that time. The condition is met when the standard error is greater than/equal to/less than the value specified. Frequency. The number of occurrences up to that time. This statistic is available for discrete (state) variables like Movement, and count variables like Rotation and Zone transition. Choosing >= or <= for frequency only makes sense when you combine the condition with another condition. Cumulative duration. The cumulative duration of a state from the start of tracking up to that time. You choose the state when clicking the Settings button. This statistic is available for discrete variables. Current duration. The duration the animal has been in that state (for example, in a specific zone or Mobile) taking only the current (uninterrupted) interval into account. You choose the state when clicking the Settings button. This statistic is available for discrete variables. Latency to first. The time from the activation of the condition to the first occurrence of the state of the discrete variable (for example In the zone becomes true for the variable In zone), or count variables like Rotation, or Zone transition. You choose the state when clicking the Settings button. A condition like Latency >= L or Latency <= L does not mean that the condition is met at time L if the first state, or occurrence does not occur within that time. The program first calculates when the first state or occurrence occurs, and then compares this with L. 6 - Conditions The following cases are an example of Latency to first In zone with L > 0 (see Figure 24, left). Once the condition becomes active, latency can get only one value, which is the time of the first In zone state: Case 1. The subject is already in the zone when the condition becomes active. The condition is NEVER met because latency of the first In zone is 0, thus smaller than L. Case 2. The subject enters the zone after the condition becomes active, but at a time < L. The condition is NEVER met because the latency is smaller than L. Case 3. The subject enters the zone after time L. This means that the latency of the first In zone is greater than L. The condition is met at that time. Case 4. The subject never enters the zone. The condition is NEVER met. Case 5. The subject enters the zone at a time < L, then exits the zone, then enters again at a time > L. The latency of the first In zone state is < L, thus the condition is NEVER met, no matter of how many times the animal enters the zone. Figure 24 Five possible cases of outcome of a condition based on Latency. This example refers to a state variable like "In zone", which has two possible states, In zone and Not in zone. The condition is met when Latency to first In zone =L (where L is the value set). A - Time of activation of the condition (see the picture on page 9 for the concept of activation). L - Latency set in the condition window. 6 - Conditions As you can see there are many cases in which the condition is never met, including Case 5 which is due to the fact that only the first instance of In zone is taken under consideration. Subjects In A Condition Select the subjects - In the Condition window, click the Settings button. In the variables properties window, click the Actors tab. In the Actors tab, you select the actors of the behavior. - Under Select, select the subject you want to base your condition on. If your condition is based on social interactions, select the focal subject in the Actors tab and the other subjects in the Receiver tab. Do so also for dyadic interactions (Subject 1 under Actors, Subject 2 under Receivers), For dependent variables with discrete values like In zone, Movement, Mobility, Elongation, Proximity, Body contact and Relative Movement, you can base your condition on the state of multiple subjects at the time the condition is evaluated. If you select two or more subjects, select one of the two options from the list immediately below the Select box: All selected Subjects. The state selected in the dependent variable properties window must be the same for all the actors simultaneously, in order for the condition to be met. Any selected Subjects. The state selected in the dependent variable properties window must be true for at least one actor in order for the condition to be met. 3. If the Actors tab also contains the Body points options, select one or more body points of the subjects selected above. 4. For the dependent variables of social interaction, a Receivers tab is also available. Click this tab and select the subjects that you have not selected under Actors (see an example below). 5. Click OK to confirm your selection. You return to the condition window (see page 72). 6 - Conditions Notes Example of choosing All selected Subjects. The researcher wants to define a In zone condition that is met when the subjects Subject 1 and Subject 2 have been in a zone simultaneously for at least one minute. Solution: In the Condition window, select Cumulative duration as Statistic and enter >= 60 s. Click Settings and select the zone you require, then click Actors and select Subject 1 and Subject 2, finally select All selected Subjects. Example of using Any selected Subjects. The researcher wants to define a Distance to zone condition that is met when one of the two subjects is at less than 5 cm from a novel object. Solution: In the Condition window, select Current and enter <= 5 cm. Click Settings and select the novel object zone, then click Actors and select Subject 1 and Subject 2, finally select Any selected Subjects. Example with Actors and Receivers. The researcher wants to define a condition that is met when the nose point of Subject 1 has been close to at least one body point of Subject 2 for more than one minute. Solution: Click the button next to Proximity and in the Condition window, select Cumulative duration and enter f. Click Settings, then: In the Actors tab, select Subject 1 and de-select Subject 2. Under Bodypoints, select Nose-point only. In the Receivers tab, select Subject 2 and de-select Subject 1. Under Bodypoints, select all points and then Any selected points, since the condition must be met when Subject 1 is in proximity of at least one of the Subject 2's body points. When Is A Condition Met? Dependent variables are calculated for each sample. When a condition based on dependent variables is met, depends on a number of factors. Effect of outliers and track smoothing Dependent variables used in conditions are not smoothed or filtered using the Lowess filter or the Minimum distance moved as they can be for data analysis (see Smooth the tracks in the EthoVision XT Help). This means that outliers, nose-tail swaps or even subject identity swaps can have a severe effects on whether and when a condition is met. 6 - Conditions Consider the following track, where EthoVision detects a reflection within the zone A as the subject. As a result, the track has an outlier. If an In Zone condition is defined that specifies Frequency of In zone A >=1, then the condition is met at that time (assuming that the condition box was active). Smoothing would remove the outlier, but that can only be done when analyzing the data, not when Trial Control is active (that is during acquisition). If such an effect occurs, Track noise reduction may solve the problem. This is applying the Lowess filter during acquisition. In the Detection settings, click Advanced and under Smoothing set Track noise reduction to On. This smooths the track during acquisition, which means that the track is altered, which cannot be reversed afterwards. Effect of missing samples Missing samples can also make Trial Control to react later. For example, an In zone condition is met only when valid samples are found within the specified zone. Consider the following track, where EthoVision misses the subject some time before it enters the zone A. The dotted line represents a number of missing samples; the hatched square is the first valid (non-missing) sample, found in the zone). If an In zone condition is defined that specifies Current of In zone A = true, then the condition is met later than it would be if there were no missing samples. Interpolating would remove the missing samples, but that can only be done when analyzing the data, not when Trial Control is active (that is during acquisition). 6 - Conditions If an In zone condition states "Cumulative duration of not in zone for more than 1 s" (here we assume that a sample rate of 5/s is used, so 5 samples make up 1 second), then the condition does not become true, because there are only 4 samples for which the state "not in zone" was true (see the 4 samples outside the zone). Similarly, the condition "Current value of In zone A = false" may become true during the state "not in zone". However, it won't become true in the period of missing samples. Below you find information on each dependent variable. We assume that the Condition window is open on your screen (step 4 on page 72). Effect of the statistics used When a condition is evaluated (and therefore may or may not be met) also depends on the statistic chosen. For Current, the condition is evaluated at the same sample time as when it is activated (for the meaning of "active", see page 11). For all other statistics (like Frequency, Current duration, etc.), it is evaluated at least one sample after the condition is activated. This depends on when the first value available for comparison occurs after the activation of the condition. When using Velocity, and Distance, it takes one sample. When using Heading and In zone, it takes two samples. When using Turn Angle and Angular velocity, it takes three samples. Conditions Based On Behaviors Scored Manually Use this kind of conditions to let EthoVision XT carry out an action when the subject performed a behavior you scored manually. For example, in a social interaction test, to stop tracking when the subject attacked three times, or when the duration of Intimidation lasted more than 30 seconds. 1. In the Components pane, under Conditions, double-click the name or click the button next to the manually scored behavior you want to base the condition on. tip If you do not see the variable name, click the More button. 6 - Conditions 2. The Manual Scoring Condition window opens. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). 3. Under Condition is met when, click the Settings button. If the behavior is of the type Start- Stop or Mutually Exclusive, choose the behavior to base the condition on, for example Rear or Not Rear. 4. In the Actors tab, select the Subjects to which the condition applies. See subjects in a condition on page 75. If the Actors tab also contains the Body points options, select one or more body points of the subjects selected above. Click OK. 5. Under Condition is met when, select the Statistic you want to use. Common cases of Statistic for manually scored behaviors: Current. For a condition that is met when the behavior at the current sample is true or not true. This statistic is available for Start-Stop and Mutually exclusive events. Frequency. For a condition that is met when the behavior occurred a number of times. Cumulative duration. For a condition that is met when the animal has shown the behavior for a specific time since the activation of the condition. This statistic is available for Start-Stop and Mutually exclusive events. Current duration. For a condition that is met when the animal has shown the behavior continuously for a specific time. This statistic is available for Start-Stop and Mutually exclusive events. Latency to first. See page 73 and Figure 24 on page 74. For more information on manually scored behaviors, see the EthoVision XT Help. Conditions Based On Hardware Devices Use this kind of conditions to check the status of hardware devices (pellet dispensers, lickometers, etc.) and have EthoVision take actions when the conditions are met. 1. In the Components pane, under Conditions, click the button next to the hardware device you want to base the condition on. 6 - Conditions 2. The Hardware condition window appears. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). 3. Under Condition is met when, select the Template device you want to use. A template device represents a group of devices of the same type, one for each arena. For more information, see page 105. 4. Under Signal to check, select the criterion that forms the condition. 5. Under Signal value, select the value of the criterion in order for the condition to be met. 6. Click OK. Insert the Condition box in the appropriate position in the rule. For information on how to do this, see the EthoVision XT Help. Hardware devices are not defined for each arena separately. If you have a setup with multiple arenas, it is assumed that each arena has the same type of device. The name in the device list is the generic name valid for all arenas. The condition will be evaluated for each arena separately. If the device type is not listed under Conditions, it means that it is not yet recognized by EthoVision XT. See also page 104. Pellet dispenser Number of drops. To base your condition on whether more/less than N food items have been delivered since the activation of the condition. Choose >= or <= and enter the value N in the box. In error state. To base your condition on whether the pellet dispenser is in error state, that is, when it can no longer drop any pellet (this happens when there are no pellets anymore in the feeder). Choose between true (error) or false. example Have EthoVision XT give a sound signal when the feeder has run out of pellets. Lickometer Duration of licks. To base your condition on the (total) duration of licks since the activation of the condition. Enter this time in the box. Number of licks. To base your condition on the number of licks since the activation of the condition. You can select >= N, <= N or = N. Top Unit of PhenoTyper Choose the option under Signal to check to base your condition on whether a sound or light signal is given since the activation of the condition. For Top Unit (NeuroBsik), use Is Fsel-1/2 on/off, Is Vol-1/2 on/off to base your condition on the value of frequency or volume specified by one input. Since the frequency and volume 6 - Conditions are specified by two inputs, you must define two conditions, one for input 1 and one for input 2. Combine the two conditions with an operator of type All. note Neuro-Bsik is a consortium of eleven Dutch Neuroscience research groups and two companies including Noldus. The consortium aims to contribute to the battle against brain disorders by developing novel mouse models for brain disorders. For this project, Noldus has developed a special Top Unit of the PhenoTyper cage that can produce ultrasound stimuli. For more information, browse to www.neurobsik.nl. For more information, see the PhenoTyper - EthoVision XT 17 - Reference Manual. TTL Port Tester Button 1/2 presses. To base your condition on the number of presses of button 1 or 2 given since the activation of the condition. You can select either >= N, <= N, or = N. Enter the value N in the box. Is button 1/2 pressed?. To base your condition on whether the button 1 or 2 is currently pressed. Select true or false from the list below. Is light 1/2 on?. To base your condition on whether the light 1 or 2 is currently on. Select true or false from the list below. Beam controller Beam 1/2 breaks.To base your condition on the number of beam breaks for beam 1 or 2 since the activation of the condition. You can select either >= N,<= N, or =N. Enter the value N in the box. Is Beam 1/2 broken?. To base your condition on whether beam 1 or 2 is currently broken. Select True or False from the Signal value list. Is cue 1/2 on?. To base your condition on whether the cue 1 or 2 is currently on. Select true or false from the Signal value list. Activity wheel counter Quarter cycles.To base your condition on the number of quarter cycles since the activation of the condition. You can select either >= N,<= N, or =N. Enter the value N in the box. Custom hardware device This includes the illuminated shelter. Input 1/2 L/H -> H/L count. To base your condition on how many times there has been a transition from High to Low (or vice versa) in input 1 or 2 during the time t-1 to t, where t 6 - Conditions is the sample time when the condition is evaluated. Choose the option that applies, select either >= N or <= N. Enter the value N in the box. This option let you create a condition based on events (transitions) in the signal, no matter when they happen during the sample time. See the note below. Is input 1/2 High/Low?. To base your condition on whether the current state of input 1 or 2 is High or Low at the sample time when the condition is evaluated. Select the option that applies, and then either true or false. Is output 1/2 High?. To base your condition on whether the current state of output 1 or 2 is High at the sample time when the condition is evaluated. Select the option that applies, and then either true or false. This option evaluates the state of the signal (High vs Low) at the sample time when the condition is evaluated. If a quick transition High -> Low -> High occurs within the sample interval, this is not noticed; the state at the sample time is still High. See the note below. Counts vs. signals: effects on conditions Consider the two conditions based on the same input (for example Input 1): Is the number of transitions H->L ≥ 1? Is the state of the signal Low? There is a fundamental difference between the two conditions. In the first condition, the software counts the number of transitions "Hight" to "Low" during the sampling interval (that is, from t-1 to t). The condition may become true or stay false for sample t, depending on that value. In the second condition, the signal is evaluated at time t, that is, at the end of the sampling interval. If short transitions occur from "High" to "Low" to "High" again, the "Low" signal is not detected by this condition, because the signal is still high at time t. Consider the cases 2 and 4 in the figure below. 6 - Conditions Figure 25 An example of how two conditions which may seem equivalent give different results. The thick line represents the Input signal from a hardware device (a similar example could be made with Output signals). The red dots represents samples in EthoVision XT. Four cases are presented. 1. The signal changes from High to Low. The two conditions (see text) are both true at the time of evaluation. 2. The signal changes from High to Low to High within the sample time. The instance of "Low" is not detected by the condition based on the signal ("Is Input Low?"), because the signal value at the time of evaluation is High. 3. Similar to case 1. 4. Similar to case 2. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 7 More about conditions based on dependent variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-7-more-about-conditions-based-on-dependent-variables Chapter: EthoVision XT 7 - More about conditions based on dependent variables More About Conditions Based On Dependent Variables In this section you find details and examples of the statistics you can use for your condition (step 3 on page 72). For more information on a dependent variable, see the EthoVision XT Help. note Dependent variables of Live Mouse Tracker and the social variables Train and Side by side are not available in the Trial Control Settings. Distance Moved Frequently-used statistics Current (default). To base your condition on the distance between the previous sample and the current one. This value depends on the chosen sample rate. Use Current velocity instead. Total. To base your condition on the distance traveled from the moment the condition becomes active up to that point. Mean. To base your condition on the average distance traveled from one sample to the next calculated from the activation of the condition box up to that time. This depends on the sample rate. Use Mean velocity instead. Effect of hidden zones. When the animal is in a hidden zone, the distance moved for the first sample in the hidden zone is based on the distance between the last location where the animal was detected and the center of the hidden zone. This is typically a relatively large distance, which can result in the condition becoming true. Effect of outliers (reflections). Detection of reflections may result in a too large distance moved and hence the condition being met. Velocity In the Condition window, click the Settings button. Choose the body point on which calculation of velocity is based, and the Averaging interval. For details, see Velocity in the EthoVision XT Help. 7 - More about conditions based on dependent variables Frequently-used statistics Current (default). For a condition that is met when the velocity at the current sample is <=/>= a specified value. Total. This does not have a physical meaning and depends on the sample rate. Choose Mean instead. Mean. For a condition that is met when the mean velocity since the activation of the condition is <=/>= a specified value. Notes Effect of hidden zones. When the animal is in a hidden zone, the Velocity for the first sample in the hidden zone is based on the distance between the last location where the animal was detected and the center of the hidden zone. This is typically a relatively large velocity, which can result in the condition becoming true. Effect of jitter. When the animal moves slowly, jitter plays a bigger role than at higher speeds. This can make velocity exceed the threshold set in the condition. Effect of outliers (reflections). Detection of reflections may result in a too high velocity and hence the condition being met. To prevent this from happening, increase the Averaging interval in the settings. Movement In the Condition window, click the Settings button. In the Movement tab, specify which threshold values of velocity specify the states Moving and Not moving. Optionally, choose an Averaging interval to smooth out random changes in velocity that do not reflect real movement. Frequently-used statistics Current. For a condition that is met when the animal's current state is either true (Moving) or false (Not moving). Frequency (default). For a condition that is met when the animal has moved/not moved a number of times. Cumulative duration. For a condition that is met when the animal has moved/not moved for a specific time since the activation of the condition. example A Movement condition is defined to stop tracking after 10 minutes of movement. If the animal moves during the first 2 minutes, stops moving for 3 minutes 7 - More about conditions based on dependent variables and then moves again without interruption. The track is stopped 13 minutes after the start. Current duration. For a condition that is met when the animal has moved/not moved continuously for a specific time. In the same example as above, the condition would be: stop tracking when the current duration of movement is 10 minutes. Tracking would stop when the animal had moved continuously for 10 minutes, that is 15 minutes after the start. Latency to first. See page 73 and Figure 24 on page 74. Acceleration In the Condition window, click the Settings button and choose the options you require. Frequently-used statistics Current (default). To base your condition on the current value of acceleration. Total. To base your condition on the total acceleration from the moment the condition becomes active up to that point. Note that this value does not have a physical meaning and depends on the sample rate. Choose Mean instead. Mean. To base your condition on the average acceleration. The average is calculated from the activation of the condition box up to that time. note Acceleration state is not available as condition criterion. However, you can create a Multi condition (page 101) that includes for example a condition "Acceleration > 10 cm/s2 for more than 1 second". This corresponds to a state variable based on Acceleration. In Zone In the Condition window, click the Settings button. Under In the following zones, select the zones of your choice. Under From following body points, select the body points of the animal that determine whether or not the animal is considered to be within a zone. Under Threshold, enter a Zone exit threshold to avoid that small movement of the body points across zone borders result in unrealistic scores of zone entries. Such movements are usually caused by body-point jitter, or the behavior of the subject (stretching, curling etc.). 7 - More about conditions based on dependent variables Frequently-used statistics Current. To base your condition on the presence of the animal in a zone at that time: either true (In zone) or false (Not in zone). Frequency (default). To base your condition on the number of times the animal has been in the zone. important The frequency of In zone becomes high very easily when the animal walks along the edge of a zone. This may result in the condition being met sooner than expected. If this happens, increase the Zone exit threshold. If that does not help, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track during acquisition, which means that the track is altered, which cannot be reversed afterwards. Cumulative duration. To base your condition on the cumulative duration the animal has been in the zone up to that time since the activation of the condition. example In a Novel Object Recognition test, stop tracking when the animal has been in the zone with the novel object for 30 seconds. After the activation of the condition, the animal spends the first 5 seconds in the zone with the novel object, then 10 seconds in the zone with the familiar object and 45 seconds in the zone with the novel object, the track is stopped 40 seconds after the activation of the condition (indicated by A). Current duration. To base your condition on the time the animal has been in the zone without interruption up to the current time. If in the example above, the condition had been defined as: stop tracking when the current duration in the zone is 30 seconds, the track would have been stopped 45 seconds after the activation of the condition. 7 - More about conditions based on dependent variables Latency to first - See page 73 and Figure 24 on page 74. Distance To Zone In the Condition window, click the Settings button. Under To the following zones, select the zones of your choice. Select Include if in zone if you want to calculate the distance to the border of a zone, regardless of whether the subject is outside or inside the zone. Under From the following body points, select the body point of the animal you want to use to calculate the distance. Frequently-used statistics Current (default). To base your condition on the current distance of the animal's body point to a zone. example Switch on a light when the current distance from the entrance of the shelter is less than 5 cm. Total. This depends on the sample rate. Choose Mean instead. Mean. To base your condition on the average distance of the animal's body point to a zone measured since the activation of the condition. example Stop the track when the average distance from the zone with the novel object is smaller than or equal to 10 cm. Distance To Point In the Condition window, click the Settings button:. Under To the following points, select the points or center of zones of your choice. If you select two or more points, the condition is based on the shorter distance between those points and the animal's body point. Under From the following body points, select the body point of the animal you want to use to calculate the distance. Frequently-used statistics Current (default). To base your condition on the current distance of the subject from the point. Total. This has little physical significance. Furthermore, its value depends on the sample rate (the higher the sample rate, the greater the cumulative distance). Choose Mean instead. 7 - More about conditions based on dependent variables Mean. To base your condition on the mean distance from the point since the activation of the condition. Meander In the Condition window, click the Settings button. In the Meander tab, select whether you want the condition to be based on the Absolute (unsigned) or Relative (signed) meander. Select Head direction meander when you want to base your condition on the angles formed by the Head direction line, not the body points (these will be ignored). In the Body points tab, select the body point on which you want to base the definition of meander. Frequently-used statistics Current (default). To base your condition on the current meander value. Total. To base the condition on the value of Meander cumulated since the activation of the condition. Mean. To base your condition on the mean value since the activation of the condition. Target Visits And Errors Use Target visits and errors to control the trial based on the visits to target zones and errors (visits to non-target zones or target zone revisits). In the Condition window, click the Settings button. In the Target visits and errors tab, select the zones that are targets and non-target. Under Condition based on, select which variable you want to use. Frequently-used statistics Frequency (default). To base your condition on the occurrence/number of successes and errors since the activation of the condition. example Take an action as soon as the animal has made three errors entering three different non-target zones. From the Statistics list, select Frequency ≥ 3. Click Settings, select the non-target zones and then under Condition based on, select Non-target first visits. Note - When using first visits (target or non-target) in the condition, make sure that you enter a frequency less or equal to the total number of corresponding zones selected under Settings. For example, if you select Condition based on Target first visits and Frequency ≥ 3, make sure that you select at least three target zones under Settings. 7 - More about conditions based on dependent variables Latency to First. See page 73 and Figure 24 on page 74. Zone Alternation Use Zone alternation to create a condition based on alternation between specific zones. For example: stop tracking when the animal makes the ten alternations (A > B > C). In the Condition window, click the Settings button. In the Zone Alternation tab, select the zones of the alternation (for example A, B, C). Under Condition based on, select which variable you want to use. Select whether you want to consider only direct transitions. In the Body points tab, select which body points define the transition from one zone to the other. Frequently-used statistics Frequency (default). To base your condition on the occurrence/number of alternations or direct/indirect revisits in zones since the activation of the condition. example Take an action as soon as the animal has completed the tenth alternation. Click Settings, select the zones and then under Condition based on, select Alternations. From the Statistics list, select Frequency ≥ 10. Latency to First. See page 73 and Figure 24 on page 74. Zone Transition In the Condition window, click the Settings button. In the Zone Transition tab, click Add to define the zone sequence (for example A > B > C). Select whether you want to consider only direct transitions. Enter a Zone exit threshold to avoid that small movement of the body points across zone borders result in unrealistic scores of zone transitions. Such movements are usually caused by body-point jitter, or the behavior of the subject (stretching, curling etc.). In the Body points tab, select the body point that moves from one zone to the other. Frequently-used statistics Frequency (default). To base your condition on the occurrence/number of transitions between zones since the activation of the condition. example Take an action as soon as the animal has gone from the Middle zone to the Left Arm of a T maze five times (Frequency=5). important The frequency of Zone transition can become high very easily when the animal walks along the boundary between zones. This may result in the condition being 7 - More about conditions based on dependent variables met sooner than expected. If that happens, increase the Zone exit threshold. If this does not help, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track. Latency to First. example Take an action when the latency of the first transition from Zone A to Zone B is longer than 1 minute. See also page 73 and in the figure on page 74 replace the state In zone with a zone transition event. Heading Use Heading for a condition based on compass-like orientation, provided that the axis orientation in the Arena Settings has some biological meaning. See also the notes for Head direction on page 92. In the Condition window, click the Settings button. In the Body points tab, select the body point that you want to use to calculate heading. Frequently-used statistics Current (default). To base your condition on the current heading value. Mean. To base your condition on the mean value since the activation of the condition. Heading To Point In the Condition window, click the Settings button. Under Select, select the point (or zone center) that your condition is based on. Under For the following body points, select the body point for which heading is calculated. Frequently-used statistics Current (default). To base your condition on the current meander value. Mean. To base your condition on the mean value since the activation of the condition. example Take an action when the animal's Heading to the Entry zone is less than 5 degrees. Select Current as Statistic, <= 5°. Click Settings and specify Entry zone (center). To restrict the condition to when the animal is moving, create a condition based on Movement, and combine the two conditions with an operator of type All. 7 - More about conditions based on dependent variables Note that Heading is about movement. If you want to create a condition based on the animal's head orientation, use Head directed to zone (see below). Head Direction Use Head direction for a condition based on compass-like orientation. Since Head direction depends on the orientation of the axes in the Arena Settings, Head direction make sense if the axis orientation has biological significance. If the animal must point to a zone or point, use Head directed to zone. Frequently-used statistics Current (default). To base your condition on the current value of head direction. Mean. To base your condition on the average head direction angle up to that time. We advise you to specify a range of Head direction, using two conditions (one specifying >=, the other <=). Then, combine the conditions with an operator of type All. example If the x axis points to North, then to make a condition that is met when Head direction is between NE and NW, combine: A condition that states Current Head direction <= +90°. A condition that states Current Head direction >= -90°. Head Directed To Zone In the Condition window, click the Settings button. Under Zone of interest, select the zone or point that your condition is based on. Under Calculate when, specify to calculate the variable only when the animal (or one of its body points) is in a specific zone. We advise you to define a zone around the focal zone/point, so the variable is calculated only when the animal is near the focal zone. Frequently-used statistics Frequency (default). To base your condition on the number of times the animal's head points to a zone (or point). Current. To base your condition on whether the animal's head points to a zone (or point). example Take an action when the animal's head is directed to the novel object. 7 - More about conditions based on dependent variables By selecting Current, the condition will become true as soon as the animal's head points to a zone for an instant. If you want to make the condition become true when the animal's head points to a zone for some time, use Current duration instead. Cumulative duration. To base your condition on the cumulative time that the animal points to a zone or point since the activation of the condition. Current Duration. To base your condition on the time that the animal's head has been pointing to the zone without interruption up to the current time. For comparison, see the same for In zone (page 87). example Take an action when the animal's head is directed to the novel object for five seconds. Latency to first. See page 73 and Figure 24 on page 74. Turn Angle In the Condition window, click the Settings button. In the Turn Angle tab, specify whether the turn is Absolute (unsigned) or Relative (signed). Select whether you want to calculate the Head direction turn angle (body points will be ignored). In the Body points tab, select the body point that you want to use to calculate Turn angle. Frequently-used statistics Current (default). To base your condition on the current value. Total. To base your condition on the cumulative value (whether absolute or relative) since the activation of the condition. Mean - To base your condition on the mean value (whether absolute or relative) since the activation of the condition. Because the way turn angle is defined, the first value available for comparison occurs at the third sample (hatched square) after the condition has become active (black square). 7 - More about conditions based on dependent variables Angular Velocity In the Condition window, click the Settings button:. In the Angular velocity tab, specify whether the turn is Absolute (unsigned) or Relative (signed). Select whether you want to calculate the Head direction angular velocity (body points will be ignored). In the Body points tab, select the body point that you want to use to calculate Angular velocity. Frequently-used statistics See Turn angle above. Because Angular velocity is based on Turn angle, the first value available for comparison occurs at the third sample after the activation of the condition (see above). Activity With Activity you can create a condition based on the change in pixels in the whole arena (thus not only in the detected body area) between samples. When properly set, this pixel change is supposed to be a measure for the subject's activity (for example, it is low when the subject freezes). Frequently-used statistics Current - The percentage pixel change in the arena relative to the previous sample. Total - The total percentage pixel change in the arena, from the moment the box becomes active (see Figure 3 on page 11) onwards. Mean - The mean percentage pixel change in the arena, from the moment the box becomes active (see Figure 3 on page 11) onwards. Set the Threshold in the field next to Is:. Click the Settings tab and specify the Averaging interval. important If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings, your rule becomes invalid. The Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. Redesign your Trial Control rule and connect the arrows between the boxes. note Activity state is not available as condition criterion. However, you can create a Multi condition (page 101) that includes for example a condition "Activity > 10% for more than 1 second". This corresponds to a state variable based on Activity. 7 - More about conditions based on dependent variables Body Elongation In the Condition window, click Settings and specify the Averaging interval Frequently-used statistics Current. To base your condition on the current value. For example, the condition is true when Body elongation < 50%. Total. This does not have a physical meaning and depends on the sample rate. In most cases you will need the statistic Current instead. Mean. For a condition that is met when the mean Body elongation since the activation of the condition is <=/>= a specified value. Like Total, this statistic does not have a "physical" meaning. In most cases you will need the statistic Current instead. Body Elongation State In the Condition window, click the Settings button. Specify the Thresholds and the Averaging interval that define the three Elongation states. Under Condition based on, select the state you want to base the condition on: Stretched, Normal, or Contracted. Frequently-used statistics Current. To base your condition on the current elongation state. example Take an action when the animal's state Contracted = True. Frequency. To base your condition on the number of times the selected elongation state occurred. Current duration. To base your condition on the duration of the current Elongation state. Cumulative duration. To base your condition on the cumulative duration of the Elongation state. Latency to first - See also page 73 and Figure 24 on page 74. To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen Elongation state. example Take an action when the latency of Stretched is longer than one minute. The condition is met when the animal is stretched, at least one minute from the moment the condition becomes active. 7 - More about conditions based on dependent variables Body Angle In the Condition window, click Settings and select Absolute angle (0° - 180° for the body bent either clockwise or counterclockwise) or Relative angle (0° - 360°). Frequently-used statistics Current. To base your condition on the current value. For example, the condition is true when Body angle > 20°. Total. This does not have a physical meaning and depends on the sample rate. In most cases you will need the statistic Current instead. Mean. For a condition that is met when the mean Body angle since the activation of the condition is <=/>= a specified value. Like Total, this statistic does not have a "physical" meaning. In most cases you will need the statistic Current instead. Body Angle State In the Condition window, click the Settings button. Specify the Threshold and the Averaging interval that define the four Body angle states. Under Condition based on, select the state you want to base the condition on: Straight, Bent, Bent counterclockwise, or Bent clockwise. Frequently-used statistics Current. To base your condition on the current body angle state. example To take an action when the animal's current state Bent counterclockwise = True. Frequency - To base your condition on the number of times the selected body angle state occurred. Current duration. To base your condition on the duration of the current body angle state. Cumulative duration - To base your condition on the cumulative duration of the body angle state up to that time. Latency to first - See also page 73 and Figure 24 on page 74. To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen Body angle state. example Take an action when the latency of Bent is longer than one minute. The condition is met when the animal is bent, at least one minute from the moment the condition becomes active. 7 - More about conditions based on dependent variables Mobility With Mobility you can create a condition based on the change in the detected shape between the previous sample and the next one, expressed in percentage. Frequently-used statistics Current - The percentage change in the detected body area in comparison with the previous sample. Total - The total percentage change in the detected body area, from the moment the box becomes active (see Figure 3 on page 11) onwards. Mean - The mean percentage change in the detected body area, from the moment the box becomes active (see Figure 3 on page 11) onwards. Set the Threshold in the field next to Is:. Click the Settings tab and specify the Averaging interval. Mobility State In the Condition window, click the Settings button. Specify the Thresholds and the Averaging interval that define the three mobility states. Under Calculate nesting for, select Highly mobile, Mobile, or Immobile. Frequently-used statistics Current. To base your condition on the current mobility state. example Take an action when the animal's current state Immobile = True. Frequency - To base your condition on the number of times the selected mobility state occurred. Current duration. To base your condition on the duration of the current mobility state. Cumulative duration - To base your condition on the cumulative duration of the selected mobility state up to that time. Latency to first - See also page 73 and Figure 24 on page 74. To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen Body angle state. example Take an action when the latency of Highly mobile is longer than one minute. The condition is met when the animal is highly mobile, at least one minute from the moment the condition becomes active. 7 - More about conditions based on dependent variables Rotation In the Condition window, click the Settings button. In the Rotation tab, specify the criteria to define a rotation. Select Body axis rotation when you want to base the condition on the rotation of the body axis, rather than that of body points. In the Body points tab, select the body point you want to use to calculate rotation. Frequently-used statistics Frequency - To base your condition on the number of rotations occurred. Latency to first -To base your condition on the time from the moment the condition becomes active to the first rotation. See also page 73 and Figure 24 on page 74. example Stop tracking when the first rotation event occurs less than one minute from the moment the condition becomes active. Javascript Variables In the Condition window, click the Settings button and enter the JavaScript code that, when processed during acquisition, produce an output value. The condition will compare that value with those in the settings. This value can be Continuous, a State or an Event depending on which JavaScript variable you use. In the Actors tab, select the subject for which to calculate the JavaScript variable value. example You want to create a condition that is based on the body area of the subject. Because EthoVision XT does not provide the body area in the Trial Control Settings, you can extract this value with a JavaScript variable of type Continuous that contains the command GetArea*() (for details, see the EthoVision XT Help). The condition could be for example "Body area > 2000" where 2000 is specified in the condition settings. A few more examples: Create a condition that becomes true when the Body length exceeds a specific value for some time. Create a condition that becomes true when the number of subjects in a zone exceeds a specific value. Create a condition that becomes true when the distance of a focal subject to the nearest neighbor is smaller than a threshold value. tip On the download page of My.Noldus.com you find some examples of JavaScript variables. Browse to my.noldus.com (either log in or register first), then choose Downloads > EthoVision XT > Drivers and Tools. Download the file EthoVision XT 17 - JavaScript custom variables.zip. Contact Noldus if you need to define a special variable. 7 - More about conditions based on dependent variables Distance Between Subjects In the Condition window, click the Settings button. In the Actors tab, select the subject and its body point that you want to use to calculate the distance to another subject. In the Receivers tab, select the other subject and its relevant body points (see also page 75). example To make an action when ano-genital sniffing takes place, use a condition box with a minimal distance between the nose point of one subject and the tail base of the other. Select Current as Statistic, then click Settings. Under Actors, select the focal subject and Nose-point. Under Receivers, select the other subject and Tail-base. Proximity In the Condition window, click the Settings button. In the Proximity tab, specify the criteria to define proximity. In the Actors tab, select the focal subjects and their body points that you want to use to calculate proximity to other subjects (Receivers). In the Receivers tab, select the other subjects and their relevant body points (see also page 75). For dyadic interactions, select Subject 1 under Actors and Subject 2 under Receivers. Frequently-used statistics Current. To base your condition on the current proximity state. example Take an action when the nose-point of subject 1 is in proximity of tail-base of subject 2. Frequency - To base your condition on the number of times the subjects were in proximity of each other. Current duration. To base your condition on the duration of the current occurrence of In proximity. Cumulative duration - To base your condition on the cumulative duration of the selected proximity state up to that time. Latency to first - To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen proximity state. See also page 73 and Figure 24 on page 74. example Take an action when the latency of Nose point of subject 1 is in proximity of Tail base of subject 2 is longer than one minute. The condition is met when the nose point of subject 1 is in proximity of the tail base of subject 2, at least one minute from the moment the condition becomes active. 7 - More about conditions based on dependent variables Body Contact In the Condition window, click the Settings button. In the Body Contact tab, specify whether the condition is based on body contact or no contact. In the Actors tab, select the subjects that should be in contact (or not in contact) with any other for the condition to become true. From the Statistics list, choose the statistic to be used and the value that make the condition true. For example, if you want to create a condition that is met when body contact last 10 seconds without interruption, choose Current Duration >=10 s. Frequently-used statistics See the statistics for Proximity on page 99. note When you select multiple Subjects in the Actors tab, the condition is evaluated separately for each subject and then combined according to what you select from the With list. If you select Subject 1 and Subject 2 in the Actors tab, and select All selected subjects from the With list, the condition is met when both Subject 1 and Subject 2 are in contact with any subject (thus not necessarily in contact with one another). See also subjects in a condition on page 75. Relative Movement In the Condition window, click the Settings button. In the Relative Movement tab, specify at which maximum distance the subjects should be considered as 'interacting', and the criteria to define relative movement. In the Actors tab, select the focal subjects and their body points that you want to use to calculate relative movement to/from other subjects. In the Receivers tab, select the other subjects and their relevant body points (see also page 75). Frequently-used statistics See the statistics for Proximity on page 99. Net Weighted Movement In the Condition window, select Current as Statistic, then click Settings. In the Net Weighted Movement tab, specify at which maximum distance the subjects should be considered as 'interacting'. In the Actors tab, select the focal subject and its body point that you want to use to calculate net relative movement to/from another subject. In the Receivers tab, select the other subject and its relevant body points (see also page 75). 7 - More about conditions based on dependent variables Weighted Movement From In the Condition window, select Current as Statistic, then click Settings. In the Weighted Movement From tab, specify at which maximum distance the subjects should be considered as 'interacting'. In the Actors tab, select the focal subject and its body point that you want to use to calculate weighted movement from another subject. In the Receivers tab, select the other subject and its relevant body point (see also page 75). Weighted Movement To In the Condition window, select Current as Statistic, then click Settings. In the Weighted Movement To tab, specify at which maximum distance the subjects should be considered as 'interacting'. In the Actors tab, select the focal subject and its body point that you want to use to calculate speed of moving to another subject. In the Receivers tab, select the other subject and its relevant body points (see also page 75). Conditions Based On Multiple Dependent Variables Use a Multi condition to let EthoVision carry out an action when the subject performs a combination of behaviors. For example, to stop tracking when the subject's nose point has been in the novel object zone while having its head directed to the object for 20 seconds. 1. In the Components pane, under Conditions, double-click the name or click the button next to the Multi condition. tip If you do not see the variable name, click the More button. 2. The 'Multi Condition' Condition window opens. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). 3. Click the Settings button. In the Actors tab, select the Subjects to which the conditions apply. See subjects in a condition on page 75. 4. Click Add Condition. Select a dependent variable from the list. Click the Settings button and specify the details for this condition. See the paragraph on using this dependent variable as condition for details. 7 - More about conditions based on dependent variables 5. In the Is: field, specify the criteria, for example When nose-point is in zone Novel Object = True. 6. Repeat steps 4 and 5 for 0ther conditions. 7. From the list at the bottom select whether all conditions or one of them should be met. Click OK. 7 - More about conditions based on dependent variables 8. Under Condition is met when, select the Statistic you want to use. Frequently-used statistics Current. For conditions that are met when the dependent variables are true or not true at the current sample. Frequency. For conditions that are met when the dependent variable values occurred a number of times. Cumulative duration. For conditions that are met when the dependent variables values occurred for a specific time since the activation of the condition. Current duration. For conditions that are met when the dependent variable values occurred continuously for a specific time. Latency to first. See page 73 and Figure 24 on page 74. You cannot use conditions based on hardware devices in multi conditions. If you want to use multiple conditions with hardware devices, use multiple condition boxes with an Operator instead. See operators on page 34. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 8 Control hardware devices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-8-control-hardware-devices Chapter: EthoVision XT 8 - Control hardware devices Control Hardware Devices Devices Supported In Ethovision Xt Noldus Pellet dispenser. Noldus Pellet receptacle. Noldus Lickometer. Top Unit of PhenoTyper. DanioVision Observation Chamber. PhenoWheel. Activity wheel counter and brake. Noldus Backlight unit with white light. Beam controller for the Mouse Feeding Monitor. Third-party and custom hardware devices. This includes any device that can be controlled with signal of TTL type. For example: The Illuminated shelter. The Ugo Basile Fear Conditioning System. The Prizmatix optogenetics setup. The Inscopix nVista Calcium imaging system (see page 151). Med Associates devices (see page 108). TTL Port tester. Additional manuals For PhenoTyper and Noldus devices, see the PhenoTyper - EthoVision XT 17 - Reference Manual and PhenoTyper - EthoVision XT 17 - Service Manual. For the Ugo Basile Fear Conditioning System, the optogenetics setup and the Inscopix Calcium imaging systems, see the EthoVision XT 17 - Application Manual. For the DanioVision Observation Chamber, see the DanioVision DVOC-0041 - Reference Manual. Basic requirements You must have EthoVision XT with the Trial and Hardware Control Module (see page 14). 8 - Control hardware devices You must have one Noldus USB-IO box or Noldus Mini USB-IO box, connected between your PC and the devices. See The USB-IO box and the Mini USB-IO box on page 120. All hardware devices must be connected through a Ethernet straight-through cable with RJ45 connectors. In EthoVision XT, you must define the devices you want to use in the Experiment Settings (see page 109). Next, assign devices to arenas (page 113), and finally program Trial Control with hardware-based actions and conditions (see page 117). Time accuracy The accuracy of sending or receiving signals from the USB-IO box is 40-120 ms, depending on factors such as the camera frame rate and the Windows priority scheduling. Terminology Physical device. A single device identified by a ID number or code. Each physical device must be associated with a specific arena in your hardware configuration (see Figure 27). example PD03 for a Pellet dispenser. Device name. A generic name that indicates the same type of physical device used in one or more arenas. The Device name is valid for all arenas defined in your Arena Settings, even if a particular arena has no physical device associated with it. examples Pellet dispenser, Wheel, Yellow light. Figure 26 The Noldus USB-IO Box. 8 - Control hardware devices Work With Multiple Devices EthoVision XT supports the use of one or two USB-IO boxes and one Mini USB-IO box. important We recommend to test a specific combination of devices before carrying out the actual trials. Whether a combination of devices works also depends on the timing of the commands. Controlling 12 pellet dispensers may, for example, work if the pellets are dropped at different times. Dropping 12 pellets at exactly the same moment will, however, not work. When working with two or more USB-IO boxes, see use multiple usb-io boxes on page 131. Tested configurations The following configurations were tested separately: Four PhenoTyper Top Units + 1 Top Unit Interface. Sixteen PhenoTyper Top Units + four Top Unit Interfaces. One USB-IO box with four Pellet dispensers. One USB-IO box with four PhenoWheels. One USB-IO box with four Lickometers. One USB-IO box with four IR Beam Controllers (for the Mouse Feeding Monitor). Two USB-IO boxes, each connected to six Pellet dispensers (TTL devices) and six Lickometers (SDI devices). DanioVision: White Light and Tapping Device (events occurring every 5 minutes). All tests lasted 30 minutes. Typical protocols included switching lights and buzzers on/off and dropping a food pellet when the subject entered a zone or every minute. When testing two USB-IO boxes simultaneously, triggering events for Lickometer and PhenoWheel occurred every two minutes or every three minutes. All tests were conducted using a PC Dell Precision 3650 with Windows 10 or Windows 11. Devices in multiple arenas If you work with multiple arenas, those arenas are expected to have the same type of devices. Trial Control is applied to each arena independently. For example, if you define an action Drop a pellet to be triggered when a condition is met, that action is executed on the pellet dispenser associated with the arena in which the condition is met. Furthermore, an arena may contain more than one physical devices of the same type. In this case you must define unique Device names in the Arena-Hardware Mapping window that can be associated with the physical devices. For example, if each cage has two pellet dispensers, you must define two Device names, for instance Pellet dispenser Left and Pellet dispenser Right (Figure 27). See assign devices to arenas on page 113. 8 - Control hardware devices Connect The Hardware Devices Before defining a hardware configuration, close EthoVision XT. 1. Connect the power cord to the 24V in socket on the USB-IO box/Mini USB-IO box rear panel. Connect the other end of the power cord to the mains socket. 2. Connect the USB socket on the rear panel of the USB-IO box/Mini USB-IO box to the EthoVision computer using a USB cable with one connector of type A (computer) and one connector of type B (USB-IO box). 3. Connect the hardware device to the first available port of the USB-IO box/Mini USB-IO box using the RJ45 cable. Depending on the device you want to connect, choose the port located on: TTL Control (front panel of the USB-IO box). For devices controlled with TTL logic (One/ Zero signal type). For example, the Pellet Dispenser, the TTL Port Tester or any Custom Hardware devices working with TTL logic. SDI Control (rear panel of the USB-IO box). Special Device Interface, for devices controlled with a serial data stream. For example, the Lickometer, Running wheel and the PhenoTyper's Top Unit Interface (see below). 4. Repeat step 3 to connect other devices. 5. To test the device, follow the next sections Setting the port connections (see below) and Assigning devices to arenas (see page 113). Figure 27 An example of mapping hardware devices in multiple arenas. 8 - Control hardware devices Connect Phenotyper To control one or more PhenoTypers, you must have the Top Unit Interface box, which functions as an interface between the USB-IO box and the Top Units (see the figure below). Connect each of the Top Units to one of the four RJ-45 sockets in the Top Unit interface. To connect a Top Unit to the Top Unit Interface, you must have an adapter between the Top Unit's TTL-in 9-pin Sub-D socket and the Top Unit connector cable. Connect the Top Unit interface to the SDI Control 13 port in the USB-IO box. You can control up to four Top Units from one SDI port using the Top Unit Interface. By using multiple Top Unit Interfaces, you can connect groups of four PhenoTypers to the USB-IO box. For more information, see the PhenoTyper - EthoVision XT 17 - Reference Manual. Connect third-party devices For third-party devices you may need additional cables and adapters between the Noldus USB-IO box / Mini USB-IO box and those devices. For example: For the Inscopix camera system, you need the Optical Isolated Interface PTISO-00x0 (see page 151). Figure 28 Connecting the PhenoTypers' Top Unit. 8 - Control hardware devices For Med Associates devices, see the following figure: For Med Associates devices and other systems with 28V inputs, you need the TTL to 28V interface. See the PhenoTyper - EthoVision XT 17 - Service Manual. You need this converter when you want to send signals to the Med Associated device (for example, a pellet dispenser). For input devices, for example a lever switch, contact Noldus. To connect a custom device like a LED lamp or a simple switch, see page 129. Contact Noldus if you need special adapters or custom solutions. Set The Port Connections Prerequisites Connect all devices to the EthoVision PC, via the USB-IO box or Mini USB-IO box. When working with two or more USB-IO boxes, make sure that all IO-boxes are connected to the PC. To set the port connections - Start EthoVision XT, and open your experiment or create a new one. - Choose Setup > Experiment Settings. - Under Trial Control Hardware, select Use of Trial Control Hardware, and click the Settings button. 8 - Control hardware devices - Select whether you use the Noldus USB-IO Box, the Noldus Mini USB-IO Box or a DanioVision Observation Chamber, and click OK. tip To find out what type of USB-IO box you have, check the label at the bottom side of the IO-box: PTIO-002x (for the USB-IO Box) or PTIO-003x (for the Mini USB-IO box). - The Device Configuration window appears, listing the available ports of the interface device USB-IO box (left-most column): TTL Port 1, 2,... for the TTL ports of the USB-IO box, and SDI Port 1, 2,... for the SDI ports. Each row can be assigned to one physical device (see page 105 for the meaning of physical device). - If you have connected multiple USB-IO boxes, select one from the list at the top. - In the Ports column, locate the first available port of the correct type. 8 - Control hardware devices Locate a TTL Port and click under Device type to view the list of the devices. Select the device that applies. Locate an SDI Port and click under Device type to view the list of the devices. Select the device that applies. Use SDI ports to connect the Lickometers and the PhenoTyper's Top Unit Interface. If you select the latter, four additional rows appear below the option. Select the PhenoTypers' Top Units. For details, see Set the port connections for Phenotyper on page 112. - From the Device type list, select the type of device that is (or will be) connected to that port. - In the Device ID field, enter the name of the physical device that should be connected to that port). 10.Repeat step 5-7 for other devices, until they are all assigned to a port of the IO-box. - Repeat the steps from 6 for the next USB-IO box. - When ready, click OK. You return to the Experiment Settings screen. Proceed with assigning devices to the arenas (see page 113). Notes The number next to IO-box is the identification number of the IO-box set by the manufacturer. You cannot change this number. You must set the port connections only the first time you connect them. The port connection settings are at experiment level, and are applied to all your Trial Control Settings. Once you acquire at least one trial, the settings become locked and you can no longer change them. If you need to add devices, create a new experiment or remove the acquired trials. If you plan to create several experiments with the same set of devices, you can use an experiment as a template experiment with the hardware settings selected but containing no trials. To create a new experiment from a template experiment: from the File menu, select New template experiment and then Use a custom template. Next, open the experiment you want to use as a template and use the new experiment to acquire data. 8 - Control hardware devices The Device ID is by default the name of the Device type + a progressive number 1, 2,... We advise you to enter a name that you can recognize easily in your setup. For the difference between TTL and SDI ports, see page 107. Under Device type, select TTL Port Tester if you want to test the functionality of a TTL port. See page 144. Under Device type, select USB-IO monitor if you want to test the connection in the USB- IO box. See page 132. When you select a device type in step 5 (page 110), that device type is added to the file Hardware Setup.xml, which is stored in one of the folders located in the experiment folder ...\Configuration Files\Add-ins\Hardware. Which file is used depends on whether you use the USB-IO box, the Mini USB-IO box or another system, for example, the Ugo Basile FC Controller, which does not require the USB-IO box / Mini USB-IO box. {A8DA8F3E-7EA3-4629-8327-9D21C90FB3ED} for the USB-IO box. {0308106B-1EBE-4620-B00D-396ABEBBC219} for the Mini USB-IO box. {3AA139A2-4737-4D6D-BF7B-0153CFD4D302} for the Ugo Basile FC Controller. Use multiple USB-IO boxes You can connect multiple Noldus USB-IO Boxes to one EthoVision XT computer, to control more devices. For more information, see use multiple usb-io boxes on page 131: Set the port connections for Phenotyper - Locate the SDI Port 13. Under Device type select Top Unit Interface. This expands the SDI Port to four extra rows: - For each of the four rows, under Device type, select Top Unit (Standard) for standard PhenoTypers or Top Unit (NeuroBsik) for PhenoTypers of the Neuro-Bsik type. Choose Top Unit Tester (PTTB-002x) only when you want to use the Top Unit Tester instead of the actual PhenoTyper Top Unit, for testing purposes. 8 - Control hardware devices - Under Device ID for the rows appended, enter the name of the physical Top Units. - When ready, click OK. Next, assign the Top Units to the arenas (see the next section). To set the port connections for other groups of PhenoTypers, you must adjust the jumpers for the ports you are going to use. See the PhenoTyper - EthoVision XT 17 - Service Manual. Assign Devices To Arenas For experiments with one arena only, hardware devices are automatically assigned to the arena. You can skip this paragraph and continue with the next step: testing the hardware devices (see page 115) or programming trial control with devices (see page 117). For multi- arena experiments follow the procedure below. Assuming that you have defined your arenas in the Arena Settings (see EthoVision XT Help), do the following: 1. In the Experiment Explorer, click the Arena Settings in which the arenas you want to use are defined. 2. In the Arena Settings window, click the Arena - Hardware mapping button. The Arena - Hardware mapping window appears. 3. Click Add device. A new row is appended to the table. 4. From the Device type list, select the type of device you want to assign. Select Custom hardware if the device type you are using is not listed. 5. Under Device name, a default name is displayed. This is the suggested Device name for the devices that you specify in that row; for more information on the meaning of Device names, see page 105. We advise you to enter a new name that can be easily recognized, especially if you have more devices of the same type in each arena. 8 - Control hardware devices example Each arena is provided with two pellet dispensers of the same type. Enter Pellet Dispenser Left under Device name. In the next step (6), select the pellet dispensers to be placed on the left side of each arena. Next, click Add device again and enter Pellet Dispenser Right under Device name, then select the pellet dispensers to be placed on the right side of each arena. 6. Under the Arena name, select the physical device that you want to assign to that arena. Assign the other devices to the remaining arenas. 7. Repeat steps 3 to 6 to add a new set of devices. 8. When finished, click OK. Figure 29 The Arena - Hardware mapping window. 8 - Control hardware devices Notes To remove a set of devices, select the corresponding row in the table and click the Remove device button. If your setup includes two or more devices of the same type in one arena, make sure that you select the physical devices that belong to the Device name specified under Device name. See page 105 for the meaning of Device name. If you cannot select any physical device under the arena names, check that the Device type selected for that row is specified in the Port Device Mapping (see page 109). The Arena - Hardware Mapping settings are valid for all Arena Settings in your experiment. They are added automatically to every new Arena Settings. Assign arenas to the PhenoTypers - Click Add device in the Arena - Hardware Mapping window. - Under Device type, select Top Unit. - Under Device name, enter a generic name (for example, Top Unit). - Under Arena n, beginning with 1, select the Device ID of the Top Unit associated with that arena. - Repeat step 4 to assign the Top Units to the remaining arenas. Test The Hardware Devices - Make sure that the hardware devices are connected to the EthoVision computer via the USB-IO box or the Mini USB-IO box (see page 107). - In the Experiment Explorer, click any Arena Settings. - In the Arena Settings window, click the Arena - Hardware mapping button. The Arena - Hardware mapping window appears. - Under the Arena name, select the physical device you want to test, and click Test. A new window appears. - Depending on the hardware device: For any device that can receive a signal from and send it back to the computer - Examples are the Pellet dispenser, Activity wheel break, or Backlight unit white light. Select the appropriate action, click Test and check that the action has been taken. You 8 - Control hardware devices can also view the result in the Test window, that is, for example the Number of drops has increased by 1. For any device that can only send a signal to the computer, not receive any. Examples are the Lickometer, PhenoWheel, or the Activity wheel counter. Trigger the device manually and check the result in the Test window. For the Top Unit. From the Command list, select the action you want to test, click Test and check the result in the PhenoTyper. For the Custom Hardware Device (for example, the Illuminated shelter). From the Command list, select the action you require, click Test and check that the device has been activated correctly. For the TTL Port Tester. Use this device to check the two-way communication for a specific port. Press a button on the device and check the result in the Test window. From the Command list, select a command and click Test. Check the result on the tester box. 6. When ready, click OK. Notes Data from the Lickometer and the PhenoWheel are read out in regular time intervals. For the Lickometers currently sold by Noldus IT, the time interval is two seconds, and for the current PhenoWheel it is 60 seconds. For all devices: The fact that a signal is given correctly in the Test window but you do not see the response from the device could mean that the device is not functioning (for example, a lamp is broken). For the Pellet dispenser: If the Test window shows in error state = true, the pellet dispenser is not connected to the IO-box, or the food pellets are no longer available. For the Lickometer: Number of licks and Duration of licks is the cumulative number and duration of licks since the Test button has been clicked, respectively. The device is read out at regular time intervals. At the end of the interval the number and duration of licks is displayed very briefly. important If you realize that the values of Number and Duration of licks given by EthoVision XT are much higher than expected, close EthoVision XT, disconnect and re- connect the IO-box to the computer and then restart EthoVision XT. For the Top Unit, TTL Port Tester and Custom Hardware Device. You can also view the result of the action to be tested in the Test window. Locate the Signal you want to test 8 - Control hardware devices and verify that Value changes from false to true or vice versa. For the TTL Port Tester, you can also press a button and check the counts of presses for that button. Program Trial Control With Hardware Devices In the Trial Control Settings, you can define: A condition based on a hardware device. For example, As soon as the cumulative duration of licks equals 1 minute, stop recording. See page 79. An action on a hardware device. For example, have the Pellet dispenser drop a pellet, or switch on the PhenoTyper's white light. To define an action on a hardware device - In the Components pane, under Actions, double-click the button next to the name of the device type you want to control, or click the button next to it. The Hardware Action window appears. - Under Name, enter an Action name. Under Comment (at the bottom) enter a description (optional). - Under Action to perform, select the Device name you want to use. The names listed there are defined in the in the Arena-Hardware mapping window. - From the Action to perform list, select the action that the device must take. - Click the Test button to check the hardware action. Click the Reset button to reset all hardware. - Click OK. Insert the Action box in the appropriate position in the rule. For information on how to do this, see the EthoVision XT Help. What you need to control hardware devices The Noldus USB-IO box, the Mini USB-IO box, or the DanioVision Observation Chamber. These devices work as physical interfaces between EthoVision XT and the devices. The hardware interface software Noldus HardwareInterface USB-IO box version 5, which is automatically installed when you install EthoVision XT. 8 - Control hardware devices tip To check what is installed on your EthoVision XT computer, see the Windows Control Panel > Programs and Features/Add or remove programs. Notes For general information on programming trial control, see page 23. The items listed under Actions are the Device names selected in the Arena-Hardware mapping window (page 113). If the device name is not listed under Actions, check that the port connections are set correctly (page 109) and that the devices are mapped in the arenas (see page 113). If you have a setup with multiple arenas, it is assumed that each arena has a physical device under that Device name. An action is taken in each arena separately, when the accompanying condition is met in that arena. Actions like Light on and Sound on result in the light/sound device being activated for an indefinite time. Remember to add an extra action that switches that light/sound off. The two actions should be separated by a time, for example Light on --> Time 1 s --> Light off. If you define a sequence of multiple actions on the same device, these are probably evaluated at the same sample time. This happens because the computer is fast enough to analyze multiple Trial Control boxes in one sample. To make sure that actions are taken in sequence, add a Time condition between actions so that the program waits for a short time (for example, 0.1 s) before taking the next action. You can also activate a hardware device like a Pellet dispenser manually. In the Manual Scoring Settings, define a fictitious behavior, for example, Pellet, and select the type Point event. In the Trial Control Settings, create a subrule that contains the following conditions and actions: [Rule Begin] > [Condition: Frequency (Pellet)>=1] > [Action: Drop pellet] > [Rule End]. During acquisition, every time you score Pellet, the drop pellet command is executed. For details, see Controlling the Pellet dispenser manually in the PhenoTyper - EthoVision XT 17 - Service Manual. If the hardware action follows a condition based on In zone, or Zone transition, the action may be carried out repeatedly if the animal walks along the border of a zone. For example, if the detected body flickers on the border of two zones, and you want to drop a pellet every time the zone border is crossed, many pellets will be dropped. If this is the case, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track during acquisition, which means that the track is altered. This cannot be reversed afterwards. For NeuroBsik Top Units: To produce ultrasound of specific frequency and intensity: Define two actions that, when combined, specify the frequency you require. 4 kHz. Fsel-1 off, Fsel-2 off. 8 kHz. Fsel-1 off, Fsel-2 on. 8 - Control hardware devices 16 kHz. Fsel-1 on, Fsel-2 off. 32 kHz. Fsel-1 on, Fsel-2 on. Next, define two actions that, when combined, specify the volume you require. 25 dBm. Vol-1 off, Vol-2 off. 50 dBm. Vol-1 off, Vol-2 on. 75 dBm. Vol-1 on, Vol-2 off. 100 dBm. Vol-1 on, Vol-2 on. Combine the four actions with an operator of type All, and then add a Time condition (see the previous note) followed by a Sound on action. Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - 9 The USB-IO box and the Mini USB-IO box URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-9-the-usb-io-box-and-the-mini-usb-io-box Chapter: EthoVision XT The USB-IO Box And The Mini USB-IO Box The Usb-io Box General information The Noldus USB-IO box is the device that the EthoVision XT video tracking software must use in order to work together with external devices such as the Noldus Pellet dispenser, the Noldus Lickometer or the light and sound devices of the PhenoTyper Top Unit. With one USB-IO box you can operate: Up to 12 Pellet dispensers or other TTL-driven devices. Up to 12 Lickometers. Four PhenoTyper Top Units (by default), expandable to a maximum of 52. For this special connection, port SDI 13 is reserved. For information on which third-party devices can be connected to the USB-IO box, see page 129. Note The total number of devices that you can connect is limited by the number of ports on the USB-IO box. For example, because the Lickometer uses the same type of port (named SDI) as the PhenoTyper Top Unit, and 13 SDI ports are available on the UBSB-IO box, if you connect 52 Top Units, all the suitable ports of the USB-IO box are occupied. Therefore no lickometer can be connected. When planning your experiment, make sure that you have enough ports on the USB-IO box for the devices you want to use. Figure 30 The USB-IO box. A typical setup - Connect the hardware devices to the computer, via the USB-IO box (see page 125). - Define the hardware configuration in EthoVision XT (see page 136). - With the Trial and Hardware Control function of EthoVision XT, you can define: Actions on the hardware device (for example, Drop a pellet). Conditions that must be met in order for Trial Control to progress. Sub-rules for a sequence of actions and conditions to be repeated. - Acquire data using the Trial Control settings specified above. Defining Hardware configuration means that you specify which communication ports of the USB-IO box are connected to which hardware devices, and, in the case you work with multiple arenas, which individual device is assigned to which arena. Figure 31 EthoVision XT setup for controlling a Pellet dispenser. A - Pellet dispenser, B - USB-IO box, C - Computer with EthoVision XT. More devices can be attached to the USB-IO box. More USB-IO boxes can be connected to one computer with EthoVision XT. Connectors and displays - Front panel These are input/outputs for devices that are controlled with TTL (Transistor Transistor Logic). Use a TTL port for the following devices: N0ldus Pellet dispenser (Noldus type number PTPD-001x). Noldus Beam controller (Noldus type number PTBC-001x). Shock, Tone, Light and Noise in the Ugo Basile Fear Conditioning System. note With EthoVision XT 17.5 and newer versions you can let EthoVision XT control the Ugo Basile Fear Conditioning System without the Noldus USB-IO box. See the connection schemes in the EthoVision XT 17 - Application Manual. White light in the Noldus Backlight unit. Noldus Pellet receptacle (Noldus type number PTPR-001x) The Activity Wheel Brake (ENV-042). Any custom hardware device that works with TTL signals. The TTL Port Tester (PTTB-001x; for testing purposes). The USB-IO box monitor (virtual device; for testing purposes). Notes Each of the 12 TTL control connectors can provide limited supply power (18 Volt DC, max. current 100 mA) available on pin 1 (ground) and 2 (+). You can control up to two physical devices with one TTL port. A typical example of controlling two devices with one TTL port is the Shock and Tone devices in the Fear Conditioning System (see the corresponding manual). For this you need a split cable from the TTL port that ends in the two devices. Please contact Noldus if you need such a cable. Ports are organized in groups of four. To optimize communication speed, we advise you to connect TTL devices to ports in the same group. For example, connect four pellet dispensers to ports 1 to 4, not to ports 1, 5, 7 and 12. Use ports 1-4 first, then 5-8 etc. LEDs Power - When the light is on, it indicates that the USB-IO box receives power from the mains adapter. USB - When burning, it indicates that the USB-IO box is connected to a computer's USB port. TTL - When burning, it indicates that communication to a TTL device is in progress. SDI - When burning, it indicates that communication to a SDI device (see Rear panel below) is in progress. Connectors - Rear panel SDI stands for Special Device Interface. SDI control ports are inputs/outputs for devices that are controlled with a serial data stream. You can connect one physical device to a SDI port. Use these ports for the following devices: The Noldus Lickometer (Noldus type number PTLM-001x). The PhenoTyper Top Unit Interface (Noldus type number PTTI-001x). The Noldus PhenoWheel. The Activity Wheel Counter (ENV-042). Notes Each Top Unit Interface is connected to one port of the USB-IO box, and can control up to 4 PhenoTyper Top Units. For more information, see the PhenoTyper - EthoVision XT 17 - Reference Manual. SDI control 13 is set by default to connect the Top Unit Interface. If you want to connect two or more Top Unit Interfaces, you must alter the jumpers for the ports other than 13 that you use to connect the Top Unit Interfaces. See page 133. Each of the 13 SDI control connectors can provide limited supply power (12 Volt DC, max. current 100 mA) available on pin 1 (ground) and 2 (+). All SDI devices mentioned above get their full power supply by the 12 Volts provided by the USB-IO box. USB Connects the USB-IO box to the PC using a USB cable with one connector of type A and one connector of type B. 24 V In Connects the USB-IO box to the Power supply via the 24V adapter. 24 V Out Connects the USB-IO box to other devices/power consumers with a power feed-through cable. For example, a PhenoTyper Top Unit. important When you connect devices to the 24 V Out power supply, do not exceed the maximum power rating of your mains supply. Install The Usb-io Box The USB-IO box comes with the following cables: Power supply 24 V 3A DC (A) with mains cable (B) USB cable with two different connectors. Connect the USB-IO box to the computer - Make sure that EthoVision XT is not running. - Connect the USB port on the USB-IO box to a USB port on the EthoVision XT computer using the USB cable. Notes Use a direct USB port on your PC, not a USB hub or a USB port on your PC's monitor. Try to minimize the number of USB devices connected to your computer. You can in principle connect multiple USB-IO boxes to the EthoVision XT computer; however, we cannot guarantee that all possible combinations of devices will work. For more information, see page 131. If you disconnect the USB-IO box while EthoVision XT is open, a message appears on top. Re-connect the USB-IO box and in EthoVision XT click Try again. Note that It can take some time before the software recognizes the USB-IO box after you re-connect it. Connect the USB-IO box with the Noldus USB extender cable The standard USB cable length is limited to 3 meters. When you need a longer distance between the computer and the PhenoTyper setup, we recommend to use the Noldus active USB extender cable of 20 meters because not all standard USB extenders work fine with the USB-IO box. The Noldus USB extender cable comes with a small jumper that must be set inside the USB-IO box in order for the USB extender cable to function correctly. When you use the USB extender cable in combination with the mini USB-IO box (PTIO-003x) you do not need to set the jumper. When you purchased your USB-IO box together with the USB extender cable, the jumper already has been set by Noldus. To set the jumper, do the following: 1. Open the USB-IO box by unscrewing 2 screws at the bottom, and remove the top part (see page 133). 2. Set the jumper on position JMPR4 (indicated by the arrow in the figure below). 3. Re-assemble the USB-IO box. 4. Now connect the USB-IO box to the computer (page 125). The USB-IO box device driver software The current driver software for the USB-IO box and Mini USB-IO box is installed automatically when you install EthoVision XT. For EthoVision XT 17, the driver software for both the USB-IO box and the Mini USB-IO box is Noldus HardwareInterface USB-IO box 5.1.8. To check that the driver is installed, open the Control Panel and go to Programs and Features/Add or remove programs. The driver name is Noldus - HardwareInterface IoBox - x64 Package - 5. If, for any reason, you want to uninstall the driver software, in the Control Panel > Add or remove programs select Noldus - HardwareInterface IoBox - x64 Package - 5 and click Uninstall. If you need the driver software for the USB-IO box and the Mini USB-IO box, you can find it on my.noldus.com. Log in or register first, then choose Downloads > EthoVision XT > Versions. Download EthoVision XT - Full installation disc - 17.5, then unzip the file and open the folder Drivers and tools > PreRequisites > HardwareInterfaceIobox. Run the file HardwareInterface IoBox - x64 Package - 5.1.8.msi. Older versions of the USB-IO box device driver It is not necessary to uninstall the drivers of previous versions of the Noldus USB-IO box or the Noldus Mini USB-IO box. Note that for EthoVision XT 11 and older versions, the USB-IO box and the Mini USB-IO box had separate drivers. Connect The Usb-io Box To Devices Connect one device - Plug one of the ends of the modular network cable in the hardware device. Although an RJ45 cable is used in computer networks, the signal from and to the hardware device is not a network signal. The device cannot be connected via a network hub or similar. - Plug the other end of the network cable in one of the ports available on the USB-IO box. TTL (front panel) for the Pellet dispenser and other devices that communicate via TTL. SDI (rear panel) for the Lickometer and the Top Unit Interface. Note: The network cable comes with the Noldus device, not the USB-IO box. To connect the PhenoTyper's Top Unit, connect the network cable to the Top Unit Interface, then connect the Top Unit Interface to each Top Unit. Connect the Top Unit Interface to port SDI 13. For more information, see the PhenoTyper - EthoVision XT 17 - Reference Manual. Connect multiple devices Connect each individual device to a TTL or SDI port of the USB-IO box. If you use PhenoTypers with devices like the Noldus Lickometer or the Noldus Pellet dispenser, connect the devices of the same type to the same group of connectors (e.g. four Pellet dispensers to TTL 1-4, or TTL 5-8). examples Four Lickometers: SDI ports 1 to 4 Four Pellet dispensers: TTL ports 1 to 4 Top Unit Interface: SDI port 13 Speed of TTL communication is optimized if devices are connected to the same group of connectors. important Always to test a specific combination of devices before carrying out the actual trials. Whether a combination of devices works also depends on the timing of the commands. Controlling 12 pellet dispensers may, for example, work if the pellets are dropped at different times. Dropping 12 pellets at exactly the same moment will, however, not work. Connect a third-party device: LED lamp You can connect a third-party device that can be controlled by TTL. Below you find two examples, one with a LED lamp and one with two switches. example Connect a LED lamp The LED lamp must be connected between TTL output1 (color: brown/white) and ground (color: orange/white). Do not forget to add a series resistor (approximate value 560 ohm) to limit current through the LED. To control the LED lamp with EthoVision XT, in the Port device mapping window select the TTL port that is connected to the LED and under Device type select TTL Port Tester. To define an action on this device, use the Light 1 on/off option. The resistor can be skipped when you connect a real TTL device like a shocker input or a maze door. Check the documentation of the device to be connected. Figure 32 Wiring scheme for connecting a LED lamp. Connect a third-party device: two-switch device Connect switch 1 between TTL input1 (color: blue/white) and ground (color: brown). Connect switch 2 between TTL input2 (color: blue) and ground (color: brown). To read the status of each switch with EthoVision XT, in the Port device mapping window select the TTL port that is connected to the switch device and under Device type select TTL Port Tester. To define a condition based on this device, use the Is button 1/2 pressed option (to check that a switch is on/off) or the Button 1/2 presses option (to check the number of presses). note When a switch is open, the TTL value of the corresponding input is High. When a switch is closed, the TTL value of the corresponding input is Low (0). Connect a third-party device: simple lever When the lever is a simple "switch" that makes contact from signal to ground, without a circuit board in it, you can connect the device directly to a TTL input line of the USB-IO (or mini USB-IO) box. When the lever is not activated, the input is "high" (logic 1). When the lever is pressed, input will go to "low" (logic 0). Connect pin 1 and/or pin 8 for ground and either pin 5 or 4 for TTL input 1 or 2 respectively). note Inside the (mini) USB-IO box, all TTL input lines are "forced high" to 5Volt TTL level by an internal resistor. So whenever an input line is not connected (open), it is interpreted as logical "high" or 1. If this line is connected to ground it will be seen as logical "low" or 0. note These instructions are valid if the lever is based on a (micro) switch. Other retractable levers may need a different connection! Figure 33 Wiring scheme for connecting a two-switch device. Use Multiple Usb-io Boxes It is in principle possible to connect multiple USB-IO boxes to the EthoVision XT computer, provided that each box has a unique ID. Tested configuration See work with multiple devices on page 106. In practice, there may be limitations due to the number of devices attached and controlled simultaneously with EthoVision XT. For example, events like a pellet drop may be skipped if they occur simultaneously with other input and output events. We always recommend to test a specific combinations of USB-IO boxes and devices before carrying out the actual trials. See also an important note in Connect multiple devices on page 128. Procedure - Make sure that each USB-IO box as a unique ID. To do so, adjust the DIP switches in one of the USB-IO boxes. See Alter the DIP switches on page 135. - Connect each USB-IO box to its own power supply; do not use power feed-through cables. - Connect each USB-IO box to a separate USB port of your PC before configuring EthoVision XT. - In the Experiment Settings, click the Settings button next to Use of Trial Control Hardware. In the window that appears, first select one USB-IO box from the drop-down list and select the devices connected to it (see steps 7 -9 on page 110). Next, select the second USB-IO box and select the devices connected to it. Figure 34 Wiring scheme for connecting a lever device. Test The Usb-io Box To test the functionality of TTL ports See page 144. To test connection in USB-IO box When you carry out long trials, it may be handy to check that the USB-IO box works properly for the entire duration of the trial. For this purpose, use the USB-IO box monitor function. 1. In the Device Configuration window (Experiment Settings), locate a free TTL Port and under Device type, choose USB-IO box monitor. 2. In the Arena-Hardware Mapping window, add a device and, and for that device select USB- IO box monitor. 3. After the trial has been acquired, in the Analysis profile click next to Hardware state and select: Device type: USB-IO box monitor. Value: true. 4. In the Integrated Visualization you should see the hardware state USB-IO box monitor as a colored bar that goes from the beginning to the end of the trial, if everything went well during the trial. If the USB cable between the PC and the USB-IO box was accidentally disconnected, or some error occurred inside the USB-IO box chip. the colored bar should end at that time in the trial. Note You can use the USB-IO monitor function to check whether the USB cable is still connected or if the communication chip is working fine. However, this function cannot help when: A specific port other than that used for USB-IO box monitor is defective. The power cable of the USB-IO box is disconnected during the trial. In both cases the USB-IO box monitor state remains unchanged till the end of the trial. Do not use the port reserved for USB-IO box monitor for connecting other devices. Jumper And Dip Switch Settings The USB-IO box contains jumpers inside the box next to the SDI ports. Jumpers are short lengths of wire that complete a circuit. By placing the jumper over a pair of available pins, you activate that line. On the USB-IO box board, jumpers can be placed in either position 1 or 2. The default jumper positions are set by Noldus Information Technology. You do not have to change them unless you intend to connect multiple Top Unit Interfaces to work with multiple groups of PhenoTypers (see altering the jumpers below). Default jumper settings JMPR5 (for SDI ports 1-4) - Set to 1 JMPR6 (for SDI ports 5-8) - Set to 1 JMPR7 (for SDI ports 9-12) - Set to 1 JMPR8 (for SDI port 13) - Set to 2 Position 1 enables use of the Lickometer. Position 2 enables communication between the USB-IO box and multiple PhenoTyper Top Units. Alter the jumpers Follow this procedure only if you want to use SDI ports other than 13 to connect the Top Unit Interface. For example, when you want to connect 8 PhenoTypers to your PC and therefore SDI port 13 is not sufficient as it can work with up to four Top Units. Note that if you alter a jumper other than JMPR8, this is done for all the four ports it corresponds to. 1. Unscrew the cover of the USB-IO box. 2. Locate the jumpers on the main board marked by JMPR5 to JMPR8. 3. Put the jumper to position 2 for the port that you require. JMPR5 (for SDI ports 1-4) JMPR6 (for SDI ports 5-8) JMPR7 (for SDI ports 9-12) The jumper position 1/2 is marked right of JMPR7. The jumper JMPR8 is set by default to 2. If you want to use SDI port 13 to connect a Top Unit Interface, leave it in that position. If you want to use port 13 to connect a Lickometer, set it to 1. 4. Close the cover. Default DIP switch settings Open the USB-IO box cover (see the previous page). The DIP switches are located in a red block on the main board. The default settings are (from 1 to 8): 1 Off, 2-8 On. This sequence Off-On-On.... corresponds to 00000001, that is 1 in binary language). Alter the DIP switches Follow this procedure if you want to connect multiple USB-IO boxes to the EthoVision XT computer. DIP switches determine the ID of the USB-IO box. Multiple boxes must have different ID (and therefore DIP switch settings) in order to work properly with EthoVision XT. 1. For the first USB-IO box, leave the DIP switch settings as default (1 Off, 2-8 On; red squares represent switch positions). 2. For the second USB-IO box, use a pen or a small screwdriver to move the DIP switch 1 to On and the DIP switch 2 to Off (this corresponds to 00000010, that is 2 in binary language). 3. For more USB-IO boxes, move the DIP switches to create unique numbers. Configure Ethovision Xt Prerequisite Make sure that the USB-IO box is connected to the EthoVision XT computer, that all devices are connected to the USB-IO box, and that the USB-IO box is connected to a power supply. If you use multiple USB-IO boxes, connect them all to the EthoVision XT computer. Procedure See Control hardware devices on page 104. The Mini Usb-io Box Overview The Noldus Mini USB-IO box (type number PTIO-003x) is an interface device used to control external devices such as an Atlantis platform, a shocker, etc., from the EthoVision XT video tracking software. It is a smaller and simplified version of the USB-IO box (type number PTIO- 002x). It is also embedded in the DanioVision system for tracking of zebrafish tracking. Ports The Mini USB-IO box is provided with (see the top panel of the box): USB - Connects the USB-IO box to the PC using a USB cable. Four TTL control connectors, TTL control 1 to 4 (see page 138). One Multi TTL output connector (see page 138). The SDI control connector is currently used in the DanioVision system, and will be used in future applications of the stand-alone Mini USB-IO box. 24V in - Connects the USB-IO box to the Power supply via the 24V adapter. Each of the 4 TTL control connectors can provide limited power supply (18Volt DC, max. current 100mA) available on pin 1 (ground) and 2 (+). LED indicators 24V On - Switches on when the Mini USB-IO box is connected to a power source. TTL control busy - Blinks whenever the Mini USB-IO box communicates with a TTL- controlled device. Figure 35 The Mini USB-IO box. SDI control busy - Blinks whenever the Mini USB-IO box communicates with a SDI- controlled device. TTL control With a TTL port you can control the following devices (one per port): The Noldus Backlight Units (Noldus codes XIRWB-xxxx) The Noldus Pellet dispenser (Noldus code PTPD-xxxx; maximally two). To use the Pellet dispenser with the Mini USB-IO box, you must replace a device file in EthoVision XT. See the instructions connect the pellet dispenser in the chapter The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 17 - Service Manual. You can open this manual from All Apps > Noldus > EthoVision XT 17 Other Documentation. Any (custom) hardware device that works with TTL logic (up to two devices per port; see page 140). To control a Noldus PhenoTyper setup, you must use the Noldus USB-IO box PTIO-002x for full PhenoTyper add-on hardware support. If you want to control the doors of 8-arm radial maze, you can use the TTL ports. Since the Mini USB-IO box has 4 TTL ports, you have in total 8 output lines, which can control all eight doors. Please contact Noldus for more information. Multi TTL control With the Multi TTL output, you can control up to 16 devices independently. This output is suitable for controlling maze doors in a 8-arm radial maze, lights or any other devices with a TTL control input. The connector is a 20 pin IDC. Beside these 16 outputs, also some supply voltages are provided: +5Volt, +12Volt and common ground. There are no TTL input lines available on this connector. Because of this, you cannot use Multi TTL to control the Noldus Pellet dispenser and any other device which requires input channels. The Mini USB-IO box device driver software The current driver software for the USB-IO box and Mini USB-IO box is installed automatically when you install EthoVision XT. For EthoVision XT 17, the driver software for both the USB-IO box and the Mini USB-IO box is Noldus HardwareInterface USB-IO box 5.1.8. To check that the driver is installed, open the Control Panel and go to Programs and Features /Add or remove programs. The driver name is Noldus - HardwareInterface IoBox - x64 Package - 5. If, for any reason, you want to uninstall the driver software, in the Control Panel > Add or remove programs select Noldus - HardwareInterface IoBox - x64 Package - 5 and click Uninstall. Older versions of the Mini USB-IO box device driver It is not necessary to uninstall the drivers of previous versions of the Noldus USB-IO box or the Noldus Mini USB-IO box. Note that for EthoVision XT 11 and older versions, the USB-IO box and the Mini USB-IO box had separate drivers. To connect the Mini USB-IO box note If you want to control the Pellet dispenser with the Mini USB-IO box, first follow the instructions connect the pellet dispenser in the chapter The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 17 - Service Manual. You can open this manual from All Apps > Noldus > EthoVision XT 17 Other Documentation. 1. Connect the Mini USB-IO box to a USB port on the EthoVision XT computer, using the USB cable that comes with the Mini USB-IO box. 2. A message may appear as you plug the USB cable to the computer USB port. Please wait that the driver software is installed. 3. Connect the Mini USB-IO box to the power supply using the appropriate cable and the mains adapter. The LED 24V On switches on. 4. Plug one of the ends of the modular network cable in the hardware device. 5. Plug the other end of the cable in one of the ports available on the Mini USB-IO box. Note: If you disconnect the Mini USB-IO box while EthoVision XT is open, reconnect it. Note that It can take some time before the Mini USB-IO box is recognized after you reconnect it. Although you use modular network cables to connect devices to the USB-IO box, the signal from and to the device is not a network signal. The device cannot be connected via a network hub or similar. The modular network cable comes with the hardware device, not the Mini USB-IO box. Connect custom hardware Whenever you want to connect your own device to a TTL control connector of the Mini USB- IO box, do so according the information below. The TTL connector will provide supply (18VDC) and TTL output and input to your device. It is a standard RJ45 modular type. Pinning and cable wire colors for the mating patch cable are shown in the figure below. To power a device, a +18 Volt power supply can be provided via pin 2 (orange). Common ground for both power and TTL on pin 1 and 8 (orange/white-brown). important Max. overall current for all TTL ports must not exceed 0.5 A! Whenever the device to be connected needs some other (lower) supply voltage, you must use some regulator in between or connect a separate power adapter to it. Input of a TTL device Two input lines are available for each TTL-connector, TTL-1 and TTL-2, connected to line 5 (white/blue) and 4 (blue) respectively. In the example below, two switches send inputs to EthoVision XT via a TTL port. You can use the TTL input to monitor the status of devices connected to those input connections. Inside the Mini USB-IO box, all TTL input lines are forced high to the +5V TTL logic level by a pull-up resistor. This enables open collector interfacing from your device into the Mini USB- IO box or you can just connect a simple switch between it and the ground. However, you can also connect any TTL logic level signal (0 Volt/5 Volt) to the input. To prevent unwanted behavior of input lines caused by noise or signal spikes, inputs are protected by debounce/ESD protection circuits. Output of a TTL device You can use TTL output to control any external device by simple 5V TTL logic. Each of the 4 TTL ports on the Mini USB-IO box is equipped with 2 TTL output lines. Every output line is protected with a current limiting resistor of 100 ohm. Maximum load current of the output is 10mA. Multi TTL output connector The Multi TTL output connector contains 16 independent output lines. Advised connector: Assmann AWP20-7240-T-R. Pin number: 1-16 - 16 x TTL compatible output lines (TTL-1 to TTL-16). 17 - +5 Volt reference (max load 10 mA). 18 - +12 Volt reference (max load 10 mA). 19, 20 - Ground. Note: No TTL input lines are available on this connector. To control non-TTL hardware, some kind of interfacing may be needed. The Mini USB-IO box and EthoVision XT Defining Hardware configuration means that you specify which communication ports of the Mini USB-IO box are connected to which hardware devices, and, in the case you work with multiple arenas, which individual device is assigned to which arena. 1. Connect the hardware devices to the computer through the Mini USB-IO box (see page 139), then start EthoVision XT. 2. Create a new experiment or open an existing one. 3. Under Setup, click Experiment Settings. Define the main characteristics of the experiment. 4. Select Use of Trial Control Hardware and click Settings. 5. In the window that opens, select Noldus Mini USB-IO Box. 6. In the Device Configuration window, select the devices you require. For more information on this step, see set the port connections on page 109. 7. Under Setup, select Arena Settings. Define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. If you have only one arena, you can skip the steps below. The hardware is automatically assigned to the arena. If you have more than one arena, proceed with step 8. 8. Click the Arena - hardware mapping button in the Arena Settings window. 9. Click Add device. Under Device type, select the device and assign it to one of the arenas. Repeat this step for all the individual devices in your setup. Make sure you assign each device to one arena. For more information on this step, see assign devices to arenas on page 113. 10.Choose Setup > Trial Control Settings. Define the Trial Control protocol (see page 23 in this manual). note To use the Pellet dispenser with the Mini USB-IO box, you must replace a device file in EthoVision XT. See the instructions connect the pellet dispenser in the chapter The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 17 - Service Manual. note If you created a DanioVision experiment, or if you used a DanioVision predefined template, select the DanioVision version that you have. For more information on setting up an experiment with the DanioVision Observation Chamber, see the DanioVision DVOC-0041 - Reference Manual. The Ttl Port Tester Use the TTL Port tester to test or demonstrate the TTL control functionality of the USB-IO box. You can also use it to simulate a TTL device (for example a pellet dispenser), trigger an action (for instance, switch on a light) or as a manual input device. Your TTL Port tester package includes a TTL Port tester PTTB-001x (Figure 36) with a green RJ45 modular cable connected (1 meter long). Technical specifications Noldus device number: PTTB-001x. Power supply: 5 V DC, supplied by the USB-IO box. Current consumption: 30 mA (when one of the LEDs is on). Connector: RJ45 8 pin modular. Dimensions: 60 x 40 x 20 mm (l x w x h). Weight: 50 grams. CE compliant in accordance with EMC directive 2004/108/EC. Test the USB-IO box TTL functionality We assume that you have set the port connection in the Experiment Settings and assigned the TTL Port tester to the arena (see configure ethovision xt on page 136). 1. Make sure that the USB-IO box is connected to (A) your EthoVision XT computer and (B) a power supply. Figure 36 The TTL Port tester. 2. Connect the TTL Port tester to the TTL port on your USB-IO box which you want to test, using the green RJ45 modular network cable. When both the USB-IO box and the TTL Port tester are properly connected, the TTL power LED on the TTL Port tester is on. 3. Start EthoVision XT and open your experiment. In the Experiment Explorer, click Arena Settings. 4. In the Arena Settings window, click the Arena - Hardware mapping button. 5. In the Arena - Hardware mapping window, under the arena name, select TTL Port Tester (PTTB-001x) and click the Test button. 6. A new window appears. In the Command drop-down list, select either Light 1 on, Light 1 off, Light 2 on or Light 2 off and click Test. Check the LEDs on the TTL Port tester (Light 1 corresponds to OUT-1, and Light 2 to OUT-2) and the information in the window. note The signal from and to the TTL Port tester is not a network signal. The TTL Port tester cannot be connected via a network hub or similar. Manual input You can also manually supply TTL input events to a TTL port. Follow steps 1-5 in the procedure above. Press either button IN-1 or IN-2 on the TTL Port tester and check the result in the window. Simulate a TTL device You can connect the TTL Port tester to a TTL port that is defined for another TTL device, for instance, the Noldus Pellet dispenser. In this way, you can simulate the working of the device. You will see that the OUT-1 LED on the TTL Port tester is turned on whenever EthoVision XT decides to have the dispenser drop a pellet. Because it is not the pellet dispenser connected to the port, there will be no "pellet dropped" reply, but you can simulate this by pressing the IN-1 button on the TTL Port tester. The IN-2 button on the TTL Port tester is connected to the same input as the "error" line of the pellet dispenser. With a pellet dispenser connected, this line while become active whenever the dispenser fails to drop a pellet. By pressing the IN-2 button, you can simulate this occurrence. Figure 37 Hardware log when the TTL Port tester is used to simulate a pellet dispenser. EthoVision XT sent two times the command to drop a pellet. With each command the OUT-1 LED on the TTL Port tester was turned on. Each time the OUT-1 LED was on, the IN-1 button on the TTL Port tester was pressed. At t = 50.56 IN-2 was pressed to simulate the error state. Trigger an action with the TTL Port tester You can use the manual input buttons on the TTL Port tester to trigger an action, for instance, switch on a light. Define a Trial Control condition based on the TTL Port tester and define that the light is switched on when, for instance, IN-1 is pressed. 1. Open your Trial Control Settings and in the Components pane click the button next to TTL Port Tester (under Conditions - Hardware). 2. In the Signal to check drop-down list select: Is button 1 pressed? or Is button 2 pressed? and in the Signal value drop-down list select True. Then click OK. The light will be on as long as the button is pressed. Button 1 presses or Button 2 presses and in the Signal value drop-down list, select = and enter 1 as the value. Then click OK. Figure 38 Using the TTL Port tester to trigger an action (switch on a light). Figure 39 Using the TTL Port tester to trigger an action (switch on a light). Every time button 1 is pressed, the light switches on. When button 1 is pressed again the light switches off. To define the appropriate action: 1. In the Components pane under Actions, click the button next to the hardware you want to control. 2. In the Action to perform drop-down list, select which action should follow the condition you defined above. Then click OK. 3. Insert the Condition and Action box in the appropriate position in the Trial Control rule. Use the TTL Port tester as a manual event recorder Although you can score behaviors manually with EthoVision XT, you can also do so with the TTL Port tester. For example, in a resident-intruder test, during acquisition press the IN-1 button when the resident mouse is aggressive and the IN-2 button when the intruder mouse is aggressive. For more complex coding schemes, use the Manual Scoring Settings in EthoVision XT. If you use the TTL Port tester as a manual event recorder, you can view the number of key presses in a hardware log. In EthoVision XT from the Export menu, choose Track Data and select the Hardware log check box. Calculate the statistics for the TTL Port tester For testing purposes, you can calculate the number of times the buttons were pressed, or visualize when the lights were switched on. To do so, in the Analysis profile: Figure 40 Hardware log with the number of key presses. To analyze and visualize button presses, under Hardware click the button next to Hardware continuous. In other cases, skip this step. In the window that appears, next to Device type, select TTL Port Tester (PTTB-001x). Next to Device, select the correct device if you have more than one device connected. Next to Signal, select Button 1 pressed, or Button 2 pressed. To analyze or visualize the time when the lights were switched on, under Hardware select Hardware Command, or Hardware State. Choose Command to view the time that the command was given. Choose Hardware state to visualize the status of the light (feedback from the TTL Port tester). In the Trial Statistics tab, of the variable properties window, select the statistic Total, then click Add. You can now calculate the number of times the button was pressed, or the light was switched on and off, by running an analysis. Choose Analysis > Results > Statistics & Charts. Make sure that the correct Analysis profile is selected on the toolbar. Next, click Calculate. You can also visualize the button presses and the light being switched on and off in the Integrated Visualization. Choose Analysis > Results > Integrated Visualization. You now see in the Time Event Plot when the buttons were pressed, or when the lights were switched on and off. The Optical Isolated Ttl-io Interface Aim To enable isolation between the Noldus USB-IO box or the Mini USB-IO box and a third party device. For example the Inscopix nVista camera system. To connect the Noldus USB-IO box or the Mini USB-IO box to a third party device with BNC connectors. important This isolator is not intended for medical applications! Features It supports TTL-output from and TTL-input to EthoVision XT (two lines each). Output/input voltages 0-5 V. Isolation protects the device from the so-called "ground loops". Minimizes noise and prevents damage to the USB-IO box in the case the device connected does not function properly. Package contents PTISO-00x0 TTL-IO Isolator. 1x network cable with RJ45 connectors. 2x input/output double cables with BNC connectors. Connect and use - Connect a TTL port of the Noldus USB-IO box / Mini USB-IO box to the TTL-I/O port of the PTISO-00x0 Isolator. - Connect one or more of the In/Out BNC connectors of the PTISO-00x0 Isolator depending on your setup. For example, to trigger a device, use Out 1 or Out 2. - When setting the port connections (page 109), specify the TTL port and the line used. Technical specifications Type name: PTISO-0010 TTL-IO Isolator. Power requirements: 18-24 V DC; 0.02 A from USB-IO box. Isolation value: Supply 2kV (1 sec); TTL IO 5.3 kV (1 sec). Connections: 1x RJ45 type from USB-IO; 4x BNC type, optical isolated TTL input/output. Input/Output: TTL level signal (0-5.5 V DC). Dimensions: 31 x 113 x 67 mm; (1 7/32 x 4 29/64 x 2 41/64 inches). Technical Specifications USB-IO box version 2 Noldus model number PTIO-002x Power supply 24 V DC Current consumption Max 2.0 A (Varies depending on the number and type of devices connected) Connections 12 TTL control connections (24 TTL Input lines and 24 TTL output lines) with RJ45 ports 13 Special Device Interface connections with RJ 45 ports Cables Power supply 24V 3A DC with mains adapter USB cable with connectors of type A and B Operating temperature 0 to +40 °C (+32 to +104 °F) Storage temperature - 20 to +70 °C (-4 to +158 °F) Operating humidity Up to 80%, no condensation Dimensions 160 x 160 x 90 mm / 6.3 x 6.3 x 3.5 inches (L x W x H) Mini USB-IO box version 1 ) Varies depending on the number and type of devices connected. Noldus model number PTIO-003x Power supply 24 V DC Current consumption 1.0 A important Max. overall current for all TTL ports must not exceed 0.5 A! See also Multi TTL output connector page 142 Interface to PC USB-2 I/O connections 4 TTL control (representing 8 TTL Input lines and 8 TTL output lines) with RJ45 modular type connectors 1 Multi TTL (representing 16 TTL output lines and external device supply) with 20 way IDC connector 1 Special Device Interface with RJ45 modular type connector Cables Power supply 24V type 70 A24 with mains adapter USB cable with connectors of type A and B, 3m type SB2403 Operating temperature 0 to +40 °C (+32 to +104 °F) Storage temperature - 20 to +70 °C (-4 to +158 °F) Operating humidity Up to 80%, no condensation Dimensions 175 x 81 x 30 mm / 6.9 x 3.2 x 1.2 inches (L x W x H) Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT - Connecting Optogenetics Hardware URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-connecting-optogenetics-hardware Chapter: EthoVision XT What Components Are Required? The complete system will include: - EthoVision XT and the computer it is running on - The Trial & Hardware Control Module for EthoVision - The USB IO box or Mini IO box connected to the computer via USB - A laser or high intensity LED light source - A pulse generator - Fiber optics, connectors, canula, etc (outside the scope of what is discussed here) EthoVision XT can be used to control a laser or LED for Optogenetics, triggering the light based on time or on the animal's activity. For example, the laser may be turned on when the animal enters a given zone. EthoVision will not pulse the laser. If that is required, a separate pulse generator will be needed. But EthoVision will trigger that pulse generator to start and stop pulsing. In general, a laser or light stimulus can be used for inhibition without pulsing, but stimulation will require pulsing (e.g. often at 20 Hz). You will need a cable from one of the TTL ports on the USB IO box or Mini IO box to your pulse generator (or directly to the laser if no pulse generator is being used). This cable will have a RJ45 connector on one end (the same as a typical network cable), and typically a BNC connector on the other (depending on the equipment to be connected). Basic Setup Within EthoVision All hardware devices to be controlled must be set up at several points within your experiment: - In the Experiment Settings, check the checkbox for Use Of Trial Control Hardware. (Note: this option will not appear if you do not have the Trial & Hardware Control Module.) - Click the Settings button next to that checkbox, and select the USB IO box or Mini IO box, depending on which you are using. For the TTL port you have connected your cable to, select Custom Hardware as the device type. - In the Arena Settings, click the Arena-Hardware Mapping button at the lower right. Your device should be listed here; if not, click Add. Make sure your device is selected in the Arena 1 column. If you have multiple arenas, you can assign a device to each arena on the same line so they will operate according to the same trial control rules (but independently per arena). - While in the Arena-Hardware Mapping window, you can test whether the laser is hooked up properly by selecting the device in the Arena 1 column and then clicking Test. Select Output 1 High and click the Test button to turn the TTL output on, or Output 1 Low and click the Test button to turn it off. If the laser does not respond as expected, you will need to adjust the settings on your pulse generator (see next section). Setting Up the Pulse Generator EthoVision is highly adaptable and can be used with a wide variety of pulse generators. This type of equipment normally uses a simple 5V trigger signal, regardless of maker, so it's just a matter of providing the correct type of cable and setting the pulse generator correctly. An Arduino can also be used in place of a pulse generator for those willing to do their own wiring. Contact Noldus support if you need assistance finding the settings for other models. Pulse generators have three general types of settings: Manual Mode There is a mode in which the laser/LED is controlled manually, which is helpful for testing the apparatus. Fixed Duration Mode A second mode triggers the pulse generator to provide a stimulus of a fixed duration (usually a "train" of pulses), which can be useful if you want the stimulation to be exactly the same each time: - Prizmatix Pulser: "Execute pulse sequence each time after trigger(s)." - AMPI Master-8 and Master-9: "Train" - Agilent Waveform Generator: "Triggered Burst Mode." Continuous Trigger Mode The third mode is one in which the pulse generator begins its output when the trigger is turned on, and then continues repeating that output until the trigger is turned off. This is ideal if you want the stimulation to continue as long as the triggering condition is true, for example as long as the animal remains in a particular region. - Prizmatix Pulser: "Execute pulse sequence after trigger HIGH, then stop when LOW." - AMPI Master-8 and Master-9: "Gate" - Agilent Waveform Generator: "External Gated Burst Mode." - Plexon PlexBright: Use "Edge Digital Input" mode in which one trigger input turns the signal on and a separate trigger input turns it off. Note that, in the trial control settings, you will still need to turn the triggers off after a certain minimum time before they can be turned on again. EthoVision Trial Control Settings Use the Trial Control to define how long the trial should run, and at what points devices should be turned on and off. The simplest possible optogenetics trial would present the stimulation (or inhibition) at a particular time. The Trial Control is simply a flow chart of the events of the trial. Individual steps in the trial can be named to make it easier to refer to them in the analysis. For example, an experiment may include an initial 5 minute pre-stimulation period, followed by a minute of stimulation, and then 5 minutes post-stimulation. Any number of events can be strung together this way. The events flow in the direction of the arrows, and when they reach Stop Track, the trial is over. Repeated Stimulation Sometimes you want to repeat events over and over. It's possible to do that by stringing many boxes together, but it can be easier to create a Sub-Rule which repeats a predefined number of times. In this example, after the 5 minute pre-stimulation period, the sub-rule is called three times. Each time, the stimulation is activated for two minutes, then turned off for two minutes. When the sub-rule has completed the third run-through, the trial continues to the Stop Track box and ends. Place-Preference A common scenario is a place preference test. In this case, the stimulation (or inhibition) occurs whenever the animal is in a particular zone. Instead of running the sub-rule a pre-determined number of times, the sub-rule runs repeatedly, checking whether the animal is in the zone or not. In this example, the stimulation begins when the animal enters the Left zone, and stops when the animal moves to the Right zone. Because the sub-rule will never complete (it will just keep checking which zone the animal is in), a time condition is added to control the duration of the whole trial (10 minutes in this example). Other Options Although the example above uses the zone to trigger the stimulation, it is possible to use any behavior the same way. Stimulation (or, for that matter, lights, sounds, pellet dispensers, or any other type of device) can be triggered based on: - Activity level - Velocity - Degree of turning - Other behavioral measures - Sensors, such as when a lever is pressed or a nose-poke sensor is triggered Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT - Experiments with Calcium Imaging URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-experiments-with-calcium-imaging Chapter: EthoVision XT Introduction EthoVision XT and Calcium Imaging To understand the working of neural circuits in the brain, it is vital to be able to view neural activity simultaneously with behavioral data. Calcium Imaging is a microscopy technique to optically measure the calcium (Ca2+) status of a cell, a tissue or a medium. This allows to monitor the electrical activity in single neurons at a spatial scale that is not possible to achieve with other techniques. The Inscopix nVista miniature microscope system enables researchers to conduct genetically targeted calcium imaging over time in awake, freely behaving rodents, and has provided insights from multiple brain areas, from the prefrontal cortex all the way to the hypothalamus. nVista's compact, sleek plug-and-play interface makes it easy to add powerful new neural circuit insights to any laboratory's behavioral research arsenal. You can combine EthoVision XT with the Inscopix nVista system in such a way that EthoVision XT takes control over the recording activity of nVista. For this you need the Noldus USB-IO box interface connected between the two systems. EthoVision XT and Optogenetic Stimulation In vivo Calcium Imaging is often coupled with Optogenetic stimulation to causally link neural circuit activity and behavior. For this purpose, the Inscopix nVoke system is coupled with EthoVision XT, which can trigger both calcium imaging and the optogenetic LED stimulation. The two triggering systems can be set independent of one another. Similarly to what is done for the EthoVision XT and the nVista system, you need the Noldus USB-IO box interface connected between EthoVision XT and nVoke. nVista vs nVoke - nVista is the Inscopix system for in vivo Calcium imaging in freely behaving animals. It includes a head-mounted miniature microscope that enables one-photon epifluorescence imaging of calcium dynamics, a correlate of neural activity. - nVoke is the Inscopix system that enables simultaneous in vivo Calcium imaging and optogenetic manipulations. EthoVision XT License Needed To enable control of Inscopix devices by EthoVision XT, you need the Trial and Hardware Control module. If you are not sure whether this function is activated, in EthoVision XT select Help > About EthoVision XT > License Info. If the Trial and Hardware Control checkbox is not selected, contact Noldus to purchase an upgrade with this module. Application Examples Place Preference in the PhenoTyper The nVista microscope is triggered every time the mouse enters a target region of the PhenoTyper, as defined in the EthoVision XT software. In an experiment that combines Calcium Imaging and Optogenetics, the PhenoTyper was divided in two side zones, and in each session one side was assigned as stimulus (LED)-paired side. Each time the mouse crossed to the stimulation side, stimulation was delivered until the mouse crossed back into the non-stimulation side (Stamatakis et al. 2018). Contextual Fear Conditioning Simultaneous Calcium Imaging and Optogenetic stimulation are performed during a fear conditioning experiment. Optogenetic stimulation during the shock phase reduced the percent time freezing during context retrieval (Jimenez et al. 2020). Motor Behavior Simultaneous optogenetics and calcium Ca2+ imaging is performed in different populations of cells to look into the functioning of fast-spiking interneurons in the control of motor behavior in an open field (Owen et al. 2018). References - Jimenez et al. (2020). Contextual fear memory retrieval by correlated ensembles of ventral CA1 neurons. Nature Communications 11: 3492. doi:10.1038/s41467-020-17270-w - Owen et al. (2018). Fast-spiking interneurons supply feedforward control of bursting, calcium, and plasticity for efficient learning. Cell 172(4): 683-695. doi: 10.1016/j.cell.2018.01.005 - Stamatakis et al. (2018). Simultaneous optogenetics and cellular resolution calcium imaging during active behavior using a miniaturized microscope. Frontiers in Neuroscience 12: 496. doi: 10.3389/fnins.2018.00496 Physical Setup Hardware Components - Noldus USB-IO box PTIO-002x - Noldus Optical Isolated TTL-IO interface PTISO-00x0 (also known as opto-isolator) - Inscopix nVoke or nVista DAQ box Connection Schemes Calcium Imaging (nVista) Connect one of the TTL ports of the USB-IO box to the opto-isolator using a network cable. Connect the Out-1 port of the opto-isolator to the TRIG port of the Inscopix device using cables with BNC connector. Calcium Imaging and LED Stimulation (nVoke) Connect the Out1 and Out2 ports of the opto-isolator to the TRIG port and the GPIO port of the Inscopix device using cables with BNC connector. Note that one TTL port on the USB-IO box can send signals through two independent output lines (Out 1 and Out 2). Make sure that the Trial Control procedure sends the correct commands to the Inscopix DAQ box through the two lines Out 1 and Out 2, one for TRIG and the other for GPIO. Notes Why Use an Opto-isolator? If you do not have the Noldus opto-isolator, you can connect the USB-IO box and the Inscopix directly. For this you need a cable with an Ethernet (RJ45) connector at one end and a BNC connector at the other end. However, we recommend using a Noldus opto-isolator to prevent ground loops and preserve the TTL signals. Use one opto-isolator per TTL port of the USB-IO box. EthoVision XT Settings Experiment Settings After creating a new experiment, choose Setup > Experiment Settings. Define the number of arenas, the features that you want to track, and the camera properties. To define the Inscopix devices: - Select Use of Trial Control hardware, and click the Settings button. - Depending on the type of USB-IO box you use, choose either Noldus USB-IO box or Noldus Mini USB-IO box. - Locate the TTL port that you use to connect the USB-IO box, and from the Device Type list choose Custom Hardware. - Under Device ID, enter a name for the device. For example, nVista Video, or nVoke Video, nVoke LED. - Repeat steps 3 and 4 to declare more devices. If you want to trigger Calcium Imaging and LED stimulation, you must use two TTL ports from the USB-IO box, one for the TRIG input and one for the GPIO[n] input of the nVoke device. - Click OK. Next, open the Arena Settings. Arena Settings Choose Setup > Arena Settings. Calibrate and define the outline of the arena(s) and the zones. To map the Inscopix devices to the arena(s): - Click the Arena - Hardware Mapping button at the bottom-right corner of the screen. - Check that the device appears under the arena name. In the case of multiple devices, assign each of them to one arena and make sure that they do not occur in the cells for other arenas. - Optionally, edit the Device name (default: Device A, B, etc.). You will see this name in the Trial Control Settings and in the Analysis profile. - Repeat steps 2 and 3 to map the remaining devices. Inscopix Devices - Connect the microscope to the subject and pass the cord through the tracking chamber or PhenoTyper and connect it to the Inscopix device. - On the Inscopix computer, launch the data acquisition software and adjust the imaging settings, such as the frame rate and the gain. - In the data acquisition software, select to trigger from external hardware. If you are doing Calcium Imaging only, you can use the Basic Recording mode in the Inscopix software. Make sure that the Recording Start mode is set to Triggered Recording. - When using optogenetics stimulation, in most cases you must use the Advanced Recording mode. Specify the type of stimulation, power, number of repeats, etc. See also the nVista and nVoke User Manual for examples. Acquiring Data Program Control of Devices in EthoVision XT Trial Control Settings The Trial Control Settings in EthoVision XT allows you to program activation of calcium imaging and optogenetic stimulation by Inscopix devices at specific times or when specific events occur, for example when the subject enters a target zone of the arena. In addition, in Trial Control Settings you can define the conditions for the start and stop of data acquisition. In EthoVision XT, choose Setup > Trial Control Settings > New, and enter a name for the new settings profile. For more information on how to work with Conditions and Actions in Trial Control Settings, see the EthoVision XT Help (press F1 in EthoVision XT) and the EthoVision XT 17 - Trial and Hardware Control - Reference Manual, which you can find in the Apps screen under Noldus > EthoVision XT 17 Other Documentation. Example 1 - Image Recording (nVista) Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. Next, EthoVision XT sends out a high TTL pulse to the TRIG port of nVista. After a time delay of 10 minutes, EthoVision XT stops tracking the subject. Hardware Connections Use the basic connections for triggering video recording from EthoVision XT in nVista systems. Prerequisites in EthoVision XT You specified the TTL port and output line (either 1 or 2) for TRIG in the Experiment Settings and mapped the port to the arena. Procedure - In the Trial Control Settings, under Actions, click the button next to Custom hardware. - Specify the device (e.g. Device A) and the type of signal (Output 1 High). - Optionally, edit the name in the Action name field. - Click OK and insert the Action box between the Condition - In zone box and the Action - Start track box. - Click Settings in the Condition - Time box and select 10 minutes. This way tracking stops after 10 minutes. - If you want to stop recording in nVista when you stop behavior tracking, bring a new Action box in the flow line which instructs the system to send out a low TTL pulse to nVista. Make sure that you place the Action box to the right of the 10-minute time box. In the Hardware Action box you can test whether EthoVision XT triggers the nVista by clicking the Test button. Make sure to instruct nVista/nVoke to record video based on the TRIG signal. Example 2 - Manual Video Recording, Triggered OG-LED Stimulation Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. You start video recording in nVoke manually by clicking the Record button. At the planned time, for example at 10 minutes after start, EthoVision XT sends out a high TTL pulse to the GPIO[n] port of nVoke. In the Inscopix DAQ software, under Video Recording configuration, make sure that Trigger is set to NONE and Control is set to Video Recording ON. Hardware Connections - Use the basic connections for triggering video recording and OG-LED stimulation from EthoVision XT in nVoke systems. You do not need to use the TRIG port of the nVoke device. - Set the GPIO[n] to Input in the Inscopix DAQ software. Prerequisites in EthoVision XT In the Experiment Settings, you defined the TTL port and output line (either 1 or 2) connected to the GPIO[n] of nVoke. In Arena Settings, you mapped that port to the arena. Procedure Because calcium imaging is started manually in this example, you only have to program the activation of the OG-LED. In the following example, the Time condition is set to wait 10 minutes before the triggering action. - In the Trial Control Settings, under Conditions, click the button next to Time. - Specify the time (e.g. 10 minutes). Optionally, edit the name in the Condition name field. - Click OK and insert the Condition box after the Action - Start track box (or wherever it applies in your protocol, for example in a sub-rule). - In the Trial Control Settings, under Actions, click the button next to Custom hardware. - Specify the device (e.g. Device A) and the type of signal (Output 1 High). - Optionally, edit the name in the Action name field. - Click OK and insert the Action box to the right of the Condition box just created. - When applicable, define a Condition and an Action (Output Low) for stopping the trigger action and insert them in the trial control flow line. Notes - In the Inscopix DAQ software, make sure to set the Trigger mode for the GPIO[n] port to Follow. - When the Trigger is set to low, LED stimulation is stopped. To set the Trigger to Low, add an Action to the same device/TTL port and output line as above, and select the signal Output Low. - You can also let the DAQ software run its own pulse protocol while the Trigger is ON. In that case the Control for the GPIO[n] port is set to Pulse protocol. - For more information, see the nVista and nVoke User Manual. Example 3 - Triggered Video Recording and LED Stimulation Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. Both video recording and the OG-LED are triggered by EthoVision XT when the corresponding conditions (time or event) are met. Hardware Connections - Use the basic connections for triggering video recording and OG-LED stimulation from EthoVision XT in nVoke systems. - Set the GPIO[n] to Input in the Inscopix DAQ software. Prerequisites in EthoVision XT In the Experiment Settings, you defined two TTL lines from the USB-IO box: one connected to the TRIG and the other to the GPIO[n] port of nVoke. In Arena Settings, you mapped the ports and lines to the arena. Procedure Define actions and conditions as explained for the previous examples. - Condition to trigger video recording. - Action to trigger video recording through the TRIG port. - Condition to trigger OG-LED stimulation. - Action to trigger the OG-LED stimulation through the GPIO[n] port. When applicable, define additional conditions and actions to stop video recording and OG-LED stimulation. Notes - In the Inscopix DAQ software, make sure to set the Trigger mode for the TRIG port to Follow, and the Control is set to Video Recording ON. In an alternative configuration, you can set Control to Recording schedule to record video for a specific time. - In the Inscopix DAQ software, make sure to set the Trigger mode for the GPIO[n] port to Follow. Select the type of Control you require (e.g. Pulse protocol). - See the Example Configuration #3 in the nVista and nVoke User Manual. Data Analysis Detection Settings Ensure your subjects are detected well by EthoVision XT. Choose Setup > Detection Settings. For more details, see the EthoVision XT Help. Sample Rate In the Video section, specify the sample rate. Source: EthoVision XT 17.5 Application Manual - Experiments with Calcium Imaging --- ## EthoVision XT - Fear Conditioning with Video Tracking URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-fear-conditioning-with-video-tracking Chapter: EthoVision XT Conduct Maze Integration with Noldus Ethovision Maze Engineers software ConductMaze is a light-weight adapter to video tracking software (Noldus EthoVision) to control the execution of Fear Conditioning. Experiment Setup in Ethovision In EthoVision, create an External Command Action with a name. In the "Select program to run", choose MazeController.exe and in the "Command line options", add open command(s) like D10. The options represent an action to open a door or close a door or dispense a pellet or a combo action. The following examples show some user configuration setups: - Example 1: MazeController.exe c=1,t=1,v=50,d=5,f=1000 - Example 2: MazeController.exe c=1,t=5,v=1,d=5,m=0.4 Example 1 will send a command to start a tone of a specified frequency for a duration of 5 seconds at a volume level of 50. Example 2 will send a command to start a shock for a duration of 5 seconds at a current level of 0.4mA. Command Parameters Command parameters for EthoVision video tracking: - c: Chamber — 1, 2, 3, or 4 - t: Message type - 1 — Frequency tone - 2 — Light - 5 — Shock - 6 — White noise - 7 — User sound file - v: Volume — 0 to 100 - d: Duration — 0 to 180 - f: Frequency — 100 to 18000 Frequency Tone - Type: t=1 - Start Command Example: c=1,t=1,v=50,d=5,f=1000 - Stop Command: c=1,t=1,v=0 Light - Type: t=2 - Start Command Example: c=1,t=2,v=30,d=5 - Stop Command: c=1,t=2,v=0 Shock - Type: t=5 - Start Command Example: c=1,t=5,v=1,d=5,m=0.4 - Stop Command: c=1,t=5,v=0 White Noise - Type: t=6 - Start Command Example: c=1,t=6,v=50,d=10 - Stop Command: c=1,t=6,v=0 User Sound File - Type: t=7 - Start Command Example: c=1,t=7,v=50 - Stop Command: c=1,t=7,v=0 Note that , is the separator and there is no space between parameters. A command can be a single command or a composite one. A composite command is composed of individual commands separated by ;. For example, the composite command c=1,t=5,v=1,d=5,m=0.4;c=1,t=1,v=50,d=5,f=1000 will instruct the fear conditioning system to deliver a shock to chamber 1 and simultaneously play a tone on chamber 1. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT - General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-general-information Chapter: EthoVision XT EthoVision XT Settings Create the Experiment - Start EthoVision XT and choose File > New from template. - In the Select a template option window, select Apply a pre-defined template. Next, follow the instructions in the guided setup. For more information, see Set Up an Experiment in the EthoVision XT Help. For details on connecting the camera, see Camera Installation in the EthoVision XT Help, or watch the video tutorial Set Up the Camera (Help > Video Tutorial). - Enter the name of the experiment and click OK. - Before you can actually acquire data, check the settings listed in the rest of this section. Experiment Settings Choose Setup > Experiment Settings. Under Video Source, and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. Note: The option Deep learning is only available if your PC has a graphic processor (GPU) that supports additional software (CUDA). See Deep learning: Requirements and Limitations in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. - Click Grab to grab an image of the empty enclosure from the camera image, or click Browse to select a video file and then click Grab. - Click 1. Draw Scale to calibrate your arena. - Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. For open fields and other enclosures, remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. - To draw zones, click 3. Select Shape and Draw Zones. See more details in the chapter about your test. For details, see Arena Settings in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of data acquisition. For details, see the EthoVision XT Help. Choose Setup > Trial Control Settings. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. - If you work with pre-recorded video, select a video file. If you work with the live camera image, release the animal in the arena. - Click Automated Setup. - Select: - Rodent for tracking rats and mice. - Adult fish for tracking fish from the top view. - Other for any other case like tracking insects, crustaceans, or when tracking fish from the side view. - When the subject does not move a lot, and is far from the enclosure walls and other objects, draw a rectangle around it. EthoVision XT detects the subject. - If the subject's body is well detected (marked in yellow), click Yes. - In other cases move the Finetune slider or click No and adjust the Advanced detection settings. Note: The Automated Setup may not work in all situations. If the subject is not detected correctly, see the Advanced detection settings below. Advanced Detection Settings - Under Video, choose the sample rate. - Under Method, check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if other methods do not work well, or if you work with hooded animals. - Select the tracking method. The options here depend on your experiment settings, including the number of body points you want to track. The optimal method is automatically selected after choosing the type of animal in the Automated Setup. For more information, see Tracking methods in the EthoVision XT Help. - When using Dynamic subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. When using Differencing, set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. For more information: - Choose Help > EthoVision XT Help and search for Advanced Detection Settings. - Choose Help > Video Tutorial and watch the videos under How Subject Detection Works. Trial List Choose Setup > Trial List. Enter your independent variables such as rat ID, first or second phase of the experiment, treatment (with values drug vs. control), dose, type of object, name of the experimenter, etc. If you want, you can pre-define all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a series of trials in the EthoVision XT Help. Acquiring Data Protocol Each test described in this manual has one or more specific protocols. See the chapter that applies. Important: Always record your video with EthoVision XT or Media Recorder. Do not record video with Pylon Viewer or other software. The resulting video file may not be compatible with EthoVision XT. Acquire the Tracks - Check that you have selected the correct Video Source in the Experiment Settings. - Choose Acquisition > Open Acquisition. - Optional: Skip this step if you have entered the values of the independent variables already in the Trial List. Open the Independent Variables tab of the Analysis Results and Scoring pane at the bottom of your screen and enter the values of the independent variables. You can also do this during acquisition. - If you did not plan any trials in the Trial List, click the New trial button in the Playback Control window (Ctrl+F3). - If you planned two or more trials, select in the Acquisition Settings window whether you want to track only the next planned trial, or all planned trials. If you carry out batch acquisition and track live, also specify the Inter-trial interval. - Optional: In the Acquisition Settings window, select Auto-start data analysis. Do this to start calculation of analysis results immediately after acquisition. If you choose this option, first create an Analysis profile and optionally a Data profile and a Track Smoothing profile. Choose whether to carry out analysis only for the profiles highlighted in blue in the Experiment Explorer, or for all possible profile combinations. In the latter case, first delete all profiles you do not need for analysis. - Start the trial (either choose Acquisition > Start Trial or click the Start trial button in the Playback Control window or press Ctrl+F5). - If you do live tracking, release the animal in the arena. - Data acquisition starts when the Start track condition in your Trial Control Settings becomes true. - The trial stops automatically when the Stop track condition specified in the Trial Control Settings becomes true or when the time defined in the Trial Control Settings under Maximum trial duration has expired. If you planned a series of trials, the next trial will start. To stop the trial manually, either choose Acquisition > Stop Trial or click the Stop trial button in the Playback Control window or press Ctrl+F6. If you chose to simultaneously record a video file, the video file that has been created is stored on your PC in the Media Files folder of your experiment. After Testing After each test, remove any debris (bedding, feces, etc.) from the arena and clean all interior surfaces, walls and floor thoroughly, first using water and soap, or a perspex cleaner, then with water. Allow at least 5 minutes between tests to ensure that any residual odor will have dissipated before the next animals are introduced into the test apparatus. Do not use wet ethylene oxide, steam, strong acids, hydrocarbons, ethanol, methanol, or solvents containing acetone. Acceptable techniques and substances for cleaning acrylic (perspex): - Electronic beam - High intensity visible light - Gamma radiation - Alkaline substances (in low concentrations) - Ethylene oxide gas - Low-temperature hydrogen peroxide gas plasma - Hydrogen peroxide (up to 3%) - Diluted solutions of isopropyl alcohol - UV radiation Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you do not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile. Select one or both options to remove noise and artifacts due to for example body wobbling. For more information, see Smooth the Tracks in the EthoVision XT Help. Select Data for Analysis Choose Analysis > Data Profile. The data you select on this screen will be analyzed or visualized. - To analyze data per zone, in the Result box, click Settings and select Results per zone. Use this function for example to analyze the velocity of the subject in the different zones. - To analyze some tracks but not others, under Filter, choose one of the variables available. For example, choose Treatment to analyze treated animals only. Insert the box in the Data profile sequence. - To analyze segments of tracks based on the subject's behavior, under Nesting choose one of the options. For example, to select all data points when the subject was moving, choose Movement. Insert the box in the Data profile sequence. - To analyze the tracks split in segments of equal duration, in the Result box, click Settings and select Time bins. Use this function for example to analyze a 10-minute recording in ten segments of one minute each. - To create groups of tracks and compare results, under Common Elements click Result and add a Result box. You can link each Result box with a specific Filter. This way you can compare the results of different selections, or visualize groups of tracks that result from different treatments, etc. For more information, see the EthoVision XT Help. Visualize the Data You can visualize your tracks in three ways: Plot the Tracks Choose Analysis > Results > Plot Tracks. You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals treated with saline and red for drug-treated animals). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast. To set the track colors, in the Track Plot Settings pane, click the Colors tab. Plot Integrated Data Choose Analysis > Results > Plot Integrated Data. Look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Just like with plotting tracks, you can show tracks or sample points in different colors. Plot Heatmaps Choose Analysis > Results > Plot Heatmaps. Make heatmaps of the location of your animals during the tracks. For more information, see Visualize Data in the EthoVision XT Help. Calculate the Statistics General Procedure - Choose Analysis > Analysis Profile > New. Select the variables you are interested in. For information about the variables suggested, see the chapter about the test of your choice and the EthoVision XT Help. - Choose Analysis > Results > Statistics & Charts, then click Calculate. The Trial Statistics tab shows the results per trial. The Group Statistics tab shows the statistics and charts from the results over all trials or the groups defined in your Data profile. Adjust the Table Layout (Optional) Sometimes you need to adjust the layout of your results table, for example to export the results to a statistics software. Click the Layout button on the toolbar and specify which headers should be on the rows and which on the columns. For details and examples, search for table layout in the EthoVision XT Help. Batch Calculations It is also possible to carry out multiple calculations at once with different filters, data profiles or analysis profiles. - In the Statistics & Charts window, click Batch. - Select the profiles from the lists and click Add. - Repeat the previous step for other combinations. - Click Calculate. Choose the profiles from the lists on the toolbar to view the analysis result for that combination. For more information, see Calculate Statistics in the EthoVision XT Help. Advanced Analysis with JavaScript Custom Variables In the Analysis profile you can create fully custom dependent variables with JavaScript code. With JavaScript you have an almost endless range of possibilities to extract information from your tracks. JavaScript variables can be of type continuous, event, or state. See JavaScript in the EthoVision XT Help. Note: If you are not familiar with programming, Noldus can create custom analysis variables for you. Please contact Noldus for information. Export the Results To find out if your independent variables (like treatment, dose, etc.) have a significant effect on the dependent variables, you can export your data to a statistical package. - Choose Analysis > Export > Statistics. - Choose Trial Statistics or Group Statistics. You can also export the raw track data. Choose Analysis > Export > Raw Data. Source: EthoVision XT 17.5 Application Manual - General Information --- ## EthoVision XT - GigE Camera Installation and Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-installation-and-setup Chapter: EthoVision XT Camera Settings and Installation Guide for GigE Cameras in EthoVision XT Gain and IR Filter Notes If you need to increase the camera's Gain (Raw) setting in Pylon, do not increase it too much or you will increase camera noise. Consider adding a second IR light if that is the case (and lowering the Gain (Raw)). As of approximately mid-July 2018, color GigE cameras (model: acA1300-30gc) purchased from Noldus after this date had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). If you bought a color GigE camera from Noldus prior to approximately July 2018, see the IR block filter removal instructions below to make your color camera IR sensitive. If you require an IR pass filter, it simply screws on to the front of the lens. Color to Monochrome If you have a color camera, you can temporarily change it to monochrome by changing the Pixel Format setting. Note: This does not make the camera IR sensitive. For IR sensitivity you must either remove the IR block filter from your color camera or use a monochrome GigE camera. As of approximately mid-July 2018, color GigE cameras (model: acA1300-30gc) purchased from Noldus after this date had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). If you bought a color GigE camera from Noldus prior to approximately July 2018, see the IR block filter removal instructions above to make your color camera IR sensitive. B - Mounting the Camera This section only applies if you bought either a Dual Option Mount and/or an Autopole with Superclamp from Noldus. Note: The items described below are NOT standard with your camera or system. Contact sales if you would like a quote to purchase. Dual Option Mount The item that connects to the camera uses a standard size tripod fitting screw on top, which fits the hole on the camera. The camera will also work with other mounts that accommodate this standard fitting. There are two alternate types of mountings that screw into the bottom of the camera fitting: - The one with three tabs is a general purpose mount that would be screwed into a wall or ceiling. This is a permanent mount. - The other is designed to attach to suspended ceilings. There are two parts that move like scissors. Open the mount so it fits over the framework of the suspended ceiling, then close them to hold. This is a temporary mount. It is sturdy, but you can open the mount to remove it from the ceiling and place it elsewhere. If you have a suspended ceiling, this is likely the best solution. Note: See below for how to use the Dual Option Mount with the Autopole and Superclamp. Autopole - Black mounting rod for camera use. - Range is 2.1 to 3.7 meters, or up to 5.7 meters with the extension (extension sold separately). - Typically installed horizontally between two walls, but can be installed vertically if you have a Dual Option Mount. - Must be installed horizontally if the system came with a Standard Camera Mount. - Often ships separately via UPS from the rest of your Noldus order. Autopole and Superclamp - The camera is connected to the Superclamp with a brass stud connector. - The Superclamp is then clamped onto the Autopole. Vertical Installation You can mount the Autopole vertically between the floor and the ceiling to do side view tracking if the system came with a Dual Option Mount. This allows you to turn the camera as needed. Note: It is NOT possible to right the image in Pylon. You must have a Dual Option Mount for vertical installation. C - Installing the Ethernet Board on a Desktop PC Aim To install an Ethernet (network) board that receives video from one or more GigE cameras. Note: If you ordered a computer from Noldus Information Technology when you purchased EthoVision XT and Basler GigE cameras, the Ethernet interface board(s) has already been installed and tested. If you bought your computer somewhere else, you will have to install the board yourself. Follow the instructions below. This topic applies to Ethernet interface boards that have been tested with EthoVision XT: - One-port board: the Intel PRO/1000 CT (or its successor), to connect one camera. - Four-port board: the Adlink PCIe-GIE74 (A), or the Basler GigE Interface Card (B) to connect up to four cameras. Procedure - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. Different PCIe slots have different properties, resulting in different performances. When possible, choose the slot that gives maximum performance. To estimate performance, take note of the slot version and compare it with the following: - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: approximately 1 GB/s - PCIe v4.0: approximately 2 GB/s - PCIe v5.0: approximately 4 GB/s Note that values are given per lane and should not be multiplied by the number of lanes in a slot (for example, x4) since the board has a 1x connector. For example, SLOT1-PCIe3x4 written near the slot means version 3.0 with four lanes. IMPORTANT: Do not insert the PCIe board in the blue or white slots. - Unpack the Ethernet board, place it into the slot, and press it carefully into position. If the board does not fit into place easily, remove it and repeat the operation. IMPORTANT: When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet and attaching its clip to the metal frame of the computer. If you do not have an earthing wristlet, hold the metal frame with one hand while holding the Ethernet board in your other hand. Ensure also that your clothing does not touch any components while handling the board. - This step only applies when installing a 4-port Ethernet interface board. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. - Fix the board to the chassis and re-fit the computer's cover. - Next: Install the driver software for the GigE cameras. IMPORTANT: Turn off Fast Startup in the Windows Power options. How to Disable Fast Startup - Open the Windows Control Panel and select System and Security. - Under Power Options, select Choose what the power button does. - Click Change settings that are currently unavailable. (Requires an admin password.) - Under Shutdown settings, de-select Turn on fast startup (recommended), Sleep, and Hibernate. D - Installing the Pylon Driver for the GigE Camera Aim To install the software that enables you to configure the camera, for example to set the video frame rate or the exposure time. Procedure via EthoVision XT 17.5 Installation - Insert the EthoVision XT installation USB stick into your computer. If your EthoVision XT installation stick is not available, download EthoVision XT 17.5. - Double-click EthoVision XT - Setup - 17.5.1718.exe. If you have already installed EthoVision XT, select Modify; otherwise select Install. Note: The folder where this file is stored must also contain the following files for a successful installation of EthoVision XT 17.5: - EthoVision XT - Package - 17.5.1718.msi - TrackerInterfaceNN_x64_2.0.10.msi - Under Drivers and tools, select: - Basler GigE camera driver if you have Basler GigE cameras. - Daheng Galaxy if you have a Daheng GigE camera. - Click Install/Update and continue with installation. - Next: Assign IP addresses. Note: Always install the drivers from the installation USB stick or the Noldus web site. Do not install drivers from other sources unless requested by Noldus Support. Procedure for Manual Installation of Pylon 7.1.0 - Download Pylon 7.1.0 and double-click the downloaded EXE file. - Accept Terms and Conditions, then click Next. - Under Profiles, select Custom, then click Next. - Under Features, select: - GigE Camera Support (or USB Camera Support if using a Basler USB Camera) - DirectShow Support - Pylon Viewer - Complete the Pylon 7.1.0 driver installation. E - Assigning an IP Address to the Network Card - In Windows, search for Network Connections. Alternatively, in Windows 11, from the Start menu choose Settings, then Network and Internet, then Advanced network settings (at the bottom of the screen), then More network adapter options. - In the Network Connections window, right-click the item that corresponds to your camera and click Properties. Tip: If your computer has more than one item, unplug the camera and take note of which item shows Unplugged. Note: You may see one or more additional items labeled Ethernet or similar. This is the standard interface board connected to your local network and internet. Do not use that board unless it is the only one available. If you choose that adapter you will not be able to connect the EthoVision XT computer to the network. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Select Use the following IP address and Use the following DNS server addresses and fill in the details as shown below. Also select the option Validate settings upon exit. When done, click OK and then Close. US and Canada customers: Use 192.168.200.101 for the computer network adaptor IP address. For multiple network cards or a single card with multiple ports, use 192.168.201.101 for the second card or port, 192.168.202.101 for the third card or port, and so on. Subnet mask should be 255.255.255.0. - A Windows Network Diagnostics window appears. Click Close when it is finished, then close all windows. Note: If you purchased a 2 or 4 port network card, follow the above procedure once for each network card or port. For more information about using multiple cameras, see Section I. F - Connecting the GigE Cameras to the PC Aim To make sure that EthoVision XT receives the video signal from the GigE camera. Prerequisites - You have followed the entire procedure in Install an Ethernet Board for GigE Cameras. - No matter how many cameras you use, you need a 1-Gb Ethernet interface board (desktop computers only). - When you use a 4-port Ethernet board, you can power the cameras with Power-over-Ethernet (PoE) injectors, or you can choose to connect the board to the power outlet inside the PC. See step 5 in Install an Ethernet Board for GigE Cameras. - When you do not use a 4-port Ethernet board, you must use 1-Gb Power-over-Ethernet (PoE) injectors; use one per camera. Procedure A - If You Have a Single or Dual Port Ethernet Board To connect one camera, you need a single or dual port Ethernet interface board. To connect two cameras, you need a dual port Ethernet interface board. In either case you need as many PoE injectors as cameras, since the single or dual port boards are not powered. - Using cross-network cables (cat-5e or newer), connect the Ethernet port or board on the PC to the IN port of the PoE injector. Connect the camera to the OUT port. Use the short cable between the PoE injector and the PC. Use the long cable between the PoE injector and the camera. - Power up the PoE injector and make sure that the two green LEDs labeled CONNECT and ON are lit. - If the green LEDs keep blinking, wait a few more seconds. If you see no change, disconnect the cables, then reconnect them. - Next: Configure the digital camera. You can also connect two cameras to two single-port Ethernet boards. Procedure B - If You Have a Four-Port Ethernet Board (Maximum of 4 Cameras, Power Injector Not Required) When you use this board, you can power the cameras without using PoE injectors. However, make sure that the board receives power from the PC. See step 5 in Install an Ethernet Board for GigE Cameras. - Connect each camera (up to four) to one of the ports on the Ethernet board. - Next: Configure the digital camera. Notes - Tip: Label the cameras and the Ethernet ports (for example Cam 1, Cam 2, etc.) and take note of the camera serial numbers. This may be useful when you need to know which camera is connected to which port and when you need to assign or adjust IP addresses. - The Power over Ethernet (PoE) injector is a device that passes power along with data (in this case, video data from the camera) on twisted-pair Ethernet cabling. G - Assigning an IP Address to the Camera - Connect the GigE camera to the PC. - In Windows, search for and start pylon IP Configurator. - Select the camera name that appears under the Ethernet port set in the previous procedure. This is the camera physically connected to that port. Note: The camera status will show as Not reachable. This is normal since the camera cannot yet communicate with the Ethernet port. - Under Static IP, fill in the details in the IP Address and Subnet Mask fields. US and Canada customers: Use 192.168.200.1 for the camera IP address. For a second camera on the same card or port, use 192.168.200.2, and so on. For multiple cameras and cards or ports, the first three numbers must match the address set for the network card the camera is connected to. For example, a camera connected to a card set to 192.168.201.101 can be designated as 192.168.201.1. Subnet mask should be 255.255.255.0 for all cameras. - Click Save and then close pylon IP Configurator, or repeat the procedure for the next camera. - Next: Configure the digital camera. H - Configuring the GigE Camera in Pylon Viewer If you will be using multiple GigE cameras in EthoVision XT at the same time in the same experiment, you need to configure EACH camera and they MUST have the SAME settings. Remember to save your settings for each camera. You will know when your camera settings are optimal when there are no Missing Samples or Interpolated Samples in EthoVision XT. Please see Section L for how to check and test that. IMPORTANT: All of the settings below can also be done in EthoVision XT, but they then ONLY apply to that one experiment, as the settings are not stored in the camera drivers. It is recommended to configure these settings in Pylon Viewer rather than in EthoVision XT to ensure that the settings are stored in the driver for future experiments. See Section P for more information about changing these settings in EthoVision XT. Aim To adjust settings in a GigE camera, such as the video frame rate, video frame resolution, and exposure time. IMPORTANT: The settings described below are stored in the digital camera, not in EthoVision XT. When working with multiple cameras, repeat the procedure for each camera. IMPORTANT: Do not use the Pylon Viewer software to record video. Always use EthoVision XT or Media Recorder. Always start with the general procedure below. The most common adjustments include: - Camera gain: Increasing the gain will brighten the image. - Pixel format: Change this setting if you have a color camera that is giving only a black and white image. - Center the camera: Change this setting if the image appears to be off to one side rather than centered. - White balance: Use this to correct an image with a color cast. It can especially help when using color marking in EthoVision. - Exposure time: Increasing exposure will brighten the image, but too high an exposure results in a high proportion of missed samples, gaps in the track, and potentially trials ending prematurely. 1. Procedure (General) - Make sure EthoVision XT (and Media Recorder, when present on the computer) are not running. - Start the Basler Pylon Viewer software that comes with the camera. Note: The Basler Pylon Viewer software is installed automatically when you install the camera drivers. - Choose Tools, then Options, and check that the User level is set to Expert or Guru. - In the Devices panel, double-click the item Basler under GigE or USB depending on the camera you have. - To preview the camera image, click the Continuous Shot button on the toolbar. IMPORTANT: Do not use the Record button if you want to record video. This creates very large files. Always use EthoVision XT. - Under Features, open the Basler GigE camera chosen in Step D and choose the settings you would like to change. Follow the applicable instructions below. Note: To be able to adjust the settings, click the Stop button first. - Save the settings. See Item 7 below. 2. Camera Gain This applies to both color and monochrome Basler cameras. Increasing the gain will brighten the image. IMPORTANT: Increasing gain also increases image noise. Do this only if no other option is available to improve the image brightness. For example, make sure that the lens aperture is at its maximum and increase lighting first. - In the Features panel, click Analog Control. - From the Gain Auto list, select Off. - Next to Gain (Raw), select the value you require. A higher Gain results in a brighter image, but also more noise and a grainy image. Note: This value is typically low, often no higher than 2. Use Exposure to brighten the image further if needed. - Save the settings. See Item 7. Source: EthoVision XT 17.5 - GigE Install and Setup Guide --- ## EthoVision XT - GigE Camera: Adjusting Camera Settings in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-adjusting-camera-settings-in-ethovision-xt Chapter: EthoVision XT Adjusting Camera Settings in EthoVision XT Adjusting camera settings directly within EthoVision XT has been possible since EthoVision XT v15 via the Noldus Basler Pylon Interface that EthoVision XT installs. However, Noldus Support recommends making these settings in Pylon Viewer as described in Section H. Settings made and saved in Pylon Viewer are applied across all EthoVision XT experiments. If you want to change the settings for a single experiment in EthoVision XT, follow the instructions below. Important: To improve the quality of the image, always try adjusting the lighting and camera aperture before changing the settings in EthoVision XT. Accessing Camera Settings in EthoVision XT - Choose Setup, then Experiment Settings, and click the camera button for the camera you require. - Open the tab you require. Format Tab The Format tab is only available for the first camera. The settings specified here are also applied to all other cameras. You can change the Resolution and Frame Rate in EthoVision XT, but the new values are not retained in the camera software after restarting the computer. They will, however, remain selected within EthoVision XT. Important: If you change the resolution, open Arena Settings and update the background image. If the Arena Settings are locked, delete all trials if possible, or make a duplicate of the Arena Settings and update the background image there. Resolution For single arenas with subjects more than a couple of centimeters long, a resolution of 384x288 (PAL) or 320x240 (NTSC) is sufficient. Higher resolutions provide more accurate tracking but result in larger video files when saving to a digital video file over a long recording period. If disk space is limited, use the resolutions noted above. For analog cameras, the resolution is determined by the TV standard. For some cameras, only one video resolution is available. Frame Rate The frame rate is the number of video images per second generated by the camera. For analog cameras, this is determined by the TV standard. For digital cameras, it can vary. A high frame rate is recommended when working with fast-moving animals or when detecting rapid movements such as startle responses in fish or rapid turns in flying insects. High frame rates require more processing power. If a high frame rate is selected, it may be necessary to lower the video resolution. A message will appear in this window when that is the case. Note that the frame rate is not the same as the sample rate. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: Camera Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-camera-settings Chapter: EthoVision XT Camera Settings Configuring the GigE Camera in Pylon Viewer If you will be using multiple GigE cameras in EthoVision XT at the same time and in the same experiment, you need to configure each camera and they must all have the same settings. Remember to save the settings for each camera. You will know when your camera settings are optimal when there are no Missing Samples or Interpolated Samples in EthoVision XT. All of the settings below can also be done in EthoVision XT, but they then only apply to that one experiment, as the settings are not stored in the camera drivers. It is strongly recommended to apply these settings in Pylon Viewer rather than in EthoVision XT to ensure that the settings are stored in the driver for future experiments. The settings described below are stored in the digital camera, not in EthoVision XT. When working with multiple cameras, repeat the procedure for each camera. Do not use the Pylon Viewer software to record video. Always use EthoVision XT or Media Recorder. The most common adjustments you may need to make include: - Camera gain: Increasing the gain will brighten the image. - Pixel format: Change this setting if you have a color camera that is giving only a black and white image. - Center the camera: Change this setting if the image appears to be off to one side, not centered in front of the camera. - White balance: Use this setting to correct an image with a color cast. It can especially help when using color marking in EthoVision. - Camera exposure time: Increasing exposure will brighten the image, but too high an exposure results in a high proportion of missed samples, gaps in the track, and potentially trials ending prematurely. General Procedure - Make sure EthoVision XT and Media Recorder, if present on the computer, are not running. - Start the Basler Pylon Viewer software that comes with the camera. The Basler Pylon Viewer software is installed automatically when you install the camera drivers. - Choose Tools, then Options, and check that the User level is set to Expert or Guru. - In the Devices panel, double-click the item Basler under GigE or USB depending on the camera you have. - To preview the camera image, click the Continuous Shot button on the toolbar. Do not use the Record button to record video. This creates very large files. Always use EthoVision XT. - Under Features, open the Basler GigE camera chosen in the previous step and choose the settings you would like to change. Follow the instructions in the subsections below that apply. To be able to adjust the settings, click the Stop button first. - Save the settings as described in the Save Camera Settings section below. Adjusting Camera Gain This applies to both color and black and white Basler cameras. Increasing the gain will brighten the image. Increasing gain also increases image noise. Only increase gain if no other option is available to improve image brightness. For example, first make sure that the lens aperture is at maximum, and that lighting is adequate. - In the Features panel, click Analog Control. - From the Gain Auto list, select Off. - Next to Gain (Raw), select the value you require. A higher Gain results in a brighter image but also more noise and a grainy image. This value is typically low, often no higher than 2. Use Exposure to brighten the image further if needed. - Save the settings as described in the Save Camera Settings section below. Setting the Pixel Format - Under Image Format Controls, locate Pixel Format and select the appropriate option from the drop-down list: - Select Mono8 for black and white (monochrome) cameras. - Select Bayer RG 8 for color cameras. - Save the settings as described in the Save Camera Settings section below. To identify which camera you have, look at the model number on the camera. It will look something like acA1300-60xx: - Where xx = gm, the camera is black and white (monochrome). - Where xx = gmNIR, the camera is black and white (monochrome) with Near Infrared. - Where xx = gc, the camera is a color camera. - All DanioVision units come with a black and white (monochrome) camera. Centering the Camera This procedure ensures the camera view is centered. If you center the camera view in EthoVision XT, the settings are not stored in the camera drivers. Setting this in Pylon Viewer ensures the settings are stored in the drivers for future experiments. - In the Features panel, open the Basler camera item and then the AOI Controls item. - Select both options Center X and Center Y. If you bought your GigE camera elsewhere or from Noldus but did not buy a PC at the same time, also set Width to 1280 and Height to 960. - Save the settings as described in the Save Camera Settings section below. Adjusting White Balance If you have a color camera, you also need to adjust its white balance. - Click Color Improvements Control. - Point the camera at a piece of white paper so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - Save the settings as described in the Save Camera Settings section below. Adjusting Camera Exposure Time The exposure time (or shutter time) is the time the camera shutter is kept open to let light in. The exposure time limits the maximum achievable frame rate. If the sum of the exposure time and the time needed for reading the chip (readout time) is greater than the time between consecutive video frames, the next frame may be dropped, resulting in a lower frame rate and missed samples during tracking. You will apply the following settings via Acquisition Control: - Exposure mode - Exposure Auto - Acquisition Frame Rate (Abs) [Hz] - Exposure Time (Abs) [us] - In the Features panel, open the Basler camera item and then double-click Acquisition Controls. - Set the Exposure mode to Timed. - Set the Exposure Auto to Off. - Set the Acquisition Frame Rate (Abs) [Hz] to 25 or 30. - Set the Exposure Time (Abs) [us] by entering the exposure time you require in microseconds, then press Tab or click another field to confirm. - This value will vary between 2000 and 15,000 depending on your lighting needs and Gain setting. - For Zebrafish larvae, enter 4000 or 2000 depending on the video resolution chosen. - In all other cases, you may choose a higher value. Faster animals require shorter exposure times. - If using DanioVision with a GigE camera: if resolution in EthoVision is 1280 x 960, use an exposure time of 4000. If resolution is 640 x 480, use an exposure time of 2000. Use the highest resolution that allows all wells to be seen on screen in EthoVision. - The ideal range of exposure will likely be anywhere from 2000 to 10,000 depending on resolution, frame rate, and lighting. - If lighting in the room is low, you will likely need a higher exposure (try 8,000 up to as high as 15,000). - It is unlikely you will need anything above 20,000 as motion blur has been observed in rodents at this setting. - When tracking in IR with an NIR GigE camera, you may need an exposure setting around 30,000 in order to brighten the image enough for tracking in EthoVision. - To check that the exposure time is compatible with the chosen frame rate, click the Continuous Shot button on the toolbar. At the bottom of the live video window, locate the resulting frame rate. This should match the value set for Acquisition Frame Rate (Abs) [Hz]. Noldus recommends 25 or 30. If the resulting frame rate is lower than the Acquisition Frame Rate (Abs) [Hz], either lower the exposure time (this will make the video image darker; open the lens diaphragm to compensate), or lower the video resolution. Repeat until you see the expected frame rate. A higher exposure setting will result in a brighter image, while a lower exposure setting will result in a darker image. However, too-high exposure will result in dropped frames, and too-low exposure may result in an image that flickers or changes rapidly between light and dark. The brightness of the image will also be affected by the aperture setting on the lens and by the camera gain. When adjusting the camera lens, the aperture adjustment will be labeled Open-Close or O-C. Turning it towards Open will brighten the image, while Close will darken the image. - Save the settings as described in the Save Camera Settings section below. Saving Camera Settings If you have multiple GigE cameras, make sure to save the settings for each camera. - Click the Stop button. - In the Features panel, open the Configuration Sets item. - From the Configuration Set Selector list, select User Set 1. - Next to User Set Save, click Execute. The camera settings are now saved under User Set 1. - From the Default Startup Set list, select User Set 1. This means that the camera always starts with the settings contained in User Set 1. - Close Pylon Viewer. These settings will be used each time you start up EthoVision XT. You can also save different settings for the same camera in User Set 2 and User Set 3. Under Default Startup Set, select which set you want EthoVision to use. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: How to Make a PC Report URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-how-to-make-a-pc-report Chapter: EthoVision XT How to Make a PC Report This section is only required if you have set up the camera correctly in both Pylon and EthoVision XT but are still experiencing problems with the camera. - Download the PC Report Utility and save it to your Desktop. - On the Desktop, locate the ZIP file, right-click it, and select Extract All, then click Extract. - In the SIW 2021 folder, double-click on siw64.exe. - Go to File, then Create Report File, then HTML Report. - Save the HTML file to your Desktop. - Send the HTML file as an attachment to support. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: Miscellaneous URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-miscellaneous Chapter: EthoVision XT Miscellaneous Laptops Only one camera is supported on laptops. The laptop's network card must be 1 GB/1000 Mbps or it will not be able to handle the load of the camera, which may result in Missing Samples or Interpolated Samples in EthoVision. This will be a dedicated camera network. If you want to be able to use the internet on the laptop you will need to use either Wi-Fi or purchase a USB network adaptor. Skip the Ethernet board installation section below, as it only applies to desktops. See the Pylon driver installation section for installing the drivers, then configure the laptop's network connection per the network card IP address section. Maximum supported time for live tracking and/or recording in EthoVision with a GigE on a Workstation laptop is 24 hours. For a Workstation desktop, the maximum is 72 hours. Cables If you bought your camera elsewhere, make sure you bought the correct cables and quality cables. Cheap or incorrect cables will affect frame rate and result in Missing Samples or Interpolated Samples. - Cat5e cable going from camera to power injector - Crossover cable going from power injector to PC: CAT6 cable recommended Power Injector If you bought your camera elsewhere and you are not using a 2 or 4 port powered network card, you need a power injector to power the camera and it must be 1 GB. IP Addresses When assigning the IP address to either the network card or camera, use the addresses specified in the relevant sections below. Do not use the IP address shown in any configuration images or whatever IP the PC defaults to. Tracking in IR The monochrome GigE camera is IR sensitive and does not require an IR pass filter unless you will be tracking in both light and dark conditions in the same trial. Depending on how bright your IR setup is, you might need to open the aperture on the lens all the way and/or adjust the camera's Gain (Raw) and/or adjust the Exposure setting in Pylon Viewer. If you need to increase the camera's Gain (Raw) setting in Pylon, do not increase it too much or you will increase camera noise. Consider adding a second IR light and lowering the Gain (Raw) instead. Color GigE cameras (model: acA1300-30gc) purchased from Noldus after approximately mid-July 2018 had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). If you bought a Color GigE camera from Noldus prior to approximately July 2018, the IR block filter will need to be removed to make your color camera IR sensitive. Should you require an IR pass filter, it simply screws on to the front of the lens. Color to Monochrome If you have a color camera, you can temporarily change it to monochrome by changing the Pixel Format setting in Pylon Viewer. Please note this does not make the camera IR sensitive. For IR sensitivity you must either remove the IR block filter from your color camera or use a monochrome GigE camera. Color GigE cameras (model: acA1300-30gc) purchased from Noldus after approximately mid-July 2018 had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: Network Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-network-configuration Chapter: EthoVision XT Network Configuration Assigning an IP Address to the Network Card - In Windows, search for Network Connections. Alternatively, in Windows 11, from the Start menu choose Settings, then Network and Internet, then Advanced network settings at the bottom of the screen, then More network adapter options. - In the Network Connections window, right-click the item that corresponds to your camera and click Properties. If your computer has more than one item, unplug the camera and take note of which item shows Unplugged. You may see one or more additional items labeled Ethernet or similar. This is the standard interface board connected to your local network and internet. Do not use that board unless it is the only one available. Choosing that adapter will prevent the EthoVision XT computer from connecting to the network. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Select Use the following IP address and Use the following DNS server addresses. Also select the option Validate settings upon exit. When done, click OK and then Close. US and Canada customers: Use 192.168.200.101 for the computer network adaptor IP address. If using multiple network cards or a card with multiple ports, use 192.168.201.101 for the second card or port, 192.168.202.101 for the third card or port, and so on. The subnet mask should be 255.255.255.0. - A Windows Network Diagnostics window will appear. Click Close when it is finished, then close all windows. If you purchased a 2 or 4 port network card, repeat the above procedure once for each network card or port. Connecting the GigE Cameras to the PC These steps ensure that EthoVision XT receives the video signal from the GigE camera. Prerequisites: - You have completed the Ethernet board installation procedure. - No matter how many cameras you use, you need a 1 Gb Ethernet interface board (desktop computers only). - When using a 4-port Ethernet board, you can power the cameras with Power-over-Ethernet (PoE) injectors, or you can connect the board to the power outlet inside the PC. - When not using a 4-port Ethernet board, you must use 1 Gb Power-over-Ethernet (PoE) injectors, one per camera. If You Have a Single or Dual Port Ethernet Board To connect one camera, you need a single or dual port Ethernet interface board. To connect two cameras, you need a dual port Ethernet interface board. In either case you need as many PoE injectors as cameras, since the single or dual port boards are not powered. - Using cross-network cables (Cat-5e or newer), connect the Ethernet port or board on the PC to the IN port of the PoE injector. Connect the camera to the OUT port. Use the short cable between the PoE injector and PC. Use the long cable between the PoE injector and camera. - Power up the PoE injector and make sure that both the CONNECT and ON green LEDs are on. - If the green LEDs keep blinking, wait a few more seconds. If you see no change, disconnect the cables and then reconnect them. - Proceed to configure the digital camera. If You Have a Four-Port Ethernet Board When using this board, you can power the cameras without using PoE injectors. Make sure the board receives power from the PC as described in step 5 of the Ethernet board installation section. - Connect each camera (up to four) to one of the ports on the Ethernet board. - Proceed to configure the digital camera. Label the cameras and the Ethernet ports, for example Cam 1, Cam 2, etc. Take note of each camera's serial number. This will be useful when you need to know which camera is connected to which port and when assigning or adjusting IP addresses. The Power over Ethernet (PoE) injector is a device that passes power along with data (in this case, video data from the camera) on twisted-pair Ethernet cabling. Assigning an IP Address to the Camera - Connect the GigE camera to the PC. - In Windows, search for and start pylon IP Configurator. - Select the camera name that appears under the Ethernet port set in the previous procedure. This is the camera physically connected to that port. Note that the camera status will show as Not reachable. This is normal since the camera cannot communicate yet with the Ethernet port. - Under Static IP, fill in the details in the IP Address and Subnet Mask fields. US and Canada customers: Use 192.168.200.1 for the camera IP address. For a second camera on the same card or port, use 192.168.200.2, and so on. When using multiple cameras and cards or ports, the first three numbers of the camera IP address must match the address set for the network card the camera is connected to. For example, a camera connected to a network adapter with IP 192.168.201.101 should be assigned an address such as 192.168.201.1. The subnet mask should be 255.255.255.0 for all cameras. - Click Save and then close pylon IP Configurator, or repeat the procedure for the next camera. - Proceed to configure the digital camera in Pylon Viewer. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: PCs Not Purchased from Noldus URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-pcs-not-purchased-from-noldus Chapter: EthoVision XT PCs Not Purchased from Noldus If you did not purchase your PC from Noldus, there are several crucial requirements to be aware of as well as some settings that may need to be configured. Without these in place, you may experience a variety of problems with this camera in EthoVision XT, including crashing, black image, low frame rate, missing or interpolated samples, or trials ending prematurely. If you are working with a laptop, the laptop's network card must be 1 GB or 1000 Mbps. A slower network card will not be able to handle the load of the camera and may result in Missing Samples or Interpolated Samples in EthoVision XT. If you cannot get the camera working properly on your PC after working through this entire document, please create a PC report as described in Section N and send it to support. Video Card Requirements Minimum requirement: The PC must have a stand-alone video card with at least 2 GB of memory that supports Direct3D Acceleration. A PC with only an onboard video card is not supported and should not be used with EthoVision. NVIDIA is the preferred brand. Deep Learning was introduced in EthoVision XT v16 and helps improve three-point tracking. This feature is GPU-intensive and requires a stand-alone video card with at least 4 GB of memory that supports CUDA in order to work properly without missing or interpolated samples. The following video cards have been tested with Deep Learning: For a desktop computer: - NVIDIA Quadro P2200, 5 GB GDDR5X, driver version 512.15 - NVIDIA RTX A2000, 6 GB GDDR6, driver version 528.02 - NVIDIA T1000, 4 GB GDDR6, driver version 517.37 For a laptop computer: - NVIDIA RTX A1000, 4 GB GDDR6, driver version 528.49 - NVIDIA Quadro P620 mobile, 4 GB GDDR5, driver version 517.66 Deep Learning Limitations - Requires a supported NVIDIA video card (GPU) with 4 GB or more. See the list above. - Maximum camera resolution: 1280x960 or 1280x1024. - One subject per arena. - One arena live or four arenas from pre-recorded video. Disabling Onboard Video Cards Many PCs sold since 2019 include both an onboard video card and a stand-alone video card. In this scenario, the onboard video card must be disabled. The process varies from PC to PC. Below are instructions for disabling the onboard video card on select Dell PCs. If this information does not apply to your PC, contact your local IT administrator or search online for instructions specific to your PC model. BIOS change on Dell 7510/7520 laptops: - Start up the PC and enter BIOS settings using F12 (previously F2). - Expand the Video item. - Select the Switchable Graphics item. - Disable Enable Switchable Graphics by deselecting it. - Save these settings and exit. - After startup, the screen resolution will be automatically lowered. Manually change it back to 1920x1080 in the display settings. - After approximately 30 seconds, Windows will automatically change the text size setting to 150%, causing the screen to go black briefly before returning with larger icons. Manually change the text size back to 125%. - Check in Windows Device Manager that the graphics adapter is recognized and using proper drivers. If not, download the latest drivers from the Dell support site or the video card manufacturer's website and install them. Do not allow Windows to search for drivers automatically. To point EthoVision to the correct video card (this option is not always available): - Go to Windows Start, then Graphics Settings, then Browse, then navigate to C:\Program Files\Noldus\EthoVision XT 17, select EthoVision.exe, then Options, then High Performance, then Save. Alternatively: - Go to the program folder: C:\Program Files\Noldus\EthoVision XT 17. - Right-click on EthoVision.exe and select Run With Graphics Processor, then select your video card, for example NVIDIA. If you cannot see a folder such as Program Files (x86) because it is hidden, follow these steps to unhide it: - Log into the PC as an administrator if you have not already. - Right-click on Windows Start and select Open Windows Explorer, which may also be called Open Explorer or Open File Explorer. - Go to the Tools menu and select Folder Options. - Go to the View tab and select Show hidden files, folders, and drives. - Click OK. You should now be able to see the directory. Power Save Settings Apply the following settings to your PC: Disable Fast Startup (Windows 10 only): - Go to the Start menu. - Click the gear icon for Settings. - Select System. - Select Power and Sleep. - Click Additional Power Options in the upper right. - Click Choose what the power buttons do in the upper left. - Click Change settings that are currently unavailable. This requires an administrator password. - Uncheck the options for Fast Startup, Sleep, and Hibernate. Power Save settings: - Go to Start and select Control Panel. - In the Search Control Panel field in the upper right, type Power. - Under Power Options, select Edit Power Plan. - For both options, select Never. - Click Save Changes. - Click Change Plan Settings. - Click Change Advanced Power Settings. - Under Hard Disk, then Turn Off Hard Disk After, set the value to 0 (Never). - Click OK. Automatic Updates: - Go to Start and select Devices and Printers. - Right-click on your PC, which appears as an icon resembling an external hard drive, and select Device Installation Settings. - Select No, let me choose what to do and then Never install driver software from Windows Update. - Click Save Changes. BIOS settings: - Turn on the PC. - During boot up, immediately press F12 to enter BIOS. You may need to press F12 multiple times. - On the left side under Settings, expand Performance. - Click on C States Control. - Deselect the checkbox for C States Control. - Return to the left side under Performance and locate Intel SpeedStep, previously called P-States. Confirm that the checkbox is deselected. If it is not, deselect it. - If you have a different processor such as AMD, you may see PowerNow!, Cool'n'Quiet, or PowerSave instead. - Click Exit. - When prompted to save changes, click Yes. - The setting change is retained and the PC finishes booting up. Network Card Requirements The network card must be a 1 GB adapter set to Auto-Negotiate. The following network cards are recommended: - Intel single port, no POE network card. Requires an Axis Power Injector. See Section A. - Basler 2-port POE network card. - Basler 4-port POE network card. Not all network cards are equally compatible. If you are unable to source one of the above network cards, refer to Basler's knowledge base for information on which network adapters are compatible with the Basler pylon performance driver. If the camera is set up correctly per this document and the PC is sufficient with a supported video card and the onboard video card disabled, but camera issues persist in EthoVision, check the following settings on your network card. In Device Manager, locate your network card, right-click it, and select Properties. Go to the Advanced tab and apply the recommended changes. If you encounter errors in Pylon such as error 0xE1000014 / 3774873620: The buffer was incompletely grabbed, refer to Basler's knowledge base article on troubleshooting lost packets or frames while using GigE cameras. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: Physical Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-physical-installation Chapter: EthoVision XT Physical Installation Mounting the Camera This section only applies if you bought either a Dual Option Mount and/or an Autopole with Superclamp from Noldus. These items are not standard with your camera or system. Contact sales if you would like a quote to purchase. Dual Option Mount The camera-side fitting uses a standard tripod screw and will fit the hole on the camera. The camera will also work with other mounts that accommodate this standard fitting. Two alternate mounting types are available: - A general purpose mount with three tabs that screws into a wall or ceiling for permanent installation. - A suspended ceiling mount with two parts that move like scissors. Open the mount to fit over the framework of the suspended ceiling, then close to hold. This is a temporary but sturdy mount that can be removed and repositioned as needed. Autopole - Range is 2.1 to 3.7 meters, or up to 5.7 meters with the extension (sold separately). - Typically installed horizontally between two walls, but can be installed vertically if you have a Dual Option Mount. - Must be installed horizontally if the system came with a Standard Camera Mount. - Often ships separately via UPS from the rest of your Noldus order. Autopole and Superclamp The camera is connected to the Superclamp with a brass stud connector. The Superclamp is then clamped onto the Autopole. Vertical Installation You can mount the Autopole vertically between the floor and the ceiling to do side view tracking if the system came with a Dual Option Mount. This allows you to turn the camera as needed. It is not possible to right the image in Pylon. A Dual Option Mount is required for vertical installation. Installing the Ethernet Board on a Desktop PC This step installs an Ethernet (network) board that receives video from one or more GigE cameras. If you ordered a computer from Noldus when you purchased EthoVision XT and Basler GigE cameras, the Ethernet interface board has already been installed and tested. If you bought your computer elsewhere, follow the instructions below. Supported Ethernet interface boards include: - One-port board: Intel PRO/1000 CT (or its successor), to connect one camera. - Four-port board: Adlink PCIe-GIE74 or the Basler GigE Interface Card, to connect up to four cameras. - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot and remove the corresponding extension cover. Different PCIe slots have different properties resulting in different performance. When possible, choose the slot that gives maximum performance. Slot performance by version is as follows: - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: approximately 1 GB/s - PCIe v4.0: approximately 2 GB/s - PCIe v5.0: approximately 4 GB/s Note that values are given per lane and should not be multiplied by the number of lanes in a slot, since the board has a 1x connector. For example, SLOT1-PCIe3x4 written near the slot means version 3.0 with four lanes. Do not insert the PCIe board in the blue or white slots. - Unpack the Ethernet board, place it into the slot, and press it carefully into position. If the board does not fit into place easily, remove it and repeat the operation. When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by wearing an earthing wristlet and attaching its clip to the metal frame of the computer. If you do not have an earthing wristlet, hold the metal frame with one hand while holding the Ethernet board in your other hand. Ensure that your clothing does not touch any components while handling the board. - This step only applies when installing a 4-port Ethernet interface board. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. - Fix the board to the chassis and re-fit the computer's cover. - Proceed to install the driver software for the GigE cameras as described in the next section. Turn off Fast Startup in the Windows Power options before proceeding. How to disable Fast Startup: - Open the Windows Control Panel and select System and Security. - Under Power Options, select Choose what the power button does. - Click Change settings that are currently unavailable (requires an admin password). - Under Shutdown settings, deselect Turn on fast startup (recommended), Sleep, and Hibernate. Software Installation Installing the Pylon Driver for the GigE Camera This step installs the software that enables you to configure the camera, for example to set the video frame rate or the exposure time. Procedure via EthoVision XT 17.5 Installation - Insert the EthoVision XT installation USB stick into your computer. If your EthoVision XT installation stick is not available, download EthoVision XT 17.5. - Double-click EthoVision XT Setup 17.5.1718.exe. If you have already installed EthoVision XT, select Modify; otherwise select Install. The folder where this file is stored must also contain the following files for a successful installation of EthoVision XT 17.5: - EthoVision XT Package 17.5.1718.msi - TrackerInterfaceNN_x64_2.0.10.msi - Under Drivers and tools, select: - Basler GigE camera driver if you have Basler GigE cameras. - Daheng Galaxy if you have a Daheng GigE camera. - Click Install/Update and continue with installation. - Proceed to assign IP addresses as described in the next section. Always install the drivers from the installation USB stick or the Noldus web site. Do not install drivers from other sources unless requested by Noldus Support. Procedure for Manual Install of Pylon 7.1.0 - Download Pylon 7.1.0 and double-click the downloaded EXE file. - Accept the Terms and Conditions and click Next. - Under Profiles, select Custom and click Next. - Under Features, select the following: - GigE Camera Support (or USB Camera Support if using a Basler USB camera) - DirectShow Support - Pylon Viewer - Complete the Pylon 7.1.0 driver installation. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-troubleshooting Chapter: EthoVision XT Troubleshooting Pylon Issues - Pylon IP Configurator is not detecting the camera: - If your camera connects to an Axis Power Injector, confirm it is connected correctly. See the wiring diagram in Section F. - Make sure that the Axis Power Injector or POE switch is powered. - Reboot the PC if you did not reboot after installing the camera driver. - In Pylon IP Configurator, the camera is visible but the Status column says Not Reachable: - The network card IP and camera IP do not match. For example, the network card should be 192.168.200.101 and the camera should be 192.168.200.1. The first three numbers must be the same but the fourth number must be different. Also verify the subnet mask is 255.255.255.0 and not 255.255.0.0. - No camera image appears in Pylon Viewer despite completing steps 1 and 2 above and swapping out hardware to cross-test the network card, cables, and camera: - Disable firewall and/or anti-virus software. - The network card could be defective. - Unable to save the camera configuration as User Set 1 in Pylon Viewer: - Click the Stop button first before attempting to save. - Confirm you have selected either Expert or Guru via the Tools menu. Select Options and check that the User Level is set to Expert or Guru. - Camera image is static or pixelated with red, blue, and green pixels: - The Color Space setting in Pylon Viewer is incorrect for the camera type. This setting can be found in Pylon Viewer under Image Format Controls, then Pixel Format. - For a black and white (monochrome) camera, select Mono8. - For a color camera, select Bayer RG 8 (previously YUV 422 (UYVY) Packed). EthoVision XT Issues - In EthoVision XT via Experiment Settings, unable to select Basler GenICam [Basler acA1300-60] even though the camera and network card are set up correctly: - Confirm camera drivers are installed per Section D and that IP addresses are assigned per Sections C and E. - Disable firewall and/or anti-virus software. - The network card may be defective. - In EthoVision XT via Experiment Settings, no image appears from the camera when clicking the Camera icon: - Make sure the camera is connected to the PC and powered prior to opening EthoVision. - Make sure that the aperture of the lens is fully open, with the lens ring turned all the way to Open or O. - Make sure that Pylon is closed. - Make sure the correct camera is selected in Experiment Settings: Basler GenICam [Basler acA1300-60]. - If the PC is running Windows 10 but you have the Windows 7 driver (4.2.1) installed, download and install driver 5.1.0 per Section D. You will need to set up the camera again by following Section H in its entirety. - Make sure the network IP and Subnet and camera IP and Subnet match. You can check and change the camera subnet via Pylon. - In EthoVision XT via Experiment Settings, when setting the Resolution to approximately 1280x960, the highest available Frame Rate is approximately 7.5 frames per second instead of 30 or 25 fps: - Check that your Exposure setting is not too high. - If the Exposure setting is correct, confirm that the Power Injector is a 1GB Power Injector. - If the Exposure setting is correct, confirm that the network card is a 1GB network card. - If the network card is 1GB, check that it is set to Auto-Negotiate. If it is, the network card may need a driver update or could be defective. - Cheap, incorrect, or defective Ethernet cables can also reduce the frame rate. - The PC may be insufficient. For example, it may only have an onboard video card. Send Support a PC report as described in Section N and see Section O. - In EthoVision XT via Experiment Settings, clicking the Camera icon shows "No frames available" in the Video Settings box: - The Video Card (GPU) driver is missing or very old. Install or update the GPU driver. - If you are using Windows 10, make sure you are using Pylon 6.2.0 or higher. The driver referenced in this document is version 7.1 for use with EthoVision XT 17.5. If you installed from an older CD, you may have installed an older Pylon driver (4.2.1) which does not support Windows 10. - Check whether settings in Pylon Viewer have changed. This issue has been seen specifically with the Trigger Mode setting found in Pylon Viewer under Acquisition Controls. It should be set to Off. - Other causes are possible, such as installing Windows 10 on an older PC that is not compatible with Windows 10. - If none of these examples apply to your situation, contact support for further assistance and include a PC report as described in Section N. - In EthoVision via Experiment Settings, clicking the Camera icon shows "No video frames" in the Video Settings box: - Confirm that the PC monitor is plugged into the stand-alone video card (GPU) and not the motherboard. - The Video Card (GPU) driver is missing or very old. Install or update the GPU driver. - If you are using Windows 10, make sure you are using Pylon 6.2.0 or higher. If you installed from an older CD, you may have installed Pylon driver 4.2.1 which does not support Windows 10. - Disable the firewall and/or virus scanner to determine whether they are interfering. See item 22 below. - The camera image in EthoVision is off-center rather than showing the area directly in front of the camera: - This occurs when a lower resolution is selected in EthoVision's Experiment Settings and the Center X and Center Y options are not checked in the camera settings. Increasing the resolution to the maximum value will provide the full field of view and will be centered. If a lower resolution is preferred, refer to the relevant section of this document for guidance. - The camera image in EthoVision XT is too narrow to display the entire arena: - The field of view is reduced when a lower resolution is selected in EthoVision's Experiment Settings. Rather than scaling the entire image down, the camera displays a limited area of interest to maintain full image quality. For the widest possible view, increase the resolution to the maximum value, typically 1280x1024. - If you have a varifocal lens, which most systems include, you can adjust the zoom setting on the lens. Note that adjusting the zoom will also change the focus, so you will need to adjust the focus afterward to see the actual effect. You may also need to loosen the lock screw on the side of the lens before the zoom setting can be adjusted. - Image appears correctly in Experiment Settings but shows a white background in Arena Settings: - The Resolution set in Experiment Settings is either too high or an unusual resolution is selected, such as 640x426. Reduce the resolution and/or select a standard resolution such as 640x480. - Similar results may occur if no drivers have been installed for the computer's graphics adapter. - The first camera can be selected without issue, but selecting a second GigE camera in Experiment Settings causes EthoVision to crash: - Select a standard resolution such as 640x480. Avoid resolutions like 640x426. - The maximum supported resolution is 1900x1200. For Deep Learning, the maximum is 1280x960 or 1280x1024. - 4K resolution is not supported, whether live or from pre-recorded video. - Image in EthoVision XT flickers or stutters: - Fluorescent and LED lighting in the US cycles at 60 Hz, which does not align with a frame rate of 25. Use a frame rate of 30. This may be sufficient to resolve the issue. - The Exposure setting in Pylon Viewer may be incorrect. The Exposure Time (Abs) [us] value is likely too low. Try a value in the range of 4000 to 8000. If lighting in the room is low, use a higher exposure value. - Disable the firewall and/or virus scanner to determine whether they are interfering. See item 22 below. - If none of the above resolve the flicker, the PC may be insufficient to run EthoVision, which is a very CPU-intensive program. If you would like Technical Support to review your PC specifications, create a PC report as described in Section N and send it to support. - The image in EthoVision XT does not flicker but has a subtle and ongoing change where the overall image lightens and darkens: - Check that Exposure Auto is set to Off. This setting is found in Pylon Viewer under Acquisition Controls. - Check that Gain Auto is set to Off. This setting is found in Pylon Viewer under Analog Controls. - Check that Balance White Auto is set to Off. This setting is found in Pylon Viewer under Color Improvement Control. - If none of the above resolve the issue, check that the Exposure Time (Abs) [us] setting in Pylon Viewer under Acquisition Controls is high enough. Try a value of 8000. - Motion blur appears in EthoVision XT: - The Exposure setting in Pylon Viewer is likely too high. The Exposure Time (Abs) [us] value may be set to 20,000 or higher. Refer to the relevant section of this document for guidance on setting the camera's Exposure settings in Pylon Viewer. - The camera will not focus regardless of mounting height or zoom adjustment, and the image is always blurry: - The camera will not focus if the wrong type of lens is mounted, for example a C-mount lens on a CS-mount camera or vice versa. If you have a C-mount lens on a CS-mount camera, an adapter ring must be installed between the lens and camera. If the camera and lens share the same mount type, ensure that no adapter ring has been installed, as it will prevent correct focus. - Perform a factory reset on the camera using the following steps: - Open Pylon Viewer and at the bottom left of the interface, confirm that the User Level is set to Guru. - In the Features Window, select your camera, for example Color Camera 1 with its serial number, and expand it. - Near the bottom of the list, expand Configuration Sets. - For Configuration Set Selector, select Default Configuration Set. - For Default Startup Set, select Default User Set. - For User Set Save, click the Execute button. - For User Set Load, click the Execute button. - The camera should now be reset to factory defaults. - While still in Pylon Viewer, configure the following settings: - Go to AOI Controls: - For Width, type 1280. - For Height, type 960. - Select the checkbox for Center X and Center Y. - Follow Section H to set the remaining settings including Exposure. - Save your settings. - Close Pylon Viewer. - When using multiple GigE cameras, if one camera signal is lost, the order of cameras in EthoVision XT becomes scrambled: - Always plug cameras into the same ports. Label the ports and camera cables if needed to keep things in order. - Restore the camera signal. - Once the camera signal is restored, open EthoVision XT and toggle between Acquisition and Experiment Settings. Go to Acquisition, then go to Experiment Settings, and then return to Acquisition. The camera order should now be restored to the original setup. - Note that despite this visual swapping of cameras listed in the Source table via Experiment Settings in EthoVision, the order of cameras should still load in the correct order per your Arena Settings definition. - When tracking in EthoVision XT, there is a significant lag. The system freezes periodically, then catches up and resumes: - Reboot the PC daily to refresh the PC's resources. - If you are using a PC purchased from Noldus and the setup is not overly demanding, such as tracking multiple animals, arenas, or multiple body points, the issue is likely caused by incorrect Exposure settings in Pylon Viewer. Also review the Resolution and Frame Rate set in EthoVision, as these may also need adjustment. See Section K for more information. - Note that a small lag when navigating between modules in EthoVision is normal. Moving between Experiment Settings, Arena Settings, Detection Settings, or the Acquisition module will cause a brief delay as EthoVision accesses the camera. This is expected behavior. - To confirm that the lag during tracking is related to camera setup, check for Missing Samples. See Section L for details. - If none of the above resolve the lag, the PC may be insufficient to run EthoVision, which is a very CPU-intensive program. If you would like Technical Support to review your PC specifications, create a PC report as described in Section N and send it to support. - The track file in EthoVision XT contains a high number of Missing Samples or Interpolated Samples: - Missing Samples or Interpolated Samples can be observed while EthoVision is acquiring data, or after the fact via the Trial List by clicking Show/Hide, selecting Variables, and choosing Missed Samples and/or Interpolated Samples. - Missing Samples or Interpolated Samples percentage should be at or very near 0%. - The Exposure Time (Abs) [us] in Pylon Viewer is likely too high. Refer to the relevant section of this document for guidance on setting the camera's Exposure settings in Pylon Viewer. - If your Pylon Viewer Exposure settings are correct and you are tracking live rather than from pre-recorded video, make sure that Video Pixel Smoothing is set to None. This setting can be found in Detection Settings. - If none of the above resolve the issue, the PC may be insufficient. When a PC lacks sufficient resources, it will miss samples. If you would like Technical Support to review your PC specifications, create a PC report as described in Section N and send it to support. - Everything is set up correctly per this document and the PC and video card are sufficient, but the camera is still not working properly in EthoVision XT, for example producing missing samples: - Disable the Firewall using the following steps: - Go to the Start menu and type "firewall", then click Firewall and Network Protection. - Click Advanced Settings at the bottom. - Under Overview in the middle panel, click Windows Defender Firewall Properties. - Click the Public Profile tab. - Next to Protected Network Connections, click Customize. - Deselect the option in front of Local Area Connection. If there is more than one local area connection, refer to the relevant step in the Ethernet card configuration section of this document to identify the correct connection. - Repeat steps 4 through 6 for the Domain Profile and Private Profile tabs. - Click Close. - A warning balloon will appear in the bottom-right of the window. Ignore this message and close all windows. - Disable anti-virus software by checking the settings in your anti-virus software or by asking your local IT administrator to disable it. - Perform a factory reset on the camera as described in Troubleshooting item 18-B. The camera must then be set up again per Section H. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GigE Camera: Using Multiple GigE Cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gige-camera-using-multiple-gige-cameras Chapter: EthoVision XT Using Multiple GigE Cameras Overview This section applies to tracking from two up to four GigE cameras using Basler GigE cameras only. You cannot use a combination of analog and digital cameras. Mixing video images of different camera types is not supported. Connection Schemes for Multiple Cameras How you connect multiple GigE cameras depends on which Ethernet interface board you have installed. - If you have multiple 1-port Ethernet boards, connect each camera to an Ethernet board and each PoE injector to a power supply. - If you have a 4-port Ethernet board, you can connect up to four cameras. Make sure the Ethernet board also receives power from the PC. Selecting Multiple GigE Cameras in EthoVision XT EthoVision XT mixes the camera images in a picture-by-picture fashion. - Connect your cameras. - In EthoVision XT, choose Setup, then Experiment Settings, and select the number of cameras from the list next to Number of sources. - Select the cameras under Source. The camera names will show their own IP address in brackets at the end, which makes it possible to distinguish between the cameras. - Select the resolution and frame rate of the first camera. The resolution and frame rate of the other cameras is set automatically to the same values as for the first camera. - Next to Merged camera view, select whether the picture-by-picture mixed image should have the same resolution as the images from the individual cameras, or whether the resolution should be the sum of each camera image. The maximum total resolution is 1920 x 1200. The camera model determines the maximum resolution. - Click the preview icon to get a preview of the merged camera images. Important notes for multiple camera setups: - Noldus does not support video tracking from multiple GigE cameras connected to a laptop computer. Always connect multiple cameras to a desktop computer. - Each camera must always be connected to the same port on the Ethernet board. The IP address of the camera and that of the adapter are linked. In the case of a multi-port Ethernet board, each port is viewed as a network adapter with its own IP address. If you swap cameras, they will not be recognized. Always label the Ethernet ports and the cameras. - When using one Ethernet interface board per camera, rename the network adapters listed in the Windows Control Panel, for example Front camera and Top camera. - Each camera must have a unique IP address Verifying Tracking Quality via Trial List You can also see the Missing Samples or Interpolated Samples after tracking via the Trial List. Go to the Trial List, then select Show/Hide, then select Variables and here select either Missed Samples or Interpolated Samples. Both should be less than 1% for proper camera setup. Source: EthoVision XT 17.5 - GigE Install and Setup --- ## EthoVision XT - GPU Video Decoding and Encoding URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-gpu-video-decoding-and-encoding Chapter: EthoVision XT Technical Note In EthoVision XT 18 Information in this document is subject to change without notice and does not represent a commitment on the part of Noldus Information Technology BV. The software described in this document is furnished under a license agreement. The software may be used or copied only in accordance with the terms of the agreement. BV. International headquarters Wageningen, The Netherlands Telephone: +31-317-473300 E-mail: contact@noldus.com For addresses of our other offices and support, please see our web site reserved. No part of this publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any other language in whole or in part, in any form or by any means, without the January 6, 2025 For EthoVision XT version 18 Why This Technical Note This technical note addresses an issue that may be of interest to those who have a previous version of the software (EthoVision XT 17.0 or earlier) and have upgraded to EthoVision XT 17.5 or later. Important Terms Decoding: This equals playing back existing video files during tracking. Encoding: This equals recording video from a live camera stream. This note is mainly about an issue that occurs when decoding video, not encoding video. Use Of The Gpu For Encoding And Decoding Video As you probably know, EthoVision XT reads information from a video file and uses the pixels values to detect one or more subjects. Please note the difference: In EthoVision XT 17.0 and earlier versions, encoding and decoding of video is done by the CPU (Central Processing Unit, or processor) of the EthoVision XT computer. In EthoVision XT 17.5 and later versions, encoding and decoding of video is done per default by the Graphics Processing Unit (also known as GPU, or graphics card). The reason for this change from version 17.0 to 17.5 is that the GPU allows faster processing of video especially when you work with video of high resolution, or track subjects with the Behavior Recognition function. This reduces the workload of the CPU, and results in greater performance during tracking. Description Of The Issue Video Image When EthoVision XT uses the GPU to decode (i.e., play back) a video file, the image looks slightly different from what it would do if the software used the CPU for the same task. This difference occurs in some videos, not others. Where a difference appears, it does, the GPU-based image is slightly brighter than the CPU-based image. For example: The figure in the middle maps the difference in gray values between the two images at the two sides. Blue pixels indicate a difference of 17 or smaller, while red pixels indicate a difference of 18 or greater. Black pixels, which in this example cover the entire mouse, indicate no difference between EthoVision XT 17.0 and EthoVision XT 17.5. In other words, EthoVision XT 17.5 and later versions "see" a video file not exactly as what EthoVision XT 17.0 and earlier would do. Effects Of This Issue On Detection If the video image in EthoVision XT 18 (playback with GPU) is not exactly the same as that in EthoVision XT 17.0 and earlier (playback with CPU), the detection settings used in experiments made in EthoVision XT 17.0 or earlier are probably no longer optimal when you use the same video file in EthoVision XT 18. For example: If you use the Gray scale detection method, you may need to change the range of gray values to detect the subject correctly. If you use the Dynamic Subtraction method, you need to make a new reference image from the current video and modify the contrast range to detect the subject correctly. If you are in the middle of an experiment that you started in EthoVision XT 17.0 or earlier, you would need to acquire the new trials with different detection settings. This may not be desirable, right? Because you want to keep consistent detection settings across the trials to reduce the risk of biases in the analysis. What Should I Do? If You Have Completed All Your Experiments In Ethovision Xt 17.0 Or Earlier You do not need to take any further action. Click Yes in the window that appeared when you opened the experiment. The experiment is converted to version 18. When you create a new experiment in EthoVision XT 18, the software uses the GPU to play back and record video. Open the Detection Settings and optimize them as usual. If You Have An Old Experiment And You Need To Acquire More Trials Complete the experiment with the old playback method If you need to complete an experiment after upgrading to EthoVision XT 18, then you may want to keep using the same video settings as before. This way you do not need to update your detection settings because EthoVision XT will use the old, CPU-based method to handle video. So you make sure that the old and new tracks are obtained with the same detection settings. Do the following after opening the (old) experiment and reading this note: 1. Click Yes in the window that appeared when you opened the experiment. The experiment is converted to version 18. 2. Choose File > Preferences. 3. Click the Video settings tab and next to Play back and record video select CPU. 4. Click OK. You are ready to acquire your trials. Re-do all trials with the new method Alternatively, you can acquire all your trials with the new playback method. This means that you have to clear the existing trials, that is, delete the tracks without removing the videos, and re-acquire all trials, while keeping the option File > Preferences > Video settings > Play back and record video with GPU selected. For how to re-do trials, see the EthoVision XT Help. How The Gpu Option Is Applied The option for enabling and disabling the GPU for video encoding and decoding is applied at the application level. That is, the settings are applied to all the new experiments that you create. Make sure that the Video settings selection is kept consistent within experiments. That is, make sure that the selection is either CPU or GPU for all the trials in that experiment. If you intend to create multiple experiments that are related to each other, we recommend that you keep your selection in Video settings consistent across those experiments. )6; +ZNU )6; Source: EthoVision XT 18 - Technical Note - Decoding and encoding video with the GPU --- ## EthoVision XT - Locomotor Adaptation Case Study URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-locomotor-adaptation-case-study Chapter: EthoVision XT Locomotor Adaptation in Mice Overview The cerebellum, or "little brain," plays a crucial role in balance and locomotion. Disorder of the cerebellum can lead to ataxia, which is characterized by increased variability and poor accuracy of movements. Even though gait ataxia and limb coordination have been investigated thoroughly in human subjects, their cellular underpinnings have been relatively neglected due to technical deficiencies in measuring all aspects of locomotion in mice. Furthermore, not much is known about the plasticity mechanisms that drive the timing and motor learning in locomotion. To study the role of specific mutations of plasticity in the cerebellar microcircuit, several mutant mice were tested in a task that assesses locomotion and locomotion adaptation. Experiment Apparatus To study locomotion, the fully automated ErasmusLadder was used. The ErasmusLadder consists of a horizontal ladder between two shelter boxes, each equipped with an LED spotlight in the roof and two pressurized air outlets in the back. Sensory stimuli (light and air) serve to control the moment of departure of the mice. The ladder itself has 37 rungs on each side, and each rung can be displaced vertically. Even rungs on one side and odd rungs on the other were elevated by 6 mm, thereby creating a left/right alternating pattern. All rungs are equipped with custom-made pressure sensors that are continuously monitored. Protocol Each mouse performed one daily session of 72 trials during 8 days, structured as follows: - During the first four sessions, naive locomotion was assessed in which none of the rungs moved. - During the last four sessions, locomotion adaptation was tested by challenging the mouse to deal with the appearance of an obstacle, which was preceded by a tone 200 ms prior to its occurrence. The obstacle was induced by elevating one of the lower rungs, creating an obstacle of 12 mm just in front of the mouse. The location of the obstacle on the ladder varied randomly between trials. The exact timing of the obstacle appearance depended on the walking pattern and the predicted trajectory of the mouse. Mouse Lines Four different types of wild-type controls and mutants were used. These mouse lines are characterized by the following: - Pcd mice: Degeneration of Purkinje cells. - Pp2b and Gamma-Delta-2 mice: Specific aberrations in the cellular mechanisms underlying motor learning in the cerebellar cortex. - a6-Cacna1a mice: Reduced input to the principal cell of the cerebellar cortex, the Purkinje cell. Results Naïve locomotion during unperturbed sessions and locomotion adaptation during perturbed sessions were studied. With the ErasmusLadder, the number, length, and accuracy of steps could be reliably tested. The rich dataset makes it possible to study advanced parameters such as: - Walking pattern consistency - Efficiency - Temporal aspects of locomotion - Inter-limb coordination Figure 1: Basic Walking Pattern Comparison Between Wild-Type and Pcd Mice Each daily session consisted of 72 trials, during which the mice had to walk back and forth from one shelter box to the other. The upper rungs, indicated by closed yellow symbols, are positioned in a left–right alternating pattern. The blue footprints represent the typical touches of the front paws of a control mouse and a Pcd mouse during a representative trial on the ladder. A single step corresponds to a front paw step. Steps are classified according to their length and direction and are represented as colored rectangles located below the ladders. Consecutive single steps of the same length merge to build blocks. The time course of the trials is also depicted, with symbols representing single touches. Conclusions With the ErasmusLadder it was possible to successfully characterize and objectify the locomotion pattern of different mouse lines with specific aberrations in the cerebellar cortex. Key findings include: - The ErasmusLadder enables precise temporal analysis of locomotion, allowing the study of interlimb coordination. - Mice can be challenged during perturbed sessions in which they must cross a suddenly appearing obstacle. - The ErasmusLadder yields a more complete and quantitative analysis of locomotion than other systems currently available. Source: Case study locomotor, Noldus Information Technology --- ## EthoVision XT - Merging Heatmaps from Different Arenas URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-merging-heatmaps-from-different-arenas Chapter: EthoVision XT Overview This technical note describes how you can merge heatmaps into one when the data have been collected in different arenas or apparatuses. Use Case Example An EthoVision XT experiment has subjects being grouped based on the treatment level (or genetic background, etc.). Subjects are tested in four separate arenas. Because of the randomized design, each arena will be used for all treatment levels/groups. For example, Arena 1 will receive a subject of treatment level A in trial 1, then a subject of level B in trial 2 etc. As a result, one arena will not contain data of all trials with a specific group. The researcher would like to create a heatmap with all the trials that belong to that treatment level, and plot it on one arena layout, not four. EthoVision XT cannot do that with the current functionality. Important Terms - Reference point: A point in the 2D space defined in the EthoVision XT Arena Settings, which serves as a reference point for re-calculation of the x,y coordinates of the subjects. The reference point must be defined in all the arenas. - JavaScript variable: A custom variable defined in the EthoVision XT Analysis profile based on JavaScript code. JavaScript variables are defined to convert the original x,y coordinates to a new set of coordinates relative to the point of reference. What You Need - EthoVision XT 16 or 17. If you have EthoVision XT 15, contact Noldus. You can still work with JavaScript by adding a registry key. - Microsoft Excel. - Power Map for Microsoft Excel, or software for creating heatmaps, for example R, MatLab, or OpenJump HORAE (featured in this note). Assumptions You have an experiment with two or more arenas oriented in the same direction. Choose what applies: - You still have to track the subjects. Go to Step 1a. - You have already acquired the tracks. Go to Step 1b. Step 1a - Draw the Axis Origin for Each Arena - Open the Arena Settings that you want to use. Draw the arenas, the zones, and do the calibration as usual. - Choose a point in the arenas that you want to use. For example, a corner of the cages. - Right-click the Calibration layer and select Unshare this Calibration. - On the panel at the right hand side, click one of the Arena layers (e.g. Arena 1). - Click the Calibration Axes button below the layers list. - Leave the coordinates of the origin to 0,0 and click OK. - Move the Axes object in such a way that the origin of the x,y axes is over the reference point. - Repeat steps 4 through 7 for each arena. - At this point, each arena should have its own Axes object positioned over the reference point and oriented the same way. You can now acquire the data. Next, go to Step 2. Step 1b - Add a Reference Point to Each Arena - Open the Arena Settings that you used to acquire the data. - Under the layer Arena 1, click the layer named Zone Group 1 (or any other zone layer). - From the tool bar choose Add point. - Click over a specific location and give the point a name. - Repeat steps 2 through 4 for the remaining arenas. Choose to use the same point name (for example: SW corner). - Each arena should have its own reference point. Make sure that the points are listed under the corresponding arena layer. - Create or open an Analysis profile. - Under Custom Variables select JavaScript Continuous. - In the window that opens, delete the text already present. Copy the text under JavaScript code for x (replace "SW corner" with the name of your reference point) and paste it in the window. Next, click OK. - Under Custom Variables select JavaScript Continuous again. In the window that opens, delete the text. Copy the text under JavaScript code for y (replace "SW corner" with the name of your reference point) and paste it in the window. Next, click OK. - At this point you should have two JavaScript Continuous entries in your Data profile. Rename the variables to X and Y, respectively. To rename a variable, right-click its name and select Rename. - Optional: Visualize the variables in Integrated Visualization to check they are correct. The values displayed should be the coordinates x and y of each subject relative to the reference point. Note: The new coordinates are in mm, no matter what you have selected as Measurement Units in EthoVision XT. Go to Step 2. JavaScript Code for x // This code returns the x coordinate relative to a point // Make sure you define this point in all the arenas const g_zone = "SW corner"; function Start() { } function Stop() { } function Process() { var pt1 = GetCenter(); var pt2 = GetPointPoi(g_zone); if (pt1) { var xc = pt1.x - pt2.x; SetOutput(xc); } else { SetOutputMissing(); } } JavaScript Code for y // This code returns the y coordinate relative to a point // Make sure you define this point in all the arenas const g_zone = "SW corner"; function Start() { } function Stop() { } function Process() { var pt1 = GetCenter(); var pt2 = GetPointPoi(g_zone); if (pt1) { var yc = pt1.y - pt2.y; SetOutput(yc); } else { SetOutputMissing(); } } Step 2 - Export the Tracks That Belong to a Specific Group or Treatment Level - In EthoVision XT, make a Data profile and use the Filter function to select the tracks of one group or treatment level (for example, control subjects). - Choose Analysis > Export > Raw Data. Choose Excel as export format. - Repeat steps 1 and 2 to create different datasets, one for each treatment level. For each treatment level, make a Data profile and export the data. You will create a heatmap for each dataset. Step 3 - Prepare the Excel Files If you are going to use Microsoft Excel 3D Maps, see the procedure for creating one global file for 3D Maps below. Procedure for Creating One File per Subject - Each Excel file corresponds to one trial and contains one, two or more tabs depending on which arenas contain data for a specific group or treatment level. If you have two or more tabs, you must save them as separate Excel files (move a tab to the front and select Save As; repeat this for all the tabs). - Open each Excel file and delete the rows up to the headers. Also delete the row with the units, immediately above the data. The file should look like this: row 1 with the headers, row 2 onwards with the data. - Save each file in the format that your software for generating heatmaps requires. If you use OpenJump HORAE or R, the format CSV (MS-DOS) should work fine. Procedure for Creating One Global File for 3D Maps - Open the Excel files and copy the X and Y coordinates of each of them to one global file. Append the rows instead of creating multiple columns. There should be no empty rows in between. - Optional: Add an extra column which specifies the subject name. You can use this column to show the heatmap in different colors based on the subject identity. - Save the new file. This file should contain all the X,Y coordinates of subjects in one group, in just two columns. - Repeat the steps above for each group or treatment level. Step 4a - Create the Heatmap in 3D Maps - Open a global file for a specific group or treatment level. - Right-click the image of the Earth and select Change Map Type. - Select New Custom Map. Leave the selection as it is and tilt up the default background. - In the Field List, drag X and Y to the Location box and specify X Coordinate for X and Y Coordinate for Y. - On the Layers pane, choose Change visualization to Heat Map. - Click on Layer Options and adjust the settings when necessary, but keep Visual Aggregation set to Sum. Step 4b - Create the Heatmap in OpenJump HoRAE OpenJump HoRAE is free software for analysis and visualization of spatial behavior. You can import a global file for all subjects or separate files, one per subject. Separate files can be visualized in separate layers and contribute to a global heatmap. Install the Software - Download from https://www.researchgate.net/publication/349224514_OpenJUMP_HoRAE_Software - Extract the files from the zip file and copy them to your PC. - Run the file .../bin/OpenJump.exe. Import the CSV Files into OpenJump HoRAE - Choose File > Open Files. - Select the CSV files (Ctrl + click each file) and click Next > Finish. The tracks are imported as layers. - Save the Project with a name (.jmp). - Select all layers, right-click and choose Combine Selected Layers. - Save each new layer by right-clicking and selecting Save Dataset as. Save layers in the same folder as the project. - To make the heatmap, select the Combined layer and from the MOVEAN menu choose HRE > Point KDE > Point Kernel Density. - The most important setting is the Distance h (smoothing factor) which is similar to the Smoothing value in EthoVision XT. You can have the software calculate it for you or you can enter a value in the same units as the coordinates. The value Cell Size is the size of each pixel in the heatmap: the greater the value, the grainier the image. - To change colors, select the layer Combined-KDE and from the Raster menu choose Raster Color Editor. - To hide the original data points, de-select all the layers except Combined-KDE. Extras Create Probability Contours - Select the layer Combined-KDE and from the MOVEAN menu choose HR Analysis > Create Probability Contours from Raster. - Enter the probability value (for example, 50%) and click OK. - De-select the other layers to view the contours. Source: EthoVision XT 17.5 - Technical Note - Merging heatmaps --- ## EthoVision XT - Optogenetics Experiments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-optogenetics-experiments Chapter: EthoVision XT Introduction Optogenetics and EthoVision XT In the last decade, a method was developed to specifically activate or even inhibit small groups of neurons with light. Today, scientists can insert light-sensitive receptor proteins (originally found in algae) into single mammalian neurons in vivo, making these neurons sensitive to activation by light of specific wavelengths. This allows scientists to control the activity of these neurons and study their downstream influence on a variety of biological processes. Optogenetics is an important development for behavioral research. Not only can the actual influence of specific neurons on behavior more specifically be determined, but also, with the help of an automatic video tracking system such as EthoVision XT, behavior can be manipulated via optogenetic methods in real time. With the Trial & Hardware Control module, EthoVision XT can control light pulses given by a third party device, based on the behavior of the animal (for instance, presence in a trigger zone). This manual focuses on the optogenetics solution for rodents that combines EthoVision XT, PhenoTyper (as test environment) and the Prizmatix optogenetics devices. For how to conduct optogenetics experiments with zebrafish, see the DanioVision DVOC-0041 Reference Manual. Examples Place Preference The animal is placed in an arena with two distinct sides, one of which is paired with optogenetic stimulation. Depending on whether this stimulation is activating or deactivating, and which neurons are affected, this can be a rewarding or aversive stimulus for the animal. If in further sessions the animal spends more time on the stimulated sides, it is fair to conclude the stimulus had a rewarding effect. If the animal avoids this side, the stimulus could then be considered aversive. Operant Conditioning In operant conditioning tests, the animal learns to perform an action in order to get a reward or avoid an aversive stimulus. The behavioral response can be recorded with EthoVision XT, either by detecting the animal (or its nose point) in a certain zone, such as the feeder, or by analyzing the external signal initiated by the nose poke or lever press. Following this action, EthoVision XT sends out the command for optogenetic stimulation. Off-On-Off Stimulus Test In an off-on-off stimulus test, you can program EthoVision XT to turn optogenetic stimulation on for a period of time during the test. For example, a 15 minute test during which continuous optogenetic stimulation takes place in the middle 5 minutes. References - Guru, A., Post, R.J., Ho, Y., Warden, M. (2015). Making Sense of Optogenetics. International Journal of Neuropsychopharmacology, Aug 2015, 1-8. - Zalocusky, K., Deisseroth, K. (2013). Optogenetics in the behaving rat: integration of diverse new technologies in a vital animal model. Optogenetics 2013: 1-17. - Stamatakis, A.M., Stuber, G.D. (2012). Activation of lateral habenula inputs to the ventral midbrain promotes behavioral avoidance. Nature Neuroscience, 15(8), 1105-1107. - Kravitz, A.V., Tye, L.D., Kreitzer, A.C. (2012). Distinct roles for direct and indirect pathway striatal neurons in reinforcement. Nature Neuroscience, 15, 816-818. Physical Setup Components (Example) Devices - PC with EthoVision XT installed. - Noldus USB-IO Box. - PhenoTyper with adapted Top Unit (optional). - Prizmatix LED controller (for different light wavelengths). To control the LED through EthoVision, on the back panel of the LED controller, near/below the TTL connector, select Ext. If you want to activate the LED manually using the button located on the front panel, select Int. The other switch on the LED controller, just near/above the Ain 0-5V connector, should be in the Int position. - Prizmatix Pulser or PulserPlus (with advanced setup). Main Cables and Fiber Cords - USB cable (USB-A to USB-B). Use this cable to connect the EthoVision XT PC to the USB-IO box [USB, type-B]. Also use this cable to connect the Pulser to the PC. - UTP to BNC cable. To connect the USB-IO box [TTL control] to the LED Controller [TTL] or Pulser [Trig. In]. Note that each TTL port of the USB-IO box has two output lines. The white RCA jack corresponds to Output 1 and the red RCA jack to Output 2. If you received UTP-to-BNC cables with four BNC connectors, only use those marked with Output to connect the LED controller or Pulser. - BNC to BNC cable. From Pulser [TTL Out] to LED Controller [TTL]. - Fiber patch cord, core 1000 micron. To connect the LED Controller [front panel] to the PhenoTyper Top Unit [Fiber Coupler adaptor]. - Fiber patch cord, core 1000 micron. This is located inside the PhenoTyper Top Unit. It connects the FC adaptor to the Rotary joint. - Single fiber. To connect the Rotary joint fixed on the bottom plate of the PhenoTyper Top Unit to the implantable cannula. Available in various core diameters (e.g. 500 micron). Other Components - Zirconia ferrules (sleeves) for 2.5 mm and 1.25 mm cannulae. - Optogenetics implantable cannulae (2.5 mm, 1.25 mm). Basic Setup Aim With a basic setup, without the Pulser, EthoVision XT controls activation of the LED directly via the Noldus USB-IO box. With this setup you can, for example, activate the LED for one second. Notes - Activation of the LED can be repeated during a trial using the Subrule function in the Trial Control Settings. - For generating two pulses of different length, you must create separate Trial Control commands. Limitations - The pulse cannot be shorter than 0.1 s. - Accuracy of onset, offset and duration of a pulse is approximately the time taken by three samples. When tracking at 30 fps, this time is 0.1 s. The higher the sample rate, the higher the accuracy. Advanced Setup (With Pulser) Aim With this setup, EthoVision XT controls activation of the LED via the Prizmatix Pulser and PulserPlus devices. With this setup you can send out very specific sequences of pulses, at a frequency higher (max 0.5 kHz) than with the basic setup. The sequence is predefined in the Pulser or PulserPlus. PulserPlus is the device with three BNC connectors. Connection Notes - On the LED controller, make sure that the switch near/below the TTL connector is in the Ext position. Keep the switch near/above the Ain 0-5V connector in the Int position. - Connect the Trigger In / Trig. In port of the Pulser or PulserPlus to the USB-IO box with the white RCA jack if you use Output 1, or with the red jack if you use Output 2. - Connect the Pulser or PulserPlus to the PC with a USB cable. - If you received UTP-to-BNC cables with four BNC connectors, only use those marked with Output to connect the Trigger In/Trig. In port on the Pulser or PulserPlus. - If you have the PulserPlus, set the Operation mode switch to PC. Measuring the LED Light Output In some circumstances you may want to measure the LED light intensity at the tip of the cannulae. For this you need a sensor and a power meter. Note that a standard power meter may not give accurate measurements. An example is the Thorlabs S140C or Thorlabs S142C coupled with the Thorlabs PM100USB interface, which shows the measurements on a computer screen. EthoVision XT Settings Create an experiment. If you use PhenoTyper, you can create an experiment from a PhenoTyper template. Choose File > New from Template and in the guided wizard, from the Arena template list, choose PhenoTyper (for one cage) or PhenoTyper quad (for two to four cages). Experiment Settings Choose Setup > Experiment Settings. General Settings - Set Video Source to Live Tracking and select the camera image. - Choose the Tracked Features that apply to your experiment. Use of Trial Control Hardware - Under Trial Control Hardware, select Use of Trial Control Hardware. - Click Settings and choose Noldus USB-IO box. - In the window that appears, locate the TTL port of the USB-IO box that is connected to the LED controller, and from the Device type list choose Custom Hardware. Under Device ID, give this device a unique name (for example, LED controller 1, or Pulser if you use the Prizmatix Pulser or PulserPlus). - Repeat the previous step if you have more LED controllers or Pulsers. Make sure that Custom Hardware is selected in the Device Configuration window, not TTL Tester or others. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. Arena-Hardware Mapping - Make sure that you have drawn all the arenas. - At the bottom of the Arena Settings window, click the Arena-Hardware Mapping button. - In the Arena-Hardware Mapping window, click Add device one or more times depending on how many physical devices (LED controllers or Pulsers) are connected. - Assign the devices to the arenas. For setups with one cage (and one device), the device is automatically assigned to Arena 1. For setups with multiple cages (and devices), assign each device to the corresponding arena. - For each row, rename the Device name (for example, rename Device A to LED controller 1 or Pulser 1). Give devices unique names, which is also helpful when analyzing the data and events of specific devices. To Test the LEDs This procedure is only valid for the Basic setup (without Pulser). - In the Arena-Hardware Mapping window, click the row that corresponds to the device you want to test and click the Test button. - Choose Output 1 High and click Test. Check that the LED is activated. - Choose Output 1 Low and click Test. Check that the LED is deactivated. Trial Control Settings In the Trial Control Settings you can program activation and deactivation of the LED controller during the trial. Choose Setup > Trial Control Settings. The following example shows how to switch on a LED one minute after the start of the trial, keep the LED active for one second, and then switch it off. To Switch On the LED - Under Actions, click the button next to Custom Hardware. - From the Custom Hardware list, select the LED controller device (this is the name given under Device name in the Arena-Hardware Mapping window). - From the Action to perform list, select Output 1 High (or Output 2 High if you connected the USB-IO box to the LED controller using the cable with the red RCA connector). - Optionally, rename the Action name (for example, rename Hardware act (1) to Start Pulse). - Click OK and insert the new Action box in the Trial Control sequence, usually after a condition. In this example, the stimulation is given one minute after the start. Therefore, a Time Condition box is inserted between the Start track box and the Action box. With this Trial Control procedure, the stimulus does not stop unless you insert another Action box that specifies Output 1 Low. To Switch Off the LED After Some Time - Follow the instructions above to program activation of the pulse. - Under Conditions, click the button next to Time. Select After a time of and enter the duration of the pulse (minimum possible: 0.1 s). Insert the Condition box immediately after the Action box. - Under Actions, click the button next to Custom Hardware. - From the Custom Hardware list, select the LED controller device (this is the name given under Device name in the Arena-Hardware Mapping window). - From the Action to perform list, select Output 1 Low (or Output 2 Low if you connected the USB-IO box to the LED controller using the cable with the red connector). - Optionally, rename the Action name (for example, from Hardware act (2) to Pulse Off). - Click OK and insert the new Action box after the second Time Condition box. The sequence can be read as follows: one minute after the start of tracking, activate the LED controller, then wait one second and deactivate the LED controller. To Activate the LED When the Animal Is in a Zone It is often required to activate the LED multiple times, for example, every time the subject enters a trigger zone, or every time the subject presses a lever. In such situations you need to create a Subrule that can be repeated indefinitely. The Subrule contains the following instructions: - Check that the subject is in the zone (or that the lever has been pressed). Source: EthoVision XT 17.5 Application Manual - Optogenetics Experiments --- ## EthoVision XT - Other Conditioning Tests URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-other-conditioning-tests Chapter: EthoVision XT Introduction EthoVision XT can be used in learning tests, such as the water maze test and the conditioning tests. The Trial and Hardware Control module of EthoVision XT can be used to operate hardware devices to be used in both classical and operant conditioning tests. In the latter, an action of the animal produces a result, for example, pressing a lever results in the food dispenser dropping a food pellet. This and other hardware actions (such as turning on a light when the animal enters the shelter, or closing the door of a radial maze when the animal has exited that arm) can be operated through the Trial and Hardware Control in EthoVision XT. Learning can be demonstrated by a change in the frequency of the animal's action over time. For example, when the animal is presented with an aversive stimulus every time it performs a certain action, the performance of the action will likely decrease over time because the animal tries to avoid the negative stimulus. To be able to operate hardware devices with EthoVision XT you need: - The Trial and Hardware Control module. This module allows you to control hardware devices from within EthoVision XT. - The USB-IO Box. This is the device that connects the EthoVision XT PC with external hardware devices such as the sound and light devices of PhenoTyper or a third-party hardware device. This document describes how to set up EthoVision XT using Trial and Hardware Control in an operant conditioning test in PhenoTyper. PhenoTyper PhenoTyper is an instrumented cage to measure and test the behavior of laboratory rodents. See www.noldus.com/animal-behavior-research/products/phenotyper for more information on PhenoTyper. If you want to use EthoVision XT to operate a third-party hardware device, please contact Noldus Information Technology at www.noldus.com. To see how a test with PhenoTyper is carried out in EthoVision XT, see the sample experiment PhenoTyper hardware XT175 on the downloads section of the Noldus website (my.noldus.com). In EthoVision XT, choose File > Restore Backup and select this file. See also the document Description of sample experiments of EthoVision XT.pdf for more information. Fear Conditioning Test The fear conditioning test uses a classical conditioning paradigm; an initially neutral stimulus (for example, a sound or light cue) is paired with an aversive stimulus (for example, a shock or loud noise). Eventually, it is investigated to what degree the neutral stimulus can elicit a state of fear. In the fear conditioning test, you can use EthoVision XT to automatically detect freezing behavior as a measure of conditioned fear. References - Liu, W., Wang, X., Zhang, R., and Zhou, Y. (2009) Effects of postnatal exposure to methylmercury on spatial learning and memory and brain NMDA receptor mRNA expression in rats. Toxicology Letters, 188, 230-235. - Pham, J., Cabrera, S.M., Sanchis-Segura, C., and Wood, M.A. (2009) Automated scoring of fear-related behavior using EthoVision software. Journal of Neuroscience Methods, 178, 323-326. Physical Setup The following suggestions are meant to optimize tracking: - The camera should have a good view of the entire region the animals can be in. For zones like the shelter where the animal is not visible, you can define hidden zones. - The lighting should be as even as possible throughout the arena and should be diffuse, so as not to cast strong shadows, which might be tracked instead of the animal. - The background should contrast with the animal. If necessary, use a different setup for light and dark colored animals. - Either make sure the sides of the box are not reflective (for example, by sanding), or exclude the sides from the arena. If your objects are close to the sides then you will need to track the animal when it is against the side, so the camera sees the side instead of the base behind the animal. - If you want to use the Deep Learning technique to track the subject's nose, keep in mind that there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. For More Information - About PhenoTyper: see the PhenoTyper - EthoVision XT 17 - Reference Manual. - About using hidden zones: see the section Shelters and other hidden zones in the EthoVision XT Help. EthoVision XT Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. In the following sections we assume that you created an experiment using the PhenoTyper arena template. Experiment Settings - Make sure that the PhenoTyper cages are connected to the EthoVision XT PC. See the PhenoTyper - EthoVision XT 17 - Reference Manual for how to connect PhenoTyper to EthoVision XT. Connect a third-party hardware device, which can be controlled by TTL, to one of the TTL control ports on the USB-IO Box. - Open the experiment and choose Setup > Experiment Settings. - Check that the correct cameras are selected under Video source. The procedure depends on the type and number of cameras. - One PhenoTyper: Select this camera and specify a saving source if you track live and also want to record a video. - Four or sixteen PhenoTypers with a quad unit: Select the output of the quad unit and specify a saving source if you track live and also want to record a video. Do not use a mixed image of sixteen PhenoTypers if you want to carry out nose-point, center-point, and tail-base tracking. For how to set up connections, see Camera installation in the EthoVision XT Help. - Four PhenoTypers without a quad unit: Select the number of cameras and select the cameras from the lists under Source. Select whether the resolution of the mixed image should be the same as the individual images, or the sum of that from the mixed images. If you also want to record video, specify that at a later stage in the Acquisition settings. Using the images from four PhenoTypers is only possible if you have the Picolo U8 H.264 board or the Picolo Alert board that receive the video output from the PhenoTypers. - If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. - Under Analysis options, select Activity analysis if you are interested in freezing behavior. - Next to Hardware, select Use of Trial Control Hardware and click Settings. - Select Noldus USB-IO box in the window that opens and click OK. - In the Port Device Mapping window, locate the row 'SDI Port 13' and check that under Device Type, Top Unit Interface PTTI-0010 is selected. Top Unit (Standard) should be selected for each PhenoTyper that you connected to the Top Unit Interface. If you have connected a third-party hardware device to, for example, TTL control port 1 on the USB-IO Box, in the Port Device Mapping window, locate row 'TTL Port 1', under Device Type, select Custom Hardware and enter a Device ID (for example, 'buzzer') for this port. - Click OK. For more information about setting up an experiment, see Set Up an Experiment in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > open Arena Settings 1. Click the Arena - hardware mapping button at the bottom of the Arena Settings pane. If you only have one arena, the hardware will be assigned to this arena automatically. If that is the case, proceed directly to Trial Control Settings. In the Arena - Hardware Mapping window, click Add Device for each device you want to add: - For PhenoTyper: Under Device Type, select Top Unit (Standard). Enter Device Name PhenoTyper and the corresponding Top Unit (Standard) number for each arena. - For a third-party hardware device: Under Device Type, select Custom Hardware. Enter a Device name and select a device from the list for each arena. Click Validate Setup to validate the Arena Settings. Trial Control Settings With the Trial and Hardware Control add-on module in EthoVision XT, you can control PhenoTyper and third-party devices in a variety of ways. For example: - Start recording when the animal is detected on top of the shelter. - Stop recording when the animal has performed a specific task 50 times. - When the animal sits on the shelter, drop a food pellet. Repeat this task 25 times. The template experiment contains two trial control profiles: - Default: The default Trial Control Start-Stop rule. - Max. Trial duration 24 hrs: In this profile, a trial stops after 24 hours. Maximum trial duration (tested): - Without video recording: 72 hours. - With simultaneous video recording: 3 hours. If you need to record video of the same subject for more than three hours, we recommend that you make a series of trials. Below you will find a few examples of Trial Control Settings. Modify the Trial Control Settings to suit your own application. Procedure Overview - The trial starts with a 30-second delay (see Start trial rule and Condition 'Start delay' below). - Next, as soon as the mouse enters the LightSpot zone with both the nose-point and center-point, the spotlight of the PhenoTyper is turned on. When both the nose-point and center-point are not in the LightSpot zone, the spotlight is turned off. This sequence is repeated three times (see Sub-rule 'Activation LightSpot' below). - After the Sub-rule is completed, the trial is stopped after a 5-second delay. Choose Setup > Trial Control Settings > New and give this a new name. Start Trial Rule - To start recording as soon as the Start trial button is clicked: - Click the (default) Condition In zone box and press Delete. - Keep this Condition if you want to start recording some time after starting the trial. Condition 'Start Delay' - To insert a 30-second delay after recording has started: - In the Components pane, under Conditions, double-click the Time Condition or click the button next to it. - In the Time condition window, type 'Delay of 30 seconds' in the Condition name field. In the Condition is met group, select After a time of 30 secs. Optionally, enter a comment and click OK. - Insert the Condition box into the main sequence. For more information about Conditions, see the EthoVision XT 17 - Trial and Hardware Control - Reference Manual. Sub-rule 'Activation LightSpot' - Because the sequence of turning on/off the spotlight depending on whether the animal is inside or outside the Spot Light Zone is repeated three times, you need to create a Sub-rule for this: - In the Components pane, under Structures, double-click Sub-rule or click the button next to it. - In the Sub-rule window, type 'Anxiety Test' in the Sub-rule name field. Optionally, enter a comment and click OK. - Create an In zone Condition for when the animal enters the Spot Light Zone: - In the Components pane, double-click the In zone Condition or click the button next to it. - In the In zone Condition window, type 'Inside LightSpot' in the Condition name field. - In the Condition is met when group, from the Statistic list, select Frequency. Next, click the Settings button, select zone Spot Light from In the following zones, and select When in any of the selected zones from the list. In the From the following body points group, select both Nose-point and Center-point. Make sure to select All selected points from the list. - Click OK. - Insert the Condition box into the Sub-rule sequence. - Create a Hardware Action (White Light on) for when the previous Condition is met: - In the Components pane, under Actions - Hardware, double-click Top Unit (standard) or click the button next to it. If a third-party device has been connected, under Actions - Hardware, double-click Custom Hardware. - Next to Action name, type "White Light on". - Next to Action to perform, select White spot on from the list and click OK. - Insert the Action box into the Sub-rule sequence. If a third-party device has been connected, select an action from the Custom Hardware. - Create an In Zone Condition for when the animal leaves the Zone LightSpot: - In the Components pane, double-click the In zone Condition or click the button next to it. - In the In zone Condition window, type 'Outside LightSpot' in the Condition name field. - In the Condition is met when group, from the Statistic list, select Frequency. Next, click the Settings button, select zone Spot Light from In the following zones and select When not in any of the zones. In the From the following body points group, select both Nose-point and Center-point. Make sure to select All selected points from the list at the bottom. - Click OK. - Insert the Condition box into the Sub-rule sequence. - Create a Hardware Action (White spotlight off) for when the previous Condition is met: - In the Components pane, under Actions - Hardware, double-click Top Unit (standard) or click the button next to it. - Next to Action name, type "White Light off". - Next to Action to perform, select White spot off from the list and click OK. - Insert the Action box into the Sub-rule sequence. If a third-party device has been connected, select an action from the Custom Hardware. The Sub-rule Anxiety Test is now completed. Sub-rule Reference 'Start Anxiety Test' - To create a Reference in the main sequence to the Sub-rule LightSpot: - In the Components pane, under Structures, double-click Sub-rule reference or click the button next to it. - Next to Reference name, type 'Start Anxiety Test'. - Next to Reference to sub-rule, select Anxiety Test. - Next to Stop Conditions, select Repeat per start condition. Select for a number of times and set it to 3. - Click OK and insert the Reference box into the main sequence. Condition 'Stop Delay' - To insert a 5-second delay before the trial is stopped: - In the Components pane, under Conditions, double-click the Time Condition or click the button next to it. - If the Add a condition window appears, configure the time condition with a delay of 5 seconds before the trial ends. Source: EthoVision XT 17.5 Application Manual - Other Conditioning Tests --- ## EthoVision XT - Sylics AHCODA Integration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-sylics-ahcoda-integration Chapter: EthoVision XT AHCODA Testing Protocols and Data Analysis Your raw tracking data is automatically processed, quality-checked and analysed by our cloud-based analysis software AHCODA™. Within 24 hours, all relevant parameters are visualized on your private website, with publish-ready art and statistics. In addition to activity and motor function during spontaneous behaviour, you can assess cognition and anxiety in PhenoTyper® automated home-cages using our optimized testing protocols. Our validated testing protocols and cloud-based data analysis let you take full advantage of PhenoTyper home-cages in your facility. Key Testing Areas In-Depth Analysis of Spontaneous Behaviour Spontaneous behaviour is dissected into a diverse set of parameters representing motor function, circadian rhythm, feeding and drinking patterns, novelty response and activity. This analysis is highly sensitive to detect manipulations, such as the administration of compounds, induction of gene mutations, and ageing. A thorough analysis of spontaneous behaviour is therefore a highly valuable component of preclinical efficacy and safety studies and for phenotyping of novel models. Cognitive Function For assessment of cognitive function in an automated home-cage environment, a range of tests has been developed. Each test makes use of a unique learning stimulus, such as a food reward (appetitive operant conditioning) or an aversive light stimulus (avoidance learning). In addition, the CognitionWall™ was developed for advanced cognitive testing, including discrimination learning and reversal learning. These automated tests detect changes in cognitive function in mouse models of cognitive decline, common inbred strains, and after pharmacological challenges. Evaluation of Anxiety-Like Behaviour The PhenoTyper is equipped with a bright LED in the top unit. The one-night anxiety test measures an animal's response to this anxiogenic stimulus. When switched on during the dark phase, it induces anxiety-like behaviour observed as avoidance behaviour. The typical anxiolytic diazepam reduces this anxiety response. References - Loos et al., PLoS One. 2014; 9:e108563 - Maroteaux et al., Genes Brain Behav. 2012; 11:772 - Remmelink et al., Behav Brain Res. 2015; doi: 10.1016/j.bbr.2015.01.020 - Aarts et al., Behav Brain Res. 2015; doi: 10.1016/j.bbr.2015.06.011 Source: Sylics AHCODA, Noldus Information Technology --- ## EthoVision XT - Sylics CognitionWall URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-sylics-cognitionwall Chapter: EthoVision XT CognitionWall Discrimination Learning Test The discrimination learning test efficiently identifies cognitive impairments in 1 or 2 nights. The CognitionWall is placed in front of a food dispenser. Mice are rewarded with a food reward when they choose to pass through one of the three entrances. The rate at which a mouse gains a relative preference for the rewarded entrance is used as a measure of discrimination learning. The discrimination learning test has been validated for use with several models of synaptic dysfunction and cognitive impairment, including Alzheimer's disease models (e.g. APP/PS1 transgenic mice) and after administration of NMDA receptor antagonist MK-801 (0.06 mg/kg). Superior Cognitive Testing in PhenoTyper Home-Cages The CognitionWall adds sufficient complexity to the home-cage environment to implement complex operant conditioning tests. The CognitionWall is a wall with three entrances, which is placed in front of the optional Pellet Dispenser. In combination with EthoVision XT's Trial & Hardware Control Module, the CognitionWall currently forms the basis of two validated operant conditioning tests. The discrimination learning test has proven to be superior to the Morris Water Maze in terms of speed, sensitivity and reproducibility when screening Alzheimer's disease models. CognitionWall Protocols The following protocols are available to assess cognitive function in PhenoTyper home-cages: - Discrimination Learning Test – Identifies cognitive impairments in 1 to 2 nights by measuring the rate at which a mouse develops a preference for the rewarded entrance. - Reversal Learning Test – Evaluates specific impairments in cognitive flexibility by measuring adaptation to a switched reward entrance. CognitionWall Reversal Learning Test After initial discrimination learning, the rewarded entrance is switched to another entrance of the CognitionWall (reversal). The rate at which a mouse gains a relative preference for the newly rewarded entrance is used as a measure of reversal learning. Including initial discrimination learning, the reversal learning test takes 4 nights. Key Features - Mice learn to use a specific entrance of the CognitionWall during the discrimination learning test. - Assessment of cognitive impairments in Alzheimer's disease models can be completed in 2 nights. - Assessment following acute MK-801 administration can be completed in 1 night. - Testing is fast, sensitive, and reproducible. Availability and Contact The CognitionWall is available through Noldus Information Technology. Contact info@noldus.nl for information on implementing operant cognitive testing using the CognitionWall in your facility. Source: Sylics CognitionWall, Noldus Information Technology --- ## EthoVision XT - Sylics Protocols - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-sylics-protocols-introduction Chapter: EthoVision XT Steps on AHCODA-DB Website Adding Mice, Strains and Experiments Prior to Running Experiments - Go to your personal website and log in as an admin. - Add strain: If you want to test a strain you have never tested before, go to the Admin & Mouse Database page and select Strains to enter information about this strain into the database. - Add experiment: In order to have a better overview of the data, you can assign an Experiment name to the mice (as seen in the example data for C57 and Balb mice). To create a new experiment name, go to the Admin & Mouse Database page and select Experiments. - Add mice: On the Admin & Mouse Database page, select Mice and add information about the mice you want to test (e.g. strain, genotype, treatment). The mouse ID (PH number) is the identifier that links data generated in EthoVision to the corresponding mouse in the AHCODA database. - Define protocol: On the Admin & Mouse Database page, select Mice and select the protocol which will be used to run the experiment. Steps in Windows General Settings in Windows - Turn off the automatic Windows updates as this can cause a reboot while your experiment is running. - In the Date/Time settings, turn off Set time automatically and turn off Adjust for daylight saving time automatically as this may cause time issues while your experiment is running. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT - Sylics Protocols - Running Experiments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-sylics-protocols-running-experiments Chapter: EthoVision XT Running the Spontaneous Behavior Protocol (EV11_01_SB3D / 02_SB3D2L) - This protocol is for experiments where the Day/Night cycle is 07:00-19:00 LIGHT; 19:00-07:00 DARK. If you are using a different Day/Night cycle these times need to be adjusted in the protocol. Please check with Sylics if this is the case for your experiments. - Before starting the experiment, mice should be single-housed for about a week. Going from socially housed in the holding rooms to single-housed on the day of testing can influence the behavior. - Prepare the PhenoTyper (bedding, water bottle, provide a tissue in the shelter as nesting material). - Introduce the mice to the PhenoTyper between 14:00 and 16:00 and place the top unit on the cage. - Start the protocol. - The protocol will run for 3 days (if protocol 1 is selected) or for 2.5 days (if protocol 2 is selected). If you are planning to run only the Spontaneous Behavior protocol, the 3 day protocol is recommended. If another protocol will run after the Spontaneous Behavior protocol (for example the CognitionWall protocol) the 2.5 days protocol is recommended. Running the 1-Night CognitionWall Protocol (EV11_09_Wall1DFR5) - This protocol is for experiments where the Day/Night cycle is 07:00-19:00 LIGHT; 19:00-07:00 DARK. If you are using a different Day/Night cycle these times need to be adjusted in the protocol. Please check with Sylics if this is the case for your experiments. - Before starting the experiment, mice should be single-housed for about a week. Going from socially housed in the holding rooms to single-housed on the day of testing can influence the behavior. - Give the mice between 10 and 15 sucrose pellets on the day before testing (the same as they will have to earn during the test) so they get used to this unfamiliar food. - Prepare the PhenoTyper (bedding, water bottle, provide a tissue in the shelter as nesting material, remove food from the food tray or replace the food tray with a white PVC cover). - Fill the Pellet Dispensers with a small amount of pellets (maximum 1/3 of the container). - Weigh animals, introduce them into the PhenoTyper at 10:00 AM and place the top unit on the cage. - Between 16:00 and 16:30 (the start time of the CognitionWall protocol), lift the top unit and introduce the CognitionWall. The bedding material should not be inside the CognitionWall. Make sure the CognitionWall is in a stable position and the tube of the Pellet Dispenser protrudes all the way into the CognitionWall compartment. - Start the protocol. - The protocol will run for 24 hours (16:30), but can be manually stopped around 10:00. Running the 4-Night CognitionWall Protocol (EV11_03_Wall4DFR5) - This protocol is for experiments where the Day/Night cycle is 07:00-19:00 LIGHT; 19:00-07:00 DARK. If you are using a different Day/Night cycle these times need to be adjusted in the protocol. Please check with Sylics if this is the case for your experiments. - Before starting the experiment, mice should be single-housed for about a week. Going from socially housed in the holding rooms to single-housed on the day of testing can influence the behavior. - Give the mice between 10 and 15 sucrose pellets on the day before testing (the same as they will have to earn during the test) so they get used to this unfamiliar food. - Prepare the PhenoTyper (bedding, water bottle, provide a tissue in the shelter as nesting material, remove food from the food tray or replace the food tray with a white PVC cover). - Fill the Pellet Dispensers with a small amount of pellets (maximum 1/3 of the container). - Weigh animals, introduce them into the PhenoTyper at 10:00 AM and place the top unit on the cage. - Between 16:00 and 16:30 (the start time of the CognitionWall protocol), lift the top unit and introduce the CognitionWall. The bedding material should not be inside the CognitionWall. Make sure the CognitionWall is in a stable position and the tube of the Pellet Dispenser protrudes all the way into the CognitionWall compartment. - Start the protocol. - The protocol will run for 96 hours (16:30), but can be manually stopped around 10:00 after the 4th night. Zone Definitions - Spontaneous Behavior protocols (SB3D and SB3D2L) - CognitionWall protocols (1 & 2 night IL and 4 night IL and RL) - Calibration of the PhenoTyper when using CognitionWall protocols Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT - Sylics Protocols - Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-sylics-protocols-setup Chapter: EthoVision XT Steps in Ethovision Installing Sylics Ethovision Protocols - Import the backup file (e.g. CognitionWall.evz) you received from Sylics by opening Ethovision and selecting "Restore backup" (see the Ethovision manual for details). - Save the experiment in a safe location (i.e. Noldus/Experiments/Templates). Running Experiments Using Sylics Ethovision Protocols - Each protocol has its own procedure. Please check the "Running Sylics Protocols" section which procedure applies for your experiment. The steps below apply to all protocols. - If you are using hardware controlled by an IO-box, continue with the steps below. If you don't have an IO box connected, continue with step 5 and ignore step 10. - Check if the IO boxes are detected by opening a previous experiment, select "Experiment Settings" in the left panel, and click on the settings button under "Trial Control Hardware". If the IO box is not detected it will show "No device connected", otherwise it will show "IO box #". - If the IO box is not detected, close, and then restart Ethovision and repeat step 3. If the IO box is detected, close the experiment and continue with step 5. - On the main screen of Ethovision, select "New from template", select the template and type a name for the new experiment (instructions provided on-screen). - Select "Experiment Settings", and check if your camera settings are correct. These can be different for each PhenoTyper (edit and check by clicking on the camera icon). - Check detection settings in order to correctly track your animals. These settings are located under "Detection Settings" in the left panel. Sylics has provided two detection settings (for dark and light animals). - The image quality should be set to 14.9850 samples per second for NTSC set-ups, and ~12 for PAL set-ups. This setting can be found in "Detection Settings" in the right panel, under "Video". - It is recommended to create a new background image for each experiment. A new background image can be created by selecting the detection setting (dark or light) and clicking Advanced → Background. See the Ethovision manual for details. - Test the communication between the software and hardware (Arena Settings → Arena – Hardware Mapping). Click on a PhenoTyper and click "Test". A hardware testing tool opens. See the Ethovision manual for details. - Make sure that the zones are defined correctly and that these are at the right positions for each trial control setting you want to use. See example zone definitions at the bottom of this document. - If everything is ready to go, open the trial list and fill out the information of the mice. Insert the PH number assigned to the mice and optionally an ID (can be text or numeric) of the PhenoTyper you are using. When ready to start, go to "Acquisition" and set the method to "Track next planned trial". Place the mice into the PhenoTyper and press start (red button). - EthoVision version 11.0 and below: If you are using the pellet dispenser for your test (i.e. with the CognitionWall), make sure you select the third tab ("Dependent Variables"), which you can find under the red button. If you don't select this tab it is not possible to check the number of pellets earned, as it will show zero pellets dropped. The counter only works when this tab is selected (see "Running the CognitionWall Protocol" below). Analyzing Your Data Using AHCODA - Go to Data Profiles → Corresponding Data Profile (i.e. if you ran a CognitionWall experiment, click on "Wall") on the left side of Ethovision and make sure the selection shown in the "Result" box is the number of tracks you expect. If this is not the case, a filter might be selected, or the data was not recorded. Please check the Ethovision manual for details. - Click on "Raw Data" on the left side of Ethovision and make sure the boxes on top are set to the same data export options as used during the experiment (these are the Smoothing Profile, Data Profile and Analysis Profile). - Check all the check boxes (Track & Dependent Variables, Trial Control Log, Hardware Log). - Set the destination folder to the folder where the data should be stored. Using the default option is recommended (i.e. Experiment folder/Export Files). - Set file type to Unicode text (default) and Delimiter to semicolon (;). - Press Start Export. This can take a while. - When finished, start the AHCODACloudConnect application, select the folder where you just exported the data, and press "Upload". The data will now be transferred to the Sylics analysis servers. - When finished uploading, the progress of your data analysis is shown on your personal website on the "Admin & Mouse Database" page. - If mice were not added to the database before the start of an experiment, new mice are added without any information. The information of each mouse can be edited afterwards. This is not recommended. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT - The Elevated Plus Maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-elevated-plus-maze-test Chapter: EthoVision XT Introduction The elevated plus-maze was designed to provide measures of anxiety that were relatively uncontaminated by changes in overall motor activity, and has been extensively validated by Pellow et al. (1985) using behavioral, physiological, and pharmacological measures. The open and closed arms are considered to evoke the same exploratory drive in the animals, therefore avoidance of the open arms is considered to be a result of the induction of higher levels of fear (Rodgers and Dalvi, 1997). It is thought that the aversion of animals to explore the open arms of the maze is caused by fear of open and/or elevated spaces. The plus-maze is sensitive to the anxiolytic effects of neurotoxic lesions of serotonergic neurons and to the anxiogenic effects of drugs (Pellow and File, 1986), drug withdrawal (File and Andrews, 1991), and predator odor (Zangrossi and File, 1992). For a discussion of the additional, ethological measures that can be taken in this test, see Rodgers et al. (1995) and Fernandes and File (1996). Unlike the social interaction and light/dark tests, the elevated plus-maze does not rely on aversion to bright light, and it has been found repeatedly that behavior in the maze is independent of light level (e.g., Becker and Grecksch, 1996). For a review of the protocol, see Walf and Frye (2007). What to Measure - Principal component analysis of the conventional plus-maze (File, 1991) has shown that the percentage of time spent on the open arms and the number of entries onto the open arms are the best measures of anxiety (these are increased by anxiolytic and decreased by anxiogenic treatments). - The number of closed arm entries is the best measure of locomotor activity. - There are marked strain differences in baseline scores and even between the scores of different batches of animals. If the scores are high it will be hard to detect an anxiolytic effect. If they are very low it will be difficult to detect an anxiogenic effect. - The plus-maze was originally developed for male rats, but it can be used with female rats. However, while in male rats anxiety is the main factor measured, in females it is activity (Fernandes et al., 1999). The plus maze has also been validated for mice (Lister, 1987; Walf and Frye, 2007). For a discussion of the factors controlling measures of anxiety in the mouse, see File (2001). Quantifying Head Dips EthoVision XT can detect when the subject's nose is outside the open arms. However, you can also score head dips manually. First define head dips in the Manual Scoring Settings. Next, during acquisition, press the assigned keyboard key when a head dip occurs. The Sample Experiment To see how a plus maze test is carried out in EthoVision XT, see also the sample experiment Elevated plus maze XT175 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. In EthoVision XT, choose File > Restore Backup and select the file. For more information, see the document Description of sample experiments of EthoVision XT.pdf. References Papers - Becker, A. and Grecksch, G. (1996). Illumination has no effect on rats' behavior in the elevated plus maze. Physiol. Behav., 59, 1175-1177. - Fernandes, C. and File, S.E. (1996). The influence of open arm ledges and maze experience in the elevated plus-maze. Pharmacol. Biochem. Behav., 54, 31-40. - Fernandes, C., Gonzalez, M.I., Wilson, C.A. and File, S.E. (1999). Factor analysis reveals that female rat behaviour is characterised by activity, male rats are driven by sex and anxiety. Pharmacol. Biochem. Behav., 64, 731-738. - File, S.E. (1991). Animal models of anxiety. In Biological Psychiatry (G. Racagni, N. Brunello, and T. Fukuda, eds.), 596-599. Elsevier, New York. - File, S.E. (2001). Factors controlling measures of anxiety and responses to novelty in the mouse. Behav. Brain Res., 125, 151-157. - File, S.E. and Andrews, N. (1991). Low but not high doses of buspirone reduce the anxiogenic effects of diazepam withdrawal. Psychopharmacology, 105, 578-582. - File, S.E., Lippa, A.S., Beer, B., Lippa, M.T (2004). Animal Tests of Anxiety. Current Protocols in Neuroscience, Unit 8.3. DOI: 10.1002/0471142301.ns0803s26 (online) - Lister, R.G. (1987). The use of a plus-maze to measure anxiety in the mouse. Psychopharmacology, 92, 180-185. - Pellow, S., Chopin, P., File S.E., and Briley, M. (1985). Validation of open:closed arm entries in an elevated plus-maze as a measure of anxiety in the rat. J. Neurosci. Methods, 14(3), 149-167. - Pellow, S. and File, S.E. (1986). Anxiolytic and anxiogenic drug effects in exploratory activity in an elevated plus-maze: A novel test of anxiety in the rat. Pharmacol. Biochem. Behav., 24, 525-529. - Rodgers, R.J., Cole, J.C., Aboualfa, K., and Stephenson, L.H. (1995). Ethopharmacological analysis of the effects of putative "anxiogenic" agents in the mouse elevated plus-maze. Pharmacol. Biochem. Behav., 52, 805-813. - Rodgers, R.J. and Dalvi, A. (1997). Anxiety, defense and the elevated plus-maze. Neurosci. Behav. Rev., 21, 801-810. - Violle, N., Balandras, F., Le Roux, Y., Desor D., and Schroeder, H. (2009). Variations in illumination, closed wall transparency and/or extramaze space influence both baseline anxiety and response to diazepam in the rat elevated plus-maze. Behav. Brain Res., 203, 35-42. - Walf, A.A. and Frye, C.A. (2007). The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nature Protocols, 2, 322-328. doi:10.1038/nprot.2007.44. - Zangrossi, H. and File, S.E. (1992). Behavioral consequences in animal tests of anxiety and exploration of exposure to cat odor. Brain Res. Bull., 29, 381-388. Videos - https://www.youtube.com/watch?v=4rRsxf1U6-w - http://www.dailymotion.com/video/x2e25p_4tgndox16_animals Physical Setup The following suggestions are specifically to optimize video tracking: - Place the plus maze in such a way that its apparent size is maximized. You can obtain this by rotating the plus maze (or the camera) until the closed arms lie along one of the diagonals of your video window. - The lighting should be as even as possible throughout the arena. Bright lights are not necessary but should you need to supplement the light, consider red (or infra-red) light, as the animals will be less sleepy. - The camera should have a good view of the entire region the animal can be in. Center the plus maze in order to have the image of the arms as symmetrical as possible. This minimizes inaccuracy of calibration due to perspective. - The lighting should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). Even, diffuse lighting is important to optimize tracking of the nose. - A plus maze with transparent walls may help reducing shadows and make it easier to observe closed arm rears. There is little practical difference between the two mazes in terms of their ability to detect differences in anxiety-related behavior. However, the transparent design may reduce the sensitivity for the detection of anxiolytic drug effects because it decreases the anxiogenic potential of the open arm, therefore leading to the reduction of anxiety-related behavioral baseline (Violle et al., 2009 and references therein). - The background should contrast with the animal. If necessary use a different setup for light and dark colored animals. In the closed arms, the contrast between animal and background is generally lower. Take this into account when positioning lights and choosing the background color. - Make sure that the color of the floor is in good contrast with the color of the animal, and in minimal contrast with the arms. This makes it possible to track the animal's nose off the edge of the open arms. - CORRECT: The gray floor contrasts with the black mouse. When the mouse dips its head off the edge of the open arms, its nose is still detected. WRONG: When the floor is too dark, the head dip is not found. - Both the plus maze arms and the floor should not be reflective. If necessary, place an opaque rubber mat on the floor. - If there are barriers above the closed arms, remove them. If that is not possible, in the Detection Settings use the Dilation-Erosion filter to prevent EthoVision from seeing the animal cut in two. See also Contour Settings in the EthoVision XT Help. - Depending on circumstances, pools of urine can cause problems with the tracking. An absorbent base can help. - Always place the apparatus in the same position in the room; cues from overhead might influence the behavior of the animal. For the same reason the experimenter should not be visible to the animal during the trial (automated tracking makes this possible). - If you want to use the Deep Learning technique to track the subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. EthoVision XT Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings Choose Setup > Manual Scoring Settings. If you used the template for an elevated plus maze experiment, two start-stop behaviors have been defined: - Head dipping, to record manually the head dips over the edge of the open arms. - Rearing, to record manually the posture of the animal with forelimbs lifted off the floor. Note that EthoVision XT does not detect rearing automatically in an Elevated Plus Maze. You must score rearing manually in order to record it. You can define more behaviors, like scanning. Stretched posture can in principle be detected automatically by using the Elongation variable in EthoVision. Notes about Head Dipping - By head dipping we mean here protruding the head over the ledge of an open arm and down towards the floor. This response can occur while the animal's body is in the closed arms, central square or open arms. - You can also let EthoVision count the number of times or the total time that the nose point is found within the head-dipping area (provided that this has been chosen in the template). This also quantifies the risk-assessment behavior. - For a more reliable scoring of head dips, you could place a camera in front of each open arm, to film the arm's side-view. You can record video from multiple cameras using the Media Recorder software. - If you film the side-view of the open arm, you can in principle record head-dips automatically with EthoVision by defining a zone immediately below the arm's floor. For these videos you need to create additional Arena Settings and Detection Settings. For more information, see Set Up an Experiment > Manual Scoring Settings in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > open Arena Settings 1. Arena Check that the arena covers the whole area in which you want to track the animal. Remember to include enough space around the open arms (so that the animal is still tracked when it dips its head off the edge of those arms) and the inner side of the walls (to track the entire animal when it rears). Exclude any bright reflective rims that might interfere with tracking. Make sure the label Arena 1 stays inside the arena. To adjust the contour of the arena to the plus maze in the video image, do the following: - Click the Normal mode button on the toolbar and drag the arena contour until it is centered on the plus maze. - Click the Point edit mode button. Click one of the corners of the arena and drag the mouse to move the corner to the position you require. If you use video files, select the aspect ratio correction that applies. For more information, see Adjust the video aspect ratio in the EthoVision XT Help. If you use the live camera image or the video was recorded with EthoVision XT in the same experiment, you can skip this step. Zone Group: Arms Check that each arm zone covers the corresponding sector of the plus maze. To make sure that a zone is limited to the actual arm, move the label of that zone until the arrow points outside the zone. The color of the zone should change. If the color changes for a wider area of the plus maze, it means that the zone label also pointed to that area. Use the edit functions to move and reshape the zone. For details, see Move, rotate and resize a shape in the EthoVision XT Help. Do not forget to place the arrow of the zone label back in its original position. If the zones "closed arms" predefined in the template overlap with the open arms of the plus maze, rotate the entire arena and zones. To do so: - Drag around all the shapes so they are selected. - Click the Rotation mode button. Click in the middle of the arena and drag the mouse to rotate it. - Click the mouse pointer icon on the toolbar to exit the rotation mode. Zone Groups: Open Arms, Closed Arms, and Head Dip Zone These are cumulative zones. They are defined automatically from the sum of the open arms, the closed arms, and the head dip zones, respectively. Trial Control Settings Choose Setup > Trial Control Settings. In the Trial Control Settings you can define conditions for the start and stop of the track. Source: EthoVision XT 17.5 Application Manual - The Elevated Plus Maze Test --- ## EthoVision XT - The Fear Conditioning Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-fear-conditioning-test Chapter: EthoVision XT Introduction Principle of Operation Fear Conditioning In a typical Fear Conditioning paradigm, single-frequency sounds are delivered as a neutral or conditioned stimulus (CS). Experimental procedures where the CS is administered are usually named Cued Fear Conditioning. Electric current from the grid floor is delivered as the naturally aversive, or unconditioned stimulus (US). This chapter describes how you can use EthoVision XT 17.5 and later with the Ugo Basile Fear Conditioning System NG-series 46000, to carry out fear conditioning experiments. If you use a previous version of EthoVision XT, please refer to the EthoVision XT Application Manual for that version. For an overview of Fear Conditioning, and how fear is measured in EthoVision XT, see the white paper which you can download from our web site: www.noldus.com/animal-behavior-research/fear-conditioning Controlling the FCS Stimuli from EthoVision XT - Connect the EthoVision XT computer to the Ugo Basile Fear Conditioning System (FCS). For details, see Physical Setup below. - In EthoVision XT, create your experiment and declare the devices that you are going to use. Next, program the activation of the devices in the Trial Control Settings. For details, see The Fear Conditioning Experiment in EthoVision XT below. If you have multiple FCS cubicles, you can control the stimuli in each cubicle independently. - Carry out data acquisition. See Acquire the Data below. Experiment Devices and Parameters You can specify the devices and their parameters directly in EthoVision XT. This also makes it easier to test a device. - Shock, with adjustable current intensity. - Tone, with adjustable frequency and volume. - White noise, with adjustable volume. - Visible (white) light, with adjustable light intensity. - IR light, with adjustable light intensity. - Fan, which can be switched on and off. You can also have EthoVision XT check if the door of the FCS cubicle is open or closed. Note: If you work with EthoVision XT 16 or earlier, you must connect the EthoVision XT computer to the Ugo Basile Touchscreen Controller 40500-001. Please refer to the EthoVision XT Application Manual for that version. Analysis of Freezing The detection of freezing can be automated and based on analysis of the variable Activity in EthoVision XT. For details, see Activity and Activity State in the EthoVision XT Help, under Dependent Variables in detail. Changes Relative to Previous EthoVision XT Versions With EthoVision XT 17.5 and later versions you can control the Ugo Basile FCS without connecting the touchscreen controller. For new systems, the cabling is largely reduced and the system is easier to troubleshoot. - Cable connections are simpler - from the PC directly to the FCS cubicles through USB. - When you create an EthoVision XT experiment, the devices of the Ugo Basile FCS are automatically added to the experiment. - In the Trial Control Settings, you can easily recognize the names of the devices (e.g. Tone) instead of for example Line 1, as it occurred in the previous EthoVision XT versions. - You can test the devices directly in the Trial Control Settings, before carrying out the actual tests. If You Have the "Old" FCS Setup It may be that you have the FCS setup connected to EthoVision XT through the Noldus USB-IO box, and that you have upgraded to EthoVision XT 17.5. In this case you can keep using the "old" connections. For the instructions, see the EthoVision XT 17.0 Application Manual, which you can find on the downloads page of my.noldus.com. Alternatively, contact Noldus to purchase the hardware necessary for the current setup. For General Information EthoVision XT Help For more details, choose Help > Help Topics or press F1 in the software. Other Documentation On the Windows Apps screen, choose Noldus > EthoVision XT 17 Other Documentation. See in particular: - For information on programming trial control, conditioning routines, actions and conditions, and the USB-IO box: the EthoVision XT 17 - Trial and Hardware Control - Reference Manual. - For information on conditioning tests and examples: see other chapters in this manual. You can find these and other manuals on the Noldus website at my.noldus.com. Note that you need to log in first to access the downloads page. About the Ugo Basile Fear Conditioning System This system comes with the instruction manual Fear Conditioning Systems-NG Series 46000, in PDF format. Technical Support If you encounter problems, browse to my.noldus.com, and contact the help desk. Physical Setup One-Cubicle Configuration Note: The diagrams only include the connections essential for communication between EthoVision XT and the FCS. See also the Ugo Basile Fear Conditioning Systems NG Series instruction manual. Step-by-Step Instructions - Connect the EthoVision XT computer to the Ugo Basile FCS using the appropriate USB cable. You need a USB cable with a type-A connector at one end and a type-B connector at the other end. - Connect the camera to the PC. If your computer has an Ethernet board with one or two ports, you need a Power over Ethernet (PoE) injector. - Connect one of the ports of the Ethernet board of the computer to the PC port (IN) on the PoE injector. - Connect the camera port on the back of the cubicle to the CAM port (OUT) of the PoE injector. - Next, connect the PoE injector to a power outlet. If your computer has a 4-port Ethernet board installed, and if this board receives power from the PC internal power supply, you do not need a PoE injector. Connect the camera directly to one of the board's Ethernet ports. See the EthoVision XT Help for details. - The cubicle is equipped with an IR light box above the conditioning cage, and an IR light controller to adjust the IR light intensity. Connect the red and black cable that comes from the cubicle to the IR light controller. Connect the IR light controller to a power outlet through its power adaptor. Attach the IR light controller as indicated on the labels. If you work with multiple cubicles, connect the IR controller as explained above for all the cubicles. The Video Camera In most cases the camera is embedded in the IR light box at the top of the cubicle. If you have not done so yet, you must configure the IP address of the camera and of the Ethernet port on your PC. You can find the IP address of the camera on the front panel of the cubicle's light box. For details on how to install and configure the EthoVision XT cameras, see Camera Installation in the EthoVision XT Help. To adjust the camera orientation, see Camera Settings below. Four-Cubicle Configuration Step-by-Step Instructions - Connect each cubicle to the EthoVision XT computer through the Ugo Basile USB Hub. For this you need 5x USB cables with a Type-A connector at one end and a Type-B connector at the other end. - Connect the Ugo Basile USB Hub to the power outlet using the appropriate power adaptor. - Connect each camera to one of the ports of the Ethernet Interface board in the EthoVision XT computer. For this you need 4x Ethernet cables with RJ45 connectors. - Connect the Top Light Units to the power outlet through the appropriate power adaptors. For more information on how to install and configure the Ethernet Interface board, see Install the GigE cameras in the EthoVision XT Help. - Connect one IR controller to each cubicle, as described in the one-cubicle procedure above. Connect Multiple Cameras If your EthoVision computer is provided with a 4-port Ethernet interface board for connecting multiple GigE cameras, the cameras can get the power from the PC itself. If you purchased the computer and Ethernet board from Noldus, the board is already powered by the PC. Otherwise, open the computer casing and connect the Ethernet interface board with the internal power supply of the computer. Once power is provided through the PC, connect each camera to one of the ports of the Ethernet interface board. Label the ports and the cables so you always know which port is connected to which camera (and which cubicle). The IP address of each camera can be found on the front panel of the cubicle's light box. You need those addresses to configure the cameras. If you have the Ugo Basile FCS equipped with USB cameras, connect the cameras directly to the EthoVision XT computer. For details: - In the HTML help: choose Help > EthoVision XT Help > Camera installation > Install GigE cameras. - In the Video Tutorial: choose Help > Video Tutorial > Set Up the Cameras. Camera Settings Camera Type and Lens The camera used in Noldus systems for Fear Conditioning is a Basler camera acA1300-60gm with a 2.95 mm lens, F2.0, 1/1.8". How to View the Live Camera Image - Make sure that the camera has been configured and connected to the PC. - Start EthoVision XT and create a new experiment (File > New) or open an existing experiment without trials acquired. - Choose Setup > Experiment Settings. - Under Video Source, select Live tracking. - Select the camera from the list under Source. - Click the camera button for the live view. Camera Orientation The camera has been optimized at Noldus before shipping, therefore in most cases you do not need to adjust its orientation. If, for any reason, the video image is not optimized, follow the instructions below. Camera Alignment Turn the three screws indicated to alter the camera orientation. If you tighten one of the screws, the camera points more to the other side. Loosen the same screw to have the opposite effect. For example, tighten screw b to have the camera pointing more to the back of the cubicle. Check the resulting image in EthoVision XT; make sure that the bottom of the cage is aligned at the center of the camera view. If the image is slightly out of focus, contact Noldus Support for how to adjust the focus of the camera lens. Camera Software Settings The camera frame rate, exposure time and other settings can be adjusted in EthoVision XT, or in the camera software Pylon Viewer. In EthoVision XT, choose Setup > Experiment Settings. Click the camera button and locate the settings you want to change. See below for the values recommended. Remember to change the settings for all the cameras. Image Brightness If the image from the camera is too dark, turn the knob of the IR light controller all the way to the right. In most cases this is enough to make detection optimal. If that is not the case, you can increase the camera Exposure time, or the Gain. The Ugo Basile FCS also has an IR light at one of the top corners of the cubicle. You do not need to operate this light if you have the IR light box above the conditioning cage. - Analog gain: 1 - Color space: Mono8 (Y800) - Resolution: 1280 x 1024 - Acquisition Frame rate: 25 or 30 - Exposure: 16000 s EthoVision XT Settings Prerequisites Make sure that all devices are connected and powered up. Create an EthoVision XT Experiment - Start EthoVision XT. - Choose File > New From Template, then click Apply a pre-defined template. - On the How is the arena configured page, select Open field square, with No zone template. Next to Number of arenas, choose 1 for a 1-cubicle configuration, 4 for a 4-cubicle configuration. - When you are asked How many subjects per arena will you track, select 1 subject. - Complete the procedure and give the experiment a name. Next, click OK. Experiment Settings Cameras - Choose Setup > Experiment Settings. - Under Video Source, next to Number of sources, select how many cameras (one per cubicle) you are working with. In the list under Source, select the name of each camera. - Next to Merged camera view, select 1280 x 1024 or similar. Number of Arenas and Tracked Features Important: Do this before selecting the Ugo Basile FCS in the Trial Control Hardware Settings. - In the Experiment Settings, under Arenas, select the Number of Arenas you use, that is, the number of cubicles. In most cases 1, 2 or 4. - Under Tracked Features, in most cases Center-point detection will suffice for fear conditioning experiments. Activity Analysis for Freezing Detection - In the Experiment Settings, under Analysis Options, select Activity analysis if you want to analyze freezing behavior. - Click the Video Tutorial button next to that option for an overview of Activity analysis. Specify the Ugo Basile Fear Conditioning System Important: Make sure that the Number of Arenas selected corresponds to the number of FCS cages used in that experiment before following the instructions below. - In the Experiment Settings, under Trial Control Hardware, select Use of Trial Control Hardware, and click Settings. - In the Hardware Interface window, select Ugo Basile F.C. Controller. - In the Fear Conditioning System COM Port Settings window, click the Add button. - Select a COM port and click OK. Repeat this step to add the COM ports connected to all the FCS cubicles. - For a setup with the Ugo Basile USB Hub and four cubicles, add COM11, then COM12, COM13 and COM14. - For a setup with one cubicle connected directly to the PC, select the COM port associated (see COM Port Communication below for how to find out which COM port is associated to a specific USB physical connection). - Important: Take note of which cubicle is connected to which COM port. Make sure that only the necessary COM ports are added. If you added accidentally a wrong COM port, select that and click Delete. - When finished, click OK and proceed with arena settings. COM Port Communication In order to know which COM port is associated with a specific cubicle, do the following: - In Windows, open the Device Manager. - Open the item named Ports (COM and LPT). If the FCSs are connected physically to the PC through the Ugo Basile USB Hub and powered up, you should see one up to four items USB Serial Port (COMx): COM11 to COM14. Tip: If you do not see the Ports item, from the View menu of the Device Manager select Devices by type. - Disconnect the USB cable from one of the FCS cubicles. - Look at the Ports (COM and LPT) list. One of the items has disappeared. That is the COM port currently associated with that cubicle. Source: EthoVision XT 17.5 Application Manual - The Fear Conditioning Test --- ## EthoVision XT - The Morris Water Maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-morris-water-maze-test Chapter: EthoVision XT Introduction The Morris Water Maze Test The Morris water maze is a behavioral procedure designed to test spatial memory. It was developed by neuroscientist Richard G. Morris in 1984, and since its initial description it has become a very popular paradigm for the study of learning and memory in rodents (D'Hooge and De Deyn, 2001). In the water maze paradigm, a rat or mouse is placed into a small circular pool of water which contains a hidden platform (the Atlantis platform). The platform is either fixed (a few millimeters below the water surface) or adjustable. In the latter case, the platform is submerged at the start of the trial (about 15 centimeters, depending on the device) and remains submerged until the subject finds the location of the platform. The platform is then automatically raised. Visual cues, such as colored shapes, are placed around the pool to aid the animal in learning to locate the platform. After sufficient training, a capable rat can swim directly from any release point to the platform. Next, animals are treated and the effects on spatial learning and memory are evaluated based on how they now perform in the Morris water maze. The Sample Experiment EthoVision XT comes with a sample experiment that shows you how a Morris water maze test is carried out with EthoVision XT. It includes a number of videos from a true research project and shows interesting patterns of spatial behavior depending on the age of the subject. If the sample experiment was installed during installation of EthoVision XT, you can open it directly: Choose File > Restore Backup and browse to C:\Users\Public\Documents\Noldus\EthoVision XT\Experiments\Sample Experiments. Select the file with extension EVZ and click Open. If you do not find the sample experiment, download it from MyNoldus.com. First log in or register, then choose Downloads > EthoVision XT > Sample Experiments. References - D'Hooge, R. and De Deyn, P.P. (2001). Applications of the Morris water maze in the study of learning and memory. Brain Research Reviews, 36, 60-90. - Gallagher, M., Burwell, R. and Burchinal, M. (1993). Severity of spatial learning impairment in aging: development of a learning index for performance in the Morris water maze. Behavioral Neuroscience, 107, 618-626. For the complete list of publications, see the results in Google Scholar. Physical Setup The following suggestions are meant to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - There must be maximum contrast between the background and the animal. If you use dark rats in the water maze, you can color the water with milk powder (400 g, pre-dissolved in 2 l). It is also possible to track white rats or mice with dark coloring in the water: add 300 g of tempera black nontoxic powdered paint to a 45-l pool. - If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. Place four (or more) bulbs round the pool, below the level of the water surface or other indirect lighting above the water maze. Globe type bulbs are ideal (twice the diameter as standard incandescent light bulbs). They should be close enough to the pool wall so that there is no direct line of sight between the bulbs and the camera lens. The light is reflected off the walls and ceiling, so that it only reaches both the lens and water surface indirectly. - The water temperature should be approximately 26 degrees C, which is cold enough to encourage the animals to seek the platform, but not too cold to induce hypothermia. EthoVision XT Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings. The zone groups in your experiment depend on what zone template you chose when creating the experiment. - Platform, quadrants - This zone template creates one arena settings profile with a zone group Platform with zones Platform and Platform Zone (the zone around the platform) and a zone group Quadrant with a zone for each quadrant. - Platform, quadrants, corridors, border - This zone template creates four arena settings profiles, one for each quadrant. The South-West Platform profile, for example, contains a zone group Platform with zones Platform and Platform Zone (the zone around the platform), a zone group Quadrant with a zone for each quadrant, a zone group Thigmotaxis with zone Border Zone, and a Whishaw's corridor for the other quadrants than the one with the platform. Whishaw's corridor is an 18-centimeter wide path from the starting location to the platform. This corridor is designated as the correct route and if a rat deviates from this route at any point it receives a maximum of one error on that trial (Whishaw's error). To be able to determine whether the animal deviates from this route, you should define the rest of the arena as an Outside corridor zone. A Whishaw's corridor is defined for each release point you use. By creating separate Arena Settings for each corridor, you can select the appropriate Arena Settings for data acquisition depending on the release point for that trial. To resize and reshape a zone, click first the Point edit mode button on the toolbar, then move the corners of the zone outline. Hold Shift down to keep the same aspect ratio of the shape. Hold Ctrl to enlarge or reduce the shape size in all directions. Zone for Analyzing Thigmotaxis To quantify thigmotaxis, that is, persistent swim along the wall of the pool, create an additional zone group, and draw a circle which should be the internal margin of the zone. Place the zone label between this circle and the outline of the arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings and open one of the following: - Default (no max duration) - When you use this profile, tracking stops when you click the Stop trial button. - Max Track duration 1 min - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the maze. The track stops automatically when the center-point of the animal has been in the zone Platform for at least 5 seconds, or when 60 seconds have elapsed since the start of the track. - Max Track duration 2 min - When you use this profile, tracking stops when the center-point of the animal has been in the zone Platform for at least 5 seconds, or after 2 minutes if the animal does not find the platform within that time. Using an Adjustable Platform If you use an adjustable platform you can define an action to raise the platform when the animal swims around the platform. Note that you need the Trial & Hardware Control module to be able to control the platform. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Check in the Video Section that the sample rate is set to 5 samples/second (for rats) or 12.5 samples/second (for mice). Advanced Detection Settings If detection of the subject is not optimal after using the Automated setup function, do the following: - Check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals. - When using Dynamic subtraction - Move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. Specify the Current frame weight. A low value (for instance, 10-20) usually works well. - When using Differencing - Set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. For more information, see Configure Detection Settings in the EthoVision XT Help. Trial List Choose Setup > Trial List. Defining Independent Variables Enter your independent variables such as: - Subject ID with the ID of your animals as predefined values. - Phase with Training and Probe as predefined values. - Treatment with Treated and Control as predefined values. - Dose with numerical values (e.g. 0.1 mg/kg, 0.5 mg/kg, etc.). - Day after treatment (with values 1, 2, etc.). - Name of the experimenter, etc. Making a List of Trials If you want, you can pre-define all your trials here. Click the Add Trials button. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Specify the values of the independent variables in advance, or enter them as you carry out the trials. Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help. Acquiring Data Protocol In a typical water maze test, an animal is put in the maze at a predefined position at the rim of the pool, facing the wall. Lower the animal gently into the water (e.g. in a paper cup), avoiding stress as much as possible. Before you start data acquisition, make sure the appropriate arena settings profile, depending on the starting location of the animal, is selected in the Acquisition Settings window. Training Trials In training trials, the animal starts swimming and the trial stops when the animal has found the platform or when the maximum trial duration has been reached. Probe Trials After the training trials, a probe trial is conducted in which the escape platform is removed from the pool and the animal is allowed to swim for 60 seconds. Thus typically each animal is tested n times (training) plus 1 time (probe). Each test corresponds to a trial in EthoVision XT. Reversal Training Trials In reversal learning tasks, after one location has been thoroughly trained, the platform is moved to a different quadrant of the pool. Because it is hidden, it is not apparent that anything has changed until the animal fails to find the platform in its usual place. The focus is on how the animal reacts to this change and how quickly it learns the new location. In EthoVision XT, mark different types of trials with an independent variable in the Trial List. For example Type, with values Training and Probe. Or, a variable Platform Position with values SouthWest, NorthWest, etc. Data Analysis Data Preparation Track Smoothing Choose Acquisition > Track Smoothing Profile. - Select Lowess smoothing to remove the effect of body wobble. - When the animal sits still on the platform, the body center-point may still move slightly due to system noise. This results in an overestimation of, for example, the total distance moved. Select Minimal distance moved to only measure the total distance moved over the time periods in which the animal was really swimming. Analysis Profiles Choose Analysis > Analysis Profile. The template experiment contains five analysis profiles: - Latency to reach platform - This profile contains the variable Latency to platform to calculate how long it takes the animal to find the platform. You can use the variable Distance to zone to calculate Gallagher's index (Gallagher et al., 1993). The variable In quadrants calculates the frequency and duration of visits to each quadrant. - Path shape - The path shape can be determined by using the variables Turn angle, Angular velocity and Meander. - Whishaw's Corridor (only present if you chose a zone template with corridors when creating the experiment) - In this profile, the variable Inside Whishaw's Corridor calculates the time the animal spent inside any of Whishaw's corridors. The variable Outside Whishaw's Corridor calculates the time the animal spent outside any of Whishaw's corridors. - Distance and Time - In this profile, the total Distance Moved and the mean Velocity and the group means with their standard errors are calculated. - Heading - In this profile, the mean Heading to each of the platforms is calculated. Swim Patterns Thigmotaxis (Wall-Hugging Swim) This is a persistent swim along the wall of the pool that could include sporadic swims toward the center of the pool. To quantify thigmotaxis, calculate the time spent in the Thigmotaxis zone, relative to the total track duration. Random Search This is swimming over the entire area of the pool in straight swims (zig-zag pattern), or in wide circular swims. Divide the pool into quadrants or even more, smaller zones, then count the number of times each zone was visited, and the time spent in zones. If zone visits and time are uniformly distributed across zones, the search pattern could be said to be random or at least covering the whole pool. Scanning The search path is restricted to a limited, often central, area of the pool. Use the same approach as for random search, but now covering only the area or zones towards the center. Relate this to the time in the external zones. Chaining/Serial Visits This is circular swimming (in anticlockwise or clockwise direction) at a fixed distance from the wall, in which the escape platform was located. To quantify chaining, draw a specific circular crown zone. Calculate the time spent in this zone versus the time in the rest of the arena, or calculate rotations occurring in that zone. Focal Search This is searching in a restricted area of the pool, usually the target quadrant. The path is characterized by a directional, straight swim to a specific area followed by dense concentration of superimposed loops and turns there. To detect rapid changes in direction, use the Multi condition dependent variable to define your criterion, for example Absolute Meander > 10 degrees/cm. This marks the time when Meander is greater than the threshold value. You can precisely capture the instances when the subject turns and heads back to the target zone. Combine Meander with an In zone variable in a Free Interval, to select the time from when the rapid change in direction occurs, to when the subject enters the target area. In the Arena Settings, define a zone around the platform or any other target point, and name it Focal zone. In the Analysis profile, define a Free interval from Interval start Meander: Absolute Meander > 10 degree/cm to Interval stop In zone: Center point is in Focal zone. Source: EthoVision XT 17.5 Application Manual - The Morris Water Maze Test --- ## EthoVision XT - The Novel Object Recognition Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-novel-object-recognition-test Chapter: EthoVision XT Introduction The Novel Object Recognition (NOR) test was first described by Ennaceur and Delacour (1988). Rats or mice are exposed first to two identical objects and then one of the objects is replaced by a new (novel) object. The time spent exploring each of the objects is measured. The test has become popular for assessing visual memory in rodents in general and to test the effects of amnesic drugs in particular. The test is based on spontaneous behavior with no reinforcement such as food or shock. Non-amnesic animals will spend more time exploring the novel object than the familiar one. An absence of any difference in exploration time can be interpreted as a memory defect or, in case an amnesic drug is tested, a non-effective drug. This chapter describes how a NOR test can be conducted with EthoVision XT. On the downloads section of the Noldus website my.noldus.com, you can find a number of sample experiments, including one that features a NOR test. The Sample Experiment To see how a Novel Object Recognition test is carried out in EthoVision XT, see also the sample experiment Novel Object Recognition test XT175 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. In EthoVision XT, choose File > Restore Backup and select the file. For more information, see the document Description of sample experiments of EthoVision XT.pdf. References - Ennaceur, A.; Delacour, J. (1988) A new one-trial test for neurobiological studies of memory in rats, 1: Behavioral data. Behavioral Brain Research, 31, 47-59. - Benice, T.J.; Raber, J. (2008). Object recognition analysis in mice using nose-point digital video tracking. Journal of Neuroscience Methods, 168, 422-430. - McDowell, K.A.; Hutchinson, A.N.; Wong-Goodrich, S.J.E.; Presby, M.M.; Su, D.; Rodriguiz, R.M.; Law, K.C.; Williams, C.L.; Wetsel, W.C.; West, A.E. (2010). Reduced cortical BDNF expression and aberrant memory in Carf knock-out mice. The Journal of Neuroscience, 30(22), 7453-7465. - Siegel, J.A.; Park, B.S.; Raber, J. (2011). Long-term effects of neonatal methamphetamine exposure on cognitive function in adolescent mice. Behavioural Brain Research, 219, 159-164. - Simmons, D.A.; Rex, C.S.; Palmer, L.; Pandyarajan, V.; Fedulov, V.; Gall, C.M.; Lynch, G. (2009). Up-regulating BDNF with an ampakine rescues synaptic plasticity and memory in Huntington's disease knock-in mice. PNAS, 106, 4906-4911. For a complete list of publications, see the results of Google Scholar. Physical Setup The following suggestions are specifically to optimize video tracking. For general information, see the Physical Setup section in the chapter on The Open Field Test. - The objects should contrast with the animal. If necessary, use a different setup for light and dark colored animals. - Make sure that the objects do not move due to the activity of the animal. - Either make sure the sides of the box are not reflective (for example, sand the box to make it matte), or exclude the sides from the arena. If your objects are close to the sides, you will need to track the animal when it is against the side. EthoVision XT Settings Create an experiment from a template (Ctrl+T). Choose Open field (round or square) as Arena template, and Novel object zones as Zone template. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. The PC must have a powerful graphics card which supports additional software (CUDA). See Deep learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings These settings enable you to record behaviors manually using keystrokes. This is useful for example to record exploratory behaviors like sniffing. Choose Setup > Manual Scoring Settings. If you created the experiment from the template with novel object zones, the Manual Scoring Settings already includes one behavior, Sniffing object. This is defined as "start-stop", which means that you press a key (default: q) to score the start of sniffing, and then you press the same key once again to score the end of sniffing. For more information, see Manual Scoring Settings in the EthoVision XT Help. With the Rat or Mouse Behavior Recognition add-on, you can have EthoVision XT detect sniffing and other behaviors without the need to score them manually. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. To set up your Arena Settings: - Click the Grab Background Image button to grab an image of the empty enclosure from the camera image. - Click 1. Draw Scale to calibrate your arena (for details, see the EthoVision XT Help). Draw the double-arrow so that it points to two opposite walls of the open field, at the level where the animal moves (not at the top of the walls). When done, enter the distance in real world units between the tips of the arrow. - Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. If the arena is not yet defined and you want to divide it into equal zones, choose the tool that applies depending on the shape of your open field and draw the outline of the arena. - If you used the Zone template Novel object zones, click 3. Select Shape and Draw Zones. Click the layer Zone group Objects. Check that the 'object 1' zone and 'object 1 boundary' zone cover the object. If the predefined zones do not have the correct shape, delete the zones and draw new ones. - If necessary, draw additional zone groups and zones. Additional Zones - Zone group Floor and Wall. Check that the 'Floor' zone covers the whole floor area of the open field. - Zone group Halves. Check that the 'West' and 'East' zones divide the 'Floor' zone into two equal halves. Make sure that the vertical line crosses the entire arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings. The template contains the following profiles: - Default. When you use this profile, tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops when you click the Stop trial button. - Track duration 10 min. When you use this profile, tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops automatically after 10 minutes. Stopping Tracking When Exploration Exceeds a Specified Time You can also stop tracking when the subject has spent some time around an object. For example, when the protocol specifies that in pre-test trials the animal must explore an object for at least 30 seconds. Make a new Trial Control Settings profile and, immediately before the Stop track box, insert a Condition box based on the variable In zone, or another variable, or a combination of variables using Multi condition. In the Condition settings, specify that Cumulative duration in the boundary zone for that object must be greater than N seconds for the nose point. If you use Multi condition, you can define "exploration" as a combination of variables. For example: In Zone for the nose point in the "object zone" is true + Head directed to Zone "object" is true + Velocity lower than 5 cm/s is true. The trial stops only when the cumulative time that all three criteria are met reaches the specified value. Stopping Tracking Automatically When No Exploration Occurs To stop tracking automatically even when the animal does not explore the object, add another condition in parallel with the first one that specifies stopping tracking after some time (for example, 10 minutes), and combine the two conditions with an Operator box of type "ANY". Detection Settings Choose Setup > Detection Settings > Detection Settings 1. If detection of the subject is not optimal after using the Automated setup function, do the following: - Check that the sample rate is set to at least 25 samples per second when tracking the nose and tail. - Check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals. - When using Dynamic subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. Specify the Current frame weight. A low value (for instance, 1 to 10) usually works well. A novel object test normally has a duration of a few minutes in which the background does not change much. When using Differencing, set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. - When detection is still not satisfactory, select Rodents / For occlusions as the tracking method and repeat step 2 above. If you want to use the Deep Learning technique to track the subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. Trial List Choose Setup > Trial List. Defining Independent Variables Enter your independent variables such as: - Subject ID with the ID of your animals as predefined values. - Phase with Acclimation, T1, and T2 as predefined values, where: - Acclimation marks trials where the animal is free to explore the arena with no objects present. - T1 marks trials where the animal is presented with a pair of identical objects. - T2 marks trials where one of the familiar objects is replaced with a new novel object. - Treatment with Treated and Control as predefined values. If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them, and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help. Acquiring Data Protocol A typical NOR test consists of three phases: - Acclimation. The animal is placed in an empty arena for 10 minutes to habituate to the environment. Tracking in this phase is optional. After 10 minutes, the animal is taken out of the arena and put back in its home cage. - T1. After 15 minutes in the home cage, the animal is put back in the arena in which two identical objects have been placed. The animal is placed at a position midway between the objects with its nose pointing towards the wall. The animal is tracked for 3 minutes and is then taken out of the arena and put back in its home cage. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T1. - T2. One of the objects in the open field is replaced with a novel object (sometimes the other object is also replaced with an identical one) and the animal is placed in the arena again. Tracking is done for 3 minutes. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T2. Score Behaviors Manually To score sniffing and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you will find the key codes and the buttons for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen. - If you are tracking from video, make sure you deselect DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help. Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped during tracking. Normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open MDM Filter 2 mm. In this profile, the Minimal Distance Moved filter is used (option set to Direct, with a threshold of 2 mm). When the animal sits still, the body points may still move slightly due to system noise. This results in an overestimation of, for example, the total distance moved. With the minimal distance moved filter, you measure the total distance moved over the time periods in which the animal was really walking. Adjust the threshold if necessary, based on your setup and sample rate. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Score behaviors manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select (Filter) your tracks according to your independent variable values (for example, Treated animals only) and also select parts of tracks (Nesting). You can create a data profile to compare Novel Object and Familiar Object trials using Filters, creating groups of tracks to obtain group statistics for each group. Analysis Profiles The template experiment contains four analysis profiles: - Touching objects. This analysis profile contains an In zone variable Nose touching objects to calculate the frequency, duration, and latency of when the nose-point of the animal touches the objects. The variable Distance to objects is used to calculate the mean and standard error of the animal's nose-point distance to the objects. The manually-scored behavior Sniffing object calculates the frequency and duration, with standard errors, of the instances when Sniffing object was scored during the trials. - In halves. In this analysis profile, the In zone variable In Halves is used to calculate the frequency, duration, and latency of time spent in each half of the arena. Source: EthoVision XT 17.5 Application Manual - The Novel Object Recognition Test --- ## EthoVision XT - The Open Field Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-open-field-test Chapter: EthoVision XT Introduction The Open Field for Rodents The open field test was first published in 1932 by C. S. Hall and E. L. Ballachey to determine the fearfulness of rats. Today, the test is often used with rats and mice to investigate their locomotory behavior and their willingness to explore. Also, the test is one of the most commonly used methods to investigate anxiety in rats and mice. It is based on the natural tendency of rats and mice to spend more time in the corners and the periphery than in the center. Changes in these measures are often used to assess the sedative or stimulant effects of pharmacological agents. The test arena consists of a circular or rectangular empty open space with walls to prevent the animals from escaping. The arena is divided into a border zone and a center zone. In addition, the arena can be subdivided into a number of other zones, like north, east, south and west zones, or corner zones. Common behaviors to be measured are: - Time spent in the border zone and center. - Time until the border of the center zone is first crossed. - Walking distance in each of the zones. - Percentage of time the animal is mobile/immobile. - Walking speed in each of the zones. - Frequency of rearing. References - Hall, C., Ballachey, E. L., 1932. A study of the rat's behavior in a field. A contribution to method in comparative psychology. University of California Publications in Psychology, Vol 6, 1-12. - Gould, T.D., Dao, D.T., Kovacsics, C.E., 2010. The Open Field Test. Neuromethods, Vol 42, 1-20. - De Visser, L., Van Den Bos, R., Kuurman, W.W., Kas, M.J.H., Spruijt, B.M., 2006. Novel approach to the behavioural characterization of inbred mice: automated home cage observations. Genes brain and behavior, Vol 5(6), 458-466. For the complete list of publications, see the results in Google Scholar. On the downloads section of the Noldus website, my.noldus.com, you can find a number of sample experiments, including the open field. The Open Field for Zebrafish Open Field The open field test is used to evaluate exploratory and affective behaviors. Fish are filmed with a video camera positioned overhead. The bottom of the tank is divided into two virtual zones, center and periphery (a circular zone with inner boundary 5 cm from the testing tank wall), which enables quantification of regional activity. In addition to standard movement parameters, primary behavioral measures include the distance traveled, number of visits and time spent in central and peripheral zones, and the ratio of time spent in the center zone over total testing time. Novel Tank Diving Test The novel tank test is used to assess exploratory and affective domains. The novel tank is a trapezoidal tank maximally filled with treated water and divided into two equal, horizontal regions (top/upper and bottom/lower zones). Primary behavioral measures include the number of visits and time spent in central and peripheral zones, the ratio of time spent in the top zone over total testing time, latency to enter the top zone, time spent in the top zone, and number of transitions to top zone. Similar to behavioral tests used in mammalian models, affective phenotypes are inferred from modulation of thigmotaxis (center/periphery in the open field test) and geotaxis (top/bottom in the novel tank diving test). References - Kalueff A.V., A.M. Stewart, R. Gerlai (2014). Zebrafish as an emerging model for studying complex brain disorders. Trends in Pharmacological Sciences, Vol. 35 (2), 63-75. Example Videos - https://www.youtube.com/watch?v=7vhK8fq_W4A Physical Setup The following suggestions are meant to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - The lighting should be as even as possible throughout the arena. Make sure there are no shadows in the corners. Bright lights are not necessary but should you need to supplement the light, consider red (or infra-red) light, as the animals will be less sleepy. Regardless of the light level chosen, the investigator should use a light meter to record the lighting level and report this level in any publication. - When working with multiple arenas, make sure that the background light intensity is the same across arenas. This is usually not a problem, as long as the contrast between each animal and its arena background is much bigger than the difference in brightness between arenas. - The lighting should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). Even, diffuse lighting is important to optimize tracking of the nose. - The background should contrast with the animal. If necessary use a different setup for light and dark colored animals. Matt, gray walls often give good results. - Depending on circumstances, pools of urine can cause problems with the tracking because they reflect light. An absorbent base can help. - Make sure the sides of the box are not reflective (e.g. by sanding). Alternatively, exclude the sides from the arena, but make sure that the animal is tracked well in the entire border zone. - Always place the apparatus in the same position in the room; cues from overhead might influence the behavior of the animal. For the same reason the experimenter should not be visible to the animal during the trial (automated tracking makes this possible). - Minimize disturbance from audio sources, especially from ultrasound sources such as ventilation fans, CRT monitors, or strip-lights. You can mask audio disturbance by using the same background sounds, for example of a radio, in the test room as in the room where the animals are normally housed. - When you handle the animals, be careful to minimize stress. - If you use multiple arenas, make sure that the animals in the arena do not influence each other. The animals should, for example, not be able to hear or smell each other. - In EthoVision XT, choose Help > Video Tutorial and watch the video chapter Set Up Your Test Environment. That provides useful tips about the camera position, how to improve lighting and contrast with the background. - If you intend to use the Deep Learning method to track the subject's nose point, note that there are additional requirements and limitations. See the EthoVision XT Help. EthoVision XT Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. - To detect freezing behavior, select Activity analysis under Analysis options. Click the video button next to it and watch the video tutorial to learn about Activity analysis. - If you work with rats or mice, you can let EthoVision XT automatically detect behaviors like Rearing, Grooming, and Sniffing. Select Behavior recognition under Analysis options and choose the options that apply to your experimental setup. The Behavior recognition option is only available if you have the Rat Behavior Recognition module or the Mouse Behavior Recognition module of EthoVision XT. Manual Scoring Settings Choose Setup > Manual Scoring Settings. If you used the template for an open field experiment, two start-stop behaviors have been predefined in the manual scoring settings. These are the behaviors rearing and grooming. Depending on your research question, you can add other behaviors that can be manually scored, like defecating, which is a measure for anxiety, and urinating and vomiting. Note that with the Rat (or Mouse) Behavior Recognition module you can have EthoVision XT detect a number of behaviors automatically. For more information, see Manual Scoring Settings and Behavior Recognition in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. Arena Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. Tip: If you create an experiment from scratch, the arena is not yet defined. Click 2. Select Shape and Draw Arena and choose the drawing tool. If you want to have the open field divided in quadrants, choose one of the subdivided tools. Depending on the shape of your open field, draw the outline of the arena and select the number of sectors. Each sector is automatically defined as a zone. Zone Group: Borders Check that the Wall zone covers only the wall of the open field. If necessary, adjust the center zone and the border zone. Zone Group: Quadrants Check that the zones NW, NE, SE, and SW divide the Floor zone into four equal quarters. Zone Group: Squares Check that the zones divide the arena into equal squares. Arena Settings for Rat/Mouse Behavior Recognition When you selected Behavior recognition in the Experiment Settings (only available when you have the Rat or Mouse Behavior Recognition module of EthoVision XT), defining a few special zones and points significantly increases behavior recognition accuracy. - Feeder zones -- to detect eating at the feeder. - Drinking spout points -- to detect drinking. - Wall zones -- to detect rearing to wall and to discriminate this from unsupported rearing. For the exact procedure, see Zones and points for Behavior recognition in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the data acquisition. Choose Setup > Trial Control Settings. Default Trial Control The templates for the open field contain two Trial Control Settings profiles: - Default. - Track duration 10 (or 30) min -- When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the arena. The track stops automatically after 10 or 30 minutes. If you use Behavior Recognition or Activity Analysis, the default Trial Control rule is slightly different. See Trial Control in the EthoVision XT Help. To Stop Acquisition After a Specific Time Open a Trial Control Settings profile, click the Settings button in the Condition - Time (1) box, and set the time you require. Traditionally, the open field test had a duration of between 2 and 10 minutes. This short length of time was chosen in the past because the data were acquired manually. It also emphasizes the exploratory behavior and response to novelty, rather than baseline activity of the rodents. Technology like video tracking with EthoVision XT allows for much longer periods of monitoring. Detection Settings Choose Setup > Detection Settings. Sample Rate Under Video, set the sample rate. Common values, expressed in number of images analyzed per second, are: - For rats: 5 samples/s. - For mice: 12.5 samples/s. - For nose-tail tracking of all rodents: 25 to 30 samples/s. - For adult zebrafish: 5 samples/s. Remember that the optimal sample rate depends on a variety of factors, including the characteristics of the setup, and even the animal's strain and behavior. Faster animals need a higher sample rate. This is also valid for fish. If the fish shows very rapid movements, set the sample rate to the maximum; in other cases a sample rate of 5 fps may be enough. To Detect Freezing Behavior Open the Activity section in the Detection Settings pane. This option is only available if you selected Activity analysis under Analysis options in the Experiment Settings. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold in such a way that when the animal is completely still, those pixels should be almost completely absent. Rat or Mouse Behavior Recognition If you selected Behavior Recognition in the Experiment Settings (only available when you have the Rat or Mouse Behavior Recognition module of EthoVision XT), remove the tail from the detected body contour. To do so, in the Detection Settings pane: - Under Subject Contour, select one or more pixels for the first Erosion field until the tail is no longer detected. The detected body area (shown in yellow) will now look smaller. - Increase the Dilation filter until the detected body area is the same size as before. Next, open the Behavior section in the Detection Settings pane. Wait until the rat has a normal, straight posture (not bending or rearing) and is moving forward. You should see the hips of the rat moving. Click Grab and check that the body contour is correct. You can also enter the values manually if you know them from previous experiments. However, in this case make sure that the conditions are equal, including lighting, size of the animal, and distance between the animal and the camera. The detected body must have a minimum length of 60 pixels (sum of nose-point to center-point and center-point to tail-base) for Behavior Recognition. The detected body must also be smaller than half the arena size. For more information, see the EthoVision XT Help. Acquiring Data Protocol A typical open field test is carried out in the following way: - Transport the subject to the testing room at least 1 hour prior to testing, to allow them to acclimate to the experimental room. This time period should be extended if the transfer involves excessive changes in the environment. - Clean the open field, even if it is not dirty prior to the initial trial. This way all animals experience the residual smell of the disinfectant equally. - In EthoVision XT, click the Start Trial button. EthoVision XT waits until the subject is detected in the arena. - Place the subject in the open field. Commonly, the subject is placed in the center. However, placing the subject adjacent to a wall is sometimes used to avoid immediate exposure to a stressful situation. Also, in the case of a large open field, the position adjacent to the wall may be easier to reach. - The researcher should leave the room, or position himself or herself as far as possible away from the arena and out of the field of view of the subject. The tester should also remain quiet throughout each trial. Data Analysis For information on analyzing data collected from the open field test, see the EthoVision XT Help and the relevant sections of this manual covering statistics and data output. Source: EthoVision XT 17.5 Application Manual - The Open Field Test --- ## EthoVision XT - The Porsolt Forced Swim Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-porsolt-forced-swim-test Chapter: EthoVision XT Introduction The Porsolt Forced Swim Test (Porsolt et al., 1977; Hedou et al., 2001; Juszczak et al., 2008) is the most commonly used test for assessment of depression in animal models. In the Porsolt test, a state of depression is induced by forcing a rodent to swim in a narrow cylinder or water tank from which it cannot escape. The procedure is generally divided into a pre-test session lasting 15 minutes, followed 24 hours later by a 5-minute test session. After a period of vigorous activity in the pre-test session, the animal adopts a characteristic immobile posture. Twenty-four hours later, after administration of antidepressants, the effect on immobility can be investigated by measuring the time of being immobile in the test session and comparing this with control animals. The Sample Experiment To see how a Porsolt forced swim test is carried out in EthoVision XT, see the sample experiment Porsolt Forced Swim test XT175 on the downloads section of the Noldus website (see my.noldus.com). Download this file and save it on your computer. Next, in EthoVision XT, select File, Restore Backup and select this file. See also the document Description of sample experiments of EthoVision XT.pdf for more information. References - Castagne, V., Moser, P., Roux, S., and Porsolt, R.D. (2011) Rodent Models of Depression: Forced Swim and Tail Suspension Behavioral Despair Tests in Rats and Mice. Current Protocols in Neuroscience 8.10A.1-8.10A.14. - Juszczak, G.R., Lisowski, P., Sliwa, A.T., and Swiergiel, A.H. (2008). Computer assisted video analysis of swimming performance in a forced swim test: Simultaneous assessment of duration of immobility and swimming style in mice selected for high and low swim-stress induced analgesia, Physiology and Behavior 95: 400-407. - Hedou, G., Pryce, C., Di Iorio, L., Heidbreder, C.A., and Feldon, J. (2001). An automated analysis of rat behavior in the forced swim test, Pharmacology, Biochemistry and Behavior 70: 65-76. - Porsolt, R.D., Bertin, A., and Jalfre, M. (1977). Behavioral despair in mice: a primary screening test for antidepressants. Archives Internationales de Pharmacodynamie et de Therapie 229: 327-36. Physical Setup The following suggestions are meant to optimize the quality of tracking. Camera View The camera should have a good, frontal view of the entire region the animals can be in. The complete body of the animal should be visible. Number of Animals You can test two or more animals simultaneously when the Porsolt cylinders fit in the same camera view. For tracking multiple animals you need the Multiple Arenas add-on module. Contrast Try to create as much contrast as possible between the animal and the background. This can be done by placing the cylinder or tank against a contrasting, non-reflecting background (so, a matt black background for white animals and vice versa). You can also use back-lighting to create maximum contrast. In this case, make sure you place a screen or curtain between the lights and the cylinders to avoid reflections. Water Surface You can reduce the contrast due to the water surface by placing the cylinders in a bigger tank with the water surface of the tank above those of the cylinders. EthoVision XT Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. Under Video Source, and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. Under Analysis options select Activity analysis. Click the video button next to it and watch the video tutorial to learn about Activity analysis. Activity is a useful feature that helps you detect changes in the movement patterns of the subject. Manual Scoring Settings EthoVision determines the behavior of your subjects automatically on the basis of the intensity of the subject's movement (see Determining Mobility Thresholds in the Acquiring Data section). This means that you do not have to manually score the subject's behavior. However, if you want to compare the data scored by EthoVision XT with your own ratings, define behavioral categories under Manual Scoring Settings. Next, during acquisition watch the video and score those categories during your trial. You can also edit the data after acquisition. Choose Setup > Manual Scoring Settings. - To add a behavior, click the Add Behavior button. Enter a name for that behavior (for example, Struggling) and specify Mutually exclusive as Behavior type. Specify the name of the behavior group (for example, Behavior Categories). - Add the remaining behaviors to the same group. We advise you to create three categories for scoring the animal's mobility levels, which correspond to the three possible states of the Mobility dependent variable in EthoVision XT: - Immobile (corresponding to EthoVision XT's Immobile state) - Swimming (corresponding to Mobile) - Struggling/Climbing (corresponding to Highly Mobile) Arena Settings - Choose Setup > Arena Settings > Open Arena Settings 1. - Click 2. Select Shape and Draw Arena and check that the pre-defined arenas have the correct shape and size. If necessary, adjust the contour of the arena to fit the cylinders. - Click 3. Select Shape and Draw Zones. Check that the zones (if you used a Zone template) have the correct shape and size. If necessary, draw additional zone groups/zones. Important: If you work with multiple cylinders and use Activity analysis to quantify the animals' behavior, make sure that the arenas have the same size (you can check this under Shape Size and Position in the Arena Settings window). For details, see Arena Settings in the EthoVision XT Help. Trial Control Settings Choose Setup > Trial Control Settings > Open one of the following: - Default. In this profile, tracking starts 1 second after the animal has been detected in the arena. Tracking stops manually (for example when you click the Stop trial button). - Max Track Duration 15 mins. In this profile, tracking starts 1 second after the animal has been detected in the arena. Tracking stops automatically after 15 minutes or when the animal has been in the Diving zone for over 1 second. You can use these Trial Control Settings for the pre-test session. If you need more time to put an animal in its cylinder, increase the number of seconds. This way you prevent detection of your hand or arm from starting tracking. The Start Condition works independently for each cylinder. - Max Track Duration 5 mins. This profile is similar to the previous one, but the maximum tracking duration is 5 minutes. You can use these Trial Control Settings for the test session. When you work with multiple arenas, trial control is applied to each arena separately. Therefore, tracking may start at different times in different arenas, depending on when the animal is released. Detection Settings Important: It is important for stable detection that the extremities of the animal (paws and tail) are either always included with the tracked body or always excluded from it. If the paws and tail are temporarily excluded and then included again in the detected subject during data acquisition, these changes affect the variables Mobility and Movement, while the animal might not actually be mobile or moving. On the other hand, the variable Activity is not affected by such changes, because it is based on the image change in the whole arena, not the change in the detected subject. - Choose Setup > Detection Settings > Detection Settings 1. - Under Video, choose a Sample rate of 5 (for rats) or 12.5 samples/second (for mice) or higher. - Click Advanced. - Under Method, choose Dynamic subtraction. Under Detection, check you selected the correct contrast. Move the slider to define the animal's contrast. The animal's body must be fully detected in all parts of the arena and the noise must be minimal. Set the Current frame weight slider to a value between 1 and 5 to adjust the number of past images that contribute to the reference image. - If the limbs and the tail are not included in the detected body and you want to include them, under Subject Contour select the Dilation filter, then the second Erosion filter. Leave the first Erosion filter to zero. Adjust Dilation and Erosion to achieve stable detection. - Under Subject Size, click Edit. Define a Minimum Subject size to prevent small objects like droppings from being detected. - If you intend to use Activity analysis to score the behavior of the subject automatically, click Activity. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold in such a way that when the animal is immobile, those pixels are almost completely absent. Set Compression artifacts filter to On if you work with pre-recorded video. Trial List Choose Setup > Trial List. Enter your independent variables such as rat ID, Session type (with values Pretest or Test), Treatment (with values Drug vs. Control), Dose, Time of drug administration, Name of the experimenter, etc. For variables which differ between subjects, select Subject as a Scope. If you want, you can pre-define all your trials here (click the Add Trials button), or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a series of trials in the EthoVision Help. Acquiring Data Protocol Basic Protocol (Rats) - Pre-test trial (day 1, before drug administration). The animal is placed in the cylinder for 15 minutes. No scoring of immobility is performed during the first session. This session is needed to acclimatize the rats to the experimental situation and to induce a stable, high level of immobility during the test session. - Test (day 2). After drug administration, the animal is placed in the cylinder for 5 minutes. Score the duration of immobility by summing the time spent immobile; score as immobile minor movements strictly necessary to maintain the animal's head above water. Alternate Protocol (Mice) The mouse is placed in the cylinder. The trial lasts 6 minutes. Measure the latency to immobility from the start of the trial and the duration of immobility for the last 4 minutes. See Castagne et al. (2011). Current Protocols in Neuroscience 8.10A.1-8.10A.14. Score Behaviors Manually If you want to score the subject's behavior manually, define behaviors first under Manual Scoring Settings. After you have started the trial, watch the subjects in the video and in the Manual Scoring tab at the bottom of the screen, click the button for the category that applies. As soon as the behavior of the subject changes, click the button for the corresponding category. - Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help. Determining Mobility Thresholds To find the optimal Highly mobile and Immobile thresholds, you can run a few test trials and check in the Analysis Results and Scoring pane (Dependent Variables tab) the values for Mobility state in relation to the behavior the animal displays. If the Mobility states do not correspond to the behavior of the animal, in the Analysis Results and Scoring pane click Dependent Variables, click the button under Mobility state and adjust the Highly mobile threshold and Immobile threshold. For example, if the animal is struggling, its corresponding Mobility state is Highly mobile. If the current Mobility score is Mobile or Immobile, you probably need to reduce the Highly mobile threshold. Note that you can also adjust the Mobility thresholds after acquisition. In the Analysis profile, add the Mobility state variable and visualize the data. If you do not see the Mobility state variable on your screen, click Show/Hide on the toolbar and select Show Dependent variables, then Mobility state and Mobility. Determining Activity Thresholds In the same way as you defined thresholds for Mobility state, you can define thresholds for Activity state. Use Activity state if Mobility state does not give satisfying results, for instance when detecting thrashing of the animal's limbs which may not be detected properly by Mobility. Note that when you work with multiple cylinders in the same video image, Activity state gives good results when the size of the arena is the same for all cylinders. In the Arena Settings, adjust the contour of the arenas to make them similar. Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors but normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open MDM 0.2 cm. In this profile, the Minimal Distance Moved filter is used (option set to Direct, with a threshold of 2 mm). This filter filters out small movements which result from system noise. Note that smoothing influences the track, that is, the coordinates of the center point of the subject, not the subject's detected area, and therefore does not influence the calculation of Activity-based variables. Source: EthoVision XT 17.5 Application Manual - The Porsolt Forced Swim Test --- ## EthoVision XT - The Radial Arm Maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-radial-arm-maze-test Chapter: EthoVision XT Introduction The Radial Arm Maze Test The radial arm maze was designed to measure spatial learning and memory in rats (Olton and Samuelson, 1976; Olton, 1978, 1985). The original apparatus consists of eight arms, each about 4 feet long, and all radiating from a small circular central platform. At the end of each arm there is a food site, the contents of which are not visible from the central platform. The design ensures that, after checking for food at the end of each arm, the rat is always forced to return to the central platform before making another choice. For example, when investigating working memory, all arms are provided with a food reward and the animal should visit each arm only once. Correct performance of the radial maze task requires intact spatial memory abilities. Performance is affected by hippocampal impairment and a variety of pharmacological agents (e.g., Janitzky et al. 2011). References - Janitzky, K, Schwegler, H., Krober, A., Roskoden, T., Yanagawa, Y. & Linke, R. (2011). Species-relevant inescapable stress differently influences memory consolidation and retrieval of mice in a spatial radial arm maze. Behavioural Brain Research, 219(1), 142-148. - Olton, D.S. (1978). Characteristics of spatial memory. In: Hulse S.H., Fowler H, Honig W.K. (Eds.), Cognitive processes in animal behavior, Hillsdale, NJ: Lawrence Erlbaum Associates, 341-373. - Olton, D.S. (1985). The radial arm maze as a tool in behavioral pharmacology. Physiol. & Behav. 40, 793-797. - Olton, D.S., & Samuelson, R.J. (1976). Remembrance of places passed: Spatial memory in rats. Journal of Experimental Psychology: Animal Behavior Processes, 2, 97-116. - Wenk, G.L. (2004). Unit 8.5A Assessment of Spatial Memory Using the Radial Arm Maze and Morris Water Maze, in: Current Protocols in Neuroscience, John Wiley and Sons, Inc. Physical Setup The following suggestions are specifically to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - There must be maximum contrast between the background and the animal. If you use white animals in the maze, make sure the floors of the arms are dark and vice versa. Preferably, the floor of the room should be the same color (and matted) as the maze, contrasting with the animal. - Lighting should be uniform and even with no shadows. - If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. To prevent reflections, place indirect lighting above or around the maze. Globe type bulbs twice the diameter of standard light bulbs are ideal. They should be close enough to the maze so that there is no direct line of sight between the bulbs and the camera lens. The light should reflect off the walls and ceiling, so that it only reaches both the lens and radial maze indirectly. EthoVision XT Settings In EthoVision XT, you can set up a radial 8-arm maze experiment by using a predefined template in the guided setup. Create an experiment. For details, see Chapter 1 of this manual, or see Setup an Experiment in the EthoVision XT Help. Experiment Settings - Make sure that the radial maze is connected to the EthoVision XT computer. To connect the radial maze to EthoVision XT, you must have the Trial and Hardware Control add-on and the USB-IO box. The procedure and the necessary cabling may differ between manufacturers of the radial maze. Please see the accompanying documentation. - Choose Setup > Experiment Settings. - Under Video Source, and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. - If you want to use Deep learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. - Under Trial Control Hardware, select Use of Trial Control Hardware and click Settings. Select Noldus USB-IO box. - In the Device Configuration window, for TTL ports 1 to 4, under Device type, select Custom Hardware. Next, type in Doors1&2 for TTL Port 1, Doors3&4 for TTL Port 2, Doors5&6 for TTL Port 3 and Doors7&8 for TTL Port 4. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. - In the Grab Background Image window, click the Grab button to grab a background image of the radial maze from the camera image. - Click 1. Draw Scale to calibrate your arena. For details, see Make the arena in the EthoVision XT Help. - Click 2. Select Shape and Draw Arena and check that the predefined arena has the correct shape and size. If necessary, adjust the contour of the arena to fit the radial maze. - If you used the Zone template, click 3. Select Shape and Draw Zones. Check that the zones have the correct shape and size. If necessary, resize or add new zones. - If you are using automated doors, click Arena - Hardware mapping in the Arena Settings window to assign the doors to the arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings > Open one of the following: - Default (no max duration) - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the Center zone. Tracking stops manually (for example when you click the Stop trial button). - Track duration 10 min - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the Center zone. The track stops automatically when 10 minutes have elapsed since the start of the track. Controlling Automated Doors If you want to control the automated doors with EthoVision XT, you need to create new Trial Control Settings. An example of Trial Control Settings for a protocol as described in Unit 8.5A of Current Protocols in Neuroscience (2004) to test basic working memory is the following: - Start condition. We assume that the animal is released in the Center zone with all doors closed. Tracking starts 3 seconds after the animal is put in the Center zone. - Opening all doors simultaneously. You can create a Sub-rule with a Reference for this. In the Sub-rule, each door is opened. For each door, you need to create a separate Hardware Action box, with the corresponding Device name (for example '1&2') and appropriate Action ('Output 1 High' which opens door 1). The reference is activated immediately after the Start trial command. - Closing and then opening all doors. When the animal has visited the Goal zone of one of the arms and returns to the Center zone, all doors are closed and re-opened after 5 seconds. You can create a Sub-rule with a Reference for this. In the Sub-rule, you need to create a Zone transition Condition for each arm separately. Next, all eight Zone transition Conditions need to be connected to an Operator 'Any input True'. With a Hardware Action box, all 8 arms are then closed. Hardware Action boxes for all doors should be arranged in a sequence similar to opening doors. - Stop condition. The trial stops when the animal has visited the Goal zones of all 8 arms OR after 15 minutes have elapsed since the start of tracking. For the first criterion (the animal visits the Goal zone of all arms), use an In Zone Condition for each Goal zone. All eight In Zone Condition boxes are connected to the Operator 'Num simultaneously True inputs'. For the second criterion (after 15 minutes), use a Time Condition box. The two criteria must be combined with OR logic using an 'Any input True' Operator box. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Advanced Detection Settings - Under Video, check that the sample rate is set to 25 or 30 samples/second for multiple body-point tracking. - Click Advanced. - Under Method: By default, Static subtraction is selected as the detection method and Rodents / Default as the method for nose-tail detection. The background in a radial maze test usually does not change much, so Static subtraction usually works well. Make sure the lighting is even and there are no shadows in the maze. If after running some test trials you get nose-tail swaps, try using the tracking method Rodents / For occlusions. If you selected to use the Deep learning technique to track the subject's nose, next to Deep learning click Define and select a box around the subject. Make sure that the box includes the subject's nose. For details, see the EthoVision XT Help. - Optionally, select Track noise reduction. Under Smoothing, set Track noise reduction to On. In some cases better quality tracking can be obtained by reducing track noise during acquisition. This may especially be the case if you use Trial and Hardware Control. For example, if the center point of an animal is detected in the center zone of the maze, you want specific doors to open followed by the closing of doors as soon as the animal enters one of the arms. If the detected center point is moving rapidly because of noise, this may result in doors opening and closing every time the center point crosses the border of the zone. Track noise reduction may solve this problem. - Under Subject size, click Advanced and set a minimum subject size to prevent droppings from being detected. Trial List Enter your independent variables such as Animal ID, Treatment, Baited arms, Name of the experimenter, etc. (for blind trials, enter only the Animal ID). If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a series of trials in the EthoVision XT Help. Baited Arms To mark the trials with the arms that were baited, create an independent variable Baited arms of text type, and define the various combinations as Predefined Values: for example, 1-3-6-8, 1-3-5-7, etc. For each subject to be tested, assign the correct value in the appropriate cell of the Baited arms column. Acquiring Data Protocol The following protocol tests for basic working memory (the subject learns not to re-enter a baited arm). Habituation (Pre-training) In a typical radial 8-arm maze test, first a pre-training session is carried out in which the animal is allowed to freely visit all arms for 10 to 15 minutes per day. Also, the doors are regularly opened and closed to habituate the animal. Training Trials In this phase, the animal is exposed to where the food is, and this is what the later tested memory is based on. Animals are trained one session per day, for approximately one week. Typically, all arms are baited in this phase. At the start of the trial, the animal is placed in the center of the maze, facing the same direction on every trial, every day. Stop the trial when: - All eight arms have been visited, or - 10 minutes have passed since the start of the trial, or - 2 minutes have passed since the animal's last arm entry. Performance Among the variables commonly used for the analysis of performance are: - The number of errors in each session (entering an arm that has been visited previously is counted as an error) and the total number of errors across eight sessions. - The number of correct choices in the first eight arm entries of each session. Reference Memory Errors While the previous protocol is primarily sensitive to impairments in working memory, an alternate protocol allows a dissociation to be achieved between working and reference types of memory. In this protocol, four arms are baited for the training phase. The same maze arms are baited each day and, across sessions, the animal learns to ignore the other arms, which never contain a reward. This is the reference memory component of the task. In the test phase, food items are placed in the same arms as they were on the memory trials that day. It is recorded when the animal gets 100% correct on his memory trials. When the animal enters an arm that is not baited, it is marked as an error. See Wenk, G.L. (2004). Current Protocols in Neuroscience, 8.5A.1-8.5A.12. Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors but normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open one of the two Track Smoothing Profiles: - No filter. - MDM 0.2 cm - In this Track Smoothing Profile, the Direct Minimal Distance Moved filter is used, with an MDM of 0.2 cm. Use Smoothing when you want to eliminate small movements, such as body wobbling during locomotion, that might affect dependent variables such as total distance moved. Selecting Data Choose Analysis > Data Profile. The template contains two data profiles: - All Data - This data profile contains all data. - Treated vs. Control - This data profile contains two Results containers with data for the treated animals and the control animals. This way you create groups of tracks to obtain group statistics for both groups. Analysis Profiles Default Analysis Profiles The template experiment contains three analysis profiles: - Distance and Velocity - In this profile, the total Distance Moved and the mean Velocity are calculated for the center-point. - In Zones - In this profile, the Frequency, Duration and Latency to First for all zones (arms and goal zones) are calculated for the center-point. A visit to a previously chosen arm is considered a working memory error. Source: EthoVision XT 17.5 Application Manual - The Radial Arm Maze Test --- ## EthoVision XT - The RotaRod Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-rotarod-test Chapter: EthoVision XT Introduction The RotaRod Test The rotarod test is widely used to evaluate drug effects on motor coordination in rodents. The principle of this test is that rats or mice are first trained to walk on a rod rotating at a certain speed. Once the animals have learned this, the effect of a test-compound on their motor performance is evaluated. Animals experiencing impaired motor coordination are unable to cope with the rotating rod and will drop off when the rotation speed exceeds their motor coordination capacity. The more disturbed the animals are, the sooner they fall off the rod. The use of rotating rods to measure balance in rodents has been described since at least the 1950s (Dunham and Miya, 1957; Kinnard and Carr, 1957). Jones and Roberts (1968) introduced a significant modification of the basic design with an accelerating rod. The rotarod is a horizontal cylinder that rotates along its long axis. It is situated above the cage floor, high enough to make sure rodents do not jump off the rod and low enough to avoid them being injured when they fall off. The speed of the rotarod is mechanically driven and can be constant or accelerated during the test. The test consists of a training phase in which the rats or mice learn to walk on the rod at a certain speed. Then three test trials are carried out in which a drug is tested. A commonly measured parameter is the time until falling off. With EthoVision XT the rotarod test can be automated. A camera is placed above the rotarod, which gives a top-view image of the setup. The rat or mouse that stays on the rod is present in the center of the camera image. When the animal falls off, or clings onto the rod and turns round on it, it moves out of the center of the image. This can be automatically quantified with various parameters in EthoVision XT. References - Dunham, N.W. and Miya, T.S. (1957). A note on a simple apparatus for detecting neurological deficit in rats and mice. J. Am. Pharmac. Assoc. Sci. Ed., 46, 208-209. - Jones, B.J. and Roberts, D.J. (1968). The quantitative measurement of motor inco-ordination in naive mice using an accelerating rotarod. J. Pharm. Pharmacol., 20, 302-304. - Kinnard, W.J. and Carr, C.J. (1957). A preliminary procedure for the evaluation of central nervous system depressants. J. Pharmacol. Exp. Ther., 121, 354-361. - Carter, R.J., Morton, A.J., and Dunnett, S.B. (2001). Motor Coordination and Balance in Rodents. In Current Protocols in Neuroscience (2001) 8.12.1-8.12.14. EthoVision XT and the RotaRod Test - Mahieu, M., Willems, R., Hoekstra, L., Ver Donck, L. (2012). Automated Detection of Aberrant Behaviour of Mice on the Rotarod: Use of EthoVision XT. Proceedings of Measuring Behavior 2012 (Utrecht, The Netherlands, August 28-31, 2012) 431-433. Physical Setup In most use cases, a video camera is positioned above the rod to record video. For systems with multiple rods, it is best to point one camera towards each rod. You can mix camera images directly with EthoVision XT or a video mixer. To detect the falling off the rod automatically, place the camera in front of the rotarod. You can have EthoVision XT detect the fall off event when the animal disappears from the arena, or a zone drawn around the rod. EthoVision XT Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Select the number of cylinders as Number of Arenas. Arena Settings - Choose Setup > Arena Settings > Open Arena Settings. - After calibrating, click Select Shape and Draw Arena. The arena covers the region around the rod. Make sure that the animal is always within the arena boundary. - Click Select Shape and Draw Zones. Zones To quantify the position of the subject's center point relative to the center of the rod, define a zone (Reference zone) at a known distance from the rotation axis of the rod. For example, draw a line (Reference line) at the right margin of the arena, and define a zone. You can then analyze the distance of the subject's center point from the border of this zone. If you know that the border of the zone is for instance at 10 cm from the rod axis (Reference distance), then you can back-calculate the relative distance of the subject center from the axis. The values of Distance to zone (border) diminished by the Reference distance will be either positive (when the subject moves forward on the rod) or negative (when it moves backward). To measure the reference distance exactly, place a ruler on top of the rod, and refresh the background image. Then draw the Reference line at a specific distance from the rod. Note: Do not define the Reference zone in the middle of the rod. If you do that, distance from the zone border will always be positive, no matter what the position of the subject is. Zones for Turnaround Behavior Detection To automate turnaround behavior detection (mice grip themselves to the rod and turn around without falling off), you can define zones in front of and at the back of the rod. Divide the arena into three main zones: Middle (the rod area), and the front and back areas just outside of the rod. It is then possible to detect turnaround behavior with the following sequence in the Zone transition variable: Middle (mouse in normal position) > Back > Front (the mouse reappears in view) > Middle. Detection Settings Click Advanced. Under Subject Contour, select one or more pixels for the first Erosion and Dilation filter. Increase the first Erosion until the subject's tail is not detected anymore. Then, increase Dilation until the entire body is detected. Acquiring Data Training Phase This phase lasts typically three days. Each subject is placed on the rotarod for a maximum of 1 minute. The trial is repeated a few times each day, with 5 to 10 minutes inter-trial interval. Testing Phase Each subject is placed on the rotarod for a maximum of 1 minute. The trial is repeated two times with 5 to 10 minutes inter-trial interval. Scoring Behaviors Manually If you want to score when the animal falls off the rod, define the behavior Falling off under Manual Scoring Settings. After you have started the trial, watch the subjects in the video and in the Manual Scoring tab at the bottom of the screen, click the button for the arena (subject) that applies. Data Analysis Choose Analysis > Analysis Profile > New. Mouse Position In the Analysis profile, choose Distance to zone and select the Reference zone. Turnaround Behavior In the Analysis profile, click the button next to Zone transition. Select the following sequence: Middle > Back > Front > Middle. The zones must be defined in the Arena Settings before running this analysis. Latency to Fall If the camera is placed in front of the rotarod apparatus, you can measure the latency to fall by using the In zone variable. This calculates the time that the animal was detected in the arena, that is, until it fell off the rod. Source: EthoVision XT 17.5 Application Manual - The RotaRod Test --- ## EthoVision XT - The Sociability Cage Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-sociability-cage-test Chapter: EthoVision XT Introduction The Sociability Test (Three-Chamber Paradigm) The three-chamber paradigm test known as Crawley's sociability and preference for social novelty protocol has been successfully employed to study social affiliation and social memory in several inbred and mutant mouse lines. Sociability testing is a more specific study of social behavior and only focuses on the behavior of one animal towards others. There are several variances to this test, all conducted in a three-chambered test apparatus. In the first variant, the animal's interest in a social stimulus (a conspecific in a wired cage placed in one of the outer chambers) versus a neutral stimulus (an empty wired cage placed in the other outer chamber) is studied. In a preference test for social novelty, the two wired cages contain a familiar and an unfamiliar conspecific. A third variation involves testing the social preference for two different, but both unfamiliar conspecifics. In most cases the interest is measured by assessing the time spent in the same chamber or in close proximity to the familiar or unfamiliar other mouse. Representative Results Typically, a wild type animal will spend significantly more time in the compartment with a strange mouse compared to the compartment with empty cage, indicating normal sociability, social motivation and affiliation. In the social novelty test, the subject has a free choice between the first, already-investigated, now-familiar mouse, and a novel unfamiliar mouse. Usually, a wild-type animal recalls its previous contact with the familiar mouse, and, in this session, tends to spend more time with the newly encountered mouse, indicating intact social memory and predilection for novel experiences. References - Nadler, J.J., Moy, S.S., Dold, G., Perez, A., Young, N.B., Barbaro, R.P., Piven, J., Magnuson, T.R., Crawley, J.N. (2004). Automated apparatus for rapid quantification of social approach behaviors in mice. Genes Brain Behav., 3:303-314. - Moy, S.S., Nadler, J.J., Perez, A., Barbaro, R.P., Johns, J.J., Magnuson, T.R., Piven, J., Crawley, J.N. (2004). Sociability and preference for social novelty in five inbred strains: an approach to assess autistic-like behaviors in mice. Genes Brain Behav 3, 287-302. - Bechtstein, P., Rehbach, N.-J., Yuhasingham, G., Schurmann, C., Gopfert, M., Kossl, M., Maronde, E. (2014). The clock gene Period1 regulates innate routine behavior in mice. Proceedings of the Royal B Society, 281, 20140034. DOI 10.1098/rspb.2014.0034. - Desbonnet, L., O'Tuathaigh, C., Clarke, G., O'Leary, C., Petit E., Clarke N., Tighe, O., Lai, D., Harvey, R., Cryan, J.F., Dinan, T.G., Waddington, J.L. (2012). Phenotypic effects of repeated psychosocial stress during adolescence in mice mutant for the schizophrenia risk gene neuregulin-1: A putative model of gene x environment interaction. Brain, Behavior, and Immunity 26(4), 660-671. - Glass, M.J., Robinson, D.C., Waters, E., Pickel, V.M. (2013). Deletion of the NMDA-NR1 receptor subunit gene in the mouse nucleus accumbens attenuates apomorphine-induced dopamine D1 receptor trafficking and acoustic startle behavior. Synapse, 67(6), 265-279. - Kim J-W, Seung H, Kwon KJ, Ko MJ, Lee EJ, et al. (2014). Subchronic Treatment of Donepezil Rescues Impaired Social, Hyperactive, and Stereotypic Behavior in Valproic Acid-Induced Animal Model of Autism. PLoS ONE 9(8): e104927. DOI: 10.1371/journal.pone.0104927. - Ter Horst, J.P., van der Mark, M., Kentrop, J., Arp, M., van der Veen, R., de Kloet, E.R., & Oitzl, M.S. (2014). Deletion of the forebrain mineralocorticoid receptor impairs social discrimination and decision-making in male, but not in female mice. Frontiers in Behavioral Neuroscience, 8, 26. DOI: 10.3389/fnbeh.2014.00026. EthoVision XT Settings Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. If you want to analyze exploration in detail, choose Center-point, Nose-point and Tail-base detection. If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings If your EthoVision XT license does not include the Behavior Recognition module, EthoVision XT cannot detect sniffing or rearing automatically. However, you can still score those and other behaviors with keystrokes. Choose Setup > Manual Scoring Settings. If you used the template for an open field experiment, four behaviors have been defined: - Sniffing R and Sniffing O, to record manually sniffing at the receiver (unfamiliar mouse) and object (either familiar mouse or empty cage, depending on the test), respectively. - Rearing R and Rearing O, to record manually rearing near the receiver (unfamiliar mouse) and the object cage (either familiar mouse or empty cage, depending on the test), respectively. You can also rename the behaviors if you like. Arena Settings Choose Setup > Arena Settings. If you work with a Sociability test cage with backlight unit, you can reduce the intensity of the backlight before adjusting the arena settings. This makes the edges of the floor plate and walls more visible. If the separation walls show reflections of the animal, this may hinder tracking. In the Arena Settings, click the Arena layer, and draw rectangles around the separation walls. Detection Settings Choose Setup > Detection Settings. Check in the Video Section that the sample rate is set to: - For center point tracking: 5-8 samples/second (for rats) and 12.5-15 samples/second (for mice). - For Nose-tail tracking (rats and mice): 25-30 samples/second. Note: If detection of the subject is not optimal after using the Automated setup function, see Configure Detection Settings in the EthoVision XT Help for details on the advanced detection settings. If you use hooded animals, use the detection method Differencing. If the animal moves from one compartment to the other, it may not be detected well. To improve detection, open the Advanced section in the Detection Settings pane. Under Subject Contour, select one or more pixels for the Dilation filter and the second Erosion filter. Leave the first Erosion filter at zero. Select more pixels for Dilation than for Erosion, for example 3 vs. 1, until the entire animal's contour is detected. Trial List Choose Setup > Trial List. Click Add Variables and enter your independent variables such as the experimental phases and the ID code of your test subject. Acquiring Data Protocol: Sociability Test For each test animal, three trials are carried out: - The first trial (for example 5 min) aims at habituating the test individual to the chamber. Tracking is required when one wishes to know whether the animal explores one chamber more than the other. - A second trial (5 min) is carried out with the empty tubes in the test chambers. The aim of this trial is to quantify the time spent in the two side chambers and near the tubes. - In the third trial (next 5 min), an empty tube is removed and replaced by a female animal restrained in an identical tube. This session is designed to observe differences between the time spent sniffing the social versus non-social object. Protocol: Social Discrimination Test For each test animal, three trials are carried out: - The first trial (10 min) is aimed at habituating the test individual to the chamber and empty tubes. - In the sociability test (next 10 min), an empty tube is removed and replaced by a female animal restrained in an identical tube. This session is designed to observe differences between the time spent sniffing the social versus non-social object. - In the social discrimination test (10 min), the other empty tube is removed and replaced by a novel female. This session is designed to test the ability of the test animal to distinguish between the two females. Score Behaviors Manually To score sniffing and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you find the key codes for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen. - Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help. Data Analysis Data Preparation Data Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. Smoothing Data Choose Acquisition > Track Smoothing Profile and open MDM Filter 0.2 cm. In this profile, the Minimal Distance Moved filter is used with a value of 2 mm and option Direct. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Analysis Profiles The template experiment contains four analysis profiles: - Distance and velocity: For quantifying activity and exploration. Combine this with a Data profile that specifies Results per zone. - In chambers: To calculate the time spent in each of the three chambers. - Behaviors: To analyze behaviors scored manually (rearing and sniffing) or the time that the nose point was detected in the area around each cage (sniffing zone). - On cage: To calculate how often and how long the center point of the subject was found in the zone "cage" (left and right). This correlates with the time the mouse spent on top of the cages. Add other analysis profiles according to your research questions. Click one of the buttons in the Dependent Variables pane and open the Trial Statistics tab to select which statistic to calculate. Example: Calculating a Free Interval The researcher wants to know the time from the moment the animal is entirely in the right compartment to the first moment the animal's nose-point is close to the cage in the same compartment. To calculate this time, in the Analysis profile choose Free Interval. Select an interval that goes from the time when the Current value of In zone, for zone Cage right, and for all body points, is "true" (Start criterion), to when the Current value of In zone for the zone "Interest zone right", and for the nose point, is true (Stop criterion). In the Statistics tab, select Cumulative duration. For more information, see the EthoVision XT Help. Visualizing Data Choose Analysis > Results and select from the following options: - Plot tracks: You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals in Phase 2 and red for animals in Phase 3). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast. - Plot integrated data: You can look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Just like with plotting tracks, you can show tracks or sample points in different colors. - Plot Heatmaps: Make heatmaps of the location of your animals during the different trials. Source: EthoVision XT 17.5 Application Manual - The Sociability Cage Test --- ## EthoVision XT - The Social Interaction Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-social-interaction-test Chapter: EthoVision XT Introduction The Social Interaction Test The Social Interaction test is widely used as a rodent model of anxiety-like behavior, under the assumption that anxiety is incompatible with social behavior (File and Hyde, 1978; File, 1980, 1988). So, an increase in anxiety generally results in a decrease in time spent on social interaction. The Social Interaction test is used to measure: - Sensitivity to both anxiogenic and anxiolytic stimuli - Sensitivity to pharmacological, physiological and environmental manipulations - Ethologically relevant behaviors that do not require confounding manipulations such as food deprivation, pain or conditioned fear Until recently, it has been difficult to automate the test with tracking systems. The features in EthoVision XT make this possible. This document describes the general procedure of how to do this. To be able to automate the social interaction test, you need the Social Interaction module. This module allows you to track two or more subjects in one arena. Note: If you intend to track a free-moving subject while a second subject is caged (social target) and barely visible from above, you can track only the free-moving animal and measure the behavior of that animal towards the cage defined as a zone. In that case you do not need the Social Interaction module. See The Sociability Cage Test. Note: With the Live Mouse Tracker add-on module you can import and analyze Live Mouse Tracker data. Live Mouse Tracker allows long-term analysis of behavior of socially-grouped mice. For more information, see the EthoVision XT Help. The Sample Experiment To see an example of a social interaction test carried out in EthoVision XT, see the sample experiment Social Interaction XT170 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. Next, in EthoVision XT, select File > Restore Backup and select this file. For more information, see the document Description of sample experiments of EthoVision XT.pdf. References - File, S.E., (1980) The use of social interaction as a method for detecting anxiolytic activity of chlordiazepoxide-like drugs. Journal of Neuroscience Methods 2, 219-238. - File, S.E., (1988) How good is social interaction as a test of anxiety? In: Simon, P., Soubrie, P., and Widlocher, D., Selected Models of Anxiety, Depression and Psychosis. Basel: Karger, 151-166. - File, S.E., and Hyde, J.R.G., (1978) Can social interaction be used to measure anxiety? British Journal of Pharmacology 62, 19-24. - Lapiz-Bluhm, M.D.S., Bondi, C.O., Rodriguez, G.A., Bedard-Arana, T., and Morilak, D.A., (2008) Behavioural assays to model cognitive and affective dimensions of depression and anxiety in rats. Journal of Neuroendocrinology 20, 1115-1137. For a list of selected publications using EthoVision XT and the Social Interaction test, see the results of Google Scholar. Physical Setup The following suggestions are aimed at optimizing video tracking of multiple, color-marked animals. Lighting Conditions - For general information on lighting conditions, see the section Physical Setup in the chapter The Open Field Test. - Use a sensitive camera if possible. A low light intensity makes it difficult to separate different colors. When it is not possible to use a sensitive camera or strong illumination in your setup, try using fluorescent marker colors with UV lighting. - For optimal color separation, illuminate your setup with lamps that approximate daylight in color temperature, that is, have a wide spectrum range. Marked vs. Unmarked Subjects In some cases it is required that the identity of the animals that interact in the arena is known and followed, for example in resident-intruder or male-female interactions, or whenever one needs to separate behavioral endpoints (e.g. speed, zone visited) for each individual. In such situations, we recommend marking the animals with color marks (see below). EthoVision XT can also track unmarked animals, however identity switches may occur. It is not guaranteed that the correct identity of each unmarked animal is kept throughout the trial. Marker Characteristics - Use a color scale (for example from a paint company) to find out which colors are most easily recognized by EthoVision in your setup and lighting conditions. Do this before applying color markers to your animals. - Use colors that have different hue values. For example, use red and green and not red and orange. - It may be wise to avoid using red for marking, since it looks like blood. - Note that marking your animals may stress them, and therefore affect their behavior. If necessary, ensure that you select a marking method that lasts for a longer period of time. - Make sure that the marker is as round as possible. This will ensure that the relative movement of the center of gravity of the marker is the same in all directions when the edges of the marker change due to posture changes or otherwise. - Make sure the marker is not too big. The marker can interfere with proper detection of the body contour. For example, make sure that a dark marker on a white animal does not cover the complete width of the animal because it can cause the body to be split in two during tracking in EthoVision XT. - See also Tips for Color Tracking in the EthoVision XT Help. EthoVision XT Settings Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. Under Subjects, specify the Subject roles (for example Resident or Intruder, or Subject 1 and Subject 2). Do not enter the ID of the individual animals. Note: Under Body point detection technique, the Deep learning option is not available for experiments with two or more subject roles. See Deep learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings Choose Setup > Manual Scoring Settings. Here you can define behaviors that you score manually, for instance by pressing a keyboard key. In the template experiment, two start-stop behaviors, Rearing and Grooming, have been defined. Define other behaviors if needed, for example Sniffing and Boxing. For more information, see Set Up an Experiment > Manual Scoring Settings in the EthoVision XT Help. Trial Control Settings Choose Setup > Trial Control Settings > New. In the Trial Control Settings, define conditions for the start and stop of the track. - Starting condition: For instance, 'Start tracking 5 seconds after both animals are detected in the arena'. If you are tracking live, this 5-second delay enables you to put both animals in the arena and to take out your hand before tracking starts (5 seconds might not be enough; check beforehand how much time you need). - Tip: To make sure that tracking starts when both individuals are in the arena, click Settings in the Condition box before the Start track box. Select Current Duration from the Statistic list, then click Settings and then Actors. Select both subject names and select All selected subjects from the list. - Stopping condition: In order to be able to compare the tracks in the analysis, they must have the same length. Either define a Maximum Trial duration or a Stop track condition based on time. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Important: Follow the instructions in the order described below. Sample Rate Click Video. Select a high sample rate: 25 (for PAL analog cameras) or 30 (for NTSC analog cameras and digital cameras) samples per second. Automated Setup Once the animals are in view, click Automated Setup. Select the type of animal you are going to test. Click Next and draw a rectangle around each subject. Make sure that you do this when the animals are not in close contact. If detection of the subject is not optimal after using the Automated Setup function, see Configure Detection Settings in the EthoVision XT Help for details on the advanced detection settings. Subject Identification for Color-Marked Subjects If you mark animals with colors, under Subject Identification make sure that Marker-assisted identification is selected. - Put the marked animals in the arena or play the video. Make sure to select a point in the video where the animals do not touch each other. Alternatively, place the animals in the arena one at a time. - In the Subject Identification section, select one of the subjects and click the Identification button. As a result, the Identification [Subject name] window opens. - Move the mouse pointer to the Video window so the pointer becomes an eyedropper. Move the eyedropper over the color marker of the subject you want to identify and click the left mouse button. - Fine-tune the color settings by adjusting the Hue, Saturation and Brightness in the Identification [subject role name] window. Change the range of color settings by changing the numbers or by resizing the Hue box on the vertical color bar, or resizing and moving the box in the color map (horizontally to adjust Saturation, vertically to adjust Brightness). As a result, the outline covers (almost) the complete marker. - Next, play the video to see in the Video window whether the marker is detected correctly in different parts of the arena. If the marker 'dances' then your color settings are too sensitive. Go back to step 4 and make the box larger. - When you are finished fine-tuning the color settings, continue with setting the Minimal marker size: increase the Minimal marker size until, first, noise is not detected anymore and, second, the marker is not detected anymore (as a result, the outline in the Video window disappears). Now enter a value for the Minimal marker size that is somewhere in between. - Click OK when you are done and repeat steps 1-6 for the other subjects. For details, see Advanced detection settings for color marks in the EthoVision XT Help. Also watch the video Identification Settings in the EthoVision XT video tutorial. Set the Subjects' Contrast Make sure you have selected the correct contrast and check the following: - When you use Static Subtraction or Dynamic Subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. For Dynamic Subtraction, set the Current frame weight slider to a value between 1 and 5 to compensate for the changes in the background with time. - When you use Differencing, adjust the position of the Sensitivity slider until the subjects are properly detected. From the Background changes list, select an option that reflects your conditions (usually, Medium slow works just fine). Contour Erosion and Dilation You need Contour erosion/dilation to get a smooth contour without the tail for accurate modeling and to remove individual pixels of noise. To improve detection, open the Advanced section in the Detection Settings pane. Under Subject Contour, select one or more pixels for the first Erosion filter and the Dilation filter. Leave the second Erosion filter to zero. Increase the number of pixels for Erosion until the animal's tail is removed, then increase Dilation until the entire animal's body contour is detected. Subject Size Before you set the Subject Size, make sure the animals are properly detected and do not touch each other. Click Subject Size, then click Advanced. - Under Modeled subject size, make sure the Apply to all subjects and Fix (for all subjects) options are selected. - Click the Grab button. This adjusts the Average size to the Current size. - Repeat clicking the Grab button until the body fill completely fits the animal. Shape Stability and Modeling Effort The Shape stability setting is used when you track animals whose body can be occluded by, for example, cage bars or part of the body of another animal. When you set the slider closer to Occlusions, EthoVision considers separate objects that are close together to be part of one animal. When you set the slider close to Noise, EthoVision considers separate smaller parts not to be part of the animal. The Modeling effort setting is used when two animals touch and EthoVision loses the separate shapes. At this point, EthoVision tries to determine which part of the large merged blob belongs to either animal, using a lot of processor load in the process. When you set the slider close to Performance, EthoVision is only allowed a short time to determine which part of the merged blob belongs to which animal, and therefore modeling quality is low. When you set the slider to Modeling, EthoVision is allowed a longer time to determine which part of the merged blob belongs to which animal, and therefore modeling quality is good, but this costs a lot of processor load. If you track from video, video tracking slows down. Trial List Enter your independent variables such as rat ID, treatment (drug vs. control), dose, name of the experimenter, etc. If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. - When using color markers, add a Marker color variable to the Trial List to specify the marker color you assigned to each Subject role. This is useful when you have defined, for example, the Subject name Experimental and Stimulus, or Subject 1 and Subject 2, and you have randomly assigned the marker colors to the Subject roles. - Furthermore, you can define a series of trials for batch acquisition. See Acquire a series of trials in the EthoVision XT Help. Acquiring Data Protocol Animals In many social interaction experiments, two animals from the same treatment group are tested together and scored as a single unit. According to Lapiz-Bluhm et al. (2008), this potentially can result in an artificial exaggeration of behavioral effects; that is, a treatment that only slightly impacts social behavior may have an apparently larger and more significant effect if the social behavior of both animals is affected. Their alternative approach tests an experimental animal paired with a neutral stimulus animal, whose behavior is as constant as possible. See The Sociability Cage Test. Habituation Source: EthoVision XT 17.5 Application Manual - The Social Interaction Test --- ## EthoVision XT - The Y-maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-the-y-maze-test Chapter: EthoVision XT Introduction The Y-maze The Y-maze is constructed with three arms of equal length that extend from a central platform at a 120° angle. In the basic version, the animal is free to explore the maze arms. In a modified version, it is possible to close off some arms either to keep the animal in a specific arm for a fixed time once it has entered that arm, or to limit exploration to some arms, not others. The Y-maze is generally used to investigate alternation behavior, where animals are supposed to alternate choices of maze arms on successive opportunities. Irrespective of the precise function of alternation, the animal must remember which arm it had entered on a previous occasion to enable it to alternate its choice on a following trial. Therefore, the use of the Y-maze is based on the assumption that, following some pharmacological manipulation, it is primarily modified memory processes that are reflected in changed alternation rates. Spontaneous Alternation Definition Spontaneous Alternation is a behavioral test for measuring the willingness of rodents to explore new environments. Rodents typically prefer to investigate a new arm of the maze rather than returning to one that was previously visited. Many parts of the brain, including the hippocampus, septum, basal forebrain, and prefrontal cortex, are involved in this task (Conrad et al. 1996). Classical Procedure The animal is released in the center of the maze, and allowed to freely explore the three arms (A, B, C). Over the course of multiple arm entries, the subject is expected to show a tendency to enter a less recently visited arm (A > B > C > A > ...). The observer records the number of arm entries and the number of visits to the three arms without a re-visit in between (for example, A > B > C, B > C > A, etc.) in order to calculate the percentage of alternation. An arm entry is scored when all four limbs are within the arm. Calculation of Alternation Index Given a zone sequence: A > B > C > B > ... An alternation is defined as multiple entries into the three different arms on overlapping triplet sets. In this example the first three visits are an alternation: A > B > C > B > ... The next overlapping triplet set, B > C > B, is not an alternation. The Alternation index is given by the number of alternations divided by the maximum number of possible alternations, that is, the number of alternations that would be obtained if the animal visited the zones in the sequence: A > B > C > A > B > C ... For a 3-arm maze like the Y-maze, the maximum number of alternations is equal to the total number of visits minus 2. Alternation index is expressed in percentage: Alternation index = (Number of alternations / (Total number of zone visits - 2)) x 100 Spontaneous Alternation in EthoVision XT You can easily calculate the Alternation index using the outputs Alternations and Max Alternations in the Zone alternation dependent variable. For more information, see Zone alternation in the EthoVision XT Help. Delayed Alternation The delayed alternation task allows assessing spatial working memory in a T- or Y-maze. The main difference with spontaneous alternation is that performance is evaluated between trials. Classical Procedure In the first trial of the test, the animal is placed at the end of the start arm and has to choose between the two other arms that are baited. Once the choice is made, the subject is removed and after a variable delay, is returned to the start arm. In this second trial, the one arm baited is now the opposite arm to which was chosen during the first trial. The animal has to make a different choice than its first one (correct choice) to get the reward. Delayed Alternation in EthoVision XT For all tests where maze arms can be considered as targets of a choice, and others non-targets (errors), you can use outputs Target first visits and Total errors in the Target visits and errors dependent variable. For more information, see Target visits and errors in the EthoVision XT Help. References - Conrad, C.D., Galea, L.A., Kuroda, Y., McEwen, B.S. (1996). Chronic stress impairs rat spatial memory on the Y maze, and this effect is blocked by tianeptine pretreatment. Behav Neurosci 110: 1321-1334. - Conrad, C.D., Lupien, S.J., Thanasoulis, L.C., McEwen, B.S. (1997). The effects of type I and type II corticosteroid receptor agonists on exploratory behavior and spatial memory in the Y-maze. Brain Res. 759, 76-83. - Hughes, R.N. (2004) The value of spontaneous alternation behavior (SAB) as a test of retention in pharmacological investigations of memory. Neurosc. Biobehav. Rev. 28, 497-505. - Detrait, E., Brohez, C., Hanon, E., De Ryck, M. (2010). Automation of Continuous Spontaneous Alternation to Increase the Throughput for In Vivo Screening of Cognitive Enhancers. Optimization of the Ethovision System for the Y-maze Test in Mice. Proceedings of Measuring Behavior 2010 (Eindhoven, The Netherlands, August 24-27, 2010), 141-144. EthoVision XT Settings Create an experiment. For details, see the Setup an Experiment section in the EthoVision XT Help (press F1 in EthoVision XT). Experiment Settings Choose Setup > Experiment Settings and configure the following: - Number of Subjects per Arena: 1. - Tracked Features: Center-point detection, or center point, nose-point, and tail-base detection. - If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements, including a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. Arena Settings For the Spontaneous Alternation Task - Choose Setup > Arena Settings > Open Arena Settings 1. - Choose the video or camera image and click Grab. - Click 2. Select Shape and Draw Arena. Resize and move the outline of the arena to make it overlap with the Y-maze image. For details on how to resize and move the arena outline, see Arena Settings in the EthoVision XT Help. For the Delayed Alternation Task - Choose Setup > Arena Settings > New. - After calibrating and drawing the outline of the arena, click 3. Select shape and draw zones. Draw the three arm zones. - To draw the start box zone and the target zones (that is, the arm ends which will be baited with food), create an additional zone group. For details on how to work with zone groups and draw and edit shapes, see Arena Settings in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of data acquisition. Choose Setup > Trial Control Settings > New. The templates for the Y-maze contain the following Trial Control Settings profiles: - Default. Tracking starts when the subject's center point is detected for 1 second in the arena. Tracking stops at the end of the video or when you give the stop command. - Tracking Duration 5 min. Tracking starts when the subject's center point moves from the start box to the center arm. Tracking stops after 5 minutes. Detection Settings Choose Setup > Detection Settings. Check in the Video Section that the sample rate is set to: - For rats: 5 samples/second. - For mice: 12.5-15 samples/second. When tracking the nose-point, center-point, and tail-base point of the rodents, always choose the maximum sample rate. If you selected the Deep Learning technique to track the subject's nose, under Method next to Deep learning click Define and select a box around the subject. Make sure that the box includes the subject's nose. Try not to include objects like walls, especially if they are the same color as the subject. For details, see the EthoVision XT Help. Trial List Independent Variables If you perform a Y-maze test where one of the arms is closed off or provided with food, it is always a good idea to create independent variables that mark the type of trial, which you can use to select a subset of trials for answering a specific question. For example, create the independent variable Correct choice with possible values Yes and No, depending on whether the subject chose the arm not visited in the previous trial. At the end of each trial, enter the value for that subject. You can use this variable to filter the trials based on the value of Correct choice. Acquiring Data Continuous Spontaneous Alternation - Release the subject in the center of the Y-maze. - Start the trial. - Let the subject explore the maze for the time required (typically 5-6 minutes). Then stop the trial. - Put the subject back in its home cage. Proceed with the next subject. Forced-choice Alternation In this variant, the subject is forced to explore one of the two arms in the first trial. - Close one of the arms of the maze. Place the subject into the start arm, and allow it to explore the maze for 15 minutes. - After a fixed inter-trial interval, open the door in the blocked arm. Return the subject to the maze by placing it in the start arm. The subject is allowed to explore freely all three arms of the maze for 5 minutes. The Y-maze is often rotated between the two trials. Two-trial Spontaneous Alternation In this task, the subject is confined for a fixed time in the T- or Y-maze arm chosen in the first trial. This allows manipulation of the time that the animal has experience with one of the arms. - In the first trial, let the subject access one of the arms after having left the start arm. Once an arm has been entered, close off that arm by lowering a guillotine door behind the subject. Leave the subject there for a fixed time (this is called the intra-trial interval). - Remove the subject and, after an inter-trial interval, let it choose the arm in a second trial. This two-trial sequence is repeated a number of times. Delayed Alternation This task is usually designed with a T- or Y-maze where one arm is the starting location and the other arms are baited. - Release the subject in the start arm. Once the subject enters one of the other two arms, close the door for that arm (trial 1). - After a predetermined inter-trial interval, release the subject and let it freely choose one of the two arms (trial 2). If the subject chooses the alternate arm, this is scored as alternation. This two-trial procedure is repeated several times. Data Analysis Analysis Profiles Choose Analysis > Analysis Profile. The template experiment contains the following analysis profiles: - Distance, Time and Movement. Calculates the total Distance moved (a measure of activity of the animal), the mean Velocity, and the total time spent in the two states of Movement (moving and not moving). Group means with their standard errors are also calculated. - Zone alternation. Includes the variable In zone (to calculate the frequency, total time, and latency to first visit for each zone) and Zone alternation (to calculate the number of alternations and the maximum number of alternations for that set of zone visits). Alternation Behavior Spontaneous Alternation - Choose Analysis > Results > Statistics and Charts. - Select the Analysis profile that contains the Zone Alternation variable. - Locate the column Zone Alternation in the table. - To calculate the Alternation index, divide Alternations by Max Alternations and multiply by 100. To change the Zone alternation definition, open the Analysis profile Zone Alternation and double-click the variable Zone alternation. Here you can specify which statistics you want. You can also enter a Zone exit threshold to remove false re-entries in a zone from the statistics, due to small movements of the body point near the zone borders. For more information, see Zone alternation in the EthoVision XT Help. Delayed Alternation For delayed alternation tests, Zone alternation is not the correct dependent variable. To analyze correct and incorrect choices, use Target visits and errors to compare performance between trials. Because the target arm changes between trials (for trial 2, the target is the arm which was not visited in the previous trial), you must define multiple instances of Target visits and errors. Whether an arm can be defined as "target" depends on the outcome of the previous trial. If the subject went to the Left arm in trial x, then for trial x+1 the target should be the Right arm, and a revisit to the Left arm should be scored as an error. To configure this: - In the Trial List (Setup > Trial List), mark each trial with a variable which states which arm was the correct choice. By definition, the first trial of each subject has no "correct" choice, as the values for subsequent trials depend on what the animal does in that trial. - In the Data Profile, filter the trials based on this variable. Create two Data profiles: one for "Right arm correct" and one for "Left arm correct". - Create two corresponding Analysis profiles: - Analysis profile: Target visits and errors for when the target (correct choice) was the Left arm. The Right arm is a non-target; visits to that arm are scored as errors. - Analysis profile: Target visits and errors for when the target (correct choice) was the Right arm. When analyzing the data, make sure to combine each Data profile with the correct Analysis profile. Visualizing Data Choose Analysis > Results > Integrated Visualization. The first plot shows the variable In zone defined in the Analysis profile, where you can see which arms were visited during the trial. The second plot shows Zone alternation. The subject visits first the zone marked in blue, then the one in red, and when the subject enters the green-marked zone, an alternation is completed. This is scored as Alternations (blue vertical segment). At every visit except the last two in a trial, Max Alternations is also scored (purple vertical segment), marking the moment a possible alternation could have occurred. Source: EthoVision XT 17.5 Application Manual - The Y-maze Test --- ## EthoVision XT - Trial and Hardware Control in EthoVision® XT 17.5 - Reference Manual URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-trial-and-hardware-control-in-ethovision-xt-175-reference-manual Chapter: EthoVision XT Reference Manual Version 17.5 Information in this document is subject to change without notice and does not represent a commitment on the part of Noldus Information Technology BV. The software described in this document is furnished under a license agreement. The software may be used or copied only in accordance with the terms of the agreement. publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any other language in whole or in part, in any form or by any means, without the written permission of Noldus Information Technology BV. EthoVision and PhenoTyper are registered trademarks of Noldus Information Technology BV. Other product names are trademarks of their respective companies. March 9, 2023 For EthoVision XT version 17.5 Noldus Information Technology BV International headquarters Wageningen, The Netherlands Phone +31-317-473300 E-mail info@ noldus.nl Contents this manual - 7 why use trial and hardware control? - 7 conditions and actions - 8 trial control rules - 9 how trial control instructions are executed - 10 your ethovision license and trial control - 14 analysis of trial control data - 15 the components pane - 17 the trial control window - 19 maximum trial duration pane - 21 procedure - 23 conditions - 26 actions - 27 trial control variables - 28 external commands - 31 operators - 34 re-use trial control elements - 36 frequently-occurring cases - 38 test the trial control sequence - 42 apply trial control to your trials - 45 the default start-stop trial rule - 47 customize the start-stop trial rule - 49 examples of start-stop trial rules - 51 Contents use sub-rules - 55 create a sub-rule - 56 create a reference to a sub-rule - 57 sub-rule start conditions - 60 sub-rule stop conditions - 61 place the sub-rule reference in the trial control sequence - 63 end a sub-rule - 63 call a sub-rule from another sub-rule - 65 conditions based on time - 67 conditions based on a time interval - 69 conditions based on a trial control variable - 71 conditions based on a dependent variable - 72 subjects in a condition - 75 when is a condition met? - 76 conditions based on behaviors scored manually - 78 conditions based on hardware devices - 79 More About Conditions Based On Dependent distance moved - 84 velocity - 84 movement - 85 acceleration - 86 in zone - 86 distance to zone - 88 distance to point - 88 meander - 89 target visits and errors - 89 zone alternation - 90 zone transition - 90 heading - 91 heading to point - 91 head direction - 92 head directed to zone - 92 turn angle - 93 angular velocity - 94 activity - 94 body elongation - 95 body elongation state - 95 body angle - 96 body angle state - 96 Contents mobility - 97 mobility state - 97 rotation - 98 javascript variables - 98 distance between subjects - 99 proximity - 99 body contact - 100 relative movement - 100 net weighted movement - 100 weighted movement from - 101 weighted movement to - 101 conditions based on multiple dependent variables - 101 devices supported in ethovision xt - 104 work with multiple devices - 106 connect the hardware devices - 107 set the port connections - 109 assign devices to arenas - 113 test the hardware devices - 115 program trial control with hardware devices - 117 the usb-io box - 120 install the usb-io box - 124 connect the usb-io box to devices - 128 use multiple usb-io boxes - 131 test the usb-io box - 132 jumper and dip switch settings - 133 configure ethovision xt - 136 the mini usb-io box - 137 the ttl port tester - 144 the optical isolated ttl-io interface - 151 technical specifications - 153 user-defined device types - 155 in a nutshell - 155 define a new device type - 157 sample file - 158 predefined ids - 162 xml file entries - 163 Contents what do you want to do? - 168 trial control events - 170 trial control states - 172 data within trial control states - 177 trial control variables - 178 hardware command - 178 hardware continuous variable - 179 hardware state variable - 181 free intervals based on trial control and hardware data - 184 the analysis results - 184 export trial control data - 185 introduction - 188 simple case: two arenas - 191 advanced case: six arenas - 196 Source: EthoVision XT 17 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 17 - GPU Video Decoding URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-17-gpu-video-decoding Chapter: EthoVision XT Decoding and Encoding Video with the GPU in EthoVision XT 17.5 Why This Technical Note This technical note addresses an issue that may be of interest to those who have a previous version of the software (EthoVision XT 17.0 or earlier) and have upgraded to EthoVision XT 17.5. Important Terms - Decoding: This equals playing back existing video files during tracking. - Encoding: This equals recording video from a live camera stream. This note is mainly about an issue that occurs when decoding video, not encoding video. Use of the GPU for Encoding and Decoding Video EthoVision XT reads information from a video file and uses the pixel values to detect one or more subjects. - In EthoVision XT 17.0 and earlier versions, encoding and decoding of video is done by the CPU (Central Processing Unit, or processor) of the EthoVision XT computer. - In EthoVision XT 17.5 and later versions, encoding and decoding of video is done by default by the Graphics Processing Unit (also known as GPU, or graphics card). The reason for this change from version 17.0 to 17.5 is that the GPU allows faster processing of video, especially when you work with video of high resolution or track subjects with the Behavior Recognition function. This reduces the workload of the CPU and results in greater performance during tracking. Description of the Issue Video Image When EthoVision XT uses the GPU to decode (i.e., play back) a video file, the image looks slightly different from what it would if the software used the CPU for the same task. This difference occurs in some videos, not others. Where a difference does appear, the GPU-based image is slightly brighter than the CPU-based image. In other words, EthoVision XT 17.5 "sees" a video file not exactly as EthoVision XT 17.0 would when playing back the same video. Effects of This Issue on Detection If the video image in EthoVision XT 17.5 (playback with GPU) is not exactly the same as that in EthoVision XT 17.0 and earlier (playback with CPU), the detection settings used in experiments made in EthoVision XT 17.0 or earlier are probably no longer optimal when you use the same video file in EthoVision XT 17.5. - If you use the Gray Scale detection method, you may need to change the range of gray values to detect the subject correctly. - If you use the Dynamic Subtraction method, you need to make a new reference image from the current video and modify the contrast range to detect the subject correctly. If you are in the middle of an experiment that you started in EthoVision XT 17.0 or earlier, you would need to acquire the new trials with different detection settings. This may not be desirable because you want to keep consistent detection settings across the trials to reduce the risk of biases in the analysis. What Should I Do? If You Have Completed All Your Experiments in EthoVision XT 17.0 or Earlier You do not need to take any particular action. Click Yes in the window that appeared when you opened the experiment. The experiment is converted to version 17.5. When you create a new experiment in EthoVision XT 17.5, the software uses the GPU to play back and record video. Open the Detection Settings and optimize them as usual. If You Have an Old Experiment and You Need to Acquire More Trials Complete the Experiment with the Old Playback Method If you need to complete an experiment after upgrading to EthoVision XT 17.5, you may want to keep using the same video settings as before. This way you do not need to update your detection settings because EthoVision XT will use the old, CPU-based method to handle video, ensuring that the old and new tracks are obtained with the same detection settings. Do the following after opening the old experiment: - Click Yes in the window that appeared when you opened the experiment. The experiment is converted to version 17.5. - Choose File > Preferences. - Click the Video Settings tab and next to Play Back and Record Video select CPU. - Click OK. You are ready to acquire your trials. Re-Do All Trials with the New Method Alternatively, you can acquire all your trials with the new playback method. This means that you have to clear the existing trials — that is, delete the tracks without removing the videos — and re-acquire all trials, while keeping the option File > Preferences > Video Settings > Play Back and Record Video set to GPU. For how to re-do trials, see the EthoVision XT Help. How the GPU Option Is Applied The option for enabling and disabling the GPU for video encoding and decoding is applied at the application level. That is, the settings are applied to all new experiments that you create. - Make sure that the Video Settings selection is kept consistent within experiments. That is, make sure that the selection is either CPU or GPU for all the trials in that experiment. - If you intend to create multiple experiments that are related to each other, we recommend that you keep your selection in Video Settings consistent across those experiments. Source: EthoVision XT 17 GPU Note, Noldus Information Technology --- ## EthoVision XT 17.5 - Technical Specs Rodent URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-175-technical-specs-rodent Chapter: EthoVision XT System Configurations EthoVision® XT Base allows you to perform complete tests with one animal in one arena. You can extend the functionality with one or more of the eight available modules: - Mouse Behavior Recognition Module – Automatically detect ten mouse behaviors such as grooming, rearing, and digging. - Rat Behavior Recognition Module – Automatically detect ten rat behaviors such as grooming, rearing, and sniffing. - External Data Module – Integrate EthoVision XT data with co-acquired external data. - Multiple Arenas Module – Track animals in up to a hundred arenas simultaneously. - Social Interaction Module – Track multiple animals within each arena. - Trial & Hardware Control Module – Create complete test protocols to initiate and control interaction with external equipment, based on real-time analysis of the animal's behavior. - Quality Assurance Module – Assign different rights to different users and comply with Good Laboratory Practice guidelines. Data Management Setup Template Experiments EthoVision XT contains a user-guided set-up with templates for several test paradigms. At the start of the program you can either start a brand-new experiment, re-use the settings from a previous experiment, or use the user-guided set-up to open an experiment template suited to a specific test (water maze, plus maze, etc.). With these templates, many basic settings are pre-set, such as arena definition, detection settings, and parameters for analysis. You can fine-tune these settings to fit your specific needs. Live Mouse Tracker Experiments If you use the Live Mouse Tracker acquisition system and want to analyze these data in EthoVision XT, you can select the Live Mouse Tracker experiment option when creating a new experiment. This creates a modified version of a standard, multi-subject, multi-body point experiment, with predefined, permanent settings for Live Mouse Tracker. Good Laboratory Practice For those conducting Quality Assurance experiments, particularly in environments adhering to Good Laboratory Practice (GLP) standards, EthoVision XT offers specialized options to meet these rigorous requirements. This ensures that your experiments not only yield reliable data but also comply with industry standards for quality and reproducibility. Flexibility For researchers seeking maximum flexibility in their experimental design, the "New from Scratch" option allows for complete customization of the experiment setup. This feature is ideal for innovative research that goes beyond standard protocols, offering the freedom to tailor every aspect of the experiment to unique research needs. Experiment Options - Tracking can be done live or from a video file. - You can use digital cameras or analog cameras (but not a combination of the two). - You can connect external data acquisition systems to EthoVision XT. - Track in one or multiple arenas, with a maximum of 100 arenas. - Track one or multiple subjects per arena, with a maximum of 16 subject roles. - For mice, rats, and zebrafish you can use center point tracking, or center of gravity, nose, and tail base. For mice and rats you have the option between a contour-based technique or a deep learning based technique. You can also track based on color or color marker. - Activity analysis – a non-tracking option analyzing overall activity per arena based on pixel changes. This is very useful for freezing detection. - Distance can be measured in millimeters, centimeters, meters, or inches. - Time can be measured in milliseconds, seconds, minutes, or hours. - Rotation can be measured in degrees, radians, gradians, or rotations. Manual Scoring The Manual Event Recorder is a built-in coding system which allows you to define a list of behaviors that you can score manually during and after data acquisition (live or offline). - Score live. - Score offline, to score at a lower or faster playback speed. You can also edit scored events. Types of behaviors: - Start-Stop Behaviors – Behaviors that are independent from each other. - Point Events – Behaviors without a duration. - Mutually Exclusive Behaviors – Behaviors grouped in such a way that activating one behavior automatically stops the other behavior. You can define different behaviors and score those categories with keyboard keys or with the mouse. Without key codes defined, you can manually score events using the mouse. Arena Settings The arena is the region in the video image where the animal is tracked. You can define: - The arena or arenas. - Subdivisions of the arena (zones). - Cumulative zones (define individual smaller zones to be taken into account for cumulative analysis). - Hidden zones (used for shelters) and entry zones to analyze entries and exits. - Zones organized in layers, so you can define and analyze zones that overlap. - Points of interest. You can define an unlimited number of zones in an arena and create zones of any shape. Calibration of your arena will allow EthoVision XT to calculate parameters such as velocity and distances to certain points. If you are tracking in multiple arenas, you can copy and paste the settings from one arena to the other. Multiple Arena Definition When your experiment contains multiple arenas – for instance a group of open fields or home cages – you can use the multiple arena set-up functionality. This means that you do not need to draw each arena separately. EthoVision XT allows you to easily rotate, scale, transpose, resize, and reposition the series of arenas simultaneously. In DanioVision experiments, automated arena detection detects the individual wells in standardized well-plates automatically. Arena and Zone Auto-Subdivision This option allows the automated subdivision of circular and rectangular arenas into multiple equal zones, including auto-labeling of these subdivisions. For example, it can be used to divide a water maze into quadrants, simplifying the process of analyzing behavior across different sections of the arena. Multi-Camera Set-Up In EthoVision XT you can combine the input of multiple cameras. This way you can track from multiple arenas (in combination with the Multiple Arenas Module) without the need to place them all under one camera. Trial Control Options You can program EthoVision XT to automatically start and stop tracking, based on any of the parameters offered by EthoVision XT. This feature also includes an external command option, which allows you to start another computer program when a condition becomes true. For example, you can present a visual stimulus on a computer screen or play a sound file when the animal enters a particular zone. With the additional Trial & Hardware Control Module, you can define complete test protocols to initiate and control interactions between your animals and external sensor and stimuli devices. Real-time analysis of any of the parameters of EthoVision XT allows you to control complete test protocols based on your animal's behavior. You can use it for complex learning tasks such as the radial arm maze with automatically controlled doors and food delivery using pellet dispensers. All standard TTL-based hardware can be attached and controlled. If you are using multiple arenas, conditions are applied to each arena individually. Detection Settings EthoVision XT offers four different detection methods: - Gray Scaling – Defines all connecting pixels with a gray value between two threshold values as a possible subject. - Static Subtraction – Looks at differences between a reference image (without the animal) and the current video image (with the animal in the arena). - Dynamic Subtraction – Like static subtraction, looks at differences between a reference image and the current image, while updating the reference image on each sample. - Differencing – Makes a statistical comparison between pixels in a reference image and the current image. The statistical comparison uses the variance in contrast between the current and reference image and determines whether each pixel has changed enough to be considered part of the subject. Besides the above-mentioned options, contrast settings can be fine-tuned, subject size can be defined, and video smoothing can be applied. There are also additional detection settings specific to the Rat or Mouse Behavior Recognition Module. Tracking Methods Body Point Estimate The tracking method specifies how the body points are estimated once the subject is detected. Depending on how many subjects and body points you specify in the Experiment Settings, one or more methods for tracking of body points are available in the Method section of the Advanced Detection Settings. Deep Learning Based Body Point Detection When using this technique, a new algorithm based on a convolutional neural network finds the nose and tail-base points of rodents with high accuracy and few or no nose-tail swaps. The network was trained to extract features from video images of rodents of various colors and in various backgrounds, with videos in which the nose and the tail-base were annotated. During tracking, the network analyzes a portion of the image that includes the detected subject. It creates a map of probability of occurrence for both the nose and tail-base points, and finally makes an estimate of the position of the nose point and the tail-base point based on the highest probability. Contour-Based Body Point Detection - Any Species – Default – This detection method analyzes the contour of the area detected as subject at each sample to assign the nose point and tail-base. Make sure in the detection settings that the tail is fully detected. With this method it may be possible to track non-rodent shapes, but the method is not designed for it. This method is automatically activated when you track the center point in one animal per arena and you specified Other Species in the automated setup. - Rodents – Default – This detection method analyzes the varying shape of the contour of the area detected as subject and builds up a rodent model. It is more robust than the shape-based method because it does not require the nose and tail to be visible; it can predict the position of the nose and tail based on previous samples. Make sure in the detection settings that the tail is removed from the body contour with Erode and Dilate. Choose this method when you want to track a single rodent without occlusions or without difficult tracking conditions. - Rodents – For Occlusions – This method can handle severe shape distortions, for example when the animal's body is occluded or when multiple animals touch. However, it requires significant computer performance. Choose this method for rodents in a social interaction context, or when you track rodents that can be occluded, for example by bars or other objects in the cage. Make sure in the detection settings that the tail is removed from the body contour with Erode and Dilate. - Other Species – For Occlusions – This method does not make any assumption about the shape of the subject. Choose this method to track insects, crustaceans, and large animals. Also use this method if you track fish from the side view of the water tank and the Adult Fish method does not give good results. Note that with this method you only track the center point. Contour adjustments can be made in one of two ways or by combining both methods: - Erosion – Decreases the animal's surface area by 1–10 pixels. - Dilation – Increases the animal's surface area by 1–10 pixels. Source: Technical Specs - EVXT 17.5 - Rodents, Noldus Information Technology --- ## EthoVision XT 17.5 - Technical Specs Zebrafish URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-175-technical-specs-zebrafish Chapter: EthoVision XT System Configurations EthoVision® XT Base allows you to perform complete tests with one animal in one arena. You can extend the functionality with one or more of the eight available modules: - External Data Module – Integrate EthoVision XT data with co-acquired external data. - Multiple Arenas Module – Track animals in up to a hundred arenas simultaneously. - Social Interaction Module – Track multiple animals within each arena. - Trial & Hardware Control Module – Create complete test protocols to initiate and control interaction with external equipment, based on real-time analysis of the animal's behavior. - Quality Assurance Module – Assign different rights to different users and comply with Good Laboratory Practice guidelines. - Track3D – Record movement of an animal in a test chamber (such as a wind tunnel or swim tank), visualize the trajectory in a three-dimensional image, and calculate a number of movement parameters. Data Management 1. Setup Template Experiments EthoVision XT contains a user-guided set-up with templates for several test paradigms. At the start of the program you can either start a brand-new experiment, re-use the settings from a previous experiment, or use the user-guided set-up to open an experiment template suited to a specific test (water maze, plus maze, 96-well plate, etc.). With these templates, many basic settings are pre-set, such as arena definition, detection settings, and parameters for analysis. You can fine-tune these settings to fit your specific needs. DanioVision Experiments If you use DanioVision™, a system specifically designed for observing and analyzing zebrafish larvae behavior, you can select the DanioVision experiment option when creating a new experiment. Furthermore, the automated arena detection detects individual wells in standardized well-plates automatically and the automated detection settings detect the subjects — for example, zebrafish larvae — and optimize detection with a few mouse clicks. Good Laboratory Practice Additionally, for those conducting Quality Assurance experiments, particularly in environments adhering to Good Laboratory Practice (GLP) standards, EthoVision XT offers specialized options to meet these rigorous requirements. This ensures that your experiments not only yield reliable data but also comply with industry standards for quality and reproducibility. Flexibility For researchers seeking maximum flexibility in their experimental design, the "New from Scratch" option allows for complete customization of the experiment setup. This feature is ideal for innovative research that goes beyond standard protocols, offering the freedom to tailor every aspect of the experiment to unique research needs. Experiment Options - Tracking can be done live or from a video file. - You can use digital cameras or analog cameras (but not a combination of the two). - You can connect external data acquisition systems to EthoVision XT. - Track in one or multiple arenas, with a maximum of 99 arenas. - Track one or multiple subjects per arena, with a maximum of 16 subject roles. - For mice, rats, and zebrafish you can use center point tracking, or center of gravity, nose, and tail base. For mice and rats you have the option between a contour-based technique or a deep learning based technique. You can also track based on color or color marker. - Activity analysis – a non-tracking option analyzing overall activity per arena based on pixel changes. This is very useful for freezing detection. - Distance can be measured in millimeters, centimeters, meters, or inches. - Time can be measured in milliseconds, seconds, minutes, or hours. - Rotation can be measured in degrees, radians, gradians, or rotations. Manual Scoring The Manual Event Recorder is a built-in coding system which allows you to define a list of behaviors that you can score manually during and after data acquisition (live or offline). - Score live. - Score offline, to score at a lower or faster playback speed. You can also edit scored events. Different types of behaviors: - Start-Stop Behaviors – Behaviors that are independent from each other. - Point Events – Behaviors without a duration. - Mutually Exclusive Behaviors – Behaviors grouped in such a way that activating one behavior automatically stops the other behavior. You can define different behaviors using the keys from the computer keyboard. Without key codes defined, you can manually score events using the mouse. Arena Settings The arena is the region in the video image where the animal is tracked. You can define: - The arena(s). - Subdivisions of the arena (zones). - Cumulative zones (define individual smaller zones to be taken into account for cumulative analysis). - Hidden zones (used for shelters) and entry zones to analyze entries and exits. - Zones organized in layers, so you can define and analyze zones that overlap. - Points of interest. You can define an unlimited number of zones in an arena, and create zones of any shape. Calibration of your arena will allow EthoVision XT to calculate parameters such as velocity and distances to certain points. If you are tracking in multiple arenas, you can copy and paste the settings from one arena to the other. Multiple Arena Definition When your experiment contains multiple arenas — for instance using a multi-well plate or a group of open fields or home cages — you can use the multiple arena set-up functionality. This means that you do not need to draw each arena separately. EthoVision XT allows you to easily rotate, scale, transpose, resize, and reposition the series of arenas simultaneously. In DanioVision experiments, automated arena detection detects the individual wells in standardized well-plates automatically. Arena/Zone Auto-Subdivision This option allows the automated subdivision of circular and rectangular arenas into multiple equal zones. It includes auto-labeling of the subdivisions. Multi-Camera Set-Up In EthoVision XT you can combine the input of multiple cameras. This way you can track from multiple arenas (in combination with the Multiple Arenas Module) without the need to place them all under one camera. Trial Control Options You can program EthoVision XT to automatically start and stop tracking, based on any of the parameters offered by EthoVision XT. This feature also includes an external command option, which allows you to start another computer program when a condition becomes true. For example, present a visual stimulus on a computer screen or play a sound file when the animal enters a particular zone. With the additional module for Trial & Hardware Control, you can define complete test protocols to initiate and control interactions between your animals and external sensor and stimuli devices. Real-time analysis of any of the parameters of EthoVision XT allows you to control complete test protocols based on your animal's behavior. If you are using multiple arenas, conditions are applied to each arena individually. You can use it for complex learning tasks such as the radial arm maze with automatically controlled doors and food delivery using pellet dispensers. Attach and control all standard (TTL-based) hardware. Detection Settings EthoVision XT offers four different detection methods: - DanioVision – For DanioVision, the detection method is chosen automatically. It provides great ease to set as a method because it is tailored specifically to larvae. - Gray Scaling – Defines all connecting pixels with a gray value between two threshold values as a possible object. - Static Subtraction – Looks at differences between pixels in a reference image (without the animal) and the current video image (with the animal in the arena). - Dynamic Subtraction – Like the previous method, looks at differences between a reference image and the current image, while updating the reference image on each sample. - Differencing – Makes a statistical comparison between pixels in a reference image and the current image. The statistical comparison uses the variance in contrast between the current and reference image and determines whether each pixel has changed enough to be considered part of the subject. Tracking Methods (Body Point Estimate) The tracking method specifies how the body points are estimated once the subject is detected. Depending on how many subjects and body points you specify in the Experiment Settings, one or more methods for tracking of body points are available in the Method section of the Advanced Detection Settings. Contour-based body point detection technique options include: - Any Species – Default – This detection method analyzes the contour of the area detected as subject at each sample to assign the nose-point and tail-base. Make sure in the detection settings that the tail is fully detected. With this method it may be possible to track non-rodent shapes, but the method is not designed for it. This method is automatically activated when you track the center-point in one animal per arena and you specified Other Species in the Automated Setup. - Adult Fish – For Occlusions – Use this method to track zebrafish and other fish of similar shape when viewed from above. Make sure that the whole body of the fish is detected, including the tail. - All Species – For Occlusions – This method does not make any assumption about the shape of the subject. Choose this method to track insects, crustaceans, and large animals. Also use this method if you track fish from the side view of the water tank and the Adult Fish method does not give good results. However, with this method you only track the center point. Contour adjustments can be made in one of two ways or by combining both methods: - Erosion – Decreases the animal's surface area by 1–10 pixels. - Dilation – Increases the animal's surface area by 1–10 pixels. Besides the above-mentioned options to optimize the detection and identification of the subject(s), contrast settings can be fine-tuned, subject size can be defined, and video smoothing can be applied. There are also some additional detection settings specific to use with the Rat or Mouse Behavior Recognition Module. Trial List The trial list consists of trials that are planned, carried out, or skipped, including system variables and user-defined independent variables. All are organized in a cross table and data can be copied to and from Excel sheets. In EthoVision XT you can schedule a list of trials based on pre-recorded video files. This list can be automatically acquired as a batch in data acquisition. The trial list also allows you to import trials from previously acquired experiments, with the aim to analyze data collected in two or more identical experiments as one data set. 2. Data Acquisition EthoVision XT offers the following acquisition methods: - Acquire Data Live – Live tracking requires no disk space for video storage, but creates no video backup either. The maximum trial duration without video recording (as tested) is 72 hours. - Acquire Data Live and Record Video – Live tracking while EthoVision XT records a backup video to an MPEG4 video file. The maximum trial duration with video recording (as tested) is 72 hours depending on the hardware used. - Longer Trials – To acquire trials longer than mentioned above, you can split your multi-day testing into multiple trials. - Record Video and Acquire Data – EthoVision XT records a video to an MPEG4 file which you can use for data acquisition later. This method is recommended if the computer is not fast enough for live data acquisition. Source: Technical Specs - EVXT 17.5 - Zebrafish, Noldus Information Technology --- ## EthoVision XT 18 - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-acquiring-data Chapter: EthoVision XT Acquire The Data Methods Choose Acquisition > Open Acquisition. Locate the Acquisition Settings window at the right side of the screen. If you track from pre-recorded video files, select Track next planned trial, click the button next to Video and open the video you want to use. If you track from the live camera image, select Track next planned trial. Select Save video if you want to save the camera footage to a video file. For more acquisition methods, see Acquire Data in the EthoVision XT Help. Procedure For Acquiring One Trial - Under Settings, choose the Arena Settings, Trial Control Settings, and Detection Settings, if they are not already selected in the Trial List. - If you track from video and do not score behaviors manually, make sure the DDS (Detection Determines Speed) checkbox is selected in the Playback Control window. With this option you ensure that every sample is analyzed. Acquire the data - To start a trial, click the Start trial button in the Playback Control window. - Release the subject in the arena. - To stop the trial, click the Stop trial button. - Return the subject to its home cage or container. - Prepare the next subject, or load a new video file to acquire the next trial. More Options You can automatically start and stop your trial depending on the behavior or position of your subject. See page 10. You can also acquire data in batch mode. For details, see Batch data acquisition in the EthoVision XT Help. You can also score behaviors manually during tracking. If you saved the video during tracking, you can review the video and add or edit existing behavioral data. For details, browse the EthoVision XT Help: To define behaviors, see Set Up an Experiment > Manual Scoring Settings. To score behaviors, see Acquire Data > Score behaviors manually. If no planned trial is left, click the Add Trial button in the Playback Control window. Sometimes EthoVision XT tracks a reflection instead of the subject, it confuses the nose- point and the tail-base or swaps subjects when you track multiple animals simultaneously. Whenever that occurs, you can correct those errors. For more information, see Edit the Tracks in the EthoVision XT Help. Calculate the statistics Source: EthoVision XT 18 - Quick Start Guide --- ## EthoVision XT 18 - Analysis, Visualization, and Export URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-analysis-visualization-and-export Chapter: EthoVision XT Calculate The Statistics Prepare The Tracks A track is the group of samples acquired for a subject. You can choose to smooth the tracks to get a more reliable measure of the animal's movement path and remove the effect of outliers (caused by accidental wrong detection), random noise and body wobble. 1. Choose Acquisition > Track Smoothing Profile. Select Open and click OK. 2. Select one or more of the options: Smoothing (Lowess), Minimal Distance Moved and Maximum Distance Moved. For information on the smoothing options, see Smooth the Tracks in the EthoVision XT Help. Analysis Profiles Choose Analysis > Analysis Profile. Select New, name the analysis profile and click OK. Distance moved and Velocity are predefined as dependent variables. To add a variable to the Analysis profile, click the button next to that variable. note If you created the experiment from a template, it contains a few analysis profiles. For example, the Morris water maze template experiment with the platform zone template, contains four analysis profiles. One of them, Latency to reach platform, contains the variables for calculating the time taken to reach the platform. Basic Calculations Total distance moved or average velocity - Open the Analysis profile (see also the picture on the next page). - If the variable is not yet listed under Selected Dependent Variables, click the button next to Distance moved or Velocity. In the Trial Statistics tab, select Total for Distance moved, or Mean for Velocity. - Choose Analysis > Results > Statistics and Charts. Time in a zone and number of zone entries In step 2 above, click the button next to In zone. Specify the zone. In the Trial Statistics tab, select Cumulative duration and Frequency. Calculate the statistics Time before reaching a zone In step 2 on the previous page, click the button next to In zone. Specify the zone you are interested in. In the Trial Statistics tab, select Latency to first. Distance or velocity in a zone - Choose Analysis > Data Profile > New or open an existing Data profile. In the box Results click Settings, then select Results per zone. Next, choose the zones you want the results for. - Open an Analysis profile. Choose the variable you want to calculate. For example, Distance moved. Next, choose Analysis > Results > Statistics and Charts. Notes EthoVision XT offers a wide range of analysis variables and methods to select data. See Other analysis options (page 21). In the results screen, the Trial Statistics tab shows the analysis results per trial, while the Group Statistics & Charts tab shows the results for all trials together, or for the groups of trials defined in your Data profile. To modify the layout of the results table, click the Layout button. To carry out multiple calculations at once with different filters, data profiles or analysis profiles, click the Batch button. Visualize the data Visualize The Data Track Visualization Choose Analysis > Results > Plot Tracks to view the tracks that you selected. This allows you to visually compare tracks. You can play back your tracks to see how your subjects moved. To display the entire track, under Filter deselect the Last [ ] seconds option, then click the Jump to End button in the Playback Control window. Integrated Visualization Choose Analysis > Results > Plot Integrated Data to view the track with the corresponding video (when video was recorded) and the time plot of the dependent variables (velocity, etc.). To plot a variable: 1. Open an Analysis profile and add the dependent variable you want to view. 2. Choose Analysis > Results > Plot Integrated Data. Other analysis options Heatmaps Choose Analysis > Results > Plot Heatmaps and click Plot Heatmaps on the toolbar. With heatmaps you get an immediate impression of which area the animal spent most time in. Other Analysis Options Select And Group Tracks Choose Analysis > Data Profile > New. To analyze some tracks, not others - Choose one of the options under Filter. For example: Choose Trial Name and select the trials you want to analyze. Choose Dose (an independent variable previously defined; see page 15) and choose the values of the variable you want to use. - Insert the Filter box between Start and Result 1. To analyze tracks in groups For example, you want to compare the results for subjects treated with a drug with those for control subjects. 1. In the Trial List, make sure that the independent variable that you want to use for grouping is defined, and that each trial is labeled with one of the possible values (e.g. Treated vs. Control). 2. Make a Filter for the first group based one of the values of the independent variable, and place the resulting box between the Start and the Result 1 box (see above). Other analysis options 3. To create the second group, click the Result button under Common elements. Click and drag from the center of the Start box to the center of the new Result box. The two boxes are now connected with an arrow. Next, make a filter for the second group, and place the Filter box in the middle of the second branch. 4. Choose Analysis > Results > Statistics and Charts. Click the Group Statistics and Charts tab to view the results per group. Analyze Track Segments For instance, visualize the data of the first five minutes of the tracks, or visualize all samples when the subject was moving or grooming. Choose Analysis > Data Profile > New. Nesting To select track segments, based on time, zones or states of the subject, click the appropriate button under Nesting and specify the options there. For example, to analyze the first five minutes, choose Time. Insert the Nest box between Start and Result 1. Other analysis options Time bins To analyze the tracks split in regular time intervals, in the Result box click Settings and select Results per time bin. For example, define intervals of 1 minute each. Then, choose Analysis > Results > Statistics and Charts. For more information, see Analyze Track Segments in the EthoVision XT Help. Export data and results Export Data And Results Main Procedure To find out if your independent variables (like treatment, dose, etc.) have a significant effect on the dependent variables, you can export your data to a statistical package. To export the averages, totals etc. per trial, or per group of trials, choose Analysis > Export > Statistics. To export the raw x,y coordinates and the surface area of the subject, or the per-sample values of the dependent variables, choose Analysis > Export > Raw Data. For details, see File Management > Export data in the EthoVision XT Help. Copy Entire Experiments To make a copy of an entire experiment, choose File > Make Backup. Choose the options you require and select OK. The backup file (*.evz) contains all your settings and data, and optionally media files, exported files and physiological data. You can copy this file to another computer where EthoVision XT is installed. To open the experiment on that computer, choose File > Restore Backup. important Backup your data to a network drive or external hard disk at least once per day. For more information For More Information Help and other manuals For more details, in EthoVision XT, press F1 to open the Help. See also other manuals stored on your computer. On the Windows Start menu, choose All Apps > Noldus > EthoVision XT 18 Other Documentation. Sample experiments *Choose File > Restore Backup and browse to C:\Users\Public\Documents\Noldus* EthoVision XT\Experiments\Sample Experiments. You find the sample experiment Morris water maze test XT180.evz. For more sample experiments, browse to my.noldus.com. Log in or register using the code that you have received. Next, choose Downloads > EthoVision XT > Sample Experiments. Each experiment focuses on a specific apparatus, or on a feature of EthoVision XT, for example, trial control. Video tutorial Choose Help > Video Tutorial. Watch the tutorial to learn how to set up a video tracking study in EthoVision XT. There are also mini video tutorials available in several parts of the program. Click the video button on the tool bar to view the tutorials. Remote training courses Noldus offers training courses to help you get the most out of our software/hardware. In addition to on-site courses at your lab and in-house courses at our headquarters in Wageningen (The Netherlands) and Leesburg (VA, USA), we offer remote training courses. Remote trainings are available in the same range of languages as on-site courses. Please contact your sales representative for more information about remote trainings. Technical support If you encounter problems, see my.noldus.com to search the support knowledgebase or contact the help desk. Source: EthoVision XT 18 - Quick Start Guide --- ## EthoVision XT 18 - Application Manual - A Conditioning Test In Ethovision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-a-conditioning-test-in-ethovision Chapter: EthoVision XT A Conditioning Test in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. In the following sections we assume that you created an experiment using the PhenoTyper arena template. Experiment Settings - Make sure that the PhenoTyper cages are connected to the EthoVision XT PC. See the PhenoTyper - EthoVision XT 18 - Reference Manual for how to connect PhenoTyper to EthoVision XT. Connect a third-party hardware device, which can be controlled by TTL, to one of the TTL control ports on the USB-IO Box. - Open the experiment and choose Setup > Experiment Settings. - Check that the correct cameras are selected under Video source. Select whether the resolution of the first camera and that of the mixed image. Note that depending on the number of cameras and the frame rate, you may need to reduce the resolution of the mixed image. For more information about installing and connecting multiple cameras, see Camera installation in the EthoVision XT Help and the PhenoTyper - EthoVision XT 18 - Reference Manual. - If you want to use the Deep learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. - Under Analysis options, select Activity analysis if you want to measure freezing behavior. - Next to Hardware, select Use of Trial Control Hardware and click Settings. - Select Noldus USB-IO box. - In this next step, you define the ports of the USB-IO box connected to PhenoTypers. Select SDI port 13, then Top Unit Interface. Select Top Unit (Standard) for all the rows below (depending on how many PhenoTypers are connected to a Top Unit Interface). For PhenoTyper 2, and for more details and examples, see the PhenoTyper - EthoVision XT 18 - Reference Manual. If you use third-party devices, also select the TTL ports that are connected to those devices. - Click OK. For More Information - About port mapping: the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - About PhenoTyper connections and devices: - PhenoTyper - EthoVision XT 18 - Reference Manual - PhenoTyper - EthoVision XT 18 - Service Manual for specific devices like the Pellet dispenser and the Lickometer. - About general experiment settings: Set Up an Experiment in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > open Arena Settings 1. Click the Arena - Hardware Mapping button at the bottom of the Arena Settings pane. If you only have one arena, the hardware will be assigned to this arena automatically. If that is the case, proceed with Trial Control Settings. In the Arena - Hardware Mapping window, click Add Device for each device you want to add: - For PhenoTyper: Under Device Type, select Top Unit (Standard). Enter Device Name PhenoTyper and the corresponding Top Unit (Standard) # for each Arena. - For a third-party hardware device: Under Device Type, select Custom Hardware. Enter a Device name and select a device from the list for each Arena. Click 4. Validate Setup to validate the Arena Settings. Trial Control Settings With the Trial and Hardware Control add-on module in EthoVision XT, you can control PhenoTyper and third-party devices in a variety of ways. For example: - Start recording when the animal is detected on top of the shelter. - Stop recording when the animal has performed a specific task 50 times. - When the animal sits on the shelter, drop a food pellet. Repeat this task 25 times. The template experiment contains two trial control profiles: - Default – The default Trial Control Start-Stop rule. - Max. Trial duration 24 hrs – In this profile, a trial stops after 24 hours. Maximum trial duration (tested): - Without video recording: 72 hours. - With simultaneous video recording: 3 hours. If you need to record video of the same subject for more than three hours, we recommend that you make a series of trials. Below you find a few examples of Trial Control Settings. Modify the Trial Control Settings to suit your own application. Procedure Overview - The trial starts with a 30-second delay (see Start Trial Rule and Condition Start Delay below). - Next, as soon as the mouse enters the LightSpot zone, with both the nose- and center-point, the spotlight of the PhenoTyper is turned on. When both the nose- and center-point are not in the LightSpot zone, the spotlight is turned off. This sequence is repeated three times (see Sub-rule Activation LightSpot below). - After the Sub-rule is completed, the trial is stopped after a 5-second delay. Choose Setup > Trial Control Settings > New and give this a new name. Start Trial Rule - To start recording as soon as the Start trial button is clicked: - Click the (default) Condition In zone box and press Delete. - Keep this Condition if you want to start recording some time after starting the trial. Condition 'Start Delay' - To insert a 30-second delay after recording has started: - In the Components pane, under Conditions, double-click Time Condition or click the button next to it. - In the Time condition window, type Delay of 30 seconds in the Condition name field. In the Condition is met group, select After a time of 30 secs. Optionally, enter a comment and click OK. - Insert the Condition box into the main sequence. For more information about Conditions, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Sub-Rule 'Activation LightSpot' - Because the sequence of turning on/off the spotlight depending on whether the animal is inside/outside the Spot Light Zone is repeated three times, you need to create a Sub-rule for this: - In the Components pane, under Structures, double-click Sub-rule or click the button next to it. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - A Conditioning Test In Ethovision (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-a-conditioning-test-in-ethovision-continued Chapter: EthoVision XT A Conditioning Test in EthoVision (Continued) - In the Sub-rule window, type 'Anxiety Test' in the Sub-rule name field. Optionally, enter a comment and click OK. - Create an In Zone Condition for when the animal enters the Spot Light Zone: - In the Components pane, double-click the In zone Condition or click the button next to it. - In the In zone Condition window, type 'Inside LightSpot' in the Condition name field. - In the Condition is met when: group, from the Statistic list, select Frequency. Next, click the Settings button, select zone Spot Light from In the following zones, and select When in any of the selected zones from the list. In the From the following body points group, select both Nose-point and Center-point. Make sure to select All selected points from the list. - Click OK. - Insert the Condition box into the Sub-rule sequence. - Create a Hardware Action (White Light on) for when the previous Condition is met: - In the Components pane, under Actions - Hardware, double-click Top Unit (standard) or click the button next to it. If a third-party device has been connected, under Actions - Hardware double-click Custom Hardware. - Next to Action name, type "White Light on". - Next to Action to perform, select White spot on from the list and click OK. - Insert the Action box into the Sub-rule sequence. If a third-party device has been connected, select an action from the Custom Hardware. - Create an In Zone Condition for when the animal leaves the Zone LightSpot: - In the Components pane, double-click the In zone Condition or click the button next to it. - In the In zone Condition window, type 'Outside LightSpot' in the Condition name field. - In the Condition is met when: group, from the Statistic list, select Frequency. Next, click the Settings button, select zone Spot Light from In the following zones and select When not in any of the zones. In the From the following body points group, select both Nose-point and Center-point. Make sure to select All selected points from the list at the bottom. - Click OK. - Insert the Condition box into the Sub-rule sequence. - Create a Hardware Action (White spotlight off) for when the previous Condition is met: - In the Components pane, under Actions - Hardware, double-click Top Unit (standard) or click the button next to it. - Next to Action name, type White Light off. - Next to Action to perform, select White spot off from the list and click OK. - Insert the Action box into the Sub-rule sequence. If a third-party device has been connected, select an action from the Custom Hardware. The Sub-rule Anxiety Test is now completed. Sub-rule Reference 'Start Anxiety Test' - To create a Reference in the main sequence to the Sub-rule LightSpot: - In the Components pane, under Structures, double-click Sub-rule reference or click the button next to it. - Next to Reference name, type Start Anxiety Test. - Next to Reference to sub-rule, select Anxiety Test. - Next to Stop Conditions, select Repeat per start condition. Select for a number of ... times and set the value accordingly. - Click OK and insert the Reference box into the main sequence. Condition 'Stop Delay' - To insert a 5-second delay before the trial is stopped: - In the Components pane, under Conditions, double-click the Time Condition or click the button next to it. - If the Add a condition window appears, it means there is at least one condition of the same type in your experiment. You are asked to choose between creating a new condition or re-using an existing one. Choose the option you require and click OK. If this window does not appear, skip this step. - In the Time condition window, type 'After 5 seconds' in the Condition name field. In the Condition is met: group, select After a time of 5 secs. Optionally, enter a comment and click OK. - Insert the Condition box into the main sequence. For more information and examples: - About PhenoTyper: PhenoTyper - EthoVision XT 18 - Reference Manual. - About subrules, conditions and actions: EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Detection Settings Choose Setup > Detection Settings > open Detection Settings 1. - Check in the Video Section that the sample rate is set to: - Rats: 5 samples/second. - Mice: 12.5 samples/second. - Nose-tail tracking: 25–30 samples/second. - Under Method, choose your detection method and the contrast with the background. If you selected to use the Deep learning technique to track the subject's nose, next to Deep learning click Define and select a box around the subject. Make sure that the box includes the subject's nose and does not include objects of the same color as the subject. For details, see the EthoVision XT Help. - If you selected Activity analysis in the Experiment settings, open the Activity section in the Detection Settings pane. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold so that when the animal is completely still, those pixels should be almost completely absent. Leave the Compression artifacts filter off if you track live. Trial List Enter your independent variables such as rat ID, first or second phase of the experiment, treatment (drug vs. control), dose, duration of treatment, name of the experimenter, etc. You can pre-define all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them, and then paste the values into your Trial List. To carry out batch acquisition, plan your trials in the Trial list. Optionally select Arena Settings, Trial Control Settings, and Detection Settings. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - A Conditioning Test In Ethovision (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-a-conditioning-test-in-ethovision-continued-dwt Chapter: EthoVision XT Settings for Each Trial If you do not select these settings in the Trial list, the ones selected in the Acquisition settings pane (see next section) will be used for all trials. For data acquisition, see acquiring tracks on page 21. Other Conditioning Tests Figure 11.7 A Trial List with two planned trials. Each trial includes four arenas (four PhenoTypers combined with a quad unit). Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquire The Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquire-the-data-FgJ Chapter: EthoVision XT Acquire the Data Things to Check First Before starting one or more trials, it is useful to do some checks. Hardware - Check that all devices are properly connected according to the schemes in this manual. - Check that all devices are powered up. - Insert the conditioning cage in the cubicle as in the figure below. The cage fits between the two clear support angles attached to the IR light box. Test the Devices in EthoVision XT Choose Setup > Arena Settings. Open the Arena Settings you want to use. Click the Arena – Hardware Mapping button and test the devices. Run a Test Trial To check that the system works correctly, run a test trial with a basic Trial Control settings profile that contains actions and conditions. After data acquisition, in the Analysis profile under Hardware choose Hardware command and define the event you want to view, for example Device A, Output 1 High (=Light on). Choose Analysis > Results > Integrated Visualization and check whether the event occurred at the expected time. Acquire Data In EthoVision XT, choose Acquisition > Open Acquisition. Follow the general procedure described in the EthoVision XT Help. Browse to Acquire Data > Acquire one trial. Analyze the Data Basic Steps - Define the intervals you want to analyze. Choose Analysis > Data Profile > New. See Analyze Intervals below. If you want to calculate statistics for the whole duration of your trials, you can skip this step. - Choose Analysis > Analysis Profile > New. Choose the variables you want to analyze. For example, velocity, time in zone, or activity. See Dependent Variables below. - Choose Analysis > Results > Statistics and Charts to calculate statistics, or Integrated Visualization to view the video and the variable plotted against time. Analyze Events Add the following variables, if not already listed in the Analysis profile: - Activity state to analyze freezing events. For more information about Activity and Activity state, and how to set the thresholds to detect freezing, see the EthoVision XT Help. - Distance moved, and Movement to quantify locomotory behavior. - Hardware command especially to visualize events like Light On, Shock On, etc. together with the video and the tracks (Analysis > Results > Integrated Visualization). - Trial Control Event to visualize for example when a condition becomes true. Use this especially for testing purposes. Analyze Intervals Define the Intervals with the Nesting Function By default, the whole trial timeline is selected for analysis. However, you may want to select part of the timeline, for example to analyze the Activity variable only when the white light was on. To do so, in the Data profile define an interval based on the event "White Light On". - Choose Analysis > Data Profile > New. - Under Nesting, click the option corresponding to the type of interval you want. - Specify the interval and place the Nest box between the Start and Results box. Which Options Shall I Choose? To analyze the behavior of the subject when, for example, the white light was on, choose Trial Control State. In the window that appears, select the action that marks the start of the interval (e.g., Light On - becomes active), and the action that marks the end of the interval (Light Off - becomes active). If you want to analyze a complex interval, from A to B, where A and B are events of different type, for example, behavior and activation of a stimulus, choose Free interval. For example, select the time from the end of the shock (Shock Off - becomes active) and the first instance of freezing (detected using Activity or Activity state). You can also combine events with time. For example, select the 30 seconds interval immediately after the end of the Shock. From Trial Control - Action: Shock Off - becomes active to Time - Elapsed time: 30 s after start event. Visualize the Intervals Once you have defined the intervals for analysis, it is always a good idea to plot the data and check that the intervals defined in the previous steps are correct. - Choose Analysis > Results > Plot Integrated Data. - The data selected within the intervals is shown in full colors while the data outside the intervals is shown in dimmed colors. Check that the intervals defined correspond to the time segments that you want to analyze. If the intervals are defined correctly, proceed with the statistics calculation. Calculate the Statistics Choose Analysis > Results > Calculate Statistics and click the Calculate button. The results table shows the statistics of the dependent variables defined in the Analysis profile, within the intervals defined in the Data profile. For More Information - For details about the analysis variables, see Dependent Variables in Detail in the EthoVision XT Help (F1). - For more examples about analyzing intervals, see Analyze Track Segments in the EthoVision XT Help (F1). - For more examples of control of hardware devices and PhenoTyper, see the chapter Conditioning Tests in this manual. Technical Specifications Infrared Top Light and Controller For the technical specifications of the Fear Conditioning system, see the Instruction Manual FCS 46000.pdf that comes with that system. Noldus Device Numbers - Top light: UBIRT-001x - Controller: UBIRC-001x Voltage 24V (standard Noldus power supply) Current Consumption On max LED intensity: 220mA Light Wavelength 940nm Incorporated Camera 1280 x 1024 pixels at max 60 fps (30 fps is recommended) Dimensions (L x W x H) - Top light: 28.6 x 29.3 x 8.5 cm (11 17/64" x 11 17/32" x 3 11/32") - Controller: 8.0 x 4.0 x 4.2 cm (3 5/32" x 1 37/64" x 1 21/32") Weight - Top light: 860 g (30.3 oz) - Controller: 50 g (1.76 oz) Power Adapter - Type number: TRH70A240-01E13VI - Input: 100–240V, 1.5 A - Output: 24V, 3.0 A Tests - Introduction - Physical Setup - A Conditioning Test in EthoVision XT - Data Analysis Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquire The Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquire-the-data Chapter: EthoVision XT Acquire the Data Protocol Each test described in this manual has one or more specific protocols. See the chapter that applies. Important: Always record your video with EthoVision XT or MediaRecorder. Do not record video with Pylon Viewer or other software! The resulting video file may not be compatible with EthoVision XT. Acquire the Tracks Procedure - Check that you have selected the correct Video Source in the Experiment Settings. - Choose Acquisition > Open Acquisition. - Optional: Skip this step if you have entered the values of the independent variables already in the Trial List. Open the Independent Variables tab of the Analysis Results and Scoring pane at the bottom of your screen and enter the values of the independent variables. You can also do this during acquisition. - If you did not plan any trials in the Trial List, click the New Trial button in the Playback Control window (Ctrl+F3). - If you planned two or more trials, select in the Acquisition Settings window whether you want to track only the next planned trial, or all planned trials. If you carry out batch acquisition and track live, also specify the Inter-trial interval. - Optional: In the Acquisition Settings window, select Auto-start data analysis. Do this to start calculation of analysis results immediately after acquisition. If you choose this option, first create an Analysis profile and optionally a Data profile and a Track Smoothing profile. Choose whether to carry out analysis only for the profiles highlighted in blue in the Experiment Explorer, or for all possible profile combinations. In the latter case, first delete all profiles you do not need for analysis. - Start the trial by choosing Acquisition > Start Trial, clicking the Start Trial button in the Playback Control window, or pressing Ctrl+F5. - If you do live tracking, release the animal in the arena. - Data acquisition starts when the Start track condition in your Trial Control Settings becomes true. - The trial stops automatically when the Stop track condition specified in the Trial Control Settings becomes true, or when the time defined under Maximum Trial Duration has expired. If you planned a series of trials, the next trial will start. To stop the trial manually, choose Acquisition > Stop Trial, click the Stop Trial button in the Playback Control window, or press Ctrl+F6. If you chose to simultaneously record a video file, the video file that has been created is stored on your PC in the Media Files folder of your experiment. After Testing After each test, remove any debris (bedding, feces, etc.) from the arena and clean all interior surfaces, walls and floor thoroughly, first using water and soap, or a perspex cleaner, then with water. Allow at least 5 minutes between tests to ensure that any residual odor will have dissipated before the next animals are introduced into the test apparatus. Do not use wet ethylene oxide, steam, strong acids, hydrocarbons, ethanol, methanol, or solvents containing acetone. Table 1: Acceptable techniques and substances for cleaning acrylic (perspex): - Electronic beam - High intensity visible light - Gamma radiation - Alkaline substances (in low concentrations) - Ethylene oxide gas - Low-temperature hydrogen peroxide gas plasma - Hydrogen peroxide (up to 3%) - Diluted solutions of isopropyl alcohol - UV radiation Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquiring-data-u1C Chapter: EthoVision XT Acquiring Data Protocol A typical NOR test consists of three phases: - Acclimation. The animal is placed in an empty arena for 10 minutes to habituate to the environment. Tracking in this phase is optional. After 10 minutes, the animal is taken out of the arena and is put back in its home cage. - T1. After 15 minutes in the home cage, the animal is put back in the arena in which two identical objects have been placed. The animal is put at a position midway between the objects and such that its nose points towards the wall. The animal is tracked for 3 minutes and is then taken out of the arena and put back in its home cage. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T1. - T2. One of the objects in the open field is replaced with a novel object (sometimes the other object is also replaced with an identical one) and the animal is put in the arena again. Tracking is done for 3 minutes. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T2. Score Behaviors Manually To score sniffing and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you find the key codes and the buttons for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen. Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. You can also score behaviors after tracking. See Acquire Data > Score Behaviors Manually in the EthoVision XT Help. Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open MDM Filter 2 mm. In this profile, the Minimal Distance Moved filter is used (option set to Direct, with a threshold of 2 mm). When the animal sits still, the body points may still move slightly due to system noise. This results in an overestimation of, for example, the total distance moved. With the minimal distance moved filter, you measure the total distance moved over the time periods in which the animal was really walking. Adjust the threshold if necessary, based on your setup and sample rate. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score Behaviors Manually. For details, see Score Behaviors Manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select (Filter) your tracks according to your independent variable values (for example, Treated animals only) and also select parts of tracks (Nesting). You can create groups of tracks to obtain group statistics for each group by using Filters to compare Novel Object and Familiar Object trials. Analysis Profiles The template experiment contains four analysis profiles: - Touching Objects. This analysis profile contains an In zone variable Nose touching objects to calculate the frequency, duration, and latency of when the nose-point of the animal touches the objects. The variable Distance to objects is used to calculate the mean and standard error of the animal's nose-point to the objects. The manually-scored behavior Sniffing object calculates the frequency and duration, with standard errors, of the instances when you scored Sniffing object during the trials. - In Halves. In this analysis profile, the In zone variable In Halves is used to calculate the frequency, duration and latency of when the center-point of the animal was in either half of the arena. - Head Directed to Zone. This analysis profile contains two Head directed to zone variables, one for the novel object and one for the familiar object. For each object, the center plus a 0.10 cm radius is used as the Point of interest. The frequency and duration for Head direction to zone is calculated when the nose-point is in the zone of the corresponding object. - Distance & Time. With the variables Distance Moved and Velocity, the total distance moved and the mean velocity are calculated. All analysis profiles also contain settings to calculate the group mean and standard errors of the statistics for trial groups. Exploratory Behavior You can quantify exploratory behavior with the analysis profiles described above, or you can create your own analysis profiles. There is usually variation between subjects in the time spent exploring an object. To account for this variation, you can select the part of each track up to when the animal explored an object for a specific time, and then analyze the behavior of the subject in that part. To do so, use the Free Interval function in the Data profile. - Choose Analysis > Data Profile > New. - Under Nesting, click the button next to Free Interval. - Select the following: - As a Start criterion: Time (select Track start). - As a Stop criterion: Dependent variable. Select the variable In zone, and the statistic Cumulative duration. In the settings, specify which zone the animal explored, and with which body point (for example, Novel object, nose point). Set the total exploration time. - Click OK and insert the resulting box as shown in the figure. - In the Analysis profile, choose the endpoints (distance moved, time spent in zones, etc.). - Choose Analysis > Results > Statistics and Charts. The results are calculated for the time until exploration reaches the duration specified. For more examples, see Free Interval in the EthoVision XT Help. Heatmaps Heatmaps facilitate identification of "hotspots" and clustering of data points. Choose Analysis > Results > Plot Heatmaps. Next, click Plot Heatmaps on the toolbar. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquiring-data-m7c Chapter: EthoVision XT Acquiring Data Protocol The subject is placed at the junction of the four arms of the maze, facing an open arm. Each subject is generally tested once for 5 minutes. For extensive protocol information, see Walf, A.A. & Frye C.A. (2007). The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nature Protocols (2): 322-328. doi:10.1038/nprot.2007.44 See also acquiring tracks on page 21. Score Behaviors Manually To score head dipping and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you find the key codes for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen. Notes - Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquiring-data-xEh Chapter: EthoVision XT Acquiring Data Protocol In a typical water maze test, an animal is put in the maze at a predefined position at the rim of the pool, facing the wall. Lower the animal gently into the water (e.g. in a paper cup), avoiding stress as much as possible. Before you start data acquisition, make sure the appropriate arena settings profile, depending on the starting location of the animal, is selected in the Acquisition Settings window. Training Trials In training trials, the animal starts swimming and the trial stops when the animal has found the platform or when the maximum trial duration has been reached. Probe Trials After the training trials, a probe trial is conducted in which the escape platform is removed from the pool and the animal allowed to swim for 60 sec. Thus typically each animal is tested n times (training) + 1 time (probe). Each test corresponds to a trial in EthoVision XT. Reversal Training Trials In reversal learning tasks, after one location has been thoroughly trained, the platform is moved to a different quadrant of the pool. Because it is hidden, it is not apparent that anything has changed until the animal fails to find the platform in its usual place. The focus is on how the animal reacts to this change and how quickly it learns the new location. In EthoVision XT, mark different types of trials with an independent variable in the Trial List. For example: - Type with values Training and Probe - Platform Position with values SouthWest, NorthWest, etc. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquiring-data Chapter: EthoVision XT Acquiring Data Protocol A typical open field test is carried out in the following way: - Transport the subject to the testing room at least 1 hr. prior to testing, to allow them to acclimate to the experimental room. This time period should be extended if the transfer involves excessive changes in the environment. - Clean the open field, even if it is not dirty prior to the initial trial. This way all animals experience the residual smell of the disinfectant equally. - In EthoVision XT, click the Start Trial button. EthoVision XT waits until the subject is detected in the arena. - Place the subject in the open field. Commonly, the subject is placed in the center. However, placing adjacent to a wall is sometimes used to avoid immediate exposure to a stressful situation. Also, in case of a large open field, the position adjacent to the wall may be easier to reach. - The researcher should leave the room, or position himself or herself as far as possible away from the arena and field of view of the subject. Also the tester should remain quiet throughout each trial. - Tracking starts after the subject is detected in the arena. Make sure that tracking does not start because your arm is detected instead of the animal. To do so, for example, make a door in the open field, or increase the period that the subject needs to be detected before tracking starts. If you use multiple arenas, tracking starts in each arena separately, depending on when the subject is detected in that arena. The subject is allowed to explore freely for a standardized time. Traditionally track duration was between 2 and 10 minutes, but video tracking with EthoVision XT allows longer tracking. - After the test has ended, take the subject out of the arena and put it back in its home cage. - Optionally, count the fecal boli in each zone of the open field. - Clean the open field and allow it to fully dry prior to introducing the next test subject. Notes - Tip: When tracking white animals, wear dark clothes, and when tracking dark animals, wear white clothes. This prevents EthoVision XT from detecting your arms while you release the animals in the arena. Score Behaviors Manually Once you have defined your behaviors of interest in the Manual Scoring Settings, you can score those behaviors in two ways: - Live: That is, during the test. On the Acquisition screen, click the Manual Scoring tab and score behaviors when these occur. - Offline: If you have recorded video, choose Acquisition > Manual Scoring. Review the video and add or edit behavior scores. For more information, see Acquire Data > Score Behaviors Manually in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquiring-data-yqV Chapter: EthoVision XT Acquiring Data Protocol The following protocol tests for basic working memory (the subject learns not to re-enter a baited arm). Habituation (Pre-Training) In a typical radial 8-arm maze test, first a pre-training session is carried out in which the animal is allowed to freely visit all arms for 10 to 15 minutes per day. Also, the doors are regularly opened and closed to habituate the animal. Training Trials In this phase, the animal is exposed to where the food is, and this is what the later tested memory is based on. Animals are trained one session per day, for approx. one week. Typically, all arms are baited in this phase. At the start of the trial, the animal is placed in the center of the maze, facing the same direction on every trial, everyday. Stop the trial when: - All eight arms have been visited - 10 minutes have passed since the start of the trial - 2 minutes have passed since the animal's last arm entry Performance Among the variables commonly used for the analysis of performance are: - The number of errors in each session (entering an arm that has been visited previously counted as an error) and the total number of errors across eight sessions - The number of correct choices in the first eight arm entries of each session Reference Memory Errors While the previous protocol is primarily sensitive to impairments in working memory, an alternate protocol allows a disassociation to be achieved between working and reference types of memory. In this protocol, four arms are baited for the training phase. The same maze arms are baited each day and, across sessions, the animal learns to ignore the other arms, which never contain a reward. This is the reference memory component of the task. In the test phase, food items are placed in the same arms as they were on the memory trials that day. It is recorded when the animal gets 100% correct on his memory trials. When the animal enters an arm that is not baited, it is marked as an error. Reference: Wenk, G.L. (2004). Current Protocols in Neuroscience, 8.5A.1-8.5A.12. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-acquiring-data-JtZ Chapter: EthoVision XT Acquiring Data Protocol Basic Protocol (Rats) Pre-test trial (day 1, before drug administration): The animal is placed in the cylinder for 15 minutes. No scoring of immobility is performed during the first session. This session is needed to acclimatize the rats to the experimental situation and to induce a stable, high level of immobility during the test session. Test (day 2): After drug administration, the animal is placed in the cylinder for 5 minutes. Score the duration of immobility by summing the time spent immobile; score as immobile minor movements strictly necessary to maintain the animal's head above water. Alternate Protocol (Mice) The mouse is placed in the cylinder. The trial lasts 6 minutes. Measure the latency to immobility from the start of the trial and the duration of immobility for the last 4 minutes. See Castagné et al. (2011). Current Protocols in Neuroscience 8.10A.1-8.10A.14. Score Behaviors Manually If you want to score the subject's behavior manually, define them first under Manual Scoring Settings. After you have started the trial, watch the subjects in the video and in the Manual Scoring tab at the bottom of the screen, click the button to the category that applies. As soon as the behavior of the subject changes, click the button for the corresponding category. Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. You can also score behaviors after tracking. See Acquire Data > Score Behaviors Manually in the EthoVision XT Help. Determining Mobility Thresholds To find the optimal Highly mobile and Immobile thresholds, you can run a few test trials and check in the Analysis Results and Scoring pane (Dependent Variables tab) the values for Mobility state in relation to the behavior the animal displays. If the Mobility states do not correspond to the behavior of the animal, in the Analysis Results and Scoring pane: - Click Dependent Variables. - Click the button under Mobility state. - Adjust the Highly mobile threshold and Immobile threshold. For example, if the animal is struggling, its corresponding Mobility state is Highly mobile. If the current Mobility score is Mobile or Immobile, you probably need to reduce the Highly mobile threshold. Note that you can also adjust the Mobility thresholds after acquisition. In the Analysis profile, add the Mobility state variable and visualize the data. If you do not see the Mobility state variable on your screen, click Show/Hide on the toolbar and select Show Dependent Variables, then Mobility state and Mobility. Determining Activity Thresholds In the same way as you defined thresholds for Mobility state, you can define thresholds for Activity state. Use Activity state if Mobility state does not give satisfying results, for instance when detecting thrashing of the animal's limbs which may not be detected properly by Mobility. Note that when you work with multiple cylinders in the same video image, Activity state gives good results when the size of the arena is the same for all cylinders. In the Arena Settings, adjust the contour of the arenas to make them similar. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Advanced Applications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-advanced-applications Chapter: EthoVision XT Differential Stimulation Depending on Zone Aim To give a pulse sequence with frequency fA when the subject is in zone A, and a pulse sequence with a frequency fB when the subject is in zone B. Prerequisites In the Arena Settings, you have defined two non-adjacent zones, A and B. Procedure - Create new Trial Control Settings. - In the main Trial Control procedure, right after the Start Trial box, define an External command box to initialize the port for the Pulser. - Add a Time condition and set it to 2 seconds. - Add one External command, to the program C:\Windows\System32\cmd.exe with the line options: /C echo S>com[port number] (for example, /C echo S>com3). This instruction cancels the current pulse sequence definition stored in the Pulser in case you have used other definitions in a previous trial. - Add one Hardware command to set Output 1 to Low. - Create two Subrules, one for zone A and the other for zone B. In the main Trial Control sequence, after the Start track box, insert the two reference boxes. For both Reference boxes, select Repeat indefinitely. - In each Subrule, define the following instructions as described in the notes below. Subrule Instructions Each Subrule contains the following action boxes: - Box a: In Zone Condition — Is the animal in zone A (or B)? (Current = true) - Box b: Time Condition — Wait 1 second. - Box c: External command — Define the pulse sequence. - Box d: Custom Hardware Action — Set Output 1 High. - Box e: In Zone Condition — Is the animal NOT in the zone? (Current = true) - Box f: Custom Hardware Action — Set Output 1 Low. - Box g: External command to C:\Windows\System32\cmd.exe with line option /C echo S>com[port number] — stops the pulse sequence definition and ensures the Pulser listens to the next definition when the subject enters the other zone. These instructions check that the animal is in a particular zone (a). If it is, after one second (b) the corresponding pulse sequence is defined (c) and the Pulser is triggered (d). When the animal leaves the zone (e), stimulation stops (f) and the sequence definition is canceled (g). If the animal enters the other zone, the instructions in the other Subrule after (b) will be executed and the corresponding stimulation starts. Notes - Important: Do not use zones that are adjacent; always leave some space between the two zones. - The 1-second Time condition (box b) has been inserted in both Subrules to ensure that there is enough time between the reset of the Pulser port at the end of one Subrule (box g) and the new pulse sequence definition in the other Subrule (box c) when the animal switches from one zone to the other. - You need as many Subrules as there are trigger zones. Multiple Simultaneous Stimulations in One Arena Aim To generate different pulse sequences and send them simultaneously to different subjects in one arena. Note: Using multiple Pulsers is necessary when stimulation in two or more subjects can occur at the same time. Basic Steps - Install the driver for the Pulser on the EthoVision XT computer. - Configure the driver for a specific Pulser (COM port). When connecting multiple Pulsers to the EthoVision XT computer, the Device Manager shows multiple instances of Prizmatix DVR (COM[n]) or USB Serial Port (COM[n]). Repeat this procedure for each instance. - Connect the Trig. In port of each Pulser/PulserPlus device to a TTL port of the USB-IO box. - In EthoVision XT (Experiment Settings), assign a TTL port to Pulser 1, another TTL port to Pulser 2, and so on. Tip: Rename the Device IDs to something descriptive, such as Pulser 1 and Pulser 2. - In EthoVision XT (Arena Settings), click the Arena-Hardware Mapping button. Add two devices and assign them to the arena. - In EthoVision XT (Trial Control Settings), for each Pulser, initialize the COM port and define the pulse sequence. Repeat this procedure for each Pulser. Details For each Pulser, define three External command Action boxes in a linear sequence before the Start track box: - One for initializing the port (Procedure 1 - Initialize the COM port) - One for stopping previous definitions (for example, from a previous trial) - One for defining the pulse sequence (Procedure 2 - Define the pulse sequence) In this example: - Pulser 1 is set to a pulse sequence of 20 ms on and 20 ms off (25 Hz stimulation; boxes A for initialization and C for pulse definition). - Pulser 2 is set to a pulse sequence of 10 ms on and 10 ms off (50 Hz stimulation; boxes D and E). Note that actions are separated by Time conditions of 1–2 seconds. Complete your Trial Control procedure to the right of the Start track box. In this example, the Subrule triggers the Pulser for 1 second of stimulation with an interval of 5 seconds. Notes - Different protocols must be defined with different Subrules. For example, create Subrule 1 for controlling Pulser 1 and Subrule 2 for controlling Pulser 2. - Tip: When using multiple Pulsers, it is convenient to use batch files. For example, the instructions for stopping sequence definitions for com3 and com5 would be: - echo S>com3 - echo S>com5 Enter these instructions in a text file and rename it with the extension .cmd. Then, instead of single instructions, create an External command pointing to this .cmd file. - Important: Test the system thoroughly before running real experiments. When using multiple Pulsers, more time may be needed to initialize the ports. If the Pulser does not respond, the 2-second waiting time may not be sufficient. Set a longer time, such as 5 seconds, if needed. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Advanced Applications (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-advanced-applications-continued Chapter: EthoVision XT Simultaneous Stimulations in Two or More Arenas When you run a trial with multiple arenas, EthoVision XT controls multiple pulsers, each assigned to a specific arena. This is only possible with the aid of batch files (see below). Why Are Batch Files Needed? A batch file is necessary to send commands for initializing the COM port and define the pulse sequence for a specific arena. The reason for this is that the Trial Control rules are applied to each arena independently, but the External commands specified in those boxes are not arena-specific. You can imagine two identical copies of the picture of the previous page, one for each arena. This means that an external command would be sent twice to the same COM port, which may result in unexpected behavior. To prevent this from happening, a batch file is needed that sends the command lines based on the name of the arena. You need two batch files, one (Initialize COM ports.cmd) for initializing the COM port, and one for defining the pulse sequences (Define sequences.cmd). The two batch files are activated one after the other, with a time interval in between. A third batch file (Stop sequences.cmd) stops the definition of sequences previously used, and is handy when you use different sequences in the same trial or between subsequent trials. Note: If you do not have those batch files, please contact Noldus IT, or follow the instructions below. To Create the Batch File "Initialize COM Ports" - Open the Windows Notepad and enter the following (here we assume that four arenas are used, with COM ports 3, 4, 5 and 6): @echo off set arena=%1 set arena=%arena:~2,-2% If "%arena%"=="Arena 1" C:\Windows\System32\cmd.exe /C mode COM3 BAUD=57600 PARITY=N DATA=8 STOP=1 DTR=off RTS=off If "%arena%"=="Arena 2" C:\Windows\System32\cmd.exe /C mode COM4 BAUD=57600 PARITY=N DATA=8 STOP=1 DTR=off RTS=off If "%arena%"=="Arena 3" C:\Windows\System32\cmd.exe /C mode COM5 BAUD=57600 PARITY=N DATA=8 STOP=1 DTR=off RTS=off If "%arena%"=="Arena 4" C:\Windows\System32\cmd.exe /C mode COM6 BAUD=57600 PARITY=N DATA=8 STOP=1 DTR=off RTS=off - Save the file, and give it the extension .cmd. Important: Make sure that "Arena 1", "Arena 2" etc. are the exact name of the arenas in the Arena Settings. Make sure to avoid leading or trailing spaces in the names. Note that this differs from that in EthoVision XT 17 and earlier versions. Also, make sure to enter the correct COM port number of your Pulsers. To Create the Batch File "Define Sequences" - Open the Windows Notepad and enter the following: @echo off set arena=%1 set arena=%arena:~2,-2% If "%arena%"=="Arena 1" C:\Windows\System32\cmd.exe /C echo M1,0,500,500,0,0,1,1,103,1,0,0,0,0@>com3 If "%arena%"=="Arena 2" C:\Windows\System32\cmd.exe /C echo M1,0,500,500,0,0,1,1,103,1,0,0,0,0@>com4 If "%arena%"=="Arena 3" C:\Windows\System32\cmd.exe /C echo M1,0,500,500,0,0,1,1,103,1,0,0,0,0@>com5 If "%arena%"=="Arena 4" C:\Windows\System32\cmd.exe /C echo M1,0,500,500,0,0,1,1,103,1,0,0,0,0@>com6 The example above would produce a sequence of 500 ms pulses (frequency 1 Hz). Replace the 500 with the pulse durations and intervals you require. - Save the file, and give it the extension .cmd. To Create the Batch File "Stop Sequences" - Open the Windows Notepad and enter the following: echo S>com3 echo S>com4 echo S>com6 echo S>com7 Replace the port number with those assigned to your Pulsers. - Save the file, and give it the extension .cmd. Basic Steps - Follow steps 1 to 4 as described in the initial setup procedure. Tip: Rename the Device IDs to, for example, Pulser 1 and Pulser 2. - Important: In EthoVision XT (Arena Settings), make sure that the name of the arenas is Arena 1, Arena 2, etc. - In EthoVision XT (Arena Settings), click the Arena-Hardware Mapping button. Add two devices, and assign each pulser to only one arena. Important: Make sure that is selected in the remaining cells under Arena 1, Arena 2, etc. - In the Trial Control Settings, define the following boxes and insert them between the Start Trial and the Start Track box: - An External command for the first batch file, Initialize.cmd. Enter %an% in the Command line options. - A time condition, set to two seconds. - An External command for the batch file Stop sequences.cmd. Command line options are not necessary. - A time condition, set to two seconds. - An External command for the second batch file, Sequence.cmd. Enter %an% in the Command line options. - Complete your Trial Control procedure to the right of the Start Track box. Different protocols must be defined with different Subrules. For example, create a Subrule 1 for controlling Pulser 1, and a Subrule 2 for controlling Pulser 2. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Aligning Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-aligning-data Chapter: EthoVision XT Aligning Data To align the data streams from EthoVision XT and Inscopix nVista/nVoke, there are two solutions: - Have EthoVision XT send a time code signal (TCAP). - Have EthoVision XT send a sequence of TTL pulses. Either way, the Inscopix system records the signal in one of its channels. The difference between the two is that with TCAP you need to export the TCAP signal that is stored in Inscopix back to EthoVision XT, together with the Inscopix data, so that EthoVision XT reads the time code and aligns the Inscopix data with the tracks. Note: The nVista/nVoke system can also send a sync pulse to EthoVision XT through the USB-IO box every time a video frame is recorded. However, the pulse generated from the SYNC port of nVista/nVoke has a duration of 10 ms. That is too little for EthoVision XT to detect and record the signal. Therefore, this solution is not optimal to sync the two data streams. Using the TCAP Signal Prerequisites For this solution you need: - The External Data add-on module for EthoVision XT. Contact Noldus if you need to purchase it. - An interface cable between EthoVision XT and the BNC connector of the nVista/nVoke DAQ box. Contact Noldus to have one made for you. - A way to convert the Inscopix data to a format compatible with EthoVision XT: fixed sample rate, without gaps. Procedure - Set the TCAP signal in the Experiment Settings of EthoVision XT, and specify the sample rate of the Inscopix channel that will receive that signal. - Start acquisition in Inscopix and then start the trial in EthoVision XT. nVoke/nVista records the TCAP signal, which should be visualized on the system's screen. - Export the Inscopix data to text files. Note that here the sample rate must be fixed and all samples must be written in the file, otherwise import won't work. - After import, EthoVision shows the TCAP signal and other Inscopix data together with the track data. For more information, see External Data in the EthoVision XT Help. Using a TTL Signal Connections Connect a TTL port of the USB/IO box to one of the GPIO ports of the Inscopix DAQ box. For this you need a cable with a RJ45 connector at one end and a BNC connector at the other end. Procedure - In the Experiment Settings in EthoVision XT, define a TTL port of the USB-IO box. Select Custom Hardware from the list. In the Arena Settings, map that TTL port to one of the arenas. - In the Trial Control Settings, add a subrule that activates the TTL port every few seconds. For example: TTL Output 1 High for 1 second, then TTL Output 1 Low for 4 seconds. Let the subrule repeat a number of times or when a Trial Control variable reaches a specific value. In general, make sure that the ON-OFF sequence runs through the duration of the trial. Tip: To stop the subrule at the end of the trial, add an Action box immediately before the Stop Trial box, where a Trial Control Variable (for example END) gets the value 1. In the Subrule reference, specify to end the subrule when END = 1. - Run a test trial and make sure that Inscopix records the signal coming to the GPIO port. - Visualize the data in both systems. In EthoVision XT, you can visualize the TTL signal by selecting, for example, Trial Control State in the Analysis profile and defining the state from the action Output 1 High to the action Output 1 Low (the numbering depends on which TTL line you use). - If the data are well aligned, the time between the first and the last pulse should be the same in EthoVision XT and Inscopix, or differ by a few milliseconds. For More Information - The nVista/nVoke User Manual. - The EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Mark EthoVision Events on the Calcium Imaging Timeline You can also use the GPIO ports on the nVoke/nVista box to send specific events to the Calcium Imaging software. In the following example, a setup that includes a fear conditioning system, all GPIO ports are set to digital and work as inputs: - GPIO-1 receives a signal from a TTL port of the USB-IO box that is set to high when tracking starts. - GPIO-2 receives a signal from a TTL port of the USB-IO box that is set to high when a 5-kHz tone is given. - GPIO-3 receives a signal from a TTL port of the USB-IO box that is set to high when a 15-kHz tone is given. - GPIO-4 receives a signal from a TTL port of the USB-IO box that is set to high or low when the optogenetic stimulation is given/stopped, respectively, or when a shock is given/stopped, respectively. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Analyze The Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-analyze-the-data Chapter: EthoVision XT Analyze the Data Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you do not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile. Select one or both options to remove noise and artifacts due to for example body wobbling. For more information, see Smooth the Tracks in the EthoVision XT Help. Select Data for Analysis Choose Analysis > Data Profile. The data you select on this screen will be analyzed or visualized. - Analyze data per zone: In the Result box, click Settings and select Results per zone. Use this function for example to analyze the velocity of the subject in the different zones. - Analyze some tracks, not others: Under Filter, choose one of the variables available. For example, Treatment to analyze Treated animals only. Insert the box in the Data profile sequence. - Analyze segments based on behavior: Under Nesting, choose one of the options. For example, to select all data points when the subject was moving, choose Movement. Insert the box in the Data profile sequence. - Analyze tracks split in equal duration segments: In the Result box, click Settings and select Time bins. Use this function for example to analyze a 10-minute recording in ten segments of one minute each. - Create groups of tracks and compare results: Under Common Elements, click Result and add a Result box. You can link each Result box with a specific Filter. This way you can compare the results of different selections, or visualize groups of tracks that result from different treatments, etc. For more information, see the EthoVision XT Help. Visualize the Data You can visualize your tracks in three ways: Plot the Tracks Choose Analysis > Results > Plot Tracks. You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals treated with saline and red for drug-treated animals). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast. To set the track colors, in the Track Plot Settings pane, click the Colors tab. Plot Integrated Data Choose Analysis > Results > Plot Integrated Data. Look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Just like with plotting tracks, you can show tracks or sample points in different colors. Plot Heatmaps Choose Analysis > Results > Plot Heatmaps. Make heatmaps of the location of your animals during the tracks. For more information, see Visualize Data in the EthoVision XT Help. Calculate the Statistics General Procedure - Choose Analysis > Analysis Profile > New. Select the variables you are interested in. For information about the variables suggested, see the chapter about the test of your choice and the EthoVision XT Help. - Choose Analysis > Results > Statistics & Charts, then click Calculate. The Trial Statistics tab shows the results per trial. The Group Statistics tab shows the statistics and charts from the results over all trials or the groups defined in your Data profile. Adjust the Table Layout (Optional) Sometimes you need to adjust the layout of your results table, for example to export the results to a statistics software. Click the Layout button on the toolbar and specify which headers should be on the rows and which on the columns. For details and examples, search for table layout in the EthoVision XT Help. Batch Calculations It is also possible to carry out multiple calculations at once with different filters, data profiles or analysis profiles. To do so: - In the Statistics & Charts window, click Batch. - Select the profiles from the lists and click Add. - Repeat the previous step for other combinations. - Click Calculate. Choose the profiles from the lists on the toolbar to view the analysis result for that combination. For more information, see Calculate Statistics in the EthoVision XT Help. Advanced Analysis with JavaScript Custom Variables In the Analysis profile you can create fully custom dependent variables with JavaScript code. With JavaScript you have an almost endless range of possibilities to extract information from your tracks. JavaScript variables can be of type continuous, event, or state. See JavaScript in the EthoVision XT Help. Note: If you are not familiar with programming, Noldus can create custom analysis variables for you. Please contact Noldus for information. Export the Results To find out if your independent variables (like treatment, dose, etc.) have a significant effect on the dependent variables, you can export your data to a statistical package. - Choose Analysis > Export > Statistics. - Choose Trial Statistics or Group Statistics. You can also export the raw track data. Choose Analysis > Export > Raw Data. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Basic Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-basic-settings Chapter: EthoVision XT Basic Settings EthoVision XT: Experiment Settings After creating a new experiment, choose Setup > Experiment Settings. Define the number of arenas, the features that you want to track, and the camera properties. To define the Inscopix devices: - Select Use of Trial Control Hardware, and click the Settings button. - Depending on the type of USB-IO box you use, choose either Noldus USB-IO box or Noldus Mini USB-IO box. - Locate the TTL port that you use to connect the USB-IO box, and from the Device Type list choose Custom Hardware. - Under Device ID, enter a name for the device. For example, nVista Video, nVoke Video, or nVoke LED. - Repeat the steps above to declare more devices. If you want to trigger Calcium Imaging and LED stimulation, you must use two TTL ports from the USB-IO box, one for the TRIG input and one for the GPIO[n] input of the nVoke device. - Click OK. Next, open the Arena Settings (see below). EthoVision XT: Arena Settings Choose Setup > Arena Settings. Calibrate and define the outline of the arena(s) and the zones. To map the Inscopix devices to the arena(s): - Click the Arena - Hardware Mapping button at the bottom-right corner of the screen. - Check that the device appears under the arena name. In the case of multiple devices, assign each of them to one arena and make sure that they do not occur in the cells for other arenas. - Optionally, edit the Device Name (default: Device A, B, etc.). This name will appear in the Trial Control Settings and in the Analysis profile. - Repeat steps 2–3 to map the remaining devices. Inscopix Devices - Connect the microscope to the subject and pass the cord through the tracking chamber/PhenoTyper and connect it to the Inscopix device. - On the Inscopix computer, launch the data acquisition software and adjust the imaging settings, such as the frame rate and the gain. - In the data acquisition software, select to trigger from external hardware. If you are doing Calcium Imaging only, you can use the Basic Recording mode in the Inscopix software. Make sure that the Recording Start mode is set to Triggered Recording. - When using optogenetics stimulation, in most cases you must use the Advanced Recording mode. Specify the type of stimulation, power, number of repeats, etc. See also the nVista and nVoke User Manual for examples. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Carrying Out Your Trials URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-carrying-out-your-trials Chapter: EthoVision XT Carrying Out Your Trials Protocol Animals In many social interaction experiments, two animals from the same treatment group are tested together and scored as a single unit. According to Lapiz-Bluhm et al. (2008), this potentially can result in an artificial exaggeration of behavioral effects, that is, a treatment that only slightly impacts social behavior may have an apparently larger and more significant effect if the social behavior of both animals is affected. Their alternative approach tests an experimental animal paired with a 'neutral' stimulus animal, whose behavior is as constant as possible. See The Sociability Cage Test on page 107. Habituation The experimental animals are gently handled for 2 minutes on each of 3 days prior to the social interaction test. In addition, they are individually familiarized with the testing room and social interaction arena for 5 minutes on the 3 days prior to testing. The stimulus animals are habituated to the testing room and arena for 5 minutes per day for 3 days prior to testing. The stimulus animals are pre-exposed to the test arena in pairs, with a different, unfamiliar other stimulus animal on each pre-exposure day. When Using Color Marks To control for the effect that the color of the marker might have on the behavior of the other animal, it is recommended to randomly assign the marker color to stimulus and experimental animals. To take into account the combinations of animal type and marker color, you can either add a user-defined variable like Marker color to the Trial List or define two Detection Settings, one for each combination. In the latter case, make sure you set the appropriate Detection Setting as current before you start data acquisition. Social Memory Test (1-Min Confrontation) - Let the focal animal establish a home-cage territory (e.g. 5 days). - Introduce the stimulus female into the home cage of a male mouse for a 1-min interaction. At the end of the 1-min trial, remove the stimulus animal. - Repeat step 2 a number of times, with a 10-min inter-exposure interval. - "Dishabituation" trial: Introduce a different stimulus female to the same male mouse for one minute. In EthoVision XT - If you use color markers, alternate different colors for the same subject (e.g. half resident mice marked orange, half marked green). - If you use different colors for the resident animal, make different detection settings in such a way that Subject 1 is always the resident animal. Before acquisition, make sure that you use the detection settings that apply to that animal. - Mark different types of trials with an independent variable in the Trial List. For example Type, with values C1, C2 ... for confrontation with the first stimulus female and D for the second stimulus female. Scoring Behaviors Manually If you want to score the subject's behavior manually, define them first under Manual Scoring Settings. After you have started the trial, watch the subjects in the video and in the Manual Scoring tab at the bottom of the screen, click the button for the category that applies. As soon as the behavior of the subject changes, click the button for the corresponding category. For more information, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis Chapter: EthoVision XT Data Analysis Analysis Profiles The template experiment contains four analysis profiles: - Distance & Time – With the variables Distance Moved and Velocity, the mean velocity and the total distance moved and the group means with their standard errors are calculated. The total distance moved is a measure of the activity of the test animal. - Movement – With this analysis profile the behavior of the animals is divided into moving and not moving. The frequency, duration and latency to either of these states and the group means with their standard errors are calculated. Like total distance moved, movement is a measure for activity. - In Zones – With this analysis profile, the frequency the animal visited the zones defined in the arena settings and the group mean with its standard error are calculated. The data profile also contains the total time spent in the zones and the latency until the animal first enters either of the zones. - Behaviors – With this analysis profile, the frequency, duration and the group means with their standard errors of the manually scored behaviors are calculated. In the template experiment, the behaviors rearing and grooming are predefined. Possibly, you added additional behaviors like defecating, or urinating. You can add these behaviors to the analysis profile and calculate for example their frequency and duration. Analysis Per Zone To calculate distance or speed in a specific zone: - Choose Analysis > Data Profile > New. Click on the Settings button on the Result box, select Results per zone and subsequently select the zones you want to analyze. - Next, choose Analysis > Analysis Profile > open the analysis profile and select the variable (distance, velocity etc.). - Choose Analysis > Results > Statistics and Charts. To calculate time spent in a specific zone: - Choose Analysis > Analysis Profile > New. Choose In zone, select the zones you are interested in. - Choose Analysis > Results > Statistics and Charts. Time Variation of Behavior Define Results per time bin. In this way, the dependent variables are calculated over each time interval. - Choose Analysis > Data Profile > New. - Click the Settings button on the Result box, select Results per time bin and specify the time interval. - Choose Analysis > Results > Statistics and Charts. Zone Crossings In addition to the predefined analysis profiles you can create an analysis profile for zone crossings. This way you can calculate the number of crossings from the border zone to the center zone. - Click the Add button next to Zone transition. - Select the zone sequence. - Depending on which option you select (Allow intermediate zone visits or Only count direct transitions) you can get different results. For more information, see the Zone transition in the EthoVision XT Help. Freezing Behavior If you want to quantify freezing behavior, which is a measure of the fear the animals experience, create an analysis profile for Activity state. Activity is defined as the amount of pixels in the arena that change at any time. Click the Add button next to Activity state and define the number of states and their thresholds (for freezing, the important threshold is Inactive below). On the Statistics tab, choose the statistics. With this analysis profile the behavior of the animals is divided into the states you specified. Next, use the Plot Integrated Data function to visualize the activity states. Adjust the settings in the Analysis profile until the state "Inactive" matches the freezing behavior of the animal in the video. The frequency, duration and latency to all those states is calculated in the next step (see Calculating Statistics). For more information on Activity, see the EthoVision XT Help. Stretch-Attend Stretch-attend postures can be detected with the Body elongation state variable in the Analysis profile. For more information, see Body elongation state in the EthoVision XT Help. Rat or Mouse Behavior Recognition To analyze the automatically detected behaviors, in the Analysis profile under Rat or Mouse Behavior Recognition choose the behaviors you are interested in. Furthermore: - If you want to analyze multiple behaviors as one, click Merged Behavior. - If you want to view the probability (that is, a measure of detection uncertainty) associated with the behaviors detected, click Behavior probability and specify the behaviors you are interested in. Comparing Groups - Prerequisite: You can define groups of tracks based on independent variables. - Choose Analysis > Data Profile > New. - Create a structure like that in the following picture. To create a new branch, click the button next to Result and connect the Start box with the new Result box. Visualizing Data Choose Analysis > Results > ... - Plot Tracks – You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals treated with saline and red for drug-treated animals). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast. - Plot Heatmaps – You can make heatmaps of the location of the subject. - Plot Integrated Data – You can look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-ARx Chapter: EthoVision XT Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open MDM Filter 2 mm. In this profile, the Minimal Distance Moved filter is used with a value of 2 mm and option Direct selected. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select (Filter) your tracks according to your independent variable values (for example, Treated animals vs. Controls) and also select parts of tracks (Nesting). This allows you to create groups of tracks to obtain group statistics for each group. To create a group, click the button next to Common elements - Result. Connect the Start box to the new Result box. This creates a new group. Next, to specify a criterion for the new group, click an option under Filter, and insert the resulting Filter box between Start and the new Result box. Analysis Profiles The template experiment contains a number of analysis profiles, depending on which arena / zone template you selected in the template wizard: - Distance & Time – With the variables Distance Moved and Velocity, the total distance moved and the mean velocity are calculated. - Movement – The variable Movement calculates how often and how long the center-point was moving. - In Zones – The variable In zone calculates how often and how long the subjects visited each zone in the Arena Settings. The latency to the first visit in a zone is also calculated for each subject. - Behaviors – In this analysis profile, the frequency and duration of Body elongation and the manually scored behaviors Rearing and Grooming are calculated. For all statistics, group means with standard errors are also calculated. Social Interaction in Detail The following variables are commonly used to study social interactions: - Distance Between Subjects – Use this dependent variable to measure the average distance between the subjects. You can also use this dependent variable to determine the appropriate thresholds for the dependent variable Proximity. - Proximity – When the nose-point of the experimental animal is in proximity relative to any of the body points of the stimulus animal, the experimental animal can be considered to be exploring or sniffing the other animal. - Body Contact – Use this variable to quantify body contact, for example how often and for how long two animals are in contact with one another. - Relative Movement – Use Relative movement to determine how much time the experimental animal is actively seeking contact with the stimulus animal. - Net Weighted Movement – Net Weighted movement can be used as an objective measure for the intensity of approach and avoidance behavior. - Weighted Movement From – Weighted movement from can be used as an objective measure for the intensity of avoidance. - Weighted Movement To – Weighted movement to can be used as an objective measure for the intensity of approach. - JavaScript State Variables – Additional variables in JavaScript code are available to quantify social approach, leaving, social contact and following behaviour. These variables can be found in the installation package under Utilities > JavaScript custom variables, and are also available on my.noldus.com or on the GitHub repository: https://github.com/noldus/EthoVision-JavaScriptCustomAnalysis See Dependent Variables in Detail in the EthoVision XT Help for details. Also see the analysis profile Social - Nose to Tail in the sample experiment Social Interaction XT180, available for download from the Noldus website. Statistics and Charts Choose Analysis > Results > Statistics & Charts, then click Calculate. The Trial Statistics tab shows the results per trial. The Group Statistics tab shows the statistics and charts from the summarized results over all trials or the groups defined in your Data Profile. Visualizing Data Choose Analysis > Results > Plot Integrated Data. Select a trial from the list on the tool bar. The video file and the Time Event Plot are displayed. You can select other data/analysis profile combinations from the lists on the tool bar. Choose Analysis > Results > Plot Heatmaps to create heatmaps of the location of your animals during the test. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-bld Chapter: EthoVision XT Data Analysis Data Preparation Data Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. Smoothing Data Choose Acquisition > Track Smoothing Profile and open MDM Filter 0.2 cm. In this profile, the Minimal Distance Moved filter is used with a value of 2 mm and option Direct. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Analysis Profiles The template experiment contains four analysis profiles: - Distance and Velocity. For quantifying activity and exploration. Combine this with a Data profile that specifies Results per zone. - In Chambers. To calculate the time spent in each of the three chambers. - Behaviors. To analyze behaviors scored manually (rearing and sniffing) or the time that the nose point was detected in the area around each cage (sniffing zone). - On Cage. To calculate how often and how long the center point of the subject was found in the zone "cage" (left and right). This correlates with the time the mouse spent on top of the cages. Add other analysis profiles according to your research questions. Click one of the buttons in the Dependent Variables pane and open the Trial Statistics tab to select which statistic to calculate. Example The researcher wants to know the time from the moment the animal is entirely in the right compartment to the first moment the animal's nose-point is close to the cage in the same compartment. To calculate this time, in the Analysis profile choose Free Interval. Select an interval that goes from the time when the Current value of In zone, for zone Cage right, and for all body points, is "true" (Start criterion), to when the Current value of In zone for the zone Interest zone right, and for the nose point, is true (Stop criterion). In the Statistics tab, select Cumulative duration. For more information, see the EthoVision XT Help. Visualizing Data Choose Analysis > Results > ... - Plot Tracks. You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals in Phase 2 and red for animals in Phase 3). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast. - Plot Integrated Data. You can look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Just like with plotting tracks, you can show tracks or sample points in different colors. - Plot Heatmaps. Make heatmaps of the location of your animals during the different trials. In the example below: Left heatmap: Cages empty. Right: mouse restrained in the Left cage (right cage empty). Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-r8N Chapter: EthoVision XT Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors but normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open one of the two Track Smoothing Profiles: - No Filter - MDM 0.2 cm – In this Track Smoothing Profile, the Direct Minimal Distance Moved filter is used, with an MDM of 0.2 cm. Use Smoothing when you want to eliminate small movements, such as body wobbling during locomotion, that might affect dependent variables such as total distance moved. Selecting Data Choose Analysis > Data Profile. The template contains two data profiles: - All Data – This data profile contains all data. - Treated vs. Control – This data profile contains two Results containers with data for the treated animals and the control animals. This way you create groups of tracks to obtain group statistics for both groups. Analysis Profiles Default Analysis Profiles The template experiment contains three analysis profiles: - Distance and Velocity – In this profile, the total Distance Moved and the mean Velocity are calculated for the center-point. - In Zones – In this profile, the Frequency, Duration and Latency to First for all zones (arms and goal zones) are calculated for the center-point. A visit to a previously chosen arm is considered a working memory error. Normal healthy young rats will perform this task almost perfectly every time, so will visit each arm and goal zone only once. - Zone Transitions – In this profile, the Frequency of zone transitions from the center zone to any arm is calculated for the center-point. For all statistics, the group means with standard errors are also calculated. Testing Working Memory Time Taken to Obtain All Rewards The most basic test conducted using the radial-arm maze is to bait the ends of all of the arms with the reward and record the time taken to obtain all the rewards. The following procedure applies to trials where all baited arms were visited. - In the Analysis profile, choose Target visits and errors. - In the Target zones box, select all the zones that were baited. - Under Calculate Statistics for, select Target first visits. - Click the Trial Statistics tab and select Latency to Last. Incorrect Arm Choices To obtain a reward, an animal must remember which arm(s) it visited previously and not re-visit those arms. - In the analysis profile, choose Target visits and errors. - In the Target zones box, select all the zones that were baited. - Under Calculate Statistics for, select Target revisits. - Click the Trial Statistics tab and select Frequency. Percentage of Correct Choices One of the parameters described in the Unit 8.5A of Current Protocols in Neuroscience (Wenk, 2004) to calculate performance of all groups is: the percentage of correct choices made in each test session in relation to the total number of arms entered. - In the analysis profile, choose Target visits and errors. - In the Target zones box, select all the zones that were baited. - Under Calculate Statistics for, select Target first visits and Target revisits. - Click the Trial Statistics tab and select Frequency. - You can calculate the percentage of correct choices with: Target first visits / (Target first visits + Target revisits) * 100 Testing Reference Memory The radial-arm maze may also be used to test reference memory by only baiting some arms of the maze. In training trials, the reward is placed consistently from trial to trial for the same animal, but its placement is varied from animal to animal. In the test trials, the time to acquire the reward and the number of incorrect choices (i.e., entering an unbaited arm or re-entering a baited arm) are analyzed. Time Taken to Obtain the Rewards - In the analysis profile, choose Target visits and errors. - In the Target zones box, select all the zones that were baited. - Under Calculate Statistics for, select Target first visits. - Click the Trial Statistics tab and select Latency to Last. Number of Entries into Unbaited Arms - In the analysis profile, choose Target visits and errors. - In the Target zones box, select all the zones that were baited. - Under Calculate Statistics for, select Not-target first visits and Not-target revisits. - Click the Trial Statistics tab and select Frequency. Note: Re-entries into baited arms are considered working memory errors. Because the arms chosen to be baited differ between animals, make copies of the dependent variable Target visits and errors and edit the arms that are considered targets. Rename the variables (right-click the variable name and select Rename) and give them logical names (e.g. Baited arms 1-3-6-8). In the analysis results, locate the variable that applies to specific subjects. To easily locate which subjects were assigned to which baited arms in your results table, create an independent variable in the Trial List which specifies which arms were baited. This variable can then be included in the results table (in the Statistics and Charts screen, choose Show/Hide > Independent Variable). Integrated Visualization Choose Analysis > Results > Plot Integrated Data. Select a trial from the list on the tool bar. Choose a data profile and an analysis profile from the tool bar. Heatmaps Choose Analysis > Results > Plot Heatmaps. Next, click Plot Heatmaps. Use heatmaps to visualize the location of the subject during the test. Calculating Statistics Choose Analysis > Results > Statistics & Charts. Select an analysis profile from the list on the tool bar, then click Calculate. Choose Analysis > Export > Statistics. Choose whether you want to export the statistics per trial, or the combined statistics of groups of trials. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-j2E Chapter: EthoVision XT Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors but normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open MDM 0.2 cm. In this profile, the Minimal Distance Moved filter is used (option set to Direct, with a threshold of 2 mm). This filter filters out small movements which result from system noise. Note that smoothing influences the track, that is, the coordinates of the center point of the subject, not the subject's detected area, and therefore does not influence the calculations of Mobility. It also has no effect on Activity analysis. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select your tracks according to your independent variable values and also select parts of tracks (nesting). You can also create groups of tracks to obtain group statistics for each group. Figure 9.7 shows an example of a Data Profile to compare the animals that were treated with a drug, with those that were treated with saline. Integrated Visualization Choose Analysis > Results > Plot Integrated Data. Select a trial from the list on the tool bar. The video file and the Time Event Plot are displayed. In the Time Event Plot tool bar you can choose which profiles to use for display of the variables. Figure 9.8 shows how variables are visualized in the sample experiment Porsolt Forced Swim Test XT180 with the Analysis Profile Mobility_10 containing the variable Mobility. Play the video and check whether the states scored under Mobility state correspond to the behavior of the animal. If they don't, fine tune the Mobility (or Activity) thresholds in the Analysis profile. Then, check the results of your changes again in the Integrated Visualization. Analysis Profile Mobility Analysis In an Analysis Profile, you select the dependent variables and statistics for analysis. For the experiment made with the template for the Porsolt Test, a dependent variable Mobility is already present. Choose Analysis > Analysis Profile > Open > Mobility. - Double-click the row for the Mobility state variable. - Under Outlier filter, the Averaging interval is the number of samples on which the running average mobility is based. With an Averaging interval of 1 sample, sudden changes in surface area caused by reflections are not filtered out. - Under Threshold, set the Highly mobile and Immobile thresholds to the values you have previously determined (see determining mobility thresholds on page 171). - Under Calculate statistics for, select the states you want to analyze. - Click the Trial Statistics tab and select Duration and Frequency. Optionally select additional statistics in the Group statistics tab. - Click OK. Comparing EthoVision Mobility Data with Your Ratings If you have scored the animal's behavior manually, you can easily compare your data with those scored by EthoVision (Mobility). Make sure that your analysis profile includes the three Mobility states and the behaviors scored manually, then visualize the data. If the EthoVision data do not match your ratings at an acceptable level, adjust the Mobility threshold values in acquisition and in analysis. An Alternative to Mobility Analysis You can use Activity state if the Mobility state variable does not give good results, for instance when detecting thrashing of the animal's limbs which may not be detected properly by Mobility state. Activity analysis is based on the temporal change in pixel value in the whole arena. Because it is not based on the detected animal's surface area, it is independent of tracking. - In the Experiment Settings, under Analysis options select Activity analysis. Click the video button next to it and watch the video tutorial to learn about Activity analysis. - In the Detection Settings, click Activity. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold in such a way that when the animal is immobile, those pixels are almost completely absent. - Run the trial. - In the Analysis profile add Activity and Activity state. - Visualize the data (Plot Integrated Data). There you see the scored Activity states and the subject in the video. Adjust the Activity state settings in such a way that the states scored by EthoVision XT match the behavior of the subject at that time. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-4gZ Chapter: EthoVision XT Data Preparation Data Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. Smoothing Data Choose Acquisition > Track Smoothing Profile and open MDM Filter 0.2 cm. In this profile, the Minimal Distance Moved filter is used with a value of 2 mm and option Direct. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select your tracks according to your independent variable values (for example, Treated animals vs. Controls) and also select parts of tracks (data nesting). The Data Profile Treated vs. Control from the template compares 'Treated animals' and 'Control animals' trials. This way you create groups of tracks to obtain group statistics for each group. For more information and to create your own data selection, see the EthoVision XT Help. Trial Statistics will be displayed per trial, and Group Statistics will be displayed per group of trials, according to the treatment level assigned to them. If you have more treatment groups (e.g. Sham), to create more treatment groups click the Common Elements - Result button in the Components pane, and place the new box somewhere on your screen. Create a new branch by connecting the first (Start) box to this new box. Click the button next to Treatment and select the new treatment level. Insert the box in the new branch. Visualizing Data You can visualize your tracks in three ways: - Plot Tracks. You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals treated with saline and red for drug-treated animals). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast. - Plot Integrated Data. You can look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Just like with plotting tracks, you can show tracks or sample points in different colors. - Heatmaps. You can make heatmaps of the location of your animals during the test. Analysis Profiles The template experiment contains three analysis profiles: - Time in Arms – This analysis profile contains two In Zone variables: - In Closed Arms to calculate the frequency and duration of when the animal was in the closed arms. - In Open Arms to calculate the frequency, duration and latency of when the animal was in the open arms. Here, latency (the time to the first visit in any open arm) is used as an indication of anxiety. For all variables, the animal is considered to be in a zone when all its body points are found in the zone simultaneously. - Behaviors – In this analysis profile, four variables have been defined: - Head Dipping and Rearing provide statistics of the behaviors manually scored. - Body Elongation is used to quantify the time that the animal shows stretching behavior. - Nose in Head Dip Area is an In Zone variable to calculate the frequency and duration of when the nose point of the animal was in the head dip areas. The last two variables are present when you set the experiment to track the three body points or you select the zone template with the head dip area. - Velocity and Distance – With the variables Distance Moved and Velocity, the total distance moved and the mean velocity and the group means and their standard errors are calculated. Movement is based on a velocity threshold, and quantifies the time that the animal has moved significantly. For more information, see the EthoVision XT Help. False Positives in Arm Entry Statistics Sometimes the center point of the animal fluctuates around the border line between the center and the arm zones. This may be caused by jitter or exploration behavior, and results in false positives when calculating the number of zone entries. To prevent this from happening, set the Zone Exit Threshold for the In Zone variable. To Set a Zone Exit Threshold - In the Analysis profile, add the In Zone variable. Specify the arm zones you are interested in, and the body points that define a zone entry (when tracking the center, nose and tail base points). - Under Threshold, enter a value for Zone Exit Threshold. This is the distance from the border of the arm zone that the animal must be in order to be considered outside the zone. Use the Zone Exit Threshold to filter out small movements of the body points that result from jitter or exploration behavior. - Visualize the data (Analysis > Results > Plot Integrated Data). Example In the following example, slight movements of the mouse's center point result in multiple open arm entries. In the Analysis profile, In Zone is set with Zone Exit Threshold = 0 cm. - Left: Mouse enters the open zone. - Middle: The center point is detected out of the zone. - Right: The center point is inside the zone; a second arm entry is scored. To remove false positives of zone entries, in the Analysis profile, In Zone is set with Zone Exit Threshold = 2 cm. This means that when the center point is outside the zone by less than 2 cm from the border, it is still considered in the zone. Result: This time, one arm entry is scored. For more information on the Zone Exit Threshold, see In Zone in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-2Hx Chapter: EthoVision XT Data Analysis Data Preparation Track Smoothing Choose Acquisition > Track Smoothing Profile. - Lowess Smoothing: Select to remove the effect of body wobble. When the animal sits still on the platform, yet the body center-point still moves slightly due to system noise, this results in an overestimation of, for example, the total distance moved. - Minimal Distance Moved: Select to only measure the total distance moved over the time periods in which the animal was really swimming. Analysis Profiles Choose Analysis > Analysis Profile. The template experiment contains five analysis profiles: - Latency to Reach Platform: This profile contains the variable Latency to platform to calculate how long it takes the animal to find the platform. You can use the variable Distance to zone to calculate Gallagher's index (Gallagher et al., 1993). The variable In quadrants calculates the frequency and duration of visits to each quadrant. - Path Shape: The path shape can be determined by using the variables Turn angle, Angular velocity and Meander. - Whishaw's Corridor (only present if you chose a zone template with corridors when creating the experiment): The variable Inside Whishaw's Corridor calculates the time the animal spent inside any of Whishaw's corridors. The variable Outside Whishaw's Corridor calculates the time the animal spent outside any of Whishaw's corridors. - Distance & Time: In this profile, the total Distance Moved and the mean Velocity and the group means with their standard errors are calculated. - Heading: In this profile, the mean Heading to each of the platforms is calculated. Swim Patterns Thigmotaxis (Wall-Hugging Swim) This is a persistent swim along the wall of the pool that could include sporadic swims toward the center of the pool. To quantify thigmotaxis, calculate the time spent in the Thigmotaxis zone relative to the total track duration. Random Search This is swimming over the entire area of the pool in straight swims (zig-zag pattern), or in wide circular swims. Divide the pool into quadrants or smaller zones, then count the number of times each zone was visited and the time in zones. If zone visits and time are uniformly distributed across zones, the search pattern could be said to be random or at least covering the whole pool. Scanning The search path is restricted to a limited, often central, area of the pool. Perform the same analysis as for random search, but covering only the area and zones towards the center (see Figure 1C in Janus C. 2004. Learning and Memory: 337–346). Relate this to the time in the external zones. Chaining/Serial Visits This is circular swimming (in anticlockwise or clockwise direction) at a fixed distance from the wall, in which the escape platform was located. To quantify chaining, draw a specific circular crown zone. Calculate the time spent in this zone versus the time in the rest of the arena, or calculate rotations occurring in that zone. Focal Search This is searching in a restricted area of the pool, usually the target quadrant. The path is characterized by a directional, straight swim to a specific area followed by dense concentration of superimposed loops and turns there. - To detect rapid changes in direction, use the Multi condition dependent variable to define your criterion, for example Absolute Meander > 10 degrees/cm. This marks the time when Meander is greater than the threshold value. - Combine Meander with an In zone variable in a Free Interval to select the time from when the rapid change in direction occurs to when the subject enters the target area. In the Arena Settings, define a zone around the platform or any other target point, and name it Focal zone. In the Analysis profile, define a Free interval with: - Interval Start: Meander: Absolute Meander > 10 degree/cm - Interval Stop: In zone: Center point is in Focal zone Direct Swim Path This is the direct swim path to the location containing the escape platform. Define an In zone variable based on the Whishaw's corridor to calculate the time spent in and outside this corridor before reaching the platform. See also the EthoVision XT Help. Floating A state of inactivity without forward movement. The plotted path is short, often with thick or tight sections caused by non-directional drift. Quantify floating with Movement (Not moving) or a Multi condition that includes Movement (Not moving) and In zone (Center point is not near the wall of the pool; define a dedicated zone if necessary). Gallagher's Proximity Score Cumulative Search Error (For Training Trials) Gallagher et al. (1993) proposed the Cumulative search error to provide information about the spatial distribution of the animal's search during training trials. This is obtained by sampling the position of the animal in the water maze 10 times per second, and calculating the averages of distance to the platform for 1-second periods. The averages are then summed up. In EthoVision XT, you have two options: - Calculate the Total Distance from the Platform: In the Analysis profile, choose the dependent variable Distance to zone, with the Statistic Total. This equals the "true" Gallagher's Cumulative search error when sample rate = 10 samples/s. In most cases the Total distance from the platform highly correlates with the "true" search error. - Calculate the "True" Gallagher's Cumulative Search Error: - In the Data profile, select time bins (1 second). - In the Analysis profile, define the dependent variable Distance to zone, with the Statistic Mean. - Choose Analysis > Results > Statistics and Charts, click Calculate, then export the results via Analysis > Export > Statistics. - In Excel, open the export file and sum up the average values per trial. Average Search Error (For Probe Trials) According to Gallagher et al. (1993), the Average search error is obtained by calculating the average distance of the animal to the platform location over 1-second intervals, and then averaging the results. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-DXJ Chapter: EthoVision XT Data Analysis In this section you find general information on how to analyze data in a conditioning test. Data Preparation There are three optional steps you can take to prepare your data: - Edit the Tracks Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. - Smooth the Tracks Choose Acquisition > Track Smoothing Profile. You can use Smoothing and/or the Minimal Distance Moved filter to remove outliers from your data and correct the distance moved calculation as a result of body wobble. - Select Tracks and Intervals Choose Analysis > Data Profile. Select your tracks according to your independent variable values and also select parts of tracks (nesting). You can also make groups of tracks to obtain group statistics. And you can define Time bins (see data selection below). Data Selection Groups of Tracks You can configure a Data Profile to compare animals that were treated with a drug with those that were treated with saline. This way you create groups of tracks to obtain group statistics for each group. Time Bins Using time bins means that you create time intervals of constant duration to analyze how variables change over time. The default data selection does not specify time bins, so the behavior will be analyzed as a whole. If you define time bins and specify an interval length of, for instance, 1 minute, you can investigate whether a specific behavior changes over time. To define time bins: - From the Analysis menu, select Data Profile. - Select New and type in Time intervals. - Click the Settings button on the Result box. - Select Results per time bin and enter the length of one interval, for example 30 s or 1 minute depending on the duration of your experiment. The data will be split in a number of intervals of the same length. When the track duration is not an exact multiple of the time bin that you set, the last time bin is shorter than the others. To ignore this time bin, select Ignore last time bin if incomplete. - Click OK. If the white spotlight is aversive to the animal, the time spent in the Spot Light zone should decrease in the course of the trial. In contrast, the time interval between consecutive entries into Zone LightSpot should show an increase. Via data analysis in EthoVision XT, this can be investigated. Analysis Profiles Choose Analysis > Analysis Profile. If you have multiple Data Profiles, create or open a Data Profile without Results per time bin. Below is described how to create the following analysis variables: - In Zone — calculates how often and how long the mouse stayed in the illuminated zone. - Trial Control State "Interval in Spot Light Zone" — measures the time elapsed until the mouse enters the light spot again, for each repeat of the learning routine. - Trial Control State "Duration Light On" — measures the time that the mouse stays in the light spot in each repeat of the learning routine. - Trial Control Event "Frequency Light On" — measures the number of times that the light is switched on. In Zone - Select New and type in In Zone. The new Analysis Profile contains the default dependent variables Distance moved and Velocity. Click on a dependent variable and press Delete to remove it. - Click the Add button next to In Zone. - Under In the following zones, select Spot Light. Under From following body points, select both Nose-point and Center-point and select All selected points from the list at the bottom. - In the Trial Statistics tab, select Mean, Frequency and Duration. - Select additional statistics in the Group Statistics tab, if you created groups of tracks in your Data Profile. - Click OK. Trial Control - Click the Add button next to Trial Control State. - From the From Element list, select Rule: Anxiety Test. From the From Event list, select becomes active. - From the to Element list, select Action: Light on. From the to Event list, select becomes active. - Select Calculate statistics per interval, for consecutive intervals. - In the Trial Statistics tab, select Cumulative duration. - Select additional statistics in the Group Statistics tab, if you created groups of tracks in your Data Profile. Then click OK. - Right-click Trial Control State, select Rename and type Interval in Spot Light zone. - Click the Add button next to Trial Control State. - From the From Element list, select Action: White Light On. From the From Event list, select becomes active. - From the to Element list, select Action: White Light off. From the to Event list, select becomes active. - Select Calculate statistics per interval, for consecutive intervals. - In the Trial Statistics tab, select Cumulative duration. - Select additional statistics in the Group Statistics tab, if you created groups of tracks in your Data Profile. Then click OK. - Right-click Trial Control State, select Rename and type Duration Light on. - Click the Add button next to Trial Control Event. - From the From Element list, select Action: White Light On. - From the From Event list, select becomes active. - In the Trial Statistics tab, select Frequency. - Select additional statistics in the Group Statistics tab, if you created groups of tracks in your Data Profile. Then click OK. - Right-click Trial Control Event, select Rename and type Frequency light on. More Options with the Free Interval Function The Free interval function in the Data Profile and in the Analysis Profile allows you to extend the possibilities to define the start and the end of intervals. For example, from the time a stimulus event occurs, to 10 seconds after that event. - Choose Analysis > Analysis Profile. - Under Miscellaneous, click next to Free Interval. For details, search the EthoVision XT Help for Free interval. Integrated Visualization When you Plot Integrated Data, the video file and the Time Event Plot are displayed. The Time Event Plot displays the variables of the active Analysis Profile. The Integrated Visualization for an Analysis Profile containing Trial Control variables displays the Time Event Plot showing (from top to bottom) Duration Light on, Frequency Light on, and Interval in LightSpot, all for each arena separately. The vertical line shows the current position in the Time Event Plot and the video window displays the corresponding frame in the video. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-E5w Chapter: EthoVision XT The Y-Maze Test Introduction The Y-Maze The Y-maze is constructed with three arms of equal length that extend from a central platform at a 120° angle. In the basic version, the animal is free to explore the maze arms. In a modified version, it is possible to close off some arms either to keep the animal in a specific arm for a fixed time once it has entered that arm, or to limit exploration to some arms, not others. The Y-maze is generally used to investigate alternation behavior, where animals are supposed to alternate choices of maze arms on successive opportunities. Irrespective of the precise function of alternation, the animal must remember which arm it had entered on a previous occasion to enable it to alternate its choice on a following trial. Therefore, the use of the Y-maze is based on the assumption that, following some pharmacological manipulation, it is primarily modified memory processes that are reflected in changed alternation rates. Spontaneous Alternation Definition Spontaneous Alternation is a behavioral test for measuring the willingness of rodents to explore new environments. Rodents typically prefer to investigate a new arm of the maze rather than returning to one that was previously visited. Many parts of the brain, including the hippocampus, septum, basal forebrain, and prefrontal cortex, are involved in this task (Conrad et al. 1996). Classical Procedure The animal is released in the center of the maze, and allowed to freely explore the three arms (A, B, C). Over the course of multiple arm entries, the subject is expected to show a tendency to enter a less recently visited arm (A > B > C > A > ...). The observer records the number of arm entries and the number of visits to the three arms without a re-visit in between (for example, A > B > C, B > C > A, etc.) in order to calculate the percentage of alternation. An arm entry is scored when all four limbs are within the arm. Calculation of Alternation Index Given a zone sequence: A > B > C > B > ... An alternation is defined as multiple entries into the three different arms on overlapping triplet sets. In this example the first three visits are an alternation: A > B > C > B > ... The next overlapping triplet set, B > C > B, is not an alternation. The Alternation index is given by the number of alternations divided by the maximum number of possible alternations, that is, the number of alternations that would be obtained if the animal visited the zones in the sequence: A > B > C > A > B > C ... For a 3-arm maze, like the Y-maze, the maximum number of alternations is equal to total number of visits minus 2. The Alternation index is expressed as a percentage: Alternation Index = Number of alternations / (Total number of zone visits - 2) Spontaneous Alternation in EthoVision XT You can easily calculate the Alternation index using the outputs Alternations and Max Alternations in the Zone alternation dependent variable. For more information, see Zone Alternation in the EthoVision XT Help. Delayed Alternation Definition The delayed alternation task allows assessing spatial working memory in a T- or Y-maze. The main difference with spontaneous alternation is that performance is evaluated between trials. Classical Procedure In the first trial of the test, the animal is placed at the end of the start arm and has to choose between the two other arms that are baited. Once the choice is made, the subject is removed and after a variable delay, is returned to the start arm. In this second trial, the one arm baited is now the opposite arm to which was chosen during the first trial. The animal has to make a different choice than its first one (correct choice) to get the reward. Delayed Alternation in EthoVision XT For all tests where maze arms can be considered as targets of a choice, and others non-targets (errors), you can use outputs Target First Visits and Total Errors in the Target visits and errors dependent variable. For more information, see Target Visits and Errors in the EthoVision XT Help. References - Conrad, C.D., Galea, L.A., Kuroda, Y., McEwen, B.S. (1996). Chronic stress impairs rat spatial memory on the Y maze, and this effect is blocked by tianeptine pretreatment. Behav Neurosci: 1321–1334. - Conrad, C.D., Lupien, S.J., Thanasoulis, L.C., McEwen, B.S. (1997). The effects of type I and type II corticosteroid receptor agonists on exploratory behavior and spatial memory in the Y-maze. Brain Res., 76–83. - Hughes, R.N. (2004). The value of spontaneous alternation behavior (SAB) as a test of retention in pharmacological investigations of memory. Neurosci. Biobehav. Rev., 497–505. - Detrait, E., Brohez, C., Hanon, E., De Ryck, M. (2010). Automation of Continuous Spontaneous Alternation to Increase the Throughput for In Vivo Screening of Cognitive Enhancers. Optimization of the Ethovision System for the Y-maze Test in Mice. Proceedings of Measuring Behavior 2010 (Eindhoven, The Netherlands, August 24–27, 2010), 141–144. For a complete list of publications, see the results of Google Scholar. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-Tzz Chapter: EthoVision XT Data Analysis Analysis Profiles Choose Analysis > Analysis Profile... The template experiment contains the analysis profiles: - Distance, Time & Movement. To calculate the total Distance moved (a measure of activity of the animal), the mean Velocity, and the total time spent in the two states of Movement (moving and not moving). The group means with their standard errors are also calculated. - Zone Alternation. With the variables In Zone (to calculate the frequency, total time and latency to first visit for each zone) and Zone Alternation (to calculate the number of alternations and the maximum number of alternations for that set of zone visits). See the section below to create analysis profiles for specific tasks. Alternation Behavior Spontaneous Alternation - Choose Analysis > Results > Statistics and Charts. - Select the Analysis Profile that contains the Zone Alternation variable. - Locate the column Zone Alternation in the table. - To calculate the Alternation Index, divide Alternations by Max Alternations and multiply by 100. To change the Zone Alternation definition, open the Analysis Profile Zone Alternation and double-click the variable Zone Alternation. Here you can specify which statistics you want to have. You can also enter a Zone Exit Threshold to remove false re-entries in a zone from the statistics, due to small movements of the body point near the zone borders. For more information, see Zone Alternation in the EthoVision XT Help. Delayed Alternation For delayed alternation tests, Zone Alternation is not the correct dependent variable. To analyze correct and incorrect choices, use Target Visits and Errors to compare performance between trials. Because the target arm changes between trials (for trial 2, the target is the arm which was not visited in the previous trial), you must define multiple instances of Target Visits and Errors. Whether an arm can be defined as "target" depends on the outcome of the previous trial. If the subject went to the Left arm in trial x, then for trial x+1 the target should be the Right arm, and a revisit to the Left arm should be scored as an error. To set this up: - In the Trial List (Setup > Trial List), mark each trial with a variable which states which arm was the correct choice. By definition, the 1st trial of each subject has no "correct" choice (the values for subsequent trials depend on what the animal does in that trial). - In the Data Profile, filter the trials based on this variable. Make two Data Profiles: one for "Right Arm Correct" and one for "Left Arm Correct". - Create two analysis profiles. For example: - Analysis Profile Target Visits and Errors for when the target (correct choice) was the Left arm. The Right arm is a non-target; visits to that arm are scored as errors. - Analysis Profile Target Visits and Errors for when the target (correct choice) was the Right arm. When you analyze the data, make sure to combine a Data Profile with the correct Analysis Profile. Visualizing Data Choose Analysis > Results > Integrated Visualization. The first plot shows the variable In Zone defined in the Analysis Profile, where you can see which arms were visited during the trial. The second plot shows Zone Alternation. The subject visits first the zone marked in blue, then that in red, and when the subject enters the green-marked zone, an alternation is completed. This is scored as Alternations (blue vertical segment; A). At every visit except the last two in a trial, Max Alternations is also scored (purple vertical segment; B). This marks the moment a possible alternation could have occurred. This variable is useful to calculate the Alternation Index. The plot also includes direct revisits (for example, green > green) or indirect revisits (green > red > green; C). The more revisits, the lower the Alternation Index. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-Aqk Chapter: EthoVision XT Data Analysis Simple Data Selection Choose Analysis > Data Profile > New. To Select the Track Segments When the LED Was Activated - Under Nesting choose Hardware state. - From the Device type list, choose Custom Hardware. - Choose the Device, the Signal (Is output 1 High), Value (true). - Click OK and insert the Nest box in the Data profile sequence. - Choose Analysis > Analysis Profile > New and define the variables you want to calculate for when the animal was stimulated (for example, the distance moved). To Select the Track Segments When the LED Was Not Activated - Under Nesting choose Hardware state. - From the Device type list, choose Custom Hardware. - Choose the Device, the Signal (Is output 1 High), Value (false). - Click OK and insert the Nest box in the Data profile sequence. - Choose Analysis > Analysis Profile > New and define the variables you want to calculate for when the animal was not stimulated. Advanced Data Selection To compare two sets of track segments (LED activated vs LED not activated), create the two Nest boxes as described above. Place each box in a separate branch ending with a Result box. To create another Result box, under Common Elements choose Result. Note that if you use the Pulser to generate high frequency optical pulses, the individual pulses are not "seen" by EthoVision XT. Because EthoVision XT controls the Pulser via the single TTL start/stop commands ("Output 1 High/Low"), it only "sees" the time that the command was sent out (Output 1 High/Low). Therefore, the pulse sequence is seen as a one time segment. For more information on data selection, see the EthoVision XT Help. To Select the Track Segments When a Particular Frequency Was Generated (Setup with Pulser) Prerequisite: your Trial Control procedure includes control of frequency of stimulation. Two Subrules are defined: one for zone A (stimulation at 25 Hz) and one for zone B (stimulation at 50 Hz). Within a Subrule, Hardware actions "Activate Pulser" and "Deactivate Pulser" can be used to mark the time that a particular frequency was used. - In the Data Profile, under Nesting choose Trial Control State. - Choose the name of the actions that refer to a particular frequency: - From Element Action: [action that triggers the Pulser] - To Element Action: [action that stops the trigger] From the Event lists, select becomes active for both elements. - Click OK and insert the Nest box in the Data profile sequence. - Choose Analysis > Analysis Profile > New and define the variables you want to calculate. Calculating Statistics Once you have selected the track segments you are interested in, choose the variables you want to calculate. Choose Analysis > Analysis Profile > New. To calculate the number of times that the optical stimulation was activated, in the Analysis profile choose Hardware command. Choose the following: - Device type = Custom Hardware - Device = the LED controller (or Pulser) - Command = Output 1 High - Under Trial Statistics choose Frequency To calculate the total time that stimulation was activated, in the Analysis profile choose Hardware state. Choose the following: - Device type = Custom Hardware - Device = the LED controller (or Pulser) - Signal = Is Output 1 High - Value = true - Under Trial Statistics choose Cumulative Duration To calculate the statistics, choose Analysis > Results > Statistics and Charts. Integrated Visualization Choose Analysis > Results > Integrated Visualization. The Trial Control protocol uses stimulation of 25 Hz when the animal is in zone A and 50 Hz when the animal is in zone B. The following variables can be displayed: - In zone. Shows when the animal was in zones A and B. To show this variable, you must define it in the Analysis profile (choose In zone under Location). - Hardware command. Marks the time when the Output 1 High was sent out from EthoVision XT. - Hardware state. Marks the time interval when Output 1 stayed High. - Trial Control state - Pulser 25 / Trial Control state - Pulser 50. Marks the time that the Hardware command within one of the Subrules was High. That command triggered the pulser for a specific stimulation (25 or 50 Hz). This way instances of Hardware state can be split according to the frequency of the stimulation. Installing the Prizmatix Pulser Follow this section if the Prizmatix Pulser/PulserPlus is not properly installed on the EthoVision XT computer. Software Installation Insert the Prizmatix Pulser software CD in the EthoVision XT computer's CD/DVD ROM drive, or download the most recent version from www.prizmatix.com/software.htm under Pulser/PulserPlus Software. Double-click setup.exe. Follow the instructions on the screen and at the end of installation restart the computer. Follow the instructions below to update the driver. Note: The installation procedure differs depending on whether you have the Pulser or PulserPlus. For more information, see the Prizmatix Pulser/PulserPlus User Manual. Driver Update Do this for each Pulser you use, when they are not recognized. - Connect the Pulser to the computer with the supplied USB cable. - In the Control Panel, open the Device Manager. - Under Other Devices, right-click Unknown device and select Update driver. - Choose Browse my computer for driver software. - Click Browse and select the following folder: C:\Program Files (x86)\Prizmatix Pulser [version number]\Drivers, then click Next. Note: This location may differ on your PC if you downloaded the drivers and saved them to another location. - In the Windows Security dialog click Install. - At the end of the update process click Close. - In the Device Manager, under Ports, you should see Prizmatix DRV. To configure the Pulser driver for EthoVision XT, see the configuration section. Calcium Imaging - Introduction - Physical Setup - Basic Settings - Program Control of Devices in EthoVision XT - Detection Settings - Aligning Data - Data Analysis in EthoVision XT Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-continued Chapter: EthoVision XT Data Analysis (Continued) Values (Average proximity; see Figure 9 in the original paper). In EthoVision XT In the Analysis profile, choose the dependent variable Distance to zone, with the Statistic Mean. This equals the Gallagher's Average search error in all cases. Data Correction For both probe trials and training trials, Gallagher et al. (1993) made a correction so that trial performance was relatively unbiased by differences in distance to the goal from the various start locations at the perimeter of the pool (see page 621 in the paper). If you want to apply this correction to your data: - Measure the distance D between the release point and the platform. In the EthoVision XT Trial List, define an independent variable D and for each trial enter the appropriate value depending on the release point used in that trial. Values will be used later in the Excel export file. - In the Analysis profile, define the dependent variables Distance to zone, In zone (not in platform) and Velocity. - Choose Analysis > Export > Raw Data and choose Excel as File type. - In Excel, create macros/formulas that calculate (see the next page): - The average velocity v when In zone = 1. - The time needed to reach the platform from that starting point: t = D/v. - Insert a new column Valid time, assign the value 1 if Recording time in the same line is higher than t. - Calculate the average distance to zone (platform) for when In zone = 1 and Valid time = 1 (use the Excel function averageifs). - Calculate the total distance to platform when In zone = 1 and Valid time = 1 (use the Excel function sumifs). Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Data Analysis In Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-data-analysis-in-ethovision-xt Chapter: EthoVision XT Data Analysis in EthoVision XT Once you acquire your trials, you want to pair the behavioral tracking with the calcium imaging/optogenetic stimulation events. To view and analyze those events, you must first define them in the Analysis profile. Here we report a few examples. Choose Analysis > Analysis Profile > New. Define a Simple Event With the variable Hardware command you can visualize the time that the USB-IO box sends a trigger command to nVista/nVoke. - In the Dependent Variables pane, under Hardware, choose Hardware command. - Choose the device and the output state, for example Output 1 High. Note that Output represents one of the two communication lines present in each TTL port of the USB-IO box. Choose the line that you used in the Action box in the Trial Control Settings to trigger the device. - Visualize the event (Analysis > Results > Integrated Visualization). Analyze Intervals (Global) You can analyze the behavior of the subject within an interval based on events. For example, calculate the average velocity of the subject from the time that stimulation starts (i.e., when the TTL Output 1 is High) to the time that stimulation ends (i.e., nVoke is triggered with Output 1 Low). To analyze the behavior within intervals, you must use the Nesting function in the Data profile. - Choose Analysis > Data Profile > New. - In the Components pane, under Nesting, choose Hardware state. - Select the device and the status of the device. For example, Device A - Is Output 1 High - true. This selects the time that the TTL Output 1 signal remains high. - Insert the box in the flow line. - Visualize the interval (Analysis > Results > Integrated Visualization). Note: If Output 1 stays high multiple times during one trial, EthoVision XT considers the cumulative time that Output 1 stays High, and that is used as the analysis interval. When you want to analyze the time defined by a specific triggering event, see below for a different solution. Analyze Specific Intervals You can use Free Intervals to specify a single interval based on one of the occurrences of a triggering event. Suppose that nVoke is triggered in ten intervals, and you want to analyze the second interval. - Choose Analysis > Data Profile > New. - In the Components pane, under Nesting, choose Free interval. - For both Start criterion and Stop criterion, select Hardware. Define the start and stop event. For example, Start criterion: Output 1 High; Stop criterion: Output 1 Low. - Select Calculate Result for interval and choose the occurrence. In this example, 2. - Insert the box in the flow line. - Visualize the interval (Analysis > Results > Integrated Visualization). - In the Analysis profile, define the variable that you want to calculate within the interval (e.g. velocity). Note: You can also use the commands of Trial Control to define intervals. For example, define an interval that starts when the tone cue is given (i.e. when the Action Tone cue becomes active). You can also use Conditions (e.g. the interval starts when the Condition Wait 30 seconds becomes active). If an Action follows immediately a Condition, then the time that the condition becomes true is essentially the same as the time that the following action becomes active, because both boxes are processed in the same sample time. In that case it does not matter which box you use for defining the interval. Export the Raw Data You can export the raw data (behavior and hardware events) with their time stamps, for example to sync EthoVision XT data with calcium imaging in a third-party application. - Choose Analysis > Export > Raw data. - Note that Raw data also includes the Trial Control events and states (e.g. a condition being true) once you include them in the Analysis profile. - Select the Hardware log option if you want to export hardware events. Align EthoVision XT and Inscopix Data Computer Clocks Ensure that the two computers used for data acquisition (EthoVision XT and Inscopix IDAS) have their clocks synchronized, for example using Network Time Protocol. Point all PCs at a time server or point one and set it up to act as a time server to the other. Unix Time Inscopix software often exports time stamps to Unix (Epoch) time. Unix time is also known as Epoch Time or Unix timestamp. It is a system that counts the number of seconds that have elapsed since the Unix Epoch, i.e. January 1st, 1970. In simple terms, Unix time is the total number of seconds that have elapsed since 00:00:00 UTC Thursday, 1 January 1970. Convert EthoVision XT Time to Unix Time You can use an Excel formula to convert the trial time in EthoVision XT to Unix time. In general, the formula is: Unix time = (EthoVision Time - DATE(1970,1,1)) * 86400 Because the trial (or recording) time in EthoVision XT is relative time (e.g. 0.200), you need to convert it to absolute time using the Reference time cell in the raw data. Then use a second formula that adds the trial (or recording) time to the reference time. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Detection Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-detection-settings Chapter: EthoVision XT Detection Settings General Ensure your subjects are detected well by Ethovision XT. Choose Setup > Detection Settings. For more details, see the EthoVision XT Help. Sample Rate In the Video section, specify the sample rate. Some commonly-used values are: - For tracking rats: 5 samples/second. - For tracking mice: 12.5 samples/second. - When tracking the nose- and tail-base points of rodents: 25–30 samples/second. Detect Immobility There are two ways to detect immobility of the subject during the trial. - Activity measures the number of pixels that change their intensity, so whenever the subject sits still, the Activity value will be low. However, when the subject is connected to a microscope cable, the cable can move continuously and keep Activity high. - Mobility is based on the change of the detected shape (i.e., the yellow blob). You can define Mobility in the Analysis profile, so you do not need to specify anything in the Detection Settings. However, make sure that the yellow blob covers the entire body of the subject and is not affected by the cable. As a result of cable interference, Activity measurements may not detect immobility with sufficient accuracy. Instead, use Mobility. Remove the Effect of the Microscope Cable When the microscope cable is detected as the subject, it changes both the Mobility measure and the position of the center point. The latter affects distance moved and other readouts. Step 1 – Define the Contrast Make sure that the entire body of the subject is well detected throughout the arena. Use Dynamic Subtraction and choose the smallest range of contrast that enables detection of the subject's body. Ensure that the contour of the subject is not too much indented and that noise (i.e., the orange areas) is limited. Note that the cable may still be detected at this stage and will be removed in the next step. Step 2 – Erode and Then Dilate the Contour In the Detection Settings, locate the Subject Contour options. Select a value for the first Erosion and a similar value for Dilation until the cable is no longer highlighted in yellow. - The Erosion filter removes pixels from the contour, including those representing the cable. - The Dilation filter restores the original size of the yellow blob but excludes the cable. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-qwx Chapter: EthoVision XT Trial Control Settings The Trial Control Settings in EthoVision XT allows you to program activation of calcium imaging and optogenetic stimulation by Inscopix devices at specific times or when specific events occur, for example when the subject enters a target zone of the arena. In addition, in Trial Control Settings you can define the conditions for the start and stop of data acquisition. In EthoVision XT, choose Setup > Trial Control Settings > New, and enter a name for the new settings profile. For More Information For more information on how to work with Conditions and Actions in Trial Control Settings, see the EthoVision XT Help (press F1 in EthoVision XT) and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, which you can find in the Apps screen under Noldus > EthoVision XT 18 Other Documentation. Example 1 - Image Recording (nVista) Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. Next, EthoVision XT sends out a high TTL pulse to the TRIG port of nVista. After a time delay of 10 minutes, EthoVision XT stops tracking the subject. Hardware Connections See the scheme on page 343. Prerequisites in EthoVision XT You specified the TTL port and output line (either 1 or 2) for TRIG in the Experiment Settings and mapped the port to the arena (see page 346). Procedure - In the Trial Control Settings, under Actions, click the button next to Custom hardware. - Specify the device (e.g. Device A) and the type of signal (Output 1 High). - Optionally, edit the name in the Action name field. - Click OK and insert the Action box between the Condition - In zone box and the Action - Start track box. - Click Settings in the Condition - Time box and select 10 minutes. This way tracking stops after 10 minutes. - If you want to stop recording in nVista when you stop behavior tracking, bring a new Action box in the flow line which instructs the system to send out a low TTL pulse to nVista. Make sure that you place the Action box to the right of the 10-minutes time box. Tip: In the Hardware Action box you can test whether EthoVision XT triggers the nVista. To do so, click the Test button. Note: Make sure to instruct nVista/nVoke to record video based on the TRIG signal. Example 2 - Manual Video Recording, Triggered OG-LED Stimulation Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. You start video recording in nVoke manually by clicking the Record button. At the planned time, for example at 10 minutes after start, EthoVision XT sends out a high TTL pulse to the GPIO[n] port of nVoke. In the Inscopix DAQ software, under Video Recording configuration, make sure that Trigger is set to NONE and Control is set to Video Recording ON. Hardware Connections See the scheme on page 344. You do not need to use the TRIG port of the nVoke device. Set the GPIO[n] to Input in the Inscopix DAQ software. Prerequisites in EthoVision XT In the Experiment Settings, you defined the TTL port and output line (either 1 or 2) connected to the GPIO[n] of nVoke. In Arena Settings, you mapped that port to the arena (see page 346). Procedure Because calcium imaging is started manually in this example, you only have to program the activation of the OG-LED. In the following example, the Time condition is set to wait 10 minutes before the triggering action. - In the Trial Control Settings, under Conditions, click the button next to Time. - Specify the time (e.g. 10 minutes). Optionally, edit the name in the Condition name field. - Click OK and insert the Condition box after the Action - Start track box (or wherever it applies in your protocol; for example in a sub-rule). - In the Trial Control Settings, under Actions, click the button next to Custom hardware. - Specify the device (e.g. Device A) and the type of signal (Output 1 High). - Optionally, edit the name in the Action name field. - Click OK and insert the Action box to the right of the Condition box just created. - When applicable, define a Condition and an Action (Output Low) for stopping the trigger action and insert them in the trial control flow line. Notes - In the Inscopix DAQ software, make sure to set the Trigger mode for the GPIO[n] port to Follow. - When the Trigger is set to low, LED stimulation is stopped. To set the Trigger to Low, add an Action to the same device/TTL port and output line as above, and select the signal Output Low. - You can also let the DAQ software run its own pulse protocol while the Trigger is ON. In that case the Control for the GPIO[n] port is set to Pulse protocol. - For more information, see the nVista and nVoke User Manual. Example 3 - Triggered Video Recording and LED Stimulation Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. Both video recording and the OG-LED are triggered by EthoVision XT when the corresponding conditions (time or event) are met. Hardware Connections See the scheme on page 344. Set the GPIO[n] to Input in the Inscopix DAQ software. Prerequisites in EthoVision XT In the Experiment Settings, you defined two TTL lines from the USB-IO box: one connected to the TRIG and the other to the GPIO[n] port of nVoke. In Arena Settings, you mapped the ports/lines to the arena (see page 346). Procedure Define actions and conditions as explained for the previous examples. - Condition to trigger video recording. - Action to trigger video recording through the TRIG port. - Condition to trigger OG-LED stimulation. - Action to trigger the OG-LED stimulation through the GPIO[n] port. When applicable, define additional conditions and actions to stop video recording and OG-LED stimulation. Notes - In the Inscopix DAQ software, make sure to set the Trigger mode for the TRIG port to Follow, and the Control is set to Video Recording ON. In an alternative configuration, you can set Control to Recording schedule to record video for a specific time. - In the Inscopix DAQ software, make sure to set the Trigger mode for the GPIO[n] port to Follow. Select the type of Control you require (e.g. Pulse protocol). - See Example Configuration #3 in the nVista and nVoke User Manual. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-cr6 Chapter: EthoVision XT Create an Experiment For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. If you use PhenoTyper, you can create an experiment from a PhenoTyper template. Choose File > New from Template and in the guided wizard, from the Arena template list, choose PhenoTyper (for one cage) or PhenoTyper quad (for two to four cages). Experiment Settings Choose Setup > Experiment Settings. General Settings - Set Video Source to Live Tracking and select the camera image. - Choose the Tracked Features that apply to your experiment. Use of Trial Control Hardware - Under Trial Control Hardware, select Use of Trial Control Hardware. - Click Settings and choose Noldus USB-IO box. - In the window that appears, locate the TTL port of the USB-IO box that is connected to the LED controller, and from the Device type list choose Custom Hardware. Under Device ID give this device a unique name (for example LED controller 1, or Pulser if you use the Prizmatix Pulser/PulserPlus). - Repeat the previous step if you have more LED controllers or Pulsers. Important: Make sure that Custom Hardware is selected in the Device Configuration window, not TTL Tester or others. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. Arena-Hardware Mapping - Make sure that you have drawn all the arenas. - At the bottom of the Arena Settings window, click the Arena-Hardware Mapping button. - In the Arena-Hardware Mapping window, click Add device one or more times depending on how many physical devices (LED controllers or Pulsers) are connected. - Assign the devices to the arenas: - For setups with one cage (and one device), that is automatically assigned to Arena 1. - For setups with multiple cages (and devices), assign each device to the corresponding arena. - For each row, rename the Device name (for example, rename Device A to LED controller 1 or Pulser 1). Tip: Give devices unique names. That is also handy when analyzing the data and events of specific devices. To Test the LEDs Note: This procedure is only valid for the Basic setup (without Pulser). - In the Arena-Hardware Mapping window, click the row that corresponds to the device you want to test and click the Test button. - Choose Output 1 High and click Test. Check that the LED is activated. - Choose Output 1 Low and click Test. Check that the LED is deactivated. Trial Control Settings In the Trial Control Settings you can program activation and deactivation of the LED controller during the trial. Choose Setup > Trial Control Settings. Below is a simple example showing how to switch on a LED one minute after the start of the trial, keep the LED active for one second, and then switch it off. To Switch On the LED - Under Actions, click the button next to Custom Hardware. - From the Custom Hardware list select the LED controller device (this is the name given under Device name in the Arena-Hardware Mapping window). - From the Action to perform list select Output 1 High (or Output 2 High if you connected the USB-IO box to the LED controller using the cable with the red RCA connector). - Optional: Rename the Action name (for example, rename Hardware act (1) to Start Pulse). - Click OK and insert the new Action box in the Trial Control sequence, usually after a condition. Note: With this Trial Control procedure, the stimulus does not stop unless you insert another Action box that specifies Output 1 Low (see below). To Switch Off the LED After Some Time - Follow the instructions in the previous section to program activation of the pulse. - Under Conditions, click the button next to Time. Select After a time of and enter the duration of the pulse (minimum possible: 0.1 s). Insert the Condition box immediately after the Action box. - Under Actions, click the button next to Custom Hardware. - From the Custom Hardware list select the LED controller device (this is the name given under Device name in the Arena-Hardware Mapping window). - From the Action to perform list select Output 1 Low (or Output 2 Low if you connected the USB-IO box to the LED controller using the cable with the red connector). - Optional: Rename the Action name (for example, from Hardware act (2) to Pulse Off). - Click OK and insert the new Action box after the second Time Condition box. The sequence can be read as follows: one minute after the start of tracking (first box), activate the LED controller (second box), then wait one second (third box) and deactivate the LED controller (fourth box). To Activate the LED When the Animal Is in a Zone It is often required to activate the LED multiple times, for example, every time the subject enters a trigger zone, or every time the subject presses a lever. In such situations you need to create a Subrule that can be repeated indefinitely. The Subrule contains the following instructions: - Check that the subject is in the zone (or the lever is pressed) (a). In this example the condition is based on Current Duration, that is, it becomes true when the subject is found in the zone for a specific time. - When the previous condition is met, turn the LED on (b). - Check that the subject is out of the zone (or presses another lever/performs an action to be linked to the end of stimulation) (c). - When condition (c) becomes true, the Action box switches off the LED (d). Next, the Subrule starts again with condition (a) being evaluated. The Reference box specifies that the Subrule is repeated indefinitely until the end of the trial. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-6oh Chapter: EthoVision XT Arena Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Choose Setup > Arena Settings > ... The zone groups in your experiment depend on what zone template you chose when creating the experiment. - Platform, Quadrants – This zone template creates one arena settings profile with a zone group Platform with zones Platform and Platform Zone (the zone around the platform) and a zone group Quadrant with a zone for each quadrant. - Platform, Quadrants, Corridors, Border – This zone template creates four arena settings profiles, one for each quadrant. The South-West Platform profile, for example, contains a zone group Platform with zones Platform and Platform Zone (the zone around the platform), a zone group Quadrant with a zone for each quadrant, a zone group Thigmotaxis with zone Border Zone, and a Whishaw's corridor for the other quadrants than the one with the platform. Whishaw's corridor is an 18-centimeter wide path from the starting location to the platform. This corridor is designated as the correct route and if a rat deviates from this route at any point it receives a maximum of one error on that trial (Whishaw's error). To be able to determine whether the animal deviates from this route, you should define the rest of the arena as an Outside corridor zone. A Whishaw's corridor is defined for each release point you use. By creating separate Arena Settings for each corridor, you can select the appropriate Arena Settings for data acquisition depending on the release point for that trial. To resize and reshape a zone, click first the Point edit mode button on the toolbar, then move the corners of the zone outline. Hold Shift to keep the same aspect ratio of the shape. Hold Ctrl to enlarge/reduce the shape size in all directions. Zone for Analyzing Thigmotaxis To quantify thigmotaxis, that is, persistent swim along the wall of the pool, create an additional zone group, and draw a circle which should be the internal margin of the zone. Place the zone label between this circle and the outline of the arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings > Open one of the following: - Default (No Max Duration) – When you use this profile, tracking stops when you click the Stop trial button. - Max Track Duration 1 Min – When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the maze. The track stops automatically when the center-point of the animal has been in the zone Platform for at least 5 seconds, or when 60 seconds have elapsed since the start of the track. - Max Track Duration 2 Min – When you use this profile, tracking stops when the center-point of the animal has been in the zone Platform for at least 5 seconds, or after 2 minutes if the animal does not find the platform within that time. Using an Adjustable Platform If you use an adjustable platform you can define an action to raise the platform when the animal swims around the platform. Note that you need the Trial & Hardware Control module to be able to control the platform. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Check in the Video Section that the sample rate is set to 5 samples/second (for rats) or 12.5 samples/second (for mice). Advanced Detection Settings If detection of the subject is not optimal after using the Automated setup function, do the following: - Check that either Dynamic Subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals. - When using Dynamic Subtraction – Move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. Specify the Current frame weight. A low value (for instance, 10–20) usually works well. - When using Differencing – Set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. For more information, see Configure Detection Settings in the EthoVision XT Help. Trial List Choose Setup > Trial List. Defining Independent Variables Enter your independent variables such as: - Subject ID with the ID of your animals as predefined values. - Phase with Training and Probe as predefined values. - Treatment with Treated and Control as predefined values. - Dose with numerical values (e.g. 0.1 mg/kg, 0.5 mg/kg, etc.) - Day After Treatment (with values 1, 2, etc.) - Name of the Experimenter, etc. Making a List of Trials If you want, you can pre-define all your trials here. Click the Add Trials button. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Specify the values of the independent variables in advance, or enter them as you carry out the trials. Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-2jh Chapter: EthoVision XT Experiment Settings Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. To detect freezing behavior, select Activity analysis under Analysis options. Click the video button next to it and watch the video tutorial to learn about Activity analysis. If you work with rats or mice, you can let EthoVision XT automatically detect behaviors like Rearing, Grooming, and Sniffing. Select Behavior recognition under Analysis options and choose the options that apply to your experimental setup. The Behavior recognition option is only available if you have the Rat Behavior Recognition module or the Mouse Behavior Recognition module of EthoVision XT. Manual Scoring Settings Choose Setup > Manual Scoring Settings. If you used the template for an open field experiment, two start-stop behaviors have been predefined in the manual scoring settings. These are the behaviors rearing and grooming. Depending on your research question, you can add other behaviors that can be manually scored, like defecating, which is a measure for anxiety, and urinating and vomiting. Note that with the Rat (or Mouse) Behavior Recognition module you can have EthoVision XT detect a number of behaviors automatically. For more information, see Manual Scoring Settings and Behavior Recognition in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. Arena Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. Tip: If you create an experiment from scratch, the arena is not yet defined. Click 2. Select Shape and Draw Arena and choose the drawing tool. If you want to have the open field divided in quadrants, choose one of the subdivided tools. Depending on the shape of your open field, draw the outline of the arena and select the number of sectors. Each sector is automatically defined as a zone. Zone Group "Borders" Check that the 'Wall' zone covers only the wall of the open field. If necessary, adjust the center zone and the border zone. Zone Group "Quadrants" Check that the zones 'NW', 'NE', 'SE', and 'SW' divide the 'Floor' zone in four equal quarters. Zone Group "Squares" Check that the zones divide the arena in equal squares. Arena Settings for Rat/Mouse Behavior Recognition When you selected Behavior recognition in the Experiment Settings (only available when you have the Rat or Mouse Behavior Recognition module of EthoVision XT), defining a few special zones and points significantly increases behavior recognition accuracy. - Feeder zones: To detect eating at the feeder. - Drinking spout points: To detect drinking. - Wall zones: To detect rearing to wall and to discriminate this from unsupported rearing. For the exact procedure, see Zones and Points for Behavior Recognition in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the data acquisition. Choose Setup > Trial Control Settings. Default Trial Control The templates for the open field contain two Trial Control Settings profiles: - Default: Track duration 10 (or 30) min — When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the arena. The track stops automatically after 10 or 30 minutes. If you use Behavior Recognition or Activity Analysis, the default Trial Control rule is slightly different. See Trial Control in the EthoVision XT Help. To Stop Acquisition After a Specific Time Open a Trial Control Settings profile, click the Settings button in the Condition - Time (1) box, and set the time you require. Traditionally, the open field test had a duration of between 2 and 10 minutes. This short length of time was chosen in the past because the data were acquired manually. It also emphasizes the exploratory behavior and response to novelty, rather than baseline activity of the rodents. Technology like video tracking with EthoVision XT allows for much longer periods of monitoring. Detection Settings Choose Setup > Detection Settings. Sample Rate Under Video, set the sample rate. Common values, expressed in number of images analyzed per second, are: - For rats: 5 samples/s. - For mice: 12.5 samples/s. - For nose-tail tracking of all rodents: 25 to 30 samples/s. - For adult zebrafish: 5 samples/s. Remember that the optimal sample rate depends on a variety of factors, including the characteristics of the setup, and even the animal's strain and behavior. Faster animals need a higher sample rate. If the fish shows very rapid movements, set the sample rate to the maximum; in other cases a sample rate of 5 fps may be enough. To Detect Freezing Behavior Open the Activity section in the Detection Settings pane. This option is only available if you selected Activity analysis under Analysis options in the Experiment Settings. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold so that when the animal is completely still, those pixels are almost completely absent. Rat or Mouse Behavior Recognition If you selected Behavior Recognition in the Experiment Settings (only available when you have the Rat or Mouse Behavior Recognition module of EthoVision XT), remove the tail from the detected body contour. To do so, in the Detection Settings pane: - Under Subject Contour, select one or more pixels for the first Erosion field until the tail is no longer detected. The detected body area (shown in yellow) will appear smaller. - Increase the Dilation filter until the detected body area is the same size as before. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt Chapter: EthoVision XT Create the Experiment - Start EthoVision XT and choose File > New from template. - In the Select a template option window, select Apply a pre-defined template. Next, follow the instructions in the guided setup. For more information, see Set Up an Experiment in the EthoVision XT Help. For details on connecting the camera, see Camera Installation in the EthoVision XT Help, or watch the video tutorial Set Up the Camera (Help > Video Tutorial). - Enter the name of the experiment and click OK. - Before you can actually acquire data, check the settings listed in the rest of this section. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. Note: The option Deep learning is only available if your PC has a graphic processor (GPU) that supports additional software (CUDA). See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. - Click Grab to grab an image of the empty enclosure from the camera image, or click Browse to select a video file and then click Grab. - Click 1. Draw Scale to calibrate your arena. - Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. For open fields and other enclosures, remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. - Tip: If you need to rotate the outline of the arena, drag around all elements, then click the Rotation mode button and move the outline until it matches the arena in the video image. - Tip: If you need to reshape the outline of the arena, click the Point edit mode button and move the vertices of the outline. - To draw zones, click 3. Select Shape and Draw Zones. See more details in the chapter about your test. For details, see Arena Settings in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of data acquisition. For details, see the EthoVision XT Help. Choose Setup > Trial Control Settings. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. - If you work with pre-recorded video, select a video file. If you work with the live camera image, release the animal in the arena. - Click Automated Setup. - Select: - Rodent for tracking rats and mice. - Adult fish for tracking fish from the top view. - Other for any other case such as tracking insects, crustaceans, or when tracking fish from the side view. - When the subject does not move a lot and is far from the enclosure walls and other objects, draw a rectangle around it. EthoVision XT detects the subject. - If the subject's body is well detected (marked in yellow), click Yes. - In other cases, move the Finetune slider or click No and adjust the Advanced Detection Settings. Note: The Automated Setup may not work in all situations. If the subject is not detected correctly, see the Advanced Detection Settings below. Advanced Detection Settings - Under Video, choose the sample rate. - Under Method, check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if other methods do not work well, or if you work with hooded animals. - Select the tracking method. The options available depend on your experiment settings, including the number of body points you want to track. The optimal method is automatically selected after choosing the type of animal in the Automated Setup. For more information, see Tracking Methods in the EthoVision XT Help. - When using Dynamic subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. When using Differencing, set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. For More Information: - Choose Help > EthoVision XT Help and search for Advanced Detection Settings. - Choose Help > Video Tutorial and watch the videos under How Subject Detection Works. Trial List Choose Setup > Trial List. Enter your independent variables such as rat ID, first or second phase of the experiment, treatment (with values drug vs. control), dose, type of object, name of the experimenter, etc. If you want, you can pre-define all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them, and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a Series of Trials in the EthoVision XT Help. Protocols on the Web Featuring EthoVision XT Researchers are encouraged to publish test protocols to improve reproducibility of animal experiments. Browse to https://www.bio-protocol.org/en/searchlist?content=ethovision to find protocols created with or mentioning EthoVision XT. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-lIz Chapter: EthoVision XT Create an Experiment For Live Mouse Tracker - Choose File > New and in the dialog that opens select Live Mouse Tracker experiment. - For the rest of the procedure, see the EthoVision XT Help. For All Other Cases Choose File > New From Template and choose a predefined template in the guided setup. See below. Experiment Settings Choose Setup > Experiment Settings. - Under Video Source, click the video icon in the camera row and adjust the camera settings if necessary. - Under Subjects, specify the Subject roles (for example Resident or Intruder, or Subject 1 and Subject 2). Do not enter the ID of the individual animals. - Under Tracked Features, select the option that corresponds to your needs. In most cases that is Center-point, nose-point and tail-based detection. - Under Body Point Detection Technique, select Contour-based if you use color-marked animals, or Deep learning if your subjects look different (e.g. the back of one individual has been partially shaved). Note: You can use Deep learning to track two subjects per arena. The Deep learning technique works if you have a recent graphics card and the driver is up to date. Manual Scoring Settings Choose Setup > Manual Scoring Settings. Here you can define behaviors that you score manually, for instance by pressing a keyboard key. In the template experiment, two start-stop behaviors, Rearing and Grooming, have been defined. Define other behaviors if needed, for example Sniffing and Boxing. For more information, see Set Up an Experiment > Manual Scoring Settings in the EthoVision XT Help. Trial Control Settings Choose Setup > Trial Control Settings > New. In the Trial Control Settings, define conditions for the start and stop of the track. - Starting condition: For instance, 'Start tracking 5 seconds after both animals are detected in the arena'. If you are tracking live, this 5-second delay enables you to put both animals in the arena and to take out your hand before tracking starts (5 seconds might not be enough; check beforehand how much time you need). - Stopping condition: In order to be able to compare the tracks in the analysis, they must have the same length. Either define a Maximum Trial duration or a Stop track condition based on time. Tip: To make sure that tracking starts when both individuals are in the arena, not before, click Settings in the Condition box before the Start track box. Select Current Duration from the Statistic list, then click Settings and then Actors. Select both subject names and select All selected subjects from the list. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Important: Follow the instructions in the order described below. If you selected Deep learning in the Experiment Settings, set the sample rate (below), and skip the next steps. The software is able to recognize the subjects automatically so you do not need to adjust subject contrast, size, contour filters etc. Sample Rate Click Video. Select a high sample rate: 25 (for PAL analog cameras) or 30 (for NTSC analog cameras and digital cameras) samples per second. Automated Setup Once the animals are in view, click Automated Setup. Select the type of animal you are going to test. Click Next and draw a rectangle around each subject. Make sure that you do this when the animals are not in close contact. If detection of the subject is not optimal after using the Automated Setup function, see Configure Detection Settings in the EthoVision XT Help for details on the advanced detection settings. Subject Identification for Color-Marked Subjects If you mark animals with colors, under Subject Identification make sure that Marker-assisted identification is selected. - Put the marked animals in the arena or play the video. Make sure to select a point in the video where the animals do not touch each other. Alternatively, place the animals in the arena one at a time. - In the Subject Identification section, select one of the subjects and click the Identification button. As a result, the Identification [Subject name] window opens. - Move the mouse pointer to the Video window so the pointer becomes an eyedropper. Move the eyedropper over the color marker of the subject you want to identify and click the left mouse button. - Fine-tune the color settings by adjusting the Hue, Saturation and Brightness in the Identification [subject role name] window. Change the range of color settings by changing the numbers or by resizing the Hue box on the vertical color bar, or resizing/moving the box in the color map (horizontally to adjust Saturation, vertically to adjust Brightness). As a result, the outline covers (almost) the complete marker. - Next, play the video to see in the Video window whether the marker is detected correctly in different parts of the arena. If the marker 'dances' then your color settings are too sensitive. Go back to step 4 and make the box larger. - When you are finished fine-tuning the color settings, continue with setting the Minimal marker size: increase the Minimal marker size until, first, noise is not detected anymore and, second, the marker is not detected anymore (as a result, the outline in the Video window disappears). Now enter a value for the Minimal marker size that is somewhere in between. - Click OK when you are done and repeat steps 1–6 for the other subjects. For details, see Advanced detection settings for color marks in the EthoVision XT Help. Also watch the video Identification Settings in the EthoVision XT video tutorial. Set the Subjects' Contrast Make sure you have selected the correct contrast and check the following: - When you use Static Subtraction or Dynamic Subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. - For Dynamic Subtraction, set the Current frame weight slider to a value between 1 and 5 to compensate for the changes in the background with time. - When you use Differencing, adjust the position of the Sensitivity slider. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-8nl Chapter: EthoVision XT EthoVision XT In EthoVision XT, you can set up a radial 8-arm maze experiment by using a predefined template in the guided setup. Create an experiment. For details, see Chapter 1 of this manual, or see Setup an Experiment in the EthoVision XT Help. Experiment Settings - Make sure that the radial maze is connected to the EthoVision XT computer. To connect the radial maze to EthoVision XT, you must have the Trial and Hardware Control add-on and the USB-IO box. The procedure and the necessary cabling may differ between manufacturers of the radial maze. Please see the accompanying documentation. - Choose Setup > Experiment Settings. - Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. - If you want to use Deep Learning technique to track the subject's nose, under Body Point Detection Technique choose Deep Learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. - Under Trial Control Hardware, select Use of Trial Control Hardware and click Settings. Select Noldus USB-IO Box. - In the Device Configuration window, for TTL ports 1 to 4, under Device Type, select Custom Hardware. Next, type in Doors1&2 for TTL Port 1, Doors3&4 for TTL Port 2, Doors5&6 for TTL Port 3, and Doors7&8 for TTL Port 4. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. - In the Grab Background Image window, click the Grab button to grab a background image of the radial maze from the camera image. - Click 1. Draw Scale to calibrate your arena. For details, see Make the Arena in the EthoVision XT Help. - Click 2. Select Shape and Draw Arena and check that the predefined arena has the correct shape and size. If necessary, adjust the contour of the arena to fit the radial maze. - If you used the Zone template, click 3. Select Shape and Draw Zones. Check that the zones have the correct shape and size. If necessary, resize or add new zones. - If you are using automated doors, click Arena - Hardware Mapping in the Arena Settings window to assign the doors to the arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings > Open one of the following: - Default (No Max Duration) - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the Center zone. Tracking stops manually (for example when you click the Stop Trial button). - Track Duration 10 Min - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the Center zone. The track stops automatically when 10 minutes have elapsed since the start of the track. Controlling Automated Doors If you want to control the automated doors with EthoVision XT, you need to create new Trial Control Settings. An example of Trial Control Settings for a protocol as described in Unit 8.5A of Current Protocols in Neuroscience (2004) to test basic working memory is the following: - Start Condition: We assume that the animal is released in the Center zone with all doors closed. Tracking starts 3 seconds after the animal is put in the Center zone. - Opening All Doors Simultaneously: You can create a Sub-rule with a Reference for this. In the Sub-rule, each door is opened. For each door, you need to create a separate Hardware Action box, with the corresponding Device name (e.g., 1&2) and appropriate Action (Output 1 High which opens door 1). The Reference box to the Sub-rule is activated immediately after the Start Trial command. - Closing and Then Opening All Doors: When the animal has visited the Goal zone of one of the arms and returns to the Center zone, all doors are closed and re-opened after 5 seconds. You can create a Sub-rule with a Reference for this. In the Sub-rule, you need to create a Zone Transition Condition for each arm separately. All eight Zone Transition Conditions need to be connected to an Operator Any Input True. Next, with a Hardware Action box, all 8 arms are closed. Put the Hardware Action box for all doors in a sequence similar to opening doors as described in the step above. - Stop Condition: The trial stops when the animal has visited the Goal zones of all 8 arms OR after 15 minutes have elapsed since the start of tracking. - For the first criterion (the animal visits the Goal zone of all arms), use an In Zone Condition for each Goal zone. All eight In Zone Condition boxes are connected to the Operator Num Simultaneously True Inputs. - For the second criterion (after 15 minutes), you need a Time Condition box. - The two criteria must be combined with OR logic. The Time Condition box and the Num Simultaneously True Inputs Operator box are connected to an Any Input True Operator box. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Advanced Detection Settings - Under Video, check that the sample rate is set to 25 or 30 samples/second for multiple body-point tracking. - Click Advanced. - Under Method: - By default, Static Subtraction is selected as the detection method and Rodents / Default as the method for nose-tail detection. The background in a radial maze test usually does not change much, so Static Subtraction usually works well. Make sure the lighting is even and there are no shadows in the maze. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-ru6 Chapter: EthoVision XT Experiment Setup Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. Under Analysis Options select Activity Analysis. Click the video button next to it and watch the video tutorial to learn about Activity Analysis. Activity is a useful feature that helps you detect changes in the movement patterns of the subject. Manual Scoring Settings EthoVision determines the behavior of your subjects automatically on the basis of the intensity of the subject's movement. This means that you do not have to manually score the subject's behavior. However, if you want to compare the data scored by EthoVision XT with your own ratings, define behavioral categories under Manual Scoring Settings. Next, during acquisition watch the video and score those categories during your trial. You can also edit the data after acquisition. Procedure: Choose Setup > Manual Scoring Settings. - To add a behavior, click the Add Behavior button. Enter a name for that behavior (for example, Struggling) and specify Mutually Exclusive as the behavior type. Specify the name of the behavior group (for example, Behavior Categories). - Add the remaining behaviors to the same group. We advise you to create three categories for scoring the animal's mobility levels, which correspond to the three possible states of the Mobility dependent variable in EthoVision XT: - Immobile (corresponding to EthoVision XT's Immobile state) - Swimming (corresponding to Mobile) - Struggling/Climbing (corresponding to Highly Mobile) Arena Settings - Choose Setup > Arena Settings > Open Arena Settings 1. - Click 2. Select Shape and Draw Arena and check that the pre-defined arenas have the correct shape and size. If necessary, adjust the contour of the arena to fit the cylinders. Important: If you work with multiple cylinders and use Activity Analysis to quantify the animals' behavior, make sure that the arenas have the same size. You can check this under Shape Size and Position in the Arena Settings window. - Click 3. Select Shape and Draw Zones. Check that the zones (if you used a Zone template) have the correct shape and size. If necessary, draw additional zone groups or zones. For details, see Arena Settings in the EthoVision XT Help. Trial Control Settings Choose Setup > Trial Control Settings and open one of the following profiles: - Default: Tracking starts 1 second after the animal has been detected in the arena. Tracking stops manually (for example, when you click the Stop Trial button). - Max Track Duration 15 Mins: Tracking starts 1 second after the animal has been detected in the arena. Tracking stops automatically after 15 minutes or when the animal has been in the Diving zone for over 1 second. You can use these Trial Control Settings for the pre-test session. - Max Track Duration 5 Mins: This profile is similar to the previous one, but the maximum tracking duration is 5 minutes. You can use these Trial Control Settings for the test session. If you need more time to put an animal in its cylinder, increase the number of seconds. This prevents detection of your hand or arm from starting tracking. The Start Condition works independently for each cylinder. When you work with multiple arenas, trial control is applied to each arena separately. Therefore, tracking may start at different times in different arenas, depending on when the animal is released. Detection Settings Important Note: For stable detection, the extremities of the animal (paws and tail) must be either always included with the tracked body or always excluded from it. If the paws and tail are temporarily excluded and then included again during data acquisition, these changes affect the variables Mobility and Movement, while the animal might not actually be mobile or moving. The variable Activity is not affected by such changes, because it is based on the image change in the whole arena, not the change in the detected subject. - Choose Setup > Detection Settings > Detection Settings 1. - Under Video, choose a Sample Rate of 5 samples/second (for rats) or 12.5 samples/second (for mice) or higher. - Click Advanced. - Under Method, choose Dynamic Subtraction. Under Detection, verify you selected the correct contrast. Move the slider to define the animal's contrast. The animal's body must be fully detected in all parts of the arena and the noise must be minimal. Set the Current Frame Weight slider to a value between 1 and 5 to adjust the number of past images that contribute to the reference image. - If the limbs and tail are not included in the detected body and you want to include them, under Subject Contour select the Dilation filter, then the second Erosion filter. Leave the first Erosion filter at zero. Adjust Dilation and Erosion to achieve stable detection. - Under Subject Size, click Edit. Define a Minimum Subject Size to prevent small objects like droppings from being detected. - If you intend to use Activity Analysis to score the behavior of the subject automatically, click Activity. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold so that when the animal is immobile, those pixels are almost completely absent. Set Compression Artifacts Filter to On if you work with pre-recorded video. Trial List Choose Setup > Trial List. Enter your independent variables such as rat ID, Session Type (with values Pretest or Test), Treatment (with values Drug vs. Control), Dose, Time of Drug Administration, Name of the Experimenter, etc. For variables which differ between subjects, select Subject as the scope. You can pre-define all your trials by clicking the Add Trials button, or enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them, and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a Series of Trials in the EthoVision Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-continued-0Vs Chapter: EthoVision XT EthoVision XT Settings Background Changes Adjust the slider until the subjects are properly detected. From the Background changes list, select an option that reflects your conditions (usually, Medium slow works just fine). Contour Erosion/Dilation You need Contour erosion/dilation to get a smooth contour without the tail for accurate modeling and to remove individual pixels of noise. To improve detection, open the Advanced section in the Detection Settings pane. Under Subject Contour, select one or more pixels for the first Erosion filter and the Dilation filter. Leave the second Erosion filter to zero. Increase the number of pixels for Erosion until the animal's tail is removed, then increase Dilation until the entire animal's body contour is detected. Subject Size Before you set the Subject Size, make sure the animals are properly detected and do not touch each other. Click Subject Size, then click Advanced. - Under Modeled subject size, make sure the Apply to all subjects and Fix (for all subjects) options are selected. - Click the Grab button. This adjusts the Average size to the Current size. - Repeat clicking the Grab button until the body fill completely fits the animal. Shape Stability and Modeling Effort The Shape stability setting is used when you track animals whose body can be occluded by, for example, cage bars or part of the body of another animal. - When you set the slider closer to Occlusions, EthoVision considers separate objects that are close together part of one animal. - When you set the slider close to Noise, EthoVision considers separate smaller parts not part of the animal. The Modeling effort setting is used when two animals touch and EthoVision loses the separate shapes. At this point, EthoVision tries to determine which part of the large merged blob belongs to either animal, using a lot of processor load in the process. - When you set the slider close to Performance, EthoVision is only allowed a short time to determine which part of the merged blob belongs to which animal. Therefore, modeling quality is low. - When you set the slider to Modeling, EthoVision is allowed a longer time to determine which part of the merged blob belongs to which animal. Therefore, modeling quality is good, but this costs a lot of processor load. If you track from video, video tracking slows down. Trial List Enter your independent variables such as rat ID, treatment (drug vs. control), dose, name of the experimenter, etc. You can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them, and then paste the values into your Trial List. Notes - When using color markers, add a Marker color variable to the Trial List to specify the marker color you assigned to each Subject role. This is useful when you have defined, for example, the Subject name Experimental and Stimulus, or Subject 1 and Subject 2, and you have randomly assigned the marker colors to the Subject roles. - You can define a series of trials for batch acquisition. See Acquire a series of trials in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-continued-XdU Chapter: EthoVision XT EthoVision XT (Continued) If after running some test trials, you get nose-tail swaps, try using the tracking method Rodents / For occlusions. If you selected to use the Deep learning technique to track the subject's nose, next to Deep learning click Define and select a box around the subject. Make sure that the box includes the subject's nose. For details, see the EthoVision XT Help. - Optional: Select Track noise reduction. Under Smoothing, set Track noise reduction to On. In some cases better quality tracking can be obtained by reducing track noise during acquisition. This may especially be the case if you use Trial and Hardware Control. As an example, if the center point of an animal is detected in the center-zone of the maze, you want specific doors to open followed by the closing of doors as soon as the animal enters one of the arms. If the detected center point is moving rapidly because of noise, this may result in doors opening and closing every time the center point crosses the border of the zone. Track noise reduction may solve this problem. - Under Subject size, click Advanced and set a minimum subject size to prevent droppings from being detected. Trial List Enter your independent variables such as Animal ID, Treatment, Baited arms, Name of the experimenter, etc. (for blind trials, enter only the Animal ID). If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a series of trials in the EthoVision XT Help. Baited Arms To mark the trials with the arms that were baited, create an independent variable Baited arms of text type, and define the various combinations as Predefined Values: for example, 1-3-6-8, 1-3-5-7, etc. For each subject to be tested, assign the correct value in the appropriate cell of the Baited arms column. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-continued Chapter: EthoVision XT The Open Field Test Behavior Section Configuration Next, open the Behavior section in the Detection Settings pane. Wait until the rat has a normal, straight, posture (so not bending or rearing) and is moving forward. You should see the hips of the rat moving. Click Grab and check that the body contour is correct. You can also enter the values manually if you know them from previous experiments. However, in this case make sure that the conditions are equal, like lighting, size of the animal and distance between the animal and the camera. Body Detection Requirements - The detected body must have a minimum length of 60 pixels (sum of nose-point to center-point and center-point to tail-base) for Behavior Recognition. - The detected body must also be smaller than half the arena size. For more information, see the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-ethovision-xt-continued-qMW Chapter: EthoVision XT Optogenetics Experiments Detection Settings Choose Setup > Detection Settings. We assume that you followed the procedure in detection settings on page 17. Set the Sample Rate In the Video section, check that the sample rate is set to: - Rats: 5 samples/second. - Mice: 12.5 samples/second. However, when tracking the nose-point, center-point and tail-base point of the rodents, always choose the highest possible sample rate, for example 25 or 30 samples/s, depending on your camera. Remove the Effect of Cables and Fibers When working with physiology and optogenetics setups, the cables and fibers often make detection of the subject impossible with the default settings. To filter fibers out of the video image, use the Subject Contour options. If the fiber is the same color as the subject, then increase the value in the first Erosion filter until the fiber is no longer detected. Increase Dilation to make the entire body fully detected. Leave the second Erosion filter to zero. If the fiber has a different color and "cuts" the yellow blob in two, try first Dilation, and then increase the second Erosion filter. In Zone Conditions and Zone Exit Threshold When the previous condition is met, turn off the LED. Note: You can also base the "In Zone" conditions on the statistic "Current". However, in such case when the subject walks along the zone border its center point will jitter between somewhere outside the zone and inside the zone. For this reason the "Current" value of the In Zone variable will rapidly change from true to false and vice versa, therefore the conditions based on this variable become true and false very often. To prevent this from happening, in the "In Zone" Condition window click Settings and enter a Zone exit threshold. This way the subject is still considered in the zone (Current In Zone = true) if its body point is found within the threshold distance from the zone border. The subject is only considered out of the zone (Current In Zone = false) if it crosses the threshold. Tip: Reduce the zone by a distance half of the exit threshold. For example, if the exit threshold is 4 cm, reduce the zone border by 2 cm. This way you do not overestimate the size of the zone when using the exit threshold. For details, in the EthoVision XT Help see Dependent Variables in Detail > In Zone. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Experiment In Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-experiment-in-ethovision-xt Chapter: EthoVision XT Experiment in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. If you want to use the Deep Learning technique to track the subject's nose, under Body Point Detection Technique choose Deep Learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings Choose Setup > Manual Scoring Settings. If you used the template for an open field experiment, two start-stop behaviors have been defined: - Head Dipping – to record manually the head dips over the edge of the open arms. - Rearing – to record manually the posture of the animal with forelimbs lift off the floor. Note that EthoVision XT does not detect rearing automatically in an Elevated Plus Maze. You must score rearing manually in order to record it. You can define more behaviors, like scanning. Stretched posture can in principle be detected automatically by using the Elongation variable in EthoVision. Notes About Head Dipping By head dipping we mean protruding the head over the ledge of an open arm and down towards the floor. This response can occur while the animal's body is in the closed arms, central square, or open arms. You can also let EthoVision count the number of times or the total time that the nose point is found within the head-dipping area (provided that this has been chosen in the template). This also quantifies the risk-assessment behavior. For a more reliable scoring of head dips, you could place a camera in front of each open arm to film the arm's side-view. You can record video from multiple cameras using the software Noldus MediaRecorder. If you film the side-view of the open arm, you can in principle record head-dips automatically with EthoVision by defining a zone immediately below the arm's floor. For these videos you need to create additional Arena Settings and Detection Settings. For more information, see Set Up an Experiment > Manual Scoring Settings in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > open Arena Settings 1. Arena Check that the arena covers the whole area in which you want to track the animal. - Remember to include enough space around the open arms so that the animal is still tracked when it dips its head off the edge of those arms, and the inner side of the walls to track the entire animal when it rears. - Exclude any bright reflective rims that might interfere with tracking. - Make sure the label Arena 1 stays inside the arena. To adjust the contour of the arena to the plus maze in the video image, do the following: - Click the Normal Mode button on the toolbar and drag the arena contour until it is centered on the plus maze. - Click the Point Edit Mode button. Click one of the corners of the arena and drag the mouse to move the corner to the position you require. If you use video files, select the aspect ratio correction that applies. For more information, see Adjust the Video Aspect Ratio in the EthoVision XT Help. If you use the live camera image or the video was recorded with EthoVision XT in the same experiment, you can skip this step. Zone Group: Arms Check that each arm zone covers the corresponding sector of the plus maze. To make sure that a zone is limited to the actual arm, move the label of that zone until the arrow points outside the zone. The color of the zone should change. If the color changes for a wider area of the plus maze, it means that the zone label also pointed to that area. Use the edit functions to move and reshape the zone. For details, see Move, Rotate and Resize a Shape in the EthoVision XT Help. Do not forget to place the arrow of the zone label back in its original position. If the zones Closed Arms predefined in the template overlap with the open arms of the plus maze, rotate the entire arena and zones: - Drag around all the shapes so they are selected. - Click the Rotation Mode button. Click in the middle of the arena and drag the mouse to rotate it. - Click the mouse pointer icon on the toolbar to exit the rotation mode. Zone Groups: Open Arms, Closed Arms, Head Dip Zone These are cumulative zones. They are defined automatically from the sum of the open arms, the closed arms, and the head dip zones, respectively. Trial Control Settings Choose Setup > Trial Control Settings. In the Trial Control Settings you can define conditions for the start and stop of the track. The template contains two trial control settings profiles: - Default - Track Duration 5 Mins – When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the plus maze. The track stops automatically after five minutes. Detection Settings Choose Setup > Detection Settings. In the Detection Settings window, check in the Video Section that the sample rate is set to: - Rats: 5 samples/second - Mice: 12.5–15 samples/second - Nose-Tail Tracking: 25–30 samples/second See Configure Detection Settings in the EthoVision XT Help for details on the advanced detection settings. If you use hooded animals, use the detection method Differencing. If the plus maze has barriers above the arms, the animal may not always be well detected. To improve detection, open the Advanced section in the Detection Settings pane. Under Subject Contour, select one or more pixels for the Dilation filter and the second Erosion filter. Leave the first Erosion filter set to zero. Select more pixels for Dilation than for Erosion (for example, 3 vs. 1) until the entire animal's contour is detected. Trial List Choose Setup > Trial List. Do one of the following: - Click Add Variables and enter your independent variables such as Animal ID and Treatment (with possible values Treated, Control, Sham, etc.), Dose, Name of the Experimenter, etc. Each trial will receive only one value per variable. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Experiment In Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-experiment-in-ethovision-xt-r6x Chapter: EthoVision XT Experiment in EthoVision XT Prerequisites Make sure that all devices are connected and powered up. Create an EthoVision XT Experiment - Start EthoVision XT and choose File > New From Template, then click Apply a pre-defined template. - On the How is the arena configured page, select: - If you work with one or two cubicles, Fear Conditioning System cubicle. Next to Number of arenas, select the appropriate number. - If you work with four cubicles, Fear Conditioning System cubicles. Next to Number of arenas, select the appropriate number. Note: This template does not include pre-defined zones as they are not used often in Fear Conditioning. - When asked How many subjects per arena will you track, select subject. - Complete the guided procedure and give the experiment a name. Click OK. Experiment Settings Cameras - Choose Setup > Experiment Settings. - Under Video Source, next to Number of sources, select how many cameras (one per cubicle) you are working with. In the list under Source, select the name of each camera. The IP address should indicate which camera belongs to which cubicle, provided that you have assigned IP addresses accordingly. - Next to Merged camera view, select 800 x 600 (cropped view of the cage) or 1280 x 1024 (full view of the cage). Number of Arenas and Tracked Features Important: Do this before selecting the Ugo Basile FCS in the Trial Control Hardware Settings. - In the Experiment Settings, under Arenas, select the Number of Arenas you use, that is, the number of cubicles (1 to 4). - Under Tracked Features, in most cases Center-point detection will suffice for fear conditioning experiments. Activity Analysis for Freezing Detection - In the Experiment Settings, under Analysis Options, select Activity analysis if you want to analyze freezing behavior. Tip: Click the Video Tutorial button next to that option for an overview of Activity analysis. Specify the Ugo Basile Fear Conditioning System Important: Ensure you have already selected the number of arenas. Make sure that Number of Arenas selected corresponds to the number of FCS cages used in that experiment. Only after that, follow the instructions below. - In the Experiment Settings, under Trial Control Hardware, select Use of Trial Control Hardware, and click Settings. - In the Hardware Interface window, select Ugo Basile F.C. Controller. - In the Fear Conditioning System COM Port Settings window, click the Add button. - Select a COM port and click OK. Repeat this step to add the COM ports connected to all the FCS cubicles. - For a setup with the Ugo Basile USB Hub and four cubicles, add COM11, then COM12, COM13, and COM14. - For a setup with one cubicle connected directly to the PC, select the COM port associated with that cubicle. If you have created the experiment from a template, there may be one or more COM ports already selected in the Fear Conditioning System COM Port Settings window. If they do not match those associated with the cubicles of your setup, delete them and add the correct ones. - When finished, click OK and proceed with arena settings. Important Notes: - Take note of which cubicle is connected to which COM port. - Make sure that only the necessary COM ports are added. If you accidentally added a wrong COM port, select it and click Delete. - When adding more COM ports in the Fear Conditioning System COM Port Settings window, start with the port for cubicle 1. Disconnect cubicle 1 and see which COM port disappears from the Windows Device Manager. Reconnect the cubicle and add that COM port. Repeat those steps for cubicles 2, 3, and 4. COM Port Communication To determine which COM port is associated with a specific cubicle, do the following: - In Windows, open the Device Manager. Choose View > Devices by type. - Open the item named Ports (COM and LPT). If the cubicles are connected physically to the PC through the Ugo Basile USB Hub and powered up, you should see one to four items labeled USB Serial Port (COMx): COM11 to COM14. Tip: If you do not see the Ports item, from the View menu of the Device Manager select Devices by type. - Disconnect the USB cable from one of the FCS cubicles. - Look at the Ports (COM and LPT) list. The item that has disappeared is the COM port currently associated with that cubicle. Tip: Number the FCS cages and cubicles, and take note of which COM port is linked with each cubicle. This makes troubleshooting easier. If, after disconnecting a cubicle, a COM port other than the expected one disappears from the list, it may be that cables are swapped between the ports in the USB Hub and the corresponding cubicles. Arena Settings: Define the Arenas Create and Calibrate the Arenas - Choose Setup > Arena Settings. - Grab a background image from the cameras, calibrate, and draw the arenas. For details, see Arena Settings in the EthoVision XT Help. Tip: To quickly calibrate, draw lines between opposite walls of the cage, next to the grid, and enter 17 cm (the cage width). - If the image of a cage is not centered, see Camera Orientation for guidance. - Proceed with declaring the FCS devices for each arena. Arena Settings: Declare the FCS Devices Follow this procedure to specify the FCS devices that you want to use for each cage (arena). - In the Arena Settings, click the Arena – Hardware Mapping button at the bottom-right corner of the EthoVision XT screen. - The Arena - Device Mapping window opens. This window lists under Device groups the FC systems connected to the COM ports currently declared. The second column, Arena, lists the arenas currently associated with each system. - Check carefully that the name of each arena matches the physical FC system and the COM port associated with it. If they do not match, select the correct arena name under Arena. - Once you are ready, click OK. The Arena-Hardware Mapping window opens. This window lists the names of the actual devices that EthoVision XT can control. By default, each device is uniquely associated with an arena. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Experiment In Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-experiment-in-ethovision-xt-continued Chapter: EthoVision XT Experiment in EthoVision XT One value of each of those variables; for example, one trial must be either Control or Treated or Sham etc. Making a List of Trials If you want, you can pre-define all your trials here. Click the Add Trials button and specify the number of trials (=recording sessions of one animal), and the values of the independent variables for each trial (see Figure 5.9). You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a series of trials for batch acquisition. See Acquire a Series of Trials in the EthoVision XT Help. The Elevated Plus Maze Test Test animals only once, unless the intention is specifically to study the different form of anxiety evoked by a second trial. If the animal falls off, it is best to exclude its scores. Independent Variables You can also enter the independent variable values as you carry out the trials. You can edit the independent variables for trials already acquired, for example to enter a-posteriori data, like whether the animal in that trial entered the open arms or not. This way you can quickly create groups of tracks based on the result of the trial, and use such groups in analysis. You can add a new independent variable at any time. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Experiment In Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-experiment-in-ethovision-xt-continued-NdU Chapter: EthoVision XT Experiment in EthoVision XT Arena-Hardware Mapping Devices are assigned automatically to one arena based on the scheme defined in the configuration window. For example, all the devices of Fear Conditioning System 1 at COM 1 are listed under Arena 1. - The Device Type column shows the types of device currently selected. If the type you want to use does not appear, add a new device. - The Device Name column contains names like Device A, Device B, etc. These are generic names for a specific type of device, which you can reference when programming device activation in the Trial Control Settings. You may rename them to Shock, Tone, etc. - The Arena 1, Arena 2, etc. columns contain the names of unique physical devices. These are automatically assigned based on which FCS system connected to a specific COM port is associated with which arena in EthoVision XT. Your task is to assign each physical device to a specific arena. Important: Test the devices after assignment. You can also test the devices in the Trial Control Settings. Note: The item UB FCS IR Light listed in the Arena - Hardware Mapping window controls the IR lamp located at the top-left corner of the cubicle, not the IR light provided by the light box. You can control the IR light of the light box by turning the knob of the IR controller. Add a New Device If the FCS devices are not listed in the Arena-Hardware Mapping window, do the following: - Click the Add Device button. - Under Device Type, select a device (e.g. UB FCS Tone). - Under Device Name, either accept the default name or enter a new, meaningful name, for example Tone. - If you plan to activate a device type in all the cages at the same time, a generic name like Shock or Tone is sufficient. - If you plan to activate a device type in different cages at different times, specify a unique device name, for example Tone for Cage 1, and assign that device only to the arena associated with that cage. - Locate the column for the arena you want to assign the device to, and select the physical device from the drop-down list. For example, under Arena 1, select UB FCS Shock 1; under Arena 2, select Ugo Basile FCS Shock 2, etc. The number of devices available in a list depends on how many COM ports you have declared. Make sure you do not select the same unique device under two or more arenas. Examples of Arena-Hardware Mapping EthoVision XT Controlling One Cage Note: The item UB FCS IR Light controls the IR lamp at the top-left corner of the cubicle, not the IR light box. EthoVision XT Controlling Four Cages - Configuration 1 Use this configuration when you plan to administer a stimulus in all FCS cages at the same time, for example to activate the tone in all cages exactly one minute after the start of the trial. Define a device name that is valid for all the cages (arenas). Under Arena 1, Arena 2, etc., select the physical devices for each arena. In the following example, Device A represents the foot shock for all the cages. When you use a hardware action Device A - Shocker On in the Trial Control Settings, that action is carried out in all the cages. - Make sure not to select the same physical device twice for two arenas. - Repeat the steps for the remaining devices. Note: You can also use this configuration when tracking starts at different times in different arenas, for example when you release the subject at different times and EthoVision XT starts tracking after the subject has been detected. EthoVision XT Controlling Four Cages - Configuration 2 Use this configuration when you need to apply different protocols to different cages. For example, to provide a stimulus after the subject has been immobile for one minute, or to give a shock in cage 1 after 1 minute and a shock in cage 2 after a random time. In such cases, the activation of a stimulus device is cage-specific. Create this configuration by linking a specific device name (e.g. Device A) only to a specific physical device in one arena (e.g. Arena 1). Device A should not be assigned to other arenas. You must add four new devices of the same type and assign each to one arena. For example, in the case of UB FCS Tone: - Device A: UB FCS Tone 1 under Arena 1 - Device B: UB FCS Tone 2 under Arena 2 - Device C: UB FCS Tone 3 under Arena 3 - Device D: UB FCS Tone 4 under Arena 4 Additionally: - Remember to select in the remaining cells of the table. - With this setup, tone stimuli are presented at different times in different cages. If the cubicles are near each other, the animal in cubicle 1 may be affected by tone presentation in adjacent cubicles. Make sure the cubicles are far apart or located in different rooms when using non-simultaneous tone presentation. - Repeat the steps for the other device types you want to use. For more information about applying different protocols to different cages, see Applying Different Protocols to Different Arenas in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Test the FCS Devices Prerequisites - All connections are set as described in the Physical Setup section. - You have created an experiment and specified the FCS in the Experiment Settings. - You have drawn and calibrated the arenas. - You have specified the FCS devices for each arena. Procedure for Actions This procedure applies to: Visible Light, Tone, Shocker, White Noise, Fan, and IR Light. - In EthoVision XT, choose Setup > Trial Control Settings and open one of the existing profiles. - In the Components pane, under Actions, click the button next to the name of the device you want to test. - In the window that appears, select the device, the type of action, and adjust its settings, then click Test. - Verify that the device works as expected. Next, click Reset to reset all devices to their default values. If the action is carried out in another cubicle, the wrong device has been selected in step 3, or the devices have not been mapped correctly in the Arena Settings. Procedure for the UB FCS Door This procedure applies to the device UB FCS Door. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Experiment In Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-experiment-in-ethovision-xt-continued-lx3 Chapter: EthoVision XT Experiment in EthoVision XT Arena-Hardware Mapping - In EthoVision XT, choose Setup > Arena Settings and click the Arena-Hardware Mapping button. - In the Arena-Hardware Mapping window, select the row for UB FCS Door. Next, click the Test button. - The Test UB FCS Door window opens on the screen. Open/close the door of the corresponding cubicle and check the message displayed in the window (Door Open? True or false). Verify That the Shocker Gives a Shock Place a LED diode between two bars of the shocker grid, or touch a bar with a phase detector. If the shocker is connected correctly and working, the LED turns on. You can also touch the grid bars, however a current intensity around 1 mA is the threshold of feeling. A lower current may not be felt. Measure the Amplitude of the Shock Important: For this you need an oscilloscope and an oscilloscope probe with insulated channel and a 100 K resistor. - Set the oscilloscope to 50V/DIV and time base 10 ms. - Connect the oscilloscope probe with a 100 K resistor to the shock grid, as indicated in the following picture. - In EthoVision XT, in the Arena - Hardware Mapping window, select the shock device for a specific cubicle and click Test. Set the shock intensity to 1.5 mA. - Click the Test button to activate the shock. You should see a square wave on the display of the oscilloscope. Read the amplitude there; remember that with the current settings one vertical division corresponds to 50 V. Once you know the voltage, the current is equal to the voltage divided by the resistance (in this example 100000). Trial Control Settings Follow this section to learn how to program EthoVision XT to send commands to the FCS devices at the right time during data acquisition. Basic Structure: Actions and Conditions To activate/deactivate a stimulus, use the Actions function. In general, two actions must be separated by some time. Below is an example of activation of a stimulus for one second. - Choose Setup > Trial Control Settings. - In the Components pane, under Actions click the button next to the device name that you want to use, and specify the type of action. - In most cases you need to add a number of boxes in a sequence. For example, the sequence Shock On (Action) > Time Condition > Shock Off (Action) defines the activation of the shock for a specific time set in the Time Condition. - Click and drag from the center of one box to the next to connect the boxes with the arrows. Depending on how you map the devices on the Arenas, this action can be carried out in one or more cubicles simultaneously. Recurring Stimulation Using Sub-Rules In most cases you need to administer a stimulus at regular intervals, for example every minute. Instead of repeating the sequence for each round, create a Sub-rule that contains the actions you want to repeat. Specify how often and when the routine is repeated in the Sub-rule settings. In the following example, a Sub-rule with the same instructions will be repeated 15 times. The shock is given every minute: - After the start of the trial, the software waits one minute (box A). - The Sub-rule reference box (B) activates the Sub-rule (C). - The stimulus is given as above (D-E-F). - A time condition of 59 seconds (G) ensures that the next stimulus is given exactly one minute later (1 s of shock + 59 s = 60 s). - The Sub-rule is repeated 15 times as specified in the settings of box B. After that, the trial stops (box H). Cued Conditioning: Pairing Tone and Shock The following example follows the protocol by Curzon et al. (2009) [In Buccafusco (ed). Methods of Behavior Analysis in Neuroscience, Chapter 2]. During the conditioning session: - A tone (Frequency 1000 kHz, Amplitude 50% of the maximum) is presented for 15 seconds. - During the last 2 seconds of the tone presentation, the shock is administered (0.5 mA). - Tone and shock end at the same time. - After the shock, a period of 60 seconds with no stimuli follows. If you want to have this sequence repeated a number of times, place it within a Sub-rule. In this example the Sub-rule is called by a Reference rule after 120 seconds of habituation. Controlling Lights - IR Light: The FCS provided by Noldus has the IR light activated by default. If the IR light is off, activate it at the start of the trial by adding an action for the IR light just after the Start Trial box. - Visible Light: In many FC protocols a house light illuminates the test chamber continuously during testing. Add an action for the UB FCS Visible Light and insert the Light On Action box after the Start Trial box. Add a second action box (with a Light Off action) immediately before the Stop Track box. Controlling the Fan The fan is by default activated when you start the cubicle. To ensure that the fan is on at the start of a trial, in Trial Control Settings click the button next to UB FCS Fan and insert the Fan On Action box after the Start Trial box. Notes: - If you add a Fan On Action at the start of the trial, the fan switches on at the start of the trial and switches off at the end of the trial. - If you do not add any action about the fan in the Trial Control Settings: - If the fan was already on at the start of the trial (for example after you start up the cubicle), the fan stays on during the trial. - If the fan was off, for example when testing it in the Trial Control Settings, it stays off during the trial. Analyze Data Using Trial Control Events If you want to analyze the data in specific time segments, you can use the actions and conditions of Trial Control Settings to define specific intervals. For More Information For more information and examples of actions, conditions and sub-rules, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. To open this manual, choose Apps > Noldus > EthoVision XT 18 Other Documentation. Detection Settings Release the subjects in the FCS cages, then choose Setup > Detection Settings to detect the subject. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Experiment In Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-experiment-in-ethovision-xt-continued-2Yz Chapter: EthoVision XT Experiment in EthoVision XT Automated Detection Setup In the Detection Settings window, click Automated Setup. Draw a rectangle around each subject in the video image, and follow the instructions on the screen. Minimize the Indentations Caused by the Grid In the Detection Settings, click Advanced. Under Subject Contour, choose what follows depending on the color of the subject and the grid bars: - If the grid bars are the same color as the subject, use the first Erosion filter. Increase the value near Erosion until the grid is no longer detected. Normally 2–3 pixels are fine. Check that the whole body is detected, indicated by the yellow blob. - If the grid bars are of a color other than the subject, and the detected subject appears to be broken in multiple parts, use the Dilation filter. Increase the value near Dilation until the yellow body is entirely over the subject's body. After that, reduce the size of the yellow blob by means of the second Erosion filter. For details, see Advanced Detection Settings: Subject Contour in the EthoVision XT Help. Minimize the Effect of the Subject's Shadow Make the contrast range smaller to exclude the pixels in the shadow. For example, if the subject has dark fur and the shadow is included in the yellow blob, then next to Dark, move the left slider to the right. This will exclude smaller values of contrast. You should see the yellow area over the shadow shrinking. EthoVision XT will not follow the shadow anymore. Do this in small steps, until the shadow is no longer detected. Make sure that the whole body is still detected in all parts of the cage. Tip: If the background looks too similar to the color of the subject, place a sheet of paper or plastic in the drawer that you find under the shock grid. Try to make as much contrast as possible between the subject and the background. Set Activity Analysis for Freezing Detection In the Detection Settings window, click Activity. Adjust the settings so that a large number of purple pixels appear only when the subject moves. - If the Activity threshold is too low, purple pixels also appear in the background. Increase the value of Activity threshold until purple pixels appear only when the subject moves, such as when a mouse moves its head. - If the Activity threshold is too high, purple pixels disappear completely. A sufficiently wide range of purple pixels is required in order to detect immobility (freezing). - When the subject freezes, the number of purple pixels should be minimized. For more information: - See Activity Settings in the EthoVision XT Help. - Click the video button next to Activity and watch the video tutorial. - For details about the advanced detection settings, see Configure Detection Settings in the EthoVision XT Help. Troubleshooting All FCS Devices Are Listed for Arena 1 Only This may have occurred when you selected the number of arenas after defining the COM ports for the FCS cages. If, at the time of defining the COM ports, the number of arenas was still 1, EthoVision XT assumes that all the devices must be associated with Arena 1. Do the following: - In the Arena-Hardware Mapping window, select each row and click Remove Device. Do so to remove all the devices. - Choose Setup > Experiment Settings. - Under Trial Control Hardware, click Settings, then choose Ugo Basile F.C. Controller. In the window that opens, make sure that the COM ports are listed and click OK. - Under Number of Arenas, select the number of arenas you work with. - Choose Setup > Arena Settings and click the Arena-Hardware Mapping button. At this point the devices should be correctly selected under one of the arenas. The IR Light Is Switched Off or Its Intensity Is Not Optimal - Create a new Trial Control Settings profile (Setup > Trial Control Settings > New). - Click the button next to Action - UB FCS IR Light. - Select the device from the UB FCS IR Light list. - Select Light ON and choose the Intensity Level (recommended: 100%). - Click Test, then OK. - Open the Detection Settings and verify that the chamber is illuminated. Tip: Keep the new Trial Control Settings profile so you can always access it in case you want to restart the IR light. Do not use this profile for tracking. Another way to restore the default IR light is to restart the cubicle (disconnect and then reconnect the power). See also Update the Cubicle Firmware to make sure that the default state of the IR light sets the default light intensity. The Fan Is Switched Off Restart the cubicle (disconnect and then reconnect the power). Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Experiments With Calcium Imaging 338 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-experiments-with-calcium-imaging-338 Chapter: EthoVision XT Introduction - EthoVision XT and Calcium Imaging - EthoVision XT and Optogenetic Stimulation - nVista vs nVoke - EthoVision XT License Needed - Application Examples - References Physical Setup - Hardware Components - Connection Schemes - Notes Basic Settings - EthoVision XT: Experiment Settings - EthoVision XT: Arena Settings - Inscopix Devices Program Control of Devices in EthoVision XT - Trial Control Settings - Example 1 - Image Recording (nVista) - Example 2 - Manual Video Recording, Triggered OG-LED Stimulation - Example 3 - Triggered Video Recording and LED Stimulation Detection Settings - General - Detect Immobility - Remove the Effect of the Microscope Cable Aligning Data - Sync Signal - Using the TCAP Signal - Using a TTL Signal - Mark EthoVision Events on the Calcium Imaging Timeline Data Analysis in EthoVision XT - Define a Simple Event - Analyze Intervals (Global) - Analyze Specific Intervals - Export the Raw Data - Align EthoVision XT and Inscopix Data General Information - Setting Up the Experiment in EthoVision XT - Acquire the Data - Analyze the Data For more manuals, from the Windows Start menu choose Apps > Noldus > EthoVision XT > Other Documentation. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-0aN Chapter: EthoVision XT Introduction The Radial Arm Maze Test The radial arm maze was designed to measure spatial learning and memory in rats (Olton and Samuelson, 1976; Olton, 1978, 1985). The original apparatus consists of eight arms, each about 4 feet long, and all radiating from a small circular central platform. At the end of each arm there is a food site, the contents of which are not visible from the central platform. The design ensures that, after checking for food at the end of each arm, the rat is always forced to return to the central platform before making another choice. For example, when investigating working memory, all arms are provided with a food reward and the animal should visit each arm only once. Correct performance of the radial maze task requires intact spatial memory abilities. Performance is affected by hippocampal impairment and a variety of pharmacological agents (e.g., Janitzky et al. 2011). References - Janitzky, K, Schwegler, H., Kröber, A., Roskoden, T., Yanagawa, Y. & Linke, R. (2011). Species-relevant inescapable stress differently influences memory consolidation and retrieval of mice in a spatial radial arm maze. Behavioural Brain Research, (1), 142-148. - Olton, D.S. (1978). Characteristics of spatial memory. In: Hulse S.H., Fowler H, Honig W.K. (Eds.), Cognitive processes in animal behavior, Hillsdale, NJ: Lawrence Erlbaum Associates, 341-373. - Olton, D.S. (1985). The radial arm maze as a tool in behavioral pharmacology. Physiol. & Behav., 793-797. - Olton, D.S., & Samuelson, R.J. (1976). Remembrance of places passed: Spatial memory in rats. Journal of Experimental Psychology: Animal Behavior Processes, 97-116. - Wenk, G.L. (2004). Unit 8.5A Assessment of Spatial Memory Using the Radial Arm Maze and Morris Water Maze, in: Current Protocols in Neuroscience, John Wiley and Sons, Inc. Physical Setup The following suggestions are specifically to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - There must be maximum contrast between the background and the animal. If you use white animals in the maze, make sure the floors of the arms are dark and vice versa. Preferably, the floor of the room should be the same color (and matted) as the maze, contrasting with the animal. - Lighting should be uniform and even with no shadows. - If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. To prevent reflections, place indirect lighting above or around the maze. 'Globe' type bulbs twice the diameter as standard light bulbs are ideal. They should be close enough to the maze so that there is no direct line of sight between the bulbs and the camera lens. The light should reflect off the walls and ceiling, so that it only reaches both the lens and radial maze indirectly. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-hVE Chapter: EthoVision XT Introduction The Porsolt Forced Swim Test The Porsolt Forced Swim Test (Porsolt et al., 1977; Hédou et al., 2001; Juszczak et al., 2008) is the most commonly used test for assessment of depression in animal models. In the Porsolt test, a state of depression is induced by forcing a rodent to swim in a narrow cylinder or water tank from which it cannot escape. The procedure is generally divided into a pre-test session lasting 15 minutes, followed 24 hours later by a 5-minute test session. After a period of vigorous activity in the pre-test session, the animal adopts a characteristic immobile posture. Twenty-four hours later, after administration of antidepressants, the effect on immobility can be investigated by measuring the time of being immobile in the test session and comparing this with control animals. The Sample Experiment To see how a Porsolt forced swim test is carried out in EthoVision XT, see the sample experiment Porsolt Forced Swim test XT180 on the downloads section of the Noldus website (see my.noldus.com). Download this file and save it on your computer. Next, in EthoVision XT, select File, Restore Backup and select this file. See also the document Description of sample experiments of EthoVision XT.pdf for more information. References - Castagné, V., Moser, P., Roux, S., and Porsolt, R.D. (2011) Rodent Models of Depression: Forced Swim and Tail Suspension Behavioral Despair Tests in Rats and Mice. Current Protocols in Neuroscience 8.10A.1-8.10A.14. - Juszczak, G.R., Lisowski, P., Sliwa, A.T., and Swiergiel, A.H. (2008). Computer assisted video analysis of swimming performance in a forced swim test: Simultaneous assessment of duration of immobility and swimming style in mice selected for high and low swim-stress induced analgesia. Physiology and Behavior: 400-407. - Hédou, G., Pryce, C., Di Iorio, L., Heidbreder, C.A., and Feldon, J. (2001). An automated analysis of rat behavior in the forced swim test. Pharmacology, Biochemistry and Behavior: 65-76. - Porsolt, R.D., Bertin, A., and Jalfre, M. (1977). Behavioral despair in mice: a primary screening test for antidepressants. Archives Internationales de Pharmacodynamie et de Therapie: 327-36. Physical Setup The following suggestions are meant to optimize the quality of tracking. Camera View The camera should have a good, frontal view of the entire region the animals can be in. The complete body of the animal should be visible. Number of Animals You can test two or more animals simultaneously, when the Porsolt cylinder fits in the same camera view. For tracking multiple animals you need the Multiple Arenas add-on module. Contrast Try to create as much contrast as possible between the animal and the background. This can be done by placing the cylinder or tank against a contrasting, non-reflecting background (so, a matt black background for white animals and vice versa). You can also use back-lighting to create maximum contrast. In this case, make sure you place a screen or curtain between the lights and the cylinders to avoid reflections. Water Surface You can reduce the contrast due to the water surface by placing the cylinders in a bigger tank with the water surface of the tank above those of the cylinders. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-wko Chapter: EthoVision XT Principle of Operation Fear Conditioning In a typical Fear Conditioning paradigm, single-frequency sounds are delivered as a neutral or conditioned stimulus (CS). Experimental procedures where the CS is administered are usually named Cued Fear Conditioning. Electric current from the grid floor is delivered as the naturally aversive, or unconditioned stimulus (US). This chapter describes how you can use EthoVision XT with the Ugo Basile Fear Conditioning System NG-series 46000, to carry out fear conditioning experiments. If you use a version of EthoVision XT earlier than 17.5, please refer to the EthoVision XT Application Manual for that version. For an overview of Fear Conditioning, and how fear is measured in EthoVision XT, see the white paper which you can download from our web site. Controlling the FCS Stimuli from EthoVision XT - Connect the EthoVision XT computer to the Ugo Basile Fear Conditioning System (FCS). For details, see Physical Setup. - In EthoVision XT, create your experiment and declare the devices that you are going to use. Next, program the activation of the devices in the Trial Control Settings. For details, see The Fear Conditioning Experiment in EthoVision XT. If you have multiple FCS cubicles, you can control the stimuli in each cubicle independently. - Carry out data acquisition. See Acquire the Data. Experiment Devices and Parameters You can specify the devices and their parameters directly in EthoVision XT. This also makes it easier to test a device. - Shock with adjustable current intensity - Tone with adjustable frequency and volume - White Noise with adjustable volume - Visible (White) Light with adjustable light intensity - IR Light with adjustable light intensity - Fan which can be switched on and off You can also have EthoVision XT check if the door of the FCS cubicle is open or closed. Note: If you work with EthoVision XT 16 or earlier, you must connect the EthoVision XT computer to the Ugo Basile Touchscreen Controller 40500-001. Please refer to the EthoVision XT Application Manual for that version. Analysis of Freezing The detection of freezing can be automated and based on analysis of the variable Activity in EthoVision XT. For details, see Activity and Activity State in the EthoVision XT Help, under Dependent Variables in Detail. Changes Relative to Previous EthoVision XT Versions With EthoVision XT 17.5 and later versions you can control the Ugo Basile FCS without connecting the touchscreen controller. For new systems, the cabling is largely reduced and the system is easier to troubleshoot. - Cable connections are simpler — from the PC directly to the FCS cubicles through USB. - When you create an EthoVision XT experiment, the devices of the Ugo Basile FCS are automatically added to the experiment. - In the Trial Control Settings, you can easily recognize the names of the devices (e.g. Tone) instead of for example Line 1, as occurred in previous EthoVision XT versions. - You can test the devices directly in the Trial Control Settings, before carrying out the actual tests. - With FCS Model 46110-NL and Serial Number higher than 0676U24, you can control the IR light inside the cubicle directly from the software. You no longer need additional hardware. If you encounter problems, contact Noldus Support. If You Have the "Old" FCS Setup FCS Controlled Through the Noldus USB-IO Box Your FCS setup is connected to EthoVision XT through the Noldus USB-IO box, and you have upgraded EthoVision XT to version 17.5 or later. In this case you can keep using the existing connections. For instructions, see the EthoVision XT 17.0 Application Manual, which you can find on the downloads page of my.noldus.com. If you purchased an upgrade kit for your setup, see the Upgrade Your FCS System section. FCS with Manual IR Light Controller Your FCS setup is equipped with an IR light box placed on top of the conditioning cage and with the IR light box manual controller. You can keep using this configuration. However, you cannot control the IR light intensity from the software. For General Information EthoVision XT Help For more details, choose Help > Help Topics or press F1 in the software. Other Documentation On the Windows Apps screen, choose Noldus > EthoVision XT 18 Other Documentation. See in particular: - For information on programming trial control, conditioning routines, actions and conditions, and the USB-IO box: the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - For information on conditioning tests and examples: see other chapters in this manual. You can find these and other manuals on the Noldus website at my.noldus.com. Note that you need to log in first to access the downloads page. About the Ugo Basile Fear Conditioning System This system comes with the instruction manual Fear Conditioning Systems - NG Series 46000, in PDF format. Technical Support If you encounter problems, browse to my.noldus.com and contact the help desk. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-0HQ Chapter: EthoVision XT Introduction The Social Interaction test is widely used as a rodent model of anxiety-like behavior, under the assumption that anxiety is incompatible with social behavior (File and Hyde, 1978; File, 1980, 1988). So, an increase in anxiety generally results in a decrease in time spent on social interaction. The Social Interaction test is used to measure I) sensitivity to both anxiogenic and anxiolytic stimuli, ii) sensitivity to pharmacological, physiological and environmental manipulations and iii) ethologically relevant behaviors that do not require confounding manipulations such as food deprivation, pain or conditioned fear. Until recently, it has been difficult to automate the test with tracking systems. The features in EthoVision XT make this possible. This document describes the general procedure of how to do this. In most cases for a social interaction test you need the Social Interaction module. This module allows you to track two or more subjects in one arena. This module also includes the Deep learning option for individual recognition in a 2-subject interaction test. Here below you find an overview of the ways you can implement a social interaction test in EthoVision XT: Sociability Test (1-Subject Tracking) If you intend to track a free-moving subject while a second subject is caged (social target) and barely visible from above, you can track only the free-moving animal and measure the behavior of that animal towards the cage defined as a zone. In that case you do not need the Social Interaction module. See The Sociability Cage Test on page 107. Social Interaction - With Deep Learning-Based Recognition This solution, new in EthoVision XT 18, is based on artificial intelligence which discriminates between two subjects in the arena. One of the two subjects must be marked, e.g. its back being partially shaved. For this solution you can use a monochrome digital camera. Note: In order to apply artificial intelligence to animal tracking you need to have a compatible Graphics Processing Unit (GPU) installed on the EthoVision XT computer. See the EthoVision XT Help for more information. Social Interaction - Marker-Based Tracking This option assumes that you can color-mark your subjects that interact in the arena, and you have a color camera compatible with EthoVision XT. Most of this chapter is based on this solution. Social Interaction - Live Mouse Tracker With the Live Mouse Tracker add-on module you can import and analyze Live Mouse Tracker data. Live Mouse Tracker allows long-term analysis of behavior of socially-grouped mice. With Live Mouse Tracker you do not have to color-mark the subjects, however each subject must have a RFID chip implanted. For more information, see the EthoVision XT Help. The Sample Experiment To see an example of a social interaction test carried out in EthoVision XT, see also the sample experiment Social Interaction XT180 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. Next, in EthoVision XT, select File > Restore Backup and select this file. For more information, see the document Description of sample experiments of EthoVision XT.pdf. References - File, S.E., (1980) The use of social interaction as a method for detecting anxiolytic activity of chlordiazepoxide-like drugs. Journal of Neuroscience Methods, 219–238. - File, S.E., (1988) How good is social interaction as a test of anxiety? In: Simon, P., Soubrie, P., and Widlocher, D., Selected Models of Anxiety, Depression and Psychosis. Basel: Karger, 151–166. - File, S.E., and Hyde, J.R.G., (1978) Can social interaction be used to measure anxiety?, British Journal of Pharmacology, 19–24. - Lapiz-Bluhm, M.D.S., Bondi, C.O., Rodriguez, G.A., Bédard-Arana, T., and Morilak, D.A., (2008) Behavioural assays to model cognitive and affective dimensions of depression and anxiety in rats. Journal of Neuroendocrinology, 1115–1137. Physical Setup The following suggestions are aimed at optimizing video tracking of multiple, color-marked animals. Lighting Conditions For general information on lighting conditions, see the section Physical Setup in the chapter The Open Field Test. - Use a sensitive camera if possible. A low light intensity makes it difficult to separate different colors. When it is not possible to use a sensitive camera or strong illumination in your setup, try using fluorescent marker colors with UV lighting. - For optimal color separation, illuminate your setup with lamps that approximate to day-light in color temperature, that is, have a wide spectrum range. Marked vs. Unmarked Subjects In some cases it is required that the identity of the animals that interact in the arena is known and followed, for example in resident-intruder or male-female interactions, or whenever one needs to separate behavioral endpoints (e.g. speed, zone visited) for each individual. In such situations, we recommend marking the animals (see below). EthoVision XT can also track unmarked animals, however identity switches may occur. It is not guaranteed that the correct identity of each unmarked animal is kept throughout the trial. Markers for Deep Learning Technique When using Deep learning, shave the back of one subject so that it looks different from the other. The shaved part should always be visible from the top. For more details, see the EthoVision XT Help. Color Marker Characteristics - Use a color scale (for example from a paint company) to find out which colors are most easily recognized by EthoVision in your setup and lighting conditions. Do this before applying color markers to your animals. - Use colors that have different hue values. For example, use orange and green, pink and yellow, not red and orange. Avoid using red for marking, since it looks like blood. - Note that marking your animals may stress them, and therefore affect their behavior. If necessary, ensure that you select a marking method that lasts for a longer period of time. - Make sure that the marker is as round as possible; this will ensure that the relative movement of the center of gravity of the marker is the same in all directions when the edges of the marker change due to posture changes or otherwise. - Make sure the marker is not too big; the marker can interfere with proper detection of the body contour. For example, make sure that a dark marker on a white animal does not cover the complete width of the animal because it can cause the body to be split in two during tracking in EthoVision XT. See also Tips for Color Tracking in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-LVc Chapter: EthoVision XT The Sociability Test (Three-Chamber Paradigm) The three-chamber paradigm test known as Crawley's sociability and preference for social novelty protocol has been successfully employed to study social affiliation and social memory in several inbred and mutant mouse lines. Sociability testing is a more specific study of social behavior and only focuses on the behavior of one animal towards others. There are several variances to this test, all conducted in a three-chambered test apparatus. In the first variant, the animal's interest in a social stimulus (a conspecific in a wired cage placed in one of the outer chambers) versus a neutral stimulus (an empty wired cage placed in the other outer chamber) is studied. In a preference test for social novelty, the two wired cages contain a familiar and an unfamiliar conspecific. A third variation involves testing the social preference for two different, but both unfamiliar conspecifics. In most cases the interest is measured by assessing the time spent in the same chamber or in close proximity to the familiar or unfamiliar other mouse. Representative Results Typically, a wild type animal will spend significantly more time in the compartment with a strange mouse compared to the compartment with empty cage, indicating normal sociability, social motivation and affiliation. In the social novelty test, the subject has a free choice between the first, already-investigated, now-familiar mouse, and a novel unfamiliar mouse. Usually, a wild-type animal recalls its previous contact with the familiar mouse, and, in this session, tends to spend more time with the newly encountered mouse, indicating intact social memory and predilection for novel experiences. References - Nadler, J.J., Moy, S.S., Dold, G., Perez, A., Young, N.B., Barbaro, R.P., Piven, J., Magnuson, T.R., Crawley, J.N. (2004). Automated apparatus for rapid quantification of social approach behaviors in mice. Genes Brain Behav., :303–314. - Moy, S.S., Nadler, J.J., Perez, A., Barbaro, R.P., Johns, J.J., Magnuson, T.R., Piven, J., Crawley, J.N. (2004). Sociability and preference for social novelty in five inbred strains: an approach to assess autistic-like behaviors in mice. Genes Brain Behav., 287–302. - Bechtstein, P., Rehbach, N.-J., Yuhasingham, G., Schürmann, C., Göpfert, M., Kössl, M., Maronde, E. (2014). The clock gene Period1 regulates innate routine behavior in mice. Proceedings of the Royal Society B, 20140034. DOI: 10.1098/rspb.2014.0034. - Desbonnet, L., O'Tuathaigh, C., Clarke, G., O'Leary, C., Petit E., Clarke N., Tighe, O., Lai, D., Harvey, R., Cryan, J.F., Dinan, T.G., Waddington, J.L. (2012). Phenotypic effects of repeated psychosocial stress during adolescence in mice mutant for the schizophrenia risk gene neuregulin-1: A putative model of gene × environment interaction. Brain, Behavior, and Immunity, (4), 660–671. - Glass, M.J., Robinson, D.C., Waters, E., Pickel, V.M. (2013). Deletion of the NMDA-NR1 receptor subunit gene in the mouse nucleus accumbens attenuates apomorphine-induced dopamine D1 receptor trafficking and acoustic startle behavior. Synapse, (6), 265–279. - Kim J-W, Seung H, Kwon KJ, Ko MJ, Lee EJ, et al. (2014). Subchronic treatment of donepezil rescues impaired social, hyperactive, and stereotypic behavior in valproic acid-induced animal model of autism. PLoS ONE, (8): e104927. DOI: 10.1371/journal.pone.0104927. - Ter Horst, J.P., van der Mark, M., Kentrop, J., Arp, M., van der Veen, R., de Kloet, E.R., & Oitzl, M.S. (2014). Deletion of the forebrain mineralocorticoid receptor impairs social discrimination and decision-making in male, but not in female mice. Frontiers in Behavioral Neuroscience, 26. DOI: 10.3389/fnbeh.2014.00026. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-9X5 Chapter: EthoVision XT Introduction The Elevated Plus Maze Test The elevated plus-maze was designed to provide measures of anxiety that were relatively uncontaminated by changes in overall motor activity, and has been extensively validated by Pellow et al. (1985) using behavioral, physiological, and pharmacological measures. The open and closed arms are considered to evoke the same exploratory drive in the animals, therefore avoidance of the open arms is considered to be a result of the induction of higher levels of fear (Rodgers and Dalvi, 1997). It is thought that the aversion of animals to explore the open arms of the maze is caused by fear of open and/or elevated spaces. The plus-maze is sensitive to the anxiolytic effects of neurotoxic lesions of serotonergic neurons and to the anxiogenic effects of drugs (Pellow and File, 1986), drug withdrawal (File and Andrews, 1991), and predator odor (Zangrossi and File, 1992). For a discussion of the additional, ethological measures that can be taken in this test, see Rodgers et al. (1995) and Fernandes and File (1996). Unlike the social interaction and light/dark tests, the elevated plus-maze does not rely on aversion to bright light, and it has been found repeatedly that behavior in the maze is independent of light level (e.g., Becker and Grecksch, 1996). For a review of the protocol, see Walf and Frye (2007). What to Measure - Principal component analysis of the conventional plus-maze (File, 1991) has shown that the percentage of time spent on the open arms and the number of entries onto the open arms are the best measures of anxiety (these are increased by anxiolytic and decreased by anxiogenic treatments). - The number of closed arm entries is the best measure of locomotor activity. - There are marked strain differences in baseline scores and even between the scores of different batches of animals. If the scores are high it will be hard to detect an anxiolytic effect. If they are very low it will be difficult to detect an anxiogenic effect. - The plus-maze was originally developed for male rats, but it can be used with female rats. However, while in male rats anxiety is the main factor measured, in females it is activity (Fernandes et al., 1999). The plus maze has also been validated for mice (Lister, 1987; Walf and Frye, 2007). For a discussion of the factors controlling measures of anxiety in the mouse, see File (2001). Quantifying Head Dips EthoVision XT can detect when the subject's nose is outside the open arms. However, you can also score head dips manually. First define head dips in the Manual Scoring Settings. Next, during acquisition, press the assigned keyboard key when a head dip occurs. The Sample Experiment To see how a plus maze test is carried out in EthoVision XT, see also the sample experiment Elevated plus maze XT180 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. In EthoVision XT, choose File > Restore Backup and select the file. For more information, see the document Description of sample experiments of EthoVision XT.pdf. References Papers - Becker, A. and Grecksch, G. (1996). Illumination has no effect on rats' behavior in the elevated plus maze. Physiol. Behav., 1175–1177. - Fernandes, C. and File, S.E. (1996). The influence of open arm ledges and maze experience in the elevated plus-maze. Pharmacol. Biochem. Behav., 31–40. - Fernandes, C., Gonzalez, M.I., Wilson, C.A. and File, S.E. (1999). Factor analysis reveals that female rat behaviour is characterised by activity, male rats are driven by sex and anxiety. Pharmacol. Biochem. Behav., 731–738. - File, S.E. (1991). Animal models of anxiety. In Biological Psychiatry (G. Racagni, N. Brunello, and T. Fukuda, eds.), 596–599. Elsevier, New York. - File, S.E. (2001). Factors controlling measures of anxiety and responses to novelty in the mouse. Behav. Brain Res., 151–157. - File, S.E. and Andrews, N. (1991). Low but not high doses of buspirone reduce the anxiogenic effects of diazepam withdrawal. Psychopharmacology, 578–582. - File, S.E., Lippa, A.S., Beer, B., Lippa, M.T. (2004). Animal Tests of Anxiety. Current Protocols in Neuroscience, Unit 8.3. DOI: 10.1002/0471142301.ns0803s26 (online). - Lister, R.G. (1987). The use of a plus-maze to measure anxiety in the mouse. Psychopharmacology, 180–185. - Pellow, S., Chopin, P., File, S.E., and Briley, M. (1985). Validation of open:closed arm entries in an elevated plus-maze as a measure of anxiety in the rat. J. Neurosci. Methods, (3), 149–167. - Pellow, S. and File, S.E. (1986). Anxiolytic and anxiogenic drug effects in exploratory activity in an elevated plus-maze: A novel test of anxiety in the rat. Pharmacol. Biochem. Behav., 525–529. - Rodgers, R.J., Cole, J.C., Aboualfa, K., and Stephenson, L.H. (1995). Ethopharmacological analysis of the effects of putative "anxiogenic" agents in the mouse elevated plus-maze. Pharmacol. Biochem. Behav., 805–813. - Rodgers, R.J. and Dalvi, A. (1997). Anxiety, defense and the elevated plus-maze. Neurosci. Behav. Rev., 801–810. - Violle, N., Balandras, F., Le Roux, Y., Desor, D., and Schroeder, H. (2009). Variations in illumination, closed wall transparency and/or extramaze space influence both baseline anxiety and response to diazepam in the rat elevated plus-maze. Behav. Brain Res., 35–42. - Walf, A.A. and Frye, C.A. (2007). The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nature Protocols, 322–328. doi:10.1038/nprot.2007.44. Web: www.nature.com/nprot/journal/v2/n2/pdf/nprot.2007.44.pdf - Zangrossi, H. and File, S.E. (1992). Behavioral consequences in animal tests of anxiety and exploration of exposure to cat odor. Brain Res. Bull., 381–388. Videos - https://www.youtube.com/watch?v=4rRsxf1U6-w - http://www.dailymotion.com/video/x2e25p_4tgndox16_animals Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-yT1 Chapter: EthoVision XT Introduction The Morris Water Maze Test The Morris water maze is a behavioral procedure designed to test spatial memory. It was developed by neuroscientist Richard G. Morris in 1984, and since its initial description it has become a very popular paradigm for the study of learning and memory in rodents (D'Hooge and De Deyn, 2001). In the water maze paradigm, a rat or mouse is placed into a small circular pool of water which contains a hidden platform (the Atlantis platform). The platform is either fixed (a few millimeters below the water surface) or adjustable. In the latter case, the platform is submerged at the start of the trial (about 15 centimeters, depending on the device) and remains submerged until the subject finds the location of the platform. The platform is then automatically raised. Visual cues, such as colored shapes, are placed around the pool to aid the animal in learning to locate the platform. After sufficient training, a capable rat can swim directly from any release point to the platform. Next, animals are treated and the effects on spatial learning and memory are evaluated based on how they now perform in the Morris water maze. The Sample Experiment EthoVision XT comes with a sample experiment that shows you how a Morris water maze test is carried out with EthoVision XT. It includes a number of videos from a true research project and shows interesting patterns of spatial behavior depending on the age of the subject. If the sample experiment was installed during installation of EthoVision XT, you can open it directly: Choose File > Restore Backup and browse to C:\Users\Public\Documents\Noldus\EthoVision XT\Experiments\Sample Experiments. Select the file with extension EVZ and click Open. If you do not find the sample experiment, download it from MyNoldus.com. First log in or register, then choose Downloads > EthoVision XT > Sample Experiments. References - D'Hooge, R. and De Deyn, P.P. (2001). Applications of the Morris water maze in the study of learning and memory. Brain Research Reviews, 60-90. - Gallagher, M., Burwell, R. and Burchinal, M. (1993). Severity of spatial learning impairment in aging: development of a learning index for performance in the Morris water maze. Behavioral Neuroscience, 618-626. For the complete list of publications, see the results in Google Scholar. Physical Setup The following suggestions are meant to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - There must be maximum contrast between the background and the animal. If you use dark rats in the water maze, you can color the water with milk powder (400 g, pre-dissolved in 2 l). It is also possible to track white rats or mice with dark coloring in the water: add 300 g of tempera black nontoxic powdered paint to a 45-l pool. - If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. Place four (or more) bulbs round the pool, below the level of the water surface or other indirect lighting above the water maze. 'Globe' type bulbs are ideal (twice the diameter as standard incandescent light bulbs). They should be close enough to the pool wall so that there is no direct line of sight between the bulbs and the camera lens. The light is reflected off the walls and ceiling, so that it only reaches both the lens and water surface indirectly. - The water temperature should be ± 26 °C, which is cold enough to encourage the animals to seek the platform, but not too cold to induce hypothermia. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction Chapter: EthoVision XT Introduction The Open Field for Rodents The open field test was first published 1932 by C. S. Hall and E.L. Ballachey to determine the fearfulness of rats. Today, the test is often used with rats and mice to investigate their locomotory behavior and their willingness to explore. Also, the test is one of the most commonly used methods to investigate anxiety in rats and mice. It is based on the natural tendency of rats and mice to spend more time in the corners and the periphery than in the center. Changes in these measures are often used to assess the sedative or stimulant effects of pharmacological agents. The test arena consists of a circular or rectangular empty open space with walls to prevent the animals from escaping. The arena is divided into a border zone and a center zone. In addition, the arena can be sub-divided into a number of other zones, like north, east, south and west zones, or corner zones. Common behaviors to be measured are: - Time spent in the border zone and center. - Time until the border of the center zone is first crossed. - Walking distance in each of the zones. - Percentage of time the animal is mobile/immobile. - Walking speed in each of the zones. - Frequency of rearing. References - Hall, C., Ballachey, E. L., 1932. A study of the rat's behavior in a field. A contribution to method in comparative psychology. University of California Publications in Psychology, Vol, 1-12. - Gould, T.D., Dao, D.T., Kovacsics, C.E., 2010. The Open Field Test. Neuromethods, Vol, 1-20. - De Visser, L., Van Den Bos, R., Kuurman, W.W., Kas, M.J.H., Spruijt, B.M., 2006. Novel approach to the behavioural characterization of inbred mice: automated home cage observations. Genes Brain and Behavior, Vol (6), 458-466. For the complete list of publications, see the results in Google Scholar. On the downloads section of the Noldus website, my.noldus.com, you can find a number of sample experiments, including the open field. The Open Field for Zebrafish Open Field The open field test is used to evaluate exploratory and affective behaviors. Fish are filmed with a video camera positioned overhead. The bottom of the tank is divided into two virtual zones, center and periphery (a circular zone with inner boundary 5 cm from the testing tank wall), which enables quantification of regional activity. In addition to standard movement parameters, primary behavioral measures included the distance traveled, number of visits and time spent in central and peripheral zones, and the ratio of time spent in the center zone over total testing time. Novel Tank Diving Test The novel tank test is used to assess exploratory and affective domains. The novel tank is a trapezoidal tank maximally filled with treated water and divided into two equal, horizontal regions (top/upper and bottom/lower zones). Primary behavioral measures include the number of visits and time spent in central and peripheral zones, the ratio of time spent in the top zone over total testing time, latency to enter the top zone, time spent in the top zone, and number of transitions to top zone. Similar to behavioral tests used in mammalian models, affective phenotypes are inferred from modulation of thigmotaxis (center/periphery in the open field test) and geotaxis (top/bottom in the novel tank diving test). References - Kalueff A.V., A.M. Stewart, R. Gerlai (2014). Zebrafish as an emerging model for studying complex brain disorders. Trends in Pharmacological Sciences, Vol (2), 63-75. Physical Setup The following suggestions are meant to optimize video tracking: - Camera position: The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - Lighting evenness: The lighting should be as even as possible throughout the arena. Make sure there are no shadows in the corners. Bright lights are not necessary, but should you need to supplement the light, consider red (or infra-red) light, as the animals will be less sleepy. Regardless of the light level chosen, the investigator should use a light meter to record the lighting level and report this level in any publication. - Multiple arenas: When working with multiple arenas, make sure that the background light intensity is the same across arenas. This is usually not a problem, as long as the contrast between each animal and its arena background is much bigger than the difference in brightness between arenas. - Diffuse lighting: The lighting should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). Even, diffuse lighting is important to optimize tracking of the nose. - Background contrast: The background should contrast with the animal. If necessary, use a different setup for light and dark colored animals. Matt, gray walls often give good results. - Urine pools: Depending on circumstances, pools of urine can cause problems with the tracking because they reflect light. An absorbent base can help. - Reflective surfaces: Make sure the sides of the box are not reflective (e.g. sanding). Alternatively, exclude the sides from the arena, but make sure that the animal is tracked well in the entire border zone. - Apparatus position: Always place the apparatus in the same position in the room; cues from overhead might influence the behavior of the animal. For the same reason, the experimenter should not be visible to the animal during the trial (automated tracking makes this possible). - Audio disturbance: Minimize disturbance from audio sources, especially from ultrasound sources such as ventilation fans, CRT monitors, or strip-lights. You can mask audio disturbance by using the same background sounds, for example of a radio, in the test room as in the room where the animals are normally housed. - Animal handling: When you handle the animals, be careful to minimize stress. - Animal isolation: If you use multiple arenas, make sure that the animals in the arena do not influence each other. The animals should, for example, not be able to hear or smell each other. - EthoVision XT guidance: In EthoVision XT, choose Help > Video Tutorial and watch the video chapter Set Up Your Test Environment. That provides useful tips about the camera position, how to improve lighting and contrast with the background. - Deep learning tracking: If you intend to use the Deep learning method to track the subject's nose point, note that there are additional requirements and limitations. See the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-ulD Chapter: EthoVision XT Introduction EthoVision XT can be used in learning tests, such as the water maze test and the conditioning tests (e.g., Pham et al., 2009). The Trial and Hardware Control module of EthoVision XT can be used to operate hardware devices to be used in both classical and operant conditioning tests. In the latter, an action of the animal produces a result, for example, pressing a lever results in the food dispenser dropping a food pellet. This and other hardware actions (such as, turning on a light when the animal enters the shelter, or closing the door of a radial maze when the animal has exited that arm) can be operated through the Trial and Hardware Control in EthoVision XT. Learning can be demonstrated by a change in the frequency of the animal's action over time. For example, when the animal is presented with an aversive stimulus every time it performs a certain action, the performance of the action will likely decrease over time because the animal tries to avoid the negative stimulus. To be able to operate hardware devices with EthoVision XT you need: - The Trial and Hardware Control Module: This module allows you to control hardware devices from within EthoVision XT. - The USB-IO Box: This is the device that connects the EthoVision XT PC with external hardware devices such as the sound and light devices of PhenoTyper or a third-party hardware device. This document describes how to set up EthoVision XT using Trial and Hardware Control in an operant conditioning test in PhenoTyper. PhenoTyper PhenoTyper is an instrumented cage to measure and test the behavior of laboratory rodents. If you want to use EthoVision XT to operate a third-party hardware device, please contact Noldus Information Technology (www.noldus.com). To see how a test with PhenoTyper is carried out in EthoVision XT, see the sample experiment PhenoTyper hardware XT180 on the downloads section of the Noldus website (my.noldus.com). In EthoVision XT, choose File > Restore Backup and select this file. See also the document Description of Sample Experiments of EthoVision XT.pdf for more information. Fear Conditioning Test In the fear conditioning test, you can use EthoVision XT to automatically detect freezing behavior as a measure of conditioned fear. References - Liu, W., Wang, X., Zhang, R., and Zhou, Y. (2009) Effects of postnatal exposure to methylmercury on spatial learning and memory and brain NMDA receptor mRNA expression in rats. Toxicology Letters, 230–235. - Pham, J., Cabrera, S.M., Sanchis-Segura, C., and Wood, M.A. (2009) Automated scoring of fear-related behavior using EthoVision software. Journal of Neuroscience Methods, 323–326. Physical Setup The following suggestions are meant to optimize tracking: - The camera should have a good view of the entire region the animals can be in (for zones like the shelter where the animal is not visible, you can define hidden zones). - The lighting should be as even as possible throughout the arena and should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). - The background should contrast with the animal. If necessary use a different setup for light and dark colored animals. - Either make sure the sides of the box are not reflective (e.g., sanding), or exclude the sides from the arena. If your objects are close to the sides then you will need to track the animal when it is against the side (so the camera sees the side instead of the base behind the animal). - If you want to use the Deep Learning technique to track the subject's nose, keep in mind that there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. For More Information - About PhenoTyper: See the PhenoTyper - EthoVision XT 18 - Reference Manual. - About Using Hidden Zones: See the section Shelters and Other Hidden Zones in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-oZN Chapter: EthoVision XT Introduction Optogenetics and EthoVision XT In the last decade, a method was developed to specifically activate or even inhibit small groups of neurons with light. Today, scientists can insert light-sensitive receptor proteins (originally found in algae) into single mammalian neurons in vivo, making these neurons sensitive to activation by light of specific wavelengths. This allows scientists to control the activity of these neurons and study their downstream influence on a variety of biological processes. Optogenetics is an important development for behavioral research. Not only can the actual influence of specific neurons on behavior more specifically be determined, but also, with the help of an automatic video tracking system such as EthoVision XT, behavior can be manipulated via optogenetic methods in real time. With the Trial & Hardware Control module, EthoVision XT can control light pulses given by a third party device, based on the behavior of the animal (for instance, presence in a trigger zone). In this manual we focus on the optogenetics solution for rodents that combines EthoVision XT, PhenoTyper (as test environment) and the Prizmatix optogenetics devices. For how to conduct optogenetics experiments with zebrafish, see the DanioVision DVOC-0041 Reference Manual. Examples Place Preference The animal is placed in an arena with two distinct sides - one of which is paired with optogenetic stimulation. Depending on whether this stimulation is activating or deactivating, and which neurons are affected, this can be a rewarding or aversive stimulus for the animal. If in further sessions the animal spends more time on the stimulated sides, it is fair to conclude the stimulus had a rewarding effect. If the animal avoids this side, the stimulus could then be considered aversive. Operant Conditioning In operant conditioning tests, the animal learns to perform an action in order to get a reward or avoid an aversive stimulus. The behavioral response can be recorded with EthoVision XT, either by detecting the animal (or its nose point) in a certain zone, such as the feeder, or by analyzing the external signal initiated by the nose poke or lever press. Following this action, EthoVision XT sends out the command for optogenetic stimulation. Off-On-Off Stimulus Test In an off-on-off stimulus test, you can program EthoVision XT to turn optogenetic stimulation on for a period of time during the test. For example, a 15 minute test during which continuous optogenetic stimulation takes place in the middle 5 minutes. References - Guru, A., Post, R.J., Ho, Y., Warden, M. (2015). Making Sense of Optogenetics. International Journal of Neuropsychopharmacology, Aug 2015, 1–8. - Zalocusky, K., Deisseroth, K. (2013). Optogenetics in the behaving rat: integration of diverse new technologies in a vital animal model. Optogenetics 2013: 1-17. - Stamatakis, A.M., Stuber, G.D. (2012). Activation of lateral habenula inputs to the ventral midbrain promotes behavioral avoidance. Nature Neuroscience, (8), 1105-1107. - Kravitz, A.V., Tye, L.D., Kreitzer, A.C. (2012). Distinct roles for direct and indirect pathway striatal neurons in reinforcement. Nature Neuroscience, 816-818. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-introduction-ZjD Chapter: EthoVision XT Introduction EthoVision XT and Calcium Imaging To understand the working of neural circuits in the brain, it is vital to be able to view neural activity simultaneously with behavioral data. Calcium Imaging is a microscopy technique to optically measure the calcium (Ca2+) status of a cell, a tissue or a medium. This allows to monitor the electrical activity in single neurons at a spatial scale that is not possible to achieve with other techniques. The Inscopix nVista miniature microscope system enables researchers to conduct genetically targeted calcium imaging over time in awake, freely behaving rodents, and has provided insights from multiple brain areas, from the prefrontal cortex all the way to the hypothalamus. nVista's compact, sleek plug-and-play interface makes it easy to add powerful new neural circuit insights to any laboratory's behavioral research arsenal. You can combine EthoVision XT with the Inscopix nVista system in such a way that EthoVision XT takes control over the recording activity of nVista. For this you need the Noldus USB-IO box interface connected between the two systems. EthoVision XT and Optogenetic Stimulation In vivo Calcium Imaging is often coupled with Optogenetic stimulation to causally link neural circuit activity and behavior. For this purpose, the Inscopix nVoke system is coupled with EthoVision XT, which can trigger both calcium imaging and the optogenetic LED stimulation. The two triggering systems can be set independent of one another. Similarly to what is done for the EthoVision XT and the nVista system, you need the Noldus USB-IO box interface connected between EthoVision XT and nVoke. Experiments with Calcium Imaging nVista vs nVoke - nVista: Inscopix system for in vivo Calcium imaging in free behaving animals. It includes a head-mounted miniature microscope that enables one-photon epifluorescence imaging of calcium dynamics, a correlate of neural activity. - nVoke: The Inscopix system that enables simultaneous in vivo Calcium imaging and optogenetic manipulations. EthoVision XT License Needed To enable control of Inscopix devices by EthoVision XT, you need the Trial and Hardware Control module. If you are not sure whether this function is activated, in EthoVision XT select Help > About EthoVision XT > License Info. If the Trial and Hardware Control checkbox is not selected, contact Noldus to purchase an upgrade with this module. Application Examples Place Preference in the PhenoTyper The nVista microscope is triggered every time the mouse enters a target region of the PhenoTyper, as defined in the EthoVision XT software. In an experiment that combines Calcium Imaging and Optogenetics, the PhenoTyper was divided in two side zones, and in each session one side was assigned as stimulus (LED)-paired side. Each time the mouse crossed to the stimulation side, stimulation was delivered until the mouse crossed back into the non-stimulation side (Stamatakis et al. 2018). Contextual Fear Conditioning Simultaneous Calcium Imaging and Optogenetic stimulation are performed during a fear conditioning experiment. Optogenetic stimulation during the shock phase reduced the percent time freezing during context retrieval (Jimenez et al. 2020). Motor Behavior Simultaneous optogenetics and calcium Ca2+ imaging is performed in different populations of cells to look into the functioning of fast-spiking interneurons in the control of motor behavior in an open field (Owen et al. 2018). References - Jimenez et al. (2020). Contextual fear memory retrieval by correlated ensembles of ventral CA1 neurons. Nature Communications: 3492. doi:10.1038/s41467-020-17270-w - Owen et al. (2018). Fast-spiking interneurons supply feedforward control of bursting, calcium, and plasticity for efficient learning. Cell (4): 683-695. doi:10.1016/j.cell.2018.01.005 - Stamatakis et al. (2018). Simultaneous optogenetics and cellular resolution calcium imaging during active behavior using a miniaturized microscope. Frontiers in Neuroscience: 496. doi:10.3389/fnins.2018.00496 Physical Setup Hardware Components - Noldus USB-IO box: PTIO-002x - Noldus Optical Isolated TTL-IO interface: PTISO-00x0 (also known as opto-isolator) - Inscopix nVoke or nVista DAQ box Connection Schemes Calcium Imaging (nVista) Basic connections for triggering video recording from EthoVision XT in nVista/nVoke systems: - Connect one of the TTL ports of the USB-IO box to the Opto-isolator using a network cable. - Connect the Out-1 port of the Opto-isolator to the TRIG port of the Inscopix device using cables with a BNC connector. Calcium Imaging + LED Stimulation (nVoke) Basic connections for triggering video recording and OG-LED stimulation from EthoVision XT in nVoke systems: - Connect the Out1 and Out2 ports of the Opto-isolator to the TRIG port and the GPIO port of the Inscopix device using cables with a BNC connector. - Note that a TTL port on the USB-IO box can send out signals through two independent lines (Output 1 and Output 2). - Make sure that the Trial Control procedure sends the correct commands to the Inscopix DAQ box through the two lines Out 1 and Out 2, one for TRIG and the other for GPIO. Notes Why Use an Opto-Isolator? If you do not have the Noldus Opto-isolator, you can connect the USB-IO box and the Inscopix directly. For this you need a cable with an Ethernet (RJ45) connector at one end and a BNC connector at the other end. However, we recommend using a Noldus Opto-isolator to prevent ground loops and preserve the TTL signals. Use one opto-isolator per TTL port of the USB-IO box. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Physical Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-physical-setup-YTL Chapter: EthoVision XT Physical Setup Components (Example) Devices - PC with EthoVision XT installed. - Noldus USB-IO Box. - PhenoTyper with adapted Top Unit (optional). - Prizmatix LED controller (for different light wavelengths). Important: To control the LED through EthoVision, on the back panel of the LED controller, near/below the TTL connector, select Ext (but if you want to activate the LED manually using the button located on the front panel, you should select Int). The other switch on the LED controller, just near/above the Ain 0-5V connector, should be in the Int position. - Prizmatix Pulser (left) or PulserPlus (right) (with advanced setup). Main Cables and Fiber Cords Port names are shown in bold; power cords and video cables are not listed. - USB cable (USB-A to USB-B): Use this cable to connect the EthoVision XT PC to the USB-IO box [USB, type-B]. Also use this cable to connect the Pulser to the PC. - UTP to BNC cable: To connect the USB-IO box [TTL control] to the LED Controller [TTL] or Pulser [Trig. In]. - Note 1: Each TTL port of the USB-IO box has two output lines. The white RCA jack corresponds to Output 1 and the red RCA jack to Output 2. Take note of this when selecting the TTL commands in EthoVision XT. - Note 2: If you received UTP-to-BNC cables with four BNC connectors, only use those marked with Output to connect the LED controller or Pulser. - BNC to BNC cable: From Pulser [TTL Out] to LED Controller [TTL]. - Fiber patch cord, core 1000 µm: To connect the LED Controller [front panel] to the PhenoTyper Top Unit [Fiber Coupler adapter]. - Fiber patch cord, core 1000 µm: Located inside the PhenoTyper Top Unit. Connects the FC adaptor to the Rotary joint. - Single fiber: To connect the Rotary joint fixed on the bottom plate of the PhenoTyper Top Unit to the implantable cannula. Available in various core diameters (e.g. 500 µm). Other Components - Zirconia ferrules (sleeves) for 2.5 mm and 1.25 mm cannulae. - Optogenetics implantable cannulae (2.5 mm, 1.25 mm). Basic Setup Aim With a basic setup, without the Pulser, EthoVision XT controls activation of the LED directly via the Noldus USB-IO box. With this setup you can, for example, activate the LED for one second. Notes - Activation of the LED can be repeated during a trial using the Subrule function in the Trial Control Settings. - For generating two pulses of different length, you must create separate Trial Control commands. Limitations - The pulse cannot be shorter than 0.1 s. - Accuracy of onset, offset and duration of a pulse is approximately the time taken by three samples. When tracking at 30 fps, this time is 0.1 s. The higher the sample rate, the higher the accuracy. Connection Scheme Cable connections for controlling the LED controller directly from EthoVision XT and the USB-IO box: - On the back panel of the LED controller, under the TTL connector, set the switch to Ext to enable external control of the LED. - Connect the LED controller to the USB-IO box using the white RCA jack if you use Output 1, or with the red jack if you use Output 2. - Set the switch near/above the Ain 0-5V connector to Int so you can manually adjust the light intensity using the knob on the front panel. Note: If you received UTP-to-BNC cables with four BNC connectors, only use those marked with Output to connect the LED controller. Advanced Setup (With Pulser) Aim With this setup, EthoVision XT controls activation of the LED via the Prizmatix Pulser and PulserPlus devices. With this setup you can send out very specific sequences of pulses, at a frequency higher (max 0.5 kHz) than with the basic setup. The sequence is predefined in the Pulser/PulserPlus. Note: PulserPlus is the device with three BNC connectors. Note: For information about how to use the Pulser with its own software, see the Prizmatix Pulser/PulserPlus user manual which comes with the device. Connection Scheme - If you received UTP-to-BNC cables with four BNC connectors, only use those marked with Output to connect the Trigger In/Trig. In port on the Pulser/PulserPlus. - On the LED controller, make sure that the switch near/below the TTL connector is in the Ext position. Also keep the switch near/above the Ain 0-5V connector in the Int position. - Connect the Trigger In / Trig. In port of the Pulser/PulserPlus to the USB-IO box with the white RCA jack if you use Output 1, or with the red jack if you use Output 2. - Connect the Pulser/PulserPlus to the PC with a USB cable. Important: If you have the PulserPlus, set the Operation mode switch to PC. For more information on how to install the Pulser/PulserPlus, see the user manual that comes with the device. Measure the LED Light Output In some circumstances you may want to measure the LED light intensity at the tip of the cannulae. For this you need a sensor and a power meter. Note that a standard power meter may not give accurate measurements. For suggestions on suitable power meters, see: https://www.prizmatix.com/blog/main/0/23/Optical-Power-Meters-for-Optogenetics An example is the Thorlabs S140C or Thorlabs S142C coupled with the Thorlabs PM100USB interface, which shows the measurements on a computer screen. See also: https://www.thorlabs.com/navigation.cfm?guide_id=37 Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Physical Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-physical-setup-QtF Chapter: EthoVision XT Physical Setup One-Cubicle Configuration The diagrams only include the connections essential for communication between EthoVision XT and the FCS. See also the Ugo Basile Fear Conditioning Systems NG Series instruction manual. Step by Step Instructions - Connect the EthoVision XT computer to the Ugo Basile FCS using the appropriate USB cable. You need a USB cable with a type-A connector at one end and a type-B connector at the other end. - Connect the camera to the PC. If your computer has an Ethernet board with one or two ports, you need a Power over Ethernet (PoE) injector. - Connect one of the ports of the Ethernet board of the computer to the PC port (IN) on the PoE injector. - Connect the camera port on the back of the cubicle to the CAM port (OUT) of the PoE injector. - Next, connect the PoE injector to a power outlet. If your computer has a 4-port Ethernet board installed, and if this board receives power from the PC internal power supply, you do not need a PoE injector. Connect the camera directly to one of the board's Ethernet ports. See the EthoVision XT Help for details. - Connect the Ugo Basile USB Hub to the power outlet using the appropriate power adapter. With the current version of the FCS you can control the IR light from EthoVision XT. If you have an older version, you must use the IR manual controller or upgrade the FCS. Please contact Noldus for information. The Video Camera The camera is embedded in the IR light box at the top of the cubicle. If you have not done so yet, you must configure the IP address of the camera and of the Ethernet port on your PC. You can find the IP address of the camera on the front panel of the cubicle's light box. Install and Configure the Cameras For details on how to install and configure the EthoVision XT cameras and adjust the IP addresses, see Camera Installation in the EthoVision XT Help. IR Light Box with Software Control FC systems of Model 46110-NL and Serial Number higher than 0676U24 are equipped with an IR light box that is switched on automatically when the cubicle is powered up. The default intensity is 100%. You can control the IR light intensity directly from the software (Trial Control Settings > Action > UB FCS IR Light). You no longer need additional hardware. It could happen that your system is recent but is not yet updated for this option. Please contact Noldus for information. You can also update the firmware of the cubicles using the firmware update procedure. IR Light Box with Manual Control In older FCS models adapted for use with EthoVision XT, the cubicle is equipped with an IR light box above the conditioning cage and an IR light controller to adjust the IR light intensity. - Connect the red and black cable that comes from the cubicle to the IR light controller. - Connect the IR light controller to a power outlet through its power adapter. Attach the IR light controller as indicated on the labels. If you work with multiple cubicles, connect the IR controller as explained above for all cubicles. Four-Cubicle Configuration Element 3 (IR light controllers) is for manual control of IR light and is no longer necessary in the current version of FCS. Step by Step Instructions - Connect each cubicle to the EthoVision XT computer through the Ugo Basile USB Hub. You need 5x USB cables with a Type-A connector at one end and a Type-B connector at the other end. - Connect the Ugo Basile USB Hub to the power outlet using the appropriate power adaptor. - Connect each camera to one of the ports of the Ethernet Interface board in the EthoVision XT computer. You need 4x Ethernet cables with RJ45 connectors. - Connect the Top Light Units to the power outlet through the appropriate power adaptors. - Connect one IR controller to each cubicle as described in the IR light box with manual control procedure. For more information on how to install and configure the Ethernet Interface board, see Install the GigE Cameras in the EthoVision XT Help. Note: The external IR light controller is no longer necessary if you have updated the cubicle firmware. Connect Multiple Cameras If your EthoVision computer is provided with a 4-port Ethernet interface board for connecting multiple GigE cameras, the cameras can receive power from the PC itself. If you purchased the computer and Ethernet board from Noldus, the board is already powered by the PC. Otherwise, open the computer casing and connect the Ethernet interface board to the internal power supply of the computer. Once power is provided through the PC, connect each camera to one of the ports of the Ethernet interface board. Label the ports and the cables so you always know which port is connected to which camera and which cubicle. IP Addresses Note: If you have the Ugo Basile FCS equipped with USB cameras, connect the cameras directly to the EthoVision XT computer and skip this section. If your FCS is equipped with Basler GigE cameras through Ethernet connections, each camera must have an IP address that matches the IP address of the Ethernet interface board on your PC. The basic rules are: - The first two numbers are the same for all cameras: 192.168. - The third number should be the same and unique for each camera-Ethernet port combination. - The fourth number can be any value, but must differ between the camera and the Ethernet interface board, and should suggest which cubicle (arena) it refers to. For example: - 192.168.1.101 for camera 1 (cubicle 1) and 192.168.1.x for Ethernet port 1 of the Ethernet interface board. - 192.168.2.102 for camera 2 (cubicle 2) and 192.168.2.52 for Ethernet port 2 of the Ethernet interface board. The IP address of each camera can be found on the front panel of the cubicle's light box. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Physical Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-physical-setup Chapter: EthoVision XT Physical Setup The following suggestions are specifically to optimize video tracking: - Place the plus maze in such a way that its apparent size is maximized. You can obtain this by rotating the plus maze (or the camera) until the closed arms lie along one of the diagonals of your video window. - The lighting should be as even as possible throughout the arena. Bright lights are not necessary but should you need to supplement the light, consider red (or infra-red) light, as the animals will be less sleepy. - The camera should have a good view of the entire region the animal can be in. Center the plus maze in order to have the image of the arms as symmetrical as possible. This minimizes inaccuracy of calibration due to perspective. - The lighting should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). Even, diffuse lighting is important to optimize tracking of the nose. - A plus maze with transparent walls may help reducing shadows and make it easier to observe closed arm rears. There is little practical difference between the two mazes in terms of their ability to detect differences in anxiety-related behavior. However, the transparent design may reduce the sensitivity for the detection of anxiolytic drug effects because it decreases the anxiogenic potential of the open arm, therefore leading to the reduction of anxiety-related behavioral baseline (Violle et al., 2009 and references therein). - The background should contrast with the animal. If necessary, use a different setup for light and dark colored animals. In the closed arms, the contrast between animal and background is generally lower. Take this into account when positioning lights and choosing the background color. - Make sure that the color of the floor is in good contrast with the color of the animal, and in minimal contrast with the arms. This makes it possible to track the animal's nose off the edge of the open arms. - Both the plus maze arms and the floor should not be reflective. If necessary, place an opaque rubber mat on the floor. - If there are barriers above the closed arms, remove them. If that is not possible, in the Detection Settings use the Dilation-Erosion filter (see page 97) to prevent EthoVision from "seeing" the animal cut in two. See also Contour Settings in the EthoVision XT Help. - Depending on circumstances, pools of urine can cause problems with the tracking. An absorbent base can help. - Always place the apparatus in the same position in the room, as cues from overhead might influence the behavior of the animal. For the same reason, the experimenter should not be visible to the animal during the trial (automated tracking makes this possible). - If you want to use the Deep Learning technique to track the subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Physical Setup (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-physical-setup-continued-Kgv Chapter: EthoVision XT Physical Setup (Continued) - Locate the holes on the back panel of the cubicle. - Attach the box to the back panel. Make sure that the cable connections are on top. - Put the lid of the box back in place and tighten the screws. - Connect the color-coded cables as shown in the next figure. - Finally, connect: - The upgrade box to the PC (or USB hub, in case of 2 or more cubicles) using the USB cable that came with the upgrade box. - The upgrade box to a power outlet. - The camera to the PC's Ethernet board. - Repeat the steps above for the remaining cubicles. - Next, follow the steps in the section The Fear Conditioning Experiment in EthoVision XT. Update the Cubicle Firmware Aim To make the FCS cubicles compatible with the new IR illumination system that is fully controllable from EthoVision XT. Important: Follow this procedure only when requested by Noldus Support. What You Need - The firmware updater installation files: FW_Updater Setup.msi and setup.exe. - The new firmware file Cubicle.elf_7.34.S19. Procedure - On the EthoVision XT full installation package, open Drivers and Tools > Utilities > Ugo Basile FCS. You can download the full installation package from my.noldus.com. - Copy the file Ugo Basile FCS FirmWare Updater [version number].zip to your EthoVision XT PC and extract its contents. - Double-click the file setup.exe. Complete the installation procedure. - Power up the cubicle and connect it to the EthoVision XT PC through the USB cable. - Start the application. - Choose Select Firmware. - In the window that opens, choose the file Cubicle.elf_7.34.S19. - Click Firmware Update. - If the current version is 2.27 or newer, the update process should start automatically. Otherwise, you need to: - Disconnect both the power supply and the USB cable from the cubicle. - Reconnect both the power supply and the USB cable, approximately at the same time. - Wait until the Erase and the Programming processes are completed. - After the device has rebooted, you can change the tab to Board Settings. - Leave or set the Device ID and set the Default IR Intensity to the desired value (recommended: 100%). This will be the default intensity at startup. - Click Save to Board. Check the Ugo Basile Interface for EthoVision XT - Open Control Panel > Programs and Features. - Check that the software Noldus - HardwareInterface UgoBasile - x64 package version 1.0.14 or later is installed. If a previous version is installed, uninstall it. Next, copy the file HardwareInterfaceUgoBasile - X64 Package - [version number].msi from the EthoVision XT 18 full installation package, under Drivers and Tools > Prerequisites > HardwareInterfaceUgoBasile to your PC, then run this file. Test the IR Light To test the IR light, in the Trial Control Settings create an action based on the IR Light. Set the intensity to 100% and click Test. Click OK then check in the Detection Settings whether the IR light is still on. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Physical Setup (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-physical-setup-continued Chapter: EthoVision XT Camera Settings Camera Type and Lens The camera used in Noldus systems for Fear Conditioning is a Basler camera acA1300-60gm with a 2.95 mm fixed focal lens, F2.0, 1/1.8". How to View the Live Camera Image In order to view the camera image, you must activate the IR light in the cubicle. The camera has an IR-pass filter that blocks visible light. - Make sure that the camera has been configured and connected to the PC. - Start EthoVision XT and create a new experiment (File > New) or open an existing experiment without trials acquired. - Choose Setup > Experiment Settings. - Under Video Source select Live tracking. - Select the camera from the list under Source. - Click the camera button for the live view. Camera Orientation The camera has been optimized at Noldus before shipping, therefore in most cases you do not need to adjust its orientation. If, for any reason, the video image is not optimized, follow the instructions below. Camera Alignment This section applies for previous FCS versions which had the Noldus IR light box on top. Turn the three screws indicated to alter the camera orientation. If you tighten one of the screws, the camera points more to the other side. Loosen the same screw to have the opposite effect. For example, tighten screw b to have the camera pointing more to the back of the cubicle. Check the resulting image in EthoVision XT; make sure that the bottom of the cage is aligned at the center of the camera view. Camera Software Settings The camera frame rate, exposure time, and other settings can be adjusted in EthoVision XT or in the camera software Pylon Viewer. In EthoVision XT, choose Setup > Experiment Settings. Click the camera button and locate the settings you want to change. For multiple cameras, adjust the settings for the first camera, then adjust the resolution of the Merged view. Video Resolution and Camera Zoom Level The camera lens of the FCS is a fixed focal lens. To adjust the zoom level, adjust the video resolution (in pixels) so that a portion of the maximal camera view is recorded. Note how the resolution setting crops the image. - Color Space: Mono8 (Y800) - Video Resolution Single Camera (H x V): 640 x 480 - Video Resolution Merged View (H x V): 1280 x 960 - Acquisition Frame Rate: 25 or 30 In the example configuration, EthoVision XT makes a video of 1600 x 1200 from four cameras set to 800 x 600. Important: Whenever you change the resolution, open the Arena Settings and update the background image for your arenas before acquiring data. The Binning Option If you need to reduce the video resolution without cropping the image, you can use the Binning option in the Video Settings of EthoVision XT. In EthoVision XT, choose Setup > Experiment Settings. Click the camera button and in the Video Settings window click the General tab. Select the Binning option. The Binning option reduces the number of pixels of the single camera image by half but does not crop the image. - If you select Binning, be aware that the brightness of the image increases. Make sure this does not negatively affect detection. If the image is too bright, reduce the Exposure time or the Gain. - The Binning option must be the same across all cameras. Remember to select or de-select the Binning option for all cameras before setting the resolution of the merged view. Image Brightness If the image from the camera is too dark, do one of the following based on your FCS version: - If you have the IR light controller attached to the cubicle, turn the knob of the IR light controller all the way to the right. In most cases this is enough to make detection optimal. - Increase the IR light intensity up to 100% with the Trial Control Settings in EthoVision XT. - Increase the IR light intensity using the software on the tablet PC. - Place white plates at the sides and at the bottom of the FCS cage to increase contrast with dark-fur animals. Place dark plates in case of white animals. To increase the brightness of the image further, adjust camera settings in EthoVision XT or Pylon Viewer: - Increase the camera Exposure time. Be aware that a too-high exposure time may conflict with the camera frame rate. EthoVision XT shows a message in the Video Settings window if that is the case. - Increase the Gain. Be aware that a higher Gain also creates more image noise. - To increase brightness without increasing noise, set Binning Horizontal and Binning Vertical with the Binning Mode set to Summing for both. Note that with binning, the video resolution width and height in pixels will be half of the original. Older versions of the Ugo Basile FCS have the IR light source placed at one of the top corners of the cubicle. You do not need to operate this light if you have the IR light box above the conditioning cage. Upgrade Your FCS System Aim To adapt the Fear Conditioning System for use in combination with EthoVision XT 17.5 and later. The touchscreen controller is no longer needed. You can adjust the FCS settings (e.g. tone frequency, shock current) directly in EthoVision XT. The time needed for installation and setting adjustment is approximately one hour. Prerequisites You have received the following from Ugo Basile: - 1x upgrade box for each cubicle - 1x power cable, 1x USB cable, 4x color-coded cables for each cubicle - Two hexagonal Allen keys Ugo Basile requires the touchscreen controller to be returned first, so that they can copy the settings of the touchscreen controller and Fear Conditioning box to the upgrade box. This ensures you can work with the same settings as before. Procedure - Remove the four screws at the corners of the upgrade box and remove the cover plate. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Recognition Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-recognition-test Chapter: EthoVision XT Introduction The Novel Object Recognition (NOR) test was first described by Ennaceur and Delacour (1988). Rats or mice are exposed first to two identical objects and then one of the objects is replaced by a new (novel) object. The time spent exploring each of the objects is measured. The test has become popular for assessing visual memory in rodents in general and to test the effects of amnesic drugs in particular. The test is based on spontaneous behavior with no reinforcement such as food or shock. Non-amnesic animals will spend more time exploring the novel object than the familiar one. An absence of any difference in exploration time can be interpreted as a memory defect or, in case an amnesic drug is tested, a non-effective drug. This chapter describes how a NOR test can be conducted with EthoVision XT. On the downloads section of the Noldus website my.noldus.com, you find a number of sample experiments, including one that features a NOR test. The Sample Experiment To see how a Novel Object Recognition test is carried out in EthoVision XT, see also the sample experiment Novel Object Recognition test XT180 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. In EthoVision XT, choose File > Restore Backup and select the file. For more information, see the document Description of sample experiments of EthoVision XT.pdf. References - Ennaceur, A.; Delacour, J. (1988) A new one-trial test for neurobiological studies of memory in rats, 1: Behavioral data. Behavioral Brain Research, 47-59. - Benice, T.J.; Raber, J. (2008). Object recognition analysis in mice using nose-point digital video tracking. Journal of Neuroscience Methods, 422-430. - McDowell, K.A.; Hutchinson, A.N.; Wong-Goodrich, S.J.E.; Presby, M.M.; Su, D.; Rodriguiz, R.M.; Law, K.C.; Williams, C.L.; Wetsel, W.C.; West, A.E. (2010). Reduced cortical BDNF expression and aberrant memory in Carf knock-out mice. The Journal of Neuroscience, (22), 7453-7465. - Siegel, J.A.; Park, B.S.; Raber, J. (2011). Long-term effects of neonatal methamphetamine exposure on cognitive function in adolescent mice. Behavioural Brain Research, 159-164. - Simmons, D.A.; Rex, C.S.; Palmer, L.; Pandyarajan, V.; Fedulov, V.; Gall, C.M.; Lynch, G. (2009). Up-regulating BDNF with an ampakine rescues synaptic plasticity and memory in Huntington's disease knock-in mice. PNAS, 4906-4911. For a complete list of publications, see the results of Google Scholar. Physical Setup The following suggestions are specifically to optimize video tracking. For general information, see the section Physical Setup in the chapter The Open Field Test. - The objects should contrast with the animal. If necessary use a different setup for light and dark colored animals. - Make sure that the objects do not move due to the activity of the animal. - Either make sure the sides of the box are not reflective (for example, sand the box to make it matte), or exclude the sides from the arena. If your objects are close to the sides, you will need to track the animal when it is against the side. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Response (Ppi) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-response-ppi Chapter: EthoVision XT Introduction Startle Pre-Pulse Inhibition (PPI) is an experimental paradigm to study sensorimotor gating. With this term we intend the ability of the brain to filter out irrelevant sensory stimuli to suppress or decrease a motor response, in this case, a startle response. The Startle PPI paradigm has been widely used in rodents, such as mice and rats, to study sensorimotor gating deficits in different animal models. In a typical PPI experiment, a startle baseline is measured as a response to a loud sound, or a light or air-puff. A pre-pulse stimulus is delivered shortly before the loud stimulus. That is supposed to decrease the startle reaction. This section refers to the Ugo Basile system for the Pre-Pulse Inhibition of the Startle Reflex. You can have this system send TTL signals to EthoVision XT when a pulse is fired or terminated, and when an environmental output is activated or deactivated. This way the EthoVision XT tracking information is synchronized with the main events generated by the PPI system. Connection Scheme For this you need the Ugo Basile PPI Startle Reflex Interface. This Interface box is connected to the PPI Startle Reflex system through a flat cable and has two additional output connectors, OUT 1 and OUT 2. You can connect one or both outputs to TTL ports of the USB-IO box. Contact Noldus if you need the proper adapter cables. - OUT 1 can be enabled with each stimulus pulse (or pre-pulse). The status is ON while the pulse is fired and OFF when the pulse is terminated. - OUT 2 can send out "environment" signals, like that for the visible light, the infrared light or the fan that can be turned ON or OFF at a specific time during the trial. See also the Ugo Basile Pre-Pulse Inhibition of Startle Reflex (PPI) User Guide. EthoVision XT - In the Experiment Settings, define the TTL ports as Custom Hardware. - In the Arena Settings, click the Arena - Hardware Mapping button and define the devices for each arena. - In the Analysis Profile, define a Hardware State variable for example to visualize the pulses together with the tracking data. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - The Nor Test In Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-the-nor-test-in-ethovision-xt Chapter: EthoVision XT The NOR Test in EthoVision XT Create an experiment from a template (Ctrl+T). Choose Open field (round or square) as Arena template, and Novel object zones as Zone template. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. The PC must have a powerful graphics card which supports additional software (CUDA). See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings These settings enable you to record behaviors manually, using keystrokes. This is handy for example to record exploratory behaviors like sniffing. Choose Setup > Manual Scoring Settings. If you created the experiment from the template with novel object zones, the Manual Scoring Settings already includes one behavior, Sniffing object. This is defined as "start-stop", which means that you press a key (default: q) to score the start of sniffing, and then you press the same key once again to score the end of sniffing. For more information, see Manual Scoring Settings in the EthoVision XT Help. Note: With the Rat or Mouse Behavior Recognition add-on, you can have EthoVision XT detect sniffing and other behaviors, without the need to score them manually. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. To set up your Arena Settings: - Click the Grab Background Image button to grab an image of the empty enclosure from the camera image. - Click 1. Draw Scale to calibrate your arena (for details, see the EthoVision XT Help). Tip: Draw the double-arrow in such a way it points to two opposite walls of the open field, at the level where the animal moves (thus not at the top of the walls). When done, enter the distance in real world units between the tips of the arrow. - Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. Tip: If the arena is not yet defined and you want to divide it into equal zones, click 2. Select Shape and Draw Arena. Choose the tool that applies depending on the shape of your open field and draw the outline of the arena. - If you used the Zone template Novel object zones, click 3. Select Shape and Draw Zones. Click the layer Zone group Objects. Check that the object 1 zone and object 1 boundary zone cover the object. If the predefined zones do not have the correct shape, delete the zones and draw new ones. - If necessary, draw additional zone groups/zones. Additional Zones - Zone group Floor and Wall: Check that the Floor zone covers the whole floor area of the open field. - Zone group Halves: Check that the West and East zones divide the Floor zone into two equal halves. Make sure that the vertical line crosses the entire arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings. The template contains the following profiles: - Default: Tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops when you click the Stop trial button. - Track duration 10 min: Tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops automatically after 10 minutes. To Stop Tracking When Exploration Exceeds a Specified Time You can also stop tracking when the subject has spent some time around an object. For example, when the protocol specifies that in pre-test trials the animal must explore an object for at least 30 seconds. Make a new Trial Control Settings, and immediately before the Stop track box, insert a Condition box based on the variable In zone, or another variable, or a combination of variables using Multi condition. In the Condition settings, specify that Cumulative duration in the boundary zone for that object must be greater than N seconds, for the nose point. If you use Multi condition, you can define "exploration" as a combination of variables. For example: - In Zone for the nose point in the "object zone" is true - Head directed to Zone "object" is true - Velocity lower than 5 cm/s is true The trial stops only when the cumulative time that the three criteria are met reaches the specified value. To Stop Tracking Automatically When No Exploration Occurs To stop tracking automatically even when the animal does not explore the object, add another condition in parallel with the first one, which specifies to stop tracking after some time (e.g. 10 minutes), and combine the two conditions with an Operator box of type ANY. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Advanced Detection Settings If detection of the subject is not optimal after using the Automated setup function, do the following: - Check that the sample rate is set to at least 25 samples/second when tracking the nose and tail. - Check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals. - When using Dynamic subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. Specify the Current frame weight. A low value (for instance, 1 to 10) usually works well. A novel object test normally has a duration of a few minutes in which the background does not change much. When using Differencing, set the Sensitivity slider. The slider determines what difference in contrast from the background is detected. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - The Nor Test In Ethovision Xt (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-the-nor-test-in-ethovision-xt-continued Chapter: EthoVision XT Trial List Choose Setup > Trial List. Defining Independent Variables Enter your independent variables such as: - Subject ID with the ID of your animals as predefined values. - Phase with Acclimation, T1, T2 as predefined values, where: - Acclimation to mark trials where the animal is free to explore the arena, with no objects present. - T1 to mark trials where the animal is presented with a pair of identical objects. - T2 to mark trials where one of the familiar objects is changed for another new (novel object test). - Treatment with Treated and Control as predefined values. If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help. Detection and Tracking Settings When detection is not satisfactory, select Rodents / For Occlusions as the tracking method and repeat the detection setup steps. Note: If you want to use the Deep Learning technique to track the subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - The Radial Arm Maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-the-radial-arm-maze-test Chapter: EthoVision XT The Radial Arm Maze Test Introduction The Radial Arm Maze test is a behavioral assessment used to evaluate spatial learning and memory in rodents. Physical Setup Details on the physical configuration required for the Radial Arm Maze test. The Radial Arm Maze Test in EthoVision XT Experiment Settings Configuration of experiment-level settings within EthoVision XT. Arena Settings Define and configure the arena for the Radial Arm Maze. Trial Control Settings Settings to control trial behavior and timing. Detection Settings Configure animal detection parameters. Trial List Define and manage the list of trials for the experiment. Acquiring Data Protocol Step-by-step protocol for acquiring data in the Radial Arm Maze test. Data Analysis Data Preparation Prepare acquired data for analysis. Analysis Profiles Configure and apply analysis profiles. Testing Working Memory Methods and metrics for evaluating working memory performance. Testing Reference Memory Methods and metrics for evaluating reference memory performance. Integrated Visualization Use integrated visualization tools to review behavioral data. Heatmaps Generate and interpret heatmaps of animal movement and location. Calculating Statistics Perform statistical calculations on analyzed data. The Porsolt Forced Swim Test Introduction The Porsolt Forced Swim Test is a widely used model for assessing depressive-like behavior in rodents. Physical Setup Details on the physical configuration required for the Porsolt Forced Swim test. The Porsolt Forced Swim Test in EthoVision XT Experiment Settings Configuration of experiment-level settings within EthoVision XT. Manual Scoring Settings Configure settings for manual behavioral scoring. Arena Settings Define and configure the arena for the Forced Swim test. Trial Control Settings Settings to control trial behavior and timing. Detection Settings Configure animal detection parameters. Trial List Define and manage the list of trials for the experiment. Acquiring Data Protocol Step-by-step protocol for acquiring data in the Forced Swim test. Score Behaviors Manually Instructions for manually scoring observed behaviors during acquisition. Determining Mobility Thresholds Define thresholds used to classify mobility states. Determining Activity Thresholds Define thresholds used to classify activity states. Data Analysis Data Preparation Prepare acquired data for analysis. Integrated Visualization Use integrated visualization tools to review behavioral data. Analysis Profile Configure and apply an analysis profile for the Forced Swim test. The Fear Conditioning Test Introduction - Principle of Operation: Overview of how the Fear Conditioning test functions. - Changes Relative to Previous EthoVision XT Versions: Summary of updates from earlier versions. - If You Have the "Old" FCS Setup: Guidance for users with legacy Fear Conditioning System hardware. - For General Information: Additional background and reference information. Physical Setup One-Cubicle Configuration Setup instructions for a single-cubicle Fear Conditioning System. Four-Cubicle Configuration Setup instructions for a four-cubicle Fear Conditioning System. Camera Settings Configure camera positioning and settings for the FCS. Upgrade Your FCS System Instructions for upgrading existing Fear Conditioning System hardware. Update the Cubicle Firmware Steps to update firmware on FCS cubicles. The Fear Conditioning Experiment in EthoVision XT Prerequisites Requirements that must be met before configuring the experiment. Create an EthoVision XT Experiment Steps to create a new Fear Conditioning experiment in EthoVision XT. Experiment Settings Configuration of experiment-level settings within EthoVision XT. COM Port Communication Configure COM port settings for hardware communication. Arena Settings: Define the Arenas Define arenas to correspond with physical cubicle configurations. Arena Settings: Declare the FCS Devices Declare and link Fear Conditioning System devices within arena settings. Examples of Arena-Hardware Mapping Illustrative examples of how arenas map to physical hardware. Test the FCS Devices Procedures for verifying that FCS devices are functioning correctly. Trial Control Settings Settings to control trial behavior, timing, and stimulus delivery. Detection Settings Configure animal detection parameters for fear conditioning trials. Troubleshooting Common issues and recommended solutions for the Fear Conditioning setup. Acquire the Data Things to Check First Pre-acquisition checklist to ensure the system is ready. Acquire Data Step-by-step instructions for running the experiment and recording data. Analyze the Data Basic Steps Overview of the fundamental steps for analyzing Fear Conditioning data. Analyze Events Methods for analyzing discrete behavioral events. Analyze Intervals Methods for analyzing behavioral data across defined time intervals. Technical Specifications Infrared Top Light and Controller Technical specifications for the infrared top light and its controller unit. Other Conditioning Tests Introduction Overview of additional conditioning paradigms supported by EthoVision XT. Physical Setup Details on the physical configuration required for other conditioning tests. A Conditioning Test in EthoVision XT Experiment Settings Configuration of experiment-level settings within EthoVision XT. Arena Settings Define and configure the arena for the conditioning test. Trial Control Settings Settings to control trial behavior and stimulus delivery. Detection Settings Configure animal detection parameters. Trial List Define and manage the list of trials for the experiment. Pre-Pulse Inhibition of the Startle Response (PPI) Introduction Overview of the Pre-Pulse Inhibition paradigm and its application. Connection Scheme Diagram and description of hardware connections required for PPI testing. Data Analysis Data Preparation Prepare acquired data for analysis. Data Selection Select relevant data subsets for focused analysis. Analysis Profiles Configure and apply analysis profiles for conditioning test data. Integrated Visualization Use integrated visualization tools to review behavioral data. The RotaRod Test Introduction The RotaRod test assesses motor coordination, balance, and fatigue in rodents using a rotating rod apparatus. Physical Setup Details on the physical configuration required for the RotaRod test. The RotaRod Test in EthoVision XT Experiment Settings Configuration of experiment-level settings within EthoVision XT. Arena Settings Define and configure the arena for the RotaRod test. Detection Settings Configure animal detection parameters for RotaRod trials. Acquiring Data Step-by-step instructions for running the experiment and recording data. Data Analysis Overview of analysis methods and metrics for RotaRod performance evaluation. The Y-Maze Test Introduction - The Y-Maze: Overview of the Y-maze apparatus and its behavioral applications. - Spontaneous Alternation: Description of the spontaneous alternation paradigm. - Delayed Alternation: Description of the delayed alternation paradigm. The Y-Maze Test in EthoVision XT Experiment Settings Configuration of experiment-level settings within EthoVision XT. Arena Settings Define and configure the Y-maze arena. Trial Control Settings Settings to control trial behavior and timing. Detection Settings Configure animal detection parameters. Trial List Define and manage the list of trials for the experiment. Acquiring Data Protocols Step-by-step protocols for acquiring data in the Y-maze test. Data Analysis Analysis Profiles Configure and apply analysis profiles for Y-maze data. Alternation Behavior Methods for calculating and interpreting alternation behavior metrics. Visualizing Data Tools and approaches for visualizing Y-maze behavioral data. Optogenetics Experiments Introduction - Optogenetics and EthoVision XT: Overview of optogenetics integration within EthoVision XT. - Examples: Illustrative examples of optogenetics experiment designs. Physical Setup Components (Example) List of hardware components used in an example optogenetics setup. Basic Setup Instructions for configuring a basic optogenetics experimental setup. Advanced Setup (With Pulser) Instructions for configuring an advanced setup incorporating a Pulser device. Measure the LED Light Output Procedures for measuring and verifying LED light output levels. Optogenetics Experiments in EthoVision XT Experiment Settings Configuration of experiment-level settings within EthoVision XT. Arena Settings Define and configure arenas for optogenetics experiments. Trial Control Settings Settings to control trial behavior and light stimulation delivery. Detection Settings Configure animal detection parameters for optogenetics trials. Using the Pulser Pulse Sequences Define and configure pulse sequences for light stimulation. Configure the COM Port for Each Pulser Steps to configure COM port settings for each connected Pulser device. Program the Prizmatix Pulser/PulserPlus Within EthoVision XT Instructions for programming the Prizmatix Pulser or PulserPlus directly within EthoVision XT. Program the Prizmatix Pulser/PulserPlus With the Prizmatix Software Instructions for programming the Prizmatix Pulser or PulserPlus using the dedicated Prizmatix software. Advanced Applications Differential Stimulation Depending on Zone Configure stimulation that varies based on the animal's current zone location. Multiple Simultaneous Stimulations in One Arena Set up and manage multiple simultaneous light stimulations within a single arena. Simultaneous Stimulations in Two or More Arenas Configure and synchronize stimulations across two or more arenas simultaneously. Data Analysis Simple Data Selection Basic methods for selecting data subsets for analysis. Advanced Data Selection Advanced techniques for selecting and filtering data. Calculating Statistics Perform statistical calculations on analyzed optogenetics data. Integrated Visualization Use integrated visualization tools to review optogenetics behavioral data. Installing the Prizmatix Pulser Software Installation Steps to install the required software for the Prizmatix Pulser. Driver Update Instructions for updating device drivers for the Prizmatix Pulser. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - The Rotarod Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-the-rotarod-test Chapter: EthoVision XT Introduction The rotarod test is widely used to evaluate drug effects on motor coordination in rodents. The principle of this test is that rats or mice are first trained to walk on a rod rotating at a certain speed. Once the animals have learned this, the effect of a test-compound on their motor performance is evaluated. Animals experiencing impaired motor coordination are unable to cope with the rotating rod and will drop off when the rotation speed exceeds their motor coordination capacity. The more disturbed the animals are, the sooner they fall off the rod. The use of rotating rods to measure balance in rodents has been described since at least the 1950s (Dunham and Miya, 1957; Kinnard and Carr, 1957). Jones and Roberts (1968) introduced a significant modification of the basic design with an accelerating rod. The rotarod is a horizontal cylinder that rotates along its long axis. It is situated above the cage floor, high enough to make sure rodents do not jump off the rod and low enough to avoid them being injured when they fall off. The speed of the rotarod is mechanically driven and can be constant or accelerated during the test. The test consists of a training phase in which the rats or mice learn to walk on the rod at a certain speed. Then three test trials are carried out in which a drug is tested. A commonly measured parameter is the time until falling off. With EthoVision XT the Rotarod test can be automated. A camera is placed above the Rotarod, which gives a top-view image of the setup. The rat or mouse that stays on the rod is present in the center of the camera image. When the animal falls off, or clings onto the rod and turns round on it, it moves out of the center of the image. This can be automatically quantified with various parameters in EthoVision XT. References - Dunham, N.W. and Miya, T.S. (1957). A note on a simple apparatus for detecting neurological deficit in rats and mice. J. Am. Pharmac. Assoc. Sci. Ed., 208-209. - Jones, B.J. and Roberts, D.J. (1968). The quantitative measurement of motor inco-ordination in naive mice using an accelerating rotarod. J. Pharm. Pharmacol., 302-304. - Kinnard, W.J. and Carr, C.J. (1957). A preliminary procedure for the evaluation of central nervous system depressants. J. Pharmacol. Exp. Ther., 354-361. - Carter, R.J., Morton, A.J., and Dunnett, S.B. (2001). Motor Coordination and Balance in Rodents. In Current Protocols in Neuroscience (2001) 8.12.1-8.12.14. - Mahieu, M., Willems, R., Hoekstra, L., Ver Donck, L. (2012). Automated Detection of Aberrant Behaviour of Mice on the Rotarod: Use of EthoVision® XT. Proceedings of Measuring Behavior 2012 (Utrecht, The Netherlands, August 28-31, 2012) 431-433. Physical Setup In most use cases, a video camera is positioned above the rod to record video. For systems with multiple rods, it is best to point one camera towards each rod. You can mix camera images directly with EthoVision XT or a video mixer. To detect the falling off the rod automatically, place the camera in front of the rotarod. You can have EthoVision XT detect the fall off event when the animal disappears from the arena, or a zone drawn around the rod. The Rotarod Test in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Select the number of cylinders as Number of Arenas. Arena Settings Choose Setup > Arena Settings > Open Arena Settings. - After calibrating, click Select Shape and Draw Arena. The arena covers the region around the rod. Make sure that the animal is always within the arena boundary. Zones - Click Select Shape and Draw Zones. To quantify the position of the subject's center point relative to the center of the rod, define a zone (Reference zone) at a known distance from the rotation axis of the rod. For example, draw a line (Reference line) at the right margin of the arena, and define a zone. You can then analyze the distance of the subject's center point from the border of this zone. If you know that the border of the zone is for instance at 10 cm from the rod axis (Reference distance), then you can back-calculate the relative distance of the subject center from the axis. The values of Distance to zone (border) diminished by the Reference distance will be either positive (when the subject moves forward on the rod) or negative (when it moves backward). To measure the reference distance exactly, place a ruler on top of the rod, and refresh the background image. Then draw the Reference line at a specific distance from the rod. Note: Do not define the Reference zone in the middle of the rod. If you do that, distance from the zone border will always be positive, no matter what the position of the subject is. Zones for Turnaround Behavior Detection To automate turnaround behavior (mice grip themselves to the rod and turn around without falling off), you can define zones in front and at the back of the rod. Divide the arena in three main zones: Middle (the rod area), the Front and the Back areas just outside of the rod. It is then possible to detect turnaround behavior with the following sequence in the Zone transition variable: Middle (mouse in normal position) > Back > Front (the mouse reappears in view) > Middle. Detection Settings Click Advanced. Under Subject Contour, select one or more pixels for the first Erosion and Dilation filter. Increase the first Erosion until the subject's tail is not detected anymore. Then, increase Dilation until the entire body is detected. Acquiring Data Training Phase This phase lasts typically three days. Each subject is placed on the rotarod for a maximum of 1 minute. The trial is repeated a few times each day, with 5 to 10 minutes inter-trial interval. Testing Phase Each subject is placed on the rotarod for a maximum of 1 minute. The trial is repeated two times with 5 to 10 minutes inter-trial interval. Scoring Behaviors Manually If you want to score when the animal falls off the rod, define the behavior Falling off under Manual Scoring Settings. After you have started the trial, watch the subjects in the video and in the Manual Scoring tab at the bottom of the screen, click the button for the arena (subject) that applies. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - The Sociability Test In Ethovision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-the-sociability-test-in-ethovision Chapter: EthoVision XT Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. If you want to analyze exploration in detail, choose Center-point, Nose-point and Tail-base detection. If you want to use the Deep Learning technique to track the subject's nose, under Body Point Detection Technique choose Deep Learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings If your EthoVision XT license does not include the Behavior Recognition module, EthoVision XT cannot detect sniffing or rearing automatically. However, you can still score those and other behaviors with keystrokes. Choose Setup > Manual Scoring Settings. If you used the template for an open field experiment, four behaviors have been defined: - Sniffing R and Sniffing O, to record manually sniffing at the receiver (unfamiliar mouse) and object (either familiar mouse or empty cage, depending on the test), respectively. - Rearing R and Rearing O, to record manually rearing at the receiver (unfamiliar mouse) and the object cage (either familiar mouse or empty cage, depending on the test), respectively. You can also rename the behaviors if you like. Arena Settings Choose Setup > Arena Settings. If you work with a Sociability test cage with backlight unit, you can reduce the intensity of the backlight before adjusting the arena settings. This makes the edges of the floor plate and walls more visible. If the separation walls show reflections of the animal, this may hinder tracking. In the Arena Settings, click the Arena layer and draw rectangles around the separation walls. Detection Settings Choose Setup > Detection Settings. Check in the Video Section that the sample rate is set to: - Center-point tracking: 5–8 samples/second (for rats) and 12.5–15 samples/second (for mice). - Nose-tail tracking (rats and mice): 25–30 samples/second. Notes If detection of the subject is not optimal after using the Automated Setup function, see Configure Detection Settings in the EthoVision XT Help for details on the advanced detection settings. If you use hooded animals, use the detection method Differencing. If the animal moves from one compartment to the other, it may not be detected well. To improve detection, open the Advanced section in the Detection Settings pane. Under Subject Contour, select one or more pixels for the Dilation filter and the second Erosion filter. Leave the first Erosion filter set to zero. Select more pixels for Dilation than for Erosion (for example, 3 vs. 1) until the entire animal's contour is detected. Trial List Choose Setup > Trial List. Click Add Variables and enter your independent variables such as the experimental phases and the ID code of your test subject. Acquiring Data Protocol Sociability Test For each test animal, three trials are carried out: - The first trial (for example, 5 min) aims at habituating the test individual to the chamber. Tracking is required when one wishes to know whether the animal explores one chamber more than the other. - A second trial (5 min) is carried out with the empty tubes in the test chambers. The aim of this trial is to quantify the time spent in the two side chambers and near the tubes. - In the third trial (next 5 min), an empty tube is removed and replaced by a female animal restrained in an identical tube. This session is designed to observe differences between the time spent sniffing the social versus non-social object. Social Discrimination Test For each test animal, three trials are carried out: - The first trial (10 min) is aimed at habituating the test individual to the chamber and empty tubes. - In the sociability test (next 10 min), an empty tube is removed and replaced by a female animal restrained in an identical tube. This session is designed to observe differences between the time spent sniffing the social versus non-social object. - In the social discrimination test (10 min), the other empty tube is removed and replaced by a novel female. This session is designed to test the ability of the test animal to distinguish between the two females. Score Behaviors Manually To score sniffing and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you will find the key codes for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen. Notes - Important: If you are doing tracking from video, make sure you deselect DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score Behaviors Manually in the EthoVision XT Help. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - The Y-Maze Test In Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-the-y-maze-test-in-ethovision-xt Chapter: EthoVision XT Experiment Setup Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. For suggestions about optimizing lighting, see the lighting optimization section of this manual. Experiment Settings Choose Setup > Experiment Settings. - Number of Subjects per Arena: 1 - Tracked Features: Center-point detection or center point, nose-point and tail-base detection. If you want to use the Deep Learning technique to track the subject's nose, under Body Point Detection Technique choose Deep Learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Arena Settings For the Spontaneous Alternation Task - Choose Setup > Arena Settings > Open Arena Settings 1. - Choose the video/camera image and click Grab. - Click 2. Select Shape and Draw Arena. Resize and move the outline of the arena to make it overlap with the Y-maze image. For details on how to resize and move the arena outline, see Arena Settings in the EthoVision XT Help. For the Delayed Alternation Task Choose Setup > Arena Settings > New. After calibrating and drawing the outline of the arena, click 3. Select Shape and Draw Zones. Draw the three arm zones. To draw the start box zone and the target zones (that is, the arm ends which will be baited with food), create an additional zone group. For details on how to work with zone groups, and draw and edit shapes, see Arena Settings in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of data acquisition. Choose Setup > Trial Control Settings > New. The templates for the Y-maze contain the following Trial Control Settings profiles: - Default: Tracking starts when the subject's center point is detected for 1 second in the arena. Tracking stops at the end of the video or when you give the stop command. - Tracking Duration 5 min: Tracking starts when the subject's center point moves from the start box to the center arm. Tracking stops after 5 minutes. Detection Settings Choose Setup > Detection Settings. Check in the Video Section that the sample rate is set to: - Rats: 5 samples/second - Mice: 12.5–15 samples/second However, when tracking the nose-point, center-point and tail-base point of the rodents, always choose the maximum sample rate. If you selected the Deep Learning technique to track the subject's nose, under Method next to Deep Learning click Define and select a box around the subject. Make sure that the box includes the subject's nose. Try not to include objects like walls, especially if they are the same color as the subject. For details, see the EthoVision XT Help. Trial List Independent Variables If you perform a Y-maze test where one of the arms is closed off or provided with food, it is always a good idea to create independent variables that mark the type of trial. For example, create the independent variable Correct Choice with possible values Yes and No, depending on whether the subject chose the arm not visited in the previous trial. At the end of each trial, enter the value for that subject. You can use this variable to filter trials based on the value of Correct Choice. Acquiring Data Protocols Continuous Spontaneous Alternation - Release the subject in the center of the Y-maze. - Start the trial. - Let the subject explore the maze for the time required (typically 5–6 minutes). Then stop the trial. - Put the subject back in its home cage. Proceed with the next subject. Forced-Choice Alternation In this variant, the subject is forced to explore one of the two arms in the first trial. - Close one of the arms of the maze. Place the subject into the start arm and allow it to explore the maze for 15 minutes. - After a fixed inter-trial interval, open the door in the blocked arm. Return the subject to the maze by placing it in the start arm. The subject is allowed to explore freely all three arms of the maze for 5 minutes. The Y-maze is often rotated between the two trials. Two-Trial Spontaneous Alternation In this task, the subject is confined for a fixed time in the T- or Y-maze arm chosen in the first trial. This allows manipulation of the time that the animal has experience with one of the arms. - In the first trial, let the subject access one of the arms after having left the start arm. Once an arm has been entered, close off that arm by lowering a guillotine door behind the subject. Leave the subject there for a fixed time (this is called the intra-trial interval). - Remove the subject and, after an inter-trial interval, let it choose the arm in a second trial. This two-trial sequence is repeated a number of times. Delayed Alternation This task is usually designed with a T- or Y-maze where one arm is the starting location and the other arms are baited. - Release the subject in the start arm. Once the subject enters one of the other two arms, close the door for that arm (trial 1). - After a predetermined inter-trial interval, release the subject and let it freely choose one of the two arms (trial 2). If the subject chooses the alternate arm, this is scored as alternation. This two-trial procedure is repeated several times. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Using The Pulser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-using-the-pulser Chapter: EthoVision XT Pulse Sequences Aim To specify a train of pulses of frequency up to 0.5 kHz. The Pulser Software The Pulser/PulserPlus can send out a very specific modulated pulse sequence. You can program the Pulser by specifying a number of parameters in a command line (string command; see below). This command line is sent out from EthoVision XT to the Pulser. Structure of the Pulse Sequence Pulse train. Two pulses (1 and 2) are organized in a pulse train. This is described by the following parameters: - The duration of pulse 1 (P1D). - The interval between pulse 1 and pulse 2 (P1I). - The duration of pulse 2 (P2D). - The interval between pulse 2 and the end of the train (P2I). - The interval between trains (BI). Number of trains. A pulse train can be repeated a number of times specified by the parameter TNT. The total duration of the signal is given by TNT times the total duration of the other five parameters. Group of pulse trains. A number of trains defined as above can be seen as a group. The duration of the group is defined automatically by the parameters above. Multiple groups of pulse trains are therefore defined by the interval between groups (GI) and the total number of groups (TNG). Structure of the String Command echo MTNT,BI,P1D,P1I,P2D,P2I,TNG,GI,OM,NoT,ToDy,ToDu,ToIt,ToNu@ > [COM port number] Where: - echo — DOS command that sends the string. - M — Command prefix. Do not put commas between this and the next parameter. - TNT — Total number of trains. - BI — Interval between trains (msec). - P1D — Duration of pulse 1 (msec). - P1I — Interval between pulse 1 and 2. - P2D — Duration of pulse 2 (msec). - P2I — Interval between pulse 2 and end of train (ms). - TNG — Total number of groups of pulse trains. - GI — Interval between groups (sec). - OM — Operational mode. For Pulser [0,1,2,3], for PulserPlus [100 to 103], where: - 0 (100) = Do not use the trigger input. - 1 (101) = Use the trigger for single sequence. - 2 (102) = Use the trigger. Perform the sequence and when finished wait for the next trigger. - 3 (103) = Use the trigger. Perform the sequence as long as the trigger is "high". This is the recommended option. - NoT — Number of triggers [1, 2, ...]. - ToDy — Delay of TrigOut from last train finish (not used by EthoVision XT). - ToDu — Duration of TrigOut (not used by EthoVision XT). - ToIt — TrigOut interval (not used by EthoVision XT). - ToNu — Total number of TrigOut (not used by EthoVision XT). - @ — End of command (no comma before it). See also the Pulser/PulserPlus User Manual. Example In an optogenetics protocol we want to stimulate the animal with light bouts of 20 ms separated by 20 ms off. This would result in 25 Hz stimulation. P1D = P2D = P1I = P2I = 20 ms. The resulting string command to send to the Pulser (note: OM = 3 for Pulser, 103 for PulserPlus): echo M1,0,20,20,20,20,1,0,3,1,0,0,0,0@ Notes - Although the total number of trains TNT is set to 1, the pulses are sent out continuously because the operation mode is set to 3. In this case the pulse trains are generated as long as EthoVision XT sends the TTL signal "high". When EthoVision XT sends the TTL signal "low", the sequence stops. - If one wants to stimulate the animal as long as the animal is in a specific zone, in the Trial Control Settings the TTL signal "high" must be associated with a condition based on the variable In Zone. - With operation mode 3, during generation of the pulse sequence the LED is lit on continuously. - If you have the Pulser and the older Pulser software (version 2.1), the command above would be: echo 1,0,20,20,20,20,1,0,3,1@. Configure the COM Port for Each Pulser Aim To configure the COM port in such a way that the Pulser/PulserPlus accepts commands from EthoVision XT. Procedure - Connect the Pulser/PulserPlus to the PC using the USB cable (type-A to type-B connectors). - In the Control Panel, open the Device Manager. - Under Ports (COM & LPT), right-click USB Serial Port and select Properties. - Click the Port Settings tab. - Make sure that the parameters are set correctly, then click OK. - Take note of the port number. - Repeat the procedure for each Pulser/PulserPlus. Notes - The COM port number is retained in the Pulser, so if you disconnect the Pulsers and reconnect them, you do not have to assign the COM ports again. - Tip: To determine which COM port is assigned to a Pulser/PulserPlus device, disconnect the USB cable from the Pulser/PulserPlus, then reconnect it. The item that appears under Ports (COM & LPT) indicates the COM port. - Tip: To change the COM port for a specific Pulser, open the Device Manager from the Control Panel. Under Ports (COM & LPT), right-click the COM port, select Properties, then Port Settings, then Advanced. From the COM Port Number list, select the desired COM port from those available. Program the Prizmatix Pulser/PulserPlus Within EthoVision XT Aim To program the pulse sequence. Prerequisites - The Pulser driver is installed. - The COM port is configured as described in the COM port configuration section. - Important: Make sure that Custom Hardware is selected in the EthoVision XT Device Configuration window, not TTL Tester or others. Procedure 1 - Initialize the COM Port In EthoVision XT, open the experiment and choose Setup > Trial Control Settings > New. Follow all instructions below. - Under Actions, choose External command. - Next to Select program to run, browse to C:\Windows\System32\cmd.exe. - Add the Command line options as follows: /C mode COMn BAUD=57600 PARITY=N DATA=8 STOP=1 DTR=off RTS=off - Important: In place of n, enter the number of the COM port for that Pulser. - Note 1: The command /C closes the window after sending the command line. - Note 2: If you have the Pulser and the older Pulser software (version 2.1), the command above would be: /C mode COMn BAUD=57600 PARITY=N DATA=8 STOP=1 DTR=on. - Click OK and insert the resulting box after the Start Trial box. - Under Conditions, choose Time. - In the Time Condition window, select After a time of 2 secs. - Insert the Time Condition box after the Action box. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Using The Pulser (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-using-the-pulser-continued Chapter: EthoVision XT Using the Pulser (Continued) A Time condition is placed to allow the instructions in the external command to be processed, before the next external command (that is, the one defining the pulse sequence; see below) is received by the Pulser. Because the two external commands act on the same program cmd.exe, if this Time condition is absent the second command may not be executed by the Pulser which is still busy with the first command. Important: If you use multiple Pulsers, there may be more time needed to initialize the ports. If the Pulser does not respond it could be due to the 2 s waiting time not being enough. Set a longer time, like 5 seconds or the like. Procedure 2 - Define the Pulse Sequence The aim of this procedure is to have EthoVision XT send the command that specifies the sequence parameters. - Under Actions choose External command. - Select the Program to run and the Command line options as follows (remember to enter the number of your port instead of [n]): /C echo MTNT,BI,P1D,P1I,P2D,P2I,TNG,GI,OM,NoT,ToDy,ToDu,ToIt,ToNu@ > com[n] For example, for a continuous pulse sequence 20 ms on and 20 ms off, and with COM port 3: /C echo M1,0,20,20,20,20,1,0,103,1,0,0,0,0@ > com3 Note 1: The Operation mode 103 (for PulserPlus, or 3 for Pulser) means that the pulse sequence is generated as long as EthoVision XT sends the TTL command to the Pulser. Note 2: If you have the Pulser and the older Pulser software (version 2.1) the command above would be: /C echo 1,0,20,20,20,20,1,0,3,1@ > com3. - Click OK and insert the resulting box after the Time Condition box created in the previous procedure. When this procedure is carried out, the Pulser "knows" what sequence to send out to the LED Controller when it is triggered. The last piece is to program one or more actions in the Trial Control procedure that activate the Pulser at the right time. See the next section. Procedure 3 - Program Activation of the Pulser In general, activating the Pulser requires four elements: - Trigger condition (wait that the condition is met). - Action that triggers the pulser. - Stop condition (wait that the condition is met). - Action that stops the pulser. In this example, stimulation is set to start one minute after the start of tracking, and last 1 second. - Under Conditions choose Time and set it to 1 minute. - Under Actions choose Custom Hardware. Choose the Pulser device. This device must be defined in experiment settings and arena settings. Under Action to perform, select Output 1 High. - Under Conditions choose Time and set it to 1 second. - Under Actions choose Custom Hardware. Choose the Pulser device as in step 2. However, under Action to perform, select Output 1 Low for deactivating the Pulser. - Place the four boxes one after the other. Tip: Add a condition after the last box, otherwise tracking stops immediately after stimulation stops. If you want these actions to be repeated, insert them in a Subrule. In the settings of this box, under Stop conditions specify Repeat indefinitely (or as long as required). Note: Consider the following sequence: /C echo M1,0,500,500,0,0,1,0,103,1,0,0,0,0 This means that the LED is switched on for 0.5 s, then is switched off for the next 0.5 s. If the Time condition between the trigger actions is set to 1 second, at the end of that time the TTL output sent to the Pulser is still high; this triggers another pulse. As a result, the LED switches on two times (On, Off, On, Off), for a total of 2 seconds. To have just one sequence, set the Time condition to a time slightly less than one second, for example 0.9. If, on the other hand, you want to have a repeated sequence, it is recommended to set 1.1 s. Procedure 3b - Program Activation Based on Zone Visit In this example stimulation is given every time the subject visits a zone named A. The Trial Control procedure is as follows: - Trigger condition: Is the subject in zone A? - Action that triggers the pulser. - Stop condition: Is the subject not in the zone? - Action that stops the pulser. The sequence must be placed in a Subrule, and the Subrule reference is set to Repeat indefinitely, so the Pulser is triggered again at the next zone visit. Set the Action boxes based on the Pulser, not the LED controller. For More Information For more information on Subrules, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. To open this manual, choose Apps > Noldus > EthoVision XT 18 Other Documentation. For more information on the Pulser, see the Prizmatix Pulser/PulserPlus User Manual. Program the Prizmatix Pulser/PulserPlus with the Prizmatix Software It is also possible to define a LED activation sequence with the software that comes with the Pulser/PulserPlus. EthoVision triggers the Pulser with a TTL signal, as shown above. The advantage is that the Prizmatix graphical interface makes the definition simple. However, you cannot change the sequence definition during a trial. A few things to remember: - Keep the Pulser software open during your trials. If you have multiple Pulsers, open one instance of Pulser software for each Pulser. - Make sure that the pulse sequence is defined in the Pulser software. - Check that the Pulser software indicates that a COM port is selected (COM3, COM4, etc.) and shows the message Prizmatix Pulser is connected. Do this for each instance of Pulser software. - On the Pulser software, set the Operation Mode to (3) Execute pulse sequence after trigger HIGH, then stop when LOW. - Before starting the trial, click the Start sequence button. If you work with multiple Pulsers, do so in each instance of the Pulser software. The Pulser software will then wait for the trigger signal from EthoVision XT. For connection schemes and further details, see the chapter The DanioVision Optogenetics Add-on in the DanioVision DVOC-0041 - EthoVision XT 18 - Reference Manual. Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Application Manual - Version 18 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-application-manual-version-18 Chapter: EthoVision XT General Information Setting up the experiment in EthoVision XT - Create the experiment - Experiment settings - Arena settings - Trial control settings - Detection settings - Trial list - Protocols on the web featuring EthoVision XT Acquire the data - Protocol - Acquire the tracks Analyze the data - Data preparation - Visualize the data - Calculate the statistics - Export the results The Open Field Test Introduction - The open field for rodents - The open field for zebrafish Physical Setup The Open Field Experiment in EthoVision XT - Experiment settings - Manual scoring settings - Arena settings - Trial control settings - Detection settings Acquiring Data - Protocol - Score behaviors manually Data Analysis - Analysis profiles - Analysis per zone - Time variation of behavior - Zone crossings - Freezing behavior - Stretch-attend - Rat or mouse behavior recognition - Comparing groups - Visualizing data The Morris Water Maze Test Introduction - The Morris water maze test - The sample experiment - References Physical Setup The Morris Water Maze Test in EthoVision XT - Arena settings - Trial control settings - Detection settings - Trial list Acquiring Data - Protocol Data Analysis - Data preparation - Analysis profiles - Swim patterns - Gallagher's proximity score The Novel Object Recognition Test Introduction - The novel object recognition test - The sample experiment - References Physical Setup The NOR Test in EthoVision XT - Experiment settings - Manual scoring settings - Arena settings - Trial control settings - Detection settings - Trial list Acquiring Data - Protocol - Score behaviors manually Data Analysis - Data preparation - Selecting data - Analysis profiles - Exploratory behavior - Heatmaps The Elevated Plus Maze Test Introduction - The elevated plus maze test - The sample experiment - References Physical Setup The Elevated Plus Maze Experiment in EthoVision XT - Experiment settings - Manual scoring settings - Arena settings - Trial control settings - Detection settings - Trial list Acquiring Data - Protocol - Score behaviors manually Data Analysis - Data preparation - Selecting data - Visualizing data - Analysis profiles The Sociability Cage Test Introduction - The sociability test (three-chamber paradigm) - References The Sociability Test in EthoVision XT - Experiment settings - Manual scoring settings - Arena settings - Detection settings - Trial list Acquiring Data - Protocol - Score behaviors manually Data Analysis - Data preparation - Analysis profiles - Visualizing data The Social Interaction Test Introduction - Measuring social interactions - The sample experiment - References Physical Setup - Lighting conditions - Marked vs. unmarked subjects The Social Interaction Test in EthoVision XT - Create an experiment - Experiment settings - Manual scoring settings - Trial control settings - Detection settings - Trial list Carrying Out Your Trials - Protocol Data Analysis - Data preparation - Analysis profiles - Social interaction in detail - Statistics and charts - Visualizing data Source: EthoVision XT 18 - Application Manual, Noldus Information Technology --- ## EthoVision XT 18 - Dongle Deactivation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-dongle-deactivation Chapter: EthoVision XT EthoVision XT 18: Switching from Dongle Key to Software-Based Licensing Deactivating Your Dongles Thanks for letting us know which dongles you want to convert to a software-based license. The next step is to deactivate the dongle key(s) and confirm the deactivation by sending the requested screenshots. Please Read This First Deactivation of the license key dongle(s) cannot be reversed! Once deactivated, dongles have a 5-day grace period before expiring and becoming inactive. Once you upgrade to a software-based license, you will NOT be able to work in experiments in any earlier version of EthoVision XT. If you are upgrading from an earlier version, please open that version and make backups of your experiments via File > Make Backup. Backups (*.EVZ files) can be opened in EthoVision XT 18 via File > Restore Backup. Complete the entire process outlined in this document (emailing information back and forth with Noldus) within 5 days to avoid losing access to your EthoVision license(s). If you run into any issues, please submit a support ticket on the MyNoldus client portal. Step 1: Install EthoVision XT 18 If you are upgrading from an earlier version of EthoVision, download and install EthoVision XT 18 first. Download the EthoVision XT 18 installation files from MyNoldus: - Log in or create a new account on MyNoldus. - Go to Downloads > EthoVision XT > Versions > Current Version > Download. - In File Explorer, locate the downloaded ZIP file, right-click it, and select Extract All > Extract. - In the unzipped folder, locate and double-click EthoVision XT - Setup - 18.XXXX.exe to install. Step 2: Deactivate Dongle(s) Repeat the following procedure for each dongle: - Insert the dongle into a USB port. - Launch EthoVision XT 18. - If you are upgrading to version 18 for the first time, the Enter Upgrade Key box will open automatically. If it does not, go to Help > Upgrade... - Enter the provided upgrade keys for the inserted dongle. - Enter Key 1 and Key 2 (if needed) and click OK. Step 3: Send Screenshot(s) of Dongle Expiration - Insert the dongle into a USB port. - Launch EthoVision XT 18. - Go to Help > About EthoVision XT > License Info. - Take a screenshot of the License Information box using Snipping Tool, Snip & Sketch, or Fn + PrintScreen then Ctrl + V. - Email the screenshot(s) to: support@noldus.com. You will receive the activation key(s) for your software-based EthoVision license within 5 business days. If you run into any issues, please submit a support ticket on the MyNoldus client portal. Source: EthoVision XT 18 - Dongle Deactivation --- ## EthoVision XT 18 - GigE Install and Setup - 1. Procedure (General) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-1-procedure-general Chapter: EthoVision XT Procedure (General) - Make sure EthoVision XT (and Media Recorder, when present on the computer) are not running. - Start the Basler Pylon Viewer software that comes with the camera. Note: The Basler Pylon Viewer software is installed automatically when you install the camera drivers. - Choose Tools > Options and check that the User level is set to Expert or Guru. - In the Devices panel, double-click the item Basler under GigE or USB depending on the camera you have. - To preview the camera image, click the Continuous Shot button on the toolbar. Important: Do not use the Record button if you want to record video. This creates very large files. Always use EthoVision XT. - Under Features, open the Basler GigE camera chosen in Step 4 and choose the settings you would like to change. Follow the instructions below that apply. Note: To be able to adjust the settings, click the Stop button first. - Save the settings. See Item 7 below. Camera Gain This applies to both color and black/white Basler cameras. Increasing the gain will brighten the image. Important: Increasing gain also increases image noise. Do this only if no other option is left to improve the image brightness. For example, make sure that the lens aperture is maximal, and increase lighting. - In the Features panel, click Analog Control. - From the Gain Auto list, select Off. - Next to Gain (Raw), select the value you require. A higher Gain results in a brighter image, but also more noise and a grainy image. - This value is typically low, often no higher than 2. Use Exposure to brighten up the image more if needed. - Save the settings. See Item 7 below. Pixel Format - Under Image Format Controls, select Pixel Format. Select the one you require via the drop-down list. - Select Mono8 for black and white (monochrome) cameras. - Select Bayer RG 8 for color cameras. - Save the settings. See Item 7 below. How To Tell Which Camera You Have Look at the model number on your camera. It will look something like this: acA1300-60xx - Where xx = gm, this camera is black and white (monochrome). - Where xx = gmNIR, this is a black and white (monochrome) camera with Near Infrared. - Where xx = gc, this is a color camera. - Note that all DanioVision units come with a black and white (monochrome) camera. Center Camera With this procedure you make sure the camera view is centered. Important: If you center the camera view in EthoVision XT, the settings are not stored in the camera drivers. In Pylon Viewer you make sure that the settings are stored in the drivers, also for future experiments. - In the Features panel, open the Basler camera item and then the AOI Controls item. - Select both options Center X and Center Y. - Save the settings. See Item 7 below. Note: If you bought your GigE camera elsewhere or from Noldus but did not buy a PC at the same time, please set: - Width to 1280 - Height to 960 If you cannot edit Width & Height (grayed out), stop the live feed by clicking the Stop button. White Balance If you have a color camera, you also need to adjust its white balance. - Click Color Improvements Control. - Point the camera at a piece of white paper so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - Save the settings. See Item 7 below. Camera Exposure Time The exposure time (or shutter time) is the time the camera shutter is kept open to let light in. The exposure time limits the maximum achievable frame rate. If the sum of the exposure time and the time needed for reading the chip (readout time) is greater than the time between consecutive video frames, the next frame may be dropped, resulting in a lower frame rate and missed samples during tracking. You will apply the following settings via Acquisition Control: - Exposure Mode - Exposure Auto - Acquisition Frame Rate (Abs) [Hz] - Exposure Time (Abs) [us] Procedure To adjust camera exposure until it matches the frame rate, follow these steps: - In the Features panel, open the Basler camera item and then double-click Acquisition Controls. - Set the Exposure Mode to Timed. - Set Exposure Auto to Off. - Set Acquisition Frame Rate (Abs) [Hz] to 25 or 30. - Set Exposure Time (Abs) [us] by entering the exposure time you require, in microseconds. Press Tab or click another field to confirm. - This value will vary between 2000 and 15000 depending on your lighting needs and your Gain setting. - For Zebrafish larvae, enter 4000 or 2000, depending on the video resolution chosen. - In all other cases, you may choose a higher value. Faster animals require shorter exposure times. - To check that the exposure time is compatible with the frame rate you have chosen, click the Continuous Shot button on the toolbar. DanioVision GigE Camera Exposure Guidelines - If resolution in EthoVision is 1280 x 960, use an exposure time of 4000. - If resolution in EthoVision is 640 x 480, use an exposure time of 2000. - Use the highest resolution that allows all wells to be seen onscreen in EthoVision. General Exposure Recommendations - The ideal range of exposure will likely be anywhere from 2000 to 10000. - If lighting in the room is low, you will likely need a higher exposure (try 8000 up to as high as 15000). - It is unlikely you will need anything above 20000, as motion blur in rodents has been observed at this level. - When tracking in IR with an NIR GigE camera, you may need an exposure setting around 30000 in order to brighten the image enough for tracking in EthoVision. - A higher exposure setting will result in a brighter image, while a lower exposure setting will result in a darker image. However, too-high exposure will result in dropped frames, and too-low exposure may result in an image that flickers or changes rapidly between light and dark. - The brightness of the image will also be affected by the aperture setting on the lens and by the camera gain. When adjusting the camera lens, the aperture adjustment will be labeled Open-Close or O-C. Turning it towards Open will brighten the image, while Close will darken the image. At the bottom of the live video window, locate the frame rate resulting from the new exposure time. This should match the value set for Acquisition Frame Rate (Abs) [Hz]. Noldus recommends 25 or 30. If the resulting frame rate is lower than Acquisition Frame Rate (Abs) [Hz], then either lower the exposure time (this will make the video image darker; open the lens diaphragm to compensate), or lower the video resolution. Repeat until you see the expected frame rate. - Save the settings. See Item 7 below. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - 16 Cameras: URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-16-cameras Chapter: EthoVision XT 16 Cameras Important: When using a 16-camera configuration, we recommend using Contour-based tracking, not Deep learning. This is because Deep learning is so resource-demanding that it is unlikely to work with 16 arenas on a typical PC. Hardware Setup and Settings - PC: Dell Precision 3680, CPU i7-14700K 3.4 GHz, RAM memory 32GB, GPU NVIDIA T1000 8 GB; Windows 11 Pro 23H2. - Cameras: 16 Basler GigE cameras acA1300-60gm. - PCIe Ethernet Interface Board: FS X550-AT2, 10GBase-T Dual-Port, PCIe 3.0 x4. - Network Switch: FS S3100-16TMS-P, 16-Port Gigabit Ethernet L2+ PoE+, 8x PoE+ Ports@125W, 2x 5Gb RJ45, with 2x 10Gb SFP+ Uplinks. - For this switch you need an adapter (SFP+ 10GBASE-T Copper 30m RJ-45 Transceiver module) for the network cable that goes to the PC. - We recommend using CAT6+ network cables. - Video Resolution: Single camera view 640 x 480, merged view in EthoVision XT 2560 x 1920. - Image Binning: 2. - Video Frame Rate: 30 fps. Trial duration: 72 hours. - Video Source: Live tracking; Number of subjects per arena: 1; Tracked features: Center-point, nose-point and tail-base detection; Body Point Detection Technique: Contour-based. Detection method: Dynamic Subtraction or Differencing. Acquisition mode: Track + Save video. Connection Scheme Follow this scheme also for PhenoTyper 2. Note that in the S3100-16TMS-P network switch, the RJ45 ports marked in yellow are powered, so eight cameras do not need PoE injectors. Connect the remaining eight cameras through PoE injectors. Assign the IP Addresses Connect the cameras to the switch using the ports as shown in the figure. For a good overview of the IP addresses, we recommend using Pylon IP Configurator. - Start Pylon IP Configurator. - For the port of the Ethernet board of the PC connected to the switch, specify the address 192.168.x.51. To do so, locate the Ethernet row in IP Configurator — the row with the board symbol connected to the cameras. Note that the name of the Ethernet row may vary between PCs. - Right-click and select Properties, then double-click Internet Protocol Version 4, select Use the following IP address, and enter the IP address in the IP Address field. - For cameras 1 to 16, specify addresses in the 192.168.x.x range. Note that the third number must be the same as that for the Ethernet port connected to the network switch. To assign IP addresses to a camera, select the camera row, then in the panel at the bottom of the screen choose Static IP and enter the IP address. - For all Ethernet ports and cameras, leave 255.255.255.0 as the Subnet Mask. For more schemes of multiple camera configurations, see also the PhenoTyper - EthoVision XT 18 - Reference Manual. Using Network Switches - The network switches must be of type PoE (Power over Ethernet), meaning they must provide power to the cameras. The maximum power provided by a switch, measured in Watts (W), must be greater than the total requirements of the cameras (one Basler camera requires about 2.5 W). - The network switches must be able to handle large packets (known as jumbo packets or jumbo frames). With jumbo frame-capable devices, the maximum packet size can be up to 16 KB. For maximum network efficiency, your camera should be configured to use the largest packet size that your network adapters and switches can handle. - Refer to the user guide of the network switch for how to set it up. G – Assign Camera IP → Pylon IP Configurator Note: If you bought your camera from Noldus, the IP has already been assigned to the camera. - Connect the GigE camera to the PC. - In Windows, search for and start Pylon IP Configurator. - Select the camera name that appears under the Ethernet port set in the previous procedure. This is the camera physically connected to that port. Note that the camera status is Not reachable. This is normal since the camera cannot communicate yet with the Ethernet port. - Under Static IP, fill in the details in the IP Address and Subnet Mask fields. - Click Save and then close Pylon IP Configurator, or repeat the procedure for the next camera. - Next: Configure the digital camera. US and Canada Customers: Use 192.168.200.1 for the camera IP address. The second camera on the same card/port should be 192.168.200.2, etc. Multiple Cameras and Cards/Ports: The first three numbers must match the address set for the network card the camera is connected to. For example, a camera connected to a card set to 192.168.201.101 can be designated as 192.168.201.1. Note: Subnet mask should be 255.255.255.0 for all cameras. H – B&W Camera Settings → Pylon Viewer If you will be using multiple GigE cameras in EthoVision XT (at the same time, in the same experiment), you need to configure each camera and they must have the same settings. Remember to save your settings for each camera. You will know when your camera settings are optimal when there are no Missing Samples or Interpolated Samples in EthoVision XT. Please see Section L for how to check and test that. Important: All of the settings below can also be done in EthoVision XT, but they then only apply to that one experiment, as the settings are not stored in the camera drivers. We recommend setting these settings in Pylon Viewer rather than in EthoVision XT to ensure that the settings are stored in the driver for future experiments. See Section K for more information about changing these settings in EthoVision XT. Aim To adjust settings in a GigE camera, such as the video frame rate, video frame resolution, and exposure time. Important: The settings described below are stored in the digital camera, not in EthoVision XT. When working with multiple cameras, repeat the procedure for each camera. Important: Do not use the Pylon Viewer software to record video. Always use EthoVision XT or Media Recorder. To adjust the camera settings, always start with the general procedure. The most common adjustments include: - Adjust the Camera Gain: Increasing the gain will brighten the image. - Pixel Format: Change this setting if you have a color camera that is giving only a black and white image. - Center the Camera: Change this setting if the image appears to be off to one side of the camera, not centered in front of the camera. - Adjust White Balance: Use this setting to correct an image with a color cast (the entire image is tinted a certain color). It can especially help when using color marking in EthoVision. - Adjust the Camera Exposure Time: Increasing exposure will brighten the image, but too high exposure results in a high proportion of missed samples, gaps in the track, and potentially trials ending prematurely. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - 7. Save Camera Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-7-save-camera-settings Chapter: EthoVision XT Save Camera Settings - Click the Stop button. - In the Features panel, open the Configuration Sets item. Note: If you have multiple GigE cameras, make sure and save the settings for EACH camera. - From the Configuration Set Selector list, select User Set 1. - Next to User Set Save, click Execute. The camera settings set in the previous steps are now saved under User Set 1. - From the Default Startup Set list, select User Set 1. This means that the camera always starts with the settings contained in User Set 1. - Close Pylon Viewer. These settings will be used each time you start up EthoVision XT. Tip: You can also save different settings for the same camera in User Set 2 and User Set 3. Under Default Startup Set (User Set Default), select which you want EthoVision to use. Color Camera Settings – Pylon Viewer Aim To make sure that the tracking of color markers in EthoVision XT is optimized. This topic applies to the Basler color cameras acA1300-60gc and acA1920-40gc. Note that the Basler acA1300-60gc is no longer officially supported and therefore not tested by Noldus. Prerequisites You have installed the camera, its driver software and EthoVision XT. The procedure below refers to the options available in the camera software. Most of the options are also available in EthoVision XT. - Close EthoVision XT and open pylon Viewer. Note: The Basler pylon Viewer software is installed automatically when you install the camera drivers. - From the Window menu select Features - All. - In the Devices panel, double-click the item Basler under GigE. - Open the item Image Format Control. Next to Pixel Format select: - YUV 422 Packed for the camera acA1300-60gc. Note that this camera has not been tested with EthoVision XT 18. - Bayer RG 8 for the camera acA1920-40gc. - Click Color Improvements Control. - Click the Continuous Shot button on the toolbar to view the live image. - Point the camera at a piece of white paper so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - To save the settings, see Item 7 in Section H above. - Close pylon Viewer and open EthoVision XT. - Open your experiment and in the Experiment Settings select Live tracking and the color camera. - Click the camera button and then in the window that appears click the Format tab. Choose the video resolution and frame rate. - Next to Color Space select: - For the camera acA1300-60gc: UYVY or YUV. - For the camera acA1920-40gc: BYRG. If the image stays black and white, select UYVY or YUV, then select BYRG again. - Select the resolution and frame rate. - Check the Current Frame Rate. If this is significantly lower than the rate you set, choose a lower resolution. Settings for Low Light Conditions When tracking animals in low light, you can adjust the camera settings so that colors are more apparent. The settings below apply to the camera acA1920-40gc. In pylon Viewer, do the following: - Under Analog Controls, set Gain to for example 240 or higher if necessary. - Next to Gamma Selector, choose User. - Next to Gamma, choose 1.0. - Increase the Digital Shift, for example to a higher value if necessary. - Under Acquisition Controls, set Exposure Time to for example a higher µs value. A higher value is not recommended. For adjusting a specific color (usually not necessary if the white balance has been done correctly): - Next to Color Adjust Enable, select the option. - Next to Color Adjust Saturation, adjust color saturation (per color). Color to Monochrome If you have a color digital camera, you can temporarily change it to monochrome. - In Pylon Viewer, change the Pixel Format to Mono8. - In EthoVision XT, set the Color Space to Y800. Note: This does not make your color camera infrared-sensitive. For that, you must either remove the infrared block filter (see below) from your color camera or use a monochrome GigE camera. Tip: Basler cameras have model numbers like this: acA1300-60xx, where: - xx = gm means monochrome. - xx = gmNIR means Near Infrared, that is, monochrome with extra sensitivity to infrared light. - xx = gc means color. Color to Infrared-Sensitive Most color cameras are not infrared-sensitive. To make them more infrared (IR)-sensitive: - Set them to monochrome (see above). - Remove the infrared-block filter, if present. For how to do so, see below. Infrared-Cut Filter Some color cameras may have a built-in infrared cut filter which prevents them from seeing some infrared light. If you bought a Color GigE camera from Noldus prior to July 2018, you can remove this filter to make your color camera IR sensitive. Note: Color GigE cameras of model acA1300-30gc purchased after July 2018 from Noldus had the IR cut filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). If you have such a camera you can skip this procedure. - Remove the lens from the camera. - Check that the filter is present: you should see two circular holes at the sides of the filter. - Use a small Allen key or a similar object to lift the filter. - Put the lens back on the camera. Experiment Settings – EthoVision There are 3 camera settings in EthoVision XT (via Experiment Settings): Resolution, Frame Rate, and Color Space. These settings override the settings set in Pylon Viewer. Make sure that you also apply these settings in EthoVision XT. Resolution and Frame Rate - If you opt for a high resolution (for example 1280x960), the frame rate must be 25 or 30 fps or lower. - We recommend 25 fps unless you have fluorescent or LED lighting in the room and see flickering or the image changes between light and dark, in which case use 30 fps. - You can only use a high frame rate (for example 60 fps) with a lower resolution (for example 640x480). Color Space Setting - Default setting is Y800. This is recommended for black and white cameras (monochrome). - For color cameras: if the image is black and white instead of color and a Moiré pattern appears in the image, try using another color space. Normally, the default color space gives good image quality. Otherwise, use YUY2. Using Multiple GigE Cameras If you will be using multiple GigE cameras in EthoVision XT at the same time, in the same experiment, you only need to set the above settings for the first camera. The settings are then applied to the other cameras automatically by EthoVision XT as the system mixes the images in a Picture by Picture configuration. In the Merged Camera View row, select whether the Picture by Picture mixed image should have the same resolution as the image from the individual camera, or whether the resolution should be the sum of each camera image. The maximum resolution in this situation is 1920x1200; however, the camera make and model determines the maximum resolution. For GigE, the recommended maximum resolution is 1280x1024. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Deep Learning Requirements URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-deep-learning-requirements Chapter: EthoVision XT Deep Learning Requirements Graphics Card (GPU) Neural networks make calculations over huge data matrices, and therefore require substantial computation power. In order for the Deep learning tracking technique to work in EthoVision XT, you need a Graphics Processing Unit (GPU, or graphics card) that is able to sustain those computations. Furthermore, Deep learning makes use of TensorRT software development kit (version 8.6.1.6) which is built on the cuDNN deep neural network library, which in its turn relies on the CUDA computing platform. For this reason, the GPU driver must support CUDA runtime version 12.2. Supported GPUs - Quadro P2200 - T1000 - GeForce RTX 4060 - th Gen boards are NOT YET supported Video Source Choose: - When tracking one subject per arena: Live tracking limited to up to four arenas, or From video file. - When tracking two subjects per arena: From video file. Tracking two subjects live using Deep learning may lead to a high number of missing samples, depending on the power of GPU. Always test your setup first. If you note a significant number of missing samples (e.g. > 5%), do not track live. Instead, record video first, then acquire the trial later using Deep learning. Sample Rate Accuracy of individual discrimination may go down when reducing the sample rate, for example from 25 to 12.5 samples/s. We strongly recommend that you track at 25 or 30 fps (unless using DavioVision, then use 60 fps). Choose the sample rate in the Detection Settings. Subject Species, Color and Size - The neural network has been trained with images of rats and mice of uniform color. - For hooded rats, like Lister and Long-Evans rats: - When tracking one subject per arena: Select Hooded rats in the Detection settings. This loads a neural network model specific for those animals. - When tracking two subjects per arena: The neural network for two interacting subjects has not been trained for the fur patterns of hooded rats. If you want to use hooded rats, test pairs of animals before the actual experiments, to check that the software produces acceptable results. - The apparent length of the subjects should be at least 10% of the size of arena. We recommend that the apparent length of the subject's body is at least 120 pixels for rats and 50 pixels for mice (nose to tail-base). Number of Subjects and Arenas You can select Deep learning as body point detection technique in experiments with: - One subject per arena, in a maximum of four arenas. - Two subjects per arena, in a maximum of four arenas. IMPORTANT: Always draw an arena in the Arena Settings for optimal results. Video Image - When working with one arena at a time, choose a resolution of 640 x 480 or higher. - When working with two to four arenas, choose a resolution of 1280x960 or 1280x1024, or similar. - In any case, use video of resolution equal to or higher than PAL/NTSC (PAL: 704 x 576; NTSC/EIA: 640 x 480). A higher resolution is not necessarily better, also considering that it makes tracking slower when tracking offline, or can cause missing samples when tracking live. First try a low resolution, and switch to a higher resolution if the results are not good. - For live tracking, not all video resolutions and frame rates are compatible with Deep learning. See Test results and then click on the camera type for configurations tested with Live tracking combined with Deep learning: GigE cameras, USB 3.0 cameras, and Analog cameras. - EthoVision XT converts video to grayscale before feeding it to the neural network. Therefore, both monochrome and color video work fine. Video Length - One subject per arena: No restrictions. Maximal trial duration tested 72 hours. - Two subjects per arena: We recommend performing trials of at least five minutes. Maximal trial duration tested 1 hour. During the trials, the two subjects should be separated for at least three minutes. If the subjects are in contact for most of the trial duration, individual recognition may fail. Also consider that, with two-subject tracking: - EthoVision XT saves additional files during acquisition, which increase the storage space needed on your PC. A 1-hour video produces 10 MB of additional files. - With long trials, the marker could change or droppings would likely cumulate in the arena. Both factors could potentially interfere with marker recognition. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Default/More URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-defaultmore Chapter: EthoVision XT Default/More - Click the Default button to change the camera settings back to default. The settings on the other tabs will not change. - Click the More button to open the camera software with additional settings. To operate this software, click first the Cancel button in the EthoVision XT Video Settings window. Gamma Human visual perception is typically non-linear. Adding 1 to a dark or bright color would not result in the same increase in the perceived brightness. Gamma adjusts the brightness of pixel values to account for this non-linearity. Choose sRGB to take a color as is. Choose user to fine-tune the color representation and get a color perception that is optimal for you. When the gamma correction value is set to 1, the output pixel brightness is not corrected. A value between 0 and 1 results in increased overall brightness; a value greater than 1 results in decreased overall brightness. Color Adjustment With Color Adjustment you can fine tune the color perception by adjusting the settings of colors separately. Select Enable, then choose a color from the list and adjust the saturation Value. Check the result in the image preview. Address Tab This contains the settings for IP cameras. IP Address Enter the IP address of the IP camera. For details about how to define an IP address for the camera, see Assigning IP Address to Camera. Port Enter the port number specified for the IP camera (default for Noldus cameras: 554). User Name Enter the user name specified for the IP camera. For details on how to define a user, see Assigning IP Address to Camera, or see the camera's manual. Password Enter the password specified for the IP camera. For details on how to set a password, see the camera's manual. Notes: - What settings are available depend on the camera type (analog vs. digital). This topic describes the most relevant ones. For digital GigE or USB 3.0 cameras, additional settings are available in the camera software Pylon Viewer. See Configuring the GigE Camera in Pylon. - When you adjust the camera settings in EthoVision XT, the settings are sent back to the camera once you re-open the experiment. - Settings are saved at the experiment level. So, you can create two EthoVision XT experiments with different camera frame rates, exposure levels, etc. Test and Check Camera Setup Aim If a digital camera is not set up properly, you will get dropped video frames which results in either Missed samples or Interpolated samples in EthoVision XT. Prerequisites - You have followed the steps to connect and configure the camera. - You have created an experiment in EthoVision XT. - You have made the Arena Settings. This step is necessary to open the Detection Settings. Procedure - In the EthoVision XT experiment, select Setup > Detection Settings > New. - Make sure that the video window shows the live camera image. - In the Detection Settings pane, under Smoothing, set Dropped Frame Correction to Off. - Locate the Detection Performance pane. - Check the value of Missed Samples. If the percentage of missed samples is low (less than 1%), then the camera is set up properly. If the percentage is higher, there may be an issue with the camera. - You have a few options: - For GigE cameras: check that the exposure time is not too high for the set frame rate. - Reduce the video resolution, the frame rate, or both. - The Ethernet board may not be set up properly. - See the Troubleshooting section. Notes: - The value of Subject Not Found is not related to the camera setup. It shows how often the software is not able to find a subject in the arena. If the arena is empty, the value grows to 100%. - The Dropped Frame Correction set to Off enables you to see if EthoVision XT can cope with the actual camera frame rate without missing samples. - If the camera is set up properly and still the number of Missed Samples is high (e.g. > 5%), you can set Dropped Frame Correction to On. However, the software interpolates samples to compensate for the missing video frames. Here is how to check for Missed Samples and/or Interpolated Samples in EthoVision XT: - Missed Samples (in Detection Settings, default) - Interpolated Samples (in Detection Settings, when Dropped Frames Correction is ON) - Missed Samples (in Acquisition, default) - Interpolated Samples (in Acquisition, when Dropped Frames Correction is ON in Detection Settings) The Missing Samples and/or Interpolated Samples percentage should be at or near 0% (anything less than 1% is acceptable). Anything higher indicates that your exposure settings in Pylon are not optimal. You can also see the Missing Samples or Interpolated Samples after tracking via the Trial List. Go to the Trial List, then select Show/Hide, then select Variables and choose either Missed Samples or Interpolated Samples. Both should be less than 1% for proper camera setup. Pylon Troubleshooting - If Pylon IP Configurator is not detecting the camera: - If your camera connects to an Axis Power injector, confirm it is connected correctly. See the wiring diagram in Section E. - Make sure that the Axis Power Injector or POE switch is powered. - Reboot the PC if you did not do so after installing the camera's driver. - In Pylon IP Configurator, the camera is visible but the Status column says Not Reachable: - The network card IP and camera IP do not match. For example, the network card should be 192.168.200.101 and the camera should be 192.168.200.1 (the first three numbers must be the same but the fourth number must be different). Also verify the subnet mask is 255.255.255.0 (not 255.255.0.0). - No camera image in Pylon Viewer despite all previous steps being verified: - Disable firewall and/or anti-virus software. - The network card could be defective. - If you cannot save your camera's configuration (as User Set 1) in Pylon Viewer: - Click the Stop button first. - Confirm you selected either Expert or Guru via the Tools menu. Select Options and check that the User Level is set to Expert or Guru. - Camera image is static/pixelated with red, blue, and green pixels: - The color space setting in Pylon Viewer is incorrect for the camera type. This setting can be found in Pylon Viewer under Image Format Controls, then Pixel Format: - Black and white camera (monochrome): select Mono8 - Color camera: select Bayer RG 8 (previously YUV 422 (UYVY) Packed) Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Dual Option Mount: URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-dual-option-mount Chapter: EthoVision XT Dual Option Mount The item on the left connects to the camera; the screw on the top in the image is a standard size tripod fitting and will fit the hole on the camera. - The camera will also work with other mounts that accommodate this standard fitting. The two items on the right are alternate types of mountings, which would screw into the bottom of the camera fitting. - The one with three tabs is a general purpose mount which would be screwed into a wall or ceiling. This would be a permanent mount. - The other one is designed to attach to suspended ceilings. There are two parts which move like scissors. Move them to open up the mount and it will fit over the framework of the suspended ceiling, then close them to hold. This is a temporary mount, it is sturdy enough but you can always open the mount to remove it from the ceiling and place it elsewhere. If you have a suspended ceiling it's probably the best solution. See below for how to use the Dual Option Mount with the Autopole and Superclamp. Autopole - Black mounting rod for camera. - Range is 2.1–3.7m, or up to 5.7m with the extension (extension sold separately). - Typically installed horizontally between two walls but can be installed vertically if you have a Dual Option Mount (see above and below). - Must install horizontally if system came with a Standard Camera Mount. - Often ships separately via UPS from the rest of your Noldus order. Superclamp - Camera is connected to the Superclamp with brass stud connector. - Superclamp is then clamped onto the Autopole. How to Attach the Camera to the Superclamp - Connect the camera to the Superclamp through the brass stud connector or the camera adapter. - The Autopole gets clamped between the jaws of the Superclamp. Turn the handle to tighten the Superclamp to the Autopole. Horizontal installation is mainly for top view tracking. For this you need the Autopole and the Superclamp. Vertical installation is for top view tracking and side view tracking. For this you need the Autopole, the Superclamp and a camera adapter (see Dual Option Mount above). For more flexibility you can use a variable friction arm attached between the Superclamp and the camera adapter. Suspended Ceilings If you need to attach the camera to suspended ceilings, you can get a special mount (i.e. Dual Option Mount) that has two parts which move like scissors. Move them to open up the mount and it will fit over the framework of the suspended ceiling, then close them to hold. Attach the camera adapter and then the camera. This is a temporary mount, it is sturdy enough but you can always open the mount to remove it from the ceiling and place it elsewhere. If you have a suspended ceiling it's probably the best solution. Things to Check - Position the camera perpendicular to the plane in which the animal moves. If this is not the case, the shape of the arena and subject inside will appear distorted on the screen and calculated distances, velocities and spatial statistics will be incorrect. - Anchor the entire setup. Secure the position of the arena, camera and illumination relative to each other, and fasten the camera zoom, focus control and aperture settings. - Adjust the zoom setting (or select the appropriate lens) and focus the lens until the entire experimental arena is visible on the screen and is displayed in focus. - When using multiple cameras, pay attention to the zoom settings. These should be in such a way that the apparent size of the arenas is the same since you calibrate the distance for all the cameras (Shared calibration). If that is not possible, make one calibration for each arena (Unshared calibration). - Turn off all automatic camera settings: focus, gain, exposure (auto-iris), anti-shake. - Adjust the camera aperture until the image shows maximal contrast. Depending on how bright your IR setup is, you might need to open the aperture on the lens all the way (do this first) and/or adjust the camera's Gain (Raw) and/or adjust the Exposure time in Pylon Viewer. Installing Ethernet Board To install an Ethernet (network) board that receives video from one or more GigE cameras. NOTE: If you ordered a computer from Noldus Information Technology when you purchased EthoVision XT and Basler GigE cameras, the Ethernet interface board(s) has already been installed and tested. If you bought your computer somewhere else, you will have to install the board yourself. Follow the instructions below. This topic applies to Ethernet interface boards that have been tested with EthoVision XT. - Two-port board: FS X550AT2-2TP (10GB NIC). This was combined with an optical switch FS 3100-16TMS to connect 16 GigE cameras. - Four-port board: the Adlink PCIe-GIE74 (A), or the Basler GigE Interface Card (B) to connect up to four cameras. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Ethovision Xt: URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-ethovision-xt Chapter: EthoVision XT EthoVision XT Troubleshooting - In EthoVision XT via Experiment Settings, I cannot select Basler GenICam [Basler acA1300-60] (camera and network card are setup 100% correctly per this document). - Camera drivers installed per Section D? And IP addresses assigned per Sections C and Section G? - Disable firewall and/or anti-virus software. - Network card defective. - In EthoVision XT via Experiment Settings, I can select my cameras but error message Device Unplugged appears. - Check cable connection between cameras and PC. - Check that camera is receiving power. - Merged Video Resolution too high? - 8 cameras → 2560 x 960 - 16 cameras → 2560 x 1920 - Network card issues. - In EthoVision XT via Experiment Settings, I cannot see an image from the camera when I click on the Camera icon. - Make sure that the camera(s) is connected to PC and powered PRIOR to opening EthoVision. - Make sure that the aperture of the lens is fully open (lens ring all the way to Open or O). - Make sure that Pylon is closed. - Make sure the correct camera is selected in Experiment Settings, that camera being: Basler GenICam [Basler acA1300-60]. - PC is running Windows 10 or 11 but you have Windows 7 driver installed (4.2.1). Download and install driver 7.5.0 per Section D (will need to reset-up camera again, follow Section H again in its entirety). - Make sure network IP/Subnet and camera IP/Subnet match (can check/change camera subnet via Pylon). - In EthoVision XT via Experiment Settings, when I set the Resolution to something in the range of 1280x960, the highest Frame Rate I can select is ~7.5 frames per second. Why can't I select 30 fps or 25 fps? - Check that your Exposure setting isn't too high. - If Exposure setting is ok, confirm that the Power Injector is in fact a 1GB Power Injector. - If Exposure setting is ok, confirm that the Network card is in fact a 1GB network card. - If network card is 1GB, check that it is set to Auto-negotiate. If it is, then the network card either needs a driver update or is defective. - Cheap, incorrect, or defective Ethernet cables can also reduce the frame rate. - PC insufficient, for example only has an onboard video card. Send Support a PC report, see Section P. Also see Section O. - In EthoVision XT via the Experiment Settings when I click on the Camera icon, the Video Settings box says "No frames available". - Video Card (GPU) driver is missing or very old. Install/update GPU. - If you are using Windows 10, make sure you are using Pylon 6.2.0 or higher. The driver linked in this document is version 7.5.0 for use with EthoVision XT 18. If you installed from an older CD, you could have installed an older Pylon driver (4.2.1) which doesn't support Windows 10. - Settings in Pylon Viewer changed? Specifically, support has seen this with the Trigger mode setting (in Pylon Viewer under Acquisition Controls). It should be set to Off. - Other causes are possible, such as installing Windows 10 on an older PC which isn't compatible with Windows 10. - If none of these examples fit your situation, contact support@noldus.com for further assistance. Please also send a PC report with your update. See Section P. - In EthoVision via the Experiment Settings when I click on the Camera icon, the Video Settings box says "No video frames". - Confirm that the PC monitor is plugged into the stand-alone video card (GPU) and NOT the motherboard. - Video Card (GPU) driver is missing or very old. Install/update GPU. - If you are using Windows 10, make sure you are using Pylon 6.2.0 or higher. The driver linked in this document is version 7.5.0 for use with EthoVision XT 18. If you installed from an older CD, you could have installed an older Pylon driver (4.2.1) which doesn't support Windows 10. - Disable firewall and/or virus scanner to see if they are interfering. - The camera image in EthoVision is off-center, rather than showing the area directly in front of the camera. This occurs if you have selected a lower resolution in EthoVision's Experiment Settings, and the Center X and Center Y options are not checked in the camera settings. Increasing the resolution to the maximum value will give you the full field of view of the camera (and it will be centered). If you prefer a lower resolution, refer to the relevant documentation section. - The camera image in EthoVision XT is too narrow to display the entire arena. - The field of view will be reduced if you have selected a lower resolution in EthoVision's Experiment Settings. Rather than scaling the entire image down to the lower resolution, this camera will display a limited "area of interest" in order to maintain full image quality. For the widest possible view, increase the resolution to the maximum value (typically 1280x1024). - If you have a varifocal lens (most systems do), you can also adjust the zoom setting on the lens. Note that adjusting the zoom will also change the focus, so you will need to adjust the focus as well in order to see the actual effect. You may also need to loosen the lock screw on the side of the lens before the zoom setting can be adjusted. - Image is ok in Experiment Settings, but a white background image appears in Arena Settings. - The Resolution set in Experiment Settings is either too high or an odd resolution is selected (such as 640x426). Reduce the resolution and/or select a standard resolution (such as 640x480). - Similar results are possible if no drivers have been installed for the computer's graphics adapter. - In EthoVision XT: I can select the first camera fine but when I select my second GigE camera in Experiment Settings, EthoVision crashes. - Select a standard resolution like 640x480. Avoid resolutions like 640x426. - Maximum resolution supported is 1900x1200 (Deep Learning: 1280x960 or 1280x1024). - 4K is not supported, live or from pre-recorded video. - Image in EthoVision XT flickers or stutters. - The underlying issue is that fluorescent and LED lighting in the US cycles at 60 Hz, which does not align with a frame rate of 25. Use a frame rate of 30. Sometimes this is enough to resolve the issue. - The Exposure setting in Pylon Viewer is incorrect (Exposure Time (Abs) [us] is likely too low). Try a value in the 4000–8000 range. If lighting is low in the room, use a higher exposure value. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Ethovision Xt: (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-ethovision-xt-continued Chapter: EthoVision XT EthoVision XT Troubleshooting (Continued) 17. Image Lightens and Darkens (Subtle Change, No Flicker) - Check that Exposure Auto is set to Off (in Pylon Viewer under Acquisition Controls). - Check that Gain Auto is set to Off (in Pylon Viewer under Analog Controls). - Check that Balance White Auto is Off (in Pylon Viewer under Color Improvement Control). - If none of the above resolve this, check that your Exposure setting (in Pylon Viewer under Acquisition Controls, Exposure Time (Abs) [us]) is high enough (try 8000). 18. Motion Blur in EthoVision XT - The Exposure setting in Pylon Viewer is incorrect (Exposure Time (Abs) [us] is likely too high, 20,000+). See the camera exposure settings guide for how to set the correct value in Pylon Viewer. 19. Camera Image Is Dark Even With Infrared Light - Aperture ring of camera lens is closed all the way or partially. - Exposure time of camera is too low. - Gain of camera is too low. Take care when increasing gain as it often introduces unwanted noise to the video image. - Some color cameras may have an IR cut filter attached by default, resulting in a dark image. To remove the IR cut filter, see the relevant guide. 20. Camera Will Not Focus - The camera will not focus if the wrong type of lens is mounted (e.g., a C-mount lens on a CS-mount camera or vice versa). If you have a C-mount lens on a CS-mount camera, it can be used but requires an adapter ring installed between the lens and camera. If the camera and lens have the same mount type, make sure the adapter ring has not been installed, as it will prevent correct focus. - Perform a factory reset on the camera: - Open Pylon Viewer and at the bottom left of the interface, make sure the User Level is set to Guru. - In the Features Window, select your camera (for example Color Camera 1 (serial number)) and expand it. - Near the bottom of the list, expand Configuration Sets: - For Configuration Set Selector, select Default Configuration Set. - For Default Startup Set, select Default User Set. - For User Set Save, click the Execute button. - For User Set Load, click the Execute button. - The camera should now be reset to factory defaults. - While still in Pylon Viewer, set the following: - Go to AOI Controls: - For Width, type 1280. - For Height, type 960. - Select the checkbox for Center X and Center Y. - Follow Section H to set the remaining settings, including the Exposure. - Save your settings. - Close Pylon Viewer. 21. Camera Order Scrambles When a GigE Camera Signal Is Lost - Always plug cameras into the same ports. Label the ports and camera cables if needed to keep things in order. - Restore the camera signal. - Once the camera signal is restored, open EthoVision XT and toggle between Acquisition and Experiment Settings. Go to Acquisition, then Experiment Settings, then back to Acquisition. The camera order should now be restored to the original setup. - Note that despite the visual swapping of cameras listed in the Source table (via Experiment Settings in EthoVision), the cameras should still load in the correct order per your Arena Settings definition. 22. Significant Lag or Freezing During Tracking - Reboot the PC daily to refresh its resources. - Assuming you are using a PC purchased from Noldus and the setup is not too taxing (multiple animals, arenas, and/or multiple body point tracking), this is likely caused by incorrect Exposure settings in Pylon Viewer. Also review your Resolution and Frame Rate settings in EthoVision (see Section K for more info). - Note that a small lag when navigating between modules (Experiment Settings, Arena Settings, Detection Settings, or Acquisition) is normal, as EthoVision accesses the camera during these transitions. - To confirm that the lag during tracking is caused by the camera setup, check for Missing Samples (see item #23 below and Section L). - If none of the above resolve the lag, and your PC was not purchased from Noldus, it may be insufficient to run EthoVision, which is a very CPU-intensive program. To have Technical Support review your PC specs, create a PC report (see Section P) and send it to support@noldus.com. 23. Track File Has Many Missing Samples or Interpolated Samples - Missing Samples or Interpolated Samples can be viewed while EthoVision is acquiring data, or after the fact via Trial List. Click Show/Hide, select Variables, then select either or both Missed Samples and Interpolated Samples. - Missing Samples or Interpolated Samples percentage should be at or very near 0%. - The Exposure setting in Pylon Viewer is likely incorrect (Exposure Time (Abs) [us] is likely too high). See the camera exposure settings guide for how to correct this in Pylon Viewer. - If your Pylon Viewer exposure settings are correct and you are tracking live (not from pre-recorded video), make sure Video Pixel Smoothing is set to None in EthoVision (found in Detection Settings). - If none of the above resolve the problem, and your PC was not purchased from Noldus, it may be insufficient to run EthoVision. An insufficient PC will cause the system to miss samples. To have Technical Support review your PC specs, create a PC report (see Section P) and send it to support@noldus.com. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Ethovision Xt: (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-ethovision-xt-continued-TgD Chapter: EthoVision XT EthoVision XT Troubleshooting (Continued) - If everything is setup correctly to a T per this document (and PC/Video card are sufficient) and camera is not working properly in EthoVision XT (missing samples for example). Then try disabling the firewall (info below), disabling anti-virus software and/or last resort do a factory reset on the camera. - Disable Firewall: - Go to Start menu and type firewall, then click Firewall and Network Protection. - Click Advanced Settings at the bottom. - Under Overview (middle panel), click Windows Defender Firewall Properties. - Click the Public Profile tab. - Next to Protected Network Connections, click Customize. - Deselect the option in front of Local Area Connection. - If there is more than one local area connection, check step 4 in To Create Settings for the Ethernet Card for the correct local area connection. - Repeat steps 4-6 for the Domain Profile and Private Profile tabs. - Click Close. - A warning balloon appears in the bottom-right of your window. Ignore this message and close all windows. - Disable Anti-Virus Software: Check the settings in your anti-virus software or ask your local IT person to disable it. - Factory Reset: See Troubleshooting #18-B for how to do a factory reset. Camera must then be setup again per Section H. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - K – Camera Settings → Ethovision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-k-camera-settings-ethovision Chapter: EthoVision XT Camera Settings in EthoVision This functionality is available since EthoVision XT v15+ via the Noldus Basler Pylon Interface that EthoVision XT installs. However, Noldus Support recommends that these settings be made in Pylon Viewer (see Section H). The reason being when set/saved in Pylon Viewer, these same settings are applied to all of your EthoVision XT experiments. Should you want to change the settings for a one off experiment in EthoVision XT, here is how: Aim: To adjust the settings of your camera within EthoVision XT. For example, the video resolution, the frame rate, or the exposure. Important: To improve the quality of the image, always try adjusting the lighting and camera aperture before changing the settings in EthoVision XT. To Access These Options - Choose Setup > Experiment Settings, and click the camera button for the camera you require. - Open the tab you require. Format Tab The Format tab is only available for the first camera. The settings you specify here are also applied to the other cameras. You can change Resolution and Frame rate in EthoVision XT, but the new values are not kept in the camera software after restarting the computer. However, they are still selected in EthoVision XT. Important: If you change resolution, open the Arena Settings and update the background image. If the Arena Settings are locked, delete all trials (if that is possible) or make a duplicate of the Arena Settings and there update the background image. Resolution For single arenas and subjects more than a couple of centimeters long, a resolution of 384x288 (PAL) or 320x240 (NTSC) is sufficient. The higher the resolution, the more accurate your tracking. However, when you choose to save video to a digital video file and record for a long time, the files can become quite large. The higher the video resolution, the bigger the files. If disk space is limiting, use the above-mentioned resolution. Note: For analog cameras, the resolution is determined by the TV standard (see below). For some cameras there is only one video resolution available. Frame Rate This is the number of video images per second that are generated by the camera. For analog cameras, this is determined by the TV standard of your camera. For digital cameras, it can vary. A high frame rate is recommended when working with fast-moving animals, or when you want to detect movements like startle responses in fish or rapid turns in flying insects. High frame rates require more processing power. If you select a high frame rate, in some cases you need to lower the video resolution. This window shows a message when that is the case. Note: The frame rate is not the same as the Sample rate. Color Space Color space determines how the information about brightness and color is encoded in the video frames that are sent to EthoVision XT. Note that this may impact the maximal framerate. The optimal color space differs between cameras. - For monochrome cameras: Choose Y800. Check the preview image to assess whether the image quality is good. - For color cameras: If the image is black-and-white instead of color and a Moire pattern appears in the image, try using another color space. Normally, the default color space gives a good image quality. Otherwise, use YUY2. If you use a high frame rate or resolution, this reduces the number of animals you can track simultaneously. This also depends on how fast your computer is. Tip: In the Detection Settings, in the Detection Performance pane check the value under Missed Samples to get an indication of the quality of tracking. Standard This is only available for analog cameras. Select the TV standard of your camera. You can find this in the specifications section of your equipment's manual. It will probably be the standard used in your country. - PAL: In Western Europe, China, Indonesia and Australia. - NTSC: In United States, Canada and Japan. Image Tab Brightness, Contrast and Saturation are only available for analog cameras. Move the slider, click the arrows or change the number in one of the fields to adjust the settings and check the resulting image. Click the Default button to revert the Image settings to default. The settings on the other tabs will not change. Click the More Settings button to open a window with additional settings. Brightness Be aware that a too dark or too bright image may reduce the quality of video tracking. Brightness is not the same as Exposure; the latter is the period of time when the camera sensor is exposed to light. Contrast This is the difference in brightness or color that makes objects in an image distinguishable. Use this slider to enhance or reduce the contrast in the image. Saturation This is the strength or purity of the color and represents the amount of gray in proportion to the hue. A saturated color is pure, while an unsaturated color has a large percentage of gray. Camera/General Tab Some options are only available for Basler cameras. Center Image When selected, this option ensures that the image is centered over the sensor when not capturing the largest possible image. We recommend keeping this option selected. If you want to have the camera image off center, for example to exclude part of the camera view, click the More button. This opens the Pylon Viewer software. First click Cancel in the EthoVision XT Video Settings window, then in Pylon Viewer double-click the camera name and under Features locate AOI Controls. For details, see the Basler camera documentation. Binning When selected, sensor pixels are grouped together to make one image pixel. For example, selecting 2 means two horizontal and two vertical pixels, thus 4 sensor pixels make up one image pixel. This increases the sensitivity of the camera but reduces the image resolution. Exposure Time Exposure determines the time when the sensor is exposed to light. The higher the value, the brighter the image. Note that if Exposure is too high, the camera may not be able to send the images at the supposed frame rate. In that case, the window shows that the frame rate is too low. Reduce the Exposure, or reduce the frame rate to have longer time intervals between subsequent video frames. - For Zebrafish larvae: Enter 4000 or 2000, depending on the video resolution chosen. - For rodents: A value below 20000 is fine. - For a mosquito filmed under infrared: A value around 10000 is fine. - All else being equal, faster animals require shorter exposure times. Tip: If the image becomes too dark due to the short exposure time, increase the Gain. Gain Adjust the Gain to change the amplification level of the signal coming from the camera sensor. A higher value means more sensitivity. Increase the gain to make the picture brighter, for example in dark environments. Be aware that higher Gain may increase noise in the image. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - N – Ethovision Restrictions & Deep Learning Requirements URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-n-ethovision-restrictions-deep-learning-requirements Chapter: EthoVision XT General Features - Subjects per Arena: 1 (Base module), up to 16 (Social Interaction module). The limit of 16 subjects is set by the software. It may be difficult to discriminate between 16 different color marks depending on the light conditions. We recommend to only use Tracking from video files when you track multiple subjects and multiple body points. - Arenas: Multiple arenas with the Multiple Arena Module; one arena with the Base Module. Arenas must not overlap. The number of arenas does not depend on the number of cameras. You can have for example 96 wells in one camera image, or 16 arenas with 16 camera views (one arena per camera). When you combine tracking of multiple subjects (with colors) and multiple arenas, performance may limit the total number of subjects followed simultaneously. - Trials: With the Trial and Hardware Control Module. - Behavior Types Scored Manually: With the Trial and Hardware Control Module. - Hardware Commands and Signals: With the Trial and Hardware Control Module. - Arena Settings Cache: 50 MB. - Heatmap Dimensions (Pixels): No restriction specified. - Rows or Columns in Analysis Results Table: One million. - Free Intervals / Time Bins: No restriction. If you create more than 1000 time bins, the group charts are not displayed. Computer Requirements - Computer Type: Workstation. We recommend the use of Dell workstations especially when using multiple add-on modules (e.g. tracking nose-, center- and tail-base points in multiple subjects simultaneously). When tracking for more than 24 hours, restart the PC before a new trial. - Video Graphics Card (GPU): NVIDIA, 4 GB or larger. Supported GPUs: - Quadro P2200 - T1000 - GeForce RTX 4060 If you opt to buy your own PC, it must have a stand-alone graphics card that supports Direct3D acceleration. We recommend NVIDIA video cards with a memory of 4 GB or larger. 5th Generation boards are NOT yet supported. For tracking subjects with Deep Learning, there are further restrictions. See Deep Learning: Requirements. - Processor and RAM Memory: Intel. We recommend an Intel processor with 32 GB RAM. Video Resolution, Sample Rate and Trial Duration - Video Resolution (Camera Image): Depends on camera type. GigE maximum resolution for use in EthoVision is 1280 x 1024. - Video Resolution (Video File): 1900 x 1200. Keep DDS selected in the Acquisition screen. - Sample Rate (Live Tracking): 60 frames per second; it depends on the camera. Possible with GigE when using with DanioVision. - Sample Rate (Tracking from Video File): Not specified. EthoVision XT can handle short video files with a frame rate of 1000, but that also depends on the video format. Test a few sample videos and check for missing samples before running the experiment. - Trial Duration: 72 hours maximum, but this depends on the tested setup. Max duration of 72 hours: - 16 GigE (2560x1920) + Contour @30fps - Sylics: Contour + Center, 4 arenas - DanioVision (live, no recording) Max duration of 3 hours: - 1 GigE (1280x1024) + DL @60fps - 2 GigE (1920x540) + DL @30fps - 4 GigE (2560x2048) + DL @25fps - 4 GigE (2560x2048) + Contour @60fps DanioVision: - Recording video: 1 hour - Live (no recording): 72 hours Deep Learning and/or MST Live (max 4 arenas): - 1 animal: 72 hours - 2+ animals: 1 hour Important: When tracking from video files at high resolution and/or frame rate, always select DDS in the Playback Control window. This way EthoVision XT adjusts the analysis speed to the time needed to analyze each frame without skipping frames. Important: When tracking for more than 24 hours, always reboot the PC after every trial to refresh the PC resources, the RAM specifically. Failure to do so could result in crashing, which can corrupt the experiment or the recorded video. Applications and Add-Ons - Multiple Body Point Module (Live Tracking): Four arenas per computer. In principle it is possible to track in more than 4 arenas, but it depends on the apparent size of the subjects in the video image (in pixels). Sample rate must be 25 or 30 FPS. - Multiple Arena Module: 100 arenas. The number of arenas may be limited by other factors, for example the number of subjects in each arena and the tracking of multiple body points. Contact Noldus if you wish to work with more than 100 arenas. - Social Interaction Module: 16 subjects per arena. If subjects are unmarked, there may be subject identity swaps. - CognitionWall (Sylics): Four arenas, only center-point tracking; up to 72 hours recording. In case of recordings longer than 24 hours, we advise to restart the PC after each trial. A workstation is required. - Behavior Recognition: One subject per arena; one arena (live tracking), up to four arenas (offline tracking). Requires the Multiple Body Point module. Camera must be overhead. Camera frame rate must be at least 25 fps with no missing frames. Cannot work together with Deep Learning-based tracking. The PC must be a workstation. - Deep Learning for Nose-Tail Base Tracking: One or two subjects per arena (up to 4 arenas). See Deep Learning Requirements below. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - O – Pc’S Not Bought From Noldus URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-o-pcs-not-bought-from-noldus Chapter: EthoVision XT PCs Not Bought from Noldus If you didn't buy your PC from Noldus, there are crucial requirements to be aware of as well as some settings that might need to be set. Without these in place, you can experience a variety of problems with this camera in EthoVision XT (crashing, black image, low frame rate, missing/interpolated samples or trials ending too soon/prematurely). If you cannot get the camera working properly on your PC after working through this entire document, then please see the PC Report section below and send support@noldus.com a PC report. To ensure your PC is sufficient for EthoVision (RAM & GPU), please see Section N. GPU/Video Card Settings How to point EthoVision to the NVIDIA (GPU) video card (this option isn't always available) rather than the onboard (GPU) video card: Method 1: Windows Start → Graphics Settings → Browse → C:\Program Files\Noldus\EthoVision XT 17 → EthoVision.exe → Options → High performance → Save Method 2: - Go to the program folder: C:\Program Files\Noldus\EthoVision XT 17 - Right-click on EthoVision.exe (the application file) and select Run With Graphics Processor, then select your video card (for example, NVIDIA). If you cannot see a folder (like Program Files (x86)), it may be hidden. To unhide it: - Log into the PC as an Admin if not already. - Right-click on Windows Start and select Open Windows Explorer (might also be called Open Explorer or Open File Explorer). - Go to Tools menu / Folder Options. - Go to the View tab and select Show hidden files, folders and drives. - Click OK. You should now be able to see the above directory. Power Save Settings Disable Fast Startup (Windows 10 only): - Go to the Start menu. - Click the gear for Settings. - Pick System. - Pick Power & Sleep. - Then Additional Power Options in the upper right. - Then Choose what the power buttons do in the upper left. - Click Change settings that are currently unavailable (requires an admin password). - Uncheck the options for Fast Startup, Sleep, and Hibernate. Power Save: - Go to Start and select Control Panel. - In the Search Control Panel field in the upper right-hand corner, type in Power. - Under Power Options, select Edit Power Plan. - For both options, select Never. - Click Save Changes. - Click Change plan settings. - Click Change advanced power settings. - Under Hard disk / Turn off hard disk after, set this to 0 (never). - Click OK. Automatic Updates - Go to Start and select Devices and Printers. - Right-click on your PC (image looks like an external hard drive) and select Device Installation Settings. - Select No, let me choose what to do and Never install driver software from Windows update (3rd bullet). - Click Save Changes. BIOS Settings - Turn on the PC. - During boot up, immediately press F12 to go into BIOS. You may need to press F12 a couple of times. - On the left-hand side under Settings, expand Performance. - Click on C States Control. - Deselect the checkbox for C States Control. - Navigate back to Performance on the left-hand side and locate Intel SpeedStep (previously called P-States). Confirm that the checkbox is deselected. If it isn't, please deselect it. - If you have another processor (like AMD), you might see PowerNow!, Cool'n'Quiet, or PowerSave. - Click Exit. - When prompted to save changes, click Yes. - The setting change is retained and the PC finishes booting up. Network Card The network card must be a 1+GB adaptor set to Auto-Negotiate. Currently supported network cards for EthoVision v18: - FS X550AT2-2TP (10GB NIC) - Adlink PCIe-GIE74 (1GB NIC) - Basler GigE Interface Card (1GB NIC) If you are unable to source the supported network cards, the following Basler resource provides information on which network cards are compatible with the GigE camera: https://www.baslerweb.com/en/sales-support/knowledge-base/frequently-asked-questions/can-you-tell-me-which-network-adapters-are-compatible-with-the-basler-pylon-performance-driver/15176/ If the camera is set up correctly per this document and the PC is sufficient (has a supported video card and the onboard video card is disabled), yet camera issues persist in EthoVision, check the following on your network card: In the Device Manager, locate your network card, right-click on it, and select Properties. Go to the Advanced tab and change the relevant settings. Should you encounter any errors in Pylon (for example: error 0xE1000014 / 3774873620: The buffer was incompletely grabbed), please also see the following: https://www.baslerweb.com/en/sales-support/knowledge-base/frequently-asked-questions/troubleshooting-lost-packets-or-frames-while-using-gige-cameras/29830/ If you cannot get the camera working properly on your PC after working through this entire document, please see the PC Report section below and send support@noldus.com a PC report. PC Report This section is only required if you have set up the camera correctly in both Pylon and EthoVision XT, yet you are still experiencing problems with the camera. - Download the PC Report Utility and save it to your Desktop. - On the Desktop, locate the ZIP file, right-click and select Extract All > Extract. - In the SIW 2021 folder, double-click on siw64.exe. - Go to File > Create Report File > HTML Report. - Save the HTML file to your Desktop. - Send the HTML file as an attachment to support@noldus.com. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Prerequisites URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-prerequisites Chapter: EthoVision XT Prerequisites - You have followed the entire procedure in Install an Ethernet Board for GigE Cameras. - No matter how many cameras you use, you need a 1-Gb Ethernet interface board (desktop computers only). - When you use a 4-port Ethernet board, you can power the cameras with Power-over-Ethernet (PoE) injectors but you can also choose to connect the board to the power outlet inside the PC. See the relevant step in Install an Ethernet Board for GigE Cameras. - When you do not use a 4-port Ethernet board, you must use 1-Gb Power-over-Ethernet (PoE) injectors; use one per camera. - Cables: Use Cat5e or Cat6e crossover cables. - Do not use an Ethernet to USB adapter to connect the camera to the PC. Always connect the camera and the PC directly using an Ethernet crossover cable. Procedure A. Single Port Ethernet Board To connect one camera, you need a single or dual port Ethernet interface board. To connect two cameras, you need a dual port Ethernet interface board. In either case you need as many PoE injectors as cameras, since the single port boards are not powered. - Using cross-network cables (Cat-5e or newer), connect the Ethernet port/board on the PC to the IN port of the PoE injector. Connect the camera to the OUT port. Use the short cable between the PoE injector and PC. Use the long cable between the PoE injector and camera. - Power up the PoE injector; make sure that the two CONNECT and ON green LEDs are on. - If the green LEDs keep blinking, wait a few more seconds. If you see no change, disconnect the cables, then re-connect them. - Next: Configure the digital camera. You can also connect two cameras to two single-port Ethernet boards. B. Two or Four-Port Ethernet Board (Power Injector Not Required) When you use this board, you can power the cameras without using the PoE injectors. However, make sure that the board receives power from the PC. See the relevant connection step in Install an Ethernet Board for GigE Cameras. - Connect each camera (up to four) to one of the ports on the Ethernet board, as shown in the figure below. - Next: Configure the digital camera. - Tip: Label the cameras and the Ethernet ports (for example Cam 1, Cam 2, etc.). Take note of the camera serial numbers; these actions may be useful when you need to know which camera is connected to which port and assign or adjust the IP addresses. - The Power over Ethernet (PoE) injector is a device that passes power along with data (in this case, video data from the camera) on twisted-pair Ethernet cabling. 2 or 4 Cameras To track from two up to four GigE cameras. This topic applies to Basler GigE cameras only. Important: You cannot use a combination of analog and digital cameras. Also, mixing video images of different camera types is not supported. Connection Schemes How you connect multiple GigE cameras depends on which Ethernet interface board you have installed. - If you have multiple 1-port Ethernet boards, connect each camera to an Ethernet board. Connect each PoE injector to a power supply. - If you have a 4-port Ethernet board, you can connect up to four cameras. Important: Make sure the Ethernet board also receives power from the PC. See the relevant connection step in Install an Ethernet Board for GigE Cameras. Select Multiple GigE Cameras in EthoVision XT EthoVision XT mixes the camera images in a picture-by-picture fashion. - Connect your cameras. - In EthoVision XT, choose Setup > Experiment Settings and select the number of cameras from the list next to Number of Sources. - Select the cameras under Source. The camera names will show their own IP address in brackets at the end, which makes it possible to distinguish between the cameras. - Select the resolution and frame rate of the first camera. The resolution and frame rate of the other cameras is set automatically to the same values as for the first camera. - Next to Merged Camera View, select whether the picture-by-picture mixed image should have the same resolution as the images from the individual cameras, or whether the resolution should be the sum of that of each camera image. The maximum total resolution is 1920 x 1200. The camera model determines the maximum resolution. - Click the preview icon to get a preview of the merged camera images. - Noldus does not support video tracking from multiple GigE cameras connected to a laptop computer. Always connect multiple cameras to a desktop computer. - Important: Each camera must always be connected to the same port on the Ethernet board; the IP address of the camera and that of the adapter are linked. In the case of a multi-port Ethernet board, each port is viewed as a network adapter with its own IP address. The information of which port is linked is stored in the driver software of each camera. If you swap cameras, they will not be recognized. Therefore, always label the Ethernet ports and the cameras. - Tip: When using one Ethernet interface board per camera, rename the network adapters listed in the Windows Control Panel, for example Front camera and Top camera. Each camera must have a unique IP address. The third set of numbers should be different between cameras. Note that the third set of numbers must be the same for the camera and the adapter it is associated with. See the following example: - Camera 1: 192.168.x.1 associated with network adapter with IP 192.168.x.101 - Camera 2: 192.168.y.1 associated with network adapter with IP 192.168.y.101 - The cameras should have the same firmware version. Check this in the Pylon Viewer software. In the Features panel, under Device Information, check Firmware Version. If the cameras do not have the same firmware version, an upgrade or downgrade must be performed. - US and Canada Customers: Use 192.168.200.1 for the camera IP address. The second camera on the same card or port should use 192.168.200.2, and so on. The subnet mask should be 255.255.255.0 for all cameras. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-procedure Chapter: EthoVision XT Procedure - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. Different PCIe slots have different properties, resulting in different performances. When possible, choose the slot that gives maximum performance. To estimate performance, take note of the slot version (2, 3, etc.) and compare it with the following: - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: ~1 GB/s - PCIe v4.0: ~2 GB/s - PCIe v5.0: ~4 GB/s Note that values are given per lane; they should not be multiplied by the number of lanes in a slot (e.g. x4) since the board has a 1x connector. For example, SLOT1-PCIe3x4 written near the slot means version 3.0 with four lanes. IMPORTANT: Do not insert the PCIe board in the blue or white slots. - Unpack the Ethernet board, place it into the slot, and press it carefully into position. If the board does not fit into place easily, remove it and repeat the operation. IMPORTANT: When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet, and attaching its clip to the metal frame of the computer. If you do not have an earthing wristlet, hold the metal frame with one hand while holding the Ethernet board in your other hand. Ensure also that your clothing does not touch any components while handling the board. - This step is only for when installing a 2 or 4-port Ethernet interface board. - Not for single port NIC where camera is powered by PoE Power Injector. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. - Fix the board to the chassis and re-fit the computer's cover. - Next: Install the driver software for the GigE cameras. IMPORTANT: Turn off Fast Startup in the Windows Power options. Disable Fast Startup - Open the Windows Control Panel, and select System & Security. - Under Power Options, select Choose what the power button does. Click Change settings that are currently unavailable. - Under Shutdown Settings, de-select Turn on fast startup (recommended). Ethernet Board Settings - In Windows, open the Device Manager. - Under Network Adapters, locate your Ethernet board, right-click on it and select Properties → Advanced. - Adjust the settings as follows: - Interrupt Moderation: Disabled - Interrupt Moderation Rate: Off - Receive Buffers: 2048 - Jumbo Packets: 9014 Bytes - Click the Power Management tab and de-select Allow the computer to turn off this device to save power. Assigning IP to Ethernet Board - In Windows, search for Network Connections. Alternatively, in Windows 11, from the Start menu choose Settings > Network and Internet > Advanced Network Settings (at the bottom of the screen) > More Network Adapter Options. - In the Network Connections window, right-click the item that corresponds to your camera and click Properties. TIP: If your computer has more than one item, unplug the camera and take note of which item shows Unplugged. NOTE: You may see one or more additional items labeled Ethernet or similar. This is the standard interface board that is connected to your local network and internet. Do not use that board unless it is the only one available. If you choose that adapter you won't be able to connect the EthoVision XT computer to the network. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Select Use the following IP address and Use the following DNS server addresses and fill in the details as shown in the figure below. Also select the option Validate settings upon exit. When done, click OK and then Close. US-Canada Customers: Use 192.168.200.101 for the computer network adapter IP address. Multiple Network Cards or 1 Card with Multiple Ports: - 192.168.201.101 for second card/port - 192.168.202.101 for third card/port, etc. Subnet Mask: 255.255.255.0 - A Windows Network Diagnostics window appears. Click Close when it is finished. Then close all windows. Note: If you purchased a 2 or 4 port network card, follow the above procedure once for each network card or port. For more information about using multiple cameras, see Section F. D – Installation → Camera Driver (Pylon) Aim To install the software that enables you to configure the camera — for example, to set the video frame rate or the exposure time. Procedure via EthoVision XT 18 Installation - Download from MyNoldus or insert the EthoVision XT installation USB stick into your computer. - Double-click EthoVision XT – Setup – 18.0.1832.exe. If you have already installed EthoVision XT, select Modify; otherwise select Install. NOTE: The folder where EthoVision XT – Setup – 18.0.1832.exe is stored must also contain the following files for a successful installation of EthoVision XT 18: - EthoVision XT – Package – 18.0.1832.msi - TrackerInterfaceNN_x64_3.0.8.msi - TrackerInterfaceMST_64x_1.0.12.msi - Under Drivers and Tools, select: - Basler GigE camera driver if you have Basler GigE cameras. - Click Install/Update and continue with installation. - Next: Assign IP addresses. NOTE: Always install the drivers from the installation USB stick or the Noldus web site. Do not install drivers from other sources, unless requested by Noldus Support. Procedure for Manual Install of Pylon 7.5.0 - Download Pylon 7.5.0 and double-click the downloaded EXE file. - Accept Terms & Conditions → Next. - Select Profiles → Custom → Next. - Under Features, select GigE Camera Support. - Also select: - DirectShow Support - Pylon Viewer - Complete the Pylon 7.5.0 driver installation. E – Connecting the Hardware Aim To make sure that EthoVision XT receives the video signal from the GigE camera. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GigE Install and Setup - Table Of Contents URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gige-install-and-setup-table-of-contents Chapter: EthoVision XT Installation Videos 2 different tutorials…same topic! They both assume the camera is powered with a PoE Power Injector when most shipments today (2025+) are coming with a powered network card with 2 or 4 ports. Both modes of powering the camera are discussed in this document. - In EthoVision XT v18 → Open camera tutorial → Help > Video Tutorial. - Download a video tutorial showing you how to install and setup this camera: - GigE Installation Video Laptops - Only 1 camera is supported. - This will be a dedicated camera network on your 1GB network port. - If you want to use the internet on the laptop you will need to use either Wi-Fi or purchase a USB network adaptor like this one: USB 3.0 to Gigabit Ethernet Adapter - USB Adapter - TRENDnet TU3-ETG - Network Card: Section C applies mostly to desktops but please see the end of Section C (Assigning IP to Ethernet Board) for how to configure your laptop's network connection. Then please see Section D for installing the drivers. - FYI: Maximum supported time for live tracking and/or recording in EthoVision XT v18 with a Basler GigE or USB3 on a workstation laptop is 12 hours. Cables - If you bought your camera elsewhere, make sure you bought the correct cables and quality cables. Cheap or incorrect cables will affect frame rate and result in missing samples or interpolated samples. - Maximum cable length 100 meters. - See Section E for connections info/wiring diagram. - Cat5e cable going from camera to power injector: CAT-5e cable from Amazon - Crossover cable going from power injector to PC: CAT6 cable from Cables to Go PoE Power Injector - 2025+ Noldus most often ships a powered network card with 2 or 4 ports. If your order did NOT come with a PoE Power Injector, then it should have shipped with a powered network card. - If you bought your camera elsewhere (and you are NOT using a 2 or 4 port powered network card), you need a power injector (to power the camera) and it MUST be 1GB. - Can purchase power injector here: Axis Power Injector 30W Midspan - 1GB - from Amazon IP Addresses - When assigning the IP address to either the network card or camera, please follow the red text in the red box on pages 13 and 17. Do not use the IP address shown in the images or whatever IP the PC defaults to. Tracking in IR - The monochrome GigE camera is IR sensitive and does not require an IR Pass Filter unless you will be tracking in both light and dark conditions in the same trial. - Depending on how bright your IR setup is, you might need to open the aperture on the lens all the way (do this first) and/or adjust the camera's Gain (Raw) (see here) and/or adjust the Exposure setting in Pylon Viewer (see here). - If you need to increase the camera's Gain (Raw) setting in Pylon, do not increase it too much or you will increase camera noise. Consider adding a second IR light if that is the case (and lowering the Gain (Raw)). - ~Mid-July 2018: Color GigE cameras (model: acA1300-30gc) purchased after this time (from Noldus) had the IR Cut Filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). - If you bought a color GigE camera from Noldus prior to ~July 2018, see below for how to remove the IR Cut Filter to make your color camera IR sensitive. IR Pass Filter (24-Hour Experiments) - New Style: It simply screws on to the front of the lens. - Old Style: It simply screws on to the front of the lens. Color to Monochrome - If you have a color camera, you can temporarily change it to monochrome by changing the Pixel Format setting (see here). - In Pylon Viewer, change the Pixel Format to Mono8. - In EthoVision XT, set the Color Space to Y800. - Please note this does not make the camera IR sensitive. For that you must either remove the IR block filter (see above) from your color camera OR use a monochrome GigE camera. - ~Mid-July 2018: Color GigE cameras (model: acA1300-30gc) purchased after this time (from Noldus) had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). - If you bought a color GigE camera from Noldus prior to ~July 2018, see above for how to remove the IR block filter to make your color camera IR sensitive. - If you do want to use your color camera in color, please see Section I for best settings. Lenses Image Magnification: If you need to get higher magnification images than is available with a standard lens, you can use one of the following techniques. - Macro Lens: A true macro lens, that is, a lens of a magnification of at least 1:1 (expressed as 'real world': CCD chip size), usually gives good quality images. However, it is often expensive and probably gives a lower magnification than either a close-up filter or an extension ring. - Extension Rings: An extension ring inserted between the camera body and the lens enables you to focus on subjects closer to the camera, and so provides a greater magnification. An extension ring is usually cheaper than a true macro lens, but more expensive than a close-up filter. It may give a reduction in optical quality and will reduce the light intensity of the signal, but you can use it to get very high magnifications. - Close-Up Filter: This is a lens attached in front of the normal lens to give greater magnification. Also known as a close-up lens, it works by shortening the focal length of the lens while keeping the lens-to-camera distance constant, which increases the magnification. The strength of a close-up filter is measured in diopters, which is the fraction by which the lens' focal length is shortened. Thus, a +3 lens reduces the focal length of the lens to which it is attached by 1/3. A close-up filter is usually cheaper than a macro lens or extension ring, but it gives lower magnification and poorer optical quality. - Microscope: EthoVision XT tracks well from cameras attached to microscopes. Use back-lighting to maximize contrast. Mounting the Camera This section only applies if you bought either a Dual Option Mount and/or an Autopole with Superclamp from Noldus. The items below are NOT standard with your camera or EthoVision purchase. Contact sales if you would like a quote to purchase any of these items. Source: EthoVision XT 18 - GigE Install and Setup, Noldus Information Technology --- ## EthoVision XT 18 - GPU Video Decoding and Encoding URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-gpu-video-decoding-and-encoding Chapter: EthoVision XT Why This Technical Note This technical note addresses an issue that may be of interest to those who have a previous version of the software (EthoVision XT 17.0 or earlier) and have upgraded to EthoVision XT 17.5 or later. Important Terms - Decoding: This equals playing back existing video files during tracking. - Encoding: This equals recording video from a live camera stream. This note is mainly about an issue that occurs when decoding video, not encoding video. Use of the GPU for Encoding and Decoding Video As you probably know, EthoVision XT reads information from a video file and uses the pixel values to detect one or more subjects. Please note the difference: - In EthoVision XT 17.0 and earlier versions, encoding and decoding of video is done by the CPU (Central Processing Unit, or processor) of the EthoVision XT computer. - In EthoVision XT 17.5 and later versions, encoding and decoding of video is done per default by the Graphics Processing Unit (also known as GPU, or graphics card). The reason for this change from version 17.0 to 17.5 is that the GPU allows faster processing of video especially when you work with video of high resolution, or track subjects with the Behavior Recognition function. This reduces the workload of the CPU, and results in greater performance during tracking. Description of the Issue Video Image When EthoVision XT uses the GPU to decode (i.e., play back) a video file, the image looks slightly different from what it would do if the software used the CPU for the same task. This difference occurs in some videos, not others. Where a difference appears, the GPU-based image is slightly brighter than the CPU-based image. The difference map between the two images uses the following indicators: - Blue pixels: Indicate a difference of 17 or smaller. - Red pixels: Indicate a difference of 18 or greater. - Black pixels: Indicate no difference between EthoVision XT 17.0 and EthoVision XT 17.5. In other words, EthoVision XT 17.5 and later versions "see" a video file not exactly as EthoVision XT 17.0 and earlier would. Effects of This Issue on Detection If the video image in EthoVision XT 18 (playback with GPU) is not exactly the same as that in EthoVision XT 17.0 and earlier (playback with CPU), the detection settings used in experiments made in EthoVision XT 17.0 or earlier are probably no longer optimal when you use the same video file in EthoVision XT 18. For example: - If you use the Gray Scale detection method, you may need to change the range of gray values to detect the subject correctly. - If you use the Dynamic Subtraction method, you need to make a new reference image from the current video and modify the contrast range to detect the subject correctly. If you are in the middle of an experiment that you started in EthoVision XT 17.0 or earlier, you would need to acquire the new trials with different detection settings. This may not be desirable because you want to keep consistent detection settings across the trials to reduce the risk of biases in the analysis. What Should I Do? If You Have Completed All Your Experiments in EthoVision XT 17.0 or Earlier You do not need to take any further action. Click Yes in the window that appeared when you opened the experiment. The experiment is converted to version 18. When you create a new experiment in EthoVision XT 18, the software uses the GPU to play back and record video. Open the Detection Settings and optimize them as usual. If You Have an Old Experiment and You Need to Acquire More Trials Complete the Experiment with the Old Playback Method If you need to complete an experiment after upgrading to EthoVision XT 18, then you may want to keep using the same video settings as before. This way you do not need to update your detection settings because EthoVision XT will use the old, CPU-based method to handle video, ensuring that old and new tracks are obtained with the same detection settings. Do the following after opening the old experiment and reading this note: - Click Yes in the window that appeared when you opened the experiment. The experiment is converted to version 18. - Choose File > Preferences. - Click the Video settings tab and next to Play back and record video select CPU. - Click OK. You are ready to acquire your trials. Re-Do All Trials with the New Method Alternatively, you can acquire all your trials with the new playback method. This means that you have to clear the existing trials — that is, delete the tracks without removing the videos — and re-acquire all trials, while keeping the option File > Preferences > Video settings > Play back and record video set to GPU. For how to re-do trials, see the EthoVision XT Help. How the GPU Option Is Applied The option for enabling and disabling the GPU for video encoding and decoding is applied at the application level. That is, the settings are applied to all new experiments that you create. - Make sure that the Video settings selection is kept consistent within experiments. That is, make sure that the selection is either CPU or GPU for all the trials in that experiment. - If you intend to create multiple experiments that are related to each other, we recommend that you keep your selection in Video settings consistent across those experiments. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - Heatmaps - From Different Arenas URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-heatmaps-from-different-arenas Chapter: EthoVision XT What You Need - EthoVision XT 16 or later. If you have EthoVision XT 15, let us know. You can still work with JavaScript by adding a registry key. - Microsoft Excel. - Power Map for Microsoft Excel, or software for creating heatmaps, for example R, MatLab, or OpenJump HORAE (featured in this note). Assumptions You have an experiment with two or more arenas oriented in the same direction. Choose what applies: - You still have to track the subjects. Go to Step 1a. - You have already acquired the tracks. Go to Step 1b. Step 1a - Draw the Axis Origin for Each Arena - Open the Arena Settings that you want to use. Draw the arenas, the zones, and do the calibration as usual. - Choose a point in the arenas that you want to use. For example, a corner of the cages. - Right-click the Calibration layer and select Unshare this Calibration. - On the panel at the right hand side, click one of the Arena layers (e.g. Arena 1). - Click the Calibration Axes button below the layers list. - Leave the coordinates of the origin to 0,0 and click OK. - Move the Axes object in such a way that the origin of the x,y axes is over the reference point. - Repeat the steps above (4-7) for each arena. - At this point, each arena should have its own Axes object positioned over the reference point and oriented the same way. You can now acquire the data. Next, go to Step 2. Step 1b - Add a Reference Point to Each Arena - Open the Arena Settings that you used to acquire the data. - Under the layer Arena 1, click the layer named Zone Group 1 (or any other zone layer). - From the tool bar choose Add point. - Click over a specific location and give the point a name. - Repeat the steps above (2-4) for the remaining arenas. Choose to use the same point name (here: SW corner). - Each arena should have its own reference point. Make sure that the points are listed under the corresponding arena layer. - Create or open an Analysis profile. - Under Custom Variables select JavaScript Continuous. - In the window that opens, delete the text already present. Copy the text under JavaScript Code for X (replace the "SW corner" with the name of your reference point) and paste it in the window. Next, click OK. - Under Custom Variables select JavaScript Continuous again. In the window that opens, delete the text. Copy the text under JavaScript Code for Y (replace the "SW corner" with the name of your reference point) and paste it in the window. Next, click OK. - At this point you should have two JavaScript Continuous entries in your Data profile. Rename the variables to X and Y, respectively. To rename a variable, right-click its name and select Rename. - Optional: Visualize the variables in Integrated Visualization to check they are correct. The values displayed should be the coordinates x and y of each subject relative to the reference point. Note: The new coordinates are in mm, no matter what you have selected as Measurement Units in EthoVision XT. Go now to Step 2. JavaScript Code for X // This code returns the x coordinate relative to a point // Make sure you define this point in all the arenas const g_zone = "SW corner"; function Start() { } function Stop() { } function Process() { var pt1 = GetCenter(); var pt2 = GetPointPoi(g_zone); if (pt1) { var xc = pt1.x - pt2.x; SetOutput(xc); } else { SetOutputMissing(); } } JavaScript Code for Y // This code returns the y coordinate relative to a point // Make sure you define this point in all the arenas const g_zone = "SW corner"; function Start() { } function Stop() { } function Process() { var pt1 = GetCenter(); var pt2 = GetPointPoi(g_zone); if (pt1) { var yc = pt1.y - pt2.y; SetOutput(yc); } else { SetOutputMissing(); } } Step 2 - Export the Tracks for a Specific Group or Treatment Level - In EthoVision XT, make a Data profile and use the Filter function to select the tracks of one group/treatment level (e.g., control subjects). - Choose Analysis > Export > Raw Data. Choose Excel as the export format. - Repeat steps 1 and 2 to create different datasets, one for each treatment level. For each treatment level, make a Data profile and export the data. You will create a heatmap for each dataset. Step 3 - Prepare the Excel Files If you are going to use Microsoft Excel 3D Maps, see the procedure for creating one global file below. Procedure for Creating One File per Subject - Each Excel file corresponds to one trial and contains one, two or more tabs depending on which arenas contain data for a specific group/treatment level. If you have two or more tabs, you must save them as separate Excel files (move a tab to the front and select Save As; repeat this for all the tabs). - Open each Excel file and delete the rows up to the headers. Also delete the row with the units, immediately above the data. The file should look like this: row 1 with the headers, row 2 onwards with the data. - Save each file in the format that your software for generating heatmaps requires. If you use OpenJump HORAE or R, the format CSV (MS-DOS) should work fine. Procedure for Creating One Global File for 3D Maps - Open the Excel files and copy the X and Y coordinates of each of them to one global file. Append the rows instead of creating multiple columns. There should be no empty rows in between. - Optional: Add an extra column which specifies the subject name. You can use this column to show the heatmap in different colors based on the subject identity. - Save the new file. This file should contain all the X,Y coordinates of subjects in one group, in just two columns. - Repeat the steps above for each group/treatment level. Step 4a - Create the Heatmap in 3D Maps - Open a global file for a specific group/treatment level. - Right-click the image of the Earth and select Change Map Type. - Select New Custom Map. Leave the selection as it is and tilt up the default background. - In the Field List, drag X and Y to the Location box and specify X Coordinate for X and Y Coordinate for Y. - On the Layers pane, choose Change visualization to Heat Map. - Click on Layer Options and adjust the settings when necessary, but keep Visual Aggregation set to Sum. Step 4b - Create the Heatmap in OpenJump HORAE OpenJump HORAE is free software for analysis and visualization of spatial behavior. You can import a global file for all subjects or separate files, one per subject. Separate files can be visualized in separate layers and contribute to a global heatmap. Install the Software - Download from the OpenJump HORAE website. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - Heatmaps - From Different Arenas (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-heatmaps-from-different-arenas-continued Chapter: EthoVision XT From Different Arenas (Continued) https://www.researchgate.net/publication/349224514_OpenJUMP_HoRAE_Software - Extract the files from the zip file and copy them to your PC. - Run the file .../bin/OpenJump.exe. Import the CSV Files into OpenJump HoRAE - Choose File > Open Files. - Select the CSV files (Ctrl + click each file) and click Next > Finish. The tracks are imported as layers. - Save the Project with a name (.jmp). - Select all layers, right-click Combine Selected Layers. - Save each new layer! Right-click and select Save Dataset As. Save layers in the same folder as the project. - To make the heatmap, select the Combined layer and from the MOVEAN menu choose HRE > Point KDE > Point Kernel Density. - The most important setting is the Distance h (smoothing factor), which is similar to the Smoothing value in EthoVision XT. You can have the software calculate it for you or you can enter a value in the same units as the coordinates. The value Cell Size is the size of each pixel in the heatmap: the greater the value, the grainier the image. - To change colors, select the layer Combined-KDE and from the Raster menu choose Raster Color Editor. - To hide the original data points, de-select all the layers except Combined-KDE. Extras To Create Probability Contours - Select the layer Combined-KDE and from the MOVEAN menu choose HR Analysis > Create Probability Contours from Raster. - Enter the probability value (e.g. 50%) and click OK. - De-select the other layers to view the contours. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - Heatmaps - In Ethovision® Xt 18 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-heatmaps-in-ethovision-xt-18 Chapter: EthoVision XT Why This Technical Note This technical note describes how you can merge heatmaps into one, when the data have been collected in different arenas/apparatuses. Use Case Example An EthoVision XT experiment has subjects being grouped based on the treatment level (or genetic background, etc.). Subjects are tested in four separate arenas. Because of the randomized design, each arena will be used for all treatment levels/groups. For example, Arena 1 will receive a subject of treatment level A in trial 1, then a subject of level B in trial 2 etc. As a result, one arena will not contain data of all trials with a specific group. The researcher would like to create a heatmap with all the trials that belong to that treatment level, and plot it on one arena layout, not four. EthoVision XT cannot do that with the current functionality. Important Terms - Reference Point: A point in the 2D space defined in the EthoVision XT Arena Settings, which serves as a reference point for re-calculation of the x,y coordinates of the subjects. The reference point must be defined in all the areas. - JavaScript Variable: A custom variable defined in the EthoVision XT Analysis profile based on JavaScript code. In this note, JavaScript variables are defined to convert the original x,y coordinates to a new set of coordinates relative to the point of reference. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - Installation and License Activation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-installation-and-license-activation Chapter: EthoVision XT Install EthoVision XT To install EthoVision XT - Browse to https://my.noldus.com. - Log in or register using the registration code on your welcome letter. - Click Downloads, then EthoVision XT. Under Versions, download the EthoVision XT 18 - Installation Package [version number] zip file. - Unzip the file and save the content to your PC. - Double-click the file EthoVision XT - Setup - [version number].exe. - Under Set Application Language, select either English (United States) or Chinese (Simplified). Under Installation type, select Standard. Notes You can also change the language at any time in EthoVision XT. Choose File > Preferences Language, then close and restart EthoVision XT. If you want to use video cameras with EthoVision XT, first install the appropriate camera interface boards and drivers on the EthoVision XT computer. For details, see Camera Installation in the EthoVision XT Help. To open the Help, press F1 in the software. If you save the installation files on a network drive before installation, copy them to your PC before running the Setup file. Make sure that all files included in the installation zip file are copied to your PC! Activate your license Activate Your License With A Usb Hardware Key If you have a hardware key, insert it into a USB port of the computer and start EthoVision XT. If you upgrade your EthoVision XT license, start EthoVision XT and enter the Upgrade key in the window that opens. With A Software License Key If you received a software license key, start EthoVision XT and activate your license. Choose between a Floating license or a Computer-locked license. Floating - The license can be used in different computers, though not simultaneously. Choose this solution if you want to be flexible on which computer you use EthoVision XT to acquire data, and your computers are connected to the internet. Computer-locked - The license is linked to one specific computer. To activate your license, that computer must have an internet connection, or you must have a smartphone with an internet connection. If you want to use EthoVision XT on a second PC to analyze existing data, not acquire new data, you can run it on that PC in Analysis mode, which does not require a license. Your first EthoVision XT experiment Source: EthoVision XT 18 - Quick Start Guide --- ## EthoVision XT 18 - Params - ▪Custom & Javascript Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-params-custom-javascript-variables Chapter: EthoVision XT EVXT Parameters Distance Moved Distance traveled by the center, nose, or tail-base - Often used as a general measure of activity; also used to calculate other parameters, like velocity and acceleration Velocity Distance moved between two points in time (i.e., speed) Movement Dichotomized variable of velocity – Moving or Not Moving - As opposed to velocity, movement provides a general measure, which is useful in long-term home cage studies Acceleration Differences in velocity between two samples Acceleration State Dichotomized variable of acceleration – High or Low 3 Day Spontaneous Behavior in the Phenotyper In Zone Discrete state event based on the zones of interest from the Arena Settings - Can be added after acquisition for subsequent analysis - Thigmotaxis, latency to platform (water maze), number of contacts and/or time spent in a zone (NOR, sociability), etc. Distance to Zone The shortest distance between a body point and a zone's edge - Mean Distance to Zone is a qualitative metric (especially if visualized) for progress towards a zone (platform, goal hole) Distance to Point The shortest distance between a body point and a single pixel point - Used in spatial orientation, e.g., upwind odor in insect flight behavior 3 Day Spontaneous Behavior in the PhenoTyper Meander Change in direction of movement relative to the distance traveled, i.e., Turn Angle corrected for distance Target Visits and Errors Specify zones as Targets or Non-Target Zone Alternation Frequency of zone visits of the selected zones consecutively Zone Transition Frequency of sequential zone visits - Transitions between zones (NOR) or Y-maze alternations Y-Maze Alternations Direction Heading - Direction of movement between frames relative to the x-axis - Used in spatial orientation, e.g., flight paths relative to wind flow Heading to Point - Direction of movement relative to a point of interest - Used to measure orientation – heading to zone (water maze or NOR) Head Direction - Angle of the "unicorn horn" relative to the x-axis - Used in orientation and searching behaviors Head Direction to Zone - Discrete state toward a zone or point - Especially designed for NOR Turn Angle - Change in heading between consecutive frames - Absolute or Relative – see Meander Angular Velocity - Change in direction of movement between two samples per unit of time, i.e., Turn Angle corrected for speed - Used to measure a response of a danio (or other fish) to a discrete stimulus Barnes Maze Activity If selected in the Experiment Settings - Percentage of pixel changes per arena Activity State Categorical variable of Activity Body Elongation If using three-point detection - Percentage of subject's detected shape - 0% is circular, 100% is a line Body Elongation State If using three-point detection – Categorical variable of Body Elongation - Stretched, Normal, and Contracted Body Angle If using three-point detection - Angle formed from the tail-center and center-nose lines Body Angle State If using three-point detection – Dichotomized variable of Body Angle Mobility Percentage of pixel changes per blob (animal) Rotation Number of turns: Clockwise or Counterclockwise - Used to measure cerebral asymmetry or amphetamine-induced rotations Fear Conditioning Acquisition - Freezing Trial Control Event The point event at which a Trial Control Event occurs Trial Control State Time interval specified by two events of the Trial Control Settings Trial Control Variable Requires the use of TC-Variables in the Trial Control Settings - Used as a counter in learning tasks (like the Progressive Ratio) or in the Cognition Wall Task Fear Conditioning – Activity After Footshock Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - QSG - Calculate The Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-qsg-calculate-the-statistics Chapter: EthoVision XT Calculate the Statistics Prepare the Tracks A track is the group of samples acquired for a subject. You can choose to smooth the tracks to get a more reliable measure of the animal's movement path and remove the effect of outliers (caused by accidental wrong detection), random noise and body wobble. - Choose Acquisition > Track Smoothing Profile. Select Open and click OK. - Select one or more of the options: Smoothing (Lowess), Minimal Distance Moved and Maximum Distance Moved. For information on the smoothing options, see Smooth the Tracks in the EthoVision XT Help. Analysis Profiles Choose Analysis > Analysis Profile. Select New, name the analysis profile and click OK. Distance moved and Velocity are predefined as dependent variables. To add a variable to the Analysis profile, click the button next to that variable. Note: If you created the experiment from a template, it contains a few analysis profiles. For example, the Morris water maze template experiment with the platform zone template contains four analysis profiles. One of them, Latency to reach platform, contains the variables for calculating the time taken to reach the platform. Basic Calculations Total Distance Moved or Average Velocity - Open the Analysis profile. - If the variable is not yet listed under Selected Dependent Variables, click the button next to Distance moved or Velocity. In the Trial Statistics tab, select Total for Distance moved, or Mean for Velocity. - Choose Analysis > Results > Statistics and Charts. Time in a Zone and Number of Zone Entries In step 2 above, click the button next to In zone. Specify the zone. In the Trial Statistics tab, select Cumulative duration and Frequency. Time Before Reaching a Zone Click the button next to In zone. Specify the zone you are interested in. In the Trial Statistics tab, select Latency to first. Distance or Velocity in a Zone - Choose Analysis > Data Profile > New or open an existing Data profile. In the Results box click Settings, then select Results per zone. Next, choose the zones you want the results for. - Open an Analysis profile. Choose the variable you want to calculate, for example, Distance moved. Next, choose Analysis > Results > Statistics and Charts. Note: EthoVision XT offers a wide range of analysis variables and methods to select data. In the results screen, the Trial Statistics tab shows the analysis results per trial, while the Group Statistics & Charts tab shows the results for all trials together, or for the groups of trials defined in your Data profile. To modify the layout of the results table, click the Layout button. To carry out multiple calculations at once with different filters, data profiles or analysis profiles, click the Batch button. Visualize the Data Track Visualization Choose Analysis > Results > Plot Tracks to view the tracks that you selected. This allows you to visually compare tracks. You can play back your tracks to see how your subjects moved. To display the entire track, under Filter deselect the Last [ ] seconds option, then click the Jump to End button in the Playback Control window. Integrated Visualization Choose Analysis > Results > Plot Integrated Data to view the track with the corresponding video (when video was recorded) and the time plot of the dependent variables (velocity, etc.). To plot a variable: - Open an Analysis profile and add the dependent variable you want to view. - Choose Analysis > Results > Plot Integrated Data. Other Analysis Options Heatmaps Choose Analysis > Results > Plot Heatmaps and click Plot Heatmaps on the toolbar. With heatmaps you get an immediate impression of which area the animal spent most time in. Select and Group Tracks Choose Analysis > Data Profile > New. To analyze some tracks, not others: - Choose one of the options under Filter. For example: - Choose Trial Name and select the trials you want to analyze. - Choose Dose (an independent variable previously defined) and choose the values of the variable you want to use. - Insert the Filter box between Start and Result 1. To analyze tracks in groups: For example, you want to compare the results for subjects treated with a drug with those for control subjects. - In the Trial List, make sure that the independent variable you want to use for grouping is defined, and that each trial is labeled with one of the possible values (e.g. Treated vs. Control). - Make a Filter for the first group based on one of the values of the independent variable, and place the resulting box between the Start and the Result 1 box. - To create the second group, click the Result button under Common elements. Click and drag from the center of the Start box to the center of the new Result box. The two boxes are now connected with an arrow. Next, make a filter for the second group, and place the Filter box in the middle of the second branch. - Choose Analysis > Results > Statistics and Charts. Click the Group Statistics and Charts tab to view the results per group. Analyze Track Segments For instance, visualize the data of the first five minutes of the tracks, or visualize all samples when the subject was moving or grooming. Choose Analysis > Data Profile > New. Nesting: To select track segments based on time, zones or states of the subject, click the appropriate button under Nesting and specify the options there. For example, to analyze the first five minutes, choose Time. Insert the Nest box between Start and Result 1. Time Bins: To analyze the tracks split in regular time intervals, in the Result box click Settings and select Results per time bin. For example, define intervals of 1 minute each. Then, choose Analysis > Results > Statistics and Charts. For more information, see Analyze Track Segments in the EthoVision XT Help. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - QSG - Detect The Subject URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-qsg-detect-the-subject Chapter: EthoVision XT Detect the Subject - Choose Setup > Detection Settings. Open the default Detection Settings 1. - If you work with video files, under Video click Select Video and choose a video file. Play the video up to when the subject appears. If you work with cameras, release the animal in the arena. - Click Automated Setup. Choose the type of subject you test, and click Next. - Wait until the subject is free from contact with objects or walls and walks with a normal posture. When ready, draw a rectangle around the subject. Do this for all subjects in the arena. Tip: For rodents, try to leave the tail out of the rectangle. In all other cases, include the animal's tail. - If the subject's body is well detected, click Yes. Otherwise, try moving the Finetune slider and check if the yellow blob covers the entire animal's body (excluding the tail). If detection does not improve, try again a few times using another image from the video. If this does not help, click No and click Advanced. For details, see Configure Detection Settings > Advanced Setup in the EthoVision XT Help. Tracking the Nose and Tail-Base In all cases, make sure that the body of the animal is well detected. If you use the Deep learning detection technique with one subject per arena, under Method click Define and select a box around the subject. Make sure that there is some space around the subject's body. Notes - Check that the subject is well detected in all parts of the arena. In the Detection Performance pane, check that the proportion of samples where the subject is not found is acceptable (for example, less than 1%). - If you selected Activity analysis in the Experiment Settings to detect freezing, click Activity. Adjust the settings until most of the purple pixels only appear when the animal moves. When the animal freezes, the number of purple pixels should be minimized. Prepare a List of Trials (Optional) The Trial List In EthoVision XT, a Trial is an uninterrupted recording session. The Trial List is a table listing the trials planned for an experiment. When you create a new experiment, a few planned trials are already present. To Add More Trials - Choose Setup > Trial List. Click the Add Trials button. - Type the number of trials you plan to carry out and click OK. - For each row: - Specify the independent variables (optional; see the next section). - Specify which video file you want to use (when tracking from video files). - Select Arena Settings, Trial Control Settings, and Detection Settings (optional). If those columns are not present in the Trial List, click the Show/Hide button, click Variables and select them. Note: Planning your trials in advance also allows you to acquire trials in batch mode. See Trial List in the EthoVision XT Help. Independent Variables Independent variables are either simple descriptive categories (such as the genotype or age of your rats or mice), or conditions manipulated by the researcher (such as the substance being tested and the dosage). You can use independent variables to create analysis groups or filter data. For example: - Compare tracks of treated subjects with tracks of control subjects. - Only analyze subjects of a specific age class. Note: If you created a template experiment, one or more independent variables have been predefined in your Trial List, for instance, Animal ID and Treatment. To Define an Independent Variable - Choose Setup > Trial List. - Click the Add Variable button. A new column appears on the right of the table. - Specify the Label (for example: Dose), Description, Type (for example, Text or Numerical), Format, Predefined values (for example, 0.01, 0.02 etc. mg/kg), and Scope (whether the values of the variable differ between subjects within the same arena, between arenas within the same trial, or between trials). Acquire the Data Methods Choose Acquisition > Open Acquisition. Locate the Acquisition Settings window at the right side of the screen. - If you track from pre-recorded video files, select Track next planned trial, click the button next to Video and open the video you want to use. - If you track from the live camera image, select Track next planned trial. Select Save video if you want to save the camera footage to a video file. For more acquisition methods, see Acquire Data in the EthoVision XT Help. Procedure for Acquiring One Trial - Under Settings, choose the Arena Settings, Trial Control Settings, and Detection Settings, if they are not already selected in the Trial List. - If you track from video and do not score behaviors manually, make sure the DDS (Detection Determines Speed) checkbox is selected in the Playback Control window. With this option you ensure that every sample is analyzed. - To start a trial, click the Start trial button in the Playback Control window. - Release the subject in the arena. - To stop the trial, click the Stop trial button. - Return the subject to its home cage or container. - Prepare the next subject, or load a new video file to acquire the next trial. More Options - You can automatically start and stop your trial depending on the behavior or position of your subject. - You can acquire data in batch mode. For details, see Batch data acquisition in the EthoVision XT Help. - You can score behaviors manually during tracking. If you saved the video during tracking, you can review the video and add or edit existing behavioral data. For details, browse the EthoVision XT Help: - To define behaviors, see Set Up an Experiment > Manual Scoring Settings. - To score behaviors, see Acquire Data > Score behaviors manually. - If no planned trial is left, click the Add Trial button in the Playback Control window. Note: Sometimes EthoVision XT tracks a reflection instead of the subject, confuses the nose-point and the tail-base, or swaps subjects when tracking multiple animals simultaneously. Whenever that occurs, you can correct those errors. For more information, see Edit the Tracks in the EthoVision XT Help. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - QSG - Export Data And Results URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-qsg-export-data-and-results Chapter: EthoVision XT Export Data And Results Main Procedure To find out if your independent variables (like treatment, dose, etc.) have a significant effect on the dependent variables, you can export your data to a statistical package. - To export the averages, totals etc. per trial, or per group of trials, choose Analysis > Export > Statistics. - To export the raw x,y coordinates and the surface area of the subject, or the per-sample values of the dependent variables, choose Analysis > Export > Raw Data. For details, see File Management > Export data in the EthoVision XT Help. Copy Entire Experiments To make a copy of an entire experiment, choose File > Make Backup. Choose the options you require and select OK. The backup file (*.evz) contains all your settings and data, and optionally media files, exported files and physiological data. You can copy this file to another computer where EthoVision XT is installed. To open the experiment on that computer, choose File > Restore Backup. Important: Backup your data to a network drive or external hard disk at least once per day. For More Information Help And Other Manuals For more details, in EthoVision XT, press F1 to open the Help. See also other manuals stored on your computer. On the Windows Start menu, choose All Apps > Noldus > EthoVision XT 18 Other Documentation. Sample Experiments Choose File > Restore Backup and browse to C:\Users\Public\Documents\Noldus\EthoVision XT\Experiments\Sample Experiments. You will find the sample experiment Morris water maze test XT180.evz. For more sample experiments, browse to my.noldus.com. Log in or register using the code that you have received. Next, choose Downloads > EthoVision XT > Sample Experiments. Each experiment focuses on a specific apparatus, or on a feature of EthoVision XT, for example, trial control. Video Tutorial Choose Help > Video Tutorial. Watch the tutorial to learn how to set up a video tracking study in EthoVision XT. There are also mini video tutorials available in several parts of the program. Click the video button on the tool bar to view the tutorials. Remote Training Courses Noldus offers training courses to help you get the most out of our software/hardware. In addition to on-site courses at your lab and in-house courses at our headquarters in Wageningen (The Netherlands) and Leesburg (VA, USA), we offer remote training courses. Remote trainings are available in the same range of languages as on-site courses. Please contact your sales representative for more information about remote trainings. Technical Support If you encounter problems, see my.noldus.com to search the support knowledgebase or contact the help desk. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - QSG - The Experiment’S Basic Properties URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-qsg-the-experiments-basic-properties Chapter: EthoVision XT The Experiment's Basic Properties Choose Setup > Experiment Settings. Specify the options listed below. Depending on your EthoVision XT license, some of the options may not be available. If you created a new template experiment, you already specified most properties of your experiment. - Video Source: Choose whether you want to track from video files or from the live camera image (Live tracking). In the latter case, select the cameras that you are going to use. If your cameras are not listed, install the camera drivers. See Camera Installation in the EthoVision XT Help. - Number of Arenas: An arena is a closed space where subjects move. Select the total number of arenas in your camera images. For example, select 1 for one water maze or open field; select 4 for four open fields, or four PhenoTyper cages. - Number of Subjects per Arena: Specify how many individuals per arena you want to track. Note: Because this guide applies to the Base version of EthoVision XT, it assumes that you track one subject per arena. - Tracked Features: Select which body points you want EthoVision XT to detect: the center-point only or the center-point with nose-point and tail-base. - Body Point Detection Technique: If you track the nose-point and the tail-base point, select which technique should be used: the contour of the subject or a trained neural network (Deep learning). The latter option only applies to rodents, and with one or two subjects per arena. - Analysis Options: With Activity analysis, you can have EthoVision XT detect behaviors like freezing in rodents and immobility in the Porsolt swim test. With Behavior recognition, EthoVision XT detects several rodent behaviors like grooming, sniffing and rearing. - Units: Select the measurement units you prefer. Draw the Arena and the Zones Tell EthoVision XT in what region in the video image the subject moves (the arena). If you created a template experiment, the arena has already been drawn in the correct shape. Change the size and/or position of the arena to match it with your video image. To Obtain a Background Image - If you use video cameras for live tracking, before starting EthoVision XT power up and connect the video camera to the PC. - In EthoVision XT, choose Setup > Arena Settings. Open the default Arena Settings 1 or create a new one. If you are doing tracking from video files, click Browse and open the video file you want to use to draw the arena. - Click Grab. If possible, do so when the arena contains no animals. To Draw an Arena - Click 1. Draw Scale to Calibrate in the Arena Settings window. - Draw a line between two points of the arena that are at a known distance from each other. In the window that appears, type in the real world distance between the two points and click OK. Optionally repeat this procedure a few times. - Click 2. Select Shape and Draw Arena in the Arena Settings window. - Click one of the drawing tools and draw the outline of the region of the video image where the animal moves. Make sure that the label Arena points to inside this region. To Draw a Zone A zone is a region within the arena that you may want to use for analysis or for starting/stopping data acquisition. If you created a template experiment, zones are already defined. Change their size and/or position to fit the arena, delete zones or draw new ones. - Click 3. Select Shape and Draw Zones in the Arena Settings window. - Select one of the drawing tools. - Draw the contour of each zone. In this example, the platform in a water maze. - Give the zone a name. Note: For more details, see Arena Settings in the EthoVision XT Help. For a DanioVision experiment, see the DanioVision DVOC-0041 - Reference Manual. Control the Start and Stop of Data Acquisition Specify the rules that control the start and stop of data acquisition. Default Settings Choose Setup > Trial Control Settings. Open the default Trial Control Settings 1. Each experiment has default Trial Control settings to start tracking when the subject is detected in the arena for one second and to stop tracking manually. If you created a template experiment, the Trial Control settings have been adjusted for that template. For instance, for the Morris water maze experiment, tracking stops either when the animal's center-point has been in the platform zone for more than five seconds, or when the animal has been swimming around for two minutes without finding the platform. To Program the Start of Tracking - In the second box, click Settings. - If you want to start tracking when the animal is in a zone, click Settings, deselect Arena and select that zone. - If necessary, change the criterion to be used (for instance, Frequency instead of Duration). To Program the Stop of Tracking - In the box immediately before Stop track, click Settings. - If you want to stop tracking after a specific time, choose After, and enter the time needed. Note: The first box, Start Trial marks the moment when you click the Start Trial button. The Start track box marks the time when EthoVision XT starts tracking. For more complex start-stop rules, like "stop when the subject is on the platform", replace the Time condition with an In zone condition, and specify the platform zone. For more examples, see Trial Control in the EthoVision XT Help. Make sure that the Trial Control Settings you want to use is selected in the Acquisition settings window before you start your data acquisition. With the Trial and Hardware Control module, you can control hardware (lights, a pellet dispenser, etc.). For instance, turn on a light when the animal enters its shelter. It also allows you to create routines, for example in conditioning experiments. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - QSG - Version 18.0 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-qsg-version-180 Chapter: EthoVision XT Install EthoVision XT - Browse to https://my.noldus.com. - Log in or register using the registration code on your welcome letter. - Click Downloads, then EthoVision XT. Under Versions, download the EthoVision XT 18 - Installation Package [version number] zip file. - Unzip the file and save the content to your PC. - Double-click the file EthoVision XT - Setup - [version number].exe. - Under Set Application Language, select either English (United States) or Chinese (Simplified). Under Installation type, select Standard. Notes - You can also change the language at any time in EthoVision XT. Choose File > Preferences > Language, then close and restart EthoVision XT. - If you want to use video cameras with EthoVision XT, first install the appropriate camera interface boards and drivers on the EthoVision XT computer. For details, see Camera Installation in the EthoVision XT Help. To open the Help, press F1 in the software. - If you save the installation files on a network drive before installation, copy them to your PC before running the Setup file. Make sure that all files included in the installation zip file are copied to your PC. Activate Your License With a USB Hardware Key If you have a hardware key, insert it into a USB port of the computer and start EthoVision XT. If you upgrade your EthoVision XT license, start EthoVision XT and enter the Upgrade key in the window that opens. With a Software License Key If you received a software license key, start EthoVision XT and activate your license. Choose between a Floating license or a Computer-locked license. - Floating — The license can be used on different computers, though not simultaneously. Choose this solution if you want to be flexible on which computer you use EthoVision XT to acquire data, and your computers are connected to the internet. - Computer-locked — The license is linked to one specific computer. To activate your license, that computer must have an internet connection, or you must have a smartphone with an internet connection. If you want to use EthoVision XT on a second PC to analyze existing data, not acquire new data, you can run it on that PC in Analysis mode, which does not require a license. Your First EthoVision XT Experiment Create an Experiment EthoVision XT creates an experiment based on the choices you make in the following guided procedure. For example, the type and color of the animals, the test enclosure, etc. - In the EthoVision XT Startup window, under New experiment, click New from template or choose File > New from Template. - Select Apply a pre-defined template and follow the instructions in the setup guide. Choose whether you track from video files or live, select the study species, the type of arena, etc. - In the New Experiment window, enter a Name for your experiment. - Browse to the Location in which you want to store your experiment. Then click OK. - You are now ready to complete setting up your experiment. You must complete the arena set-up and adjust the Detection Settings. You can optionally make a Trial List, Trial Control Settings, and Manual Scoring Settings. Notes - If your test setup is not among those included in the template list, choose File > New. This way you create an experiment without predefined settings. - If you work with the DanioVision Observation Chamber, see the DanioVision DVOC-0041 - Reference Manual. Working with EthoVision XT Experiments An EthoVision XT experiment is the container of all information related to an experimental setup. The Experiment Explorer lists all components of the experiment currently open. By default, your experiment is located in: C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments\ All experiment files are stored in a folder with the same name as the experiment. Note: Settings and Profiles are collections of settings that belong to a specific function, for example the arena. You can define multiple settings and later choose which to use for a specific trial or group of trials. For example, in a water maze experiment, for a first set of trials, use Arena Settings 1 with the platform defined in a specific quadrant. For another set of trials, use Arena Settings 2 where the platform is defined in a different quadrant. Important Experiment Components - Experiment Settings — Basic properties that do not change throughout the experiment. - Arena Settings — Draw the arena and zones. - Detection Settings — Detect the subject in your camera image. - Acquisition — Record data and video. - Data Profiles — Select which part of your data to analyze. - Analysis Profiles — Specify output variables (distance, speed, etc.). - Results — Results options. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - Setting Up Your First Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-setting-up-your-first-experiment Chapter: EthoVision XT Your First EthoVision XT Experiment Create An Experiment EthoVision XT creates an experiment based on the choices you make in the following guided procedure. For example, the type and color of the animals, the test enclosure, etc. 1. In the EthoVision XT Startup window, under New experiment, click New from template or choose File > New from Template. 2. Select Apply a pre-defined template and follow the instructions in the setup guide. Choose whether you track from video files or live, select the study species, the type of arena, etc. 3. In the New Experiment window, enter a Name for your experiment. 4. Browse to the Location in which you want to store your experiment. Then click OK. 5. You are now ready to complete setting up your experiment. You must complete the arena set-up and adjust the Detection Settings. You can optionally make a Trial List, Trial Control Settings, and Manual Scoring Settings. Notes If your test setup is not among those included in the template list, choose File > New. This way you create an experiment without predefined settings. If you work with the DanioVision Observation Chamber, see the DanioVision DVOC-0041 - Reference Manual. Your first EthoVision XT experiment Working With Ethovision Xt Experiments An EthoVision XT experiment is the container of all information related to an experimental setup. The Experiment Explorer (Figure 1, left) lists all components of the experiment currently open. By default, your experiment is located in: C:\Users\Public\Public Documents\Noldus\EthoVision XT\ Experiments\ All experiment files are stored in a folder with the same name as the experiment. note Settings and Profiles are collections of settings that belong to a specific function, for example the arena. You can define multiple settings and later choose which to use for a specific trial or group of trials. For example, in a water maze experiment, for a first set of trials, use Arena Settings 1 with the platform defined in a specific quadrant. For another set of trials, use Arena Settings 2 where the platform is defined in different quadrant. Figure 1 Important components in your experiment: 1. Experiment Settings (basic properties that do not change throughout the experiment). 2. Arena Settings to draw the arena and zones. 3. Detection Settings to detect the subject in your camera image. 4. Acquisition to record data and video. 5. Data Profiles to select which part of your data to analyze. 6. Analysis profiles to specify output variables (distance, speed etc.). 7. Results options. The experiment's basic properties The Experiment's Basic Properties Choose Setup > Experiment Settings. Specify the options listed below. Depending on your EthoVision XT license, some of the options may not be available. If you created a new template experiment, you already specified most properties of your experiment. Video Source Choose whether you want to track From video files or from the live camera image (Live tracking). In the latter case, select the cameras that you are going to use. If your cameras are not listed, install the camera drivers. See Camera Installation in the EthoVision XT Help. Number of Arenas An arena is a closed space where subjects move. Select the total number of arenas in your camera images. For example, select 1 for one water maze or open field; select 4 for four open fields, or four PhenoTyper cages. Number of Subjects per Arena Specify how many individuals per arena you want to track. Note: Because this guide applies to the Base version of EthoVision XT, it assumes that you track one subject per arena. Tracked Features Select which body points you want EthoVision XT to detect: the center-point only or the center-point with nose-point and tail-base. Body Point Detection Technique If you track the nose-point and the tail-base point, select which technique should be used: the contour of the subject or a trained neural network (Deep learning). The latter option only applies to rodents, and with one or two subjects per arena. Analysis Options With Activity analysis, you can have EthoVision XT detect behaviors like freezing in rodents and immobility in the Porsolt swim test. With Behavior recognition, EthoVision XT detects several rodent behaviors like grooming, sniffing and rearing. Units Select the measurement units you prefer. Draw the arena and the zones Draw The Arena And The Zones Tell EthoVision XT in what region in the video image the subject moves (the arena). If you created a template experiment, the arena has already been drawn in the correct shape. Change the size and/or position of the arena to match it with your video image. To obtain a background image - If you use video cameras for live tracking, before starting EthoVision XT power up and connect the video camera to the PC. - In EthoVision XT, choose Setup > Arena Settings. Open the default Arena Settings 1 or create a new one. If you do tracking from video files, click Browse and open the video file you want to use to draw the arena. - Click Grab. If possible, do so when the arena contains no animals. To draw an arena - Click 1. Draw Scale to Calibrate in the Arena Settings window. - Draw a line between two points of the arena that are at a known distance from each other. In the window that appears, type in the real world distance between the two points and click OK. Optionally repeat this procedure a few times. Draw the arena and the zones - Click 2. Select Shape and Draw Arena in the Arena Settings window. - Click one of the drawing tools and draw the outline of the region of the video image where the animal moves. Make sure that the label Arena points to inside this region. To draw a zone A zone is a region within the arena that you may want to use for analysis or for starting/ stopping data acquisition. If you created a template experiment, zones are already defined. Change their size and/or position to fit the arena, delete zones or draw new ones. 1. Click 3. Select Shape and Draw Zones in the Arena Settings window. 2. Select one of the drawing tools. 3. Draw the contour of each zone. In this example, the platform in a water maze. 4. Give the zone a name. Notes For more details, see Arena Settings in the EthoVision XT Help. For a DanioVision experiment, see the DanioVision DVOC-0041 - Reference Manual. Control the start and stop of data acquisition Source: EthoVision XT 18 - Quick Start Guide --- ## EthoVision XT 18 - Software License Key (SBLK) Activation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-software-license-key-sblk-activation Chapter: EthoVision XT EthoVision XT 18 – Activating your Software Based License Software-based licenses can be activated as either FIXED or FLOATING. For more information on the differences between Fixed and Floating, see the License Management section below. EthoVision licenses have a variety of modules (multiple arenas, multiple body points, etc.). Some licenses in the lab might not contain any modules (known as a base license, 1 animal in 1 arena) while other licenses could have all the modules (known as a core license). When the modules vary from license to license this results in a new activation key for each module variation. For example, if you have a base license and a core license, you will be sent 2 Activation Keys. When you have multiple licenses with the same modules, these can all reside under the same Activation Key, which has multiple Seats. You can fix or float any Software Based License, regardless of how many Activation Keys or Seats you have. Activation Activating as Fixed PC Has Internet Connection - Download and install EthoVision XT 18 (see Installing EthoVision XT 18 below). - Launch EthoVision XT 18. - Select Use the software activation key. - Select Computer-locked license – Online Activation. - Enter the provided Activation Key. - You are now ready to use EthoVision XT 18. The PC can be online or offline during use of EthoVision XT 18. PC Has No Internet Connection - Download and install EthoVision XT 18 (see Installing EthoVision XT 18 below). - Launch EthoVision XT 18. - Select Use the software activation key. - Select Computer-locked license – Offline Activation. - Enter the provided Activation Key. - Scan the QR code using the camera of your smartphone to get a Computer Key. - Under Activate Offline, enter the Computer Key. - You are now ready to use EthoVision XT 18. The PC can be online or offline during use of EthoVision XT 18. Activating as Floating PC Requires Internet - Download and install EthoVision XT 18 (see Installing EthoVision XT 18 below). - Launch EthoVision XT 18. - Select Activate software license key. - Select Floating – On multiple computers. - Enter the provided Activation Key. - You are now ready to use EthoVision XT 18. The PC must be online during use of EthoVision XT 18. Installing EthoVision XT 18 The installation files for version 18 can be found on your MyNoldus account. - Log in or create a new account. - Go to: Downloads > EthoVision XT > Versions > Current Version > Download. - In File Explorer, locate the downloaded ZIP file, right-click it, and select Extract All > Extract. - In the unzipped folder, locate and double-click EthoVision XT – Setup – 18.XXXX.exe to install. License Management Permissions When activated as a Fixed license via the internet (online), it will check the license server for permission, after which it will lock the license to that specific PC for use for 90 days. After 90 days, the license checks the server for permission again. When activated as a Fixed license without an internet connection (offline), it will check the license server for permission, after which it will lock the license to that specific PC for use for 365 days. After 365 days, the license will require a reactivation to confirm permission for another year of use. Since EthoVision XT setups are oftentimes stationary and offline, we recommend the Fixed – Offline Activation option. When activated as a Floating license, permission is shared. Internet access is required each time a PC wants to utilize the full version of the software (i.e., acquire data), as it uses the internet to check for license permission. Access to the Key/Seat will be on a first come, first served basis. You can switch between fixed and floating activations by deactivating via Help > Deactivate License. See the Deactivation section below for more information. When a license is deactivated, it is immediately available to fix or float on another PC. EthoVision licenses have a variety of modules (multiple arenas, multiple body points, etc.). Some licenses in the lab might not contain any modules (known as a base license, 1 animal in 1 arena) while other licenses could have all the modules (known as a core license). When the modules vary from license to license this results in a new activation key for each module variation. For example, if you have a base license and a core license, you will be sent 2 Activation Keys. When you have multiple licenses with the same modules, these can all reside under the same Activation Key, which has multiple Seats. You can fix or float any Software Based License, regardless of how many Activation Keys or Seats you have. Fixed License A fixed license is used on a single computer. An internet connection is required during activation but not during use of EthoVision XT 18. Once a license is activated as Fixed it takes up a Seat permanently. If you receive an error indicating the license is already active on another PC, it will need to be deactivated on that PC first. Floating License A floating license (with 1 or more Seats) can be accessed on multiple computers. A permanent internet connection is required. You can install EthoVision XT 18 on as many PCs as you would like, but only the number of Seats purchased can be used simultaneously at any given time. Users must close EthoVision XT 18 after use. This will free up a Seat so another user can use the software on another computer. You do not need to deactivate a license after it has been used. Simply close EthoVision XT 18 to free up the Seat. A shared online calendar, spreadsheet, or schedule can be useful for the following: - Keep track of who is using EthoVision XT 18 and when, so you know who last used it should you need to ask them to close EthoVision XT 18 to free up a Seat. - Keep a list of all PC names (company and private) which have EthoVision XT 18 installed. - For each Activation Key, note whether it is set to Fixed or Floating. If you have trouble accessing the license due to a strict local network, ask your IT department to add an exception for: https://qlmlicenses.noldus.com:9999 Deactivation To deactivate your license, go to Help > Deactivate License within EthoVision XT 18. When a license is deactivated, it is immediately available to fix or float on another PC. If you run into any issues, please submit a support ticket on the MyNoldus website. Source: EthoVision XT 18 - Software License Key (SBLK) Activation --- ## EthoVision XT 18 - Technical Specs Rodent URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-technical-specs-rodent Chapter: EthoVision XT System Configurations EthoVision® XT Base allows you to perform complete tests with one animal in one arena. You can extend the functionality with one or more of the eight available modules: - Mouse Behavior Recognition Module – Automatically detect ten mouse behaviors such as grooming, rearing, and digging. - Rat Behavior Recognition Module – Automatically detect ten rat behaviors such as grooming, rearing, and sniffing. - External Data Module – Integrate EthoVision XT data with co-acquired external data. - Multiple Arenas Module – Track animals in up to a hundred arenas simultaneously. - Social Interaction Module – Track multiple animals within each arena. - Trial & Hardware Control Module – Create complete test protocols to initiate and control interaction with external equipment, based on real-time analysis of the animal's behavior. - Quality Assurance Module – Assign different rights to different users and comply with Good Laboratory Practice guidelines. Data Management 1. Setup Template Experiments EthoVision XT contains a user-guided set-up with templates for several test paradigms. At the start of the program you can either start a brand-new experiment, re-use the settings from a previous experiment, or use the user-guided set-up to open an experiment template suited to a specific test (water maze, plus maze, etc.). With these templates, many basic settings are pre-set, such as arena definition, detection settings, and parameters for analysis. You can fine-tune these settings to fit your specific needs. DanioVision Experiments If you use the DanioVision system for multi-well plates you can select the DanioVision experiment option which optimizes the arena settings and detection settings for zebrafish larvae in well plates. Live Mouse Tracker Experiments If you use the Live Mouse Tracker acquisition system and want to analyze these data in EthoVision XT you can select the Live Mouse Tracker experiment option when creating a new experiment. This creates a modified version of a standard, multi-subject, multi-body point experiment, with predefined, permanent settings for Live Mouse Tracker. Good Laboratory Practice For those conducting Quality Assurance experiments, particularly in environments adhering to Good Laboratory Practice (GLP) standards, EthoVision XT offers specialized options to meet these rigorous requirements. This ensures that your experiments not only yield reliable data but also comply with industry standards for quality and reproducibility. Flexibility For researchers seeking maximum flexibility in their experimental design, the "New from Scratch" option allows for complete customization of the experiment setup. This feature is ideal for innovative research that goes beyond standard protocols, offering the freedom to tailor every aspect of the experiment to unique research needs. Experiment Options - Tracking can be done live or from a video file. - You can use digital cameras or analog cameras (but not a combination of the two). - You can connect external data acquisition systems to EthoVision XT. - Track in one or multiple arenas, with a maximum of 100 arenas. - Track one or multiple subjects per arena, with a maximum of 16 subject roles. - For mice, rats, and zebrafish you can use center point tracking, or center of gravity, nose, and tail base. For mice and rats you have the option between a contour-based technique or a deep learning based technique. You can also track based on color or color marker. - Activity analysis – a non-tracking option analyzing overall activity per arena based on pixel changes. This is very useful for freezing detection. - Distance can be measured in millimeters, centimeters, meters, or inches. - Time can be measured in milliseconds, seconds, minutes, or hours. - Rotation can be measured in degrees, radians, gradians, or rotations. Manual Scoring The Manual Event Recorder is a built-in coding system which allows you to define a list of behaviors that you can score manually during and after data acquisition (live or offline). - Score live. - Score (also) offline, to score at a lower or faster playback speed. You can also edit scored events. Types of behaviors: - Start-Stop Behaviors – behaviors that are independent from each other. - Point Events – behaviors without a duration. - Mutually Exclusive Behaviors – behaviors grouped in such a way that activating one behavior automatically stops the other behavior. You can define different behaviors and score those categories with keyboard keys or with the mouse. Without key codes defined, you can manually score events using the mouse. Arena Settings The arena is the region in the video image where the animal is tracked. You can define: - The arena(s). - Subdivisions of the arena (zones). - Cumulative zones (define individual smaller zones to be taken into account for cumulative analysis). - Hidden zones (used for shelters) and entry zones to analyze entries and exits. - Zones organized in layers, so you can define and analyze zones that overlap. - Points of interest. You can define an unlimited number of zones in an arena and create zones of any shape. Calibration of your arena will allow EthoVision XT to calculate parameters such as velocity and distances to certain points. If you are tracking in multiple arenas, you can copy and paste the settings from one arena to the other. Multiple Arena Definition When your experiment contains multiple arenas – for instance a group of open fields or home cages – you can use the multiple arena set-up functionality. This means that you do not need to draw each arena separately. EthoVision XT allows you to easily rotate, scale, transpose, resize, and reposition the series of arenas simultaneously. In DanioVision experiments, automated arena detection detects the individual wells in standardized well-plates automatically. Arena and Zone Auto-Subdivision This option allows the automated subdivision of circular and rectangular arenas into multiple equal zones, including auto-labeling of these subdivisions. For example, it can be used to divide a water maze into quadrants, simplifying the process of analyzing behavior across different sections of the arena. Multi-Camera Set-Up In EthoVision XT you can combine the input of multiple cameras. This way you can track from multiple arenas (in combination with the Multiple Arenas Module) without the need to place them all under one camera. Trial Control Options You can program EthoVision XT to automatically start and stop tracking, based on any of the parameters offered by EthoVision XT. This feature also includes an external command option, which allows you to start another computer program when a condition becomes true. For example, present a visual stimulus on a computer screen or play a sound file when the animal enters a particular zone. With the additional Trial & Hardware Control Module, you can define complete test protocols to initiate and control interactions between your animals and external sensor and stimuli devices. Real-time analysis of any of the parameters of EthoVision XT allows you to control complete test protocols based on your animal's behavior. You can use it for complex learning tasks such as the radial arm maze with automatically controlled doors and food delivery using pellet dispensers. All standard TTL-based hardware can be attached and controlled. If you are using multiple arenas, conditions are applied to each arena individually. Tracking Methods for One Animal Per Arena (Body Point Estimate) The tracking method specifies how the body points are estimated once the subject is detected. Depending on how many subjects and body points you specify in the Experiment Settings, one or more methods for tracking of body points are available in the Method section of the Advanced Detection Settings. Deep Learning Based Body Point Detection Technique When using this technique, a new algorithm based on a convolutional neural network finds the nose and tail-base points of rodents with high accuracy and few or no nose-tail swaps. The network was trained to extract features from video images of rodents of various colors and in various backgrounds, with videos in which the nose and the tail-base were annotated. During tracking, the network analyzes a portion of the image that includes the detected subject. It creates a map of probability of occurrence for both the nose and tail-base points, and finally makes an estimate of the position of the nose point and the tail-base point based on the highest probability. Contour-Based Body Point Detection Technique - Any Species – Default – This detection method analyzes the contour of the area detected as subject at each sample to assign the nose point and tail base. Make sure in the detection settings that the tail is fully detected. With this method it may be possible to track non-rodent shapes but the method is not designed for it. This method is automatically activated when you track the center point in one animal per arena and you specified Other Species in the automated setup. - Rodents – Default – This detection method analyzes the varying shape of the contour of the area detected as subject and builds up a rodent model. It is more robust than the shape-based method because it does not require the nose and tail to be visible: it can predict the position of the nose and the tail based on previous samples. Make sure in the detection settings that the tail is removed from the body contour with Erode and Dilate. Choose this method when you want to track a single rodent without occlusions or without difficult tracking conditions. - Rodents – For Occlusions – This method can handle severe shape distortions, for example when the animal's body is occluded or when multiple animals touch. However, it requires a lot of computer performance. Choose this method for rodents in a social interaction context, or when you track rodents that can be occluded, for example by bars or other objects in the cage. Make sure in the detection settings that the tail is removed from the body contour with Erode and Dilate. - Other Species – For Occlusions – This method does not make any assumption about the shape of the subject. Choose this method to track, for example, insects, crustaceans, and large animals. Also use this method if you track fish from the side view of the water tank and the Adult Fish method does not give good results. However, with this method you only track the center point. Contour adjustments can be made in one of two ways or by combining both methods: - Erosion – decreases the animal's surface area by 1–10 pixels. - Dilation – increases the animal's surface area by 1–10 pixels. Besides the above-mentioned options to optimize the detection and identification of subjects, contrast settings can be fine-tuned, subject size can be defined, and video smoothing can be applied. There are also some additional detection settings specific for when you are using the Rat or Mouse Behavior Recognition Module. Tracking Methods for Multiple Subjects Per Arena Color marker tracking uses the color marker itself to track the subject and identify it. Contour-based body point detection offers two options: - Center of gravity tracking only. - Center of gravity, nose point, and tail-base tracking. In this case two subject identification methods are available: - Marker-Assisted Identification – Identities are distinguished based on a color marker. - Unmarked Subjects – Identities may switch. Source: Technical Specs - EVXT 18 - Rodents, Noldus Information Technology --- ## EthoVision XT 18 - Technical Specs Zebrafish URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-technical-specs-zebrafish Chapter: EthoVision XT System Configurations EthoVision® XT Base allows you to perform complete tests with one animal in one arena. You can extend the functionality with one or more of the eight available modules: - External Data Module – Integrate EthoVision XT data with co-acquired external data. - Multiple Arenas Module – Track animals in up to a hundred arenas simultaneously. - Social Interaction Module – Track multiple animals within each arena. - Trial & Hardware Control Module – Create complete test protocols to initiate and control interaction with external equipment, based on real-time analysis of the animal's behavior. - Quality Assurance Module – Assign different rights to different users and comply with Good Laboratory Practice guidelines. - Track3D – Record movement of an animal in a test chamber (such as a wind tunnel or swim tank), visualize the trajectory in a three-dimensional image, and calculate a number of movement parameters. Data Management 1. Setup Template Experiments EthoVision XT contains a user-guided set-up with templates for several test paradigms. At the start of the program you can either start a brand-new experiment, re-use the settings from a previous experiment, or use the user-guided set-up to open an experiment template suited to a specific test (water maze, plus maze, 96-well plate, etc.). With these templates, many basic settings are pre-set, such as arena definition, detection settings, and parameters for analysis. You can fine-tune these settings to fit your specific needs. DanioVision Experiments If you use DanioVision™, a system specifically designed for observing and analyzing zebrafish larvae behavior, you can select the DanioVision experiment option when creating a new experiment. Furthermore, the automated arena detection detects individual wells in standardized well-plates automatically and the automated detection settings detect the subjects — for example, zebrafish larvae — and optimize detection with a few mouse clicks. Good Laboratory Practice Additionally, for those conducting Quality Assurance experiments, particularly in environments adhering to Good Laboratory Practice (GLP) standards, EthoVision XT offers specialized options to meet these rigorous requirements. This ensures that your experiments not only yield reliable data but also comply with industry standards for quality and reproducibility. Flexibility For researchers seeking maximum flexibility in their experimental design, the "New from Scratch" option allows for complete customization of the experiment setup. This feature is ideal for innovative research that goes beyond standard protocols, offering the freedom to tailor every aspect of the experiment to unique research needs. Experiment Options - Tracking can be done live or from a video file. - You can use digital cameras or analog cameras (but not a combination of the two). - You can connect external data acquisition systems to EthoVision XT.1 - Track in one or multiple arenas, with a maximum of 99 arenas.2 - Track one or multiple subjects per arena, with a maximum of 16 subject roles.2 - For mice, rats, and zebrafish you can use center point tracking, or center of gravity, nose, and tail base. For mice and rats you have the option between a contour-based technique or a deep learning based technique. You can also track based on color or color marker.2 - Activity analysis – a non-tracking option analyzing overall activity per arena based on pixel changes. This is very useful for freezing detection. - Distance can be measured in millimeters, centimeters, meters, or inches. - Time can be measured in milliseconds, seconds, minutes, or hours. - Rotation can be measured in degrees, radians, gradians, or rotations. Manual Scoring The Manual Event Recorder is a built-in coding system which allows you to define a list of behaviors that you can score manually during and after data acquisition (live or offline). - Score live. - Score (also) offline, to score at a lower or faster playback speed. You can also edit scored events. Different types of behaviors: - Start-Stop Behaviors – Behaviors that are independent from each other. - Point Events – Behaviors without a duration. - Mutually Exclusive Behaviors – Behaviors grouped in such a way that activating one behavior automatically stops the other behavior. You can define different behaviors using the keys from the computer keyboard. Without key codes defined, you can manually score events using the mouse. Arena Settings The arena is the region in the video image where the animal is tracked. You can define: - The arena(s). - Subdivisions of the arena (zones). - Cumulative zones (define individual smaller zones to be taken into account for cumulative analysis). - Hidden zones (used for shelters) and entry zones to analyze entries and exits. - Zones organized in layers, so you can define and analyze zones that overlap. - Points of interest. You can define an unlimited number of zones in an arena, and create zones of any shape. Calibration of your arena will allow EthoVision XT to calculate parameters such as velocity and distances to certain points. If you are tracking in multiple arenas, you can copy and paste the settings from one arena to the other. Multiple Arena Definition When your experiment contains multiple arenas — for instance using a multi-well plate or a group of open fields or home cages — you can use the multiple arena set-up functionality. This means that you do not need to draw each arena separately. EthoVision XT allows you to easily rotate, scale, transpose, resize, and reposition the series of arenas simultaneously. In DanioVision experiments, automated arena detection detects the individual wells in standardized well-plates automatically. Arena/Zone Auto-Subdivision This option allows the automated subdivision of circular and rectangular arenas into multiple equal zones. It includes auto-labeling of the subdivisions. Multi-Camera Set-Up In EthoVision XT you can combine the input of multiple cameras. This way you can track from multiple arenas (in combination with the Multiple Arenas Module) without the need to place them all under one camera. Trial Control Options You can program EthoVision XT to automatically start and stop tracking, based on any of the parameters offered by EthoVision XT. This feature also includes an external command option, which allows you to start another computer program when a condition becomes true. For example, present a visual stimulus on a computer screen or play a sound file when the animal enters a particular zone. Detection Settings Besides the options mentioned above to optimize the detection and identification of the subject(s), contrast settings can be fine-tuned, subject size can be defined, and video smoothing can be applied. There are also some additional detection settings specific to when you are using the Rat or Mouse Behavior Recognition Module. EthoVision XT offers four different detection methods: - DanioVision – For DanioVision, the detection method is chosen automatically. It provides great ease to set as a method because it is tailored specifically to larvae. - Gray Scaling – Defines all connecting pixels with a gray value between two threshold values as a possible object. - Static Subtraction – Looks at differences between pixels in a reference image (without the animal) and the current video image (with the animal in the arena). - Dynamic Subtraction – Like the previous method, looks at differences between a reference image and the current image, while updating the reference image at each sample. - Differencing – Makes a statistical comparison between pixels in a reference image and the current image. The statistical comparison uses the variance in contrast between the current and reference image and determines whether each pixel has changed enough to be considered part of the subject. Tracking Methods (Body Point Estimate) The tracking method specifies how the body points are estimated once the subject is detected. Depending on how many subjects and body points you specify in the Experiment Settings, one or more methods for tracking of body points are available in the Method section of the Advanced Detection Settings. Contour-Based Body Point Detection Technique: - Any Species – Default – This detection method analyzes the contour of the area detected as subject at each sample to assign the nose-point and tail-base. Make sure in the detection settings that the tail is fully detected. With this method it may be possible to track non-rodent shapes, but the method is not designed for it. This method is automatically activated when you track the center-point in one animal per arena and you specified Other Species in the Automated Setup. - Adult Fish – For Occlusions – Use this method to track zebrafish and other fish of similar shape, when viewed from above. Make sure that the whole body of the fish is detected, including the tail. - All Species – For Occlusions – This method does not make any assumption about the shape of the subject. Choose this method to track, for example, insects, crustaceans, and large animals. Also use this method if you track fish from the side view of the water tank and the Adult Fish method does not give good results. However, with this method you only track the center point. Contour adjustments can be made in one of two ways or by combining both methods: - Erosion – Decreases the animal's surface area by 1–10 pixels. - Dilation – Increases the animal's surface area by 1–10 pixels. Trial List The trial list consists of trials that are planned, carried out, or skipped, including system variables and user-defined independent variables. All are organized in a cross table and data can be copied to and from Excel sheets. In EthoVision XT you can schedule a list of trials based on pre-recorded video files. This list can be automatically acquired as a batch in data acquisition. The trial list also allows you to import trials from previously acquired experiments, with the aim of analyzing data collected in two or more identical experiments as one data set. 2. Data Acquisition EthoVision XT offers the following acquisition methods: - Acquire Data Live – Live tracking requires no disk space for video storage, but creates no video backup either. The maximum trial duration without video recording (as tested) is 72 hours. - Acquire Data Live and Record Video – Live tracking while EthoVision XT records a backup video to an MPEG4 video file. The maximum trial duration with video recording (as tested) is 72 hours depending on the hardware used. - Longer Trials – To acquire trials longer than mentioned above, you can split your multi-day testing into multiple trials. - Record Video and Acquire Data – EthoVision XT records a video to an MPEG4 file which you can use for data acquisition later. This method is recommended if the computer is not fast enough for live data acquisition. With the additional module for Trial & Hardware Control, you can define complete test protocols to initiate and control interactions between your animals and external sensor and stimuli devices. Real-time analysis of any of the parameters of EthoVision XT allows you to control complete test protocols based on your animal's behavior. You can use it for complex learning tasks such as the radial arm maze with automatically controlled doors and food delivery using pellet dispensers. Attach and control all standard (TTL-based) hardware. If you are using multiple arenas, conditions are applied to each arena individually. 1 Only available with the Physiology Integration Module. 2 Depending on whether you are using one of the modules. Source: Technical Specs - EVXT 18 - Zebrafish, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - 10 User-Defined Device Types URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-10-user-defined-device-types Chapter: EthoVision XT User-Defined Device Types Device types like the PhenoTyper's Top Unit Interface, the Lickometer and the Pellet Dispenser are pre-defined in EthoVision XT as default device types, so when you use such devices you do not have to define their properties at every new experiment. In the case you want to use a new device type or a device with parameters different from those set in Noldus devices, you can create a User-defined device type. For example: - You want to sample the Lickometer at a rate different from the default one, that is one sample every two seconds. To do so, create a new Lickometer device type, where the only difference between the existing Lickometer and the new device type is the value for the sampling interval. - Add a "Trapdoor" device type by duplicating the existing Custom Device, and by replacing the various command- and signal texts. For instance: replace Output 1 High with Door 1 open. This section instructs how to make simple changes to an existing device. For more complex changes, the Noldus HardwareInterface USB-IO box software and maybe even EthoVision XT itself may need to be changed. Contact Noldus Technical Support for wishes and ideas. In order to carry out the procedure below, you need some experience with computers and XML language. In a Nutshell When you install EthoVision XT, the following file DeviceTypesNoldus.xml is copied to the following folders (henceforth named ProgramData folder): - C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface Iobox\{version number} - C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface MiniIobox\{version number} Two files are present in this folder: - DeviceTypesNoldusChCh.xml — used with the Chinese version of EthoVision XT - DeviceTypesNoldusEnUs.xml — used with the English version The XML file contains all the details of the types of hardware devices that you can control with EthoVision XT with the USB-IO box and the Mini USB-IO box. You can edit this file for small changes in the hardware devices, for example if you want to change the frequency a PhenoWheel counter is read out. You can also define custom devices and create a file DeviceTypesUser.xml. If you do so, make sure the file DeviceTypesUser.xml and DeviceTypesNoldus[language version].xml do not contain settings for the same device. When you create an experiment, EthoVision XT copies these files to your experiment folder, under Configuration Files\Add-ins\Hardware\{dll serial number}. The dll serial number depends on the type of USB-IO box and its version. See Table 3.1 for which serial number belongs to which device and version. Tip: To find out which version of the driver is installed on your computer, see the Programs and Features list in the Control Panel. Every time that you open the experiment, EthoVision XT reads the files in the experiment folder, not the ones in the ProgramData folder, and does not change them. Therefore: - If you edit the files in the ProgramData folder, the new device types will be available to all your new experiments. - If you edit the files in a specific experiment folder, the new device types will only be available to that experiment. When you make a backup of the experiment, the device type files are also copied, so the new devices can be recognized on other computers where you restore the experiment from the backup. Important: Always make a backup of the ProgramData folder before you edit the file DeviceTypesNoldus[language version].xml. DLL Serial Numbers The following table lists the dll serial numbers for the different versions of the USB-IO box and the Mini USB-IO box. Serial Number — USB-IO Box Serial Number — Mini USB-IO Box {A8DA8F3E-7EA3-4629-8327-9D21C90FB3ED} {0308106B-1EBE-4620-B00D-396ABEBBC219} {33DF79E0-53C2-44C6-BA2F-A24C4C702615} {F9AAD805-B910-4FEC-AC2F-31DED85324B2} {C183DC50-0CAB-4E67-905E-9D45D8213BD2} {B1336ED5-DE91-4C40-A59D-6A2D131C4F9B} {DF396575-4883-47C4-9124-8DE30AE1E4C6} {2EDFF151-DF50-486E-887F-55AD41457A5B} {83BF6F4E-D35B-489A-9F5E-703C4EE9453B} {93C9527C-8B2F-4530-9370-7CA330856D15} Undo the Changes in the Device Type Files If you want to undo the changes made and return to the original situation, proceed as follows: - Close EthoVision XT. - Remove or rename the file DeviceTypesUser.xml in the ProgramData folder. - Copy the files from the backup of the ProgramData folder to the ProgramData folder. - Optional: Run installation of EthoVision XT and select Repair. Browse to my.noldus.com if you need to download the EthoVision XT installation files. Any experiments that you have created which refer to the user devices can still be analyzed and continued. To remove every trace of your user devices, you must also delete these experiments (and if you made experiment backups, delete these too) by removing them from the Experiments folder. Define a New Device Type Important: Before making changes to files in the ProgramData folder, make a backup of this folder, so you can recover the files if anything goes wrong. The ProgramData folder contains other information important to EthoVision XT. If the files in this folder get corrupted or deleted, you can restore EthoVision XT by re-running installation of EthoVision XT and selecting Repair. To define a new device type: - Make the necessary changes to the DeviceTypesUser.xml file in the ProgramData folder as described below. Use the program XML Notepad, which you can download from www.microsoft.com/downloads, to edit a device type file. Other editors could add undesired characters that may not be read in EthoVision XT. - For changes to standard Noldus device types, edit the file DeviceTypesUser.xml. Note: You can in fact make the changes to the file DeviceTypesNoldus[language version].xml, but these changes will be overwritten when EthoVision XT is subsequently re-installed, repaired, or a new version is installed. - For all other types, also edit the file DeviceTypesUser.xml. - Make sure that the file DeviceTypesUser.xml is stored in the appropriate folder: - C:\ProgramData\Noldus\Components\EthoVision\Noldus HardwareInterface Iobox\5 - C:\ProgramData\Noldus\Components\EthoVision\Noldus HardwareInterface Mini Iobox\5 - Start EthoVision XT, create a new experiment, and test the devices. - If EthoVision XT crashes or does not behave as expected: - Delete the created (failed) experiments. - Review and correct your changes to the DeviceTypesUser.xml file before retrying. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - 10 User-Defined Device Types (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-10-user-defined-device-types-continued Chapter: EthoVision XT User-Defined Device Types (Continued) Make corrections to the file DeviceTypesUser.xml in the ProgramData folder specified above. Go to step c. - When everything works fine, create a new experiment and use the changed or new device types. Note: If you use the Quality Assurance module: The change to the device type file is not recorded in the GLP log. Sample File On the download page of EthoVision XT you can download two sample files. - Browse to my.noldus.com (you must log in or register first to access this site). - Choose Downloads > EthoVision XT. Download EthoVision XT - Full installation disc [version number]. Unzip the file and locate the folder Drivers and Tools > IoBox MiniIoBox Devices. There you find the file User defined device types.zip. - Unzip the file User defined device types.zip and save the files on your computer: - DeviceTypesUser - Example.xml (see below) - DeviceTypesUser Pheno Wheel (30).xml DeviceTypesUser - Example.xml The file DeviceTypesUser - Example.xml specifies several devices. The top part specifies the PhenoTyper White spot commands, and the bottom part specifies the counter of the Running wheel. DeviceTypesUser Pheno Wheel (30).xml For a running wheel with a reading interval of 30 s instead of 60 s as in the standard Noldus PhenoWheel, you need a file like this: Rename the file to DeviceTypesUser.xml. This XML file specifies a device type for a running wheel with a reading interval of 30 s instead of 60. Note the device type ID (10006), name (PhenoWheel (30)), and the custom sample frequency (30). When you restart EthoVision XT, the new device types are then shown, for example in the Arena-Hardware Mapping window that you access in the Arena Settings. Predefined IDs For both devices and connectors, IDs must be unique. IDs from 0 to 9999 are for Noldus device (and connector) types. IDs above 10000 are reserved for device (and connector) types that you may want to add. If you create a device type based on a Noldus device type (for example a Lickometer), always use an ID above 10000. The Arena-Hardware Mapping window shows the new device type PhenoWheel (30) in the first column of the table. The following device types are available: - Top Unit (Standard) - Top Unit (Neuro-Bsik) - Pellet Dispenser (PTPD-001x) - Lickometer (PTLM-001x) - TTL Port Tester (PTTB-001x) - Custom Hardware - PhenoWheel - USB-IO box monitor - Beam Controller (PTBC-0010) - Med Associates Activity Wheel Counter (ENV-042) - Med Associates Activity Wheel Brake (ENV-042) - Backlight Unit White Light - Top Unit Tester (PTTB-002x) - Pellet Receptacle (PTPR-001x) - Top Unit Interface (PTTI-001x) XML File Entries Not all of the entries below always apply to each signal, command, etc. If you make edits in a device type file, beware that besides editing the data below you might have to change some numbers that the boost::serialize normally creates itself (vector counts, for example). NCHiIobConnectorTypes Devices can be connected to the USB IO box (or mini IO box) via a connector. There can be more than one connector type in the setup. Following are the properties of the collection of connectors (m_vecConnectorType): - Count: Indicates the number of connectors - Item_version: Indicates the version of the connectors Following are the properties of each connector (NCHiIobConnectorType): - HiIob::ConnectorTypeId m_iId: Every connector type must have a unique ID. g_ConnectorTypeIdInvalid(-1l): invalid value - Item_version: Indicates the version of the connectors - nstring m_strName: Name of the connector NCHiIobDeviceTypes Devices can be connected to the USB-IO box directly (e.g., not via a connector). Following are the properties of the collection of device types (m_vecDeviceType): - Count: Indicates the number of device types - Item_version: Indicates the version of the device types Following are the properties of each device type (NCHiIobDeviceType): - HiIob::DeviceTypeId m_iDeviceTypeId: Every device type must have a unique ID. g_DeviceTypeIdInvalid(-1l): invalid value - nstring m_strDeviceTypeName: Name of device type, showing up in the UI of port-device mapping dialog (hwdll) and various places in EthoVision XT (for example: ATC, test dialog, etc.) - int m_MaxFrequency: Most device types are read every read cycle and have m_MaxFrequency = 0. So-called "slow device types" (e.g., Lickometer) are not read every read cycle but with the slower frequency MaxFrequency (in seconds). Use integer values only. - HiIob::ePortTypes m_ePortType: - ePrtUndefined(-1): undefined - ePrtSD(0): simple device port - ePrtCD(1): complex device port - int m_iNrPorts: Number of ports used by the connector - int m_iOffsetPin: Pin offset for the device connected via the connector - HiIob::ConnectorTypeId m_iConnectorTypeId: Every connector type must have a unique ID. Most device types do not use a connector and have g_ConnectorTypeIdInvalid(-11): invalid value. Currently the only connector type is the top unit connector, used with the top unit. NCHiIobSignal Each device type can have more than one signal. Following are the properties of the collection of signals (m_vecSignal): - Count: Indicates the number of signals - Item_version: Indicates the version of the device type signals Following are the properties of each signal: - HiIob::SignalId m_iId: Every signal must have a unique (within device type) ID. g_SignalIdInvalid(-11): invalid value - nstring m_strName: Name of signal, showing up in the interface of the Device Configuration window and other places, for example the test window in Trial Control - HiIob::eSignalSource m_eSignalSource: - eSrcUndefined(-1): undefined - eSrcInput(0): signal comes from the hardware - eSrcOutput(1): signal is created in the software and is related to an output state (e.g., there are outputs "White spot off" and "White spot on"; for these outputs "Is white spot on" is an output state that is treated as an artificial input, because it does not come from the hardware) - HiIob::eSignalHwType m_eSignalHwType Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - 10 User-Defined Device Types (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-10-user-defined-device-types-continued-fZ5 Chapter: EthoVision XT User-Defined Device Types (Continued) Signal Hardware Type Values - eShtUndefined(-1): undefined - eShtPin(0): uses pins (most device types) - eShtBytes(1): uses direct bytes reading (e.g.: lickometer) Signal Properties - long m_iPin The pin used by the signal. Only relevant if eSignalHwType = eShtPin. - int m_iNrBytes The number of bytes used for reading the signal. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. - int m_iIndexFirstByte Least significant byte. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. - int m_iIndexLastByte Most significant byte. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. - HiIob::eStateEventType m_eStateEventType - eSetUndefined(-1): undefined - eSetL(0): signal is based on Low state - eSetH(1): signal is based on High state - eSetL2H(2): signal is based on transitions from Low to High - eSetH2L(3): signal is based on transitions from High to Low Only relevant if eSignalHwType = eShtPin. - bool m_bHighInit Initial value for the signal. True if High, false if Low. Only relevant if m_eSignalSource = eSrcInput and eSignalHwType = eShtPin. - bool m_bTotalsSinceLastCall True if signal returns a value (via the hwdll COM interface) that represents a total since the last call. - EAdinsIdtHiValueType m_eValueType The type of the value the signal returns (via the hwdll COM interface). One of the following values: - eAdinsIdtHiVtUndefined(-1) - eAdinsIdtHiVtBool(0) - eAdinsIdtHiVtLongLong(1) - eAdinsIdtHiVtDouble(2) - eAdinsIdtHiVtDuration(3) This value is used by EthoVision XT: Trial Control and logging. - bool m_bHasValueDefault True if the signal has a default value. Indicates how the value of the signal has to be treated by the exported hardware log in VTS: - If true: only the values not equal to the default value are logged. - If false: only changes in the values are logged (default value is not used). - NCHiIobValue m_valueDefault Default value for the signal. Only relevant if m_bHasValueDefault = true. - HiIob::eValueType m_eTypeValueDefault Default value type for the signal (see m_eValueType) for the values. NCHiIobCommand Each device type can have more than one command. The following are the properties of the collection of commands (m_vecCommand): Collection Properties - Count: Indicates the number of commands. - Item_version: Indicates the version of the device type commands. Default Value Properties - bool m_bValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtBool. - LONGLONG m_lValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtLongLong. - double m_dbValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtDouble. Command Properties - HiIob::CommandId m_iId Every command must have a unique (within device type) id. g_CommandIdInvalid(-11): invalid value. - nstring m_strName Name of command, showing up in the UI of the port-device mapping dialog (hwdll) and various places in EthoVision XT (for example: Trial Control boxes, test dialog, etc.). - bool m_bIsDefaultCommand True if command is the default command. Default commands are called before start sampler (start of a trial) and after stop sampler (end of a trial). - long m_iPin The pin used by the command (if any). - bool m_bHigh True if command corresponds to a High bit value; false if command corresponds to a Low bit value. - int m_iDuration Duration in milliseconds. After writing this command, a new command is scheduled to be written the given duration time later (only if duration > 0). If the original command was High, the scheduled command is Low and vice versa. Used for the pellet feeder to reset. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Analysis Of Trial Control Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-analysis-of-trial-control-data Chapter: EthoVision XT Analysis of Trial Control Data What Do You Want to Do? Trial Control data are analyzed as Dependent variables. Choose your dependent variables in the Analysis Profile. Analyze Events That Occurred During the Trial How many times a condition became true? How many times the food reward was given? What is the latency of the first reward? To answer these questions, we consider the events associated with single Trial Control boxes. See Trial Control Events below. Analyze the Time Defined by Two Events How much time elapsed from the moment the cue light switched on to when the subject entered the reward zone? See Trial Control States. A special case in this category is the analysis of learning. Did the time between the event Light on and the event Subject in reward zone decrease during the test? Analyze the Data Within the Time Between Two Events How many times a certain behavior occurred when the stimulus light was on? What was the speed of the subject between event A and event B? To answer such questions, use the Nest function to define the time segments within which the event or behavior of interest occurred. See Analyze the Data Within Trial Control States. Analyze Trial Control Variables A Trial Control variable has been defined in the Trial Control procedure. Its value is increased every time the subject makes a correct choice. To analyze the performance of the subjects, calculate the maximum value of the variable, and visualize when the maximum value occurred. See Trial Control Variables. Analyze the Commands Sent to Hardware Devices How many times did EthoVision XT send a command to a pellet dispenser to drop one pellet? See Hardware Command. Analyze Variables Associated With Hardware Devices For example, analyze the data from the Lickometer. For hardware devices, there are continuous variable and state variables. See Hardware Continuous Variable and Hardware State Variable. Notes - For more general information on analysis variables, see Dependent Variables in the EthoVision XT Help. - To visualize Trial Control data, from the Analyze menu, select Results and then Plot Integrated Data (see the EthoVision XT Help). - To export Trial Control data, see the Export section. - Trial statistics of Duration and Latency can only be a multiple of the sample interval (= 1/sample rate). For example, a condition like Subject in zone A for >= 3 s is met when the time elapsed from its activation exceeds 3 s. If the sample rate is 12.5 frames/s (sample interval = 1/12.5 = 0.08 s), the condition is met at the first multiple of 0.08 greater than 3 s, that is 3.04 s. For this reason, the latency of the event Condition becomes true is 3.04 s. Trial Control Events If you are interested in the rate of events such as the number of times the lever was pressed, the number of pellets dropped, or the latency of an action, use the Trial Control event function in the Analysis Profile. - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - In the Dependent Variables pane, under Trial Control, double-click Trial Control event, drag it to the middle of the screen, or click the button next to it. - The Trial Control event window appears. Under Event, from the Element list select the element to be analyzed. For example, to analyze the hardware-based action Drop pellet, locate it among Action: Drop pellet and select it. - From the Event list, select the event for the element selected. The options available depend on what you have chosen as Element (see Possible Events of Trial Control Elements below). - Click the Trial Statistics tab and select the statistic you want to analyze. - Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. - Click Add. The new Trial Control event appears in the list of Selected Dependent Variables. - Choose the option you require: - To calculate statistics of the selected events, choose Analyze > Results > Statistics & Charts. - To visualize the events, choose Analysis > Results > Plot Integrated Data. Notes - If one or more other instances of Trial Control event are listed under Selected Dependent Variables, the Trial Control event name is followed by a progressive number (1, 2, 3...). - The Element list contains the Trial Control elements defined in all your Trial Control Settings. For each element, the list shows the name of the corresponding Trial Control box. - Choose Latency to first to analyze the time of the first instance of the event defined since the start of tracking. Choose Latency to last to analyze the time from the start of data recording to the last instance of the event defined. - For calculating frequency and latency of the subject's behavior, choose the appropriate Dependent Variable (see Dependent Variables in Detail in the EthoVision XT Help). Possible Events of Trial Control Elements - Becomes active (for Start-stop trial rule begin, sub-rule begin, conditions, actions, references and operators). Marks the time that the trial starts (for the Start-stop trial rule begin) or the element becomes active (in all other cases). This is the time when control passes from the previous box in the Trial Control sequence. See the notes below for the difference between Becomes active and Becomes true. - Becomes true (for conditions and operators). Marks the time that a condition is met. Choose this option for example to analyze the instances when the condition In zone A was met. - Becomes false (for conditions and operators). Marks the time that a condition is not met. Choose this option for example to analyze the instances when the condition In zone A was not met. - Becomes inactive (for Start-stop trial rule end, sub-rule end, conditions, actions, references and operators). Marks the time that the element becomes inactive, that is, when control passes to the next box in the Trial Control sequence. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Analysis Of Trial Control Data (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-analysis-of-trial-control-data-continued-IxU Chapter: EthoVision XT Batch Analysis To run different analyses with different combinations of these filters, do the following: - Click Batch. - Select the profiles from the lists and click Add. - Repeat the previous step for other combinations. - Click Calculate. - Select the combination of profiles from the lists on the toolbar to view the results. Export Trial Control Data You can export Trial Control data just like the other dependent variables. - Choose Analysis > Export > Raw Data. - Select the following: - Track & dependent variables. To export events and intervals defined in the Analysis profile. For example, actions and conditions and intervals in between. This option also includes hardware-based actions and conditions, not the actual communication signals. - Hardware log. To export the communication signals between EthoVision XT and the hardware device. - Click Start Export. Exported Raw Data File In the exported raw data file, each Trial Control event or Trial Control state defined in the Analysis Profile is stored in a column. A Trial Control event is exported as 1 in the row corresponding to the time when the event occurs. In the other rows, it is exported as 0. A Trial Control state interval is exported as 1 in the rows corresponding to the time included in the interval. If the interval occurs in multiple instances during the trial, you will see multiple segments of 1. For more information about exporting track data, see Export Tracks in the EthoVision XT Help. Hardware Log File When you select Hardware log in the export screen, hardware events are exported to a separate file. The data are organized in columns as follows: - Time is the time when the signal value is read or the action is taken. Note: This is the time elapsed since the start of the trial, not the start of tracking. For lickometers, values are updated about every 2 s. - Device ID is the name of the physical device that the event refers to. - Command/Signal is the type of data (Command, or Signal). - Name is the name of the command or signal. - Value is the value of the signal at that time. Each row of the file contains one of the two: - Rows marked with Signal. The value of the signal since the last time the device was read (for example, the number of licks or the duration of licks since the last reading). Duration of licks is expressed in milliseconds. - Rows marked with Command. The command (for example, Drop pellet). The hardware log file is one per trial, no matter how many arenas and devices are used. If you re-do a trial, the log files recorded with the previous instance of the trial are deleted. In order to be logged, hardware devices must be connected to the computer and configured in EthoVision XT. Notice that the Time in the Hardware log file is the time since the start of the trial, while the time in the Track data file is the time since the start of tracking. Example: If you have defined a command like Drop pellet as a Trial Control event, to find a specific Drop pellet event in the data file, take note of the Time in the Hardware log file for that event and locate that time in the Time trial column in the Track data file. For Pellet dispensers: Number of drops is the feedback signal sent by the device to EthoVision. Usually it is recorded 0.04 s after the actual Drop pellet command. Choose Hardware log if you want to export communication data between EthoVision and the hardware device, even when the device was not used during the trial. If you select both Track data and Hardware log, data are exported in separate files when choosing the Text format, and in one file when choosing the Excel format. In the Excel file, Track data and Hardware log data are stored in separate sheets. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Analysis Of Trial Control Data (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-analysis-of-trial-control-data-continued-Sbz Chapter: EthoVision XT Analysis of Trial Control Data Devices such as the Lickometer and PhenoWheel send data to EthoVision XT at fixed times, every two seconds for the Lickometer and every 60 seconds for PhenoWheel. At each sample time, EthoVision XT reads the data since the last reading event: - For the Lickometer: number and duration of licks. - For PhenoWheel: number of rotations. The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also include some time before the trial start (< 2 s for Lickometer, < 60 s for PhenoWheel). This time is included in the results. - The data between the last reading event and the stop of the trial are not included in the results. This time is again < 2 s for Lickometer, < 60 s for PhenoWheel, depending on when the trial stopped. In most cases the two discrepancies have no effect on your data when the trial lasts at least a few minutes or hours, like in typical PhenoTyper tests. Tip: If you want the devices to have another sampling rate, contact Noldus. Hardware State Variable A variable based on a Hardware continuous variable. You can, for example, define a Hardware state variable Number of dropped pellets is equal to or greater than 1 and calculate, for instance, the duration of this interval. How to Add a Hardware State Variable to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware state. - The Hardware state variable window opens. From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze the signal from your pellet dispenser, select Pellet Dispenser (PTPD-001x). - In the Device list the name of the hardware device will appear as you defined it when you assigned the device to the arena. - From the Signal list, select which signal you want to analyze. For instance, for the pellet dispenser you can select Number of drops or In error state. - Set the appropriate Value (threshold) or select the value you are interested in. For instance, for Number of drops set a threshold of equal to or greater than 1; for In error state select true or false. - Cumulative value: Select this option to calculate/visualize the cumulative value of the signal. - Click the Trial Statistics tab to choose the statistics for the dependent variable. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Next, click Add. For details, see Calculate Statistics in the EthoVision XT Help. Application You can use Hardware state variables to analyze, for instance, how long a light was on. You can also use Hardware state variables to analyze learning behavior. For instance, when training an animal you may want to know how long it takes before it completes a task (and receives a food pellet). For this purpose, you can calculate the statistic Latency to first for the Hardware state variable Number of drops greater than or equal to 1. For naive animals the latency will be high at the start of the training and will decrease as the animals learn the task in subsequent trials. Please note that the following question requires a different procedure: What was the average time between "light on" and "lever press" in a learning experiment? It is not possible to define a variable based on two separate hardware events. To answer this question, define a Free interval using hardware events. For more information, see Free interval in the EthoVision XT Help. Free Intervals Based on Trial Control and Hardware Data Free intervals are the most flexible solution to analyze slices of time which go from an event, or time, to another event or time. You can use them in the Analysis profile and in the Data profile. Example: In a DanioVision experiment, analyze the speed of the subjects in the 5-s time interval before the onset of the light stimulus, and in a second interval, in the 5-s time interval after the onset of the light stimulus. Because you want to analyze the speed within the intervals, define those intervals as Free intervals in the Data profile. How to Add a Free Interval to an Analysis Profile In the Analysis profile, under Custom Variables, click the Add button next to Free interval. For more information, see Dependent Variables in Detail > Custom Variables in the EthoVision XT Help. How to Add a Free Interval to a Data Profile In the Data profile, under Nesting, click the Add button next to Free interval. For more information, see Analyze Track Segments > Nesting over a free interval in the EthoVision XT Help. The Analysis Results To Calculate the Statistics - Click Statistics & Charts in the Project Explorer. The analysis window that appears has the tab Trial Statistics for the analysis results per trial and Group Statistics & Charts with statistics and charts from the summarized results over different trials. - If you have different filters, data profiles, or analysis profiles, make your selection on the toolbar. - Click Calculate. - Optional: Click the Layout button to modify the layout of the results table. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Analysis Of Trial Control Data (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-analysis-of-trial-control-data-continued-Bhc Chapter: EthoVision XT Analysis of Trial Control Data Notes If the interval specified in the step above occurs in multiple instances, the program considers the total time line included in those intervals to calculate durations, frequencies etc. If your experiment includes multiple subjects per arena, the Nesting over Subjects group of options is also available. Select Trial Control state under Nesting over Subjects if you want to define an interval based on what one or more of the subjects do during the trial. For example, to define an interval that goes from the action "Cue light on" when activated, to the condition "Subject 1 in zone A" when it becomes true. Click the Actors tab and select the subject that the condition refers to. Analysis will be done for all the subjects, in the interval defined by Subject 1. Note that conditions can be met by specific subjects, while actions cannot be triggered by specific subjects. However, they can be triggered indirectly, when an action follows a condition met by that subject. For information on Nesting, see Analyze Track Segments in the EthoVision XT Help. Trial Control Variables You can analyze and visualize the values of the Trial Control variables defined in the Trial Control Settings. Use this function also for testing purposes. For example, to check that a Trial Control variable receives the value expected at a specific time. - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Trial Control variable and choose a variable from the list. - Calculate the statistics or plot the variable with the Integrated Visualization. For more information, see the EthoVision XT Help. Hardware Command A Hardware command is a command given by the EthoVision software to your hardware device. You can define when and what hardware commands are sent as Actions in your Trial Control settings. For instance, you can have EthoVision send a command to your pellet dispenser to drop a pellet after the mouse has been detected in the Trigger zone. For more information about programming Trial Control, see Chapter 3. How to Add a Hardware Command to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware command. The Hardware command window opens. - From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze how many Drop pellet commands EthoVision gave to your pellet dispenser, select Pellet Dispenser (PTPD-001x). - In the Device list, the name of the hardware device will appear as you defined it when you assigned the device to the arena. - From the Command list, select which command you want to analyze. For instance, for the Phenotyper 1's Top Unit, you can select White spot on, White spot off, Yellow light on, Yellow light off, Sound on or Sound off. For other hardware devices (Pellet Dispenser, Lickometer) there is only one option. - Click the Trial Statistics tab to choose the statistics for the dependent variable. Next, click Add. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. See Calculate Statistics in the EthoVision XT Help for details. Application: Hardware Command By selecting Hardware command as Dependent Variable, you can calculate the frequency of the commands the EthoVision software gives to your hardware device. In addition, you can calculate the latency to the first command and the latency to the last. You can also visualize Hardware commands. This enables you to check whether your Trial Control settings do what you expect them to do. For example, visualize the Hardware command Drop pellet for your pellet dispenser and plot it in the integrated visualization together with the video to check how often the command was given and when. Hardware commands appear as Point events in your plot, that is, as events with no duration. Hardware Continuous Variable After EthoVision XT has started tracking, connected hardware devices start sending signals to the EthoVision computer. You can analyze these signals by adding Hardware continuous variables to your analysis profile. You can calculate and visualize, for instance, the number of pellets dropped by your pellet dispenser or the duration of licks at the lickometer. How to Add a Hardware Continuous Variable to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware continuous. The Hardware continuous variable window opens. - From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze how many pellets your pellet dispenser dropped, select Pellet Dispenser (PTPD-001x). - In the Device list, the name of the hardware device will appear as you defined it when you assigned the device to the arena. - From the Signal list, select which signal you want to analyze. For instance, for the pellet dispenser you can select Number of drops. - Click the Trial Statistics tab to choose the statistics for the dependent variable. If you want summarized statistics over all trials, or the groups of trials defined in your Data Profile, click the Group Statistics tab and select additional statistics. Next, click Add. For details, see Calculate Statistics in the EthoVision XT Help. Application: Hardware Continuous Variable By selecting Hardware continuous variable as Dependent Variable, you can calculate, for instance, how many pellets your pellet dispenser dropped or how long your mouse has been drinking from its water bottle. You can also calculate the frequency with which drinking from the bottle took place. However, many of these drinking occurrences together often form a single drinking bout. Analyzing such bouts is not possible in the current version of EthoVision XT. This means that to calculate how often such bouts occurred, you have to export the data to a Hardware log and analyze this in an external program like Excel. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Analysis Of Trial Control Data (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-analysis-of-trial-control-data-continued-qda Chapter: EthoVision XT Analysis of Trial Control Data When the animal actually enters the zone (and thus Current = true for that sample). - If you use any other statistic to define the condition (for example, "when Frequency of In zone >= 1"): - When the condition becomes true after the condition box is activated, the Trial Control State starts (or stops) at the expected sample time (see A in Figure 47). - When the condition is already true when the condition box is activated (for example, a condition "Frequency of In zone = 1" is activated when the animal is already in the zone), such statistic is only evaluated at the next sample (or in the second next sample, in the case of Heading). In that case, the Trial Control state starts (or stops) one sample (or two) later than expected from the condition (see B in Figure 47). However, for the consecutive frequencies of In zone = 2, 3, etc., the condition is already active by definition; therefore the Trial Control State starts at the expected time, when the condition becomes true. Figure 47: In this example, a Trial Control condition has been defined in the Trial Control Settings, which checks that the Frequency of In zone is >= 1 for the Center of the open field. A Trial Control state has been defined in the Analysis profile, which starts when the condition "Frequency of In zone >= 1" is true. - A1 — The animal enters the Center zone (and therefore the condition becomes true) after the condition is activated. The Frequency statistic is evaluated at the same sample time. - A2 — Plot of the variables "In zone" for the Center and the Trial Control state. The Trial Control state starts at the expected sample time, that is, when the animal actually enters the zone. - B1 — The animal is already in the zone when the condition is activated. Therefore, the condition becomes true at the same time that it is activated, but the Frequency statistic is evaluated at the next sample (here, sample rate = 5/s, thus after 0.2 s). - B2 — Same plot as A2; here, the Trial Control state starts 0.2 s after the In zone state. If you de-select Calculate statistics per interval, the Cumulative duration statistic is the total duration of the intervals in that trial. If you want to know how many occurrences of the intervals a specific trial contains, follow the procedure above making sure that Calculate statistics per interval is not selected, and Frequency is selected under Trial Statistics. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Next, run the analysis. The table shows the number of intervals under Frequency for that dependent variable. The occurrences are counted if the From condition is met. If the trial ends before the To condition is met, the interval is still counted in the Frequency. Examples of Trial Control States Example 1 In a conditioning test, it is required that the subject must go to zone A in order to receive a reward. The researcher wants to know the time from the moment the subject could have responded (Condition Subject in zone A becomes active) to the moment the subject eats the reward (Condition Subject in feeder zone becomes true). The Trial Control sequence is as follows: Rule Begin → Condition - In zone A → Action - Drop a food item → Condition - In Feeder zone → Rule End. In the Analysis profile, click Trial Control state and select: - From - Element Condition: In Zone A, Event = becomes active - To - 1st occurrence of Element Condition: In Feeder zone, Event = becomes true In the Trial Statistics tab, make sure that Cumulative duration is selected. Example 2 In a variant of the experiment above, the researcher wants to know the time that it takes the mouse to get the pellet after being in zone A. Here we assume that if the animal enters zone A, then gets out and subsequently gets back in before collecting the food item, one wants to analyze from the first instance that the mouse went in zone A. In the Analysis Profile, click Trial Control state and select: - From - Element Condition: In Shelter zone, Event = becomes true (because one wants to analyze the time from when the condition is met) - To - 1st occurrence of Element Condition: In Feeder zone, Event = becomes true In the Trial Statistics tab, make sure that Cumulative duration is selected. Analyze Learning Behavior When a sequence like Cue stimulus → Subject's action → Reward is repeated a number of times, you may want to know whether there is a trend of decreasing or increasing duration of intervals from one component of the sequence to the next. For example, is the time from the cue stimulus to the subject's lever press decreasing during a 30-minute test? To analyze learning behavior, follow the procedure on page 180, and make sure that: - In the Trial Control State Interval tab, select the Calculate statistics per interval option. - Next to For consecutive intervals, select which occurrences of the interval you want to analyze. - In the Trial Statistics tab, make sure that Cumulative duration is selected. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Calculate the statistics, and export the results (see Calculate Statistics in the EthoVision XT Help). Analyze Data Within Trial Control States If you want to calculate statistics on or visualize data within intervals defined by Trial Control events, you must first define those intervals as Nesting intervals in the Data Profile. - In the Experiment Explorer, right-click Data Profiles and select New, or click one of the existing profiles. - In the Components pane, under Nesting, double-click Trial Control state or drag it to the middle of the screen, or click the button next to it. - The Trial Control state window appears. Define the interval as described in the procedure on page 180 (the options are the same, only the Statistics tab is not present). - Click OK. The Nest box appears on the screen. Insert this box between the Start and the Result box. - In the Experiment Explorer, right-click Analysis Profiles and select New, or click one of the existing profiles. - Define the dependent variables you want to analyze and run analysis or visualize the data. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Analysis Of Trial Control Data (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-analysis-of-trial-control-data-continued Chapter: EthoVision XT Analysis of Trial Control Data Trial Control Events - Makes sub-rule active (for sub-rule references): Marks the time that a reference to a sub-rule triggers the sub-rule. This is the time that one of the Start conditions set in the Reference box becomes true. - Makes sub-rule inactive (for sub-rule references): Marks the time that the last repeat of a sub-rule planned for a specific Start condition is completed. Notes: - For a condition like Is the subject in zone A?, choose Becomes true to consider the moment when the condition is met. Choose Becomes inactive when you want to consider the time that a condition could be met (no matter whether or not the subject is in zone A). - Becomes active/inactive are especially used when analyzing intervals (see below). Trial Control States If you are interested in the time interval between two events — for example, from the Action "cue light on" to the Condition "subject on shelter" being met — use the Trial Control state function in the Analysis profile. - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - In the Dependent Variables pane, under Trial Control, click Trial Control state or drag it to the middle of the screen, or click the button next to it. The Trial Control State window appears. - Next to From, from the Element list select the Trial Control element that makes the criterion for the start of the interval. From the Event list, select the event that marks the start of the interval. - Next to To, from the Element list select the Trial Control element that makes the criterion for the end of the interval. From the Event list, select the event that marks the end of the interval. The event that marks the end of the interval may occur multiple times. Therefore, choose which occurrence (from 1st to 9th) should be used. The 1st occurrence is the first occurrence of the event selected under To available after each occurrence of the event selected under From. - Select Ignore last interval if incomplete to ignore the interval when the Trial Control event that defines the end of the state is not found. If you do not select this option and the end criterion is not met, EthoVision XT defines an interval up to the end of the track. - An interval may occur several times in a trial. If you want to have statistics for each occurrence, select the Calculate statistics per interval option. Next to For consecutive intervals, choose the range of occurrences of the intervals you want to have in the results. Example: If the interval from Light On (cue) to Mouse on Shelter (response) occurs 10 times and you want to have the first four occurrences displayed in your table, select 1 to 4. If you want to have all occurrences displayed, select 1 to 10. Note: If you do not know exactly how many instances of the state interval the tracks contain, enter a reasonably high number (for example, 50 or 100) to ensure analysis is carried out on all instances. Note: If you do not select this option, the multiple occurrences are considered as one interval. Click the Trial Statistics tab and select the statistic you want to analyze. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials or the groups of trials defined in your Data Profile. Click Add. The new Trial Control state appears in the list of Selected Dependent Variables. - Choose the option you require: - To calculate statistics of the selected intervals, from the Analysis menu, select Results and then Statistics & Charts. The analysis window that appears has the tab Trial Statistics for the analysis results per trial and Group Statistics for the statistics and charts from the summarized results over different trials. If you have different filters, data profiles, or analysis profiles, make your selection on the toolbar. Click Calculate. - To visualize the intervals, choose Analyze > Results > Plot Integrated Data. Notes: - If one or more other instances of Trial Control state are listed under Selected Dependent Variables in the main window, the Trial Control state name is followed by a progressive number (1, 2, 3...). It is advisable to rename the trial control state (right-click the name and select Rename). - The Element list contains the Trial Control elements defined in all your Trial Control Settings. For each element, the list shows the Name of the corresponding Trial Control box. - Choose Becomes active instead of Becomes true when you want the interval to be based on a condition from the moment it could have been met, regardless of when it was actually met. - If you define an interval by choosing the same event under From and To, the instance of the event marking the end of the interval is not used as a starting point for the next occurrence of the interval. For example, given a sequence of four actions of the same type: A1, A2, A3, A4 — selecting a trial control state From A To A results in analyzing the time between A1 and A2, and between A3 and A4. Trial Control States Based on Conditions The sample time at which a Trial Control state starts or ends also depends on the statistic used in the condition in the Trial Control rule. - If you use Current to define the condition (for example, when Current In zone = true), the Trial Control state starts or stops at the expected sample time. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Arenas URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-arenas Chapter: EthoVision XT Introduction This document is intended for EthoVision users who record data with multiple arenas simultaneously, and want to apply different Trial Control protocols to different arenas. Example: The camera points at two separate arenas, each with one animal. In arena 1, provide a foot shock 30 seconds from the start of the trial. In arena 2, provide a foot shock at a randomly chosen time between 0 and 90 seconds from the start. Multiple Arenas in Your EthoVision Experiment If you work with multiple arenas within an experiment, each arena is treated as an independent replicate. In most cases, you want to apply the same Trial Control protocol to all the arenas. Imagine that you create a Trial Control protocol that stops tracking when the subject has moved a certain distance. You define one Trial Control Settings profile and apply that profile for your trial. Because subjects differ in their behavior, tracking will stop at different times for each of those arenas. That is because EthoVision XT uses multiple copies of the same Trial Control Settings, one for each arena. Same Protocol, but Independent Processes The Trial Control Settings are applied to each arena independently. Suppose that the protocol is "After starting the trial, switch on a light when the animal enters the zone named Food Zone." A light device has been installed on top of both arenas, and a zone named "Food Zone" has been defined in the Arena Settings for both arenas. If the animal in Arena 1 enters its Food Zone, the corresponding light will be switched on. However, the light on top of Arena 2 won't be activated, unless the animal in Arena 2 enters its own Food Zone too. Although the protocol is the same, it is applied in two copies, one for each arena. To implement this, select the different physical devices (Light 1 for Arena 1, Light 2 for Arena 2, etc.) on the same line in the Arena - Hardware Mapping window (Arena Settings). This way, different arenas refer to the same generic device name (e.g., "Light"). This "generic" name is then used in the instructions of the Trial Control protocol. Another typical example is the PhenoTyper setup, where the same protocol is applied to a group of 4 or more cages. Conditions and actions are processed independently for each cage. Different Protocols in Different Arenas In some cases, two or more arenas may need different protocols. For example, your camera view includes three arenas: - In Arena 1, a light (Light 1) is switched on at a specific time, for example at one minute after start. - In Arena 2, the light (Light 2) is switched on at a moment randomly chosen between 30 seconds and 2 minutes. - Arena 3 is used as a control, with no light stimuli presented. - For all arenas, the trial lasts 3 minutes. If the Trial Control procedure is based on an Arena - Hardware Mapping where the two light devices Light 1 and Light 2 are represented by the same device name, any instruction using that device name would be executed for both arenas. As a result, the light would be switched on in both arenas twice — once at 1 minute, and again at a random time between 30 seconds and 2 minutes. Similarly, if an action depends on the animal's behavior (for example, "Switch on the light when the animal is in the Food Zone"), the command would be executed in both arenas, producing incorrect results. The solution is to map devices in a different way, by specifying one physical device in each row in the Arena - Hardware Mapping window. Simple Case: Two Arenas To illustrate the concept, we assume that we work with two arenas with one animal in each arena. The animals are subject to two different treatment protocols. In Arena 1, the stimulus is administered at a fixed time, while in Arena 2 the stimulus is administered at a randomly chosen time. Hardware devices are controlled through TTL commands. Experiment Settings - Connect all hardware devices to the EthoVision XT computer via the appropriate TTL port in the Noldus USB-IO box. - In the Experiment Settings, under Trial Control Hardware, click Settings. - Choose Noldus USB-IO box. - In the Device Configuration window, assign a hardware device to a port of the USB-IO box. Select the device type in the Device type/Device column. This may be a standard device (such as the Top Unit Light for PhenoTyper) or a Custom Hardware device. In the Device Configuration window, the Device ID indicates the name of each physical device. For example, Light 1 will be installed in Arena 1, Light 2 in Arena 2, and so on. Arena Settings - In the Arena Settings, define and calibrate the arenas as usual. Next, click the Arena - Hardware Mapping button in the Arena Settings window. - In the Arena - Hardware Mapping window, click Add Device two or more times to create multiple rows — one row for each physical device that has to work independently. - For each arena, assign a device in a different row. Make sure that the other cells of the row show . Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Arenas (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-arenas-continued-Der Chapter: EthoVision XT Arenas (Continued) Shock is given at the same time, but to keep this case more general we leave them separate. The arenas with no shock treatment (Arenas 5 and 6) have no shocker device selected. The olfactometer is used in all arenas, and at the same time. This means that the command to activate/deactivate the olfactometer can be represented by one Device name in Trial Control (see the last row in the table above). Therefore, the same Device name is assigned to all arenas. Define the Protocols Make a sketch of the events in each arena. Draw a time line for each arena. On the time line, write down the events that should occur, and their duration. This will help creating the Trial Control protocols. Trial Control Settings Sequence for Arena 1 and 2 Note that only the sequences for Arena 1 and 2 are connected to the Stop trial box. There is no need to connect the sequences for Arena 3 and 4 and the sequence for the olfactometers to the Stop Trial box, because these instructions proceed in parallel with those for Arena 1 and 2. The track duration is the same for all arenas. The trial control sequence for controlling a foot shocker at 28 s from the start, in both Arena 1 and Arena 2. The shock ends at 28+2 = 30 s from the start. Sequence for Arena 3 and 4 The trial control sequence for controlling a foot shocker at a time randomly chosen within a 90-s period. In order to center the 90-s period for the random shock in the 4-min period after the offset of the odor, a 75-s condition has been added (75+90+75 = 240 s = 4 minutes). Note that the 30-s Condition box and the two 75-s conditions could be replaced by one 105-s Condition box, connected to both Random time conditions. In this picture the 105-s time has been kept split in two parts (30 s + 75 s) to visually match the sequences for the other arenas. Repeat the Sequence Within the Trial If you want the sequences described above to be repeated a number of times within a trial, you must use the Sub-rule function in Trial Control. Here, the sub-rule is repeated 10 times. Note that the end box of the sub-rule is connected to the sequence for Arena 1 and 2. This sets the duration of the repeats (30 min. with odor stimulus + 4 minutes), and the trial as a whole. For more information on how to use Sub-rules, see Sub-rules on page 61. A sub-rule has been added to repeat the protocol a number of times in the same trial. Index Symbols - %an% - %tn% A - Absolute Angular Velocity Condition - Absolute Meander Condition - Absolute Time - Time condition - Time interval condition - Absolute Turn Angle Condition - Acceleration - Accuracy of Hardware Events - Acoustic Stimulus - Acquiring Data - Action Box - Activation - Inactivation - Actions - After a specific time - At the same time - Defining - Examples - Multiple instances - On a hardware device - On a trial control variable - On external commands - On trial control variables - Repeating a sequence - Time interval - Using - With different conditions - Activation - Of action box - Of condition box - Active — see Becomes Active - Activity - Condition based on - Activity Analysis - Activity Wheel Counter - Condition based on - Actors - Distance between subjects condition - In conditions - Net weighted movement condition - Proximity condition - Relative movement condition - Weighted movement from condition - Weighted movement to - Add Device - After Clock Time - Time condition - All Operator - Analyzing Learning Behavior - Analyzing Trial Control Data - Data within state intervals - Hardware commands - Hardware continuous variables - Hardware state variables - Simple events - State intervals - Trial control variables - Angular Velocity - Absolute - Condition based on Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Arenas (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-arenas-continued Chapter: EthoVision XT Arenas (Continued) Apply Different Protocols to Different Arenas Define the Protocols Make a sketch of the events in each arena. Draw a time line for each arena. On the time line, write down the events that should occur, and their duration. This will help creating the Trial Control protocols. Trial Control Settings There may be parts of the protocol shared between arenas. In the example of Figure 59, the first 30 seconds after the start of the trial are the same for the two arenas. Therefore, one condition box after the Start track box will suffice. The sequence of instructions for the two treatments must originate from the same point (so they will start at the same time) and proceed in parallel. Note that the two branches do not have to end back into the main start-stop sequence. However, you must make sure that the trial does not stop before the two branches have been processed. In this example, we have set the trial to stop after 2 minutes. Therefore, a Time box has been added to the Start-stop sequence that waits 90 s to complete the trial (30 s of the first box + 90s = 120 s). Sequence for Arena 1 — According to the protocol, for Arena 1 the light must be switched on immediately after the 30 s period, then 2 s later it must be switched off. This can be programmed with two hardware actions (ON and OFF) and a Time condition in between. The actions must specify the device Light Arena 1. Sequence for Arena 2 — According to the protocol, for Arena 2 the light must be switched on at a time randomly chosen between 0 and 90 s. This can be programmed with a time condition that determines the random time, followed by a sequence similar to that for Arena 1. The actions must specify the device Light Arena 2. The Random time condition defines a time between 0 and 88 seconds, to make sure that the 2-seconds light flash is always given in its entire duration within 90 seconds. Repeat a Sequence Within the Trial In most cases, a sequence of actions is repeated a number of times, or until a condition is met. If you want the two sequences described above to be repeated, you must use the Sub-rule function in Trial Control. The Sub-rule settings ensure that the sub-rule is repeated 10 times, and the time between the start of 2 successive repeats is 2 minutes. For more information on how to use Sub-rules, see Sub-rules. Advanced Case: Six Arenas In this use case, we plan to record data in six arenas, with one animal per arena. This use case is considered advanced for several reasons: - Each treatment (odor stimulus and a subsequent foot shock) is duplicated in two arenas. This example shows that even when two of a number of arenas share the same protocol, each arena must have its own trial control procedure with unique Device names defined. - Together with two treatments that require different protocols, a third group (control) is added that requires no foot shock. Control animals are recorded simultaneously with the other animals. - All animals share part of the protocol. They all receive an odor stimulus by means of an olfactometer. Therefore, part of the Trial Control procedure must work for all arenas. - All hardware devices are assumed to be controlled through TTL commands. Experiment Settings - Connect all hardware devices to the EthoVision XT computer, via the appropriate port in the Noldus USB-IO box. - In the Experiment Settings, select the Number of Arenas. - Under Trial Control Hardware click Settings. - In the window that opens, select Noldus USB-IO box. - In the Device Configuration window, assign a hardware device to a port of the USB IO box. Here Device ID represents a name for each physical device. For example, Shocker 1 will be installed in Arena 1, Shocker 2 in Arena 2, etc. Since the olfactometers work the same way in all arenas, they can be connected to the same port of the USB IO box. Therefore, you need 4 ports for the shock generators (Arenas 1 to 4) and one port for the olfactometer. Arena Settings - In the Arena Settings, define and calibrate the arenas as usual. Next, click the Arena - Hardware Mapping button in the Arena Settings window. - In the Arena - Hardware Mapping window, click Add Device two or more times to create multiple rows, one row for each physical device that has to work independently. In this case, 5 rows. - For each arena, assign a device in a different row. Make sure that the other cells of the row show . Note that: - Although Arena 1 and 2 and Arena 3 and 4 share the same treatment, they must be linked to different Device names. This is to avoid that any command given to, for example, the shocker in Arena 3 does not go to Arena 4. - In the last row of the Arena - Hardware Mapping window, the olfactometer is selected for all arenas, using the Device name Olfactometer. This name will be used in Trial Control. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Conditions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-conditions Chapter: EthoVision XT Conditions A condition can be based on: - On Time (see below) or a Time interval. - On a Trial Control variable. - On a Dependent variable like Distance moved, In zone, Mobility, etc. - A combination of dependent variables, like "is the subject moving above a certain speed and is it in a certain zone?" - On a Manually-scored behavior. - On a Hardware device. Conditions Based on Time With a Time condition, some time must elapse before the next Trial Control box is evaluated. - In the Components pane, under Conditions, double-click Time or click the button next to it. The Time condition window opens. - Under Name, enter a Condition Name. - Select one of the following options: - After. To have an action been taken some time after the condition becomes active. Example: Start tracking after two seconds. - After a random time. To have an action been taken with a delay chosen randomly between two time limits. Enter the lower and higher limits and choose the time unit (seconds, minutes, or hours). The random value is counted from the moment the condition becomes active. Choose this option when programming rewards in a variable interval schedule. Example: At the end of a random time between 10 and 30 seconds (condition), drop a food item (action). - At clock time. To have an action been taken at an absolute time (hh:mm:ss). Example: At 12:00 AM (condition), start tracking (action). Note: If you want to start tracking at 12:00 AM of the next day, and you click Start Trial in the afternoon of the current day, EthoVision XT starts tracking immediately because it sees that the condition 12:00 AM has been met already. For how to solve this, see the topic Start and stop the trial at specific clock times in the EthoVision XT Help. - Infinite time (condition never met). To wait indefinitely (see the notes below). - Insert a Comment (optional) and click OK. - The Condition box appears in the upper-left corner of the Trial Control screen. Insert it in the appropriate position in the Trial Control sequence. For information on how to insert a Trial Control box, see the EthoVision XT Help. Notes: - If you want to stop a trial after a specific time has been reached, refer to the relevant stop trial documentation. - If you track from video files, see the note Tracking from video files under Apply Trial Control to your trials. - The format for clock time is hh:mm:ss where: hh = hours, 24-hour format with leading zero; mm = minutes with leading zero; ss = seconds with leading zero. - If you choose clock times, be aware of changeover between wintertime and summertime (Daylight Saving Time, DST) and vice versa. For example, the time 02:30:00 is encountered twice on the day of onset of wintertime (in which case the first occurrence makes the condition true), or never on the day of onset of summertime. - If you create a condition to stop a trial after a specific time, say two hours, and within that time interval a changeover between summertime and wintertime (or vice versa) occurs, the trial lasts two hours as planned. - The Infinite time option is useful in the following cases: - When you want to stop tracking manually. Place the resulting box immediately to the left of the Stop track box. - When two sequences have been placed in parallel, and you want the program to take further actions when Sequence 1 has been completed, independent of Sequence 2. Place a Time condition with the Infinite time option immediately to the right of Sequence 2. Combine Sequence 1 and the Time box with an Any operator. Important: If you combine an Infinite time condition with an All operator, the program does not go further in the Trial Control rule, as it waits forever for the condition to be met. Conditions Based on a Time Interval A Time interval condition makes sense when it is combined with another condition. For example: take an action when the animal is found in Zone A (In zone condition) between 5 and 10 minutes (interval condition). - In the Components pane, double-click Time interval or click the button next to it. The Time interval Condition window opens. - Under Name, enter a Condition Name. - Under Condition is met, select one of the following: - Between. Define an interval between two time points (x and y seconds, minutes, or hours). Enter the time values and choose the time units. Note: The time points are counted from the time that the condition box becomes active, not from the start of the trial or tracking. - Between clock times. Define an interval between two absolute time points. For example, stop the track when the rat is in quadrant A between 12:00:30 and 12:01:00. The time format is hh:mm:ss where hh = hours, 24-hour format with leading zero; mm = minutes with leading zero; ss = seconds with leading zero. - Insert a Comment (optional) and click OK. - The Condition box appears in the upper-left corner of the Trial Control screen. Insert it in the appropriate position in the Trial Control sequence. For how to do this, see the EthoVision XT Help. Notes: - Combining Time interval and Zone conditions. In a conditioning experiment, the researcher wants to drop a food reward when the animal is found on its shelter some time between 30 s and 60 s from the previous action (for instance, a cue light being switched on). To do this, a Time interval condition must be defined that specifies the interval between 30 s and 60 s. This condition must be met at the same time as the condition "subject on shelter" in order to drop a food pellet. Therefore, the two condition boxes must be placed in parallel with an operator of type All. - Be aware when using Time interval conditions combined with operators of type All. If the animal enters a zone after the upper time limit, the condition is never met, and Trial Control does not progress. Conditions Based on a Trial Control Variable A condition based on a Trial Control variable is essentially the comparison between a Trial Control variable and a value, another variable, or a formula at the time the condition becomes active and is evaluated. - In the Components pane, under Conditions, double-click Trial Control variable or click the button next to it. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Conditions (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-conditions-continued-ZoT Chapter: EthoVision XT TTL Port Tester - Button 1/2 Presses. To base your condition on the number of presses of button 1 or 2 given since the activation of the condition. You can select either >= N, <= N, or = N. Enter the value N in the box. - Is Button 1/2 Pressed? To base your condition on whether the button 1 or 2 is currently pressed. Select true or false from the list below. - Is Light 1/2 On? To base your condition on whether the light 1 or 2 is currently on. Select true or false from the list below. Beam Controller - Beam 1/2 Breaks. To base your condition on the number of beam breaks for beam 1 or 2 since the activation of the condition. You can select either >= N, <= N, or = N. Enter the value N in the box. - Is Beam 1/2 Broken? To base your condition on whether beam 1 or 2 is currently broken. Select True or False from the Signal value list. - Is Cue 1/2 On? To base your condition on whether the cue 1 or 2 is currently on. Select true or false from the Signal value list. Activity Wheel Counter - Quarter Cycles. To base your condition on the number of quarter cycles since the activation of the condition. You can select either >= N, <= N, or = N. Enter the value N in the box. Custom Hardware Device This includes the illuminated shelter. - Input 1/2 L/H -> H/L Count. To base your condition on how many times there has been a transition from High to Low (or vice versa) in input 1 or 2 during the time t-1 to t, where t is the sample time when the condition is evaluated. Choose the option that applies, select either >= N or <= N. Enter the value N in the box. This option lets you create a condition based on events (transitions) in the signal, no matter when they happen during the sample time. - Is Input 1/2 High/Low? To base your condition on whether the current state of input 1 or 2 is High or Low at the sample time when the condition is evaluated. Select the option that applies, and then either true or false. - Is Output 1/2 High? To base your condition on whether the current state of output 1 or 2 is High at the sample time when the condition is evaluated. Select the option that applies, and then either true or false. This option evaluates the state of the signal (High vs Low) at the sample time when the condition is evaluated. If a quick transition High -> Low -> High occurs within the sample interval, this is not noticed; the state at the sample time is still High. Counts vs. Signals: Effects on Conditions Consider the two conditions based on the same input (for example Input 1): - Is the number of transitions H->L >= N? - Is the state of the signal Low? There is a fundamental difference between the two conditions. In the first condition, the software counts the number of transitions from High to Low during the sampling interval (that is, from t-1 to t). The condition may become true or stay false for sample t, depending on that value. In the second condition, the signal is evaluated at time t, that is, at the end of the sampling interval. If short transitions occur from High to Low to High again, the Low signal is not detected by this condition, because the signal is still High at time t. Example Cases The following cases illustrate how two conditions which may seem equivalent can give different results. The signal in each case represents the input from a hardware device, and the sample points represent evaluations in EthoVision XT: - The signal changes from High to Low. Both conditions are true at the time of evaluation. - The signal changes from High to Low to High within the sample time. The instance of Low is not detected by the condition based on the signal (Is Input Low?), because the signal value at the time of evaluation is High. - Similar to case 1. - Similar to case 2. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Conditions (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-conditions-continued-b2W Chapter: EthoVision XT Conditions (Continued) segment of the track, because it refers to the state of a current sample, not a duration. In that case the subject is out of the zone, so the current value of In Zone is "false". However, the condition won't be met in the period of missing samples because EthoVision does not know the current state of the subject. The next sections contain information on each dependent variable. We assume that the Condition window is open on your screen. Effect of the Statistics Used When a condition is evaluated (and therefore may or may not be met) also depends on the statistic chosen. - For Current, the condition is evaluated at the same sample time as when it is activated. - For all other statistics (like Frequency, Current duration, etc.), it is evaluated at least one sample after the condition is activated. This depends on when the first value available for comparison occurs after the activation of the condition. - When using Velocity and Distance, it takes one sample. - When using Heading and In Zone, it takes two samples. - When using Turn Angle and Angular Velocity, it takes three samples. Conditions Based on Behaviors Scored Manually Use this kind of conditions to let EthoVision XT carry out an action when the subject performed a behavior you scored manually. For example, in a social interaction test, to stop tracking when the subject attacked three times, or when the duration of Intimidation lasted more than 30 seconds. - In the Components pane, under Conditions, double-click the name or click the button next to the manually scored behavior you want to base the condition on. Tip: If you do not see the variable name, click the More button. - The Manual Scoring Condition window opens. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). - Under Condition is met when, click the Settings button. If the behavior is of the type Start-Stop or Mutually Exclusive, choose the behavior to base the condition on, for example Rear or Not Rear. - In the Actors tab, select the Subjects to which the condition applies. If the Actors tab also contains the Body points options, select one or more body points of the subjects selected above. Click OK. - Under Condition is met when, select the Statistic you want to use. Common cases of Statistic for manually scored behaviors: - Current. For a condition that is met when the behavior at the current sample is true or not true. This statistic is available for Start-Stop and Mutually Exclusive events. - Frequency. For a condition that is met when the behavior occurred a number of times. - Cumulative Duration. For a condition that is met when the animal has shown the behavior for a specific time since the activation of the condition. This statistic is available for Start-Stop and Mutually Exclusive events. - Current Duration. For a condition that is met when the animal has shown the behavior continuously for a specific time. This statistic is available for Start-Stop and Mutually Exclusive events. - Latency to First. See the EthoVision XT Help for more information. For more information on manually scored behaviors, see the EthoVision XT Help. Conditions Based on Hardware Devices Use this kind of conditions to check the status of hardware devices (pellet dispensers, lickometers, etc.) and have EthoVision take actions when the conditions are met. - In the Components pane, under Conditions, click the button next to the hardware device you want to base the condition on. - The Hardware Condition window appears. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). - Under Condition is met when, select the Template device you want to use. A template device represents a group of devices of the same type, one for each arena. - Under Signal to check, select the criterion that forms the condition. - Under Signal value, select the value of the criterion in order for the condition to be met. - Click OK. Insert the Condition box in the appropriate position in the rule. Hardware devices are not defined for each arena separately. If you have a setup with multiple arenas, it is assumed that each arena has the same type of device. The name in the device list is the generic name valid for all arenas. The condition will be evaluated for each arena separately. If the device type is not listed under Conditions, it means that it is not yet recognized by EthoVision XT. Pellet Dispenser - Number of drops. To base your condition on whether more/less than N food items have been delivered since the activation of the condition. Choose >= or <= and enter the value N in the box. - In error state. To base your condition on whether the pellet dispenser is in error state, that is, when it can no longer drop any pellet (this happens when there are no pellets anymore in the feeder). Choose between true (error) or false. Example: Have EthoVision XT give a sound signal when the feeder has run out of pellets. Lickometer - Duration of licks. To base your condition on the (total) duration of licks since the activation of the condition. Enter this time in the box. - Number of licks. To base your condition on the number of licks since the activation of the condition. You can select >= N, <= N or = N. Top Unit of PhenoTyper Choose the option under Signal to check to base your condition on whether a sound or light signal is given since the activation of the condition. For Top Unit (NeuroBsik), use Is Fsel-1/2 on/off or Is Vol-1/2 on/off to base your condition on the value of frequency or volume specified by one input. Since the frequency and volume are specified by two inputs, you must define two conditions, one for input 1 and one for input 2. Combine the two conditions with an operator of type All. Note: Neuro-Bsik is a consortium of eleven Dutch Neuroscience research groups and two companies including Noldus. The consortium aims to contribute to the battle against brain disorders by developing novel mouse models for brain disorders. For this project, Noldus has developed a special Top Unit of the PhenoTyper cage that can produce ultrasound stimuli. For more information, browse to www.neurobsik.nl. For more information, see the PhenoTyper - EthoVision XT 18 - Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Conditions (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-conditions-continued-M1m Chapter: EthoVision XT Conditions (Continued) Case Descriptions - Case 2. The subject enters the zone after the condition becomes active, but at a time less than L. The condition is NEVER met because the latency is smaller than L. - Case 3. The subject enters the zone after time L. This means that the latency of the first In zone is greater than L. The condition is met at that time. - Case 4. The subject never enters the zone. The condition is NEVER met. - Case 5. The subject enters the zone at a time less than L, then exits the zone, then enters again at a time greater than L. The latency of the first In zone state is less than L, thus the condition is NEVER met, no matter how many times the animal enters the zone. As you can see there are many cases in which the condition is never met, including Case 5, which is due to the fact that only the first instance of In zone is taken under consideration. Subjects in a Condition Select the Subjects - In the Condition window, click the Settings button. In the variables properties window, click the Actors tab. In the Actors tab, you select the actors of the behavior. - Under Select, select the subject you want to base your condition on. If your condition is based on social interactions, select the focal subject in the Actors tab and the other subjects in the Receiver tab. Do so also for dyadic interactions (Subject 1 under Actors, Subject 2 under Receivers). For dependent variables with discrete values like In zone, Movement, Mobility, Elongation, Proximity, Body contact, and Relative Movement, you can base your condition on the state of multiple subjects at the time the condition is evaluated. If you select two or more subjects, select one of the two options from the list immediately below the Select box: - All Selected Subjects. The state selected in the dependent variable properties window must be the same for all the actors simultaneously, in order for the condition to be met. - Any Selected Subjects. The state selected in the dependent variable properties window must be true for at least one actor in order for the condition to be met. - If the Actors tab also contains the Body Points options, select one or more body points of the subjects selected above. - For the dependent variables of social interaction, a Receivers tab is also available. Click this tab and select the subjects that you have not selected under Actors. - Click OK to confirm your selection. You return to the condition window. Notes and Examples Example of choosing All Selected Subjects. The researcher wants to define an In zone condition that is met when Subject 1 and Subject 2 have been in a zone simultaneously for at least one minute. Solution: In the Condition window, select Cumulative Duration as Statistic and enter >= 60 s. Click Settings and select the zone you require, then click Actors and select Subject 1 and Subject 2, finally select All Selected Subjects. Example of using Any Selected Subjects. The researcher wants to define a Distance to zone condition that is met when one of the two subjects is at less than 5 cm from a novel object. Solution: In the Condition window, select Current and enter <= 5 cm. Click Settings and select the novel object zone, then click Actors and select Subject 1 and Subject 2, finally select Any Selected Subjects. Example with Actors and Receivers. The researcher wants to define a condition that is met when the nose point of Subject 1 has been close to at least one body point of Subject 2 for more than one minute. Solution: Click the button next to Proximity and in the Condition window, select Cumulative Duration and enter the required value. Click Settings, then: - In the Actors tab, select Subject 1 and de-select Subject 2. Under Body Points, select Nose-point only. - In the Receivers tab, select Subject 2 and de-select Subject 1. Under Body Points, select all points and then Any Selected Points, since the condition must be met when Subject 1 is in proximity of at least one of Subject 2's body points. When Is a Condition Met? Dependent variables are calculated for each sample. When a condition based on dependent variables is met depends on a number of factors. Effect of Outliers and Track Smoothing Dependent variables used in conditions are not smoothed or filtered using the Lowess filter or the Minimum Distance Moved as they can be for data analysis. This means that outliers, nose-tail swaps, or even subject identity swaps can have severe effects on whether and when a condition is met. If a condition of type In zone is defined which specifies Frequency of In zone A >= 1, then the condition is met the moment that the subject is wrongly detected in zone A, assuming that the condition box was active. Track noise reduction may solve the problem. In the Detection settings, click Advanced and under Smoothing set Track Noise Reduction to On. This applies an online smoothing effect as the subject is being tracked. Note that this change in the track cannot be reversed afterwards. Effect of Missing Samples Missing samples can also cause Trial Control to react later. For example, an In zone condition is met only when valid samples are found within the specified zone. If a condition of type In zone is defined which specifies Current of In zone A = true, then the condition is met later than it would be if there were no missing samples. If a condition of type In zone states "Current duration of not in zone longer than 1 s" (assuming a sample rate of 5/s, so 5 samples make up 1 second), then the condition does not become true, because there are only 4 samples for which the state "not in zone" was true. Similarly, the condition Current value of In zone A = false may be met in the first missing sample period. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Conditions (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-conditions-continued Chapter: EthoVision XT Conditions (Continued) Creating Conditions Based on a Trial Control Variable Tip: If you do not see Trial Control Variable, click the More button. - In the Trial Control Condition window, under Name, enter a Condition Name. - Under Condition is met when, select the Trial Control variable from the first list. If the variable has not been defined yet, define it first by clicking Variables. - Select the comparison operator (=, >, etc.) from the second list. - Do one of the following: - To compare the Trial Control Variable with another variable, or a numerical value, select that variable/value from the third list. - To compare a Trial Control variable with a formula, click the double-arrow button and select the operator, then complete the formula in the next list. Important: Be careful using the operator =. The comparison only takes place when the condition box becomes active. If the variable is updated in other boxes, it may be that this condition box is activated too early or too late. For example, if the condition is met when A = 4 and an Action box sets the value to A = 5 before the condition box is activated, then the condition is never met. Rather use >= or <=. - Insert a Comment (optional) and click OK. - Insert the Condition box in the appropriate position in the rule. For information on how to insert a Trial Control box, see the EthoVision XT Help. Creating Conditions Based on a Dependent Variable - In the Components pane, under Conditions, double-click the name or click the button next to the dependent variable the condition is based on. For details about dependent variables, see the dependent variables section. Tip: If you do not see the variable name, click the More button. Note: The following variables are not available for creating conditions: Acceleration state, Activity state, and behaviors scored with Behavior recognition. - In the condition window, under Name, enter a Condition Name. Under Comment (at the bottom), enter a description (optional). - Under Condition is met when, from the Statistic list choose the statistic on which the condition is based. See Selecting the Statistic below. - Click the Settings button. A window opens with the variable properties. - If you track multiple subjects in one arena, see also the Selecting the Subjects section. - When finished, click OK in the variable window. - From the list next to is:, choose the comparison >=, =, or <= to specify whether the statistic must be greater than, equal to, or smaller than a value x. Enter this value in the box. - If you have chosen Current as a Statistic for a discrete variable, choose between true and false. True means the current state must be the one chosen in Settings; False means the current state must not be the one chosen in Settings. - Click OK. Insert the Condition box in the appropriate position in the rule. For information on how to do this, see the EthoVision XT Help. Note: The Body Points tab in the variable properties window is only available if your experiment is set to Nose-point, center-point, and tail-base detection. Selecting the Statistic - Current: The value of the variable in the current sample. For example, if a condition based on Velocity is evaluated at sample n, Current is the velocity calculated for sample n. If you want to base the condition on the average velocity from the time of activation of the condition to the current time, choose Mean. - Total: The total value of the variable (only for continuous variables like Distance or Velocity). This is the sum of all values of the variable up to that time. - Mean: The mean value of the variable (only for continuous variables like Distance or Velocity) up to that time. - Minimum, Maximum, Standard Error, Standard Deviation, and Variance: These statistics are normally less obvious to use in a condition. For example, if you select Standard Error for Distance moved, the program calculates the standard error of all distance values calculated between consecutive samples of the track up to that time. The condition is met when the standard error is greater than, equal to, or less than the value specified. - Frequency: The number of occurrences up to that time. This statistic is available for discrete (state) variables like Movement, and count variables like Rotation and Zone transition. Choosing >= or <= for frequency only makes sense when combined with another condition. - Cumulative Duration: The cumulative duration of a state from the start of tracking up to that time. You choose the state when clicking the Settings button. This statistic is available for discrete variables. - Current Duration: The duration the animal has been in a state (for example, in a specific zone or Mobile), taking only the current uninterrupted interval into account. You choose the state when clicking the Settings button. This statistic is available for discrete variables. - Latency to First: The time from the activation of the condition to the first occurrence of the state of the discrete variable (for example, In the zone becomes true for the variable In zone), or count variables like Rotation or Zone transition. You choose the state when clicking the Settings button. - A condition like Latency >= L or Latency <= L does not mean that the condition is met at time L if the first state or occurrence does not occur within that time. The program first calculates when the first state or occurrence occurs, and then compares this with L. - Case 1: The subject is already in the zone when the condition becomes active. The condition is never met because the latency of the first In zone state is 0, which is smaller than L. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Control Hardware Devices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-control-hardware-devices Chapter: EthoVision XT Devices Supported in EthoVision XT - Noldus Pellet Dispenser - Noldus Pellet Receptacle - Noldus Lickometer - Top Unit of PhenoTyper 1 and PhenoTyper 2 - Noldus DanioVision Observation Chamber - Noldus PhenoWheel - Med Associates Activity Wheel Counter and Activity Wheel Brake - Noldus Backlight Unit with White Light - Beam Controller for the Noldus Mouse Feeding Monitor - Third-party and custom hardware devices. This includes any device that can be controlled with a signal of TTL type. For example: - The Illuminated Shelter - The Ugo Basile Fear Conditioning System - The Prizmatix Optogenetics Setup - The Inscopix nVista Calcium Imaging System - Med Associates devices - Third-party and custom hardware devices controlled through a COM port, for example an Arduino board. Support for this type of device is limited. - TTL Port Tester Additional Manuals - For PhenoTyper and Noldus devices, see the PhenoTyper - EthoVision XT 18 - Reference Manual and PhenoTyper - EthoVision XT 18 - Service Manual. - For the Ugo Basile Fear Conditioning System, the optogenetics setup, and the Inscopix Calcium Imaging Systems, see the EthoVision XT 18 - Application Manual. - For the DanioVision Observation Chamber, see the DanioVision DVOC-0041 - Reference Manual. Basic Requirements - You must have EthoVision XT with the Trial and Hardware Control Module. - You must have the Noldus USB-IO box or the Noldus Mini USB-IO box connected between your PC and the devices. - All hardware devices must be connected through an Ethernet straight-through cable with RJ45 connectors. - In EthoVision XT, you must define the devices you want to use in the Experiment Settings. Next, assign devices to arenas, and finally program Trial Control with hardware-based actions and conditions. Time Accuracy The accuracy of sending or receiving signals from the USB-IO box is 40–120 ms, depending on factors such as the camera frame rate and the Windows priority scheduling. Terminology - Physical Device: A single device identified by an ID number or code. Each physical device must be associated with a specific arena in your hardware configuration. For example, PD03 for a Pellet Dispenser. - Device Name: A generic name that indicates the same type of physical device used in one or more arenas. The device name is valid for all arenas defined in your Arena Settings, even if a particular arena has no physical device associated with it. It is recommended to use generic names such as Pellet Dispenser, Running Wheel, or Yellow Light. Work with Multiple Devices EthoVision XT supports the use of one or two USB-IO boxes and one Mini USB-IO box. Important: It is recommended to test a specific combination of devices before carrying out actual trials. Whether a combination of devices works also depends on the timing of the commands. For example, controlling 12 pellet dispensers may work if the pellets are dropped at different times, but dropping 12 pellets at exactly the same moment will not work. When working with two or more USB-IO boxes, see the Use Multiple USB-IO Boxes section. Tested Configurations The following configurations were tested separately: - Four PhenoTyper 1 Top Units + 1 Top Unit Interface (SDI device) - Sixteen PhenoTyper 1 Top Units + four Top Unit Interfaces - One USB-IO box with four Pellet Dispensers (TTL device) - One USB-IO box with four TTL Port Testers (TTL device) - One USB-IO box with four PhenoWheels (SDI device) - One USB-IO box with four Lickometers (SDI device) - One USB-IO box with four IR Beam Controllers for the Mouse Feeding Monitor (TTL device) - Two USB-IO boxes, each connected to eight TTL Port Testers (TTL devices) - DanioVision: White Light and Tapping Device (events occurring every 5 minutes) All tests lasted 30 minutes. Typical protocols included switching of lights and buzzers on/off and dropping a food pellet when the subject entered a zone, or at regular intervals. When testing two USB-IO boxes simultaneously, trials lasted one hour. All tests were carried out with a Dell Precision 3680 desktop computer with Windows 11. Devices in Multiple Arenas If you work with multiple arenas, those arenas are expected to have the same type of devices. Trial Control is applied to each arena independently. For example, if you define an action Drop a Pellet to be triggered when a condition is met, that action is executed on the pellet dispenser associated with the arena in which the condition is met. An arena may contain more than one physical device of the same type. In this case, you must define unique device names in the Arena-Hardware Mapping window that can be associated with the physical devices. For example, if each cage has two pellet dispensers, you must define two device names, such as Pellet Dispenser Left and Pellet Dispenser Right. Connect the Hardware Devices Before defining a hardware configuration, close EthoVision XT. - Connect the power cord to the 24V In socket on the USB-IO box or Mini USB-IO box rear panel. Connect the other end of the power cord to the mains socket. - Connect the USB socket on the rear panel of the USB-IO box or Mini USB-IO box to the EthoVision computer using a USB cable with one connector of type A (computer) and one connector of type B (USB-IO box). - Connect the hardware device to the first available port of the USB-IO box or Mini USB-IO box using the RJ45 cable. Depending on the device you want to connect, choose the port located on: - TTL Control (front panel of the USB-IO box): For devices controlled with TTL logic (One/Zero signal type), for example the Pellet Dispenser, the TTL Port Tester, or any custom hardware devices working with TTL logic. - SDI Control (rear panel of the USB-IO box): Special Device Interface, for devices controlled with a serial data stream, for example the Lickometer, PhenoWheel, and the PhenoTyper Top Unit Interface. - Repeat the previous step to connect other devices. - To test the device, follow the steps in Setting the Port Connections and Assigning Devices to Arenas. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Control Hardware Devices (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-control-hardware-devices-continued-8Ek Chapter: EthoVision XT Control Hardware Devices If the hardware action follows a condition based on In Zone, or Zone Transition, the action may be carried out repeatedly if the animal walks along the border of a zone. For example, if the detected body flickers on the border of two zones, and you want to drop a pellet every time the zone border is crossed, many pellets will be dropped. If this is the case, open the Detection Settings and click Advanced, then under Smoothing set Track Noise Reduction to On. This smooths the track during acquisition, which means that the track is altered. This cannot be reversed afterwards. NeuroBsik Top Units: Ultrasound Frequency and Intensity To produce ultrasound of specific frequency and intensity, define two actions that, when combined, specify the frequency you require. - 4 kHz: Fsel-1 off, Fsel-2 off - 8 kHz: Fsel-1 off, Fsel-2 on - 16 kHz: Fsel-1 on, Fsel-2 off - 32 kHz: Fsel-1 on, Fsel-2 on Next, define two actions that, when combined, specify the volume you require. - 25 dBm: Vol-1 off, Vol-2 off - 50 dBm: Vol-1 off, Vol-2 on - 75 dBm: Vol-1 on, Vol-2 off - 100 dBm: Vol-1 on, Vol-2 on Combine the four actions with an operator of type All, and then add a Time condition followed by a Sound On action. Send Information to a Device Through a COM Port EthoVision XT can also communicate with devices like Arduino boards through a serial (COM) port. Numbers are sent out as an ANSI string. Commands are of the following types: - Long Format: For example, number 1234 is sent as 1234. - String Type: Either normal or hexadecimal. To send hexadecimal strings, put 0x in front of it. For example, 0x6261 sends two bytes: first 0x61, then 0x62. Signals must be of long or double type. They must be delimited with CR (carriage return, \r) and LF (new line, \n) syntax. For example, to send the command $1DO0001, enter the string $1DO0001\r\n. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Control Hardware Devices (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-control-hardware-devices-continued-hx1 Chapter: EthoVision XT Control Hardware Devices (Continued) - Under the Arena name, select the physical device you want to test, and click Test. A new window appears. - Depending on the hardware device: - For any device that can receive a signal from and send it back to the computer (examples are the Pellet dispenser, Activity wheel break, or Backlight unit white light): Select the appropriate action, click Test and check that the action has been taken. You can also view the result in the Test window — for example, the Number of drops has increased by 1. - For any device that can only send a signal to the computer, not receive any (examples are the Lickometer, PhenoWheel, or the Activity wheel counter): Trigger the device manually and check the result in the Test window. - For the Top Unit: From the Command list, select the action you want to test, click Test and check the result in the PhenoTyper. - For the Custom Hardware Device (for example, the Illuminated shelter): From the Command list, select the action you require, click Test and check that the device has been activated correctly. - For the TTL Port Tester: Use this device to check the two-way communication for a specific port. Press a button on the device and check the result in the Test window. From the Command list, select a command and click Test. Check the result on the tester box. - When ready, click OK. Notes - Data from the Lickometer and the PhenoWheel are read out in regular time intervals. For the Lickometers currently sold by Noldus IT, the time interval is two seconds, and for the current PhenoWheel it is 60 seconds. - For all devices: The fact that a signal is given correctly in the Test window but you do not see the response from the device could mean that the device is not functioning (for example, a lamp is broken). - For the Pellet dispenser: If the Test window shows error state = true, the pellet dispenser is not connected to the IO-box, or the food pellets are no longer available. - For the Lickometer: Number of licks and Duration of licks is the cumulative number and duration of licks since the Test button has been clicked, respectively. The device is read out at regular time intervals. At the end of the interval the number and duration of licks is displayed very briefly. Important: If you realize that the values of Number and Duration of licks given by EthoVision XT are much higher than expected, close EthoVision XT, disconnect and re-connect the IO-box to the computer and then restart EthoVision XT. - For the Top Unit, TTL Port Tester and Custom Hardware Device: You can also view the result of the action to be tested in the Test window. Locate the Signal you want to test and verify that Value changes from false to true or vice versa. For the TTL Port Tester, you can also press a button and check the counts of presses for that button. Program Trial Control with Hardware Devices In the Trial Control Settings, you can define: - Conditions based on a hardware device. For example, as soon as the cumulative duration of licks equals 1 minute, stop recording. - Actions on a hardware device. For example, have the Pellet dispenser drop a pellet, or switch on the PhenoTyper's white light. Define an Action on a Hardware Device - In the Components pane, under Actions, double-click the button next to the name of the device type you want to control, or click the button next to it. The Hardware Action window appears. - Under Name, enter an Action name. Under Comment (at the bottom) enter a description (optional). - Under Action to perform, select the Device name you want to use. The names listed there are defined in the Arena-Hardware mapping window. - From the Action to perform list, select the action that the device must take. - Click the Test button to check the hardware action. Click the Reset button to reset all hardware. - Click OK. Insert the Action box in the appropriate position in the rule. For information on how to do this, see the EthoVision XT Help. What You Need - One of the following hardware interfaces: the Noldus USB-IO box, the Noldus Mini USB-IO box, or the DanioVision Observation Chamber. - You can control the Ugo Basile Fear Conditioning system without a hardware interface. See the EthoVision XT 18 - Application Manual. - The hardware interface software Noldus HardwareInterface USB-IO box version 5 (for the USB-IO box/Mini USB-IO box/DanioVision). This software is automatically installed when you install EthoVision XT. Tip: To check what is currently installed on your EthoVision XT computer, see Windows Control Panel > Programs and Features / Add or remove programs. General Notes - For general information on programming trial control, see the relevant section in the documentation. - The items listed under Actions are the Device names selected in the Arena-Hardware mapping window. If the device name is not listed under Actions, check that the port connections are set correctly and that the devices are mapped in the arenas. - If you have a setup with multiple arenas, it is assumed that each arena has a physical device under that Device name. An action is taken in each arena separately, when the accompanying condition is met in that arena. - Actions like Light on and Sound on result in the light or sound device being activated for an indefinite time. Remember to add an extra action that switches that light or sound off. The two actions should be separated by a condition. For example: Action Light on > Condition Wait 1 s > Action Light off. - If you define a sequence of multiple actions on the same device, these are probably evaluated at the same sample time. This happens because the computer is fast enough to analyze multiple Trial Control boxes in one sample. To make sure that actions are taken in sequence, add a Time condition between actions so that the program waits for a short time (for example, 0.1 s) before executing the next action. - You can also activate a hardware device like a Pellet dispenser manually. In the Manual Scoring Settings, define a fictitious behavior (for example, Pellet) and select the type Point event. In the Trial Control Settings, create a sub-rule that contains the following conditions and actions: [Rule Begin] > [Condition: Frequency (Pellet)>=1] > [Action: Drop pellet] > [Rule End]. During acquisition, every time you score Pellet, the Drop pellet action will be triggered. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Control Hardware Devices (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-control-hardware-devices-continued-QUB Chapter: EthoVision XT Set the Port Connections for PhenoTyper 1 For PhenoTyper 2, see the PhenoTyper - EthoVision XT 18 - Reference Manual. - Locate the SDI Port 13. Under Device type select Top Unit Interface. This expands the SDI Port to four extra rows. - For each of the four rows, under Device type, select: - Top Unit (Standard) for standard PhenoTypers - Top Unit (NeuroBsik) for PhenoTypers of the Neuro-Bsik type - Top Unit Tester (PTTB-002x) only when you want to use the Top Unit Tester instead of the actual PhenoTyper Top Unit, for testing purposes - Under Device ID for the rows appended, enter the name of the physical Top Units. - When ready, click OK. Next, assign the Top Units to the arenas (see the next section). To set the port connections for other groups of PhenoTyper 1, you must adjust the jumpers for the ports you are going to use. See the PhenoTyper - EthoVision XT 18 - Service Manual. Set the Port Connections for COM Ports Prerequisite: Install the Serial interface for EthoVision XT. To do so: - Close EthoVision XT. - In the EthoVision XT 18 full installation package, open the folder Drivers and Tools. Open the folder HardwareInterface SerialPort and double-click HardwareInterface_SerialPort_[version number].msi. You can download the EthoVision XT 18 full installation package from my.noldus.com. - Restart EthoVision XT. Define the COM port in EthoVision XT: - Connect the device to the EthoVision XT computer. - Open the EthoVision XT experiment and choose Setup > Experiment Settings. - Under Trial Control Hardware, select Use of Trial Control Hardware, and click the Settings button. Select COM Ports in the Hardware Interface window and click OK. - In the Devices window, click Add and add one or more COM ports that you want to use. - After acquiring one or more trials, you cannot add COM ports. First delete the trials, then repeat the steps above. - To know which COM port should be added, disconnect the USB cable and check in the Windows Device Manager under Ports (COM & LPT) which item has disappeared. - To check the port settings, select a COM port currently connected to a device and click Settings. The following settings should work fine: Baud rate 9600, Data bits 8, Parity None, Stop bits 1, Flow control None. When ready, click OK. - Click OK in the Devices window. Next, assign the COM ports to the arenas (see the next section). Assign Devices to Arenas For experiments with one arena only, hardware devices are automatically assigned to the arena. You can skip this section and continue with testing the hardware devices or programming trial control with devices. For multi-arena experiments, follow the procedure below. Assuming that you have defined your arenas in the Arena Settings, do the following: - In the Experiment Explorer, click the Arena Settings in which the arenas you want to use are defined. - In the Arena Settings window, click the Arena - Hardware Mapping button. The Arena - Hardware Mapping window appears. - Click Add device. A new row is appended to the table. - From the Device type list, select the type of device you want to assign. Select Custom hardware if the device type you are using is not listed. - Under Device name, a default name is displayed. We advise you to enter a new name that can be easily recognized, especially if you have more devices of the same type in each arena. - Example: Each arena is provided with two pellet dispensers of the same type. Enter Pellet Dispenser Left under Device name and select the pellet dispensers to be placed on the left side of each arena. Then click Add device again and enter Pellet Dispenser Right under Device name, then select the pellet dispensers to be placed on the right side of each arena. - Under the arena name, select the physical device that you want to assign to that arena. Assign the other devices to the remaining arenas. - Repeat the previous steps to add a new set of devices. - When finished, click OK. Notes - To remove a set of devices, select the corresponding row in the table and click the Remove device button. - If your setup includes two or more devices of the same type in one arena, make sure that you select the physical devices that belong to the Device name specified under Device name. - If you cannot select any physical device under the arena names, check that the Device type selected for that row is specified in the Port Device Mapping. - The Arena - Hardware Mapping settings are valid for all Arena Settings in your experiment. They are added automatically to every new Arena Settings. Assign Arenas to the PhenoTypers - Click Add device in the Arena - Hardware Mapping window. - Under Device type, select: - For PhenoTyper 1: Top Unit (Standard) - For PhenoTyper 2: Top Unit Light (NOCA-TU1x) - Under Device name, enter a generic name (for example, Top Unit) or accept the default name. You will see the Device name again in the Trial Control Settings. - Under Arena n, select the physical device (Top Unit) associated with that arena. - Repeat the previous step to assign the Top Units to the remaining arenas. The physical devices placed in the different arenas are now linked to a generic Device name. You will use that name in the Trial Control Settings to create actions and conditions based on those devices. Test the Hardware Devices - Make sure that the hardware devices are connected to the EthoVision computer via the USB-IO box or the Mini USB-IO box. - In the Experiment Explorer, click any Arena Settings. - In the Arena Settings window, click the Arena - Hardware Mapping button. The Arena - Hardware Mapping window appears. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Control Hardware Devices (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-control-hardware-devices-continued Chapter: EthoVision XT Control Hardware Devices Requirements for PhenoTyper Control To control one or more PhenoTypers, you must have: - For PhenoTyper 1: the USB-IO box and the Top Unit Interface box, which functions as an interface between the USB-IO box and each Top Unit. - For PhenoTyper 2: The USB-IO box. For more information, see the PhenoTyper - EthoVision XT 18 - Reference Manual. Connect Third-Party Devices For third-party devices you may need additional cables and adapters between the Noldus USB-IO box / Mini USB-IO box and those devices. For example: - For the Inscopix camera system, you need the Optical Isolated Interface PTISO-00x0. - For Med Associates devices and other systems with 28V inputs, you need the TTL to 28V interface. See the PhenoTyper - EthoVision XT 18 - Service Manual. You need this converter when you want to send signals to the Med Associates device (for example, a pellet dispenser). For input devices, for example a lever switch, contact Noldus. - To connect a custom device like a LED lamp or a simple switch, contact Noldus if you need special adapters or custom solutions. - To connect a device through a Serial interface/COM port you can use USB connections. Make sure that at least one COM port is available. To identify the correct COM port number, open the Windows Device Manager. Briefly disconnect the USB cable and check in the Device Manager under Ports (COM & LPT) which item has disappeared. That is the COM port number you need to use in the next step. Set the Port Connections Prerequisites - Connect all devices to the EthoVision PC, via the USB-IO box or Mini USB-IO box. - When working with two or more USB-IO boxes, make sure that all IO-boxes are connected to the PC. To Set the Port Connections - Start EthoVision XT, and open your experiment or create a new one. - Choose Setup > Experiment Settings. - Under Trial Control Hardware, select Use of Trial Control Hardware, and click the Settings button. - Select the interface you use: - Noldus USB-IO Box - Noldus Mini USB-IO Box - One of the DanioVision DVOC versions Tip: To find out what type of USB-IO box you have, check the label on the bottom side of the box: PTIO-002x (for the USB-IO box) or PTIO-003x (for the Mini USB-IO box). Other options (not the focus of this section): - For the Ugo Basile Fear Conditioning System, select the Ugo Basile F.C. Controller. For more information, see the chapter The Fear Conditioning Test in the EthoVision XT 18 - Application Manual. - For custom devices controlled through serial ports, select COM Ports. This option is only available if you install the appropriate software. - The Device Configuration window appears, listing the available ports of the interface device: TTL Port 1, ... and SDI Port 1, ... (the latter only for the USB-IO box and the Mini USB-IO box). You can assign one physical device to each row. - If you have connected multiple USB-IO boxes, select one from the list at the top. - In the Ports column, locate the first available port of the correct type: - Locate a TTL Port and click under Device type to view the list of devices. Select the device that applies. - Locate an SDI Port and click under Device type to view the list of devices. Select the device that applies. Use SDI ports to connect the Lickometers and the PhenoTyper's Top Unit Interface. If you select the latter, four additional rows appear below the option. Select the PhenoTypers' Top Units. - From the Device type list, select the type of device that is (or will be) connected to that port. - In the Device ID field, enter the name of the physical device that should be connected to that port. - Repeat steps 5–7 for other devices, until they are all assigned to a port of the IO-box. - Repeat the steps for the next USB-IO box. - When ready, click OK. You return to the Experiment Settings screen. Proceed with assigning devices to the arenas. Notes - The number next to IO-box is the identification number of the IO-box set by the manufacturer. You cannot change this number. - You must set the port connections only the first time you connect them. - The port connection settings are at experiment level, and are applied to all your Trial Control Settings. Once you acquire at least one trial, the settings become locked and you can no longer change them. If you need to add devices, create a new experiment or remove the acquired trials. - If you plan to create several experiments with the same set of devices, you can use an experiment as a template experiment with the hardware settings selected but containing no trials. To create a new experiment from a template experiment: from the File menu, select New template experiment and then Use a custom template. Next, open the experiment you want to use as a template and use the new experiment to acquire data. - The Device ID is by default the name of the Device type plus a progressive number (1, 2, ...). It is advised to enter a name that you can recognize easily in your setup. - Under Device type, select TTL Port Tester if you want to test the functionality of a TTL port. - Under Device type, select USB-IO monitor if you want to test the connection in the USB-IO box. - When you select a device type, that device type is added to the file Hardware Setup.xml, which is stored in the experiment folder under ...\Configuration Files\Add-ins\Hardware. The file used depends on the interface: - {A8DA8F3E-7EA3-4629-8327-9D21C90FB3ED} — USB-IO box - {0308106B-1EBE-4620-B00D-396ABEBBC219} — Mini USB-IO box - {3AA139A2-4737-4D6D-BF7B-0153CFD4D302} — Ugo Basile FC Controller Use Multiple USB-IO Boxes You can connect multiple Noldus USB-IO Boxes to one EthoVision XT computer to control multiple devices simultaneously. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Index URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-index Chapter: EthoVision XT Index A - Relative – Any operator - Applying Trial Control - Arduino Board - Arena - Hardware Mapping - TTL Tester - Arena Settings - Adding TTL Tester - Assigning Arenas to PhenoTypers - Assigning Hardware Devices to Arenas B - Backlight Unit - Base Version of EthoVision XT - Bat Extension - Batch File for UltraVox XT - Batch Files - Beam 1-2 Breaks - Beam controller condition - Beam Controller - Condition based on - Becomes Active - Becomes False - Becomes Inactive - Becomes True - Behavior - Condition based on - Learning - Scored manually - Behavior Recognition - Behavioral State - Condition based on - BNC Connectors - Body Angle - Condition based on - Body Angle State - Condition based on - Body Contact - Condition based on - Body Elongation - Condition based on - Button 1/2 Pressed? - TTL port tester condition - Button 1/2 Presses - TTL port tester condition C - Calculate Statistics per Interval - Occurrence - Trial control state analysis - Calculating Statistics for TTL Tester - Checking USB-IO Box with TTL Tester - Checking When Condition Is Met - Clock Time - Sub-rule start condition - Summer/wintertime - Time condition - Time interval condition - When using video files - COM Ports - Command Line Option - Components Pane - How to use - Showing/hiding - Condition Box - Activation - Evaluation - Inactivation - Conditioning Test - Conditions - Based on dependent variable - Based on hardware devices - Based on manually-scored behavior - Based on multiple variables - Based on time - Based on time interval - Based on trial control variable - Defining - Examples - For starting/stopping the trial - Naming - Repeating a sequence - Time interval - Using - Connecting Hardware Devices - Connecting PhenoTypers - Controlling Hardware Devices - Cumulative Duration - Body angle state condition - Body elongation state condition - Defining conditions - Head directed to zone condition - In zone condition - Mobility state condition - Movement condition - Proximity condition - Cumulative Value - Hardware continuous variable analysis - Current - Acceleration condition - Activity condition - Body angle condition - Body angle state condition - Body elongation condition - Body elongation state condition - Defining conditions - Distance moved condition - Distance to point condition - Distance to zone condition - Elongation condition - Head directed to zone condition - Head direction condition - Heading condition - Heading to point condition - In zone condition - Meander condition - Mobility condition - Movement condition - Proximity condition - Turn angle condition - Velocity condition - Current Duration - Body angle state condition - Body elongation state condition - Defining conditions - Head directed to zone condition - In zone condition - Mobility state condition - Movement condition - Proximity condition - Custom Hardware Device - Condition based on D - DanioVision - Data Acquisition - Trial vs. track - Daylight Saving Time - Defining - Actions - Conditions - Trial control variables - Delay - Sub-rule start condition - When starting a sub-rule - Delay New Repeat... - Sub-rule start condition - Deleting Sub-Rules - Dependent Variables - Condition based on - Detection Determines Speed - Device Name - Devices - See Hardware Devices - Distance Moved - Condition based on - Distance to Point - Condition based on - Distance to Zone - Condition based on - Do Not Start New Repeat... - Sub-rule start condition - Dongle - See License - DOS Command - Dropping a Pellet - Duplicating Trial Control Elements - Duration - Maximum trial duration - Duration of Licks - Lickometer conditions E - Elevated Plus Maze - Endless Loop - EthoVision XT - Base version - License - Trial and hardware control module - Versions - Excel - Exporting to - Exe Extension - Executables - External command actions - Execute Once - Sub-rule stop condition - Experiment - Use as template - Exporting - Hardware log - Track data - Trial control data - Trial control settings as image - External Commands - Actions on - Command line option - Testing F - Fear Conditioning System - Fixed Ratio Schedule - Food Dispenser - See Pellet Dispenser - For Consecutive Intervals - Trial control state analysis - Formula with Trial Control Variable - Frequency - Body angle state condition - Body elongation state condition - Defining conditions - Head directed to zone condition - In zone condition - Mobility state condition - Movement condition - Proximity condition - Rotation condition - Target visiting and zones condition - Zone alternation condition - Zone transition condition - Fsel-1/2 On/Off - NeuroBsik top unit condition G - Generate a Random Value - Grid - Show/hide - Snap to - Trial control H - Hardware Commands - Analyzing - Hardware Continuous Variables - Analyzing - Hardware Devices - Assigning to arenas - Condition based on - Connecting - Controlling - Programming trial control - Testing - Hardware Interface Software - Hardware Log - Exporting - Number of key presses - Hardware Mapping - Hardware State Variables - Analyzing - Head Directed to Zone - Condition based on - Head Direction - Condition based on - Heading - Condition based on - Heading to Point - Condition based on - Hidden Zones - Effect on distance moved condition - Effect on velocity condition I - Illuminated Shelter - Image of Trial Control Settings - Image File - In Error State - Pellet dispenser condition - In Zone - Condition based on - Inactivation of Condition Box - Inactive - See Becomes Inactive - Infinite Time - Input 1/2 High/Low? - Custom hardware device condition - Input 1/2 L/H -> H/L Count - Custom hardware device condition - Inscopix Camera System - Instructions of Trial Control - How they are executed - IO-Box - See USB-IO Box - Is Beam 1-2 Broken? - Beam controller condition - Is Cue 1-2 On? - Beam controller condition - Isolated Cable J - JavaScript Variables - Jitter - Effect on velocity condition L - Latency to First - Body angle state condition - Body elongation state condition - Defining conditions - Head directed to zone condition - In zone condition - Mobility state condition - Movement condition - Proximity condition - Rotation condition - Target visiting and zones condition - Zone alternation condition - Zone transition condition - Learning Behavior - Analyzing - Levels of Sub-Rules - License - Lickometer - Condition based on - Controlling hardware devices - Testing - Light 1/2 On? - TTL port tester condition - Locked Trial Control Settings - Loop - See Endless Loop M - Makes Sub-Rule Active Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Index (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-index-continued-ges Chapter: EthoVision XT Index (Continued) T - Turn Angle - Absolute - Condition Based On - Relative U - Ultrasound - UltraVox XT - USB-IO Box - Controlling Hardware Devices - Multiple - Testing - USB-IO Monitor V - Velocity - Condition Based On - Video Files - Applying Trial Control - Visual Stimulus - Visualization - Number of Button Presses - Visualizing - Trial Control Events - Vol-1/2 On/Off - NeuroBsik Top Unit Condition W - Water Maze - Platform - Stopping a Trial - Weighted Movement From - Condition Based On - Weighted Movement To - Condition Based On - Wintertime - Without Delay - Sub-Rule Start Condition Z - Zone Alternation - Condition Based On - Zone Exit Threshold - Zone Transition - Condition Based On - Zoom In - Zoom Out - Zoom to Fit Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Index (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-index-continued Chapter: EthoVision XT Index (Continued) M - Makes Sub-Rule Inactive - Manual Event Recording – TTL Tester - Manually-Scored Behaviors - Maximum - Value of trial control variable - Trial duration - Multiple arenas - Maximum Trial Duration Pane – Showing/hiding - Mean - Acceleration condition - Activity condition - Body angle condition - Body elongation condition - Defining conditions - Distance moved condition - Distance to point condition - Distance to zone condition - Head direction condition - Heading condition - Heading to point condition - Meander condition - Mobility condition - Turn angle condition - Velocity condition - Meander - Absolute - Condition based on - Relative - Media Recorder – Running external command actions - Mini USB-IO Box - Minimum - Value of trial control variable - Missing Samples - Mobility - Condition based on - Mobility State - Condition based on - Morris Water Maze – See Water Maze - Multi Condition – Condition based on - Multiple Arenas - Maximum trial duration - Open field - Trial control - Multiple Instances of an Action - Multiple USB-IO Boxes N - N of All - Logic - Operator - Nesting - Over subjects - Over trial control states - Net Weighted Movement – Condition based on - NeuroBsik - NeuroBsik Top Unit – Condition based on - No Valid Reference - Number of Button Presses - Number of Drops – Pellet dispenser condition - Number of Licks – Lickometer conditions O - Open Field - Operators - All - Any - N of All - Re-using - With one input box - Optical Isolated TTL-IO Interface - Optogenetics Setup - OR Logic - Outliers - Effect on distance moved condition - Effect on velocity condition - Output 1/2 High? – Custom hardware device condition P - Pellet – Dropping - Pellet Dispenser - Calculating statistics - Condition based on - Controlling - Testing - Pellet Receptacle - Permutation - PhenoTyper - PhenoTyper Top Unit - Condition based on - Controlling hardware devices - NeuroBsik - Standard - Testing - PhenoTypers - Assigning arenas - Connecting - PhenoWheel - Physical Device - Pixel Change - Platform – Water maze - Playing a Sound - Port Connections - Hardware devices - PhenoTyper - Profiles – Trial control settings - Programming Trial Control – Hardware devices - Proximity – Condition based on - Pseudorandom Sequence Q - Quarter Cycles – Activity wheel counter condition R - Radial Maze – Stopping the trial - Random Time - Random Value – Trial control variables - Receivers - Distance between subjects condition - In conditions - Net weighted movement condition - Proximity condition - Relative movement condition - Weighted movement from condition - Weighted movement to - Recording Video - Applying trial control - Redo a Trial - Applying trial control - Hardware log - Re-Doing a Trial - Reference Box - Reference to a Sub-Rule - Creating - Modifying - Multiple references - Place in trial control sequence - Re-using - References - Relative Angular Velocity Condition - Relative Meander Condition - Relative Movement – Condition based on - Relative Turn Angle Condition - Remove Device - Repeat Indefinitely – Sub-rule stop condition - Repeat Per Start Condition – Sub-rule stop condition - Repeating Sub-Rules – Options - Re-Using - Operators - Sub-rules - Trial control elements - Rewards - Action leads to - After a time - Calculate number of - Conditioning test - Specify number of - Rotation – Condition based on - Rule – See Trial Control Rule S - Sample Rate – Effect on analysis - Sample Time - SDI Port – Connecting - Selecting - Statistics in conditions - Subjects in conditions - Sending a String - Sequence – Of conditions and actions - Serial Interface - Serial Ports - Show Grid – Trial control window - Show/Hide - Components pane - Maximum trial duration pane - Signal to Check - Hardware device conditions - PhenoTyper top unit conditions - Signal Value – Hardware device conditions - Snap to Grid – Trial control boxes - Social Interactions – Defining a condition - Sound File - Standard Deviation – Defining a condition - Standard Error – Defining a condition - Start-Stop Trial Rule - Customizing - Default - Default one - Examples - State Intervals - Analyzing - Analyzing data within intervals - Statistics – Condition based on dependent variable - Stimulus Presentation - Stop Condition of Sub-Rule - Stopping a Sub-Rule - Stopping a Trial - Subjects – Condition based on dependent variables - Subroutines – See Sub-Rules - Sub-Rule - Begin box - Defining - End box - Repeating - Sub-Rules - Calling from another sub-rule - Creating - Deleting - Ending - Examples - Reference to - Repeating - Re-using - Stop conditions - Why use - Summertime T - Target Visiting and Errors – Condition based on - TC-Variable – See Trial Control Variable - Template Experiment - Terminate Ongoing Repeat – Sub-rule start condition - Testing - External command - Hardware devices - Trial control sequence - Threshold (Zone Exit) - Time - Starting data recording - Stopping data recording - Time condition - Time interval condition - Time Condition – When tracking from video files - Time Interval – Condition based on - T-Maze - Top Unit – See PhenoTyper Top Unit - Total - Activity condition - Body angle condition - Body angle state condition - Body elongation condition - Defining conditions - Distance moved condition - Distance to point condition - Distance to zone condition - Meander condition - Turn angle condition - Track – vs. Trial - Track Data – Exporting - Tracking from Video Files - Trial – vs. Track - Trial and Hardware Control – Version of EthoVision XT - Trial Control - Analysis - Applying to multiple arenas - Applying to trials - Data analysis - Endless loop prevention - Exporting data - How are instructions executed - How it works - In multiple arenas - Programming - Programming hardware devices - Re-doing a trial - Rules - Screen - Start-stop rule - Sub-rule - Testing - Tracking from video files - Visualizing - Why use - Trial Control Boxes – Snap to grid - Trial Control Rules – For starting/stopping trials - Trial Control Settings - Exporting as image - Locked - Trial Control Variable - Condition based on - Start condition - Trial Control Variables - Actions on - Analyzing - Defining - Maximum value - Minimum value - Random value - Using - Trial Control Window - Zoom in/out - Zoom to fit - Trial Duration – Maximum - Trial vs. Track - TTL - Simulation - Testing USB-IO box - TTL Port – Connecting - TTL Port Tester - Condition based on - Testing - TTL Tester - Manual event recording - Technical specifications - Trigger an action - TTL to 28V Interface - TTL-IO Isolator Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Introduction To Trial Control URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-introduction-to-trial-control Chapter: EthoVision XT Introduction to Trial Control This Manual This manual is meant for all users of EthoVision XT: - For users of the Base version. You can find extensive information on the Trial Control conditions and analysis of Trial Control data. This information is not present in the EthoVision XT Help. - For users of the Base version plus the Trial and Hardware Control module. You find all the information you need in this guide. - If you use EthoVision XT in combination with hardware devices, you can find the relevant information in Section 7. EthoVision XT Help For extensive information on EthoVision XT or for troubleshooting, see the EthoVision XT Help. In EthoVision XT, choose Help > EthoVision XT Help or press F1. Other Documentation From the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 > Other Documentation. There you find: - EthoVision XT 18 - Application Manual for information on common tests including conditioning tests that make use of sub-rules in the Trial Control Settings. - PhenoTyper - EthoVision XT 18 - Reference Manual for information on PhenoTyper and how to connect it to EthoVision XT. - PhenoTyper - EthoVision XT 18 - Service Manual for information about PhenoTyper and devices such as the Noldus Pellet dispenser, the Noldus Lickometer and PhenoWheel. - DanioVision DVOC-0041 - Reference Manual if you use Trial Control with the DanioVision Observation Chamber. Why Use Trial and Hardware Control? Trial Control allows you to automate your experiment. For example: - You want to set a maximum duration for your trials. - You want to automate the start and/or stop of data acquisition. For example: - Start recording when the rat is first detected in the open field. - Stop recording when the rat has reached the platform in the Morris water maze. - Start recording at exactly 12:30:00. - Stop recording after the animal has been in the closed arms of the plus maze for 5 minutes. - You want to automate conditioning schedules, or operate hardware devices. For example: - When the animal presses a lever, have the food dispenser drop a food pellet. - When the animal leaves the shelter, use an External Command action to start a recording with Media Recorder. - When the animal enters the shelter, turn on a light. - Close the door of a radial maze when the animal has exited that arm. To Use Trial and Hardware Control - Open the Trial Control screen. - Define the conditions that, when met during your trial, trigger specific actions. Organize conditions and actions in sequences. - Before starting data acquisition, make sure that those Trial Control Settings are active. For information on how to manage Trial Control Settings, see also Settings and Profiles, under File Management in the EthoVision XT Help. Conditions and Actions A Condition is a statement that EthoVision evaluates. An Action is a command executed on a variable or a hardware device. You can therefore control your experiment by linking conditions with actions. Example 1: In a Morris water maze test, stop tracking when the rat reaches the platform (provided that the platform has been defined as a zone). Stop tracking is the action and Rat on the platform is the condition. Example 2: In a Fixed Ratio schedule, have EthoVision send a command to drop a pellet when the mouse has been detected in the Trigger zone. Drop one pellet is the action and Mouse in the Trigger zone is the condition. You define and link conditions with actions in a graphical form. You can copy, move, connect and delete Trial Control elements such as actions and conditions. For how to do so, see the EthoVision XT Help. Trial Control Rules A Trial Control rule is a set of conditions and actions organized in a logic sequence. It can be viewed as a set of instructions executed during a trial. There are two types of Trial Control rules: - Start-Stop Trial Rule: For starting and stopping data acquisition. This rule cannot be repeated or deleted. - Sub-rules (available only in EthoVision XT with the Trial and Hardware Control Module): Subroutines of the Start-Stop trial rule, which are meant to carry out specific actions. Sub-rules can start at specific times and be repeated according to conditions specified in a Sub-rule reference. How Trial Control Instructions Are Executed The instructions contained in the Trial Control Settings are carried out from the moment you start a trial, to the moment the trial is stopped. Only the instructions in the Trial Control Settings currently active (that is, highlighted in blue in the Experiment Explorer) are carried out. The program evaluates the Trial Control sequence at each sample time. The rate at which this happens depends on your chosen sample rate, not on the video frame rate. For the Start-Stop trial rule and each active sub-rule, the program remembers which Trial Control boxes were evaluated (active) in the previous sample. Depending on the type of box: - Condition Box: EthoVision XT waits until the condition is met. When this happens (condition becomes true), the program passes control to the next box in the sequence. The condition then becomes inactive. - Action Box: EthoVision XT carries out the action and passes control to the next box, which becomes active. The Action box then becomes inactive. - Sub-rule Begin Box: Control is passed to the box that follows. The Sub-rule Begin box becomes inactive. - Sub-rule End Box: This marks the end of a sub-rule. The sub-rule becomes inactive. Control is passed to the Reference box that had called that sub-rule. This Reference checks whether the sub-rule must be repeated. If this is not the case, control is passed to the box following the Reference box. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Introduction To Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-introduction-to-trial-control-continued Chapter: EthoVision XT Introduction to Trial Control (Continued) For a Reference box. Control is passed to the Sub-rule Begin box. The Reference box makes the sub-rule active. The Reference box stays active until the last sub-rule repeat is completed. Next, the Reference box makes the sub-rule inactive and passes control to the box that follows. Next, the Reference box becomes inactive. The events marked in italics above are those you can define in the Analysis profile and analyze or visualize in a chart. When a box becomes active, the previous one becomes inactive. Schematic Representation of Trial Control Execution The following steps describe how Trial Control Instructions are executed, using an example of a Start-Stop trial rule: - Tracking starts, either manually or because a previous condition has been met. - Control passes to a Condition box (for example "Is mouse on top of Shelter?"), which becomes active. The condition is evaluated. - The Condition is met (becomes true). - Control passes to the next box. In this case, it is an Action. Actions are taken immediately (but see the note below on actions on hardware devices). - The Action box becomes inactive, and the next box becomes active. For clarity, certain steps have been placed separately. In reality, the software is so fast that when a condition becomes true it also becomes inactive at the same sample time, and control passes to the next box. - Hatched Outlines: Condition box becomes active. - Dark Outlines: Condition becomes true or Action is taken. - Pale Outlines: Box becomes inactive. Evaluation of Trial Control Boxes Boxes combined in parallel using operators are evaluated at about the same time, in random order. This means that you cannot establish which condition is evaluated or which action is taken first. When your trial control is complex, for example when it includes sub-rules or conditions combined with operators, it is possible that two or more Trial Control boxes are evaluated at the same sample time. When a condition based on a dependent variable is evaluated (and therefore may or may not be met) also depends on the statistic used. If two or more boxes are evaluated at the same time, an action on a hardware device is taken only after all active boxes that must be evaluated have been evaluated. Time Plot of Trial Control Events When tracking starts, the Action "Start track" becomes active (1st line) and immediately inactive (2nd line) as control passes to the next box. The condition "On top of Shelter?" becomes active (3rd line) and immediately false (4th line) since the animal is not in that zone. When the animal enters the zone, the condition becomes true (5th line), and becomes immediately inactive (6th line) as control passes to the next box. The action becomes active (7th line) and immediately inactive (8th line) as the command "drop a pellet" is sent to the pellet dispenser. If the next box to be evaluated contains a condition that is fulfilled immediately, the program passes control to the next box. Therefore, within one sample time the program can pass control to two or more boxes to the right. When you stop the trial or the Maximum trial duration has been reached, all Trial Control boxes are deactivated. When the Rule End box of the Start/Stop trial rule is evaluated for an arena, data recording stops for that arena. From that moment, Trial Control is deactivated for that arena, even in those sub-rules that were ongoing in the meantime. A trial stops when trial control is deactivated in all arenas. Actions on Hardware Devices A command is sent to a device after all boxes that must be evaluated have been evaluated. However, it may take some time for the outcome to be seen. For example, when a pellet dispenser is almost empty it may take a few seconds before a pellet is released. Important: When two or more actions on hardware devices follow each other, it is possible that they are evaluated at the same sample time. This happens because the computer is fast enough to analyze multiple Trial Control boxes in the sample interval. To make sure that actions are taken in the correct sequence and do not interfere with each other, add a Time condition between the action boxes, so after the first action is carried out EthoVision XT waits for a short time (for example, 0.1 s) before carrying out the next one. Sub-Rules A sub-rule is completed when the Rule End box has been evaluated, or when it is interrupted. If two or more sub-rules are evaluated at the same time, it is not possible to establish which sub-rule is evaluated first at a specific sample. Trial Control in Multiple Arenas If your experimental setup includes two or more arenas, Trial Control is applied to each arena separately. This means that, if a condition is met in one arena, EthoVision XT takes the corresponding action in that arena, not the others. Example: The setup includes four cages, each defined as an arena. A Trial Control "In zone" condition has been defined so that tracking starts when the animal is first detected in the arena. When you first put an animal in Arena 2, the condition is met in this arena and tracking starts for that arena. When you release the second animal in Arena 4, two seconds later, tracking in that arena starts two seconds later than in Arena 2. The advantage of Trial Control in multiple arenas is that you can put one animal at a time into the arenas, and EthoVision XT will start tracking in each arena at the appropriate moment. If your setup includes multiple arenas, you cannot define a condition or action specific to one arena. This means that the zones and hardware devices specified in the condition or action must be present in all arenas, and have the same name. If a zone or hardware device is not present in an arena, and a condition is based on that zone or device, Trial Control cannot progress for that arena. Therefore, tracking does not stop unless you set a maximum trial duration or tracking reaches the end of the video. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Introduction To Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-introduction-to-trial-control-continued-Rtc Chapter: EthoVision XT Your EthoVision License and Trial Control Trial Control executes the instructions for each arena separately, however one cannot establish which arena is evaluated first at a specific sample time. Your EthoVision XT license determines which type of Trial Control you can set up. - EthoVision XT Base License. You can define a rule to start and stop data recording (Start-Stop trial rule), not sub-rules. You can also use an External command action. You cannot control hardware devices. - EthoVision XT Base + Trial and Hardware Control Module. You can define a Start/Stop trial rule, and in addition sub-rules that serve as subroutines of the Start-Stop trial rule. Moreover, you can control hardware devices. To acquire data in an experiment created with the Trial and Hardware Control Module, you must have a license that includes this module. For more information on your EthoVision XT license, see the EthoVision XT Help. Analysis of Trial Control Data The Trial Control function also allows you to easily analyze events that occurred during the trial. For example, in a conditioning experiment: - Number of Rewards. Calculate the number of pellets dropped during a trial. - Latency Between Action and Reward. Calculate the time interval between the time the animal pressed the lever and the time the animal approached the pellet dispenser. - Number of Failures. Calculate the number of times the animal approached the lever during the period between 'dropping the pellet' and 'animal approaching the pellet dispenser'. That is, how many times the animal pressed the lever when a reward was already available. You analyze Trial Control data the same way as for the behavioral variables. In the Experiment Explorer, open an Analysis profile, and specify the data you want to analyze (Trial Control event for point events, Trial Control state for time intervals between two events). Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control Chapter: EthoVision XT Program Trial Control If you just want to record data for a specific time, you can do so by setting the maximum trial duration. If you want to start and stop data recording in relation to a few simple conditions (for example, start recording when the animal is detected in the water maze, and stop when the animal reaches the platform), define the Start/Stop trial rule. In other cases, see below. Procedure - Before defining Trial Control in the program, it is helpful to draw your experimental procedure as a flow diagram, where each block represents an action or a condition which, when met, triggers other actions or conditions. The logical order in the example below reads from left to right. - From the Setup menu, select Trial Control Settings, select New, enter a name of the new Trial Control Settings or accept the suggested one, and click OK. The default Start/Stop trial rule appears on the screen. - Build the Trial Control sequence outlined in step 1, using the components available. - To define a Condition or an Action, click one of the buttons under Conditions or Actions. Insert the box in the appropriate place in the sequence. - For conditions: See the Conditions section and detailed overview. - For actions on hardware devices: See the hardware devices section. - For actions on Trial Control variables: See the Trial Control variables section. - To define a set of actions and conditions to be repeated (Sub-rule), under Structures, click the button next to Sub-rule. - To define the command that calls a sub-rule, under Structures, click the button next to Reference. Insert the box in the appropriate place in the sequence. - Test the Trial Control sequence. - To apply Trial Control to your trials, before starting data acquisition make sure that the Trial Control Settings are highlighted in blue in the Experiment Explorer. Notes - When you create a new Trial Control element (action, condition, sub-rule or reference) and another of the same type has already been defined in this or other Trial Control Settings, a message appears asking you whether you want to create a new element or make a copy of the existing control. - A Trial Control variable is a variable that you can define to control your trials. For example, a counter variable that is incremented every time a specific event occurs. You can then define conditions and actions based on this variable. - If the experimental protocol is very complex, like in the case of a multiple-day recording session, it is handy to split the procedure into main blocks; then, for each block specify the basic actions and conditions, and whether the logical sequence should be repeated. This helps you identify the main building blocks of your Trial Control logic, which will translate into Sub-rules. - If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings, the Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. This makes the rule invalid. Redesign your Trial Control rule and connect the arrows between the boxes. - If you choose to record video with EthoVision XT by selecting the option Save video only, track later in the Acquisition screen, Trial Control is applied when you do tracking, not when you record video. To start and stop video recording, do so manually. - Procedures that must be repeated or represent a specific task must be defined as Sub-rules. Sub-rules can be called at specific times or under specific conditions. In the main Start-Stop diagram, draw a block that calls each sub-rule. Conditions A Condition is a statement that EthoVision checks during the trial. When the Condition is met (True), the program evaluates the next Trial Control element (another condition, an action, or a reference to a sub-rule). Example — Conditions are indicated in italics: - When the rat reaches the platform, stop tracking. - When the mouse is around the novel object, switch on the light. - When the animal presses the lever, drop a pellet. To Define a Condition - In the Components pane, under Conditions, locate the type of condition you want to define. - Double-click the condition name or click the button next to it. - If the Add a condition window appears, it means that there is at least one condition of the same type in your experiment. You are asked to choose between creating a new condition or re-using an existing one. Choose the option you require and click OK. If this window does not appear, skip this step. - Next to Condition name, type in the name you want to give to the condition, or accept the default name. - Specify the condition properties. - Enter a Comment (optional), then click OK. - Insert the condition box in the sequence. If the condition is complex (for example, Stop the trial either if the rat has reached the platform or it has been swimming for 60 seconds), then you must define separate conditions and combine them. Important: If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings, the Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. This makes the rule invalid. Redesign your Trial Control rule and connect the arrows between the boxes. Actions An Action is a command that EthoVision carries out during acquisition and that influences the trial. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control-continued-IFn Chapter: EthoVision XT Program Trial Control Visualizing Trial Control Data Choose Trial Control State to select the time between events occurred during the trial. For example, From Action Light On To Condition In Trigger Zone True. This will show the time interval from when the light switches on to when the animal enters the Trigger zone. - Start a trial. Watch the Trial Control Events or States in the Analysis Results and Scoring Pane at the bottom of your screen. - Create an Analysis profile and use the Trial Control event/state/variable and other dependent variables to specify the events you want to visualize. See page 176 for details. - To visualize the trial, choose Analysis > Results > Plot Integrated Data. Trial Control data are visualized as vertical segments (for events, with no duration) or horizontal bars (for states, with a duration) along the time line. Examine the data and check that EthoVision XT has responded as expected. - You can also check when exactly a condition becomes active or true, or when a command is given by looking at the Trial Control Events pane at the bottom-right corner of your screen. Select an Arena name from the list to visualize the sequence of Trial Control for that arena. Play the track. The red hairline moves along the sequence and shows at what point Trial Control is. Play the track frame-by-frame to see when exactly a condition becomes true, or a command becomes active. In the following example, a Trial Control sequence is defined: Condition: In trigger zone → Action: Drop pellet → Condition: In feeder zone. Play the track until the cursor gets between Condition: In trigger zone - becomes false and Condition: In trigger zone - becomes true. This is the time when the condition is activated and the program waits until the animal enters the trigger zone. At 15.48 s the condition becomes true. The program executes the instructions that follow (Action: Drop pellet) and positions at the next condition (In feeder zone) until that becomes true too. - Make the necessary corrections to the Trial Control rules and start again from step 1. Notes For a clear overview of the Trial Control events occurring during a trial, for each Trial Control box (except the Rule End box) define three dependent variables: - Trial Control event (becomes active): Under Element, choose which box to test, and under Event, choose becomes active. This marks the time when an action is taken, a condition is evaluated, or a sub-rule is activated. - Trial Control event (becomes inactive): Under Element, choose which box to test, and under Event, choose becomes inactive. This marks the time immediately after an action is taken (this is usually not distinguishable from the time the action is taken), a condition is met, or a sub-rule is completed. - Trial Control state: Select From when the box becomes active To when the box becomes inactive. This will display a colored bar that marks the time that the box is activated up to when it is deactivated. Define also one or more In Zone dependent variables to monitor the position of the animal. Once you have carried out a trial, the Trial Control Settings used for that trial are locked. To edit them, either delete the trial acquired or make a copy of the Trial Control Settings (right-click the Trial Control Settings in the Experiment Explorer and select Duplicate). To check at what time an action is taken or a condition is met, you can also export the Trial Control events and the Hardware log data (see page 193). You can also test your Trial Control Settings by providing visual/audible feedback during the trial. Define an action box that calls up some feedback once the program has reached a specific point in the Trial Control sequence. Insert this box immediately to the right of the condition/action/rule reference box that you want to test. To test hardware devices, see page 123. Apply Trial Control to Your Trials To apply Trial Control to your trials, make sure that the Trial Control Settings profile containing that logic is highlighted in blue in the Experiment Explorer. Test your setup thoroughly before carrying out the actual trials (see page 47). Setups with Multiple Arenas Trial Control is applied to each arena independently. Locked Trial Control Settings When a Trial Control Settings profile is used for acquiring at least one trial, it becomes locked. Locked settings are indicated by a lock symbol in the Experiment Explorer, and cannot be edited. To edit a locked Trial Control Settings profile, make a copy of it and edit this copy. Tracking from Pre-Recorded Video Files When you track from video files, Trial Control checks conditions using video time instead of real time. - Conditions based on time: If you select the Detection Determines Speed option, Trial Control is carried out at the speed set by EthoVision in order not to skip video images. This results in the video playing faster or slower than normal (1x), depending on the processor load necessary to detect subjects. For example, if detection requires little processor work, the program tracks the subject faster than normal. A time condition (for example, 60 s) is therefore met earlier than at real time. - Using clock time: If you define a condition based on clock time, or schedule a sub-rule with clock time, this is translated into the video start time — that is, the date and time the video file used for tracking was created. Example 1: You set a Time condition to start tracking After clock time 11:30. The video file was created on March 6, 2008 at 11:00. Once you start the trial, the condition is met half an hour later in the video. If you had set to start tracking After clock time 10:30, tracking would start immediately after starting the trial. Example 2: You set a sub-rule to start at 10:00 (1st day). The video file was created on March 6, 2008 at 11:00. Once you start the trial, the sub-rule never starts, because the planned start occurs before the initial time of the video. To make a sub-rule start when tracking from that video, set the start time between 11:00 and the video end time. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control-continued-NbE Chapter: EthoVision XT Program Trial Control The program does not ask you whether you want to re-use the Trial Control element if no element of the same type has been defined in the other Trial Control Settings. You cannot re-use a Trial Control element from the same Trial Control Settings. This is because the Trial Control elements must be unique in order for correct analysis to be done. Frequently-Occurring Cases Have an Action Taken When a Condition Is Met Example: A food pellet is dropped (Action) when the mouse is detected in the zone that marks the top of the shelter (Condition). The condition must precede the action. In the example above, the condition is based on a zone. The action is performed on the Pellet dispenser. Have Two Actions Taken at the Same Time Example: In a radial maze experiment, make sure that the device Door 1 opens at the same time when Door 2 closes. Define two action boxes, one for each door device. Next, do one of the following: - Place the two action boxes in parallel, and combine them with an All operator. - Place the two action boxes one after the other. The time between the two actions is negligible. Specify a Time Interval Between Actions/Conditions Example: Wait one minute between the action Cue Light On and the action Drop one pellet. Insert a Time condition box between the two existing boxes. Make Multiple Instances of an Action Example: In a conditioning experiment, drop two food pellets in sequence. The two actions are placed in a linear sequence. If the action is performed on a hardware device, insert a Time condition between the two action boxes, for example wait 10 s before proceeding to the second action. If you do not do this, EthoVision XT interprets the twin actions as one. In the example above, it would deliver one food pellet only. If the pellet dispenser is almost empty, it may take up to 30 seconds to deliver a pellet. Make sure that the time specified in the Time condition exceeds the time that it takes the action to be carried out. Another possible solution is to place a condition based on hardware between the two actions, that checks that the Number of pellet drops is >=1 before taking the next Drop pellet action. Have a Sequence of Conditions and Actions Repeated Example: Make sure that the sequence Mouse on Shelter → Drop one pellet is repeated every time the animal is found on the shelter. Define a Sub-rule and insert the sequence of conditions and actions in it. Next, create a Reference to that sub-rule, and specify when and how many times the sequence must be repeated. Give a Reward After Multiple Instances of the Subject's Action Example: In a Fixed Ratio schedule, it is required that the animal has to press the lever three times (Action) before getting a reward. - Define a Trial Control variable C that counts the number of lever presses. The action C=C+1 is triggered every time the condition Lever pressed is met. - Define a Sub-rule that includes the sequence Condition Lever pressed → Action C=C+1. - Define a Reference for that sub-rule, and specify that the sub-rule must be repeated until C reaches the value required (3). Place the Action box for Drop a pellet immediately after the sub-rule's Reference box. For more information: - Trial Control variables: See the Trial Control Variables section. - Sub-rules and references to sub-rules: See the Sub-rules and References sections. Have an Action Taken When a Condition Is Met Within a Specific Time Example: Have EthoVision XT drop a food pellet when the animal visits zone A within 1 minute from the release of a light stimulus. - Define the main condition (in the example above, animal in zone A). Specify that the Current value of In zone must be true. - Define the action that must be taken (Drop a pellet). - Define the accompanying Time condition (Wait one minute). - Place the main condition followed by the action. Place those two boxes in parallel with the Time condition, using an operator of "Any" type. With such a sequence, the food pellet is dropped as soon as the animal is found in zone A. If the animal does not go to zone A, one minute after the light was switched on the Time condition is met, and the operator becomes active. Therefore, control passes to the box following the operator, and the In zone condition is no longer evaluated. With this solution, the action Drop a pellet is not taken when the animal enters zone A more than one minute after the light has been switched on. Important: If you combine the two conditions above with an operator of All type, the program may wait indefinitely until both conditions are met. Have Different Actions Taken According to Different Conditions Example: A T-maze is provided with two doors, one in the middle of arm A and one in the middle of arm B. It is required that door A is opened when the animal enters arm A, and door B when the animal enters arm B. - Define two conditions, one for arm A and one for arm B. For both conditions, specify that the Current value of In zone must be true. - Define two actions, one for opening door A and one for opening door B. - Connect each condition to the corresponding action. Next, connect the resulting sequences through an operator of the "Any" type. Define Phases in a Trial Example: It is required that tracking occurs in different phases of a trial, for example, Baseline, Conditioning, and Testing. In each phase, different trial control rules must be applied. - For each phase, define a Sub-rule with its actions and conditions. Specify when the sub-rule must start. - For each sub-rule, define a Sub-rule reference and insert it in the Start/Stop rule. Make sure that the references are in the order specified in your experimental protocol. Test the Trial Control Sequence It is not easy to make a complex Trial Control sequence work right the first time. To check that Trial Control works as expected, follow this procedure: - Make sure that the Trial Control Settings that you want to test are highlighted in blue in the Experiment Explorer. Otherwise, click the Trial Control Settings you want to test. - Open the Acquisition menu (choose Acquisition > Open Acquisition). - Click Show/Hide and choose Show Dependent Variable. Choose Trial Control Event for simple events like Action Drop a pellet becomes active, or Condition Subject in zone A becomes true. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control-continued-Lze Chapter: EthoVision XT Program Trial Control Example 3 - Play a Sound at Trial 3 This example assumes that the researcher acquires a batch of trials live, and wants to present an acoustic stimulus during trial 3. The batch file looks like as follows: @echo off echo %1 IF %1=="Trial 3" ( start wmplayer D:\Temp\Stimulus_sound.wav ) timeout /t 5 /nobreak > NUL Next, in the Trial Control settings, create an External command, specify the batch file and in the Command line options enter "%tn%". Note: - The line echo %1 reads the first parameter; in this case, the trial name. - In the IF line, there must be five spaces between Trial and the number 3. Reduce by one space if the trial number has more digits: 4 spaces for Trial 10–99, three spaces for Trial 100–999, etc. - To make sure that you enter the correct number of spaces in the Trial name, copy the name of the trial from the Trial list (Setup menu > Trial List, then click Show/Hide > Variables and choose Trial Name). Copy the content of the cell in the Trial name column for that trial, and paste the trial name in the batch file. Operators Aim The Operators help you combine actions, conditions and sub-rules in various ways. Examples - When at least one of the two conditions A and B is met, then do … . This is an example of conditions combined by an operator of the Any type (OR logic). - When two conditions are met at the same time, then do … . This is an example of conditions combined by an operator of the All type (AND logic). - When at least/at most/exactly 4 of 8 conditions are met, then do … . This is an example of conditions combined by an operator of the N of All type. Procedure - Define the conditions, actions, and rules that you want to combine. Place them in your Trial Control sequence as parallel branches, as shown in the figure below. - In the Components pane, under Structures, double-click Operator or click the button next to it. - If the Add an Operator window appears, it means that there is at least one operator of the same type in your experiment. You are asked to choose between creating a new operator, or re-using an existing one. If this window does not appear, skip this step. - Create a new operator: A new operator is created. - Re-use an existing operator: Select the name of the operator already present in your experiment. Click OK. The Operator window appears. - Under Name, enter the Operator name or accept the default name Operator (n), where n is a progressive number. - Under Operator Triggers When, select the option that applies: - Any (at least one) of the inputs is 'true'. - All inputs are simultaneously 'true'. - N of All inputs are simultaneously 'true'. Where 'true' means a condition met, an action carried out, or a sub-rule finished (depending on the elements you want to combine). If you choose the third option, specify how many inputs must be 'true': = (exactly equal to), not= (not equal to), >= (at least), <= (a maximum of), etc. Specify the number in the box. - Enter a Comment (optional) to describe this operator, and click OK. - A new Operator box appears in the Trial Control. Place the box to the right of the elements defined in step 1, and connect each element to the operator box. - Connect the operator to the next element in the Trial Control sequence. Notes - Names of operators must be unique in your experiment. You cannot define two operators with the same Operator name, even if these are defined in two different Trial Control Settings. - An Operator can also have just one input box. In that case the operator is of no use, because control passes immediately to the next box as soon as the input condition becomes true or the input action is carried out. EthoVision informs you about this. - Operators can also combine sequences of elements. For example: - Sequence 1: When the animal presses a lever (Condition), then drop a food item (Action). - Sequence 2: Time = 5 minutes (Condition; this equals to waiting 5 minutes). If you want the program to take an action when either sequence has been completed, combine the two sequences with an Any operator. Re-Use Trial Control Elements The elements of Trial Control (conditions, actions, operators, sub-rules and sub-rule references) that you have defined in other Trial Control Settings can be duplicated and re-used in the current Trial Control Settings to reduce your time spent editing. To re-use all the elements defined in your current Trial Control Settings profile, make a copy of it: right-click the profile in the Experiment Explorer and select Duplicate. To Re-Use a Trial Control Element - Click the button next to the category of element that you want to re-use. - The Add window appears. Select Reuse an existing condition / action / sub-rule / reference. This window does not appear when the experiment contains only one Trial Control Settings profile, or the experiment contains more Trial Control Settings profiles but none of them contains an element of the same type as that you have chosen. - Select the name of the existing element from the list next to the option. The second list shows the Trial Control Settings profile that contains that element. If the element is present in multiple Trial Control Settings, choose the appropriate one from the list. - Click OK. - A window appears for the type of element chosen. The Name and settings specified here are the same as in the element chosen in step 3. - To create an identical copy of the element, click OK and go to step 7. - In all other cases, edit the settings and click OK, then go to step 6. - If you have changed any property of the new element (including name and comment), a window appears showing two options: - Apply the new settings only in the current Trial Control profile. - Apply the new settings in all writable Trial Control profiles. Choose whether you want to apply the properties only to the new copy, or to extend those changes to the original elements in all Trial Control Settings that are writable (that means, not locked after acquisition). Choose the option you require and click OK. - Insert the resulting box in the Trial Control sequence. Notes - If you choose the option Apply the new settings in all writable Trial Control profiles, changes are not made in those profiles made read-only after data acquisition. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control-continued-iCL Chapter: EthoVision XT Program Trial Control Network Configuration Example Example network configuration: - Network Switch: 192.168.0.239 (Netgear GS310TP) - EthoVision XT PC: 192.168.0.201 - UltraVox XT PC: 192.168.0.202 Batch File Configuration The available batch files are located in C:\ProgramData\Noldus\Common\Tools\UltraVox XT 3 Control. When working with one arena, use the file SUV - 2 PCs.bat: @if exist "\\IP address of UltraVox XT PC\Synch\start.txt" del "\\IP address of UltraVox XT PC\Synch\start.txt" @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 3 Control\start.txt" "\\IP address of UltraVox XT PC\Synch" > nul Open the file with Notepad and enter the actual IP address of the UltraVox XT PC. Alternatively, you can enter the name of the PC as found in Windows (e.g. DESKTOP-123ABC) instead of the IP address. The batch file copies the start.txt file to the trigger folder of UltraVox XT. This starts and stops sound recording. - Action 1: Calls the batch file to start recording in UltraVox XT. - Condition 2: Determines the duration of the recording. - Action 3: Calls the same batch file again and stops recording in UltraVox XT. In UltraVox XT, open the Trial Control Settings and choose External program trigger for both Start acquisition and Stop acquisition. For more information, see Control UltraVox XT from other software in the EthoVision XT Help. If you work with multiple arenas, use the batch file SUV - 2 PC multiple arenas.bat. This sends the start.txt file just one time, for Arena 1. If the arena has a different name, open the file with Notepad and edit the name between the quotes: @if exist "\\IP address of UltraVox XT PC\Synch\start.txt" del "\\IP address of UltraVox XT PC\Synch\start.txt" @echo off echo %1 IF %1=="Arena 1" ( @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 3 Control\start.txt" "\\IP address of UltraVox XT PC\Synch" > nul ) In both Action boxes in the Trial Control Settings, specify the following Command line options (quotes included): "%an%" It is also possible to run EthoVision XT and UltraVox XT on the same PC. In this case, use the batch file SUV - 1 PC.bat. However, this may cause high workload on memory and the processor. Test this solution thoroughly and ensure the proportion of missing samples in your tracks is acceptable. Examples Example 3 - Present an Acoustic Stimulus You can use an EthoVision XT external command to run a batch file that plays a sound during your trials. Define an action using the batch file Play sound.bat. The batch file Play sound.bat starts Windows Media Player and plays the sound file Stimulus_sound.wav. Its content is: start wmplayer D:\Temp\Stimulus_sound.wav A similar solution utilizes Windows PowerShell: powershell -c (New-Object Media.SoundPlayer "D:\temp\Stimulus_sound.wav").PlaySync(); Example 4 - Present a Visual Stimulus With the free tool Frameless you can easily display images on a separate monitor based on subject behavior or at a specific time. - Download Frameless and copy the executable to the EthoVision XT PC. - In the Trial Control Settings, create an external command action and specify Frameless along with the required parameters. In this example, the stimulus S1.jpg is presented 10 seconds after the start of the trial, displayed full screen on monitor 2 for two seconds. Tip: Create a subrule to present multiple stimuli during a trial. Tip: If you work with multiple arenas, see Example 2 below. External Commands: Arena- and Trial-Specific Command Line Options: Arena and Trial Name Use the Command line options %an% and %tn% in the External Command window to send information about the Arena and Trial name in command lines from the Trial Control rule. This is especially useful for controlling events based on specific arenas or trials. Example 1 - Display Arena and Trial Name A batch file can be created to display the current Trial name and Arena name in the DOS window (one for each arena, in the case of multiple arenas). The instructions echo %1 and echo %2 listen to the values of the parameters in the Command line options, %an% and %tn%, in the order specified. The DOS window closes 5 seconds later: echo %1 echo %2 timeout /t 5 /nobreak > NUL In the External Command Action window, specify the name and location of the batch file and enter the command line options "%an%" "%tn%" including the quotes. Note: - All characters must be lower case. - The parameters must be on the same line, separated by one space. - The line echo %1 reads the first parameter specified in the command line options (the arena name). - The line echo %2 reads the second parameter specified (the trial name). Example 2 - Present a Stimulus to Multiple Arenas A researcher wants to present a visual stimulus to fish larvae swimming in six wells (six arenas). Using the procedure described in Example 4 alone would send the command six times simultaneously, which is not desirable. Using Command line options, the image can be associated with one specific arena, for example Arena 3. Because the monitor is placed under the wells, all subjects still receive the stimulus. First, create a batch file with the following content: @echo off echo %1 IF %1=="Arena 3" ( [path]\Frameless.exe "[path]\Stimulus.jpg" mon=2 fullscreen=yes duration=00:00:02 ) Where mon=2 specifies the second monitor. The image is displayed in full-screen mode for two seconds. For additional adjustable parameters, see the Frameless documentation. Note: The arena name may differ in your experiment (e.g. "A1", "Maze 1"). Save the file with the extension .bat, for example ShowImage.bat. Next, in the Trial Control Settings, create an External Command, specify the path to the batch file, and enter the following in the Command line options (quotes included): "%an%" Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control-continued-sLT Chapter: EthoVision XT Program Trial Control (Continued) Permutation To explain how Permutation works, consider a variable action within a sub-rule that is repeated a number of times with an interval of 1 second. In the first five repeats, the action generates random numbers in the following sequence: 5, 4, 2, 3, 1. Because Permutation is selected, a new value can only occur at the 6th repeat (indicated with the arrow) or later, after all the numbers within the range 1–5 have been generated. Use the Permutation option to create sequences of unique numbers that control which events will be carried out. For example, which door of a maze must be opened in a pseudorandom sequence, or which stimuli should be administered in a conditioning experiment. In the following example, the researcher wants to carry out 10 presentations of each of two stimuli, CS+ and CS-. The stimuli should alternate in a pseudorandom fashion, that is, at the end of the trial a mix of 10 instances of CS+ and 10 instances of CS- has occurred. - Define a main sub-rule that will be repeated 20 times. In this sub-rule, insert a Variable action that defines the variable Var1 with Random integer values chosen between 1 and 20, and with the Permutation option selected. - Next, two conditions determine which way is taken at each repeat of the main sub-rule: - If the value is between 1 and 10, a sub-rule for the stimulus type CS+ will be activated. - If the value is between 11 and 20, a sub-rule for the stimulus type CS- will be activated. - Because each stimulus type is nested in a sub-rule, define two sub-rules: Subrule CS+, which contains the actions for the stimulus CS+, and Subrule CS-, which contains the actions for the stimulus CS-. - Next to the conditions outlined above, the sub-rule reference boxes Reference CS+ and Reference CS- call the corresponding sub-rules. The two branches must be combined with an OR operator. Each stimulus-specific sub-rule is set to Repeat once. However, each stimulus type is presented 10 times in total, because the main sub-rule creates 10 values of Var1 that activate that sub-rule 10 times, while leaving the other inactive. Notes - If your setup includes multiple arenas, each arena receives an instance of the variable. Thus, a variable can have different values in different arenas. - You can define several instances of variable-based actions and conditions in the same Trial Control profile. Such instances may well become active at the same time. Make sure that they do not interfere with each other. For example, two actions on the same variable are carried out in two different sub-rules: - If the actions A=1 and A=2 are evaluated at the same sample time, the value of the variable A after the actions are executed depends on the order of the Reference boxes those sub-rules refer to. - If the reference to Sub-rule 1 comes first, A=1 is executed first. - If references are placed in parallel, the order is undefined. In the Visualization, you can check which action is executed first. - To analyze the values of a Trial Control variable, or visualize its values plotted against time (also for testing purposes), in the Analysis profile choose Trial Control variable. External Commands Actions Based on an External Command - In the Components pane, under Actions, click the button next to External command. - Next to Action Name, enter a name for the action (for example, Play sound) or accept the default name. Click the Information button to get additional information about defining an External command. - Under Actions to perform, select which file you want to run by clicking the ellipsis button. - Select one of the file types from the list: - Executables (*.exe) - Batch Files (*.bat, *.cmd) - All Files (*.*) - Locate the file and click Open. - Optionally, enter a Command line option. - To test the command, click the Test button. Example 1 - Trigger Media Recorder to Record Video You carry out live tracking during a 24-hour period and you want to record video with Media Recorder, but only when the animal is not in the shelter (defined as a Hidden Zone, where it spends most of its time). Note: For this configuration you need an analog camera. You must split the video signal from the cameras (using a BNC T-splitter connector) and send it to two BNC connectors of the Picolo Alert encoder board: one for tracking in EthoVision XT and the other for Media Recorder. In order for the board to receive the two signals correctly, you need to adjust the dip switches on the encoder board: usually On for the first input and Off for the second input. - Create an External command box to start Media Recorder. Choose Executables (*.exe) and select MRCmd.exe as the application to run. As a Command line option, enter /E to specify that the external command launches Media Recorder. - Insert a Condition Out of shelter and combine this with a Time condition to make sure that Media Recorder is launched before recording starts. - At the right of the Operator box, insert a second External command box to start video recording: select MRCmd.exe as the executable to run and enter /R as a Command line option to start recording. - Similarly, you can have EthoVision XT stop recording (Command line option: /S) when the subject enters the shelter again. Note: There may be a delay between the command Start Recording and the moment Media Recorder actually starts recording. Run a test recording to measure that delay. Example 2 - Trigger UltraVox XT to Record Ultrasound In this scenario, you plan to video-track mice with EthoVision XT and, at the same time, record their ultrasonic vocalizations with UltraVox XT. For ease of use, you want to start and stop recording from one place — EthoVision XT. Define an External command action based on one of the batch files SUV.bat. Computer Setup: It is recommended to use one PC for EthoVision XT and one PC for UltraVox XT. Connect the two computers through a network switch and assign the IP addresses to enable communication. See the EthoVision XT Help for more information. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control-continued Chapter: EthoVision XT Program Trial Control Actions are indicated in italics: - When the animal is detected in the arena, start tracking. This is an example of system actions (start tracking and stop tracking). - When the animal enters the maze's left arm, do C= C+1. This is an example of actions on a Trial Control variable. - When the animal is found on the shelter, drop a pellet. This is an example of actions on hardware devices. - When the animal leaves the shelter, play a sound or present a visual stimulus. Or, when you start tracking, also start ultrasound recording with UltraVox XT. Those are examples of actions based on an external command. To Define an Action - In the Components pane, under Actions, locate the type of action you want to define: - Trial Control variable for an action on a Trial Control variable. - The device type name for actions on a hardware device. - External command to start an external program or run a batch file. - Double-click the action name or click the button next to it. - If the Add an action window appears, it means that there is at least one action of the same type in your experiment. You are asked to choose between creating a new action or re-using an existing one. Choose the option you require and click OK. If this window does not appear, skip this step. - Next to Action name, type in the name you want to give to the action, or accept the default name. - Specify the action properties: - For actions on Trial Control variables, see the Trial Control Variables section. - For actions on External commands, see the External Commands section. - For actions on Hardware devices, see the Hardware Devices section. - Enter a Comment (optional), then click OK. - Insert the action box in the sequence. You cannot create additional actions of type Start track and Stop track, nor can you delete the existing ones. Trial Control Variables You can define variables to be temporarily stored during a trial, which you can use to influence the control of the experiment. - Example 1 — Variable as a marker: The variable Phase has been defined to specify the various phases of a trial (Phase = 1 means Conditioning; 2 Testing, etc.). The researcher can then program EthoVision to follow specific Trial Control sequences according to the current value of Phase. - Example 2 — Variable as a counter: A researcher has defined the variable SR (successful response) to count the number of times the subject responds correctly to a stimulus. To increment the value of SR after a correct response, specify the formula SR= SR+1. To Define a Trial Control Variable - In the Components pane, click the button next to Trial Control variable under Conditions or Actions. Next, click the TC Variables button. - The Trial Control Variables window lists the variables currently in the experiment (including those defined in other Trial Control Settings). To add a new variable, click Add variable. - A new row is appended to the table. Under Name, type in the name you want to give to the variable. Under Initial Value, enter the value of this variable at the start of the trial (default: 0). - Click OK. In the TC-variable action/condition window, define the action or condition you require. Click Cancel if you do not want to create a condition or action based on this variable at this point. - To delete a variable, click the variable name in the Trial Control Variables window and click the Delete variable button. - To rename a variable, click the variable name in the Trial Control Variables window and edit the name. The variable name cannot contain blank spaces. The default name of a new trial control variable is VarN, where N is a progressive number. Actions on a Trial Control Variable To assign a new value to a variable in Trial Control, define a Variable action in your Trial Control rule. - In the Components pane, under Actions, click the button next to Trial Control variable. - If the Add an action window appears, it means that there is at least one action of the same type in your experiment. You are asked to choose between creating a new action or re-using an existing one. If this window does not appear, skip this step. - Next to Action Name, enter the name of the action (for example, Increment Counter) or accept the default name. - Under Action to perform, select the variable from the list. You can also create the variable by clicking the TC Variables button if you have not yet done so. - Next to the = symbol, do one of the following: - To assign the same value of another variable (for example A = B), select the other variable (B) from the second list. - To enter a formula, click the double-arrow button. Select the operator from the list and specify the formula in the second and third lists. For example, A= A + 1. - To assign a random value, select Random from the second list, and enter the Minimum and Maximum limits (integer numbers 1 up to 999) within which the random value must fall. When you select Random, the Permutation option also appears. - Enter a Comment (optional), then click OK. - Insert the resulting action box in the Trial Control rule. Random Values and the Permutation Option When programming variable ratio schedules, it is a good idea to use the Random option. Define a random variable R that specifies the number of rewards to be provided. Insert the resulting box in a sub-rule. Every time the sub-rule is repeated, the variable R gets a new value. Make sure that the food dispenser is activated as many times as specified by R during that repeat. You can do this by calling a second sub-rule that activates the food dispenser (action drop pellet followed by a time condition that waits for a short time interval). This second sub-rule is repeated as many times as specified by the value of R. You cannot combine Random with a formula (for example, to compute A= Random+1). The equivalent solution is to define first an action B= Random, and then one more action A= B+1. Place the two boxes in sequence. Select the Permutation option to generate a value such that all n values within the specified range occur once before a value is generated again. For example, if you specify 1 as Minimum and 5 as Maximum (n = 5), the value 1 will be generated only when all five values in the range have been generated in previous repeats of the action. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Program Trial Control (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-program-trial-control-continued-qdY Chapter: EthoVision XT Program Trial Control (Continued) You can choose to record video first and then acquire data from the resulting video file. You do this by selecting Save video only, track later in the Acquisition screen. When recording video, Trial Control is turned off. You get an appropriate message when selecting the option Save video only, track later. When you track from the video recorded in the previous stage, Trial Control for Start-Stop is activated, but you cannot control hardware devices. Re-Do a Trial For video files recorded with EthoVision, you can re-do the corresponding trial (see Redo trials in the EthoVision XT Help). However, if you re-do a trial the Trial Control log files recorded with the previous instance of the trial are deleted. Stop a Trial When you stop the trial, all rules active in the Trial Control Settings are ended immediately, and hardware devices are reset. The Start-Stop Trial Rule Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Sub-Rules URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-sub-rules Chapter: EthoVision XT Sub-Rules Use Sub-Rules A sub-rule is a sequence of actions and conditions separated from the Start-Stop trial rule. You can view a sub-rule like a subroutine in a larger program, where the program is your Trial Control. You can have the sub-rule start at specific times or under specific conditions. Each criterion defined is a Start condition of the sub-rule. A sub-rule can be repeated, that is, when EthoVision finishes executing the instructions contained in the sub-rule, the program can start the sub-rule again from the beginning, for a specified number of times or until a condition is met. You can also have the same sub-rule called from different points of the Trial Control sequence. To do so, define multiple References to the same sub-rule. Why Use a Sub-Rule? A sub-rule is necessary when your trials involve repetition of tasks. For example, when the animal has to press a lever to obtain a reward, and you want to repeat that 50 times. This is not feasible within the Start-Stop trial rule. A sub-rule is also handy when your Trial Control logic is very complex, because it helps you have a clear overview of the phases within your trial. For example, different tasks within a trial can be kept separated and managed more easily. Create a Sub-Rule - In the Components pane, under Structures, double-click Sub-rule, or click the button next to it. - If the Add a sub-rule window appears, choose one of the following: - Create a new sub-rule. This creates a new sub-rule. You will be asked to enter a unique name for this sub-rule. - Reuse an existing sub-rule. Choose this option if you want to re-use an existing sub-rule. Select the existing sub-rule and, if necessary, the Trial Control Settings where it is stored. Note: You only copy the sub-rule name, the Rule Begin and the Rule End boxes, not the actions and conditions inside the existing sub-rule. - Under Name, enter a name for the sub-rule. The default name is Sub-rule (n) where n is a progressive number. - Under Comment, enter a description of the sub-rule (optional). - Click OK. The sub-rule is displayed on your Trial Control screen. It consists of a Rule Begin box and a Rule End box. - Complete the sub-rule by inserting the appropriate conditions and actions between the Rule Begin and Rule End boxes. - Define a reference to this sub-rule (see the next section). Notes - Sub-rule names. Names of sub-rules must be unique in your Trial Control Settings. You cannot define two sub-rules with the same name, even if these are defined in two different Trial Control Settings. However, you can create a sub-rule with the same name as an existing sub-rule stored in other Trial Control Settings by re-using it. - Re-using a sub-rule. If you choose to re-use a sub-rule and then change any property of this copy (Name or Comment), a window appears with the message Define the scope of your changes. The program asks you whether you want to apply the properties only to the newly-created sub-rule, or to the sub-rules with the same name in all Trial Control Settings. Choose the option you require and click OK. - Deleting a sub-rule. You cannot delete a sub-rule if at least one reference to that sub-rule is present in the Trial Control. You must first delete its reference. If you create a sub-rule without a valid reference, you can still acquire data but EthoVision informs you that trial control may not work as expected. Create a Reference to a Sub-Rule A Reference calls the instructions contained in an existing sub-rule. - Make sure that the sub-rule has been defined in the Trial Control screen. - In the Components pane, under Structures, double-click Reference or click the button next to it. If the Add a reference window appears, choose one of the following, then click OK: - Create a new reference. To create a new reference to a sub-rule. - Reuse an existing reference. Choose this option if you want to make a copy of an existing reference. Select that reference and, if necessary, the Trial Control Settings where it is stored. - The Sub-rule Reference window appears. Under Name, enter a name for the reference. The default name is Reference (n), where n is a progressive number. - Under Reference, from the Reference to sub-rule list select the sub-rule you have defined. - Under Schedule, the Start conditions box shows Without delay. This means that, by default, the sub-rule starts as soon as the reference box becomes active. You can define one or more start conditions. Click the Add button to add a Start condition. The Add Start Condition window appears. - From the Select type list, select one of the following: - Without delay. To start the sub-rule as soon as the reference is activated. - Delay (default). To start a specific time after the reference becomes active. Enter this time in the Delay field. - Clock Time. To start at a specific day and time. - Trial Control variable. To start when a Trial Control variable gets a specific value. - Repeat steps 5–6 to add more start conditions. If you want to delete a start condition, select it and click the Delete button. - Under Stop conditions, select one of the options to specify whether you want the sub-rule to be repeated once or more times. - If you select to repeat the sub-rule, the Repeat interval option becomes available. Select: - Stop to Start (default). To keep a constant time between the stop of a repeat and the start of the next repeat. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Sub-Rules (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-sub-rules-continued-TnV Chapter: EthoVision XT Sub-rules (Continued) If your variable is of the type true/false, and switches between true and false several times, the sub-rule starts only the first time that the variable gets the value required since the activation of the Reference. For more information on Trial Control variables, see page 28. Sub-rule Stop Conditions - Execute sub-rule once per start condition (default): The sub-rule is executed once when one of the Start conditions is met. - Repeat indefinitely (no scheduled stop): The sub-rule is repeated until the trial stops (see page 69 for how this can happen). - Repeat per start condition: The sub-rule is repeated a number of times, or until a condition is met. - For a number of times. To have the sub-rule repeated a fixed number of times for that start condition. Enter this number in the box (default = 2). - For a duration of (hh:mm:ss). To have the sub-rule repeated for a specific time period beginning from the corresponding start condition. Enter this time in the box. The maximum time allowed is 99 h 59 min 59 sec. Choose this option if you want a task to be repeated for some time, no matter how many times in that period. If you choose this option, when the time elapsed since the start condition exceeds the time set here, the ongoing repeat will continue till its end, but no new repeat will start. - Until Trial Control variable. To have the sub-rule repeated until a Trial Control variable (see page 28) gets a certain value. Click Edit, specify the variable, its value and click OK. For example, repeat the sub-rule until the variable Count reaches 100. Specify Count <= 100. If you select two or more Repeat per start condition options, no more new repeats are started as soon as any of the conditions is fulfilled. A sub-rule is completed when the last repeat for the planned Start condition is ended. See also the note on Endless loops on page 65. Options for Starting a New Repeat - Do not start new repeat when there is still a repeat ongoing. A new repeat is not started. A new repeat will start at the planned time, after the ongoing repeat has been completed. - Delay new repeat till ongoing repeat finishes. The repeat starts as soon as the ongoing repeat finishes. - Terminate ongoing repeat and start new one. The ongoing repeat is ended no matter at which point it is, and a new repeat is started. Example: A sub-rule is planned to start every 10 minutes. The first Start condition is set to 12:00 h, the second to 12:20 h etc. Suppose that at 12:10, a repeat has not been completed yet, and it will be completed at 12:15. - When selecting the first option above, the repeat planned at 12:10 is not started. The program will start the next planned repeat, at 12:20, provided that the first repeat has been completed. - When selecting the second option, the repeat of 12:10 starts at 12:15 when the first repeat has been completed. - When selecting the third option, the repeat of 12:10 starts at the planned time. The repeat of 12:00 is forcibly terminated. If Trial Control switches on a light or sound device at the time the repeat is aborted, that device stays on until a switch off command is encountered in the next repeat (or another ongoing sub-rule). Place the Sub-rule Reference in the Trial Control Sequence The position of the sub-rule's Reference box influences progress in the Trial Control sequence. Consider the difference between the following two cases: - Reference box in the linear sequence. Control can only progress when the Reference box becomes inactive. This occurs when the last repeat of the sub-rule has been completed. - Reference box on a dead branch of the sequence. When the sub-rule's Reference box becomes active, the box placed in parallel becomes active too. Thus, control moves forward independent of whether the sub-rule has been completed. For more information on activation of Trial Control boxes, see page 10. End a Sub-rule A sub-rule is normally ended when the last repeat (see page 63) is completed. However, it can also be forcibly interrupted in the following cases: - When the maximum trial duration has been reached. - When you stop the trial manually. - When a condition passes control to the next box in the sequence. When the Condition is met, the Any operator applies the OR logic, and passes control to the next box. The sub-rule is interrupted. - When the Reference box is placed on a dead end of the Trial Control sequence. Depending on the instructions specified in the Start-Stop Trial rule, the trial may stop before the last repeat of the sub-rule is completed. When the last repeat of the sub-rule is ended, the corresponding Reference box becomes inactive. See also the note about Endless loops on page 65. Call a Sub-rule from Another Sub-rule Within a sub-rule, you can define a reference that calls another sub-rule. Why insert a sub-rule within another sub-rule? Suppose that your Trial Control is made of four sub-rules that have at least some instructions in common. For example, sub-rules that start at different times, but include the instructions to have the program make a light flash. In such a case, you can define the instructions for the light flash in a separate sub-rule, and then in each of the four sub-rules insert a reference to this sub-rule. - Define the sub-rule that should contain the reference to another sub-rule (see page 61). - Define the sub-rule that should be called by the first one, and its own reference (see page 63). - Insert the Reference box of the second sub-rule in the sequence of the first sub-rule. Example of Calling a Sub-rule from Another Sub-rule Sub-rule 1 counts the number of times the animal enters the shelter via a particular route. When the animal does so (Condition A), a Reference box (B) calls Sub-rule 2. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Sub-Rules (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-sub-rules-continued-l24 Chapter: EthoVision XT Sub-rules (Continued) When the mouse enters the shelter via a particular entry. - A - Zone transition condition "Mouse enters the shelter via Entry zone 1" is met (A). - B - Reference to Sub-rule 2. - C - Action "Light on", followed by a Time condition "0.5 s" and an action "Light off". - 5 - Sub-rules Sub-rule 2 is a sub-rule defined to switch a light on for 0.5 seconds (see C for details). As soon as Sub-rule 2 is completed, control is taken back to Sub-rule 1 where the remaining instructions are executed. Notes - You can call sub-rules in up to 4 levels of existing sub-rules: for example, you can define the Start-Stop trial rule calling Sub-rule 1, which on its turn calls Sub-rule 2, which on its turn calls Sub-rule 3 etc, but you cannot have Sub-rule 4 calling Sub-rule 5. - EthoVision XT informs you when you try to create more than 4 levels of sub-rules. - If a sub-rule includes the reference to another sub-rule, it cannot be completed until the sub-rule that is called within it has been completed. - You cannot create circular references amongst sub-rules. For example: - Insert a reference in the sub-rule that this reference calls. - In Sub-rule 1, insert a reference to Sub-rule 2, which on its turn contains a reference to Sub-rule 1. - EthoVision XT informs you when you try to create a circular reference. Conditions Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Sub-Rules (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-sub-rules-continued Chapter: EthoVision XT Sub-Rules (Continued) Configuring Sub-Rule References To configure how a sub-rule repeats and starts, use the following options: - Start to Start: To keep a constant time between the start of successive repeats. For example, start repeats at every hour. Enter this time in the corresponding box (hh:mm:ss). - Select one of the options to specify what to do when a new start condition becomes true and a previous repeat is still ongoing. For details, see Options for Starting a New Repeat. - Under Comment, enter a description of the sub-rule reference (optional). - Click OK. The reference box is displayed on your Trial Control screen. - Insert the reference box in the appropriate place in the Trial Control sequence (this can be either the Start-Stop trial rule, or another sub-rule). Notes - If you want the sub-rule not to start immediately as its Reference becomes active, select Without Delay and click the Delete button. - If you accept the default options (Without Delay in the Start conditions box and one repeat), the sub-rule starts immediately and is repeated just once. - You cannot edit a condition that you have added to the Start conditions box. Delete the condition first (select the condition and click the Delete button), then click Add to add a new condition. - The Start conditions are listed in the following order: Without Delay, Delay, Clock Time, Trial Control variable. - Stop to Start of a Repeat: There is always at least 1 sample difference between the time that the Rule End box is evaluated and the time that the Rule Begin box is evaluated for the start of a new repeat. This means that a new repeat can never start exactly at the same time as the end of a repeat. Reference Names Names of sub-rule references must be unique in your experiment, unless you have re-used an existing reference. You cannot define two sub-rule references with the same name, even when these are defined in two different Trial Control Settings. This is because analysis of Trial Control data is based on names of elements (sub-rules, references, actions and conditions). Elements with the same name would give ambiguous results. Re-Using a Sub-Rule Reference If you choose to create a copy of a sub-rule reference and then change any property of this copy (Name, Reference options, or Comment), a window appears with the message Define the scope of your changes. The program asks you whether you want to apply the properties only to the newly-created reference, or to the references with the same name in all Trial Control Settings. Choose the option you require and click OK. If you re-use a Reference that is stored in another Trial Control profile, and this profile is locked after data acquisition, changing any of the Reference settings will not affect the Reference in the locked profile. Modifying a Sub-Rule Reference To modify a sub-rule reference, click the Settings button in the reference box. Multiple References to One Sub-Rule You can define multiple references to the same sub-rule, and place the corresponding Reference boxes in the same Trial Control sequence. In the case they are activated at the same time, the program executes the sub-rule in two parallel instances. Such instances are independent; however, they can interfere with each other if they both contain actions on a Trial Control variable or on hardware devices. Endless Loop Prevention EthoVision XT prevents the occurrence of an endless loop in the Trial Control, which would make EthoVision XT unresponsive. When in a Sub-rule Reference box the number of repeats is not set to a fixed value and the Sub-rule has a 0-second duration, this Sub-rule is evaluated endlessly from the Sub-rule Reference box. To prevent this, in EthoVision XT a Sub-rule is evaluated only once per sample from the Reference box. Sub-rules that are empty, only contain a Trial Control variable Action box, or Hardware Action boxes, are 0-second Sub-rules. With a 0-second Sub-rule, the Sub-rule Reference box never becomes inactive and, therefore, the Stop track Action box and Rule End box are never reached. In this case, the trial is stopped when you click the Stop Trial button (for live and offline tracking) or when the end of the video file is reached (for offline tracking). Sub-Rule Start Conditions To access these options, click Add in the sub-rule's Reference window. Without Delay Choose this option to start the sub-rule as soon as the sub-rule reference becomes active. Clock Time Choose this option to start the sub-rule at specific times of the day. - Select Trial Day: Select the day from the start of the trial that the sub-rule should start. 1st trial day = the same day that the trial starts. - Set Time (hh:mm:ss): Enter the time of the day that the sub-rule should start. Example: If you want to start the sub-rule at 12:00 h of the fifth day of the trial, select 5th day and enter 12:00:00. Delay Choose this option to start the sub-rule with a specific delay from the moment that the Reference box becomes active. Example: If you want to start the sub-rule one hour after the start of tracking, enter 01:00:00. Place the Reference box immediately to the right of the Start track box. The time that the Reference becomes active is essentially the time that the previous box in the sequence becomes inactive (a condition being met, or an action being taken). Trial Control Variable Choose this option to start the sub-rule when a Trial Control variable gets a certain value for the first time since the Reference becomes active. - Click the Edit TC-Variable button. The TC-variable condition window appears. - From the first list, select the Trial Control variable. If you need to create a new variable, click TC Variables. - Select the comparison operator (=, >, etc.) from the second list. - Do one of the following: - If you want to compare the Trial Control variable with another variable, select that variable from the third list. - If you want to compare the Trial Control variable with a numerical value, enter this value in the third list. - If you want to compare a Trial Control variable with a formula, click the double-arrow button and select the operator, then the variable and/or values to complete the formula. Example: You have defined the variable Phase which can have one of three values 1, 2, and 3 during the trial. You want to start a sub-rule when the current value of Phase is 2. Select Phase = 2. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Start-Stop Trial Rule URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-start-stop-trial-rule Chapter: EthoVision XT The Start-Stop Trial Rule The Start-Stop trial rule is displayed on your screen when you create or open Trial Control Settings. With this rule, you control the start and stop of data acquisition. The Default Start-Stop Trial Rule The default Start-Stop trial rule is a sequence of six boxes: - Rule Begin - Start-Stop Trial. Activated when you start the trial (from the Acquisition menu, select Start Trial, or click the Start Trial button, or press Ctrl+F5). Once you start the trial, control passes to the next box. - Condition - In Zone - Cumulative Duration >= 1 s. This is the default Start track condition. It is fulfilled when the center point of the subject (or of any subjects, in the case of an arena with multiple subjects) has been detected in the arena for 1 second after you started the trial. If you start the trial and the animal is not detected yet, the program waits until it detects the animal for 1 second, then it starts tracking. - Action - Start Track. Activated when the condition on its left side is met. Once this box is activated, data recording (tracking) starts. If the condition placed between the Start-Stop trial box and this box is not met immediately, tracking starts later than the time you start the trial. - Condition - Time - Infinite Time (condition never met). This is the default Stop track condition. This condition is never met. The trial stops when you give the Stop command or the time exceeds the maximum trial duration (when this has been set). - Action - Stop Track. Marks the end of all tracks (and trial). - Rule End - Start-Stop Trial. This box is just the delimiter of the rule; it does not take any action. Important: Always keep a Condition box that determines when the track is stopped right before the Stop track Action box, otherwise the trial stops immediately after you start the trial. The Start-Stop Trial Rule in Special Cases - Multiple Arenas. When working with multiple arenas, the rule is applied separately for each arena. This means that tracking can start at different times in different arenas in the same trial, depending on when the condition placed immediately before the Start track box is met in a specific arena. - DanioVision and Activity Analysis. If you selected Activity analysis in the Experiment Settings, or created a DanioVision experiment, there is no box between the Start-Stop trial and the Start track box. This means that tracking starts immediately when you click the Start Trial button. For more information on Activity analysis, see Activity analysis in the EthoVision XT Help, or the DanioVision DVOC-0041 - Reference Manual. - Behavior Recognition. If you selected Behavior recognition in the Experiment Settings, the default Trial Control rule contains a Time condition box set to 3 seconds. This means that tracking starts 3 seconds after starting the trial. This is done because the Behavior recognition algorithm needs 3 seconds of video images to make the first classification of behavior. With this condition you make sure that your track contains Behavior recognition data since the first sample. If you selected both Activity analysis and Behavior recognition in the Experiment Settings, the Trial Control Rule is the same as when you selected Behavior recognition only. For more information on Behavior recognition, see Behavior recognition in the EthoVision XT Help. An Important Distinction: Trial vs. Track - Trial. A trial can be viewed as a container for the data collected in one recording session. It starts when you give the Start command in acquisition and stops when the tracks for all arenas and subjects have stopped. - Track. A track corresponds to the actual recording of a subject's position and behavior. The start of a track may or may not coincide with the start of the trial. This depends on your Trial Control Settings. If you use the default Trial Control Settings, the track starts 1 second after the animal has been detected in the arena and stops when you stop the trial. A trial may contain one or more tracks. For example, if you track two subjects simultaneously, each trial includes two tracks, one per subject. Similarly, if your setup contains four arenas with two subjects each, each trial includes 4 arenas x 2 subjects = 8 tracks. In a multiple-arena setup, the end of a track does not necessarily mean the end of the trial. The trial ends when all tracks come to an end. Customize the Start-Stop Trial Rule Although you can customize your Start-Stop trial rule in a number of ways, you cannot delete the following boxes: Rule Begin, Rule End, Action - Start track, and Action - Stop track. Modify the Start Track Condition The default Start track condition is an In Zone condition. - To modify that condition, click the Settings button. In the window that appears, click Settings and specify the zone in which the animal should or should not be in order for the program to start tracking. - To use another condition (for example: start recording exactly 1 minute after starting the trial), delete first the current condition (click that box and press Delete) and insert the new one. - To start recording as soon as you start the trial, delete the Start track condition. Click the box immediately before the Start track box and press Delete. Modify the Stop Track Condition The default Stop track condition is a Time condition. - To modify that condition, click the Settings button and choose the option you require. - To use another condition, delete first the current condition (click that box and press Delete) and insert the new one. Important: Keep at least one condition between Start track and Stop track. If you do not do this, tracking stops immediately after tracking starts, resulting in no data. Important: If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment Settings, the Condition boxes based on Activity are removed from your sequence. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Start-Stop Trial Rule (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-start-stop-trial-rule-continued Chapter: EthoVision XT The Start-Stop Trial Rule (Continued) Call a Sub-Rule Sub-rules are subroutines of the Start-Stop trial rule. You can program EthoVision XT in such a way that a subset of Trial Control actions and conditions is called from a specific point in the Start-Stop trial rule. When this subset of instructions is finished (or repeated a number of times), the program resumes following the instructions of the Start-Stop trial rule. - Define a sub-rule. - In the Components pane, under Structures, click the button next to Sub-rule reference. Enter a name for the reference, and select the sub-rule you have defined. - Insert the reference box in the correct place in the Start-Stop trial rule. You cannot define a sub-rule reference without defining the sub-rule first. Examples of Start-Stop Trial Rules Start Data Recording at a Specific Time You want to start recording at a time you are not in the lab, for example at 23:00 h. Delete the default Start track condition. Define a Time condition. Select At clock time and enter 23:00:00. Click OK and place the resulting box before the Start track box. Before leaving the lab, click the Start trial button to start the trial. The program waits till 23:00 to start data recording. Start Data Recording with a Remote Control For this you need: - The USB-IO box PTIO-002x - The TTL Port Tester PTTB-001x, which can be used as a remote control Have EthoVision XT start tracking when you press the button on the TTL Port Tester. To do so: - Connect the TTL Port Tester to a TTL port of the USB-IO box. See The USB-IO Box and the Mini USB-IO Box. - In the Experiment Settings, define the TTL port for the TTL Port Tester. See Set the Port Connections and, when needed, assign devices to arenas. - In the Trial Control Settings, create a Condition based on the TTL Port Tester that becomes true when button 1 is pressed. - Place the condition box between the Start Trial box and the Start track box. - You can now use the TTL Port Tester as a remote control. Note that with this solution you must first click the Start trial button in EthoVision XT, which then waits for the button press. Stop Data Recording After the Maximum Time Has Elapsed Click Settings in the Condition box immediately before the Stop track box. Select After and enter the maximum time. Alternatively, instead of using a Time condition, you can also use the Maximum trial duration option. Water Maze: Stop the Trial When the Animal Has Found the Platform In the Arena Settings, make sure that the platform has been defined as a zone. In the Trial Control Settings, delete the default Stop track condition. Next, define an In Zone condition. - If you want the program to stop recording as soon as the animal is over the platform, select Frequency as Statistic and choose >= 1. Click Settings and select the platform zone. - If the animal sometimes swims over the platform without stopping, select Current duration and set the minimum time the animal must stay on the platform (for example, 3 seconds). Click Settings and select the platform zone. Click OK and place the resulting box before the Stop track box. Water Maze: Stop the Trial Either When the Rat Has Found the Platform, or After 60 Seconds The Arena Settings and the condition In platform zone are similar to those in the example above. The condition subject swimming for 60 s can be translated to Time >= 60 s. - A – Zone condition: The subject must be for at least 3 seconds over the Platform zone. Select Current duration >= 3s. - B – Time condition: 60 s since the track started. - C – "Any" operator box. The track stops when either condition is met. The two conditions are combined with OR logic. This solution results in tracks of different duration: less than 60 s for the animals that found the platform, and 60 s for the others. Tip: Instead of two Condition boxes in the example above, you can also define the In Zone condition box and set a Maximum Trial Duration. Multiple Open Fields: Starting Tracking When the Subject Is Released In this setup, four open fields are treated as separate arenas. You want to start acquisition when the animal is detected in the open field, independently of what happens in other arenas. This can be achieved by using the default Start-Stop trial rule. As soon as the subject is detected in an arena, tracking starts for that arena only. This way you do not have to release all the animals at the same time. Conditioning Test: Stop the Trial When the Conditioning Task Has Been Repeated N Times For example, when the animal has obtained 25 rewards: - Create a new sub-rule containing the instructions for the testing session: - Sub-rule Begin - Condition: Is subject on top of the shelter? - Action: Drop a pellet - Sub-rule End - Since the sub-rule is restarted immediately after the pellet has been dropped, you must ensure the sub-rule ends when the animal has visited the reward zone. Define a condition In Feeder zone that is met when the animal has been in the Feeder zone for at least 1 s without break (Current duration >= 1s). Place this box to the left of Rule End. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Start-Stop Trial Rule (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-start-stop-trial-rule-continued-xW2 Chapter: EthoVision XT The Start-Stop Trial Rule (Continued) - Create a Reference to the sub-rule (see page 63) and specify to have the sub-rule repeated 25 times. Place the resulting box at the left side of the Stop track box. Eight-Arm Radial Maze Stop the trial when the subject has been in four arms within 10 minutes. Combine eight conditions, one for each arm. At least four conditions must be met, no matter which arm the animal visits. - Create an In zone condition (see page 92) and specify that the Frequency for Arm 1 must be >=1. That is, the animal must have visited Arm 1 at least once. Do the same for each of the other arms. - Connect the resulting eight condition boxes in parallel using the N of All operator (see Figure 17). - Set the Maximum trial duration (see page 21) to 10 minutes to stop tracking in the case the animal fails to visit four arms in the meantime. For more information on operators of type N of All, see page 40. Important: The frequency of In zone can become high very easily when the animal walks along the edge of a zone. This may result in the condition being met sooner than expected. If that happens, increase the Zone exit threshold. If that does not help, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track. Figure 17 A Trial Control sequence for an eight-arm radial maze. The trial must stop when the animal has visited four of the arms at least once. - 1, 2,...8 - In zone condition boxes for Arm 1, 2,... respectively. A condition is met when the Frequency of In zone for that arm is greater than or equal to 1. - A - Operator that checks that at least four of the eight conditions are met. - B - Stop track box. When four conditions are met, the trial is stopped. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Trial Control Screen URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-trial-control-screen Chapter: EthoVision XT The Trial Control Screen To access the Trial Control screen, in the Experiment Explorer, click Trial Control Settings 1 in the Trial Control Settings folder, or from the Setup menu, select Trial Control Settings, then click Open and select Trial Control Settings 1. The Trial Control screen appears, showing the default Trial Control settings. You can also access the Trial Control screen by creating a new Trial Control Settings, or opening one other than Trial Control Settings 1. The Trial Control screen contains the following components: - Components Pane: Lists the conditions on which you can base your actions and the operators which you can use to combine conditions. - Trial Control Window: Shows the Trial Control Settings that are active. It contains a sequence of boxes connected by arrows. - Maximum Trial Duration Pane: Allows you to define a maximum duration for all trials. You can show or hide the Components pane and the Maximum Trial Duration pane by clicking the Show/Hide button on the components toolbar and selecting or deselecting the corresponding option in the menu. The Components Pane With the Components pane you choose the blocks that build up your trial control rules. Expand the list by clicking the More button. Not all the components listed below may be available on your screen, depending on what EthoVision XT license you have on your computer. Conditions - Time - Time Interval - Trial Control Variable - Dependent Variables: To define a condition based on a variable that describes the animal's behavior, for example velocity, presence in a zone, movement, etc. Note: You cannot define a condition based on behaviors scored manually, behaviors detected automatically with Behavior Recognition, Activity state, Acceleration state, or Free intervals. - Hardware: To define a condition based on the state of a hardware device. If devices are not listed, you must first configure EthoVision XT so that it recognizes the devices. Actions - Trial Control Variable - External Command - Hardware Structures - Sub-Rule: To define a subroutine that can be called from a specific point of the Trial Control sequence. - Operator: To combine two or more conditions in such a way that an action is taken when All, Any, or N of All conditions are met. - Reference: To insert a call to a sub-rule within a sequence of instructions. To Define a Sub-Rule, Condition, Action, or Operator Do one of the following: - Double-click its name. - Click the button next to it. - Drag the name from the Components pane to the middle of the screen. A new Trial Control box appears in the top-left corner of the Trial Control window. Insert the new box in the sequence of boxes. The Trial Control Window The Trial Control window contains the sequences of instructions (rules) currently present in the Trial Control Settings. When you create a new Trial Control Settings profile, the Trial Control window contains the default Start-Stop trial rule, consisting of six boxes connected by arrows. You can then define: - Your own conditions that determine the start and stop of data acquisition. - If your EthoVision license includes Advanced Trial Control: - Additional sub-rules — sequences of actions and conditions that work like subroutines in a program, which can be called from another point in the Trial Control sequence. - Control hardware devices, such as a food dispenser or a door. Grid The Trial Control boxes automatically snap to a grid. You can change this by clicking the Show/Hide button on the component toolbar and selecting or deselecting the two Grid options (Snap to Grid and Show Grid). Zoom The component toolbar of the Trial Control Settings shows three zoom icons: - Zoom In: You can keep zooming in until all Trial Control boxes fit in the window. - Zoom Out - Zoom to Fit: Clicking this button fits all Trial Control boxes into the window. The Trial Control window is dynamic, meaning it expands when you move Trial Control boxes to the right. You can navigate from left to right in the Trial Control window using the scroll bar at the bottom. Use the Zoom to Fit button in the component toolbar to make all Trial Control boxes visible. Trial Control in Special Cases - If you selected Activity Analysis in the Experiment Settings, the first condition box is removed from the default Start-Stop rule. To carry out tracking and activity analysis simultaneously and start tracking when your subject is detected in the arena for a specific time, insert a new In Zone condition box in the Start-Stop rule. - If you selected Behavior Recognition in the Experiment Settings, the default Trial Control rule also contains a Time condition box (3 seconds), meaning that tracking starts 3 seconds after starting the trial. - If you selected both Activity Analysis and Behavior Recognition in the Experiment Settings, the same Trial Control rule is used as for Behavior Recognition only. To Export Trial Control Settings You can export an image of the Trial Control Settings: - Click the Export Image button on the toolbar. - Select a location to save the image to, type in the File Name or accept the default, and select an image type from the Save as Type list. - Click Save. The complete Trial Control window is exported, irrespective of the zoom factor. Maximum Trial Duration Pane Use the Maximum Trial Duration pane to define a maximum duration for the trial. This prevents EthoVision XT from waiting indefinitely for a condition to be met. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Trial Control Screen (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-trial-control-screen-continued Chapter: EthoVision XT The Trial Control Screen The trial runs indefinitely until the condition to stop the trial is met. Example: In a novel object test, in the Start-Stop Trial rule you have defined a condition 'stop the track when the mouse enters the zone with the familiar object'. It may happen that the mouse completely ignores the familiar object and only pays attention to the novel object. To prevent EthoVision from never stopping tracking, set a maximum trial duration. Accessing Maximum Trial Duration In the Trial Control Settings screen, locate the Maximum Trial Duration pane, right below the Components pane. If you do not see it, click the Show/Hide button on the toolbar and select Maximum Trial Duration. Notes Instead of using a Maximum Trial Duration, you can also define a condition based on time and place it immediately before the Stop Track box. However, there are two important differences: - If you use the Maximum Trial Duration, the program counts the time from the start of the trial (indicated by the Start-Stop Trial box). A condition placed immediately before the Stop Track box instead considers the time from the start of data recording (indicated by the Start Track box). The two starting points may not be the same if you have a condition between Start-Stop Trial and Start Track that makes data recording start some time later than the trial. - With a multi-arena setup, a Maximum Trial Duration stops the trial (and thus data recording) in all arenas simultaneously, even when data recording had started at different times. A time condition placed between the Start Track and Stop Track box instead stops data recording in one arena when the condition is met in that arena. This means that data recording can stop at different times in different arenas. Example: You set data recording to start when the animal is detected for the first time in its arena. For this purpose, you make an In Zone-based condition. Next, you define a 5-minute Time condition and place it immediately before the Stop Track box. If the animals are detected for the first time at different times in different arenas, data recording stops at different times too, because of the 5-minute interval set for all arenas. The trial ends when the recording stops in the last arena. The Maximum Trial Duration is not applied when you record video with the option Save Video Only, Track Later. You must stop video recording manually. When you track from the resulting video file, the Maximum Trial Duration is applied. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Usb-Io Box And The Mini Usb-Io Box URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-usb-io-box-and-the-mini-usb-io-box Chapter: EthoVision XT The USB-IO Box General Information The Noldus USB-IO box (type number PTIO-002x) is the device that the EthoVision XT video tracking software must use in order to work together with external devices such as the Noldus Pellet dispenser, the Noldus Lickometer or the light and sound devices of the PhenoTyper Top Unit. With one USB-IO box you can operate: - Up to 12 Pellet dispensers or other TTL-driven devices. - Up to 12 Lickometers. - Four PhenoTyper Top Units (by default), expandable to a maximum of 52. For this special connection, port SDI is reserved. For information on which third-party devices can be connected to the USB-IO box, see the third-party devices section. Note: The total number of devices that you can connect is limited by the number of ports on the USB-IO box. For example, because the Lickometer uses the same type of port (named SDI) as the PhenoTyper Top Unit, and 13 SDI ports are available on the USB-IO box, if you connect 52 Top Units, all the suitable ports of the USB-IO box are occupied. Therefore no Lickometer can be connected. When planning your experiment, make sure that you have enough ports on the USB-IO box for the devices you want to use. A Typical Setup - Connect the hardware devices to the computer, via the USB-IO box. Important: Always connect the USB-IO box to a USB port of your PC, not to a USB hub or a docking station for laptop computers. - If you use a laptop and encounter issues, connect the USB-IO box to a USB port on the other side of the PC. - If you use a desktop, connect the USB-IO box to a USB port on the back of the PC. - Define the hardware configuration in EthoVision XT. - With the Trial and Hardware Control function of EthoVision XT, you can define: - Actions on the hardware device (for example, Drop a pellet). - Conditions that must be met in order for Trial Control to progress. - Sub-rules for a sequence of actions and conditions to be repeated. - Acquire data using the Trial Control settings specified above. Defining hardware configuration means that you specify which communication ports of the USB-IO box are connected to which hardware devices, and, in the case you work with multiple arenas, which individual device is assigned to which arena. Connectors and Displays - Front Panel TTL Control 1...12 These are input/outputs for devices that are controlled with TTL (Transistor Transistor Logic). Use a TTL port for the following devices: - Noldus Pellet dispenser (Noldus type number PTPD-001x). - Noldus Beam controller (Noldus type number PTBC-001x). - Shock, Tone, Light and Noise in the Ugo Basile Fear Conditioning System. - White light in the Noldus Backlight unit. - Noldus Pellet receptacle (Noldus type number PTPR-001x). - The Med Associates Activity Wheel Brake (ENV-042). - Any custom hardware device that works with TTL signals. - The TTL Port Tester (PTTB-001x; for testing purposes). - The USB-IO box monitor (virtual device; for testing purposes). - The TTL devices of PhenoTyper 2. Note: With EthoVision XT 17.5 and newer versions you can let EthoVision XT control the Ugo Basile Fear Conditioning System without the Noldus USB-IO box. See the connection schemes in the EthoVision XT 18 - Application Manual. Notes: - Each of the 12 TTL control connectors can provide limited supply power (18 Volt DC, max. current 100 mA) available on pin 1 (ground) and 2 (+). - You can control up to two physical devices with one TTL port. A typical example of controlling two devices with one TTL port is the Shock and Tone devices in the Fear Conditioning System. For this you need a split cable from the TTL port that ends in the two devices. Please contact Noldus if you need such a cable. - Ports are organized in groups of four. To optimize communication speed, connect TTL devices to ports in the same group. For example, connect four pellet dispensers to ports 1 to 4, not to ports 1, 5, 7 and 12. Use ports 1–4 first, then 5–8, etc. LEDs - Power – When the light is on, it indicates that the USB-IO box receives power from the mains adapter. - USB – When burning, it indicates that the USB-IO box is connected to a computer's USB port. - TTL – When burning, it indicates that communication to a TTL device is in progress. - SDI – When burning, it indicates that communication to a SDI device is in progress. Connectors - Rear Panel SDI Control 1...13 SDI stands for Special Device Interface. SDI control ports are inputs/outputs for devices that are controlled with a serial data stream. You can connect one physical device to a SDI port. Use these ports for the following devices: - The Noldus Lickometer (Noldus type number PTLM-001x). - The Top Unit Interface of PhenoTyper 1 (Noldus type number PTTI-001x). - The Noldus PhenoWheel. - The Med Associates Activity Wheel Counter (ENV-042). Notes: - Each Top Unit Interface is connected to one port of the USB-IO box, and can control up to four PhenoTyper 1 Top Units. For more information, see the PhenoTyper - EthoVision XT 18 - Reference Manual. - SDI control port 13 is set by default to connect the Top Unit Interface. If you want to connect two or more Top Unit Interfaces, you must alter the jumpers for the ports other than 13 that you use to connect the Top Unit Interfaces. - Each of the 13 SDI control connectors can provide limited supply power (12 Volt DC, max. current 100 mA) available on pin 1 (ground) and 2 (+). - All SDI devices mentioned above receive their full power supply from the 12 Volts provided by the USB-IO box. USB Connects the USB-IO box to the PC using a USB cable with one connector of type A and one connector of type B. Important: Always connect the USB-IO box to a USB port of your PC, not to a USB hub or a docking station for laptop computers. If you use a laptop and encounter issues, connect the USB-IO box to a USB port on the other side of the PC. If you use a desktop, connect the USB-IO box to a USB port on the back of the PC. 24V In Connects the USB-IO box to the power supply via the 24V adapter. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Usb-Io Box And The Mini Usb-Io Box (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-usb-io-box-and-the-mini-usb-io-box-continued-7z6 Chapter: EthoVision XT Jumper and DIP Switch Configuration Default DIP Switch Settings Open the USB-IO box cover. The DIP switches are located in a red block on the main board. The default settings are (from 1 to 8): 1 Off, 2-8 On. This sequence Off-On-On... corresponds to 00000001, that is 1 in binary language. Jumper JMPR8 Configuration The jumper position 1/2 is marked right of JMPR7. The jumper JMPR8 is set by default to position 2. If you want to use SDI port 13 to connect a Top Unit Interface, leave it in that position. If you want to use port 13 to connect a Lickometer, set it to 1. Alter the DIP Switches Follow this procedure if you want to connect multiple USB-IO boxes to the EthoVision XT computer. DIP switches determine the ID of the USB-IO box. Multiple boxes must have different IDs (and therefore different DIP switch settings) in order to work properly with EthoVision XT. - For the first USB-IO box, leave the DIP switch settings as default (1 Off, 2-8 On). - For the second USB-IO box, use a pen or a small screwdriver to move DIP switch 1 to On and DIP switch 2 to Off (this corresponds to 00000010, that is 2 in binary language). - For more USB-IO boxes, move the DIP switches to create unique numbers. Configure EthoVision XT Prerequisite Make sure that the USB-IO box is connected to the EthoVision XT computer, that all devices are connected to the USB-IO box, and that the USB-IO box is connected to a power supply. If you use multiple USB-IO boxes, connect them all to the EthoVision XT computer. Procedure See Control Hardware Devices on page 110. The Mini USB-IO Box Overview The Noldus Mini USB-IO box (type number PTIO-003x) is an interface device used to control external devices such as an Atlantis platform, a shocker, etc., from the EthoVision XT video tracking software. It is a smaller and simplified version of the USB-IO box (type number PTIO-002x). It is also embedded in the DanioVision system for zebrafish tracking. Ports The Mini USB-IO box is provided with the following ports (see the top panel of the box): - USB — Connects the USB-IO box to the PC using a USB cable. - TTL Control 1–4 — Four TTL control connectors. Each connector can provide limited power supply (18V DC, max. current 100mA) available on pin 1 (ground) and pin 2 (+). - Multi TTL Output — One Multi TTL output connector. - SDI Control — Currently used in the DanioVision system; will be used in future applications of the stand-alone Mini USB-IO box. - 24V In — Connects the USB-IO box to the power supply via the 24V adapter. LED Indicators - 24V On — Switches on when the Mini USB-IO box is connected to a power source. - TTL Control Busy — Blinks whenever the Mini USB-IO box communicates with a TTL-controlled device. - SDI Control Busy — Blinks whenever the Mini USB-IO box communicates with a SDI-controlled device. TTL Control With a TTL port you can control the following devices (one per port): - The Noldus Backlight Units (Noldus codes XIRWB-xxxx). - The Noldus Pellet dispenser (Noldus code PTPD-xxxx; maximum two). To use the Pellet dispenser with the Mini USB-IO box, you must replace a device file in EthoVision XT. See the instructions in the chapter The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 18 - Service Manual, accessible from All Apps > Noldus > EthoVision XT 18 Other Documentation. - Any custom hardware device that works with TTL logic (up to two devices per port). To control a PhenoTyper setup, you must use the Noldus USB-IO box PTIO-002x for full PhenoTyper add-on hardware support. If you want to control the doors of an 8-arm radial maze, you can use the TTL ports. Since the Mini USB-IO box has 4 TTL ports, you have a total of 8 output lines, which can control all eight doors. Please contact Noldus for more information. Multi TTL Control With the Multi TTL output, you can control up to 16 devices independently. This output is suitable for controlling maze doors in an 8-arm radial maze, lights, or any other devices with a TTL control input. - The connector is a 20-pin IDC. - Supply voltages provided: +5V, +12V, and common ground. - There are no TTL input lines available on this connector. Because of this, you cannot use Multi TTL to control the Noldus Pellet dispenser or any other device that requires input channels. SDI Control This is currently in use in combination with the DanioVision Observation Chamber. Do not connect SDI devices such as the Lickometer or the PhenoTyper Top Unit Interface. The Mini USB-IO Box Device Driver Software The current driver software for the USB-IO box and Mini USB-IO box is installed automatically when you install EthoVision XT. For EthoVision XT 18, the driver software for both the USB-IO box, the Mini USB-IO box, and DanioVision is Noldus HardwareInterface USB-IO box 5.1.14. To check that the driver is installed, open the Control Panel and go to Programs and Features / Add or Remove Programs. The driver name is Noldus - HardwareInterface IoBox - x64 Package - 5. If you want to uninstall the driver software, in Control Panel > Add or Remove Programs, select Noldus - HardwareInterface IoBox - x64 Package - 5 and click Uninstall. Older Versions of the Mini USB-IO Box Device Driver It is not necessary to uninstall the drivers of previous versions of the Noldus USB-IO box or the Noldus Mini USB-IO box. Note that for EthoVision XT 11 and older versions, the USB-IO box and the Mini USB-IO box had separate drivers. To Connect the Mini USB-IO Box Note: If you want to control the Pellet dispenser with the Mini USB-IO box, first follow the instructions in the chapter The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 18 - Service Manual, accessible from All Apps > Noldus > EthoVision XT 18 Other Documentation. - Connect the Mini USB-IO box to a USB port on the EthoVision XT computer using the USB cable that comes with the Mini USB-IO box. - A message may appear as you plug the USB cable into the computer USB port. Wait until the driver software is installed. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Usb-Io Box And The Mini Usb-Io Box (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-usb-io-box-and-the-mini-usb-io-box-continued-1Tt Chapter: EthoVision XT The USB-IO Box and the Mini USB-IO Box To connect the Noldus USB-IO box or the Mini USB-IO box to a third party device with BNC connectors. Important: This isolator is not intended for medical applications! Features - It supports TTL-output from and TTL-input to EthoVision XT (two lines each). - Output/input voltages 0-5 V. - Isolation protects the device from the so-called "ground loops". - Minimizes noise and prevents damage to the USB-IO box in the case the device connected does not function properly. Package Contents - PTISO-00x0 TTL-IO Isolator. - 1x network cable with RJ45 connectors. - 2x input/output double cables with BNC connectors. Connect and Use - Connect a TTL port of the Noldus USB-IO box / Mini USB-IO box to the TTL-I/O port of the PTISO-00x0 Isolator. - Connect one or more of the In/Out BNC connectors of the PTISO-00x0 Isolator depending on your setup. For example, to trigger a device, use Out 1 or Out 2. - When setting the port connections, specify the TTL port and the line used. Technical Specifications PTISO-0010 TTL-IO Isolator - Type Name: PTISO-0010 TTL-IO Isolator - Power Requirements: 18-24 V DC; 0.02 A from USB-IO box - Isolation Value: Supply 2kV (1 sec); TTL IO 5.3 kV (1 sec) - Connections: 1x RJ45 type from USB-IO; 4x BNC type, optical isolated TTL input/output - Input/Output: TTL level signal (0-5.5 V DC) - Dimensions: 31 x 113 x 67 mm (1 7/32 x 4 29/64 x 2 41/64 inches) USB-IO Box Version 2 - Noldus Model Number: PTIO-002x - Power Supply: 24 V DC - Current Consumption: Max 2.0 A (varies depending on the number and type of devices connected) - Connections: - 12 TTL control connections (24 TTL input lines and 24 TTL output lines) with RJ45 ports - 13 Special Device Interface connections with RJ45 ports - Cables: - Power supply 24V 3A DC with mains adapter - USB cable with connectors of type A and B - Operating Temperature: 0 to +40 °C (+32 to +104 °F) - Storage Temperature: -20 to +70 °C (-4 to +158 °F) - Operating Humidity: Up to 80%, no condensation - Dimensions: 160 x 160 x 90 mm / 6.3 x 6.3 x 3.5 inches (L x W x H) Mini USB-IO Box Version 1 - Noldus Model Number: PTIO-003x - Power Supply: 24 V DC - Current Consumption: 1.0 A (varies depending on the number and type of devices connected) Important: Max. overall current for all TTL ports must not exceed 0.5 A! - Interface to PC: USB-2 - I/O Connections: - 4 TTL control (representing 8 TTL input lines and 8 TTL output lines) with RJ45 modular type connectors - 1 Multi TTL (representing 16 TTL output lines and external device supply) with 20 way IDC connector - 1 Special Device Interface with RJ45 modular type connector - Cables: - Power supply 24V type 70 A24 with mains adapter - USB cable with connectors of type A and B, 3m type SB2403 - Operating Temperature: 0 to +40 °C (+32 to +104 °F) - Storage Temperature: -20 to +70 °C (-4 to +158 °F) - Operating Humidity: Up to 80%, no condensation - Dimensions: 175 x 81 x 30 mm / 6.9 x 3.2 x 1.2 inches (L x W x H) Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Usb-Io Box And The Mini Usb-Io Box (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-usb-io-box-and-the-mini-usb-io-box-continued-Gu4 Chapter: EthoVision XT Testing the TTL Port Tester - Connect the TTL Port tester to the TTL port on your USB-IO box which you want to test, using the green RJ45 modular network cable. When both the USB-IO box and the TTL Port tester are properly connected, the TTL power LED on the TTL Port tester is on. - Start EthoVision XT and open your experiment. In the Experiment Explorer, click Arena Settings. - In the Arena Settings window, click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, under the arena name, select TTL Port Tester (PTTB-001x) and click the Test button. - A new window appears. In the Command drop-down list, select either Light 1 on, Light 1 off, Light 2 on, or Light 2 off and click Test. Check the LEDs on the TTL Port tester (Light 1 corresponds to OUT-1, and Light 2 to OUT-2) and the information in the window. Note: The signal from and to the TTL Port tester is not a network signal. The TTL Port tester cannot be connected via a network hub or similar. Manual Input You can also manually supply TTL input events to a TTL port. Follow steps 1–5 in the procedure above. Press either button IN-1 or IN-2 on the TTL Port tester and check the result in the window. Simulate a TTL Device You can connect the TTL Port tester to a TTL port that is defined for another TTL device, for instance, the Noldus Pellet dispenser. In this way, you can simulate the working of the device. You will see that the OUT-1 LED on the TTL Port tester is turned on whenever EthoVision XT decides to have the dispenser drop a pellet. Because it is not the pellet dispenser connected to the port, there will be no "pellet dropped" reply, but you can simulate this by pressing the IN-1 button on the TTL Port tester. The IN-2 button on the TTL Port tester is connected to the same input as the "error" line of the pellet dispenser. With a pellet dispenser connected, this line will become active whenever the dispenser fails to drop a pellet. By pressing the IN-2 button, you can simulate this occurrence. Trigger an Action with the TTL Port Tester You can use the manual input buttons on the TTL Port tester to trigger an action, for instance, switch on a light. Define a Trial Control condition based on the TTL Port tester and define that the light is switched on when, for instance, IN-1 is pressed. - Open your Trial Control Settings and in the Components pane click the button next to TTL Port Tester (under Conditions - Hardware). - In the Signal to check drop-down list, select one of the following: - Is button 1 pressed? or Is button 2 pressed? — In the Signal value drop-down list, select True, then click OK. The light will be on as long as the button is pressed. - Button 1 presses or Button 2 presses — In the Signal value drop-down list, select = and enter the desired value, then click OK. To define the appropriate action: - In the Components pane under Actions, click the button next to the hardware you want to control. - In the Action to perform drop-down list, select which action should follow the condition you defined above. Then click OK. - Insert the Condition and Action box in the appropriate position in the Trial Control rule. Use the TTL Port Tester as a Manual Event Recorder Although you can score behaviors manually with EthoVision XT, you can also do so with the TTL Port tester. For example, in a resident-intruder test, during acquisition press the IN-1 button when the resident mouse is aggressive and the IN-2 button when the intruder mouse is aggressive. For more complex coding schemes, use the Manual Scoring Settings in EthoVision XT. If you use the TTL Port tester as a manual event recorder, you can view the number of key presses in a hardware log. In EthoVision XT, from the Export menu, choose Track Data and select the Hardware log check box. Calculate the Statistics for the TTL Port Tester For testing purposes, you can calculate the number of times the buttons were pressed, or visualize when the lights were switched on. To do so, in the Analysis profile: - To analyze and visualize button presses, under Hardware click the button next to Hardware Continuous. In the window that appears, next to Device type, select TTL Port Tester (PTTB-001x). Next to Device, select the correct device if you have more than one device connected. Next to Signal, select Button 1 pressed or Button 2 pressed. - To analyze or visualize the time when the lights were switched on, under Hardware select Hardware Command or Hardware State. Choose Command to view the time that the command was given. Choose Hardware State to visualize the status of the light (feedback from the TTL Port tester). - In the Trial Statistics tab of the variable properties window, select the statistic Total, then click Add. You can now calculate the number of times the button was pressed, or the light was switched on and off, by running an analysis. Choose Analysis > Results > Statistics & Charts. Make sure that the correct Analysis profile is selected on the toolbar, then click Calculate. You can also visualize the button presses and the light being switched on and off in the Integrated Visualization. Choose Analysis > Results > Integrated Visualization. You will then see in the Time Event Plot when the buttons were pressed, or when the lights were switched on and off. The Optical Isolated TTL-IO Interface Aim To enable isolation between the Noldus USB-IO box or the Mini USB-IO box and a third-party device, for example the Inscopix nVista camera system. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Usb-Io Box And The Mini Usb-Io Box (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-usb-io-box-and-the-mini-usb-io-box-continued-Gar Chapter: EthoVision XT Connecting the Mini USB-IO Box - Connect the Mini USB-IO box to the power supply using the appropriate cable and the mains adapter. The LED 24V On switches on. - Plug one of the ends of the modular network cable in the hardware device. - Plug the other end of the cable in one of the ports available on the Mini USB-IO box. Note: If you disconnect the Mini USB-IO box while EthoVision XT is open, reconnect it. Note that it can take some time before the Mini USB-IO box is recognized after you reconnect it. Although you use modular network cables to connect devices to the USB-IO box, the signal from and to the device is not a network signal. The device cannot be connected via a network hub or similar. The modular network cable comes with the hardware device, not the Mini USB-IO box. Connect Custom Hardware Whenever you want to connect your own device to a TTL control connector of the Mini USB-IO box, do so according to the information below. The TTL connector will provide supply (18VDC) and TTL output and input to your device. It is a standard RJ45 modular type. Pinning and cable wire colors for the mating patch cable are shown in the figure below. To power a device, a +18 Volt power supply can be provided via pin 2 (orange). Common ground for both power and TTL on pin (orange/white-brown). Important: Max. overall current for all TTL ports must not exceed 0.5 A! Whenever the device to be connected needs some other (lower) supply voltage, you must use some regulator in between or connect a separate power adapter to it. Input of a TTL Device Two input lines are available for each TTL connector, TTL-1 and TTL-2, connected to line 5 (white/blue) and (blue) respectively. In the example below, two switches send inputs to EthoVision XT via a TTL port. You can use the TTL input to monitor the status of devices connected to those input connections. Inside the Mini USB-IO box, all TTL input lines are forced high to the +5V TTL logic level by a pull-up resistor. This enables open collector interfacing from your device into the Mini USB-IO box or you can just connect a simple switch between it and the ground. However, you can also connect any TTL logic level signal (0 Volt/5 Volt) to the input. To prevent unwanted behavior of input lines caused by noise or signal spikes, inputs are protected by debounce/ESD protection circuits. Output of a TTL Device You can use TTL output to control any external device by simple 5V TTL logic. Each of the 4 TTL ports on the Mini USB-IO box is equipped with 2 TTL output lines. Every output line is protected with a current limiting resistor of 100 ohm. Maximum load current of the output is 10mA. Multi TTL Output Connector The Multi TTL output connector contains 16 independent output lines. Advised connector: Assmann AWP20-7240-T-R. - Pin 1–16: 16 x TTL compatible output lines (TTL-1 to TTL-16). - +5 Volt reference (max load 10 mA). - +12 Volt reference (max load 10 mA). - Pin 19, 20: Ground. Note: No TTL input lines are available on this connector. To control non-TTL hardware, some kind of interfacing may be needed. The Mini USB-IO Box and EthoVision XT Defining hardware configuration means that you specify which communication ports of the Mini USB-IO box are connected to which hardware devices, and, in the case you work with multiple arenas, which individual device is assigned to which arena. - Connect the hardware devices to the computer through the Mini USB-IO box, then start EthoVision XT. - Create a new experiment or open an existing one. - Under Setup, click Experiment Settings. Define the main characteristics of the experiment. - Select Use of Trial Control Hardware and click Settings. - In the window that opens, select Noldus Mini USB-IO Box. - In the Device Configuration window, select the devices you require. For more information on this step, see set the port connections on page 116. - Under Setup, select Arena Settings. Define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. If you have only one arena, you can skip the steps below. The hardware is automatically assigned to the arena. If you have more than one arena, proceed with step 8. - Click the Arena - Hardware Mapping button in the Arena Settings window. - Click Add Device. Under Device Type, select the device and assign it to one of the arenas. Repeat this step for all the individual devices in your setup. Make sure you assign each device to one arena. For more information on this step, see assign devices to arenas on page 121. - Choose Setup > Trial Control Settings. Define the Trial Control protocol. Note: To use the Pellet dispenser with the Mini USB-IO box, you must replace a device file in EthoVision XT. See the instructions connect the pellet dispenser in the chapter The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 18 - Service Manual. Note: If you created a DanioVision experiment, or if you used a DanioVision predefined template, select the DanioVision version that you have. For more information on setting up an experiment with the DanioVision Observation Chamber, see the DanioVision DVOC-0041 - Reference Manual. The TTL Port Tester Use the TTL Port tester to test or demonstrate the TTL control functionality of the USB-IO box. You can also use it to simulate a TTL device (for example a pellet dispenser), trigger an action (for instance, switch on a light) or as a manual input device. Your TTL Port tester package includes a TTL Port tester PTTB-001x with a green RJ45 modular cable connected (1 meter long). Technical Specifications - Noldus Device Number: PTTB-001x - Power Supply: 5 V DC, supplied by the USB-IO box - Current Consumption: 30 mA (when one of the LEDs is on) - Connector: RJ45 8 pin modular - Dimensions: 60 x 40 x 20 mm (l x w x h) - Weight: 50 grams - CE compliant in accordance with EMC directive 2004/108/EC Test the USB-IO Box TTL Functionality The following steps assume that you have set the port connection in the Experiment Settings and assigned the TTL Port tester to the arena. - Make sure that the USB-IO box is connected to (A) your EthoVision XT computer and (B) a power supply. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Usb-Io Box And The Mini Usb-Io Box (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-usb-io-box-and-the-mini-usb-io-box-continued-y6S Chapter: EthoVision XT Connecting Third-Party Devices Connect a Third-Party Device: Two-Switch Device Connect switch 1 between TTL input1 (color: blue/white) and ground (color: brown). Connect switch 2 between TTL input2 (color: blue) and ground (color: brown). To read the status of each switch with EthoVision XT, in the Port device mapping window select the TTL port that is connected to the switch device and under Device type select TTL Port Tester. To define a condition based on this device, use the Is button 1/2 pressed option (to check that a switch is on/off) or the Button 1/2 presses option (to check the number of presses). Note: When a switch is open, the TTL value of the corresponding input is High. When a switch is closed, the TTL value of the corresponding input is Low (0). Connect a Third-Party Device: Simple Lever When the lever is a simple "switch" that makes contact from signal to ground, without a circuit board in it, you can connect the device directly to a TTL input line of the USB-IO (or mini USB-IO) box. - When the lever is not activated, the input is "high" (logic 1). - When the lever is pressed, input will go to "low" (logic 0). Connect pin 1 and/or pin 8 for ground and either pin 5 or pin 4 for TTL input 1 or 2 respectively. Note: Inside the (mini) USB-IO box, all TTL input lines are "forced high" to 5Volt TTL level by an internal resistor. Whenever an input line is not connected (open), it is interpreted as logical "high" or 1. If this line is connected to ground it will be seen as logical "low" or 0. Note: These instructions are valid if the lever is based on a (micro) switch. Other retractable levers may need a different connection. Using Multiple USB-IO Boxes It is in principle possible to connect multiple USB-IO boxes to the EthoVision XT computer, provided that each box has a unique ID. A setup with two USB-IO boxes was tested. In practice, there may be limitations due to the number of devices attached and controlled simultaneously with EthoVision XT. For example, events like a pellet drop may be skipped if they occur simultaneously with other input and output events. We always recommend testing a specific setup before carrying out the actual trials. Procedure - Make sure that each USB-IO box has a unique ID. To do so, adjust the DIP switches in one of the USB-IO boxes. See Alter the DIP Switches for details. - Connect each USB-IO box to its own power supply; do not use power feed-through cables. - Connect each USB-IO box to a separate USB port of your PC before configuring EthoVision XT. - In the Experiment Settings, click the Settings button next to Use of Trial Control Hardware. In the window that appears, first select one USB-IO box from the drop-down list and select the devices connected to it. Next, select the second USB-IO box and select the devices connected to it. Testing the USB-IO Box Testing Functionality of TTL Ports Refer to the TTL port testing section for instructions on testing TTL port functionality. Testing Connection in USB-IO Box When you carry out long trials, it may be handy to check that the USB-IO box works properly for the entire duration of the trial. For this purpose, use the USB-IO box monitor function. - In the Device Configuration window (Experiment Settings), locate a free TTL Port and under Device type, choose USB-IO box monitor. - In the Arena-Hardware Mapping window, add a device and for that device select USB-IO box monitor. - After the trial has been acquired, in the Analysis profile click next to Hardware state and select: - Device type: USB-IO box monitor - Value: true - In the Integrated Visualization you should see the hardware state USB-IO box monitor as a colored bar that goes from the beginning to the end of the trial, if everything went well. If the USB cable between the PC and the USB-IO box was accidentally disconnected, or some error occurred inside the USB-IO box chip, the colored bar should end at that time in the trial. Note: You can use the USB-IO monitor function to check whether the USB cable is still connected or if the communication chip is working fine. However, this function cannot help when: - A specific port other than that used for USB-IO box monitor is defective. - The power cable of the USB-IO box is disconnected during the trial. In both cases the USB-IO box monitor state remains unchanged till the end of the trial. Do not use the port reserved for USB-IO box monitor for connecting other devices. Jumper and DIP Switch Settings The USB-IO box contains jumpers inside the box next to the SDI ports. Jumpers are short lengths of wire that complete a circuit. By placing the jumper over a pair of available pins, you activate that line. On the USB-IO box board, jumpers can be placed in either position 1 or 2. The default jumper positions are set by Noldus Information Technology. You do not have to change them unless you intend to connect multiple Top Unit Interfaces to work with multiple groups of PhenoTyper 1. Default Jumper Settings - JMPR5 (for SDI ports 1–4) — Set to 1 - JMPR6 (for SDI ports 5–8) — Set to 1 - JMPR7 (for SDI ports 9–12) — Set to 1 - JMPR8 (for SDI port 13) — Set to 2 Position 1 enables use of the Lickometer. Position 2 enables communication between the USB-IO box and multiple PhenoTyper 1 Top Units. Alter the Jumpers Follow this procedure only if you want to use SDI ports other than 13 to connect the Top Unit Interface. For example, when you want to connect 8 PhenoTypers to your PC and SDI port 13 is not sufficient as it can work with up to four Top Units. Note: If you alter a jumper other than JMPR8, this is done for all four ports it corresponds to. - Unscrew the cover of the USB-IO box. - Locate the jumpers on the main board marked by JMPR5 to JMPR8. - Put the jumper to position 2 for the port that you require: - JMPR5 (for SDI ports 1–4) - JMPR6 (for SDI ports 5–8) - JMPR7 (for SDI ports 9–12) Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - The Usb-Io Box And The Mini Usb-Io Box (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-the-usb-io-box-and-the-mini-usb-io-box-continued Chapter: EthoVision XT Installing the USB-IO Box The USB-IO box comes with the following cables: - Power supply 24 V 3A DC (A) with mains cable (B) - USB cable with two different connectors Connects the USB-IO box to other devices/power consumers with a power feed-through cable, for example, a PhenoTyper Top Unit. Important: When you connect devices to the 24 V Out power supply, do not exceed the maximum power rating of your mains supply. Connect the USB-IO Box to the Computer - Make sure that EthoVision XT is not running. - Connect the USB port on the USB-IO box to a USB port on the EthoVision XT computer using the USB cable. Notes: - Use a direct USB port on your PC, not a USB hub or a USB port on your PC's monitor. Try to minimize the number of USB devices connected to your computer. - You can in principle connect multiple USB-IO boxes to the EthoVision XT computer; however, Noldus cannot guarantee that all possible combinations of devices will work. - If you disconnect the USB-IO box while EthoVision XT is open, a message appears on screen. Re-connect the USB-IO box and in EthoVision XT click Try Again. Note that it can take some time before the software recognizes the USB-IO box after you re-connect it. Connect the USB-IO Box with the Noldus USB Extender Cable The standard USB cable length is limited to 3 meters. When you need a longer distance between the computer and the PhenoTyper setup, Noldus recommends using the Noldus active USB extender cable of 20 meters, as not all standard USB extenders work correctly with the USB-IO box. The Noldus USB extender cable comes with a small jumper that must be set inside the USB-IO box in order for the USB extender cable to function correctly. - When you use the USB extender cable in combination with the mini USB-IO box (PTIO-003x), you do not need to set the jumper. - When you purchased your USB-IO box together with the USB extender cable, the jumper has already been set by Noldus. To set the jumper, do the following: - Open the USB-IO box by unscrewing the 2 screws at the bottom, and remove the top part. - Set the jumper on position JMPR4 (indicated by the arrow in the figure). - Re-assemble the USB-IO box. - Connect the USB-IO box to the computer. The USB-IO Box Device Driver Software The current driver software for the USB-IO box and Mini USB-IO box is installed automatically when you install EthoVision XT. For EthoVision XT 18, the driver software for both the USB-IO box, the Mini USB-IO box, and DanioVision is Noldus HardwareInterface USB-IO box 5.1.14. To check that the driver is installed, open the Control Panel and go to Programs and Features / Add or Remove Programs. The driver name is Noldus - HardwareInterface IoBox - x64 Package - 5. If you want to uninstall the driver software, in Control Panel > Add or Remove Programs, select Noldus - HardwareInterface IoBox - x64 Package - 5 and click Uninstall. If you need the driver software for the USB-IO box and the Mini USB-IO box, you can find it on my.noldus.com. Log in or register first, then choose Downloads > EthoVision XT > Versions. Download EthoVision XT - Full Installation Disc - 18.0, then unzip the file and open the folder Drivers and tools > PreRequisites > HardwareInterfaceIobox. Run the file HardwareInterface IoBox - x64 Package - 5.1.12.msi. Older Versions of the USB-IO Box Device Driver It is not necessary to uninstall the drivers of previous versions of the Noldus USB-IO box or the Noldus Mini USB-IO box. Note that for EthoVision XT 11 and older versions, the USB-IO box and the Mini USB-IO box had separate drivers. Connecting the USB-IO Box to Devices Connect One Device - Plug one end of the modular network cable into the hardware device. Note that although an RJ45 cable is used in computer networks, the signal from and to the hardware device is not a network signal. The device cannot be connected via a network hub or similar. - Plug the other end of the network cable into one of the ports available on the USB-IO box: - TTL (front panel): for the Pellet dispenser and other devices that communicate via TTL. - SDI (rear panel): for the Lickometer and the Top Unit Interface. Note: The network cable comes with the Noldus device, not the USB-IO box. - To connect the Top Unit of PhenoTyper 1, connect the network cable to the Top Unit Interface, then connect the Top Unit Interface to each Top Unit. Connect the Top Unit Interface to port SDI 13. - To connect the Top Unit of PhenoTyper 2, use the TTL ports, not the SDI ports. For more information, see the PhenoTyper - EthoVision XT 18 - Reference Manual. Connect Multiple Devices Connect each individual device to a TTL or SDI port of the USB-IO box. If you use PhenoTypers with devices like the Noldus Lickometer or the Noldus Pellet dispenser, connect devices of the same type to the same group of connectors. Examples: - Four Lickometers: SDI ports 1 to 4 - Four Pellet dispensers: TTL ports 1 to 4 - Top Unit Interface: SDI port 13 Speed of TTL communication is optimized if devices are connected to the same group of connectors. Important: Always test a specific combination of devices before carrying out actual trials. Whether a combination of devices works also depends on the timing of the commands. Controlling 12 pellet dispensers may work if the pellets are dropped at different times; however, dropping 12 pellets at exactly the same moment will not work. Connect a Third-Party Device: LED Lamp You can connect a third-party device that can be controlled by TTL. The following example describes connecting a LED lamp. The LED lamp must be connected between TTL output 1 (color: brown/white) and ground (color: orange/white). Add a series resistor (approximate value 560 ohm) to limit current through the LED. To control the LED lamp with EthoVision XT, in the Port Device Mapping window select the TTL port connected to the LED and under Device Type select TTL Port Tester. To define an action on this device, use the Light 1 On/Off option. The resistor can be skipped when you connect a real TTL device such as a shocker input or a maze. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-variables Chapter: EthoVision XT Variables In this section you find details and examples of the statistics you can use for your condition. For more information on a dependent variable, see the EthoVision XT Help. Note: Dependent variables of Live Mouse Tracker and the social variables Train and Side by side are not available in the Trial Control Settings. Distance Moved Frequently-Used Statistics - Current (default). To base your condition on the distance between the previous sample and the current one. This value depends on the chosen sample rate. Use Current velocity instead. - Total. To base your condition on the distance traveled from the moment the condition becomes active up to that point. - Mean. To base your condition on the average distance traveled from one sample to the next calculated from the activation of the condition box up to that time. This depends on the sample rate. Use Mean velocity instead. Notes - Effect of hidden zones. When the animal is in a hidden zone, the distance moved for the first sample in the hidden zone is based on the distance between the last location where the animal was detected and the center of the hidden zone. This is typically a relatively large distance, which can result in the condition becoming true. - Effect of outliers (reflections). Detection of reflections may result in a too large distance moved and hence the condition being met. Velocity In the Condition window, click the Settings button. Choose the body point on which calculation of velocity is based, and the Averaging interval. For details, see Velocity in the EthoVision XT Help. Frequently-Used Statistics - Current (default). For a condition that is met when the velocity at the current sample is <=/>= a specified value. - Total. This does not have a physical meaning and depends on the sample rate. Choose Mean instead. - Mean. For a condition that is met when the mean velocity since the activation of the condition is <=/>= a specified value. Notes - Effect of hidden zones. When the animal is in a hidden zone, the velocity for the first sample in the hidden zone is based on the distance between the last location where the animal was detected and the center of the hidden zone. This is typically a relatively large velocity, which can result in the condition becoming true. - Effect of jitter. When the animal moves slowly, jitter plays a bigger role than at higher speeds. This can make velocity exceed the threshold set in the condition. - Effect of outliers (reflections). Detection of reflections may result in a too high velocity and hence the condition being met. To prevent this from happening, increase the Averaging interval in the settings. Movement In the Condition window, click the Settings button. In the Movement tab, specify which threshold values of velocity specify the states Moving and Not moving. Optionally, choose an Averaging interval to smooth out random changes in velocity that do not reflect real movement. Frequently-Used Statistics - Current. For a condition that is met when the animal's current state is either true (Moving) or false (Not moving). - Frequency (default). For a condition that is met when the animal has moved/not moved a number of times. - Cumulative duration. For a condition that is met when the animal has moved/not moved for a specific time since the activation of the condition. Example: A Movement condition is defined to stop tracking after 10 minutes of movement. If the animal moves during the first 2 minutes, stops moving for 3 minutes, and then moves again without interruption, the track is stopped 13 minutes after the start. - Current duration. For a condition that is met when the animal has moved/not moved continuously for a specific time. In the same example as above, the condition would be: stop tracking when the current duration of movement is 10 minutes. Tracking would stop when the animal had moved continuously for 10 minutes, that is 15 minutes after the start. - Latency to first. For details, see the Latency to First section. Acceleration In the Condition window, click the Settings button and choose the options you require. Frequently-Used Statistics - Current (default). To base your condition on the current value of acceleration. - Total. To base your condition on the total acceleration from the moment the condition becomes active up to that point. Note that this value does not have a physical meaning and depends on the sample rate. Choose Mean instead. - Mean. To base your condition on the average acceleration. The average is calculated from the activation of the condition box up to that time. Note: Acceleration state is not available as a condition criterion. However, you can create a Multi condition that includes for example a condition "Acceleration > 10 cm/s for more than 1 second". This corresponds to a state variable based on Acceleration. In Zone In the Condition window, click the Settings button. Under In the following zones, select the zones of your choice. Under From following body points, select the body points of the animal that determine whether or not the animal is considered to be within a zone. Under Threshold, enter a Zone exit threshold to avoid that small movement of the body points across zone borders result in unrealistic scores of zone entries. Such movements are usually caused by body-point jitter, or the behavior of the subject (stretching, curling, etc.). Frequently-Used Statistics - Current. To base your condition on the presence of the animal in a zone at that time: either true (In zone) or false (Not in zone). - Frequency (default). To base your condition on the number of times the animal has been in the zone. Important: The frequency of In zone becomes high very easily when the animal walks along the edge of a zone. This may result in the condition being met sooner than expected. If this happens, increase the Zone exit threshold. If that does not help, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track during acquisition, which means that the track is altered and cannot be reversed afterwards. - Cumulative duration. To base your condition on the cumulative duration the animal has been in the zone up to that time since the activation of the condition. Example: In a Novel Object Recognition test, stop tracking when the animal has been in the zone for a specified cumulative duration. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Variables (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-variables-continued-lv1 Chapter: EthoVision XT Variables (Continued) Weighted Movement From Use to calculate net relative movement to/from another subject. In the Receivers tab, select the other subject and its relevant body points. In the Condition window, select Current as Statistic, then click Settings. In the Weighted Movement From tab, specify at which maximum distance the subjects should be considered as 'interacting'. In the Actors tab, select the focal subject and its body point that you want to use to calculate weighted movement from another subject. In the Receivers tab, select the other subject and its relevant body point. Weighted Movement To In the Condition window, select Current as Statistic, then click Settings. In the Weighted Movement To tab, specify at which maximum distance the subjects should be considered as 'interacting'. In the Actors tab, select the focal subject and its body point that you want to use to calculate speed of moving to another subject. In the Receivers tab, select the other subject and its relevant body points. More About Conditions Based on Dependent Variables Conditions Based on Multiple Dependent Variables Use a Multi Condition to let EthoVision carry out an action when the subject performs a combination of behaviors. For example, to stop tracking when the subject's nose point has been in the novel object zone while having its head directed to the object for 20 seconds. - In the Components pane, under Conditions, double-click the name or click the button next to the Multi Condition. Tip: If you do not see the variable name, click the More button. - The Multi Condition window opens. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). - Click the Settings button. In the Actors tab, select the subjects to which the conditions apply. - Click Add Condition. Select a dependent variable from the list. Click the Settings button and specify the details for this condition. See the paragraph on using this dependent variable as a condition for details. - In the Is: field, specify the criteria, for example When nose-point is in zone Novel Object = True. - Repeat steps for other conditions. - From the list at the bottom, select whether all conditions or one of them should be met. Click OK. - Under Condition Is Met When, select the Statistic you want to use. Frequently-Used Statistics - Current: For conditions that are met when the dependent variables are true or not true at the current sample. - Frequency: For conditions that are met when the dependent variable values occurred a number of times. - Cumulative Duration: For conditions that are met when the dependent variable values occurred for a specific time since the activation of the condition. - Current Duration: For conditions that are met when the dependent variable values occurred continuously for a specific time. - Latency to First: For conditions based on the latency to the first occurrence of the dependent variable. You cannot use conditions based on hardware devices in multi conditions. If you want to use multiple conditions with hardware devices, use multiple condition boxes with an Operator instead. See Operators for more information. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Variables (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-variables-continued-Riu Chapter: EthoVision XT Variables (Continued) Rotation of the body axis, rather than that of body points. In the Body Points tab, select the body point you want to use to calculate rotation. Frequently-Used Statistics - Frequency - To base your condition on the number of rotations occurred. - Latency to First - To base your condition on the time from the moment the condition becomes active to the first rotation. Example: Stop tracking when the first rotation event occurs less than one minute from the moment the condition becomes active. More About Conditions Based on Dependent Variables JavaScript Variables In the Condition window, click the Settings button and enter the JavaScript code that, when processed during acquisition, produces an output value. The condition will compare that value with those in the settings. This value can be Continuous, a State, or an Event depending on which JavaScript variable you use. In the Actors tab, select the subject for which to calculate the JavaScript variable value. Example: You want to create a condition that is based on the body area of the subject. Because EthoVision XT does not provide the body area in the Trial Control Settings, you can extract this value with a JavaScript variable of type Continuous that contains the command GetArea(). The condition could be for example "Body area > 2000" where 2000 is specified in the condition settings. A few more examples: - Create a condition that becomes true when the Body length exceeds a specific value for some time. - Create a condition that becomes true when the number of subjects in a zone exceeds a specific value. - Create a condition that becomes true when the distance of a focal subject to the nearest neighbor is smaller than a threshold value. Examples of JavaScript Variables Browse to my.noldus.com (either log in or register first), then choose Downloads > EthoVision XT > Versions. Download the file EthoVision XT - Full Installation Disc.zip. Next, extract the contents of the zip file, open Drivers and Tools > Utilities > JavaScript custom variables. More examples are available on GitHub: https://github.com/noldus/EthoVision-JavaScriptCustomAnalysis. Contact Noldus if you need to define a variable tailored to your research. Distance Between Subjects In the Condition window, click the Settings button. In the Actors tab, select the subject and its body point that you want to use to calculate the distance to another subject. In the Receivers tab, select the other subject and its relevant body points. Example: To make an action when ano-genital sniffing takes place, use a condition box with a minimal distance between the nose point of one subject and the tail base of the other. Select Current as Statistic, then click Settings. Under Actors, select the focal subject and Nose-point. Under Receivers, select the other subject and Tail-base. Proximity In the Condition window, click the Settings button. In the Proximity tab, specify the criteria to define proximity. In the Actors tab, select the focal subjects and their body points that you want to use to calculate proximity to other subjects (Receivers). In the Receivers tab, select the other subjects and their relevant body points. For dyadic interactions, select Subject 1 under Actors and Subject 2 under Receivers. Frequently-Used Statistics - Current - To base your condition on the current proximity state. Example: Take an action when the nose-point of subject 1 is in proximity of tail-base of subject 2. - Frequency - To base your condition on the number of times the subjects were in proximity of each other. - Current Duration - To base your condition on the duration of the current occurrence of In Proximity. - Cumulative Duration - To base your condition on the cumulative duration of the selected proximity state up to that time. - Latency to First - To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen proximity state. Example: Take an action when the latency of Nose point of subject 1 is in proximity of Tail base of subject 2 is longer than one minute. Body Contact In the Condition window, click the Settings button. In the Body Contact tab, specify whether the condition is based on body contact or no contact. In the Actors tab, select the subjects that should be in contact (or not in contact) with any other for the condition to become true. From the Statistics list, choose the statistic to be used and the value that makes the condition true. For example, if you want to create a condition that is met when body contact lasts 10 seconds without interruption, choose Current Duration >= 10 s. Frequently-Used Statistics See the statistics for Proximity. Note: When you select multiple subjects in the Actors tab, the condition is evaluated separately for each subject and then combined according to what you select from the With list. If you select Subject 1 and Subject 2 in the Actors tab, and select All selected subjects from the With list, the condition is met when both Subject 1 and Subject 2 are in contact with any subject (thus not necessarily in contact with one another). Relative Movement In the Condition window, click the Settings button. In the Relative Movement tab, specify at which maximum distance the subjects should be considered as 'interacting', and the criteria to define relative movement. In the Actors tab, select the focal subjects and their body points that you want to use to calculate relative movement to/from other subjects. In the Receivers tab, select the other subjects and their relevant body points. Frequently-Used Statistics See the statistics for Proximity. Net Weighted Movement In the Condition window, select Current as Statistic, then click Settings. In the Net Weighted Movement tab, specify at which maximum distance the subjects should be considered as 'interacting'. In the Actors tab, select the focal subject and its body point that you want to use. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Variables (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-variables-continued-Mf8 Chapter: EthoVision XT Variables (Continued) Set the Threshold in the field next to Is:. Click the Settings tab and specify the Averaging interval. Important: If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings, your rule becomes invalid. The Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. Redesign your Trial Control rule and connect the arrows between the boxes. Note: Activity state is not available as condition criterion. However, you can create a Multi condition that includes for example a condition "Activity > 10% for more than 1 second". This corresponds to a state variable based on Activity. Body Elongation In the Condition window, click Settings and specify the Averaging interval. Frequently-Used Statistics - Current. To base your condition on the current value. For example, the condition is true when Body elongation < 50%. - Total. This does not have a physical meaning and depends on the sample rate. In most cases you will need the statistic Current instead. - Mean. For a condition that is met when the mean Body elongation since the activation of the condition is <=/>= a specified value. Like Total, this statistic does not have a "physical" meaning. In most cases you will need the statistic Current instead. Body Elongation State In the Condition window, click the Settings button. Specify the Thresholds and the Averaging interval that define the three Elongation states. Under Condition based on, select the state you want to base the condition on: Stretched, Normal, or Contracted. Frequently-Used Statistics - Current. To base your condition on the current elongation state. Example: Take an action when the animal's state Contracted = True. - Frequency. To base your condition on the number of times the selected elongation state occurred. - Current Duration. To base your condition on the duration of the current Elongation state. - Cumulative Duration. To base your condition on the cumulative duration of the Elongation state. - Latency to First. To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen Elongation state. Example: Take an action when the latency of Stretched is longer than one minute. The condition is met when the animal is stretched, at least one minute from the moment the condition becomes active. Body Angle In the Condition window, click Settings and select Absolute angle (0° - 180° for the body bent either clockwise or counterclockwise) or Relative angle (0° - 360°). Frequently-Used Statistics - Current. To base your condition on the current value. For example, the condition is true when Body angle > 20°. - Total. This does not have a physical meaning and depends on the sample rate. In most cases you will need the statistic Current instead. - Mean. For a condition that is met when the mean Body angle since the activation of the condition is <=/>= a specified value. Like Total, this statistic does not have a "physical" meaning. In most cases you will need the statistic Current instead. Body Angle State In the Condition window, click the Settings button. Specify the Threshold and the Averaging interval that define the four Body angle states. Under Condition based on, select the state you want to base the condition on: Straight, Bent, Bent counterclockwise, or Bent clockwise. Frequently-Used Statistics - Current. To base your condition on the current body angle state. Example: To take an action when the animal's current state Bent counterclockwise = True. - Frequency. To base your condition on the number of times the selected body angle state occurred. - Current Duration. To base your condition on the duration of the current body angle state. - Cumulative Duration. To base your condition on the cumulative duration of the body angle state up to that time. - Latency to First. To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen Body angle state. Example: Take an action when the latency of Bent is longer than one minute. The condition is met when the animal is bent, at least one minute from the moment the condition becomes active. Mobility With Mobility you can create a condition based on the change in the detected shape between the previous sample and the next one, expressed in percentage. Frequently-Used Statistics - Current. The percentage change in the detected body area in comparison with the previous sample. - Total. The total percentage change in the detected body area, from the moment the box becomes active onwards. - Mean. The mean percentage change in the detected body area, from the moment the box becomes active onwards. Set the Threshold in the field next to Is:. Click the Settings tab and specify the Averaging interval. Mobility State In the Condition window, click the Settings button. Specify the Thresholds and the Averaging interval that define the three mobility states. Under Calculate nesting for, select Highly mobile, Mobile, or Immobile. Frequently-Used Statistics - Current. To base your condition on the current mobility state. Example: Take an action when the animal's current state Immobile = True. - Frequency. To base your condition on the number of times the selected mobility state occurred. - Current Duration. To base your condition on the duration of the current mobility state. - Cumulative Duration. To base your condition on the cumulative duration of the selected mobility state up to that time. - Latency to First. To base your condition on the time from the moment the condition becomes active to the first occurrence of the chosen mobility state. Example: Take an action when the latency of Highly mobile is longer than one minute. The condition is met when the animal is highly mobile, at least one minute from the moment the condition becomes active. Rotation In the Condition window, click the Settings button. In the Rotation tab, specify the criteria to define a rotation. Select Body axis rotation when you want to base the condition on the rotation of the body axis. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Variables (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-variables-continued-3bI Chapter: EthoVision XT Variables (Continued) Arm of a T maze five times (Frequency=5). Important: The frequency of Zone transition can become high very easily when the animal walks along the boundary between zones. This may result in the condition being met sooner than expected. If that happens, increase the Zone exit threshold. If this does not help, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track. Latency to First. Example: Take an action when the latency of the first transition from Zone A to Zone B is longer than 1 minute. Heading Use Heading for a condition based on compass-like orientation, provided that the axis orientation in the Arena Settings has some biological meaning. In the Condition window, click the Settings button. In the Body points tab, select the body point that you want to use to calculate heading. Frequently-Used Statistics - Current (default). To base your condition on the current heading value. - Mean. To base your condition on the mean value since the activation of the condition. Heading to Point In the Condition window, click the Settings button. Under Select, select the point (or zone center) that your condition is based on. Under For the following body points, select the body point for which heading is calculated. Frequently-Used Statistics - Current (default). To base your condition on the current meander value. - Mean. To base your condition on the mean value since the activation of the condition. Example: Take an action when the animal's Heading to the Entry zone is less than 5 degrees. Select Current as Statistic, <= 5°. Click Settings and specify Entry zone (center). To restrict the condition to when the animal is moving, create a condition based on Movement, and combine the two conditions with an operator of type All. Note: Heading is about movement. If you want to create a condition based on the animal's head orientation, use Head directed to zone (see below). Head Direction Use Head direction for a condition based on compass-like orientation. Since Head direction depends on the orientation of the axes in the Arena Settings, Head direction makes sense if the axis orientation has biological significance. If the animal must point to a zone or point, use Head directed to zone. Frequently-Used Statistics - Current (default). To base your condition on the current value of head direction. - Mean. To base your condition on the average head direction angle up to that time. We advise you to specify a range of Head direction, using two conditions (one specifying >=, the other <=). Then, combine the conditions with an operator of type All. Example: If the x axis points to North, then to make a condition that is met when Head direction is between NE and NW, combine: - A condition that states Current Head direction <= +90°. - A condition that states Current Head direction >= -90°. Head Directed to Zone In the Condition window, click the Settings button. Under Zone of interest, select the zone or point that your condition is based on. Under Calculate when, specify to calculate the variable only when the animal (or one of its body points) is in a specific zone. We advise you to define a zone around the focal zone/point, so the variable is calculated only when the animal is near the focal zone. Frequently-Used Statistics - Frequency (default). To base your condition on the number of times the animal's head points to a zone (or point). - Current. To base your condition on whether the animal's head points to a zone (or point). Example: Take an action when the animal's head is directed to the novel object. By selecting Current, the condition will become true as soon as the animal's head points to a zone for an instant. If you want to make the condition become true when the animal's head points to a zone for some time, use Current duration instead. - Cumulative Duration. To base your condition on the cumulative time that the animal points to a zone or point since the activation of the condition. - Current Duration. To base your condition on the time that the animal's head has been pointing to the zone without interruption up to the current time. Example: Take an action when the animal's head is directed to the novel object for five seconds. Latency to First. See Figure 24 for reference. Turn Angle In the Condition window, click the Settings button. In the Turn Angle tab, specify whether the turn is Absolute (unsigned) or Relative (signed). Select whether you want to calculate the Head direction turn angle (body points will be ignored). In the Body points tab, select the body point that you want to use to calculate Turn angle. Frequently-Used Statistics - Current (default). To base your condition on the current value. - Total. To base your condition on the cumulative value (whether absolute or relative) since the activation of the condition. - Mean. To base your condition on the mean value (whether absolute or relative) since the activation of the condition. Angular Velocity In the Condition window, click the Settings button. In the Angular velocity tab, specify whether the turn is Absolute (unsigned) or Relative (signed). Select whether you want to calculate the Head direction angular velocity (body points will be ignored). In the Body points tab, select the body point that you want to use to calculate Angular velocity. Frequently-Used Statistics See Turn Angle above. Activity With Activity you can create a condition based on the change in pixels in the whole arena (thus not only in the detected body area) between samples. When properly set, this pixel change is supposed to be a measure for the subject's activity (for example, it is low when the subject freezes). Frequently-Used Statistics - Current. The percentage pixel change in the arena relative to the previous sample. - Total. The total percentage pixel change in the arena, from the moment the box becomes active onwards. - Mean. The mean percentage pixel change in the arena, from the moment the box becomes active onwards. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Variables (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-variables-continued Chapter: EthoVision XT Variables (Continued) the zone with the novel object for 30 seconds. After the activation of the condition, the animal spends the first 5 seconds in the zone with the novel object, then 10 seconds in the zone with the familiar object and 45 seconds in the zone with the novel object, the track is stopped 40 seconds after the activation of the condition (indicated by A). Current Duration. To base your condition on the time the animal has been in the zone without interruption up to the current time. If in the example above, the condition had been defined as: stop tracking when the current duration in the zone is 30 seconds, the track would have been stopped 45 seconds after the activation of the condition. More About Conditions Based on Dependent Variables Latency to First — See page 80 and Figure 24 on page 80. Distance to Zone In the Condition window, click the Settings button. Under To the following zones, select the zones of your choice. Select Include if in zone if you want to calculate the distance to the border of a zone, regardless of whether the subject is outside or inside the zone. Under From the following body points, select the body point of the animal you want to use to calculate the distance. Frequently-Used Statistics - Current (default). To base your condition on the current distance of the animal's body point to a zone. Example: Switch on a light when the current distance from the entrance of the shelter is less than 5 cm. - Total. This depends on the sample rate. Choose Mean instead. - Mean. To base your condition on the average distance of the animal's body point to a zone measured since the activation of the condition. Example: Stop the track when the average distance from the zone with the novel object is smaller than or equal to 10 cm. Distance to Point In the Condition window, click the Settings button. Under To the following points, select the points or center of zones of your choice. If you select two or more points, the condition is based on the shorter distance between those points and the animal's body point. Under From the following body points, select the body point of the animal you want to use to calculate the distance. Frequently-Used Statistics - Current (default). To base your condition on the current distance of the subject from the point. - Total. This has little physical significance. Furthermore, its value depends on the sample rate (the higher the sample rate, the greater the cumulative distance). Choose Mean instead. - Mean. To base your condition on the mean distance from the point since the activation of the condition. Meander In the Condition window, click the Settings button. In the Meander tab, select whether you want the condition to be based on the Absolute (unsigned) or Relative (signed) meander. Select Head direction meander when you want to base your condition on the angles formed by the Head direction line, not the body points (these will be ignored). In the Body points tab, select the body point on which you want to base the definition of meander. Frequently-Used Statistics - Current (default). To base your condition on the current meander value. - Total. To base the condition on the value of Meander cumulated since the activation of the condition. - Mean. To base your condition on the mean value since the activation of the condition. Target Visits and Errors Use Target visits and errors to control the trial based on the visits to target zones and errors (visits to non-target zones or target zone revisits). In the Condition window, click the Settings button. In the Target visits and errors tab, select the zones that are targets and non-target. Under Condition based on, select which variable you want to use. Frequently-Used Statistics - Frequency (default). To base your condition on the occurrence/number of successes and errors since the activation of the condition. Example: Take an action as soon as the animal has made three errors entering three different non-target zones. From the Statistics list, select Frequency ≥. Click Settings, select the non-target zones and then under Condition based on, select Non-target first visits. Note — When using first visits (target or non-target) in the condition, make sure that you enter a frequency less or equal to the total number of corresponding zones selected under Settings. For example, if you select Condition based on Target first visits and Frequency ≥, make sure that you select at least three target zones under Settings. - Latency to First. See page 80 and Figure 24 on page 80. Zone Alternation Use Zone alternation to create a condition based on alternation between specific zones. For example: stop tracking when the animal makes the ten alternations (A > B > C). In the Condition window, click the Settings button. In the Zone Alternation tab, select the zones of the alternation (for example A, B, C). Under Condition based on, select which variable you want to use. Select whether you want to consider only direct transitions. In the Body points tab, select which body points define the transition from one zone to the other. Frequently-Used Statistics - Frequency (default). To base your condition on the occurrence/number of alternations or direct/indirect revisits in zones since the activation of the condition. Example: Take an action as soon as the animal has completed the tenth alternation. Click Settings, select the zones and then under Condition based on, select Alternations. From the Statistics list, select Frequency ≥. - Latency to First. See page 80 and Figure 24 on page 80. Zone Transition In the Condition window, click the Settings button. In the Zone Transition tab, click Add to define the zone sequence (for example A > B > C). Select whether you want to consider only direct transitions. Enter a Zone exit threshold to avoid that small movement of the body points across zone borders result in unrealistic scores of zone transitions. Such movements are usually caused by body-point jitter, or the behavior of the subject (stretching, curling etc.). In the Body points tab, select the body point that moves from one zone to the other. Frequently-Used Statistics - Frequency (default). To base your condition on the occurrence/number of transitions between zones since the activation of the condition. Example: Take an action as soon as the animal has gone from the Middle zone to the Left zone. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - THC - Trial and Hardware Control - Version 18 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-thc-trial-and-hardware-control-version-18 Chapter: EthoVision XT Introduction to Trial Control This manual covers trial and hardware control in EthoVision XT version 18. The Trial Control Screen - The components pane - The trial control window - Maximum trial duration pane Program Trial Control - Procedure - Conditions - Actions - Trial control variables - External commands - External commands: arena- and trial-specific - Operators - Re-use trial control elements - Frequently-occurring cases - Test the trial control sequence - Apply trial control to your trials The Start-Stop Trial Rule - The default start-stop trial rule - Customize the start-stop trial rule - Examples of start-stop trial rules Sub-Rules - Use sub-rules - Create a sub-rule - Create a reference to a sub-rule - Sub-rule start conditions - Sub-rule stop conditions - Place the sub-rule reference in the trial control sequence - End a sub-rule - Call a sub-rule from another sub-rule Conditions - Conditions based on time - Conditions based on a time interval - Conditions based on a trial control variable - Conditions based on a dependent variable - Subjects in a condition - When is a condition met? - Conditions based on behaviors scored manually - Conditions based on hardware devices Variables - Distance Moved: Total distance traveled by the subject. - Velocity: Speed of the subject. - Movement: General movement detection. - Acceleration: Rate of change of velocity. - In Zone: Whether the subject is within a defined zone. - Distance to Zone: Distance from the subject to a zone. - Distance to Point: Distance from the subject to a point. - Meander: Change in heading relative to distance moved. - Target Visits and Errors: Visits to target zones and error counts. - Zone Alternation: Alternation between zones. - Zone Transition: Transitions from one zone to another. - Heading: Direction the subject is moving. - Heading to Point: Direction from subject toward a point. - Head Direction: Orientation of the subject's head. - Head Directed to Zone: Whether the head is directed toward a zone. - Turn Angle: Angle turned by the subject. - Angular Velocity: Rate of turning. - Activity: Level of activity detected. - Body Elongation: Elongation of the subject's body. - Body Elongation State: State derived from body elongation. - Body Angle: Angle of the subject's body. - Body Angle State: State derived from body angle. - Mobility: Degree of mobility of the subject. - Mobility State: State derived from mobility. - Rotation: Rotational movement of the subject. - JavaScript Variables: Custom variables defined via JavaScript. - Distance Between Subjects: Distance between two tracked subjects. - Proximity: Whether subjects are within a defined proximity. - Body Contact: Detection of physical contact between subjects. - Relative Movement: Movement of one subject relative to another. - Net Weighted Movement: Net weighted movement value. - Weighted Movement From: Weighted movement away from a reference. - Weighted Movement To: Weighted movement toward a reference. - Conditions Based on Multiple Dependent Variables: Combining multiple variables in a condition. Control Hardware Devices - Devices supported in EthoVision XT - Work with multiple devices - Connect the hardware devices - Set the port connections - Assign devices to arenas - Test the hardware devices - Program trial control with hardware devices The USB-IO Box and the Mini USB-IO Box - The USB-IO box - Install the USB-IO box - Connect the USB-IO box to devices - Use multiple USB-IO boxes - Test the USB-IO box - Jumper and DIP switch settings - Configure EthoVision XT - The Mini USB-IO box - The TTL port tester - The optical isolated TTL-IO interface - Technical specifications User-Defined Device Types - Overview of user-defined device types - In a nutshell - Define a new device type - Sample file - Predefined IDs - XML file entries Analysis of Trial Control Data - What do you want to do? - Trial control events - Trial control states - Analyze the data within trial control states - Trial control variables - Hardware command - Hardware continuous variable - Hardware state variable - Free intervals based on trial control and hardware data - The analysis results - Export trial control data Apply Different Protocols to Different Arenas - Introduction - Simple case: two arenas - Advanced case: six arenas Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EthoVision XT 18 - Trial Control and Subject Detection URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-18-trial-control-and-subject-detection Chapter: EthoVision XT Detect The Subject - Choose Setup > Detection Settings. Open the default Detection Settings 1. - If you work with video files, under Video click Select Video and choose a video file. Play the video up to when the subject appears. If you work with cameras, release the animal in the arena. - Click Automated Setup. Choose the type of subject you test, and click Next. - Wait until the subject is free from contact with objects or walls and walks with a normal posture. When ready, draw a rectangle around the subject. Do this for all subjects in the arena. tip For rodents, try to leave the tail out of the rectangle. In all other cases, include the animal's tail. - If the subject's body is well detected, click Yes. Otherwise, try moving the Finetune slider and check if the yellow blob covers the entire animal's body (excluding the tail). If detection does not improve, try again a few times using another image from the video. If this does not help, click No and click Advanced. For details, see Configure Detection Settings > Advanced Setup in the EthoVision XT Help. Tracking the nose and tail-base In all cases, make sure that the body of the animal is well detected. Detect the subject If you use the Deep learning detection technique with one subject per arena, under Method click Define and select a box around the subject. Make sure that there is some space around the subject's body, like in this example. Notes Check that the subject is well detected in all parts of the arena. In the Detection Performance pane, check that the proportion of samples where the subject is not found is acceptable (for example less than 1%). If you selected Activity analysis in the Experiment Settings to detect freezing, click Activity. Adjust the settings until most of the purple pixels only appear when the animal moves. When the animal freezes, the number of purple pixels should be minimized. Prepare a list of trials (optional) Prepare A List Of Trials (optional) The Trial List In EthoVision XT, a Trial is an uninterrupted recording session. The Trial List is a table listing the trials planned for an experiment. When you create a new experiment, a few planned trials are already present. To add more trials - Choose Setup > Trial List. Click the Add Trials button. - Type the number of trials you plan to carry out and click OK. - For each row: Specify the independent variables (optional; see the next page). Specify which video file you want to use (when tracking from video files). Select Arena Settings, Trial Control Settings, and Detection Settings (optional). If those columns are not present in the Trial list, click the Show/Hide button, click Variables and select them. Notes Planning your trials in advance also allows you to acquire trials in batch mode. See Trial List in the EthoVision XT Help. Figure 2 Planning ten trials in the Trial List. Prepare a list of trials (optional) Independent Variables What are Independent variables? Independent variables are either simple descriptive categories (such as the genotype or age of your rats or mice), or conditions manipulated by the researcher (such as the substance being tested and the dosage). You can use independent variables to create analysis groups or filter data. For example: Compare tracks of treated subjects with tracks of control subjects. Only analyze subjects of a specific age class. note If you created a template experiment, one or more independent variables have been predefined in your Trial List. For instance, Animal ID and Treatment. To define an independent variable - Choose Setup > Trial List. - Click the Add Variable button. A new column appears on the right of the table. - Specify the Label (for example: Dose), Description, Type (for example, Text or Numerical), Format, Predefined values (for example, 0.01, 0.02 etc. mg/kg), and Scope (whether the values of the variable differ between subjects within the same arena, between arenas within the same trial, or between trials). Acquire the data Source: EthoVision XT 18 - Quick Start Guide --- ## EthoVision XT 19 - Acceleration state URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acceleration-state Chapter: EthoVision XT Definition A discrete (state event) variable, related to one of the body points, with two possible states, High acceleration and Low acceleration. At any sample time: - The state is High acceleration when the running average acceleration exceeds the High acceleration above threshold. - The state is Low acceleration when the running average acceleration is below the High acceleration above threshold. The running average acceleration is calculated according to the formula for Acceleration for each sample, over the number of samples specified by the Averaging interval. How to Specify Acceleration State - Click the Add button next to Acceleration state. - In the Acceleration State tab, enter the following: - Averaging interval. This is the number of samples over which the running average acceleration is based. The default value is 1, that is, acceleration is not smoothed before calculating the Acceleration state variable. - High acceleration above. The acceleration above which the animal must be considered in the High acceleration state. - Under Calculate statistics for, select the state you want to analyze, High acceleration and/or Low acceleration. - Under State duration threshold, next to Exclude instances shorter than, enter the minimum duration of the Acceleration state (see the note below). - In the Body Points tab (if present), select the body points for which you want to calculate Acceleration state. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - Enter zero as High acceleration above to distinguish between positive and negative acceleration. - To find the optimal High acceleration above threshold, run a few test trials and in the Integrated Visualization plot the values of Acceleration and Acceleration state. Adjust the threshold value in such a way that the state High acceleration is scored only when the animal shows bursts of rapid movement in the video. - We advise you to use an Averaging interval greater than 1 to remove the effect of random changes in velocity between consecutive samples that would result in false transitions between Low and High acceleration. However, the greater the Averaging interval, the longer the delay in the determination of a state transition. See Averaging interval. - The State duration threshold is the minimum duration of the set of consecutive samples with Acceleration above (or below) the High acceleration above threshold required in order to be scored as the corresponding state. If the set of samples passes the threshold, the samples are scored as the state. If the set of samples does not pass the threshold, the previous state ends, but no new state is defined. Use this option to filter out brief transitions between High and Low acceleration caused by body-point jitter or noise detection. Applications Use Acceleration state to mark bursts of rapid movement, like swimming bursts in fish. Activity: Definition The dependent variable Activity is only available when you selected Activity analysis in the Experiment Settings and you track only one subject per arena. Activity gives the percentage of changed pixels in the entire arena between the current sample and the previous sample. Calculation See step 1 and 2 in Activity state for information on how this percentage of changed pixels is calculated. With the dependent variable Activity state, you can calculate how much time and how often your subject was inactive, moderately active and active, and highly active. With the dependent variable Activity, you can calculate the average activity of your subject. How to Specify Activity - Click the Add button next to Activity. - Under Outlier filter, select the Averaging interval. This is the number of samples over which the running average mobility is based. The default value is 1, that is, the current value of Activity is only based on the current image. See Averaging interval. See Activity state for more information. - Complete the procedure to add the variable. See Calculate statistics: procedure. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Acquire Data - Acquire a Series of Trials Live + Save Video URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-acquire-a-series-of-trials-live-save-video Chapter: EthoVision XT Acquire a Series of Trials Live + Save Video Aim To carry out video tracking in a live situation, for a number of times (trials), in a predefined list. Video is recorded. Prerequisites - For general recommendations, see Acquire a Series of Trials - Live. - In the Acquisition Settings window, select both Track all planned trials and Save video. Procedure See the procedure Acquire a Series of Trials - Live. The differences are: - Video for the current trial is being recorded to a file on the hard disk. Video recording starts at the start of the trial, not at the start of tracking. - For each trial, video recording is stopped before the start of the inter-trial interval. - Saving the video at the end of each trial takes time. The inter-trial interval countdown only starts after the video has been saved. For this reason, the total time between the end of the i-th trial and the start of the i+1-th trial may be longer than the inter-trial interval. Record a Series of Videos, Then Acquire a Series of Trials Aim To record a number of video files while the tests are carried out. Video tracking is done in a later phase. Important: With this method, Trial Control is not applied during video recording. This means that for example you cannot stop video recording automatically after 10 minutes. To stop video recording, do so manually (see below). Trial Control is applied in the second phase (acquire trial). Prerequisites - For general recommendations, see Acquire a Series of Trials - Live. - Choose Acquisition > Open Acquisition. In the Acquisition Settings window, select Save video only, track later. - If no trials are planned, click the New trial button in the Playback Control window. Procedure Record a Series of Video Files - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start trial button in the Playback Control window. The Video window says Recording video. - Release the animal in the arena. - To stop video recording, choose Acquisition > Stop Trial, or press Ctrl+F6, or click the Stop trial button in the Playback Control window. Repeat the procedure for more video files. Acquire a Series of Trials from the Video Files - In the Acquisition Settings window, select Track all saved video files. - Make sure that the video file is positioned at its beginning or, in any case, at the point where you want to start data acquisition. Optionally, select Detection determines speed in the Playback Control window to make sure that samples are not missed. See DDS (Detection Determines Speed) for the advantages of applying this option. - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start trial button in the Playback Control window. The video is played forward and tracking takes place. - Acquisition stops automatically when the video file has reached the end and EthoVision XT automatically proceeds with the next saved video in your Trial List. - When all the videos have been analyzed, a message informs you that acquisition is done. Notes - If you wish to discard the tracks and re-do tracking from that video, see Redo a Trial. - To make sure that tracking starts and stops at the correct moment in the video, you must define appropriate Trial Control settings. Acquire a Series of Trials from Video Recorded with Other Programs Aim To carry out video tracking from a number of video files, recorded with a program other than EthoVision XT. Prerequisites For general recommendations, see Acquire a Trial from a Video File Recorded with Other Programs. Procedure - Release the animals in the arena and record video to a digital media file using the appropriate hardware and software. We recommend using MediaRecorder. At the end of this step you should have a number of video files. - Make a Trial List for batch acquisition and add one video for each trial in the list. See Prepare the Trial List for Batch Acquisition. - Acquire a series of trials from the video files: - Choose Acquisition > Open Acquisition. In the Acquisition Settings window select Track all planned trials. The name of the first planned trial in the Trial List appears in the field next to Trial and the associated video file opens in the Video window. - Make sure that the video file is positioned at its beginning or, in any case, at the point where you want to start data acquisition. Select DDS in the Playback Control window to make sure that samples are not missed. - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start series button in the Playback Control window. Notes - To make sure that tracking starts and stops at the correct time point, you must define appropriate Trial Control settings. - If you stop batch acquisition manually, all trials acquired up to that time are saved, including the current one that was interrupted. Click the Start series button again to complete the series. If necessary, redo the trial that was interrupted. See Redo a Trial. - If you wish to track data once again from that video, add a trial and follow the procedure for single trial acquisition. See Acquire One Trial. - The lighting conditions could be different between the start of subsequent trials. When using subtraction or differencing for subject detection, you can update the reference image based on the first video frame, keeping the reference image matched with the current conditions. See Use First Frame of Each Trial in Optimize the Reference Image > The Reference Image. --- ## EthoVision XT 19 - Acquire Data - Acquire a Trial From a Video File Recorded With Ot URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-acquire-a-trial-from-a-video-file-recorded-with-ot Chapter: EthoVision XT Acquire a Trial From a Video File Recorded With Other Programs Aim To carry out video tracking from a video file recorded with a program other than EthoVision XT. Prerequisites - The video file is compatible with EthoVision XT. See Video File Formats. - In the Experiment Settings, under Video Source, select From video file. - In the Arena Settings, check the video aspect ratio. - Optional: Make a Trial List and add a video to each trial. - Choose Acquisition > Open Acquisition. If no trial is planned, to add a new trial, in the Playback Control window click the New trial button or press Ctrl+F3. Procedure - In the Acquisition Settings window select Track next planned trial. - In the Acquisition Settings window, under Settings click the Video button. Select the video file you require. To have files of all formats listed, select All files from the Files of type list. - Position the video at the point you require. - Select DDS in the Playback Control window to make sure that samples are not missed. See DDS (Detection Determines Speed) for more information. - To start the trial, choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start trial button in the Playback Control window. The video is played forward and tracking takes place. - Acquisition stops automatically when the video file has reached the end, or when the condition before the Start track box in the Trial Control rule is met, or when you choose Acquisition > Stop Trial, or press Ctrl+F6, or click the Stop trial button. What Next? - If you need to enter values of independent variables, click the Independent Variables tab in the Analysis Results and Scoring pane. Edit the values where needed. - You cannot redo a trial obtained with this acquisition method. Acquire a Series of Trials (Batch Acquisition) What Do You Want to Do? - Acquire a series of trials - live - Acquire a series of trials live + save video - Record a series of videos, then acquire a series of trials - Acquire a series of trials from video recorded with other programs Learn About - Choosing the optimal reference image in a series of trials See Also - Acquire one trial - Split a multi-day test in multiple trials Acquire a Series of Trials - Live Aim To carry out video tracking in a live situation, for a number of times (trials), in a predefined list. Video is not recorded. Trials and Inter-Trial Intervals In the following example, the duration of the trials is assumed to be constant (for example, 5-minute trials in an open field). Click the Start series button to start acquisition. The inter-trial interval is not applied before the start of the first trial. You specify the inter-trial interval in the Acquisition Settings window. If you want to start the next trial before the end of the inter-trial interval, click the Skip countdown button. Important: The serial acquisition is interrupted automatically when the available disk space gets lower than 100 MB. EthoVision XT checks the available disk space before starting a new trial. Close the experiment, clean up some disk space, and then resume acquisition. Prerequisites - See also Before You Start Acquisition. - In the Experiment Settings, under Video Source select Live tracking. - Make sure that the Trial List includes all trials that you plan to acquire. If necessary, open the Trial List and add trials. Select a combination of Arena Settings, Trial Control Settings and Detection Settings for each planned trial. - Choose Acquisition > Open Acquisition. In the Acquisition Settings window, select Track all planned trials and specify the Inter-trial interval (H:mm:ss). The name of the first planned trial in the Trial List appears in the field next to Trial. Procedure - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start series button in the Playback Control window. - Release the animal for the first trial in the arena. - The trial is stopped automatically according to the rules set in the Trial Control Settings. Remove the animal from the arena, clean the experiment setup and prepare the next animal. The Video window shows the countdown (inter-trial interval). - At the end of the countdown, the next trial starts. Release the animal in the arena. - To stop the series of trials: the series stops automatically when the last planned trial has been tracked. You can stop the series manually at any time by choosing Acquisition > Stop Trial, or pressing Ctrl+F6, or clicking the Stop series button in the Playback Control window. If you stop batch acquisition manually, all trials acquired up to that time are saved, including the current one that was interrupted. Click the Start series button again to complete the series. If necessary, redo the trial that was interrupted. See Redo a Trial. Notes - If cleaning the experiment setup takes less time than the inter-trial interval and you do not want to wait until the end of the countdown, skip the remaining time and start the next trial by clicking the Skip interval and Start trial button (or pressing Ctrl+F5). - During the inter-trial interval, you can view information on when the next trial starts. In the Acquisition Settings window, next to Track all planned trials you see [name of next trial] starts in [H:mm:ss]. In the Video window you see [name of next trial] (Number of trials remaining) Starts in [H:mm:ss] (the last, in red). This text is always shown, even when you specify to hide the overlay text. - Automatic analysis does not start if you stop the series manually. - If you save video while tracking, saving the video at the end of each trial takes time. The inter-trial interval countdown only starts after the video has been saved. For this reason, the total time between the end of the i-th trial and the start of the i+1-th trial may be longer than the inter-trial interval. --- ## EthoVision XT 19 - Acquire Data - Acquire a Trial Live URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-acquire-a-trial-live Chapter: EthoVision XT Acquire a Trial Live Aim To carry out video tracking in a live situation. Video is not recorded. Prerequisites - In the Experiment Settings, under Video Source select Live tracking. - Choose Acquisition > Open Acquisition. In the Acquisition Settings window, select Track next planned trial; do not select Save video. - Make sure at least one trial is planned. To add a new trial, in the Playback control window click the New trial button or press Ctrl+F3. - IMPORTANT: Make sure that video resolution, frame rate and duration do not exceed the values reported in Resolution, frame rate, and maximum trial duration. Procedure - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start trial button in the Playback control window. - Release the animal in the arena. As soon as data recording starts, the Video window says Acquiring. - The trial stops when the condition before the Stop track box is met, or when you choose Acquisition > Stop Trial, or press Ctrl+F6, or click the Stop trial button. What Next? - If you need to enter values of independent variables, click the Independent Variables tab in the Analysis Results and Scoring pane. Edit the values where needed. - Remove the animal from the arena and repeat the procedure with the next trial. Acquire a Trial Live + Save Video Aim To carry out video tracking in a live situation. Video is recorded for backup purposes. This is also useful when one needs to re-do tracking. Prerequisites - In the Experiment Settings, under Video Source select Live tracking. Choose Acquisition > Open Acquisition. In the Acquisition Settings window, select both Track next planned trial and Save video. - Make sure at least one trial is planned. To add a new trial, in the Playback Control window click the New trial button or press Ctrl+F3. - Important: Make sure that video resolution, frame rate and duration do not exceed the values reported in Resolution, frame rate, and maximum trial duration. Procedure - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start trial button in the Playback Control window. EthoVision XT starts recording video, and waits for the condition to start tracking to be met. - Release the animal in the arena. - The trial stops when the condition before the Stop track box is met, or when you choose Acquisition > Stop Trial, or press Ctrl+F6, or click the Stop trial button. Video recording stops at the same time. What Next? - If you need to enter values of independent variables, click the Independent Variables tab in the Analysis Results and Scoring pane. Edit the values where needed. - Remove the animal from the arena and proceed with the next trial. Record Video, Then Acquire a Trial Aim To record video while the test is carried out. Video tracking is done at a later stage. Important: With this method, the Trial Control rule is applied in the second stage (acquire trial), not during the first stage (save video). To stop video recording after a fixed time, do so manually (see below) or see the suggestions in Stop Video Recording After Some Time. Prerequisites - In the Experiment Settings, under Video Source select Live tracking. - Choose Acquisition > Open Acquisition. In the Acquisition Settings window, select Save video only, track later. - Make sure at least one trial is planned. To add a new trial, in the Playback Control window click the New trial button or press Ctrl+F3. - Important: Make sure that video resolution, frame rate and duration do not exceed the values reported in Resolution, frame rate, and maximum trial duration. Procedure Record Video - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start trial button in the Playback Control window. The Video window shows a message: Recording video. - To stop video recording, choose Acquisition > Stop Trial, or press Ctrl+F6, or click the Stop trial button in the Playback Control window. Remove the animal from the arena. You can now proceed with the next subject or track the data from the video just saved (see below). Acquire the Trial From the Recorded Video - In the Acquisition Settings window, select Track next saved video file. The trial name shown next to Trial refers to the first saved video in your Trial List that you still have to track from. - Position the video at the point you require. - Select DDS in the Playback Control window to make sure that samples are not missed. See DDS (Detection Determines Speed) on page 586. - Choose Acquisition > Start Trial, or press Ctrl+F5, or click the Start trial button in the Playback Control window. The video is played forward and tracking takes place. - Acquisition stops automatically based on the Trial Control Settings, or when the video file has reached the end, or when you choose Acquisition > Stop Trial, or press Ctrl+F6, or click the Stop trial button. What Next? - If you need to enter values of independent variables, click the Independent Variables tab in the Analysis Results and Scoring pane. Edit the values where needed. - If you wish to discard the track and re-do tracking from that video, see Redo a Trial on page 530. --- ## EthoVision XT 19 - Acquire Data - Acquiring and Managing Trials URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-acquiring-and-managing-trials Chapter: EthoVision XT Acquiring and Managing Trials Re-Enable a Skipped Trial - Locate the trial and change its Acquisition status from To Skip to Planned. Make sure that you do this for all the arenas you want to use in that trial. - Go to the Acquisition module and carry out the trials as usual. After that, its Acquisition status changes from Planned to Acquired. Notes - To skip a trial other than the current one in the Acquisition screen, open the Trial List. Click the Show/Hide button on the toolbar, select Variables and make sure Acquisition status is selected in the Show Variables window. Locate the trial you want to skip, and change the Acquisition status for that trial from Planned to To Skip. - You can also skip arenas within a trial. Acquire Data for Some Arenas, Not Others Use this procedure to acquire data only in the arenas that contain subjects. For example, for Trial 32, a few arenas in a well plate are empty, but you want to track the subjects in the remaining arenas. - In the Experiment Explorer, click Trial List. - Locate the Acquisition status column. If it is not present, click the Show/Hide button on the toolbar, select Variables and select Acquisition status. - Locate the trial for which you want to skip arenas, and change the Acquisition status for those arenas from Planned to To Skip. - Carry out the trials as usual. Notes - After acquisition, the Acquisition status of the skipped arenas changes from To Skip to Skipped. - You can no longer acquire data for the skipped arenas because the trial itself has been acquired. To acquire data for those arenas, add a new trial and acquire data anew. Redo a Trial Use this procedure to record video or track data once again for a trial previously acquired. Important: When you redo a trial, you remove the tracks, the events scored manually and the trial control event data (including hardware device data) recorded during that trial. - In the Acquisition Settings window, under Options next to Clear and redo a trial, click the Select button. - In the Redo Trial window, select the trial that you want to redo. - Select one of the options, then click OK. When tracking from video files: - Clear tracks. The tracks are deleted. Choose this option if you want to redo the trial using a video file different from the current one. - Clear tracks but re-use the video reference. As above, however the link to the video file is retained. You can open Acquisition to track from that video file. When tracking live: - Clear tracks. The tracks are deleted. This option is available if you acquired tracks without saving video. - Clear tracks but re-use the video. Deletes the tracks but not the video file used to acquire those tracks. You can then track again from the video file. - Clear tracks and video. Deletes the tracks and the associated video so you can redo the trial anew. - Clear video. Clears a trial that has video only. You can then record a new video and acquire tracks. This is the only option available if you acquire data by saving the video first. - In the Acquisition Settings pane, under Method: - If you cleared a trial that used a video file not made with EthoVision XT, choose Track next planned trial. This is the option for redoing the trial from that existing video file. - If you cleared a trial with a video file made with EthoVision XT and deleted that video file, choose Track next planned trial. Alternatively, choose Save video only, track later to record a new video file for that trial without tracking. - If you cleared a trial with a video file made with EthoVision XT but kept the video file, choose Track next saved video file. With this option you redo the trial for that video file. - Choose Track all planned trials if you have a list of planned trials and you want to acquire data for all of them in one go. - Under Settings, next to Trial, verify the number of the trial you are about to acquire. The Video box shows either Live video or the video file you will track from, depending on the options chosen above. - If necessary, click the button next to Video and select the video file to track from. - Click the Start Trial button in the Playback Control window to start the trial. Notes - The options available next to Select action vary depending on how you acquire the trials. For example, if you track from pre-recorded video files, then only the first two options Clear tracks and Clear tracks but re-use the video reference are available. - Before redoing a trial, always check in the Acquisition Settings pane under Method which option is selected, and under Settings the video file you are going to acquire the trial from. - If you track from video recorded with programs other than EthoVision XT and you want to delete the video file corresponding to the trial you want to redo, you must delete the video manually. Rename or Delete a Trial To Rename a Trial Trials are given default names depending on the order they are added in your Trial List: Trial 1, Trial 2, etc. (first column of the Trial List). To rename your trials, edit the Trial name variable in the Trial List. - Choose Setup > Trial List. - Click the Show/Hide button on the toolbar and select Variables. In the Show Variables window, select Trial name. - In the Trial name column, double-click the cell corresponding to the trial you want to rename, then enter the new name. - The name under Trial is changed automatically, matching what is entered under Trial name. To Delete a Trial Deleting a trial removes all the tracks and external data files (if these have been imported in EthoVision XT) from your PC. To delete a trial, in the Trial List, click a trial and press Delete, or right-click a trial and select Delete Trials. Notes - If you have tracked from video files generated with EthoVision XT, you are asked whether you want to keep the video file associated with the trial or delete it too. - If you have tracked from video files generated with programs other than EthoVision, the video file associated with the trial is kept on your PC. - To delete multiple trials, select the trials in the first column of the Trial List, then press Delete or right-click and select Delete Trials. - In a multiple-arena experiment, you cannot delete tracks acquired in some arenas within a trial. You can only delete all tracks, that is, the entire trial. - If you delete a trial and then add a new one, it is not given the name of the deleted trial. For example, if you have 10 trials in your Trial List and you delete Trial 4, when adding a new trial it is named Trial 11. To avoid this, do not delete the trial but clear it: right-click the trial in the Trial List and select Clear Trials. Rename or Delete a Generated Video File Video files recorded within EthoVision XT are given the same name as the corresponding trial: Trial 1.mpg, Trial 2.mpg, etc. If you want to rename or delete a video file, you must first delete the corresponding trial. If you want to rename a video file without deleting its trial, make a copy of the video file with File Explorer and give this copy the new name. - Choose Setup > Trial List. - In the Trial List, right-click the row corresponding to the video you want to delete and select Delete. - In the window that appears: - Choose Rename generated video files for backup if you want to rename the file and delete the trial. - Choose Delete generated video files if you want to delete the video file and the trial. Important: In either case, the tracks and the external data files associated with that trial will be deleted. - Click Yes to confirm. Use a Remote Control to Start and Stop Acquisition Use this procedure to start and stop data acquisition when standing far from the EthoVision XT computer. You need a remote control with Page-up (<) and Page-down (>) buttons, such as those typically used for PowerPoint presentations. - Close EthoVision XT. - Browse to my.noldus.com, log in or register. Click Downloads, then EthoVision XT, then Drivers and Tools, and download the file for remote control. Save remote_control.zip to your EthoVision XT computer. - Extract and double-click the remote_control.reg file. When a message appears, click Yes. You can now use the remote control. - Switch on and connect the remote control. This is usually done by plugging a USB receiver into the EthoVision XT computer. - Start EthoVision XT and choose Acquisition > Open Acquisition. - To start a trial, press Page-up (<) on the remote control. - To stop a trial, press Page-down (>) on the remote control. Notes - Signals from the remote control will only be recognized: - While acquiring data, and if the trial is not finished yet. - When you are not entering independent values. - When you are not browsing through the video. - For earlier versions, download the full installation package and look for the Remote Control folder under Utilities. - If your PC is connected to a network through Wi-Fi, you could control EthoVision XT from a smartphone using one of the apps available, provided that the network's security settings allow communication. - If you have the USB-IO box and the TTL Port Tester PTTB-001x, you could have EthoVision XT start tracking when you press the button on the TTL Port Tester. To do so, connect the TTL Port Tester to a TTL port of the USB-IO box. In the Trial Control Settings, create a condition based on the TTL Port Tester that becomes true when button 1 is pressed. Place the condition box between the Start Trial box and the Start Track box. Note that with this solution you must click the Start Trial button in EthoVision XT, which then waits for the button press. Export Track Data Live Use this procedure to create a sample interface that exports track samples in real time during data acquisition. To enable external data export, you can write a DLL (COM DLL, also known as COM component) in C++. The DLL should implement the sample interface and should include instructions for processing the samples, for example: - Write the sample data to a local file. - Send the sample data over the network to an external application. If you need help writing the code for your DLL, please contact Noldus. Notes - The sample interface is specific to the EthoVision XT version you are using. --- ## EthoVision XT 19 - Acquire Data - Auto-Start Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-auto-start-data-analysis Chapter: EthoVision XT Auto-Start Data Analysis The Auto-start data analysis option in the Acquisition Settings window allows you to automatically start batch calculations immediately after data acquisition has ended, without the need to give any additional command. Example: You have a large set of video files, and you plan to start the batch data acquisition before leaving the lab in the evening. By selecting Auto-start data analysis, you make sure that analysis starts immediately after the end of the last trial, so that the results are ready the next morning. To Enable Auto-Start Data Analysis - Define your series of trials in the Trial List. - In the Acquisition module, before starting acquisition, in the Acquisition Settings window, under Options, select Auto-start data analysis. - Select one of the two options: - Active profiles only. To calculate the statistics using only the combination of the Track smoothing profile, Data profile and Analysis profile currently active (highlighted in blue in the Experiment Explorer). - All profile combinations. To calculate the statistics using all combinations of the Track smoothing profiles, Data profiles and Analysis profiles in your experiment. - Carry out data acquisition as usual. Notes - If you choose the second option, to minimize processing time and disk space occupied by results, make sure that the Track smoothing, Data and Analysis profiles in your experiment are those you want to use for analysis. Remove any duplicate or non-interesting profiles. - If you want to analyze data using certain profile combinations, not others, do not select Auto-start data analysis. Instead, do batch analysis after acquisition; there you can choose those profile combinations. - The analysis does not start automatically when you stop tracking manually. - If you move to another window and then return to the Data acquisition screen, you have to set the Auto-start data analysis option again. - The Auto-start data analysis option is not available when you select Save video only, track later as acquisition method. - Once analysis is started, a window with a progress bar opens. You can see that there are a few stages: - Step 1 - Data Preparation (for when tracking two subjects with Deep learning). For details see Prepare the data in multi-subject trials. - Step 2 - Track Smoothing, for adjusting the tracks based on a Track smoothing profile. - Step 3 - Data Selection, for choosing tracks, and track segments based on a Data profile. - Step 4 - Analysis, for calculating the values of the dependent variables specified in an Analysis profile. Score Behaviors Manually What do you want to do? - Score behaviors manually during acquisition - Score behaviors manually after acquisition - Edit the duration of manually-scored behaviors - Replace a behavior with another one - Score behaviors in different arenas - Score behaviors of two or more subjects - Delete a manually-scored behavior Score Behaviors Manually During Acquisition Aim To record behaviors manually, while EthoVision XT tracks the subjects. Note: You can also score behaviors manually after acquisition. Prerequisites - You have defined behaviors in the Manual Scoring Settings. - In the Acquisition screen locate the Analysis Results and Scoring pane, and click the Manual scoring tab. If you do not see the Analysis Results and Scoring pane, click the Show/Hide button and select Analysis Results and Scoring. - If you track from video files, in the Playback Control window, deselect DDS. This ensures that the video file is played at the normal speed. Behavior Buttons and Key Codes Each behavior has its corresponding buttons (with key code, if defined) for each arena and subject. Mutually-exclusive behaviors are shown under their group name. For multiple animals per arena, you can use the fill color as a reference to identify animals. If at least one trial is set to Planned in your Trial List, the buttons for behaviors defined as Initially active in the Manual Scoring Settings are highlighted in green, indicating that when you start the trial this is recorded automatically as initial behavior. Procedure - Start the trial. - To score a behavior for a specific subject, arena and behavior, press the key for that combination, or click the button for that combination. The button of the scored behavior is highlighted in green and the behavior's start has been scored. For mutually-exclusive behaviors, the button of the previous behavior is reset. - When the subject no longer shows that behavior, do the following: - For Mutually-exclusive states, score the behavior that is active next. - For Start-Stop states, press the stop key or click the button for that behavior. The button of the behavior is reset. For mutually-exclusive behaviors, the button of the new behavior is highlighted in green. Notes - Data can only be recorded after tracking has started. If you start the trial and tracking starts some time later as a result of Trial control conditions setting some delay, any scoring action between the start of the trial and the tracking is not recorded. - You cannot pause recording behaviors even when you track from a video file. However, after acquisition you can score behaviors manually after acquisition. - If you want to change the initial state of a subject for the next trials, do so in the Manual Scoring Settings. Initial behavior for trials already acquired remains as it is. - To modify the coding scheme, stop the trial and click Manual Scoring Settings in the Experiment Explorer. - To improve clarity in the video image during the observation, choose which body points to show, and adjust their size. See The video window > Show/hide body points and other track features. - If you want to show the arena and zones during the scoring sessions, click the Show/Hide button at the top-left corner, and choose Arena features. --- ## EthoVision XT 19 - Acquire Data - Carry Out Trials in an Order Different from That S URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-carry-out-trials-in-an-order-different-from-that-s Chapter: EthoVision XT Carry Out Trials in an Order Different from That Specified in the Trial List Example Carry out Trial 5 before Trial 4. - Skip Trial 4 and let EthoVision XT acquire data for Trial 5. - If you want to carry out Trial 4 at a later time, in the Trial List set this trial back to Planned. Note: This procedure also applies when you track subjects in multiple arenas simultaneously. Set all arenas to To Skip. Procedure To skip the current trial: - Make sure that the Acquisition Settings window shows the name of the trial you want to skip. - Click the Skip Trial button in the Playback Control window. The Acquisition Settings window shows the next trial number. - Carry out the trials as usual. To carry out the skipped trial: - In the Experiment Explorer, click Trial List. Click the Show/Hide button on the toolbar, select Variables and make sure Acquisition status is selected in the Show Variables window. --- ## EthoVision XT 19 - Acquire Data - Choosing the Optimal Reference Image in a Series o URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-choosing-the-optimal-reference-image-in-a-series-o Chapter: EthoVision XT --- ## EthoVision XT 19 - Acquire Data - Editing Behavior Scores URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-editing-behavior-scores Chapter: EthoVision XT Editing Behavior Scores Extend a Color Bar to the Current Position - Hover with mouse over the existing color bar, right-click and choose Extend to current, or double-click the existing score. - Result: The color bar now ends at the specified time. Fill the Gap Between Two Behavior Scores Follow this procedure if you scored two instances of the same behavior, and you want to fill the gap between the two instances since they actually refer to one bout of behavior. The frequency of the behavior will be reduced by 1. - Position the video at the start of the second color bar. - Point to the first color bar, and double-click or right-click and select Extend to current. Create a Gap Between Two Behavior Scores This applies to Start-stop behaviors only. Follow this procedure if you scored an instance of a Start-stop behavior, and you want to insert a gap between the original start and end points. The frequency of the focal behavior will increase by 1. The gap will appear as Not [behavior name] in the analysis. - Click the Start scoring mode button. - Position the video to where you want the end of the gap (= the second start point of the behavior). - Click the button for the behavior. - Play the video backward. Use the frame-by-frame controls for accurate scoring. Pause the video at the start of the gap (= the first end point of the behavior). - When finished, click the Stop scoring mode button. Reduce the Duration to a Specific Time Point Follow this procedure if the behavior score is too long relative to what is shown in the video. Do one or both of the following, depending on whether the color bar occurs before (a) or after (b) the actual behavior in the video, or both (a) and (b). (a) Crop from the left side: - Position the video where the behavior starts. - Point to the color bar at the left of the hairline. The mouse pointer turns to a delete symbol on the left side. - Right-click and choose Crop to current, or double-click the color bar. - Result: The color bar is shortened. (b) Crop from the right side: - Position the video where the behavior ends. - Point to the color bar at the right of the hairline. The mouse pointer turns to a delete symbol on the right side. - Right-click and choose Crop to current, or double-click the color bar. - Result: The color bar is shortened. Note: Which side of the color bar is deleted by Crop to current depends on where the mouse pointer is located relative to the hairline. Replace a Behavior With Another One Aim To replace the score of a behavior with that of another behavior from the same Mutually-exclusive group. Prerequisites - You scored behaviors of a group defined as Mutually-exclusive. See Define the Behaviors That You Want to Record Manually. - You have opened the Manual Scoring screen (Acquisition > Manual Scoring). Procedure - Choose the trial, and when it applies, the arena in which you want to score behaviors. - To enable the scoring mode, click the Start scoring mode button. Before editing existing data, click the Save button on the toolbar. This will save a copy of the current behavior scores. In case you make mistakes when editing, you can always revert to that copy by clicking Undo. For more information, see Saving the Track Edits. - Position the video to the point where the new behavior starts. - Click the button for the new behavior. - Play the video forward. Use the frame-by-frame controls for accurate scoring. - Pause the video when the behavior ends. - To confirm, click the behavior button again. To quit editing, click the Stop scoring mode button. See Also - Delete a Manually-Scored Behavior Delete a Manually-Scored Behavior Aim To remove an instance of behavior scored manually. Prerequisites - You have opened the Manual Scoring screen (Acquisition > Manual Scoring). Procedure - Choose the trial, and when it applies, the arena in which you want to score behaviors. - Hover with the mouse on the color bar (or vertical segment) which represents the instance you want to delete. The cursor changes to a symbol depending on where this instance is relative to the hairline. If you are not sure of the results of editing, click first the Save button on the toolbar. You can always return to the last saved data by clicking Undo. See Saving the Track Edits. - Right-click and choose Delete event. - The same is valid for point events. When deleting point events, make sure that the hand cursor is slightly to the right of the event you want to delete. Notes - If you delete a behavior from a mutually-exclusive group, the previous behavior is extended up to the end of the color bar that you delete. - You can only delete a behavioral category defined in the Manual Scoring Settings after deleting all the trials. Note that if you remove all trials, you remove all your data. See Edit the Manual Scoring Settings. Score Behaviors in Different Arenas Aim To edit behaviors manually for subjects that were tracked in different arenas. Prerequisites - You have defined two or more arenas in the Arena Settings. - You have defined behaviors in the Manual Scoring Settings. - You have acquired one trial and its corresponding video. - You have opened the Manual Scoring screen (Acquisition > Manual Scoring). Procedure - In the Manual Scoring screen, select the arena in which you see the subject you want to score behaviors for. Result: The body points of the subjects in the selected arena are displayed. - To enable the scoring mode, click the Start scoring mode button. - Score or edit the behavior for the subjects in that arena. See Score Behaviors Manually After Acquisition. - Repeat the procedure for the remaining arenas. --- ## EthoVision XT 19 - Acquire Data - Important Things to Know About Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-important-things-to-know-about-data-acquisition Chapter: EthoVision XT Important Things to Know About Data Acquisition Four Methods to Acquire Data Choose the method that best suits your setup and experimental protocol: - Acquire data live. The animals are tracked as they move in your experimental setup. The disadvantage of this method is that you do not have a video backup, so if you need to repeat data acquisition you have to repeat the test itself. See Acquire a trial live or Acquire a series of trials - live. - Acquire data live and save video simultaneously. Like above, in addition EthoVision XT records video to a digital video file. You can use the video to re-do tracking if needed. See Acquire a trial live + save video or Acquire a series of trials live + save video. - Record video with EthoVision XT, then acquire data. This is a two-step method. First, record video to a digital video file as the animals move in your experimental setup. Afterwards, open the video file and acquire the data. This way you are free to track data later. See Record video, then acquire a trial, or Record a series of videos, then acquire a series of trials. - Acquire data from video files recorded with other programs. Use an external program, like MediaRecorder, to record video to a file while the animals move in the experimental setup. Later on, open the video file and acquire the data. See Acquire a trial from a video file recorded with other programs, or Acquire a series of trials from video recorded with other programs. See also Video file formats. Advantages of Using Video Files - You have a video backup. A video file is very handy since it allows you to acquire data for a trial once again, if needed. For example, if you realize that the detection settings were not optimal when you acquired the data. See Redo a trial. - You make sure that tracking is reliable. When you track from a video file, let EthoVision XT take as much time as it needs to analyze each sample, independent of the actual frame rate. For example, if the detection method used requires a lot of time per sample, acquisition may be slower than real time, but you ensure that no sample is missed. See DDS (Detection determines speed). Settings Used for Data Acquisition You can view which settings were used for a particular trial. In the Experiment Explorer, click Trial List. Click the Show/Hide button on the toolbar and in the Show Variables window, select Arena Settings, Detection Settings and Trial Control Settings. In the Experiment Explorer, settings profiles are marked with a lock icon, meaning that they cannot be edited. To edit a settings profile, make a copy. To View Your Trials Choose Setup > Trial List. Click the Show/Hide button on the toolbar. In the Show Variables window, select Acquisition status. For an explanation of Acquisition status, see System variables. Correct Tracking Errors Good detection settings do not generally result in tracking errors. Before editing tracks, make sure that the lighting conditions and the detection settings are optimized. See Edit the Tracks. Acquire One Trial Learn About - Before you start acquisition What Do You Want to Do? - Acquire a trial live - Acquire a trial live + save video - Record video, then acquire a trial - Acquire a trial from a video file recorded with other programs See Also - Acquire a series of trials (Batch acquisition) Before You Start Acquisition Screen Saver and Power Options Turn off the screen saver and make sure that the power save options of your computer are turned off. Video Cameras and Video Files Make sure that the video cameras are connected to your PC's encoder board (for analog cameras) or USB/Ethernet ports (for digital cameras). See Camera Installation. Use the Correct Settings Make sure that the Arena Settings, Trial Control Settings and Detection Settings you want to apply are selected in the Acquisition Settings window. Enter the Independent Variables for the Next Trial In the Analysis Results and Scoring pane, click the Independent Variables tab and enter or select the values of the independent variables in the row highlighted in green. You can enter independent variable values at any time in the Trial List. See Independent Variables tab. When Co-Acquiring External (Physiological) Data If you want to acquire external data during the trial (only live, not from video files), make sure that the external data recording device is switched on and connected to the EthoVision XT computer. In EthoVision XT, in the Experiment Settings under Video Source select Enable DAQ co-acquisition. See also External Data. NOTE: You must have the External Data Module in order to use this functionality. Auto-Start Data Analysis If you want to start analysis immediately after finishing the trial (or series of trials), in the Acquisition Settings window select Auto-start data analysis. To Speed Up Analysis - Hide the Analysis Results and Scoring pane. To do this, click the Show/Hide button and then deselect Analysis Results and Scoring. - For tracking offline: Select DDS in the Playback Control window. This way EthoVision XT plays the video faster than 1x if subject detection requires little processor time. --- ## EthoVision XT 19 - Acquire Data - Prepare the Trial List for Batch Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-prepare-the-trial-list-for-batch-acquisition Chapter: EthoVision XT Prepare the Trial List for Batch Acquisition Aim To make a list of the trials to be acquired in batch, either live or from video files. Prerequisites - Click the Show/Hide button on the toolbar and select Variables. When you track from pre-recorded video files, make sure that Video file is selected. - Optionally select to display Arena settings, Trial Control settings and Detection settings. Prepare the Trial List for Batch Acquisition - Add the trials you need. - OPTIONAL: If you defined multiple Arena Settings, Trial Control settings or Detection settings, for each trial select which settings you want to use. Either select settings for all the trials or for none at all. - Add video files to the planned trials, either automatically or manually. See the options below. You can either select different video files for different trials or the same video for multiple trials. Choose the latter way of working if you made a long video with multiple trial recordings. If you choose the same video, EthoVision will start tracking at that point in the video where the previous trial stopped. To make sure that tracking starts and stops at the correct time point, you must define appropriate Trial Control settings. TIP: If you want to use the same Arena Settings, Trial Control settings or Detection Settings for all the trials, select them in the Acquisition Settings window. Automatically Add Video Files to the Trial List - Click the Add Videos button on the toolbar. - In the Add Videos window, select the video files you want to use and click Open. - Select one of the options under Sort order and click OK: - Date-time order. Selecting this option links the video file with the earliest date/timestamp to Trial 1, the next video file to Trial 2, etc. - Alphabetical order. Selecting this option links the video files to the trials in alphabetical order. Manually Add Video Files to the Trial List Click one of the cells in the Video file column. In the Select Video window, select the video file and click Open. Do this for the other planned trials. Notes - If you select more video files than the number of planned trials in the Trial List, EthoVision will add additional trials to the Trial List. - If you manually linked videos to some of the planned trials, and for the remaining trials you use the automatic option, EthoVision only fills the gaps, that is, it adds videos to those trials which do not have video references yet. To Carry Out Batch Acquisition Choose Acquisition > Open Acquisition. In the Acquisition Settings window, select Track all planned trials. See Also - Acquire a series of trials (Batch acquisition) Acquire Data Main Topics and Tasks - Introduction to Data Acquisition - Acquire one trial - Acquire a series of trials (Batch acquisition) - Additional information on data acquisition - Score behaviors manually - Import data from other experiments - Import Live Mouse Tracker data - View real-time information - The data acquisition screen NOTE: If you plan to use hardware devices like a pellet dispenser or the PhenoTyper, see also the EthoVision XT 19 - Trial and Hardware Control - Reference Manual, which you can find on the Apps screen, under Noldus > EthoVision XT 19 Other Documentation. Introduction to Data Acquisition Learn About - Important terms in acquisition - Important things to know about data acquisition Important Terms in Acquisition Trial vs. Track A trial is a single acquisition session. A track is the data collected during a trial. A trial can contain one or more tracks. See Trial vs. track. Batch Acquisition Acquisition of a series of trials, either live, or from pre-recorded video files. Inter-Trial Interval When you choose a live series of trials, an inter-trial interval between two consecutive trials allows you to take the subject from the maze or cage, clean the maze/cage and release the next subject before the next trial starts automatically. Planned Trial When you add trials in your Trial List, their default acquisition status is Planned. EthoVision XT acquires the planned trials in the order specified in the Trial List: Trial 1, Trial 2, etc. You can skip a planned trial whenever you cannot acquire data, for example when the subject assigned to that trial is no longer available. Skipping a Trial It may happen that a trial planned in the Trial List cannot be acquired, for example when the animal to be tested is not available. You can skip one or more trials and acquire a trial further down in the Trial List. When you skip a trial (and all arenas within it), you can always set it back to Planned to acquire data at a later time. See Carry out trials in an order different from that specified in the trial list. You can also skip single arenas within a trial, for example not to acquire data in empty wells in a well plate. See Skip arenas within a trial. Start-Stop Trial Rule This is the rule in the Trial Control Settings that determines when actual tracking (data acquisition) starts and stops. For example, start tracking when the animal is detected in the arena. See The default Start-Stop Trial rule. --- ## EthoVision XT 19 - Acquire Data - Score Behaviors Manually After Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-score-behaviors-manually-after-acquisition Chapter: EthoVision XT Score Behaviors Manually After Acquisition Aim To add new or edit existing behavior scores in your trials. Prerequisites - You have defined behaviors in the Manual Scoring Settings. - You have acquired one trial and its corresponding video. Procedure - Choose Acquisition > Manual Scoring. - Choose the trial, and when it applies, the arena in which you want to score behaviors. - To enable the scoring mode, click the Start scoring mode button. - Follow one or more of the procedures below. - When finished, click the Stop scoring mode button. Tip: Before editing existing data, click the Save button on the toolbar. This will save a copy of the current behavior scores. In case you make mistakes when editing, you can always revert to that copy by clicking Undo. For more information, see Saving the track edits. To Score a Behavior With a Duration This applies to behaviors defined as Mutually exclusive and Start-stop. See Define the behaviors that you want to record manually. - Play the video to the point where the behavior starts. - To score the behavior at that point in the video, click the color button with the behavior name at the left side of the plot. The button is highlighted in red. - Play the video forward. As you play the video, a colored bar appears at the left of the hairline. If you play the video backward, the color bar is reduced in length. - Pause the video where the behavior stops. To score the end of the behavior, click again the button at the left, so it is not highlighted anymore. - Repeat steps 1-4 to add more instances of the behavior. To Score a Point Event Point events are events with no duration. See Define the behaviors that you want to record manually. - Play the video to when the behavior occurs. - To score the behavior at that point in the video, click the color button with the behavior name at the left side of the plot. - Play the video further. The point event is displayed as a vertical segment. Notes - After clicking the Start scoring mode button, the video image shows [On] and the message next to the button changes to Scoring on. When you play the video, behavior scores do not change until you click the corresponding button at the left side of the plot. - If you want to hide the center point to make the subject more visible, choose Track Visualization or Integrated Visualization or Track Editor, and de-select the body points on the right-hand pane. Next, close and re-open the experiment. - When you click the button for a behavior, the name of the behavior is displayed on the video image. To show/hide and customize this text, choose Show/Hide > Text Features. - When you score the start of a behavior (either Mutually exclusive or Start-Stop) and then you reach the end of the trial without scoring the end of the same behavior, that behavior is considered to last until the last sample. If the behavior is defined as Start-stop, a complementary behavior ("not-behavior") is added at the end of the behavior you scored. This means that the statistics of the complementary behavior is increased by 1. - Behaviors that are defined as Initially Active in the Manual Scoring Settings are shown as active throughout the trial, if you do not edit them. - If you want to show the arena and zones during the scoring sessions, click the Show/Hide button at the top-left corner, and choose Arena features. See Also - Edit the duration of manually-scored behaviors - Replace a behavior with another one - Delete a manually-scored behavior - Score behaviors in different arenas - Score behaviors of two or more subjects Edit the Duration of Manually-Scored Behaviors Aim To increase or reduce the duration of instances of behaviors already scored in your trial. This way you can improve the match between what you see in the video and the behavior scores. Note: This applies to all behavior types but Point events. Prerequisites - You have scored behaviors manually. See Score behaviors manually. Procedure - Open the Manual Scoring screen (Acquisition > Manual Scoring). - Choose the trial, and when it applies, the arena in which you want to score the behaviors. - Follow one or more of the procedures below. Tip: Before editing existing data, click the Save button on the toolbar. This will save a copy of the current behavior scores. In case you make mistakes when editing, you can always revert to that copy by clicking Undo. For more information, see Saving the track edits. To Extend the Duration to a Specific Time Point - Play the video up to when the behavior ends. --- ## EthoVision XT 19 - Acquire Data - Score Behaviors of Two or More Subjects URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquire-data-score-behaviors-of-two-or-more-subjects Chapter: EthoVision XT Score Behaviors of Two or More Subjects Aim To edit behaviors manually in a social interaction context. Important: If you tracked unmarked subjects, always check that there is no subject swap in your tracks. If that is the case, correct the swaps in the Track Editor screen. Otherwise you take the risk of scoring a behavior for the wrong subject. See Swap Subjects. Prerequisites - You have defined behaviors in the Manual Scoring Settings. - You have acquired one trial and its corresponding video. - You have opened the Manual Scoring screen (Acquisition > Manual Scoring). Procedure - In the Manual Scoring screen, subjects are indicated with different colors. - To score the behaviors of a subject, locate the plot marked with the same color. - Score the behavior as described in Score Behaviors Manually After Acquisition. - When you score a behavior with duration, the subject name is also indicated on the video image. Simultaneous Scoring of Behavior Behaviors are always associated with a subject. If you want to score a behavior valid for all subjects simultaneously, score the same behavior for each subject. - Position the video at the start of the behavior. - Click the button for each subject involved. - Play the video until the end of the behavior. - Click the button for that behavior again, for each subject. Notes - Behaviors like proximity can be automatically measured. See Social Dependent Variables. - Before editing existing data, click the Save button on the toolbar. This saves a copy of the current behavior scores. In case you make mistakes when editing, you can always revert to that copy by clicking Undo. For more information, see Saving the Track Edits. - To show or hide and customize the overlay text, choose Show/Hide > Text Features. Import Data From Other Experiments Aim To analyze data collected in two or more identical experiments. Example: You run experiments with a number of PhenoTyper cages. Each group of four PhenoTypers is controlled by a computer with EthoVision XT. Therefore, you have as many experiments as computers. You would like to analyze all the data from the original (source) experiments in one master experiment. Prerequisites - You have two or more EthoVision XT experiments containing data. - The setup must be identical between the original experiments. Import of different experiments (e.g. an open field and a PhenoTyper) will not work. - The original experiments and the master experiment must have identical settings, for example: - The same detected features (e.g. center point). - The same number of arenas and the same number of subjects per arena. - The same Arena Settings, with for example the same zone names, Detection Settings, and Trial Control Settings. - The same Behavior Recognition settings. - The same behavioral events defined in the Manual Scoring Settings. - The same hardware device names, mapped on the same arenas. For example, Lickometer 1 must be mapped on Arena 1 in all experiments. When you create the first of the original experiments, adjust the settings and then, before acquiring the first trial, save it with a different name to create an identical copy (File > Save As). This will be your second original experiment. Step 1 - Create the Empty Master Experiment - Start EthoVision XT on the PC that contains one of the original experiments. - Choose File > New from Template. Choose Use a custom template and select one of the original experiments. Select the file with the name of that experiment and the extension evxt. - Complete the procedure, and give the new experiment a name, for example Master experiment. - If you intend to work with the master experiment on a different PC, copy the original experiments and the master experiment to that PC. Step 2 - Import the Trials Into the Master Experiment - If needed, copy the original experiments to the PC where the master experiment is stored. - Open the master experiment. - Choose Setup > Trial List. - Delete the empty trials in the master experiment. These rows were generated and left empty when you created the experiment from the custom template. Select all rows, right-click and choose Delete Trials. See Delete Trials. - Click the Import Trials button. - In the window that opens, select EthoVision XT data (trials) and click OK. - Locate the experiment that you want to import. Select the file with the extension evxt and click Open. To locate this file, open the folder that has the same name as the experiment. - Select which trials you want to import. If you want to copy the video files into the master experiment, select Also import the associated video files. Note: This option only applies when the video files were generated by EthoVision XT in experiments set to Live tracking. If your original experiments are set to Offline tracking, the video files that were used for tracking are not copied; however, the master experiment preserves the link to those video files. After import, which may take some time depending on the number and length of the tracks, the imported trials are shown in the trial list. Result of the Trial Import What is imported in the master experiment: - The trials (track data, independent variables, manually-scored events, hardware events). - The settings associated with the trials (Arena Settings, Trial Control Settings, Detection Settings, Manual Scoring Settings). - The physiological data associated with the trials. Notes - If two settings profiles have the same name but slightly differ — for example, one Detection Settings profile named Detection Settings 1 in the first experiment is set to Gray Scaling 40 to 255 while Detection Settings 1 in the second experiment differs — the profiles will be treated as separate settings upon import. Source: EthoVision XT 19 Help - Acquire Data, Noldus Information Technology --- ## EthoVision XT 19 - Acquiring Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-acquiring-data Chapter: EthoVision XT Calculate the Statistics Time Before Reaching a Zone In step 2, click the button next to In zone. Specify the zone you are interested in. In the Trial Statistics tab, select Latency to first. Distance or Velocity in a Zone - Choose Analysis > Data Profile > New or open an existing Data profile. In the box Results click Settings, then select Results per zone. Next, choose the zones you want the results for. - Open an Analysis profile. Choose the variable you want to calculate. For example, Distance moved. Next, choose Analysis > Results > Statistics and Charts. Notes - EthoVision XT offers a wide range of analysis variables and methods to select data. See Other Analysis Options below. - In the results screen, the Trial Statistics tab shows the analysis results per trial, while the Group Statistics & Charts tab shows the results for all trials together, or for the groups of trials defined in your Data profile. To modify the layout of the results table, click the Layout button. - To carry out multiple calculations at once with different filters, data profiles or analysis profiles, click the Batch button. Visualize the Data Track Visualization Choose Analysis > Results > Plot Tracks to view the tracks that you selected. This allows you to visually compare tracks. You can play back your tracks to see how your subjects moved. To display the entire track, under Filter deselect the Last [ ] seconds option, then click the Jump to End button in the Playback Control window. Integrated Visualization Choose Analysis > Results > Plot Integrated Data to view the track with the corresponding video (when video was recorded) and the time plot of the dependent variables (velocity, etc.). To plot a variable: - Open an Analysis profile and add the dependent variable you want to view. - Choose Analysis > Results > Plot Integrated Data. Other Analysis Options Heatmaps Choose Analysis > Results > Plot Heatmaps and click Plot Heatmaps on the toolbar. With heatmaps you get an immediate impression of which area the animal spent most time in. Select and Group Tracks Choose Analysis > Data Profile > New. To Analyze Some Tracks, Not Others - Choose one of the options under Filter. For example: - Choose Trial Name and select the trials you want to analyze. - Choose Dose (an independent variable previously defined) and choose the values of the variable you want to use. - Insert the Filter box between Start and Result 1. To Analyze Tracks in Groups For example, you want to compare the results for subjects treated with a drug with those for control subjects. - In the Trial List, make sure that the independent variable that you want to use for grouping is defined, and that each trial is labeled with one of the possible values (e.g. Treated vs. Control). - Make a Filter for the first group based on one of the values of the independent variable, and place the resulting box between the Start and the Result 1 box. Source: EthoVision XT 19 - Quick Start Guide --- ## EthoVision XT 19 - Activity state URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-activity-state Chapter: EthoVision XT Activity State The dependent variable Activity state is only available when you selected Activity analysis in the Experiment Settings and you track only one subject per arena. With Activity state you can calculate how long and how frequent your subject has been in different activity states. These states depend on the total pixel change within the arena between a sample and the previous sample. The number of states and their thresholds are user-defined. When the subject goes missing for more than three samples, the current Activity state is ended and the remaining missing samples are ignored. Calculation Step 1 - Calculation of Proportion of Pixel Change All pixel coordinates in the arena, so not only of the detected subject, are determined immediately after they have been detected. The gray scale values of all pixels are compared with the previous sample to determine the number of changed pixels in the arena between the two. The formula for Activity is simply the number of changed pixels for the current sample k divided by the total number of pixels in the arena. Activity is calculated by taking every pixel and comparing it between the current image and the previous one. If all the pixels are the same, there is zero activity. If all the pixels are different, there is 100% activity. If the animal is moving and increases its velocity (whilst keeping the same shape) there will be an increase in activity, because the pixels belonging to the animal are increasingly different as it moves faster. Step 2 - Running Average To smooth the values of Activity, an Averaging interval is used. This gives you the option to specify the number of samples for calculating a running average of Activity. The Activity percentage is summed over the number of samples that you specify, and divided by the number of samples. This way, sudden changes in surface area caused by such factors as the animal entering a shadowed area, or a reflection, are smoothed out. NOTE When you export the dependent variable, each row in the export file contains the Activity value, but not the averaging interval. Step 3 - Calculation of the Activity State Dependent Variable The Activity state variable is established for each sample, according to the value of running average Activity relative to the thresholds. You can define between two and four states, varying from Inactive (below the lowest threshold) to Highly active (above the highest threshold). How to Specify Activity State - Click the Add button next to Activity State. - Enter the following: - Averaging Interval: The number of samples over which the running average mobility is based. The default value is 1, that is, the current value of Elongation is only based on the current image. - Under Number of states, select the number of activity levels you are interested in. The following options are available, dependent on the number of states: - 2 states: Highly active above and Inactive below. - 3 states: Highly active above, Moderately active between and Inactive below. - 4 states: Highly active above, Active between, Moderately active between and Inactive below. - Under Thresholds, specify thresholds for the states defined in step 3. You can enter a number with up to two decimals. - Under State duration threshold, in the field next to Exclude instances shorter than, enter how long a state must last before it is scored as one of the four Activity states. If the duration passes this threshold, the samples in this time length are scored as one of the four states according to the criteria above. If the duration does not pass the threshold, the previous state ends, but no new state is defined. When you visualize Activity state in the Integrated Visualization, this is displayed as a gap between two adjacent color bars, which represent the scored activity states. - Under Calculate statistics for, select at least one of the states defined in step 3. - Complete the procedure to add the variable. See Calculate statistics: procedure. To find the optimal activity thresholds, run a few test trials and check in the Analysis Results and Scoring pane the values of Activity when the animal shows such behavior. These values are calculated real-time during acquisition. See an example in Fear conditioning: view Activity state. Notes - IMPORTANT The Activity detection thresholds set in Acquisition are not used in analysis. When you specify Activity in your Analysis profile, enter the new values in the appropriate fields. - In some cases the number of samples available for smoothing can be less than the averaging interval entered. For example, when there are missing samples or at the beginning of the track. In such cases EthoVision XT uses the samples available in the specified interval. For example, the value of Activity for the first sample of the track is always calculated over one sample. - You set the thresholds during acquisition, but you can override them when calculating statistics to produce new values for Activity state. To see what the original values of Activity state thresholds were (unless you have changed them while acquiring data), open the Acquisition module and click the button under Activity in the Analysis results and Scoring pane. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Activity state (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-activity-state-continued Chapter: EthoVision XT Frequently Asked Questions About Activity - What is the difference between Activity and Mobility? Activity is the percentage change in all pixels in the arena between the current sample and the previous sample. This is independent of the detected subject. Mobility is the percentage pixel change between the current sample and the previous sample in the detected subject only. See Rotation. - When should I use Activity and when should I use Mobility? Use Activity when the dependent variable Mobility does not give satisfying results, or if detection of your subject is difficult. This can be the case when bars of the shock grid floor in the background complicate detection of the animal's surface area, or when the animal is very large compared to the arena size. - Does Activity detection depend on the size of the subject relative to the arena? Yes. Activity is calculated as the number of changed pixels divided by the total number of pixels in the arena. The smaller the subject relative to the arena, the smaller the activity will be. When your animal is very large in comparison to the arena size, for example when you have a rat in a small cage, activity detection is generally more suitable than mobility detection. - Does Activity detection depend on the video resolution? Yes. The higher the video resolution, the greater the number of pixels that change when the subject moves. Therefore, when you have a high video resolution, it is less likely that a small movement of the subject results in an abrupt change in activity. However, this effect is present at very low resolution (for example, when the subject is less than 100 pixels large). We advise you not to compare values of Activity between videos of different resolutions. - Does Activity detection depend on sample rate? Yes. Since Activity is detected from the change in pixels between two samples, and the pixel change depends on how frequently the area is acquired (that is, the sample rate), Activity depends on the sample rate. All being equal, the higher the sample rate, the smaller the pixel change. See also the effect of the sample rate on Mobility in Frequently Asked Questions About Mobility. Applications Activity can be used to determine freezing behavior in rodents. Also, it may be used to assess inactivity of rodents in a Porsolt Swim Test. Furthermore, the startle response of zebrafish larvae can automatically be detected with (in)activity. Definition Body elongation measures how much the subject's detected shape differs from a circle. NOTE Body elongation is not available if your experiment is set to: - Center-point detection. - Color marker tracking. - Live Mouse Tracker (but see Stretch Attend Posture). - Center-point, nose-point and tail-base detection, with two subjects per arena tracked with Deep learning. Calculation - The Body elongation measure E is calculated as follows: - x, y are the coordinates of the pixels of the subject's contour in the current sample. - xc and yc are the coordinates of the center of the subject. - The Body elongation value is smoothed at each sample using the optional Averaging interval. Body elongation is expressed as a percentage and ranges from 0% (when the subject's shape is perfectly circular) to 100% (when the subject's shape is a line). How to Specify Body Elongation - Click the Add button next to Body elongation and click the Body Elongation tab. - Enter the Averaging interval. This is the number of samples over which the running average elongation is based. The default value is 1, that is, the variable is not smoothed using the values of neighboring samples. See Averaging Interval. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - Body elongation is not calculated with Live Mouse Tracker data. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Add a user URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-add-a-user Chapter: EthoVision XT Add a User The procedure to add a user differs depending on whether EthoVision XT came installed on a computer, or was installed by the user, and on whether the computer is on a domain or not. Follow the procedure according to your situation. Prerequisites - You have been assigned User Management rights in EthoVision XT. - There is no experiment open. Adding a User on a Domain (Pre-Installed System) Make sure that user EVXT has also been added to the domain by your network administrator. To add a new user in EthoVision XT: - Log on to Windows as user EVXT and open EthoVision XT. - Choose File > Users. - In the User Management window, click Add. - In the Add New User window, click Network. - A list of users on the domain appears. Select a user from the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add a user to the list of users that can access EthoVision XT. Next, assign rights to the new user. Adding a User Not on a Domain (Pre-Installed System) When EthoVision XT was installed by Noldus Information Technology on an EthoVision XT computer, initially there is only one user, EVXT, on that computer. Log on to Windows as this user. You can find the password in the welcome letter you received with the software. You first need to define new users in Windows before you can add them to the list of authorized users in EthoVision XT. You must have a local computer administrator account to add a new user to the computer. To add a new user in Windows, click the Start button, then select Settings > Accounts > Other people/Other users. Next, add this user in EthoVision XT: - Open EthoVision XT and choose File > Users. - In the User Management window, click Add. - Local users on the computer are shown. Select one of the users in the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add this user to the list of users that can access EthoVision XT. Next, assign rights to the new user. Adding a User on a Domain (User-Installed System) The user that installed EthoVision XT can add new users to the list of authorized users in EthoVision XT. - Open EthoVision XT and choose File > Users. - In the User Management window, click Add. - In the Add New User window, click Network. - A list of users on the domain appears. Select a user from the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add a user to the list of users that can access EthoVision XT. Next, assign rights to the new user. Adding a User Not on a Domain (User-Installed System) First, you might need to add local users to the computer. You must have a local computer administrator account to add a new user to the computer. To add a new user in EthoVision XT: - Open EthoVision XT and choose File > Users > Add. - Local users on the computer are shown. Select one of the users in the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add this user to the list of users that can access EthoVision XT. User Roles When you add a new user, you have the option to select one of three predefined roles, each representing a set of rights. However, these rights can be changed at any time. The three initial roles are: - Administrator — With default rights User Management and EthoVision Preferences. - Researcher — With default rights Experiment Management, Experiment Settings, Trial Control Settings, Arena / Trial Control / Detection Settings, Acquisition, Import External Data, Edit Tracks, Edit Data Profile / Analysis Profile. - Technician — With default rights Arena / Trial Control / Detection Settings, Acquisition, Import External Data. User Rights - User Management — Gives you the right to add and remove users, and change user rights. - EthoVision Preferences — Gives you the right to change the default experiment folder, the warnings displayed, and the autosave options. - Experiment Management — Gives the right to create new experiments, make and restore backups. - Experiment Settings — Gives the right to set and change Experiment Settings. - Trial Planning — Gives the right to add trials and variables to the Trial list, and to skip trials or arenas within trials, and re-do trials. - Arena / Trial Control / Detection Settings — Gives you the right to create and/or edit Arena Settings, Trial Control Settings, and Detection Settings. - Acquisition — Gives the right to change Acquisition settings and carry out Acquisition. - Import External Data — Gives the right to import external data files. - Edit Tracks — Gives the right to edit tracks. Note: It is likely that your Standard Operating Procedure forbids modifying acquired data. If this is the case, no user should have this right. The original data is always stored in your experiment. - Edit Track Smoothing, Data, Analysis Profiles — Gives the right to smooth tracks, create and edit Data profiles and Analysis profiles. - Delete Trials and Clear Log — Gives you the right to delete trials and delete the Experiment log file. Notes on User Rights - It is likely that your Standard Operating Procedure forbids modifying acquired data. If this is the case, no user should have this right. By default, this right is disabled for all users. - The Delete Trials and Clear Log right is useful when you want to create a template experiment. This template experiment, for example, contains default settings as defined in a Standard Operating Procedure, but should not contain test trials and an already filled log file. Also see Creating an Experiment Template. It is advisable to create a special user for this right. In normal operation under GLP, no user should be able to perform these actions. EthoVision XT Logging With the logging functionality in EthoVision XT, you enable auditing of changes to settings that were made during an experiment. EthoVision XT creates two types of log files: - General Log File — In this Application log, the usage of EthoVision XT by authorized users is registered. See The General Log File. - Experiment Log File — One for each experiment, to register the settings made and actions carried out during that experiment. The user, date, and time are logged for each setting and action. See The Experiment Log File. Notes on Logging - The user can at any time add additional user comments to the Experiment log file. - The log file is tamper-proof. As soon as someone edits it outside EthoVision XT, that is detected and it is logged that the file has been tampered with. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Analog cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analog-cameras Chapter: EthoVision XT PhenoTyper 1 - TV Standard: PAL and NTSC. - Cable Length: Up to 100 m (not tested). - Maximum Number of Cameras: 16 when using one Picolo Alert encoder board and four video processors (Quad Units). See Install Analog Cameras. - Resolution: For configurations with two or more cameras, the resolution of the resulting video file is reported. In brackets, the resolution of the single camera image is reported. - Important: When mixing 16 PhenoTyper 1 cameras, the resolution of a single camera image is 384 x 288 (PAL) or 320 x 240 (NTSC). This resolution is often too low for nose-tail tracking. If you want to use the Deep learning-based method to track subjects, work with up to four analog cameras (and four arenas). Tested Configurations With 4 Cameras, Desktop Notes: Detection method used: Dynamic subtraction or Differencing. Missing samples: 0.0%. Computer Video Resolution (WxH) Frame Rate (fps) Duration (h) DL or C Dell Precision PAL 1536 x 1152 (768 x 576) DL Dell Precision NTSC 1280 x 960 (640 x 480) 29.97 DL Tested Configurations With 16 Cameras, Desktop Notes: Detection method used: Dynamic subtraction or Differencing. Missing samples: 0.0%. Computer Video Resolution (WxH) Frame Rate (fps) Duration (h) DL or C Dell Precision PAL 1536 x 1152 (384 x 288) C Dell Precision NTSC 1280 x 960 (320 x 240) 29.97 C - Body Point Detection Technique: DL = Deep learning, C = Contour-based. - Desktop: Dell Precision 3680, Graphics card NVIDIA T1000 8 GB, Picolo Alert encoder board. For deep learning see also GPUs Tested and Supported. - Quad Unit Used for Testing 16 Cameras: UHPPOTE 4CH Color Quad System. See Also - Resolution, Frame Rate, and Maximum Trial Duration - Connect Analog Cameras to the Computer - The PhenoTyper - EthoVision XT 19 - Reference Manual. See Manuals. Install GigE Cameras Together with the Basler GigE camera, you need a 1Gb Ethernet board installed in your computer. To connect the camera, you need at least cat-5e cables. Important: To install the camera, follow each step below. Most information applies to the Basler GigE cameras. What Do You Want to Do? - Install an Ethernet board for GigE cameras - Install the driver software for the digital cameras - Assign IP addresses - Disable the Windows firewall for the Ethernet board - Connect the GigE camera to the PC - Configure the digital camera - Using multiple GigE cameras See Also - Cameras Supported by EthoVision XT Install an Ethernet Board for GigE Cameras Aim: To install a network board that receives video from one or more GigE cameras. Note: If you ordered a computer from Noldus Information Technology when you purchased EthoVision XT and Basler GigE cameras, the Ethernet interface board(s) has already been installed and tested. If you bought your computer somewhere else, you will have to install the board yourself. Follow the instructions below. Important: The network interface board must support data transfer of 1 Gb/s. This topic applies to Ethernet interface boards that have been tested with EthoVision XT. - One-Port Board: The Intel PRO/1000 CT (or its successor), to connect one camera. - Four-Port Board: The Adlink PCIe-GIE74 (A), or the Basler GigE Interface Card (B) to connect up to four cameras. - Two-Port Board: FS X550AT2-2TP. This was combined with an optical switch FS 3100-16TMS to connect 16 GigE cameras. See 16-Camera Configuration. Procedure - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. Different PCIe slots have different properties, resulting in different performances. When possible, choose the slot that gives maximum performance. To estimate performance, take note of the slot version (2, 3, etc.) and compare it with the following: - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: ~1 GB/s - PCIe v4.0: ~2 GB/s - PCIe v5.0: ~4 GB/s - PCIe v6.0: ~8 GB/s Note that values are given per lane; they should not be multiplied by the number of lanes in a slot (e.g. x4) since the board has a 1x connector. For example, SLOT1-PCIe3x4 written near the slot means version 3.0 with four lanes. Important: Do not insert the PCIe board in the blue or white slots. - Unpack the Ethernet board, place it into the slot, and press it carefully into position. If the board does not fit into place easily, remove it and repeat the operation. Important: When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet, and attaching its clip to the metal frame of the computer. If you do not have an earthing wristlet, hold the metal frame with one hand while holding the Ethernet board in your other hand. Ensure also that your clothing does not touch any components while handling the board. - This step is only for when installing a 4-port board. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. See Power the Ethernet Board for the GigE Cameras. - Fix the board to the chassis and re-fit the computer's cover. - Important: If you have not done so yet, turn off Fast Startup in the Windows Power options. See Power Options When Using Cameras. - Next: Install the driver software for the digital cameras. Main Settings of the Ethernet Board You may need to check these settings if the PC and camera are set correctly based on this Help and yet you get camera issues in EthoVision XT: - In Windows, open the Device Manager. - Under Network Adapters, locate your Ethernet board, right-click on it and select Properties. - Click the Power Management tab. - Make sure that Allow the computer to turn off this device to save power is not selected. Notes - For information from Basler about network interface boards and which ones are supported with the GigE cameras, see: - https://docs.baslerweb.com/hardware-installation-(gige-cameras)#basler-1gige-cameras - https://docs.baslerweb.com/knowledge-articles#gige - Important: Turn off Fast Startup in the Windows Power options. See Power Options When Using Cameras. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Analysis, Visualization, and Export URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analysis-visualization-and-export Chapter: EthoVision XT Other Analysis Options Creating a Second Group and Viewing Group Statistics - To create the second group, click the Result button under Common elements. Click and drag from the center of the Start box to the center of the new Result box. The two boxes are now connected with an arrow. - Make a filter for the second group, and place the Filter box in the middle of the second branch. - Choose Analysis > Results > Statistics and Charts. Click the Group Statistics and Charts tab to view the results per group. Analyze Track Segments Use this option to visualize the data of the first five minutes of the tracks, or to visualize all samples when the subject was moving or grooming. - Choose Analysis > Data Profile > New. - To select track segments based on time, zones, or states of the subject, click the appropriate button under Nesting and specify the options there. For example, to analyze the first five minutes, choose Time. - Insert the Nest box between Start and Result 1. Time Bins To analyze the tracks split in regular time intervals: - In the Result box, click Settings and select Results per time bin. For example, define intervals of 1 minute each. - Choose Analysis > Results > Statistics and Charts. For more information, see Analyze Track Segments in the EthoVision XT Help. Export Data and Results Main Procedure To find out if your independent variables (like treatment, dose, etc.) have a significant effect on the dependent variables, you can export your data to a statistical package. - To export the averages, totals, etc. per trial or per group of trials, choose Analysis > Export > Statistics. - To export the raw x,y coordinates and the surface area of the subject, or the per-sample values of the dependent variables, choose Analysis > Export > Raw Data. For details, see File Management > Export data in the EthoVision XT Help. Copy Entire Experiments To make a copy of an entire experiment: - Choose File > Make Backup. - Choose the options you require and select OK. The backup file (*.evz) contains all your settings and data, and optionally media files, exported files, and physiological data. You can copy this file to another computer where EthoVision XT is installed. To open the experiment on that computer, choose File > Restore Backup. Important: Backup your data to a network drive or external hard disk at least once per day. For More Information Help and Other Manuals For more details, in EthoVision XT, press F1 to open the Help. See also other manuals stored on your computer. On the Windows Start menu, choose All Apps > Noldus > EthoVision XT 19 Other Documentation. Sample Experiments Choose File > Restore Backup and browse to C:\Users\Public\Documents\Noldus\EthoVision XT\Experiments\Sample Experiments. You will find the sample experiment Morris water maze test XT190.evz. For more sample experiments, browse to my.noldus.com. Log in or register using the code that you have received. Next, choose Downloads > EthoVision XT > Sample Experiments. Each experiment focuses on a specific apparatus or on a feature of EthoVision XT, for example, trial control. Video Tutorial Choose Help > Video Tutorial. Watch the tutorial to learn how to set up a video tracking study in EthoVision XT. Mini video tutorials are also available in several parts of the program. Click the video button on the toolbar to view the tutorials. Remote Training Courses Noldus offers training courses to help you get the most out of our software and hardware. In addition to on-site courses at your lab and in-house courses at our headquarters in Wageningen (The Netherlands) and Leesburg (VA, USA), we offer remote training courses. Remote trainings are available in the same range of languages as on-site courses. Please contact your sales representative for more information about remote trainings. Technical Support If you encounter problems, visit my.noldus.com to search the support knowledgebase or contact the help desk. Source: EthoVision XT 19 - Quick Start Guide --- ## EthoVision XT 19 - Analyze Entire Tracks - Analyze Groups of Tracks URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-entire-tracks-analyze-groups-of-tracks Chapter: EthoVision XT Analyze Groups of Tracks - Define groups of tracks - View the results for groups of tracks Define Groups of Tracks Aim To compare groups of tracks. For example, to compare the tracks of animals treated with a drug with the tracks of control animals. You can easily create groups by filtering tracks according to one or more independent variables, and linking that filter criterion to a specific Result box. Procedure - Create a new Data Profile. - To add a Result box, in the Components pane under Common Elements click the button next to Result. The new Result box is by default named Result 2. Place this box somewhere under the Result 1 box. - Connect the Start box to the Result 2 box. - Filter your tracks by the independent variable Treatment Level: - Click the button next to Treatment Level. Choose Control and place the resulting Filter box between Start and Result 1. - Click again the button next to Treatment Level. Choose Treated and place the resulting Filter box between Start and Result 2. - The Data Profiles window should now display the configured filter connections for both groups. Source: EthoVision XT 19 Help - Analyze Entire Tracks, Noldus Information Technology --- ## EthoVision XT 19 - Analyze Entire Tracks - Create a New Result Box URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-entire-tracks-create-a-new-result-box Chapter: EthoVision XT Create a New Result Box Create a new Result box when you want to display analysis results from different data selection criteria at the same time. For example, to calculate statistics for two groups of tracks. - In the Components pane, under Common elements, click the button next to Result. The new Result box appears in the top-left corner of the Data Profiles window. Connect the selection box to other boxes. - Drag the new Result box to the right-hand side of the Data Profiles window, below the first Result box. - Complete the selection sequence by making a branching so that each data selection criterion ends up in its own Result box. Edit the Result Box Name The Result boxes are named automatically as you create them: Result 1, Result 2, etc. The Result box name is shown in the Analysis results (statistics and track plots), so it is good to give a name that reminds you from which data selection that result comes from. - Click the Settings button in the bottom-right corner of the box. - Enter the new name in the Name field. Snap to Grid The data selection boxes automatically snap to a grid. You can change this by clicking the Show/Hide button on the toolbar and selecting/deselecting the two Grid options (Snap to Grid and Show Grid). Zoom In and Out The toolbar of the Data Profiles window shows three zoom icons: - Zoom in (Ctrl+.). Click this button until all data selection boxes fit in the window. - Zoom out (Ctrl+,). - Fit all. Click this button to fit all data selection boxes into the window. The Data Profiles window is dynamic: this means that it expands when you move data selection boxes to the right. In this case, you can navigate from left to right in the Data Profiles window by using the scrollbar at the bottom. Use the Zoom to Fit button on the toolbar to make all data selection boxes visible. --- ## EthoVision XT 19 - Analyze Entire Tracks - Filter Tracks URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-entire-tracks-filter-tracks Chapter: EthoVision XT Filter Tracks What Is Filtering? Filtering is the process of picking out entire tracks, either manually or based on the value of independent variables (System or User-defined). Filtered tracks and the corresponding video and external (physiological) data are subject to analysis. Unlike filtering, Nesting picks out segments of tracks. You can combine Filter and Nesting criteria. To Filter Tracks - Create a new data profile or open an existing one. - Locate the variable in the Components pane that you want to use for filtering data, and click the corresponding button. If you do not see the item you are looking for, click the button next to More. - A Filter box appears in the top-left corner of the Data Profiles screen. The Independent Variable values window opens on top. - Select the values of the variable for the tracks you want to analyze, and click OK. - Drag the Filter box to the desired position in the selection sequence between the Start and the Result box. - Repeat steps 2 to 5 to add more Filter boxes and refine your selection. Notes: - Scope of the variable. Within a single trial, you can select different data sets depending on the Scope of the variable used (Trial, Arena or Subject). Depending on your setup, a trial may consist of one or more arenas. Each arena can include one or more subjects. - By filtering by a variable with Trial scope, you analyze all data for the trials that you specify, no matter how many subjects and arenas those trials contain. - By filtering by a variable with Arena scope, you analyze all subjects recorded in the arenas that you specify, and you ignore the data recorded in other arenas in the same trial. - By filtering by a variable with Subject scope, you analyze the tracks referring to the subjects that you specify, and ignore the tracks of other subjects recorded in the same arena and trial. - If the Independent Variable values window does not list any value available for selection, it means that no values have been assigned to any trial in the Trial List. - You can combine different filtering criteria to create complex data selections. To do so, insert multiple Filter boxes in the same sequence. - You cannot filter tracks according to specific values of external (physiological) data. For example, filter all tracks for which average heart rate was higher than 600 bpm. - If you want to edit an existing Filter box, click the Settings button of that box. Variables Available for Filtering System Variables - Start time. Filters the tracks belonging to the trials started at the times you select from the list. Tracks acquired from video files have the time of creation of the video files as their start date/time. Tracks that belong to the same trial have equal Start Time. If you have applied Trial Control with Start conditions, actual data recording may have started at different times in each track. If you want to select individual tracks according to when actual data recording started, filter tracks by the variable Recording after. - Video file. Filters the tracks recorded from the video files you select from the list. - Tracking source. Shows the camera source if you track live. Since EthoVision allows one camera source per experiment, this variable will show only one camera. - Trial Duration. Filters the tracks belonging to the trials of the duration you select from the list. Tracks that belong to the same trial have equal Trial Duration. If you have applied Trial Control with Start or Stop conditions, the duration of actual data recording may be different for each track. If you want to select individual tracks according to the duration of actual data recording, filter tracks by the variable Recording Duration. - Arena settings. Filters the tracks recorded using the Arena Settings profile you select from the list. - Trial name. Filters the tracks belonging to the trials you select from the list. Tracks recorded in the same trial have the same Trial name. If you want to select individual tracks, filter by the variable Arena name or Track. - Arena name. Filters the tracks recorded in the arenas you select from the list. This option is useful if you have a multiple arena setup and want to analyze data from some arenas but not others. - Subject name. Filters the tracks of the subjects you select from the list (available when tracking multiple subjects per arena). - Track. Filters the tracks you select from the list. Each track name corresponds to data of one individual subject recorded in one arena and in one session (trial). If you want to select data according to the recording sessions, filter by Trial name. - Recording after. Filters the tracks that started a specific time after the start of the Trial. This option is useful if you apply Trial Control with Start conditions, where actual data recording for each track may have started later than the trial's start time. For example, in a multiple arena setup, Trial 1 started at 10:23:00, but actual data recording started after 5 seconds in Arena 1 and after 30 seconds in Arena 2. If you do not use Trial Control with Start conditions, the Filter Variables window for Recording after shows only the value 0. - Recording duration. Filters the tracks recorded for the time you select from the list. This option is useful if you apply Trial Control with Start and Stop conditions, where actual data recording may be shorter than the trial duration. For example, in a two-arena setup, a trial lasted 15 minutes; in Arena 1 actual data recording lasted 15 minutes while in Arena 2 it lasted 12 minutes because a Stop condition was met before the trial stopped. If you do not use Trial Control, actual data recording lasts as long as the trial, so Recording duration is the same as Trial Duration. - Video start time. Filters the tracks recorded from the video file created (or last saved) on the date and time you select from the list. - Detection settings. Filters the tracks recorded using the Detection Settings profiles you select from the list. The Detection profile variable has Trial Scope, meaning that within a trial all tracks have the same Detection Profile. - Trial control settings. Filters the tracks recorded using the Trial Control profile you select from the list. - Sync status. Filters the tracks corresponding to the status of the synchronization between track and co-acquired external data. - Planned: Filters the tracks for which no external data co-acquisition has been carried out. - Acquired: Filters the tracks for which co-acquisition was carried out. - Missed Samples. Filters the tracks corresponding to the proportion of missed samples caused by, for example, a too high processor load. - Subject not found. Filters the tracks corresponding to the proportion of samples which were processed by EthoVision but in which no subject was detected. User-Defined Variables This list depends on the variables that have been defined in the Trial List. Click the button next to the variable you want to use as a criterion for filtering data. External Data If you import external data into one or more trials, the physiological variables are listed in the Components pane under Filter. Click the button next to the variable you want to use to filter data. In the window that appears, select the imported data files you want to analyze. Tracks linked with those data files are selected for analysis. If you filter by External data, the data subject to analysis also includes the tracks and the video files associated. What track data are selected with external data files depends on how you linked the external data files to the track data during import (whether at the Trial, Arena or Subject level). For example, if ECG data files are linked at the Trial level, entire trials are filtered. If ECG data files are linked to Subjects, only the tracks for the subjects linked to those ECG files are filtered. --- ## EthoVision XT 19 - Analyze Track Segments - Analyzing Track Segments in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-analyzing-track-segments-in-ethovision-xt Chapter: EthoVision XT Analyzing Track Segments in EthoVision XT Result Boxes and Filtered Data The two Result boxes receive the data filtered according to the independent variable Treatment Level. Result 1 receives five tracks filtered with Treatment Level = Control. Result 2 receives other five tracks filtered with Treatment Level = Treated. Tip: The name of the Result box is shown in the results (statistics and track plots), so it is good to give a name that reminds you from which data selection that result comes from. Click Settings in a Result box and rename it. For example, rename Result 1 to Control Group. View the Results for Groups of Tracks Prerequisite You have defined one or more groups of tracks. To View the Results for Groups of Tracks - Create a new Analysis profile and choose the dependent variables (for example, Distance Moved). - In the Experiment Explorer, under Results, choose the option you require (Calculate Statistics, Heatmaps, etc.). In the analysis results, you can see which output is produced by which Result box. Look up the Result header. For example, in the Statistics & Charts screen, click Group Statistics and Charts. In the Heatmaps screen, click Group Mean and then click the Plot Heatmaps button. Analyze Track Segments Main Topics and Tasks - Analyze Track Segments: Main Concepts - Nesting over Time - Nesting Using Zones - Nesting over Behavioral States - Nesting over a Trial Control State - Nesting over a Free Interval - Nesting over a Multi Condition - Nesting over External Data - Nesting over Subjects - Results per Time Bin Analyze Track Segments: Main Concepts Analyzing Track Segments In EthoVision XT you can pick out segments of tracks specified by time intervals or the behavior of the subject. To do so, use the Nesting function in the Data profile. When Nesting is activated, analysis is carried out on the samples within those track segments, and the corresponding video and external (physiological) data. The track segments outside the selection are not included in the analysis. A track is represented by samples on a time line. For example, a mouse entering a zone partway through the track, then sniffing air towards the end. The samples selected for analysis differ depending on whether you are nesting over a zone, over time (for example, the first half of the track), or over a behavior (for example, sniffing). An Important Difference Selecting a variable in the Data profile is not the same as selecting the same variable in the Analysis profile. For example: - When you choose In Zone under Nesting in the Data profile, you select the samples when the animal was in a zone. Then, in the Analysis profile you choose a dependent variable, like Velocity. As a result, EthoVision XT calculates the velocity of the subject when it was in the zone. - When you choose In Zone under Location in the Analysis profile, EthoVision XT calculates statistics for the variable In Zone, for example, the time spent in a zone, or the number of zone entries, but not the velocity of the subject when it was in that zone. Nesting Options - Nesting over time — to analyze a time interval defined by a Start time and a Stop time. For example, analyze the first 15 minutes of each track. - Nesting over zones — to analyze the track segments when one or more subjects are within a zone or a combination of zones. For example, analyze the behavior of the mouse when its nose point was in a zone defined around the novel object. - Nesting over behavioral states — to analyze the track segments corresponding to the state of one or more subjects (for example, Movement or Grooming). This option includes manually-scored behaviors and behaviors recognized automatically. For example, analyze all the samples collected when the animal's body was stretched, or analyze the locations where the animal was sniffing. - Nesting over trial control states — to analyze the track segments corresponding to the time between two events of Trial Control. For example, analyze the time from when the cue light switched on to when the mouse consumed the food item delivered. - Nesting over subjects — to analyze the track segments based on the behavior of another subject. This is available when your arena contains multiple subjects, such as in a social interaction test. For example, analyze the track segments of Subject 1 when Subject 2 was in proximity of Subject 1. Notes - Track segments defined with Nesting are left-closed [A, B). That is, the start sample A, not the stop sample B, is included in the analysis. - To analyze entire tracks, use the Filter function. See Filter Tracks. - You can also combine Filter and Nest boxes to create complex selections. See Complex Data Selections. How to Select Track Segments - Create a new data profile or open an existing one. - Locate the variables under Nesting or Nesting over Subjects in the Components pane that you want to use to select track segments, and click the corresponding button. A Nest box appears in the top-left corner of the Data Profiles screen and a new window opens on top. - Select the values that define the track segments you want to analyze, and click OK. - Drag the Nest box to the desired position between the Start and the Result box. See Insert a Box in a Data Selection Sequence. - Repeat steps 2 to 4 to add more Nest boxes and refine your selection. If you want to edit an existing Nest box, click the Settings button in that box. - Choose Analysis > Results > then one of the options available to obtain numerical and graphical results for the track segments selected. Notes - If you have tracked two or more subjects per arena, you have two main nesting options: - Nesting — choose this category if you want to analyze the track segments that correspond to the behavior of the subject of that track. - Nesting over Subjects — choose this category if you want to analyze the track segments that correspond to the behavior of subjects other than the subject of that track, or a combination of subjects. See Nesting over Subjects. --- ## EthoVision XT 19 - Analyze Track Segments - Examples of Nesting Over a Free Interval URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-examples-of-nesting-over-a-free-interval Chapter: EthoVision XT Examples of Nesting Over a Free Interval Example 1: Analyze the First 20 cm of Swim Path in a Water Maze Aim Suppose you want to analyze the movement of the subject in the initial swim path, say in the first 20 cm. A Data profile with Free interval "From track start to Total distance moved 20 cm" is defined. In the Analysis profile you can then for example define the heading angle of the subject, which will be calculated for that interval. Solution In the Data profile, under Nesting choose Free interval, with: - Start criterion: Track start. - Stop criterion: Dependent variable Distance moved, Statistic Total, is >= 20 cm. Note that the Total Distance moved is unlikely to be exactly 20 cm at a given sample time; for this reason, the end criterion says ">= 20 cm". Next, in the Analysis profile choose the variable you want to calculate, for example Heading to point, or Turn angle. Then choose Analysis > Results > Statistics and Charts. See also: - Analysis advisor: Analysis in relation to the path Example 2: Analyze the Time up to When the Subject Has Explored an Object for 30 Seconds Aim In a novel object experiment, the trial lasts for example 5 minutes. Subjects often differ in the amount of time spent exploring the objects. The researcher wants to analyze the same exploration time across subjects, for the object labeled as zone "Familiar object". Solution In the Data profile, under Nesting choose Free interval, with: - Start criterion: Track start. - Stop criterion: Dependent variable In zone, Statistic Cumulative duration, is >= 30 s. In zone is a dependent variable defined for the zone "Familiar object" and the body point "nose-point". Next, in the Analysis profile choose the variable you want to calculate, for example In zone, to calculate the number of exploration events in the 30 s of exploration time. Then choose Analysis > Results > Statistics and Charts. See also: - Zone visits (entries and time spent) - Other analyses with zones Example 3: Compare Two Intervals, 5-s Before vs. 5-s After a Stimulus Aim In a DanioVision experiment, a white light stimulus is presented to zebrafish larvae. The researcher wants to compare the movement parameters of the animals in the 5 s before the onset of the stimulus, with those in the 5 s thereafter. Solution In the Data profile, create two Free intervals based on Trial Control. The first free interval goes from 5 seconds before "Action: Light on" to 0 s after start event (which is "Action: Light on"). The second free interval goes from 0 s before "Action: Light on" to 5 s after start event (which is "Action: Light on"). Connect the two Nest boxes to different Result boxes. To create an additional Result box, under Common elements click the button next to Result. See Multiple selections in a data profile. Next, in the Analysis profile choose the variable you want to calculate, for example Movement, to quantify movement in the selected periods of time. Then choose Analysis > Results > Statistics and Charts. Nesting Over a Multi Condition Aim To pick out the track segments corresponding to a Multi condition. To get an idea of what a Multi condition is, see Multi condition in the Analysis profile. You can also define complex selections by combining two or more Nesting boxes. See Multiple nesting criteria. However, there are limitations. For example, you cannot select the points when "Distance to zone was less than 10 cm" using a Nest box. However, you can do that by creating a Multi condition. Example: Select all the points in the track when (a) the subject's Body elongation state was Stretched and (b) its Distance from the zone Object was less than 10 cm. Then, create a heatmap. Procedure - In the Data Profile, under Nesting click the button next to Multi condition. - In the Multi Condition window, specify the single conditions that define the Multi condition. - Combine the conditions with either All conditions are true (AND logic) or Any condition is true (OR logic). For details, see Dependent Variables in Detail > Multi condition. - Click OK. Insert the resulting Nest box in the appropriate position between the Start and the Result box. See How to Select Track Segments. Nesting vs. Nesting Over Subjects If your trials contain multiple subjects and you want to analyze one subject in Multi condition based on the behavior of another subject, click Multi condition under Nesting over Subjects. See Nesting vs. Nesting over subjects. Notes - Note the difference: - You define a Multi condition in the Data Profile when you want to analyze any dependent variable within the resulting track segment. For example, to calculate the average velocity of the subject when a Multi condition is true. - You define a Multi condition in the Analysis Profile when you want to analyze the interval itself. For example, when you want to know the total duration of the Multi condition being true. However, you won't get, for example, the average velocity in the resulting track segment. See Free interval in the Analysis profile. Nesting Over External Data Aim To pick out the track segments and the associated external data corresponding to a specific range of values in the external data signal. Example: Select all intervals when heart rate was above a certain value. Then analyze distance moved, velocity, and movement. Procedure - In the Data profile, under Nesting, click the Add button next to [data set name] state. - Define the state variable. For details, see External data - state in the Analysis profile. - Click OK. Proceed with step 4 on How to Select Track Segments. Notes - The track segments are based on the values of external data calculated on the re-sampled signal, not the original (imported) signal. - If you have chosen the variable under Nesting over Subjects, the Actors tab is also available. Select the subjects whose state define the nesting intervals. If you select two or more subjects, select: - Any selected subject. To analyze the time that at least one subject was in that state. - All selected subjects. To analyze the time that all subjects were in that state simultaneously. Nesting Over Subjects See also: - Nesting vs. Nesting over subjects - Nesting over subjects - How to Select Track Segments --- ## EthoVision XT 19 - Analyze Track Segments - Nesting Over a Trial Control State URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-a-trial-control-state Chapter: EthoVision XT Nesting Over a Trial Control State Aim To pick out the track segments corresponding to a Trial Control state. A Trial Control state is an interval defined by two events occurred during the trial (a condition met, a sub-rule started, an action taken etc.). To learn more about Trial Control states, see Trial Control state in the Analysis profile. Example: Calculate the average velocity of the subject between the time that the light went on to the time that the pellet was given. Procedure - In the Data Profile, under Nesting click the button next to Trial Control state. - In the Trial Control State window, select the Trial Control elements that define the start and the stop of the interval to analyze. For details about how you can define a Trial Control state, see Dependent Variables in Detail > Trial Control state. - Click OK. Proceed with step 4 in How to Select Track Segments. Notes - If the Trial Control state occurs more times in your trial, like those defined with events in a subrule, there will be multiple selection intervals in one trial. You have the following options: - Select Calculate result for interval if you want to restrict your selection to just one interval, for example the first one, or the third one. Next to For consecutive intervals, enter the number of the interval (1 for the first). - Leave Calculate result for interval not selected if you want to select all the resulting intervals. Analysis is based on all those intervals merged in one. - The Actors tab in the Trial Control state window is of no use, because Trial Control states occur at the trial and arena level, independent of the subjects. You cannot assign a Trial Control state to a specific subject. Nesting Over a Free Interval With Nesting over a Free interval you can define the beginning and the end of a track segment, and analyze the dependent variables within that segment. For example, define an interval that goes from the start of the track to when the subject has explored an object for a total of 30 seconds. Then, analyze the zones that the subject visited, or calculate the average speed in that interval. - Nest over a Free Interval - Examples of Nesting over a Free Interval See also: - Free interval in the Analysis profile Nest Over a Free Interval Aim To pick out the track segments corresponding to a Free interval, i.e., the interval included between event (or time) A and event (or time) B. See Examples of Nesting over a Free Interval. Example: Analyze the mobility of the subject in the five seconds immediately following administration of a stimulus. In this example, event A is the onset of the stimulus. Event B occurs 5 seconds after A. Nesting vs. Nesting Over Subjects If your trials contain multiple subjects in the same arena and you want to analyze data of one subject based on the behavior of another subject, click Free Interval under Nesting over Subjects. See Free interval based on multiple subjects. Procedure - In the Data Profile, under Nesting click the button next to Free Interval. - In the Free Interval window, specify the criteria that define the start and stop of the interval. For details about how you can define a free interval, see Dependent Variables in Detail > Free interval. - Click OK. Insert the resulting Nest box in the appropriate position between the Start and the Result box. See How to Select Track Segments. Notes - Important: If a start criterion is not met in a track, EthoVision XT does not select any interval for that track. - The following dependent variables are not available for the definition of start/stop criteria: Activity state, Acceleration state, and the behaviors of Rat and Mouse Behavior Recognition. - Note the difference: - You define a Free Interval in the Data Profile when you want to analyze any dependent variable within the resulting track segment. For example, to calculate the average velocity of the subject in a certain track segment. - You define a Free Interval in the Analysis Profile when you want to analyze the interval itself. For example, you can calculate the duration of an interval. However, you won't get, for example, the average velocity in the resulting track segment. See Free interval in the Analysis profile. - Multiple occurrences of the interval. If the interval defined in the Data profile results in multiple occurrences within a track, you can nest over a specific interval occurrence. Select Calculate results for interval and enter the number of the occurrence. For example, 10 to nest over the 10th occurrence of the interval. Other occurrences are not used in the analysis. If you do not select Calculate results for interval, analysis is done in all occurrences merged into one result. - Nest over a Free interval based on external data. If you imported external (physiological) data, you can analyze the track segments that correspond to a free interval based on external data. For example, nest over a Free interval that goes from the track start to when Heart rate reaches 400 bpm. If you want to select the track segments between two values of external data, for example from Heart rate = 300 to Heart rate = 400, then choose Nest over external data (state) instead. --- ## EthoVision XT 19 - Analyze Track Segments - Nesting Over Activity State URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-activity-state Chapter: EthoVision XT Nesting Over Activity State Aim To pick out the data collected when the subject was in one of the states defined by the dependent variable Activity State. Example: Select all samples when the rat was inactive (freezing), and based on this selection, make a heatmap to highlight where freezing occurred. Procedure - In the Data Profile, under Nesting, click the button next to Activity state. - In the Activity State window: - Under Outlier filter, enter an Averaging interval to smooth the values of acceleration. - Under Number of states, enter how many different categories you want to split the data in. - Under Thresholds, enter the thresholds that define the various activity states. - Under Calculate nesting for, select the state that the intervals are based on. - Under State duration threshold, enter the minimal duration of the state chosen in the previous step. For details about how Activity state is calculated, see Dependent Variables in Detail > Activity State. - Click OK. Proceed with step 4 in How to Select Track Segments. Notes - You can only nest over Activity state if you selected Activity analysis in the Experiment Settings, and for experiments with one subject per arena. - If you want to select track segments based on more states (e.g., Active and Highly active), create one Nest box for each state, and combine them with OR logic. This selects the time when the subject was in one of those states (e.g., either Active or Highly active). See Basic Rules for Combining Selection Boxes. - For Activity state, it is possible to select different thresholds for nesting (see above) and for analysis (see Activity State in the Analysis Profile). You should either use the same thresholds or make the thresholds in your analysis profile more restrictive, so that the variable specified in the Analysis Profile is in effect a fine-tuning of your nesting criteria. Nesting Over Acceleration State Aim To pick out the data collected when one or more subjects were in one of the states High acceleration or Low acceleration. Example: Select the time intervals when the fish performed swim bursts (for this, use Acceleration state). Next, calculate how much time the fish was in the stimulus zone compared with the rest of the arena during those time fragments (for this, use the variable In zone). Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Acceleration state of that subject, choose Acceleration state under Nesting. See the procedure below. - To select data of a subject based on the Acceleration state of other subjects, choose Acceleration state under Nesting over Subjects. There you find the Actors tab where you can specify which subjects (Actors) were in a certain Acceleration state. See Nesting Over Subjects. Procedure - In the Data Profile, under Nesting, click the button next to Acceleration state. - In the Acceleration State window: - Under Outlier filter, enter an Averaging interval to smooth the values of acceleration. - Under Threshold, enter the threshold that defines the states High acceleration and Low acceleration. - Under Calculate nesting for, select the state that the intervals are based on. For details about how Acceleration state is calculated, see Dependent Variables in Detail > Acceleration State. - Click the Body Points tab (when available), and specify the body points that Acceleration is based on. Choose whether Acceleration state is based on all the chosen points being in the same state simultaneously (All selected points) or at least one being in that state (Any selected point). - Click OK. Proceed with step 4 in How to Select Track Segments. See Also - Nesting Over Subjects Nesting Over Body Elongation State Aim To pick out data collected when the subject was in one of the Body elongation states: Stretched, Normal, or Contracted. Example: Analyze the time that the subject spent in the zones Object and Rest of Arena when it was in the Stretched state. The aim is to test whether the subject spent more time stretched near the object than when in the rest of the arena. Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Body elongation state of that subject, choose Body elongation state under Nesting. See the procedure below. - To select data of a subject based on the Body elongation state of other subjects, choose Body elongation state under Nesting over Subjects. There you find the Actors tab where you can specify which subjects (Actors) were in a certain Body elongation state. See Nesting Over Subjects. Procedure - In the Data Profile, under Nesting, click the button next to Body elongation state. - In the Body Elongation State window: - Under Outlier filter, enter an Averaging interval to smooth the body elongation values. - Under Threshold, enter the thresholds that define the states Stretched, Normal, and Contracted. - Under Calculate nesting for, select the state that the intervals are based on. For details about how Body elongation state is calculated, see Dependent Variables in Detail > Body Elongation State. - Click OK. Proceed with step 4 in How to Select Track Segments. See Also - Nesting Over Subjects --- ## EthoVision XT 19 - Analyze Track Segments - Nesting over Behaviors of Rat/Mouse Behavior Recog URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-behaviors-of-ratmouse-behavior-recog Chapter: EthoVision XT Nesting over Behaviors of Rat/Mouse Behavior Recognition Aim To pick out the samples collected when the subject was in one or more of the behavioral states detected using the Rat or Mouse Behavior Recognition function. Example: You want to visualize where in the arena Grooming occurred. First, nest over Grooming (see the procedure below), then create heatmaps. Procedure - In the Data Profiles screen, under Nesting, click the button corresponding to the behavior you want to use to select the track segments. - In the window that appears, select the properties and which state you want to consider for nesting. Then click OK. See also Behavior Recognition in the Analysis Profile. If you want to analyze the track segments in which the behavior was not active, select Not [behavior name]. - Click OK. Proceed with step 4 in How to Select Track Segments. Options Behavior Decision Method The Behavior decision method acts as a filter that you can use to ignore samples where the behavior's probability is below a certain value. Default means that EthoVision uses the original scores (thus no filtering based on probabilities). The figure below shows the effect of Behavior decision method on the track segment selected for analysis. Top: The probability of Grooming, and another behavior plotted against time (for simplicity, other behaviors are ignored here). Bottom: When Nesting over Grooming. With Default selected, analysis is done on the samples for which the probability of Grooming exceeds the probability of any other behavior (default behavior recognition). With a set Probability > 50%, analysis is done on the samples for which the probability is higher than 50%. The higher the value, the more conservative the selection. - If you want to select the samples when a behavior probability was lower than a certain value, choose that value, then under Calculate nesting for, select Not [behavior name]. - To choose a specific probability threshold, it is best to view the per-sample values of probability for that behavior. In the Analysis profile, under Rat/Mouse Behavior Recognition select Behavior probability, and select the behavior(s) you are interested in. Choose Plot Integrated Data to see the probability values plotted against time. Notes (All Behaviors) - This nesting option is only available if you have the Rat or Mouse Behavior Recognition add-on module. - Since Hopping (mouse behavior) and Twitching are events with no duration, it is not possible to nest over those behaviors. - If you want to pick out samples based on two or more behaviors and analyze them together as if they were one (for example, Rearing unsupported and Rearing supported), click next to Merged Behavior instead. See Notes about Merged Behavior. - If you want to calculate duration of a behavior as a percentage of a track, but excluding the time scored as Unknown, make two nesting criteria, one with [behavior name] and the other with Not [behavior name] selected. Combine the resulting boxes with OR logic and then in the Analysis profile define the behavior you are interested in, and under Trial statistics choose the statistic Cumulative Duration within Nesting (%). - The Behavior duration threshold acts as a filter to ignore short transitions between states. See also Behaviors Detected with Behavior Recognition in the Analysis Profile. Notes about Merged Behavior - Nesting over Merged Behavior: When you select multiple behaviors under Merged behavior, the track segments are selected in which the subject was in one of the selected states, and then combined with OR logic. - Nesting over "Not" Merged Behavior: The Merged Behavior window does not allow you to select Not [behavior name]. If you want to select the samples when two or more behaviors were not active, make a Nesting criterion for each behavior, selecting Not [behavior name], then place the resulting Nest boxes in a linear sequence (see Basic Rules for Combining Selection Boxes). Note that the track segments are not selected when the behavior is Unknown, or when no behavior is scored in that segment (this is represented as a gap between behaviors). Nesting over Behaviors of Live Mouse Tracker Currently it is possible to select track segments based on the behavior Look of Live Mouse Tracker data. Data are selected when they occur at the same time as the chosen state. Procedure - In the Data profile, under Nesting, or Nesting over Subjects, choose Look. - Choose the state of this variable, either Look_up or Look_down. - To select data of a subject based on the Look behavior of that subject, choose Look under Nesting. - To select data of a subject based on the Look behavior of other subjects, choose Look under Nesting over Subjects. There you find the Actors tab where you can specify which subject (Actor) performed that behavior. See Nesting over Subjects. - Click OK. Proceed with step 4 in How to Select Track Segments. See Also - For an overview of Live Mouse Tracker analysis variables, see Live Mouse Tracker. --- ## EthoVision XT 19 - Analyze Track Segments - Nesting Over Body Angle State URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-body-angle-state Chapter: EthoVision XT Nesting Over Body Angle State Aim To pick out data collected when the subject was in one of the body angle states: Straight or Bent (with the Bent state which can be further split into Bent counterclockwise and Bent clockwise). Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Body angle state of that subject, choose Body angle state under Nesting. See the procedure below. - To select data of a subject based on the Body angle state of other subjects, choose Body angle state under Nesting over subjects. There you find the Actors tab where you can specify which subjects (Actors) were in a certain Body angle state. See Nesting over subjects. Procedure - In the Data Profile, under Nesting click the button next to Body angle state. - In the Body Angle State window: - Under Outlier filter, enter an Averaging interval to smooth the body angle values. - Under Threshold, enter the angle value that defines the state bent. - Under Calculate nesting for, select the Body angle state that defines the intervals. For details about how Body angle state is calculated, see Dependent Variables in Detail > Body angle state. - Click OK. Proceed with step 4 in How to select track segments. See Also - Nesting over Subjects Nesting Over Movement Aim To pick out the data collected when the subject was in one of the movement states: Moving or Not moving. Example: Calculate the average Head direction (an estimate of body orientation in fish) when the subject was Moving. Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Movement state of that subject, choose Movement under Nesting. See the procedure below. - To select data of a subject based on the Movement state of other subjects, choose Movement under Nesting over subjects. There you find the Actors tab where you can specify which subjects (Actors) were in a certain Movement state. See Nesting over subjects. Procedure - In the Data Profile, under Nesting click the button next to Movement. - In the Movement window: - Under Outlier filter, enter an Averaging interval to smooth the velocity values. - Under Threshold, enter the Start velocity and the Stop velocity that the states Not moving and Moving are based on. - Under Calculate nesting for, select the Movement state that defines the intervals. Note: The default values are an example and may not apply to your experiment. The threshold values also vary between species. If the subject is very slow, like a walking tick, you must reduce the two thresholds to detect true movement. See also Dependent Variables in Detail > Movement. - Click the Body Points tab (when available), and specify the body points that Movement is based on. Choose whether Movement is based on all the chosen points moving simultaneously (All selected points) or not (Any selected point). - Click OK. Proceed with step 4 in How to select track segments. Notes - In some cases the number of samples available for smoothing can be less than the averaging interval entered. For example, in tracks with missing samples or at the beginning of the track. In such cases EthoVision XT uses the samples available in the specified interval. See Averaging interval. - When the velocity is between the two thresholds, the current state of the subject does not change relative to the previous sample. - For Movement, it is possible to select different thresholds for nesting (see above) and for analysis (see Movement in the Analysis profile). You should either use the same thresholds or make the thresholds in your analysis profile more restrictive, so that the variable specified in the Analysis profile is in effect a fine-tuning of your nesting criteria. See Also - Nesting over Subjects --- ## EthoVision XT 19 - Analyze Track Segments - Nesting Over Latency To Zone URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-latency-to-zone Chapter: EthoVision XT Nesting Over Latency To Zone Aim To pick out the data collected before or after the subject has entered a specific zone. Example: Calculate the velocity of the subject up to when it entered a zone for the first time. Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the latency to enter a zone by that subject, choose Latency to zone under Nesting. See the procedure below. - To select data of a subject based on the latency to enter a zone by other subjects, choose Latency to zone under Nesting over Subjects. There you find the Actors tab where you can specify which subjects (Actors) entered the selected zone. See Nesting Over Subjects. Procedure - In the Data Profile, under Nesting, click the button next to Latency to zone. - In the Latency to Zone window, under Settings, next to "Latency to," choose which zone visit you want to use for your data selection. - Select the zone of interest and choose from the list at the bottom of the window whether you want to analyze the Interval before zone visit or the Interval after zone visit. - Click the Body Points tab (when available), and specify the body points that Latency is based on. Next, select one of the following: - All selected points: The data is analyzed before/after all the selected body points were simultaneously in the zone. - Any selected point: The data is analyzed before/after at least one of the selected body points entered the zone. - Click OK. Proceed with step 4 in How to Select Track Segments. Notes - If you select Latency to zone under Nesting, different subjects in the same arena are analyzed in different track segments because the nesting criterion is defined based on each subject separately. - If you select Latency to zone under Nesting over Subjects, different subjects are analyzed in the same track segments, because the nesting criterion is determined by the Actors specified and is valid for all the subjects. See Nesting Over Subjects. Nesting Over Head Directed To Zone Aim To pick out the data collected when the head of the subject (or more subjects, named Actors) is pointing to a zone or a circular area around a point. The zone or point must be defined in the Arena Settings. Example: Calculate the velocity of the subject every time it was pointing to the target zone. Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on when that subject points to a zone, choose Head directed to zone under Nesting. See the procedure below. - To select data of a subject based on when other subjects point to a zone, choose Head directed to zone under Nesting over Subjects. There you find the Actors tab where you can specify which subjects (Actors) were pointing to the selected zone. See Nesting Over Subjects. Procedure - In the Data Profile, under Nesting, click the button next to Head directed to zone. - In the Head Directed to Zone window, select: - The zone of interest (a zone or a point of interest plus a specific radius). - When to calculate the Head directed to zone state. Use this option to restrict the selection criterion (e.g., calculate Head directed to zone only when the subject was in an area around the target zone, not the entire arena). For details about how Head directed to zone is calculated, see Dependent Variables in Detail > Head Directed to Zone. - Click OK. Proceed with step 4 in How to Select Track Segments. See Also - Nesting Over Subjects Nesting Over Behavioral States Aim To pick out the data collected when the subject was in a specific behavioral state. See the following sections for information on each option: - Nesting Over Activity State - Nesting Over Acceleration State - Nesting Over Body Elongation State - Nesting Over Body Angle State - Nesting Over Movement - Nesting Over Mobility State - Nesting Over Proximity - Nesting Over Body Contact - Nesting Over Relative Movement - Nesting Over Side by Side - Nesting Over Behaviors Scored Manually - Nesting Over Behaviors of Rat/Mouse Behavior Recognition - Nesting Over Behaviors of Live Mouse Tracker Important: You may have defined thresholds during acquisition for behavioral states, like Movement, Activity State, or Mobility State in the Analysis Results and Scoring Pane. Those thresholds are not copied to Data Selection. So you have to adjust the thresholds here as well. --- ## EthoVision XT 19 - Analyze Track Segments - Nesting Over Mobility State URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-mobility-state Chapter: EthoVision XT Nesting Over Mobility State Aim To pick out data collected when the subject was in one of the Mobility states: Immobile, Mobile or Highly Mobile. Example: Calculate the average velocity for when the subject was in the state Highly mobile. Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Mobility state of that subject, choose Mobility state under Nesting. See the procedure below. - To select data of a subject based on the Mobility state of other subjects, choose Mobility state under Nesting over subjects. There you find the Actors tab where you can specify which subjects (Actors) were in a certain Mobility state. See Nesting over subjects. Procedure - In the Data Profile, under Nesting click the button next to Mobility state. - In the Mobility State window: - Under Outlier filter, enter an Averaging interval to smooth the Mobility values. - Under Threshold, enter the thresholds of the mobility variable that define the states Immobile, Mobile and Highly mobile. - Under Calculate nesting for, select the Mobility state that defines the intervals. For details about how Mobility state is calculated, see Dependent Variables in Detail > Mobility state. - Click OK. Proceed with step 4 in How to select track segments. Notes - For Mobility state, it is possible to select different thresholds when you define Mobility state in Nesting (see above) and in the Analysis profile (see Calculate statistics: procedure). You should either use the same thresholds or set the thresholds in your analysis profile more restrictive, so that the variable specified in the Analysis profile is in effect a fine-tuning of your nesting criteria. - In some cases the number of samples available for smoothing can be less than the averaging interval entered. For example, in tracks with missing samples or at the beginning of the track. In such cases EthoVision XT uses the samples available in the specified interval. See Averaging interval. - If you select Mobility state under Nesting over subjects, and you select two or more subjects in the Actors tab of the settings window, you have the following options: - To analyze the track segment when at least one of those subjects was in the selected Mobility state, choose Any selected subject. - To analyze the track segments when all the selected subjects were in the selected Mobility state simultaneously, choose All selected subjects. See Also - Nesting over Subjects Nesting Over Proximity Aim To pick out data collected when one or more subjects (Actors) were within a user-defined distance from one or more other subjects (Receivers). Example: Calculate the average mobility when the subject was in proximity of other subjects. Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Proximity behavior of that subject, choose Proximity under Nesting. In the Receivers tab you specify which subject was in proximity of the focal subject. See the procedure below. - To select data of a subject based on the Proximity behavior of other subjects, choose Proximity under Nesting over Subjects. There you find the Actors tab and the Receivers tab where you can specify which subjects (Actors) were in proximity of which other subjects (Receivers). See Nesting over subjects. Procedure - In the Data Profile, under Nesting click the button next to Proximity. - In the Proximity window, select the Proximity state that defines the intervals to analyze. - Enter the In proximity threshold and the Not in proximity threshold. - Under Calculate nesting for, choose which state defines the intervals. For details about how proximity is calculated, see Dependent Variables in Detail > Proximity. - Click the Body Points tab (when available), and specify the body points that define proximity. Choose whether proximity is based on all the chosen points being in proximity simultaneously (All selected points) or not (Any selected point). - Click OK. Proceed with step 4 in How to select track segments. See Also - Nesting over Subjects --- ## EthoVision XT 19 - Analyze Track Segments - Nesting over Relative Movement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-relative-movement Chapter: EthoVision XT Nesting over Relative Movement Aim To pick out data collected when one or more subjects (Actors) were moving to or away from one or more other subjects (Receivers). Example: Analyze the velocity when the subject was moving away from another subject. Nesting vs. Nesting over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Relative movement of that subject, choose Relative movement under Nesting. In the Receivers tab you specify which subject the focal subject was moving to/from. See the procedure below. - To select data of a subject based on the Side-by-side behavior of other subjects, choose Side by side under Nesting over Subjects. There you find the Actors tab and the Receivers tab where you can specify which subject (Actor) was moving to/from which other subjects (Receivers). See Nesting over Subjects. Procedure - In the Data Profile, under Nesting click the button next to Relative movement. - In the Relative Movement window: - Enter the Maximum interaction distance. - Enter the Minimum velocity that defines movement. - Under Calculate nesting for, choose the state that defines the intervals. For details about how Relative movement is calculated, see Dependent Variables in Detail > Relative movement. - Click the Body Points tab (when available), and specify the body points that define movement. Choose whether movement is based on all body points moving simultaneously (All selected points) or not (Any selected point). - Click OK. Proceed with step 4 in How to Select Track Segments. Notes On the Receivers tab: - To select the samples when one subject moves to the other, select both Subject 1 and Subject 2, and choose Any selected subject from the list. - To select the samples when one specific (focal) subject moves toward other subjects simultaneously, do not select the focal subject under Receivers. Select all the other subjects and choose All selected subjects from the list. See Also - Nesting over Subjects - Dependent Variables in Detail > Relative Movement Nesting over Behaviors Scored Manually Aim To pick out the track segments in which a behavior was scored manually. To learn more about manually scoring behaviors, see Manual Scoring Settings and Score Behaviors Manually During Acquisition. Example: You manually scored freezing behavior, and you want to visualize where in the arena it occurred during the trial. First, nest over the manually-scored behavior Freezing (see below for the procedure), then create the heatmaps. Nesting vs. Nesting over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the behavior of that subject, choose that behavior under Nesting. See the procedure below. - To select data of a subject based on the behavior of other subjects, choose that behavior under Nesting over Subjects. There you find the Actors tab where you can specify which subject (Actor) was performing that behavior. See Nesting over Subjects. Procedure - In the Data Profile, under Nesting click the button next to the behavior's name, or the group of behaviors it belongs to. - In the window that appears, select the behavior and click OK. If you want to analyze the track segments in which the behavior was not active, select Not [behavior name]. - Click OK. Proceed with step 4 in How to Select Track Segments. Notes - If the behavior is part of a mutually-exclusive group, under Nesting you see the name of the group, not the individual behavior. - If you select a behavior from a mutually-exclusive group, the other behaviors of the same group are automatically left out of analysis and visualization. --- ## EthoVision XT 19 - Analyze Track Segments - Nesting Over Side by Side URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-side-by-side Chapter: EthoVision XT Nesting Over Side by Side Aim To pick out data occurring when two subjects were side by side within a proximity threshold distance. Example: Calculate the average velocity of the subject when it was side-by-side with another subject, pointing to the same direction. Nesting vs. Nesting Over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on the Side-by-side behavior of that subject, choose Side by side under Nesting. In the Receivers tab you specify which subject was side-by-side with the focal subject. See the procedure below. - To select data of a subject based on the Side-by-side behavior of other subjects, choose Side by side under Nesting over Subjects. There you find the Actors tab and the Receivers tab where you can specify which subject (Actor) was side by side with which other subjects (Receivers). See Nesting over subjects. Procedure - In the Data Profile, under Nesting click the button next to Side by side. - In the Side by side window, either enter the proximity threshold distance or accept the default value (see notes below for details). - Under Calculate nesting for, choose which state of the Side by side variable defines your selection: either Side by side, same direction or Side by side, opposite direction. For details about the Side by side variable, see Dependent Variables in Detail > Social > Side by side. - Click the Receivers tab and select which subjects should be in proximity with the focal subject. - Click OK. Proceed with step 4 in How to select track segments. Notes - The default proximity threshold distance is 5.26 cm. This corresponds to the threshold used in Live Mouse Tracker, that is, 2 x 15 = 30 pixels, where 15 is the original value of MAX_DISTANCE_HEAD_HEAD_GENITAL_THRESHOLD in Live Mouse Tracker, and the scale factor for converting pixels to cm is 10/57. - If you select multiple subjects A, B, etc. in the Receivers tab, and select the option All selected subjects, then the track segments are selected when the focal subject was side by side with A, B, etc. simultaneously. That may not occur often. Instead, select Any selected subject if you want to analyze the track segments when the focal subject was side by side either with A, or B, etc. See Also - Nesting over Proximity - Nesting over Subjects Nesting over Body Contact Aim To pick out the track segments corresponding to when one subject was in contact or not in contact with another subject. Nesting vs. Nesting over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on that subject being in contact with any other subject, choose Body contact under Nesting. In the Receivers tab specify which subject was in contact with the focal subject. See the procedure below. - To select data of a subject based on when other subjects were in contact with any subject, choose Body contact under Nesting over Subjects. There you find the Actors tab where you can specify which subjects were in contact with any other subject. See the notes below and also Nesting over Subjects. Procedure - In the Data Profile, under Nesting click the button next to Body contact. - In the Body contact window, select the state that defines the intervals to analyze. For details on how Body contact is calculated, see Dependent Variables in Detail > Body contact. - Click OK. Proceed with step 4 in How to Select Track Segments. Notes - You can nest over "No contact" to filter out all the instances of body contact. For example, if contact situations result in subject identity swaps or nose-tail swaps. - If you select Body contact under Nesting over Subjects, the Actors tab is also available. The track segments are selected based on the Body contact of the Actors. For example, if the arena contains three subjects and in the Actors tab you select Subject 1 and Subject 3, the data are selected when both Subject 1 and 3 are in contact with any subject, or when at least one of them is in contact with any other subject. For details and examples, see Nesting over Subjects. With Nesting over Subjects, you cannot specify body contact between two specific subjects. If you select Subject 1 and Subject 3 in the Actors tab, you will not get the track segments when those two subjects are in contact. Instead, you get the track segments when, depending on the options you choose, both subjects (or at least one) are in contact with any subject. --- ## EthoVision XT 19 - Analyze Track Segments - Nesting over Time URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-over-time Chapter: EthoVision XT Nesting over Time Aim To pick out the samples in one time interval, from time tstart to time tend. Procedure - In the Data Profile, under Nesting, click the button next to Time. Note that choosing Time under Nesting over Subjects leads to the same data selection. - In the Time window, enter the Interval start and Interval end: - Relative time is the time since the start of the track. Enter the relative time. In EthoVision XT 17.5 and later, you can specify any time within the trial, even after 24 hours. - Track start / Track end mark the start and end of each track, respectively. Therefore, they may mean different relative times between tracks. - Complete the procedure from step 4 in How to Select Track Segments. Examples - To analyze the first 10 minutes of each track, set Interval start to 0:00:00.000 and Interval end to 0:10:00.000. - To analyze from 10 minutes to the end of each track, set Interval start to 0:10:00.000 and Interval end to Track end. Notes - Time intervals are applied in each track independently. - Default: Interval start 0:00:00.000 (h:mm:ss.fff), Interval end 0:00:30.000. - 0:00:00.000 represents the time that tracking started for that arena. With multiple arenas, tracks may actually start at different times within the same trial. - If you want to split the data in regular intervals (for example, a one-hour recording in six 10-minute intervals), do not nest over time. Instead, in the Data profile choose Results per Time Bin. - Tip: If you want to select a track segment that lasts some time relative to an event (for example, select the 10 seconds after the presentation of a stimulus, or select up to when an object is explored for 1 minute), then choose Free Interval instead. See Nesting over a Free Interval. - When working with multiple arenas, if you apply Trial Control with Start and Stop conditions for each arena separately, actual data recording may start and stop at different times in each arena. For example, if tracking started automatically as soon as the animal was detected, and the mouse in Arena 1 was released earlier than in Arena 2, tracking started earlier in Arena 1. When nesting over time and selecting the first minute of each track, the two track segments may not overlap completely on the timeline. - When working with multiple subjects per arena, tracking starts at the same time for all subjects within an arena. Therefore, nesting over time results in the same interval being selected for all subjects. Note that tracking starts for all subjects even when one has not been released yet, in which case the track for that subject begins with missing samples. Nesting Using Zones Nesting over In Zone Aim To pick out the data collected when one or more subjects were in a specific zone, or in a combination of zones. Nesting over In Zone is only necessary when you want to analyze track segments by combining zones or subjects. If you simply want to calculate statistics of distance, velocity, etc. for each zone without combining subjects or zones, see Calculate the Results per Zone. Nesting vs. Nesting over Subjects Notice the difference when there are multiple subjects in the same arena: - To select data of a subject based on that subject being in specific zones, choose In Zone under Nesting. See also item B in Nesting vs. Nesting over Subjects. - To select data of a subject based on other subjects being in specific zones, choose In Zone under Nesting over Subjects. There you find the Actors tab where you can specify which subjects (Actors) were in the selected zone(s). See items C and D in Nesting vs. Nesting over Subjects, and the procedure in Nesting over Subjects. Procedure - In the Data Profile, under Nesting, click the button next to In Zone. - In the In Zone window, under In the Following Zones, deselect Arena and select the zones in which the animal must be. - Choose the remaining options to specify which combination of zones (any, all, not in any) and body points. For explanation, see Dependent Variables in Detail > In Zone. - Click OK. Proceed with step 4 in How to Select Track Segments. Notes - If your experiment is set to Only Center-Point Detection, the From Following Body Points options are not available. Calculations are based on the center-point of the body. - Select When in All Selected Zones only when the zones are overlapping at least partially (for example, North Quadrant and Center of an open field). Nesting Over Zones When two zones are not overlapping, selecting "When in all selected zones" results in no data being selected, because a body point can never be in two different locations at the same time. Application Examples Example 1: A Center zone has been defined in an open field. When you do Nesting and choose Center under "In the following zones," the samples in the center of the open field are selected for analysis. When you visualize the track, selected samples are displayed in bright colors; non-selected samples are dimmed out. Example 2: For the same open field as above, but when also tracking the nose and tail-base points, if you select the three body points and select "All selected points" from the list, a sample is only selected when the three body points are within the Center zone. In the example below, the tail-base is outside the Center zone (highlighted in yellow). Therefore, that sample is not selected for analysis. --- ## EthoVision XT 19 - Analyze Track Segments - Nesting vs. Nesting over Subjects URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-analyze-track-segments-nesting-vs-nesting-over-subjects Chapter: EthoVision XT Nesting vs. Nesting over Subjects Aim To select track segments based on the behavior of one or more subjects. In experiments with multiple animals per arena, the Data profile offers two types of nesting options. Prerequisite - You have the Social Interaction Module. Nesting To analyze the track segments of a subject based on that subject's behavior, choose an option under Nesting, and follow the procedure on How to Select Track Segments. Result: Each subject will be analyzed in different track segments (intervals), according to its own behavior (see B in the figure below). Nesting over Subjects To analyze the track segments of a subject based on the behavior of a specific subject (or combination of subjects, called Actors), choose an option under Nesting over Subjects, and select the Actors. Result: Within the same arena, subjects will be analyzed in equal track segments, according to the behavior of the Actors (see C and D in the figure below). Notes - Arenas are independent replicates. Therefore, nesting intervals are applied to each arena separately depending on the state of their subjects. - Selecting Time under Nesting or Nesting over Subjects makes no difference, because within one arena the tracks of multiple subjects start at the same time. Effect of Nesting in One Arena with Three Animals Dotted lines: tracks. Black bars: time intervals when a behavioral state or Trial Control state is active (for example: In zone for the variable In zone, or Highly mobile for Mobility). White bars: data selected for analysis. A: Original data. B: Results of Nesting. Track segments are selected according to the state of the corresponding subject. C: Results of Nesting over Subjects, with one subject selected in the Actors tab. D: Results of Nesting over Subjects, with two or more subjects selected in the Actors tab. For reasons of space, the combinations "Any/All of Subjects 1 and 3" and "Any/All of Subjects 2 and 3" are not displayed. Nesting over Subjects Aim To analyze the track segments of a subject based on the behavior of a specific subject or combination of subjects, called Actors. This option is only available if you track two or more subjects simultaneously in the same arena. Procedure - In the Data profile, choose the variable under Nesting over Subjects. - Click the Actors tab of the nesting window. - Select the actors of the behavior defining the interval. Select the subject that should show the behavior of interest. If you select two or more subjects in the Actors tab, select one of the two options from the list immediately below the Subjects box: - All selected subjects: To analyze the samples when all the actors show that behavior simultaneously. - Any selected subject: To analyze the samples when at least one actor shows that behavior. - If the Actors tab also contains the Body points options, select one or more body points of the subjects selected above. - For the dependent variables of social interaction, a Receivers tab is also available. Receivers are the subjects towards which the behavior of the Actor is directed. For example: - To analyze when Subject 2 is moving to Subject 1, Subject 2 is the Actor and Subject 1 is the Receiver. - To analyze when Subject 1 is in proximity of Subject 2, Subject 1 is the Actor and Subject 2 is the Receiver. Click the Receivers tab and select the subjects that you want to define as Receivers. - Click OK. Proceed with step 4 in How to Select Track Segments. Important: Be careful when selecting the same subject under Actors and Receivers. In such a case you may also get unwanted selections, for example Subject 1's nose point (Actor) In proximity of Subject 1's tail base (Receiver). The resulting selection has little meaning. Examples - Social interactions. You want to analyze the time that the nose-point of Subject 1 was in proximity of the tail-base point of Subject 2 (ano-genital sniffing). Solution: Subject 1 is Actor, Subject 2 is Receiver. - Under Nesting over Subjects, click the button next to Proximity. - In the Actors tab select Subject 1 and deselect Subject 2. Under Body points, select Nose-point only. - In the Receivers tab select Subject 2 and deselect Subject 1. Under Body points, select Tail-base point only. If you want to select the time that the nose point of Subject 1 was in proximity of the tail-base point of Subject 2, or vice versa, create two nesting boxes, one that specifies Subject 1's nose in proximity of Subject 2's tail base, and the other that specifies Subject 2's nose in proximity of Subject 1's tail base. Next, combine the two boxes with OR logic (see Basic Rules for Combining Selection Boxes). - One Actor, no Receivers. You want to select the track segments when Subject 2 was moving, and quantify the distance moved by other subjects in that period of time. Solution: Subject 2 is the Actor. Under Nesting over Subjects, click the button next to Movement. - In the Actors tab select Subject 2 and deselect the other subjects. - In the Analysis profile, select Distance moved. The statistics results refer to each subject in the specified interval. Results per Time Bin Aim To split tracks into segments of equal duration. You can then show results for each time bin. Time bins are different from Nesting over time. Procedure - In the Data profile, click the Settings button on the Result box. If your data profile contains more Result boxes, open the one corresponding to the data you want to be split in time bins. - In the Result Settings window, select Results per time bin. Source: EthoVision XT 19 Help - Analyze Track Segments, Noldus Information Technology --- ## EthoVision XT 19 - Angular velocity URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-angular-velocity Chapter: EthoVision XT Definition The change in direction of movement of the nose, center, tail-base point or Head direction line between two consecutive samples, calculated per unit time. Angular velocity is expressed in degrees/second (°/s) and can be either positive or negative (see below). Calculation Where: - RAVk is the Relative Angular velocity for sample k. - RTAk is the Relative Turn Angle for sample k. - tk-tk-1 is the time difference between the current and the previous sample. Angular velocity can be calculated based on body points or the Head direction line: - Based on body points: The angular velocity is calculated from the turn angle of the specified body point (nose, center or tail-base; see below). - Based on Head direction: The angular velocity is calculated from the turn angle based on Head direction. IMPORTANT: Note that calculating Angular velocity from Head direction is not the same as calculating it from the nose-point. This is because Turn angle (and therefore Angular velocity) at sample k based on a body point depends on the last three samples k–2, k–1 and k, while Turn angle based on Head direction depends only on the samples k–1 and k. Range The minimum and maximum angular velocity depend on the time between two samples. For example, if the sample rate is 25, the maximum attainable turn (+180°, see Turn angle) results in an angular velocity of 180/0.04 = 4500°/s. Absolute vs. Relative Angular Velocity - Absolute Angular velocity: The rate of change in direction is unsigned. Also known as Turning rate. - Relative Angular velocity: The rate of change in direction is signed. Depending on the orientation of the x- and y-axes, a clockwise turn is scored as positive or negative value, a counterclockwise turn is scored with opposite sign (see the relative Turn angle). Turn bias (degrees/s) and circling tendency are synonyms for this variable. The difference between relative and absolute Angular velocity is best explained by looking at the mean values of the two dependent variables. The mean absolute Angular velocity reflects the amount of turning, whereas the mean relative Angular velocity gives a better indication of the overall direction of turning. How to Specify Angular Velocity - Click the Add button next to Angular velocity and click the Angular velocity tab. Select Absolute or Relative. - Select Head direction angular velocity (body point is ignored) if you want to calculate angular velocity based on head direction. - Click the Body points tab. Select the body points for which you want to calculate the velocity. By default, Center-point is selected. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If your experiment is set to Only center-point detection or Color marker tracking, the Body points tab is absent. Calculations are based on the center point. - If the body point turns more than 180° between one sample and the next, the direction of turning is calculated incorrectly. For example, if the subject makes a fast counterclockwise turn of 270° between two samples, the program interprets this as a 90° clockwise turn. As a result, Angular velocity gets a value smaller than expected, and in the case of relative Angular velocity, a false sign. This kind of error occurs when the sample rate is too low and the subject makes very fast turns. To prevent this kind of error, set the sample rate at such a level that it is practically impossible for the subject to make a turn more than 180° between two subsequent samples. - The Head direction line is calculated using the subject's contour. However, if you swap nose- and tail-base points, or interpolate those two points, the Head direction line is not recalculated using the contour; instead it is calculated as the prolongation of the segment joining the nose-point and the center-point. Angular velocity is then calculated based on those head direction lines. Applications - The absolute Angular velocity is used to express the amount of turning per unit time. Generally, a high value of this dependent variable is associated with local search, for instance in response to non-volatile semiochemicals (Bell (1991) Searching Behaviour: The Behavioural Ecology of Finding Resources. London: Chapman & Hall). - The relative Angular velocity measures the speed of change in direction of movement. The mean of this dependent variable can be used to assess turn bias or circular tendency, the tendency of a subject to turn to a specific direction. Studying this helps detecting peculiarities or abnormalities of behavior (for instance, stereotypic movements, reaction to toxic substances, etc.). Body Angle Definition The angle formed by the prolongation of the segment joining the tail-base and the center-point, and the segment joining the center-point and the nose-point, calculated at the current sample. Range Absolute Body angle ranges from 0° to 180°. Relative Body angle ranges from -180° to +180°. 0° occurs when the nose point, center point and tail base point are aligned. Values around ±180° are only hypothetical, because they would imply that the animal is completely curled up in such a way that the nose points to the tail base. Values higher than 100° often occur with wrong detection of the body points. How to Specify Body Angle - Click the Add button next to Body angle. - In the Body Angle tab, specify whether you want to calculate: - Absolute angle: The unsigned angle. - Relative angle: The signed angle. It is negative when the body is bent to the right (clockwise); positive when the body is bent to the left (counterclockwise). - Complete the procedure to add the variable. See Calculate statistics: procedure. Note When the nose-point and the tail-base point are swapped, and these are not properly corrected in the Track Editor, the value of relative body angle is opposite to what it should be. For example, if the actual body angle is +10°, EthoVision XT gives -10°. However, absolute angle remains correct. Therefore, if your track contains nose-tail base swaps, either correct them in the Track Editor, or use Absolute angle. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Arena Settings - Adjust the Video Aspect Ratio URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-adjust-the-video-aspect-ratio Chapter: EthoVision XT Adjust the Video Aspect Ratio Aim To correct for image distortion that sometimes occurs when recording video from analog cameras. Prerequisites - You are tracking from pre-recorded video files. - You know that the aspect ratio in the video file differs from that of the original camera image. Procedure - Open the Arena Settings. - Click the Adjust Aspect Ratio button. - Choose the option based on the software and hardware you used, then click OK. Source: EthoVision XT 19 Help - Arena Settings, Noldus Information Technology --- ## EthoVision XT 19 - Arena Settings - Calibrate the Arena URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-calibrate-the-arena Chapter: EthoVision XT Calibrate the Arena Aim To convert the subject's coordinates expressed in pixels to real-world coordinates. Avoid barrel and spherical distortion by using correct lenses. Place the camera above the middle of the arena, and perpendicular to the arena surface. If you use Track3D, do not perform calibration within EthoVision XT; instead, make sure that you set Pixel calibration to ON. Prerequisites - You grabbed a background image. - You know the real-world size of the arena. Measure this distance at the height of the animal, not at the top of the arena. Procedure - In the Arenas and Zones section, click 1. Draw Scale to Calibrate. - Click the mouse button on the first point in the video image, hold the button down, and drag to the second point in the image. Then release the mouse button. - In the Calibration Distance window, type in the real-world distance between the two points. Notes - Repeat the steps above for all calibration lines. EthoVision XT uses the average of the scale factors obtained from each calibration line. This factor is used to analyze movement of the subject in all directions. Draw calibration lines in both directions, horizontal and vertical. - For each calibration line, EthoVision XT calculates a scale factor (real-world distance entered divided by the length of the line in pixels). If this factor differs by more than 20% from the average of the other lines, a message is shown: "Calibration scale substantially larger or smaller than other existing calibration scales." Click No to edit the real-world distance, or click No and then Cancel to re-draw the last calibration line. Click Yes to accept the value. Be aware that very different scale factors may produce false results. - If you enter a real-world distance smaller than 10 mm or greater than 10 m, a message is shown. Click Yes to confirm the value or No to edit it. - If you have clicked Cancel and want to repeat the calibration procedure, click again 1. Draw Scale to Calibrate. Calibrating with the Noldus Calibration Card - Open the Grab Background Image dialogue (also accessible via Arena Settings > Arenas and Zones > right-click on Background > Grab Background Image). - Place the Noldus Calibration Card in view inside the arena. Make sure that the black rectangular outline within the card is clearly visible in the camera view. If you are using a dark arena, you can place a piece of white paper behind the card. - Click Calibrate. The Calibration dialogue will open. - Click Calibrate to accept or decline the result. - If calibration using the Noldus Calibration Card fails, you can use the manual calibration procedure described above. Draw the Arena Aim To define an area of interest so that EthoVision XT ignores all activity outside this area, so only movement inside the arena is tracked. With multiple arenas within one video image, you can track more animals simultaneously and separately. Each arena is an independent replicate. Prerequisites - You have calibrated the video image. Procedure - Click 2. Select Shape and Draw Arena in the Arenas and Zones section. When working with multiple arenas, click the layer for the arena you want to draw. - Select a shape on the Arena Settings toolbar at the top of the window by clicking it or by pressing the corresponding shortcut key. To split an arena into quadrants automatically (for example, in a Morris water maze or an open field), choose Create Subdivided 3-Point Circle or Create Subdivided Rectangle. - Create a shape that covers the region on the screen in which you want EthoVision XT to track the subject. Make sure the arrow point of the arena label is inside the shape you just created. Arena Settings Add Subdivided Arena If you have chosen one of the subdivided options, the Add Subdivided Circle (or Rectangle) window appears. - For circular arenas, enter the number of sectors (for example, 4 for quadrants in a Morris water maze). Default = 2, maximum = 50. - For rectangular arenas, enter the number of rows and columns. A total of rows x columns equal zones will be defined. In the Arenas and Zones section, a new zone group named Subdivision Zones is added, listing the new zones. Notes - If you do not draw an outline, the whole background image is considered as the arena. - If you have multiple arenas with the same size and shape, you do not have to draw each arena separately. You just draw one arena and duplicate it. - The shape is filled with the color visible next to the arena name in the Arenas and Zones section. To change this color, click the color next to the name. - To create a circle or a square, select the Ellipse or Rectangle tool respectively, and hold Shift down while you draw the shape. - To export the image of the arena, click the camera button on the toolbar. Give the export file a name and select a picture format (*.png, *.jpg, *.bmp, *.gif). The image contains all layers that are currently visible. - For an experiment in DanioVision mode, EthoVision XT can detect the arenas automatically. See the DanioVision DVOC-0041 Reference Manual. - You cannot delete an arena that has been used for acquisition; it has become read-only. To edit it for future tracks, duplicate the arena, edit the copy, and use these settings for acquisition. Make a Subdivided Arena When you draw an arena using the subdivided tools, note the following: If the Auto-Label Zone is active, all sectors are automatically defined as zones and labeled with S1, S2, etc. A layer named Subdivision is added in the Arenas and Zones section together with its zones. When the Auto-Label Zone is active, the Auto-Label Zone button is highlighted in orange. If the Auto-Label Zone button is not highlighted, the arena is still divided in sectors, but the resulting zones are not labeled. Click the Add Zone Label button to label the zones. To activate or deactivate Auto-Label Zone, click 3. Select Shape and Draw Zones (Optional) in the Arenas and Zones section and click the Auto-Label Zone button. --- ## EthoVision XT 19 - Arena Settings - Cumulative Zones URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-cumulative-zones Chapter: EthoVision XT Cumulative Zones Analyze two or more zones as one. The procedure below creates a cumulative zone using two or more existing zones. The original zones are not deleted; the cumulative zone is added as a new zone, outside the original zone group. For example, in an Elevated Plus Maze test, if you have defined two open arms and two closed arms, you can define the two open arms as cumulative zone Open Arms, and the two closed arms as cumulative zone Closed Arms. You can add zones from different zone groups to a cumulative zone. Procedure - In the Arenas and Zones section, click a zone group in which you want to create a cumulative zone. - Click the Add Cumulative Zone button at the bottom of the Arenas and Zones section. - In the Add Cumulative Zone window, choose one of the following options: - Create New Cumulative Zone: Type in the name of the new cumulative zone, click OK, and select the zones in the window that appears. - Use Existing Cumulative Zone: From the drop-down list, choose the name of an existing cumulative zone in another Arena Settings profile. Duplicate a Cumulative Zone Use the option Use Existing Cumulative Zone to replicate a cumulative zone that was defined in another Arena Settings profile and include it in a new Arena Settings. Make sure that all the zones that make up the existing cumulative zone are also defined in the new Arena Settings. For example, in a radial-arm maze test, four zones can be either baited or not baited. In some trials zones 1 and 3 are baited; in other trials zones 2 and 4 are baited. - In Arena Settings 1, define all zones. Next, define a cumulative zone Baited with zones 1 and 3. You can double-click the label Cumulative Zone 1 and rename it to Baited. - Create a new Arena Settings (or duplicate Arena Settings 1). Make sure all relevant zones are defined. - Swap the labels for the zones. - If you created Arena Settings 2 anew, create a cumulative zone and choose Use Existing Cumulative Zone. Choose the existing cumulative zone from Arena Settings 1. If you have duplicated Arena Settings 1 to obtain Arena Settings 2, the cumulative zone is already pointing to the correct zones after you swap the labels. Note that the same physical zone is labeled with different names in the two Arena Settings profiles; take this into account when you analyze single zones. Important: Do not rename the cumulative zone in Arena Settings 2 when it is pointing to physical zones other than those in Arena Settings 1. If you do so, the name also changes in Arena Settings 1, which would create confusion. Notes - A cumulative zone is not the same as a zone group. A zone group is one of the layers in the Arena Settings, where zones are always analyzed separately. A cumulative zone is an extra zone, outside the zone group it originates from. For example, zones S2 and S3 can form Cumulative Zone 1. Shelters and Other Hidden Zones Hidden Zones and Entry Zones You can define a shelter or any zone where the animal is out of view as a Hidden zone. After you have defined a hidden zone, you must define at least one Entry zone for that hidden zone. The entry zone is used to determine whether the animal has entered or left the hidden zone. Entering a Hidden Zone Suppose you have a square shelter defined as hidden zone and an entry zone on the side of the shelter where the animal can enter it. When the animal enters the entry zone, one or more body points are tracked in that zone. As soon as a body point is not detected anymore, that body point is assumed to have entered the hidden zone and this body point is positioned in the center of the hidden zone during the time the animal is inside the shelter. Leaving a Hidden Zone By default, the animal is considered to have left the shelter when it is next detected, that is, when its body points are "not missing". However, every time an animal pokes its nose out, this may be recorded as an exit. Subsequently, retracting back into the shelter without ever really leaving the shelter would count as entering again. This results in an overestimation of how often the animal enters and exits the hidden zone. Therefore, EthoVision XT versions 5.1 and up have the possibility to also use the entry zone as leaving zone. The animal is then considered to have left the hidden zone when it was first considered to be in a hidden zone, and subsequently detected outside of the entry zone. In other words, the exit is counted only when the body point crosses the border between the entry zone and the rest of the arena. We recommend you use this function if you want to prevent an overestimation of entrances into, and exits from, the hidden zone. If the animal's center point is first detected in the entry zone, and then disappears because the apparent size of the animal becomes smaller than the minimum size set in Detection Settings, then the animal is considered to be in the shelter. The detection for exiting the hidden zone differs depending on whether you use the entry zone as a leaving zone: - Without using the entry zone as a leaving zone, the subject is detected as having left the hidden zone as soon as the minimum subject size is detected anywhere within the arena. Depending on the minimum size set, only poking out the nose could count as "exiting". - When using the entry zone as a leaving zone, the subject is detected outside the hidden zone, but will only be recognized as "out of the hidden zone" as soon as it crosses the border of the entry zone into the rest of the arena. Define a Hidden Zone - At the bottom of the Arenas and Zones section, click the Add Hidden Zone Group button. - Create a zone covering the area you want to define as a hidden zone. If the Auto-label zones option is switched on, the zone is automatically named Hidden Zone 1. Right-click the name to rename it. If the auto-label option is switched off, click the Add Zone Label button on the toolbar, click the zone, and rename the zone. Note: If a hidden zone is included in a larger, overlapping zone, the time spent in the hidden zone is not included in the results for the larger zone. See the note under the topic In Zone. --- ## EthoVision XT 19 - Arena Settings - Define an Entry Zone URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-define-an-entry-zone Chapter: EthoVision XT Define an Entry Zone Aim To define a region of the arena where the subject must be immediately before moving into the hidden zone and disappearing from view. It is important that at least one sampled location of the subject's body point is found in the entry zone for the subject to be considered in the hidden zone. Otherwise, the subject is considered missing. Make the entry zone large enough. Prerequisites You have defined a Hidden zone. See Shelters and Other Hidden Zones. To Define an Entry Zone - In the Arenas and Zones section, select the Entry Zone Group row. - Draw a zone that covers the area, overlapping the hidden zone, to define as an entry zone. The size of the entry zone is critical; it must be wide enough, but not too wide, so that: - When entering: the subject never goes straight away from the area outside the entry zone to the hidden zone. There should be at least one instance of the subject's body point within the entry zone before disappearing from view. If necessary, increase your sample rate to make sure that this happens. - When exiting: the subject's body point is far, but not too far from the hidden zone when it crosses the entry zone border to the rest of the arena, just enough for it to be considered as having left the hidden zone. This only applies if you select Use This Entry Zone Also as Leaving Zone. You can use the Integrated Visualization to help you set the right size. - If the Auto-label zone option is activated, the Add Entry Zone window opens. If the auto-label option is switched off, click the Add Zone Label button on the toolbar and click the zone to open the Add Entry Zone window. - In the Add Entry Zone window, link this entry zone to the appropriate hidden zone by selecting the Link box under Linked Hidden Zone. You can link more than one entry zone to a hidden zone, but you cannot link more than one hidden zone to an entry zone. - If you want to define the entry zone also as a leaving zone, select the check box for Use This Entry Zone Also as Leaving Zone. This will be applied to all hidden zones in your Arena Settings. Each entry zone will also be used as a leaving zone for the hidden zone associated with it. - Click OK to assign the label to the entry zone. Notes: - To display the hidden zone while drawing the entry zone, in the Arenas and Zones section, select the check box in the View column of the Hidden Zone Group row, next to the Color column. - If you have multiple arenas, create hidden zones and entry zones in the first arena first, then duplicate that arena and its contents. See Duplicate an Arena. To Link a Hidden Zone to an Entry Zone If you did not link an entry zone to its hidden zone when you defined the hidden zone, you can do one of the following: - In the video image, right-click the hidden zone label or right-click the hidden zone row in the Arena Settings window. Select Link Entry Zones and select the Link check box of the appropriate entry zone in the Links to Entry Zones window. - In the video image, right-click the entry zone label, or right-click the entry zone row in the Arena Settings window. Select Link Hidden Zones and select the Link check box of the appropriate hidden zone in the Link to Hidden Zone window. Change the Hidden Zone Subject Coordinates Aim To specify the coordinates of the subject when it is in the hidden zone. When a subject enters a hidden zone, its body points are assumed to be in the center of the hidden zone. However, if you have a very large hidden zone, the distance the subject moves from the entry zone to the center of the hidden zone every time it enters the hidden zone contributes rather significantly to Distance Moved. In these cases, you can move the coordinates of the subject near the entry zone. Prerequisites You have defined a hidden zone. See Shelters and Other Hidden Zones. To Set the Hidden Zone Subject Coordinates - Right-click the hidden zone label and select Hidden Subject Coordinates. - Select one of two options to set the hidden subject coordinates: - Center of the Zone, unless the center is outside the zone, in which case it is the arrow tip location. Select this option when you have a small hidden zone. - Arrow Tip Location. Select this option when you have a large hidden zone, to minimize the contribution to Distance Moved. --- ## EthoVision XT 19 - Arena Settings - Define Zones URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-define-zones Chapter: EthoVision XT Define Zones Define specific regions of the arena to be used in analysis or to start and stop tracking. Any area falling outside the arena is not considered as a zone. Prerequisite - You have defined the arena. Procedure for One Zone - Click 3. Select Shape and Draw Zones (Optional) in the Arenas and Zones section. If multiple zone groups are defined, click the zone group where you want to insert the zone. This group is highlighted in the background image. - Select a shape from the toolbar. - Create a shape that covers the area of interest within the arena. Do so at the height of the animal, not at the top of the cage. If you choose one of the subdivided options, select the number of sectors or rows x columns and click OK. - In the Add Zone Label window that appears, enter the name of the zone or accept the suggested name, then click OK. When you have multiple arenas and want to give the same name to a zone defined in each arena (for example, the Feeder in multiple PhenoTypers), select Use Existing Zone and choose the zone name. Notes - The zone shape is filled with the color visible next to the zone name in the Arenas and Zones section. Click the color next to the name to change it. - To create quadrants in an existing arena, draw two perpendicular lines over the arena. Click the Add Zone Label button and drag the label to one quadrant. Repeat this step for each quadrant. Auto-Label Zone By default, the Auto-Label Zones option is turned on (the Auto-Label Zone button on the toolbar is highlighted in orange). This means that every time you draw a closed shape, the zone label is added automatically. To switch the auto-label option off, click the Auto-Label Zone button on the toolbar or press A. If the auto-label option is off (the button is not highlighted in orange) and the zone has no name, click the Add Zone Label button on the toolbar, drag the label to the zone, then click the mouse button. Name the zone and click OK. Edit a Zone You can resize and re-shape the zone using the Work with Shapes tools. Organize the Zones in Your Arena Zone Groups Zones are organized in zone groups. You can add an unlimited number of zone groups to each arena. Within one zone group, zones must be non-overlapping. If zones within a zone group are overlapping, the overlapping area is excluded from both zones. Zones That Do Not Overlap If two or more zones do not overlap, like the quadrants of a Morris water maze, define them in the same zone group. To create a new zone group, select the arena and then click the Add Zone Group button in the lower part of the Arena Settings window. You cannot edit zone groups that contain zones that have been used in Trial Control (for example, to start tracking when the animal is detected in that zone) or have been used as hidden or entry zones. However, you can add new zone groups and add zones there. These zones can then be used, for example, for analysis. Zones That Do Overlap If you want to define zones that overlap, define them in separate zone groups or use cumulative zones. For example, in a circular open-field, you may want two circular zones (Center and Border) and four quadrant zones (NW, NE, SW, SE). Create two zone groups: one with the two circular zones, and one with the four quadrant zones. Draw a Point Define a reference point, for example to calculate the average distance of the subject to the point, or the heading angle. Procedure - In the Arenas and Zones section, select the zone group in which you want to add one or more points. - Click the Add Point button on the toolbar. - Click the background image to position the point. Note that you can also position a point outside the arena. - In the Add Point window, enter the point name and click OK. Validate the Arena Settings Check that the Arena Settings are consistent after defining all arenas and zones. This includes verifying that the arena is calibrated, that multiple arenas do not overlap, and that all zones are inside the arena. Procedure - Click the 4. Validate Arena Setup button in the Arenas and Zones section. If arenas and zones are created correctly, a message will be shown that Arena Settings are valid. If not, an error message appears. More About Zones Copy a Zone To Copy a Zone Within the Same Arena - Right-click the shape and select Duplicate. - In the Duplicate window, enter an Enlargement factor and click OK. To Copy a Zone to Another Arena - In the Arenas and Zones section, select the zone group into which you want to add a zone. - Make a zone that covers the area of interest within the arena. - Click the Label Zone button on the toolbar and click in the shape you have just created. - In the Add Zone window, select Use Existing Zone and select one of the zones from the list. - Click OK. Notes - You cannot copy individual zones from one arena to another. You can redraw the zone in the destination arena and use a label with the same zone name. - If you have multiple arenas with the same size and shape, you can duplicate a complete arena including all zones, then arrange the arenas using the Multiple Arena Setup. Move an Entire Arena with Its Zones - In the Arenas and Zones section, click the Arena row to display the corresponding arena in the video image. - Drag the mouse cursor over the entire arena in the window on the left to select all components, then move the entire selection. --- ## EthoVision XT 19 - Arena Settings - Draw Subdivided Shapes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-draw-subdivided-shapes Chapter: EthoVision XT Draw Subdivided Shapes Aim To automatically divide a circle and a rectangular shape into a number of zones. This applies when: - You draw an arena and you want to split it in equal zones like the four quadrants in a Morris water maze. - Within an existing arena, draw a shape and divide it in a number of zones. Result: Zones are automatically defined with labels S1, S2, etc. provided that the Auto-Label Zone option is active. To Subdivide an Arena in Zones This applies when you still have to draw the outline of the arena. See Make a Subdivided Arena. To Divide a Shape Within an Existing Arena - In the Arenas and Zones section, click 2. Select Shape and Draw Zones (Optional). - In the Arenas and Zones section, click the zone group where you want to insert the zones that result from the subdivision. - Click one of the buttons on the toolbar: for circular shapes, select Subdivided 3-Point Circle or press I; for rectangular shapes, select Subdivided Rectangle or press U. - Draw the shape. - In the Add Subdivided Circle/Rectangle window: for circular shapes, enter the number of sectors (for example, 4 for quadrants in a Morris water maze); for rectangular arenas, enter the number of rows and columns. A total of rows x columns equal zones will be defined. Result: in the Arenas and Zones section, the zones are defined in the zone group that you clicked in step 2. The Subdivision Zones Group Subdivision Zones is a zone group that includes the zones created in a subdivided arena. Note: The Subdivision Zones zone group is not created when you subdivide a shape within an existing arena. Subdivision Segments A subdivided shape is defined by a number of segments. Move and resize a segment just like with other shapes. Move, Rotate and Resize a Shape Important: Whenever you edit an arena or zone, make sure the arrow point of the corresponding label stays within the shape. To Move a Shape - On the Arena Settings toolbar, click the Normal mode button or press V. - Move the mouse pointer over the shape, so the pointer becomes a move pointer. Then click the object and move it. To Rotate a Shape - Click the Rotation mode button on the Arena Settings toolbar or press R. - Move the mouse pointer over the shape, so the pointer becomes a rotation pointer. - Click the object with the left mouse button, keep the mouse button pressed and move the pointer to rotate the shape. - Click Normal mode again when you are done rotating. To Resize a Shape (or Multiple Shapes) - Click the Normal mode button on the toolbar (or press V), and select the shape. For multiple shapes, drag the mouse around all shapes. - Use the handles to resize the shape. To resize a rectangle also at the opposite side, press Ctrl and move the resize handle. To Rescale a Shape If you rescale a shape, the size changes but the aspect ratio is maintained. - Click the Normal mode button on the toolbar (or press V), then select the shape. For multiple shapes, drag the mouse around all shapes. - Use the resize handles at the corners of the shape. To rescale the shape with the center point of the shape as the reference point, press Ctrl and move the resize handle. To rescale the shape with the opposite corner handle as the reference point, press Shift and move the resize handle. To Reshape a Shape - Click the Point Edit mode button on the toolbar (or press P). - Click and drag the handles at the corners to a new position. - Select Normal mode when you are done reshaping. To Add or Remove Corners in a Shape - Click the Point Edit mode button on the toolbar (or press P). - To add a corner, click on the contour of the shape. To remove a corner, right-click the corner and select Remove Point. Work With Multiple Arenas - Calibrate multiple arenas - Duplicate an arena - Add and delete an arena - Arrange arenas with the Multiple Arena Setup Calibrate Multiple Arenas When the video image includes two or more arenas, by default the calibration is shared. This means that the calibration is used for all arenas. When you need more accurate calibration, for example when the distance between individual arenas and the camera varies, you can calibrate each arena individually. To Make Calibration Unshared To make the default shared calibration unshared and calibrate individual arenas, in the Arenas and Zones section, right-click Calibration and select Unshare This Calibration. Next, calibrate each arena. See Calibrate the Arena. To Make Calibration Shared In the Arenas and Zones section, right-click the calibration you want to share and select Share This Calibration. --- ## EthoVision XT 19 - Arena Settings - Duplicate an Arena URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-duplicate-an-arena Chapter: EthoVision XT Duplicate an Arena Aim To make copies of an existing arena in the same video image. For example, in an experiment with four PhenoTypers, draw an arena for cage 1, and then copy that arena for the other three cages. Important: Before duplicating an arena, make sure you have created all the zones for that arena. Procedure - In the Arena Settings window, click the row for the arena you want to duplicate. - Click the Copy Arena button, or right-click the row and select Duplicate Complete Arena. - In the Duplicate Arena window, select an option from the drop-down list. If you select the option All Other Arenas, also select how the arenas are arranged in rows and columns. The Multiple Arena Setup now opens. - Select Duplicate Content to Existing Arenas if you want to duplicate zones and points to the other arenas. - Move the duplicated arena to the appropriate location. - Repeat steps above for all consecutive arenas. - Adjust the position, shape and size of individual arenas. See Move, Rotate and Resize a Shape. - If the arenas are evenly distributed in the video image, use the Multiple Arena Setup to move, scale, rotate and space all arenas. Notes - To duplicate an arena, you can also right-click the outline of the arena and select Duplicate. - When you copy an arena, calibration is also duplicated if it is unshared. See Calibrate Multiple Arenas. - An arena to which another arena is duplicated loses its previous definitions and contents. - If you select the option Duplicate Content to Existing Arenas, the position of existing arenas is maintained. If you do not select this option, the position of each arena is adjusted based on the number of arenas and their layout. See The Multiple Arena Setup. Add and Delete an Arena You cannot add or delete an arena in the Arena Settings. You can only delete the shape that defines the contour of the arena. To Add or Delete an Arena In the Experiment Settings, increase or reduce the number of arenas in the drop-down list next to Number of Arenas. Note: You cannot add or delete an arena in the Experiment Settings once you have carried out Acquisition in the Experiment. The Multiple Arena Setup Use the Multiple Arena Setup to configure multiple arenas which are regularly distributed (for example, four open fields placed on a 2x2 grid). Taking into account the number of arenas and their layout (that is, the number of arenas on rows and on columns), EthoVision XT creates a virtual grid in which the arenas are initially evenly distributed. You can then configure the multiple arenas with the Multiple Arena Setup. There are two ways to open the Multiple Arena Setup: - The Multiple Arena Setup window opens automatically when you copy an arena to all other arenas. - In the Arenas and Zones section, click the Arrange Arenas button. Arranging Arenas The following options are available in the Arrange Arenas window: - Move Grid. You can move all shapes (including zone shapes) both horizontally and vertically, by using the slider, by pressing the up/down arrows of the corresponding box or by entering a number in a box. - Scale Arenas. To resize all shapes by using the sliders, by pressing the up/down arrows of the corresponding box or by entering a number in a box. By default the option Keep Proportions is not selected. If you select this option, both the height and width of all shapes are changed while the original shape and position is kept. If you do not select the option Keep Proportions, you can resize the height and width of all shapes separately. - Rotate Grid. To rotate all shapes. The shapes rotate around the geometric center of Arena 1. - Arena Spacing. To change the space between the shapes. By default, the option Keep Proportions is not selected. If you select this option, spacing is done both in horizontal and vertical direction relative to Arena 1. If you do not select Keep Proportions, you can change the space between the shapes separately in the vertical and horizontal direction (relative to the first row and first column, respectively). To Reset the Multiple Arena Setup Set the values back to zero. Make sure to deselect the option Keep Proportions. Alternatively, press the Cancel button; this resets all configurations. To View Details in Multiple Arenas If you have multiple arenas, you can view or hide layers and labels of all arenas for better viewing. In the Arenas and Zones section, right-click an arena and select one of the options: - To show or hide the border of all arenas, select Show All Arenas or Hide All Arenas, respectively. - To show or hide the fill color and the label of all arenas, select Show All Fills and Labels or Hide All Fills and Labels, respectively. - To show or hide a zone group or a zone in all arenas, right-click that group or zone and select Show in All Arenas or Hide in All Arenas, respectively. Applying Colors to Arenas and Zones To Apply a Color to All Arenas - Change the color of one arena. - In the Arena Settings window, right-click the row of that arena and choose Apply Color to All Arenas, or right-click the color field and select Apply to All Arenas. To Apply the Color of a Zone in All Arenas This changes the fill color for a zone in all arenas where a zone is defined with the same name. - Make sure the zone is present in all arenas and has the same name for all of them. - In the Arena Settings window, change the fill color of the zone in one of the arenas. - Right-click the row of that zone and choose Apply Color to All Arenas, or right-click the color field and select Apply to All Arenas. To Change the Contour Color of a Zone in All Arenas The color of the contour of a zone depends on the color selected for the zone group (layer). By changing the contour color of a zone, you also change the contour color of all zones in that group. - In the Arena Settings window, change the color for the zone group the zone belongs to by clicking the color cell for the row with the zone group name. - Right-click the row of that zone group and choose Apply Color to All Arenas, or right-click the color field and select Apply to All Arenas. Further Information on Arena Settings Learn About - The x-y coordinate system in the arena What Do You Want to Do? - Modify the coordinate system of the arena - Check the video aspect ratio - Adjust the video aspect ratio - Use the Arena - Hardware mapping --- ## EthoVision XT 19 - Arena Settings - The X-Y Coordinate System in the Arena URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-the-x-y-coordinate-system-in-the-arena Chapter: EthoVision XT The X-Y Coordinate System in the Arena The Default Coordinate System By default, the x- and y-coordinates of your track are expressed relative to the center point of the background image. The positive x-axis points to the right, and the positive y-axis points upward. Position of Shapes in the Coordinate System After calibrating the arena, the Shape Size and Position section at the bottom of the Arena Settings pane shows the real-world coordinates X and Y of the object currently selected. If the arena is not calibrated yet, the coordinates X and Y are given in pixels. - If you click the calibration arrow line, the X and Y values are the coordinates of the center of the arrow. - If you click an object like a zone, X and Y are the coordinates of the geometric center of the object. Width and Height are the width and height of the rectangle around the object, respectively. - Remember that the value of X and Y depend on where the origin (0,0) is placed. In the default coordinate system, a negative value means that the center of the object is to the left (for X) or below (for Y) the center of the background image. World Point / Pixel Point In the Status bar, World Point and Pixel Point indicate the current position of the mouse pointer. You can use this function to know the exact position of an object. If you do not see the Status bar, choose View > Status Bar. - World Point gives you the coordinates of a point based on the calibration scale and origin, and the distance unit chosen in the Experiment Settings. The world coordinates can be positive or negative depending on where your axis origin is. - Pixel Point gives you the coordinates of a point in pixels. The 0,0 coordinates correspond to the top-left corner of the video image. The pixel coordinates are always positive. Modify the Coordinate System of the Arena Aim To use a coordinate system different from the default one. For example: - You want to export the real-world coordinates expressed relative to a point of reference in the real world that is not in the middle of your image. - You want the dependent variables that use angle (Head Direction, Heading, Meander, Turn Angle) to be expressed relative to a reference line different from the default one (horizontal and pointing to the right). For example, if you have an external cue to the north-east of your arena and want to express the animal's orientation relative to this cue, rotate the Calibration Axes so the x-axis points towards the cue. Use the Calibration Axes object to specify the orientation of the real-world coordinate system and to specify the real-world coordinates for one pixel point. To Modify the Coordinate System - Click the Create Calibration Axes button at the bottom of the Arenas and Zones section. - Optionally, in the Calibration Coordinate System window, type the real-world origin of the x-axis (Origin X) and of the y-axis (Origin Y) relative to the current position of the origin on your screen. Do this if you know the origin of the coordinate system is outside the background image. For example, if you type 10 cm for Origin X, it means the origin (0,0) of your calibration system is shifted 10 cm to the left relative to the center of the video image. - Click and drag the Calibration Axes object to reposition the axes origin. To flip the y-axis of the Calibration Axes object, double-click it and select Flipped Y-Axis. Move the Rotation Mode arrow to rotate the calibration axes. To Return to the Default Coordinate System Select the Calibration Axes object and press Delete. Check the Video Aspect Ratio The Video Aspect Ratio The video aspect ratio is the relation of the horizontal to vertical size of a video image. When you pre-record video from analog cameras, the aspect ratio of the resulting video files is not the same as that of the source camera. This results in a distorted background image. In such cases, a perfectly circular Morris water maze may look ellipse-like in EthoVision XT after you grab a background image from the video file. When Is the Video Aspect Ratio Not Correct? The problem of the aspect ratio occurs in the following situations: - When you record video with a program other than EthoVision XT, such as MediaRecorder, and from analog cameras. - When you recorded video with EthoVision XT and you use that video in a new experiment. If you record video and do tracking within the same experiment, the video aspect ratio is always correct. How to Identify a Distorted Video Aspect Ratio - The shape of the test enclosure as displayed in the background deviates from the expected shape. For example, a circular water maze looks like an ellipse, or a square open field looks like a rectangle. - Place a sheet with a circle under the camera and grab this image as the background image. In Arena Settings, draw a three-point circle. If the aspect ratio of the image is correct, the three-point circle fits over the circle from the camera image. Calculate the Correct Aspect Ratio in a Video Image - After grabbing the background image, locate the bitmap file of your background image in the Bitmap Files folder of your experiment folder. - Open the file in an image editing program such as Paint.NET. - Draw a shape exactly around the arena and note the dimensions of the shape you have drawn. If the ratio (for instance, width/height) of the dimensions of the drawn shape deviates from the ratio of the real-world dimensions of the arena, the image is distorted. Example 1: You have a perfectly circular water maze with a diameter of 100 cm. When you open the background image in an image editing program and draw an ellipse around the maze, the ratio of width/height is 1.019 instead of exactly 1. This means you need to adjust the aspect ratio by dividing the width of the image by 1.019 in the Adjust Aspect Ratio window. Do not change the height. Example 2: You have a square open field measuring 40 x 40 cm. When you open the background image and draw a rectangle around the open field, the ratio of width/height is 0.8 instead of exactly 1. This means you need to adjust the aspect ratio by dividing the width of the image by 0.8 in the Adjust Aspect Ratio window. Do not change the height. --- ## EthoVision XT 19 - Arena Settings - Validate the Manual Scoring Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-validate-the-manual-scoring-settings Chapter: EthoVision XT Validate the Manual Scoring Settings Aim To have EthoVision XT check that the coding scheme is consistent. Procedure In the Manual Scoring Settings screen, click the Validate button or press Ctrl+V. The program checks that the manual scoring settings are valid every time you leave the Manual Scoring Setting screen. Notes Manual scoring settings are valid if: - For Start-Stop behaviors: A key has been selected for both start and stop, or for neither of the two. If you define a start key but not a stop key or vice versa, when leaving the manual scoring settings an error message is displayed. - For Mutually-exclusive behaviors: All behavior groups contain at least two behaviors, and one is selected as Initially active. - All behaviors and behavior groups have unique names. Arena Settings Introduction to Arena Settings Learn About - Important terms in Arena Settings - Useful things to know about Arena Settings Important Terms in Arena Settings Arena An arena is the region in the video image on the screen in which a moving subject is tracked by EthoVision XT. You can have one or more (up to 100) separate arenas in one screen. If you have multiple arenas, they must not overlap. Zone A zone is a specific area of interest within an arena. For example, in a Morris water maze, define the hidden platform as a zone named Platform. You can use a zone to calculate, for example, the time the animal spent in that zone, or the number of zone visits; you can also use a zone for starting and stopping data acquisition. Point A point is a dimensionless object that you can use as a reference. For example, an odor source that is the target of an insect. You can define the source as a point, to determine whether the animal is heading towards that spot. Cumulative Zone A zone that combines two or more existing zones, so you analyze them as one. For example, the two open arms "Open arm 1" and "Open arm 2" of an Elevated plus maze can be analyzed as a Cumulative zone "Open arms". Hidden Zone A zone that you can use to calculate the time that the subject stays out of view, for example in a shelter. Zone Group You can organize zones in zone groups. Within one zone group, zones must be non-overlapping. Useful Things to Know About Arena Settings Define Different Arena Settings in the Same Experiment Arena Settings define the configuration of arenas and zones in an experiment. You can create as many Arena Settings as you want. This can be useful if your trials are carried out with different zone configurations. For example, when the position of the hidden platform changes in different trials in a Morris water maze experiment. Arena Settings in the Experiment Explorer All Arena Settings you create are listed under Arena Settings in the Experiment Explorer. To open Arena Settings, choose Setup > Arena Settings > Open, or in the Experiment Explorer, under Arena Settings, click one of the Arena Settings. The Arena Settings currently active are shown in blue. Acquisition is done using those settings, unless you specify otherwise in the Trial list or in the Acquisition Settings window. Read-Only Arena Settings Arena Settings that have been used in acquisition are read-only and cannot be renamed or deleted. Read-only Arena Settings are indicated by a small lock symbol in the Arena Settings icon. You can make an editable duplicate of read-only Arena Settings, edit it and use the new settings for acquisition. Alternatively you can delete all trials, which unlocks the read-only arena settings. In addition: - Zones that are used in Trial Control cannot be deleted or edited. - You can add new zones to read-only arena settings. Working with Layers The elements of the Arena Settings are organized in layers. - To display arenas, zones, calibrations and background image on your screen, select an arena, zone group, zone, calibration or background image by clicking its row in the Arenas and Zones section. This way you can highlight the correct layer. - To hide a layer, deselect the corresponding check box in the View column. - To view more than one layer at the same time in the video image, select the appropriate check boxes in the View column. Make the Arena Steps - Grab the background image - Calibrate the arena - Draw the arena - Define zones (optional) and organize the zones in your arena - Validate the Arena Settings Grab the Background Image Aim To create a background that you can use to draw arenas and zones. Procedure - Choose Setup > Arena Settings > New or right-click Arena Settings in the Experiment Explorer and select New. The Grab Background Image window opens. - If you track from video, click Browse and open a video file. In the Video window, if possible, browse to a video frame without animals. Then click Grab. If you track live, if possible, remove the animal from the arena and click Grab. - Check that the aspect ratio of the background image is correct, and if necessary, adjust it. Notes - If the Grab Background Image window shows a white background, that may be due to the graphics card settings. See Troubleshooting > The camera image is not shown in the Arena Settings or Integrated Visualization. - You can define and update a background of existing Arena Settings at any time, as long as they are not read-only. To do so, click the Grab Background Image button in the lower part of the Arena Settings window. - For all experiments from video: The default video file shown in the Video window is the last video used to grab a background image. - For DanioVision experiments: After grabbing the background image, EthoVision XT attempts to detect the well plates and draw the arenas automatically. Check that the outline of the arenas overlap with the well borders. If they do, click Yes in the window that appears. - When presence of the animal makes it difficult to draw the arena, and it is not possible to grab a background image without the animal, open the Detection Settings. When the animal moves around in the arena, under Method click Background and use the Learn function. This saves a bitmap of the empty arena. Next, in the Arena Settings, click the Grab Background Image button, then Browse and open the Bitmap Files folder within your experiment folder. From the file type list, select All files (*.*) to also view image files. Choose the bitmap image just saved — its name starts with DetProf_. Then click Grab. --- ## EthoVision XT 19 - Arena Settings - Zones and Points for Behavior Recognition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-arena-settings-zones-and-points-for-behavior-recognition Chapter: EthoVision XT Zones and Points for Behavior Recognition Aim When you use the Rat/Mouse Behavior Recognition function, defining a few special zones and points significantly increases behavior recognition accuracy. - Drinking spout points to detect drinking. - Feeder zones to detect eating behavior at the feeder. - Wall zones to detect rearing to wall. Prerequisites - You need the Rat or Mouse Behavior Recognition Module of EthoVision XT. - You have read important notes about behavior recognition. See Behavior Recognition: Requirements. - In the Experiment Settings under Tracked Features, you selected center-point, nose-point, and tail-base detection. Under Behavior Recognition, you selected one or more of the options Feeder, Drinking Bottle, Arena Walls. If one of the options is not selected, the corresponding layer is not added in the Arena Settings. - Make sure that the outline of the arena covers all possible regions where all detected body points of the animal can be, including when rearing. Make sure that the aspect ratio of the video image is correct. To Define the Drinking Spout Points - In the Arenas and Zones section, click Select Shape and Draw Zones (Optional). - Click the Drinking Spout Points zone group. - Click the Add Point button on the toolbar. The mouse pointer changes to a cross. - Click the background image to position the point. - In the Add Point window, accept the default name or enter another name, then click OK. Repeat these steps to define more points. Tip: To have a better view of the background image and locate the tip of the drinking spout more easily, in the Arenas and Zones section deselect the View option for the Arena and other zone groups. To Define the Feeder Zones - In the Arenas and Zones section, click Select Shape and Draw Zones (Optional). - Click the Feeder Zones zone group. - Using one or more drawing tools available on the toolbar, draw the outline of the feeder. - If the Auto-label Zone option is activated, the zone is automatically named Feeder Zone 1. Right-click the label to rename it. Repeat steps 3 and 4 to define more feeder zones. To Define the Wall Zones All high objects that the rat can use for supported rearing should be defined as wall zones. - In the Arenas and Zones section, click Select Shape and Draw Zones (Optional). - Click the Wall Zones zone group. - Using the polygon drawing tool, draw the outline of the floor of the arena. It is important that all sides of the arena are included in the wall zone, even when the side walls are barely visible. - If the Auto-label Zone option is activated, the zone is automatically named Wall Zone 1. Right-click the label to rename it. - Make sure that the zone label points to the arena walls in the video image. If it points to the inside of the arena, move the label. When the camera is not centered on the arena, as in a multiple arena setup, side walls may be partly or totally hidden. Draw the polygon in such a way that the wall zone also covers those regions. Notes: - In the Drinking Spout Points group, you can only define points, not zones. - You cannot delete one of the zone groups Drinking Spout Points, Feeder Zones, or Wall Zones. You can delete the zone or point label, but the zone group itself remains. To delete a group, deselect the corresponding option under Behavior Recognition in the Experiment Settings. Work with Shapes What Do You Want to Do? - Draw simple shapes - Draw subdivided shapes - Move, rotate, and resize a shape Draw Simple Shapes Line, Rectangle, Ellipse - Click the appropriate shape button on the toolbar, or press L for a line, S for a rectangle, and E for an ellipse. - Click the background image to define the first point of the shape, keep the mouse button pressed, and drag to the end point. When ready, release the mouse button. To create a circle with the Ellipse tool, hold Shift down. Polyline - Click the appropriate shape on the toolbar, or press O for an Open Polyline and Y for a Closed Polyline. - Click in the background image to position the first point, move the mouse pointer to the position of the second point and click in the background image. Next, move the mouse pointer to a new position for the third point, etc. - When ready, double-click. 3-Point Circle - Click the 3-point circle button on the toolbar or press T. - Click in the background image to position the first point, move the mouse and click to position the second point. - Move the mouse to position the 3-point circle and click to finish. When you resize a 3-point circle, it becomes an ellipse. If you don't want that, press Shift while you resize the circle. To show or hide the center of the bounding rectangle of a shape, right-click it and select Show/Hide Center. To Copy and Enlarge a Shape - Right-click the shape and select Duplicate. - In the Duplicate window, enter an Enlargement factor and click OK. --- ## EthoVision XT 19 - Behavior Recognition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-behavior-recognition-uUP Chapter: EthoVision XT Basic Rules For each sample in your track, EthoVision XT calculates a probability value for each behavior (see Behaviors Detected with Behavior Recognition). The sum of probability values is 100%. All behaviors but Twitching and Hopping are mutually-exclusive states, that is, only one can be assigned to a sample. A behavior is assigned to a sample based on a number of decision rules that take into account the probability of that behavior relative to that of others, and the behaviors assigned to adjacent samples. See also the figure below. - Twitching and Hopping have their own probability, but are not compared with that of the others. As a result, Twitching and Hopping are scored independent of other behaviors. Each may be assigned to a sample also when one of the other behaviors is scored for that sample. For example, Hopping when Walking is active. - When two or more behaviors (excluded Twitching and Hopping) have similar probability values, and the same behaviors are not scored in adjacent samples, or when all behaviors have probability values below 25%, then none of the behaviors are scored for that sample. This results in gaps between scored behaviors when you visualize them in the Integrated Visualization. Example Below you see an example of how behaviors are scored based on their per-sample probability values. Top: X-Y chart of probability (here ranging from 0 to 1) of five behaviors (others are not shown for simplicity). Bottom: The resulting scored behaviors. In general, the behavior is assigned to a sample that has the highest probability (see for example Sniffing at the beginning of the time line). However, the state is smoothed based on the values in a number of samples before and after the current sample. For example, at 75 s Sniffing has a lower probability than Twitching, but the state Sniffing is still active. Note that Twitching is scored as a point event, with no duration, and is represented with a vertical segment. The gap between scored states is caused by samples where two or more behaviors have similar probability values (for example at about 75.9 s, with Jumping and Walking having probabilities around 0.5) or the probability is below 0.25 for all behaviors. The example is taken from Rat Behavior Recognition data. Behavior, "Not" Behavior and "Unknown" Each behavior type, except Twitching and Hopping, has three complementary, mutually-exclusive states. For example, Grooming, Not Grooming and Unknown. At any sample, the "Not" behavior is automatically scored if the corresponding behavior is not scored, unless Unknown is scored for that sample (see below). Behavior "Unknown" A behavior type is scored as Unknown in the following cases: - At the beginning of the track if the Trial Control Settings rule does not include an additional Time condition that waits three seconds before the start of tracking, and in the last portion of the track (see Behavior Recognition: Data, Performance and Accuracy). - When the nose and tail base points are not detected. - In all cases when the subject is not found or samples are missed for more than 0.4 s. Statistics of Unknown can be calculated for all behaviors except Twitching. The statistics are the same for all behaviors. For example, the duration of Unknown calculated for Grooming is equal to that of Unknown for Rearing supported. Behavior Probability Each behavior is associated with a probability, calculated per sample. Whether a behavior state is scored for a specific sample depends on a set of decision rules (for details see How Behaviors Are Scored in Behavior Recognition). All behaviors but Twitching and Hopping are mutually-exclusive, therefore the sum of their probability values is 1. Twitching and Hopping have a probability too, but whether they are scored at a specific time does not depend on the probability of other behaviors. How to Specify Behavior Probability - Click the Add button next to Behavior probability. - In the Behavior Probability tab, select the state(s) you would like to calculate the probability for. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Application You may want to filter the occurrences of a behavior based on their probability values. If the probability of that behavior is lower than a threshold at a specific sample, that sample is left out and the behavior state is re-calculated (see an example in Behaviors Detected with Behavior Recognition). - In the Analysis profile: - Add the behavior you are interested in. - Add the Behavior probability variable and, in the window that appears, select the same behavior. - Plot the integrated data to view the behavior detected and its probability together with the video. Check how those states correspond with the subject's behavior in the video. - To filter data based on probability, in the Analysis profile click the behavior variable, and select a probability value for Behavior probability threshold. - Plot the data again to see the result of filtering. Merged Behavior You can define a behavior state that includes two or more of the behaviors detected automatically. For example, to calculate the overall frequency of Rearing = Rearing supported + Rearing unsupported. How to Specify Merged Behavior - Click the Add button next to Merged Behavior. - Under Select behaviors to merge, select which behaviors you would like to merge for analysis. For example, select Rearing supported and Rearing unsupported to analyze the total occurrences of Rearing. - Under Behavior probability threshold, select: - Default: Statistics will be calculated by using all samples scored as that behavior (no filtering based on the state's probability). - Probability greater than: Statistics will be calculated by using only the samples for which the probability of one of the merged behaviors is higher than a specific value. Select this value from the list. See the note below. - Under Behavior duration threshold, next to Exclude behavior instances shorter than, enter the minimal duration of the merged behavior to be considered for analysis. Note: The threshold is applied to the merged behavior, not the instances of single behaviors. For example, two instances of behaviors Rearing unsupported and Rearing supported follow each other in the time line. The first lasts one second, the other two seconds. When you merge the two behaviors and select a duration threshold of 3 seconds, the two behaviors are considered for analysis. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Note The Frequency of Merged behavior may not always be equal to the sum of the frequencies of the single behaviors. This can happen, for example, when an instance of Rearing supported is immediately followed by an instance of Rearing unsupported. Then the frequency of Merged behavior is 1, not 2. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Behavior Recognition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-behavior-recognition Chapter: EthoVision XT Definitions See also the reference in Notes. Digging Rooting with the muzzle or digging with the front paws in the bedding material (for Mouse Behavior Recognition only). Drinking The subject licks at the spout of the water bottle. Eating The subject eats at the feeder or from the floor, or is eating while holding food in front paws. Grooming The subject grooms snout, head, fur or genitals. Includes scratching and licking of paws during a grooming session. Hopping The subject moves forward with both hind limbs at the same time. Head goes first, followed by the rear. Unlike Jumping, Hopping is scored as a point event with no duration, and does not interrupt behavior states (for Mouse Behavior Recognition only). Jumping The subject moves quickly forward with both hind limbs at the same time. Jumping interrupts other states like Walking (for Rat Behavior Recognition only). Rearing Unsupported The subject stands in an upright posture, with front paws not in contact with any object. Includes the rise and descend. Rearing Supported The subject stands in an upright posture, leaning with front paws against the cage-wall. Includes the rise and descend. Resting The subject rests with hardly any moving, either sits or is lying down. Includes sleeping. Apparently no interest in the environment. Sniffing The subject makes slight movements of the head, possibly with slight, discontinuous body displacement. Includes sniffing the air, the wall, the floor and other objects. Twitching The subject makes sudden and short movements of the body or head. Includes body shake and head shake. Twitching is scored as a point event with no duration, and does not interrupt behavior states (for Rat Behavior Recognition only). Twitching is defined as a point event, that is, an event marking a point in the time line, but with no duration. Walking The subject moves to another place, and hind legs move as well. Note the difference between Walking and Movement: Both dependent variables Walking and Movement are based on displacement of the subject's body point in the 2D space. However, Walking is based on many more video frames than Movement, and therefore Walking is a more accurate measure of walking behavior. How to Specify a Behavior for Behavior Recognition - Click the Add button next to the behavior you want to analyze. - Under Behavior decision method, select: - Default: Statistics will be calculated by using all samples scored as that behavior (no filtering based on the behavior's probability). - Probability greater than: Statistics will be calculated by using only the samples for which the probability of that behavior is higher than a specific value. Select this value from the list (0–99%). - Under Behavior duration threshold, next to Exclude instances shorter than, enter how long the current state must last before it changes from the previous state (in seconds). If the bout length passes this threshold, the previous samples in the bout are included in the new state. If the bout length does not pass the threshold, the previous state ends, but no new state is defined. - Under Calculate statistics for, select which state you would like to calculate statistics for. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Accuracy According to our tests, the average recall rate, that is, the proportion of ground truth manually-scored behaviors that are correctly recognized, is around 70%. For more information, see the paper mentioned below. - Drinking can be confused with Sniffing especially when the Drinking Spout Points are not defined. - Make sure to draw the Feeder Zones in the Arena Settings to maximize the detection accuracy of Eating. - To maximize accuracy of detection of Rearing supported and reduce false positives, carefully draw the Wall zone in the Arena Settings. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Behavior Recognition (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-behavior-recognition-continued Chapter: EthoVision XT Notes - For Twitching and Hopping, which is an event with no duration, the Behavior duration threshold and the Calculate statistics for options are not available. - For more information on Behavior recognition in EthoVision XT, see the following paper: van Dam, E., J.E. van der Harst, C.J.F. ter Braak, R.A.J. Tegelenbosch, B.M. Spruijt, L.P.J.J. Noldus (2013). An automated system for the recognition of various specific rat behaviours. Journal of Neuroscience Methods (2), 214–224. http://dx.doi.org/10.1016/j.jneumeth.2013.05.012 - The Behavior decision method acts as a filter to ignore samples for which the behavior is associated with a low probability, making it easier to extract more reliable data. By default, EthoVision XT uses the original scores (thus no filtering based on probabilities). See the figure below for an example. Top: The probability of Grooming, and another behavior plotted against time (for simplicity, other behaviors are ignored here). Bottom: When defining Grooming in the Analysis profile, consider the following options: - With Default selected, Grooming occurs every time its probability exceeds the probability of any other behavior (default behavior recognition). - With Probability greater than 50% selected, Grooming is limited to the samples for which its probability is higher than 50%. The higher the value, the more conservative the definition. - The Behavior duration threshold acts as a filter to ignore short transitions between states. For example, if the behavior Grooming is scored for 0.8 s and you select a Behavior duration threshold of 1.0 s, the Grooming state does not exceed that threshold, and is therefore excluded from analysis. - For all behaviors but Twitching and Hopping, the percentage statistics are calculated including Unknown. For example, when Grooming lasts 30 seconds, Not Grooming 1 min 30 s, and Unknown 30 s, then the Cumulative Duration within Track (%) for Grooming is 30/150 = 20%. If you want to exclude Unknown from the percentage, in the Data profile make two nesting intervals, one with [behavior name] and the other with Not [behavior name], then combine the two Nest boxes in parallel. Next, in the Analysis profile specify the behavior and its statistic, Cumulative Duration within Nesting (%). In the example above, the result would be 30/120 = 25%. - The duration of the behaviors may not add up to 100% of the track duration, also when including Unknown. This could result, for example, when you filter a behavior using a probability threshold. When visualizing behaviors, samples filtered out appear as gaps between behaviors. - When you specify a Behavior probability threshold for one behavior, the other behaviors (which are mutually-exclusive by definition) are not re-calculated according to that setting. Depending on the value of the probability threshold, the behavior may become overlapping with other behaviors. For example, if you select a probability threshold of 15% for Grooming, some parts of the track may be scored as Grooming where also Eating was scored based on the default settings (see below). To prevent this from happening, either use Default or choose the same probability threshold for all behaviors. Below: Event plots of behaviors Grooming and Eating. Top: Behavior probability. Middle: Grooming is defined with a Behavior probability greater than 15%. Bottom: Eating is defined with Default probability settings, and is scored for most of the time due to the high probability (see the probability plot). As a result, Grooming is partially overlapping with Eating, although the two behaviors are supposed to exclude each other. With default settings, Grooming would not be scored. See Also - How Behaviors Are Scored in Behavior Recognition Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Body angle state URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-body-angle-state Chapter: EthoVision XT Definition A discrete (state event) variable with two possible states: Straight and Bent, depending on where the running average body angle (see Body angle for its definition) of the subject calculated for the current sample lays relative to a user-defined threshold: - If the running average body angle is greater than the threshold value, the state is Bent. This state can be further split in Bent counterclockwise and Bent clockwise depending on the sign of the angle. - If the running average body angle is smaller than the threshold value, the state is Straight. The running average body angle is calculated for each sample, over the number of samples specified by the Averaging interval. Below: Visualization of Body angle state (top chart) and Body angle (bottom). Body angle state was based on the Body angle values smoothed with averaging interval of 5. How to Specify Body Angle State - Click the Add button next to Body angle state and click the Body Angle State tab. - Enter the following: - Averaging interval: The number of samples over which the running average body angle is based. - Body bent above: The angle above which the subject is considered to be bent. This value is unsigned and applied to both negative and positive Body angles. - Under Calculate statistics for, select which state you want to calculate statistics for: Straight, Bent, Bent counterclockwise (that is, when the running average body angle is positive; see Body angle for its definition), and Bent clockwise (when the running average body angle is negative). - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - When a body point is missing for more than three samples, the current Body angle state ends and the remaining missing samples are ignored. - Averaging interval: The default value is 1. In that case the body angle state is based on the value of Body angle at the current sample. If you select a number k higher than 1, EthoVision takes the body angle of the last k samples (including the current sample) and replaces the current value with the average. See Averaging interval. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Body contact URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-body-contact Chapter: EthoVision XT Definition A discrete (state event) variable with two possible states, In contact and Not in contact, based on whether the subject's body contour is in contact with the body contour of any of the other subjects. NOTE Body contact is not available or does not give results if: - The tracks were recorded in EthoVision XT 11 or earlier. - Your experiment is set to: - Color marker tracking. - Live Mouse Tracker - But see Raw Live Mouse Tracker data - Center-point, nose-point and tail-base detection, with two subjects per arena tracked with Deep learning. How to Specify Body Contact - Click the Add button next to Body contact. - In the Body contact tab, select the state you want to analyze. For example, select Body Contact if you want to know how often or how long the subjects were in contact during the test. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - An animal's contour is determined by computer vision, which is unlike human vision. This is exemplified when dark animals are tracked: often their shadow on the background will be considered part of the animal. Thus, the detected contour is regularly a bit bigger than the human eye would observe. - Body contact is not subject-specific. That is, you cannot isolate instances of contact for a specific combination of subjects (for example, Subject 1 in contact with Subject 3). Instead, use Proximity and specify the two subjects. - Body contact is based on the subject's contour, while Proximity is based on the distance between subject's body points. For example, two subjects next to each other may be in proximity, but not in body contact. - Body contact is affected by the track smoothing methods The Minimal Distance Moved smoothing method and The Maximum Distance Moved smoothing method. When you apply one of those methods, Body contact is recalculated and may be slightly different with respect to when the method is not applied. The difference is usually limited to one or a few samples. Applications Body contact can be used in any social interaction tests: - To quantify the level of interaction between subjects. Add Body contact in the Analysis profile (see above). - To exclude instances of body contact when these result in unreliable tracking. In this case, instead of adding Body contact in the Analysis profile, in the Data profile choose Nesting over Body contact and select Not in contact. TIP In Integrated Visualization, the body contour is not visible. To view the body contour, open Acquisition, click the Show Hide button, choose Detection Features and select Body contour. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Body elongation state URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-body-elongation-state Chapter: EthoVision XT Definition A discrete (state event) variable with three possible states: Stretched, Normal and Contracted, depending on where the running average elongation measure (E) of the subject's contour calculated for the current sample lays relative to two user-defined thresholds (see Calculation below). NOTE Body elongation state is not available if your experiment is set to: - Center-point detection. - Color marker tracking. - Live Mouse Tracker (but see Stretch attend posture). - Center-point, nose-point and tail-base detection, with two subjects per arena tracked with Deep learning. Calculation - The Body elongation is calculated for each sample. See Body elongation. - The running average of Body elongation is calculated for each sample using the number of samples specified by the Averaging interval. - The Body elongation state variable is determined for each sample: - If the running average elongation percentage is greater than the Stretched above value, the state is Stretched. - If the running average elongation percentage is smaller than the Contracted below value, the state is Contracted. - In all the other cases, the state is Normal. Below: Visualization of Body elongation state (top) and Body elongation (bottom). The two variables have been set with the same Averaging interval (10 samples). Stretched is scored when Body elongation is above 80%. Contracted is scored when the resampled variable is below 50%. How to Specify Body Elongation State - Click the Add button next to Body elongation state and click the Body Elongation State tab. - Enter the following: - Averaging interval: The number of samples over which the running average elongation is based. The default value is 1, that is, the elongation measure is not smoothed before calculating Body Elongation state. - Stretched above: The elongation measure above which the subject is considered to be Stretched. - Contracted below: The elongation measure below which the subject is considered to be Contracted. To find the optimal Stretched above and Contracted below, run a few test trials and check in the Analysis Results and Scoring pane the values of Body elongation state when the animal shows such behavior. These values are calculated real-time during acquisition. Values of elongation percentage between Stretched above and Contracted below result in the subject being scored as Normal. - Under Calculate statistics for, select which state you want to calculate statistics for: Stretched, Normal or Contracted. Select at least one state. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - The elongation measure is independent of video size and the subject's position and orientation. - When a body point is missing for more than three samples, the current Body elongation state ends and the remaining missing samples are ignored. - The Body elongation thresholds set in Acquisition are not used in analysis. When you specify the Body elongation dependent variable in your Analysis profile, enter the new values in the appropriate fields. - By increasing the averaging interval, you can increase the reliability of detection of stretching and contracting. A running average elongation based on more samples diminishes the effect of random changes in elongation measure between consecutive samples that would be detected as state transitions. However, a drawback of increasing the Averaging interval is that it causes a delay in the determination of a state transition, proportional to the length of the interval. See Averaging interval. - In some cases the number of samples available for smoothing can be less than the averaging interval entered. For example, when there are missing samples or at the beginning of the track. In such cases EthoVision XT uses the samples available in the specified interval. For example, the value of Elongation for the first sample of the track is always calculated over one sample. - In the Detection Settings, under Subject Contour, select Erosion and then Dilation to remove the animal's tail from the detected image of the subjects. This way you get a more accurate measurement of Body elongation. - Body elongation is not calculated with Live Mouse Tracker data. Application The Body elongation state variable can help you assess the frequency and cumulative duration of stretch attend postures in a more objective way. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Calculate Statistics - Calculate Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-calculate-statistics Chapter: EthoVision XT Calculate Statistics Calculate Statistics: Procedure Aim To calculate descriptive statistics of one or more dependent variables. Prerequisites - You have smoothed data (optional). - You have selected data in a Data profile (optional). To Calculate Statistics - Choose Analysis > Analysis Profile > Open (to open an existing profile) or New (enter a name for the new profile), then click OK. - Choose the dependent variable. Click the Add button next to the dependent variable you want to use for analysis. If you do not see that variable name, click the More button. In most cases Distance Moved and Velocity are already selected. - In the dependent variable-specific tab, select the properties of the dependent variable. For details on dependent variables, see Dependent Variables in Detail. - Choose the Trial statistics. Click the Trial Statistics tab, and choose the statistics you want to calculate for each trial. - Choose the Group statistics. Click the Group Statistics tab, choose the statistics you want to calculate as a summary for a group. For example, if you want to calculate the average and standard error of the Total distance moved for Control and Treated subjects, choose Distance Moved as a dependent variable, Total as a Trial statistic, and Mean and Standard Error as Group statistics. - Repeat steps 2 to 5 to add more dependent variables. - Choose Analysis > Results > Statistics and Charts, then click the Calculate button on the toolbar. - The Statistics and Charts table appears on the screen. Notes - Some dependent variables are available if you have one or more of the following add-on modules: Social Interaction, Rat/Mouse Behavior Recognition, Trial and Hardware Control. - You can only select specific body points if your experiment is set to Center-point, nose-point and tail-base detection. - You can change the properties or delete a dependent variable already selected. You can also add multiple instances of a dependent variable with different settings. See Edit the Analysis Profile. - You can also calculate statistics in batch mode. See Batch Calculation. Statistics Available Statistics are a summary of the values of the dependent variable calculated for all the samples in your tracks (or the segments you have selected in the active Data profile). For each dependent variable you select in the Analysis profile, you can choose Trial Statistics and Group Statistics. Click on the corresponding tab to select the statistics you want to have in the results table. List of Trial Statistics Aim Trial Statistics give you summary statistics of individual trials. If a trial includes two or more tracks (subjects), the statistics are by default shown for each subject separately. The Data profile filters tracks and/or intervals within tracks. If the Data profile contains groups of tracks, these groups are ignored in the results. To view results per group, choose Results > Group Statistics and Charts. Cumulative Duration The cumulative duration of the state variable in the whole track, or in the track segment selected. For example, the time that the animal spent in a zone (for the variable In Zone), or the time that the subject was in the state Mobile. When a state does not occur at all in a track or track segment, the value of Cumulative Duration is zero. Cumulative Duration (%) The Cumulative Duration divided by the following, expressed as a percentage: - If you do not define time bins: The duration of the track (this corresponds to the Recording Duration independent variable, not Trial Duration). This is also the case when you define nesting intervals or results per zone. - If you define time bins: The duration of a time bin defined. Cumulative Duration Within Nesting (%) The Cumulative Duration divided by the following, expressed as a percentage: - If you calculate results per zone: The total time the animal is in the zone. - If you defined track segments with Nesting: The total duration of the track segments defined. - If you defined time bins: The duration of a time bin defined. - If you combine any of the three above: The duration of the time period shared by all selection criteria (the time periods of each criterion are combined with AND logic). Frequency The total number of occurrences of a state (only for state variables). Latency to First The time from the start of the track to the first occurrence of the behavior (for example, the first time in the track that the animal is in a zone). Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. Latency to Last The time from the start of the track to the last occurrence of the behavior. Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. Notes About Latency to First/Last - Latency to First and Latency to Last are calculated from the start of the track. This is the time when EthoVision XT collects the first sample (missing or not). If the animal is not yet in the arena and tracking has started, EthoVision XT collects a number of missing samples. The time that the animal is missing is included in Latency to First/Last, which may overestimate the true latency. To prevent this, make sure that the Trial Control rule includes a Start Track condition so that tracking only starts when the animal is first found in the arena. To calculate the time from one event to another event in the trial, select a Free Interval in the Analysis profile. - When two or more animals are tested simultaneously in the same arena, the meaning of Latency to First/Last depends on how you set this condition. Consider the following scenarios when you want to calculate the Latency of "In Zone A" for two subjects released at different times: - If you set the Trial Control to start tracking when any subject is found in the arena, tracking starts when the first animal is released. Latency is calculated from that point also for the second animal, which enters the arena later, meaning that Latency for this animal will be overestimated. - If you set the Trial Control to start tracking when all subjects are found in the arena, tracking starts when both animals are found. Latency is calculated from this point, so Latency for the second animal is correct. However, for the first-released animal, the time it was in the arena before the second was released is not counted in Latency, which may underestimate the result. For this reason, try to release the animals at the same time, or one immediately after the other. Mean - For linear variables like Distance Moved, Velocity, Distance to Zone, or Distance Between Subjects, and the variables Turn Angle, Angular Velocity and Meander, the arithmetic mean is used: the sum of the per-sample values divided by the number of samples. - For the angular variables Heading, Head Direction, and Heading to Point, the mean is calculated according to the circular mean formula, where the circular mean value can also be represented by the angle of the vector resultant R obtained by summing up all the vectors that represent the per-sample angle values. - For state variables like In Zone, Movement and behaviors scored manually or automatically recognized, the sum of the duration of occurrences of the state divided by the number of occurrences. Minimum The lowest value of the variable. For state variables, this is the minimum duration of the instances of a state. When the state does not occur at all in a track or track segment, the value of Minimum is zero. Maximum The highest value of the variable. For state variables, this is the maximum duration of the instances of a state. When the state does not occur at all in a track or track segment, the value of Maximum is zero. Number of Samples The total number of valid values of that variable (only for numerical variables like Distance Moved). Standard Error The standard deviation divided by the square root of the number of samples. This is also the case for angular variables Heading, Head Direction, and Heading to Point. Standard Deviation For most variables, including Turn Angle, Angular Velocity and Meander, the sample standard deviation of the mean, where x is the individual variable value, x-bar is the mean of the variable, and N is the number of samples. --- ## EthoVision XT 19 - Calculate Statistics - Change Colors, Fill Patterns, Dot Size and Bar Wid URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-change-colors-fill-patterns-dot-size-and-bar-wid Chapter: EthoVision XT Change Colors, Fill Patterns, Dot Size and Bar Width - In the Chart Properties window, click Series format. - Select either Color or Pattern. - Under Elements, choose the color or pattern for each item. These elements may include, depending on the type of chart: - Body points. - Subjects. - The type of behavior (e.g. Moving vs. Not Moving). - The Median (when you choose a Box and Whiskers chart) and the Datapoints (when you choose Box, Whiskers and Data Points chart). Note: Pattern fill is only available when you choose a Bars or Box and Whiskers chart. - The following options are available for some chart types: - Dot size. Select the size of the dots. This applies to Box, Whiskers and Data Points. Note that all dots lie on the vertical middle line of the box plot, so individual points may overlap and therefore not all be visible. - Bar width / Box width. Select the bar or box width (range 0–100). Note that for Box and Whiskers charts, this also changes the width of the whiskers. - Gap between bars. Move the slider or click the arrow buttons to select the required gap between adjacent bars (range 0–100). Edit Axes, Gridlines, and Legend In the Chart Properties window, click Axes and Legend. For the vertical axis: - Select Display vertical axis title and enter the new title. The default title is [name of trial statistic] [unit]. - Next to Scale min and Scale max, set the minimum and maximum value of the vertical axis automatically (Auto), or select Fixed and enter the values you require. - Select or deselect Display gridlines. For the horizontal axis: - Select Display horizontal axis title and enter the new title. The default title is the name of the category selected as Horizontal axis. For the legend: - Select Display legend. The legend lists the possible combinations of specifiers and the item selected under Data series, separated by "/". Apply the Changes to Other Charts Click Apply to All at the bottom of the Chart Properties window. This copies the settings to all charts on that tab, but not to other tabs. Reset to Default Charts Click Reset to Default at the bottom of the Chart Properties window. This resets the current chart to default, but does not affect other charts. Notes - In Box and Whiskers charts, the box includes from 25% (first quartile) to 75% (third quartile) of the data points; this range is also named the interquartile range. The whiskers include the whole range of the data, including potential outliers. - If you deselect an element from the Show/Hide menu, this element is removed from the statistics table, not from the chart. - To remove a statistic from the chart, right-click the header of the dependent variable in the table and click Properties. Click Group Statistics, and deselect that statistic. Batch Statistics Calculation What Do You Want to Do? - Run Batch calculation See Also - Auto-start data analysis Source: EthoVision XT 19 Help - Calculate Statistics, Noldus Information Technology --- ## EthoVision XT 19 - Calculate Statistics - Customize the Group Charts URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-customize-the-group-charts Chapter: EthoVision XT Customize the Group Charts How to Access These Options Do one of the following: - Double-click the chart. - Right-click the chart and select Chart Properties. - Click the Edit Chart Properties button (if there are more charts in the same tab, the first one is selected by default; to customize another one, first click the chart you want to edit). Tip: To apply the same properties to all charts in the same tab, make the changes in one chart and then click Apply to All. Tip: If you want to make a Box and Whiskers chart, you must first specify 5 Number Summary as a group statistic for the variable of interest. You can do this in two ways: (1) in the Analysis profile, open the variable settings window and locate the Group Statistics tab; or (2) in the statistics result table, right-click the variable name and choose Properties, then locate the Group Statistics tab. Change Chart Type, Size and Title Click Chart in the Chart Properties window. - Chart Type. Choose between Bars, Lines, Box and Whiskers, and Box, Whiskers and Data Points. By default, a Bars chart is created. However, if you define time bins, a line chart is created; if you specify 5-number summary in Group Statistics, a box and whiskers chart is created. Select a different type from the list when applicable. Choose Box, Whiskers and Data Points if you also want to plot the data points that generated the charts. Note that each dot represents the value of a variable calculated for a specific trial. - Chart Width. Move the slider or click the arrow buttons to select the required width (range 50–500). To change the width of a chart, you can also drag the vertical line at the right of the chart. To change the height of the chart, drag the upper margin of the chart window. - Display Chart Title. Enter the title you require. The default is [name of dependent variable] – [name of statistic]. Arrange the Data in the Chart Click Data Selection in the Chart Properties window. - Specifiers. These are elements that can create independent data series. What you see under Specifiers depends on the variable you want to analyze. They can be single body points (e.g. center-point for the variable Distance Moved), subjects, variable states (e.g. Mobile, Immobile and Highly Mobile for Mobility), manually-scored behaviors (Grooming and Not Grooming for the behavior Grooming), or combinations of elements, for example Proximity of Nose point to another subject's center-point. Select the specifier that you require. - Data Series. Choose the categories that you want to appear in the legend. If you select Specifiers, for each category on the horizontal axis you get as many data series as the specifiers selected. Note that if you only have one item in the Specifiers box, Specifiers is not in this list. - Example 1: You have the two subjects Control and Treated and selected Relative Movement in the Analysis profile, and selected the body point Nose point for the actor and Tail base for the receiver. The Specifiers of the chart for Relative Movement are Moving To / Nose Point / Control – Tail Base; Moving From / Nose Point / Control – Tail Base; No Movement / Nose Point / Control – Tail Base; etc. - Example 2: You track the center-point of one animal, specified the zones Center and Border, and selected the dependent variable In Zone in the Analysis profile. The Specifiers of the chart for In Zone are Border / Center-point and Center / Center-point. - If you select Results, you get as many data series as the combinations [Result containers] × [Specifiers]. - If you select Results/Zones, you get as many series as the combinations [Result containers] × [Zones selected in Results per Zone in the Data profile] × [Specifiers]. - If you select Zones, you get as many series as combinations [Zones selected in Results per Zone in the Data profile] × [Specifiers]. - If you select an independent variable, you get as many data series as combinations [independent variable values] × [Specifiers]. Important: A category or independent variable is listed only when it identifies each group uniquely. For example, if tracks in a group (selection in the Result container of your Data Profile) have two or more different values of Treatment level, this variable is not shown in the list. In this case, the Group Statistics table shows [multiple values] in the header. - Horizontal Axis. Select what you want to have as the categories on the horizontal axis. - Results: to have the groups defined in your Data Profile as the categories. - [Independent variable name]: to have for example treatment levels or dosage values as the categories (but see the note above). - Zones, or Results/Zones, when applicable. - Time Bins is selected by default when you defined time bins in your Data Profile. Tip: To combine two independent variables, choose one as Data Series and the other as Horizontal Axis. Show the Error Bars Click Data selection in the Chart Properties window. Select Show error bars when you want to plot the standard deviation/standard error as error bars. The option is only available when the statistic is selected under Group Statistics for that dependent variable. To add the statistic, right-click the header of the dependent variable in the Group Statistics and Charts tab and click Properties. Click Group Statistics and select the statistic you require. Sort the Elements of a Chart - In the Chart Properties window, click Data sort order. - Here you can change the sort order of the categories for both horizontal axis and data series. Choose Alphabetical (Ascending or Descending) or Manual (click a category and then click the arrow buttons to move it up or down). --- ## EthoVision XT 19 - Calculate Statistics - Export the Statistics Result URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-export-the-statistics-result Chapter: EthoVision XT Export the Statistics Result Aim To export the statistics of the dependent variables in the results table to an external program, for example to export the values of average velocity to SPSS. Prerequisites - The statistics result is open on your screen. - Select the Data profile and Analysis profile from the lists on the toolbar. - If the table layout does not match the requirements of the program you want to export the result to, see The Statistics Result. Procedure - Choose Analysis > Export > Statistics, or in the Experiment Explorer under Analysis > Export, click Statistics. - Under Export, choose to export Trial Statistics or Group Statistics. - Click the Browse button to select the location for your export file. Its suggested location is the Export Files folder located in your experiment folder. - Under File Type, select either ANSI text (*.txt), Excel (*.xlsx), or Unicode text - default (*.txt). - Next to Missing Value Representation, enter the character that you want to export when the value for a particular cell is missing. - For text export, enter the Delimiter character you want to use to separate columns in the exported file. - Click OK. Options - Missing Value Representation. Missing values in a statistic result are statistics that could not be calculated for that particular cell. For example, if the subject never visited a zone during trial 2, the result for the statistic Latency to First and for the dependent variable In Zone is "-". By default, missing values are exported as "-". Make sure the destination program recognizes the character you specify as a missing value. - Merge Column Headers (selected by default in new experiments). Keep this option selected if you want to export to applications like Excel or SPSS. If you do not select this option, each of the four column headers in the results table will appear in separate rows in the export file. Note that the order of the text elements in the header depends on the order of the headers in the results table. You can change the order using the Layout function. Notes - The name of the export file is Statistics-[Experiment name]. If you export results multiple times to the same location, EthoVision attaches a number at the end of the file name: (1), (2), etc. - Choose Unicode text to export according to the Unicode character set. This supports most world languages, including Chinese. Choose ANSI text to export the data as text files according to the ANSI character set. Choose this option only if the application in which you will open the exported file cannot handle the Unicode character set. - The values exported have a variable number of decimals, depending on the number of integers. The total number of significant digits exported is always six (for example, 1.23456 or 1234.56), or seven if the unsigned number is smaller than one (0.123456). Because of this restriction, there may be a very small difference between the values in the results table and in the export file. This difference is in the order of 1/10000th of the measurement unit. - To change the layout of the exported table, follow Modify the Layout of the Results Table and then export the results. Export Settings for Specific Applications - For R: Export to text. Make sure that R can recognize "-" as a missing value. Use the na.strings parameter to include all possible "no data" characters or strings, for example: loadfile <- read.table("exportfile.txt", header = TRUE, sep=";", na.strings = c("-", "NODATA", ....)) - For SPSS: Select the option Merge Column Headers. - For Systat: Each case must be written in one line. Separator (for text files): space or comma. - For SAS: For text files, use the DELIMITER option to specify the text delimiter if this is other than space. For Excel files, use the PROC IMPORT procedure with the SHEET option to specify the worksheet to import. Use the GETNAMES option to read variable names from the first row of the worksheet. The Statistics Result Learn About - Trial Statistics Result - Group Statistics Result What Do You Want to Do? - Modify the layout of the results table - Sort the results table Trial Statistics Result Aim The Trial Statistics tab gives the statistics for each trial separately. Procedure Choose Analysis > Results > Statistics and Charts. The Trial Statistics tab opens. Default Layout In the Trial Statistics table, each row corresponds to a subject tracked in one arena during a specific trial. The row headers (A) tell you which Trial, Arena and Subject a specific cell corresponds to. Remember that, depending on your experiment design, one Trial may contain one or more Arenas, and one arena may contain one or more Subjects. The column headers (B) show the type of dependent variable (e.g. velocity), the body point (e.g. center point), the type of statistic (e.g. mean) and the measurement unit. Additional headers appear depending on your data selection: - Selection results. If you define two or more Result boxes in the Data profile, the name of the boxes are shown in the first cell (C). - Time bins. If you selected Results per time bin in your Data Profile, extra rows are added, one per time bin, and the headers show the corresponding time periods. For example: 0:00:00 - 0:00:20, 0:00:20 - 0:00:40, etc. (D). - Results per zone. If you selected Results per zone in your Data Profile, the zone names are displayed on rows, together with the body points in those zones (E). What you see in the result table depends on which Data profile and Analysis profile are selected on the toolbar. --- ## EthoVision XT 19 - Calculate Statistics - Group Statistics Result URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-group-statistics-result Chapter: EthoVision XT Group Statistics Result Aim The Group Statistics & Charts tab shows the statistics for the groups of trials defined in your Data Profile. - In the Group Statistics result table, each group is labeled as the corresponding Result container in the Data profile. The statistics are calculated for the trials/arenas/subjects included in that Result container. For how to group data, see Analyze Groups of Tracks. - The dependent variables (e.g. velocity) are those specified in the currently selected Analysis profile. Note: If you use the default Data profile, all trials are grouped. The Group Statistics & Charts table shows the statistics for all trials together. Procedure Choose Analysis > Results > Statistics and Charts and click the Group Statistics & Charts tab. Example In the following example, the Data profile includes two Result containers: Result 1 for treated subjects, Result 2 for control subjects. The groups have been created with Filter boxes, each selecting a value of the independent variable Treatment, Control or Treated. Each Result Container contains two tracks. The statistics are displayed for each Result container. Result 1 contains the tracks marked as Treated; Result 2 contains the tracks marked as Control. In addition, a chart is created automatically for each dependent variable in the table. See Group Charts. How to Read the Group Statistics - Statistics should be read as follows: [Lower level header] of [Higher level header] is [value in cell]. For example: 415.3275 cm is the Mean of the per-trial Total Distance moved for the tracks contained in Result 1. - N is the number of tracks used to calculate the group statistic for that dependent variable. - Group statistics are split in multiple rows when you define results per time bin and/or zone. Results can be split per zone defined in the Data profile, under Results per zone. See Calculate the Results per Zone. - By default, user-defined independent variables are displayed in the table. To show more independent variables, click the Show/Hide button and choose Independent Variables. - If tracks in a group have different values of an independent variable, the text [multiple values] is displayed for that group. How Group Statistics Are Calculated For most dependent variables, the group Mean is the arithmetic mean of the values of the dependent variable reported in Trial Statistics. For angle variables like Heading, Heading to point, and Head direction (but not for Turn angle), circular statistics are used. Group statistics are not weighted. For example, if the total distance moved is 100 cm for trial 1 and 200 cm for trial 2, the resulting group mean is 150, independent of how many samples each track is made of. Similarly, the group Standard error, Standard deviation, and the 5-number summary (Minimum, First Quartile, Median, Third Quartile and Maximum) are calculated from the single values of the dependent variables reported in Trial Statistics. Notes - The number of decimals in the Trial Statistics and Group Statistics is fixed to four. When exporting the results table, the number of decimals varies depending on the number of integers in the value. See Export the Statistics Result. - The dependent variables displayed in Group Statistics & Charts are those defined in the Analysis profile chosen from the list in the toolbar. - The statistics displayed in Group Statistics & Charts are those selected under Group Statistics for that variable in the currently active Analysis profile. Group statistics are always measures of central tendency, either a Mean (with Standard deviation and/or Standard error) or the 5-number summary (Minimum, First Quartile, Median, Third Quartile and Maximum). You cannot calculate, for example, the group total of distance moved. - The group statistics can be calculated for all the trial statistics, except for the standard error, the standard deviation and the variance. For example, you cannot calculate the group mean of the trials' standard deviations of a variable. - To add and remove statistics, right-click any column header for the dependent variable for which you want to add or remove the statistics, and select Properties. On the Trial Statistics and Group Statistics tabs, select the statistics that you require. - See also Analyze Groups of Tracks. --- ## EthoVision XT 19 - Calculate Statistics - List of Trial Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-list-of-trial-statistics Chapter: EthoVision XT List of Trial Statistics N (Sample Size) - For numerical variables like Distance Moved or Velocity, the number of samples used to calculate the mean. - For state variables like In Zone, Mobility, and the behaviors scored manually or automatically recognized, the number of occurrences of the state used to calculate the mean (for example, when a subject visited a zone 4 times, then N=4). For the angular variables Heading, Head Direction, and Heading to Point, the circular standard deviation is given by a formula where R is the resultant vector length and N is the number of samples. Total The sum of all the values. Variance - For most variables, including Turn Angle, Angular Velocity, and Meander, the square of the standard deviation. - For the angular variables Heading, Head Direction, and Heading to Point, the variance is given by 1 - R/N, where R is the resultant vector length and N is the number of samples. Notes (For All Statistics) - Not all statistics listed above are available for every dependent variable. To view the list of statistics for a specific variable, double-click its name under Selected Dependent Variables and click the Trial Statistics tab. - Values of latency and duration can only be a multiple of the sample interval (= 1 second divided by the sample rate). - To add or remove statistics for a dependent variable, double-click that variable under Selected Dependent Variables and change your selection. List of Group Statistics Aim Group statistics are a summary of trials in a specific experimental group. Here a "group" refers to the tracks selected in a Result box in the Data profile. Choose between Group Mean and 5 Number Summary. Note: Group statistics are not available when you only select Standard Deviation, Standard Error, or Variance as Trial statistics. Group Mean - For most variables, including Turn Angle, Angular Velocity, and Meander, the Group Mean is the arithmetic mean of the trial statistics, calculated for each group. - For the variables Heading, Head Direction, and Heading to Point, the group mean is calculated as the circular mean, with N being the number of trials in the group. If you select Group Mean, the following options are available: - Standard Deviation. For most variables, the sample standard deviation of the trial statistics, calculated for each group. For the variables Heading, Head Direction, and Heading to Point, the group standard deviation is calculated as the circular standard deviation, with N being the number of trials in the group. - Standard Error. The standard deviation divided by the square root of the number of tracks used to calculate the standard deviation. This is also the case for angular variables Heading, Head Direction, and Heading to Point. 5 Number Summary This is the Minimum, the Lower Quartile, the Median, the Upper Quartile, and the Maximum value of trial statistics calculated for each group. The method used to calculate quartiles is the N + 1 Basis interpolation, which is also used in SPSS. If the sample size is lower than 3, the lower quartile is the same as the minimum and the upper quartile is the same as the maximum value, which is also the same as in SPSS. Note: With 5 Number Summary you can also plot data in the form of Box and Whiskers charts. You can also show the original data points for better interpretation. Edit the Analysis Profile Aim - To change the properties and settings of a dependent variable - To make multiple instances of a dependent variable - To rename a dependent variable - To remove a dependent variable from the Analysis profile After editing the Analysis profile, re-run analysis via Analysis > Results. To Modify the Properties of a Dependent Variable You can change the properties of a dependent variable at any time, for example to add one more statistic. - Open the Analysis profile that contains the dependent variable you want to modify. - Under Selected Dependent Variables, double-click the dependent variable. - Edit the variable's properties. For how to modify the variable's properties, choose the variable in Dependent Variables in Detail and see the How to Specify section. - Choose Analysis > Results > Statistics and Charts, then click the Calculate button. You can also modify a dependent variable directly in the Statistics result. Right-click the dependent variable header and select Properties. Change the properties of the variable, then click the Calculate button. To Calculate Multiple Instances of a Dependent Variable You can add multiple instances of a dependent variable to an Analysis profile. This is handy when you want to compare the effect of different settings on the same dependent variable, for example two instances of Mobility with different Mobility thresholds. - Open the Analysis profile that contains the dependent variable. - Right-click the dependent variable under Selected Dependent Variables and select Duplicate. A new row is appended under Selected Dependent Variables. - Double-click the new row and set the properties you require for the new instance of the dependent variable. Additional instances of a dependent variable are given names with a progressive number (for example, Distance Moved 2, Distance Moved 3, etc.). You can rename those variables. To Rename a Dependent Variable - Open the Analysis profile that contains the dependent variable. - Under Selected Dependent Variables, right-click the variable's name and select Rename. - Type in the name you want to give and press Enter. To Remove a Dependent Variable from the Analysis Profile Under Selected Dependent Variables, click the variable's name and press Delete, or right-click the variable's name and select Delete. --- ## EthoVision XT 19 - Calculate Statistics - Modify the Layout of the Results Table URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-modify-the-layout-of-the-results-table Chapter: EthoVision XT Modify the Layout of the Results Table Aim To make sure your results are grouped and displayed in the most useful way possible. This is particularly the case when exporting the results to another application. Note: This applies to Trial Statistics and Group Statistics. Prerequisites - You have run analysis (Analysis > Results > Statistics and Charts > Calculate). General Procedure Click the Layout button on the toolbar, or choose Show/Hide > Layout. By default, the results table shows the dependent variables and their statistics on the columns, and the trials on the rows. Add a Header to the Table Example: In the Trial Statistics page, add the independent variable Treatment, so that each row (trial) is labeled with the value of Treatment, either Compound or Vehicle. - Click the Layout button on the toolbar. - In the Available box, click the header you want to add. - Click the arrow button which points to the On Rows box. - Optionally, move the header up in the list to have trials separated based on the values of Treatment. Notes: - If you click the arrow button which points to On Columns, the variable is placed in columns. - To add a new dependent variable, do this in the Analysis profile, then return to Analysis > Results > Statistics and Charts. Remove a Header from the Table Example: Remove the Arena name from your table headers. - Click the Layout button on the toolbar. - In the On Columns/On Rows box, click Arena. - Click the arrow button which points to the Available box. - To remove measurement units, in the Layout window de-select Measurement units. - To remove the detail of a dependent variable, like the body point name, in the Layout window de-select Detail about variable. Note: Removing an element from the headers does not aggregate the results under that header. For example, if you remove Arena, all results are still displayed for each arena separately. If you want to aggregate results, see Define Groups of Tracks. Move a Header Between Rows and Columns Example: The dependent variables (Velocity, In zone, etc.) are placed in columns. Move them to the rows, so that each row represents one trial/dependent variable combination. - Click the Layout button on the toolbar. - In the On Columns box, click Variable with detail. - Click the arrow button which points to the On Rows box. Swap Rows and Columns Select each item under On Columns and move it to On Rows. Next, select the items originally under On Rows and move them to On Columns. Modify the Table Hierarchy To place a header to a higher level in the table, click the element in the On Columns or On Rows box, and then click the Up button. To place an element lower in the table hierarchy, click the element in the On Columns or On Rows box, and then click the Down button. Note: It is not possible to put Time bin above the Selection Result. Show and Hide Part of the Table - Click the Show/Hide button at the top-right corner and select the corresponding element. - In the window that appears, select the trials, arenas, subjects, etc. that you want to have in the table. - Click OK. Remove Empty Rows or Columns Tip: Do this if you have many rows or columns that are empty and you want to export only the rows and columns with significant results. In the Layout window, select Hide empty rows or columns. Note: Rows and columns are not removed if at least one dependent variable is calculated for that row or column. Reset the Table Layout To return to the default layout, click the Layout button and in the Layout window click the Reset Default button. Move the Headers in the Group Statistics Results Table The results of group statistics shows the group statistic under the trial statistic. For example, you may find the group statistic Mean under the trial statistic Total for distance moved, meaning that the result is the mean value of the total distance moved calculated for each trial in that group. When you click the Layout button, the item Group Statistic with units is selected under On Columns. You can move the Group statistics headers and the units to the table rows or move them to a higher level in the table. - Move a header between rows and columns - Modify the table hierarchy - To have the track groups in different columns instead of rows, select Selection Result and move it to On Columns. Special Headers in the Layout Window - Statistic with unit and Group statistic with unit show the names of the trial statistics and group statistic selected in the Analysis profile, respectively. If you move those headers in the table, the measurement units are moved to the same location. - Selection Result refers to the dataset specified in the Results boxes of the Data profile. If the Data profile includes two or more Result boxes, for example to group tracks, the headers for the corresponding boxes are automatically added to the table. If you remove Selection Result from the rows and columns, the results for different groups are still kept separate, because the Data profile defines the grouping. --- ## EthoVision XT 19 - Calculate Statistics - Results Table Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-results-table-notes Chapter: EthoVision XT Results Table Notes The group specification remains active even when headers disappear. If you want to merge results, use another Data profile. - Time bin refers to the time bins defined in the Results box of your Data profile. If you do not define time bins in the Data profile and select Time bin in the Layout window, the headers Start-End are added; no time bin is created. See Results per Time Bin. - Zone refers to the zones specified in the Results box of your Data profile. If zones are not specified, analysis is done for the whole arena and the table shows In Arena. See Calculate the Results per Zone. - The independent variables that you have defined are not shown in the table by default. To export the table with the independent variable values as an analysis factor, click the Layout button and move that variable to On Rows or On Columns depending on how your statistics program treats analysis factors. Example: An independent variable Group with possible values Mutant and WT has been defined in the Trial List. To have the values of this independent variable displayed for each trial, click Layout, select the variable Group on the left and move it to the On Rows box. - Missed Samples. This is the percentage of samples that EthoVision XT could not analyze. To reduce this percentage, see Factors Affecting the Occurrence of Missing Samples in Sample Rate. - Subject Not Found. This is the percentage of the analyzed samples in which EthoVision XT could not find the subject. A lower value indicates high reliability of data. To reduce this value further, optimize the lighting conditions and adjust the Detection Settings to improve detection rate. - If you select track segments with Nesting, there is no special header for them. However, remember that the results are calculated over the track segments defined, not the entire tracks. See Also - The Statistics Result - Trial Statistics Result - Group Statistics Result Sort the Results Table Aim - To sort the results table based on the row headers. - To sort the results table based on the values in a column. - To change the order of and group the dependent variables in the results table. Prerequisites - You have run analysis (Analysis > Results > Statistics and Charts). Sort the Table Rows Based on Their Headers Example: Sort the results table based on the header Treatment, an independent variable with values Drug and Vehicle. - Click the Layout button and under On Rows move Treatment to the highest position in the list. See Modify the Layout of the Results Table. - Right-click one of the headers you want to sort, and select Sort Ascending or Sort Descending. Note: If you sort the rows based on the headers on the second, third, etc. column, the rows are sorted only within that level, not globally. For example: to have all rows marked with Subject 1 at the top of the table, then all rows with Subject 2, etc., click the Layout button and move Subjects to the top of the list under On Rows, then sort the subject headers. Sort the Table Rows Based on Cell Values Example: Sort the table based on the values of Frequency of Zone Entries. Right-click one of the cells containing the values you want to sort, and select one of the two sorting options. Sort the Dependent Variables in the Results Table Example: Sort the results table by the dependent variables; first Distance Moved, then Movement and then In Zone. - Click the Show/Hide button at the top-right corner and select Dependent Variables. - In the window that appears, select a dependent variable and click the Up and Down buttons to move a variable to a higher or lower position in the table. The dependent variable at the top of the list in that window is shown in the first row or column in the result table. Group Charts How to Read the Group Charts Charts are generated automatically from the results in the Group Statistics & Charts table. Charts are generated for the dependent variables Distance Moved, Velocity and In Zone (on separate tabbed pages). The horizontal axis shows the zones (In Border and In Center). Two data series (from the Result containers Control and Treated) are plotted. Chart Tabs Each tab refers to a dependent variable defined in the Analysis Profile. A tab may contain one or more charts, one for each Trial Statistic specified for that dependent variable. Notes - A chart is not created for the Trial statistics Standard Deviation, Standard Error and Variance. - Charts in EthoVision XT have limited formatting options and are mainly meant for inspection purposes. If you want to make a chart for a publication, export the statistics table to Excel or a statistics program. - If you delete a dependent variable and subsequently add it again to the Analysis profile, the properties of the new chart are set to default. - Chart settings are stored for each combination of data profile and analysis profile. If you make an exact copy of a data/analysis profile, the resulting charts have default settings. - Effect of Data Selection: Results per Time Bin. If in the Data profile you specify Results per time bin, time bins are always shown on the horizontal axis. The first value is 0:00:00 and represents the results calculated in the first time bin (for example from 0 s to one minute). - Effect of Data Selection: Results per Zone. If in the Data profile you specify to Calculate the Results per Zone, you can show the zones on the horizontal axis or as data series. See Customize the Group Charts. - If you specify both time bins and results per zone, time bins are displayed on the horizontal axis and zone statistics as data series. - If you specify more than 1000 time bins in your Data profile, the group charts are not displayed. To Export Group Charts You can export one chart at a time. To export a chart as an image file, do one of the following: - Right-click the chart and select Export Chart. - Click the chart and then click the Export Chart button just above the chart. The default file name is the same as the chart title. Four formats are available: Portable Network Graphics (*.png), JPEG file (*.jpg), Windows bitmap (*.bmp), and Graphics Interchange Format (*.gif). To copy the chart to an external program, right-click the chart and select Copy, then paste it to the other program. --- ## EthoVision XT 19 - Calculate Statistics - Track Visualization Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-track-visualization-settings Chapter: EthoVision XT Track Visualization Settings Customize the Color of Missing Samples Missing sample points are always visualized in the track plot. You can change the color of missing samples to distinguish them more easily from the actual data. The current color for missing samples is indicated next to Missing Sample Color. To change the color for missing samples, click the button and select a new color in the Color window. Display Background, Arenas and Zones Aim To customize how the background image, the arena and the zones are displayed in Track Visualization or Integrated Visualization. Customize the Background (for Track Visualization) - Choose Analysis > Results > Plot Tracks. - On the toolbar, click the Show/Hide button and select Background. - Select one of the following, then click OK. - Plain. To have a uniform background. Click the button next to this option to select a color. To select colors other than the basic ones, click the button Other. - Captured Image. If you want to have the captured image from the Arena Settings as background. Show/Hide the Video Image (for Integrated Visualization) Choose Analysis > Results > Plot Integrated Data. The Video window is shown by default. To hide the Video window, click the Show/Hide button on the toolbar and deselect Video Window. Show/Hide Arenas and Zones in the Track Plots Arenas, zones and points can be displayed on top of the background as overlay objects. The color of each arena and zone depends on the color chosen in the Arena Settings. - Choose Analysis > Results > Plot Tracks or Plot Integrated Data. - Click the Show/Hide button on the toolbar and select Arena Features. - Select the arena feature you want to have displayed. Arenas and zones are shown in a semi-transparent color, so their appearance also depends on what you select as background. If you want to change the color of an arena or zone group, open the appropriate Arena Settings, click the correct Color row and select the color of your choice. For a multi-arena setup, you cannot select to view some arenas and not others. --- ## EthoVision XT 19 - Calculate statistics: procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-calculate-statistics-procedure Chapter: EthoVision XT Calculate Statistics: Procedure Aim To calculate descriptive statistics of one or more dependent variables. Prerequisite - You have smoothed data (optional). - You have selected data in a Data profile (optional). To Calculate Statistics - Choose Analysis > Analysis Profile > Open (to open an existing profile) or New (enter a name for the new profile), then click OK. - Choose the dependent variable. Click the Add button next to the dependent variable you want to use for analysis. If you do not see that variable name, click the More button. TIP: In most cases Distance moved and Velocity are already selected. - In the dependent variable-specific tab, select the properties of the dependent variable. For details on dependent variables, see Dependent Variables in Detail. - Choose the Trial statistics. Click the Trial Statistics tab, and choose the statistics you want to calculate for each trial. - Choose the Group statistics. Click the Group Statistics tab, choose the statistics you want to calculate as a summary for a group. EXAMPLE: You want to calculate the average and standard error of the Total distance moved, for Control and Treated subjects (we assume here that you create such groups in the Data profile; see Analyze groups of tracks). Choose Distance moved as a dependent variable, Total as a Trial statistic, and Mean and Standard Error as Group statistics. - Repeat steps above to add more dependent variables. - Choose Analysis > Results > Statistics and Charts, then click the Calculate button on the toolbar. - The Statistics and Charts table appears on the screen. Notes - Some dependent variables are available if you have one or more of the following add-on modules: Social Interaction, Rat/Mouse Behavior Recognition, Trial and Hardware Control. - You can only select specific body points if your experiment is set to Center-point, nose-point and tail-base detection. - You can change the properties or delete a dependent variable already selected. You can also add multiple instances of a dependent variable, with different settings. See Edit the Analysis Profile. - You can also calculate statistics in batch mode. See Batch Calculation. See Also - The statistics result Statistics Available Statistics are a summary of the values of the dependent variable calculated for all the samples in your tracks (or the segments you have selected in the active Data profile). For each dependent variable you select in the Analysis profile, you can choose Trial Statistics and Group Statistics. Click on the corresponding tab to select the statistics you want to have in the results table. See Also - List of Trial statistics - List of Group statistics Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Camera position and settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-camera-position-and-settings Chapter: EthoVision XT Camera Position and Settings TIP Watch the video Set Up the Cameras, in the EthoVision XT video tutorial (Help > Video Tutorial). Attach the Cameras With the Ceiling Mount With the Autopole For this configuration you need an Autopole, a SuperClamp and a camera adapter (all shown in the following figure). The Autopole range is 2.1-3.7m, or up to 5.7m with the extension (sold separately). NOTE The elements shown here may slightly differ from those you have purchased. How to attach the camera to the SuperClamp: - Connect the camera to the SuperClamp through the brass stud connector or the camera adapter. - The Autopole gets clamped between the jaws of the SuperClamp. Turn the handle to tighten the SuperClamp to the Autopole. Horizontal installation is mainly for top view tracking. For this you need the Autopole and the SuperClamp. Vertical installation is for top view tracking and side view tracking. For this you need the Autopole, the SuperClamp and a camera adapter (see above). For more flexibility you can use a variable friction arm attached between the SuperClamp and the camera adapter. Suspended Ceilings If you need to attach the camera to suspended ceilings, you can get a special mount that has two parts which move like scissors. Move them to open up the mount and it will fit over the framework of the suspended ceiling, then close them to hold. Attach the camera adapter and then the camera. This is a temporary mount, it is sturdy enough but you can always open the mount to remove it from the ceiling and place it elsewhere. If you have a suspended ceiling it's probably the best solution. Cable Length The maximal length of the cable between camera and computer depends on the type of camera you use. - For GigE cameras and Analog cameras: 100 m. - For USB 3.0 cameras: 5 m. You can increase this length by means of an active extension cable (not tested though). See Connect the USB 3.0 Camera to the PC. Things to Check - Position the camera perpendicular to the plane in which the animal moves. If this is not the case, the shape of the arena and subject inside will appear distorted on the screen and calculated distances, velocities and spatial statistics will be incorrect. - Anchor the entire setup. Secure the position of the arena, camera and illumination relative to each other, and fasten the camera zoom, focus control and aperture settings. - Adjust the zoom setting (or select the appropriate lens) and focus the lens until the entire experimental arena is visible on the screen and is displayed in focus. - When using multiple cameras, pay attention to the zoom settings. These should be in such a way that the apparent size of the arenas is the same since you calibrate the distance for all the cameras (Shared calibration). If that is not possible, make one calibration for each arena (Unshared calibration). See Calibrate Multiple Arenas. - Turn off all automatic camera settings: focus, gain, exposure (auto-iris), anti-shake. - Adjust the camera aperture until the image shows maximal contrast. Depending on how bright your IR setup is, you might need to open the aperture on the lens all the way (do this first) and/or adjust the camera's Gain (Raw) and/or adjust the Exposure time in Pylon Viewer. See Configure the Digital Camera. See also Lighting Setup. View the Camera Image in EthoVision XT - IMPORTANT When using digital cameras, close the camera software Basler pylon Viewer before operating the camera in EthoVision XT. - Create a new experiment. - Choose Setup > Experiment Settings. - Set the Video source to Live tracking. For details, see Video Source. - Click the camera button (for single cameras) or the eye button (for multiple cameras in merged view). Image Magnification If you need to get higher magnification images than is available with a standard lens (get 'closer'), then you can use one of the following techniques. Macro Lens A true macro lens, that is, a lens of a magnification of at least 1:1 (expressed as 'real world': CCD chip size) usually gives good quality images. However, it is often expensive and probably gives a lower magnification than either a close-up filter or an extension ring. Extension Rings An extension ring inserted between the camera body and the lens enables you to focus on subjects closer to the camera, and so provides a greater magnification. An extension ring is usually cheaper than a true macro lens, but more expensive than a close-up filter. It may give a reduction in optical quality, and it will reduce the light intensity of the signal, but you can use it to get very high magnifications. Close-Up Filter This is a lens attached in front of the normal lens, to give greater magnification. It is also known as a close-up lens. It works by shortening the focal length of the lens while keeping the lens-to-camera distance constant, which increases the magnification of the lens. The strength of a close-up filter is measured in diopters, which is the fraction by which the lens' focal length is shortened. Thus, a +3 lens reduces the focal length of the lens to which it is attached by 1/3. A close-up filter is usually cheaper than a macro lens or extension ring, but it gives lower magnification, and poorer optical quality. Microscope EthoVision XT tracks well from cameras attached to microscopes. Use back-lighting to maximize contrast. Change Color to Monochrome If you have a color camera, you can temporarily change it to monochrome by changing the Pixel format setting. For Basler cameras: - In pylon Viewer, change the Pixel format to Mono8. See Set the Pixel Format. - In EthoVision XT, set the Color space to Y800. See Adjust Camera Settings in EthoVision XT > Color Space. See also Settings for the Color Camera. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Camera Recording Duration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-camera-recording-duration Chapter: EthoVision XT Duration Click the link below for the camera type you are using. There you will find the main settings we used in our tests: the maximal resolution, frame rate and duration. - In all tested configurations, EthoVision XT tracked the nose-, center- and tail-base point of one subject with the Contour-based method (that is, no Deep learning) and recorded video simultaneously. Video was recorded without audio. When using multiple cameras, one arena was defined for each camera. Each section reports which detection method worked with zero (or a low percentage of) missed samples. - If you want to track the subjects using Deep learning, there are further restrictions. See Deep Learning: Requirements. - If a test was successful with Deep Learning (DL in the tables in the following sections), then it is assumed that Contour-based tracking (C) also works. - The figures report the maximum time tested. Acquiring longer trials is possible in principle, but you must test your configuration thoroughly. Run a test trial with the desired resolution and frame rate, and check that the resulting video does not contain too many missing video frames, and check that the tracks obtained do not contain too many missing samples, for example less than 5%. See View the Detection Statistics. - IMPORTANT: When tracking for more than 24 hours, always reboot the PC after every trial to refresh the PC resources, the RAM specifically. Failure to do so could result in crashing, which can corrupt the experiment, or the recorded video. - IMPORTANT: When you track many animals in multiple arenas, simultaneous tracking and video recording may go beyond the processor's capability. In those cases, choose Save Video, Track Later in the Acquisition Settings window to be able to record at higher resolution without skipping video frames. See Record Video, Then Acquire a Trial. - IMPORTANT: The test results reported here may differ from those you experience, even when using the same camera, PC and graphics card. For example depending on the lighting and the camera settings. Click the camera type that applies: - GigE Cameras - USB 3.0 Cameras - Analog Cameras Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Color markers URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-color-markers Chapter: EthoVision XT Color Markers General Information - Use a color scale (for example from a paint company) to find out which colors are most easily recognized by EthoVision XT in your setup and lighting conditions. Do this before applying color markers to your animals. - Use colors that have different hue values. For example, use red and green and not red and orange. - For birds and animals in general that perceive color in the red-green wavelength range, using red markers is not advisable as it looks like blood, and may influence the subjects' behavior. Rodents have dichromatic vision, that is, they perceive wavelengths around the blue and the green, so probably red is seen as gray or a mix of blue and green. Albino animals have heavily impaired vision, both in acuity and color perception. - If you want to use red together with orange or pink, provide more light around (by means of additional lamps) and then close the aperture of the camera lens. - If the color of your marker is also present elsewhere in the arena, you can get rid of it by using a minimal marker size. - Marking your animals may stress them, and therefore affect their behavior. If necessary, ensure that you select a marking method that lasts for a longer period of time. - To improve color discrimination in EthoVision XT, you can alter the Saturation settings of the video image (this only applies for live tracking). In the Detection Settings window, under Video click Image Quality. Alter the Saturation value and check in the video window if the markers are more distinguishable. However, before altering the Image Quality always try to optimize the lighting and camera aperture settings. Note that if you alter the Image Quality values you need to redefine the color detection (click Identification for each subject). Marker Characteristics - Make sure that the marker is visible as much as possible; preferably place it on the center of the animal's backbone. - Make sure that the marker is as round as possible. This will ensure that the relative movement of the center of gravity of the marker is the same in all directions when the edges of the marker change due to posture changes or otherwise. For color marker tracking it will help to prevent the jitter of the marker. - When you use marker assisted tracking, make sure the marker is not too big; the marker can interfere with proper detection of the body contour. For example, make sure that a dark marker on a white animal does not cover the complete width of the animal because it can cause the body to be split in two. Markers for Rodents and Other Small Mammals There are several ways to color mark small mammals like rats and mice. Color mark as much of the head and back as possible. This way the mark is always visible, also when the animals rear or turn. - Livestock markers are intended for large animals but can also be used on smaller animals. These markers come as paint sticks and spray cans, and are available in many colors including fluorescent ones. The markers are weather-resistant, non-toxic and they stay on for one or two days. - Fluorescent tubes can be used for color-tracking in the dark. It is possible to mark rats with fluorescent markers and illuminate the arena with UV-light (350–400 nm, 2 lamps of 1.2 W each). The fluorescent spots on the rats appear as patches of different color against a dark background. EthoVision XT can then effectively separate the two animals (source: J.P. Johansson and M.L. Carlsson, Institute of Clinical Neuroscience, Göteborg University, Göteborg, Sweden). See Tracking Colors in the Dark. - Hair dyes — the fur of rats and mice can be marked with commercial products for dyeing human hair. Dark fur can be bleached (like dark human hair, to make it blonde) before coloring. Hair dyes are available in many bright colors, and provide long-lasting coloration. Schwarzkopf PolyColor Hair Color Cream, for example, can be applied to a rat's fur with a cotton swab. - Permanent marker pens (for example, Edding or Marks-A-Lot) present a cheap and easy way to mark small mammals. Take care to make a large and uniform blob. This method may only work for a short period of time as many species may remove the mark by grooming. - Chalk ink markers can be used to mark rodents. They are available in a variety of bright colors. Their main advantages are that they are not toxic, are readily available and inexpensive, and, in contrast with other marker types, can be applied directly to dark fur without bleaching it first. Coloration may last several hours. It is advised not to mark the animals just before you start a test, because the handling of the animals might affect their subsequent behavior. If you use a marker that stays on the animal for only a short period of time, you should habituate the animal to the marking procedure. - Colored jackets can be used to color-track mammals with colored fur like cats. Jackets cover most of the cat's back, and can be provided with Velcro strips, so one can place pieces of cloth of different colors to test optimal color combinations. Orange vests may give problems when animals are red-haired, so they should be replaced by either bright green, yellow, or pink. Markers for Large Mammals You can use livestock markers to mark large animals such as cows, sheep, and pigs. Markers for Birds - The feathers of birds can be marked with commercial products for dyeing human hair or permanent marker pens (see the Small Mammals section above). - Seabird ecologists often use picric acid (2,4,6-trinitrophenol, TNP) to mark their birds. You paint a dab of this yellow liquid on the feathers. It is permanent and very bright yellow, although it turns orange in the sun. To use it to mark animals you dissolve it in an excess of ethanol. If the acid (a powder) dries, it becomes explosive, so it is important to keep it dissolved (source: J. Blount, Division of Environmental and Evolutionary Biology, University of Glasgow, UK). Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Color markers (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-color-markers-continued Chapter: EthoVision XT Markers for Fish - Fish can be color marked by attaching plastic pearls. This technique has been used successfully in Mediterranean damsel fish (Chromis chromis, size: about 9 cm long) and trout (about 25 cm). Colored pearls can be bought from a toy store or a warehouse. Use bright colors that are as distinct as possible. For damsel fish pearls of 1 cm are used and for trout pearls of 8 mm are used. Damsel fish. The pearls can be attached under the dorsal fin with blue non-resorbable surgery polyamide mono filament (for example, from B/Braun), using a surgical needle under anaesthesia. The fish can be anesthetized by placing them in a small tank with 2-phenoxy-ethanol (0.3 ml/l for the damsel fish) for five minutes, before attaching the pearl. The bottom and sides of the arena have to be very dark. The pearls do not significantly impair swimming in damsel fish (Source: M. Ylieff, Institut de Zoologie, Université de Liège, Belgium). Trout. The pearls can be attached at the base of the first ray of the dorsal fin. Use a curved needle and normal fishing-line to attach the pearls to the fin. X-ray images showed no injury after several weeks using this method. The fish can be anesthetized by placing them in a tank with 2-phenoxy-ethanol (0.3 ml/l), before attaching the pearl. - Visible implant fluorescent elastomer (VIE) tags are produced by Northwest Marine Technologies (NMT). VIE material is implanted beneath transparent or translucent tissue (it may become difficult to detect it beneath pigmented tissue). The material is injected as a liquid and soon turns into a pliable, bio-compatible solid. VIE colors are well visible under normal lighting conditions and have greatly enhanced visibility under ultra-violet light or with other fluorescence enhancing techniques. You can test which colors work best in your own setup with a color test patch from NMT. (Source: J. Merilä, Evolutionary Biology Centre, Uppsala University, Sweden and Delcourt et al. (2012). Behavior Research Methods: 590–600). Markers for Reptiles Nail polish (available in many colors) can be used to mark lizards. The mark usually lasts 10 days in small (up to 10 cm) lizards in the field. (Source: M. Massot, Laboratoire d'Ecologie, Université Pierre et Marie Curie, Paris, France). Markers for Amphibians For amphibians you can use visible implant fluorescent elastomer (VIE) tags (see Fish above). They work fine with small tadpoles. Markers for Insects - Acrylic paint (for example, Royal Talens Amsterdam deco) can be used to mark insects. The paint can be applied with a fine brush or thread. You have to hold the insect with forceps until the paint is dry (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands; S. Belmain, Natural Resources Institute, Chatham Maritime, UK). - Some species of parasitic wasp develop a colored abdomen when you feed them honey with a non-toxic dye, as used for coloring food. The dyes can be obtained from a normal bakery. The advantage of this method over marking with paint is that you do not have to anesthetize the insects (which may influence their behavior and survival). The method will work best in insects with unpigmented abdomens (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands). - Mosquitoes can be fed with a sugar solution in water containing fluorescent dyes. Blue-black light is used to illuminate the subjects. See the paper by Sarkar et al. 2017, International Journal of Mosquito Research (6): 5–9 (animals were not video-tracked though). Other techniques using fluorescent powders or dyes are described by Verhulst et al. (2013), Parasites & Vectors: 200–206. - For insects you can also use visible implant fluorescent elastomer (VIE) tags (see Fish above). - Aphids have successfully been color marked with fluorescent powders. The powders that are fluorescent under ultraviolet light can be obtained from Day Glo, Cleveland, Ohio. For optimal detection, a high intensity UV long wave UV·366 nm lamp can be used. To apply the powder to the aphids, gently dust the powder with a powder insufflator. Make sure each aphid gets at least 10 grains of powder. For more information see Thomas et al. (1997). Journal of Agricultural Entomology (2): 187–198. - Ants can be color marked with a small drop of paint on the thorax or the abdomen. Anesthetize the ant with CO₂. To restrain the ant during painting, use a sponge with a single strand of hair attached to it. Place the ant under the hair and apply the color mark. Transfer the ant to a plastic tube and allow the paint to dry for approximately 20 minutes. After 24 hours, the ant can be used in experiments. - For a review of the marking techniques see Hagler & Jackson (2001). Annual Reviews of Entomology: 511–543. Markers for Zooplankton - Nanoparticles known as Quantum dots have been applied to the carapace of crustaceans Daphnia sp. Like any other fluorescent molecule, they must be excited with light of one wavelength in order to emit fluorescence at a longer wavelength. Among the advantages of these markers is great photostability — animals can be tracked for up to 24 hours after labeling, without loss of signal due to photo-bleaching. Note that some quantum dots may be toxic to animals. For more information see Lard et al. (2010). PLoS ONE (10): e13516. doi:10.1371/journal.pone.0013516. Tracking Colors in the Dark If you want to apply color markers and track the animals in the dark, you need lighting conditions that allow EthoVision XT to detect the marker and detect the contour of the animals. To track colors in the dark, combine fluorescent markers with ultraviolet (UV) light. UV light makes the marker emit visible light, which is then detected by the camera. EthoVision will track the marker as it would normally do in daylight. To track the contour of the animal, you must also use light sources other than UV. If you only use UV light, the contour of the animal will not be seen. A couple of solutions that may work: - Use visible light. Make sure that the contrast between animal and background is maximized. - Use infrared (IR) light. Some good color cameras are also sensitive to IR light. You can then use IR light to enhance the contour of the animal, provided that the camera lens does not have an IR-block filter. Note that fine-tuning this setup may take considerable effort and time. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Color markers (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-color-markers-continued-4TS Chapter: EthoVision XT Useful Web Sites - Carmel livestock markers: http://www.livestockmarkers.com - La-co livestock markers: http://www.allweathermarker.com - Net-Tex livestock markers: http://www.net-tex.co.uk and search for "marker". - Edding markers: http://www.edding.com - Marks-A-Lot markers: http://www.avery.com - MS Schippers (livestock or rodent markers): https://www.schippers.nl. See the product line "MS Merkstift" (in Dutch). - Chalk Ink markers: http://www.chalkink.com. Choose a 15-mm broad tip marker. - Schwarzkopf hair dyes: https://www.schwarzkopf.com - Royal Talens acrylic paint: https://www.royaltalens.com/en/products/acrylic-colours/ - B/Braun surgical sutures and needles for attaching pearls to fish: http://www.bbraun.com - Northwest Marine Technology fish markers: http://www.nmt.us/ - Invitrogen quantum dots: http://www.thermofisher.com/nl/en/home/brands/invitrogen.html - Fluorescent powders: https://www.dayglo.com/ Settings for the Color Camera Aim: To make sure that the tracking of color markers in EthoVision XT is optimized. This topic applies to the Basler color cameras acA1300-60gc and acA1920-40gc. Note that the Basler acA1300-60gc is no longer officially supported and therefore not tested by Noldus. Prerequisites You have installed the camera, its driver software and EthoVision XT. See Install GigE Cameras. Settings in Pylon Viewer The procedure below refers to the options available in the camera software. Most of the options are also available in EthoVision XT. See Adjust Camera Settings in EthoVision XT. - Close EthoVision XT and open pylon Viewer. NOTE: The Basler pylon Viewer software is installed automatically when you install the camera drivers. - From the Window menu select Features - All. - In the Devices panel, double-click the item Basler under GigE. - Open the item Image Format Control. Next to Pixel Format select: - YUV 422 Packed for the camera acA1300-60gc. Note that this camera has not been tested with EthoVision XT 19. - Bayer RG 8 for the camera acA1920-40gc. - Click Color Improvements Control. - Click the Continuous Shot button on the tool bar to view the live image. - Point the camera at a piece of white paper, so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - To save the settings, see Save the Camera Settings. - Close pylon Viewer and open EthoVision XT. - Open your experiment and in the Experiment Settings select Live tracking and the color camera. - Click the camera button and then in the window that appears click the Format tab. Choose the video resolution and frame rate. - Next to Color space select: - For the camera acA1300-60gc: UYVY or YUV. - For the camera acA1920-40gc: BYRG. If the image stays black and white, select UYVY or YUV, then select BYRG again. - Select the resolution and frame rate. See what has been tested for the Basler acA1920-40gc. - Check the Current frame rate. If this is significantly lower than the rate you set, choose a lower resolution. Settings for Low Light Conditions When tracking animals in low light, you can adjust the camera settings in such a way that the colors are more apparent. The settings below apply to the camera acA1920-40gc. In pylon Viewer, do the following: - Under Analog Controls, set Gain to for example 240 or higher if necessary. - Next to Gamma Selector, choose User. - Next to Gamma, choose 1.0. - Increase the Digital Shift for example to the recommended value or higher if necessary. - Under Acquisition Controls, set Exposure Time to for example the recommended value in µs. A higher value is not recommended. For adjusting a specific color (usually not necessary if the white balance has been done correctly): - Next to Color Adjust Enable, select the option. - Next to Color Adjust Saturation, adjust color saturation (per color). Color to Monochrome If you have a color digital camera, you can temporarily change it to monochrome. - For Basler cameras: see Change Color to Monochrome. NOTE: This does not make your color camera infrared-sensitive. For that, you must either remove the infrared block filter (see below) from your color camera or use a monochrome GigE camera. TIP: Basler cameras have model numbers like this: acA1300-60xx, where: - xx = gm means monochrome. - xx = gmNIR means Near Infrared, that is, monochrome with extra sensitivity to infrared light. - xx = gc means color. Color to Infrared-Sensitive Most color cameras are not infrared-sensitive. To make them more infrared (IR)-sensitive: - Set them to monochrome (see above). - Remove the infrared-block filter, if this is present. For how to do so, see below. Infrared-Block Filter Some color cameras may have a built-in infrared block filter which prevents them from seeing some infrared light. If you bought a Color GigE camera from Noldus prior to July 2018, you can remove this filter to make your color camera IR sensitive. NOTE: Color GigE cameras of model acA1300-30gc purchased after July 2018 from Noldus had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). If you have such a camera you can skip this procedure. - Remove the lens from the camera. - Check that the filter is present: you should see two circular holes at the sides of the filter. - Use a small Allen key or a similar object to lift the filter. - Put the lens back on the camera. See Also - Lighting Setup Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Complex Data Selections - Complex Data Selections URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-complex-data-selections-complex-data-selections Chapter: EthoVision XT Complex Data Selections Combining Selection Boxes Selection boxes can be combined in a variety of ways to create complex data selections. Basic Rules for Combining Selection Boxes Boxes in a Linear Sequence (AND Logic) When you line up boxes in a single sequence, the data in the Result box (and thus selected for analysis) satisfy all conditions set by the boxes (AND logic). Example: Select the samples in the center of the open field (Nest; second box), AND only for subjects with the value of the independent variable Treatment = Injected (Filter; third box). Boxes in Parallel (OR Logic) When you split a sequence in two or more branches which end in the same Result box, the data in the Result box (and thus selected for analysis) satisfy either one condition or another set in those branches (OR logic). Example: Select all samples when the animal was either Moving (Nest, top box) OR Mobile (Nest; bottom). Multiple Filters To Filter by Two or More Values of a Variable Specify those values in one Filter box. Example: A Morris water maze experiment contains a number of trials of different type, either training or probe. Training trials are marked with t1, t2, etc. according to their position in a sequence, using the user-defined variable Trial type. You want to analyze the tracks for type t1 and t2, not probes (p). - Create a Filter box corresponding to the filtering variable. - Specify the values of the variable. - Insert the Filter box in the sequence. To Filter by Two or More Variables Create one box per variable. Connect them between the Start box and the Result box using the logic you require. See Basic Rules for Combining Selection Boxes. Example: Your experiment contains a number of tracks recorded for two groups of subjects, Young and Aged, and on a variable number of days after the treatment. You want to calculate the statistics for the Young subjects, and for Day 1 after the treatment. Since the selection criteria depend on different variables, place the Filter boxes one after the other; which comes first does not matter. Multiple Nesting Criteria To Nest over Multiple Values of the Same Variable - For variables like In Zone, specify those values in one Nest box. - For variables with more than 2 states, like Body Elongation State, Activity State, and Mobility State, create one Nest box per value, and combine the resulting boxes with OR logic. Example 1: With the Variable In Zone You want to visualize the track segments when the subject was entirely in one of the open arms of the Elevated Plus Maze. Each open arm has been defined as a zone. - Create a Nest box corresponding to the variable; in this example, In Zone. - Specify your selection. - Insert the Nest box in the sequence. Analysis is done on the samples collected when the center point, nose-point, and tail-base of the subject were all in either open arm 1 or open arm 2 of the plus maze. - If the zones do not overlap, from the In the Following Zones list select When in Any of the Selected Zones (OR logic). - If the zones do overlap, and you want to select the time when the subject was in the intersection of those zones, from the In the Following Zones list select When in All Selected Zones (AND logic). Example 2: With the Variable Activity State You want to select the track segments when the subject was either Active or Highly Active. It is assumed here that Activity State is defined with 3 possible states: Inactive, Moderately Active, and Highly Active. - Create a Nest box for the variable Activity State. Under Calculate Nesting For, choose Moderately Active. - Create a second Nest box for Activity State. Under Calculate Nesting For, choose Highly Active. - Combine the Nest boxes with OR logic. See Boxes in Parallel = OR Logic. To Nest over Two or More Variables Create one Nest box per criterion. To refine nesting according to two or more nesting criteria, create the corresponding Nest boxes and connect them between the Start box and the Result box using the logic you require. Example: You want to visualize the track segments when the animal was completely in the center of the open field AND its body was stretched. The center of the open field was defined as a zone. If you want to nest over multiple values of the same variable (for example, nest over Highly Mobile AND Mobile of the variable Mobility), create one Nest box per value and connect them using the logic you require (AND, OR, or Multiple Results). Order of Selection Boxes in a Sequence In some instances the order in which you place selection boxes in the Data Selection sequence may be important. Filter Boxes - If two or more Filter boxes refer to different variables (for example, one to filter trials, another one to filter drug doses), then the order you place the Filter boxes in does not matter. - If two or more Filter boxes refer to the same variable, then selection will only work if the elements selected in the second box are also selected in the first box. Example: If you filter male subjects in one Filter box and female subjects in the second Filter box, the selection contains no data. Nest Boxes The order you place the Nest boxes relative to Filter boxes does not matter. Source: EthoVision XT 19 Help - Complex Data Selections, Noldus Information Technology --- ## EthoVision XT 19 - Complex Data Selections - Results Per Time Bin Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-complex-data-selections-results-per-time-bin-settings Chapter: EthoVision XT Results Per Time Bin Settings - Under Settings, select: - The Length of the single interval (range: 0.001 second to 24 hours). - Ignore last time bin if incomplete. To exclude the last interval in the case this is of a shorter duration than the Length you have set. - Apply to all Results. Select this option if your data profile contains more than one Result box and you want to apply time bins to all of them. - Click OK. Notes - Results per time bin is applied for each track separately. - In a setup with multiple arenas, tracking can start at different times for each arena, depending on when the Trial Control's Start conditions are met in the arenas. Therefore, the same time interval may refer to different 'real' times for different arenas. - In a setup with multiple subjects per arena, tracking starts simultaneously for all the subjects in each arena. Therefore, the same time interval refers to the same 'real' time for all the subjects in that arena. - If you select a time bin length that is short compared to the sample rate, bear in mind that: (1) Increasing the number of time bins increases the calculation time. (2) If the length of the time bins is shorter than the sample time, only some of the time bins will contain a sample. - If the length of the time bins is not a multiple of the sample length, the time bins will differ in the number of samples they contain. For example, with a sample rate of 1 per second and a time bin length of 1.5 seconds, half the time bins will contain 1 sample and the others will contain 2. - If you use time bins in combination with Nesting or Filtering, the time bins outside the data selection are shown in the table headers but with no results. In the example below, time bins of 10 seconds were used and a time interval was created with Nest over Time from 20 to 30 seconds. - If you specify more than 1000 time bins in your Data profile, the group charts are not displayed. See Group Charts. --- ## EthoVision XT 19 - Conditions Based on Dependent Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-conditions-based-on-dependent-variables Chapter: EthoVision XT Conditions Based on Dependent Variables Selecting Subjects for a Condition - If the Actors tab also contains the Body points options, select one or more body points of the subjects selected above. - For the dependent variables of social interaction, a Receivers tab is also available. Click this tab and select the subjects that you have not selected under Actors. - Click OK to confirm your selection. You return to the condition window. Example: Using All Selected Subjects The researcher wants to define an In zone condition that is met when Subject 1 and Subject 2 have been in a zone simultaneously for at least one minute. Solution: In the Condition window, select Cumulative duration as Statistic and enter >= 60 s. Click Settings and select the zone you require, then click Actors and select Subject 1 and Subject 2, finally select All selected Subjects. Example: Using Any Selected Subjects The researcher wants to define a Distance to zone condition that is met when one of the two subjects is at less than 5 cm from a novel object. Solution: In the Condition window, select Current and enter <= 5 cm. Click Settings and select the novel object zone, then click Actors and select Subject 1 and Subject 2, finally select Any selected Subjects. Example: Using Actors and Receivers The researcher wants to define a condition that is met when the nose point of Subject 1 has been close to at least one body point of Subject 2 for more than one minute. Solution: Click the button next to Proximity and in the Condition window, select Cumulative duration and enter the required value. Click Settings, then: - In the Actors tab, select Subject 1 and de-select Subject 2. Under Body points, select Nose-point only. - In the Receivers tab, select Subject 2 and de-select Subject 1. Under Body points, select all points and then Any selected points, since the condition must be met when Subject 1 is in proximity of at least one of Subject 2's body points. When Is a Condition Met? Dependent variables are calculated for each sample. When a condition based on dependent variables is met depends on a number of factors. Effect of Outliers and Track Smoothing Dependent variables used in conditions are not smoothed or filtered using the Lowess filter or the Minimum distance moved as they can be for data analysis. This means that outliers, nose-tail swaps, or even subject identity swaps can have severe effects on whether and when a condition is met. For example, if EthoVision XT detects a reflection within zone A as the subject, the track shows a spike. If a condition of type In zone is defined which specifies Frequency of In zone A >= 1, then the condition is met the moment the subject is wrongly detected in zone A, assuming that the condition box was active. Track noise reduction may solve this problem. In the Detection settings, click Advanced and under Smoothing set Track noise reduction to On. This applies an online smoothing effect as the subject is being tracked. Note: This change in the track cannot be reversed afterwards. Effect of Missing Samples Missing samples can also cause Trial Control to react later. For example, an In zone condition is met only when valid samples are found within the specified zone. If EthoVision XT misses the subject some time before it enters zone A, the following applies: - If a condition of type In zone specifies Current of In zone A = true, then the condition is met later than it would be if there were no missing samples. - If a condition of type In zone states "Current duration of not in zone longer than 1 s" (assuming a sample rate of 5/s, so 5 samples make up 1 second), then the condition does not become true, because there are only 4 samples for which the state "not in zone" was true. - The condition "Current value of In zone A = false" may be met in the first segment of the track, because it refers to the state of a current sample, not a duration. In that case the subject is out of the zone, so the current value of In zone is "false". However, the condition will not be met in the period of missing samples because EthoVision XT does not know the current state of the subject. Effect of the Statistics Used When a condition is evaluated also depends on the statistic chosen: - For Current, the condition is evaluated at the same sample time as when it is activated. - For all other statistics (such as Frequency, Current duration, etc.), it is evaluated at least one sample after the condition is activated. This depends on when the first value available for comparison occurs after the activation of the condition. - When using Velocity and Distance, it takes one sample. - When using Heading and In zone, it takes two samples. - When using Turn Angle and Angular velocity, it takes three samples. Conditions Based on Behaviors Scored Manually Use this kind of condition to have EthoVision XT carry out an action when the subject performed a behavior you scored manually. For example, in a social interaction test, to stop tracking when the subject attacked three times, or when the duration of Intimidation lasted more than 30 seconds. - In the Components pane, under Conditions, double-click the name or click the button next to the manually scored behavior you want to base the condition on. If you do not see the variable name, click the More button. - The Manual Scoring Condition window opens. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). - Under Condition is met when, click the Settings button. If the behavior is of the type Start-Stop or Mutually Exclusive, choose the behavior to base the condition on, for example Rear or Not Rear. - In the Actors tab, select the subjects to which the condition applies. If the Actors tab also contains the Body points options, select one or more body points of the subjects selected above. Click OK. - Under Condition is met when, select the Statistic you want to use. Common cases of Statistic for manually scored behaviors: - Current. For a condition that is met when the behavior at the current sample is true or not true. This statistic is available for Start-Stop and Mutually exclusive events. - Frequency. For a condition that is met when the behavior occurred a number of times. - Cumulative duration. For a condition that is met when the animal has shown the behavior for a specific time since the activation of the condition. This statistic is available for Start-Stop and Mutually exclusive events. - Current duration. For a condition that is met when the animal has shown the behavior continuously for a specific time. This statistic is available for Start-Stop and Mutually exclusive events. - Latency to first. See the Latency to First section for details. For more information on manually scored behaviors, see the EthoVision XT Help. Conditions Based on Hardware Devices Use this kind of condition to check the status of hardware devices (pellet dispensers, lickometers, etc.) and have EthoVision XT take actions when the conditions are met. - In the Components pane, under Conditions, click the button next to the hardware device you want to base the condition on. - The Hardware condition window appears. Under Name, enter a Condition Name. Under Comment (at the bottom) enter a description (optional). - Under Condition is met when, select the Template device you want to use. A template device represents a group of devices of the same type, one for each arena. - Under Signal to check, select the criterion that forms the condition. - Under Signal value, select the value of the criterion in order for the condition to be met. - Click OK. Insert the Condition box in the appropriate position in the rule. Hardware devices are not defined for each arena separately. If you have a setup with multiple arenas, it is assumed that each arena has the same type of device. The name in the device list is the generic name valid for all arenas. The condition will be evaluated for each arena separately. If the device type is not listed under Conditions, it means that it is not yet recognized by EthoVision XT. Pellet Dispenser - Number of drops. To base your condition on whether more or less than N food items have been delivered since the activation of the condition. Choose >= or <= and enter the value N in the box. - In error state. To base your condition on whether the pellet dispenser is in error state, that is, when it can no longer drop any pellet (this happens when there are no pellets left in the feeder). Choose between true (error) or false. Example: Have EthoVision XT give a sound signal when the feeder has run out of pellets. Lickometer - Duration of licks. To base your condition on the total duration of licks since the activation of the condition. Enter this time in the box. - Number of licks. To base your condition on the number of licks since the activation of the condition. You can select >= N, <= N, or = N. Top Unit of PhenoTyper - Choose the option under Signal to check to base your condition on whether a sound or light signal is given since the activation of the condition. - For Top Unit (NeuroBsik), use Is Fsel-1/2 on/off or Is Vol-1/2 on/off to base your condition on the value of frequency or volume specified by one input. Since the frequency and volume are specified by two inputs, you must define two conditions, one for input 1 and one for input 2. Combine the two conditions with an operator of type All. Note: Neuro-Bsik is a consortium of eleven Dutch Neuroscience research groups and two companies including Noldus. The consortium aims to contribute to the battle against brain disorders by developing novel mouse models for brain disorders. For this project, Noldus has developed a special Top Unit of the PhenoTyper cage that can produce ultrasound stimuli. For more information, see the PhenoTyper - EthoVision XT Reference Manual. TTL Port Tester - Button 1/2 presses. To base your condition on the number of presses of button 1 or 2 given since the activation of the condition. You can select either >= N, <= N, or = N. Enter the value N in the box. - Is button 1/2 pressed? To base your condition on whether button 1 or 2 is currently pressed. Select true or false from the list. - Is light 1/2 on? To base your condition on whether light 1 or 2 is currently on. Select true or false from the list. Beam Controller - Beam 1/2 breaks. To base your condition on the number of beam breaks for beam 1 or 2 since the activation of the condition. You can select either >= N, <= N, or = N. Enter the value N in the box. - Is Beam 1/2 broken? To base your condition on whether beam 1 or 2 is currently broken. Select True or False from the Signal value list. - Is cue 1/2 on? To base your condition on whether cue 1 or 2 is currently on. Select true or false from the Signal value list. Activity Wheel Counter - Quarter cycles. To base your condition on the number of quarter cycles since the activation of the condition. You can select either >= N, <= N, or = N. Enter the value N in the box. Custom Hardware Device This includes the illuminated shelter. - Input 1/2 L/H -> H/L count. To base your condition on how many times there has been a transition from High to Low (or vice versa) in input 1 or 2 during the time t-1 to t, where t is the sample time when the condition is evaluated. Choose the option that applies, select either >= N or <= N. Enter the value N in the box. This option lets you create a condition based on events (transitions) in the signal, no matter when they happen during the sample time. - Is input 1/2 High/Low? To base your condition on whether the current state of input 1 or 2 is High or Low at the sample time when the condition is evaluated. Select the option that applies, and then either true or false. - Is output 1/2 High? To base your condition on whether the current state of output 1 or 2 is High at the sample time when the condition is evaluated. Select the option that applies, and then either true or false. This option evaluates the state of the signal (High vs Low) at the sample time when the condition is evaluated. If a quick transition High -> Low -> High occurs within the sample interval, this is not noticed; the state at the sample time is still High. Counts vs. Signals: Effects on Conditions Consider two conditions based on the same input (for example Input 1): - Is the number of transitions H->L >= 1? - Is the state of the signal Low? There is a fundamental difference between the two conditions: - In the first condition, the software counts the number of transitions from High to Low during the sampling interval (that is, from t-1 to t). The condition may become true or stay false for sample t, depending on that value. - In the second condition, the signal is evaluated at time t, that is, at the end of the sampling interval. If short transitions occur from High to Low to High again, the Low signal is not detected by this condition, because the signal is still High at time t. More About Conditions Based on Dependent Variables This section provides details and examples of the statistics you can use for your condition. Note: Dependent variables of Live Mouse Tracker and the social variables Train and Side by side are not available in the Trial Control Settings. Distance Moved Frequently-used statistics: - Current (default). To base your condition on the distance between the previous sample and the current one. This value depends on the chosen sample rate. Use Current velocity instead. - Total. To base your condition on the distance traveled from the moment the condition becomes active up to that point. - Mean. To base your condition on the average distance traveled from one sample to the next, calculated from the activation of the condition box up to that time. Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - Configure Detection Settings - Activity Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-activity-settings Chapter: EthoVision XT Activity Settings If you selected Activity analysis in the Experiment Settings, you must create settings for this analysis. To make it easier to judge whether the settings are correct, make sure the detected Body fill of your subject is not shown in the Video window. Click the Show/Hide button in the top-right corner of your window, select Detection Features and deselect Body fill and Noise. Then select Activity. Close the Detection Features window and play the video. The detected pixel change between samples is shown in purple. Open the Activity section in the Detection Settings pane. Activity Threshold This value gives the threshold for the difference in gray scale values between a sample and the previous sample. Background Noise Filter Use this filter to remove noise in the video or camera image. With the background noise filter, a pixel change is only counted as a change if the surrounding pixels also have changed. The pixels that are not fully surrounded by changed pixels are removed, and around the remaining pixels a layer of changed pixels is added. The higher the setting for the background noise filter, the more surrounding pixels are used. Compression Artifacts Filter Use the compression artifacts filter to compensate for video artifacts that are regularly recurring. With the compression artifacts filter, only the changes that are occurring in a number of consecutive frames are taken into account. - If you track live, we recommend leaving this setting on the default value Off. - If you track from video, or if you select Redo tracking from an existing video file, select On. - However, if you are interested in very brief or fast occurring changes, leave the setting for the Compression artifacts filter on Off. Create settings in such a way that all activity of your animal is detected and some noise is left. Also try whether lowering the sample rate and using Video Pixel Smoothing improves Activity detection. Then, click the Show/Hide button once more and select Detection Features. Deselect Activity and select Body fill. Then create detection settings for your subject. Or, if you need different sample rates for activity analysis and tracking, create separate detection settings for tracking. It is also possible to only carry out activity analysis and not create detection settings for tracking. However, if you do so, it may happen that EthoVision XT has so much difficulty detecting the animal that this decreases the performance of acquisition. This may result in many missed samples. Therefore, while creating activity settings, check that the proportion of missed samples does not become too high. Optimize the Reference Image Learn About - The reference image - How the reference image is updated in Dynamic subtraction - How the reference image is updated in Differencing --- ## EthoVision XT 19 - Configure Detection Settings - Adjust Detection Settings - General Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-adjust-detection-settings-general-procedure Chapter: EthoVision XT Adjust Detection Settings - General Procedure Subject detection works well if there is good contrast between the subject and the background in the video image, and for the whole duration of the trials. Increasing the contrast (for example, by changing the background so it differs as much as possible in color from the subject) is far more effective than any detection setting. To Adjust the Detection Settings - Select the sample rate and video file. See Video File, Image Quality and Sample Rate. - Use the Automated Setup functionality to detect the subject. See Detection Settings: Automated Setup. - Optionally use advanced detection settings if Automated Setup does not give satisfying detection. See Detection Settings: Advanced Setup. Notes - Important: Make sure you carefully follow the order of steps as described in the next topics. If a particular step does not apply to your setup, proceed to the next step. - Every time you apply changes in the Detection Settings window, you can see the consequences in the Video window. - To save the detection settings, click the Save Changes button at the bottom of the pane. If you have made more changes and you want to return to the last saved settings, click the Undo Changes button. - EthoVision XT offers a number of real-time statistics on the quality of detection that you can check while you adjust detection settings. Video File, Image Quality and Sample Rate Learn About - Video file and image quality - Sample rate Video File and Image Quality What you see under Video depends on whether you track from video files, or live. Select Video Available when tracking from video files. By default, the Detection Settings shows the same video file used in the Arena Settings, to obtain a background image. To use another video file, click Select Video. Image Quality Available when tracking live, and for some cameras, not others. To adjust, for example, the image contrast or brightness, click the Image Quality button under Video. Important: Always try adjusting the lighting and camera aperture settings before changing the Image Quality Settings. In the window that appears, adjust the properties you require. - Contrast enhances the lighter and darker parts of the image. - Brightness makes the image lighter. - Saturation increases the color intensity. Dependent on the camera, some settings may be grayed out. Notes - For some cameras, the Image Settings are not available. In the Experiment Settings, click the camera button and click the Image tab. See Video Source. - The Image Quality Settings also affect the image that is saved to a video file. - To return to the defaults of the camera driver, click the Default button. --- ## EthoVision XT 19 - Configure Detection Settings - Adjust the Settings for Nose-Tail Base Detection ( URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-adjust-the-settings-for-nose-tail-base-detection-LH8 Chapter: EthoVision XT Adjust the Settings for Nose-Tail Base Detection (Deep Learning) Aim To achieve detection of the nose- and tail-base points of your subjects using the Deep Learning method. This topic applies to tracking of one subject per arena. If you track two or more subjects per arena with Deep Learning, you do not need to adjust settings besides the sample rate. Prerequisites - In the Experiment Settings: - Under Subjects, 1 is selected. - Under Tracked Features, Center-point, nose-point and tail-base detection is selected. - Under Body Point Detection Technique, Deep Learning is selected. - You optimized the lighting and the background based on Deep Learning: Requirements. Procedure - Open the Detection Settings. - In the Video section (top-right), select the video file (if you track offline) and choose the sample rate. See Video File, Image Quality and Sample Rate. - Under Advanced > Method, choose the detection method and the contrast range. See Advanced Detection Settings: Method. - In the Detection Settings window, under Detection, click the Automated Setup button and follow the instructions. When the Automated Setup gives good detection, proceed with the next step. See Detection Settings: Automated Setup. - Play the video or wait until the subject in the live image is located (a) far from walls and other objects (especially when the walls and objects provide little or no contrast with the subject), (b) its body is not curled or contracted, and (c) its nose is visible. For best results, position the video on a frame where the animal is slightly stretched. - If you work with hooded animals, like the Lister rats or the Long-Evans rats, under Method, next to Deep Learning Settings, select Hooded Rats. - Under Method, next to Deep Learning Settings, click the Define button. The Cutout window opens. EthoVision XT shows a square box around the subject. The size of this box should already be optimized based on the detected subject. The Cutout box should include the whole subject's body leaving some space around it. - If that is not the case, click Automated. - Click OK. - The Video window now shows the subject with its nose and tail-base highlighted (nose = light blue). - If the nose and tail-base are not detected sufficiently well, click Define again and move the slider until the box includes the entire body of the subject. See the suggestions below. - The tail of the rodent does not have to be included. - Important: Keep some space between the subject and the outline of the Cutout box. Notes - To improve detection, see also Deep Learning: Requirements. - The Cutout box size is saved in the Detection Settings. The next time you click Define, the Cutout dialog shows the last saved value. - Which Value for the Cutout Box Size? The Cutout value is shown for reference. Do not focus on a specific value, because other similar values may work fine (for example, 135 and 137). However, take note of that value if you know that it works, so you can use it in the next experiment assuming that you use the same camera distance, arena size, etc. As a rule of thumb, the Cutout box should include the animal also when it is stretched. Make sure that the box includes some space around the animal, at least half the body length. - Small Animals: With small animals, the Cutout box can quickly become too small or too big. Adjust the Cutout value by small steps, until the nose and tail-base points are detected correctly. - Occlusions: When the subject image is obstructed by, for example, a door, increase the Cutout box size so that the nose or tail can be found on the other side of the obstruction. This usually improves the detection. - Reflections: If there are reflections at the wall of the apparatus and these give problems with detection of the nose point, try to reduce the size of the Cutout box. See an example in Troubleshooting: The Detected Nose Point Is Far from the Animal's Contour. - Multiple Arenas: When you work with two or more arenas, the Cutout box is displayed only in the last arena. Adjust its size as described above. Examples of a Good Cutout Box Size Subject in an Open Field: In the first picture below, detection won't work because the rat's nose is outside the box. In the second picture, detection may work but a large Cutout size increases the risk that other objects are included that are of similar color as the rat. Detection Settings for Behavior Recognition Prerequisites - You have the Rat/Mouse Behavior Recognition Module. - In the Experiment Settings, under Tracked Features, you have selected Center-point, Nose-point and tail-base tracking. Under Analysis Options, you have selected Behavior recognition. - See also Behavior Recognition: Requirements Procedure - Put the animal in the arena or play the video. Optimize the camera setup, and lighting conditions. Try to reduce reflections on the walls of the arena as much as possible. - Select the image source and sample rate. In the Detection Settings pane, under Video, select a value of sample rate between 25 and 30 samples/second. See Video file, image quality and sample rate. - Use the Automated Setup as described in Detection settings: Automated setup. - When detection is good, open the Behavior Recognition section in the Detection Settings pane and follow Advanced detection settings: Behavior recognition. Notes - If detection with the Automated Setup is not good, in the Detection Settings pane, click Detection and then Advanced. Under Method, select one of the following: - Rodents / Default. This is selected automatically when you use Behavior recognition, and should work in most cases. - Rodents / For occlusions. Choose this method only when Default does not give good results. This option is optimal when there are objects in the arena (for example a novel object) which create occlusions and make detection of the whole subject's body difficult. - The quality and amount of light is very important when using Behavior recognition. See Subject exposure. --- ## EthoVision XT 19 - Configure Detection Settings - Adjust the Settings for Nose-Tail Base Detection ( URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-adjust-the-settings-for-nose-tail-base-detection Chapter: EthoVision XT Adjust the Settings for Nose-Tail Base Detection (Contour-Based) Aim To achieve detection of the nose- and tail-base points of your subjects with high accuracy. Prerequisites - In the Experiment Settings, under Tracked Features, you chose Center-point, nose-point and tail-base detection. - You have optimized the lighting and the background. See Optimize Nose-Tail Base Detection. Procedure - Select the image source and sample rate. See Video File, Image Quality and Sample Rate. - Use the Automated Setup. When the Automated Setup gives good detection, proceed with acquisition. If not, follow the steps below. See Detection Settings: Automated Setup. - Under Video, choose the sample rate. Use a sample rate as high as possible. However, for nose-tail tracking in combination with marker-assisted tracking, use a sample rate of 12.5, 15 or 14.98 samples/s depending on the camera. - Open the Advanced Detection Settings: Method. Choose the detection method and the method for estimating the body points. See Methods for Estimating the Body Points. If you followed the Automated Setup, a Default method is selected automatically for one-subject tracking, and For Occlusions for multiple-subject tracking. In the picture below: Left, a sub-optimal result of body detection (part of the right side of the body is not detected). Right, the result when the contrast settings are optimized; now the complete body is detected. The color of the body contour at this stage is orange (=noise) because the model parameters have not been configured yet. Notes - The maximum sample rate depends on the camera. Subject Contour for Nose-Tail Base Detection Aim To optimize the shape of the detected subject, so that the body points are correctly found. Procedure - When you use one of the following methods for detecting the body points, Any Species / Default, or Adult Fish / For Occlusions, make sure the tail is fully detected as part of the subject. - When you use a Rodents method (Default or For Occlusions), it is best to remove detection of the rodent's tail. See Advanced Detection Settings: Subject Contour. Notes - When you track fish from above, the tail-base point is not positioned on the tail fin, rather more towards the mid-point. That is normal and is not a sign of bad detection. See Also - Advanced Detection Settings: Subject Contour - Subject Size for Nose-Tail Base Detection Subject Size for Nose-Tail Base Detection Aim To optimize the size of the detected subject, so that the body points are correctly found. Procedure Choose the option depending on which method for estimating the body points you are using. - For Any Species / Default or Rodents / Default: See Advanced Detection Settings: Subject Size (one subject per arena). - For Rodents / For Occlusions and Other Species / For Occlusions: See Advanced Detection Settings: Subject Size (multiple animals per arena). --- ## EthoVision XT 19 - Configure Detection Settings - Advanced Detection Settings for Tracking Multiple URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-advanced-detection-settings-for-tracking-multiple Chapter: EthoVision XT Advanced Detection Settings for Tracking Multiple Unmarked Subjects Aim To set EthoVision to track multiple subjects per arena, when the subjects are not color-marked. - To minimize subject identity swaps, make sure that the subjects are well detected in the whole arena. Make lighting as uniform as possible, and use indirect light, to minimize shadows. - When subjects crowd closely together EthoVision may temporarily assign the same position to those subjects, or lose track of one of them. This can be minimized or totally eliminated by setting good detection settings. Make sure that the body of the subjects is fully detected, and that the reference image does not contain the image of the subjects. This Topic Applies To Experiments set to: - Number of Subjects per Arena: 2 or more. - Tracked Features: Center-point, nose-point and tail-base detection. - Body point detection technique: Contour-based. If you use Deep learning to track two subjects, you do not need to adjust detection settings. Simply choose the sample rate (step 1 below) and skip the remaining steps. See Deep Learning: Requirements. Procedure - In the Detection Settings window, under Video, select the image source and sample rate. See Video File, Image Quality and Sample Rate. - Use the Automated Setup. When the Automated Setup gives good detection, proceed with the next step. If not, create advanced detection settings and follow the procedure in Advanced Detection Settings: Method. - In the Detection Settings pane, under Subject Identification, select Unmarked Subjects. - OPTIONAL: Click a cell under Body Fill and specify the color for a subject. This helps checking identity swaps during tracking. - Adjust Advanced Detection Settings: Smoothing Settings. - When tracking the three body points, adjust Subject Contour for Nose-Tail Base Detection. In all other cases see Advanced Detection Settings: Subject Contour. - Adjust Advanced Detection Settings: Subject Size (Multiple Animals per Arena). Notes - When tracking unmarked animals, it is not possible to specify which animal is labeled "Subject 1", which "Subject 2" and so on. EthoVision XT chooses which individual is assigned a label. This also means that the same animal in video 1 is not necessarily labeled with the same name in video 2. To link the identity (or role) of Subject 1, Subject 2, etc., enter that information as an independent variable in the Trial List. See Define an Independent Variable. - When tracking unmarked subjects, identity swaps may occur; that is, what is labeled Subject 1 may at some point in the track be labeled as Subject 2, and what was Subject 2 is now Subject 1. Always check carefully the tracks, and, if necessary, correct the identity swaps. See Swap Subjects. Advanced Detection Settings for Tracking Color-Marked Subjects Aim Use color marks in one of the following cases: - When detection of the subject is difficult, for example because its color is similar to that of the arena. - When you want to track multiple animals per arena, and you want to keep the correct identity of each individual. Background Information There are two ways of tracking subjects that are color-marked: Marker-Assisted Identification and Color Marker Tracking. The difference between the two is as follows: - Marker-Assisted Identification. EthoVision XT tracks the animal's body but uses the marker to determine the animal's identity. In the Detection Settings pane, under Subject Identification, select Marker-Assisted Identification. See the procedure in Advanced Detection Settings: Marker-Assisted Identification. - Color Marker Tracking. EthoVision XT only tracks the marker's geometric center, and ignores the subject's body. The actual shape and size of the animal is ignored. To apply this method, in the Experiment Settings under Tracked Features select Color Marker Tracking (treat marker as center-point). Next, see the procedure Advanced Detection Settings for Color Marker Tracking. In all cases, you can track up to 16 animals simultaneously in the same arena. This is a technical limit; in practice, it may be difficult to discriminate between 16 different color marks depending on the light conditions. Procedure - Advanced Detection Settings: Marker-Assisted Identification - Advanced Detection Settings: Smoothing - Advanced Detection Settings: Subject Contour - Advanced Detection Settings: Subject Size (Multiple Animals per Arena) See Also - Advanced Detection Settings for Tracking Multiple Unmarked Subjects --- ## EthoVision XT 19 - Configure Detection Settings - Advanced Detection Settings: Behavior Recognition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-advanced-detection-settings-behavior-recognition Chapter: EthoVision XT Advanced Detection Settings: Behavior Recognition To Adjust Behavior Recognition Settings - In the Detection Settings pane, click Behavior Recognition. - If you work with video, play the video up to a frame where the subject is walking normally, and its hind limbs can be partially seen. It is important that the animal's body is not contracted or stretched, and that nose- and tail-base points are correctly detected. If you track live, wait until the animal shows a normal walking posture. - In the Behavior Recognition Settings window, click the Grab button. - A still image appears showing the detected subject's contour and the detected body points. You can update the grabbed image at any time: - If you track from video files, position the video to another frame, and click Grab. - If you track live, wait until the posture of the animal is as described above, and click Grab. EthoVision XT only stores the image grabbed last. - In the Behavior Recognition Settings window, make sure that the calculated Subject length is greater than 60 pixels (55 for mice), and that the Posture index is between 70 and 90. If the Subject length is smaller than 60 pixels (55 for mice), move the camera closer to the animal, or use a higher video resolution. The subject length must not exceed half the arena size. - Click OK to close the Behavior Recognition Settings window. To Enter Specific Size Values (Optional) If you know specific size values (for example, from a previous experiment using the same animal size, camera, lighting, camera-arena distance and the same calibration), click Manual in the Behavior Recognition Settings window and in the Manual Settings window enter the following values: - Subject area (in distance unit square) - Center-nose length (in distance unit) - Center-tail length (in distance unit) - Posture (between 70–90) Then click OK. The Behavior Recognition Settings window says: No image saved: Size settings were manually set. - Subject size is expressed in the unit selected in the Experiment Settings. - The value of Subject length in the Behavior Recognition Settings window is the sum of Center-nose length and Center-tail length, expressed in pixels. If this value is lower than 60 (55 for mice), when opening the Acquisition screen an error message appears. To increase subject length, move the camera closer to the animal, or use a higher video resolution. Making Size-Dependent Detection Settings Accurate recognition of behavior is based on subject size settings. Since apparent size increases with the subject age, all being equal, we advise you to create detection settings specific for a certain age class. Each Detection Settings profile can only be used for a limited time. For example, for Wistar rats, a Detection Settings profile for rats that are 3–5 weeks old, which can be used about one week, and a Detection Settings profile for rats older than 5 weeks, which can be used for two weeks. Subjects should not vary in size for more than 10%. If that happens, create more Detection Settings (for example, one for smaller animals and one for larger animals). Important: EthoVision XT shows a warning message in the following cases: - When the sample rate set is lower than 25 or higher than 31 samples/s. - When the Subject length is smaller than 60 pixels for rats, or 55 pixels for mice. - When the animal is larger than the arena. Other Settings for Behavior Recognition Smoothing See Advanced detection settings: Smoothing. Subject Contour For optimal results, we recommend selecting Erosion and then Dilation to remove the tail from the detected body. See Advanced detection settings: Subject contour. Subject Size Choose the option depending on the method for estimating the body points. - If you select Rodents / Default: See Advanced detection settings: Subject size (one subject per arena). - If you select Rodents / For occlusions: See Advanced detection settings: Subject size (multiple animals per arena). Subject Exposure When using Behavior recognition, the amount of light that the camera receives from the subject is even more important than usual. See Subject exposure. Subject Exposure Aim To obtain a balanced image of the subject. This is of critical importance when using Behavior recognition. Prerequisites - Your experiment is set for Behavior recognition. - You open the Detection Settings. Procedure - Play the video or let the subject walk in the arena. - In the Detection Performance window, locate the Subject Exposure indicator. - Make sure that the Exposure is Good when the subject has been in all parts of the arena. - When the image is overexposed or underexposed, the subject looks too bright or too dark, respectively. The details of the fur are hardly visible. Try the following: - To reduce the subject's exposure, close the aperture of the camera lens. Alternatively, for GigE and USB cameras, reduce the Exposure time. - To increase the subject's exposure, open the aperture of the camera lens or increase the Exposure time. If that is not possible, increase the Gain. For how to adjust the exposure and gain, see Adjust camera settings in EthoVision XT. Notes Check the exposure level when the subject is walking or sitting still. The subject's tail should not touch the sides of its body. If that occurs, the estimate of subject exposure may not be reliable. Wait until the subject's tail does not touch its body, and check the Exposure Level for a more reliable indication. --- ## EthoVision XT 19 - Configure Detection Settings - Advanced Detection Settings: Marker-Assisted Ident URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-advanced-detection-settings-marker-assisted-ident Chapter: EthoVision XT Advanced Detection Settings: Marker-Assisted Identification Prerequisites - You have marked the animals with colors. - You have optimized lighting as suggested in Tips for Color Tracking. To Adjust Detection Settings for Marker-Assisted Identification - Put the marked animals in the arena or play the video. - In the Detection Settings window, under Video, select the image source and sample rate. See Video File, Image Quality and Sample Rate. - Use the Automated Setup. At this stage EthoVision XT detects the subjects, but does not distinguish between the animals yet. When the Automated Setup gives good detection, proceed with the next step. If not, create advanced detection settings and follow the procedure in Advanced Detection Settings: Method. When done with the Automated Setup, make sure Marker-Assisted Identification is selected in the Subject Identification section in the Detection Settings pane. Note: - IMPORTANT: Make sure you select a point in the video where the animals do not touch. - If you use three-body point detection, it is normal that the nose is not correctly identified at this point. - If detection is processor intensive and you track from video, the video slows down so all frames can be analyzed to enable creating good detection settings. - In the Subject Identification section, click the name of one of the subjects and click the Identification button. The Identification [Subject name] window opens. Optionally enlarge the Video window by dragging its bottom-right corner. - Move the mouse pointer to the Video window so the pointer becomes an eyedropper. - Move the eyedropper on top of the color marker of the subject you want to identify and click the left mouse button. The Identification [Subject name] window now displays the color you just picked and the pixels with the initial color are highlighted in the Video window. In the Identification [Subject name] window, you can change the following: - Hue: Hue is the predominant wavelength of the marker color and represents what is usually referred to as color in everyday life (red, green, blue, etc.). The range of values for Hue of the picked color are shown and this range is represented by the box on the vertical color bar on the right. - Saturation: Saturation represents the purity of a color. Saturation decreases when a pure color is mixed with white; "red" is saturated, "pink" is less saturated. The range of values for Saturation are shown and this range is represented by the width of the box on the Color Map. - Brightness: Brightness (or Intensity) represents the amount of light reflected by the colored surface. The range of values for Brightness are shown and this range is represented by the height of the box on the Color Map. If you set this range too broad, you will not be able to separate the colors well. If the marker is not detected completely or not detected in all areas of the arena, expand the range of Hue, Saturation and Brightness slightly. Change the color range by changing the numbers or by resizing the Hue box on the vertical color bar, or resizing and moving the box in the Color Map (horizontally to adjust Saturation, vertically to adjust Brightness). As a result, the outline covers almost the complete marker. - Play the video to see in the Video window whether the marker is detected correctly in different parts of the arena. If the marker "dances" then your color settings are too sensitive. Go back to step 5 and make the box larger. - Continue with setting the following: - Marker Erosion: Set the number of pixels to erode. By selecting Erode First, Then Dilate, you can make the marker more round to prevent the center-point of the marker from jittering. - Marker Dilation: Set the number of pixels to dilate. By selecting Dilate First, Then Erode, you can prevent the marker from being masked or divided into two separate markers by, for instance, a grid on top of the arena. - Minimal Marker Size: Set the Minimal Marker Size to prevent noise from being detected as the marker. First, increase the Minimal Marker Size until noise is not detected anymore. Next, enter a value for the Minimal Marker Size that is somewhere in between this lower threshold and the value of the Current Marker Size. - Marker Pointer: Select a Marker Pointer from the list. With relatively small markers it is useful to select Cross Lines. - Click OK when you are done. Click another subject under Subject Identification and repeat steps 2 through 8 for all subjects you want to identify. If you used the Automated Setup, estimates for the settings have been created. Optionally fine-tune these settings if detection of all subjects does not go well in the entire track. What Next? Follow the procedure in this order: - Advanced Detection Settings: Smoothing - Advanced Detection Settings: Subject Contour - Advanced Detection Settings: Subject Size (Multiple Animals per Arena) --- ## EthoVision XT 19 - Configure Detection Settings - Advanced Detection Settings: Method URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-advanced-detection-settings-method Chapter: EthoVision XT Advanced Detection Settings: Method Aim To choose: - The detection method, that is, how EthoVision XT finds the subject over the background. Once you have selected the method, specify the background image (for the detection methods Static Subtraction, Dynamic Subtraction and Differencing only) and the level of contrast between subject and background. - The method for estimating the body points. See Methods for Estimating the Body Points. Gray Scaling Choose Gray Scaling when: - The animal's grayness differs from the background in all parts of the arena. - The background does not change during a trial. - Lighting is even (minimal shadows and reflections) during the trial. Example: Tracking a white rat in a uniform black open field with no bright objects. Static Subtraction Choose Static Subtraction when: - The Gray Scaling method does not work, for example because other objects in the arena have a similar color as the animal. - The background does not change in time. - The light is constant during the trial. Example: Tracking a white rat in an open field with unavoidable reflections or bright objects. Dynamic Subtraction Choose this method when during trials light conditions gradually change or the background changes, for example because bedding material is kicked around, food pellets are dropped, droppings appear, etc. Example: Tracking a mouse in a home cage provided with bedding material. The activity of the mouse causes the bedding to change appearance in the video image. Differencing Choose this method when there is a lot of variation in contrast between a subject and the background within an arena. Example: There is a gradient in light intensity over the apparatus that cannot be removed, or a strong difference in the color of the fur of the animal, like in hooded rats. Gray Scaling Aim To detect the subject, under the assumption that its color is always different from that of the background (no shadows, gradients etc.). How Gray Scaling Works The video image is converted to monochrome. Each pixel in the image has a gray scale value, ranging from 0 (black) to 255 (white). With Gray scaling, you define which range of gray scale values should be considered as the subject. The remaining gray scale values are considered as background. The Gray scaling method does not make use of a background image; the subject is determined by its gray scale values only. Procedure - In the Detection Settings pane, click Advanced, then Method. Select Gray scaling. - Release the subject in the arena, or position the media file at a point where the subject is moving. - Move the two sliders next to Range or type the values in the corresponding fields to define the lower and higher limits of gray scale values for the subject. Make sure there are no areas in the background with gray scale values that fall in this range, otherwise they will be detected as the subject. - In the Video window, check the quality of detection. - If the detected area (by default, in yellow) is too large, or other objects are detected as the subject, reduce the range in either direction (brighter or darker). - If the detected area is too small relative to the real subject, increase the range at least in one direction (brighter or darker). - Areas marked as noise (by default, in orange) indicate that the gray scale range is too wide: you need to narrow it in at least one direction. - Move the sliders until the subject (or the part which is of interest) is detected fully, and the noise is minimized. Check that the subject is properly detected in all parts of the arena by moving the video slider, or by waiting for the live animal to move. Important: The whole animal's body must be detected for optimal tracking. Proceed with the Contour adjustments to optimize body detection. --- ## EthoVision XT 19 - Configure Detection Settings - Advanced Detection Settings: Subject Contour URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-advanced-detection-settings-subject-contour Chapter: EthoVision XT Advanced Detection Settings: Subject Contour Aim - To eliminate the detection of thin objects such as the rodent's tail. - To remove the effect of fibers and other thin objects of similar color as the subject, for example in optogenetic stimulation systems. - To remove the effect of cage bars. - To join up the parts of the body when they are detected separately, for example a zebrafish when swimming over a dark object. How to Access This Option In the Detection Settings window, locate Subject Contour. Procedures To Remove the Rodent's Tail or Thin Objects - Select Erosion >0, Dilation >0. In most cases the second Erosion filter is not necessary. - Increase the values Erosion and Dilation until the rodent's tail or the interfering objects are no longer detected. Tip: Try with equal values for Erosion and Dilation; alternatively, Erosion slightly higher than Dilation. For example, 3, 2, 0. For tethered animals, increase Erosion until only the subject is detected. To Remove the Effect of Cage Bars - If the cage bars are the same color as the subject, first erode, then dilate. For example, Erosion 1, Dilate 3, Erosion 0. - If the cage bars are darker (or lighter) than the subject, then first dilate, then erode. For example, Erosion 0, Dilation 4, Erosion 1. To Join Up Parts of Animals Like Fish and Insects - Select Erosion 0, Dilate >0, Erosion >0. - Increase Dilation until the subject's body is fully detected. Then increase Erosion to return to the normal subject size. For example Erosion 0, Dilation 4, Erosion 2. How Erosion and Dilation Work Contour Erosion Erosion removes an external layer of pixels from the subject's contour. The detected subject appears smaller. 1 means that a layer of 1 pixel is removed. Range: 1 to 10. Contour Dilation Dilation adds a layer of pixels around the subject's contour. The detected subject appears larger. 1 means that a layer of one pixel is added. Range: 1 to 20. Combine Erosion and Dilation Select Erosion and Dilation when you want to keep the apparent size of the subject as the original. When you select at least two filters, erosion and dilation are applied based on the sequence that results from which filters you choose. - Erosion >0, Dilation >0, Erosion =0: A layer of pixels is removed, then another layer is added to the contour. This is the same as Erode first, then dilate in EthoVision XT 15 and earlier. - Erosion =0, Dilation >0, Erosion >0: A layer of pixels is added, then another layer is removed from the contour. This is the same as Dilate first, then erode in EthoVision XT 15 and earlier. - Erosion >0, Dilation >0, Erosion >0: A layer of pixels is removed, then another layer is added, and finally a third layer is removed. Tip: Use this combination to improve nose-tail detection in some difficult situations, for example when the subject enters a darker area. Adding the second Erosion filter may help. Notes - It is important that the complete body of the animal is detected. If even after setting the Contour adjustments you do not achieve this, go back to the appropriate Detection method and adjust the contrast to improve body detection. - A reason for why you may want to eliminate the animal's tail is that when the animal sits still and its tail moves, it adds to distance moved. Furthermore, when the tail is not part of the detected blob, the center point is better estimated. - If you apply Erosion 2, Dilation 0, Erosion 2, the effect is like that of Erosion 4, Dilation 0, Erosion 0. See Also - The video tutorial Contour Settings. Advanced Detection Settings: Subject Size (One Subject Per Arena) Aim To set a minimum and a maximum apparent size of the subject to prevent objects like droppings or large reflections from being detected during tracking. This Topic Applies To All experiments set to: - Number of Subjects per Arena: 1 - Body point detection technique: Contour-based Procedure - In the Detection Settings window, locate the Subject Size. - When EthoVision XT finds the subject, check the value under Current. The Current value gives an idea of the detected body size in pixels. - Click the Edit button and set the Minimum and Maximum subject sizes. Objects that have the same color as the animal, but are smaller than the Minimum or larger than Maximum size, are not tracked. You are now ready to acquire data. Notes - The term size here means surface area in video pixels, not length or screen pixels. Enlarging the Video window does not change the subject's size in video pixels. - Objects whose size is outside the size range are shown in the color under Noise (default: orange; see View the Detection Features on the Video Window). - Click the video icon next to Subject Size and watch the video tutorial. --- ## EthoVision XT 19 - Configure Detection Settings - Advanced Detection Settings: Subject Size (Multipl URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-advanced-detection-settings-subject-size-multipl Chapter: EthoVision XT Advanced Detection Settings: Subject Size (Multiple Animals Per Arena) Aim To specify the average (and variation) of size of subjects, when tracking multiple subjects per arena. Important: When setting the Subject size, make sure the animals do not touch each other. To Set Subject Size - In the Subject size section, click the Advanced button. In the Size window, in the figure at the top, the thin red contour represents the current size of what EthoVision XT assumes is the animal shape. - To set the Detected subject size, proceed with step 2. Set the Detected subject size to ensure that small or very large objects are not detected as a subject. - To set the Modeled subject size, proceed with step 3. Set the Modeled subject size to obtain an estimate of the subject's body size, and body position of the different subjects when they overlap or touch. - Set the Minimum and Maximum subject size (represented by a green contour): - Maximum subject size: The largest surface area (in pixels) that is detected as the subject. Objects bigger than the Maximum subject size, for example, the experimenter's arm, are detected as noise and not tracked. Decrease the Maximum subject size until its thick green contour surrounds the thin red contour by a fair margin. - Minimum subject size: The smallest surface area (in pixels) that is detected as the subject. Objects smaller than the Minimum subject size, such as droppings or disturbed sawdust, are detected as noise and not tracked. Increase the Minimum subject size until its thick green contour is smaller than the thin red contour by a fair margin. The two sliders are interdependent. So, after you have set the Minimum subject size, when you next change the Maximum subject size, the slider for the Minimum subject size also moves (although the size in pixels stays the same). - In the Modeled subject size group, select Apply settings to all subjects if your multiple animals have similar sizes. - Select one of the subjects to model the subject size for, by clicking the name of the subject. - Next, adjust the modeled subject size (under Average - pixels) to the detected subject size (under Current - pixels). You do this by clicking the Grab button. Keep clicking the Grab button until the modeled (Average) subject size equals the detected (Current) subject size. When the modeled (Average) subject size equals the detected (Current) subject size, the following becomes visible: - In the Modeled subject size group: the Average subject size now equals or is larger than the Current subject size. - In the Video window: the modeled subject size now completely overlaps with the current subject size. - In the Size window: the bold yellow contour represents the modeled subject size. This now coincides with the detected subject size indicated by the thin red contour. - You can now set the Tolerance. Click the corresponding cell and enter a value. The Tolerance determines the deviation of the average subject size. When the Current detected size deviates more from the Average subject size than the Tolerance, then the object is not considered to be the subject anymore and EthoVision starts making an educated statistical guess about the body contour of the animal. This is visible in the Video window by a wobbling marker-color area. When this happens when animals do not touch, you should increase the Tolerance. - Select the Fix check box for each subject. - Optionally click Advanced Modeled Parameters and change the settings for the Maximum noise size, Shape stability, and Modelling effort (see below). Subject Size When Tracking Multiple Fish Click Grab until the body fill color covers the whole body. Or, enter the body size under Average and select Fix. Keep Tolerance high (70–100%). Make sure that in the Subject size window, the red contour oscillates within the limits of the Average subject size (bold yellow contour). If that is not the case, click Grab when you see in the Video window that the subjects are detected correctly, or enter the appropriate value of size in the Average cell, then select Fix. --- ## EthoVision XT 19 - Configure Detection Settings - Advanced Modeled Parameters URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-advanced-modeled-parameters Chapter: EthoVision XT Advanced Modeled Parameters Maximum Noise Size Set the Maximum noise size. The value should be lower than the minimum subject size, but high enough to make sure that small objects with the same contrast as the subject are not detected. Shape Stability The Shape stability setting is used when you track animals whose body can be occluded by, for example, cage bars or part of the body of another animal. When this happens, the animal's body consists of two separate objects that are close together. The Shape stability optimized for slider has two extreme settings: - Occlusions: When you set the slider close to Occlusions, EthoVision considers separate objects that are close together part of one animal. - Noise: When you set the slider close to Noise, EthoVision considers separate smaller parts not part of the animal. If you are not sure which setting to select, leave Shape stability at the default value of 620. Modeling Effort The Modeling effort setting is used when two animals touch and EthoVision loses the separate shapes. At this point, EthoVision tries to determine which part of the big merged body fill belongs to either animal, which costs a lot of processing load. The Modeling effort optimized for slider has two extreme settings: - Performance: When you set the slider close to Performance, EthoVision is only allowed a short time to determine which part of the merged body fill belongs to which animal. Therefore, modeling quality is low. - Modelling: When you set the slider to Modelling, EthoVision XT is allowed a longer time per frame to determine which part of the merged body fill belongs to which animal. Therefore, modelling quality is good, but this costs a lot of processor load. We recommend selecting Modelling only when you have a computer that exceeds the minimum system requirements. When you are not sure which setting to select, leave Modeling effort at the default value of 500. Tips for Setting the Subject Size - Make sure you do not set the Tolerance too small; it is better to get a wrong body size/shape than a wrong location of the animal. - It is better to set the Average subject size slightly bigger than the actual subject size, especially when you carry out nose-tail tracking. - If you want to carry out live tracking with multiple similarly-sized animals, it is recommended to first introduce one animal into the arena and make the Subject Size settings for this animal. - If the subject size changes a lot between trials, it is recommended to create new Detection Settings for this new size. Advanced Detection Settings for Color Marker Tracking Aim To specify which colors EthoVision XT should follow when tracking color markers. Prerequisites - You have marked the animals. - In the Experiment Settings under Tracked Features you selected Color marker tracking (treat marker as center-point). Note that with this option you track only the marker, while the animal's shape is ignored. Procedure - Put the marked animals in the arena or play the video. Optimize the camera setup, lighting conditions and marker characteristics. See Tips for color tracking. - In the Detection Settings window, under Video, select the image source and sample rate. See Video file, image quality and sample rate. - In the Detection Settings window, click Subject Identification. - Carry out steps 4 to 9 in Advanced detection settings: Marker-assisted identification for all subjects. No additional settings are necessary. EthoVision XT tracks the markers and makes no estimate of the body contours. Detect the Nose and the Tail Base Learn About - Overview of nose-tail base detection - Optimize nose-tail base detection When Do I Need This Information? In the Experiment Settings, under Tracked features, you chose Center-point, nose-point and tail-base detection. Choose the procedure based on what you selected under Body point detection technique. Contour-Based Technique Follow the procedure in this order: - Adjust the settings for nose-tail base detection (Contour-based) - Adjust Advanced detection settings: Smoothing - Adjust Subject contour for nose-tail base detection - Adjust Subject size for nose-tail base detection Deep Learning Follow the procedure: Adjust the settings for nose-tail base detection (Deep learning). Note: Subject size and contour do not affect the performance of the Deep learning algorithm. Therefore, EthoVision XT should be able to find the nose and tail base points also when the detection of the subject's body is not optimal. However, we advise you to adjust the settings for size and contour, especially if you want to analyze the body's mobility. Overview of Nose-Tail Base Detection When you set an experiment for Nose-tail base detection, EthoVision XT analyzes the contour of the area detected as subject at each sample, and assigns Nose-point and Tail-base to two specific pixels of the contour. Furthermore, it determines the direction the animal is supposed to point to (Head direction). Nose-tail base detection is optimized for rodents and for adult fish, depending on the method used. Nose- and Tail-Base Points The two points are detected independently through one of two complex algorithms. The nose-point is found in all cases, except when the center-point is not found either. The tail-base may not be found in a few cases if detection is good. Reliable tracking of nose and tail-base is limited by the size of the video image. You can mix four camera images like in the case of a group of PhenoTypers, with good results. Mixing 16 camera images makes the subjects too small for reliable nose and tail-base tracking. Head Direction Once the nose-point has been found, two points are determined along the contour lying at a specific distance from the nose-point. The Head direction is the line dividing equally the angle formed by the center and those additional points. Important: If you use Nose-tail tracking with two or more subjects per arena, track from video file instead of live. --- ## EthoVision XT 19 - Configure Detection Settings - Analyze Trial Control Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-analyze-trial-control-data Chapter: EthoVision XT Analyze Trial Control Data Aim To analyze the events of the Trial Control rule which occurred during a trial. For example, visualize when a condition became true, or when EthoVision sent a command to an external device. You may want to do this for two reasons: - To test if the Trial Control rule works as expected. - To analyze the subject's response to presentation of stimuli in conditioning tests. To Visualize or Calculate Statistics of Trial Control Data - Choose Analysis > Analysis Profile > New. In the Components pane, under Trial Control, click the button next to: - Trial Control event — for example, to visualize when exactly a condition became true. - Trial Control state — for example, to visualize the time from the moment a condition became active to when the condition became true. - Calculate statistics or visualize the data (choose Analyze > Results > ...). For details, see Trial Control in the Analysis Profile (page 1116), and Analysis of Trial Control Data in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To Analyze Intervals Based on Trial Control Data If you want to calculate statistics and visualize data of dependent variables like velocity in portions of a track based on Trial Control data, do the following: - In the Data profile, define an interval based on Trial Control data. You can use: - Nesting over a Trial Control state, or - Nesting over a Free interval based on Trial Control events. - Specify the dependent variables in the Analysis profile. - Calculate statistics or visualize the data (choose Analyze > Results > ...). To Export Trial Control Data See Export Trial Control Data. Configure Detection Settings Main Topics and Tasks - Introduction to Detection Settings - Video file, image quality and sample rate - Detection settings: Automated setup - Detection settings: Advanced setup - Advanced detection settings for tracking multiple unmarked subjects - Advanced detection settings for tracking color-marked subjects - Detect the nose and the tail base - Detection settings for Behavior recognition - Activity settings - Optimize the reference image - Customize the Detection Settings screen Introduction to Detection Settings Learn About - Useful things to know about Detection Settings - Adjust detection settings - General procedure - Detection settings: Automated setup - Detection settings: Advanced setup Useful Things to Know About Detection Settings Detection Settings are a set of criteria to track moving subjects. Detection Settings specify, for example, how different the subject is from the background in terms of gray scale or color values, and how many images per second will be analyzed among those available. You can create multiple Detection settings in the same experiment. For example, you can have one set for detecting white animals, and another to detect dark ones. Tip: For a DanioVision experiment, see the DanioVision DVOC-0041 - Reference Manual. To open this manual, on the Apps screen choose Noldus > EthoVision XT 19 Other Documentation. To Open the Detection Settings Choose Setup > Detection Settings > choose one of the options. By default, the following windows are displayed: - A. Detection Settings - B. Video, showing the current camera image or video file. - C. Playback Control - D. Detection Performance. Click the Show/Hide button on the toolbar to view/hide windows, or change features shown, like the yellow blob representing the subject being detected. Automated Setup EthoVision XT has an Automated Setup function to apply the detection settings that work well in the most common scenarios. In most cases you will obtain good detection using the Automated Setup. In difficult situations, for example if video quality is bad, or if you have multiple animals with color markers that are not distinct enough, the Automated Setup may not give good enough detection. If this is the case, use the advanced settings to create the detection settings manually. Detection Settings Available in Your EthoVision XT License Which settings are available depends on your EthoVision XT license: - EthoVision XT Base version: In this version, you can track the center-point, the nose-point and the tail-base point of a single animal. The base version also allows tracking of a color marker on a single animal; in this case the color marker is treated as the center-point of the animal. - Social Interaction Module: This add-on allows you to track two or more animals in one arena, either color-marked or unmarked. Use this module in combination to study social interactions in detail. We recommend to only use tracking from video files if you track the three body points in combination with the Social Interaction module. - Behavior Recognition Module: For detecting a number of behaviors automatically, including rearing, grooming and sniffing. In the Detection Settings, the Behavior Settings are enabled. --- ## EthoVision XT 19 - Configure Detection Settings - Calculation of the Center-Point URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-calculation-of-the-center-point Chapter: EthoVision XT Calculation of the Center-Point For New Experiments In all new experiments, the subject's center-point is determined using the area of the blob that indicates the detected subject. The x, y coordinates of the center-point are the average of the x, y coordinates of each pixel in the blob. If the tail is detected, that contributes to the position of the center-point. Experiments Created in EthoVision XT 14 and Earlier If your experiment was created in a previous EthoVision XT version, and you use one of the For Occlusions methods, you can choose whether to use the detected area (as described above) or the shape model. Choose Use center of model (XT14 and earlier). The x, y coordinates of the center-point are the average of the pixel coordinates of the model fit over the detected subject. In many situations the model has a more regular shape than the detected area. Choose Use center of model (XT14 and earlier) to keep compatibility with older experiments. Note that if detection or the model parameters are not optimal, the model may differ greatly from the subject's image. In this case the center point may shift compared to the expected position, which may add up distance moved over time. If that happens often, choose Use center of detected area. Or, for multi-subject tracking, adjust the modeled subject size. See Advanced Detection Settings: Subject Size (Multiple Animals per Arena). See Also - Adjust the Settings for Nose-Tail Base Detection (Contour-Based) - Subject Contour for Nose-Tail Base Detection Advanced Detection Settings: Smoothing Aim To make tracking less dependent on noise. - Use Video pixel smoothing to remove fine-grained noise in the video image. - Use Dropped frames correction to compensate for irregular frame rate in low-end cameras. - Use Track noise reduction to reduce jitter of the body points and smooth out the track during acquisition. How to Access These Options In the Detection Settings window, under Advanced, click Smoothing. Procedure - Video Pixel Smoothing - Dropped Frames Correction - Track Noise Reduction See Also - Smooth the Tracks After Acquisition Video Pixel Smoothing Aim The Video pixel smoothing option reduces the difference between adjacent pixels prior to detection, by smudging the image — that is, replacing the gray scale value of each pixel with the median of the surrounding pixels. Background Information In the following example, a bright pixel with gray value 240 is surrounded by darker pixels: - If you select Video pixel smoothing = Low, that pixel gets the median value calculated among the 8 nearest pixels plus that pixel itself. In that case the median is 150, so that pixel will look darker. - If you specify Video pixel smoothing = Medium, the median is calculated over the 24 nearest pixels plus the pixel itself. - If you specify Video pixel smoothing = High, an even bigger group of surrounding pixels is considered. Procedure - In the Detection Settings, under Advanced, open Smoothing. - Next to Video pixel smoothing, choose one of the values: - None (default): No pixel smoothing. The video image is analyzed for subject detection as it is. - Low: Each pixel is blended with the 8 nearest pixels (pixel distance = 1). - Medium: Each pixel is blended with the 24 nearest pixels (pixel distance 1 or 2). - High: Each pixel is blended with the 48 nearest pixels (pixel distance 1, 2 or 3). Notes - Select a moderate Video pixel smoothing value or leave None selected if adjacent pixels in the background are relatively constant. Using more surrounding pixels for the smoothing effect does not bring better results. - Select a high Video pixel smoothing value if adjacent pixels in the background are on average very different — for example, when the cage's bedding material looks grainy. In such cases you need to smooth each pixel using more surrounding pixels to compensate for this variation. - A high Video pixel smoothing level requires a significant amount of processor capacity. - Using Video pixel smoothing may result in losing information in the video image that is important for detection, such as sharp borders of subjects. - Pixel smoothing does not affect Color marker tracking. It does affect detecting the body contour in Marker assisted tracking. See Also - Advanced Detection Settings: Smoothing --- ## EthoVision XT 19 - Configure Detection Settings - Detection Settings: Automated Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-detection-settings-automated-setup Chapter: EthoVision XT Detection Settings: Automated Setup Aim To quickly instruct EthoVision XT how to recognize the subject that moves in the arena. For common tests like the Open Field and the Morris Water Maze, choose Automated Setup. If Automated Setup does not work well enough, see Detection Settings: Advanced Setup. Prerequisites - The subject must be released in the arena. If you work with pre-recorded video, play the video to a point when the subject is well visible. - The contrast of the subject with the background is crucial for success with video tracking software. Choose Help > Video Tutorial and watch the video chapter Set up your Test Environment for tips on how to improve the contrast between the subject and the background. Procedure - In the Detection Settings pane, click the Automated Setup button. - Choose the type of animal you work with, then click Next. - Drag the mouse to draw a rectangle around the subject. - If you have multiple subjects, draw a rectangle around each of them. Make sure that the subjects are not in contact with one another. - If you have multiple arenas, draw a rectangle around each subject in every arena. - For rodents, draw the rectangle around the animal's body. Try to leave the tail out of the rectangle. - For fish, always include the caudal fin in the rectangle. - Move the Finetune slider until detection quality is satisfactory. Moving the slider to the left detects more from the subject, for example it results in including the legs and tail of a rodent, but also more noise. Moving the slider to the right results in detecting less noise, but also less of the subject. - Check in the Detection Performance pane under Subject Not Found if detection is good. As a guideline, the percentage Subject Not Found should be lower than 10% if the animal is visible at all times. Realize that the initial frames in which the subject was not detected yet is included in this percentage. If the number of samples (in brackets) under Subject Not Found does not increase or hardly increases anymore, and the percentage Subject Not Found decreases, detection is good. After acquisition, in the Trial List click the Show/Hide button and select Variables. Select Subject Not Found and check the percentage in the Subject Not Found column. - If detection quality is satisfactory, click Yes. If not, click No and continue with Detection Settings: Advanced Setup. Notes - If you work with the Deep Learning detection technique, the Automated Setup also includes the automatic adjustment of the Cutout window. This makes it less likely that you need to adjust this setting once again. See Adjust the Settings for Nose-Tail Base Detection (Deep Learning). The Next Step What you do next depends on how many subjects and what EthoVision XT functions you want to use. - One subject per arena; Center-point detection: At this point you do not need to do anything anymore. If detection is not good enough, see Detection Settings: Advanced Setup. - One subject per arena; Nose-tail detection: See Detect the Nose and the Tail Base. - Social interaction (marker-assisted identification): See Advanced Detection Settings: Marker-Assisted Identification, step 4. If not all subjects are detected well after the Automated Setup, click No. Click Automated Setup again, and repeat the procedure when the subjects are in other locations. If this does not help, see Advanced Detection Settings for tracking color-marked subjects. - Social interaction (unmarked subjects): See Advanced Detection Settings for Tracking Multiple Unmarked Subjects. - Rat or Mouse behavior recognition: See Detection Settings for Behavior Recognition. If detection is not satisfactory after the Automated Setup, continue with Detect the Nose and the Tail Base. Then proceed with Detection Settings for Behavior Recognition. Detection Settings: Advanced Setup If you do not get satisfactory detection with the Automated Setup, in the Detection Settings pane click Advanced. To Track One Animal Per Arena, Center-Point Only Follow the procedures in this order: - Advanced Detection Settings: Method - Advanced Detection Settings: Smoothing - Advanced Detection Settings: Subject Contour - Advanced Detection Settings: Subject Size (One Subject Per Arena) Other Cases - For tracking multiple animals per arena, color-marked: See Advanced Detection Settings for Tracking Color-Marked Subjects. - For tracking multiple animals per arena, unmarked: See Advanced Detection Settings for Tracking Multiple Unmarked Subjects. - For tracking center-point, nose-point and tail-base: See Detect the Nose and the Tail Base. - For Behavior Recognition: See Detection Settings for Behavior Recognition. - For tracking larvae in DanioVision: See the DanioVision DVOC-0041 Reference Manual. To open this manual, on the Apps screen, choose Noldus > EthoVision XT 19 Other Documentation. --- ## EthoVision XT 19 - Configure Detection Settings - Dropped Frames Correction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-dropped-frames-correction Chapter: EthoVision XT Dropped Frames Correction Aim To interpolate data points when a video frame is not available at the required sample time. Note: This information does not apply if you use analog cameras, GigE cameras and USB cameras supported with EthoVision XT. Normally those cameras do not skip a significant number of video frames, provided that you set the camera properly, especially the resolution, the frame rate and the exposure time. For digital cameras, see Configure the Digital Camera. Important: This correction only deals with missing video frames, not when EthoVision XT does not detect the subject in a valid video frame, for example because of wrong detection settings. If you want to interpolate the points when the subject was not found, do this in the Track Editor. See Interpolate Points. Background Information Some low-end cameras like webcams and IP cameras are not capable of achieving a fixed video frame rate. With those cameras, the time between two consecutive video frames is not constant enough, so that EthoVision XT cannot assign a video frame to a specific sampled time. EthoVision XT accepts video frames originated from a camera or a frame grabber, and assigns them to the expected sample time t, t+1, t+2, etc. according to the specified sample rate. In the figure below, frames 1 and 3 arrive at the expected times. Frame 2 arrives a bit late but it is assigned anyway to its expected time. In all those cases EthoVision XT produces a valid sample. However, if video frames do not arrive for significant time, no frame is assigned for one or more sample times. The result is a missing sample at time 3. Note that, because a frame was missing, frame 3 is assigned to time 4. Whenever missing samples occur, EthoVision XT can fill the gaps with interpolation, using the adjacent valid samples. Procedure - In the Detection Settings, under Advanced, open Smoothing. - Next to Dropped Frames Correction, do one of the following: - Select On if you want to apply the dropped frames correction. The missing samples will be replaced with valid samples obtained with linear interpolation. - Select Off (default) to leave the missing samples. If you select Off, you can always interpolate the missing samples after acquisition, in the Track Editor. See Interpolate Points. Notes - Dropped frames correction occurs during tracking. Interpolation is performed only for missing samples due to dropped frames. EthoVision XT interpolates between the last valid sample before a missing sample and the first valid sample after the last missing sample, for a maximum of 10 consecutive dropped frames. If more than 10 dropped frames are found, correction is not done, and the subject remains missing for those samples. - Dropped frames correction does not change the video time of the valid video frames. For example if the frame rate is not exactly 30 fps, the time between subsequent frames will not be exactly 1/30 s = 0.03333 s. Small differences in the time between subsequent frames remain. - Interpolation is only applied to the body points, and to the subject area. The center point is interpolated linearly using the center points in the adjacent samples. The nose- and tail-base point are obtained by doing interpolation on the angles formed by the segment joining the nose-point, the center point and the tail-base point. See How the Nose-Point and Tail-Base Point Are Interpolated. - Interpolation is not applied to: body elongation, head direction, area change from the previous sample (used to calculate mobility), and activity. Those values remain missing for the interpolated sample. - To know the percentage of video frames actually corrected, see View the Detection Statistics. See Also - Advanced Detection Settings: Smoothing --- ## EthoVision XT 19 - Configure Detection Settings - Dynamic Subtraction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-dynamic-subtraction Chapter: EthoVision XT Dynamic Subtraction Aim To detect the subject, while compensating for temporal changes in the background. Examples - Detect a rat in a water maze, where other detection methods do not work, usually because of the effect of waves in the pool. - Detect a mouse in a PhenoTyper or home cage with bedding material, where the animal's activity (e.g. digging) changes the appearance of the background. - All cases where lighting changes slowly. How Dynamic Subtraction Works Like with Static subtraction, EthoVision XT compares each sampled image with a reference image, with the important difference that the reference image is updated regularly. This compensates for temporal changes in the background. See How the Reference Image Is Updated in Dynamic Subtraction. Procedure - In the Detection Settings pane, click Advanced, then Method. Select Dynamic subtraction. - Click the Background button. The Reference Image window opens with the image that is currently used as background. The aim is to obtain a reference image that does not contain images of the animals you want to track. To do so, follow the instructions on the screen in consecutive order. If A fails, move on to B; if that fails, move on to C. See Optimize the Reference Image. - From the Subject color list, select one of the options from the list, depending on the color of the subject you want to track. - Move the slider next to Bright/Dark to select the range of the contrast between subject and background. - Move the slider next to Frame weight or enter the value in the appropriate field to specify how the reference image is updated (range 0–100%). In typical situations, a value between 1–5 gives a good result. Important: As much of the animal's body as possible must be detected for good tracking. See Advanced Detection Settings: Subject Contour to optimize body detection. Frame Weight - Select a low value if you want a large number of past images to contribute to each reference image. As a result, changes in the background are diluted over many images. Choose a low value when the background changes slowly. - Select a high value if you want a small number of past images to contribute to each reference image. As a result, changes in the background are captured over a short time. Choose a high value when the background changes rapidly, for example when the subject is very active and moves the bedding material around. - If you select 0 as Frame weight, the reference image is not updated. This is the same as using Static Subtraction. - If you select 100, each sample gets its own reference image with no contribution from past images. In most cases a Frame weight of 100 does not give good detection, because the subject itself is often removed from the detected image when it moves slowly or sits still. Tip: To find the optimal Frame weight, set a value and carry out one or more trials. Evaluate whether the tracking was satisfactory. If not, increase or decrease the setting by 20% and try again. Differencing Aim To detect the subject, while compensating for spatial and temporal changes in the background. How Differencing Works Like with Dynamic subtraction, the Differencing method updates the reference image over time. Differencing makes a statistical (probabilistic) comparison between each pixel in the reference image and the pixels of the current image. The statistical comparison uses the variance in the contrast between the current and reference image to calculate the probability that each pixel is the subject. The Differencing method takes more processor load than the subtraction methods. Therefore, when using Differencing, make sure your computer meets the system requirements. Procedure - In the Method section of the Detection Settings window, select Differencing. - Click the Background button. The Reference Image window opens with the image that is currently used as background. The aim is to obtain a reference image that does not contain images of the animals you want to track. To do so, follow the instructions on the screen in consecutive order. If A fails, move on to B; if that fails, move on to C. See Optimize the Reference Image. - From the Subject color list, select one of the options from the list, depending on the color of the subject you want to track. - If necessary, adjust the position of the Sensitivity slider and change the option selected in the Background Changes list. - The Sensitivity slider determines what difference in contrast from the background is seen as the animal. For an image with good contrast, there is no need to change the slider. For images with less contrast, adjust the position of the slider to the right or left until the subject is properly detected. - In the Background Changes list, select options that reflect how fast the background changes. For example, a cage with bedding might change a lot because of animals kicking around the bedding material. In this case, to prevent changes in the background from interfering with detection, select Medium fast or faster. Usually, Medium slow works just fine. Important: As much as possible of the animal's body must be detected for good tracking. --- ## EthoVision XT 19 - Configure Detection Settings - How the Reference Image Is Updated in Dynamic Subt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-how-the-reference-image-is-updated-in-dynamic-subt Chapter: EthoVision XT How the Reference Image Is Updated in Dynamic Subtraction A video stream is composed of a number of video images (frames). During data acquisition, EthoVision XT analyzes one every x images according to the sample rate specified. When analyzing the sample (image) n, the reference image is obtained by summing up the gray scale values of each pixel from two images: - The reference image made of pixels which have an average value of previous images. - The current image, where a square area around the subject detected in the previous sample has been removed. This provides a rough estimate of the current background. The gray scale values are summed up according to the formula: Referencei,n = (1-α) * Referencei,n-1 + α * Currenti,n for each pixel i, where: - Referencei,n = Gray scale value of pixel i in the reference image of sample n. - Referencei,n-1 = Gray scale value of pixel i in the reference image of sample n–1. - Currenti,n = Gray scale value of pixel i in sample n where a square area around the subject previously detected has been removed. - α = Current Frame weight. The Current Frame weight determines the relative weight of the two components of the new reference image. Because the above formula is recursive, that is, each value of Referencei,n is also a function of the previous sample, the value of α determines the number of past images that contribute to the reference image for the sample n. The lower α, the more past images contribute at least partially to the current reference image. The extent to which each past image contributes to the current reference image is a power function of 1-α. The older an image relative to the current one, the smaller its contribution to the reference image. If α=20%, then 1-α =80%. The first video image contributes by 80% to the second sample, by 80%2 =64% to the third sample, then by 80%3 =51% to the fourth sample, etc. At the 21st sample, the contribution by the first image gets below 1%. In the Dynamic Subtraction detection method, the reference image is updated at each sample. The starting reference image is the one you specify by clicking one of the buttons in the Reference Image window, otherwise it is the first frame analyzed. For the general sample n, the reference image is obtained by summing the reference image of the previous sample n–1 and the current image n where the area around the subject estimated from the previous sample has been removed. The current image with subject removed is given the weight α that you specify, while the previous reference image is given the weight (1-α). Because of the way it is determined, each reference contains information on a number of past images, depending on the value of α. How the Reference Image Is Updated in Differencing The Differencing method uses a Gaussian distribution of all pixels in a frame. EthoVision XT keeps a running average of the mean μ and the variance σ2 of the gray value of each pixel to detect unlikely pixels. These pixels are considered to be the subject. The mean of the gray values is summed up according to the same formula as for Dynamic Subtraction. The variance of the gray values is summed up according to the following formula: Variancei,n = (1-α) * Variancei,n-1 + α * (Currenti,n. Referencei,n)2 for each pixel i, where: - Variancei,n = Variance of gray scale value of pixel i in the reference image of sample n. - Currenti,n = Mean gray scale value of pixel i in sample n where a square area around the subject previously detected has been removed. - Referencei,n-1 = Mean gray scale value of pixel i in the reference image of sample n–1. - α = Frame weight, which depends on the Background changes option. The higher the value set (from Very Slow to Very Fast), the higher α. The Frame weight determines the relative weight of the two components of the new reference image (see the example in How the Reference Image Is Updated in Dynamic Subtraction). Customize the Detection Settings Screen To achieve optimal subject detection, you need proper feedback about the effect of your settings on the quality of detection. EthoVision offers you a number of statistics for this purpose. What Do You Want to Do? - View the detection features on the video window - View the detection statistics --- ## EthoVision XT 19 - Configure Detection Settings - Methods for Estimating the Body Points URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-methods-for-estimating-the-body-points Chapter: EthoVision XT Methods for Estimating the Body Points Depending on the experiment mode (standard vs. DanioVision) and how many subjects and body points you specify in the Experiment Settings, the Method section of the Advanced Detection Settings window lists one or more options. Note: In some cases, like when tracking the center point of one subject, this group of options is not available, because EthoVision XT applies the only method possible for that experiment. Any Species / Default - This was called Shape-based / Any in EthoVision XT 14 and earlier. - This method analyzes the contour of the blob detected as subject at each sample to assign the nose-point and the tail-base. If you track rodents, make sure that the tail is fully detected. - The subject's center-point is calculated as the geometric center of the area detected as subject. See Calculation of the Center-Point below for details. - This method is automatically activated when you track the center-point in one animal per arena, and you specified Other species in the Automated setup. - If your experiment is from an older EthoVision XT version, you have additional options available. Here you can choose to use the last improvements or keep the settings as they were in the older experiments. - Choose Priority on tail base position whenever the tail is apparent in the video and well detected. This method finds the tail base and then assigns the nose-point to the opposite point in the subject contour. If the tail base is not found, then other rules based on the contour are used to find the nose-point. Choose Balanced (XT 14 and earlier) if you want to use the same method as in previous EthoVision XT versions, or if for any reason the first option does not give good results. Rodents / Default - This was called Simple Model / Rodents in EthoVision XT 14 and earlier. - This method analyzes the shape of the blob detected as subject and builds up a "rodent model". It is more robust than the Any Species / Default method because it does not require the nose and tail to be visible: it can predict the position of the nose and the tail based on previous samples. - The subject's center-point is calculated as the geometric center of the area detected as subject. See Calculation of the Center-Point below. - Choose this method when you want to track a single rodent without occlusions or without difficult tracking conditions, like in an open field or a novel object recognition test. For optimal results, make sure in the detection settings that the tail is removed from the body contour, using Erosion and then Dilation. See Advanced Detection Settings: Subject Contour. - If you upgrade your experiment from an older version of EthoVision XT, select Extra correction of nose-tail swaps to use the latest algorithm that aims at correcting nose-tail swaps during tracking. Compared to previous versions, this algorithm corrects swaps faster, reducing the total number of samples with swaps (if they occur). Choose EthoVision XT 15 and earlier if you want to keep using the old algorithm. - The extra correction is based on the detection of false backward movements, that is, when the animal looks like it is moving backward when the nose and the tail-base points are swapped. Rodents / For Occlusions - This was called Advanced Model / Rodents in EthoVision XT 14 and earlier. - This method learns the animal shape and how it moves in the first 15 frames and continually updates its statistics. Therefore, it can handle severe shape distortions, such as when the subject's body is occluded or when two subjects come into contact. However, it requires a lot of computer performance. - The subject's center-point is calculated as the geometric center of the area detected as subject. For experiments created with previous EthoVision XT versions, choose how EthoVision XT should find the center point. See Calculation of the Center-Point below for details. - Choose this method for rodents in a social interaction context, or when you track rodents that can be occluded, for example, by bars or other objects in the cage. For optimal results, make sure in the detection settings that the tail is removed from the body contour, using Erosion and then Dilation. See Advanced Detection Settings: Subject Contour and Subject Contour for Nose-Tail Base Detection. Adult Fish / For Occlusions - This was called Advanced Model / Adult Fish in EthoVision XT 14 and earlier. - Choose this method to track adult zebrafish and other fish of similar shape, when viewed from above. Make sure that the whole body of the fish is detected, including the tail. This method is recommended no matter how many fish you track in the same tank. - The subject's center-point is calculated as the geometric center of the area detected as subject. For experiments created with previous EthoVision XT versions, choose how EthoVision XT should find the center point. See Calculation of the Center-Point below for details. Other Species / For Occlusions - This was called Advanced Model / Other in EthoVision XT 14 and earlier. - This method does not make any assumption about the shape of the subject. Note: with this method you only track the center point. - The subject's center-point is calculated as the geometric center of the area detected as subject. For experiments created with previous EthoVision XT versions, choose how EthoVision XT should find the center point. See Calculation of the Center-Point below for details. - Choose this method to track insects, crustaceans or large animals, and when multiple subjects move in the same arena, or when occlusions make detection difficult. - Also choose this method to track fish from the front view of the water tank when the Adult Fish method does not give good results. DanioVision - This method is optimized to track zebrafish larvae on a white background. It is only available in DanioVision experiments. - Moving the Sensitivity slider to the left results in detecting more of the body of the larvae, but also more noise. Moving the slider to the right results in detecting less noise, but also gives less good detection of the larvae. - For more information, see the DanioVision DVOC-0041 - Reference Manual. Method Names The names of the methods differ from those used in EthoVision XT 14 and earlier versions: EthoVision XT 15–17 EthoVision XT 12–14 EthoVision XT 11 and Earlier Any Species / Default Shape-based / Any Shape-based (XT 4) Rodents / Default Simple Model / Rodents Model-based (XT 5) Rodents / For Occlusions Advanced Model / Rodents Advanced Model-based (XT 6) Adult Fish / For Occlusions Advanced Model / Adult Fish — Other Species / For Occlusions Advanced Model / Other — --- ## EthoVision XT 19 - Configure Detection Settings - Optimize Nose-Tail Base Detection URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-optimize-nose-tail-base-detection Chapter: EthoVision XT Optimize Nose-Tail Base Detection Because of the way the nose- and tail-base points are found, nose-tail base detection is much depending on the quality of the video image and the experimental setup. Before using this feature, please check the following guidelines. Conditions Related to the Arenas - Light: Light conditions must be equal across the arena. Try to remove shades, light spots and reflections. For proper detection, the subject's body contour must be kept as constant as possible across the whole arena. - Subject/Background Contrast: The color of the subject and of the background must be contrasting enough to get a full and clear body contour. - Video Quality: Noise and interference reduce the proportion of samples which are correctly detected. - Noise Reduction: The Video Pixel Advanced Detection Settings: Smoothing function can sometimes help getting a more appropriate body contour. However this is of little use if the video has too much noise or too little contrast. - Areas Hidden to the Camera View: When the animal enters or exits areas hidden to the camera (for instance, a shelter), nose-point and tail-base are wrongly assigned. - Number of Arenas: Reliable tracking of nose and tail-base is limited by the size of the video image. You can mix maximally four camera images like in the case of a group of PhenoTypers, with good results. Conditions Related to the Subjects - Subject's Apparent Size: The subject must be large enough to get a constant body contour. Small animals and large arenas pose detection problems with nose- and tail-base points. When you mix the image of multiple cameras with a quad unit, like in the case of a group of PhenoTypers, a group of 4 cameras gives good results. When mixing 16 PhenoTypers, the apparent size of the subject is generally too small. - Subject's Color Variation: For hooded rats, both the flanks (white) and the head (dark) must contrast with the background, otherwise detection of body contour is sub-optimal. In the Detection Settings, next to Subject color compared to background select Brighter and darker than background. You can also try the Differencing detection method instead of the Subtraction methods. - Subjects in a Water Maze: Tracking nose- and tail-base points in a water maze is impossible because the tail-base is under the water, and it is not possible to obtain a proper body contour. - Subject's Behavior: Immobile animals are hard to track because their body contour differs from that of a mobile animal. Nose-points are therefore hard to detect. Important Choices - Tracking Live vs. from Video Files: We recommend tracking from video files if you use one of the methods named For Occlusions. Tracking live requires high processor load, which may result in many missing points, especially when you use multi-subject tracking and multiple arenas simultaneously. - When Tracking from Video Files: Keep the DDS (Detection determines speed) option selected, unless you score behaviors manually. - Missing Tail-Base Points: A high percentage of missing tail-base points is an indication of poor detection. The higher this percentage, the greater the probability that the nose-point is not placed in the correct location. To estimate the proportion of missing tail-base points, run some test trials and visualize the Sample list in the Track Editor screen. You can also calculate the Number of samples as a statistic for a dependent variable such as Velocity for the nose point. In Practice The contour of the blob detected as subject is crucial for proper detection of nose- and tail-base points. If only part of the subject is detected, EthoVision XT may swap the pixels assigned as nose-point and tail-base, or the nose-point may not be placed on the subject's nose tip. If you use a Subtraction method, select a wider range of gray scale values or, for Differencing, adjust the sensitivity to increase the number of pixels detected as subject. Detection of the tail depends on which method you use for detecting the body points. See Methods for Estimating the Body Points. - When you use the Any Species / Default method for estimating the body points, make sure that the tail is fully detected. - When you use one of the Rodents methods, remove the tail from the detected subject using the Erosion then the Dilation filter. See Subject Contour for Nose-Tail Base Detection. --- ## EthoVision XT 19 - Configure Detection Settings - Sample Rate URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-sample-rate Chapter: EthoVision XT Sample Rate The sample rate is the number of images EthoVision XT analyzes per second. Selecting a certain sample rate does not mean that the program can always analyze data at that rate. If the computer processor load is too high, EthoVision XT may skip a sample and analyze the next one. Skipped samples result in missed samples. The maximum sample rate is the camera frame rate. The sample rate you set in EthoVision XT can only be the frame rate divided by an integer. For example, for PAL video it is 25, 12.5, 8.33, etc. Important: Some digital cameras support very high frame rates. However, subject detection at such rates requires a lot of processor capacity. To prevent EthoVision XT from discarding samples while tracking live, do not set the frame rate and sample rate too high. Check the percentage of missed samples (see View the Detection Statistics) to make sure EthoVision XT can handle the selected frame rate. What Is the Optimal Sample Rate? Setting the correct sample rate is very important. If the rate is too high, the noise caused by small movements of your animal will be picked up and give an overestimate of dependent variables such as the distance moved. If the sample rate is too low, you will lose data and get an underestimate of the distance moved. General Guidelines for the Sample Rate We strongly recommend that you determine the optimum sample rate for your specific setup and animals (see To Determine the Optimal Sample Rate). If, for instance, your treatment causes hyperactivity, you will need a higher sample rate for hyperactive animals than somnolent animals. Note: In the list below, the sample rate for NTSC video (29.97/s) is approximated to 30/s. Rodents - Rat, single subject, center-point only: 5/s - Mouse, single subject, center-point only: 12/s - Rat/Mouse Behavior recognition: 25–31/s (depending on TV standard) - Rat/Mouse, three body points: 25/s (PAL) to 30/s (NTSC or digital camera) - Rat/Mouse, three body points combined with marker-assisted identification: 12.5/s (PAL) to 15/s (NTSC or digital camera) - Rat/Mouse, three body points combined with Deep learning-based identification: 25/s or higher. See Deep Learning: Requirements. Other Mammals - Tree shrew (Tupaia): 6–12/s Fish - Zebrafish, adult: 5–6/s - Zebrafish larva: For analog camera: 25/s (PAL) or 30/s (NTSC). For digital camera: 30/s or 60/s. For rapid movements you may want to track with a higher sample rate. It depends on the number of tracked subjects, the video resolution, the camera settings and the processor speed of your computer whether that is possible. - Damselfish: 5/s - Goldfish: 0.5/s Arthropods - Mite: 1/s - Parasitic wasp: 2/s - Tick: 3/s To Determine the Optimal Sample Rate The optimal sample rate is the minimum sample rate that provides an accurate estimation of the dependent variables (distance, velocity, etc.) without including the redundant information due to phenomena other than the real locomotion. For example, for an animal walking in a straight line the data points will never be in a straight line because the center-point of the subject shifts laterally with each step. In order to distinguish between real movement and effects like the one described above, you can calculate dependent variables like distance moved using the maximum or a lower sample rate. - Create new Detection Settings and specify the maximum sample rate. Be aware that the maximum sample rate also depends on the performance of your computer, the number of animals you track, and the video resolution. - Acquire data with those Detection Settings. - Calculate the dependent variable you are interested in. - Export the data to Excel and plot the dependent variable values against the sample rate. In the example below, distance moved is used. --- ## EthoVision XT 19 - Configure Detection Settings - Sample Rate Optimization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-sample-rate-optimization Chapter: EthoVision XT Sample Rate Optimization Repeat the steps above by selecting smaller sample rates. Once the data are plotted, there should be a range of sample rates for which the dependent variable value does not change much (plateau). This means that slight changes in the sample rate do not result in loss of information, or addition of redundant information (noise and movements like body wobble). Low sample rates result in loss of useful information, because the sinuosity of the original path is removed. Therefore, the total distance moved is usually decreased. High sample rates result in acquisition of redundant information. In the case of body wobbling, and assuming that the animal is moving along a straight line, the lateral shift of the body center causes the total distance moved to be longer than the real one. With Track smoothing you can filter out noise as a result of body wobble. See Smooth the Tracks. Missed Samples The actual sample rate may be lower than the maximum you set, because an image cannot be captured until the previous one is processed. If the sample rate you define is too high, EthoVision will miss samples (up to 1% is acceptable) and the processor load will be high. The percentage of missed samples is shown in the Detection Performance pane and in the Trial List as a System Variable. You can calculate the number of missed samples in acquired tracks with the Number statistic of continuous variables (e.g., velocity). If your processor load is larger than 100, and there are large amounts of missed values, you will have to lower the sample rate. After acquisition you can see the proportion of missed samples in the Trial List as one of the System Variables. When acquiring from video files, in the Playback Control window select the option DDS (Detection Determines Speed). This way, no samples will be missed. See DDS (Detection Determines Speed). Factors Affecting the Occurrence of Missing Samples The following factors may cause the processor load to be too high: - Computer memory, processor speed and video graphics card capacity: See the system requirements. In general, using a computer with a dual-core CPU helps you to work with higher sample rates than normal computers do. - Other programs installed: Do not install other video software (for example, video editing programs, DVD burning software), because this can interfere with EthoVision XT's video processing and cause a reduction in performance. - Other programs are running: Make sure you shut down all other programs, including those running in the background such as e-mail programs and virus scanners. These are usually shown in the System Tray in the bottom-right corner of your screen. - Image resolution: For live video tracking, in the Experiment Settings you can choose the resolution for your video image. - Size of arenas: Make arenas as small as possible (but including the entire area the animal can be in). - Number of arenas: If you track live and use more than four arenas in a trial, check first that no samples are missed. If the number of missed samples is too high, first make a video file, then track from that. More generally, if you track from video files the number of arenas is never a problem as long as you select DDS (Detection Determines Speed). When making detection settings, you could start with making an arena definition with only one area which speeds up the detection process. After you have finished configuring detection settings for one arena, you can add the others to the arena definition. - Display options: You can decrease processor load by minimizing the number of Track Features to be displayed. See View the Detection Features on the Video Window. - Detection method: If possible, use the Gray Scaling method which requires less processor load than Static Subtraction. Static Subtraction requires less processor load than Dynamic Subtraction and Differencing. See Advanced Detection Settings: Method. --- ## EthoVision XT 19 - Configure Detection Settings - Static Subtraction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-static-subtraction Chapter: EthoVision XT Static Subtraction Aim To detect the subject, assuming that the background does not change over time. How Static Subtraction Works The video image is converted to monochrome. Each pixel in the image has a gray scale value, ranging from 0 (black) to 255 (white). With the Static subtraction method, you choose an image of the arena without the subject, named Reference Image. When analyzing the images, EthoVision XT subtracts the gray scale value of each pixel in the reference image from the gray scale value of the corresponding pixel in the current image (live or from video files). The pixels with non-zero difference are considered the subject. You can remove small non-zero differences by defining the contrast between the current image and background that must be considered as the subject. The remaining pixels are considered as the background. The gray scale value of each pixel of the reference image is subtracted from the gray scale value of each pixel of the live image. The result is 0 for every pixel where there is no difference; if the difference is greater than 0 and within the gray scale range you have set, these pixels are considered to be the subject. With this method, your task is to specify the contrast that optimizes the detection of the subject. Procedure - In the Detection Settings pane, click Advanced, then Method. Select Static subtraction. - Click the Background button. The Reference Image window opens with the image that is currently used as background. The aim is to obtain a reference image that does not contain images of the animals you want to track. To do so, follow the instructions on the screen in consecutive order. If A fails, move on to B; if that fails, move on to C. See also Optimize the Reference Image. - From the Subject color list, select one of the following, depending on the color of the subject you want to track: - Brighter: For example, to track a Wistar rat in a black open field. - Darker: For example, to track a C57BL6 mouse in an open field with white bedding. - Brighter and darker: For example, to track a DBA2 mouse in a home cage with white background and a black shelter, or a hooded (black and white) rat in a uniform gray open field. Depending on the selection above, different contrast sliders become available. For each slider, the contrast varies from 0 (no contrast) to 255 (full contrast). Unlike with Gray scaling, the values selected with the sliders represent the difference between the current and the reference image, not absolute gray scale values. - Release the subject in the arena, or position the media file at a point where the subject is moving. - Move the appropriate slider or type the values in the corresponding fields to define the lower and higher limits of the contrast that corresponds to the subject. In the Video window, check the quality of detection. - Example 1: The subject is brighter than the background and only the whiter area of the subject is detected. Move the Bright slider to the left to increase the range towards values of lower contrast between subject and background. - Example 2: The subject is darker than the background and its body is detected only partially in the area of lower contrast. Move the Dark slider to the left to increase the range towards lower values of contrast between subject and background. - Example 3: The subject is brighter and darker than the background and only the darker areas of the black fur are detected. Move the Bright slider to the left to increase the range towards less contrast between the subject's white areas and the gray background. Then move the Dark slider to the left to increase the range towards less contrast between the subject's black areas and the background. - Move the sliders until the subject (or the part which is of interest) is detected fully, and the noise is minimized. Check that the subject is properly detected in all parts of the arena by playing back different parts of the video file, or by waiting for the live animal to move. Notes When the subject is brighter and darker than the background, detection only works well when there is enough contrast between the areas of different brightness and the background. For example, tracking a hooded rat works well when the background is intermediate between black and white. Otherwise, use Differencing. --- ## EthoVision XT 19 - Configure Detection Settings - The Reference Image URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-the-reference-image Chapter: EthoVision XT The Reference Image Aim To provide EthoVision XT an image of the background (that is, the arena without the subject) in such a way it can discriminate between the subject to track and everything else. Background Information A reference image should not contain the image of the subject. The options below help you create a reference image even when it is not possible to have the subject removed from the video image. A reference image is used in detection methods Static Subtraction, Dynamic Subtraction and Differencing. Grabbing a reference image is optional. However, if you do not do so, EthoVision XT takes the first video frame available from the camera or video file and considers that as the reference image. Procedure - Click Background in the Method section. - In the Reference Image window, choose Grab Current (A). Scroll through the video until you find an image without animals. If you track live, make sure that there are no animals in the arena, then click Grab Current (A). This image will be the initial reference image. Skip B and C and click Close. If your video does not contain images without animals, continue with option B. Also continue with option B if you track live and you cannot start with an empty arena. - Grab from Other (B). You may have a video with an identical background as the one you use for tracking, but without animals. Or you may have an image of a background without animals. If this is the case, click Grab from Other and select this video file or image file. If you select a video file, the first frame of this file will be used as an initial reference image. If you select an image file, this has to have the same resolution as the video file you use for tracking. Browse to this file and click Open. Skip option C and click Close. If you do not have such video or image, proceed with option C. - Start Learning (C). With this option EthoVision XT makes an average image of the entire video. If the animals are moving, this process will average out the pixels of the animals, resulting in a reference image without animals. If you track live, you have to click Start Learning, and subsequently click Stop Learning as soon as you have obtained an initial reference image without animals. Click Close if you have a good reference image without animals. If you use Dynamic Subtraction or Differencing and the reference image is still not good, continue with step 5. - Acquisition settings: If you run a number of consecutive trials, you may want to choose which image to use as initial reference image. Pay particular attention here, since the video image may not be exactly the same between the end of a trial and the start of the next one. - Use saved reference image. Choose this option if the background remains constant between the different trials. For example, when there are no moving objects, bedding material, shadows etc. - Use dynamic reference image. Choose this option if the background changes between the different trials, and you assume that the video image at the end of a trial is the same as that of the start of the next trial. For example, when a trial starts a few seconds or minutes after the end of the previous trial. - Use first frame of each trial. Choose this option whenever the video image at the end of a trial is likely to differ from that at the start of the next trial. This may be the case for example when you do batch acquisition from a number of video files, where shadows or reflections appear in the arena in the new video. EthoVision XT takes the first video frame available from the camera (or video file) and considers it as the background. Note that if you choose this option and the subject is already in the arena the moment that you start a new trial, EthoVision XT misses the subject in the first frames and finds it only when it moves away from the starting location. To avoid this, release the subject after you have started the trial. - Click Close. Notes - By default, the reference images are stored in the folder Bitmap Files of your experiment. If the background has not changed, you can use these images as reference images in other experiments. - If you are tracking from video files, you must play the video forward whilst making dynamic subtraction settings. This is because the program needs to update the reference image. Do not skip through the file, since the reference image will then not be correctly made. - The option Acquisition settings is available only in Dynamic Subtraction and Differencing, since in these methods the background is continually updated during the trial. See Also - How the Reference Image Is Updated in Dynamic Subtraction - How the Reference Image Is Updated in Differencing --- ## EthoVision XT 19 - Configure Detection Settings - Track Noise Reduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-track-noise-reduction Chapter: EthoVision XT Track Noise Reduction Aim To reduce the effect of noise in the data during tracking. Example: When the center point of an animal is detected in a zone, you want the pellet dispenser to drop a pellet. If the detected center point is moving rapidly because of noise, this may result in a number of consecutive pellets to be dropped, every time the center point crosses the border of the zone. Track noise reduction may solve this problem. Important: Do not use Track Noise Reduction if you are particularly interested in rapid movements of the subject, for example, if you study the startle response of zebrafish larvae. Background Information If the detected center point of the subject is continuously moving, while in fact the subject is sitting still, the total distance moved will be overestimated. You can use track smoothing to correct for this after you have acquired your data (see Smooth the Tracks), however in some cases you may want to smooth the track during acquisition. This may especially be the case if you use Trial and Hardware Control. The example below shows the effect of track noise reduction (TNR) on the x coordinates of the tracked subject. The chart plots the x coordinate against time. With TNR on, the path is smoothed out. Procedure - In the Detection Settings, under Advanced, open Smoothing. - Next to Track Noise Reduction, do one of the following: - Select Off (default) if you do not want to apply track noise reduction. - Select On if you want to apply track noise reduction. Notes - Track noise reduction makes use of the Gaussian Process Regression method. Track noise reduction is applied during acquisition. Hence, it alters the acquired tracks, which cannot be undone afterwards. With Gaussian Process Regression, the sample points are smoothed, using the x,y coordinates of the previous 12 sample points. This differs from the Lowess post-acquisition smoothing method that uses samples before and after the sample point to be smoothed. This is not possible during acquisition, because the x,y coordinates of future samples are not yet known. - Using Track Noise Reduction in the Detection Settings influences the acquired track, and therefore it is not possible to change it back after acquisition. This is in contrast to post-acquisition smoothing (see Smooth the Tracks) where you can use profiles to calculate analysis results with and without those filters applied. - If you use nose-tail tracking, the paths of the nose point and tail base are smoothed independent of the path of the center point. - If you use Track Noise Reduction, the sample points may lag behind when compared with the video images, especially when the subject moves fast. This is because the sample position is smoothed using point locations acquired in the previous samples. - When you use Track Noise Reduction in combination with hidden zones, the subject may go missing when it is in fact in a hidden zone. This occurs when the last (smoothed) position of the subject before it disappears from view is outside the entry zone. See the Troubleshooting topic: The Animal Is in the Hidden Zone but the Data Show "Missing Sample". See Also - Advanced Detection Settings: Smoothing --- ## EthoVision XT 19 - Configure Detection Settings - View the Detection Features on the Video Window URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-detection-settings-view-the-detection-features-on-the-video-window Chapter: EthoVision XT View the Detection Features on the Video Window Important: Displaying detection features can use a lot of processor power and reduce the maximum possible sample rate if you are tracking live. Procedure - In the Detection Settings screen, click the Show/Hide button on the toolbar and select Track Features. - Select View for the feature you want to view. Choose the color and, for the body points, whether to show the trails. - If you have selected to view the body points' trail, choose the number of Samples you want to be shown at a time. - Adjust the Line thickness and the Dot size. - Click Close and check the result in the Video window. Detection Features Nose-point: To check that the nose tip is detected correctly. Center-point: To check that the center-point of the subject is detected correctly. The center-point is the point whose X,Y coordinates are the arithmetic mean of the X,Y coordinates of all pixels detected as subject. For more information on how the nose- and tail-base points are calculated, see Overview of Nose-Tail Base Detection. Tail-base: To check that the base of the tail is detected correctly. Head direction: To estimate at what the subject is sniffing. Select this option especially with Novel Object and Orientation tests. Body contour: To check that the subject's contour (or the part which should be found) is detected. Body fill: To check that the subject's body (or part of it) is detected. For example, in a test where it is important to measure the change in the animal's shape to estimate its mobility. If you do not select a color for Body fill, the body contour will be shown as noise. Noise: To view the pixels that match the criteria for subject detection (depending on the detection method), but other than those detected as subject. We recommend to keep Noise selected. This way you can see which parts of the video image have gray scale values similar to those of the subject(s) to be detected. Activity: To view the pixels that match the criteria for activity detection (see Activity Settings). This setting is only available if you selected Activity Analysis in the Experiment Settings. Some of the options above are not available if your experiment is set to Only Center-Point Detection in the Experiment Settings. Line thickness: This refers to the thickness of the trails, the body contour and the head direction line. Dot size: This refers to the size of the body points visualized. View the Detection Statistics The detection statistics are displayed in the Detection Performance pane, which is, by default, displayed at the bottom of the screen. If the Detection Performance pane is not displayed, click the Show/Hide button on the toolbar and select Detection Performance. The Detection Performance pane shows immediate feedback when you change detection settings. Missed Samples The percentage and number of samples that were skipped due to lack of processor time. This value tells you whether your PC can handle the sample rate specified (see Sample Rate). See also Missed Samples for tips on how to increase the maximum sample rate handled by the PC. The value is reset to zero when you load another video file or click Save Changes in the Detection Settings pane. Interpolated Samples The percentage and number of missing samples due to missing video frames that were interpolated. This statistic is only available when in the Detection Settings under Smoothing the option Dropped Frames Correction is On. See Dropped Frames Correction. - What is the maximum acceptable percentage of interpolated samples? Only accept a high value of interpolated samples when you are sure that the tracks represent the movement of the subject reliably. If the percentage is as high as 30% and the subject moves fast or makes sharp turns, the resulting track includes lots of artifacts and the statistics are unreliable. In Integrated Visualization check whether the tracks with high percentages of interpolated samples match the actual movement of the subject. - The value is reset to zero when you load another video file or click Save Changes in the Detection Settings pane. Source: EthoVision XT 19 Help - Configure Detection Settings, Noldus Information Technology --- ## EthoVision XT 19 - Configure the digital camera URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-the-digital-camera Chapter: EthoVision XT Configure the Digital Camera Aim: To adjust settings in a Basler GigE camera or USB 3.0 camera, like the video frame rate, video frame resolution, and exposure time, within the camera software. - You can also change most of these settings within EthoVision XT. See Adjust Camera Settings in EthoVision XT. - IMPORTANT: Do not use pylon Viewer to record video! Always use EthoVision XT or MediaRecorder. Main Actions - Procedure (General) - Set the Video Resolution - Set the Camera Frame Rate - Center the Camera View - Set the Pixel Format - Adjust the Camera Exposure Time - Adjust the Camera Gain - Adjust the White Balance - Save the Camera Settings - Do a Factory Reset on the Basler GigE Camera Procedure (General) - Make sure EthoVision XT (and MediaRecorder, when present on the computer) are not running. - In the Apps screen, choose Basler > pylon Viewer. pylon Viewer is installed only if you selected to install the Basler camera drivers during installation of EthoVision XT. See Install EthoVision XT. - From the Windows menu of pylon Viewer select Features - All. - In the Devices panel, double-click the item Basler under GigE or USB depending on the camera you have. If an error message Failed to download... appears, it is probably caused by the mismatch between IP addresses of camera and Ethernet interface. Adjust the IP addresses and when ready click the Refresh button in pylon Viewer. See Assign IP Addresses. - To preview the camera image, click the Continuous Shot button on the toolbar. IMPORTANT: Do not use the Record button if you want to record video! This creates very large files. Always use EthoVision XT to record video. - Under Features - All, expand the camera name and choose the settings category that you would like to adjust. See the instructions that apply in the following sections. NOTE: To be able to adjust the settings, click the Stop button first. - After you have adjusted the camera settings, save them under Configuration Sets. See Save the Camera Settings. - When working with multiple cameras, repeat the procedure for each camera. Set the Video Resolution - In the Features panel, open the Basler camera item and then the AOI Controls item (Image Format Control for USB 3.0 cameras). - You can set the resolution by adjusting the Width and the Height. - Recommended: 1280 x 960 or 1280 x 1024. - When using multiple cameras you may need to limit the resolution, also depending on the frame rate and the tracking methods you intend to use. See suggestions for GigE cameras and USB 3.0 cameras. - Save the settings. See Save the Camera Settings. Set the Camera Frame Rate - In the Features panel, under Category, open the camera item and then click Acquisition Controls. - Select Enable Acquisition Frame Rate. - Next to Acquisition Frame Rate (Abs) [Hz], enter the frame rate you require (frames per second). - To check that the frame rate is stable, click the Continuous Shot button on the toolbar. Under the live video window, locate the resulting frame rate. This is the frame rate that the camera can sustain with the current settings. Check that this matches the value you have just set. - Save the camera settings. Center the Camera View Follow this procedure to make sure the camera view is centered. Alternatively, you can use part of the original camera image by operating the Offset controls. - In the Features panel, open the Basler camera item and then the AOI Controls item (Image Format Control for USB 3.0 cameras). - Select both options Center X and Center Y. - Save the camera settings. NOTE: If you want to have the camera image off center, for example to focus on one region of interest, do the following in pylon Viewer: - Under Features > AOI Controls de-select Center X and Center Y. - Click the Stop button. - De-select Center X and/or Center Y. - If the Width and Height of the image are set to the maximum values, reduce those values so you have room for the offset adjustment (see below). - Move the X Offset and Y Offset sliders. - Click the Continuous Shot button and check the live camera view. - When you are satisfied with the new off-center camera view, save the camera settings. For more details, see the camera documentation. Set the Pixel Format Pixel format is the format in which video data sent out by the camera sensor is represented and analyzed by EthoVision XT. - Click the Stop button. - In the Features panel, under Category, open the camera item and then click Image Format Controls. - Select the Pixel Format: - For monochrome cameras, choose Mono 8. - For color cameras, choose Bayer RG 8. See also Settings for the Color Camera. IMPORTANT: Mono 8 corresponds to the option Y800 in EthoVision XT. See Adjust Camera Settings in EthoVision XT > Format tab. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Configure the digital camera (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-configure-the-digital-camera-continued Chapter: EthoVision XT Adjust the Camera Exposure Time The exposure time (or shutter time) is the time the camera shutter is kept open to let light in. The exposure time limits the maximum achievable frame rate. If the sum of the exposure time and the time needed for reading the chip (readout time) is greater than the time between consecutive video frames, the next frame may be dropped, resulting in a lower frame rate, and missed samples during tracking. To adjust camera exposure that matches a frame rate: - In the Features panel, under Category, open the camera item and then click Acquisition Controls. - Make sure that Exposure Mode is Timed, and Exposure Auto is Off. - Next to Exposure Time (Abs) [us], enter the exposure time you require, in microseconds. - For Zebrafish larvae, enter 4000 or 2000, depending on the video resolution chosen. If resolution in EthoVision is 1280 x 960 or similar, select 4000. If the resolution is 640 x 480 or similar, select 2000. - In all other cases, you may choose a higher value. The ideal range of exposure will likely be anywhere from 2000 to 10000. - If lighting in the room is low, you will likely need a longer exposure time. Try 8000 up as high as 15000. When tracking under infrared light, you generally need to set high exposure times, up to 20000. - Values higher than 20000 are not recommended — increase illumination or set the gain a bit higher. See Adjust the Camera Gain. - Note that a longer exposure time may cause motion blur. Faster animals like flying insects require shorter exposure times than other, slow-moving animals. In case of motion blur, reduce exposure time and compensate by opening the lens aperture and/or increasing the amount of ambient light (the latter is preferred). - A longer exposure time may conflict with the time that the software needs to process an image, because both must fit within the time between two successive video images. In that case some video images may be dropped during acquisition. To check that the exposure time is compatible with the frame rate you have chosen, click the Continuous Shot button on the toolbar. At the bottom of the live video window, locate the frame rate resulting with the new exposure time. If the camera can cope with the new exposure time, the current frame rate should be the same as that set next to Acquisition Frame Rate (Abs) [Hz]. This is usually 25, 30 or 60. If the exposure time is very high, the resulting frame rate could be lower than the set frame rate Acquisition Frame Rate (Abs) [Hz]. For example, setting an exposure time of 40000 (40 ms) reduces the frame rate from 25 to 20. To solve this, do one of the following: - Under Acquisition Controls, lower the Exposure Time (Raw). This makes the video image darker. To compensate for that, open the lens diaphragm so that the camera sensor receives more light. Note, however, that an open diaphragm reduces the depth of field, that is, the range of distances where the object appears sharp in the camera image. - Under AOI Controls, lower the Width and Height (video resolution). Do this until you see the expected frame rate under the live view. - Save the camera settings. Adjust the Camera Gain Camera gain amplifies the video signal. A higher value of gain results in a brighter image. That could be an option whenever the image is too dark for EthoVision XT to detect a subject, and you do not have other ways to correct for that — for example, when the lens of the camera is wide open and you cannot increase light intensity in the test room. Tip: Whenever possible, add lights instead of increasing camera gain. See Lighting Setup and the video tutorial Set up Your Test Environment (Help > Video Tutorial). - Start the live view by clicking the Continuous Shot button. - In the Features panel, click Analog Control. - From the Gain Auto list, select Off. - Next to Gain (Raw), select the value you require. In normal situations values like 0 or 1 should suffice. Only increase the gain further if there is no other way to get a bright image (e.g. by increasing the exposure time, improving the ambient light, or opening the aperture ring of the lens). Note that increasing gain results in more image noise. - Check the live view and adjust the gain when necessary. - When ready, save the camera settings. Adjust the White Balance If you have a color camera, you also need to adjust its white balance. - Click Color Improvements Control. - Point the camera at a piece of white paper, so that the camera image looks entirely white. Click in the field next to Balance White Auto and select Once from the list. - Save the settings. See also Settings for the Color Camera. Save the Camera Settings Important: If you have multiple GigE/USB 3.0 cameras, make sure that you save the settings for each camera. To select a camera, double-click its name in the Device panel in pylon Viewer, adjust the settings that you require, and repeat the procedure to save the settings. - Click the Stop button. - In the Features panel, click Configuration Sets (User Set Control for USB 3.0 cameras). - From the Configuration Set Selector list (User Set Selector for USB 3.0 cameras), select User Set 1. - Next to User Set Save, click Execute. The camera settings are saved under User Set 1. - From the Default Startup Set list (User Set Default for USB 3.0 cameras), select User Set 1. This means that the camera always starts with the settings contained in User Set 1. - Close pylon Viewer. These settings will be used each time you start up EthoVision XT. Tip: You can also save different settings for the same camera in User Set 2 and User Set 3. Under Default Startup Set/User Set Default, select which set you want EthoVision to use. Do a Factory Reset on the Basler GigE Camera - Open pylon Viewer and double-click the camera name. At the bottom left of the interface, click All Features. - In the Features window, expand Configuration Sets. - For Configuration Set Selector, select Default Configuration Set. - For Default Startup Set, select Default User Set. - For User Set Save, click the Execute button. - For User Set Load, click the Execute button. - The camera should now be reset to factory defaults. At this point you need to set the resolution, frame rate, exposure, and other settings while still in pylon Viewer. Finally, save the settings with a specific name (e.g. User Set 1) so you can always return to those settings using User Set Load when needed. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Connect the GigE camera to the PC URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-connect-the-gige-camera-to-the-pc Chapter: EthoVision XT Connect the GigE Camera to the PC Aim: To make sure that EthoVision XT receives the video signal from the GigE camera. Prerequisites - You have followed the entire procedure in Install an Ethernet board for GigE cameras. - No matter how many cameras you use, you need a 1-Gb Ethernet interface board (desktop computers only). - When you use a 4-port Ethernet board, you can power the cameras with Power-over-Ethernet (PoE) injectors but you can also choose to connect the board to the power outlet inside the PC. See Power the Ethernet board for the GigE cameras. - You must use a 1-Gb (1 Gigabit/s) Power-over-Ethernet (PoE) injector: - When the Ethernet interface board is not powered. This is usually the case for 1- or 2-port boards. Also 4-port boards may not be powered — see Power the Ethernet board for the GigE cameras. - When you use a network switch and this has RJ45 ports that are not powered. In all cases, use one PoE injector per camera. - Cables: Use Cat5e or Cat6e crossover cables. - Do not use an Ethernet to USB adapter to connect the camera to the PC. Always connect the camera and the PC directly using an Ethernet crossover cable. Procedure If You Have a Single or Dual Port Ethernet Board To connect one camera, you need a single or dual port Ethernet interface board. To connect two cameras, you need a dual port Ethernet interface board. If the board is not powered, you need as many PoE injectors as cameras. Only use 1 Gbit/s PoE injectors. - Using cross-network cables (Cat-5e or newer), connect the Ethernet port/board on the PC to the IN port of the PoE injector. Connect the camera to the OUT port. Use the short cable between the PoE injector and PC. Use the long cable between the PoE injector and camera. - Power up the PoE injector; make sure that the two CONNECT and ON green LEDs are on. If the green LEDs keep blinking, wait a few more seconds. If you see no change, disconnect the cables, then re-connect them. - Next: Configure the digital camera. If You Have a Four-Port Ethernet Board When you use this board, the PoE injector is not required. However, the Ethernet board must receive power from the PC. See the connection scheme in Power the Ethernet board for the GigE cameras. - Connect each camera (up to four) to one of the ports on the Ethernet board, as shown in the figure below. - Next: Assign IP addresses. Notes - TIP: Label the cameras and the Ethernet ports (for example, Cam 1, Cam 2, etc.). Take note of the camera serial numbers; these actions may be useful when you need to know which camera is connected to which port and assign or adjust the IP addresses. - The Power over Ethernet (PoE) injector is a device that passes power along with data (in this case, video data from the camera) on twisted-pair Ethernet cabling. - If you bought your camera elsewhere, make sure you bought the correct Ethernet cables. Cheap or incorrect cables will affect frame rate and result in missing samples. Always use Cat5e, Cat6, or Cat7. - Cat6 and Cat7 cables support higher network speeds (5 Gb/s or higher) than Cat5e (2.5 Gbps), but these are well above the network speeds required for a GigE camera and Ethernet board. - Cat5e cables are cheaper, lighter, and thinner and may be the preferred choice for some applications due to ease of installation in tight spots. They are typically easier to terminate as well. See Also - Using Multiple GigE Cameras - Assign IP Addresses - Configure the Digital Camera Assign IP Addresses Aim: To make sure that the IP address of the GigE camera and the Ethernet interface board physically connected to that camera match. This ensures reliable data transfer to and from the camera. What Do You Want to Do? - Assign the IP address to the Ethernet interface board - Assign the IP address to the camera TIP: For how to assign IP addresses and connect digital GigE Vision cameras, watch the video tutorial Set Up the Cameras. To open the tutorial, choose Help > Video Tutorial. Assign the IP Address to the Ethernet Interface Board This applies to Basler GigE cameras. - In Windows, search for Network connections or Network computers. Alternatively, in Windows 11, from the Start menu choose Settings > Network and Internet > Advanced network settings (at the bottom of the screen) > More network adapter options. - The Network Connections window opens. Right-click the item that corresponds to your camera and click Properties. - TIP: If your computer has more than one adapter item, unplug the camera and take note of which item shows Unplugged. That indicates the port the camera was connected to. - NOTE: You may see one or more additional items named Ethernet or similar. This is the standard interface board that is connected to your local network and the internet. Do not use that port unless it is the only one available. If you use that port to connect the camera, you won't be able to connect the EthoVision XT computer to your local network and the internet. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Select Use the following IP address and fill in the details as shown in the figure below. Also select the option Validate settings upon exit. When done, click OK and then Close. For US/Canada users: please enter 192.168.200.101. In case of multiple Ethernet boards or one board with multiple ports, use 192.168.201.101 for the second board/port, 192.168.202.101 for the third, etc. - Close all windows. Repeat the steps for each port on the board connected to a camera. See also Using Multiple GigE Cameras. Assign the IP Address to the Camera The procedure below is for Basler GigE cameras, not Basler USB 3.0 cameras. - If you have not done so yet, connect the GigE camera to the PC. - In Windows, search for and start pylon IP Configurator. - Select the camera name that appears under the Ethernet port set in the previous procedure. This is the camera physically connected to that port. Note that the camera status is Not reachable. This is normal since the camera cannot communicate yet with the Ethernet port. - Under Static IP, fill in the details in the IP Address and Subnet Mask fields as shown. If you have multiple cameras, the IP address must differ between cameras and match the IP address of the Ethernet port. See also Using Multiple GigE Cameras. For US/Canada users: please enter 192.168.200.1 for the camera IP address. For the second camera on the same card, use 192.168.200.2, etc. The first three numbers must match the address set for the Ethernet port the camera is connected to. For example, a camera connected to 192.168.201.101 can be designated as 192.168.201.1. - Click Save and then close pylon IP Configurator, or repeat the procedure for the next camera. See also Using Multiple GigE Cameras. - Next: Configure the digital camera. See Also - Connect the GigE Camera to the PC - Configure the Digital Camera - Using Multiple GigE Cameras Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Connect the USB 3.0 camera to the PC URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-connect-the-usb-30-camera-to-the-pc Chapter: EthoVision XT One USB 3.0 Camera Connect the camera to the USB 3.0 interface board of the EthoVision XT desktop computer, or to a USB 3.0 port on the EthoVision XT laptop computer. - USB cables are usually 3 to 5 meter long. These are generally passive cables, meaning that quality of the signal degrades with cable length. Longer passive cables are not recommended. If you need cables to cover more than 5 m distance, use an active (powered) extension cable. - Some USB 3.0 connectors and ports can be recognized by their blue color coding. Others show 'SS' (SuperSpeed) and the USB sign. Multiple USB 3.0 Cameras IMPORTANT EthoVision XT has been tested with one USB 3.0 camera. If you want to use multiple USB 3.0 cameras simultaneously, test them thoroughly before running your experiments. Install as many USB 3.0 PCIe interface boards as cameras, unless you have a USB 3.0 4-port interface board. See Install the USB 3.0 Interface Board. How you connect multiple USB 3.0 cameras depends on which USB 3.0 interface board you have installed. - If you have multiple interface boards with 2 ports each, connect each camera to one of the ports on the USB 3.0 boards. IMPORTANT Do not connect two cameras to the same USB 3.0 interface board. - If you have a 4-port interface board, you can connect up to four cameras. Connect each camera to one of the USB ports. Notes - If you have one USB 3.0 interface board with two ports, always connect one camera. You can use the second port as a power source when using an extension cable. See Also - Cameras Supported by EthoVision XT What Do You Want to Do? - Install the Picolo Alert encoder board. NOTE The Picolo H.264 boards are no longer supported with EthoVision XT. - Connect analog cameras to the computer - Test an analog camera See Also - Cameras Supported by EthoVision XT > Analog Cameras Install the Picolo Alert Encoder Board Aim: To install the encoder board Picolo Alert on your computer. You need this board to track and record video using analog cameras. NOTE If you ordered a computer from Noldus Information Technology when you purchased EthoVision XT, the encoder board is already installed. Follow the procedure below if you bought your computer somewhere else. Prerequisite - IMPORTANT Turn off Fast startup in the Windows Power options. See Power Options When Using Cameras. Procedure Insert the Picolo Alert Board in the PC - Turn off the PC and disconnect the power cable. - Open the computer and gently but firmly insert the board into a free PCI express slot. Avoid touching the contacts or other metal parts of the board. For details about PCIe slots, see Install an Ethernet Board for GigE Cameras. - Close the PC. - Connect the power cable and turn the PC on. Install the Driver for the Picolo Alert Board - Browse to my.noldus.com, log in or register, and select Downloads > EthoVision XT > Drivers and Tools. - Download and save the file Euresys Multicam - Driver win10. - Run the .exe file and continue with installation. - When the installation message appears, click Install. - At the end of installation, restart the PC. - Next, see Connect Analog Cameras to the Computer. Notes - Always install the drivers from my.noldus.com. Do not install drivers from other sources, unless requested by Noldus Support. See Also - Analog Cameras - Install Analog Cameras Connect One to Four Cameras Connect each camera to one of the inputs of the Picolo Alert encoder board. Furthermore: - Take note of which camera is connected to which input of the board. - Make sure that all four switches on the board are in the position opposite to their labels. - Create or open an experiment, choose Setup > Experiment Settings, then select Live tracking and under Video Source select the camera inputs. Next, view the mixed camera image. See Video Source. Connect Up to 16 Cameras You can track from up to 16 analog cameras simultaneously if you connect Quad Unit Processors between each group of four cameras and the four inputs of the Picolo Alert encoder board. A Quad Unit Processor mixes the video inputs of up to four cameras. Connect the output of the Quad Unit Processor to one of the inputs of the Picolo Alert board, as shown in the figure below. To connect 16 cameras, you need: - Four Quad Unit Processors. - One Picolo Alert board. Connect the output of each Quad Unit Processor to one input of the Picolo Alert board. Notes - The Picolo U4/U8 H.264 boards are no longer supported with EthoVision XT. See Also - Install the Picolo Alert Encoder Board - Experiment Settings > Video Source - The PhenoTyper - EthoVision XT 19 - Reference Manual for more information about using multiple PhenoTypers. See Manuals. Test an Analog Camera Aim: To check whether your analog camera and the Euresys Picolo Alert encoder board are functioning properly. Prerequisites - When you install EthoVision XT you have also installed the Euresys Multicam driver for the Picolo Alert encoder board. See Install EthoVision XT. This software also includes Multicam Studio. - If Multicam Studio is not installed on your EthoVision XT computer, browse to my.noldus.com, log in or register, and select Downloads > EthoVision XT > Drivers and Tools and download and save the file Euresys Multicam - Driver win10. Run this file and install Multicam Studio. Procedure - Connect the camera to the EthoVision XT computer. - Power up the camera. - Double-click Multicam Studio. - Select the video input and check the camera image. When necessary, adjust the settings like the video standard. See Also - Install Analog Cameras Power Options When Using Cameras Aim: To disable Fast startup on your computer. This prevents problems when recording videos from within EthoVision XT. NOTE By default the computer has the Fast startup option enabled. This can sometimes cause EthoVision XT and MediaRecorder to stop responding when selecting an input of the frame grabber board or camera. That problem has been found when using encoder boards for analog cameras, but we recommend following the procedure below for any type of camera you have. Procedure - Open the Windows Control Panel, and select System & Security. - Under Power Options select Choose what the power button does. Click Change settings that are currently unavailable. - Under Shutdown settings, de-select Turn on fast startup (recommended). See Also - Install GigE Cameras - Install USB 3.0 Cameras - Install Analog Cameras Learn About - Camera position and settings - Physical setup of an arena - Lighting setup TIP Watch the video Set Up Your Test Environment, which you can find in the main EthoVision XT video tutorial (Help > Video Tutorial). Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Controlling Hardware Devices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-controlling-hardware-devices Chapter: EthoVision XT Controlling Hardware Devices Set the Port Connections - The Device Configuration window appears, listing the available ports of the interface device: TTL Port 1, 2,... and SDI Port 1, 2,... (the latter only for the USB-IO box and the Mini USB-IO box). You can assign one physical device to each row. - If you have connected multiple USB-IO boxes, select one from the list at the top. - In the Ports column, locate the first available port of the correct type. - Locate a TTL Port and click under Device type to view the list of the devices. Select the device that applies. - Locate an SDI Port and click under Device type to view the list of the devices. Select the device that applies. Use SDI ports to connect the Lickometers and the PhenoTyper's Top Unit Interface. If you select the latter, four additional rows appear below the option. Select the PhenoTypers' Top Units. For details, see Set the Port Connections for PhenoTyper below. - From the Device type list, select the type of device that is (or will be) connected to that port. - In the Device ID field, enter the name of the physical device that should be connected to that port. - Repeat steps 1 through 5 for other devices, until they are all assigned to a port of the IO-box. - Repeat the steps above for the next USB-IO box. - When ready, click OK. You return to the Experiment Settings screen. Proceed with assigning devices to the arenas. Notes: - The number next to IO-box is the identification number of the IO-box set by the manufacturer. You cannot change this number. - You must set the port connections only the first time you connect them. - The port connection settings are at experiment level, and are applied to all your Trial Control Settings. Once you acquire at least one trial, the settings become locked and you can no longer change them. If you need to add devices, create a new experiment or remove the acquired trials. - If you plan to create several experiments with the same set of devices, you can use an experiment as a template experiment with the hardware settings selected but containing no trials. To create a new experiment from a template experiment: from the File menu, select New template experiment and then Use a custom template. Next, open the experiment you want to use as a template and use the new experiment to acquire data. - The Device ID is by default the name of the Device type plus a progressive number 1, 2,... We advise you to enter a name that you can recognize easily in your setup. - For the difference between TTL and SDI ports, see the relevant section of the reference manual. - Under Device type, select TTL Port Tester if you want to test the functionality of a TTL port. - Under Device type, select USB-IO monitor if you want to test the connection in the USB-IO box. - When you select a device type, that device type is added to the file Hardware Setup.xml, which is stored in one of the folders located in the experiment folder ...\Configuration Files\Add-ins\Hardware. Which file is used depends on whether you use the USB-IO box, the Mini USB-IO box, or another system (for example, the Ugo Basile FC Controller, which does not require the USB-IO box or Mini USB-IO box): - {A8DA8F3E-7EA3-4629-8327-9D21C90FB3ED} for the USB-IO box. - {0308106B-1EBE-4620-B00D-396ABEBBC219} for the Mini USB-IO box. - {3AA139A2-4737-4D6D-BF7B-0153CFD4D302} for the Ugo Basile FC Controller. Use Multiple USB-IO Boxes You can connect multiple Noldus USB-IO Boxes to one EthoVision XT computer to control more devices. For more information, see the section on using multiple USB-IO boxes in the reference manual. Set the Port Connections for PhenoTyper - Locate SDI Port 13. Under Device type, select Top Unit Interface. This expands the SDI Port to four extra rows. - For each of the four rows, under Device type, select: - Top Unit (Standard) for standard PhenoTypers. - Top Unit (NeuroBsik) for PhenoTypers of the Neuro-Bsik type. - Top Unit Tester (PTTB-002x) only when you want to use the Top Unit Tester instead of the actual PhenoTyper Top Unit, for testing purposes. - Under Device ID for the rows appended, enter the name of the physical Top Units. - When ready, click OK. Next, assign the Top Units to the arenas. To set the port connections for other groups of PhenoTypers, you must adjust the jumpers for the ports you are going to use. See the PhenoTyper - EthoVision XT 18 - Service Manual. Set the Port Connections for COM Ports Prerequisite: Install the Serial interface for EthoVision XT using the steps below. Install the Serial Interface - Close EthoVision XT. - In the EthoVision XT 18 full installation package, open the folder Drivers and Tools. Open the folder HardwareInterface SerialPort and double-click HardwareInterface_SerialPort_[version number].msi. You can download the EthoVision XT 18 full installation package from my.noldus.com. - Restart EthoVision XT. Define the COM Port in EthoVision XT - Connect the device to the EthoVision XT computer. - Open the EthoVision XT experiment and choose Setup > Experiment Settings. - Under Trial Control Hardware, select Use of Trial Control Hardware, and click the Settings button. Select COM Ports in the Hardware Interface window and click OK. - In the Devices window, click Add and add one or more COM ports that you want to use. - Note: After acquiring one or more trials, you cannot add COM ports. First delete the trials, then repeat the steps above. - Note: To know which COM port should be added, disconnect the USB cable and check in the Windows Device Manager under Ports (COM & LPT) which item has disappeared. - To check the port settings, select a COM port currently connected to a device and click Settings. The following settings should work fine: Baud rate 9600, Data bits 8, Parity None, Stop bits 1, Flow control None. When ready, click OK. - Click OK in the Devices window. Next, assign the COM ports to the arenas. Assign Devices to Arenas For experiments with one arena only, hardware devices are automatically assigned to the arena. You can skip this section and continue with testing the hardware devices or programming trial control with devices. For multi-arena experiments, follow the procedure below. Assuming that you have defined your arenas in the Arena Settings, do the following: - In the Experiment Explorer, click the Arena Settings in which the arenas you want to use are defined. - In the Arena Settings window, click the Arena - Hardware mapping button. The Arena - Hardware mapping window appears. - Click Add device. A new row is appended to the table. - From the Device type list, select the type of device you want to assign. Select Custom hardware if the device type you are using is not listed. - Under Device name, a default name is displayed. This is the suggested Device name for the devices that you specify in that row. We advise you to enter a new name that can be easily recognized, especially if you have more devices of the same type in each arena. Example: Each arena is provided with two pellet dispensers of the same type. Enter Pellet Dispenser Left under Device name. In the next step, select the pellet dispensers to be placed on the left side of each arena. Next, click Add device again and enter Pellet Dispenser Right under Device name, then select the pellet dispensers to be placed on the right side of each arena. - Under the Arena name, select the physical device that you want to assign to that arena. Assign the other devices to the remaining arenas. - Repeat steps 3 to 6 to add a new set of devices. - When finished, click OK. Notes: - To remove a set of devices, select the corresponding row in the table and click the Remove device button. - If your setup includes two or more devices of the same type in one arena, make sure that you select the physical devices that belong to the Device name specified under Device name. - If you cannot select any physical device under the arena names, check that the Device type selected for that row is specified in the Port Device Mapping. - The Arena - Hardware Mapping settings are valid for all Arena Settings in your experiment. They are added automatically to every new Arena Settings. Assign Arenas to the PhenoTypers - Click Add device in the Arena - Hardware Mapping window. - Under Device type, select: - Top Unit (Standard) for PhenoTyper 1. - Top Unit Light (NOCA-TU1x) for PhenoTyper 2. - Under Device name, enter a generic name (for example, Top Unit) or accept the default name (for example, Device A). You will see the Device name again in the Trial Control Settings. - Under Arena n, beginning with 1, select the physical device (Top Unit) associated with that arena. - Repeat step 4 to assign the Top Units to the remaining arenas. The physical devices placed in the different arenas are now linked to a generic Device name. You will use that name in the Trial Control Settings to create actions and conditions based on those devices. Test the Hardware Devices - Make sure that the hardware devices are connected to the EthoVision computer via the USB-IO box or the Mini USB-IO box. - In the Experiment Explorer, click any Arena Settings. - In the Arena Settings window, click the Arena - Hardware mapping button. The Arena - Hardware mapping window appears. - Under the Arena name, select the physical device you want to test, and click Test. A new window appears. - Depending on the hardware device: - For any device that can receive a signal from and send it back to the computer (examples are the Pellet dispenser, Activity wheel break, or Backlight unit white light): Select the appropriate action, click Test and check that the action has been taken. You can also view the result in the Test window, for example that the Number of drops has increased by 1. - For any device that can only send a signal to the computer, not receive any (examples are the Lickometer, PhenoWheel, or the Activity wheel counter): Trigger the device manually and check the result in the Test window. - For the Top Unit: From the Command list, select the action you want to test, click Test and check the result in the PhenoTyper. - For the Custom Hardware Device (for example, the Illuminated shelter): From the Command list, select the action you require, click Test and check that the device has been activated correctly. - For the TTL Port Tester: Use this device to check the two-way communication for a specific port. Press a button on the device and check the result in the Test window. From the Command list, select a command and click Test. Check the result on the tester box. - When ready, click OK. Notes: - Data from the Lickometer and the PhenoWheel are read out in regular time intervals. For the Lickometers currently sold by Noldus IT, the time interval is two seconds, and for the current PhenoWheel it is 60 seconds. - For all devices: The fact that a signal is given correctly in the Test window but you do not see the response from the device could mean that the device is not functioning (for example, a lamp is broken). - For the Pellet dispenser: If the Test window shows in error state = true, the pellet dispenser is not connected to the IO-box, or the food pellets are no longer available. - For the Lickometer: Number of licks and Duration of licks is the cumulative number and duration of licks since the Test button has been clicked, respectively. The device is read out at regular time intervals. At the end of the interval the number and duration of licks is displayed very briefly. - Important: If you realize that the values of Number and Duration of licks given by EthoVision XT are much higher than expected, close EthoVision XT, disconnect and re-connect the IO-box to the computer, and then restart EthoVision XT. - For the Top Unit, TTL Port Tester, and Custom Hardware Device: You can also view the result of the action to be tested in the Test window. Locate the Signal you want to test and verify that Value changes from false to true or vice versa. For the TTL Port Tester, you can also press a button and check the counts of presses for that button. Program Trial Control with Hardware Devices In the Trial Control Settings, you can define: - Conditions based on a hardware device. For example, as soon as the cumulative duration of licks equals 1 minute, stop recording. - Actions on a hardware device. For example, have the Pellet dispenser drop a pellet, or switch on the PhenoTyper's white light. Define an Action on a Hardware Device - In the Components pane, under Actions, double-click the button next to the name of the device type you want to control, or click the button next to it. The Hardware Action window appears. - Under Name, enter an Action name. Under Comment (at the bottom) enter a description (optional). - Under Action to perform, select the Device name you want to use. The names listed there are defined in the Arena-Hardware mapping window. - From the Action to perform list, select the action that the device must take. - Click the Test button to check the hardware action. Click the Reset button to reset all hardware. - Click OK. Insert the Action box in the appropriate position in the rule. What You Need - One of the following hardware interfaces: the Noldus USB-IO box, the Noldus Mini USB-IO box, the Noldus Nortio Core combined with the Nortio TTL Terminal Hub, or the DanioVision Observation Chamber. - You can control the Ugo Basile Fear Conditioning system without a hardware interface. See the EthoVision XT 18 - Application Manual. - The hardware interface software Noldus HardwareInterface USB-IO box version 5 (for the USB-IO box, Mini USB-IO box, and DanioVision) and the Noldus HardwareInterface Nortio version 1 (for the Nortio system). This software is automatically installed when you install EthoVision XT. Tip: To check what is currently installed on your EthoVision XT computer, see the Windows Control Panel under Programs and Features / Add or remove programs. General Notes - The items listed under Actions are the Device names selected in the Arena-Hardware mapping window. If the device name is not listed under Actions, check that the port connections are set correctly and that the devices are mapped in the arenas. - If you have a setup with multiple arenas, it is assumed that each arena has a physical device under that Device name. An action is taken in each arena separately, when the accompanying condition is met in that arena. - Actions like Light on and Sound on result in the light or sound device being activated for an indefinite time. Remember to add an extra action that switches that light or sound off. The two actions should be separated by a condition. For example: Action Light on then Condition Wait 1 s then Action Light off. - If you define a sequence of multiple actions on the same device, these are probably evaluated at the same sample time and may conflict. Separate sequential actions on the same device with a wait condition. Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - Create a video from your data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-create-a-video-from-your-data Chapter: EthoVision XT Create a Video from Your Data Aim: To export the animated track and the plots of the dependent variables to a video file, for instance for presentation purposes. Procedure - Choose Analysis > Results > Integrated Visualization. - From the toolbar, select the Analysis profile that contains the variables to plot. - If you do not want the Track Plot Settings pane to be part of the screen capture, click the Show/Hide button on the toolbar and deselect Track Plot Settings. - Position the video where you want your recording to start, or click the Jump to Begin button to start from the beginning of the trial. - Click the Start Screen Recording button. - In the Screen Recording window, under Region, choose whether you want to capture the Video, tracks and plots or the Full screen. Note that with Full screen you also record the Experiment Explorer and the desktop (if visible). - Choose the Frame rate (default: 25 fps) and the Resolution (default width: 1280). - Choose the video file Saving location and File name. - Click Start. - Play the video at the speed you require. - To stop screen recording, click the Stop Screen Recording button. Notes - If you choose Video, tracks and plots, the Track Plot Settings pane is also recorded. To remove this from your video, see step 3. - Video resolution is available in a number of steps. The values of width are 320, 480, 640, 800, 1024, 1280 (default), and 1600 pixels. The values of height are adjusted in each step, based on the Region option you choose and the current size of the EthoVision screen. - The video file is saved in DivX format; the file extension is *.mpg. - The suggested video file name is Screen Recording n, where n is a progressive number (0001, 0002, etc.). What Do You Want to Do? - Customize the elements and length of the tracks - Customize the track colors - Display background, arenas and zones Tracks Aim: To optimize visibility of data points. To Access These Options Choose Analysis > Results > Plot Tracks or Plot Integrated Data. In the Track Plot Settings pane, click the Show/Hide tab. What Do You Want to Do? - Show and hide body points - Adjust line thickness and dot size - Show and hide subjects - Show part of the track Show and Hide Body Points Under Features, select the following: - Nose-point (only for nose-tail tracking). - Center-point. - Tail-base (only for nose-tail tracking). - Connectors (only for nose-tail tracking) to display the line connecting the nose-point and the tail-base to the center-point. To view the body points, select the Sample option next to that body point. To view the line connecting samples for a body point, select the Trail option next to that body point. The nose-point is always represented by a filled triangle, the center-point by a filled circle, and the tail-base by a filled square. You cannot change the shape of body points in your tracks. Adjust Line Thickness and Dot Size In the Show/Hide pane on the right, under Features, choose a value for: - Line thickness. This changes the thickness of the tracks and the connectors, that is, the segments joining the body point. - Dot size. This changes the size of the body points along the tracks. Show and Hide Subjects When you track multiple subjects in the same arena, under Subjects select the Visible option for the subjects you want to have displayed and clear the selection for the others. Show Part of the Track Under Filter, choose how many samples you want to display at the same time. - Last ... seconds. Choose this option to visualize only part of the track, for instance only the last 5 seconds. - Every ... sample. If the subject moves slowly, the samples are very dense. Choose this option to visualize, for example, every 5th sample. Tips - To show the entire track, deselect Last ... seconds and click the Jump to End button in the Playback Control window. - To show all samples in the track, select Every ... sample and enter the appropriate value. - To only show the last sample, select Every ... sample and enter the appropriate value next to it. Make sure that in the Features box the option under Sample is selected for the body point you want to plot. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Customize the dependent variable plots URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-customize-the-dependent-variable-plots Chapter: EthoVision XT Show and Hide the Plots Click the Show/Hide button, select Dependent Variables and then choose the items you want to display. By default, all external data files are selected for that trial unless the associated tracks have been filtered out in the Data selection. Sort the Plots You can change the order in which data plots are displayed by dragging them up and down on the screen. - Click the leftmost column next to the plot you want to move. Result: The cursor changes and the plot border is highlighted in red. - Drag the plot up or down to the position you require. Release the mouse button to insert the plot. You can also sort plots by dependent variable, subject name, or arena name. To do so: - Click the Show/Hide button, then select Chart Sorting. - In the Chart Sorting window, if there are multiple sorting factors, like dependent variables and arena names, choose them under Sort order. - Under Variable order, click the arrow buttons to sort the dependent variables. Change the Color of a Plot - Click the square symbol next to the name of the body point, subject, or behavioral state. Alternatively, click next to the data line (for numerical variable plots) or the color bar (for the discrete variables). - In the Color window, choose a new color and click OK. NOTE: For color bars, you can also choose a hatch pattern. Show and Hide the Data Points Click the Show/Hide button on the toolbar, and select/deselect Show Graph Data Points. Specify the Time Mode You can choose to display time values on the x-axis as elapsed time, remaining time (that is, time to the end of the trial) or the actual time. - Right-click the top-left corner of the chart with the time label. - Select one of the following: - Relative time. The time elapsed since the start of the trial. The 0:00:00.00 time on the far left side corresponds to the start of the trial. - Remaining time. The time to the end of the trial. The 0:00:00.00 time on the far right side corresponds to the end of the trial. - Absolute time. The actual date and time the trial was acquired (for example 11/13/2017 16:29:30.00). External Data Plots External data are shown in the form of X-Y plots. The start and end time of the tracks does not always coincide with the start and end time of the co-acquired external data. When you visualize the integrated data, you can only view the external data acquired in the same time interval as the tracks associated with the external data file. External data samples acquired before the start and after the end of the tracks are not plotted. The hairline shows the current video/track position. The current value of heart rate is shown next to the data set name. By default the external data are not plotted in the Integrated Visualization. Plot the Original Signals - Choose Show/Hide > Dependent Variables. - Select the [data set name] (original signal) that you require. By default the original signal is plotted in green. Plot the Resampled Signals - Define the resampled signal in the Analysis profile. See External data (resampled). - Choose Analysis > Results > Integrated Visualization. By default, resampled signals are plotted in red. - Select Show/Hide > Show Graph Data Points to better view the original and resampled signals. - If you upsample a signal with a sample rate much lower than the EthoVision sample rate, and you choose Missing value as the Upsampling method, it may be difficult to see the data points. Choose Show/Hide > Show Graph Data Points and zoom in the plot. Synchronize the External Data with the Tracks Click the Synchronize External Data button. Either change the Start date and time and Stop date and time, or move the external data plot to the correct position. For details, see Synchronize data manually after import. The Plot's Titles The titles are shown at the left of the plots and vary according to what level the external data have been linked at. - If linked to the subject level, the title shows the Arena and Subject names. - If linked to the arena level, the title shows the Arena name. - If linked to the whole trial, the title is not shown. In the example below, the first plot was linked at the Arena level, the second at the subject level. Trial Control Events Pane The Trial Control Events pane gives you an overview of the events that occurred during the trial as a result of the Trial Control Settings you specified. The first condition (the center-point of the mouse is in the arena for more than 2 seconds) is met after 2 seconds. At that moment the track is started. One minute later, the track is stopped. During playback, the hairline indicates the current position. Customize the Visualization of the Trial Control Events Pane By default, the Trial Control Events pane is shown in the lower right corner of the screen. Choose one of the following options to change the visualization of the pane: - To show the pane, click the Show/Hide button on the toolbar and select Trial Control Events. - To move the pane, click its title bar and drag it to the desired position. You can either dock the pane or let it float on the screen. - To resize the pane, point with your mouse to either the pane's upper margin or its left margin so the mouse pointer turns to a double arrow. Drag the margin to the desired position to have a larger pane. Alternatively, click the small black triangle in the upper right corner of the pane to have a full view of the pane and hide the Track Plot Settings pane. Export the Integrated Visualization Aim To export Dependent variable plots in the form of image files. Procedure - Make sure that no other window is on top of the plots. Zoom the plots in/out to reach the level of detail you require for the export picture. - On the toolbar, click the Export image icon. - In the Export Image window, enter the name and location of your image file. - From the Save as type list, select one of the available formats, then click Save. See Also - Adjust the time scale (x-axis) - Zoom the y-axis in/out Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Customize the group charts URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-customize-the-group-charts Chapter: EthoVision XT How to Access These Options Do one of the following: - Double-click the chart. - Right-click the chart and select Chart Properties. - Click the Edit Chart Properties button (if there are more charts in the same tab, the first one is selected by default. To customize another one, first click the chart you want to edit). TIP: To apply the same properties to all charts in the same tab, make the changes in one chart and then click Apply to All. What Do You Want to Do? - Change chart type, size and title - Arrange the data in the chart - Show the error bars - Sort the element of a chart - Change colors, fill patterns, dot size and bar width - Edit axes, gridlines, and legend - Apply the changes to other charts - Reset to default charts TIP: If you want to make a Box and Whiskers chart, you must first specify 5 number summary as a group statistic for the variable of interest. You can do this in two ways: (1) in the Analysis profile, open the variable settings window and locate the Group Statistics tab. Or (2) in the statistics result table, right-click the variable name and choose Properties, then locate the Group Statistics tab. Change Chart Type, Size and Title Click Chart in the Chart Properties window. - Chart type. Choose between Bars, Lines, Box and whiskers, and Box, whiskers and data points. By default, a Bars chart is created. However, if you define time bins, a line chart is created; if you specify 5-number summary in Group Statistics, a box and whiskers chart is created. Select a different type from the list (when applicable). Choose Box, whiskers and data points if you also want to plot the data points that generated the charts. Note that each dot represents the value of a variable calculated for a specific trial. - Chart width. Move the slider or click the arrow buttons to select the required width (range 50–500). TIP: To change the width of a chart, you can also drag the vertical line at the right of the chart. To change the height of the chart, drag the upper margin of the chart window. - Display chart title. Enter the title you require. The default is [name of dependent variable] - [name of statistic]. Arrange the Data in the Chart Click Data selection in the Chart Properties window. - Specifiers. These are elements that can create independent data series. What you see under Specifiers depends on the variable you want to analyze. They can be single body points (e.g. center-point for the variable Distance moved), subjects, variable states (e.g. Mobile, Immobile and Highly Mobile for Mobility), manually-scored behaviors (Grooming and Not Grooming for the behavior Grooming), or combinations of elements, for example Proximity of Nose point to another subject's center-point. Select the specifier that you require. - Data Series. Choose the categories that you want to appear in the legend. If you select Specifiers, for each category on the horizontal axis you get as many data series as the specifiers selected. Note that if you only have one item in the Specifiers box (see above), Specifiers is not in this list. - Example: You have the two subjects Control and Treated and selected Relative movement in the Analysis profile and selected the body point Nose point for the actor and Tail base for the receiver. The Specifiers of the Chart for Relative movement are Moving to / Nose point / Control - Tail base; Moving from / Nose point / Control - Tail base; No movement / Nose point / Control - Tail base; etc. - Example: You track the center-point of one animal, specified the zones Center and Border, and selected the dependent variable In zone in the Analysis Profile. The Specifiers of the Chart for In zone are Border / Center-point and Center / Center-point. - If you select Results, you get as many data series as the combinations [Result containers]*[Specifiers]. The Results are the names of the Result containers of your Data Profile. - If you select Results/Zones, you get as many series as the combinations [Result containers]*[Zones selected in Results per zone in the Data profile]*[Specifiers]. - If you select Zones, you get as many series as combinations [Zones selected in Results per zone in the Data profile]*[Specifiers]. - If you select an independent variable, you get as many data series as combinations [independent variable values]*[Specifiers]. Important: A category or independent variable is listed only when it identifies each group uniquely. For example, if tracks in a group (selection in the Result container of your Data Profile) have two or more different values of Treatment level, this variable is not shown in the list. In this case, the Group Statistics table shows [multiple values] in the header. - Horizontal axis. Select what you want to have as the categories on the horizontal axis. - Results. To have the groups defined in your Data Profile as the categories. - [Independent variable name]. To have for example treatment levels or Dosage values as the categories (but see the note above). - Zones, or Results/Zones (when applicable). - Time bins is selected by default when you defined time bins in your Data Profile. TIP: To combine two independent variables, choose one as Data series and the other as Horizontal axis. Show the Error Bars Click Data selection in the Chart Properties window. Select Show error bars when you want to plot the standard deviation/standard error as error bars. The option is only available when the statistic is selected under Group Statistics for that dependent variable. To add the statistic, right-click the header of the dependent variable in the Group statistics and Charts tab and click Properties. Click Group Statistics and select the statistic you require. Sort the Element of a Chart - In the Chart Properties window, click Data sort order. - Here you can change the sort order of the categories for both horizontal axis and data series. Choose Alphabetical (Ascending or Descending) or Manual (click a category and then click the arrow buttons to move it up or down). Change Colors, Fill Patterns, Dot Size and Bar Width - In the Chart Properties window, click Series format. - Select either Color or Pattern. - Under Elements, choose the color or pattern for each item. These elements may include, depending on the type of chart: - Body points. - Subjects. - The type of behavior (e.g. Moving vs. Not Moving). - The Median (when you choose a Box and Whiskers chart) and the Datapoints (when you choose a Box, Whiskers and Data Points chart). Note: Pattern fill is only available when you choose a Bars or Box and Whiskers chart. - The following options are available for some chart types: - Dot size. Select the size of the dots. This applies to Box, Whiskers and Data Points. Note: All dots lie on the vertical middle line of the box plot. It is likely that individual points overlap and are therefore not all visible. - Bar width / Box width. Select the bar/box width (range 0–100). Note that for Box and Whiskers charts, this also changes the width of the whiskers. - Gap between bars. Move the slider or click the arrow buttons to select the required gap between adjacent bars (range 0–100). Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Customize the group charts (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-customize-the-group-charts-continued Chapter: EthoVision XT Edit Axes, Gridlines, and Legend In the Chart Properties window, click Axes and Legend. For the Vertical axis: - Select Display vertical axis title and enter the new title. The default title is [name of trial statistic] [unit]. - Next to Scale min and Scale max, set minimum and maximum value of the vertical axis automatically (Auto), or select Fixed and enter the values you require. - Select or deselect Display gridlines. For the Horizontal axis: - Select Display horizontal axis title and enter the new title. The default title is the name of the category selected as Horizontal axis. For the Legend: - Select Display legend. The legend lists the possible combinations of specifiers and the item selected under Data series, separated by "/". Apply the Changes to Other Charts Click Apply to All at the bottom of the Chart Properties window. This copies the settings to all charts on that tab, not in other tabs. Reset to Default Charts Click Reset to Default at the bottom of the Chart Properties window. This resets the current chart to default, not other charts. Notes - In Box and whiskers charts, the box includes from 25% (first quartile) to 75% (third quartile) of the data points; the range of data is also named interquartile range. The whiskers include the whole range of the data, including potential outliers. - If you deselect an element from the Show/Hide menu, this element is removed from the statistics table, not from the chart. - To remove a statistic from the chart, right-click the header of the dependent variable in the table, and click Properties. Click Group Statistics, and deselect that statistic. Batch Calculation Aim Batch calculation helps you perform calculations in multiple runs, each with a particular combination of track smoothing settings, data profiles and analysis profiles. It is handy when you have large data sets that take hours to analyze. In that case you can start batch calculation at the end of the day, and return the next day to collect the results. Each analysis run is based on a combination of three profiles: - Track Smoothing profile (for smoothing tracks and filtering noise). - Data profile (the trials and samples subject to analysis). - Analysis profile (the dependent variables and their statistics). When you carry out batch data acquisition, it is also useful to couple this with batch statistics calculations, so that analysis is started automatically after acquisition of the last trial has ended. See Auto-start data analysis. To Run Batch Calculation - Make sure that all Track Smoothing profiles, Data profiles and Analysis profiles that you want to use are defined in the Experiment Explorer. - Choose Analysis > Results > Statistics & Charts, or in the Experiment Explorer, under Results, click Statistics & Charts. - Click the Batch button. - In the Batch Calculation window, do one of the following: - If you want to carry out batch calculation for all the combinations of Track smoothing profiles, Data profiles and Analysis profiles, click Add all. - If you are interested in specific combinations of profiles, select the combination of profiles that you want to use, and click Add. Repeat this step for all the combinations you require. To remove a profile combination, click that combination in the list and then click Delete. To select multiple combinations, click each combination while holding the Ctrl key down. To minimize processing time and disk space occupied by the results, make sure that when you select Add all, the Track smoothing, Data and Analysis profiles in your experiment are those you want to use for analysis. Remove any duplicate or non-interesting profiles. - The Batch Calculation window lists the combinations selected for calculation. - Click Calculate when you are ready. To retrieve the results for a particular combination of profiles, select this combination from the lists on the toolbar. - Export the results. Note: You can export the result for one combination of profiles at a time. See Export the statistics result. Note - Batch statistics calculations create a number of temporary files. For this reason, they may require large disk space, especially when you analyze large amounts of data. These files may also make backup files excessively large. Before backing up an experiment, make sure to remove unnecessary files to create a smaller backup file. For more information, see Back up an experiment. Dependent Variables Notes - You can use dependent variables: - In Trial Control. For example, to start tracking when a specific behavior or event occurs. - In the Data profile. For example, to select the intervals when the subject was moving. - In the Analysis profile. For example, to calculate statistics of distance, velocity or specific behaviors. - Some dependent variables are only available if you have one of the add-on modules installed: Trial and Hardware Control, Social Interaction, Rat/Mouse Behavior Recognition and Live Mouse Tracker. Activity and Movement - Distance Moved - Velocity - Movement - Acceleration - Acceleration State - Activity - Activity State - Body Elongation - Body Elongation State - Mobility - Mobility State Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Customize the track colors URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-customize-the-track-colors Chapter: EthoVision XT Customize the Track Colors Aim: To plot data in colors depending on the subject, the treatment level, or other variables of interest. To Access These Options Choose Analysis > Results > Plot Tracks or Plot Integrated Data. In the Track Plot Settings pane, click the Colors tab. Specify how colors should vary, for example between arenas, or within tracks. Subject Under Level, select Subject. To change the color for a subject and a body point, click the corresponding cell under Settings. - If you tracked more than one subject per arena, choose this option to have the tracks of different subjects displayed in different colors. By default, different subjects have different colors for the center-point, and the same color for the nose- and tail-base points. - If you tracked subjects in multiple arenas, the track of Subject 1 in Arena 1 is displayed in the same color as that of Subject 1 in Arena 2, Arena 3, etc. Track Under Level, select Track to have tracks in colors based on the value of an independent variable, for example to show subjects in colors based on the treatment level. - Select an independent variable from the Variable list. - Click the buttons next to Color Range and select the colors that you want at the ends of the range. Next, click Apply to assign colors automatically. Alternatively, for each value of the variable selected, click the color cell and choose the color you want to assign to the tracks with that value. - Do the same for each subject in the arena. Sample Under Level, select Sample to have the samples within tracks displayed in a color depending on the value of a dependent variable, for example velocity. This way you can see where changes in behavior took place. - Select a dependent variable from the Variable list. The list shows the dependent variables selected in the currently active Analysis profile. If you do not see the variable you want, open the Analysis profile and include that variable, or from the list on the toolbar select the analysis profile that contains the variable. - Click the cell under From/To and choose a color for the lowest/highest value of the dependent variable, respectively. EthoVision calculates the spectrum of colors in between and shows it in the middle cell. The lowest and highest values are shown under From and To. For State variables, those are false and true. For continuous variables, those are the minimum and maximum value measured for that variable in the trial. For example, 0 to 33.37 for Distance moved. - If you tracked more than one subject per arena, repeat step 2 for each subject. Below is an example of a track plot where Sample is selected under Level. Samples are displayed in red when the subject was in any of the closed arms of the Elevated Plus Maze. In the Analysis profile, a dependent variable In zone is defined for the center-point in any of the closed arms (the When in any of the selected zones option is selected in the In zone settings dialog). When plotting the tracks, samples in any of the open arms are displayed in the color selected for the true value of the In zone variable. Other samples are displayed in the color under false. Customize the Color of Missing Samples Missing sample points are always visualized in the track plot. You can change the color of missing samples to distinguish them more easily from the actual data. The current color for missing samples is indicated next to Missing Sample Color. To change the color for missing samples, click the button and select a new color in the Color window. Display Background, Arenas and Zones Aim: To customize how the background image, the arena and the zones are displayed in Track Visualization or Integrated Visualization. Customize the Background (for Track Visualization) - Choose Analysis > Results > Plot Tracks. - On the toolbar, click the Show/Hide button and select Background. - Select one of the following, then click OK. - Plain. To have a uniform background. Click the button next to this option to select a color. To select colors other than the basic ones, click the button Other. - Captured image. If you want to have the captured image from the Arena Settings as background. Show/Hide the Video Image (for Integrated Visualization) Choose Analysis > Results > Plot Integrated Data. The Video window is shown by default. To hide the Video window, click the Show/Hide button on the toolbar and deselect Video Window. Show/Hide Arenas and Zones in the Track Plots Arenas, zones and points can be displayed on top of the background as overlay objects. The color of each arena and zone depends on the color chosen in the Arena Settings. - Choose Analysis > Results > Plot Tracks or Plot Integrated Data. - Click the Show/Hide button on the toolbar and select Arena Features. - Select the arena feature you want to have displayed. Arenas and zones are shown in a semi-transparent color, so their appearance also depends on what you select as background. If you want to change the color of an arena or zone group, open the appropriate Arena Settings, click the correct Color row and select the color of your choice. For a multi-arena setup, you cannot select to view some arenas and not others. Related Topics and Tasks Main Topics - Calculate statistics - The statistics result - Group charts - Batch statistics calculation What Do You Want to Do? - Calculate statistics: procedure - Edit the Analysis profile - Export the statistics result Learn About - Statistics available Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Dependent variable plots URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-dependent-variable-plots Chapter: EthoVision XT Dependent Variable Plots Dependent variable plots show the values of the dependent variables selected in your active Analysis profile, on a time line. Dependent variables are displayed in different ways depending on their type: - States like In zone: colored bars indicating the state's duration. - Point events like Rotation: vertical segments indicating the event's occurrence, with no duration. - Continuous variables like Velocity: values are plotted as a time series, with one value per sample time. Procedure To plot a dependent variable: - Define the variable. Calculate statistics: procedure. - See Plot integrated data. Scope of the Dependent Variable Plot When the trial includes more than one arena or subject, the plot's header indicates which arena and the subject it refers to. Why Use Dependent Variable Plots? Dependent variable plots are especially useful: - To check whether you set correct thresholds for state variables like Body elongation, Movement, Mobility and Activity. - Open your analysis profile, double-click the variable's name and enter your best estimate for the thresholds. - Plot integrated data. Play back your data, watch the video and check whether the states shown in the plot correspond with the states of the animals in the video. If necessary, repeat steps a and b. - To check that you have scored behaviors manually at a good level of accuracy. - In your Analysis profile, select the manually scored behaviors you want to check. - Plot integrated data. Play back your data, watch the video and check whether the states shown in the plot correspond with the behavior of the animals in the video. If necessary, export the data to The Observer XT, where you can correct the errors. - To view the behaviors of Behavior Recognition together with their probability values. This helps when you want to refine the definition of those behaviors based on their probability value. - To check whether your Trial Control Settings do what you want them to do. You can visualize Trial Control events and Trial Control states. For more information about Trial Control, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Dependent Variables Reference URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-dependent-variables-reference Chapter: EthoVision XT Variables Aim In this topic you find the commands and functions that you can use to extract and process tracking data with JavaScript code. Get Started We assume that you have basic knowledge about JavaScript. To get started with JavaScript we recommend this online compiler: https://repl.it/languages/javascript Many courses on the internet concern JavaScript for web page developers. An excellent course more focused on JavaScript as a data processing tool can be found here: https://www.youtube.com/watch?v=Bv_5Zv5c-Ts Extract Subject Features Use the functions below to extract the position and other features of your subjects. - GetCenter, GetNose, GetTail - GetSubjectCenter, GetSubjectNose, GetSubjectTail - GetArea, GetChangedArea - GetSubjectArea, GetSubjectChangedArea - GetElongation - GetSubjectElongation - GetViewDirection - GetSubjectViewDirection Extract Other Data - GetSampleTime - GetPixelChange - GetDistanceToZone - GetDistanceToPoi - GetBehaviorEvent - GetCommand - GetSignal - new Point - GetPointPoi Query Data Use the functions below to ask simple questions, like Is the subject in the central zone? The software gives a boolean answer (true/false). - IsInZone (discontinued) - IsSubjectCenterInZone, IsSubjectNoseInZone, IsSubjectTailInZone - IsPointInZone - Point.Equals - IsSubjectActor Calculate - Distance - Point.Distance - TurnAngle - Heading - SetOutput - SetOutputMissing GetCenter, GetNose, GetTail Returns the x,y coordinates of the center-point, nose-point or tail-base point of the subjects in a single-subject trial, respectively. Use this function in a single-subject experiment, or in a multi-subject experiment to extract the body points of the focal subject. - Syntax GetCenter() GetNose() GetTail() - Example In the following example, the code verifies if the center point of the subject, when found, is in the zone named Zone 1. const g_Zone = "Zone 1"; (...) function Process() { var ptC = GetCenter(); if (ptC) { g_bInZone = IsInZone(g_Zone, ptC); } } - Example In the following example, we calculate the average x coordinate of the center point and the nose point. var ptC = GetCenter(); var ptN = GetNose(); var x_avg = ptC.x + ptN.x; GetSubjectCenter, GetSubjectNose, GetSubjectTail Returns the x, y coordinates of a body point of a specific subject in a multi-subject experiment. You can use this function to compare the position of different subjects in the same JavaScript variable. See also the sample experiment Subject Counter with JavaScript code XT160, which you can find on my.noldus.com, under Downloads > EthoVision XT > Drivers and tools. - Syntax GetSubjectCenter(Subject name) GetSubjectNose(Subject name) GetSubjectTail(Subject name) - Arguments Subject name: the name of one of the subjects as defined in the Experiment Settings. - Example In the following loop (not shown entirely), the center point of each subject is loaded in the variable pt. const g_aSubjects = ["Subject 1", "Subject 2", "Subject 3", ... ] (...) for (i = 0; i < g_aSubjects.length; ++i) { var pt = GetSubjectCenter(g_aSubjects[i]); (...) } Note that g_aSubject.length function gets the length of the array variable g_aSubjects which contains the names of the subjects. The variable g_aSubjects is defined at the top of the script. GetArea, GetChangedArea Returns the current value of the subject's area (in practice, the yellow blob that you see during tracking), and the area that has changed from the previous sample, respectively. Use these functions for: - The subject in a single-subject experiment. - The focal subject in a multi-subject experiment. Here "focal" refers to the subject for which the statistics are calculated. Areas are expressed in internal units (mm), independent of the units selected in the Experiment Settings. For information on the Changed area, see Rotation. - Syntax GetArea() GetChangedArea() - Example var a = GetArea(); var ca = GetChangedArea(); - Notes GetArea and GetChangedArea are not available when using Deep learning with two subjects per arena, because this method does not record the subjects' body contour. GetSubjectArea, GetSubjectChangedArea GetSubjectArea returns the current value of the area of a specified subject in a multi-subject experiment. GetSubjectChangedArea returns the area of the subject in a multi-subject experiment that has changed from the previous sample. For information on the Changed area, see Rotation. The subject's area is the area of the yellow blob that you see during tracking. It is expressed in internal units (mm), independent of the units selected in the Experiment Settings. - Syntax GetSubjectArea("subject name") GetChangedArea("subject name") where Subject name is the name of the subject specified in the Experiment Settings. - Example var a = GetSubjectArea("Subject 1"); - Example // This for loop extracts the area for a number of subjects for (i = 0; i < g_aSubjects.length; ++i) { var AreaSubj = GetSubjectArea(g_aSubjects[i]); ... } - Notes GetSubjectArea and GetSubjectChangedArea are not available when using Deep learning with two subjects per arena, because this method does not record the subjects' body contour. GetElongation GetElongation returns the current value of Body elongation for: - The subject in a single-subject experiment. - The focal subject in a multi-subject experiment. Here "focal" refers to the subject for which the statistics are calculated. It is expressed as a number between 0 and 1. To obtain the same as the dependent variable Body elongation, multiply it by 100. - Syntax GetElongation() - Example var y = GetElongation(); if (y != null) { SetOutput(y*100); } else { SetOutputMissing(); } - Notes GetElongation is not available when using Deep learning with two subjects per arena, because this method does not record the subjects' body contour. GetSubjectElongation Returns the current value of Body elongation for a specified subject in a multi-subject experiment. It is expressed as a number between 0 and 1. To obtain the same as the dependent variable Body elongation, multiply it by 100. - Syntax GetSubjectElongation("Subject name") where Subject name is the name of the subject specified in the Experiment Settings. - Example // This for loop extracts the body elongation for a number of subjects for (i = 0; i < g_aSubjects.length; ++i) { var EloSubj = GetSubjectElongation(g_aSubjects[i]); ... } - Notes GetSubjectElongation is not available when using Deep learning with two subjects per arena, because this method does not record the subjects' body contour. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Dependent Variables Reference (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-dependent-variables-reference-continued Chapter: EthoVision XT GetViewDirection Returns the current value of the Head direction variable for: - The subject in a single-subject experiment. - The focal subject in a multi-subject experiment. Here "focal" refers to the subject for which the statistics are calculated. It is expressed in radians. Note that the Head direction dependent variable provided by EthoVision XT is expressed in degrees. To convert your JavaScript variable to degrees, see the example below. Syntax GetViewDirection() Example The following example retrieves the head direction and converts it to degrees: var dir = GetViewDirection(); If you want to extract the head direction in degrees, convert the value of head direction to degrees with the following formula: function toDegrees(angle) { return angle * (180 / Math.PI); } (...) var dir = GetViewDirection(); angle = toDegrees(dir); Notes GetViewDirection is not available when using Deep learning with two subjects per arena, because this method does not record the subjects' head direction. GetSubjectViewDirection Returns the value of the Head direction of a specified subject in a multi-subject experiment, for the current sample. The value is given in radians. Note that the Head direction dependent variable provided by EthoVision XT is expressed in degrees. To convert your JavaScript variable to degrees, see the example in GetViewDirection. Syntax GetSubjectViewDirection("subject name") where Subject name is the name of the subject specified in the Experiment settings. Example The following for loop extracts the Head direction in radians for a number of subjects: // This for loop extracts the Head direction in radians for a number of subjects for (i = 0; i < g_aSubjects.length; ++i) { var HDirSubj = GetSubjectViewDirection(g_aSubjects[i]); ... } Notes GetSubjectViewDirection is not available when using Deep learning with two subjects per arena, because this method does not record the subjects' head direction. GetSampleTime Returns the sample time (in seconds) of the sample currently processed. You can use this function to calculate the latency of an event that you cannot obtain through the other dependent variables. Note: The sample time in this function is the track time, that is, the time elapsed from the start of the track (the first sample), not the start of the trial. Syntax GetSampleTime() Example The following example outputs the value of the current sample time. If it is not found, a missing value is assigned with the SetOutputMissing command: function Process() { var st = GetSampleTime(); if (st != null) { SetOutput(st); } else { SetOutputMissing(); } } GetPixelChange Returns the current proportion of pixels in the arena that have changed intensity above the specified Activity threshold from the previous video frame. This proportion can be between 0 (no pixel in the arena has changed intensity value above the threshold) and 1 (all pixels in the arena have changed intensity value above the threshold). A pixel change value of 0.156 (expressed as proportion) corresponds to a Body angle value without smoothing of 15.6%. To use this variable, you must select Activity analysis in the Experiment Settings and define the threshold value in Activity settings in the Detection settings. For information on the pixel change, see Body angle. Syntax GetPixelChange() Example var a = GetPixelChange(); GetDistanceToZone Returns the distance of a (body) point from a zone. The distance is zero if the body point is within the zone. Distances are expressed in internal units (mm), independent of the units selected in the Experiment Settings. Syntax GetDistanceToZone(Zone, Point) Arguments - Zone: The name of the zone as it appears in the Arena Settings; e.g. "Platform". - Point: The name of the point; usually a body point. Example const g_strZone = "Object"; (...) function Process() { var ptNose = GetNose(); var dist = GetDistanceToZone(g_strZone, ptNose); } GetDistanceToPoi This is similar to GetDistanceToZone; it returns the distance from the specified point of interest. Distances are expressed in internal units (mm), independent of the units selected in the Experiment Settings. Syntax GetDistanceToPoi(Point of interest, Point) Arguments - Point of interest: The name of the point of interest as it is defined in the Arena Settings. - Point: The name of the point to which distance is determined; usually a body point. GetBehaviorEvent This command returns the value of an event scored manually using the Manual Scoring function. If you work with Live Mouse Tracker, this command also works with the events listed under Raw Live Mouse Tracker data in the Analysis profile. Syntax GetBehaviorEvent(behavior) GetBehaviorEvent(behavior, receiver) Arguments - Behavior: The name of the behavior as in the Manual Scoring Settings or listed under Raw Live Mouse Tracker data in the Analysis profile. - Receiver (optional): The name of the receiver, in case of multi-subject tracking. Return Values - undefined: No behavior event. - 1: Start of a state event. - 2: Stop. - 4: Point event. Example The following code gets the values of the behavior Sleep that was scored. The function UpdateState at the top copies the values of Sleep, 1 or 2, to a new state variable g_bState with values true or false, respectively: var g_bState = false; function UpdateState(evt) { if (evt != undefined) { if (evt == 1) { g_bState = true; } else if (evt == 2) { g_bState = false; } } } function Process() { var evt = GetBehaviorEvent("Sleep"); UpdateState(evt); SetOutput(g_bState); } GetCommand Returns the event that represents a command to a hardware device. Syntax GetCommand(Device name, Command name) Arguments - Device name: The name of the device specified in EthoVision XT. For example, "Device A". To find the device name, in the Arena Settings click the Arena-Hardware Mapping button, under Device name click the cell of the device you require and press Ctrl+C. Paste the text into the JavaScript code as Device name. - Command name: The name of the command used in the Trial Control Settings. For example, "Drop pellet". To find the command name, open the Trial Control Settings, locate the Action box that contains that command and click Settings. Take note of the text near Action to perform. Enter this text in the JavaScript code as Command name. Example In the following example, JavaScript reads the command "Drop pellet" of a Pellet dispenser with name Device A and outputs the value for each sample of the track (1 = drop a pellet; missing value = no pellets dropped): function Process() { var DropPellet = GetCommand("Device A", "Drop pellet"); SetOutput(DropPellet); } Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Dependent Variables Reference (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-dependent-variables-reference-continued-lC6 Chapter: EthoVision XT GetSignal Returns the value of a hardware signal. - Syntax GetSignal(Device name, Signal name) - Arguments - Device name: the name of the device specified in EthoVision XT. For example, "Device B". To know the device name, in the Arena Settings click the Arena-Hardware Mapping button, under Device name click the cell of the device you require and press Ctrl+C. Paste the text into the JavaScript code as Device name. - Signal name: the name of the signal that you want to acquire. For example, "Number of licks". To know the signal name, open an Analysis profile, click the button next to Hardware continuous, select a Device type, Device, and Signal. Take note of the text near Signal, and enter this text in the JS code as Signal name. - Example In the following example, JavaScript reads the value of the signal "Number of licks" of a lickometer (Device B) and outputs it for each sample of the track. function Process() { var s = GetSignal("Device B", "Number of licks"); SetOutput(s); } New Point With the new Point statement you can define a point in space. - Syntax new Point(x,y,z) - Arguments - x, y, z (z is optional): The coordinates in mm based on the calibration axes and origin in the Arena Settings. - Example pt1 = new Point(200, 300); - Note: You cannot visualize the position of points defined with JavaScript. To do so, define points in the Arena Settings. GetPointPoi With this command you can extract the coordinates of a point of interest of the center of a zone or arena. Note that GetPointPoi returns the position of the point, then you have to extract the coordinates with additional commands (e.g. x = pt.x). - Syntax GetPointPoi(point) - Arguments - point: The name of the point or the zone or arena, of which you want to find the center. - Example const g_zone = "Zone 1"; function Start() { } function Stop() { } function Process() { var pt = GetPointPoi(g_zone); var xc = pt.x; var xy = pt.y; } IsInZone This function has been replaced by other functions in EthoVision XT 19 (see below). - For single-subject tracking: see IsPointInZone - For multi-subject tracking: see IsSubjectCenterInZone, IsSubjectNoseInZone, IsSubjectTailInZone You can still use IsInZone in your code, but it won't work properly when analyzing data points in hidden zones. IsSubjectTailInZone Use this function to determine if a body point of a subject is within a zone. The zone must be defined in the Arena Settings. The return value is boolean (true or false). - Syntax IsSubjectCenterInZone(Subject name, Zone name); IsSubjectNoseInZone(Subject name, Zone name); IsSubjectTailInZone(Subject name, Zone name); - Arguments - Subject name: the name of one of the subjects listed in the Experiment Settings. - Zone name: the name of the zone of interest defined in the Arena Settings; for example, "Zone 1". You can specify the name directly ("Zone 1" with quotes), or a variable that contains that name. The zone can be a single zone, a cumulative zone, an entry zone, or a hidden zone. - Example – One Subject var bC = IsSubjectCenterInZone("Subject 1", "Zone 1"); var bN = IsSubjectNoseInZone("Subject 1", "Zone 1"); var bT = IsSubjectTailInZone("Subject 1", "Zone 1"); or const g_sZone = "Zone 1" var bC = IsSubjectCenterInZone("Subject 1", g_sZone); var bN = IsSubjectNoseInZone("Subject 1", g_sZone); var bT = IsSubjectTailInZone("Subject 1", g_sZone); - Example – Multiple Subjects var bC1 = IsSubjectCenterInZone("Subject 1", "Zone 1"); var bC2 = IsSubjectCenterInZone("Subject 2", "Zone 1"); IsPointInZone Use this function to determine if a point (a body point, or a point of interest) is within a zone. The zone must be defined in the Arena Settings. The return value is boolean (true or false). - Syntax IsPointInZone(Zone name, Point name) - Arguments - Zone name: the name of a zone defined in the Arena Settings; for example, "Zone 1". - Point name: The name of a body point or a point of interest defined in the Arena Settings. - Example pt = GetCenter(); var b1 = IsPointInZone("Zone 1", pt); or pt = new Point(10, 10); var b1 = IsPointInZone("Zone 1", pt); Point.Equals Checks if two points are equal. - Syntax point1.Equals(point2) - Arguments - point1: the first point - point2: the second point - Example The variable b gets the value 1 if the two points pt1 (the center of the subject) and pt2 (a point in space defined with the new statement) have the same coordinates. var pt1 = GetCenter(); var pt2 = new Point(1.0, 2.0); var b = pt1.Equals(pt2); - Errors: If one of the two points is null, the value is not calculated and an invalid reference is returned. IsSubjectActor Determines if the subject specified (argument) is currently the actor (focal subject) of the track being analyzed. The return value is boolean (true or false). You can use this function to skip comparisons and calculations that do not make sense. - Syntax IsSubjectActor(Subject name) Where Subject name is the name of one of the subjects listed in the Experiment Settings. - Example In this example a for loop scans the list of i subjects Subject 1, Subject 2, etc. contained in the array g_aSubjects[i] and calculates the distance between the focal subject (that is, the subject of the currently analyzed track) and the subject i. for (i = 0; i < g_aSubjects.length; ++i) { var ptSubj = GetSubjectCenter(g_aSubjects[i]); (...) //invoke Distance function var Dist = Distance(ptFocal, ptSubj); } Obviously at some point in this loop the focal subject and the subject i are the same individual. You can exclude the distance calculation focal-to-focal by inserting an extra check. var b = IsSubjectActor(g_aSubject[i]); if (b == true) { //invoke distance function } Distance To calculate the distance between two points, see Point.Distance. You can also use the code below and invoke the function in your script. Distance is expressed in internal units (mm), independent of the units selected in the Experiment Settings. - Function // Function to calculate distance between two points function Distance(pt1, pt2) { var dx = pt1.x - pt2.x; var dy = pt1.y - pt2.y; return Math.sqrt(dx * dx + dy * dy); } - Example of Function Call //Get the center point of subject 1 and subject 2 var cSubj1 = GetSubjectCenter("Subject 1"); var cSubj2 = GetSubjectCenter("Subject 2"); //call distance function var Dist = Distance(cSubj1, cSubj2); - Errors: If one of the two points is null, the value is not calculated. Point.Distance Calculates the distance between two points. Distance is expressed in internal units (mm), independent of the units selected in the Experiment Settings. - Syntax point1.Distance(point2) - Arguments - point1: the first point - point2: the second point - Example var pt1 = GetCenter(); var pt2 = GetNose(); var dist = pt1.Distance(pt2); - Errors: If one of the two points is null, the value is not calculated and an invalid reference is returned. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Dependent Variables Reference (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-dependent-variables-reference-continued-cXp Chapter: EthoVision XT TurnAngle Returns the angle in radians between three points. The name suggests that this function is restricted to turn angles but you can use it to calculate any angle formed by three points in general. See also Turn angle. - Syntax TurnAngle(Point 1, Point 2, Point 3) - Arguments - Point 1: the name of the begin point. - Point 2: the name of the middle point. - Point 3: the name of the end point. This is the point at the current sample time, while Point 1 and Point 2 are the points at two immediately preceding sample times. - Example ta = TurnAngle(g_aPoints[0], g_aPoints[1], g_aPoints[2]); where g_aPoints is an array variable of length 3. Remember that TurnAngle is in radians. At the top of the code, define a function to obtain the value in degrees: function toDegrees(angle) {     return angle * (180 / Math.PI); } (...) var tadg = toDegrees(ta); - Errors If any of the three points is null, the value is not calculated. Heading Returns the value of heading in radians based on two sample points. See Heading. - Syntax Heading(Point 1, Point 2) - Arguments - Point 1: Begin point. - Point 2: End point. To calculate heading, Point 1 is the point at the previous sample time and Point 2 the point at the current sample time. - Example var hd = Heading(g_aPoints[0], g_aPoints[1]); where g_aPoints is an array variable of length 2. At the top of the code, define a function to obtain the value in degrees: function toDegrees(angle) {     return angle * (180 / Math.PI); } (...) var hdg = toDegrees(hd); - Errors If one of the two points is null, the value is not calculated. SetOutput Assigns a value to the JavaScript variable for the current sample time. - Syntax SetOutput(Value) SetOutput(Output, Value) - Arguments - Value: the value that you want to assign to the variable at the current sample time. - For JavaScript Continuous variables: a rational number. - For JavaScript State variables: true or false. - For JavaScript Event variables: 0 or 1. - Output: Output number. When the variable has just one value per sample, like in most applications, then you do not need to specify Output. When the variable has multiple outputs, like in a state variable with 4 possible states, specify the output in each line (beginning from zero). For example: SetOutput(0, bOutput1); //write first state SetOutput(1, bOutput2); //write second state SetOutput(2, bOutput3); //write third state SetOutput(3, bOutput4); //write fourth state - Example if (x != null) {     SetOutput(x); } - Errors If the value is null or undefined, the output will be missing. - Notes When the variable has multiple outputs, remember to specify the Number of outputs at the bottom of the JavaScript window. SetOutputMissing Assigns a missing value to the JavaScript variable for the current sample time. - Syntax SetOutputMissing() - Example In the following example, if the value of x is not null, it is assigned to the output of the JavaScript variable; otherwise it is set to missing. if (x != null) {     SetOutput(x); } else {     SetOutputMissing(); } See also - JavaScript continuous - JavaScript state - JavaScript event Live Mouse Tracker In the Analysis profile you find two groups of variables based on Live Mouse Tracker data. Under Raw Live Mouse Tracker data you find basic events of Live Mouse Tracker, like Contact and Approach. - Raw Live Mouse Tracker data Under Live Mouse Tracker you find more complex variables: - Approach rearing subject - Drink - Follow - Get Away - Group - Make and break group - Make contact - Move - Nest - Nose contact - Nose contact sequence - Out of nest - Rear - Social approach - Stretch attend posture - Social escape Notes - You can also use the basic events of Live Mouse Tracker (first group above) to carry out custom analysis. For example, analyze Contact events with JavaScript code. To extract Live Mouse Tracker events, use the function GetBehaviorEvent. See Commands and functions for JavaScript variables. - In the Analysis profile, under Social, you find variables derived from Live Mouse Tracker with extended options: - Side by side - Train - In experiments based on Live Mouse Tracker data, some standard EthoVision XT variables are not available. See a note in the topic Live Mouse Tracker: Workflow. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Distance moved URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-distance-moved Chapter: EthoVision XT Distance Moved Definition The distance traveled by the center, nose or tail-base point of the subject from the previous sample to the current one. It is calculated as: - DMk = Distance moved from sample k–1 to sample k - Xk-1, Yk-1 = X,Y coordinates of the center, nose or tail-base point at sample k-1 - Xk, Yk = X,Y coordinates of the center, nose or tail-base point at sample k-1 How to Specify Distance Moved - Click Add next to Distance moved. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If your experiment is set to Center-point, nose-point and tail-base detection, click the Body points tab and select the body points for which you want to calculate the distance. - Because it is based on change in X,Y coordinates, Distance moved needs two valid (non-missing) samples. A missing sample in your track results in missing Distance moved values in that and in the next sample. Make sure that the proportion of missing samples is low (less than 1%). - Sample rate influences the values of Distance moved. When tracking at too low a sample rate, parts of the actual path are cut off, resulting in an underestimation of per-sample (and total) Distance moved. If, on the other hand, the sample rate is too high, EthoVision XT catches the wobbling of the body's center point of the walking animal, causing extra apparent movement, and therefore an overestimation of per-sample (and total) Distance moved. See Track Smoothing for a description of how to filter out small movements. Applications Distance moved is often used to give a general measure of activity. It is also used as the basis for calculating other parameters such as velocity (see below). In rodent models of aging, the total and maximum distance moved are used to calculate the frailty index. See Parks et al. (2012) J. Gerontol. A 67(3): 217-227. Velocity Definition The distance moved by the center, nose or tail-base point of the subject per unit time. Velocity is obtained by dividing Distance moved by the time difference between a sample and the previous one, where Vk = velocity at sample k (expressed in the unit you have defined in the Experiment Settings) and DMk = Distance moved at sample k. How to Specify Velocity - Click the Add button next to Velocity. - Under Outlier filter, specify the Averaging interval. Leave 1 if you want to keep the raw data; enter a value to smooth the values using a running average method. See Averaging interval. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If your experiment is set to Center-point, nose-point and tail-base detection, click the Body points tab and select the body points for which you want to calculate the velocity. - Sample rate influences the calculation of Distance moved, and therefore Velocity. When tracking at too low a sample rate, parts of the actual path are cut off, resulting in an underestimation of per-sample Velocity. If, on the other hand, the sample rate is too high, EthoVision XT catches all random movements and wobbling of the body point of the walking subject, causing extra apparent displacement, therefore an overestimation of Velocity. See Track Smoothing for a description of how to filter out small movements. - Because it is based on change in distance moved, Velocity needs two valid (non-missing) samples. A missing sample in your track results in missing Velocity values in that and in the next sample. Make sure that the proportion of missing samples is low (less than 1%). You can view the proportion of missing samples as one of the System Variables in the Trial list. Applications - Apart from the obvious applications of this dependent variable, the mean velocity is sometimes used as a measure of general activity (for example, Nilsson et al. 1993, J. Exp. Biol., 153-162; Winberg et al. 1993, J. Exp. Biol., 213-232). - TIP: Define Velocity and Movement in the same Analysis profile to find out which averaging interval results in the best match between movement bouts and video. - In rodent models of aging, the average velocity is used to calculate the frailty index. See Parks et al. (2012) J. Gerontol. A 67(3): 217-227. Averaging Interval Aim To smooth the values of a dependent variable. This Topic Applies To Dependent variables: Acceleration state, Body angle, Activity state, Body angle state, Body elongation, Body elongation state, External data (resampled), External data - state, Rotation, Mobility state, Movement, Velocity. The dependent variable can be in a condition defined in the Trial Control Settings, in the Analysis profile and in the Data profile. Setting the Averaging interval in one part of EthoVision XT does not influence the value of the same variable in the others. How to Access This Option In the Trial Control Settings, in the Analysis profile or in the Data profile select the dependent variable and locate Outlier filter. How Averaging Interval Works - When Averaging interval is 1, the outlier filter is off, thus the values of the variable are not smoothed. - When Averaging interval is 2 or larger, EthoVision XT replaces the per-sample value of the dependent variable with the average calculated over the number of samples specified by the interval. The table below shows how EthoVision XT re-calculates a variable V in a few samples when Averaging interval is set to 2. Note how the average (avg) is obtained when values of the dependent variable are missing. Remember that velocity V at time t is only calculated when there are valid samples at time t and t-1. Sample Valid (•) or Missing (−) Original Value Smoothed Value when Averaging Interval = 2 1 • V V 2 • V avg (V, V) 3 • V avg (V, V) 4 − not calculated avg (V, [no value]) = V 5 − not calculated avg ([no value], [no value]) = [no value] 6 • not calculated avg ([no value], [no value]) = [no value] 7 • V avg ([no value], V) = V Notes - Note the difference between Track Smoothing and the Outlier filter: - With Track Smoothing, you smooth the raw x,y coordinates. This also has an effect on the dependent variables calculated based on those coordinates, for example Distance moved. See Smooth the Tracks. - With Outlier filter, you smooth the values of the dependent variable, for example velocity or mobility, after they are calculated from the raw data. The Outlier filter is useful when you want to calculate state variables. Apply the Outlier filter, for example, when you want to smooth Velocity to calculate the Movement states, which are based on velocity; or smooth Mobility when you want to calculate Mobility state. - If you combine Track Smoothing with Outlier filter, the dependent variable is calculated with the Outlier filter after the raw coordinates are smoothed with Track Smoothing. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Distance to zone URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-distance-to-zone Chapter: EthoVision XT Definition The shortest distance between a subject's body point (or selection of points) and a zone (or group of zones). You can calculate the distance regardless of where the body point is, or assuming that the point is always outside the zone (in the latter case, the distance is set to zero when the body point enters the zone). The calculation of this variable is performed in two steps: - The coordinates of the point on the zone border that is closest to the coordinates of the body point for the current sample are found. - The distance in a straight line between the two coordinates is calculated. How to Specify Distance to Zone - Click the Add button next to Distance to zone and click the Distance to zone tab. - Under To the following zones, select the zones you want to consider for the calculation. For example, if you want to calculate the mean distance to Zone 1, select Zone 1. By default, Arena is selected. If you have chosen two or more zones, select how the zones should be analyzed: - For each of the selected zones. Zones are analyzed separately. - Shortest distance to any zone. For each sample, EthoVision XT chooses the zone that is currently closest to the point(s) you have chosen, and uses the resulting distances for calculating the statistics. - Select the Include if in zone option if you want to calculate the distance to the border of a zone of interest, regardless of whether the subject is outside or inside the zone. If you want to calculate the distance to the border of the zone when the subject is outside the zone, leave this option cleared. See one of the Notes below. - Under From following body points, select the points you want to consider for the calculation. For example, select Nose-point if you want to analyze the distance between the nose-point and a specific zone. By default, Center-point is selected. If you have chosen two or more body points, select one of the following from the list: - For each selected point. Statistics are calculated for each point separately. - Shortest distance to any point. For each sample, EthoVision XT chooses the body point that is currently closest to the zone, and uses the resulting distances for calculating the statistics. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If you have selected Include if in zone in the Distance to zone tab of the variable's properties window, and the body point's coordinates lie inside the zone, the Distance to zone is greater than 0. Example: Effect of the option Include if in zone on the distance to zone (DZ, dotted lines) for three consecutive samples 1, 2 and 3. The zone is shown in gray. When the option is not selected, and sample 3 is within the zone, DZ for that sample is zero. When the option is selected, DZ for sample 3 has a value larger than zero. - If your experiment is set to Only center-point detection or Color marker tracking, the body point options are not available. Calculations are based on the center point. Application Two examples of how you can use Distance to zone with Include if in zone not selected: - In a Morris water maze test with the hidden platform defined as a zone, Distance to zone can measure the animal's progress towards the platform. You can select the Total statistic to give a measure of the cumulative distance to zone (for training trials) and the Mean statistic to give a measure of average proximity (for probe trials; Gallagher et al. 1993. Behav. Neurosci.: 618–626). See also the chapter The Morris water maze test in the EthoVision XT 19 Application Manual for the exact procedure. You can also divide the maze into quadrants to give a more fine-grained analysis of behavior during the trial. - In a study of territorial behavior, the resident's territory could be defined as a zone. You can then measure how close the intruder comes to that area. One example of how you can use Distance to zone with Include if in zone selected: - In a study of anxiety, one could define an entire open field as a zone, and then use Distance to zone to measure to what extent animals dare to move away from the wall. More generally, if you are interested in the distance between a subject and the edge of an open field or the border of an Elevated plus maze, you can select the complete arena as a zone. Definition The shortest distance between a subject's body point and one or more points. The calculation of this variable is performed in two steps: - The coordinates of the defined point(s) and the body point(s) for the current sample are found. - The distance in a straight line between the coordinates is calculated. If your experiment is set to Only center-point detection or Color marker tracking, the body point options are not available. Calculations are based on the center point. How to Specify Distance to Point - Click the Add button next to Distance to point and click the Distance to point tab. - Under To following points, select the points you want to consider for the calculation. For example, if you want to calculate the mean distance to Cue 1, select Cue 1. By default, Arena (that is, the center of the Arena) is selected. If you have chosen two or more points, select how the points should be analyzed: - For each of the selected points: Points are analyzed separately. - Shortest distance to any points: For each sample, EthoVision XT chooses the point that is currently closest to the body point(s) you have chosen, and uses the resulting distances for calculating the statistics. - Under From following body points, select the points you want to consider for the calculation. For example, select Nose-point if you want to analyze the distance between the nose-point and a specific point. By default, Center-point is selected. If you have chosen two or more body points, select one of the following from the list: - For each of the selected points: Statistics are calculated for each point separately. - Shortest distance to any point: For each sample, EthoVision XT chooses the body point that is currently closest to the point, and uses the resulting distances for calculating the statistics. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If your experiment is set to Only center-point detection or Color marker tracking, the body point options are not available. Calculations are based on the center point. - The center point of a zone can lie outside the zone itself. This occurs when the zone is ring-shaped or very asymmetrical. Applications Below are two examples of how Distance to point is of particular use in studies of spatial orientation: - When analyzing the flight behavior of an insect in an odor plume, the plume itself can be defined as a zone, while the upwind odor source is regarded as a point. Using Distance to point, you can measure the insect's progress towards the source at any moment in time. - In an open field test, using the center point of the central area of the arena, Distance to point can be used to measure how far the animal ventured into the central area. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Edit the Tracks - Auto Swap Nose-Tail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-auto-swap-nose-tail Chapter: EthoVision XT Auto Swap Nose-Tail Finding and Swapping Intervals - In the Auto Swap Nose-Tail window, under Find Interval, do the following: - From the Find nose-tail swaps in the track list, select the arena and the subject you want to search. For single-arena setups and single-subject setups, only one arena/subject is available, so go to the next step. - In the Turning angle threshold field, enter the threshold angle. The first sample with a change in orientation of the nose-tail base vector larger than this threshold is considered for swapping. - Click the Next >> button. Result: A number of samples are highlighted (selected). Under Find Interval, the following times are displayed: - Start sample found at: The time of the sample in the track with turning angle greater than the threshold relative to the previous sample. It is the start of the interval of samples considered for swapping. - Stop sample found at: The time of the sample immediately preceding the sample with turning angle greater than the threshold. It is the end of the interval of samples considered for swapping. - Do one of the following: - If the first sample of the selected interval in your track is oriented correctly, click the Next >> button until the first sample of the new interval is not oriented correctly. - If the first sample of the selected interval is not oriented correctly, this is the start of the interval of samples to be swapped. Proceed to step 4. - Once you have selected an interval of samples that does not match the orientation of the animal, do one of the following: - If you want to let EthoVision XT swap the intervals of samples throughout the track based on the above criteria, select the option Automatically swap the current selection and swapped intervals in the remainder of the track, and click the Swap button in the Auto Swap Nose-Tail window. - If you only want to swap the selected interval, make sure that the option above is cleared and click the Swap button in the Auto Swap Nose-Tail window. Result: The nose-point and tail-base in the selected intervals are swapped. - Do one of the following: - If you want to search for the next interval to be swapped, go back to step 3. - If the track contains only samples oriented correctly, click the Close button. To swap nose-point and tail-base in another arena, select that arena from the appropriate list. Notes - When you click Next>> for the first time, the interval from the start of the track (0:00:00.000) to the first change in the nose-tail vector orientation greater than the threshold is displayed. If you click the Next>> button more times, other intervals are displayed depending on where in the track other significant turns are found. - Select the Automatic swap option only if you are confident that the angle threshold specified results in identifying the correct intervals to be swapped. This usually happens when you have checked the intervals yourself a few times. - If you select points outside the Auto Swap Nose-Tail window, the Start sample found at and Stop sample found at fields show . In this case the Automatic swap option is not available. Click the < Samples List. - In the Samples List window, click a cell corresponding to the first sample of the range. The line is highlighted in green. Tip: Clicking a row in the Sample List does not move the video to that position. Double-click that row to move the video, so you can see where the subject is at the time you have just selected. - Press and hold the left mouse button, and drag down to the last sample you want to select. Release the button when ready. Right-click one of the rows highlighted in green and select Jump to Time to display the selected samples in the plot. Tip: The time highlighted in blue always corresponds to the current video image. The current sample is highlighted with a white fill and orange outline. Notes - To select samples for all subjects in the arena, click the cell in the Time column for the first sample of the range, then drag down to the last sample you want to select. - You can also select samples for two or more subjects that are adjacent in the Sample List (e.g. Subject 1 and 2). Click the first sample for Subject 1, and drag down to the last sample you want to select for Subject 2. --- ## EthoVision XT 19 - Edit the Tracks - Delete, Move, and Interpolate Points URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-delete-move-and-interpolate-points Chapter: EthoVision XT Delete, Move, and Interpolate Points Delete Points Aim To remove a sample (or some of the points of your sample) from your data set. Deleting points means that they are set to missing. Important: If you delete a point, you cannot recover the original coordinates, you can only interpolate it. If you delete an entire sample, the surface area is also lost. If you are not sure about the consequences of setting points to missing, save the edits first. You can always return to your original track data. Procedure - Select the sample (or range) that contains the points you want to set to missing. - Do one or more of the following: - If your track contains only center-points, click the Set to missing button on the toolbar or press Ctrl+Del. - If your data also contains nose-point and tail-base, to set all points to missing, click the Set to missing button or press Ctrl+Del. - To set only nose-points to missing, click the Set nosepoint to missing button or press Ctrl+Shift+M. - To set only tail-base points to missing, click the Set tailbase to missing button or press Ctrl+M. What "Set To Missing" Means - Missing points are shown as linear interpolations between the non-missing points of their own type. However, their coordinates are not in the track data and are not subject to analysis. For example, if sample n is missing, the distance moved between the two non-missing points n–1 and n+1 is given by the straight line connecting the two points of the same type (nose-point to nose-point, etc.). - In the Samples List, the points' X,Y coordinates are removed. If you set the sample to missing, the surface area is also removed. Missing values are indicated by "-". - If you set a nose-point to missing, the Head direction value for that sample is removed. Move Points Aim To change the X,Y coordinates of a point on the track plot. Procedure - Hover the mouse on the point you want to move. The mouse cursor changes to a four-headed arrow. - Press and hold the left mouse button and drag to the position you require. - Release the mouse button. The point is moved to the new position and its X,Y coordinates are updated in the Samples List. - To de-select the point, press Esc or click on the background image. Notes - If you move a missing sample, this becomes non-missing and therefore included in your data. - You cannot move a sample outside the arena. - If your experiment is set to Center-point, nose-point and tail-base detection, a sample is made of three points (no matter whether those are actual data points or missing). You cannot move a sample as a whole; you must move each point separately (center-, nose-, and tail-base points). - If you move the nose-point, the corresponding value of Head direction for that sample is unchanged. Interpolate Points Aim To replace one or more missing points (or samples) or points clearly misplaced with points calculated on the basis of the position of the first previous and next non-missing points. If your experiment is set to Center-point, nose-point and tail-base detection, you can choose between two types of interpolation: interpolate all selected body points or the center-points only. Procedure - If you want to interpolate non-missing points that are clearly misplaced, set them first to missing (see Delete Points). In other cases go to step 2. - Select the missing sample (or the range of samples) you want to interpolate. Tip: To select missing samples automatically, click the Auto Select button on the toolbar, then choose Missing samples. Click the Next>> button to move the video to the next missing sample. - Click one of the following buttons on the toolbar: - Interpolate the selection (or press Ctrl+I): Click this button if you want to interpolate all the body points of the selected samples. - Interpolate center points (or press Ctrl+Shift+I): Click this button if you want to interpolate the center points for the selected samples, and leave the nose-point and tail-base as they are currently (no matter whether missing or not). If your experiment is set to Only center-point detection, only the first button is available. Click that button to interpolate the center-points. - A message appears after you have clicked the interpolate buttons, informing you that EthoVision XT has extended the range of samples to be interpolated, if needed. Click Yes if you want to continue. If you are not sure about the result of the interpolation, click Cancel. Notes - The interpolated points are highlighted in the track plot and get the color of non-missing points. In the Samples List, the points obtain X,Y coordinates. - The subject area is interpolated linearly. - When you visualize the data, missing points are shown as linear interpolation between the first previous and next valid points. However, their coordinates are not calculated (you can check this in the Samples List). This means that missing points are not actually in the data set. If you want to include them in your data set, you must first interpolate them. - In some cases interpolation may result in points being located outside the arena. In those cases, they are automatically set to missing. This could be the reason why you still see missing points after you have carried out interpolation. - If you are not sure whether interpolation gives good results, save the edits first. - If you interpolate the nose- and tail-base points, the Head direction line is recalculated as the prolongation of the segment that joins the center-point and the nose-point after interpolation. This has consequences on all variables based on the Head direction line: Head direction, Head directed to zone, and Turn angle and Angular velocity when they are based on head direction. More Information About Interpolation Interpolation Range To interpolate points, EthoVision XT needs complete samples immediately before and after the sample to be interpolated. "Complete samples" means that: - For Only center-point detection, the center point of the adjacent samples must not be missing. - For Center-point, nose-point and tail-base detection: - If you chose Interpolate the selection on the toolbar, all three points of the adjacent samples must not be missing. - If you chose Interpolate center points on the toolbar, the center-point of the adjacent samples must not be missing. If the samples adjacent to the selected range are not complete, EthoVision XT searches for the first complete sample before and after that sample (or range). Therefore, all incomplete samples in the middle are included in the range to interpolate. Example: The missing samples 5 and 6 have been selected for interpolation. Samples 4 and 7 are adjacent to the range, but not complete: sample 4 lacks the nose-point, while sample 7 lacks the tail-base point. - If you choose to interpolate the entire selection, EthoVision XT needs the coordinates of the three points for both adjacent samples in order to calculate the coordinates of the three points of samples 5 and 6. Therefore, samples 4 and 7 are not used. Instead, the complete samples 3 and 8 are used as adjacent samples, so the interpolating range is extended to samples 4 and 7. The coordinates of the missing points of samples 4 to 7 are calculated. --- ## EthoVision XT 19 - Edit the Tracks - Edit the Tracks URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-edit-the-tracks Chapter: EthoVision XT Edit the Tracks Introduction to Editing Tracks Why Edit Data? Correcting Tracking Errors Sometimes EthoVision XT tracks a reflection instead of the subject, or confuses the nose-point and tail-base. If that occurs, you can correct such errors in the Track Editor screen. Examples - Reflections in a water maze. EthoVision XT tracks accidentally a reflection next to the maze's border. There are "spikes" in the resulting track. Make sure that light is not directed to the water surface. - Nose-tail base swaps. In experiments set to nose-tail base tracking, the nose-point could be detected as the tail-base, and vice versa. In the last sample of the following track, the two body points are inverted. The Track Editor offers some ways to correct such swaps. Try out the Deep Learning tracking technique, which is superior at finding the subject's nose-point. Notes - The Edit Tracks function in EthoVision XT is only intended for minor changes of a few points. If you have many errors, there is a problem with your experimental set-up, trial control or detection settings, and you should correct those problems rather than try to manipulate the raw data. For example, if EthoVision XT tracks the arm of the operator who released the animal in the water maze, do one or both of the following: - In the Trial Control Settings, select to start tracking a few seconds after the subject is detected in the arena. - In the Detection Settings, set a maximum subject size. Important Definitions in Track Editing Sample vs. Body Point A sample is the set of coordinates found at any sampling time. This means that: - If your experiment is set to Only center-point detection, a sample is the subject's center point (one pair of X, Y coordinates). - If your experiment is set to Center-point, nose-point and tail-base detection, a sample includes the center-point, nose-point and tail-base point (three pairs of X, Y coordinates). Within a sample, one or more points can be missing. Missing points are shown in a different color. Sample List The Sample List is the list of coordinates of the subject's body points and surface area, for each sample time. It is the actual raw data used in all the subsequent analysis functions (from Track Smoothing to Results). To access the Sample List window, choose Acquisition > Edit Tracks. If the Sample List is not shown, choose Show/Hide > Sample List. When you select samples in the Sample List, selected samples are highlighted in green, while the sample time that corresponds to the current video image is the one shown in blue in the Time column. These two selections are independent of each other, meaning that the video image may show a sample time that is not within the range selected. Save Edits You can save a copy of the track that includes the last edits. If you make changes after clicking Save, you can always go back to that copy if you are not satisfied with those changes. Customize Your Screen Before Editing Visualize the Tracks in the Track Editor Screen To access the Track Editor screen, choose Acquisition > Edit Tracks, or in the Experiment Explorer, under Acquisition click Track Editor. In the track editing screen you can view the following objects: - A. The track area, where you can view: - The background. This can be of uniform color, the captured image of the arenas from the Arena Settings, or the content of the video file. - Arenas and zones as overlay objects. - Tracks (samples and paths). - B. The toolbar, which contains tools for: - Selecting the trials to be edited. - Managing track edits and reverting to the original data if needed. - Selecting and editing data points. - The Show/Hide button for choosing the elements to display. - C. The Playback Control window. - D. The Samples List window, listing the coordinates of the data points and the surface area of the subjects tracked. - The Time column shows the time elapsed since the start of the trial. If data recording started after the start of the trial or ended before the end of the trial, the Samples List shows asterisks (*) for the samples not collected before the start and after the end of data recording. - The current time (also shown in the Playback Control window) is marked in blue. - Missing points are listed with coordinates and surface area '-'. - E. The Track Plot Settings pane, for customizing the tracks and body points. To display the Playback Control window, the Samples List and the Track Plot Settings pane, click the Show/Hide button on the toolbar and make sure they are selected. To visualize the track you want to edit, select the trial name from the list on the toolbar. You can visualize one trial at a time. To switch from one trial to the previous or next, click the Previous Trial button or the Next Trial button on the toolbar, respectively. To play back tracks, use the buttons in the Playback Control window. Set the playback speed you require. To visualize the whole tracks, clear the options under Filter in the Track Plot Settings pane and click the Jump to End button in the Playback Control window. Colors In the Colors tab of the Track Plot Settings pane, by default, Subject is selected under Level, that is, the track color does not change between tracks of the same subject. If you select Track, the color of tracks can change between tracks, according to the value of the variable selected under Variable for those tracks. Improve the Readability of the Tracks Before Editing The following options help you locate and edit the tracks more easily. Zoom In and Out the Track Plots Click the Zoom In button (Ctrl+.) or the Zoom Out button (Ctrl+.) on the toolbar, respectively. If the data points are out of view after zooming in, use the scrollbars to find them. Visualize Part of the Track In the Track Plot Settings pane, click the Show/Hide tab, and under Filter select Last and enter the time interval. This way, only the last few seconds are visualized before the current sample. The current sample is highlighted in blue in the Samples List. Visualize One Sample Every N-th This option is handy when you edit tracks with high sample rates or of slow-moving animals. To show one sample every n-th, click the Show/Hide tab, and under Filter select Every and enter n in the corresponding field. - If you select 0, only the current sample point is shown. - If you select 1, this is the same as not selecting the Last option (all samples are displayed). Hide the Tracks You Do Not Need When two or more subjects move in the same arena, the tracks become a dense population of points. If you edit the track of subject A, you can hide the tracks of the other subject B which you do not edit at that time. To hide tracks of subjects, in the Track Plot Settings pane click the Show/Hide tab. Under Subjects, clear the box corresponding to those subjects. Hide Unnecessary Track Features To hide unnecessary features like body points and connectors, in the Track Plot Settings pane click the Show/Hide tab. Under Features, clear the corresponding box for Sample or Trail. - The nose-point and the tail-base point are not selected by default. - What you choose under Features also determines which body points are shown in the Sample List. Adjust the Line Thickness and Dot Size Sometimes dots are too small and therefore scarcely visible, or too large and make the tracks difficult to edit. The tracks may be hardly visible especially when using high resolution video. In the Track Plot Settings pane click the Show/Hide tab. Under Features, adjust the following: - Line thickness. Adjust the thickness of the trails and the segments joining the body points (Connectors). - Dot size. Adjust the size of the body points visualized. Customize the Missing Sample Points Missing sample points are always visualized in the track plot. You can change the color of missing points to distinguish them more easily from the actual data. The current color for missing points is indicated next to Missing Samples Color at the bottom of the Colors tab in the Track Plot Settings pane. To change the color for missing points, click this button and select the new color in the Color window. - Remember that within a sample, nose-point and tail-base can be missing independently. For example, the nose-point may be missing, while the corresponding tail-base may not. However, if the center-point is missing, then the other two points are too. - If the experiment is set to Only center-point detection or Color marker tracking, the term sample coincides with the only point (center). --- ## EthoVision XT 19 - Edit the Tracks - Interpolating Points URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-interpolating-points Chapter: EthoVision XT Interpolating Points How the Center Point Is Interpolated If you interpolate only the center points, EthoVision XT needs the coordinates of the center points for the adjacent samples in order to calculate the coordinates of the center points 5 and 6. Samples 4 and 7 are used because they are the first previous and next samples with valid center points, respectively. The interpolating range is not extended. The coordinates of the missing center points, not nose point and tail-base points, of samples 5 and 6 are calculated. The center points of the selected samples are a linear interpolation between the first previous non-missing center point and the first next non-missing center point found around the interpolating (expanded) range. If your track contains nose point and tail base, interpolation of center points is independent of whether you choose to also interpolate nose point and tail base. In any case, center points are interpolated first. How the Nose Point and Tail-Base Point Are Interpolated Nose points and tail-base points are always interpolated after the center points have been found, and their interpolation is dependent on the orientation of the non-missing nose points and non-missing tail-base points immediately preceding and following those missing samples, respectively. Before interpolation, the missing points are indicated as a linear interpolation between the first previous and the first next non-missing points of their type. The direction of movement does not play any role in interpolation. Consider the following example with three missing samples. First, center points are linearly interpolated. Second, for the two adjacent non-missing samples, the program determines: - The length of the segment joining the center and the nose (or tail-base) points. - The angle formed by this segment and the horizontal x-axis generating from the center point (this angle can be either positive or negative depending on whether the segment lies above or below the axis). Third, the program calculates the interpolated values of segment length and angle for the missing points, using linear interpolation of the values obtained in the previous step. For example: - If the length of the center-nose point segment for the two adjacent samples is 50 and 10 mm respectively, then the length of the three segments joining the interpolated nose points and their center points will be 40, 30, and 20 mm respectively. - If the orientation of the center-nose point segment for the two adjacent samples is 90 and -10 degrees respectively, then the orientation of the three segments joining the interpolated nose points and their center points will be 65, 40, and 15 degrees respectively. The second and third steps are repeated to interpolate the tail-base points. Interpolating Points at the Beginning or End of the Track If the range of missing points to interpolate is at the beginning or the end of the track, the missing points are not interpolated. This is also the case when you want to interpolate nose or tail-base points at the beginning or end of the track and the corresponding center points are non-missing. Synchronize Video and Tracks Aim To correct the delay between video image and tracks in the various visualizations: Track Editor, Track Visualization, and Integrated Visualization. Note: Normally you do not need to edit the offset between video and tracks, because this is calculated by the software. Follow the procedure below if you notice that the tracks are lagging behind the video. Prerequisites You acquired data using the method Live Tracking and Save Video. Procedure See Troubleshooting: Data Visualization > There Seems to Be a Delay Between Video and Track. Manage Your Edits Saving the Track Edits Aim To save edits done up to that time. If you make more changes after saving and are not satisfied with those changes, you can always recover the edits made at the point of Save. Note: This and the following topics apply to editing tracks and manually scored behaviors. Example: You want to interpolate points but are not sure whether the result is satisfactory. Click Save to create a copy of the track with the current edits, then do the interpolation: - If the result of interpolation is good, click Save again. This replaces the previous track edits. - If the result is not good, you can revert to the data of the last Save by clicking Undo. What Is the Difference Between Saving the Experiment and Saving in the Track Editor? Save Experiment: To save your edited tracks at any time, choose File > Save Experiment or press Ctrl+S. However, once you have saved the data, you cannot revert to the first edit. In other words, you cannot undo any save action. However, you can always return to your original track data. Save in the Track Editor: With Save in the Track Editor you can revert to the previous set of changes. You do so with the Undo action. This is useful when you want to make sure you can recover the data after carrying out some editing. Important: The Save action persists until you close the experiment. If you save, then make further changes to the data and close the experiment, all changes are saved, but when you re-open the experiment you cannot revert to the Save point. Notes - Every time you click Save, the new copy replaces the previous one. This means that you can always keep only one copy of edited data. - The original (unedited) data are always stored in your experiment. To revert to the original tracks and discard all changes, click the Undo All button on the toolbar. - Auto Save in EthoVision XT works like a normal Save command. Therefore, if an auto save action occurs, all changes made so far to the currently edited trial are applied. However, if you make further changes and an auto save action occurs, you can always revert to the saved copy that was made before the auto save action. To alter your auto save settings, choose File > Preferences > Auto Save. --- ## EthoVision XT 19 - Edit the Tracks - NTP Configuration and Track Editing URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-ntp-configuration-and-track-editing Chapter: EthoVision XT NTP Configuration and Track Editing Verifying NTP Status - Click the NTP Status tab. You should see the green line indicating that the service is running correctly. - Click the Statistic tab in the NTP Time Server Monitor window. A few minutes later you can view the statistics of the NTP synchronization. - To monitor the offset between the server and the client, under Available Logfiles click the browse button and in the folder C:\NTP\ETC\ select the loop statistics file. Typically, one file is generated per day. Click that file in the list to view the time-offset plot (in red). In most cases the offset, that is the difference in the clock time between the computers, is within one millisecond. The NTP.CONF File The ntp.conf file is a text file which contains the lines as shown below. You can open the file with the Windows Notepad. Make sure that the IP address shown in bold is the IP address of the NTP Time Server, that is, your DSI-computer. # NTP Network Time Protocol #IMPORTANT: WITH W7 MAKE SURE THE MONITOR RUNS AS ADMIN # SET THIS IN THE PROPERTIES OF THE SHORTCUT ignore_bigtimestep yes # Use drift file driftfile "C:\NTP\etc\ntp.drift" # your local system clock, could be used as a backup server 123.456.78.901 minpoll 4 maxpoll 4 burst iburst # generate statistics enable stats statsdir "c:\NTP\etc" statistics loopstats # End of generated ntp.conf --- Please edit this to suit your needs Notes - When the two computers are in the same network domain, the domain administrator can use his/her existing account. However it is always possible to create a separate account as described above. The account must have the rights to start the NTP Service. See Also - Import profiles for DSI physiological data --- ## EthoVision XT 19 - Edit the Tracks - Save the Track Edits URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-save-the-track-edits Chapter: EthoVision XT Save the Track Edits Aim To create a copy of your tracks and manually scored behaviors that serves as a restore point. In the case you make further changes and are not satisfied with them, you can revert to the restore point. Prerequisites - You have acquired at least one trial. - Open the Track Editor (Acquisition > Edit Tracks). Procedure - Edit the tracks. - When you want to save the changes, click the Save button on the toolbar. - Continue with editing. - If you are not satisfied with the changes, click Undo to return to the saved copy. Notes - The tracks that are visualized and analyzed always include the changes you made. If you want to visualize or analyze the original data, click the Undo All button on the toolbar. However, keep in mind that you will lose the edits. Source: EthoVision XT 19 Help - Edit the Tracks, Noldus Information Technology --- ## EthoVision XT 19 - Edit the Tracks - Select Samples Automatically URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-select-samples-automatically Chapter: EthoVision XT Select Samples Automatically Aim To easily find: - Missing points. - Samples separated by a distance greater or smaller than a specific value. For example, to find points lying far from the normal path. - Samples with a surface area greater or smaller than a specific value. For example, to find all points where the detected blob is too large to be the actual subject. - Samples with the distance between nose-point and tail-base greater or smaller than a specific value. To Access This Function Choose Acquisition > Edit Tracks, and select the trial you want to view. Procedure - On the toolbar, click the Auto Select button. - In the Auto Select Samples window, under Select, choose the option you require. For more information, see the notes below. - Under Scope, select the arena you want to search. If you want to find samples in all arenas, select All Arenas. Select the subject you want to search. If you want to find samples in all subjects, select All Subjects. - Click Select All. The samples matching the criterion are highlighted in the track plot. In the Samples List, the corresponding rows are highlighted in green. - If you chose Missing Samples in step 2, click the Next >> and < and < does not result in complementary selections. Some samples may be selected in both cases. Tip: To remove outliers, for example data points resulting from detection of reflections in a water maze, select > and enter a value of distance. This value must be greater than a realistic estimate of the maximal distance that the subject could move between two consecutive samples. Note that this value also depends on the sample rate. The higher the sample rate, the shorter the distance moved by the subject between two consecutive samples. Next, use Delete Points and then Interpolate Points to replace the outliers. Surface Area For this option, specify the value in the measurement unit selected in the Experiment Settings. Nose-Tailbase Length This is only available if your experiment is set to Center-point, nose-point and tail-base detection. Nose-tailbase length is the total length of the segments between nose-point and center-point, and that between center-point and tail-base point. Restrict to Samples Visible in Plot Select this option if you want to select only the samples that match the Select criterion and that are currently displayed in the track plot. The other samples that match the criterion but are not displayed are not selected. Note: If you select this option and then play back the track, the samples that are not currently visualized but that match the selection criterion under Select are not selected. To have them selected, pause the video and click Select All once again. To Deselect Samples Do one of the following: - Press Esc. - Click anywhere on the background image that is not a point. - Right-click anywhere on the background image. Swap Subjects and Body Points What Do You Want to Do? Swap subjects: - Swap subjects - Prepare the data in multi-subject trials Swap body points: - Swap nose-point and tail-base - Swap nose-point and tail-base point manually - Swap nose-point and tail-base point automatically Swap Subjects Aim To exchange the identities of two subjects within one sample (or range of samples, or the entire track), after checking that these were assigned incorrectly by EthoVision XT. An example of subject identity swap: before the swap, Subject 1 has a yellow track and Subject 2 has a red track. At the moment of the swap, the mouse with the yellow track becomes Subject 2 and the mouse with the red track becomes Subject 1. To correct the subject identity swap, swap the subjects for all samples beginning from the moment of the swap up to a new swap, if present, where subjects are labeled correctly again. Notes: - If a large number of samples contain body points assigned to the wrong subject, it may mean that the detection settings defined to discriminate between subjects are not optimal, or that you need to improve the lighting or the color marking of your setup. - You can click Save on the toolbar so that if you are editing many swaps and make a mistake, you do not lose your previous edits. See Saving the Track Edits. Procedure - If you work with multiple arenas, choose first the arena in the Samples List. - Play the track until you find samples with wrongly-assigned subjects. Tip: Play frame-by-frame to position the video when the first samples are swapped. - Select the sample (or range of samples) in which you want to swap the subjects. In the Samples List, double-click the time value highlighted in blue, then drag to select the rows corresponding to all the samples to swap. The last row selected should be immediately before the next swap where body points are assigned correctly again. Important: If you drag on the Time column, all subjects in the trial are selected. If you have more than two subjects (for example, three subjects and you want to swap Subject 1 and 3), do not drag in the Time column. Instead, select the cells of one of the two subjects to swap. In the next step you will be asked to select the other subject. - Click the Swap Subjects button on the toolbar, or press D. - If you have more than two subjects, the Swap Subject window appears. Select Swap Selected Samples, select the second subject of the pair you want to swap, then click Apply. --- ## EthoVision XT 19 - Edit the Tracks - Swap Nose-Point and Tail-Base URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-swap-nose-point-and-tail-base Chapter: EthoVision XT Swap Nose-Point and Tail-Base Aim To exchange the nose-point and the tail-base within a sample (or range of), after checking that these were assigned incorrectly by EthoVision XT. In the example below, the nose-point and the tail-base point are assigned incorrectly (left). The Swap action puts the nose-point and the tail-base point back in the correct place. To check that nose-point and tail-base were mistakenly exchanged, choose Analysis > Results > Integrated Visualization. Play back the tracks with the video on the background. Check that the nose-point and tail-base do correspond to the actual orientation of the subject. Procedure Choose Acquisition > Edit Tracks. Then choose one of the two options: - Swap nose-point and tail-base point manually. Look for the samples with exchanged nose-point and tail-base, and give the Swap command for those samples. - Swap nose-point and tail-base point automatically. Define a criterion for automatic detection of changes in orientation of the nose-point and tail-base. EthoVision XT searches your tracks for the samples where a sudden change in orientation has occurred. It is up to you to swap nose-point and tail-base for those samples. Notes - By selecting the tracking methods Rodents / For Occlusions or Adult Fish / For Occlusions, you can minimize the occurrence of nose-tail swaps. However, this method requires much processor load, so make sure you do not miss samples. - If a large number of samples contain wrongly-assigned nose-point and tail-base, it may mean that the detection settings for nose-point and tail-base detection are not optimal, or that you need to improve the lighting or other settings of your setup. - You can click Save on the toolbar so that if you are editing many swaps and make a mistake, you do not lose your edits. - When you swap nose- and tail-base points, the Head Direction line is recalculated too. This influences the calculation of Head Direction, Head Directed to Zone, and Turn Angle and Angular Velocity when they are based on Head Direction. Swap Nose-Point and Tail-Base Point Manually Aim To correct body point swaps that may have occurred when tracking the nose-point and the tail-base point. Procedure - Play the track until you find samples with wrongly-assigned nose-point and tail-base. Choose Analysis > Results > Integrated Visualization. Play back the tracks with the video on the background. Check that the nose-point and tail-base do correspond to the actual orientation of the subject. - Select the sample (or range of) in which you want to swap the nose-point and tail-base. The selected samples are highlighted. - Click the Swap Nose and Tail button on the toolbar, or press the W key. The nose-point and tail-base within each sample in the selection are swapped. In the Samples List, the coordinates are swapped between Nose-point and Tail-base for those samples. Notes - When you swap nose- and tail-base points, the Head Direction line is recalculated as the prolongation of the segment joining the center-point and the tail-base point. This influences the calculation of Head Direction, Head Directed to Zone, and Turn Angle and Angular Velocity when they are based on Head Direction. Swap Nose-Point and Tail-Base Point Automatically With automatic swapping, EthoVision looks for the samples where the subject made a turn exceeding a user-specified threshold relative to the previous sample. These turns are interpreted as nose-point and tail-base being incorrectly assigned. You can then select those samples and let EthoVision exchange the corresponding nose-point and tail-base. Use this method when a large number of consecutive samples have body points wrongly assigned. What Does 'Turn' Mean Here? Turn refers to the change in orientation of the nose-tail base vector. The nose-tail base vector is the vector connecting the nose-point and the tail-base point within a sample. With automatic swapping, if the change in the vector's direction from sample n to n+1 is larger than the angle you specify, the sample n+1 is considered for swapping. Then it is up to you to decide whether to swap the points. If the nose-point or the tail-base is missing, the nose-tail base vector is the vector connecting the center with the other point. If both nose- and tail-base points are missing, the sample is not considered for swapping. If samples following n+1 have a vector's turn lower than the specified threshold, they too are assumed to have nose-point and tail-base detected wrongly. Therefore, they are included in the swapping interval. Example: A - the body points are assigned correctly. B - the nose-tail base vector makes a turn greater than the specified threshold (for example, 150°). This is the start of the swapping interval. C - a new significant turn of the nose-tail base vector is found. Samples between B and C (not included) are swapped. The samples after C are considered correct, until a new significant turn is found. Procedure - Position the track at the beginning and check whether the first sample in your track is orientated correctly. If you have tracked data from a video file, make sure that the video file is on the background. If you have tracked live, make sure that the nose-tail base orientation matched the direction of movement. - Click the Auto Swap button on the toolbar, or press Ctrl+F. --- ## EthoVision XT 19 - Edit the Tracks - Swap Subjects URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-edit-the-tracks-swap-subjects Chapter: EthoVision XT Swap Subjects The subjects in the selection are swapped. You can check this in the Samples List, where the coordinates and the area are swapped between subjects and for the rows selected. Notes - To search for subject swaps, plot the dependent variable Distance Moved in the Integrated Visualization. The peaks in the plot appearing for two subjects indicate a quick displacement of the body points, that is a suspect subject swap. - To quickly swap two subjects for just one sample, drag the mouse around the subject's body points in the video window. Make sure that the Track Editor only displays one sample. Then click the Swap Subjects button. - In the Time column of the Samples List, the cell highlighted in blue corresponds to the sample highlighted in white in the video window. - If you select several samples and choose to have one sample every n-th visualized, you also swap the body points in the selected range that are not visualized. - In the Swap Subjects window, select Swap All Samples to swap the subjects for the entire track length. Prepare the Data in Multi-Subject Trials Aim To fix potential identity swaps after tracking multiple subjects with the Deep Learning body point detection technique. This Topic Applies To Experiments set as follows (see Experiment Settings): - Number of Subjects per Arena: 2. - Tracked Features: Center-point, nose-point and tail-base detection. - Body Point Detection Technique: Deep learning. Background Information When EthoVision XT tracks unmarked subjects, there is a chance that subject identity is swapped. This could occur for example when two subjects come into contact with each other. In the example below, the dotted line is the true trajectory of the two subjects. After the crossing, the subject orange is labeled as blue, and blue is labeled as orange. To reduce or entirely remove identity swaps, when using Deep Learning, the software works in two steps: - Step 1 (Tracking) - The software finds and tracks the subjects' body points. - Step 2 (Data Set Preparation) - The software reviews the tracks and sorts them based on the visual differences between the subjects. This step is carried out after tracking, and automatically when you calculate or visualize the data. As a result, the occurrence of identity swaps is reduced. Recognition of individuals is based on the differences in the appearance of the subjects' fur. For how to mark your subjects, see the recommendations in Deep Learning: Requirements. Procedure The Data Set Preparation is done automatically the first time that you calculate the statistics or visualize the tracks. You can also run this procedure manually in the Track Editor. - Choose Acquisition > Edit Tracks. - Select one trial from the list on the toolbar that is marked with (not yet prepared). - Click Prepare Data. - Wait until the trial name shows "(ready)". Depending on a few factors, including the length of the video and its resolution, this process may take some time. - You can now edit the tracks or run analysis. Error Messages If for any reason the Data Set Preparation procedure fails for at least one trial or arena, the Data Preparation Report shows in which trial and arena that happened, and what the possible causes could be. - Not enough data points available to reliably train the network. This occurs if the trial was short, or the two animals were separated for too short a time. Another possibility is that the animals were separated, but at least one of them was curled up for a long time. In all those cases the software cannot create a high number of reliable images of the two subjects. In general, we recommend acquiring a trial of at least five minutes, at the maximum sample rate (25 samples/s or higher). Although the message may sound pessimistic, there are cases when the individual discrimination worked well. For example, when the visual difference between the two subjects is very clear, a relatively small number of video frames may still be sufficient to create a reliable network for individual discrimination. Check the identity labels of the two animals and edit the tracks when necessary. - No data points available to train the network. This could occur when tracking was very poor because of poor detection (e.g. not enough contrast, or presence of reflections) or because the two subjects were in contact for the entire duration of the trial. In such a situation there are no data points at all available for training the network; individual discrimination fails, no matter how long the trial lasted. We advise checking the lighting conditions, the contrast between the subjects and the background, and repeating the trial. - The subjects look too similar. This occurs when the two subjects are not marked and there is no significant difference in their visual appearance. Check the suggestions about marking animals in Deep Learning: Requirements > Individual Marking (for two-subject tracking). Notes - The Data Set Preparation may take some time, depending on the length of the video and the power of the GPU. - The Data Set Preparation is not applied to trials where the subjects are tracked with the Contour-based technique for body point detection. For the difference between Contour-based and Deep Learning, see Body Point Detection Technique. - The trial where data preparation failed is still added to your results table. However, there may be significant identity swaps. There are two options: - Open the trial in the Track Editor and fix the identity swaps. See Swap Subjects. - Exclude the problematic trials in your Data Profile. See Filter Tracks. - Check that you have the latest version of the driver for the secondary graphics card, which does most of the work in deep learning-based tracking. See Also - Advanced Detection Settings for Tracking Multiple Unmarked Subjects - Introduction to Editing Tracks - Swap Subjects - Deep Learning: Basics - Deep Learning: Requirements --- ## EthoVision XT 19 - Ethernet Board Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethernet-board-settings Chapter: EthoVision XT Ethernet Board Aim: To allow the camera network traffic through the firewall. Procedure By following this procedure, you exempt the network adapter connected to the camera(s) from the firewall. You may need to do this if EthoVision XT does not show the live camera image, or EthoVision XT shows a message like Device unplugged. - Do one of the following: - From the Windows Start menu, select Settings. Next, select Privacy & Security > Windows Security > Firewall & Network Protection, then click Advanced Settings. - In the Windows Control Panel, select Network and Internet > Network and Sharing Center > Windows Defender Firewall, then click Advanced Settings. - At the bottom of the Overview middle panel click Windows Defender Firewall Properties. - In the new window that opens, click the Domain Profile tab. - Next to Protected network connections, click the Customize button. - De-select the network adapters that are used only for the camera(s), and click OK. - Repeat the steps 4-6 above on the Private Profile and Public Profile tabs. - Click Close. See Also - Connect the GigE Camera to the PC - Configure the Digital Camera - Using Multiple GigE Cameras Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - EthoVision XT and Quality Assurance - Assign Rights to Users URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethovision-xt-and-quality-assurance-assign-rights-to-users Chapter: EthoVision XT Assign Rights to Users Prerequisites - You have been assigned User Management rights in EthoVision XT. - There is no experiment open. User Roles When you add a new user, you have the option to select one of three predefined roles, each representing a set of rights. However, these rights can be changed at any time. The three initial roles are: - Administrator — With default rights User Management and EthoVision Preferences. - Researcher — With default rights Experiment Management, Experiment Settings, Trial Control Settings, Arena / Trial Control / Detection Settings, Acquisition, Import External Data, Edit Tracks, and Edit Data Profile / Analysis Profile. - Technician — With default rights Arena / Trial Control / Detection Settings, Acquisition, and Import External Data. User Rights - User Management — Gives you the right to add and remove users, and change user rights. - EthoVision Preferences — Gives you the right to change the default experiment folder, the warnings displayed, and the autosave options. - Experiment Management — Gives the right to create new experiments, make and restore backups. - Experiment Settings — Gives the right to set and change Experiment Settings. - Trial Planning — Gives the right to add trials and variables to the Trial list, and to skip trials or arenas within trials, and re-do trials. - Arena / Trial Control / Detection Settings — Gives you the right to create and/or edit Arena Settings, Trial Control Settings, and Detection Settings. - Acquisition — Gives the right to change Acquisition settings and carry out Acquisition. - Import External Data — Gives the right to import external data files. - Edit Tracks — Gives the right to edit tracks. Note: It is likely that your Standard Operating Procedure forbids modifying acquired data. If this is the case, no user should have this right. The original data is always stored in your experiment. - Edit Track Smoothing, Data, Analysis Profiles — Gives the right to smooth tracks, create and edit Data profiles and Analysis profiles. - Delete Trials and Clear Log — Gives you the right to delete trials and delete the Experiment log file. Notes - It is likely that your Standard Operating Procedure forbids modifying acquired data. If this is the case, no user should have this right. By default, this right is disabled for all users. - The right to delete trials and the Experiment log file is useful when you want to create a template experiment. This template experiment, for example, contains default settings as defined in a Standard Operating Procedure, but should not contain test trials and an already filled log file. It is advisable to create a special user for this right. In normal operation under GLP, no user should be able to perform these actions. EthoVision XT Logging Aim With the logging functionality in EthoVision XT, you enable auditing of changes to settings that were made during an experiment. EthoVision XT creates two types of log files: - General Log File — In this Application log, the usage of EthoVision XT by authorized users is registered. - Experiment Log File — One for each experiment, to register the settings made and actions carried out during that experiment. The user, date, and time are logged for each setting and action. Notes - The user can at any time add additional user comments to the Experiment log file. - The log file is tamper-proof. As soon as someone edits it outside EthoVision XT, that is detected and it is logged that the file has been tampered with. The General Log File The General log file is created the moment EthoVision XT is installed. The following actions are logged: - Start and stop of an experiment. - Creation of a new experiment. - Users that are added, user rights that are assigned, and user rights that are modified. - Errors that occurred when opening or closing an experiment. For every action, the user name, date, and time are logged. To View the General Log File - Choose File > GLP Log Files. - In the GLP log window, select General log file. To Export the General Log File - Choose File > GLP Log Files and click the Export button, or in the Experiment Explorer, under Export, click GLP Log. - Select General log file. - Browse to the folder where you want to export the log file to and click OK. Notes - The export format is HTML (*.html). The name of the export file is GLP-EthoVision(n), where n is a progressive number. - You cannot delete the General log file. --- ## EthoVision XT 19 - EthoVision XT and Quality Assurance - Assign Rights to Users URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethovision-xt-and-quality-assurance-assign-rights-to-users-Rdk Chapter: EthoVision XT Assign Rights to Users Prerequisites - You have been assigned User Management rights in EthoVision XT. - There is no experiment open. User Roles When you add a new user, you have the option to select one of three predefined roles, each representing a set of rights. However, these rights can be changed at any time. The three initial roles are: - Administrator — With default rights User Management and EthoVision Preferences. - Researcher — With default rights Experiment Management, Experiment Settings, Trial Control Settings, Arena / Trial Control / Detection Settings, Acquisition, Import External Data, Edit Tracks, Edit Data Profile / Analysis Profile. - Technician — With default rights Arena / Trial Control / Detection Settings, Acquisition, Import External Data. User Rights - User Management — Gives you the right to add and remove users, and change user rights. - EthoVision Preferences — Gives you the right to change the default experiment folder, the warnings displayed, and the autosave options. - Experiment Management — Gives the right to create new experiments, make and restore backups. - Experiment Settings — Gives the right to set and change Experiment Settings. - Trial Planning — Gives the right to add trials and variables to the Trial list, and to skip trials or arenas within trials, and re-do trials. - Arena / Trial Control / Detection Settings — Gives you the right to create and/or edit Arena Settings, Trial Control Settings, and Detection Settings. - Acquisition — Gives the right to change Acquisition settings and carry out Acquisition. - Import External Data — Gives the right to import external data files. - Edit Tracks — Gives the right to edit tracks. Note: It is likely that your Standard Operating Procedure forbids modifying acquired data. If this is the case, no user should have this right. The original data is always stored in your experiment. - Edit Track Smoothing, Data, Analysis Profiles — Gives the right to smooth tracks, create and edit Data profiles and Analysis profiles. - Delete Trials and Clear Log — Gives you the right to delete trials and delete the Experiment log file. Notes - It is likely that your Standard Operating Procedure forbids modifying acquired data. If this is the case, no user should have this right. By default, this right is disabled for all users. - The right to delete trials and the Experiment log file is useful when you want to create a template experiment. This template experiment, for example, contains default settings as defined in a Standard Operating Procedure, but should not contain test trials and an already filled log file. It is advisable to create a special user for this right. In normal operation under GLP, no user should be able to perform these actions. EthoVision XT Logging Aim With the logging functionality in EthoVision XT, you enable auditing of changes to settings that were made during an experiment. EthoVision XT creates two types of log files: - General Log File — In this Application log, the usage of EthoVision XT by authorized users is registered. - Experiment Log File — One for each experiment, to register the settings made and actions carried out during that experiment. The user, date, and time are logged for each setting and action. Notes - The user can at any time add additional user comments to the Experiment log file. - The log file is tamper-proof. As soon as someone edits it outside EthoVision XT, that is detected and it is logged that the file has been tampered with. The General Log File The General log file is created the moment EthoVision XT is installed. The following actions are logged: - Start and stop of an experiment. - Creation of a new experiment. - Users that are added, user rights that are assigned, and user rights that are modified. - Errors that occurred when opening or closing an experiment. For every action, the user name, date, and time are logged. To View the General Log File - Choose File > GLP Log Files. - In the GLP log window, select General log file. To Export the General Log File - Choose File > GLP Log Files and click the Export button, or in the Experiment Explorer, under Export, click GLP Log. - Select General log file. - Browse to the folder where you want to export the log file to and click OK. Notes - The export format is HTML (*.html). The name of the export file is GLP-EthoVision(n), where n is a progressive number. - You cannot delete the General log file. --- ## EthoVision XT 19 - EthoVision XT and Quality Assurance - Records and Reports URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethovision-xt-and-quality-assurance-records-and-reports Chapter: EthoVision XT Records and Reports All items require to be managed in such a way that GLP-compliance is facilitated and ensured. CFR21/11 more specifically describes guidelines for the use of electronic records. Important: The Quality Assurance functions in EthoVision XT do not actively check that experiments made in EthoVision XT are GLP-compliant. EthoVision XT User Management With EthoVision XT User Management you can: - Prevent non-GLP users from accessing EthoVision XT with the Quality Assurance module installed. - Define which users may access which function in EthoVision XT (for example experiment design, data recording, editing, etc.). How EthoVision XT User Management Works You can define a list of users that can access EthoVision XT. Furthermore, users can have different rights; these rights can only be assigned by a user with User Management rights in EthoVision XT. Initially, after installation, only one user has access to EthoVision XT. Which user this is depends on how EthoVision XT was installed: - EthoVision XT came installed on a computer provided by Noldus Information Technology. - EthoVision XT was installed by the user. EthoVision XT Came Installed on a Computer When you purchased both EthoVision XT and the EthoVision XT computer from Noldus Information Technology, EthoVision XT is already installed on that computer. In that case, a user account EVXT has been created to log on to Windows. This user EVXT, with administrator rights, initially is the only user who can access EthoVision XT on that computer. Choose File > Users. User EVXT has, by default, the following rights: User Management and EthoVision Preferences. Use EVXT to add new users and assign them rights. EthoVision XT Was Installed by User When a user with administrator rights installed EthoVision XT, this user is automatically added to the list of users in the User Management window in EthoVision XT. Also, a user EVXT is automatically added to the list of users. With this standard user EVXT, any administrator can at all times create a user account EVXT through which EthoVision XT can be accessed. Next, either the user that installed EthoVision XT or user EVXT can add new users and assign them rights. Add a User The procedure to add a user differs depending on whether EthoVision XT came installed on a computer or was installed by the user, and on whether the computer is on a domain or not. Follow the procedure according to your situation. EthoVision XT Came Installed on a Computer That Is on a Domain Make sure that user EVXT has also been added to the domain by your network administrator. To add a new user in EthoVision XT: - Log on to Windows as user EVXT and open EthoVision XT. - Choose File > Users. - In the User Management window, click Add. - In the Add New User window, click Network. - A list of users on the domain appears. Select a user from the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. - Click Add to add a user to the list of users that can access EthoVision XT. Next, assign rights to the new user. EthoVision XT Came Installed on a Computer That Is Not on a Domain When EthoVision XT was installed by Noldus Information Technology on an EthoVision XT computer, initially there is only one user, EVXT, on that computer. Log on to Windows as this user. You can find the password in the welcome letter you received with the software. You first need to define new users in Windows before you can add them to the list of authorized users in EthoVision XT. You must have a local computer administrator account to add a new user to the computer. To add a new user in Windows, click the Start button, then select Settings > Accounts > Other People/Other Users. Next, add this user in EthoVision XT: - Open EthoVision XT and choose File > Users. - In the User Management window, click Add. - Local users on the computer are shown. Select one of the users in the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. - Click Add to add this user to the list of users that can access EthoVision XT. Next, assign rights to the new user. EthoVision XT Was Installed by User on a Computer That Is on a Domain The user that installed EthoVision XT can add new users to the list of authorized users in EthoVision XT. - Open EthoVision XT and choose File > Users. - In the User Management window, click Add. - In the Add New User window, click Network. - A list of users on the domain appears. Select a user from the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. - Click Add to add a user to the list of users that can access EthoVision XT. Next, assign rights to the new user. EthoVision XT Was Installed by User on a Computer That Is Not on a Domain First, you might need to add local users to the computer. You must have a local computer administrator account to add a new user to the computer. To add a new user in EthoVision XT: - Open EthoVision XT and choose File > Users > Add. - Local users on the computer are shown. Select one of the users in the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. - Click Add to add this user to the list of users that can access EthoVision XT. --- ## EthoVision XT 19 - EthoVision XT and Quality Assurance - Records and Reports URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethovision-xt-and-quality-assurance-records-and-reports-w1j Chapter: EthoVision XT Records and Reports All items related to GLP compliance require management in such a way that GLP-compliance is facilitated and ensured. CFR21/11 more specifically describes guidelines for the use of electronic records. Important: The Quality Assurance functions in EthoVision XT do not actively check that experiments made in EthoVision XT are GLP-compliant. EthoVision XT User Management With EthoVision XT User Management you can: - Prevent non-GLP users from accessing EthoVision XT with the Quality Assurance module installed. - Define which users may access which function in EthoVision XT (for example experiment design, data recording, editing, etc.). How EthoVision XT User Management Works You can define a list of users that can access EthoVision XT. Furthermore, users can have different rights; these rights can only be assigned by a user with User Management rights in EthoVision XT. Initially, after installation, only one user has access to EthoVision XT. Which user this is depends on how EthoVision XT was installed: - EthoVision XT came installed on a computer provided by Noldus Information Technology. - EthoVision XT was installed by the user. EthoVision XT Came Installed on a Computer When you purchased both EthoVision XT and the EthoVision XT computer from Noldus Information Technology, EthoVision XT is already installed on that computer. In that case, a user account EVXT has been created to log on to Windows. This user EVXT, with administrator rights, initially is the only user who can access EthoVision XT on that computer. Choose File > Users. User EVXT has, by default, the following rights: User Management and EthoVision Preferences. Use EVXT to add new users and assign them rights. EthoVision XT Was Installed by User When a user with administrator rights installed EthoVision XT, this user is automatically added to the list of users in the User Management window in EthoVision XT. Also, a user EVXT is automatically added to the list of users. With this standard user EVXT, any administrator can at all times create a user account EVXT through which EthoVision XT can be accessed. Next, either the user that installed EthoVision XT or user EVXT can add new users and assign them rights. Add a User The procedure to add a user differs depending on whether EthoVision XT came installed on a computer or was installed by the user, and on whether the computer is on a domain or not. Follow the procedure according to your situation. EthoVision XT Came Installed on a Computer That Is on a Domain Make sure that user EVXT has also been added to the domain by your network administrator. To add a new user in EthoVision XT: - Log on to Windows as user EVXT and open EthoVision XT. - Choose File > Users. - In the User Management window, click Add. - In the Add New User window, click Network. - A list of users on the domain appears. Select a user from the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add a user to the list of users that can access EthoVision XT. Next, assign rights to the new user. EthoVision XT Came Installed on a Computer That Is Not on a Domain When EthoVision XT was installed by Noldus Information Technology on an EthoVision XT computer, initially there is only one user, EVXT, on that computer. Log on to Windows as this user. You can find the password in the welcome letter you received with the software. You first need to define new users in Windows before you can add them to the list of authorized users in EthoVision XT. You must have a local computer administrator account to add a new user to the computer. To add a new user in Windows, click the Start button, then select Settings > Accounts > Other people/Other users. Next, add this user in EthoVision XT: - Open EthoVision XT and choose File > Users. - In the User Management window, click Add. - Local users on the computer are shown. Select one of the users in the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add this user to the list of users that can access EthoVision XT. Next, assign rights to the new user. EthoVision XT Was Installed by User on a Computer That Is on a Domain The user that installed EthoVision XT can add new users to the list of authorized users in EthoVision XT. - Open EthoVision XT and choose File > Users. - In the User Management window, click Add. - In the Add New User window, click Network. - A list of users on the domain appears. Select a user from the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add a user to the list of users that can access EthoVision XT. Next, assign rights to the new user. EthoVision XT Was Installed by User on a Computer That Is Not on a Domain First, you might need to add local users to the computer. You must have a local computer administrator account to add a new user to the computer. To add a new user in EthoVision XT: - Open EthoVision XT and choose File > Users > Add. - Local users on the computer are shown. Select one of the users in the list. At this point, you have the option to select an initial role (Administrator, Researcher, or Technician) for the new user. See Assign Rights to Users. - Click Add to add this user to the list of users that can access EthoVision XT. --- ## EthoVision XT 19 - EthoVision XT and Quality Assurance - The Experiment Log File URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethovision-xt-and-quality-assurance-the-experiment-log-file-HGr Chapter: EthoVision XT The Experiment Log File The Experiment log file is started at the moment a GLP experiment is created. Changes made by the user that affect the data and results of an experiment can be traced back in the log file. These changes are logged from the moment you actually start acquiring data. At that moment a snapshot is taken of the various settings in your experiment and this snapshot is logged. Thereafter, all changes that can affect your data are logged. When a user makes changes to settings (for example, in the Trial List or Trial Control Settings) and/or leaving a Setting, the user is prompted to add a comment to the Experiment log file. A new snapshot is then taken when new data are acquired. When the user cancels this automatic pop-up or does not enter a comment, a line appears in the Experiment log file with user name, date and time but without a comment. To Add a Comment to the Experiment Log File - Choose File > Add log comment (Ctrl+L). - Type in comments and click OK. To View the Experiment Log File Before you can view an experiment log file, you need to open the corresponding experiment. To view the experiment log file in EthoVision XT: - Choose File > GLP Log Files. - In the GLP log window, select the experiment log file radio button. If necessary, click on one of the html links to go to a specific part of the Experiment log file. To Delete the Experiment Log File You can only clear the contents of the Experiment log file, not delete it. You can only clear the Experiment log file when you have the user management right to Delete Trials and Clear Log. - Choose File > GLP Log Files. - Select Experiment log file and click the Clear Log button. To Export the Experiment Log File - Choose File > GLP Log Files, and click the Export button, or in the Experiment Explorer, under Export, click GLP Log. - Select Experiment log file. - Browse to the folder where you want to export the log file to and click OK. Notes - In the case of large experiments, when the log file exceeds a size of 1 MB, it is split in multiple log files. - The export format is HTML (*.html). The name of the export file is GLP-[Experiment name](n), where n is a progressive number. - Experiment Settings, Arena Settings, Trial list, Trial Control Settings and Detection Settings are not stored in the log file until the first data are acquired. After that, only changes are logged. - Logged Arena Settings include a screenshot of Arenas and their Calibrations. It also contains a screenshot of each Zone Group and its Zones. - If your current experiment is not set for Quality Assurance, there is no Experiment log file present. - The suggested export location is the experiment's Export Files folder. Create a GLP Experiment from a Template Aim Create a new experiment with all the right default settings, but without tracks and an Experiment log file, based on an existing GLP experiment. Prerequisites - You must have the User Management right to delete trials and clear log. See Assign Rights to Users. - You have a GLP experiment that you want to use as a template, for example an experiment with specific arenas and zones. Procedure - Choose File > New template experiment or press Ctrl+T. - In the Template option window, select Use a custom template. - Click Browse and select the existing GLP experiment you want to use as a template. Select the file with extension *.evxt and click OK. - Type in the name of the new experiment. - Select GLP experiment and click OK. Notes - Create a backup of the template and store it in a safe place. - To open a GLP experiment, you need an EthoVision XT license that includes the Quality Assurance module. See Upgrade EthoVision XT. - In a GLP experiment you cannot change or edit the zones already used in Acquisition. - If your license includes the Quality Assurance module, you can still create or open non-GLP experiments. In that case User Management does not apply and no log file is kept. - Multiple copies of the same version of EthoVision XT installed on the same computer share the General log file. Different versions of EthoVision XT installed on the same computer each have their own General log file. Troubleshooting Main Topics and Tasks - Troubleshooting: Installation and License - Troubleshooting: General - Troubleshooting: Pylon Camera Software - Troubleshooting: Camera - Troubleshooting: Video Image - Troubleshooting: Arenas and Zones - Troubleshooting: Detection - Troubleshooting: Data Acquisition - Troubleshooting: External Data - Troubleshooting: Track Editor - Troubleshooting: Statistics - Troubleshooting: Behavior Recognition - Troubleshooting: Deep Learning - Troubleshooting: Data Visualization - Troubleshooting: Control of Hardware Devices - Troubleshooting: DanioVision - Troubleshooting: Live Mouse Tracker - Troubleshooting: Import Trials - Troubleshooting: Quality Assurance (GLP) --- ## EthoVision XT 19 - EthoVision XT and Quality Assurance - The Experiment Log File URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethovision-xt-and-quality-assurance-the-experiment-log-file Chapter: EthoVision XT The Experiment Log File The Experiment log file is started at the moment a GLP experiment is created. Changes made by the user that affect the data and results of an experiment can be traced back in the log file. These changes are logged from the moment you actually start acquiring data. At that moment a snapshot is taken of the various settings in your experiment and this snapshot is logged. Thereafter, all changes that can affect your data are logged. When a user makes changes to settings (for example, in the Trial List or Trial Control Settings) and/or leaving a Setting, the user is prompted to add a comment to the Experiment log file. A new snapshot is then taken when new data are acquired. When the user cancels this automatic pop-up or does not enter a comment, a line appears in the Experiment log file with user name, date and time but without a comment. To Add a Comment to the Experiment Log File - Choose File > Add log comment (Ctrl+L). - Type in comments and click OK. To View the Experiment Log File Before you can view an experiment log file, you need to open the corresponding experiment. To view the experiment log file in EthoVision XT: - Choose File > GLP Log Files. - In the GLP log window, select the experiment log file radio button. If necessary, click on one of the html links to go to a specific part of the Experiment log file. To Delete the Experiment Log File You can only clear the contents of the Experiment log file, not delete it. You can only clear the Experiment log file when you have the user management right to Delete Trials and Clear Log. - Choose File > GLP Log Files. - Select Experiment log file and click the Clear Log button. To Export the Experiment Log File - Choose File > GLP Log Files, and click the Export button, or in the Experiment Explorer, under Export, click GLP Log. - Select Experiment log file. - Browse to the folder where you want to export the log file to and click OK. Notes - In the case of large experiments, when the log file exceeds a size of 1 MB, it is split into multiple log files. - The export format is HTML (*.html). The name of the export file is GLP-[Experiment name](n), where n is a progressive number. - Experiment Settings, Arena Settings, Trial list, Trial Control Settings and Detection Settings are not stored in the log file until the first data are acquired. After that, only changes are logged. - Logged Arena Settings include a screenshot of Arenas and their Calibrations. It also contains a screenshot of each Zone Group and its Zones. - If your current experiment is not set for Quality Assurance, there is no Experiment log file present. - The suggested export location is the experiment's Export Files folder. Create a GLP Experiment from a Template Aim Create a new experiment with all the right default settings, but without tracks and an Experiment log file, based on an existing GLP experiment. Prerequisites - You must have the User Management right to delete trials and clear log. - You have a GLP experiment that you want to use as a template, for example an experiment with specific arenas and zones. Procedure - Choose File > New template experiment or press Ctrl+T. - In the Template option window, select Use a custom template. - Click Browse and select the existing GLP experiment you want to use as a template. Select the file with extension *.evxt and click OK. - Type in the name of the new experiment. - Select GLP experiment and click OK. Notes - Create a backup of the template and store it in a safe place. - To open a GLP experiment, you need an EthoVision XT license that includes the Quality Assurance module. - In a GLP experiment you cannot change or edit the zones already used in Acquisition. - If your license includes the Quality Assurance module, you can still create or open non-GLP experiments. In that case User Management does not apply and no log file is kept. - Multiple copies of the same version of EthoVision XT installed on the same computer share the General log file. Different versions of EthoVision XT installed on the same computer each have their own General log file. Troubleshooting Main Topics and Tasks - Troubleshooting: Installation and License - Troubleshooting: General - Troubleshooting: Pylon Camera Software - Troubleshooting: Camera - Troubleshooting: Video Image - Troubleshooting: Arenas and Zones - Troubleshooting: Detection - Troubleshooting: Data Acquisition - Troubleshooting: External Data - Troubleshooting: Track Editor - Troubleshooting: Statistics - Troubleshooting: Behavior Recognition - Troubleshooting: Deep Learning - Troubleshooting: Data Visualization - Troubleshooting: Control of Hardware Devices - Troubleshooting: DanioVision - Troubleshooting: Live Mouse Tracker - Troubleshooting: Import Trials - Troubleshooting: Quality Assurance (GLP) Troubleshooting: Installation and License Issues: Installation - Error message (ID 10020) - Installation stops halfway - Blue-screen crash during installation of Euresys Multicam - The hardware key does not light up - When I start EthoVision XT, I get the message: No license key found - Installation of EthoVision XT fails, likely due to an error during installation of the Basler camera drivers - I have realized that I installed the wrong camera driver software. What can I do? Issues: License - My EthoVision XT license has expired. What should I do? - I am trying to upgrade my license, but the upgrade key is not being accepted - I cannot start EthoVision XT with a floating license - I purchased an add-on module but I cannot use it - I purchased an add-on module. How do I update my license? - I entered a license key but an error message shows a different one - I need to create a Firewall rule to access the Noldus license server. Which port do I need to access? - I cannot deactivate a license. The menu item Deactivate license is greyed out - EthoVision XT is in Analysis mode, but there is no way to work with a full license - Message: "Activation not complete" - Message: "License already activated..." Source: EthoVision XT 19 Help - EthoVision XT and Quality Assurance, Noldus Information Technology --- ## EthoVision XT 19 - EthoVision XT and Quality Assurance - Troubleshooting: Installation and License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-ethovision-xt-and-quality-assurance-troubleshooting-installation-and-license Chapter: EthoVision XT Troubleshooting: Installation and License Issues: Installation - Error message (ID 10020) - Installation stops halfway - Blue-screen crash during installation of Euresys Multicam - The hardware key does not light up - When I start EthoVision XT, I get the message: No license key found - Installation of EthoVision XT fails, likely due to an error during installation of the Basler camera drivers - I have realized that I installed the wrong camera driver software. What can I do? Issues: License - My EthoVision XT license has expired. What should I do? - I am trying to upgrade my license, but the upgrade key is not being accepted - I cannot start EthoVision XT with a floating license - I purchased an add-on module but I cannot use it - I purchased an add-on module. How do I update my license? - I entered a license key but an error message shows a different one - I need to create a Firewall rule to access the Noldus license server. Which port do I need to access? - I cannot deactivate a license. The menu item Deactivate license is greyed out - EthoVision XT is in Analysis mode, but there is no way to work with a full license - Message: "Activation not complete" - Message: "License already activated..." Source: EthoVision XT 19 Help - EthoVision XT and Quality Assurance, Noldus Information Technology --- ## EthoVision XT 19 - Experiments with Calcium Imaging URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-experiments-with-calcium-imaging Chapter: EthoVision XT Program Control of Devices in EthoVision XT Trial Control Settings The Trial Control Settings in EthoVision XT allows you to program activation of calcium imaging and optogenetic stimulation by Inscopix devices at specific times or when specific events occur, for example when the subject enters a target zone of the arena. In addition, in Trial Control Settings you can define the conditions for the start and stop of data acquisition. In EthoVision XT, choose Setup > Trial Control Settings > New, and enter a name for the new settings profile. For more information on how to work with Conditions and Actions in Trial Control Settings, see the EthoVision XT Help (press F1 in EthoVision XT) and the EthoVision XT 19 - Trial and Hardware Control - Reference Manual, which you can find in the Apps screen under Noldus > EthoVision XT 19 Other Documentation. Example 1 - Image Recording (nVista) Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. Next, EthoVision XT sends out a high TTL pulse to the TRIG port of nVista. After a time delay of 10 minutes, EthoVision XT stops tracking the subject. Hardware Connections Refer to the hardware connection scheme for nVista in the hardware setup section of this manual. Prerequisites in EthoVision XT You specified the TTL port and output line (either 1 or 2) for TRIG in the Experiment Settings and mapped the port to the arena. Procedure - In the Trial Control Settings, under Actions, click the button next to Custom hardware. - Specify the device (e.g. Device A) and the type of signal (Output 1 High). - Optionally, edit the name in the Action name field. - Click OK and insert the Action box between the Condition - In zone box and the Action - Start track box. - Click Settings in the Condition - Time box and select 10 minutes. This way tracking stops after 10 minutes. - If you want to stop recording in nVista when you stop behavior tracking, bring a new Action box in the flow line which instructs the system to send out a low TTL pulse to nVista. Make sure that you place the Action box at the right of the 10-minutes time box. Tip: In the Hardware Action box you can test whether EthoVision XT triggers the nVista. To do so, click the Test button. Note: Make sure to instruct nVista/nVoke to record video based on the TRIG signal. Example 2 - Manual Video Recording, Triggered OG-LED Stimulation Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. You start video recording in nVoke manually by clicking the Record button. At the planned time, for example at 10 minutes after start, EthoVision XT sends out a high TTL pulse to the GPIO[n] port of nVoke. In the Inscopix DAQ software, under Video Recording configuration, make sure that Trigger is set to NONE and Control is set to Video Recording ON. Hardware Connections Refer to the hardware connection scheme for nVoke in the hardware setup section of this manual. You do not need to use the TRIG port of the nVoke device. Set the GPIO[n] to Input in the Inscopix DAQ software. Prerequisites in EthoVision XT In the Experiment Settings, you defined the TTL port and output line (either 1 or 2) connected to the GPIO[n] of nVoke. In Arena Settings, you mapped that port to the arena. Procedure Because calcium imaging is started manually in this example, you only have to program the activation of the OG-LED. In the following example, the Time condition is set to wait 10 minutes before the triggering action. - In the Trial Control Settings, under Conditions, click the button next to Time. - Specify the time (e.g. 10 minutes). Optionally, edit the name in the Condition name field. - Click OK and insert the Condition box after the Action - Start track box (or wherever it applies in your protocol; for example in a sub-rule). - In the Trial Control Settings, under Actions, click the button next to Custom hardware. - Specify the device (e.g. Device A) and the type of signal (Output 1 High). - Optionally, edit the name in the Action name field. - Click OK and insert the Action box at the right of the Condition box just created. - When that applies, define a Condition and an Action (Output Low) for stopping the trigger action and insert them in the trial control flow line. Notes - In the Inscopix DAQ software, make sure to set the Trigger mode for the GPIO[n] port to Follow. - When the Trigger is set to low, LED stimulation is stopped. To set the Trigger to Low, add an Action to the same device/TTL port and output line as above, and select the signal Output Low. - You can also let the DAQ software run its own pulse protocol while the Trigger is ON. In that case the Control for the GPIO[n] port is set to Pulse protocol. - For more information, see the nVista and nVoke User Manual. Example 3 - Triggered Video Recording and LED Stimulation Use Case EthoVision XT starts tracking after locating the subject's center point in the arena. Both video recording and the OG-LED are triggered by EthoVision XT when the corresponding conditions (time or event) are met. Hardware Connections - Refer to the hardware connection scheme for nVoke in the hardware setup section of this manual. - Set the GPIO[n] to Input in the Inscopix DAQ software. Prerequisites in EthoVision XT In the Experiment Settings, you defined two TTL lines from the USB-IO box: one connected to the TRIG and the other to the GPIO[n] port of nVoke. In Arena Settings, you mapped the ports/lines to the arena. Procedure Define actions and conditions as explained for the previous examples. - Condition to trigger video recording. - Action to trigger video recording through the TRIG port. - Condition to trigger OG-LED stimulation. - Action to trigger the OG-LED stimulation through the GPIO[n] port. When applicable, define additional conditions and actions to stop video recording and OG-LED stimulation. Notes - In the Inscopix DAQ software, make sure to set the Trigger mode for the TRIG port to Follow, and the Control is set to Video Recording ON. In an alternative configuration, you can set Control to Recording schedule to record video for a specific time. - In the Inscopix DAQ software, make sure to set the Trigger mode for the GPIO[n] port to Follow. Select the type of Control you require (e.g. Pulse protocol). - See the Example Configuration #3 in the nVista and nVoke User Manual. Detection Settings General Ensure your subjects are detected well by EthoVision XT. Choose Setup > Detection Settings. For more details, see the EthoVision XT Help. Sample Rate In the Video section, specify the sample rate. Some commonly-used values are: - For tracking rats: 5 samples/second. - For tracking mice: 12.5 samples/second. - When tracking the nose- and tail-base points of rodents: 25-30 samples/second. Detect Immobility There are two ways to detect immobility of the subject during the trial. - Activity measures the number of pixels that change their intensity, so whenever the subject sits still, the Activity value will be low. However, when the subject is connected to a microscope cable, the cable can move continuously and keep Activity high. As a result, Activity measurements may not detect immobility with sufficient accuracy. Instead, use Mobility. - Mobility is based on the change of the detected shape (i.e., the yellow blob). You can define Mobility in the Analysis profile, so you do not need to specify anything in the Detection Settings. However, make sure that the yellow blob covers the entire body of the subject and is not affected by the cable (see below). Remove the Effect of the Microscope Cable When the microscope cable is detected as the subject, it changes both the Mobility measure and the position of the center point. The latter affects distance moved and other readouts. Step 1 - Define the Contrast The first thing to do is to make sure that the entire body of the subject is well detected throughout the arena. Use for example Dynamic subtraction and choose the smallest range of contrast that enables detection of the subject's body. In this step the cable may still be detected. This will be removed in the next step. Make sure that the contour of the subject is not too much indented and noise (i.e. the orange areas) is limited. Step 2 - Erode and Then Dilate the Contour In the Detection Settings, locate the Subject Contour options. Select 1 or a higher value for the first Erosion and a similar value for Dilation until the cable is no longer highlighted in yellow. The Erosion filter removes the pixels from the contour (and therefore the cable too); the Dilation filter restores the original size of the yellow blob but excludes the cable. Aligning Data Sync Signal To align the data streams from EthoVision XT and Inscopix nVista/nVoke, there are two solutions: - Have EthoVision XT send a time code signal (TCAP). - Have EthoVision XT send a sequence of TTL pulses. Either way, the Inscopix system records the signal in one of its channels. The difference between the two is that with TCAP you need to export the TCAP signal that is stored in Inscopix back to EthoVision XT, together with the Inscopix data, so that EthoVision XT reads the time code and aligns the Inscopix data with the tracks. Note: The nVista/nVoke system can also send a sync pulse to EthoVision XT through the USB-IO box every time a video frame is recorded. However, the pulse generated from the SYNC port of nVista/nVoke has a duration of 10 ms. That is too little for EthoVision XT to detect and record the signal. Therefore, this solution is not optimal to sync the two data streams. Using the TCAP Signal Prerequisites For this solution you need: - The External Data add-on module for EthoVision XT. Contact Noldus if you need to purchase it. - An interface cable between EthoVision XT and the BNC connector of the nVista/nVoke DAQ box. Contact Noldus to have one made for you. - A way to convert the Inscopix data to a format compatible with EthoVision XT: fixed sample rate, without gaps. Procedure - Set the TCAP signal in the Experiment Settings of EthoVision XT, and specify the sample rate of the Inscopix channel that will receive that signal. - Start acquisition in Inscopix and then start the trial in EthoVision XT. nVoke/nVista records the TCAP signal, which should be visualized on the system's screen. - Export the Inscopix data to text files. Note that here the sample rate must be fixed and all samples must be written in the file, otherwise import will not work. - After import, EthoVision shows the TCAP signal and other Inscopix data together with the track data. For more information, see External Data in the EthoVision XT Help. Using a TTL Signal Connections Connect a TTL port of the USB/IO box to one of the GPIO ports of the Inscopix DAQ box. For this you need a cable with a RJ45 connector at one end and a BNC connector at the other end. Procedure - In the Experiment Settings in EthoVision XT, define a TTL port of the USB-IO box. Select Custom Hardware from the list. In the Arena Settings, map that TTL port to one of the arenas. - In the Trial Control Settings, add a subrule that activates the TTL port every few seconds. For example: TTL Output 1 High for 1 second, then TTL Output 1 Low for 4 seconds. Let the subrule repeat a number of times or when a Trial Control variable reaches a specific value. In general, make sure that the ON-OFF sequence runs through the duration of the trial. Tip: To stop the subrule at the end of the trial, add an Action box immediately before the Stop Trial box, where a Trial Control Variable, for example END, gets the value 1. In the Subrule reference, specify to end the subrule when END = 1. - Run a test trial and make sure that Inscopix records the signal coming to the GPIO port. - Visualize the data in both systems. In EthoVision XT, you can visualize the TTL signal by selecting, for example, Trial Control state in the Analysis profile and defining the state from the action Output 1 High to the action Output 1 Low (here the numbering depends on which TTL line you use). - If the data are well aligned, the time between the first and the last pulse should be the same in EthoVision XT and Inscopix, or differ by a few milliseconds. For more information, see the nVista/nVoke User Manual and the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Mark EthoVision Events on the Calcium Imaging Timeline You can also use the GPIO ports on the nVoke/nVista box to send specific events to the Calcium Imaging software. In the following example, a setup that includes a fear conditioning system, all GPIO ports are set to digital and work as inputs. - GPIO-1 receives a signal from a TTL port of the USB-IO box that is set to high when tracking starts. - GPIO-2 receives a signal from a TTL port of the USB-IO box that is set to high when a 5-kHz tone is given. - GPIO-3 receives a signal from a TTL port of the USB-IO box that is set to high when a 15-kHz tone is given. - GPIO-4 receives a signal from a TTL port of the USB-IO box that is set to high or low when the optogenetic stimulation is given/stopped, respectively, or when a shock is given/stopped, respectively. Data Analysis in EthoVision XT Once you acquire your trials, you want to pair the behavioral tracking with the calcium imaging/optogenetic stimulation events. To view and analyze those events, you must first define them in the Analysis profile. Choose Analysis > Analysis Profile > New. Define a Simple Event With the variable Hardware command you can visualize the time that the USB-IO box sends a trigger command to nVista/nVoke. - In the Dependent Variables pane, under Hardware, choose Hardware command. - Choose the device and the output state, for example Output 1 High. Note that Output represents one of the two communication lines present in each TTL port of the USB-IO box. Choose the line that you used in the Action box in the Trial Control Settings to trigger the device. - Visualize the event (Analysis > Results > Integrated Visualization). Analyze Intervals (Global) You can analyze the behavior of the subject within an interval based on events. For example, calculate the average velocity of the subject from the time that stimulation starts (i.e., when the TTL Output 1 is High) to the time that stimulation ends (i.e., nVoke is triggered with Output 1 Low). To analyze the behavior within intervals, you must use the Nesting function in the Data profile. - Choose Analysis > Data Profile > New. - In the Components pane, under Nesting, choose Hardware state. - Select the device and the status of the device. For example, Device A - Is Output 1 High - true. This selects the time that the TTL Output 1 signal remains high. - Insert the box in the flow line. - Visualize the interval (Analysis > Results > Integrated Visualization). Note: If Output 1 stays high multiple times during one trial, EthoVision XT considers the cumulative time that Output 1 stays High, and that is used as the analysis interval. When you want to analyze the time defined by a specific triggering event, see the Analyze Specific Intervals section below. Analyze Specific Intervals You can use Free Intervals in the Data profile to define and analyze specific intervals based on individual triggering events within a trial. For more information, see the EthoVision XT Help. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - Export Raw Data Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-export-raw-data-variables Chapter: EthoVision XT Aim To export the x,y coordinates and the subject size for each sample together with the values of the dependent variables selected in the currently active analysis profile, including manually-scored behaviors and automatically recognized behaviors. The raw data file includes the independent variables that you defined in the Trial List. Procedure - Choose Analysis > Export > Raw Data, or in the Experiment Explorer under Analysis - Export click Raw Data. - In the Raw Data Export window, select the Track Smoothing profile, the Data profile and the Analysis profile that define the data to be exported. - Under Data to Export, select Track & dependent variables. - Click Browse next to Destination folder and navigate to the location where you want to save the export files. - Under File Type, select either ANSI text (*.txt), Excel (*.xlsx), or Unicode text - default (*.txt). For text export, enter the Delimiter character you want to use to separate columns in the exported file. - Next to Missing value representation, choose the character that you want to use to mark missing values. - Click Start export. Options File Type - If you export to text, data of each subject (track) is exported to a separate file. Each file name is unique, and is formed by, in the following order: Raw Data (or Manual Scoring, depending on what option you have chosen) - Experiment name - Trial number - Arena name - Subject name. For example Raw Data-Open Field-Trial 1-Arena 1-Subject 1.txt - Choose Unicode text to export according to the Unicode character set. This supports most world languages, including Chinese. Choose ANSI text to export the data as text files according to the ANSI character set. Choose this option only if the application in which you will open the exported file cannot handle the Unicode character set. - If you export to Excel, the file contains all tracks of a trial. The file name is unique and formed by the following elements: Raw data (independent of the type of export) - Experiment name - Trial number. For example Raw Data-Plus Maze-Trial 1.xlsx. Data of each subject is written in a separate tab of the worksheet, named for example Track-Arena 1-Subject 1. IMPORTANT: If your tracks contain more than approximately one million samples, Excel is unable to load the exported file. With 30 samples per second, this happens just after 9 hours. To solve this, export the file to text and use the Excel macro SplitTxtFiles.xlsm. You can find this file on my.noldus.com, under Downloads > EthoVision XT > Drivers and tools. Manual Scoring Log - If you want to export the manually-scored behaviors to The Observer XT, or in a format like for example, 5.12s Rearing, 5.88s Not Rearing, choose Manual scoring log. - You can also export behaviors (both manually-scored and automatically recognized) in the same format as the other dependent variables, where a behavior is scored as 0 or 1 for each sample time, depending on whether it occurs or not at that time. Choose Track & dependent variables. Make sure that the Analysis profile includes the behaviors to export. Trial Control Data - Choose Track & dependent variables also if you want to export Trial Control events and states defined in your Analysis profile. For example, to export the state from Cue light on To Subject in Feeder zone. The state is exported as a series of 0s and 1s (0 = state not active, 1 = state active) in the corresponding column of the export file. - Choose Trial Control log if you want to export Trial Control events and states with their own time stamp, for example 6.8 s - Cue light on - Activated. For more information, see Export Trial Control Data. Hardware Log Choose Hardware log if you want to export the complete log of events of hardware devices as a separate file. See the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. External Data Choose External data log (not resampled) if you want to export the values of the physiological data streams. Note that these export files contain the original data, not the resampled data that appear in the EthoVision XT analysis profile. See External Data (resampled). Missing Value Representation Enter the character for missing values. By default, missing values are exported as -. See also Export Settings for Specific Applications. A missing value is exported in the following cases: - The X,Y coordinates of a missing body point. - The values of a dependent variable that could not be calculated for that sample. For example, the distance moved when the previous sample was missing. File Names, Folders, and Data Format - If you export the same data multiple times to the same location, EthoVision XT attaches a number at the end of the file name: (1), (2), etc. - The files' suggested location is the Export Files folder located in your experiment folder. See File Locations. - The values exported have a variable number of decimals, depending on the number of integers. The total number of significant digits exported is always six (for example, 1.23456 or 1234.56), or seven if the unsigned number is smaller than one (0.123456). Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Export Raw Data Variables (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-export-raw-data-variables-continued Chapter: EthoVision XT The Raw Data File Below: Part of a raw data file, opened in Excel. Top: Headers with independent variables. Bottom: data lines with time, x,y coordinates, subject area and dependent variables (one line per sample). Reading the Raw Data File - The track file export takes into account your data selection for entire tracks, but not for within tracks. So, if you make a data selection such that you only have track 1 and only zone 1, EthoVision will export track 1, but the entire track. If you want to filter out zone 1 in your track data, you should include the zone as a dependent variable and then filter on that column in Excel. The result column in the export file has values 0 and 1 dependent on the fact if the data selection criteria were met (1) or not met (0). - Trial time is the time elapsed from the start of the trial (basically, the moment when you clicked the green Start button). Recording time is the time elapsed from the start of the track. The difference between the two time values is also shown next to the header Recording after. For more information on trials and tracks, see Important terms in Trial Control. - The values of the x,y coordinates and the subject size (Area) in the exported track files are expressed in calibrated units, (square) millimeters, (square) inches, etc., not in pixels. - Areachange is the change in the pixels of the subject area from the previous sample, used to calculate Rotation. Note that this is not the same as the difference in Area between the current sample and the previous one. - Samples that were missing (EthoVision XT could not analyze the video image) or not found (EthoVision XT could not find the subject) are indicated by - instead of the coordinate values. Note that sometimes the center point is found, not the nose point or the tail base (or neither of the two). To see the proportion of samples that were not found in a trial, in the Trial list click the Show/Hide button on the toolbar, choose Variables and select Subject not found. Check the value in the column Subject not found corresponding to that trial. - Excel can import a limited number of rows and columns. For Excel 2007 and newer versions this is 16384 rows and 1048576 columns. Excel will only import the maximum number of rows. If necessary, you can import the exported files to another program like SPSS. Export External Data Aim: To export data like physiological data that were imported into EthoVision XT, to another application for further analysis. You can export the original data or the resampled data. To Export the Original External Data - Choose Analysis > Export > Raw Data. - Select External data log (non resampled). - Choose the File type and click Start Export. Notes: - Each line in the exported data file represents one sample according to the original sample rate. For example, for Heartbeat sampled at 1 sample/s. - Trial time and Recording time are the original time stamps relative to the start of the trial and the start of the track, respectively. - For text export: each file contains the original signal combined with the current Data profile/Result container. The default file name is: External-[experiment name]-[Trial number]-[signal name]-[Data profile or Result container name]-[Arena name]-[Subject name].txt. - For Excel export: each file contains the signal from one trial. The default file name is: Raw data-[experiment name]-[Trial number].xlsx. Within an Excel file, each sheet contains the signal combined with the current Data profile/Result container. Sheets are named in this way: [signal name]-[Data profile or Result container name]-[Arena name]-[Subject name]. This name may be truncated. - For more information on other options, see Export the raw data (track and dependent variables). To Export the Resampled External Data - Choose Analysis > Export > Raw Data. - Select Track and dependent variables. - From the list on the toolbar, select the Analysis profile that contains the resampled signals. See External data (resampled). - Choose the File type and click Start Export. - In the exported data file, each line is one EthoVision XT sample. Each resampled signal is written in a column. The Data profile column indicates whether a sample is included (1) or not (0) in the Data profile. - Export files are named like Raw data files. For more information on other options, see Export the raw data (track and dependent variables). - To export a specific selection of resampled external data, first edit the Data profile. To Export the Signal Statistics Make sure that the signal is selected in the Analysis profile, with the Trial Statistics that you require. Next, choose Analysis > Export > Statistics. See Export the statistics result. Export Manually-Scored Behaviors Aim: To export the behaviors scored manually, depending on the file structure you require. - Export as dependent variable. The behaviors are exported as 0s or 1s, depending on whether the behavior is active (1) or not (0) at a specific sample time. Note that the export file contains a header. For example: Time    Grooming head 10.00   0 10.04   1 ...     ... 12.00   0 - As a Manual Scoring log. The behaviors are exported to a file where the start and stop events are written in sentences with the following structure: Time - Subject - Behavior - Event type (State start or State stop) For example: 10.04   Subject 1   Grooming head   State start 12.00   Subject 1   Grooming head   State stop Procedures To Export Manually-Scored Behaviors as Dependent Variables - Make sure that the Analysis profile includes the behaviors to export. - Choose Analysis > Export > Raw Data, and select Track and dependent variables. See also Export the raw data (track and dependent variables). To Export Manually-Scored Behaviors as a Manual Scoring Log - Choose Analysis > Export > Raw Data, or in the Experiment Explorer under Analysis - Export click Raw Data. - Select Manual scoring log. Select the export format. If you export to The Observer XT, select a Text option and select semicolon (;) as Delimiter. - Click Start export. For more options see Export the raw data (track and dependent variables). Notes - See Import manually scored data into The Observer XT. - If you export to Excel, the manually scored data are stored in a separate tab of the Excel worksheet. The tab is named Manual scoring - [arena name]. - If you export to Text, data of different arenas are exported to different files. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Export the heatmaps URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-export-the-heatmaps Chapter: EthoVision XT Export the Heatmaps You can export a single heatmap, some heatmaps or the whole matrix of heatmaps to image files. A great advantage of this function compared to copy and paste is that you can rescale the heatmap to a resolution higher than that of the original video, resulting in quality pictures ready for publications. Export a Single Heatmap - Click the heatmap you want to export, so that its border becomes highlighted in red. - Right-click the heatmap and select Export image, or on the toolbar click the Export image icon. - Select the image Resolution (width x height) in pixels. - Click Export. In the Export Image window, enter the name and location of your image file, choose the image format and click Save. TIP You can also copy and paste single heatmaps: click a heatmap, right-click and select Copy or press Ctrl+C, then paste the picture to an external program. You cannot copy/paste multiple heatmaps. Export Multiple Heatmaps - Select the heatmaps you want to export. - To export all heatmaps in the matrix, make sure that no heatmap is highlighted. Click outside the heatmaps area to remove any selection. - To export multiple, non-adjacent heatmaps, hold Ctrl down and click the individual heatmaps. - To export multiple, adjacent heatmaps, hold Shift down, then click the first, then the last of the heatmaps you want to export. Result: The border of the selected heatmaps becomes highlighted in red. - On the toolbar click the Export image icon. If you have selected some heatmaps, you can also right-click anywhere over the selected heatmaps and choose Export image. - Under Export, choose one of the options: To separate image files or To one image file. - Select the image Resolution (width x height) in pixels. TIP To ensure that each heatmap has a sufficient resolution, under Export select first To separate image files, select the resolution you require and then choose To one image file. The image resolution (width, height, or both) is increased by a number of times depending on how many heatmaps are in the rows and columns. - Choose Independent variable as overlay to have the trial information (headers) displayed on the exported images. - Click Export. In the Export Image window, enter the name and location of your image file, choose the image format and click Save. Notes - The available image resolutions depend on the aspect ratio of the original background pictures. The zoom level chosen for the plots affects the default resolution. - To choose the appropriate information to display on the heatmaps, see Custom Layout in Arrange Heatmaps. - The suggested export file name is Heatmap Image followed by a progressive number. For heatmaps exported to separate files, the name of the exported file is the name you enter in the Export Image window followed by the row headers and the column headers. For example, Heatmap Image 0001 - Trial 1 - Center point. Plot Integrated Data Choose Integrated Visualization to visualize a set of tracks obtained from one tracking session (trial), together with video, external data (if applicable), and plots of your dependent variables (including manually scored behaviors and external data). This function is particularly useful when you want to compare tracks with the corresponding video. IMPORTANT You can visualize up to 200 plots at the same time. If the number of subjects/arenas times the number of dependent variables currently selected exceeds this limit, filter the subjects or arenas in your Data Profile, or remove some dependent variables from your Analysis Profile. Prerequisite Make sure that the dependent variables you want to plot are specified in the active Analysis Profile. To Plot Integrated Data - Choose Analysis > Results > Plot Integrated Data, or in the Experiment Explorer, under Results, click Integrated Visualization. - On the toolbar, choose the Track Smoothing profile, the Data Profile and the Analysis Profile that you want to use. - On the toolbar, choose the selection result and the trial you want to visualize. By default, the first trial is selected. To select the next/previous trial, click the buttons next to the drop-down list. The selection result list is available if your current Data Profile includes two or more selection results. - OPTIONAL Customize tracks and plots. - View and interpret variable plots. Notes - In the Integrated Visualization screen you can also find one or more External Data plots, depending on how many external data files have been imported in that trial. See External Data Plots. - Not all playback speeds might be available. Depending on the video format, you may not be able to play the video at a specific speed. - If your data selection contains nesting criteria, all samples are plotted but the samples excluded by nesting are shown shaded. - You can visualize up to 200 plots per trial. If the number of dependent variables in your Analysis Profile times the number of subjects/arenas exceeds this limit, a message informs you that not all charts are visualized. Filter the subjects/arenas in your Data Profile, or remove some variables in your Analysis Profile. - The begin time in the video window is the time of the first sample acquired in all arenas. - The end time in the video window is the time of the last sample from all arenas. Within each arena, the last sample is marked by the message End of track over the top-left corner of the corresponding arena. - For multi-arena setups, the tracks are synchronized; that is, samples of different arenas visualized at a given moment were acquired at the same absolute time. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Export the statistics result URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-export-the-statistics-result Chapter: EthoVision XT Export the Statistics Result Aim: To export the statistics of the dependent variables in the results table to an external program. For example, export the values of average velocity to SPSS. Prerequisites - The statistics result is open on your screen. - Select the Data profile and Analysis profile from the lists on the toolbar. - If the table layout does not match the requirements of the program you want to export the result to, see The Statistics Result. Procedure - Choose Analysis > Export > Statistics, or in the Experiment Explorer under Analysis > Export, click Statistics. - Under Export, choose to export Trial Statistics or Group Statistics. - Click the Browse button to select the location for your export file. Its suggested location is the Export Files folder located in your experiment folder. - Under File Type, select either ANSI text (*.txt), Excel (*.xlsx), or Unicode text - default (*.txt). - Next to Missing value representation, enter the character that you want to export when the value for a particular cell is missing. - For text export, enter the Delimiter character you want to use to separate columns in the exported file. - Click OK. Options - Missing value representation. Missing values in a statistic result are statistics that could not be calculated for that particular cell. For example, if the subject never visited a zone during trial 2, the result for the statistic Latency to first and for the dependent variable In zone will be "-". By default, missing values are exported as -. Make sure the destination program recognizes the character you specify as a missing value. - Merge column headers (selected by default in new experiments). Keep this option selected if you want to export to applications like Excel or SPSS. In this example, the column headers are merged after export to Excel. If you do not select this option, each of the four column headers in the results table will appear in separate rows in the export file. Note that the order of the text elements in the header depends on the order of the headers in the results table. You can change the order using the Layout function. Here an example where the units cm were at the bottom level of the results table — they are now at the end of the header. Notes - The name of the export file is Statistics-[Experiment name]. If you export results multiple times to the same location, EthoVision attaches a number at the end of the file name: (1), (2), etc. - Choose Unicode text to export according to the Unicode character set. This supports most world languages, including Chinese. Choose ANSI text to export the data as text files according to the ANSI character set. Choose this option only if the application in which you will open the exported file cannot handle the Unicode character set. - The values exported have a variable number of decimals, depending on the number of integers. The total number of significant digits exported is always six (for example, 1.23456 or 1234.56), or seven if the unsigned number is smaller than one (0.123456). Because of this restriction, there may be a very small difference between the values in the results table and in the export file. This difference is in the order of 1/10000th of the measurement unit. - To change the layout of the exported table, follow Modify the Layout of the Results Table and then export the results. Export Settings for Specific Applications - For R: Export to text. Make sure that R can recognize - as a missing value. Use na.strings to include all possible "no data" characters or strings, for example: loadfile <- read.table("exportfile.txt" , header = TRUE , sep=";" , na.strings = c("-" , "NODATA", ....)) - For SPSS: Select the option Merge column headers. - For Systat: Each case must be written in one line. Separator (for text files): space or comma. - For SAS: For text files, use the DELIMITER option to specify the text delimiter if this is other than space. For Excel files, use the PROC IMPORT procedure with the SHEET option to specify the worksheet to import. Use the GETNAMES option to read variable names from the first row of the worksheet. Trial Statistics Result Aim: The Trial Statistics tab gives the statistics for each trial separately. Procedure Choose Analysis > Results > Statistics and Charts. The Trial Statistics tab opens. Default Layout In the Trial Statistics table, each row corresponds to a subject tracked in one arena during a specific trial. - The row headers (A) tell you which Trial, Arena, and Subject a specific cell corresponds to. Depending on your experiment design, one Trial may contain one or more Arenas, and one Arena may contain one or more Subjects. - The column headers (B) show the type of dependent variable (e.g. velocity), the body point (e.g. center point), the type of statistic (e.g. mean), and the measurement unit. Additional headers appear depending on your data selection: - Selection results. If you define two or more Result boxes in the Data profile, the name of the boxes are shown in the first cell (C). - Time bins. If you selected Results per time bin in your Data Profile, extra rows are added, one per time bin, and the headers show the corresponding time periods. For example: 0:00:00 - 0:00:20, 0:00:20 - 0:00:40, etc. (D). - Results per zone. If you selected Results per zone in your Data Profile, the zone names are displayed on rows, together with the body points in those zones (E). What you see in the result table depends on which Data profile and Analysis profile are selected on the toolbar. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Export Trial Control data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-export-trial-control-data Chapter: EthoVision XT Export Trial Control Data Choose between two ways to export the Trial Control data, depending on the file structure you require. - As dependent variables. Data are saved to additional columns of the track data file, and each sample point receives a "0" or "1" depending on whether a state (or event) is active at that time. - As a Trial Control log. Data are written to a separate file, where all events occurred during the trial (also those not included in the Analysis Profile) are stored as lines each with a time stamp. To Export Trial Control Data as Dependent Variables - Define Trial Control events and states in the Analysis profile (see Hardware and Advanced in the Analysis profile). - Choose Analysis > Export > Raw Data. Select Track & dependent variables then click Start export. Below: Part of a raw data file containing Trial Control data. The columns Frequency Light on and Duration Light on are dependent variables defined in an Analysis profile. Frequency Light on is a Trial Control event defined by the action "Light on". Duration Light on is a state interval that goes as long as the light is on. At trial time 40.48, a light device switches on. This is marked by Frequency Light On which gets the value 1. From that moment, the variable Duration Light On gets value 1. To Export Trial Control Data as a Trial Control Log - Choose Analysis > Export > Raw Data. - Select Trial Control log and click Start export. Below: Part of a Trial Control log. Activation of conditions and actions is written as an event with a time stamp. The event is written in the Event column. The next columns describe which type of Trial Control element becomes true/false/active/inactive. The Trial Control log file contains the following columns: - Trial time and Recording time. See Reading the raw data file for the difference. - Event. The type of trial control event. For an explanation of the terms, see How the trial control instructions are executed. - Rule, Condition, Action, Operator, Reference. The Trial Control element that is involved in the event described in the corresponding Event cell. - Variable, Value. The variable that is subject to an action, and the new value assigned to the variable. - Reference1..., Repeat1.... Marks the time that a sub-rule is active. Repeat indicates the number of times that sub-rule has been repeated up to that time. To export log files of the hardware devices operated during the trial, select also the Hardware log option. For more information, see Analysis of Trial Control data in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To Import Analysis Results Analysis results here refers to the table in the Trial Statistics or Group Statistics tabs. - Export the statistics result, with Excel as format. - Open the file in Excel. To Import EthoVision XT Raw Data and Dependent Variables - Export the raw data (track and dependent variables). - Open the file in Excel. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - External Data - DSI URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-dsi Chapter: EthoVision XT DSI DSI Ponemah 6.40 The following picture shows the import profile for Ponemah 6.40. With this profile you can import one or more data columns. - Note that the second column of the data file (B) contains time stamps and must be dragged to the Time series field. - IMPORTANT: Import of data from Ponemah 6.40 to EthoVision XT works when the time format in Windows is set without AM/PM. When exported, the time should be in a format like 10:57:55.000. - To export the data in Ponemah, choose Action > Start Review. Select all signals you want to export, and the time range. In the graph window, choose File > ASCII Output. Select the channels and the data range. Select the option to Include Time in Output. Next, click Convert to ASCII. The file is ready for import into EthoVision XT. DSI DataQuest A.R.T. 4.3 For DataQuest, the profile specifies that the first column of the data file (A in Data Sets) contains the time stamps. Column B contains the sync data, and the remaining columns C-G contain activity and physiological data. BIOPAC For the BIOPAC system, AcqKnowledge is the software used to record, analyze and export the data. This is an example of an export file of AcqKnowledge 5. The file contains information about the sample interval. In this case the sample interval is 2 ms. The following picture shows the Import Profile Definition window in EthoVision XT for a BIOPAC AcqKnowledge 5 file. The header contains information about the sample interval (milliseconds), and information about the channels. In this example, the ECG, heart rate, the R-R interval and R-peak height were measured. The sample rate is calculated based on the sample interval. In this case the samples are taken at an interval of 2 milliseconds. This corresponds to a sample rate of 500 Hz. Doric Doric (*.doric) data files can be exported as CSV files to EthoVision XT. The following figure shows an import profile for CSV files with multiple channels. The first column of the CSV includes the time stamps. The other columns contain data of the channels recorded. The arrows indicate where you need to drag the cell contents in the Header section and in the Data sets section in order to create a similar import profile. Polar The Polar system is used for monitoring heart rate. After data acquisition the data can be transferred to a computer (not available with all Polar systems). The data is stored in a HRM file. These HRM files can be directly imported into EthoVision XT. EthoVision XT cannot be connected to the Polar system. Therefore, Polar heart rate data and EthoVision tracking data always need to be synchronized manually. To facilitate manual synchronization of Polar heart rate data and tracking data you can do the following: - If the Polar software is running on the EthoVision XT computer: Synchronize the Polar watch with the clock of the EthoVision XT computer. Please see the Polar Precision Performance software Reference Manual for a description of how to do this. Please note that this is not possible for all Polar systems. - If the Polar software is not running on the EthoVision XT computer: Synchronize the EthoVision XT computer and the Polar computer. Synchronize the Polar watch with the clock of the Polar computer. The settings on the Polar receiver determine what header information is written to the HRM file. Please refer to your Polar manual for a detailed description of the settings. The file header contains information about date and time, the length of the recording period (00:12:54:08) and the sample interval (5 sec). It also contains information about settings of the upper and lower limit of the heart rate. Depending on the settings of the receiver, the HRM file can contain additional information. This does affect subsequent import of HRM files acquired with different types of receivers. The HRData column shows the mean heart rate (in beats per minute) over a 5-second period. Polar Precision Performance 4.01 (No Date - Time) This is an example of the Import Profile Definition window in EthoVision XT for the profile Polar Precision Performance 4.01 (no date - time) obtained with the Polar file described above. Note that in the Data definition section the cells under Start Date and Start Time are empty, meaning that the import profile does not read date and time information in the Polar file. Polar Precision Performance 4.01 This is an example of the Import Profile Definition window in EthoVision XT for the profile Polar Precision Performance 4.01 obtained with the Polar file described above. This profile reads the date and time information contained in the export file header. Note that in the Data definition section the cells under Start Date and Start Time contain the information read from the Header section (the corresponding cells in the Header section are grayed out). Interbeat Interval Data Interbeat interval data obtained with a Polar system have the same format as HRM data. However, the file does not contain the time stamps that EthoVision XT needs for time information. --- ## EthoVision XT 19 - External Data - Importing External Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-importing-external-data Chapter: EthoVision XT Importing External Data Import a Complete External Data File at Once To import an external data file: - Choose Setup > Trial List. - Click the row for the trial you want to import the data to. - Do one of the following: to import data to a specific arena or subject within that trial, right-click that arena or subject and select Import External Data. - Next, you can either: - Select a predefined Import Profile from the list under Files of type. Next, locate the external data file, select the filename and click Open. - Create a new custom import profile. Notes - To import specific data sets in an external data file in the Trial List, click the Import External Data button. See Import One or More Specific Data Sets. See Also - Create a new custom import profile Import One or More Specific Data Sets - Choose Setup > Import External Data, or in the Trial List, click the Import External Data button. - Select a predefined Import Profile from the drop-down list under Files of type. Next, locate the external data file, select the filename and click Open. A second Import External Data window shows one or more Data Set Names. The Trial list also appears. - To add external data to a trial, select one or more Data Set rows and drag-and-drop it to the Trial list. You can choose to drag-and-drop external data to a Trial, Arena, or a Subject. - Click the Import button in the Import External Data window to finish the import. EthoVision XT offers predefined Import Profiles for a number of export formats from DAQ systems. If your file type is not in the list, create a Custom Import Profile. Create a New Custom Import Profile Aim To import external data as ASCII files when EthoVision XT does not have a predefined import profile. With an import profile you create a template based on the structure of the external data file. Prerequisites - Your license for EthoVision XT includes the External Data Module. - You exported your external data as ASCII files. Procedure - Choose Setup > Import External Data. - Click the Custom Import Profiles button and then the New button. - Browse to the external data file. - Build the import profile by specifying the structure of the data file. This is done by dragging and dropping cells. To undo a selection, select the cell to which content was dropped and press Delete. Follow the procedure in these sections: - Header - Delimiters - Time Information - Data - Import a text file with the new import profile. 1 - Header EthoVision XT usually automatically detects header and data information in the file. If not, specify which part of the data file contains the header. Choose an option from the Header detection list: - Automatic (default). EthoVision XT is set to automatically detect the header and data sections in the data file. Choose one of the other options if automatic header detection does not work. - Specify tag. Select this option if the data file has a variable number of header lines and the header always ends with the same word. Specify the phrase (with either nominal or numerical information) that indicates the end of the header part of the file. If necessary, also specify the number of rows between the header line that contains this phrase and the data. For example, if the header always ends with a line containing the text [Data] and there is always an empty line before the data starts, enter [Data] in the End tag field and 1 in the Extra rows field. - Specify row number. If the data file always has the same number of rows in the header, select this option and specify the number of header rows. 2 - Delimiters EthoVision XT uses the comma as the default delimiter to separate text in the header and data sets. However, the data file may have other delimiters. If this is the case, select the correct ones from the Select header delimiters and Select data delimiters lists. You can also select multiple delimiters. Some DAQ software enables you to select the type of delimiter when saving the DAQ data to an ASCII export file. In that case, select the same delimiter in the File content section of the Profile Definition window. A comma or semicolon are advised as delimiters. 3 - Time Information Specify which cell or column contains the time information. This can be a column with time stamps, a cell with the sample rate, or a cell with the sample interval, which is the time between samples. Drag and drop the cell or column with time information to the appropriate field in the Profile definition section. - Sample rate. If the header contains a cell with the sample rate, select the Sample rate button under Timing based on in the Profile definition section. Drag the cell with the sample rate to the Sample rate box and select the appropriate unit (Hz or kHz) from the list. - Sample interval. If the header contains a cell with the sample interval, select the Sample interval button in the Profile definition section. Drag the cell with the sample interval to the Sample interval box. Select the unit of time from the list. - Time series. If the header does not contain information on sample rate, select the Time series button under Timing based on. Under Data sets in the File content section, select the column with time stamps and drag this to the Time series box. The column with time stamps now appears grayed. The Select Time Format window opens. If the time matches one of the predefined formats, EthoVision XT automatically selects one. Converted time shows the conversion of the text to time and Conversion is OK. You can also define your own format by typing an H for each number representing hours, an m for minutes, an s for seconds, and an f for each decimal of a second. Under Import Time, select one of the following options: - Relative to time zero. If the first row in the imported external data set has time 00:00:05, the time stamp of the first row of the imported data set will remain 00:00:05. - Relative to the time of the first data line. If the data set you want to import starts at 14:28:00 and has samples every 5 seconds, the first row of the imported data will get the time stamp 00:00:00. The second row will have time stamp 00:00:05. The options under Import Time are grayed out when your time stamps contain the date the file was created, in which case the option Relative to time zero is used. - Allow timestamps to be non equidistant when the time stamps do not represent regular intervals, for example 0, 490, 572, etc. 4 - Data Under Data definition in the Profile definition section there are two parts. The lilac part is labeled Header Data, where you drag cells from the lilac Header section. The green part is labeled Raw data, where you drag Data sets from the green cells in the Data sets section. - Drag the first column under Data Sets to the first empty cell in the Raw data - Data Set column. As a result, the letter of the original column appears in the cell and the column in the Data Sets section is grayed. - Locate the data set name, the unit, and optionally other information in the header, and drag those cells to the Header data cells in the same row. If you drag and drop the Start Date and/or Start Time, a window opens in which you can define the format. Accept the default format, or follow the procedure in step 3 of Time Information to change it. Multiple Data Sets - Follow the procedure above to define the next dataset. Once two datasets are defined, the Validity Check button becomes active. - Click this button. EthoVision XT now automatically fills the other rows in the Data definition field. - Check that the correct columns are selected. How the Validity Check Is Applied EthoVision XT assumes that your header and data set information are ordered in a regular way in your external data file (for example, left to right, with or without empty cells in between). For example, if your external data file contains four Data Sets in columns A, C, E, and G with columns B, D, and F empty, dragging columns A and C to the first two rows in the Raw Data column and clicking the Validity Check button will cause EthoVision XT to automatically assign columns E and G to rows 3 and 4, taking into account the empty columns between Data Sets. The distance between the columns must be the same. For example, dropping columns A and C and clicking Validity Check works, and columns E, G, I, K, etc. are automatically added to the other rows. Dropping columns A and B and clicking Validity Check also works, and all other columns are automatically added to the other rows. However, dropping A, B, and D and clicking Validity Check does not work, because there is an empty column between B and D but not between A and B. Data Sets with Missing Samples If your data set contains missing samples indicated by non-numeric symbols, specify this symbol and select the Treat as number checkbox. Alternatively, click the button next to the Treat as number field to select one or more predefined symbols. To select specific text, click , click OK, and enter this text after a comma. If text is identified by a character, select this from the Text qualifier list. Save the Import Profile When all the information is in the Import Profile Definition sheet, click the Save As button and give the profile a name. Import a Text File with the New Import Profile The newly created import profile is now in the Files of Type list. - Locate the external data file and select the filename. - Click Open. Notes - A missing sample is converted to a zero. As a result, it is plotted as a zero in the Visualization. - The import profile is stored with the extension *.eip. Edit a Custom Import Profile If you want to import an external data file that is very similar to, but not exactly the same as, another data file for which you already have an Import Profile, you can edit the existing Import Profile. - In the Import External Data window, click Custom Import Profiles. - Select the Import Profile from the list in the Import Profiles window and click Edit. In the Select Sample File group you see the original sample file behind Profile based on. - Click Browse in the Select Sample File group to select the new external data file and click Open. - Follow the instructions for Create a New Custom Import Profile. - Click Save Profile As when you are finished filling in the Data definition sheet. - Type in the name for the Import Profile and click OK. Close the Profile Definition window. - Close the Import Profiles window. Make sure you select the right Import Profile. - Select the external data file and click Open to finish the import. Note - You cannot edit the import profile for European Data Format files. Examples of Import Profiles The following DAQ systems and software have predefined import profiles: - DSI Ponemah 6.40 and DSI DataQuest A.R.T. 4.3 - BIOPAC AcqKnowledge 4.4 - Doric - Polar Precision Performance 4.0 - European Data Format files - Noldus UltraVox XT 3 --- ## EthoVision XT 19 - External Data - Independent Variables Tab URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-independent-variables-tab Chapter: EthoVision XT Independent Variables Tab The Independent Variables tab is a simplified version of the Trial List. It shows the user-defined independent variables and the Acquisition status for the acquired trials and the planned trials. Row Colors - Before acquisition, the current trial (about to be acquired) is highlighted in green. Acquisition status says Ready to start. - During acquisition, the current trial is highlighted in red. Acquisition status says Acquiring. Dependent Variables Tab In the Dependent Variables tab you can view any dependent variable in real time during acquisition, for each subject and arena. By default, it shows the following variables: Velocity and Movement. To view more variables during a trial, see Choose a Variable to View Real-Time. Important: Adding variables may reduce performance and increase missing samples. Select only the variables and its properties you are interested in. For example, if you are interested in monitoring the Immobile state during a Porsolt swim test, add the Mobility state variable, then select Immobile and deselect the other two states under Calculate for state in the Mobility State properties window. Manual Scoring Tab See Score Behaviors Manually During Acquisition. External Data Introduction to External Data Work with External Data External Data Types You can import external data, like for example heart rate, EEG, GSR or accelerometer data into EthoVision XT and synchronize these data with the tracks. EthoVision XT can import data in ASCII format with a constant sample rate or a time stamp column in the file. Note: It is also possible to import European Data Format (EDF) files, or BioSemi Data Format (BDF) files, which is the 24 bit version of EDF, into EthoVision XT. Import of EDF+ or BDF+ files, which may contain annotations, is not supported. Procedure Working with external data in EthoVision XT involves some basic steps: - When possible, connect the EthoVision XT computer to one of the input channels of the external DAQ system. This allows you to synchronize EthoVision XT and the external data automatically. See Connect EthoVision XT to the DAQ System. - Enable DAQ co-acquisition in EthoVision XT. - Acquire the trials, while the DAQ system acquires its own data. See Acquire a Trial Live for the general procedure. - After data acquisition, import the external data file(s) and assign them to a Trial, Arena, or Subject. See Import a Complete External Data File at Once. Tracking data and external data are automatically synchronized in case you used DAQ co-acquisition. If not, you can use manual synchronization. - Visualize external data together with video and acquired tracks. Notes - The external data are saved on the computer dedicated to the DAQ device, not on the EthoVision XT computer. - If you want to visualize tracks according to the values of a dependent variable, make sure that you specify that dependent variable in the active Analysis profile. To edit a profile, click it in the Experiment Explorer and make the necessary changes. Connect EthoVision XT to the DAQ System Aim To ensure that EthoVision XT sends a synchronization signal to the DAQ system during data acquisition. Prerequisites You must have: - A free USB port on your EthoVision XT computer. - A USB-to-Serial (COM) converter. - A sync cable from Noldus. This cable has connectors that depend on the DAQ system you have. Optional: Connect the two computers through a local network for easy data transfer from the DAQ system to the EthoVision XT computer. See Import External Data: General Information. Notes - It is also possible to ensure synchronicity between EthoVision XT and the DSI Ponemah system without a sync signal. See Sync the Computer Clocks for EthoVision XT and DSI Ponemah. Enable DAQ Co-Acquisition in EthoVision XT Aim To program EthoVision XT to send a synchronization signal to the external DAQ system. Procedure - In EthoVision XT, open your experiment. - Choose Setup > Experiment Settings. - Under Video Source, choose Live tracking and select the Enable DAQ co-acquisition box. Click the Edit button. - Under Predefined Settings, select the item corresponding to your DAQ system, or create a new one (see below). Notes - When you have acquired data, the Experiment Settings are read-only (settings are grayed out). - You can only co-acquire external data when you carry out Live Tracking. To Create a New DAQ Hardware Settings Profile - In the DAQ Hardware Settings window, click the New button. - A new field appears at the bottom of the list of predefined profiles. Type a name for the new profile. - Under Output device, select one of the COM ports from the list. This COM port is used to connect the EthoVision XT computer to the DAQ system. Click the Check Status button to check the availability of the port. It may be that either all COM ports on your PC are occupied, or your PC does not have a COM port. In those cases, contact Noldus for a USB-to-COM converter. - Under Signal Type, select: - On-Off if the external signals are sampled at low rate (less than 10 Hz) and without interruption (thus no scheduled sampling). - Time Code (TCAP) in all other cases. Enter the Sample rate (in Hz) with which you sample data on your DAQ system. If you want to sample data at a rate higher than 2 KHz, set 2000 Hz. Depending on the Sample rate, the Minimal sampling time changes; this indicates the minimum time the data should be acquired on the DAQ system for synchronization to work properly. - Click OK. To Delete a DAQ Hardware Settings Profile In the DAQ Hardware Settings window, select a Profile and click Delete or press Delete. To Change the Order of DAQ Hardware Settings Profiles In the DAQ Hardware Settings window, select a Profile and click the Move Up / Move Down button or press ALT-arrow down / ALT-arrow up on your keyboard. To Add a Description to a DAQ Hardware Settings Profile In the DAQ Hardware Settings window, select a Profile, click in the Description box and type in text. Click on another Profile and click Yes to save the Description. --- ## EthoVision XT 19 - External Data - On-Off vs. Time Code (TCAP) Synchronization Signal URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-on-off-vs-time-code-tcap-synchronization-signal Chapter: EthoVision XT On-Off vs. Time Code (TCAP) Synchronization Signal In order to synchronize external data and EthoVision XT tracking data, you can send out a synchronization signal with time information (SyncOut) from the EthoVision XT computer to the DAQ device. This signal is sampled by the DAQ computer and after acquisition imported into the EthoVision computer as a home coming signal where it is compared with the original synchronization signal. On-Off and Time Code (TCAP: Time Code Auxiliary Parity) are two types of signals that reflect two ways of synchronizing external data (for example, heart rate) with tracking data. On-Off This signal is sent from EthoVision XT to the DAQ device shortly after a trial is started and stopped. Note that the On and Off signal are not sent at the exact moments of trial start and stop. The difference in offset between the synchronization signal and reference signal is calculated at the start and at the end of the recording. In order for synchronization to be successful, the DAQ recording must start before starting acquisition in EthoVision XT, and end after stopping acquisition in EthoVision XT. A dialog in EthoVision XT informs you to start and stop data acquisition on your DAQ device. Furthermore, the DAQ recording should not be stopped during acquisition in EthoVision XT, which means that you cannot use the On-Off signal when performing scheduled sampling (that is, starting and stopping DAQ acquisition at regular intervals). Time Code A series of bits called a frame is sent from the EthoVision XT computer to the external DAQ device. Each frame contains the current date and time and additional information. The difference in offset between the synchronization signal and the reference copy is calculated for several time points during acquisition (by default, for 10 time points), while the gain is calculated through regression analysis of offset values obtained at different points in time (that is, different frames). Therefore, synchronization of tracking and external data is more accurate using the Time Code signal because it is done for more than two offset points and not just at the start and stop of acquisition as with the On-Off signal. Import External Data in EthoVision XT Import External Data: General Information External Data Files To import external data you need to link it to an acquired Trial, an Arena or a Subject. You can import external data with the following characteristics: - It is stored in ASCII format. - The sample rate is constant, or when it is not constant, the data file contains time stamps. - The file contains at least 15 data lines. It preferably contains a header with information describing the data sets. This information about the data set, such as data set name, date and time information, sample rate, is typically stored in the header section of a DAQ export file. - You can import European Data Format (EDF) or BioSemi Data Format (BDF) data files. Import of EDF+ or BDF+ files is not supported. Notes - It is not necessary that external data are recorded when you do the tracking; for example, when you track from video files. However, you must ensure synchronization between the external data and the video file. - You can only import external data into an acquired Trial. This is indicated in the Trial List by 'Acquired' in the System Variable Status column. Data Sets Within a File An external data file can contain one or more data sets. For example, you test three rats, each in its own arena, and for each rat you have acquired ECG data. The resulting external data file contains three ECG data sets. In EthoVision XT you now have the option: - To link the complete external data file (i.e. all three data sets at once) to a Trial, Arena, or Subject. - To link one or more data sets from an external data file to a Trial, Arena, or Subject. --- ## EthoVision XT 19 - External data - state URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-state Chapter: EthoVision XT Definition Dependent variable with two possible values (0 and 1) calculated from an imported data signal, resampled to the same sample rate as the EthoVision XT sample rate. The value of the state variable is calculated per sample from the values of the corresponding resampled variable, relative to one or two thresholds. Top: Heartbeat. Bottom: Heartbeat state, defined in the Analysis profile as "Heartbeat > 400 bpm, with Downsampling= Mean value, Upsampling= Last value, Averaging interval =1". For clarity, it was renamed to Heartbeat state: hb >400. How to Specify an External Data Variable "State" - Click the Add button next to the [data set name] state. - Under Select, choose the Downsampling method (default: Mean value) and the Upsampling method (default: Last value). - Under Outlier filter, select the Averaging interval (default: 1). See Averaging interval in External data (resampled). - Under State threshold, specify that the state is scored when the Signal is: - above (>=) or below (<=) a threshold value x. - within a range (>= x and <= x) or outside a range (<= x and >= x). Enter the thresholds you require. - Complete the procedure to add the variable. - Plot Integrated Data, or calculate the statistics. The resulting state (frequency and duration) is much dependent on what you choose as downsampling/upsampling methods. Below: Effect of different upsampling methods on a state variable Temperature state. Original temperature signal sampled every minute. Variables resampled at 25 Hz. The state variable is scored when the resampled value is >= 30 ºC, using the methods Last value, Linear interpolation, Missing value, and Zero value. Note that Temperature state in cases 4 and 5 gives very short states, because most of the data points in the corresponding Temperature resampled variable are missing or zeros, respectively. NOTE: When calculating states, if the sample with a valid variable value is followed by missing samples, EthoVision XT keeps the calculated value of the state for the next three missing samples. Below: Zoomed-in view of the previous picture for Temperature state upsampled with Missing value, and Temperature state upsampled with Zero value, around 240 s. A state is scored when the resampled value is >= 30 ºC. For simplicity, Averaging interval = 1. When calculating states, if the value of the resampled variable is followed by missing values, like in Temperature - "Missing", the calculated value of the state is kept for the next 3 samples. This is the reason why the Temperature state - "Missing" around time 240 s lasts 4 samples. In the case of upsampling with Zero value, the state is assigned only to the current sample. How to Retrieve States from an Imported Signal In the following example, the file containing the data set Phase with possible values 1, 2 and 3 is imported. If you want to retrieve the original states with their duration: - In the Analysis profile, define three Phase state variables, and rename them to, for example, Phase 1, Phase 2, and Phase 3. - For each state variable, set the appropriate thresholds. For example, for Phase 1: Signal is <= 1.5. - Plot the variables to compare them with the original signal. From top to bottom: original signal, resampled signal, states calculated using thresholds. Right: threshold for Phase 1. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - External Data - Sync the Computer Clocks for EthoVision XT and DSI URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-sync-the-computer-clocks-for-ethovision-xt-and-dsi Chapter: EthoVision XT Sync the Computer Clocks for EthoVision XT and DSI Ponemah Aim To ensure high synchronicity between EthoVision XT data and physiological data collected with DSI Ponemah. Background Information Synchronization between the EthoVision XT system and the DSI Ponemah system is based on a Network Time Protocol (NTP), a networking protocol for computer clock synchronization. The NTP Time Server runs on the DSI Ponemah computer and acts as time reference. The NTP Client runs on the EthoVision XT and adjusts that PC's clock time based on the NTP Time Server. Prerequisites - The NTP Server is already installed on the DSI Ponemah computer. - You need two installation files: - ntp-time-server-monitor-104.exe (NTP Server Monitor) - ntp-4.2.8p15-v2-win32-setup.exe (NTP Client) Procedure 1 - DSI Ponemah - On the DSI computer, create the following folder structure: - C:\ - C:\NTP\ - C:\NTP\ETC\ - C:\NTP\Installation\ - Copy the file ntp-time-server-monitor-104.exe to C:\NTP\Installation. - Double-click the file and follow the instructions. As the Destination Folder, choose C:\NTP. As the Select Program Manager Group, keep Meinberg selected. Click Next and continue installation. - When installation is done, a new icon NTP Time Server Monitor appears on the desktop. - Right-click on the icon and choose Run as administrator. - In the NTP Time Server Monitor window, click the NTP Status tab. You should see a line highlighted in green, which indicates that the service is running correctly. In the next steps you take note of the IP address of the DSI computer. Note that the DSI computer has two network cards; one is connected to the matrix (2.0) and the other one should be connected to the network which connects that computer to the EthoVision XT computer. - On the DSI computer, open the Network Connections. - Locate the item that corresponds to the network port to be connected to the EthoVision XT computer. To find the correct port, temporarily disconnect the network cable from one of the network ports and check which item shows the message Network cable unplugged. That helps you find which item corresponds to which network port. - Right-click the network adapter item and choose Status, then click Details. - Take note of the IP address next to IPv4 Address. Procedure 2 - EthoVision XT This procedure is meant to install the NTP Client on the computer which runs EthoVision XT. The NTP client adjusts the computer clock in such a way that it will be in sync with the clock of the NTP Server. This ensures that the system time of the EthoVision XT computer is in sync with the system time of the DSI computer. - On the EthoVision XT computer, create the following folder structure: - C:\NTP - C:\NTP\ETC - C:\NTP\ETC\ntp.conf - C:\NTP\Installation - C:\NTP\Installation\ntp-4.2.8p15-v2-win32-setup.exe - C:\NTP\Installation\ntp-time-server-monitor-104.exe - Double-click ntp-4.2.8p15-v2-win32-setup.exe. - Choose C:\NTP as the installation folder. Click Next and under Choose Components keep the default settings. - Under Files have been installed, keep C:\NTP\etc\ntp.conf selected. This is the file that you copied in the first step, and contains all the necessary settings, except for the IP address of the DSI computer. De-select Create an initial configuration file with the following settings. - Click Next and under Setting Up NTP Service, select Create and use a special NTP account (recommended). Leave all selections as they are. - Click Next and enter a name and password, then complete installation. After this, the service is installed and started automatically. If the service does not start after the installation because you used an existing network account, do the following: (1) Start Services in Windows (see Administrative Tools in the Windows Control Panel). (2) Select the Network Time Protocol Daemon service. (3) Change the Logon properties to the desired account (when you do that, the account will be given service rights). (4) Start the service. - On the EthoVision XT computer, double-click the file ntp-time-server-monitor-104.exe (for details see Procedure 1 above). - When installation is done, run the NTP Time Server Monitor as administrator and click the NTP Configuration file tab. There, change the IP address by entering the one you found at the end of Procedure 1. Once ready, click the Save configuration button. At this point you will be asked to restart the service. You can always restart the service in the Windows Services. Source: EthoVision XT 19 Help - External Data, Noldus Information Technology --- ## EthoVision XT 19 - External Data - Synchronize Data Manually After Import URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-synchronize-data-manually-after-import Chapter: EthoVision XT Synchronize Data Manually After Import Aim To adjust the offset between external data and video/track data. Note: You change the offset of the original signal. The offset is automatically applied to all the EthoVision XT variables derived from that signal. Choose Analysis > Results > Integrated Visualization. Procedure - From the lists available on the toolbar, choose the Track smoothing profile, the Data profile, the Analysis profile and the trial to visualize. - Make sure that the signals are well visible; zoom in/out if necessary. - If you want to re-synchronize using an event visible in a specific video frame, position the video to that frame. - Click the External data synchronization button on the toolbar, or choose Show/Hide > External data synchronization. If no original signal is displayed in a chart, EthoVision asks you to select the original signal for synchronization. Take note of the original start and stop time in the Synchronize external data window. If you change the offset and click OK, the start/stop times are overwritten and cannot be recovered. - You can synchronize data in two ways: - In the Synchronize external data window, enter the new Start date and time and the Stop date and time for the chosen signal. - In the plot area, hover the mouse over the original signal and drag to the position you require. While you drag the mouse, the time plot of the original signal is shifted to the left or to the right. The Synchronize external data window shows the new Start and Stop time of the original signal. Release the mouse button when ready. - Select the option Apply synchronization to all signals originating from the same data file if you also want to apply that offset to the EthoVision XT variables derived from the other signals imported from the same data file. Make sure to keep this option selected when you import data sets from the same data file and you want to maintain the original offset for all those data sets. - When ready, click OK. Notes - The shift in the offset is also applied to signals derived from the original signal, which are not currently visualized. - After clicking OK, the shift in offset cannot be undone. To restore the original offset you must know the original Start and Stop time and enter them in the Synchronize external data window. - To stretch the data in time, enter new values for Start and Stop time in such a way that the duration of the data set is longer than the original. First enter Start time, then Stop time. - To shrink the data in time, enter new values for Start and Stop time in such a way that the duration of the data set is shorter than the original. First enter Start time, then Stop time. - If your data plots include EthoVision XT variables derived from signals other than the one you synchronize, these are not synchronized automatically, unless the original signals come from the same file and you select Apply synchronization to all signals originating from the same data file. In all other cases, to synchronize those variables, open the signal they are derived from and repeat the procedure above for that signal. - Re-synchronization may affect your data selection when this contains Nesting functions based on those external data. For example, your Data profile contains a Nesting function based on Temperature state, which selects the intervals when Temperature > 30 °C. If you re-synchronize Temperature and Temperature state, then also the intervals based on Temperature state will shift accordingly. Plot the data to check the changes. - To undo the changes and return to the current offset between data sets, click Reset in the Synchronize external data window. - If you synchronize external data at least once, re-opening the Synchronize external data window and clicking Reset does not restore the offset when you imported the data. It simply restores the last saved offset. Other Ways to Ensure Synchronicity Between Video and Data Streams Aim Whenever you want to ensure high synchronicity between your video and the external data streams, for example EMG, this topic describes the possible solutions. This topic applies to Basler digital cameras. Method 1 - Send a Signal at Every Video Frame Many Basler digital cameras including the acA1300-60gm GigE camera have a 6-pin I/O connector on the back. Pin number 2 is for input (named Line1 in Pylon Viewer), while pin number 4 is for output (Out1 in Pylon Viewer). You can connect pin 4 to a channel of the DAQ system that reads the time that the video frame is sent out. Note: Which pin number serves a specific function may vary depending on the camera model. Please refer to the camera documentation. - Set the camera for example to free-running at 60 fps and get an electrical signal on the camera output Out1 pin when the camera makes a new frame. Settings can be made using the Pylon Viewer application. For details, see the Pylon Viewer manual and the camera manual. - Connect the camera output to the data recording channel. This way you know down to microseconds accuracy when the camera creates a video frame. Method 2 - Send a TTL Pulse to the DAQ System For this you need a USB-IO box and the Trial and Hardware Control add-on module. - Connect a TTL port of the USB/IO box to one of the channels of the DAQ system. For this you need a cable with a RJ45 connector at the end of the USB-IO box and a connector at the other end that matches the DAQ system. - In the Trial Control Settings of EthoVision XT, make a sub-rule with an action on the chosen TTL port that sends a pulse of 1 second at regular intervals, for example every 5 seconds. - During the trial, the pulses are recorded by the DAQ systems. For more information: - The chapter Experiments with Calcium Imaging in the EthoVision XT 19 - Application Manual, which includes an example with the Inscopix nVoke system. - The EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Note: To connect the camera to a DAQ system, you can use the standard cable available from Basler, or make your own using a Hirose connector HR10-7P-6S(73). --- ## EthoVision XT 19 - External Data - Synchronize Data Manually at Import URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-synchronize-data-manually-at-import Chapter: EthoVision XT Synchronize Data Manually at Import Aim To synchronize the tracking data and the external data if it was not possible to connect the EthoVision XT computer and the external DAQ system. You can manually synchronize external and tracking data during import of external data into EthoVision XT: - Shift the offset. This means that the complete external Data Set is shifted in time. The duration of the external Data Set remains unchanged. Shifting is done by changing the Start Date/Time of a Data Set. - Stretch or shrink the external data set. This means that the duration of the external data set is changed to match the duration of an acquired Trial. Stretching the external data set is done by changing the Start Date/Time and/or the Stop Date/Time. This way you can either stretch or shrink the duration of the data set. Manual synchronization of external data and tracking data is accurate to within one millisecond. However, note that the sample rate of EthoVision XT, and therefore the resolution of the derived data, can never be higher than the video frame rate. When Do I Need to Shift the Offset? For example, you started acquisition on your DAQ system 10 seconds after you started acquisition in EthoVision XT. During import, shift your external data set 10 seconds to match the offset of the Trial. When Do I Need to Stretch/Shrink? You need stretching/shrinking in the scenario that you carry out acquisition during a prolonged period of time during which the clocks of the EthoVision XT computer and the DAQ computer start running out of sync (you started with synchronized clocks). Example: You carry out tracking for 24 hours and after this period you notice that the DAQ computer is 10 seconds ahead of the EthoVision XT computer. This means you need to shrink the external data set by changing the Stop Time of the data set to 10 seconds earlier. To Facilitate Manual Synchronization You can facilitate manual synchronization by synchronizing the clock of the EthoVision computer and the computer on which the external DAQ system is running, before acquisition. You can use one of the following methods: - If the computers are situated next to each other, double-click the clock in the taskbar at the bottom of the screen on both computers. In the Date & Time tab, set both clocks to the same time. - In all cases: use an online clock, when connected to the Internet, to set both clocks to the same time; or use NetTime, a simple Network Time Protocol (SNTP). If, for some reason, it is not possible to synchronize the computer clocks there is a more advanced method to facilitate manual synchronization. This method only works when the external data file contains information about date and time of acquisition. - Acquire tracking data in EthoVision XT and external data on the DAQ system and make sure on both systems a synchronization event is recorded. For example, you can use a relay to create a peak on your DAQ system and simultaneously switch on a light which is visible in the video. - Import the external data into EthoVision XT. - Visualize the data by choosing Analysis > Results > Plot Integrated Data. Go to the position in the video where the swiping action occurs. Note down the time stamp. - In the external data window, move the hairline to the position where the peak, caused by the swiping action, occurs. Note down the corresponding time. Example: The swiping action in the video occurred at 1.01. The corresponding peak in the external data occurred at 0.85 in the external data plot, so 16 seconds earlier. - In the Trial list, remove the external data. To do so, select the columns that contain the external data sets, right-click and select Delete Variable. - Change the start time of the external data file by doing one of the following: - Open the external data file (for example, with Notepad) and change the start time. - Import the external data file. In the Import External Data window, you can change the start time of the external data set. Example: The difference in offset was 16 seconds (with the external data starting earlier than the tracking data). This means that the start time of the external data set should be set to 16 seconds later. - If you have edited the external data file, re-import it into EthoVision XT. Manual synchronization of tracking data and external data is accurate to within one millisecond. To Shift an External Data Set - Import the external data that was simultaneously acquired during live tracking into EthoVision XT. - In the Import External Data window, double-click the Start Date/Time cell of the external data set you want to shift. - In this cell, click the year, month, day, hours, minutes, seconds or milliseconds and change them by using the arrow-up/arrow-down on your keyboard, the up/down arrow at the right side of the cell, or just type in the desired value. When you change the Start Date/Time of a Data Set, the Stop Date/Time also changes. As a result the duration remains the same. - Finish import. To Stretch/Shrink an External Data Set Stretching or shrinking can be used in the unlikely case that during acquisition the clock of the external DAQ system starts running out of sync with the clock of the EthoVision computer. This probably only occurs when live tracking is performed for a prolonged period of time. For example, in EthoVision XT, the clock time is determined by the camera frame rate. If the camera frame rate is not accurate, for example when a low-end consumer model is used, the time stamps in EthoVision gradually become out of sync with the DAQ computer clock. Then you need to manually increase or decrease the duration of the external data set. - Import the external data that was simultaneously acquired during live tracking into EthoVision XT. Shift the external data set if necessary. - In the Import External Data window, double-click the Stop Date/Time cell of the external data set you want to stretch. - In this cell, click the year, month, day, hours, minutes, seconds or milliseconds and change them by using the arrow-up on your keyboard or the up-arrow at the right of the cell. You can shorten the external data set by changing the Stop Date/Time to earlier. - Finish import. --- ## EthoVision XT 19 - External Data - UltraVox XT 3 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-external-data-ultravox-xt-3 Chapter: EthoVision XT UltraVox XT 3 Background Information UltraVox XT is software for analysis of ultrasound emitted by rodents and other animals. EthoVision XT can import UltraVox XT files (ETX) using a specific import profile. The following picture shows an example of an ETX file for EthoVision XT 11 and later. The first column contains the time stamps in milliseconds. The other columns show 0 (not a call start) or 1 (call start time). The 0 in the row following a 1 marks the end of that call. Each column represents a call category (call name, or call name*pattern label). Note that the time stamps are not equidistant. The UltraVox XT 3 Import Profile The following figure shows an example of the Import Profile Definition window in EthoVision XT for the import profile of UltraVox XT 3. In the Data definition section, the cells under Data Set Name contain the information read from the Header section (the corresponding cells in the Header section are grayed out). The cells in the Type column contain the call types and the green cells in the Data Set section contain the data sets. Install the UltraVox XT 3 Import Profile If you do not see UltraVox XT 3 in the list of import profiles when you attempt to import the call data (that is, during Import a complete external data file at once), it may not be installed. Install the import profile from the UltraVox XT installation USB Flash drive. - Close EthoVision XT. - On the UltraVox XT 3 installation USB Flash drive, open the folder Extras\Import Profiles. - Double-click the file EthoVision XT 11 and Newer.bat. - You should now see the UltraVox XT 3 import profile in the list. Notes - The UltraVox XT 3 import profile is installed in the following folder: C:\ProgramData\Noldus\Common\Profiles. It includes the folder UltraVox XT 3 and a file, UltraVox XT 3.eip. - You can find the UltraVox XT installation files on my.noldus.com. Log in, and locate Downloads > UltraVox XT > Current Version. European Data Format Files European Data Format (EDF) files and BioSemi Data Format (BDF) files are binary files. EDF files are 16 bit and BDF files are 24 bit. The import profile for EDF and BDF files cannot be edited, as for BIOPAC and other import profiles. Simply import the files by selecting the European Data Format in the import window. Notes - Import of EDF+ and BDF+ files, which may contain annotations, is not supported. Synchronization of Tracking Data and External Data Synchronize Data Automatically Aim: To synchronize EthoVision XT data and external data using the synchronization signal sent to the external DAQ system during live tracking. Procedure: - Import the external data that was simultaneously acquired during live tracking into EthoVision XT. - In the Import External Data window, you see one or more Normal Data Sets (indicated by a diagram icon) and one or more Sync Data Sets (indicated by a clock icon). The Link Variable cell for a Sync Data Set shows which Trial was acquired simultaneously with the external data. A Sync Data Set is automatically detected when you use the Time Code (TCAP) synchronization signal. When you use the On-Off signal, it may be necessary to select Sync Data Set from the context menu to tell EthoVision XT that the data set contains the synchronization signal. In the Import External Data window, right-click the Data Set that you want to change to Sync Data Set and select Sync Data Set. - If necessary, adjust the Synchronization Settings or proceed to step 4. Click the Synchronization Settings button to open the Synchronization Settings window. Here you can set values for the following parameters that determine how the information from the synchronization signal is extracted from the imported external data file (default values in brackets): - Number of offset values (10) is the number of time points in the synchronization signal used to calculate offset points. This only applies to the Time Code signal. The offset values are used for the calculation of average offset and gain. A higher value increases the accuracy of synchronization, but also increases calculation time. - Smoothing factor (1) is the number of sample points over which an average signal level is calculated. A higher value reduces spikes on the signal, but also reduces the time accuracy of the synchronization. The Smoothing Factor is used for both On-Off and Time Code signal. - Signal-to-noise-ratio (50) determines the tolerance for detecting high-low signal transitions. A higher value increases this tolerance, but also increases the chance of detecting false transitions. - Number of samples prescan TCAP (180000) is the maximum number of sample points used for auto-detection of a Time Code signal in the DAQ samples. For example, 180 seconds at 1 kHz or 30 minutes at 100 Hz. This setting only applies when you started your DAQ system before you started tracking in EthoVision XT. Click in the boxes to set a value for each of the parameters. Click Defaults if you want to return to the default values or click OK to finish. - In the Import External Data window, select one or more Data Sets you want to link, click on one of the Data Sets with the left mouse button, keep the left mouse button pressed and link the Data Sets with a drag-and-drop action to the corresponding Trial, Arena or Subject. - Click Import to finish linking the Data Sets. Notes - The Synchronization Settings button in the Import External Data window is only available if Enable DAQ co-acquisition is selected in the Experiment Settings. - The information in the synchronization signal is sampled by the DAQ system. During import into EthoVision XT some digital signal processing takes place to deal with noise, signal distortion, spikes etc. This processing is determined by the Synchronization Settings above. --- ## EthoVision XT 19 - File locations URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-locations Chapter: EthoVision XT Program Folder The default folder for EthoVision XT is C:\Program Files\Noldus\EthoVision XT 19 Experiments Folder The default folder for EthoVision XT experiments is C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments. Each experiment has its own folder, the experiment folder. An experiment folder contains the following sub-folders: - Bitmap Files. Contains the background images that were used in the Arena Settings and the reference images that were used in the Detection Settings. - Configuration Files. Contains the configuration files that are created when you set the connection between EthoVision XT and hardware devices. - Data Files. Contains the binary track files acquired during acquisition. - Export Files. When you export your track data, manually scored behaviors, analysis results or the experiment's GLP log files, the export files are, by default, stored in this subfolder. - External. When you import external data files, they are stored in this subfolder. In addition, the subfolder contains the sync-out files that were used for external data co-acquisition. - Intermediate. This folder contains intermediate results. - Log. Contains the log files if your experiment is set for Quality Assurance (GLP experiment). - Media Files. This is the default location for media files that have been recorded during the experiment. - Temp. This is a folder where temporary files are stored. It is usually empty. Import Profiles The default folder for profiles for import of physiological data is C:\ProgramData\Noldus\Common\Profiles. The Log File for Technical Support Locate the file in: C:\ProgramData\Noldus\EthoVision\XT 18\Log. The Dump Files for Technical Support Our Technical Support department may also request the dump files EthoVision XT [version number].dmp. You can find the dump files in the following locations: - For Noldus debug-mode dump files: C:\Users\[user name]\AppData\Local\Temp. Tip: To access this folder, in the Windows Search field type %temp%. - For user-mode dump files: C:\Users\[user name]\AppData\Local\CrashDumps A user-mode dump is a dump created for a specific process, for example an application like EthoVision XT. Notes - The AppData folder may be hidden on your computer. If so, in the File Explorer, from the View menu select Options and then Change folder and search options. Click the View tab and make sure that under Hidden files and folders the option Show hidden files, folders and drivers is selected. - If EthoVision XT did not create a DMP file, do the following: - Start EthoVision and use the system until it freezes. Let the software sit there frozen and proceed with the instructions below. - Navigate to C:\Windows\SysWOW64, double-click on a file called Taskmgr.exe. The Task Manager opens. - On the Processes tab, right-click on EthoVision XT and select Create dump file. - Wait until a message pops up telling you the location of the DMP file (likely here: C:\Users\\AppData\Local\Temp\EthoVision.DMP). - Close EthoVision XT, copy the DMP file and send it to Technical Support. Back Up an Experiment Aim: To keep a safe copy of your data, or transfer an experiment to a different computer. Prerequisites - The second computer must have EthoVision XT installed, with a version equal or more recent than that in the first computer. - Note that the hardware key is necessary to acquire the data, not create or restore the backup file. Procedure - Choose File > Make Backup. - In the Backup Experiment window, enter a name for your experiment backup file, and browse to the location in which you want to store your experiment backup file. - Choose the backup options (see below). - Copy or send the *.evz file to the final destination. - Restore the backup on the second computer (see below). Backup Options Select whether you want to: - Include Media Files: These are the video files stored in the Media Files folder of that experiment. Important: Video files used in that experiment but stored in other locations are not copied to the backup file. - Include Export Files: These are the result files and image files stored in the Export Files folder of that experiment. - Include External Data Files: These are the physiological data files stored in the External folder of that experiment. - Make backup read-only. When you select this option you get a warning in case you (accidentally) delete the backup file. Notes - The backup file has the extension *.evz. The file name must not contain any of the following characters: / : * ? \ " < > | . ; - Important: Your backup files can get very big if you include your media files. - If you have recently carried out batch statistics calculations, the backup file may be unnecessarily large. To reduce file size, for each Track Smoothing profile in your experiment click two times a Track Smoothing option (see details below). Next, make a backup. - Make sure that your media files, export files and external data files are within the experiment folder, otherwise they will not be included in the backup. - You should store the backup file on a secure medium (preferably a network drive), in a separate location. - When you carry out batch statistics calculations, EthoVision XT stores the results in a number of files, one for each combination of Track Smoothing profiles, Data profiles, Analysis profiles, dependent variable, track, etc. These files are stored in the Intermediate sub-folder in the experiment folder. A large number of result files can make the backup file exceedingly large, especially when you deal with a large number of tracks and/or profiles. To remove the result files, open a Track Smoothing profile that you used for analysis and click an option two times, whether that option was selected or not. Do this for all Track Smoothing profiles that you used for analysis. Next, make a backup of your experiment. To restore the batch calculation results, repeat the batch calculation procedure. To Restore an Experiment from the Backup File - Choose File > Restore Backup, or in the EthoVision Startup window, under Restore experiment, click Restore backup. - Browse to the location where your backup file is stored, select it and click Open. - Browse to the location where you want to save the experiment and click OK. The experiment folder and all associated files of the experiment are restored. To Delete a Backup File Do one of the following: - Choose File > Restore Backup. In the window that opens, click the backup file you want to delete and press Delete. Click Yes to confirm. - In Windows File Explorer, browse to the experiment backup file (*.evz) and delete it. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - File Management - Back Up an Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-back-up-an-experiment Chapter: EthoVision XT Back Up an Experiment Aim To keep a safe copy of your data, or transfer an experiment to a different computer. Prerequisites - The second computer must have EthoVision XT installed, with a version equal to or more recent than that on the first computer. - Note that the hardware key is necessary to acquire the data, not to create or restore the backup file. Procedure - Choose File > Make Backup. In the Backup Experiment window, enter a name for your experiment backup file, and browse to the location in which you want to store your experiment backup file. Choose the backup options (see below). - Copy or send the *.evz file to the final destination. - Restore the backup on the second computer (see below). Backup Options Select whether you want to: - Include Media Files: These are the video files stored in the Media Files folder of that experiment. Video files used in that experiment but stored in other locations are not copied to the backup file. - Include Export Files: These are the result files and image files stored in the Export Files folder of that experiment. - Include External Data Files: These are the physiological data files stored in the External folder of that experiment. - Make Backup Read-Only: When you select this option you get a warning in case you accidentally delete the backup file. Notes - The backup file has the extension *.evz. The file name must not contain any of the following characters: / : * ? \ " < > | . ; - Your backup files can get very big if you include your media files. - If you have recently carried out batch statistics calculations, the backup file may be unnecessarily large. To reduce file size, for each Track Smoothing profile in your experiment click two times a Track Smoothing option. Next, make a backup. - Make sure that your media files, export files and external data files are within the experiment folder, otherwise they will not be included in the backup. - You should store the backup file on a secure medium (preferably a network drive), in a separate location. - When you carry out batch statistics calculations, EthoVision XT stores the results in a number of files, one for each combination of Track Smoothing profiles, Data profiles, Analysis profiles, dependent variable, track, etc. These files are stored in the Intermediate sub-folder in the experiment folder. A large number of result files can make the backup file exceedingly large, especially when you deal with a large number of tracks and/or profiles. To remove the result files, open a Track Smoothing profile that you used for analysis and click an option two times, whether that option was selected or not. Do this for all Track Smoothing profiles that you used for analysis, then make a backup of your experiment. To restore the batch calculation results, repeat the batch calculation procedure. To Restore an Experiment from the Backup File - Choose File > Restore Backup, or in the EthoVision Startup window, under Restore Experiment, click Restore Backup. - Browse to the location where your backup file is stored, select it and click Open. - Browse to the location where you want to save the experiment and click OK. The experiment folder and all associated files of the experiment are restored. To Delete a Backup File Do one of the following: - Choose File > Restore Backup. In the window that opens, click the backup file you want to delete and press Delete. Click Yes to confirm. - In Windows File Explorer, browse to the experiment backup file (*.evz) and delete it. Settings and Profiles You can store your favorite options in Settings and Profiles that apply to specific procedures. Settings and profiles are visible in the Experiment Explorer. Except for Experiment Settings and Manual Scoring Settings, you can store multiple settings for different situations, for example different Trial Control settings to acquire trials of different durations. --- ## EthoVision XT 19 - File Management - Create a New Experiment from Scratch URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-create-a-new-experiment-from-scratch Chapter: EthoVision XT Create a New Experiment from Scratch Aim To create an experiment without predefined settings. You can also create an experiment in EthoVision XT using a template, for example for a Morris Water Maze test, or a Radial Maze test, and for a specific animal, like the rat, mouse, or zebrafish. See Create an Experiment from a Predefined Template. Procedure - Choose File > New, or in the EthoVision XT Startup window, under New Experiment, click New, or press Ctrl+N. - In the New Experiment window, enter a name for your experiment. - Browse to the location in which you want to store your experiment. Do not create an experiment on a removable disc, like a USB Flash drive or an external hard disk. - Additional options: - Select GLP Experiment if you want EthoVision XT to support you in making a Quality Assurance-compliant experiment. For this, you need the Quality Assurance add-on module. - Select DanioVision Experiment if your PC is connected to a DanioVision system and you want to create a DanioVision experiment. - Select Live Mouse Tracker Experiment if you want to import Live Mouse Tracker data. For this, you need the Live Mouse Tracker add-on module. See Live Mouse Tracker: Workflow. - Click OK. Notes - You can find the experiment file (*.evxt) in a folder with the same name as the experiment. See File Locations for the default experiment locations. You can specify the default experiment location during installation. You can change it any time in the Preferences for Default Folders. - If you select DanioVision Experiment, the EthoVision XT interface is adjusted for DanioVision. Unnecessary functions like the Manual Scoring Settings are not available. Detection settings are optimized for detection of zebrafish larvae and the arenas are detected automatically. For more information, see the DanioVision DVOC-0041 - Reference Manual. Save an Experiment Procedure Choose File > Save or press Ctrl+S. Notes - You can also choose to save the data automatically at regular intervals. Choose File > Preferences > Auto Save, select Enable Auto Save and enter the auto-save interval. - When you make changes to your experiment, e.g., changes in settings, these are saved with save or auto-save. - During data acquisition and track editing, data are saved to file immediately. Save an Experiment with a Different Name Aim To create a copy of an experiment, with a different name and saved in a different location (optional). Do not rename the experiment file *.evxt and any other files within the experiment, as that would invalidate the data within the experiment. Instead, save the experiment with a different name. Do not save experiments within the folder of another experiment. Procedure - Open the experiment in EthoVision XT. - Choose File > Save As. - Enter the new experiment name and choose the destination folder. Notes - By default, the destination folder is the same folder as that of the original experiment. - When you save an experiment with a different name, a new experiment folder is created in the destination folder with the same name as the experiment. Open an Existing Experiment Procedure Choose one of the following: In EthoVision XT - In the EthoVision XT Startup window, under Open, click one of the experiments in the recent experiment list. To open a different experiment, click Browse and open the folder where your experiment is stored. Select the file with the extension evxt and click Open. - Press Ctrl+O. Browse to the location where your experiment is stored, select the file with the extension evxt and click Open. - Choose File > Open. Browse to the location where your experiment is stored, select the file with the extension evxt and click Open. With the File Explorer - Using the Windows File Explorer, open the folder where your experiment is stored. Right-click the file with extension evxt and click Open or Start Experiment. Notes - You can open an experiment saved in older versions of EthoVision XT. - You cannot open experiments made in newer versions of EthoVision XT. Use the newest version to open that experiment. - GLP compliant experiments that have been made with EthoVision XT 12 or earlier cannot be opened in EthoVision XT 19. Delete an Experiment Aim To remove an experiment from your computer. If video files are included in the experiment folder, these files will be deleted. Procedure - In the Windows File Explorer, browse to the experiments folder. - Click the folder of the experiment that you want to delete and press Delete, or right-click that folder and select Delete. --- ## EthoVision XT 19 - File Management - Effects on the Coding Scheme URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-effects-on-the-coding-scheme Chapter: EthoVision XT Effects on the Coding Scheme If you import manually scored data without creating a coding scheme in advance, at import of the first file The Observer creates a coding scheme with all behaviors contained in that file. By default, all behaviors are put in a start-stop group named Behavior1. To re-arrange the coding scheme, delete the observation just imported, move the behaviors of Behavior1 to the groups they belong to, and re-import the data. Independent Variables The Observer does not import the independent variables from EthoVision XT. You must define those variables in the Observer's Independent Variables List and assign the values of those variables to each imported file. You can find those values in the headers of the original export files. Data From Multiple Arenas If your setup includes multiple arenas, for each trial you import one file per arena. If you want to keep data from different arenas (in the same trial) in the same observation, you can import the files of the second, third, etc. arena in the same observation as that of the first arena. To do so, follow these steps: - Follow the procedure above for the first arena. Right-click the name of the resulting observation and select Properties. Edit the observation name by giving a name that specifies the trial only, not the arena (for example, Open Field Trial 12). - For the second, third, etc. arena file, instead of following step 6 of the procedure above, in the Project Explorer right-click the observation name and select Import Observational Data, then follow the rest of the procedure. The files are imported in the observation of the first arena as separate event logs. Rename each event log in such a way that it clearly indicates the arena from which it was obtained. To Import Video in The Observer XT - Open the observation, and from the Observe menu select Video, then Open in Current Observation, and select the video file. - Choose the option below that applies: - If the video file was obtained with programs other than EthoVision XT, or if you tracked from video previously recorded with EthoVision, take note of the difference between the Start time and the Video start time (you can find these in the headers of the raw data export file). This difference is 0 only if you start the trial from the first video frame. Also, take note of the value of Recording after (also available in the export file). Calculate the value of Offset = Start time - Video start time + Recording after. - If the video file was recorded with EthoVision while doing live tracking, take note of the value of Recording after (you can find this in the headers of the raw data export file). In your case Offset = Recording after. - In The Observer XT, click the Offset button. - Then choose Numerical Offset and locate the imported event log. In the corresponding cell, enter the Offset calculated as described above, and make sure that the sign stays positive (+). - Open the observation and click the start line of the event log. The video is positioned to the point that the tracking started. See Also - Trial vs. Track - For more information on creating an import profile for The Observer XT, see Importing Other Observational Data in The Observer XT Help. Camera Installation Main Topics and Tasks - Choose Your Camera - Install GigE Cameras - Install USB 3.0 Cameras - Install Analog Cameras - The Test Environment Choose Your Camera Learn About - Types of Cameras - Cameras Supported by EthoVision XT - Using Multiple GigE Cameras Source: EthoVision XT 19 Help - File Management, Noldus Information Technology --- ## EthoVision XT 19 - File Management - Export the Raw Data (Track and Dependent Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-export-the-raw-data-track-and-dependent-variables Chapter: EthoVision XT Export the Raw Data (Track and Dependent Variables) Aim To export the x,y coordinates and the subject size for each sample together with the values of the dependent variables selected in the currently active analysis profile, including manually scored behaviors and automatically recognized behaviors. The raw data file includes the independent variables that you defined in the Trial List. Procedure - Choose Analysis > Export > Raw Data, or in the Experiment Explorer under Analysis - Export click Raw Data. - In the Raw Data Export window, select the Track Smoothing profile, the Data profile, and the Analysis profile that define the data to be exported. - Under Data to Export, select Track & Dependent Variables. - Click Browse next to Destination Folder and navigate to the location where you want to save the export files. - Under File Type, select either ANSI text (*.txt), Excel (*.xlsx), or Unicode text - default (*.txt). For text export, enter the delimiter character you want to use to separate columns in the exported file. - Next to Missing Value Representation, choose the character that you want to use to mark missing values. - Click Start Export. Options File Type - If you export to text, data of each subject (track) is exported to a separate file. Each file name is unique and is formed by, in the following order: Raw Data (or Manual Scoring, depending on what option you have chosen) - Experiment name - Trial number - Arena name - Subject name. For example: Raw Data-Open Field-Trial 1-Arena 1-Subject 1.txt. - Choose Unicode text to export according to the Unicode character set, which supports most world languages including Chinese. Choose ANSI text to export data as text files according to the ANSI character set. Choose this option only if the application in which you will open the exported file cannot handle the Unicode character set. - If you export to Excel, the file contains all tracks of a trial. The file name is unique and formed by the following elements: Raw Data - Experiment name - Trial number. For example: Raw Data-Plus Maze-Trial 1.xlsx. Data of each subject is written in a separate tab of the worksheet, named for example Track-Arena 1-Subject 1. Important: If your tracks contain more than approximately one million samples, Excel is unable to load the exported file. With 30 samples per second, this happens just after 9 hours. To solve this, export the file to text and use the Excel macro SplitTxtFiles.xlsm, available under Downloads > EthoVision XT > Drivers and Tools. Manual Scoring Log - If you want to export the manually scored behaviors to The Observer XT, or in a format such as 5.12s Rearing, 5.88s Not Rearing, choose Manual Scoring Log. - You can also export behaviors (both manually scored and automatically recognized) in the same format as the other dependent variables, where a behavior is scored as 0 or 1 for each sample time depending on whether it occurs at that time. Choose Track & Dependent Variables and make sure the Analysis profile includes the behaviors to export. Trial Control Data - Choose Track & Dependent Variables if you want to export Trial Control events and states defined in your Analysis profile. For example, to export the state "from Cue light on to Subject in Feeder zone." The state is exported as a series of 0s and 1s (0 = state not active, 1 = state active) in the corresponding column of the export file. - Choose Trial Control Log if you want to export Trial Control events and states with their own time stamp, for example: 6.8s - Cue light on - Activated. For more information, see Export Trial Control Data. Hardware Log Choose Hardware Log if you want to export the complete log of events of hardware devices as a separate file. See the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. External Data Choose External Data Log (not resampled) if you want to export the values of the physiological data streams. Note that these export files contain the original data, not the resampled data that appear in the EthoVision XT analysis profile. Missing Value Representation Enter the character for missing values. By default, missing values are exported as "-". A missing value is exported in the following cases: - The x,y coordinates of a missing body point. - The values of a dependent variable that could not be calculated for that sample, for example the distance moved when the previous sample was missing. File Names, Folders, and Data Format - If you export the same data multiple times to the same location, EthoVision XT attaches a number at the end of the file name: (1), (2), etc. - The files' suggested location is the Export Files folder located in your experiment folder. - The values exported have a variable number of decimals depending on the number of integers. The total number of significant digits exported is always six (for example, 1.23456 or 1234.56), or seven if the unsigned number is smaller than one (0.123456). --- ## EthoVision XT 19 - File Management - Export Trial Control Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-export-trial-control-data Chapter: EthoVision XT Export Trial Control Data Choose between two ways to export the Trial Control data, depending on the file structure you require. - As dependent variables. Data are saved to additional columns of the track data file, and each sample point receives a "0" or "1" depending on whether a state (or event) is active at that time. - As a Trial Control log. Data are written to a separate file, where all events that occurred during the trial (also those not included in the Analysis Profile) are stored as lines each with a time stamp. To Export Trial Control Data as Dependent Variables - Define Trial Control events and states in the Analysis profile (see Hardware and Advanced in the Analysis profile). - Choose Analysis > Export > Raw Data. Select Track & dependent variables then click Start Export. To Export Trial Control Data as a Trial Control Log - Choose Analysis > Export > Raw Data. - Select Trial Control log and click Start Export. The Trial Control log file contains the following columns: - Trial time and Recording time. See Reading the Raw Data File for the difference. - Event. The type of trial control event. For an explanation of the terms, see How the Trial Control Instructions Are Executed. - Rule, Condition, Action, Operator, Reference. The Trial Control element that is involved in the event described in the corresponding Event cell. - Variable, Value. The variable that is subject to an action, and the new value assigned to the variable. - Reference1...4, Repeat1...4. Marks the time that a sub-rule is active. Repeat indicates the number of times that sub-rule has been repeated up to that time. To export log files of the hardware devices operated during the trial, select also the Hardware log option. For more information, see Analysis of Trial Control Data in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Import Data into Excel To Import Analysis Results Analysis results here refers to the table in the Trial Statistics or Group Statistics tabs. - Export the statistics result, with Excel as format. - Open the file in Excel. To Import EthoVision XT Raw Data and Dependent Variables - Export the raw data (track and dependent variables). - Open the file in Excel. Import Manually Scored Data into The Observer XT Aim To analyze the events scored manually in EthoVision XT in The Observer XT, for further analysis. Prerequisite In EthoVision XT, export the data in the form of Manual scoring log (for details see Export Manually-Scored Behaviors). Before clicking Start Export, select Manual Scoring log; select one of the Text options as export format, and select semicolon (;) as Delimiter. To export a subset of tracks or subjects, filter the data before exporting. Procedure - Open the export file in the Windows Notepad. - Remove the lines from "Experiment" to "" so that the first line of the file contains "Header Lines" and the second "Trial time". - Change the number of header lines to 2, then save and close the file. - In The Observer XT, create a project or open an existing one. Make sure that the project's coding scheme contains exactly the same behavior names and that these are organized in the same groups (mutually-exclusive or start-stop) as the corresponding behaviors scored in EthoVision XT. See Effects on the Coding Scheme below. - Choose File > Import Observational Data. - From the Files of type list, select EthoVision XT Data File (*.txt). EthoVision XT Data File is an import profile made for manual scoring logs exported from EthoVision XT. It is installed automatically when you install The Observer XT. Importing Data From EthoVision XT Into The Observer XT - If you do not have the EthoVision XT import profile, click Create New and follow the steps below. - Select the file you want to import and click Open. - Repeat the procedure for the remaining export files (remember that each trial and arena results in a separate export file). - Choose Setup > Independent Variables. Define the independent variables and enter the values of those variables for the trials you have imported. To Create an Import Profile in The Observer XT In the Import Profile Definition window, drag the columns of the Data Sets box as shown here: - Time. Drag the column B (Recording time) to the Time column. This is the time of manually scored behaviors relative to the time that tracking started. In the Select Time Format window, if the time matches one of the predefined formats, EthoVision XT automatically selects one. Converted time shows the converted time and Conversion is OK. Click OK. - You can also define your own format by typing an 'H' for each number representing 'hour', an 'm' for 'minute', an 's' for second, and an 'f' for each number representing millisecond. If Conversion is OK, then click OK. - Under Import Time, select one of the options: - Relative to time zero. Suppose the first row in the imported external data set has time 00:00:05. When the option Relative to time zero is selected, the time stamp of the first row of the imported data set will remain 00:00:05. - Relative to the time of the first data line. Suppose the data set you want to import starts at 14:28:00 and samples every 5 seconds. With the option Relative to the time of the first data line, the first row of the imported data will get the time stamp 00:00:00. The second row will have time stamp 00:00:05. The options under Import Time are grayed out when your time stamps contain the date the file was created. In this case the option Relative to time zero is used. - Do not drag the column A (Trial time) as this provides the same timing as column B when imported into The Observer. - The predefined import profile EthoVision XT Data File uses the Recording time as the time code for the manually scored behaviors. - Event Type. Drag the E column and click OK in the window that appears. - If you want to import video in The Observer, you must keep the correct sync between events and video. See To Import Video in The Observer XT below. --- ## EthoVision XT 19 - File Management - File Locations URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-file-locations Chapter: EthoVision XT File Locations Program Folder The default folder for EthoVision XT is C:\Program Files\Noldus\EthoVision XT 19. Experiments Folder The default folder for EthoVision XT experiments is C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments. Each experiment has its own folder, the experiment folder. An experiment folder contains the following sub-folders: - Bitmap Files. Contains the background images that were used in the Arena Settings and the reference images that were used in the Detection Settings. - Configuration Files. Contains the configuration files that are created when you set the connection between EthoVision XT and hardware devices. - Data Files. Contains the binary track files acquired during acquisition. - Export Files. When you export your track data, manually scored behaviors, analysis results or the experiment's GLP log files, the export files are, by default, stored in this subfolder. - External. When you import external data files, they are stored in this subfolder. In addition, the subfolder contains the sync-out files that were used for external data co-acquisition. - Intermediate. This folder contains intermediate results. - Log. Contains the log files if your experiment is set for Quality Assurance (GLP experiment). - Media Files. This is the default location for media files that have been recorded during the experiment. - Temp. This is a folder where temporary files are stored. It is usually empty. Import Profiles The default folder for profiles for import of physiological data is C:\ProgramData\Noldus\Common\Profiles. The Log File for Technical Support Locate the file in: C:\ProgramData\Noldus\EthoVision\XT 18\Log. The Dump Files for Technical Support Technical Support may also request the dump files EthoVision XT [version number].dmp. You can find the dump files in the following locations: - For Noldus debug-mode dump files: C:\Users\[user name]\AppData\Local\Temp. To access this folder, in the Windows Search field type %temp%. - For user-mode dump files: C:\Users\[user name]\AppData\Local\CrashDumps. A user-mode dump is a dump created for a specific process, for example an application like EthoVision XT. Notes - The AppData folder may be hidden on your computer. If so, in the File Explorer, from the View menu select Options and then Change Folder and Search Options. Click the View tab and make sure that under Hidden Files and Folders the option Show Hidden Files, Folders and Drivers is selected. - If EthoVision XT did not create a DMP file, do the following: - Start EthoVision and use the system until it freezes. Let the software sit there frozen and proceed with the instructions below. - Navigate to C:\Windows\SysWOW64 and double-click on a file called Taskmgr.exe. The Task Manager opens. - On the Processes tab, right-click on EthoVision XT and select Create Dump File. - Wait until a message pops up telling you the location of the DMP file (likely here: C:\Users\\AppData\Local\Temp\EthoVision.DMP). - Close EthoVision XT, copy the DMP file and send it to Technical Support. --- ## EthoVision XT 19 - File Management - Managing Settings and Profiles URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-managing-settings-and-profiles Chapter: EthoVision XT Managing Settings and Profiles To View the Settings Used in a Trial - Choose Setup > Trial List. - Click the Show/Hide button on the toolbar and select Variables. - Choose the type of settings you want to view. - The settings column is added to your Trial List. For a specific trial, the column shows the name of the settings used to acquire the data. - In the Experiment Explorer, open that settings profile. Profiles that have been used to acquire data are marked with a lock symbol. To Create a New Settings/Profile - Right-click the corresponding folder in the Experiment Explorer and select New. - Type the name for the new profile or accept the suggested name, then press Enter. To Activate Settings/Profiles In the Experiment Explorer, right-click the settings/profile you want to activate and select Set as Current. Active profiles are highlighted in blue in the Experiment Explorer. Activating means that EthoVision XT uses that profile to carry out a procedure. For example, when acquiring data it uses the Arena Settings active at that moment. When calculating statistics, it uses the active Track Smoothing profile. To Open Settings/Profiles Right-click the settings/profile you require under the corresponding folder in the Experiment Explorer and select Open. Opening settings/profiles also means that those settings/profiles are activated. To Edit Settings/Profiles To edit settings/profiles, open them and then make the necessary changes. When at least one trial has been carried out, the Arena Settings, Trial Control Settings, and Detection Settings used for that trial are locked. Locked settings are marked by a lock symbol in the Experiment Explorer. You cannot edit locked settings. If you want to make changes to those settings, make a copy and edit it. Then make sure that you carry out the next trial using the new profile. If you delete all trials acquired with specific settings, those settings are unlocked and you can edit them. To Copy Settings/Profiles Do one of the following: - Open the settings/profile folder in the Experiment Explorer. Right-click the name of the settings/profile you want to copy and select Duplicate. - From the Setup or Analyze menu, select the type of settings/profile you want to copy. In the window that opens, select Duplicate From. Change the name of the new settings/profile if necessary, then select the settings/profile you want to copy from. A new item is added to the folder. Type a new name or accept the suggested one, then press Enter. The suggested name for a new settings/profile is [Settings/Profile] N, where N is the first integer not yet used in the name of the other settings/profiles in that folder. To Rename Settings/Profiles - In the Experiment Explorer, right-click the name of the settings/profile you want to rename and select Rename. - The profile name is highlighted. Type the name you require and press Enter. You cannot rename settings/profiles that were used to acquire at least one trial. To Delete Settings/Profiles In the Experiment Explorer, right-click the name of the settings/profile you want to delete and select Delete. Notes: - You cannot delete settings/profiles that were used to acquire at least one trial. To delete those settings/profiles, you must first delete the trials (make sure you do not lose any important data). - You cannot delete settings/profiles if your experiment is set for Quality Assurance (GLP experiment) and you do not have specific rights. - If the currently active settings/profile is deleted, the first of the remaining settings/profiles in the folder is activated automatically. - If you delete the only settings/profile in the folder, a new default settings/profile is created automatically. - If you delete a Data profile or an Analysis profile used to create an analysis result open on your screen (track plot or statistics result), the result is updated according to the first available Data profile, or, if no other profiles are available, a newly created default profile. Import Data Aim To import data from other programs to analyze tracks and other data combined. Import Track Data from Other Experiments - Import data from other experiments. Choose this option to merge data from multiple experiments. - Import Live Mouse Tracker data. Import Other Types of Data - Import UltraVox XT 3 call data. - Import Live Mouse Tracker data. - To import data acquired with a separate data acquisition (DAQ) system, see Import External Data in EthoVision XT. For how to create an import profile, see Create a New Custom Import Profile. Note: You cannot import track files from one EthoVision XT experiment into another. Data that you want to analyze together in EthoVision must be acquired in the same experiment. Import UltraVox XT 3 Call Data Procedure - In EthoVision XT, open the Trial List. - Click the Import External Data button. - Under Files of Type, select UltraVox XT 3. If you do not see this profile, install it from the UltraVox XT 3 installation package. Open the folder ...Extras\Import profiles and double-click EthoVision XT 11 and Newer.bat. - Select the *.etx files and click Open. - Drag the data lines from the Import External Data window to the trial, arena, or subject you require. - When ready, click Import. Notes: - Data for each call name (or call name*pattern label) is imported and resampled as a separate dependent variable. - For more information on importing and analyzing UltraVox XT call data, and how to control UltraVox XT start and stop data recording, see the UltraVox XT 3 Help. Export Data Aim To export EthoVision XT data to other programs to carry out further analysis. Export Data from EthoVision XT - Export the raw data (track and dependent variables). - Export external data. - Export manually scored behaviors. - Export Trial Control data. Import EthoVision XT Data in Other Applications - Import data into Excel. - Import manually scored data into The Observer XT. --- ## EthoVision XT 19 - File Management - Reading the Raw Data File URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-file-management-reading-the-raw-data-file Chapter: EthoVision XT Reading the Raw Data File - The track file export takes into account your data selection for entire tracks, but not for within tracks. So, if you make a data selection such that you only have track 1 and only zone 1, EthoVision will export track 1, but the entire track. If you want to filter out zone 1 in your track data, you should include the zone as a dependent variable and then filter on that column in Excel. The result column in the export file has values 0 and 1 dependent on the fact if the data selection criteria were met (1) or not met (0). - Trial time is the time elapsed from the start of the trial (basically, the moment when you clicked the green Start button). Recording time is the time elapsed from the start of the track. The difference between the two time values is also shown next to the header Recording after. For more information on trials and tracks, see Important Terms in Trial Control. - The values of the x,y coordinates and the subject size (Area) in the exported track files are expressed in calibrated units, (square) millimeters, (square) inches, etc., not in pixels. - Areachange is the change in the pixels of the subject area from the previous sample, used to calculate Rotation. Note that this is not the same as the difference in Area between the current sample and the previous one. - Samples that were missing (EthoVision XT could not analyze the video image) or not found (EthoVision XT could not find the subject) are indicated by "-" instead of the coordinate values. Note that sometimes the center point is found, not the nose point or the tail base (or neither of the two). To see the proportion of samples that were not found in a trial, in the Trial list click the Show/Hide button on the toolbar, choose Variables and select Subject Not Found. Check the value in the column Subject Not Found corresponding to that trial. - Excel can import a limited number of rows and columns. For Excel 2007 and newer versions this is 16,384 rows and 1,048,576 columns. Excel will only import the maximum number of rows. If necessary, you can import the exported files to another program like SPSS. Export External Data Aim To export data like physiological data that were imported into EthoVision XT, to another application for further analysis. You can export the original data or the resampled data. To Export the Original External Data - Choose Analysis > Export > Raw Data. - Select External data log (non resampled). - Choose the File type and click Start Export. Notes - Each line in the exported data file represents one sample according to the original sample rate. - Trial time and Recording time are the original time stamps relative to the start of the trial and the start of the track, respectively. - For text export: each file contains the original signal combined with the current Data profile/Result container. The default file name is: External-[experiment name]-[Trial number]-[signal name]-[Data profile or Result container name]-[Arena name]-[Subject name].txt. - For Excel export: each file contains the signal from one trial. The default file name is: Raw data-[experiment name]-[Trial number].xlsx. Within an Excel file, each sheet contains the signal combined with the current Data profile/Result container. Sheets are named in this way: [signal name]-[Data profile or Result container name]-[Arena name]-[Subject name]. This name may be truncated. - For more information on other options, see Export the Raw Data (Track and Dependent Variables). To Export the Resampled External Data - Choose Analysis > Export > Raw Data. - Select Track and dependent variables. - From the list on the toolbar, select the Analysis profile that contains the resampled signals. See External Data (Resampled). - Choose the File type and click Start Export. - In the exported data file, each line is one EthoVision XT sample. Each resampled signal is written in a column. The Data profile column indicates whether a sample is included (1) or not (0) in the Data profile. - Export files are named like Raw data files. For more information on other options, see Export the Raw Data (Track and Dependent Variables). - To export a specific selection of resampled external data, first edit the Data profile. To Export the Signal Statistics Make sure that the signal is selected in the Analysis profile, with the Trial Statistics that you require. Next, choose Analysis > Export > Statistics. See Export the Statistics Result. Export Manually-Scored Behaviors Aim To export the behaviors scored manually, depending on the file structure you require. - Export as dependent variable. The behaviors are exported as 0s or 1s, depending on whether the behavior is active (1) or not (0) at a specific sample time. Note that the export file contains a header. - As a Manual Scoring log. The behaviors are exported to a file where the start and stop events are written in sentences with the following structure: Time - Subject - Behavior - Event type (State start or State stop). Procedures To Export Manually-Scored Behaviors as Dependent Variables - Make sure that the Analysis profile includes the behaviors to export. - Choose Analysis > Export > Raw Data, and select Track and dependent variables. See also Export the Raw Data (Track and Dependent Variables). To Export Manually-Scored Behaviors as a Manual Scoring Log - Choose Analysis > Export > Raw Data, or in the Experiment Explorer under Analysis - Export click Raw Data. - Select Manual scoring log. Select the export format. If you export to The Observer XT, select a Text option and select semicolon (;) as Delimiter. - Click Start Export. For more options see Export the Raw Data (Track and Dependent Variables). Notes - See Import Manually Scored Data into The Observer XT. - If you export to Excel, the manually scored data are stored in a separate tab of the Excel worksheet. The tab is named Manual scoring - [arena name]. - If you export to Text, data of different arenas are exported to different files. --- ## EthoVision XT 19 - Follow URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-follow Chapter: EthoVision XT Follow Definition A discrete (state event) variable that is scored when the focal subject walks directly in the path of another subject. Calculation Follow along path is scored when the following conditions are met: - Both subjects move at a speed higher than 5 pixels per frame. - The two subjects are not in contact with any other subject. - The angle between their direction vectors is smaller than 45°. - The focal subject's center point lies within a rectangular area drawn based on the position of the followed subject. This is checked beginning from the current video frame time to the 15th frame before the current one. So the software checks that the focal subject enters the path up to 0.5 s after the followed subject has been there. - The distance between the two subjects' center points is smaller than two mean body lengths. This mean body length is calculated using all values of distance nose-tail base of the followed (i.e., non focal) subject within the track. How to Specify Follow - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Follow. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Note Follow looks similar to a train of two mice. However it depends on the definition of the train. If subject A is following closely subject B, this is scored as A Follows B but also as a Train for subject A, when the distance between A and B is shorter than the threshold set in the Train settings, and when the train is defined as in the cases below: - A > B. - Actor > B. - Actor > Any. Note that: - Follow is scored for the subject that follows another one. If subject A follows subject B, Follow is scored for subject A, not B. - Train is scored for all the subjects involved in the train definition. So when subject A follows subject B, an instance of Train defined as A > B is scored for subject A and for subject B. See Also - Dependent variables for Live Mouse Tracker Get Away Definition A discrete (state event) variable that is scored when the focal subject walks away from another subject. Calculation The variable Get away is scored when: - The speed of the focal subject is greater than or equal to the speed of the other subject. - The speed of the focal subject or the other subject is greater than the value set as threshold (5 cm/s). This threshold cannot be changed as it is hard-coded. - The distance between the two subjects increases. Note that if the other subject is sitting still, Get away is not scored for the focal subject, no matter what the latter does. How to Specify Get Away - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Get away. - Click the Receivers tab. Under Select, choose the subjects that the focal subject moved away from. If you select two or more subjects, select one of the available options from the list: - All selected subjects: Get away is scored when the focal subject moved away from all the subjects selected above simultaneously. - Any selected subject: Get away is scored when the focal subject moved away from any of the subjects selected above. - Each subject: Get away is scored when the focal subject moved away from one of the subjects selected above. The results are displayed for each Receiver. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Notes - To calculate this variable, EthoVision XT checks the subject's speed at time t based on the change in the X,Y coordinates between t-1 and t+1, like in the original algorithm of Live Mouse Tracker. In EthoVision XT, the Velocity variable at time t is calculated based on the change in the X,Y coordinates between t-1 and t. See Velocity. Example Subject A is moving to the left, away from subjects B and D. Accordingly, the state events Get away are scored for the two combinations A-B and A-D. The duration of the state events depends on when the conditions listed above are valid for each combination. Because subject C is still, Get away is not scored for the combination A-C. In the Trial Statistics results table, with the default layout, the results of Get away are shown per subject (on the rows). The columns vary depending on what you chose in the Receivers tab: - If you chose Each subject, the columns contain the statistics of Get away from specific subjects (for example, From A to D). - If you chose All selected subjects or Any selected subject, a column From all of A, B, C, D or From any of A, B, C, D contains cumulative statistics of Get away when the subject moved away from all the cage mates simultaneously or from any of them, respectively, depending on which option you chose. See Also - Dependent variables for Live Mouse Tracker Group Definition A discrete (state event) variable that is scored when the focal subject is in contact with one or more subjects. Calculation EthoVision XT uses the events of type Contact stored in the Live Mouse Tracker database. - Group size 2 is scored when the focal subject is in contact with only one subject. If the animal is in contact with more than one animal the event is not scored. - Group size 3 is scored when the focal subject is in contact with only two other subjects to form a group of three animals. - Group size 4 is scored when the focal subject is in contact with three other subjects to form a group of four animals. EthoVision XT splits the results depending on who forms each group. For example, A can form groups of 2 subjects, resulting in groups AB, AC and AD. The overall results (AB+AC+AD) are also shown. How to Specify Group - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Group. - Specify the Group size. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. - If you wish to have the results for all group sizes in one table, repeat the steps above to add a total of three Group variables, one for each group size. Applications You can use the Group variable to quantify the tendency of subjects to form groups. For example, a mouse model of social deficit may show reduced time spent in groups. See Also - Dependent variables for Live Mouse Tracker Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Free interval URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-free-interval Chapter: EthoVision XT Definition A segment of track from sample A to sample B, where A and B are determined by a time, the value of another dependent variable, a Trial Control event, or the value of a signal from a hardware device. Use Cases Frequent cases: - Group instances of behavior (e.g. Immobile) in a bout. - Filter instances of behavior (e.g. Not moving) longer than one second. See Examples of Free Intervals in the Analysis Profile. Calculation A Free interval is defined by a Start criterion and a Stop criterion. Depending on whether and how often the criteria are met within a track, a Free interval may result in zero, one or more instances of the interval within the same track. NOTE Like all intervals defined with Nesting, a Free interval is left-closed [A, B). That is, the start sample A, not the stop sample B, is included in the analysis. Multiple Instances of the Same Interval Definition When you define a Free interval, this may result in zero, one or more (up to 2000) instances of an interval depending on where the Start and Stop criteria are met. An instance of a free interval starts at the sample time when the Start criterion is met, and stops at the sample time when the Stop criterion is met. A new instance is defined if the Start criterion and Stop criterion are met again, after the time in the track that the last Stop criterion was met. NOTE Multiple instances of the same free interval definition cannot overlap. An interval is NOT defined when its start criterion falls within a previous instance of the same interval definition. For example, you define a Free interval that starts when the subject enters zone A, to 10 seconds after that time. If a new instance of In zone A occurs before the end of the interval, that instance of In zone is ignored. Similarly, if you define a Free interval that goes from track start to when the external data Heart rate > 400, then one interval is defined, from Track start to the time when Heart rate reaches 400 bpm for the first time. This is because the "Track start" criterion is met once in each track, no matter how many times Heart rate reaches 400 bpm. Multiple Free Intervals in the Analysis Profile You can define multiple intervals in the Analysis profile by repeating the procedure below. The interval definitions are independent of each other; therefore the resulting intervals may be overlapping. To Specify a Free Interval - In the Analysis Profile, under Custom Variables, click the button next to Free Interval. - Under Start criterion select the starting point of the interval: - Time. To select a time. For example, Track start (that is, the first sample in a track) or an Elapsed time after the track start (format: H:mm:ss.fff). For example 0:01:00.00 for one minute after the start. NOTE Track start corresponds to the first sample in the track (Recording time = 0.0), not the Trial time. For multiple-subject setups, Track start is the first sample of the animal detected first. - Dependent Variable. To select the time that a dependent variable has a specific value. For example, Distance moved >= 1 m, or frequency of In zone >=10. This list also includes behaviors scored manually and external data. See Free Interval Based on a Dependent Variable. - Trial Control. To select the time that an event in your trial control procedure occurs. For example, when a condition becomes true, or a command to a hardware device is given. See Free Interval Based on a Trial Control Event. - Hardware. To select the time that a hardware-related variable has a specific value. For example, when the number of food pellets dropped by a Pellet Dispenser is greater than 10. This option is only available when hardware devices are defined in your experiment. See Free Interval Based on Hardware. - Under Stop criterion select the end point of the interval. See above for most of the options. If you choose Time, and under Interval stop you choose Elapsed time, you have two options: after track start to stop the interval at a specific time after the track start (that is, the first sample in the track); after start event to stop the interval a specific time after the event selected as start criterion. Note that this "start event" is not the same as the start time of the resulting interval, if you set some time before the event (for example, 10 s before the frequency of In zone becomes 1). The "start event" is when the Frequency of In zone becomes 1. However, the interval starts 10 s earlier. - Select Ignore last interval if incomplete to ignore the interval when the stop criterion is not met. If you do not select this option, and the stop criterion is not met, EthoVision XT defines an interval up to the end of the track. - A free interval may occur once or more in a track (see above). To analyze each instance separately, select Calculate statistics per interval and enter the number of intervals you want to view in the results (1 to 2000). To be sure you view all intervals, enter a large number that exceeds the maximum possible number of instances per track. See Restrictions in EthoVision XT. To analyze all instances as one, de-select Calculate statistics per interval. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Free interval (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-free-interval-continued Chapter: EthoVision XT Notes - Note the difference between Free Interval in the Analysis Profile (this topic) and Nesting over a Free Interval in the Data Profile. - Define a Free Interval in an Analysis Profile when you want to analyze the interval itself, not other dependent variables within that interval. For example, to calculate the duration of an interval. - Define a Free Interval in a Data Profile when you want to analyze any dependent variable within the resulting track segment. For example, to calculate the average velocity of the subject in the interval. - If a start criterion is not met in a track, EthoVision XT does not define the Free Intervals in that track. - If a stop criterion is not met in a track, EthoVision XT does the following: - If you selected Ignore last intervals if incomplete, it does not define the interval. - If you did not select that option, it defines an interval up to the end of the track. - Free intervals in multiple-subjects setups. A free interval is calculated for each subject separately, based on the data (dependent variables, behavior, etc.) for that subject. See Free Interval Based on Multiple Subjects. - Free intervals and missing samples. A free interval is not interrupted if one, two, or three consecutive missing samples occur. With four or more consecutive missing samples, the current interval is interrupted and a new one starts when the Start criterion is met. - Contiguous intervals. When two instances of a Free Interval are contiguous — for example, when the Interval Start criterion is supposed to be met immediately after the Interval Stop criterion for the previous instance is met — one sample is always excluded between the end of an instance and the start of the next instance. For example, the first instance goes from time 0 (included) to sample 100 (excluded), then from sample 101 (included) to sample 250 (excluded). Samples 100 and 250 are not included in the analysis. The reason is that the statistic used to find the start of the interval is updated one sample after the end of the previous interval. More Details - Free Interval Based on a Dependent Variable - Free Interval Based on a Trial Control Event - Free Interval Based on Hardware - Free Interval Based on Multiple Subjects - Examples of Free Intervals in the Analysis Profile Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Free Interval Event URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-free-interval-event Chapter: EthoVision XT Background This topic contains details about defining a Free interval. For the main procedure, see Free interval. To Specify the Trial Control Event In the Free Interval window, under Start criterion or Stop criterion, choose Trial Control and select the following: - In the Start at / Stop at field, enter the time of the start (or stop) of the interval relative to the Trial Control event specified in the next steps. Example: To start an interval 1 s before a Trial Control condition becomes true, next to Start at enter 0:00:01:000 before event. Example: To stop an interval 10 s after the Trial Control action "Drop pellet", next to Stop at enter 0:00:10:000 after event. - From the Occurrence list, select which occurrence should mark the start of the interval (1st to 9th). Select 1st if you want to define an interval from the first time that a trial control event occurs. Select 2nd, etc. when the trial control event occurs repeatedly, for example in sub-rules. - From the Element list, select the trial control category (condition, action, sub-rule, etc.). - From the Event list, select the event. The options differ depending on the Element chosen. - For actions, sub-rules: becomes active/inactive. - For conditions: becomes active/inactive, and becomes true/false. - For sub-rule references: becomes active/inactive, and makes sub-rule active/inactive. Notes - A Free interval can only start at the time that, or before (not after) a Trial Control event occurs. Similarly, a Free interval can only end at the time that, or after (not before) a Trial Control event occurs. See Also - For information on the meaning of active/inactive, false/true, see How the trial control instructions are executed. - For information on sub-rules and analysis of trial control data, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Nesting Over a Trial Control State With Free intervals you can select the same track segments that you can define with Nesting over a Trial Control state in the Data profile. The main differences are that: - With a Free interval, you can also specify the number of occurrences of an event in the Interval start criterion. For example, define an interval that starts when an action is carried out the 3rd time. With Trial Control state that is not possible. There, you can only specify the number of occurrences in the Interval stop criterion. - With a Free interval, you can combine Trial Control events with other criteria (time, dependent variable values, hardware log values). For example, define an interval that goes from the time a light switches on, to 1 minute after that time. To Specify the Hardware State or Value In the Free Interval window, under Interval start or Interval stop, choose Hardware and select the following: - In the Start at / Stop at field, enter the time of the start (or stop) of the interval relative to the Hardware event specified in the next steps. Example: To start an interval 1 s before the PhenoTyper's white light switches on, next to Start at enter 0:00:01:000 before event. Example: To stop an interval 10 s after a pellet was dropped, next to Stop at enter 0:00:10:000 after event. - From the Select device type list, choose the type of device you want to use. - From the Select name list, select the name of the device of the chosen type. The names in this list have been assigned to that device type in the Arena - Hardware mapping window in the Arena Settings. - From the Select signal/command list, select the variable or the command you are interested in. - From the Signal value list, choose which value the signal should have to define the start/stop of the interval, using the operators available (<=, >= or false/true). Notes - The Cumulative value option is available for numerical variables like Number of pellet drops, Number of licks, Duration of licks, or counts (for example, Input 1 L->H count). - When Cumulative value is selected, hardware events are summed up and EthoVision "remembers" that at any time. Keep this option selected if, for example, you want to start an interval when the Signal value is >= 10. - When Cumulative value is not selected, each hardware event is a state that lasts one sample time (for example, 0.04 s if the sample rate is 25). At any time, EthoVision does not "know" how many events have occurred up to that time. De-select Cumulative value when you want to specify multiple intervals, for example for each time a pellet is dropped. - The options under Interval start and Interval stop are based on the Hardware state dependent variable. For more information, see also Hardware state under Analysis of Trial Control data in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. See Also - The EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To open this manual, on the Windows Apps screen choose Noldus > EthoVision XT 19 Other documentation. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Free Interval Profile URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-free-interval-profile Chapter: EthoVision XT Profile For all the examples below, define the interval first, then choose Analyze > Results to calculate the statistics or visualize the results. Tip: If you want to define a free interval to further analyze the events within that interval, choose Nest over a Free Interval in the Data profile. Examples - Example 1: From the track start to when the subject is in a zone for a specific time - Example 2: From the start of a conditioning routine to when 10 rewards are given to the subject - Example 3: Split a track in segments of a specific path length - Example 4: Detect bouts of a behavior - Example 5: From the track start to when external (physiological) data reach a specific value - Example 6: Filter the instances of a behavior longer than a certain time Example 1: From the Track Start to When the Subject Is in a Zone for a Specific Time Aim This free interval can be used, for example: - Exploratory behavior. Calculate the time that the subject takes to explore the novel object for at least 30 s (Cumulative duration). - Learning. Calculate the time that the animal takes to stay in a zone for 30 s uninterrupted (Current duration). Solution Define a Free interval with: - Start criterion: Track start - Stop criterion: Dependent variable In zone. The Statistic depends on the type of question you want to answer. In the Novel object test, you want to stop the interval when the subject has explored the object for a total of 30 s. Choose Cumulative duration. In the learning example, you want to stop the interval when the subject enters a zone and stays for 30 s without exiting. Choose Current duration. Example 2: From the Start of a Conditioning Routine to When 10 Rewards Are Given to the Subject Aim In a conditioning experiment, the subject has to stay in a specific zone to obtain a food pellet. The action-reward sequence is repeated a number of times in a subrule. The researcher wants to know how long it took the subject to get 10 rewards. Solution Create a Free interval with: - Start criterion: Trial Control. Element: Subrule. Event: becomes active. - Stop criterion: Hardware. Device type: Pellet dispenser. Select signal: Number of drops >=10. The option Cumulative is selected. Example 3: Split a Track in Segments of a Specific Path Length Aim Suppose you want to split your tracks in segments of a specific distance moved by the subject, for example 1 m, and you want to calculate the duration of each segment. Solution Create a Free interval with: - Start criterion: Dependent variable Distance Moved. Statistic: Current ≥ 0 cm. - Stop criterion: Dependent variable Distance Moved. Statistic: Total ≥ 100 cm. To calculate the duration of individual instances, select Calculate statistics per interval and enter a number that exceeds the maximum number of intervals per track. Plot 1: Per-sample distance moved. Plot 2: Free interval that runs from Current Distance Moved ≥ 0 to Total Distance Moved ≥ 100 cm. Note that the faster the animal (i.e. the longer the per-sample distance moved), the shorter the resulting interval. Example 4: Detect Bouts of a Behavior Aim Calculate the number and duration of bouts of a behavior, for example Movement or Activity. The single instances of Movement being part of a bout may be separated by up to time tmax. In the example below, instances 1 to 5 are grouped in a bout. Solution Create a Free interval with: - Start criterion: Dependent variable Movement with state Moving. Statistic: Current. - Stop criterion: Dependent variable Movement with state Not moving. Statistic: Current Duration ≥ 5 s (tmax). This ensures that the interval ends when the animal has not moved for five seconds without interruption. In the Trial Statistics tab of the same window, select Mean if you want to know the average duration of a bout. Notes - Because each free interval also includes tmax, you have to subtract that time to obtain the true average duration. - If the event which specifies the end of a bout (in this example, Not moving for at least 5 seconds) is never found, the result for that trial is that there is no bout at all. The result is one long bout if you de-select the option Ignore last interval if incomplete. - For the same reason described above, if the Stop criterion is not met, the last bout of a trial is not detected — for example, when the time between the start of Not moving and the end of the trial is less than tmax. You can have the last bout detected by selecting the option Ignore last interval if incomplete, but the duration of this bout will be truncated. Example 5: From the Track Start to When External (Physiological) Data Reach a Specific Value Aim To calculate the time that it takes for a physiological variable (e.g. heart rate) to reach a specific value. Prerequisite The physiological variable has been imported in the trial. See External Data. Solution Create a Free interval with: - Start criterion: Track start - Stop criterion: Dependent variable Heart rate. The Statistic chosen is Current. If necessary, click Settings and choose how to re-sample the variable from the original signal. See External data (resampled). The result is shown in the first plot, together with the plot of Heart rate. Choose Analysis > Results > Statistics and Charts to obtain the length of the free interval. Tip: If you want to analyze the time between two values of external data — for example, from Heart rate = 300 to Heart rate = 400 — choose External data (state) in the Analysis profile instead of Free interval. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Free Interval Profile (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-free-interval-profile-continued Chapter: EthoVision XT Certain Time Aim In this example we want to filter the behavioral states (e.g. Not Moving). We want to remove the instances of Not Moving that last less than 1 second. Solution - In the Analysis profile create a free interval with Movement as a criterion. - Start Criterion: Select Dependent variable. - Start at: Enter the minimum time duration. In this example, 1 s. - Select variable: Choose the behavior. In this example, Movement. - Statistic: Current Duration. - Settings: Define the behavior state. In this example, Not Moving is chosen, based on thresholds Start velocity 2.0 cm/s and Stop velocity 1.5 cm/s. - Stop criterion: The main difference from the Start criterion is that you must select the opposite of the behavior above. In this example, under Settings, Moving is selected with the same thresholds as above, and the Statistic is Current; then select true. Next to Stop at, leave 0.0 selected. - In the Integrated Visualization you can check if the free interval works as expected. - The first plot shows the typical Movement variable, with the two states Moving and Not Moving. - The second plot is that of the free interval defined above. It plots the instances of Not Moving longer than 1 s, while ignoring the shorter instances. - Calculate the statistics of the free interval. TIP In the interval definition, select Calculate results for interval 1 to ... if you want results for each instance of the filtered behavior. On the Trial Statistics tab, choose the statistic that you need: - Choose Frequency to know how many instances of the filtered behavior occur. - Choose Latency to first to know at what time that behavior occurs, for each instance. See Also - Free interval based on a dependent variable - Free interval based on a Trial Control event - Free interval based on hardware - Free interval based on multiple subjects - Analysis advisor Procedure When working with multiple subjects per arena, you can define free intervals in two ways: - Under Nesting, choose Free interval to define a free interval for each subject separately. The interval is based on the behavior of that subject, not the other(s). As a result, for each subject a specific time period is selected. - Under Nesting over Subjects, choose Free interval to define an interval based on a combination of conditions based on two or more subjects. The resulting interval is applied to all subjects. As a result, the same time period is selected for all subjects. Example Your arena contains two subjects. A free interval is defined that goes from Total Distance moved >= 100 to Total Distance moved >= 200. - If you choose Free interval from Nesting, the start/stop criteria are applied per subject, resulting in most cases in different time periods being analyzed for each subject. Below: Time plot of a dependent variable (in this example, Distance moved) after defining the Free interval from Nesting. Different time periods are analyzed for Subject 1 (from A1 to B1) and Subject 2 (from A2 to B2). - If you choose Free Interval from Nesting over Subjects, the start/stop criteria are applied per subject, but the intervals are defined after combining the criteria based on what is selected in the Actors tab. Below: Time plots of a dependent variable (in this example Distance moved) after defining a Free interval from Nesting over Subjects (compare with the previous figure). Depending on what is selected in the Actors tab: - With All selected subjects (top): The time period shared between subjects (from A1 to B2). - With Any selected subject (middle): The time period defined by at least one subject (from A2 to B1). - With one subject selected (bottom): The time period defined by the criterion met by that subject (in this example, subject 2; therefore, from A2 to B2). Definition A segment of track that corresponds to the combination of the value of one, two or more dependent variables. Use Cases - In Trial Control: Stop the trial when exploration time reaches a specified value. In a Novel object test, stop the trial when the exploration of an object reaches 30 seconds. Exploration is defined as (a) Nose point in the zone "object sniffing zone", and (b) Head direction pointing to the "object sniffing zone". When the total time that (a) and (b) are simultaneously true reaches 30 s, stop the trial. TIP Define this condition in the Trial Control Settings. - In Analysis: Calculate the time that the animal swims pointing to the platform. In a probe trial of the Morris water maze test, the subject swims for a number of seconds around the platform. You want to know how long the animal points to the platform while it is swimming. This can be translated to (a) Heading to platform less than a user-defined angle (for example 10 degrees) and (b) Velocity higher than a user-defined value (for example 10 cm/s). TIP Define this in the Analysis profile. Calculation The track segments are defined for each condition independently. Then, the track segments are combined according to the logic specified (All conditions true = AND; Any condition true = OR). Below: The variable Multi condition marks the time when the animal swims towards the platform with a certain speed. Here the multi condition is defined with three conditions: (1) Heading to platform less or equal than +15 degrees; (2) Heading to platform greater than -15 degrees; (3) Velocity greater than 10 cm/s. Conditions are combined with All conditions true. The first plot shows Multi condition; the second Heading to point (center of the platform), with both negative and positive values; the third plot Velocity. To Specify a Multi-Condition - In the Analysis profile, under Custom Variables, click the button next to Multi condition. - Click the Add button at the right of Add conditions. - Choose the variable from the Select variable list. - To specify further options, click Settings. Next, specify which values (or range of) make the condition true. - Click OK. The condition is added to the list. - Repeat steps 2–5 to add more conditions. - Combine the conditions with All conditions are true (AND logic) or Any condition is true (OR logic). - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - To define a Multi condition you can use continuous variables, like Distance moved, and state variables, like In zone (excluding Activity state and Acceleration state). - Variables that are not available include: variables representing points in time, like Rotation, Zone transition, Zone alternation; behaviors of Behavior Recognition; and behaviors scored as point events. - To edit a condition, select that condition in the list and click Edit. To delete a condition, click that condition and click Delete. See Also - For how to use a Multi condition in Trial Control, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. - To analyze the track segments based on the Multi condition, see Nesting over a Multi condition in the Data profile. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Free Interval Variable URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-free-interval-variable Chapter: EthoVision XT Background This topic contains details about defining a Free interval. For the main procedure, see Free interval. NOTE Dependent variable here also includes external data and manually-scored behaviors, not behaviors of Rat and Mouse Behavior Recognition. To Specify the Dependent Variable In the Free Interval window, under Start criterion or Stop criterion, choose Dependent variable. - In the Start at / Stop at field, enter the time of the start (or stop) of the interval relative to the event described by the variable. EXAMPLE To start an interval 1 s before the animal enters a zone, next to Start at enter 0:00:01:000 before event. EXAMPLE To stop an interval 10 s after the total distance moved reached 10 m, next to Stop at enter 0:00:10:000 after event. - From the Select variable list, choose the dependent variable. For example In zone if you want the interval to start or stop when the animal enters a zone for the nth time, or has spent a specific time in that zone. - From the Statistic list, choose the statistic of the dependent variable. For example: - Frequency if you want the interval to start/stop when the animal has entered a zone for the 10th time. - Cumulative Duration if you want the interval to start/stop when the animal has spent a specific total time in that zone. See Statistic: When to Use Frequency, Current, or Others. - Click the Settings button to specify the dependent variable in more detail. For example, which zone the animal should enter to define the stop of the interval, or which body points should be in the zone. See Dependent Variables in Detail. - Next to is:, specify which value the statistic should have to define the start/stop of the interval, using the operators available (<=, >= or false/true). Notes - The following dependent variables are not available as start/stop criteria: Activity state, Acceleration state, and the behaviors of Rat or Mouse Behavior Recognition. - A Free interval can only start at the time that, or before (not after) a variable reaches the specified value. Similarly, a Free interval can only end at the time that, or after (not before) a variable reaches the specified value. - If you have imported external data in an experiment, you can define an interval based on the values of the resampled external data, not the original (imported) external data. Choose the external data from the Select variable list. See External Data (Resampled) and Examples of Free Intervals in the Analysis Profile. - If you want to define a free interval based on two values of external data (for example, Heart rate between 300 and 400 bpm), do not use Free intervals. Instead, use the dependent variable under External data in the Analysis profile. Statistic: When to Use Frequency, Current, or Others - Frequency. To define an interval that starts/stops when the animal has entered a zone or has shown certain behavior (Moving, Highly mobile, Grooming, etc.) a number of times. - Current. To define an interval that starts/stops when a variable reaches a specific value. For discrete variables (state events or point events) like In zone, the Current statistic can be false or true. EXAMPLES - For In zone, Current = true means that the interval starts/stops as soon as the animal enters the selected zone. Current = false means that the interval starts/stops as soon as the animal is outside the selected zone. - For Velocity, Current >= 10 means that the interval starts/stops as soon as the animal's velocity is higher than or equal to 10. - Total. Used especially with Distance moved. This makes the interval start/end when the animal has covered a specific distance since the start of the track or the start of the interval. - Cumulative Duration. To define an interval that starts/stops when the animal has been in a certain state (that is, within a specific zone, or in the state Highly mobile, etc.) for a specific total time since the start of the track or the start of the interval. It does not matter if the subject's state was sometimes interrupted. EXAMPLE The interval starts when Cumulative duration of In zone >= 10 s. The green dot indicates where the interval starts. - Current Duration. To define an interval that starts/stops when the animal has been in a certain state (within a specific zone, or in the state Moving, etc.) for a specific time without interruption. EXAMPLE The interval starts when Current duration of In zone = 10 s. The green dot indicates where the interval starts. - Latency to First. To define an interval that starts/stops when the time to the first instance of an event (for example, the animal being in a certain state or within a zone) has reached a specific value. Note that latency is always calculated from the start of the track. Interval Stop Criterion Behavior Where in the track an interval ends depends on the value of the statistic of the dependent variable used. The following information applies to the statistics Total, Frequency, Current Duration, Cumulative Duration, and Latency to first. Once the start point of an interval is found, EthoVision XT resets the statistic at that point, and starting from the next sample time, updates its value until it matches the stop criterion. - If the stop criterion is met, the interval is fully defined. - If the value of the statistic does not match the stop criterion before the end of the track, the result depends on whether you select the option Ignore last interval if incomplete. See Free interval. EXAMPLE The statistic Frequency for the dependent variable In Zone. A free interval is defined that ends when the Frequency of In zone is equal to 2. The green bars represent the time when the subject is in the specified zone (numbers indicate frequency). The green dots indicate when the Start criterion is met. The arrows represent the free intervals defined. The red circles show when the statistic Frequency for In zone is reset to zero. EXAMPLE The statistic Total for the dependent variable Distance moved. A recurring free interval is defined to split the track in segments of 100-inch distance moved. - Interval start: Dependent variable Distance moved, Statistic Total >= 0. - Interval stop: Dependent variable Distance moved, Statistic Total >= 100. When the second, third, etc. interval starts, the total Distance moved is reset to zero and updated, starting from the next sample time, until the Stop criterion is met. Other Statistics For other statistics like Current (for example In zone or Not in zone), EthoVision XT evaluates the value at the current sample and checks that the Stop criterion is met. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-general-information Chapter: EthoVision XT Setting up the experiment in EthoVision XT Create the Experiment - Start EthoVision XT and choose File > New from template. - In the Select a template option window, select Apply a pre-defined template. Next, follow the instructions in the guided setup. For more information, see Set Up an Experiment in the EthoVision XT Help. For details on connecting the camera, see Camera Installation in the EthoVision XT Help, or watch the video tutorial Set Up the Camera (Help > Video Tutorial). - Enter the name of the experiment and click OK. - Before you can actually acquire data, check the settings listed in the rest of this section. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. Note: The option Deep learning is only available if your PC has a graphic processor (GPU) that supports additional software (CUDA). See Deep learning: Requirements and Limitations in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. - Click Grab to grab an image of the empty enclosure from the camera image, or click Browse to select a video file and then click Grab. - Click 1. Draw Scale to calibrate your arena. - Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. For open fields and other enclosures, remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. - If you need to rotate the outline of the arena, drag around all elements, then click the Rotation mode button and move the outline until it matches the arena in the video image. - If you need to reshape the outline of the arena, click the Point edit mode button and move the vertices of the outline. - To draw zones, click 3. Select Shape and Draw Zones. See more details in the chapter about your test. For details, see Arena Settings in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of data acquisition. For details, see the EthoVision XT Help. Choose Setup > Trial Control Settings. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. - If you work with pre-recorded video, select a video file. If you work with the live camera image, release the animal in the arena. - Click Automated Setup. - Select: - Rodent for tracking rats and mice. - Adult fish for tracking fish from the top view. - Other for any other case such as tracking insects, crustaceans, or when tracking fish from the side view. - When the subject does not move a lot and is far from the enclosure walls and other objects, draw a rectangle around it. EthoVision XT detects the subject. - If the subject's body is well detected (marked in yellow), click Yes. - In other cases, move the Finetune slider or click No and adjust the Advanced detection settings. Note: The Automated Setup may not work in all situations. If the subject is not detected correctly, see the Advanced detection settings below. Advanced Detection Settings - Under Video, choose the sample rate. - Under Method, check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if other methods do not work well, or if you work with hooded animals. - Select the tracking method. The options here depend on your experiment settings, including the number of body points you want to track. The optimal method is automatically selected after choosing the type of animal in the Automated Setup. For more information, see Tracking methods in the EthoVision XT Help. - When using Dynamic subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. When using Differencing, set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. For more information: - Choose Help > EthoVision XT Help and search for Advanced Detection Settings. - Choose Help > Video Tutorial and watch the videos under How Subject Detection Works. Trial List Choose Setup > Trial List. Enter your independent variables such as rat ID, first or second phase of the experiment, treatment (with values drug vs. control), dose, type of object, name of the experimenter, etc. If you want, you can pre-define all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them, and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a series of trials in the EthoVision XT Help. Protocols on the Web Featuring EthoVision XT Researchers are encouraged to publish test protocols to improve reproducibility of animal experiments. Browse to https://www.bio-protocol.org/en/searchlist?content=ethovision to find protocols created with or mentioning EthoVision XT. Acquire the Data Protocol Each test described in this manual has one or more specific protocols. See the chapter that applies. Important: Always record your video with EthoVision XT or MediaRecorder. Do not record video with Pylon Viewer or other software. The resulting video file may not be compatible with EthoVision XT. Acquire the Tracks - Check that you have selected the correct Video Source in the Experiment Settings. - Choose Acquisition > Open Acquisition. - Optional: Skip this step if you have already entered the values of the independent variables in the Trial List. Open the Independent Variables tab of the Analysis Results and Scoring pane at the bottom of your screen and enter the values of the independent variables. You can also do this during acquisition. - If you did not plan any trials in the Trial List, click the New trial button in the Playback Control window (Ctrl+F3). - If you planned two or more trials, select in the Acquisition Settings window whether you want to track only the next planned trial or all planned trials. If you carry out batch acquisition and track live, also specify the Inter-trial interval. - Optional: In the Acquisition Settings window, select Auto-start data analysis. Do this to start calculation of analysis results immediately after acquisition. If you choose this option, first create an Analysis profile and optionally a Data profile and a Track Smoothing profile. Choose whether to carry out analysis only for the profiles highlighted in blue in the Experiment Explorer, or for all possible profile combinations. In the latter case, first delete all profiles you do not need for analysis. - Start the trial by choosing Acquisition > Start Trial, clicking the Start trial button in the Playback Control window, or pressing Ctrl+F5. - If you do live tracking, release the animal in the arena. - Data acquisition starts when the Start track condition in your Trial Control Settings becomes true. - The trial stops automatically when the Stop track condition specified in the Trial Control Settings becomes true. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - GigE cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-gige-cameras Chapter: EthoVision XT Basler acA1300-60gm - Monochrome. - Standard camera of PhenoTyper 2. - Interface: Gigabit Ethernet (RJ45 connector, CAT5e or CAT6 (the latter recommended when using 16 cameras). - Sensor: 1/1.8" Progressive Scan CMOS. - Cable length: 10 m (standard) up to 100 m (not tested). - Maximum number of cameras: 16. - Recommended color space in EthoVision XT: Y800. - This camera is also the standard camera in DanioVision and PhenoTyper version 2. - Tested on Operating system Windows 11 Pro, 23H2. - Resolution: For configurations with two or more cameras, the resolution of the resulting video file is reported. The resolution of the single camera image is given in brackets. - Example: 2560 x 2048 (1280 x 1024) means that four images 1280 x 1024 arranged 2x2 result in a video file with resolution 2560 x 2048. The resolution of each camera image in the video file is the same as the original value. - Example: 1280 x 1024 (1280 x 1024) means that four images 1280 x 1024 arranged 2x2 result in a video file with the same resolution. That is, the resolution of the camera image in the video file is reduced to one half of the original value. Tested Configurations with 1 Camera, Desktop and Laptop Computer Operating System Resolution (W x H) Frame Rate (fps) Duration (h) DL or C Desktop Dell Precision W11 1280 x 1024 DL Laptop Dell Precision W11 1280 x 1024 DL Notes: - Graphics card: for desktop, NVIDIA T1000, 8 GB; for laptop, NVIDIA RTX 1000 Mobile. Detection method: Dynamic Subtraction or Differencing. Missing samples: 0.0 to 0.1%. Tested Configurations with 2 Cameras, Desktop Computer Operating System Resolution (W x H) Frame Rate (fps) Duration (h) DL or C Dell Precision W11 1920 x 540 (960 x 540) DL Notes: - Graphics card: NVIDIA T1000, 8 GB. Detection method: Dynamic Subtraction or Differencing. Missing samples: 0.0%. - The cameras were connected to the network interface board FS X550AT2-2TP through a network switch FS 3100-16TMS. For this switch you need an adapter (SFP+ 10GBASE-T Copper 30m RJ-45 Transceiver module) attached to the Ethernet RJ45 connector. We recommend to use CAT6 network cables. Connect the cameras to the powered ports of the switch. - See also Using Multiple GigE Cameras. Tested Configurations with 4 Cameras Computer Operating System Resolution (W x H) Frame Rate (fps) Duration (h) DL or C Dell Precision W11 2560 x 2048 (1280 x 1024) DL Dell Precision W11 2560 x 2048 (1280 x 1024) C Notes: - Graphics card: NVIDIA T1000, 8 GB. Detection method: Dynamic Subtraction. Binning: 1 (see Binning). Missing samples: 0.0%. - The cameras were connected to the network interface board FS X550AT2-2TP through a network switch FS 3100-16TMS. For this switch you need an adapter (SFP+ 10GBASE-T Copper 30m RJ-45 Transceiver module) attached to the Ethernet RJ45 connector. Connect the cameras to the powered ports of the switch. - See also Using Multiple GigE Cameras. Tested Configurations with 16 Cameras Notes: - Graphics card: NVIDIA T1000, 8 GB. Detection method: Dynamic Subtraction or Differencing. Missing samples: 0.0%. Binning: 2 (see Binning). - Body point detection technique: DL = Deep Learning, C = Contour-based. - For Deep Learning, see also Deep Learning: Requirements and GPUs Tested and Supported. - The cameras were connected to a network interface board FS X550AT2-2TP through a network switch FS 3100-16TMS. For this switch you need an adapter (SFP+ 10GBASE-T Copper 30m RJ-45 Transceiver module) attached to the Ethernet RJ45 connector. We recommend to use CAT6 network cables. With this switch, you need to connect eight cameras to eight PoE injectors because the switch has only eight powered ports. Instead, use a 16-powered ports switch (not tested). - See also Using Multiple GigE Cameras and 16-Camera Configuration. Basler acA1920-40gc - Color camera; recommended for tracking colors in dim light. - Interface: Gigabit Ethernet (RJ45 connector, CAT5e or higher). - Sensor: 1/1.2" CMOS. - Maximum number of cameras: 4. - Recommended color space in EthoVision XT: BYRG. - In the Basler pylon Viewer software the pixel format that corresponds to BYRG is Bayer RG8. See Settings for the Color Camera and Pixel Format and Color Space. - Resolution: For configurations with two or more cameras, the resolution of the resulting video file is reported. The resolution of the single camera image is given in brackets. Tested Configurations, Desktop Computer Operating System Nr. Cameras Resolution (W x H) Frame Rate (fps) Duration (h) DL or C Dell Precision W11 1920 x 1200 30 (DS, DF) DL Dell Precision W11 3840 x 2400 (1920 x 1200) 15 (DS) DL Notes: - Detection method tested: Dynamic Subtraction (DS) or Differencing (DF). Missing samples 0.0%. For tracking monochrome video: color space Y800. For color-marker tracking: color space BYRG. - Body point detection technique: DL = Deep Learning, C = Contour-based. For Deep Learning, see also Deep Learning: Requirements. - Desktop: Dell Precision 3680, Graphics card NVIDIA T1000 8 GB, AdLink 4-port PCIe-GIE74 network interface board. For Deep Learning see also GPUs Tested and Supported. See Also - Cameras Supported by EthoVision XT Basler acA1920-155um - Monochrome. - Interface: USB 3.0. A separate PCIe USB 3.0 interface board is required. - Sensor: 1/1.2" CMOS. - Cable length: 3 m (standard) or 20 m (with powered extension cable, not tested). - Maximum number of cameras: 1. - Recommended color space in EthoVision XT: Y800. - See Install USB 3.0 Cameras. Tested Configurations with 1 Camera Computer Operating System Resolution (W x H) Frame Rate (fps) Duration (h) DL or C Desktop Dell Precision W11 1920 x 1200 60 (DS) DL Laptop Dell Precision W11 1920 x 1200 25 (DS, DF) DL Notes: - Detection method used: Dynamic Subtraction (DS) or Differencing (DF). Missing samples 0.0%. - Body point detection technique: DL = Deep Learning, C = Contour-based. - Desktop: Dell Precision 3680, Graphics card NVIDIA T1000 8 GB. The camera was connected through a Basler USB 3.0 PCIe Interface card. - Laptop: Dell Precision 3591, Graphics card NVIDIA RTX 1000. The camera was connected through a USB 3.0 port on the motherboard. - For Deep Learning see also GPUs Tested and Supported. See Also - Resolution, Frame Rate, and Maximum Trial Duration Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Group Statistics result URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-group-statistics-result Chapter: EthoVision XT Group Statistics Result Aim The Group Statistics & Charts tab shows the statistics for the groups of trials defined in your Data Profile. - In the Group Statistics result table, each group is labeled as the corresponding Result container in the Data profile. The statistics are calculated for the trials/arenas/subjects included in that Result container. For how to group data, see Analyze groups of tracks. - The dependent variables (e.g. velocity) are those specified in the currently-selected Analysis profile. NOTE If you use the default Data profile, all trials are grouped. The Group Statistics & Charts table shows the statistics for all trials together. Procedure Choose Analysis > Results > Statistics and Charts and click the Group Statistics & Charts tab. Example In the following example, the Data profile includes two Result containers: Result 1 for treated subjects, Result 2 for control subjects. The groups have been created with Filter boxes, each selecting a value of the independent variable Treatment, Control or Treated. Each Result Container contains two tracks. The statistics are displayed for each Result container. Result 1 contains the tracks marked as Treated; Result 2 contains the tracks marked as Control. In addition, a chart is created automatically for each dependent variable in the table. See Group Charts. How to Read the Group Statistics - Statistics should be read as follows: [Lower level header] of [Higher level header] is [value in cell]. For example: 415.3275 cm is the Mean of the per-trial Total Distance moved for the tracks contained in Result 1. - N is the number of tracks used to calculate the group statistic for that dependent variable. - Group statistics are split in multiple rows when you define results per time bin and/or zone. In the example below, results are split per zone defined in the Data profile, under Results per zone. See Calculate the Results per Zone. - By default, user-defined independent variables are displayed in the table. To show more independent variables, click the Show/Hide button and choose Independent Variables. - If tracks in a group have different values of an independent variable, the text [multiple values] is displayed for that group. How Group Statistics Are Calculated For most dependent variables, the group Mean is the arithmetic mean of the values of the dependent variable reported in Trial Statistics. For angle variables like Heading, Heading to point, and Head direction (but not for Turn angle), the circular statistics are used. Group statistics are not weighted. For example, if the total distance moved is 100 cm for trial 1 and 200 cm for trial 2, the resulting group mean is 150, independent of how many samples each track is made of. Similarly, the group Standard error, Standard deviation, and the 5-number summary (Minimum, First Quartile, Median, Third Quartile and Maximum) are calculated from the single values of the dependent variables reported in Trial Statistics. Notes - The number of decimals in the Trial Statistics and Group Statistics is fixed to four. When exporting the results table, the number of decimals varies depending on the number of integers in the value. See Export the Statistics Result. - The dependent variables displayed in Group Statistics & Charts are those defined in the Analysis profile chosen from the list in the toolbar. - The statistics displayed in Group Statistics & Charts are those selected under Group Statistics for that variable in the currently active Analysis profile. Group statistics are always measures of central tendency, either a Mean (with Standard deviation and/or Standard error) or the 5-number summary (Minimum, First Quartile, Median, Third Quartile and Maximum). You cannot calculate, for example, the group total of distance moved. - The group statistics can be calculated for all the trial statistics, except for the standard error, the standard deviation and the variance. For example, you cannot calculate the group mean of the trials' standard deviations of a variable. - To add and remove statistics, right-click any column header for the dependent variable for which you want to add or remove the statistics, and select Properties. On the Trial Statistics and Group Statistics tabs, select the statistics that you require. - See also Analyze Groups of Tracks. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Head directed to zone URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-head-directed-to-zone Chapter: EthoVision XT Definition A discrete (state event) variable that is scored when the subject's head is directed towards a zone or a circular area around a point. See Define Zones and Draw a Point. NOTE Head directed to zone is not available if your experiment is set to: - Center-point detection. - Color marker tracking. - Live Mouse Tracker. - Center-point, nose-point and tail-base detection, with two subjects per arena tracked with Deep Learning. Calculation - The Head direction line is calculated. See Head Direction. - If the Head direction line crosses the zone of interest (or a circular area around a point), the value of Head directed to zone for that sample is set to 1. The samples with 1 are used to calculate the duration of Head directed to zone. The figure below shows Head directed to zone in the exported data file (Analysis > Export > Raw Data). Two samples are highlighted, one when the head is directed to the zone (circle), the other when it is not. How to Specify Head Directed to Zone - Click the Add button next to Head directed to zone. - In the Head directed to zone tab, under Zone of interest select a Zone or a Point. For the latter, you can select either a point you defined in the Arena Settings or the center of a zone. Because a point has an infinitely small surface area, you need to define a circular zone around the point. The default radius is 0.1 cm. The smaller the radius around a point, the less likely it is that the animal's head is exactly directed at this point. - Next, you can specify when Head directed to zone should be calculated, depending on the location of the animal: - Calculate when: From this list you select the body point that should be in the zone selected in the In list. If you select All detected body points, Head directed to zone is only calculated when all three body points are in the zone selected in the In list. - In: Select one of the zones from this list. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - Head directed to zone is based on the Head direction variable, which in turn depends on which method is used to track the nose-point. See Head Direction. - Head directed to zone is not available if your experiment is set to only center-point detection or color marker tracking. - If you swap the nose-point and the tail-base point in the Track Editor, the Head direction line is updated, and it is calculated as the prolongation of the segment joining the nose-point and the center-point. Head directed to zone is calculated based on the new angle. - If you edit the position of the nose-point or the center-point in the Track Editor, the value of Head directed to zone does not change. Applications Head directed to zone is especially designed for use in the Novel Object Test. Exploration of a novel object is normally defined as directly attending to the object when the head is within a 2 cm radius of the object (Ennaceur and Delacour (1988) Behavioural Brain Research, 47–59). In EthoVision XT, you calculate Head directed to zone when the Nose-point of the animal is within a 2 cm radius from the center of the zone you have drawn around the novel object. Orientation - Meander - Heading - Heading to Point - Head Direction - Turn Angle - Angular Velocity - Body Angle - Body Angle State - Rotation Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Heading to point URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-heading-to-point Chapter: EthoVision XT Definition The direction of movement of the nose, center or tail-base point of the current sample relative to a point of interest. See Define zones and Draw a point. If your experiment is set to Center-point detection or Color marker tracking, calculations are based on the center point. Calculation Heading to point is calculated in a way similar to Heading. The difference is that for Heading to point the reference line is the line that connects the previous sample and the point of interest. For Heading, the reference line is the line parallel to the x-axis. Heading to point for sample k is the angle α formed by the segment joining the samples k-1 and k, with the line connecting sample k-1 and the point P (a point of interest or the center of a zone). Range Heading to point ranges from -180° to +180°. The closer to zero Heading to point is, the straighter the subject moves toward the point. Negative values occur when the subject moves to the right of the point; positive values in the other case. Below: Example of Heading to point with positive and negative values in a water maze test. The platform has been specified as a target point. The chart shows Heading to point in the Integrated Visualization (Analysis > Results > Integrated Visualization). How to Specify Heading to Point - Click the Add button next to Heading to point. - From the Point of interest list, select the center of the Arena, center of gravity (COG) of a zone, or a point you defined in the Arena Settings. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If your experiment is set to Center-point, nose-point and tail-base detection, click the Body points tab and select the body points for which you want to calculate heading to point. - The mean, standard deviation and variance are calculated with circular statistics. See Statistics available. Applications Use Heading to point to measure the subject's orientation relative to a point of interest. - Morris water maze. Use Heading to point to determine the Heading angle error. The Heading angle error is usually determined after the animal has traveled a minimum distance, or after the first few seconds of each track. The Heading angle error at this point is the deviation from a direct line from starting point to center of the platform. Below: The Heading angle error (α) in a water maze. The first two samples of the track are displayed. The arrow indicates the release point. How? First, in the Data profile under Nesting choose Time, and select for example from 0 to 2 seconds. This means that analysis is done on the data points of the first two seconds of the track. Next, in the Analysis profile choose Heading to point and select the platform as point of interest. As Trial Statistic, choose Mean. For other water maze output variables, see also the EthoVision XT 19 - Application Manual. - Novel object test. Use Heading to point to determine the subject's movement relative to an object. The assumption is that an animal is interested in a novel object when it is heading towards the center of the object. Head Direction Definition The smallest angle formed by the Head direction line of the current sample relative to a line parallel to the x-axis in the coordinate system. See also Head directed to zone. The Head direction line is determined for each sample, based on the contour of the detected subject. It originates from the nose-point but it does not necessarily pass through the center-point. The angle α is assigned to the dependent variable Head direction for that sample. Note: Head direction is not available if your experiment is set to: - Center-point detection. - Color marker tracking. - Live Mouse Tracker. - Center-point, nose-point and tail-base detection, with two subjects per arena tracked with Deep learning. Examples Below: An example of Head direction when exported in the raw data file (Analysis > Export > Raw Data; locate the Head direction column). The angle is negative (-180°, 0] when the Head direction line departing from the nose-point lies left to the line parallel to the x-axis. The angle is positive [0, +180°] in the opposite case (in this example the x-axis is in the default position; it is horizontal and points to the right). The top-left picture shows the Head direction at the sample highlighted below. Important: Note that the value of Head direction depends on the orientation of the x-axis set in the Arena Settings. Head Direction Range Head direction ranges from -180° to +180°. Therefore, values like -179 and +179 represent very similar orientations (head pointing to the left). Take this into account when interpreting the raw data. How to Specify Head Direction - In the Analysis profile, click the Add button next to Head direction. - Complete the procedure to add the variable. See Calculate statistics: procedure. Head Direction Notes - Head direction is a very different thing than the Turn angle based on the nose point. The latter variable measures the direction of movement, not the orientation of the head. See Turn angle. - You can check the head direction line during data acquisition. Click the Show/Hide button on the toolbar, select Track Features and make sure Head direction is selected. Next, let the animal move in the arena or play the video file. The real time Head direction values are shown in the Analysis Results and Scoring pane. - The mean, standard deviation and variance are calculated with circular statistics. The mean Head direction represents the average orientation of the animal relative to the x-axis. See Statistics available. - Head direction is calculated relative to the orientation of the x-axis you have chosen in the Arena Settings used for that trial. By default, the x-axis is horizontal and pointing to the right. If the x-axis is not horizontal or is pointing to another direction, Head direction is calculated based on that axis direction. - Note: If you swap nose- and tail-base points, or interpolate those two points, the Head direction line is recalculated as the angle formed by the segment joining the nose-point and the center-point and the x-axis. - If you edit the position of the nose-point or center point, the value of Head direction does not change. - Be careful when interpreting values of Head direction relative to objects, for example two zones, or values extracted from different arenas. Example: In a mirror test, we want to measure the head direction of the fish, and compare the data between two arenas. The mirror is placed at opposite sides in Arena 1 and Arena 2. You can see that the same orientation relative to the mirror is measured with different angles: - For a negative angle in Arena 1: Angle in Arena 2 = Angle in Arena 1 + 180° (see the figure below, top). - For a positive angle in Arena 1: Angle in Arena 2 = Angle in Arena 1 - 180° (bottom). To compare the results between arenas, convert angles from Arena 2 to Arena 1 (or vice versa). Head Direction Applications Head direction is useful for studies of spatial orientation and searching behavior. For this you can, for example, use the average and variation in Head direction. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - In zone URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-in-zone Chapter: EthoVision XT Definition A discrete (state event) variable with two possible states, In zone and Not in zone, depending on whether the body point chosen is within a zone (or group of zones). The state for a specified zone is determined for each sample by comparing the coordinates of the chosen body point with the coordinates that make up the zone of interest. How to Specify In Zone - Click the Add button next to In zone and click the In zone tab in the window that appears. - Under In the following zones, select the zones you want to analyze. For example, if you want to calculate the total time the animal was in Zone 1, select Zone 1. If you have chosen two or more zones, select how body points should be analyzed: - For each selected zone: The body points are analyzed in each zone separately. - When in any of the selected zones: The body points are analyzed when in any of the selected zones. - When in all selected zones: The body points are analyzed when in all those zones simultaneously. - When not in any of the zones: The body points are analyzed that are in none of the selected zones. - Under From following body points, select the points you want to consider for the calculation. For example, select Nose-point if you want to calculate the statistics of the time the nose point was in a specific zone. By default, Center-point is selected. If you have chosen two or more body points, select one of the following from the list: - For each selected point: Statistics are calculated for each point separately. - If any point is in zone: Statistics are calculated for when any of the selected points is in the zone. - When all points are in zone: Statistics are calculated for when all the selected points are in a zone simultaneously. - Under Threshold, enter the Zone exit threshold. That is, once the animal's body point is detected in the zone, the animal is considered to be in the zone until its distance from the zone border (when outside the zone) exceeds that threshold. Default: 0 cm. Use this option to remove false re-entries resulting from random movements of the body point around the zone border. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - If your experiment is set to Only center-point detection or Color marker tracking, the In zone variable is calculated for the center-point. - To find a good Zone exit threshold for In zone, plot the values of Distance moved for the body point you are interested in. For instance, in a Novel object test, plot the distance moved for the nose-point while the subject explores an object, that is, while its nose-point is within the border of the zone "object". Take note of the variation in the per-sample distance moved and set the Zone exit threshold higher than this range. - If two zones are adjacent (that is, not overlapping), the subject's body point is supposed to be either in one or the other zone. However, when the zone exit threshold is greater than zero, the subject's body point may not yet be outside zone 1, and (by definition) be already in zone 2. To prevent this, redefine the two zones so that there is a gap between them, with its width at least the same as the threshold. - When you export In zone as raw data, the values are exported for each sample time, with possible values 0 (Not in zone), 1 (In zone), or - (unknown). See Export the Raw Data (Track and Dependent Variables). - When a body point is missing for more than three consecutive samples, the In zone state ends and the remaining missing samples are not assigned to any state (neither In zone nor Not in zone). - If you analyze the time that the subject spent in a zone that includes a hidden zone, the results are only given for when the subject is visible (and therefore detected) in the larger zone. If you want to calculate the total time in that zone including the time spent in the hidden zone, select both zones in the In zone settings (step 2 above), and sum up the time values for the two zones reported in the results table. Application In zone is a standard variable for any study involving the usage of space by animals. For example: - Open field: How much time did the animal spend by the walls, and how long did it take to cross the open center? (for example, Berendsen et al. 1994, Behav. Pharm. (Suppl. 1): 81). - Maze studies: How many errors did the animal make? (for example, Ploeger G.E. 1995, PhD thesis, Utrecht University). How long did it take to get to the target? (Ploeger et al. 1994, Behav. Neurosci., 927–934). How many times did the animal enter the open arms in a plus maze? (Law et al. 2003, J. Neurosci.: 10419–10432). - Four-way olfactometer: How much time did the animal spend in the treated odor field? When did it first enter one of the arms? (Kaiser and de Jong 1994, Behav. Proc.: 175–184). - Water-maze: How much time does the animal spend in an 18-cm wide path (Whishaw's corridor) from the starting location to the platform, designated as the correct route? If a rat deviated from this route, it received a maximum of one error on that trial (Whishaw's error, Whishaw 1985, Behav. Neurosci. (5): 979–1005), indicating that it did not show a direct swim path. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Install GigE Cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-install-gige-cameras Chapter: EthoVision XT Cameras Aim: To power the GigE cameras without the PoE injectors. This topic applies when you have a 4-port Ethernet interface board to connect the GigE cameras to your EthoVision XT computer. Prerequisites - You have installed a 4-port Ethernet board. See Install an Ethernet Board for GigE Cameras. Procedure Power cable and connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. If a separate cable is not available, you can disconnect the cable that from the power supply (PSU) goes to the hard disk (HD) and connect that end to a Y adapter cable, whose other two ends go to the hard disk and to the Ethernet board. Notes - When your Ethernet board is not powered, you must power the camera using a Gigabit Power-over-Ethernet injector (PoE injector; one per camera). The data transfer rate of the PoE injector must be 1 Gbit/s. See Connect the GigE Camera to the PC. Install Basler Camera Driver Software Aim: To install the software that enables you to configure the camera, for example, to set the video frame rate or the exposure time. IMPORTANT: Whenever possible, install the Basler driver software from the setup file of EthoVision XT, following the procedure below, not from the original Basler driver installation file Basler_pylon_[version number].exe. If, for any reason, you must install the driver from that file, follow the note at the end of this topic. This topic applies to Basler GigE cameras (model name ending with gm or gc), and Basler USB cameras (model name ending with um). Procedure (Recommended) - If you have not done so, download the EthoVision XT installation files from my.noldus.com. - Double-click EthoVision XT - Setup - [version number].exe. If you have already installed EthoVision XT, select Modify; otherwise select Install. - Under Drivers and Tools, select: - Basler GigE camera driver if you have Basler GigE cameras. - Basler USB camera driver if you have Basler USB 3.0 cameras. - Click Install/Update and continue with installation. - Next: Assign IP addresses. Procedure (Manual Installation) If you need to install the camera driver software from the original installation file, do the following: - If you have the installation file already, make sure that its version is the version that EthoVision XT uses. For Basler cameras, this is Basler_pylon_7.5.0. Skip the next step and go to step 3. - To download the driver, log in to my.noldus.com. Choose Downloads > EthoVision XT > Drivers and Tools. For Basler cameras, choose Basler Camera Driver. Extract its content and copy everything to the local disk. - Double-click the .exe file. Accept the Terms and Conditions, then click Next. - For the Basler driver: Under Profiles, select Custom and click Next. - For the Basler driver: Under Features, choose: - For GigE Vision cameras, GigE Camera Support. - For USB 3.0 cameras, USB Camera Support. - Also select: - pylon Viewer and - DirectShow Support. - Complete the installation. Notes - Always install the drivers that you download from the Noldus web site. Do not install drivers from other sources, unless requested by Noldus Support. Settings of the Ethernet Board Aim: If the camera is set up correctly based on this Help and you have checked all the system requirements and yet there are camera issues in EthoVision XT, for example dropped frames, it may be good to check the settings of the Ethernet interface board. Procedure - In the Windows search field, type device. In the results list, click Device Manager. - Open the Network Adapters item. - Locate the item that has the same name as the network port connected to the camera. - Right-click that item in the Device Manager and select Properties, then click the Advanced tab. - Adjust the settings as follows: - Interrupt Moderation: Disabled. - Interrupt Moderation Rate: Off. - Receive Buffers: (set as required). - Jumbo Packet: 9014 Bytes. - Click the Power Management tab and de-select Allow the computer to turn off this device to save power. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Installation and License Activation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-installation-and-license-activation Chapter: EthoVision XT Install EthoVision XT To install EthoVision XT - Browse to https://my.noldus.com. - Log in or register using the registration code on your welcome letter. - Click Downloads, then EthoVision XT. Under Versions, download the EthoVision XT 19 - Installation Package [version number] zip file. - Unzip the file and save the content to your PC. - Double-click the file EthoVision XT - Setup - [version number].exe. - Under Set Application Language, select either English (United States) or Chinese (Simplified). Under Installation type, select Standard. Notes: - You can also change the language at any time in EthoVision XT. Choose File > Preferences > Language, then close and restart EthoVision XT. - If you want to use video cameras with EthoVision XT, first install the appropriate camera interface boards and drivers on the EthoVision XT computer. For details, see Camera Installation in the EthoVision XT Help. To open the Help, press F1 in the software. - If you save the installation files on a network drive before installation, copy them to your PC before running the Setup file. Make sure that all files included in the installation zip file are copied to your PC. Activate Your License With a USB Hardware Key If you have a hardware key, insert it into a USB port of the computer and start EthoVision XT. If you upgrade your EthoVision XT license, start EthoVision XT and enter the Upgrade key in the window that opens. With a Software License Key If you received a software license key, start EthoVision XT and activate your license. Choose between a Floating license or a Computer-locked license. - Floating - The license can be used on different computers, though not simultaneously. Choose this solution if you want to be flexible about which computer you use EthoVision XT on to acquire data, and your computers are connected to the internet. - Computer-locked - The license is linked to one specific computer. To activate your license, that computer must have an internet connection, or you must have a smartphone with an internet connection. If you want to use EthoVision XT on a second PC to analyze existing data, not acquire new data, you can run it on that PC in Analysis mode, which does not require a license. Your First EthoVision XT Experiment Create an Experiment EthoVision XT creates an experiment based on the choices you make in the following guided procedure. For example, the type and color of the animals, the test enclosure, etc. - In the EthoVision XT Startup window, under New experiment, click New from template or choose File > New from Template. - Select Apply a pre-defined template and follow the instructions in the setup guide. Choose whether you track from video files or live, select the study species, the type of arena, etc. - In the New Experiment window, enter a Name for your experiment. - Browse to the Location in which you want to store your experiment. Then click OK. - You are now ready to complete setting up your experiment. You must complete the arena set-up and adjust the Detection Settings. You can optionally make a Trial List, Trial Control Settings, and Manual Scoring Settings. Notes: - If your test setup is not among those included in the template list, choose File > New. This way you create an experiment without predefined settings. - If you work with the DanioVision Observation Chamber, see the DanioVision DVOC-0041 - Reference Manual. Working with EthoVision XT Experiments An EthoVision XT experiment is the container of all information related to an experimental setup. The Experiment Explorer lists all components of the experiment currently open. By default, your experiment is located in: C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments\ All experiment files are stored in a folder with the same name as the experiment. Note: Settings and Profiles are collections of settings that belong to a specific function, for example the arena. You can define multiple settings and later choose which to use for a specific trial or group of trials. For example, in a water maze experiment, for a first set of trials, use Arena Settings 1 with the platform defined in a specific quadrant. For another set of trials, use Arena Settings 2 where the platform is defined in a different quadrant. Important components in your experiment: - Experiment Settings - Basic properties that do not change throughout the experiment. - Arena Settings - Draw the arena and zones. - Detection Settings - Detect the subject in your camera image. - Acquisition - Record data and video. - Data Profiles - Select which part of your data to analyze. - Analysis Profiles - Specify output variables (distance, speed, etc.). - Results - Results options. The Experiment's Basic Properties Choose Setup > Experiment Settings. Specify the options listed below. Depending on your EthoVision XT license, some of the options may not be available. If you created a new template experiment, you already specified most properties of your experiment. Video Source Choose whether you want to track From video files or from the live camera image (Live tracking). In the latter case, select the cameras that you are going to use. If your cameras are not listed, install the camera drivers. See Camera Installation in the EthoVision XT Help. Number of Arenas An arena is a closed space where subjects move. Select the total number of arenas in your camera images. For example, select 1 for one water maze or open field; select 4 for four open fields, or four PhenoTyper cages. Number of Subjects per Arena Specify how many individuals per arena you want to track. Note: Because this guide applies to the Base version of EthoVision XT, it assumes that you track one subject per arena. Tracked Features Select which body points you want EthoVision XT to detect: the center-point only or the center-point with nose-point and tail-base. Body Point Detection Technique If you track the nose-point and the tail-base point, select which technique should be used: the contour of the subject or a trained neural network (Deep learning). The Deep learning option only applies to rodents, and with one or two subjects per arena. Analysis Options With Activity analysis, you can have EthoVision XT detect behaviors like freezing in rodents and immobility in the Porsolt swim test. With Behavior recognition, EthoVision XT detects several rodent behaviors like grooming, sniffing, and rearing. Units Select the measurement units you prefer. Source: EthoVision XT 19 - Quick Start Guide --- ## EthoVision XT 19 - Introduction to Data Analysis - Analysis Advisor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-introduction-to-data-analysis-analysis-advisor Chapter: EthoVision XT Analysis Advisor What Do You Want to Do? - Simple calculations (e.g. total distance moved, average velocity) - Zone visits (entries and time spent) - Other analyses with zones - Analysis in relation to the path - Analysis of regular time intervals - Analysis of event transitions and sequences Notes - To analyze groups of tracks, define first your groups in the Data profile. See Define Groups of Tracks. - Tip: If none of the dependent variables represents an adequate behavioral endpoint for your research question, please contact Noldus so we can discuss your analysis requirements. EthoVision XT contains functions which can process the raw data based on JavaScript code. See Custom Variables. - For information on analysis related to specific apparatuses, like the Open Field, the Morris Water Maze, the Novel Object Recognition and others, see also the EthoVision XT 19 Application Manual. Simple Calculations (e.g. Total Distance Moved, Average Velocity) What Do You Want to Do? - Calculate the results for the whole arena - Calculate the results per zone Calculate the Results for the Whole Arena - Tip: Smooth the tracks to get more realistic measures of distance. See Smooth the Tracks. - In the Experiment Explorer, click an Analysis profile, and then click the button next to the dependent variable if it is not already selected. For example, Distance Moved or Velocity. In the Trial Statistics tab, select the statistics you want to calculate (for example, Total for Distance Moved, and Mean for Velocity). - In the Experiment Explorer, click Statistics and Charts, then click the Calculate button. Calculate the Results per Zone - Create a new Data profile or open an existing one. - Click the Settings button on the Result box. In the Result Settings window, select Results per Zone. - Under Settings - For Zones, select the zones you want to analyze your data for. - Under Settings - For Body Points, select which body points should be in the selected zones. This option is only available if you track the three body points. - Click OK. - In the Analysis profile, define the variables you want to calculate. - In the Experiment Explorer, under Results, click Statistics and Charts, then click the Calculate button. Notes - The Zone Exit Threshold works this way: once the animal's body point is detected in the zone, the animal is considered to be in the zone until its distance from the zone border exceeds that threshold. Use this option to remove false re-entries resulting from random movements of the body point around the zone border. If you enter a value greater than 0, you make sure that when the animal exits the zone border for a short distance (less than the threshold), that data will be included in the results for that zone. For more information, see In Zone. - Select Apply to All Results if you want to copy the settings specified in the Results Settings window to other Result boxes. This applies if you have defined more than one Result box in that Data profile. Zone Visits (Entries and Time Spent) What Do You Want to Do? - Calculate the number of entries and time spent in specific zones - Calculate the number of entries and total time spent in two or more zones - Calculate the number of entries and time spent in an intersection of zones - Analyze the visits to target zones and errors - Find out which zone the subject visited first - Count the number of times that the subject was in a zone for more than N seconds - Calculate the time that the three body points were in a zone Calculate the Number of Entries and Time Spent in Specific Zones - In the Analysis profile, under Location, click the button next to In Zone. Specify the zones you are interested in. In the Trial Statistics tab, select Frequency (for zone entries) and Cumulative Duration (for time spent). - Click Statistics and Charts, then Calculate. Calculate the Number of Entries and Total Time Spent in Two or More Zones If you want to group results for two or more zones, like the open arms of an Elevated Plus Maze: - In step 1 above, specify the zones you are interested in, and make sure that When in Any of the Selected Zones is selected. In the Trial Statistics tab, select Frequency and Cumulative Duration. - Click Statistics and Charts, then Calculate. Alternatively, in the Arena Settings make a Cumulative zone from the selected zones and calculate the frequency and cumulative duration in this zone. Calculate the Number of Entries and Time Spent in an Intersection of Zones When two zones are defined in different layers, it is possible to analyze their intersection. In this example, the intersection of the quadrant "North-West" and the annulus-shape "Maze Border": - In the Analysis profile, under Location, click the button next to In Zone. Specify the zones you are interested in, and make sure that When in All Selected Zones is selected. In the Trial Statistics tab, select Frequency and Cumulative Duration. - Click Statistics and Charts, then Calculate. Analyze the Visits to Target Zones and Errors For example, in a Barnes Maze test, calculate how many non-target holes were visited and the time to the first visit to the escape hole (target visit). --- ## EthoVision XT 19 - Introduction to Data Analysis - Analysis in Relation to the Path URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-introduction-to-data-analysis-analysis-in-relation-to-the-path Chapter: EthoVision XT Analysis in Relation to the Path Calculate the Initial Heading Angle in a Water Maze Experiment That is, calculate the deviation from the optimal route, for example in the first 15 cm of the swim path. Specify the track segment from track start until the animal swam 15 cm with a Data profile, then select the dependent variable Heading to Point in an Analysis profile. - Smooth the tracks to obtain a swim path less influenced by noise. - In the Data profile, in the Components pane, under Nesting, click the button next to Free Interval. Specify the interval "From Track Start to Total Distance Moved >= 15 cm". See Nest Over a Free Interval. - In the Analysis profile, specify the dependent variable Heading to Point. Select the center point of the platform. In the Trial Statistics tab, select Mean. - Click Statistics and Charts, then Calculate. Split the Track Into Segments Based on Distance Traveled Specify the track segments in the Analysis profile. - In the Analysis profile, under Custom Variables, click Free Interval. Specify the interval "From Distance Moved - Total >= 0" to "Distance Moved - Total >= 100 cm". Select the option Calculate Statistics Per Interval. In the Trial Statistics tab, select Cumulative Duration. - Click Statistics and Charts, then Calculate. The duration is shown in the columns for each 1-meter segment (Interval Occurrence 1, Interval Occurrence 2, etc.). Analysis of Regular Time Intervals Split the track in a number of regular intervals, and then calculate statistics for each interval. Specify the track segments in a Data profile and select the dependent variable Distance Moved in an Analysis profile. - In the Data profile, in the Result box, click the Settings button and then select Results per time bin. Specify the length of the single time interval. - In the Analysis profile, specify the dependent variable. In the Trial Statistics tab, select the statistic (for example, Total for Distance Moved). - Click Statistics and Charts, then Calculate. Analysis of Event Transitions and Sequences What do you want to do? - Calculate transitions between zone visits - Analyze bouts of behavior Calculate Transitions Between Zone Visits For example, how many times did the subject go from zone A to zone B? Or, in a Y-maze experiment, how many times did the subject go from zone A, to B, then C? Or, in a radial maze experiment, how many 8-arm visits were made without any revisits? - In the Analysis profile: for zone alternations (like in a Y-maze test), choose the dependent variable Zone Alternation. For transitions in general, choose Zone Transition and define the sequence (for example, in a radial maze test, Arm 1 > Arm 3 > Arm 5). Select the sequence of zone visits. If necessary, select more sequences. In the Trial Statistics tab, select the statistic Total Number. - Click Statistics and Charts, then Calculate. Analyze Bouts of Behavior If you define a bout of behavior as a group of events where the interval t between them is lower than a specified limit (t < tmax), you can detect those bouts with the Free Intervals function. For example, look for bouts of movement, where single instances of the state Moving are separated by less than five seconds. In the Analysis profile, choose the dependent variable Free Interval. For an example, see Detect Bouts of Behavior in Examples of Free Intervals in the Analysis profile. Basics of Data Selection Aim To carry out analysis on a selection of data, not all data. Learn About - The Data Profiles screen - Create your data selection - Work with data selection boxes Notes - You can create as many Data profiles as you want, containing different criteria for data selection. - Data selection is optional. If you do not select data, the default data selection profile is used, which contains all data in your experiment. The Data Profiles Screen To Access the Data Profiles Screen - Choose Analysis > Data Profile > New. Enter a name for the new Data profile and click OK. - In the Experiment Explorer, in the Analysis folder, right-click Data Profiles, select New, enter a name and press Enter. You can also open an existing data profile. Choose Analysis > Data Profile > Open. Default Data Profile The Data Profile contains two selection boxes: - The Start box (left) contains all tracks currently stored in the experiment. - The Result 1 box (right) contains the data used for analysis. The two boxes are connected through an arrow. This means that in the default Data profile all data are used for analysis. Create Your Data Selection By default, all tracks in your experiments are selected. To refine your selection: - In the Components pane, click the button next to the variable you want to use. If you do not see the Components pane, click the Show/Hide button on the toolbar and select Components. - A new box appears in the top-left corner of the Data Profiles window, and a new window appears on top, listing all possible values or characteristics of the chosen variable. For example, which treatment level you want to select for analysis. Choose the values that specify your selection and click OK. - Drag the box over the arrow that connects the two preexisting boxes. When the arrow turns white, release the mouse button. If you do not see all buttons as shown above, click the More button. To Create Complex Selections You can define complex data selections by inserting two or more selection boxes in the sequence. See Combining Selection Boxes. To Create Different Selections in the Same Data Profile By clicking the button next to Result (last button in the Components pane), you get a new Result box. Additional Result boxes allow you to view the results in the same table for different data selections. For example, create groups based on an experimental treatment and compare the results. See Define Groups of Tracks. --- ## EthoVision XT 19 - Introduction to Data Analysis - Analysis With Zones URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-introduction-to-data-analysis-analysis-with-zones Chapter: EthoVision XT Analysis With Zones Find Out Which Zone the Subject Visited First For example, in a dual choice test, in a T maze, leaf disc, or a Y-maze, etc. - In the Analysis profile, specify the dependent variable In Zone. In the Trial Statistics tab, select Latency to First. - Click Statistics and Charts, then Calculate. - Under Export, click Statistics. In the exported file check which zone has a lower Latency value. Note: Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. Calculate Target Visits and Errors - In the Analysis profile, specify the dependent variable Target Visits and Errors. Select the target zones and the non-target zones. In the Trial Statistics tab, select Total Number and Latency to First. - Click Statistics and Charts, then Calculate. Note: Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. Use the variable Target Visits and Errors also for a radial-arm maze test. Count the Number of Times the Subject Was in a Zone for More Than N Seconds - In the Analysis profile, specify the dependent variable Free Interval. Define an interval: - From: Dependent variable: In Zone (specify the zone in the settings); Statistic: Current Duration > N seconds. - To: Dependent variable: In Zone (specify the same zone); Statistic: Current; Value: When Not in Zone = true. - In the Trial Statistics tab, select Frequency. - Click Statistics and Charts, then Calculate. If you want to calculate the actual duration of each of those visits, export the results table, then add N seconds to each result under Cumulative Duration. Calculate the Time That Three Body Points Were in a Zone With this solution, the animal is considered: - In a zone only when all its body points are within the zone. - Out of the zone only when all its body points are outside the zone. Example: A Y-maze test, with arm zones A, B, C. - In the Arena Settings, define the main zones of interest. - In the Arena Settings, create additional zone groups, one for each main zone. In the example of a Y-maze, create 3 zone groups. In each group, define a cumulative zone including all zones but the focal zone — for example, "Other Than A", "Other Than B", etc. Each of these cumulative zones must be in separate zone groups. See Cumulative Zones. - In the Analysis profile, from each main zone A, B, C, define a Free Interval which goes from In Zone (Frequency > 0, for zone 1, with all three points) to In Zone (Current = true, for "Other Than Zone 1"). Repeat this step to create more Free Intervals. - Calculate the statistics or visualize the Free Interval. --- ## EthoVision XT 19 - Introduction to Data Analysis - Other Analyses With Zones URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-introduction-to-data-analysis-other-analyses-with-zones Chapter: EthoVision XT Other Analyses With Zones Calculate Path Length and Speed for Specific Zones In this case you calculate dependent variables for track segments. First, specify the track segments When in Zone with a Data profile and then choose the dependent variables in an Analysis profile. - In the Data profile, in the Result box, click the Settings button and then select Results Per Zone. Specify the zones you are interested in. - In the Analysis profile, click the button next to the dependent variable you require, e.g. Distance Moved or Velocity. In the Trial Statistics tab, select the statistic (e.g., Total for distance moved and Mean for velocity). - Click Statistics and Charts, then Calculate. Calculate Path Length and Speed for a Combination of Zones - In the Data profile, in the Components pane, under Nesting, click the button next to In Zone. Specify the zones you are interested in. Select the option that you require: - When in Any of Selected Zones to analyze when the animal was in one or another zone. - When in All Selected Zones to analyze when the animal was in all the zones simultaneously. This assumes that the zones are at least partially overlapping — for instance, a quadrant and a border zone in a water maze. If zones are not overlapping, data are not selected since the subject's body points cannot be in two non-overlapping zones at the same time. - In the Analysis profile, click the button next to the dependent variable (e.g. Velocity). - Click Statistics and Charts, then Calculate. Calculate the Distance Traveled Before Reaching the Platform in a Morris Water Maze Use the function Free Interval in the Data profile to select the interval from the track start to when the animal stays on the platform for a specified duration, for example five seconds. - In the Data profile, in the Components pane, under Nesting, click the button next to Free Interval. Specify the interval: - Start Criterion: Time (Track Start). - Stop Criterion: Dependent variable In Zone. Statistic: Current Duration >= 5 s. - Select Ignore Last Interval if Incomplete. This will consider only cases when the animal reaches the platform. - In the Analysis profile, click the button next to Distance Moved. In the Trial Statistics tab, select Total. - Click Statistics and Charts, then Calculate. EthoVision XT only gives results for those trials where the animal stayed on the platform for five seconds. In all other cases, including when the animal swims over the platform but does not stop there, EthoVision XT shows "-". Calculate the Distance Traveled or Time Before Entering a Zone For example, in a Barnes maze, you want to calculate the total distance moved before the animal enters a zone. For Distance Traveled - In the Data profile, in the Components pane, under Nesting, click the button next to Latency to Zone. Specify 1st Visit, the zone, and keep Interval Before Zone Visit selected. - In the Analysis profile, click the button next to Distance Moved. In the Trial Statistics tab, select Total. - Click Statistics and Charts, then Calculate. For Time If you want to know the time before the animal enters a zone, you do not need a Data profile. - In the Analysis profile, click the button next to In Zone. Choose the zone and in the Trial Statistics tab, select Latency to First. - Click Statistics and Charts, then Calculate. Note: Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. Calculate the Distance Traveled or Time Before a Specific Zone Visit In this example, we want to know the distance traveled or the time taken to stay in a zone for more than a specific duration. For Distance Traveled - In the Data profile, in the Components pane, under Nesting, click the button next to Free Interval. Specify the interval from Time (Track Start) to the dependent variable — for example, "From track start to Current Duration >= 20 s". This will pick out the interval until the animal stays in a zone for at least 20 seconds. - In the Analysis profile, click the button next to Distance Moved. In the Trial Statistics tab, select Total. - Click Statistics and Charts, then Calculate. For Time - In the Analysis profile, under Custom Variables, click the button next to Free Interval. Define the interval. In the Trial Statistics tab, select Cumulative Duration. - Click Statistics and Charts, then Calculate. Find Where a Behavior Occurred The term "behavior" here indicates a state such as Movement, Mobility, Activity, Body Elongation, behaviors scored manually, or behaviors detected automatically. Quantitative Analysis If you are interested in quantitative results (for example, the number of occurrences per zone), specify the zones in a Data profile and select the behavior in an Analysis profile. - In the Data profile, in the Result box, click the Settings button and then select Results Per Zone. Select the zones you are interested in. - In the Analysis profile, select the behavior you are interested in. In the Trial Statistics tab, select Frequency. - Click Statistics and Charts, then Calculate. Qualitative Analysis If you are interested in a visualization, select the behavior and optionally the zones of interest in a Data profile and then create a heatmap of the frequency of visits to the zones. - In the Data profile, in the Components pane, under Nesting, click the button next to the behavior you want to visualize. Optionally, if you are interested in particular zones, in the Result box click the Settings button and then select Results Per Zone. Specify the zones you are interested in. - Click Heatmap Visualization, then Plot Heatmaps. Find Out When the Subject Disappears From View There are situations when you want to know when the subject is no longer found in the arena. In the wire hanging test, used to evaluate abnormalities in muscle strength, the time that the subject remains hanging on the wire needs to be recorded. A way to do this is to measure the time until the subject falls from the wire and disappears from view. - Make sure that the camera view does not include the bottom of the experimental cage, so that when the animal falls the software no longer detects it. - In the Arena Settings, define a hidden zone at the bottom of the arena. Define an entry zone that occupies the lower half of the arena. Make sure that the entry zone partly overlaps with the hidden zone. See Shelters and Other Hidden Zones. - Acquire the tracks. When the subject falls, its center point is first found in the entry zone, then it disappears and is automatically assigned to the hidden zone. - In the Analysis profile, click the button next to In Zone. Select the hidden zone and on the Trial Statistics tab choose Latency to First. - Click Statistics and Charts, then Calculate. --- ## EthoVision XT 19 - Introduction to Data Analysis - The Maximum Distance Moved Smoothing Method URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-introduction-to-data-analysis-the-maximum-distance-moved-smoothing-method Chapter: EthoVision XT The Maximum Distance Moved Smoothing Method Aim To remove outliers in the track, due to erratic detection of objects within the arena. For example, in a DanioVision experiment, if detection is not optimal, the margin of the well is sometimes detected as the fish. Important: If you see many errors, adjust the Arena Settings and/or the Detection Settings. Procedure - Choose Acquisition > Track Smoothing Profile > Open. - Select the Maximum Distance Moved check box and click the Edit button. - Enter the threshold value of distance moved, above which the sample will be set to missing. If the distance moved from sample 1 to 2 is longer than the threshold, sample 2 is set to missing. - Click OK. - Plot the tracks to see the result. Notes - Tip: To know which value of distance to use as a threshold, plot the values of distance moved in the Integrated Visualization, and look at the spikes corresponding to the outliers. Take a value well below the value of the spikes. Be aware that a threshold being too low can remove good data. - The Maximum Distance Moved method is applied after data editing, and after the Smoothing (Lowess) and the Minimal Distance Moved methods (when selected). The smoothed data, not the original data, are used for analysis and for export. Applying the Maximum Distance Moved method does not change the original data. Introduction to Data Analysis Overview of Data Analysis Analysis Functions For data preparation: - Data Profiles. For choosing the data points subject to analysis. You can filter tracks, create groups, select specific time periods or track segments, etc. - Analysis Profiles. For choosing the behavioral endpoints, like speed, distance moved, time spent in a zone, etc. For the analysis results: - Statistics and Charts. For obtaining a table with summary statistics of the dependent variables per trial and summary statistics and charts per group of trials. - Track Visualization. For visualizing data as tracks plotted over a static background video image. - Heatmap Visualization. For visualizing the location where your animals spent most time. - Integrated Visualization. For visualizing the track together with video, and plotting dependent variables against time. - Export (Raw Data, Statistics and GLP Log). To export raw data, dependent variables and their summary statistics, and the GLP log (available with the Quality Assurance module). Note In general, the analysis results depend on a few factors: - Whether you applied Noise reduction during acquisition. - Whether the tracks are smoothed, and how. - Which tracks and data points are selected in the current Data profile. - Which dependent variables and statistics are selected in the current Analysis profile. Important Terms in Data Analysis Dependent Variables In EthoVision XT, a dependent variable is a variable that quantifies the behavior of a subject or marks an event occurred in a trial. - Example 1: To quantify locomotor activity, choose Distance Moved, or Velocity, or Movement as dependent variables. - Example 2: To calculate how many food pellets were dropped by a pellet dispenser, choose Hardware Continuous as a dependent variable. Dependent variables are calculated for each sample of the track, when data are available. The table below shows the Distance Moved calculated for a few samples. X and Y are the coordinates of the center of the subject's body. Note that distance moved is not calculated at time = 0, because there is no previous sample to use as a reference. TimeXYDistance Moved 0-8.7393-26.1678– 0.08-6.8267-26.96992.0740 0.16-4.7220-27.07482.1074 0.24-3.2380-26.62271.5513 State Dependent Variables Some dependent variables are state variables, that is, they have discrete values. For example, In Zone with values 1 (in zone) and 0 (not in zone). The following table shows the In Zone variable calculated for zone A and for a few samples. When the animal's body point is found within zone A, then In Zone = 1, otherwise In Zone = 0. In the example below, the subject's center point enters the zone at 0.16 s. TimeXYIn Zone 0-8.7393-26.16780 0.08-6.8267-26.96990 0.16-4.7220-27.07481 0.24-3.2380-26.62271 Statistics In EthoVision XT, statistics are descriptive statistics of the per-sample values of a dependent variable. - Example 1: To quantify locomotor activity, choose the Total statistic for the dependent variable Distance Moved. Choose the Mean statistic for the dependent variable Velocity. The total distance moved is the sum of the per-sample values of distance. In the example of the table above, the total is 5.73 cm. - Example 2: To calculate the time spent in zone, choose the Total statistic for the dependent variable In Zone. Trial Statistics vs. Group Statistics For each dependent variable you can specify two types of statistics: - Trial Statistics. Statistics calculated per trial. Example: Your experiment contains 100 trials of one animal in one arena. Choose Total as a Trial Statistic for the dependent variable Distance Moved. You obtain 100 values of Total Distance Moved. - Group Statistics. Summary statistics of the Trial Statistics, calculated over all the trials specified in the data profile, or in a group. Example: You have defined two groups of tracks, Treated and Saline, and you want to calculate the Mean and Standard Deviation of Distance Moved and other variables per group. In the example above with the 100 trials, with Group Statistics you would obtain the average and standard deviation of the 100 values of distance moved. --- ## EthoVision XT 19 - Introduction to Data Analysis - Work With Data Selection Boxes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-introduction-to-data-analysis-work-with-data-selection-boxes Chapter: EthoVision XT Work With Data Selection Boxes This topic contains instructions for the basic operations with selection boxes. See also Create Your Data Selection. Move a Selection Box - Click the margin of the box. The mouse cursor changes to a four-headed arrow. - Drag the box to the position you require. - Release the mouse button. The new box is inserted. To move a group of selection boxes: - Draw a box around the boxes you want to move, or click on the boxes you want to select while holding the Ctrl key. As a result, the border of the selected boxes becomes darker. - Hover the mouse on the margin or the colored area of one of the selected boxes. The mouse cursor changes to a four-headed arrow. - Drag the group of boxes to the position you require. Insert a Box in a Data Selection Sequence - Drag the selection box between two boxes, until the connecting arrow turns white. Connect Two Selection Boxes - Point the mouse to the center of the first box, press and hold the left mouse button and drag toward the center of the other box. - Release the mouse button when the pointer has reached the center of the other box. The two boxes are connected. You cannot create connections from the Result box to any other box, and from any box to the Start box. Change the Selection Criteria in a Selection Box Follow the instructions below when you have inserted a selection box and you want to adjust the settings to restrict or widen your selection. For example, when you have selected drug dose = 0.01 and 0.05 in the first instance, and you want to remove 0.05. - Locate the selection box that specifies the criterion you want to change. - Click the Settings button. - Select the appropriate values in the window that appears. Copy and Paste a Selection Box Follow this procedure to quickly duplicate Filter, Nesting, and Results boxes. If needed, you can always change the settings in the new selection box that is created. - Select one or more selection boxes in the Data profile. - Choose Edit > Copy, or right-click and choose Copy, or press Ctrl+C. - If necessary, open the Data profile where you want to copy the boxes to. - Choose Edit > Paste, or right-click and select Paste, or press Ctrl+V. Note that the new selection box is given the same name as the original one, followed by a number (2), (3), etc. Delete a Selection Box - Click the title of the box so the mouse pointer changes to a four-headed arrow. To select a group of selection boxes, draw a box around the selection boxes that you want to delete, or click on each of those boxes while holding the Ctrl key. - Press Delete, or choose Edit > Delete, or right-click and choose Delete. You cannot delete the Start box. You can delete a Result box only if another one has been inserted in the Data Profiles window. If you delete a box within a sequence, the arrows connecting the adjacent boxes are lost. Therefore, you must re-connect the adjacent boxes. Delete a Connecting Arrow - Click the connecting arrow you want to delete. The arrow turns bold to show it is selected. - Press Delete. The arrow is deleted. Source: EthoVision XT 19 Help - Introduction to Data Analysis, Noldus Information Technology --- ## EthoVision XT 19 - Introduction to Trial Control URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-introduction-to-trial-control Chapter: EthoVision XT Introduction to Trial Control This Manual This manual is meant for all users of EthoVision XT: - For users of the Base version. You can find extensive information on the Trial Control conditions and analysis of Trial Control data. This information is not present in the EthoVision XT Help. - For users of the Base version plus the Trial and Hardware Control module. You find all the information you need in this guide. - If you use EthoVision XT in combination with hardware devices, you can find the relevant information in Section 7. EthoVision XT Help For extensive information on EthoVision XT or for troubleshooting, see the EthoVision XT Help. In EthoVision XT, choose Help > EthoVision XT Help or press F1. Other Documentation From the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 Other documentation. There you find: - EthoVision XT 18 - Application Manual for information on common tests including conditioning tests that make use of sub-rules in the Trial Control Settings. - PhenoTyper - EthoVision XT 18 - Reference Manual for information on PhenoTyper and how to connect it to EthoVision XT. - PhenoTyper - EthoVision XT 18 - Service Manual for information about PhenoTyper and devices such as the Noldus Pellet dispenser, the Noldus Lickometer and PhenoWheel. - DanioVision DVOC-0041 - Reference Manual if you use Trial Control with the DanioVision Observation Chamber. Why Use Trial and Hardware Control? Trial Control allows you to automate your experiment. For example: - You want to set a maximum duration for your trials. - You want to automate the start and/or stop of data acquisition. For example: - Start recording when the rat is first detected in the open field. - Stop recording when the rat has reached the platform in the Morris water maze. - Start recording at exactly 12:30:00. - Stop recording after the animal has been in the closed arms of the plus maze for 5 minutes. - You want to automate conditioning schedules, or operate hardware devices. For example: - When the animal presses a lever, have the food dispenser drop a food pellet. - When the animal leaves the shelter, use an External Command action to start a recording with Media Recorder. - When the animal enters the shelter, turn on a light. - Close the door of a radial maze when the animal has exited that arm. To Use Trial and Hardware Control - Open the Trial Control screen. - Define the conditions that, when met during your trial, trigger specific actions. Organize conditions and actions in sequences. - Before starting data acquisition, make sure that those Trial Control Settings are active. For information on how to manage Trial Control Settings, see also Settings and profiles, under File management in the EthoVision XT Help. Conditions and Actions A Condition is a statement that EthoVision evaluates. An Action is a command executed on a variable or a hardware device. You can therefore control your experiment by linking conditions with actions. - Example 1: In a Morris water maze test, stop tracking when the rat reaches the platform (provided that the platform has been defined as a zone). Stop tracking is the action and Rat on the platform is the condition. - Example 2: In a Fixed Ratio schedule, have EthoVision send a command to drop a pellet when the mouse has been detected in the Trigger zone. Drop one pellet is the action and Mouse in the Trigger zone is the condition. You define and link conditions with actions in a graphical form. A condition is followed by an action. The condition checks that the animal is in the zone named "Trigger zone". The action "Drop a pellet" is taken when the condition is met. You can copy, move, connect and delete Trial Control elements such as actions and conditions. For how to do so, see the EthoVision XT Help. Trial Control Rules A Trial Control rule is a set of conditions and actions organized in a logic sequence. It can be viewed as a set of instructions executed during a trial. There are two types of Trial Control rules: - Start-Stop trial rule. For starting and stopping data acquisition. This rule cannot be repeated or deleted. - Sub-rules (available only in EthoVision XT with the Trial and Hardware Control Module). Subroutines of the Start-Stop trial rule, which are meant to carry out specific actions. Sub-rules can start at specific times and be repeated according to conditions specified in a Sub-rule reference. How Trial Control Instructions Are Executed The instructions contained in the Trial Control Settings are carried out from the moment you start a trial, to the moment the trial is stopped. Only the instructions in the Trial Control Settings currently active (that is, highlighted in blue in the Experiment Explorer) are carried out. The program evaluates the Trial Control sequence at each sample time. The rate at which this happens depends on your chosen sample rate, not on the video frame rate. For the Start-Stop trial rule and each active sub-rule, the program remembers which Trial Control boxes were evaluated (active) in the previous sample. Depending on the type of this box: - For a Condition box. EthoVision XT waits until the condition is met. When this happens (condition becomes true), the program passes control to the next box in the sequence. The condition becomes then inactive. - For an Action box. EthoVision XT carries out the action, and passes control to the next box, which becomes active. Then, the Action box becomes inactive. - For a Sub-rule Begin box. Control is passed to the box that follows. The Sub-rule Begin box becomes inactive. - For a Sub-rule End box. This marks the end of a sub-rule. The sub-rule becomes inactive. Control is passed to the Reference box that had called that sub-rule. This Reference checks whether the sub-rule must be repeated. If this is not the case, control is passed to the box following the Reference box. - For a Reference box. Control is passed to the Sub-rule Begin box. The Reference box makes the sub-rule active. The Reference box stays active until the last sub-rule repeat is completed. Next, the Reference box makes the sub-rule inactive and passes control to the box that follows. Next, the Reference box becomes inactive. The events marked in italics above are those you can define in the Analysis profile and analyze or visualize in a chart. When a box becomes active, the previous one becomes inactive. Schematic of Trial Control Instruction Execution - Tracking starts, either manually or because a previous condition has been met. - Control passes to a Condition box (for example "Is mouse on top of Shelter?"), which becomes active. The condition is evaluated. - The Condition is met (becomes true). - Control passes to the next box. In this case, it is an Action. Actions are taken immediately. - The Action box becomes inactive, and the next box becomes active. For clarity, steps 3 and 4 are placed separately. In reality, the software is so fast that when a condition becomes true it also becomes inactive at the same sample time, and control passes to the next box. When plotted against time, the time that the animal is in the zone is indicated by a horizontal bar. When tracking starts, the Action "Start track" becomes active and immediately inactive as control passes to the next box. The condition "On top of Shelter?" becomes active and immediately false since the animal is not in that zone. When the animal enters the zone, the condition becomes true and becomes immediately inactive as control passes to the next box. The action becomes active and immediately inactive as the command "drop a pellet" is sent to the pellet dispenser. Evaluation of Trial Control Boxes - Boxes combined in parallel using operators are evaluated at about the same time, in random order. This means that you cannot establish which condition is evaluated or which action is taken first. - When your trial control is complex, for example when it includes sub-rules or conditions combined with operators, it is possible that two or more Trial Control boxes are evaluated at the same sample time. - When a condition based on a dependent variable is evaluated (and therefore may or may not be met) also depends on the statistic used. - If two or more boxes are evaluated at the same time, an action on a hardware device is taken only after all active boxes that must be evaluated have been evaluated. - If the next box to be evaluated contains a condition that is fulfilled immediately, the program passes control to the next box. Therefore, within one sample time the program can pass control to two or more boxes to the right. - When you stop the trial or the Maximum trial duration has been reached, all Trial Control boxes are deactivated. - When the Rule End box of the Start/Stop trial rule is evaluated for an arena, data recording stops for that arena. From that moment, Trial Control is deactivated for that arena, even in those sub-rules that were ongoing in the meantime. - A trial stops when trial control is deactivated in all arenas. - Actions on hardware devices. A command is sent to a device after all boxes that must be evaluated have been evaluated. However, it may take some time for the outcome to be seen. For example, when a pellet dispenser is almost empty it may take a few seconds before a pellet is released. - Sub-rules. A sub-rule is completed when the Rule End box has been evaluated, or when it is interrupted. - If two or more sub-rules are evaluated at the same time, it is not possible to establish which sub-rule is evaluated first at a specific sample. Important: When two or more actions on hardware devices follow each other, it is possible that they are evaluated at the same sample time. This happens because the computer is fast enough to analyze multiple Trial Control boxes in the sample interval. To make sure that actions are taken in the correct sequence and do not interfere with each other, add a Time condition between the action boxes, so after the first action is carried out EthoVision XT waits for a short time (for example, 0.1 s) before carrying out the next one. Trial Control in Multiple Arenas If your experimental setup includes two or more arenas, Trial Control is applied to each arena separately. This means that, if a condition is met in one arena, EthoVision XT takes the corresponding action in that arena, not the others. Example: The setup includes four cages, each defined as an arena. A Trial Control In zone condition has been defined so that tracking starts when the animal is first detected in the arena. When you first put an animal in Arena 2, the condition is met in this arena and tracking starts for that arena. When you release the second animal in Arena 4, 2 seconds later, tracking in that arena starts 2 seconds later than in Arena 2. The advantage of Trial Control in multiple arenas is that you can put one animal at a time into the arenas, and EthoVision XT will start tracking in each arena at the appropriate moment. If your setup includes multiple arenas, you cannot define a condition or action specific to one arena. This means that the zones and hardware devices specified in the condition or action must be present in all arenas, and have the same name. - If a zone or hardware device is not present in an arena, and a condition is based on that zone or device, Trial Control cannot progress for that arena. Therefore, tracking does not stop unless you set a maximum trial duration or tracking reaches the end of the video. - Trial Control executes the instructions for each arena separately; however one cannot establish which arena is evaluated first at a specific sample time. Your EthoVision License and Trial Control Your EthoVision XT license determines which type of Trial Control you can set up. - EthoVision XT Base license. You can define a rule to start and stop data recording (Start-Stop trial rule), not sub-rules. You can also use an External command action. You cannot control hardware devices. - EthoVision XT Base + Trial and Hardware Control Module. You can define a Start/Stop trial rule, and in addition sub-rules that serve as subroutines of the Start-Stop trial rule. Moreover, you can control hardware devices. Note: To acquire data in an experiment created with the Trial and Hardware Control Module, you must have a license that includes this module. For more information on your EthoVision XT license, see the EthoVision XT Help. Analysis of Trial Control Data The Trial Control function also allows you to easily analyze events that occurred during the trial. For example, in a conditioning experiment: - Number of rewards. Calculate the number of pellets dropped during a trial. - Latency between action and reward. Calculate the time interval between the time the animal pressed the lever and the time the animal approached the pellet dispenser. - Number of failures. Calculate the number of times the animal approached the lever during the period between dropping the pellet and the next opportunity. Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - JavaScript custom variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-javascript-custom-variables Chapter: EthoVision XT JavaScript Custom Variables Aim To expand EthoVision XT's analysis capabilities by introducing calculations, custom expressions, and search functions in JavaScript code embedded in EthoVision XT. There is a wide range of questions that can be answered with custom JavaScript variables. Here are a few examples: - Calculate the average of coordinates x and y of a number of subjects. - Calculate the number of subjects present in a zone. - Find the body length of an animal by taking the distance between the nose-point and the tail-base point. - Calculate the nearest neighbor distance in a school of fish. - Recalculate the coordinates of a subject based on a reference point. - Calculate the running average of a variable. - Find the time when the animal reaches 80% of correct choices in a learning test. - Create bins of velocity and assign each sample to one of them depending on the speed of the subject. You can find JavaScript variables ready to use on the EthoVision XT 19 installation package, under Drivers and tools\JavaScript custom variables. You can also find the variables on GitHub at https://github.com/noldus/EthoVision-JavaScriptCustomAnalysis. Simply copy the code to the JavaScript window in an Analysis profile of EthoVision XT (see below). You can often customize the code by adjusting specific parameters. Calculation When you define JavaScript code in EthoVision XT, the software considers the data available at sample Sk and produces a value JSk (numeric, or boolean) based on the JavaScript code specified. Sk represents a generic sample, which contains not only the x,y coordinates of the subjects but also their body area, elongation, and mobility at the current time. You can extract a lot of information and process it in the code. The output values can be in one of three formats: - A rational number, like the average of speed of three subjects. This is an example of a JavaScript continuous variable. - A point event, like the event that occurs when a certain variable reaches the threshold of 80%. This is an example of a JavaScript event variable. - A state event, like the time that a variable stays above a certain threshold. This is an example of a JavaScript state variable. Remember that the JavaScript code outputs one or more values (depending on the code) per sample. Those values are used to calculate trial statistics and group statistics just like any other dependent variable; for example, the average and the standard deviation. Procedure - Open your Analysis profile. - Choose one of the three options: JavaScript continuous, JavaScript event, or JavaScript state. - Insert the code in the window that appears. - Run analysis as usual. Definition A custom variable that processes raw data (for example, the subject coordinates, or the distance moved) and produces a numeric value for each sample of the track, based on an algorithm. The JavaScript continuous variable outputs a rational number; other solutions are possible with JavaScript state (with a duration) and JavaScript event (with no duration). See Commands and Functions for JavaScript Variables for more information. Use Cases - Subject counter. Count the number of subjects currently present in a zone. For example: How many fish swim at the top of the tank? How many fruit flies enter each side of the T-maze? - Subject counter. Calculate the ratio between the number of subjects in zone A to the number of subjects in zone B. - Body length. Calculate the body length as the distance of the nose-point to the tail-base point. - Tail beat detector. Calculate the ratio between the distance moved by the tail-base and the distance moved by the center-point. This helps quantify tail beats in fish. To Specify a JavaScript Continuous Variable - In the Analysis profile, under Custom Variables, click the button next to JavaScript continuous. - In the JavaScript Continuous window, enter the code you require. Important: Always specify the following functions: Start(), Stop(), and Process(), even when they do not include code lines. - Click Check to see if there are syntax errors. Note that this check is not thorough and does not guarantee that the code provides meaningful data. - Complete the procedure to add the variable. See Calculate Statistics: Procedure for more information. Notes - When you use functions like GetCenter, the coordinates are given in millimeters regardless of what measurement unit is selected in the Experiment Settings. Therefore, all calculations based on coordinates are given in millimeters. If your calibration is done in cm, divide the results by ten. Similarly, values of subject area obtained with the function GetArea are in mm². - Select a Number of outputs other than 1 if the JavaScript variable is made of two or more outputs. For example, suppose your code creates three state outputs for b1, b2, b3: SetOutput(0, b1); SetOutput(1, b2); SetOutput(2, b3); Then select 3 as the Number of outputs. The value of each output is updated at each sample. - JavaScript is not the same thing as Java. Although the two programming languages may show similarities in syntax, there are profound differences, for example in the rules that govern how variables and functions work. - EthoVision XT uses the Internet Explorer 11-compatible JavaScript engine. This engine does not support the following features: - Strict equality operators, for example === or !==. - Class expression (classes are only available through function expressions). - Arrow function expression. - Fill for arrays. - The Math.hypot function. See Also - JavaScript Event - JavaScript State - Commands and Functions for JavaScript Variables Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - JavaScript event URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-javascript-event Chapter: EthoVision XT JavaScript Event Definition A custom variable that processes raw data (for example, the subject coordinates, or the distance moved) and produces a point event (i.e., with no duration) for each sample of the track, based on an algorithm. Use Cases - Zone visits detector. For example, detect when the subject has visited 80% of the zones. Use the event to calculate the latency of that event. - TIP An example JavaScript event variable that detects when a subject has visited a specific percentage of zones is available for download from the Noldus customer portal under Downloads > EthoVision XT > Drivers and tools. Simply copy the code to the JavaScript Event window and follow the instructions (see below). Calculation The main difference with the JavaScript continuous variable is that the value specified in SetOutput() is either 0 or 1 and has no duration. See JavaScript Continuous > Calculation How to Specify a JavaScript Event Variable - In the Analysis profile, under Custom Variables, click the button next to JavaScript event. - Follow the rest of the procedure in JavaScript Continuous > To Specify a JavaScript Continuous Variable. Notes - In the Trial Statistics tab, select Latency to First to calculate the latency of the event. Latency of a dependent variable is calculated from the start of the track, even when you define time bins and nesting intervals. See Also - JavaScript Continuous - JavaScript State - Commands and Functions for JavaScript Variables JavaScript State Definition A custom variable that processes raw data (for example, the subject coordinates, or the distance moved) and produces a state (on/off) value for each sample of the track, based on an algorithm. Use Cases - Velocity bins. Get the per-sample values of velocity and create velocity bins, for example from 0 to 100 mm/s, from 100 to 200 mm/s etc. - Aggregation detector. Calculate the number of subjects present in a zone and set the output of the variable to 1 if the number of subjects exceeds a certain threshold. Use this variable for example to calculate the time that more than 50% of the subjects cluster in one zone. - TIP Examples of JavaScript state variables are available for download from the Noldus customer portal under Downloads > EthoVision XT > Drivers and tools. Simply copy the code to the JavaScript State window and follow the instructions (see below). Calculation The main difference with the JavaScript continuous variable is that the value calculated per sample and specified in SetOutput() is either 0 or 1. The variable has a duration based on the total number of 1s in the track or selected track segment. See JavaScript Continuous > Calculation How to Specify a JavaScript State Variable - In the Analysis profile, under Custom Variables, click the button next to JavaScript state. - Enter the code in the JavaScript State window. - Next to Number of outputs, select the number of possible states of the variable. For example, in the Velocity example described above, select 4. - Follow the rest of the procedure in JavaScript Continuous > To Specify a JavaScript Continuous Variable. Notes - In the Trial Statistics tab, select Cumulative Duration to calculate the total time that the state variable is "on". See Also - JavaScript Continuous - JavaScript Event - Commands and Functions for JavaScript Variables Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Lighting conditions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-lighting-conditions Chapter: EthoVision XT General Generally, for optimal tracking it is important that the contrast between the subject and the background is as good as possible. For marker tracking, EthoVision XT needs to be able to distinguish the different marker colors. For both issues, the lighting conditions play an important role. - It must be bright enough. A low light intensity can result in a suboptimal contrast between the animal and the background and therefore tracking might not be optimal. Furthermore, a low light intensity makes it difficult to separate different colors. When it is not possible to use strong illumination in your setup, try using fluorescent marker colors with UV lighting. - It must be even. The light source should be diffuse, for example, a shaded fluorescent tube or globe-type incandescent bulbs. This way, the contrast between the animal and the subject and the intensity of the marker color are the same throughout the arena. - Shadows must be avoided. To avoid shadows, do not point the light directly to your animals, but, for example to the walls or ceiling. Use several lamps, to obtain an even illumination. Full-Spectrum Lights For optimal color separation, illuminate your setup with lamps that approximate to day-light in frequency distribution of wavelengths, that is, have a full-spectrum range. There is no technical definition of "Full spectrum", therefore it cannot be measured. However, to compare full-spectrum lights you can directly compare spectral distributions. In practice, full-spectrum lights can be recognized from two parameters: - High Color Temperature (measured in degrees Kelvin). Usually higher than 5000 ºK. Values of color temperature around 2500–3000 ºK are typical of "warm" color lights (yellowish), for example incandescent bulbs. - High Color Rendering Index (expressed as percentage). Higher than 95. A value of 100 represents the ideal or natural light. See also: - For color temperature: http://en.wikipedia.org/wiki/Color_temperature - For color rendering index: http://en.wikipedia.org/wiki/Color_Rendering_Index When buying LED lamps, make sure that the technical specifications report the required color temperature and CRI. A disadvantage of most LED lamps is that they cast light in one direction at a narrow angle compared to energy-saving fluorescent lights, creating more shadows and reflections. We have tested the following lamps: - True-Light Energy Saving Light 15 W. Color Temperature 5500 ºK, Power 15 W, Brightness 720 lumen. - ProLite Helix Compact Fluorescent ES 15. Color Temperature 6400 ºK, Power 15 W, Brightness 795 lumen. Both lamps have E27 fitting. Recommendations - Choose a light source with color temperature ≥ 5500 °K and color rendering index > 95. - Do not use halogen lamps; instead use LEDs, as halogen light is too "cold". - Use at least four lights and place them at equal distance around the arena, at least 1 m from the subjects. - If the image of white animals looks overexposed, close the aperture of the camera lens. Too much light heavily reduces color discrimination. - If light creates shadows in the arena, place white sheets in front of the lamps to obtain more diffuse light. - Set the white balance of your camera, to obtain a wider color spectrum. Consult the manual of your camera for the exact procedure. Generally, you can set the camera to white balance the image automatically. To check whether this is done correctly, point the camera to a white wall and check whether the wall appears white in the video image. If this is not the case, search for the settings to set the white balance manually. Point the camera to a white wall and set the white balance. Make sure you do this every time the light changes. Useful Web Sites Below you find the web addresses of full-spectrum light producers: - True-Light: http://www.true-light.eu/en/ - BlueMax Lighting: https://www.fullspectrumsolutions.com - OSRAM: http://www.osram.com/ - Philips: https://www.lighting.philips.com/main/home - Pro-Lite: http://www.prolite-lamps.co.uk - Viva-Lite: http://www.viva-lite.nl/home.html Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Lighting setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-lighting-setup Chapter: EthoVision XT Ideal Light Conditions A good lighting setup is vital to get a good image that EthoVision can use to accurately track your animal. This is particularly important when you want to do nose-tail tracking or track multiple animals with color markers. To produce a good image, the lighting must satisfy three criteria: - It must be bright enough. Stand-alone video cameras (which we recommend) can sometimes work at 0.1 lux or darker. At higher light levels you can work with a smaller aperture. See also Using EthoVision XT in near darkness. Please note that poor lighting gives more noise in the image which enlarges the video file size. - It must be even. That is, a diffuse light source, such as a shaded fluorescent tube or globe-type incandescent bulb. Spotlights can produce changing shadows and reflections. - There must be no reflection of the light source visible in the image (see below). TIP Watch the video Set Up Your Test Environment, which you can find in the EthoVision XT video tutorial (Help > Video Tutorial). Eliminating Reflections If you have reflections in your image, EthoVision may confuse those reflections with your subject, and track the reflections rather than your animal. Preventing reflections is particularly important when you want to do nose-tail tracking. There are a number of measures that you can take to reduce this problem: - Surfaces within the arena should be (whenever possible) a dark color and matte texture. - Lighting should be from a diffuse source, such as a shaded fluorescent tube or globe-type incandescent bulb. - The light source should not be in direct line-of-sight of the camera (that is, it should be indirect lighting). You can achieve this by bouncing the light off the ceiling or walls (which should be a pale color and matte texture) and, if necessary, placing a shield in between the light source and lens. - If your arena is transparent (for example, a glass olfactometer), you can use backlighting. This will eliminate reflections, but you must take special care that the lighting is even and diffuse. Place the light source underneath the setup and attach a sheet of white paper to the bottom to create diffuse back light. It is important to avoid light coming from above as much as possible, otherwise there is no effect of back light. - You could also try a polarizing filter in front of the camera lens. The filter will remove reflections that are incident to the reflective surface at 32°–37°. - If possible, draw your arena in such a way that bright reflecting rims of mazes are excluded. - To remove reflections brighter or darker than your animal, set appropriate thresholds in the Detection Settings. - To remove reflections larger than your animal, enter an appropriate value for the Maximum Subject size in the Detection Settings. Note that if your animal enters the area of the reflection, EthoVision might no longer be able to track it if you use this setting. Lighting a Morris Water Maze Lighting a Morris water maze needs to be carried out particularly carefully because the water can give large and variable reflections. Some of these can be excluded by the software settings listed above, and the following lighting setup should give good results: Place four (or more) bulbs round the pool, below the level of the water surface or at the ceiling. 'Globe' type bulbs are ideal (twice the diameter as standard incandescent light bulbs). They should be close enough to the pool wall so that there is no direct line of sight between the bulbs and the camera lens. The light is reflected off the walls and ceiling, so that it only reaches both the lens and water surface indirectly. - Take special care when dealing with water and electricity in the same room. The lights should be placed so that water cannot splash on them, ideally they should be suitable for outdoor use (double-insulated) and if connected to an electrical outlet in the same room as the water maze they should be connected through a circuit-breaker. - Ask a photographer for advice on the lighting of your water maze. Lighting Water Tanks When using water tanks like in the Porsolt forced swim test, a problem is often that there is a lot of reflection, especially just above the water surface. Furthermore, detection of the animal can be hindered by the water's meniscus. Try to make a set-up with as much contrast between animals and background as possible. For instance, when you have white rats, preferably use a completely black background. Back light (that is, light from behind the subjects so you only see the animals' contour) generally gives very good results. A solution to remove the water's meniscus in the video image is also to place the test cylinders in a separate tank with water (for example an aquarium) and then make recordings. The water level in the tank should be higher than in the cylinders. For more information on the Porsolt forced swim test, see the EthoVision XT 19 - Application Manual. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Lighting setup (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-lighting-setup-continued Chapter: EthoVision XT Using EthoVision XT in Near Darkness Nocturnal animals like rats and mice are active in the dark. It is, therefore, a logical choice to measure their behavior in the dark. You can use infrared (IR) lights to illuminate the arena and a camera that is sensitive in the infrared. Most animals, including rats and mice, do not see infrared (IR) or near-infrared (NIR) light. Infrared illumination is perceived by them (and also by humans) as being total darkness. Camera Infrared light (IR) is light of a longer wavelength than visible light. Generally, to track with EthoVision XT, near-infrared light is used, with a wavelength of 700-900 nm (near the visible range of 400-700 nm). Color video cameras are insensitive to infrared but standard monochrome cameras have reasonable sensitivity to near IR. In particular, the Basler monochrome GigE cameras are IR sensitive. Normally they do not require an IR-pass filter unless you want to track the animals in both dark and light conditions during the same trials, for example in multi-day trials. Optimizing Image Brightness Depending on how bright your IR setup is, you might need to: - Open the aperture on the lens all the way (do this first). - Adjust the camera's Gain and/or the Exposure setting in EthoVision XT. - A high Gain increases brightness but also noise in the image. - A longer Exposure time may not be compatible with the frame rate set in the camera. Check carefully in Adjust the Camera Exposure Time. TIP: Watch the video Set Up the Cameras, which you can find in the EthoVision XT video tutorial (Help > Video Tutorial). Light Source As your light source, you can use IR illuminators, which basically are LED lamps that produce infrared rather than visible light. Using an IR illuminator is just like using a lamp, except that neither you nor your animals can see its light. Check the image from your camera to see what the illumination actually looks like. Just as with visible light, you want uniform lighting throughout your arenas. You may find that objects that look light in visible light appear dark in the IR image, and vice versa. Likewise, objects that appear transparent may be opaque, or opaque objects (especially some kinds of acrylic) may be transparent in the IR image. You can record through acrylic, unless it has been colored or coated with pigments that absorb IR light. You can use, for example, a sheet of acrylic to cover the top of a cage or arena. If you use an IR illuminator from overhead, you may get spots of reflective glare, just as with normal lighting. Moving the illuminators to the sides, rather than overhead, can eliminate the glare. To eliminate shadows, you may get the best results by using two or more illuminators. - You can obtain IR LED illuminators from Noldus Information Technology. - You can also use an IR lightbox as your light source. An IR lightbox provides a uniform source of IR illumination from beneath your animal. Unlike the case with an IR illuminator, the camera will see a dark silhouette of the animal against a light background, which is easy to track in EthoVision. An IR lightbox is also an excellent solution if your animals are highly variable or mottled in color, for example Long Evans rats, and eliminates any concern about glare. Light in 24-Hour Experiments If you want to go from light to dark conditions (or vice versa) during a single trial (e.g., recording across a 24-hour circadian cycle), EthoVision needs consistent lighting. This can be accomplished by using an IR-pass filter on your camera and by preventing any variation in the amount of IR illumination. Should you require an IR-pass filter, take note of the lens characteristics. The filter should match the diameter of the lens, and simply screws on to the front of the lens. The filter prevents the camera from seeing visible light — only IR light gets through. The filter is not necessary under constant lighting conditions, but you need it if the visible light level changes during the trial. The IR illumination must remain on for the entire duration of the trial. Some IR illuminators have the feature of automatically turning off when there is visible light (for example, IR illuminators designed for security applications usually turn off during the day). If your illuminator has this function, it needs to be disabled. Consult the documentation for your illuminator to see how this is done. If it is not possible to prevent the automatic turning off, you can cover the illuminator's light sensor with tape so that it will not detect light. The normal light in the room should not affect the detection setting unless it also emits IR light. Many light fixtures will give off some IR illumination in addition to visible light. Incandescent and halogen lights especially will produce a great deal of infrared light. Preferably use fluorescent lights which produce much less infrared light. If there is an intensity adjustment on your IR illuminator, turn it up as high as possible. Increasing the amount of IR illumination will minimize the impact of any infrared light from your visible lights. Sunlight also has an IR component, so if you have windows, they should be covered. When watching the camera image, ideally you should see no change in the image when the visible lights turn on or off. It might be that your image is slightly out of focus, but that is no problem for tracking in EthoVision. Notes: - If you have light colored animals, use the darkest non-reflective bedding possible for improved contrast. Be aware that some dark materials may appear white under infrared light. See also the section Recommended Materials in the PhenoTyper - EthoVision XT 19 - Reference Manual. - If you have not eliminated all infrared light from the visible light in the test room, and you are using Static subtraction as your detection method, the entire arena may be detected as the animal after the visible lighting changes. Choose Dynamic subtraction and the animal will be detected after a few frames. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - List of Trial statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-list-of-trial-statistics Chapter: EthoVision XT Aim Trial Statistics give you summary statistics of individual trials. If a trial includes two or more tracks (subjects), the statistics are by default shown for each subject separately. The Data profile filters tracks and/or intervals within tracks. If the Data profile contains groups of tracks, these groups are ignored in the results. To view results per group, choose Results > Group Statistics and Charts. Cumulative Duration The cumulative duration of the state variable in the whole track, or in the track segment selected. For example, the time that the animal spent in a zone (for the variable In zone), or the time that the subject was in the state Mobile. When a state does not occur at all in a track or track segment, the value of Cumulative Duration is zero. Cumulative Duration (%) The Cumulative Duration divided by: - If you do not define time bins: The duration of the track (this corresponds to the Recording duration independent variable, not Trial duration). This is also the case when you define nesting intervals or results per zone. - If you define time bins: The duration of a time bin defined. This statistic is expressed as a percentage. Cumulative Duration within Nesting (%) The Cumulative Duration divided by: - If you calculate results per zone: The total time the animal is in the zone. - If you defined track segments with Nesting: The total duration of the track segments defined. - If you defined time bins: The duration of a time bin defined. - If you combine any of the three above: The duration of the time period shared by all selection criteria (the time periods of each criterion are combined with AND logic). This statistic is expressed as a percentage. Frequency The total number of occurrences of a state (only for state variables). Latency to First The time from the start of the track to the first occurrence of the behavior (for example, the first time in the track that the animal is in a zone). Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. Latency to Last The time from the start of the track to the last occurrence of the behavior. Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. Notes about Latency to First/Last - Latency to First and Latency to Last are calculated from the start of the track. This is the time when EthoVision XT collects the first sample (missing or not). If the animal is not yet in the arena and tracking has started, EthoVision XT collects a number of missing samples. The time that the animal is missing is included in Latency to First/Last. This overestimates the "true" latency, which should be calculated from the time that the animal is released. To prevent this from occurring, make sure that the Trial Control rule includes a Start track condition in such a way that tracking only starts when the animal is first found in the arena. - To calculate the time from an event to another event in the trial, select a Free interval in the Analysis profile. - When two or more animals are tested simultaneously in the same arena, the meaning of Latency to First/Last depends on how you set the start condition. Suppose you start your trial by releasing one animal, then a little later the second animal, and you want to calculate the Latency of In Zone A for both subjects. Consider the two scenarios: - If you set the Trial Control to start tracking when any subject is found in the arena, tracking starts when the first animal is released. Latency is calculated from that point also for the second animal, which enters the arena later. This means that Latency for this animal will be overestimated. - If you set the Trial Control to start tracking when all subjects are found in the arena, tracking starts when both animals are found — that is, when the second animal is released and the first is detected (also when in a hidden zone). Latency is calculated from this point, so Latency for the second animal is correct. However, for the first-released animal, the time that it was in the arena before the second was released is not counted in Latency. This means that Latency may be underestimated, for example when the first animal enters Zone A before the second animal is released. For this reason, try to release the animals at the same time, or one immediately after the other. Mean - For linear variables like Distance moved, Velocity, Distance to zone, or Distance between subjects, and the variables Turn angle, Angular Velocity, and Meander, the arithmetic mean is used — that is, the sum of the per-sample values divided by the number of samples. - For the angular variables Heading, Head direction, and Heading to Point, the mean is calculated according to the circular mean formula, where α is the per-sample angle and N is the number of samples. The circular mean value can also be represented by the angle of the vector resultant R obtained by summing up all the vectors that represent the per-sample angle values. - For state variables like In zone, Movement, and the behaviors scored manually or automatically recognized: the sum of the duration of occurrences of the state, divided by the number of occurrences. Minimum The lowest value of the variable. Note: For state variables, this is the minimum duration of the instances of a state, for example Moving. When the state does not occur at all in a track or track segment, the value of Minimum is zero. Maximum The highest value of the variable. Note: For state variables, this is the maximum duration of the instances of a state, for example Moving. When the state does not occur at all in a track or track segment, the value of Maximum is zero. Number of Samples The total number of valid values of that variable (only for numerical variables like Distance moved). Standard Error The standard deviation divided by the square root of the number of samples. This is also the case for angular variables Heading, Head direction, and Heading to Point. Standard Deviation For most variables, including Turn angle, Angular Velocity, and Meander, the sample standard deviation of the mean is used, where x is the individual variable value and x̄ is the mean of the variable. N is defined as follows: - For numerical variables like Distance moved or Velocity: the number of samples used to calculate the mean. - For state variables like In zone, Mobility, and the behaviors scored manually or automatically recognized: the number of occurrences of the state used to calculate the mean (for example, when a subject visited a zone 4 times, then N=4). For the angular variables Heading, Head direction, and Heading to Point, the circular standard deviation is used, where R is the resultant vector length (see the circular mean description above) and N is the number of samples. Total The sum of all the values. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - List of Trial statistics (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-list-of-trial-statistics-continued Chapter: EthoVision XT Variance - For most variables, including Turn angle, Angular Velocity and Meander, the square of the standard deviation. - For the angular variables Heading, Head direction, and Heading to Point, the variance is given by 1 - R/N, where R is the resultant vector length (see the text above for the circular mean) and N the number of samples. Notes (For All Statistics) - Not all statistics listed above are available for every dependent variable. To view the list of statistics for a specific variable, double-click its name under Selected Dependent Variables and click the Trial Statistics tab. - Values of latency and duration can only be a multiple of the sample interval (= 1 second divided by the sample rate). - To add or remove statistics for a dependent variable, double-click that variable under Selected Dependent Variables and change your selection. List of Group Statistics Aim: Group statistics are a summary of trials in a specific experimental group. Here a "group" refers to the tracks selected in a Result box in the Data profile. See Define groups of tracks. Choose between Group mean and 5 number summary. NOTE: Group statistics are not available when you only select Standard deviation, Standard error or Variance as Trial statistics. Group Mean - For most variables, including Turn angle, Angular Velocity and Meander, the Group mean is the arithmetic mean of the trial statistics, calculated for each group. - For the variables Heading, Head direction, and Heading to Point, the group mean is calculated as the circular mean, with N being the number of trials in the group. If you select Group mean, the following options are available: - Standard Deviation. For most variables, the sample standard deviation of the trial statistics, calculated for each group. For the variables Heading, Head direction, and Heading to Point, the group standard deviation is calculated as the circular standard deviation (see above), with N being the number of trials in the group. - Standard Error. The Standard deviation divided by the square root of the number of tracks used to calculate the Standard deviation. This is also the case for angular variables Heading, Head direction, and Heading to Point. 5 Number Summary This is the Minimum, the Lower quartile, the Median, the Upper quartile and the Maximum value of trial statistics calculated for each group. The method used to calculate quartiles is the N + 1 Basis interpolation, which is also used in SPSS. If the sample size is lower than 3, the lower quartile is the same as the minimum and the upper quartile is the same as the maximum value, which is also the same as in SPSS. NOTE: With 5 number summary you can also plot data in form of Box and whiskers charts. You can also show the original data points for better interpretation. See Group charts > Customize the group charts. See Also - List of Trial statistics - Define groups of tracks - View the results for groups of tracks Edit the Analysis Profile Aim: - To change the properties and settings of a dependent variable - To make multiple instances of a dependent variable - To rename a dependent variable - To remove a dependent variable from the Analysis profile After editing the Analysis profile, re-run analysis (Analysis > Results > ...). To Modify the Properties of a Dependent Variable You can change the properties of a dependent variable at any time, for example to add one more statistic. - Open the Analysis profile that contains the dependent variable you want to modify. - Under Selected Dependent Variables, double-click the dependent variable. - Edit the variable's properties. For how to modify the variable's properties, choose the variable in Dependent Variables in Detail and see the How to specify section. - Choose Analysis > Results > Statistics and Charts, then click the Calculate button. You can also modify a dependent variable directly in the Statistics result. Right-click the dependent variable header and select Properties. Change the properties of the variable, then click the Calculate button. To Calculate Multiple Instances of a Dependent Variable You can add multiple instances of a dependent variable to an Analysis profile. This is handy when you want to compare the effect of different settings on the same dependent variable. For example, two instances of Mobility with different Mobility thresholds. - Open the Analysis profile that contains the dependent variable. - Right-click the dependent variable under Selected Dependent Variables and select Duplicate. A new row is appended under Selected Dependent Variables. - Double-click the new row and set the properties you require for the new instance of the dependent variable. Additional instances of a dependent variable are given names with a progressive number (for example, Distance moved 2, Distance moved 3, etc.). You can rename those variables (see below). To Rename a Dependent Variable - Open the Analysis profile that contains the dependent variable. - Under Selected Dependent Variables, right-click the variable's name and select Rename. - Type in the name you want to give and press Enter. To Remove a Dependent Variable from the Analysis Profile Under Selected Dependent Variables click the variable's name and press Delete, or right-click the variable's name and select Delete. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Make and break group URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-make-and-break-group Chapter: EthoVision XT Definition A discrete (point event) variable that is scored when the focal subject joins or leaves a group of conspecifics. Because it is a point event variable, it has no duration. - Make group of size n (2 to 4). The subject joins a group of n-1 subjects to form a group of n subjects in contact with each other. - Break group of size n (2 to 4). The subject leaves a group of n subjects. The group is now of size n-1, or does not exist anymore in the case of n=2. Calculation EthoVision XT detects the make/break events based on the state of type Group. - If the subject is not in contact with any subject one video frame before the start of the event Group, a Make group event is scored. - If the subject is not in contact with any subject one video frame after the end of the event Group, a Break group event is scored. NOTE: In EthoVision XT, a point event is an event with no duration. In contrast, state events have a duration. How to Specify Make and Break Group - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Make and break group. - Specify the Group size. This is the final size when making a group, or the initial size when leaving a group. For example, enter 3 if you want to have the instances when a subject joined another subject to form a group of three subjects, or left a group of three, so the group became two subjects. - Complete the procedure to add the variable to the Analysis profile. See Calculate Statistics: Procedure. Applications In a study of a mouse model of ASD, Shank2 mutant mice observed in a social context displayed increased frequency of completing or breaking a group of three or four mice (de Chaumont et al. 2019. Nat. Biomed. Eng. 3: 930-942). Note While Group is a state event that aims at quantifying the time that a subject was part of a group, Make and break group is a point event variable; that is, it tells you exactly when the subject joined or left a group. See Also - Dependent variables for Live Mouse Tracker Make Contact Definition A discrete (state event) variable that is scored when the subject approaches another one to make contact with it. Calculation Make contact is scored when the following conditions are met simultaneously: - The distance between the focal subject and the other subject shortens (approach event). - The speed of the focal subject is higher than that of the approached subject. If the speeds of the two animals involved in the contact are not different enough, Make contact is not computed. - The contact event starts some time during the approach event or immediately after the end of the approach event. That is, the video frame immediately before a contact event must be within the timeline of the approach event. - The contact event lasts more than three video frames. Instances of contact separated by one video frame are merged together. An instance of Make contact starts at the start time of approach and ends at the video frame just before the contact event. It does not include the time of contact. NOTE: In Live Mouse Tracker, contact between subjects is detected when the distance between the contours gets below a fixed threshold. Contact is detected during data acquisition and its settings cannot be modified in EthoVision XT. How to Specify Make Contact - Open an Analysis profile. - In the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Make contact. - Complete the procedure to add the variable to the Analysis profile. See Calculate Statistics: Procedure. Example Subject B has made contact with subject C. See Also - Dependent variables for Live Mouse Tracker Move Definition A discrete (state event) variable that marks the time that the focal subject makes some displacement in space. The subject may move alone or in contact with any other subject. Calculation EthoVision XT considers the subject moving for the time between two subsequent events of type Stop. Events of type Stop are scored when the speed of the subject is lower than the threshold value (5.26 cm/s or 2 5/64 in). This threshold is set in the Live Mouse Tracker algorithms and cannot be changed. How to Specify Move - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Move. - Under Calculate Statistics for, select Move in contact, Move alone, or both. - Click the Receivers tab. These apply when you select Move in contact. Under Select, choose the subjects that were in contact with the focal subject while it was moving. If you select two or more subjects, select one of the available options from the list: - All selected subjects: Move in contact is scored only when the focal subject was in contact with all the subjects selected above. - Any selected subject: Move in contact is scored when the focal subject was in contact with any of the subjects selected above. - Each subject: Move in contact is scored when the focal subject was in contact with one of the subjects selected above. The results are displayed for each Receiver. - Complete the procedure to add the variable to the Analysis profile. See Calculate Statistics: Procedure. Example In the Trial Statistics results table, with the default layout, the results of Move are shown per subject (on the rows). The columns vary depending on what you chose in the Receivers tab. - If you chose Each subject, the columns contain the statistics of Move in contact with specific subjects (With A to D). - If you chose All selected subjects or Any selected subject, a column With all of A, B, C, D or With any of A, B, C, D contains cumulative statistics of Move when the subject was in contact with all cage mates or any of them, respectively, depending on which option you chose. Notes - Move may look similar to EthoVision XT's Movement, with its possible states Moving and Not moving. However, the results may not always overlap. Movement uses two adjustable speed thresholds, which filter the changes in velocity in a different way. See Also - Dependent variables for Live Mouse Tracker Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Manage your experiments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-manage-your-experiments Chapter: EthoVision XT Learn About - File locations What Do You Want To Do? - Create a new experiment from scratch - Save an experiment - Save an experiment with a different name - Open an existing experiment - Delete an experiment - Back up an experiment - Import data from other experiments - Manage settings and profiles Create a New Experiment From Scratch Aim: To create an experiment without predefined settings. You can also create an experiment in EthoVision XT using a template, for example for a Morris Water Maze test, or a Radial Maze test, and for a specific animal, like the rat, mouse, or zebrafish. See Create an Experiment from a Predefined Template. Procedure - Choose File > New, or in the EthoVision XT Startup window, under New experiment, click New, or press Ctrl+N. - In the New Experiment window, enter a name for your experiment. - Browse to the location in which you want to store your experiment. IMPORTANT: Do not create an experiment on a removable disc, like a USB Flash drive or an external hard disk. - Additional options: - Select GLP Experiment if you want EthoVision XT to support you in making a Quality Assurance-compliant experiment. For this, you need the Quality Assurance add-on module. - Select DanioVision experiment if your PC is connected to a DanioVision system and you want to create a DanioVision experiment. - Select Live Mouse Tracker experiment if you want to import Live Mouse Tracker data. For this, you need the Live Mouse Tracker add-on module. See Live Mouse Tracker: Workflow. - Click OK. Notes - You can find the experiment file (*.evxt) in a folder with the same name as the experiment. See File Locations for the default experiment locations. You can specify the default experiment location during installation. You can change it any time in the Preferences for default folders. - If you select DanioVision experiment, the EthoVision XT interface is adjusted for DanioVision. Unnecessary functions like the Manual Scoring Settings are not available. Detection settings are optimized for detection of zebrafish larvae and the arenas are detected automatically. For more information, see the DanioVision DVOC-0041 - Reference Manual. Save an Experiment Procedure Choose File > Save or press Ctrl+S. Notes - You can also choose to save the data automatically at regular intervals. Choose File > Preferences > Auto save, select Enable auto save and enter the auto-save interval. - When you make changes to your experiment, e.g., changes in settings, these are saved with save or auto-save. - During data acquisition and track editing, data are saved to file immediately. Save an Experiment With a Different Name Aim: To create a copy of an experiment, with a different name and saved in a different location (optional). IMPORTANT: Do not rename the experiment file *.evxt and any other files within the experiment. That would invalidate the data within the experiment. Instead, save the experiment with a different name. IMPORTANT: Do not save experiments within the folder of another experiment. Procedure - Open the experiment in EthoVision XT. - Choose File > Save As. - Enter the new experiment name and choose the destination folder. Notes - By default, the destination folder is the same folder as that of the original experiment. - When you save an experiment with a different name, a new experiment folder is created in the destination folder with the same name as the experiment. Open an Existing Experiment Procedure Choose one of the following: In EthoVision XT: - In the EthoVision XT startup window, under Open, click one of the experiments in the recent experiment list. To open a different experiment, click Browse and open the folder where your experiment is stored. Select the file with the extension evxt and click Open. - Press Ctrl+O. Browse to the location where your experiment is stored, select the file with the extension evxt and click Open. - Choose File > Open. Browse to the location where your experiment is stored, select the file with the extension evxt and click Open. With the File Explorer: - Using the Windows File Explorer, open the folder where your experiment is stored. Right-click the file with extension evxt and click Open or Start experiment. Notes - You can open an experiment saved in older versions of EthoVision XT. - You cannot open experiments made in newer versions of EthoVision XT. Use the newest version to open that experiment. - GLP compliant experiments that have been made with EthoVision XT 12 or earlier cannot be opened in EthoVision XT 19. Delete an Experiment Aim: To remove an experiment from your computer. If video files are included in the experiment folder, these files will also be deleted. Procedure - In the Windows File Explorer, browse to the experiments folder. - Click the folder of the experiment that you want to delete and press Delete, or right-click that folder and select Delete. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Manually scored behavior URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-manually-scored-behavior Chapter: EthoVision XT Definition Behaviors defined in the Manual Scoring Settings are analyzed as dependent variables with discrete states, like In zone, Movement etc. How to Specify a Manually Scored Behavior - Click the Add button next to the name of the behavior (or behavior group) you want to calculate. - In the tab named as the behavior (or the behavior group), select the behavior you want to calculate statistics for, and clear the options for the behaviors you do not want to include in the table. - For Mutually-exclusive behaviors, the window lists all behaviors of the group selected by default. The analysis result will show the statistics for each behavior separately. Clear the option for the behavior you do not want to analyze. - For Start-Stop behaviors, the window lists the behavior (selected by default) and its opposite, indicated by Not [behavior name]. Selecting Not [behavior name] means that the program calculates the statistics for the time that the behavior was not active (see below). - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - Not [behavior name]: For example, if you define Rearing as a Start-Stop behavior and score it one time during the test (not at the start of the trial), then the results will be: - Frequency of Rearing = 1. - Frequency of Not Rearing = 2. The first occurrence of Not Rearing is at the start of the trial, and the second occurrence is after you press the Stop code for Rearing. The cumulative duration of Not [behavior name] is the sum of all the periods of time that the behavior was not scored. See Also - Export manually-scored behaviors Hardware and Advanced - Trial Control event - Trial Control state - Trial Control variable - External data - Free interval - Multi condition - JavaScript continuous - JavaScript event - JavaScript state See Also For Hardware variables related to devices like the Pellet dispenser, the Lickometer, PhenoWheel or the PhenoTyper Top Unit, see the Analysis of Trial Control data in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To open this manual, choose Apps > Noldus > EthoVision XT 19 Other Documentation. Definition A point event, with no duration, defined by an element of Trial and Hardware Control (condition, action, rule/sub-rule and reference). A Trial Control event has no duration. For Trial Control events you can only calculate frequency and latency of first or last occurrence. How to Specify Trial Control Event - Click the Add button next to Trial Control event. - From the Element list select the Trial and Hardware Control element to be analyzed. For example, if you want to analyze the hardware-based action Drop pellet, select Action: Drop pellet. - From the Event list, select the state of the element. The options available depend on what you have chosen as Element. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - Statistics of Cumulative duration and Latency can only be a multiple of the sample interval (= 1/sample rate). For example, when you define a condition Subject in zone A for >= 3 s, this condition is met when the time elapsed from its activation exceeds 3 s. If the sample rate is 12.5 frames/s (thus the sample interval is 1/12.5 = 0.08 s), the condition is met at the first multiple of 0.08 greater than 3 s, that is 3.04 s. This affects data analysis; for example, the latency of the event Condition becomes true is 3.04 s. - For Trial Control events based on Conditions, the sample time at which a Trial Control event is scored also depends on the statistic used in the condition: - If you use Current to define the condition (for example: when Current In zone = true), the Trial Control event is scored at the expected sample time. For example, when the animal enters the zone (and thus Current = true for that sample). See also A in the figure in Trial Control state, where the start of the Trial Control state is like a Trial Control event. - If you use any other statistic to define the condition (for example, when Frequency of In zone >= 1), consider the following scenarios: - When the condition becomes true after the condition box is activated, the Trial Control event is scored at the expected sample time. See How the trial control instructions are executed for an explanation of the terms true and active. - When the condition is already true when the condition box is activated (for example, a condition Frequency of In zone = 1 is activated when the animal is already in the zone), such a statistic is only evaluated at the next sample (or in the second next sample, in the case of Heading). In that case, the Trial Control event is scored one sample (or two) later than expected from the condition (see B in the figure in Trial Control state). However, for the consecutive frequencies of In zone = 2, 3, etc., the condition is already active by definition; therefore the Trial Control event is scored at the expected time, when the condition becomes true. See Also - The EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To open this manual, choose Apps > Noldus > EthoVision XT 19 Other Documentation. Application You can use Trial Control event to test whether trial control works as expected. For example, visualize the Trial Control event condition true and plot it together with the video to check that the condition is met at the correct time. You can also define a Trial Control event to calculate the number of occurrences of specific actions, such as dropping a food pellet in a learning experiment. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Meander URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-meander Chapter: EthoVision XT Definition Meander is the change in direction of movement of a subject relative to the distance moved by that subject. It provides an indication of how convoluted the subject's trajectory is. Meander can be relative or absolute: - Relative Meander: The change in direction is signed. With a default position of the Calibration axes (x-axis pointing to the right; y-axis pointing upward), a clockwise turn is scored as negative value because turn angle is negative; a counterclockwise turn is scored as positive. With other orientations of the x- and y-axes, the same turn may have different sign, depending on the relative turn angle. See Turn angle for how turns are given positive vs. sign. - Absolute Meander: The turn angle that measures the change in direction is unsigned. Meander is therefore always positive. Calculation Where RMk is Relative Meander, RTAk is the Relative Turn angle and DMk is the Distance moved at sample k. Absolute Meander is the absolute value of the Relative Meander. You can calculate Meander in two ways: - Based on body points: Meander is calculated from the turn angle and the distance moved of the specified body point, as shown in the figure above. - Based on Head direction: Meander is calculated from the turn angle based on the Head direction line and the distance moved by the nose point. Range Given the formula above, Relative Meander can range from -∞º/cm to +∞º/cm, while Absolute Meander from 0°/cm to +∞°/cm. When DM is very small, Meander can get high, unrealistic values. One case when DM is very small is when you use a high sample rate and the subject does not move significantly. TIP: Before running analysis, make sure you use Track Smoothing to remove very small values of distance moved from your tracks. See also Troubleshooting: Statistics > I get unrealistic values of path shape and direction. How to Specify Meander - Click the Add button next to Meander and click the Meander tab. Select Absolute or Relative. - Select Head direction meander (body point is ignored) if you want to calculate meander based on the head direction line. - Click the Body points tab and select the body points for which you want to calculate meander. By default, Center-point is selected. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If your experiment is set to Only center-point detection or Color marker tracking, the Body points tab is absent. Calculations are based on the center point. - Meander is very sensitive to small, random movements of the body points. When the animal sits still, Meander can get very high, unrealistic values. To remove such small movements from your data, smooth the tracks, then run analysis. Application - The Relative Meander is a measure for the direction of turning per unit distance. This dependent variable can be of additional value to other turn bias variables, such as relative Turn angle and relative Angular velocity, since the turn bias is 'corrected' for the distance moved. For instance, if two individuals move at different speeds, the two can have very different values for the mean relative Turn angle, but at the same time have identical values for the mean relative meander. - The Absolute Meander is often used in combination with the dependent variables absolute Turn angle and absolute Angular velocity to study turning rates. Bell (1991) reports that in most studies, when plotting the values, absolute Meander generates a smoother curve than absolute Angular velocity. This is caused by the fact that the latter dependent variable is influenced both by speed as well as by real turning rate. See Bell (1991). Searching Behaviour: The Behavioural Ecology of Finding Resources. Chapman & Hall, London. - In rodent models of aging, the average meander is used to calculate the frailty index. See Parks et al. (2012) J. Gerontol. A 67(3): 217-227. Definition The direction of movement of the nose, center or tail-base point of the current sample relative to a line parallel to the x-axis in the coordinate system. 'Compass heading' and 'compass angle' are synonyms for Heading. See also Heading to point. Calculation Heading is calculated in three steps: - The smallest angle α is found between the reference line and the vector connecting the samples k–1 and k. The figure below shows the relationship between the angle α formed by the segment joining samples k-1 and k, the horizontal line parallel to the x-axis, and the dependent variable Heading (HE). Four cases are illustrated, corresponding to the possible directions an animal's body point can be moving relative to the x-axis. Here, it is assumed the x-axis is horizontal and pointing to the right, and the y-axis is pointing upward. - The value of α is calculated according to the formula, where: - DMk is the distance moved at sample k. - Xk and Xk-1 are the x-coordinates of the center, nose or tail-base point at sample k and k–1, respectively. Because the way α is defined, it can only range from 0° to 90°. - How to convert α to Heading depends on the direction of movement between samples k–1 and k. The relation between Heading and α is determined by the following rules: - If ΔX > 0 and ΔY ≥ 0, then Heading = α. - If ΔX ≥ 0 and ΔY < 0, then Heading = -α. - If ΔX < 0 and ΔY ≤ 0, then Heading = -(180 - α). - If ΔX ≤ 0 and ΔY > 0, then Heading = 180 - α. Where ΔX = Xk - Xk-1 and ΔY = Yk - Yk-1. Range Heading ranges from -180° to +180°. How to Specify Heading - Click the Add button next to Heading. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - If your experiment is set to Center-point, nose-point and tail-base detection, click the Body points tab and select the body points for which you want to calculate heading. - The mean, standard deviation and variance are calculated with circular statistics. See Statistics available. - Heading is calculated relative to the orientation of the x-axis you have chosen in the Arena Settings used for that trial. By default, the x-axis is horizontal and pointing to the right. If the x-axis is not horizontal or is pointing to another direction, Heading is calculated based on that axis direction. Application Heading is used in studies of spatial orientation. For example, you can use it to determine the direction of flight of a moth relative to the direction of the air flow in a wind tunnel. In a Morris water maze test, you can use this variable to measure initial heading of the path after releasing the animal in the basin. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Mobility URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-mobility-kb9 Chapter: EthoVision XT What Is the Difference Between Mobility and Movement? Mobility can be defined as the degree of movement of an animal's body independent of spatial displacement of the center or any other body point, which is measured by Movement. 'Independent' does not mean that mobility is corrected for the center-point position, it means that the calculation does not use the x,y coordinates of the animal (they are not in the equation used to calculate it). Mobility is calculated 100% independent of movement of the coordinates identified as the center-point (or the nose/tail point). That means that the center-point can have zero movement but high mobility. For example, imagine that you are tracking a rat in an open field. When the rat stands still and grooms, the center of gravity does not move, therefore there is no spatial displacement of the subject (the current state for the Movement variable is Not moving), however the rat's head and forelimbs move, resulting in changes in the surface area. Although there is no spatial displacement of the body, the current state of the Mobility variable is Mobile (depending on the threshold value). Does Mobility Depend on the Size of the Subject vs. Arena? No. It is dependent on the size of the subject only. Keeping resolution constant, the smaller the subject, the smaller the number of pixels that form its image, the more likely that any small movement results in a change in area that is detected as Mobility. Does Mobility Depend on the Video Resolution? Yes. The higher the video resolution, the greater the number of pixels that form the image of the subject. Therefore, the less likely that a small movement of the subject results in an abrupt change in area. However, this effect is present at very low resolution (for example, when the subject is less than 100 pixels large). At resolutions provided by video files, this effect is negligible. Does Mobility Depend on the Sample Rate? Yes. Since Mobility is detected from the change in area of the subject between two samples, and the change in area depends on how frequently the subject area is acquired (that is, the sample rate), Mobility depends on the sample rate. All being equal, the higher the sample rate, the smaller the change in subject area. In the example below, the Immobile threshold was set to 2%, and the Highly mobile threshold was set to 10%. A certain movement pattern detected with a sample rate x determines a change in area of around 15%, which causes EthoVision to consider the subject Highly mobile. If the sample rate doubles, more samples are captured in the same time interval, therefore the same movement results in a smaller change in area between samples. For the intermediate samples, EthoVision XT considers the subject Mobile since the change in area is smaller than 10%. The proportion of samples where the subject is considered Mobile increases relative to the proportion of samples where the subject is considered Highly mobile. As a general rule, the higher the sample rate, the lower the Immobile and Highly mobile thresholds must be. Does Mobility Depend on Track Smoothing? The results of Mobility may differ depending on whether you set a Minimum Distance Moved filter (see The Minimal Distance Moved Smoothing Method). When you apply this filter, a sample in the track that is very close to that at the previous time stamp is given the same coordinates as the previous one. When that occurs, the Area change is also set to zero for that sample. This results in a lower value of the average Mobility. In contrast, other track smoothing methods do not influence Mobility. See Smooth the Tracks. If you want to preserve the values of Mobility when the animal is almost completely still, instead of using the Minimal Distance Moved filter, select the data based on Movement. In the Data profile, choose Nesting > Movement. Under Calculate nesting for, select Not moving and set the threshold velocities in such a way the animal is considered Not moving when its velocity is lower than the Stop velocity value. See Nesting over Movement. Next, calculate Mobility. See Also - Movement - Rotation Zones and Exploration - In zone - Distance to zone - Distance to point - Target visits and errors - Zone alternation - Zone transition - Head directed to zone Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Mobility URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-mobility Chapter: EthoVision XT Definition The percentage changed pixels of the detected subject between current sample and previous sample. NOTE Mobility is not available if your experiment is set to: - Live Mouse Tracker (but see Stretch attend posture). - Center-point, nose-point and tail-base detection, when you track two subjects per arena with Deep learning. Calculation Step 1 - Calculation of the Changed Area All pixel coordinates of the subjects are determined immediately after they have been detected. Those coordinates are compared with the previous sample to determine the number of changed pixels between the two. The changed pixels are: - The subject pixels found in the current sample but not in the previous sample AND. - The subject pixels found for the previous sample but not for the current sample. This can be expressed in the following formula: CAk = (Ak - Ak-1) + (Ak-1 - Ak) Where CAk is the changed area for the current sample k, Ak is the area for the sample k, and Ak-1 the area for the sample k–1. In the example below, CA is the sum of the orange areas when comparing the contour of the subject with that at the previous sample. The sum equals the symmetric difference between sets of points known in mathematics and is generally indicated with delta (Δ). The changed area is shown for samples 2 and 3. The changed area (in number of pixels) is available when you export your raw data. Open the export file and locate the column named Areachange. Note that Areachange is not the same as the difference in Area between the current and the previous sample. Mobility is calculated by taking every pixel identified as the subject and comparing it between the current image and the previous one. Note that Mobility also includes movement in space (e.g. walking). Step 2 - Calculation of Mobility The formula for Mobility is the changed area for the current sample k divided by the sum of the current area and the previous area. Step 3 - Running Average To smooth the Mobility parameter, an Averaging interval is used. This gives you the option to specify the number of samples for calculating a running average of Mobility. The Mobility percentage calculated as above is averaged over the number of samples that you specify. This way, sudden changes in surface area caused by such factors as the animal entering a shadowed area and not being identified correctly, or a reflection being identified momentarily as the animal, are smoothed out. See also Averaging interval. When you export data, you do not export any information about which averaging interval was used. Range Mobility ranges from 0% to 100%. - If all the pixels of the detected subject are equal in value between sample k-1 and sample k, for example when the subject is completely still, Mobility at sample k is 0. - If the animal moves and increases its velocity, whilst keeping the same shape, there will be an increase in mobility, because the pixels belonging to the animal are increasingly different as it moves faster. - When the subject is so fast that its contour at consecutive samples does not overlap anymore, then all the pixels are different. CA is maximal and equals the sum of the two contours. Therefore, Mobility is 100%. How to Specify Mobility - Open an Analysis profile and in the Dependent Variables panel, under Body, click the Add button next to Mobility. - Select the Averaging interval. See Step 3 - Running Average above for more information on the Averaging interval. - Click the Trial Statistics tab and select the statistics you want to calculate. Notes - When the experiment is set to Color marker tracking, that is, when EthoVision only tracks the markers and ignores the body contour of the subject, Mobility is calculated based on the surface area of the marker. See Also - Mobility state - Frequently asked questions about Mobility Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Mobility state URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-mobility-state Chapter: EthoVision XT Definition A discrete (state event) variable with three possible states: Highly mobile, Mobile and Immobile, depending on where the changed pixels of the detected subject between current sample and previous sample (referred to as changed area) lay relative to two user-defined thresholds. - For the difference between Mobility and Movement, see Frequently asked questions about Mobility. - For the difference between Mobility and Activity, see Frequently asked questions about Activity. NOTE Mobility state is not available if your experiment is set to: - Live Mouse Tracker. - Center-point, nose-point and tail-base detection, when you track two subjects per arena with Deep learning. Calculation The Mobility state variable is calculated for each sample according to the value of the running average Rotation relative to the thresholds: - Below the Immobile threshold, the state is Immobile. - Between the Immobile threshold and the Highly mobile threshold, the state is Mobile. - Above the Highly mobile threshold, the state is Highly mobile. When the subject goes missing for more than three samples, the current Mobility state is ended and the remaining missing samples are ignored. See also Frequently asked questions about Mobility. How to Specify Mobility State - Open an Analysis profile and in the Dependent Variables panel, under Body, click the Add button next to Mobility state and click the Mobility State tab. - Enter the following: - Averaging Interval: The number of samples over which the running average mobility is based. The default value is 1, that is, the mobility measure is not smoothed before determining the Mobility state variable. - Highly mobile threshold: The percentage of change in body area above which the subject is considered to be Highly mobile. - Immobile threshold: The percentage of change in body area below which the subject is considered Immobile. You can enter a number with up to two decimals. - Under Calculate statistics for, select at least one of the three following options: - Highly mobile: Statistics are calculated for when the subject is considered Highly mobile. - Mobile: Statistics are calculated for when the subject is considered Mobile. - Immobile: Statistics are calculated for when the subject is considered Immobile. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - To find the optimal Highly mobile and Immobile threshold, run a few test trials and check in the Analysis Results and Scoring pane the values of Mobility when the animal shows such behavior. These values are calculated real-time during acquisition. See an example in Porsolt swim test: view the Mobility state variable. - Since Mobility is calculated on the detected subject, the gray-scale threshold values used in detection also have an influence on the mobility variable. If your detection settings are such that only part of the animal is detected, then only the mobility for that part is calculated. - In some cases the number of samples available for smoothing can be less than the averaging interval entered. For example, when there are missing samples or at the beginning of the track. In such cases EthoVision XT uses the samples available in the specified interval. For example, the value of Mobility for the first sample of the track is always calculated over one sample. See Averaging interval. - You set the thresholds during acquisition, but you can override them when calculating statistics to produce new values for Mobility. To see what the original values of Mobility thresholds were (unless you have changed them while acquiring data), open the Acquisition module and click the button next to Mobility in the Analysis results and Scoring pane. Applications - Mobility can be used to assess general activity, and changes in behaviors in specific paradigms. For example, in Porsolt swim tests (for example, Russig et al. 2003, Behav. Pharm. : 1-18) it allows to detect changes in behavior, for example from swimming to floating, more objectively than when observing directly. - You can also use Mobility to detect freezing behavior in which case you need to set a very low value of Immobile threshold. Mobility can also be used to quantify movement of zebra fish embryos within their eggs in a 24-well plate with back-lighting. See Also - Frequently asked questions about Mobility Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Modify the layout of the results table URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-modify-the-layout-of-the-results-table Chapter: EthoVision XT Aim To make sure your results are grouped and displayed in the most useful way possible. This is particularly the case when exporting the results to another application. NOTE: This applies to Trial Statistics and Group Statistics. Prerequisites - You have run analysis (Analysis > Results > Statistics and Charts > Calculate). General Procedure Click the Layout button on the toolbar, or choose Show/Hide > Layout. By default, the results table shows the dependent variables and their statistics on the columns, and the trials on the rows. In the following example you can see how you can customize the layout of the table. What Do You Want to Do? - Add a header to the table - Remove a header from the table - Special headers in the Layout window - Move a header between rows and columns - Swap rows and columns - Modify the table hierarchy - Show and hide part of the table - Remove empty rows or columns - Reset the table layout - Move the headers in the Group Statistics results table Add a Header to the Table EXAMPLE: In the Trial Statistics page, add the independent variable Treatment, so that each row (trial) is labeled with the value of Treatment, either Compound or Vehicle. - Click the Layout button on the toolbar. - In the Available box, click the header you want to add. - Click the arrow button which points to the On Rows box. - OPTIONAL: Move the header up in the list to have trials separated based on the values of Treatment. NOTES: - If you click the arrow button which points to On Columns, the variable is placed in columns. - TIP: To add a new dependent variable, do this in the Analysis profile, then return to Analysis > Results > Statistics and Charts. Remove a Header from the Table EXAMPLE: Remove the Arena name from your table headers. - Click the Layout button on the toolbar. - In the On Columns/On Rows box, click Arena. - Click the arrow button which points to the Available box. - To remove measurement units, in the Layout window de-select Measurement units. - To remove the detail of a dependent variable, like the body point name, in the Layout window de-select Detail about variable. NOTE: Removing an element from the headers does not aggregate the results under that header. For example, if you remove Arena, all results are still displayed for each arena separately. If you want to aggregate results, see Define groups of tracks. Move a Header Between Rows and Columns EXAMPLE: The dependent variables (Velocity, In zone, etc.) are placed in columns. Move them to the rows, so that each row represents one trial × dependent variable combination. - Click the Layout button on the toolbar. - In the On Columns box, click Variable with detail. - Click the arrow button which points to the On Rows box. Swap Rows and Columns Select each item under On Columns and move it to On Rows. Next, select the items originally under On Rows and move them to On Columns. Modify the Table Hierarchy To place a header to a higher level in the table, click the element in the On Columns or On Rows box, and then click the Up button. To place an element lower in the table hierarchy, click the element in the On Columns or On Rows box, and then click the Down button. NOTE: It is not possible to put Time bin above the Selection Result. Show and Hide Part of the Table - Click the Show/Hide button at the top-right corner and select the corresponding element. - In the window that appears, select the trials, arenas, subjects, etc. that you want to have in the table. - Click OK. Remove Empty Rows or Columns TIP: Do this if you have many rows or columns that are empty, and you want to export only the rows and columns with significant results. In the Layout window, select Hide empty rows or columns. NOTE: Rows and columns are not removed if at least one dependent variable is calculated for that row or column. Reset the Table Layout To return to the default layout, click the Layout button and in the Layout window click the Reset Default button. Move the Headers in the Group Statistics Results Table The results of group statistics shows the group statistic under the trial statistic. In the example below, you find the group statistic Mean under the trial statistic Total for distance moved. This means that the result is the mean value of the total distance moved calculated for each trial in that group. When you click the Layout button, the item Group Statistic with units is selected under On Columns. You can move the Group Statistics headers and the units to the table rows or move them to a higher level in the table. - Move a header between rows and columns - Modify the table hierarchy - TIP: To have the track groups in different columns, not rows, select Selection Result and move it to On Columns. Special Headers in the Layout Window - Statistic with unit and Group statistic with unit show the names of the trial statistics and group statistic selected in the Analysis profile, respectively. If you move those headers in the table, the measurement units are moved to the same location. - Selection Result refers to the dataset specified in the Results boxes of the Data profile. If the Data profile includes two or more Result boxes, for example to group tracks, the headers for the corresponding boxes are automatically added to the table. NOTE: If you remove Selection Result from the rows and columns, the results for different groups are still kept separate, because the Data profile that specifies those groups is still active; only the headers disappear. If you want to merge results, use another Data profile. - Time bin refers to the time bins defined in the Results box of your Data profile. If you do not define time bins in the Data profile, and select Time bin in the Layout window, the headers Start-End are added; no time bin is created. See Results per time bin. - Zone refers to the zones specified in the Results box of your Data profile. If zones are not specified, analysis is done for the whole arena and the table shows In Arena. See Calculate the results per zone. - The independent variables that you have defined are not shown in the table by default. To export the table with the independent variable values as an analysis factor, click the Layout button and move that variable to On Rows or On Columns depending on how your statistics program treats analysis factors. EXAMPLE: An independent variable Group with possible values Mutant and WT has been defined in the Trial List. To have the values of this independent variable displayed for each trial, click Layout, select the variable Group on the left and move it to the On Rows box. - Missed samples — This is the percentage of samples that EthoVision XT could not analyze. To reduce this percentage, see Factors affecting the occurrence of missing samples in Sample rate. - Subject not found — This is the percentage of the analyzed samples in which EthoVision XT could not find the subject. A lower value indicates high reliability of data. To reduce this value further, optimize the lighting conditions and adjust the Detection Settings to improve detection rate. - If you select track segments with Nesting, there is no special header for them. However, remember that the results are calculated over the track segments defined, not the entire tracks. See Also - The Statistics Result - Trial Statistics Result - Group Statistics Result Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Movement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-movement Chapter: EthoVision XT Definition A discrete (state event) variable, based on one of the body points, with two possible states, Moving and Not moving: - The state is Moving if the running average velocity of the body point exceeds the user-defined Start velocity. - The state remains Moving until the running average velocity drops below the user-defined Stop velocity. - The state then becomes Not moving until the running average velocity reaches the Start velocity again. In order to reduce the sensitivity of this dependent variable to brief changes in velocity, the data can be smoothed by taking the running average of the last k samples. This number is referred to as the averaging interval. When a body point is missing for more than three samples, the current Movement state ends and the remaining missing samples are ignored. In the following example, the velocity initially lies between the Stop velocity and the Start velocity. Therefore, the Movement state is undefined. When velocity exceeds the Start value, Movement is given the value Moving. When velocity drops below the Stop value, Movement is given the value Not moving. How to Specify Movement - Click the Add button next to Movement. - In the Movement tab, enter the following: - Averaging interval: The number of samples over which the running average velocity is based. The default value is 1, that is, velocity is not smoothed before calculating the Movement variable. - Start velocity: The velocity above which the subject is considered to be moving. - Stop velocity: The velocity below which displacements of the subject's body points are no longer attributed to locomotion but to system noise, body wobble or pivoting on the spot. NOTE: The default values are an example and may not apply to your experiment. The threshold values also vary between species. If the subject is very slow, like a walking tick, you must reduce the two thresholds to detect true movement. - Under Calculate statistics for, select either one or both of the following: - Moving: To calculate statistics for when the subject is moving. - Not moving: To calculate statistics for when the subject is not moving. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - If your experiment is set to Center-point, nose-point and tail-base detection, click the Body points tab and select the body points for which you want to calculate movement. - To find the optimal Start velocity, plot the values of Velocity and take note of the values when the animal moves in the video. Do this for a couple of videos. The Start velocity should be just below those values. Similarly, to find the optimal Stop velocity, take note of the values of velocity when the animal sits still. The Stop velocity should be just above those values. A more objective evaluation could come from a statistical approach (e.g. to find cutoff values that discriminate between different behaviors, moving vs not moving). - By increasing the averaging interval, you can increase the reliability of movement detection. A running average velocity based on more samples diminishes the effect of random changes in velocity due to noise. However, a drawback of increasing the averaging interval is that it causes a delay in the determination of a state transition, proportional to the length of the interval. See Averaging Interval. - Values of velocity between Start velocity and Stop velocity result in no change in the current state of the subject (moving or not moving). The smaller the difference between the two threshold velocities, the more likely that transitions between the states Moving and Not moving are scored. By defining such a buffer, you prevent overestimation of transition rates because of a velocity joggling just around the movement threshold. Application Like Velocity, Movement provides information on the subject's locomotor activity. In rodent models of aging, the total duration of Moving, both in seconds and as percentage of the trial time, are used to calculate the frailty index. See Parks et al. (2012) J. Gerontol. A 67(3): 217–227. Definition Acceleration at sample k is obtained by dividing the difference in Velocity by the time difference between that sample and the previous one, where: - Ak = Acceleration at sample k - Vk = Velocity at sample k How to Specify Acceleration - Click the Add button next to Acceleration. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - If your experiment is set to Center-point, nose-point and tail-base detection, click the Body points tab and select the body points for which you want to calculate acceleration. - Because it is based on change in velocity, Acceleration needs three valid consecutive samples. A missing sample in your track results in missing Acceleration values in that and in the next two samples. See also the notes under Velocity. - Acceleration is sensitive to random changes in velocity between consecutive samples due to noise. Check the track and velocity plot to see if changes in velocity represent true acceleration. If necessary, apply Lowess smoothing to the tracks. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Multi-arena Protocols URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-multi-arena-protocols Chapter: EthoVision XT Analysis of Trial Control Data How to add a Hardware Continuous Variable to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware continuous. - The Hardware continuous variable window opens. From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze how many pellets your pellet dispenser dropped, select Pellet Dispenser (PTPD-001x). - In the Device list the name of the hardware device will appear as you defined it when you assigned the device to the arena. - From the Signal list, select which signal you want to analyze. For instance, for the pellet dispenser you can select Number of drops. - Click the Trial Statistics tab to choose the statistics for the dependent variable. If you want summarized statistics over all trials, or the groups of trials defined in your Data Profile, click the Group Statistics tab and select additional statistics. Next, click Add. For details, see Calculate Statistics in the EthoVision XT Help. Application: Hardware Continuous Variable By selecting Hardware continuous variable as Dependent Variable, you can calculate, for instance, how many pellets your pellet dispenser dropped or how long your mouse has been drinking from its water bottle. You can also calculate the frequency drinking from the bottle took place. But often many of these drinking occurrences together form a single drinking bout. Analyzing such bouts is not possible in the current version of EthoVision XT. This means that to calculate how often such bouts occurred, you have to export the data to a Hardware log and analyze this in an external program like Excel. Note: Devices with Fixed Sampling Intervals Devices such as the Lickometer and PhenoWheel send data to EthoVision XT at fixed times, every two seconds for the Lickometer and every 60 seconds for PhenoWheel. At each sample time, EthoVision XT reads the data since the last reading event: - For the Lickometer: number and duration of licks. - For PhenoWheel: number of rotations. The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also include some time before the trial start (less than 2 seconds for Lickometer, less than 60 seconds for PhenoWheel). This time is included in the results. - The data between the last reading event and the stop of the trial are not included in the results. This time is again less than 2 seconds for Lickometer, less than 60 seconds for PhenoWheel, depending on when the trial stopped. In most cases the two discrepancies have no effect on your data when the trial lasts at least a few minutes or hours, like in typical PhenoTyper tests. Tip: If you want the devices to have another sampling rate, contact Noldus. Hardware State Variable A variable based on a Hardware continuous variable. You can, for example, define a Hardware state variable Number of dropped pellets is equal to or greater than 1 and calculate, for instance, the duration of this interval. How to add a Hardware State Variable to an Analysis Profile - In the Experiment Explorer, right-click Analysis Profiles and select New, or click an existing profile. - Click the Add button next to Hardware state. - The Hardware state variable window opens. From the Device type list, select the hardware device you want to calculate statistics for. For example, if you want to analyze the signal from your pellet dispenser, select Pellet Dispenser (PTPD-001x). - In the Device list the name of the hardware device will appear as you defined it when you assigned the device to the arena. - From the Signal list, select which signal you want to analyze. For instance, for the pellet dispenser you can select Number of drops or In error state. - Set the appropriate Value (threshold) or select the value you are interested in. For instance, for Number of drops set a threshold of equal to or greater than 1, for In error state select true or false. - Cumulative value: Select this option to calculate/visualize the cumulative value of the signal. - Click the Trial Statistics tab to choose the statistics for the dependent variable. Click the Group Statistics tab and select additional statistics if you want summarized statistics over all trials, or the groups of trials defined in your Data Profile. Next, click Add. For details, see Calculate Statistics in the EthoVision XT Help. Application: Hardware State Variable You can use Hardware state variables to analyze, for instance, how long a light was on. You can also use Hardware state variables to analyze learning behavior. For instance, when training an animal you may want to know how long it takes before it completes a task (and receives a food pellet). For this purpose, you can calculate the statistic Latency to first for the Hardware state variable Number of drops greater than or equal to 1. For naive animals the latency will be high at the start of the training and will decrease as the animals learn the task in subsequent trials. Please note that the following question requires a different procedure: What was the average time between "light on" and "lever press" in a learning experiment? It is not possible to define a variable based on two separate hardware events. To answer this question, define a Free interval using hardware events. For more information, see Free interval in the EthoVision XT Help. Free Intervals Based on Trial Control and Hardware Data Free intervals are the most flexible solution to analyze slices of time which go from an event, or time, to another event or time. You can use them in the Analysis profile and in the Data profile. Example: In a DanioVision experiment, analyze the speed of the subjects in the 5-second time interval before the onset of the light stimulus, and in a second interval, in the 5-second time interval after the onset of the light stimulus. Because you want to analyze the speed within the intervals, define those intervals as Free intervals in the Data profile. How to add a Free Interval to an Analysis Profile In the Analysis profile, under Custom Variables, click the Add button next to Free interval. For more information, see Dependent variables in Detail > Custom Variables in the EthoVision XT Help. How to add a Free Interval to a Data Profile In the Data profile, under Nesting, click the Add button next to Free interval. For more information, see Analyze Track Segments > Nesting over a free interval in the EthoVision XT Help. The Analysis Results To Calculate the Statistics - Click Statistics & Charts in the Project Explorer. The analysis window that appears has the tab Trial Statistics for the analysis results per trial and Group Statistics & Charts with statistics and charts from the summarized results over different trials. - If you have different filters, data profiles, or analysis profiles, make your selection on the toolbar. - Click Calculate. - Optional: Click the Layout button to modify the layout of the results table. Batch Analysis To run different analyses with different combinations of filters, do the following: - Click Batch. - Select the profiles from the lists and click Add. - Repeat the previous step for other combinations. - Click Calculate. - Select the combination of profiles from the lists on the toolbar to view the results. Export Trial Control Data You can export Trial Control data just like the other dependent variables. - Choose Analysis > Export > Raw Data. - Select the following: - Track & dependent variables: To export events and intervals defined in the Analysis profile. For example, actions and conditions and intervals in between. This option also includes hardware-based actions and conditions, not the actual communication signals. - Hardware log: To export the communication signals between EthoVision XT and the hardware device. - Click Start Export. Exported Raw Data File In the exported raw data file, each Trial Control event or Trial Control state defined in the Analysis Profile is stored in a column. - A Trial Control event is exported as 1 (one) in the row corresponding to the time when the event occurs. In the other rows, it is exported as 0 (zero). - A Trial Control state interval is exported as 1 (one) in the rows corresponding to the time included in the interval. If the interval occurs in multiple instances during the trial, you will see multiple segments of 1. For more information about exporting track data, see Export tracks in the EthoVision XT Help. Hardware Log File When you select Hardware log in the export screen, hardware events are exported to a separate file. The data are organized in columns as follows: - Time is the time when the signal value is read or the action is taken. Note: This is the time elapsed since the start of the trial, not the start of tracking. For lickometers, values are updated about every 2 seconds. - Device ID is the name of the physical device that the event refers to. - Command/Signal is the type of data (Command, or Signal). - Name is the name of the command or signal. - Value is the value of the signal at that time. Each row of the file contains one of the two: - Rows marked with Signal: The value of the signal since the last time the device was read (for example, the number of licks or the duration of licks since the last reading). Duration of licks is expressed in milliseconds. - Rows marked with Command: The command (for example, Drop pellet). - The hardware log file is one per trial, no matter how many arenas and devices are used. - If you re-do a trial, the log files recorded with the previous instance of the trial are deleted. - In order to be logged, hardware devices must be connected to the computer and configured in EthoVision XT. - Notice that the Time in the Hardware log file is the time since the start of the trial, while the time in the Track data file is the time since the start of tracking. Example: If you have defined a command like Drop pellet as a Trial control event, to find a specific Drop pellet event in the data file, take note of the Time in the Hardware log file for that event and locate that time in the Time trial column in the Track data file. - For Pellet dispensers: Number of drops is the feedback signal sent by the device to EthoVision. Usually it is recorded 0.04 seconds after the actual Drop pellet command. - Choose Hardware log if you want to export communication data between EthoVision and the hardware device, even when the device was not used during the trial. - If you select both Track data and Hardware log, data are exported in separate files when choosing the Text format, and in one file when choosing the Excel format. In the Excel file, Track data and Hardware log data are stored in separate sheets. Apply Different Protocols to Different Arenas Introduction This section is intended for EthoVision users who record data with multiple arenas simultaneously, and want to apply different Trial Control protocols to different arenas. Example: The camera points at two separate arenas, each with one animal. In arena 1, provide a foot shock 30 seconds from the start of the trial. In arena 2, provide a foot shock at a randomly chosen time between 0 and 90 seconds from the start. Multiple Arenas in Your EthoVision Experiment If you work with multiple arenas within an experiment, each arena is treated as an independent replicate. In most cases, you want to apply the same Trial Control protocol to all the arenas. Imagine that you create a Trial Control protocol that stops tracking when the subject has moved a certain distance. You define one Trial Control Settings profile and apply that profile for your trial. Because subjects differ in their behavior, tracking will stop at different times for each of those arenas. That is because EthoVision XT uses multiple copies of the same Trial Control Settings, one for each arena. Same Protocol, but Independent Processes The Trial Control Settings are applied to each arena independently. Suppose that the protocol is "After starting the trial, switch on a light when the animal enters the zone named Food zone". A light device has been installed on top of both arenas, and a zone named Food zone has been defined in the Arena Settings for both arenas. If the animal in Arena 1 enters its Food zone, the corresponding light will be switched on. However, the light on top of Arena 2 will not be activated, unless the animal in Arena 2 enters its own Food zone too. Although the protocol is the same, it is applied in two copies, one for each arena. To implement this, select the different physical devices (Light 1 for Arena 1, Light 2 for Arena 2, etc.) on the same line in the Arena - Hardware Mapping window (Arena Settings). This way different arenas refer to the same generic Device name (for example, "Light"). This generic name is then used in the instructions of the Trial Control protocol. Another typical example is the PhenoTyper setup, where the same protocol is applied to a group of 4 or more cages. Conditions and actions are processed independently for each cage. Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - Multi-Camera Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-multi-camera-configuration Chapter: EthoVision XT EthoVision XT Multi-Camera Configuration Aim To have EthoVision XT mix the images from multiple cameras in a picture-by-picture fashion. Procedure - Connect your cameras. Connect each camera to the port of its Ethernet board. Each camera has its unique link with one of the Ethernet boards. This link is the IP address. If you swap cameras, EthoVision XT won't get the camera image. See Connect the GigE Camera to the PC and Assign IP Addresses. - In EthoVision XT, choose Setup > Experiment Settings and select the number of cameras from the list next to Number of sources. - Select the cameras under Source. The camera names will show their own IP address in brackets at the end, which makes it possible to distinguish between the cameras. - Select the resolution and frame rate of the first camera. The resolution and frame rate of the other cameras is set automatically to the same values as for the first camera. - Next to Merged camera view, select whether the picture-by-picture mixed image should have the same resolution as the images from the individual cameras, or whether the resolution should be the sum of that of each camera image. NOTE: The maximum total resolution depends on which cameras you have. For Basler monochrome cameras, the maximum resolution is 2560 x 2048 when mixing four camera images. However, each camera model has its own set of available resolutions, which also determine the maximum resolution when merging the camera images. See tested configurations for GigE cameras (including PhenoTyper 2). - Click the preview icon to get a preview of the merged camera images. Recommended Video Resolutions - 4-camera configuration: Single camera view 1280 x 1024, merged camera view 2560 x 2048. See Using Multiple GigE Cameras. - 8-camera configuration: Single camera view 640 x 480, merged camera view 2560 x 960. See Using Multiple GigE Cameras. - 16-camera configuration: Single camera view 640 x 480, merged camera view 2560 x 1920. See 16-Camera Configuration. - See also Resolution, Frame Rate, and Maximum Trial Duration. Notes - Noldus does not support video tracking from multiple GigE cameras connected to a laptop computer. Always connect multiple cameras to a desktop computer. - When using multiple cameras, pay attention to the lens settings. These should be in such a way that the apparent size of the arenas is the same since you calibrate the distance for all the cameras (Shared calibration). If that is not possible, make one calibration for each arena (Unshared calibration). See Calibrate Multiple Arenas. - The cameras should have the same firmware version. Check this in the pylon Viewer software. In the Features panel, under Device Information, check Firmware Version. If two or more cameras do not have the same firmware, an upgrade or downgrade must be done. See Also - Cameras Supported by EthoVision XT - For examples of frame rate and resolution when using multiple cameras: GigE Cameras - Connect the GigE Camera to the PC - Assign IP Addresses - To View the Camera Image: Select Multiple Cameras - PhenoTyper - EthoVision XT 19 - Reference Manual. See Manuals. Install USB 3.0 Cameras To work with a USB 3.0 camera, if your PC does not have a USB 3.0 port, then you need to install a USB 3.0 interface board (for desktop computers). What Do You Want to Do? - Install the USB 3.0 interface board - Install the USB 3.0 camera driver - Connect the USB 3.0 camera to the PC - Configure the digital camera See Also - Cameras Supported by EthoVision XT Install the USB 3.0 Interface Board Aim To install an interface board that receives video from one or more USB 3.0 cameras. The following USB 3.0 interface boards have been tested: - U3-PCIE1XG205-1S Ren 1HC, x1, 2 ports - U3X4-PCIE4XE111 Fresco FL1100, 4HC, x4, 4 ports IMPORTANT: Although these boards have multiple USB ports, always connect one camera only. Procedure - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. For details about PCIe slots, see Install an Ethernet Board for GigE Cameras. - Unpack the USB 3.0 interface board, place it into the slot, and press it carefully into position. If the board does not fit into place easily, remove it and repeat the operation. - Fix the board to the chassis and re-fit the computer's cover. If you have a 4-port Fresco Logic U3X4-PCIE4XE111 board, make sure that the board receives power from the PC. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. - Proceed with Install the USB 3.0 Camera Driver. Notes - For the best performance, the USB 3.0 interface board should be installed in a PCIe Gen 2 compliant slot in the host computer. Most computers have PCIe Gen 2 (5.0 Gbps) throughput on x8, x16, or x32 slots. A PCIe Gen 1 compliant slot reaches up to 2.5 Gbps throughput. - IMPORTANT: Turn off Fast Startup in the Windows Power options. See Power Options When Using Cameras. Install the USB 3.0 Camera Driver Aim To install the software that enables you to configure the camera — for example, to set the video frame rate or the exposure time. Prerequisite - You have installed the USB 3.0 interface board. See Install the USB 3.0 Interface Board. Procedure - Follow the procedure in the topic Install the Driver Software for the Digital Cameras: - If you have already installed EthoVision XT, on the installation screen choose Modify and under Drivers and tools choose Basler USB camera driver. - If you still have to install EthoVision XT, choose Install, then under Drivers and tools choose Basler USB camera driver. - Next: Connect the USB 3.0 Camera to the PC. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Nest URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-nest Chapter: EthoVision XT Nest Definition A discrete (state event) variable that is scored when the subject is in contact with two or more subjects. All those subjects do not move. Note that the variable Nest has nothing to do with nest-building behavior. Calculation EthoVision XT considers the events of type Contact stored in the Live Mouse Tracker database, which overlap with the events of type Stopped. That means that Nest includes only instances when the focal subject is in contact with other subjects, like in Group, with the additional condition that none of those subjects moves. Finally, instances of Nest shorter than two samples are removed and adjacent instances up to three samples apart are joined to form one instance. Contrary to Group, EthoVision XT does not split the results based on the identity of the subjects forming a Nest. How to Specify Nest - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Nest. - Specify the Nest size. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. - If you wish to have the results for all nest sizes in one table, repeat the steps above to add more Nest variables, one for each size. Example Subject A (red dot), B (light green) and D (dark green) are forming a nest. Subject C (orange dot) walks around and is therefore not part of the nest. In the Trial Statistics, Frequency is the number of instances of Nest (color bars on the time line as in the figure above) and Cumulative Duration is the sum of the duration of all the instances in the selected trial (or interval). Applications You can use Nest to quantify the tendency of subjects to huddle together and form groups. Nest occurs especially in the sleep (light) phase. See also - Group - Dependent variables for Live Mouse Tracker Nose Contact Definition A discrete (state event) variable that is scored when the focal subject's nose is near the nose point or the tail-base point of another subject. Calculation - Nose-nose contact is scored when the distance between the nose-point of the focal subject is at less than 15 pixels (26 mm for Live Mouse Tracker arenas) from the nose-point of another subject. - Nose-anogenital contact is scored when the distance between the nose-point of the focal subject is at less than 15 pixels (26 mm for Live Mouse Tracker arenas) from the tail-base point of another subject. How to Specify Nose Contact - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Nose contact. - Under Calculate Statistics for, select Nose-nose contact, Nose-anogenital contact, or both. - Click the Receivers tab. Under Select, choose the subjects that the focal subject was in nose contact with. If you select two or more subjects, select one of the available options from the list: - All selected subjects: Nose contact is scored when the focal subject was in contact with all the subjects selected above. - Any selected subject: Nose contact is scored when the focal subject was in contact with any of the subjects selected above. - Each subject: Nose contact is scored when the focal subject was in contact with one of the subjects selected above. The results are displayed for each Receiver. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Example A Nose contact variable has been defined with both options Nose-nose contact and Nose-anogenital contact selected. In the current video image, Subject A (red dot) is in nose contact with Subject D (dark green dot). In the Trial Statistics results table, with the default layout, the results of Nose contact are shown per subject (on the rows). The columns vary depending on what you chose in the Receivers tab: - If you chose Each subject, the columns contain the statistics of Nose contact with specific subjects (for example, Nose-nose contact / A to D). - If you chose All selected subjects or Any selected subject, a column Nose-nose (or Nose-anogenital) / All of A, B, C, D or Nose-nose (or Nose-anogenital) / Any of A, B, C, D contains cumulative statistics of Nose contact when the subject was in contact with all cage mates simultaneously or with any of them, respectively, depending on which option you chose. Notes - For this variable, Live Mouse Tracker takes the distance between the body points on the X,Y plane, and ignores their Z coordinates. - In the Analysis profile under Social, you find Body contact. This is a variable that quantifies the level of generic body contact between subjects. See also - Nose contact sequence - Social Behavior > Body contact - Dependent variables for Live Mouse Tracker Nose Contact Sequence Definition A discrete (state event) variable that is scored from an instance of nose contact of one type to the following nose contact of opposite type, both performed by the focal subject. In other words: - From an instance of Nose-nose contact to the next instance of Nose-anogenital contact. Or - From an instance of Nose-anogenital contact to the next instance of Nose-nose contact. See also Nose contact. Calculation - EthoVision XT selects all instances of type Nose-nose contact or Nose-anogenital contact (depending on what is chosen in the settings), and longer than 10 video frames (0.33 s for a video of 30 fps). - EthoVision XT selects all the instances of type of Nose-contact other than that selected in the previous step, and longer than 10 video frames (0.33 s). - If the second Nose-contact occurs within 60 video frames (2 seconds, for a video of 30 fps) from the end of the first one, a Nose contact sequence is found. How to Specify Nose Contact Sequence - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Nose contact sequence. - Under Calculate Statistics for, select Nose-nose to Nose-anogenital, Nose-anogenital to Nose-nose, or both. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Example The following example shows a sequence of type Nose-nose contact to Nose-anogenital contact of Subject A directed to Subject B. The position and orientation of the subjects at the beginning and at the end of the sequence are shown. Triangles represent the nose points and squares represent the tail-base points. See also - Nose contact - Dependent variables for Live Mouse Tracker - Social > Body contact Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-observer-xt Chapter: EthoVision XT Observer XT Aim: To analyze the events scored manually in EthoVision XT in The Observer XT, for further analysis. Prerequisite In EthoVision XT, export the data in the form of Manual scoring log (for details see Export manually-scored behaviors). Before clicking Start Export, select Manual Scoring log; select one of the Text options as export format, and select semicolon (;) as Delimiter. To export a subset of tracks or subjects, filter the data before exporting. Procedure - Open the export file in the Windows Notepad. - Remove the lines from Experiment to the blank line so that the first line of the file contains Header Lines and the second Trial time. - Change the number of header lines, then save and close the file. - In The Observer XT, create a project or open an existing one. Make sure that the project's coding scheme contains exactly the same behavior names and that these are organized in the same groups (mutually-exclusive or start-stop) as the corresponding behaviors scored in EthoVision XT. See Effects on the Coding Scheme below. - Choose File > Import Observational Data. - From the Files of type list, select EthoVision XT Data File (*.txt). EthoVision XT Data File is an import profile made for manual scoring logs exported from EthoVision XT. It is installed automatically when you install EthoVision XT. If you do not have this import profile, click Create New and see below. - Select the file you want to import and click Open. - Repeat the procedure for the remaining export files (remember that each trial and arena results in a separate export file). - Choose Setup > Independent Variables. Define the independent variables and enter the values of those variables for the trials you have imported. To Create an Import Profile in The Observer XT In the Import Profile Definition window, drag the columns of the Data Sets box as shown here: - Time. Drag the column B (Recording time) to the Time column. This is the time of manually scored behaviors relative to the time that tracking started. In the Select Time Format window, if the time matches one of the predefined formats, EthoVision XT automatically selects one. Converted time shows the converted time and Conversion is OK. Click OK. - You can also define your own format by typing an H for each number representing hour, an m for minute, an s for second, and an f for each number representing millisecond. If Conversion is OK, then click OK. - Under Import Time, select one of the options: - Relative to time zero. Suppose the first row in the imported external data set has time 00:00:05. When the option Relative to time zero is selected, the time stamp of the first row of the imported data set will remain 00:00:05. - Relative to the time of the first data line. Suppose the data set you want to import starts at 14:28:00 and samples every 5 seconds. With the option Relative to the time of the first data line, the first row of the imported data will get the time stamp 00:00:00. The second row will have time stamp 00:00:05. The options under Import Time are grayed out when your time stamps contain the date the file was created. In this case the option Relative to time zero is used. - Do not drag the column A (Trial time) as this provides the same timing as column B when imported into The Observer. - The predefined import profile EthoVision XT Data File uses the Recording time as time code for the manually scored behaviors. - Event Type. Drag the E column and click OK in the window that appears. - If you want to import video in The Observer, you must keep the correct sync between events and video. See To Import Video in The Observer XT below. Effects on the Coding Scheme If you import manually scored data without creating a coding scheme in advance, at import of the first file The Observer creates a coding scheme with all behaviors contained in that file. By default, all behaviors are put in a start-stop group named Behavior1. To re-arrange the coding scheme, delete the observation just imported, move the behaviors of Behavior1 to the groups they belong to, and re-import the data. Independent Variables The Observer does not import the independent variables from EthoVision XT. You must define those variables in the Observer's Independent Variables List and assign the values of those variables to each imported file. You can find those values in the headers of the original export files. Data from Multiple Arenas If your setup includes multiple arenas, for each trial you import one file per arena. If you want to keep data from different arenas (in the same trial) in the same observation, you can import the files of the second, third, etc. arena in the same observation as that of the first arena. To do so, follow these steps: - Follow the procedure above for the first arena. Right-click the name of the resulting observation and select Properties. Edit the observation name by giving a name that specifies the trial only, not the arena (for example, Open Field Trial 12). - For the second, third, etc. arena file, instead of following step 6 of the procedure above, in the Project Explorer right-click the observation name and select Import Observational Data, then follow the rest of the procedure. The files are imported in the observation of the first arena as separate event logs. Rename each event log in such a way that it clearly indicates the arena from which it was obtained. To Import Video in The Observer XT - Open the observation, and from the Observe menu select Video, then Open in Current Observation and select the video file. - Choose the option below that applies: - If the video file was obtained with programs other than EthoVision XT, or if you tracked from video previously recorded with EthoVision, take note of the difference between the Start time and the Video start time (you can find these in the headers of the raw data export file). This difference is 0 only if you start the trial from the first video frame. Also, take note of the value of Recording after (also available in the export file). Calculate the value of Offset = Start time - Video start time + Recording after. - If the video file was recorded with EthoVision while doing live tracking, take note of the value of Recording after (you can find this in the headers of the raw data export file). In this case, Offset = Recording after. - In The Observer XT, click the Offset button. - Choose Numerical Offset and locate the imported event log. In the corresponding cell, enter the Offset calculated as described above, and make sure that the sign stays positive (+). - Open the observation and click the start line of the event log. The video is positioned to the point that the tracking started. See Also - Trial vs. track - For more information on creating an import profile for The Observer XT, see Importing other observational data in The Observer XT Help. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Optogenetics Experiments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-optogenetics-experiments Chapter: EthoVision XT Introduction Optogenetics and EthoVision XT In the last decade, a method was developed to specifically activate or even inhibit small groups of neurons with light. Today, scientists can insert light-sensitive receptor proteins (originally found in algae) into single mammalian neurons in vivo, making these neurons sensitive to activation by light of specific wavelengths. This allows scientists to control the activity of these neurons and study their downstream influence on a variety of biological processes. Optogenetics is an important development for behavioral research. Not only can the actual influence of specific neurons on behavior more specifically be determined, but also, with the help of an automatic video tracking system such as EthoVision XT, behavior can be manipulated via optogenetic methods in real time. With the Trial & Hardware Control module, EthoVision XT can control light pulses given by a third party device, based on the behavior of the animal (for instance, presence in a trigger zone). This chapter focuses on the optogenetics solution for rodents that combines EthoVision XT, PhenoTyper (as test environment) and the Prizmatix optogenetics devices. For how to conduct optogenetics experiments with zebrafish, see the DanioVision DVOC-0041 Reference Manual. Examples Place Preference The animal is placed in an arena with two distinct sides, one of which is paired with optogenetic stimulation. Depending on whether this stimulation is activating or deactivating, and which neurons are affected, this can be a rewarding or aversive stimulus for the animal. If in further sessions the animal spends more time on the stimulated sides, it is fair to conclude the stimulus had a rewarding effect. If the animal avoids this side, the stimulus could then be considered aversive. Operant Conditioning In operant conditioning tests, the animal learns to perform an action in order to get a reward or avoid an aversive stimulus. The behavioral response can be recorded with EthoVision XT, either by detecting the animal (or its nose point) in a certain zone, such as the feeder, or by analyzing the external signal initiated by the nose poke or lever press. Following this action, EthoVision XT sends out the command for optogenetic stimulation. Off-On-Off Stimulus Test In an off-on-off stimulus test, you can program EthoVision XT to turn optogenetic stimulation on for a period of time during the test. For example, a 15 minute test during which continuous optogenetic stimulation takes place in the middle 5 minutes. References - Guru, A., Post, R.J., Ho, Y., Warden, M. (2015). Making Sense of Optogenetics. International Journal of Neuropsychopharmacology, Aug 2015, 1-8. - Zalocusky, K., Deisseroth, K. (2013). Optogenetics in the behaving rat: integration of diverse new technologies in a vital animal model. Optogenetics 2013: 1-17. - Stamatakis, A.M., Stuber, G.D. (2012). Activation of lateral habenula inputs to the ventral midbrain promotes behavioral avoidance. Nature Neuroscience, 15(8), 1105-1107. - Kravitz, A.V., Tye, L.D., Kreitzer, A.C. (2012). Distinct roles for direct and indirect pathway striatal neurons in reinforcement. Nature Neuroscience, 15, 816-818. Physical Setup Components (Example) Devices - PC with EthoVision XT installed. - Noldus USB-IO Box. - PhenoTyper with adapted Top Unit (optional). - Prizmatix LED controller (for different light wavelengths). - Prizmatix Pulser (left) or PulserPlus (right) (with advanced setup). Important: To control the LED through EthoVision, on the back panel of the LED controller, near/below the TTL connector, select Ext (but if you want to activate the LED manually using the button located on the front panel, you should select Int). The other switch on the LED controller, just near/above the Ain 0-5V connector, should be in the Int position. Main Cables and Fiber Cords - USB cable (USB-A to USB-B). Use this cable to connect the EthoVision XT PC to the USB-IO box [USB, type-B]. Also use this cable to connect the Pulser to the PC. - UTP to BNC cable. To connect the USB-IO box [TTL control] to the LED Controller [TTL] or Pulser [Trig. In]. - Note 1: Each TTL port of the USB-IO box has two output lines. The white RCA jack corresponds to Output 1 and the red RCA jack to Output 2. Take note of this when selecting the TTL commands in EthoVision XT. - Note 2: If you received UTP-to-BNC cables with four BNC connectors, only use those marked with Output to connect the LED controller or Pulser. - BNC to BNC cable. From Pulser [TTL Out] to LED Controller [TTL]. - Fiber patch cord, core 1000 um. To connect the LED Controller [front panel] to the PhenoTyper Top Unit [Fiber Coupler adapter]. - Fiber patch cord, core 1000 um. This is located inside the PhenoTyper Top Unit. It connects the FC adaptor to the Rotary joint. - Single fiber. To connect the Rotary joint fixed on the bottom plate of the PhenoTyper Top Unit to the implantable cannula. Available in various core diameters (e.g. 500 um). Other Components - Zirconia ferrules (sleeves) for 2.5 mm and 1.25 mm cannulae. - Optogenetics implantable cannulae (2.5 mm, 1.25 mm). Basic Setup Aim With a basic setup, without the Pulser, EthoVision XT controls activation of the LED directly via the Noldus USB-IO box. With this setup you can, for example, activate the LED for one second. Notes - Activation of the LED can be repeated during a trial using the Subrule function in the Trial Control Settings. - For generating two pulses of different length, you must create separate Trial Control commands. Limit - The minimum pulse duration that can be generated with the basic setup (without Pulser) is determined by the sample rate of EthoVision XT. For example, at a sample rate of 25 samples/second, the minimum pulse duration is 40 ms. Optogenetics Experiments in EthoVision XT Hardware Settings - Choose Setup > Hardware Settings > New. - Select USB-IO box from the device list and click Add. - Select the correct COM port for the USB-IO box. - Click Test to verify the connection. - If using the Pulser, also add the Prizmatix Pulser from the device list and select the correct COM port. Trial Control Settings In the Trial Control Settings, you define when and how the optogenetic stimulus is delivered based on the behavior of the animal. - Choose Setup > Trial Control Settings > New. - Add a rule that defines the trigger condition (for example, the animal's center point enters a defined zone). - Add an action to that rule to send a TTL output signal via the USB-IO box to the LED controller. - Define the duration of the TTL pulse to match the desired stimulation duration. - Use the Subrule function to repeat stimulation if needed. Note: Each TTL port of the USB-IO box has two output lines. The white RCA jack corresponds to Output 1 and the red RCA jack to Output 2. Make sure to select the correct output line in the Trial Control Settings to match the physical cable connection. Selecting the TTL Output - In the Trial Control Settings, select the action Set output. - Select the USB-IO box as the device. - Select the appropriate TTL port and output line (Output 1 or Output 2) that is connected to the LED controller or Pulser. - Set the output state to On to activate and Off to deactivate the LED. Using the Pulser Overview The Prizmatix Pulser and PulserPlus allow you to generate precise, high-frequency pulse trains that cannot be produced by EthoVision XT alone. The Pulser is triggered by a TTL signal from the USB-IO box and then independently generates the configured pulse train to the LED controller. The Pulser is configured using the Pulser software and stores its settings internally. Once configured and triggered, it operates independently of EthoVision XT for the duration of the pulse train. Installing the Prizmatix Pulser - Connect the Pulser to the PC using a USB cable (USB-A to USB-B). - Connect the USB-IO box [TTL control] to the Pulser [Trig. In] using a UTP-to-BNC cable. - Connect the Pulser [TTL Out] to the LED Controller [TTL] using a BNC-to-BNC cable. - Install the Pulser software on the PC. - Open the Pulser software and configure the pulse parameters (frequency, pulse width, number of pulses, etc.). - Save the configuration to the Pulser device. Configuring Pulse Parameters in the Pulser Software - Frequency: The number of pulses per second (Hz). - Pulse width: The duration of each individual pulse (ms). - Number of pulses: The total number of pulses to deliver per trigger event. - Delay: The delay between the trigger signal and the start of the pulse train (ms). Triggering the Pulser from EthoVision XT - In Setup > Hardware Settings, ensure both the USB-IO box and the Pulser are added as devices. - In the Trial Control Settings, create a rule with a behavioral trigger condition (for example, animal enters zone). - Add an action to send a TTL output via the USB-IO box to the Pulser [Trig. In]. - The Pulser receives the TTL trigger and delivers the pre-configured pulse train to the LED controller. Advanced Setup with PulserPlus The PulserPlus provides additional channels and more advanced pulse configuration options, allowing simultaneous control of multiple LED controllers with independent pulse parameters per channel. - Connect each PulserPlus output channel to the corresponding LED controller TTL input using BNC-to-BNC cables. - Configure each channel independently in the Pulser software. - Trigger the PulserPlus from the USB-IO box in the same manner as the standard Pulser. Data Analysis Analysis Profiles Choose Analysis > Analysis Profile. For optogenetics experiments, create analysis profiles that include variables relevant to the experimental design. Typical variables include: - In zone: To calculate the frequency, total time, and latency to first visit for each zone (for example, the stimulation zone and the non-stimulation zone in a place preference test). - Distance moved: A measure of overall locomotor activity. - Velocity: Mean velocity during the trial. - Time in zone: Total time spent in each defined zone, used to calculate place preference scores. Place Preference Analysis - Define zones for the stimulation side and the non-stimulation side of the arena in Setup > Arena Settings. - Create an analysis profile that includes the In zone variable for each zone. - Choose Analysis > Results > Statistics and Charts. - Compare the total time spent in the stimulation zone versus the non-stimulation zone across sessions to assess place preference or avoidance. Operant Conditioning Analysis - Define the relevant zones (for example, the feeder zone or nose poke zone) in Setup > Arena Settings. - Create an analysis profile that includes In zone variables to count the frequency of visits to the operant zone. - Use external event markers or hardware event inputs to log the timing of stimulation delivery relative to the behavioral response. - Analyze visit frequency and latency to first visit to assess learning and response rates across sessions. Off-On-Off Stimulus Analysis - Use the Trial phases or time bins feature in EthoVision XT to divide the trial into the off, on, and off periods. - Create an analysis profile that calculates distance moved, velocity, and time in zones for each phase separately. - Compare behavioral measures across the three phases to assess the effect of optogenetic stimulation. Visualizing Data Choose Analysis > Results > Integrated Visualization to view track plots and event timelines overlaid with zone visits and stimulus delivery events. - Use track plots to visualize the animal's position over time in relation to the stimulation zone. - Use timeline plots to compare the timing of behavioral events with the timing of TTL output signals sent to the LED controller. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - Other Conditioning Tests URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-other-conditioning-tests Chapter: EthoVision XT Analyzing Intervals in the Fear Conditioning Test Define the Intervals with the Nesting Function By default, the whole trial timeline is selected for analysis. However, you may want to select part of the timeline, for example to analyze the Activity variable only when the white light was on. To do so, in the Data profile define an interval based on the event "White Light On". - Choose Analysis > Data Profile > New. - Under Nesting, click the option corresponding to the type of interval you want. - Specify the interval and place the Nest box between the Start and Results box. Which options shall I choose? To analyze the behavior of the subject when, for example, the white light was on, choose Trial Control State. In the window that appears, select the action that marks the start of the interval (e.g., Light On - becomes active), and the action that marks the end of the interval (Light Off - becomes active). If you want to analyze a complex interval, from A to B, where A and B are events of different type, for example, behavior and activation of a stimulus, choose Free interval. For example, select the time from the end of the shock (Shock Off - becomes active) and the first instance of freezing (detected using Activity or Activity state). You can also combine events with time. For example, select the 30 seconds interval immediately after the end of the Shock. From Trial Control - Action: Shock Off - becomes active to Time - Elapsed time: 30 s after start event. Visualize the Intervals Once you have defined the intervals for analysis, it is always a good idea to plot the data and check that the intervals defined in the previous steps are correct. - Choose Analysis > Results > Plot Integrated Data. - The data selected within the intervals is shown in full colors while the data outside the intervals is shown in dimmed colors. Check that the intervals defined correspond to the time segments that you want to analyze. In the example, Activity is visualized within an interval defined as "from Tone On to Shock On". If the intervals are defined correctly, proceed with the statistics calculation. Calculate the Statistics Choose Analysis > Results > Calculate Statistics and click the Calculate button. The results table shows the statistics of the dependent variables defined in the Analysis profile, within the intervals defined in the Data profile. For More Information - For details about the analysis variables, see Dependent Variables in Detail in the EthoVision XT Help (F1). - For more examples about analyzing intervals, see Analyze Track Segments in the EthoVision XT Help (F1). - For more examples of control of hardware devices and PhenoTyper, see the chapter Conditioning Tests in this manual. Technical Specifications Infrared Top Light and Controller For the technical specifications of the Fear Conditioning system, see the Instruction Manual FCS 46000.pdf that comes with that system. Noldus Device Numbers - Top light: UBIRT-001x - Controller: UBIRC-001x Voltage: 24V (standard Noldus power supply) Current consumption on max LED intensity: 220mA Light wavelength: 940nm Incorporated camera: 1280 x 1024 pixels at max 60 fps (30 fps is recommended) Dimensions (L x W x H): - Top light: 28.6 x 29.3 x 8.5 cm (11 17/64" x 11 17/32" x 3 11/32") - Controller: 8.0 x 4.0 x 4.2 cm (3 5/32" x 1 37/64" x 1 21/32") Weight: - Top light: 860 g (30.3 oz) - Controller: 50 g (1.76 oz) Power adapter: Type number TRH70A240-01E13VI, Input 100-240V 1.5 A, Output 24V 3.0 A Other Conditioning Tests Introduction EthoVision XT can be used in learning tests, such as the water maze test and the conditioning tests. The Trial and Hardware Control module of EthoVision XT can be used to operate hardware devices in both classical and operant conditioning tests. In the latter, an action of the animal produces a result, for example, pressing a lever results in the food dispenser dropping a food pellet. This and other hardware actions (such as turning on a light when the animal enters the shelter, or closing the door of a radial maze when the animal has exited that arm) can be operated through the Trial and Hardware Control in EthoVision XT. Learning can be demonstrated by a change in the frequency of the animal's action over time. For example, when the animal is presented with an aversive stimulus every time it performs a certain action, the performance of the action will likely decrease over time because the animal tries to avoid the negative stimulus. To be able to operate hardware devices with EthoVision XT you need: - The Trial and Hardware Control module. This module allows you to control hardware devices from within EthoVision XT. - The USB-IO Box. This is the device that connects the EthoVision XT PC with external hardware devices such as the sound and light devices of PhenoTyper or a third-party hardware device. This document describes how to set up EthoVision XT using Trial and Hardware Control in an operant conditioning test in PhenoTyper. PhenoTyper PhenoTyper is an instrumented cage to measure and test the behavior of laboratory rodents. See https://noldus.com/phenotyper for more information on PhenoTyper. If you want to use EthoVision XT to operate a third-party hardware device, please contact Noldus Information Technology (www.noldus.com). To see how a test with PhenoTyper is carried out in EthoVision XT, see the sample experiment PhenoTyper hardware XT180 on the downloads section of the Noldus website (my.noldus.com). In EthoVision XT, choose File > Restore Backup and select this file. See also the document Description of sample experiments of EthoVision XT.pdf for more information. Fear Conditioning Test In the fear conditioning test, you can use EthoVision XT to automatically detect freezing behavior as a measure of conditioned fear. References - Liu, W., Wang, X., Zhang, R., and Zhou, Y. (2009) Effects of postnatal exposure to methylmercury on spatial learning and memory and brain NMDA receptor mRNA expression in rats. Toxicology Letters, 188, 230-235. - Pham, J., Cabrera, S.M., Sanchis-Segura, C., and Wood, M.A. (2009) Automated scoring of fear-related behavior using EthoVision software. Journal of Neuroscience Methods, 178, 323-326. Physical Setup The following suggestions are meant to optimize tracking: - The camera should have a good view of the entire region the animals can be in (for zones like the shelter where the animal is not visible, you can define hidden zones). - The lighting should be as even as possible throughout the arena and should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). - The background should contrast with the animal. If necessary use a different setup for light and dark colored animals. - Either make sure the sides of the box are not reflective (e.g., sanding), or exclude the sides from the arena. If your objects are close to the sides then you will need to track the animal when it is against the side (so the camera sees the side instead of the base behind the animal). - If you want to use the Deep learning technique to track the subject's nose, keep in mind that there are additional requirements. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. For More Information - About PhenoTyper: see the PhenoTyper - EthoVision XT 19 - Reference Manual. - About using hidden zones: see the section Shelters and other hidden zones in the EthoVision XT Help. A Conditioning Test in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. In the following sections we assume that you created an experiment using the PhenoTyper arena template. Experiment Settings - Make sure that the PhenoTyper cages are connected to the EthoVision XT PC. See the PhenoTyper - EthoVision XT 19 - Reference Manual for how to connect PhenoTyper to EthoVision XT. Connect a third-party hardware device, which can be controlled by TTL, to one of the TTL control ports on the USB-IO Box. - Open the experiment and choose Setup > Experiment Settings. - Check that the correct cameras are selected under Video source. Select whether the resolution of the first camera and that of the mixed image. Note that depending on the number of cameras and the frame rate, you may need to reduce the resolution of the mixed image. For more information about installing and connecting multiple cameras, see Camera installation in the EthoVision XT Help and the PhenoTyper - EthoVision XT 19 - Reference Manual. - If you want to use the Deep learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. - Under Analysis options, select Activity analysis if you want to measure freezing behavior. - Next to Hardware, select Use of Trial Control Hardware and click Settings. - Select Noldus USB-IO box. - In this next step, you define the ports of the USB-IO box connected to PhenoTypers. Select SDI port 13, then Top Unit Interface. Select Top Unit (Standard) for all the rows below (depending on how many PhenoTypers are connected to a Top Unit Interface). For PhenoTyper 2, and for more details and examples, see the PhenoTyper - EthoVision XT 19 - Reference Manual. If you use third-party devices, also select the TTL ports that are connected to those devices. - Click OK. For More Information - About port mapping: see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. - About PhenoTyper connections and devices: see the PhenoTyper - EthoVision XT 19 - Reference Manual and the PhenoTyper - EthoVision XT 19 - Service Manual for specific devices like the Pellet dispenser and the Lickometer. - About general experiment settings: see Set Up an Experiment in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > open Arena Settings 1. Click the Arena - hardware mapping button at the bottom of the Arena Settings pane. If you only have one arena, the hardware will be assigned to this arena automatically. If that is the case, proceed with Trial Control Settings below. In the Arena - Hardware Mapping window, click Add Device for each device you want to add: - For PhenoTyper: under Device Type, select Top Unit (Standard). Enter Device Name PhenoTyper and the corresponding Top Unit (Standard) # for each Arena. - For a third-party hardware device: under Device Type, select Custom Hardware. Enter a Device name and select a device from the list for each Arena. Click 4. Validate Setup to validate the Arena Settings. Trial Control Settings With the Trial and Hardware Control add-on module in EthoVision XT, you can control PhenoTyper and third-party devices in a variety of ways. For example: - Start recording when the animal is detected on top of the shelter. - Stop recording when the animal has performed a specific task 50 times. - When the animal sits on the shelter, drop a food pellet. Repeat this task 25 times. The template experiment contains two trial control profiles: - Default - The default Trial Control Start-Stop rule. - Max. Trial duration 24 hrs - In this profile, a trial stops after 24 hours. Maximum trial duration (tested): - Without video recording: 72 hours. - With simultaneous video recording: 3 hours. If you need to record video of the same subject for more than three hours, we recommend that you make a series of trials. Below you find a few examples of Trial Control Settings. Modify the Trial Control Settings to suit your own application. Procedure Overview - The trial starts with a 30-second delay (see Start trial rule and Condition 'Start delay' below). - Next, as soon as the mouse enters the LightSpot zone, with both the nose- and center-point, the spotlight of the PhenoTyper is turned on. When both the nose- and center-point are not in the LightSpot zone, the spotlight is turned off. This sequence is repeated three times (see Sub-rule 'Activation LightSpot' below). - After the Sub-rule is completed, the trial is stopped after a 5-second delay. Choose Setup > Trial Control Settings > New and give this a new name. Start Trial Rule - To start recording as soon as the Start trial button is clicked, click the (default) Condition In zone box and press Delete. Keep this Condition if you want to start recording some time after starting the trial. Condition 'Start Delay' - To insert a 30-second delay after recording has started: - In the Components pane, under Conditions, double-click the Time Condition or click the button next to it. - In the Time condition window, type 'Delay of 30 seconds' in the Condition name field. In the Condition is met: group, select After a time of 30 secs. Optionally, enter a comment and click OK. - Insert the Condition box into the main sequence. For more information about Conditions, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Sub-rule 'Activation LightSpot' - Because the sequence of turning on/off the spotlight depending on whether the animal is inside/outside the Spot Light Zone is repeated three times, you need to create a Sub-rule for this: - In the Components pane, under Structures, double-click Sub-rule or click the button next to it. - In the Sub-rule window, type 'Anxiety Test' in the Sub-rule name field. Optionally, enter a comment and click OK. - Create an In zone Condition for when the animal enters the Spot Light Zone: - In the Components pane, double-click the In zone Condition or click the button next to it. - In the In zone Condition window, type 'Inside LightSpot' in the Condition name field. - In the Condition is met when: group, from the Statistic list, select Frequency. Next, click the Settings button, select zone Spot Light from In the following zones, and select When in any of the selected zones from the list. In the From the following body points group, select the relevant body points. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - Out of nest URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-out-of-nest Chapter: EthoVision XT Definition A discrete (state event) variable that is scored when the focal subject is away from the remaining subjects, which form a nest. Calculation EthoVision XT finds all the instances of Nest 3, that is, when three subjects are in contact and do not move (see Nest). The state event Out of nest is scored for the remaining subject and lasts as long as the Nest 3 lasts. How to Specify Out of Nest - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Out of nest. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Example In the following figure, subject B is far from the remaining subjects B, C and D, which huddle together forming a nest. The state event Out of nest has been scored for subject A and lasts until one of the subjects B, C, and D leaves the nest, or when A joins the others to form a nest of size 4. See Also - Nest - Dependent variables for Live Mouse Tracker Definition A discrete (state event) variable that is scored when the focal subject stands only on its hindlimbs and raises its head above its body. Two categories are defined: - Rear alone: the subject is not in contact with any other subject. - Rear in contact: the subject rears while in contact with another subject. Calculation EthoVision XT considers the samples when the focal subject's nose point is at least 40 mm higher than its tail base. - Rear in contact is scored when rearing overlaps with any event of type Contact scored for the focal subject. - In all other cases, Rear alone is scored. How to Specify Rear - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Rear. - Under Calculate Statistics for, select Rear alone, Rear in contact, or both. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Note Note the differences between Rear in Live Mouse Tracker and Rearing in Behavior Recognition: - Rear in Live Mouse Tracker is detected using 3D data obtained from the depth camera, while Rearing in Behavior Recognition is detected using features of the pose extracted from a series of 2D images. - Rear in Live Mouse Tracker does not distinguish between rearing at the wall and rearing unsupported. - Rear in Live Mouse Tracker works with multiple subjects in the arena, while Rearing in Behavior Recognition only works with one subject at a time. See Also - Setting up Behavior Recognition - Behavior Recognition: Requirements - Analysis of Behaviors Detected with Behavior Recognition - Dependent variables for Live Mouse Tracker Definition A discrete (state event) variable that is scored when the focal subject approaches another subject. The distance between the center points of the two subjects is within two mean body lengths of the approached subject. Social approach does not necessarily lead to contact. Calculation - EthoVision XT finds all the instances of the events Approach between two subjects in the Live Mouse Tracker database. - EthoVision XT calculates the average body length of the approached subject, measured as the distance between the nose-point and the tail-base point, throughout the entire track. - If the distance between the center point of the focal subject is within two times the average body length of the approached subject, Social approach is scored for that sample. How to Specify Social Approach - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Social approach. - Click the Receivers tab. Under Select, choose the subjects that the focal subject approached. If you select two or more subjects, select one of the available options from the list: - All selected subjects: Social approach is scored when the focal subject approached all the subjects selected above simultaneously. For example, when the focal subject approached a group of three cage mates. - Any selected subject: Social approach is scored when the focal subject approached any of the subjects selected above. - Each subject: Social approach is scored when the focal subject approached one of the subjects selected above. The results are displayed for each Receiver. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Notes In the Trial Statistics results table, with the default layout, the results of Social approach are shown per subject (on the rows). The columns vary depending on what you chose in the Receivers tab. - If you chose Each subject, the columns contain the statistics of Social approach directed to specific subjects (for example, Social approach A to D). - If you chose All selected subjects or Any selected subject, a column All of A, B, C, D or Any of A, B, C, D contains cumulative statistics of Social approach when the subject approached all the cage mates simultaneously or approached any of them, respectively, depending on which option you chose. See Also - Approach Rearing Subject - Social Escape - Social > Relative Movement Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Pascal GPU Deprecation Note URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-pascal-gpu-deprecation-note Chapter: EthoVision XT NVIDIA Pascal Architecture No Longer Supported Applies to: EthoVision XT 19 | January 2026 Summary Starting with EthoVision XT 19, NVIDIA Pascal architecture GPUs are no longer supported for deep learning features (body point detection via neural networks, behavior recognition). Standard tracking methods (grayscale, differencing) are not affected but are no longer tested on Pascal hardware. This aligns with NVIDIA's end of Game Ready driver support (October 2025) and CUDA 13.x dropping Pascal support. Affected GPU Models Architecture GPU Series Examples Pascal GeForce GTX 10 series GTX 1060, 1070, 1080, 1080 Ti Pascal Quadro P series Quadro P4000, P5000, P6000 Pascal Tesla P series Tesla P40, P100 Minimum Supported GPU for Deep Learning Architecture Minimum GPU Compute Capability Turing GeForce GTX 1650 / RTX 2060 7.5 Ampere GeForce RTX 3060 8.6 Ada Lovelace GeForce RTX 4060 8.9 Blackwell GeForce RTX 5070 10.0 Driver Requirements and Recommendations - Minimum NVIDIA driver: 591.74 or later - CUDA version: 13.1 or later Warning: Users with Pascal GPUs who require deep learning features should upgrade to an NVIDIA RTX 30 series or newer. For workstation environments, NVIDIA RTX A-series or RTX PRO series cards are recommended. Always use the latest drivers from nvidia.com/drivers. For questions about GPU compatibility, contact Noldus Information Technology support or visit www.noldus.com. Source: EthoVision XT 19 - Pascal GPU Deprecation Note --- ## EthoVision XT 19 - Physical setup of an arena URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-physical-setup-of-an-arena Chapter: EthoVision XT Physical Setup of an Arena Think carefully about the kind of enclosure to use in your experiments. Consider both the background of the arena, as well as its size and position. Location Place the computer and all electrical equipment other than the cameras in a room separate from the test room. Computers and electrical devices produce ultrasound, which may affect the behavior of the subjects. For specific tests, see also the EthoVision XT 19 - Application Manual. See Manuals for details. TIP: Watch the video Set Up Your Test Environment, which you can find in the EthoVision XT video tutorial (Help > Video Tutorial). Background - The animals you are tracking should be able to move freely and naturally. - The background must be fixed in relation to the camera. Make sure you firmly anchor the entire setup when it is completed. If the arena moves, you must update the background image. - The background should be made of non-reflective surfaces. If this is unavoidable (e.g. the water in a Morris water maze) use indirect illumination (e.g. bounce light off the ceiling) and non-reflective surfaces (e.g. black pool sides). For details, see Lighting Setup. - There should be maximum contrast between the background and the animal. For a Morris water maze: - If you use dark animals, color the water with white tempera paint. - If you use white animals, add 300 g of tempera black nontoxic powdered paint to a 45 liter pool. Dimensions of the Arena - The arena should have no 'depth', because the camera can only see in two dimensions. If the animal can move towards or away from the camera, like when climbing on a shelter, its apparent size will vary. This may interfere with subject detection and tracking. - If you want to track animals in a three-dimensional environment like an aquarium, then make sure this is as shallow as possible, or only calculate variables like In zone, not Distance moved or Distance to a zone. For true 3D movement analysis, contact your nearest Noldus office. - The maximum arena size (in pixels) is limited by the image resolution (W x H) of the digital video file you are using, or the resolution of the live camera image set in the Experiment Settings. Your subject must be at least three pixels wide in order for EthoVision XT to distinguish it from system noise. Therefore, the ratio of your maximum subject size to the maximum arena size is given by the limiting resolution (usually H) divided by three. With digital cameras and a vertical resolution of 1024 pixels, this is approximately 300 times the animals' size. In practice the limit is lower, depending on various factors including the animal's contrast with the background. Especially when tracking small insects, for more robust tracking, make sure that the subject is always at least 10–20 pixels large. Maximum Size of the Arena When you have video of resolution L × H (in pixels), and you want to track a subject of l × w (length x width, in mm), check the following: - Calculate the ratio maximum subject size to maximum arena size = H/3. - Calculate the maximum arena size = w × (H/3). If the arena were bigger than that limit, the subject would often be less than three pixels wide and EthoVision XT would not be able to distinguish it from random noise. Maximum Size of Multiple Arenas in One Image If you use multiple arenas, the calculation applies to the total distance across all arenas. For example, if you have four arenas in a square, the maximum width of each one is half what it would be if you had only one arena. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Pixel format and color space URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-pixel-format-and-color-space Chapter: EthoVision XT Pixel Format and Color Space Aim To inform you about the relation between pixel format and color space used to create video. This Topic Applies To - Basler digital cameras. Background - A Pixel format is the format of the image data transmitted by the camera. For example, for monochrome cameras the default pixel format is Mono8. This means that the camera outputs 8 bits of data for each pixel in the image captured by the chip. TIP You find the Pixel format setting in the pylon Viewer software. See Configure the Digital Camera. - A Color space is a specific organization of colors. Selecting a color space in the camera driver software or in EthoVision XT determines the way color information is encoded in the video file. TIP You find the Color space setting in EthoVision XT. See Adjust Camera Settings in EthoVision XT. There is a relation between the pixel format and the color space. When you specify the color space in EthoVision XT, the camera software may automatically change the pixel format. Follow the tables below to find which pixel format is used in your video. This is usually the format that is optimal to convert color into the selected color space. If the Starting Pixel Format Is Mono8 or YUV422 (YUYV) Packed When you set the color space to... Then the pixel format changes to... UYVY YUV422 Packed RGB24 YUV422 (YUYV) Packed RGB32 YUV422 (YUYV) Packed YV12 YUV422 (YUYV) Packed YUY2 YUV422 (YUYV) Packed Y800 Mono8 BYRG Bayer RG8 If the Starting Pixel Format Is YUV422 Packed When you set the color space to... Then the pixel format changes to... UYVY YUV422 Packed RGB24 YUV422 Packed RGB32 YUV422 Packed YV12 YUV422 Packed YUY2 YUV422 (YUYV) Packed Y800 Mono8 BYRG Bayer RG8 If the Starting Pixel Format Is Bayer RG8, Bayer RG12, or Bayer GRG12 Packed When you set the color space to... Then the pixel format changes to... UYVY YUV422 Packed RGB24 Bayer RG8 RGB32 Bayer RG8 YV12 Bayer RG8 YUY2 YUV422 (YUYV) Packed Y800 Mono8 BYRG Bayer RG8 See Also - Adjust Camera Settings in EthoVision XT - Configure the Digital Camera (in pylon Viewer) EthoVision XT and Quality Assurance EthoVision XT offers functionality to support the user in fulfilling quality requirements in in-vivo studies. The Quality Assurance (QA) functions can also be used to help comply with Good Laboratory Practice (GLP) regulations. IMPORTANT It is not possible to open a GLP experiment that was made with EthoVision XT 12 or earlier. If you upgrade, you can leave both versions of EthoVision XT on one computer, to be able to open the old experiments. Quality Assurance Functions - EthoVision XT user management — You can set up the program so that only authorized users are able to take particular actions, and that certain actions such as editing or deleting data are prevented. - EthoVision XT logging — All user actions which can result in changes to the acquired data (for instance altering settings) are logged and every time you leave a part of the program you are prompted to add a comment to the log file. This creates an audit trail suitable for a QA auditor to review. IMPORTANT You need the EthoVision XT Quality Assurance module to use the Quality Assurance functions in EthoVision XT. See Modules of EthoVision XT. Note About GLP GLP (Good Laboratory Practice) is a set of rules for conducting non-clinical laboratory studies that support or are intended to support applications for research or marketing permits for products regulated by the U.S. Food and Drug Administration. These products include animal food additives, medical devices for human use, biological products and human and animal drugs. The principles of and regulations for GLP are described under the Code of Federal Regulations Title 21, Part 58 (CFR21/58). For Europe, the GLP rules have been compiled and adapted by the Organization of Economic Cooperation and Development (OECD). Subparts of the CFR21/58 GLP rules define and describe the following major points: - Organization and personnel. - Facilities. - Equipment. - Testing Facilities Operations. - Test and Control Articles. - Protocol for and Conduct of a Non-clinical Laboratory Study. - Records and Reports. - Disqualification of Testing Facilities. All these items require to be managed in such a way that GLP-compliance is facilitated and ensured. CFR21/11 more specifically describes guidelines for the use of electronic records. IMPORTANT The Quality Assurance functions in EthoVision XT do not actively check that experiments made in EthoVision XT are GLP-compliant. EthoVision XT User Management With EthoVision XT User Management you can: - Prevent non-GLP users from accessing EthoVision XT with the Quality Assurance module installed. - Define which users may access which function in EthoVision XT (for example experiment design, data recording, editing, etc.). How EthoVision XT User Management Works You can define a list of users that can access EthoVision XT. Furthermore, users can have different rights; these rights can only be assigned by a user with User Management rights in EthoVision XT. Initially, after installation, only one user has access to EthoVision XT. Which user this is depends on how EthoVision XT was installed: - EthoVision XT came installed on a computer provided by Noldus Information Technology. - EthoVision XT was installed by the user. EthoVision XT Came Installed on a Computer When you purchased both EthoVision XT and the EthoVision XT computer from Noldus Information Technology, EthoVision XT is already installed on that computer. In that case, a user account EVXT has been created to log on to Windows. This user EVXT, with administrator rights, initially is the only user who can access EthoVision XT on that computer. Choose File > Users. User EVXT has, by default, the following rights: User Management and EthoVision Preferences. Use EVXT to add new users and assign them rights. See Add a User. EthoVision XT Was Installed by User When a user with administrator rights installed EthoVision XT, this user is automatically added to the list of users in the User Management window in EthoVision XT. Also, a user EVXT is automatically added to the list of users. With this standard user EVXT, any administrator can at all times create a user account through which EthoVision XT can be accessed. Next, either the user that installed EthoVision XT or user EVXT can add new users and assign them rights. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Programming Trial Control URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-programming-trial-control Chapter: EthoVision XT The Trial Control Screen Maximum Trial Duration Pane Aim: To define a maximum duration of the trial. This prevents EthoVision XT from waiting indefinitely for the condition to stop the trial to be met. Example: In a novel object test, in the Start-Stop Trial rule you have defined a condition to stop the track when the mouse enters the zone with the familiar object. It may happen that the mouse completely ignores the familiar object and only pays attention to the novel object. To prevent EthoVision from never stopping tracking, set a maximum trial duration. To Access This Option In the Trial Control Settings screen, locate the Maximum Trial Duration pane, right below the Components pane. If you do not see it, click the Show/Hide button on the toolbar and select Maximum trial duration. Notes - Instead of using a Maximum trial duration, you can also define a condition based on time and place it immediately before the Stop track box. However, there are two important differences: - If you use the maximum trial duration, the program counts the time from the start of the trial (indicated by the Start-Stop trial box). A condition placed immediately before the Stop track box considers the time from the start of data recording (indicated by the Start track box). The two starting points may not be the same if you have a condition between Start-Stop trial and Start track that makes data recording start some time later than the trial. - With a multi-arena setup, a maximum trial duration stops the trial (and thus data recording) in all the arenas simultaneously, even when data recording had started at different times. A time condition placed between the Start track and the Stop track box stops data recording in one arena when the condition is met in that arena. This means that you can have data recording stop at different times in different arenas. Example: You set data recording to start when the animal is detected for the first time in its arena using an In zone-based condition. Next, you define a 5-minute Time condition and place it immediately before the Stop track box. If the animals are detected for the first time at different times in different arenas, data recording stops at different times too, because of the 5-minute interval set for all arenas. The trial ends when the recording stops in the last arena. - The Maximum trial duration is not applied when you record video with the option Save video only, track later. You must stop video recording manually. When you track from the resulting video file, the Maximum trial duration is applied. Program Trial Control - If you just want to record data for a specific time, you can do so by setting the maximum trial duration. - If you want to start and stop data recording in relation to a few simple conditions (for example, start recording when the animal is detected in the water maze, and stop when the animal reaches the platform), define the Start/Stop trial rule. - In other cases, see the procedure below. Procedure - Before defining Trial Control in the program, it is helpful to draw your experimental procedure as a flow diagram, where each block represents an action or a condition which, when met, triggers other actions or conditions. The logical order in the example reads from left to right. - From the Setup menu, select Trial Control Settings, select New, enter a name for the new Trial Control Settings or accept the suggested one, and click OK. The default Start/Stop trial rule appears on the screen. - Build the Trial Control sequence outlined in step 1 using the components available. - To define a Condition or an Action, click one of the buttons under Conditions or Actions. Insert the box in the appropriate place in the sequence. - For conditions: see the Conditions section and the detailed overview. - For actions on hardware devices: see the Hardware Devices section. - For actions on Trial Control variables: see the Trial Control Variables section. - To define a set of actions and conditions to be repeated (Sub-rule), under Structures click the button next to Sub-rule. - To define the command that calls a sub-rule, under Structures, click the button next to Reference. Insert the box in the appropriate place in the sequence. - Test the Trial Control sequence. - To apply Trial Control to your trials, before starting data acquisition make sure that the Trial Control Settings are highlighted in blue in the Experiment Explorer. Notes - When you create a new Trial Control element (action, condition, sub-rule or reference) and another of the same type has already been defined in this or other Trial Control Settings, a message appears asking you whether you want to create a new element or make a copy of the existing control. - A Trial Control variable is a variable that you can define to control your trials. For example, a counter variable that is incremented every time a specific event occurs. You can then define conditions and actions based on this variable. - If the experimental protocol is very complex, like in the case of a multiple-day recording session, it is helpful to split the procedure into main blocks; then, for each block specify the basic actions and conditions, and whether the logical sequence should be repeated. This helps you identify the main building blocks of your Trial Control logic, which will translate into Sub-rules. - Important: If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings, the Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. This makes the rule invalid. Redesign your Trial Control rule and connect the arrows between the boxes. - If you choose to record video with EthoVision XT by selecting the option Save video only, track later in the Acquisition screen, Trial Control is applied when you do tracking, not when you record video. To start and stop video recording, do so manually. Example: A trial is to be run for a few days. On day 5 after the start, during the dark phase, an operant conditioning session must be repeated 10 times. On day 6, the same sequence must be carried out just once. Procedures that must be repeated or represent a specific task must be defined as Sub-rules. Sub-rules can be called at specific times or under specific conditions. In the main Start-Stop diagram, draw a block that calls each sub-rule. Conditions A Condition is a statement that EthoVision checks during the trial. When the Condition is met (True), the program evaluates the next Trial Control element (another condition, an action, or a reference to a sub-rule). Examples of conditions: - When the rat reaches the platform, stop tracking. - When the mouse is around the novel object, switch on the light. - When the animal presses the lever, drop a pellet. To Define a Condition - In the Components pane, under Conditions, locate the type of condition you want to define. - Double-click the condition name or click the button next to it. - If the Add a condition window appears, it means that there is at least one condition of the same type in your experiment. You are asked to choose between creating a new condition or re-using an existing one. Choose the option you require and click OK. If this window does not appear, skip this step. - Next to Condition name, type in the name you want to give to the condition, or accept the default name. - Specify the condition properties. - Enter a Comment (optional), then click OK. - Insert the condition box in the sequence. If the condition is complex (for example, stop the trial either if the rat has reached the platform or it has been swimming for 60 seconds), then you must define separate conditions and combine them. Important: If you have inserted Condition boxes based on Activity in your Trial Control rule and then deselect Activity analysis in the Experiment settings, the Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. This makes the rule invalid. Redesign your Trial Control rule and connect the arrows between the boxes. Actions An Action is a command that EthoVision carries out during acquisition and that influences the trial. Examples of actions: - When the animal is detected in the arena, start tracking. This is an example of system actions (start tracking and stop tracking). - When the animal enters the maze's left arm, do C = C+1. This is an example of actions on a Trial Control variable. - When the animal is found on the shelter, drop a pellet. This is an example of actions on hardware devices. - When the animal leaves the shelter, play a sound or present a visual stimulus. Or, when you start tracking, also start ultrasound recording with UltraVox XT. These are examples of actions based on an external command. To Define an Action - In the Components pane, under Actions, locate the type of action you want to define: - Trial Control variable for an action on a Trial Control variable. - The device type name for actions on a hardware device. - External command to start an external program or run a batch file. - Double-click the action name or click the button next to it. - If the Add an action window appears, it means that there is at least one action of the same type in your experiment. You are asked to choose between creating a new action or re-using an existing one. Choose the option you require and click OK. If this window does not appear, skip this step. - Next to Action name, type in the name you want to give to the action, or accept the default name. - Specify the action properties: - For actions on Trial Control variables, see the Trial Control Variables section. - For actions on External commands, see the External Commands section. - For actions on Hardware devices, see the Hardware Devices section. - Enter a Comment (optional), then click OK. - Insert the action box in the sequence. You cannot create additional actions of type Start track and Stop track, nor can you delete the existing ones. Trial Control Variables You can define variables to be temporarily stored during a trial that you can use to influence the control of the experiment. Example 1 - Variable as a marker: The variable Phase has been defined to specify the various phases of a trial (Phase = 1 means Conditioning; 2 = Testing, etc.). The researcher can then program EthoVision to follow specific Trial Control sequences according to the current value of Phase. Example 2 - Variable as a counter: A researcher has defined the variable SR (successful response) to count the number of times the subject responds correctly to a stimulus. To increment the value of SR after a correct response, specify the formula SR = SR+1. To Define a Trial Control Variable - In the Components pane, click the button next to Trial Control variable under Conditions or Actions. Next, click the TC Variables button. - The Trial Control Variables window lists the variables currently in the experiment (including those defined in other Trial Control Settings). To add a new variable, click Add variable. - A new row is appended to the table. Under Name, type in the name you want to give to the variable. Under Initial Value, enter the value of this variable at the start of the trial (default: 0). - Click OK. In the TC-variable action/condition window, define the action or condition you require. Click Cancel if you do not want to create a condition or action based on this variable at this point. - To delete a variable, click the variable name in the Trial Control Variables window and click the Delete variable button. - To rename a variable, click the variable name in the Trial Control Variables window and edit the name. - The variable name cannot contain blank spaces. - The default name of a new Trial Control variable is VarN, where N is a progressive number. Actions on a Trial Control Variable To assign a new value to a variable in Trial Control, define a Variable action in your Trial Control rule. - In the Components pane, under Actions, click the button next to Trial Control variable. - If the Add an action window appears, it means that there is at least one action of the same type in your experiment. You are asked to choose between creating a new action or re-using an existing one. If this window does not appear, skip this step. - Next to Action Name, enter the name of the action (for example, Increment Counter) or accept the default name. - Under Action to perform, select the variable from the list. You can also create the variable by clicking the TC Variables button if you have not yet done so. - Next to the "=" symbol, do one of the following: - To assign the same value of another variable (for example A = B), select the other variable (B) from the second list. - To enter a formula, click the double-arrow button. Select the operator from the list and specify the formula in the second and third lists. For example, A = A + 1. - To assign a random value, select Random from the second list, and enter the Minimum and Maximum limits (only integer numbers 1 up to 999) within which the random value must fall. When you select Random, the Permutation option also appears. - Enter a Comment (optional), then click OK. - Insert the resulting Action box in the Trial Control rule. Random Values and the Permutation Option - When programming Variable ratio schedules, it is a good idea to use the Random option. Define a random variable R that specifies the number of rewards to be provided. Insert the resulting box in a sub-rule. Every time the sub-rule is repeated, the variable R gets a new value. Make sure that the food dispenser is activated as many times as specified by R during that repeat. You can do this by calling a second sub-rule that activates the food dispenser (Action "drop pellet" followed by a time condition that waits for a short time interval like a few seconds). This second sub-rule is repeated as many times as specified by the value of R. - You cannot combine Random with a formula (for example, to compute A = Random+1). The equivalent solution is the following: define first an action B = Random, and then one more action A = B+1. Place the two boxes in sequence. - Select the Permutation option to generate a value in such a way that all n values within the specified range occur once before a value is generated again. For example, if you specify 1 as Minimum and 5 as Maximum (n = 5), the value 1 will be generated only when all five values in the range have been generated in previous repeats of the action. Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - Proximity URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-proximity Chapter: EthoVision XT Definition A discrete (state event) variable with two possible states, In proximity and Not in proximity: - The state is In proximity when the distance between the selected body points of the focal subject (Actor) and the body points of another subject (Receiver) is lower than a user-defined In proximity threshold. - The state is Not in proximity when the distance between the selected body points of the Actor and the body points of another subject Receiver is greater than a user-defined Not in proximity threshold. - The state does not change from the previous sample when the distance stays between the two thresholds. If at least one of two subjects' selected body points is missing for more than three samples, the current Proximity state ends and the remaining missing samples are ignored. Calculation For each sample, the program calculates first the Distance between subjects, then it compares this value with the In proximity and Not in proximity thresholds to establish the state at that sample. How to Specify Proximity - Click the Add button next to Proximity. - In the Proximity tab, enter the In proximity and Not in proximity distance values that specify when the two subjects are considered in proximity to each other. - Under Calculate statistics for, select the state you want to analyze. For example, select In proximity if you want to know how often or how long the subjects were close to each other. Select Not in proximity if you want to analyze when the animals were far from each other. - Click the Body points tab. Select the body points of the focal subject (Actor) you want to use to calculate proximity. If you select two or three points, a drop-down list becomes available. Choose: - All selected points: A state is assigned only when all selected points are in that state relative to the Receiver (In proximity or Not in proximity). If body points are in different states, that sample is not used in analysis. - Any selected point: A state is assigned when at least one selected body point is in that state relative to the Receiver (In proximity or Not in proximity). - Each point: A state is defined for each point of the Actor. Results are displayed for each point separately. - Click the Receivers tab. Here, you specify the other subjects (Receivers). Under Select, choose the subjects you want to calculate the distance from. If you select two or more subjects, select one of the available options from the list: - All selected subjects: A state is assigned only when the Actor is in that state for all selected Receivers (In proximity / Not in proximity). If the Actor is in different states relative to different Receivers (for example, Subject 1 In proximity of Subject 2 and Not in proximity of Subject 3), that sample is not used in analysis. - Any selected subject: A state is assigned when the Actor is in that state for at least one Receiver (In proximity / Not in proximity). - Each subject: A state is assigned to each combination Actor*Receiver. Results are displayed for each Receiver. - Under Body points, select the body points of the Receivers you want to use to define proximity. If you select two or three points, select one of the available options: - All selected points: A state is assigned only when all selected points are in that state relative to the Receiver (In proximity / Not in proximity). If different body points are in different states, the sample is not used in the analysis. - Any selected point: A state is assigned when at least one selected body point is in that state relative to the Receiver (In proximity / Not in proximity). - Each point: A state is defined for each point of the Actor. Results are shown for each point separately. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - If the experiment is set to Only center-point detection or Color marker tracking, the Body points tab is absent. Calculations are based on the center point. - Any selected points: At any sample time, it is possible that the Actor's body points are in different states relative to the body points of the Receiver. For example, the Actor's nose point being In proximity of the Receiver's center point, and the Actor's center point Not in proximity of the Receiver's center point. In such cases when you select Any selected point (steps 4 and 5 above), multiple states can be assigned to that sample. - Any selected subjects: At any sample time, it is possible that the Actor is in different states relative to different Receivers. For example, Subject 1 being In proximity of Subject 2 and Not in proximity of Subject 3. In such cases when you select Any selected subject (step 5 above), multiple states can be assigned to that sample. You can check multiple states occurring at one sample time when exporting the raw data. At a specific sample time, the value of the variable is 1 in more than one column, depending on which subject is in proximity of the Actor. Application Proximity can be used to study the behavioral interactions between individual animals, for instance the effects of individual housing vs. group housing on social behavior of rats (Spruijt et al. 1992. Physiology & Behavior: 747–752), or social isolation as a symptom of schizophrenia (Sams-Dodd, 1995. J. Neurosc. Methods: 157–167). Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Raw Live Mouse Tracker data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-raw-live-mouse-tracker-data Chapter: EthoVision XT Raw Live Mouse Tracker Data Aim: You can use the following variables to analyze basic events in the Live Mouse Tracker datasets. For example, Contact events. Approach Definition and Calculation A discrete (state event) variable that is scored when the focal subject reduces its distance to another subject. Approach is based on the approach events detected by Live Mouse Tracker and imported in EthoVision XT. Approach events occur when: - The speed of the focal subject is greater than the speed of the other subject. - The distance between the two subjects at the sample k-3, that is, three video frames before the current one k, is greater than the distance at the sample k+3, that is, three video frames after the current one k. Detection occurs during data acquisition, therefore outside EthoVision XT, and its settings cannot be modified in EthoVision XT. Contact A discrete (state event) variable that is scored when the focal subject is in contact with another subject. Contact is based on the contact events detected by Live Mouse Tracker and imported in EthoVision XT. Contact events occur when the distance between the detected contours of the animals gets below a fixed threshold. Detection occurs during data acquisition, therefore outside EthoVision XT, and its settings cannot be modified in EthoVision XT. For more information, please see the Live Mouse Tracker documentation. NOTE: The dependent variable Body contact under Social behavior in the Analysis profile won't give results with Live Mouse Tracker data, because Body contact can only be based on EthoVision XT's own track data. Look Look is a state event variable with possible values Look_up and Look_down. - Look_down: The subject's head is pointing downward, for example when sniffing the substrate. - Look_up: The subject's head is pointing upward, for example when rearing at the wall. Rearing Rearing is a discrete (state event) variable with two possible values, Rearing and Not rearing. For how it is calculated, see Rear (you can find this variable under Live Mouse Tracker). The difference between Rearing and Rear is that Rearing includes all rearing events, instead of splitting them into two categories, Rear in contact and Rear alone. Speed Speed is imported into EthoVision XT and shown in the Analysis profile under Raw Live Mouse Tracker data, but it is not used as an output variable. Stop Stop is based on the stop events detected by Live Mouse Tracker and imported in EthoVision XT. Stop events occur when the speed of the subject gets below a fixed threshold (see Live Mouse Tracker > Stop). Detection of stop events occurs during data acquisition, therefore outside EthoVision XT, and its settings cannot be modified in EthoVision XT. TIP: To analyze stop events when the subject is in contact with its cage mates, see Stop under Live Mouse Tracker data. How to Specify Raw Live Mouse Tracker Data - Open an Analysis profile and in the Dependent Variables panel, under Raw Live Mouse Tracker data, click the Add button next to a category. - Under Calculate statistics for, select the options you require. - If the Receivers tab is available, there you can specify which subject the behavior is directed to. Keep all subjects selected for an overview of all the events directed to any individual (A, B, etc.). - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Notes - You can also use raw Live Mouse Tracker data within JavaScript code to create custom analysis variables. For this purpose, use the GetBehaviorEvent function. See Commands and functions for JavaScript variables. - Raw Live Mouse Tracker data are not affected by track smoothing. This is because the data are stored during acquisition, and not calculated after import in EthoVision XT. For example, no matter whether you apply Lowess smoothing, the statistics of Contact do not change. On the contrary, Live Mouse Tracker analysis variables are affected by track smoothing, just like any dependent variable in EthoVision XT. See Also - Dependent variables for Live Mouse Tracker Approach Rearing Subject Definition A discrete (state event) variable that is scored when the focal subject approaches another subject in rearing posture. Calculation This variable combines the variables Social approach and Rear in contact. The state Approach rearing subject is scored when: - The focal subject is approaching the other, that is, the distance between the two shortens, and that distance is shorter than two times the average body length of the approached subject, calculated throughout the entire track. - The speed of the focal subject is higher than that of the approached subject. - The approached subject is in rearing posture, defined as any time that subject's nose point is at least 40 mm higher than its tail base. Rearing in contact occurs within 15 video frames (that is, 0.5 s for video at 30 fps) from the end of the Social approach event. How to Specify Approach Rearing Subject - Open an Analysis profile and in the Dependent Variables panel, under Social, click the Add button next to Approach rearing subject. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. See Also - Social approach - Rear - Live Mouse Tracker Drink Definition A discrete (state event) variable that estimates the time that a subject spent drinking. Drink has two components: - In the water zone: This marks the time that the focal subject is within a circular zone that includes the water source. - Drink: The subject is within a smaller circular zone around the water source with a radius being half the radius as above. In addition, the subject is stopped for more than 2 seconds. Therefore, Drink is a more restrictive criterion to estimate the amount of time that the subject spent drinking. Calculation Drink is essentially a variable like In zone, because it calculates the time that the subject's center point lies within a zone. In this case the zone is a circle that covers the water tank placed at the bottom-right corner of the apparatus. - If the distance between the subject's center point and the center of the circle is less than the zone radius, then In the water zone is scored for that sample. - A smaller zone concentric to the first zone is also considered. If the distance between the subject's center point and the center of the smaller zone is shorter than the zone radius, and if the subject is stopped (see Stop), then Drink is scored for that sample. How to Specify Drink - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Drink. - Under Calculate Statistics for, select In the water zone, Drink or both. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. See Also - Dependent variables for Live Mouse Tracker Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Record digital video URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-record-digital-video Chapter: EthoVision XT Background Digital video requires a lot of storage capacity and always needs to be compressed before it can be stored on a disk medium. In order to compress a video recording you need an encoder, usually a plug-in board, which converts the video signal into a media file on disk at a fraction of the original size. The input signal can either be analog or digital. Prerequisites - If you have analog cameras: EthoVision XT works with the Picolo Alert encoder board. You can use this board not only for live tracking, but also for recording video. See Install Analog Cameras. - If you have digital cameras: - Install GigE cameras - Install USB 3.0 cameras Another possibility is to use the Noldus MediaRecorder software to make digital video files and track from these videos in EthoVision XT (offline tracking). Procedure - Create a new experiment or open an existing one. - In the Experiment Settings, select the camera(s). See Video Source. - In the Arena Settings, calibrate and draw the arena. - In the Acquisition screen, on the right-hand pane select Save video only, track later. With this option you record the live image to a video file without tracking. Select this option especially if your computer is not fast enough to do tracking and recording at the same time. For other options, see Acquire Data in this Help. - To start recording, click the Start Trial button. TIP: Save this experiment as a template (File > Save As). You can then re-use the same settings in a new experiment when you create a new experiment based on an existing experiment. Video File Location Your video files are saved in the Media Files subfolder of your experiment folder. By default in: C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments\[experiment name]\Media Files. Video File Size Roughly speaking, the file size is given by: File size = Bitrate x Duration x Compression ratio Where: - The Bitrate is the product of Frame size x Frame rate (frames per second). - The Duration is the length of the video (in seconds). - The Compression ratio tells how much space is needed to store similar frames that have fewer moving parts, like an empty open field. You can use the following table as a reference for video created with EthoVision XT. Please note that the figures reported are only indicative. There are other factors which influence video file size, such as whether a variable bit rate is used or which color space is used. Also the amount of movement in the video influences file size. The more movement, the larger the resulting video file. Therefore, the size of your video files may well differ from what is reported here, even when using a comparable setup. Resolution, Frame Rate Camera 10 Minutes Video Duration Per GB 1280x1024, 30 fps Basler GigE, monochrome 75–150 MB 1–2 h 1280x1024, 25 fps Basler GigE, color 175 MB < 1 h 2560x1024, 10 fps Basler GigE, color 100–160 MB 1–2 h 720x480, 30 fps Analog cameras, monochrome 60 MB 16 h DanioVision 800x600, 60 fps Basler GigE, monochrome 90–125 MB 1–1.5 h DanioVision 1280x960, 25 fps Basler GigE, monochrome 355 MB < 30 min Main Topics and Tasks - Lighting Conditions - Color Markers - Settings for the Color Camera - Pixel Format and Color Space Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Relative movement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-relative-movement Chapter: EthoVision XT Definition A discrete (state) variable with four possible states: Moving to, Moving from, No relative movement, and No interaction. - The state is Moving to when the focal subject (Actor) is moving towards another subject (Receiver). NOTE: An Actor is the subject listed on the rows in the statistics table, or in the Integrated Visualization at the left side of each chart. Other subjects in the same arena are Receivers. NOTE: The term moving refers to a subject moving faster than a specified minimum velocity. - The state is Moving from when the Actor is moving away from the Receiver. - The state is No relative movement when two subjects are not moving relative to each other. - The state is No interaction when the distance between subjects is great enough that they can be considered as not interacting. Calculation - To calculate the Relative Movement for sample k, the body points of the Actor and the Receiver must be known for sample k and k-1. - The middle point Q is determined on the segment that joins the body points of the Receiver for samples k–1 and k. In this example, A is the body point of the Actor, R of the Receiver. Q is the interpolated position of the Receiver's body point. - The distance between the Actor's body point and Q is calculated for samples: Dk and Dk-1, respectively. - The state of Relative Movement is determined: - If Dk > Dk-1: Moving from - If Dk < Dk-1: Moving to - If Dk = Dk-1: No relative movement - If Dn > Maximum interaction distance (user defined): No interaction - If the velocity of the Actor is lower than the Minimum velocity (user defined): No relative movement From the figure above, one can see that the outcome depends on which animal is considered as Actor and which as Receiver. If the other subject is considered as the Actor, the point Q is defined in the middle of the segment joining the Receiver's points Rk-1 and Rk. Note that Dk is longer than Dk-1. Therefore, this subject, when considered as the Actor, is Moving from the other subject. How to Specify Relative Movement - Click the Add button next to Relative movement. - In the Relative Movement tab: - Next to Maximum interaction distance, enter the distance above which you do not want to consider the subjects as interacting (Default: 50 cm / 16.69 inches). - Next to Minimum velocity, enter the minimum velocity of the Actor for it to be considered as moving from or moving to the other subject. Note that the velocity of other subjects does not count here. - Under Calculate statistics for, select the states you want to consider. By default, all states are selected. - Click the Body points tab. Select the body points of the focal subject (Actor) you want to use to calculate relative movement. If you select two or three points, a drop-down list becomes available. Choose: - All selected points: A state is assigned only when all selected points are in that state relative to the Receiver (moving to / from / no movement / no interaction). If body points are in different states, the state is not assigned to that sample. - Any selected point: A state is assigned when at least one selected body point is in that state relative to the Receiver (moving to / from / no movement / no interaction). See the note below. - Each point: A state is defined for each point of the Actor. Results are shown for each point separately. - Click the Receivers tab. Here, you specify the other subjects (Receivers). Under Select, choose the subjects. If you select two or more subjects, select one of the available options from the list: - All selected subjects: A state is assigned only when the Actor is in that state for all selected Receivers (moving to / from / no movement / no interaction). If the Actor is in different states relative to different subjects (for example, Subject 1 Moving to Subject 2 and Moving from Subject 3), the state is not assigned to that sample. - Any selected subject: A state is assigned when the Actor is in that state for at least one Receiver (moving to / from / no movement / no interaction). - Each subject: A state is assigned to each selected subject as a separate Receiver. Results are shown for each Receiver. Under Body points, select the body points of the subjects selected above. If you select two or three points, select one of the available options: - All selected points: A state is assigned when the Actor is in that state relative to all selected points of the Receivers (moving to / from / no movement / no interaction). If the Actor is in different states relative to different Receiver body points, the state is not assigned to that sample. - Any selected point: A state is assigned when the Actor is in that state relative to at least one selected body point (moving to / from / no movement / no interaction). - Each point: A state is defined for each body point of the Receiver. Results are shown for each Receiver body point separately. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - All / Any selected points: At any sample, body points of one subject can be in different states relative to another subject's point. Consider an example where the center point of Actor A (circles) is moving to Receiver R, while the nose point of A (triangles) is moving from the Receiver. - Selecting All selected points gives no unique state for Relative Movement at sample k. - Selecting Any selected points gives the state Moving to for the center point and Moving from for the nose point at sample k. - Any selected subject: At any sample time, it is possible that the Actor is in different states relative to different Receivers. For example, Subject 1 Moving to Subject 2 and Moving from Subject 3. In such cases when you select Any selected subject, multiple states are assigned to that sample. You can check multiple states being assigned to one sample time when exporting the dependent variable. At a specific sample time, the value of the variable is 1 in more than one column of the export file. In the example above, the columns for Moving to and Moving from will both show 1 in the corresponding sample row. - If your experiment is set to Only center-point detection or Color marker tracking, the body point options are absent. Calculations are based on the center point. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Relative movement (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-relative-movement-continued Chapter: EthoVision XT Application Relative movement can be used to study the effects of individual housing vs. group housing on the social behavior of rats (Spruijt et al. 1992. Physiology & Behavior : 747-752; Hol et al. 1999. Behavioural Brain Research : 91-97), or for studying the behavioral interactions between individually recognized animals. The following examples show the behavior of subject 1 (red dot) relative to subject 2 (green dot). - Moving to - Moving from - No movement (Subject 1's velocity is under the Minimum velocity threshold) - No interaction (Subject 1's distance from Subject 2 is greater than the Maximum interaction distance) Note that the No interaction state is active even when Subject 1's velocity exceeds the threshold, until the distance between the two subjects goes below the Maximum interaction distance. Definition The signed, distance-weighted change in distance between two subjects from one sample to the next. Net weighted movement is weighted by the distance between two subjects. Changes in positions of subjects which are at a large distance from each other have a lower weight, so they can be distinguished from movements at close distance, which have a different biological meaning. Unlike Relative movement, this is a continuous variable (in distance units). The Net weighted movement is positive if the subject (Actor) is getting closer to another subject (Receiver), negative in the other case. Calculation Formula: NWMn = (Dk-1 - Dk) * abs (DSk - DSk-1) / (max (DSk, DSk-1)) Where: - Dk-1, Dk is the distance between the Actor's body point and the interpolated point of the Receiver calculated for two consecutive samples. - DSk-1, DSk is the distance between subjects for two samples. In the example of the first figure in the topic Relative movement, the value of the variable depends on which subject is considered as Actor and which as Receiver. Similarly, Net weighted movement of subject A is positive relative to R. If the other subject was the Actor (see the second figure in the topic), the point Q would be defined for the other subject in the middle of the Rk-1-Rk segment. In that case Dk would be longer than Dk-1, thus Net weighted movement would be negative relative to R. How to Specify Net Weighted Movement - Click the Add button next to Net weighted movement. - In the Net Weighted Movement tab, under Maximum interaction distance, enter the distance above which you do not want to consider the subjects as interacting. (Default: 50 cm/16.69 inches) - Click the Body points tab. Select the body points of the focal subject (Actor) you want to use to calculate net weighted movement. If you select two or three points, results are calculated for each point separately. - Click the Receivers tab. - Under Select, choose the subjects you want to consider as Receivers. - Under Body points, select the body points of the subjects selected above. If you select two or more subjects and points, results are calculated for each combination separately. - Complete the procedure to add the variable. See Calculate statistics: procedure. Notes - Net weighted movement is calculated for all the subjects selected in the Data profile. Each subject displayed on the rows of your result table is considered as Actor. The subjects displayed on the columns are the Receivers. - If your experiment is set to Only center-point detection or Color marker tracking, the body point options are absent. Calculations are based on the center point. Application Net weighted movement can be used as an objective measure for the intensity of approach and avoidance behavior (Spruijt et al. 1992. Physiology & Behavior, 747-752). The advantage of this variable relative to Weighted movement to/from is that it integrates both. This means that you can analyze, for instance, the movement of subjects regardless of the direction towards or away from each other. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Rotation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-rotation Chapter: EthoVision XT Definition This is the number of turns, either clockwise or counterclockwise, of 360° (if not otherwise defined). A rotation can be based on the movement of a body point or on the change in direction of a body axis. Calculation Body Point Rotation The software scores a rotation event when the cumulative turn angle of the chosen body point exceeds the threshold value (default: a complete rotation, that is, 360°). Consider the simplified example in the figure below. Left: the original track, starting from the sample at time 0. Here we consider the center point but the calculation is the same for the nose-point and the tail-base point. Middle: The turn angles (α) calculated for the body point of samples 1, 2, 3, etc. Right: cumulative turn angle. For details about turn angles, see the dependent variable Turn Angle. At sample 7, the cumulative turn angle exceeds 360°. Therefore, a rotation event is scored. The cumulative turn angle is reset and consecutive turn angles are summed until the cumulative turn angle, again, exceeds the rotation threshold. Body Axis Rotation This method is based on the turn angle formed between the body axis at two consecutive sample times (k-1 and k). As a body axis, you can choose the segment joining the center-point and the nose-point, or the segment between the tail-base and the center-point. The software scores a rotation event when the cumulative turn angle of the chosen body axis α+α+... exceeds the threshold value (default: a complete rotation, that is, 360°). Note that the angles depend only on the orientation of the body axis, not the position of the body center. Note: This rotation method is only available if your experiment is set to Center-point, nose-point and tail-base detection. Which Method Shall I Choose? - Choose Body point rotation if the track clearly shows the rotation movement that you want to quantify. For example, a mouse walking along the walls of a cage, or a fish larva swimming in a well. In that case the trajectory of the center point is sufficient to characterize the behavior. - Choose Body axis rotation if the subject is spinning around its own axis and you want to quantify exactly that behavior. - Choose Body axis rotation if the subject is performing micro-rotations and you do not want to count them. Micro-rotations occur when the subject makes small repetitive movements of the body that cause the center point to rotate, while the subject itself does not walk along a circle. Such rotations are hardly noticeable in the track plots. That could occur for example while a rodent does body grooming. Note that the center point rotates while the body axis does not. If micro-rotations are a problem in your trials and you do not want them included in the results, choose Body axis rotation. - Tip: To eliminate or reduce the detection of micro-rotations when using Body-point rotation, apply a track-smoothing filter based on minimum distance moved. See The Minimal Distance Moved Smoothing Method. - More generally, you can use the Minimum Distance Moved filter to rectify the trajectory of the subject, so that the software ignores the moments when the subject is still or moves little. In this example a MDM of 25 cm was used to make the larger-scale rotations more visible. How to Specify Rotation - Click the Add button next to Rotation. - Under Select, choose one of the two methods Body points rotation or Body axis rotation. If you choose Body axis rotation, select which axis you want to use to count rotation: Axis: Center-point to Nose-point or Axis: Tail-base to Center-point. - Under Settings, select whether EthoVision XT should count rotations in the Clockwise direction or in the Counter-clockwise direction. - In the Count every … rotation list, specify how rotations should be counted. The default value of 1 means that every 360° turn in the specified direction is counted as one rotation. If you select 0.5 in this list, every 180° turn is counted as one rotation. - By entering a threshold angle in the Threshold box, you can compensate for turns in the direction opposite to the one you selected in step 2. Tip: Visualize the rotation events in the Integrated Visualization to validate your choice of the threshold value. - Enter a value of Minimum Distance Moved if you want to remove the samples for which the distance from the last sample selected in the track is too short to represent actual movement. By default this is 2 cm / 0.78 inch. Turn angles and Rotation are re-calculated according to this filter. If you do not want to apply any filter, enter 0. - If you track three body points (center-point, nose-point and tail-base point), and you select Body point rotations, in the Body Points tab select the body points you want to use to calculate the rotations. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. The Role of the Threshold Angle Suppose that in the figure shown at the top of this page the subject makes a counterclockwise turn between sample 2 and sample 3 (α), then it makes a new turn in the clockwise direction (α) before completing a rotation. The threshold angle allows you to compensate for turns in the opposite direction. In this example we are interested in clockwise rotations. Depending on the value of the turn angle α in the counterclockwise direction, one of the following occurs: - The turn angle α is smaller than or equal to the threshold angle. EthoVision XT continues to calculate the cumulative turn angle until it exceeds the corresponding rotation count. A turn in the opposite direction means that the cumulative angle is reduced at that sample. - The turn angle α is larger than the threshold angle. EthoVision XT resets the cumulative turn angle (R in the figure below) and uses a new series of samples to calculate the cumulative turn angle until the latter exceeds the corresponding rotation count. The rationale for applying a threshold angle is that if the animal makes large turns in the opposite direction, the trajectory can no longer be described as a circle-like pattern, and the subject is likely to have changed its behavior. The counting of cumulative turn angle should therefore be reset. Notes - When you apply a Minimum Distance Moved filter, samples are filtered with the Direct method for Minimal Distance Moved. This filter changes the values of turn angle at a specific sample. Consider the following example (movement is from A to B): The filter sets samples C and D equal to B since their distance from B is shorter than the threshold entered. The turn angle for sample E is the angle formed with A and B (=C, D). See Turn Angle. - To count both clockwise and counter-clockwise rotations, repeat the steps from step 1 and specify the alternative option. As a result, you have two instances of the variable Rotation, one for clockwise rotations and the other for counter-clockwise rotations. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Rotation (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-rotation-continued Chapter: EthoVision XT Applications Circling or rotational behavior is used in rats as an indicator of cerebral asymmetry. For example, striatal asymmetries in dopamine characteristics, such as dopamine levels, metabolites, release and uptake, have been functionally related to an increase in rotational behavior (e.g., Carlson and Click, 1989; Schirmer et al., 2007). Amphetamine, a dopamine releaser, induces rotations in animals with striatal asymmetries, which can be blocked by haloperidol. The animal usually turns away from the side of higher dopaminergic activity. Social - Distance between subjects - Social Contact - Approach - Proximity - Body Contact - Relative Movement - Net Weighted Movement - Weighted Movement From - Leaving - Weighted Movement To - Following - Side by Side - Train Definition The distance between a body point of a subject and a body point of another subject. Distance is calculated for each Subject (Actor) relative to other subjects (Receivers). Calculation Where DSk is the distance between Actor and Receiver at sample k, Xa,k and Ya,k the X,Y coordinates of the selected body point of the Actor at sample k, and Xr,k and Yr,k the X,Y coordinates of the selected body point of the Receiver at sample k. How to Specify Distance Between Subjects - Click the Add button next to Distance between subjects. - Click the Body points tab and select the body points of the focal subject (Actor) you want to use to calculate distance. - Click the Receivers tab. Here, you specify the other subjects (Receivers). - Under Select, choose the subjects you want to calculate the distance from. - Under Body points, select the body points of the subjects selected above. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes Distance is calculated for each combination of Actor's body points and Receiver's body points. Each row of the result table shows the results for an Actor. For example: the row heading shows Subject 1. The column heading Nose point / Subject 2 / Center point. This can be read as 'the cell contains the distance between the nose point of Subject 1 and the center point of Subject 2'. Applications This parameter forms the basis for the Proximity dependent variable used in studies of social or aggressive behavior. In zebrafish, shoaling behavior is analyzed with Distance between subjects; see Green et al. (2012) J. Neurosc. Methods, 266–271. Social Contact A discrete (state event) variable that is scored when the subject (actor) is near a conspecific (receiver). The actor's nose point is within a specified distance from the receiver's body, and the actor's center-nose vector is oriented toward the receiver's body points by less than the specified angle. Parameters: - Orientation-independent contact distance — Within this distance, contact is scored regardless of the actor's orientation. - Maximum distance — Beyond the orientation-independent distance and up to this value, contact is only scored when the orientation criterion is met. - Maximum orientation angle — The maximum allowed angle between the actor's center-nose vector and the direction toward the receiver's body points. Approach A discrete (state event) variable that is scored when the subject (actor) moves toward a conspecific (receiver) within the specified distance. The angle between the actor's center-nose vector and the receiver's center point is less than specified. The receiver moves at a velocity lower than the specified value. Parameters: - Minimum distance — The minimum distance between actor and receiver for the event to be scored. - Maximum distance — The maximum distance between actor and receiver for the event to be scored. - Maximum orientation angle — The maximum allowed angle between the actor's center-nose vector and the direction toward the receiver. - Maximum velocity of receiver (Advanced) — The receiver must move slower than this value. This distinguishes approach from mutual movement. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Set Up an Experiment - Activity Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-activity-analysis Chapter: EthoVision XT Activity Analysis Aim Activity measures temporal changes in the video image that may have biological meaning. For example, a sudden drop in the levels of activity in an open field may indicate freezing in a fear conditioning experiment. This can be detected automatically by EthoVision XT, based on the amount of temporal change in the gray scale value of each pixel in the arena. Pixels with temporal change in their gray scale value indicate subject movement; no pixel change indicates the subject is completely immobile. Additional examples: - Detect immobility in a Porsolt swim test. When the subject stays still in the cylinder, activity is reduced to a minimal level. - Detect activity of insects flying around a target object. The more insects are flying around the target, the higher the level of activity. Procedure - Choose Setup > Experiment Settings, and under Analysis Options select Activity Analysis. - In the Arena Settings, define the arena. - In the Detection Settings, define the level of significant activity. - Run your trials. During acquisition, you can monitor the level of activity and, if necessary, use this information to adjust the activity settings to better detect the behavior you are interested in. - To analyze activity, in the Analysis Profile choose the variables Activity and Activity State. Notes - Activity analysis is only available when in the Experiment Settings, under Subjects, you select 1 Subject per arena. See Also - Activity and Activity State as Dependent Variables - Fear Conditioning: View Activity State Behavior Recognition Aim To activate the functions Rat Behavior Recognition and Mouse Behavior Recognition. Prerequisites - You have the Rat/Mouse Behavior Recognition module. Procedure - Choose Setup > Experiment Settings. - Under Subjects, choose 1. - Under Tracked Features, select Center-point, nose-point and tail-base detection. - Under Body Point Detection Technique, select Contour-based. - Under Analysis Options, select Behavior Recognition and choose the function Rat Behavior Recognition or Mouse Behavior Recognition. - Select the options that apply (see below). Options - Feeder. Select this if you want to analyze eating behavior at the feeder. In the Arena Settings, you must draw a zone over the feeder. - Drinking Bottle. Select this if you want to detect drinking. In the Arena Settings, you must draw a point over the tip of each drinking bottle spout. - Arena Walls. To have EthoVision XT discriminate between rearing to the walls and rearing unsupported. In the Arena Settings, you must draw a zone over the walls. - Settings (for Mouse Behavior Recognition). When you select Mouse Behavior Recognition, click the Settings button and select the options that apply to your setup: - Select Bedding Present if the cage includes bedding material and you want to detect digging behavior. - Select Food Available if there is food for the mice and you want to detect eating behavior. Next Steps - In the Arena Settings, draw the zones important for behavior recognition. - In the Detection Settings, set a sample rate between 25 and 31 samples per second, and specify the detection settings for Behavior Recognition. - Run your trials. See Also - Behavior Recognition: Requirements - Choose Help > Video Tutorial and watch the tutorial about Behavior Recognition. Trial Control Hardware Aim To set the EthoVision XT experiment to control hardware devices. Prerequisites You must have one of the following interface devices: - The USB-IO box. - The Mini USB-IO box. - The DanioVision DVOC-00xx observation chamber. Procedure - Connect the interface device (USB-IO box, Mini USB-IO box, or DanioVision Observation Chamber) to the EthoVision XT computer. For details and connection schemes, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. - Select Trial Control Hardware and click Settings. --- ## EthoVision XT 19 - Set Up an Experiment - Behavior Recognition: Requirements URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-behavior-recognition-requirements Chapter: EthoVision XT Behavior Recognition: Requirements Species - The Behavior Recognition function has been developed and tested for tracking rats and mice, not other animal species. Number of Arenas - When tracking live: one arena. - When tracking from pre-recorded video files: one to four arenas. Subjects - If you use multiple arenas, the subjects must have similar size. The apparent size of the subjects is specified in the Detection Settings. That size is used for all arenas. - The subject's length (nose to tail base) in the video image must be at least 60 pixels for rats, and 55 pixels for mice. In all cases its length must not exceed half the arena size. - The subject's fur must be of uniform color. Hooded animals like Lister and Long-Evans rats have not been tested with Behavior Recognition. - For rats: the subject must be older than approximately three weeks. In all cases the subject must be able to walk. - In the Detection Settings, make sure that the subject's tail is not detected. To do so, use the erosion filter. See Advanced Detection Settings: Subject Contour. - Behavior detection is much depending on the subject age and size. For Wistar rats of age 3–5 weeks, the behavior size setting can be used about one week; from age 5 weeks on, it may be used two weeks. We advise to create separate Detection Settings for different age classes. Camera and Video - The camera is placed above the subject, and provides a top view of the test setup. - Because video compression introduces artifacts, live video is preferred over pre-recorded video. - Video frame size (video resolution) must be greater than 352 x 288 per arena. - The frame rate of the recorded videos can only be a multiple of the sample rate that you intend to use. For example, for a sample rate of 25 samples per second, the camera/video file frame rate should be 25 or 50 etc. For a sample rate of 30, set the frame rate to 30 or 60. - The video image must not be overexposed. Details of the subject's fur must be visible. - If you use pre-recorded video, compression should be as lossless as possible. Reducing compression by decreasing the GOP size (that is, the number of video frames between two full frames) produces better results than increasing video resolution. Values of GOP size of 10–15 worked well, however the lower the better. Reducing GOP size, however, increases file size. - To check that your video file has artifacts, create a separate experiment with Activity analysis enabled. Set the Activity threshold to a minimum. See Activity Settings. If the video contains artifacts, you should see purple pixels appearing with a regular rhythm. See also Troubleshooting: Behavior Recognition. - Try to avoid evident fish-eye effect (barrel distortion) in the video image, which hampers behavior recognition. If necessary, use a lens with lower distortion. Test Environment - The test setup must be simple, for example a home cage (without bars) or an open field with no objects around. - The animal should not climb on top of objects like a shelter. When the animal climbs on top of an object, it gets closer to the camera, and its apparent size changes significantly. This may bias results. See also Behavior Recognition: Data, Performance and Accuracy. - Lighting must be from the top, not backlighting. Slow changes in lighting in the course of the test are not a problem, but moving spotlights reduce reliability of detection. - Avoid reflections on the walls. Tracking Settings - In the Experiment Settings, you must select Contour-based as Body Point Detection Technique. - In the Detection Settings, the sample rate must be set between 25 and 31 samples per second. Further Recommendations - During acquisition, keep DDS (Detection Determines Speed) selected. - After acquiring data, visualize the detected behaviors in the Integrated Visualization and check whether no gaps between scored behaviors occur. If gaps occur, which are not due to the fact that the subject is not found, they could be the result of video frames not being analyzed due to high processor load. To decrease processor load, lower the video resolution. Also, try not to use Differencing as detection method, and any of the methods named For Occlusions as the tracking method. See Advanced Detection Settings: Method. Behavior Recognition: Data, Performance and Accuracy Data With the Rat/Mouse Behavior Recognition functions, the following behaviors can be automatically detected: digging (only for mice), drinking, eating, grooming, hopping (for mice), jumping (for rats), rearing (unsupported and supported), resting, sniffing, twitching (for rats), and walking. For the definition of those behaviors, see Behavior Recognition. For each video frame, behavior is detected by analyzing a number of frames before and after the current one. - Behavior data are available from the start of the track, to about 13 seconds before the end of the track when using default Trial Control Settings, which has an additional condition for starting the track. - When the Trial Control Settings does not have the special condition mentioned above, behavior is not scored in the first 3 seconds of the track. - When samples are missed or the subject is not found for a maximum of 0.4 seconds, the subject's position and size is interpolated using the adjacent frames. - When samples are missed or the subject is not found for more than 0.4 seconds, or when the subject enters a hidden zone, the behavior detector is reset. This means that behavior is not scored some time before the first missing sample (or before entering the hidden zone) and after the last missing sample (or after exiting the hidden zone). The behavior is set to Unknown. We advise you to adjust the duration of the trial in the Trial Control Settings. For example, set 6 minutes of track duration to get at least 5 minutes of automatically detected behaviors. The first part of the track is scored as Unknown only if you start tracking as soon as the animal is detected in the arena. If your Trial Control rule includes a condition that waits 3 seconds after the animal is detected, then you make sure that behavior is scored from the start of the track. We recommend using the default Trial Control settings. --- ## EthoVision XT 19 - Set Up an Experiment - Color Tab URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-color-tab Chapter: EthoVision XT Color Tab Gamma Human visual perception is typically non-linear. Adding 1 to a dark or bright color would not result in the same increase in perceived brightness. Gamma adjusts the brightness of pixel values to account for this non-linearity. Choose sRGB to take colors as-is. Choose User to fine-tune the color representation and get a color perception that is optimal for you. When the gamma correction value is set to 1, the output pixel brightness is not corrected. A value between 0 and 1 results in increased overall brightness; a value greater than 1 results in decreased overall brightness. Color Adjustment With Color Adjustment you can fine-tune the color perception by adjusting the settings of colors separately. Select Enable, then choose a color from the list and adjust the saturation value. Check the result in the image preview. Address Tab This contains the settings for IP cameras. IP Address Enter the IP address of the IP camera. Port Enter the port number specified for the IP camera (default for Noldus cameras: 554). User Name Enter the user name specified for the IP camera. For details on how to define a user, consult the camera's manual. Password Enter the password specified for the IP camera. For details on how to set a password, see the camera's manual. More Settings For some types of cameras, the More button takes you to additional settings. For example, for GigE cameras, these settings correspond to those accessible through the camera software. See Configure the Digital Camera. The main settings are: - Analog Controls > Gain: Increase the value of Gain Raw to increase light intensity. Note that this also increases background noise. - AOI Controls > Resolution: See the Format tab for this setting. - Acquisition Controls: - Exposure Time: Increase the value of Exposure Time to get a brighter image. However, a long Exposure Time may conflict with other settings, in particular frame rate. See Configure the Digital Camera. - Acquisition Frame Rate: See the Format tab for this setting. Notes - For digital GigE or USB 3.0 cameras, all settings are available in the camera software. See Configure the Digital Camera. - When you adjust the camera settings in EthoVision XT, the settings are sent back to the camera once you re-open the experiment. - The camera settings are saved at the experiment level, so you can create two EthoVision XT experiments with different camera frame rates, exposure levels, and so on. See Also - Configure the Digital Camera - Check That the Camera Is Set Up Properly Check That the Camera Is Set Up Properly Aim If a digital camera is not set up properly, you will get dropped video frames which results in either Missed Samples or Interpolated Samples in EthoVision XT. Prerequisites - You have followed the steps in Camera Installation to connect and configure the camera. - You have created an experiment in EthoVision XT. - You have made the Arena Settings. This step is necessary to open the Detection Settings. Procedure - In the EthoVision XT experiment, select Setup > Detection Settings > New. - Make sure that the video window shows the live camera image. - In the Detection Settings pane, under Smoothing, set Dropped Frame Correction to Off. - Locate the Detection Performance pane. - Check the value of Missed Samples. If the percentage of missed samples is low, say less than 1%, then the camera is set up properly. If the percentage is higher, there may be an issue with the camera. - You have a few options: - For GigE cameras: check that the exposure time is not too high for the set frame rate. See Adjust the Camera Exposure Time. - Reduce the video resolution, the frame rate, or both. - The Ethernet board may not be set up properly. See Settings of the Ethernet Board. - See Troubleshooting: Camera. Notes - The value of Subject Not Found is not related to the camera setup. It shows how often the software is not able to find a subject in the arena. If the arena is empty, the value grows to 100%. - Setting Dropped Frame Correction to Off enables you to see if EthoVision XT can cope with the actual camera frame rate without missing samples. - If the camera is set up properly and the number of Missed Samples is still high (for example, greater than 5%), you can set Dropped Frame Correction to On. However, the software will interpolate samples to compensate for the missing video frames. See Dropped Frames Correction. Number of Arenas Aim To specify the number of enclosures (arenas) that you use during a trial. Prerequisites - Your EthoVision XT license includes the Multiple Arenas Module. - You want to track animals in two or more arenas simultaneously. Procedure - Choose Setup > Experiment Settings. - Specify the Number of Arenas in the video image. Notes - Examples of multiple arenas: a well plate with 96 wells; two apparatuses for a novel object recognition test placed one next to the other; four open fields; 4 or 16 PhenoTypers. - It does not matter how many cameras you use. If you use for example four cameras, each pointing to an open field, select 4 as the number of arenas. - With the Base version of EthoVision XT you can track one subject in one arena. With the Multiple Arenas Module you can track in up to 100 arenas simultaneously. - Important: If you want to use more than one arena, first check that no samples are missed during acquisition before deciding to work with live tracking. You can display statistics on missing samples during acquisition, in the Analysis Results and Scoring pane, in the Trial Status tab. --- ## EthoVision XT 19 - Set Up an Experiment - Create an Experiment from a Predefined Template URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-create-an-experiment-from-a-predefined-template Chapter: EthoVision XT Create an Experiment from a Predefined Template Aim To create a new experiment based on standard experimental setups like Morris water maze, Elevated plus maze, DanioVision, PhenoTyper, etc. Procedure - Choose File > New From Template (Ctrl+T), or in the EthoVision XT Startup window, under New experiment, click New from template. - In the Select a template option window, select Apply a predefined template and follow the instructions in the guided setup. - Step 1 - Which video source will you use? - From video file: If you select this option, you can click Browse to select the video file. Optionally, you can also open the video file later. - Live tracking (and saving video files): Select this option and click Sources. In the window that opens, select the video sources for tracking. You can also set up your video source here. If you plan to co-acquire physiological data, select DAQ Co-acquisition. You can only select Live tracking if EthoVision XT detects an encoder board for analog cameras or a digital camera. See Cameras supported by EthoVision XT. - Step 2 - Which subjects will you track? If you select the option Rodents, Fish or Arthropods, select a species from the list. If your species is not in one of these lists, select Other. Based on the subject you select, different arena configurations are available in the next step of the guided setup, a suitable sample rate is selected and the nose-tail detection is made available. - Step 3 - How is the arena configured? - Arena template: Select a type of arena from the list (a picture is shown upon selection). - Zone template: Here you have the choice to select predefined zones for the type of arena you select in the Arena template list. - Number of Arenas: Select the number of arenas in the list. You can only select multiple arenas if you have the Multiple Arenas module. - Rows and columns: If you have multiple arenas, select the layout of the arenas. - Step 4 - How many subjects per arena will you track? You can only select multiple animals if you have the Social Interaction module. This step is skipped for some single-subject configurations like the Morris water maze. - Step 5 - Which features will you track? Select the tracked features. Also select whether the animal is Darker, Brighter or Brighter and darker than the background. The features option is skipped for configurations like the Novel object test, where tracking the nose-point is mandatory, or DanioVision where only the center point is tracked. You can change your selection later in the Experiment Settings. See Tracked features. - Step 6 - Initialize template experiment. This window gives an overview of the selected settings. Click Previous if you want to change settings, otherwise click Finish. - In the New Experiment window, in the Name field, enter a name for your experiment. Select GLP Experiment if you want EthoVision to help you make a Quality Assurance-compliant experiment. - Click Browse and select the location in which you want to store your experiment. Do not select a removable disc, like a USB memory drive. - Click OK. The EthoVision XT Overview window appears. - Next: check the Experiment settings. Notes - Each experiment is stored in a folder with the same name as the experiment. - The default experiment location is the location specified during installation. See File locations. - The pre-defined templates (*.tpl) are stored in C:\ProgramData\Noldus\EthoVision\XT 18\Templates. Do not move or delete those files. - For experiments with one or two subjects per arena, you can select to use Deep learning to detect the nose and tail base of your subjects. Note that Deep learning works if a recent graphics card (GPU) is installed on your PC and its driver is up-to-date. See Deep learning: Requirements and More information on graphics cards (GPUs). - If you select DanioVision as arena template, the EthoVision XT interface is adjusted for DanioVision. Unnecessary functions like the Manual Scoring Settings are not available. Detection settings are optimized for detection of zebrafish larvae and the arenas are detected automatically. For more information, see the DanioVision DVOC-0041 - Reference Manual. See Manuals. Create a New Experiment Based on an Existing Experiment Aim To create a new experiment with settings (arena shape, detection settings etc.) imported from an existing experiment. Note that the new experiment will not contain data from the existing experiment. Procedure - Choose File > New From Template (Ctrl+T), or in the EthoVision Startup window, under New experiment, click New from template. - In the Select a template option window, click Use a custom template. - Browse to the experiment folder of the existing experiment, click the experiment file (*.evxt) and click Open. - In the Name field, enter a name for your experiment. Select GLP Experiment if you want EthoVision to help you make a Quality Assurance-compliant experiment. See EthoVision XT and Quality Assurance. - Browse to the location in which you want to store your experiment, then click OK. The default location is the location that you specified during installation. - The EthoVision XT Overview window appears. Click the buttons to check and adjust settings if necessary. Notes - When you create an experiment based on an existing experiment set to Live tracking, the new experiment imports the camera settings from that existing experiment. Check that the camera settings, for example the frame rate and the exposure time, still apply to the new situation. See Adjust camera settings in EthoVision XT. - If you create an experiment based on an existing experiment which used Live tracking and was created on a different computer, you must remake the Video source settings for the new experiment. Protocols on the Web Featuring EthoVision XT Researchers are encouraged to publish test protocols on the internet to improve reproducibility of animal experiments. Browse to https://www.bio-protocol.org/en/searchlist?content=ethovision to find protocols created with or mentioning EthoVision XT. See Also - Your first EthoVision XT experiment --- ## EthoVision XT 19 - Set Up an Experiment - Deep Learning Tracking: Requirements and Recommend URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-deep-learning-tracking-requirements-and-recommend Chapter: EthoVision XT Deep Learning Tracking: Requirements and Recommendations Tracking Mode - When tracking one subject per arena: Live tracking limited to up to four arenas, or from video file. - When tracking two subjects per arena: From video file. Tracking two subjects live using Deep Learning may lead to a high number of missing samples, depending on the power of the GPU. Always test your setup first. If you note a significant number of missing samples (e.g. more than 5%), do not track live. Instead, record video first, then acquire the trial later using Deep Learning. Sample Rate Accuracy of individual discrimination may go down when reducing the sample rate, for example from 25 to 12.5 samples/s. We strongly recommend that you track at the maximum sample rate available, that is, the frame rate of your camera. Choose the sample rate in the Detection Settings. Subject Species, Color, and Size - The neural network has been trained with images of rats and mice of uniform color. - For hooded rats, like Lister and Long-Evans rats: - When tracking one subject per arena: Select Hooded Rats in the Detection Settings. This loads a neural network model specific for those animals. - When tracking two subjects per arena: The neural network for two interacting subjects has not been trained for the fur patterns of hooded rats. If you want to use hooded rats, test pairs of animals before the actual experiments to check that the software produces acceptable results. - The apparent length of the subjects should be at least 10% of the size of the arena. We recommend that the apparent length of the subject's body is at least 120 pixels for rats and 50 pixels for mice (nose to tail base). Number of Subjects and Arenas You can select Deep Learning as the body point detection technique in experiments with: - One subject per arena, in a maximum of four arenas. - Two subjects per arena, in a maximum of four arenas. Important: Always draw an arena in the Arena Settings for optimal results. Video Image - When working with one arena at a time, choose a resolution of 640 x 480 or higher. - When working with two to four arenas, choose a resolution of 1280 x 960 or 1280 x 1024, or similar. - In any case, use video of resolution equal to or higher than PAL/NTSC (PAL: 704 x 576; NTSC/EIA: 640 x 480). A higher resolution is not necessarily better, also considering that it makes tracking slower when tracking offline, or can cause missing samples when tracking live. First try a low resolution, and switch to a higher resolution if the results are not good. - For live tracking, not all video resolutions and frame rates are compatible with Deep Learning. Test results and then click on the camera type for configurations tested with live tracking combined with Deep Learning: GigE cameras, USB 3.0 cameras, and analog cameras. - EthoVision XT converts video to grayscale before feeding it to the neural network. Therefore, both monochrome and color video work fine. Video Length - One subject per arena: No restrictions. Maximum trial duration tested is 72 hours. - Two subjects per arena: We recommend performing trials of at least five minutes. Maximum trial duration tested is 1 hour. During trials, the two subjects should be separated for at least three minutes. If the subjects are in contact for most of the trial duration, individual recognition may fail. Also consider that with two-subject tracking: - EthoVision XT saves additional files during acquisition, which increase the storage space needed on your PC. A 1-hour video produces 10 MB of additional files. - With long trials, the marker could change or droppings would likely accumulate in the arena. Both factors could potentially interfere with marker recognition. --- ## EthoVision XT 19 - Set Up an Experiment - Deep Learning: Basics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-deep-learning-basics Chapter: EthoVision XT Deep Learning: Basics Background Information NOTE: The following information only applies to tracking of rodents when using the Deep learning function. See also Adjust the Settings for Nose-Tail Base Detection (Deep Learning). Deep learning is a type of machine learning. While machine learning is a general category that encompasses all sorts of mathematical tools that help a computer learn by experience, deep learning refers to the use of deep neural networks, where "deep" indicates that the networks are made of multiple, hidden layers of neurons or decision nodes. In a deep neural network, intermediate layers are placed between the input layer, which receives the data (for example the RGB values of the pixels that make up a bitmap picture), and the output layer, which represents the categories of classification; for example, when classifying a picture, "the picture is of a cat" or "the picture is not of a cat". Deep Learning In EthoVision XT A deep neural network can find structures in unstructured data, like pictures and video images. They can recognize recurring patterns, such as the eyes of humans in a number of portraits, and relationships between those patterns. Because of the layered structure of decision nodes, deep neural networks can learn to represent data at various levels, from low levels such as edges, colors and curves, to higher levels such as semicircles (a combination of a curve and a straight edge), squares (a combination of straight edges), up to even higher, more abstract levels (concepts), such as "handwriting", "dark object", "a tail" and so on. EthoVision XT uses a trained network, that is, the network has learned to extract features from a number of video images of rodents of various colors and in various backgrounds, where the nose and the tail-base were previously annotated. During tracking, the network analyzes a portion of the image that includes the detected subject. It creates a map of probability of occurrence for both the nose and the tail-base points, and finally makes an estimate of the position of the nose point and the tail-base point based on the highest probability. With deep learning, the detection of the body points is less dependent on the detected contour of the subject. You can see this effect in cases with low contrast between the subject and the background. For example, a dark mouse is only partly detected when it rears with the forepaws placed on the cage wall; however, the neural network can still find the nose point. Convolutional Networks EthoVision XT uses a deep Convolutional Neural Network (CNN) to find the nose and tail-base points in each sampled video image. CNNs are particularly suitable to classify images based on spatial relationships. CNNs resemble the structures of the cells in the visual cortex of our brain. The visual cortex has small regions of cells that are sensitive to specific regions of the visual field. Hubel and Wiesel (Journal of Physiology 165: 559–568, 1963) showed that some neurons fired only in the presence of edges of a certain orientation. Some neurons fired when exposed to vertical edges and some when shown horizontal or diagonal edges. The basis of convolutional networks is the idea that specialized components in the network have specific tasks, that is, to look for specific characteristics in the image. Features Detected With Deep Learning When you track subjects with deep learning, the main features of the subjects, for example the body center point, are calculated in different ways — either predicted by the neural network or calculated based on the contour of the detected subject. When tracking multiple subjects with deep learning, some of those features are not calculated at all. One Subject Per Arena - Center-point: calculated from contour - Nose-point: calculated using deep learning - Tail-base point: calculated using deep learning - Body elongation: calculated from contour - Body area: calculated from contour - Body changed area: calculated from contour - Head direction line: calculated from contour and nose-point - Body elongation is used to calculate the dependent variable Body Elongation and Body Elongation State. - Body area and Body changed area are used to calculate Mobility and Mobility State. - The Head direction line is used to calculate Head Direction and Head Directed to Zone. Two Subjects Per Arena - Center-point: calculated using deep learning - Nose-point: calculated using deep learning - Tail-base point: calculated using deep learning - Body elongation: not calculated - Body area: not calculated - Body changed area: not calculated - Head direction line: not calculated Deep Learning: Requirements Main Topics - Graphics card (GPU) - Video source - Sample rate - Subject species, color and size - Number of subjects and arenas - Video image - Video length - Individual marking (for two-subject tracking) - Test apparatus and background - Recording protocol - Behavior Recognition - Test results Graphics Card (GPU) Neural networks make calculations over huge data matrices, and therefore require substantial computation power. In order for the deep learning tracking technique to work in EthoVision XT, you need a Graphics Processing Unit (GPU, or graphics card) that is able to sustain those computations. Deep learning makes use of the TensorRT software development kit (version 8.6.1.6), which is built on the cuDNN deep neural network library, which in turn relies on the CUDA computing platform. For this reason, the GPU driver must support CUDA runtime version 12.2. - More information on graphics cards (GPUs) - Install a graphics card for deep learning Video Source --- ## EthoVision XT 19 - Set Up an Experiment - Experiment Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-experiment-settings Chapter: EthoVision XT Experiment Settings To access the Experiment Settings, in the EthoVision XT Overview window, click Experiment Settings, or choose Setup > Experiment Settings. In the Experiment Settings, specify those aspects of your experiment that remain constant during the entire course of the experiment. - Experiment information - Video source - Enable DAQ co-acquisition of external data - Number of arenas - Subjects per arena - Tracked features - Body point detection technique - Analysis options: Activity analysis and Behavior Recognition - Trial control hardware - Units See Also - Select multiple cameras - Adjust camera settings in EthoVision XT - More about Experiment Settings Experiment Information Experiment Mode The mode depends on your EthoVision XT license and the options you choose while creating a new experiment. The mode can be: - Standard if you created an experiment, without selecting the DanioVision experiment, or GLP experiment option. - DanioVision if you selected DanioVision experiment while you created a new experiment, or created an experiment using a DanioVision template. Manual Scoring Settings are not available and the Arena Settings and Detection Settings are optimized for zebrafish larvae in well plates. - Standard GLP if you selected GLP experiment while you created a new experiment. This option is only available if you have the Quality Assurance Module. See EthoVision XT and Quality Assurance. - DanioVision GLP if you create a new experiment and select both options DanioVision experiment and GLP experiment. The experiment is set up for Quality Assurance and optimized for DanioVision. Important: Once you created an experiment, the mode cannot be changed. Create a new default experiment if you want to change the mode. For details about setting up a DanioVision experiment, see the DanioVision DVOC-0041 - Reference Manual. See Manuals. Location The location where your experiment is stored on your computer. The default location is (unless it changed during installation or in the Preferences): C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments. To change the default location for experiments, choose File > Preferences. Description Enter information about your experiment such as the kind of test that you perform, the scientific research question that you aim to answer with this study, etc. To edit the description, use Unicode characters in the Basic Multilingual Plane range. You can enter up to 255 characters. See http://en.wikipedia.org/wiki/Plane_(Unicode)#Basic_Multilingual_Plane. Video Source From Video File Select this option if you track from video files acquired with software other than EthoVision XT, for example MediaRecorder. For the list of compatible video formats, see Video File Formats. Live Tracking Select this option to acquire data live from the camera image. Important: If you work with Basler digital cameras, close the camera software Pylon Viewer before operating the camera in EthoVision XT. One Digital Camera Connect the camera to the Ethernet port of the PC. Click the Refresh button. Select 1 from the list next to Number of Sources and select the camera from the list under Source. Tip: For how to install and connect digital GigE Vision cameras, watch the video tutorial Set Up the Cameras. To open the tutorial, choose Help > Video Tutorial. Multiple Digital Cameras - See Select Multiple Cameras. One Analog Camera Connect your camera to the encoder board. Select 1 from the list next to Number of Sources and select the correct input from the list under Source. Multiple Analog Cameras - See Select Multiple Cameras. Notes - Important: You cannot use a combination of analog and digital cameras. Always use the same type of camera in one experiment. - You can use 1, 2, 3, 4, 8, 12, or 16 cameras simultaneously. Using for example 5 cameras is not supported. - When you use analog cameras, you need an encoder board. See Install Analog Cameras and Connect Analog Cameras to the Computer. - If you mix the image from multiple cameras with a hardware video mixer, follow the procedure for one analog camera. - The quality of the camera image can only be adjusted prior to acquisition. For details, see Adjust Camera Settings in EthoVision XT. See Also - Cameras Supported by EthoVision XT - Check That the Camera Is Set Up Properly - Install GigE Cameras and Install USB 3.0 Cameras - Install Analog Cameras Enable DAQ Co-Acquisition Aim To co-acquire external data with a separate Data AcQuisition (DAQ) system. You can co-acquire, for example, physiological data while you track the subjects. Prerequisites - Under Video Source in the Experiment Settings, you have selected Live Tracking. - You have the External Data module. Procedure - Choose Setup > Experiment Settings. - Under Video Source select Live Tracking. - Select Enable DAQ Co-Acquisition. - For the complete procedure, see Enable DAQ Co-Acquisition in EthoVision XT. See Also - External Data --- ## EthoVision XT 19 - Set Up an Experiment - Hardware Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-hardware-setup Chapter: EthoVision XT Hardware Setup - Depending on which device is connected to the EthoVision XT computer, select either Noldus USB-IO box or Noldus Mini USB-IO box, or the DanioVision version you have. Next, click OK. - If you have connected multiple USB-IO boxes, in the window that appears, select the interface device from the IO interface list. Otherwise, skip this step. - For each device connected, under Device Type select the port that device is connected to, and under Device ID specify the device name or accept the default name. See some examples below. - If you use multiple USB-IO boxes, repeat steps 4–5 for each USB-IO box. Specify the hardware connected to that box. Examples One Pellet Dispenser Locate the TTL port connected to the Pellet dispenser, and in that row under Device Type select Pellet Dispenser. One Pellet Dispenser And One Lickometer Under Device Type, select Pellet Dispenser next to the TTL port connected to the Pellet dispenser. For Lickometer, select Lickometer next to the SDI port that is connected to the Lickometer. PhenoTyper The connections depend on whether you use PhenoTyper 1 or PhenoTyper 2. For information, see the PhenoTyper 2 - EthoVision XT 19 - Reference Manual. DanioVision The White Light stimulus and the Tapping stimulus (when present) are already assigned. For the Temperature Control Unit, or custom hardware, under Device Type select the device next to the TTL port you use. Notes - IMPORTANT: If you use multiple Noldus USB-IO boxes, their identity number must be different. You can set this number using the jumpers inside the USB-IO box. For details, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. We recommend testing your own configuration of USB-IO boxes and devices before carrying out the actual trials. - You cannot combine the regular Noldus USB-IO Box with the Noldus Mini USB-IO Box. - To see what type of USB-IO box you have, check the label at the bottom side of the box: PTIO-002x for the Noldus USB-IO Box or PTIO-003x for the Noldus Mini USB-IO Box. See Also - For details on how to connect hardware devices, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. - For DanioVision, see the DanioVision DVOC-0041 - EthoVision XT 19 - Reference Manual. - For PhenoTyper, see the PhenoTyper - Reference Manual for general information, and the PhenoTyper - EthoVision XT 19 - Service Manual for details about the Noldus devices that work with PhenoTyper. Units Specify the units for distance, time and rotation. Changing the units does not affect the raw data, only their presentation. You can change the displayed units at any time. Unit Of Distance EthoVision measures the distance between two points in pixels. To convert these to real values you must calibrate your arena. Here, you can choose what unit of distance you prefer: millimeters (mm), centimeters (cm), meters (m) or inches (inch). Unit Of Time Milliseconds (ms), seconds (s), minutes (min) or hours (hr). Unit Of Rotation Degrees (°), radians (rad), gradians (grad) or rotations (rot). Notes - You can change the units after you have acquired tracks. This only affects the presentation; the data are always correct. - Changing the units only affects the present experiment. To change the default units for future experiments, choose File > Preferences, click Default Units and select the units you want. - Settings of units are saved on your computer. If you open another EthoVision XT experiment from a colleague, numbers will be displayed according to your settings, regardless of the settings your colleague used. For example, your colleague tracked an animal moving one inch; on your computer it is shown as 2.54 cm. --- ## EthoVision XT 19 - Set Up an Experiment - Individual Marking for Two-Subject Tracking URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-individual-marking-for-two-subject-tracking Chapter: EthoVision XT Individual Marking for Two-Subject Tracking This section refers to tracking two subjects per arena with Deep Learning (up to four arenas). If you track one subject per arena, you do not need to mark the animals. For successful application of Deep Learning-based discrimination between two individuals, the interacting animals must look different, or be marked. Important: EthoVision XT does not detect differences in the subject's body size. Toe clipping, ear punching, or tagging will not work. Differences in fur color and markings (also on the tail base) are essential for successful individual discrimination with EthoVision XT. For information about non-invasive marking techniques, see Klabukov et al. 2023. Animals 13(22): 3452. Different Fur Color If the two subjects are of different fur color, for example one white and the other brown or black, you do not need to mark them. Tail Marks Tail marks only work if they are close enough to the abdomen of the subject. Only mark one subject, not the other. Make one ring leaving some space between the mark and the abdomen. Note that if the tail mark is too far from the abdomen, individual discrimination will not work. - Advantages: The procedure is painless and easy. - Disadvantages: It may require weekly marking, which could cause stress. Furthermore, droppings left in the arena could be detected as tail marks and affect individual discrimination. This could especially occur in long trials. Shaving Marks You can use a hair trimmer to shave a patch of fur from one of the subjects. The patch must be located along the spine of the subject. If you decide to shave both subjects, they must exhibit different patterns. Such marks generally last one to four weeks, depending on the stage of the hair cycle. - Advantages: The procedure is painless; grooming and manipulation do not remove shaving marks; it may be performed on rodents of all colors. - Disadvantages: The marking is temporary due to hair regrowth; you need to monitor the animals regularly to assess the condition of the mark. In long-term experiments, you need to renew the mark as hair regrows. The marking may also look too irregular, reducing the identification rate. Fur Staining White rodents can be marked with non-toxic dye or felt-tip pens. When using infrared illumination, make sure that the marks are visible under infrared light. Mark only one of the subjects. - Advantages: The procedure is easy and painless, and may be used with rodents of all ages. - Disadvantages: Dyes may fade over time or due to grooming; daily monitoring is needed to assess the condition of the mark; it may be used predominantly on white-furred animals; there is a potential adverse response to solvents and odor. Do not make V-shape markings or separate markings that converge on the back of the subjects, as these could interfere with the detection of the nose point. Bleaching - Advantages: The procedure is painless and bleach marks are not removed during grooming. - Disadvantages: It may only be used on dark-furred rodents. The software will not work optimally if the bleached area is irregular and so large that it breaks the subject's contour. Important: Remove bleach solutions to avoid skin damage. Color Marking Color marks only work when they exhibit different light intensity in grayscale, for example light pink and blue. Different colors may look too similar in grayscale. A safer option is to mark one subject and not the other. For more details about color marking, see Tips for Color Tracking. Marker Location Make sure that the marks are visible in most cases, including when the animal is sitting curled up. Marks on the shoulders that are too small, combined with the effect of direct lighting (which should be avoided in all cases), may cause the marks to disappear within a few frames, making individual recognition unreliable. Size of Marks The mark must be at least 4 x 4 pixels after the arena has been rescaled to 256 x 256. This applies to tail marks and marks on the back of the animal. If in doubt, follow these steps: - Open the video file at zoom level 1:1 (Original Size). - Make a screenshot of the video window. - In a paint program, crop the image to include approximately only the arena. - Rescale the arena to 256 x 256 pixels. For rectangular arenas, rescale so that the longest side is 256 pixels, maintaining the original aspect ratio. - After rescaling, verify that the marker is at least 4 x 4 pixels. Hooded Rats The neural network for two-subject tracking and identification has not been trained with the color patterns of hooded rats, so acceptable results cannot be guaranteed when tracking two hooded rats. Perform tests before the actual experiments to verify that the software provides acceptable results. --- ## EthoVision XT 19 - Set Up an Experiment - Install a Graphics Card for Deep Learning URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-install-a-graphics-card-for-deep-learning Chapter: EthoVision XT Install a Graphics Card for Deep Learning Aim To give general information about the installation of an advanced graphics card (Graphics Processing Unit, or GPU). Note: This topic is not exhaustive and is not focused on a particular graphics card. If you need more details, see the documentation provided by the card's manufacturer. Prerequisites - Space requirements. Ensure that there is enough space around the card in its final position. Other cards could reduce ventilation and cause overheating. If necessary, remove those cards and place them on another slot. Plan additional space for the cables. - The NVIDIA T1000 needs 15.5 cm x 6.9 cm (6.1" x 2.7"). This card occupies one PCIe slot. - The NVIDIA RTX 4060 dual fan needs 24.7 cm x 13 cm x 4.1 cm (9.8" x 5.1" x 1.6"). This card occupies two PCIe slots. - Power requirements. Ensure that the computer has a Power Supply Unit (PSU) that can provide enough power to the graphics card. Some graphics cards need additional power. For example: - The NVIDIA T1000 has a maximum power consumption of 50 W and a suggested PSU of 250 W. - The NVIDIA RTX 4060 dual fan has a maximum power consumption of 115 W and a suggested PSU of 300 W. - Power cables. Make sure your Power Supply Unit has the correct connectors to support the graphics card. Cheap PSUs may offer fewer options and shorter lengths. Check with your motherboard and graphics card documentation to determine which connector types are needed. - The NVIDIA T1000 does not need an additional power supply. - The NVIDIA RTX 4060 needs a power cable with a PCIe 8-pin connector. - A graphics card must support the CUDA software. Check the following page if you have an NVIDIA graphics card: https://developer.nvidia.com/cuda-gpus Procedure Important: Before installation, disconnect the AC main source and place the computer on a stable surface. Discharge your body's static electricity by touching a grounded surface, for example, the computer chassis. Do not install near water or when your hands or body are wet. - Remove the cover/side panel of the computer. - Remove any existing graphics card (if there is one). - Remove one or two adjacent slot brackets. Some graphics cards are double-wide and require removing two slot brackets. - Plug the graphics card into the Primary PCI Express (PCIe) x16 slot on your motherboard. This is often the slot closest to the CPU. Sometimes this slot has a color different from the others (for example, blue instead of black), or has a retention lever on one end. - Most graphics cards need additional power. For this reason they have their own power connector. Connect the 6-pin (or 6+2 pin, or 8 pin) power connector from the PC's power supply to the power connector on the card. Note: The connector and socket on the graphics card have a unique shape and connect one way only. - Put the cover back on your computer and reconnect any cables that you removed earlier. - Install the drivers that come with the card. When possible, choose to activate the automatic update of the drivers. - Restart the computer. Update the Neural Network Model After Installing a New GPU Follow the procedure below if you installed a new GPU and you have used the deep learning-based tracking technique on that computer. Background information: The deep learning trackers use a built and serialized model specific for the GPU. This needs to be rebuilt when a different GPU is used. Do one or both of the following depending on what applies to your situation: - When tracking one subject per arena: Open the folder C:\ProgramData\Noldus\Components\Ethovision\TrackerInterfaceNN\3 (or latest version number). Remove the file modelnn.trt and model_hoodednn.trt. If that does not solve the issue, in Control Panel > Programs and Features remove the component Noldus – Tracker Interface NN – x64 Package – 3. Next, repair EthoVision XT from the installation package (choose Repair in the start screen). - When tracking two subjects per arena: Open the folder C:\ProgramData\Noldus\Components\Ethovision\TrackerInterfaceMST\1. Remove the file model_mstnn.trt. If that does not solve the issue, in Control Panel > Programs and Features remove the component Noldus – Tracker Interface MST – x64 Package – 1. Next, repair EthoVision XT from the installation package (choose Repair in the start screen). Notes - Install the graphics card into the primary PCI Express x16 slot. If you install the graphics card into the secondary slot, your system may not recognize the graphics card and there will be nothing displayed on the monitor. When your PC has more than one PCI Express x16 slot, you can configure the physical location of the primary slot in the motherboard's BIOS. --- ## EthoVision XT 19 - Set Up an Experiment - Manual Scoring Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-manual-scoring-settings Chapter: EthoVision XT Manual Scoring Settings Learn About - Scoring behaviors manually What Do You Want to Do? - Define the behaviors that you want to record manually - Edit the manual scoring settings - Validate the manual scoring settings Scoring Behaviors Manually Aim - To record rodent behaviors that cannot be detected automatically with the Rat and Mouse Behavior Recognition; for example, pouncing or fighting. - To record behaviors in animals other than rodents; for example, thrashing in fish. Note: You can also score behaviors after acquisition, for example to correct scoring errors and add data. See Score Behaviors Manually After Acquisition. Procedure - Define the behaviors that you want to record manually. - Optional: Score behaviors manually during acquisition. You score behaviors and events by pressing a predefined key or clicking an appropriate button on the screen as soon as the behavior or event occurs. Score behaviors manually after acquisition. Note: This is only possible when you have tracked from a video file, or you tracked live and saved video. Notes - Manual scoring settings are not available in a DanioVision experiment. - Manually-scored behaviors are stored in a special Manual Scoring log associated with the track data. - If you record video and track later, you can only record events when you do tracking, not during video recording. - If you are familiar with The Observer XT software, the manual scoring settings in EthoVision XT is a simplified The Observer XT coding scheme. You can export the scored behaviors to The Observer XT for further analysis. See Export Manually-Scored Behaviors. - With the Rat (or Mouse) Behavior Recognition module, EthoVision XT can detect a set of rodent behaviors automatically. See More About Experiment Settings. Define the Behaviors That You Want to Record Manually Prerequisite Think in advance how the different categories of behavior relate to each other. You may for example want to score different types of grooming (Unilateral Stroke, Bilateral Stroke, etc.). Each type will be a behavior; however, these are best organized in a group. If you plan to score behaviors that do not relate to each other (for example Rearing and Drinking), they do not need to be defined in a group. Procedure - Choose Setup > Manual Scoring Settings, or in the Experiment Explorer, click Manual Scoring Settings. - Click the Add Behavior button or press Ctrl+B. The Add Behavior window appears. - Next to Behavior Name, enter the name of the behavioral category you want to score. For example, Follow, or Bite. - Next to Behavior Type, choose the type of behavior. This choice affects how you score the behavior relative to others. See Behavior Types. - If in the previous step you have chosen Mutually-Exclusive, then the Behavior Group list becomes available. Type in the name of the group the behavior belongs to, or, if you have already defined it, select it from the list. If you have chosen Start-Stop or Point Event, the behavior cannot be part of any group, and therefore the Behavior Group list is not available. Go to the next step. - Enter a description (optional) for the behavior. - If you think that the behavior is active at the start of the trial, select the Initially Active option. - Click OK. The behavior is listed in the table, under the group it belongs to. - In the cell under Keys, select the keyboard key that you want to use for scoring that behavior. See Choose the Keys for Coding. Behavior Types Mutually Exclusive The behavior will be part of a group, where one item, when scored, automatically switches off the item currently active. For example, you define a group of two behaviors, Rearing and No Rearing. When the subject shows rearing, score this behavior. Rearing is now active. As the subject stops rearing, score No Rearing. This state is now active, while Rearing is stopped automatically. Within a mutually-exclusive group, only one behavior can be defined as initially active. If one of the behaviors of a Mutually-Exclusive group is already selected as Initially Active and you check the same option in the Add Behavior window for a second behavior, the program asks you whether you want to remove that option for the first behavior. Click Yes to do so. If you click No, you return to the dialog so you can clear the Initially Active option. Start-Stop Scoring that behavior is fully independent of other behaviors. To stop that behavior you must press the Stop key. Point Event With this option you only score a point of time when the behavior occurs. Choose this option when you only want to measure the frequency, not the duration of the behavior. Typical examples of such behaviors are biting and twitching. In the Dependent Variable Plots, a Point Event would look like this: Choose the Keys for Coding - It is not required to use key codes. You can also score events using the mouse. - Choose keys that you can press without taking your eyes off the keyboard (for example A, S, D) rather than keys which are easy to remember. If your scoring settings contain so many behaviors that you cannot remember the keys, it is probably too complex. - For each cell you can enter one key, among those available: a...z, and 0...9. - If your setup includes multiple subjects and arenas, choose a key for each arena-subject-behavior combination. - For Start-Stop behaviors, choose a key to start the behavior and a key to stop it. You can also define the same key for starting and stopping it. - Only the keys available are listed, not those already in use. For Start-Stop behaviors, you can select the same key for both starting and stopping a behavior. --- ## EthoVision XT 19 - Set Up an Experiment - More Information on Graphics Cards (GPUs) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-more-information-on-graphics-cards-gpus Chapter: EthoVision XT More Information on Graphics Cards (GPUs) Aim - To provide information about graphics cards and their software needed to perform video tracking with the Deep Learning technique. - This topic does not apply if you track your subject with the Contour-Based method. NOTE: Technically, the GPU indicates the main processor in the graphics card. The graphics card includes other components such as the video memory (VRAM), the printed circuit board (PCB), a power management unit, the PCIe connectors, and the display connectors. In this topic, GPU is assumed to coincide with the physical board that you install on your PC. GPU Microarchitecture Graphics cards are categorized based on their microarchitecture, also known as generations. To find which microarchitecture category your GPU belongs to, browse to https://en.wikipedia.org/wiki/CUDA. - Under the table Compute Capability, GPU Semiconductors and Nvidia GPU Board Products, locate the name of the GPU in the column GeForce. The name under Micro-architecture tells which generation the GPU belongs to. - In the table Compute Capability (CUDA SDK Support vs. Microarchitecture) you can see whether that GPU generation works with the CUDA SDK version used with EthoVision XT, currently 12.2. GPU Speed When comparing two GPUs for deep learning applications, one of the best indicators is the memory bandwidth, rather than single properties like the GPU memory speed. A GPU's memory bandwidth determines how fast it can move data from and to the memory (VRAM) to the computation cores. Theoretically, the memory bandwidth depends on: - The memory clock speed (in Hz). - The width of the data bus between the card memory and the graphics processor, in bits (also known as memory interface). This is the physical count of bits that may fit along the bus every clock cycle. - The memory type (the so-called memory clock type multiplier). Memory bandwidth is measured in GB/s. For example, a graphics card with bandwidth of 1000 GB/s is expected to perform two times faster than one with 500 GB/s. This is a rough indication of the difference in performance, as real performance may depend on several other factors, including the neural network architecture. If there is no reading from memory at any particular clock cycle, that cycle's worth of bandwidth goes unused and cannot be stored for later use. Because GPUs tend to acquire data in spurts, the usable bandwidth is generally lower than the numerically available bandwidth. Another useful measure is the number of Floating Point Operations per Second (FLOPS). For example: - NVIDIA Quadro P2200: 3.8 TFLOPS (teraFLOPS, equal to 1012 FLOPS). - NVIDIA T1000: 2.5 TFLOPS. - NVIDIA GeForce RTX 4060: 15.1 TFLOPS. For the specifications of graphics cards, see: https://www.techpowerup.com/gpu-specs/ GPUs Tested and Supported The following NVIDIA graphics cards have been successfully tested with Deep Learning-based tracking. TIP: Install the most recent driver version available on the NVIDIA website for your GPU. Desktop NOTE: The GeForce RTX 4060 is a dual-slot GPU, occupying two PCIe slots. There are several versions of this board, with two or three fans. Make sure it can fit in your PC. Both the T1000 and the MSI GeForce 4060 Ventus 2X (dual fan) fit in the Dell Precision 3680 desktop computer. GPU Architecture Memory Bandwidth Driver Version T1000 Turing 4 GB GDDR6 160 GB/s 553.09 GeForce RTX 4060 Lovelace 8 GB GDDR6 272 GB/s 552.22 Laptop NOTE: If you install a new GPU on a computer that you have previously used to acquire data with Deep Learning, you must update the neural network model stored on your computer. See Update the Neural Network Model After Installing a New GPU. GPU Architecture Memory Bandwidth Driver Version RTX 1000 Mobile Lovelace 6 GB GDDR6 192 GB/s 553.09 Performance A few NVIDIA GPUs were tested in an EthoVision XT experiment with four arenas, one subject per arena, using Deep Learning as the body point detection technique. A 5-minute video of resolution 1280 x 1024 at 30 fps was used. The average time taken to acquire one trial was as follows: - Quadro P2200: 4 min 29 s. - T1000: 4 min 24 s. - GeForce RTX 4060 Ventus 2X: 1 min 58 s. Importance of CUDA The driver of the graphics card must support the CUDA component. CUDA is a parallel computing platform and programming model created by NVIDIA that helps speed up applications by using the power of graphics cards. Each graphics card may have its own latest driver version in Windows Update. For the cards specified above, Windows Update installs the needed minimal version. However, other cards may need more recent versions than those available through Windows Update. When a driver version is insufficient for supporting CUDA, EthoVision XT displays the following message in the Experiment Settings: The graphics card driver is outdated or not installed, or the graphics card does not support CUDA. It is recommended to download and install the latest driver from the card's manufacturer. This should make the card work properly with CUDA, provided that the hardware supports that version. To find out whether your NVIDIA graphics card is CUDA-enabled, refer to: https://developer.nvidia.com/cuda-gpus CUDA Version If your GPU is already installed on the PC, follow these steps to find out which version of CUDA is installed: - In Windows Explorer, locate the folder C:\ProgramData\Noldus\Components\Ethovision\TrackerInterfaceNN\[version number]. - In that folder, find the file named CudaReport.txt. - Open this file. The runtime version should give an indication of the version of CUDA currently present on your PC. If you do not see the folder specified above, create an experiment and in the Experiment Settings under Body Point Detection Technique select Deep Learning. Then check the folder again as described in step 1. NOTE: The version of CUDA is not the same as the version of the GPU driver. Which GPU Should I Choose? - Choose a recent NVIDIA GPU of the 1000, 2000, 3000 or 4000 series. However, a very recent GPU or one of a new generation may not be compatible. Contact Noldus if in doubt. - In principle, a graphics card of the Pascal microarchitecture category, with 4 GB memory, 1024 CUDA cores and memory bandwidth up to 140 GB/s represents the minimum specifications. Click one of the links below depending on the camera you use and locate the row with a specific graphics card and DL (Deep Learning) specified in the rightmost column: - GigE cameras - USB 3.0 cameras - Analog cameras - The number of CUDA cores can be a useful indicator of performance when comparing GPUs within the same microarchitecture. However, when comparing cards between generations (e.g. Pascal vs. Turing), the difference in CUDA core count does not reliably predict actual performance. An older card with more CUDA cores may not perform as well as a more recent card with fewer CUDA cores. - Overall, newer generations perform better. For example, an Ampere GPU should perform better than a Turing GPU. - GPUs of the Maxwell generation / 900 series are not supported with EthoVision XT 19. - A more powerful GPU requires more power from the PC. Make sure your PC has enough power to feed the GPU. See the prerequisites in Install a Graphics Card for Deep Learning. - Performance of a graphics card depends not only on its own characteristics but also heavily on the sample rate and resolution chosen in EthoVision XT. See Video Source. See Also - Install a Graphics Card for Deep Learning - Deep Learning: Requirements --- ## EthoVision XT 19 - Set Up an Experiment - Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-notes Chapter: EthoVision XT Notes - For mutually exclusive behaviors, it is always a good idea to define a default behavior that can be scored when the subject does not show any significant behaviors. Choose this behavior as Initially Active. - Names of groups and Start-Stop behaviors are displayed in a gray row. Names of mutually exclusive behaviors are displayed in a white row under the corresponding group name. - Behavior names and group names must be no more than 64 characters long. The characters you use must be Unicode characters in the Basic Multilingual Plane range. See: http://en.wikipedia.org/wiki/Plane_(Unicode)#Basic_Multilingual_Plane - How many behaviors? You can define as many behaviors as you need. However, since the number of available keys is 36, we advise you to limit the number of arena-subject-behavior combinations to 36, so you can assign a keyboard key to a behavior of a specific subject in a specific arena. If you need to define more combinations, do so without assigning a key code. You can score those behaviors by clicking the corresponding button on the acquisition screen. - When you need to score behaviors live, keep the scoring settings as simple as possible, with few behaviors. If you try to score many complex behaviors at once then you may make mistakes. See Also - Score Behaviors Manually - Analyze a Manually Scored Behavior - Export Manually Scored Behaviors to The Observer XT Edit the Manual Scoring Settings Rename a Behavior or Behavior Group Click the name of the behavior or behavior group, make the necessary changes and press Enter. Modify the Key Code Click the cell under Keys for a behavior, and type in the new key code, or select another key. If the new key you want to use is assigned to another behavior, it is not available in the Keys list. Pressing that key on your keyboard makes no change in the selected cell. To delete a key code, click the corresponding cell and press Backspace. Edit the Behavior Properties Double-click the behavior row or right-click and select Edit Behavior. Create a New Behavior Group Create first a behavior that belongs to that group, then from the Behavior Type list select Mutually Exclusive, and in the Behavior Group list enter the name of the new group. Add a Behavior to a Specific Group Right-click the behavior group row and select Add Behavior. Type in a new name. Delete Behaviors and Behavior Groups You can delete a behavior or behavior group only after you have deleted all your trials. Right-click anywhere on the behavior (or behavior group) row, and select Delete Behavior (or Delete Behavior Group). Important: If you delete a behavior group, all behaviors of that group are deleted. Move a Behavior from One Group to Another Double-click a behavior to edit it. In the Edit Behavior window, select the Behavior Group you want to move the behavior to. Edit Manual Scoring Settings After Acquiring Data Choose Setup > Manual Scoring Settings. You can: - Add a new behavior. - Rename an existing behavior or behavior group. - Edit the behavior's description. - Set a behavior as Initially Active. This will not modify your existing data; it will only set that behavior as initially active for the next trial. You cannot: - Delete behaviors, unless they have been added after data acquisition. If you acquire more trials, those new behaviors cannot be deleted. - Rename or change the properties of behaviors in a Quality Assurance experiment. Source: EthoVision XT 19 Help - Set Up an Experiment, Noldus Information Technology --- ## EthoVision XT 19 - Set Up an Experiment - Select Multiple Cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-select-multiple-cameras Chapter: EthoVision XT Select Multiple Cameras Aim To mix the live view of multiple cameras in a picture-by-picture fashion. Important: When you mix video images of many cameras, the resulting resolution per camera image is reduced. Make sure that this resolution is high enough for proper detection and tracking. Prerequisites - For GigE cameras (including PhenoTyper 2), see Using Multiple GigE Cameras, Connect the GigE Camera to the PC, and Assign IP Addresses. - For analog cameras (PhenoTyper 1), see Connect Analog Cameras to the Computer. Multiple Digital Cameras EthoVision XT mixes the camera images in a picture-by-picture fashion. - Connect your cameras. Plug each camera to the port of its Ethernet board. Each camera has its unique link with one of the ports of the Ethernet interface board. If you swap cameras, EthoVision XT won't get the camera image. See Using Multiple GigE Cameras and Assign IP Addresses. - In the Experiment Settings, select the number of cameras from the list next to Number of Sources. - Select the cameras under Source. The camera names will show a number in brackets at the end, which makes it possible to distinguish between the cameras. - Select the Resolution, the Frame Rate, and the Color Space for the first camera. The settings are then applied automatically to the other cameras. See Adjust Camera Settings in EthoVision XT. - Next to Merged Camera View, select the resolution of the merged camera view. This is also the resolution of the video file that EthoVision XT creates if you opt for video recording. - Click the preview icon to get a preview of the merged camera images. Notes - For how to install and connect digital GigE cameras, watch the video tutorial Set Up the Cameras. To open the tutorial, choose Help > Video Tutorial. - The video resolution and frame rate that you set in one experiment is selected automatically in your next experiment. When you create a new experiment, always check that the camera settings are those required for that experiment. See also Configure the Digital Camera. See Also - Connect the GigE Camera to the PC - Using Multiple GigE Cameras - Tested Configurations with GigE Cameras - Check That the Camera Is Set Up Properly Multiple Analog Cameras Note: Mixing images from analog cameras using encoder boards other than the Picolo Alert is not supported. Two or Four Analog Cameras - Connect your cameras to the inputs of your encoder board. See Connect Analog Cameras to the Computer. - Next to Number of Sources, select the correct number of cameras from the list and select the inputs from the list under Source. The resolution and frame rate are selected automatically, dependent on whether you have NTSC or PAL cameras. - Next to Merged Camera View, select the resolution of the mixed image. This is also the resolution of the video file that EthoVision XT creates if you opt for video recording. See Acquire One Trial. - Click the preview icon to get a preview of the merged image. More Than Four Analog Cameras When using more than four analog cameras, we recommend using a hardware video mixer also known as a Quad Processing Unit. See Connect Analog Cameras to the Computer. If you use PhenoTyper 1, see also the PhenoTyper - EthoVision XT - Reference Manual. See Manuals. See Also - Tested Configurations with Analog Cameras - Install Analog Cameras Adjust Camera Settings in EthoVision XT Aim To adjust the settings of your camera within EthoVision XT, for example the video resolution, the frame rate, or the exposure. Important: To improve the quality of the image, always try adjusting the lighting and camera aperture before changing the settings in EthoVision XT. Prerequisites - If you work with Basler digital cameras, before using the camera in EthoVision XT close the camera software Pylon Viewer. To Access the Camera Options - Choose Setup > Experiment Settings, and click the camera button for the camera you require. - Click one of the tabs and adjust the settings (see below): - Format Tab - Image Tab - Camera/General Tab - Color Tab - Address Tab - More Settings Format Tab The Format tab is only available for the first camera. The settings you specify here are also applied to the other cameras. Important: If you change the resolution within an experiment, open the Arena Settings profile and grab the background image. This will update the background image with the new resolution. If the Arena Settings profile is locked, right-click it and select Duplicate. In the new profile you can now grab the background image. Next, use that Arena Settings profile to acquire new trials. Resolution For single arenas and subjects more than a couple of centimeters long, a resolution of 384x288 (analog cameras, PAL) or 320x240 (analog cameras, NTSC) or 640x480 (GigE cameras) is sufficient. For digital cameras: when you reduce the resolution, the field of view also changes. For example, reducing the resolution from 800x600 to 640x480 results in a cropped image. You can compensate for this if your camera is provided with a zoom lens. Another option is to leave the resolution unchanged and use the Binning function, which reduces the size of the image in pixels but does not affect the field of view. If you opt for a higher resolution in GigE cameras, for example 1280x1024, always check that it does not conflict with the frame rate. - The higher the video resolution, the more accurate your tracking. - The higher the video resolution, the larger the resulting video files. If disk space is limiting, use the above-mentioned resolution. - Use a high resolution especially in the following situations. --- ## EthoVision XT 19 - Set Up an Experiment - Settings for Experiments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-settings-for-experiments Chapter: EthoVision XT Settings for Experiments Settings for experiments set to Rat or Mouse Behavior Recognition include this additional condition. Note: To visualize or analyze the portions of the tracks scored as Unknown, select Unknown in the behavior property window in the Analysis profile. Performance When Behavior Recognition is selected and you track live, use maximally one arena. To improve performance and avoid samples being discarded because of the use of too much processor capacity, follow these rules: - As a detection method, use one of the Subtraction methods, not Differencing. - For the nose-tail tracking, try first Rodents / Default, not Rodents / For Occlusions. Use the latter only if the first does not give good results. Accuracy - Rat Behavior Recognition was trained on Sprague Dawley rats and tested on various strains by DeltaPhenomics and Radboud University Nijmegen, The Netherlands. The details of this validation are in the publication listed below. - Mouse Behavior Recognition was trained on C57Bl6 mice, and tested on various models and strains including BalbC, CD1 (white), and TgAD models. The module has been beta tested by four experienced animal behavior specialists at different labs (two in USA, two in Europe). The average recall rate, that is, the fraction of ground truth manually scored behaviors that EthoVision XT recognizes correctly, is 0.70. van Dam, E., J.E. van der Harst, C.J.F. ter Braak, R.A.J. Tegelenbosch, B.M. Spruijt, L.P.J.J. Noldus (2013). An automated system for the recognition of various specific rat behaviours. Journal of Neuroscience Methods 218 (2), 214–224. http://dx.doi.org/10.1016/j.jneumeth.2013.05.012 See Also - Trial Control with Behavior Recognition - Behavior Recognition in the Analysis Profile Live Mouse Tracker: Workflow Background Information - Live Mouse Tracker (https://livemousetracker.org) is a system for prolonged monitoring of mice housed in small groups and in enriched environment. - Tracking and individual recognition is based on a Kinect depth camera and RFID antennas and readers. - You can track up to four subjects (tested). - For the assembling instructions, see https://livemousetracker.org. - EthoVision XT supports data of Live Mouse Tracker version 1.0.3 (October 4, 2022). Prerequisites - You must have the Social Interaction add-on module in your EthoVision XT license. See Upgrade EthoVision XT. Procedure - Assemble the Live Mouse Tracker setup. - Connect all the hardware to the PC. - Collect the data with Live Mouse Tracker. - In EthoVision XT, create an experiment in Live Mouse Tracker mode. Choose File > New Experiment. Select the check box Live Mouse Tracker Experiment. - Import Live Mouse Tracker data. For this you need the Live Mouse Tracker databases and the video files (optional). - In the Analysis profile, choose the dependent variables. See Live Mouse Tracker. - Visualize and analyze the data. Notes - Live Mouse Tracker works with 3D coordinates (x, y, z). While analysis is mostly based on 2D (x, y) coordinates, some dependent variables are also based on the z-coordinates, for example Rear. See Dependent Variables for Live Mouse Tracker. - In the Live Mouse Tracker database, the x and y coordinates are in pixels, while z is in mm. However, EthoVision XT converts pixel coordinates to distance units specified in the Experiment Settings. - In Live Mouse Tracker experiments you can also analyze data using the well-known analysis variables like Velocity and In Zone. However, the following variables will not be available in your Analysis profile because they cannot be calculated with Live Mouse Tracker data: - Head direction and Head Directed to Zone. - Turn angle when it is based on head direction. - Activity and Activity State. - Body elongation and Body Elongation State. - Mobility and Mobility State. - Body contact. - Behavior Recognition (all behaviors). Live Mouse Tracker: Create an Experiment Aim To create an EthoVision XT experiment that is compatible with the Live Mouse Tracker behavioral data acquisition system. Background Information An EthoVision XT experiment set to Live Mouse Tracker is a modified version of a standard, multi-subject, multi-body point experiment, with predefined, permanent settings. The main characteristics are: - In the Experiment Settings, the Video Source is Video File, the Number of Arenas is 1, the Number of Subjects is 4, and under Tracked Features the option Tracker Add-In is selected. We recommend not changing those settings. You can, however, change the settings under Units. - In the Arena Settings, the arena is already calibrated using the scaling factor of Live Mouse Tracker. If you like, you can add zones for analysis beyond the standard readouts of Live Mouse Tracker. - Trial Control Settings, Detection Settings, Acquisition, and Track Editor have been removed because they are not relevant in Live Mouse Tracker. - All analysis functionalities of EthoVision XT are kept. So you can, for example, analyze the tracks obtained with Live Mouse Tracker combined with zones using a Data profile, or combine Live Mouse Tracker readouts with the EthoVision XT analysis variables. For more information about the Live Mouse Tracker acquisition system, see https://livemousetracker.org. Prerequisites - You have collected data using the Live Mouse Tracker acquisition system. - You must have the Social Interaction add-on module in your EthoVision XT license. See Upgrade EthoVision XT. Procedure - Choose File > New. - Enter a name for the experiment. - Select the Live Mouse Tracker Experiment. - Click OK. - Next: Import Live Mouse Tracker data. Notes - You may notice that in all Live Mouse Tracker experiments, when opening the Experiment Settings under Tracked Features, the option Tracker Add-In is selected. This is the correct selection in the experiments made for Live Mouse Tracker. Please leave it as it is. See Also - Live Mouse Tracker: Workflow --- ## EthoVision XT 19 - Set Up an Experiment - Subjects Per Arena URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-subjects-per-arena Chapter: EthoVision XT Subjects Per Arena Aim To specify the number of subjects that are present in each arena during a trial. This setting is valid throughout the experiment, and cannot be changed after you have acquired the first trial. Procedure - Choose Setup > Experiment Settings. - Next to Number of Subjects per Arena, select the number of subjects that are present in each arena simultaneously. If you intend to use the Deep Learning technique for body point detection, you can apply it to one or two subjects per arena. - Under Subject Roles, enter the role of the subjects or accept the default ones (Subject 1, Subject 2, etc.). Subject Roles To modify the subject's role name, right-click a name, select Rename and type in the new name. Enter generic role names; for instance in a Resident-Intruder test with two animals, enter Resident and Intruder, or Mutant and Wild Type. Do not enter the ID of the subjects you are going to test. You can specify the ID of your subjects as an independent variable. If you use the Deep Learning technique to track two subjects in an arena, the software does not know which role belongs to a specific individual. So it may happen that the resident subject is labeled Resident in one trial, and Intruder in another trial. To correct this, open the Track Editor and swap the subjects in the trial where the resident subject is labeled as Intruder. Notes - With the Base version of EthoVision XT you can track one subject per arena. - With the Social Interaction Module, you can track up to 16 subjects per arena. Mind that this is a technical limit; the actual number of subjects that you can track depends on other factors. When using color markers to discriminate between individuals, it may be difficult to discriminate between 16 different color marks depending on the light conditions. - To change the number of subjects per arena after acquisition, either delete the trials or make a copy of the experiment with a different name (File > Save As) and delete all trials. Tracked Features Aim To specify which feature of the subject body is tracked. This choice affects the X,Y coordinates resulting in a track. Procedure - Choose Setup > Experiment Settings. - Under Tracked Features, choose the option that applies to your experiment. Center-Point Detection To track only the geometric center of the subject detected (or the part of its body being detected). For example, in an open field or Morris water maze test. Center-Point, Nose-Point and Tail-Base Detection Tracking the nose-point is essential in, for example, a Novel Object Recognition test or in a Social Interaction test to determine how often and how long your subject touches the object of interest or follows and interacts with the other subject. Also select this option: - When you track two or more rodents per arena, marked with colors. - When you want to use the Behavior Recognition function. Color Marker Tracking (Treat Marker as Center Point) If you choose this option, EthoVision XT will only detect the color marker, and track its geometric center. EthoVision XT won't extract the position of body points and any information about the subject's body posture. Choose this option for social interaction tests where you do not need to track nose and tail base (e.g. color-marked insects or fish). Body Point Detection Technique Aim To choose which technique EthoVision XT uses to detect the nose-point and the tail-base points of your subjects. Prerequisites - In the Experiment Settings, under Tracked Features, you selected Center-point, nose-point and tail-base detection. - The camera must be placed overhead. Procedure - Choose Setup > Experiment Settings. - Under Body Point Detection Technique, choose the option that applies to your experiment. Contour-Based This technique uses foreground/background segmentation based on conventional image processing. The center-point, the nose-point and the tail-base point are derived from the detected body contour. This technique is suitable for any animal with an elongated body and pointed snout, for example rodents, fish, and certain insects. Note: Contour-based is used by default in older EthoVision XT versions. Deep Learning If you choose this option, the nose-point and the tail-base point are detected using a trained neural network. The center-point is detected based on the contour of the detected subject, as described above (except for when there are two subjects in the arena; in that case the center point is also found using the neural network). Important: Deep Learning is currently limited to rodents, and for up to two subjects. If you want to use the Deep Learning technique, consider that there are specific restrictions and hardware requirements. See also: - Deep Learning: Basics - Deep Learning: Requirements Notes - If you chose Center-point as the tracking feature, the center-point is always detected with the Contour-based technique. - You cannot use the Deep Learning technique combined with Behavior Recognition. - When you select Deep Learning, you may see this message: The graphics card driver is outdated or not installed or the graphics card does not support CUDA. It is possible that the graphics card is too old, or the graphics card driver is not up-to-date. See Deep Learning: Requirements. --- ## EthoVision XT 19 - Set Up an Experiment - Test Apparatus and Background URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-test-apparatus-and-background Chapter: EthoVision XT Test Apparatus and Background Test Apparatus EthoVision XT's neural networks have been trained with videos of: - One subject per arena, subjects of uniform color: Open field (regular or with round objects), PhenoTyper (with or without bedding material), Elevated Plus Maze, Three-Chamber Social Approach Cage, Barnes Maze, Fear Conditioning Cage with floor grid, Y-maze (with no objects), and a maze with multiple chambers and openings. - One subject per arena, hooded rats: Open field (regular or with round, rectangular, or triangular objects), PhenoTyper (with or without bedding material), and Elevated Plus Maze. - Two subjects per arena: Open field (with no objects), PhenoTyper (with or without bedding material), and home cage. Size of the Arena - One subject per arena: No particular requirements, but see the Video Image section above. - Two subjects per arena: Small containers reduce the probability that the two animals are separated for sufficient time, which is a necessary condition for success with Deep Learning-based individual recognition. Background - If the animal is small relative to the arena and there is no way to zoom in the camera image, try to improve the contrast with the background, for example by providing more infrared light, in order to compensate for the lower level of spatial detail. - If contrast is too low, increase lighting, open up the lens aperture, or increase the camera gain. - Floor grids are compatible with the Deep Learning detection technique. If necessary, reduce the amount of light to minimize the reflections and shadows caused by the metal bars. - Bedding material can also be used with Deep Learning-based tracking. However, there should be enough contrast with the animals. If a dark individual is frequently going undetected, try increasing the lighting or, if possible, switch to another type of bedding. - Too much bedding or nest material can cause occlusions when the animal digs in it, in which case subject detection and discrimination may not work properly. - For one-subject tracking, the apparatus can contain objects, such as in the Novel Object Recognition test or the Sociability test. Whenever possible, use objects of a color different from the subject's color. - When working with multiple arenas simultaneously, check that there are no blind corners, as these may reduce the detection rate. Corridors and Walls For elevated plus mazes, radial mazes and other apparatuses with corridors, make sure that the walls are not of the same color as the subject. In the following example, an excess of light from one side of the test room makes the top of the walls of this plus maze look white. A white mouse is still detected but when it touches the walls the nose-point and/or the tail-base point are no longer detected. Dim the lights and adjust their orientation to reduce the reflections. When you define the Cutout size in the Detection Settings, try not to include walls and objects in the cutout box, especially if those objects are the same color as the animal. See Adjust the Settings for Nose-Tail Base Detection (Deep Learning). Hole Boards Deep learning-based tracking also performs well in situations of low contrast between the subject and the holes. TIP: Define the target hole as a hidden zone. See Shelters and Other Hidden Zones. Apparatuses with Backlight - One subject per arena: Backlight is compatible but may not be ideal. In one example, the mouse explores a plus maze with an infrared-lit background. When the mouse dips the head below the level of the open arms, the nose is not found. To solve this, place dim lights on the floor. - Two subjects per arena: Backlight is not compatible. Tethered Animals - One subject per arena: When running experiments with tethered animals, the contour of the subjects seen by EthoVision XT is often disrupted by the fiber. The Deep Learning technique may not be able to resolve the position of the nose. Deep Learning has not been tested with tethered animals. Therefore, run a few tests with sample videos to make sure that detection of the nose point is accurate enough. To improve detection of tethered subjects, use the Dilation and Erosion filter options. See an example in Advanced Detection Settings: Subject Contour. - Two subjects per arena: This setup has not been tested thoroughly; therefore applying Deep Learning is not recommended. Recording Protocol - One subject per arena: No particular limitations. - Two subjects per arena: Preferably, tracking should start when both animals are in the arena. The software also works when you release one animal first, then the other. However, for best results, ensure that the second animal is released within up to 30 seconds after the first. - With the Trial Control Settings, you can ensure that the data acquisition starts when both subjects are in the arena. See Start the Trial in the Social Interaction Test. Behavior Recognition It is not yet possible to combine Deep Learning for body point detection and Behavior Recognition for behavior classification in the same experiment. When you select Deep Learning under Body Point Detection Technique in the Experiment Settings, the Behavior Recognition option is grayed out. Test Results Deep Learning was tested with various combinations of PCs, graphics cards and cameras. A high-end workstation is recommended when working with Deep Learning-based tracking. Click the link that applies based on which camera type you have: - GigE cameras - USB 3.0 cameras - Analog cameras In all tests, live tracking and save video were used, with one arena per camera. All tests were based on an open-field experiment with a black mouse and a clearly contrasting gray background. See Also - Cameras Supported by EthoVision XT - System Requirements > Hardware --- ## EthoVision XT 19 - Set Up an Experiment - Video Settings and Camera Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-video-settings-and-camera-configuration Chapter: EthoVision XT Video Settings and Camera Configuration When Three Body Points Are Tracked - When you track the three body points in general. - You work with Behavior Recognition. See Behavior Recognition: Requirements. - You track the subjects with the Deep learning technique. See Deep Learning: Requirements. Frame Rate This is the number of video images per second that are generated by the camera. Note that the frame rate is not the same as the Sample rate, which is the number of images EthoVision XT analyzes per second. - For digital cameras, the frame rate can vary. Common values are 25 and 30. A frame rate higher than 30 is recommended when working with fast-moving animals, or when you want to detect movements like startle responses in fish or rapid turns in flying insects. High frame rates require more processing power. If you select a high frame rate, in some cases you need to lower the video resolution. This window shows a message when that is the case. See the tested configurations in GigE Cameras. - For analog cameras, the frame rate is determined by the TV standard of your camera. Color Space This option is available for digital cameras only. Color space determines how the information about brightness and color is encoded in the video frames that are sent to EthoVision XT. Note that this may impact the maximal frame rate. The optimal color space differs between cameras. See also Pixel Format and Color Space. - For monochrome cameras: Choose Y800. Check the preview image to assess whether the image quality is good. - For color cameras: If the image is black-and-white instead of color and a Moiré pattern appears in the image, try selecting another color space. Normally, the default color space gives a good image quality. If you use a high frame rate or resolution, this reduces the number of animals you can track simultaneously. This also depends on how fast your computer is. In the Detection Settings, in the Detection Performance pane, check the value under Missed Samples to get an indication of the quality of tracking. See also Settings for the Color Camera and Pixel Format and Color Space. Standard This is only available for analog cameras. Select the TV standard of your camera. You can find this in the specifications section of your equipment's manual. It will probably be the standard used in your country. - PAL: In Western Europe, China, Indonesia, and Australia. - NTSC: In United States, Canada, and Japan. Image Tab Brightness, Contrast, and Saturation are only available for analog cameras. Move the slider, click the arrows, or change the number in one of the fields to adjust the settings and check the resulting image. Click the Default button to revert the Image settings to default. The settings on the other tabs will not change. Click the More Settings button to open a window with additional settings. Brightness Be aware that a too dark or too bright image may reduce the quality of video tracking. Brightness is not the same as Exposure; the latter is the period of time when the camera sensor is exposed to light. Contrast This is the difference in brightness or color that makes objects in an image distinguishable. Use this slider to enhance or reduce the contrast in the image. Saturation This is the strength or purity of the color and represents the amount of gray in proportion to the hue. A saturated color is pure, while an unsaturated color has a large percentage of gray. Camera/General Tab Some options are only available for Basler cameras. Center Image When selected, Center Image ensures that the resulting camera image is centered over the sensor when not capturing the largest possible image. We recommend keeping this option selected. See also Center the Camera View. Binning Use Binning when you want to reduce the video size and increase brightness without cropping the video image. When selected, sensor pixels are grouped together to make one image pixel. For example, selecting 2 means that two horizontal and two vertical pixels, thus 4 sensor pixels, make up one image pixel. This increases the sensitivity of the camera but reduces the size of the video image. For example, setting binning to 2 reduces the video size from 800 x 600 to 644 x 513. Note that the image is just smaller, not cropped. - Binning results in a brighter image. Check that detection is still optimal. To reduce brightness, close the aperture ring of the camera lens, or reduce the Exposure time or the Gain. - When you select or deselect Binning, do that for all the cameras in your experiment. Binning should be the same across the cameras. - If you want to reduce the video size and crop the video image, clear the Binning option, keep Center Image selected, and reduce the resolution. - You can also crop the video image when your camera lens is multi-focal (that is, the lens has a zoom ring). Exposure Time Exposure determines the time when the sensor is exposed to light. The higher the value, the brighter the image. Note that if Exposure is too high, the camera may not be able to send images at the required frame rate. In that case, the window shows that the frame rate is too low. Reduce the Exposure, or reduce the frame rate to allow longer time intervals between subsequent video frames. - For zebrafish larvae, enter 4000 or 2000, depending on the video resolution chosen; the smaller the resolution, the shorter the exposure time needed. - For rodents in an open field, a value between 5000 and 20000 is appropriate. - For a mosquito filmed under infrared, a value around 10000 is appropriate. - All else being equal, faster animals require shorter exposure times. If the image becomes too dark due to a short exposure time, increase the Gain. Gain Adjust the Gain to change the amplification level of the signal coming from the camera sensor. A higher value means more sensitivity. Increase the gain to make the picture brighter, for example in dark environments. Be aware that higher Gain may increase noise in the image. Default/More - Click the Default button to change the camera settings back to default. The settings on the other tabs will not change. - Click the More button to open the camera software with additional settings. To operate this software, click the Cancel button in the EthoVision XT Video Settings window first. --- ## EthoVision XT 19 - Set Up an Experiment - Wix Toolset URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-set-up-an-experiment-wix-toolset Chapter: EthoVision XT Wix Toolset Tools to author software installers. - Website: http://wixtoolset.org/ - Organization: .NET Foundation — https://dotnetfoundation.org/ - License: Microsoft Reciprocal License (MS-RL) - All copyright, patent, trademark attribution notices that are present in the installation software are retained by Microsoft. - License details: https://wixtoolset.org/docs/about/#license Set Up an Experiment Main Topics and Tasks - Your first EthoVision XT experiment - Experiment settings - More about Experiment Settings - Manual scoring settings Your First EthoVision XT Experiment Learn About - Important terms - Protocols on the web featuring EthoVision XT What Do You Want to Do? - Create an experiment from a predefined template Notes - You can also create a new experiment based on an existing experiment. To do so, open the existing experiment and choose File > Save as. In the new experiment, delete the existing trials and settings if needed. - Important: When you create experiments, do not move, rename or delete experiment files and folders with Windows Explorer. Instead, always manage your experiments from within EthoVision XT. See File Management. - To create an experiment for Live Mouse Tracker, choose File > New and select the option Live Mouse Tracker experiment. For details, see Live Mouse Tracker: Create an experiment and Live Mouse Tracker: Workflow. - For information on how to conduct EthoVision XT experiments with specific apparatuses, like the Open Field, the Morris Water Maze, the Novel Object Recognition and others, see the EthoVision XT 19 - Application Manual in the Other Documentation folder. Important Terms Experiment In EthoVision XT, the experiment is the container of all information related to an experimental setup. For example, you can create an experiment to collect data of a Morris water maze test, and another experiment for a Porsolt forced swim test. Create an Experiment from a Template (Recommended) You can create an experiment with already predefined settings, for example a circular arena for a Morris water maze. You can create a template experiment in two ways: a) from one of the predefined templates or b) from one of your preexisting experiments. - Create an experiment from a predefined template - Create a new experiment based on an existing experiment If none of the predefined templates applies to your experiment, create an experiment from scratch (see below). Create an Experiment from Scratch You can create a new experiment with no predefined settings. To do so, choose File > New. See Create a new experiment from scratch. DanioVision Experiment A special version of an experiment for tracking zebrafish larvae with DanioVision. For the procedure, see the DanioVision DVOC-0041 - Reference Manual. See Manuals. GLP Experiment This is a special version of an EthoVision XT experiment made for Quality Assurance. Certain actions such as editing or deleting data can only be done by specific users. EthoVision XT logs all user actions which can result in changes to the acquired data, for instance altering settings. It is also possible to leave a comment in the log when a user leaves a part of the program. - EthoVision XT and Quality Assurance Live Mouse Tracker Experiment This is a special version of an EthoVision XT experiment made for importing data from Live Mouse Tracker systems. In a Live Mouse Tracker experiment, some elements are not available, like the Track Editor and the Acquisition module. You cannot acquire data directly. Instead, import the Live Mouse Tracker databases into EthoVision XT. You do not need to draw the arena since that is already defined in the Live Mouse Tracker database. You analyze Live Mouse Tracker data just like any other EthoVision XT experiment. Note: EthoVision XT is based on Live Mouse Tracker version 1.0.3. Trial A trial is a single, uninterrupted data acquisition session. The trial starts when you either click the Start Trial button or press Ctrl+F5. Track A track is the actual data collected by EthoVision XT — a succession of 2D positions of each subject. A track includes additional information such as the subject's apparent size in pixels, and other information. The start of a track may or may not coincide with the start of the trial. This depends on your Trial Control Settings. In most cases, with the default Trial Control Settings, EthoVision XT waits one second after the subject has been detected in the arena. Therefore, depending on when the subject is in view, the track begins some time after the moment that you click the Start Trial button. If you have multiple subjects or multiple arenas in the same video image, each subject produces one track within the trial. --- ## EthoVision XT 19 - Setting Up Your First Experiment URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-setting-up-your-first-experiment Chapter: EthoVision XT Draw the Arena and the Zones Tell EthoVision XT in what region in the video image the subject moves (the arena). If you created a template experiment, the arena has already been drawn in the correct shape. Change the size and/or position of the arena to match it with your video image. To Obtain a Background Image - If you use video cameras for live tracking, before starting EthoVision XT power up and connect the video camera to the PC. - In EthoVision XT, choose Setup > Arena Settings. Open the default Arena Settings 1 or create a new one. If you do tracking from video files, click Browse and open the video file you want to use to draw the arena. - Click Grab. If possible, do so when the arena contains no animals. Calibrating with the Noldus Calibration Card - The Grab Background Image dialog opens automatically when first accessing Arena Settings. You can also open it manually via Arena Settings > Arenas and zones > right-click on Background > Grab Background Image. - Place the Noldus Calibration Card inside the arena, ensuring the black rectangular outline on the card is clearly visible in the camera view. If you are using a dark arena, place a piece of white paper behind the card. - Click Calibrate. In the Calibration dialog that opens, review the result and accept or decline. If the automatic calibration fails, continue with the steps below. To Manually Calibrate and to Draw an Arena - Click 1. Draw Scale to Calibrate in the Arena Settings window. - Draw a line between two points of the arena that are at a known distance from each other. In the window that appears, type in the real world distance between the two points and click OK. Optionally repeat this procedure a few times. - Click 2. Select Shape and Draw Arena in the Arena Settings window. - Click one of the drawing tools and draw the outline of the region of the video image where the animal moves. Make sure that the label Arena points to inside this region. To Draw a Zone A zone is a region within the arena that you may want to use for analysis or for starting/stopping data acquisition. If you created a template experiment, zones are already defined. Change their size and/or position to fit the arena, delete zones or draw new ones. - Click 3. Select Shape and Draw Zones in the Arena Settings window. - Select one of the drawing tools. - Draw the contour of each zone. In this example, the platform in a water maze. - Give the zone a name. - For more details, see Arena Settings in the EthoVision XT Help. - For a DanioVision experiment, see the DanioVision DVOC-0041 - Reference Manual. Control the Start and Stop of Data Acquisition Specify the rules that control the start and stop of data acquisition. Default Settings Choose Setup > Trial Control Settings. Open the default Trial Control Settings 1. - Each experiment has default Trial Control settings to start tracking when the subject is detected in the arena for one second and to stop tracking manually. - If you created a template experiment, the Trial Control settings have been adjusted for that template. For instance, for the Morris water maze experiment, tracking stops either when the animal's center-point has been in the platform zone for more than five seconds, or when the animal has been swimming around for two minutes without finding the platform. To Program the Start of Tracking - In the second box, click Settings. - If you want to start tracking when the animal is in a zone, click Settings, deselect Arena and select that zone. - If necessary, change the criterion to be used (for instance, Frequency instead of Duration). To Program the Stop of Tracking - In the box immediately before Stop track, click Settings. - If you want to stop tracking after a specific time, choose After, and enter the time needed. - The first box, Start Trial marks the moment when you click the Start Trial button. The Start track box marks the time when EthoVision XT starts tracking. - For more complex start-stop rules, like "stop when the subject is on the platform", replace the Time condition with an In zone condition, and specify the platform zone. For more examples, see Trial Control in the EthoVision XT Help. - Make sure that the Trial Control Settings you want to use is selected in the Acquisition settings window before you start your data acquisition. - With the Trial and Hardware Control module, you can control hardware (lights, a pellet dispenser, etc.). For instance, turn on a light when the animal enters its shelter. It also allows you to create routines, for example in conditioning experiments. Detect the Subject - Choose Setup > Detection Settings. Open the default Detection Settings 1. - If you work with video files, under Video click Select Video and choose a video file. Play the video up to when the subject appears. If you work with cameras, release the animal in the arena. - Click Automated Setup. Choose the type of subject you test, and click Next. - Wait until the subject is free from contact with objects or walls and walks with a normal posture. When ready, draw a rectangle around the subject. Do this for all subjects in the arena. - For rodents, try to leave the tail out of the rectangle. In all other cases, include the animal's tail. - If the subject's body is well detected, click Yes. Otherwise, try moving the Finetune slider and check if the yellow blob covers the entire animal's body (excluding the tail). If detection does not improve, try again a few times using another image from the video. If this does not help, click No and click Advanced. For details, see Configure Detection Settings > Advanced Setup in the EthoVision XT Help. Tracking the Nose and Tail-Base - In all cases, make sure that the body of the animal is well detected. - If you use the Deep learning detection technique with one subject per arena, under Method click Define and select a box around the subject. Make sure that there is some space around the subject's body. - Check that the subject is well detected in all parts of the arena. In the Detection Performance pane, check that the proportion of samples where the subject is not found is acceptable (for example less than 1%). - If you selected Activity analysis in the Experiment Settings to detect freezing, click Activity. Adjust the settings until most of the purple pixels only appear when the animal moves. When the animal freezes, the number of purple pixels should be minimized. Source: EthoVision XT 19 - Quick Start Guide --- ## EthoVision XT 19 - Settings and profiles URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-settings-and-profiles Chapter: EthoVision XT Settings and Profiles You can store your favorite options in Settings and Profiles that apply to specific procedures. Settings and profiles are visible in the Experiment Explorer. Except for Experiment Settings and Manual Scoring Settings, you can store multiple settings for different situations, for example different Trial Control settings to acquire trials of different durations. To View the Settings Used in a Trial - Choose Setup > Trial List. - Click the Show/Hide button on the toolbar and select Variables. - Choose the type of settings you want to view. - The settings column is added to your Trial List. For a specific trial, the column shows the name of the settings used to acquire the data. - In the Experiment Explorer, open that settings profile. Profiles that have been used to acquire data are marked with a lock symbol (see below). To Create a New Settings/Profile - Right-click the corresponding folder in the Experiment Explorer and select New. - Type the name for the new profile or accept the suggested name, then press Enter. To Activate Settings/Profiles In the Experiment Explorer, right-click the settings/profile you want to activate and select Set as Current. Active profiles are highlighted in blue in the Experiment Explorer. Activating means that EthoVision XT uses that profile to carry out a procedure. For example, when acquiring the data it uses the Arena Settings active at that moment. When calculating statistics, it uses the active Track Smoothing profile. To Open Settings/Profiles Right-click the settings/profile you require under the corresponding folder in the Experiment Explorer and select Open. Opening settings/profiles also means that those settings/profiles are activated. To Edit Settings/Profiles To edit settings/profiles, open them (see above) and then make the necessary changes. When at least one trial has been carried out, the Arena Settings, Trial Control Settings and Detection Settings used for that trial are locked. Locked settings are marked by a lock symbol in the Experiment Explorer. You cannot edit locked settings. If you want to make changes to those settings, make a copy (see below) and edit this. Then, make sure that you carry out the next trial using the new profile. If you delete all trials acquired with specific settings, those settings are unlocked, so you can edit them. To Copy Settings/Profiles Do one of the following: - Open the settings/profile folder in the Experiment Explorer. Right-click the name of the settings/profile you want to copy and select Duplicate. - From the Setup or Analyze menu, select the type of settings/profile you want to copy. In the window that opens, select Duplicate From. Change the name of the new settings/profile if necessary. Next, select the settings/profile you want to copy from. Result: A new item is added to the folder. Type a new name or accept the suggested one, then press Enter. The suggested name for a new settings/profile is [Settings/Profile] N, where N is the first integer not yet used in the name of the other settings/profiles in that folder. To Rename Settings/Profiles - In the Experiment Explorer, right-click the name of the settings/profile you want to rename and select Rename. - The profile name is highlighted. Type the name you require and press Enter. You cannot rename settings/profiles that were used to acquire at least one trial. To Delete Settings/Profiles In the Experiment Explorer, right-click the name of the settings/profile you want to delete and select Delete. Notes - You cannot delete settings/profiles that were used to acquire at least one trial. To delete those settings/profiles, you must first delete the trials (make sure you do not lose any important data!). - You cannot delete settings/profiles if your experiment is set for Quality Assurance (GLP experiment) and you do not have specific rights. - If the currently-active settings/profile is deleted, the first of the remaining settings/profiles in the folder is activated automatically. - If you delete the only settings/profile in the folder, a new default settings/profile is created automatically. - If you delete a Data profile or an Analysis profile used to create an analysis result open on your screen (track plot or statistics result), the result is updated according to the first available Data profile, or, if no other profiles are available, a newly-created default profile. Import Data Aim: To import data from other programs to analyze tracks and other data combined. What Do You Want to Do? Import track data from other experiments - Import data from other experiments — Tip: Choose this option to merge data from multiple experiments. - Import Live Mouse Tracker data Import other types of data - Import UltraVox XT 3 call data - Import Live Mouse Tracker data - To import data acquired with a separate data acquisition (DAQ) system, see Import External Data in EthoVision XT. For how to create an import profile see Create a New Custom Import Profile. Note: You cannot import track files from one EthoVision XT experiment into another. This means that data which you want to analyze together in EthoVision must be acquired in the same experiment. Procedure - In EthoVision XT, open the Trial List. - Click the Import External Data button. - Under Files of type, select UltraVox XT 3. If you do not see this profile, install it from the UltraVox XT 3 installation package. Open the folder ...Extras\Import profiles, and double-click EthoVision XT 11 and Newer.bat. - Select the *.etx files and click Open. - Drag the data lines from the Import External Data window to the trial, arena, or subject you require. - When ready, click Import. Notes - Data for each call name (or call name*pattern label) is imported and resampled as a separate dependent variable. - For more information on importing and analyzing UltraVox XT call data, and how to control UltraVox XT start and stop data recording, see the UltraVox XT 3 Help. See Also - The import profile for UltraVox XT 3 Export Data Aim: To export EthoVision XT data to other programs to carry out further analysis. What Do You Want to Do? Export data from EthoVision XT - Export the raw data (track and dependent variables) - Export external data - Export manually-scored behaviors - Export Trial Control data Import EthoVision XT data in other applications - Import data into Excel - Import manually scored data into The Observer XT See Also - Export the statistics result Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Shortcuts URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-shortcuts-DuG Chapter: EthoVision XT Shortcuts Keyboard shortcuts are only available when the corresponding menu or window is active. - Windows – General - Experiment Explorer - EthoVision XT – General - Select and Edit - Trial List and Other Grids - Row-Select Grids - Playback Control, Acquisition and Visualization - Arena Settings - Manual Scoring Settings - Trial Control - Detection Settings - Track Editor - Analysis Profiles - Statistics and Charts Windows – General Some of these shortcut keys can also be used in the Experiment Explorer, the Show/Hide menu, the Arena Settings window, the Trial Control window, and the Detection Settings window. - Esc – Cancel action - F1 – Help - F2 – Rename / edit - F3 – Find next - Shift+F3 – Find previous - F4 – Expand pull down list - Ctrl+F4 – Close active window (does not apply to EthoVision XT) - Alt+F4 – Close application - Alt+Enter – Open properties of selected item (e.g. Settings dialog of dependent variable) - Shift+F10 or context menu key – Open context menu of selected item - Alt+Spacebar – Open shortcut menu of selected window - Ctrl+Esc – Display Start menu - Alt+underlined letter – Application: open corresponding main menu; Dialog: carry out corresponding command - F10 – Activate main menu bar - Main menu: down arrow key – Open menu item / cycle through sub-items - Main menu: up arrow key – Open menu item / cycle through sub-items - Main menu: right arrow key – Open sub-items / cycle through items - Main menu: left arrow key – Close sub-items / cycle through items - Spacebar – Select / clear checkbox if active option is a checkbox - Arrow keys – Move / nudge cursor (highlighted item in grid) or selected item - Alt+Tab – Switch between open applications - Alt+Esc – Cycle through applications in order they were opened EthoVision XT – General Shortcuts from the Menu Use the keyboard to activate all the functions in EthoVision XT that are on the menus. Press Alt plus the letter underlined in the menu and then select the desired function by scrolling down to the function or by pressing the underlined letter. For example, to go to Preferences on the File menu, press Alt+F, f. Main Shortcuts - End – Display the bottom of the active window - Home – Display the top of the active window - * (numeric keypad) – Display all subfolders under the selected folder - + (numeric keypad) – Display the contents of the selected folder - - (numeric keypad) – Collapse the selected folder - Left arrow key – Collapse current selection if it is expanded, or select parent folder - Right arrow key – Display current selection if it is collapsed, or select first subfolder - Up arrow key – Previous item - Down arrow key – Next item - Ctrl+N – New default experiment - Ctrl+O – Open (experiment or other file type) - Ctrl+S – Save experiment - Ctrl+Shift+S – Save experiment as… - Ctrl+T – New template experiment Trial List and Other Grids - Ctrl+X – Cut - Ctrl+C – Copy - Ctrl+V – Paste - Ctrl+Delete or Delete – Delete - Ctrl+drag item – Copy selected item - Shift+drag item – Move selected item - Shift+arrow keys – Expand / contract block selection in direction of arrow key - Ctrl+left arrow key – Go to first cell of row - Ctrl+right arrow key – Go to last cell of row - Ctrl+up arrow key – Go to first cell of column - Ctrl+down arrow key – Go to last cell of column - Arrow keys – Move highlight in direction of key - F2 – Rename / edit cell content (see Windows – General) - Tab – Go to next cell in row; if last cell, do nothing - Shift+Tab – Go to previous cell in row; if first cell, do nothing - Enter – Accept entry and go to same column, next row; if last row, go to first cell of last row - Home – Go to the first character within the cell (edit mode, only for user-defined variables) - End – Go to the last character within the cell (edit mode, only for user-defined variables) - Page Up – Go to row minus the number of rows visible in window and highlight same location (and de-select) - Page Down – Go to row plus the number of rows visible in window and highlight same location (and de-select) - Ctrl+Home – Go to first cell of first column - Ctrl+End – Go to last cell of last column - Ctrl+Alt+T – Add trials to the Trial List - Ctrl+Alt+V – Add an independent variable to the Trial List Row-Select Grids An example of a row-select grid is the Components pane in the Data Profile screen and Analysis Profile screen. There you can select rows, not individual cells. Playback Control, Acquisition and Visualization - Ctrl+Alt+L – Add videos to the Trial List - Ctrl+Alt+I – Import external data into the Trial List - Ctrl+Alt+E – Import trials into the Trial List - Up arrow key – Step one row up - Down arrow key – Step one row down - Enter – Open the settings window of the selected row in the Analysis Profile - Ctrl+up arrow key – Jump to begin - Ctrl+down arrow key – Jump to end - Ctrl+left arrow key – Step 1 sample (or frame) backward - Ctrl+right arrow key – Step 1 sample (or frame) forward - Play forward – Play forward at the speed selected. When playing back the tracks, one step forward corresponds to the time interval for the sample rate used for tracking (for example, 0.04 seconds if the sample rate is 25/s). - Play backward – Play backward. When playing back the tracks, one step backward corresponds to the time interval for the sample rate used for tracking. - Pause / stop – Pause or stop playback - Ctrl+. – Zoom x2 (Track Visualization, Heatmaps and variable plots in Integrated Visualization) - Ctrl+, – Zoom x1/2 (Track Visualization, Heatmaps and variable plots in Integrated Visualization) - Ctrl+/ – Fit all (Track Visualization only) - Ctrl+' – Play forward at speed 0.01x (Visualization only). Note: This is the key to the left of the return key on the international keyboard. - Play forward at speed 0.04x – Visualization only - Play forward at speed 0.2x – Visualization only - Play forward at speed 0.5x – Visualization only - Play forward at speed 1x – Visualization only - Play forward at speed 2x – Visualization only - Play forward at speed 4x – Visualization only - Play forward at speed 8x – Visualization only - Play forward at speed 16x – Visualization only - Ctrl+Shift+' – Play backward at speed 0.01x (Visualization only). Note: This is the key to the left of the return key on the international keyboard. - Play backward at speed 0.04x – Visualization only - Play backward at speed 0.2x – Visualization only - Play backward at speed 0.5x – Visualization only - Play backward at speed 1x – Visualization only - Play backward at speed 2x – Visualization only - Play backward at speed 4x – Visualization only - Play backward at speed 8x – Visualization only - Play backward at speed 16x – Visualization only - Ctrl+F3 – New trial (Acquisition only) Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Shortcuts URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-shortcuts Chapter: EthoVision XT Shortcuts Keyboard shortcuts are only available when the corresponding menu or window is active. - Windows – General - Experiment Explorer - EthoVision XT – General - Select and Edit - Trial List and Other Grids - Row-Select Grids - Playback Control, Acquisition and Visualization - Arena Settings - Manual Scoring Settings - Trial Control - Detection Settings - Track Editor - Analysis Profiles - Statistics and Charts Windows – General Some of these shortcut keys can also be used in the Experiment Explorer, the Show/Hide menu, the Arena Settings window, the Trial Control window, and the Detection Settings window. - Esc – Cancel action - F1 – Help - F2 – Rename / edit - F3 – Find next - Shift+F3 – Find previous - F4 – Expand pull down list - Ctrl+F4 – Close active window (does not apply to EthoVision XT) - Alt+F4 – Close application - Alt+Enter – Open properties of selected item (e.g. Settings dialog of dependent variable) - Shift+F10 or context menu key – Open context menu of selected item - Alt+Spacebar – Open shortcut menu of selected window - Ctrl+Esc – Display Start menu - Alt+underlined letter – Application: open corresponding main menu; Dialog: carry out corresponding command - F10 – Activate main menu bar - Main menu: down arrow key – Open menu item / cycle through sub-items - Main menu: up arrow key – Open menu item / cycle through sub-items - Main menu: right arrow key – Open sub-items / cycle through items - Main menu: left arrow key – Close sub-items / cycle through items - Spacebar – Select / clear checkbox if active option is a checkbox - Arrow keys – Move / nudge cursor (highlighted item in grid) or selected item - Alt+Tab – Switch between open applications - Alt+Esc – Cycle through applications in order they were opened EthoVision XT – General Shortcuts from the Menu Use the keyboard to activate all the functions in EthoVision XT that are on the menus. Press Alt plus the letter underlined in the menu and then select the desired function by scrolling down to the function or by pressing the underlined letter. For example, to go to Preferences on the File menu, press Alt+F, f. Main Shortcuts - End – Display the bottom of the active window - Home – Display the top of the active window - * on numeric keypad – Display all subfolders under the selected folder - + on numeric keypad – Display the contents of the selected folder - - on numeric keypad – Collapse the selected folder - Left arrow key – Collapse current selection if it's expanded, or select parent folder - Right arrow key – Display current selection if it's collapsed, or select first subfolder - Up arrow key – Previous item - Down arrow key – Next item - Ctrl+N – New default experiment - Ctrl+O – Open (experiment or other file type) - Ctrl+S – Save experiment - Ctrl+Shift+S – Save experiment as… - Ctrl+T – New template experiment Trial List and Other Grids - Ctrl+X – Cut - Ctrl+C – Copy - Ctrl+V – Paste - Ctrl+Delete or Delete – Delete - Ctrl+drag item – Copy selected item - Shift+drag item – Move selected item - Shift+arrow keys – Expand / contract block selection in direction of arrow key - Ctrl+left arrow key – Go to first cell of row - Ctrl+right arrow key – Go to last cell of row - Ctrl+up arrow key – Go to first cell of column - Ctrl+down arrow key – Go to last cell of column - Arrow keys – Move highlight in direction of key - F2 – Rename / edit cell content (see Windows – General) - Tab – Go to next cell in row; if last cell, do nothing - Shift+Tab – Go to previous cell in row; if first cell, do nothing - Enter – Accept entry and go to same column, next row; if last row, go to first cell of last row - Home – Go to the first character within the cell (edit mode, only for user-defined variables) - End – Go to the last character within the cell (edit mode, only for user-defined variables) - Page Up – Go to row minus the number of rows visible in window and highlight same location (and de-select) - Page Down – Go to row plus the number of rows visible in window and highlight same location (and de-select) - Ctrl+Home – Go to first cell of first column - Ctrl+End – Go to last cell of last column - Ctrl+Alt+T – Add trials to the Trial List - Ctrl+Alt+V – Add an independent variable to the Trial List Row-Select Grids An example of a row-select grid is the Components pane in the Data Profile screen and Analysis Profile screen. There you can select rows, not individual cells. Playback Control, Acquisition and Visualization - Ctrl+Alt+L – Add videos to the Trial List - Ctrl+Alt+I – Import external data into the Trial List - Ctrl+Alt+E – Import trials into the Trial List - Up arrow key – Step one row up - Down arrow key – Step one row down - Enter – Open the settings window of the selected row in the Analysis Profile - Ctrl+up arrow key – Jump to begin - Ctrl+down arrow key – Jump to end - Ctrl+left arrow key – Step 1 sample (or frame) backward - Ctrl+right arrow key – Step 1 sample (or frame) forward - Play forward – Play forward at the speed selected. When playing back the tracks, one step forward corresponds to the time interval for the sample rate used for tracking (for example, 0.04 seconds if the sample rate is 25/s). - Play backward – Play backward. When playing back the tracks, one step backward corresponds to the time interval for the sample rate used for tracking. - Pause / stop – Pause or stop playback - Ctrl+. – Zoom x2 (Track Visualization, Heatmaps and variable plots in Integrated Visualization) - Ctrl+, – Zoom x1/2 (Track Visualization, Heatmaps and variable plots in Integrated Visualization) - Ctrl+/ – Fit all (Track Visualization only) - Ctrl+' – Play forward at speed 0.01x (Visualization only). Note: This is the key to the left of the Enter key on the international keyboard. - Play forward at speed 0.04x – Visualization only - Play forward at speed 0.2x – Visualization only - Play forward at speed 0.5x – Visualization only - Play forward at speed 1x – Visualization only - Play forward at speed 2x – Visualization only - Play forward at speed 4x – Visualization only - Play forward at speed 8x – Visualization only - Play forward at speed 16x – Visualization only - Ctrl+Shift+' – Play backward at speed 0.01x (Visualization only). Note: This is the key to the left of the Enter key on the international keyboard. - Play backward at speed 0.04x – Visualization only - Play backward at speed 0.2x – Visualization only - Play backward at speed 0.5x – Visualization only - Play backward at speed 1x – Visualization only - Play backward at speed 2x – Visualization only - Play backward at speed 4x – Visualization only - Play backward at speed 8x – Visualization only - Play backward at speed 16x – Visualization only - Ctrl+F3 – New trial (Acquisition only) Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Shortcuts (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-shortcuts-continued-QdT Chapter: EthoVision XT Arena Settings See also Windows – General and Normal Grids shortcut keys. - Ctrl+F5 – Start trial (Acquisition only) - Ctrl+F6 – Stop trial (Acquisition only) - Ctrl + + – Playback speed one step up. The current speed is shown next to this button. Note: It does not work with the key + on the numerical keyboard. - Ctrl + - – Playback speed one step down. Note: It does not work with the key - on the numerical keyboard. - (no shortcut) – Reset the background (grabs the current video frame and uses it as background) - (no shortcut) – Skip trial - (no shortcut) – Optimize tracking speed. See DDS (Detection determines speed) - (no shortcut) – Starts screen recording (Integrated Visualization only) - Del – Delete selected element - Ctrl+J – Validate the Arena Settings - V – Normal (arrow) mode - R – Rotation mode - P – Point edit mode - L – Draw lines - S – Draw rectangle - O – Draw open polyline - Y – Draw closed polyline - E – Ellipse - T – 3-Point circle - I – Subdivided circle - U – Subdivided rectangle - Z – Add zone label - A – Auto label zone - C – Add point - Up arrow key – Nudge selected element smallest resolution unit up - Down arrow key – Nudge selected element smallest resolution unit down - Left arrow key – Nudge selected element smallest resolution unit left - Right arrow key – Nudge selected element smallest resolution unit right - Shift+arrow key – Nudge 10x - Ctrl+. – Zoom in the background image and arena elements - Ctrl+, – Zoom out the background image and arena elements Manual Scoring Settings - Ctrl+B – Add a behavior category - Ctrl+V – Validate the current coding scheme Trial Control See Windows – General and Row-select Grids shortcut keys. Detection Settings See Windows – General and Row-select Grids shortcut keys. The following shortcut keys for playing back the video file work in the Detection Settings window. Track Editor The shortcut keys for playing back the video files, listed in Playback Control, Acquisition and Visualization also work in the Track Editor screen. - Ctrl+Up arrow key – Jump to begin - Ctrl+Down arrow key – Jump to end - Ctrl+Left arrow key – Step -1 sample - Ctrl+Right arrow key – Step +1 sample - Ctrl+▶ – Play forward - Ctrl+▮▮ – Pause / stop - Ctrl+E – Open the Auto Select window - W – Swap nose and tail in selection - Ctrl+F – Open the Fix Nose-Tail swaps window - D – Swap subjects in selection - Ctrl+Del – Set selection to missing - Ctrl+I – Interpolate selection - Ctrl+Shift+I – Interpolate only center-points - Ctrl+M – Set tail-base points to missing - Ctrl+Shift+M – Set nose points to missing Analysis Profiles - For the Components pane: see Row-select grids - For the Dependent Variables list: see Trial List and other grids Statistics and Charts - C – Refresh the statistics results table - B – Start batch analysis - E – Export the statistics results table Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Shortcuts (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-shortcuts-continued Chapter: EthoVision XT Arena Settings See also Windows – General and Normal Grids shortcut keys. - Ctrl+F5 – Start trial (Acquisition only) - Ctrl+F6 – Stop trial (Acquisition only) - Ctrl + + – Playback speed one step up. The current speed is shown next to this button. Note: It does not work with the key + on the numerical keyboard. - Ctrl + - – Playback speed one step down. Note: It does not work with the key - on the numerical keyboard. - (no shortcut) – Reset the background (grabs the current video frame and uses it as background) - (no shortcut) – Skip trial - (no shortcut) – Optimize tracking speed. See DDS (Detection determines speed) - (no shortcut) – Starts screen recording (Integrated Visualization only) - Del – Delete selected element - Ctrl+J – Validate the Arena Settings - V – Normal (arrow) mode - R – Rotation mode - P – Point edit mode - L – Draw lines - S – Draw rectangle - O – Draw open polyline - Y – Draw closed polyline - E – Ellipse - T – 3-Point circle - I – Subdivided circle - U – Subdivided rectangle - Z – Add zone label - A – Auto label zone - C – Add point - Up arrow key – Nudge selected element smallest resolution unit up - Down arrow key – Nudge selected element smallest resolution unit down - Left arrow key – Nudge selected element smallest resolution unit left - Right arrow key – Nudge selected element smallest resolution unit right - Shift+arrow key – Nudge 10x - Ctrl+. – Zoom in the background image and arena elements - Ctrl+, – Zoom out the background image and arena elements Manual Scoring Settings - Ctrl+B – Add a behavior category - Ctrl+V – Validate the current coding scheme Trial Control See Windows – General and Row-select Grids shortcut keys. Detection Settings See Windows – General and Row-select Grids shortcut keys. The following shortcut keys for playing back the video file work in the Detection Settings window. Track Editor The shortcut keys for playing back the video files, listed in Playback Control, Acquisition and Visualization also work in the Track Editor screen. - Ctrl+up arrow key – Jump to begin - Ctrl+down arrow key – Jump to end - Ctrl+left arrow key – Step -1 sample - Ctrl+right arrow key – Step +1 sample - Ctrl+ – Play forward - Ctrl+ – Pause / stop - Ctrl+E – Open the Auto Select window - W – Swap nose and tail in selection - Ctrl+F – Open the Fix Nose-Tail Swaps window - D – Swap subjects in selection - Ctrl+Del – Set selection to missing - Ctrl+I – Interpolate selection - Ctrl+Shift+I – Interpolate only center-points - Ctrl+M – Set tail-base points to missing - Ctrl+Shift+M – Set nose points to missing Analysis Profiles - For the Components pane: see Row-select Grids - For the Dependent Variables list: see Trial List and Other Grids Statistics and Charts - C – Refresh the statistics results table - B – Start batch analysis - E – Export the statistics results table Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Smooth the Tracks - Minimum Distance Moved Methods URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-smooth-the-tracks-minimum-distance-moved-methods Chapter: EthoVision XT Minimum Distance Moved Methods In both cases, all five samples are selected for analysis. However, some samples have been "moved" to a previous sample in such a way that their own value of distance moved is zero. Direct The program calculates the shortest distance between a sample and the next (AB, dashed line). If this distance is shorter than the threshold distance MDM, sample B is set to sample A. Then the program calculates the distance to the second next sample (AC), etc. until it finds a segment (AD) longer than MDM. Samples B and C are both set to sample A. This procedure is then repeated up to the end of the track. With the Direct method, samples B and C overlap with A, and E with D. Along the Path EthoVision XT calculates the distance between a sample and the next (AB, dashed line). If this distance is shorter than the distance threshold, sample B is set to sample A. Then the program calculates the cumulative distance along the path to the second next sample (AB + BC, etc.). In this example, sample B is set to sample A. However, the distance AB + BC is greater than MDM, so C stays in its place. Next, sample D is set to sample C because CD < MDM. However, CD + DE is longer than MDM, so sample E stays in its place. The procedure is repeated up to the end of the track. With Along the Path, sample B overlaps with A, and D with C. The resulting total distance moved can therefore differ depending on which option is chosen. Source: EthoVision XT 19 Help - Smooth the Tracks, Noldus Information Technology --- ## EthoVision XT 19 - Smooth the Tracks - The Lowess Smoothing Method URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-smooth-the-tracks-the-lowess-smoothing-method Chapter: EthoVision XT The Lowess Smoothing Method Lowess stands for Locally Weighted Scatter Plot Smoothing. This method fits a curve to the dataset, using a least square regression modified as follows: - The Lowess method uses a moving time window (or half size window) that contains a subset of sample points. - The Lowess method uses a 2-degree (non-linear) polynomial fit. This fit is applied to the center-point. If you use center-point, nose-point and tail-base detection, the fit is also applied to the angle between center-point and nose-point and between the center-point and tail-base. - The Lowess method is weighted; sample points nearest to the point being fitted have a larger influence on the fit than sample points further away. The Lowess method has been successfully applied to track data from EthoVision. To Apply Lowess Smoothing - Choose Acquisition > Track Smoothing Profile > Open. - Select the Smoothing (Lowess) check box and click the Edit button. - Change the number of sample points in the Half Window Size list. The default value is 10, which is the recommended value. Selecting a larger half window size results in a smoother path. Selecting a smaller half window size results in a path that more resembles the original path. With a lower sample rate, you should use a larger half window size to get the same smoothing as with a higher sample rate. Notes - Smoothing is applied after data acquisition and after data editing, but before the Minimal Distance Moved method. The smoothed data, not the original data, are used for analysis and for export. Applying smoothing does not change the original data. - Smoothing and body points. Smoothing is applied to the center-point, and subsequently, if you also tracked the nose-point and the tail-base, to the angle formed by the three body points. - Smoothing and missing samples. When up to 200 consecutive samples are missing, they are interpolated. Next, their x,y coordinates are re-calculated based on the Lowess method. The subject area for missing samples is interpolated linearly, but is not smoothed. If the subject is missing for more than 200 samples (this corresponds to 8 seconds for a sample rate of 25), that track segment stays missing and is not smoothed. - Smoothing of Live Mouse Tracker data. When you apply Lowess smoothing to Live Mouse Tracker data, EthoVision XT takes the 3D coordinates of the body points (x-, y- and z-coordinates). The 3D position of the nose-point and the tail-base point are represented with spherical coordinates bound to the center-point. For example, the coordinates of the nose point are based on the length r and angles θ and ϕ of the segment joining the center-point and the nose-point. The z-coordinate of the nose- (or tail-base) point includes the angle θ formed between the x-y plane and the segment joining that body point and the center-point. Smoothing of Live Mouse Tracker data is done with vectors and angles drawn in 3D instead of 2D as in typical EthoVision XT nose-tail data. - Smoothing and hidden zones. Samples assigned to a hidden zone are smoothed too. For this reason, after smoothing with the Lowess method, part of the samples in the hidden zone are "moved" outward. Those samples add up to the total distance moved in your results. How many samples are moved depends on the original trajectory. References - Drai and Golani, 2001. SEE: a tool for the visualization and analysis of rodent exploratory behavior. Neuroscience & Biobehavioral Reviews 25(5): 409–426. - Hen, I. et al., 2004. The dynamics of spatial behavior: How can robust smoothing techniques help? Journal of Neuroscience Methods 133(1-2): 161–172. - Kafkafi, N. et al., 2005. Genotype-environment interactions in mouse behavior: a way out of the problem. Proceedings of the National Academy of Sciences USA 102(12): 4619–4624. Acknowledgments We gratefully acknowledge the ongoing collaboration with Prof. Ilan Golani, Prof. Yoav Benjamini and their colleagues at Tel Aviv University. Their pioneering work on the detailed analysis of animal movement has been a source of inspiration for the developers of EthoVision and for many of its users around the world. The Minimal Distance Moved Smoothing Method Aim To filter out small movements of the subject's center point that are caused by random noise, not by the subject's spatial displacement. Working Principle With the Minimal Distance Moved method, you can pick out the data when the subject moved a minimal distance from one sample to the next. - When the distance moved between the current and the previous sample is above (or equal to) the threshold for Minimal Distance Moved, the current sample is used for analysis. - If the distance moved between the current and the previous sample does not exceed the threshold, the current sample is "moved back" to the previous sample. The result of this filter is that small movements of the body points, supposedly due to noise, are removed, and the trajectory of the subject becomes simpler. Procedure - Choose Acquisition > Track Smoothing Profile > Open. - Select the Minimal Distance Moved check box and click the Edit button. - Under Select, enter the Minimal Distance Moved threshold. - Choose one of the two options: - Direct (A > MDM). To select samples on the basis of the shortest distance (beeline distance) between samples. Select Direct to exclude movements such as breathing when the animal is sitting still. - Along the Path (B + C + D > MDM). To select samples on the basis of the actual path between samples. Select Along the Path whenever you want to filter samples according to the distance moved along the path. - Click OK. Notes - Minimal Distance Moved is only applied to the center-point. - Under some circumstances, using the Minimal Distance Moved filter might affect dependent variables other than Distance Moved and Velocity. To apply Minimal Distance Moved to some dependent variables but not others, create two Track Smoothing profiles: one with Minimal Distance Moved selected, the other without Minimal Distance Moved selected. Run batch calculations using both smoothing profiles. Direct vs. Along the Path Minimal Distance Moved As shown by the case of Distance Moved, calculation of the dependent variables is affected by which Minimal Distance Moved option you choose. --- ## EthoVision XT 19 - Smooth the Tracks - Undo Track Edits URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-smooth-the-tracks-undo-track-edits Chapter: EthoVision XT Undo Track Edits Aim To revert to previously saved data after you have changed the data further and you do not want to keep the last edits. Note: The procedure below is also valid when you edit data in the Manual Scoring screen. There you also find the Save and Undo buttons. Prerequisites - In the Track Editor, or in the Manual Scoring screen, you have done edits after saving the data at least one time. Procedure - Click the Undo button on the toolbar. A message appears, asking you whether you want to lose the changes since the last save. - If you click Yes, the original track plot is restored. If you click No, you return to the main screen without losing the changes. Notes - To return to the original data, click Undo All. However, keep in mind that you lose all changes. - If you edit data in one trial and then select another trial in the trial selection list on the toolbar, the changes you have made to that trial are saved automatically, including those you made after saving. - If you open another EthoVision XT screen, for example to calculate statistics, or close the experiment after making changes to the track, those changes are saved and retained when you switch back to the Track Editor screen. However, the saved copy (restore point) is always deleted when closing the experiment. Therefore, you cannot revert to the saved copy. Consider the following sequence of actions: - Edit data, then click Save. - Make a second run of changes, then close the experiment. - Re-open the experiment and choose Acquisition > Edit Tracks. The screen also shows the second set of changes made, but you cannot revert to the saved copy (restore point). Smooth the Tracks Why Smooth the Tracks? In any tracking system, there are three sources of noise that potentially affect the values of dependent variables such as Distance Moved or Velocity: - System noise. The noisy output of tracking systems means that when you track an object that does not move, the position of the object irregularly oscillates between two or more locations. This way the track may show continuous movement of the object that corresponds to a real-world distance of, for example, 1 cm, while in fact the animal is sitting still. As a result, the data show that the immobile object traveled quite a distance. - Outliers resulting from tracking noise. Occasionally the tracking system generates a single outlier which obviously affects a dependent variable such as Velocity. - Small movements of the animal ('body wobble'). When you track a moving animal using a high sample rate, sideways movements from the wobbling of the animal's body are also tracked. This results in an overestimation of, for instance, the total distance moved. Smoothing Methods Smoothing (Lowess) Use this method to eliminate small movements, such as body wobbling during locomotion, that might affect dependent variables such as total distance moved. Minimal Distance Moved Use Minimal Distance Moved when the animal sits still, yet the body points move slightly due to system noise or breathing. Maximal Distance Moved Use Maximal Distance Moved to remove outliers due to erratic detection, for example in a water maze test when some water reflection is detected as the subject, or in DanioVision experiments when the subject does not move and EthoVision XT detects the margins of the well as the subject. Track Smoothing During Acquisition The track smoothing methods listed above affect the tracks after acquisition. In some cases you may already want to smooth the track during acquisition. This may especially be the case if you use Trial and Hardware Control. As an example, if the center-point of an animal is detected in a zone, you want the pellet dispenser to drop a pellet. If the detected center-point is moving rapidly because of noise, this may result in a number of consecutive pellets being dropped, every time the center-point crosses the border of the zone. Track smoothing does not solve this problem. Instead, use Track Noise Reduction in the detection settings to smooth the tracks during data acquisition. --- ## EthoVision XT 19 - Social escape URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-social-escape Chapter: EthoVision XT Social Escape Definition A discrete (state event) variable that is scored when the focal subject walks away from a conspecific (named Receiver). The distance between the center points of the two subjects is within two times the average body length of the receiver. Calculation - EthoVision XT finds all the events of type Get Away in the Live Mouse Tracker database. - EthoVision XT calculates the average body length of the subject which the focal subject is moving away from. The body length is measured as the distance between the nose-point and the tail-base point, and averaged throughout the entire track. - If the distance between the center point of the focal subject is within two times the average body length of the other subject, Social escape is scored for that sample. How to Specify Social Escape - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Social escape. - Click the Receivers tab. Under Select, choose the subjects that the focal subject escaped from. If you select two or more subjects, select one of the available options from the list: - All selected subjects: Social escape is scored when the focal subject escaped from all the subjects selected above simultaneously. For example, when the focal subject left a group of three cage mates. - Any selected subject: Social escape is scored when the focal subject escaped from any of the subjects selected above. - Each subject: Social escape is scored when the focal subject escaped from one of the subjects selected above. The results are displayed for each Receiver. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Notes In the Trial Statistics results table, with the default layout, the results of Social escape are shown per subject (on the rows). The columns vary depending on what you chose in the Receivers tab. - If you chose Each subject, the columns contain the statistics of Social escape from specific subjects (for example, Social escape A to D). - If you chose All selected subjects or Any selected subject, a column All of A, B, C, D or Any of A, B, C, D contains cumulative statistics of Social escape when the subject escaped from all the cage mates simultaneously or from any of them, respectively, depending on which option you chose. See also - Social Approach - Social > Relative Movement Stop Definition A discrete (state event) variable that marks the time that the focal subject's center point moves little or not at all in space. Two categories are defined, based on whether the subject is in contact with other subjects or not. Calculation - EthoVision XT finds all the events of type Stop in the Live Mouse Tracker database. These are scored when the speed of the subject is lower than the threshold value (5.26 cm/s or 2 5/64 in). This threshold is set in the Live Mouse Tracker algorithms and cannot be changed. - EthoVision XT finds the events of type Contact in the Live Mouse Tracker database. - If the event Stop and Contact overlap, then Stop in contact is scored for that sample. In all other cases, Stop alone is scored. How to Specify Stop - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Stop. - Under Calculate Statistics for, select Stop alone, Stop in contact, or both. - Click the Receivers tab. This applies if you selected Stop in contact in the previous step. Under Select, choose the subjects that the focal subject was in contact with while it was not moving. If you select two or more subjects, select one of the available options from the list: - All selected subjects: Stop in contact is scored when the focal subject was in contact with all the subjects selected above simultaneously. - Any selected subject: Stop in contact is scored when the focal subject was in contact with any of the subjects selected above. - Each subject: Stop in contact is scored when the focal subject was in contact with one of the subjects selected above. The results are displayed for each Receiver. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Notes - The state Not moving, which you can find in the EthoVision XT dependent variable Movement, is similar to Stop. However, there are differences: - You can set the speed thresholds for Not moving, not for Stop. - Instances of Not moving cannot be split based on the events of contact with other subjects. - In the Trial Statistics results table, with the default layout, the results of Stop are shown per subject (on the rows). When choosing Stop in contact, the columns vary depending on what you chose in the Receivers tab. - If you chose Each subject, the columns contain the statistics of Stop in contact with specific subjects (for example, Stop in contact with A to D). - If you chose All selected subjects or Any selected subject, a column With all of A, B, C, D or With any of A, B, C, D contains cumulative statistics of Stop in contact when the subject was in contact with all the cage mates simultaneously or with any of them, respectively, depending on which option you chose. See also - Live Mouse Tracker > Move - Movement Stretch Attend Posture Definition A discrete (state event) variable that is scored when the subject slows down and stretches its body forward. The subject's apparent body length (measured from the top view) increases and its height (measured with the depth camera) decreases. Calculation - EthoVision XT calculates the average and the standard deviation (SD) of the body length, measured as the distance between the nose-point and the tail-base point, throughout the entire track. - EthoVision XT calculates the median body height, where body height is measured using the z-coordinate of the subject's center point. - Stretch attend posture is scored when the following occur simultaneously: - The current body length is equal to or greater than the average + 1 SD of the body length. - The current body height is smaller than the median body height. - The current speed of the subject is lower than 5 pixels per video frame (at 30 fps, this is about 26 cm/s). How to Specify Stretch Attend Posture - Open an Analysis profile and in the Dependent Variables panel, under Live Mouse Tracker, click the Add button next to Stretch Attend Posture. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Note Stretch attend posture is not detected if the nose-point or the tail-base point are not found at that time. The software needs both points to estimate the body length. See also - Dependent Variables for Live Mouse Tracker Managing Files and Experiments Main Topics and Tasks - Manage your experiments - Import data - Export data Important: Manage your files and experiments within EthoVision XT. If you delete, move, or rename files using the Windows File Explorer, EthoVision XT may not be able to find the files again. To move or copy data and experiments to another location, see Back up an experiment. See also - Using Digital Video - File Locations Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Software Installation - Deactivate an EthoVision XT License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-deactivate-an-ethovision-xt-license Chapter: EthoVision XT Deactivate an EthoVision XT License Aim To deactivate a license, either to end the license agreement or to transfer the license to another computer. For example, if you have purchased a new computer and would like to transfer your EthoVision XT license from the old to the new computer. Prerequisites - EthoVision XT is running, and no experiment is open. - The EthoVision XT computer is connected to the internet, or you have a smartphone connected to the internet. What Do You Want to Do? - Deactivate a computer-locked license - Deactivate a floating license See Types of EthoVision XT License. Deactivate a Computer-Locked License - If an experiment is open in EthoVision XT, close it (File > Close). - Choose Help > Deactivate License. - Choose Computer-locked and click Continue. - Select one of the options depending on whether your EthoVision XT computer is connected to the internet: - Deactivate online. Do this if your EthoVision XT computer is connected to the internet. Select this option and click OK. - Deactivate offline. If your computer is not connected to the internet, you need a smartphone connected to the internet that can scan a QR code. (1) Select this option and click OK. (2) A QR code appears on the screen. (3) Scan this code using a smartphone and follow the link within 24 hours. (4) Click Deactivate on the screen that appears in your browser. - EthoVision XT shows a message that the license has been deactivated and closes. Notes - If your smartphone is not connected to the internet, leave the link open, go to a place where your smartphone is connected to the internet, and open the linked page. - When you click Deactivate offline, your license is deactivated on your computer, but not yet on the Noldus Server. For this second step you must scan the QR code, follow the associated link, and click Deactivate in a web browser on your smartphone. Do this within 24 hours. Deactivate a Floating License Deactivate a floating license when you need to transfer that license to another computer. Note that when you have floating licenses, in order to be able to work on one computer you just need to close EthoVision XT on the other computer(s). You do not need to deactivate the license on the other computer(s). - Make sure that the EthoVision XT computer is connected to the internet. - In EthoVision XT, choose Help > Deactivate License. - A message appears: The license was successfully deactivated. - Click Close. You can now activate that floating license on another computer. See Activate Your EthoVision XT License. See Also - Activate Your EthoVision XT License - Types of EthoVision XT License Turn a Floating License to a Computer-Locked License Aim You may want to turn a floating license to a computer-locked (fixed-seat) license so you can use EthoVision XT on a computer without an internet connection. Prerequisites - You have an Activation Key for your license. Procedure - Open EthoVision XT and deactivate the floating license. An internet connection is required for this step. See Deactivate a Floating License. - After deactivation of the license, EthoVision XT closes. - Start EthoVision XT on the computer where you want to have the license activated. - Choose Activate software license key, then Computer-locked. Follow the instructions in Activate a Computer-Locked License - Online. See Also - Types of EthoVision XT License Turn a Computer-Locked License to a Floating License Aim You may want to turn a computer-locked (fixed-seat) license to a floating license because you want to use EthoVision XT on multiple computers, although not simultaneously. Note that if you purchased multiple floating licenses, you can work on multiple computers simultaneously, because a license will be active on each computer. Prerequisites - You have the Activation Key for your license. Procedure - Open EthoVision XT and deactivate the computer-locked license. See Deactivate a Computer-Locked License. - After deactivation of the license, EthoVision XT closes. - Start EthoVision XT on the computer where you want to activate the floating license. An internet connection is required for this step. - Choose Activate software license key, then Floating - On multiple computers. Follow the instructions in Activate a Floating License. Notes - If you choose to deactivate offline, first click OK, then scan the QR code that appears. Follow the link and click/tap Deactivate. See Also - Types of EthoVision XT License --- ## EthoVision XT 19 - Software Installation - Floating License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-floating-license Chapter: EthoVision XT Floating License This is a license that is not associated with a specific computer. It is intended to be used in multiple computers, although not simultaneously, for example, in one PC at the lab and one or more PCs in the office. See Types of EthoVision XT License. Prerequisites - You have installed EthoVision XT. See Install EthoVision XT. - You have received a license Activation Key from Noldus. Contact Noldus Support. - If your license is stored in a hardware key (dongle), you do not have to follow this procedure. Simply plug in the key in a USB port of your PC. What Do You Want to Do? - Activate a floating license – Use a license on different computers at different times. However, if you have two or more floating licenses instead of one, you can use EthoVision XT on multiple computers simultaneously. For this type of license you need an internet connection. - Activate a computer-locked license - online – Your license is coupled with a specific computer. Activate your license online. You need an internet connection during activation. - Activate a computer-locked license - offline – Your license is coupled with a specific computer. The computer does not have to be connected to the internet, but you need a smartphone or tablet with an internet connection during activation. Note: This option is not available if you have purchased a time-limited license or received a license for a free trial. See Duration of the EthoVision XT License. Activate a Floating License Important: You can only activate and use a floating license when your EthoVision XT computers are connected to the internet. Make sure that your EthoVision XT computer in the lab is always connected. Follow these steps for each computer. - Make sure that your EthoVision XT computer is connected to the internet. - Start EthoVision XT. - In the window that appears, choose Use the software activation key and click Continue. - Choose Floating license - Online connection required and click Continue. - Enter or copy the activation key that you received from Noldus. - Click Continue. - When the license has been activated, a message appears. Repeat the procedure on the other computers. Activate a Computer-Locked License - Online - Make sure that your EthoVision XT computer is connected to the internet. - Start EthoVision XT. - In the window that appears, choose Use the software activation key and click Continue. - Choose Computer-locked license - Online activation and click Continue. - Enter or copy the activation key that you received from Noldus. - Click Continue. - When the license has been activated, a message appears. Activate a Computer-Locked License - Offline - Make sure that you have a smartphone connected to the internet that can scan a QR code. - Start EthoVision XT. - In the window that appears, choose Use the software activation key and click Continue. - Choose Computer-locked license - Offline activation and click Continue. - Enter or copy the activation key that you received from Noldus. - A QR code appears on the window. Scan the QR code with your smartphone. If the QR code is recognized, the Noldus License Manager web page opens on your smartphone, showing the required Computer Key. - Enter this key in the Enter computer key field in the Noldus License Activation window. - Click Continue. - When the license has been activated, a message appears. Notes - You cannot activate a term license after the expiration date. - If activation fails: - Try once again and make sure that you enter the correct Activation/Computer Key, including capital letters and dashes. - Contact Noldus to obtain a valid Activation Key. - If your license is not activated, you can still start EthoVision XT and work in Analysis mode. See EthoVision XT in Analysis Mode. - If the license activation window does not appear after starting EthoVision XT, it may be that the software is in Analysis mode. To activate/deactivate the license, first choose Help > Deactivate License. The window says Deactivate Analysis mode. Choose Continue, then restart EthoVision XT. - See also Upgrade EthoVision XT. --- ## EthoVision XT 19 - Software Installation - Hardware URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-hardware Chapter: EthoVision XT Hardware Computer EthoVision XT has been tested with the workstations listed below. If you order a complete solution from Noldus Information Technology, you will obtain one of these computers or its successor, with EthoVision XT installed and ready to use. See also Ordering a PC from Another Supplier. Dell Precision 3680 Tower Workstation (Desktop) - Processor: Intel Core i7-14700, 20 CPU cores, 3.4 GHz. - Internal memory: 32 GB DDR5. - Hard disks: M.2 1TB PCIe NVMe SSD. - Graphics card: NVIDIA T1000, 4 GB GDDR6. - PCIe slots (full-height): 1x Gen5 PCIe x16, 1x Gen3 PCIe x4, 1x Gen4 PCIe x4 (open-ended). - Operating system: Windows 11 Pro. Dell Precision PCs are recommended when tracking subjects with the Deep Learning method. See Deep Learning: Requirements. Dell Precision 3591 Workstation (Laptop) - Processor: Intel Core Ultra 7 155H vPro Essentials, 16 cores, up to 4.8 GHz. - Internal memory: 16 GB DDR5. - Hard disks: M.2 2280 1 TB PCIe NVMe SSD. - Graphics card: NVIDIA RTX 1000, 6 GB GDDR6. - Operating system: Windows 11 Pro. Ordering a PC from Another Supplier If you choose to order a PC from a supplier other than Noldus or its distributors, you can use the above specifications as a guideline. Use a Professional Workstation We recommend that you use a professional workstation. It is possible to buy consumer-range computers with a high processor speed and plenty of memory, but in order to remain competitive regarding price, the manufacturers often economize on the underlying system architecture. That means those computers are suitable for home use, but not for running professional scientific software. You should select a computer which is intended for professional use or labeled by the manufacturer as a workstation. Desktop or Laptop? - If you plan to purchase a desktop computer, always choose a tower mid-size or full tower size. Do not use mini or small form factor desktops. When in doubt, ask your Noldus representative. - If you plan to use a laptop or a desktop with an unpowered network interface board (also known as network interface card, NIC), you need a Power over Ethernet Injector to power a GigE camera. - If you plan to use analog cameras (e.g. for PhenoTyper 1), you need a desktop computer with at least one PCI slot. - The Ethernet interface board should support data transfer of 1 Gb/s (one port). - If you plan to use a laptop, please consider the following: - Only one camera is supported, either GigE (Basler acA1300-60gm) or USB 3.0 (acA1920-155um). We recommend using a laptop with an RJ45 Ethernet port. Some laptops have a USB-C port for internet; in that case you need a USB-C to Ethernet adapter, but not all of them work properly when connecting a digital camera. Test a few adapters if needed. - If you need internet, use Wi-Fi or a second USB-Ethernet adapter. - There may be restrictions in terms of maximum resolution and/or maximum recording time. Check carefully what has been tested. See Cameras Supported by EthoVision XT. - Always acquire data with the laptop plugged in. In Windows, click Settings, then type power. Click Power, sleep and battery settings. Next, click Screen and sleep. Next to When plugged in, put my device to sleep after, select Never. Intel Processor (CPU) We strongly recommend using a computer with Intel x64-compatible processors, Intel Xeon or i7 CPU. In Intel processors, the acceleration required by the IPP (Integrated Performance Primitives) software is guaranteed. That may not be the case for other manufacturers which offer high-quality and fast processors. IPP is an extensive library of ready-to-use, domain-specific functions. It is used by EthoVision XT during image processing and data acquisition, and therefore affects performance of video tracking. Processors from other manufacturers are compatible with EthoVision XT, but tracking could be significantly slower. Consider this when you plan to purchase a computer to acquire large amounts of data from high-resolution video, or to analyze video with Behavior Recognition or Deep Learning. - Other processors such as AMD may well work with the IPP, although Noldus does not support them. Always test your computer thoroughly before running the actual experiments. - EthoVision XT will not work on Qualcomm/ARM chips. Important Factors to Keep in Mind - The more animals and arenas you track, the more processor load you require. - Nose-tail tracking requires more processor load than tracking the center-point only. - The optimal sample rate depends on the species you track. Mice, for example, require a higher sample rate than rats. See Sample Rate for more information about the optimal sample rate. - A larger image requires more computer resources for tracking, so a larger image does not necessarily lead to better tracking. GPU - Full support for NVIDIA RTX 50 series GPUs and CUDA 13.1. Pascal architecture (GTX 10 series) is no longer supported for deep learning features. RAM Memory - For desktop computers, we recommend 32 GB RAM memory. - For laptops, 16 GB RAM memory should suffice. USB 3.0 Port Current PCs have USB 3.x ports installed as standard. USB ports are necessary if you use a USB 3.0 camera. See Install USB 3.0 Cameras. If you use hardware like the USB-IO box, you need an additional USB port. Power Supply Unit (PSU) Powerful graphics cards need additional power. Ensure that the computer has a Power Supply Unit (PSU) that can provide enough power to the graphics card. Take note of the Suggested PSU for a specific card and make sure the PC can handle it. See also More Information on Graphics Cards (GPUs) and Install a Graphics Card for Deep Learning. Virtual Machines Virtualization allows you to run different operating systems on the same computer. However, EthoVision XT was not designed to work on a virtual machine, and its use on virtual machines is not supported. Ethernet Interface Board Ethernet Interface in Desktop Computers In order to use high-quality GigE cameras, your computer must have a 1 Gb Ethernet Interface Adapter (board), also known as a Network Interface Card (NIC). Depending on the number of Ethernet ports, you can connect one to four cameras per board. The following boards have been tested successfully: - CT1000 Pro (1 camera) - Adlink PCIe-GIE74 (1–4 cameras) - Basler GigE Interface Card, 4 port PoE (1–4 cameras) - FS X550AT2-2TP (1–16 cameras) Make sure that the board has the necessary number of ports when you use multiple cameras. See Install an Ethernet Board for GigE Cameras and Using Multiple GigE Cameras. Ethernet Interface in Laptop Computers If you have a laptop, you can connect only one GigE camera. The RJ45 Ethernet port on your laptop will be the dedicated camera port. If you want to connect the laptop to the internet, use a Wi-Fi connection or a USB-Ethernet adapter. Some laptops have a USB-C port for internet. In that case you need a USB-C to Ethernet adapter. However, not all of those adapters work properly when connecting a digital camera. There may be issues such as video signal interruption and frame drops. Test a few adapters if needed. --- ## EthoVision XT 19 - Software Installation - Install EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-install-ethovision-xt Chapter: EthoVision XT Install EthoVision XT Please Read This First - Installing EthoVision XT 19 does not replace previous versions (that is, EthoVision XT 17 and earlier). If you want to remove previous versions, do so in the Windows Control Panel > Programs and Features. - Close all other programs before installing EthoVision XT and turn off the screen saver and power save options. Check that programs do not run in the background (look in the system tray at the bottom right of your screen). We recommend to follow these procedures: Disable the Power save options, Disable fast startup, Turn off automatic updates for device drivers. - IMPORTANT: For users of Quality Assurance: If you have added EthoVision XT users in User Management and re-install the software, those users and their rights are deleted. Procedure - Browse to the MyNoldus portal and log in or register. If you are a new user you can use the registration code which you can find on the Welcome letter. - Click Versions and download the EthoVision XT - Installation Package [version number].zip. Save the zip file on your PC. Note: The Installation Package is a very large file; download may take some time. If you store the zip file on a network drive, copy it to your PC before the next step. - Unzip and extract the files on your computer. The zip file contains six installation files: - EthoVision XT - Setup - [version number].exe - EthoVision XT - Package - [version number].msi - Tracker Interface NN - x64 Package - [version number].msi - Tracker Interface NN - x64 Cabinet - [version number]-01.cab - Tracker Interface MST - x64 Package - [version number].msi - Tracker Interface MST - x64 Cabinet - [version number]-01.cab - Double-click EthoVision XT - Setup - [version number].exe. - Select the interface language. You have the choice between English (United States) and Chinese (Simplified). - Under Installation type, select Standard, then click Next. Select Custom if you want to specify the location for the program and the experiments other than those selected by default. - Application location: C:\Program Files\Noldus\EthoVision XT 19 - Experiments location: C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments IMPORTANT: Do not select a removable disc, like a USB memory drive, as the experiments location. - Under Drivers and Tools, select the drivers you want to install. - If you have USB 3.0 cameras, choose Basler USB camera driver. - If you have GigE Vision cameras, choose Basler GigE camera driver. - If you have analog cameras, choose Euresys Multicam. This works with the Picolo Alert encoder board. Note: If you need to re-install the drivers for your camera, you can find them on the MyNoldus support portal. See also Install the Driver Software for the Digital Cameras. - Click Next. Read the end-user license agreement. Select I agree with the End-User License Agreement and click Install. - When the message Installation is complete! appears, click Close. Notes - To view the manuals other than the EthoVision XT Help, you need a PDF reader like Acrobat Reader or Foxit Reader. - To uninstall EthoVision XT, do this from the Control Panel. See Uninstall EthoVision XT. See Also - Software Components Installed with EthoVision XT - Camera Installation - End-User License Agreement --- ## EthoVision XT 19 - Software Installation - Power over Ethernet (PoE) Injector URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-power-over-ethernet-poe-injector Chapter: EthoVision XT Power over Ethernet (PoE) Injector If you bought your GigE camera elsewhere and you are not using an Ethernet board powered from the PC, you need a Power over Ethernet (PoE) injector to power the camera. In all cases it must be a Gigabit PoE injector. USB 3.0 Interface Boards See Install the USB 3.0 interface board. Graphics Card for Deep Learning-Based Tracking If you intend to use the Deep learning technique for nose- and tail-base detection, you need a powerful NVIDIA Graphics Processing Unit (GPU). GPUs other than NVIDIA would not work due to lack of compatibility with the NVIDIA TensorRT software component. For suggestions, see Deep learning: Requirements. IMPORTANT Make sure to install the latest driver for your graphics card. Monitor Your monitor should be set to at least 24 bit color depth. If you use a dual monitor set-up, both monitors should be at least 24 bit. To check the color depth, search for Display in Windows or open the graphics control panel of your display. Camera For a list of the camera models currently supported, see Camera Installation. If you would like to use another type of camera, please check with your nearest Noldus representative first. IMPORTANT For correct functioning of cameras, we recommend to turn off automatic updates for device drivers. See Turn off Automatic Updates for Device Drivers. Disk Space to Store Video Files If you are tracking from video files, you need sufficient free disk space to store them. You need to be especially aware of the disk space when you let EthoVision XT save videos while you carry out batch acquisition and for long recordings. See Video File Size. If your video files are on a DVD or network drive, first copy them to your hard disk drive before loading them in EthoVision XT. External Hard Disk Drives - For tracking. We do not recommend that you do tracking from video files that are stored on an external hard disk. Always store the video files on the hard disk of the EthoVision XT computer. - For video playback. Once you have done tracking, you can store the video files on an external hard disk. When you want to review the video in the Integrated Visualization (see Plot Integrated Data), EthoVision XT asks you to locate the video files if it does not find them in the default experiment location on the hard disk. Select the folder on the external hard disk where the video files are stored. You can also instruct EthoVision XT to look for video files in an alternate folder. See also Preferences for Default Folders. NOTE Video might sometimes not play smoothly depending on the size of the video file and the speed of data transfer from the external hard disk. See Also - System Requirements - Restrictions in EthoVision XT - How to Prevent Missed Samples Network and User Rights Using EthoVision XT across a Network Please note that it is not possible to install EthoVision XT on one computer and access it from another across a local area network. The program must be installed on the computer where it will be used. However, you can work with EthoVision XT remotely using one of the remote control applications like TightVNC or TeamViewer. See Work with EthoVision XT Remotely. You can track from video files stored at other computers in your network (depending on your network's bandwidth), although we recommend to copy the file to your hard disk before tracking. To let EthoVision XT know where to find the video files, choose File > Preferences and select the location on the network in the Alternative Media Location field. Working with EthoVision XT as a Restricted User The user rights for folders and files are different for System administrators, Power users, and restricted (normal) users. Users who have Administrator rights and Power users have enough access rights to use EthoVision XT and its files without any limitations. For restricted users the following limitations apply: - As a restricted user you can create new experiments and view, edit and delete your own experiments. - If you want to make it possible for other users to edit or delete your experiments, your system administrator must change the Windows security rights for the folder that contains the experiments. By default this folder is C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments. For instance, to set the Modify rights to Everyone: in the Windows Explorer, select the folder mentioned above, right-click it, select Properties and then the Security tab and set the rights. --- ## EthoVision XT 19 - Software Installation - Preferences for Default Units URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-preferences-for-default-units Chapter: EthoVision XT Preferences for Default Units Aim To specify the default units for distance, time and rotation for future experiments. Procedure Choose File > Preferences > Default Units. - Unit of distance: choose between mm (millimeters), cm (centimeters), m (meters) or inch (inches). - Unit of time: choose between ms (milliseconds), s (seconds), min (minutes) or hr (hours). - Unit of rotation: choose between deg (degrees; °), rad (radians), grad (gradians; 1 grad = 9/10° or π/200 rad) or rot (rotations). Notes - EthoVision XT measures the distance between two points in pixels. With the Calibration procedure in Arena Settings, these are converted to distance values. - Changing the default units in Preferences does not affect the experiment currently open. To change the units in your present experiment, do so in Experiment Settings > Units. - Changing the units does not affect the raw data, only their presentation. Preferences for Language Aim To specify the language in EthoVision XT. You can choose between US English and Simplified Chinese. Procedure - Choose File > Preferences > Language. - Select either English (US) or Chinese (Simplified). - Click OK and restart EthoVision XT to apply the change. Preferences for Video Settings Aim To specify how video is processed during tracking. These settings are applied to all new experiments. Background Information In EthoVision XT 17.5 and later versions you can set playback of video to be done through the Graphics Processing Unit (GPU or dedicated graphics card) instead of the CPU. This allows greater performance, especially when tracking in demanding conditions like with Behavior Recognition. Up to EthoVision XT 17.0 it was only possible to playback video with the CPU. Procedure - Choose File > Preferences > Video settings. - Next to Play back and record video with, select either GPU (default) or CPU. - Choose GPU if you want the GPU to process video. - Choose CPU if you want the CPU to process video. - Click OK to apply the change. Notes - If you are in the middle of an experiment started with EthoVision XT 17.0 or an earlier version and some tracks were acquired before upgrading to EthoVision XT 19, you have two options: - Complete the experiment with the old playback method. Keep the option CPU selected (recommended). The reason is that if you choose GPU a video file could look slightly brighter than it would with CPU. In that case you would need to make new detection settings for the next trials. To keep consistent detection settings across trials, choose CPU. - Acquire all trials with the new playback method. Clear the existing trials (i.e., delete the tracks without removing the videos), and re-acquire all trials with the option set to GPU for consistency. See Redo a Trial. - For all new experiments, we recommend keeping the option GPU selected. - What option you choose next to Play back and record video with does not affect tracking based on Deep Learning, even though this relies on the GPU. So whatever option you choose, you can use the Deep Learning body-point detection technique, provided that your PC meets specific requirements. See Deep Learning: Requirements. See Also - Preferences License Agreement Topics and Tasks - End-User License Agreement - Acknowledgments and Copyright Notices End-User License Agreement Procedure To open a PDF copy of the End-User License Agreement, do one of the following: - Browse to the following file: C:\Program Files\Noldus\EthoVision XT 19\Documentation\Legal\End-User License Agreement.pdf - In EthoVision XT, choose Help > About EthoVision XT > License Info > End-User License Agreement. Notes - If you installed EthoVision XT in a folder other than the default one, browse to that folder and open ...\EthoVision XT 19\Documentation\Legal. See Also - File Locations - Acknowledgments and Copyright Notices Acknowledgments and Copyright Notices EthoVision® is a registered trademark of Noldus Information Technology bv. EthoVision XT would not be what it is without the use of third-party software. This page lists all software libraries and other software products used in EthoVision XT and where you can find license and compliance information and acknowledgments for that product. For the complete terms and conditions in PDF format, refer to the Acknowledgments folder, located by default at C:\Program Files\Noldus\EthoVision XT 19\Documentation\Legal\Acknowledgments. If you installed EthoVision XT in another location, refer to that location. - Boost — Open source (Boost community) software library, C++ templates. Boost Software License. - Euresys Multicam — Driver to address Picolo boards. Euresys Terms & Conditions. - FFmpeg — Cross-platform solution to record, convert and stream audio and video. GNU Lesser General Public License. - HASP — Library for software protection. EULA via Thales Group. - IPP, MKL, TBB — Software library for signal, image, speech and audio processing (Intel Corporation). Intel Simplified Software License. - LeadTools — Video encoder and decoder software. LeadTools License Agreement. Portions of EthoVision XT were created using LEADTOOLS ©1991-2021, LEAD Technologies, Inc. ALL RIGHTS RESERVED. Portions of this product are licensed under US patents 9,552,527, 10,318,563 and 10,576,653 and foreign counterparts. - LibTorch — C++ frontend for PyTorch machine learning framework. 3-Clause BSD License. - NVIDIA CUDA® — Parallel computing platform for general computing on GPUs. NVIDIA CUDA Toolkit EULA. - NVIDIA cuDNN — Library of primitives for deep neural networks. NVIDIA EULA. - NVIDIA TensorRT — SDK for deep-learning inference. Apache License 2.0. - OpenCV — Software library for various computer vision problems. Apache License 2.0. - Pylon Camera Software Suite — Driver for Basler cameras. Pylon End-User License Agreement. - QR Code Generator Library — Library for generating QR codes. MIT License. Project Nayuki. Source: EthoVision XT 19 Help - Software Installation, Noldus Information Technology --- ## EthoVision XT 19 - Software Installation - Software Components Installed with EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-software-components-installed-with-ethovision-xt Chapter: EthoVision XT Software Components Installed with EthoVision XT Components Installed Automatically The following components are installed automatically when you install EthoVision XT: - Noldus - Basler Pylon Interface - x64 Package - 1: version 1.1.12 (EthoVision XT 19), version 1.1.10 (EthoVision XT 17.5) - Noldus - Chart Wrapper Control - x64 Package - 3: version 3.0.6 (EthoVision XT 19), version 3.0.4 (EthoVision XT 17.5) - Noldus - Data Storage Converter - x86 Package - 1: version 1.0.10 (EthoVision XT 19), version 1.0.8 (EthoVision XT 17.5) - Noldus - Frame Counter - x64 Package - 2: version 2.0.2 (EthoVision XT 19), not included in EthoVision XT 17.5 - Noldus - HardwareInterface IoBox - x64 Package - 5: version 5.1.16 (EthoVision XT 19), version 5.1.10 (EthoVision XT 17.5) - Noldus - HardwareInterface UgoBasile - x64 Package - 1: version 1.0.14 (EthoVision XT 19), version 1.0.10 (EthoVision XT 17.5) - Noldus - ImporterInterface LMT - x64 Package - 1: version 1.0.8 (EthoVision XT 19), version 1.0.6 (EthoVision XT 17.5) - Noldus - IPP - x64 Package - 8: version 8.2.4 (EthoVision XT 19), version 8.2.2 (EthoVision XT 17.5) - Noldus - LeadTools - x64 Package - 21: version 21.0.14 (EthoVision XT 19), version 21.0.8.0 (EthoVision XT 17.5) - Noldus - MBRM Interface - x64 Package - 2: version 2.0.6 (EthoVision XT 19), version 1.3.2 (EthoVision XT 17.5) - Noldus - MediaLooks ScreenCapture - x64 Package - 2: version 2.0.4 (EthoVision XT 19), version 2.0.4 (EthoVision XT 17.5) - Noldus - ParameterInterface LMT - x64 Package - 1: version 1.0.10 (EthoVision XT 19), version 1.0.8 (EthoVision XT 17.5) - Noldus - RBRM Interface - x64 Package - 2: version 2.0.6 (EthoVision XT 19), version 1.3.2 (EthoVision XT 17.5) - Noldus - Resizer Filter - x64 - Package - 13: version 13.1.10 (EthoVision XT 19), version 13.1.6 (EthoVision XT 17.5) - Noldus - SampleGrabber - x64 Package - 15: version 15.0.4 (EthoVision XT 19), version 14.0.2 (EthoVision XT 17.5) - Noldus - Tracker Interface NN - x64 Package - 2: version 3.0.8 (EthoVision XT 19), version 2.0.10 (EthoVision XT 17.5) - Noldus - Tracker Interface MST - x64 Package - 1: version 1.0.12 (EthoVision XT 19), not included in EthoVision XT 17.5 - Sentinel Runtime: version 8.11 (both EthoVision XT 19 and EthoVision XT 17.5) - Microsoft Visual C++ 2015-2019 Redistributable (x64) / (x86): version 14.29 (*) (EthoVision XT 19), version 14.29 (EthoVision XT 17.5) To view the components currently installed on your computer, from the Windows Start menu choose Settings > Apps > Apps & features. Sort the list by install date and locate the items installed with EthoVision XT. (*) Not installed if a newer version is already present on the PC. Additional Components The list of components under Apps and features also includes camera drivers and drivers for the PCIe interface boards. These are usually installed when you install EthoVision XT. See also Cameras Supported by EthoVision XT. - pylon 7 Camera Software Suite: version 7.5.0.15658 - Daheng Galaxy SDK: version 1.12.2102.9251 - Euresys MultiCam: version 6.15.1.3573 - Noldus - HardwareInterface SerialPort - x64 Package - 1 (*): version 1.1.6 (*) You need this component to be able to control hardware devices through a serial (COM) port. You find this component on the EthoVision XT full installation disk, under Drivers and Tools. For more information, see Set the Port Connections for COM Ports in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Notes - To view the components currently installed on your computer, from the Windows Start menu choose Settings > Apps > Apps & features. Sort the list by install date and locate the items installed with EthoVision XT. - There may be components installed with previous EthoVision XT versions: - Noldus MainConcept Encoder Package 7.7 (for recording video) - Noldus MainConcept Codec Package 8.5.34 (for playback of video files) - Noldus MediaLooks AV Filter 5.0.1.0 - Components similar to those listed in the table above, but with a lower version number (for example, Sample Grabber 13) Please keep them only if you still use previous versions of EthoVision XT. The MainConcept software has been replaced by the LeadTools software in EthoVision XT 16 and 17. - To add a component, like a camera driver or the video tutorial, that is not installed yet on your computer, double-click the file EthoVision XT - Setup - [version number].exe (see Install EthoVision XT) and select Custom, then Modify. Select the component you require and click Update. - The Euresys Picolo U4/U8 H.264 encoder boards are no longer supported with EthoVision XT. Those boards do not work on 64-bit software. See Also - Camera Installation - End-User License Agreement EthoVision XT Trial Version Aim To evaluate the full functionality of EthoVision XT for a limited period of time (14 days). Prerequisites - You have received a Software Activation Key from your Noldus Sales Representative. - You have downloaded and installed the EthoVision XT trial version. - By downloading the trial version you agree: - That you shall only use the trial version to review EthoVision XT. - That you shall not acquire data that you use to produce scientific research and/or publication. - That you shall not hand over or sell the trial version to a third party. To Start a Trial Version - Start EthoVision XT. A message appears that no valid license key is detected. - Click Activate software license key. - Choose whether to activate a Computer-locked license or a Floating license. See Types of EthoVision XT License. - Activate Online is automatically selected as that is the only option available. Type in the Activation key that you received and click OK. Notes - The EthoVision XT trial version is fully functional and includes all add-on modules as the full license, like Multiple Arenas, Social Interaction and Behavior Recognition, except the Quality Assurance Module and Track3D. See Modules of EthoVision XT. - To check the number of days left for evaluation, choose Help > About EthoVision XT. When the trial period is over, a message is shown. - Experiments from the EthoVision XT trial version cannot be opened in previous versions of EthoVision XT. See Also - Install EthoVision XT - Activate Your EthoVision XT License --- ## EthoVision XT 19 - Software Installation - Software Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-software-installation Chapter: EthoVision XT Software Installation Overview Complete your experiments and make a backup of all of them before installing the new version. Main Topics and Tasks - System requirements - Install EthoVision XT - License activation - Upgrade EthoVision XT - Preferences See Also - Camera Installation - End-user license agreement System Requirements Before You Install EthoVision XT If you ordered a computer from Noldus Information Technology when you purchased EthoVision XT, the software and any internal hardware has already been installed and tested. If you did not order a computer, you must install EthoVision XT from the MyNoldus portal. See the Welcome Letter for more information. Prior to installation, please check the packing list to make sure all the components are present. If any of the components listed is missing or damaged, please let us know. The contents of your package differ for new and existing users: - If you are a new EthoVision XT user, you received a Software Activation Key. - If you are upgrading from older versions of EthoVision XT, you received a Software Upgrade Key to upgrade your current license. See Upgrade EthoVision XT. Learn About - Operating system - Hardware - Network and user rights See Also - Restrictions in EthoVision XT - Camera Installation - EthoVision XT and Quality Assurance Operating System Windows Version EthoVision XT 19.0 supports Microsoft Windows 11 Pro and was tested with Windows 11 Pro, 64 bits, version 23H2. EthoVision XT 19 was also installed on Windows 10 Pro, version 22H2 and Windows 11 Pro, version 24H2 for short tests unrelated to the assessment of tracking performance with specific camera configurations. Although no significant issues were reported, Noldus cannot guarantee that the same performance as on Windows 11 can be obtained on these versions when using a specific camera configuration. See Resolution, Frame Rate, and Maximum Trial Duration. EthoVision XT is not designed for use with the Touch features of Windows. User Rights To install EthoVision XT, you must have administrator rights. In other words: either you are the system administrator or you are a member of the Windows group Administrators and have been assigned administrator rights. We recommend turning off automatic updates for device drivers. See Turn Off Automatic Updates for Device Drivers. We also recommend not using a comma as a decimal separator in the Windows regional settings. To check the regional settings, in Windows choose Apps > Windows System > Control Panel. Under Clock, Language and Region, click Change date, time or number formats, then click Additional settings. Language Support EthoVision XT has also been tested with Cyrillic, Japanese, and Chinese language packs. Like any software package, it remains possible that minor differences in the operating systems of certain local language versions may affect how well the program runs. If you encounter a problem of this sort, please contact Noldus Technical Support. Windows Update There have been cases of EthoVision XT trials being interrupted by forced Windows Update. It is not straightforward to prevent unwanted updates during data acquisition, especially in Windows 11. If you plan to do long data acquisition sessions (e.g. 24+ hours), an easy solution is to disconnect the EthoVision XT computer from the network and restart it before starting the new acquisition session. --- ## EthoVision XT 19 - Software Installation - Types of EthoVision XT License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-types-of-ethovision-xt-license Chapter: EthoVision XT Types of EthoVision XT License There are two main types of EthoVision XT license: - License on a hardware key - Software license key In all cases, to find out which modules your license includes, choose Help > About EthoVision XT > License Info. License on a Hardware Key Your EthoVision XT license is stored on a USB key. A USB key looks similar to a USB flash drive, but does not include any disk storage space. Important: Make sure that you do not lose the hardware key. You will need to pay for a new license if you do. Please handle the hardware key with care, as it is sensitive and can be easily damaged. In order to use the full functionality of EthoVision XT on either one computer or another, you must plug the hardware key into that computer. Alternatively, you can start EthoVision XT without a hardware key plugged in and work in Analysis mode to analyze trials already acquired, but not acquire new trials. See EthoVision XT in Analysis Mode. Software License Key A software license key allows you to use EthoVision XT without a hardware key plugged into your computer. Important: Your software license key is coupled to the hardware of your computer, not to a specific user or user group name. A software license can be of two types: Computer-Locked and Floating. Computer-Locked License This license is meant to be used on a specific computer for an extended period. It is a fixed-seat license associated with that computer. This association is registered on the Noldus Server. In order to use a computer-locked license on another computer, you must first deactivate that license on the computer where it is currently active. See Deactivate an EthoVision XT License. Floating License This license is useful when you want to use EthoVision XT to acquire data and video on two or more computers, though not simultaneously. - For example, you can activate a floating license on two computers: one in the lab for recording video, and one in the office to acquire tracks from the resulting video files. - If you always record data and video on the same computer in the lab and analyze or visualize data on your laptop in the office, a floating license may not be needed. You can activate a computer-locked license on your lab computer to acquire data and video, and install EthoVision XT on your office computer to use it in Analysis mode. See EthoVision XT in Analysis Mode. - With a floating license you can work on one computer at a time. Make sure that EthoVision XT is closed on all computers other than the one you are currently using. - Important: In order to work with a floating license, your EthoVision XT computer must be connected to the internet. When you close EthoVision XT on one computer with a floating license, the license is automatically deactivated, provided that the computer is connected to the Noldus Server. At that point you can start using EthoVision XT on another computer. Licensing and Preferences Floating License Offline Use With a floating license you can work offline with EthoVision XT for a maximum of 90 days. After that, you must re-connect the EthoVision XT PC to the internet in order to continue to work with the software or to deactivate the license and make it possible to use the license on another PC. Notes on License Requirements - If the hardware key is not plugged in to your PC or the software license is not activated, you can still start EthoVision XT and work in Analysis mode. This means that you can analyze and visualize previously-recorded data, but cannot acquire more data. Duration of the EthoVision XT License An EthoVision XT license can be one of the following types: Perpetual License This is the most common license. You purchase a copy of EthoVision XT on a one-time basis and can use the software forever. Time-Limited License This license is generally valid for a period of six or twelve months. - A time-limited license can only be activated online. Trial License This is a temporary, free-of-charge license that you can use to evaluate the newest version of the software. - A trial license can only be activated online. EthoVision XT in Analysis Mode Aim To carry out analysis and visualization of already-existing track data in EthoVision XT without a license. Background Information An EthoVision XT license is needed whenever you acquire new data and record video. So it is important to activate a license on the computer that you use to collect data. However, you can also install EthoVision XT on other computers without a license. If an experiment already contains data, you can open it in EthoVision XT, filter data, calculate statistics and make charts and heatmaps. For example, collect the data in your lab. Copy the experiment to your laptop where you have installed EthoVision XT without a license. There you can visualize and analyze your data. Procedure - If you have not done so yet, install EthoVision XT on a computer. - Start EthoVision XT. - If EthoVision XT does not find a valid license, a window opens with the message Your license. - Choose Start in analysis mode. What You Can Do in Analysis Mode EthoVision XT in analysis mode offers all the functions necessary to refine analysis and produce results. - Add new zones and modify existing zones in the Arena Settings. - Edit tracks in the Track Editor screen. For example, remove outliers before running analysis. - Create behavioral categories in the Manual Scoring Settings, and score those categories manually while reviewing existing video. - Adjust the Track Smoothing settings. - Create new Data profiles and select data. - Create new Analysis profiles and select dependent variables. - Use all the analysis functions under Analysis > Results. - Export data and results. - Make a backup of your experiment. Furthermore you can create new Detection Settings profiles, create new Trial Control Settings profiles, and add trials and variables in the Trial List. Notes - To return to or start a full license, you must first deactivate the analysis mode. Close the experiment, then choose Help > Deactivate License, then click Continue. Next, restart EthoVision XT. --- ## EthoVision XT 19 - Software Installation - Uninstall EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-uninstall-ethovision-xt Chapter: EthoVision XT Uninstall EthoVision XT Aim To remove EthoVision XT, drivers and other components from the computer. Note: If you have a computer-locked license or a floating license and want to use that license somewhere else, first deactivate the license, then uninstall EthoVision XT. See Deactivate an EthoVision XT License. Procedure - In the Windows Search screen, search for programs or apps and select Programs and Features or Apps and Features (depending on the Windows version). - In the Programs/Apps and Features window, select EthoVision XT 19 and click Uninstall. - To make a complete uninstall, also select and uninstall each of the components installed with EthoVision XT. Sort the programs list by Installed On and look for the components installed on the same day as EthoVision XT. See Software Components Installed with EthoVision XT. Notes - When you uninstall EthoVision XT, your software license stays on that computer. So if you re-install the software on that computer you do not have to re-activate it. See Also - Install EthoVision XT - Software Components Installed with EthoVision XT License Activation What Do You Want to Do? - Activate Your EthoVision XT License - Deactivate an EthoVision XT License - Software License - Offline - Turn a Floating License to a Computer-Locked License - Turn a Computer-Locked License to a Floating License Learn About - Types of EthoVision XT License - Duration of the EthoVision XT License - EthoVision XT in Analysis Mode Activate Your EthoVision XT License Aim To activate an EthoVision XT license after purchase. Note that you do not need to follow this procedure if your license is on a USB hardware key. If you have already an EthoVision XT license and you purchased a new add-on module, see Add New Modules to Your License. Background Information When you start EthoVision XT, the software checks that your license is valid. The license may be stored in your hardware key (dongle), in your EthoVision XT computer (Computer-locked license) or in the Noldus server (Floating license). See Types of EthoVision XT License. If no valid license is found, you can activate your license by following the procedure below. Important Terms Activation Key: An activation key is provided by Noldus to activate your license. You find an activation key on a letter or email sent to you. Computer Key: A computer key comes into play when you activate your license offline. This is a key that identifies the computer that you are using during activation. License Key: A license key is the unique piece of information that you obtain after you activate the license. You can find this key in EthoVision XT by choosing Help > About EthoVision XT > License Info. See Types of EthoVision XT License. Computer-Locked License: This is a license that is bound to a specific computer. It is a fixed-seat license intended to be used for a long time in the same location. However, when necessary, you can easily transfer this license to another computer. See Types of EthoVision XT License. --- ## EthoVision XT 19 - Software Installation - Upgrade EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-upgrade-ethovision-xt Chapter: EthoVision XT Upgrade EthoVision XT Aim To activate the license for a newer version of EthoVision XT. Prerequisites - You have an older version of EthoVision XT (17.5 or earlier) and you have just purchased a new EthoVision XT 19 license. - You received a code (named Upgrade Key) from Noldus, either on the Welcome letter or by e-mail. - If you have a USB hardware key, insert that in a USB port of your EthoVision XT computer. Procedure for a Software-Based License - Download and install EthoVision XT from my.noldus.com. You do not need to uninstall previous EthoVision XT versions. - Start EthoVision XT. - Choose Activate software license key. - Choose whether to activate online or offline and follow the instructions on the screen. Procedure for a License Stored on the Hardware Key - Download and install EthoVision XT from my.noldus.com. You do not need to uninstall previous EthoVision XT versions. - Start EthoVision XT. - Enter the Upgrade Key that you received from Noldus and complete the upgrade procedure. Add New Modules to Your License Aim To update your EthoVision XT license after you have purchased one or more add-on modules, for example: - The Multiple Arena module. - The Rat Behavior Recognition module. Prerequisites - If you have a software license, the EthoVision XT computer must be connected to the internet, or you have a smartphone connected to the internet. - If you have a license stored on a hardware key, insert the hardware key in a USB port of your EthoVision XT computer. Software License - Online If your EthoVision XT computer is connected to the internet, the license is updated automatically the next time that you start the software. You do not have to take any further action. Software License - Offline - Start EthoVision XT. - Choose Help > Reactivate Offline. - In the window that appears, click the Deactivate button. - A QR code appears on the right. Scan that QR code with your smartphone. - Tap the link that appears on the smartphone, then on the smartphone tap Deactivate. The web page that opens on the smartphone shows your current license key and a code that identifies your computer. You will notice nothing changes after you have clicked Deactivate on the smartphone screen. That is ok. - On the computer screen, click Scanned. - A new QR code appears. Scan this code and tap the link that appears on the smartphone. - On the computer screen, next to Computer key, enter the code that appears on the smartphone. - A message informs you that the license has been activated, and the software closes. You can now start EthoVision XT and work as usual. License Stored on a Hardware Key - Start EthoVision XT. Make sure that no experiment is open. - Choose Help > Upgrade. - Enter the Upgrade Key 1 and, if that applies, the Upgrade Key 2 that you received from Noldus. - Click OK to complete the upgrade procedure. Notes - To know which modules are included in your current license, choose Help > About EthoVision XT > License Info. Preferences Aim After installing EthoVision XT, it is a good idea to set general preferences, for example where to store the experiments, the default measurement units, and so on. The options under Preferences are at the application level, meaning they are applied to all new experiments. However, default units can also be changed per experiment. Procedure Choose File > Preferences. The following preference categories are available: - Preferences for default folders - Preferences for warnings - Preferences for auto save - Preferences for default units - Preferences for language - Preferences for video settings Notes - To return to the default settings, click the Defaults button. This resets the default experiment folder to the location specified during installation, selects all warnings, and re-enables auto save with an interval of 5 minutes. - When you click the Defaults button with the Default Folders tab open, the preferences for warnings, auto save and default units are also reset, and vice versa. Preferences for Default Folders Procedure Choose File > Preferences > Default Folders tab. Default Folder Location Click Browse to specify a default location for new experiments. The initially suggested location is the location specified during installation. Alternative Media Location When visualizing and animating tracks, EthoVision XT needs the corresponding video files. If EthoVision XT does not find the video files in the Media Files folder of the experiment, it looks in the folder specified under Alternative media location. This can happen, for example, when you copy an experiment to another computer and the video files are not stored in the Media Files folder of the experiment but in a different folder external to the experiment, or even on a different drive. When you open the experiment on the second computer, EthoVision XT does not find the video files. To have EthoVision XT look for videos in an additional location, click Browse and select the correct location. Preferences for Warnings Aim To enable or disable a warning that appears after you perform a certain action. Procedure Choose File > Preferences > Warnings. Preferences for Auto Save Aim To enable or disable auto save of data and settings. Procedure Choose File > Preferences > Auto Save. Select Enable auto save. Enter the time interval at which you would like to save your data. Notes - Auto save saves all data (tracks, independent variables, detection settings, data and analysis profiles, and so on), just like when you save the experiment manually by choosing File > Save Experiment or pressing Ctrl+S. - Auto saves during acquisition are suspended to prevent auto save from interfering with data acquisition. --- ## EthoVision XT 19 - Software Installation - Work with EthoVision XT Remotely URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-software-installation-work-with-ethovision-xt-remotely Chapter: EthoVision XT Work with EthoVision XT Remotely Aim You can use utilities like TightVNC or TeamViewer to control EthoVision XT fully remotely. Prerequisites - When using a hardware key, remember to leave the hardware key plugged in the EthoVision XT computer before you leave work if you need to acquire data (i.e., do tracking). However, if you only need to do post-acquisition data analysis and export, you do not need to leave the hardware key inserted. This may actually free up the hardware key to be inserted in another computer at work running EthoVision XT so another user can use it for data acquisition. See EthoVision XT in Analysis Mode. - When using a software license, make sure that the license on the EthoVision XT computer is active. See Activate Your EthoVision XT License. Procedure - Leave the EthoVision XT computer running. - On the remote computer use a utility to access EthoVision XT on that PC. - Only one user can access a remote EthoVision XT computer at any one time. Of course you can install EthoVision XT on multiple PCs so multiple users can work with EthoVision XT. TightVNC IMPORTANT You must have a VPN connection to the network where the PC you are connecting to is located. - Download the installer of TightVNC for Windows from the TightVNC website and run it on the PC with EthoVision XT. Use the Full install to install both the Viewer and the Server. Use the default install, but set the passwords for security. - Restart the PC, and leave it running in order to be able to connect to it. - Install the Viewer on the PC you want to work with. - Make the connection to the Local Network where the remote computer is running. - Run the Viewer and type the name or the IP address of the PC you want to connect to. - Enter the password. You can view the desktop of the remote PC in a window. TeamViewer - Download TeamViewer for Windows. - When installing TeamViewer on both the work PC and your remote PC, make sure to select Unattended Access. - Open TeamViewer on the workplace PC. On the General tab under Unattended Access, select Start TeamViewer. - Write down the Partner ID (or Your ID) and Password (or take a photo of the screen). - Before leaving your workplace, launch TeamViewer and leave it running. Install EthoVision XT Please Read This First - Installing EthoVision XT 19 does not replace previous versions, for example EthoVision XT 17. - You can keep working with both versions. However, if you have completed your experiments in the previous version, you can uninstall that previous version. - We recommend that you complete your experiments and make a backup of all of them before you open them in a new version of the software. See Back Up an Experiment. - Removing or installing EthoVision XT does not remove your experiments and data already stored on that computer. What Do You Want to Do? - IMPORTANT Turn off Automatic Updates for Device Drivers - IMPORTANT Disable Fast Startup - IMPORTANT Disable the Power Save Options - Install EthoVision XT See Also - Uninstall EthoVision XT - Upgrade EthoVision XT - Read the End-User License Agreement - Acknowledgments and Copyright Notices - EthoVision XT Trial Version Turn off Automatic Updates for Device Drivers Aim To make sure EthoVision XT works with the drivers that were tested by Noldus. Although the general recommendation from Microsoft to use automatic updates is good, especially for security updates, automatic updates of hardware device drivers can sometimes give problems. Follow this procedure to specifically turn off the automatic updates only for device drivers. Procedure - Click the Windows Start menu and type change device. - Click Change device installation settings in the search results under Best match. - In the Device installation settings window, select No (your device might not work as expected). - Click Save Changes. Note There have been cases of EthoVision XT trials being interrupted by forced Windows Update. It is not straightforward to prevent unwanted updates during data acquisition, especially in Windows 11. If you plan to do long data acquisition sessions (e.g. 24+ hours), an easy solution is to disconnect the EthoVision XT computer from the network and restart it before starting the new acquisition session. Do not forget to recover internet connection after you complete your trials. See Also - Disable Fast Startup - Disable the Power Save Options - Install EthoVision XT Disable Fast Startup Aim To disable the Fast startup option in Windows 10/11, which can have an adverse effect on EthoVision XT performance. Procedure - Click the Windows Search icon on the taskbar and enter control panel. - Click Control Panel, choose System and Security > Power Options. - Click Choose what the power buttons do in the upper left corner. - Click Change settings that are currently unavailable (this may require an administrator password). - De-select the options Turn on fast start-up, Sleep, and Hibernate. See Also - Turn off Automatic Updates for Device Drivers - Disable the Power Save Options - Install EthoVision XT Disable the Power Save Options Aim To prevent the computer from being put to sleep or the hard disk from being turned off during tracking. Procedure - Click the Windows Search icon on the taskbar and type edit power plan. - Click Edit power plan when it appears in the search results. - Click Change advanced power settings. - Under Hard disk > Turn off hard disk after, select 0 (Never). For laptops, select Never for both On battery and Plugged in. - Click OK. See Also - Turn off Automatic Updates for Device Drivers - Install EthoVision XT --- ## EthoVision XT 19 - Sort the results table URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-sort-the-results-table Chapter: EthoVision XT Sort the Results Table Aim - To sort the results table based on the row headers. - To sort the results table based on the values in a column. - To change the order of and group the dependent variables in the results table. Prerequisites - You have run analysis (Analysis > Results > Statistics and Charts). Procedure Sort the Table Rows Based on Their Headers Example: Sort the results table based on the header Treatment, an independent variable with values Drug and Vehicle. - Click the Layout button and under On Rows move Treatment to the highest position in the list. See Modify the Layout of the Results Table. - Right-click one of the headers you want to sort, and select Sort Ascending or Sort Descending. Note: If you sort the rows based on the headers on the second, third, etc. column, the rows are sorted only within that level, not globally. For example: to have all rows marked with Subject 1 at the top of the table, then all rows with Subject 2, etc., click the Layout button and move Subjects to the top of the list under On Rows, then sort the subject headers. Sort the Table Rows Based on the Cell Values Example: Sort the table based on the values of Frequency of zone entries. Right-click one of the cells containing the values you want to sort, and select one of the two sorting options. Sort the Dependent Variables in the Results Table Example: Sort the results table by the dependent variables; first Distance moved, then Movement, and then In zone. - Click the Show/Hide button at the top-right corner and select Dependent Variables. - In the window that appears, select a dependent variable and click the Up and Down buttons to move a variable to a higher or lower position in the table. Result: The dependent variable at the top of the list in that window is shown in the first row or column in the results table. How to Read the Group Charts Charts are generated automatically from the results in the Group Statistics & Charts table. In this example, charts are generated for the dependent variables Distance moved (shown on top), Velocity, and In zone (on the other two tabbed pages). The horizontal axis shows the zones (In Border and In Center). Two data series (from the result containers Control and Treated) are plotted. Chart Tabs Each tab refers to a dependent variable defined in the Analysis Profile. A tab may contain one or more charts, one for each Trial Statistic specified for that dependent variable. Notes - A chart is not created for the trial statistics Standard Deviation, Standard Error, and Variance. - Charts in EthoVision XT have limited formatting options and are mainly meant for inspection purposes. If you want to make a chart for a publication, export the statistics table to Excel or a statistics program. - If you delete a dependent variable and subsequently add it again to the Analysis Profile, the properties of the new chart are set to default. - Chart settings are stored for each combination of data profile and analysis profile. If you make an exact copy of a data/analysis profile, the resulting charts have default settings. - Effect of Data selection: Results per time bin — If in the Data Profile you specify Results per time bin, time bins are always shown on the horizontal axis. The first value is 0:00:00 and represents the results calculated in the first time bin (for example, from 0 s to one minute). - Effect of Data selection: Results per zone — If in the Data Profile you specify to Calculate the results per zone, you can show the zones on the horizontal axis or as data series. See Customize the Group Charts. - If you specify both time bins and results per zone, time bins are displayed on the horizontal axis and zone statistics as data series. - If you specify more than 1000 time bins in your Data Profile, the group charts are not displayed. To Export Group Charts You can export one chart at a time. To export a chart as an image file, do one of the following: - Right-click the chart and select Export Chart. - Click the chart and then click the Export Chart button just above the chart. The default file name is the same as the chart title. Four formats are available: Portable Network Graphics (*.png), JPEG file (*.jpg), Windows Bitmap (*.bmp), and Graphics Interchange Format (*.gif). To copy the chart to an external program, right-click the chart and select Copy, then paste it into the other program. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Sub-rules and Conditions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-sub-rules-and-conditions Chapter: EthoVision XT Examples of Start-Stop Trial Rules Start Data Recording at a Specific Time You want to start recording at a time you are not in the lab, for example at 23:00 h. Delete the default Start track condition. Define a Time condition. Select At clock time and enter 23:00:00. Click OK and place the resulting box before the Start track box. Before leaving the lab, click the Start trial button to start the trial. The program waits till 23:00 to start data recording. Stop Data Recording After the Maximum Time Has Elapsed Click Settings in the Condition box immediately before the Stop track box. Select After and enter the maximum time. Note: Instead of using a Time condition, you can also use the Maximum trial duration option. Water Maze: Stop the Trial When the Animal Has Found the Platform In the Arena Settings, make sure that the platform has been defined as a zone. In the Trial Control Settings, delete the default Stop track condition. Next, define an In Zone condition. - If you want the program to stop recording as soon as the animal is over the platform, select Frequency as Statistic and choose >= 1. Click Settings and select the platform zone. - Sometimes the animal swims over the platform but does not stop there. In such cases the program would stop recording while the animal has not found the platform. Instead of selecting Frequency, choose Current duration and the minimum time the animal must stay on the platform (for example, 3 seconds). Click Settings and select the platform zone. Click OK and place the resulting box before the Stop track box. Water Maze: Stop the Trial Either When the Rat Has Found the Platform, or When It Has Been Swimming for 60 Seconds The Arena Settings and the condition In platform zone are similar to those in the example above. The condition subject swimming for 60 s can be translated to Time >= 60 s. The track stops when either condition is met. The two conditions are combined with OR logic. This solution results in tracks of different duration: less than 60 s for the animals that found the platform, and 60 s for the others. Tip: Instead of two Condition boxes in the example above, you can also define the In zone condition box and set a Maximum Trial duration. Multiple Open Fields (Multiple Arenas): Starting Tracking When the Subject Is Released in the Open Field Tracking starts independently in each open field. In this setup, four open fields are treated as separate arenas. You want to start acquisition when the animal is detected in the open field independent of what happens in other arenas. This can be achieved by using the default Start-Stop trial rule. As soon as the subject is detected in an arena, tracking starts for that arena, not the others. This way you do not have to release all the animals at the same time. Conditioning Test: Stop the Trial When the Conditioning Task Has Been Repeated N Times For example, when the animal has obtained 25 rewards. - Create a new sub-rule containing the instructions for the testing session. Sub-rule Begin - Condition: Is subject on top of the shelter? - Action: Drop a pellet - Sub-rule End. Since the sub-rule is restarted immediately after the pellet has been dropped, it is possible that the animal is still on top of the shelter, and a new pellet is dropped before the animal eats the previous one. Therefore, you must make sure that the sub-rule ends when the animal has visited the reward zone, so the sub-rule can be repeated from that moment onward. You can do this by defining a condition "In Feeder zone" that is met when the animal has been in the Feeder zone for at least 1 s without break (Current duration >=1 s). Place this box to the left of Rule End. - Create a Reference to the sub-rule and specify to have the sub-rule repeated 25 times. Place the resulting box at the left side of the Stop track box. Eight-Arm Radial Maze: Stop the Trial When the Subject Has Been in Four Arms Within 10 Minutes Combine eight conditions, one for each arm. At least four conditions must be met, no matter which arm the animal visits. - Create an In zone condition and specify that the Frequency for Arm 1 must be >=1. That is, the animal must have visited Arm 1 at least once. Do the same for each of the other arms. - Connect the resulting eight condition boxes in parallel using the N of All operator. - Set the Maximum trial duration to 10 minutes to stop tracking in the case the animal fails to visit four arms in the meantime. Important: The frequency of In zone can become high very easily when the animal walks along the edge of a zone. This may result in the condition being met sooner than expected. If that happens, increase the Zone exit threshold. If that does not help, open the Detection settings and click Advanced, then under Smoothing set Track noise reduction to On. This smooths the track. Sub-rules Use Sub-rules A sub-rule is a sequence of actions and conditions separated from the Start-Stop trial rule. You can view a sub-rule like a subroutine in a larger program, where the program is your Trial Control. - You can have the sub-rule start at specific times or under specific conditions. Each criterion defined is a Start condition of the sub-rule. - A sub-rule can be repeated. When EthoVision finishes executing the instructions contained in the sub-rule, the program can start the sub-rule again from the beginning, for a specified number of times or until a condition is met. - You can also have the same sub-rule called from different points of the Trial Control sequence. To do so, define multiple References to the same sub-rule. Why Use a Sub-rule? A sub-rule is necessary when your trials involve repetition of tasks. For example, when the animal has to press a lever to obtain a reward, and you want to repeat that 50 times. This is not feasible within the Start-Stop trial rule. A sub-rule is also handy when your Trial Control logic is very complex, because it helps you have a clear overview of the phases within your trial. For example, different tasks within a trial can be kept separated and managed more easily. Create a Sub-rule - In the Components pane, under Structures, double-click Sub-rule, or click the button next to it. - If the Add a sub-rule window appears, choose one of the following: - Create a new sub-rule. This creates a new sub-rule. You will be asked to enter a unique name for this sub-rule. - Reuse an existing sub-rule. Choose this option if you want to re-use an existing sub-rule. Select the existing sub-rule and, if necessary, the Trial Control Settings where it is stored. Note: You only copy the sub-rule name, the Rule Begin and the Rule End boxes, not the actions and conditions inside the existing sub-rule. - Under Name, enter a name for the sub-rule. The default name is Sub-rule (n) where n is a progressive number. - Under Comment, enter a description of the sub-rule (optional). - Click OK. The sub-rule is displayed on your Trial Control screen. It consists of a Rule begin box and a Rule end box. - Complete the sub-rule by inserting the appropriate conditions and actions between the Rule Begin and Rule End boxes. - Define a reference to this sub-rule (see the next section). Notes: - Sub-rule names. Names of sub-rules must be unique in your Trial Control Settings. You cannot define two sub-rules with the same Name, even if these are defined in two different Trial Control Settings. However, you can create a sub-rule with the same name of an existing sub-rule stored in other Trial Control Settings by re-using it. - Re-using a sub-rule. If you choose to re-use a sub-rule and then change any property of this copy (Name or Comment), a window appears with the message Define the scope of your changes. The program asks you whether you want to apply the properties only to the newly-created sub-rule, or to the sub-rules with the same name in all Trial Control Settings. Choose the option you require and click OK. - Deleting a sub-rule. You cannot delete a sub-rule if at least one reference to that sub-rule is present in the Trial Control. You must first delete its reference. - If you create a sub-rule without a valid reference, you can still acquire data but EthoVision informs you that trial control may not work as expected. Create a Reference to a Sub-rule A Reference calls the instructions contained in an existing sub-rule. - Make sure that the sub-rule has been defined in the Trial Control screen. - In the Components pane, under Structures, double-click Reference or click the button next to it. If the Add a reference window appears, choose one of the following, then click OK. - Create a new reference. To create a new reference to a sub-rule. - Reuse an existing reference. Choose this option if you want to make a copy of an existing reference. Select that reference and, if necessary, the Trial Control Settings where it is stored. - The Sub-rule Reference window appears. Under Name, enter a name for the reference. The default name is Reference (n), where n is a progressive number. - Under Reference, from the Reference to sub-rule list select the sub-rule you have defined. - Under Schedule, the Start conditions box shows Without delay. This means that, by default, the sub-rule starts as soon as the reference box becomes active. You can define one or more start conditions. Once the sub-rule starts according to Start condition, you can have it be repeated one or more times. Click the Add button to add a Start condition. The Add Start Condition window appears. - From the Select type list, select one of the following: - Without delay. To start the sub-rule as soon as the reference is activated. - Delay (default). To start a specific time after the reference becomes active. Enter this time in the Delay field. - Clock Time. To start at a specific day and time. - Trial Control variable. To start when a Trial Control variable gets a specific value. - Repeat steps 5-6 to add more start conditions. If you want to delete a start condition, select it and click the Delete button. - Under Stop conditions, select one of the options to specify whether you want the sub-rule to be repeated once or more times. - If you select to repeat the sub-rule, the Repeat interval option becomes available. Select: - Stop to Start (default). To keep a constant time between the stop of a repeat and the start of the next repeat. - Start to Start. To keep a constant time between the start of successive repeats. For example, start repeats at every hour. Enter this time in the corresponding box (hh:mm:ss). - Select one of the options to specify what to do when a new start condition becomes true and a previous repeat is still ongoing. - Under Comment, enter a description of the sub-rule reference (optional). - Click OK. The reference box is displayed on your Trial Control screen. - Insert the reference box in the appropriate place in the Trial Control sequence (this can be either the Start-Stop trial rule, or another sub-rule). Notes: - If you want the sub-rule not to start immediately as its Reference becomes active, select Without delay and click the Delete button. - If you accept the default options (Without delay in the Start conditions box and one repeat), the sub-rule starts immediately and is repeated just once. - You cannot edit a condition that you have added to the Start conditions box. Delete the condition first (select the condition and click the Delete button), then click Add to add a new condition. - The Start conditions are listed in the following order: Without delay, Delay, Clock Time, Trial Control variable. - Stop to Start of a repeat. There is always at least 1 sample difference between the time that the Rule End box is evaluated and the time that the Rule Begin box is evaluated for the start of a new repeat. This means that a new repeat can never start exactly at the same time as the end of a repeat. - Reference names. Names of sub-rule references must be unique in your experiment, unless you have re-used an existing reference. You cannot define two sub-rule references with the same Name, even when these are defined in two different Trial Control Settings. This is because analysis of Trial Control data is based on names of elements (sub-rules, references, actions and conditions). Elements with the same name would give ambiguous results. - Re-using a sub-rule reference. If you choose to create a copy of a sub-rule reference and then change any property of this copy (Name, Reference options, or Comment), a window appears with the message Define the scope of your changes. The program asks you whether you want to apply the properties only to the newly-created reference, or to the references with the same name in all Trial Control Settings. Choose the option you require and click OK. If you re-use a Reference that is stored in another Trial Control profile, and this profile is locked after data acquisition, changing any of the Reference settings will not affect the Reference in the locked profile. - Modifying a sub-rule reference. To modify a sub-rule reference, click the Settings button in the reference box. - Multiple references to one sub-rule. You can define multiple references to the same sub-rule, and place the corresponding Reference boxes in the same Trial Control sequence. Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - Target visits and errors URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-target-visits-and-errors Chapter: EthoVision XT Definition An event marking the time when the animal visits a zone defined as target, or non-target (error) zone. How to Specify Target Visits and Errors - Click the Add button next to Target visits and errors. - In the Target Visits and Errors tab, under Settings, choose the Target zones and the Non-target zones. Under Threshold, enter the Zone exit threshold. That is, once the animal is detected in the zone, the animal is considered to be in the zone until its distance from the zone border exceeds that threshold. Use this option to remove false re-entries resulting from random movements of the body point around the zone border. - Under Calculate Statistics for, select the options you require: - Target first visits: Visits to zones defined as targets. - Target revisits: Revisits to the target zones (to analyze working memory). - Non-target first visits: First visits to non-target zones. - Non-target revisits: Revisits to non-target zones (to analyze reference memory). - Total errors: The total number of non-target zone visits and target zone revisits. - In the Body points tab, select the body point(s) you want to use for calculation. If you have chosen two or three body points, select one of the following from the list: - Each point: Visits are scored for each point separately. This results, for example, in one value of Successes for Center-point, and one value of Successes for Nose-point. - Any selected point: Visits are scored no matter which selected point enters a zone. - All selected points: Visits are scored when all the selected points are in a zone simultaneously. - Complete the procedure to add the variable. See Calculate statistics: procedure. Application - In a Barnes maze experiment, use Target visits and errors to analyze spatial reference memory. Calculate the number of successes and errors and their latencies, and compare those figures between probe trials (with escape hole being closed) and training trials. TIP: Select Nose-point to estimate nose pokes. - In a Radial-arm maze experiment, use Target visits and errors to analyze working memory. Define the baited ends of the maze as targets. Calculate the number of target first visits and target revisits. To calculate the time needed to visit all arms, choose the Trial Statistic Latency to Last and in the results locate this statistic in the Target first visits column. NOTE: Latency is always calculated from the start of the track, even when you define time bins and nesting intervals. - See also the EthoVision XT 19 - Application Manual for more information on the Radial-arm maze test. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Fish - Analyze Data - Dependent Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-fish-analyze-data-dependent-variables Chapter: EthoVision XT Analyze Data - Dependent Variables - Velocity – Distance traveled per unit of time. - Distance Moved – Distance from previous to current sample. - In Zone – 'in zone' or 'not in zone' state. - Acceleration – Rate of change of velocity. - Acceleration State – 'accelerating', 'decelerating', or 'constant speed'. - Distance to Zone – Shortest distance to zone border. - Distance to Point – Shortest distance to point of interest. - Zone Transitions – Times animal moves between sequence of zones. - Zone Alternations – Consecutive zone visits (Y-maze). - Target Visits and Errors – Successes and errors in mazes. - Heading to Point – Movement direction relative to a point. - Heading – Movement direction relative to x-axis. - Turn Angle – Change in moving direction (relative/absolute). - Angular Velocity – Change in direction per unit of time. - Meander – Direction change relative to distance (tortuosity). - Movement – 'moving' or 'not moving' state. - Mobility State – 'highly mobile', 'mobile', 'immobile'. - Mobility – Surface area change of detected animal. - Rotation – Clockwise/counter-clockwise rotations. Standard Available Output Variables - Activity State – Four levels of activity duration. - Activity – Percentage of activity in arena. - Manually Scored Events – Behaviors scored manually. - Free Interval – Custom interval duration analysis. Multiple Body Points - Head Direction – Angle nose point is pointing towards. - Body Elongation State – 'stretched', 'normal', 'contracted'. - Body Elongation – Elongation percentage per interval. - Head Directed to Zone – Duration head is directed to zone. - Body Angle State – 'Straight', 'Bent', 'Bent clockwise', 'Bent counterclockwise'. - Body Angle – Body angle per sample point. Social Interaction - Distance Between Subjects – Distance between body points of different animals. - Body Contact – Contact between bodies (whole detected area). - Proximity – 'in proximity' or 'not in proximity' state. - Relative Movement – 'moving to', 'moving from', 'no relative movement', 'no interaction'. - Net Weighted Movement – Signed, distance-weighted change in distance. - Weighted Movement From/To – Distance-weighted change when moving away from/toward. - Social Contact [NEW] – Nose point near conspecific with orientation toward receiver. - Approach [NEW] – Actor moves toward receiver within specified parameters. - Following [NEW] – Actor follows receiver with both moving. - Leaving [NEW] – Actor moves away from receiver. - Side by Side – Two animals positioned parallel. - Train – One animal follows directly behind another. Trial and Hardware Control - Trial Control State – Time interval specified by Trial & Hardware Control events. - Trial Control Variable – Variables defined in Trial Control Settings. - Trial Control Event – Point event from Trial & Hardware Control. - Hardware Variables – Commands and signals from external devices. Multi-Condition Variables You can create new, customized parameters by combining two or more of the ones mentioned above, including manually or automatically scored events, hardware events, and external data. Other custom-built parameters are available upon request. Javascript Variables You can create custom dependent variables with JavaScript code. With JavaScript you have an almost endless range of possibilities to extract information from your track. JavaScript variables can be of type continuous, event, or state. You can find JavaScript variables ready to use on the EthoVision 19 Installation package and they are also available on GitHub: https://github.com/noldus/EthoVision-JavaScriptCustomAnalysis Statistics Available Depending on the parameter, the following statistics are available: - Frequency - Latency to first occurrence - Latency to last occurrence - Total duration - Variance - Standard deviation - Standard error - Number - Mean - Maximum - Minimum - Number of samples used to calculate the statistic Group statistics available: - Group mean and standard deviation - Group mean and standard error - 5-number summary (Minimum, First Quartile, Median, Third Quartile, Maximum) For grouped statistics, charts are automatically created. By default, this is a bar chart. When time bins are used, a line chart is created. When specifying a 5-number summary, a box-whiskers chart is created. Charts can also be exported as image files. Output and Export Data Track data, values of dependent variables, and all statistics can be exported as *.xls or *.txt file: - Export Track Data and Dependent Variable Values – Export the X,Y coordinates together with the value of the parameters chosen. Each track is exported as a separate file and the arena name and track number are attached. - Export Statistics – Export the spreadsheet-like table with all statistic results. The layout can be customized. - Export Hardware Log – If you are using Trial & Hardware Control, you can export the hardware log file. - Export Manual Scoring Log – If you have manually scored events, these can be exported as raw data. - Export Trial Control Log – The instructions of Trial Control and when the events occurred. - Export the External Data Log – Original data from external sources. Arena definition, graphs and heatmaps can be exported as *.jpg, *.png, *.bmp, and *.gif. The heatmaps can be exported in a high resolution (up to 3072 × 2304 px), making it suitable for publications. Quality Assurance Quality Assurance (Premium package) offers three tools to safeguard your experiment: - The ability to set user management rights - An Application Log that logs: Start and stop of trial, Creation of new experiment, Start/Stop of an experiment, Restoration of an experiment - An Experiment Log that contains: Snapshots of and changes made in the experiment settings, detection settings, and arena settings; Date and time a trial started and ended; Values of independent variables; Hyperlinks to earlier logged settings; Comments made by the user; Snapshot of data selection and analysis profile Both the application log and experiment log can be exported and printed. Help Features - Browser Based (HTML) Help – Highly searchable and responsive Help, can also be opened on tablets. - Video Tutorials – EthoVision incorporates mini video tutorials in certain parts of the software. A complete tutorial is available via the Help menu. - Help Desk – Professional personal help, available in many different time zones via phone, Teams or e-mail. - Sample Experiments – Provided with the software. More are available at my.noldus.com. Hardware Components Minimum Set-Up - EthoVision Base software - Camera (e.g. GigE, USB3, Basler, Analog) - Computer Optional Components - DanioVision - DanioVision Temperature Control Unit - Various mazes and tanks - Backlight unit - Camera table - DAQ system - MediaRecorder (for high resolution recordings) - USB-IO-box Source: EthoVision XT 19 Technical Specifications - Fish, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Fish - Data Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-fish-data-management Chapter: EthoVision XT Data Management Template Experiments EthoVision contains a user-guided set-up with templates for several test paradigms (water maze, plus maze, 96-well plate, etc.). Many basic settings are pre-set, such as arena definition, detection settings, and parameters for analysis. DanioVision Experiments If you use DanioVision™, a system specifically designed for observing and analyzing zebrafish larvae behavior, you can select the DanioVision experiment option. The automated arena detection detects individual wells in standardized well-plates automatically and optimizes detection with a few mouse clicks. Good Laboratory Practice For those conducting Quality Assurance experiments, particularly in environments adhering to Good Laboratory Practice (GLP) standards, EthoVision offers specialized options to meet these rigorous requirements. This ensures that your experiments not only yield reliable data but also comply with industry standards for quality and reproducibility. Flexibility For researchers seeking maximum flexibility in their experimental design, the "New from scratch" option allows for complete customization of the experiment setup. This feature is ideal for innovative research that goes beyond standard protocols. Setup Experiment Options - Tracking can be done live or from a video file. - Use digital or analog cameras (but not a combination). - Connect external data acquisition systems. - Track in up to 99 arenas with up to 16 subjects per arena. - Center point, center of gravity, nose and tail base tracking; color or color marker tracking. - Activity analysis – a non-tracking option analyzing overall activity per arena based on pixel changes. - Distance in mm, cm, m, or inches. Time in ms, s, min, or hours. Rotation in degrees, radians, gradians, or rotations. Manual Scoring The Manual Event Recorder is a built-in coding system which allows you to define a list of behaviors that you can score manually during and after data acquisition (live or offline). - Start-stop behaviors – behaviors that are independent from each other. - Point events – behaviors without a duration. - Mutually exclusive behaviors – activating one automatically stops the other. Contour-based Body Point Detection - Any species - Default – Analyzes the contour to assign nose-point and tail-base. - Adult Fish - For occlusions – Track zebrafish and similar fish when viewed from above. - All species - For occlusions – No shape assumptions; for insects, crustaceans, large animals, or side-view fish tracking (center point only). Contour adjustments: Erosion (decrease 1-10 pixels) and Dilation (increase 1-10 pixels). Detection Settings - DanioVision – Automatic detection method tailored specifically to larvae. - Gray scaling – Pixels with gray value between thresholds as possible object. - Static subtraction – Differences between reference image and current image. - Dynamic subtraction – Like static, but updates reference on each sample. - Differencing – Statistical comparison using variance in contrast. Trial List Trials organized in a cross table with system and user-defined variables. Schedule trials based on pre-recorded video files for batch acquisition. Import trials from previous experiments. Arena Settings Define arenas, zones, cumulative zones, hidden zones, overlapping zone layers, and points of interest. Unlimited zones per arena, any shape. Calibration enables velocity and distance calculations. Multiple Arena Definition For multi-well plates or groups of arenas, use the multiple arena set-up functionality. Rotate, scale, transpose, resize, and reposition arenas simultaneously. In DanioVision experiments, automated arena detection detects wells automatically. Arena/Zone Auto-subdivision Automated subdivision of circular and rectangular arenas into multiple equal zones with auto-labeling. Multi Camera Set-up Combine input from multiple cameras to track from multiple arenas without placing them all under one camera. Trial Control Options Program EthoVision to automatically start and stop tracking based on parameters. External command options can start other programs when conditions become true. With Trial & Hardware Control, define complete test protocols with real-time analysis. Conditions are applied to each arena individually. Tracking Methods (Body Point Estimate) The tracking method specifies how body points are estimated once the subject is detected. EthoVision offers the following acquisition methods: - Acquire data live – Live tracking requires no disk space for video storage, but creates no video backup either. Maximum trial duration (as tested) is 72 hours. - Acquire data live and record video – Live tracking while EthoVision records a backup video to an MPEG4 file. Maximum trial duration (as tested) is 72 hours depending on hardware. - Longer trials – To acquire trials longer than mentioned above, you can split your multi-day testing into multiple trials. - Record video and acquire data – EthoVision records a video to an MPEG4 file for data acquisition later. (Recommended if the computer is not fast enough for live acquisition and recording simultaneously.) - Acquire data from existing video files – Track data from video recorded with programs other than EthoVision. - Acquire data from a batch of existing video files at once – Track data from a series of pre-recorded video files. In options 2–5, the video file is available for post-acquisition visualization. If you choose option 3, 4, or 5, it is possible to analyze samples at a rate faster than the actual sample rate. EthoVision supports MPEG2, MPEG4 and H.264 AVC video formats. Series of Trials from Live Video Feed You can use a live video feed to acquire a series of trials. You can predefine start & stop conditions and an inter-trial interval. Data Acquisition Acquire Additional Behavioral Data You can score behaviors manually, adding scores live (while the test is running) or offline (by reviewing the video file). In addition, EthoVision is able to automatically recognize ten rat or mouse behaviors. Acquire Data with DAQ System External data acquired with a separate DAQ system can be synchronized with the tracking data. When you simultaneously acquire tracking and physiological data, EthoVision sends out a synchronization signal to the external DAQ system. After acquisition, you can import the physiological data and the two data streams are synchronized. EthoVision offers import profiles for a number of DAQ systems, such as DSI's Ponemah. You can import signals sampled at a constant rate. Source: EthoVision XT 19 Technical Specifications - Fish, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Fish - Data Management (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-fish-data-management-continued Chapter: EthoVision XT Data Management Supported Data Types - Signals sampled at a constant rate (with equidistant time stamps) - Signals sampled at a non-constant rate (with non-equidistant time stamps) - Physiological data stored in ASCII or EDF format - Ultrasonic vocalization data recorded with UltraVox Edit Data In the Track Editor the stored video file can be used to evaluate the tracking result. This allows you to quickly and easily find wrong data points and correct them. EthoVision will find samples that match a specific criterion, for instance to find missing points or samples that are separated by a distance greater or smaller than a specific value. Furthermore, points can be deleted, moved to another position or interpolated. It can be used to swap subjects in case these were assigned incorrectly, or correct the nose-point and tail-base if they were swapped. You can save a copy of the track with the edits, and the original track data also stays stored. - Time Bins – Time intervals of constant duration that you can define to analyze data as if the tracks were split into segments. (Length can vary between 1 second and 24 hours.) - Results Per Zone – An easy way to calculate the results of individual analysis parameters per zone. Smooth Tracks Small (erratic) movements, such as body wobbles or outliers, may lead to an overestimation of certain parameters. - The Lowess Filtering method essentially smooths the acquired tracks of the body center point. - Minimal Distance Moved smoothing allows you to specify the minimal distance moved between samples that is taken into account as actual movement, excluding micro movements. - Maximal Distance Moved removes outliers. Select Data EthoVision offers four methods for data selection or separation: - Filtering – Picking out entire tracks, based on the value of system variables, user-defined variables, or the presence of co-acquired external data. - Nesting – Picking out parts of tracks, according to the zone the animal was in, the behavioral state the animal was in, or during a certain time interval. Visualize Data You can plot all the selected tracks, or partial tracks, in one matrix. In this view you can sort rows and columns according to one or more independent variables. You can also visualize integrated data: the video, the animal's track, and the values of the selected parameters in one dynamic, synchronized view. With the built-in screen recording tool you can make a screen recording of either full screen or the tracks and plots area of the integrated visualization. All output variables can be presented in tables and graphs. You can customize the layout of the statistics results table, making data export to other applications easier. You can view the results per trial or for groups, such as treatment groups. You can also visualize your data in heatmaps. For this you can select data and variables of interest, and present heatmaps per individual or group. High quality export options with min-max scale allow for use in publications. Source: EthoVision XT 19 Technical Specifications - Fish, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Fish - Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-fish-specifications Chapter: EthoVision XT Specifications Video tracking software for zebrafish behavioral research EthoVision® is available in three packages to suit your research needs: Essential Perform complete tests with one animal in one arena. Includes all core tracking and analysis functionality. Advanced Everything in Essential, plus: - External Data Integration – Integrate EthoVision data with co-acquired external data. - Multiple Arenas – Track animals in up to a hundred arenas simultaneously. - Social Interaction – Track multiple animals within each arena. - Trial & Hardware Control – Create complete test protocols to initiate and control interaction with external equipment. - Track3D – Record movement in a test chamber, visualize the trajectory in 3D, and calculate movement parameters. Premium Everything in Advanced, plus: - Quality Assurance – Assign different rights to different users and comply with Good Laboratory Practice (GLP) guidelines. Additional Options - Additional software seats - System configurations Source: EthoVision XT 19 Technical Specifications - Fish, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Fish - Supported Cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-fish-supported-cameras Chapter: EthoVision XT Supported Cameras EthoVision was tested with a selected range of cameras. The maximum number of cameras depends on whether EthoVision is installed on a desktop or laptop computer. Cameras must be of the same type; a combination of analog and digital cameras is not supported. Mixing video images from different camera types is not supported. The drivers for the supported cameras are available on MyNoldus: my.noldus.com. Type Brand/Model Max. Number Interface Board Frame Rate GigE Basler acA1300-60gm (mono) Desktop: 1–16, Laptop: not supported CT1000 Pro, Adlink PCIe-GIE74, Basler GigE 4 port PoE fps GigE Basler acA1920-40gc (color) Desktop: 4, Laptop: not supported CT1000 Pro, Adlink PCIe-GIE74 fps USB 3.0 Basler acA1920-155μm (mono) Desktop: 1, Laptop: 1 U3-PCIE1XG205-1S, U3X4-PCIE4XE111 fps Analog PhenoTyper Desktop: 1–16, Laptop: not supported Picolo Alert (1–4 cameras) 25/29 fps System Requirements For optimal performance and functionality of EthoVision, an up-to-date professional workstation is strongly recommended. EthoVision 19 is tested on Windows 11 Pro 64-bit, version 25H2 on a Desktop Dell Pro Max Tower T2. Laptop compatibility testing is pending. For this system we guarantee compatibility. Recommended Computer Requirements - Processor (CPU): 14th Gen Intel Core i7-14700, 20 cores, 2.1–5.4 GHz - Internal Memory (RAM): 32 GB for desktop PCs and 16 GB for laptop PCs - Graphics Card (GPU): NVIDIA RTX 5070, 12 GB GDDR7 - Connectivity: USB 3.0 ports or an additional Ethernet network interface adapter, depending on the cameras - Hard Disk: 1 TB free space (to store experiments including video files) Performance will depend on the functionality used. Some processes, such as live acquisition or tracking multiple animals within one arena, will require more from the processor and may influence the working speed. Deep Learning Requirements Deep learning relies on the CUDA computing platform. For this reason, the graphics processing unit (GPU) driver must support CUDA version 13.1. For tracking live or from video files, we tested and guarantee compatibility with: - Desktop Computer (Dell Pro Max Tower T2): NVIDIA GeForce RTX 5070, 12 GB GDDR7, driver version 581 - Laptop: Compatibility testing is pending. When a driver version is not sufficient for supporting CUDA, EthoVision displays the following message in the Experiment Settings: "The graphics card driver is not installed or the graphics card does not support CUDA". We recommend downloading and installing the latest driver from the card's manufacturer. Deep Learning Limitations - One-Subject Tracking: Up to four arenas, live tracking or from video file. No minimal trial duration required. Maximum trial duration tested: 72 hours. - Two-Subject Tracking: Up to four arenas, tracking from video file only. Tracking of hooded rats is not supported. It is recommended to perform trials of at least five minutes. Maximum trial duration tested: 1 hour. - Subject Size: The apparent length of the subjects should be at least 10% of the size of the arena. We recommend that the apparent length of the subject's body is at least 120 pixels for rats and 50 pixels for mice (nose to tail-base). Source: EthoVision XT 19 Technical Specifications - Fish, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - Analyze Data - Dependent Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-analyze-data-dependent-variables Chapter: EthoVision XT Analyze Data - Dependent Variables Standard Available Output Variables - Velocity – Distance traveled by the body point per unit of time. - Distance Moved – The distance traveled by a body point from the previous sample to the current one. - In Zone – A discrete variable with two possible states, 'in zone' and 'not in zone', depending on whether the body point is within a specific zone (or group of zones). - Acceleration – The rate of change of velocity of the body point over time, indicating how quickly it is speeding up or slowing down. - Acceleration State – A categorization of the acceleration behavior, typically defined by thresholds: 'accelerating', 'decelerating', or 'constant speed'. - Distance to Zone – The shortest distance between a body point and the border of a specific zone (or group of zones). - Distance to Point – The shortest distance between a body point and a particular point of interest. (Centers of arenas and zones are automatically defined as points.) - Zone Transitions – The number of times an animal moves between a user-defined sequence of zones (2 or more). - Zone Alternations – The number of times an animal visits a user-defined number of zones consecutively (typically used in Y-maze experiments). - Target Visits and Errors – Number of errors and successes in e.g. Barnes maze target zone or baited arm in radial maze. - Heading to Point – Direction of movement of a body point between one sample and the previous, relative to a user-defined point. This indicates to what degree the animal moves towards the point, regardless of whether the animal faces the point. - Heading – Direction of movement of a body point between one sample and the previous, relative to a line parallel to the x-axis in the coordinate system. - Turn Angle (Relative and Absolute) – The change in moving direction of a body point between one sample and the previous. Relative turn angle takes the direction of turning into account (clockwise or anti-clockwise), whereas absolute turn angle does not. - Angular Velocity (Relative and Absolute) – The change in moving direction of a body point per unit of time. Relative angular velocity takes the direction of turning into account. - Meander – The change in moving direction of a body point, relative to the distance moved. It is a measure of the tortuosity of a trajectory. Relative meander takes the direction of turning into account. - Movement – A discrete variable with two possible states, 'moving' and 'not moving', indicating whether the spatial movement of a body point is within user-definable speed thresholds. - Mobility State – A discrete variable with three possible states, 'highly mobile', 'mobile', and 'immobile', indicating the percentage of change in the animal's surface area between consecutive samples, with user-definable thresholds. - Mobility – Calculates the mobility for which the complete area detected as animal is changing, even if the center point remains at the same place. - Rotation – The number of clockwise and/or counter-clockwise rotations made by the animal, in which the definition of a rotation can be freely chosen (for instance turning 360°, 180°, or 90°). - Activity State – The duration of levels of activity within the arena boundaries. It calculates four levels of activity (high, active, moderately active and inactive) based on user definable thresholds. - Activity – The percentage of activity within the arena boundaries. - Manually Scored Events – Behaviors that were scored manually. - Free Interval – For custom analysis of interval duration, cumulative durations, etc. - Body Elongation State – A discrete variable with three possible states, 'stretched', 'normal', and 'contracted', indicating the elongation percentage of the animal's body, with user definable thresholds. - Body Elongation – This parameter indicates the elongation percentage of the animal's body per user defined averaging interval. - Head Directed to Zone – The duration the animal's head is directed towards a specific zone or a circular area around a point. - Body Angle State – The body angle of the animal over a user-defined interval with output in four states: 'Straight', 'Bent', 'Bent Clockwise' and 'Bent Counterclockwise'. - Body Angle – The body angle of the animal (relative or absolute) per sample point. Multiple Body Points - Head Direction – The smallest angle formed by the direction that the nose point is pointing towards in a certain sample, relative to a line parallel to the x-axis. Social Interaction - Distance Between Subjects – The distance between a body point of one animal and a body point of another animal. - Body Contact – Contact between the bodies of two animals (not related to body points, but to the whole detected area of the animal's body). - Proximity – A discrete variable with two possible states, 'in proximity' and 'not in proximity', indicating whether an animal is within the proximity of another animal, with user-definable thresholds. - Relative Movement – Discrete variable describing the animal's movement relative to another animal with four possible states: 'moving to', 'moving from', 'no relative movement', and 'no interaction'. The maximum interaction distance is user-definable. - Net Weighted Movement – The signed, distance-weighted change in distance between two subjects from one sample to the next. - Weighted Movement From – The distance-weighted change in distance between subjects, when an animal (actor) is moving away from another animal (receiver). - Weighted Movement To – The distance-weighted change in distance between subjects, when an animal (actor) moves towards another animal (receiver). - Social Contact [NEW] – Detected when the nose point of the subject (actor) is near a conspecific (receiver) and the actor's center-nose vector is oriented toward the receiver's body points by less than the specified angle. - Approach [NEW] – Detected when the subject (actor) moves toward a conspecific (receiver) within the specified distance, the angle between the actor's center-nose vector and the receiver's center point is less than specified, and the receiver moves at a velocity lower than specified. - Following [NEW] – Detected when the subject (actor) follows a conspecific (receiver) within the specified distance, the actor's nose is oriented towards the receiver's center point within the specified angle, and both animals move faster than specified. - Leaving [NEW] – Detected when the subject (actor) moves away from a conspecific (receiver) within the specified distance, the angle between the actor's center-nose vector and the receiver's center point exceeds the specified threshold. Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - Analyze Data - Dependent Variables (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-analyze-data-dependent-variables-continued Chapter: EthoVision XT Analyze Data - Dependent Variables (Continued) Social Interaction Parameters - Side by Side – A parameter indicating when two animals are positioned parallel to each other, reflecting a specific type of social interaction or alignment. - Train – A parameter used to describe a behavior where one animal follows directly behind another, forming a 'train'. Live Mouse Tracker - Approach Rearing Subject - Drink - Follow - Get Away - Group - Make and Break Group - Make Contact - Move - Nest - Nose Contact - Nose Contact Sequence - Out of Nest - Rear - Social Approach - Stretch Attend Posture - Social Escape - Stop Trial and Hardware Control - Trial Control State – A time interval specified by two events of Trial & Hardware Control that occurs during the trial. The interval may occur in two or more instances if the events repeat. - Trial Control Variable – With this variable you can analyze and visualize the variables defined in the Trial Control Settings. - Trial Control Event – A point event, with no duration, defined by an element of the Trial & Hardware Control (a condition, action, rule, subrule, or reference). - Hardware Variables – EthoVision allows you to analyze hardware events in the software. Hardware events can be commands sent to external devices or signals sent back by hardware devices to the USB-IO box. Multi-Condition Variables You can create new, customized parameters by combining two or more of the ones mentioned above, including manually or automatically scored events, hardware events, and external data. Other custom-built parameters are available upon request. JavaScript Variables You can create custom dependent variables with JavaScript code. With JavaScript you have an almost endless range of possibilities to extract information from your track. JavaScript variables can be of type continuous, event, or state. You can find JavaScript variables ready to use on the EthoVision 19 Installation package and they are also available on GitHub: https://github.com/noldus/EthoVision-JavaScriptCustomAnalysis Rat Behavior Recognition Automatically detected behaviors: Drinking, Eating, Grooming, Jumping, Rearing Supported, Rearing Unsupported, Resting, Sniffing, Walking, Twitching. - Behavior Probability – The probability of the behavior that is detected. You can use this variable to display behavior probability in the integrated visualization. - Merged Behavior – You can merge automatically detected behaviors into one group, such as rearing (unsupported and supported) and eating and drinking combined. All automatically scored behaviors have a duration, except for twitching, which has a frequency. Mouse Behavior Recognition Automatically detected behaviors: Drinking, Eating, Grooming, Hopping, Rearing Supported, Rearing Unsupported, Resting, Sniffing, Walking, Digging. - Behavior Probability – The probability of the behavior that is detected. - Merged Behavior – You can merge automatically detected behaviors into one group. Statistics Available Depending on the parameter, the following statistics are available: - Frequency - Latency to first occurrence - Latency to last occurrence - Total duration - Variance - Standard deviation - Standard error - Number - Mean - Maximum - Minimum - Number of samples used to calculate the statistic Group statistics available: - Group mean and standard deviation - Group mean and standard error - 5-number summary (Minimum, First Quartile, Median, Third Quartile, Maximum) For grouped statistics, charts are automatically created. By default, this is a bar chart. When time bins are used, a line chart is created. When specifying a 5-number summary, a box-whiskers chart is created. Charts can also be exported as image files. Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - Data Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-data-management Chapter: EthoVision XT Data Management Template Experiments EthoVision contains a user-guided set-up with templates for several test paradigms. At the start of the program you can either start a brand-new experiment, re-use the settings from a previous experiment, or use the user-guided set-up to open an experiment template suited to a specific test (water maze, plus maze, etc.). With these templates, many basic settings are pre-set, such as arena definition, detection settings, and parameters for analysis. You can fine-tune these settings to fit your specific needs. PhenoTyper Experiments If you use a PhenoTyper system for home cage monitoring or any other test you can select the PhenoTyper experiment option which optimizes the arena settings and detection settings for this application. Live Mouse Tracker Experiments If you use the Live Mouse Tracker (LMT) acquisition system (https://livemousetracker.org) and want to analyze these data in EthoVision you can select the LMT experiment option when creating a new experiment. This creates a modified version of a standard, multi-subject, multi-body point experiment, with predefined, permanent settings for LMT. Setup Good Laboratory Practice For those conducting Quality Assurance experiments, particularly in environments adhering to Good Laboratory Practice (GLP) standards, EthoVision offers specialized options to meet these rigorous requirements. This ensures that your experiments not only yield reliable data but also comply with industry standards for quality and reproducibility. Flexibility For researchers seeking maximum flexibility in their experimental design, the "New from scratch" option allows for complete customization of the experiment setup. This feature is ideal for innovative research that goes beyond standard protocols. Experiment Options - Tracking can be done live or from a video file. - You can use digital cameras or analog cameras (but not a combination of the two). - You can connect external data acquisition systems to EthoVision XT. - Track in one or multiple arenas, with a max of 100 arenas. - Track one or multiple subjects per arena, with a maximum of 16 subject roles. - For mice, rats and zebrafish you can use center point tracking, or center of gravity, nose and tail base. For mice and rats you have the option between a contour-based technique or a deep learning based technique. You can also track based on color or color marker. - Distance can be measured in millimeters, centimeters, meters, or inches. - Time can be measured in milliseconds, seconds, minutes, or hours. - Rotation can be measured in degrees, radians, gradians, or rotations. Manual Scoring The Manual Event Recorder is a built-in coding system which allows you to define a list of behaviors that you can score manually during and after data acquisition (live or offline). - Score live. - Score (also) offline, to score at a lower or faster playback speed. You can also edit scored events. Types of behaviors: - Start-stop behaviors – behaviors that are independent from each other. - Point events – behaviors without a duration. - Mutually exclusive behaviors – behaviors grouped in such a way that activating one behavior automatically stops the other behavior. You can define different behaviors and score those categories with keyboard keys or with the mouse. Without key codes defined, you can manually score events using the mouse. Arena Settings The arena is the region in the video image where the animal is tracked. You can define: - The arena(s) - Subdivisions of the arena (zones) - Cumulative zones (define individual smaller zones to be taken into account for cumulative analysis) - Hidden zones (used for shelters) and entry zones to analyze entries/exits - Zones organized in layers, so you can define and analyze zones that overlap - Points of interest You can define an unlimited number of zones in an arena, and create zones of any shape. Calibration of your arena will allow EthoVision to calculate parameters such as velocity and distances to certain points. If you are tracking in multiple arenas, you can copy and paste the settings from one arena to the other. Multiple Arena Definition When your experiment contains multiple arenas — for instance a group of open fields or home cages — you can use the multiple arena set-up functionality. This means that you do not need to draw each arena separately. EthoVision allows you to easily rotate, scale, transpose, resize, and reposition the series of arenas simultaneously. Arena/Zone Auto-Subdivision This option allows the automated subdivision of circular and rectangular arenas in multiple equal zones, including auto-labeling of these subdivisions. For example, it can be used to divide a water maze into quadrants, simplifying the process of analyzing behavior across different sections of the arena. Multi Camera Set-Up In EthoVision you can combine the input of multiple cameras. This way you can track from multiple arenas without the need to place them all under one camera. Trial Control Options You can program EthoVision to automatically start and stop tracking, based on any of the parameters offered by EthoVision. This feature also includes an external command option, which allows you to start another computer program when a condition becomes true. For example, present a visual stimulus on a computer screen or play a sound file when the animal enters a particular zone. With Trial & Hardware Control, you can define complete test protocols to initiate and control interactions between your animals and external sensor and stimuli devices. Real-time analysis of any of the parameters of EthoVision allows you to control complete test protocols based on your animal's behavior. You can use it for complex learning tasks such as the radial arm maze with automatically controlled doors and food delivery using pellet dispensers. Attach and control all standard (TTL-based) hardware. If you are using multiple arenas, conditions are applied to each arena individually. Tracking Methods Body Point Estimate for 1 Animal Per Arena The tracking method specifies how the body points are estimated, once the subject is detected. Depending on how many subjects and body points you specify in the Experiment Settings, one or more methods for tracking of body points are available. Deep Learning Based Body Point Detection When using this technique a new algorithm based on a convolutional neural network finds the nose and tail-base points of rodents with high accuracy and few or no nose-tail swaps. Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - Data Management (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-data-management-continued Chapter: EthoVision XT Data Management Network-Based Feature Extraction The network was trained to extract features from video images of rodents of various colors and in various backgrounds. During tracking, the network analyzes a portion of the image that includes the detected subject, creates a map of probability of occurrence for both the nose- and tail-base points, and makes an estimate of the position based on the highest probability. Contour-Based Body Point Detection Any Species - Default This detection method analyzes the contour of the area detected as subject at each sample to assign the nose-point and tail-base. Make sure in the detection settings that the tail is fully detected. Rodents - Default This detection method analyzes the varying shape of the contour of the area detected as subject and builds up a 'rodent model'. It is more robust because it does not require the nose and tail to be visible: it can 'predict' the position based on previous samples. Choose this method when you want to track a single rodent without occlusions. Rodents - For Occlusions This method can handle severe shape distortions, for example when the animal's body is occluded or when multiple animals touch. However, it requires a lot of computer performance. Choose this method for rodents in a social interaction context. Other Species - For Occlusions This method does not make any assumption about the shape of the subject. Choose this method to track insects, crustaceans and large animals. With this method you only track the center point. Contour Adjustments - Erosion – Decreases the animal's surface area with 1–10 pixels. - Dilation – Increases the animal's surface area with 1–10 pixels. Tracking Methods for Multiple Subjects Per Arena Color Marker Tracking: The color marker itself is tracked and used for subject identification. Contour-Based Body Point Detection offers two options: - Center of gravity tracking only - Center of gravity and nose point and tail-base tracking Subject Identification Methods: - Marker-Assisted Identification – Identities are distinguished based on a color marker. - Unmarked Subjects – Identities may switch when paths cross. Deep Learning Based Body Point Detection: This method requires the animals have uniform color but appear somewhat different in the camera image. When 2 identical mice or rats are used, it is recommended to use a tail marker, bleach the fur on the back of one animal, or shave part of the fur. Hooded rats (2-tone rodents) are not supported. Detection Settings EthoVision offers four different detection methods: - Gray Scaling – Defines all connecting pixels with a gray value between two threshold values as a possible subject. - Static Subtraction – Looks at differences between a reference image (without the animal) and the current video image (with the animal in the arena). - Dynamic Subtraction – Like static subtraction, but updates the reference image on each sample. - Differencing – Makes a statistical comparison between pixels in a reference image and the current image, using the variance in contrast to determine whether each pixel has changed enough to be considered part of the subject. Trial List The trial list consists of trials that are planned, carried out, or skipped, including system variables and user-defined independent variables. All are organized in a cross table and data can be copied to and from Excel sheets. You can schedule a list of trials based on pre-recorded video files which can be automatically acquired as a batch. The trial list also allows you to import trials from previously acquired experiments to analyze data collected in two or more identical experiments as one data set. EthoVision offers the following acquisition methods: - Acquire Data Live – Live tracking requires no disk space for video storage, but creates no video backup either. Maximum trial duration (as tested) is 72 hours. - Acquire Data Live and Record Video – Live tracking while EthoVision records a backup video to an MPEG4 file. Maximum trial duration (as tested) is 72 hours depending on hardware. - Longer Trials – To acquire trials longer than mentioned above, you can split your multi-day testing into multiple trials. - Record Video and Acquire Data – EthoVision records a video to an MPEG4 file for data acquisition later. (Recommended if the computer is not fast enough for live acquisition and recording simultaneously.) - Acquire Data from Existing Video Files – Track data from video recorded with programs other than EthoVision. - Acquire Data from a Batch of Existing Video Files at Once – Track data from a series of pre-recorded video files. In options 2–5, the video file is available for post-acquisition visualization. If you choose option 3, 4, or 5, it is possible to analyze samples at a rate faster than the actual sample rate. EthoVision supports MPEG2, MPEG4 and H.264 AVC video formats. Series of Trials from Live Video Feed You can use a live video feed to acquire a series of trials. You can predefine start and stop conditions and an inter-trial interval. Data Acquisition Acquire Additional Behavioral Data You can score behaviors manually, adding scores live (while the test is running) or offline (by reviewing the video file). In addition, EthoVision is able to automatically recognize ten rat or mouse behaviors. Acquire Data with DAQ System External data acquired with a separate DAQ system can be synchronized with the tracking data. When you simultaneously acquire tracking and physiological data, EthoVision sends out a synchronization signal to the external DAQ system. After acquisition, you can import the physiological data and the two data streams are synchronized. EthoVision offers import profiles for a number of DAQ systems, such as DSI's Ponemah. You can import: - Signals sampled at a constant rate (with equidistant time stamps) - Signals sampled at a non-constant rate (with non-equidistant time stamps) - Physiological data stored in ASCII or EDF format - Ultrasonic vocalization data recorded with UltraVox Edit Data In the Track Editor the stored video file can be used to evaluate the tracking result. This allows you to quickly and easily find wrong data points and correct them. EthoVision will find samples that match a specific criterion, for instance to find missing points or samples that are separated by a distance greater or smaller than a specific value. With the Track Editor, points can be deleted, moved to another position or interpolated. It can be used to swap subjects in case these were assigned incorrectly. Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - Data Management (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-data-management-continued-V4z Chapter: EthoVision XT Data Management Correct the nose-point and tail-base if they were swapped. You can save a copy of the track with the edits, and the original track data also stays stored. - Time Bins – Time intervals of constant duration that you can define to analyze data as if the tracks were split into segments. (Length can vary between 1 second and 24 hours.) - Results Per Zone – An easy way to calculate the results of individual analysis parameters per zone. Smooth Tracks Small (erratic) movements, such as body wobbles or outliers, may lead to an overestimation of certain parameters. - The Lowess filtering method, which essentially smooths the acquired tracks of the body center point. - Minimal Distance Moved smoothing allows you to specify the minimal distance moved between samples that is taken into account as actual movement, excluding micro movements. - Maximal Distance Moved removes outliers. Select Data EthoVision offers four methods for data selection or separation: - Filtering – Picking out entire tracks, based on the value of system variables, user-defined variables, or the presence of co-acquired external data. - Nesting – Picking out parts of tracks, according to the zone the animal was in, the behavioral state the animal was in, or during a certain time interval. Visualize Data You can plot all the selected tracks, or partial tracks, in one matrix. In this view you can sort rows and columns according to one or more independent variables. You can also visualize integrated data: the video, the animal's track, and the values of the selected parameters in one dynamic, synchronized view. With the built-in screen recording tool you can make a screen recording of either full screen or the tracks and plots area of the integrated visualization. All output variables can be presented in tables and graphs. You can customize the layout of the statistics results table, making data export to other applications easier. You can view the results per trial or for groups, such as treatment groups. You can also visualize your data in heatmaps. For this you can select data and variables of interest, and present heatmaps per individual or group. High quality export options with min-max scale allow for use in publications. Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - Output And Export Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-output-and-export-data Chapter: EthoVision XT Output and Export Data Track data, values of dependent variables, and all statistics can be exported as *.xls or *.txt file: - Export Track Data and Dependent Variables Values – Export the X,Y coordinates together with the value of the parameters chosen. Each track is exported as a separate file and the arena name and track number are attached. - Export Statistics – Export the spreadsheet-like table with all statistic results. The layout can be customized. - Export Hardware Log – If you are using Trial & Hardware Control, you can export the hardware log file. - Export Manual Scoring Log – If you have manually scored events, these can be exported as raw data. - Export Trial Control Log – The instructions of Trial Control and when the events occurred. - Export the External Data Log – Original data from external sources. Arena definition, graphs and heatmaps can be exported as *.jpg, *.png, *.bmp, and *.gif. The heatmaps can be exported in a high resolution (up to 3072 × 2304 px), making it suitable for publications. Quality Assurance Quality Assurance (Premium package) offers three tools to safeguard your experiment: - The ability to set user management rights - An application log that logs: - Start and stop of trial - Creation of new experiment - Start/Stop of an experiment - Restoration of an experiment - An experiment log that contains: - Snapshots of and changes made in the experiment settings, detection settings, and arena settings - Date and time a trial started and ended - Values of independent variables - Hyperlinks to earlier logged settings - Comments made by the user - Snapshot of data selection and analysis profile Both the application log and experiment log can be exported and printed. Help Features - Browser Based (HTML) Help – Highly searchable and responsive Help, can also be opened on tablets. - Video Tutorials – EthoVision incorporates mini video tutorials in certain parts of the software. A complete tutorial is available via the Help menu. - Help Desk – Professional personal help, available in many different time zones via phone, Teams or e-mail. - Sample Experiments – Provided with the software. More are available at my.noldus.com. Hardware Components Minimum Set-Up - EthoVision Base software - Camera (e.g. GigE, USB3, Basler, Analog) - Computer Optional Components - PhenoTyper® - Various mazes and open fields - Backlight unit - Camera table - DAQ system - MediaRecorder (for high resolution recordings) - UltraVox - USB-IO-box Supported Cameras EthoVision was tested with a selected range of cameras. The maximum number of cameras depends on whether EthoVision is installed on a desktop or laptop computer. - Cameras must be of the same type; a combination of analog and digital cameras is not supported. - Mixing video images from different camera types is not supported. - The drivers for the supported cameras are available on MyNoldus: my.noldus.com. Type Brand/Model Max. Number Interface Board Frame Rate GigE Basler acA1300-60gm (mono) Desktop: 1–16, Laptop: not supported CT1000 Pro, Adlink PCIe-GIE74, Basler GigE 4 port PoE fps GigE Basler acA1920-40gc (color) Desktop: 4, Laptop: not supported CT1000 Pro, Adlink PCIe-GIE74 fps USB 3.0 Basler acA1920-155μm (mono) Desktop: 1, Laptop: 1 U3-PCIE1XG205-1S, U3X4-PCIE4XE111 fps Analog PhenoTyper Desktop: 1–16, Laptop: not supported Picolo Alert (1–4 cameras) 25/29 fps Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-specifications Chapter: EthoVision XT Video Tracking Software for Rodent Behavioral Research EthoVision® is available in three packages to suit your research needs: Essential Perform complete tests with one animal in one arena. Includes all core tracking and analysis functionality. Advanced Everything in Essential, plus: - Mouse Behavior Recognition – Automatically detect ten mouse behaviors such as grooming, rearing, and digging. - Rat Behavior Recognition – Automatically detect ten rat behaviors such as grooming, rearing, and sniffing. - External Data Integration – Integrate EthoVision data with co-acquired external data. - Multiple Arenas – Track animals in up to a hundred arenas simultaneously. - Social Interaction – Track multiple animals within each arena. - Trial & Hardware Control – Create complete test protocols to initiate and control interaction with external equipment, based on real-time analysis of the animal's behavior. Premium Everything in Advanced, plus: - Quality Assurance – Assign different rights to different users and comply with Good Laboratory Practice (GLP) guidelines. Additional Software Seats System Configurations Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - Technical Specs Rodent - System Requirements URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-technical-specs-rodent-system-requirements Chapter: EthoVision XT System Requirements For optimal performance and functionality of EthoVision, an up-to-date professional workstation is strongly recommended. EthoVision 19 is tested on Windows 11 Pro 64 bit, version 25H2 on a Desktop Dell Pro Max Tower T2. Laptop compatibility testing is pending. For this system we guarantee compatibility. Recommended Computer Requirements - Processor (CPU) – 14th Gen Intel Core i7-14700, 20 cores, 2.1–5.4 GHz - Internal Memory (RAM) – 32 GB for desktop PCs and 16 GB for laptop PCs - Graphics Card (GPU) – NVIDIA RTX 5070, 12 GB GDDR7 - Connectivity – USB 3.0 ports or an additional Ethernet network interface adapter, depending on the cameras - Hard Disk – 1 TB free space (to store experiments including video files) Performance will depend on the functionality used. Some processes, such as live acquisition or tracking multiple animals within one arena, will require more from the processor and may influence the working speed. Requirements Deep Learning Deep learning relies on the CUDA computing platform. For this reason, the graphics processing unit (GPU) driver must support CUDA version 13.1. For tracking live or from video files, we tested and guarantee compatibility with: - Desktop Computer (Dell Pro Max Tower T2) – NVIDIA GeForce RTX 5070, 12 GB GDDR7, driver version 581 Laptop compatibility testing is pending. When a driver version is not sufficient for supporting CUDA, EthoVision gives the message in the Experiment Settings: "The graphics card driver is not installed or the graphics card does not support CUDA". We recommend downloading and installing the latest driver from the card's manufacturer. Deep Learning Limitations - One Subject Tracking – Up to four arenas, live tracking or from video file. No minimal trial duration required. Maximal trial duration tested: 72 hours. - Two-Subject Tracking – Up to four arenas, only tracking from video file. Tracking of hooded rats not supported. It is recommended to perform trials of at least five minutes. Maximal trial duration tested: 1 hour. - Subject Size – The apparent length of the subjects should be at least 10% of the size of the arena. We recommend that the apparent length of the subject's body is at least 120 pixels for rats and 50 pixels for mice (nose to tail-base). Apparatuses EthoVision's neural networks have been trained with videos of: - One Subject Per Arena, Subjects of Uniform Color – Open field (regular or with round objects in it), PhenoTyper (with or without bedding material), Elevated plus maze, Three-chamber social approach cage, Barnes maze, Fear conditioning cage with floor grid, Y-maze (with no objects), and a maze with multiple chambers and openings. - One Subject Per Arena, Hooded Rats – Open field (regular or with round, rectangular or triangular objects in it), PhenoTyper (with or without bedding material), and Elevated plus maze. - Two Subjects Per Arena – Open field (with no objects), PhenoTyper (with or without bedding material), and home cage. Requirements Behavior Recognition When using Rat or Mouse Behavior Recognition, take the following requirements into account: - Behavior Recognition requires the detection of the nose point, center of gravity and tail base. The subject's apparent length (nose to tail base in walking position) must be at least 60 pixels for rats, and 55 pixels for mice. In all cases its apparent length must not exceed half the arena size. - Rats must be older than approximately three weeks. In all cases subjects must be able to walk. - The animal needs to be uniform in color. (Hooded rats have not been tested.) - You can track one animal per arena. When tracking live, you can use only one arena. - Behavior Recognition is tested in open field and home cage situations without a shelter. Using a shelter or other objects in your arena can influence the results. - It is preferred that the animal is visible in the arena at all times. - Use a top-view camera position and lighting from the top (instead of backlight). - Slow changes in the light during the course of a test are not a problem. Moving spotlights can reduce the reliability of the detection. - Video frame size must be greater than 352 × 288 pixels per arena. - The frame rate of the recorded videos can only be a multiple of the sample rate. The sample rate must be set between 25 and 31 samples per second. - The video image must not be overexposed. Details of the subject's fur must be visible. - Video compression should be as low as possible. Source: EthoVision XT 19 Technical Specifications - Rodent, Noldus Information Technology --- ## EthoVision XT 19 - The Elevated Plus Maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-elevated-plus-maze-test Chapter: EthoVision XT The Elevated Plus Maze Test Physical Setup The following suggestions are specifically to optimize video tracking: - Place the plus maze in such a way that its apparent size is maximized. You can obtain this by rotating the plus maze (or the camera) until the closed arms lie along one of the diagonals of your video window. - The lighting should be as even as possible throughout the arena. Bright lights are not necessary but should you need to supplement the light, consider red (or infra-red) light, as the animals will be less sleepy. - The camera should have a good view of the entire region the animal can be in. Center the plus maze in order to have the image of the arms as symmetrical as possible. This minimizes inaccuracy of calibration due to perspective. - The lighting should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). Even, diffuse lighting is important to optimize tracking of the nose. - A plus maze with transparent walls may help reducing shadows and make it easier to observe closed arm rears. There is little practical difference between the two mazes in terms of their ability to detect differences in anxiety-related behavior. However, the transparent design may reduce the sensitivity for the detection of anxiolytic drug effects because it decreases the anxiogenic potential of the open arm, therefore leading to the reduction of anxiety-related behavioral baseline (Violle et al., 2009 and references therein). - The background should contrast with the animal. If necessary use a different setup for light and dark colored animals. In the closed arms, the contrast between animal and background is generally lower. Take this into account when positioning lights and choosing the background color. - Make sure that the color of the floor is in good contrast with the color of the animal, and in minimal contrast with the arms. This makes it possible to track the animal's nose off the edge of the open arms. The gray floor contrasts with the black mouse. When the mouse dips its head off the edge of the open arms, its nose is still detected. When the floor is too dark, the head dip is not found. - Both the plus maze arms and the floor should not be reflective. If necessary, place an opaque rubber mat on the floor. - If there are barriers above the closed arms, remove them. If that is not possible, in the Detection Settings use the Dilation-Erosion filter to prevent EthoVision from seeing the animal cut in two. See also Contour Settings in the EthoVision XT Help. - Depending on circumstances, pools of urine can cause problems with the tracking. An absorbent base can help. - Always place the apparatus in the same position in the room; cues from overhead might influence the behavior of the animal. For the same reason the experimenter should not be visible to the animal during the trial (automated tracking makes this possible). - If you want to use the Deep Learning technique to track the subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. The Elevated Plus Maze Experiment in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep Learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings Choose Setup > Manual Scoring Settings. If you used the template for an elevated plus maze experiment, two start-stop behaviors have been defined: - Head dipping, to record manually the head dips over the edge of the open arms. - Rearing, to record manually the posture of the animal with forelimbs lifted off the floor. Note that EthoVision XT does not detect rearing automatically in an Elevated Plus Maze. You must score rearing manually in order to record it. You can define more behaviors, like scanning. Stretched posture can in principle be detected automatically by using the Elongation variable in EthoVision. Notes about Head Dipping: - By head dipping we mean protruding the head over the ledge of an open arm and down towards the floor. This response can occur while the animal's body is in the closed arms, central square or open arms. - You can also let EthoVision count the number of times or the total time that the nose point is found within the head-dipping area (provided that this has been chosen in the template). This also quantifies the risk-assessment behavior. - For a more reliable scoring of head dips, you could place a camera in front of each open arm, to film the arm's side-view. You can record video from multiple cameras using the software Noldus MediaRecorder. - If you film the side-view of the open arm, you can in principle record head-dips automatically with EthoVision by defining a zone immediately below the arm's floor. For these videos you need to create additional Arena Settings and Detection Settings. For more information, see Set Up an Experiment > Manual scoring settings in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > open Arena Settings 1. We assume that you followed the procedure in Arena Settings described earlier in this manual. Arena Check that the arena covers the whole area in which you want to track the animal. Remember to include enough space around the open arms (so that the animal is still tracked when it dips its head off the edge of those arms) and the inner side of the walls (to track the entire animal when it rears). Exclude any bright reflective rims that might interfere with tracking. Make sure the label Arena 1 stays inside the arena. To adjust the contour of the arena to the plus maze in the video image, do the following: - Click the Normal mode button on the toolbar and drag the arena contour until it is centered on the plus maze. - Click the Point edit mode button. Click one of the corners of the arena and drag the mouse to move the corner to the position you require. If you use video files, select the aspect ratio correction that applies. For more information, see Adjust the video aspect ratio in the EthoVision XT Help. If you use the live camera image or the video was recorded with EthoVision XT in the same experiment, you can skip this step. Zone Group: Arms Check that each arm zone covers the corresponding sector of the plus maze. To make sure that a zone is limited to the actual arm, move the label of that zone until the arrow points outside the zone. The color of the zone should change. If the color changes for a wider area of the plus maze, it means that the zone label also pointed to that area. Use the edit functions to move and reshape the zone. For details, see Move, rotate and resize a shape in the EthoVision XT Help. Do not forget to place the arrow of the zone label back in its original position. If the zones "closed arms" predefined in the template overlap with the open arms of the plus maze, rotate the entire arena and zones. To do so: - Drag around all the shapes so they are selected. - Click the Rotation mode button. Click in the middle of the arena and drag the mouse to rotate it. - Click the mouse pointer icon on the toolbar to exit the rotation mode. Zone Group: Open Arms, Closed Arms, Head Dip Zone These are cumulative zones. They are defined automatically from the sum of the open arms, the closed arms and the head dip zones, respectively. Trial Control Settings Choose Setup > Trial Control Settings. In the Trial Control Settings you can define conditions for the start and stop of the track. The template contains two trial control settings profiles: - Default. - Track duration 5 mins - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the plus maze. The track stops automatically after five minutes. Detection Settings Choose Setup > Detection Settings. In the Detection Settings window, check in the Video Section that the sample rate is set to: - Rats: 5 samples/second. - Mice: 12.5-15 samples/second. - Nose-tail tracking: 25-30 samples/second. See Configure Detection Settings in the EthoVision XT Help for details on the advanced detection settings. If you use hooded animals, use the detection method Differencing. If the plus maze has barriers above the arms, the animal is not always well detected. To improve detection, open the Advanced section in the Detection Settings pane. Under Subject Contour, select one or more pixels for the Dilation filter and the second Erosion filter. Leave the first Erosion filter set to zero. Select more pixels for Dilation than for Erosion, for example 3 vs. 1, until the entire animal's contour is detected. Trial List Choose Setup > Trial List. Do one of the following: Click Add Variables and enter your independent variables such as Animal ID and Treatment (with possible values Treated, Control, Sham, etc.), Dose, Name of the experimenter, etc. Each trial will receive only one value of each of those variables; for example, one trial must be either Control or Treated or Sham. Making a List of Trials If you want, you can pre-define all your trials here. Click the Add Trials button and specify the number of trials (recording sessions of one animal), and the values of the independent variables for each trial. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a series of trials for batch acquisition. See Acquire a series of trials in the EthoVision XT Help. - Test animals only once, unless the intention is specifically to study the different form of anxiety evoked by a second trial. If the animal falls off, it is best to exclude its scores. Independent Variables - You can also enter the independent variable values as you carry out the trials. You can edit the independent variables for trials already acquired, for example to enter a-posteriori data, like whether the animal in that trial entered the open arms or not. This way you can quickly create groups of tracks based on the result of the trial, and use such groups in analysis. - You can add a new independent variable at any time. Acquiring Data Protocol The subject is placed at the junction of the four arms of the maze, facing an open arm. Each subject is generally tested once for 5 minutes. For extensive protocol information, see Walf, A.A. & Frye C.A. (2007). The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nature Protocols 2(2): 322-328. doi:10.1038/nprot.2007.44 Score Behaviors Manually To score head dipping and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you find the key codes for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen. Notes: - Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help. Data Analysis Data Preparation Data Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. Smoothing Data Choose Acquisition > Track Smoothing Profile and open MDM Filter 0.2 cm. In this profile, the Minimal Distance Moved filter is used with a value of 2 mm and option Direct. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select your tracks according to your independent variable values (for example, Treated animals vs. Controls) and also select parts of tracks (data nesting). The Data Profile Treated vs. Control from the template compares Treated animals and Control animals trials. This way you create groups of tracks to obtain group statistics for each group. For more information and to create your own data selection, see the EthoVision XT Help. If you have more treatment groups (e.g. Sham), to create more treatment groups click the Common Elements - Result button in the Components pane, and place the new box somewhere on your screen. Create a new branch by connecting the first (Start) box to this new box. Click the button next to Treatment and select the new treatment level. Insert the box in the new branch. Visualizing Data You can visualize your tracks in three ways: - Plot tracks. You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals treated with saline and red for drug-treated animals). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast. - Plot integrated data. You can look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The Fear Conditioning Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-fear-conditioning-test Chapter: EthoVision XT The Fear Conditioning Test Hardware Setup and Camera Connection Connecting Cameras and Light Units - Connect each camera to one of the ports of the Ethernet Interface board in the EthoVision XT computer. For this you need 4x Ethernet cables with RJ45 connectors. - Connect the Top Light Units to the power outlet through the appropriate power adaptors. For more information on how to install and configure the Ethernet Interface board, see Install the GigE cameras in the EthoVision XT Help. - Connect one IR controller to each cubicle. Note: The external IR light controller is no longer necessary if you updated the cubicle. See update the cubicle firmware section below. Connect Multiple Cameras If your EthoVision computer is provided with a 4-port Ethernet interface board for connecting multiple GigE cameras, the cameras can get the power from the PC itself. If you purchased the computer and Ethernet board from Noldus, the board is already powered by the PC. Otherwise, open the computer casing and connect the Ethernet interface board with the internal power supply of the computer. Once power is provided through the PC, connect each camera to one of the ports of the Ethernet interface board. Label the ports and the cables so you always know which port is connected to which camera (and which cubicle). IP Addresses Note: If you have the Ugo Basile FCS equipped with USB cameras, connect the cameras directly to the EthoVision XT computer. Please skip this section. If your FCS is equipped with Basler GigE cameras through Ethernet connections, each camera must have an IP address that matches the IP address of the Ethernet interface board on your PC. The basic rules are: - The first two numbers are the same for all cameras: 192.168. - The third number should be the same and unique for each camera-Ethernet port combination. - The fourth number can be any value, but must differ between camera and Ethernet interface board, and should suggest which cubicle (arena) it refers to. For example: - 192.168.1.101 for camera 1 (cubicle 1) and 192.168.1.51 for Ethernet port 1 of the Ethernet interface board. - 192.168.2.102 for camera 2 (cubicle 2) and 192.168.2.52 for Ethernet port 2 of the Ethernet interface board. The IP address of each camera can be found on the front panel of the cubicle's light box. You need those addresses to configure the cameras. For details about assigning IP addresses: - In the HTML help: choose Help > EthoVision XT Help > Camera installation > Install GigE cameras. - In the Video Tutorial: choose Help > Video Tutorial > Set Up the Cameras. Camera Settings Camera Type and Lens The camera used in Noldus systems for Fear Conditioning is a Basler camera acA1300-60gm with a 2.95 mm fixed focal lens, F2.0, 1/1.8". How to View the Live Camera Image In order to view the camera image, you must activate the IR light in the cubicle. The camera has an IR-pass filter that blocks visible light. - Make sure that the camera has been configured and connected to the PC. - Start EthoVision XT and create a new experiment (File > New) or open an existing experiment without trials acquired. - Choose Setup > Experiment Settings. - Under Video Source, select Live tracking. - Select the camera from the list under Source. - Click the camera button for the live view. Camera Orientation The camera has been optimized at Noldus before shipping, therefore in most cases you do not need to adjust its orientation. If, for any reason, the video image is not optimized, follow the instructions below. Camera Alignment This section applies for previous FCS versions which had Noldus IR light box on top. Turn the three screws indicated to alter the camera orientation. If you tighten one of the screws, the camera points more to the other side. Loosen the same screw to have the opposite effect. For example, tighten screw b to have the camera pointing more to the back of the cubicle. Check the resulting image in EthoVision XT; make sure that the bottom of the cage is aligned at the center of the camera view. Camera Software Settings The camera frame rate, exposure time and other settings can be adjusted in EthoVision XT, or in the camera software Pylon Viewer. In EthoVision XT, choose Setup > Experiment Settings. Click the camera button and locate the settings you want to change. For multiple cameras, you need to adjust the settings for the first camera. Then, adjust the resolution of the Merged view. Video Resolution and Camera Zoom Level The camera lens of the FCS is a fixed focal lens. To adjust the zoom level, adjust the video resolution (in pixels) so that a portion of the maximal camera view is recorded. Note how the resolution setting crops the image. - Analog gain: 1 - Color space: Mono8 (Y800) - Video resolution single camera (H x V): 640 x 480 - Video resolution merged view (H x V): 1280 x 960 - Acquisition Frame rate: 25 or 30 - Exposure: 16000 us In a typical example, EthoVision XT makes a video of 1600 x 1200 from four cameras set to 800 x 600. Important: Whenever you change the resolution, open the Arena Settings and update the background image for your arenas before acquiring the data. The Binning Option If you need to reduce the video resolution without cropping the image, you can use the Binning option in the Video Settings of EthoVision XT. In EthoVision XT, choose Setup > Experiment Settings. Click the camera button and in the Video Settings window click the General tab. Select the Binning option and leave the value at 2. The Binning option reduces the number of pixels of the single camera image by half but does not crop the image. If you choose to select Binning, note that the brightness of the image increases. Make sure that this does not have negative effects on detection. If the image is too bright, reduce the Exposure time or the Gain. The Binning option must be the same across cameras. Remember to select (or de-select) the Binning option for all cameras, before setting the resolution of the merged view. Image Brightness If the image from the camera is too dark, do one of the following based on what FCS version you have: - If you have the IR light controller attached to the cubicle, turn the knob of the IR light controller all the way to the right. In most cases this is enough to make detection optimal. - Increase the IR light intensity up to 100% with the Trial Control Settings in EthoVision XT. - Increase the IR light intensity using the software on the tablet PC. - Place white plates at the sides and at the bottom of the FCS cage to increase contrast with dark-fur animals. Place dark plates in case of white animals. To increase the brightness of the image further, you can adjust camera settings in EthoVision XT or Pylon Viewer: - Increase the camera Exposure time. Be aware that a too high Exposure time may conflict with the camera frame rate. EthoVision XT shows a message in the Video Settings window if that is the case. - Increase the Gain to 1 or 2. Note that a higher Gain also creates more image noise. - Another option to increase the brightness of the image without increasing noise is to set the image Binning Horizontal and Binning Vertical to 2. Make sure that the Binning Mode is set to Summing for both. However, with binning the video resolution (that is, the width and the height of the camera image, in pixels) is half of the original. Older versions of the Ugo Basile FCS have the IR light source placed at one of the top corners of the cubicle. You do not need to operate this light if you have the IR light box above the conditioning cage. Upgrade Your FCS System Aim To adapt the Fear Conditioning System to use in combination with EthoVision XT 17.5 and later. - The touchscreen controller is no longer needed. - You can adjust the FCS settings (e.g. tone frequency, shock current) directly in EthoVision XT. - The time needed for installation and setting adjustment is about one hour. Prerequisites - You have received the following from Ugo Basile: - 1x upgrade box for each cubicle. - 1x power cable, 1x USB cable, 4x color-coded cables for each cubicle. - Two hexagonal Allen keys. - Ugo Basile needs the touch screen controller back first, so that they can copy the settings of the touch screen controller / Fear Conditioning box to the upgrade box. That way you can work with the same settings as before. Procedure - Remove the four screws at the corners of the upgrade box and remove the cover plate. - Locate the holes on the back panel of the cubicle. - Attach the box to the back panel. Make sure that the cable connections are on top. - Put the lid of the box back in place and tighten the screws. - Connect the color-coded cables as shown in the installation diagram. - Finally, connect: - The upgrade box to the PC (or USB hub, in case of 2 or more cubicles) using the USB cable that came with the upgrade box. - The upgrade box to a power outlet. - The camera to the PC's Ethernet board. - Repeat the steps above for the remaining cubicles. - Next, follow the steps in The Fear Conditioning Experiment in EthoVision XT section below. Update the Cubicle Firmware Aim To make the FCS cubicles compatible with the new IR illumination system that is fully controllable from EthoVision XT. Important: Follow this procedure only when requested by Noldus Support. What You Need - The firmware updater installation files: FW_Updater Setup.msi and setup.exe. - The new firmware file Cubicle.elf_7.34.S19. Procedure - On the EthoVision XT full installation package, open Drivers and Tools > Utilities > Ugo Basile FCS. You can download the full installation package from my.noldus.com. - Copy the file Ugo Basile FCS FirmWare Updater [version number].zip to your EthoVision XT PC and extract its contents. - Double-click the file setup.exe. Complete the installation procedure. - Power up the cubicle and connect it to the EthoVision XT PC through the USB cable. - Start the application. - Choose Select Firmware. - In the window that opens, choose the file Cubicle.elf_7.34.S19. - Click Firmware Update. - If the current version is 2.27 or newer, the update process should start automatically. Otherwise, you need to: - Disconnect both the power supply and the USB cable from the cubicle. - Reconnect both the power supply and the USB cable, approximately at the same time. - Wait until the Erase and the Programming processes are completed. - After the device has rebooted, you can change the tab to BOARD SETTINGS. - Leave or set the Device ID to 1 and set the Default IR intensity to the desired value (recommended: 100%). This will be the default intensity at startup. - Click Save to Board. Check the Ugo Basile Interface for EthoVision XT - Open the Control Panel > Programs and Features. - Check that the software Noldus - HardwareInterface UgoBasile - x64 package version 1.0.14 or later is installed. If a previous version is installed, uninstall it. Next, copy the file HardwareInterfaceUgoBasile - X64 Package - [version number].msi from the EthoVision XT 18 full installation package, under Drivers and Tools > Prerequisites > HardwareInterfaceUgoBasile to your PC, then run this file. Test the IR Light To test the IR light, in the Trial Control Settings create an Action based on the IR Light. Set the intensity to 100% and click Test. Click OK then check in the Detection Settings whether the IR light is still on. The Fear Conditioning Experiment in EthoVision XT Prerequisites Make sure that all devices are connected and powered up. Create an EthoVision XT Experiment - Start EthoVision XT and choose File > New From Template, then click Apply a pre-defined template. - On the How is the arena configured page, select: - If you work with one or two cubicles, select Fear Conditioning System 1 cubicle. Next to Number of arenas, select 1 or 2. - If you work with four cubicles, select Fear Conditioning System 4 cubicles. Next to Number of arenas, select 4. Note: This template does not include pre-defined zones as they are not used often in Fear Conditioning. - When you are asked How many subjects per arena will you track, select 1 subject. - Complete the guided procedure and give the experiment a name. Next, click OK. Experiment Settings Cameras - Choose Setup > Experiment Settings. - Under Video Source, next to Number of sources, select how many cameras (one per cubicle) you are working with. In the list under Source, select the name of each camera. The IP address should indicate which camera belongs to which cubicle, provided that you have assigned IP addresses correctly. - Next to Merged camera view, select 800 x 600 (cropped view of the cage) or 1280 x 1024 (full view of the cage). Number of Arenas and Tracked Features Important: Do this before selecting the Ugo Basile FCS in the Trial Control Hardware Settings. - In the Experiment Settings, under Arenas, select the Number of Arenas you use, that is, the number of cubicles (1 to 4). - Under Tracked Features, in most cases Center-point detection will suffice for fear conditioning experiments. Activity Analysis for Freezing Detection - In the Experiment Settings, under Analysis Options, select Activity analysis if you want to analyze freezing behavior. Tip: Click the Video Tutorial button next to that option for an overview of Activity analysis. Specify the Ugo Basile Fear Conditioning System Important: Have you already selected the number of arenas? Make sure that the Number of Arenas selected corresponds to the number of FCS cages used in that experiment. Only after that, follow the instructions below. - In the Experiment Settings, under Trial Control Hardware, select Use of Trial Control Hardware, and click Settings. - In the Hardware Interface window, select Ugo Basile F.C. Controller. - In the Fear Conditioning System COM Port Settings window, click the Add button. - Select a COM port and click OK. Repeat this step to add the COM ports connected to all the FCS cubicles. - For a setup with the Ugo Basile USB Hub and four cubicles, add COM11, then COM12, COM13, and COM14. - For a setup with one cubicle connected directly to the PC, select the COM port associated with that cubicle. If you have created the experiment from a template, there may be one or more COM ports already selected in the Fear Conditioning System COM Port Settings window. If they do not match those associated with the cubicles of your setup, delete them and add the correct ones. - When finished, click OK and proceed with arena settings. Important: Take note of which cubicle is connected to which COM port. Make sure that only the necessary COM ports are added. If you accidentally added a wrong COM port, select that port and click Delete. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The General log file URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-general-log-file Chapter: EthoVision XT The General Log File The General log file is created the moment EthoVision XT is installed. The following actions are logged: - Start and stop of an experiment. - Creation of a new experiment. - Users that are added / user rights that are assigned / user rights that are modified. - Errors that occurred when opening or closing an experiment. For every action, the user name, date and time are logged. To View the General Log File - Choose File > GLP Log Files. - In the GLP log window, select General log file. To Export the General Log File - Choose File > GLP Log Files, and click the Export button, or in the Experiment Explorer, under Export, click GLP Log. - Select General log file. - Browse to the folder where you want to export the log file to and click OK. Notes - The export format is HTML (*.html). The name of the export file is GLP-EthoVision(n), where n is a progressive number. - You cannot delete the General log file. The Experiment Log File The Experiment log file is started at the moment a GLP experiment is created. Changes made by the user that affect the data and results of an experiment can be traced back in the log file. These changes are logged from the moment you actually start acquiring data. At that moment a snapshot is taken of the various settings in your experiment and this snapshot is logged. Thereafter, all changes that can affect your data are logged. When a user makes changes to settings (for example, in the Trial List or Trial Control Settings) and/or leaving a setting, the user is prompted to add a comment to the Experiment log file. A new snapshot is then taken when new data are acquired. When the user cancels this automatic pop-up or does not enter a comment, a line appears in the Experiment log file with user name, date and time but without a comment. To Add a Comment to the Experiment Log File - Choose File > Add log comment (Ctrl+L). - Type in comments and click OK. To View the Experiment Log File Before you can view an experiment log file, you need to open the corresponding experiment. To view the experiment log file in EthoVision XT: - Choose File > GLP Log Files. - In the GLP log window, select the Experiment log file radio button. If necessary, click on one of the HTML links to go to a specific part of the Experiment log file. To Delete the Experiment Log File You can only clear the contents of the Experiment log file, not delete it. You can only clear the Experiment log file when you have the user management right to Delete Trials and Clear Log. - Choose File > GLP Log Files. - Select Experiment log file and click the Clear Log button. To Export the Experiment Log File - Choose File > GLP Log Files, and click the Export button, or in the Experiment Explorer, under Export, click GLP Log. - Select Experiment log file. - Browse to the folder where you want to export the log file to and click OK. Notes - In the case of large experiments, when the log file exceeds a size of 1 MB, it is split into multiple log files. - The export format is HTML (*.html). The name of the export file is GLP-[Experiment name](n), where n is a progressive number. - Experiment Settings, Arena Settings, Trial list, Trial Control Settings and Detection Settings are not stored in the log file until the first data are acquired. After that, only changes are logged. - Logged Arena Settings include a screenshot of Arenas and their Calibrations. It also contains a screenshot of each Zone Group and its Zones. - If your current experiment is not set for Quality Assurance, there is no Experiment log file present. - The suggested export location is the experiment's Export Files folder. Creating an Experiment Template Aim: Create a new experiment with all the right default settings, but without tracks and an Experiment log file, based on an existing GLP experiment. Prerequisites - You must have the User Management right to delete trials and clear log. See Assign Rights to Users. - You have a GLP experiment that you want to use as a template, for example an experiment with specific arenas and zones. Procedure - Choose File > New template experiment or press Ctrl+T. - In the Template option window, select Use a custom template. - Click Browse and select the existing GLP experiment you want to use as a template. Select the file with extension *.evxt and click OK. - Type in the name of the new experiment. - Select GLP experiment and click OK. Notes - Create a backup of the template and store it in a safe place. - To open a GLP experiment, you need an EthoVision XT license that includes the Quality Assurance module. See Upgrade EthoVision XT. - In a GLP experiment you cannot change or edit the zones already used in Acquisition. - If your license includes the Quality Assurance module, you can still create or open non-GLP experiments. In that case User Management does not apply and no log file is kept. - Multiple copies of the same version of EthoVision XT installed on the same computer share the General log file. Different versions of EthoVision XT installed on the same computer each have their own General log file. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - The Morris Water Maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-morris-water-maze-test Chapter: EthoVision XT Introduction The Morris water maze is a behavioral procedure designed to test spatial memory. It was developed by neuroscientist Richard G. Morris in 1984, and since its initial description it has become a very popular paradigm for the study of learning and memory in rodents (D'Hooge and De Deyn, 2001). In the water maze paradigm, a rat or mouse is placed into a small circular pool of water which contains a hidden platform (the Atlantis platform). The platform is either fixed (a few millimeters below the water surface) or adjustable. In the latter case, the platform is submerged at the start of the trial (about 15 centimeters, depending on the device) and remains submerged until the subject finds the location of the platform. The platform is then automatically raised. Visual cues, such as colored shapes, are placed around the pool to aid the animal in learning to locate the platform. After sufficient training, a capable rat can swim directly from any release point to the platform. Next, animals are treated and the effects on spatial learning and memory are evaluated based on how they now perform in the Morris water maze. The Sample Experiment EthoVision XT comes with a sample experiment that shows you how a Morris water maze test is carried out with EthoVision XT. It includes a number of videos from a true research project and shows interesting patterns of spatial behavior depending on the age of the subject. If the sample experiment was installed during installation of EthoVision XT, you can open it directly: Choose File > Restore Backup and browse to C:\Users\Public\Documents\Noldus\EthoVision XT\Experiments\Sample Experiments. Select the file with extension EVZ and click Open. If you do not find the sample experiment, download it from MyNoldus.com. First log in or register, then choose Downloads > EthoVision XT > Sample Experiments. References - D'Hooge, R. and De Deyn, P.P. (2001). Applications of the Morris water maze in the study of learning and memory. Brain Research Reviews, 36, 60-90. - Gallagher, M., Burwell, R. and Burchinal, M. (1993). Severity of spatial learning impairment in aging: development of a learning index for performance in the Morris water maze. Behavioral Neuroscience, 107, 618-626. For the complete list of publications, see the results in Google Scholar. Physical Setup The following suggestions are meant to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - There must be maximum contrast between the background and the animal. If you use dark rats in the water maze, you can color the water with milk powder (400 g, pre-dissolved in 2 l). It is also possible to track white rats or mice with dark coloring in the water: add 300 g of tempera black nontoxic powdered paint to a 45-l pool. - If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. Place four (or more) bulbs round the pool, below the level of the water surface or other indirect lighting above the water maze. 'Globe' type bulbs are ideal (twice the diameter as standard incandescent light bulbs). They should be close enough to the pool wall so that there is no direct line of sight between the bulbs and the camera lens. The light is reflected off the walls and ceiling, so that it only reaches both the lens and water surface indirectly. - The water temperature should be +/- 26 degrees C, which is cold enough to encourage the animals to seek the platform, but not too cold to induce hypothermia. The Morris Water Maze Test in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > ... The zone groups in your experiment depend on what zone template you chose when creating the experiment. - Platform, quadrants - This zone template creates one arena settings profile with a zone group Platform with zones Platform and Platform Zone (the zone around the platform) and a zone group Quadrant with a zone for each quadrant. - Platform, quadrants, corridors, border - This zone template creates four arena settings profiles, one for each quadrant. The South-West Platform profile, for example, contains a zone group Platform with zones Platform and Platform Zone (the zone around the platform), a zone group Quadrant with a zone for each quadrant, a zone group Thigmotaxis with zone Border Zone, and a Whishaw's corridor for the other quadrants than the one with the platform. Whishaw's corridor is an 18-centimeter wide path from the starting location to the platform. This corridor is designated as the correct route and if a rat deviates from this route at any point it receives a maximum of one error on that trial (Whishaw's error). To be able to determine whether the animal deviates from this route, you should define the rest of the arena as an Outside corridor zone. A Whishaw's corridor is defined for each release point you use. By creating separate Arena Settings for each corridor, you can select the appropriate Arena Settings for data acquisition depending on the release point for that trial. To resize and reshape a zone, click first the Point edit mode button on the toolbar, then move the corners of the zone outline. Hold Shift down to keep the same aspect ratio of the shape. Hold Ctrl to enlarge/reduce the shape size in all directions. Zone for Analyzing Thigmotaxis To quantify thigmotaxis, that is, persistent swim along the wall of the pool, create an additional zone group, and draw a circle which should be the internal margin of the zone. Place the zone label between this circle and the outline of the arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings > Open one of the following: - Default (no max duration) - When you use this profile, tracking stops when you click the Stop trial button. - Max Track duration 1 min - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the maze. The track stops automatically when the center-point of the animal has been in the zone Platform for at least 5 seconds, or when 60 seconds have elapsed since the start of the track. - Max Track duration 2 min - When you use this profile, tracking stops when the center-point of the animal has been in the zone Platform for at least 5 seconds, or after 2 minutes if the animal does not find the platform within that time. Using an Adjustable Platform If you use an adjustable platform you can define an action to raise the platform when the animal swims around the platform. Note that you need the Trial & Hardware Control module to be able to control the platform. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Check in the Video Section that the sample rate is set to 5 samples/second (for rats) or 12.5 samples/second (for mice). Advanced Detection Settings If detection of the subject is not optimal after using the Automated setup function, do the following: - Check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals. - When using Dynamic subtraction - Move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. Specify the Current frame weight. A low value (for instance, 10-20) usually works well. - When using Differencing - Set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. For more information, see Configure Detection Settings in the EthoVision XT Help. Trial List Choose Setup > Trial List. Defining Independent Variables Enter your independent variables such as: - Subject ID with the ID of your animals as predefined values. - Phase with Training and Probe as predefined values. - Treatment with Treated and Control as predefined values. - Dose with numerical values (e.g. 0.1 mg/kg, 0.5 mg/kg, etc.) - Day after treatment (with values 1, 2, etc.) - Name of the experimenter, etc. Making a List of Trials If you want, you can pre-define all your trials here. Click the Add Trials button. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Specify the values of the independent variables in advance, or enter them as you carry out the trials. Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help. Acquiring Data Protocol In a typical water maze test, an animal is put in the maze at a predefined position at the rim of the pool, facing the wall. Lower the animal gently into the water (e.g. in a paper cup), avoiding stress as much as possible. Before you start data acquisition, make sure the appropriate arena settings profile, depending on the starting location of the animal, is selected in the Acquisition Settings window. Training Trials In training trials, the animal starts swimming and the trial stops when the animal has found the platform or when the maximum trial duration has been reached. Probe Trials After the training trials, a probe trial is conducted in which the escape platform is removed from the pool and the animal allowed to swim for 60 sec. Thus typically each animal is tested n times (training) + 1 time (probe). Each test corresponds to a trial in EthoVision XT. Reversal Training Trials In reversal learning tasks, after one location has been thoroughly trained, the platform is moved to a different quadrant of the pool. Because it is hidden, it is not apparent that anything has changed until the animal fails to find the platform in its usual place. The focus is on how the animal reacts to this change and how quickly it learns the new location. In EthoVision XT, mark different types of trials with an independent variable in the Trial List. For example Type, with values Training and Probe. Or, a variable Platform Position with values SouthWest, NorthWest, etc. Data Analysis Data Preparation Track Smoothing Choose Acquisition > Track Smoothing Profile. - Select Lowess smoothing to remove the effect of body wobble. - When the animal sits still on the platform, yet the body center-point still moves slightly due to system noise, this results in an overestimation of, for example, the total distance moved. Select Minimal distance moved to only measure the total distance moved over the time periods in which the animal was really swimming. Analysis Profiles Choose Analysis > Analysis Profile. The template experiment contains five analysis profiles: - Latency to reach platform - This profile contains the variable Latency to platform to calculate how long it takes the animal to find the platform. You can use the variable Distance to zone to calculate Gallagher's index (Gallagher et al., 1993). The variable In quadrants calculates the frequency and duration of visits to each quadrant. - Path shape - The path shape can be determined by using the variables Turn angle, Angular velocity and Meander. - Whishaw's Corridor (only present if you chose a zone template with corridors when creating the experiment) - In this profile, the variable Inside Whishaw's Corridor calculates the time the animal spent inside any of Whishaw's corridors. The variable Outside Whishaw's Corridor calculates the time the animal spent outside any of Whishaw's corridors. - Distance & Time - In this profile, the total Distance Moved and the mean Velocity and the group means with their standard errors are calculated. - Heading - In this profile, the mean Heading to each of the platforms is calculated. Swim Patterns Thigmotaxis (Wall-Hugging Swim) This is a persistent swim along the wall of the pool that could include sporadic swims toward the center of the pool. To quantify thigmotaxis, calculate the time spent in the Thigmotaxis zone defined as described in the Arena Settings section, relative to the total track duration. Random Search This is swimming over the entire area of the pool in straight swims (zig-zag pattern), or in wide circular swims. Divide the pool into quadrants or even more, smaller zones, then count the number of times each zone was visited, the time in zones. If zone visits/time are uniformly distributed across zones, the search pattern could be said to be random or at least covering the whole pool. Scanning The search path is restricted to a limited, often central, area of the pool. Do the same as above, but now covering only the area/zones towards the center (see Janus C. 2004. Learning and Memory 11: 337-346). Relate this to the time in the external zones. Chaining/Serial Visits This is circular swimming (in anticlockwise or clockwise direction) at a fixed distance from the wall, in which the escape platform was located. To quantify chaining, draw a specific circular crown zone. Calculate the time spent in this zone versus the time in the rest of the arena, or calculate rotations occurring in that zone. Focal Search This is searching in a restricted area of the pool, usually the target quadrant. The path is characterized by a directional, straight swim to a specific area followed by dense concentration of superimposed loops and turns there. To detect rapid changes in direction, use the Multi condition dependent variable to define your criterion, for example Absolute Meander > 10 degrees/cm. This marks the time when Meander is greater than the threshold value. You can precisely capture the instances when the subject turns and heads back to the target zone. Combine Meander with an In zone variable in a Free Interval, to select the time from when the rapid change in direction occurs, to when the subject enters the target area. In the Arena Settings, define a zone around the platform or any other target point, and name it Focal zone. In the Analysis profile, define a Free interval from Interval start "Meander: Absolute Meander > 10 degree/cm" to Interval stop "In zone: Center point is in Focal zone". Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The Novel Object Recognition Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-novel-object-recognition-test Chapter: EthoVision XT The Novel Object Recognition Test Physical Setup The following suggestions are specifically to optimize video tracking. For general information, see the section Physical setup in the chapter The Open Field test. - The objects should contrast with the animal. If necessary use a different setup for light and dark colored animals. - Make sure that the objects do not move due to the activity of the animal. - Either make sure the sides of the box are not reflective (for example, sand the box to make it matte), or exclude the sides from the arena. If your objects are close to the sides, you will need to track the animal when it is against the side. The NOR Test in EthoVision XT Create an experiment from a template (Ctrl+T). Choose Open field (round or square) as Arena template, and Novel object zones as Zone template. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. - Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. - If you want to use the Deep learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. The PC must have a powerful graphics card which supports additional software (CUDA). See Deep learning: Requirements and Limitations in the EthoVision XT Help. Manual Scoring Settings These settings enable you to record behaviors manually, using keystrokes. This is handy for example to record exploratory behaviors like sniffing. Choose Setup > Manual Scoring Settings. If you created the experiment from the template with novel object zones, the Manual Scoring Settings already includes one behavior, Sniffing object. This is defined as "start-stop", which means that you press a key (default: q) to score the start of sniffing, and then you press the same key once again to score the end of sniffing. For more information, see Manual Scoring Settings in the EthoVision XT Help. Note: With the Rat or Mouse Behavior Recognition add-on, you can have EthoVision XT detect sniffing and other behaviors, without the need to score them manually. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. To set up your Arena Settings: - Click the Grab Background Image button to grab an image of the empty enclosure from the camera image. - Click 1. Draw Scale to calibrate your arena (for details, see the EthoVision XT Help). Draw the double-arrow in such a way it points to two opposite walls of the open field, at the level where the animal moves (not at the top of the walls). When done, enter the distance in real world units between the tips of the arrow. - Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. If the arena is not yet defined and you want to divide it in equal zones, choose the tool that applies depending on the shape of your open field and draw the outline of the arena. - If you used the Zone template Novel object zones, click 3. Select Shape and Draw Zones. Click the layer Zone group Objects. Check that the object 1 zone and object 1 boundary zone cover the object. If the predefined zones do not have the correct shape, delete the zones and draw new ones. - If necessary, draw additional zone groups/zones. Additional zones: - Zone group Floor and Wall. Check that the Floor zone covers the whole floor area of the open field. - Zone group Halves. Check that the West and East zones divide the Floor zone in two equal halves. Make sure that the vertical line crosses the entire arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings. The template contains the following profiles: - Default. When you use this profile, tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops when you click the Stop trial button. - Track duration 10 min. When you use this profile, tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops automatically after 10 minutes. To Stop Tracking When Exploration Exceeds a Specified Time You can also stop tracking when the subject has spent some time around an object. For example, when the protocol specifies that in pre-test trials the animal must explore an object for at least 30 seconds. Make a new Trial Control Settings, and immediately before the Stop track box, insert a Condition box based on the variable In zone, or another variable, or a combination of variables using Multi condition. In the Condition settings, specify that Cumulative duration in the boundary zone for that object must be greater than N seconds, for the nose point. If you use Multi condition, you can define "exploration" as a combination of variables. For example: In Zone for the nose point in the "object zone" is true + Head directed to Zone "object" is true + Velocity lower than 5 cm/s is true. The trial stops only when the cumulative time that the three criteria are met reaches the specified value. To Stop Tracking Automatically When No Exploration Occurs To stop tracking automatically even when the animal does not explore the object, add another condition in parallel with the first one, which specifies to stop tracking after some time (e.g. 10 minutes), and combine the two conditions with an Operator box of type ANY. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Advanced Detection Settings If detection of the subject is not optimal after using the Automated setup function, do the following: - Check that the sample rate is set to at least 25 samples/second when tracking the nose and tail. - Check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals. - When using Dynamic subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. Specify the Current frame weight. A low value (for instance, 1 to 10) usually works well. A novel object test normally has a duration of a few minutes in which the background does not change much. When using Differencing, set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal. - When detection still is not satisfactory, select Rodents / For occlusions as the tracking method and repeat step 2 above. Note: If you want to use the Deep learning technique to track the subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. Trial List Choose Setup > Trial List. Defining Independent Variables Enter your independent variables such as: - Subject ID with the ID of your animals as predefined values. - Phase with Acclimation, T1, T2 as predefined values, where: - Acclimation to mark trials where the animal is free to explore the arena, with no objects present. - T1 to mark trials where the animal is presented with a pair of identical objects. - T2 to mark trials where one of the familiar objects is changed for another new (novel object test). - Treatment with Treated and Control as predefined values. If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help. Acquiring Data Protocol A typical NOR test consists of three phases: - Acclimation. The animal is placed in an empty arena for 10 minutes to habituate to the environment. Tracking in this phase is optional. After 10 minutes, the animal is taken out of the arena and is put back in its home cage. - T1. After 15 minutes in the home cage, the animal is put back in the arena in which two identical objects have been placed. The animal is put at a position midway between the objects and such that its nose points towards the wall. The animal is tracked for 3 minutes and is then taken out of the arena and put back in its home cage. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T1. - T2. One of the objects in the open field is replaced with a novel object (sometimes the other object is also replaced with an identical one) and the animal is put in the arena again. Tracking is done for 3 minutes. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T2. Score Behaviors Manually To score sniffing and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you find the key codes and the buttons for the behaviors. To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen. Notes: - Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help. Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open MDM Filter 2 mm. In this profile, the Minimal Distance Moved filter is used (option set to Direct, with a threshold of 2 mm). When the animal sits still, the body points may still move slightly due to system noise. This results in an overestimation of, for example, the total distance moved. With the minimal distance moved filter, you measure the total distance moved over the time periods in which the animal was really walking. Adjust the threshold if necessary, based on your setup and sample rate. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Score behaviors manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select (Filter) your tracks according to your independent variable values (for example, Treated animals only) and also select parts of tracks (Nesting). You can create a data profile to compare Novel Object and Familiar Object trials using Filters. This way you create groups of tracks to obtain group statistics for each group. Analysis Profiles The template experiment contains four analysis profiles: - Touching objects. This analysis profile contains an In zone variable Nose touching objects to calculate the frequency, duration, and latency of when the nose-point of the animal touches the objects. The variable Distance to objects is used to calculate the mean and standard error of the animal's nose-point to the objects. The manually-scored behavior Sniffing object calculates the frequency and duration, with standard errors, of the instances when you scored Sniffing object during the trials. - In halves. In this analysis profile, the In zone variable In Halves is used to calculate the frequency, duration and latency of when the center-point of the animal was in either half of the arena. - Head directed to zone. This analysis profile contains two Head directed to zone variables, one for the novel object and one for the familiar object. For each object, the center plus a 0.10 cm radius is used as the Point of interest. The frequency and duration for Head direction to zone is calculated when the nose-point is in the zone of the corresponding object. - Distance & Time. With the variables Distance Moved and Velocity, the total distance moved and the mean velocity are calculated. All analysis profiles also contain settings to calculate the group mean and standard errors of the statistics for trial groups. Exploratory Behavior You can quantify exploratory behavior with the Analysis profiles described above, or you can create your own Analysis profiles. There is usually variation between subjects in the time spent exploring an object. To account for this variation, you can select the part of each track up to when the animal explored an object for a specific time, and then analyze the behavior of the subject in that part. To do so, use the Free Interval function in the Data profile. - Choose Analysis > Data Profile > New. - Under Nesting, click the button next to Free Interval. - Select the following: - As a Start criterion: Time (select Track start). - As a Stop criterion: Dependent variable. Select the variable In zone, and the statistic Cumulative duration. In the settings, specify which zone the animal explored, and with which body point (for example, Novel object, nose point). Set the total exploration time. - Click OK and insert the resulting box as described in the EthoVision XT Help. - In the Analysis profile, choose the endpoints (distance moved, time spent in zones etc.). - Choose Analysis > Results > Statistics and Charts. The results are calculated for the time until exploration reaches the duration specified. For more examples, see Free interval in the EthoVision XT Help. Heatmaps Heatmaps facilitate identification of "hotspots" and clustering of data points. Choose Analysis > Results > Plot Heatmaps. Next, click Plot Heatmaps on the toolbar. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The Open Field Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-open-field-test Chapter: EthoVision XT Introduction The Open Field for Rodents The open field test was first published 1932 by C. S. Hall and E.L. Ballachey to determine the fearfulness of rats. Today, the test is often used with rats and mice to investigate their locomotory behavior and their willingness to explore. Also, the test is one of the most commonly used methods to investigate anxiety in rats and mice. It is based on the natural tendency of rats and mice to spend more time in the corners and the periphery than in the center. Changes in these measures are often used to assess the sedative or stimulant effects of pharmacological agents. The test arena consists of a circular or rectangular empty open space with walls to prevent the animals from escaping. The arena is divided into a border zone and a center zone. In addition, the arena can be sub-divided into a number of other zones, like north, east, south and west zones, or corner zones. Common behaviors to be measured are: - Time spent in the border zone and center. - Time until the border of the center zone is first crossed. - Walking distance in each of the zones. - Percentage of time the animal is mobile/immobile. - Walking speed in each of the zones. - Frequency of rearing. References: - Hall, C., Ballachey, E. L., 1932. A study of the rat's behavior in a field. A contribution to method in comparative psychology. University of California Publications in Psychology, Vol 6, 1-12. - Gould, T.D., Dao, D.T., Kovacsics, C.E., 2010. The Open Field Test. Neuromethods, Vol 42, 1-20. - De Visser, L., Van Den Bos, R., Kuurman, W.W., Kas, M.J.H., Spruijt, B.M., 2006. Novel approach to the behavioural characterization of inbred mice: automated home cage observations. Genes brain and behavior, Vol 5(6), 458-466. For the complete list of publications, see the results in Google Scholar. On the downloads section of the Noldus website, my.noldus.com, you find a number of sample experiments, including the open field. The Open Field for Zebrafish Open Field The open field test is used to evaluate exploratory and affective behaviors. Fish are filmed with a video camera positioned overhead. The bottom of the tank is divided into two virtual zones, center and periphery (a circular zone with inner boundary 5 cm from the testing tank wall), which enables quantification of regional activity. In addition to standard movement parameters, primary behavioral measures included the distance traveled, number of visits and time spent in central and peripheral zones, and the ratio of time spent in the center zone over total testing time. Novel Tank Diving Test The novel tank test is used to assess exploratory and affective domains. The novel tank is a trapezoidal tank maximally filled with treated water and divided into two equal, horizontal regions (top/upper and bottom/lower zones). Primary behavioral measures include the number of visits and time spent in central and peripheral zones, the ratio of time spent in the top zone over total testing time, latency to enter the top zone, time spent in the top zone, number of transitions to top zone. Similar to behavioral tests used in mammalian models, affective phenotypes are inferred from modulation of thigmotaxis (center/periphery in the open field test) and geotaxis (top/bottom in the novel tank diving test). References: - Kalueff A.V., A.M. Stewart, R. Gerlai (2014). Zebrafish as an emerging model for studying complex brain disorders. Trends in Pharmacological Sciences, Vol. 35 (2), 63-75. Example videos: https://www.youtube.com/watch?v=7vhK8fq_W4A Physical Setup The following suggestions are meant to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - The lighting should be as even as possible throughout the arena. Make sure there are no shadows in the corners. Bright lights are not necessary but should you need to supplement the light, consider red (or infra-red) light, as the animals will be less sleepy. Regardless of the light level chosen, the investigator should use a light meter to record the lighting level and report this level in any publication. - When working with multiple arenas, make sure that the background light intensity is the same across arenas. This is usually not a problem, as long as the contrast between each animal and its arena background is much bigger than the difference in brightness between arenas. - The lighting should be diffuse, so as not to cast strong shadows (which might be tracked instead of the animal). Even, diffuse lighting is important to optimize tracking of the nose. - The background should contrast with the animal. If necessary use a different setup for light and dark colored animals. Matt, gray walls often give good results. - Depending on circumstances, pools of urine can cause problems with the tracking because they reflect light. An absorbent base can help. - Make sure the sides of the box are not reflective (e.g. sanding). Alternatively, exclude the sides from the arena, but make sure that the animal is tracked well in the entire border zone. - Always place the apparatus in the same position in the room, cues from overhead might influence the behavior of the animal. For the same reason the experimenter should not be visible to the animal during the trial (automated tracking makes this possible). - Minimize disturbance from audio sources, especially from ultrasound sources such as ventilation fans, CRT monitors, or strip-lights. You can mask audio disturbance by using the same background sounds, for example of a radio, in the test room as in the room where the animals are normally housed. - When you handle the animals, be careful to minimize stress. - If you use multiple arenas, make sure that the animals in the arena do not influence each other. The animals should, for example, not be able to hear or smell each other. - In EthoVision XT, choose Help > Video Tutorial and watch the video chapter Set Up Your Test Environment. That provides useful tips about the camera position, how to improve lighting and contrast with the background. - If you intend to use the Deep learning method to track the subject's nose point, note that there are additional requirements and limitations. See the EthoVision XT Help. The Open Field Experiment in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Choose Setup > Experiment Settings. - To detect freezing behavior, select Activity analysis under Analysis options. Click the video button next to it and watch the video tutorial to learn about Activity analysis. - If you work with rats or mice, you can let EthoVision XT automatically detect behaviors like Rearing, Grooming, and Sniffing. Select Behavior recognition under Analysis options and choose the options that apply to your experimental setup. The Behavior recognition option is only available if you have the Rat Behavior Recognition module or the Mouse Behavior Recognition module of EthoVision XT. Manual Scoring Settings Choose Setup > Manual Scoring Settings. If you used the template for an open field experiment, two start-stop behaviors have been predefined in the manual scoring settings. These are the behaviors rearing and grooming. Depending on your research question, you can add other behaviors that can be manually scored, like defecating, which is a measure for anxiety, and urinating and vomiting. Note that with the Rat (or Mouse) Behavior Recognition module you can have EthoVision XT detect a number of behaviors automatically. For more information, see Manual Scoring Settings and Behavior Recognition in the EthoVision XT Help. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. Arena Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. Tip: If you create an experiment from scratch, the arena is not yet defined. Click 2. Select Shape and Draw Arena and choose the drawing tool. If you want to have the open field divided in quadrants, choose one of the subdivided tools. Depending on the shape of your open field, draw the outline of the arena and select the number of sectors. Each sector is automatically defined as a zone. Zone Group "Borders" Check that the Wall zone covers only the wall of the open field. If necessary, adjust the center zone and the border zone. Zone Group "Quadrants" Check that the zones NW, NE, SE, and SW divide the Floor zone in four equal quarters. Zone Group "Squares" Check that the zones divide the arena in equal squares. Arena Settings for Rat/Mouse Behavior Recognition When you selected Behavior recognition in the Experiment Settings (only available when you have the Rat or Mouse Behavior Recognition Module of EthoVision XT), defining a few special zones and points significantly increases behavior recognition accuracy. - Feeder zones. To detect eating at the feeder. - Drinking spout points. To detect drinking. - Wall zones. To detect rearing to wall and to discriminate this from unsupported rearing. For the exact procedure, see Zones and points for Behavior recognition in the EthoVision XT Help. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the data acquisition. Choose Setup > Trial Control Settings. The templates for the open field contain two Trial Control Settings profiles: - Default. - Track duration 10 (or 30) min - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the arena. The track stops automatically after 10 or 30 minutes. If you use Behavior Recognition or Activity Analysis, the default Trial Control rule is slightly different. See Trial Control in the EthoVision XT Help. To stop acquisition after some specific time, open a Trial Control Settings profile, click the Settings button in the Condition - Time (1) box, and set the time you require. Traditionally, the open field test had a duration of between 2 and 10 minutes. This short length of time was chosen in the past because the data were acquired manually. It also emphasizes the exploratory behavior and response to novelty, rather than baseline activity of the rodents. Technology like video tracking with EthoVision XT allows for much longer periods of monitoring. Detection Settings Choose Setup > Detection Settings. Sample Rate Under Video, set the sample rate. Common values are, expressed in number of images analyzed per second: - For rats: 5 samples/s. - For mice: 12.5 samples/s. - For nose-tail tracking of all rodents: 25 to 30 samples/s. - For adult zebrafish: 5 samples/s. Remember, however, that the optimal sample rate is much depending on a variety of factors, including the characteristics of the setup, and even the animal's strain and behavior. Faster animals need a higher sample rate. This is also valid for fish. If the fish shows very rapid movements, then set the sample rate to the maximum; in other cases a sample rate of 5 fps may be enough. To Detect Freezing Behavior Open the Activity section in the Detection Settings pane. This option is only available if you selected Activity analysis under Analysis options in the Experiment settings. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold in such a way that when the animal is completely still, those pixels should be almost completely absent. Rat or Mouse Behavior Recognition If you selected Behavior Recognition in the Experiment settings (only available when you have the Rat or Mouse Behavior Recognition module of EthoVision XT), remove the tail from the detected body contour. To do so, in the Detection Settings pane: - Under Subject Contour, select one or more pixels for the first Erosion field until the tail is no longer detected. The detected body area (in yellow) looks now smaller. - Increase the Dilation filter until the detected body area is the same as before. Next, open the Behavior section in the Detection Settings pane. Wait until the rat has a normal, straight, posture (so not bending or rearing) and is moving forward. You should see the hips of the rat moving. Click Grab and check that the body contour is correct. You can also enter the values manually if you know them from previous experiments. However, in this case make sure that the conditions are equal, like lighting, size of the animal and distance between the animal and the camera. The detected body must have a minimum length of 60 pixels (sum of nose-point to center-point and center-point to tail-base) for Behavior Recognition. The detected body must also be smaller than half the arena size. For more information, see the EthoVision XT Help. Acquiring Data Protocol A typical open field test is carried out in the following way: - Transport the subject to the testing room at least 1 hr. prior to testing, to allow them to acclimate to the experimental room. This time period should be extended if the transfer involves excessive changes in the environment. - Clean the open field, even if it is not dirty prior to the initial trial. This way all animals experience the residual smell of the disinfectant equally. - In EthoVision XT, click the Start Trial button. EthoVision XT waits until the subject is detected in the arena. - Place the subject in the open field. Commonly, the subject is placed in the center. However, placing adjacent to a wall is sometimes used to avoid immediate exposure to a stressful situation. Also, in case of a large open field, the position adjacent to the wall may be easier to reach. - The researcher should leave the room, or position himself or herself as far as possible away from the arena and field of view of the subject. Also the tester should remain quiet throughout each trial. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The Porsolt Forced Swim Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-porsolt-forced-swim-test Chapter: EthoVision XT Trial Control Settings Choose Setup > Trial Control Settings and open one of the following profiles: - Default. In this profile, tracking starts 1 second after the animal has been detected in the arena. Tracking stops manually (for example when you click the Stop trial button). - Max Track Duration 15 mins. In this profile, tracking starts 1 second after the animal has been detected in the arena. Tracking stops automatically after 15 mins or when the animal has been in the Diving zone for over 1 second. You can use these Trial Control Settings for the pre-test session. If you need more time to put an animal in its cylinder, increase the number of seconds. This way you prevent that detection of your hand or arm starts tracking. The Start Condition works independently for each cylinder. - Max Track Duration 5 mins. This profile is similar to the previous one, but now the maximum tracking duration is 5 minutes. You can use these Trial Control Settings for the test session. When you work with multiple arenas, trial control is applied to each arena separately. Therefore, tracking may start at different times in different arenas, depending on when the animal is released. Detection Settings Important note: It is important for stable detection that the extremities of the animal (paws and tail) are either always included with the tracked body or always excluded from it. If the paws and tail are temporarily excluded and then included again in the detected subject during data acquisition, these changes affect the variables Mobility and Movement, while the animal might not actually be mobile or moving. On the other hand, the variable Activity is not affected by such changes, because it is based on the image change in the whole arena, not the change in the detected subject. - Choose Setup > Detection Settings > Detection Settings 1. - Under Video, choose a Sample rate of 5 (for rats) or 12.5 samples/second (for mice) or higher. - Click Advanced. - Under Method, choose Dynamic subtraction. Under Detection, check you selected the correct contrast. Move the slider to define the animal's contrast. The animal's body must be fully detected in all parts of the arena and the noise must be minimal. Set the Current frame weight slider to a value between 1 and 5 to adjust the number of past images that contribute to the reference image. - If the limbs and the tail are not included in the detected body, and you want to include them, under Subject Contour select the Dilation filter, then the second Erosion filter. Leave the first Erosion filter to zero. Adjust Dilation and Erosion to achieve stable detection. - Under Subject Size, click Edit. Define a Minimum Subject size to prevent small objects like droppings from being detected. - If you intend to use Activity analysis to score the behavior of the subject automatically, click Activity. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold in such a way that when the animal is immobile, those pixels are almost completely absent. Set Compression artifacts filter to On if you work with pre-recorded video. Trial List Choose Setup > Trial List. Enter your independent variables such as rat ID, Session type (with values Pretest or Test), Treatment (with values Drug vs. Control), Dose, Time of drug administration, Name of the experimenter, etc. For variables which differ between subjects, select Subject as a Scope. If you want you can pre-define all your trials here (click the Add Trials button), or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them and then paste the values into your Trial List. Furthermore, you can define a list of trials for batch acquisition. See Acquire a series of trials in the EthoVision Help. Acquiring Data Protocol Basic Protocol (Rats) - Pre-test trial (day 1, before drug administration). The animal is placed in the cylinder for 15 minutes. No scoring of immobility is performed during the first session. This session is needed to acclimatize the rats to the experimental situation and to induce a stable, high level of immobility during the test session. - Test (day 2). After drug administration, the animal is placed in the cylinder for 5 minutes. Score the duration of immobility by summing the time spent immobile; score as immobile minor movements strictly necessary to maintain the animal's head above water. Alternate Protocol (Mice) The mouse is placed in the cylinder. The trial lasts 6 minutes. Measure the latency to immobility from the start of the trial and the duration of immobility for the last 4 minutes. See Castagné et al. (2011). Current Protocols in Neuroscience 8.10A.1-8.10A.14. Score Behaviors Manually If you want to score the subject's behavior manually, define them first under Manual Scoring Settings. After you have started the trial, watch the subjects in the video and in the Manual Scoring tab at the bottom of the screen, click the button to the category that applies. As soon as the behavior of the subject changes, click the button for the corresponding category. - Important: If you do tracking from video, make sure you de-select DDS in the Playback Control window. - You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help. Determining Mobility Thresholds To find the optimal Highly mobile and Immobile thresholds, you can run a few test trials and check in the Analysis Results and Scoring pane (Dependent Variables tab) the values for Mobility state in relation to the behavior the animal displays. If the Mobility states do not correspond to the behavior of the animal, in the Analysis Results and Scoring pane click Dependent Variables, click the button under Mobility state and adjust the Highly mobile threshold and Immobile threshold. For example, if the animal is struggling, its corresponding Mobility state is Highly mobile. If the current Mobility score is Mobile or Immobile, you probably need to reduce the Highly mobile threshold. Note that you can also adjust the Mobility thresholds after acquisition. In the Analysis profile, add the Mobility state variable and visualize the data. If you do not see the Mobility state variable on your screen, click Show/Hide on the toolbar and select Show Dependent variables, then Mobility state and Mobility. Determining Activity Thresholds In the same way as you defined thresholds for Mobility state, you can define thresholds for Activity state. Use Activity state if Mobility state does not give satisfying results, for instance when detecting thrashing of the animal's limbs which may not be detected properly by Mobility. Note that when you work with multiple cylinders in the same video image, Activity state gives good results when the size of the arena is the same for all cylinders. In the Arena Settings, adjust the contour of the arenas to make them similar. Data Analysis Data Preparation Track Editing Choose Acquisition > Edit Tracks. You can fix tracking errors but normally you will not need to edit your data. Track Smoothing Choose Acquisition > Track Smoothing Profile > open MDM 0.2 cm. In this profile, the Minimal Distance Moved filter is used (option set to Direct, with a threshold of 2 mm). This filter filters out small movements which result from system noise. Note that smoothing influences the track, that is, the coordinates of the center point of the subject, not the subject's detected area, and therefore does not influence the calculations of Mobility. It also has no effect on Activity analysis. Review Video and Behaviors If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Acquire Data > Score behaviors manually in the EthoVision XT Help. Selecting Data Choose Analysis > Data Profile. You can select your tracks according to your independent variable values and also select parts of tracks (nesting). You can also create groups of tracks to obtain group statistics for each group. Integrated Visualization Choose Analysis > Results > Plot Integrated Data. Select a trial from the list on the tool bar. The video file and the Time Event Plot are displayed. In the Time Event Plot tool bar you can choose which profiles to use for display of the variables. Play the video and check whether the states scored under Mobility state correspond to the behavior of the animal. If they do not, fine tune the Mobility (or Activity) thresholds in the Analysis profile. Then check the results of your changes again in the Integrated Visualization. Analysis Profile Mobility Analysis In an Analysis Profile, you select the dependent variables and statistics for analysis. For the experiment made with the template for the Porsolt Test, a dependent variable Mobility is already present. Choose Analysis > Analysis Profile > Open > Mobility. - Double-click the row for the Mobility state variable. - Under Outlier filter, the Averaging interval is the number of samples on which the running average mobility is based. With an Averaging interval of 1 sample, sudden changes in surface area caused by reflections are not filtered out. - Under Threshold, set the Highly mobile and Immobile thresholds to the values you have previously determined. - Under Calculate statistics for, select the states you want to analyze. - Click the Trial Statistics tab and select Duration and Frequency. Optionally select additional statistics in the Group statistics tab. - Click OK. Comparing EthoVision Mobility Data with Your Ratings If you have scored the animal's behavior manually, you can easily compare your data with those scored by EthoVision (Mobility). Make sure that your analysis profile includes the three Mobility states and the behaviors scored manually, then visualize the data. If the EthoVision data do not match your ratings at an acceptable level, adjust the Mobility threshold values in acquisition and in analysis. An Alternative to Mobility Analysis You can use Activity state if the Mobility state variable does not give good results, for instance when detecting thrashing of the animal's limbs which may not be detected properly by Mobility state. Activity analysis is based on the temporal change in pixel value in the whole arena. Because it is not based on the detected animal's surface area, it is independent of tracking. - In the Experiment Settings, under Analysis options select Activity analysis. Click the video button next to it and watch the video tutorial to learn about Activity analysis. - In the Detection Settings, click Activity. Enter the Activity threshold for detecting a change in the pixels in the arena. Start with the default value and check the purple-colored pixels in the video image. Adjust the threshold in such a way that when the animal is immobile, those pixels are almost completely absent. - Run the trial. - In the Analysis profile add Activity and Activity state. - Visualize the data (Plot Integrated Data). There you see the scored Activity states and the subject in the video. Adjust the Activity state settings in such a way that the states scored by EthoVision XT match the behavior of the subject at that time. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The Radial Arm Maze Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-radial-arm-maze-test Chapter: EthoVision XT Introduction The Radial Arm Maze Test The radial arm maze was designed to measure spatial learning and memory in rats (Olton and Samuelson, 1976; Olton, 1978, 1985). The original apparatus consists of eight arms, each about 4 feet long, and all radiating from a small circular central platform. At the end of each arm there is a food site, the contents of which are not visible from the central platform. The design ensures that, after checking for food at the end of each arm, the rat is always forced to return to the central platform before making another choice. For example, when investigating working memory, all arms are provided with a food reward and the animal should visit each arm only once. Correct performance of the radial maze task requires intact spatial memory abilities. Performance is affected by hippocampal impairment and a variety of pharmacological agents (e.g., Janitzky et al. 2011). References - Janitzky, K, Schwegler, H., Kröber, A., Roskoden, T., Yanagawa, Y. & Linke, R. (2011). Species-relevant inescapable stress differently influences memory consolidation and retrieval of mice in a spatial radial arm maze. Behavioural Brain Research, 219(1), 142-148. - Olton, D.S. (1978). Characteristics of spatial memory. In: Hulse S.H., Fowler H, Honig W.K. (Eds.), Cognitive processes in animal behavior, Hillsdale, NJ: Lawrence Erlbaum Associates, 341-373. - Olton, D.S. (1985). The radial arm maze as a tool in behavioral pharmacology. Physiol. & Behav. 40, 793-797. - Olton, D.S., & Samuelson, R.J. (1976). Remembrance of places passed: Spatial memory in rats. Journal of Experimental Psychology: Animal Behavior Processes, 2, 97-116. - Wenk, G.L. (2004). Unit 8.5A Assessment of Spatial Memory Using the Radial Arm Maze and Morris Water Maze, in: Current Protocols in Neuroscience, John Wiley and Sons, Inc. Physical Setup The following suggestions are specifically to optimize video tracking: - The camera should have a good view of the entire region the animal can be in. The arena should fill the field of view. - There must be maximum contrast between the background and the animal. If you use white animals in the maze, make sure the floors of the arms are dark and vice versa. Preferably, the floor of the room should be the same color (and matted) as the maze, contrasting with the animal. - Lighting should be uniform and even with no shadows. - If you have reflections in your image, EthoVision XT may confuse those reflections with your subject, and track the reflections rather than your animal. To prevent reflections, place indirect lighting above or around the maze. 'Globe' type bulbs twice the diameter as standard light bulbs are ideal. They should be close enough to the maze so that there is no direct line of sight between the bulbs and the camera lens. The light should reflect off the walls and ceiling, so that it only reaches both the lens and radial maze indirectly. The Radial Arm Maze Test in EthoVision XT In EthoVision XT, you can set up a radial 8-arm maze experiment by using a predefined template in the guided setup. Create an experiment. For details, see Chapter 1 of this manual, or see Setup an Experiment in the EthoVision XT Help. Experiment Settings - Make sure that the radial maze is connected to the EthoVision XT computer. To connect the radial maze to EthoVision XT, you must have the Trial and Hardware Control add-on and the USB-IO box. The procedure and the necessary cabling may differ between manufacturers of the radial maze. Please see the accompanying documentation. - Choose Setup > Experiment Settings. - Under Video Source and Tracked Features, make sure that the options selected correspond to your needs. To adjust the camera settings, click the video icon in the camera row. - If you want to use the Deep learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help. - Under Trial Control Hardware, select Use of Trial Control Hardware and click Settings. Select Noldus USB-IO box. - In the Device Configuration window, for TTL ports 1 to 4, under Device type, select Custom Hardware. Next, type in Doors1&2 for TTL Port 1, Doors3&4 for TTL Port 2, Doors5&6 for TTL Port 3, and Doors7&8 for TTL Port 4. Arena Settings Choose Setup > Arena Settings > Open Arena Settings 1. - In the Grab Background Image window, click the Grab button to grab a background image of the radial maze from the camera image. - Click 1. Draw Scale to calibrate your arena. For details, see Make the arena in the EthoVision XT Help. - Click 2. Select Shape and Draw Arena and check that the predefined arena has the correct shape and size. If necessary, adjust the contour of the arena to fit the radial maze. - If you used the Zone template, click 3. Select Shape and Draw Zones. Check that the zones have the correct shape and size. If necessary, resize or add new zones. - If you are using automated doors, click Arena - Hardware mapping in the Arena Settings window to assign the doors to the arena. Trial Control Settings In the Trial Control Settings you can define conditions for the start and stop of the track. Choose Setup > Trial Control Settings > Open one of the following: - Default (no max duration) - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the Center zone. Tracking stops manually (for example when you click the Stop trial button). - Track duration 10 min - When you use this profile, tracking starts automatically 2 seconds after the animal has been placed in the Center zone. The track stops automatically when 10 minutes have elapsed since the start of the track. Controlling Automated Doors If you want to control the automated doors with EthoVision XT, you need to create new Trial Control Settings. An example of Trial Control Settings for a protocol as described in Unit 8.5A of Current Protocols in Neuroscience (2004) to test basic working memory is the following: - Start condition. We assume that the animal is released in the Center zone with all doors closed. Tracking starts 3 seconds after the animal is put in the Center zone. - Opening all doors simultaneously. You can create a Sub-rule with a Reference for this. In the Sub-rule, each door is opened. For each door, you need to create a separate Hardware Action box, with the corresponding Device name (for example '1&2') and appropriate Action ('Output 1 High' which opens door 1). The Sub-rule 'open beginning' contains the sequence in which doors are opened. The Reference box to the Sub-rule is activated immediately after the Start trial command. - Closing and then opening all doors. When the animal has visited the Goal zone of one of the arms and returns to the Center zone, all doors are closed and re-opened after 5 seconds. You can create a Sub-rule with a Reference for this. In the Sub-rule, you need to create a Zone transition Condition for each arm separately. Next, all eight Zone transition Conditions need to be connected to an Operator 'Any input True'. With a Hardware Action box, all 8 arms are then closed. Place the Hardware Action box for all doors in a sequence similar to opening doors as described in the opening step above. - Stop condition. The trial stops when the animal has visited the Goal zones of all 8 arms OR after 15 minutes have elapsed since the start of tracking. - For the first criterion (the animal visits the Goal zone of all arms), use an In Zone Condition for each Goal zone. All eight In Zone Condition boxes are connected to the Operator 'Num simultaneously True inputs'. - For the second criterion (after 15 minutes), use a Time Condition box. - The two criteria must be combined with OR logic. The Time Condition box and the 'Num simultaneously True inputs' Operator box are connected to an 'Any input True' Operator box. An extra delay of 3 seconds can be included before the trial stops. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Advanced Detection Settings - Under Video, check that the sample rate is set to 25 or 30 samples/second for multiple body-point tracking. - Click Advanced. - Under Method: - By default, Static subtraction is selected as the detection method and Rodents / Default as the method for nose-tail detection. The background in a radial maze test usually does not change much, so Static subtraction usually works well. Make sure the lighting is even and there are no shadows in the maze. - If after running some test trials you get nose-tail swaps, try using the tracking method Rodents / For occlusions. - If you selected to use the Deep learning technique to track the subject's nose, next to Deep learning click Define and select a box around the subject. Make sure that the box includes the subject's nose. For details, see the EthoVision XT Help. - Optional: Select Track noise reduction. Under Smoothing, set Track noise reduction to On. In some cases better quality tracking can be obtained by applying track noise reduction. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The RotaRod and Y-maze Tests URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-rotarod-and-y-maze-tests Chapter: EthoVision XT The RotaRod Test Introduction The rotarod test is widely used to evaluate drug effects on motor coordination in rodents. The principle of this test is that rats or mice are first trained to walk on a rod rotating at a certain speed. Once the animals have learned this, the effect of a test-compound on their motor performance is evaluated. Animals experiencing impaired motor coordination are unable to cope with the rotating rod and will drop off when the rotation speed exceeds their motor coordination capacity. The more disturbed the animals are, the sooner they fall off the rod. The use of rotating rods to measure balance in rodents has been described since at least the 1950s (Dunham and Miya, 1957; Kinnard and Carr, 1957). Jones and Roberts (1968) introduced a significant modification of the basic design with an accelerating rod. The rotarod is a horizontal cylinder that rotates along its long axis. It is situated above the cage floor, high enough to make sure rodents do not jump off the rod and low enough to avoid them being injured when they fall off. The speed of the rotarod is mechanically driven and can be constant or accelerated during the test. The test consists of a training phase in which the rats or mice learn to walk on the rod at a certain speed. Then three test trials are carried out in which a drug is tested. A commonly measured parameter is the time until falling off. With EthoVision XT the Rotarod test can be automated. A camera is placed above the Rotarod, which gives a top-view image of the setup. The rat or mouse that stays on the rod is present in the center of the camera image. When the animal falls off, or clings onto the rod and turns round on it, it moves out of the center of the image. This can be automatically quantified with various parameters in EthoVision XT. References - Dunham, N.W. and Miya, T.S. (1957). A note on a simple apparatus for detecting neurological deficit in rats and mice. J. Am. Pharmac. Assoc. Sci. Ed., 46, 208-209. - Jones, B.J. and Roberts, D.J. (1968). The quantitative measurement of motor inco-ordination in naive mice using an accelerating rotarod. J. Pharm. Pharmacol., 20, 302-304. - Kinnard, W.J. and Carr, C.J. (1957). A preliminary procedure for the evaluation of central nervous system depressants. J. Pharmacol. Exp. Ther., 121, 354-361. - Carter, R.J., Morton, A.J., and Dunnett, S.B. (2001). Motor Coordination and Balance in Rodents. In Current Protocols in Neuroscience (2001) 8.12.1-8.12.14. - Mahieu, M., Willems, R., Hoekstra, L., Ver Donck, L. (2012). Automated Detection of Aberrant Behaviour of Mice on the Rotarod: Use of EthoVision XT. Proceedings of Measuring Behavior 2012 (Utrecht, The Netherlands, August 28-31, 2012) 431-433. Physical Setup In most use cases, a video camera is positioned above the rod to record video. For systems with multiple rods, it is best to point one camera towards each rod. You can mix camera images directly with EthoVision XT or a video mixer. To detect the falling off the rod automatically, place the camera in front of the rotarod. You can have EthoVision XT detect the fall off event when the animal disappears from the arena, or a zone drawn around the rod. The Rotarod Test in EthoVision XT Create an experiment. For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help. Experiment Settings Select the number of cylinders as Number of Arenas. Arena Settings - Choose Setup > Arena Settings > Open Arena Settings. - After calibrating, click Select Shape and Draw Arena. The arena covers the region around the rod. Make sure that the animal is always within the arena boundary. Zones - Click Select Shape and Draw Zones. To quantify the position of the subject's center point relative to the center of the rod, define a zone (Reference zone) at known distance from the rotation axis of the rod. For example, draw a line (Reference line) at the right margin of the arena, and define a zone. You can then analyze the distance of the subject's center point from the border of this zone. If you know that the border of the zone is for instance at 10 cm from the rod axis (Reference distance), then you can back-calculate the relative distance of the subject-center from the axis. The values of Distance to zone (border) diminished by the Reference distance will be either positive (when the subject moves forward on the rod) or negative (when it moves backward). To measure the reference distance exactly, place a ruler on top of the rod, and refresh the background image. Then draw the Reference line at a specific distance from the rod. Note: Do not define the Reference zone in the middle of the rod. If you do that, distance from the zone border will always be positive, no matter what the position of the subject is. Zones for Turnaround Behavior Detection To automate turnaround behavior (mice grip themselves to the rod and turn around without falling off), you can define zones in front and at the back of the rod. Divide the arena in three main zones: Middle (the rod area), the front and the back areas just outside of the rod. It is then possible to detect turnaround behavior with the following sequence in the Zone transition variable: Middle (mouse in normal position) > Back > Front (the mouse reappears in view) > Middle. Detection Settings - Click Advanced. - Under Subject Contour, select one or more pixels for the first Erosion and Dilation filter. - Increase the first Erosion until the subject's tail is not detected anymore. - Then increase Dilation until the entire body is detected. Acquiring Data Training Phase This phase lasts typically three days. Each subject is placed on the rotarod for a maximum of 1 minute. The trial is repeated a few times each day, with 5 to 10 minutes inter-trial interval. Testing Phase Each subject is placed on the rotarod for a maximum of 1 minute. The trial is repeated two times with 5 to 10 minutes inter-trial interval. Scoring Behaviors Manually If you want to score when the animal falls off the rod, define the behavior Falling off under Manual Scoring Settings. After you have started the trial, watch the subjects in the video and in the Manual Scoring tab at the bottom of the screen, click the button for the arena (subject) that applies. Data Analysis Choose Analysis > Analysis Profile > New. Mouse Position In the Analysis profile, choose Distance to zone and select the Reference zone. Turnaround Behavior In the Analysis profile, click the button next to Zone transition. Select the following sequence: Middle > Back > Front > Middle. The zones must be defined in the Arena Settings. Latency to Fall If the camera is placed in front of the rotarod apparatus, you can measure the latency to fall by using the In zone variable. This calculates the time that the animal was detected in the arena (that is, until it fell off the rod). The Y-maze Test Introduction The Y-maze is constructed with three arms of equal length that extend from a central platform at a 120 degree angle. In the basic version, the animal is free to explore the maze arms. In a modified version, it is possible to close off some arms either to keep the animal in a specific arm for a fixed time once it has entered that arm, or to limit exploration to some arms, not others. The Y-maze is generally used to investigate alternation behavior, where animals are supposed to alternate choices of maze arms on successive opportunities. Irrespective of the precise function of alternation, the animal must remember which arm it had entered on a previous occasion to enable it to alternate its choice on a following trial. Therefore, the use of the Y-maze is based on the assumption that, following some pharmacological manipulation, it is primarily modified memory processes that are reflected in changed alternation rates. Spontaneous Alternation Definition Spontaneous Alternation is a behavioral test for measuring the willingness of rodents to explore new environments. Rodents typically prefer to investigate a new arm of the maze rather than returning to one that was previously visited. Many parts of the brain, including the hippocampus, septum, basal forebrain, and prefrontal cortex, are involved in this task (Conrad et al. 1996). Classical Procedure The animal is released in the center of the maze, and allowed to freely explore the three arms (A, B, C). Over the course of multiple arm entries, the subject is expected to show a tendency to enter a less recently visited arm (A > B > C > A > ...). The observer records the number of arm entries and the number of visits to the three arms without a re-visit in between (for example, A > B > C, B > C > A, etc.) in order to calculate the percentage of alternation. An arm entry is scored when all four limbs are within the arm. Calculation of Alternation Index Given a zone sequence: A > B > C > B > ... An alternation is defined as multiple entries into the three different arms on overlapping triplet sets. In this example the first three visits are an alternation: A > B > C > B > ... The next overlapping triplet set, B > C > B, is not an alternation. The Alternation index is given by the number of alternations divided by the maximum number of possible alternations, that is, the number of alternations that would be obtained if the animal visited the zones in the sequence: A > B > C > A > B > C ... For a 3-arm maze, like the Y-maze, the maximum number of alternations is equal to total number of visits minus 2. Alternation index is expressed in percentage: Alternation index = (Number of alternations / (Total number of zone visits - 2)) x 100 Spontaneous Alternation in EthoVision XT You can easily calculate the Alternation index using the outputs Alternations and Max Alternations in the Zone alternation dependent variable. For more information, see Zone alternation in the EthoVision XT Help. Delayed Alternation The delayed alternation task allows assessing spatial working memory in a T- or Y-maze. The main difference with spontaneous alternation is that performance is evaluated between trials. Classical Procedure In the first trial of the test, the animal is placed at the end of the start arm and has to choose between the two other arms that are baited. Once the choice is made, the subject is removed and after a variable delay, is returned in the start arm. In this second trial, the one arm baited is now the opposite arm to which was chosen during the first trial. The animal has to make a different choice than its first one (correct choice) to get the reward. Delayed Alternation in EthoVision XT For all tests where maze arms can be considered as targets of a choice, and others non-targets (errors), you can use outputs Target first visits and Total errors in the Target visits and errors dependent variable. For more information, see Target visits and errors in the EthoVision XT Help. References - Conrad, C.D., Galea, L.A., Kuroda, Y., McEwen, B.S. (1996). Chronic stress impairs rat spatial memory. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The Social Interaction Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-social-interaction-test Chapter: EthoVision XT The Social Interaction Test Introduction Measuring Social Interactions The Social Interaction test is widely used as a rodent model of anxiety-like behavior, under the assumption that anxiety is incompatible with social behavior (File and Hyde, 1978; File, 1980, 1988). So, an increase in anxiety generally results in a decrease in time spent on social interaction. The Social Interaction test is used to measure i) sensitivity to both anxiogenic and anxiolytic stimuli, ii) sensitivity to pharmacological, physiological and environmental manipulations and iii) ethologically relevant behaviors that do not require confounding manipulations such as food deprivation, pain or conditioned fear. Until recently, it has been difficult to automate the test with tracking systems. The features in EthoVision XT make this possible. This document describes the general procedure of how to do this. In most cases for a social interaction test you need the Social Interaction module. This module allows you to track two or more subjects in one arena. This module also includes the Deep learning option for individual recognition in a 2-subject interaction test. Here below you find an overview of the ways you can implement a social interaction test in EthoVision XT: Sociability Test (1-Subject Tracking) If you intend to track a free-moving subject while a second subject is caged (social target) and barely visible from above, you can track only the free-moving animal and measure the behavior of that animal towards the cage defined as a zone. In that case you do not need the Social Interaction module. Social Interaction - with Deep Learning-Based Recognition This solution, new in EthoVision XT 18, is based on artificial intelligence which discriminates between two subjects in the arena. One of the two subjects must be marked, e.g. its back being partially shaved. For this solution you can use a monochrome digital camera. Note: In order to apply artificial intelligence to animal tracking you need to have a compatible Graphics Processing Unit (GPU) installed on the EthoVision XT computer. See the EthoVision XT Help for more information. Social Interaction - Marker-Based Tracking This option assumes that you can color-mark your subjects that interact in the arena, and you have a color camera compatible with EthoVision XT. Most of this chapter is based on this solution. Social Interaction - Live Mouse Tracker With the Live Mouse Tracker add-on module you can import and analyze Live Mouse Tracker data. Live Mouse Tracker allows long-term analysis of behavior of socially-grouped mice. With Live Mouse Tracker you do not have to color-mark the subjects, however each subject must have a RFID chip implanted. For more information, see the EthoVision XT Help. The Sample Experiment To see an example of a social interaction test carried out in EthoVision XT, see also the sample experiment Social Interaction XT190 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. Next, in EthoVision XT, select File > Restore Backup and select this file. For more information, see the document Description of sample experiments of EthoVision XT.pdf. References - File, S.E., (1980) The use of social interaction as a method for detecting anxiolytic activity of chlordiazepoxide-like drugs. Journal of Neuroscience Methods 2, 219-238. - File, S.E., (1988) How good is social interaction as a test of anxiety? In: Simon, P., Soubrie, P., and Widlocher, D., Selected Models of Anxiety, Depression and Psychosis. Basel: Karger, 151-166. - File, S.E., and Hyde, J.R.G., (1978) Can social interaction be used to measure anxiety?, British Journal of Pharmacology 62, 19-24. - Lapiz-Bluhm, M.D.S., Bondi, C.O., Rodriguez, G.A., Bedard-Arana, T., and Morilak, D.A., (2008) Behavioural assays to model cognitive and affective dimensions of depression and anxiety in rats. Journal of Neuroendocrinology 20, 1115-1137. For a list of selected publications on EthoVision XT and the Social Interaction test, see the results of Google Scholar. Physical Setup The following suggestions are aimed at optimizing video tracking of multiple, color-marked animals. Lighting Conditions - For general information on lighting conditions, see the section Physical Setup in the chapter The Open Field Test. - Use a sensitive camera if possible. A low light intensity makes it difficult to separate different colors. When it is not possible to use a sensitive camera or strong illumination in your setup, try using fluorescent marker colors with UV lighting. - For optimal color separation, illuminate your setup with lamps that approximate to day-light in color temperature, that is, have a wide spectrum range. Marked vs. Unmarked Subjects In some cases it is required that the identity of the animals that interact in the arena is known and followed, for example in resident-intruder or male-female interactions, or whenever one needs to separate behavioral endpoints (e.g. speed, zone visited) for each individual. In such situations, we recommend marking the animals (see below). EthoVision XT can also track unmarked animals, however identity switches may occur. It is not guaranteed that the correct identity of each unmarked animal is kept throughout the trial. Markers for When Using the Deep Learning Technique When using Deep learning, shave the back of one subject so that it looks different from the other. The shaved part should always be visible from the top. For more details, see the EthoVision XT Help. Color Marker Characteristics - Use a color scale (for example from a paint company) to find out which colors are most easily recognized by EthoVision in your setup and lighting conditions. Do this before applying color markers to your animals. - Use colors that have different hue values. For example, use orange and green, pink and yellow, not red and orange. Avoid using red for marking, since it looks like blood. - Note that marking your animals may stress them, and therefore affect their behavior. If necessary, ensure that you select a marking method that lasts for a longer period of time. - Make sure that the marker is as round as possible. This will ensure that the relative movement of the center of gravity of the marker is the same in all directions when the edges of the marker change due to posture changes or otherwise. - Make sure the marker is not too big; the marker can interfere with proper detection of the body contour. For example, make sure that a dark marker on a white animal does not cover the complete width of the animal because it can cause the body to be split in two during tracking in EthoVision XT. - See also Tips for Color Tracking in the EthoVision XT Help. The Social Interaction Test in EthoVision XT Create an Experiment For Live Mouse Tracker: - Choose File > New and in the dialog that opens select Live Mouse Tracker experiment. - For the rest of the procedure, see the EthoVision XT Help. For all other cases: Choose File > New From Template and choose a predefined template in the guided setup. Experiment Settings Choose Setup > Experiment Settings. - Under Video Source, click the video icon in the camera row and adjust the camera settings if necessary. - Under Subjects, specify the Subject roles (for example Resident or Intruder, or Subject 1 and Subject 2). Do not enter the ID of the individual animals. - Under Tracked Features, select the option that corresponds to your needs. In most cases that is Center-point, nose-point and tail-based detection. - Under Body Point Detection Technique, select Contour-based if you use color-marked animals, or Deep learning if your subjects look different (e.g. the back of one individual has been partially shaved). Note: You can use Deep learning to track two subjects per arena. The Deep learning technique works if you have a recent graphics card and the driver is up to date. Manual Scoring Settings Choose Setup > Manual Scoring Settings. Here you can define behaviors that you score manually, for instance by pressing a keyboard key. In the template experiment, two start-stop behaviors, Rearing and Grooming, have been defined. Define other behaviors if needed, for example Sniffing and Boxing. For more information, see Set Up an Experiment > Manual Scoring Settings in the EthoVision XT Help. Trial Control Settings Choose Setup > Trial Control Settings > New. In the Trial Control Settings, define conditions for the start and stop of the track. - Starting condition. For instance, 'Start tracking 5 seconds after both animals are detected in the arena'. If you are tracking live, this 5-second delay enables you to put both animals in the arena and to take out your hand before tracking starts (5 seconds might not be enough; check beforehand how much time you need). Tip: To make sure that tracking starts when both individuals are in the arena, not before, click Settings in the Condition box before the Start track box. Select Current Duration from the Statistic list, then click Settings and then Actors. Select both subject names and select All selected subjects from the list. - Stopping condition. In order to be able to compare the tracks in the analysis, they must have the same length. Either define a Maximum Trial duration or a Stop track condition based on time. Detection Settings Choose Setup > Detection Settings > Detection Settings 1. Important: Follow the instructions in the order described below! If you selected Deep learning in the Experiment Settings, set the sample rate (below), and skip the next steps. The software is able to recognize the subjects automatically so you do not need to adjust subject contrast, size, contour filters etc. Go to Trial List. Sample Rate Click Video. Select a high sample rate: 25 (for PAL analog cameras) or 30 (for NTSC analog cameras and digital cameras) samples per second. Automated Setup Once the animals are in view, click Automated Setup. Select the type of animal you are going to test. Click Next and draw a rectangle around each subject. Make sure that you do this when the animals are not in close contact. If detection of the subject is not optimal after using the Automated Setup function, see Configure Detection Settings in the EthoVision XT Help for details on the advanced detection settings. Subject Identification for Color-Marked Subjects If you mark animals with colors, under Subject Identification make sure that Marker-assisted identification is selected. - Put the marked animals in the arena or play the video. Make sure to select a point in the video where the animals do not touch each other. Alternatively, place the animals in the arena one at a time. - In the Subject Identification section, select one of the subjects and click the Identification button. As a result, the Identification [Subject name] window opens. - Move the mouse pointer to the Video window so the pointer becomes an eyedropper. Move the eyedropper over the color marker of the subject you want to identify and click the left mouse button. - Fine-tune the color settings by adjusting the Hue, Saturation and Brightness in the Identification [subject role name] window. Change the range of color settings by changing the numbers or by resizing the Hue box on the vertical color bar, or resizing/moving the box in the color map (horizontally to adjust Saturation, vertically to adjust Brightness). As a result, the outline covers (almost) the complete marker. - Next, play the video to see in the Video window whether the marker is detected correctly in different parts of the arena. If the marker 'dances' then your color settings are too sensitive. Go back to step 4 and make the box larger. - When you are finished fine-tuning the color settings, you continue with setting the Minimal marker size: increase the Minimal marker size until, first, noise is not detected anymore and, second, the marker is not detected anymore (as a result, the outline in the Video window disappears). Now enter a value for the Minimal marker size that is somewhere in between. - Click OK when you are done and repeat steps 1-6 for the other subjects. For details, see Configure Detection Settings in the EthoVision XT Help. Source: EthoVision XT 19 - Application Manual --- ## EthoVision XT 19 - The USB-IO Box URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-the-usb-io-box Chapter: EthoVision XT The TTL Port Tester Use the TTL Port tester to test or demonstrate the TTL control functionality of the USB-IO box. You can also use it to simulate a TTL device (for example a pellet dispenser), trigger an action (for instance, switch on a light) or as a manual input device. Your TTL Port tester package includes a TTL Port tester PTTB-001x with a green RJ45 modular cable connected (1 meter long). Technical Specifications - Noldus device number: PTTB-001x - Power supply: 5 V DC, supplied by the USB-IO box - Current consumption: 30 mA (when one of the LEDs is on) - Connector: RJ45 8 pin modular - Dimensions: 60 x 40 x 20 mm (l x w x h) - Weight: 50 grams - CE compliant in accordance with EMC directive 2004/108/EC Test the USB-IO Box TTL Functionality We assume that you have set the port connection in the Experiment Settings and assigned the TTL Port tester to the arena. - Make sure that the USB-IO box is connected to (A) your EthoVision XT computer and (B) a power supply. - Connect the TTL Port tester to the TTL port on your USB-IO box which you want to test, using the green RJ45 modular network cable. When both the USB-IO box and the TTL Port tester are properly connected, the TTL power LED on the TTL Port tester is on. - Start EthoVision XT and open your experiment. In the Experiment Explorer, click Arena Settings. - In the Arena Settings window, click the Arena - Hardware mapping button. - In the Arena - Hardware mapping window, under the arena name, select TTL Port Tester (PTTB-001x) and click the Test button. - A new window appears. In the Command drop-down list, select either Light 1 on, Light 1 off, Light 2 on or Light 2 off and click Test. Check the LEDs on the TTL Port tester (Light 1 corresponds to OUT-1, and Light 2 to OUT-2) and the information in the window. Note: The signal from and to the TTL Port tester is not a network signal. The TTL Port tester cannot be connected via a network hub or similar. Manual Input You can also manually supply TTL input events to a TTL port. Follow steps 1-5 in the procedure above. Press either button IN-1 or IN-2 on the TTL Port tester and check the result in the window. Simulate a TTL Device You can connect the TTL Port tester to a TTL port that is defined for another TTL device, for instance, the Noldus Pellet dispenser. In this way, you can simulate the working of the device. You will see that the OUT-1 LED on the TTL Port tester is turned on whenever EthoVision XT decides to have the dispenser drop a pellet. Because it is not the pellet dispenser connected to the port, there will be no "pellet dropped" reply, but you can simulate this by pressing the IN-1 button on the TTL Port tester. The IN-2 button on the TTL Port tester is connected to the same input as the "error" line of the pellet dispenser. With a pellet dispenser connected, this line will become active whenever the dispenser fails to drop a pellet. By pressing the IN-2 button, you can simulate this occurrence. Trigger an Action with the TTL Port Tester You can use the manual input buttons on the TTL Port tester to trigger an action, for instance, switch on a light. Define a Trial Control condition based on the TTL Port tester and define that the light is switched on when, for instance, IN-1 is pressed. - Open your Trial Control Settings and in the Components pane click the button next to TTL Port Tester (under Conditions - Hardware). - In the Signal to check drop-down list select one of the following options: - Is button 1 pressed? or Is button 2 pressed? and in the Signal value drop-down list select True. Then click OK. The light will be on as long as the button is pressed. - Button 1 presses or Button 2 presses and in the Signal value drop-down list, select = and enter 1 as the value. Then click OK. To define the appropriate action: - In the Components pane under Actions, click the button next to the hardware you want to control. - In the Action to perform drop-down list, select which action should follow the condition you defined above. Then click OK. - Insert the Condition and Action box in the appropriate position in the Trial Control rule. Use the TTL Port Tester as a Manual Event Recorder Although you can score behaviors manually with EthoVision XT, you can also do so with the TTL Port tester. For example, in a resident-intruder test, during acquisition press the IN-1 button when the resident mouse is aggressive and the IN-2 button when the intruder mouse is aggressive. For more complex coding schemes, use the Manual Scoring Settings in EthoVision XT. If you use the TTL Port tester as a manual event recorder, you can view the number of key presses in a hardware log. In EthoVision XT from the Export menu, choose Track Data and select the Hardware log check box. Calculate the Statistics for the TTL Port Tester For testing purposes, you can calculate the number of times the buttons were pressed, or visualize when the lights were switched on. To do so, in the Analysis profile: - To analyze and visualize button presses, under Hardware click the button next to Hardware continuous. In other cases, skip this step. In the window that appears, next to Device type, select TTL Port Tester (PTTB-001x). Next to Device, select the correct device if you have more than one device connected. Next to Signal, select Button 1 pressed or Button 2 pressed. - To analyze or visualize the time when the lights were switched on, under Hardware select Hardware Command or Hardware State. Choose Command to view the time that the command was given. Choose Hardware state to visualize the status of the light (feedback from the TTL Port tester). In the Trial Statistics tab of the variable properties window, select the statistic Total, then click Add. You can now calculate the number of times the button was pressed, or the light was switched on and off, by running an analysis. Choose Analysis > Results > Statistics & Charts. Make sure that the correct Analysis profile is selected on the toolbar. Next, click Calculate. You can also visualize the button presses and the light being switched on and off in the Integrated Visualization. Choose Analysis > Results > Integrated Visualization. You will see in the Time Event Plot when the buttons were pressed, or when the lights were switched on and off. The Optical Isolated TTL-IO Interface Aim - To enable isolation between the Noldus USB-IO box or the Mini USB-IO box and a third party device, for example the Inscopix nVista camera system. - To connect the Noldus USB-IO box or the Mini USB-IO box to a third party device with BNC connectors. Important: This isolator is not intended for medical applications. Features - It supports TTL-output from and TTL-input to EthoVision XT (two lines each). - Output/input voltages 0-5 V. - Isolation protects the device from the so-called "ground loops". - Minimizes noise and prevents damage to the USB-IO box in the case the device connected does not function properly. Package Contents - PTISO-00x0 TTL-IO Isolator - 1x network cable with RJ45 connectors - 2x input/output double cables with BNC connectors Connect and Use - Connect a TTL port of the Noldus USB-IO box or Mini USB-IO box to the TTL-I/O port of the PTISO-00x0 Isolator. - Connect one or more of the In/Out BNC connectors of the PTISO-00x0 Isolator depending on your setup. For example, to trigger a device, use Out 1 or Out 2. - When setting the port connections, specify the TTL port and the line used. Technical Specifications - Type name: PTISO-0010 TTL-IO Isolator - Power requirements: 18-24 V DC; 0.02 A from USB-IO box - Isolation value: Supply 2kV (1 sec); TTL IO 5.3 kV (1 sec) - Connections: 1x RJ45 type from USB-IO; 4x BNC type, optical isolated TTL input/output - Input/Output: TTL level signal (0-5.5 V DC) - Dimensions: 31 x 113 x 67 mm (1 7/32 x 4 29/64 x 2 41/64 inches) Technical Specifications USB-IO Box Version 2 - Noldus model number: PTIO-002x - Power supply: 24 V DC - Current consumption: Max 2.0 A (varies depending on the number and type of devices connected) - Connections: 12 TTL control connections (24 TTL Input lines and 24 TTL output lines) with RJ45 ports; 13 Special Device Interface connections with RJ45 ports - Cables: Power supply 24V 3A DC with mains adapter; USB cable with connectors of type A and B - Operating temperature: 0 to +40 degrees C (+32 to +104 degrees F) - Storage temperature: -20 to +70 degrees C (-4 to +158 degrees F) - Operating humidity: Up to 80%, no condensation - Dimensions: 160 x 160 x 90 mm / 6.3 x 6.3 x 3.5 inches (L x W x H) Mini USB-IO Box Version 1 - Noldus model number: PTIO-003x - Power supply: 24 V DC - Current consumption: 1.0 A (varies depending on the number and type of devices connected). Important: Max. overall current for all TTL ports must not exceed 0.5 A. - Interface to PC: USB-2 - I/O connections: 4 TTL control (representing 8 TTL Input lines and 8 TTL output lines) with RJ45 modular type connectors; 1 Multi TTL (representing 16 TTL output lines and external device supply) with 20 way IDC connector; 1 Special Device Interface with RJ45 modular type connector - Cables: Power supply 24V type 70 A24 with mains adapter; USB cable with connectors of type A and B, 3m type SB2403 - Operating temperature: 0 to +40 degrees C (+32 to +104 degrees F) - Storage temperature: -20 to +70 degrees C (-4 to +158 degrees F) - Operating humidity: Up to 80%, no condensation - Dimensions: 175 x 81 x 30 mm / 6.9 x 3.2 x 1.2 inches (L x W x H) The Nortio Interface System Nortio is the hardware and software system that allows control of hardware devices by EthoVision in a very efficient manner. The system consists of one Nortio Core, connected to the EthoVision XT computer, and one or more Nortio Hubs, which form the interface with various devices such as PhenoTyper Top Units, Pellet dispensers, etc. - EthoVision XT 18 supports one Nortio Core connected to one Nortio T12T TTL Terminal Hub. Check regularly the Noldus web site for updates. - When using PhenoTyper 2, we recommend connecting up to eight PhenoTypers to one Nortio TTL Terminal Hub. - Nortio is compatible with EthoVision XT 16 and later versions. - A daisy-chaining configuration of multiple Nortio Hubs (not yet available) will greatly increase the number of possible connections to one EthoVision XT computer, with minimal cabling. Main Features Compared with the previous USB-IO box, the Nortio system has several advantages. Speed The Nortio system does not depend on USB protocols as was the case for the USB-IO box and the Mini USB-IO box. A significant amount of data is processed within the Nortio Core, and is therefore independent of the operating system of the computer. As a result, there is less variability in the time needed to process a command or receive an input signal. - Trial Control actions that are sent out to the Nortio Core are processed within 10 ms. - EthoVision XT synchronizes the data with the Nortio Core once per video frame. - A sequence of events from receiving an input signal and sending out a command in response can take up to two frames. For a typical experiment with video at 30 frames per second, that corresponds to 66.7 ms. Higher Degree of Scalability With Nortio Core connected to several Nortio Hubs it becomes easier to expand systems at minimal cost. Note: The current release is limited to one Nortio Core and one Nortio T12T TTL Terminal Hub. Both are included in the Trial and Hardware Control add-on module of EthoVision XT. Improved Usability - The system architecture designed for Nortio makes it possible to reduce cabling, particularly in complex configurations like that of multiple PhenoTypers. - Future versions of the Nortio Hub can in principle host interfaces to third-party devices. Therefore, there is no need of separate interfaces between EthoVision XT and those devices. - Robust connectors make device communication more reliable. Devices Supported with Nortio The following devices are supported with the Nortio Hub T12T TTL interface: - Noldus Pellet dispenser (Noldus type number PTPD-001x) - Noldus Pellet receptacle (Noldus type number PTPR-001x) - Noldus Lickometer (Noldus type number PTLM-001x). Note: To use the Lickometer in combination with the Nortio system, you need to alter the jumper position in the electronics box. Instructions are found in the chapter The Lickometer in the PhenoTyper 2 - EthoVision XT 18 - Service Manual. - Noldus Beam Controller (Noldus type number PTBC-001x) - Top Unit TTL interface of PhenoTyper 2 (Noldus type number PT2I-01_TTL) - Shock, Tone, Light and Noise in the Ugo Basile Fear Conditioning System. Note: With EthoVision XT 17.5 and later versions you can have EthoVision XT control the Ugo Basile Fear Conditioning System without any additional hardware. See the connection schemes in the chapter Fear conditioning experiments in the EthoVision XT 18 - Application Manual. - White light in the Noldus Backlight unit (Noldus type number IRWB-xxxx) - The Med Associates Activity Wheel Brake (ENV-042) - The TTL Port Tester (for testing purposes; Noldus type number PTTB-001x) - Custom devices controlled through TTL signals For the Pellet dispenser, the Pellet receptacle, the Lickometer and the Feeding Monitor (IR Beam Controller), more information is available in the PhenoTyper 2 - EthoVision XT 18 - Service Manual and the PhenoTyper 2 - EthoVision XT 18 - Reference Manual. Components Nortio Core Product code: NOCO-IMX6-00xx The Nortio Core manages communication between each device and EthoVision XT. The Nortio Core is based on ARM architecture. ARM stands for Advanced RISC Machine, where RISC stands for Reduced Instruction Set Computing. Because of minimal power consumption and low heat generation, ARM-based chips are ideal for light and portable devices. Buttons and Ports Buttons: - Start - Press the button to switch on the Nortio Core. The red LED turns on for a few seconds. Wait about one minute, then the green LED turns on again and stays on. You can then start using the system. Ports currently in use: - Power adapter - For connecting to the mains power through its adapter Nortio NOPS-2403-0010 100-240V AC. - Ethernet board - RJ45 jack for connecting Nortio Core to the EthoVision XT PC through its dedicated 1GB Ethernet interface board. - Backbone cable - For connecting Nortio Core to one of the Nortio Hubs. Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - Tips for Color Tracking - Color Markers URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-color-markers-0eN Chapter: EthoVision XT Color Markers Aim You need the information below when you track color-marked animals. General Information - Use a color scale (for example from a paint company) to find out which colors are most easily recognized by EthoVision XT in your setup and lighting conditions. Do this before applying color markers to your animals. - Use colors that have different hue values. For example, use red and green and not red and orange. - For birds and animals in general that perceive color in the red-green wavelength range, using red markers is not advisable as it looks like blood, and may influence the subjects' behavior. Rodents have dichromatic vision, that is, they perceive wavelengths around the blue and the green, so probably red is seen as gray or a mix of blue and green. Albino animals have heavily impaired vision, both in acuity and color perception. - If you want to use red together with orange or pink, provide more light around (by means of additional lamps) and then close the aperture of the camera lens. - If the color of your marker is also present elsewhere in the arena, you can get rid of it by using a minimal marker size. - Marking your animals may stress them, and therefore affect their behavior. If necessary, ensure that you select a marking method that lasts for a longer period of time. - To improve color discrimination in EthoVision XT, you can alter the Saturation settings of the video image (this only applies for live tracking). In the Detection Settings window, under Video click Image Quality. Alter the Saturation value and check in the video window if the markers are more distinguishable. However, before altering the Image Quality always try to optimize the lighting and camera aperture settings. Note that if you alter the Image Quality values you need to redefine the color detection (click Identification for each subject). Marker Characteristics - Make sure that the marker is visible as much as possible; preferably place it on the center of the animal's backbone. - Make sure that the marker is as round as possible. This will ensure that the relative movement of the center of gravity of the marker is the same in all directions when the edges of the marker change due to posture changes or otherwise. For color marker tracking it will help to prevent the jitter of the marker. - When you use marker assisted tracking, make sure the marker is not too big; the marker can interfere with proper detection of the body contour. For example, make sure that a dark marker on a white animal does not cover the complete width of the animal because it can cause the body to be split in two. Markers for Rodents and Other Small Mammals There are several ways to color mark small mammals like rats and mice. Color mark as much of the head and back as possible. This way the mark is always visible, also when the animals rear or turn. - Livestock markers are intended for large animals but can also be used on smaller animals. These markers come as paint sticks and spray cans, and are available in many colors including fluorescent ones. The markers are weather-resistant, non-toxic and they stay on for one or two days. - Fluorescent tubes can be used for color-tracking in the dark. It is possible to mark rats with fluorescent markers and illuminate the arena with UV-light (350–400 nm, 2 lamps of 1.2 W each). The fluorescent spots on the rats appear as patches of different color against a dark background. EthoVision XT can then effectively separate the two animals (source: J.P. Johansson and M.L. Carlsson, Institute of Clinical Neuroscience, Göteborg University, Göteborg, Sweden). See Tracking Colors in the Dark. - The fur of rats and mice can be marked with commercial products for dyeing human hair. Dark fur can be bleached (like dark human hair, to make it blonde) before coloring. Hair dyes are available in many bright colors, and provide long-lasting coloration. Schwarzkopf PolyColor Hair Color Cream, for example, can be applied to a rat's fur with a cotton swab. - Permanent marker pens (for example, Edding or Marks-A-Lot) present a cheap and easy way to mark small mammals. Take care to make a large and uniform blob. This method may only work for a short period of time as many species may remove the mark by grooming. - Chalk ink markers can be used to mark rodents. They are available in a variety of bright colors. Their main advantages are that they are not toxic, are readily available and inexpensive, and, in contrast with other marker types, can be applied directly to dark fur without bleaching it first. Coloration may last several hours. It is advised not to mark the animals just before you start a test, because the handling of the animals might affect their subsequent behavior. If you use a marker that stays on the animal for only a short period of time, you should habituate the animal to the marking procedure. - Colored jackets can be used to color-track mammals with colored fur like cats. Jackets cover most of the cat's back, and can be provided with Velcro strips, so one can place pieces of cloth of different colors to test optimal color combinations. Orange vests may give problems when animals are red-haired, so they should be replaced by either bright green, yellow, or pink. Markers for Large Mammals You can use livestock markers to mark large animals such as cows, sheep, and pigs. Markers for Birds - The feathers of birds can be marked with commercial products for dyeing human hair or permanent marker pens (see the Small Mammals section above). - Seabird ecologists often use picric acid (2,4,6-trinitrophenol, TNP) to mark their birds. You paint a dab of this yellow liquid on the feathers. It is permanent and very bright yellow, although it turns orange in the sun. To use it to mark animals you dissolve it in an excess of ethanol. If the acid (a powder) dries, it becomes explosive, so it is important to keep it dissolved (source: J. Blount, Division of Environmental and Evolutionary Biology, University of Glasgow, UK). Markers for Fish - Fish can be color marked by attaching plastic pearls. This technique has been used successfully in Mediterranean damsel fish (Chromis chromis, size: about 9 cm long) and trout (about 25 cm). Colored pearls can be bought from a toy store or a warehouse. Use bright colors that are as distinct as possible. For damsel fish, pearls of 1 cm are used; for trout, pearls of 8 mm are used. - Damsel Fish. The pearls can be attached under the dorsal fin with blue non-resorbable surgery polyamide mono filament (for example, from B/Braun), using a surgical needle under anaesthesia. The fish can be anesthetized by placing them in a small tank with 2-phenoxy-ethanol (0.3 ml/l for the damsel fish) for five minutes before attaching the pearl. The bottom and sides of the arena have to be very dark. The pearls do not significantly impair swimming in damsel fish (source: M. Ylieff, Institut de Zoologie, Université de Liège, Belgium). - Trout. The pearls can be attached at the base of the first ray of the dorsal fin. Use a curved needle and normal fishing line to attach the pearls to the fin. X-ray images showed no injury after several weeks using this method. The fish can be anesthetized by placing them in a tank with 2-phenoxy-ethanol (0.3 ml/l) before attaching the pearl. - Visible implant fluorescent elastomer (VIE) tags are produced by Northwest Marine Technologies (NMT). VIE material is implanted beneath transparent or translucent tissue (it may become difficult to detect beneath pigmented tissue). The material is injected as a liquid and soon turns into a pliable, bio-compatible solid. VIE colors are well visible under normal lighting conditions and have greatly enhanced visibility under ultra-violet light or with other fluorescence enhancing techniques. You can test which colors work best in your own setup with a color test patch from NMT. --- ## EthoVision XT 19 - Tips for Color Tracking - Color Markers URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-color-markers Chapter: EthoVision XT Color Markers Aim You need the information below when you track color-marked animals. General Information - Use a color scale (for example from a paint company) to find out which colors are most easily recognized by EthoVision XT in your setup and lighting conditions. Do this before applying color markers to your animals. - Use colors that have different hue values. For example, use red and green and not red and orange. - For birds and animals in general that perceive color in the red-green wavelength range, using red markers is not advisable as it looks like blood, and may influence the subjects' behavior. Rodents have dichromatic vision, that is, they perceive wavelengths around the blue and the green, so probably red is seen as gray or a mix of blue and green. Albino animals have heavily impaired vision, both in acuity and color perception. - If you want to use red together with orange or pink, provide more light around (by means of additional lamps) and then close the aperture of the camera lens. - If the color of your marker is also present elsewhere in the arena, you can get rid of it by using a minimal marker size. - Marking your animals may stress them, and therefore affect their behavior. If necessary, ensure that you select a marking method that lasts for a longer period of time. - To improve color discrimination in EthoVision XT, you can alter the Saturation settings of the video image (this only applies for live tracking). In the Detection Settings window, under Video click Image Quality. Alter the Saturation value and check in the video window if the markers are more distinguishable. However, before altering the Image Quality always try to optimize the lighting and camera aperture settings. Note that if you alter the Image Quality values you need to redefine the color detection (click Identification for each subject). Marker Characteristics - Make sure that the marker is visible as much as possible; preferably place it on the center of the animal's backbone. - Make sure that the marker is as round as possible. This will ensure that the relative movement of the center of gravity of the marker is the same in all directions when the edges of the marker change due to posture changes or otherwise. For color marker tracking it will help to prevent the jitter of the marker. - When you use marker assisted tracking, make sure the marker is not too big; the marker can interfere with proper detection of the body contour. For example, make sure that a dark marker on a white animal does not cover the complete width of the animal because it can cause the body to be split in two. Markers For Rodents And Other Small Mammals There are several ways to color mark small mammals like rats and mice. Color mark as much of the head and back as possible. This way the mark is always visible, also when the animals rear or turn. - Livestock markers are intended for large animals but can also be used on smaller animals. These markers come as paint sticks and spray cans, and are available in many colors including fluorescent ones. The markers are weather-resistant, non-toxic and they stay on for one or two days. - Fluorescent tubes can be used for color-tracking in the dark. It is possible to mark rats with fluorescent markers and illuminate the arena with UV-light (350–400 nm, 2 lamps of 1.2 W each). The fluorescent spots on the rats appear as patches of different color against a dark background. EthoVision XT can then effectively separate the two animals (source: J.P. Johansson and M.L. Carlsson, Institute of Clinical Neuroscience, Göteborg University, Göteborg, Sweden). - The fur of rats and mice can be marked with commercial products for dyeing human hair. Dark fur can be bleached before coloring. Hair dyes are available in many bright colors and provide long-lasting coloration. Schwarzkopf PolyColor Hair Color Cream, for example, can be applied to a rat's fur with a cotton swab. - Permanent marker pens (for example, Edding or Marks-A-Lot) present a cheap and easy way to mark small mammals. Take care to make a large and uniform blob. This method may only work for a short period of time as many species may remove the mark by grooming. - Chalk ink markers can be used to mark rodents. They are available in a variety of bright colors. Their main advantages are that they are not toxic, are readily available and inexpensive, and, in contrast with other marker types, can be applied directly to dark fur without bleaching it first. Coloration may last several hours. It is advised not to mark the animals just before you start a test, because the handling of the animals might affect their subsequent behavior. If you use a marker that stays on the animal for only a short period of time, you should habituate the animal to the marking procedure. - Colored jackets can be used to color-track mammals with colored fur like cats. Jackets cover most of the cat's back, and can be provided with Velcro strips, so one can place pieces of cloth of different colors to test optimal color combinations. Orange vests may give problems when animals are red-haired, so they should be replaced by either bright green, yellow or pink. Markers For Large Mammals You can use livestock markers to mark large animals such as cows, sheep and pigs. Markers For Birds - The feathers of birds can be marked with commercial products for dyeing human hair or permanent marker pens (see the small mammals section above). - Seabird ecologists often use picric acid (2,4,6-trinitrophenol, TNP) to mark their birds. You paint a dab of this yellow liquid on the feathers. It is permanent and very bright yellow, although it turns orange in the sun. To use it to mark animals you dissolve it in an excess of ethanol. If the acid (a powder) dries, it becomes explosive, so it is important to keep it dissolved (source: J. Blount, Division of Environmental and Evolutionary Biology, University of Glasgow, UK). Markers For Fish - Fish can be color marked by attaching plastic pearls. This technique has been used successfully in Mediterranean damsel fish (Chromis chromis, size: about 9 cm long) and trout (about 25 cm). Colored pearls can be bought from a toy store or a warehouse. Use bright colors that are as distinct as possible. For damsel fish, pearls of 1 cm are used and for trout, pearls of 8 mm are used. - Damsel Fish. The pearls can be attached under the dorsal fin with blue non-resorbable surgery polyamide mono filament (for example, from B/Braun), using a surgical needle under anaesthesia. The fish can be anesthetized by placing them in a small tank with 2-phenoxy-ethanol (0.3 ml/l for the damsel fish) for five minutes before attaching the pearl. The bottom and sides of the arena have to be very dark. The pearls do not significantly impair swimming in damsel fish (source: M. Ylieff, Institut de Zoologie, Université de Liège, Belgium). - Trout. The pearls can be attached at the base of the first ray of the dorsal fin. Use a curved needle and normal fishing line to attach the pearls to the fin. X-ray images showed no injury after several weeks using this method. The fish can be anesthetized by placing them in a tank with 2-phenoxy-ethanol (0.3 ml/l) before attaching the pearl. - Visible implant fluorescent elastomer (VIE) tags are produced by Northwest Marine Technologies (NMT). VIE material is implanted beneath transparent or translucent tissue (it may become difficult to detect it beneath pigmented tissue). The material is injected as a liquid and soon turns into a pliable, bio-compatible solid. VIE colors are well visible under normal lighting conditions and have greatly enhanced visibility under ultra-violet light or with other fluorescence enhancing techniques. You can test which colors work best in your own setup with a color test patch from NMT. --- ## EthoVision XT 19 - Tips for Color Tracking - Lighting for Animal Tracking URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-lighting-for-animal-tracking Chapter: EthoVision XT Lighting for Animal Tracking Reference Information - For color rendering index: http://en.wikipedia.org/wiki/Color_Rendering_Index When buying LED lamps, make sure that the technical specifications report the required color temperature and CRI. A disadvantage of most LED lamps is that they cast light in one direction at a narrow angle compared to energy-saving fluorescent lights, creating more shadows and reflections. We have tested the following lamps: - True-Light Energy Saving Light 15 W. Color Temperature 5500 ºK, Power 15 W, Brightness 720 lumen. - ProLite Helix Compact Fluorescent ES 15. Color Temperature 6400 ºK, Power 15 W, Brightness 795 lumen. Both lamps have E27 fitting. Recommendations - Choose a light source with color temperature ≥ 5500 °K and color rendering index > 95. - Do not use halogen lamps; instead use LEDs, as halogen light is too "cold". - Use at least four lights and place them at equal distance around the arena, at least 1 m from the subjects. - If the image of white animals looks overexposed, close the aperture of the camera lens. Too much light heavily reduces color discrimination. - If light creates shadows in the arena, place white sheets in front of the lamps to obtain more diffuse light. - Set the white balance of your camera to obtain a wider color spectrum. Consult the manual of your camera for the exact procedure. Generally, you can set the camera to white balance the image automatically. To check whether this is done correctly, point the camera to a white wall and check whether the wall appears white in the video image. If this is not the case, search for the settings to set the white balance manually. Point the camera to a white wall and set the white balance. Make sure you do this every time the light changes. Useful Websites Below you find the web addresses of full spectrum light producers: - True-Light: http://www.true-light.eu/en/ - BlueMax Lighting: https://www.fullspectrumsolutions.com - OSRAM: http://www.osram.com/ - Philips: https://www.lighting.philips.com/main/home - Pro-Lite: http://www.prolite-lamps.co.uk - Viva-Lite: http://www.viva-lite.nl/home.html --- ## EthoVision XT 19 - Tips for Color Tracking - Lighting Recommendations URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-lighting-recommendations Chapter: EthoVision XT Lighting Recommendations For information on color rendering index, see the Wikipedia article on Color Rendering Index. When buying LED lamps, make sure that the technical specifications report the required color temperature and CRI. A disadvantage of most LED lamps is that they cast light in one direction at a narrow angle compared to energy-saving fluorescent lights, creating more shadows and reflections. We have tested the following lamps: - True-Light Energy Saving Light 15 W. Color Temperature 5500 ºK, Power 15 W, Brightness 720 lumen. - ProLite Helix Compact Fluorescent ES 15. Color Temperature 6400 ºK, Power 15 W, Brightness 795 lumen. Both lamps have E27 fitting. Recommendations - Choose a light source with color temperature ≥ 5500 °K and color rendering index > 95. - Do not use halogen lamps; instead use LEDs, as halogen light is too "cold". - Use at least four lights and place them at equal distance around the arena, at least 1 m from the subjects. - If the image of white animals looks overexposed, close the aperture of the camera lens. Too much light heavily reduces color discrimination. - If light creates shadows in the arena, place white sheets in front of the lamps to obtain more diffuse light. - Set the white balance of your camera to obtain a wider color spectrum. Consult the manual of your camera for the exact procedure. Generally, you can set the camera to white balance the image automatically. To check whether this is done correctly, point the camera to a white wall and check whether the wall appears white in the video image. If this is not the case, search for the settings to set the white balance manually. Point the camera to a white wall and set the white balance. Make sure you do this every time the light changes. --- ## EthoVision XT 19 - Tips for Color Tracking - Markers for Reptiles URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-markers-for-reptiles-Xz1 Chapter: EthoVision XT Markers for Reptiles Nail polish (available in many colors) can be used to mark lizards. The mark usually lasts 10 days in small (up to 10 cm) lizards in the field. (Source: M. Massot, Laboratoire d'Ecologie, Université Pierre et Marie Curie, Paris, France). Markers for Amphibians For amphibians you can use visible implant fluorescent elastomer (VIE) tags. They work fine with small tadpoles. Markers for Insects - Acrylic paint (for example, Royal Talens Amsterdam deco) can be used to mark insects. The paint can be applied with a fine brush or thread. You have to hold the insect with forceps until the paint is dry. (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands; S. Belmain, Natural Resources Institute, Chatham Maritime, UK). - Some species of parasitic wasp develop a colored abdomen when you feed them honey with a non-toxic dye, as used for coloring food. The dyes can be obtained from a normal bakery. The advantage of this method over marking with paint is that you do not have to anesthetize the insects (which may influence their behavior and survival). The method will work best in insects with unpigmented abdomens. (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands). - Mosquitoes can be fed with a sugar solution in water containing fluorescent dyes. Blue-black light is used to illuminate the subjects. See the paper by Sarkar et al. 2017, International Journal of Mosquito Research 4(6): 5–9. Other techniques using fluorescent powders or dyes are described by Verhulst et al. (2013), Parasites & Vectors 6: 200–206. - For insects you can also use visible implant fluorescent elastomer (VIE) tags. - Aphids have successfully been color marked with fluorescent powders. The powders that are fluorescent under ultraviolet light can be obtained from Day Glo, Cleveland, Ohio. For optimal detection, a high intensity UV long wave UV 366 nm lamp can be used. To apply the powder to the aphids, gently dust the powder with a powder insufflator. Make sure each aphid gets at least 10 grains of powder. For more information see Thomas et al. (1997), Journal of Agricultural Entomology 14(2): 187–198. - Ants can be color marked with a small drop of paint on the thorax or the abdomen. Anesthetize the ant with CO2. To restrain the ant during painting, use a sponge with a single strand of hair attached to it. Place the ant under the hair and apply the color mark. Transfer the ant to a plastic tube and allow the paint to dry for approximately 20 minutes. After 24 hours, the ant can be used in experiments. - For a review of the marking techniques see Hagler & Jackson (2001), Annual Reviews of Entomology 46: 511–543. Markers for Zooplankton - Nanoparticles known as Quantum dots can be applied to the carapace of crustaceans Daphnia sp. Like any other fluorescent molecule, they must be excited with light of one wavelength in order to emit fluorescence at a longer wavelength. Among the advantages of these markers is great photostability — animals can be tracked for up to 24 hours after labeling, without loss of signal due to photo-bleaching. Note that some quantum dots may be toxic to animals. For more information see Lard et al. (2010), PLoS ONE 5(10): e13516. doi:10.1371/journal.pone.0013516. Tracking Colors in the Dark If you want to apply color markers and track the animals in the dark, you need lighting conditions that allow EthoVision XT to detect the marker and detect the contour of the animals. To track colors in the dark, combine fluorescent markers with ultraviolet (UV) light. UV light makes the marker emit visible light, which is then detected by the camera. EthoVision will track the marker as it would normally do in daylight. To track the contour of the animal, you must also use light sources other than UV. If you only use UV light, the contour of the animal will not be seen. A couple of solutions that may work: - Use visible light. Make sure that the contrast between animal and background is maximized. - Use infrared (IR) light. Some good color cameras are also sensitive to IR light. You can then use IR light to enhance the contour of the animal, provided that the camera lens does not have an IR-block filter. Note that fine-tuning this setup may take considerable effort and time. Useful Websites - Carmel livestock markers: http://www.livestockmarkers.com - La-co livestock markers: http://www.allweathermarker.com - Net-Tex livestock markers: http://www.net-tex.co.uk (search for "marker") - Edding markers: http://www.edding.com - Marks-A-Lot markers: http://www.avery.com - MS Schippers (livestock or rodent markers): https://www.schippers.nl (see the product line "MS Merkstift", in Dutch) - Chalk Ink markers: http://www.chalkink.com (choose a 15-mm broad tip marker) - Schwarzkopf hair dyes: https://www.schwarzkopf.com - Royal Talens acrylic paint: https://www.royaltalens.com/en/products/acrylic-colours/ - B/Braun surgical sutures and needles for attaching pearls to fish: http://www.bbraun.com - Northwest Marine Technology fish markers: http://www.nmt.us/ - Invitrogen quantum dots: http://www.thermofisher.com/nl/en/home/brands/invitrogen.html - Fluorescent powders: https://www.dayglo.com/ --- ## EthoVision XT 19 - Tips for Color Tracking - Markers for Reptiles URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-markers-for-reptiles Chapter: EthoVision XT Markers for Reptiles Nail polish (available in many colors) can be used to mark lizards. The mark usually lasts 10 days in small (up to 10 cm) lizards in the field. (Source: M. Massot, Laboratoire d'Ecologie, Université Pierre et Marie Curie, Paris, France). Markers for Amphibians For amphibians you can use visible implant fluorescent elastomer (VIE) tags. They work fine with small tadpoles. Markers for Insects - Acrylic paint (for example, Royal Talens Amsterdam deco) can be used to mark insects. The paint can be applied with a fine brush or thread. You have to hold the insect with forceps until the paint is dry. (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands; S. Belmain, Natural Resources Institute, Chatham Maritime, UK). - Some species of parasitic wasp develop a colored abdomen when you feed them honey with a non-toxic dye, as used for coloring food. The dyes can be obtained from a normal bakery. The advantage of this method over marking with paint is that you do not have to anesthetize the insects (which may influence their behavior and survival). The method will work best in insects with unpigmented abdomens. (Source: G. Driessen, Institute of Evolutionary and Ecological Sciences, Leiden University, The Netherlands). - Mosquitoes can be fed with a sugar solution in water containing fluorescent dyes. Blue-black light is used to illuminate the subjects. See the paper by Sarkar et al. 2017, International Journal of Mosquito Research 4(6): 5–9. Other techniques using fluorescent powders or dyes are described by Verhulst et al. (2013), Parasites & Vectors 6: 200–206. - For insects you can also use visible implant fluorescent elastomer (VIE) tags. - Aphids have successfully been color marked with fluorescent powders. The powders that are fluorescent under ultraviolet light can be obtained from Day Glo, Cleveland, Ohio. For optimal detection, a high intensity UV long wave UV 366 nm lamp can be used. To apply the powder to the aphids, gently dust the powder with a powder insufflator. Make sure each aphid gets at least 10 grains of powder. For more information see Thomas et al. (1997), Journal of Agricultural Entomology 14(2): 187–198. - Ants can be color marked with a small drop of paint on the thorax or the abdomen. Anesthetize the ant with CO2. To restrain the ant during painting, use a sponge with a single strand of hair attached to it. Place the ant under the hair and apply the color mark. Transfer the ant to a plastic tube and allow the paint to dry for approximately 20 minutes. After 24 hours, the ant can be used in experiments. - For a review of the marking techniques see Hagler & Jackson (2001), Annual Reviews of Entomology 46: 511–543. Markers for Zooplankton - Nanoparticles known as Quantum dots can be applied to the carapace of crustaceans Daphnia sp. Like any other fluorescent molecule, they must be excited with light of one wavelength in order to emit fluorescence at a longer wavelength. Among the advantages of these markers is great photostability; animals can be tracked for up to 24 hours after labeling without loss of signal due to photo-bleaching. Note that some quantum dots may be toxic to animals. For more information see Lard et al. (2010), PLoS ONE 5(10): e13516. doi:10.1371/journal.pone.0013516. Tracking Colors in the Dark If you want to apply color markers and track the animals in the dark, you need lighting conditions that allow EthoVision XT to detect the marker and detect the contour of the animals. To track colors in the dark, combine fluorescent markers with ultraviolet (UV) light. UV light makes the marker emit visible light, which is then detected by the camera. EthoVision will track the marker as it would normally do in daylight. To track the contour of the animal, you must also use light sources other than UV. If you only use UV light, the contour of the animal will not be seen. A couple of solutions that may work: - Use visible light. Make sure that the contrast between animal and background is maximized. - Use infrared (IR) light. Some good color cameras are also sensitive to IR light. You can then use IR light to enhance the contour of the animal, provided that the camera lens does not have an IR-block filter. Note that fine-tuning this setup may take considerable effort and time. --- ## EthoVision XT 19 - Tips for Color Tracking - Pixel Format Conversion Tables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-pixel-format-conversion-tables-34L Chapter: EthoVision XT Pixel Format Conversion Tables If the Starting Pixel Format Is Mono8 or YUV422 (YUYV) Packed When You Set the Color Space To...Then the Pixel Format Changes To... UYVYYUV422 Packed RGB24YUV422 (YUYV) Packed RGB32YUV422 (YUYV) Packed YV12YUV422 (YUYV) Packed YUY2YUV422 (YUYV) Packed Y800Mono8 BYRGBayer RG8 If the Starting Pixel Format Is YUV422 Packed When You Set the Color Space To...Then the Pixel Format Changes To... UYVYYUV422 Packed RGB24YUV422 Packed RGB32YUV422 Packed YV12YUV422 Packed YUY2YUV422 (YUYV) Packed Y800Mono8 BYRGBayer RG8 If the Starting Pixel Format Is Bayer RG8, Bayer RG12, or Bayer GRG12 Packed When You Set the Color Space To...Then the Pixel Format Changes To... UYVYYUV422 Packed RGB24Bayer RG8 RGB32Bayer RG8 YV12Bayer RG8 YUY2YUV422 (YUYV) Packed Y800Mono8 BYRGBayer RG8 See Also - Adjust Camera Settings in EthoVision XT - Configure the Digital Camera (in Pylon Viewer) EthoVision XT and Quality Assurance EthoVision XT offers functionality to support the user in fulfilling quality requirements in in-vivo studies. The Quality Assurance (QA) functions can also be used to help comply with Good Laboratory Practice (GLP) regulations. Important: You need the EthoVision XT Quality Assurance module to use the Quality Assurance functions in EthoVision XT. See Modules of EthoVision XT. Important: It is not possible to open a GLP experiment that was made with EthoVision XT 12 or earlier. If you upgrade, you can leave both versions of EthoVision XT on one computer to be able to open the old experiments. Quality Assurance Functions - EthoVision XT User Management: You can set up the program so that only authorized users are able to take particular actions, and that certain actions such as editing or deleting data are prevented. - EthoVision XT Logging: All user actions which can result in changes to the acquired data (for instance altering settings) are logged, and every time you leave a part of the program you are prompted to add a comment to the log file. This creates an audit trail suitable for a QA auditor to review. Note About GLP GLP (Good Laboratory Practice) is a set of rules for conducting non-clinical laboratory studies that support or are intended to support applications for research or marketing permits for products regulated by the U.S. Food and Drug Administration. These products include animal food additives, medical devices for human use, biological products, and human and animal drugs. The principles of and regulations for GLP are described under the Code of Federal Regulations Title 21, Part 58 (CFR21/58). For Europe, the GLP rules have been compiled and adapted by the Organization of Economic Cooperation and Development (OECD). Subparts of the CFR21/58 GLP rules define and describe the following major points: - Organization and personnel. - Facilities. - Equipment. - Testing Facilities Operations. - Test and Control Articles. - Protocol for and Conduct of a Non-clinical Laboratory Study. Main Topics and Tasks - EthoVision XT and Quality Assurance - EthoVision XT User Management - EthoVision XT Logging - Create a GLP Experiment from a Template See Also - Troubleshooting: Quality Assurance (GLP) Source: EthoVision XT 19 Help - Tips for Color Tracking, Noldus Information Technology --- ## EthoVision XT 19 - Tips for Color Tracking - Pixel Format Conversion Tables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-pixel-format-conversion-tables Chapter: EthoVision XT Pixel Format Conversion Tables If the Starting Pixel Format Is Mono8 or YUV422 (YUYV) Packed When you set the color space to...Then the pixel format changes to... UYVYYUV422 Packed RGB24YUV422 (YUYV) Packed RGB32YUV422 (YUYV) Packed YV12YUV422 (YUYV) Packed YUY2YUV422 (YUYV) Packed Y800Mono8 BYRGBayer RG8 If the Starting Pixel Format Is YUV422 Packed When you set the color space to...Then the pixel format changes to... UYVYYUV422 Packed RGB24YUV422 Packed RGB32YUV422 Packed YV12YUV422 Packed YUY2YUV422 (YUYV) Packed Y800Mono8 BYRGBayer RG8 If the Starting Pixel Format Is Bayer RG8, Bayer RG12, or Bayer GRG12 Packed When you set the color space to...Then the pixel format changes to... UYVYYUV422 Packed RGB24Bayer RG8 RGB32Bayer RG8 YV12Bayer RG8 YUY2YUV422 (YUYV) Packed Y800Mono8 BYRGBayer RG8 See Also - Adjust camera settings in EthoVision XT - Configure the digital camera (in pylon Viewer) EthoVision XT and Quality Assurance Main Topics and Tasks - EthoVision XT and Quality Assurance - EthoVision XT user management - EthoVision XT logging - Create a GLP experiment from a template If you need a Certificate of Validation for EthoVision XT, please contact Noldus. Important: It is not possible to open a GLP experiment that was made with EthoVision XT 12 or earlier. If you upgrade, you can leave both versions of EthoVision XT on one computer, to be able to open the old experiments. See Also - Troubleshooting: Quality Assurance (GLP) EthoVision XT and Quality Assurance EthoVision XT offers functionality to support the user in fulfilling quality requirements in in-vivo studies. The Quality Assurance (QA) functions can also be used to help comply with Good Laboratory Practice (GLP) regulations. Quality Assurance Functions - EthoVision XT user management: You can set up the program so that only authorized users are able to take particular actions, and that certain actions such as editing or deleting data are prevented. - EthoVision XT logging: All user actions which can result in changes to the acquired data (for instance altering settings) are logged and every time you leave a part of the program you are prompted to add a comment to the log file. This creates an audit trail suitable for a QA auditor to review. Important: You need the EthoVision XT Quality Assurance module to use the Quality Assurance functions in EthoVision XT. See Modules of EthoVision XT. Note About GLP GLP (Good Laboratory Practice) is a set of rules for conducting non-clinical laboratory studies that support or are intended to support applications for research or marketing permits for products regulated by the U.S. Food and Drug Administration. These products include animal food additives, medical devices for human use, biological products and human and animal drugs. The principles of and regulations for GLP are described under the Code of Federal Regulations Title 21, Part 58 (CFR21/58). For Europe, the GLP rules have been compiled and adapted by the Organization of Economic Cooperation and Development (OECD). Subparts of the CFR21/58 GLP rules define and describe the following major points: - Organization and personnel. - Facilities. - Equipment. - Testing Facilities Operations. - Test and Control Articles. - Protocol for and Conduct of a Non-clinical Laboratory Study. Source: EthoVision XT 19 Help - Tips for Color Tracking, Noldus Information Technology --- ## EthoVision XT 19 - Tips for Color Tracking - Settings for the Color Camera URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-settings-for-the-color-camera-SbU Chapter: EthoVision XT Settings for the Color Camera Aim To make sure that the tracking of color markers in EthoVision XT is optimized. This topic applies to the Basler color cameras acA1300-60gc and acA1920-40gc. Note that the Basler acA1300-60gc is no longer officially supported and therefore not tested by Noldus. Prerequisites You have installed the camera, its driver software, and EthoVision XT. Settings in Pylon Viewer The procedure below refers to the options available in the camera software. Most of the options are also available in EthoVision XT. - Close EthoVision XT and open pylon Viewer. Note: the Basler pylon Viewer software is installed automatically when you install the camera drivers. - From the Window menu select Features - All. - In the Devices panel, double-click the item Basler under GigE. - Open the item Image Format Control. Next to Pixel Format select: - YUV 422 Packed for the camera acA1300-60gc. Note that this camera has not been tested with EthoVision XT 19. - Bayer RG 8 for the camera acA1920-40gc. - Click Color Improvements Control. - Click the Continuous Shot button on the tool bar to view the live image. - Point the camera at a piece of white paper, so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - To save the settings, see Save the Camera Settings. - Close pylon Viewer and open EthoVision XT. - Open your experiment and in the Experiment Settings select Live Tracking and the color camera. - Click the camera button and then in the window that appears click the Format tab. Choose the video resolution and frame rate. - Next to Color Space select: - For the camera acA1300-60gc: UYVY or YUV. - For the camera acA1920-40gc: BYRG. If the image stays black and white, select UYVY or YUV, then select BYRG again. - Select the resolution and frame rate. - Check the Current Frame Rate. If this is significantly lower than the rate you set, choose a lower resolution. Settings for Low Light Conditions When tracking animals in low light, you can adjust the camera settings so that colors are more apparent. The settings below apply to the camera acA1920-40gc. In pylon Viewer, do the following: - Under Analog Controls, set Gain to for example 240 or higher if necessary. - Next to Gamma Selector, choose User. - Next to Gamma, choose 1.0. - Increase the Digital Shift, for example to 1 or higher if necessary. - Under Acquisition Controls, set Exposure Time to for example 20000 µs. A higher value is not recommended. For adjusting a specific color (usually not necessary if the white balance has been done correctly): - Next to Color Adjust Enable, select the option. - Next to Color Adjust Saturation, adjust color saturation (per color). Color to Monochrome If you have a color digital camera, you can temporarily change it to monochrome. For Basler cameras, see Change Color to Monochrome. Note: this does not make your color camera infrared-sensitive. For that, you must either remove the infrared block filter from your color camera or use a monochrome GigE camera. Basler cameras have model numbers in the format acA1300-60xx, where: - xx = gm means monochrome. - xx = gmNIR means Near Infrared, that is, monochrome with extra sensitivity to infrared light. - xx = gc means color. Color to Infrared-Sensitive Most color cameras are not infrared-sensitive. To make them more infrared (IR)-sensitive: - Set them to monochrome (see above). - Remove the infrared-block filter, if present. Infrared-Block Filter Some color cameras may have a built-in infrared block filter which prevents them from seeing some infrared light. If you bought a color GigE camera prior to July 2018, you can remove this filter to make your color camera IR sensitive. Note: color GigE cameras of model acA1300-30gc purchased after July 2018 had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). If you have such a camera you can skip this procedure. - Remove the lens from the camera. - Check that the filter is present: you should see two circular holes at the sides of the filter. - Use a small Allen key or a similar object to lift the filter. - Put the lens back on the camera. See Also - Lighting Setup Pixel Format and Color Space Aim To inform you about the relation between pixel format and color space used to create video. This topic applies to Basler digital cameras. Background - A pixel format is the format of the image data transmitted by the camera. For example, for monochrome cameras the default pixel format is Mono8, meaning that the camera outputs 8 bits of data for each pixel in the image captured by the chip. The Pixel Format setting can be found in the pylon Viewer software. - A color space is a specific organization of colors. Selecting a color space in the camera driver software or in EthoVision XT determines the way color information is encoded in the video file. The Color Space setting can be found in EthoVision XT. There is a relation between the pixel format and the color space. When you specify the color space in EthoVision XT, the camera software may automatically change the pixel format. Follow the tables below to find which pixel format is used in your video. This is usually the format that is optimal to convert color into the selected color space. --- ## EthoVision XT 19 - Tips for Color Tracking - Settings for the Color Camera URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-tips-for-color-tracking-settings-for-the-color-camera Chapter: EthoVision XT Settings for the Color Camera Aim To make sure that the tracking of color markers in EthoVision XT is optimized. This topic applies to the Basler color cameras acA1300-60gc and acA1920-40gc. Prerequisites You have installed the camera, its driver software and EthoVision XT. Settings in Pylon Viewer The procedure below refers to the options available in the camera software. Most of the options are also available in EthoVision XT. - Close EthoVision XT and open pylon Viewer. Note: the Basler pylon Viewer software is installed automatically when you install the camera drivers. - From the Window menu select Features - All. - In the Devices panel, double-click the item Basler under GigE. - Open the item Image Format Control. Next to Pixel Format select: - YUV 422 Packed for the camera acA1300-60gc. Note that this camera has not been tested with EthoVision XT 19. - Bayer RG 8 for the camera acA1920-40gc. - Click Color Improvements Control. - Click the Continuous Shot button on the tool bar to view the live image. - Point the camera at a piece of white paper, so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - To save the settings, see Save the Camera Settings. - Close pylon Viewer and open EthoVision XT. - Open your experiment and in the Experiment Settings select Live tracking and the color camera. - Click the camera button and then in the window that appears click the Format tab. Choose the video resolution and frame rate. - Next to Color space select: - For the camera acA1300-60gc, UYVY or YUV. - For the camera acA1920-40gc, BYRG. If the image stays black and white, select UYVY or YUV, then select BYRG again. - Select the resolution and frame rate. - Check the Current frame rate. If this is significantly lower than the rate you set, choose a lower resolution. Settings for Low Light Conditions When tracking animals in low light, you can adjust the camera settings in such a way that the colors are more apparent. The settings below apply to the camera acA1920-40gc. In pylon Viewer, do the following: - Under Analog Controls, set Gain to for example 240 or higher if necessary. - Next to Gamma Selector, choose User. - Next to Gamma, choose 1.0. - Increase the Digital Shift for example to 1 or higher if necessary. - Under Acquisition Controls, set Exposure Time to for example 20000 µs. A higher value is not recommended. For adjusting a specific color (usually not necessary if the white balance has been done correctly): - Next to Color Adjust Enable, select the option. - Next to Color Adjust Saturation, adjust color saturation (per color). Color to Monochrome If you have a color digital camera, you can temporarily change it to monochrome. Note that this does not make your color camera infrared-sensitive. For that, you must either remove the infrared block filter from your color camera or use a monochrome GigE camera. Basler cameras have model numbers in the following format: acA1300-60xx, where: - xx = gm means monochrome. - xx = gmNIR means Near Infrared, that is, monochrome with extra sensitivity to infrared light. - xx = gc means color. Color to Infrared-Sensitive Most color cameras are not infrared-sensitive. To make them more infrared (IR)-sensitive: - Set them to monochrome. - Remove the infrared-block filter, if this is present. Infrared-Block Filter Some color cameras may have a built-in infrared block filter which prevents them from seeing some infrared light. If you bought a Color GigE camera prior to July 2018, you can remove this filter to make your color camera IR sensitive. Note that Color GigE cameras of model acA1300-30gc purchased after July 2018 had the IR block filter removed, making the color camera IR sensitive like the monochrome version (model: acA1300-30gm). If you have such a camera you can skip this procedure. - Remove the lens from the camera. - Check that the filter is present: you should see two circular holes at the sides of the filter. - Use a small Allen key or a similar object to lift the filter. - Put the lens back on the camera. Pixel Format and Color Space Aim To inform you about the relation between pixel format and color space used to create video. This topic applies to Basler digital cameras. Background - A pixel format is the format of the image data transmitted by the camera. For example, for monochrome cameras the default pixel format is Mono8. This means that the camera outputs 8 bits of data for each pixel in the image captured by the chip. You can find the Pixel Format setting in the pylon Viewer software. - A color space is a specific organization of colors. Selecting a color space in the camera driver software or in EthoVision XT determines the way color information is encoded in the video file. You can find the Color Space setting in EthoVision XT. There is a relation between the pixel format and the color space. When you specify the color space in EthoVision XT, the camera software may automatically change the pixel format. Follow the tables below to find which pixel format is used in your video. This is usually the format that is optimal to convert color into the selected color space. --- ## EthoVision XT 19 - Train URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-train Chapter: EthoVision XT Definition A discrete (state event) variable that is scored when one subject follows (or is followed by) one or more subjects at close distance. Trains can be of two, three or four subjects. Examples of Trains - Actor > B. EthoVision returns all instances when the actor (or focal subject) followed subject B. Here, Actor is the focal subject reported in the results table or in the plots of Integrated Visualization. For example, where subject A is the actor, the instances of the train A > B are found. Where subject B is the actor, no results are found since the train B > B makes no sense. Where subject C is the actor, the instances of the train C > B are found, etc. - Actor > Any > Any. This is the predefined train when you create a new Train variable. All instances are found where the actor followed two other subjects, no matter who they were. For example, when subject A is the actor, trains like A > B > C, A > C > B, or A > D > B etc. are found. Similarly, where subject B is the actor, trains like B > A > C, B > C > D etc. are found. Statistics are given for all the combinations of "Any" subjects pooled together. - B > A. This definition returns all the instances when subject B followed closely subject A. - A > Actor > Any. This definition returns all the instances when the focal subject was followed by individual A and followed any other subject. Calculation The state Train is active when: - The speed of the subjects is higher than the minimum value specified (see below). - The distance between the actor's nose point and another subject's tail base, or the distance between the actor's tail base point and another subject's nose point is less than the maximum value specified (see below). How to Specify Train - Open an Analysis profile and in the Dependent Variables panel, under Social, click the Add button next to Train. - By default, the variable Train contains a predefined train with three animals: Actor > Any > Any. - To define new trains, follow the steps below. - If you do not want to have the predefined train in this variable, select that train definition under Settings and click the Delete button. - Click the Add button to make a new definition of a train. The Add Train window opens with the names of the subjects listed on the left. - Select the name of the first subject in the train, that is, the one that follows the other subjects. Next, either double-click the name or click the double-arrow button. As a result, the subject's name is placed under Train. - Repeat the steps above for the second, third etc. subject that must be part of the train definition. - When ready, click the Add button. - As a result, the new train definition, in this example Actor > A > C, is added under Settings. - Do one of the following: - To add more train definitions, repeat the steps above beginning from step 4. - If you are ready with the definitions, click the Close button in the Add Train window. - Adjust the thresholds if necessary (see below for details). - Complete the procedure to add the variable to the Analysis profile. See Calculate Statistics: Procedure. Notes - Maximum distance (nose - tail base). A train is defined only if the distance between subjects, measured between the nose-point of one subject and the tail-base point of another subject, is less than the value specified. This condition must be valid for all the subjects in the train definition. - Minimum velocity. A train is defined only if the animals that follow each other are faster than the value specified. - Exclude instances shorter than. You can use this setting to filter out instances that are too short to have biological meaning. - To delete an existing train definition, select that definition under Settings and click Delete. - To delete an element of the train, in the Add Train window click the Delete button. Click multiple times until the element is deleted from the definition under Train. If necessary, add more elements to complete the train definition. Behavior Recognition The Rat/Mouse Behavior Recognition group of dependent variables is only available when you have the Rat or Mouse Behavior Recognition add-on module of EthoVision XT, respectively. - Behaviors detected with Behavior Recognition - Behavior Probability - Merged Behavior Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Trial Control and Subject Detection URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-and-subject-detection Chapter: EthoVision XT Prepare a List of Trials (Optional) In EthoVision XT, a Trial is an uninterrupted recording session. The Trial List is a table listing the trials planned for an experiment. When you create a new experiment, a few planned trials are already present. To Add More Trials - Choose Setup > Trial List. Click the Add Trials button. - Type the number of trials you plan to carry out and click OK. - For each row: - Specify the independent variables (optional; see the next section). - Specify which video file you want to use (when tracking from video files). - Select Arena Settings, Trial Control Settings, and Detection Settings (optional). If those columns are not present in the Trial List, click the Show/Hide button, click Variables and select them. Note: Planning your trials in advance also allows you to acquire trials in batch mode. See Trial List in the EthoVision XT Help. Independent Variables What Are Independent Variables? Independent variables are either simple descriptive categories (such as the genotype or age of your rats or mice), or conditions manipulated by the researcher (such as the substance being tested and the dosage). You can use independent variables to create analysis groups or filter data. For example: - Compare tracks of treated subjects with tracks of control subjects. - Only analyze subjects of a specific age class. Note: If you created a template experiment, one or more independent variables have been predefined in your Trial List. For instance, Animal ID and Treatment. To Define an Independent Variable - Choose Setup > Trial List. - Click the Add Variable button. A new column appears on the right of the table. - Specify the Label (for example: Dose), Description, Type (for example, Text or Numerical), Format, Predefined values (for example, 0.01, 0.02 etc. mg/kg), and Scope (whether the values of the variable differ between subjects within the same arena, between arenas within the same trial, or between trials). Acquire the Data Methods Choose Acquisition > Open Acquisition. Locate the Acquisition Settings window at the right side of the screen. - If you track from pre-recorded video files, select Track next planned trial, click the button next to Video and open the video you want to use. - If you track from the live camera image, select Track next planned trial. Select Save video if you want to save the camera footage to a video file. For more acquisition methods, see Acquire Data in the EthoVision XT Help. Procedure for Acquiring One Trial - Under Settings, choose the Arena Settings, Trial Control Settings, and Detection Settings, if they are not already selected in the Trial List. - If you track from video and do not score behaviors manually, make sure the DDS (Detection Determines Speed) checkbox is selected in the Playback Control window. With this option you ensure that every sample is analyzed. - To start a trial, click the Start trial button in the Playback Control window. - Release the subject in the arena. - To stop the trial, click the Stop trial button. - Return the subject to its home cage or container. - Prepare the next subject, or load a new video file to acquire the next trial. More Options - You can automatically start and stop your trial depending on the behavior or position of your subject. See the Trial Control Settings section for details. - You can also acquire data in batch mode. For details, see Batch data acquisition in the EthoVision XT Help. - You can also score behaviors manually during tracking. If you saved the video during tracking, you can review the video and add or edit existing behavioral data. For details, browse the EthoVision XT Help: - To define behaviors, see Set Up an Experiment > Manual Scoring Settings. - To score behaviors, see Acquire Data > Score behaviors manually. - If no planned trial is left, click the Add Trial button in the Playback Control window. - Note: Sometimes EthoVision XT tracks a reflection instead of the subject, it confuses the nose-point and the tail-base or swaps subjects when you track multiple animals simultaneously. Whenever that occurs, you can correct those errors. For more information, see Edit the Tracks in the EthoVision XT Help. Calculate the Statistics Prepare the Tracks A track is the group of samples acquired for a subject. You can choose to smooth the tracks to get a more reliable measure of the animal's movement path and remove the effect of outliers (caused by accidental wrong detection), random noise and body wobble. - Choose Acquisition > Track Smoothing Profile. Select Open and click OK. - Select one or more of the options: Smoothing (Lowess), Minimal Distance Moved and Maximum Distance Moved. For information on the smoothing options, see Smooth the Tracks in the EthoVision XT Help. Analysis Profiles Choose Analysis > Analysis Profile. Select New, name the analysis profile and click OK. Distance moved and Velocity are predefined as dependent variables. To add a variable to the Analysis profile, click the button next to that variable. Note: If you created the experiment from a template, it contains a few analysis profiles. For example, the Morris water maze template experiment with the platform zone template contains four analysis profiles. One of them, Latency to reach platform, contains the variables for calculating the time taken to reach the platform. Basic Calculations Total Distance Moved or Average Velocity - Open the Analysis profile. - If the variable is not yet listed under Selected Dependent Variables, click the button next to Distance moved or Velocity. In the Trial Statistics tab, select Total for Distance moved, or Mean for Velocity. - Choose Analysis > Results > Statistics and Charts. Time in a Zone and Number of Zone Entries In step 2 above, click the button next to In zone. Specify the zone. In the Trial Statistics tab, select Cumulative duration and Frequency. Source: EthoVision XT 19 - Quick Start Guide --- ## EthoVision XT 19 - Trial Control Settings - Control Tracking URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-control-tracking Chapter: EthoVision XT Control Tracking Start Track Conditions You can configure when tracking begins using the following conditions: - Frequency — Start tracking when the animal has visited the zone a number of times. - Latency to First — Start tracking when the latency to its first visit to the zone is less than or greater than a specific time. To Use a Different Start Track Condition Click the Condition - In Zone box and press Delete, then choose another condition (see the examples below). Example 1: Start tracking exactly 1 minute after clicking the Start Trial button. - Click the Condition - In Zone box and press Delete. - Under Conditions, click the button next to the variable you want to use (Time in this example), and select the options you require. - Insert the new box in the sequence and re-connect the boxes. See Connect Two Boxes. Example 2: Start tracking at a time you are not in the lab, for example at 23:00. - In step 2 above, click the button next to Time, choose After Clock Time, and enter 23:00:00. - Before leaving the lab, choose Acquisition > Open Acquisition and click the Start Trial button. The program waits until 23:00 to start tracking. Examples Example 1: Start tracking immediately when you start the trial. - Click the condition box and press Delete. - Reconnect the first box with the second one. See Connect Two Boxes. Example 2: Start tracking when both (all) subjects are in the arena. - This assumes that the experiment is set to multi-subject tracking. - Click the Settings button in the condition box. - In the window that appears, click the Actors tab and select the subjects that should be in the arena at the start of tracking. - Select All Selected Subjects. Control the End of Tracking Stop Tracking After Some Time This option allows you to create tracks of fixed length. The default Stop Track condition is a Time condition. Click the Settings button, and choose the option you require. - To stop tracking after some time, choose After a Time Of and set the time. For example, set 5 min if you want to track subjects for five minutes. - To stop tracking at a specific clock time of the same day, choose After Clock Time and set the time required. To stop tracking after the current day, you must have the Trial and Hardware Control module. Stop Tracking Based on the Behavior of the Subject - Click the Time condition box and press Delete. - Under Conditions, choose the variable that describes the behavior and click the corresponding button. For example, to stop tracking when the subject is in a zone, click In Zone. - Configure the variable and insert the new box in the Start-Stop Trial rule. See Insert a Box in a Trial Control Sequence. To Set a Maximum Duration for Your Trials If the conditions to stop the trial are never met, EthoVision XT waits indefinitely and the trial never ends. To prevent this from happening, define a maximum trial duration. Example: In a Novel Object test, if the Stop Track box is preceded by a condition "when the subject enters the zone with the familiar object," it may happen that the subject completely ignores the familiar object and only pays attention to the novel object. In that case the condition to stop tracking is never met. In the Maximum Trial Duration pane, select Use a Maximum Trial Duration and enter the maximum duration of the trial (in hours, minutes, or seconds). For information about the duration of trials tested with specific cameras and computers, see Resolution, Frame Rate, and Maximum Trial Duration. Longer trials and videos are possible in principle but they have not been thoroughly tested. Stop Video Recording After Some Time All the options above refer to stopping the trial when you do tracking. If you record video and then acquire the tracks (see Record Video, Then Acquire a Trial), the Maximum Trial Duration option will not work. This is because the Trial Control Settings, including the Maximum Trial Duration option, are not active when EthoVision XT just records video without acquiring data. You must stop video recording manually. An alternative strategy is the following: - Set the Maximum Trial Duration (see above). - Acquire a trial live and save video. - The saved video has a fixed length. You can now use that video to redo tracking in the same experiment, or use that video in another experiment (set to offline tracking). Notes - Keep at least one condition between Start Track and Stop Track. If you do not do this, tracking stops immediately after tracking starts, resulting in no data. - If you do not see the Maximum Trial Duration pane, click the Show/Hide button on the toolbar and select Maximum Trial Duration. If the text in this pane is grayed out, it means that Trial Control Settings are read-only. Open another Trial Control Settings profile or create a new one. - Instead of using a maximum trial duration, you can also define a condition based on time and place it immediately before the Stop Track box. This way you set the exact duration of the tracks. See Stop Tracking After Some Time. - For more information on conditions, see Overview of Conditions in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. --- ## EthoVision XT 19 - Trial Control Settings - External Commands URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-external-commands Chapter: EthoVision XT External Commands Aim To trigger external software with EthoVision XT. Prerequisites - You need at least the Base version of EthoVision XT. Procedure - Open or create new Trial Control Settings. - In the Components pane, under Actions, click the button next to External Command. - Next to Action Name, enter the name of the action (for example, start recording) or accept the default name. - Under Actions to Perform, select which file you want to run by clicking the ellipsis button. - Select one of the file types from the list: Executables (*.exe) or Batch Files (*.bat, *.cmd). - Browse to the file and click Open. - Optionally, enter a Command Line option. Click the Information button to get additional information about defining an External Command. For more details, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. - To test the command, click the Test button. Note If you work with two or more arenas, be aware that an external command is sent out for each arena. For example, the command to play a sound is repeated 96 times for a 96-well plate DanioVision experiment. To prevent this from happening, put a condition before the External Command box that will only become true for one of the arenas, for example Arena 1. In the Arena Settings, create a zone in Arena 1 and call it "Zone 1A". Make the zone as large as the arena. In the Trial Control Settings, make a condition like "Is subject in Zone A?", followed by the external command. Make sure that the sequence does not interfere with the rest of the Trial Control rule. Application Examples - Play a sound - Trigger video recording with MediaRecorder - Trigger sound recording with UltraVox XT Play a Sound Aim To play a sound file while carrying out a trial. Procedure - Open the Windows Notepad and enter the following text, replacing the text within quotes with the actual path to your sound file: @echo off set soundFile="D:\Sound Files\Stimulus1.wav" start "" "C:\Program Files\Windows Media Player\wmplayer.exe" %soundFile% - Save the file with the *.bat extension. - Follow the procedure in External Commands to create an External Command action that selects the batch file. - Place the External Command box in the Trial Control rule. Notes - Create one batch file for each sound file you want to play during the trial. Create multiple External Command actions, one for each batch file, and place them in the Trial Control rule. - wmplayer represents Windows Media Player. You can also use other software to play audio, for example VLC: @echo off set soundFile="D:\Sound files\Stimulus1.wav" start "" "C:\Program Files\VideoLAN\VLC\vlc.exe" --play-and-exit %soundFile% - For examples of Command Line options, see External Commands in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. See Also - External Commands Trigger Video Recording with MediaRecorder Aim To record high resolution video with MediaRecorder while tracking subjects with EthoVision XT. Prerequisites - You work with analog video cameras. If you work with digital cameras, EthoVision XT and MediaRecorder cannot access the signal from a digital camera simultaneously. Procedure - In the Trial Control Settings, create a condition that must be true in order to trigger video recording. - Follow the procedure in External Commands to create an External Command action that starts video recording in MediaRecorder. To visualize batch (*.bat) files, choose Batch Files (*.bat; *.cmd) next to File Name. - Place the second box after the first in the Trial Control rule. Example 1 In this example, the trial starts in the early afternoon but the researcher wants to start video recording only after 6 PM (18:00) and end it after 12 hours. The box sequence is as follows: - Start Tracking. - Open MediaRecorder. Add the Command Line option /E. - Wait until 18:00. - Start video recording. Add the Command Line option /R. - Wait 12 more hours. - Stop video recording. Add the Command Line option /S. Example 2 In this example, the researcher carries out live tracking during a 24-hour period. The trial starts during the light cycle when the animal is inside the shelter, but the researcher wants to start recording video only when the animal leaves the shelter. This saves significant disk space as the resulting video will be shorter. - Create an External Command action to open MediaRecorder. Select MRCmd.exe as the program to run and enter /E as a Command Line option. - Create an In Zone condition "Out of Shelter". - Create a Time condition to make sure that video recording starts when MediaRecorder is already open on the screen. Combine the two condition boxes with an operator of type All Inputs True. - Create an External Command similar to the first one, this time with /R as a Command Line option to start recording. --- ## EthoVision XT 19 - Trial Control Settings - Hardware URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-hardware Chapter: EthoVision XT Hardware To define a condition based on the signal given by a hardware device. To use hardware-based conditions, you must have the Trial and Hardware Control Module. See the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Notes - If the Add a Condition window appears, it means that there is at least one condition with the same name in your experiment. Create a new condition, or re-use the existing condition. See Re-use Trial Control Elements. - For a complex condition like "stop the trial when the rat reaches the platform or it has been swimming for 60 seconds", see an example for the Start/Stop the Trial in the Morris Water Maze Test. - Trial Control conditions cannot be defined based on behaviors scored automatically with Rat or Mouse Behavior Recognition. This is because the detection of behavior also depends on video frames that come after the time that the condition is evaluated. - If you insert a Condition box based on Activity, and then deselect Activity Analysis in the Experiment Settings, your rule becomes invalid. The Condition boxes based on Activity are removed from your sequence and the connecting arrows are removed. Re-connect the boxes. - See also Overview of Conditions in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Actions Aim An Action is a command that EthoVision XT carries out during acquisition. Examples - Start Tracking and Stop Tracking (see The Start-Stop Trial Rule). - Do C = C+1. This is an example of an action on a Trial Control variable. See Using Trial Control Variables. - Start video recording with MediaRecorder. This is an example of an External Command. See External Commands. - Open the door of LeftArm or Drop a pellet. These are actions on hardware devices (only with the Trial and Hardware Control Module). Procedure - Open or create new Trial Control Settings. - In the Components pane under Actions, locate the type of action you want to define and click the button next to it. - Next to Action Name, type in the name you want to give to the action, or accept the default name. - Specify the action. - Enter a Comment (optional), then click OK. - Insert the action box in the Trial Control rule. Using Trial Control Variables Aim Trial Control variables help you keep track of events that occur during the trial. An example of a Trial Control variable is a counter. To Define a Trial Control Variable - Open or create new Trial Control Settings. - In the Components pane, under Conditions or Actions, click the button next to Trial Control Variable. - Next, click the Variables button. The Trial Control Variables window lists the variables currently in the experiment (also those defined in other Trial Control Settings). To add a new variable, click Add Variable. - A new row is appended to the table. Under Name, type in the name you want to give to the variable. Under Initial Value, enter the value of this variable at the start of the trial (default: 0). - Click OK. In the TC-Variable Action/Condition window, define the action or condition you require. Click Cancel if you do not want to create a condition or action based on that variable at that point. Notes - To delete a variable, click the variable name in the Trial Control Variables window and click the Delete Variable button. - To rename a variable, click the variable name in the Trial Control Variables window and edit the name. - The default name of a new Trial Control variable is VarN, where N is a progressive number. - The variable name cannot contain blank spaces. To Define an Action on a Trial Control Variable - In the Components pane, under Actions, click the button next to Trial Control Variable. If you do not see this action, under Actions click the More button. - If the Add an Action window appears, it means that there is at least one action of the same type in your experiment. You are asked to choose between creating a new action or re-using an existing one. See Re-use Trial Control Elements. - In the TC-Variable Action window, next to Action Name, enter the name of the action (for example, Increment Counter) or accept the default name. - Under Action to Perform, select the variable from the list. You can also create the variable by clicking Variables if you have not yet done so. - Next to the = symbol, do one of the following: - To assign the same value of another variable (for example A = B), select the other variable (B) from the second list. - To enter a formula, click the double-arrow button. Select the operator from the list and specify the formula in the second and third lists. For example, A = A + 1. - To assign a random value, select Random from the second list, and select the Minimum and Maximum limits (only integer values, 0 up to 999) for the random value. - Click OK. Insert the resulting Action box in the Trial Control rule. Notes - If your setup includes multiple arenas, each arena receives an instance of the variable. Thus, a variable can have different values in different arenas. - You cannot combine Random with a formula (for example, to compute A = Random+1). The equivalent solution is the following: define first an action B = Random, and then one more action A = B+1. Place the two resulting Action boxes in sequence. - For a random variable, select the Permutation option to generate a random value that is unique in the sequence of all values in the specified range. For example, if the Minimum is 1 and the Maximum is 5, any value will be generated only after all the other possible values have been generated in previous repeats of the action. That is, a new value 1 can only occur after all the other possible numbers are generated during previous repeats of the action: 3, 2, 4, 1, 5, 1. Use the Permutation option to create sequences of unique numbers, for example to activate routines in a pseudo-random order but without the repetitions that would occur if you generate fully random numbers (for example, 2, 4, 1, 1, 5). See Also - The EthoVision XT - Trial and Hardware Control - Reference Manual. See Manuals. --- ## EthoVision XT 19 - Trial Control Settings - Operators URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-operators Chapter: EthoVision XT Operators Aim To combine actions, conditions, and sub-rules in various ways. Examples - When at least one of two conditions A and B is met, then do something. This is an example of conditions combined by an operator of the Any type (OR logic). - When two conditions are met at the same time, then do something. This is an example of conditions combined by an operator of the All type (AND logic). - When at least/at most/exactly 4 of 8 conditions are met, then do something. This is an example of conditions combined by an operator of the N of All type. Procedure - Define the conditions, actions, or rules that you want to combine. Place them in your Trial Control sequence as parallel branches. The connecting arrows must originate from the condition or action that precedes the combination of elements you want to define. - In the Components pane under Structures, double-click Operator or click the button next to it. - Under Name, enter the operator name or accept the default name Operator (n), where n is a progressive number. - Under Operator Triggers When, select the option that applies: - Any (at least one) of the inputs is true. - All inputs are simultaneously true. - N of All inputs are simultaneously true. Specify how many inputs N must be true: = (exactly equal to), ≠ (not equal to), >= (at least), <= (a maximum of), etc. An input being true means a condition being met, an action carried out, or a sub-rule finished. - Enter a comment (optional) to describe this operator, and click OK. - A new Operator box appears in the Trial Control. Place the box to the right of the elements defined in step 1, and connect each element (or ending element, in the case of a sequence) to the operator. - Connect the operator to the next element that should be activated. Notes - Instead of using multiple condition boxes, you can also combine conditions with Multi Condition. For details, see the EthoVision XT 19 Trial and Hardware Control Reference Manual. - If the Add an Operator window appears, it means that there is at least one operator of the same type in your experiment. For more information, see Re-Use Trial Control Elements. - Names of operators must be unique in your experiment. You cannot define two operators with the same operator name. - An operator can also have just one input box. In that case the operator is of no use, because control passes immediately to the next box as soon as the input condition becomes true or the input action is carried out. EthoVision informs you about this. Re-Use Trial Control Elements Aim To create a Trial Control element without starting from scratch. All elements of Trial Control (conditions, actions, operators, sub-rules, and sub-rule references) defined in other Trial Control Settings can be duplicated and re-used in your current Trial Control Settings. Procedures Re-Use a Trial Control Element (General) Use this procedure to create a Trial Control element from an existing one, even when it is stored in another Trial Control Settings profile. - Click the button next to the element you want to create. - The Add window appears. Select Reuse an Existing Condition/Action and select the name of the existing element from the list next to the option. From the second list, choose the Trial Control Settings profile that contains the element you want to re-use. - Click OK. - A window appears for the type of element chosen. The name and settings specified here are the same as in the element chosen in step 2. - To create an identical copy of the element, click OK and go to step 5. - In all other cases, edit the settings and click OK, then go to the next step. - Insert the resulting box in the Trial Control sequence. Copy and Paste a Trial Control Element Use this procedure to quickly copy one or more Trial Control elements visible on the screen. This applies to actions, conditions, operators, and references to sub-rules. See Copy and Paste a Box. Notes - To duplicate an entire Trial Control procedure, in the Experiment Explorer under Trial Control Settings, right-click the profile and select Duplicate. - When you duplicate a Trial Control element and change any settings of the new element, including name and comment, a window appears showing two options: - Apply the new settings only in the current trial control profile. Choose this option to apply the settings only to the new copy. - Apply the new settings in all writable Trial Control profiles. Choose this option to extend those changes to the original elements in all Trial Control Settings that are writable, meaning not locked after acquisition. Working with Trial Control Boxes Create a New Box Click the button that applies in the Components pane. Copy and Paste a Box You can create duplicates of one or more Trial Control boxes. This makes it easier to create procedures with similar actions and conditions. - Click the box you want to copy. To select multiple boxes, click and drag the mouse around them. - Choose Edit > Copy, or right-click anywhere and choose Copy, or press Ctrl+C. - When necessary, open the Trial Control Settings where you want to insert the new boxes. - Choose Edit > Paste, or right-click anywhere and select Paste, or press Ctrl+V. Notes - The name of the new Trial Control box is the same as that of the original one, followed by (2), (3), etc. - You cannot copy and paste a sub-rule, only the actions and conditions within it. Move a Box - Hover the mouse over the margin or the colored area of the box. The mouse cursor changes to a four-headed arrow. - Drag the box to the position you require. To move a group of boxes: - Draw a rectangle around the boxes you want to move, or click the boxes you want to select while holding the Ctrl key. The selected boxes get a gray, dark border. - Hover the mouse over the margin or the colored area of one of the selected boxes. The mouse cursor changes to a four-headed arrow. - Drag the group of boxes to the position you require. Insert a Box in a Trial Control Sequence - Drag the Trial Control box between two boxes until the connecting arrow turns white. --- ## EthoVision XT 19 - Trial Control Settings - Options URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-options Chapter: EthoVision XT Options If you used Noldus MPEG Recorder 1.1/2.0, or MediaRecorder, and analog cameras: - When you used MediaRecorder with a Picolo H.264 encoder board, choose Noldus Recorder and select Euresys PICOLO U4 H.264. Make sure you select the TV standard of the camera (NTSC or PAL). - When you used an older encoder board (Picolo Diligent or IVC-4300), choose Noldus Recorder and select one of the other options. If you used MediaRecorder, and digital cameras: - In most cases you do not need to correct the aspect ratio. However, if you are sure the video image is distorted, select Custom and enter the correct aspect ratio. If you used video files recorded with EthoVision XT, but in a different experiment: - Select Noldus Recorder and select Euresys Picolo U4 H.264. If you used video files recorded with programs other than MediaRecorder: - Select Custom and enter the adjusted aspect ratio. See Calculate the Correct Aspect Ratio in a Video Image. Arena - Hardware Mapping If your experiment is set to use Trial Control hardware, the Hardware Mapping section at the bottom of the Arena Settings pane is available. Click the Arena-hardware mapping button to assign hardware devices to each of your arenas. If your experiment consists of only one arena, the hardware is automatically assigned to this arena, so you do not have to take further actions. If you have more than one arena, assign the hardware to the arenas manually. See Also - The section Assign Devices to Arenas in the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To open this manual, on the Apps screen choose Noldus > EthoVision XT 19 Other Documentation. Trial Control Settings Main Topics And Tasks - Introduction to Trial Control - The Start-Stop Trial Rule - Examples of Start-Stop Trial Rules - Programming Trial Control - Further Information on Trial Control Important: This chapter describes the Trial Control functions of the EthoVision XT Base version only. For a detailed overview of conditions, creating sub-rules and controlling hardware devices via the USB-IO box, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To access this manual, on the Apps screen choose Noldus > EthoVision XT 19 Other Documentation. Introduction To Trial Control Learn About - Why Use Trial Control? - Important Terms in Trial Control Why Use Trial Control? Start And Stop Data Acquisition Trial Control allows you to automate your experiment. Let EthoVision XT control the start and stop of data acquisition (tracking) depending on time, the behavior of the subjects and other conditions. For example: - Start tracking when the subject is released and detected in the open field. - Start tracking at exactly 12:30:00, and stop tracking after one hour. - Stop tracking when the rat has reached the platform in the Morris water maze, or one minute after the start in any case. - Stop tracking after the animal has been in the closed arms of the Elevated Plus Maze for five minutes. - Stop tracking when the subject has explored an object for five minutes. See Also - The Start-Stop Trial Rule Advanced Trial Control With the EthoVision XT Trial and Hardware Control Module, you can also: - Define conditioning routines for the subject, based on sequences of conditions and actions that are repeated a number of times (sub-rules). - Control hardware devices, like a pellet feeder, or the arms of a radial maze. Your EthoVision XT license must include the Trial and Hardware Control module. For more information about advanced trial control options, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Important Terms In Trial Control Trial Vs. Track A Trial is a single, uninterrupted acquisition session. The trial can be viewed as a container for the data collected in one recording session. It starts when you give the Start command in acquisition and stops when the tracks for all arenas and subjects have stopped. A Track is the actual recording of a subject's position and behavior. The start of a track may or may not coincide with the start of the trial. This depends on your Trial Control Settings. If you use the default Trial Control Settings, the track starts 1 second after the animal has been detected in the arena and stops when you stop the trial. Conditions And Actions A Condition is a statement that EthoVision evaluates. A condition can be based on time, presence of the subject in a zone, any variable that quantifies behavior, or the state of a device connected to EthoVision XT. An Action is a command executed on a variable or a hardware device. You can therefore control your experiment by linking conditions with actions. Example: In a Morris water maze test, stop tracking when the rat is detected on the platform (provided that the platform has been defined as a zone). The action is Stop tracking and the condition is Rat detected on the platform. A condition is followed by an action. The condition checks that the animal is in the zone named "Platform". The action "Stop track" is taken when the condition is met. The Start-Stop Trial Rule Learn About - The Default Start-Stop Trial Rule What Do You Want To Do? - Control the Start of Tracking - Control the End of Tracking - Split a Multi-Day Test in Multiple Trials --- ## EthoVision XT 19 - Trial Control Settings - Split a Multi-Day Test in Multiple Trials URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-split-a-multi-day-test-in-multiple-trials Chapter: EthoVision XT Split a Multi-Day Test in Multiple Trials Aim To acquire trials longer than the maximum duration that is tested at Noldus. See Cameras Supported by EthoVision XT > Resolution, Frame Rate, and Maximum Trial Duration. Procedure - In the Trial Control Settings, remove the condition immediately before the Start Track action box. - In the Trial Control Settings, set the maximum trial duration. For example, 24 hours. See Control the End of Tracking. Set this time to a little less than 24 hours, for example 1439 min (= 24 h minus 1 min). The remaining minute is used as the inter-trial interval (see below). You can also choose a shorter inter-trial interval if you like. - Choose Setup > Trial List. Add a number of trials that cover the total duration of the test for the subject. - Example 1: One arena. Each subject is tested over five days. Therefore, add five trials for that subject. - Example 2: Subjects in four PhenoTypers (arenas) are tested over five days. Add five trials. Each trial contains data of one day and the four arenas. Only add the trials for the current subject(s), not for the subjects that come next in the protocol. Because you will use the series of trials with a short inter-trial interval, in most cases you will not have time to clean the cages and release the next subject. Add a variable "Subject ID" to the Trial List, and enter the ID of the subjects to be tested so you know which trials refer to which subject. - Choose Acquisition > Open Acquisition. Under Method, select Track All Planned Trials with an Inter-Trial Interval of 1 minute. This ensures that EthoVision XT has the time to save the data. If you want to use a shorter time, test it beforehand. - Acquire the data. - In step 3, add the trials for the next subject(s), and repeat the procedure. - In the Data profile, group the trials based on the subject ID. This way you can analyze a multi-trial test as one trial. See Define Groups of Tracks. Examples of Start-Stop Trial Rules Start/Stop the Trial in the Morris Water Maze Test Aim 1: Stop Tracking When the Animal Has Found the Platform - In the Arena Settings, make sure that the platform has been defined as a zone. - In the Trial Control Settings, delete the Time condition before the Stop Track box. - Define an In Zone condition. See also Stop Tracking Based on the Behavior of the Subject. If you want the program to stop recording as soon as the animal is over the platform, select Frequency as Statistic and choose >= 1. Click Settings and select the platform zone. See details about the variable In Zone. Sometimes the animal swims over the platform but does not stop there. In such cases the program would stop recording while the animal has not found the platform. Instead of selecting Frequency, choose Current Duration and the minimum time the animal must stay on the platform (for example, 3 s) without interruption. Click Settings and select the platform zone. Aim 2: Stop Tracking When the Rat Has Found the Platform or Has Been Swimming for 60 Seconds The Arena Settings and the condition "the rat has found the platform" are similar to those in the example above. The condition "rat swimming for 60 s" can be translated to "time from start tracking >= 60 s." The track stops when either condition is met. The two conditions are combined with OR logic. See also Operators. This solution results in tracks of different duration: less than 60 s for the animals that found the platform, and 60 s for the others. With the Start-Stop Trial rule described below, the trial stops when the subject has been in the platform zone for at least 3 s without break, or the time since the start of tracking is 60 s. - A. In Zone condition that specifies that the subject must be over the Platform zone for at least 3 seconds. Select Current Duration >= 3s. - B. Time condition that specifies a time of 60 s since the track started. - C. "Any" operator box. Start the Trial in the Social Interaction Test Aim: Start Tracking When All Subjects Have Been Released in the Arena - Click the Settings button in the second box (Condition - In Zone). - Click Settings and then the Actors tab. - Select all the subjects that need to be in the arena at the time of start. - Choose All Selected Subjects below the subject list. Stop the Trial in the Eight-Arm Radial Maze Test Aim: Stop Tracking When the Subject Has Been in Four Arms Within 10 Minutes This can be done by combining eight conditions specifying that the animal must be in each arm, with at least four conditions being met regardless of which arms the animal visits. - Create an In Zone condition and specify that the Frequency for Arm 1 must be >= 1, meaning the animal must have visited Arm 1 at least once. Do the same for each of the other arms. - Connect the resulting eight condition boxes in parallel using the N of All operator. See Operators. - Set the maximum trial duration to 10 minutes to stop tracking in the case the animal fails to visit four arms in the meantime. See To Set a Maximum Duration for Your Trials. The Trial Control sequence for an eight-arm radial maze works as follows: the trial must stop when the animal has visited four of the arms at least once. Condition boxes 1 through 8 represent In Zone conditions for Arm 1 through Arm 8 respectively. A condition is met when the Frequency of In Zone for that arm is greater than or equal to 1. An operator box checks that at least four of the eight conditions are met. When four conditions are met, the Stop Track box is triggered and the trial is stopped. See Also - Operators --- ## EthoVision XT 19 - Trial Control Settings - Start and Stop the Trial at Specific Clock Times URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-start-and-stop-the-trial-at-specific-clock-times Chapter: EthoVision XT Start and Stop the Trial at Specific Clock Times Aim To control the start and stop of the trials, without the need for the researchers/technicians to be in the stable to control EthoVision XT. Procedure 1 - One Trial You want to start tracking at 9 AM (9:00) and stop at 7 PM (19:00). You are in the lab the day before. - Open the Trial Control Settings and create time conditions as in the figure below. - Before leaving the lab, in the Acquisition screen click Start Trial. The screen says Checking start condition. - The software waits until 9 AM on the following day and then starts tracking. - Tracking stops on 19:00 (7 PM). Note: If you click Start Trial before 9:00, it will start tracking on the same day. Procedure 2 - Repeated Trials Using a Series of Trials You plan to record your subjects for 20 days. Each trial should be carried out during the day, from 8 AM (8:00) to 7 PM (19:00). - Create a Trial List with the number of planned trials. See Plan Your Trials. - In the Trial Control Settings, create a Start-Stop rule similar to the one above, to start tracking from 8 AM to 7 PM. - In the Acquisition screen, select Track all planned trials. In the Inter-trial interval field, enter the time that covers the interval from the end of one trial to some time before the beginning of the next. In this case the inter-trial interval runs from 7 PM to 7:59 AM = 12 h 59 min. Leave some time between the end of the inter-trial interval (7:59 AM) and the Time condition of the rule (8 AM). This way the two instructions will not interfere with each other. At 7:59 AM of the next day, the trial starts but the software waits till 8:00 AM to start tracking. - To start the first trial in the series, make sure to click the Start Trial button before the time specified in the Time Condition box placed at the left of the Start track box (in this case 8 AM). - In the remaining days you do not have to be in the lab at that time because the series of trials will do the work for you. See also Acquire a Series of Trials (Batch Acquisition). Procedure 3 - Repeated Trials Using Task Scheduler You plan to record your subjects for 20 days. Each trial should be carried out during the day, from 8 AM (8:00) to 7 PM (19:00). This is an alternative method that makes use of the Windows Task Scheduler. - Create batch files to trigger the start of the trials (this replaces the clicking of the Start Trial buttons in the procedures above). - Use the Windows Task Scheduler to trigger the batch files at a specific time. - Do not forget to add the planned trials in the Trial List; in this example, 20 trials. Do the following: - Using the Windows Notepad, create a file with extension VBS that performs a key press Ctrl+F5. This triggers the start of the trial. Enter the following code: Set WshShell = WScript.CreateObject("WScript.Shell") WshShell.AppActivate "EthoVision" WScript.Sleep 1000 WshShell.SendKeys "^{F5}" And name this file vbsprogram.vbs. Note: The WScript.Sleep 1000 (1 s delay) ensures that the key press is given when EthoVision XT is in focus. - Using the Windows Notepad, create a second file, this time with extension BAT, which triggers the vbs script. Enter the following code: wscript "C:\vbsprogram.vbs" And name this file start_vbsprogram.bat. - Save both files on C:\. - Start the Windows Scheduler and define a new basic task, which runs daily. Under Action, select Start a program and select the batch file C:\start_vbsprogram.bat. Make sure that the task is repeated daily at the required time. - To program the end of the trial, do this in the Trial Control Settings. See Control the End of Tracking. - Leave EthoVision XT open on your screen and close all other unnecessary windows. When Windows runs the task at 8 AM, the trial starts automatically. Notes - If you select the option Save video in the Acquisition screen, video recording starts the moment that you click Start Trial. Depending on the condition placed immediately before the Start Track box, video recording starts some time before the actual start of tracking. In the case of Procedure 1, several hours earlier. This means that you record many hours of video when tracking is not yet active. Programming Trial Control Follow this section if you need more information on how to define conditions and actions in the Start-Stop trial rule. Tip: Before defining Trial Control in EthoVision XT, draw your experimental procedure as a flowchart, where each block represents either an action or a condition which, when met, triggers other actions or conditions. Learn About - Conditions - Actions - External Commands - Operators See Also - Useful Things to Know - Re-use Trial Control Elements - Working with Trial Control Boxes Other Manuals For further information, including information on controlling hardware devices such as the PhenoTyper Top Unit, the Pellet dispenser, PhenoWheel and the Lickometer, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. To open this manual, choose Apps > Noldus > EthoVision XT 19 Other Documentation. --- ## EthoVision XT 19 - Trial Control Settings - The Default Start-Stop Trial Rule URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-the-default-start-stop-trial-rule Chapter: EthoVision XT The Default Start-Stop Trial Rule How To Access The Start-Stop Trial Rule - Choose Setup > Trial Control Settings > Open and select an existing Trial Control Settings. - In the Experiment Explorer, click one of the Trial Control Settings. With this rule, you control the start and stop of data acquisition (tracking). What The Start-Stop Trial Rule Means The sequence of boxes A to F can be read as follows: - When you start the trial, for example by clicking the Start Trial button, box A (Rule Begin - Start-Stop Trial) is activated. Control passes immediately to box B. - EthoVision XT checks that the condition in box B (Condition - In Zone) is true. The condition states that the center point of the subject (or of any subject in the same arena) must be detected in the arena for an uninterrupted period of one second. When you start the trial and the subject is not yet in the arena, the condition is false. EthoVision XT waits until the subject has been detected for one second. At that time, the condition becomes true. Control passes immediately to box C. Note: In special cases this box is absent or has different settings. See The Start-Stop Trial Rule in Special Cases. - When condition B becomes true, box C (Action - Start Track) is activated, and tracking starts. - Control passes to box D (Condition - Time). EthoVision XT checks that the condition is met. This condition is set to wait indefinitely, so that tracking stops when you give the stop command, or when the end of the video file has been reached, or when the maximum trial duration has been reached. See Control the End of Tracking. - When one of the events specified above occurs, box E (Action - Stop Track) marks the end of the tracks in the arena. - Box F (Rule End - Start-Stop Trial) marks the stop of the trial; it does not take any action. Notes - If the condition in box B is not met immediately, the time that tracking starts (C) is different from the time that the trial starts. - The Start-Stop Trial rule only works when you acquire data (live or offline). If you only record video, the Start-Stop Trial rule is inactive. You must start and stop video recording manually. See Also - Trial Vs. Track - How the Trial Control Instructions Are Executed - The Start-Stop Trial Rule in Special Cases The Start-Stop Trial Rule In Special Cases Multiple Arenas When multiple enclosures are defined as separate arenas, the default Start-Stop Trial rule is applied for each arena separately. This means that the condition in box B is applied separately for each arena. As soon as the subject is detected in an arena, tracking starts for that arena, not the others. As a result: - You do not have to release all the animals at the same time. - Tracking may start at different times in different arenas in the same trial, depending on when a subject is released in its arena. See Also - Trial Control in Multiple Arenas Multiple Subjects In The Same Arena When multiple subjects are present in the arena, tracking starts when the first subject is found. Therefore, tracking starts for all subjects at the same time, even if the others are not yet in the arena. For those subjects, the track starts with a number of missing samples, until the subject is found. To start tracking only when all subjects are found in the arena, and thereby avoid missing samples at the beginning of the track, see Start the Trial in the Social Interaction Test. With DanioVision If you create a DanioVision experiment, the Condition - In Zone box is not present. Tracking starts as soon as you start the trial. With Activity Analysis If you select Activity Analysis under Analysis Options in the Experiment Settings, the Condition - In Zone box is removed from the default Start-Stop rule. To carry out tracking and activity analysis simultaneously, and start tracking when your subject is detected in the arena for a specific time, insert a new In Zone condition box in the Start-Stop rule. Note: If you also select Behavior Recognition in the Experiment Settings, the Start-Stop rule is as described below. With Behavior Recognition If you select Behavior Recognition under Analysis Options in the Experiment Settings, a Time condition is added between the Condition - In Zone box and the Action Start Track box. This means that EthoVision XT waits 3 seconds after detecting the animal for the first time, before starting actual tracking. This is done because the behavior recognition algorithms need a number of video frames equivalent to about three seconds before the current frame in order to recognize behavior. The time condition "After a time of 3.0 s" is removed automatically from a Trial Control rule if you deselect Behavior Recognition in the Experiment Settings. Control The Start Of Tracking To Modify The Start Track Condition The default Start Track condition is a condition based on the variable In Zone. The condition becomes true when the subject is detected in the arena for one second. - Click the Settings button. - In the window that appears, specify in which zone the subject should be to start tracking. Click Settings and choose the zone. See details about the variable In Zone. - Specify the criterion (time, frequency in the zone, etc.). From the Statistic list, choose one of the statistics. See the details below. Statistics Available - Current Duration or Cumulative Duration to start tracking when the animal has been detected for some time in the zone. Current Duration is an uninterrupted period of time (for instance, the animal must be detected for 1 s without interruption). Cumulative Duration sums up all periods when the animal is in the zone since the start of the trial. - Current to start tracking as soon as the animal is detected (one sample is sufficient). Note that this condition may become true also when noise is occasionally detected as a subject for a very short time, before the animal is released in the arena. Make sure that this does not happen. --- ## EthoVision XT 19 - Trial Control Settings - Trial Control When Tracking from Video Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-trial-control-when-tracking-from-video-files Chapter: EthoVision XT Trial Control When Tracking from Video Files When Tracking from Pre-Recorded Video Files EthoVision XT checks conditions using the time in the video file, instead of the real time. - For conditions based on time: If you select the DDS option, Trial Control is carried out at the speed set by EthoVision in order not to skip video images. This results in the video playing faster or slower than normal (1x), depending on the processor load necessary to detect subjects. For example, if detection requires little processor work, the program tracks the subject faster than normal. A Time condition (for example, Time 60 s) is therefore met earlier than at real time. - For conditions that use clock time: If you define a condition based on clock time, or schedule a sub-rule with clock time, this is translated into the video start time, that is, the date and time the video file used for tracking was created. Example 1: You set a Time condition to start tracking After clock time 11:30. The video file was created on March 6, 2008 at 11:00. Once you start the trial, the condition is met half an hour later in the video. If you had set tracking to start After clock time 10:30, tracking would start immediately after starting the trial. Example 2: You set a sub-rule to start at 10:00 (1st day). The video file was created on March 6, 2008 at 11:00. Once you start the trial, the sub-rule never starts, because the planned start occurs before the initial time of the video. To make a sub-rule start when tracking from that video, set the start time between 11:00 and the video end time. When Recording Video, Then Tracking You can choose to record video first with EthoVision XT and then acquire the tracks from the resulting video file. In that case: - When recording video, Trial Control is turned off. - When you track from that video, Trial Control is activated, but you cannot control hardware devices. See Record Video, Then Acquire a Trial. When Re-Doing a Trial For video files recorded with EthoVision XT, you can re-do the corresponding trial. Note that the Trial Control log files recorded with the previous instance of the trial are deleted. Trial Control in Multiple Arenas Each Arena Gets Its Own Copy of Trial Control Settings If your experimental setup includes two or more arenas, Trial Control is applied to each arena separately. This means that if a condition is met in one arena, EthoVision XT takes the corresponding action in that arena, not the others. EthoVision XT evaluates the instructions for each arena within the same sample time. The order in which arenas are evaluated is not stored in your data. Using Zones in Multiple Arenas A condition or action is not specific to one arena. If the condition is based on a zone, that zone must be present in all arenas and have the same name. If the zone is not present in an arena, Trial Control cannot progress for that arena. Therefore, tracking does not stop unless you set a maximum trial duration or tracking reaches the end of the video. See Control the End of Tracking. Maximum Trial Duration with Multiple Arenas Note the following difference: - If the Trial Control Settings include a maximum trial duration, tracking stops in all arenas simultaneously. - If the Trial Control Settings do not include a maximum trial duration, and a condition is set before the Stop Track box, tracking does not necessarily stop in all arenas simultaneously. For example, if Start Tracking is set when the subject is found for the first time (as in the default Start-Stop trial rule) and a Time condition of 5 minutes is placed before the Stop Track box, and subjects in two arenas are found for the first time at different times, tracking starts and stops at different times in each arena, with the five-minute duration applied to each subject independently. View Trial Control Instructions During Acquisition Overview During acquisition you can view the status of the trial control instructions. This allows you to check that the Trial Control Rule works as expected — for example, that an action is taken when the subject enters a zone. You can also view Trial Control States, which are time intervals defined by two Trial Control Events. To View Trial Control States or Events During Acquisition In the Acquisition screen, click Show/Hide and select Show Dependent Variables. Then select Trial Control Event or Trial Control State. See Also - An example in Conditioning Test: View a Trial Control State Variable Source: EthoVision XT 19 Help - Trial Control Settings, Noldus Information Technology --- ## EthoVision XT 19 - Trial Control Settings - Trigger Sound Recording with UltraVox XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-trigger-sound-recording-with-ultravox-xt Chapter: EthoVision XT Trigger Sound Recording with UltraVox XT Aim To record ultrasonic vocalizations with UltraVox XT 3 while tracking the subjects with EthoVision XT. UltraVox XT is triggered by an EthoVision XT external command. Prerequisites - We recommend running UltraVox XT and EthoVision XT on separate computers, preferably connected through a network switch. Alternatively, you can use a local network, but that could add delays in communication between the two computers. On both computers, disable the firewall. - Set the IP addresses of the Ethernet ports on both PCs to match the IP address of the network switch. The following IP addresses have been tested: - Network switch (Netgear GS310TP): 192.168.0.239 - EthoVision XT 19 PC: 192.168.0.201 - UltraVox XT 3 PC: 192.168.0.202 - Important: If you decide to run EthoVision XT and UltraVox XT on the same machine, make sure that you start EthoVision XT and open the experiment before starting UltraVox XT. Also check that the PC can handle the recording of video, data, and sound simultaneously. Check that there are few or no missing samples in your data before carrying out the actual experiment. For more information, see the UltraVox XT Help. Procedure - When working with two computers, make the folder C:\ProgramData\Noldus\UltraVox\XT 3\Synch shared so it can be accessed by the SUV batch file. - In the EthoVision XT Trial Control Settings, define an external command that runs one of the batch files SUV.bat stored on the EthoVision XT computer. You can find the SUV batch files on the EthoVision XT full installation package, under Drivers and Tools > Utilities > UltraVox XT 3 Control. For more information on this file, see the UltraVox XT Help. If you work with two PCs and multiple arenas, use the batch file SUV - 2PC multiple arenas.bat (see below). We recommend not running EthoVision XT and UltraVox XT on the same PC when working with multiple arenas. - Place the external command immediately after the Start Track box. - Define a second instance of the external command and place it immediately before the Stop Track box. - Open your experiment in UltraVox XT and, in the Trial Control Settings under Start Acquisition, select External Program Trigger. - Start acquisition by starting the trial in EthoVision XT. - After acquisition, import the UltraVox XT data in EthoVision XT using the import profile for UltraVox XT 3. See also Import a Complete External Data File at Once. Note: for this step you need the External Data add-on module. See Modules of EthoVision XT. Triggering UltraVox XT with Two or More Arenas If you work with multiple arenas, use the batch file SUV - 2 PCs multiple arenas.bat so that the start command is given only once, for the first arena. This is the content of the batch file SUV - 2 PCs.bat for working with one arena: @if exist "\\IP address\Synch\start.txt" del "\\IP address\Synch\start.txt" @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 3 Control\start.txt" "\\IP address\Synch" > nul This is the content of the batch file SUV - 2 PCs multiple arenas.bat for working with two or more arenas: @if exist "\\IP address\Synch\start.txt" del "\\IP address\Synch\start.txt" @echo off echo %1 IF %1=="Arena 1" ( @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 3 Control\start.txt" "\\IP address\Synch" > nul ) Notes - In the Trial Control Settings, and for both action boxes, add a command line option: "%an%" (including quotes). - In the batch files, replace IP address with the IP address of the UltraVox XT computer (suggested: 192.168.0.202, or 10.0.0.9 as suggested in the UltraVox XT 3 Help). You can also use the computer name instead, for example DESKTOP-ABC123. - If the arena has a name different from Arena 1, replace Arena 1 with that name in the batch file. See Also - Import Profile for UltraVox XT 3 - Import a Complete External Data File at Once - External Commands --- ## EthoVision XT 19 - Trial Control Settings - Useful Things to Know URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-useful-things-to-know Chapter: EthoVision XT Useful Things to Know Components Pane Use the Components pane to choose conditions, actions and other elements for your Start-Stop trial rule. If you do not see the Components pane, click the Show/Hide button on the toolbar and select Components. To display the complete list of options, click the buttons next to More. What you see in the Components pane depends on what EthoVision XT license you have on your computer. Trial Control Boxes A Trial Control box has the following information: - A. Type of control (Rule Begin/End, Action, Condition, Operator, Reference). You cannot change this text. - B. Text describing the control. To change this text, click the Settings button and enter the text under Name, for example Drop one food item. You can also add a longer description under Comment (this is not shown). Names of Trial Control boxes must be unique, unless you make a copy of an existing box. See Re-use Trial Control Elements. - C. Depending on the type of control, this text shows the option chosen, for example the command to be given, or the sub-rule that the box refers to. Trial control boxes have different colors: - Light blue for the Start-Stop Trial rule, sub-rules and sub-rule References. - Olive green for conditions. - Light green for actions. - Grey for operators. To Zoom the Trial Control Rule In and Out - To enlarge the size of all trial control boxes up to their original size, click the Zoom in button (Ctrl+.). - To reduce the size of all trial control boxes, click the Zoom out button (Ctrl+,). - To make all trial control boxes visible on your screen, click the Fit all button (Ctrl+/). Tip: Navigate from left to right in the Trial Control window by using the scrollbar at the bottom. Use the Fit all button to make all trial control boxes visible. To Keep Trial Control Boxes Aligned The Trial Control boxes automatically snap to a grid. This helps you keep the boxes aligned. To show the grid, click the Show/Hide button on the toolbar and select Show Grid. To disable the grid alignment, click the Show/Hide button on the toolbar and deselect Snap to Grid. Trial Control Settings Become Locked After Acquisition After you have acquired at least one trial, the Trial Control Settings used for that become locked. In the Experiment Explorer, locked settings are indicated by a lock symbol, and cannot be edited. To edit a locked Trial Control Settings profile, duplicate it and edit this copy. See Re-use Trial Control Elements. To Export a Picture of the Trial Control Settings - Click the Export image button on the toolbar. - Select a location to save the image to, type in the File name or accept the default one and select an image type from the Save as type list, then click Save. The complete Trial Control window is exported, irrespective of the zoom factor. Conditions Aim A Condition is a statement that EthoVision checks during the trial. When the Condition is met (True), the program evaluates the next element in the Trial Control sequence. Examples (conditions highlighted): - When the rat reaches the platform, stop tracking. - When the mouse is detected in the open field, start tracking. - When the animal has visited zone A ten times, stop tracking. To Define a Condition - Open or create new Trial Control Settings. - In the Components pane under Conditions, locate the type of condition you want to define and click the button next to it. Tip: Combine two or more conditions using the Multi condition. For details, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. - Next to Condition name, type in the name you want to give to the condition, or accept the default name. - Specify the condition properties. See Types of Condition. - Enter a Comment (optional), then click OK. - Insert the condition box in the Trial Control rule. Types of Condition Time Defines a time interval that must elapse before an action is taken. Example: Start tracking two seconds after clicking the Start Trial button, or start tracking at 12 PM. Time Interval This condition makes sense when it is combined with another condition. Example: Stop tracking when the animal is found in Zone A (In zone condition) between 5 and 10 minutes (Time interval condition). Trial Control Variable To create a condition that is met when a Trial Control variable has a certain value, or a value within a range, or equal to another variable at the time the condition becomes active. See also To Define a Trial Control Variable. Example: Stop tracking when the variable Counter is greater than or equal to 10. Dependent Variables To define a condition based on the behavior of the subject, including behaviors scored manually. Choose one of the dependent variables to create the condition. - Example 1 - In Zone Condition: Stop tracking when the subject visits the target zone 10 times. - Example 2 - Movement Condition: Stop tracking when the subject has been in the Not moving state for more than five minutes. - Example 3 - Multi Condition: Stop tracking when the subject has explored an object for more than 5 minutes. Here, "explored" is defined with a Multi condition: (a) the subject's nose point is in the object zone AND (b) its head is directed to the object. When the two conditions are met simultaneously for a total of 5 minutes, the trial stops. --- ## EthoVision XT 19 - Trial Control Settings - Working with Boxes in Trial Control URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-settings-working-with-boxes-in-trial-control Chapter: EthoVision XT Working with Boxes in Trial Control Insert a New Box - Release the mouse button. The new box is inserted. Connect Two Boxes - Point the mouse to the center of the first box, press and hold the left mouse button and drag toward the center of the other box. - Release the mouse button when the pointer has reached the center of the other box. The two boxes are connected. Operator boxes can have one, two or more input arrows; all other boxes have no more than one input arrow. All boxes can have one or more output arrows, pointing to different boxes. Modify the Settings in a Box Click the Settings button in the lower part of the box. Make the appropriate changes in the window that appears. Delete a Box - Click the title of the box. The box border is highlighted. - Press Delete. Delete a Group of Boxes - Draw a box around the boxes you want to delete, or click on the boxes you want to select while holding the Ctrl key. - Press Delete. You cannot delete the Rule Begin box, the Rule End box, the Start Track box, or the Stop Track box. Delete a Connecting Arrow - Click the arrow you want to delete. The arrow turns bold to show it is selected. - Press Delete. You cannot delete the arrow connecting the Stop Track box and the Rule End box. Apply Trial Control to Your Trials Apply Trial Control Settings to a Single Trial Before starting the trial, do one of the following: - In the Experiment Explorer, make sure that the Trial Control Settings profile you require is highlighted in blue. - In the Acquisition screen, under Settings, select the Trial Control Settings you require. Test your setup thoroughly before carrying out the actual trials. Apply Trial Control Settings to Multiple Planned Trials Choose Setup > Trial List. For each trial planned in the list, select the Trial Control Settings you require in the Trial Control Settings column. For more information, see Prepare the Trial List for Batch Acquisition. Further Information on Trial Control Learn About - How the trial control instructions are executed - Trial control when tracking from video files - Trial control in multiple arenas What Do You Want to Do? - View trial control instructions during acquisition - Analyze trial control data How the Trial Control Instructions Are Executed When EthoVision XT Evaluates Conditions and Actions During a trial, EthoVision XT evaluates the Trial Control Settings selected for that trial and checks the state of conditions and actions at each sample time. Note that the sample time depends on the chosen sample rate, not on the video frame rate. How EthoVision XT Evaluates Conditions and Actions The program remembers which Trial Control box was evaluated (active) in the previous sample. Depending on the type of this box: - For a Condition box: EthoVision XT checks whether the condition at the current sample time is met. If it is not, the condition becomes false. The program waits until the condition is met. When this happens (condition becomes true), the program passes control to the next box in the sequence. The condition then becomes inactive. - For an Action box: EthoVision XT carries out the action and passes control to the next box, which becomes active. Then the Action box becomes inactive. - For sub-rules and sub-rule references, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. When a box becomes active, the previous box becomes inactive. Notes - Boxes combined in parallel using operators are evaluated at the same sample time, in unspecified order. This means that one cannot establish which condition is evaluated or which action is taken first. - Actions on Trial Control variables are executed immediately. Actions on hardware devices are executed when all boxes that must be evaluated at that sample time have been evaluated. - If a box being evaluated contains a condition that is immediately true, the program passes control to the next box. Therefore, within one sample time the program can pass control to two or more boxes to the right. - When you stop the trial or the maximum trial duration has been reached, all Trial Control boxes are deactivated and hardware devices are reset. See Control the End of Tracking. - When the Rule End box of the Start/Stop trial rule is evaluated, data recording stops. From that moment, Trial Control is deactivated, even in those sub-rules that were ongoing in the meantime. How Trial Control Instructions Are Executed: Step-by-Step Example The following steps describe an example of a Start-Stop trial rule: - Tracking starts, either manually or because a previous condition has been met. - Control passes to a Condition box (for example, "Is mouse on top of Shelter?"), which becomes active. The condition is evaluated. Since the condition is not met immediately, it becomes false. - The condition becomes true. - Control passes to the next box. In this case it is an Action box. Actions are taken immediately. - The Action box becomes inactive. The next box becomes active. For clarity, steps 3 and 4 are described separately. In reality, when a condition is met it becomes inactive at the same time, and control passes to the next box. --- ## EthoVision XT 19 - Trial Control state URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-state Chapter: EthoVision XT Definition A time interval specified by two events of Trial and Hardware Control occurred during the trial. The interval may also occur in two or more instances if the events that mark its start and end occur repeatedly during the trial. If an interval occurs in more instances during a trial, you can choose to analyze either each occurrence or sum up the results for all occurrences. See the Calculate Statistics Per Interval option below. How to Specify a Trial Control State - Click the Add button next to Trial Control state. - Next to From, from the Element list select the Trial and Hardware Control element that makes the criterion for the start of the interval. From the Event list, select the state of that element that makes the start of the interval. - Next to To, from the Element list select the Trial and Hardware Control element that makes the criterion for the end of the interval. From the Event list, select the state of that element that makes the end of the interval. Choose which occurrence of the ending event you want to consider. - Select Ignore last interval if incomplete to ignore the interval when the Trial Control event that defines the end of the state is not found. If you do not select this option, and the end criterion is not met, EthoVision XT defines an interval up to the end of the trial. Example: A Trial Control state is defined "from Trial start to when the condition 'Subject in zone A' becomes true." If the subject never enters the zone, then the end criterion is never met. If you select the Ignore option, the Trial Control state is not defined. If you do not select the option, the Trial Control state is defined from the start to the end of the trial. - An interval may occur several times in a trial. If you want to have statistics for each occurrence, select the Calculate statistics per interval option. Next to For consecutive intervals, choose the range of occurrences you want to have in the results. - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Notes - Do not select Calculate statistics per interval when you want to sum up the results from the occurrences of the state interval in the trial. For example, to calculate the cumulative duration of the state From condition 'In Cue zone' becomes true To condition 'In Feeder zone' becomes true. - Statistics of duration and latency can only be a multiple of the sample interval (= 1 / sample rate). For example, when you create a condition 'Subject in zone A for >= 3 s', this condition is met when the time elapsed from its activation exceeds 3 s. If the sample rate is 12.5 frames/s (thus the sample interval is 1/12.5 = 0.08 s), the condition is met at the first multiple of 0.08 greater than 3 s, that is 3.04 s. This affects data analysis; for example, the duration of the state 'From condition active to condition true' is 3.04 s. - The Frequency of a Trial Control state is determined by the start of the state. This means that at the end of a trial, a Trial Control state is counted even if there is no stop event. Trial Control States Based on Conditions The sample time at which a Trial Control state starts (or ends) also depends on the statistic used in the condition in the Trial Control rule. - If you use Current to define the condition (for example, "when Current In zone = true"), the Trial Control state starts (or stops) at the expected sample time. For example, when the animal actually enters the zone (and thus Current = true for that sample). - If you use any other statistic to define the condition (for example, "when Frequency of In zone >= 1"), consider the two scenarios: - When the condition becomes true after the condition box is activated (see How the Trial Control Instructions Are Executed for an explanation of the terms true and active), the Trial Control state starts (or stops) at the expected sample time (see A in the figure below). - When the condition is already true when the condition box is activated (for example, a condition "Frequency of In zone = 1" is activated when the animal is already in the zone), such a statistic is only evaluated at the next sample (or in the second next sample, in the case of Heading). In that case, the Trial Control state starts (or stops) one sample (or two) later than expected from the condition (see B in the figure below). However, for the consecutive frequencies of In zone = 2, 3, etc., the condition is already active by definition; therefore the Trial Control state starts at the expected time, when the condition becomes true. Example: A Trial Control condition has been defined in the Trial Control Settings, which checks that the statistic Frequency of the dependent variable In zone is >= 1 for the Center of the open field. A Trial Control state has been defined in the Analysis profile, which starts when the condition "Frequency of In zone >= 1" is true. A1: The animal enters the Center zone (and therefore the condition becomes true) after the condition is activated. The Frequency statistic is evaluated at the same sample time. A2: Plot of the variables In zone for the Center and the Trial Control state. The Trial Control state starts at the expected sample time, that is, when the animal actually enters the zone. B1: The animal is already in the zone when the condition is activated. Therefore, the condition becomes true at the same time that it is activated, but the Frequency statistic is evaluated at the next sample (here, sample rate = 5/s, thus after 0.2 s). B2: Same plot as A2; here, the Trial Control state starts 0.2 s after the In zone state. See Also - The EthoVision XT 19 - Trial and Hardware Control Reference Manual. To open this manual, in the Apps screen under Noldus choose EthoVision XT 19 Other Documentation. Application You can use Trial Control states to test whether trial control works as expected, and for analyzing learning behavior. For example, calculate the duration of the Trial Control state 'From Cue light ON to Subject in Feeder zone' to see whether this interval decreases during a trial. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Trial Control variable URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-control-variable Chapter: EthoVision XT Definition A variable defined in the Trial Control settings. See Actions > To define a Trial Control variable. You may want to analyze or visualize the values of a Trial Control variable. For example, you defined a variable named Counter, and: - You want to calculate the maximum value that the variable reached during different trials. - You want to visualize its values plotted against time. How to Specify a Trial Control Variable - In the Analysis profile, click the Add button next to Trial Control variable. - From the Element list, select the variable you want to analyze. - Complete the procedure to add the variable. See Calculate statistics: procedure. - To visualize the variable on the timeline, choose the Integrated Visualization. Notes - If you want to calculate the time that the Trial Control variable had a specific value, in the Analysis profile choose Multi-condition instead. There you can select the Trial Control variable and define the selection criteria. See Multi condition. - If you want to calculate the time based on a From - To criterion, choose Free Interval instead. There you can define, for example, an interval from Trial Control variable = 10 to Trial Control Variable = 15. See Free interval. External Data Variable Definition EthoVision XT only analyzes external data after resampling. That is, it does not analyze the original data, but a Dependent variable representing the imported signal, resampled to the same sample rate as the EthoVision XT sample rate. This is accomplished by combining upsampling and downsampling (see below). Downsampling and Upsampling Downsampling If the sample rate of the external data signal is higher than the EthoVision XT sample rate, the signal is downsampled. For each sample k, a new value is calculated from the values of the original signal in the interval (k-1; k] (or in multiple preceding sample intervals, depending on the Averaging interval chosen). The interval is half-closed, that is, all values of the signal between k-1 (not included) and k are considered. The new value gets the time stamp of sample k. Five methods are available to downsample the signal: - Last value - Maximum - Mean - Minimum - Total value Upsampling If the sample rate of the external data signal is lower than the EthoVision XT sample rate, the signal is upsampled. For each sample k, a new value is calculated from the values present in the sample interval (k-1; k] (or in multiple preceding sample intervals, depending on the Averaging interval chosen). If no value is found, a new value is interpolated using one of the methods available, or replaced by missing sample or a zero value. Four upsampling methods are available: - Last value - Linear interpolation - Missing value - Zero value Averaging Interval With Averaging interval you can smooth the values of the converted signal. This has an effect on both resampled and state variables. - With Averaging interval 1, the new value for sample k only depends on the original values of the signal in the interval (k-1, k]. Example: Downsampling an EEG signal with the Mean value method and an Averaging interval of 1. - With Averaging interval x (where x = 2, 3, ...), the new value for sample k depends on the original values of the signal in the interval (k-x, k]. Example: Downsampling an EEG signal with the Mean value method and an Averaging interval of 3. The signal is downsampled by calculating averages over 3 sample intervals, then averaging those three averages. Special Case: Resampling If the sample rate of the external data signal is the same as the EthoVision XT sample rate, but with different time stamps, the signal is re-sampled to align its values to the EthoVision XT samples. Values are shifted to the right. How to Specify an External Data Variable (Resampled) - Click the Add button next to the [data set name]. - Under Select, choose the Downsampling method (default: Mean value) and the Upsampling method (default: Last value). - Under Outlier filter, select the Averaging interval (default: 1). - Complete the procedure to add the variable. See Calculate statistics: procedure. - Plot Integrated Data or calculate the statistics. Notes - If you upsample a signal with a sample rate much lower than the EthoVision sample rate, and you choose Missing value as the Upsampling method, it may be difficult to see the data points. In Integrated Visualization, choose Show/Hide > Show Graph Data Points and zoom in the plot. - See also Averaging interval. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Trial List - Clear Trials in the Trial List URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-list-clear-trials-in-the-trial-list Chapter: EthoVision XT Clear Trials in the Trial List Aim To delete the tracks, the associated data and the recorded videos of one or more trials, but leave those trials as empty rows in the Trial List, so you can redo those trials at a later time. Important: When you clear a trial, the data scored manually (Manual Scoring log), the events of Trial Control and the hardware events associated with the trial are deleted. Note: Clear Trials is not the same as Delete Trials. When you delete a trial, the tracks are deleted and the corresponding row is removed from the Trial List. Procedure - Right-click the name of the trial that you want to clear and select Clear Trials. - Choose one of the options that appear. These depend on whether you tracked from external video files or live (+ save video). When tracking from external video files: - Clear tracks. The tracks are deleted. In the Trial List, the link to the video file used for tracking located in the System - Video File column is removed. Choose this option if you want to redo the trial using a video file different from the current one. - Clear tracks but re-use the video reference. As above, however the link to the video file is retained. You can open Acquisition to track from that video file. When tracking live (and optionally saving video): - Clear tracks. The tracks are deleted. This option is available if you acquired tracks without saving video. - Clear tracks but re-use the video. To delete the tracks, not the video file used to acquire those tracks. You can then track again from the video file. - Clear tracks and video. To delete the tracks and the associated video and redo the trial anew. - Clear video. To clear a trial that has video only (its current status is Postponed). You can then record a new video and acquire tracks. Notes - When you clear a trial, the Arena Settings, Trial Control Settings and Detection Settings that were selected in the Trial List are retained. See Also - Redo a Trial - Skip Trials - Skip Arenas Within a Trial Source: EthoVision XT 19 Help - Trial List, Noldus Information Technology --- ## EthoVision XT 19 - Trial List - Detection Statistics and Trial List URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-list-detection-statistics-and-trial-list Chapter: EthoVision XT Detection Statistics and Trial List Subject Not Found The percentage and number of samples in which the subject was not found. This information is useful to check the quality of detection in general. When a subject is not found, it means that EthoVision XT processed the image, but did not find anything matching the current Detection Settings. Use Subject Not Found to assess the quality of tracking. When you select another video file, or click Save Changes, the value for Subject Not Found is reset to zero. Note: This correction is not applied when the subject is not found for reasons other than dropped frames, for example when the subject is out of view. Warning Color Thresholds The percentages of missed samples, interpolated samples and samples where the subject is not found are usually displayed in green for each arena and subject. When the values are above the set threshold, they are highlighted in red. This helps you monitor the quality of tracking and spot detection issues. Click the button under Missed Samples, Interpolated Samples or Subject Not Found to change the thresholds. --- ## EthoVision XT 19 - Trial List - Edit the Trial List URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-list-edit-the-trial-list Chapter: EthoVision XT Edit the Trial List Enter Values in the Trial List Click a cell in the Trial List and enter the value you require, or select it from the list of values available. Filling the Trial List table is not mandatory. You can also enter those values in the data acquisition screen. Delete Values from the Trial List Select the appropriate cell and click Delete, or right-click the appropriate cell and select Delete. To delete trials, see Delete Trials or Clear Trials in the Trial List. Copy and Paste Values You can copy and paste part of the Trial List: - To/from Excel. You can copy a list of trials from Excel, for example, when you have made your list of independent variables and its values. You can copy and paste multiple columns but make sure the columns are in the exact same order as in the Trial List. - Within the same Trial List. You can copy and paste part of the Trial List to newly added cells, for example, when you have added new trials. - Select one or more cells in the Trial List or in the Excel worksheet. - Right-click one of the selected cells and select Copy, or press Ctrl+C. - Click a cell in the Trial List or in the Excel worksheet and either right-click and select Paste or press Ctrl+V. You can also select multiple adjacent cells to copy to. Click the first cell of the range, hold down Shift and click the last cell, then paste. You can also select nonadjacent cells using the Shift and Ctrl keys. It is only possible to paste in such a selection if there is just a single value on the clipboard. Drag and Drop Cell Values from Excel You can also drag and drop cells from an Excel worksheet. Drag the cells to the first cell in the Trial List where you want the values to be copied, then release the mouse button. Notes - A value can only be pasted if the format of the value corresponds to the format required by the cell. For instance, it is not possible to paste a cell with a non-numerical independent variable to a cell with a numerical variable. If you do that, you will get a warning. The existing cell value remains unchanged. - Check that the copied values of numerical independent variables are either within the predefined range or correspond to individual predefined values of numerical independent variables in the Trial List. - You can change the order of variables by selecting a column and dragging it to the new position. Skip Trials Aim To skip one or more of the planned trials because of unforeseen circumstances, for instance when a subject is no longer available. You can skip: - An entire trial. See the procedure below. For example, you track mice in an open field. For trial 5, the subject is no longer available. That means that after acquiring trial 4 you want to proceed with trial 6. - One or more arenas within a trial. See Skip Arenas Within a Trial. Procedure - Open the Trial List, and click Show/Hide > Variable > select Acquisition Status. - In the Acquisition Status column, select To Skip for the corresponding trial. - Proceed with acquiring your trials. If for any reason you want to acquire the trial set to To Skip, set it back to Planned in the Trial List and open the Acquisition screen. Notes - You can also skip a trial in the Acquisition screen. When the text on the video window shows the name of the trial that you want to skip, click the Skip Trial button. EthoVision is ready to acquire the next planned trial. - If your trials include multiple arenas and you want to skip an entire trial, select To Skip for all the arenas in that trial. Otherwise you can skip specific arenas within a trial. See Skip Arenas Within a Trial. - If you have recorded video and you want to skip trials or arenas before acquiring data, in the Trial List change the status from Postponed to Postponed To Skip. Skip Arenas Within a Trial Aim To skip one or more of the arenas within a trial because those arenas are empty or the subjects there should not be tracked. Example: You track fish larvae in a well plate with 24 wells. Therefore, each trial contains 24 arenas. When some wells are empty, it does not make sense to do tracking in empty arenas. Therefore, skip those arenas before acquiring the trial. Background Information - Before you acquire a trial which includes two or more arenas, all arenas are set to Planned. After acquiring the trial, they are all set to Acquired. - The To Skip option in the Trial List allows you to skip some arenas in a specific trial, so you can proceed with tracking in the remaining arenas. For example, in Trial 2, Arena 2 is empty, so you want to skip Arena 2. After you acquire Trial 2, Arena 1 is set to Acquired and Arena 2 is set automatically to Skipped. Procedure - Open the Trial List, and click Show/Hide > Variable > select Acquisition Status. - In the Acquisition Status column, select To Skip for the corresponding arena. - Proceed with acquiring your trials. Notes - When you skip arenas within a trial, only the subjects in the non-skipped arenas are tracked. - You can clear a trial with one or more skipped arenas. After clearing a trial, all arenas are set to Planned (or Postponed if you chose to record video and track later). Delete Trials Aim To remove the trial from the Trial List and the experiment. This includes: - The track data - The manually-scored data - The Trial Control events - The Hardware log - The video file (when requested) Delete Trials also removes the corresponding row from the trial list. Procedure - Do one of the following: - Click the trial name in the list, press Delete. - Right-click the trial name in the list, select Delete Trials. - If the trial is associated to a video file recorded with EthoVision XT, you are asked whether you want to rename it for backup purposes, or delete it. Choose the option that applies and click Yes. Notes - A video file is renamed with a number 0001 appended to its original name. The renamed video file is kept in the Media Files folder of the experiment. - With Clear Trials you can remove the tracks, keep the row empty and when necessary acquire that trial again. See Clear Trials in the Trial List and Redo a Trial. See Also - Clear Trials in the Trial List --- ## EthoVision XT 19 - Trial List - Trial and Arena Status URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-list-trial-and-arena-status Chapter: EthoVision XT Trial and Arena Status - Waiting. An arena gets the status Waiting when you have started the trial but acquisition did not yet start because you defined a Trial Control profile with a Start recording rule and the starting condition is not yet met. - Acquiring. An arena gets the status Acquiring when acquisition is ongoing. - Acquired. An arena gets the status Acquired when data has been acquired for that arena. System Variables Arena Name The name of the arena in which the animal was tracked. Arena Settings The name of the Arena Settings used to acquire your tracks. Detection Settings The name of the Detection Settings used to acquire your tracks. Interpolated Samples The proportion of samples that were interpolated during the trial, expressed in percentage. Interpolation occurs when the camera fails to send the video frames at the expected time. For details, see Detection Settings: Advanced Setup > Dropped Frames Correction. Missed Samples The proportion of missed samples, expressed in percentage. EthoVision misses samples if the processor load is too high or the camera delivers fewer video frames than expected. Recording After The length of the interval between the start of the trial and the start of acquisition. This variable has the value 0 unless you defined a condition between the Start Trial box and the Start Track box in the Start-Stop Trial rule in the Trial Control settings. Recording Duration The length of the interval from start of acquisition till stop of acquisition. Recording duration is equal to Trial Duration unless you defined a condition between the Start Trial box and the Start Track box in the Start-Stop Trial rule in the Trial Control settings. Start Time The date and time of the start of the trial. Subject Name The name of the subject that the track refers to. Subject names are specified in the Experiment Settings. Subject Not Found Proportion of time the subject was not found. If the subject is not found, it means EthoVision processed the sample but did not find anything matching the current Detection Settings. Therefore, this system variable is a measure of the quality of detection. Sync Status The status of the sync-out file. When no external data co-acquisition has been carried out for a specific trial, the status is Planned. As soon as co-acquisition is started on the DAQ system, the status becomes Acquired. Track The name of the track file. Tracking Source The video input on the encoder board connected to the camera. If you use a digital camera, this is the name of the camera. The cell is empty when you track from a video file. Trial Control Settings The name of the Trial Control profile used during tracking. Trial Duration The length of the interval from start of the trial until the stop of the trial. Trial Name By default, Trial 1, Trial 2, etc. To change a trial name, double-click it and enter a new name. Video File The name and location of the video file that was used or will be used for acquisition. Video Start Time The date and time the video file that you used for tracking was created. System Variable Format For the time stamp variables (Start Time and Video Start Time) and duration variables (Recording After, Recording Duration, and Trial Duration) you can specify the format. Double-click in the Format field. In the Format String window, enter your preferred format in the field at the top and click OK. For the other system variables Label, Description, Type, Predefined Values, and Scope you cannot change their format. Preparing the List of Trials - Plan your trials - Edit the Trial List - Skip trials - Clear trials in the Trial List - Prepare the trial list for batch acquisition - Import data from other experiments (use this option when you want to merge data from multiple identical experiments) Plan Your Trials Aim - To prepare the list of experimental trials in detail and in advance, so that fewer actions have to be taken during their execution. - Planning trials in the Trial List also allows you to run a batch acquisition. Select video files for all the trials in your trial list. For each trial you can optionally select separate Arena Settings, Trial Control Settings, and Detection Settings. Then you can automatically acquire all trials. If you do not predefine a trial list, it is built up automatically as you acquire new trials. Example: Define the independent variables ID and Dose and fill in the list of trials with the ID of the subjects to be tested, and the drug amount planned for each trial. When you start data acquisition, EthoVision XT informs you that for Trial 1 you need to prepare subject A21034 which has to be injected with 1.0 mg/kg apomorphine. To Define the List of Trials - Choose Setup > Trial List, or in the Experiment Explorer click Trial List. - To add trials, do one of the following: - If you track live or from videos, click the Add Trials button on the toolbar, then enter the number of new trials you want to add. - If you track from videos, you can add trials automatically based on the video files you select. Each video will be associated with one trial. Click the Add Videos button on the toolbar and select your videos. See also Automatically Add Video Files to the Trial List. - A number of rows appear in the lower half of the Trial List. Each row represents a trial, that is, an acquisition session to be carried out in one or more arenas. If your setup is made of multiple arenas, each trial is divided into multiple rows, each one representing a track, that is, data of one individual subject tracked in a single trial. - For each trial, enter the value of the independent variables in the corresponding cells, when required. - For each trial, select the Arena Settings, the Trial Control Settings, and the Detection Settings you want to use. Notes - If you do not see the columns Arena Settings, Trial Control Settings, and Detection Settings, click the Show/Hide button on the toolbar, select Variables, and under System select the items you want to view. - You can also edit the Trial List before, during, or after acquisition. See Edit the Trial List. - If trials are already present in the table, the trials you add are appended. --- ## EthoVision XT 19 - Trial List - Trial List URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-trial-list-trial-list Chapter: EthoVision XT Trial List Introduction to the Trial List Important Terms in the Trial List Independent Variable: An independent variable is a variable that you define to record specific experiment conditions, the identity of your subjects, or the amount of drug injected. An independent variable potentially determines the value of a dependent variable, such as speed of movement or distance moved. EthoVision XT assumes that the value of the variable stays constant throughout a trial. Independent variables are especially useful to create analysis groups. Example: The independent variable Treatment with possible values Control, Sham, and Treated. Each subject is assigned one of the values. In the Data Profile you can group tracks based on the value of Treatment. System Variable: A system variable is a variable that EthoVision records during acquisition. For example, the duration of a trial, or the name of the video file used in that trial. Trial: A trial is a single data acquisition session, no matter how many subjects are tracked simultaneously. For each trial, you can enter the value of independent variables. In the Trial List you can plan your trials. You can add and delete planned trials. You can also delete acquired trials. Useful Things to Know About the Trial List To Open the Trial List: Choose Setup > Trial List, or in the Experiment Explorer click Trial List. To Show and Hide Variables in the Trial List: - Do one of the following: - Click the Show/Hide button on the toolbar and select Variables. - Right-click a column header and choose Show Variable. - In the Show Variables window, select the variables of your choice and click Apply. Tip: Under System, also choose Subject Not Found and Missed Samples. These two variables give useful information about the reliability of your data. To Sort Columns in the Trial List: You can change the order of the columns. Click the column header to select the column of your choice and then drag it to the new position. While you drag it, a red line shows the insertion point of the column. To Show and Hide Row Headers in the Trial List: Do one of the following: - Click the Show/Hide button on the toolbar, select Row Headers, and then select the headers you want to display. - Right-click on any of the headers (Trial, Arena, Subject, No.) and select which headers you want to display. Import External Data Button: If you have the External Data Module, the Import External Data button is available on the toolbar of the Trial List. Click this button to import external data like EEG or Heart Rate into EthoVision XT and synchronize it with the tracks. Independent Variables Define an Independent Variable To label trials, arenas and subjects using an independent variable, for example the level of the treatment, the ID of the subjects and the day of testing: - Open the Trial List. - Click the Add Variable button. A new column with the label User-Defined is inserted at the end of the table. - Specify the label (name), description, type, format, predefined values and scope of the variable. Delete an Independent Variable To remove an independent variable that you no longer need in your experiment. This action removes the column from the Trial List and also removes the values of the variable assigned to each trial, arena and subject. Right-click the column header and choose Delete Variable. Notes: - You can only delete variables that you defined yourself. - To hide system variables, see System Variables. Variable Values, Formats and Other Properties Variable Label: In the Label field enter the name of the variable. The name must be unique. Names cannot be longer than 64 characters. The characters you use must be Unicode characters in the Basic Multilingual Plane range. Variable Description: In the Description field you can enter a short text or any other background information about the variable. The description is limited to 255 characters. The characters you use must be Unicode characters in the Basic Multilingual Plane range. Variable Type: Click the Type field and from the drop-down list choose one of the following options: - Text: A text variable is denoted by alphanumeric characters, composed of letters, numbers or both. For example, the name of the treatment. - Numerical: A variable represented by numbers only, for example, the dose of the drug that you apply. - Time Stamp: A variable represented by a time stamp, for example, the start date and time of the trial. - Duration: A variable represented by a duration, for example the duration of the treatment. - Boolean: A variable that is either False or True. For example, the presence of a novel object in the arena. Variable Format: - For Text variables you do not need to specify a format. - For Numerical variables, double-click in the Format field. In the Format window, select No. of Decimals and enter the number of decimals (1 to 9). If you work with integer values, leave the check box unselected. Select Scientific Notation if you want to write, for example, 1485 as 1.485e+0.03. In the Unit field, enter the unit of your variable, for instance µg/g for the dose of the drug, then click OK. To enter Greek symbols, use the Windows Character Map. - For Time Stamp variables, click in the Format field. In the Format String window, enter your preferred format in the field at the top. - For Duration variables, click in the Format field. In the Format String window, enter your preferred format in the field at the top. - For Boolean variables you do not need to specify a format. Predefined Values: - For Text variables, double-click in the Predefined Values field. In the Predefined Values window, under Predefined Value enter one of the possible values of the independent variable, then click Add. Repeat this step for all values. Keep the Allow Other Values check box selected if you are not sure whether the values that you defined are exhaustive. Clear this option if the values under Predefined Values are exhaustive. To delete a predefined value, select it in the Predefined Values field and click Remove. The characters you use must be Unicode characters in the Basic Multilingual Plane range. Example: Your independent variable is the treatment you apply, with possible values drug and saline. Enter drug, then click Add. Repeat this step for saline. - For Numerical variables, double-click in the Predefined Values field. In the Predefine Numerical Values window, select one of the following options: - Allow Any Value: Select this option if you do not want to predefine a range of values or individual values. - Define a Range: Define a minimum and maximum value. For instance, when the age of the rats in your experiment ranges from 6 to 18 months, enter 6 as the minimum value and 18 as the maximum. - Define Individual Values: Select this option when you are, for instance, testing a drug in three dosages: 0.05, 0.1 and 0.5 mg/g. Enter 0.05 in the Predefined Value field and click Add. The value moves to the Predefined Values field. Repeat this procedure for the other two values. Keep the Allow Other Values check box selected if you are not sure whether the values that you defined are exhaustive. Clear the check box if you are sure that you do not want to add new independent variable values. To delete a predefined value, select it in the Predefined Values field and click Remove. - For Time Stamp and Duration variables you cannot specify any predefined values. - For Boolean variables, double-click in the Predefined Values field. In the Predefine Boolean window, enter values for True and False. For instance, if your independent variable is Presence of Novel Object, define the values Yes (True) and No (False). Variable Scope: For the scope of an independent variable you can choose between the following three options: Trial, Arena and Subject. Example: The scope of the variable Bedding Type is Trial if all the arenas in a trial have the same kind of bedding material. Select Arena if the bedding material differs for different arenas during the same trial. For variables whose values may differ between subjects in the same arena and trial, select Subject. For instance, in two-subject interaction tests, the variable Sex (with subject 1 being male, and subject 2 female) or Status (subject 1 being resident, and subject 2 intruder). System Variables To View or Hide a System Variable: - From the Show/Hide menu on the toolbar, choose Variables. - Select the variables you want to view. To hide a system variable, clear its check box. Acquisition Status: The current status per arena: - Planned: When a trial is added to the Trial List, all the arenas within the trial get the status Planned. - To Skip: You can give an arena the status To Skip when for any reason you do not want or cannot track a subject in that arena. For example, when the subject that was planned in that arena is no longer available. - Skipped: The status Skipped is given to an arena that was previously set to To Skip. The status Skipped is therefore a label given after the trial has been acquired (or at least video was recorded for that trial). - Postponed: This label appears when you choose to record video and track later. After recording video, the arenas within a trial get the status Postponed. After you do tracking from that video, the status changes to Acquired. - Postponed to Skip: If you have recorded video without tracking, the status of the trials and arenas in the Trial List is Postponed. You can then choose to skip one of the trials or arenas by selecting Postponed to Skip. Do this for example if one of the arenas in the video is empty. --- ## EthoVision XT 19 - Troubleshooting Hardware Devices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-hardware-devices Chapter: EthoVision XT Issues - EthoVision XT does not record the pellet drops - The USB-IO box was accidentally disconnected, or is not found - EthoVision XT does not trigger the LED in an optogenetics setup - I cannot select devices from the second USB-IO box - Some inputs of the Fear Conditioning System do not work - How can I send data through a COM port? EthoVision XT Does Not Record the Pellet Drops The problem occurs also when the Pellet dispenser works just fine. - Check that all USB-IO boxes are powered up. If the USB-IO box is not powered up, it may work half way and that is rarely noticed. - If many devices are connected or there is much USB activity, EthoVision XT cannot read the pellet drops in the necessary time. The Pellet dispenser sends out an approximately 100 ms pulse to the USB-IO box and then EthoVision XT; if it takes longer to read the pulse, EthoVision XT misses the read out. Try to reduce USB devices that work simultaneously. See also the EthoVision XT 19 - Trial and Hardware Control - Reference Manual for limitations in the number of devices that can be controlled. The USB-IO Box Was Accidentally Disconnected, or Is Not Found The message At least one USB-IO box was not found appears. - Reconnect the USB-IO box to the EthoVision XT PC. Check that the USB-IO box is powered. - Click the Retry button (when this button is available). - Establishing connection requires some time. Wait until a message is given that the USB-IO box is detected again. If the message of re-established connection does not appear, close and then restart EthoVision XT. EthoVision XT Does Not Trigger the LED in an Optogenetics Setup In an optogenetics experimental setup, EthoVision XT controls one or more Pulsers through the USB-IO box. The Pulser and the LED can be triggered manually or with the Pulser software, but not through EthoVision XT. When the trigger command is sent out from EthoVision XT, the LED in the USB-IO box does not switch on. Solution: Review all the cable connections as described in the chapter Optogenetics experiments in the EthoVision XT 19 - Application Manual. Check that on the LED controller box, the switch at the back is set to Ext. Also in the Device Configuration window of EthoVision XT, make sure that for the ports TTL1, TTL2, etc., Custom hardware is selected. For details on this step, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. I Cannot Select Devices from the Second USB-IO Box A number of devices are connected to the EthoVision XT system through two USB-IO boxes. When one tries to select devices in the Device Configuration window, the drop-down menu under Devices is grayed-out. Solution: - Close EthoVision XT, and uninstall the Noldus HardwareInterface software. You can find this in the Windows Control Panel > Programs and Features. - Download the full installation file (see Install EthoVision XT), and browse to Drivers and tools > PreRequisites > HardwareInterfaceIobox. Run the installation file HardwareInterface_Iobox_x64 [version number].msi. Some Inputs of the Fear Conditioning System Do Not Work Check that the USB-IO box is powered. Review the cable connections as described in the section of the EthoVision XT 19 - Application Manual which describes the Ugo Basile Fear Conditioning System. How Can I Send Data Through a COM Port? Use case: Send a string or an integer to an Arduino board via COM. To do so, you must first install a DLL interface component. Please contact Noldus for further details. Once this component is installed: - In the Experiment Settings, declare the COM port as you would when using the Noldus USB-IO box and other devices. - In the Arena-Hardware Mapping window, map the COM port onto the arena. - In the Trial Control Settings, add an action based on a COM port. Note that: - Data (string or long integers) is sent out as a string. For example, if you specify 1234, the string "1234" is sent out. - A string can also be hexadecimal, for example, 0x6261. Two bytes are sent out, first 0x61, then 0x62. Issues - The quality of detection deteriorates with time - I cannot specify the white light fade duration in minutes and hours - There are spikes in the tracks - The DanioVision White light does not work when I skip some arenas The Quality of Detection Deteriorates with Time After a few trials, the subjects are no longer correctly detected. The issue likely occurs because of condensation on the Fresnel lens. - Set the anti-condensation mechanism to permanent On (see the DanioVision DVOC-0041 - Reference Manual for details). This bypasses the automatic control. - If condensation disappears after a while, the temperature sensor and/or the sensor circuit may be defective. If condensation remains, the glass heater may be defective. Contact Noldus Support for more information. I Cannot Specify the White Light Fade Duration in Minutes and Hours Probably you have an experiment created with a previous version of EthoVision XT. In that version you can only select a fade duration of the white light in seconds. There Are Spikes in the Tracks See the topic Troubleshooting: Data Acquisition > I see spikes in the track. The DanioVision White Light Does Not Work When I Skip Some Arenas Normally the White light device is associated with Arena 1 (A1 in most well plates). If you set that arena to To Skip, once you start the trial EthoVision XT does not send any command to the White light device because the corresponding arena is not active. To solve this issue, do one of the following: - In the Trial List, set Arena 1 back to Planned. EthoVision XT collects data for all the planned arenas, including Arena 1. If you are not interested in the data of Arena 1, you can filter it out in the Data Profile (Filter option). - In the Trial List, keep Arena 1 set to To Skip. Open the Arena Settings and in the Arena-Hardware Mapping window select No device allocated under Arena 1 and select White Light Stimulus under one of the arenas that you do not skip. The second option is only available when your experiment does not contain tracks yet. Issues - My results differ from what I obtain using the original Python scripts - Number and names of subjects do not match those in the LMT database file - The LMT database file is of incompatible format My Results Differ from What I Obtain Using the Original Python Scripts This may occur when you use Python scripts that were modified after the release of EthoVision XT. In that case we cannot guarantee that EthoVision XT gives exactly the same results. EthoVision XT is based on the Live Mouse Tracker scripts of version 1.0.3 (October 4, 2022). Number and Names of Subjects Do Not Match Those in the LMT Database File After you have selected a LMT database (*.sqlite) for import, an error message opens. - Click Close and open the Experiment Settings. - Next to Number of Subjects per Arena, enter the number of individuals that interacted in the LMT experiment. - If necessary, rename the subjects to A, B, C, etc. Do not enter other names. See Subjects per Arena. - Repeat the import data procedure. See Import Live Mouse Tracker Data. The LMT Database File Is of Incompatible Format After you have selected a LMT database (*.sqlite) for import, an error message opens. This could be caused by the experiment file being empty or without a definition of the subjects. It is probably corrupt. Try to export the LMT data again. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting Hardware Devices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-hardware-devices Chapter: EthoVision XT Issues - EthoVision XT does not record the pellet drops - The USB-IO box was accidentally disconnected, or is not found - EthoVision XT does not trigger the LED in an optogenetics setup - I cannot select devices from the second USB-IO box - Some inputs of the Fear Conditioning System do not work - How can I send data through a COM port? EthoVision XT Does Not Record the Pellet Drops The problem occurs also when the Pellet dispenser works just fine. - Check that all USB-IO boxes are powered up. If the USB-IO box is not powered up, it may work half way and that is rarely noticed. - If many devices are connected or there is much USB activity, EthoVision XT cannot read the pellet drops in the necessary time. The Pellet dispenser sends out an approximately 100 ms pulse to the USB-IO box and then EthoVision XT; if it takes longer to read the pulse, EthoVision XT misses the read out. Try to reduce USB devices that work simultaneously. See also the EthoVision XT 19 - Trial and Hardware Control - Reference Manual for limitations in the number of devices that can be controlled. The USB-IO Box Was Accidentally Disconnected, or Is Not Found The message At least one USB-IO box was not found appears. - Reconnect the USB-IO box to the EthoVision XT PC. Check that the USB-IO box is powered. - Click the Retry button (when this button is available). - Establishing connection requires some time. Wait until a message is given that the USB-IO box is detected again. If the message of re-established connection does not appear, close and then restart EthoVision XT. EthoVision XT Does Not Trigger the LED in an Optogenetics Setup In an optogenetics experimental setup, EthoVision XT controls one or more Pulsers through the USB-IO box. The Pulser and the LED can be triggered manually or with the Pulser software, but not through EthoVision XT. When the trigger command is sent out from EthoVision XT, the LED in the USB-IO box does not switch on. Solution: Review all the cable connections as in the chapter Optogenetics experiments in the EthoVision XT 19 - Application Manual. Check that on the LED controller box, the switch at the back is set to Ext. Also in the Device Configuration window of EthoVision XT, make sure that for the ports TTL1, TTL2, etc. Custom hardware is selected. For details on this step, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. I Cannot Select Devices from the Second USB-IO Box A number of devices are connected to the EthoVision XT system through two USB-IO boxes. When one tries to select devices in the Device Configuration window, the drop-down menu under Devices is grayed-out. Solution: - Close EthoVision XT, and uninstall the Noldus HardwareInterface software. You can find this in the Windows Control Panel > Programs and Features. - Download the full installation file (see Install EthoVision XT), and browse to Drivers and tools > PreRequisites > HardwareInterfaceIobox. Run the installation file HardwareInterface_Iobox_x64 [version number].msi. Some Inputs of the Fear Conditioning System Do Not Work Check that the USB-IO box is powered. Review the cable connections as described in the section of the EthoVision XT 19 - Application Manual which describes the Ugo Basile Fear Conditioning System. How Can I Send Data Through a COM Port? Use case: Send a string or an integer to an Arduino board via COM. To do so, you must first install a DLL interface component. Please contact Noldus for further details. Once this component is installed: - In the Experiment Settings, declare the COM port as you would when using the Noldus USB-IO box and other devices. - In the Arena-Hardware Mapping window, map the COM port onto the arena. - In the Trial Control Settings, add an action based on a COM port. Note that: - Data (string or long integers) is sent out as a string. For example, if you specify 1234, the string "1234" is sent out. - A string can also be hexadecimal, for example, 0x6261. Two bytes are sent out, first 0x61, then 0x62. Issues - The quality of detection deteriorates with time - I cannot specify the white light fade duration in minutes and hours - There are spikes in the tracks - The DanioVision White light does not work when I skip some arenas The Quality of Detection Deteriorates with Time After a few trials, the subjects are no longer correctly detected. The issue likely occurs because of condensation on the Fresnel lens. - Set the anti-condensation mechanism to permanent On (see the DanioVision DVOC-0041 - Reference Manual for details). This bypasses the automatic control. - If condensation disappears after a while, the temperature sensor and/or the sensor circuit may be defective. If condensation remains, the glass heater may be defective. Contact Noldus Support for more information. I Cannot Specify the White Light Fade Duration in Minutes and Hours Probably you have an experiment created with a previous version of EthoVision XT. There you can only select a fade duration of the white light in seconds. There Are Spikes in the Tracks See the topic Troubleshooting: Data Acquisition > I see spikes in the track. The DanioVision White Light Does Not Work When I Skip Some Arenas Normally the White light device is associated with Arena 1 (A1 in most well plates). If you set that arena to To Skip, once you start the trial EthoVision XT does not send any command to the White light device because the corresponding arena is not active. To solve this issue, do one of the following: - In the Trial List, set Arena 1 back to Planned. EthoVision XT collects data for all the planned arenas, including Arena 1. If you are not interested in the data of Arena 1, you can filter it out in the Data Profile (Filter option). - In the Trial List, keep Arena 1 set to To Skip. Open the Arena Settings and in the Arena-Hardware Mapping window select No device allocated under Arena 1 and select White Light Stimulus under one of the arenas that you do not skip. The second option is only available when your experiment does not contain tracks yet. Issues - My results differ from what I obtain using the original Python scripts - Number and names of subjects do not match those in the LMT database file - The LMT database file is of incompatible format My Results Differ from What I Obtain Using the Original Python Scripts This may occur when you use Python scripts that were modified after the release of EthoVision XT. In that case we cannot guarantee that EthoVision XT gives exactly the same results. EthoVision XT is based on the Live Mouse Tracker scripts of version 1.0.3 (October 4, 2022). Number and Names of Subjects Do Not Match Those in the LMT Database File After you have selected a LMT database (*.sqlite) for import, an error message opens. - Click Close and open the Experiment Settings. - Next to Number of Subjects per Arena, enter the number of individuals that interacted in the LMT experiment. - If necessary, rename the subjects to A, B, C, etc. Do not enter other names. See Subjects per Arena. - Repeat the import data procedure. See Import Live Mouse Tracker Data. The LMT Database File Is of Incompatible Format After you have selected a LMT database (*.sqlite) for import, an error message opens. This could be caused by the experiment file being empty or without a definition of the subjects. It is probably corrupt. Try to export the LMT data again. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Arenas and zones URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-arenas-and-zones Chapter: EthoVision XT Issues - How do I know the coordinates of the arenas, points and zones? - Tracking does not start when the animal is inside the shelter - The animal is in the hidden zone but the data show "missing sample" - How do I view the analysis results for hidden zones? - What if a hidden zone is part of a larger (overlapping) zone? - I get a warning that two zones point to the same region, when in fact they don't - I want to repeat calibration but I do not see the '+' cursor anymore How Do I Know the Coordinates of the Arenas, Points and Zones? - Open the Arena Settings. - Position the mouse pointer on one vertex of the arena/zone outline or on a point of interest. - Do not move the mouse. In the Status bar, locate the World point (for the coordinates in calibrated units, for example cm) or Pixel point (for the coordinates in pixels). Tips - If you do not see the Status bar, choose View > Status bar. - Zoom in the arena for a more precise positioning of the mouse pointer. - You can use the point coordinates to calculate the coordinates of the subject relative to a point of interest. See an example in Troubleshooting: How can I merge heatmaps generated in different arenas? - See also The x-y coordinate system in the arena. Tracking Does Not Start When the Animal Is Inside the Shelter In an experiment with a hidden zone, for example a shelter, it is possible that the animal is already inside that zone when you start the trial. In that case, the trial will only start when the animal first exits the hidden zone. If you want the trial to start straight away, recording the animal inside the hidden zone, you can make a second entry zone, somewhere where you can put, for instance, your finger. If you cannot get close to the shelter, you can draw a zone that runs along the arena side. After starting the trial, put your finger in that zone in such a way that EthoVision detects it (so the trial can start), then remove it — but make sure that the finger only appears and disappears in this entry zone, not the rest of the arena. This way EthoVision assumes that the animal has entered the hidden zone. The Animal Is in the Hidden Zone but the Data Show "Missing Sample" You may encounter this issue in the Track Editor or in the Track Visualization/Integrated Visualization. Normally this happens when the last recorded position of the animal immediately before disappearing from view is outside the entry zone. There are at least two possible reasons for that to occur: - The entry zone is too narrow and too near the hidden zone. So chance increases that the last data point occurs outside the entry zone, before the subject disappears from view. - Another reason is that Track noise reduction is applied during tracking. In such a situation, the position of the subject at any time is smoothed using the last 12 samples. Especially when the subject moves fast, the data points may "lag behind" the image of the moving subject (you can check this in the Integrated Visualization). It can happen that the last smoothed position is calculated outside the entry zone. In both cases there is some chance that the last data point before the subject goes missing is still outside the entry zone. For this reason, EthoVision XT considers the subject missing, not in the hidden zone. To solve the issue, do at least one of the following: - Make the entry zone larger. Duplicate the Arena Settings, enlarge the entry zone in such a way that the last position is likely to be inside that zone, and then use the new Arena Settings for the next trials. - Increase the sample rate. Especially if the animals move fast, increase the sample rate. This increases the chance that at least one point position is determined inside the entry zone. - Disable Track noise reduction. If you use Track noise reduction, duplicate the Detection Settings, under Smoothing set Track noise reduction to Off, and use the new Detection Settings to acquire the next trials. How Do I View the Analysis Results for Hidden Zones? To calculate the time that the subject spent in a hidden zone, choose In zone in the Analysis profile and select the hidden zone. What If a Hidden Zone Is Part of a Larger (Overlapping) Zone? - If the hidden zone is part of a larger zone, the results for that zone do not include the time spent in the hidden zone. This is because the time in the hidden zone is always calculated separately. - If an entry zone is part of a larger zone, the time in the entry zone is also included in the time spent in the larger zone. In practice: if a zone includes a hidden zone, in order to know the total time spent in that zone, including the time spent in the hidden zone, you must sum up the times shown in the results table. See a note under the topic In zone. I Get a Warning That Two Zones Point to the Same Region, When in Fact They Don't This is caused by very sharp corners of one or more zones. Using the Point edit tool (press P), move single points so that sharp corners are removed — for instance by adding a point just next to the sharp corner. See Move, rotate and resize a shape. I Want to Repeat Calibration but I Do Not See the '+' Cursor Anymore Click the Draw Scale to Calibrate button at the top-right corner of the screen. Issues - I cannot modify the Detection Settings - The yellow blob changes its size periodically - The percentage of Missed samples is very high - The detected nose point is far from the animal's contour I Cannot Modify the Detection Settings Once data has been acquired in EthoVision using a specific profile (Arena Settings, Trial Control Settings, or Detection Settings), they become locked from changes. This ensures that EthoVision always preserves the settings you used to acquire your data, so it can be checked or replicated. If you need to make changes, right-click your existing settings profile, and select Duplicate. The new profile will allow modifications. The Yellow Blob Changes Its Size Periodically The area considered as detected subject changes at regular intervals, as if the brightness of the image was not constant. - Check that the auto iris function of the camera is not enabled. - For digital cameras, increase the Exposure time. It may be that periodical changes in the intensity of the ambient light are picked up by the camera sensor. The Percentage of Missed Samples Is Very High There may be a few reasons for this: - The video resolution of the camera and/or the frame rate are set too high for the current detection method. EthoVision XT cannot acquire so much video information and at the same time track the subject. Reduce the frame rate and if necessary the video resolution in the Video source. - The camera may not be sending the video frames at the expected rate. This occurs often with webcams or IP cameras. Select Dropped frames correction. - The detection method currently selected is using too much processor time and that may not be necessary. For example, try a less demanding method like Static Subtraction instead of Dynamic Subtraction or Differencing. See also Sample rate. The Detected Nose Point Is Far from the Animal's Contour This may happen in some cases with detection based on Deep learning. For example, the nose is placed somewhere on an object or on the image of the subject reflected on a wall. In the Detection Settings, under Method, click Define and reduce the size of the box around the animal. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Behavior recognition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-behavior-recognition Chapter: EthoVision XT Issues - How do I check that the video file contains artifacts? - EthoVision XT finds more instances of a behavior than expected - EthoVision XT finds no instances of Grooming - I get different results when I use Behavior Recognition in two EthoVision XT versions How Do I Check That the Video File Contains Artifacts? Artifacts due to video compression can reduce performance of Behavior Recognition. - Create an experiment and set it to tracking From video file and Activity analysis. - In the Detection Settings, open the Activity analysis. Reduce the Activity threshold to the minimum. - If the video contains artifacts, you should see purple pixels appearing and disappearing with a regular rhythm. - Just to be sure, do a test trial and plot the Activity values in the Integrated Visualization. A pattern resulting from video compression artifacts looks like this: EthoVision XT Finds More Instances of a Behavior Than Expected This may occur due to the low contrast of the subject with the background, and too little contrast within the subject area, that is, too little detail in the fur. For example, too many Grooming instances are scored when the subject is asleep. This occurs when the image of the subject is overexposed. For example, white rats look pure white. In this case the inner part of the subject area is fairly constant in time, compared with the outline, and that increases the probability of detecting grooming. To solve the issue, close the lens' aperture or reduce the exposure time. See Adjust Camera Settings in EthoVision XT. EthoVision XT Finds No Instances of Grooming The subject clearly displays bouts of grooming, however EthoVision XT does not detect it at all. This may happen when the regular shape of the subject viewed from above is more "round" than usual, as it occurs in certain strains or circumstances. In that case, after clicking Grab in the Define Subject Properties dialog often results in a value of Posture being lower than the minimum required (70 for mice). This means that the contracted shape of the subject during grooming is more likely to be considered as "normal", therefore grooming is not detected. Find a video frame where the subject walks and looks a bit stretched, preferably when one can see the contour of the hindlimbs. Then, click Grab. Repeat these steps until the value of Posture obtained is higher than the minimum required. Different Results Between EthoVision XT Versions There may be differences in the scores of behaviors between EthoVision XT 19 and a previous version, even when using the same video file and the same Behavior Recognition settings. This may have to do with the different video decoding software that is used in the two versions. Small changes in the way video is displayed (e.g. the same pixel displayed with slightly different intensity value) may result in changes in the probability of some behaviors, and therefore influence the automatic scores. Testing of a number of video files found that the codec used to create the video file may affect the difference in the results between software versions. When the video was created with H.264 MPEG-4 AVC codec or the mp4v MPEG-4 codec, the average difference in the behavior scores (either frequency of occurrence or cumulative duration) expressed as a percentage of the scores obtained with the same video in EthoVision XT 15, is between 0 and 2% (averaged across all behavior categories). The H.264 MPEG-4 AVC codec is used by EthoVision XT 16–18 and MediaRecorder 5–6. The mp4v MPEG-4 codec is used by EthoVision XT 15 and MediaRecorder 4. For codecs like DivX, Xvid, MPEG 1 and MPEG 2, the average difference between EthoVision XT 15 and 16 is larger — up to 22%. As general recommendations: - Always use EthoVision XT or MediaRecorder to record video that you will analyze with Behavior Recognition. - When you upgrade an experiment made with an older version of EthoVision XT to EthoVision XT 19, and you want to re-do Behavior Recognition, make sure you use exactly the same Arena Settings and Detection Settings that you used with that particular video file. - In the Analysis profile, adjust the criteria based on the behavior probability to only consider the instances of behaviors that have a high probability, for example higher than 95%. That usually gives more robust results. See Also - Behavior Recognition: Data, Performance and Accuracy - How Behaviors Are Scored in Behavior Recognition - Dependent Variables: Behavior Recognition Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Camera URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-camera Chapter: EthoVision XT Issues - The camera name is partly hidden in the Experiment Settings - I cannot see the camera image when I click on the Camera icon in the Experiment Settings - When I click on the camera icon in the Experiment Settings, the Video Settings box says "No frames available" - There is no video camera listed in the Experiment Settings - One or more cameras are not listed in the Experiment Settings - The settings for color space are not available - I cannot select a specific combination of frame rate and color space - EthoVision XT stops working when two or more digital cameras are connected - I cannot select a high frame rate - I notice that video frames are dropped. Reducing Exposure time did not help. - After selecting the first GigE camera in Experiment Settings, when I select the second camera, EthoVision crashes - When using multiple GigE cameras, if one of the camera signals is lost, the order of the cameras in EthoVision XT scrambles - EthoVision XT freezes in live video mode - Error message "Device unplugged" The Camera Name Is Partly Hidden in the Experiment Settings In the Windows Control Panel, choose Display and reduce the text size, for example select 100%. Cannot See the Camera Image in the Experiment Settings - Make sure that pylon Viewer is closed. - Make sure that the camera(s) is connected to the PC and powered prior to opening EthoVision XT. - Make sure that the aperture of the lens is fully open (lens ring all the way to Open or O). - Make sure the correct camera is selected in the Video Source list of the Experiment Settings. For example: Basler GenICam [Basler acA1300-60]. - Make sure that the correct camera driver version 7.5.0 is installed. To find the version number, in the Windows Control Panel choose Programs and Features and locate the pylon Camera Software Suite. - Check the IP addresses of the Ethernet board ports and the cameras. See Assign IP Addresses. The Video Settings Box Says "No Frames Available" - When using Windows 10: make sure you installed the camera driver from the installation files. If you installed it from an older installation disk, you could have installed an older driver (for example 4.2.1) which does not support Windows 10. For the driver version that applies to your cameras, check the table in Cameras Supported by EthoVision XT. - If you changed the settings in pylon Viewer, check in that software under Acquisition Controls that the Trigger Mode is set to Off. - Other causes are possible, such as installing Windows 10 on an older PC which is not compatible with Windows 10. - If none of these examples fit your situation, contact Noldus Support for further assistance. Please also make a PC report for Support. There Is No Video Camera Listed in the Experiment Settings - Make sure that the IP addresses are assigned to all cameras and ports in the Ethernet board. See Assign IP Addresses. - Check in the Windows Control Panel that the drivers for the camera are installed. - Check the driver version. If the driver version differs from that reported in the table (see Cameras Supported by EthoVision XT), uninstall the driver from the Control Panel and install the correct driver. IMPORTANT: Always re-install the camera drivers from the EthoVision XT setup file, using the Modify option. If you need to install the Basler camera driver software from the original installation file Basler_pylon_[version number].exe, do the following: - Log in to my.noldus.com. Choose Downloads > EthoVision XT > Drivers and Tools. Download Basler Camera Driver - Noldus - [version number]. Extract its content and copy everything to the local disk. - Double-click the file Basler_pylon_[version number].exe. Accept the Terms and Conditions, then click Next. - Under Profiles, select Custom and click Next. - Under Features, choose GigE Camera Support for GigE Vision cameras, or USB Camera Support for USB 3.0 cameras. Make sure to select pylon Viewer and DirectShow Support. - Complete the installation. One or More Cameras Are Not Listed in the Experiment Settings - Check that you selected the correct number of cameras. - Check that all cameras are connected and powered up. For digital cameras: close EthoVision XT and start pylon IP Configurator. There you should see which cameras are connected. - Make sure that the IP addresses are assigned to all cameras and ports in the Ethernet board. See Assign IP Addresses. - Check whether that camera is already selected in a different input. For example, you may not see a camera for input 4 because that camera was already selected for input 1. - It may be that after adjusting the settings for the first camera, those settings are no longer compatible with those still applied to the other cameras. For example, suppose you select Binning for the first camera, then you decide to de-select it. When you return to the camera list, Binning is still selected for the remaining cameras. This makes the camera views of the other cameras incompatible with that of the first one. The result is that the remaining cameras are removed from the list. To solve this, select a new camera from the list at the top, and clear the Binning option for that camera. Click OK, and do the same for the remaining cameras. The Settings for Color Space Are Not Available For a color camera such as the Basler AcA1920-40gc, when choosing the color space, the settings for BYRG may not be available. Solution: - Select BYRG as the color space. - Disconnect the camera so it does not receive power. - Reconnect the camera. - Fine-tune the camera setup, leaving the color space set to BYRG. Cannot Select a Specific Combination of Frame Rate and Color Space This happens because some values of video frame rate and color space are not compatible in some cameras. Those frame rate and color space combinations have been removed in the software. EthoVision XT Stops Working When Two or More Digital Cameras Are Connected The problem occurs when the video resolution does not match the values accepted by the software. Select for example 800x600, not 640x426. See the tables in Cameras Supported by EthoVision XT. See also: - Adjust Camera Settings in EthoVision XT - Camera Installation Cannot Select a High Frame Rate For example, in the EthoVision XT Experiment Settings, when the resolution is set to a range of 1280x960, the maximum attainable frame rate may be as low as 7.5 frames per second. - Check that the Exposure Time setting is not too high. See Adjust Camera Settings in EthoVision XT > Camera/General Tab. - Make sure that the Power Injector is in fact a 1GB Power Injector. - Make sure that the network card is in fact a 1GB network card. If that is the case, check that it is set to Auto-negotiate. If it is, then the network card either needs a driver update or is defective. - Check the cables. Cheap, incorrect, or defective Ethernet cables can also reduce the frame rate. - The PC may have insufficient resources, for example only an on-board video card. Please contact Noldus Support and make a PC report for Support. Video Frames Are Dropped and Reducing Exposure Time Did Not Help Check that the camera settings match those of the Ethernet board by referring to the following resource: https://docs.baslerweb.com/knowledge/how-to-troubleshoot-lost-packets-or-frames-while-using-gige-cameras EthoVision Crashes When Selecting the Second GigE Camera In the Experiment Settings, next to each video source, select a standard resolution such as 640x480. Avoid non-standard resolutions such as 640x426. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Camera (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-camera-continued Chapter: EthoVision XT Scrambles - Always plug the cameras into the same ports. Label the ports and camera cables if needed to keep things in order. - Restore the camera signal. - In EthoVision XT, choose Setup > Acquisition, then choose Setup > Experiment Settings, and then go back to Acquisition. The camera order should now be restored to what you originally setup when first setting up this experiment. Despite the visual swapping of the cameras listed in Source table (via Experiment Settings), the order of the cameras should still load in the correct order matching the arenas. Error Message "Device Unplugged" Check first the cable connections between cameras and PC. Check the video resolution in the Experiment Settings screen. Probably the resolution of resulting merged view is too large. Reduce the resolution in such a way it is compatible with the software. - For eight cameras, 2560 x 960. - For sixteen cameras, 2560 x 1920. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Data acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-data-acquisition Chapter: EthoVision XT Video Tracking - The Start Trial button is grayed out - I track from the live camera image, and I get missing samples - I track from video, yet I get missing samples - Tracking from video is slow - During tracking there is a significant lag - The subject's trail (or the area where it was first detected) is detected as the subject - The text on top of the video window during acquisition is too small - Tracking does not start when the animal is inside the shelter - I cannot make tracks of long duration - I selected the DDS option but my video plays at normal speed. Why? - I see spikes in the track - Error: The trial duration does not correspond with the system time (Id: 12015) - The subject is detected in one arena, while in another arena I only see an orange blob Manual Scoring - I do not see a behavior category in the Manual Scoring screen - I want to remove the center point of the subject while observing - The body points of one or more subjects are not displayed in the Manual Scoring screen Other Issues and Questions - I cannot start acquisition with a remote control - I cannot import external data, or I get an error message "a gap was detected in the raw data" - How can I randomize the start time of my trials? - The Acquisition screen is not available in a Quality Assurance (GLP) experiment - How do I start data acquisition on multiple PCs simultaneously? The Start Trial Button Is Grayed Out This may also happen when trials are planned. Adding trials in the Trial List does not help. - Make sure that, in the trial list, all the necessary settings are selected (Arena, Trial Control, Detection). - Make sure that the video selected in the Trial List is the same as that selected in the Acquisition screen (you find its name next to the Video button). - If you defined behaviors in the Manual Scoring Settings, make sure that there is one selected as initially active. I Track From the Live Camera Image and I Get Missing Samples This could be due to a number of reasons. - Tracking is too processor-demanding. - Try reducing the sample rate, or use another detection method (e.g. Dynamic subtraction instead of Differencing). - Camera settings are not optimal. - Make sure that the Exposure of the camera does not reduce the frame rate of the camera. See Adjust the Camera Exposure Time. - Make sure in EthoVision XT that Video Pixel Smoothing is set to None. See Detection Settings > Video Pixel Smoothing. - In the Experiment Settings, click the camera button. Make sure that the color space is Y800 for monochrome cameras. See Adjust Camera Settings in EthoVision XT. - Communication between camera and computer not optimal. - In some circumstances the Ethernet board is not set properly, or the data transfer rate is too low for the frame size. You may see this message in pylon Viewer. Either reduce the video resolution and frame rate, or increase the packet size in pylon Viewer (in the Feature panel, locate Transport Layer). A packet size of 1500 should be fine. If this is not sufficient, increase the packet size to the maximum. If it does not help, there may be something wrong with the Ethernet board. See also Settings of the Ethernet Board. - Disable the firewall. See Disable the Windows Firewall for the Ethernet Board. - Disable your anti-virus software: check the settings in your anti-virus software or ask your local IT person to disable it. - As a last resort, do a factory reset on the camera. See Do a Factory Reset on the Basler GigE Camera. - If none of the above solves the issue, please Make a PC Report for Support. See also: Missed Samples. I Track From Video Yet I Get Missing Samples This is probably caused by the option DDS (Detection Determines Speed) not being selected. When DDS is selected, EthoVision XT takes the time necessary to process the images, and samples are not missed. See DDS (Detection Determines Speed). If you work with multiple subjects per arena, and you do not want to select DDS — for example because you score behaviors live and you do not want video to be played back too fast — then in the Detection Settings (Subject size section), move the Modeling effort slider towards Performance. This reduces the likelihood that samples are missed. See Advanced Detection Settings: Subject Size (Multiple Animals Per Arena). Also make sure that the camera Exposure time does not conflict with the camera frame rate. See I Cannot Select a High Frame Rate. Tracking From Video Is Slow Close other programs, including virus scanners. Check if the drivers of the video board (not the encoder board) are up to date. During Tracking There Is a Significant Lag At times the system freezes a bit, then catches up and resumes. - Restart the PC daily to refresh the PC's resources. - Assuming you are using a PC purchased from Noldus and the setup isn't too demanding (e.g. multiple arenas, deep learning), then this is likely to be related to incorrect exposure settings in pylon Viewer. See Adjust the Camera Exposure Time. - Check that the video resolution is compatible with the frame rate; this may also need adjusting. See Adjust Camera Settings in EthoVision XT. - Also do a check for missing samples. See Check That the Camera Is Set Up Properly. - If none of the above resolves your lag problem, consider whether your PC was purchased from Noldus. If not, it may be insufficient to run EthoVision XT. To have Noldus Support review your PC specifications, please Make a PC Report for Support and submit a support case at my.noldus.com. The Subject's Trail Is Detected as the Subject Make a reference image of the empty arena. Or if you use video, open the Advanced section in the Detection Settings pane and click Background next to Detection Reference Image. Choose one of the options in the window that opens. The Text on Top of the Video Window During Acquisition Is Too Small The size of the text is proportional to the screen resolution. The higher the resolution, the smaller the text. To solve this, choose a lower screen resolution. I Cannot Make Tracks of Long Duration Try the following: - Switch off the Windows power-save options. - Remove virus scanners. - Switch off the automatic Windows Update. If that cannot be done, disconnect the computer from the internet and restart it before acquiring data. - Make sure that you have enough disk space. For information on the maximum trial duration tested with specific cameras, see Resolution, Frame Rate, and Maximum Trial Duration. To track or record video for longer than the durations reported above, we recommend that you make a series of trials. See Split a Multi-Day Test in Multiple Trials. I Selected the DDS Option but My Video Plays at Normal Speed The cause could be related to the amount of data processing that EthoVision XT carries out. For example, the following options in the Detection Settings may be enabled: Track noise reduction and Dropped frames correction. To speed up data acquisition, make a copy of the Detection Settings, set the options above to Off, and re-do the trial with those new settings. Alternatively, accept the slow data acquisition if you need those settings to produce good data. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Data acquisition (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-data-acquisition-continued Chapter: EthoVision XT I See Spikes in the Track This may occur in the Detection Settings, during data acquisition or in Track Visualization, or in the Integrated Visualization. In most cases you need to correct the arena settings and the detection settings. Here are a few examples: - EthoVision XT tracks light reflections as the subject. Remove sources of reflections by using diffuse, indirect light. Watch the video chapter Set Up the Test Environment in Help > Video Tutorial. - EthoVision XT detects some noise at the margin of the well. You can do two things: - In the Arena Settings, reduce the size of the arenas, so they do not include the margin of the wall where the animal will never be. This should solve most of the issues. - In the Detection Settings, increase the Minimum Subject Size so small groups of pixels will not be detected as the subject. If you work with DanioVision, move the Sensitivity slider to the right. See Advanced detection settings: Subject size (one subject per arena). - EthoVision XT finds the subject but it considers it as noise (here in orange), while other objects are detected as the subject. In this case it may suffice to increase the Maximum Subject Size in the Detection Settings. The Maximum value should always be higher than that under Current when the animal is detected correctly. See Advanced detection settings: Subject size (one subject per arena). You can also remove spikes by editing the tracks (not in DanioVision though). See Edit the Tracks. Mismatch Between System Time and Tracking Time This could occur if the video camera provides an unreliable (i.e., fluctuating) frame rate. This may cause a mismatch between the system time and the tracking time. This halts data acquisition. Industrial cameras such as the Basler cameras have reliable frame rates, while IP cameras and web cams often do not. If the camera is faulty or the driver is not installed properly, unreliable frame rates could occur. I Only See an Orange Blob This may be caused by one of the following: - The second animal is of a color that does not match the current detection settings. - The reference image is not updated. - The subject in the second arena is larger than the one in the first arena, and it exceeds the Maximum Subject Size currently set in the Detection Settings. See Advanced detection settings: Subject size (one subject per arena). - The second arena is set to To Skip. Open the Trial List and set the Acquisition Status for that arena back to Planned. I Do Not See a Behavior Category in the Manual Scoring Screen This happens when you open the Manual Scoring screen, then open the Manual Scoring Settings to define a new behavior there, and then return to the Manual Scoring screen. Solution: Close and reopen the experiment. Subject Visibility While Observing In some cases the center point of a small animal makes it hardly visible. Solution: To hide the center point, choose Track Visualization or Integrated Visualization or Track Editor, and de-select the body points on the right-hand pane. Next, close and re-open the experiment. Missing Subjects in the Manual Scoring Screen This happens when one or more subjects have been de-selected in the Track Editor or in one of the Visualization screens. Solution: - Open the Track Editor or the Integrated Visualization. - In the Track Plot Settings, under Subjects select the items you are interested in. - Return to the Manual Scoring screen. I Cannot Start Acquisition with a Remote Control The remote control only works after opening the Acquisition screen and adding a new trial. To activate the remote control, follow the instructions, see Use a remote control to start and stop acquisition. Contact Noldus Information Technology to obtain a remote control. IMPORTANT: Before using the remote control, make sure that the Video window or the Playback Control window are on focus. To do so, click anywhere on the Video window or the Playback Control window. Then, operate the remote control. How Can I Randomize the Start Time of My Trials? For example, start a one-minute trial every N minutes chosen randomly between 60 and 120. - Create a batch file that performs a key press Ctrl+F5, which triggers the start of the trial. In this example, a batch (*.bat) file calls a VBS script (*.vbs) in Windows: wscript "C:\vbsprogram.vbs" - The VBS script contains the following code: Set WshShell = WScript.CreateObject("WScript.Shell") WshShell.AppActivate "EthoVision" WScript.Sleep 1000 WshShell.SendKeys "^{F5}" - In Windows, open the Task Scheduler and create a new task. - In the Triggers tab, specify when a trial should start (e.g. with a random delay). - In the Actions tab, select the batch file (*.bat) that triggers the key press Ctrl+F5. - See also Start and stop the trial at specific clock times. Notes: - When the task is enabled, make sure that the EthoVision XT Acquisition screen is open, and there are no other windows or applications open. - The end of each trial should be set in the Trial Control Settings. - In the Trial List, create a list of trials with the appropriate settings already assigned to each trial. - WScript.Sleep 1000 (1 s delay) ensures that the key press is given when EthoVision XT is in focus. Cannot Open a GLP Experiment First, make sure that you have a valid EthoVision XT license that includes the Quality Assurance module. See Modules of EthoVision XT. This issue could occur if you use EthoVision XT 17 or earlier, and you try to open Acquisition with an EthoVision XT software license. In that case you need a license on a hardware key instead. See Types of EthoVision XT license. Contact Noldus when needed. How Can I Start Data Acquisition on Multiple Computers Simultaneously? In the following example, we want to start data acquisition (that is, tracking) in three computers. For this you need three USB-IO boxes and EthoVision XT with the Trial and Hardware Control module in all PCs. - Connect the first PC (master) to the other two through the USB-IO boxes: TTL port 1 of the master PC to the TTL port 1 of the second PC, and TTL port 2 of the master PC to the TTL port 1 of the third PC. - For each PC, configure the hardware in the Experiment Settings. - On the master PC, open the Trial Control Settings and modify the Start-Stop Trial rule in such a way that a TTL "high" signal is sent after the start of tracking to both ports TTL 1 and TTL 2 simultaneously. Make sure that the Action boxes and the Operator are at the right of the Start track box. - For each of the other PCs, open the Trial Control Settings and modify the Start-Stop Trial rule in such a way that tracking starts as soon as a TTL "high" signal is detected in TTL port 1. Make sure that you place the Condition box at the left of the Start track box. - To start acquisition in all the PCs, click the Start Trial button on the master PC. As an alternative solution, you could devise a push button that sends TTL signals to each of the USB-IO boxes through UTP cables. Contact Noldus if you need this device. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Data visualization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-data-visualization-dMz Chapter: EthoVision XT Tracks and Integrated Visualization - I defined "In zone" for two adjacent zones. In the Integrated Visualization, I see that the animal is in the two zones simultaneously - I defined a free interval, and in the visualization I get an interval every other sample - I plotted a variable in the Integrated Visualization. I only get a few values on the timeline. Why? - I interpolated my data, but some variables including Elongation and Mobility still show missing values - Screen recording could not be started - There seems to be a delay between video and track - The video image is not shown - Video is choppy or does not play smooth - The points are too small (or too large) or the traces are too narrow (or too thick) - When I import UltraVox XT data, some calls are visualized as 1, others as 0.5. Why? - The Integrated Visualization shows "Not calculated" - The Data Preparation Report says "Failed" for some trials - I cannot visualize a trial - The name of the trial is not fully visible Heatmaps - A heatmap is plotted outside the arena, or merged with the heatmap of other arenas - In the Heatmaps screen the Group Mean button is not available - How can I merge heatmaps generated in different arenas? Animal Appearing in Two Zones Simultaneously This happens when a Zone exit threshold has been defined that is greater than 0, and the two zones Center and Border are adjacent. In such a case, when the animal moves from Border to Center, it is at some point considered to be in Center, but if it is not yet outside the zone exit threshold of Border, it is also considered to be in Border. To prevent this, re-define the two zones in such a way that there is a gap between the two, its width being at least the same as the zone exit threshold. Getting an Interval Every Other Sample Most probably you defined a free interval based on two values of external data or a hardware variable, for instance: - From Heart rate >= 300 to Heart rate >= 400 - From Number of pellet drops >= 1 to Number of pellet drops >= 10 When the value of the (resampled) variable reaches the second (higher) threshold, the interval ends and EthoVision XT finds the next sample that matches the criterion defined in From (first threshold). If the current value is higher than the first threshold, a new free interval is defined. However, if the value at the next sample is also higher than the second threshold, the interval is ended, resulting in a free interval of one sample. The search is repeated in the next samples, generating a repeating pattern. In such cases, do not use a free interval. Instead, use a state variable that is based on the original external or hardware signal. You can find the state variable in the Analysis profile. For example, for the external data Heart rate, in the Analysis profile under External data choose Heart rate state. For a hardware signal, under Hardware choose Hardware state. There you can define the range of values you are interested in. Only a Few Values Appearing on the Timeline This may happen for variables which require two or more consecutive data points to be calculated. Consider the following examples: - Your data contain missing samples. If one sample is missing, the variable is not calculated for one, two or more time points. For example, Distance moved is not calculated for two time points, and Turn Angle is not calculated for three time points. - You may have applied the Minimal Distance Moved smoothing method. When using this method, if the distance between body points for time t and t+1 is lower than the Minimal Distance Moved, the body point at time t+1 is "moved" to the same coordinates as the point at time t. In this case Distance moved gets the value 0 (zero), but any variable that quantifies change in direction has no meaning and is therefore not calculated for that sample. If many samples in your track are filtered out this way, variables like Turn Angle, Meander, and Heading only appear in short segments. Because the filter removes data points that do not represent movement, these few remaining segments are a more realistic measure of the subject's behavior. See also: How variables are calculated: Dependent Variables in Detail Elongation and Mobility Still Showing Missing Values After Interpolation Interpolation is only applied to missing body points to obtain valid x,y coordinates. When the subject is not detected, the subject's contour and surface area remain unknown. This is why variables such as Activity, Elongation, and Mobility still show missing values after interpolation. Screen Recording Could Not Be Started When trying to make a screen recording, you may receive an error message. This may be caused by the fact that older versions of the Noldus MediaLooks A/V filters are still installed, but the newest version was not installed. - Close EthoVision XT. - In the Windows Control Panel, choose Programs and Features, and remove old versions of Noldus MediaLooks A/V Filter. - Download the full installation ZIP file (see Install EthoVision XT), extract and browse to Drivers and tools > PreRequisites > MediaLooks. Copy Noldus Medialooks ScreenCapture 2.0 x64.msi to your EthoVision XT computer and run that file. - Follow the installation, then start EthoVision XT. Delay Between Video and Track The track is lagging behind the video or the other way round. This issue can only occur when you track live and save video. Solution: - Choose Acquisition > Edit Tracks. - Choose the trial from the list at the top. - Play the video until the subject and the track are well in view. Tip: Choose a frame when the animal walks fast so you can see exactly in which sample the nose point overlaps with the subject's nose in the video. - In the Playback Control window, click the Offset button. This button is only available when you tracked live and saved video. - In the Synchronize video window that opens, enter a number of frames (negative or positive) to correct the discrepancy between track and video. Click OK when ready. For example, enter -1 to move the video one frame backward relative to the track. Video Image Not Shown This issue can occur in computers with two graphics cards: a primary (integrated) card and a secondary card, usually more advanced and powerful than the integrated one. The issue is solved when you choose which card EthoVision XT uses. See also: The Camera Image Is Not Shown in the Arena Settings or Integrated Visualization Video Is Choppy or Does Not Play Smoothly This may occur if you play video at high playback speed such as 16x in the Integrated Visualization. The effect is worse if the secondary graphics card (GPU) which handles playback is less powerful. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Data visualization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-data-visualization Chapter: EthoVision XT Tracks and Integrated Visualization - I defined "In zone" for two adjacent zones. In the Integrated Visualization, I see that the animal is in the two zones simultaneously - I defined a free interval, and in the visualization I get an interval every other sample - I plotted a variable in the Integrated Visualization. I only get a few values on the timeline. Why? - I interpolated my data, but some variables including Elongation and Mobility still show missing values - Screen recording could not be started - There seems to be a delay between video and track - The video image is not shown - Video is choppy or does not play smooth - The points are too small (or too large) or the traces are too narrow (or too thick) - When I import UltraVox XT data, some calls are visualized as 1, others as 0.5. Why? - The Integrated Visualization shows "Not calculated" - The Data Preparation Report says "Failed" for some trials - I cannot visualize a trial - The name of the trial is not fully visible Heatmaps - A heatmap is plotted outside the arena, or merged with the heatmap of other arenas - In the Heatmaps screen the Group Mean button is not available - How can I merge heatmaps generated in different arenas? Animal Detected in Two Zones Simultaneously This happens when a Zone exit threshold has been defined that is greater than 0, and the two zones Center and Border are adjacent. In such a case, when the animal moves from Border to Center, it is at some point considered to be in Center, but if it is not yet outside the zone exit threshold of Border, it is also considered to be in Border. To prevent this, re-define the two zones in such a way that there is a gap between the two, its width being at least the same as the zone exit threshold. Free Interval Generates an Interval Every Other Sample Most probably you defined a free interval based on two values of external data or a hardware variable, for instance: - From Heart rate >= 300 to Heart rate >= 400 - From Number of pellet drops >= 1 to Number of pellet drops >= 10 When the value of the resampled variable reaches the second (higher) threshold, the interval ends and EthoVision XT finds the next sample that matches the criterion defined in From (first threshold). If the current value is higher than the first threshold, a new free interval is defined. However, if the value at the next sample is also higher than the second threshold, the interval is ended, resulting in a free interval of one sample. The search is repeated in the next samples, generating the pattern shown in the first plot. In such cases, do not use a free interval. Instead, use a state variable that is based on the original external or hardware signal. You can find the state variable in the Analysis profile. For example, for the external data Heart rate, in the Analysis profile under External data choose Heart rate state. For a hardware signal, under Hardware choose Hardware state. There you can define the range of values you are interested in. Only a Few Values Appear on the Timeline This may happen for variables which require two or more consecutive data points to be calculated. Consider the following examples: - Your data contain missing samples. If one sample is missing, the variable is not calculated for one, two or more time points. For example, Distance moved is not calculated for two time points, and Turn Angle is not calculated for three time points. - You may have applied the Minimal Distance Moved smoothing method. When using this method, if the distance between body points for time t and t+1 is lower than the Minimal Distance Moved, the body point at time t+1 is "moved" to the same coordinates as the point at time t. In this case Distance moved gets the value 0 (zero), but any variable that quantifies change in direction has no meaning here and is therefore not calculated for that sample. If many samples in your track are filtered out that way, variables like Turn Angle, Meander, and Heading only appear in short segments. Because the filter removes data points that do not represent movement, these few remaining segments are a more realistic measure of the subject's behavior. See also: How variables are calculated: Dependent Variables in Detail Elongation and Mobility Still Show Missing Values After Interpolation Interpolation is only applied to missing body points to obtain valid x,y coordinates. When the subject is not detected, the subject's contour and surface area remain unknown. This is why variables such as Activity, Elongation, and Mobility still show missing values after interpolation. Screen Recording Could Not Be Started When trying to make a screen recording, you may receive an error message. This may be caused by the fact that older versions of the Noldus MediaLooks A/V filters are still installed, but the newest version was not installed. - Close EthoVision XT. - In the Windows Control Panel, choose Programs and Features and remove old versions of Noldus MediaLooks A/V Filter. - Download the full installation ZIP file (see Install EthoVision XT), extract and browse to Drivers and tools > PreRequisites > MediaLooks. Copy Noldus Medialooks ScreenCapture 2.0 x64.msi to your EthoVision XT computer and run that file. - Follow the installation, then start EthoVision XT. Delay Between Video and Track The track is lagging behind the video or the other way around. This issue can only occur when you track live and save video. Solution: - Choose Acquisition > Edit Tracks. - Choose the trial from the list at the top. - Play the video until the subject and the track are well in view. Tip: Choose a frame when the animal walks fast so you can see exactly in which sample the nose point overlaps with the subject's nose in the video. - In the Playback Control window, click the Offset button. This button is only available when you tracked live and saved video. - In the Synchronize video window that opens, enter a number of frames (negative or positive) to correct the discrepancy between track and video. Click OK when ready. For example, enter -1 to move the video one frame backward relative to the track. Video Image Is Not Shown This issue can occur in computers with two graphics cards: a primary (integrated) card and a secondary card, usually more advanced and powerful than the integrated one. The issue is solved when you choose which card EthoVision XT uses. See also: The Camera Image Is Not Shown in the Arena Settings or Integrated Visualization Video Is Choppy or Does Not Play Smoothly This may occur if you play video at high playback speed such as 16x in the Integrated Visualization. The effect is worse if the secondary graphics card (GPU) which handles playback is less powerful. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Data visualization (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-data-visualization-continued-Bn1 Chapter: EthoVision XT Narrow (or Too Thick) Track Lines Solution: In various parts of EthoVision XT you can change the thickness of the lines and the size of the dots. - Click Show/Hide (at the top-right corner of the screen) and select Detection Features. - Adjust the Line thickness and Dot size. Note: - What you select in the Detection Settings screen are also selected in the Acquisition screen, and the other way round. - What you select in one of the following screens is also selected in the other screens: Track Editor, Track Visualization, Integrated Visualization, Manual Scoring screen. - The line thickness is also applied to the body contour in Detection Settings and Acquisition screen. It is not available in the Manual Scoring screen. Some Values Show as 0.5 This is due to the type of resampling selected in the external variable of your Analysis profile. Consider the following example. The first plot shows the original signal imported from UltraVox XT and the second plot shows the same signal after resampling. For the second call at 25.5, the time between the "1" and "0" in the original signal is so short that it fits in one sample interval. Two points in the same sample interval result in downsampling. Open the Analysis profile, and open the External data variable. See External data (resampled). - If you choose Mean for downsampling, the value A in the resampled signal will be the average of 1 and 0, that is 0.5. - If you choose Total for downsampling, the value in the resampled signal will be 1 + 0 = 1. After selecting Total, the signal is corrected. So, choosing Total should solve the issue. The Integrated Visualization Shows "Not Calculated" One or more trials are corrupt, or something went wrong with editing the tracks. See The Results Table Contains "?" in Many Cells. The Data Preparation Report Says "Failed" for Some Trials This message occurs in experiments with Deep learning based body point detection. In some cases EthoVision XT fails to review the tracks and fix subject identity swaps. For example, when the two subjects spent most of the trial time in close contact. See the note in Prepare the Data in Multi-Subject Trials. I Cannot Visualize a Trial In most cases, this occurs when a Data profile is active that does not include that trial. Make a Data profile that includes that trial and visualize the data. See Filter Tracks. The Name of the Trial Is Not Fully Visible The name of the trial on the toolbar of the Integrated Visualization screen is partially hidden. This may occur when the display is set to a high resolution. Reduce the screen resolution in Windows. Heatmap Color Smoothing Across Other Arenas Solution: In the Heatmap Settings pane, click Colors and under Smoothing select a lower value. See also: - Color smoothing Group Mean Button Not Available You are probably working with a DanioVision experiment. The Group Mean button is disabled in experiments set as DanioVision. How Can I Merge Heatmaps Generated in Different Arenas? For example, you acquired tracks in Arena 1 and Arena 3 with subjects that belong to the same treatment group, and you would like to create one heatmap based on the data of both arenas. Unfortunately, merging heatmaps from different arenas is not possible within EthoVision XT. However, with simple JavaScript code you can re-calculate the coordinates in the tracks and export them to an external application that creates heatmaps. The following describes a possible solution: - In the Arena Settings, define a Point of interest (see Draw a Point) in each arena. For example, the south-west corner of the open field. This point will be the new reference point of the coordinates, so it must represent the same physical location in all arenas. If the arenas already include a zone or point, like the shelter of PhenoTyper, and the zone has the same position and orientation in all arenas, then you do not need to define a Point of interest. - In the Analysis profile, add two JavaScript continuous variables. See JavaScript Continuous. The first variable is for recalculating the x-coordinate. Add the following text (replace "Point" with the name of your point or zone): const g_zone = "Point"; function Start() { } function Stop() { } function Process() { var pt1 = GetCenter(); var pt2 = GetPointPoi(g_zone); if (pt1) { var xc = pt1.x - pt2.x; SetOutput(xc); } else { SetOutputMissing(); } } - For the second variable, repeat the step above, this time replacing x with y. - Export the two variables (Analysis > Export > Raw Data). These contain the x,y coordinates expressed relative to the point in the arena. - Import the data in an application that creates heatmaps, such as Excel Power Maps, R, or MATLAB. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Data visualization (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-data-visualization-continued Chapter: EthoVision XT Narrow (or Too Thick) Track Lines Solution: In various parts of EthoVision XT you can change the thickness of the lines and the size of the dots. - Click Show/Hide (at the top-right corner of the screen) and select Detection Features. - Adjust the Line thickness and Dot size. Note: - What you select in the Detection Settings screen are also selected in the Acquisition screen, and the other way round. - What you select in one of the following screens is also selected in the other screens: Track Editor, Track Visualization, Integrated Visualization, Manual Scoring screen. - The line thickness is also applied to the body contour in Detection Settings and Acquisition screen. It is not available in the Manual Scoring screen. Some Values Show as 0.5 This is due to the type of resampling selected in the external variable of your Analysis profile. Consider the following example. The first plot shows the original signal imported from UltraVox XT and the second plot shows the same signal after resampling. For the second call at 25.5, the time between the 1 and 0 in the original signal is so short that it fits in one sample interval. Two points in the same sample interval result in downsampling. Open the Analysis profile and open the External data variable. See External data (resampled): - If you choose Mean for downsampling, the value in the resampled signal will be the average of 1 and 0, that is 0.5. - If you choose Total for downsampling, the value in the resampled signal will be 1 + 0 = 1. So, choosing Total should solve the issue. The Integrated Visualization Shows "Not Calculated" One or more trials are corrupt, or something went wrong with editing the tracks. See The results table contains "?" in many cells. The Data Preparation Report Says "Failed" for Some Trials This message occurs in experiments with Deep learning based body point detection. In some cases EthoVision XT fails to review the tracks and fix subject identity swaps — for example, when the two subjects spent most of the trial time in close contact. See the note in Prepare the data in multi-subject trials. I Cannot Visualize a Trial In most cases, this occurs when a Data profile is active that does not include that trial. Make a Data profile that includes that trial and visualize the data. See Filter tracks. The Name of the Trial Is Not Fully Visible The name of the trial on the toolbar of the Integrated Visualization screen is partially hidden. This may occur when the display is set to a high resolution. Reduce the screen resolution in Windows. Heatmap Color Bleeding Into Other Arenas Solution: In the Heatmap Settings pane, click Colors and under Smoothing select a lower value. See also: - Color smoothing Group Mean Button Not Available You are probably working with a DanioVision experiment. The Group Mean button is disabled in experiments set as DanioVision. How Can I Merge Heatmaps Generated in Different Arenas? For example, you acquired tracks in Arena 1 and Arena 3 with subjects that belong to the same treatment group, and you would like to create one heatmap based on the data of both arenas. Unfortunately, merging heatmaps from different arenas is not possible within EthoVision XT. However, with simple JavaScript code you can re-calculate the coordinates in the tracks and export them to an external application that creates heatmaps. The following describes a possible solution: - In the Arena Settings, define a Point of interest (see Draw a point) in each arena — for example, the south-west corner of the open field. This point will be the new reference point of the coordinates, so it must represent the same physical location in all arenas. If the arena already includes a zone or point, like the shelter of PhenoTyper, and the zone has the same position and orientation in all arenas, then you do not need to define a Point of interest. - In the Analysis profile, add two JavaScript continuous variables. See JavaScript continuous. The first variable is for recalculating the x-coordinate. Add the following text (replace Point with the name of your point or zone): const g_zone = "Point"; function Start() { } function Stop() { } function Process() { var pt1 = GetCenter(); var pt2 = GetPointPoi(g_zone); if (pt1) { var xc = pt1.x - pt2.x; SetOutput(xc); } else { SetOutputMissing(); } } - For the second variable, repeat the step above, this time replacing x with y. - Export the two variables (Analysis > Export > Raw Data). These contain the x,y coordinates expressed relative to the point in the arena. - Import the data into an application that creates heatmaps, such as Excel Power Maps, R, or MatLab. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Deep learning URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-deep-learning Chapter: EthoVision XT Issues - I see identity swaps during data acquisition - The nose and tail base points are not stable even when the contour of the subject is detected well - The results of two-subject tracking are not consistent when using the same video - The Data Preparation Report says "Failed" for some trials - A subject is labeled as Subject 1 in the first trial and Subject 2 in the second trial - The results of two-subject tracking differ depending on the graphics card (GPU) used - One of the subjects was not tracked at the start of the video I See Identity Swaps During Data Acquisition This is normal when using the Deep learning technique in two-subject tracking. The identity swaps are corrected during the Data Set Preparation process. During that process, the track segments are sorted and put together based on the visual appearance of the subjects. This procedure greatly reduces identity swaps. See Prepare the data in multi-subject trials. The Nose and Tail Base Points Are Not Stable Even When the Contour of the Subject Is Detected Well - With one subject per arena: In the Detection Settings, click the Define button, then Automated. - With one or two subjects per arena: check that there is enough contrast between subjects and background. - Furthermore, objects in the arena may reduce the accuracy of the position of the nose point. - See also Deep learning: Requirements The Results of Two-Subject Tracking Are Not Consistent When Using the Same Video This occurs because the individual recognition algorithm is not entirely deterministic. Probability plays a role in determining whether an animal in a certain video frame is labeled as Subject 1 or Subject 2. As a result, the statistics may differ between two trials, even when using the same video and tracking settings (Trial Control Settings, Arena Settings and Detection Settings). - Mirror labeling. The first thing you may notice is that, when you acquire two trials from the same video, one individual (say that with the tail marks) is labeled as Subject 1 in trial 1 (red dot; left), whilst as Subject 2 in trial 2 (green dot; right). Conversely, its partner is labeled as Subject 2 in trial 1, and as Subject 1 in trial 2. Thus, the second trial is a sort of mirror image of the first one. If you want to keep consistency of labeling, for example to have the resident individual of a resident-intruder pair of mice always labeled as Subject 1, swap the subjects in the entire trial (see below). - Consistency of ID assignment. Even when the same individual is labeled as Subject 1 in both trials, there is a small chance that the results are not 100% consistent. Within short segments of the tracks, the identity labels may differ: for example, the marked mouse is labeled as Subject 1 in trial 1, and as Subject 2 in trial 2. Such segments last a few seconds and usually occur during situations of body contact. According to tests carried out on videos provided by users, the probability that an individual at any time point in the video is labeled the same way in both trials, after correcting for the mirror labeling (see above), is 99.6% (range 83.5 to 99.9, n=9). Low values occurred in videos where the animals were in contact most of the time, or videos of low resolution and with more noise. In the Track Editor, review the video to evaluate the extent to which identity swaps occur. If that is not acceptable, swap the subjects where necessary, so that you get fully consistent results. - Consistency of general statistics. The non-deterministic mechanisms of the multi-subject tracker based on deep learning also cause the statistics to be not 100% repeatable when tracking multiple times from the same video. When analyzing the Total Distance moved in trials acquired from the same video, the coefficient of variation is 0.4% (range 0.1 - 2.5). In practice, a video where an animal walks 100 meters could result in some 40 cm difference in distance moved between trials. Higher-quality videos produce variability of the results lower than 1% of the mean. If this variability is not acceptable, open the Track Editor and swap the subjects where necessary. See also - Prepare the data in multi-subject trials - Deep learning: Requirements A Subject Is Labeled as Subject 1 in the First Trial and Subject 2 in the Second Trial You may want to keep the identity labels consistent. For example, to assign the label Subject 1 always to the resident individual, or the individual marked on the tail. To make identity labeling consistent, swap the subjects for the entire trial. - Open the Track Editor (Acquisition > Edit Tracks). - Select the trial where you want to swap the subjects. - Click the header for the first subject (default: Subject 1) in the Sample List. You may have replaced Subject 1 and Subject 2 by other role names in the Experiment Settings; see Subjects per arena. - Press Shift, and click the header of the second subject (default: Subject 2). - As a result, the entire sample list is highlighted in green. See also Select samples manually. - Click the Swap subjects button. See also - Swap subjects - Select samples manually The Results of Two-Subject Tracking Differ Depending on the Graphics Card (GPU) Used The results of two-subject tracking could be slightly different based on which GPU was installed, everything else being equal (e.g., computer, arena settings, etc.). When the neural network model is not highly certain about the pose of the subject, small differences in handling of numbers with decimals could lead to noticeable differences, for example in the position of the nose at a certain sample time. Another reason could be that precision handling could differ between NVIDIA driver versions. Tests carried out with supported GPUs show that the maximal difference in distance moved between GPUs is in the order of 0.1%. One of the Subjects Was Not Tracked at the Start of the Video When you open the Integrated Visualization, there is one track in each arena, while you expect two tracks. One of the two subjects apparently was not detected. This usually occurs in the first few seconds of the video. In reality both subjects were detected, but their tracks now overlap. You can check this by de-selecting one of the subjects in the Show/Hide pane. To prevent this from happening: - Create new Detection Settings and select the maximal sample rate, i.e. at least 25 samples per second, then re-do the trial. See Sample rate. - Make sure that the two animals are released at the same time, or one shortly after the other (e.g. less than 30 seconds). The video should not contain a long segment with just one animal in the arena. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: External data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-external-data Chapter: EthoVision XT Issues - I cannot import external data, or I get an error message "a gap was detected in the raw data" - I imported the external data in EthoVision XT, but the values are missing - The external signals look "stretched", or "compressed" over the time line Cannot Import External Data or Error "A Gap Was Detected in the Raw Data" Check carefully the prerequisites for importing external data. See Import External Data: General Information. TIP Open one of your data files with the Notepad, and check whether there are irregularities in the file. Move the cursor between the numbers. If there are blank spaces, not tabs between them, then in the import profile you must specify Space under Select Data Delimiters. See also: - Create a New Custom Import Profile - Edit a Custom Import Profile Imported External Data Values Are Missing - Case: In the Integrated Visualization, you see the original signal, but not the downsampled signal as defined in the Analysis Profile: In most cases this could be due to the fact that the original signal is not in sync with the track data. Check the synchronization and re-import the files, or change the set of the external data by editing the start/end time. See Synchronize Data Manually After Import and Synchronize Data Automatically. - Case: The external data, both original and downsampled, are absent. When trying to re-synchronize the data, the Start Date and Time and the End Date and Time are identical. This occurs when the original imported data (files with extension *.pbi) are not available, for example when they are stored on an external device. Make sure all files (experiment, and external data) are stored on the local drive. External Signals Look "Stretched" or "Compressed" Over the Time Line This may occur if one of the TCAP pulse trains, which encode the time used for alignment, is truncated. EthoVision XT calculates the average set using 10 values of time, and if one or more of the train pulses are incorrect, the data may be out of sync, or their form may look compressed or stretched. In this example the last pulse train is shorter than the others: - Remove the imported data from the trial. - Open the original data (text) file and remove the last pulse train. - Re-import the edited data file. Issues - When I select a sample in the Sample List, the corresponding point in the track is not highlighted - I try to move a point, but nothing happens. The software moves a point at an earlier time stamp - When I select a group of samples of one subject, samples of another subject are also selected - I no longer see the Track Editor toolbar - When I click to jump to another time, video update takes very long time Selected Sample in Sample List Does Not Highlight Corresponding Point in Track When double-clicking a row in the Sample List, the corresponding point stays as a filled symbol, while it should be highlighted. This occurs when the trials were recorded with EthoVision XT 17 or an earlier version. If that is the case, and provided that you still have the associated video files, clear the trials and re-do them using the same video and settings. See Redo a Trial. Software Moves a Point at an Earlier Time Stamp You may have noted that when you click the point you want to move, the cursor on the Sample List (indicated with a green row) jumps to another time stamp. In the video image, the point is no longer highlighted. This happens because multiple samples overlap in the small portion of the image where you click. It is more likely to happen when you visualize the last few seconds of a track. Solution: In the Track Plot Settings pane on the right, under Filter select Last and enter a value next to seconds. This way, only the current sample — that is, the one highlighted in blue in the Samples List — is selected. TIP To select the nose point, hover with the mouse until the tip of the mouse cursor is near the tip of the triangle. To select the tail-base point, hover the mouse next to the lower-right corner of the square. When the mouse cursor is near the point, a four-headed cross symbol appears. Drag the point to the new position. If the actions outlined above do not solve the issue, it may be that the trials were recorded with EthoVision XT 17 or an earlier version. If that is the case, and provided that you still have the associated video files, clear the trials and re-do them using the same video and settings. See Redo a Trial. Selecting a Group of Samples Also Selects Samples of Another Subject This occurs when you draw a box to select a group of samples, and the Filter option Last ... seconds is set to a value greater than zero. In that case EthoVision XT also selects the samples of other subjects that lie within the box, and have a time stamp within the interval set in the Last ... seconds option. This makes it likely that you move or delete points of other subjects unintentionally. Solution: Set the filter to Last 0 seconds. If the problem still occurs it is because the body points of two subjects are very close to each other, and those subjects appear in the Samples List. To avoid this issue, de-select the subject you are not editing from the Samples List. Track Editor Toolbar Is No Longer Visible - Close EthoVision XT. - In the experiment folder, locate two files with extensions .POS and .POB respectively. Delete both files. - Start EthoVision XT and open the experiment. Video Update Takes Very Long Time When Jumping to Another Time Do one or more of the following until the problem is solved: - From the Apps screen, under Windows System, click Run, type dxdiag and click OK. After the diagnostic procedure has been completed, click Exit. - Restart the PC and have the computer enter hibernation mode. Then resume the PC and start EthoVision XT. - Upgrade the video graphics card drivers. - Change the video graphics card. Contact Noldus Information Technology for information. - See also System Requirements: Hardware. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: General URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-general Chapter: EthoVision XT Issues - Some items in the EthoVision XT screen are missing - EthoVision XT does not start when I double-click the icon on the desktop - I cannot open an experiment - EthoVision XT crashes after opening an experiment - EthoVision XT hangs after creating a new experiment - I cannot create new experiments, or acquire data with EthoVision XT - Video and data seem out of sync - When I create a new DanioVision experiment with a template made with a previous EthoVision XT version, my trial control rule does not work - I get a message that a dll file is missing - I cannot work remotely with EthoVision XT - I get a message that the backup file cannot be created - After selecting Deep Learning in the Experiment Settings, the software becomes unresponsive - EthoVision XT crashes after opening a GLP log - The text and boxes look very small (Windows 11) Some Items in the EthoVision XT Screen Are Missing Check that the item is selected in the Show/Hide menu at the top-right corner of the EthoVision XT screen. Menu items, items in the Experiment Explorer, icons, etc. may become unavailable due to memory limitations. Use the data selection functions to reduce the amount of data to analyze. EthoVision XT Does Not Start When Double-Clicking the Icon on the Desktop This means that an instance of EthoVision XT is running in the background. This could also be due to removal of the dongle while EthoVision XT was running. Do one of the following: - Press Ctrl+Alt+Del and then click Task Manager. Click the Processes tab, select each instance of EthoVision XT and click End Task. - Restart the computer and start EthoVision XT. I Cannot Open an Experiment Experiment (General) - This occurs when you try to open an experiment (File > Open) that is saved in a newer EthoVision XT version. Start that version and open the experiment. - Another reason could be that the experiment contains files whose names include non-ASCII or special characters. Please use standard ASCII characters when creating backups and saving copies of experiments (Save As). - It may be that the experiment repository file (*.evxt) is corrupt. First, delete that file (though not permanently — just leave it in the recycle bin). Locate the file Restore.btn and rename this file as the file you have just deleted, including the extension *.evxt. Next, in EthoVision XT, open that repository file (*.evxt). If none of the actions above solve the issue, contact Noldus Support. Experiment from a Backup - You get a message like Backup [name of backup file] could not be restored. Probably the backup file is stored on a location for which you do not have write rights, such as a DVD or a network drive. Copy the backup to a location where you have full rights, and restore the experiment from that file. - You get a message like [name of backup file] is not a valid backup archive. (ID 10060). Probably the backup is still in a zip folder after downloading (for example, My PC > Downloads > [folder name].zip). Extract the files to another folder. The backup should be outside zip folders. Experiment from My Documents or Windows Explorer Make sure that My Documents is a mapped network drive. If My Documents is on a non-mapped network drive (the file path shows no drive letter but \\computer\), you can open the experiment there by double-clicking its name (*.evxt), but it is not possible to open it by selecting File > Open. EthoVision XT Crashes After Opening an Experiment This may occur if you open an EthoVision XT experiment while UltraVox XT 3 is open on the same PC. Always follow this sequence of actions when working with UltraVox XT 3 and EthoVision XT: Close UltraVox XT > Start EthoVision XT > Open the EthoVision XT experiment > Start UltraVox XT. This issue does not occur if you use UltraVox XT 4. EthoVision XT Hangs After Creating a New Experiment This may occur when the USB-IO box is connected to a USB port on a docking station or a USB hub. Some docks and hubs interfere with the signal between EthoVision and the hardware connected over USB. Therefore, always connect the USB-IO box and other USB peripherals directly to the computer instead of through USB hubs or docking stations. - If you use a laptop and encounter issues, connect the USB-IO box on the other side of the machine. - If you use a desktop and encounter issues, connect the USB-IO box to the back side of the machine. Video and Data Seem Out of Sync You can test a video source on timing. This can determine how accurate a camera is in combination with EthoVision XT and can in some cases explain synchronization problems. To do so, you can use the TestVideo utility software. Browse to my.noldus.com, log in or register, then select Downloads > EthoVision XT > Drivers and Tools and download TestVideo. Copy the file TestVideo [version number].exe to a location on your EthoVision XT computer and run it. IMPORTANT: Only install and operate TestVideo when requested by Noldus Support. Trial Control Rule Does Not Work in a New DanioVision Experiment This happens if you change the Trial Control Hardware Settings in the Experiment Settings. We recommend creating a new experiment in EthoVision XT 19 and using this as a template for new ones. I Get a Message That a DLL File Is Missing When starting EthoVision, the message appears: The program can't start because api-ms-win-crt-heap-I1-1-0.dll is missing from your computer. To solve the issue, perform a Windows Update. I Cannot Work Remotely with EthoVision XT You cannot control EthoVision XT from another computer through the Remote Desktop app. See Work with EthoVision XT Remotely. See also Use a Remote Control to Start and Stop Acquisition. I Get a Message That the Backup File Cannot Be Created The backup is created anyway. You can restore the backup as usual. The issue occurs when some files in the experiment folder are still open — for example, one or more Excel export files. Close all files before creating a backup of an experiment. Software Becomes Unresponsive After Selecting Deep Learning The first time the Deep Learning function is selected, a model is created for the specific GPU installed on that computer. For some GPUs this process takes some time. During this time EthoVision will be unresponsive and may appear to have crashed. If this is the case, wait until EthoVision becomes responsive again. If the software no longer responds, contact Noldus Support. The Text and Boxes in EthoVision XT Look Very Small (Windows 11) This occurs sometimes in Windows 11 at very high screen resolutions. Do the following: - Right-click the shortcut of EthoVision XT on the desktop and select Properties. - Click the Compatibility tab. - Click Change High DPI Settings. - Under High DPI Scaling Override, check the option Override High DPI Scaling Behavior and select System or System (Enhanced) from the list below. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Import trials URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-import-trials Chapter: EthoVision XT Hardware This occurs when the Device ID of the hardware devices declared in the experiment settings (Device Configuration window) differ between the experiments. Or, if the names are the same but the devices ID have been mapped to different arenas. For example, when Lickometer 1 was assigned to Arena 1 in the current experiment, and in Arena 2 in the experiment you want to import the trials from. Unfortunately there is no way to re-assign Devices ID post-acquisition. Always make sure to use the same names and mapping criteria when creating new experiments that you want to merge. Troubleshooting: Quality Assurance (GLP) Issues - I cannot start EthoVision XT (GLP restriction) - I cannot create new experiments, or acquire data with EthoVision XT - EthoVision XT crashes after opening a GLP log I Cannot Start EthoVision XT (GLP Restriction) A message appears: You are not registered as a GLP user, so you cannot use EthoVision XT. Please ask a EthoVision XT user manager for help. This issue could be caused by the fact that the user that has started EthoVision XT is not known as a GLP user. - Restart the computer and ask the system administrator or someone with an administrator account to log in. - Start EthoVision XT. Add users as GLP users. Make sure to add all the persons that are going to use EthoVision XT. See EthoVision XT user management. - The administrator logs out. - Log in with your account. - Start EthoVision XT. Alternatively, ask your system administrator to add your user account to the administrator group. I Cannot Create New Experiments or Acquire Data with EthoVision XT The File > New menu items and the Acquisition menu are disabled. When using the Quality Assurance module, it seems that users have been removed as authorized GLP users. This may occur for two reasons: - The hardware key is not plugged in. - You reinstalled or repaired the application. In the latter case the Quality Assurance user list is deleted. Ask your Quality Assurance user manager to add your user ID and give you the appropriate rights. EthoVision XT Crashes After Opening a GLP Log This occurs when using Quality Assurance experiments, after you click within the GLP log or when you click the Close button. Do the following: - Open the Windows Notepad and enter the following text: Windows Registry Editor Version 5.00 [HKEY_CURRENT_USER\SOFTWARE\Microsoft\Internet Explorer\Main\FeatureControl\FEATURE_USE_LEGACY_JSCRIPT] "EthoVision.exe"=dword:00000001 - Save the file as [file name].reg on the EthoVision XT computer. - Run the file. - Click OK in the message that appears. TIP: Files with extension *.reg are blocked by Windows and mail servers. Do not run REG files stored on network drives. If you need to send a REG file by email, enclose it in a ZIP file. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Import trials URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-import-trials-MF4 Chapter: EthoVision XT Hardware This occurs when the Device ID of the hardware devices declared in the experiment settings (Device Configuration window) differ between the experiments. Or, if the names are the same but the device IDs have been mapped to different arenas. For example, when Lickometer 1 was assigned to Arena 1 in the current experiment, and in Arena 2 in the experiment you want to import the trials from. Unfortunately there is no way to re-assign Device IDs post-acquisition. Always make sure to use the same names and mapping criteria when creating new experiments that you want to merge. Troubleshooting: Quality Assurance (GLP) Issues - I cannot start EthoVision XT (GLP restriction) - I cannot create new experiments, or acquire data with EthoVision XT - EthoVision XT crashes after opening a GLP log I Cannot Start EthoVision XT (GLP Restriction) A message appears: You are not registered as a GLP user, so you cannot use EthoVision XT. Please ask a EthoVision XT user manager for help. This issue could be caused by the fact that the user that has started EthoVision XT is not known as a GLP user. - Restart the computer and ask the system administrator or someone with an administrator account to log in. - Start EthoVision XT. Add users as GLP users. Make sure to add all the persons that are going to use EthoVision XT. See EthoVision XT User Management. - The administrator logs out. - Log in with your account. - Start EthoVision XT. Alternatively, ask your system administrator to add your user account to the administrator group. I Cannot Create New Experiments or Acquire Data with EthoVision XT The File > New menu items and the Acquisition menu are disabled. When using the Quality Assurance module, it seems that users have been removed as authorized GLP users. This may occur for two reasons: - The hardware key is not plugged in. - You reinstalled or repaired the application. In the latter case the Quality Assurance user list is deleted. Ask your Quality Assurance user manager to add your user ID and give you the appropriate rights. EthoVision XT Crashes After Opening a GLP Log This occurs when using Quality Assurance experiments, after you click within the GLP log or when you click the Close button. Do the following: - Open Windows Notepad and enter the following text: Windows Registry Editor Version 5.00 [HKEY_CURRENT_USER\SOFTWARE\Microsoft\Internet Explorer\Main\FeatureControl\FEATURE_USE_LEGACY_JSCRIPT] "EthoVision.exe"=dword:00000001 - Save the file as [file name].reg on the EthoVision XT computer. - Run the file. - Click OK in the message that appears. Tip: Files with extension *.reg are blocked by Windows and mail servers. Do not run REG files stored on network drives. If you need to send a REG file by email, enclose it in a ZIP file. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Installation and license URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-installation-and-license Chapter: EthoVision XT Issues: Installation - Error message (ID 10020) - Installation stops halfway - Blue-screen crash during installation of Euresys Multicam - The hardware key does not light up - When I start EthoVision XT, I get the message: No license key found - Installation of EthoVision XT fails, likely due to an error during installation of the Basler camera drivers - I have realized that I installed the wrong camera driver software. What can I do? Issues: License - My EthoVision XT license has expired. What should I do? - I am trying to upgrade my license, but the upgrade key is not being accepted - I cannot start EthoVision XT with a floating license - I purchased an add-on module but I cannot use it - I purchased an add-on module. How do I update my license? - I entered a license key but an error message shows a different one - I need to create a Firewall rule to access the Noldus license server. Which port do I need to access? - I cannot deactivate a license. The menu item Deactivate License is greyed out - EthoVision XT is in Analysis mode, but there is no way to work with a full license - Message "Activation not complete" - Message "License already activated..." Error Message (ID 10020) This usually happens when you install EthoVision XT after logging in with a guest account, or an account with insufficient rights. In those cases EthoVision XT may not use various folders on the hard drive. Ask your system administrator to create a user account with more (local) rights than guest accounts, or ask the administrator to log in and install EthoVision XT. Installation Stops Halfway There may be a few reasons why installation fails. The log file may provide clues about the actual cause. To get this file, see The Log File for Technical Support. Do the following: - Open the Windows Control Panel, and under Programs and Features check that an item named Sentinel Runtime is listed. If that is the case, remove it. Next, restart the PC, and install EthoVision XT (choose Modify on the installation screen). - The issue could also be caused by the Basler Installer which tries to install its certificates on a Windows 10 version LTSC. If the procedure above does not solve the problem, you may first need to remove the root certificates from your PC, then install the Basler driver, then install EthoVision XT. You can remove root certificates with the app mmc.exe in Windows. Contact Noldus Support for more information. - Open the Windows Control Panel, and under Programs and Features check whether software like Microsoft Visual C++ Redistributable (version 14) is present. If that is the case, uninstall it. We know that version 14, not earlier, of this software has caused a couple of issues during installation of EthoVision XT. Next, install EthoVision XT. After that, you may want to re-install Visual C++ Redistributable software. Blue-Screen Crash During Installation of Euresys Multicam For the Dell Precision 3650 Solution: Disable the Secure Boot option in the PC's BIOS. - Start up the PC. Press the F12 key and once in the BIOS Setup menu, select Boot Configuration. - Set the Enable Secure Boot option to Disabled. - Save and exit the BIOS Setup menu. NOTE: There may be different ways to open the BIOS Setup menu in different computers. In Windows 11, you can press F2 while your PC is booting. Or, if the PC is running, hold the Shift key while selecting Restart. Go to Troubleshoot > Advanced Options > UEFI Firmware Settings, then select Restart. The BIOS Setup opens. For the Dell Precision 3640 A blue-screen crash in the Dell 3640 has been reported after the update of the BIOS firmware (the firmware update is nowadays integrated in the Windows Update routine). The crash is triggered with firmware version 1.4.3 or later. It is possible to roll back to an earlier version of the firmware. - Start up the PC. Press the F12 key and once in the BIOS menu, select Maintenance > BIOS Downgrade. - Select the option Allow BIOS Downgrade. - Save and exit the BIOS. Note that firmware version 1.3.2 is tested OK. If you need this version, consult the Dell support website or contact Noldus Support. Sentinel Runtime Is Already Installed - Cancel installation of EthoVision XT. - Open the Windows Control Panel and choose Programs and Features. Look for Sentinel Runtime and uninstall it. - If necessary, download the latest version of the Sentinel Hasp Driver from my.noldus.com. Copy the setup file to your PC and run it. - Re-install EthoVision XT. The Hardware Key Does Not Light Up - Close EthoVision XT and remove the hardware key. - Run the installation file of EthoVision XT. Select Custom, then Repair. See Install EthoVision XT. - Insert the hardware key into the computer and start EthoVision XT. The hardware key should now light up. No License Key Found - If you work with a hardware license key, check that the hardware key is plugged in and its red LED is on (see above). NOTE: When the hardware key is not plugged in, you can open an existing experiment and analyze data already collected. However, you cannot acquire more data. See EthoVision XT in Analysis Mode. - See also Activate Your EthoVision XT License. Installation Fails Due to an Error During Installation of the Basler Camera Drivers Based on the Basler error log file, installation stops because the system fails to register a Basler .ax file. Solution: - Install EthoVision XT while keeping all Basler camera driver options de-selected. See Install EthoVision XT. - Browse to my.noldus.com, log in or register, then select Downloads > EthoVision XT > Drivers and Tools and download Basler Pylon Camera Driver to your PC. Run this file. During installation, choose the Custom option and de-select DirectShow Support. TIP: Remember to also select pylon Viewer and the option that applies to your camera (USB vs. GigE). - Continue with installation. - At the end of installation, double-click the .exe file again and choose Modify the Current Installation. Choose Custom, and this time keep DirectShow Support selected. I Installed the Wrong Camera Driver Software. What Can I Do? - Run the file EthoVision XT - Setup - [version number].exe (see Install EthoVision XT) and select Modify. Select the correct driver and continue installation. - If the action above does not help, open the Windows Control Panel and under Programs and Features select the driver software (for example, for a Basler camera there is an item named Basler Pylon), and select Uninstall. Next, run the setup file (step above) and select the correct driver. See also Install the Driver Software for the Digital Cameras. Upgrade Key Is Not Being Accepted This may occur when your hardware key (dongle) specifies an EthoVision XT version that is later than that specified in the Upgrade Key you have received. For example, you have a license number EV180-... (this number can be viewed in Help > About EthoVision XT > License Info), and you are trying to enter an Upgrade Key for a (probably old) license number that starts with EV150 or similar. Another possible cause of the error is that the version of the Upgrade Key is not the same as the EthoVision XT version. Please contact Noldus to receive a matching Upgrade Key. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Installation and license (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-installation-and-license-continued Chapter: EthoVision XT My EthoVision XT License Has Expired. What Should I Do? - Contact Noldus to purchase a new license. See Noldus Support. - Start EthoVision XT. - A message says No License key found. Choose Activate software license key. - Choose either Floating or Computer-locked depending on how you want to use the software. See Types of EthoVision XT license. - Click OK and enter the new software activation key that you received from Noldus. See Activate your EthoVision XT license. I Purchased an Add-On Module but I Cannot Use It Choose Help > About EthoVision XT > License info to view which modules are enabled on your EthoVision XT system. See Upgrade EthoVision XT. If necessary, contact Noldus for help. I Purchased an Add-On Module. How Do I Update My License? This depends on whether you have a software license or a license stored on the USB hardware key. See Add new modules to your license. TIP To know which modules are included currently in your license, choose Help > About EthoVision XT > License Info. See also Modules of EthoVision XT. I Cannot Start EthoVision XT with a Floating License This occurs when a floating license was not deactivated on one of the other computers before starting EthoVision XT on that computer. This could happen for example when EthoVision XT is closed on a computer that has a floating license but currently no internet connection. Restart EthoVision XT on that computer and make sure that the computer is connected to the internet, then close EthoVision XT. Then start EthoVision XT on the computer you want to work with. NOTE With a floating license, all EthoVision XT computers must have an internet connection. See Types of EthoVision XT license. However, you can work offline with EthoVision XT under a floating license for a maximum of 90 days. After that, you must re-connect the EthoVision XT PC to the internet in order to continue to work with the software. See also Software license - offline. I Entered a License Key but an Error Message Shows a Different One Contact Noldus for support. Contact the Noldus Support. Which Port Do I Need to Access the Server? You need port 443. The Deactivate License Option Is Greyed Out Close the experiment, then select Help > Deactivate license. Working with a Full License After starting EthoVision XT, you can work in Analysis mode, but the dialog that offers to work with the full license does not show up. - Close the experiment (if open). - Choose Help > Deactivate License. - Click Continue. EthoVision XT will now close. - Insert the hardware key in the PC or have the license key ready. - Start EthoVision XT and choose how to activate the license. Message "Activation Not Complete" This may be caused by the following reasons: - A wrong or expired license key was entered in the previous step of the activation procedure. Click Back, and enter the license activation key that you received from Noldus. - The computer may temporarily be disconnected from the internet. Check the internet connection and repeat the license activation procedure. - The license may have been revoked, or is expired. Please contact your Noldus representative to purchase a new license. Message "License Already Activated..." After trying to activate a license, EthoVision XT (or the Noldus page displayed on your smartphone) shows a message: The license [license number] has already been activated on a system called [computer name]. The license that you are trying to activate is still active on another computer. - Deactivate the license on the first computer. See Deactivate an EthoVision XT license. - Activate the license on the second computer. See Activate your EthoVision XT license. It is possible that EthoVision XT was removed from the first computer, but the license is still active there. Please re-install EthoVision XT in order to deactivate the license on the first computer. See Install EthoVision XT. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: pylon camera software URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-pylon-camera-software Chapter: EthoVision XT Issues - Pylon IP Configurator is not seeing a camera - Pylon IP Configurator can see my camera but the Status column says Not Reachable - I cannot save my camera settings in pylon Viewer - No camera image in pylon Viewer This section applies to the applications pylon Viewer and pylon IP Configurator for Basler cameras. NOTE: These two applications are installed automatically when you select to install the drivers for the Basler GigE camera or the Basler USB 3.0 camera. See Install EthoVision XT. Pylon IP Configurator Is Not Seeing a Camera - Make sure that the camera is connected. See Connect the GigE Camera to the PC. - If you use a Power injector or PoE switch, make sure that it is powered. - Restart the PC (if you did not after installing the camera's driver). - If the issue persists, check the Ethernet board that is connected to the camera. See the following: - Install the Driver Software for the Digital Cameras - Settings of the Ethernet Board NOTE: An issue has been reported for Dell 3540 running Windows 10 Pro, when using a 4-port AdLink Ethernet interface board. All ports in the Device Manager show an exclamation mark (!) and the cameras are not detected by pylon IP Configurator. The problem appears to be caused by the Fast Startup feature in Windows. This feature is disabled by default by Noldus. To enable Fast Startup on Windows 10 systems, navigate to Settings > System > Power & Sleep > Additional Power Settings > Choose What the Power Buttons Do and click Change the Settings That Are Currently Unavailable. Select Turn On Fast Startup and save the changes. Status Column Says Not Reachable This may be caused by the IP address of the network card not matching that of the camera. For example, the network card should be 192.168.1.51 and the camera should be 192.168.1.101; that is, the first three numbers must be the same and the fourth number must be different. Also verify that the subnet mask is 255.255.255.0. See Install GigE Cameras. I Cannot Save My Camera Settings in Pylon Viewer - In pylon Viewer, click the Stop button on the toolbar. - From the Window menu, select All Features. - In the Features panel, locate Configuration Sets. You can now save the current settings. See Save the Camera Settings. No Camera Image in Pylon Viewer - Check the issues above about IP Configurator. - Check that each Ethernet board has different networks in their IP addresses. For example, 192.168.x.x for board 1 and 192.168.y.x for board 2. - If the video screen is completely black, it may be that the camera has an IR-block filter and the light in the test room contains little infrared, or that the aperture of the lens is minimized. - Swap cables, cameras, etc. to exclude the possibility that hardware is faulty. - Disable firewall and anti-virus software. - Check the Ethernet board settings and driver: - Settings of the Ethernet Board - Make sure that the Ethernet board allows data transfer of 1 Gigabit/s. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-statistics Chapter: EthoVision XT Issues - A variable does not appear in my results - I get unrealistic values of path shape and direction - A subject shows rotational behavior. However, when I look at the stats of Angular velocity or Turn Angle, the values are lower than for a subject which does not show rotation. Why? - I get different results in two EthoVision XT versions - I get different results when I analyze the same video twice - I want to validate angle variables like Heading, Head direction, and Heading to Point, but the average value I calculate in Excel does not match the results in EthoVision XT - The total distance moved does not always match the mean velocity - I want to analyze Activity to detect freezing in rodents. However, when I plot the data I get lots of Inactive states - I get wrong statistics of manually-scored behaviors - The statistics result table contains many empty rows or columns - The statistics result table contains two or more values of a dependent variable for the same trial, arena or subject - The statistics result table does not appear - The Data Preparation Report says "Failed" for some trials - The percentage of "Subject not found" does not match the time in the arena - The results table contains "?" in many cells - How do I know the time between the starting point of a video and the time that I started tracking? - I get more zone entries than expected - The Analysis profile does not list Mobility and Head direction A Variable Does Not Appear in My Results One or more of the following may be the case: - The experiment is not set to Nose-point, center-point and tail-base point tracking. - You do not have the add-on module that allows to calculate those variables. - For social behavior variables: double-click a variable in the Analysis Profile and define Receivers there. - Your experiment is set to Live Mouse Tracker. This type of experiment does not contain the raw data needed to calculate variables like Mobility, Head direction and Body elongation. See Also - Dependent Variables in Detail: Social I Get Unrealistic Values of Path Shape and Direction Variables like Meander may have very high values (e.g. 5000 º/min) despite the fact that the animal moves approximately on a straight line. High values of the variable occur when body points for consecutive samples (that is, at times t-1, t, t+1...) lie near each other. For example, when the sample rate is high, and the subject does not move much, the distance moved between consecutive samples is very small, consequently Meander (which is by definition Turn angle divided by Distance moved) will be very high. In this case it is useful to filter data using the Minimal Distance Moved method. To choose the threshold, plot the data of Distance moved together with your variable. For example, if you see that values of Distance moved around 0.05 produce unrealistic values of the variable, set Minimal Distance Moved = 0.1. If this does not fix the problem, try re-tracking from the same video, but with a lower sample rate. See Also - Dependent Variables in Detail > Path - The Minimal Distance Moved Smoothing Method Angular Velocity Values Are Lower for a Rotating Subject Than a Non-Rotating Subject Angular velocity does not necessarily correlate with rotations. If the animal turns slowly, its Angular velocity is low. Furthermore, when the subject sits still, but its body point oscillates in all directions due to random noise, high values of Turn angle (and therefore Angular velocity) will appear. To minimize this effect, either use the Minimal Distance Moved filter (see the previous issue), or nest over Movement to only select the data points when the animal is Moving. Then, calculate your variables. The figure below compares Angular velocity calculated for when the animal moves significantly, with when it does not move. To quantify rotational behavior, also use Rotation. I Get Different Results in Two EthoVision XT Versions The possible causes of this issue are: - You specified a sample rate that is lower than the maximum sample rate; in that case EthoVision XT analyzes every nth video frame (where n is the video frame rate divided by your sample rate; for example if you choose a sample rate of 12.5 for a video file of 25 frames per second, then n = 2, that is, the software analyzes every two frames). In some previous versions, EthoVision XT always took the second frame in the video and every nth frame thereafter. The results like distance moved may be slightly different, but that is very unlikely to affect the outcome of an experiment. - EthoVision XT 17.5 and later play video using the GPU by default. In contrast, EthoVision XT 17.0 and earlier used the CPU. This may result in slight differences in the appearance of the video image, for example, video looking brighter, which in turn could affect detection and the tracking results. You have two options: - Revert to playback with the CPU in the Preferences for video settings. - Keep using the GPU and adjust the detection settings in the new version so they match the detection in the old version as much as possible. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Statistics (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-statistics-continued-NnF Chapter: EthoVision XT The Statistics Result Table Does Not Appear Problem: The results table in Trial Statistics or Group Statistics and Charts shows no headers and no results. Explanation/Solution: This could happen for example when: - The experiment has no data yet. - The data have been completely filtered out in the Data Profile. Please check your data selection. - For Group Statistics: An independent variable was inserted in the table Layout, and at least one of those groups contains multiple values of that variable. Example: In the Data Profile, you group tracks in two groups, Treated and Control. In the Group Statistics and Charts, you insert the independent variable Rat ID in the Layout, but each group contains many values of this variable (one per subject tested). Therefore, the grouped results cannot be listed properly. To solve this, either remove the variable from the Layout (Modify the layout of the results table), or in the Data Profile group your trials in a different way. See also Trial Statistics Result. The Data Preparation Report Says "Failed" for Some Trials This message occurs in experiments with Deep Learning based body point detection. In some cases EthoVision XT fails to review the tracks and fix subject identity swaps. For example, when the two subjects spent most of the trial time in close contact, or the video file was too short to obtain a reliable trained neural network. See a note in Prepare the Data in Multi-Subject Trials. Time in the Arena Problem: "Subject not found" gives one value (e.g. 5%) and the total time the animal is in the arena (Cumulative duration% in the Arena) is 96%, while I expect them to be complementary. Explanation/Solution: In the following example there is a gap of 25 frames of "subject not found". With 25 frames per second (so 0.04 s per frame), that comes down to a missed sample time of 1 second, which may be for example 0.5% of the total time. That percentage you see in the Trial List. However, when the subject goes missing, EthoVision XT assumes that it is still in the arena in the next 3 frames, before considering it "not in the arena". In this example, the gap is not 25 frames but 25-3 = 22 frames. Therefore, the total time "not in the arena" is 22*0.04 s = 0.88 s instead of 1 s. Thus, Subject Not Found and Cumulative Duration% in Arena do not always match. The Results Table Contains "?" in Many Cells This could indicate that one or more trials are corrupt. However, it is also possible that you edited the tracks and something went wrong with editing. - Click Calculate and take note of a trial that gives the "?" results. - Go to the Track Editor, select the trial and then click Undo All. Note that this action erases all your edits in that trial. - Re-do editing when necessary. - Run analysis. The Time That I Started Tracking This applies to cases when you positioned the video later than its starting point and then clicked Start Trial. - Export the raw data (choose Analysis > Export > Raw Data). - Open the exported file and look at the difference between the value next to Start Time and the value next to Video Start Time. I Get More Zone Entries Than Expected This applies to In Zone variables where the number of entries is higher than expected. This could occur for different reasons: - A common issue is that the center point of the subject moves back and forth around the boundary between zones when the animal moves just on that spot. This overestimates the number of true zone entries. To avoid this, use the Zone Exit Threshold in the In Zone dependent variable settings, or use all three body points to score a zone entry. See In Zone. - Another reason for an overestimate of zone entries is that the center point is no longer detected in a zone, although the subject is still found. Consider for example a zero maze where the open and closed zones do not cover the arena completely. The region of the arena outside the zones means that when the center point is detected there, a zone exit is scored. A new zone entry is scored when the center point is found in the zone again, resulting in a train of repeated zone entries. To solve this issue, re-draw the zones in such a way that they overlap the entire region of interest within the arena. The Analysis Profile Does Not List Mobility and Head Direction This occurs when your experiment is set to Number of Subjects = 2 and Body Point Detection Technique = Deep Learning. In that case the software does not calculate the body contour and the Head Direction line. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Statistics (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-statistics-continued Chapter: EthoVision XT I Get Different Results When I Analyze the Same Video Twice There may be a few reasons for this to happen. Reason 1 - The effect of the reference image. When you use the detection methods Dynamic Subtraction or Differencing, the image used as reference may differ between trials even when you use exactly the same detection settings. The effect is more pronounced when you use Differencing. - If you position the video file at different times (thus at different frames) then you go back to the beginning and start the trial, the reference image may be different in the two trials. This will cause the track to differ slightly between the trials. - If you choose to use the dynamic reference image instead of the saved reference image at the start of each trial in a series (see The Reference Image) then the reference image with which trial 2 starts may not be exactly the same as the one at the start of trial 1. The difference may be of one or few more pixels brighter or darker, but still that difference has an effect. To ensure that you use a consistent reference image, duplicate the Detection Settings and under Advanced select Background > under Acquisition Settings select Use saved reference image or Use first frame of each trial. This way at the start of each trial the same reference image is used. See The Reference Image. Reason 2 - Missing samples can affect the track duration. This happens especially if the missing samples happen to occur just when trial control start or stop conditions are evaluated. Reason 3 - In multi-subject tracking done with Deep Learning, the results are not entirely repeatable due to the non-deterministic nature of the algorithm. Note that this occurs when you select to track two subjects in the arena, not just one. See Troubleshooting: Deep Learning > The Results of Two-Subject Tracking Are Not Consistent When Using the Same Video. Concluding, to improve the consistency between trials: - Start both trials at the beginning of the video file, without positioning the video on any frame in the middle. - Improve the subjects' detection to reduce the number of missing samples. - Use Gray Scaling or Static Subtraction (if possible). If you use Differencing or Dynamic Subtraction, choose to use a fixed reference image. See The Reference Image. - To smooth out the tracks and remove outliers, apply the Lowess smoothing to the tracks. See The Lowess Smoothing Method. The Average Heading Calculated in Excel Does Not Match the Results in EthoVision XT If you use the ATAN formula, the value is wrong because ATAN uses another convention for the sign of the average sine and cosine of angles. Use instead ATAN2. The formula for the average heading in a track is: =DEGREES(ATAN2(AverageCos, AverageSin)) Where AverageCos is the average of Cos values (calculated as =COS(RADIANS(angle))), and AverageSin is the average of Sin values (calculated as =SIN(RADIANS(angle))), and angle is the per-sample value of Heading, Head Direction, or Heading to Point. There Is No Linear Relationship Between Average Velocity and Total Distance Moved When plotting the average velocity and the total distance moved, there should be a linear relationship between the two. In particular: Average Velocity = Total Distance Moved / T Where T is the time interval (e.g. trial, or time bin) within which the samples are used to do the calculations. In some cases the data points deviate from the linear relationship. The reason is that the total distance moved is calculated over the available samples. If some samples within an interval are missing, or in some samples the subject was not found, or if the interval is incomplete (for example, the last time bin in a track), then the total distance is underestimated while the average velocity is unaffected. As a result, the mean velocity no longer lies on the straight line; rather, it lies above the line. The mean velocity is higher than expected from the current distance moved. This pattern is therefore an artifact of the variation in the number of samples available for each time interval. In principle, there is nothing wrong with the data, provided that the proportion of missing samples or samples with "subject not found" is low. I Defined an Active State in the Analysis Profile, However When I Plot the Data I Get Lots of Inactive States This usually happens when the Activity settings in the Detection Settings are too high. For example, the Activity threshold is 20, or Background noise filter is set to more than 3. In such cases the thresholds are so high that in almost no video frame the subject is considered Active, even if in the Analysis profile the Active state was defined with low threshold values. Solution: Make a duplicate of your Detection Settings, reduce the Activity threshold and/or the Background noise filter. Check in the video image that purple pixels appear only when the subject moves. Then repeat the tracking with those Detection Settings. I Get Wrong Statistics of Manually-Scored Behaviors Problem: I scored a behavior of type "Start-stop". In the Statistics and Charts page, the frequency of Not [behavior name] is X+1 when it should be X. Explanation: This occurs when you score a Start-stop behavior until the end of the trial. At the last sample time, the behavior is automatically ended, and its complementary Not [behavior name] is scored. This results in the additional occurrence of Not [behavior name] in the statistics. However, the statistics of the actual behavior are correct. The Results Table Shows Empty Rows or Columns This occurs often when you make multiple data selections. For example, you make a Nest condition to select the time from 12 hours to 24 hours, then you create time bins of one hour each. The results table also shows the "empty" bins from 0 to 12 hours. To hide the empty rows/columns: - Click the Layout button on the toolbar (or click the Show/Hide button at the top-right corner of the screen and select Layout). - In the window that opens, select Hide empty rows or columns. The Results Table Shows the Same Value for the Same Dependent Variable for the Same Trial, Arena or Subject This may be due to the fact the results are calculated with a data profile containing two or more Results boxes, but the table does not show the corresponding headers. Click the Layout button and add Selection Result, Arena name, or Subject. See Modify the Layout of the Results Table. The Results Table Shows Wrong or Missing Units This occurs when in the Layout window you place the Variable with detail on the rows and the Statistic with unit on the columns, and vice versa. To solve the issue, place both items on the rows or on the columns. See Modify the Layout of the Results Table. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Video image URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-video-image Chapter: EthoVision XT Issues - The camera image is not detected by EthoVision XT - EthoVision XT shows a message "No video frames" - I do not see the image of the video file - The video image looks grainy - The live image from the camera looks distorted - The camera image is static/pixelated with red, blue and green pixels - The camera image is off-center - The camera image is too narrow to display the entire arena - The camera image is ok in the Experiment Settings, but in the Arena Settings I see a white background image - The camera image is not shown in the Arena Settings or Integrated Visualization - The camera image flickers - The camera image doesn't flicker but the overall image lightens and darkens - There is motion blur in the camera image - The camera image is not in focus, no matter what I do - The camera image is dark, even when using a lot of infrared light - My video file is not playing correctly - Video is being processed poorly - A black bar is displayed when zooming in to a video file - EthoVision XT freezes when playing a video file - EthoVision XT freezes in live video mode The Camera Image Is Not Detected by EthoVision XT Try the following: - Make sure that the camera is powered and switched on, that the video cables are not broken and that there is no loose connection between camera and computer. Try, for example, another video cable to see whether the image is then detected. - If you have an analog camera, check that the camera is connected to the input of the encoder board that is selected under Video source in the Experiment Settings. If you have a digital camera, check that it is connected to the correct port on your PC. - If you have a Basler digital camera, make sure to close the pylon Viewer software. - Make sure that the lens cap is removed, and turn the camera's aperture ring to Open. - Click the Show/Hide button on the toolbar and make sure that Video Source is selected. - If the camera was accidentally disconnected, reconnect the camera, then in EthoVision XT choose Setup > Experiment Settings and click the Refresh button next to the camera name. - If you have MediaRecorder 2.5 installed on the same PC, it could be that the problem occurs because you have installed MediaRecorder 2.5 after installing EthoVision XT. Note that this problem does not occur with MediaRecorder 4 to 6. To solve the issue, download the installation files (see Install EthoVision XT) and double-click EthoVision XT - Setup - [version number].exe. In the window that opens, select Repair. This re-installs the correct software for displaying the camera image. - If the problem persists, re-install the drivers for the encoder board or digital camera. To do so, download the installation files (see Install EthoVision XT) and double-click EthoVision XT - Setup - [version number].exe. On the window that opens, select Modify and choose the appropriate driver from the list. See Install EthoVision XT. EthoVision XT Shows a Message "No Video Frames" The message is shown in the Experiment Settings > Video Settings window. - See the issue above. - Confirm that the PC monitor is plugged into the stand-alone graphics card (GPU) and not the motherboard. - If you are using Windows 10 and GigE Basler cameras, make sure you installed the driver from the installation files. If you installed from an older installation drive, you might have installed an older driver (e.g. 4.2.1) which does not support Windows 10. - The message "No video frames" is also shown when there is something wrong with the camera, the power supply, or the video cable. Please replace cables or connect the camera to another input channel of the board, or another computer. - Disable the Firewall for the network ports connected to the cameras. Disable the Windows firewall for the Ethernet board. I Do Not See the Image of the Video File - Click the button next to Video in the Acquisition Settings window and select the file you require. - Click the Show/Hide button on the toolbar and make sure that Video Source is selected. - TIP: Choose File > Preferences > Default Folder. Under Alternative media location, enter the folder where your video files are stored. This way EthoVision XT looks in this folder if video files are not found in the Media Files folder of the experiment. The Video Image Looks Grainy The problem occurs only when connecting the video cables from a T splitter to input 1 and 2 of the Picolo H.264 board. Splitting the video signal into two cabling was necessary to acquire the tracks and simultaneously save video. However, in EthoVision XT 12 and later versions this is no longer necessary. Just connect the camera to video input 1 of the board. The Live Image from the Camera Looks Distorted This may occur when you change the resolution of the camera image in the Experiment Settings (see Adjust camera settings in EthoVision XT), without updating the background image in the Arena Settings. To do so, open the Arena Settings and click the Grab Background Image button in the lower part of the Arena Settings window. The Camera Image Is Static/Pixelated with Red, Blue, and Green Pixels Make sure that the camera is set to black and white mode (via the camera menu; see the camera user manual for how to access this menu). - If you have a digital monochrome camera, in EthoVision XT, make sure that the Color space is set to Y800. If you set the color space in pylon Viewer, the correct option is Mono 8. - If you have a digital color camera, see the camera type in Cameras supported by EthoVision XT for the recommended color space. See also Adjust camera settings in EthoVision XT > Format tab. The Camera Image Is Off-Center This may occur if you select a lower resolution in the Experiment Settings, and the Center X and Center Y options are not checked in the camera settings. To solve this, increase the resolution to the maximum value and the arena will be centered. See Adjust camera settings in EthoVision XT > Format tab. If you prefer a lower resolution, check the option Center Image in the Camera/General tab. See Adjust camera settings in EthoVision XT > Camera/General tab. The Camera Image Is Too Narrow to Display the Entire Arena - This may occur when you select a low video resolution in the Experiment Settings. Rather than scaling the entire image down to the lower resolution, this camera displays a limited area of interest in order to maintain the full image quality. For the widest possible view, increase the resolution to the maximum value (typically 1280x1024). - If you have a varifocal lens, you can also adjust the zoom setting on the lens. Note that adjusting the zoom will also change the focus, so you will need to adjust the focus as well in order to see the actual effect. Also note that you may need to loosen the lock screw on the side of the lens before the zoom setting may be adjusted. TIP: Watch the video tutorial Set Up Your Test Environment. To open the tutorial, choose Help > Video Tutorial. Arena Settings Shows a White Background Image - The video resolution set in the Experiment Settings is either too high or an odd resolution is selected, such as 640x426. Reduce the resolution and/or select a standard resolution (such as 640x480). - A similar issue occurs when no drivers have been installed for the computer's graphics card. See below. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Troubleshooting: Video image (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-troubleshooting-video-image-continued Chapter: EthoVision XT Integrated Visualization Note: This information is probably obsolete for EthoVision XT 19, since EthoVision XT no longer needs hardware acceleration. We keep it in the Help in the case you encounter this issue in EthoVision XT 17 or earlier. This issue can occur in computers and laptops with two graphics cards, a primary (integrated) card and a secondary card (Graphics Processing Unit, or GPU), usually more advanced and powerful than the integrated one. The issue occurs when EthoVision XT uses a graphics card that is not given hardware acceleration. Choose one of the two solutions. In either case the chosen card is given hardware acceleration. Solution: Select the Integrated (Primary) Card for EthoVision XT With this solution EthoVision XT uses the integrated card, which saves energy. You can choose that other programs use the secondary card, which requires more power. - Method 1: - Open the settings for the secondary card. For example, NVIDIA Control Panel. - Under Manage 3D Settings, click Program Settings and click the Add button to add EthoVision XT. - From the list below 2. Select the preferred graphics processor for this program, select Integrated graphics. If the option is not available, follow Method 2 below. - Method 2: - In Windows choose Settings. Next to Search, type graphics and press Enter. Choose Graphics Settings. - Click Graphics. - If EthoVision XT is not listed yet, under Add an app choose Desktop app, browse to the installation folder (default C:\Program Files\Noldus\EthoVision XT 19), select EthoVision.exe and click Add. - Click Options under EthoVision XT. In the Graphics Preference window, choose Power saving. Below this option you should see the name of the integrated graphics card. EthoVision XT will use this card to play back video. Solution: Disable the Integrated Card in the Computer's BIOS This solution has the disadvantage that the computer won't use the integrated graphics card, which saves energy compared with the secondary card. EthoVision XT will always use the secondary graphics card. - Shut down the computer and start it again. Enter the BIOS. This is usually done by pressing the F2, F12 or other keys when the first screen appears. See your PC's documentation for details. - Under Video, select Switchable graphics on the left, and de-select Enable Switchable Graphics, click Apply and exit the BIOS. - Now Windows only sees the secondary graphics card, which is given hardware acceleration. You can check that in the Windows Device Manager, under Display adapters. The Camera Image Flickers The underlying issue is that fluorescent and LED lighting cycles at a specific frequency, for example at 60 Hz in the US, and that frequency does not align with a frame rate of 25. Instead, use a frame rate of 30. Sometimes this is enough to resolve this issue. If the problem persists, try the following: - The Exposure Time setting set in pylon Viewer or EthoVision XT is likely too low. To increase Exposure Time, see Adjust camera settings in EthoVision XT. Try something in the 4000–8000 range. If lighting is low in the room, go for a higher exposure or open the aperture of the lens. - If none of the above resolve the problem, then was your PC purchased from Noldus? If not, it may be insufficient to run EthoVision XT in some conditions. If you would like Noldus Support to review your PC specs, please Make a PC report for Support. The Camera Image Lightens and Darkens - Check that in pylon Viewer under Acquisition Controls, Exposure Auto is set to Off. - Check that in pylon Viewer under Analog Controls, Gain Auto is set to Off. - Check that in pylon Viewer under Color Improvement Control, White Balance Auto is set to Off. - If none of the above resolve this, then check that your Exposure Time setting (in pylon Viewer under Acquisition Controls, or in EthoVision XT via Experiment Settings > click the camera button) is high enough (try 8000). There Is Motion Blur in the Camera Image The Exposure Time setting is likely too high, for example 20000 (microseconds) or higher. - See Adjust camera settings in EthoVision XT for how to reduce the camera's Exposure Time. The faster the subject, the lower the Exposure Time must be. - With a lower exposure time, the image becomes darker. You can compensate for this by increasing the lens' aperture or the camera Gain. For the latter, see Gain in Adjust camera settings in EthoVision XT. The Camera Image Is Not in Focus It does not matter how high the camera is mounted or whether you zoom in then focus — the image from the camera is always blurry. The camera will not focus if the wrong type of lens is mounted: - A C-mount lens on a CS-mount camera. The camera can be used but requires an adapter ring installed between the lens and camera. - A CS-mount lens on a C-mount camera. In that case the camera and the lens are not compatible. If the camera and lens have the same mount type, make sure this adapter ring has not been installed, as it will prevent correct focus. If the solution above does not help, try resetting the camera. See Do a factory reset on the Basler GigE camera. When in doubt, contact Noldus Support. The Camera Image Is Too Dark This may be due to a few reasons: - The Aperture ring on the camera lens is closed all the way. - The Exposure Time of the camera is too low. See Adjust the camera exposure time. - The Gain of the camera is too low. Note that if you increase the camera gain, noise also increases. See Adjust the camera gain. - Some color cameras may have infrared block filters attached by default. In that case the IR light is blocked and the image looks dark. For Basler cameras, you can remove that filter. See Infrared-block filter. My Video File Is Not Playing Correctly Download and use the Gspot software to check that the video file contains header information. If a video lacks header information, playback may not be smooth in EthoVision XT. http://www.headbands.com/gspot/ We advise converting the video file to another format. - Some MPEG-2 videos play back irregularly in the Track Editor and in the Integrated Visualization. In this case too, convert the video to another format. - The following formats are not supported in EthoVision XT: WMV, Quick Time, FLV (YouTube), Xvid variants of the MPEG-4 format. See Video file formats. Video Is Being Processed Poorly Set the hardware acceleration to maximum. You can do this in the graphics card control panel. A Black Bar Is Displayed When Zooming In to a Video File This may happen in the Track Editor or in Integrated Visualization. When zooming in and the size or position of the video exceeds the total size of the graphic display, then on some computers the hardware acceleration needed for rendering the video will stop functioning, causing a (partially) black video. Contact Noldus Information Technology for a new video graphics card. EthoVision XT Freezes When Playing a Video File This may happen with MPEG-2 videos. Convert the video file to another format. EthoVision XT Freezes in Live Video Mode This occurs with one or more digital cameras connected simultaneously. Experience shows that the software does not freeze when you lower the resolution to e.g. 800x600. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Turn angle URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-turn-angle Chapter: EthoVision XT Definition The change in direction of the nose, center, tail-base point or Head direction line between two consecutive samples. Calculation You can calculate Turn angle in two ways, based on body points or the Head direction line. Based on Body Points Turn angle is calculated as the difference between two subsequent values for Heading of the specified body point: - ΔHeading = Headingk - Headingk-1 - If ΔHeading < -180°, then Relative Turn angle = ΔHeading +360°. - If ΔHeading ≥ +180°, then Relative Turn angle = ΔHeading -360°. - Else Relative Turn angle = ΔHeading. In the example below, there is a turn to the right (clockwise) at sample k. The heading HEk-1 is positive, while HEk is negative. As a result, the difference HEk - HEk-1 is negative. For the default axis orientation shown in the figure below, a clockwise turn corresponds to a negative Turn angle. A counter-clockwise turn corresponds to a positive Turn angle. Based on Head Direction Turn angle is calculated as the difference between two subsequent values for Head direction (see the figure below, left). This value is independent of the position of the body points: - ΔHead direction = Head directionk - Head directionk-1 - If ΔHead direction < -180° then relative Turn angle = ΔHead direction +360°. - If ΔHead direction ≥ +180° then relative Turn angle = ΔHead direction -360°. - Else relative Turn angle = ΔHead direction. The Turn angle based on head direction depends only on the samples k–1 and k, while the Turn angle based on a body point depends on the last three samples (k–2, k–1 and k). Note: The Head direction line is calculated using the subject's contour. If you swap nose- and tail-base points, or interpolate those two points, the Head direction line is not recalculated using the contour, instead as the prolongation of the segment joining the nose-point and the center-point. Turn angle is then calculated based on those head direction lines. Absolute vs. Relative Turn Angles - Absolute Turn angle: The difference in direction is unsigned. Absolute Turn angle ranges from 0° to +180°. - Relative Turn angle: The difference in direction is signed. With a default axis orientation, a clockwise turn is signed negative, and a counterclockwise is signed positive. Therefore, the Relative Turn angle ranges from -180° to +180°. Relative angles help you distinguish between clockwise turns and counterclockwise turns. Absolute and Relative turn angles result in different averages. Consider for example two angles, -10° and +40°. The average relative turn angle is (-10°+40°)/2 = 15°. The average absolute turn angle is (10+40)/2 = 25°. Tip: With the default axis orientation, a clockwise (right) turn means a negative turn angle. A counter-clockwise (left) turn means a positive angle. Whenever you use a coordinate system other than the default one, rotate the image to know the sign of the turn. For example, a right turn on a coordinate system with the x-axis flipped gets a positive value. How to Specify Turn Angle - Click the Add button next to Turn angle and click the Turn angle tab. Select Absolute or Relative. - Select Head direction turn angle (body point is ignored) if you want to calculate turn angle based on the Head direction line. - Click the Body points tab. Select the body points for which you want to calculate the turn angle. By default, Center-point is selected. If your experiment is set to Only center-point detection or Color marker tracking, this tab is absent. Calculations are based on the center point. This tab is not available if you choose the option in step 2. - Complete the procedure to add the variable. See Calculate statistics: procedure. Relative and absolute turn angle based on the change in direction of the Head direction line can be visualized in Integrated Visualization (Analysis > Results > Integrated Visualization). The first chart shows Relative turn angle, displaying positive and negative values for left and right turns of the head respectively. The second chart shows Absolute turn angle. These dependent variables can also be exported in the raw data file (Analysis > Export > Raw Data). Relative Turn Angle and Axis Orientation Relative Turn angle depends on the orientation of the x- and y-axes in the Arena Settings used for that trial. By default, the x-axis is horizontal and pointing to the right. A clockwise turn is scored as a negative value, and a counterclockwise turn is scored as a positive value. However, if the x-axis is pointing to the left, a clockwise turn is scored as a positive value, and a counterclockwise turn is scored as a negative value. The sign of the Relative Turn angle (RTA) depends on the orientation of the x- and y-axes. The sign inside the circles indicates the sign of Heading (HE) values. When the difference HEk - HEk-1 is larger than +180° or smaller than -180°, the rules described in Heading apply. If the axes are swapped, the reference line is now vertical and the Relative Turn angle is calculated relative to the vertical axis. Notes - The mean, standard deviation and variance are calculated with linear statistics. - Turn angle is calculated in a way different from that in EthoVision 3. This is because Turn angle is based on Heading, which is set consistent with Head direction. - Turn angle is very sensitive to small, random movements of the body points. When the animal sits still, Turn angle can get very high, unrealistic values. To remove such small movements from your data, smooth the tracks, then run analysis. - Turn angle should not be confused with turn bias or turning rate. These are actually synonyms for the dependent variables Relative Angular velocity and Absolute Angular velocity, respectively. Application Assessing turn angles can be helpful for detecting stereotypic movements. In this case, consecutive turn angles tend to have large values (for example, in circling behavior of rodents), or show repeating patterns (for example, rocking or waving). For better quantification of biases in the left/right direction, first filter the data with the Minimal Distance Moved method, to ignore points where the animal does not move significantly. Cumulative Turn angles are used to calculate rotations. See Rotation. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Types of cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-types-of-cameras Chapter: EthoVision XT Types of Cameras You should select the video camera most suitable for your needs. Color vs. Monochrome Monochrome cameras are cheaper, more compact and usually have greater light sensitivity. If you want to film in near darkness, you must use a monochrome (or specialist IR) camera. If you want to track multiple animals and distinguish them on the basis of color markers, you (of course) need a color camera. See also: - Tips for color tracking - Camera position and settings - Lighting setup Digital vs. Analog The advantage of analog over digital cameras used to be that they can be placed at considerable distance from the computer and that they were more light sensitive. However, this is no longer true. Furthermore, current digital cameras can be as light sensitive as analog cameras. GigE Vision Digital Cameras Henceforth called GigE cameras. Noldus can supply a GigE camera that is sensitive to 0.5 lux, and to near IR light. You can connect up to four GigE cameras to a desktop computer. See Install GigE cameras. Advantages of GigE cameras: - You can use much longer cables than, for example, USB cameras. This way you can place the camera further away from the PC. When working with rodents, this solves the problem of ultrasound emissions from computers, which stress animals. - You do not need an encoder board to convert the analog signal into digital video. - Relative to analog cameras, you can use a higher frame rate and a greater video resolution. However, recording video with a GigE camera requires a lot of computer resources, which may potentially decrease the quality of tracking. Therefore, lower the frame rate at high resolution, and vice versa. USB 3.0 Digital Cameras USB 3.0 cameras can create video of higher resolution and frame rate than analog cameras. However, the cable that connects the camera to the PC may be up to 5 m long, unless you use a powered repeater cable. A 20-m powered repeater cable works well with EthoVision XT. - EthoVision XT supports the use of one USB 3.0 camera. See USB 3.0 cameras. - Most USB 2.0 cameras are not accurate enough for video tracking with EthoVision XT. See USB 3.0 cameras. FireWire (IEEE 1394 Standard) EthoVision XT does not support FireWire cameras. The Imaging Source FireWire camera of older DanioVision systems is no longer officially supported. Internet Protocol (IP) Cameras IP cameras are definitely cheaper than industrial GigE or USB 3.0 cameras, however they are less accurate in the timing of video frames sent out to the EthoVision XT computer. This can cause EthoVision XT to skip a number of video frames during tracking. If you use IP cameras, for information open the Help of EthoVision XT 17 or earlier, which you can download from my.noldus.com. Webcams EthoVision XT could in principle work with most webcams. However, we do not support and do not recommend the use of webcams when timing of video frames is important. For example, you can use a webcam to film a mouse in an open field, with the aim of measuring the distance moved. However, do not use webcams to track multiple animals in an apparatus, or in multiple apparatuses, or when you use the Behavior Recognition, or whenever precise timing of events and behavior is needed. Furthermore, test if the webcam still works when other software needed to run during the trials is open, for example PowerPoint for stimulus presentation. Other Cameras If you want to use a camera model other than one of the models listed under Cameras Supported by EthoVision XT, before starting an experiment make sure that the timing of the camera is accurate enough for a frame-level video analysis. To do so, create a live tracking experiment, and carry out a test trial with the video footage of a digital clock for some ten minutes. Just before stopping the trial, check that the trial duration shown on your screen does not deviate from that obtained with the clock time. Also check the Noldus support center for more information. See Noldus Support. See also: - Cameras supported by EthoVision XT Overview The figures reported in the following tables refer to the configurations tested. For more details, see Resolution, Frame Rate, and Maximum Trial Duration. NOTE: You can use one, two, three, four, eight, 12 or 16 cameras simultaneously. Using for example 5 cameras is not supported. Furthermore, we do not support the use of a combination of different camera types. NOTE: The term Not supported does not necessarily mean that a specific solution will not work. It is to indicate that Noldus has not (yet) confirmed the solution to be working. Type Brand/Model Max Number Interface Board (for Desktop) Driver Version Frame Rate (fps) GigE Basler acA1300-60gm (monochrome) Desktop: 16 Laptop: 1 CT1000 Pro (1 camera) Adlink PCIe-GIE74 (1–4 cameras) (c) Basler GigE Interface Card, 4 port PoE (1–4 cameras) (c) FS X550AT2-2TP, 2-port (1–16 cameras) (c) 7.5.0.15658 GigE Basler acA1920-40gc (color) (b) Desktop: 4 Laptop: not tested, not supported CT1000 Pro (1 camera) Adlink PCIe-GIE74 (1–4 cameras) 7.5.0.15658 USB 3.0 Basler acA1920-155um (monochrome) Desktop: 1 Laptop: 1 U3-PCIE1XG205-1S, U3X4-PCIE4XE111 7.5.0.15658 Analog PhenoTyper 1 (f) Desktop: 16 Laptop: not tested, not supported Picolo Alert (1–4 cameras) (g) Multicam 6.15.1.3573 25 (PAL) 29.97 (NTSC) Drivers - (a) You can find the drivers for the supported cameras on the full installation package, or on my.noldus.com, under Downloads > EthoVision XT > Drivers and Tools. GigE Cameras - (b) Recommended for color tracking in low light (< 10 lux). - (c) To connect multiple GigE cameras, see Using Multiple GigE Cameras and 16-Camera Configuration. - For resolution, frame rates etc. see GigE cameras. USB 3.0 Cameras - For resolution, frame rates etc. see USB 3.0 cameras. Analog Cameras - (f) In theory you could use any analog camera, in combination with the Picolo Alert encoder board. Test your camera thoroughly before running the actual trials. - (g) One Picolo Alert board works with a maximum of 4 analog cameras, or 16 cameras in combination with Quad Unit Processors. See Connect Analog Cameras to the Computer. - For resolution, frame rates etc. see Analog cameras. IP Cameras and Webcams - IP cameras and webcams are no longer tested and supported. If you wish to keep using those cameras, make sure you test them thoroughly before running the actual experiments. Make sure that the number of missing samples is not too high. See also: - Resolution, Frame Rate, and Maximum Trial Duration - Restrictions in EthoVision XT - Install GigE Cameras - Install USB 3.0 Cameras - Install Analog Cameras - System Requirements > Hardware Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - User-defined Hardware and Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-user-defined-hardware-and-analysis Chapter: EthoVision XT User-defined Device Types Device types like the PhenoTyper's Top Unit Interface, the Lickometer and the Pellet Dispenser are pre-defined in EthoVision XT as default device types, so when you use such devices you do not have to define their properties at every new experiment. In the case you want to use a new device type or a device with parameters different from those set in Noldus devices, you can create a User-defined device type. For example: - You want to sample the Lickometer at a rate different from the default one, that is one sample every two seconds. To do so, create a new Lickometer device type, where the only difference between the existing Lickometer and the new device type is the value for the sampling interval. - Add a "Trapdoor" device type by duplicating the existing Custom Device, and by replacing the various command- and signal texts. For instance: replace Output 1 High with Door 1 open. This section instructs how to make simple changes to an existing device. For more complex changes, the Noldus HardwareInterface USB-IO box software and maybe even EthoVision XT itself may need to be changed. Contact Noldus Technical Support for wishes and ideas. In order to carry out the procedure below, you need some experience with computers and XML language. In a Nutshell When you install EthoVision XT, the following file: DeviceTypesNoldus.xml is copied to the following folders (henceforth named ProgramData folder): - C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface Iobox\{version number} - C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface MiniIobox\{version number} Two files are present in this folder: DeviceTypesNoldusChCh.xml and DeviceTypesNoldusEnUs.xml. The first is used with the Chinese version of EthoVision XT, the second with the English version. The XML file contains all the details of the types of hardware devices that you can control with EthoVision XT with the USB-IO box and the Mini USB-IO box. You can edit this file for small changes in the hardware devices, for example if you want to change the frequency a PhenoWheel counter is read out. You can also define custom devices and create a file DeviceTypesUser.xml. If you do so, make sure the file DeviceTypesUser.xml and DeviceTypesNoldus[language version].xml do not contain settings for the same device. When you create an experiment, EthoVision XT copies these files to your experiment folder, under Configuration Files\Add-ins\Hardware\{dll serial number}. The dll serial number depends on the type of USB-IO box and its version. See Table 3.1 for which serial number belongs to which device and version. Tip: To find out which version of the driver is installed on your computer, see the Programs and Features list on the Control Panel. Every time that you open the experiment, EthoVision XT reads the files in the experiment folder, not the ones in the ProgramData folder, and does not change them. Therefore: - If you edit the files in the ProgramData folder, the new device types will be available to all your new experiments. - If you edit the files in a specific experiment folder, the new device types will only be available to that experiment. When you make a backup of the experiment, the device type files are also copied, so the new devices can be recognized on other computers where you restore the experiment from the backup. Important: Always make a backup of the ProgramData folder before you edit the file DeviceTypesNoldus[language version].xml. Table 3.1: DLL Serial Numbers for USB-IO Box and Mini USB-IO Box Versions Serial Number USB-IO Box Mini USB-IO Box {A8DA8F3E-7EA3-4629-8327-9D21C90FB3ED} 5 {0308106B-1EBE-4620-B00D-396ABEBBC219} 5 {33DF79E0-53C2-44C6-BA2F-A24C4C702615} 4 {F9AAD805-B910-4FEC-AC2F-31DED85324B2} 4 {C183DC50-0CAB-4E67-905E-9D45D8213BD2} 3 {B1336ED5-DE91-4C40-A59D-6A2D131C4F9B} 3 {DF396575-4883-47C4-9124-8DE30AE1E4C6} 2 {2EDFF151-DF50-486E-887F-55AD41457A5B} 2 {83BF6F4E-D35B-489A-9F5E-703C4EE9453B} 1 {93C9527C-8B2F-4530-9370-7CA330856D15} 1 Undo the Changes in the Device Type Files If you want to undo the changes made and return to the original situation, proceed as follows: - Close EthoVision XT. - Remove or rename the file DeviceTypesUser.xml in the ProgramData folder. - Copy the files from the backup of the ProgramData folder to the ProgramData folder. - Optional: Run installation of EthoVision XT and select Repair. Browse to my.noldus.com if you need to download the EthoVision XT installation files. Any experiments that you have created which refer to the user devices can still be analyzed and continued. To remove every trace of your user devices, you must also delete these experiments (and if you made experiment backups, delete these too) by removing them from the Experiments folder. Define a New Device Type Important: Before making changes to files in the ProgramData folder, make a backup of this folder, so you can recover the files if anything goes wrong. The ProgramData folder contains other information important to EthoVision XT. If the files in this folder get corrupted or deleted, you can restore EthoVision XT by re-running installation of EthoVision XT and selecting Repair. To Define a New Device Type - Make the necessary changes to the DeviceTypesUser.xml file in the ProgramData folder as described below. Use the program XML Notepad that you can download from www.microsoft.com/downloads to edit a device type file. Other editors could add undesired characters that may not be read in EthoVision XT. - For changes to standard Noldus device types, edit the file DeviceTypesUser.xml. Note: You can in fact make the changes to the file DeviceTypesNoldus[language version].xml but these changes will be overwritten when EthoVision XT is subsequently re-installed, repaired or a new version installed. - For the other types, also edit file DeviceTypesUser.xml. - Make sure that the file DeviceTypesUser.xml is stored in the appropriate folder under: - C:\ProgramData\Noldus\Components\EthoVision\Noldus HardwareInterface Iobox\5 - C:\ProgramData\Noldus\Components\EthoVision\Noldus HardwareInterface Mini Iobox\5 - Start EthoVision XT, create a new experiment and test the devices. - If EthoVision XT crashes, or does not behave as expected: - Delete the created (failed) experiments. - Make corrections to the file DeviceTypesUser.xml in the ProgramData folder specified above. - Go to step 2. - When everything works fine, create a new experiment and use the changed or new device types. Note: If you use the Quality Assurance module: The change to the device type file is not recorded in the GLP log. Sample File On the download page of EthoVision XT you can download two sample files. - Browse to my.noldus.com (you must log in or register first to access this site). - Choose Downloads > EthoVision XT. Download EthoVision XT - Full installation disc [version number]. Unzip the file and locate the folder Drivers and Tools > IoBox MiniIoBox Devices. There you find the file User defined device types.zip. - Unzip the file User defined device types.zip and save the files on your computer: - DeviceTypesUser - Example.xml - DeviceTypesUser Pheno Wheel (30).xml DeviceTypesUser - Example.xml The file DeviceTypeUser - Example.xml specifies several devices. The top part specifies the PhenoTyper White spot commands. The bottom part specifies the counter of the Running wheel. DeviceTypesUser Pheno Wheel (30).xml For a running wheel, with reading interval of 30 s instead of 60 s as in the standard Noldus PhenoWheel, you need a file like this. Rename the file to DeviceTypesUser.xml. The XML file specifies a device type for a running wheel with reading interval of 30 s instead of 60. Note the device type ID (10006), name (PhenoWheel (30)) and the custom sample frequency (30). When you restart EthoVision XT, the new device types are then shown, for example in the Arena-Hardware Mapping window that you access in the Arena Settings. Predefined IDs For both devices and connectors, IDs must be unique. IDs from 0 to 9999 are for Noldus device (and connector) types. IDs above 10000 are reserved for device (and connector) types that you may want to add. If you create a device type based on a Noldus device type (for example a Lickometer), always use an ID above 10000. Device Type ID Name 0 Top Unit (Standard) 1 Top Unit (Neuro-Bsik) 2 Pellet Dispenser (PTPD-001x) 3 Lickometer (PTLM-001x) 4 TTL Port Tester (PTTB-001x) 5 Custom Hardware 6 PhenoWheel 7 USB-IO box monitor 8 Beam Controller (PTBC-0010) 9 Med Associates Activity Wheel Counter (ENV-042) 10 Med Associates Activity Wheel Brake (ENV-042) 11 Backlight Unit White Light 12 Top Unit Tester (PTTB-002x) 13 Pellet Receptacle (PTPR-001x) XML File Entries Not all of the entries below always apply to each signal, command, etc. If you make edits in a device type file, beware that besides editing the data below you might have to change some numbers that the boost::serialize normally creates itself (vector counts, for example). NCHiIobConnectorTypes Devices can be connected to the USB IO box (or mini IO box) via a connector. There can be more than one connector type in the setup. Following are the properties of the collection of connectors (m_vecConnectorType): Connector Type ID Connector Type Name 0 Top Unit Interface (PTTI-001x). Note that the Top Unit Standard and Special both use this type of connector. Property Description Count Indicates the number of connectors Item_version Indicates the version of the connectors Following are properties of each connector (NCHiIobConnectorType): Property Description HiIob::ConnectorTypeId m_iId Every connector type must have a unique id. g_ConnectorTypeIdInvalid(-1l): invalid value Item_version Indicates the version of the connectors nstring m_strName Name of the connector HiIob::ePortTypes m_ePortType ePrtUndefined(-1): undefined; ePrtSD(0): simple device port; ePrtCD(1): complex device port int m_iNrPorts Number of ports used by the connector int m_iOffsetPin Pin offset for the device connected via the connector NCHiIobDeviceTypes Devices can be connected to the USB-IO box directly (e.g., not via a connector). Following are the properties of the collection of device types (m_vecDeviceType): Property Description Count Indicates the number of device types Item_version Indicates the version of the device types Following are properties of each device type (NCHiIobDeviceType): Property Description HiIob::DeviceTypeId m_iDeviceTypeId Every device type must have a unique id. g_DeviceTypeIdInvalid(-1l): invalid value nstring m_strDeviceTypeName Name of device type, showing up in the UI of port-device mapping dialog (hwdll) and various places in EthoVision XT (for example: ATC, test dialog, etc.) int m_MaxFrequency Most device types are read every read cycle and have m_MaxFrequency = 0. So called "slow device types" (e.g., Lickometer) are not read every read cycle but with the slower frequency MaxFrequency (in seconds). Use integer values only. HiIob::ePortTypes m_ePortType ePrtUndefined(-1): undefined; ePrtSD(0): simple device port; ePrtCD(1): complex device port HiIob::ConnectorTypeId m_iConnectorTypeId Every connector type must have a unique id. Most device types do not use a connector and have value g_ConnectorTypeIdInvalid(-11): invalid value. Currently the only connector type is the top unit connector, used with the top unit. NCHiIobSignal Each device type can have more than one signal. Following are the properties of the collection of signals (m_vecSignal): Property Description Count Indicates the number of signals Item_version Indicates the version of the device type signals Following are properties of each signal: Property Description HiIob::SignalId m_iId Every signal must have a unique (within device type) id. g_SignalIdInvalid(-11): invalid value nstring m_strName Name of signal, showing up in the interface of Device configuration window and other places, for example: the test window in Trial Control. HiIob::eSignalSource m_eSignalSource eSrcUndefined(-1): undefined; eSrcInput(0): signal comes from the hardware; eSrcOutput(1): signal is created in the software and is related to an output state. E.g.: there are outputs "White spot off" and "White spot on", for these outputs "Is white spot on" is an output state that is treated as an (artificial, because not coming from the hardware) input. HiIob::eSignalHwType m_eSignalHwType eShtUndefined(-1): undefined; eShtPin(0): uses pins (most device types); eShtBytes(1): uses direct bytes reading (e.g.: lickometer) long m_iPin The pin used by the signal. Only relevant if eSignalHwType = eShtPin. int m_iNrBytes The number of bytes used for reading the signal. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. int m_iIndexFirstByte Least significant byte. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. int m_iIndexLastByte Most significant byte. Only relevant if both m_eSignalSource = eSrcInput and eSignalHwType = eShtBytes. HiIob::eStateEventType m_eStateEventType eSetUndefined(-1): undefined; eSetL(0): signal is based on Low state; eSetH(1): signal is based on High state; eSetL2H(2): signal is based on transitions from Low to High; eSetH2L(3): signal is based on transitions from High to Low. Only relevant if eSignalHwType = eShtPin. bool m_bHighInit Initial value for the signal. True if High, false if Low. Only relevant if m_eSignalSource = eSrcInput and eSignalHwType = eShtPin. bool m_bTotalsSinceLastCall True if signal returns a value (via the hwdll COM interface) that represents a total since the last call. EAdinsIdtHiValueType m_eValueType The type of the value the signal returns (via the hwdll COM interface). One of the values: eAdinsIdtHiVtUndefined(-1); eAdinsIdtHiVtBool(0); eAdinsIdtHiVtLongLong(1); eAdinsIdtHiVtDouble(2); eAdinsIdtHiVtDuration(3). This value is used by EthoVision XT: Trial Control and logging. bool m_bHasValueDefault True if the signal has a default value. Indicates how the value of the signal has to be treated by the exported hardware log in VTS: If true: only the values not equal to the default value are logged. If false: only changes in the values are logged (default value is not used). NCHiIobValue m_valueDefault Default value for the signal. Only relevant if m_bHasValueDefault = true. HiIob::eValueType m_eTypeValueDefault Default value type for the signal (see m_eValueType for the values). bool m_bValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtBool. LONGLONG m_lValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtLongLong. double m_dbValueDefault Default value for the signal if m_eValueType = eAdinsIdtHiVtDouble. NCHiIobCommand Each device type can have more than one command. Following are the properties of the collection of commands (m_vecCommand): Property Description Count Indicates the number of commands Item_version Indicates the version of the device type commands HiIob::CommandId m_iId Every command must have a unique (within device type) id. g_CommandIdInvalid(-11): invalid value nstring m_strName Name of the command Source: EthoVision XT 19 - Trial and Hardware Control Reference Manual --- ## EthoVision XT 19 - Using Digital Video - H.264 AVC Video Format URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-using-digital-video-h264-avc-video-format Chapter: EthoVision XT H.264 AVC Video Format H264 AVC in MP42 container, with extension *.mp4, is the format of video created by EthoVision XT 16-18 and MediaRecorder 5 and 6. Video Files Created by EthoVision XT When you record video with EthoVision XT, video is encoded with the H.264/MPEG-4 AVC codec and is stored in a container of MP4-version 2 (MP42). The video file extension is mp4. Note that a container is something different from the codec. - The container is the structure that handles various streams such as video and audio streams. You can imagine the container as a box that contains your video frames. - The codec is software that compresses the video stream data. Video Files Created by Media Recorder MediaRecorder 4.0 - With analog cameras: H.264 AVC in an MPG container. - With GigE cameras: MPEG-4 Video in an MP4-version 2 container. - With IP cameras: H.264 stream in an MP4-version 2 container. MediaRecorder 5.0 - With all cameras: H.264 stream in an MP4-version 2 container. MediaRecorder 6.5 - With all cameras: H.264 stream in an MP4-version 2 container. All video files have file extension mp4. Video Formats Not Supported by EthoVision XT Important: The term "not supported" means that the video formats listed below were not thoroughly tested by Noldus. It may be that some formats work fine. If you have old MPEG-2 videos and you want to re-track them with EthoVision XT, test them and check whether (1) video plays smooth and without artifacts ("blocks" in the image) and (2) samples are not missed during tracking, even when selecting the Detection Determines Speed (DDS) option. Important: When using camcorders or other encoding software to make video files, test those files in EthoVision XT before deciding to work with them or convert them to a supported format. - MPEG-1. - MPEG-2. This is a collection of formats; not all may work in EthoVision XT. - DivX. - Variants of MPEG-4. However, an AVI 1.0 file with codec MP43, and an OpenDML AVI file with codec MP4S-ISO MPEG-4 Video V1 may work. - DV-AVI. This is uncompressed video from FireWire cameras. This format is not recommended because of the large file size. DV-AVI is a special case of AVI. In general, EthoVision XT does not support video files of AVI format. The AVI format should not be confused with the file extension avi. - WMV. However, an OpenDML AVI file with codec WMP v9 may work. - QuickTime. - FLV (Flash video, YouTube). - XviD variants of the MPEG-4 format. However, an OpenDML AVI file with codec XviD 1.0 RC4 may work. Record Digital Video Background Digital video requires a lot of storage capacity and always needs to be compressed before it can be stored on a disk medium. In order to compress a video recording you need an encoder, usually a plug-in board, which converts the video signal into a media file on disk at a fraction of the original size. The input signal can either be analog or digital. Prerequisites - If you have analog cameras: EthoVision XT works with the Picolo Alert encoder board. You can use this board not only for live tracking, but also for recording video. - If you have digital cameras: - Install GigE cameras - Install USB 3.0 cameras Another possibility is to use the Noldus MediaRecorder software to make digital video files and track from these videos in EthoVision XT (offline tracking). Procedure - Create a new experiment or open an existing one. - In the Experiment Settings, select the camera(s). See Video Source. - In the Arena Settings, calibrate and draw the arena. - In the Acquisition screen, on the right-hand pane select Save video only, track later. With this option you record the live image to a video file without tracking. Select this option especially if your computer is not fast enough to do tracking and recording at the same time. - To start recording, click the Start Trial button. Tip: Save this experiment as a template (File > Save As). You can then re-use the same settings in a new experiment when you create a new experiment based on an existing experiment. Video File Location Your video files are saved in the Media Files subfolder of your experiment folder. By default in: C:\Users\Public\Public Documents\Noldus\EthoVision XT\Experiments\[experiment name]\Media Files. Video File Size Roughly speaking, the file size is given by: File size = Bitrate x Duration x Compression Ratio Where: - The Bitrate is the product of Frame size x Frame rate (frames per second). - The Duration is the length of the video (in seconds). - The Compression Ratio tells how much space is needed to store similar frames that have fewer moving parts, like an empty open field. The following table can be used as a reference for video created with EthoVision XT. Note that the figures reported are only indicative. There are other factors which influence video file size, such as whether a variable bit rate is used or which color space is used. The amount of movement in the video also influences file size — the more movement, the larger the resulting video file. Therefore, the size of your video files may differ from what is reported below, even when using a comparable setup. Resolution, Frame Rate Camera 10 Minutes Video Duration Per GB 1280x1024, 30 fps Basler GigE, monochrome 75–150 MB 1–2 h 1280x1024, 25 fps Basler GigE, color 175 MB < 1 h 2560x1024, 10 fps Basler GigE, color 100–160 MB 1–2 h 720x480, 30 fps Analog cameras, monochrome 60 MB 16 h DanioVision 800x600, 60 fps Basler GigE, monochrome 90–125 MB 1–1.5 h DanioVision 1280x960, 25 fps Basler GigE, monochrome 355 MB < 30 min Tips for Color Tracking --- ## EthoVision XT 19 - Using Digital Video - Lighting Conditions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-using-digital-video-lighting-conditions Chapter: EthoVision XT Lighting Conditions General Generally, for optimal tracking it is important that the contrast between the subject and the background is as good as possible. For marker tracking, EthoVision XT needs to be able to distinguish the different marker colors. For both issues, the lighting conditions play an important role. - It must be bright enough. A low light intensity can result in a suboptimal contrast between the animal and the background, and therefore tracking might not be optimal. Furthermore, a low light intensity makes it difficult to separate different colors. When it is not possible to use strong illumination in your setup, try using fluorescent marker colors with UV lighting. - It must be even. The light source should be diffuse, for example, a shaded fluorescent tube or globe-type incandescent bulbs. This way, the contrast between the animal and the subject and the intensity of the marker color are the same throughout the arena. - Shadows must be avoided. To avoid shadows, do not point the light directly at your animals, but instead toward the walls or ceiling. Use several lamps to obtain an even illumination. Full-Spectrum Lights For optimal color separation, illuminate your setup with lamps that approximate daylight in frequency distribution of wavelengths, that is, have a full-spectrum range. There is no technical definition of "full spectrum," therefore it cannot be measured. However, to compare full-spectrum lights you can directly compare spectral distributions. In practice, full-spectrum lights can be recognized from two parameters: - High Color Temperature (measured in degrees Kelvin). Usually higher than 5000 ºK. Values of color temperature around 2500–3000 ºK are typical of "warm" color lights (yellowish), for example incandescent bulbs. - High Color Rendering Index (expressed as percentage). Higher than 95. A value of 100 represents the ideal or natural light. Source: EthoVision XT 19 Help - Using Digital Video, Noldus Information Technology --- ## EthoVision XT 19 - Using multiple GigE cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-using-multiple-gige-cameras Chapter: EthoVision XT Using Multiple GigE Cameras Aim: To track from two up to four GigE cameras. This topic applies to Basler GigE cameras only. Important: You cannot use a combination of analog and digital cameras. Also, mixing video images of different camera types is not supported. Connect the Cameras How you connect multiple GigE cameras depends on which Ethernet interface board you have installed. - If you have multiple, 1-port Ethernet boards, connect each camera to an Ethernet board. If the boards are not powered, you must connect the cameras through PoE injectors to a power supply. Only use 1Gbit/s PoE injectors. - If you have a 4-port Ethernet board, you can connect up to four cameras. Important: Make sure the Ethernet board also receives power from the PC. See the connection in Power the Ethernet Board for the GigE Cameras. Important: Each camera must always be connected to the same port on the Ethernet board, because the IP address of the camera and that of the Ethernet port must match. In the case of a multi-port Ethernet board, each port is viewed as a network adapter, with its own IP address. The information of which port is linked is stored in the driver software of each camera. If you swap cameras, they will not be recognized. Therefore, always label the Ethernet ports and the cameras. Tip: When using one Ethernet interface board per camera, rename the network adapters listed in the Windows Control Panel, for example Front camera and Top camera. Assign the IP Addresses to Multiple Cameras You can assign IP addresses with pylon IP Configurator. - Assign an IP address to each Ethernet port on your PC. See Assign IP Addresses. - Assign an IP address to each camera. See Assign IP Addresses. Here are the main rules: - Each camera must have a unique IP address. - Always set the first two numbers to 192.168. - The third number must be the same for the camera and the Ethernet port the camera is connected with. Example: - Camera 1: IP address 192.168.x.101 connected to Ethernet port with IP address 192.168.x.51 - Camera 2: IP address 192.168.x.102 connected to Ethernet port with IP address 192.168.x.52 Video Resolution You can set the video resolution in EthoVision XT. See Select Multiple GigE Cameras in EthoVision XT. See Also - 16-Camera Configuration - GigE Cameras - Install an Ethernet Board for GigE Cameras - Power the Ethernet Board for the GigE Cameras - Assign IP Addresses - Configure the Digital Camera 16-Camera Configuration Important: When using a 16-camera configuration, we recommend using Contour-based tracking, not Deep learning. This is because Deep learning is so resource-demanding that it is unlikely to work with 16 arenas on a typical PC. Setup Hardware and Settings: - PC: Dell Precision 3680, CPU i7-14700K 3.4 GHz, RAM 32GB, GPU NVIDIA T1000 8GB; Windows 11 Pro 23H2 - Cameras: 16 Basler GigE cameras acA1300-60gm - PCIe Ethernet interface board: FS X550-AT2, 10GBase-T Dual-Port, PCIe 3.0 x4 - Network switch: FS S3100-16TMS-P, 16-Port Gigabit Ethernet L2+ PoE+, 8x PoE+ Ports@125W, 2x 5Gb RJ45, with 2x 10Gb SFP+ Uplinks - For this switch you need an adapter (SFP+ 10GBASE-T Copper 30m RJ-45 Transceiver module) for the network cable that goes to the PC. - We recommend using CAT6+ network cables. - Video resolution: Single camera view 640 x 480, merged view in EthoVision XT 2560 x 1920 - Image binning: 2. See Binning. - Video frame rate: 30 fps. Trial duration: 72 hours. - Video source: Live tracking; Number of subjects per arena: 1; Tracked features: Center-point, nose-point and tail-base detection; Body Point Detection Technique: Contour-based; Detection method: Dynamic Subtraction or Differencing; Acquisition mode: Track + Save video. Connection Scheme Follow this scheme also for PhenoTyper 2. Note that in the S3100-16TMS-P network switch, the RJ45 ports marked in yellow are powered, so eight cameras do not need PoE injectors. Connect the remaining eight cameras through PoE injectors. Assign the IP Addresses Connect the cameras to the switch using the ports as shown in the connection scheme figure. For a good overview of the IP addresses, we recommend using pylon IP Configurator. - Start pylon IP Configurator. - For the port of the Ethernet board of the PC connected to the switch, specify the address 192.168.x.51. To do so, locate the Ethernet row in IP Configurator — that is, the row with the board symbol connected to the cameras. Note that the name of the Ethernet row may vary between PCs. - Right-click and select Properties, then double-click Internet Protocol Version 4, select Use the following IP address, and enter the IP address in the IP Address field. - For the cameras (1 to 16), specify sequential addresses in the 192.168.x.x range. Note that the third number must be the same as that for the Ethernet port connected to the network switch. To assign the IP addresses to a camera, select the camera row, then in the panel at the bottom of the screen choose Static IP and enter the IP address. - For all Ethernet ports and cameras, leave 255.255.255.0 as the Subnet Mask. For more schemes of multiple camera configurations, see also the PhenoTyper - EthoVision XT 19 - Reference Manual. Using Network Switches - The network switches must be of type PoE (Power over Ethernet), that is, they must provide power to the cameras. Note that the maximum power provided by a switch, measured in Watt (W), must be greater than the total requirements of the cameras (one Basler camera requires about 2.5 W). - The network switches must be able to handle large packets (known as jumbo packets or jumbo frames). With jumbo frame-capable devices, the maximum packet size can be up to 16 KB. For maximum network efficiency, your camera should be configured to use the largest packet size that your network adapters and switches can handle. - Refer to the user guide of the network switch for how to set it up. See Also - GigE Cameras - Install an Ethernet Board for GigE Cameras - Power the Ethernet Board for the GigE Cameras - Connect the GigE Camera to the PC - Assign IP Addresses - Configure the Digital Camera - Select Multiple GigE Cameras in EthoVision XT Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Video file formats URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-video-file-formats Chapter: EthoVision XT Background Information One of the difficulties with digital video files is that the file extension does not indicate what the file type is. For example, the extension *.mpg can mean any one of different type of formats, and an MPEG-4 movie can have the extension mpg, mpeg, mp4, m4v or avi. IMPORTANT If you are not sure whether the format of your video files is compatible with video tracking in EthoVision XT, test a few video files thoroughly and check that there are no or few missing video frames. - Video file formats supported by EthoVision XT - Video files created by EthoVision XT - Video files created by Media Recorder - Video formats not supported by EthoVision XT Video File Formats Supported by EthoVision XT IMPORTANT When in doubt, test a video format thoroughly before carrying out experiments. Acquire test trials and check that there are no missing samples, and the video plays smooth in the various parts of the software. If the video format is not compatible, convert video to H.264 MPEG-4. That should solve the issue. MPEG-4 This is a collection of formats, not all are supported. MPEG-4 can achieve a very high rate of compression with good quality, because it separately codes the background (which does not change much from frame to frame) from the moving parts of the video. MPEG-4 (mp4v) in a MP42 container, with extension *.mp4, is the format of video files recorded with Media Recorder 4 and EthoVision XT 15. H.264 AVC H.264 AVC is a type of MPEG-4 and is also known under the names H.264/AVC, AVC/H.264, H.264/MPEG-4 AVC, MPEG-4/H.264 AVC, MPEG-4 Part 10 or x.264. It creates good video quality and uses previously-encoded pictures as references in a much more flexible way than in other standards, allowing the use of up to 16 reference frames. H264 AVC in MP42 container, with extension *.mp4, is the format of video created by EthoVision XT 16–18 and MediaRecorder 5 and 6. See Video Files Created by EthoVision XT. Video Files Created by EthoVision XT When you record video with EthoVision XT, video is encoded with the H.264/MPEG-4 AVC codec and is stored in a container of MP4-version 2 (MP42). The video file extension is mp4. Note that a container is something different from the codec. - The container is the structure that handles various streams such as video and audio streams. You can imagine the container as a box that contains your video frames. - The codec is software that compresses the video stream data. For information about the H.264 specification, you can find many internet pages that explain the process of video/audio compression. Here is one of them: https://www.videoproc.com/resource/h264-codec.htm Video Files Created by Media Recorder MediaRecorder 4.0 - With analog cameras: H.264 AVC in an MPG container. - With GigE cameras: MPEG-4 Video in an MP4-version 2 container. - With IP cameras: H.264 stream in an MP4-version 2 container. MediaRecorder 5.0 - With all cameras: H.264 stream in an MP4-version 2 container. MediaRecorder 6.5 - With all cameras: H.264 stream in an MP4-version 2 container. All video files have file extension mp4. Video Formats Not Supported by EthoVision XT IMPORTANT The term "not supported" means that the video formats listed below were not thoroughly tested by Noldus. It may be that some formats work fine. If you have old MPEG-2 videos and you want to re-track them with EthoVision XT, test them and check whether (1) video plays smooth and without artifacts ("blocks" in the image) and (2) samples are not missed during tracking, even when selecting the Detection Determines Speed (DDS) option. IMPORTANT When using camcorders or other encoding software to make video files, test those files in EthoVision XT before deciding to work with them or convert them to a supported format. See Video File Formats Supported by EthoVision XT. - MPEG-1. - MPEG-2. This is a collection of formats, not all may work in EthoVision XT. - DivX. - Variants of MPEG-4. However, an AVI 1.0 file with codec MP43, and an OpenDML AVI file with codec MP4S-ISO MPEG-4 Video V1 may work. - DV-AVI. This is uncompressed video from FireWire cameras. This format is not recommended because of the large file size. DV-AVI is a special case of AVI. In general, EthoVision XT does not support video files of AVI format. The AVI format should not be confused with the file extension avi. - WMV. However, an OpenDML AVI file with codec WMP v9 may work. - QuickTime. - FLV (Flash video, YouTube). - XviD variants of the MPEG-4 format. However, an OpenDML AVI file with codec XviD 1.0 RC4 may work. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - View and interpret variable plots URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-view-and-interpret-variable-plots Chapter: EthoVision XT Effect of Data Selection on Plots If the data profile contains nesting criteria, the selected intervals are shown with a white background. The non-selected intervals are shown semi-transparent enabling you to see the excluded data in these intervals. This example shows a plot of the dependent variables Distance moved and In zone after nesting over the border zone of the open field. If the data profile contains time bins, these are not visualized. Navigate Through the Data Use the scrollbar at the bottom to run through the visualization. The hairline represents the current time in the trial, and is always fixed in the middle of the plot area. For numerical variables, the current sample is highlighted with a circle. The current value of the variable is also shown near the variable name. To move from the start to the end of the trial, you can also: - Click anywhere in the plot, hold the left mouse button and drag the background. - Hold the Shift key down and scroll with the mouse wheel. This way you zoom in/out while the cursor moves forward/backward by one time span. NOTE Each wheel step corresponds to the time span chosen from the Show/Hide menu. If part of the data plot is not visible at the current zoom level, you can either zoom out or move the plot line. Use the scrollbar at the right end of the plot area, or drag the background of the plot. TIP To visualize the whole vertical data range, zoom out the plot until you no longer see the vertical scrollbar. Visualize a Single Variable Value - For discrete variables (states or events). Each state or event is shown as a colored bar. When a variable includes multiple states like In zone (with different zones being defined) or Mobility (with its states Immobile, Mobile, Highly mobile), these are shown as parallel channels. Keep the mouse pointer above a colored bar. A tooltip is shown with the following information: - The name of the dependent variable. - Label: the name of the state or event. - Time: the sample time the mouse pointer points to. - Duration: the length of the state, in seconds. For point events like Rotation or Trial Control events, the duration is not shown. - For numerical variables (including external data). Values are connected with lines. Keep the mouse pointer over the data plot. A tooltip is shown with the following information: - The name of the dependent variable. - The sample Time selected. - The value of the dependent variable at that time. This is indicated by a circle on the plot line. IMPORTANT Although the plot lines may look continuous, the numerical variable values are not interpolated and do not become continuous. For data selection and analysis, the discrete samples are used. Resize the Plots - Resize the time window displayed. Point to the y-axis in the upper part of the plot, so the mouse pointer turns to a double arrow. Drag the y-axis to the desired position to resize the time window. - Resize the width of the plot. Point to the lower margin of the gray cell on the far left of the plot so the mouse pointer turns to a double arrow. Drag the margin to the desired position to have a larger or narrower plot. NOTE The data of continuous variables are stretched/condensed when you resize the plot, but the range of data does not change. Adjust the Time Scale (X-Axis) Do one of the following: - Click the Zoom in or Zoom out button on the toolbar, then click the time scale one or more times. - Right-click the plot and select Zoom in or Zoom out. Next, click the time scale one or more times. - Press Ctrl+. and Ctrl+, to zoom in/out, respectively. - Click the time scale, hold the Ctrl key down and turn the mouse wheel forward (to zoom in) and backward (to zoom out). For the first two methods: to stop zooming in/out and return to the normal mouse pointer, click the No Zoom button on the toolbar, or right-click the plot and select No Zoom. Notes: - Every time you zoom in/out, the plot scale is enlarged or reduced by a factor of 2. - The shortest time that you can display is 0.1 seconds; the maximum time is seven days. - When you zoom in/out by clicking the plot, the clicked time becomes the new current time. Set a Specific Time Span The time span is the duration of the time visible in the time axis at any moment. To set a specific time span, click the Show/Hide button on the toolbar, then click Time span and select one of the values available (minimum 5 sec; maximum 1 hour). NOTE The available values depend on the length of your trial. For example, if your trial is 10 minutes long, the 30 minutes and the 1 hour options are not available. Zoom the Y-Axis In/Out You can adjust the range of values for continuous variables (dependent variables and external data). If you have two or more continuous data plots, the variable scale changes only for the plot you have clicked. - Do one of the following: - Click the Zoom in or Zoom out button on the toolbar. - Right-click the plot and select Zoom in or Zoom out. Result: The mouse pointer turns to a magnifier symbol. - Click the y-axis scale one or a few times. - To stop zooming in/out and return to the normal mouse pointer, click the No Zoom button on the toolbar, or right-click the plot and select No Zoom. Every time you zoom in/out, the plot scale is enlarged or reduced by a factor of 2. TIP To zoom in/out the y-axis in all plots, hold the Ctrl and Alt keys down and scroll with the mouse wheel. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Visualize Data - Arrange Heatmaps URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-arrange-heatmaps Chapter: EthoVision XT Arrange Heatmaps You can arrange heatmaps in two ways: with Layout Presets (below), or manually arranging headers in the matrix (Custom layout). With Layout Presets In the Heatmap Settings pane, click the Show/Hide tab. Under Layout presets, click one of the following: - Adjacent. The heatmaps are arranged from left to right, and from top to bottom to fill the screen as much as possible. The following order is used: first Result container, then trial name, then subject name, then body point. With Adjacent, each heatmap represents a single track per arena. Tracks from multiple arenas are combined in the same heatmap. With this preset, the Merging method Cumulated is selected automatically. Clicking Adjacent is the same as selecting Show/Hide > Layout > Arrange adjacently. - Trials. The matrix is arranged in this way: - On rows: Trial names. - On columns: Result containers, subject names and body-points (if more than one), in this order. With Trials, each heatmap represents a single track, and the Merging method Cumulated is selected automatically. - Time bins. This button is available if you define time bins for at least one Result container in your Data profile. Choose this option for example to inspect behavioral changes over time. The matrix is arranged this way: - On rows: Result containers, trial names, subject names, and body points in this order. - On columns: Time bins ordered by starting time. With Time bins, each heatmap represents a segment of a single track. With the Time bins preset, the Merging method Cumulated is selected automatically. - Group Mean. Choose this option when you create two or more Result containers in your Data profile and you want to compare the corresponding heatmaps, just like you would do with Group statistics, or when you just want to inspect the behavior of a whole group of tracks. The matrix is arranged this way: - On rows: No independent variable. Heatmaps are always arranged in one row. - On columns: Result containers, subjects and body-points in this order. With Group mean, each heatmap always represents a group of tracks, unless a Result container only contains one track. The Merging method Mean is selected automatically. Note: This button is not available in experiments defined as DanioVision experiment. Custom Layout Besides the Layout presets, you can re-arrange the heatmaps by moving and adding/removing the matrix headers. - In the Heatmap Settings pane, under Presets click the Custom button, or click the Show/Hide button on the toolbar and select Layout. - In the Layout window, select Arrange by headers. - To place headers on the other side of the matrix, select the corresponding element under On Columns / On Rows and click the Place Horizontal or Place Vertical button. To alter the sorting order, select an element and click the arrow buttons to place it in an upper or lower position. To add a header, select the corresponding element under Available and click the arrow button next to On Columns or On Rows, depending on where you want to place the new header. To remove a header, select its name under On Columns or On Rows and click the arrow button. Notes - Tip: You can also re-arrange the heatmaps from the matrix itself. - Right-click a header and select Place Horizontal/Place Vertical to place the headers on the other side of the matrix, or Move Up/Move Down to modify the sorting order. - To add an independent variable as a new header, right-click the header row/column and select Insert, then choose the independent variable. - To remove an independent variable as a header, right-click it and select Delete. - You can only remove a header if that does not generate ambiguities in the heatmap matrix. For example, if your Data profile contains two Result containers, you cannot remove the Results header. For the same reason, you cannot delete the Body Points header because mixing body points in a heatmap does not make sense. - The Arrange adjacently option is equal to clicking the Adjacent button under Presets. See Also - Sort Track Plots - Merging Method for Heatmaps --- ## EthoVision XT 19 - Visualize Data - Customize the Track Colors URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-customize-the-track-colors Chapter: EthoVision XT Customize the Track Colors Aim To plot data in colors depending on the subject, the treatment level, or other variables of interest. Accessing These Options Choose Analysis > Results > Plot Tracks or Plot Integrated Data. In the Track Plot Settings pane, click the Colors tab. Specify how colors should vary, for example between arenas or within tracks. Subject Under Level, select Subject. To change the color for a subject and a body point, click the corresponding cell under Settings. - If you tracked more than one subject per arena, choose this option to have the tracks of different subjects displayed in different colors. By default, different subjects have different colors for the center-point, and the same color for the nose- and tail-base points. - If you tracked subjects in multiple arenas, the track of Subject 1 in Arena 1 is displayed in the same color as that of Subject 1 in Arena 2, Arena 3, etc. Track Under Level, select Track to have tracks in colors based on the value of an independent variable, for example to show subjects in colors based on the treatment level. - Select an independent variable from the Variable list. - Click the buttons next to Color Range and select the colors that you want at the ends of the range. Next, click Apply to assign colors automatically. Alternatively, for each value of the variable selected, click the color cell and choose the color you want to assign to the tracks with that value. - Do the same for each subject in the arena. Sample Under Level, select Sample to have the samples within tracks displayed in a color depending on the value of a dependent variable, for example velocity. This way you can see where changes in behavior took place. - Select a dependent variable from the Variable list. The list shows the dependent variables selected in the currently active Analysis profile. If you do not see the variable you want, open the Analysis profile and include that variable, or from the list on the toolbar select the analysis profile that contains the variable. - Click the cell under From/To and choose a color for the lowest and highest value of the dependent variable respectively. EthoVision calculates the spectrum of colors in between and shows it in the middle cell. The lowest and highest values are shown under From and To. For State variables, those are false and true. For continuous variables, those are the minimum and maximum value measured for that variable in the trial, for example 0 to 33.37 for Distance moved. - If you tracked more than one subject per arena, repeat step 2 for each subject. Example: In a track plot where Sample is selected under Level, samples are displayed in red when the subject was in any of the closed arms of the Elevated Plus Maze. In the Analysis profile, a dependent variable In Zone is defined for the center-point in any of the closed arms. When plotting the tracks, samples in any of the closed arms are highlighted accordingly. Source: EthoVision XT 19 Help - Visualize Data, Noldus Information Technology --- ## EthoVision XT 19 - Visualize Data - Dependent Variable Plots URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-dependent-variable-plots Chapter: EthoVision XT Dependent Variable Plots Dependent variable plots show the values of the dependent variables selected in your active Analysis Profile on a time line. Dependent variables are displayed in different ways depending on their type: - States like In Zone: colored bars indicating the state's duration. - Point events like Rotation: vertical segments indicating the event's occurrence, with no duration. - Continuous variables like Velocity: values are plotted as a time series, with one value per sample time. Procedure - Define the variable and calculate statistics. - See Plot Integrated Data. Scope of the Dependent Variable Plot When the trial includes more than one arena or subject, the plot's header indicates which arena and subject it refers to. Why Use Dependent Variable Plots? Dependent variable plots are especially useful in the following scenarios: - To check whether you set correct thresholds for state variables like Body Elongation, Movement, Mobility, and Activity. - Open your Analysis Profile, double-click the variable's name and enter your best estimate for the thresholds. - Plot integrated data. Play back your data, watch the video and check whether the states shown in the plot correspond with the states of the animals in the video. If necessary, repeat steps 1 and 2. - To check that you have scored behaviors manually at a good level of accuracy. - In your Analysis Profile, select the manually scored behaviors you want to check. - Plot integrated data. Play back your data, watch the video and check whether the states shown in the plot correspond with the behavior of the animals in the video. If necessary, export the data to The Observer XT, where you can correct the errors. - To view the behaviors of Behavior Recognition together with their probability values. This helps when you want to refine the definition of those behaviors based on their probability value. - To check whether your Trial Control Settings do what you want them to do. You can visualize Trial Control events and Trial Control states. View and Interpret Variable Plots Effect of Data Selection on Plots If the Data Profile contains nesting criteria, the selected intervals are shown with a white background. The non-selected intervals are shown semi-transparent, enabling you to see the excluded data in these intervals. If the Data Profile contains time bins, these are not visualized. Navigate Through the Data Use the scrollbar at the bottom to run through the visualization. The hairline represents the current time in the trial and is always fixed in the middle of the plot area. For numerical variables, the current sample is highlighted with a circle. The current value of the variable is also shown near the variable name. To move from the start to the end of the trial, you can also: - Click anywhere in the plot, hold the left mouse button and drag the background. - Hold the Shift key down and scroll with the mouse wheel. This way you zoom in/out while the cursor moves forward/backward by one time span. Note: Each wheel step corresponds to the time span chosen from the Show/Hide menu. If part of the data plot is not visible at the current zoom level, you can either zoom out or move the plot line. Use the scrollbar at the right end of the plot area, or drag the background of the plot. Tip: To visualize the whole vertical data range, zoom out the plot until you no longer see the vertical scrollbar. Visualize a Single Variable Value - For discrete variables (states or events): Each state or event is shown as a colored bar. When a variable includes multiple states like In Zone (with different zones being defined) or Mobility (with its states Immobile, Mobile, Highly Mobile), these are shown as parallel channels. Keep the mouse pointer above a colored bar. A tooltip is shown with the following information: - The name of the dependent variable. - Label: the name of the state or event. - Time: the sample time the mouse pointer points to. - Duration: the length of the state, in seconds. For point events like Rotation or Trial Control events, the duration is not shown. - For numerical variables (including external data): Values are connected with lines. Keep the mouse pointer over the data plot. A tooltip is shown with the following information: - The name of the dependent variable. - The sample Time selected. - The value of the dependent variable at that time, indicated by a circle on the plot line. Important: Although the plot lines may look continuous, the numerical variable values are not interpolated and do not become continuous. For data selection and analysis, the discrete samples are used. Resize the Plots - Resize the time window displayed: Point to the y-axis in the upper part of the plot so the mouse pointer turns to a double arrow. Drag the y-axis to the desired position to resize the time window. - Resize the width of the plot: Point to the lower margin of the gray cell on the far left of the plot so the mouse pointer turns to a double arrow. Drag the margin to the desired position to have a larger or narrower plot. Note: The data of continuous variables are stretched or condensed when you resize the plot, but the range of data does not change. Adjust the Time Scale (X-Axis) Do one of the following: - Click the Zoom In or Zoom Out button on the toolbar, then click the time scale one or more times. - Right-click the plot and select Zoom In or Zoom Out. Next, click the time scale one or more times. - Press (Ctrl+.) and (Ctrl+,) to zoom in/out, respectively. - Click the time scale, hold the Ctrl key down and turn the mouse wheel forward (to zoom in) and backward (to zoom out). For the first two methods: To stop zooming in/out and return to the normal mouse pointer, click the No Zoom button on the toolbar, or right-click the plot and select No Zoom. Notes - Every time you zoom in/out, the plot scale is enlarged or reduced by a factor of 2. - The shortest time that you can display is 0.1 seconds; the maximum time is seven days. - When you zoom in/out by clicking the plot, the clicked time becomes the new current time. --- ## EthoVision XT 19 - Visualize Data - Export the Heatmaps URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-export-the-heatmaps Chapter: EthoVision XT Export the Heatmaps You can export a single heatmap, some heatmaps, or the whole matrix of heatmaps to image files. A great advantage of this function compared to copy and paste is that you can rescale the heatmap to a resolution higher than that of the original video, resulting in quality pictures ready for publications. Export a Single Heatmap - Click the heatmap you want to export, so that its border becomes highlighted in red. - Right-click the heatmap and select Export Image, or on the toolbar click the Export Image icon. - Select the image Resolution (width x height) in pixels. - Click Export. In the Export Image window, enter the name and location of your image file, choose the image format and click Save. Tip: You can also copy and paste single heatmaps: click a heatmap, right-click and select Copy or press Ctrl+C, then paste the picture to an external program. You cannot copy/paste multiple heatmaps. Export Multiple Heatmaps - Select the heatmaps you want to export. - To export all heatmaps in the matrix, make sure that no heatmap is highlighted. Click outside the heatmaps area to remove any selection. - To export multiple, non-adjacent heatmaps, hold Ctrl down and click the individual heatmaps. - To export multiple, adjacent heatmaps, hold Shift down, then click the first, then the last of the heatmaps you want to export. The border of the selected heatmaps becomes highlighted in red. - On the toolbar click the Export Image icon. If you have selected some heatmaps, you can also right-click anywhere over the selected heatmaps and choose Export Image. - Under Export, choose one of the options: To Separate Image Files or To One Image File. - Select the image Resolution (width x height) in pixels. Tip: To ensure that each heatmap has a sufficient resolution, under Export select first To Separate Image Files, select the resolution you require and then choose To One Image File. The image resolution (width, height, or both) is increased by a number of times depending on how many heatmaps are in the rows and columns. - Choose Independent Variable as overlay to have the trial information (headers) displayed on the exported images. - Click Export. In the Export Image window, enter the name and location of your image file, choose the image format and click Save. Notes - The available image resolutions depend on the aspect ratio of the original background pictures. The zoom level chosen for the plots affects the default resolution. - To choose the appropriate information to display on the heatmaps, see Custom Layout in Arrange Heatmaps. - The suggested export file name is Heatmap Image plus a progressive number. For heatmaps exported to separate files, the name of the exported file is the name you enter in the Export Image window followed by the row headers and the column headers. For example: Heatmap Image 0001 - Trial 1 - Center Point. Plot Integrated Data Overview Choose Integrated Visualization to visualize a set of tracks obtained from one tracking session (trial), together with video, external data (if applicable), and plots of your dependent variables (including manually scored behaviors and external data). This function is particularly useful when you want to compare tracks with the corresponding video. Important: You can visualize up to 200 plots at the same time. If the number of subjects/arenas times the number of dependent variables currently selected exceeds this limit, filter the subjects or arenas in your Data Profile, or remove some dependent variables from your Analysis Profile. Prerequisite Make sure that the dependent variables you want to plot are specified in the active Analysis Profile. To Plot Integrated Data - Choose Analysis > Results > Plot Integrated Data, or in the Experiment Explorer, under Results, click Integrated Visualization. - On the toolbar, choose the Track Smoothing profile, the Data Profile, and the Analysis Profile that you want to use. - On the toolbar, choose the selection result and the trial you want to visualize. By default, the first trial is selected. To select the next/previous trial, click the buttons next to the drop-down list. The selection result list is available if your current Data Profile includes two or more selection results. - Optionally, customize tracks and plots. - View and interpret variable plots. Notes - In the Integrated Visualization screen you can also find one or more External Data plots, depending on how many external data files have been imported in that trial. - Not all playback speeds might be available. Depending on the video format, you may not be able to play the video at a specific speed. - If your data selection contains nesting criteria, all samples are plotted but the samples excluded by nesting are shown shaded. - You can visualize up to 200 plots per trial. If the number of dependent variables in your Analysis Profile times the number of subjects/arenas exceeds this limit, a message informs you that not all charts are visualized. Filter the subjects/arenas in your Data Profile, or remove some variables in your Analysis Profile. - The begin time in the video window is the time of the first sample acquired in all arenas. - The end time in the video window is the time of the last sample from all arenas. Within each arena, the last sample is marked by the message End of Track over the top-left corner of the corresponding arena. - For multi-arena setups, the tracks are synchronized; that is, samples of different arenas visualized at a given moment were acquired at the same absolute time. --- ## EthoVision XT 19 - Visualize Data - Heatmap Colors URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-heatmap-colors Chapter: EthoVision XT Heatmap Colors Color Range In the Heatmap Settings pane, click the Colors tab. Under Select range, select one of the five color ranges: - From dark blue to dark red (default). - From dark blue to white. - From green to red. - A custom range where the end colors can be changed. - A custom range where the end and middle colors can be changed. For the last two options, to change a color, click the corresponding button and choose the color you require. The end colors represent the minimum and the maximum density of data points per pixel. Whether the colors represent the same value in different heatmaps depends on what you choose as Color level (see below). Color Level In the Heatmap Settings pane, click the Colors tab. Under Color level, specify how the color range is mapped to the range of location frequencies between different heatmaps, and according to what variable: - Per heatmap. When you choose this option, the colors are mapped to the range of density of points in each heatmap separately. This means that a specific color may represent different densities of points in different heatmaps. Choose this option to compare the utilization of space within heatmaps. - Over heatmaps. When you choose this option, the colors are mapped to the global range of density of points, calculated over all the heatmaps plotted on your screen. This means that a specific color represents the same density of points in different heatmaps. Choose this option to compare the utilization of space between heatmaps. When you choose this option: - The maximum color (e.g., dark red) is only displayed in the heatmap(s) with the highest absolute value of point density. - The way heatmaps will look also depends on what Merging method for heatmaps you choose. - What (level) - Heatmap Color Per Variable. In addition to the track density heatmap, which shows how often the animal visited each location, EthoVision XT offers parameter heatmaps. A parameter heatmap displays the average value of a selected parameter (e.g., velocity or distance moved) at each location in the arena, color-coded from low to high. This lets you explore spatial patterns in behavior beyond mere presence, for example, where in the arena the animal moved fastest. A Gaussian smoothing option is available to produce a visually gradual color gradient. However, when data is sparse, smoothing can distort the visualization: isolated high-value locations may be suppressed while dense low-value areas become amplified, giving a misleading impression of where extremes occurred. For accurate interpretation, consider using no smoothing or a low smoothing level. The unsmoothed view always reflects the true recorded values. Parameters with negative values (such as turn angle) are fully supported; a separate validity mask ensures that locations without data are excluded from the visualization and from the smoothing calculation. Color Smoothing With Smoothing, you can specify the distance around a point at which the influence of the point will be felt when determining the color. Larger values result in greater smoothing, but smaller values may show finer details and variation. - In the Heatmap Settings pane, click the Colors tab. - Under Smoothing, choose the smoothing intensity (range 1 to 125). Choose a small value when you work with small arenas, like in well plates, and when you want to view small-scale differences in location. Notes - If your trials include two or more arenas, the options Per heatmap/over heatmaps do not have an effect on the difference in the color mapping between arenas. However, the duration of the tracks in two different arenas may influence the heatmaps. See an example in Plot Heatmaps. - The value of Smoothing is the standard deviation of the Gaussian kernel density function centered on a sample. The heatmap is created by summing up the density functions for the selected data points. Smoothing also influences how many points are represented by a multicolor blob. For example, heatmaps created from two data points show: A: with Smoothing = 1 pixel. B: with Smoothing = 3 pixels. --- ## EthoVision XT 19 - Visualize Data - Merging Method for Heatmaps URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-merging-method-for-heatmaps Chapter: EthoVision XT Merging Method for Heatmaps Aim To specify how data of different tracks are merged in one heatmap. Procedure - Choose Analysis > Results > Plot Heatmaps, or in the Experiment Explorer, under Results, click Heatmap Visualization. - In the Heatmap Settings pane, click the Show/Hide tab. Choose one of the options under Merging Method. Cumulated Each sample in a track gets a weight equal to 1/sample rate. Therefore, the color of a pixel in the heatmap represents the total time that the subject's body point was at that location. Choose this option when you want to make a heatmap based on all the possible locations of the animals for a group of tracks. With this method, a subject's position is over-represented in tracks longer than others. Mean Each sample in a track gets a weight equal to 1/track length. The color of a pixel represents the average proportion of a track that is found at that location. Choose this option when you want to make a heatmap that represents the average distribution for that group, and you want to compare averages between two or more groups of tracks. Example: Consider two tracks, recorded at 25 samples/s. One track is 10 samples long, the other 1000 samples long. The total track duration is 1010/25 = 40.4 seconds. A subject's center point is found at location P two times in track 1 (= 20% of track 1), and 100 times in track 2 (= 10% of track 2). When the two tracks are merged: - With Cumulated, the color of pixel P represents a total time of (2 x 1/25) + (100 x 1/25) = 4.08 s. This means that, in total, 4.08 s / 40.4 s = 10.1% of the data points are at that location. The longer track has a greater weight in this calculation. - With Mean, the color of pixel P represents [(2/10) + (100/1000)] / 2 = 0.15 = 15% of the track duration. This means that on average, 15% of the data points are at that location. Short and long tracks have the same weight in this calculation. Notes - Merging makes sense when two or more tracks share the same value of an independent variable chosen as a header. For example, two tracks with the same Treatment level = Control. If Control is one of the headers, the two tracks contribute to the same heatmap. Customize the Heatmaps Aim To choose which text, arena feature or background image to be displayed with the heatmaps. How to Access These Options Click the Show/Hide button on the toolbar. Show and Hide the Overlay Text To facilitate orientation in a heatmap matrix, you can display the value of independent variables used to arrange the heatmaps, and the number n of tracks used to create the current heatmap: Merged heatmaps: [n]. - From the Show/Hide menu, select Text Features. - Under View, select Show information if you want to see overlay text over the heatmap. - Under Text properties, choose the text Fill color and Opacity. Note: Even when selecting Show information, the overlay text is not shown if that information is redundant. For example, independent variables are not shown when the heatmaps have headers; for the same reason, the Merged heatmaps: [n] text is not shown when heatmaps are based on single tracks. Show and Hide Arenas, Zones and Points - From the Show/Hide menu, select Arena Features. - In the Arena Features window, choose the arenas, zones, zone centers and points of interest you want to view over the heatmap. - Select the feature outline color. Next, click OK. Note: Arenas and zones are displayed as outlines, not semi-transparent regions like in the Track Visualization. Zone centers and points of interest are displayed as crosses. Customize the Background of the Heatmap - From the Show/Hide menu, select Background. - Choose one of the following options: - Plain - by range minimum to have a uniform background that is the same as the color for the minimum value in the heatmap. To change the color, click the Colors tab in the Heatmap Settings window and change the option under Display. - Plain - custom to have a uniform background. Click the button next to this option to select a color. To select colors other than the basic ones, click the button Other. - Captured image to have the image captured in the Arena Settings as a background. If a heatmap is based on tracks with different Arena Settings, it is displayed with the background in the color currently selected next to Plain - custom. Zoom the Heatmap In/Out You can find the Zoom in (Ctrl+.) and Zoom out (Ctrl+,) buttons on the toolbar. To fit all heatmaps on the screen, click the Fit all button. To zoom in/out to predefined percentages, from the Show/Hide menu, select Zoom level, and choose one of the values available (6% to 800%). --- ## EthoVision XT 19 - Visualize Data - Multiple Selections in a Data Profile URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-multiple-selections-in-a-data-profile Chapter: EthoVision XT Multiple Selections in a Data Profile You can create different data selections in the same Data profile. Each sequence of boxes must end in a separate Result box. When you analyze the data using that Data profile, the results (statistics, track plots, or heatmaps) are displayed for each selection separately. Tip: With large data sets, you may have a large number of possible data selections. Create multiple Data profiles, each specifying one of those selection criteria, and then run batch calculations for each combination between Data profiles and Analysis profiles. Example: Tracks have been recorded for a number of animals at Day after treatment 1 and 2. Day after treatment is an independent variable. You want to calculate statistics for the two groups separately, but also with all tracks pooled together. Connect each Filter sequence to a separate Result box. To add a Result box, click the button next to Result in the Components pane. The first Result box receives the data after filtering with the independent variable Day after treatment = 1. The second Result box receives the data after filtering with Day after treatment = 2. The third Result box receives all data. The statistics are calculated separately for each criterion. Tip: Click the Settings button in a Result box to change its name. Enter a name associated with the selection (for example, "Day 1"). You will see this name in the results table. In the analysis results, you can see which output is produced by which Result box. Look up the Result header. See Also - Analyze Groups of Tracks Visualize Data Main Topics and Tasks - Introduction to Data Visualization - Plot Tracks - Plot Heatmaps - Plot Integrated Data - Customize Tracks and Plots Introduction to Data Visualization Learn About - Important Terms in Data Visualization - Useful Things to Know in Data Visualization Important Terms in Data Visualization Track Plot Visualization of one or multiple trials, where the subject's position is displayed over a static (background) image. Use track plots to visually inspect trials and compare the effect of experimental treatments. - See Plot Tracks Heatmap Visualization of one or multiple trials, where the density of sample points is represented as a color. It is useful to find hotspots. - See Plot Heatmaps Integrated Data Combines visualization of tracks with video (when present), and dependent variables and external data (when present) plotted against time. - See Plot Integrated Data Useful Things to Know in Data Visualization To Visualize the Data Do one of the following: - Choose Analysis > Results > one of the options Plot Tracks, Plot Heatmaps, or Plot Integrated Data. - In the Experiment Explorer, under Results, click Track Visualization, Heatmap Visualization, or Integrated Visualization. To Visualize a Specific Data Set On the toolbar, choose the Track Smoothing profile, Data Profile and Analysis Profile, and a trial (for Integrated visualization). To Customize Track Colors, Data Points, Etc. Choose the options on the right-hand pane. - See Customize Tracks and Plots To Customize the Elements on Your Screen Click the Show/Hide button at the top-right corner and choose the options you require. - See Customize Tracks and Plots To Move and Resize Windows - To move a window, click its title bar and drag it to the desired position. You can either dock a window or let it float on the screen. - To resize a window, point with your mouse to the window's left or top margin so the mouse pointer turns to a double arrow. Drag the margin to the desired position. Plot Tracks What Do You Want to Do? - Plot Tracks - Sort Track Plots - View and Play Back Tracks - Export Track Plots Plot Tracks Aim Choose Track Visualization to visualize a set of tracks. This function is particularly useful when you want to have an overview of your data acquired so far. If you want to visualize data from one specific trial together with video or external data, see Plot Integrated Data. Procedure - Choose Analysis > Results > Plot Tracks, or in the Experiment Explorer, under Results, click Track Visualization. - On the toolbar, choose the Track Smoothing profile and the Data profile that you want to use. The two profiles define the samples to plot. - See Customize Tracks and Plots. Notes - If you want to plot tracks in colors depending on the value of a dependent variable, like velocity, make sure that that variable is defined in one of the Analysis profiles. Then, repeat the steps above and choose the correct Analysis profile. - If your data selection contains nesting criteria, all samples are plotted, however the samples excluded by nesting are displayed in a different color. - You may sometimes get the following message: You have recorded data with more than one Arena Settings, and the layout of the plot matrix is such that tracks obtained with different Arena Settings are expected to be plotted in the same plot. Add the independent variable Arena Settings to the layout (see Sort the Track Plots by a New Variable). Alternatively, in your Data profile filter data from one of the Arena Settings. - Sometimes a variable number of cells in the plot matrix are empty. This is caused by the fact that there are no tracks corresponding to the values of the independent variable specified in the plot headers. To create a more compact matrix, choose a different set of independent variables to sort track plots (see Sort Track Plots). --- ## EthoVision XT 19 - Visualize Data - Plot Heatmaps URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-plot-heatmaps Chapter: EthoVision XT Plot Heatmaps Notes on Image Resolution and Formats The available image resolutions depend on the aspect ratio of the original background pictures. The zoom level chosen for the plots affects the default resolution. Available Image Formats - Portable Network Graphic (*.png) (default). A picture format using lossless compression. - JPEG file (*.jpg). A compression format for color images, particularly photographs. It can reduce file sizes to about 5% of their original size, but some detail might be lost in the compression. - Windows Bitmap (*.bmp). A non-compressed format generally resulting in large files. - Graphics Interchange Format (*.gif). A lossless format limited to 256 colors. This makes the GIF format suitable for storing graphics with relatively few colors such as simple diagrams. Heatmaps in EthoVision XT What Are Heatmaps? A heatmap is a graphical representation of the subject's position in the 2D space where the density of utilization of a specific place is represented as a color. Heatmaps facilitate identification of "hotspots" and clustering of data points. Choose Heatmap Visualization to generate heatmaps. You can generate a heatmap for single tracks or groups of tracks, and sort heatmaps according to various criteria. You can combine heatmaps with data selection to visualize, for example, the subject's position while it shows a specific behavior. Finally, you can export heatmaps to a high-resolution graphics file. How Are Heatmaps Created? In EthoVision XT, a track is a group of sample points, each with x and y coordinates. If one sample is found at specific coordinates, the frequency (= number of samples) for the corresponding pixel in the video image is 1. If more samples are found exactly on that pixel, for example when the subject returns to the same location, or when it sits still for some time in that location, then the frequency for that pixel is higher: 2, 3, 4, etc. Important: Here by frequency we mean the number of samples that are found on a specific pixel, not the number of entries in a zone or the like. The number of samples can be plotted in a 2D histogram, where the length of each column indicates how much time the body point of the subject was found exactly at that location. The heatmap is created from that histogram, based on the concept of kernel density estimation. At each pixel, the probability is calculated to find the subject at that specific location. The density function states that there is some (lower) probability to find the subject also in the surroundings of the focal pixel. This can be represented with a bell-shaped three-dimensional curve. The kernel density function is calculated at each location. The single 3D bell curves for neighboring locations are merged together, resulting in higher and wider curves. However, heatmaps in EthoVision XT are a 2D representation of the hilly landscape that results from the kernel density estimation. It is like viewing the hills and valleys from the top. The colors represent the altitude of the landscape. In EthoVision XT, the colors may represent the cumulative time in a particular pixel, or the fraction of the track that is found at that pixel. This depends on what you choose under Color Level. Examples of Heatmaps Morris Water Maze Test In this example, we compare the swim pattern between two groups of rats in probe trials. The young rats (right) display more focused search than the old ones (left). Zebrafish in a Novel Tank Diving Test In this example we want to show the bias toward top-swimming after the fish was treated with an anxiolytic drug. The two zones, Top and Bottom, are outlined in white. Novel Object Recognition Test In this test the subject explores two objects, one familiar and one novel. The heatmap clearly shows the difference in the "density" of location points around the two objects. The two object zones are outlined in white. Mosquito in a Wind Tunnel A mosquito tends to reach the odour source located behind the upwind screen of the flight chamber. The middle of the screen is indicated with a cross. Notes - Be careful when interpreting color heatmaps. First, the colors lack the natural perceptual ordering found, for example, in gray scale color maps. The changes between colors lead to perception of gradients that are not actually present, making actual gradients less prominent. --- ## EthoVision XT 19 - Visualize Data - Set a Specific Time Span URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-set-a-specific-time-span Chapter: EthoVision XT Set a Specific Time Span The time span is the duration of the time visible in the time axis at any moment. To set a specific time span, click the Show/Hide button on the toolbar, then click Time Span and select one of the values available (minimum 5 sec; maximum 1 hour). Note: The available values depend on the length of your trial. For example, if your trial is 10 minutes long, the 30 minutes and the 1 hour options are not available. Zoom the Y-Axis In/Out You can adjust the range of values for continuous variables (dependent variables and external data). If you have two or more continuous data plots, the variable scale changes only for the plot you have clicked. - Do one of the following: - Click the Zoom In button or the Zoom Out button on the toolbar. - Right-click the plot and select Zoom In or Zoom Out. The mouse pointer turns to a magnifier symbol. - Click the y-axis scale one or a few times. - To stop zooming in/out and return to the normal mouse pointer, click the No Zoom button on the toolbar, or right-click the plot and select No Zoom. Every time you zoom in/out, the plot scale is enlarged or reduced by a factor of 2. Tip: To zoom in/out the y-axis in all plots, hold the Ctrl and Alt keys down and scroll with the mouse wheel. Customize the Dependent Variable Plots Show and Hide the Plots Click the Show/Hide button, select Dependent Variables and then choose the items you want to display. By default, all external data files are selected for that trial unless the associated tracks have been filtered out in the Data Selection. Sort the Plots You can change the order in which data plots are displayed by dragging them up and down on the screen. - Click the leftmost column next to the plot you want to move. The cursor changes and the plot border is highlighted in red. - Drag the plot up or down to the position you require. Release the mouse button to insert the plot. You can also sort plots by dependent variable, subject name, or arena name. To do so: - Click the Show/Hide button, then select Chart Sorting. - In the Chart Sorting window, if there are multiple sorting factors, like dependent variables and arena names, choose them under Sort Order. - Under Variable Order, click the arrow buttons to sort the dependent variables. Change the Color of a Plot - Click the square symbol next to the name of the body point, subject, or behavioral state. Alternatively, click next to the data line (for numerical variable plots) or the color bar (for the discrete variables). - In the Color window, choose a new color and click OK. Note: For color bars, you can also choose a hatch pattern. Show and Hide the Data Points Click the Show/Hide button on the toolbar, and select or deselect Show Graph Data Points. Specify the Time Mode You can choose to display time values on the x-axis as elapsed time, remaining time (that is, time to the end of the trial), or the actual time. - Right-click the top-left corner of the chart with the time label. - Select one of the following: - Relative Time. The time elapsed since the start of the trial. The 0:00:00.00 time on the far left side corresponds to the start of the trial. - Remaining Time. The time to the end of the trial. The 0:00:00.00 time on the far right side corresponds to the end of the trial. - Absolute Time. The actual date and time the trial was acquired (for example 11/13/2017 16:29:30.00). External Data Plots External data are shown in the form of X-Y plots. The start and end time of the tracks does not always coincide with the start and end time of the co-acquired external data. When you visualize the integrated data, you can only view the external data acquired in the same time interval as the tracks associated with the external data file. External data samples acquired before the start and after the end of the tracks are not plotted. The hairline shows the current video/track position. The current value of heart rate is shown next to the data set name. By default the external data are not plotted in the Integrated Visualization. Plot the Original Signals - Choose Show/Hide > Dependent Variables. - Select the [data set name] (original signal) that you require. By default the original signal is plotted in green. Plot the Resampled Signals - Define the resampled signal in the Analysis profile. See External Data (Resampled). - Choose Analysis > Results > Integrated Visualization. By default, resampled signals are plotted in red. - Select Show/Hide > Show Graph Data Points to better view the original and resampled signals. - If you upsample a signal with a sample rate much lower than the EthoVision sample rate, and you choose Missing Value as the Upsampling method, it may be difficult to see the data points. Choose Show/Hide > Show Graph Data Points and zoom in the plot. Synchronize the External Data with the Tracks Click the Synchronize External Data button. Either change the Start Date and Time and Stop Date and Time, or move the external data plot to the correct position. For details, see Synchronize Data Manually After Import. The Plot's Titles The titles are shown at the left of the plots and vary according to what level the external data have been linked at. - If linked to the subject level, the title shows the Arena and Subject names. - If linked to the arena level, the title shows the Arena name. - If linked to the whole trial, the title is not shown. --- ## EthoVision XT 19 - Visualize Data - Sort Track Plots URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-sort-track-plots Chapter: EthoVision XT Sort Track Plots Aim Track plots are displayed in the form of a matrix. You can sort rows and columns according to one or more independent variables. Example: Subjects of both sexes were assigned to two different treatment levels (drug or saline). You want to visualize tracks according to Subject sex (on the rows) and Treatment (on the columns). By default, plot headers do not include the name of an independent variable and the variable's value for that row/column. To show the variables' name, right-click a header and select Show Name. The values of the variables and the resulting sorting order are not removed. To hide the variables' name, right-click the header and deselect Show Name. Sort the Track Plots by a New Variable Do one of the following: - Click the Show/Hide button on the toolbar, and select Layout. In the Layout window, select Arrange by headers. Under Available, click the variable you want to use. Next, click one of the buttons next to On Columns or On Rows, depending on whether you want to sort columns or rows by that variable. - Right-click the header of a column or a row, depending on where you want to place the new variable. Next, select Insert. In the Select Independent Variables to Insert window, from the Independent Variable Name list, select the variable you want to use, then click OK. Note: The variable list does not include the variables already present in the plot headers. Remove a Sorting Variable Do one of the following: - Click the Show/Hide button on the toolbar and select Layout. Click the variable name under On Columns or On Rows, and click the deselect button next to it. - Right-click a header for that variable and select Delete. If you remove all variables from one side of the matrix, the headers will be empty. All tracks are plotted on one row or column. Sort the Plots in Ascending or Descending Order By default, track plots are sorted in ascending order of the corresponding variables (numeric or alphabetic). - To sort variable values in descending order, right-click a header for that variable and select Sort Descending. - To sort variable values in ascending order, right-click a header for that variable and select Sort Ascending. You cannot change the plot order from the Layout window. Re-Arrange Multiple Sorting Levels When two or more variables are inserted or moved to the same side of the matrix, they form a multi-level structure. In the example below, plots are first sorted by Subject sex (top level), and then by Treatment (bottom level). To re-arrange sorting levels, do one of the following: - Click the Show/Hide button on the toolbar and select Layout. Click the variable you want to move. To move the variable one level up, click the Up button. To move the variable one level down, click the Down button. - Right-click a track plot header for a variable. To move a variable one level up, select Move up. To move a variable one level down, select Move down. Or click a header for that variable, and drag it to a lower or upper level. In the example below, the variable Treatment has been moved above Subject sex. As a result, plots are first sorted by Treatment, then by Subject sex. Swap Variables from Columns to Rows and Vice Versa You can re-arrange your plots by moving the variables shown in the rows to columns and vice versa. Do one of the following: - Click the variable name under On Columns or On Rows, and click the Place Horizontal or Place Vertical button. - Right-click a row/column header for that variable and select Place Horizontal or Place Vertical, or click a row/column header and drag it to a new position. View and Play Back Tracks Zoom the Track Plots In and Out The Zoom buttons are located on the toolbar. - To zoom in, click the Zoom in button or press Ctrl+. - To zoom out, click the Zoom out button or press Ctrl+, - To fit all track plots on the screen, click the Fit all button. To zoom in/out to predefined percentages, from the Show/Hide menu, select Zoom level, and choose one of the values available (6% to 800%). Customize the Length of Tracks See Customize the Elements and Length of the Tracks. Play Back the Tracks Click the buttons in the Playback Control window. See Playback Control, Acquisition and Visualization. View the Tracks in Multi-Arena Setups In trials with multiple arenas, all tracks are played back starting from the first sample. If the tracks started at different times in different arenas, the samples visualized at a given time refer to different real times in those arenas. To preserve the time difference between arenas, choose Integrated Visualization. In a multi-arena setup, data recording may start at different times in different arenas. When tracks are plotted together, their starting times are aligned. This means that samples visualized simultaneously for the two arenas may refer to two different moments in the real time line. Export Track Plots Export a Single Track Plot - Click the plot you want to export, so that its border becomes highlighted in red. - On the toolbar, click the Export image icon. - Under Export, choose Selected plot. - Select the image resolution in pixels. - Click Export. In the Export Image window, enter the name and location of your image file, choose the image format and click Save. Export Multiple Plots as Separate Files Each plot is exported as a single image file. - Hold the Ctrl key down and click the plots you want to export. If you do not make a selection, all plots will be exported. - On the toolbar, click the Export image icon. - Under Export, choose To separate image files. - Select the image resolution in pixels, and click Export. Export Multiple Plots as One File The matrix grid is exported as a single image file. - Select the plots you want to export. If you do not make a selection, all plots will be exported. - On the toolbar, click the Export image icon. - Under Export, choose To one image file. - Select the image resolution in pixels, and click Export. --- ## EthoVision XT 19 - Visualize Data - The Heatmap Color Scale URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-the-heatmap-color-scale Chapter: EthoVision XT The Heatmap Color Scale Aim To help estimate how much time the subject spent in a region of the arena. Because heatmaps create gradients by definition, they are not meant to accurately measure the time that the subject spent in a certain zone. For that, calculate the statistics for the variable In Zone. See Analysis Advisor. To Access This Option Choose Analysis > Results > Plot Heatmaps. Locate the scale at the right-hand side of the heatmap. Scale Maximum You find the maximum value at the top of the scale. It is expressed in: - Seconds, if you choose Cumulated as a merging method for heatmaps. - A fraction of the track duration, if you choose Mean as a merging method for heatmaps. To calculate the maximum, EthoVision XT finds the pixel of the heatmap with the highest number of recorded positions and calculates the total time spent in a circular area around that position. The circular area depends on the Color Smoothing that is currently set. The larger the smoothing value, the larger the circular area around the maximum, and the higher the value in the scale because more point locations around the "peak" pixel are included in the calculation. This correction is made because the highest absolute density of sample points (shown in dark red by default) is usually found in one or few pixels per track; taking only the cumulated time for those pixels would not provide a realistic estimate of the time spent by a subject in a certain location. Scale Minimum You find the minimum value at the bottom of the scale. This is always zero seconds (or fraction of the track duration). It represents the locations where the subject was never found. Notes - The scale is plotted independently for each heatmap. The maximum value only depends on the original data points that form that heatmap. - In order to make a good judgment when comparing heatmaps, make sure that the total track duration is the same or very similar between groups or subjects. - If you choose Over Heatmap as Color Level, the scale maximum also changes. For example, the maximum for that heatmap is represented with blue or green, not red. That happens because the overall maximum is found in other heatmaps. See Heatmap Colors. - If you choose Mean instead of Cumulated as a merging method for heatmaps, the maximum is expressed as a fraction of the total time that the subject was in that region. If the subject keeps moving across the arena, this value can be rather low, for example 0.01, meaning that the region of peak occurrence contained 1% of the positions. How to Plot Heatmaps Aim To create heatmaps from the tracks currently selected in the Data Profile. Procedure - Choose Analysis > Results > Plot Heatmaps, or in the Experiment Explorer, under Results, click Heatmap Visualization. - On the toolbar, choose the Track Smoothing profile and the Data profile that you want to use. The two profiles specify the set of samples to be used in the heatmaps. - In the Heatmap Settings pane, click the Show/Hide tab. Choose the Features (body points) and the Subjects to visualize. - Under Presets, click one of the buttons to arrange the layout. See Arrange Heatmaps. Under Merging, specify how EthoVision should normalize data of different tracks when putting them in a single heatmap. See Merging Method for Heatmaps. - Click the Plot Heatmaps button. - Optionally, customize the heatmaps. - Optionally, export the heatmaps. Notes - By default, heatmaps are displayed with overlay text and without arena and zone outlines. - If your video image includes two or more arenas, the heatmap is calculated across arenas, not per individual arena. This means that if the track in one arena has fewer samples than the track in another arena, the heatmap in the first arena is less likely to show high-density colors. This is generally not a problem in DanioVision or PhenoTyper experiments because the track duration is comparable between arenas. For other setups, compare heatmaps from different arenas only when the duration of the tracks is more or less the same, or export the tracks and create the heatmaps in an external application. - If you want to know where a behavior occurs, in your Data profile nest over that behavior (see Nesting over Behaviors Scored Manually or Nesting over Behaviors of Rat/Mouse Behavior Recognition), and then plot the heatmaps. - When you combine tracks from different arena settings, the corresponding heatmaps may have different sizes and aspect ratios. The tracks are first aligned at the upper-left corner before they are combined. Therefore, a specific point in the combined heatmap may represent different locations for different tracks. --- ## EthoVision XT 19 - Visualize Data - Trial Control Events Pane URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-visualize-data-trial-control-events-pane Chapter: EthoVision XT Trial Control Events Pane The Trial Control Events pane gives you an overview of the events that occurred during the trial as a result of the Trial Control Settings you specified. The first condition (the center-point of the mouse is in the arena for more than 2 seconds) is met after 2 seconds. At that moment the track is started. One minute later, the track is stopped. During playback, the hairline indicates the current position. Customize the Visualization of the Trial Control Events Pane By default, the Trial Control Events pane is shown in the lower right corner of the screen. Choose one of the following options to change the visualization of the pane: - To show the pane, click the Show/Hide button on the toolbar and select Trial Control Events. - To move the pane, click its title bar and drag it to the desired position. You can either dock the pane or let it float on the screen. - To resize the pane, point with your mouse to either the pane's upper margin or its left margin so the mouse pointer turns to a double arrow. Drag the margin to the desired position to have a larger pane. Alternatively, click the small black triangle in the upper right corner of the pane to have a full view of the pane and hide the Track Plot Settings pane. Export the Integrated Visualization Aim To export dependent variable plots in the form of image files. Procedure - Make sure that no other window is on top of the plots. Zoom the plots in/out to reach the level of detail you require for the export picture. - On the toolbar, click the Export Image icon. - In the Export Image window, enter the name and location of your image file. - From the Save As Type list, select one of the available formats, then click Save. See Also - Adjust the Time Scale (X-Axis) - Zoom the Y-Axis In/Out Create a Video from Your Data Aim To export the animated track and the plots of the dependent variables to a video file, for instance for presentation purposes. Procedure - Choose Analysis > Results > Integrated Visualization. - From the toolbar, select the Analysis profile that contains the variables to plot. - If you do not want the Track Plot Settings pane to be part of the screen capture, click the Show/Hide button on the toolbar and deselect Track Plot Settings. - Position the video where you want your recording to start, or click the Jump to Begin button to start from the beginning of the trial. - Click the Start Screen Recording button. - In the Screen Recording window, under Region, choose whether you want to capture the Video, Tracks and Plots or the Full Screen. Note that with Full Screen you also record the Experiment Explorer and the desktop (if visible). - Choose the Frame Rate (default: 25 fps) and the Resolution (default width: 1280). - Choose the video file Saving Location and File Name. - Click Start. - Play the video at the speed you require. - To stop screen recording, click the Stop Screen Recording button. Notes - If you choose Video, Tracks and Plots, the Track Plot Settings pane is also recorded. To remove this from your video, see step 3. - Video resolution is available in a number of steps. The values of width are 320, 480, 640, 800, 1024, 1280 (default), and 1600 pixels. The values of height are adjusted in each step, based on the Region option you choose and the current size of the EthoVision screen. - The video file is saved in DivX format; the file extension is *.mpg. - The suggested video file name is Screen Recording n, where n is a progressive number (0001, 0002, etc.). Customize Tracks and Plots What do you want to do? - Customize the elements and length of the tracks - Customize the track colors - Display background, arenas and zones Customize the Elements and Length of the Tracks Aim To optimize visibility of data points. To Access These Options Choose Analysis > Results > Plot Tracks or Plot Integrated Data. In the Track Plot Settings pane, click the Show/Hide tab. What do you want to do? - Show and hide body points - Adjust line thickness and dot size - Show and hide subjects - Show part of the track Show and Hide Body Points Under Features, select the following: - Nose-point (only for nose-tail tracking). - Center-point. - Tail-base (only for nose-tail tracking). Track Visualization Settings Body Points and Connectors The following display options are available for track visualization: - Connectors (only for nose-tail tracking) to display the line connecting the nose-point and the tail-base to the center-point. To view the body points, select the option under Sample next to that body point. To view the line connecting samples for a body point, select the Trail option next to that body point. The nose-point is always represented by a filled triangle, the center-point by a filled circle, and the tail-base by a filled square. You cannot change the shape of body points in your tracks. Adjust Line Thickness and Dot Size In the Show/Hide pane on the right, under Features, choose a value for: - Line thickness. This changes the thickness of the tracks and the connectors, that is, the segments joining the body point. - Dot size. This changes the size of the body points along the tracks. Show and Hide Subjects When you track multiple subjects in the same arena, under Subjects select the Visible option for the subjects you want to have displayed and clear the selection for the others. Show Part of the Track Under Filter, choose how many samples you want to display at the same time. - Last ... seconds. Choose this option to visualize only part of the track, for instance only the last 5 seconds. - Every ... sample. If the subject moves slowly, the samples are very dense. Choose this option to visualize, for example, every 5th sample. Tips - To show the entire track, deselect Last ... seconds and click the Jump to End button in the Playback Control window. - To show all samples in the track, select Every ... sample and enter 1. - To only show the last sample, select Every ... sample and enter 0 next to it. Make sure that in the Features box the option under Sample is selected for the body point you want to plot. --- ## EthoVision XT 19 - Weighted movement from URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-weighted-movement-from Chapter: EthoVision XT Definition The distance-weighted change in distance between subjects, when a subject (Actor) moves away from another subject (Receiver). Weighted movement from (WMF) is a continuous variable, and is always positive. It is calculated only when the state of the Actor is moving from the Receiver (see also Relative movement). Calculation Formula: - If Dk - Dk-1 > 0, then WMFk = (Dk - Dk-1) * abs(DSk - DSk-1) / (max(DSk, DSk-1)) - If Dk - Dk-1 ≤ 0, or DSk = 0, then WMFk = missing value - If DSk-1 > Maximum interaction distance, then WMFk = missing value Where: - Dk-1, Dk is the distance between the Actor's body point and the interpolated point of the Receiver calculated for two consecutive samples. - DSk-1, DSk is the distance between the subjects' body points for two samples. In the figure below, A is the body point of the Actor, R of the Receiver. Q is the interpolated position between the Receiver's body points at samples k and k-1. Notes - Weighted movement from is equal to the absolute value of Net weighted movement, taken for those samples in which the value of NWM is negative (the focal subject moves away from another subject). - Weighted movement from is weighted by the distance between two subjects. Changes in positions of subjects which are at a large distance from each other have a lower weight, so they can be distinguished from movements at close distance, which have a different biological meaning. - From the figure above one can see that the outcome depends on which of the two interacting subjects is considered as Actor and which as Receiver. This is because the formula takes possible differences in speed of approach of the subjects into account. In that case, the difference Dk - Dk-1 is positive, therefore Weighted movement from R is calculated. If R was the Actor, the point Q would be defined for the other subject in the middle of the Ak-1–Ak segment. In that case Dk would be shorter than Dk-1, thus Dk - Dk-1 < 0, and the dependent variable would not be calculated. - This dependent variable is not a speed, as time is not involved in its calculation. However, the parameter is quadratically sensitive to movement of the subject. How to Specify Weighted Movement From - Click the Add button next to Weighted movement from. - In the Weighted movement From tab, under Maximum interaction distance, enter the distance above which you do not want to consider the subjects as interacting. (Default: 50 cm / 16.69 inches) - Click the Body points tab. Select the body points of the focal subject (Actor) you want to use to calculate the dependent variable. If you select two or three points, results are calculated for each point separately. - Click the Receivers tab. - Under Select, choose the subjects you want to consider as Receivers. - Under Body points, select the body points of the subjects selected above. If you select two or more subjects and points, results are calculated for each combination separately. - Complete the procedure to add the variable. See Calculate statistics: procedure. Additional Notes - Weighted movement from is calculated for all the subjects selected in the Data profile. Each subject displayed on the rows of your result table is considered as Actor. The subjects displayed on the columns are the Receivers. - If your experiment is set to Only center-point detection or Color marker tracking, the body point options are absent. Calculations are based on the center point. Application Weighted movement from can be used as an objective measure for the intensity of avoidance (Spruijt et al. 1992. Physiology & Behavior, 747–752). Leaving A discrete (state event) variable that is scored when the subject (Actor) moves away from a conspecific (Receiver) within the specified distance. The angle between the actor's center-nose vector and the receiver's center point is less than specified. The actor is moving at a velocity higher than the specified value. Parameters: - Minimum distance — The minimum distance between actor and receiver. - Maximum distance — The maximum distance between actor and receiver. - Maximum orientation angle — The maximum allowed angle between the actor's center-nose vector and the direction toward the receiver. - Minimum velocity of actor — The actor must move at least this fast. - Minimum velocity of receiver (Advanced) — Minimum receiver velocity threshold. - Maximum velocity of both subjects (Advanced) — Upper velocity limit for both subjects. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Weighted movement to URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-weighted-movement-to Chapter: EthoVision XT Definition The distance-weighted change in distance between subjects, when a subject (Actor) moves towards another subject (Receiver). Weighted movement to (WMT) is a continuous variable, and is always positive. It is calculated only when the state of the Actor is moving to the Receiver (see also Relative movement). Calculation Formula: - If Dk - Dk-1 < 0: WMTk = (Dk-1 - Dk) * abs(DSk - DSk-1) / (max(DSk, DSk-1)) - If Dk - Dk-1 ≥ 0, or DSk = 0: WMTk = missing value - If DSk = 0, and DSk > Maximum interaction distance, then WMTk = missing value Where: - Dk-1, Dk is the distance between the Actor's body point and the interpolated point of the Receiver calculated for two consecutive samples k-1 and k. - DSk-1, DSk is the distance between the subjects' body points for two samples (see Distance between subjects). Notes - Weighted movement to is equal to the absolute value of Net weighted movement, taken for those samples in which the value of NWM is positive (the focal subject moves towards another subject). - Weighted movement to is weighted by the distance between two subjects. Changes in positions of subjects which are at a large distance from each other have a lower weight, so they can be distinguished from movements at close distance, which have a different biological meaning. - The outcome depends on which of the two interacting subjects is considered as Actor and which as Receiver. If R was the Actor, the point Q would be defined for the other subject (A in the figure) in the middle of the segment joining the two consecutive body points. In that case Dk would be longer than Dk-1, thus Dk - Dk-1 > 0 (i.e., R moves away from A), and the Weighted movement to would not be calculated. Instead, Weighted movement from would be calculated. - This dependent variable is not a speed, as time is not involved in its calculation. However, it is quadratically sensitive to movement of the subject. How to Specify Weighted Movement To - Click the Add button next to Weighted movement to. - In the Weighted movement To tab, under Maximum interaction distance, enter the distance above which you do not want to consider the subjects as interacting. (Default: 50 cm/16.69 inches) - Click the Body points tab. Select the body points of the focal subject (Actor) you want to use to calculate the dependent variable. If you select two or three points, results are calculated for each point separately. - Click the Receivers tab. - Under Select, choose the subjects you want to consider as Receivers. - Under Body points, select the body points of the subjects selected above. If you select two or more subjects and points, results are calculated for each combination separately. - Complete the procedure to add the variable. See Calculate statistics: procedure. Additional Notes - Weighted movement to is calculated for all the subjects selected in the Data profile. Each subject displayed on the rows of your result table is considered as Actor. The subjects displayed on the columns are the Receivers. - If your experiment is set to Only center-point detection or Color marker tracking, the body point options are absent. Calculations are based on the center point. Application Weighted movement to can be used as an objective measure for the intensity of avoidance (Spruijt et al. 1992. Physiology & Behavior, 747-752). Following A discrete (state event) variable that is scored when the subject (actor) follows a conspecific (receiver) within the specified distance. The actor's nose is oriented toward the receiver's center point within the specified angle. Both animals move faster than the specified value. Parameters: - Minimum distance — The minimum distance between the two subjects. - Maximum distance — The maximum distance between the two subjects. - Maximum orientation angle — The maximum allowed angle between the actor's center-nose vector and the direction toward the receiver. - Minimum velocity of both subjects — Both subjects must move at least this fast for the event to be scored. - Maximum velocity of both subjects (Advanced) — Upper velocity limit for both subjects, to exclude fast transient crossings. Side by Side Definition The focal subject is side-by-side with another subject. The latter is named receiver in EthoVision XT. Two categories are defined, based on how the subjects are oriented relative to one another: - Same direction: the focal subject and the receiver are side by side and pointing to the same direction. - Opposite direction: the focal subject and the receiver are side by side and pointing to different directions. This variable is available in experiments set to Center-point, nose-point and tail-base detection. See Tracked Features. Side by Side Calculation - For Side by side, same direction: - EthoVision XT finds the samples where both the distance between the nose-point of the focal subject and the nose-point of the receiver and the distance between the tail-base point of the focal subject and the tail-base point of the receiver are below the specified threshold (default: 5.26 cm). - If the two vectors formed by the tail-base point and the nose-point of each subject point to the same directions (that is, the dot product of the two vectors is positive), then Side by side, same direction is scored for that sample. - For Side by side, opposite direction: - EthoVision XT finds the samples where both the distance between the nose-point of the focal subject and the tail-base point of the receiver and the distance between the tail-base point of the focal subject and the nose-point of the receiver are below the specified threshold (default: 5.26 cm). - If the two vectors formed by the tail-base point and the nose-point of each subject point to opposite directions (that is, the dot product of the two vectors is negative), then Side by side, opposite direction is scored for that sample. How to Specify Side by Side - Open an Analysis profile and in the Dependent Variables panel, under Social, click the Add button next to Side by side. - Under Threshold, enter the maximal In proximity distance acceptable between the two subjects' body points (nose to nose or nose to tail-base). - Under Calculate statistics for, select the option Side by side, same direction, or Side by side, opposite direction, or both. - Complete the procedure to add the variable to the Analysis profile. See Calculate statistics: procedure. Side by Side Note Side by side is similar to Proximity, however the latter cannot tell whether the subjects are oriented in the same or different directions. See also: - Proximity Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Welcome to EthoVision XT - Applications and Add-Ons URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-welcome-to-ethovision-xt-applications-and-add-ons Chapter: EthoVision XT Applications and Add-Ons See Also - Choose Your Camera - System Requirements - The Test Environment Feature Limits - Multiple Body Point Module (Live Tracking): Maximum four arenas per computer. In principle it is possible to track in more than four arenas, but it depends on the apparent size of the subjects in the video image (in pixels). Sample rate must be 25 samples/s or higher. - Multiple Arena Module: Maximum 100 arenas. The number of arenas may be limited by other factors, for example the number of subjects in each arena and the tracking of multiple body points. Contact Noldus if you wish to work with more than 100 arenas. - Social Interaction Module: Maximum 16 subjects per arena. If subjects are unmarked, there may be subject identity swaps. - CognitionWall (Sylics): Four arenas, only center-point tracking; up to 72 h recording. In case of recordings longer than 24 h, we advise to restart the PC after each trial. A workstation is required. - Behavior Recognition: One subject per arena; one arena (live tracking), up to four arenas (offline tracking). Requires the Multiple Body Point module. Camera must be overhead. Camera frame rate must be at least 25 fps with no missing frames. Cannot work together with Deep Learning-Based Tracking. The PC must be a workstation. See Behavior Recognition: Requirements. - Deep Learning for Nose-Tail Base Tracking: One or two subjects per arena (up to four arenas). See Deep Learning: Requirements. For More Information Manuals For all other manuals, open the Windows Start menu and choose All Apps > Noldus > EthoVision XT 19 Other Documentation. For EthoVision XT: - EthoVision XT 19 - Quick Start Guide - English.pdf. Recommended when you use EthoVision XT for the first time. The Quick Start Guide is also available in Simplified Chinese, German, French, Italian, and Spanish. - EthoVision XT 19 - Application Manual.pdf. This manual shows you how to use EthoVision XT with standard tests like the Morris Water Maze test, the Novel Object test, and the Sociability/Social Novelty test, but also complex setups like Optogenetics and Calcium Imaging. - EthoVision XT 19 - Trial and Hardware Control - Reference Manual.pdf. An extensive manual about controlling external devices and creating complex routines within EthoVision XT. For PhenoTyper: - PhenoTyper - EthoVision XT 19 - Reference Manual.pdf - PhenoTyper - EthoVision XT 19 - Service Manual.pdf For DanioVision: - DanioVision DVOC-0041 - EthoVision XT 19 - Reference Manual.pdf You can also find all manuals on the MyNoldus portal. Sample Experiments On the download page of EthoVision XT you can find all the documentation listed above and sample experiments. Open a sample experiment to see how a specific test, for example the Morris Water Maze test or the Novel Object Recognition test, is conducted in EthoVision XT. Log in to the MyNoldus portal, click Downloads, then EthoVision XT, and then Sample Experiments. Note that to access the MyNoldus pages you must register and log in. Help Menu Choose Help > ... to access the following options: - Help Topics. Opens this Help. - Video Tutorial. The Video Tutorial explains how to set up an experiment in EthoVision XT and shows useful examples of how to adjust various settings. - Noldus Online. If your computer is connected to the Internet, you can choose this option to go to the EthoVision XT home page, check for updates, contact Noldus Support, or consult the EthoVision XT knowledge base. If you encounter a problem with EthoVision XT, choose Report an Issue. The EthoVision XT home page contains all kinds of information about the program as well as examples of how EthoVision XT is used. - Upgrade. See Upgrade EthoVision XT. - About EthoVision XT. Choose this option to see details of exactly which version of EthoVision you are using, the end-user license agreement, and the copyright notices for third-party software. Information Messages In some parts of the program you see an "i" icon next to specific features. Click the icon to learn more about that feature. --- ## EthoVision XT 19 - Welcome to EthoVision XT - Noldus Support URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-welcome-to-ethovision-xt-noldus-support Chapter: EthoVision XT Noldus Support If you have any problems, questions, remarks, or comments, please contact Noldus Support. We offer 24-hour support in various time zones. Before you contact Technical Support, please have the following information available. To find this information, go to the Help menu and select About EthoVision XT: - The version number of your copy of EthoVision XT. - The name of the registered user of EthoVision XT (click License Info). - The license number of your copy of EthoVision XT (click License Info). Our Technical Support department may request a log file and/or a dump file when answering your support question. Please see File Locations. Make a PC Report for Support This section is needed if Noldus Support has asked you to send a PC report for the EthoVision XT computer. - Download the SIW utility as indicated by Noldus Support and save it to the EthoVision XT computer. - Double-click on the file called siw64.exe. - Choose File > Create Report File > HTML Report. - Save the HTML file to your Desktop. - Send the HTML file as an e-mail attachment to Noldus Support. Send Video Material to Noldus In order to provide adequate support, it is possible that we request you to supply us with video recordings made by your organization. Since May 25th 2018 the new GDPR rules apply to all people in the EEA (EU plus Norway, Iceland, and Liechtenstein). For this reason we need your signed consent that you agree with the fact that you have given us permission to use these video recording(s). Please be aware that the person(s) who are recognizable in the video also have to give consent that the video is sent to Noldus Information Technology BV and our technology partners, and that it is your responsibility to arrange this consent. More information regarding our Privacy Policy can be found on the Noldus website. NoldusCare Your license of EthoVision XT comes with a standard service package of one year. This includes a one-year period of free technical support. With NoldusCare you make sure that you work with the latest version of your software, based on input from our worldwide customer base. Updates, upgrades, and new releases are available for free, as well as update meetings where you can discuss new features with a Noldus consultant. For more information, log in to the MyNoldus portal and select NoldusCare. The EthoVision XT Screen Screen Components The EthoVision XT interface is made of three main elements: the menu bar (A), the Experiment Explorer (B), and the Working Area (C). When you click an item in the Experiment Explorer, the Working Area shows the elements related to that item. Use the Show/Hide button at the top-right corner to specify which windows and other elements in the Working Area you want to show. Menu Bar Throughout this Help, instructions like "Choose File > Open..." refer to menu items. The three menus Setup, Acquisition, and Analysis contain the same functions as the Experiment Explorer. With the View menu you can show or hide the Standard Toolbar, the Experiment Explorer, and the Status Bar. The Experiment Explorer The Experiment Explorer helps you keep an overview of your experiments, including your data and the settings used for tracking. It consists of three main items: Setup, Acquisition, and Analysis. - Expand and Collapse. Click an item to view its components. - View or Hide. By default, the Experiment Explorer is visible. To hide it, choose View and deselect Experiment Explorer. - Auto Hide. You can minimize the Experiment Explorer by clicking the Auto Hide button in its upper-right corner. To expand the Experiment Explorer again, hover with your mouse over the minimized Experiment Explorer in the upper-left corner of your screen. To expand it permanently, click the Auto Hide button once more. - Right-Click Menus. Most items in the Experiment Explorer have right-click menus to access key functionality, for example to create a new settings profile. Other Tools The Working Area shows specific toolbars which depend on the function that is currently open. For example, when you open the Arena Settings, this toolbar includes the tools for drawing arenas and zones. The Standard Toolbar includes icons for basic functions like creating and opening experiments, saving, and copying and pasting. To view the Standard Toolbar, choose View > Standard Toolbar. The Status Bar is located at the bottom of the screen. It gives information about the status of some keyboard keys: Caps Lock, Num Lock, and Scroll Lock. To view the Status Bar, choose View > Status Bar. Customize Your EthoVision XT Screen To Show and Hide Windows and Other Elements Click the Show/Hide button at the top-right corner of the screen. The menu options that appear are related to the current phase of the experiment. For example, during acquisition, choose Show/Hide > Detection Features and choose in which colors to show the subject being tracked. To Position and Resize the Windows By default, all the windows on your screen are docked. You can change their position and resize them according to your needs. To re-position a window, click its title bar and drag it to the new position. To undock a window, click its title bar and drag it anywhere until you see its margins no longer constrained by other windows. Docking icons appear to show you where you can position the undocked window. Source: EthoVision XT 19 Help - Welcome to EthoVision XT, Noldus Information Technology --- ## EthoVision XT 19 - Welcome to EthoVision XT - Video in EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-welcome-to-ethovision-xt-video-in-ethovision-xt Chapter: EthoVision XT Video in EthoVision XT EthoVision XT can work with different types of cameras: Analog Cameras To use analog CCD cameras, you need an encoder board, which converts the analog signal to digital. With this board you can also save the video image to a video file directly with EthoVision XT. See Install Analog Cameras. Digital Cameras You can plug a digital camera (GigE Vision or USB 3.0) directly into your computer. The video signal is used directly in EthoVision XT to track live and save video. However, for acquisition the quality of the input signal is crucial, therefore not all digital cameras can be used. See Cameras Supported by EthoVision XT. Mixing Camera Images You can feed multiple cameras to the EthoVision XT computer. EthoVision XT mixes the images of up to sixteen cameras. Video is saved with all camera images merged into one. For example, when you use two cameras, the resulting video file contains the two camera views next to each other. For information on the supported cameras, frame rates, and resolutions, and the maximum number of cameras supported, see Camera Installation. Recording Video with MediaRecorder With the Noldus MediaRecorder software you can record video to be used in EthoVision XT for offline tracking. An advantage of using MediaRecorder is that you can create separate, full resolution video files from multiple cameras. With EthoVision XT, the images from multiple cameras are merged in one video file. Modules of EthoVision XT To know which add-on module you have, choose Help > About EthoVision XT then click the License Info button. The modules enabled in your license are marked with a check symbol. What module is enabled depends on the EthoVision XT license currently active on that computer. You cannot select and deselect those modules from the software. See also Types of EthoVision XT License. Base Module The Base module of EthoVision XT allows tracking of the center-point, the nose-point and tail-base point and other relevant features of one subject in one arena. - Tracking the nose-point is, for instance, relevant in the Elevated Plus Maze test to determine the number of times the subject puts its head in one of the open arms of the maze without actually entering the arm. Tracking the center-point is then not so useful. - You can also record your subjects' behavior manually using the Manual Scoring function. - You can also measure body elongation on the basis of thresholds that you set yourself. Note: The Multiple Body Points module is included in the Base module. You can extend the base functionality with the add-on modules listed below. Multiple Arenas Module Allows tracking in more than one arena at the same time. You can track one subject per arena. Rat Behavior Recognition Module With this module you can have EthoVision XT detect various behaviors automatically: drinking, eating, jumping, grooming, rearing (supported and unsupported), resting, sniffing, twitching and walking. Mouse Behavior Recognition Module With this module you can have EthoVision XT detect various behaviors of mice automatically: digging, drinking, eating, grooming, hopping, rearing (supported and unsupported), resting, sniffing and walking. Important: The Mouse Behavior Recognition and the Rat Behavior Recognition modules are not interchangeable. For example, you cannot use the Mouse Behavior Recognition to detect digging in rats. External Data Module With this module, you can import any external data in ASCII format. External data may include physiological data (e.g. EEG, blood pressure, heart rate, body temperature, etc.) or environmental data (e.g. room temperature, humidity, etc.). You can synchronize track data and associated external data and subsequently visualize, select and export these data. See External Data. Quality Assurance Module This module supports you in making experiments which fulfill quality requirements. It helps you protect your data and creates log files so you can easily keep track of everything that happens during a project. See EthoVision XT and Quality Assurance. Social Interaction Module This module allows you to track more than one animal per arena and study social interactions. For the statistical analysis a number of variables are available like the distance between the animals, and the relative movement. See also Advanced Detection Settings for Tracking Color-Marked Subjects. Trial & Hardware Control Module With this module, you can make advanced rules to start and stop the trial. You can also control hardware, like a pellet feeder, and make settings in such a way that the pellet feeder drops a pellet when the animal is in the trigger zone for 30 seconds. See Trial Control Settings and the EthoVision XT 19 - Trial and Hardware Control - Reference Manual. Track3D Module Track3D is a solution for tracking animals in a 3D space. This add-on includes a MATLAB application that converts 2D tracks obtained from two cameras to a three-dimensional track, and calculates a wealth of movement parameters in 3D. Note that Track3D only works with one tracked individual at a time. --- ## EthoVision XT 19 - Welcome to EthoVision XT - Video Tracking with EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-welcome-to-ethovision-xt-video-tracking-with-ethovision-xt Chapter: EthoVision XT Video Tracking with EthoVision XT EthoVision XT is an automated video tracking and motion analysis system. Video tracking means that EthoVision XT detects and follows one or more animals, or objects, in a video image (live footage or pre-recorded video file), and tracks their location and movement. EthoVision XT is a software platform. The Base version helps you carry out tests like the Open Field and the Morris Water Maze test. With its add-on modules, it offers a wide range of video tracking options, and extensive analysis of locomotion and behavior. Overview The entire process carried out by EthoVision may be summarized as follows: a video camera observes the movement of one or more subjects, and passes images of the subjects to your computer. There they are transformed into a digital signal and optionally encoded as a digital video file. From this digital signal or file, EthoVision first detects the subjects and then extracts the size of the subjects and position of one or more body points of the subjects in each image. That data is then transformed into a series of dependent variables quantifying the behavior of the subjects. See Also - The EthoVision XT 19 Quick Start Guide, which came with the software. - The EthoVision XT Video Tutorial to learn how to set up an experiment in EthoVision XT. In EthoVision XT, choose Help > Video Tutorial. Note that the Video Tutorial contains audio. Image Sensing The starting point of an imaging system is a video camera. A video camera transforms a scene (the area in front of the lens) into an image (a picture taken by the camera). If you have an analog camera, the image must be converted into a digital image consisting of pixels. With USB, Gigabit Ethernet (GigE) and Internet Protocol (IP) cameras, digitization occurs within the camera. You can plug them directly into your computer. Instead of using live video from a camera, you can also make a digital video file and use that for tracking. One video image from a camera or digital video file is called a frame. The frame is made by a point which scans the scene in a series of horizontal lines (called fields), starting at the top and working its way down to the bottom. The fields are interlaced, that is, the camera first scans the odd lines, then the even lines. As the scene is scanned, the brightness (or color) of the scene is transformed into an analog signal describing the intensity of the image at each point of the scan. The number of frames scanned in each second is called the frame rate, and this determines the maximum possible sample rate for EthoVision. The frame rate differs between cameras. Subject Detection When EthoVision XT receives the video frame, it does not "see" a mouse in an open field (for instance), but a bitmap composed of pixels, each of which has a particular gray value. The first thing that EthoVision XT does is to distinguish between the subjects to be tracked and the background. In order to establish which pixel is part of the animal and which pixel is part of the background, EthoVision makes use of different detection methods. You can choose which detection method to use, or you can let EthoVision XT select the best method for you by choosing the Automated Setup of the Detection Settings. Excluding Noise Whichever detection method you choose, it is possible that some pixels are identified as the subject that are in fact just system noise or reflections. You can exclude these as follows: - Before tracking: In the Arena Settings, define an arena so that pixels outside the arena are ignored. In the Detection Settings, make various settings to exclude noise. - After tracking: Smooth the track to filter out system noise, outliers and small movements. Identifying Multiple Subjects EthoVision XT can track more than one animal per arena. A few techniques are available, from the basic tracking of unmarked subjects to the state-of-the-art identification technique based on Deep Learning. To track multiple subjects, you need the Social Interaction add-on module. Tracking of Unmarked Subjects You can track multiple animals without using color markers. For instance, track a shoal of fish to measure the average between-individual distance. However, keep in mind that there may be subject identity swaps, that is, what is labeled subject 1 may be labeled subject 2 later in the track. Therefore individual identification is not guaranteed. The methods listed below keep track of the subjects' identities. Color-Marker Tracking EthoVision XT follows the color spots on the back of the insects, ignoring the shape of the animals. Marker-Assisted Identification With Marker-Assisted Identification, EthoVision XT uses the colors to identify the subjects, but tracks their entire body. This method allows collection of detailed data in social interaction tests, particularly in rodents. Just like for the previous method, you need to tell EthoVision XT which colors to follow. Tracking Based on Deep Learning If two subjects look different, or are marked in some way (also in grayscale video), EthoVision XT can discriminate between the two using its neural network. In most cases you need to mark one of the two subjects on its back or at the base of its tail. Individual discrimination is accomplished after tracking, in a process named Data Preparation, which involves a thorough review of the tracks and the corresponding video images. The neural network re-assigns the identity labels to the subjects based on their visual appearance. Note that to use Deep Learning you need a compatible secondary graphics card (GPU). Video Tracking and Video Recording You can set EthoVision XT to track the subjects and, at the same time, save the video image to a digital video file. Alternatively, you can choose to save video first, and track the subjects later from that video. Subject Position, Size and Orientation When EthoVision XT has identified a group of adjacent pixels as a subject, it extracts the following features (depending on which add-on you have): - Subject position. This is the x,y coordinates of the body points being tracked: either the center-point only (the point mathematically in the center of the shape considered to be the subject), or the center-point, the nose-point and the tail-base point. - Subject area. This is the area of the surface in the video image (camera image or video file) which composes the detected subject. The area is expressed and exported as squared distance units. - Subject area change. This is the proportion of the subject's area that changes between frames. It is used to estimate the subject's mobility. - Subject's head orientation. When you track the subject's nose point (only for contour-based methods), the software estimates the direction of the gaze, indicated by a blue line that originates from the nose point. - Subject elongation. This quantifies how stretched the subject's body is. Quantifying Behavior The output of video tracking is a series of numbers representing the x,y coordinates and size of the subject. From the raw data, EthoVision XT calculates a number of dependent variables describing the behavior of the subject. These include speed and distance moved, but also complex variables such as the direction of movement relative to an object. Furthermore, with the Rat and Mouse Behavior Recognition modules, behaviors like grooming and rearing can be detected automatically. Data Analysis and Results Export For all the dependent variables, EthoVision XT can calculate a wealth of descriptive statistics (such as mean, standard deviation, etc.). These are shown for each trial, and for the groups of trials that you may want to define (for example, treated vs. vehicle subjects). Results and raw data (x,y coordinates and per-sample values of dependent variables) can be exported to text and Excel format. With custom code written in JavaScript language within EthoVision XT, you can greatly expand analysis capabilities. Examples are available in the following topics: - JavaScript Continuous - JavaScript Event - JavaScript State --- ## EthoVision XT 19 - Welcome to EthoVision XT - Welcome to EthoVision XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-welcome-to-ethovision-xt-welcome-to-ethovision-xt Chapter: EthoVision XT Welcome to EthoVision XT Main Topics and Tasks - How to Use This Help - Introduction to EthoVision XT - The EthoVision XT Screen See Also - What's New in EthoVision XT 19 How to Use This Help Table of Contents - If you do not see the Table of Contents on the left, enlarge the Help window or zoom out the characters (Ctrl+mouse wheel). - If you want to know the current topic's position within the browse sequence, click the Table of Contents icon and locate the green indicator. Search - To search for two or more adjacent words, use quotes. For example, "plus maze". - While you type, the Help gives you suggestions about recurring terms and sentences. Click one of them to refine your search. - The search results are shown on the left side pane. - To go back to the main page, click the EthoVision XT icon at the top-left corner of the screen. Index - To use the index, type a word in the Filter keyword field. - If an index term (or sub-term) occurs in different topics, these are listed under the term. - To reset the index, delete the word you typed or click the X button and press Enter. Notes - The EthoVision XT Help is in responsive HTML5 format. Depending on the size and shape of the Help window, the buttons are automatically re-arranged, for example in tablet mode. See Also For more manuals, choose All Apps > Noldus > EthoVision XT 19 Other Documentation from the Windows Start menu. Introduction to EthoVision XT Learn About - Video Tracking with EthoVision XT - Video in EthoVision XT - Modules of EthoVision XT - What's New in EthoVision XT 19 - Restrictions in EthoVision XT - For More Information --- ## EthoVision XT 19 - Welcome to EthoVision XT - What's New in EthoVision XT 19 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-welcome-to-ethovision-xt-whats-new-in-ethovision-xt-19 Chapter: EthoVision XT What's New in EthoVision XT 19 In the Spotlight Automatic Size Calibration - Place the calibration card in view of the camera and EthoVision XT automatically determines the scale. No manual pixel-to-centimeter calculations are needed. See Calibration. Four New Social Interaction Variables - Social Contact, Approach, Following, and Leaving are now available as built-in dependent variables with fully adjustable thresholds for distance, orientation angle, and velocity. These variables work with any multi-subject experiment and are not limited to specific species or arena types. See Social Contact, Approach, Following, Leaving. Faster Re-ID After Occlusions - Post-tracking re-identification of individuals after social interactions now completes in seconds. See Re-Identification. Parameter Heatmaps - In addition to the existing track density heatmap, you can now visualize the average value of a selected parameter (e.g., velocity, distance moved) at each location in the arena. Smoothing can be adjusted or set to none. Parameters with negative values are supported. See Heatmap. Detection and Data Acquisition - Lens focus assist: a visual feedback tool helps you achieve optimal camera focus before recording. See Arena Settings. Data Analysis - Reorganized variable categories: dependent variables are now organized into five categories: Activity and Movement, Zones and Exploration, Orientation, Social, and Hardware and Advanced. Miscellaneous - New package structure: Essential, Advanced, and Premium packages replace the previous module-based licensing. See Packages. - Updated system requirements: full support for NVIDIA RTX 50 series GPUs and CUDA 13.1. Pascal architecture (GTX 10 series) is no longer supported for deep learning features. Recommended OS is Windows 11 Pro 25H2. See System Requirements. Restrictions in EthoVision XT General FeatureMaximum NumberNotes Subjects per arena 1 (Base module), up to 16 (Social Interaction module) The limit of 16 subjects is set by the software. It may be difficult to discriminate between 16 different color marks depending on the light conditions. See Color Markers. We recommend only using tracking from video files when tracking multiple subjects and multiple body points. The technical limit of 16 subjects per arena can be overridden in the software; contact Noldus Support for possible solutions. Arenas 100 With the Multiple Arena Module; one arena with the Base Module. Arenas must not overlap. The number of arenas does not depend on the number of cameras. You can have, for example, 96 wells in one camera image, or 16 arenas with 16 camera views (one arena per camera). When combining tracking of multiple subjects (with colors) and multiple arenas, performance may limit the total number of subjects followed simultaneously. Trials 10,000 Behavior types scored manually 256 Hardware commands and signals 1,024 With the Trial and Hardware Control Module. Arena Settings cache 50 MB Heatmap dimensions (pixels) 65,536 Rows or columns in analysis results table One million Free intervals 2,000 See Free Interval. Time bins No restriction If you create more than 1,000 time bins, the group charts are not displayed. Computer FeatureLimitationsNotes Computer type Workstation We recommend the use of Dell workstations especially when using multiple add-on modules (e.g. tracking nose-, center- and tail-base points in multiple subjects simultaneously). When tracking for more than 24 hours, restart the PC before a new trial. See Hardware. Video graphics card NVIDIA, 4 GB or larger If you opt to buy your own PC, it must have a stand-alone graphics card that supports Direct3D acceleration. We recommend NVIDIA video cards with a memory of 4 GB or larger. For tracking subjects with deep learning, there are further restrictions. See Deep Learning: Requirements. Processor and RAM memory Intel We recommend an Intel processor; for desktop PCs, 32 GB RAM, and for laptops 16 GB RAM. Video Resolution, Sample Rate and Trial Duration Important: When tracking from video files at high resolution and/or frame rate, always select DDS in the Playback Control window. This way EthoVision XT adjusts the analysis speed to the time needed to analyze each frame without skipping frames. See DDS (Detection Determines Speed). Important: When tracking for more than 24 hours, always reboot the PC after every trial to refresh the PC resources, the RAM specifically. Failure to do so could result in crashing, which can corrupt the experiment or the recorded video. FeatureMaximumNotes Video resolution (camera image) Depends on camera type See Cameras Supported by EthoVision XT. Video resolution (video file) 1900 x 1200 Higher resolutions, for example 4K video, may work. Test a few sample videos and check for missing samples. Keep DDS selected in the Acquisition screen. See DDS (Detection Determines Speed). Sample rate (live tracking) 60 frames per second; depends on the camera See Cameras Supported by EthoVision XT. Sample rate (tracking from video file) Not specified EthoVision XT can handle short video files with a frame rate of 1000, but that also depends on the video format. Test a few sample videos and check for missing samples before running the experiment. Trial duration 72 hours, but this depends on the tested setup See Resolution, Frame Rate, and Maximum Trial Duration. --- ## EthoVision XT 19 - Zone alternation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-zone-alternation Chapter: EthoVision XT Definition An event scored when the animal visits specific zones in: - Alternations: Multiple entries into different zones, with no reentries, in overlapping sets of zone entries. For example, for a Y maze with three zones A, B and C, the sequence of zone entries ABC is an alternation. - Revisits: Multiple entries into the same zone. They can be direct (for example, AA) or indirect (for example, ABA). Consider the zone entry sequence in a Y-maze: ABCBACBCAB. The eight overlapping 3-zone entry sequences are: ABC, BCB, CBA, BAC, ACB, CBC, BCA, CAB. Of these, six are alternations (underlined): ABC, BCB, CBA, BAC, ACB, CBC, BCA, CAB. Alternation is often calculated together with the maximum possible number of alternations for the given sequence (that is, the total number of zone entries minus 2). In this example, it is 10 - 2 = 8. The sequence above results in zero direct revisits, and two indirect revisits: BCB and CBC. How to Specify Zone Alternation - Click the Add button next to Zone alternation. - In the Zone Alternation tab, under Settings, choose the zones that define the alternation. - Under Threshold, enter the Zone exit threshold. That is, once the animal is detected in a zone, the animal is considered to be in the zone until its distance from the zone border exceeds that threshold. Use this option to remove false re-entries resulting from random movements of the body point around the zone border. - Under Calculate Statistics for, select the options you require: - Alternations: To calculate statistics of alternations (ABC, ACB, etc.). - Max alternations: To count the maximum possible alternations given the sequence of zone entries in your data. - Direct revisits: To calculate statistics of the direct revisits (AA, BB, etc.). - Indirect revisits: To calculate statistics of the indirect revisits (ABA, ACA, etc.). - Complete the procedure to add the variable. See Calculate Statistics: Procedure. Applications In a T-maze or Y-maze experiment, you can use Zone alternation to analyze Spontaneous Alternation. See Hughes (2004) Neuroscience & Biobehavioral Reviews, (5), 497–505. - In the Zone alternation tab, select the arm zones. If the arm zones are separated by a Center zone in the same zone group, do not include the Center zone. - Also select Max alternations. The ratio Alternations/Max alternations expressed in percentage gives the spontaneous alternation index. An alternation index around 50% indicates random arm selection. Notes - If your experiment is set to Center-point, nose-point and tail-base detection, click the Body points tab and select the body points you want to use for calculation. If you have chosen two or three body points, select one of the following from the list: - Each point: Alternations and revisits are scored for each point separately. - Any selected point: Alternations and revisits are scored no matter which selected point enters a zone. - All selected points: Alternations and revisits are scored when all the selected points are in a zone simultaneously. - Max alternations measures the maximum number of alternations that are possible with the actual data and given that number of zones considered. It is calculated as follows: Max Alternation = Total visits - (Number of zones - 1) - Total visits is the total number of zone visits. - Number of zones is the number of zones chosen under Settings; for the Y maze this is 3, for the plus maze it is 4. For example, given a sequence of 22 visits to zones A, B, and C, Max alternations is 22 - (3 - 1) = 20. The number of visits is diminished by two to account for the fact that the last two visits in the sequence are not part of complete alternations, because the remaining visits are unknown. A value of 20 means that if the animal had visited each zone after visiting the other two in the previous two visits (ABCABC, etc.), it would have made 20 consecutive alternations (ABC, BCA, CAB). An example of this procedure can be found in Ragozzino and Gold (1994), Journal of Neuroscience (12), 7478–7485. - In Integrated Visualization, a Max alternations event is scored from completion of the first set of entries and for each new zone entry from that point. In the Statistics results, the total number of those events is shown under Frequency. - Direct revisits are evaluated in 2-zone entry sequences, ignoring entries in zones not selected in step 2. For example, the sequence ADA results in one direct revisit (AA) when D is not selected. - Indirect revisits are evaluated in 3-zone entry sequences, ignoring entries in zones not selected in step 2. For example, the sequence ABDAB results in the indirect revisits ABA and BAB when D is not selected. - Direct revisits and indirect revisits are calculated when you select at least two and three zones, respectively. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## EthoVision XT 19 - Zone transition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ethovision-xt-19-zone-transition Chapter: EthoVision XT Definition This is the number of times an animal visits two or more zones in a sequence. For example, in a T-maze study, the transition Long Arm > Left Arm > Right Arm. A Zone transition is scored when the animal enters the last zone of the sequence. How to Specify Zone Transition - Click the Add button next to Zone transition. - In the Zone transition tab, to add a sequence click the Add button. - Select a zone and click or double-click a zone to include it in the sequence you want to define. Repeat this step to add more zones and complete the sequence. Under Zone sequence you can view the current selection. If the sequence is not correct, click and select the correct zones. - When ready click Add. Repeat steps 2–3 to add more sequences. - Depending on which option under Settings you select, you can get different results. See the notes below. - Under Threshold, enter the Zone exit threshold. That is, once the animal is detected in a zone, the animal is considered to be in the zone until its distance from the zone border exceeds that threshold. Use this option to remove false re-entries resulting from random movements of the body point around the zone border. - Click the Body points tab, select the body point(s) you want to use for calculation. - Complete the procedure to add the variable. See Calculate statistics: procedure. Zone Transition Counting Options For all options below, the zone transitions found in the data are marked in green. Zone transitions ignored are marked in red. The numbers in blue show the statistic Total number. - Allow intermediate visits to any zone With this option the sequence ABC is found in the zone visit data ABDC, where D represents any zone defined. In the following example, the zone sequence CAB has been defined. A total of four transitions have been found. - Allow intermediate visits to zones not in the sequence With this option the sequence ABC is found in the zone visit data ABDC, just like in the example above, because D does not belong to the sequence defined. However, the same sequence ABC is not found in the zone visit data ABAC, because the second A is defined in the sequence. In the following example, two transitions CAB have been found. The last two sequences are ignored. - Only count direct transitions With this option, sequences with intermediate visits to any zone are ignored. Do not use this option if your focal zones are not adjacent (for example, zones for a novel object and a familiar object) and the arena includes multiple zone groups. In that case, direct transitions from the focal zones may not be counted if the subject crosses a third zone in another zone group. However, if your arena only includes one zone group with the non-adjacent zones, the results are reliable. - Include overlapping sequences You can apply this additional option to any of the options above. Overlapping sequences may occur if the first zone of the sequence defined is visited again before the previous instance is completed. Consider the following zone visit data: ...BABAB... When looking for the sequence BAB, two overlapping sequences BAB are found: ...BABAB... ...BABAB... Consider the following zone visit data: ...BABABAB... If the option Include overlapping sequences is selected, the sequence BAB is found three times. If the same option is not selected, the sequence BAB is found two times. However, overlapping sequences that are completed at the same time point (that is, the same zone visit) are counted as one. In the following example, the sequence CAB is defined, and the method Allow intermediate visits to any zone is used. The two sequences CAB ending at the same visit to B are scored as one. Note that transitions are scored at the end of the last zone entry. Notes - The Body Points tab is only available if your experiment is set to Center-point, nose-point and tail-base detection. - When you visualize the Zone transition variable, only the end of the transitions (which equals the last zone entry) is marked on the time plot. EthoVision does not calculate the duration of the transition. - To delete a sequence, select that sequence under Settings and click the Delete button. - Effect of missing samples. A transition from Zone 1 to Zone 2 is also counted when the subject enters Zone 1, then it becomes missing before exiting the zone, it is found again outside Zone 1, and finally enters Zone 2. Applications - In a Novel object test, calculate the number of transitions from the zone Familiar object to the zone Novel object, and from Novel object to Novel object. Or in a PhenoTyper or home cage test, calculate the transitions between the different corner visits. When the focal zones are not adjacent, select Allow intermediate zone visits. - For Y-maze tests, see Zone alternation. Source: EthoVision XT 19 Help, Noldus Information Technology --- ## In Vivo Calcium Imaging - nVista and PhenoTyper Integration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/in-vivo-calcium-imaging-nvista-and-phenotyper-integration Chapter: EthoVision XT Introduction The ability to acquire in vivo neural activity data simultaneously with behavioral data is vital to truly understanding the brain in action. The nVista miniature microscope system from Inscopix enables researchers to conduct genetically targeted calcium imaging in hundreds of cells over time in awake, freely behaving rodents, and has provided insights from multiple brain areas, from the prefrontal cortex all the way to the hypothalamus. nVista's compact, sleek plug-and-play interface makes it easy to add powerful new neural circuit insights to any laboratory's behavioral research arsenal. The Noldus PhenoTyper system is a proven behavioral observation platform which obtains behavioral data during multiple types of experimental paradigms, integrating the animal test environment with video equipment and automated animal tracking. nVista is fully compatible with the PhenoTyper system, allowing you to harness these two data powerhouses in the service of your research questions. There are multiple ways to sync the nVista system with the Noldus PhenoTyper depending on the behavioral paradigm that best fits your research question. Here, we detail an example of triggering nVista recordings in an implanted animal when the animal crosses into a target region of the arena, as defined in the EthoVision® XT software. Capabilities With nVista and PhenoTyper you can: - Produce synchronized population-level neural activity data with behavioral videos during active behavioral sessions. - Obtain longitudinal neural circuit and behavioral recordings of the same animal. - Filter data for specific behaviors, locations, and times. - Adapt the synced behavioral and neural activity system setup to address diverse research questions. Setting Up nVista Hardware To use the Noldus PhenoTyper to trigger the nVista system, attach a male BNC cable to the nVista Trig port. The other end will be connected to the RJ45 port of the PhenoTyper system. Software Open the nVista Acquisition software. Under the Device menu at the top of the software interface, select Trigger from external hardware. Configure your other nVista settings, such as image acquisition format, GPIO status, LED power, etc., as needed based on your experimental needs. The EthoVision software will control when the recordings start and stop. Under Preferences, select whether or not you would like the GPIO port to be toggled On or Off, and whether or not it should be an input or an output. To set the nVista system to record only when the animal has entered a specific part of the behavioral box arena, select Arena Settings in the Experiment Explorer. Set up the arena to satisfy your experimental needs. To ensure the correct hardware device will be used during the experiment, scroll down to Hardware Mapping from the Arena Settings window on the right, and make sure the Arena Hardware Device type, interface, and name are linked to the proper Arena (please refer to the EthoVision XT manual for additional instruction). Set up the Trial Control Settings to dictate when the Noldus system will communicate with nVista and trigger a recording to begin or end. This controls triggering an nVista recording every time the animal approaches a target region in the behavioral box. To start the experiment, navigate to Arena Settings > Trial Control Settings > Acquisition, and begin acquiring data under the Playback Control window. Acquiring Simultaneous In Vivo Calcium Imaging and Behavioral Recordings The following describes a representative experiment combining nVista data with EthoVision XT data, where animals were imaged across multiple days: - Cortical Activity and Behavioral Tracking: Recording and behavioral tracking was performed across 3 days for 20 minutes each day using nVista and EthoVision XT. Animals were placed in an arena devoid of any objects on Day 1. Two texturally different objects (Gel Pad and Wood Block) were placed in the arena for 3 consecutive days, and animals were imaged on the last day of object familiarization (Day 4). On Day 5, one object was replaced with a novel object (Sandpaper) and the animals' activity was recorded. - nVista Snapshots: Snapshots from three days at different time points show mouse somatosensory cortical activity. - Mouse Tracks: Mouse tracks over the three days of imaging were computed using EthoVision XT. - Heat Maps: Respective heat maps of the mouse's location were extracted using EthoVision XT. Summary The ability to gather population-level neural activity data in the context of awake behavior is proving essential for gathering meaningful insights in an increasing number of innovative neuroscience applications. The nVista miniature microscope system provides new insights into different cell types in a variety of brain regions. Used in concert with the Noldus PhenoTyper system, this powerful pairing empowers researchers to bring firing rates into the context of behavior and advance neural circuits research projects. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper - 1 Introduction to PhenoTyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-1-introduction-to-phenotyper Chapter: EthoVision XT Introduction To PhenoTyper What Is Phenotyper? PhenoTyper combines an open field and video-based monitoring equipment in a complete observation system that you can use to monitor rodent behavior automatically. The infrared lighting system ensures robust monitoring regardless of ambient light conditions in the lab. You can also use PhenoTyper to administer visual and acoustical stimuli to your subjects, or to monitor the subjects using specific sensors. To this purpose, PhenoTyper 2 can easily integrate additional devices. Figure 1 PhenoTyper 2 for different applications. Left: PhenoTyper for mouse. Middle: PhenoTyper for rats in a social interaction context. Right: PhenoTyper for single rats. The TopPlate hosts a GigE Vision digital camera and offers space for sensors and stimulus devices. The walls of PhenoTyper can be configured in different ways, making it suitable for a variety of applications. PhenoTyper can be fully controlled by the EthoVision XT video tracking software. Activity, movement and specific behaviors (e.g. feeding, grooming) of the subjects can be continuously measured and analyzed afterwards. This And Other Manuals To open the manuals, manual, from the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 Other Documentation. You can also find all the manuals on the my.noldus portal: my.noldus.com PhenoTyper - EthoVision XT 18 - Reference Manual.pdf (this manual). Includes information on how to install and configure PhenoTyper and control its devices to automate experiments in EthoVision XT. It also includes examples of PhenoTyper applications. Figure 2 Examples of the components of the PhenoTyper cage. PhenoTyper - EthoVision XT 18 - Service Manual.pdf See this manual for specific information on the PhenoTyper camera, and the devices that can be used together with PhenoTyper, for example the Pellet dispenser and PhenoWheel. EthoVision XT 18 - Trial and Hardware Control - Reference Manual.pdf This manual contains extensive information on the control of hardware devices through EthoVision XT. Learn how to combine conditions, actions, subrules to create complex task protocols for your subjects. EthoVision XT 18 Help Consult the Help for extensive information about EthoVision XT, for example how to draw arenas and zones, select tracks for analysis and create charts. To open the EthoVision XT Help, press F1 in EthoVision XT. Main Features Of Phenotyper Home cage environment Observation and tracking of subjects in a home cage environment has the main advantage that the behavior is more natural and less influenced by human intervention. The cages can be equipped with a shelter, a feeder, a water bottle and a rotating wheel, and can be enriched with bedding material and other objects. For details, see phenotyper configurations on page 18. Top Unit/TopPlate The Top Unit (TopPlate in PhenoTyper 2) is the "brain" of PhenoTyper. It holds the camera and additional sensors and actuators and contains all the electronic equipment necessary to exchange information with the tracking software (Figure 3). It also includes infrared and white light arrays (see below). Lighting An array of Infrared (IR) LEDs is activated as long as PhenoTyper is switched on. This allows continuous monitoring and video-tracking independent of the light conditions in the test room. An array of white LEDs (in PhenoTyper 2 only) provides visible white light. You can switch on this light and use it as a visual stimulus or when you need to track color-marked animals. You can adjust the intensity of the IR and white light using the controls on the front panel of the TopPlate TTL Interface. Video camera PhenoTyper is equipped with a monochrome analog camera (in PhenoTyper 1) or a monochrome GigE Vision digital camera (in PhenoTyper 2). Both cameras detect infrared light and exclude most of the light in the visible range. For optimal image quality a built-in infrared array ensures illumination; this way your recordings are Figure 3 The TopPlate of PhenoTyper 2 with the camera module. Additional modules (currently under development) can be added around the camera. independent of visible light. You can run tests throughout the light- dark cycle because the image of the subject and the background processed in EthoVision XT won't change. important Do not use incandescent light bulbs as visible light source in the test room, because they produce a lot of infrared light which can interfere with video tracking. If you need extra (visible) light in your test room, use tube lamps, LED lamps or the LED arrays provided with PhenoTyper 2, which produce far less infrared light. See lighting conditions on page 48. The camera can see the subjects at night but does not detect the heat produced by animals. The lens focus and orientation of the camera is optimized by Noldus. In the case you need to make adjustments, see the PhenoTyper - EthoVision XT 18 - Service Manual (see page 7). Visible light and sound The following stimulus devices are available: In PhenoTyper 1: the white light spot and the yellow light spot. Each of these illuminate approximately a quarter of the cage bottom. Furthermore, PhenoTyper 1 has a buzzer module can be used to administer a sound stimulus. In PhenoTyper 2: the white light (not a light spot) is currently available as a visual stimulus. Contact Noldus if you need additional stimulus devices. The stimuli can be administered automatically using the Trial Control function in EthoVision XT. PhenoTyper - EthoVision XT communication PhenoTyper is the ideal cage for use in combination with the tracking and analysis software EthoVision XT, no matter how long and complex the trials are. PhenoTyper receives commands from and sends feedback to EthoVision XT. When working with multiple PhenoTypers simultaneously, you can administer stimuli in different cages independently. See Set up PhenoTyper 1 on page 35. The course of events during a trial is logged in EthoVision XT. The events are readily available for analysis. See examples in Common tests with PhenoTyper on page 85. For extensive information, see Analysis of Trial Control data in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual (see page 7). How Can I Use Phenotyper? For monitoring and video tracking Connect the PhenoTyper camera to the EthoVision XT computer (page 37). The software tracks the subject's position and calculate a wealth of statistics of the subjects' behavior (distance moved, time spent in specific zones etc.). With Behavior Recognition you can analyze behaviors like grooming and sniffing. This setup does not perform actions on any device. For recording video Connect the PhenoTyper camera to a computer with EthoVision XT or MediaRecorder (see page 42). MediaRecorder is especially useful when you want separate high-resolution video files for each cage. You can use the video later on to carry out offline video-tracking with EthoVision XT. For video tracking and administration of stimuli This advanced setup is meant for controlling the PhenoTyper devices during a trial, for example in a conditioning experiment where the subject is given a reward when it performs a specific behavior. You can have EthoVision XT carry out actions like switching on a light when a condition is met. PhenoTyper is connected to the EthoVision XT computer through the USB-IO box. In the software you can program the Trial Control with a sequence of conditions (e.g. check that the mouse has reached a zone) and subsequent actions (e.g. switch on the white light) that will be executed during a trial. You can also combine PhenoTyper with other devices like the Noldus Pellet dispenser or the Noldus Lickometer. EthoVision XT also receives feedback from PhenoTyper. For example, you can track in your data how often a stimulus was given, and when a pellet was dropped. For extensive information about how to control hardware devices, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. What's New In Phenotyper? Digital video quality Digital video quality. PhenoTyper 2 hosts a Basler acA1300-60gm monochrome digital camera. The main advantage of a digital camera is that its image is less sensitive to noise and allows to record video at a resolution greater than that attainable with PhenoTyper 1. A GigE Vision camera such as that of PhenoTyper can be easily connected to a PC through an Ethernet interface board, so you no longer need an expensive frame-grabber board to record video. Here we compare the video resolution of PhenoTyper 2 (1280 x 1024) with that of PhenoTyper 1 (PAL video, 768 x 576). in a 4-PhenoTyper configuration: In a 16-PhenoTyper configuration: Modularity Another great improvement in PhenoTyper 2 resides in its modularity. With PhenoTyper 1 adding a custom device to the Top Unit was relatively cumbersome. In contrast, PhenoTyper 2 has a modular structure. Besides the central module that hosts the video camera, additional devices can be attached using the eight slots available. When needed, you can replace them with other devices for a new protocol. Improved lighting PhenoTyper 2 is equipped with an internal white light ring that ensures consistent illumination across your experiments. Better lighting means better detection of the subjects, and more reliable and reproducible results. Backward compatibility PhenoTyper 2 is backward-compatible with PhenoTyper 1, allowing for an effortless upgrade without changing cables and cage elements. Current development of PhenoTyper 2 The TopPlate of PhenoTyper 2 is subject to continuous development. Some functions of PhenoTyper 1 are not yet available in PhenoTyper 2. Contact Noldus if you wish to use a specific device with PhenoTyper 2. Advantages Of Phenotyper Compared With Ordinary Test Setups Robustness The video camera blocks out visible light, therefore EthoVision XT works on infrared light only. This makes tracking independent of ambient light conditions in the lab, and even allows to carry out studies of circadian rhythms without having to change settings in EthoVision XT when the light conditions change. Ease of use You no longer have to worry about choosing, mounting and positioning a camera, nor how to set up the ambient light conditions in the lab. PhenoTyper is also a complete monitoring system: camera, lights, open field, and even visual and acoustical stimuli are all integrated in one system. Flexibility PhenoTyper can be configured in different ways and extended with a number of accessories. Not only you can combine cage elements, but you can also easily customize the cage walls so that the cage is tailored to your research. This makes it possible to apply PhenoTyper to a wide range of studies and research questions, from a short open field test to multi-day circadian rhythm monitoring, from toxicology trials to operant tests. Scalability and reproducibility You can easily extend your study by adding cages and replicating experiments with the same settings in EthoVision XT. Furthermore, because the cages can be easily standardized using the same components, you can improve reproducibility by applying the same setup in different studies and across labs. Minimal human interference PhenoTyper is a home-cage environment. The subject can live in the cage for days when provided with food and water. Tests can be performed in a series, without moving the subject. This way the subject's behavior is more natural and handling by the operator is minimized. Variable observation periods Because PhenoTyper is a home cage and the video image is independent of the external lighting conditions, it can be used in short- term tests as well as in multi-day recordings. For example, it is sometimes necessary to observe animals for long time in order to detect phenotypic differences between strains or experimental treatments. Applications Of Phenotyper There is a wide range of applications of PhenoTyper as a home-cage monitoring system, and the following the list is not exhaustive. Check noldus.com regularly for more examples of use of PhenoTyper with the relevant literature. For an extensive review of studies conducted with PhenoTyper, see the following article: Grieco, F. et al. (2021) Measuring behavior in the home cage: study design, applications, challenges, and perspectives. Front. Behav. Neurosci. 15:735387. doi: 10.3389/fnbeh.2021.735387 https://www.frontiersin.org/articles/10.3389/fnbeh.2021.735387/full Test paradigm/behavior to be measured PhenoTyper add-on or device needed EthoVision XT module needed Spontaneous behaviors Activity-related measures Activity-related measures (> 12 hrs) Drinking bottle, Feeder, Shelter Circadian rhythm Drinking bottle, Feeder, Shelter Habituation, novelty response Drinking bottle, Feeder, Shelter Running wheel activity PhenoWheel or Med Associates running wheel Trial and Hardware Control Feeding behavior Feeding monitor Trial and Hardware Control Drinking behavior Lickometer Trial and Hardware Control Rearing, grooming, sniffing, jumping, twitching (rat) Rat Behavior Recognition Rearing, grooming, sniffing, hopping, digging (mouse) Mouse Behavior Recognition Cognition Discrimination learning e.g. CognitionWall Trial and Hardware Control Reversal learning e.g. CognitionWall Trial and Hardware Control Avoidance learning Illuminated shelter Trial and Hardware Control Appetitive operant conditioning Shelter, Pellet dispenser Trial and Hardware Control Anxiety Light avoidance Shelter Trial and Hardware Control Sheltered feeding Open and close feeding platforms Social behavior Dyadic interaction Social Interaction Optogenetics Single or dual channel stimulation Single/Dual channel commutator in top unit, dual channel LED illuminator, pulse train generator Trial and Hardware Control Biotelemetry Physiology (third party product needed) Telemetry receiver placed under PhenoTyper Trial and Hardware Control, External Data Phenotyper Configurations Cage size Model 3000. Suitable for mouse studies. Model 4500. Suitable for both rat and mouse studies. Model 9000. Suitable for multi-subject rat studies. See the cage sizes in Technical Specifications on page 113. Cage types You can make three main cage types depending on the walls and accessories chosen: Basic cage Cage with one plain wall, one wall with door, and two ventilation walls. Suitable for short-term studies. Home cage Cage provided with door, a feeder, a drinking bottle, and a shelter. Two walls have ventilation holes. Suitable for long-term observations. Note: The Model 4500 includes two drinking bottles and one feeder larger than that of Model 3000. The Model 9000 home cage includes two drinking bottles and two large feeders. The Model 4500 and 9000 are provided with a shelter bigger than that of the Model 4500. Additional wall types Beside the standard walls in clear perspex, several wall types are also available in a matte version. Wall types are available for the following systems: The PhenoWheel for mice. See the section PhenoWheel in the PhenoTyper - EthoVision XT 18 - Service Manual. The Activity Wheel for rats. The Pellet dispenser and the Pellet receptacle. See the section The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 18 - Service Manual. The Mouse Feeding Monitor. The CognitionWall. See page 95. Custom cage Any combination of walls and accessories that differs from the Basic and the Home cage. You can build, for example, a custom cage with feeder and bottle but no shelter, or a cage with three or four ventilation walls if necessary. For connecting third party hardware to the PhenoTyper cage, contact Noldus to see what the possibilities are for your specific devices. Using Multiple Phenotypers When using multiple PhenoTypers, consider the following: Maximum number of PhenoTyper cameras The following configuration have been tested: PhenoTyper 1 (analog camera): 16. See page 39. PhenoTyper 2 (digital camera): 16. See page 67. See also page 35 for how to set up PhenoTyper. You can also record video using MediaRecorder and then do tracking offline (see page 42). MediaRecorder is especially useful when you need to record high-resolution video for each cage. Maximum number of PhenoTypers that can be controlled You can have EthoVision XT control the PhenoTyper devices. The EthoVision XT Trial Control Settings are applied to each PhenoTyper independently, provided that each PhenoTyper is defined as a separate arena (page 57). PhenoTyper 1: You can connect four PhenoTypers to one Top Unit Interface and up to 13 Top Unit interfaces to one EthoVision XT computer through the Noldus USB-IO box. You could in principle control up to 52 PhenoTypers simultaneously. However, the resulting video resolution would be very low. Therefore, we recommend to connect up to 16 PhenoTyper to one computer. PhenoTyper 2: You can connect PhenoTypers directly to the USB-IO box (TTL ports). With the current version of PhenoTyper 2, connect up to 12 PhenoTypers to each USB-IO box. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - 2 Assemble PhenoTyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-2-assemble-phenotyper Chapter: EthoVision XT Assemble PhenoTyper Before You Start Assembling PhenoTyper involves the same basic steps no matter what the came model and configuration is. The instructions below are based on the home cage configuration for PhenoTyper model 3000. Home cage components note The PhenoTyper components you have purchased may not match exactly the illustrations in this manual. For example, walls may be matte instead of being translucent. Figure 4 Wall elements for the home cage. F applies for model 4500 only. The model 4500 comes with two drinking bottles (H+I). The letters are used throughout the instructions. *) The plain wall is part PTC3-W000 for cage model 3000 and PTC4- W000 for cage model 4000. See part serial numbers, see page 107. Remove the protecting foil from the walls All cage elements A-E, G and J in Figure 4 are provided with a protecting plastic foil on both sides. Remove the foil before assembling the cage. Mounting set For cage model 3000: page 108. For cage model 4500: page 110. Walls with airgap (2x per cage). See page 23. Airgap shields (2x per cage). See page 23. Cage bottom. See page 24. Wall prepared for feeder and bottle (replaced by a plain wall* in the basic cage). See page 24. Wall prepared for shelter (replaced by a plain wall in the basic cage). See page 25 L pieces for fixing the walls (2x per cage). See page 27 Cover plate. See page 34. Bottle support. See page 28. Drinking bottle. page 29. Shelter. See page 30. Feeder. See page 31. Assemble The Cage optional for cage 4500 Add the drinking bottle If you have PhenoTyper walls with one hole only for the bottle support, attach the bottle support with one M4 12 mm screw. The correct position of the drinking bottle is as follows: Add the shelter Attach the shelter to cage walls PTC3(4)-W005 (cage wall prepared for shelter). See parts list on page 107. Before placing the shelter, remove the protecting sheet from the inside! Add the feeder Attach the TopPlate and the TopPlate TTL Interface - PhenoTyper 2 For models 4500 and 9000: Attach the Top Unit - PhenoTyper 1 Place the metal frame and the Top Unit on top of the cage. The cover plate - PhenoTyper 1 When you do not use the Top Unit, place the cover plate (G in Figure 4) on top of the cage. This prevents the animal from escaping. important Do not leave the cover plate in between the Top Unit and the cage during the experiments. It may decrease image quality. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - 3 Set up PhenoTyper 1 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-3-set-up-phenotyper-1 Chapter: EthoVision XT Set Up PhenoTyper 1 Aim This section applies to PhenoTyper version 1, with the Top Unit hosting an analog camera. Topics cables and adapters - page 36 connect one phenotyper to the pc - page 37 connect multiple phenotypers to the pc - page 39 working with groups of phenotypers - page 44 connect additional devices - page 47 lighting conditions - page 48 test the phenotyper's functions - page 48 adjust light intensity - page 50 copy light intensity values from one phenotyper to another - page 52 the phenotyper camera - page 55 Cables And Adapters A, B - Power cord and transformer. For PhenoTyper 1: code PT-PS1. C - Power feed-through cable (code PT-PSC) for connecting multiple PhenoTypers. D - Composite video cable of variable length with BNC connectors (code PT-BNCxx; see Figure 6). For the complete list of components and their codes, see page 107. If you purchased the USB-IO box and the Top Unit Interface, you also have the following cables: 1x Network cable, 1m (green). 4x Network cable, 2 m (green). Figure 5 The PhenoTyper' s cable set. Figure 6 Video cable with BNC connectors. USB cable with connectors of type A and B. Power cord and DC adapter 24 V 3A. Connect One Phenotyper To The Pc Power and video - Connect the PhenoTyper's Supply In socket to the power outlet using the elements A and B (see Figure 5 on page 36). - Connect the PhenoTyper's Video Out socket to one of the BNC connectors of the Euresys Picolo Alert encoder board installed on your computer, using a video cable with BNC connectors (D). Connect the video cables directly to the BNC connector on the board. Below: 1. Power plug. 2. Video cable from the PC's encoder board. For installing the Picolo Alert encoder board, see the EthoVision XT Help under Camera Installation > Install analog cameras. Control of devices using the USB-IO box - Connect the USB port of the USB-IO box (or the Mini USB-IO box) to one of your PC's USB ports using the USB cable that comes with the (Mini) USB-IO box. - Connect the 24 V IN port of the (Mini) USB-IO box to the power outlet using its adapter. - Connect the SDI Control port number 13 of the USB-IO box (or the Mini USB-IO box) to the USB IO-box port of the Top Unit Interface, using the 1 m green network cable with RJ-45 connectors at its ends. 4. Connect the port 1 of the Top Unit Interface to the TTL In port of PhenoTyper, using the 2 m green network cable with one RJ-45 connector and a SubD-9 connector at its ends. Connect Multiple Phenotypers To The Pc Power and video - Connect the first PhenoTyper's Power Supply In socket to the power outlet using the elements A and B (page 36). - Using three power feed-through cables (C), connect the Power Supply out socket of the first, second and third PhenoTyper to the Power Supply in socket of the next one, respectively. So, 1 out to 2 in, 2 out to 3 in, 3 out to 4 in. 3. Connect each PhenoTyper's Video Out socket to one of the BNC connectors of the Euresys Picolo Alert encoder board installed on your computer, using a video cable with BNC connectors (D). Connect the video cables directly to the BNC connector on the board. Note: Resolution of each camera image: 768 x 576 (PAL Top Unit camera) or 640 x 480 (NTSC Top Unit camera). The resulting picture-by- picture video file created by EthoVision XT is 1536 x 1152 (PAL) or 1280 x 960 (NTSC). For mix the video image of four to sixteen PhenoTypers 1 using Quad Units, see page 40. Furthermore, if you have the MediaRecorder software you can record full resolution video file from each PhenoTyper (page 42). For more information, in the EthoVision XT Help see Camera Installation > Install analog cameras. When using more than 4 PhenoTypers, connect each group of 4 PhenoTypers to a separate power outlet. Mix the camera images with a Quad Unit This section only applies to PhenoTyper 1 (analog camera). Use a video processor (Quad Unit) to mix video of 4 or 16 PhenoTypers. EthoVision XT will process that mixed image. You can work with this setup when you track live or from previously-recorded video files (offline). important If you track the subject's center-point, nose-point and tail- base, mix maximally four video images. Otherwise the individual images become too small for accurate tracking. To mix four PhenoTyper images, you need one Quad Unit. 1. Connect the Video Out socket of each PhenoTyper to one of the quad unit's Video In sockets, using composite cables with BNC connectors. 2. Connect the quad unit's Video Out socket one of the BNC connectors of the of the encoder board installed on the PC. To mix sixteen PhenoTyper 1 images, you need four Quad Units. 1. Connect the Video out from of each 4-Phenotypers group to the video inputs of a quad unit. 2. Connect the four video outputs of the quad units to the inputs of the Picolo Alert encoder board on the EthoVision XT computer. Notes In your EthoVision XT experiment, define as many arenas as cages. When using Quad Unit VM-Q401A: When it does not display video, chances are that it is set to the incorrect TV standard. First, unplug the device from the power supply. Next, to select the PAL mode, hold down own the Left arrow button on the front of the device while plugging in the power supply. To select the NTSC mode, hold down the Right arrow button while plugging in the power supply. important When you mix the camera images with a Quad Unit, the resolution of each camera view is one quarter of the original. This is because both the width and the height of the image are reduced to half of the original. Especially when you use the Behavior Recognition function, check that the apparent size of the subjects in pixels is still acceptable. You find more information in the topic Behavior Recognition: Prerequisites in the EthoVision XT Help. When mixing four PhenoTyper 1 images with a Quad Unit, the video resolution of each camera image is 384 x 288 (PAL Top Unit camera) or 320 x 240 (NTSC Top Unit camera). The resulting resolution of the picture-by-picture video file created by EthoVision XT is 768 x 576 (PAL) or 640 x 480 (NTSC). When mixing four PhenoTyper 1 images with the Picolo Alert encoder board (see the scheme on page 39) the original resolution is preserved. The resulting picture-by-picture video file created by EthoVision XT is 1536 x 1152 (PAL) or 1280 x 960 (NTSC). When mixing 16 PhenoTyper 1 images with Quad Units, the resolution of each camera image is 384 x 288 (PAL) or 320 x 240 (NTSC). Because the output resolution of each Quad Unit is preserved in the Picolo Alert encoder board, the resulting resolution of the picture-by-picture video file created by EthoVision XT is 1536 x 1152 (PAL) or 1280 x 960 (NTSC). Do not mix 16 camera images if you want to track the nose-point and the tail-base point of the rodents, because the image will be too small for accurate tracking. Mix maximally four images. For a complete overview of the video resolutions and frame rates supported by EthoVision XT, see the EthoVision XT Help. Record video to separate video files This section applies to both PhenoTyper 1 and PhenoTyper 2. You can use the MediaRecorder software to record video from each PhenoTyper to a separate video file. This setup is possible only if you track offline and you have MediaRecorder. Each PhenoTyper sends the video signal directly to one input of the Picolo Alert encoder board (for PhenoTyper 1) or to the Ethernet interface board (for PhenoTyper 2). For details, see the MediaRecorder Help. 1. Once you have recorded video to separate video files, create a new EthoVision XT experiment. Choose Setup > Experiment Settings and under Video source select From video file. 2. Because each video file contains the image of one arena, in your Experiment Settings, under Number of Arenas, select 1. 3. You can now load the video files in EthoVision XT and perform offline tracking. If you choose this setup, mind that you cannot control hardware devices during offline tracking. In an alternative setup, you can do live tracking with hardware control, and let EthoVision XT trigger video recording with MediaRecorder (see Trial Control in the EthoVision XT Help). Control of devices using the USB-IO box - Connect the USB port of the USB-IO box (or the Mini USB-IO box) to one of your PC's USB ports using the USB cable that comes with the IO box. - Connect the 24 V IN port of the (Mini) USB-IO box to the power outlet using its adapter. - Connect the SDI Control port number 13 of the USB-IO box (or the Mini USB-IO box) to the USB IO-box port of the Top Unit Interface, using the 1 m green network cable with RJ-45 connectors at its ends. 4. Connect the port 1, 2, 3 and 4 of the Top Unit Interface to the TTL In port of the first, second etc. PhenoTyper, respectively, using 2-m green network cables with one RJ-45 connector and a SubD-9 connector at their ends. Note By default, the USB IO-box is set to be connected with one Top Unit Interface only (and therefore four PhenoTypers) through the SDI Control port 13. If you work with 8 to 16 PhenoTypers, you must use additional SDI Control ports. Connect the USB-IO box port of each Top Unit Interface to one of the SDI Control port 1 to 4 of the USB-IO box. For example, the Top Unit Interface of group 1 to SDI control port number 1, etc. Make sure that the IO-box is set correctly for communicating with multiple Top Unit Interfaces (see Jumper Settings in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. To open this manual, from the Windows Start menu choose All Apps > Noldus > EthoVision XT 18 Other Documentation. Working With Groups Of Phenotypers You can have one to 16 PhenoTypers controlled by one EthoVision XT computer. When working with more than 16 PhenoTypers, it is advisable to use multiple computers. This optimizes level of throughput and video resolution, which ultimately affect data quality. Experiments Create one EthoVision XT experiment in each PC controlling a group of PhenoTypers. However, if you plan to conduct the same test with two or more groups of PhenoTypers, it is wise to create a template experiment: 1. Choose File > New from Template. 2. Select the PhenoTyper configuration, whether it includes zones of interest etc. 3. Draw the arenas, zones and adjust the detection settings (page 57). 4. Choose File > Make backup. Copy the backup file to the other computers controlling a group of PhenoTypers. 5. On each computer, choose File > Restore backup. Save the experiment with a unique name for example PhenoTyper Group A, B, C, etc. Assign arenas to the PhenoTypers When you mix the image of 8 or 16 PhenoTypers, each group of four cages will be displayed in a quarter of the monitor window (A to D in the figure below). In the mixed video image, group A with PhenoTypers 1 to 4 will be shown in the top-left corner. After creating an EthoVision XT experiment, define the number of arenas in the Experiment Settings (8 or 16). When opening the Arena Settings, the arenas are sorted in rows, that is, the first row contains Arenas 1 to 4, corresponding to PhenoTypers 1 and 2 of Group A and PhenoTypers 5 and 6 of Group B. For example, the label Arena 3 is placed over the image of the first PhenoTyper in Group B, while the label Arena 5 is placed over the third PhenoTyper in Group A. This could cause some confusion. To create a more logical correspondence between PhenoTyper number and Arena number, do one of the following: Exchange the cables from the quad unit, in such a way that phenotypers of one group are displayed on the same row on the monitor. Alternatively, in EthoVision XT, re-order the arenas, for example exchange Arena 3 with Arena 5. First, de-select Arena 9 or other arenas in the Arena Settings panel to have more space where to place object temporarily. Drag with the mouse to select a rectangle around the first arena that you want to move, including its zones and labels. Make sure that you do not select the zones of neighboring arenas. Next, drag the objects to the temporary position. Repeat the step above to move the second arena to the new position. Finally, move the first arena to the new position. Repeat the steps for the other arenas that need to be swapped. Analyze data from multiple experiments If you want to analyze the data of PhenoTypers of multiple groups, you can open a master experiment and import the trials from the original experiments associated with those groups. Note that in order to import trials from multiple computers, the settings in the experiments must be identical. For example, the zone names. For information on importing trials from other experiments, see the topic Import trials from other experiments in the EthoVision XT Help. Connect Additional Devices TTL devices Use the USB-IO box (TTL Control panel) to connect any other TTL compatible device. For example, the Noldus Pellet dispenser. SDI devices Use the USB-IO box (SDI Control panel) to connect SDI devices like the Lickometer and PhenoCount. For more information See the following manuals: For devices that work with PhenoTyper, the PhenoTyper - EthoVision XT 18 - Service Manual. For the USB-IO box, the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. For defining and mapping devices in your EthoVision XT experiment, the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Lighting Conditions PhenoTyper uses infrared as light source, and since the camera is infrared sensitive and is provided with an IR-pass filter, EthoVision XT works independent of external light conditions (day vs. night). However, the light we see also contains a variable amount of infrared frequencies, which is seen by the camera and therefore may compromise detection by EthoVision XT. For example, direct sunlight or light produced by bulb lamps contain a lot of infrared light. If you need extra visible light in your test room, use tube lamps and LED lamps, which produce little or no infrared light. This minimizes the amount of infrared light that comes from outside the PhenoTypers. Test The Phenotyper's Functions - If you want to test the infrared light source, follow this step. Otherwise, go to step 2. Connect the video cable from PhenoTyper (or the quad unit if you work with multiple PhenoTypers) to a monitor or to the encoder board on your EthoVision XT computer. In the latter case, create a new experiment, next in the Experiment Settings select Live tracking, select the camera input and click the camera preview button. There you should see the live camera image. - Connect the Control Unit to the PhenoTyper's Top Unit by attaching the Control Unit cable to the PhenoTyper's 15-pin Sub-D socket located on the front panel, next to the red LED. - Switch on PhenoTyper. Result - The Control Unit's LCD display switches on. Some of the lamps may burn less intensely than others when they are switched on. Wait a few seconds until all lamps burn equally. - Press one of the Control Unit FUNCTION buttons one or more times to select the device (1 to 6). Each time you press a button, the Control Unit display changes: 1 BUZZER 2 White LED 3 Yellow LED 4 IR array-1 5 IR array-2 6 IR array-3 READ FROM PT WRITE TO PT 1 BUZZER In the following example, we have selected the white light: Result - The corresponding light turns on (see below for infrared lights). Do not press the TEST button at this point! If you do, light intensity may change because the value read from another cage is copied to that cage. 5. To test the buzzer, select 1 BUZZER and press the TEST button. Press TEST again to stop the buzzer. If sound does not work when you connect multiple PhenoTypers, it is likely that the jumpers inside the Top Units are not set correctly for EthoVision XT. For information on jumper settings, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Adjust Light Intensity Use the instructions below if you want to change the intensity of light produced by PhenoTyper. If you need to customize light intensity of two or more PhenoTyper cages, copy the light settings from one cage to the next (see page 52). 1. Connect the Control Unit to PhenoTyper (see page 49). 2. Switch on PhenoTyper. Result - The Control Unit's LCD display switches on. Some of the lamps may burn less intensely than others when switched on. Wait a few seconds until all lamps burn equally. 3. Press one of the Control Unit's FUNCTION buttons one or more times to select the device. Each time you press the UP button, the display changes in the following way: 1 BUZZER 2 White LED 3 Yellow LED 4 IR array-1 5 IR array-2 6 IR array-3 1 BUZZER READ FROM PT WRITE TO PT 1 BUZZER Check the light intensity: Directly (for the yellow and white light spots). Through the camera image in EthoVision XT (for the IR light). If you have not done this yet, connect the video cable from the PhenoTyper to one of the video inputs of the encoder board on the EthoVision XT computer. Next, start EthoVision XT, create a new experiment, next in the Experiment Settings select Live tracking, select the camera input and click the camera preview button. There you should see the live camera image. 4. Press the LEVEL buttons on the Control Unit to increase or decrease light intensity. Notes The values shown on the Control Unit screen can range from 0 to 200 (this indicates the current in mA) for the yellow and white lights, and from 0 to 100 for the infrared lights. Please note that even if you set the value to the minimum (that is, 0) the lights are still switched on, although the light intensity is very low. Intensity values are stored in the non volatile EEPROM memory of the PhenoTyper's Top Unit. Therefore, once you set the values you want, you do not need to check them the next time you work with PhenoTyper, even if power was turned off. Measure light intensity with a light meter or a light meter app for smartphones that you can download from the internet. Make sure that the white/yellow light intensity is equal between cages, and that it does not change with time (unless for reasons related to the experimental treatment). You cannot change the intensity of the sound produced by PhenoTyper. The duration of the signals cannot be set from the Control Unit. You set this in EthoVision XT, using Time conditions in the Trial Control Settings. For details. see Trial Control Settings in the EthoVision XT Help, and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Copy Light Intensity Values From One Phenotyper To Another This section only applies to PhenoTyper 1 (analog camera). You can copy the values of light intensity (infrared LED arrays and visible light spots) from one cage to other cages. If you want to copy one value only (for example, the intensity of the yellow light), first copy all values from one cage (see below) and then write the value you require to the other cages (see page 53). Read the values from PhenoTyper - Connect the Control Unit to the PhenoTyper cage you want to copy the values from (see connect one phenotyper to the pc on page 37) and switch on that cage. 2. Press the FUNCTION buttons until READ FROM PT is shown on the Control Unit display. 3. Press TEST. Result - The Control Unit reads the light intensity values from all sources (IR, yellow and white). The yellow and white light switch on and the Control Unit display shows 'READING...' until the reading process is completed. 4. Follow one of the procedures below to copy the values to the other cages. Write all values to PhenoTyper - Connect the Control Unit to the PhenoTyper cage you want to copy the values to (see connect one phenotyper to the pc on page 37) and switch on that cage. 2. Press the FUNCTION buttons until WRITE TO PT is shown on the Control Unit display. 3. Press TEST. Result - The Control Unit writes the light intensity values for all sources (IR, yellow and white) to the cage. The yellow and white light switch on and the Control Unit display shows 'WRITING...' until the writing process is completed. If a value copied differs from that currently selected in the cage, the Control Unit display shows Increase... or Decrease... while the intensity is increased or reduced to match the value copied, respectively. When the display shows WRITE TO PT again, all values are updated. Repeat the procedure to copy the values to other cages. Write a single value to PhenoTyper - Make sure that you have read the light intensity values from a cage (see above). - Connect the Control Unit to the PhenoTyper cage you want to copy the value to (see connect one phenotyper to the pc) and switch on that cage. 3. Press the FUNCTION buttons until the light device you want to update is selected. 4. Press TEST. Result - The Control Unit writes the light intensity value to the cage. If you have selected the yellow or the white light, these switch on for a short time. The display shows 'WRITING...' until the writing process is completed. If the value copied differs from that currently selected in the cage, the Control Unit display shows Increase... or Decrease... while the intensity is increased or reduced to match the value copied, respectively. When the display shows WRITE TO PT again, the value is updated. Repeat the procedure to copy the values to the other cages. Example: Copy the light intensity value of IR array-1 value from cage 1 to cage 2: 1. Connect the Control Unit to cage 1 and read the values (see above) 2. Connect the Control Unit to cage 2 and press the FUNCTION buttons until you see 4 IR array-1. 3. Press TEST. 4. When the display shows 4 IR array-1 again, the value is updated. The Phenotyper Camera Camera orientation If the camera does not point to the center of the cage bottom, and some parts of the cage like the feeder are not visible enough, you can change the orientation of the camera. For more information, see the PhenoTyper - EthoVision XT 18 - Service Manual. Lens focus If the camera image is out of focus: 1. The camera is in the center of the Top Unit's covering plate. Remove the ring around the lens, and rotate the lens ring. 2. Put the test animal (or an object of approximately the same height) in the cage. 3. Put the Top Unit back on the cage. Check in EthoVision that the test animal/object is on focus. If you have a NTSC Top Unit with serial number 01000 or below, you have to remove the covering plate. Turn off PhenoTyper, unscrew the covering plate, and loosen a small screw on the lens, then rotate the focus ring. When closing the Top Unit, do not over-tighten the first screws! Doing so may make it difficult to put the remaining ones in the right place. Instead, insert first two or three screws on different sides of the plate, and turn them 2-3 times. The plate should be still free to move at this stage. Move the plate so that the remaining screws can fit in the corresponding holes. Additional settings for PhenoTyper 1 Although the PhenoTyper camera is optimized for video tracking, there may be cases when you need to adjust some camera settings. For example, when the image of the animal is too bright, you can switch off the Automatic Gain Control and adjust the Shutter speed. PhenoTyper Top Units with a serial number between 01051 and 01412 are equipped with OSD functionality. For details, see the PhenoTyper - EthoVision XT 18 - Service Manual, under The PhenoTyper Top Unit Camera > Camera Settings. For Top Units with serial number above 1470, contact Noldus to order an OSD controller. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - 4 Set up an experiment with PhenoTyper 1 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-4-set-up-an-experiment-with-phenotyper-1 Chapter: EthoVision XT Set Up An Experiment With PhenoTyper 1 For this section you need: PhenoTyper 1 and the USB-IO box. Create An Experiment - Choose File > New from Template. In the Select a template option window, select Apply a pre-defined template. - Follow the instructions in the guided setup. Under How is the arena configured, choose PhenoTyper (for one cage) or PhenoTyper, quad (four cages). After you have created the new experiment, you must still check/ adjust Experiment Settings, Arena Settings and Detection Settings before you can track any animal correctly. Experiment Settings Select the cameras - In the Experiment Explorer, click Experiment Settings. - Under Video source, select the number of cameras from the list next to Number of sources. For PhenoTyper 1 (analog camera): If you use a quad unit to mix four camera images, select 1. Select your cameras under Sources. For more information, see the EthoVision XT Help. Configure the devices of PhenoTyper 1 with the USB-IO box Follow this procedure if you have connected PhenoTyper to EthoVision XT through the USB-IO box. 1. In the Experiment Settings, next to Trial Control Hardware, select Use of Trial Control Hardware and click Settings. In the window that pops up, select Noldus USB-IO Box and click OK. 2. In the Device Configuration window, locate the row SDI Port 13 and check that under Device Type, Top Unit Interface PTTI-0010 is selected. Top Unit (Standard) should be selected for each PhenoTyper that you connected to the Top Unit Interface. In the same way, assign a Pellet Dispenser or custom TTL hardware device to a TTL Port. Note that the Noldus Lickometer and PhenoWheel are SDI devices. Assign those devices to a SDI port. For the procedure to test the connected hardware, See arena settings (page 59). Additional options To detect freezing behavior, under Analysis options select Activity analysis. Click the video button next to it and watch the video tutorial to learn about Activity analysis. If you work with rats, you can let EthoVision XT automatically detect behaviors like grooming, drinking, eating and rearing. Select Behavior recognition under Analysis Options. You need the Rat Behavior Recognition Module for this automatic behavior recognition. Arena Settings Choose Setup > Arena Settings and open Arena Settings 1. For details, see Arena Settings in the EthoVision XT Help. Calibration Click Draw Scale to Calibrate and draw a line between two opposite cage walls or along an object of known length. Do this for both dimensions. Enter this length after drawing the line. For reference, the PhenoTyper cage width is 30 cm for model 3000, 45 cm for model 4500 and 90 cm for model 9000. Arena Click Select Shape and Draw Arena. Move the outline of the arena over the cage floor in the video image. Check that the arena covers the whole area in which you want to track the animal. Include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the pointing tip of the label stays within the arena. Repeat this step for all the cages in the video image. Zones Check that the Spotlight zone, Drinking zone, Feeding zone and Shelter zone with its Entry zones are positioned where the respective zones are on the video image, and that all have the correct shape. If necessary, adjust their size and position. If necessary, remove zones and/or draw additional zone groups/zones. If you want to know how often the animal is on top of the shelter, you have to create an extra shelter zone. If you use a Pellet Dispenser for learning tasks, create a zone where the pellet drops. Check that the pellets always fall within this zone. For testing anxiety-like behaviors, draw an additional zone in the center of each PhenoTyper. This way you can analyze the time that the subject spends in the center relative to the total time. This proves useful when comparing data obtained with PhenoTyper and those obtained with classic Open field or Elevated plus maze tests. Shelters If you put a shelter in PhenoTyper, we advise you to define it as a Hidden zone. This way, from the time the animal enters the shelter to the time it is detected again, EthoVision XT records the animal as being in that zone. To define a hidden zone, draw a zone corresponding to the shelter and specify it as hidden zone. For more information, see Hidden zones in the EthoVision XT Help. Arena settings for Rat behavior or Mouse behavior recognition When you selected Behavior recognition (only available when you have the Rat Behavior Recognition Module or Mouse Behavior Recognition Module of EthoVision XT), in the Experiment Settings, defining a few special zones and points significantly increases behavior recognition accuracy. See Zones and points for Behavior recognition in the EthoVision XT Help. Figure 7 PhenoTyper with Spotlight zone, Food zone, Drinking zone and the hidden Shelter zone with two Entry zones. Assign The Phenotyper Devices To The Arenas For this procedure you must have the Trial and Hardware Control Module. Open the Arena Settings and follow the instructions below. Assign the devices of PhenoTyper 1 connected to the USB-IO box - In the Arena - Hardware Mapping window, you should see as many rows as device added in the Experiment Settings. If not, click Add device for each device you want to add. For example, for four PhenoTypers, click Add device four times. 2. Under Device Type, select Top Unit (Standard) if it is not selected already. For four PhenoTypers, you should see four rows, each with Top Unit Standard selected. 3. Under Device Name, enter a name (e.g. PhenoTyper Top Unit) or accept the default name (A, B, C...). 4. For each Arena, select the corresponding Top Unit (Standard) #. Scroll the table to the right when needed. For multiple PhenoTypers: Make sure that a each Top Unit is assigned to only one Arena (PhenoTyper cage), and that each Arena hosts only one Top Unit. 5. For other devices, click Add device. Repeat the steps above for the Noldus Lickometer, Pellet Dispenser, and PhenoWheel. For a third-party hardware device, under Device Type, select Custom Hardware. Enter a name under Device name and select one of the physical devices from the list for each Arena. For more information about this step, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. To test a device Click the name of the device you want to test, and click Test. Select the action you want to test and click Test. For more information on a device, see the PhenoTyper 2 - Service Manual. Trial Control Settings For more information on Trial Control, see Trial Control Settings in the EthoVision XT Help, and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. See also the chapter Common tests with PhenoTyper. Detection Settings For more information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - 5 Set up PhenoTyper 2 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-5-set-up-phenotyper-2 Chapter: EthoVision XT Set Up PhenoTyper 2 Aim This section is about connecting and adjusting the settings of PhenoTyper 2. This is the version with the TopPlate hosting a digital camera. Topics cables and adapters - page 64 connect one phenotyper to the pc - page 65 connect multiple phenotypers to the pc - page 67 working with groups of phenotypers - page 76 connect additional devices - page 76 lighting conditions - page 76 test the phenotyper's functions - page 76 adjust light intensity - page 77 the phenotyper camera - page 78 add a ttl-controlled module - page 79 Cables And Adapters A, B - Power cord and transformer (see Figure 5). For PhenoTyper 2: code MAPS-0014. C - Power feed-through cable (see Figure 5) for connecting two PhenoTypers. For PhenoTyper 2: code PT-PSC. D - Cross network cable with RJ45 connectors for connecting the digital camera to the EthoVision XT PC. If you purchased the USB-IO box, you also have the following cables: Network cables (as many as PhenoTyper Top Units). USB cable with connectors of type A and B. Power cord and DC adapter 24 V 3A for the USB-IO box. Connect One Phenotyper To The Pc Power and video - Connect the IN socket og the TopPlate TTL Interface to the power outlet using the elements A and B (see Figure 5, page 36). - Connect the camera's Ethernet socket to one of the ports of the Ethernet interface board on your computer, using a cross-network cable with RJ-45 connectors (D). - Furthermore, you must set the IP address in the digital camera and the port on the Ethernet interface board. For how to do so, see Configure the digital camera the EthoVision XT Help or watch the video tutorial Set up your cameras in EthoVision XT. Control of the white light with the USB-IO box Follow this section if you have the USB-IO box. 1. Connect the USB port of the USB-IO box to one of your PC's USB ports using the USB cable that comes with the IO box. 2. Connect the TTL 1 port (or another one available) of the USB-IO box to the TTL 1 port of the TopPlate TTL Interface. 3. Make sure that the USB-IO box is connected to the power outlet as shown in the figure above. Notes For information about the USB-IO box, see the - EthoVision XT 18 - Trial and Hardware Control - Reference Manual. At the time of release of PhenoTyper 2, control is limited to the PhenoTyper white light. Contact Noldus to discuss possible extensions. See also add a ttl-controlled module on page 79 Connect Multiple Phenotypers To The Pc Power and video - Connect the first PhenoTyper's 24 VOLT IN socket to the power outlet using the elements A (MAPS-0014) and B (page 36). Repeat this step for every other PhenoTyper in the group, that is, the first of each pair. important Connect a maximum of two PhenoTyper TTL Interfaces to the same power supply! 2. Using power feed-through cables (C), connect the 24 VOLT OUT socket of the first PhenoTyper to the 24 VOLT IN socket of the second. Connect the 24 VOLT OUT socket of the third PhenoTyper to the 24 VOLT IN socket of the fourth, and so on. 3. Connect each PhenoTyper's camera to one of the ports of the Ethernet interface board on your computer, using a cross-network cable with RJ-45 connectors (D). Notes Resolution of each camera image: 1280 x 1024. When using four PhenoTypers, the resolution of the resulting video is 2560 x 2048. When using more than two PhenoTypers, connect each pair of PhenoTypers to a separate power outlet. Video resolutions that work in PhenoTyper 2 Note that the maximal resolution attainable in your system is also depending on the frame rate and the tracking methods. Open the EthoVision XT Help (press F1 in the software) and see the topic GigE cameras for a list of tested configurations. (*) Set the following in EthoVision XT (Experiment Settings): Frame rate: 30 fps. Higher frame rates may result in camera connection being lost. You can find the Frame rate option in the Experiment Settings > click the camera button > Format tab. Binning: 2. You can find the Binning option in the Experiment Settings > click the camera button > General tab. With Binning set to 2, the resolution of the single camera view is half of the original, while the image is not cropped. tip If you want to return to the full resolution, de-select Binning, click OK and in the Experiment Settings click the Refresh button, then click again the camera button. important Do not forget to update the background image in the Arena Settings whenever you change the video resolution! Record video to separate files You can use MediaRecorder to save video from each cage to a separate video file, at the maximal resolution. See Record video to separate video files on page 42. Nr. cameras Single camera Merged view Connections 1280 x 1024 page 65 1280 x 1024 2560 x 1024 page 67 1280 x 1024 2560 x 2048 page 67 640 x 480 2560 x 960 page 69 16 (*) 640 x 480 2560 x 1920 page 72 Control of devices with the USB-IO box - Connect the USB port of the USB-IO box to one of your PC's USB ports using the USB cable that comes with the IO box. - Connect the 24 V IN port of the USB-IO box to the power outlet using its adapter. - Connect a TTL port on the USB-IO box to the TTL 1 port of each PhenoTyper, using the network cables with RJ-45 connectors at their ends. This line controls the white light. - If your PhenoTypers have additional modules that can be controlled through TTL, connect the TTL ports of the USB-IO box to TTL ports 2 to 4 of each PhenoTyper. For a 8-PhenoTyper configuration you can also use the solution for 16 PhenoTypers. See page 72. Hardware and settings 1x 4-port AdLink PCIe-GIE74 Ethernet interface board. 2x Network switches (tested switch: Netgear S350 Series 8-Port Gigabit PoE+). Only use network switches with at least 1Gb Ethernet ports. Also the Ethernet network interface board must have 1Gb ports. See the suggestions in the section Camera Installation in the EthoVision XT Help. The network switches must have at least n+1 Ethernet ports, where n is the number of PhenoTypers connected to the switch. The network switches must provide power over Ethernet (PoE) to the cameras. Alternatively, you must connect each camera to the switch through a separate PoE injector with its own power plug. This increases the complexity of cabling. Procedure - Install the Ethernet network interface board on the PC and the network switches. - Connect each PhenoTyper camera to a Ethernet port of the network switch (four cameras per switch). - Connect the network switches to two ports of the Ethernet board on the PC. - Assign an unique IP address to each port on the network switch that is connected to a camera. - Assign an IP address to each camera that matches the first three numbers of the IP address of the port on the network switch that camera is connected to. See the figure below for an example. important Keep the first two numbers 192.168 of the IP address for all ports and cameras. The network switches must be of type PoE (Power over Ethernet), that is, they must provide power to the cameras. Mind that the maximum power provided by a switch, measured in Watt (W), must be greater than that the total requirements of the cameras (one Basler camera requires about 2.5 W) and the other devices connected to the switch. The network switches must be able to handle large packets (known as "jumbo packets" or "jumbo frames"). With jumbo frame-capable devices, the maximum packet size can be up to 16 KB. For maximum network efficiency, your camera should be configured to use the largest packet size that your network adapters and switches can handle. For information on how to assign IP addresses, see Install the GigE camera on the EthoVision XT Help. Refer to the user guide of the network switch for how to set it up. Video resolution Single camera view: 640 x 480. Merged 8-camera image: 2560 x 960. To set the resolution, open the Experiment Settings, under Video Source select Live tracking and choose 8 as Number of sources. Select all the cameras and make sure that the resolution of the single cameras is 640 x 480 and that of the Merged camera view is 2560 x 960. For this configuration you need a high-end workstation (see page 74). Hardware and settings 16 Basler GigE cameras acA1300-60gm. PCIe Ethernet interface board: FS X550-AT2, 10GBase-T Dual-Port, PCIe 3.0 x4. Network switch: FS S3100-16TMS-P, 16-Port Gigabit Ethernet L2+ PoE+, 8x PoE+ Ports@125W, 2x 5Gb RJ45, with 2x 10Gb SFP+ Uplinks. An adapter (SFP+ 10GBASE-T Copper 30m RJ-45 Transceiver module) for the network cable that goes from the PC to the network switch. We recommend to use CAT6+ network cables. Procedure - Install the Ethernet network interface board on the PC and the network switch. - Connect each PhenoTyper camera to a Ethernet port of the network switch. If you use the network switch FS S3100-16TMS-P, or similar switches with only a fraction of the ports being powered, connect the remaining cameras through a PoE injector. Alternatively, use a network switch with 16 powered ports. - Connect the network switch to one of the ports of the Ethernet board on the PC. - Assign an unique IP address to the port on the Ethernet board that is connected to the network switch. - Assign an unique IP address to each camera that matches the first three numbers of the IP address of the port on the Ethernet board. See the figure above for an example. Notes The network switches must be of type PoE (Power over Ethernet), that is, they must provide power to the cameras. If the switch has only a limited number of powered ports, you must use PoE injectors for the remaining ports. The maximum power provided by a switch, measured in Watt (W), must be greater than that the total requirements of the cameras (one Basler camera requires about 2.5 W) and the other devices connected to the switch. The network switches must be able to handle large packets (known as "jumbo packets" or "jumbo frames"). With jumbo frame-capable devices, the maximum packet size can be up to 16 KB. For maximum network efficiency, your camera should be configured to use the largest packet size that your network adapters and switches can handle. For information on how to assign IP addresses, see Install the GigE camera on the EthoVision XT Help. Refer to the user guide of the network switch for how to set it up. Tested configuration Tested PC: Dell Precision 3680, CPU i7-14700K 3.4 GHz, RAM memory 32GB, GPU NVIDIA T1000 8 GB; Windows 11 Pro 23H2. Experiment Settings in EthoVision XT: Video source: Live tracking; Image binning (in Video settings): 2. Number of subjects per arena: 1; Tracked features: Center-point, nose-point and tail-base detection; Body Point Detection Technique: Contour-based. Detection Settings: Dynamic Subtraction or Differencing. Acquisition mode: Track + Save video. Video frame rate: 30 fps. Trial duration: 72 hours. Video resolution Single camera view: 640 x 480. Merged 16-camera video image: 2560 x 1920. To set the resolution: 1. In EthoVision XT, open the Experiment Settings and under Video Source select Live tracking and choose 16 as Number of sources. 2. Select the first camera. Make sure that the resolution of the single cameras is 1280 x 1024. 3. Click the camera button and in the General tab set the Binning to 2. This rescales the image without cropping it. 4. Select the remaining cameras from the first list and make sure that the Bigging option is set to 2. 5. Make sure that the Merged camera view is 2560 x 1920. tip Put a sheet with a number in each PhenoTyper cage. That way you easily see which PhenoTyper camera has been selected. Select the first four cameras for group 1, then the fifth to the eighth for group 2, etc. Working With Groups Of Phenotypers See the section on working with groups of phenotypers on page 44. Note that with PhenoTyper 2 we recommend to connect up to 16 cages (when recording video only) or 12 cages (when controlling PhenoTyper through TTL) to one EthoVision XT computer. Connect Additional Devices You can have EthoVision XT control PhenoTyper and additional devices. See the section connect additional devices on page 47. Lighting Conditions The general recommendations about lighting in the test room for PhenoTyper 1 are also valid for PhenoTyper 2. See lighting conditions on page 48. Test The Phenotyper's Functions Camera image and the infrared light source: - Connect the network cable from the PhenoTyper camera to one of the ports of the Ethernet interface board on the EthoVision XT computer. For information on how to set up the IP addresses of the camera and of the Ethernet interface board, see the EthoVision XT Help. - Start EthoVision XT, create a new experiment, next in the Experiment Settings select Live tracking, select the camera input and click the camera preview button. There you should see the live camera image. 3. Switch off all the light in the room. If the infrared light source works properly, you should see a clear image of the cage bottom. White light - Press the white - test button on the front panel of the TopPlate TTL Interface. - Check that the light inside the cage switches on. Adjust Light Intensity PhenoTyper 2 (digital camera) For this you need the trimmer adjustment tool that is provided with the PhenoTyper TopPlate TTL Interface, or a small screwdriver. To adjust the intensity of the infrared light: 1. Connect the network cable from the PhenoTyper camera to one of the ports of the Ethernet interface board on the EthoVision XT computer. For information on how to set up the IP addresses of the digital camera and of the Ethernet interface board, see the EthoVision XT Help. 2. Start EthoVision XT, create a new experiment, and in the Experiment Settings select Live tracking, then select the camera input from the list and click the camera preview button. There you should see the live camera image. 3. Turn the IR control on the TopPlate TTL Interface, as indicated with the arrows. 4. Check the image in the EthoVision XT screen. To adjust the intensity of the white light: 1. Turn the WHITE control on the TopPlate TTL Interface, as indicated with the arrows. 2. Check the intensity of the white light in the cage. Make sure that the white light intensity is equal between cages, and that it does not change with time (unless for reasons related to the experimental treatment). tip Measure light intensity with a light meter or a light meter app for smartphones that you can download from the internet. Repeat the procedure for the other cages. The Phenotyper Camera Lens focus The camera focus is optimized at production. For more information on the camera and lens, see the PhenoTyper 2 - Service Manual. Advanced camera settings The Basler acA1300-60gm is the default camera of PhenoTyper 2. For extensive information on camera settings (resolution, frame rate, exposure, gain etc.) and for how to install and configure the camera in EthoVision XT, see Install GigE cameras in the EthoVision XT Help. Add A Ttl-controlled Module Aim To control an additional TTL device, like a spotlight. The type of control is currently limited to On/Off. You can have EthoVision XT switch on and off the spotlight, however you cannot adjust the light intensity through the software. Fit the new module on the Top Plate Remove the cover plate from one of the slots of the Top Plate. Insert the new module and gently press it in such a way the connectors come in contact. Fix the module with the two screws. Current TTL ports configuration TTL 1 is reserved for the PhenoTyper White light. It is not available for use with other modules. TTL 2 and TTL 3 are set to output by default. Through these ports you can have EthoVision XT send out On/Off commands to the device you have added. That is, the signal always goes from EthoVision XT to the device through the (mini) USB-IO box. In EthoVision XT Trial Control Settings, choose Output Line 1 for that device. TTL 4 is currently not available. note The name Output line refers to the internal lines that you can set for each port of the interface device - the (Mini) USB-IO box. In general, for each port of those interface devices two output lines (Output Line 1 and Output Line 2) and two input lines (Input Line 1 and Input Line 2) are available. You can specify them in the EthoVision XT Trial Control Settings. For PhenoTyper 2, only Output Line 1 applies currently. For more details, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual (see page 7). Advanced solutions If you need additional configurations, contact your nearest Noldus representative. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - 6 Set up an experiment with PhenoTyper 2 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-6-set-up-an-experiment-with-phenotyper-2 Chapter: EthoVision XT Set Up An Experiment With PhenoTyper 2 For this section you need: PhenoTyper 2 and the USB-IO box. Create An Experiment Prerequisites You have followed the section Set up PhenoTyper 2 on page 63. Procedure - Choose File > New from Template. In the Select a template option window, select Apply a pre-defined template. - Follow the instructions in the guided setup. Under How is the arena configured, choose PhenoTyper (for one cage) or PhenoTyper, quad (four cages). After you have created the new experiment, you must still check/ adjust Experiment Settings, Arena Settings and Detection Settings before you can track any animal correctly. Please follow the steps below. Experiment Settings Select the cameras - In the Experiment Explorer, click Experiment Settings. - Under Video source, select the number of cameras from the list next to Number of sources. Select your cameras under Sources. For more information, see the EthoVision XT Help. Configure the devices of PhenoTyper 2 (USB-IO box) Follow this procedure if you have connected PhenoTyper 2 to EthoVision XT through the USB-IO box. With this setup you can control the white light. 1. In the Experiment Settings, next to Trial Control Hardware, select Use of Trial Control Hardware and click Settings. 2. In the window that pops up, select Noldus USB-IO Box and click OK. 3. In the Device Configuration window, locate the TTL Port of the USB- IO box that is connected to the PhenoTyper Control Unit (TTL 1). note The SDI ports do not work with PhenoTyper 2. 4. Under Device Type select PhenoTyper 2 TTL 1 White Light (PT2I- 01_TTL) to control the white light. To control another module, select one of the other options (PhenoTyper 2 TTL 2 Module or PhenoTyper 2 TTL 3 Module). Note that modules other than the White Light are not standard; you have to purchase them separately. 5. Repeat the steps 3-4 for each PhenoTyper, then click OK. Example with four PhenoTypers: Analysis Options Activity analysis. Under Analysis Options select Activity analysis to detect freezing behavior. Behavior recognition. Under Analysis Options select Behavior recognition. If you work with rodents, you can let EthoVision XT automatically detect behaviors like grooming, drinking, eating and rearing. For this option, you need the Rat/Mouse Behavior Recognition Module. Arena Settings For drawing arenas and zones, see page 59. Assign The Phenotyper Devices To The Arenas For this procedure you must have the Trial and Hardware Control Module. Open the Arena Settings and follow the instructions below. Assign the devices of PhenoTyper 2 connected to the USB-IO box Prerequisite: you have followed the previous step on page 82. 1. In the Arena - Hardware Mapping window, click Add device. 2. Under Device Type, select the type of device. For the standard white light, choose PhenoTyper 2 TTL 1 White Light. 3. Under Device Name, enter a name (for example, PhenoTyper White Light), or accept the default name (Device A, Device B, etc.). 4. For each Arena, select the physical device that is associated with that arena. For example, PhenoTyper 2 TTL 1 White Light 1 under Arena 1, PhenoTyper 2 TTL 1 White Light 2 under Arena 2, etc. Which device you should select depends on which TTL port of the USB-IO box is connected to that PhenoTyper (Arena). tip Scroll the table to the right to view the remaining arenas. 5. To add more devices, click Add device. for the Noldus Lickometer, Pellet Dispenser, and PhenoWheel, Under Device Type, repeat the steps from 2 above. For a third-party hardware device, under Device Type, select Custom Hardware. Enter a name under Device name and, for each arena, select one of the physical devices from the list. For more information about this step, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Trial Control Settings In the Trial Control Settings you can define the events that take place during the trial and at which condition. For example, have the software switch a light For more information on Trial Control, see Trial Control Settings in the EthoVision XT Help, and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. See also the chapter Common tests with PhenoTyper. Detection Settings For more information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - 7 Common tests with PhenoTyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-7-common-tests-with-phenotyper Chapter: EthoVision XT Common Tests With PhenoTyper Short-term experiments can be carried out while the subjects are monitored in PhenoTyper. This can be, for example, learning tasks, anxiety tests, or tests on the effects of drugs. For information on how to set up an experiment in EthoVision XT, see Set Up an Experiment in the EthoVision XT Help. general behavior monitoring - see below. create routines - page 88. food receiving task - page 89. illuminated shelter task - page 92. cognitionwall™ task - page 95. anxiety tests - page 96. General Behavior Monitoring Maximum trial duration (tested) With or without simultaneous video recording: 72 hours. For more information on tested configurations, see the EthoVision XT Help. To open the Help, in EthoVision XT choose Help > Help Topics. Prolonged video recordings If you need to record video of the same subject for more than 72 hours, we recommend that you make a series of trials. 1. In the Trial Control Settings, remove the condition immediately before the Start track action box. 2. In the Trial Control Settings, set the Maximum Trial Duration. tip To make a trial of about 72 hours, set this time to 72 hour minus x minutes. The remaining x minutes are used as inter-trial interval (see below) to give the software enough time to save the video and the data. In this example 72 h minus 5 minutes = 4315 minutes. 3. In the Acquisition screen, select Track all planned trials with an inter-trial interval equal to the time x chosen above. If you want to select a shorter time, test it beforehand. 4. After data acquisition, and before running analysis, open a Data profile and group the trials based on the subject. Selected references Bass, J. S., Tuo, A. H., Ton, L. T., Jankovic, M. J., Kapadia, P. K., Schirmer, C., et al. (2020). On the digital psychopharmacology of valproic acid in mice. Frontiers in Neuroscience 14: 594612. doi: 10.3389/ fnins.2020.594612 de Visser, L., van den Bos, R., Stoker, A. K., Kas, M. J. H., and Spruijt, B. M. (2007). Effects of genetic background and environmental novelty on wheel running as a rewarding behaviour in mice. Behavioral and Brain Research, 177: 290 - 297. doi: 10.1016/j.bbr.2006.11.019 Deiana, S., Platt, B., and Riedel, G. (2008). Scopolamine-induced changes in activity measured in a home cage observation system. Proceedings of Measuring Behavior 2008 (Maastricht, The Netherlands, August 26-29, 2008): 312-313. de Mooij-van Malsen, A. J. G., van Lith, H. A., Oppelaar, H., Hendriks, J., de Wit, M., Kostrzewa, E., et al. (2009). Interspecies trait genetics reveals association of Adcy8 with mouse avoidance behavior and a human mood disorder. Biological Psychiatry, 66: 1123 - 1130. doi: 10.1016/ j.biopsych.2009.06.016 Jankovic, M. J., Kapadia, P. P., and Krishnan, V. (2019). Home-cage monitoring ascertains signatures of ictal and interictal behavior in mouse models of generalized seizures. PLoS One, 14:e0224856. doi: 10.1371/journal.pone.0224856 Namdar, I., Feldman, R., Glazer, S., Meningher, I., Shlobin, N. A., Rubovitch, V., et al. (2020). Motor effects of minimal traumatic brain injury in mice. Journal of Molecular Neuroscience, 70: 365 - 377. doi: 10.1007/s12031-019-01422-9 Create Routines In a conditioning test, drop a food pellet when the animal has been detected on the shelter. Repeat this procedure as soon as the animal eats the food item. The trial must be stopped when the procedure is repeated 25 times. Between two subsequent repeats, an interval of 10 s is defined. The corresponding sequence is defined as a Sub-rule in the Trial Control Settings. With the following boxes: Rule Begin - Start of the sub-rule. Condition - Specifies that the animal must be in the zone Shelter. Action - Specifies the command Drop a pellet to the pellet dispenser. You must define this and all other devices in the Port Device Mapping and in the Arena - Hardware Mapping in order to be able to define actions on those devices. Condition - Specifies that the animal must be in the zone Feeder. Rule End - Stop of the sub-rule. Define a Reference for this sub-rule and specify that the sub-rule must be repeated 25 times and the Stop to Start interval for subsequent repeats is 10 seconds. Place the Reference box in the Start-Stop trial rule, immediately before the Stop track box. Figure 8 shows a rule with which a pellet is dropped every time the animal enters a trigger zone. In a similar way you can create a rule to switch on the light in a illuminated shelter when a particular entrance is chosen. See page 85 for those procedures. For more details about creating routines, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Food Receiving Task In a commonly used learning test, the animal receives a food pellet from the pellet dispenser when it enters a certain zone, for example when it jumps on top of the shelter. The test generally lasts 15 minutes, Figure 8 An example of a Trial Control rule to control the Pellet Dispenser. followed by a period of 1 hour in which no reward can be obtained. If the dark phase in which the animals are active lasts 12 hours, 10 tests can be carried out in this period. To give the test animal a cue that a reward can be obtained, the yellow light of the PhenoTyper is switched on in every 15 minutes testing period. In this test is assessed whether the frequency of moving from the shelter zone to the food pellet zone changes over time. Arena Settings - In the Arena Settings, create a zone for the top of the shelter. Note that this is not the same as the hidden zone used for detecting the animal when it is inside the shelter. - Define a zone for the area where the pellet is dropped. Check that the pellets always dropped in this zone. Especially when no bedding material is used, the pellets may roll far from where they are dropped. Trial Control Settings In the Trial Control Settings, create a Trial Control Rule for the Pellet Dispenser (for an example see page 88). Include conditions for the clock times the tests start and the action "PhenoTyper yellow light on". See the next page for an example of part of the Trial Control Rule. Create other necessary settings, like detection settings. Next, acquire the data. Data profile Create a Data Profile with multiple time conditions to filter out the 15 minutes periods. See below for an example. Analysis profile Create a analysis profile and select the dependent variable Zone transition. Under Settings select from the zone On top of Shelter to the Pellet Dispenser zone. Select Allow intermediate zone visits. Click the Trial Statistics tab and select Frequency. If you run multiple trials, click the Group statistics tab and select the Group mean and Standard Error of the Frequency. Calculate the statistics Make sure the data profile that filters the 15 minutes task periods is active. In the Experiment Explorer click Analysis output under Results. Click Calculate. The frequency of transitions from the top of the shelter to the pellet dispenser zone is now given for each 15 minute task period. If the animal learns, this number increases over time. Illuminated Shelter Task The illuminated shelter has been developed to automate the Discriminative Avoidance Task in mice in the PhenoTyper 3000. The aversive stimulus is generated by two light boxes, each housing a bright white LED and mounted on two cage walls, shining inwards through the Perspex wall into the shelter. The light is switched on briefly or continuously, depending on the presence of the mouse near or inside the shelter. Mice can learn to avoid the "preferred entrance" of the shelter. In a study with 43 different mouse mutants, Maroteaux et al. (2012) showed that mutants differ in their ability to associate a specific shelter entrance with the aversive stimulus A typical protocol is the following: Day 1-4. First it is assessed over the first four days which of the entrances is preferred by the animal. Day 5-6. For this trial, a Trial Control Rule is defined in which a light in the shelter is switched on when the animal uses the preferred entrance. Day 7. In the probe trial, during a 24 hr period it is checked if the animal learns to use the other entrance of the shelter. In the EthoVision XT experiment, define the following: Arena Settings In the Arena Settings create zones for both shelter entrances. These zones are predefined in the PhenoTyper template. Trial Control Settings Make a Trial Control subrule comparable with the example in Figure 8 on page 89. Create a condition for when the animal enters the zone "preferred shelter entrance" and an action to switch on the light in the illuminated shelter. Also create a condition and action to switch off the light in the shelter when the animal leaves it. Create other necessary settings, like detection settings. Next, acquire the data. Data profile In the Data profile, select the testing trials (days 5-6) or if the testing phase is part of an uninterrupted trial, create a Time filter for the 48 hr testing phase. Click the Settings button on the Result box and select Results per time bin. Use time bins of, for example, 1 hour. Time bins help find trends in cognitive and aversive responses; for instance, an increase in the use of the shelter entry that did not trigger the light. Analysis profile - To calculate statistics of each entrance, create an Analysis profile and select the dependent variable In Zone. Select both shelter entrances. Click the Trial Statistics tab and select Frequency. If you run multiple trials, click the Group statistics tab and select the Group mean and Standard Error of the Frequency. 2. Make sure the data profile that filters the 48-hr testing phase is active. In the Experiment Explorer click Analysis output under Results. Click Calculate. The frequency of visits to both shelter entrances is now shown for every time bin. References Heer, R.C. de; Schenke, M.; Kuurman, W.W.; Spruijt, B.M. (2008). Learning (in) the PhenoTyper: an integrative approach to conducting cognitive behavioural challenges in a home cage environment. Proceedings of Measuring Behavior 2008, 6th International Conference on Methods and Techniques in Behavioral Research (Maastricht, The Netherlands, 26-29 August 2008), 57. Maroteaux, G.; Loos, M.; van der Sluis, S.; Koopmans, B.; Aarts, E.; van Gassen, K.; Geurts, A.; The NeuroBSIK Mouse Phenomics Consortium; Largaespada, D.A.; Spruijt, B.M.; Stiedl, O.; Smit, A.B.; Verhage, M. (2012). High-throughput phenotyping of avoidance learning in mice discriminates different genotypes and identifies a novel gene. Genes, Brain and Behavior, 11: 772 - 784. doi: 10.1111/ j.1601-183X.2012.00820.x. Cognitionwall™ Task The CognitionWall was designed for the development of operant cognitive tests in PhenoTyper home-cages. The CognitionWall is a wall with three entrances, which is placed in front of the Pellet dispenser. Mice are rewarded with a food pellet when they choose to pass through one of the three entrances. The rate at which a mouse gains a relative preference for the rewarded entrance is used as a measure of discrimination learning. After an initial discrimination learning phase, the rewarded entrance is switched to another entrance (reversal). The rate at which a mouse gains a relative preference for the newly rewarded entrance is used as a measure of reversal learning. References Logan, S., Owen, D., Chen, S. et al. (2018). Simultaneous assessment of cognitive function, circadian rhythm, and spontaneous activity in aging mice. GeroScience 40: 123 - 137. doi:10.1007/s11357-018-0019-x Remmelink, E., Aartsma-Rus, A., Smit, A. B., Verhage, M., Loos, M. and van Putten, M. (2016), Cognitive flexibility deficits in a mouse model for the absence of full-length dystrophin. Genes, Brain and Behavior, 15: Remmelink, E., Chau, U., Smit, A. B., Verhage, M., and Loos, M. (2017). A one-week 5-choice serial reaction time task to measure impulsivity and attention in adult and adolescent mice. Scientific Reports, 7:42519. doi: 10.1038/srep42519 Anxiety Tests In anxiety tests, the exploratory behavior of the animals is tested. The animals are placed under mild stress by projecting a white light beam on the food area during the first three hours of the dark period, in which the animals are active. The animal must choose between feeding and avoiding the bright light. The time it takes before the animal starts feeding could reflect its level of anxiety. Arena Settings Define a zone for the feeding area. Trial Control Settings Create a Trial Control rule with an Action White light on, followed by a Time condition for the first three hours of the dark phase (i.e., "wait three hours"), followed by a second Action White light off which switches off the light after three hours. Create other necessary settings, like detection settings. Next, acquire the data. Data profile Create a data profile with a filter for the experiment time. Create a data profile with a filter for some time after the light on the feeding area has been switched off. For example, one hour. Analysis profile Create an analysis profile and select the dependent variable In zone. Select the zone Feeding area. Click the Trial Statistics tab and select Mean (gives mean duration per visit), Frequency (gives the number of visits), and Cumulative duration (gives the total duration over all visits). If you run multiple trials, click the Group statistics tab and select the Group mean and Standard Error for each statistic. Create an analysis profile and select the dependent variable In zone. Select the zone Feeding area. Click the Trial Statistics tab and select Latency to first. Next, select the correct combination of data profile and analysis profile. In the Experiment Explorer click Analysis output under Results. Click Calculate. Selected references Aarts, E., Maroteaux, G., Loos, M., Koopmans, B., KovaLcevi´c, J., Smit, A. B., et al. (2015). The light spot test: measuring anxiety in mice in an automated home-cage environment. Behavioral Brain Research, 294: de Mooij-van Malsen, A. J. G., van Lith, H. A., Oppelaar, H., Hendriks, J., de Wit, M., Kostrzewa, E., et al. (2009). Interspecies trait genetics reveals association of Adcy8 with mouse avoidance behavior and a human mood disorder. Biological Psychiatry, 66: 1123 - 1130. doi: 10.1016/ j.biopsych.2009.06.016 Prevot, T. D., Misquitta, K. A., Fee, C., Newton, D. F., Chatterjee, D., Nikolova, Y. S., et al. (2019). Residual avoidance: a new, consistent and repeatable readout of chronic stress-induced conflict anxiety reversible by antidepressant treatment. Neuropharmacology 153, 98 - 110. doi: 10.1016/j.neuropharm.2019.05.005 Other References de Visser, L. (2008). Home Sweet Home: Home Cage Testing for Behavioural Phenotyping of Mice. Dissertation Utrecht University, Faculty Veterinary Medicine. Grieco, F. et al. (2021) Measuring behavior in the home cage: study design, applications, challenges, and perspectives. Front. Behav. Neurosci. 15:735387. doi: 10.3389/fnbeh.2021.735387 Loos, M., Koopmans, B., Aarts, E., Maroteaux, G., van der Sluis, S., et al. (2014). Sheltering Behavior and Locomotor Activity in 11 Genetically Diverse Common Inbred Mouse Strains Using Home-Cage Monitoring. PLoS ONE 9(9): e108563. doi:10.1371/journal.pone.0108563 Maroteaux, G., Loos, M., van der Sluis, S., Koopmans, B., Aarts, E., van Gassen, K., Geurts, A., Largaespada, D. A., Spruijt, B. M., Stiedl, O., Smit, A. B. and Verhage, M. (2012). High-throughput phenotyping of avoidance learning in mice discriminates different genotypes and identifies a novel gene. Genes, Brain and Behavior, 11: 772 - 784. doi: 10.1111/j.1601-183X.2012.00820.x Pham, J., Cabrera, S. M., Sanchis-Segura, C., Wood, M. A. (2009). Automated scoring of fear-related behavior using EthoVision software. Journal of Neuroscience Methods, 178(2): 323-326. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - 8 Maintenance URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-8-maintenance Chapter: EthoVision XT Maintenance Your PhenoTyper cage will last longer if you follow these few recommendations. Please always keep the cages clean and dry. Make sure that no liquid penetrates the equipment on top of the cage. Clean The Cage General information The cage walls, the bottom plate and the shelter of PhenoTyper are made of Acrylic, also known as Polymethylmethacrylate or PMMA. To clean the cage, please use water and soap only, or wipes for alcohol- sensitive materials (see below). Do not wash the cage with water at more than 80 C (176 F). important - read this first Do not use chemicals to wash the cage except those listed in the next section. Whatever substance you use to clean PhenoTyper, wipe the surface completely dry. Make sure that droplets do not remain on any component of the cage. Do not use autoclaves to sterilize the cage or any of its components! It may damage it. Clean the cage walls provided with the pellet receptacle Beginning from items with serial number 132, the cage walls with a pellet receptacle can be cleaned without removing the pellet receptacle first. For those items, moisture is expected not to damage the circuits. You can also clean the inside of the receptacle by loosing the screws. However, if you want to clean the pellet receptacle thoroughly, follow this procedure: 1. Disconnect all cables and remove the wall with the pellet receptacle from the cage. 2. Unscrew the receptacle unit from the wall. 3. Remove the label with the serial number, or cut it through on the line between the black enclosure and the transparent support frame. 4. Gently pull out the two parts from the wall. Each part must be cleaned separately. Clean those parts just like you do for the regular cage walls. 5. Reassemble the components and attach them back to the cage wall. Acceptable Cleaning Techniques And Substances important Noldus takes no responsibility for any damage resulting from improper use of cleaning substances. Always test a substance when in doubt. Always remove remaining liquid after cleaning. Use the following substances and techniques to clean the cage walls, the shelter and the bottom plate. For the drinking bottle and the Top Unit/TopPlate/TopPlate TTL Interface, see page 104. Electronic beam. Gamma radiation. Ethylene oxide gas. Hydrogen peroxide (HP), liquid (up to 3% concentration). Only use HP to clean the cage's acrylate/PMMA components. important Do not use HP with any metal or electronic components, including the Top Unit/TopPlate/TopPlate TTL Interface! Metals can be severely damaged by HP. If you use (vaporized) hydrogen peroxide, we recommend to clean the surfaces afterwards using water and mild soap, or a perspex/ acrylic cleaner. Always dry all the surfaces. Vaporized hydrogen peroxide (VHP, up to 30% concentration). This technique requires specific apparatuses and procedures. See https://www.sciencedirect.com/topics/immunology-and- microbiology/vaporized-hydrogen-peroxide important Make sure that the VHP procedure includes the dehumidification process, Dehumidification reduces relative humidity (ideally to less than 30%). If dehumidification is not done, condensation of the gas occurs, resulting in a large number of droplets on the surface of the objects. This means that a much higher concentration of hydrogen peroxide than in the gas phase will be in contact with the objects. This is likely to damage plastic on the long term. When in doubt, always check with the manufacturer of the VHP cleaning equipment about the compatibility of VHP with Acrylate (PMMA) and electronic components. The risk of damage increases with the number of times that an object is subject to VHP cycles during its lifetime. Only use VHP to bring material to the safe environment, not to clean the cages on a daily basis. We recommend to clean the surfaces afterwards using water and mild soap, or a perspex/acrylic cleaner. Always dry all the surfaces. Peracetic acid (also known as Peroxyacetic acid, or PAA; up to 2% concentration). This is a good alternative to autoclaving. A trade name for Peracetic acid is Nu-Cidex. UV radiation. High intensity visible light. Alkaline substances (albeit in low concentrations). Perspex/acrylic cleaner. Disinfection wipes that are compatible with acrylate. A good one is wipes with Meliseptol® by Carl Roth: https://www.carlroth.com/nl/en/surface-disinfectants/ disinfection-wipes-meliseptol-wipes-sensitive/p/xp57.1 Low-temperature hydrogen peroxide gas plasma. Diluted solutions of isopropyl alcohol can be used to wipe down acrylic without adverse reaction. important Take care on the cleaning conditions below: Cleaning should take place in a well ventilated room. Take the cage apart and clean each component (bottom, walls, etc.) separately. Make sure that there are no parts together. Use spray or damp cloth to apply the isopropanol. After wipe down the surfaces, make sure all isopropanol is evaporated; droplets should not remain on the surfaces. Substances That Can Damage Phenotyper Clean The Drinking Bottle The bottle itself is made out of polycarbonate and can be autoclaved at 125 °C (257°F). The stopper is made of neoprene and can be cleaned at temperatures up to 90 °C (194°F). important Make sure that the following chemicals do not come in contact with PhenoTyper (cage and Top Unit/TopPlate/ TopPlate TTL Interface). Noldus takes no responsibility for any damage resulting from improper use of cleaning substances. Always test a substance when in doubt. Acetaldehyde Acetone Allyl alcohol Aniline Acetic acid Benzene Benzyl alcohol Butyl acetate Butyl alcohol Carbon disulfide Carbon tetrachloride Chloroform Chlorine gas Chlorobenzene Dichloroethane Dioxane Ethanol Ethoxyethane Ethyl acetate Ethylene oxide (wet) Hydrocarbons Hydrogen Fluoride Hydrogen peroxide liquid (>3%) Methanol Methyl acetate Methylated spirit Methylene chloride Methylethylketone Nitric acid Steam Any strong acid Clean The Top Unit/topplate/topplate Ttl Interface To clean these devices, please use a damp cloth. Please do not use chemicals or soap to wash the cage. Make sure that no liquid penetrates the equipment inside the device or its connectors. Pay particular attention when cleaning the TopPlate of PhenoTyper 2. Always remove liquid after cleaning, whatever method you use. Do not use Vaporized Hydrogen Peroxide (VHP) or any of the substances listed on page 103 to clean devices or boxes that contain electronics. Recommended Materials For your animals in the PhenoTyper, you may want to use bedding and nesting material. Several suppliers offer different materials. We know that the products described below work well for tracking with EthoVision XT. Bedding material When tracking black or brown animals, wood chips work well, like for example 5x5x1 mm Wood chips from ABEDD® - LAB & VET Service GmbH (www.abedd.com). Use this material together with a white PhenoTyper floor. When tracking white animals, you need a black background. In this case, use a black PhenoTyper floor. We know that tracking white animals goes well when using Paperchip pellets (www.lbs- biotech.com) as bedding material. This material appears black under infrared light. note When you try out different types of bedding materials, be aware that many materials that we see as black appear as white under infra- red light. When you track hooded animals, it depends on the proportion of black and white whether you can best track with a white or a black background. Nesting material When tracking black or brown animals, a simple white tissue is often used as nesting material and placed inside the shelter. When tracking white animals, nesting material that appears as black under infra-red light should be most suitable. However, we are not aware that such material exists. Most black tissue-like materials unfortunately appear as white under infra-red light. Therefore, also for these animals a white tissue is often used. However, when you do so, check that the animals do not drag the tissue out of their shelter. If the tissue is present on the PhenoTyper floor, EthoVision XT might detect this tissue as the animal. Pellets for the Pellet dispenser For the Pellet dispenser you can use 20 mg or 45 mg pellets. For more information, see The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 18 - Service Manual. Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - A Technical Support URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-a-technical-support Chapter: EthoVision XT A - Technical Support A Technical Support Help Desk If you run into problems, please contact us at my.noldus.com. Please check this manual carefully and the EthoVision XT Help before contacting the Help desk. To send experiment data, use the Backup procedure (see the EthoVision XT Help). Replacement Of Components If any component breaks or wears out, please contact Noldus to have it sent back to us. Please note that in any case you must send it to our international headquarters (Wageningen, The Netherlands) no matter where you are. Broken components will be fixed or replaced with new ones. See the next page for a list of the parts available. To have components replaced, enter a support ticket at my.noldus.com. important Plastic components (such as the cage walls) will only be replaced or repaired free of charge if they are broken due to a defect of workmanship and the damage is reported within one month of shipment. Other components are covered by a one year guarantee; to claim under guarantee you must report the damage within one year of shipment. It is possible that you may have a service contract entitling you to free replacement of parts for a longer period, please contact the support department if you are not sure. In any case we can still fix or replace the parts, but it may be necessary to levy a charge. The guarantee is only valid if you treat the PhenoTyper as described in this manual. In any case, shipping broken parts is at your expenses, while sending repaired or replacing parts back to you will be at our expenses. important If you connect PhenoTyper to any third-party products, such as video tracking system other than EthoVision XT, Noldus is not responsible for maintenance of that product, or for damage done to the PhenoTyper by that product. To order spare parts, contact your Noldus representative. A - Technical Support Parts List Top Units, Control Unit, Power supplies and accessories Item Code Description Notes PhenoTyper 1 PT-T10.5/P Top Unit V1.5 PAL/CCIR camera version Includes camera, circuitry, lights, buzzer PT-T10.5/N Top Unit V1.5 NTSC/EIA camera version Includes camera, circuitry, lights, buzzer PT-CU-10 Control Unit Includes cable to connect to PhenoTyper PT-PS1 Power supply 120V AC-240V AC / 24V DC PTTO-SD01 Remote On Screen Device (OSD) Available on request. PT-PSC Power supply feed-through cable 1.8 m PT-BNC30 Coaxial cable with BNC connectors, 75, 3 m PT-BNC100 Coaxial cable with BNC connectors, 75, 10 m PhenoTyper 2 PT2TP-0020 TopPlate PT2I-01_TTL TopPlate TTL Interface MAPS-0014 Power supply 120V AC-240V AC / 24V DC PT-PSC Power supply feed-through cable 1.8 m PT2MC-BGM- 1300 Camera module set Includes camera acA1300-60gm, lens, IR filter, insert module, bracket, mounting material Network cable with RJ-45 connectors Available in different lengths TTL Interface Toolkit Includes yellow adjust tool, 1x hex key 2.5mm, 2x mounting screws M3 x 40mm A - Technical Support The following cables are no longer available as a standard part (only on request): PT-LPT PC TTL cable 1.8 m. PT-LPT18 TTL extension cable 1.8 (Extension of PT-LPT). PT-LPT100 TTL extension cable 10 m (Extension of PT-LPT). PT-TTL18 TTL feed-through cable 1.8 m. Cage model 3000 (for mice) Below the standard cage components are listed. For custom solutions, please contact Noldus. Item Code Description Notes PTC3-W000 Wall plain, model 3000 Material: polymethylmethacrilate PTC3-W001 Wall with air-gap, model 3000 Material: polymethylmethacrilate PTC3-S001 Airgap shielding, model 3000 Material: polymethylmethacrilate PTC3-W002 Wall prepared for feeder and bottle, model 3000 Material: polymethylmethacrilate PTC3-W005 Wall prepared for shelter, model 3000 Material: polymethylmethacrilate PTC3-S010 Cover plate, model 3000 Material: polymethylmethacrilate PTC3-BT01 Cage bottom, model 3000 Material: polymethylmethacrilate, dual satin opaque. Side 31.5 cm Includes L piece (5x3x1.5 cm) to keep cage walls firm A - Technical Support PT-C-S-MNT1 Set of assembling material and tools for the cage, model 3000 Includes: 1x hexagon key 3 mm 1x hexagon key 2.5 mm 4x silicone tube, 1 cm 8x hexagon socket screw, cap head, stainless steel, M5 x 12 2x bolts M4x12 6x black nylon spacer 5 mm 6x white nylon screw CS M4 x 16 6x white nylon nut/washer A - Technical Support Cage model 4500 (for rats) Below the standard cage components are listed. For custom solutions, please contact Noldus. Item Code Description Notes PTC4-W000 Wall plain, model 4500 Material: polymethylmethacrilate PTC4-W001 Wall with airgap, model 4500 Material: polymethylmethacrilate PTC4-S000 Airgap shielding, model 4500 Material: polymethylmethacrilate PTC4-S001 Airgap shielding for mice, model 4500 Material: polymethylmethacrilate PTC4-W002 Wall prepared for feeder and bottle, model 4500 Material: polymethylmethacrilate PTC4-W005 Wall prepared for shelter, model 4500 Material: polymethylmethacrilate PTC4-F001 Cover plate with air holes, model 4500 Material: polymethylmethacrilate PTC4-F002 Cover plate with air holes for mice, model 4500 Material: polymethylmethacrilate PTC4-BB01 (black) PTC4-BW01 (white) Cage bottom Material: polymethylmethacrilate, matted A - Technical Support PT-C-L-MNT1 Set of assembling material and tools for the cage, model 4500 Includes: 1x hexagon key 3 mm 1x hexagon key 2.5 mm 8x silicone tube, 1 cm 8x hexagon socket screw, cap head, stainless steel, M5 x 12 4x hexagon socket bolts M4x12 10x black nylon spacer 5 mm 10x white nylon screw CS M4 x 16 10x white nylon nut/washer A - Technical Support Bottles, feeder and shelters PT-C-L-MNT1 Set of assembling material and tools for the cage, model 4500 (continued from previous page) 4x stainless steel screw, M3x12 4x hexagonal nuts Item Code Description Notes PT-B-00 Standard drinking bottle Model 3000 can have 1 bottle. Model 4500 can have one or two PTBM-0001 Drinking bottle mount Comes with silicone tubes (see assembling tools, page 108 and 110) PT-F-00 Feeder, model 3000 Made of stainless steel PT-F-01 Feeder, model 4500 Made of stainless steel PT-SH-BL-0 Shelter, small black Size 100 x 100 x 50 mm, holes 32 mm PT-SH-WH-0 Shelter, small white Size 100 x 100 x 50 mm, holes 32 mm PT-SH-BL-1 Shelter, large black Size 150 x 150 x 120 mm, holes 75 mm PT-SH-WH-1 Shelter, large white Size 150 x 150 x 120 mm, holes 75 mm Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - B Technical Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-b-technical-specifications Chapter: EthoVision XT B - Technical Specifications B Technical Specifications Phenotyper 1 Power supply 24V DC - 15 W Video output CCIR black/white 1 Vpp - 75 W Resolution 720x576 (PAL) or 640x480 (NTSC) Infrared lighting 3 integrated IR arrays through diffuser. Wavelength 940 nm Audio stimulus (TTL on/off controllable) Frequency ±2300 Hz Amplitude ±80 dB Yellow light stimulus (TTL on/off controllable) Wavelength 590 nm White light gradient (TTL on/off controllable) Color temperature 5500°K Intensity 0 - approx. 1000 lux Connections Supply 24V DC in Supply 24V DC out (feed-through) TTL control in/out Sub-D 9 TTL control in/out Sub-D9 (feed-through) Video out (BNC) Control unit Sub-D15 Remote On Screen Device (OSD) For Top Units with serial number 001051 to 1412. For 1471 and higher, OSD on request only. Cage components Clear or matte Acrylic (PMMA). Operating temperature 0 to +40 °C (+32 to +104 °F) Storage temperature - 20 to +70 °C (-4 to +158 °F) Operating humidity Up to 80%, no condensation Dimensions L x W x H, Top Unit excluded Model 3000: 300 x 300 x 435 mm / 11.8 x 11.8 x 17.1 in, Floor area 841 cm2 (130.4 in2) Model 4500: 450 x 450 x 660 mm / 17.7 x 17.7 x 26.0 in, Floor area 1936 cm2 (300.1 in2) Model 9000: 900 x 900 x 1000 mm / 35.4 x 35.4 x 39.4 in, Floor area 7744 cm2 (1200.3 in2) B - Technical Specifications Top unit versions Top Unit interface PT-T10.0 Introduced 09-2004; started from serial nr. Features: CMOS type camera PT-T10.1 Introduced 09-2005; started from serial nr. Features: CMOS camera replaced by a CCD- type PT-T10.2 Introduced 03-2011; started from serial nr. 801 Features: Camera mount with alignment method PT-T10.3 Introduced 03-2012; started from serial nr. 1001 Features: new LED type for white stimulus/ cue light PT-T10.4 Introduced 10-2013; from serial nr. 1053 to 1412. Feature: On Screen Display for camera settings added PT-T10.5 Introduced 4-2018; started from serial nr. 1471 OSD control on request only Noldus type number PTTI-001x Power supply 12V DC supplied by the USB IO-box Current consumption 40 mA Connectors 1x RJ45 8-pin modular to USB IO-box 4x RJ45 8-pin modular to PhenoTyper Top Units Dimensions 115 x 65 x 32 mm / 4.5 x 2.6 x 1.3 in (L x W x H) Weight 100 g Cable to USB IO-box 1x 1m modular RJ45 (green) Cable to PhenoTyper Top Unit 4x 2m modular RJ45 (green) with SubD-9 adapter B - Technical Specifications Phenotyper 2 Mains adapter Input 100-240 V AC Output 24 V DC 3 A maximum Power requirements 24 V DC 0.4 A Standard camera Basler acA1300-60gm Interface: Gigabit Ethernet (RJ45 connector, CAT5e or higher) Sensor: 1/1.8" Progressive Scan CMOS, monochrome Max. resolution: 1280 x 1024 Max. frame rate: 60 fps Lens Evetar F1.8 4mm includes IR pass filter Infrared lighting Wavelength 940 nm Intensity adjustable manually, 0.1 to 0.35 mW/cm2 (*); light permanent on White light Color temperature 4000°K Intensity adjustable manually, 0,5 to 2700 lux (*). Default 500 lux Connections 24 V DC input/output feed-through 4x RJ-45 TTL control port (**) Cage components Clear Acrylic (PMMA) Operating temperature 0 to +40 °C (+32 to +104 °F) Operating humidity 20 to 80 %, relative, non-condensing Storage temperature - 20 to +70 °C (-4 to +158 °F) Dimensions cage L x W x H TopPlate excluded Model 3000: 300 x 300 x 435 mm / 11.8 x 11.8 x 17.1 in, Floor area 841 cm2 (130.4 in2) Model 4500: 450 x 450 x 660 mm / 17.7 x 17.7 x 26.0 in, Floor area 1936 cm2 (300.1 in2) Model 9000: 900 x 900 x 1000 mm / 35.4 x 35.4 x 39.4 in, Floor area 7744 cm2 (1200.3 in2) Dimensions TopPlate 338 x 305 x 22 mm / 13.3 x 12.0 x 0.9 in Dimensions TTL Interface 305 x 88 x 34 mm / 12.0 x 3.5 x 1.3 in Weight TopPlate 2.1 kg (4.6 lbs) (camera module included) Weight TTL Interface 0.4 kg (o,9 lbs) () Measured at the bottom of a PT3000 cage. (*) Ports 3 and 4 for future use Top elements PT2TP-0020 PhenoTyper 2 TopPlate Introduced 01-2024; started from serial nr. PT2I-01_TTL PhenoTyper 2 TopPlate TTL Interface Introduced 01-2024; started from serial nr. PT2MC-BGM-1300 Digital camera module with Basler acA1300- 60gm Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper - C Declaration of Conformity URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-c-declaration-of-conformity Chapter: EthoVision XT C Declaration Of Conformity Phenotyper 1 PhenoTyper 1 We Noldus Information Technology b.v. Nieuwe Kanaal 5 NL-6700 AG Wageningen The Netherlands Declare that our product: "PhenoTyper" to which this declaration relates is in compliance with the requirements of the EMC Directive (89/336/EEC) because of the following reasons: It complies with the requirements of NEN-EN50082-1 (Generic immunity standard - Commercial and light industry). It complies with the requirements of NEN-EN50081-1 (Generic emission standard - Commercial and light industry). The CE marking is affixed on the product according to article 10 of the EC Directive 89/336/EEC. Wageningen, 15 October 2004 EC declaration of conformity Manufacturer: Noldus Information Technology Nieuwe Kanaal 5 6709PA Wageningen The Netherlands Declares that the following line of products: PhenoTyper PT-T10 series Fulfills all relevant provisions of the EC EMC directive 89/336/EEC. According the harmonized standards: NEN-EN 50081-1 January 1994 Electromagnetic Compatibility - Generic Emission Standard Part 1: Residential, Commercial and Light Industry NEN-EN 50082-1 September 1993 Electromagnetic compatibility - Generic immunity standard - Part 1: Residential, commercial and light industry Fulfills all relevant provisions of the EC RoHS directive 2011/65/EU. According the harmonized standards: EN IEC 63000 : 2018 Technical documentation for the assessment of electrical and electronic products with respect to the restriction of hazardous substances Fulfills all relevant provisions of the EC WEEE Directive 2012/19/EU. Waste Electrical and Electronic Systems (WEEE) The signatory on behalf of the manufacturer: Date: September 30 2020 Name : Jeroen Kemerink Vice President Research & Development Phenotyper 2 PhenoTyper 2 digital camera - EU Declaration of Conformity PhenoTyper 2 digital camera - FCC Supplier's Declaration of Conformity Acetic acid - 103 Acetone - 103 Acoustical stimuli - 14 Acrylic - 99 Action - 11 Actions based on PhenoTyper - 11 Airgap shield - 22, 108 Alkaline substances - 102 Analyzing data - 11 Assembling PhenoTyper - 21 Autoclave - 99 Automatic gain control - 56 Backup - 44 Bedding material - 104 Behavior Recognition - 41 Benzene - 103 Benzyl alcohol - 103 Bottle - 28, 103, 112 Bottom of cage - 22 Buzzer - 10 Cable connections PhenoTyper 1 - 36 Camera - 9 PhenoTyper 1 - 55 PhenoTyper 2 - 78 Charts exporting - 122 Cleaning the cage - 99 CognitionWall - 95 Condition - 11 Conditioning test - 88 Connect PhenoTyper 1 - 37, 39 PhenoTyper 2 - 65, 67 Control Unit - 107 PhenoTyper 1 - 49, 50 PhenoTyper 2 - 66 Cover plate - 34 Declaration of Conformity - 117 Documentation - 7 Drinking bottle - 28, 103, 112 Ethanol - 103 EthoVision XT general information - 6 Ethylene oxide - 101, 103 Experiments (multiple) - 46 Extension cables - 108 Index Feeder - 18, 31 Focus (lens) PhenoTyper 1 - 55 PhenoTyper 2 - 78 Food receiving task - 89 Frame grabber - 11 Gamma radiation - 101 Handling of subjects - 15 Help - 106 Hexagon key - 109, 111 Home cage - 8, 18 Hydrogen peroxide - 101, 103 Illuminated shelter task - 92 Import trials - 47 Infrared light - 9, 48 copying settings - 52 PhenoTyper 1 - 48, 50 PhenoTyper 2 - 76, 77 Infrared lighting - 113, 115 Isopropyl alcohol - 102 Jumper settings - 43 LED arrays - 9 Lens focus PhenoTyper 1 - 55 PhenoTyper 2 - 78 Light conditions - 6 Light intensity PhenoTyper 1 - 50, 51 PhenoTyper 2 - 77 Light meter - 52, 78 Light stimuli - 14 Light-dark cycle - 10 L-shape element - 27 Manuals - 7 Maximum trial duration - 85 MediaRecorder - 42 Methanol - 103 Mixed video images - 40 Model - 18 Multiple experiments - 46 Neoprene - 103 Nesting material - 105 Pellet dispenser - 19, 47, 105 Pellet receptacle - 19 cleaning - 99 Pellets - 105 Peracetic acid - 102 Index Perspex/acrylic cleaner - 102 PhenoTyper assembling - 21 benefits - 14 communication with EthoVision - configurations - 18 experiment - 99 general information - 6 maintenance - 99 setups - 11 PhenoTyper 1 assign devices to arenas - 61 cable connections - 35, 36 set up experiment - 57 PhenoTyper 2 assign devices to arenas - 83 cable connections - 63 set up experiment - 81 PhenoWheel - 19 Picolo Alert encoder board - 37, 39, PMMA - 99 Polycarbonate - 103 Polymethylmethacrylate - 99 Power cord - 36, 64 Power supply - 107 Protecting sheet - 22 Quad unit - 40 Resolution PhenoTyper 1 - 39, 41 PhenoTyper 2 - 67 Restore backup - 44 Rodent - 6 SDI Control port - 43 SDI control port - 38, 43 SDI devices - 47 Separate video images - 42 Shelter - 18, 30, 112 Shutter speed - 56 Sound intensity - 52 Sound stimuli - 10 Specifications - 113 Stimuli - 10 Technical support - 106 Testing PhenoTyper 1 - 48 PhenoTyper 2 - 76 Tools - 109 Top Unit - 8, 107 cleaning - 104 Top Unit Interface - 38, 43 Trial Control - 11, 62, 84 Trial Control Settings - 85, 88, 90, 93, 96 TTL devices - 47 TTL In - 38, 43 Tube lamps - 48 USB-IO box - 38, 43, 47, 66, 69 with PhenoTyper 1 - 38, 42, 57, with PhenoTyper 2 - 65, 69, 82, USB-IO box jumpers - 43 UV radiation - 102 Index Vaporized hydrogen peroxide - 101 Ventilation holes - 18 VHP - 101 Video cable PhenoTyper 1 - 36 PhenoTyper 2 - 64 Video camera - 9 Video images (mixing) - 40 Video processor - 40 Video resolution PhenoTyper 1 - 41 PhenoTyper 2 - 41, 67 Video tracking - 11 Visual stimuli - 14 Walls - 18, 108 protecting sheets - 22 Water bottle - 112 Wavelength - 113, 115 White light (PhenoTyper 2) - 66, 78 White light spot (PhenoTyper 1) - 10, 50, 51 Yellow light spot - 10, 50, 51 Source: PhenoTyper - EthoVision XT 18 - Reference Manual --- ## PhenoTyper XT 18 Service - End-User License Agreement (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-xt-18-service-end-user-license-agreement-continued-2PK Chapter: EthoVision XT End-User License Agreement (Continued) 6. Support and Updates 6.6. Noldus and Authorized Partners, are not responsible for maintaining or supporting use of the Software or obligated to provide any updates, fixes or support to the Software unless otherwise expressly agreed in writing between End-User and Noldus or the Authorized Partners. 7. Use Limitations; Liability; Indemnification 7.1. End-User acknowledges that the Software is intended for research or training purposes only and agrees not to use the Software for diagnosis or treatment of disease in human subjects. End-User agrees not to use the Software in any application where the failure, malfunction or inaccuracy of the Software carries the risk of death or bodily injury. 7.2. Noldus Software shall not be used for collection of biometric data from human subjects without prior informed consent from the person whose data is being captured. 7.3. Noldus does not allow the use of its Software for the following applications: - Active defense, i.e. embedding Noldus Software in a weapon system. - Biometric data collection in a judicial context with the aim to use such data as evidence in court. Noldus software cannot and shall not be used as a lie detector. - Surveillance of people in public spaces for security purposes. - Any other use that may potentially violate fundamental human rights. 7.4. If Noldus notices that its Software is used for applications that it does not approve of, this may lead to discontinuation of customer support and termination of the EULA. 7.5. To the fullest extent permitted by law, and notwithstanding any other provision of this EULA to the contrary: In no event will Noldus or the Authorized Partners be liable to the End-User for Indirect Losses or for special, incidental, consequential, exemplary, enhanced, or punitive damages, including without limitation, any damages resulting from interruption of business, loss of use, loss of profits or revenue, or loss of business, arising out of or in connection with this EULA, the Software, or the performance of Noldus, the Authorized Partners or the third parties engaged by Noldus in the performance of this EULA, regardless of whether Noldus, the Authorized Partners, or third parties engaged by Noldus, End-User, or any other person or entity has been advised of (or could have reasonably foreseen) the possibility of such damages or Indirect Losses. If, despite the provisions in this EULA, liability exists anyway, only direct damage will be eligible for reimbursement. 7.6. Noldus' and Authorized Partner's liability shall also be excluded, and Noldus and the Authorized Partners shall not have any liability under this EULA in the event of: - End-User's use of the Software other than in accordance with Section 7.1; - Direct and indirect consequences of the End-User's failing to adhere strictly to the user documentation provided or made available by Noldus or the Authorized Partner; - Any loss of or damage to files howsoever caused. 7.7. A liability claim will be unenforceable and lapse unless Noldus or the Authorized Partner receives a written notice thereof no later than 6 months after the discovery of an event or circumstance that gives or may give rise to that claim. 7.8. Noldus will hold harmless, defend, and indemnify End-User from and against all losses, damages, claims, liabilities, and expenses incurred by End-User that arise out of, relate to, or are caused by any third party claim that End-User's use of the Software, pursuant to the terms of this EULA, infringes the intellectual property rights of such third party. If such a claim is made or appears likely to be made, Noldus, at its option, will have the right to either: - Procure for the End-User the right to continue to use the Software; - Modify or replace the Software so that it is no longer infringing (in a manner that substantially retains its functionality and quality); or - Require End-User to terminate the use of and return the Software and refund a pro rata portion, if any, of the amount paid by End-User to Noldus for the infringing Software. Notwithstanding the foregoing, Noldus will have no liability to End-User if the infringement results from use of the Software in combination with software not provided by Noldus or from modifications made by Noldus to conform to specifications provided by End-User. The indemnification obligations in this section are subject to: - End-User giving Noldus prompt written notice of any claim (provided that End-User's failure to provide prompt written notice will only relieve Noldus of its obligations under this Section to the extent such failure materially limits or prejudices Noldus' ability to defend or settle such claim); - The transfer of sole control of the defense and any related settlement negotiations to Noldus; and - End-User's cooperation, at Noldus' expense, in the defense of such claim. THIS SECTION STATES END-USER'S SOLE AND EXCLUSIVE REMEDIES FOR THIRD PARTY PROPERTY INFRINGEMENT CLAIMS. 7.9. End-User shall indemnify, and hold harmless Noldus, the Authorized Partners or the third parties engaged by Noldus from and against any and all losses (including Indirect Losses and special, incidental, consequential, exemplary, enhanced, or punitive damages) arising out of or caused by: - Any failure in the performance of the obligations of the End-User under the law, this EULA or Noldus' General Terms and Conditions; and - Any and all third party claims on any grounds whatsoever, directly or indirectly related to the End-User's use of the Software, the contents thereof or any results or materials generated by the Software. 7.10. THE LIMITATION OF LIABILITY PROVISIONS SET FORTH IN THIS SECTION 7 SHALL APPLY EVEN IF END-USER'S REMEDIES UNDER THIS EULA FAIL OF THEIR ESSENTIAL PURPOSE. 7.11. Noldus and End-User acknowledge and agree that the parties entered into this EULA in reliance upon the limitations of liability set forth in this Section 7, that the same reflect an allocation of risk between the parties (including the risk that a contract remedy may fail of its essential purpose and cause consequential loss), and that the same form an essential basis of the bargain between the parties. 8. Miscellaneous 8.1. Parties may communicate with each other by electronic mail. Parties recognize the risks associated with electronic mail and declare that they accept such risks. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - End-User License Agreement (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/phenotyper-xt-18-service-end-user-license-agreement-continued Chapter: EthoVision XT General Provisions That they shall not hold each other liable for any damage incurred by either of them as a result of the use of electronic mail. If a Party is in doubt as to the content of an electronic message received, the content of the message originating with the sender shall be decisive. 8.2. The invalidity or unenforceability of any provision this EULA shall not affect or limit the validity or enforceability of any other provisions thereof. Any such invalid or unenforceable provision shall be deemed to be substituted by a provision that is considered to be valid and enforceable. The interpretation of the substituting provision shall be as close as possible to the economic, legal and commercial objectives of the severed provision. 8.3. Failure by Noldus or the Authorized Partner to enforce any of its rights under the EULA shall not constitute a waiver of such rights thereunder and shall not relieve End-User of its obligation to comply with such provisions. No waiver or amendment of any provisions therein shall be effective unless signed in writing by a Noldus representative. Any such written waiver shall only be applicable to the specific instance to which it relates and shall not be deemed to be a continuing or future waiver. 8.4. Amendments or changes to this EULA can only be agreed upon in writing between the Parties. 8.5. The EULA shall be binding upon the Parties thereto, their legal representatives, successors and assigns. End-User shall not assign any right or obligation arising out of this EULA without the prior written consent of Noldus. Any attempt by End-User to assign or delegate any obligation hereunder shall be deemed null and void. Governing Law: End-Users USA or Canada 9.1. If End-User is a legal entity and its principal place of business is located in the United States of America or Canada, or if End-User is an individual whose primary residence is located in the United States of America or Canada: - This EULA is exclusively governed by the law of the Commonwealth of Virginia and the applicable federal laws of the United States of America, without regard to the conflicts of law provisions of any jurisdiction. Without limiting the previous sentence, End-User and Noldus expressly agree: (i) that the Virginia Uniform Computer Information Transactions Act, Virginia Code §§ 59.1-501.1 et seq. ("UCITA"), and the United Nations Convention on Contracts for the International Sale of Goods ("CISG") are expressly excluded from this EULA, (ii) that any all terms contained in UCITA or CISG will have no force or effect on any portion of this EULA, and (iii) that UCITA and CISG do not apply to this EULA or the Software. - Any and all claims and disputes arising out or in connection with this EULA, the Software, or the performance or non-performance by either party of any of its obligations under this EULA, which End-User and Noldus cannot resolve amicably within a reasonable period of time will be commenced and maintained only in a state or federal court of competent subject matter jurisdiction situated or located in the United States of America. Noldus and End-User consent to the exclusive jurisdiction of and venue in any such court. - To the extent permitted by law: End-User must commence or file any claim or action arising out of or relating to this EULA or the Software within six months after the cause of action accrues, otherwise such claim or cause of action is permanently barred. To the extent permitted by law, End-User expressly waives the right to commence or file any such claim or action under any longer statute of limitations. Governing Law: End-Users Other Countries 10.1. If End-User is a legal entity and its principal place of business is located in any country other than the United States of America or Canada, or if End-User is an individual whose primary residence is located in any country other than the United States of America or Canada: - This EULA is exclusively governed by the law of The Netherlands. The United Nations Convention for Contracts on the International Sale of Goods is expressly excluded. - Any disputes arising out or in connection with this EULA that cannot be solved amicably within a reasonable period of time will be submitted to the competent court in Arnhem, The Netherlands, for any dispute with End-Users having their principal place of business in the European Union. In the event that an End-User has its principal place of business outside the European Union, the United States of America or Canada, any dispute shall be finally settled in accordance with the Arbitration Rules of the Netherlands Arbitration Institute. Location shall be Arnhem, the Netherlands. The arbitration procedure shall be conducted by one (1) arbiter in the English language. Revised: July 21, 2022 Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## uLog 3 - Data in The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ulog-3-data-in-the-observer-xt Chapter: EthoVision XT Coding Scheme Only uLog events that have been logged are added to the coding scheme when a log file is imported in The Observer XT. Three different event types are added as mutually exclusive behavior groups: - Mouse Events – With the mouse clicks, double-clicks, mouse wheel turns and mouse drags as point events. - Keyboard Events – With the characters and keys typed as point events. This group also contains the behavior String, which combines the key presses separated by pressing a special key, like the space bar, enter key, or backspace key, to words. - Other Events – With events like starting and stopping applications, activation of windows and browsing behavior. The Coding Scheme also contains a number of modifier groups: - ControlType – Linked to the behaviors Mouse click, Mouse doubleclick and Mousewheel turn. This modifier specifies, for example, where a mouse click took place. The individual modifiers are: - listitem - edit - tabitem - combobox - pane - window - button - slider - group - list - headeritem - dataitem - document - KeyboardCharacter – That contains the logged characters. - KeyboardSpecialKey – That contains the special keys: - Backspace - Arrow - Return - Space - Alt key with Numpad keys - KeyboardKeyCombination – That contains the key combinations like Ctrl + S, or Ctrl + A. - MouseButton – Which button is used, left, right, or middle. - ApplicationName – Which application is opened, or closed. - MouseX – The X coordinate in pixels of the mouse event starting from the left side of your screen. - MouseY – The Y coordinate in pixels of the mouse event starting from the upper side of your screen. The name of applications and web pages in which events took place and typed text are imported as comments in the Event Log. Events in Event Log The figure below shows an example of how the events are shown in the Event Log. The test participant used the Windows + D key combination to switch to their desktop, started Google Chrome and typed my.noldus.com to access their MyNoldus account. Technical Support Noldus Help Desk If you have any problems, questions, remarks or comments, please let us know. We offer 24 hour support via help desks in different time zones. From the Help menu choose Noldus Online and subsequently Contact Help Desk. This brings you to the MyNoldus portal on the Noldus website. Create a new account or log into your existing MyNoldus account. Under Get Support you will find the contact details of the help desk in your region, you can view the status of your current support cases or submit a new support case. Before you contact the help desk, please have the following information available so our support staff can help you as quickly as possible. - The version number of your copy of uLog (choose Help > About uLog). - The name of the registered user of The Observer XT (choose Help > About The Observer XT > License Info). Error Messages All error messages are displayed in a Critical Message box. The error is displayed and, if possible, a solution. Whenever such an error occurs, a log file is created called uLog.log. The Technical Support Department may request this file when answering your support question. You can locate the file in: C:\Users\Public\Public Documents\uLog\Log Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## uLog 3 - End-User License Agreement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ulog-3-end-user-license-agreement Chapter: EthoVision XT End-User License Agreement Important – Read Carefully. Please read this End-User License Agreement ("EULA") carefully before checking the "Accept" checkbox, downloading or using the Software (as defined below). By checking the "Accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions in this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "Accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions Terms used in this EULA but not otherwise defined shall have the meaning assigned to them below: - 1.1. Authorized Partner: the individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. - 1.2. End-User: the individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3. EULA: this End-User License Agreement. - 1.4. Indirect Losses: any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5. Network License: a licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. - 1.6. Noldus: Noldus Information Technology bv, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries listed in the document http://www.noldus.com/legal/noldus_corporate.pdf. - 1.7. Security System: a system of software protection to limit installation and use of the Software to the authorized End-Users and computers. - 1.8. Security Device: a device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. - 1.9. Software: the software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) provided to the End-User by Noldus or an Authorized Partner together with this EULA, that is not covered by third party terms and conditions and is included in the list under "Noldus software" in the Annex to the General Terms and Conditions (http://www.noldus.com/legal/noldus_gtc.pdf). 2. License 2.1. Upon payment by the End-User of the license fee for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates or supplements of the Software. If upgrades, updates or supplements of the Software are obtained, however, the use of such upgrades or updates is governed by this EULA and the amendments that may accompany them and may be subject to additional payments and conditions. 2.2. The End-User may download, install and use the Software on as many computers as is reasonably necessary, however the Software may not be shared or used concurrently on more computers than for which EULAs are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. 2.3. End-User is allowed to store or install a copy of the Software for back-up or archival purposes. 2.4. End-User shall not (i) modify, alter, adapt, merge, decompile or reverse-engineer the Software or any part thereof nor create any derivative works based on all or any part of the Software, or (ii) remove or obscure any copyright, trademark or other ownership notices from the Software, or (iii) sub-license, sell, rent, lease, hire, loan, assign or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. 2.5. The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices and Network Licensing. End-User is prohibited to (attempt to) remove, alter or circumvent in any way any part of such Security System. 2.6. End-User is responsible for regular, frequent and effective backups of all files produced or modified while working with the Software. 3. Intellectual Property 3.1. All title, copyright and other industrial, intellectual or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. 3.2. The Software may include or make use of third party software, including open source software. Such third party software may be subject to the third party's terms and conditions provided in the documentation accompanying the Software and may contain copyright or other industrial, intellectual or proprietary rights of such third party. End-User hereby agrees to the terms and conditions for such third party software. In the absence of any third party terms and conditions, this EULA will govern the third party software in the Software. 3.3. End-User may, from time to time, provide Noldus with comments, suggestions, data, information or feedback ("Feedback") on the Software. End-User acknowledges and agrees that such Feedback may be freely used by Noldus, at its sole discretion, for the design, development, improvement, marketing and commercialization of its products and services, without any restrictions based on confidentiality or intellectual property rights. 4. Transfer 4.1. End-User is entitled to make a one-time, permanent transfer of this EULA and Software only directly to one other End-User. This transfer must include all of the Software (including all component parts, the media and printed materials, any upgrades and this EULA). Such transfer may not be by way of consignment or any other indirect transfer and shall be subject to the following provisions: - End-User will provide to Noldus prior to any such transfer the full details of the proposed transfer. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## uLog 3 - End-User License Agreement (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ulog-3-end-user-license-agreement-continued Chapter: EthoVision XT 4. Transfer (Continued) - name and address details of the new End-User and the expected date of transfer in writing; - The new End-User understands and agrees to all the terms and conditions of this EULA in the same way as if the new End-User had obtained the Software from Noldus or an Authorized Partner; - End-User will destroy all (partial) copies of the Software and all accompanying materials, including but not limited to installed copies and any backup copies on data storage devices and guarantee to Noldus in writing that this has been done. If the Software is an upgrade, any transfer must include all prior versions of the Software; - Noldus reserves the right to levy an administrative charge upon the End-User and/or the new End-User in relation to transfer of the Software to an End-User. 4.2. Any attempted transfer without prior written permission from Noldus shall constitute a material breach of this Agreement and shall be deemed null and void. 5. Term; Termination 5.1. The EULA shall enter into force on the date of acceptance by the End-User and shall continue until terminated in accordance with this Section 5. 5.2. If the Software is licensed on a subscription basis, the EULA shall continue until the end of the current subscription period. 5.3. Noldus is entitled to terminate the EULA immediately upon prior written notice upon: - the breach of any material provision of this Agreement by the End-User if (i) such breach is not curable or (ii) if curable, the End-User has not cured such breach within 30 (thirty) day period following receipt of a written notice by Noldus substantiating such breach ("ingebrekestelling"); - the filing or institution of bankruptcy, liquidation or receivership proceedings of the End-User or in the event a receiver or custodian is appointed for the End-User's business, or if its business is discontinued or if it has a petition presented by a creditor for its winding up or if the End-User enters into any liquidation (other than for purpose of reconstruction or amalgamation). 5.3. Upon termination of the EULA, the End-User shall immediately discontinue the use of the Software and remove the software of all computers, destroy all (partial) copies of the Software from all storage media and return the documentation and materials relating to the Software to Noldus or its Authorized Partner. 5.4. Termination of this Agreement does not remove or reduce End-User's obligation to pay any outstanding license fees or other monies, all of which shall be due for payment immediately on termination of the EULA. 5.5. The following provisions shall survive termination of this EULA: Section 3, 7, 9, 10 and this Section 5.6. In addition, any other provisions which are required to interpret and enforce the Parties' rights and obligations under the EULA shall also survive any termination or expiration of this EULA, but only to the extent required for the full observation and performance of the EULA. 6. Warranty 6.1. Noldus warrants that the Software as of the date of delivery to the End-User by Noldus or its Authorized Partner, the Software will, for a period of 90 days ("Warranty Period") materially conform to the specifications set out in the user documentation accompanying the Software ("Specifications"), provided that: - the Software is properly installed on a supported computer platform (as defined in documents that can be accessed on https://my.noldus.com) and used in accordance with the provisions of the accompanying user documentation and/or any Noldus-approved training course; - Noldus is notified in writing within 14 days after any non-conformity of the Software was known or should reasonably have been known to End-User and the End-User has made available all the information that might reasonably be required to allow Noldus to investigate, recreate and where possible remedy a non-conformity; - the Software has not been (a) altered, repaired or modified by any party other than Noldus or a third party provider approved by Noldus; or (b) used with software or a computer platform other than set out in the documents that can be accessed on https://my.noldus.com or have been subjected to negligence, or computer or electrical malfunction; or (c) were used, adjusted, or installed other than in accordance with instructions by Noldus. 6.2. Other than set out in Section 6.1, no warranties are expressed or implied with respect to Software or any element thereof, including without limitation its quality, performance, accuracy, merchantability or suitability or fitness for any purpose, whether or not that purpose has been communicated by End-User to Noldus. The Software is a general product developed by Noldus for a wide range of solutions, requirements and situations and End-User is responsible for purchasing the Software required for his needs. Noldus explicitly does not warrant that the Software shall be entirely without error or fault, nor that it will operate without interruption. End-User agrees that such errors, faults or interruptions shall not be deemed material and cause to terminate this EULA. 6.3. The warranty by Noldus set out in Section 6.1 applies only to the first installation of the Software and will not apply, resume or renew upon delivery or installation of any subsequent update or upgrade to the Software, alteration in the number of EULAs granted for use of the Software, or any other extensions, upgrades or alterations to the Software where the Software has previously been delivered to or installed by the End-User. 6.4. The warranty by Noldus set out in Section 6.1 shall further not apply to Software that is licensed or otherwise made available at no cost, or Software that is designated as 'prototype', 'alpha' or 'beta' code, all of which are provided 'as is' and without warranty, representation or liability. 6.5. Upon receipt of an End-User's written notice of the Software not conforming to the Specifications during the Warranty Period, Noldus shall at its option and in its sole discretion (i) assist the Customer in correcting or replacing the non-conforming Software or, (ii) terminate the EULA immediately and refund the purchase price paid by the End-User. The remedies described above shall be End-User's sole and exclusive remedies. Upon expiration of the Warranty Period, Noldus shall have no obligation to provide such remedies. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## uLog 3 - Introduction and Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ulog-3-introduction-and-setup Chapter: EthoVision XT Introduction What Is uLog? uLog is a tool for automatic recording of user-computer interaction. With uLog you can log basic computer events such as mouse clicks, scrolling, activating windows and typing words. It creates .odx log files that can be imported into The Observer XT, synchronized with manually scored events and other data, and analyzed in this program. Logging computer events can be started and stopped manually, but you can also control uLog with commands from The Observer XT. This allows easy synchronization of logged events with manually scored events in The Observer XT. The following computer events are logged with uLog: - Key presses. - Strings, which are a sequence of related characters, like words. - Special keys like Ctrl and Alt. - Combinations of keys with special keys like Ctrl + S. - Mouse clicks and double-clicks. - Mouse drags. - Position of mouse clicks, double-clicks and drags. - Mouse wheel turns. - Starting and closing applications. - Windows activated. - Message boxes activated. Information About The Observer XT uLog 3.5 is supported with The Observer XT 12.5 or higher. We assume that you are familiar with the procedures of The Observer XT. The Observer XT Help can be accessed with the shortcut on the desktop of the computer with The Observer XT. You can also download a PDF of The Observer XT Help from the Noldus website: browse to my.noldus.com, create an account or log into your existing MyNoldus account and click on Downloads. Please note that uLog logs all keyboard and mouse activity, so also typed passwords. Please make sure your test participants are aware of this before you start the test. Please note that special keys that require double key presses like ', or ~ may not be logged properly with some keyboard layouts. Change the keyboard layout if you notice this. To do so click the Keyboard layout icon in the task bar (bottom right corner of your screen) and select a new keyboard layout. Installation Requirements uLog 3.5 was tested with The Observer XT 17 on computers with the 64-bit Professional editions of Windows 11 and Windows 10. It was tested with the US English language pack. It is possible that certain local language versions of Windows may affect how well the program runs. Installation To install uLog: - Download uLog_3.5.zip from the Noldus website: browse to my.noldus.com, create an account or log into your existing MyNoldus account and then click Downloads. You can find the file under The Observer XT → Versions. - Copy the file to the test participant PC. - Right-click the zip file, select Extract All, select the location where you want to save the uLog file and click Extract. This creates a folder named uLog containing the program file uLog.exe. Note this location, because you need it later. It also creates a folder named uLog in the folder C:\Users\Public\Public Documents\Noldus. This is the default location where the log files are stored. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## uLog 3 - Logging URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ulog-3-logging Chapter: EthoVision XT Logging You can start and stop uLog manually on the test PC. Alternatively, you can start and stop uLog with commands from The Observer XT. If uLog runs on another computer than The Observer XT, you need the program PsExec to send commands from the computer with The Observer XT to the computer with uLog. Start and Stop uLog Manually - Double-click the file uLog.exe in the folder uLog that was created during installation. - Optionally, change the folder where uLog saves its log files in the File location field. - Optionally, select the check box Minimize to system tray when logging starts. This removes the uLog window from the screen of the test computer when the test starts. - Click Start. - When the test ends, click the arrow in the bottom right corner of the screen to open the system tray. - Double-click the uLog icon. - Click Stop. Import the Log Files into The Observer XT - Copy the .odx file from the folder you set in the File location field to the computer with The Observer XT. - On the computer with The Observer XT, open the project and then the observation into which you want to import the log file. If you do not have an observation yet, choose File > Import > Observational Data and continue with step 4. The log file is imported as a new observation. - Click the Import data button on the tool bar and select Import Observational data. - Locate the .odx file and click Import. - In the window that appears, select Yes import new coding scheme elements. The log file is now imported as a new event log in the observation. Synchronization If you did not start logging at exactly the same time as you started the observation, you need to synchronize the log file with the observation. Do so in the following way: - Click the Offset button on the Component tool bar, then choose Numerical Offset. The File Synchronization window appears. This window lists the event log currently open, the video files, and the imported uLog data. - Locate the data set (event, video, uLog data) of which you want to change the synchronization point relative to others, and click the Offset cell. - Enter the offset value. Example: If you started logging two seconds before the Event Log started, enter an offset of -2 for the uLog Event Log. - Click Apply. For more information on synchronizing, see Synchronize data sets in Carry out an Observation in The Observer XT Help. Start and Stop uLog with The Observer XT You can send commands from The Observer XT to start uLog when you create a new observation and to start and stop logging automatically when you start and stop an observation. To do so, select uLog.exe as an external program and specify which command you want to use. This program is present in the folder uLog that was created during installation. The following commands are available: - No parameter or /E — Starts uLog. - /R — Starts logging. /S — Stops logging. - /X — Closes uLog. Settings in The Observer XT - In The Observer XT, choose Setup > Project Setup. - Under Observation Source, select Live Observation. The Devices window opens. If not, click the Devices button. - Click the Add External Program button. In the Add External Program window that opens, under Name, type a name for the commands (for viewing purposes only). For example, Control uLog. - Select the check box next to New Observation. - In the same row, click the ellipsis button and browse to the file uLog.exe. - In the same row, leave the space under Command line options empty, or type the command /E in this field. This results in The Observer XT starting uLog when creating a new observation. - Select the check box next to Start observation. - In the same row, click the ellipsis button and browse to the file uLog.exe. - In the same row, under Command line options, type the command /R. This way recording starts when you start an observation in The Observer XT. - Select the check box next to Stop observation. - In the same row, click the ellipsis button and browse to the file uLog.exe. - In the same row, under Command line options, type the command /S. This way recording stops when you stop an observation in The Observer XT. - Click OK. A new row Control uLog appears in the Devices window. You can now start observing in The Observer XT. uLog opens when you create a new observation, and logging starts and stops when you start and stop an observation. - Import the log file in the observation. See Import the Log Files into The Observer XT for the procedure. If you set the delay correctly in the ms. before fields of the Add External Program window, the uLog events are synchronized with the manually scored events of The Observer XT. Delay To assess the delay between the start of the observation and the moment uLog starts logging, define a behavior with a key code. Press this key during the observation in The Observer XT while simultaneously logging with uLog. When you press this key, this event is recorded in The Observer XT and also in the log file. Import the log file into The Observer XT and calculate the offset from the difference between time stamps in milliseconds for this event. Enter this value in the ms. before fields in the Add External Program window. If you make a video recording of the observation with MediaRecorder as well, make a recording where the camera points at your keyboard. When you press a key for an event, the event is recorded in The Observer XT event log, the video, and in the log file. You can then visualize video and event data to estimate the time difference between the event recorded, the key logged, and the corresponding video footage when the key was pressed. Synchronize the video with the logged events as described in the Synchronization section. Start and Stop uLog with The Observer XT on Another Computer If uLog runs on a different computer than The Observer XT, use the program PsExec to send commands from the computer running The Observer XT to the computer running uLog. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## uLog 3 - Logging (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ethovision-xt/page/ulog-3-logging-continued Chapter: EthoVision XT PsExec Overview PsExec is a light-weight program that allows you to execute processes on a remote computer. The program allows you to access the command-prompt of the remote computer. With PsExec you can start uLog on one computer with The Observer XT on another computer. PsExec is part of the PsTools suite from Microsoft Corporation. For a complete overview go to http://technet.microsoft.com/en-us/sysinternals/bb897553.aspx. Installation To install PsExec, go to http://technet.microsoft.com/en-us/sysinternals/bb897553.aspx and click Download PsTools. Locate the downloaded zip folder with Windows Explorer and open it. Double-click PsExec and choose Extract all. Browse to the location where you want to store the executable and click Extract. The program is copied to the specified location on your computer. Registry Entry To ensure you connect to the remote computer as a full administrator, you must add a key to the registry of both computers. To do so: Windows 10 + Windows 11 — Type registry editor in the Windows search field, right-click on Registry Editor and run it as administrator. - Open the registry editor and browse to HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System. - Right-click in the right field and select New and then DWORD (32-bit) Value. - Name the registry entry LocalAccountTokenFilterPolicy. - Right-click the entry and select Modify. In the Edit DWORD (32-bit) Value window that appears, enter 1 in the field under Value data. - Click OK and close all windows. More information about this registry entry can be found at http://support.microsoft.com/kb/951016. Firewall Some anti-virus scanners report that one or more of the tools are infected with a "remote admin" virus. None of the PsTools contain viruses, but they have been used by viruses, which is why they trigger virus notifications. You may need to create an exception for PsExec in the firewall or virus scanner of both computers. The procedure to create an exception in Windows Firewall is described below. If you have another firewall, consult its manual for the correct procedure. - Open the Control Panel and click Windows Defender Firewall. - Click Allow a program or feature through Windows Defender Firewall. - Click Change Settings at the top of the page. On the computer with PsExec: - Click Allow another app, browse to PsExec.exe and click Add. - Select all check boxes next to Execute processes remotely. Then click OK and close the Control Panel. On the computer with The Observer XT: - Select all check boxes next to Remote Service Management. Then close the Control Panel. If PsExec still does not work properly, you may disable the firewall or anti-virus scanner completely on the remote computer during the time PsExec is used. The procedure to disable Windows Defender Firewall is described below. If you have another firewall or virus scanning application, consult its manual for information on how to disable it. - Open the Control Panel and open Windows Defender Firewall. - Click Turn Windows Defender Firewall on or off. - Select Turn off Windows Defender Firewall (not recommended) for all networks. User Account Control Settings If PsExec does not work, although you followed the procedure above and disabled the firewall, adjust the User Account Control Settings. To do so: - Open the Control Panel and click User Accounts. - Click Change User Account Control settings. - Move the slider completely towards Never notify. - Click OK and close the Control Panel. Now restart the computer. Remember to turn the Firewall on again after you have finished working with PsExec. User Account If PsExec still does not work, although you followed all the steps above, let your system administrator create a new user account with administrator rights on the computer with uLog. Log on with this new user account. Settings in The Observer XT - Open The Observer XT. - In The Observer XT, choose Setup > Project Setup. - Under Observation source, select Live Observation. The Devices window opens. If not, click the Devices button. - Click the Add external program button. In the Add External Program window that opens: - In the field next to Name, type a name for the commands (for viewing purposes only), for example, Control uLog. - Select the check box next to New Observation. In the same row, browse to PsExec.exe and type the following command in the field under Command line options: -u user name remote PC -p password remote PC \\remote PC name -i 1 -d "location uLog.exe" - Select the check box next to Start Observation. In the same row, browse to PsExec.exe and type the following command in the field under Command line options: -u user name remote PC -p password remote PC \\remote PC name -i 1 -d "location uLog.exe" /R Enter the delay to start uLog in the field next to ms, before. - Select the check box next to Stop Observation. In the same row, browse to PsExec.exe and type the following command in the field under Command line options: -u user name remote PC -p password remote PC \\remote PC name -i 1 -d "location uLog.exe" /S Enter the delay to stop uLog in the field next to ms, before. - Click OK. A new row Control uLog appears in the Devices window. You can now start observing in The Observer XT. uLog opens when you create a new observation, and logging starts and stops when you start and stop an observation. - Import the log file into the observation. If you set the delay correctly in the ms. before fields of the Add External Program window, the uLog events are synchronized with the manually scored events of The Observer XT. Note: "location uLog.exe" is the path to the program file uLog.exe. This path depends on the folder in which you installed uLog and can be, for example, C:\Program Files (x86)\ulog\ulog.exe. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EyeReader - Applications and Use Cases URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/eyereader-applications-and-use-cases Chapter: FaceReader Eye Tracking Performance and Correlation Gaze results can help track what captures the participant's attention. Correlation within different categories in two tasks between fixation duration of Tobii Nano eye tracker and EyeReader output was observed. The chosen category recorded approximately 2.0 seconds on not chosen categories, versus 11.1 seconds and 2.6 seconds for the eye tracker. The slightly lower estimates in EyeReader are likely due to a slightly higher percentage of failed eye localizations. In addition, the total fixation duration for each category indicated strong correlation between the two systems (Mean r = 0.91). Research Applications and Suitability The results show that eye tracking via the webcam can be a useful and easily applicable research tool. Under good conditions, varying individual and screen characteristics do not cause large differences in performance. Generally speaking, there is often a trade-off between ecological validity and measurement precision. If high precision is required, a lab setting is more appropriate where participants can also put their head in a headrest and have long calibration sessions. EyeReader is very suitable for researching realistic behaviors where you expect clear discernible effects. You can use EyeReader in a flexible and mobile lab environment or within the FaceReader Online platform for online testing. If you are already a FaceReader Online user, make sure you are using FaceReader 9. When you open a project, click on the tab Details and make sure version 9 is selected as analysis engine for the participants' recordings. You can then turn gaze tracking on in your experiment design. Getting Started with EyeReader Visit www.facereader-online.com for more information and sample studies. To start using FaceReader Online or for more information on how to integrate EyeReader in a lab environment or other tool, please contact Noldus. Contact Information International Headquarters - Company: Noldus Information Technology bv - Location: Wageningen, The Netherlands - Phone: +31-317-473300 - Fax: +31-317-424496 - Email: info@noldus.nl North American Headquarters - Company: Noldus Information Technology Inc. - Location: Leesburg, VA, USA - Phone: +1-703-771-0440 - Toll-free: 1-800-355-9541 - Fax: +1-703-771-0441 - Email: info@noldus.com Global Representation Noldus is also represented by a worldwide network of distributors and regional offices. Visit the Noldus website for contact information. Legal Notices Due to our policy of continuous product improvement, information in this document is subject to change without notice. The Observer is a registered trademark of Noldus Information Technology bv. FaceReader is a trademark of Vicarious Perception Technologies BV. © 2022 Noldus Information Technology bv. All rights reserved. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## EyeReader - Webcam Eye Tracking Technology URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/eyereader-webcam-eye-tracking-technology Chapter: FaceReader Tracking Technology You can use EyeReader in a flexible and mobile lab environment or within the FaceReader Online platform for online testing. How It Works The EyeReader algorithm estimates the gaze direction and relates that to an image on the screen. The first step is face analysis to locate key-points in the face (such as eyes, nose, etc.) and estimate the head pose. The eye image and head pose information are then used by a pre-trained neural network (a convolutional neural network or CNN) to produce a 3D gaze vector (a line segment in three directions, x,y,z) representing the direction of the person's eye gaze. The neural network is trained with many labelled datasets of screen locations and video recordings to learn the relation between the image of the eyes and the gaze vector. To go from a 3D model of the gaze to a location on a screen one needs to know exactly where the screen is. With the help of a calibration task in which the participant follows dots on a screen, the 3D vector can be mathematically decoded to 2D gaze x,y points on the screen. EyeReader We have tested on our own validation dataset, which includes data from 17 participants (12 males/5 females, 9 aged 18-29/8 aged 30-59) with EyeReader and a Tobii Nano eye tracker with natural lighting conditions. Participants performed a calibration task and a few psychological tasks. They were situated with a distance of approximately 75 cm in front of a 1920x1080 23-inch screen and also performed a calibration task on a 15-inch laptop (without eye tracker). The results on the 32-dot calibration task (different dots used for calibration and testing) on a desktop computer show that the system predicts gaze points on screen with an average deviation of 2.4 ±0.6 cm (or an average of 113.6 pixels, and average of 5.2% deviation of the screen). Also, the results demonstrate that a large amount of sections of the screen can be discerned with high accuracy (it can estimate a gaze location in 1/16th of the screen with 96% accuracy), albeit not in the range of hardware eye tracking systems (having over 99% accuracy for 1/16th of the screen). If one wants to study a difference in fixation between two points on the screen, it is ideal if they are in different 1/16th sections of the screen. The results are comparable with competitor systems on the market, although it should be noted that direct comparison is not possible due to different screen sizes (making noting errors in pixels problematic) and different testing settings. Laptop Versus Desktop Another outcome of this test was that the system is more accurate on the laptop (Mean Absolute Error: 2.3 ±0.5 cm) in comparison with the desktop (MAE: 2.5 ±0.7 cm). This is likely due to the smaller screen and the fixed ideal alignment of the in-built webcam of the laptop. The results are similar for brown (MAE: 2.5 cm) in comparison to blue eyes (MAE: 2.4 cm), and for those not wearing glasses (MAE: 2.4 cm) in comparison to those that are wearing glasses (MAE: 2.7 cm). However, this is based on only 3 people who are wearing glasses (with thin lenses); when there is reflection of the surrounding light this will likely cause issues. Validation of This Application An important but simple finding within eye tracking research is that people look longer at what they find interesting. Participants performed two simple choice tasks, where they viewed a few images of items (e.g. cookies, chocolate, etc.) and were allowed to choose one afterwards. A comparison of the EyeReader gaze estimations with the eye tracker estimations shows a high correlation between the X and Y coordinate estimation (X: Mean r = 0.87, Y: Mean r = 0.77). Gaze estimations can be classified into being a saccade (fast movements with less visual information processing) or fixation (slower eye focus relevant for information processing) based on the speed of the gaze movements. For each category that was presented, total duration of fixation time was calculated. Both systems resulted in the same interpretation of the results: 79% of participants looked longest at the category that they preferred (choice as a reward for participation), with EyeReader giving an average of 9.3 seconds on the preferred category. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader - Facial Muscle Movements Encoding Pain URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-facial-muscle-movements-encoding-pain Chapter: FaceReader Facial Muscle Movements Encoding Pain: A Systematic Review Abstract Facial expressions of pain are not undefined grimaces, but they convey specific information about the internal state of the individual in pain. With this systematic review, we aim to answer the question of which facial movements are displayed most consistently during pain. We searched for studies that used the Facial Action Coding System to analyze facial activity during pain in adults, and that report on distinct facial responses (action units [AUs]). Twenty-seven studies using experimental pain and 10 clinical pain studies were included. We synthesized the data by taking into consideration: - The criteria used to define whether an AU is pain-related - Types of pain - The cognitive status of the individuals When AUs were selected as being pain-related based on a "pain > baseline" increase, a consistent subset of pain-related AUs emerged across studies: lowering the brows (AU4), cheek raise/lid tightening (AUs6_7), nose wrinkling/raising the upper lip (AUs9_10), and opening of the mouth (AUs25_26_27). This subset was found independently of the cognitive status of the individuals and was stable across clinical and experimental pain with only one variation, namely that eye closure (AU43) occurred more frequently during clinical pain. This subset of pain-related facial responses seems to encode the essential information about pain available in the face. However, given that these pain-related AUs are most often not displayed all at once, but are differently combined, health care professionals should use a more individualized approach, determining which pain-related facial responses an individual combines and aggregates to express pain, instead of erroneously searching for a uniform expression of pain. Introduction The facial expression of pain has attracted considerable interest in experimental and clinical research based on an increasing awareness that it supports the communication of pain as a second signal system besides the verbal one, and thus can be used as another indicator of pain when self-report is missing (e.g., in patients with dementia). Right from the start of research on facial expressions of pain, researchers tried to characterize how facial activity during the experience of pain looks like. The vision was to define a prototypical facial expression of pain, similarly to prototypical facial expressions having been suggested for different emotional states. Groundbreaking research was conducted by Prkachin, who analyzed in a sample of 41 healthy students which facial responses are displayed consistently across different types of experimental pain stimulation (pressure, temperature, electrical current, and ischemia). Facial responses were analyzed using the Facial Action Coding System (FACS), the gold standard for facial expression research. The FACS is a fine-grained, objective, and anatomically based coding system that differentiates between 44 facial movements (action units [AUs]). Coders are trained to apply specific operational criteria to determine the onset and offset as well as the intensity of the AUs. Using the FACS, Prkachin suggested that there are four facial movements that are more steadily displayed across experimental pain modalities than other AUs: - Lowering the brows (AU4) - Cheek raise/lid tightening (AUs6_7) - Nose wrinkling/raising the upper lip (AUs9_10) - Eye closure longer than 0.5 seconds (AU43) Prkachin and Salomon further suggested that this set of facial movements is not only indicative for experimental pain but also for clinical pain. When studying facial responses in a group of 129 shoulder pain patients undergoing a range of painful movement exercises, the authors found that the same set of facial movements was displayed as had been previously found for experimental pain. Mainly based on these two studies, this subset is regarded as presenting the key components of the facial expression of pain. Meanwhile, a substantial number of further studies have been conducted, investigating facial expressions of pain in various groups of individuals (e.g., young, old, patients with depression, individuals with intellectual disabilities) and during various types of pain conditions (low back pain, chest pain, and experimental pain). At least parts of the above-described set of facial responses have also been found to be associated with pain in these further studies. Nevertheless, there is also considerable variability between studies, with other facial movements also having been found to be pain-related. For example, "raising the chin" (AU17) or even "oblique lip raising" (AU12, smiling) have been recurrently found to occur while individuals are experiencing pain. Indeed, some studies include up to 17 AUs as a set of pain-associated AUs. One reason for the variability between studies is the difference in how studies defined whether an AU is pain-related. Overall, there are two main approaches: - Frequency of Occurrence Criterion: An AU is defined as pain-related when it occurs during pain above a critical frequency level, which is often set to 5%. - Pain > Baseline Criterion: An AU is defined as pain-related when it occurs statistically more frequently during pain compared with a non-painful baseline condition, or more frequently in pain patients compared with pain-free controls. Often, approach two is not conducted on all possible 44 AUs of the FACS system. Instead, authors use approach two consecutively after having used approach one to preselect AUs that fulfil the frequency of occurrence criterion, and then in a second step, the pain > baseline criterion is used to define which of these preselected AUs are really pain-related. The aim of this systematic review is to examine the question of which facial movements are indeed pain-related by making use of the substantial number of primary studies that have analyzed facial responses during pain. We take into consideration: - The different criteria used to define whether an AU is pain-related - Different types of pain (clinical vs experimental pain) - The cognitive status of the individuals being examined Given that FACS is the most often used and best operationalized method to analyze facial expressions of pain, we limited our review to those studies using FACS, although other methods can also be used to assess facial communication of pain (e.g., non-FACS-based automatic systems and observational pain scales). Methods The systematic review was performed following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Search Strategy and Study Selection Literature Search An extensive search of literature published until April 2018 was conducted using the databases PubMed and PsycINFO. No restrictions were set with regard to the earliest year of publication. The search combined keywords for pain (pain, nociception) with keywords for facial expression (facial expression, facial display, facial activity, facial expressiveness, facial response, FACS) using logical AND and OR operators. Given that we were interested in facial activity during pain in human adults, the following keywords were excluded using a NOT qualifier: - Child - Neonat* - Animal In addition, reference lists from identified articles as well as reviews and book chapters on facial expression of pain were screened for missing articles. The systematic search was limited to articles published in English or German. Eligibility Criteria Studies were selected based on the following inclusion criteria: - Facial responses were analyzed using the FACS - Results were provided on single AUs - A minimum sample size of N = 20 was included - A clear description of statistics was provided Non-original research, conference proceedings, and doctoral theses were excluded. Two independent reviewers screened the titles and abstracts for the eligibility criteria. Full texts of all potentially relevant studies were retrieved. In cases of discrepancies or disagreement between the two reviewers, a third reviewer was consulted and discrepancies were resolved. Information Extraction From each included study, the following information was extracted: - Sample: Patients or healthy participants, number of participants, age, sex, and cognitive status - Type of Pain: Experimental pain (pressure, thermal, electrical, or other procedures such as blood sampling or injections) and clinical pain - FACS Coding: Duration of sampling, how many and which AUs were coded, and AU information being coded (intensity, frequency, duration, and apex) - Approach Used to Determine Pain-Related AUs: Selection based on a frequency of occurrence criterion or a pain > baseline criterion Information was extracted by one reviewer and independently verified by a second reviewer. To control for bias caused by the inclusion of multiple reports of the same study, authors were contacted in cases where an overlap of the sample was suspected and duplicate samples were excluded. All ambiguities in data extraction (6% reviewer discrepancies) were double-checked and resolved. Assessing the Quality of Studies To assess the quality of the studies and the risk of bias, studies were graded according to pre-specified quality criteria. Source: FaceReader pain encoding, Noldus Information Technology --- ## FaceReader - Physical setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-physical-setup Chapter: FaceReader Physical setup Physical Setup The physical setup of your experiment is crucial for an accurate analysis with FaceReader. We give the following general guidelines: Place the camera in front of the test participant and slightly below eye level. Make sure your camera provides images with good contrast and brightness. Good lighting is crucial. Avoid direct light, reflections and shadows on the face. Make sure the lighting on the face comes directly from the front, for example by placing the setup in front of a window. If necessary, use lights on either side of the monitor, or a professional photo light to increase light intensity, or to compensate for unwanted light sources. Install FaceReader Install FaceReader To install FaceReader - Download the installation file (FaceReader [version number] Setup.exe) from the MyNoldus portal of the Noldus website (my.noldus.com). If you do not have a MyNoldus account yet, you can create one. - Double-click the file. - As Installation type, select Standard. - Follow the rest of the instructions on your screen to install FaceReader. To install the Stimulus Presentation Tool (Project Analysis Module only) If you have the Project Analysis Module, you need the Stimulus Presentation Tool to present stimuli automatically. To install it: 1. Download the installation file (Stimulus Presentation Tool 4 Setup.exe) from the Noldus website using your MyNoldus account (my.noldus.com). 2. Double-click the file to run it. 3. As Installation type, select Standard. 4. Follow the rest of the instructions on your screen to install the Stimulus Presentation Tool. Work with FaceReader Work With FaceReader Setup - Dependent on your license, do one of the following: - If you have a hardware key, insert it into the computer and open FaceReader. - If you have a software license key, start FaceReader and activate your license. You can choose between a Floating or a Fixed activation. Floating - Choose Floating if you want to be flexible on which computer you use FaceReader and your computer is connected to the internet. Fixed - A Fixed activation is linked to one computer. Your computer must have an internet connection to activate/deactivate a fixed license. After you have activated the license you can use FaceReader without internet. - Create a new Project (File > New > Project). Give the project a name and select a location to store it, or accept the default location. Work with FaceReader - Choose Participant > Add Participant. Enter a name or identification code for the participant. - The gender and age of your participants are added as independent variables and are automatically estimated by FaceReader. To select the age and gender manually, double-click the participant name. Click on the pencil button next to the independent variable to enter the values. - Add one or more analyses for each participant and choose to analyze from video, live from your camera or from images. To do so, select the participant for which you want to add an analysis in the Project Explorer. Click on the Video, Camera or Image button on the toolbar to add the appropriate analysis. It is not possible to mix image analyses with camera or video analyses. Work with FaceReader - To carry out a camera analysis, select the option Use as default camera if you always use this camera. To record audio, select your microphone. Optionally, select Record to create a video file of the test participant's face. The video will always be saved at a frame rate of 15 frames per second. To add multiple video analyses to a participant, right-click the participant's name, select Add Multiple Video Analyses, and select your videos. Work with FaceReader Analyze - Click on the magnifying glass button next to an analysis to open it. - Check the options for this analysis in the Settings window in the bottom-left corner of the analysis window. To create default settings for each new analysis, choose File > Settings. Open the tab Default Analysis Settings and make your selection. Work with FaceReader See the FaceReader Help for an explanation of the options. Press F1 in the program to open it. Choose File > Settings > Analysis Options and select Action units, Estimate heart rate and heart rate variability and/or Consumption behavior to activate the Action Unit module, the Remote PPG module and/or the Consumption Behavior module. important If you select the Baby Face model, Facial expressions are not available as analysis output. You will obtain Action Unit intensities. See Action Unit Module in the FaceReader Help for more information. Work with FaceReader - Click on the Start analysis button to carry out the analysis. tip To analyze all analyses at once, click on the Start batch analysis button on the toolbar. important We recommend to close all visualization windows before you start batch analysis. Bear in mind that carrying out batch analysis on a high number of long videos with a high resolution and frame rate may cause problems. 4. The Model quality bar should cross the dashed line. If this is not the case, improve lighting or reposition your camera. Output FaceReader displays a number of windows with graphical and tabular output. Work with FaceReader Important notes Not all visualization options may be available by default. If you do not see some of the options described in this Quick Start Guide, choose File > Settings > Analysis Options and select all options. If you selected the Baby Face model, not all output is available. See the FaceReader Help for more information. Procedure - Click on one of the buttons in the Analysis Visualization window to show, for example, the key points in the face or the Facial States. - To switch windows, click on the Select window button in the upper- right corner of one of the windows and make your selection. See Analysis windows on page 16 for a short description of the options. - To zoom, or to copy or save graphs, click on one of the icons on the window toolbar. Work with FaceReader - To show more windows, click on the Split/Unsplit button in the upper-right corner of one of the windows. tip If you notice the test participant shows a bias towards some facial expressions, use one of the calibration methods to correct for that. See Analyze Facial Expressions/ Calibrate FaceReader in the FaceReader Help for details. Analysis windows For the upper windows you can choose between: Analysis Visualization - Click on a button on the left to view how FaceReader analyzes the face. Subject Characteristics - With, for example, the estimated age and gender. Facial States - Whether, for example, mouth or eyes are open or closed. Expression Intensity - A chart that displays which of the facial expressions show up in the face. Expression Summary - A pie chart with the distribution of the facial expressions. Circumplex Model of Affect - A chart in which emotions are described in a two- dimensional circular space, containing arousal on the vertical axis and valence on the horizontal axis. Action Unit Intensity - Available with the Action Unit Module. Heart rate - Available with the Remote PPG Module. Consumption Behavior Statistics - Available with the Consumption Behavior Module. Custom Expression Table - Available with the Action Unit Module. For the lower windows you can choose between the line charts: Timeline - An overview of the facial expressions, and facial states on a timeline. Valence Line Chart - The valence indicates whether the emotional status of the test participant is positive or negative. Arousal Line Chart - Arousal indicates whether the test participant is active or not active. Expression Line Chart - A line chart with the facial expression intensities over time. Head Orientation Line Chart - The head orientation on a time line (Pitch, Yaw and Roll). Heart Rate and Variability Line Chart - Available with the Remote PPG Module. Work with FaceReader Custom Expression Line Chart - Available with the Action Unit Module. Heart Beat Chart - Available with the Remote PPG Module. Head Position Line Chart - Horizontal, Vertical and Depth position on a time line. Gaze Angles Line Chart - Horizontal and Vertical gaze angle on a time line. See FaceReader's Output in the FaceReader Help for a full description of the analysis windows. Export To export your data, choose File > Export. Choose to export the results of the analysis, participant, or entire project. You have the following options: State log - A text file or Excel file with the dominant facial expressions as states over time. Detailed log - A text file or Excel file with the intensities of all facial expressions over time. To save extra options, like facial states, global gaze direction, valence and arousal values to the log file, select these options in the Data Export tab of the Settings window (File > Settings). Optionally, adjust the sample rate of the export file and select whether to include headers. Heart beat log - A text file or Excel file with the inter-beat interval data (the time intervals between individual heart beats). The Observer XT log - Choose this option if you want to import the analysis results in the annotation software The Observer® XT for further analysis. The screenshot below comes from The Observer sample project 'Child FaceReader'. In this project a 3-year old boy is observed during play with an online game. His face is filmed with a webcam, while the screen is captured with the Noldus screen capture device. The video of the boy's face was analyzed in FaceReader. The Observer log was exported from FaceReader and imported into The Observer XT. The screenshot shows the facial expressions on the time line. Work with FaceReader tip It is also possible to send the analysis results directly during the FaceReader analysis to The Observer XT, using the Noldus network communication program N-Linx. See FaceReader with The Observer XT in the FaceReader Help for details. Source: FaceReader 9 Quick Start Guide --- ## FaceReader - Project Analysis Module URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-project-analysis-module Chapter: FaceReader Project Analysis Module Project Analysis Module Setup The general procedure to set up an experiment with FaceReader also applies to the Project Analysis Module. The Project Analysis Module contains the following extra options: 1. Independent Variables - The independent variables Age and Gender are present by default. Choose Project > Independent Variable > Add Independent Variable to add more independent variables, like whether the participants saw the commercial before, or their native language. Double-click Independent Variables under a participant name to score them. Age and Gender can be estimated by FaceReader, or entered manually. 2. Stimuli and Event Markers - Define stimuli or event markers (Project menu) to mark episodes of interest. Stimuli have a fixed duration and can be linked to a video or image to show to the test participants. Project Analysis Module Stimulus Presentation Tool Use the stimulus presentation tool to automatically show the stimuli to the test participants and synchronize them with the analyses. important In a two computer setup, synchronize the computer clock times with a time server. See Synchronize computers with a network time protocol in the FaceReader Help how to do so. On the computer with FaceReader - Choose File > Settings > Data Export and under External Communication (API and Stimulus Presentation Tool) select the checkbox Enable External Control. - To add tests, open the Tests tab in the bottom pane of the Project Explorer. Then click on the Add test button. - Select the camera and the stimuli to show to the test participants. Optionally, choose to let participants enter their own name, age and gender, randomize the presented stimuli, set the stimulus display size and the length of the pause between the stimuli. Project Analysis Module On the test participant computer - Start the Stimulus Presentation Tool and follow the instructions to connect with the FaceReader computer. - Select a test and click Start. - Fill in the participant details and click Start again, or let the participant do this. The test and analysis start. Project Analysis Module Analyze Participants are automatically added when you use the stimulus presentation tool. Also, analyses are automatically carried out. Watch the Model quality bar when the test runs. The bar should cross the dashed line. If this is not the case, improve lighting or reposition your camera. Optionally, score event markers during the analysis. Output Apart from the general FaceReader output options (page 14), the Project Analysis Module has the following output: Quick Layouts - This will open a number of charts to give you a first impression of the data. Pie chart, Box plot, Bar chart, Circumplex model or Line chart - Circumplex Model and Line Chart are only available if you scored stimuli in your project. Project Analysis Module Table - To calculate statistics on the analyzed facial expressions and other parameters of all participants, participant groups or single participants. Stimulus - To add your stimulus videos to the visualization. You can play back your stimulus videos together (synchronized) with a Line chart with the facial expressions and other parameters. Participant - To add your participant face video to the visualization. You can play back your participant videos together (synchronized) with the stimulus video and a Line chart with the facial expressions and other parameters. Project Analysis Module Compare - To compare two or more data sets in a chart or table and carry out a t-test to test for significant differences. You can select what data to include in the analysis: Select what parameters to visualize/tabulate. Select a stimulus or event marker to visualize/tabulate the data during this stimulus/ event marker. Select whether you want to visualize/tabulate absolute or relative values of your parameters. Project Analysis Module Select how to aggregate data over time. Select how to aggregate data over test participants. Select which test participants to include in your analysis. Project Analysis Module Source: FaceReader 9 Quick Start Guide --- ## FaceReader - Up and running quickly URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-up-and-running-quickly Chapter: FaceReader Up and running quickly Up And Running Quickly This Quick Start Guide guides you through the main steps to analyze facial expressions with FaceReader. Only the most basic features are addressed. Inevitably, some features that may be vital to your application are not discussed. You can find additional information in the FaceReader Help. General Information The first part of the Quick Start Guide contains general information on using FaceReader. Follow the instructions to set up your system, install FaceReader and to analyze the facial expressions. You can extend your FaceReader license with a number of modules. Project Analysis Module The Project Analysis Module allows you to create groups of participants based on independent variable values like age and gender, and to analyze average expression values per group. In addition to this, you can view the stimulus video together with the video of the test participant's face and the FaceReader analysis. The second part of this Quick Start Guide describes the Project Analysis Module. Up and running quickly Other Modules FaceReader also has the following other modules: Action Unit Analysis Module To analyze a set of 20 action units of the Facial Action Coding System (FACS). These are the action units that are most commonly used. Up and running quickly Remote PPG Module To estimate the heart rate and heart rate variability of the subject in front of the camera by means of remote photoplethysmography (RPPG). This is a method based on the fact that changes in blood volume due to pressure pulses cause small changes in the reflectance of the skin. Consumption Behavior Module To analyze consumption behaviors like Intake event and Chewing. Please note that the Consumption Behavior Module is experimental. If you have the Consumption Behavior Module and want to use this in the analysis, you have to enable this analysis (File - Settings - Analysis Options - Optional Classifications) More Information? See the FaceReader Help that opens when you press F1 in the program. It can also be accessed in the Windows apps screen, and can be downloaded from the MyNoldus portal. From the Help menu select Noldus Online and then Customer Support Center to access the MyNoldus portal. Up and running quickly Support If you encounter problems, see the Support section on the MyNoldus portal or a help desk in your area. From the Help menu select Noldus Online and then Contact Help Desk to access the MyNoldus portal. Note that if you send us videos showing people's faces, you should have permission from those people that you can use the video for that purpose and you may need to sign a form granting consent for us to use those videos. Source: FaceReader 9 Quick Start Guide --- ## FaceReader 10 - 2. License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-2-license Chapter: FaceReader End-User License Agreement 2. License Upon payment by the End-User of the license fees for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates or supplements of the Software. If upgrades, updates or supplements of the Software are obtained, however, the use of such upgrades or updates is governed by this EULA and the amendments that may accompany them and may be subject to additional payments and conditions. 2.2. The End-User may download, install and use the Software on as many computers as is reasonably necessary, however the Software may not be shared or used concurrently on more computers than for which EULA's are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. 2.3. End-User is allowed to store or install a copy of the Software for back-up or archival purposes. 2.4. End-User shall not (i) modify, alter, adapt, merge, decompile or reverse-engineer the Software or any part thereof nor create any derivative works based on all or any part of the Software, or (ii) remove or obscure any copyright, trademark or other ownership notices from the Software, or (iii) sub-license, sell, rent, lease, hire, loan, assign or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. 2.5. The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices and Network Licensing. End-User is prohibited to (attempt to) remove, alter or circumvent in any way any part of such Security System. 2.6. End-User is responsible for regular, frequent and effective backups of all files produced or modified while working with the Software. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - 4. Transfer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-4-transfer Chapter: FaceReader 3. Intellectual Property 3.1. All title, copyright and other industrial, intellectual or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. 3.2. The Software may include or make use of third party software, including open source software. Such third party software may be subject to the third party's terms and conditions provided in the documentation accompanying the Software and may contain copyright or other industrial, intellectual or proprietary rights of such third party software. End-User hereby agrees to the terms and conditions for such third party software. In the absence of any third party terms and conditions, this EULA will govern the third party software in the Software. 3.3. End-User may, from time to time, provide Noldus with comments, suggestions, data, information or feedback ("Feedback") on the Software. End-User acknowledges and agrees that such Feedback may be freely used by Noldus, at its sole discretion, for the design, development, improvement, marketing and commercialization of its products and services, without any restrictions based on confidentiality or intellectual property rights. 4. Transfer 4.1. End-User is entitled to make a one-time, permanent transfer of this EULA and Software only directly to one other End-User. This transfer must include all of the Software (including all component parts, the media and printed materials, any upgrades and this EULA). Such transfer may not be by way of consignment or any other indirect transfer and shall be subject to the following provisions: - End-User will provide to Noldus prior to any such transfer the full name and address details of the new End-User and the expected date of transfer in writing. - The new End-User understands and agrees to all the terms and conditions of this EULA in the same way as if the new End-User had obtained the Software from Noldus or an Authorized Partner. - End-User will destroy all (partial) copies of the Software and all accompanying materials, including but not limited to installed copies and any backup copies on data storage devices and guarantee to Noldus in writing that this has been done. If the Software is an upgrade, any transfer must include all prior versions of the Software. - Noldus reserves the right to levy an administrative charge upon the End-User and/or the new End-User in relation to transfer of the Software to an End-User. 4.2. Any attempted transfer without prior written permission from Noldus shall constitute a material breach of this Agreement and shall be deemed null and void. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - 5. Term; Termination URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-5-term-termination Chapter: FaceReader 5. Term; Termination 5.1. The EULA shall enter into force on the date of acceptance by the End-User and continue until terminated in accordance with this Section 5. 5.2. If the Software is licensed on a subscription basis, the EULA shall continue until the end of the current subscription period. 5.3. Noldus is entitled to terminate the EULA immediately upon prior written notice upon: - The breach of any material provision of this Agreement by the End-User if (i) such breach is not curable or (ii) if curable, the End-User has not cured such breach within 30 (thirty) day period following receipt of a written notice by Noldus substantiating such breach ("ingebrekestelling"). - The filing or institution of bankruptcy, liquidation or receivership proceedings of the End-User or in the event a receiver or custodian is appointed for the End-User's business, or if its business is discontinued or if it has a petition presented by a creditor for its winding up or if the End-User enters into any liquidation (other than for purpose of reconstruction or amalgamation). 5.4. Upon termination of the EULA, the End-User shall immediately discontinue the use of the Software and remove the software of all computers, destroy all (partial) copies of the Software from all storage media and return the documentation and materials relating to the Software to Noldus or its Authorized Partner. 5.5. Termination of this Agreement does not remove or reduce End-User's obligation to pay any outstanding license fees or other monies, all of which shall be due for payment immediately on termination of the EULA. 5.6. The following provisions shall survive termination of this EULA: Sections 3, 7, 9, 10 and this Section 5.6. In addition, any other provisions which are required to interpret and enforce the Parties' rights and obligations under the EULA shall also survive any termination or expiration of this EULA, but only to the extent required for the full observation and performance of the EULA. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - 6. Warranty URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-6-warranty Chapter: FaceReader 6. Warranty 6.1. Noldus warrants that the Software as of the date of delivery to the End-User by Noldus or its Authorized Partner, the Software will, for a period of 90 days ("Warranty Period") materially conform to the specifications set out in the user documentation accompanying the Software ("Specifications"), provided that: - The Software is properly installed on a supported computer platform (as defined in documents that can be accessed on https://my.noldus.com) and used in accordance with the provisions of the accompanying user documentation and/or any Noldus-approved training course. - Noldus is notified in writing within 14 days after any non-conformity of the Software was known or should reasonably have been known to End-User and the End-User has made available all the information that might reasonably be required to allow Noldus to investigate, recreate and where possible remedy a non-conformity. - The Software has not been (a) altered, repaired or modified by any party other than Noldus or a third party provider approved by Noldus; or (b) used with software or a computer platform other than set out in the documents that can be accessed on https://my.noldus.com or have been subjected to negligence, or computer or electrical malfunction; or (c) were used, adjusted, or installed other than in accordance with instructions by Noldus. 6.2. Other than set out in Section 6.1, no warranties are expressed or implied with respect to Software or any element thereof, including without limitation its quality, performance, accuracy, merchantability or suitability or fitness for any purpose, whether or not that purpose has been communicated by End-User to Noldus. The Software is a general product developed by Noldus for a wide range of solutions, requirements and situations and End-User is responsible for purchasing the Software required for his needs. Noldus explicitly does not warrant that the Software shall be entirely without error or fault nor that it will operate without interruption. End-User agrees that such errors, faults or interruptions shall not be deemed material and cause to terminate this EULA. 6.3. The warranty by Noldus set out in Section 6.1 applies only to the first installation of the Software and will not apply, resume or renew upon delivery or installation of any subsequent update or upgrade to the Software, alteration in the number of EULA's granted for use of the Software, or any other extensions, upgrades or alterations to the Software where the Software has previously been delivered to or installed by the End-User. 6.4. The warranty by Noldus set out in Section 6.1 shall further not apply to Software that is licensed or otherwise made available at no cost, or Software that is designated as 'prototype', 'alpha' or 'beta' code, all of which are provided 'as is' and without warranty, representation or liability. 6.5. Upon receipt of an End-User's written notice of the Software not conforming to the Specifications during the Warranty Period, Noldus shall at its option and in its sole discretion (i) assist the Customer in correcting or replacing the non-conforming Software or, (ii) terminate the EULA immediately and refund the purchase price paid by the End-User. The remedies described above shall be End-User's sole and exclusive remedies. Upon expiration of the Warranty Period, Noldus shall have no obligation to provide such remedies. 6.6. Noldus and Authorized Partners, are not responsible for maintaining or supporting use of the Software or obligated to provide any updates, fixes or support to the Software unless otherwise expressly agreed in writing between End-User and Noldus or the Authorized Partners. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - 7. Use Limitations; Liability; Indemnification URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-7-use-limitations-liability-indemnification Chapter: FaceReader 7. Use Limitations; Liability; Indemnification 7.1. End-User acknowledges that the Software is intended for research or training purposes only and agrees not to use the Software for diagnosis or treatment of disease in human subjects. End-User agrees not to use the Software in any application where the failure, malfunction or inaccuracy of the Software carries the risk of death or bodily injury. 7.2. Noldus Software shall not be used for collection of biometric data from human subjects without prior informed consent from the person whose data is being captured. 7.3. Noldus does not allow the use of its Software for the following applications: - Active defense, i.e. embedding Noldus Software in a weapon system. - Biometric data collection in a judicial context with the aim to use such data as evidence in court. Noldus Software cannot and shall not be used as a lie detector. - Surveillance of people in public spaces for security purposes. - Any other use that may potentially violate fundamental human rights. 7.4. If Noldus notices that its Software is used for applications that it does not approve, this may lead to discontinuation of customer support and termination of the EULA. 7.5. To the fullest extent permitted by law, and notwithstanding any other provision of this EULA to the contrary: In no event will Noldus or the Authorized Partners be liable to the End-User for Indirect Losses or for special, incidental, consequential, exemplary, enhanced, or punitive damages, including without limitation, any damages resulting from interruption of business, loss of use, loss of profits or revenue, or loss of business, arising out of or in connection with this EULA, the Software, or the performance of Noldus, the Authorized Partners, or third parties engaged by Noldus in the performance of this EULA, regardless of whether Noldus, the Authorized Partners, End-User, or any other person or entity has been advised of (or could have reasonably foreseen) the possibility of such damages or Indirect Losses. If, despite the provisions in this EULA, liability exists anyway, only direct damage will be eligible for reimbursement. 7.6. Noldus' and Authorized Partners' liability shall also be excluded, and Noldus and the Authorized Partners shall not have any liability under this EULA in the event of: - End-User's use of the Software other than in accordance with Section 7.1. - In the event of direct and indirect consequences of the End-User's failing to adhere strictly to the user documentation provided or made available by Noldus or the Authorized Partner. - Any loss of or damage to files or data howsoever caused. 7.7. A liability claim will be unenforceable and lapse unless Noldus or the Authorized Partner receives a written notice thereof no later than 6 months after the discovery of an event or circumstance that gives or may give rise to that claim. 7.8. Noldus will hold harmless, defend, and indemnify End-User from and against all losses, damages, claims, liabilities, and expenses incurred by End-User that arise out of, relate to, or are caused by any third party claim that End-User's use of the Software, pursuant to the terms of this EULA, infringes the intellectual property rights of such third party. If such a claim is made or appears likely to be made, Noldus, at its option, will have the right to either (i) procure for the End-User the right to continue to use the Software, (ii) modify or replace the Software so that it is no longer infringing (in a manner that substantially retains its functionality and quality), or (iii) require End-User to terminate the use of and return the Software and refund a pro rata portion, if any, of the amount paid by End-User to Noldus for the infringing Software. Notwithstanding the foregoing, Noldus will have no liability to End-User if the infringement results from use of the Software in combination with software not provided by Noldus or from modifications made by Noldus to conform to specifications provided by End-User. The indemnification obligations in this section are subject to: (i) End-User giving Noldus prompt written notice of any claim (provided that End-User's failure to provide prompt written notice will only relieve Noldus of its obligations under this Section to the extent such failure materially limits or prejudices Noldus' ability to defend or settle such claim); (ii) the transfer of sole control of the defense and any related settlement negotiations to Noldus; and (iii) End-User's cooperation, at Noldus' expense, in the defense of such claim. THIS SECTION STATES END-USER'S SOLE AND EXCLUSIVE REMEDIES FOR THIRD PARTY INTELLECTUAL PROPERTY INFRINGEMENT CLAIMS. 7.9. End-User shall indemnify and hold harmless Noldus, the Authorized Partners, and the third parties engaged by Noldus from and against any and all losses (including Indirect Losses and special, incidental, consequential, exemplary, enhanced, or punitive damages) arising out of or caused by (i) any failure in the performance of the obligations of the End-User under the law, this EULA, or Noldus' General Terms and Conditions, or (ii) any and all third party claims on any grounds whatsoever, directly or indirectly related to the End-User's use of the Software, the contents thereof, or any results or materials generated by the Software. 7.10. THE LIMITATION OF LIABILITY PROVISIONS SET FORTH IN THIS SECTION 7 SHALL APPLY EVEN IF END-USER'S REMEDIES UNDER THIS EULA FAIL OF THEIR ESSENTIAL PURPOSE. 7.11. Noldus and End-User acknowledge and agree that the parties entered into this EULA in reliance upon the limitations of liability set forth in this Section 7, that the same reflect an allocation of risk between the parties (including the risk that a contract remedy may fail of its essential purpose and cause consequential loss), and that the same form an essential basis of the bargain between the parties. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - 9. Governing Law: End-Users USA Or Canada URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-9-governing-law-end-users-usa-or-canada Chapter: FaceReader 8. Miscellaneous 8.1. Parties may communicate with each other by electronic mail. Parties recognize the risks associated with electronic mail and declare that they shall not hold each other liable for any damage incurred by either of them as a result of the use of electronic mail. If a Party is in doubt as to the content of an electronic message received, the content of the message originating with the sender shall be decisive. 8.2. The invalidity or unenforceability of any provision this EULA shall not affect or limit the validity or enforceability of any other provisions thereof. Any such invalid or unenforceable provision shall be deemed to be substituted by a provision that is considered to be valid and enforceable. The interpretation of the substituting provision shall be as close as possible to the economic, legal and commercial objectives of the severed provision. 8.3. Failure by Noldus or the Authorized Partner to enforce any of its rights under the EULA shall not constitute a waiver of such rights thereunder and shall not relieve End-User of its obligation to comply with such provisions. No waiver or amendment of any provisions therein shall be effective unless signed in writing by a Noldus representative. Any such written waiver shall only be applicable to the specific instance to which it relates and shall not be deemed to be a continuing or future waiver. 8.4. Amendments or changes to this EULA can only be agreed upon in writing between the Parties. 8.5. The EULA shall be binding upon the Parties thereto, their legal representatives, successors and assigns. End-User shall not assign any right or obligation arising out of this EULA without the prior written consent of Noldus. Any attempt by End-User to assign or delegate any obligation hereunder shall be deemed null and void. 9. Governing Law: End-Users USA Or Canada 9.1. If End-User is a legal entity and its principal place of business is located in the United States of America or Canada, or if End-User is an individual whose primary residence is located in the United States of America or Canada: - This EULA is exclusively governed by the laws of the Commonwealth of Virginia and the applicable federal laws of the United States of America, without regard to the conflicts of law provisions of any jurisdiction. Without limiting the previous sentence, End-User and Noldus expressly agree: (i) that the Virginia Uniform Computer Information Transactions Act, Virginia Code §§ 59.1-501.1 et seq. ("UCITA"), and the United Nations Convention on Contracts for the International Sale of Goods ("CISG") are expressly excluded from this EULA, (ii) that any and all terms contained in UCITA or CISG will have no force or effect on any portion of this EULA, and (iii) that UCITA and CISG do not apply to this EULA or the Software. - Any and all claims and disputes arising out of or in connection with this EULA, the Software, or the performance or non-performance by either party of any of its obligations under this EULA, which End-User and Noldus cannot resolve amicably within a reasonable period of time, will be commenced and maintained only in a state or federal court of competent subject matter jurisdiction situated or located in the United States of America. Noldus and End-User consent to the exclusive personal jurisdiction of and venue in any such court. - To the extent permitted by law: End-User must commence or file any claim or action arising out of or relating to this EULA or the Software within six months after the cause of action accrues, otherwise, such claim or cause of action is permanently barred. To the extent permitted by law, End-User expressly waives the right to commence or file any such claim or action under any longer statute of limitations. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Acknowledgments And Copyright Notices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-acknowledgments-and-copyright-notices Chapter: FaceReader 10. Governing Law: End-Users Other Countries 10.1. If End-User is a legal entity and its principal place of business is located in any country other than the United States of America or Canada, or if End-User is an individual whose primary residence is located in any country other than the United States of America or Canada: - This EULA is exclusively governed by the laws of The Netherlands. The United National Convention for Contracts on the International Sale of Goods is expressly excluded. - Any disputes arising out or in connection with this EULA that cannot be solved amicably within a reasonable period of time will be submitted to the competent court in Arnhem, The Netherlands, for any dispute with End-Users having their principal place of business in the European Union. In the event that an End-User has its principal place of business outside the European Union, the United States of America or Canada, any dispute shall be finally settled in accordance with the Arbitration Rules of the Netherlands Arbitration Institute. Location shall be Arnhem, The Netherlands. The arbitration procedure shall be conducted by one (1) arbiter in the English language. Acknowledgments And Copyright Notices FaceReader™ is a trademark of Vicarious Perception Technologies BV but the End-user license agreement for products from Noldus Information Technology BV applies. FaceReader would not be what it is without the use of third-party software. This page lists software libraries and other software products used in FaceReader and where you can find license and compliance information and/or acknowledgments for that product. For the complete terms and conditions in PDF format, see the PDF files in the folder Documentation\Legal\Acknowledgements, located in your application folder (default: C:\Program Files\Noldus\FaceReader 10). Third-Party Software Libraries - Boost — Open source (Boost community) software library, C++ templates. License: Boost software license. http://www.boost.org/users/license.html - IPP, MKL, TBB — Software library for signal, image, speech and audio processing (Intel Corporation). License: Intel Composer XE. https://software.intel.com/en-us/license/intel-simplified-software-license - OpenCV — Software library, collection of algorithms and sample code for various computer vision problems. License: 3-clause BSD License. http://opencv.org/license.html - HASP — Library for software protection. License: Safenet EULA. https://safenet.gemalto.com/DownloadNotice.aspx?dID=8589947119; Sentinel Gemalto: https://sentinel.gemalto.com/ - Wix Toolset — Tools to author software installers. License: Microsoft Reciprocal License (MS-RL). http://wixtoolset.org/about/license/ - Emgu CV — .Net wrapper to Open Source Computer Vision Library. FaceReader contains Emgu CV components under a commercial license. http://www.emgu.com - FFmpeg — Video file decoding and encoding. License: GNU Lesser General Public License. http://www.gnu.org/licenses/lgpl-3.0.txt. Source code available at: https://ffmpeg.org/ - NAudio — NAudio is used for audio playback of stimulus videos. License: Microsoft Public License (Ms-PL). http://naudio.codeplex.com/license. Source code available at: http://naudio.codeplex.com/ - Caffe — Caffe is a deep learning framework. License: BSD 2-Clause license. https://github.com/BVLC/caffe/blob/master/LICENSE. Source code available at: https://github.com/BVLC/caffe - Tensorflow Lite — Tensorflow Lite is used for multiple deep learning models within FaceReader. License: Apache License Version 2.0. https://github.com/tensorflow/tensorflow/blob/master/LICENSE. Source code available at: https://github.com/tensorflow/tensorflow - OpenVino — OpenVino is used for multiple deep learning models within FaceReader. License: Apache License Version 2.0. https://github.com/openvinotoolkit/openvino/blob/master/LICENSE. Source code available at: https://github.com/openvinotoolkit/openvino Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Action Units in the Log Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-action-units-in-the-log-files Chapter: FaceReader Action Units in the Log Files Aim To export the Action Units to a text file, Excel file or The Observer XT format file. Prerequisites - Your FaceReader license includes the Action Unit Module. - Action Unit analysis is switched on in the Settings. See Analyze Action Units. - You carried out an analysis. Export Action Units as States - Choose File > Settings and then click the Data Export tab. - Under Export (Detailed log, ODX, N-Linx and API), select Action units. Do not select Export Action Units as continuous values. To export the unilateral Action Unit intensities, select the corresponding checkbox. - Choose File > Export and select one of the options. See Export the data in FaceReader's output. The intensities are exported as letters to the detailed log. The letters correspond to the following Action Unit intensities: - Not active – [0.00 - 0.100] - A – [0.100 - 0.217] - B – [0.217 - 0.334] - C – [0.334 - 0.622] - D – [0.622 - 0.910] - E – [0.910 - 1.000] If you selected to export the unilateral Action Unit intensities, the Detailed log contains three columns for each Action Unit (the intensity on the left side of the face, on the right side and combined). The combined value is the maximum of the two. Export Action Units as Continuous Values You can also export Action Unit intensities as continuous values. To do so: - Choose File > Settings > Data export. - Under Export (Detailed log, ODX, N-Linx and API) select Action Units and Export Action Units as continuous values. - Choose File > Export and select one of the options. See Export the data in FaceReader's output. If you selected to export the unilateral Action Unit intensities, the Detailed log contains three columns for each Action Unit (the intensity on the left side of the face, on the right side and combined). The combined value is the maximum of the two. Action Unit Intensities in The Observer XT If you send FaceReader data to The Observer XT 13 or higher versions using the N-Linx network communication protocol, Action Unit intensities are not transferred to The Observer XT as numerical values but as intensity classes. See FaceReader with The Observer XT. If you want to import the intensities as continuous values: - Select to Export action units as continuous values. - Export FaceReader log files, export the data as Detailed log. - Import the detailed logs as external data. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Add Analysis Input URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-add-analysis-input Chapter: FaceReader Add Analysis Input Aim To define the videos, camera output, or images that FaceReader must analyze for each participant. Prerequisite You added at least one participant. See Add Your Test Participants Before You Start If you want to use Settings other than the default ones for your analyses, choose them before you add all analyses. If you, for example, work with Asian test participants, change the default face model to EastAsian before you add the analyses. See Choose Settings Add Analysis Input With The Project Wizard If you know before you create your project how many participants and analyses per participant your project will contain, you do not need to enter them manually. Use the Project wizard instead. See Project Wizard for more information. With The Stimulus Presentation Tool With The Stimulus Presentation Tool, the analysis is added automatically to the project when a participant starts a test. See Carry Out A Test With The Stimulus Presentation Tool Add Analysis Input Manually - Do one of the following: - Right-click a participant name and choose Add Analysis > Video, Camera, or Image. - Select the participant for which you want to add an analysis. Click the Video, Camera or Image button on the toolbar to add a video file, a live video source or images. - Select and open the input source. If you carry out camera analysis, select the Resolution and the Frame rate. See also: - More Information On Camera Analysis - Camera Resolution And Analysis In FaceReader Select the Use as Default Camera check box if you want FaceReader to automatically select the current camera for future camera analysis sessions. A new analysis is added to the Project Explorer. The video, camera or images icon indicates what type of analysis it is. - Repeat steps 1 and 2 to add more video files, images or live video sources. You are now ready to start an analysis. See Analyze Facial Expressions See Also More Information On Camera Analysis Notes - To edit an analysis, right-click the analysis and select Edit Analysis and make your choice. - To delete an analysis, make sure it is closed. To close an analysis, click the button next to it. Right-click the analysis and choose Delete Analysis. - To add multiple video files to your project, right-click the participant name in the Project Explorer and select Add Multiple Video Analyses. - If your project contains image analyses you cannot add video or camera analyses and if your project contains video or camera analyses you cannot add an image analysis. - If you carry out a camera analysis, or video analysis, do not carry out very long analyses/use long recordings. Especially if you export many different data, like facial states, Action Units, Stimuli and Event markers, these files get very large, which may cause performance problems. FaceReader has been tested and works well with camera analyses of two hours and video analyses of two hours with 15 fps and one hour with 30 fps. When you open a video that is longer than one hour, FaceReader shows a warning. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Add Your Test Participants URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-add-your-test-participants Chapter: FaceReader Add Your Test Participants Aim To define the test participants in your study. FaceReader organizes the data per test participant. You can enter participants automatically, or manually. Add Participants Automatically With A Basic FaceReader License If you know before you create your project how many participants and analyses per participant your project will contain, you do not need to enter them manually. Use the Project wizard instead. With The Stimulus Presentation Tool With Project Analysis and The Stimulus Presentation Tool, each participant is added automatically to the project when he/she starts a test. You do not have to add participants manually. See Carry Out A Test With The Stimulus Presentation Tool Add Participants Manually - Do one of the following for each test participant in your study: - Choose Participant > Add Participant. - Click the Add Participant button on the toolbar. - In the Name field, enter the participant's name or, for example, a number. - Two Independent Variables, Age and Gender, are present by default. FaceReader automatically estimates the age and gender of the participant from the video, camera input or image. To set the age or gender manually, click the pencil button and enter the correct value. Enter integer values for age, for example 40, not 40.5. Notes - To edit a participant, double-click its name and edit the details. - To delete a participant, make sure all its analyses are closed. To close an open analysis, click the button next to it. Right-click the participant's name and select Delete Participant. - You can define extra Independent Variables. If you do so, also enter the values for these variables in step 3. See Define Independent Variables - If you set the participant's gender or age manually, these are fixed with these values in the Circumplex Model of Affect and are not estimated by FaceReader. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Additional Modules URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-additional-modules Chapter: FaceReader FaceReader 10 - Additional Modules Multi-Subject Analysis FaceReader can detect and analyze multiple faces within the same video. When adding a multi-subject video to your project, FaceReader will automatically find all the participants in the video and add them as participants to the Project Explorer. After analyzing your video, you can select up to 8 participants in total for data analysis. Opening a single participant analysis added from a Multi-Subject Source will open the standard Analysis View, but only those parts where this participant was found show valid face results. Eye Tracking With web-based eye tracking, users of FaceReader can use a webcam to track where their participants are looking during a test. Eye tracking in FaceReader captures a person's gaze and their emotional reactions. A webcam streams the image and the software pinpoints key landmarks on the face. Then it measures head pose—the tilt and angle of the participant's head relative to the camera. All this information goes into a pre-trained neural network. The network finds a 3D gaze vector, which is visualized as a line extending from the eyes in the direction the participant is looking. A calibration step helps line up someone's gaze with the display. This way, the software can track where their eyes are moving and calculate metrics like fixation points and saccades. To include eye tracking data, you need to set up an experiment with the Stimuli Presentation Tool. After the test, you can view the fixations and saccades of someone's gaze, or visualize your results in a heatmap. Consumption Behavior Analyze behavior of the test participant that is related to eating and drinking. You can also view our online repository for custom expressions, which will be updated continually. The following behaviors can be analyzed: - Chewing and chewing motion - Intake event (taking a bite or taking a sip) Consumption behavior can be visualized in the Timeline, and exported for analysis in other packages. To enable a good measurement of intake behavior, the hands must be visible. FaceReader Online Integration FaceReader Online is based on FaceReader and runs online on a cloud server and does not need any on-site installation. It supports your online research and is flexible in where and when you can use it. Combining FaceReader and FaceReader Online offers the possibility to quickly test a large group of participants. Perform your tests from whatever location, even at the participant's home. You can analyze the data you collect with FaceReader Online in more detail by importing it into FaceReader. Want to test your experiment setup before inviting your participants to the lab? FaceReader Online allows you to quickly check your experiment with a pilot, including stimuli and data quality. Baby FaceReader The regular FaceReader enables expression analysis of participants starting from 3 years old. For analysis of younger test subjects you can use Baby FaceReader. This special version supports the analysis of infants between 6–24 months. It is possible to either only have Baby FaceReader or the regular FaceReader, or combine both versions in one installation. Baby FaceReader is based on Baby FACS as developed by Prof. Oster. Analysis Baby FaceReader works in a comparable way as the regular FaceReader, but there are a number of differences between the analyses of both versions. With Baby FaceReader, you can measure valence and arousal, as well as Action Units and custom expressions. The software also measures gaze direction, head orientation, and facial states. Eye tracking and vital signs measurement are possible as well. Note: Baby FaceReader does not contain basic expression analysis as these were not validated by Baby FACS. Source: FaceReader 10 Technical Specifications, Noldus Information Technology Source: FaceReader 10 Technical Specifications, Noldus Information Technology --- ## FaceReader 10 - Additional Options URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-additional-options Chapter: FaceReader How Continuous Calibration Works FaceReader continuously averages the facial expression intensities in the analysis. Correcting Expression Intensities With Continuous calibration, FaceReader corrects each expression intensity other than neutral in the following way: Corrected expression intensity = max (0, (Ia - Im))/ (1-Im). Where Ia is the intensity of that expression in the current frame and Im is the average intensity of that expression over all frames before the current frame. If (Ia - Im)/ (1-Im) is lower than zero, the calculated expression intensity will be zero. Correcting Intensity of Neutral The intensity of Neutral is calculated in the following way: Corrected Intensity Neutral = (Na + (1- Imaxm))/2 Where Na is the intensity of Neutral classified by FaceReader in the current frame and Imaxm is the average intensity of the expression with the highest average intensity in all the frames before the current one, excluding Neutral and Contempt. Example Consider the following average expression intensities: - Neutral = 0.6 - Happy = 0.9 - Sad = 0.1 - Angry = 0 - Surprised = 0 - Scared = 0 - Disgusted = 0 This gives an Imaxm of 0.9 And a corrected intensity of Neutral of: Corrected Intensity Neutral = (0.6 + (1 - 0.9)) / 2 = 0.35 Additional Options What Do You Want To Do? - Look for analysis information - Recover analyses after an interrupted batch analysis - Speed up analysis - Move an analysis to another participant Look For Analysis Information Open the analysis. Settings Click the Analysis Settings button to view the settings for the current analysis. Most fields are editable. See Settings for the Current Analysis Source Details Click the Source Details button to view information on the source of analysis, that is, the video file name, its location, duration, number of frames, frame rate, resolution and bitrate or in case of a camera analysis the camera name, its frame rate and resolution. Track Bar The Track bar at the bottom of the screen shows the following information: - Video analysis — Progress of the analysis, the analysis speed (in fps), the running end time of the analysis, the end time of the video and whether the video has audio. - Camera analysis — The analysis speed (in fps), the recording time left and whether audio is recorded. The maximum camera analysis duration is one hour. Please note that it is possible to run a camera analysis without recording video/audio. Recover Analyses After An Interrupted Batch Analysis An autosave file is created after each analysis. This is particularly important during batch analysis. If, for any reason, batch analysis is interrupted (for example after a power failure), you can recover the autosave file by renaming it to the original project file name. To do so: - Make sure FaceReader is closed. - Browse to the project folder and locate the file ~[project name]_Autosave (with no extension). - Rename the original project file to [project name]_backup.frx. - Rename the autosave file to the original project name. - Open the project again in FaceReader. There you should find all analyses completed before the interruption. Speed Up Analysis Carry out one or more options below to increase analysis speed. - Select only the option Framing in the Analysis visualization window, or close the entire Analysis Visualization window. - Close all visualization windows that you are not looking at. Each visualization slows down the analysis. - Analyze every 2nd or 3rd frame instead of every frame. To do so, choose File > Settings > Default Analysis Settings. Choose one of the options under Video. - Carry out only the analyses you require. Selecting Optional classifications decreases analysis speed. - Do not keep other programs running in the background. Move An Analysis To Another Participant If you have multiple videos of the same participant and you accidentally added another participant to the project and added the second, third etc. analysis to the new participant, you can combine all the analyses of one participant. Right-click the appropriate analysis in the Project Explorer, click Analysis and then Move Analysis To Other Participant. Select the target participant and then Yes to confirm the move. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Advanced Options URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-advanced-options Chapter: FaceReader Export (Detailed Log Only) Subject Characteristics With this option selected, three extra columns are added to the Detailed log: Gender (male/female), Age (an estimation of the test person's age) and Glasses (Yes/No). See Circumplex Model of Affect in FaceReader's output Participant Name And Analysis Index The name of the participant and the name of the analysis. Model Quality The model quality is indicated by a value between 0 and 1. See one of the following: - Step 3 in Manual procedure image analysis - Step 3 in Manual procedure video and camera analysis in Analyze facial expressions Empty Data Choose how the following values are exported to the export files: - Log value when the face could not be found – The term when FaceReader cannot find a face Default: FIND-FAILED. - Log value when the model fit failed – The term when FaceReader finds a face but cannot create a model of it. Default: FIT-FAILED. - Log value for when an item is unknown – The term when FaceReader finds a face and can create a model, but cannot determine the facial expression. Default: UNKNOWN Visualization Camera Automatically Clear Results After 1 Minute (For Demonstration Only) Select this option when giving a demonstration, to make sure that FaceReader can run for a long time. Default: Not selected. Video Repeat Video (For Demonstrations Only) This option is for demonstration purposes only. If you select this option your video is played continuously. Default: Not selected. Advanced Options Face Modeling Minimum Model Quality The minimum model quality required for a model to be valid. Accepted values: 0 (low quality) - 1 (high quality). Default value: 0.5 (this is the hatched line that you see in the middle of the Model quality bar). Gaze Tracking Angular Speed Threshold This threshold is used to distinguish between saccades (faster than the threshold) and fixations (slower than the threshold). Head Orientation The test person should stand or sit and look frontally into the camera, an angle of 30° (in both directions, yaw and pitch) is accepted by default. If the angle is bigger than this threshold, the face model will be rejected. You can increase or decrease the thresholds to accept face models of lower/higher quality, respectively. - Maximum allowed pitch angle — If the pitch angle is higher than this threshold, the face model will be rejected. Default value: 30 degrees. - Maximum allowed yaw angle — If the yaw angle is higher than this threshold, the face model will be rejected. Default value: 30 degrees. - Minimum allowed pitch angle — If the pitch angle is lower than this threshold, the face model will be rejected. Default value: -30 degrees. - Minimum allowed yaw angle — If the yaw angle is lower than this threshold, the face model will be rejected. Default value: -30 degrees. Heart Rate Heart Rate Variability Period The minimum time that is needed to calculate heart rate variability. Accepted values: 1-60 minutes. Default: 5 minutes. See also Calibration in The Vital Signs Module. Size Of Interest You can set the Size of Interest by clicking the up and down arrows for the Minimum face fraction and/or the Maximum face fraction. Minimum Face Fraction Minimum fraction of the face surface relative to the entire image surface. Accepted values: 0.01 - 1. Default: 0.11. Maximum Face Fraction Maximum fraction of the face surface relative to the entire image surface. Accepted values: 0.01 - 1. Default: 0.80. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Advanced Options For Data Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-advanced-options-for-data-analysis Chapter: FaceReader Data Selection Aim - Select what parameters to analyze - Select what stimuli/event markers to analyze - Select absolute or relative values for your parameters - Select how to aggregate data over time and over test participants - Select participants Prerequisites - Your license includes the Project Analysis Module. - Your project contains video or camera analyses. Procedure - Open the Project Analysis section (see Project analysis in short). - Select the chart or table of your choice. The Data selection window opens. Select What Parameters To Analyze The first section lists the parameters that will be included in your chart or table. Click select to see all the variables that are available and make a selection. The parameters in gray are the ones that are selected. Notes - It is not possible to select Valence or Arousal when you make a Pie Chart. - You cannot select any parameters when you make a Circumplex Model because this chart always shows a combination of Valence and Arousal. Select What Stimuli/Event Markers To Analyze The Stimulus or Event Marker section lists the stimuli and event markers that were scored in the project. Click a stimulus or event marker to select it and to visualize/tabulate the data during this stimulus/event marker. If you do not make a selection the whole observation period is taken into account. Advanced Options For Data Analysis Aim - To select whether you want to visualize/tabulate absolute or relative values of your parameters - To select how to aggregate data over time. - To select how to aggregate data over test participants. Prerequisites - Your license includes the Project Analysis Module. - Your project contains video or camera analyses. Procedure - Open the Project Analysis section (see Project analysis in short). - Select the chart or table of your choice. The Data selection window opens. - Click select next to Advanced Options to open the Advanced Options window and click the options you want to use: Select Absolute Or Relative Values For Your Parameters Select one of the options under Baseline Correction to visualize/tabulate either the absolute values or relative values of your parameters. Baseline Correction is not available when you make a Pie Chart. You can only visualize absolute values as relative values can be negative. - None (default) — With this option selected the absolute intensities of the selected data will be visualized/tabulated. The bar chart in the example below shows the mean absolute intensities of the facial expressions that the test participants showed during Commercial 1. - All Other Measurements — To visualize/tabulate the selected data during a stimulus relative to all other time fragments. Use this option to calculate in which way the facial expressions, for example, during watching a certain commercial differ from the expressions while the participants were not watching it. The bar chart in the example below shows the mean intensities of the facial expressions of the test participants during Commercial 1 relative to the facial expressions that they showed during the rest of the test. The chart shows that the test participants were happier during Commercial 1 than during the rest of the test. - Other Stimuli Or Event Markers — The selected data during a stimulus/event marker relative to the expression intensities during another stimulus/event marker. When you select this option, choose what stimuli or event markers to use as the baseline. With this option you can for example correct the facial expressions of test participants when they watched a certain commercial for the expressions while watching a neutral scene. The bar chart in the example below shows the mean intensities of the test participants during Commercial 1 relative to the facial expressions that they showed during a Neutral stimulus. The chart shows that the test participants were happier during Commercial 1 than during the Neutral stimulus. - Interval Before Stimulus/Event Marker — The selected data during a Stimulus relative to the expressions just before the stimulus or event. With this option you can measure the effect of a stimulus on the participant's mood, by looking at the changes induced by the stimulus. Enter the duration of the interval before the stimulus or event marker in the Interval field. The bar chart in the example below shows the mean intensities of the facial expressions of the test participants during Commercial 1 relative to the facial expressions that they showed during the 5-second interval before Commercial 1. The chart shows that the test participants were happier during Commercial 1 than during the 5-second interval before Commercial 1. Select How To Aggregate Data Over Time And Over Test Participants Select one of the options under Temporal Aggregation to select how the values per test participant are aggregated over time. If you choose Activation Period FaceReader counts the percentage of frames which have an activation higher than the threshold. The default threshold is 0.2. That means that the value for 'Happy' is, for instance, 60% if the intensity of 'Happy' is 0.2 or higher in 60% of the frames. Notes: - Temporal aggregation is not available when you make a Circumplex Model or Line Chart because these chart types are based on temporal data. - You can select multiple temporal aggregation methods when you make a table. Select one of the options under Participant Aggregation to select how the values of the different participants are aggregated. Note: Participant Aggregation is not available when you make a Box Plot because a Box Plot by definition shows a number of participant aggregation values (Q1, Q2, Q3). See Box Plot for more information. How Baseline Correction And Aggregation Is Performed Suppose you have three participants with one analysis each and you scored the same Stimulus for all three participants. You selected All Other Measurements as Baseline Correction in the Advanced Options and Mean for both Temporal Aggregation and Participant Aggregation. As an example, calculation of the relative mean value of Happy during the Stimulus is done in the following way: Participant 1 (P1) — (mean intensity Happy P1 within Stimulus interval) - (mean intensity Happy P1 outside Stimulus interval) = A Participant 2 (P2) — (mean intensity Happy P2 within Stimulus interval) - (mean intensity Happy P2 outside Stimulus interval) = B Participant 3 (P3) — (mean intensity Happy P3 within Stimulus interval) - (mean intensity Happy P2 outside Stimulus interval) = C Relative Mean value of Happy = (A + B + C)/ 3 Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - An Introduction to FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-an-introduction-to-facereader Chapter: FaceReader Introduction Main Topics - How to use this Help? - An introduction to FaceReader - How does FaceReader work? - Sample projects - Limitations of the current version - Modules - What is new in FaceReader 10 How to Use This Help? TIPS - If you do not see the Table of Contents on the left, enlarge the Help window or zoom out the characters (Ctrl+mouse wheel, or Ctrl+-). - To search for two or more adjacent words, use quotes, for example "Action Unit". - To go back to the search results after visiting one of the result pages, click again on the magnifying glass icon in the Search field. An Introduction to FaceReader Six Basic Expressions FaceReader is a program for facial expression analysis. It can detect emotional expressions in the face. It can identify six basic expressions: - Happy - Sad - Angry - Surprised - Scared - Disgusted - A Neutral state Contempt In addition to the six basic expressions, FaceReader can detect contempt. Contempt is an expression in which one corner of the lips is tightened and slightly raised. Baby FaceReader Baby FaceReader is a special version of FaceReader. It has been developed for babies and infants from 6-24 months old. Please note that Baby FaceReader analyzes Action Units, Valence and Arousal, it cannot detect the basic facial expressions. Baby FaceReader is based on the Baby FACS developed by Oster. Valence calculation in Baby FaceReader is based on Action Unit 6, 12 and 25 for positive valence. It takes the average intensity of these Action Units. Activity of Action Unit 1, 4, 7, 20, 25 and 43 results in a negative valence value. Your Baby FaceReader license can be extended with the Vital Signs Module. Baby FaceReader cannot be combined with other modules. The Voice Analysis Module, the Advanced Research Module and the Consumption Behavior Module are not available with Baby FaceReader. References Messinger, D.S., Mahoor, M.H., Chow, S.M. & Cohn, J.F. (2009). Automated measurement of facial expression in infant-mother interaction: A pilot study. Infancy 14(3): 285-305. Oster, H. 2003. Baby FACS: Facial Action Coding System for Infants and Young Children. Unpublished monograph and coding manual. New York University. Oster, H. 2012. The repertoire of infant facial expressions: An ontogenetic perspective. DOI: 10.1093/acprof:oso/9780198528845.003.0010. Rosenstein, D. & Oster, H. (1988). Differential facial responses to four basic tastes in newborns. Child development 59(6): 1555-1568. Webb, R., Ayers, S. & Endress, A. (2018). The City Infant Faces Database: A validated set of infant facial expressions. Behavior Research Methods 50: 151-159. Additional Classifications FaceReader can also analyze: - Facial states — Left and right eye open or closed, mouth open or closed and eyebrows raised, neutral or lowered - Global gaze direction — The gaze direction of the eyes, to the left, left-up and left-down, to the right, right-up and right-down and straight forward, up and down. - Gaze Type — Fixation or saccade. - Gaze angles — Horizontal and vertical gaze angle (in degrees). - Gaze location — The participant's gaze location on the screen/stimulus. This option is available with the Advanced Research Module. - Head orientation — The orientation of the head (pitch, yaw and roll, in degrees deviating from looking straight forward). - Head position — Horizontal, vertical and depth position relative to the camera. - Valence — Which indicates whether the person's emotional status is positive, negative or neutral. - Arousal — Which indicates how active the person is. - Subject characteristics — The estimation of the test participant's gender and age, and whether the person is wearing glasses or not. Subject characteristics are not available in Baby FaceReader. - Action Units — FaceReader can analyze the 20 most common Action Units in the face. In addition, there are a number of Action Units available as Custom Expressions. FaceReader analyzes Action Units in the left and right part of the face. Action Units are available with the Action Unit Module. For Baby FaceReader you do not need the Action Unit Module as extra module. Action Unit analysis is an integral part of Baby FaceReader. See The Action Unit Module - Custom expressions — FaceReader comes with a library of expressions like Interest, Attention, Confusion and Boredom. It is also possible to define your own Custom Expressions, based on Action Units, facial expressions, valence, arousal, and other parameters. Custom Expressions are available with the Action Unit Module. - Vital signs — This option is available with the Vital Signs Module. FaceReader can estimate the test participant's heart rate and heart rate variability and respiratory (breathing) rate from the camera or video images of their face. See The Vital Signs Module - Expressions in the voice — This option is available with the Voice Analysis Module. FaceReader can detect Neutral, Happy, Sad and Angry in the participant's voice. - Consumption Behavior — This option is available with the Consumption Behavior Module. FaceReader can analyze chewing behavior and count the number of intake events (bites/sips). Consumption Behavior analysis is not available in Baby FaceReader. See The Consumption Behavior Module FaceReader and The Observer XT FaceReader data can be imported into The Observer XT, the leading software package for the collection, analysis and presentation of observational data. This enables you to integrate FaceReader data with other data, such as manually logged events, physiological data and eye tracker data and to analyze the full context. For instance, what is the test participant watching on the screen and what emotion does that trigger. FaceReader can be used in a wide range of research areas: - Psychology — How do people respond to particular stimuli, e.g. in cognitive research. - Education — Observing students' facial expressions can support the development of educational tools. - Human-computer interaction — Facial expressions can provide valuable information about user experience. - Usability testing — Emotional expressions can indicate the ease of use and efficiency of user interfaces. - Market research — How do people respond to a new commercial's design? - Consumer behavior — How do participants in a sensory panel react to a new product? Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Analysis In Phases URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-analysis-in-phases Chapter: FaceReader Analyze Heart Rate, Heart Rate Variability And Breathing Rate Aim To switch on heart rate, heart rate variability, and breathing rate analysis. Prerequisite You have the Vital Signs Module. Procedure - Choose File > Settings > Analysis options. - Under Optional Classifications, select Vital signs. Note The option to analyze vital signs must be switched on, which is by default the case if you have the Vital Signs Module. However, when you upgrade a basic FaceReader license with the Vital Signs Module, you must switch the option on manually. Analysis In Phases Heart rate and breathing rate analysis is carried out in three phases, calibration, calculation, and post-processing. Calibration FaceReader requires a 8.5 second calibration period for RPPG measurements in which the signal of the skin color is sampled and processed for a reliable measurement. During the calibration stage the test participant should look into the camera and avoid extensive head movement. Calibration is done at the start of analysis and every time the participant's face is found again after it was not found for some time. When the face is found again, the Heart rate window shows Calibrating. FaceReader needs at least 5 minutes to calculate a value for the heart rate variability. This default setting was chosen according to standards found in the literature. You can change the heart rate variability period in the settings (File > Settings > Advanced settings). The calibration period for breathing rate measurements is 15 seconds. Excessive movements of e.g., arms in front of the chest will reset calibration. If chest movements are very shallow, or there is no breathing detected, a warning message will be shown in the Vital Signs window. Calculation To calculate the heart rate and breathing rate, for each time step the pulses/breaths over the previous ten seconds are used. Heart rate is expressed in beats per minute (bpm) and breathing rate in breaths per minute (bpm). Post-Processing At the end of analysis, the estimated heart rate, heart rate variability, and breathing rate are post-processed to improve the accuracy, also in the initial 8.5/15 seconds and every time a new calibration was carried out. Note that after analysis the reported heart rate and breathing rate values can differ from those seen during analysis. Do not rely on the exact values you see during analysis. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Analysis Modules URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-analysis-modules Chapter: FaceReader FaceReader 10 - Analysis Modules In-Depth Analysis Project Analysis The project explorer in FaceReader gives an overview of analyses per participant, and of participants per project. Projects which contain image analysis results cannot be analyzed here. You can view a number of different charts and tables: - Pie Chart - Box Plot - Bars - Circumplex Model - Line Chart - Table It is possible to calculate the mean, minimum, maximum, median or standard deviation of groups of participants. These values can be aggregated in the available chart types using both aggregation over time and aggregation over participants. You can also apply Baseline Correction. This baseline can be calculated using the following options: - All Other Measurements - Other Stimuli or Event Markers, which can be selected by the user - A specific interval before a Stimulus or Event Marker Both Stimuli and Event Markers are mutually exclusive. They can be regarded as two different behavioral classes. For more advanced coding, it is possible to use The Observer XT. It is possible to specify 36 Event Markers and Stimuli in total. The start of a Stimulus or the Start/Stop of an Event is triggered by a key (lower case letter or number). Markers are visualized in the Timeline, the color can be specified by the user. Event Markers or Stimuli can also be triggered externally, using the FaceReader API. Furthermore, this API can be used to generate triggers in case a Stimulus or Event Marker is scored in FaceReader. Markers can be placed both during live and during video analysis. Time information (start and stop of Stimuli and Event Markers) can be added in the detailed logs and .odx for export to The Observer XT. It is possible to analyze the response of separate groups of participants towards stimuli and event markers. Groups can be selected manually or automatically, based on independent variable values. Selections based on combinations of independent variables are also possible. When comparing responses, FaceReader carries out a t-test per stimulus with the participants as samples. The p-value threshold for the significance test is variable. Charts can be copied to clipboard or saved as an image (format .png, .bmp, .jpg, .tiff, .gif). Analysis data can be exported in a .txt or .xls format. Independent variables are participant specific variables, defined by the user. There are 2 types of independent variables: - Numerical — can take any numerical value. - Nominal — predefined values. Examples of nominal independent variables are native language or experience level. There are two default independent variables, which are always present: Age & Gender. These are the independent variables that can also be determined automatically by FaceReader. Stimulus Presentation Tool In order to indicate and select relevant episodes and events for analysis, you can use two types of markers. First, it is possible to specify Stimuli. A stimulus has a fixed duration specified by the user, and can be accompanied by a video or image. In case of a video, the start time of the stimulus within the video file can be specified by the user. Aside from Stimuli, it is possible to specify Event Markers, for example to indicate that the test participant is drinking or gets distracted. It is possible to synchronize stimulus presentation with the trigger of a stimulus marker in the FaceReader project. The Stimulus Presentation Tool can be used on the same computer where FaceReader is running, or on a separate computer. In this case the computers are connected via a local network. Action Units FaceReader can analyze the following 20 Action Units: - 1 – Inner Brow Raiser* - 2 – Outer Brow Raiser* - 4 – Brow Lowerer** - 5 – Upper Lid Raiser* - 6 – Cheek Raiser* - 7 – Lid Tightener* - 9 – Nose Wrinkler - 10 – Upper Lip Raiser - 12 – Lip Corner Puller* - 14 – Dimpler* - 15 – Lip Corner Depressor* - 17 – Chin Raiser - 18 – Lip Pucker - 20 – Lip Stretcher* - 23 – Lip Tightener - 24 – Lip Pressor - 25 – Lips Part - 26 – Jaw Drop - 27 – Mouth Stretch - 43 – Eyes Closed* *For Action Units marked with an asterisk, unilateral analysis is possible: you can choose whether the value of the Left and Right Action Units should be analyzed independently or not. **In Baby FaceReader, AU4 is replaced by AU3+4 (Brow Knitting and Knotting). Intensities are annotated by appending letters A (Trace), B (Slight), C (Pronounced), D (Severe), or E (Max). Action Units and their intensities can be visualized in the Timeline and in the Analysis Visualization, and exported in the detailed log. Export in the detailed log as numerical values is also possible. The continuous action unit values have the following ranges: - 0.000 – 0.100: Not Active - 0.100 – 0.217: A (Trace) - 0.217 – 0.334: B (Slight) - 0.334 – 0.622: C (Pronounced) - 0.622 – 0.910: D (Severe) - 0.910 – 1.000: E (Max) Custom Expressions It is also possible to define and analyze your own custom expressions. Users of FaceReader can build their own algorithms, using the following measurements as inputs: - Facial expressions - Action Units - Derived expressions (valence & arousal) - Custom expressions - Head orientation - Head position - Gaze angles - Heart rate, heart rate variability - Constant values These inputs can be combined in a self-defined algorithm, using the following processors: - Mathematical operations (maximum, minimum, sum, average, scale, offset, subtract, divide, multiply, scale to range, power, absolute, clip) - Logical operations (condition, and, or, not, if…else…) - Temporal operations (average, weighted average, sum, maximum, minimum, running average, running maximum, running minimum) A number of custom expressions is already available in the software: - The commonly occurring affective attitudes: interest, boredom, and confusion - Attention - Blink rate (AU45) - Head turn left (AU51), head turn right (AU52), head up (AU53), head down (AU54) - Laughing and smiling - Leaning backward and leaning forward - Spontaneous laughter and talking - With Baby FaceReader, Baby Cry and Baby Smile are available as default custom expressions The intensities of custom expressions can be displayed as a line chart, and can be exported for analysis in other software packages as well. Vital Signs Heart Rate and Heart Rate Variability Analyze heart rate and heart rate variability (HRV) of the test participant without additional hardware, using the FaceReader camera. Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the tissue under the skin. It is based on the principle that changes in the blood volume result in changes in the light reflectance of the skin. With each cardiac cycle the heart pumps blood to the periphery. Even though this pressure pulse is somewhat damped by the time it reaches the skin, it is enough to distend the arteries and arterioles in the subcutaneous tissue. PPG is often used non-invasively to make measurements at the skin surface. In remote PPG (RPPG), FaceReader can detect the change in blood volume caused by the pressure pulse when the face is properly illuminated. The amount of light reflected is then measured. When reflectance is plotted against time, each cardiac cycle appears as a peak. This information can be converted to heart rate (expressed in beats per minute). HRV is based on RMSSD (Root Mean Square of Successive Differences in msec) or SDNN (Standard Deviation of NN Intervals). The heart rate and HRV can be visualized as a line chart, and exported for analysis in other packages. The European Patent Office has granted patent EP2960862A1 to Vicarious Perception Technologies (VicarVision) for the method for stabilizing vital sign measurements using parametric facial appearance models via remote sensors. For more information, see: https://patents.google.com/patent/EP2960862A1/en. For an overview of the accuracy of the estimated heart rate, see: Gudi, Amogh, Marian Bittner, and Jan van Gemert. "Real-Time Webcam Heart-Rate and Variability Estimation with Clean Ground Truth for Evaluation." Applied Sciences 10.23 (2020): 8630. Breathing Rate FaceReader also supports the measurement of breathing rate by detecting upper-body movements associated with respiration. As breathing is a relatively slow process, the software needs 15 seconds for calibration to show values, and another 15 seconds to see reliable measurements. Note that the upper body should be visible in the video for the breathing rate measurement to work, and that excessive movement will reset calibration. If chest motions are very shallow or if there is no breathing detected, a warning will show in the vital signs panel. Voice Analysis Using English-language data, including both scripted and natural speech. Preliminary tests show potential applicability to other languages, particularly those with close linguistic or cultural similarities, such as Germanic languages. A volume threshold is used to decide whether to classify the audio signal (as to not classify background noise). Unlike video, audio cannot be segmented into discrete frames. Therefore, an audio buffer is used to collect approximately one second of data before starting analysis. The Voice Expression Line Chart shows the detected emotions over time. If at any point in time the volume is below the threshold, gaps will appear. The Voice Expression Intensity bar chart shows the currently detected emotions. The Voice View shows a four-second audio waveform, with different colors to indicated different detected emotions. Loudness and Speech Rate will appear alongside it. The Voice Valence and Arousal Line Chart shows valence and arousal over time. Using a high-quality microphone and limiting background noise is recommended to improve the accuracy of the voice analysis. It might be necessary to adjust the microphone's sensitivity to achieve the best results. For more information, download the White Paper about Voice Analysis on the FaceReader resources page. Source: FaceReader 10 Technical Specifications, Noldus Information Technology --- ## FaceReader 10 - Analysis Options URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-analysis-options Chapter: FaceReader Analysis Options Batch Analysis Skip Already Analyzed Frames When you have selected this option, video fragments that were already analyzed will be skipped in batch analysis. IMPORTANT Make sure you deselect this option when you carry out a camera analysis while simultaneously recording video and want to re-analyze these videos offline. Otherwise FaceReader will not analyze the frames that were already analyzed in the camera analysis. Camera Analysis Maximum Camera Analysis Duration Enter the maximum duration for analyses carried out with a live camera image. - Default: 1 hour. - Maximum: 2 hours. Optional Classifications Action Units With this option selected, FaceReader classifies Action Units. This option is only available when you have the Action Unit Module. See The Action Unit Module Consumption Behavior With this option selected, FaceReader analyzes whether the test participant is taking a bite or a sip ('Intake event') or is Chewing. See The Consumption Behavior Module Contempt Select this option to classify Contempt, which is an expression in which one corner of the lips is tightened and slightly raised. Treat Contempt As An Emotional State Select this option to add Contempt to the expression states in the State log and Timeline. This makes contempt mutually exclusive with the other expressions. Gaze Tracking With this option selected, FaceReader classifies whether the test participant looks left, forward or right, while taking the head orientation into account. The output is one of nine gaze directions: Left, Left-Up, Left-Down, Right, Right-Up, Right-Down, Up, Down and Forward. In addition, the gaze angle can be logged and visualized (Horizontal gaze angle and Vertical gaze angle). See Show Global Gaze Direction in FaceReader's Output Vital Signs With this option selected, FaceReader estimates the participant's current heart rate and heart rate variability by means of Photoplethysmography and respiratory (breathing) rate. This option is only available if your license includes the Vital Signs Module. See The Vital Signs Module Voice Analysis Select this option to analyze vocal characteristics and determine whether there is happiness, sadness or anger audible in the voice or whether it is neutral. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Analysis Visualization Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-analysis-visualization-notes Chapter: FaceReader Analysis Visualization Window To Access This Option Click one of the Select Window buttons, select Face Analysis and then Analysis Visualization. Analysis Visualization The Analysis Visualization window shows how FaceReader analyzes your images. Click the icons on the left of this window to select one or more of the options. In previous versions of FaceReader it was possible to view the texture model, the model constructed by the face modeling algorithm. In FaceReader 10 this option is no longer available. Show Image Shows the face in the video or camera image. You may want to hide the face for privacy reasons. Show Framing Draws a white box around the face at the location where the face was found. Show Mesh Shows the positions of the 468 key points used by the face modeling algorithm. The axes on the nose indicate the head orientation. Show Global Gaze Direction Shows the gaze direction of both eyes. The button Show Global Gaze Direction is not available when in the Analysis Settings under Optional Classifications, Gaze tracking is deselected. Show Facial States Shows the Facial States: whether the left and right eye is open or closed, whether the mouth is open or closed and whether the eyebrows are raised, neutral or lowered. Zoom On Face Zooms in on the face (if the face can be modeled). The model quality does not change when you zoom in on the face. Analysis Visualization Notes After the analysis, you can play back the visualizations together with the video. If you have The Action Unit Module, you can also display Action Units in the Analysis Visualization window. You can see what Action Units are active in the face and how active they are (Trace activation, Slight, Pronounced, Severe or Max). This option is available if you selected Action Units in the Settings (Settings -> Analysis Options -> Optional Classifications). See Visualize Action Units Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Analyze Multiple Subjects Per Video URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-analyze-multiple-subjects-per-video Chapter: FaceReader The Advanced Research Module Main Topics - Introduction to the Advanced Research Module - Analyze multiple subjects per video - Track the test participant's gaze when presenting stimuli Introduction to the Advanced Research Module The Advanced Research Module enables you to analyze multiple faces in a video, for instance participants in a focus group that were filmed with a single camera. See Analyze multiple subjects per video for the steps to follow. Please note that you cannot use any of the following analyses in a multi-subject analysis: Vital Signs analysis, Voice analysis and Consumption Behavior analysis. With the Advanced Research Module you can also track the gaze of a test participant. For gaze tracking you need the Stimulus Presentation Tool. After the test you can visualize the stimulus with a gaze overlay. You can also create a heatmap showing the hotspots on the stimulus where the participant looked the longest. See Track the test participant's gaze when presenting stimuli. Please note that you cannot combine the Advanced Research Module with Baby FaceReader. Analyze Multiple Subjects Per Video Aim To analyze facial expressions of multiple faces in a video. Prerequisites You have a pre-recorded video to analyze in FaceReader. It is not possible to analyze facial expressions of multiple subjects when you do a camera analysis. Procedure - On the Multi-subject Sources tab click the Add multi-subject video icon or from the Project menu select Multi-Subject Sources > Add Multi-Subject Video. - Optionally, click the Analysis settings button to view or adjust the settings. See Settings for the current analysis for more information. - Position the video to where you want to start the analysis. Optionally, deselect the Visualize results checkbox to speed up the analysis. - Click the Start analysis button. The track bar shows the progress of the analysis, the analysis speed (in fps), how many minutes:seconds.milliseconds of the video have been analyzed, the duration of the video and whether the video has audio. - Click the Stop Analysis button to stop the analysis or wait until the video has been fully analyzed. FaceReader shows how many participants were detected in the video and for how many minutes/seconds each participant was detected. - Optional — Select participants to merge them, for instance because a participant walks out of the camera view and FaceReader labels him/her as a new participant when he/she enters the camera view again. - Select the participants that you want to add to your project and click Add to project and Yes to confirm your choice. You can add a maximum of eight participants. The participants are added to the Participants tab and the Multi-Subject Sources tab of the Project Explorer. Participants Tab On the Participants tab you can find the individual analyses per participant. When you hover with your mouse over the video icon of one of the participants, you will see the first face image that could be analyzed. In this way you can identify who is participant 1, participant 2, etc. Click the magnifying glass button next to one of the analyses to open it. A standard analysis view will open. Click the Show framing icon in the Analysis Visualization window to view who is participant 1, 2, 3, etc. On the track bar you can see in what parts of the video the participant face could be analyzed. The rest of the data is shown as gaps (shown in white). If you analyze multiple videos of the same participants, FaceReader will not recognize the participants in the second, third etc. video. If you like, you can bring the analyses together. Right-click on an analysis in the Project Explorer, click Analysis and then Move Analysis To Other Participant. Select the target participant and then Yes to confirm the move. Multi-Subject Sources Tab On the Multi-Subject Sources tab the participants are grouped by source. Double-click Participants or click the icon next to Participants to get an overview of the participants that were detected in the video and added to the project. The overview also shows for how many minutes/seconds each participant was detected. Click the source button on the Participants tab or the Multi-Subject Sources tab to view the Multi-Subject Source window again. Click Exclude/Merge if you want to exclude/merge (more) participants. Please note: - You cannot calibrate participants in a multi-subject analysis. - You cannot add analyses to multi-source participants. - You cannot re-analyze the video. Track the Test Participant's Gaze When Presenting Stimuli Aim To assess what details in a stimulus attract the test participant's attention. Prerequisites - You have installed the Stimulus Presentation Tool. - You selected Gaze tracking in the Settings > Analysis options. Procedure Define a test in FaceReader and select Perform gaze calibration. See Define a test and Carry out a test with the Stimulus Presentation Tool under Project Analysis. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Calculate Statistics And Summarize Them In A Table URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-calculate-statistics-and-summarize-them-in-a-table Chapter: FaceReader Line Chart A Line chart shows the values of your parameters over time, aggregated over the test participants you selected. The Line Chart below shows the custom expressions of the five test participants in the 'FaceReader sample project - Two stimuli'. The data that are taken into account are those of the time period when the test participants were watching the 'Twins eating' stimulus. You can visualize a Line Chart together with the stimulus/event marker and one or more participant videos. If the stimulus is a video, you can play it back and a hairline in the Line Chart shows the position in the video. Please note that a warning will appear if you select analyses of different length. This may happen in a project in which no stimuli were presented to the test participants. The Line chart will show data up to the duration of the shortest analysis. A Line Chart has a number of two icons in the toolbar: - Zoom Out and Zoom In — To zoom out and in on the timeline. And the Y axis icon to access: - Auto Range — To display a scale with a minimum and maximum value that fit your data. - Full Range — To display a scale with a minimum of -1.00 and a maximum of +1.00. Use this scale to compare multiple charts, for instance, one chart for your female subjects and one for your male subjects. - MIN and MAX — To set the minimum and maximum Y-value. Heatmap A heatmap shows the hotspots of the test participant's gaze overlay on a stimulus, indicating where the test participant looked the longest. On the time axis you can define an interval for which you want to see the heatmap. Calculate Statistics And Summarize Them In A Table Aim To calculate statistics on the analyzed facial expressions and other parameters of all participants, participant groups or single participants. Prerequisites - Your FaceReader license includes the Project Analysis Module. - Your project includes one or more video or camera analyses. Procedure - Open the Project Analysis section and click Table. - Select the data you want to include in your analysis. See Data selection for more information. Click OK when you are ready. FaceReader will show a table with the results. A table has the same information/icon in the toolbar as a chart. See Visualize Your Data In A Chart for more information. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Camera And Accessories URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-camera-and-accessories Chapter: FaceReader FaceReader Trial Version Aim To try FaceReader for free for a limited period. Restrictions - Valid for 14 days (from the day of activation). Prerequisite - You received a link to download the setup file. - You received a software license key. - Your computer meets the System requirements Procedure - Open the FaceReader trial download page and download the setup file. - Double-click the setup file that you downloaded and follow the instructions on your screen. - Start FaceReader. - A window opens, choose Activate software license key. - In the following window select either Floating or Fixed. See What Is The Difference Between A Floating And A Fixed Activation? - In the window that appears, enter the software license key. - Click OK. Notes - To see how many days are left in your trial, choose Help > About. - When the trial period expires, a message is shown at start up. - The Action Unit Module, The Vital Signs Module, The Advanced Research Module, and The Consumption Behavior Module are enabled in the trial version. With the Trial version you can use the regular FaceReader functionality and Baby FaceReader. Camera And Accessories Supported Cameras FaceReader can only classify facial expressions correctly if it gets a good image. Both the placement of the camera and the lighting of the subject's face are of crucial importance in obtaining reliable classification results. Also the quality of the camera is crucial. The following cameras are supported. USB cameras FaceReader is supported with current generation CCD webcams with a resolution of at least 640 x 480 pixels. FaceReader and all its modules has been tested with the following USB cameras: - Logitech C920, C922, C925e, C930e - Logitech Brio - Microsoft Lifecam Studio Do note that the Logitech Brio and Microsoft LifeCam Studio are not suitable for the Vital Signs Module due to internal image processing (see Introduction to Vital Signs). You can purchase these cameras from us or use another current generation high quality webcam with a resolution of at least 640 x 480 pixels. IP cameras An IP camera is connected with the FaceReader PC via Internet, and enables you to do tests with test participants at another location or at the test participant's home. FaceReader works with IP camera that support MJPEG or JPEG output. FaceReader cannot import RTSP output of IP cameras. Compared to webcams such as the Microsoft LifeCam Studio, IP camera signals are processed slower. This is caused by the fact that IP cameras need time to encode video. Also sending videos over a network takes time. This means that the IP camera video signals received by FaceReader are analyzed with a delay. This effect is also seen when The Stimulus Presentation Tool is used. The delay is in the order of magnitude of 0.1 - 0.3 seconds if you use the FaceReader setup in a company network. If you use a dedicated local network for the FaceReader setup, which is recommended, the delay is less and in the order of magnitude of 0.1-0.2 seconds. If this delay is too large for your experiment's accuracy, record with a USB camera instead. Infrared cameras You can also use a camera that is sensitive to (near) infrared light, in combination with lights of this type, for instance, if you want to analyze people's facial expressions in a cinema or other (near)-dark environments. Please note that such cameras are not suitable for vital signs measurements and it is not possible to measure heart rate, heart rate variability, and breathing rate with infrared recordings. To get started with the Microsoft LifeCam Studio Download the drivers (Microsoft LifeCam 5.20.msi) from the MyNoldus portal (my.noldus.com). IMPORTANT If you upgrade an older version of the Microsoft LifeCam Studio driver to the driver that comes with FaceReader 10, you cannot downgrade it to the old driver anymore. To get started with the Logitech BRIO, C920, C922, C925e and C930e The Logitech BRIO, C920, C922, C925ed and C930e do not require driver installation. See also - Camera Frame Rate And Samples In FaceReader - Camera Resolution And Analysis In FaceReader Camera Position It is important to place the camera at a location that will give the most steady frontal view of the subject's face throughout the experiment. The ideal position for the camera is directly in front of the test participant. If the subject faces a computer screen, the camera can be placed either directly above or directly below the screen. When placing the camera on top of the monitor, try to position it slightly below eye level, either by raising the chair and/or by lowering the monitor. When placing the camera below the monitor, lower the chair to position the camera slightly below eye level. The classification output may have a small bias towards 'angry' when the camera is placed on top of the monitor and a small bias towards 'surprised' when the camera is placed below the monitor. This is due to the fact that people tend to tilt their head when showing these emotions. If that is a problem, you can compensate for it by calibration. See Calibrate FaceReader Image Brightness And Contrast It is important to adjust your camera to provide images with a good contrast and brightness. You can adjust the contrast and brightness by adjusting the hardware settings using the software provided by the manufacturer of your camera. When adjusting your hardware settings, do not pay attention to the lighting of the background. Focus only on the face area of the image and ignore a very light or very dark background. Do note that for the Vital Signs Module, slightly different camera capture settings apply. See Introduction to Vital Signs for more information. The picture above is an example of a face image showing a good contrast and lighting. Dark areas of the face (such as the eyebrows and the pupils) are near-black and the lightest part of the face (the eye whites) are nearly white. The intensity histogram (made of the face area only) shows how the intensity values fill the whole spectrum. The face area of the image below is overexposed. The forehead and cheekbones are nearly white and show very little texture. The histogram shows how only the high intensity part of the spectrum is filled. Decrease the brightness by adjusting the hardware settings of your digital camera or decrease the aperture size of your analog camera to correct this problem. A very common problem is that the image has too little contrast. Especially when the background is very dark or very light and the camera is set to 'automatic', the face area of the image will have a very low variability in intensity (a low contrast). The contrast is too low when the face area of the image contains no bright white and no deep black pixels. The intensity histogram shows that only the middle section of the spectrum is filled. Correct this problem by adjusting your camera (increase the contrast). When working with a person with a dark or very pale skin color, you may need to make some extra adjustments. The default settings will often yield an image as shown below. Although there are both dark areas and white areas (the eyes) in the face, the skin itself shows too little variations in intensity. By increasing the brightness (to make the face lighter) and increasing the contrast (to increase the variation in skin tones) you can correct this problem. For people with a very pale skin, decrease the brightness and contrast. The corrected image should look similar to the image below. Pay special attention to the skin tones. Notes - IMPORTANT Changing the brightness and/or contrast of an already recorded video or an image will have little or no effect on the quality of the analysis. The procedure above can only improve FaceReader's performance when applied at the moment the video is made. - It is not possible to view intensity histograms in FaceReader. To view such plots, use graphics software like Paint.NET or Photoshop. To analyze video images, first make a screenshot of the image of interest. - To assess the quality of your (video) image, view FaceReader's model quality bar. See one of the following: - Step 3 in Manual Procedure Image Analysis in Analyze Facial Expressions - Step 3 in Manual Procedure Video And Camera Analysis in Analyze Facial Expressions See also - Camera Frame Rate And Samples In FaceReader - Camera Resolution And Analysis In FaceReader Lighting Setup A good lighting setup is vital to get a good image. Diffuse frontal and natural lighting is desirable. The light intensity or color is less relevant. Strong shadows or reflections should be avoided. If possible, place the FaceReader setup in front of a window. Make sure that any windows to the sides of the subject are blinded. Lights from the ceiling, common in most buildings, will produce shadows below the eyebrows and nose. In situations where interior lighting cannot be controlled, stronger lights (e.g., professional photo lights) can be used to negate the effect of other, undesirable, light sources. You can purchase such lights from Noldus IT. You can also use (near) infrared light, in combination with a camera that is sensitive to this type of light. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Choose Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-choose-settings Chapter: FaceReader Analyze Facial Expressions Main Topics - Choose Settings - Analyze Facial Expressions - Calibrate FaceReader - Additional Options Choose Settings Aim - To choose settings that are valid for all future analyses, for example to choose the Video frame rate — See Settings for All Future Analyses - To adjust some settings for the analysis that is open on your screen, for example to choose the Active Face Model — See Settings for the Current Analysis Set default or current analysis settings for the following: - Face model – see Active Face Model - Calibration – see Calibrate FaceReader - Smoothen classifications – see Classification - Image rotation – see Rotation - Video sample rate – see Video Settings for All Future Analyses - Choose File > Settings > Default Analysis Settings. - Specify the settings. See Default Analysis Settings for an explanation of the options. Note The Default Analysis Settings do not apply to already existing analyses. To apply the new settings to an existing analysis, select Settings for the current analysis and redo the analysis. Settings for the Current Analysis - Open the analysis by double-clicking it in the Project Explorer or clicking the magnifying glass button next to it. - Select the Analysis Settings by clicking the Settings button on the bottom of your screen. - Click the pencil next to a setting to edit it. See Default Analysis Settings for an explanation of the options. The Analysis Settings panel includes the following options: - Face model – General - Smoothen classifications – Yes - Sample rate – Every frame - Image rotation – None - Consumption behavior c... – Unknown - Continuous calibration – No - Selected calibration – No calibrations for General Note You can only select Continuous calibration if you first set the Selected calibration to None. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Circumplex Model URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-circumplex-model Chapter: FaceReader Pie Chart A Pie Chart shows for each parameter that you selected the proportion of the analysis time it was the dominant one (for facial expressions) or it was active (for Action Units) aggregated over the participants that you selected. In the above Pie Chart 'Happy' was the dominant facial expression for 41% of the analyzed time and 'Neutral' for 37% of the time. When you move over the chart with your mouse pointer you can also see the percentages for the other facial expressions. For instance, 'Sad' was the dominant facial expression for 0.158 (= 15.8%) of the analyzed time. Box Plot A Box Plot shows the minimum value (the lowest data point of the error bar), Q1 (first quartile) and Q3 (third quartile) (the borders of the box) and the median (Q2) for each parameter that you selected. When you move over the plot with your mouse pointer, you can see the values for Q1, Q2 and Q3. Notes - A quartile is the percentage of participants that shows this or a lower expression intensity. So if the first quartile (Q1, or 25th quartile) of the facial expression Happy is 0.3, this means that 25 percent of the participants has an intensity of Happy of maximally 0.3. - The individual participants represent the samples. Hence, if you have five participants with three analyses each, the box plots are based on five samples. - The quartiles are calculated with N + 1 Basis interpolation, which is also used in the statistical program SPSS. If the sample size is lower than 3, the first quartile (25th quartile) is the same as the minimum and the third quartile (75th quartile) is the same as the maximum value, which is also the same as in SPSS. Bar Chart A Bar Chart shows the values of the parameters you selected, aggregated over your selected participants and aggregated over time. When you move over the chart with your mouse pointer you can see the value for each parameter. Circumplex Model A Circumplex Model describes emotions in the form of a heatmap in a two-dimensional circular space, containing arousal on the vertical axis and valence on the horizontal axis. The center of the circle represents a neutral valence and a medium level of arousal. The Circumplex Model is based on the data of the participants that you selected. The Circumplex Model is only available if you scored stimuli or event markers in your project. The chart below shows the Circumplex Model for the five test participants in the 'FaceReader sample project - Two stimuli'. The data that are taken into account are those of the time period when the test participants were watching the 'Twins eating' stimulus. You can visualize another Circumplex Model, select the 'Frying insects' stimulus and compare the two plots. The color of the heatmap is based on the percentage of time the affect that was most present occurred. This percentage of time (37% in the plot below) is set as the maximum and is colored red. The Circumplex Model in FaceReader is based on the model described by Russel (1980). Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Compare Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-compare-data Chapter: FaceReader Visualize Your Stimulus, Participant Videos And Line Chart Aim To display the stimulus video to play it back together with the recorded video of the test participant's face and a Line Chart with the data. Prerequisites - Your license includes the Project Analysis Module. - Your project contains video or camera analyses and one or more stimuli. Procedure - Open the Project Analysis section and click Stimulus. - Select the stimulus that you want to display and click OK. The stimulus video will open. Not all videos supported by FaceReader can directly be shown in the Project Analysis Module. They might require conversion first. - Click Participant and select the appropriate participant and analysis to display the corresponding video. Then click OK. The participant video will open next to the stimulus video. The participant video window contains three icons, one to switch the sound on and off, one to display the video full screen and one to move the video from the video window and display it as a picture-in-picture. The participant video displayed above is from the 'FaceReader sample project - Two stimuli'. In this project the test participants watched two stimulus videos, 'Twins Eating' and 'Frying insects'. You can display a Line Chart together with the stimulus video and the participant video and play back the videos in sync. A hairline in the Line Chart shows the position in the videos. Compare Data Aim To compare two or more data sets in a chart or table and carry out a t-test to test for significant differences. Prerequisites - Your license includes the Project Analysis Module. - Your project contains video or camera analyses. Procedure Select Data - Open the Project Analysis section and click Compare. - Click Add Data Selection. - If your project contains stimuli or events markers — Select a stimulus/event marker to compare data sets for this stimulus/event marker only. - Click Adjust Filter to choose what participants you want to include in the selection. You can base your selection on participant name, analysis name, participant/analysis combination, gender or age. Select, for instance, all the male subjects in your project. Click Update to add the filter to your selection. See Select Participants for more information. - Click OK. The Participant Filter is added to the Selection window. You can see how many test participants have been selected. - Click Add Data Selection to select a second data selection. - Click Adjust Filter and select the second set of data. Select, for instance, all female subjects in your project. Click Update and then OK. - Repeat steps 6 and 7 to add more data sets to the comparison in case you have more than two participant groups. - Select whether you want to compare the two data sets in a Bar Chart, Table, Correlation Table or Line Chart or visualize Insights. - Select the parameters you want to visualize/tabulate. Then click OK. - Select the advanced options of your choice. Then click OK. See Advanced Options For Data Analysis for more information. Tip: You can change the color of the selected data. Click on the colored bar in front of the data set and pick the color you like. Add All Participants As A Separate Selection Select this option to compare the data of all the participants in your project. - Open the Project Analysis section and click Compare. - Click Add All Participants As A Separate Selection. A list with all the participants in your project will appear as a separate data selection. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Compare Data in a Line Chart URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-compare-data-in-a-line-chart Chapter: FaceReader Compare Data in a Line Chart - Select two or more data sets following the steps in Compare data. - Click Line Chart and select the parameters you want to include in your test. - Select what Comparison Type you prefer: either Side By Side or Synchrony. - Select what Baseline correction method and what Temporal Aggregation method you want to use and click OK. Side by Side If you choose the option Side By Side the absolute intensities of the facial expressions are plotted over time. Hover with your mouse over a filter icon to see what data have been selected. The example in the screenshot below comes from the FaceReader 10 - Sample project - Two stimuli. The data of the participants older than 40 (n=2) are shown as continuous lines and the data of the participants younger than 40 (n=3) as dotted lines. The graph shows that a few seconds after the start of the 'Frying insects' stimulus the younger participants had a higher valence than the older participants and it remained higher until the end of the stimulus. The reason was that the female participants found the stimulus so disgusting that they started to laugh. Synchrony If you choose Synchrony a correlation chart will be shown with a sliding window of 10 seconds. The screenshot below again shows the data of the FaceReader 10 - Sample Project - Two stimuli during the 'Frying insects' stimulus. The graph shows the correlation between the valence of the older participants (n=2) and the valence of the younger participants (n=3). The correlation varies quite a lot with a peak at the start of the stimulus and a smaller peak around 15 seconds after the start of the stimulus. How Is the Correlation Calculated? FaceReader calculates a Pearson correlation coefficient. Its value ranges from -1 to 1. 1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship. 0 indicates no linear relationship at all. Compare Data in a Correlation Table - Select two or more data sets following the steps in Compare data. - Click Correlation Table and select the parameters you want to include in your test. - Select what Baseline correction method and what Temporal Aggregation method you want to use and click OK. The Correlation Table appears with for each parameter (facial expression, Valence, Arousal, etc.) the correlation between the two data sets. When you hover with your mouse over the filter icons you can see what data have been selected. See How is the correlation calculated? for more details. Compare Data and Visualize Insights - Select two or more data sets following the steps in Compare data. - Select Insights and select the parameters you want to visualize in your chart. - Set a P-value threshold to carry out a two-tailed t-test. The default value for the threshold is 10%. - Select what Temporal Aggregation method you want to use and click OK. Bar charts will appear for all the parameters that show significant differences. - Move with your mouse pointer over a filter icon to see what data have been selected. The bar chart in the example below shows the insight when comparing Male and Female test participants during Stimulus 1. A P-value threshold of 10% was used. FaceReader shows bar charts for the parameters that are significantly different, in this case Surprised. The data selection also included Happy but the two groups did not show any significant differences for this facial expression. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Compare Data in a Table and Carry Out a T-Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-compare-data-in-a-table-and-carry-out-a-t-test Chapter: FaceReader Adjust Your Selection - Edit Selection — Click the pencil icon to change your selection. - Adjust Caption — To give the selected data a more logical or shorter name. - Remove Data Selection Compare Data in a Bar Chart - Select two or more data sets following the steps in Compare data. - Click Bar Chart and select the parameters you want to visualize in your chart. - Select what Temporal Aggregation method and Participant Aggregation method you want to use and click OK. Your Bar Chart appears. - Hover with your mouse over a filter icon to see what data have been selected. The Bar Chart in the example below shows the mean intensities of the four negative facial expressions (Sad, Angry, Scared and Disgusted) for two groups of test participants (Male and Female subjects). Compare Data in a Table and Carry Out a T-Test - Select two or more data sets following the steps in Compare data. - Click Table and select the parameters you want to include in your test. - Set a P-value threshold to carry out a two-tailed t-test. The default value for the threshold is 10%. - Select what Temporal Aggregation method you want to use and click OK. Your table appears with the mean values and standard deviation for the parameters that you have selected in step 2. Each row in the table shows the results for one of the data sets that you have selected in step 1. - Click one of the rows to test for significant differences. Colored cells indicate significant differences. When you move with your mouse pointer over a colored cell you can see the exact P-value. The table in the example below shows the mean intensities and standard deviations of four facial expressions of two groups of test participants, Male (upper row) and Female (lower row). The colored cell indicates that the two groups show a significant difference in the intensity of Happy. Note on Standard Deviations Each participant is a replicate. So if you have one participant with three analyses, the standard deviations will be zero, because the sample size is one. If you have three participants with two analyses each, the standard deviations will be based on three samples. IMPORTANT Please note that the appropriate statistical test depends on your data. Your data may not be normally distributed, which means that you need a non parametric test instead of a t-test. Also corrections like Bonferroni on the P-values may be needed for multiple comparisons. Consult your statistician for advice. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Continuous Calibration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-continuous-calibration Chapter: FaceReader How Participant Calibration Works If you use images for calibration, FaceReader searches for the image with the lowest model error. If you use camera or video analysis, FaceReader analyzes two seconds and uses the image with the lowest model error for calibration. Correcting Expression Intensities FaceReader corrects each expression other than neutral in the following way: Corrected Expression intensity = max (0, (Ia - Ic))/ (1-Ic) Where Ia is the intensity of that expression in the analysis and Ic is the intensity of that expression found in the calibration. If (Ia - Ic)/ (1-Ic) is lower than zero, the calculated expression intensity will be zero. You can find the Ic values in the header of the Detailed log file. Correcting The Intensity Of Neutral The intensity of Neutral is calculated in the following way: Corrected Intensity Neutral = (Na + (1- Imax)))/2 Where Na is the intensity of Neutral classified by FaceReader and Imax is the intensity of the expression with the highest intensity, excluding Neutral and Contempt. Example Consider the following expression intensities: - Neutral = 0.6 - Happy = 0.9 - Sad = 0.1 - Angry = 0 - Surprised = 0 - Scared = 0 - Disgusted = 0 This gives an Imax of 0.9 And a corrected intensity of Neutral of: Corrected Intensity Neutral = (0.6 + (1 - 0.9)) / 2 = 0.35 Continuous Calibration Aim To correct for person-specific biases in facial expressions if you do not have images during which the test participant looks neutral. Procedure - Open the analysis for which you want to use continuous calibration. To open an analysis, double-click it in the Project Explorer, or click the magnifying glass button next to it. - Click the Analysis Settings button at the bottom of your screen to open the Analysis Settings window. - Click the pencil button next to Selected Calibration and select None. - In the same window, click the pencil button next to Continuous Calibration and select Yes. This sets the Selected Calibration field to Disabled. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Control FaceReader With The Observer XT Using N-Linx URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-control-facereader-with-the-observer-xt-using-n-linx Chapter: FaceReader Control FaceReader With The Observer XT Using N-Linx Aim To automatically analyze facial expressions with FaceReader together with an observation in The Observer XT, import the FaceReader data and videos and synchronize them automatically with the event log. Background The communication between FaceReader and The Observer XT makes use of the Noldus network communication protocol N-Linx. For details on N-Linx, see the Reference Manual - N-Linx. You can download it from the download section of the Noldus website. Prerequisites - You have a license for The Observer XT 14.1 or higher that includes the External Data Module. To see if you have this module, open The Observer XT and choose Help > About The Observer XT > License info. - N-Linx Server is installed on a computer in the network. - Both FaceReader and The Observer XT are open. - You created a project in The Observer XT and FaceReader. These projects are open. - Your FaceReader project does not contain image analyses. You cannot mix image analyses with camera analyses in FaceReader. - You selected a default camera in FaceReader. - IMPORTANT The Coding Scheme in The Observer XT does not contain element names that are also used in FaceReader, like Neutral, Unknown, or Happy. - FaceReader, The Observer XT and N-Linx Server run on computers that are part of the same network. Procedure - If FaceReader, The Observer XT, and N-Linx Server are not all installed on the same computer, make sure that traffic through the N-Linx port is not blocked by Windows Firewall. Create exceptions in Windows Firewall for the N-Linx port on all computers with FaceReader, The Observer XT, and N-Linx Server. See Create exceptions for the N-Linx port in Windows Firewall. - If FaceReader and The Observer are installed on different computers and you want to import the FaceReader videos automatically in The Observer XT, make sure that The Observer XT can access the FaceReader videos. See Make sure The Observer XT can access the FaceReader video files. - Set up FaceReader to work with The Observer XT. - Set up The Observer XT to work with FaceReader. - Carry out your observation in The Observer XT and co-acquire data with FaceReader. See Observe in The Observer XT and analyze in FaceReader. Note Check on the download section of the Noldus website if an update of this procedure is available. For example in case of an update of The Observer XT or N-Linx. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Core Features and Capabilities URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-core-features-and-capabilities Chapter: FaceReader FaceReader 10 - Core Features and Capabilities Functionality FaceReader can recognize a number of specific properties in facial images, including the following six basic expressions: - Happy - Sad - Angry - Surprised - Scared - Disgusted These are the six universal or basic emotions as described by Ekman (Universal Facial Expressions of Emotion, California Mental Health Research Digest, 8, 151-158, 1970), which are cross cultural. Additionally, FaceReader can recognize a neutral state and analyze contempt as an emotional state. The primary output is a continuous value between 0 and 1 per expression, which corresponds with the intensity and clarity of an emotion. Furthermore, calibration is not required in order to start analysis. All emotions are represented as bar graphs and can also be displayed as a line graph. An additional graph summarizes the valence (negativity or positivity) of the emotional status of the subject. Happy is regarded as a positive emotion; sad, angry, scared, and disgusted as negative emotions. Valence is calculated as the intensity of happy minus the maximum value of the negative emotions. Data are also visualized in a pie chart, showing the percentage per emotion. The line graphs and pie chart can be copied or saved as an image, for example for use in a Word report. Valence can also be visualized in a circumplex model, as described by Russell, J. A. (A Circumplex Model of Affect. Journal of Personality and Social Psychology, 39(6), 1161, 1980). In this model, valence is displayed on the horizontal axis. On the vertical axis the level of arousal is shown. The calculation of arousal in FaceReader is based on activation of Action Units and volatility. Arousal can also be displayed as a line graph. FaceReader contains a model quality bar, which gives you a good indication of how well the program is able to model the face depicted in the image. This information can also be stored in the logs created by FaceReader. When using multiple cameras, this information can be used to select the best analysis result. In addition to emotions, FaceReader can detect subject characteristics. There are two default independent variables: Age and Gender. These are the independent variables that can also be determined automatically by FaceReader. A range is given for age. For gender, a certainty level (between 0 and 100%) is given. Finally, FaceReader offers a number of extra classifications: Facial States Classification of certain parts of the face: - Left and right eye open or closed - Mouth open or closed - Left and right eyebrow raised, neutral, or lowered Global Gaze Direction Nine directions: right up, right, right down, up, forward, down, left up, left, or left down. There also is an indication of horizontal and vertical gaze angle. Head Orientation Tracking Enables tracking of the full 3D orientation of the head of the analyzed person. Head orientation is recorded in three angles (pitch, yaw, and roll), which denote the head rotation around the X, Y, and Z axis. FaceReader also measures the distance between the face and the camera in three directions. The extra classifications can be visualized in line graphs. Input FaceReader can be used with different input sources: Video FaceReader supports most common video codecs, including: MPEG1, MPEG2, XviD, DivX4, DivX5, DivX6, H.264, H.265, DivX, DV-AVI, and uncompressed AVI. The advantage of video analysis is that you can achieve a higher resolution. Videos can be analyzed frame-by-frame, or at a higher speed, analyzing every 2nd or every 3rd frame. When using frame-by-frame, the sample rate depends on the frame rate of the video, i.e. 30 frames/sec. This mode makes it possible to detect even short emotion changes (100 msec) and micro-expressions. For demonstration purposes, the video can run in loop (repeat) mode. When logging from video, the video time is used in the log (not the PC time). It is also possible to play back audio together with the video. FaceReader supports and has been tested with the following audio codecs: AAC, MP3, AC3, WMA. Multiple videos can be analyzed in one batch, without having to open every file separately. Analysis results of different videos are stored in separate files. The maximum advised duration for video analysis is 2 hours with 15 fps and 1 hour with 30 fps. Output FaceReader can generate two types of text files or Excel files, the first being a detailed log that contains all the emotional classifier outputs. If no information was available at a certain time, the log will show the text 'Missing', or in case no correct model could be built, 'FIT-FAILED' for each column in the record. Additionally, optional classifications, model quality, arousal and the emotional valence can be logged (selectable). It is also possible to log the X-, Y-, and Z-coordinates of all key points in the mesh in mm, or the X- and Y-coordinates of the 67 main ones in pixels. The main key points are the points around the mouth, nose, eyes, and eyebrows. The values of these coordinates are relative to the upper-left-corner of the image. The second file is the state log. This file contains the 'emotional state' a person is in, which is an emotional category shown clearly and with a significant duration. An update to the log file is only made when the state changes. The data is tab separated, making it easily importable in most spreadsheet programs or text editors. Combining FaceReader with The Observer XT FaceReader can also store data in an .odx format, for direct import into The Observer XT, the software package for collection, analysis, and presentation of observational data. The data can then be synchronized with event logs, keystrokes, mouse clicks, video, screen capture, physiological data, eye-tracking data, etc. The state logs are stored as an event file showing the dominant emotional state as behaviors. Facial states, gaze direction, valence, arousal, and head orientation are also included. The detailed log is entered as numerical modifiers in a second event log, showing the exact value of every expression per sample. - Voice Expression Intensity Bar Chart - Voice View - Voice Valence and Arousal Line Chart - Fixations - Saccades - Vital Signs - Heart Beat Chart - Breathing Rate - Consumption Behavior Statistics - Intake Events - Chewing - Chewing Motion - Live analysis using a webcam (via USB or IP camera) — In this case the sample rate is dependent on processing power and on image quality. Typical sampling rates will be 5–10 frames/sec. Live analysis is also possible using an IP-camera. The live image can be recorded in a DivX/MP4V format, allowing for more detailed frame-by-frame analysis afterwards in FaceReader or integration with other video and data modalities in The Observer® XT. It is possible to record audio together with the video signal. The maximum duration for camera analysis is 2 hours. - Still images — Use *.jpg, *.bmp, *.gif, *.png, or *.tga. Animated gifs are not supported - in this case the first frame of the animated gif will be used. Images and videos to be analyzed can be rotated 90°, 180°, or 270°. Visualization The subject's face can be visualized in different ways: - Show Framing — draws a box around the face at the location where the face was found. - Show Mesh — shows the positions of key points on the face and the head orientation. - Show Global Gaze Direction. - Show Classifications of Facial States. - Show Activated Action Units. - Zoom In on Face. These visualizations can also be shown simultaneously. Visualization of FaceReader analyses can also be displayed in a Reporting Display which enables the creation of a flexible layout with the output of the user's choice, including: - Analysis Visualization - Expression Intensity - Expression Summary - Valence Line Chart - Arousal Line Chart - Head Orientation Line Chart - Custom Expression Chart - Circumplex Model of Affect - Heart Rate - Valence Monitor - Emoticon - Expression Line Chart - Head Position Line Chart - Gaze Angles Line Chart - Voice Expression Line Chart Source: FaceReader 10 Technical Specifications, Noldus Information Technology --- ## FaceReader 10 - Create Exceptions In Windows Firewall For Stimulus Presentation Tool URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-create-exceptions-in-windows-firewall-for-stimulus-presentation-tool Chapter: FaceReader Computer Settings For A Two Computer Setup With Stimulus Presentation Tool Aim To allow communication between the computers through Windows FireWall and to synchronize the computers in order to synchronize the Stimuli and analysis. Prerequisite You use the Stimulus Presentation Tool on another computer than the one with FaceReader. Procedure You must carry out the following steps: - Create exceptions in Windows Firewall for Stimulus Presentation Tool - Synchronize computers with a network time protocol Create Exceptions In Windows Firewall For Stimulus Presentation Tool Aim To allow traffic in Windows FireWall for port 9090, or the port you choose if 9090 is not available. See Computer Configurations Prerequisite You use the Stimulus Presentation Tool on another computer than the one with FaceReader. Procedure - In the Windows' Search field, type firewall, and under the results click Windows Firewall. - Turn on the firewall for all networks, then click OK. - Click Advanced Settings. - On the left panel of the Windows Firewall and Advanced Security window, click Inbound Rules and on the right panel under Actions choose New Rule. - In the New Inbound Rule Wizard, on the Rule Type page, choose Port, then click Next>. - Select Specific local ports and enter 9090 (or the port chosen, if different), then click Next>. - On the Action page select Allow the connection, then click Next>. - On the Profile page choose the network the rule applies to, then click Next>. - On the Name page, enter a Name (for example Port9090). Then click Finish. - On the left panel of the Windows Firewall and Advanced Security window, click Outbound Rules and on the right panel under Actions choose New Rule. Repeat the procedure to complete the Outbound Rule. Make sure you choose the same options as for the Inbound Rule. - Repeat all steps above for the other PC. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Custom Expression Inputs In Detail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-custom-expression-inputs-in-detail Chapter: FaceReader Custom Expression Inputs In Detail You can choose one or more of the following building blocks: Facial Expressions The default facial expressions (Neutral, Happy, Sad, Angry, Surprised, Scared, Disgusted and Contempt). Please note that the default expressions are available as building blocks with Baby FaceReader but they do not generate an output as Baby FaceReader cannot detect the default facial expressions. - Click the facial expression building block you need and then click OK to add it to the grid. - Click the Edit button to select one of the three Smoothing options and choose whether the smoothed or raw values are used: - Based on analysis settings — FaceReader uses the option chosen in the Analysis Settings. See Classification in the Settings chapter. - Always smoothed — FaceReader uses smoothed data. - Always raw — FaceReader uses the raw, unsmoothed data. Derived Expressions Valence and Arousal Action Units The 20 Action Units that are available in FaceReader, unilateral Action Units (left and right) and combined. - Click the Action Unit building block you need and then click OK to add it to the grid. - Click the Edit button to select one of the three Smoothing options and choose if the smoothed or raw values are used. See Facial Expressions. - Set the Intensity threshold. If the intensity of the Action Unit is lower than this threshold, the Action Unit will not be taken into account. The output of the building block will be zero. Default value: 0.1 which is equal to the Not Active threshold (see Action Unit Intensity). Head Orientation Orientation of the head relative to the x, y and z-axis (Pitch, Yaw and Roll). Head Position Horizontal position, Vertical position and Depth position relative to the camera. Landmarks Landmark X, Landmark Y, Landmark Z (respectively, the horizontal, vertical and depth translation of the landmark relative to the camera) and Landmarks Distance (the distance between two landmarks relative to the camera in millimeters). - Click one of the four building blocks and then click OK to add it to the grid. - Click the Edit button to set the Landmark index and in case of Landmarks Distance also the Dimensionality (either 2D or 3D). Gaze Angles Horizontal gaze angle, Vertical gaze angle. Heart Rate Heart Rate, Heart Rate Variability (RMSSD) and Heart Rate Variability (SDNN). Tip: Click on one of the blocks to read the information that comes with it. Each block comes with a description and information on what values it can have as output. The Action Units also come with an example video in which the Action Unit is demonstrated. Voice Expressions Neutral from Voice, Happy from Voice, Sad from Voice and Angry from Voice. Voice Secondary Expressions Valence from Voice, Arousal from Voice, Loudness, Speech rate Miscellaneous Model quality — The model quality has a value between 0 and 1 and is represented by the Model quality bar in the analysis. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Custom Expression Processors in Detail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-custom-expression-processors-in-detail Chapter: FaceReader Custom Expression Processors in Detail To combine blocks you need processors. The following processors are available: Mathematical Processors - Maximum — This processor compares two (or more) numerical input values. The output is the highest value. For instance, when calculating Valence, FaceReader compares the intensities values of Angry, Sad, Scared and Disgusted. The highest value of the four is subtracted from the intensity of Happy. - Minimum — This processor compares two (or more) numerical input values. The output is the lowest value. - Sum — This processor calculates the sum of all its numerical input values. The screen shot below is part of the Custom Expression 'Interest'. The first step in the definition is to assess which of the Action Units 1, 2 or 12, has the highest value and sum this value and half of the intensity of Attention. - Average — This processor calculates the average of all its numerical input values. - Filtered Aggregate — With this processor FaceReader can, for instance, calculate the average of the three highest input elements. In the screen shot below FaceReader calculates the average intensity of the three Action Units with the highest intensity (1, 17 and 20). In this example this means calculating the average of 0.6; 0.5 and 0.4. The output value is 0.5. Click the pencil icon to edit the settings: - Selection: either Top or Bottom. - Number of elements: select how many inputs you want to take into account. - Aggregation operation: select whether you want to calculate the Average, Sum, Standard Deviation, Maximum, Minimum or Median of the input values. - Scale — This processor multiplies its numerical input value with the value you enter as a parameter. - Offset — This processor adds the value that you enter as a parameter to the numerical input value. - Subtract — With this processor FaceReader subtracts numerical input value B (bottom connector) from numerical input value A (top connector). The screenshot below is part of the definition of the Custom Expression 'Attention' in which the maximum of four input values is subtracted from the constant value 1. - Divide — With this processor FaceReader divides numerical input value A (top connector) by numerical input value B (bottom connector). - Multiply — With this processor FaceReader multiplies input value A (top connector) by input value B (bottom connector). - Scale to Range — Use this processor if you want the numerical input to fall within a new range. Enter the minimum and maximum values of the original range and the minimum and maximum value of the new range. The Custom Expression definition for 'Confusion' contains the 'Scale to range' processor in the screenshot below. In step x of the definition the output values can range from 0 to 4. With the 'Scale to range' processor, you scale the values from 0 to 1. - Power — With this processor the input value (0.2 in the example in the screenshot below) is raised to the power of n. In this example n=2 and the output is 0.04. - Exponent — This processor has two inputs (A and B). The Exponent block uses the formula: B to the power of A (0.3 to the power of 2 in the example below). If you connect the input blocks the other way around the result is 2 to the power of 0.3. - Logarithm — This processor takes the logarithm of the top input (A) with the bottom input (B) as base. The output is Log B(A) (logarithm of 2 to base 0.3 in the example below). If you connect the input blocks the other way around the result is logarithm of 0.3 to base 2. - Logistic — A Logistic block has one input, x. When you click the pencil button you can set the limit (L), the steepness (k) and the midpoint (x0). The output is L/(1+e^(-k(x-x0))). The Logistic processor is used in the custom expression 'Spontaneous laughter'. The S-shaped logistic function helps to promote high activation values and suppress low activation values. - Square Root — This processor takes the square root of the input value. - Absolute — This processor takes the absolute value of the input. You can, for instance, base your Custom Expression on the Valence and treat positive and negative values similarly. An input value of -0.6 (like in the screenshot below) results in an output of 0.6 and a Valence intensity of 0.6 also results in an output of 0.6. - Clip — This processor changes the input value into a value that fits in a range between a minimum and a maximum value. The example in the screenshot below shows part of the definition for Frowning. The input value (Sum = the sum of the intensities values of Action Unit 4 and 0.5 x Action Unit 7) is >1. The maximum set for the clip range is 1 so the output value is 1. Logical - Condition — This processor compares input value A (top connector) with input value B (bottom connector). It checks either whether A>B, A≥B, A'. As 0.13 is smaller than 0.7, the condition is False. - And — This processor has multiple Boolean values (True/False) as input and a single Boolean value as output. Use this processor, for instance if you want two or more conditions to be true for the Custom Expression to be active. The screenshot below is part of the definition of the Custom Expression 'Duchenne smile'. For a Duchenne smile (genuine smile) both Action Unit 6 and Action Unit 12 must be active. In this example, the definition is that both Action Units must have a value greater than 0.2. If Condition 1 (for Action Unit 6) AND condition 2 (for Action Unit 12) are true, there is a Duchenne smile. - Or — This processor has multiple Boolean values (True/False) as input and a single Boolean value as output. It compares two or more conditions with an OR logic. The screenshot below shows part of the definition of the Custom Expression 'Attention' (binary). The Or processor checks four conditions. If one of them is true, the output is True. If all four conditions are false, the output is False. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Data Export URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-data-export Chapter: FaceReader Data Export External Communication (API And Stimulus Presentation Tool) External communication is needed when you use the Stimulus Presentation Tool. Also, with FaceReader, an Application Programming Interface (API) is included. This API allows you to analyze images or videos with FaceReader on one computer and send the logged data to an application on another computer. Our support department (see Help desk for contact information) can supply you with a detailed description of how to use the API functionality. They can also give you an example of an application that can receive FaceReader data. Enable External Control (API) Select this option when you want to use the Stimulus Presentation Tool and when you want to use the API functionality. Default: Not selected. External Connection Port Specify the port through which the external application or the Stimulus Presentation Tool can connect to FaceReader. External applications can also receive the logged data through this port. Default: 9090. Please note that if you use The Observer XT 13 or higher versions with FaceReader 7 or higher, you do not use this setting, but connect with the Noldus network communication protocol N-Linx instead. See External Communication (N-Linx) Export With A Fixed Interval (5 Frames Per Second) If this option is selected, an update to the Detailed log will be made every 200 milliseconds. If your computer cannot process the incoming images fast enough, frames will be skipped and a record with MISSING will be added to the Detailed log. Default: Not selected. External Communication (N-Linx) N-Linx is a network communication protocol that enables data transfer between Noldus software. Use N-Linx if you have The Observer XT 13 or higher versions, and want FaceReader to start and stop analyzing together with an observation in The Observer XT. The FaceReader data are imported automatically into the observation and synchronized with the manual annotations. If you do not use N-Linx, or if you have an older version of The Observer XT, you must export the FaceReader data and import them into The Observer XT manually. Data import with N-Linx is easier and faster and ensures synchronization. For this functionality to work, your license for The Observer XT must include the External Data Module. Enable N-Linx Select this option to start and stop FaceReader analysis together with an observation in The Observer XT and to import the data automatically in the observation. N-Linx Server Address Enter the IP address, or full computer name, of the computer with N-Linx Server. If connection with N-Linx Server is established the text N-Linx connected appears in the upper right corner of your FaceReader window. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Data Selection - Filter Options URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-data-selection-filter-options Chapter: FaceReader Select Participants Aim To select which participants to include in your analysis. You can make a selection based on name, analysis number or the values of one or more independent variables. Prerequisites - Your project includes the Project Analysis Module. - Your project contains video or camera analyses. Procedure - Open the Project Analysis section. - Select what chart/table you want to create. - Under Filter your participants click Adjust Filter to make a selection based on: - Participant — Select the participants that you want to include in your analysis. - Analysis — Select the analyses that you want to include in your charts/table. For instance, select 'Analysis 2' if these are the analyses of test day 2 on which the respondents tested 'Ice cream 2'. Data Selection - Filter Options - Participant - Analysis — Select the participant/analysis combinations that you want to include in your charts/table. For instance, select the first three analyses of test participant 1-10 if these are the analyses of test day 1, 2 and 3 on which these participants tested razor blade X. - Age, Gender and Other Independent Variables — Age and gender are the independent variables that can be estimated by FaceReader, from the analyzed images. You can, for instance, first select all male respondents and make a bar chart of their facial expressions during Stimulus 1 and then select all female subjects and make a similar chart. You can also make a selection based on the independent variables that you defined yourself like socioeconomic status of the test participants or whether the participant had previous experience with the product under investigation. - Click Update to add the filter to your selection. In the lower left corner of the filter window the number of participants that match your filter are shown. Add Condition For numerical variables like age or number of years of experience with the product, you can add a condition and select, for instance, all the test participants older than 40. - Click Add to add the condition to the list of values to choose from. - Click Update to add the filter to your selection. Remove a Filter To remove a filter from your selection, click the button next to it. Change Your Selection Click Adjust Filter to open the window to filter your participants. The blue dots indicate what independent variables have been used to make a selection. Change your selection and click Update to add the new filter to your selection. Save Your Selection To save your selection criteria, click Save Filter and enter a name for your filter. Load an Existing Filter To open a filter that you have saved previously. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Default Analysis Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-default-analysis-settings Chapter: FaceReader Default Analysis Settings Active Face Model Face Model Choose the model that will be used by FaceReader for finding, modeling and classifying faces. Note that for a specific analysis you can use another model. If you have Baby FaceReader there is only one face model available ('Baby'). See Settings For The Current Analysis in Analyze Facial Expressions You can choose between the following models: - General (default) — This model has been trained on a very diverse selection of images. The model works well under most circumstances for most people. - Baby — Select this model if you work with babies or infants between the age of 6 months and 2 years. If you have a regular FaceReader license, the baby face model is not available. - EastAsian — Select this model to analyze East Asian faces, for instance, Chinese or Japanese faces. Calibration Continuous Calibration With this option selected, FaceReader continuously calibrates during an analysis. See Continuous Calibration in Analyze Facial Expressions Classification Smoothen Classifications With this option selected (default), classification values are transformed to obtain a smooth output signal. FaceReader smoothens the classification values taking the duration between frames into account. When there is a large time gap between frames, FaceReader will consider the facial expressions detected in those frames as less correlated then when there is a small time gap and thus adapts the strength of the smoothing. When this option is not selected, FaceReader gives the raw output data. If you are analyzing a set of images, this option has no effect. Rotation Image Rotation If you have images that are rotated, select one of the options from the drop-down list to make sure the faces are upright. - None (default). - 90º CW (clockwise). - 180º CW. - 270º CW. Video Sample Rate This option applies when you perform video analysis. By default, Every frame is selected. This means that all video frames are analyzed. To speed up the analysis, change the sample rate to analyze Every 2nd frame or Every 3rd frame. Under normal circumstances, analyzing 10–15 frames per second is sufficient for an accurate analysis. This means that if your video contains 30 frames per second or more, you can safely decrease the sample rate of FaceReader without loss of accuracy and make the analysis two to three times faster. For camera analysis — Video is sampled at 15 frames per second, also when your camera is set to a higher frame rate, and independent of what you choose under Sample rate. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Define A New Custom Expression URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-define-a-new-custom-expression Chapter: FaceReader Export A Custom Expression Definition Aim To save the Custom Expression to a FCX file and use it on another computer, give it to a colleague or send it to Noldus Support. Prerequisite You have the Action Unit Module or Baby FaceReader. Procedure Click the Export button to save your Project Custom Expression or Custom Expression under My Custom Expressions as a FCX file. Delete A Custom Expression Aim To clean up your project and remove the Custom Expressions that you will not use anymore. Prerequisite - You have the Action Unit Module or Baby FaceReader. - You can delete Project Custom Expressions and Custom Expressions under My Custom Expressions. It is not possible to delete the Custom Expressions under Remote Custom Expression Library. Procedure To Delete A Project Custom Expression Locate the Custom Expression in the Custom Expressions pane. Right-click on the expression and select Remove Custom Expression From Project. To Delete A Custom Expression In The List Under My Custom Expressions Locate the Custom Expression in the list under My Custom Expressions and click the Delete button. Define A New Custom Expression Aim To construct your own Custom Expression and use it to quantify its activation in the test participant's face. Prerequisite You have the Action Unit Module or Baby FaceReader. Procedure - From the File menu select Custom Expressions Browser or click the Add custom expression to project icon in the Custom Expressions pane. - Click New Custom Expression in the toolbar. The Custom Expression Information window opens. Enter a name and (optional) a description for the expression and choose a color. You can also enter the name of the author (optional). A new window opens with a grid with an Output block. - Click the Add block button on the toolbar to add the blocks that define your Custom Expression. The block browser opens with the Inputs, Processors and Custom Expressions that you can use. - Click on an Input, Processor or Custom Expression and then click OK to add it to the grid. - See Custom Expression inputs in detail - See Custom Expression processors in detail - Repeat step 2 and 3 to add more blocks to the grid. - Connect the blocks with connectors in such a way that you get the correct definition of the Custom Expression. Tip: You can check whether you defined your Custom Expression correctly by using the Input simulator. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Define A Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-define-a-test Chapter: FaceReader Carry Out A Test With The Stimulus Presentation Tool Aim To carry out a test with the Stimulus Presentation Tool so that the Stimuli are shown to the test participants and the test participant's face is analyzed. Prerequisites - Your FaceReader license includes the Project Analysis Module. - You installed the Stimulus Presentation Tool. See To install the Stimulus Presentation Tool - You have defined one or more Stimuli. See Define Stimuli - You have opened the FaceReader project that contains those Stimuli. - Optionally, the Advanced Research Module if you want to track the test participant's gaze. Procedure Carry out the following steps: - Define a test - Specify connection settings for the Stimulus Presentation tool - Run a test Define A Test Aim To define the Stimuli to show to the test participants and the order they should be presented. Prerequisites - Your FaceReader license includes the Project Analysis Module. - You have defined one or more Stimuli. See Define Stimuli - You have opened the FaceReader project that contains those Stimuli. Procedure - In FaceReader, choose Project > Tests > Add Test, or on the bottom-left pane, click the Test tab and click the Add Test button. - Give a Name to the test (default: Test 1, Test 2,…). - Select the Default camera you want to use. In the Select Camera window, choose the options that apply and click OK. - Add Stimuli. From the Select Stimuli list, select the first Stimulus video you want to add, and click the Add button. Repeat this step for the next Stimulus. - The Stimuli appear under Stimuli Order. - Specify the independent variables for the test. Under Independent Variable Usage, click an independent variable and choose how you want to determine the value for a participant. - Automatic (only for Gender and Age) — FaceReader enters the values automatically for each participant, based on the analysis. - Entered by Participant — The participant is asked to enter the value of this variable at the start of the test. Instead of asking a participant to fill in a value for an independent variable, you can ask him/her any type of question. When defining the independent variable/question you must define either a Numerical or Nominal value/answers. In a consumer test you can ask, for instance, what the participant had for breakfast and define the following Nominal answers: cereal, bread, pancakes, hot meal and coffee only. A variable/question can have a maximum number of 50 characters. - Leave blank — To leave the value blank and edit it later. - [value or category] — Specify one of the values available; note that the value you specify here will be assigned to all analyses and participants who take part in that test. Use this option for example to compare data between tests which differ by that variable. - Under Options, choose the additional options that apply: - Stimulus display size - Default value is 60%. Change the value to 100% to display the stimulus full-screen. - Minimum pause between stimuli - Define the length of the pause between stimuli (in hours:minutes:seconds.milliseconds). The default value is 3 seconds. Please note that the pause can be longer than the value you set if FaceReader needs more time to load the stimulus. - Randomize stimulus order to present the Stimuli in a random order. - Perform gaze calibration — This enables FaceReader to track the gaze of the test participant. - Let Participants enter their name at the start of the test. - Click OK. Notes - Video formats accepted by FaceReader: QuickTime (mov), MP4, VOB (from camcorders), H.264 DivX, MPEG-4 DivX, MPEG-1, MPEG-2, DV-AVI. - Once the Stimuli are listed under Stimuli Order, you cannot change their order. To put them in a specific order, delete the Stimuli and re-add them in that order. - To add Stimuli that are not in the list, close the Add New Test window, then add the Stimuli you need (see Define Stimuli), then on the bottom-left pane click the Test tab and double-click the test to the re-open the test window, and complete step 4. - To add independent variables, close the Add New Test window, then add the independent variables (see Define Independent Variables). Next, on the bottom-left pane click the Test tab and double-click the test to the re-open the test window, and complete step 6. - To delete a Stimulus from the test, under Stimuli Order click the Delete button for that Stimulus. - To edit an existing test, double-click the test name on the bottom-left pane (Test tab). - To delete a test, on the bottom-left pane (Test tab) right-click the test name and select Delete Test. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Define Event Markers URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-define-event-markers Chapter: FaceReader Offset And Lag Offset is the estimated difference in time between the clocks that cumulated up to the time of the update. This is the accuracy of synchronization of the Stimulus Presentation Tool with FaceReader. A positive value means that the FaceReader PC clock is faster than the test PC. Lag (also known as delay) is the traveling time of time packets from the client to the server and from the server back to the client. The shorter this lag, the more accurate the estimate of the offset between clocks. - You are now ready to start the test with the Stimulus Presentation Tool. See Run A Test Notes - After clicking Update Now, always make sure that on the Network Time window the Status cell for the FaceReader PC says Good. - To change the order of the servers in the NetTime Options window, copy and paste the name of one cell to the other. - Click Update Now every time you start a test to keep the time offset between FaceReader and Stimulus Presentation Tool as low as possible. - For more information: - https://en.wikipedia.org/wiki/Network_Time_Protocol - http://www.timesynctool.com Event Markers Event markers are used to indicate that, for instance, the participant was distracted or was trying food product A. With Event markers, you can mark the parts of the analyses you are especially interested in and that were not defined as Stimuli beforehand. In contrast to Stimuli, Event markers have no fixed duration. In FaceReader you can compare the analyses over these time periods with other data. Main Topics - Define Event Markers - Score Event Markers Define Event Markers Aim To specify the markers and their associated key codes. Prerequisite Your FaceReader license includes the Project Analysis Module. Procedure - Choose Project > Event Marker and then Add Event Marker. - In the Name field, enter the Event marker name, for instance, Food product A. - Click the button on the right of the Trigger Key field and enter the key for this marker. This is the key on your keyboard that you press when the event (In this example Test participant takes food product A) starts. - Select a color for the marker and click OK. This color will be used throughout the program for the Event marker. Notes To delete or edit an Event marker: - Open the Event Markers tab at the bottom of the Project Explorer. - Right-click the Event marker you want to delete or edit and select the option you require. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Define Project Wizard Manually URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-define-project-wizard-manually Chapter: FaceReader Project Wizard Why A Project Wizard? If you know before you create your project how many participants and analyses per participant your project will contain, you can automate adding them. Also use the project wizard if you created many videos, or images and stored them in a structured way. For example, you created a folder per participant and each participant folder contains a number of folders and subfolders that contain the videos or images to analyze. You can use this folder and file structure to make a template and create the participants and analyses automatically. With a project wizard template it is also possible to read the age and gender from the file names and enter these values as independent variables for the participants. See Video And Image Formats which file formats can be used with the project wizard. See: - Define Project Wizard Manually - Define Project Wizard With The Folder Structure Of The Video Or Image Files Define Project Wizard Manually Aim To automate adding a large number of participants or analyses. You define how analyses are organized in the Project Explorer. To assign videos to analyses automatically, follow the topic Define Project Wizard With The Folder Structure Of The Video Or Image Files instead. Prerequisite You have a large number of participants, or analyses. Procedure - Choose File > New > Project Wizard. - Give the project a name, select the location to store it, and select whether you want to carry out video, camera or image analysis from the Source type list. - Select Manual. - Select the No. of participants and the No. of Analyses per participant. - If you have chosen Camera as Source type, also select the camera under Default camera. The Project Preview on the right displays the project structure. - Click OK. - Open each analysis to browse to the video, or image, or select the camera and carry out analysis. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Define Stimuli URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-define-stimuli Chapter: FaceReader Stimuli and the Stimulus Presentation Tool Main Topics - Define Stimuli - Score Stimuli - The Stimulus Presentation Tool - Carry Out a Test with the Stimulus Presentation Tool - Define a Test - Specify Connection Settings for the Stimulus Presentation Tool - Run a Test - Computer Settings for a Two Computer Setup with Stimulus Presentation Tool - Create Exceptions in Windows Firewall for Stimulus Presentation Tool - Synchronize Computers with a Network Time Protocol Define Stimuli Aim To define the Stimuli to show to test participants and, to score them manually, the associated key codes. Prerequisites - Your FaceReader license includes the Project Analysis Module. - You have Stimuli with a fixed duration, for example video fragments. Procedure - Choose Project > Stimulus > Add Stimulus or click the Add Stimulus button on the bottom-left pane. - In the window that opens, enter the Stimulus name, for instance, 'Commercial 1'. - Under Trigger Key, enter a keyboard key for this Stimulus. If you score the Stimuli manually, press this key when the Stimulus (commercial 1 in this example) starts. - Under Color, optionally change the color for the Stimulus and click OK. This color will be used throughout the program for this Stimulus. - Select to present either a video, or an image as Stimulus, or no external Stimulus. If Your Stimulus Is a Video - Select the video, for instance, the video with the six commercials which your test participants will watch. - Enter the Start Time in video (in hours:minutes:seconds with two decimals). In our example this is the start time of Commercial 1. If this commercial starts half a minute after the start of the video, enter 00:00:30.00. Leave 00:00:00.00 if the video starts with this Stimulus. - Enter the Duration (in hours:minutes:seconds.milliseconds). In our example this is the duration of Commercial 1. If the entire video file is a Stimulus, do not edit Duration. If Your Stimulus Is an Image - Select the image, for example a screen capture of a web page, or a wrapping of a chocolate bar. - Enter the Duration (in hours:minutes:stimulusseconds.milliseconds). If Your Stimulus Is Not a Video or Image To score an event manually, for example a Stimulus by an external program other than the Stimulus Presentation Tool, or a phase in a test: - Select No Media. - Enter the Duration (in hours:minutes.seconds.milliseconds). Note To delete or edit a Stimulus, open the Stimuli tab at the bottom of the Project Explorer. Right-click the Stimulus you want to delete or edit, and select the option you require. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Detailed Log URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-detailed-log Chapter: FaceReader Detailed Log The Detailed log contains all the expression classifier outputs and the other data you selected for export. Each expression has a value between 0 and 1, indicating the intensity of the expression. '0' means that the expression is not visible, '1' means that it is fully present. You can export the Detailed logs as text files with the data separated by tabs or as Excel files. When no face is found or the face cannot be modeled (e.g. because the quality of the video is poor), a record with FIND_FAILED or FIT_FAILED is added. If you work live (using a camera) and your computer cannot process the incoming images fast enough, frames will be skipped and a record with MISSING will be added to the Detailed log. NOTE To change the word 'Unknown' in the State log, see Export (Detailed log and API) in Settings. NOTE If you want to use other criteria to define a state, for example when the intensity of an emotion is above 0.5, export the detailed log. Then calculate the states in another program, like Excel. NOTE To change the words FIND_FAILED, FIT_FAILED, or Unknown in the Detailed log, see Export (Detailed log and API) in Settings. If you analyze a video file and skip frames (that is, you set the Sample rate to Every 2nd frame or Every 3rd frame), the logging frequency changes accordingly. For the Detailed log you have the following options: - Adjust the export sample rate – To create a log file with a lower sample rate than the FaceReader analysis. You can choose a value between 1 and 15 frames per second. FaceReader interpolates the analysis results if the chosen sample rate results in interpolated timestamps. You can also choose to adjust the export sample rate to a value between 1 and 60 frames per minute. Note that this is averaging the results towards the new time base, centered at the time logged. So if you log 1 frame per minute, the result at the 1st minute will be the average of 0:00:30.000 to 0:01:30.000. - Include file header – To include the following information as header in the export file: - Face Model - Calibration – calibration name and calibration values (the average intensity values of Neutral, Happy, Sad, etc. that are found during the calibration, that is, Ic in the formula used to calculate the corrected expression intensities. See How participant calibration works). - Start date and time - Video filename - Analysis frame rate - Independent variables - Include column header – To include column details in the export file. Note If you analyzed from video and your video was not recorded with exactly the frame rate you selected, for example 29.9 fps instead of 30 fps, the timestamps may be slightly different from what you may have expected. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Edit A Custom Expression URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-edit-a-custom-expression Chapter: FaceReader Copy A Custom Expression Aim To edit the Custom Expression and use it in your project. Prerequisite - You have the Action Unit Module or Baby FaceReader. - Your FaceReader computer has a connection to the internet to access the Remote Custom Expression Library. Procedure Click the Copy to my custom expressions button to copy your Project Custom Expressions or custom expressions from your Remote Custom Expression Library to My Custom Expressions. Import A Custom Expression Aim To use a Custom Expression made on another computer. Prerequisite - You have the Action Unit Module or Baby FaceReader. - You have received a Custom Expression (*.FCX) file or you have exported a Custom Expression definition (see Export a Custom Expression definition). Procedure Click the Import custom expression button on the toolbar and browse to the location where you stored your Custom Expression (*.FCX file). Select it and then click Open. The new Custom Expression is added to My Custom Expressions. Edit A Custom Expression Aim To change the Custom Expression definition before using it in your analyses. Prerequisite - You have the Action Unit Module or Baby FaceReader. - You can edit either Project Custom Expressions or Custom Expressions under My Custom Expressions. It is not possible to edit Custom Expressions from the Remote Custom Expression Library. To use a Custom Expression from the Remote Custom Expression Library in your project, you can either add it to your project or copy it to the list under My Custom Expressions (and then edit it and add it to your project). Procedure Editing Project Custom Expressions - Locate the Custom Expression under Project Custom Expressions and click the Edit custom expression button. The detailed view of the Custom Expression opens and you can now add blocks, edit the existing ones or edit the processors. - Right-click the Custom Expression in the Custom Expressions pane and select Select/Adjust Project Custom Expressions. Locate the Custom Expression under Project Custom Expressions and click the Edit custom expression button (see above). Editing My Custom Expressions Locate the Custom Expression in the list under My Custom expressions and click the Edit custom expression icon. The detailed view of the Custom Expression opens and you can now add blocks, edit the existing ones or edit the processors. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - End-User License Agreement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-end-user-license-agreement Chapter: FaceReader End-User License Agreement IMPORTANT – READ CAREFULLY. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading or using the Software (as defined below). By checking the "accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions in this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions Terms used in this EULA but not otherwise defined shall have the meaning assigned to them below: 1.1. Authorized Partner: the individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. 1.2. End-User: the individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. 1.3. EULA: this End-User License Agreement. 1.4. Indirect Losses: any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. 1.5. Network License: a licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. 1.6. Noldus: Noldus Information Technology BV, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries listed in the document https://www.noldus.com/legal/noldus_corporate.pdf 1.7. Security System: a system of software protection to limit installation and use of the Software to the authorized End-Users and computers. 1.8. Security Device: a device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. 1.9. Software: the software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Export (Detailed Log And API) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-export-detailed-log-and-api Chapter: FaceReader Export (Detailed Log And API) Consumption Behavior Statistics This option is only available if your FaceReader license includes the Consumption Behavior Module. Select this option to add the variables Intake count and Chew motion count to the Detailed log. Gaze Fixation Index And Location This option is only available if your FaceReader license includes the Advanced Research Module. Select this option to add three columns to the Detailed log file: Gaze Location X, Gaze Location Y and Fixation Index. Gaze Location X and Gaze Location Y are the x,y coordinates of the test participant's gaze point on the screen. The X,Y-coordinates are in pixels relative to the upper left corner of the screen. The Fixation Index is the total number of fixations up until that point in time. 2D Landmarks With this option selected the X-Y-coordinates of the dots around the eyes, nose and mouth of the mesh are added to the log file. The log file has 134 numbers in the column Landmarks. The first two numbers are the X- and Y-coordinates of landmark 0, the third and fourth are the coordinates of landmark 1 etc. The following landmarks are present in the detailed log: - 0-9 – left eyebrow - 10-19 – right eyebrow - 20-21 – corners left eye - 22-23 – corners right eye - 24-26 – nose - 27-66 – mouth The X,Y-coordinates are in pixels relative to the upper left corner of the image. Please contact Technical Support if you want to know the position of the landmark points in the face. They can send you a photo of a face with the 67 landmark point positions. They can also provide you with a photo of all the 468 landmark point positions in the face. See Show Mesh in FaceReader's output Log Complete Set Of 3D Landmarks Select this option if you want to include the X,Y, Z coordinates of all the (468) landmark points in the Detailed log. Please note that the 3D landmarks are not in pixels but in millimeters relative to the camera. To project the 3D landmark points on the camera or video images you need the camera matrix: C = fx, 0, cx 0, fy, cy 0, 0, 1 if w = image width in pixels h = image height in pixels then: fx = 1.2 * Max(w,h) fy = 1.2 * Max(w,h) cx = w/2 cy = h/2 Then each 3D world coordinate (xw, yw, zw) can be projected to an image coordinate (xm, ym) by: xm = (xw * fx)/zw + cx ym = (yw * fy)/zw + cy Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Export (Detailed Log, ODX, N-Linx And API) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-export-detailed-log-odx-n-linx-and-api Chapter: FaceReader Export (Detailed Log, ODX, N-Linx And API) By default, the detailed export file contains the classification output values for the six basic emotions, and the neutral state. Contempt is added if you selected it as optional classification in the Analysis options tab. Select one of the options below to add extra information to the log file. IMPORTANT Please note that if your observations are long, writing a lot of extra information to the log can make your log files very large and can make the analysis slower. Action Units This option is only available if your FaceReader license includes the Action Unit Module. With this option selected, extra columns with the Action Units are added to the log file. Values are between A (trace) and E (max). This option is only available when you have the Action Unit Module. See Action Units in the log files in The Action Unit Module Export Action Units As Continuous Values With this option selected, the Action Unit categories A-E are exported as numerical values between 0 and 1. See Action Units in the log files in The Action Unit Module With this option selected, the Action Unit intensities can be imported into The Observer XT as external data. See Import the detailed logs as external data in FaceReader with The Observer XT Export The Unilateral Action Unit Intensities If you select this option, the Detailed log file will have three columns for each unilateral Action Unit, one for the intensity of the Action Unit on the right side of the face, one for the left side and one combined which is the maximum of the left and right values. Consumption Behavior This option is only available if your FaceReader license includes the Consumption Behavior Module. With this option selected, FaceReader adds three columns to the Detailed log file, 'Intake event', 'Chewing' and 'Chew motion' with for each analyzed frame 'Yes' or 'No' to indicate whether the behavior was active or not. Custom Expressions This option is only available if your FaceReader license includes the Action Unit Module. Selecting this option, adds a column to the Detailed log file for each custom expression showing its intensity for each analyzed frame. Facial States With this option selected, 5 extra columns are added to the Detailed log: Mouth (open or closed), Left-Eye (open or closed), Right-Eye (open or closed), Left-Eyebrow (raised, neutral or lowered) and Right-Eyebrow (raised, neutral or lowered). See Facial States in FaceReader's output Gaze Data With this option selected, two extra columns are added to the Detailed log: Gaze Direction and Gaze Type. The gaze direction can either be Left, Left-Up, Left-Down, Right, Right-Up, Right-Down, Up, Down and Forward. The gaze type is either Fixation, Saccade or Unknown. This option is only available if Gaze tracking is selected in the Analysis Options. Gaze Angles With this option selected two extra columns are added to the Detailed log: Horizontal gaze angle and Vertical gaze angle. The horizontal and vertical gaze angles are 0 degrees when the test participant looks straight ahead. Head Orientation With this option selected, three extra columns are added to the Detailed log: Pitch, Yaw and Roll (in degrees). See Reporting Display in FaceReader's output Head Position With this option selected three extra columns are added to the Detailed log: Horizontal position, Vertical position and Depth position with the head position angles in millimeters relative to the camera. Vital Signs This option is only available if your FaceReader license includes the Vital Signs Module. With this option selected, eight extra columns (Heart Rate, Heart Rate Variability (RMSSD), Heart Rate Variability (SDNN), Heart Rate Warnings, Heart rate confidence, Breathing Rate, Breathing Rate Warnings and Breathing rate confidence) are added to the Detailed log. The Heart Rate Warnings and Breathing Rate Warnings columns may contain the following warnings: - FIND_FAILED/FIT_FAILED — If no face is found or the face cannot be modeled (e.g. because the quality of the video is poor) - MISSING — If you work live (using a camera) and your computer cannot process the incoming images fast enough, frames will be skipped - Framerate, bitrate, resolution ratio too low — If your camera settings deviate from the recommended settings. See The Vital Signs Module for more information about the recommended settings for heart rate, heart rate variability, and breathing rate measurement. The Heart rate confidence values and Breathing rate confidence values are values between 0 and 1, indicating the quality of the heart rate/breathing rate measurements. Valence And Arousal If you select this option the valence and arousal are added to the log file. See Valence and Arousal Line Chart and in FaceReader's output. Expressions From Voice This option is only available if your FaceReader license includes the Voice Analysis Module. With this option selected seven extra columns are added to the Detailed log: Neutral from Voice, Happy from Voice, Sad from Voice, Angry from Voice, Valence from Voice, Arousal from Voice, Loudness and Speech rate. Voice Analysis in the Analysis Options must be enabled. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Export Analysis Results URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-export-analysis-results Chapter: FaceReader Export Analysis Results Aim To save your analysis results as text file, Excel file or The Observer XT format file (.odx) for further analysis in another program. Prerequisites - You carried out analyses. - The values of all independent variables have been scored for all participants. Analyses of participants with unscored independent variables cannot be exported. This is indicated with a warning icon in front of the participant name. Score the independent variable values for those participants. Procedure Exporting analysis results consists of the following steps: - Choose what to export - Export the data Choose What To Export - Choose File > Settings > Data Export. - Under Export (Detailed log, ODX, N-Linx and API) choose the data to export. Export The Data - Choose File > Export > and choose one of the following: Export Analysis Results — To export the results of the analysis currently open. Export Participant Analysis Results — To export the results of all analyses related to the participant currently selected. Export Project Results — To export the results of the entire project. - Browse to the location on your computer where you want to store your log files and click OK. The default location is: C:\Users\\Documents\Noldus\FaceReader 10\Projects\\Logs. - If you chose Export Analysis Result in step 1, give the export file a name. A suffix with the export type, like detailed or state, will be added to the export name. If you chose Export Participant Analysis Result or Export Project Result, the export files are named automatically. - Choose one of the following: - Export to text files or Excel files — There are four options to select from: - Text files (tab delimited) - 1 file per participant/analysis - Excel files - 1 file per participant/analysis - Combined Excel files (one sheet per analysis) - 1 file, analyses on sheets - Combined Excel files (all analyses in one sheet) - 1 file, all data on 1 sheet - Export to The Observer XT (.odx) Export To Text Files Or Excel Files Choose to export the State log, Detailed log or Heart beat log. The Heart beat log option is available if you have the Vital Signs Module. For more information see Export Heart Beat Log. State Log The State log shows the expression state the test person displays (see the figure below for an example). A record is added to the log each time the dominant expression changes and is active for at least 0.5 seconds. If no face is found or the face cannot be modeled, for instance because the quality of the video is poor, a record with Unknown is added to the State log. You can export State logs as text files with the data separated by tabs or as Excel files. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Export Consumption Behavior Events URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-export-consumption-behavior-events Chapter: FaceReader Export Consumption Behavior Events Aim To export the Consumption Behavior events (Intake event, Chewing, Chew motion) to a text file, Excel file or The Observer XT format file. Prerequisites - Your FaceReader license includes the Consumption Behavior Module. - Consumption Behavior analysis is switched on in the Settings. See Analyze Consumption Behavior Procedure - Choose File > Settings and then click the Data Export tab. - Under Export (Detailed log, ODX, N-Linx and API), select Consumption behavior. If you like, you can export the Consumption behavior events together with the Consumption behavior statistics (Intake count and Chew motion count) in one log file. In that case under Export (Detailed log and API), also select Consumption behavior statistics. See Export Consumption Behavior statistics. - Choose File > Export and select one of the three options. See Export the data in FaceReader's output - Choose the folder in which to save your log files and click Select Folder. - From the Log type drop-down list select the format of your log files, either Excel format or text. - Select Save detailed log or Save The Observer XT log if you want to open your log files in The Observer XT. Then click OK. The log files contain three columns (in addition to the columns with the intensities of the facial expressions) with the Consumption behavior events ('Intake event', 'Chew motion' and 'Chewing') and for each exported sample 'Yes' or 'No' to indicate whether the behavior was active or not. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Export Consumption Behavior Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-export-consumption-behavior-statistics Chapter: FaceReader Export Consumption Behavior Statistics Aim To export the Consumption Behavior statistics (Intake count and Chew motion count) to a text file or Excel file. Prerequisites - Your FaceReader license includes the Consumption Behavior Module. - Consumption Behavior analysis is switched on in the Settings. See Analyze Consumption Behavior Procedure - Choose File > Settings and then click the Data Export tab. - Under Export (Detailed log and API), select Consumption behavior statistics. If you like, you can export the Consumption behavior statistics together with the Consumption behavior events (Intake event, Chewing and Chew motion) in one log file. In that case under Export (Detailed log, ODX, N-Linx and API) also select Consumption behavior. See Export Consumption Behavior events. - Choose File > Export and select one of the three options. See Export the data in FaceReader's output - Choose the folder in which to save your log files and click Select Folder. - From the Log type drop-down list select the format of your log files, either Excel format or text. Choose Text files if you want to import the log files into The Observer XT. - Select Save detailed log and click OK. The log files contain two columns (in addition to the columns with the intensities of the facial expressions) with the Consumption behavior statistics ('Intake count' and 'Chew motion count') with for each analyzed frame the total number of intake/chew motion events up until that point in time. Consumption Behavior Data in The Observer XT Consumption Behavior Events If you send FaceReader data to The Observer XT 13 or higher versions using the N-Linx network communication protocol or export the Consumption behavior events as *.odx data and import them into The Observer, they are imported as event log data. A new behavioral group (Consumption Behavior) is added to the coding scheme. Consumption Behavior Statistics You can also import the Consumption behavior statistics into The Observer XT, either automatically using the N-Linx protocol or manually by importing your Detailed log files as external data. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Export Heart Beat Log URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-export-heart-beat-log Chapter: FaceReader Heart Beat Chart The Heart Beat Chart shows the heart beats on a time line. It gives you an impression of the heart rate variability. Heart rate and heart rate variability are subject to Post-processing. The heart rate peaks have a different color before and after post-processing. To View The Heart Beat Chart Click the Select window button in one of the visualization windows and select Vital Signs > Heart Beat Chart. Export Heart Rate, Heart Rate Variability And Breathing Rate Data Aim To export the heart rate, heart rate variability and breathing rate data of your test participants to an Excel file or a text file to view them outside FaceReader or to import them into The Observer XT. Prerequisites - You have the Vital Signs Module. - You selected Vital Signs analysis and export in the Settings. - You carried out an analysis. Procedure - Choose File > Export and select one of the three options. See Export the Data in FaceReader's Output - Browse to the folder in which you want to save the export files and click Select. - From the Log type drop-down list select the format of your log files, either Excel format or text. Choose Text files if you want to import the log files into The Observer XT. - Select Save detailed log and click OK. Export Heart Beat Log Aim To export the inter-beat interval data (the time intervals between individual heart beats). Prerequisites - Your FaceReader license includes the Vital Signs Module. - Vital signs analysis and export is switched on in the Settings. See Analyze Vital Signs - You ran a video or camera analysis. Procedure - From the File menu select Export and select one of the three available options. - Select the folder in which you want to save the log file. - Select Save heart beat log. See Export Analysis Results in FaceReader's Output. Vital Signs Data In The Observer XT If you send FaceReader data to The Observer XT 13 or higher versions using the N-Linx network communication protocol, Vital Signs data are imported as external data. You can also manually import Vital Signs data. To be able to import Vital Signs data as external data you need the External Data Module of The Observer. See FaceReader with The Observer XT Please note that the data in the screen shot below come from a project in which the Heart rate variability period was set to one minute (the default is five minutes). Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Export Voice Analysis Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-export-voice-analysis-data Chapter: FaceReader Export Voice Analysis Data Aim To export the expressions detected in your test participant's voice to a text file or The Observer XT format file. Prerequisites - You have the Voice Analysis Module. - You carried out an analysis. Procedure - Choose File > Settings and then click the Data Export tab. - Under Export (Detailed log, ODX, N-Linx and API), select Expressions from voice and then click OK. - Choose File > Export and select one of the options. See Export the data in FaceReader's output The export file contains columns for each expression (Neutral from Voice, Happy from Voice, Sad from Voice and Angry from Voice), as well as for Valence (Valence from Voice), Arousal (Arousal from Voice), Loudness and Speech rate. Each expression has a value between 0 and 1, indicating the intensity of the expression. '0' means that the expression is not detected in the voice, '1' means that it is maximally present. Arousal from Voice, Loudness and Speech rate also have a value between 0 and 1. Valence from Voice has a value between +1 and -1. For more information see Voice Valence and Arousal Line Chart and Voice View. The first milliseconds of the log file have 'Unknown' as value. This is due to the audio buffer which is used to collect approximately one second of data before starting the analysis. Voice Expression Data In The Observer XT If you send FaceReader data to The Observer XT 13 or higher versions using the N-Linx network communication protocol, Voice expression data are imported as external data. You can also manually import Voice expression data. To be able to import Voice expression data as external data you need the External Data Module of The Observer. See FaceReader with The Observer XT Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Expression Intensity Chart URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-expression-intensity-chart Chapter: FaceReader Circumplex Model Of Affect The Circumplex Model of Affect describes emotions in a two-dimensional circular space, containing arousal on the vertical axis and valence on the horizontal axis. The center of the circle represents a neutral valence and a medium level of arousal. The Circumplex Model of Affect in FaceReader is based on the model described by Russel (1980). Options The following additional options can be selected with the Options button on the toolbar: Show Current Position Shows a circle around the affect, with the color of the current expression state. Show History If you carried out video analysis or camera analysis, the affect found in previous images is shown when playing back the analysis. Show Expression Label Shows the expression state found in the image selected in the Analysis View window. This option is not available with Baby FaceReader. Show Heatmap This option is only available for camera and video analyses. It displays a heatmap of the affect found in the analysis. - Based on absolute percentage – The color of the heatmap is based on the percentage of time a certain affect was found in a video or camera analysis. The maximum is 100%. - Based on maximum percentage – The color of the heatmap is based on the percentage of time the affect that was most present occurred. This percentage of time is set as the maximum and is colored red. References Russell, James (1980). A circumplex model of affect. Journal of Personality and Social Psychology 39: 1161–1178. http://en.wikipedia.org/wiki/Emotion_classification#Circumplex_model Expression Intensity Chart This option is not available with Baby FaceReader. To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Expression Intensity. Expression Intensity The Expression Intensity chart displays the intensity of the six basic emotions, the neutral state and, optionally, Contempt. When your input is a live video stream or a video file, you will see the bars change over time, reflecting the changes in expressions on the face. The Expression Intensity chart displays the following states: Neutral, Happy, Sad, Angry, Surprised, Scared, Disgusted, and Contempt. See Expression states explained when dominant expressions appear in the Timeline and State log. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - FaceReader In Combination With The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-facereader-in-combination-with-the-observer-xt Chapter: FaceReader FaceReader With The Observer XT Main Topics - FaceReader in combination with The Observer XT - Control FaceReader with The Observer XT using N-Linx - Import FaceReader videos only - Import multiple FaceReader analyses into the same observation - How FaceReader data are imported into The Observer XT - Visualize FaceReader data in The Observer XT - The Observer XT sample projects with FaceReader data FaceReader In Combination With The Observer XT Integrating FaceReader data with other data may give you a more complete picture of the phenomena that you are studying. For instance, when testing your newly developed website, it may be interesting to know what emotions it evokes, but it may be even more intriguing to see at what part of the web site your test person is looking when his facial expressions are classified as 'happy' or 'surprised'. Manually logging the test person's verbal reactions or measuring his physiological responses makes the picture complete. For the integration of all these data, you can use The Observer XT. You can let FaceReader record a video of the test participant's face and import FaceReader's log files together with the video into The Observer XT. You can then visualize the test person's facial expressions together with your observational data and calculate statistics. The procedure for co-acquiring and importing FaceReader data depends on whether you observe live or offline. If you observe live, the procedure depends on the version of The Observer XT. IMPORTANT Make sure that FaceReader elements that are imported into The Observer XT do not already exist in the Coding Scheme of The Observer XT. Otherwise the FaceReader data will be assigned to the element that was already present in the Coding Scheme and your Observer data will be incorrect. Please be especially aware to not use the element names Unknown, or Neutral in the Coding Scheme of The Observer XT, since these names are used for the facial expressions. Which Option Applies To You? - Observe live in The Observer XT with the External Data Module - Observe live in The Observer without the External Data Module - Observe offline in The Observer XT Observe Live In The Observer XT With The External Data Module The Observer XT 13.0 and higher versions make use of the Noldus network communication protocol N-Linx to control FaceReader. For details on N-Linx, see the Reference Manual - N-Linx. You can download it from the download section of the Noldus website. To use this functionality, you need the External Data Module (EDM) of The Observer XT. For the detailed procedure, see Control FaceReader with The Observer XT using N-Linx. Observe Live In The Observer Without The External Data Module If you do not have The External Data Module (EDM), you can set up The Observer XT to start and stop FaceReader analysis together with an observation. See Add a Custom External Device in The Observer XT Help for the procedure. Observe Offline In The Observer XT When you carry out offline observations in The Observer XT, you start and stop FaceReader analysis manually. Also you must export the data from FaceReader and import them together with the videos into The Observer XT manually. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Facial States URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-facial-states Chapter: FaceReader Expression Line Chart This option is not available with Baby FaceReader. To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Expression Line Chart. Expression Line Chart The Expression Line Chart displays facial expressions over time. Each expression is plotted in a different color. When you play back the video, a hairline shows the time in the video. Expressions From the Expressions list choose the emotions you want to view. Expression Summary This option is not available with Baby FaceReader. To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Expression Summary. Expression Summary The chart shows the distribution of facial expressions for the complete analysis. If you analyzed multiple intervals in one video all the intervals are taken into account in the Expression Summary chart. Options Click Settings and select Show Values to view the subdivision of emotions in percentages. What Does Other Mean? Expressions that make up less than 5% of the sum of all expression intensities are included in the category Other. The example below shows part of the detailed log of an analysis. For each expression, the total intensity is calculated. Angry, Surprised, Scared and Disgusted each have a total intensity of less than 5% of the sum of all intensities. The sum of these four expressions is displayed as Other in the Expression summary. Facial States To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Facial States. Facial States The Facial States table gives a dynamic overview of the following states: - Gaze Direction (Left, Left-Up, Left-Down, Forward, Up, Down or Right, Right-Up, Right-Down) (only available if you selected Gaze tracking in the Settings > Analysis Options). - Gaze Type (Fixation or Saccade) (only available if you selected Gaze tracking in the Settings > Analysis Options). - Mouth (open or closed) - Eyes (open or closed) - Eyebrows (raised, neutral or lowered) Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - File Name URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-file-name Chapter: FaceReader Export to The Observer XT (.odx) The Observer log contains the analysis results, in XML format. Select this output format if you want to import your data for further analysis in The Observer XT, our software package for collecting observational data. You have the following options: - Include detailed values – To save both the Detailed log as the State log in the export file. Choose this option if your license for The Observer XT does not include the External Data Module. The Detailed log data will be imported as numerical modifiers. If you have the External Data Module, select Save Detailed log. The Detailed log data will then be imported as external (continuous) data into The Observer XT. See How FaceReader data are imported into The Observer XT. - Save all analyses to a single The Observer XT log – This option is available when you export the results of a participant, or an entire project. This option allows you to import all analyses results at once into The Observer XT. The different participants and analyses are imported into separate observations. Since FaceReader export files can be very large, we recommend to create a FaceReader export file for each analysis and import them one by one in The Observer XT. Each observation in The Observer XT contains the name of the imported participant and analysis. File Name The default name for the export log files is: [Participant number]_[Participant name]_[Analysis name]_[Analysis type]_YYYYMMDD_hhmmss_[Export file type] Where: - [Participant number] is the number given automatically (Participant 1, 2 etc.) - [Participant name] is the name entered under Name when adding that participant - [Analysis name] the name of the selected analysis - [Analysis type] specifies whether an image, video, or camera analysis has been carried out. - YYYYMMDD_hhmmss is the date/time code of the start of the analysis. - YYYY = year including the century. - MM = month with leading zero. - DD = day with leading zero. - hh = hours, 12-hour format with leading zero. - mm = minutes with leading zero. - ss = seconds with leading zero. Note If you want to import the detailed log as external data into The Observer XT, export the detailed log as text file and select the options Include file header and Include column header. Otherwise the import profile FaceReader 10 detailed log as external data does not work. If you have additional modules and selected additional data when you exported the Detailed log data (like Action Units or Expressions from voice) you need to make a new import profile. See External Data in The Observer XT Help how to do so, or contact Noldus Support. See also: - Export to text files or Excel files - Import the detailed logs as external data in FaceReader with The Observer XT Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - General Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-general-settings Chapter: FaceReader Settings Settings In Detail These topics list the settings that you can make in FaceReader. Each topic refers to one tab in the Settings window. See also Choose Settings To Access Settings For All Future Analyses Choose File > Settings. Choose the option you require. These settings will be used for all new analyses, including the one currently open if that has not been analyzed yet. For many options, additional information is available as tool tips, as shown in the figure below. The settings you specify this way apply to all future analyses. To Reset To Default Click the Reset to Default button to undo the changes you made in the settings and go back to the default settings. Notes - Clicking Reset to Default resets all tabs to the default settings, not only the tab that is currently open. - Clicking Reset to Default will make General the default face model. If you are in the middle of a project in which you used another face model, make sure that you re-select the face model you used. This way you do not mix data obtained with different face models. General Settings In the General settings you can view your license info and select the default location where FaceReader saves its projects. License Your License Number Shows the license number of the hardware key currently plugged in or the license number connected to your software activation key. This license determines the software modules that you can use. See also: - Modules in Introduction - FaceReader Trial Version in Installation Project Explorer Open Analysis On Creation The analysis immediately opens once it is created. Default: selected. Show Participant Preview Image If enabled you will see a preview image of each participant by hovering over the video icon in the Participant Explorer. Default: selected. Project Information Custom Expression Folder The default folder where newly-defined and imported custom expressions are saved. Click the button next to it to select another location. Default: C:\Users\\Documents\Noldus\FaceReader 10 9\Custom Expressions. Default Project Folder The default location where the projects are stored. Click the button next to it to select another location. Default: C:\Users\\Documents\Noldus\FaceReader 10 9\Projects. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Guidelines For An Optimal Vital Signs Measurement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-guidelines-for-an-optimal-vital-signs-measurement Chapter: FaceReader Guidelines For An Optimal Vital Signs Measurement Lighting Make sure that lighting is diffuse. Indirect natural light is preferable, otherwise artificial diffused lighting can also be used. Lighting is preferably from a frontal direction and there are no strong shadows on the face. Strong specular reflection (e.g., bright white spots on the forehead) should be avoided. See also Camera and accessories Subject Requirements - Distance between camera and subject: 0.5 - 1 m. - Ensure that the subject's full forehead/upper part of the face is clearly visible for reliable RPPG measurements. Since RPPG primarily depends on the analysis of the upper region of the face, it must be well exposed to the camera, and not occluded by hair, a hat, etc. - For reliable breathing rate measurements it is crucial that the test participant's shoulders are visible in the camera view/video. Excessive movement of e.g., arms in front of the chest will reset the calibration and should be avoided. If chest motions are very shallow or if there is no breathing detected, a warning will be shown in the Vital Signs window informing you that FaceReader "failed to model body pose". Camera Settings Remote PPG is intended to work with the cameras supported for FaceReader (see Camera and accessories). Do note that for Remote PPG the following cameras are unsuitable due to internal video processing: Logitech Brio, Microsoft Lifecam. Below you find recommended settings: - In general, videos should be recorded with the minimum amount of compression (e.g., ideal settings are: the YUY2 stream encoded with HUFFYUV, FFV1, MJPEG (lossless/low compression ratio), H264/H265 (lossless/low compression ratio)). If your camera offers different video formats, choose the format that gives the highest file size, (for example, .avi). - Frame rate: at least 15 fps; preferred 30 fps. Make sure FaceReader analyzes each frame. See Video in Settings. - Face size: at least 100 x 100 pixels, for example: - In a 1280 x 720 video, the face should cover 8-14% of the frame dimensions - In a 800 x 448 video, the face should cover 12-20% of the frame dimensions - Note that most cameras will only allow lossless/low compression recording at a lower resolution such as 800 x 448. - Bits per pixel ratio: at least 0.15 bits/pixel, preferred 1 bit/pixel. The BitsPerPixel ratio is calculated as follows: [BitsPerPixel] = [BitRate] / ([FrameRate] * [TotalPixels]) For example, a video recorded at 30 fps with a resolution of 640 x 480 pixels should have a bit rate of at least 1.382 Mbit/second (preferred 9.216 Mbit/second). You can find the frame rate, resolution and bit rate of your video when you right-click the video filename in Windows Explorer and select Properties. You can find the information on the Details tab. - The following camera capture settings are optimal for accurate Remote PPG measurement: - Saturation: High - Contrast: High Do note that adjusting these settings to extreme values can result in the image being distorted which may cause FaceReader to not find the face. Therefore, these settings should be adjusted such that the face appearance remains proper. These camera settings allow for the best possible heart rate detection. These settings might impact the visual quality of the video, but will lead to a more accurate heart rate estimation. - For optimal remote PPG measurements the camera should be able to capture a frontal view of the subject's face throughout the session. The accuracy of the measurement is related with the head pose. Frontal head pose is recommended where abrupt head pose changes can degrade the optimal performance. Ensure that the camera is roughly at eye level. Recording Video With MediaRecorder To ensure video recording with enough detail for remote PPG, MediaRecorder 6 (Noldus' video recording tool) has a setting. In the Output settings window, choose 'FaceReader-RPPG' from the list. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Head Position Line Chart URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-head-position-line-chart Chapter: FaceReader Note If the table shows Disabled behind all the states and you want to view the Facial States, choose File > Settings. On the tab Analysis Options, under Optional Classifications select Facial States. Gaze Angles Line Chart To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Gaze Angles Line Chart. The Gaze Angles Line Chart is only available if you selected Gaze tracking in the Settings > Analysis Options. Gaze Angles Line Chart The Gaze Angles Line Chart displays the Horizontal and Vertical gaze angle over time (in degrees). When you play back the video, a hairline shows the time in the video. Click Gaze Angles to select what gaze angle you want to view over time (Horizontal gaze angle and/or Vertical gaze angle). Head Orientation Line Chart To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Head Orientation Line Chart. Head Orientation Line Chart The Head Orientation Line Chart displays the head orientation as the Pitch, Yaw and Roll over time. It is displayed in degrees deviating from looking straight forward. When you play back the video, a hairline shows the time in the video. Head Orientations Click Head Orientation to select whether you want to view the Pitch, Yaw or Roll. Head Position Line Chart To Access This Option Click the Select window button in one of the visualization windows, select Face, and then Head Position Line Chart. Head Position Line Chart The Head Position Line Chart displays the head position relative to the camera over time (Horizontal, Vertical and Depth position, in millimeters). When you play back the video, a hairline shows the time in the video. FaceReader's face model is defined in millimeters. By a projection of the 3D model to the 2D image FaceReader can derive where in real world coordinates the face is in the 2D image (and an estimated camera projection matrix). FaceReader's 3D coordinates are centered around the camera, the camera is at (0,0,0). Therefore, the 3D coordinates of the fitted model will tell you where the face is relative to the camera. Head Positions Click Head Position to select what head position you want to view over time (Horizontal position, Vertical position and/or Depth position). Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - How Does FaceReader Work? URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-how-does-facereader-work Chapter: FaceReader How Does FaceReader Work? FaceReader classifies facial expressions in several steps which is explained in the figure below. Please see [1] - [3] and the references mentioned in the text below for more information. FaceReader 10 uses new methods that are different from the ones used in previous versions of the software. We recommend using the same FaceReader version within one project. - Face finding — The position of the face in an image is found using a deep learning based face finding algorithm [1], which searches for areas in the image having the appearance of a face. - Face modeling — FaceReader uses a facial modeling technique based on deep neural networks [2]. It synthesizes an artificial face model, which describes the location of almost 500 key points in the face. The predicted key points of such a model are learned from a database of annotated images. It is a single pass quick method to directly estimate the full collection of landmarks in the face. After the initial estimation, the key points are compressed using Principal Component Analysis. This leads to a highly compressed vector representation describing the state of the face. - Facial expression classification — Classification of the facial expressions is done by a trained deep artificial neural network to recognize patterns in the face [3]. FaceReader directly classifies the facial expressions from image pixels. Over 100,000 images of people faces from all over the world, that were manually annotated, were used to train the artificial neural network. The network was trained to classify the six basic or universal emotions described by Ekman [4]: happy, sad, angry, surprised, scared, disgusted and a neutral state. Additionally, the network was trained to classify the set of facial Action Units available in FaceReader, as well as to estimate other facial attributes such as age, gender, and the presence of glasses. The diagram above illustrates the FaceReader processing pipeline: Input image → Face finding → Face image → Face modeling (2A) → Face model → Deep neural network (2B) → Face classification → Final output (3). Validation Facial expression analysis of FaceReader 10 is validated using the Amsterdam Dynamic Facial Expression Set (ADFES) [5] and the Warsaw Set of Emotional Facial Expression Pictures (WSEFEP) [6], wherein expressions are manually scored by FACS certified annotators. In addition, relevant validation was also performed on other datasets including Baby FACS manual dataset [7] and Taiwanese Facial Expression Image Database (TFEID) [8]. - For facial expression classification on ADFES and WSEFEP FaceReader 10 has an accuracy of 98.7% and 97.2%, respectively. For FaceReader 9 these values were 99.3% and 95.7%, resp. That means that facial expression estimation under ideal conditions is improved in FaceReader 10. For Action Unit classification on ADFES and WSEFEP FaceReader 10 has an F1 score* of 0.83 and 0.80, resp. For FaceReader 9 these values were ~0.78 and ~0.76, resp. That means that facial expression estimation under ideal conditions is improved in FaceReader 10. - For Action Unit estimation using the baby model, FaceReader 10 has an F1 score of 0.69 on the Baby FACS Manual dataset [7]. FaceReader 9 also had a score of 0.63. This means that the baby model in FaceReader 10 performs even better on baby faces compared to FaceReader 9. - The East Asian model on average performed approximately 10% better on Asian faces of our internal test data set (1200 East Asian faces) than the General model. The East Asian model and General model had an accuracy of 93% and 91%, resp. when the Taiwanese Facial Expression Image Database (TFEID, 268 images, [7]) was tested. - Gender classification in FaceReader 10 achieves and accuracy of 94% on an internal test set. - The detection of (eye) glasses on faces achieves an accuracy of 99.2% on an internal test set. * The F1 score is the weighted average of precision and recall. This score takes both false positives and false negatives into account. References - Zafeiriou, S.; Zhang, C.; Zhang, Z. (2015) A survey on face detection in the wild: Past, present and future. Computer Vision and Image Understanding, 138: 1-24. - Bulat, A.; Tzimiropoulos, G. (2017) How far are we from solving the 2D & 3D face alignment problem? (and a dataset of 230,000 3D facial landmarks). Proceedings of the IEEE International Conference on Computer Vision, pp. 1021-1030. - Gudi, A.; Tasli, H.E.; den Uyl, T.M.; Maroulis, A. (2015) Deep learning based FACS action unit occurrence and intensity estimation. International Conference and Workshops on automatic face and gesture recognition (FG), 6: 1-5. - P. Ekman. Universal facial expressions of emotion. California Mental Health Research Digest, 8: 151-158, 1970. - Van der Schalk, J., Hawk, S. T., Fischer, A. H., & Doosje, B. J. (2011). Moving faces, looking places: The Amsterdam Dynamic Facial Expressions Set (ADFES), Emotion, 11, 907-920. DOI: 10.1037/a0023853 - Olszanowski, M.; Pochwatko, G.; Kuklinski, K.; Scibor-Rylski, M.; Lewinski, P.; Ohme, R.K. (2014) Warsaw Set of Emotional Facial Expression Pictures: A validation study of facial display photographs. Frontiers in Psychology 5, DOI: 10.3389/fpsyg.2014.01516. - Oster, H. (2016). Baby FACS: Facial Action Coding System for infants and young children. Unpublished monograph and coding manual. New York University. - Chen, L.F.; Yen, Y.S. (2007) Taiwanese facial expression image database. Ph.D. dissertation, Brain Mapping Lab, Inst. Brain Sci., Nat. Yang-Ming Univ., Taipei, Taiwan. To cite the use of FaceReader in publications you can use the following reference: Noldus (2021). FaceReader: Tool for automatic analysis of facial expressions: Version 10 [Software]. Wageningen, The Netherlands: Noldus Information Technology B.V. It is important to include the version number of the software in the reference since FaceReader's algorithms are improved with every upgrade. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - How FaceReader Data Are Imported Into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-how-facereader-data-are-imported-into-the-observer-xt Chapter: FaceReader How FaceReader Data Are Imported Into The Observer XT See Visualize FaceReader data in The Observer XT for a full overview of how FaceReader data appear in The Observer XT. Event Data FaceReader event data are imported into The Observer XT as separate event logs within the observations. This is the case for the following FaceReader data: - State Expression Values - Facial States - Stimuli - Event markers - Action Units (with the Action Unit Module, if you exported them to an odx file) - Consumption Behavior events (Intake event, Chewing and Chew motion, with the Consumption Behavior Module) - Gaze direction Continuous Data Continuous data are imported into The Observer XT at a sample rate of 5 frames per second. Your license for The Observer XT must include the External Data Module. The following data can be imported as continuous data: - Facial expression intensity values. - Valence. - Arousal. - Head orientation (Pitch, Yaw, Roll). - Head position (Horizontal, Vertical and Depth position). - Gaze angle (Vertical and Horizontal gaze angle). - Action Units (with the Action Unit Module, if you selected 'Export action units as continuous values' in the Settings and exported them in a Detailed log file). - Heart rate, heart rate variability, and respiratory (breathing) rate (if your FaceReader license includes the Vital Signs Module). - Custom Expressions (if your FaceReader license includes the Action Unit Module). - Expressions from voice (including Valence from voice, Arousal from voice, Loudness and Speech rate, with the Voice Analysis Module). Note: See Set up FaceReader to work with The Observer XT how to select the data to export from FaceReader and to import in The Observer XT. Independent Variables The FaceReader independent variables Age, Gender and ParticipantID are imported into The Observer XT together with the FaceReader data. The values for Age and Gender are estimated by FaceReader and the ParticipantID is the participant number automatically assigned by FaceReader. If the independent variables are not present yet in The Observer XT, they will be added to the Independent Variables list. If you created them as User defined variables in the Independent Variables list of The Observer XT (with the exact variable names as mentioned above) and no values are filled in yet before observation start, the FaceReader values are imported into the list after the end of the observation. If you already entered values in The Observer XT before observation start, these values are maintained. FaceReader does not overwrite the Independent Variable values in The Observer XT. To enter the independent variable values in The Observer XT instead of importing the FaceReader values, create user defined independent variables Age, Gender and ParticipantID in The Observer XT. Make sure the names match exactly. Choose to enter the independent variables before starting the observation (Choose Setup > Project Settings > Observation Settings and choose Before Observation from the Edit Independent Variables list). To import FaceReader independent variable values in the Independent Variables list of The Observer XT, the variable name must exactly match the FaceReader variable name. FaceReader contains by default the independent variables Age, Gender and ParticipantID. If you, for example, have an Independent Variable age in The Observer XT (lower case a instead of upper case), or Participant ID (with a space), a new Independent Variable Age or ParticipantID will be added to the Independent Variables list when you import the FaceReader data. Notes Duplicate Elements IMPORTANT Elements that are imported as events into The Observer should not already exist in the Coding Scheme of The Observer XT with the exact same name. As an example, you may have a mutually exclusive behavior group that contains the behavior Neutral, or Unknown. If you import FaceReader emotional expressions into The Observer XT, the expressions Neutral, or Unknown will then be scored for the behavior group that was already present in the Coding Scheme and will not be present in the imported event log State Expression Values. Therefore both the event log with the manual annotations and the event log State Expression Values will be incorrect. Sample Rate FaceReader data are imported into The Observer XT with a sample rate of 5 frames per second. This is to limit the amount of data that is transferred to The Observer XT. FaceReader itself samples with the camera frame rate and converts the data to a sample rate of 15 frames per second after the analysis is finished. Therefore, the data in The Observer XT may differ slightly from the analysis results in FaceReader. See Camera frame rate and samples in FaceReader in Set up your project Vital Signs If your FaceReader license includes the Vital Signs Module, FaceReader can estimate the test participants' heart rate, heart rate variability, and respiratory (breathing) rate. These data can be imported real-time in The Observer XT. In FaceReader, the first 15 seconds of the analysis is used for calibration and the heart rate and breathing rate data are post-processed after the analysis is finished. The Observer XT imports the heart rate and breathing rate data real-time. Therefore, the heart rate and breathing rate data of the first ten seconds that are imported into The Observer XT contain data that are not yet calibrated. The data that are imported are not post-processed and will differ from the FaceReader data. Since post-processing is used to re-calculate the data, based on the calibration, the data in FaceReader itself are more reliable. Whereas for heart rate the first 8.5 seconds of an analysis are post-processed after the analysis is finished, for breathing rate this is 15 seconds and for heart rate variability this is the first 5 minutes (or even longer). See Vital Signs Module Event Log Duration - There will be a slight delay between the moment you start an observation in The Observer XT and the moment FaceReader starts analyzing. Since the end of all event logs is determined by the end of the observation, the FaceReader event log will have a shorter duration than The Observer XT event log in the analysis. This is caused by the offset between the event logs. - The observation in The Observer XT ends when you click the stop observation button. However, the FaceReader analysis will stop when you click the stop observation button. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Import Multiple FaceReader Analyses Into The Same Observation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-import-multiple-facereader-analyses-into-the-same-observation Chapter: FaceReader Import FaceReader Videos Only Aim To import the videos of the test participants' faces into the observation in The Observer XT after you carried out the analysis. Prerequisite One of the following is true: - You observe offline in The Observer XT. - You control FaceReader with The Observer XT 14.0 or lower. - You do not import FaceReader analyses as .odx files manually. When you import the .odx output of FaceReader analyses into The Observer XT, the FaceReader videos are also imported, so you can skip this topic. Procedure - Open your observation in The Observer XT. - Click the Import video button on the toolbar. - Select your video file and click OK. - Synchronize the video file with the observation and imported FaceReader data. See Carry out an observation/Synchronize data sets in The Observer XT Help. Import Multiple FaceReader Analyses Into The Same Observation Aim To import analyses of different test participants from the same experiment into the same observation of The Observer XT. You are, for example, interested in the interaction between a doctor and a patient. You want to import the analysis results of both the doctor and the patient into the same observation in The Observer XT. Prerequisites - You are interested in the interaction between two or more test participants. For example, a doctor and a patient, a teacher and a pupil, or a parent and a child. You want to import their analyses together into the same observation of The Observer XT. - You exported the FaceReader data as .odx files. See Export analysis results Procedure To be able to import multiple analyses into the same observation of The Observer XT, the exported FaceReader data must be converted. Conversion adds a Subject to the data. Conversion is done with the Subject labeler. To Install The Subject Labeler - Download the installation file from the Drivers & Tools section of the MyNoldus portal (my.noldus.com). - Double-click the file Subject Labeler Setup.exe. - Choose Standard as installation type and choose Next. - Accept the terms in the End-user license agreement and click Install. To Convert The Export Files - Open the Subject Labeler. - Browse to the folder that contains the FaceReader export files. The .odx files found in this folder are listed in the ODX files field. The Subject column shows whether a Subject is present in the export file or not. - Select the files to add the first Subject to. For example, the analyses of the doctors. - In the Subject name field, enter a name to add as Subject to the files, for example Doctor. - Click Label. This adds the Subject name to the .odx file and the file name. - Repeat all steps for the other Subject, for example the analyses of the Patients. To Import The Converted File Into The Observer XT - Open the observation. - Click the Import data button on the toolbar and choose Import Observational Data. - Browse to the converted file and select it. Then click Open. - If the question appears Do you want to import new coding scheme elements, click Yes, import new coding scheme elements. - A message appears that import is successful. Click Close. Notes - If an ODX file contains Subjects, it cannot be converted. FaceReader export files do not contain Subjects. However, The Observer XT export files may have Subjects. - After conversion, the file appears in the ODX files field of the ODX converter. The Status column shows that this file contains a Subject and cannot be converted anymore. - Importing multiple analyses into the same observation adds each FaceReader independent variable as a separate variable to the Independent Variables list of The Observer XT. Although the coding scheme contains Subjects, the independent variables have scope Observation. - See Set up your project/ Create Coding Scheme/ Subjects in The Observer XT Help for more information on Subjects. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Import The FaceReader Data And Videos Into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-import-the-facereader-data-and-videos-into-the-observer-xt Chapter: FaceReader Offline Observations Aim To manually import FaceReader data and videos into The Observer XT. Procedure Carry out the following steps - Export FaceReader log files - Import the FaceReader data and videos into The Observer XT - Synchronize data sets. See Carry out an observation/Synchronize data sets in The Observer XT Help. Export FaceReader Log Files In FaceReader, choose File > Export > [one of the options], to export the data for a single analysis, single participant, or entire project. Under Export to text files (.txt) choose Save Detailed log. The Detailed log file contains the intensities of the facial expressions per sample and other data that you have selected under Settings > Data Export. Important Select Include file header and Include column headers. If you do not select both check boxes, import into The Observer XT fails. Under Export to The Observer XT (.odx), choose Save The Observer XT log. Do not select the Include detailed values checkbox. Select Save all analyses to single The Observer XT log to export one log file with the data of all the participants in the project. The Observer XT log file lists the dominant facial expressions during the tests. See also Export analysis results in FaceReader's output. Then: - Import the FaceReader data and videos into The Observer XT Import The FaceReader Data And Videos Into The Observer XT Procedure Carry out the following steps: - Import the Observer XT log files plus videos into The Observer XT - Import the detailed logs as external data Import The Observer XT Log Files Plus Videos Into The Observer XT - Start The Observer XT, open the appropriate project or create a new one. Choose File > Import > Observational Data. - In the Files of type field, select The Observer XT (*.odx) from the list. - Browse to your Observer log file and open it. The log files are by default in the folder: C:\Users\\Documents\Noldus\FaceReader 10\Projects\[project name]\Logs. This imports the FaceReader analysis together with the video of the test participant's face. Import The Detailed Logs As External Data To import FaceReader data as external data, your license for The Observer XT must include the External Data Module. To see if you have this module, open The Observer XT and choose Help > About The Observer XT > License info. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Import Your FaceReader Online Project into FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-import-your-facereader-online-project-into-facereader Chapter: FaceReader FaceReader in Combination with FaceReader Online Main Topics - What is FaceReader Online? - Import your FaceReader Online project into FaceReader - Create a FaceReader Online trial account What Is FaceReader Online? FaceReader Online is our facial expression analysis service that runs online on a cloud server and does not need any on-site installation. This means that you can test appreciation or impact on-site while participants can stay at home, allowing you to incorporate a much larger number of participants and saving them the effort of coming to the lab at the same time. If you like, you can define questions in FaceReader Online or integrate FaceReader Online into your own survey software, such as Qualtrics. You can view a screen recording with the test participant's gaze overlay in FaceReader Online's Recording Results. You can import data from your FaceReader Online projects directly into FaceReader and analyze the data using all the analysis functions that are available in FaceReader. Import Your FaceReader Online Project into FaceReader - Use one of the following two options: - In the FaceReader Start window click Import project or - From the File menu select Import FaceReader Online Project. - Sign in to your FaceReader Online account. A webpage on the FaceReader Online website opens showing an overview of all your Active, Completed and Closed projects. - The status of your FaceReader Online projects is either: - Not Yet Created: you do not have a project file yet. - New Results Available: invitees participated in your FaceReader Online test after you created the previous project file. The data of these participants are not in the project file yet. - Up To Date: your project file contains the data of all the subjects who participated in your test sofar. - Click the Generate project file icon to create a project file or add new results or recordings to your existing project file. - Select whether you want to include recordings in your project file and click Generate. The project file status changes to Generating and you can follow the progress of the file generation. When the project file is ready, the project file status will change to Up To Date. - Click the Import project file icon. - Select where you want to save your FaceReader project. Optionally, enter a new name for your project and click OK. You are now ready to: - Open the analyses, view the data per test participant and make charts — See FaceReader's output. If you selected to show your participants' recordings when you created the FaceReader Online project and you included your recordings when you imported the project in FaceReader, you can visualize the test participant's face next to the Stimulus View and, for instance, the participant's Expression Intensity chart. See Stimulus View in FaceReader's output for more information. If you selected to Include gaze tracking when you defined your FaceReader Online experiment, the Stimulus View window shows the participant's gaze overlay. - Export the data of each participant in a State log or Detailed log file — See FaceReader's output. - If you selected to include your recordings when you imported the project — Re-analyze the videos, for instance, to select the EastAsian face model instead of the General model or to calibrate and then run a new analysis. - In the Project Analysis section — Visualize your data in charts and calculate statistics over all participants or per participant group (for instance, male and female participants or different age groups). Create a FaceReader Online Trial Account If you are new to FaceReader Online and want to try it out you can create a trial account. In the FaceReader Start window select Create account under FaceReader Online and follow the steps on your screen. Click Learn more in the Start window to open the FaceReader Online page on the Noldus website. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Important Concepts in Project Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-important-concepts-in-project-analysis Chapter: FaceReader Important Concepts in Project Analysis Independent Variables Independent Variables Independent Variables are factors that remain constant throughout an analysis, but can vary per participant. By default, each project contains the independent variables Age and Gender of the participant. These can be estimated by FaceReader, from the analyzed images. Alternatively, you can enter the values of these variables manually. You can define more independent variables. Examples of independent variables are the native language of the test participant, or whether the participant has previous experience with the product under investigation. Independent variables can be used to compare participant groups. See Independent Variables Stimuli and Event Markers You can mark episodes that you are especially interested in. This can be, for example, a time fragment during which the test participant watches a certain commercial. Or it can be the time a participant is allowed to drink or eat a certain product you are interested in. Stimuli Use Stimuli to mark the parts of the analyses you are especially interested in. Stimuli are, for instance, the new commercials the test participants will watch or the pages of your newly developed website they will view. These time fragments have a fixed duration. You can use a video fragment as Stimulus source, for example a video with the commercial. You can score a Stimulus manually during or after carrying out the analysis. But if you use The Stimulus Presentation Tool, any Stimulus included in the test is automatically recorded by FaceReader, so you do not need to score it manually. See Stimuli and the Stimulus Presentation Tool You can analyze the facial expressions over the time the Stimulus occurred and visualize the test participants face together with the Stimulus video. If you have the Action Unit Module you can also analyze Action Units and Custom Expressions. If you have the Vital Signs Module you can analyze heart rate, heart rate variability, and breathing rate. Event Markers With Event markers you can mark time fragments in the analysis, just like with Stimuli. In contrast to Stimuli, Event markers have no fixed duration and are not linked to a video. With Event markers you can, for example, mark episodes where something unexpected occurs, like a visitor entering the room, or mark events that have no fixed duration, like drinking a fruit juice. You score an Event marker manually and score it again, or score another one to set the stop time of the marker. See Event Markers Stimuli and Event Markers in The Observer XT Stimuli and Event markers can be exported into the detailed log. If you use FaceReader together with the annotation software The Observer XT, the Stimuli and events are imported into The Observer XT as state events. These can then be used to select the time fragments for further analysis. See FaceReader with The Observer XT The Stimulus Presentation Tool With the Stimulus Presentation Tool you can automatically present Stimuli to test participants. You do not have to score Stimuli manually. You can organize the Stimuli in Tests (see below). The Stimuli and analysis are automatically synchronized. See The Stimulus Presentation Tool Tests In a test you define which Stimuli to present to test participants and in which order. Tests are carried out with the Stimulus Presentation Tool. When you carry out a test, a participant and analysis is automatically added to the project. The Stimulus Presentation Tool displays the Stimuli during the test while FaceReader records and/or analyzes the participant's face. See Define a Test Calibration Versus Baseline Correction Instead of participant calibration, or continuous calibration, you can define a Neutral stimulus. Score this Stimulus when the test participant watches a neutral set of images or a neutral video fragment. In the analysis, calculate the facial expressions during the experimental Stimulus relative to the facial expressions during the neutral Stimulus. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Importing FaceReader Detailed Log Files Into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-importing-facereader-detailed-log-files-into-the-observer-xt Chapter: FaceReader Importing FaceReader Detailed Log Files Into The Observer XT On the FaceReader > Drivers & Tools section of our MyNoldus portal (my.noldus.com) you will find an import profile to import Detailed log files. Follow the steps below to copy the import profile to your computer: - Make sure The Observer XT is not running. - Download the Import Profile from the MyNoldus portal. - Copy the import profile FaceReader 10 Detailed log as external data.eip to the default directory for import profiles: C:\ProgramData\Noldus\Common\Profiles. The ProgramData folder is a hidden folder. To view this folder, browse to C:\ and from the View drop-down list select Show and then Hidden items. You are now ready to import your log files into The Observer XT. To do so: - Choose File > Import > External Data. - In the Files of type field, select FaceReader 10 Detailed log as external data (*.txt) from the drop-down list. - Browse to the location on your computer where you stored your log file. The default location is: C:\Users\\Documents\Noldus\FaceReader 10\Projects\[project name]\Logs. - Select the observation into which you want to import the log file. - If a message appears that missing values are found, choose Import and Ignore > OK. - Select the appropriate log file and click Open. The data are imported into The Observer XT. If you have additional modules and selected additional data when you exported the Detailed log data (like Action Units or Expressions from voice), you need to make a new import profile. See External Data in The Observer XT Help how to do so, or contact Noldus Support. What's Next Synchronize the data sets. See Carry out an observation/Synchronize data sets in The Observer XT Help. Notes - IMPORTANT Importing FaceReader data adds FaceReader elements to the coding scheme. However, these elements cannot be scored in a new observation in The Observer XT. Make sure the FaceReader elements do not already exist in the coding scheme of The Observer XT. - If you only import FaceReader data as external data into The Observer XT, the videos are not imported. Continue with Import FaceReader videos only. - If you import FaceReader data as .odx file into The Observer XT, the FaceReader independent variables and videos are also imported. - If you import the detailed logs as external data, they are imported as continuous values. - You can calculate statistics like, e.g., the mean and maximum classification value for each of the facial expressions in The Observer XT. For more information see Calculate Statistics in The Observer XT Help. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Independent Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-independent-variables Chapter: FaceReader Score Event Markers Aim To mark episodes other than the time Stimuli were presented. Prerequisites - Your FaceReader license includes the Project Analysis Module. - You have a video or camera analysis. - You defined Event markers. Procedure To Score During An Analysis - Press the trigger key that is associated with your Event marker. If you have the Timeline window open, a bar appears in the line Event markers. - Press the same trigger key to stop the Event, or press another key to start another event. To Score After An Analysis - Open the Timeline Window and scroll the video to the position where the event starts. - Press the Event marker trigger key. A question appears whether you want to score the Event marker at that point. Choose Yes. - Scroll the video to the position where the Event marker should stop. - Press the same trigger key to stop the event, or press another key to stop the event and start another event. Notes - Scored Event markers appear as dots below the analysis in the project explorer. - To edit a scored Event marker, unfold the analysis and double-click Scored Event Markers. In the window that opens, edit the markers by dragging them to the correct position. - To copy a scored Event marker to other participants or analyses, unfold the analysis and double-click Scored Event Markers. Click the Event marker you want to copy. Click Scored Event Markers at the top of the window, and choose one of the options under Copy To. Independent Variables Independent variables are factors that can vary but are constant per participant and can, potentially, affect the analysis results. Examples are the nationality of the participant, or the previous experience with a product or commercial. Independent Variables can be used to compare participant groups, for example to compare groups of males and females, or to make groups with and without previous experience with the product. By default, each project contains the independent variables Age and Gender of the participant. These cannot be deleted. Their values can be estimated by FaceReader, from the analyzed images. Alternatively, you can enter the values manually. Independent Variables must be scored for each participant. Participants for which one or more Independent Variables have not been scored are left out of the analysis. Main Topics - Define Independent Variables - Score Independent Variables Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Install FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-install-facereader Chapter: FaceReader Select Correct Power Options In Windows 10 Aim To make sure the computer shuts down properly. This step is needed for Windows 10 computers only. Background Information On computers with Windows 10, by default the computer resumes rather than restarts after shutdown. This can cause problems with FaceReader and associated software like MediaRecorder, and The Observer XT. Therefore, we recommend to make sure that the computer really shuts down. Procedure - Click the Windows icon on your desktop or keyboard and type Control Panel. Then click Power options. - Click Choose what the power buttons do. - Click Change settings that are currently unavailable. - Select the following options (both for On battery and Plugged in): - When I press the power button – Shut down. - When I close the lid – Shut down. - Under Shutdown settings deselect the checkboxes Sleep, Hibernate, and Turn on fast startup (recommended). Install FaceReader IMPORTANT If your FaceReader license comes with a hardware key, first install FaceReader and then connect the hardware key to your computer, not the other way around. Procedure - Download the installation file (FaceReader 10 Setup.exe) from the MyNoldus portal of the Noldus website (my.noldus.com). If you do not have a MyNoldus account yet, you can create one. - Double-click the file. If a security message appears, click Run. - We recommend to choose Standard as Installation type. Choose Custom if you want to change the folder into which FaceReader is installed, or if you do not want shortcuts on the desktop to the program and the FaceReader Help. - Click Next, read the End-User License Agreement carefully, Select I agree, and click Install and then Yes. The installation of FaceReader starts. - When the installation of FaceReader is finished, a message appears informing you that installation is complete. Click Launch to start FaceReader, or Close to exit. Notes - IMPORTANT Projects saved in FaceReader 10 cannot be opened in earlier versions anymore. - FaceReader is installed in C:\Program Files\Noldus\FaceReader 10\ - You can install FaceReader 10 next to older versions of FaceReader but we advise to not combine data from projects made in different versions. - A number of sample images and video files is installed in C:\Users\Public\Public Documents\Noldus\FaceReader 10\Examples. - To install the Stimulus Presentation Tool, see To install the Stimulus Presentation Tool. - It is not possible to install FaceReader on one computer and access it from another across a network. The program must be installed on the computer where it will be used. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Integration and Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-integration-and-setup Chapter: FaceReader FaceReader 10 - Integration and Setup Integration with The Observer XT FaceReader data can be visualized and analyzed in The Observer XT, enabling integration with other observational and physiological data. The advanced video editing functions of The Observer XT can be used to create highlight clips. If you have The Observer XT 13 (or newer) with the External Data Module and you observe live, you can use the Noldus network communication protocol N-Linx to control FaceReader with The Observer XT. When you start or stop the observation in The Observer XT, the FaceReader analysis will also start or stop. The FaceReader analysis and FaceReader video can automatically be imported into the observation. In addition it is possible to create a participant with camera analysis when creating an observation in The Observer XT. Communication with Other Applications Using the FaceReader API Facial expressions detected by FaceReader and other output values can be accessed real-time by other applications, making the program an ideal tool for research into affective computing and the design of adaptive interfaces. In other words, FaceReader allows other software programs to respond instantaneously to the emotional state of the user. The FaceReader API can send classification results to remote programs over TCP/IP. This API can be used in a .Net application to easily make a connection with FaceReader. For more information, refer to the Technical Note 'FaceReader 9 Application Programming Interface'. Individual Calibration This function enables the correction of person specific biases towards a certain emotional expression. A calibration model can be created using live camera input, or images or video of the test participant showing a neutral expression. If there is no calibration model selected, there is a possibility of using continuous calibration. In this mode, FaceReader continuously adapts to the bias of a certain user. Set-Up FaceReader achieves the best performance if it gets a good (video) image. Both the placement of the camera and the lighting of the subject's face are of crucial importance in obtaining reliable classification results. Camera Position The ideal position for the camera is directly in front of the subject's face. If the subject faces a computer screen, the camera can be placed either directly above or directly below the screen. Classification output might have a small bias towards the angry emotion when the camera is placed on top of the monitor and a small bias towards surprised when the camera is placed below the monitor. This is due to the fact that people tend to tilt their head when showing these emotions. Illumination The best results are achieved with diffuse frontal lighting. The light intensity or the color is less relevant. Strong reflections or shadows, for example caused by lights from the ceiling, should be avoided. Sideward lighting from a window will generally degrade performance. If the subject faces a computer screen, two columns of LED lights or two TL-tubes to either side of the monitor will give a good result under most circumstances. In situations where interior lighting cannot be controlled, stronger lights (e.g. professional photo lamps) can be used to negate the effect of other undesirable light sources. Noldus provides illumination for the optimization of your set-up. FaceReader contains a model quality bar, which gives you a good indication of how well the program is able to model the face depicted in the image. Source: FaceReader 10 Technical Specifications, Noldus Information Technology --- ## FaceReader 10 - Introduction to Action Unit Classification URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-introduction-to-action-unit-classification Chapter: FaceReader The Action Unit Module Main Topics - Introduction to Action Unit classification - Analyze Action Units - Visualize Action Units - Action Units in the log files - Custom Expressions Introduction to Action Unit Classification Action Units are muscles or muscle groups in the face that are responsible for facial expressions. The Action Units are described in the Facial Action Coding System (FACS) published by Ekman and Friesen (1978). FaceReader can analyze Action Units with the Action Unit Module. The following Action Units are analyzed: Action Unit FACS Name 1Inner Brow Raiser 2Outer Brow Raiser 4Brow Lowerer 5Upper Lid Raiser 6Cheek Raiser 7Lid Tightener 9Nose Wrinkler 10Upper Lid Raiser 12Lip Corner Puller 14Dimpler 15Lip Corner Depressor 17Chin Raiser 18Lip Pucker 20Lip Stretcher 23Lip Tightener 24Lip Pressor 25Lips Part 26Jaw Drop 27Mouth Stretch 43Eyes Closed If you have Baby FaceReader, you can analyze the combined activation of Action Unit 3 and 4 (Brow Knitting and Knotting). Intensities are annotated by appending letters: - A - trace. - B - slight. - C - pronounced. - D - severe. - E - max. These intensities follow the classification as described in Ekman et al. (2002). In FaceReader 9.1.8 and higher the classification of Action Units gives slightly lower intensities than in older versions of the software. In older versions non-active Action Units could be classified with intensity level A, A-level Action Unit activations with level B, etc. The reason for this difference is an error in the conversion script of the underlying deep neural network that has been corrected in FaceReader 9.1.8. The values of Contempt, Arousal, facial states (except Gaze direction) and Valence in Baby FaceReader are also affected as these parameters are based on Action Units. Valence in the regular version of FaceReader is based on facial expressions only and is, therefore, not affected. The calculation of most custom expressions is also based on Action Units and the intensities of these custom expressions are, thus, also different. For the most accurate Action Unit estimation it is important to use the latest version of the software and re-analyze old videos if you want to compare the data with those obtained with the new FaceReader version. References - Ekman P. and W. V. Friesen (1978). Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto. - Ekman P., W. V. Friesen, and J. C. Hager (2002). The Facial Action Coding System. Second edition. Salt Lake City: Research Nexus eBook. London: Weidenfeld & Nicolson (world). Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Introduction to Project Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-introduction-to-project-analysis Chapter: FaceReader Project Analysis Main Topics - Introduction to Project Analysis - Important Concepts in Project Analysis - Stimuli and the Stimulus Presentation Tool - Event Markers - Independent Variables - Project Analysis in Short - Data Selection - Visualize Your Data in a Chart - Calculate Statistics and Summarize Them in a Table - Visualize Your Stimulus, Participant Videos and Line Chart - Compare Data Introduction to Project Analysis In FaceReader you can: - Annotate Stimuli and events, to compare different parts of the analysis. - Automatically present Stimuli to the test participant and synchronize them with FaceReader data (for this purpose use the The Stimulus Presentation Tool). Alternatively, manually present Stimuli to test participants and keep track which analysis parts correspond with the moments the Stimuli were shown. In the Project Analysis section you can: - Create and compare groups of participants. - Calculate mean intensities of facial expressions (and other parameters) of single participants, for participant groups, or when Stimuli were shown. If you have the Action Unit Module you can also calculate statistics for Action Units and Custom Expressions. If you have the Vital Signs Module you can calculate statistics for heart rate, heart rate variability, and breathing rate. If you have the Voice Analysis Module you can calculate statistics for expressions in the voice, loudness and speech rate. - Calculate relative statistics using baseline correction. For example, calculate the expression intensities of test participants when they watched a certain commercial relative to the expression intensities when they were watching a neutral Stimulus. You can mark the time during which the test participants watched the commercial with a Stimulus. Note Project Analysis was not designed for image analyses. Therefore, if your project only contains image analyses, you cannot carry out group analyses. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Introduction To The Voice Analysis Module URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-introduction-to-the-voice-analysis-module Chapter: FaceReader The Voice Analysis Module Main Topics - Introduction to the Voice Analysis Module - Analyze voice characteristics - Visualize voice characteristics - Export voice analysis data Introduction To The Voice Analysis Module The Voice Analysis Module enables you to analyze vocal characteristics. FaceReader can currently detect the following emotions in a voice: Neutral, Happy, Sad, Angry. The software was trained and tested using British and American English data, both acted and natural speed. Preliminary tests show potential applicability to other languages, particularly those with close linguistic and cultural similarities. An audio buffer is used to collect approximately one second of data before starting the analysis because audio (unlike video) cannot be segmented into discrete frames. FaceReader uses a simple Voice Activity Detection (VAD) and analyzes all sound above the threshold. If there is noise in the audio signal this will be analyzed as well. There is no preprocessing step to decide if audio is speech, so background noise can result in incorrect detections. Using a high-quality microphone and limiting background noise is recommended to improve the accuracy of the voice analysis. Furthermore, it might be necessary to adjust the microphone's sensitivity to achieve the best results. Please note that you cannot combine the Voice Analysis Module with Baby FaceReader and you cannot analyze emotions in voices in a multi-subject analysis. Note The Voice Analysis module employs Voice Activity Detection (VAD) based on a Gaussian Mixture Model (GMM) to distinguish between speech and non-speech segments. This approach helps ensure that only voiced segments are processed, reducing the influence of silence or background noise. While GMM-based VAD is generally reliable under typical conditions, it is not immune to mis-classifications, particularly in environments with overlapping speech, high levels of ambient noise, or non-speech sounds within similar frequency bands. Only if voice is detected, the following measures will be calculated and reported by FaceReader. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Limitations Of The Current Version URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-limitations-of-the-current-version Chapter: FaceReader Sample Projects You can download two example projects from your MyNoldus account: https://my.noldus.com Sample Project - Two Stimuli Five test participants watch two videos, one with baby twins that feed each other and one in which strange food is being prepared. Compare the facial expressions of the test participants while watching the two videos. Sample Project - Infrared Recording In this sample project we filmed a driver in a car driving in the near-dark to illustrate that FaceReader can analyze infrared recordings. In this project you can see what head rotations FaceReader can deal with. You can visualize Head orientation, Head position and Gaze angle. Read the PDF file Description of FaceReader 10 sample projects, to see all the features that you can view in the projects. You can download this PDF file from the MyNoldus portal on the Noldus website (my.noldus.com). Limitations Of The Current Version The current FaceReader version has a number of limitations. It is good to keep these in mind when you start working with FaceReader. - Glasses may hinder classification. Especially thick and dark frames can reduce performance significantly. It may be useful to have a number of rimless reading glasses available in a few strengths when you carry out a test. A polarization filter on the camera can help to avoid reflections in the glasses. - Pose, movement and rotation of the test person are limited. The test person should stand or sit and look frontally into the camera (angle < 30°). That means that you should sit opposite of the test participant and not next to him/her if you want to ask questions during the test. In a social interaction setting (medical student - patient or consultant-client interaction) you would ideally position the camera on the conversation partner's shoulder. With this set-up people look almost straight into the camera when they talk to their partner. In practice this may not be possible but if you put the camera a short distance away, at the same height, with direct sight line to the participant's face, you have a working solution. In a consumer study you can use a cup or bowl holder so the dish is closer to the face and the test participant does not need to tilt his/her head downwards. If your test participants need to read instructions or fill in a questionnaire, you can present this information on a screen and attach the camera to the screen. - FaceReader requires strict light conditions. See Lighting Setup. You can use (near) infrared light with a camera that is sensitive for this type of light. FaceReader 10 supports (near) infrared recordings. Please note that it is not possible to measure heart rate, heart rate variability and respiratory rate with infrared recordings. - Factors that partially hide the face, like a hat, hair that covers the forehead, or very heavy facial hair may hinder the analysis. Hands in front of the face should also be avoided. You may normally offer your test participants something to eat or drink during the test to make them feel more comfortable. However, when eating or drinking the test participant blocks part of the face with his/her hand and the cup/glass/cutlery. Make sure the test participant finishes his/her cup of coffee before you start the test unless, of course, the purpose of the test is to see the reaction to a new food product or beverage. Some people have the natural tendency to touch their face without realizing it. You may want to warn your test participant to keep their arms on the table throughout the test in order to get the best possible results. - With the base functionality of FaceReader can analyze one face at once. If there are more faces in an image, you can select one of the faces by dragging the borders in the preview window and analyze that face. Then do the same with the other faces. Of course, the positions of the faces must not change significantly. See also the notes in Analyze Facial Expressions. If your FaceReader license included the Advanced Research Module you can analyze up to eight faces in a video simultaneously. See The Advanced Research Module. - For FaceReader to analyze facial expressions, emotions must be visible in the face. "All my test participants looked neutral throughout the test" is an often heard complaint. It may help to test people in their natural environment, at home or in another familiar environment (restaurant, school, office, etc.). Running your tests in the test facilities in your office has the obvious advantage that you can control the test conditions much better than out in the field. The downside, however, is that people may react differently to your stimuli or not at all. - Please contact us if any of the limitations above impede your research. Improving FaceReader's Performance The following tips to improve FaceReader's performance apply to all analyses done in FaceReader and are especially important when using batch analysis of videos. - Length of videos - Although there are no built-in limitations regarding the length of videos, it is good to keep in mind that the longer the video, the more data needs to be saved in the computer's internal memory. Data is only saved to the hard disk after every analysis. We recommend to use videos that have a maximum duration of two hours (if 15 fps) or one hour (if 30 fps). - Resolution of videos - Higher resolution does not mean better facial expression analysis with FaceReader. High resolutions are scaled down to a maximum of 1280x1280 pixels while keeping the original video aspect ratio. Keep in mind that the scaling costs processing power and other resources which do have an influence on the performance. The minimum video resolution is 640x480. - Analysis options - In the FaceReader Settings you can select what optional classifications you want to analyze. Select only those options that you need. Selecting more options requires more processor capacity. - Visualizations - Graphical presentations cost a huge amount of processing power and other resources (e.g. memory). For best performance you can best close the visualizations during analysis. - Processing unit - A powerful processor and sufficient internal memory is a prerequisite. Please see the System Requirements. - Applications running in the background - Make sure that no other applications are running. - Test real products - You can show test participants pictures of your product, videos/commercials featuring your product, or you can give them the real product. Generally real products elicit greater responses. While having the real product to view is preferable to seeing a photo, real-life use is even more preferred. So, if you want to know whether your test participants like your new healthy flour mix, for example, you can ask them to bake pancakes in a test kitchen, and observe the displayed reactions during the baking process and the consumption phase. - Present more than one stimulus - If you want to test your new product (commercial, beverage, etc.) it is best to embed it in a series of other products. In this way the test participants do not concentrate fully on the focus product and will respond in a more natural way. This also allows the participants to compare your product with similar ones. Be sure to randomize the order in which you present the products. Mouse Control Some features of FaceReader are controlled with mouse clicks. If you do not have a mouse, you can use a mouse-emulator like NeatMouse to use those FaceReader functions. You can download NeatMouse for free. http://neatdecisions.com/products/neatmouse/ Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Make Sure The Observer XT Can Access The FaceReader Video Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-make-sure-the-observer-xt-can-access-the-facereader-video-files Chapter: FaceReader Create Exceptions For The N-Linx Port In Windows Firewall Aim To make sure traffic through the port that is used by N-Linx is not blocked by Windows Firewall. Prerequisite FaceReader, The Observer XT and N-Linx Server are not all installed on the same computer. If they are all installed on the same computer, skip this topic. Procedure Follow this procedure for all computers with FaceReader, The Observer XT, and N-Linx Server. - Open the Control Panel and select Windows Defender Firewall. - On the left side of the window, click Advanced Settings. - Click Inbound Rule and click New Rule in the Actions pane. - In the New Inbound Rule Wizard Window that opens, select Port and click Next. - Select TCP and enter 5672 in the Specific local ports field and click Next. - Click Allow the connection and click Next. - Select to which network the rule applies and click Next. - Give the rule a name, for example N-Linx connection and click Finish. - Check in the Inbound Rules windows that this rule is set to Enabled. - Click Outbound Rule and click New Rule in the Actions pane. - Repeat steps 4-9 for the outbound rule. - Close all Control Panel windows. Make Sure The Observer XT Can Access The FaceReader Video Files Aim To make sure The Observer XT can access that videos FaceReader records. The videos are not copied to The Observer XT. The Observer XT creates a link to the FaceReader videos. Procedure Carry out the following steps: - Share the folder where FaceReader stores its video files. IMPORTANT Since the FaceReader videos are stored in the subfolder Recorded Videos in the project folder, this procedure has to be carried out for every new FaceReader project. If a project has only a few videos it may be easier to import the video files manually into The Observer XT. - Switch off password protected sharing on the FaceReader computer. - Map the shared folder with FaceReader video files. Share The Folder Where FaceReader Stores Its Video Files - Right-click the folder where the video files are going to be stored, which is by default C:\Users\\Documents\Noldus\FaceReader 10\Projects\[Project name]\Recorded Videos and select Give access to and then Advanced Sharing Settings. - Change the sharing options for all your network profiles ('Private', 'Guest or Public' and 'Domain'): select the option Turn on file and printer sharing for all your profiles. - Under 'All Networks' select the option Turn on sharing so anyone with network access can read and write files in the Public folders. Then click Save Changes. Switch Off Password Protected Sharing On The FaceReader Computer This procedure is needed to make sure that the folder where FaceReader stores its videos files can be accessed without a password by the computer with The Observer XT. The procedure differs for a Windows workgroup or a domain. To see whether the FaceReader computer is in a workgroup or a domain, open the Control Panel and choose System and then Advanced System Settings and click the Computer Name tab. The type of network is listed under Computer name, domain, and workgroup settings. Procedure For Workgroup - Follow the procedure in Share the folder where FaceReader stores its video files to open the Advanced sharing settings. - Under Password protected sharing, select the option Turn off password protected sharing. IMPORTANT If you do not see this option, most likely your computer is in a domain, not a workgroup. Carry out the procedure for domain below. Procedure For Domain - Press the Windows key + R. - Type lusrmgr.msc and press OK. - Open the Users folder and double-click Guest. - Deselect Account is disabled and click OK and close the lusrmgr window. - Press the Windows key + R. - Type gpedit.msc and press OK. - Open Computer Configuration\Windows Settings\Security Settings\Local Policies\User Rights Assignment and double-click Deny access to this computer from the network. - Click Guest and then choose Remove > OK. - Close the Local Group Policy Editor window. Map The Shared Folder With FaceReader Video Files Carry out this procedure on both computers. - Open File Explorer and then This PC. - Click Computer and then click the Map network drive icon. - Choose a name for the drive and browse to the shared folder. IMPORTANT Make sure you select the same drive letter on both computers. - Click Finish. Notes - When you now start the computer with The Observer XT you need to enter the login details for the computer with FaceReader. - Make sure the computer with FaceReader videos is switched on when you open your project in The Observer XT. Otherwise The Observer XT will not be able to open the videos. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Manage Analysis Windows URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-manage-analysis-windows Chapter: FaceReader FaceReader's Output Main Topics - Manage Analysis Windows - Reporting Display - Export Analysis Results Manage Analysis Windows Aim To change the windows displayed on your screen. Prerequisite You opened an analysis. To do so, click the magnifying glass button next to it. What Do You Want To Do? - Select Analysis Windows - Add More Analysis Windows - Merge Analysis Windows - Reset the Analysis Window Layout - Read About Common Options - Create a Custom Visualization with the Reporting Display Select Analysis Windows - Click the Select Window button in the right-corner of one of the analysis windows. - Select one of the options. Face Analysis You can choose between: - Action Unit Intensity* - Circumplex Model of AffectΔΔ - Expression IntensityΔΔ - Expression Line ChartΔΔ - Expression SummaryΔΔ - Facial States - Gaze Angles Line Chart - Head Orientation Line Chart - Head Position Line Chart - Subject CharacteristicsΔΔ - Valence and Arousal Line Chart Consumption Behavior - Consumption Behavior Statistics**ΔΔ Vital Signs - Heart Beat Chart*** - Vital Signs*** - Vital Signs Line Chart*** Voice Analysis - Voice Expression IntensityΔ - Voice Expression Line ChartΔ - Voice Valence and Arousal Line ChartΔ - Voice ViewΔ Analysis Visualization Custom Expressions Table* Custom Expressions Line Chart* Stimulus View Timeline * This window is available if you have The Action Unit Module or Baby FaceReader ** This window is available if you have The Consumption Behavior Module *** This window is available if you have The Vital Signs Module Δ This window is available if you have The Voice Analysis Module ΔΔ Not available with Baby FaceReader Notes - When you choose a visualization that is already open in another window, the other window closes. - Each facial expression has a fixed color which is the same in all the charts. It is not possible to change the colors of the expressions. Add More Analysis Windows - Click one of the Split/Unsplit buttons in an analysis window. This will split the window either horizontally or vertically. - Click the Select Window icon, select either Face, Consumer Behavior, Vital Signs, Voice or Timeline and then select a window from the list that appears. Merge Analysis Windows To merge the windows again, click the Close button in the window that you want to delete. Reset The Analysis Window Layout To close any extra windows that you opened and to reset the position of your windows, choose Window > Reset Analysis Window Layout. Common Options Most windows and charts can be exported or copied to the clipboard, and zoomed in/out. - Export the window/chart as a *.PNG, *.JPG, *.BMP, *.GIF, *.TIF or *.EMF image. An EMF image is a vector image and therefore scalable. - Copy the window/chart to the clipboard, to paste it in another program like Word or PowerPoint. - Use the Zoom In and Zoom Out buttons to change the level of detail. Common Options For Line Charts If you analyzed multiple intervals in one video, the windows with data over time show gaps. Click Options and then select Auto Scale Y Axis to adjust the Y axis to the maximum value. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Manual Procedure Image Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-manual-procedure-image-analysis Chapter: FaceReader Analyze Facial Expressions Aim To carry out the FaceReader analyses. Prerequisite You checked the Analysis settings by clicking the Settings button on the bottom of your screen. Make sure you selected the correct Face Model. See Active Face Model See Choose Settings Which Procedure Are You Looking For? - Automatic analysis procedure - Manual procedure image analysis - Manual procedure video and camera analysis - Optional classifications With the Advanced Research Module you can analyze multiple faces in a video simultaneously. See Analyze Multiple Subjects Per Video. Automatic Analysis Procedure With the Project Analysis and The Stimulus Presentation Tool, analysis is carried out automatically when the participant starts a test. You do not have to start and stop analysis manually. See Carry Out a Test with the Stimulus Presentation Tool in Project Analysis Manual Procedure Image Analysis Aim To analyze facial expressions from images. Prerequisites - You created a participant for each person. See Add Your Test Participants - You created at least one image analysis for every participant. See Add Analysis Input Procedure - Optionally, select more than one image in an analysis and select Analyse all images to analyze all images of the participant at once. - Click the Start analysis button. The track bar shows a dot in the color of the dominant expression for each image. When you hover with your mouse over the dot, the filename of the image and the dominant facial expression are shown. - Check the Model quality bar for the analysis quality. The green bar should cross the dashed line. - To export analysis results, choose File > Export and select to export the results of the analysis, participant, or the entire project. See Export Analysis Results Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Manual Procedure Video and Camera Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-manual-procedure-video-and-camera-analysis Chapter: FaceReader Manual Procedure Video and Camera Analysis Aim To analyze facial expressions from video, or live from camera images. Prerequisites - You do not carry out analysis with The Stimulus Presentation Tool. When you use the Stimulus Presentation Tool, the analysis starts when the participant starts a test. - You created at least one participant. See Add Your Test Participants - You created at least one video or camera analysis for every participant. See Add Analysis Input Procedure - For Video analysis – Position the video to where you want to start the analysis. - Click the Start analysis button at the bottom of your screen. The track bar shows the progress of the analysis, the analysis speed (in fps), the running end time of the analysis, the end time of the video and whether the video has audio. - During analysis, check the Model quality bar in the Analysis Visualization window. It should look like the one below, the colored bar must cross the dashed line. You can adjust the model quality, see Minimum Model Quality. If the quality of your camera image is not good enough, the text Could not find a face or Could not classify the face (FaceReader cannot model the face) will appear in the Analysis Visualization window. Probably either the lighting of the test person's face or the position of the camera is not optimal. See Camera and Accessories how to improve your setup. - Click the Stop Analysis button to stop the analysis. - Video analysis – to analyze more episodes, move the video to a new position and click the Start analysis button again. The analyzed episodes are shown on the track bar. IMPORTANT The data of all the analysis intervals are saved in one log file. The text Not Analyzed will appear in the log file for the time points that were not analyzed. This can result in very big files. - To export analysis results, choose File > Export and select to export the results of the analysis, participant, or the entire project. See Export Analysis Results Notes - By default, videos are processed frame-by-frame. To speed up the analysis, change the sample rate. See Video - To carry out all video analyses at once, press the Start batch analysis button on the toolbar of the project explorer. Please see the tips on Improving FaceReader's performance which are especially important when using batch analysis. - To redo an analysis, click the Clear results button and start the analysis again. Exported log files will not be deleted. - When you run a camera analysis, a new video frame is analyzed when the analysis of the previous frame is finished. If detection is demanding, the number of frames being analyzed per second may be lower than the camera frame rate. In this case FaceReader skips a frame to keep up with the camera frame rate. After the analysis is finished, FaceReader interpolates the results in the skipped frames to the frame rate of the recorded video. See also Camera Frame Rate and Samples in FaceReader in Set Up Your Project - When you run a video analysis, the average frame rate may be lower than that expected from the frame rate of the video file. For example 27 fps when the video frame rate is 30 fps and you set to analyze every frame. In that case video plays slower than 1x during analysis, but all frames are analyzed. See also: - Speed Up Analysis - Video in Settings - Sample Rate in Settings - To analyze part of the video image, for example because your video contains multiple faces and you only want to analyze one of them, click the Select area of interest button. The Draw the selected area window opens. Drag a window around the face that you want to analyze. Either click the Apply button to start analyzing the selected face or the Reset selected area button to delete the selected area and draw a new one. - You can analyze multiple faces in a video with the Advanced Research Module. - To increase the speed and the accuracy of analysis, FaceReader uses information from previous frames to analyze the current frame. For instance, if in the previous frame FaceReader could correctly model the face, a re-detection is not required, because FaceReader already knows the location of the face. Information about previous frames is also used to smooth the output of FaceReader. These enhancements lead to much faster analysis, and it also allows the face modeling algorithm to better fit the face in the image. A side effect of this is that results depend on the start position used. - If you re-analyze the video of a camera analysis and notice that the video is not analyzed. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Modules URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-modules Chapter: FaceReader Modules You can extend the base functionality of FaceReader with modules. Your license determines which modules you can use. For Baby FaceReader only the Vital Signs Module is available. You can check what modules have been enabled on your license. From the Help menu select About and in the window that opens under Modules click Enabled Modules. Action Unit Module With the Action Unit Module you can analyze the intensity of a number of Action Units from the Facial Action Coding System (FACS). FaceReader can analyze 20 Action Units, that are most common in facial expressions. With the Action Unit Module you can also define your own expressions (Custom Expressions). You can, for instance, combine 'Happy' and 'Arousal' to assess what commercial makes your test participants happily aroused. Interest, Boredom and Confusion which were called Affective Attitudes in FaceReader 7.1, are now available as Custom Expressions. See The Action Unit Module Vital Signs Module With the Vital Signs Module you can analyze the heart rate and heart rate variability of the test participant by means of remote photoplethysmography. In FaceReader 10 you can also analyze the participant's respiratory (breathing) rate. See The Vital Signs Module Voice Analysis Module With the Voice Analysis Module FaceReader can recognize emotions in the voice (Neutral, Happy, Sad and Angry) and Valence and Arousal. In addition, the software can assess the Loudness and Speech rate. See The Voice Analysis Module Advanced Research Module This module allows you to analyze multiple faces in a video. With this module and the Stimulus Presentation Tool you can also track the gaze of the test participant to assess what he/she is looking at when you present stimuli. See The Advanced Research Module and Stimulus Presentation Tool Consumption Behavior Module With the Consumption Behavior Module you can determine whether your test participants show chewing behavior, take a bite when testing a food item or take a sip when testing drinks. Bites and sips are called 'intake events' in FaceReader. See The Consumption Behavior Module Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - More Information On Camera Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-more-information-on-camera-analysis Chapter: FaceReader More Information On Camera Analysis What Information Are You Looking For? - Supported Cameras - Default Camera - Camera Frame Rate And Samples In FaceReader - Camera Resolution And Analysis In FaceReader - Video Format - Camera Analysis With An IP Camera Supported Cameras See Camera And Accessories In Installation Please also read the sections below about video frame rate and resolution. Default Camera If you always use the same camera for camera analysis, set this camera as the default one. - Choose File > Set Default Camera. - Select your camera. This camera will be automatically selected in future analyses. Camera Frame Rate And Samples In FaceReader When you record video from a live camera image, the resulting frame rate of the video file is the chosen camera frame rate. See step 2 in Add Analysis Input Manually. Camera Resolution And Analysis In FaceReader FaceReader analyzes (video/camera) images with a maximum resolution of 1280 x 1280. If the resolution of your video file, camera, or images is higher than 1280 x 1280, FaceReader scales it down while maintaining the aspect ratio. Using a higher resolution than 1280 x 1280, therefore, does not improve analysis. Also, using a higher resolution slows down the analysis. Video Format The video file format of the recorded video is DivX/MP4V. This format is compatible with The Observer XT. To play back a DivX video on a computer without FaceReader or The Observer XT, it may be necessary to install a DivX player. Camera Analysis With An IP Camera Important FaceReader works with IP cameras that create MJPEG or JPEG output. FaceReader does not work with RTSP output of IP cameras. To select an IP camera, follow the steps below: - In the Select Camera window, under Select Camera, choose IP Camera. - Under Source URL, enter the source URL of your camera. Check the documentation of your camera or contact the service department of your camera brand for the correct URL. For Axis IP cameras, enter one of the following: - http://IP address camera/mjpg/video.mjpg - http://IP address camera/axis-cgi/mjpg/video.cgi - Under Frame rate, select the frame rate (default: 5 fps). - If your camera is password-protected, select Secured and enter the Username and the Password. For Axis IP cameras supplied by Noldus, enter root and Noldus, respectively. - Select either JPEG or MJPEG. Check in the documentation of the camera what type of stream the camera produces (JPEG or MJPEG). Choose MJPEG for Axis IP cameras. - Select Use as Default Camera if you want FaceReader to automatically select the current camera for future camera analyses. The camera view appears in the Preview Image window. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-notes Chapter: FaceReader Running A Test With Stimulus Presentation Tool - Let the participant sit in front of the computer. - In the Welcome window, let the participant enter: - His/her name (optional; see step 7 in Define a test). - The values of the independent variables (optional, see step 6 in Define a test). - When ready, ask the participant to click Start. The Start button is available when the participant has entered the values of all required independent variables. - If you selected Perform gaze calibration when you defined the test, a message appears informing the participant that calibration will start when they click. The participant should look at the dots that appear on the screen and hover over them with their mouse. - After a couple of seconds the first Stimulus is displayed. - At the end of the test a message Thanks for Participating appears. The participant and analysis are added automatically in FaceReader. Notes Before The Test - To go from Select Test to Connect to FaceReader, click the arrow at the bottom-left corner of the Stimulus Presentation Tool window. - To go from the Welcome window back to Select Test, click anywhere on the window, then press Alt+Home, then click Connect. During The Test - During the test, FaceReader shows the message Test in Progress. To change the views in FaceReader, click OK and select the windows you require. Do not change settings. - Analysis is done automatically during the test. Do not click the Start/Stop analysis button during the test. - Between presentation of two Stimuli, a message "Get ready" is shown for a number of seconds. - After the test participant has clicked Start in the Welcome window (step 7), and before the first Stimulus is presented, a new FaceReader analysis is created and started in the background on the FaceReader PC. - When a stimulus starts, the Stimulus Presentation Tool sends the information to FaceReader, which scores the start of the Stimulus. - To switch the Stimulus Presentation Tool window to full screen, press F11. Press F11 again to resume the original window size. - To stop the test before the end of the last Stimulus, in FaceReader click the Stop analysis button or in the Stimulus Presentation Tool click anywhere on the window, then press Alt+Home. The analysis and participant are marked with an error icon. After The Test - To start the test for the next participant, click the arrow at the bottom-right corner of the Stimulus Presentation Tool window. - To choose another test, click anywhere on the Stimulus Presentation Tool window, then press Alt+Home, then click Connect. - To close the Stimulus Presentation Tool, click the Close button. - You can view the stimuli in the Stimulus View window, next to the face of the participant and, for instance, the Expression Intensity chart with his/her facial expressions. If you selected Perform gaze calibration when you defined the test and selected Gaze tracking in the Settings, you can also see the gaze tracking data. General - You can connect FaceReader with one Stimulus Presentation Tool at a time. - When the Stimulus Presentation Tool is connected to FaceReader, this is displayed in the upper-right corner of the FaceReader window. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Observe In The Observer XT And Analyze In FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-observe-in-the-observer-xt-and-analyze-in-facereader Chapter: FaceReader Observe In The Observer XT And Analyze In FaceReader Procedure - Check the following: That your camera is connected to the PC, that it is turned on, and selected as default camera in FaceReader. That FaceReader is open and the upper right corner shows the text N-Linx-connected. That you selected the data to export in FaceReader. Important Select only the data you really need. Data files can become very large when you select many export options. This slows down data import into The Observer XT. - Let the test participant take place at the test computer and check that the FaceReader webcam has a proper view of the face. See Camera and accessories in Installation - Create a new observation in The Observer XT. A new participant is created in FaceReader with a camera analysis. - Start the observation in The Observer XT. Dependent on the settings in The Observer XT, the Independent Variables list appears. This list contains the independent variables you created in The Observer XT together with the FaceReader independent variables Age, Gender and ParticipantID. When you enter the values of the user defined independent variables, the observation and FaceReader analysis start. See Independent Variables how FaceReader independent variables are imported into The Observer XT. - Score data in The Observer XT. FaceReader automatically analyzes the camera images and creates a video file. - Stop the observation. Classification in FaceReader is automatically stopped. The FaceReader data and videos are automatically imported into the observation. The Expression states are imported as behaviors and the values of the detailed log are imported as external data. Notes - If your license for The Observer XT does not include the External Data Module, you must set up The Observer XT to start and stop FaceReader analysis together with an observation. See Add a Custom External Device in The Observer XT Help for the procedure. Important Importing FaceReader data adds FaceReader elements to the coding scheme. However, these elements cannot be scored manually in a new observation in The Observer XT. - When you enter a name in the Identify device as field in step 10 of Set up The Observer XT to work with FaceReader, this name is added as a subject to the Coding Scheme. When you now manually score events, The Observer XT expects that for each event you first score a subject and then a behavior. Define a subject in the Coding Scheme. Then choose Setup > Project Settings > Scoring Options and select Auto-record subject. You now have to score the subject only once at the start of the test. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Optional Classifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-optional-classifications Chapter: FaceReader Optional Classifications Aim To select other analyses in addition to facial expressions. FaceReader can, optionally, analyze the following: - Contempt - Facial states - Gaze tracking - Action Units (if you have The Action Unit Module or you have Baby FaceReader) - Custom Expressions (if you have the Action Unit Module or you have Baby FaceReader) - Heart rate, heart rate variability (by means of Remote PPG), and breathing rate (if your license includes The Vital Signs Module) - Consumption Behavior (if you have The Consumption Behavior Module, not available with Baby FaceReader) - Expressions in the voice (if your license includes the Voice Analysis Module. Note this feature is not available with Baby FaceReader) Note Each optional classification decreases analysis speed, so only select the options you require. Procedure To select these optional classifications, choose File > Settings. Click the Analysis Options tab, and make your selection under Optional Classifications. Contempt Contempt is an expression in which one corner of the lips is tightened and slightly raised. It can be classified reliably in different cultures [1]. Some authors state that it should be added to the six basic emotions defined by Paul Ekman [2]. However, other authors disagree with this [3]. To add contempt to the expression states, select the option Treat contempt as an emotional state. This adds contempt to the State Log and Timeline and makes contempt mutually exclusive with the other emotions in the State Log and Timeline, meaning that only one emotional state can be active at any given time. References - Ekman, P., & Friesen, W. V. (1986). A new pan-cultural facial expression of emotion. Motivation and emotion, 10(2), 159-168. - P. Ekman. Universal facial expressions of emotion. California Mental Health Research Digest, 8: 151-158, 1970. - Ekman, P. (1992). An argument for basic emotions. Cognition & Emotion, 6(3-4), 169-200. Facial States FaceReader can detect whether the left and right eye is open or closed, whether the mouth is open or closed and whether the eyebrows are raised, neutral or lowered. These states are shown in the Facial States window. They are also visualized in the Analysis visualization window, when the option Show facial states is selected. Gaze Tracking FaceReader can detect the test participant's Gaze Direction, Gaze Type and Gaze angles. Gaze direction indicates whether the participant looks to the left, left-up, left-down, or to the right, right-up or right-down, Up, Down or Forward. Gaze Type indicates whether the test participant's eyes fixate on something (that is, the eyes are still and looking at, for instance, the eyes in a face) or whether there is movement of the eyes when the test participant shifts his/her focus of vision (a saccade). In addition, FaceReader measures the horizontal and vertical Gaze angle over time. If your license includes the Advanced Research Module you can view the test participant's gaze overlay on the stimuli that you present with the Stimulus Presentation Tool. See Run a test in Project Analysis. Gaze direction, Gaze Type and Gaze angles are shown on the Timeline. Gaze Direction is also visualized in the Analysis Visualization window, when the option Show global gaze direction is selected. If the Show global gaze direction button is not active, select File > Settings > Analysis Options and under Optional Classifications select Gaze tracking. Action Units FaceReader can analyze Action Units from the Facial Action Coding System (FACS) published by Ekman and Friesen (1978), if you have The Action Unit Module or you have Baby FaceReader. The Affective Attitudes Interest, Boredom and Confusion that were called Affective Attitudes in FaceReader 7.1, are now available as Custom Expressions. You can also define your own Custom Expressions. Heart Rate, Heart Rate Variability, And Breathing Rate FaceReader can analyze the heart rate, heart rate variability and breathing rate of the test participants, if your license includes The Vital Signs Module. Consumption Behavior With the Consumption Behavior Module you can determine whether your test participants are chewing or taking a bite or sip. This option is not available with Baby FaceReader. See The Consumption Behavior Module Expressions In The Voice With the Voice Analysis Module you can analyze emotions in the voice (Neutral, Happy, Sad and Angry), and Valence and Arousal from the voice. FaceReader can also assess the Loudness and Speech rate. Voice analysis is not available with Baby FaceReader. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Options URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-options Chapter: FaceReader Expression States Explained An expression is dominant when its intensity is higher than that of all others. Each time the dominant facial expression changes and is active for at least 0.5 seconds, this expression is scored as a state. This state appears in the Timeline and is also scored with its time stamp in the State log. Note that if the intensity, as displayed in the Head Orientation Line Chart, exceeds 0.5, this does not necessarily mean that an expression state is scored. In the following example the Expression Intensity is compared with the Expression states. Sad and Disgusted exceed 0.5, but only Disgusted is scored at that time, because its intensity is higher than that of Sad and was dominant for at least 0.5 seconds. (see the blue bar on the timeline). Unknown means that no face is found or the face cannot be modeled (for instance, because the quality of the video is poor or a hand partly hides the face). For video analysis, Not Analyzed indicates what part of the video has not yet been analyzed. Options Expressions Click Expressions and choose which expressions you want to view. By default all expressions are selected. Events The timeline also shows the Stimuli and Event Markers in your project. Optionally deselect either the Stimuli, Event Markers, or both using the Events button. Expressions Deselect Expressions if you do not want to see them on the Timeline. Facial States With Facial States, choose whether you want to display the Facial States (Left Eye, Right Eye, Left Eyebrow, Right eyebrow, Mouth). By default, all these options are selected. Gaze Tracking If you selected Gaze tracking in the Settings you can visualize the Gaze Direction and Gaze Type on the Timeline. Action Units If you have the The Action Unit Module, the timeline also shows the intensity of the Action Units. Optionally, deselect some Action Units, using the Action Units button. Consumption Behavior If you have The Consumption Behavior Module, the timeline also shows the behaviors 'Intake event', 'Chewing' and 'Chew motion'. Optionally, deselect some from the Consumption Behavior drop-down list. Voice Expressions If you have the Voice Analysis Module the Timeline also displays the dominant emotions recognized in the participant's voice. Notes - For more information about the State log, see Export Analysis Results. - If you want to use other criteria to define a state, for example when the intensity of an expression is above 0.5, export the detailed log. Then calculate the states in another program, like Excel. See Export Analysis Results Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Output and Export URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-output-and-export Chapter: FaceReader Output and Export Output FaceReader displays a number of windows with graphical and tabular output. Important Notes - Not all visualization options may be available by default. If you do not see some of the options described in this Quick Start Guide, choose File > Settings > Analysis Options and select all options. - If you selected the Baby Face model, not all output is available. See the FaceReader Help for more information. Output Procedure - Click on one of the buttons in the Analysis Visualization window to show, for example, the key points in the face or the Facial States. - To switch windows, click on the Select window button in the upper-right corner of one of the windows and make your selection. See Analysis Windows below for a short description of the options. - To zoom, or to copy or save graphs, click on one of the icons on the window toolbar. - To show more windows, click on the Split/Unsplit buttons in the upper-right corner of one of the windows. Tip If you notice the test participant shows a bias towards some facial expressions, use one of the calibration methods to correct for that. See Analyze Facial Expressions/Calibrate FaceReader in the FaceReader Help for details. Analysis Windows You can choose between: - Face Analysis - Action Unit Intensity – Available with the Action Unit Module. - Circumplex Model of Affect – A chart in which emotions are described in a two-dimensional circular space, containing arousal on the vertical axis and valence on the horizontal axis. - Expression Intensity – A chart that displays which of the facial expressions show up in the face. - Expression Line Chart – A line chart with the facial expression intensities over time. - Expression Summary – A pie chart with the distribution of the facial expressions. - Facial States – Whether, for example, mouth or eyes are open or closed. - Gaze Angles Line Chart – Horizontal and Vertical gaze angle on a time line. - Head Orientation Line Chart – The head orientation on a time line (Pitch, Yaw and Roll). - Head Position Line Chart – Horizontal, Vertical and Depth position on a time line. - Subject Characteristics – With, for example, the estimated age and gender. - Valence and Arousal Line Chart – Valence indicates whether the emotional status of the test participant is positive or negative. Arousal is based on the activation of the 20 Actions Units in FaceReader. - Consumption Behavior (available with the Consumption Behavior Module) - Vital Signs (available with the Vital Signs Module) - Voice Analysis (available with the Voice Analysis Module) - Analysis Visualization – Click on a button on the left to view how FaceReader analyzes the face. - Custom Expression Table – Available with the Action Unit Module. - Custom Expression Line Chart – Available with the Action Unit Module. - Stimulus View - Timeline – An overview of the facial expressions, and facial states on a timeline. See FaceReader's Output in the FaceReader Help for a full description of the analysis windows. Export To export your data, choose File > Export. Choose to export the results of the analysis, participant, or entire project. You have the following options: - State log – A text file or Excel file with the dominant facial expressions as states over time. - Detailed log – A text file or Excel file with the intensities of all facial expressions over time. To save extra options, like facial states, global gaze direction, valence and arousal values to the log file, select these options in the Data Export tab of the Settings window (File > Settings). Optionally, adjust the sample rate of the export file and select whether to include headers. - Heart beat log – A text file or Excel file with the inter-beat interval data (the time intervals between individual heart beats). - The Observer XT log – Choose this option if you want to import the analysis results in the annotation software The Observer® XT for further analysis. The Observer XT log exported from FaceReader can be imported into The Observer XT to display facial expressions on the time line. An example project called 'Child FaceReader' demonstrates this: a 3-year old boy is observed playing an online game, his face filmed with a webcam while the screen is captured with the Noldus screen capture device. The facial expressions are shown as states on the timeline in The Observer XT. Tip It is also possible to send the analysis results directly during the FaceReader analysis to The Observer XT, using the Noldus network communication program N-Linx. See FaceReader with The Observer XT in the FaceReader Help for details. Source: FaceReader 10 Quick Start Guide, Noldus Information Technology --- ## FaceReader 10 - Participant Calibration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-participant-calibration Chapter: FaceReader Calibrate FaceReader Aim To correct for person-specific biases in facial expressions, for example if someone looks angry or sad by nature. Instead of calibration you can also use a Stimulus to score an episode in which your test participants have a neutral expression and carry out relative analysis. See Select absolute or relative values for your parameters. Prerequisites - You have the regular version of FaceReader. Calibration is not available in Baby FaceReader. - You notice a person-specific bias in facial expressions. If there is no such bias, we recommend not to use calibration since it may then decrease analysis accuracy. - You first checked whether changing the camera, or lighting conditions removes the bias. Two Calibration Methods FaceReader has two calibration methods: - Participant calibration — Use this method if you analyze videos or images. Also use this method if you do camera analysis and the experimental setup allows capturing a neutral phase before the experiment starts. See Participant calibration - Continuous calibration — Use this method if you carry out camera analysis and the experimental setup does not allow capturing a neutral phase before the experiment starts. This is for example the case if you start FaceReader automatically with another program. See Continuous calibration Participant Calibration Aim To correct for person-specific biases in facial expressions. Prerequisite You have a video fragment, or images in which the expression of the test participant was neutral. Alternatively, if you carry out camera analysis, you are able to record a scene during which the test participant looks neutral. Please note that you need at least 100 images for the calibration. See also How participant calibration works Procedure - Create a participant calibration - Select a participant calibration Create A Participant Calibration - Make sure all analyses of the participant are closed. To close an open analysis, click the button next to it. - Do one of the following: - Choose Participant > Calibrate Participant. - Right-click the participant and choose Calibrate Participant. - Select the Face Model. See Active Face Model - Choose the calibration source: - Images – Select the files in which the participant looks neutral. - Video – Select the video file and scroll to the part where the test participant looks neutral. - Camera – Ask the test participant to look neutral. - Click the Start analysis button. When the calibration is created, the Calibration Effect field shows the facial expressions before and after calibration. - When you are satisfied with the calibration, give it a name and click OK. FaceReader asks whether you want to use this calibration for all future analyses of this participant. Choose Yes if you want this. If you are not satisfied with the calibration, click the Retry with same source button and repeat step 5. Notes - If you chose to use the calibration for all new analyses of this participant in step 6, the calibration is selected automatically in all new analyses of that participant. For the already created analyses you must select the calibration manually and redo the analysis. - To change a calibration for a participant, select the new one, choose Participant > Set calibration as default. - To delete a participant calibration do one of the following: - Choose Participant > Delete calibration. - Unfold the participant item in the Project Explorer. Then right-click the calibration and choose Delete calibration. Select A Participant Calibration IMPORTANT Use the same Face model (see Active Face Model) in the analysis, as was used to create the calibration. To use another face model, first create a new calibration with this model. Then do one of the following: - Select the calibration for a specific analysis - Select the calibration automatically for all future analyses of a participant Select the calibration for a specific analysis - Make sure that continuous calibration is set to No in the Analysis settings window on the bottom-left of the analysis part on your screen. - Click the pencil button next to Selected calibration and select the calibration from the list. Select the calibration automatically for all future analyses of a participant - Open the Participant item and then the Calibrations item in the Project Explorer. - Right-click the calibration and select Set Calibration as Default. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Physical Setup and Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-physical-setup-and-installation Chapter: FaceReader Physical Setup The physical setup of your experiment is crucial for an accurate analysis with FaceReader. The following general guidelines apply: - Place the camera in front of the test participant and slightly below eye level. Make sure your camera provides images with good contrast and brightness. - Good lighting is crucial to get a good image. Avoid direct light, reflections and shadows on the face. Diffuse frontal lighting is desirable. The light intensity or color is less relevant. If possible, place the FaceReader setup in front of a window. Make sure that any windows to the sides of the subject are blinded. Lights from the ceiling, common in most buildings, will produce shadows below the eyebrows and nose. In situations where interior lighting cannot be controlled, stronger lights (e.g., on either side of the monitor or professional photo lights) can be used to negate the effect of other, undesirable, light sources. You can also use (near) infrared light, in combination with a camera that is sensitive to this type of light. Install FaceReader To Install FaceReader - Download the installation file (FaceReader [version number] Setup.exe) from the MyNoldus portal of the Noldus website. If you do not have a MyNoldus account yet, you can create one. - Double-click the file. - As Installation type, select Standard. - Follow the rest of the instructions on your screen to install FaceReader. To Install the Stimulus Presentation Tool (Project Analysis Module Only) If you have the Project Analysis Module, you need the Stimulus Presentation Tool to present stimuli automatically. To install it: - Download the installation file (Stimulus Presentation Tool 5 Setup.exe) from the Noldus website using your MyNoldus account. - Double-click the file to run it. - As Installation type, select Standard. - Follow the rest of the instructions on your screen to install the Stimulus Presentation Tool. Source: FaceReader 10 Quick Start Guide, Noldus Information Technology --- ## FaceReader 10 - Predefined Templates URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-predefined-templates Chapter: FaceReader Define Project Wizard With the Folder Structure of the Video or Image Files Aim To automate adding a large number of participants or analyses. The videos or images are automatically assigned to analyses. Prerequisites - You have a large number of participants, or analyses. - You want to analyze videos or images. - The videos or images of the test participants are stored in a structured way. For example, the videos of the different participants are stored in separate folders. Procedure - Choose File > New > Project Wizard. - Give the project a name, select the location to store it and select Video, or Images from the Source type list. - Select From file structure. The Project Preview window displays the project structure with the selected options. - Under Path, select the root of the folders where your videos or images are stored. - Under Predefined Templates, select one of the following: - one of the Predefined templates - Custom template — Use the building blocks under Choose File Template Parts to create your custom structure. See Custom Template - Click OK when ready. Predefined Templates The File template field shows the building blocks used for this template. For an explanation of the building blocks, see Custom Template. Add All Videos to a Unique Participant File template . Each video found in the folders and subfolders will be added as analysis to a separate participant. Participants will be named Participant 1, Participant 2, etc. The analyses will be named Analysis 1. Video location plays no role here. Folder Equals Participant Name File template \. Each video found in the folders and subfolders will be assigned as analysis to a separate participant. Each participant will get the name of the folder where the video was found. Note that this results in the same person being represented by several "participants" in FaceReader. All analyses will be named Analysis 1. Folder Equals Unique Participant Name File template \. Each participant will get the name of the folders found in the root folder. Each participant name will only be used once. If more videos are found in the same folder, these will be added as analyses to the same participant. The analyses will be named Analysis 1, Analysis 2, ....etc. Folder Equals Participant Index File template \. In case your folders have numbers instead of letters. Each participant will get the folder number and the videos in this folder or subfolders are assigned as analyses to this participant. The analyses will be named Analysis 1, Analysis 2, ....etc. Folder Equals Participant Index, Subfolders Equal Analysis Index File template \\. Use this template when your folders and subfolders have numbers instead of letters. Each subfolder may contain only one video file. Each participant will get the number of the folder directly under the root folder specified in the Path field. Each analysis will get the number of the subfolder and the name of the file. Custom Template To create your structure, click one or more items under Choose File Template Parts. - Use a slash (\) to indicate a new folder. - Use a dot (.) to separate the filename from the extension. ParticipantIndex For folders and files with numerical names. Uses the folder numbers for the participants numbers. UniqueParticipantName Uses the folder or file names for the participant names. Each participant name will be used once. ParticipantName Uses the folder or file names for the participant names. Different participants can have the same name. ParticipantAge Reads the participant age from the file name and enters this as category for the independent variable Age. Example: file name is 32_male_commercial 1.avi Use building blocks _. ParticipantGender Reads the gender from the file name and enters this as category for the independent variable Gender. Example: file name is 32_male_commercial 1.avi Use building blocks: __. You can also combine ParticipantAge and ParticipantGender in the following way: __. AnalysisIndex For subfolders or files with numerical names. Each subfolder may contain only one video file. Uses the folder numbers for the analysis names. Wildcard Allows any character. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Privacy URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-privacy Chapter: FaceReader Privacy Privacy-By-Design FaceReader is installed on-site and adheres to strict privacy-by-design protocols. For example, the software offers the option not to record the test participant's face during the analysis. In this case only meta data are acquired that cannot be related to an identifiable person. Examples of meta data are facial expressions, head pose, age and gender. FaceReader is a software tool for scientific research. FaceReader is not capable of recognizing or identifying faces or people, and therefore unsuitable for surveillance purposes. For more details about applications please refer to our ethics statement on the following web page: https://www.noldus.com/about-noldus/ethics-face-reading GDPR And HIPAA Compliance FaceReader analyzes your participant's face while interacting with the digital content on their screen. When you analyze or record the participant's face, please be aware of requirements for storing personal data. Video and audio of the participant are personally identifiable information and are, therefore, subject to GDPR regulations in Europe and HIPAA regulations in the USA. Facial expressions, video recordings with the test participant's voice, heart rate, breathing rate data are sensitive data. With the correct procedure you can make sure that you comply with privacy regulations. To comply with GDPR or HIPAA regulations, take notice of the following: When you record the participant, or share these recordings, make sure you ask the participant consent for video recording and let him or her sign a consent form. This informed consent form should include: - The purpose of the recordings. If there is a possibility that the recordings will be reused for other studies, describe this explicitly. - Which personally identifiable information is stored. When you do a camera analysis, by default the video is stored, which is personally identifiable information. To switch off video recording, deselect the Record option in the window in which you select your camera. If you enter participant details like their name, age or gender this is also personally identifiable information. We recommend to use generic names, like participant 1, and to use age classes instead of specific ages. Facial expressions, video recordings with the test participant's voice, heart rate, and breathing rate data are sensitive data. Export files may also contain personally identifiable information or sensitive data. - Who will have access to the personally identifiable information. Think of authorized staff directly involved in the study, but also of Noldus support staff in case support is needed. - The retention policy, when the personally identifiable information will be deleted. - The right of subjects to withdraw permission for the use of the personally identifiable information and instructions for the participant to withdraw permission. - The right to data portability and instructions for the participant how to receive their data. - Security and privacy measures taken. In FaceReader, video and data are stored locally on the computer. Take security measurements for the stored videos and describe this in the consent form. For information about Noldus' Privacy Policy with regard to your data, see: https://www.noldus.com/legal/privacy-policy Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Processors: Boolean and Temporal URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-processors-boolean-and-temporal Chapter: FaceReader Processors: Boolean and Temporal Not This processor has a single Boolean value as input (for instance, a condition that is either True or False) and a single Boolean value as output. If the input is True, the output is False and vice versa. If.. Else.. An If.. Else block has three inputs: (1) Condition C (left connector); (2) Numerical value A (top connector); (3) Numerical value B (bottom connector). The output is A if C is True and B if C is False. The screen shot below is part of the definition of the Custom Expression 'Duchenne smile'. The output of the If.. Else.. processor is the average intensity value of Action Unit 12 and Action Unit 6 if Action Unit 6 AND Action Unit 12 are active (that is, have both an intensity value higher than 0.2). The output is 0.2 if one or both Action Units are not active. Temporal The temporal processors are identical to their non-temporal counterparts except for the temporal aspect. The temporal processors calculate the (weighted) average/sum/maximum/minimum over the time (duration) you specify. You can also specify the minimum percentage of valid samples required to produce a valid output. You can use the temporal processors if your custom expression cannot be determined based on a single point in time and requires a history. For the running processors you cannot set any parameters. - Temporal Average — This processor calculates the average of its numerical input values over the specified time. - Temporal Weighted Average — This processor calculates a weighted average of its numerical input values over the specified time. Older results weigh less than more recent results. - Temporal Standard Deviation — This processor calculates the standard deviation of its numerical input values over the specified time. - Temporal First Derivative — This processor calculates the rate of change over the specified time. The output is (value of the last valid frame - value of first valid frame)/duration. - Temporal Sum — This processor calculates the sum of all its numerical input values over the specified time. - Temporal Maximum — This processor compares two or more numerical input values. The output is the highest value. - Temporal Minimum — This processor compares two or more numerical input values. The output is the lowest value. - Temporal Counter — This processor counts the number of times an input value crosses a given threshold in a specified direction. - Running Average — This processor calculates the average value over all previous valid samples. - Running Maximum — This processor calculates the maximum value of all previous valid samples. - Running Minimum — This processor calculates the minimum value of all previous valid samples. - Running Counter — This processor counts the total number of times an input value crosses a given threshold in a specified direction from the beginning of the analysis. Miscellaneous - Constant Value — Use this processor for instance in combination with a Condition to compare the intensity value of an Action Unit with the constant value. See 'Condition' for an example. - Unknown — Use this processor to give a custom expression the value 'Unknown'. In the screenshot below we defined a custom expression that only gives a value if Action Unit 43 has intensity = 1. In the example, the intensity of AU43 < 1. That means that the condition is false and that the output of the If/else processor is B (Unknown). - Pi (π) — The number pi (≈ 3.14159) is a mathematical constant, the ratio of a circle's circumference to its diameter. - e — The number e (Euler's number, ≈ 2.71828) is a mathematical constant. Tip: Click on a processor to read the information that comes with it. Each processor comes with a description and information on what type of input it can have, what the output will be and what parameters you can define. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Project Analysis In Short URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-project-analysis-in-short Chapter: FaceReader Project Analysis In Short Aim - Visualize or tabulate the data that you have acquired and calculate the average intensities of the facial expressions and other parameters for your participant groups. - Compare participant groups and run a t-test to test for significant differences. - Play back your stimulus video together with a video of the participant's face and a Line Chart with the facial expressions and other parameters. - Create heatmaps on your stimuli showing the hotspots that attracted your test participants' attention. - Calculate correlations between data sets and visualize data sets side by side or in a correlation graph. Prerequisites - Your license includes the Project Analysis Module. - Your project includes one or more video analyses or camera analyses. Procedure - Open the Project Analysis: from the Project menu select Open Project Analysis or click the Open project analysis icon above the Participants list. Project Analysis In Short Default FaceReader shows a Line Chart with the average intensities of the facial expressions of all your test participants. See Line Chart for more information about this type of chart. FaceReader also shows the face video of your first test participant. If your project contains stimuli FaceReader will show the first stimulus video/image. If your stimulus is a video — Play the stimulus video and the face video together with the Line Chart. See Visualize your stimulus, participant videos and line chart for more details. - Click one of the tiles for the option of your choice: - Quick Layouts — This option allows you to pick from a couple of charts to give you a first impression of the data. See Quick Layouts for more information. - Pie Chart, Bar Chart, Box Plot, Line Chart or Circumplex Model — Select one of the options to visualize your data. Circumplex Model is only available if you scored stimuli or event markers in your project. See Visualize your data in a chart for more information. - Heatmap — To create a heatmap on one of the stimuli. - Table — To calculate statistics on the analyzed facial expressions and other parameters of all participants, participant groups or single participants. See Calculate statistics and summarize them in a table for more information. - Stimulus — To add your stimulus videos to the visualization. You can play back your stimulus videos together (synchronized) with a Line Chart with the facial expressions and other parameters. See Visualize your stimulus, participant videos and line chart for more information. - Participant — To add your participant face video to the visualization. You can play back your participant videos together (synchronized) with the stimulus video and a Line Chart with the facial expressions and other parameters. See Visualize your stimulus, participant videos and line chart for more information. - Compare — To compare two or more data sets in a chart or table and carry out a t-test to test for significant differences. See Compare data for more information. - Select the data you want to include in your analysis. See Data selection for more information. Your chart/table will appear. Click Save Layout to save the chart/tables you made so you can use them again. Enter a Layout name and click OK. Click Load Layout to open the charts/tables/videos that you saved in your layout. Click Clear Layout to delete all the charts/tables/videos. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Project Analysis Module URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-project-analysis-module Chapter: FaceReader Project Analysis Setup The Project Analysis section contains the following extra options: - Independent Variables - The independent variables Age and Gender are present by default. Choose Project > Independent Variable > Add Independent Variable to add more independent variables, like whether the participants saw the commercial before, or their native language. The Independent Variables panel displays variables such as Gender, Age, Experience with commercial, and Nationality, each represented with a checkbox indicator. Double-click Independent Variables under a participant name to score them. Age and Gender can be estimated by FaceReader, or entered manually. - Stimuli and Event Markers – Define stimuli or event markers (Project menu) to mark episodes of interest. Stimuli have a fixed duration and can be linked to a video or image to show to the test participants. The Stimuli panel shows example stimuli such as "Twins eating" and "Frying insects," each assigned a number for ordering. Stimulus Presentation Tool Use the stimulus presentation tool to automatically show stimuli to the test participants and synchronize them with the analyses. Important: In a two computer setup, synchronize the computer clock times with a time server. See Synchronize computers with a network time protocol in the FaceReader Help for how to do so. On the Computer with FaceReader - Choose File > Settings > Data Export and under External Communication (API and Stimulus Presentation Tool) select the Enable External Control checkbox. - To add tests, open the Tests tab in the bottom pane of the Project Explorer. Then click on the Add test button. - Select the camera and the stimuli to show to the test participants. Optionally, choose to let participants enter their own name, age and gender, perform gaze calibration, randomize the presented stimuli, set the stimulus display size and the length of the pause between the stimuli. On the Test Participant Computer - Start the Stimulus Presentation Tool and follow the instructions to connect with the FaceReader computer. The Connect to FaceReader dialog requires the following fields: - FaceReader ip/host – e.g., localhost - FaceReader port – e.g., 9090 - Temporary storage path – e.g., C:\Users\Public\Documents\Noldus\Stimulus Presentation Tool Click Connect to proceed. - Select a test and click Start. - Fill in the participant details and click Start again, or let the participant do this. The test and analysis start. The Welcome screen prompts the participant to enter their name, gender, and age before clicking Start. Analyze Participants are automatically added when you use the stimulus presentation tool. Also, analyses are automatically carried out. Watch the Model quality bar when the test runs. The bar should cross the dashed line. If this is not the case, improve lighting or reposition your camera. The Model quality bar displays a color-coded indicator ranging from red through yellow to green, showing the quality level of the facial detection model during analysis. Optionally, score event markers during the analysis. Output Apart from the general FaceReader output options (page 15), the Project Analysis section has the following output: - Quick Layouts — This will open a number of charts to give you a first impression of the data. - Pie chart, Bar chart, Box plot, Line Chart or Circumplex model — Circumplex Model is only available if you scored stimuli in your project. Example: A bar chart titled "Twins eating (N = 5)" displays mean emotion scores with baseline correction using "Frying insects" as reference, with Temporal Aggregation: Mean and Participant Aggregation: Mean. Emotions shown include Neutral, Happy, Sad, Angry, Surprised, Scared, Disgusted, and Contempt. - Heatmap — Only available if you used the Stimulus Presentation Tool and tracked the test participant's gaze. The latter is possible with the Advanced Research Module. - Table — To calculate statistics on the analyzed facial expressions and other parameters of all participants, participant groups or single participants. Example table for "Twins eating (N = 5)" with Baseline Correction: None, Temporal Aggregation: Mean, Participant Aggregation: Mean shows the following mean values across all participants: Neutral 0.3521, Happy 0.5033, Sad 0.0387, Angry 0.0320, Surprised 0.0261, Scared 0.0051, Disgusted 0.0055. - Stimulus — To add your stimulus videos to the visualization. You can play back your stimulus videos together (synchronized) with a Line chart with the facial expressions and other parameters. Example: The "Twins eating" stimulus shows a video of two babies eating at a table, with a synchronized line chart below showing emotion data over time. - Participant — To add your participant face video to the visualization. You can play back your participant videos together (synchronized) with the stimulus video and a Line chart with the facial expressions and other parameters. Example: "Participant 3 - Hans - Analysis 1" shows a face video of the participant synchronized with stimulus markers for "Twins eating" and "Frying insects." - Compare — To compare two or more data sets in a chart or table and carry out a t-test to test for significant differences. Example comparison table displays mean and standard deviation values for Sad, Angry, Surprised, and Scared emotions across two data sets. Highlighted cells indicate statistically significant differences between groups. You can select what data to include in the analysis: - Select what parameters to visualize/tabulate. - Select a stimulus or event marker to visualize/tabulate the data during this stimulus/event marker. - Select whether you want to do a baseline correction and visualize/tabulate absolute or relative values of your parameters. - Select how to aggregate data over time. - Select how to aggregate data over test participants. - Select which test participants to include in your analysis. The Bar Chart configuration dialog allows you to: - Select which data you want to use — available emotion parameters include: Angry, Contempt, Disgusted, Happy, Neutral, Sad, Scared, and Surprised. - (Optional) Select the advanced options — including Temporal Aggregation (e.g., Mean) and Participant Aggregation (e.g., Mean). Source: FaceReader 10 Quick Start Guide, Noldus Information Technology --- ## FaceReader 10 - Project Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-project-management Chapter: FaceReader Deactivate Your FaceReader License Aim - To use your Fixed FaceReader license on another computer. - To change a Fixed FaceReader license into a Floating license. - To make sure that FaceReader cannot be used on a certain computer. IMPORTANT If you want to uninstall FaceReader, first deactivate the license otherwise you will lose it. Please contact Noldus Technical Support if this happened. Procedure Deactivate Your Floating License - From the Help menu select License and then Deactivate. - You will get a message that your license key was successfully removed and that FaceReader will exit. Click OK to close the software. Deactivate Your Fixed License From the Help menu select License and then Deactivate and select: - Deactivate Online if the computer is connected to the internet. You will get a message that your license key was successfully removed and that FaceReader will exit. Click OK to close the software. - Deactivate offline if the computer does not have internet connection. Scan the QR code with your smartphone. Click OK to deactivate the license on the PC. You will get a message that your license key was successfully removed and that FaceReader will exit. Click OK to close the software. Follow the QR code link on your smartphone within 24 hours to deactivate your license on the Noldus server. You can also first deactivate your license on the Noldus server and then select the checkbox in the window on your PC to deactivate the license on your PC. Project Management What Do You Want To Do? - Read About Projects - Create A Project - Save A Project - Back Up A Project - Read About The Project Explorer Projects A project groups all the data belonging to one experimental set-up. Your project contains the persons who participated in the experiment, their personal details (name, gender and age and other characteristics that are important for your research), the videos, and the analysis results. The project may also contain Stimuli, Event Markers, Tests and Independent Variables. Create A Project - Do one of the following: - Choose File > New > Project. - In the startup window, under Create a new project, choose New project. - Give the project a name and select a location to store it, or accept the default location. - Continue with Add Your Test Participants. Save A Project - To save a project, choose File > Save or press Ctrl+S. - To save a copy of the project with a different name, choose File > Save As or press Ctrl+Shift+S. IMPORTANT This does not make a copy of the video files and the saved log files. To create a copy of the project with all the videos and log files, see Back Up A Project. IMPORTANT Never shut down the computer by pressing the power button, or cutting off the electricity. Your project data may become lost, even after you saved your project. Always use the Windows shut down feature to close your computer. Back Up A Project IMPORTANT If you use the Save As option, the video files and the saved log files are not copied. To create a copy of the project with all the videos and log files: - Choose File > Project Backup > Copy Media to Project Folder. This makes all the paths in the project relative, so you can copy the entire project to another location. Copy the Stimulus videos to the project folder as well. Choose File > Project Backup > Copy Stimuli to Project Folder. - Choose File > Open Project Folder. This opens the project folder in Windows Explorer. - Select the contents of this folder and copy it. - Paste this to the backup location, for example a network drive or an external harddisk. Notes: - Please be aware that video files are generally very large, so make sure the computer with the project folder has enough disk space. - Create a backup of your project at least once a day and store it in a safe location, for example on a network, or an external hard drive in another building. If you record videos from the test participants' faces, create backups of these videos as well. The Project Explorer The Project Explorer is present on the left side of your screen. It displays the test participants and analyses currently in the project. Expand or double-click elements to view more details. The Multi-Subject Sources tab is only visible if your license includes the Advanced Research Module. Show/Hide The Project Explorer To create more space on your screen for the analysis, you may want to hide the Project Explorer. To do so, click the Hide button in the top-right corner of the Project Explorer. To restore the Project Explorer, click the Project Explorer button. The Project Explorer has a window with four tabs at the bottom of your screen: - Stimuli – See Define Stimuli in Project Analysis - Event Markers – See Define Event Markers in Project Analysis - Independent Variables – See Define Independent Variables in Project Analysis - Tests – See Define A Test in Project Analysis Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - References URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-references Chapter: FaceReader The Vital Signs Module Main Topics - Introduction to the Vital Signs Module - Analyze heart rate, heart rate variability and breathing rate - Analysis in phases - Visualize vital signs Introduction To The Vital Signs Module Vital Signs The Vital Signs Module allows you to measure heart rate, heart rate variability and breathing rate. Heart rate and heart rate variability are measured by means of remote photoplethysmography (RPPG). Breathing rate is measured by detecting upper-body movement associated with respiration. Remote PPG Photoplethysmography is a simple and low-cost optical technique that can be used to detect blood volume changes in the tissue under the skin. It is based on the principle that changes in the blood volume result in changes in the light reflectance of the skin. With each cardiac cycle the heart pumps blood to the periphery. Even though this pressure pulse is somewhat damped by the time it reaches the skin, it is enough to distend the arteries and arterioles in the subcutaneous tissue. PPG is often used non-invasively to make measurements at the skin surface. In remote PPG (RPPG), FaceReader can detect the change in blood volume caused by the pressure pulse when the face is properly illuminated. The amount of light reflected is then measured. When reflectance is plotted against time, each cardiac cycle appears as a peak. This information can be converted to heart rate average and variability. For an overview of the accuracy of the estimated heart rate, see Gudi et al. (2020). References Photoplethysmography Reisner, A. T., Shaltis, P. A., McCombie, D. and Asada, H. H. (2008). Utility of the Photoplethysmogram in Circulatory Monitoring. Anesthesiology, 108, 950-958. http://en.wikipedia.org/wiki/Photoplethysmogram Remote PPG And FaceReader Gudi, A.; Bittner, M.; Van Gemert, J. (2020) Real-time webcam heart rate and variability estimation with clean ground truth for evaluation. Applied Sciences 10(23): 8630. Tasli H. E., Gudi, A., and den Uyl, M. (2014). Integrating Remote PPG in Facial Expression Analysis Framework. Proceedings of the 16th International Conference on Multimodal Interaction, Istanbul, November 12-16, 2014, 74-75. http://www.vicarvision.nl/pub/RPPG_Facial_Expression_Analysis.pdf Please cite the original work in your studies when based on FaceReader's remote PPG. Patent Number The European Patent Office has granted patent EP2960862A1 to Vicarious Perception Technologies for the method for stabilizing vital sign measurements using parametric facial appearance models via remote sensors (https://patents.google.com/patent/EP2960862A1/en). Vital Signs Module With FaceReader's Vital Signs Module, you can analyze heart rate, heart rate variability (HRV), and breathing rate of the test participant without additional hardware other than a suitable webcam. Heart rate variability can be derived from the single heart beats that are used to calculate the heart rate. HRV measures the variability between heart beats, which can give important insights into the physiology of a person as it reflects changes in activation of the autonomic nervous system. With FaceReader, you can obtain the timing of individual heart beats (which can be visualized in FaceReader's heart beat log), as well as HRV measures like RMSSD and SDNN. In addition, FaceReader can measure a test participant's respiration rate. RMSSD One of the most commonly used measures of heart rate variability is the root mean square of successive differences (RMSSD). The differences in time between single heart beats are called RR intervals or interbeat intervals. RRn = beatn+1 - beatn Differences between the RR intervals are called successive differences (SD). SDn = RRn+1 - RRn The RMSSD is the root mean square of two successive RR intervals. The unit of RMSSD is the same as the time unit chosen in equation 1 (usually it is milliseconds). RMSSD = √( 1/(n-1) ∑i=1n (SDn)2 ) SDNN SDNN is the standard deviation of normal to normal R-R intervals. "Normal" means that abnormal beats, like ectopic beats (heart beats that originate outside the right atrium's sinoatrial node), have been removed. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Reporting Display URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-reporting-display Chapter: FaceReader Reporting Display The reporting display is a fully customizable visualization of FaceReader's output. You can use it on a second monitor, or to create visuals in a report or presentation. To Access This Option - Choose View > Reporting Display. - Click the plus sign and choose one of the available windows. For more information on the output in these windows see the links below. - Analysis Visualization Click on the Ellipsis button (...) for visualization options. The same options are available as in the regular output of Facereader. The additional option Show status displays the Model Quality Bar. - Circumplex Model Of Affect Click on the Ellipsis button (...) for visualization options. The same options are available as in the regular output of Facereader. - Custom Expressions Line Chart See Visualize Custom Expressions in The Action Unit Module. This option is available when you have the Action Unit Module and added a Custom Expression to your project. Click on the Ellipsis button (...) to select which custom expression to display. - Emoticon The emoticon dynamically visualizes the test participant's facial expressions. Each expression has a number of features (except 'scared'): - Happy — Smiling mouth. - Sad — Corners of the mouth down and tears dropping from the eyes. - Angry — Red face, eyebrows lowered. - Surprised — Big eyes, raised eyebrows. - Disgusted — Tongue sticking out. - Expression Intensity - Expression Line Chart Click on the Ellipsis button (...) to select the expressions to display in the chart. - Expression Summary Click on the Ellipsis button (...) and choose Show values to display percentages for the facial expressions. - Gaze Angles Line Chart Click on the Ellipsis button (...) to select whether you want to view the changes in the Horizontal or Vertical gaze angle. - Head Orientation Line Chart Click on the Ellipsis button (...) to select whether you want to view the changes in Pitch, Yaw or Roll. - Head Position Line Chart Click on the Ellipsis button (...) to select whether you want to view the changes in the Horizontal, Vertical or Depth position. - Valence And Arousal Line Chart Click on the Ellipsis button (...) to select whether you want to view the Valence or the Arousal or both parameters. - Valence Monitor The Valence Monitor is a three-light indicator. The light is: - Green — The valence of the analyzed frame is above 0.33. - Orange — The valence is between -0.33 and +0.33. - Red — The valence is below -0.33. - Vital Signs This option is available if you have the Vital Signs Module. See Vital Signs window in The Vital Signs Module. - Voice Expression Intensity This option is available if your FaceReader license includes the Voice Analysis Module. See Voice Expression Intensity in The Voice Analysis Module. - Voice Expression Line Chart Click on the Ellipsis button (...) to select the expressions to display in the chart. This option is available if your FaceReader license includes the Voice Analysis Module. See Voice Expression Line Chart in The Voice Analysis Module. - Voice Valence And Arousal Line Chart Click on the Ellipsis button (...) to select whether you want to view the Valence or the Arousal or both parameters. This option is available if your FaceReader license includes the Voice Analysis Module. See Voice Valence and Arousal Line Chart in The Voice Analysis Module. - Voice View This option is available if your FaceReader license includes the Voice Analysis Module. See Voice View in The Voice Analysis Module. General Options All Charts - To position a window in front of or behind another window, click on the Toggle Back/Front icon on the chart. - To Maximize a window, click on the Maximize icon on the chart. - To scale a window, drag the border of the window. - To copy the presentation view, for example to paste it in a report or presentation, click on the Copy icon. - To maximize the entire reporting display, click on the Toggle Full Screen icon in the upper-right corner of the window. - To remove all windows, click on the Reset icon. Line Charts To adjust the Y axis to the maximum value, click on the Ellipsis button (...) and choose Auto Scale Y Axis. Note The Reporting display is persistent. When you open a new project, the reporting display will open with the windows and layout that you selected in your last project. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Run A Test URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-run-a-test Chapter: FaceReader Specify Connection Settings For The Stimulus Presentation Tool Aim To specify the connection settings in FaceReader so that it can communicate with the Stimulus Presentation Tool. Prerequisites - Your FaceReader license includes the Project Analysis Module. - You installed the Stimulus Presentation Tool. See To install the Stimulus Presentation Tool - If you run a test in a two-PC configuration, the two computers are connected, and the appropriate settings were made. See Computer settings for a two computer setup with Stimulus Presentation Tool Procedure - In FaceReader, choose File > Settings > Data Export. - Under External Communication (API and Stimulus Presentation Tool), select Enable External Control. Note Make sure the External Connection Port number is the same as that in the Stimulus Presentation Tool. By default, this is 9090. If you prefer, you can enter another port number. Enter this number also in the Stimulus Presentation Tool. See Specify the connection settings in the Stimulus Presentation Tool so that it can communicate with FaceReader Run A Test Aim To display the Stimuli to the test participants and to carry out the analysis. Prerequisites - Your FaceReader license includes the Project Analysis Module. - You installed the Stimulus Presentation Tool. See To install the Stimulus Presentation Tool - You have defined at least one test in your FaceReader project. See Define a test - If you run a test in a two-PC configuration, the two computers are connected, and the appropriate settings were made. See Computer settings for a two computer setup with Stimulus Presentation Tool - Optionally, the Advanced Research Module to track the test participant's gaze. Procedure - On the test leader's PC, open the FaceReader project. - On the participant PC, start Stimulus Presentation Tool. - Specify the connection settings in the Stimulus Presentation Tool so that it can communicate with FaceReader. In the Connect to FaceReader window, under FaceReader IP/Host enter the IP address of the computer with FaceReader. In a One computer setup, leave the default address 127.0.0.1. This is identified as the same PC. Under FaceReader Port leave 9090 or enter the number entered in FaceReader in step 1. When necessary, change the Temporary storage path of the participant PC where data are stored during the test. When ready, click Connect. - In the Select Test window, choose a test from the Available Tests list, then click Start. If the test you require is not listed, in FaceReader open the project that contains that test. Next, in the Stimulus Presentation Tool click the Refresh button. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Score Independent Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-score-independent-variables Chapter: FaceReader Define Independent Variables Aim To define factors that can vary but are constant per participant and can, potentially, affect the analysis results. Prerequisite Your FaceReader license includes the Project Analysis Module. Define Independent Variables - Choose Project > Independent Variables > Add Independent Variable. - Give a name to the variable, for example Experience level. - Choose one of the following: Numerical – Numerical variable values can have decimals and can also be negative. Nominal – Enter the independent variables categories in the Categories field. Click the Plus button to add the category. Define at least two categories for each independent variable. Notes - To delete or edit an independent variable, open the Independent Variables tab at the bottom of the Project Explorer. Right-click the independent variable you want to delete or edit and select the option you require. Score Independent Variables Aim To enter a value for each Independent Variable. Prerequisites - Your FaceReader license includes the Project Analysis Module. - You defined independent variables. Procedure - Expand the Participant item in the Project Explorer. - Double-click Independent Variables. - Click the pencil button next to the Independent Variable. - Select the category. In the example below, this would mean defining the native language of each participant. Note The Independent Variables item in the Project Explorer displays a warning icon if the values have not been scored yet for a participant. Open the participant item and double-click Independent Variables. Then fill in the values. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Score Stimuli URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-score-stimuli Chapter: FaceReader Score Stimuli Aim To mark the time the Stimulus was shown to the test participant. Prerequisites - Your license includes the Project Analysis Module. - You defined Stimuli. See Define Stimuli - You have a video or camera analysis. Procedure To Score a Stimulus During an Analysis - Automatically — Use The Stimulus Presentation Tool - Manually — Press the trigger key that is associated with your Stimulus. If you have the Timeline window open, a bar appears with the same length as the Stimulus duration that you chose when you created the Stimulus. You can press the Stimulus trigger key for each time the Stimulus starts. To Score a Stimulus After an Analysis Open the Timeline window and scroll the video to the position where the Stimulus starts. Then press the Stimulus trigger key. A question appears whether you want to score the Stimulus at that point. Choose Yes. Notes - Multiple instances of the same Stimulus may not overlap. Therefore, do not start a Stimulus when the previous instance of this Stimulus has not ended. - Do not score a Stimulus when the remaining video time is shorter than the Stimulus duration. If you do so, opening the Scored Stimulus window automatically moves the Stimulus start time to the latest possible moment in that video. - Scored Stimuli appear in the Project Explorer as dots above the analysis bar. Expand the Analysis and Scored Stimuli items to view the scored Stimuli. - To copy scored Stimuli to other participants or analyses, unfold the analysis and double-click Scored Stimuli. Click the Stimulus you want to copy. Click Scored Stimuli at the top of the window that opens, and choose one of the options under Copy To. - To make sure the analysis is not interrupted, FaceReader does not give a warning during the analysis if you score overlapping Stimuli or score a Stimulus that continues after the end of the analysis. Instead, an error mark will appear in the Project Explorer and you must correct the scored Stimuli after the analysis is finished. To do so, double-click Scored Stimuli or one of the lines. Alternatively, right-click Scored Stimuli, then select Edit Analysis, and then Edit Scored Stimuli & Event Markers. The Scored Stimuli window opens. The time periods in which Stimuli of the same type are overlapping are marked in red. Move the Stimuli to their correct position, so that they are no longer overlapping. To delete a scored Stimulus, click the Delete Scored Marker button. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Set Up The Observer XT To Work With FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-set-up-the-observer-xt-to-work-with-facereader Chapter: FaceReader Set Up FaceReader To Work With The Observer XT Procedure - Choose File > Set Default camera, choose your camera and select the option Record. - Choose File > Settings > Data Export. - Under External Communication (N-Linx), select Enable N-Linx. - If FaceReader and N-Linx Server run on the same computer, leave the default address localhost in the N-Linx server address field. If the programs run on different computers, enter the IP address or computer name of the computer with N-Linx Server. To find that name, open the Control Panel and choose System. - In the N-Linx server port field, leave the default port 5672. Ask your system administrator for assistance if this port is in use by another program. - Under Export (Detailed Log, ODX, N-Linx and API), choose which data to send to The Observer XT. Application Settings - Data Export Export (Detailed Log, ODX, N-Linx and API) - Action units - Export action units as continuous values - Export the unilateral action unit intensities (left and right) - Consumption behavior - Custom expressions - Facial states - Gaze data - Gaze angles - Head orientation - Head position - Vital signs - Valence and arousal - Expressions from voice Set Up The Observer XT To Work With FaceReader Prerequisites - FaceReader is open. - You followed the steps in Set up FaceReader to work with The Observer XT Procedure - In The Observer XT, open your project and choose File > Preferences > N-Linx Settings. - Select Use N-Linx server to connect with other applications. - In the Services address field, enter the name of the computer with N-Linx Server. Enter localhost if N-Linx Server and The Observer XT run on the same computer. - In the Services port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. - Click Test connection. If connection with N-Linx Server is found, the Status will change to Connected. If not, enter the correct settings and click Test connection again. - Click OK. - Choose Setup > Project Setup. - Select Live Observation. The Devices window now opens. If not, click the Devices button. - Double-click the line FaceReader -[computer name] - If you have multiple instances of FaceReader connected to The Observer XT, enter a unique name in the Identify device as field. This name will be added as Subject to the Coding Scheme. If you leave the Identify device as field empty, no subject will be added. - Select the FaceReader settings for your experiment. For an explanation of the settings, see: Smoothen classifications – Classification Continuous calibration – Procedure To use Participant calibration (see Create a participant calibration), select that option manually in FaceReader. Face model – Active Face Model Image rotation – Rotation - Click OK and select the checkbox in front of the line FaceReader -[computer name]. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Setup and Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-setup-and-analysis Chapter: FaceReader Work With FaceReader Setup - Dependent on your license, do one of the following: - If you have a software license key, start FaceReader and activate your license. You can choose between a Floating or a Computer-locked activation. - Floating License - Online Connection Required: Choose Floating if you want to be flexible on which computer you use FaceReader. Your computer needs to be connected to the Internet every time when starting up the software. - Computer-Locked License - Online Activation: A Fixed activation is linked to one computer. Your computer must have an Internet connection to activate/deactivate a fixed license. After you have activated the license you can use FaceReader without an Internet connection. - Computer-Locked License - Offline Activation: Use this option if your computer does not have an Internet connection. You need to use a smartphone with Internet instead. - If you have a hardware key, insert it into the computer and open FaceReader. - Create a new Project (File > New > Project). Give the project a name and select a location to store it, or accept the default location. - Choose Participant > Add Participant. Enter a name or identification code for the participant. You can also automatically add participants by selecting a video with multiple faces on the Multi-Subject Sources tab. - The gender and age of your participants are added as independent variables and are automatically estimated by FaceReader. To select the age and gender manually, double-click the participant name. Click on the pencil button next to the independent variable to enter the values. - Add one or more analyses for each participant and choose to analyze from video, live from your camera or from images. To do so, select the participant for which you want to add an analysis in the Project Explorer. Click on the Video, Camera or Image button on the toolbar to add the appropriate analysis. It is not possible to mix image analyses with camera or video analyses. The Multi-Subject Sources tab is only available if you have the Advanced Research Module. On this tab click the Add multi-subject icon and select the video that you want to analyze. - To carry out a camera analysis, select the option Use as default camera if you always use this camera. To record audio, select your microphone. Optionally, select Record to create a video file of the test participant's face. The video will always be saved at a frame rate of 15 frames per second. To add multiple video analyses to a participant, right-click the participant's name, select Add Multiple Video Analyses, and select your videos. Analyze - Click on the magnifying glass button next to an analysis to open it. - Check the options for this analysis by clicking the Analysis Settings button at the bottom of your screen. To create default settings for each new analysis, choose File > Settings. Open the tab Default Analysis Settings and make your selection. The Application Settings panel includes the following sections: General, Default Analysis Settings, Analysis Options, Data Export, Visualization, and Advanced. Under Default Analysis Settings, you can select the Active Face Model. Available face models include General, Baby, and EastAsian. A Continuous calibration option is also available. See the FaceReader Help for an explanation of the options. Press F1 in the program to open it. Choose File > Settings > Analysis Options and select Action units, Consumption behavior, Vital signs and/or Voice analysis to activate the Consumption Behavior Module, the Vital Signs Module and/or the Voice Analysis Module. Important If you select the Baby Face model, Facial expressions are not available as analysis output. You will obtain Action Unit intensities. See Action Unit Module in the FaceReader Help for more information. - Click on the Start analysis button at the bottom of your screen to carry out the analysis. - Tip To analyze all analyses at once, click on the Start batch analysis button on the toolbar. Important Bear in mind that carrying out batch analysis on a high number of long videos with a high resolution and frame rate may cause problems. - The Model quality bar should cross the dashed line. If this is not the case, improve lighting or reposition your camera. Source: FaceReader 10 Quick Start Guide, Noldus Information Technology --- ## FaceReader 10 - Start FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-start-facereader Chapter: FaceReader Set Up Your Project Main Topics - Start FaceReader - Project Management - Add Your Test Participants - Add Analysis Input - Project Wizard Start FaceReader Aim To start working with FaceReader. Procedure The procedure depends on your license type. You may either have: - A software license key. - One or more hardware keys. Activate FaceReader With A Software License Key - Start FaceReader, select the option Activate software license key and click OK. - Select either Floating or Fixed and click OK. What Is The Difference Between A Floating And A Fixed Activation? When you have a software license key you can choose between a Floating and a Fixed activation. - Floating activation — Choose this option if you want to be flexible on which computer you use FaceReader. If you bought, for instance, a software key with two licenses, you can simultaneously use the software on, for instance, the FaceReader computer in your lab and on the computer in your office. If your student wants to use FaceReader as well (on his/her personal laptop) then this is possible. You can install and activate FaceReader on as many computers as you want but with two licenses you can use the software only on two PCs at a time. If you want to use FaceReader on a third PC the software should not be running on one of the other two PCs. Please note that a computer must have an internet connection to activate and work with a Floating license. - Fixed activation — A Fixed activation is linked to one computer. The advantage of having a Fixed activation is that you do not need an internet connection to work with the software. If you bought a software key with, for instance, two licenses, you can activate FaceReader on two computers (if you choose 'Fixed' for both licenses). If you want to use FaceReader on a third computer, you have to deactivate one of the licenses and activate it on the new computer (either as Fixed or as Floating). See Deactivate your FaceReader license for more information. Please note that a computer must have an internet connection to activate/deactivate a Fixed license. After you have activated the license you can use FaceReader without internet. Alternatively, you can activate/deactivate your license using your smartphone. Activate Your Floating License Enter your Activation key and click OK. The software now opens. Activate Your Fixed License In An Online Mode Enter the Activation key that you received with the software and select: - Activate Online if the PC is connected to the internet. When you click OK the FaceReader software opens. - Activate Offline if the PC does not have an internet connection. Scan the QR code with your smartphone and click WEB. Copy the Computer key shown on your smartphone to the Computer key field on the FaceReader PC and click OK. The FaceReader software opens. Activate Your Fixed License In An Offline Mode Enter the Activation key that you received with the software and select: - Activate Online if the PC is connected to the internet. When you click OK the FaceReader software opens. - Activate Offline if the PC does not have an internet connection. Scan the QR code with your smartphone and click WEB. Copy the Computer key shown on your smartphone to the Computer key field on the FaceReader PC and click OK. The FaceReader software opens. If You Have A Hardware Key - Plug the key into a USB port on your computer. If the hardware key is correctly connected, a red light is visible inside the key. - Now start FaceReader. Keep the key inserted in your computer while you work with FaceReader. IMPORTANT The hardware key is your FaceReader license. This is an important piece of equipment. It is sensitive and can be easily damaged. Please be careful with the hardware key and make sure you do not lose it. You will need to pay for a new license if you do so. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Supported Video Formats URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-supported-video-formats Chapter: FaceReader Video and Image Formats Supported Video Formats FaceReader supports the following video formats: Container Code Name/Encoder mpgmpg1MPEG-1 Part 2 mpgmpg2MPEG-2 mpgH264H.264/ MPEG-4 mpgH265H.265/ MPEG-4 vob (DVD)mpg2MPEG-2 mp4mp4vMPEG-4 Video movmp4vMPEG-4 Quicktime aviXVIDXviD ISO MPEG-4 aviXVIDXviD 1.1.0 Final aviDIB (_RGB)BI_RGB Raw Bitmap aviDIV3DivX 3 Low-Motion aviDIV5DivX 5.x/6.x aviDIVXDivX 4 avidvsdDVC/DV Video aviDX50DivX 6.0.0 aviDX50DivX 5.x aviCRAMMicrosoft Video 1 avicvidCinepak aviIV32Indeo 3.x aviMJPGMotion JPEG aviMP42S-MPEG 4 version 2 aviWMV3WMP v9 (VC-1 Simple/Main) asf (.wmv)WMV1WMP v7 asf (.wmv)WMV2WMP v8 asf (.wmv)WMV3WMP v9 (VC-1 Simple/Main) asfMP43S-Mpeg 4 version 3 3gps263ITU H.263 video (3GPP) Notes - The container is not the same as the file extension. Different containers can have the same file extension. - If you are not sure what the format of your video files is, you can use a program like GSpot to find this out. To download GSpot (free of charge): http://www.headbands.com/gspot Video File Extensions in Project Wizard The following video file extensions can be used in combination with the project wizard: - .mpg - .mpeg - .avi - .wmv - .mov - .asf - .3gp - .vob - .mp4 - .mkv - .flv Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Synchronize Computers With A Network Time Protocol URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-synchronize-computers-with-a-network-time-protocol Chapter: FaceReader Synchronize Computers With A Network Time Protocol Aim To synchronize face analysis with stimulus presentation. The clocks of the test participant PC and the FaceReader PC must be exactly the same. We recommend to set the two clocks to the same time using a Network Time Protocol (NTP) server. Noldus has tested the Stimulus Presentation Tool with NetTime version 3.14. Prerequisite You use the Stimulus Presentation Tool on another computer than the one with FaceReader. Procedure The following steps are needed on both PCs: - Install NetTime - Adjust the NetTime Settings - Create exceptions for NetTime in Windows Firewall - Before the start of a test with Stimulus Presentation Tool, synchronize the two PCs. You can also choose to do this automatically at regular intervals (minimum 15 minutes). See Synchronize The Test PC To The FaceReader PC Install NetTime Do the following on both FaceReader and test PCs: - Browse to http://www.timesynctool.com, and download the latest version of NetTimeSetup.exe. - Run the installation file. During installation, select Install as Service (Recommended). Adjust The NetTime Settings - Click the arrow in the lower-right corner of your screen to open the system tray. - Click the Network Time Synchronization icon. - Click Settings. - Under Hostname or IP Address: - For the FaceReader PC — Leave the Time Servers names as shown in the next table. - For the test PC — In the first Time Servers field, enter the name of the FaceReader PC, and delete all other external Time Servers. See the following table. FaceReader PC Test PC Time Servers 0.nettime.pool.ntp.org [FaceReader PC's name] 1.nettime.pool.ntp.org [empty] 2.nettime.pool.ntp.org [empty] 3.nettime.pool.ntp.org [empty] Update Interval 15 minutes 60 seconds To find the name of a PC, right-click My Computer and choose Properties. - Choose SNTP as Protocol and 123 as Port. - Next to Update Interval enter (see also the table above): - For the FaceReader PC — 15 minutes. - For the test PC — 60 seconds. - For the FaceReader PC only — Select Allow other computers to sync to this computer. - For both PCs — - Select Show NetTime icon in the system tray at login and Start NetTime service at bootup. - De-select Demote Servers after [ ] failures. - Next to If time adjustment greater than, select 10 milliseconds, then Adjust System Time. - Click OK. When a warning appears about Update Intervals being lower than 10 minutes (on the test PC), click No. Create Exceptions For NetTime In Windows Firewall To prevent that syncing fails because of the Firewall, create exceptions on both PCs as follows. - In the Windows' Search field, type firewall, and under the results click Windows Defender Firewall. - Turn on the firewall for all networks, then click OK. - Click Advanced Settings. - Inbound Rule - On the left panel of the Windows Defender Firewall and Advanced Security window, click Inbound Rules and on the right panel under Actions choose New Rule. - In the New Inbound Rule Wizard, on the Rule Type page, choose Program, then click Next>. - On the Program page, select This Program path, click Browse and select the file C:\ProgramFiles (x86)\NetTime\NetTimeService.exe. - Then click Open and Next>. - On the Action page select Allow the connection, then click Next>. - On the Profile page select all options Domain, Private, and Public. Then click Next>. - On the Name page, enter a Name (for example NetTime Service). Then click Finish. - Outbound Rule - On the left panel of the Windows Defender Firewall and Advanced Security window, click Outbound Rules and on the right panel under Actions choose New Rule. - Repeat step 4 above to complete the Outbound Rule. Make sure you choose the same options as for the Inbound Rule. - Repeat all steps above for the other PC. Note If you followed all procedures for establishing Firewall exceptions (Create exceptions in Windows Firewall for Stimulus Presentation Tool and Create exceptions for NetTime in Windows Firewall), each computer should have two Inbound Rules and two Outbound Rules: - One for the port (for communication between FaceReader and Stimulus Presentation Tool) - One for NetTime Service. Synchronize The Test PC To The FaceReader PC - Always start the test PC after starting the FaceReader PC. This ensures that the test PC always finds its time server. - On the test PC, click the arrow in the lower-right corner of your screen to open the system tray. - Click the Network Time Synchronization icon. - Make sure that the first item under Server Name is the name of the FaceReader PC. If this is not the case, click Settings and enter the FaceReader PC's name for the first time server. See Adjust The NetTime Settings - Click the Update Now button. The Offset and Lag are updated. Please note that you may get an error if the test PC is in another network. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - System Requirements URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-system-requirements Chapter: FaceReader Installation Main Topics - System requirements - Software license key or hardware key - The steps to install FaceReader - Upgrade to FaceReader 10 - FaceReader trial version - Camera and accessories System Requirements Operating System FaceReader has been thoroughly tested using a US English version of Windows 11 (64 bit Professional edition). To check which version you have, type System information in the App window. Note the information in the OS Name, Version, and System Type fields. Language Support Like any software package, it remains possible that minor differences in the operating systems of certain local language versions may affect how well the program runs. If you encounter a problem of this sort, please contact Noldus Technical Support. Computer If you order a complete solution from Noldus Information Technology, you will obtain a Dell Precision™ T3680 Workstation (or its successor), or a Dell Precision™ 3591 mobile workstation (or its successor) with the FaceReader software installed and ready to use. Technical Specifications Dell Precision T3680 - Processor: Intel Core i7 14700 - Internal memory: 32 GB or more - Hard disk: 1 TB - Graphics card: 8 GB NVIDIA Quadro T1000 or better Technical Specifications Dell Precision 3591 Mobile Workstation - Processor Intel Core Ultra 7 155H - Memory: 16 GB - 1st Hard-disk: M.2 512 GB PCIe - Graphics card: RTX 1000 Ada Other Computers If you choose to order a PC from another supplier, you can use the above specifications as a guideline. We recommend that you use a professional workstation. It is possible to buy consumer-range computers with a high processor speed and plenty of memory, but in order to remain competitive regarding price, the manufacturers often economize on the underlying system architecture. That means those computers are suitable for home use, but not for running professional scientific software. You should select a computer which is intended for professional use or labeled by the manufacturer as a workstation. We, therefore, recommend to use the specifications of the Dell Precision 3591 mobile workstation that are mentioned above if you prefer to use FaceReader on a notebook. A CPU with AVX is required when using the Consumption Behavior Module. Camera Supported Cameras We tested FaceReader with the following cameras: - Logitech BRIO (USB3) - Microsoft LifeCam Studio (USB2) - Axis M1065-L (IP-camera) - Logitech C920, C922, C925e, C930e See also Camera and Accessories The Logitech BRIO is not suitable for measuring heart rate and heart rate variability. Use a Logitech C920, C922, C925e or C930e with the Vital Signs module. Internet Connection If you are using an IP camera, you need a fast Internet connection for this set-up to work. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Technical Information and Requirements URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-technical-information-and-requirements Chapter: FaceReader FaceReader 10 - Technical Information and Requirements Background Information How Does It Work? For details about how FaceReader works, please contact your representative at Noldus or download from our website: White Paper – FaceReader Methodology. The actual accuracy depends on the quality of the input and the environmental circumstances. As an indication, you may expect an expression recognition accuracy of 99% when using high-quality image material. It is essential to compare the performance with the performance of a human observer as facial coder, rather than for example a question list completed by the test participant afterwards. For more details about performance and accuracy, please read FaceReader AU Module Validation (available via your representative at Noldus). Technical Guidelines There are a number of limitations to keep in mind before starting to use FaceReader: - Glasses may hinder classification — especially thick and dark frames can reduce performance significantly. A polarization filter can help to reduce reflection in the glasses. - Ethnic groups — FaceReader is trained to work with people from different ethnicities. - Acceptable pose, movement, and rotation of the test participant are limited — the test participant should stand or sit, and look into the camera frontally (angle <45°). - FaceReader can analyze one face at a time — if there are more faces in an image, these can be analyzed in different runs, provided the positions do not change significantly. It's also possible to use multi-subject analysis with video. FaceReader will automatically create separate analyses for up to eight different people in one video. Miscellaneous Two Different Licensing Systems Available - Floating software license — a floating license offers the flexibility to use your software on any internet-connected computer. This means you can easily switch the license between devices, enabling you to work from any location, whether you're at the office, your lab, the train, or at home. Licensing License Types - Floating Software License — A floating license requires an internet connection to start up your software. The software itself runs on your computer and stores your data in any safe location you choose. It's also easier to share software access with your team. - Fixed Software License — A fixed license allows you to run the software on a specific computer without the need for internet access. After a one-time online activation, you can work offline. This solution is ideal for environments with limited or restricted internet connectivity. You can also move your license to a new computer, providing you with flexibility while still maintaining a secure, stable setup. Store your data in any safe location you choose. Documentation The documentation consists of a comprehensive reference manual, which is included in HTML5 format with the software. Documentation can also be downloaded from MyNoldus. Languages When installing the application, you can choose for an English or Chinese (simplified) version of the user interface. Documentation is available in both languages. System Requirements Computer If you order a complete solution from Noldus Information Technology, you will obtain a Dell Pro Max Tower T2 FCT2250 (or its successor) which is optimized for this application and with the FaceReader software installed and ready to use. When using your own computer, you need: - Windows 11 - CPU — Intel Core i5 8th generation or higher - AMD — Ryzen 5 4000 series or higher - Support for AVX2 or higher - RAM — minimum of 8GB FaceReader was tested with a Dell Pro Max Tower T2: - Processor — Intel Core Ultra 7 Serie 2 (20 Core, 30MB Cache, 2.4GHz) - Internal memory — 8GB GDDR6 SDRAM - Graphics card — NVIDIA RTX A1000 Operating System FaceReader has been thoroughly tested using a US English version of Windows 11 Pro (64-bit). Like any software package, it is possible that minor differences in the operating systems of certain local language versions may affect how well FaceReader runs. Camera CCD webcam with a resolution of at least 640x480 pixels or Imaging Source USB. We strongly recommend that you use a high-quality webcam. Simple webcams are not suitable. You can also use an IP camera. For use of FaceReader in areas with low light conditions, it is possible to use infrared (IR) cameras. In this case it is not possible to analyze heart rate or heart rate variability with the RPPG module, because this requires color video or camera images. For an optimal RPPG measurement, we recommend to use videos with a resolution of 1280 x 720 pixels and a frame rate of at least 15 fps, but preferably 30 fps. Customer Service and Support Technical Support Noldus prides itself in superior customer support provided by technically skilled support engineers in our helpdesks, located in The Netherlands, Germany, USA west coast, USA east coast, and China. As a registered user, you are entitled to technical support as part of NoldusCare. Technical support questions can be submitted via MyNoldus, where you can also find an archive of Frequently Asked Questions and Tips and Tricks. You will also receive free subscription to Noldus Newsline, which informs you about new product developments, applications, and tips and tricks. Consulting Services Our customer support goes far beyond solving technical problems. Our staff includes consultants with an academic degree in the behavioral sciences, as well as qualified engineers. They are happy to help you with research problems related to the use of our solutions, the design of your experimental set-up, the choice of the appropriate hardware for your application, etc. Source: FaceReader 10 Technical Specifications, Noldus Information Technology --- ## FaceReader 10 - Technical Support URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-technical-support Chapter: FaceReader Technical Support FaceReader Help To open FaceReader Help, press F1 or choose Help > Help. There is also a shortcut to FaceReader Help on the desktop and in the Start menu of the computer with FaceReader. Use the Search function to find information on the topic you are looking for. Help Menu FaceReader's Help menu contains the following options: - Help – Opens the FaceReader Help. - Noldus Online - FaceReader Home Page — Links to the FaceReader section on the Noldus website. - Check for Updates — Brings you to the MyNoldus section on the Noldus website. Create a new account or log into your existing account. Under Downloads click on Software and documentation and check whether there are updates available. - Contact Help Desk — Brings you to the MyNoldus section on the Noldus website. Create a new account or log into your existing account. Under Get support you will find the contact details of the help desk in your region, you can view the status of your current support cases or submit a new support case. - Customer Support Center — Brings you to the MyNoldus section on the Noldus website. Create a new account or log into your existing account. On your MyNoldus page you can find the licenses and NoldusCare contracts associated with your account, you can download the latest version of the software, manuals and sample projects, contact Support or request a Sales visit. - Report an Issue — You are forwarded to an online form where you can report your issue. Noldus Support will contact you after they received the form. - FaceReader Online — This is a link to the FaceReader Online section on the Noldus website. - FaceReader SDK — This brings you to the FaceReader SDK portal. You can fill out an SDK (software development kit) request form. - License - Deactivate — This option is available if you activated FaceReader with a software license key. See Deactivate your FaceReader license for the procedure to follow. - Upgrade — Clicking this option opens the Upgrade Key dialog box. The dialog box contains your license number. It opens automatically when you start FaceReader for the first time after installation and FaceReader detects that you have a hardware key for an earlier version. See Upgrade the license. - About – Choose this option to see details of exactly which version of FaceReader you are using, the serial number of your software and what modules have been enabled. Help Desk If you have any problems, questions, remarks or comments, please let us know. From the Help menu select Noldus Online and then Contact Help Desk or browse to https://my.noldus.com. This brings you to the MyNoldus section on the Noldus website. Create a new account or log into your existing account. Under Get support you will find the contact details of the help desk in your region, you can view the status of your current support cases or submit a new support case. We offer 24 hour support via several help desks in different time zones. Check the FaceReader Online Help before contacting our support department. Press F1 to open it, then use the search function to find the topic you are having problems with. Before you contact Technical Support, please have the version number and license number of your copy of FaceReader available. To find these numbers, choose Help > About. In order to provide adequate support, it is possible that we request you to supply us with video recordings made by your organization. Since May 25th 2018 the new GDPR rules apply to all people in the EEA (EU + Norway, Iceland and Liechtenstein). For this reason we need your signed consent that you agree with the fact that you have given us permission to use these video recordings. Please be aware that the persons who are recognizable in the videos also have to give consent that the videos are sent to Noldus Information Technology BV and our technology partners, and that it is your responsibility to arrange this consent. More information regarding our Privacy policy can be found at: https://www.noldus.com/legal/privacy-policy NoldusCare Your FaceReader license includes one year NoldusCare. NoldusCare extends the standard service you are entitled to and provides peace of mind at reasonable cost. Please look on our web site for more information. We also recommend a training upon installation of FaceReader. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - The Observer XT Sample Projects with FaceReader Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-the-observer-xt-sample-projects-with-facereader-data Chapter: FaceReader The Observer XT Sample Projects with FaceReader Data On the MyNoldus portal of the Noldus website (my.noldus.com) under The Observer XT > Downloads > Sample projects, you can find two sample projects with FaceReader data for The Observer XT. Child FaceReader In this sample project the facial expressions of a child playing an online game are recorded in a media file and analyzed with FaceReader. Simultaneously, the Noldus screen capture device is used to create a media file of the monitor. With an Event marker the time intervals during which the child looks away were marked in FaceReader. FaceReader data, with Action Units, Stimuli and Event markers, and video files were imported into The Observer XT. For a full description of this sample project you can download the PDF file "Description of sample projects of The Observer XT - psychology usability ergonomics" from The Observer XT section of the Noldus website. You need to register and login to be able to download this file. https://my.noldus.com FaceReader & The Observer In this sample project two test participants test the taste of three fruit juices. The time periods after the test participants drank each fruit juice were marked with Event markers. Each participant has been videotaped with two cameras, a webcam (for analysis in FaceReader) and a camcorder (to see what cup the participant takes). The FaceReader log files (Observer log and Detailed log), with Action Units, Stimuli and Event markers, have been imported into The Observer XT. The test participants' behavior has been manually scored. In the Data profile Intervals by fruit juices, the time intervals after the participants drank each fruit juice were separated using the imported FaceReader Event markers Fruit juice 1, Fruit juice 2 and Fruit juice 3, respectively. Under Behavior Analysis, you can find the archived Behavior Analysis State Expression Values per fruit juice, with an accompanying chart. For this Behavior analysis the data profile 'Intervals by fruit juices' was used. Video Files You can download the associated media files from the MyNoldus portal. Before opening the sample projects, make sure to copy the media files to the default Video files folder of The Observer XT: C:\Users\Public\Public Documents\Noldus\The Observer XT\Video Files. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - The Steps To Install FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-the-steps-to-install-facereader Chapter: FaceReader Software License Key Or Hardware Key A license for FaceReader comes with either a software license key or a hardware key. The license determines which options are available to you. See Modules Software License Key Your software license key makes either one or multiple activations of the software possible, depending on the number of licenses that you purchased and the type of activation that you choose. For information on how to activate your license see Activate FaceReader with a software license key. Hardware Key A hardware key is a very important piece of equipment, as it represents the full value of your license and cannot be replaced if lost. You can install FaceReader on more than one computer. However, to work with the program you need to insert the hardware key into one of the computer's USB ports. IMPORTANT Please make sure that you do not lose the key! You will need to pay for a new license if so. Also be careful with it, because it is sensitive and can be easily damaged. The drivers for the hardware key are installed together with FaceReader. First install FaceReader with the drivers for the hardware key, then connect the hardware key to the computer. If you connect the hardware key first, other drivers are automatically installed which may lead to incorrect functioning of the hardware key. When the hardware key is installed and connected properly, a red light glows inside it. The Steps To Install FaceReader Aim To set up the computer to work with FaceReader. Prerequisites - You have a license for FaceReader. This can be a software license key or a hardware key. See Start FaceReader - You downloaded the FaceReader installation file from the MyNoldus portal (my.noldus.com). - You did not order a computer with FaceReader from Noldus IT. If you did, all your software and any internal hardware is already installed and tested and you can skip this topic. - You have administrator rights on the computer for FaceReader. This means you either are the system administrator or a member of the Windows group Administrators and have been assigned administrator rights. - You checked the packing list to make sure all the components are present. If any of the components listed is missing or damaged, please report this to Noldus IT immediately. - Your computer meets the System requirements needed for FaceReader 10. Procedure Carry out the following steps: - Turn off automatic device driver installation and automatic updates - Select correct power options in Windows 10 - Install FaceReader Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - The Stimulus Presentation Tool URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-the-stimulus-presentation-tool Chapter: FaceReader The Stimulus Presentation Tool What Is The Stimulus Presentation Tool? FaceReader is often used to analyze how a subject responds to one or more Stimuli in form of video, for example video commercials. Synchronizing the display of a Stimulus with the trigger of the corresponding Stimulus marker in FaceReader is essential. With FaceReader and the Stimulus Presentation Tool, you can: - Define the Stimuli to be presented, organized in a test (see below). - Present the Stimuli while FaceReader analyzes the test participant's face. - Automatically synchronize FaceReader data with Stimulus trigger markers. - Track the test participant's gaze with the Advanced Research Module. Tests A test is a collection of video Stimuli being presented to a test participant. You can store one or more tests in your FaceReader project. The Stimulus Presentation Tool displays the Stimuli during the test while FaceReader records and/or analyzes the participant's face. Furthermore: - A test includes independent variables, like Gender, Age, or any other variable of interest defined in the project. - Presentation of Stimuli can be randomized. Software You Need - FaceReader with the Project Analysis Module. - The Stimulus Presentation Tool. - The Advanced Research Module if you want to track the test participant's gaze. - Recommended for two-PC configurations: a Network Time Protocol tool to synchronize computers. See Synchronize computers with a network time protocol To Install The Stimulus Presentation Tool - Download the installation file Stimulus Presentation Tool 5 Setup.exe from the MyNoldus portal (my.noldus.com) and run it. - Follow the instructions on the screen. By default, the Stimulus Presentation Tool is installed in the following location: C:\Program Files\Noldus\Stimulus Presentation Tool 5. To Upgrade The Stimulus Presentation Tool If you upgraded FaceReader from version 6, 7, 8 or 9 and have Stimulus Presentation Tool version 1, 2, 3 or 4, there is no need to uninstall the previous version. However, version 1 works only with FaceReader 6, version 2 only with FaceReader 7, version 3 only with FaceReader 8 and version 4 only with FaceReader 9. Computer Configurations One Computer In this configuration, the test participant uses a computer (for example the Noldus Portable Observation Lab) where both FaceReader and the Stimulus Presentation Tool are installed. Two Computers In this configuration, the computer of the test participant has the Stimulus Presentation Tool installed and running. On the test leader computer, FaceReader is installed and running. The two computers are connected through a network. The diagram above illustrates a two-computer setup where the Stimulus Presentation Tool runs on the participant's PC and FaceReader runs on the test leader's PC, both connected via a local network. To allow proper communication between the FaceReader PC and the test participant's PC, follow the procedure in Computer settings for a two computer setup with Stimulus Presentation Tool first. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Timeline URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-timeline Chapter: FaceReader Stimulus View To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Stimulus View. Stimulus View FaceReader comes with the Stimulus Presentation tool which allows you to present stimuli to your test participants during the test. The Stimulus View window displays the stimulus video or image. In addition to the Stimulus View window you can, for instance, visualize the participant's Expression Intensity chart, play back the analysis and assess what facial expressions the stimuli induced. If your FaceReader license includes the Advanced Research Module and you selected Perform gaze calibration when you defined the test, the window also shows the participant's gaze overlay. Timeline To Access This Option Click the Select window button in one of the visualization windows and select Timeline. Timeline The Timeline gives an overview of the Facial Expressions, Facial States, Stimuli, Event markers and Optional classifications on a timeline. - If your license includes The Action Unit Module, the Timeline also displays Action Units. - If you selected Gaze tracking in the Settings > Analysis Options, the Timeline also displays Gaze Direction and Gaze Type (saccades/fixations). - If you have the Consumption Behavior Module, the Timeline also displays the behaviors 'Intake event', 'Chewing' and 'Chew motion' on a timeline. - If your license includes the Voice Analysis Module, the Timeline also displays the dominant emotions recognized in the participant's voice. - If you have Baby FaceReader, the Timeline only shows Action Units and Facial States. You can play back through the timeline together with playing back the analyzed/recorded video. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Turn Off Automatic Device Driver Installation And Automatic Updates URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-turn-off-automatic-device-driver-installation-and-automatic-updates Chapter: FaceReader Turn Off Automatic Device Driver Installation And Automatic Updates Aim To make sure the cameras use the drivers that were tested with FaceReader and to prevent automatic system restarts that cannot be controlled. Background Information The general recommendation from Microsoft to use automatic updates is good, especially for security updates. However, automatic updates of hardware device drives can sometimes give problems. FaceReader is tested with the device drivers that are available at the moment of the release. If device drivers are updated afterwards, we cannot guarantee that they work properly with FaceReader. Therefore we recommend to switch off automatic updates of device drivers. If you ordered a computer with FaceReader from Noldus IT, the automatic device driver installation and automatic updates have already been turned off and you can skip this topic. - Procedure for Windows 11 and Windows 10 from version 1809 onwards - Procedure for Windows 10 up till version 1803 Procedure For Windows 11 And Windows 10 From Version 1809 Onwards As of Windows 10 version 1809 please use the Group Policy Settings to prevent automatic device driver installation: - Click on the Windows icon in the taskbar and then type Edit group policy. The Local Group Policy Editor window opens. - Under Computer Configuration select Administrative Templates, System, Device Installation and then Device Installation Restrictions. - Check whether the appropriate settings are configured. Tip: Click on a setting to get additional information. If you are unsure what settings should be configured, ask your system administrator for help. Also check that your computer has the appropriate settings to prevent automatic updates: - Click on the Windows icon in the taskbar and then type Edit group policy. The Local Group Policy Editor window opens. - Under Computer Configuration select Administrative Templates, Windows Components and then Windows Update. - Manage updates offered from Windows Server Update Service - Manage updates offered from Windows Update - Check whether the appropriate settings are configured. Tip: Click on a setting to get additional information. If you are unsure what settings should be configured, ask your system administrator for help. Procedure For Windows 10 Up Till Version 1803 - Click the Windows icon on your desktop and type Change device. - Click Change Device Installation Settings. - In the window that appears, select No (your devices might not work as expected). Then click Save Changes. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Types of Custom Expressions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-types-of-custom-expressions Chapter: FaceReader Custom Expressions Custom Expressions are facial expressions/states that you can define yourself by combining the facial expressions and Action Units that FaceReader can recognize by default (Neutral, Happy, Sad, Angry, Surprised, Scared, Disgusted and Contempt and the 20 Action Units). You can, for instance, define 'Duchenne smile' as a Custom Expression by combining Action Unit 6 and 12. You can also use Valence, Arousal, Head Orientation, Head Position, Gaze Angles, Landmarks, Heart Rate, Heart Rate Variability, Expressions in the voice, and Model quality in your definition of a Custom Expression. If you have Baby FaceReader you can base your Custom Expressions on Valence and Arousal, the 20 Actions Units that FaceReader can recognize in baby faces, Head Orientation, Head Position, Gaze Angles, Heart Rate and Heart Rate Variability. If you have the regular version of FaceReader, you need the Action Unit Module to be able to define Custom Expressions. If you have Baby FaceReader you do not need an extra module. Types of Custom Expressions There are three types of Custom Expressions: - Project Custom Expressions - These Custom Expressions are available in the project that is currently open. - My Custom Expressions - These Custom Expressions are available on your PC to be used in the project that is currently open and in all existing and future projects. - Remote Custom Expression Library - These expressions come with your FaceReader license. You can copy and edit them and use them in your projects. They are stored in an online library and are curated by Noldus IT. Your FaceReader license comes with the following Custom Expressions in the Remote Custom Expression Library: Additional Action Units - Blink (AU45) — Eyes closing and opening (>0.5 difference in the intensity of AU43) within 200 milliseconds - Head Turn Left (AU51) — This Custom Expression/Action Unit is based on the head orientation (Yaw). - Head Turn Right (AU52) — This Custom Expression/Action Unit is based on the head orientation (Yaw). - Head Up (AU53) — This Custom Expression/Action Unit is based on the head orientation (Pitch). - Head Down (AU54) — This Custom Expression/Action Unit is based on the head orientation (Pitch). - Eyes Turn Left (AU61) — Only for central head position. - Eyes Turn Right (AU62) — Only for central head position. - Eyes Up (AU63) — Only for central head position. - Eyes Down (AU64) — Only for central head position. Baby Expressions - Baby Cry — This Custom Expression is based on Action Unit 12 (Lip Corner Puller), 20 (Lip Stretcher), 25 (Lips Part), 26 (Jaw Drop) and 27 (Mouth Stretch). - Baby Smile — This Custom Expression is based on Action Unit 12 (Lip Corner Puller), 20 (Lip Stretcher), 25 (Lips Part), 26 (Jaw Drop) and 27 (Mouth Stretch). Behavioral States - Attention — Indicates whether the test participant is centrally focussed based on the head orientation (Pitch and Yaw) and head position (Depth position). This custom expression does not include emotion. - Attention (binary) — Takes the head orientation into account (Pitch and Yaw). Attention is 1 if the pitch and yaw are 0, otherwise attention is 0. This Custom Expression is validated (median accuracy: 0.87). For more information see the 'Validating FaceReader's attention detection: a reliable measure using gaze and head pose' blog post on the Noldus website. - Blink Rate — Calculates the number of blinks per minute over a 10 second window. - Leaning Backward - Leaning Forward - Talking — Talking is classified by looking at the rate of Action Unit 25 (parting lips) over a typical frequency (e.g. two words per second). Action Unit 25 is also important in other expressions (e.g. smiling, spontaneous laughter). You may find false positive events when the lips part and close with a similar frequency in other expressions. The value of Talking can either be 1 (talking) or 0 (no talking). Complex Expressions - Boredom — See below for more information. - Confusion — See below for more information. - Interest — See below for more information. - Spontaneous Laughter — Laughing out loud. Takes into account Action Unit 6 and 12 and 25 and 26. Lower activation of spontaneous laughter can indicate regular laughing or in rare cases a strong smile. Facial Gestures - Frowning — AU4 is a frown but often people also tighten their eyelids (AU7). AU4 contributes most to this custom expression, AU7 only max 50%. - Laughing — Laughing with mouth open. Takes into account Action Unit 6 and 12 and 25, and 26. - Mouth Opening — Any form of mouth opening. - Mouth Tightening — Any Action Unit activity that puts tension on the mouth (Action Unit 10, 15, 18, 23, 24). - Moving Eyes — General eye movement, away from the center. A higher value indicates more movement. - Moving Head — General head movement, away from the center. A higher value indicates more movement. - Raising Eyebrows — Upward movement of the eyebrows irrespective of the inner and outer brow. - Smiling — Mouth is closed. Takes into account Action Unit 6, 12, 25, and 26. Baby Cry and Baby Smile come with Baby FaceReader. Boredom, Confusion and Interest come with the regular version of FaceReader. These expressions were called Affective Attitudes in FaceReader 7. Boredom, Confusion and Interest are estimated using all frames in a time interval. Therefore, the analysis of these Custom Expressions can only be done with video and camera analyses. For each frame, the estimate of the Custom Expression is calculated using the current frame and all the previous frames in the time interval. To calculate Interest, Boredom and Confusion the following time intervals are used: - Interest – 2 seconds. - Boredom – 5 seconds. - Confusion – 2 seconds. At the start of the analysis, there is no time interval yet to analyze these Custom Expressions. Therefore the visualization will display no data. FaceReader starts the analysis when half the time interval has been reached. This means that the analysis of Interest and Confusion starts 1 second after the start of the analysis. The analysis of Boredom starts 2.5 seconds after start of the analysis. The analysis of Interest, Boredom and Confusion is based on references 1, 2 and 3. - McDaniel, B., D'Mello, S., King, B., Chipman, P., Tapp, K., & Graesser, A. (2007, January). Facial features for affective state detection in learning environments. In Proceedings of the Cognitive Science Society (Vol. 29, No. 29). - Kapoor, A., Mota, S., & Picard, R. W. (2001, November). Towards a learning companion that recognizes affect. In AAAI Fall symposium (pp. 2-4). - Grafsgaard, J., Wiggins, J. B., Boyer, K. E., Wiebe, E. N., & Lester, J. (2013, July). Automatically recognizing facial expression: Predicting engagement and frustration. In Educational Data Mining 2013. Please cite the original work in your studies when based on FaceReader's analysis. Please note that the custom expressions in FaceReader are not qualitatively validated (due to lack of available real-world data, except Attention (binary)). The idea with most of these custom expressions is that they are primarily theory-based (based on findings/observations in the literature). They can serve as a starting point, and their formulas can be modified as needed. Regardless, the custom expressions are based on FaceReader's validated AU predictions, so the source of their input information is validated. The extra AU custom expressions are indirectly validated, e.g. Blink (AU45) is based on eye closure (AU43), which is validated; AU 51-53 are based on head pose angles, which are internally validated. Some Custom Expressions have been updated in FaceReader 10. You can continue using the older versions (that were available in FaceReader 9) by clicking Show all versions. The screenshot below shows the two versions of Interest that are available in FaceReader 10. Select one of the actions below to work with custom expressions: - Add a Custom Expression to your project - View a Custom Expression definition - Copy a Custom Expression - Import a Custom Expression - Export a Custom Expression definition - Delete a Custom Expression - Define a new Custom Expression - Custom Expression inputs in detail - A Custom Expression block in detail - Working with custom expression blocks - Input simulator - Visualize Custom Expressions - Export Custom Expressions - Custom Expression intensities in The Observer XT Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Unsupported Video Formats URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-unsupported-video-formats Chapter: FaceReader Other Video Formats For a number of other formats, codecs are included, but these formats have not been tested. We can, therefore, not guarantee that they work. Container Code Name/Encoder aviDIV1, DIV2, mp41, MPG4, MPG3Divx (1,2,3) aviDIV4, DIV6, col1, col0, 3ivdDivX 4, 5, 6, 3ivx D4, MPEG-4 avih261H.261 avih262H.262 avih263H.263/H.263i avih264, s264, AVC1, DAVC, H264, X264, VSSH aviIV31Indeo Video 3 avimp4s, m4s2, fmp4, 3iv2, smp4MPEG-4 Part 2 (AVP), Xvid aviSVQ 1Sorenson 1 (Quicktime) aviSVQ 3Sorenson 3 (Quicktime) aviVP31, VP30, VP3On2 VP3 aviVP50, VP5, VP51On2 VP5 aviVP60, VP61, VP62, VP6F, VP6AOn2 VP6 (used by FLV) flvFSV1Flash Screen Video mpgmp2v, mpg2, vcr2, hdv1, hdv2, hdv3, mx*n, mx*pMPEG-2 Part 2 mpgmpeg, mp1v, PIM1MPEG-1 Part 2 rmRV10, RV13, RV20Real Video 1.0, 1.3, 2.0 wmvwmv1, wmv2WMV 1/2 (7/8) wmvwmv3, wvc1, wmvaWMV 3/WMV-9/VC-1* * Not all profiles are supported. Unsupported Video Formats The following codecs are not included and installing them yourself will not work: Container Code Name/Encoder aviIV50, IV51Indeo 5.x avitsccTechSmith Screen Capture aviIV41Indeo 4.x aviI263H.263 avicvid(_RGB)BI_RGB Raw Bitmap avi(_RGB)BI_RGB Raw Bitmap (8bit) mp4avc1MPEG-4 AVC mov3IV13ivx (MPEG-4 based) movsvq3Unknown movavc1MPEG-4 AVC Video Length, Duration and Number of Samples For some video formats, FaceReader may have a slightly different calculation of the video length, duration, or number of samples than other video programs, like, for example, Windows Media Player. This is the case in the following cases: The frame information in the video is incorrect – Somehow the information on video duration, number of video frames and video frame rate do not agree. If this is the case, FaceReader calculates the frame rate from the number of frames and the duration of the video file. This may slightly differ from how other programs calculate this information. The video frame rate varies – If this is the case, FaceReader calculates the average frame rate over the entire video. If the way FaceReader calculates the video information leads to analysis problems, convert the videos with a converter based on FFMPEG. For example, use WinFF. http://winff.org/html_new/ Supported Image Formats The minimum dimensions of your images should be about 640 x 480 pixels (120 x 120 minimally for the face area, 200 x 200 is recommended). For FaceReader to work at a reasonable speed, the maximum dimensions should not be greater than about 2000 x 2000 pixels. FaceReader supports the following image formats: - JPG - BMP - GIF - TIF - PNG Animated GIFs are not supported, FaceReader uses the first frame of the animated GIF. Image File Extensions in Project Wizard The following image file formats can be used in combination with the project wizard: - .bmp - .jpg - .jpeg - .jpe - .jfif - .png - .gif - .tiff - .tif Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Up and Running URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-up-and-running Chapter: FaceReader Up and Running Quickly This Quick Start Guide guides you through the main steps to analyze facial expressions with FaceReader. Only the most basic features are addressed. Inevitably, some features that may be vital to your application are not discussed. You can find additional information in the FaceReader Help. General Information The first part of the Quick Start Guide contains general information on using FaceReader. Follow the instructions to set up your system, install FaceReader and to analyze the facial expressions. The second part of this Quick Start Guide describes the Project Analysis functions. The Project Analysis functionality allows you to create groups of participants based on independent variable values like age and gender, and to analyze average expression values per group. In addition to this, you can view the stimulus video together with the video of the test participant's face and the FaceReader analysis. You can extend your FaceReader license with a number of modules. Other Modules FaceReader also has the following other modules: Action Unit Analysis Module To analyze a set of 20 action units of the Facial Action Coding System (FACS). These are the action units that are most commonly used. The Action Unit Analysis interface displays action unit intensities across multiple levels: Not Active, Trace, Slight, Pronounced, Severe, and Max. Each action unit is identified by a number and description. Examples of tracked action units include: Inner Brow Raiser, Outer Brow Raiser, Brow Lowerer, Upper Lid Raiser, Cheek Raiser, Lid Tightener, Nose Wrinkler, Upper Lip Raiser, Lip Corner Puller, Dimpler, Lip Corner Depressor, Chin Raiser, Lip Puckerer, Lip Stretcher, Lip Tightener, Lip Pressor, Lips Part, Jaw Drop, Mouth Stretch, and Eye Closure. The Analysis Visualization panel overlays detected action unit labels directly on the participant's face video in real time. Vital Signs Module To estimate the heart rate, heart rate variability, and breathing rate of the subject in front of the camera. Heart rate and heart rate variability are measured by means of remote photoplethysmography (RPPG). This is a method based on the fact that changes in blood volume due to pressure pulses cause small changes in the reflectance of the skin. Breathing rate is measured by detecting upper-body movement associated with respiration. The Vital Signs panel displays the following measurements in real time: - Heart rate (BPM) with confidence indicator - Breathing rate (BPM) with confidence indicator - Heart rate variability RMSSD (ms) - Heart rate variability SDNN (ms) Consumption Behavior Module To analyze consumption behaviors like Intake event and Chewing. If you have the Consumption Behavior Module and want to use this in the analysis, you have to enable this analysis (File - Settings - Analysis Options - Optional Classifications). Voice Analysis Module With this module FaceReader can recognize emotions in the voice (Neutral, Happy, Sad and Angry) and Valence and Arousal in the voice. Advanced Research Module The Advanced Research Module allows you to analyze multiple faces in a video simultaneously. With this module you can also track the test participant's gaze when you present stimuli using the Stimulus Presentation Tool, view the gaze overlay on the stimuli when you analyze the data and make heatmaps. More Information See the FaceReader Help that opens when you press F1 in the program. It can also be accessed in the Windows apps screen, and can be downloaded from the MyNoldus portal. From the Help menu select Noldus Online and then Customer Support Center to access the MyNoldus portal. Support If you encounter problems, see the Support section on the MyNoldus portal or a help desk in your area. From the Help menu select Noldus Online and then Contact Help Desk to access the MyNoldus portal. Note that if you send us videos showing people's faces, you should have permission from those people that you can use the video for that purpose and you may need to sign a form granting consent for us to use those videos. Source: FaceReader 10 Quick Start Guide, Noldus Information Technology --- ## FaceReader 10 - Upgrade To FaceReader 10 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-upgrade-to-facereader-10 Chapter: FaceReader MediaPipe MediaPipe offers open source cross-platform, customizable ML solutions Apache License Version 2.0 https://github.com/google/mediapipe/blob/master/LICENSE Source code available at: https://github.com/google/mediapipe Upgrade To FaceReader 10 To upgrade a previous FaceReader version to version 10, carry out the following steps: - Install FaceReader. Carry out all steps in The Steps To Install FaceReader. - Upgrade the license See Upgrade The License - Upgrade the Stimulus Presentation Tool. See To Upgrade The Stimulus Presentation Tool in Project Analysis Notes - You can install FaceReader 10 9 next to older versions of the software. - If you open a project that was created in an older version, it is converted to a FaceReader 10 project and cannot be opened in the older FaceReader version anymore. To work with that project in older versions first create a backup in an older version. See Back Up A Project - We recommend to use the same FaceReader version within one project. Upgrade The License If you have a software license key Start FaceReader and activate your new license with your software license key following the procedure in Activate FaceReader With A Software License Key. If you have a hardware key - Insert the hardware key into your computer and start FaceReader. - The system automatically detects the old license on the hardware key and the Enter Upgrade Key window appears. Enter the key code that was supplied to you by Noldus IT. These numbers are normally sent by e-mail or are written in your welcome letter. If you bought an extra module When you already have FaceReader and bought an extra module, for example the Action Unit Module, you also need to upgrade your license. Open FaceReader and choose Help > Upgrade. Then enter the upgrade key that was supplied to you by Noldus IT. Opening an analysis made in a previous version of FaceReader When you open an analysis in a project that has been made in version 8 or lower of FaceReader, a message will appear in the Analysis Visualization window that, for instance, the mesh and the gaze cannot be shown. You will have to re-analyze the video to see these visualizations. If the analysis was done with the Children model or the Elderly face model that have become obsolete in FaceReader 10, then a message will pop up asking you whether you would like to switch to the General model. If you select 'Yes' you will see 'General' as the face model in the current settings. The analysis results remain intact. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Valence And Arousal Line Chart URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-valence-and-arousal-line-chart Chapter: FaceReader Subject Characteristics This option is not available with Baby FaceReader. To Access This Option Click the Select window button in one of the visualization windows, select Face Analysis, and then Subject Characteristics. Subject Characteristics The Subject Characteristics table displays the following: - Gender – A range is given with a certainty value. If the gender is entered manually in the Independent Variables, the value is fixed and the certainty is 100%. - Age – A range is given with a certainty value. If the age is entered manually in the Independent Variables, the value is fixed and there is no certainty displayed in the table. - Presence of glasses – A certainty value is given. Note The Subject Characteristics table also gives you an indication of the quality of the image. If the quality of your image is poor, the information will not be correct. For instance, if FaceReader reports that a female test person is male, then the modeling is not correct, most probably because the image is of poor quality or the lighting conditions are bad. Valence And Arousal Line Chart To Access This Option Click the Select window button in one of the visualization windows, and select Face Analysis and then Valence and Arousal Line Chart. Valence Valence indicates whether the facial expressions display a positive or negative emotion. See the figure below for an example. When you play back the video, a hairline shows the time in the video. How Valence Is Calculated The valence indicates whether the emotional status of the subject is positive or negative. 'Happy' is the only positive emotion, 'Sad', 'Angry', 'Scared' and 'Disgusted' are considered to be negative emotions. 'Surprised' can be either positive or negative and is, therefore, not included in the calculation of valence. Contempt is also not included in the calculation of Valence. Valence is calculated as the intensity of 'Happy' minus the intensity of the negative emotion with the highest intensity. If you have Baby FaceReader, Valence is based on Action Units. Example Consider the following expression intensities: - Happy – 0.8 - Sad – 0.1 - Angry – 0.0 - Scared – 0.05 - Disgusted – 0.05 In this case Valence is 0.8 - 0.1 = 0.7. Arousal Arousal indicates whether the test participant's face is active (+1) or not active (0). Arousal is based on the activation of 20 Action Units (AUs) of the Facial Action Coding System (FACS). See the figure above for an example. When you play back the video, a hairline shows the time in the video. How Arousal Is Calculated - The activation values (AV) of 20 AUs are taken as input. These are AU 1, 2, 4, 5, 6, 7, 9, 10, 12, 14, 15, 17, 18, 20, 23, 24, 25, 26, 27, and the inverse of 43. The value of AU43 (eyes closed) is inverted because it indicates low arousal instead of high arousal like the other AUs. - The arousal is calculated by taking the mean of the three highest values. Note - Contempt is not included in the calculation of Arousal. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - View A Custom Expression Definition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-view-a-custom-expression-definition Chapter: FaceReader Add A Custom Expression To Your Project Aim To analyze a Custom Expression, that is, to quantify the activation of the Custom Expression in the test participant's face. Prerequisite - You have the Action Unit Module or Baby FaceReader. - Your FaceReader computer has a connection to the internet to access the Remote Custom Expression Library. - All the analyses in the project are closed. To close an analysis, click the button next to it. Procedure - From the File menu select Custom Expressions Browser or click the Add custom expression to project icon in the Custom Expressions pane. The Custom Expression browser opens with three tabs: Project Custom Expressions, My Custom Expressions and Remote Custom Expression Library. - Click the Remote Custom Expression Library tab. If you like you can sort the custom expressions, please see below. - Add a Custom Expression to the project that is currently open by clicking the Add to project icon and then click OK. View A Custom Expression Definition Aim To view what elements have been used in a Custom Expression definition and how they are combined. Prerequisite - You have the Action Unit Module or Baby FaceReader. - Your FaceReader computer has a connection to the internet to access the Remote Custom Expression Library. Procedure - From the File menu select Custom Expressions Browser. The Custom Expression browser opens with three tabs: Project Custom Expressions, My Custom Expressions and Remote Custom Expression Library. If you like you can sort the custom expressions, please see below. - Add a Custom Expression to your project by clicking the Add to project icon. - Click the Edit Custom Expression icon. A new window opens with a detailed view of the blocks and processors that are part of the expression. In the screenshot below you can see part of the Custom Expression 'Attention'. To Sort Custom Expressions Click the Sort by name or Sort by date modified button on the toolbar to sort your Project Custom Expressions, the expressions under My Custom Expressions or the expressions in the Remote Custom Expression Library in alphabetical order or by date last modified. Click the Revert sort order to change the order from A-Z into Z-A or from latest to earliest date or vice versa. To Zoom In And Out Use the Zoom out, Zoom in and Fit to screen icons on the toolbar to customize the window. You can also use Ctrl- and Ctrl+ or Ctrl + scroll wheel to zoom out or in. To Rename A Custom Expression Or Change Its Color Click the Edit information icon on the toolbar to open a new pane with the Custom Expression's name, author, description and color. If you like you can edit the information. Each Custom Expression has its own unique color which is the same throughout the program. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Visualize Action Units URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-visualize-action-units Chapter: FaceReader Analyze Action Units Aim To quantify activation of Action Units in the test participant's face. Prerequisite Your FaceReader license includes the Action Unit Module. Procedure - Choose File > Settings > Analysis options. - Under Optional Classifications, select Action units. Action Unit Analysis is by default switched on if your FaceReader license includes the Action Unit Module. Visualize Action Units Aim To display Action Units during or after the analysis. Prerequisites - Your FaceReader license includes the Action Unit Module or you have Baby FaceReader. - You are running an analysis, or viewing the analysis afterwards. Action Units in the Analysis Visualization Window Click the Show action units button on the left side of this window. Action Units appear in the Analysis Visualization when the activity is Trace or higher. The colors under the name represent the activity of this Action Unit. Action Unit Intensity Select the Action Unit Intensity window from one of the visualization windows (see Manage analysis windows). It shows the intensity of 20 Action Units, divided into the classes Trace, Slight, Pronounced, Severe, and Max. These intensities are shown by consecutive letters from A to E. From the Action Units list, choose which ones to display. Unilateral Action Units Most Action Units are unilateral, that is, they can be visible in the left and/or right part of the face. To assess the intensity of the left and right part independently, select Options and then Split unilateral action units. Please note that the unilateral Action Units have been evaluated only qualitatively, but not validated quantitatively. This is mainly due to unavailability of data: images of unilateral AU activation examples are rare in current datasets and hard to produce in general. Continuous Value Bars Select Options and then Show continuous value bars to visualize the intensity of the Action Units on a continuous scale. Action Unit States The intensity of the Action Units is displayed on the Timeline. Select Timeline in one of the windows (see Manage analysis windows). Choose which Action Units to display from the Action Units list on the toolbar. By default all Action Units are selected. Note: To copy, save, or zoom in this window, see Common options in FaceReader's output. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Visualize Consumption Behavior URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-visualize-consumption-behavior Chapter: FaceReader The Consumption Behavior Module Main Topics - Introduction to the Consumption Behavior Module - Analyze Consumption Behavior - Visualize Consumption Behavior Introduction to the Consumption Behavior Module The Consumption Behavior Module allows you to analyze the behaviors Intake event, Chewing and Chew motion. Intake event is taking a bite or sip. Chew motion is one movement of the jaws to chew the food in the mouth. Chewing is the state from the first chew motion (after taking a bite) till the last chew motion (before swallowing the food). Please note that you cannot combine the Consumption Behavior Module with Baby FaceReader and you cannot analyze consumption behavior in a multi-subject analysis. Guidelines To make sure that analysis of consumption behavior goes well, it is important that not only the face but also the test participant's hands are visible in the camera view. Currently, FaceReader can only detect hands and no cutlery, hence, the hands entering the face region is important for FaceReader to detect eating behavior. Wiping the mouth can yield a false positive intake event. To detect drinking behavior, FaceReader uses images of cups, not straws. Hence, it is important not to use straws in your experiments. Analyze Consumption Behavior Aim To switch on Consumption Behavior analysis. Prerequisite - You have the regular version of FaceReader with the Consumption Behavior Module. - From the participant, both the face and the hands are visible. - You followed the Guidelines for good analysis. Procedure - Choose File > Settings > Analysis options. - Under Optional Classifications, select Consumption behavior. Visualize Consumption Behavior Aim To display the Consumption Behavior during or after the analysis. Prerequisites - You have the regular version of FaceReader and your license includes the Consumption Behavior Module. - Consumption Behavior analysis is switched on in the Settings. See Analyze Consumption Behavior Consumption Behavior on the Timeline - Click the Select window button in one of the visualization windows and select Timeline. The Timeline window opens. The Timeline gives an overview of the Facial Expressions States, and Optional classifications on a timeline. - From the Consumption Behavior drop-down list, select what behaviors you want to view. You can play back through the timeline together with playing back the analyzed video. Consumption Behavior Statistics - Click the Select window button in one of the visualization windows and select Consumer Behavior and then Consumption Behavior Statistics. The table displays the number of intake events (bites and sips) and chew motions. The Current column displays the numbers up to the current moment in the analysis. During the analysis, the Total column displays the numbers up to the current moment in the analysis. After the analysis, the Total column displays the numbers in the entire analysis. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Visualize Custom Expressions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-visualize-custom-expressions Chapter: FaceReader Input Simulator To check whether you defined your Custom Expression correctly, you can use the Input simulator. The Input simulator allows you to fill in values for each input. You can also use the slider to specify a value. Each step in the definition will be calculated and you can check what the output is. In this way you can assess whether you correctly defined your Custom Expression. The Input simulator indicates whether the Custom Expression is valid. If, for instance one of the connections is missing, the Custom Expression is invalid. If you use a temporal processor in your definition, FaceReader comes with the following note: "Your Custom Expression contains a Temporal processor. During input simulation the complete history is assumed to have the same value as entered below". In the screenshot above you can see this note, indicating that the definition of the Custom Expression contains a temporal processor. If you, for instance, filled in 02.00 seconds as the duration of the history when defining the temporal processor, FaceReader assumes that during these 02.00 seconds the Action Units 6, 12, 25, and 26 had a constant value, that is, the value that you defined in the Input simulator. Visualize Custom Expressions Aim To display Custom Expressions during or after the analysis. Prerequisites - Your FaceReader license includes the Action Unit Module or you have Baby FaceReader. - Action Unit analysis is switched on in the Settings. Custom Expressions Table Select Custom Expression Table from one of the visualization windows. The table shows the intensities of the Custom Expressions that you added to your project. If your input is a live video stream or a video file, you will see the intensities change over time during the analysis or when you play back the analysis, reflecting the changes in custom expressions on the face. Custom Expressions Line Chart - Select the Custom Expressions Line Chart from one of the visualization windows (see Manage analysis windows). - Choose which Custom Expressions to display from the Custom Expressions list on the toolbar. By default all Custom Expressions are selected. Note To copy, save, or zoom in this window, see Common options in FaceReader's output. Export Custom Expressions Aim To export the Custom Expressions to a text file or The Observer XT format file. Prerequisites - You have the Action Unit Module or Baby FaceReader. - You carried out an analysis. Procedure - Choose File > Settings and then click the Data Export tab. - Under Export (Detailed log, ODX, N-Linx and API), select Custom expressions and then click OK. - Choose File > Export and select one of the options. See Export the data in FaceReader's output. Custom Expression Intensities in The Observer XT If you send FaceReader data to The Observer XT 13 or higher versions using the N-Linx network communication protocol, Custom Expression intensities are imported as external data. You can also manually import Custom Expressions. To be able to import Custom Expressions as external data you need the External Data Module of The Observer. See FaceReader with The Observer XT The Observer XT displays Custom Expression intensities as external data channels in a timeline view, showing intensity values over relative time. The following Custom Expression channels are shown as separate waveform graphs: - Custom Expression - Boredom - Custom Expression - Confusion - Custom Expression - Interest Each channel displays intensity values ranging from 0.0 to their respective peak values over the observation period, allowing comparison of multiple custom expression intensities across time. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Visualize FaceReader Data in The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-visualize-facereader-data-in-the-observer-xt Chapter: FaceReader Visualize FaceReader Data in The Observer XT State Expression Values State Expression values are imported into the observation as a separate event log. When you open the coding scheme, you will see that a behavioral group Dominant Expressions has been added with the six basic expressions, Contempt (optionally), the Neutral state plus Unknown and Not Analyzed as behaviors. Unknown is the expression that is logged when FaceReader cannot find or model the face. See the figure below for a visualization of imported State log values. Event Markers and Stimuli Event Markers and Stimuli are imported as separate event logs into the observation. They are added to the Coding Scheme as behavior groups Event Markers and Stimuli. See the figure below for an example of a visualization of imported Event Markers and Stimuli. Facial States and Global Gaze Direction If you imported Facial States or Global Gaze Direction in The Observer XT, the new observation contains an extra Event log: Facial States. The behavioral group Facial States has been added to the coding scheme containing the states as State Events with modifiers. For example the State Left eye has the modifiers Open and Closed. Consumption Behavior Data If you imported a Detailed log file with Consumption Behavior events in The Observer XT, the new observation contains an extra Event log: Consumption Behavior. The behavioral group Consumption Behavior has been added to the coding scheme containing the states as State Events. Continuous Data Continuous data are shown as a continuous graphs when you use FaceReader and The Observer XT 13 or higher versions with N-Linx, or imported the detailed log as external data into The Observer XT. Your license for The Observer XT must include the External Data Module. Action Unit Intensities as Continuous Data This option is only available if your FaceReader license includes the Action Unit Module. In addition to this, you chose to export Action Units as continuous values in the Data export tab of the FaceReader Settings window (File > Settings). You imported the detailed log into The Observer XT as external data. The Action Unit intensities are displayed as continuous graphs. Action Units as Observational Data This option is only available if you have the Action Unit Module in FaceReader. If you imported the detailed log as odx file, or used FaceReader and The Observer XT with N-Linx, the Action Units are imported as a separate event log in the observation. The Coding Scheme contains a behavior group Action Units with the modifier group Activation intensity that contains the intensities A to E. See the figure below for an example of a visualization. Click the + sign next to an Action Unit to visualize its intensity values (A, B,...). Custom Expression Intensities as Continuous Data This option is only available if your FaceReader license includes the Action Unit Module. You imported the detailed log into The Observer XT as external data (either via the N-Linx protocol or manually). The Custom Expression intensities are displayed as continuous graphs. Expressions from Voice Intensities as Continuous Data This option is only available if your FaceReader license includes the Voice Analysis Module. You imported a detailed log file into The Observer XT (either via the N-Linx protocol or manually). The Expressions from voice are displayed as continuous graphs, one for each expression and graphs for Valence from voice, Arousal from voice, Loudness and Speech rate. Data Selection and Statistical Analysis You can use the imported data for data selection and statistical analysis. For example to select the time period over which Stimulus 1 was scored and to analyze the facial expressions over this time period. For more information on Data selection and statistical analysis, see The Observer XT Help. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Visualize Voice Characteristics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-visualize-voice-characteristics Chapter: FaceReader Analyze Voice Characteristics Aim To switch on voice analysis. Prerequisite You have the Voice Analysis Module. Procedure - Choose File > Settings > Analysis options. - Under Optional Classifications, select Voice analysis. Note The option to analyze the voice must be switched on, which is by default if you have the Voice Analysis Module. However, when you upgrade a basic FaceReader license with the Voice Analysis Module, you must switch the option on manually. Visualize Voice Characteristics Aim To display the voice characteristics during or after the analysis. Prerequisites - Your FaceReader license includes the Voice Analysis Module. - Voice analysis is switched on in the Settings. See Analyze voice characteristics - You are running an analysis, or viewing the analysis afterwards. Voice Expression Intensity The Voice Expression Intensity chart displays the intensity of the four basic emotions that can be recognized in the voice (Neutral, Happy, Sad and Angry). You will see the bars change over time, reflecting the changes in expressions in the voice. To view the Voice Expression Intensity Chart Click the Select window button in one of the analysis windows and select Voice Analysis and then Voice Expression Intensity Chart. Voice Expression Line Chart The Voice Expression Line Chart shows the detected emotions over time. There are gaps in the line chart if the VAD does not detect voice. This detection method cannot be adjusted. If there is noise in the audio signal, the Voice Expression Line Chart may show continuous lines even though the participant did not speak all the time. To view the Voice Expression Line Chart Click the Select window button in one of the analysis windows and select Voice Analysis and then Voice Expression Line Chart. There are gaps in the line chart at the time points when the volume was below the threshold. Voice Valence And Arousal Line Chart The Voice Valence indicates whether the emotional state of the subject is positive or negative. 'Happy' is the only positive emotion, while 'Sad' and 'Angry' are considered to be negative emotions. Valence is calculated by subtracting the intensity of the strongest negative emotion from the intensity of 'Happy'. Arousal is the weighted average of Loudness and Speech rate. See How is Loudness calculated? and How is Speech rate calculated? To view the Voice Valence and Arousal Line Chart Click the Select window button in one of the analysis windows and select Voice Analysis and then Voice Analysis and Arousal Line Chart. There are gaps in the line chart at the time points when the volume was below the threshold. Voice View The Voice View shows a two-second audio waveform. The color indicates the detected emotions. If a volume threshold is crossed, the two meters on either side of the waveform show the volume-independent Loudness and the Speech Rate. To view the Voice View Click the Select window button in one of the analysis windows and select Voice Analysis and then Voice View. How Is Loudness Calculated? Loudness is a custom volume-independent loudness measure. Variations in microphone sensitivity and speaker positioning can significantly affect the absolute volume of a recording. To address this, the loudness measure is computed using a continuously updated, normalized audio signal. For each frame in the video, the system analyzes the past second of audio. Within this one-second window, the audio is normalized so that its maximum absolute amplitude is 1.0. This ensures that the measurement reflects the speaker's vocal dynamics, i.e. how energetically a person is speaking within their own dynamic range, rather than the recording conditions. After normalization, the RMS (root mean square) value is calculated to capture the average energy of the speech in that time frame. Because the signal is normalized before computing the RMS, the resulting loudness value is always scaled between 0 and 1, where 0 corresponds to silence and 1 represents a sustained signal at maximum amplitude. How Is Speech Rate Calculated? The speech rate measure estimates how quickly a person is speaking. The algorithm detects peaks in the audio signal, typically corresponding to syllables, by identifying bursts of vocal energy. These peaks are counted over the same one-second window used for loudness analysis. The count is then normalized to a value between 0 and 1, using an upper bound suitable for capturing various emotional states [1,2]. A higher value indicates faster speech, while a lower value reflects slower or more deliberate speaking. - Arnfield, S., Roach, P., Setter, J., Greasley, P., Horton, D. (1995) Emotional stress and speech tempo variation. Proc. ESCA/NATO Workshop on Speech under Stress, 13–15. - Braun, Angelika & Oba, Reiko. (2007). Speaking Tempo in Emotional Speech - a Cross-Cultural Study Using Dubbed Speech. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Visualize Your Data in a Chart URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-visualize-your-data-in-a-chart Chapter: FaceReader Quick Layouts Aim Visualize your data in a number of charts to get a quick first impression of your results. Prerequisites - Your FaceReader license includes the Project Analysis Module. - Your project includes one or more video or camera analyses. Procedure - Open the Project Analysis section and click Quick Layouts. - Select the data you want to include in your analysis. See Data Selection for more information. - Select which Quick Layout you prefer. Click OK when you are ready. The following Quick Layout options are available: - Stimulus, participant video and Line Chart. See Visualize Your Stimulus, Participant Videos and Line Chart. - Stimulus, Line Chart, Bar Chart, Circumplex Model and Pie Chart. - Stimulus and Line Chart. - Pie Chart, Box Plot and Table. See also Calculate Statistics and Summarize Them in a Table. By default FaceReader shows a Line chart and the face video of the first participant. If you selected a stimulus, FaceReader will also show the (first) stimulus video/image. If your stimulus is a video — Play the stimulus video together with the Line Chart. See Visualize Your Stimulus, Participant Videos and Line Chart for more details. Visualize Your Data in a Chart Aim To visualize your data in a Pie Chart, Box Plot, Bar Chart, Circumplex Model or Line Chart. Prerequisites - Your FaceReader license includes the Project Analysis Module. - Your project includes one or more video or camera analyses. Procedure - Open the Project Analysis section and click either Pie chart, Box Plot, Bar Chart, Circumplex Model or Line Chart. - Select the data you want to include in your analysis. See Data Selection for more information. Click OK when you are ready. FaceReader will show the chart. Click on the colored circles below the chart to exclude or re-include the corresponding data from/into the chart. Each chart has a toolbar with the following information/icons: - Edit Selection — Click this button to open the Data selection window and change your selection. Click OK when you are ready. - Adjust Caption — Click this button to change or reset the chart's caption. - Display Data — Click this button to view a table containing the data on which the chart is based, per participant and aggregated over participants. The table also shows the number of frames in the participant video or camera stream that was taken into account. If the chart is a Line chart or Circumplex Model the table shows the data per sample point aggregated over participants. The table in the example below comes from the 'FaceReader sample project - Two stimuli' and shows the mean intensities of the facial expressions Neutral and Happy per test participant and (in the last row) the mean intensities over test participants during the time that the test participants watched the 'Twins eating' stimulus. Click the Save button to save the table, either in *.txt format or in *.xlsx format. - Save Data — To save the data, either in *.txt format or in *.xlsx format. This results in the same output as when you click the Save button under Display Data. - Copy as Image — To copy the chart to the clipboard. - Save as Image — To save the chart in one of the following formats: *.png, *.jpg, *.bmp, *.gif or *.tif. - Increase/Decrease Size — To increase or decrease the chart's width. - Close — To close the chart. Use the four-arrow cursor to move your chart to another position in the layout. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Vital Signs Line Chart URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-vital-signs-line-chart Chapter: FaceReader Visualize Vital Signs Aim To display the heart rate, heart rate variability and breathing rate during or after the analysis. Prerequisites - Your FaceReader license includes the Vital Signs Module. - Vital signs analysis is switched on in the Settings. See Analyze vital signs. - You are running an analysis, or viewing the analysis afterwards. Vital Signs The Vital Signs window shows the current heart rate of the participant estimated by means of remote photoplethysmography. Heart rate is expressed in beats per minute (bpm). The Vital Signs window also shows the heart rate variability (RMSSD and SDNN) and breathing rate. The window shows confidence indicator bars indicating how confident the current measurements are. See Introduction to the Vital Signs Module To View The Vital Signs Window Click the Select window button in one of the analysis windows and select Vital Signs and again Vital Signs. If your settings deviate from the recommended settings, a warning will show up in the Vital Signs Heart Rate window, informing you that the ratio between the frame rate, bit rate and resolution is too low to estimate the vital signs heart rate with high accuracy. See Camera settings for the recommended settings. Vital Signs Line Chart The Vital Signs Line Chart shows the heart rate, heart rate variability estimated with Remote photoplethysmography, and the respiratory rate plotted against time. To View The Vital Signs Line Chart Click the Select window button in one of the visualization windows and select Vital Signs > Vital Signs Line Chart. Vital Signs Line Chart From the Vital Signs drop-down list, select what you want to view, Heart Rate, Heart Rate Variability (RMSSD), Heart Rate Variability (SDNN) and/or Breathing Rate. Please note that in the chart above heart rate variability was not selected. When you play back a video, a hairline shows the time in the video. At the end of analysis, the estimated heart rate, heart rate variability, and breathing rate are post-processed to improve the accuracy, also in the initial 8.5/15 seconds and every time a new calibration was carried out. Note that the reported heart rate and breathing rate values after analysis can differ from those seen during analysis. Do not rely on the exact values you see during analysis. The heart rate, heart rate variability, and breathing rate lines in the 'Vital Signs Line Chart' have a different color before and after post-processing. Notes - Click Options and then select Auto Scale Y Axis to adjust the Y axis to the maximum value. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Vital Signs White Paper - Applications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-vital-signs-white-paper-applications Chapter: FaceReader Learn More About - Applications in UX, consumer, and psychology research - How to get objective data in no time - Experiences from happy customers Measuring Vital Signs with FaceReader References - A. Gudi, M. Bittner, and J. van Gemert (2020). Real-time webcam heart-rate and variability estimation with clean ground truth for evaluation. Applied Sciences, vol. 10 (23), p. 8630, doi: 10.3390/app10238630. - A. Deo Mehta and H. Sharma. (2023). OPOIRES: A robust non-contact respiratory rate extraction based on optimal points-of-interest selection from an RGB camera. Biomedical Signal Processing and Control, vol. 86, p. 105193, doi: 10.1016/j.bspc.2023.105193. - X. Li, J. Chen, G. Zhao, and M. Pietikainen. (2014). Remote heart rate measurement from face videos under realistic situations, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4264–4271. - M.-Z. Poh, D. J. McDuff, and R. W. Picard. (2010). Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Optics Express, vol. 18 (10), pp. 10762–10774. - H. Demirezen and C. E. Erdem. (2018). Remote photoplethysmography using nonlinear mode decomposition, in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, pp. 1060–1064. - W. Wang, S. Stuijk, and G. De Haan. (2015). A novel algorithm for remote photoplethysmography: Spatial subspace rotation. IEEE Transactions on Biomedical Engineering, vol. 63 (9), pp. 1974–1984. - G. De Haan and V. Jeanne (2013). Robust pulse rate from chrominance-based rPPG. IEEE Transactions on Biomedical Engineering, vol. 60 (10), pp. 2878–2886. - M. Finžgar and P. Podržaj (2020). Feasibility of assessing ultra-short-term pulse rate variability from video recordings. PeerJ, vol. 8, p. e8342. - L. Tarassenko, M. Villarroel, A. Guazzi, J. Jorge, D. A. Clifton, and C. Pugh. (2014). Non-contact video-based vital sign monitoring using ambient light and auto-regressive models. Physiological Measurement, 35 (5), 807. https://doi.org/10.1088/0967-3334/35/5/807. - M.-Z. Poh, D. J. McDuff, and R. W. Picard. (2010). Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Transactions on Biomedical Engineering, 58 (1), 7–11. - A. D. Metha and H. Sharma. (2020). Tracking nostril movement in facial video for respiratory rate estimation. In International Conference on Computing, Communication and Networking Technologies (ICCCNT), 1–6. https://doi.org/10.1109/ICCCNT49239.2020.9225464. - C. Massaroni, E. Schena, S. Silvestri, and M. Soumyajyoti. (2019). Comparison of two methods for estimating respiratory waveforms from videos without contact. In IEEE International Symposium on Medical Measurements and Applications (MeMeA), 1–6. https://doi.org/10.1109/MeMeA.2019.8802167. Contact Information International Headquarters Noldus Information Technology bv Wageningen, The Netherlands Phone: +31-317-473300 Email: contact@noldus.com North American Headquarters Noldus Information Technology Inc. Leesburg, VA, USA Phone: +1-703-771-0440 Toll-free: 1-800-355-9541 Email: info@noldus.com Representation Noldus is represented by a worldwide network of distributors and regional offices. Visit noldus.com for contact information. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader 10 - Vital Signs White Paper - How It Works URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-vital-signs-white-paper-how-it-works Chapter: FaceReader Vital Signs Performance Evaluation To demonstrate the effectiveness of FaceReader's voice analysis, we evaluated and benchmarked their performance on a collection of established and proprietary RPPG datasets. This collection consists of approximately 200 front-facing videos of approximately 50 participants, and includes ground truth signals for heart rate, heart rate variability and breathing rate under various recording conditions. This makes them suitable for objective validation and comparison with existing methods. For this evaluation, we divided the data into two subsets: - A high-compression/low-movement set, where the participants show minimal movement; these videos are highly compressed. - A low-compression/high-movement set, wherein participants make certain head/body movements; these videos are uncompressed. State-of-the-Art Accuracy As video compression can introduce unwanted noise, all heart rate related evaluations were performed on the low-compression/high-movement subset. For heart rate estimation, we report a mean absolute error (MAE) of 0.21 bpm (Table 1), demonstrating a state-of-the-art result. Compared to previously published methods, our method shows a significant improvement in accuracy. In terms of HRV, our results indicate improved performance over earlier methods as well, with a lower MAE of 14 ms for RMSSD and 6 ms for SDNN, compared to 16.8 ms and 8.1 ms reported by Finžgar [8]. Based on the HRV literature and considering that the average human heart rate variability is in the range of 19–75 ms RMSSD, error rates of approximately 30 ms or lower RMSSD are generally considered acceptable for distinguishing between broad HRV level groups. Our results fall well within this range. Table 1: Heart Rate Estimation Performance Heart rate estimation performance of FaceReader, in comparison with prior methods. Method MAE STD LiCVPR [3] 28.2 - ICA [4] 24.1 30.9 NMD-HR [5] 8.7 24.1 2SR [6] 2.4 - CHROM [7] 2.07 - FaceReader 10 0.21 0.35 Table 2: Heart Rate Variability Performance Heart rate variability performance of FaceReader, in comparison with prior methods. Method HRV Metric MAE STD Finžgar [8] RMSSD 16.8 - FaceReader 10 RMSSD 14.6 13.2 Finžgar [8] SDNN 8.1 - FaceReader 10 SDNN 6.1 - These results show that FaceReader can estimate heart rate and HRV with sufficient accuracy even under movement conditions when the video quality is sufficiently high. How Compression Noise Impacts Accuracy Heart rate estimation is based on the extraction of a faint signal that is invisible to the naked eye. Video compression algorithms, which are commonly used to reduce file size, preserve visual quality but remove the invisible heart rate information contained in a video, introducing what we refer to as compression noise. This can drastically reduce the quality of the extracted signal and thereby reduce the accuracy of the estimated heart rate. The effect of compression noise can clearly be seen when comparing heart rate estimation accuracy on low-compression and high-compression video subsets. Despite the high-compression videos having relatively low movement, their high video compression noise level results in noticeably worse performance. In contrast, the low-compression videos, which have more motion but no compression, achieve higher accuracy — showing the extent of performance degradation caused by video compression noise. Highly Accurate Measurement of Breathing Rate To evaluate the accuracy of our breathing rate estimation method, we benchmarked its performance against existing approaches using the low-movement subset. On these videos, we achieved a mean absolute error (MAE) of 0.55 breaths per minute, showing state-of-the-art performance compared to other published methods for breathing rate evaluation. Table 3: Breathing Rate Performance Breathing rate performance of FaceReader, in comparison with prior methods. Method MAE STD Tarassenko et al. [9] 9.0 11.8 Poh et al. [10] 4.2 5.2 Mehta et al. [11] 3.6 4.6 Massaroni et al. [12] 2.4 5.7 OPOIRES [2] 0.62 1.4 FaceReader 10 0.55 0.73 These results show that FaceReader is able to estimate the breathing rate accurately in limited-movement scenarios where the observed chest movement is not significantly distorted by movement noise. For Your Research The results demonstrate that measuring vital signs such as heart rate, breathing rate, and heart rate variability (HRV) through a standard webcam is both practical and accessible for researchers using FaceReader. Provided that lighting and participant positioning are adequate, individual differences and technical variations have minimal impact on measurement accuracy. As with any physiological assessment, there is a trade-off between ecological validity and measurement precision. For maximum precision, a controlled laboratory environment with specialized equipment may be preferable. However, measuring vital signs with FaceReader is ideal for studies that prioritize natural behavior and require scalable, non-intrusive data collection. Recordings When planning a video recording setup for analyses that include vital signs, the following guidelines can help to ensure optimal signal quality. - Heart Rate and HRV: When recording videos, make sure to use a lossless compression method to reduce compression noise in the video. Ensure that the participant's forehead and upper face are clearly visible, and avoid strong specular reflections (e.g., bright white spots on the forehead). Note that heart rate and heart rate variability estimations may not work for participants wearing heavy makeup. - Breathing Rate: For the cleanest breathing rate signal, minimize participants' upper-body movement. This works best in scenarios where participants are sitting calmly, such as when watching a stimulus or engaging in passive interaction. Please refer to the Guidelines for an Optimal RPPG Measurement page in the FaceReader manual for more specific and detailed recommendations. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader 10 - Vital Signs White Paper - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-vital-signs-white-paper-introduction Chapter: FaceReader What Can You Measure with FaceReader? With just a regular webcam, FaceReader lets you detect key physiological signals like heart rate and heart rate variability. These vital signs are an important dimension to consider in human-centric experiments and support the integration of physiological data into the analysis. Without the need for extra hardware, you can measure heart rate, breathing rate, and heart rate variability (HRV). - Heart Rate: A strong indicator of cardiovascular effort and offers a practical way to approximate real-time energy use. - Breathing Rate: Can be used to estimate metabolic demand and highlight shifts in emotional arousal, e.g., distinguishing relaxed breathing from stress-induced hyperventilation. - Heart Rate Variability: Often used to assess autonomic nervous system balance, providing an indirect measure of overall recovery status and cumulative fatigue. This white paper discusses the methodology and expected performance of FaceReader's vital sign measurement techniques, including validation examples and practical tips for optimal results. How Does It Work? FaceReader measures vital signs with two underlying technologies: one to estimate blood volume changes for heart rate and heart rate variability; and another to detect respiratory motion for measuring breathing rate. At their core, both breathing and heart rate estimation methods work on the principle of extracting and cleaning an information-dense signal and detecting the relevant physiological information from this signal. Estimating Heart Rate and Heart Rate Variability Estimation of heart rate via photoplethysmography (PPG) is based on the principle that changes in the blood volume result in changes in the light reflectance of the skin. The visual color of the face changes with each heartbeat due to increase or decrease in blood volume within the skin's capillaries. While these changes are invisible to the naked eye, digital cameras are able to capture them remotely. When tracking these color changes in a patch of skin over time, the variations form a signal called the blood volume pulse. Extracting blood volume pulse changes using a camera is known as remote photoplethysmography or RPPG. The RPPG algorithm processes video data in the following steps: - Face Detection and Tracking: The RPPG algorithm starts by detecting and tracking the face to extract color changes from the cheeks and forehead. It reduces noise in the signal by excluding the eye and mouth regions. - Noise Reduction: After enough signal has been gathered during a brief calibration period, noise from movement and other sources is filtered from the signal. This is done by an initial aggregation step that removes movement information based on intensity changes in different color channels. - Signal Filtering: The signal is then further refined using a two-stage filter. A Fourier-based filter first removes all frequencies outside of the heart rate range and those caused by rhythmic head movements. This is followed by a time-based filter that produces a signal with clear peaks and valleys. - Heartbeat Detection: Each peak in this signal represents a heartbeat. The time differences between individual beats, the inter-beat intervals (IBIs), are used to calculate heart rate and heart rate variability. Heart Rate Calculation The heart rate in beats per minute (bpm) is calculated using a time window (w) of 8.5 seconds, where N represents the number of IBIs within that window and 60 represents the number of seconds per minute. Heart Rate Variability Calculation FaceReader supports the calculation of two HRV measures: - RMSSD: The Root Mean Square of Successive Differences. - SDNN: The Standard Deviation of Normal-to-Normal intervals. The calculation of both short-term (5 minute window) and ultra-short term (under 5 minute window) heart rate variability is supported. Estimating Breathing Rate The breathing rate algorithm processes video data in the following steps: - Chest Motion Detection: Breathing rate is estimated by detecting key points on the chest and shoulders and tracking their motion across video frames. - Motion Signal Extraction: After removing irrelevant points not correlated with breathing, the changes in motion of individual points are combined into a single motion signal. - Signal Filtering: This signal is cleaned using a two-stage filter, similar to how it works with heart rate. A Fourier-based filter first removes all frequencies from the signal outside of the breathing rate range. This is followed by a time-based filter that creates a signal with clear peaks and valleys, from which breathing rate can be calculated. Breathing Rate Calculation The breathing rate in breaths per minute (bpm) is calculated from the average of inter-breath intervals (IBIs), where w represents a time window of 15–30 seconds, N represents the number of IBIs within that window, and 60 represents the number of seconds per minute. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader 10 - Voice Analysis White Paper - Applications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-voice-analysis-white-paper-applications Chapter: FaceReader Performance of Voice Analysis Table 1 summarizes the performance of FaceReader's voice analysis on a diverse English-language test set. This test set was constructed using both publicly available and proprietary datasets. It was also explicitly excluded from training to ensure unbiased evaluation. Table 1. Overall Performance Metrics on the English-Language Test Set. - Accuracy – 87.1: Percentage of predictions that were correct across all emotion classes. - Precision – 87.2: Measures how many of the predicted emotions were correct (focuses on minimizing false positives). - Recall – 87.1: Measures how many of the emotions were correctly identified (focuses on minimizing false negatives). - F1 Score – 87.1: Harmonic mean of precision and recall; a balanced measure of model accuracy. - UAR – 87.3: Unweighted Average Recall: average recall per class, giving equal weight to each emotion regardless of how often it occurs. The test set includes a broad spectrum of recordings, covering both acted and spontaneous expressions of emotion. The dataset features over 4,000 recordings from speakers of varying gender, ethnicity, and dialects to ensure robustness across demographic variation. Emotion labels were either predefined (in the case of scripted, acted speech) or obtained through crowd-sourced or expert annotation (for both spontaneous and acted speech). Inter-annotator agreement was used to assess and improve labeling reliability. Table 2 breaks down performance by emotion category, highlighting consistently strong and balanced results across all four target emotions. Table 2. Classification Performance Per Emotion Category on the Test Set. - Neutral: Precision 90.2, Recall 86.7, F1 Score 88.4 - Happy: Precision 83.2, Recall 84.8, F1 Score 84.0 - Sad: Precision 84.4, Recall 91.9, F1 Score 88.0 - Angry: Precision 90.7, Recall 85.9, F1 Score 88.2 Voice Analysis To minimize gender bias in FaceReader's voice analysis, deliberate steps are taken throughout data collection, training, and evaluation. Datasets are carefully balanced to include a representative mix of male and female voices across a range of speaking styles and dialects. Model performance is also evaluated separately by gender to identify and address any disparities. The current model shows a performance difference of 2.7% in accuracy and 3.9% in unweighted average recall (UAR), with slightly better results for female speakers. The training data primarily consists of English-speaking adult voices; voices from children or elderly individuals are currently underrepresented. Performance will be lower for other languages, especially those that are linguistically distant from English. The approach is continuously monitored and refined to support fairness and inclusivity, while improving generalization across diverse linguistic contexts. Optimizing Voice Analysis for Your Research The following recommendations can help you get high-quality input and reliable results when using FaceReader's voice analysis in your research. Setup - Use a high-quality microphone in a quiet environment: voice analysis only works on speech and background noise can negatively affect results. - Ensure the recording level is appropriate: neither too low (voice won't be detected) nor too high (to prevent clipping or distortion). - Avoid overlapping speech: voice analysis works best when one person speaks at a time. Research - Try voice analysis on sample data to make sure your setup is clean and the results are stable. - Results are relative, so compare values across time or across speakers rather than relying on a single absolute number. - Use in combination with facial expressions and the measurement of vital signs for more complete emotional insights. References - Reynolds, D. (2009). Gaussian Mixture Models. In: Li, S.Z., Jain, A. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. - Arnfield, S., Roach, P., Setter, J., Greasley, P., Horton, D. (1995). Emotional stress and speech tempo variation. Proc. ESCA/NATO Workshop on Speech under Stress, 13–15. - Braun, A. & Oba, R. (2007). Speaking tempo in emotional speech – a cross-cultural study using dubbed speech. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader 10 - Voice Analysis White Paper - How It Works URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-voice-analysis-white-paper-how-it-works Chapter: FaceReader How Does It Work? Unlike video, where each frame can be analyzed independently, audio-based emotion recognition requires a time window to extract patterns. A single moment of sound lacks information to determine emotional state, as vocal features such as pitch, loudness, and speech rate can only be measured over time. To account for this, each video frame is analyzed alongside the preceding second of audio, meaning that voice analysis begins only after enough audio has been processed to detect a signal. Detecting Voice Activity Voice analysis in FaceReader employs Voice Activity Detection (VAD) based on a Gaussian Mixture Model (GMM) to filter out audio that clearly falls outside the typical range of human speech. Although it does not explicitly classify segments as speech or non-speech, this approach helps reduce the impact of background noise and other irrelevant sounds. While GMM-based VAD is generally reliable under typical conditions, it is not immune to misclassifications, particularly in environments with overlapping speech, high levels of ambient noise, or non-speech sounds within the speech frequency range. When a valid voice signal is detected, the following vocal measures will be calculated and reported by FaceReader. Emotions Emotions are estimated based on a deep learning model that analyzes a broad set of vocal and audio features. These features are extracted from diverse datasets covering multiple languages and include both natural and acted speech to reflect a wide range of expressive variations. The model accounts for differences in gender, ethnicity, and speaking style, aiming to provide a robust estimation of the expressed emotional state. The model focuses on prosodic features such as pitch, loudness, speech rate, and intonation, rather than the semantic content of speech. This approach is less dependent on the spoken language, as it emphasizes how something is said rather than the specific words used. However, because the model was trained primarily on English-language data, its performance is highest for English speakers. Valence Valence represents the emotional positivity or negativity of speech and is derived from speech emotion recognition. - Positive emotions, such as happiness, contribute to a higher valence score. - Negative emotions, including anger and sadness, result in a lower valence score. Valence is normalized to a scale from –1 to 1, where –1 indicates strong negative affect, 0 is neutral, and 1 reflects strong positive affect. Arousal Arousal is estimated using both loudness and speech rate, which are also included as individual vocal measures in FaceReader. Higher loudness and faster speech are typically associated with excitement or stress, while lower loudness and slower speech indicate calmness or disengagement. Arousal is normalized to a 0 to 1 scale, with 0.5 being average arousal. When interpreted alongside valence, arousal helps differentiate between emotions that share a similar emotional direction but vary in intensity. For example, sadness (low arousal) versus anger (high arousal), both of which have negative valence. Loudness Loudness is a custom volume-independent measure of sound intensity. Variations in microphone sensitivity and speaker positioning can significantly affect the absolute volume of a recording. To address this, the loudness measure is computed using a continuously updated, normalized audio signal. For each frame, the system analyzes the past second of the audio signal. Within this one-second window, the audio is normalized to a maximum absolute amplitude of 1.0. This ensures that the measurement reflects the speaker's vocal dynamics — how energetically a person is speaking within their own dynamic range, rather than the recording conditions. Speech Rate The speech rate measure estimates how quickly a person is speaking. The algorithm detects peaks in the audio signal, typically corresponding to syllables, by identifying bursts of vocal energy. These peaks are counted over the past one-second window of audio, using an upper bound of 160 syllables per minute, which is suitable for capturing various emotional states. The count is normalized to a value between 0 and 1. A higher value indicates faster speech, while a lower value reflects slower or more deliberate speaking. Calibration Voice data is not automatically calibrated during acquisition. However, in the Project Analysis window, you can apply baseline correction to your voice data. This works by normalizing each voice feature based on its average across the selected samples (e.g., within a subject, session, or stimulus condition, depending on the analysis context). The result is a mean-centered dataset where inter-subject or inter-session comparisons are more meaningful. This approach is particularly useful in group analyses where absolute voice feature values are less informative than relative changes or patterns. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader 10 - Voice Analysis White Paper - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-voice-analysis-white-paper-introduction Chapter: FaceReader What Is Voice Analysis? Voice analysis is a powerful tool for understanding human emotions, offering a new dimension to affective computing. So, how does it work? Speech Emotion Recognition (SER) refers to the process of identifying and classifying emotional expressions based on vocal characteristics, using machine learning models trained on diverse datasets. By analyzing features such as pitch, loudness, intonation, and speech rate, SER can estimate the expressed emotional state of a speaker, independent of the actual words spoken. SER has a wide range of research applications, including human-computer interaction, psychological research, and human factors studies. It enables the investigation of emotional responses in social interactions, cognitive load during task performance, and user experience in conversational systems. By integrating voice analysis with existing affective computing technologies, researchers can gain a more comprehensive understanding of human emotions. Voice Analysis in FaceReader FaceReader, which already provides facial expression analysis, eye tracking, heart rate, and breathing rate estimation, now also supports voice-based emotion recognition. This multimodal approach allows for a more holistic assessment of affective states by combining facial and vocal expressions. With this enhancement, FaceReader can better capture subtle emotional cues, making it an even more powerful tool for emotion research and applied behavioral studies. This white paper discusses the methodology and expected performance of FaceReader's voice analysis techniques, including the assessment of potential bias and practical guidelines for optimal results. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader 10 - What Is New In FaceReader 10 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-what-is-new-in-facereader-10 Chapter: FaceReader What Is New In FaceReader 10 Customers that upgrade FaceReader from a previous version should read this section carefully to get an impression of the new features in FaceReader 10. If You Upgraded From FaceReader 9.1 Voice Analysis Module FaceReader 10 comes with the Voice Analysis Module which allows you to detect emotions in the voice (Neutral, Happy, Sad and Angry), Valence and Arousal in the voice, Loudness and Speech rate. New Vital Sign: Breathing Rate FaceReader 10 allows you to measure three vital signs. The RPPG Module in previous FaceReader versions made it possible to measure heart rate and heart rate variability. In FaceReader 10 it is possible to measure respiratory (breathing) rate as well. The RPPG Module has, therefore, been renamed and is now called the Vital Signs Module. Advanced Research Module This module allows you to analyze multiple faces in a video. With this module and the Stimulus Presentation Tool you can also track the gaze of the test participant to assess what he/she is looking at when you present stimuli. See The Advanced Research Module and Stimulus Presentation Tool Project Analysis Module The Project Analysis Module is now part of the basic FaceReader functionality. Improved Accuracy The accuracy of basic facial expression analysis, analysis of Action Units, baby Action Units and the subject characteristics estimation has improved, including a relatively better estimation of contempt. In addition, there are significant improvements in facial state estimations (mouth and eyes open/close) and in left/right unilateral Action Unit activations. If You Upgraded From FaceReader 9.0 Improved Action Unit Classification In FaceReader 9.1.8 and higher the classification of Action Units gives slightly lower intensities than in older versions of the software. In older versions non-active Action Units could be classified with intensity level A, A-level Action Unit activations with level B, etc. The values of Contempt, Arousal, facial states (except Gaze direction), most custom expressions and Valence in Baby FaceReader are also affected as these parameters are based on Action Units. For the most accurate Action Unit estimation it is important to use the latest version of the software. See Introduction To Action Unit Classification for more information. Improved Face Modeling In FaceReader 10 the face modeling has been improved. The new model is just as fast as the model in FaceReader 9.0 but the modeling of the mouth, the eyes and the eyebrows is much better. This is important in situations in which the test participant talks (for instance, when using a think aloud protocol in a usability test) or eats. Improved Project Analysis Functionality The Project Analysis now shows a default layout upon opening. The data selection window has been re-arranged to make it easier to use. Charts and tables have more extensive headers which can be adjusted. New Custom Expressions New custom expressions have been added to FaceReader 10, including 'Spontaneous laughter', 'Talking', Frowning and 'Raising Eyebrows'. FaceReader 10 also has extra processors to define custom expressions. If You Upgraded From FaceReader 8.1 New Face Finding And Modeling Technique FaceReader 10 uses a new and improved face finding and face modeling technique. It is more accurate and much faster and can better deal with rotations. See How Does FaceReader Work? for more information. As a result there are only three face models available now (the 'General' model, 'East-Asian' model and if you have Baby FaceReader, the 'Baby' model). The 'Children' model and the 'Elderly' model have become obsolete. Renewed Project Analysis Design The Project Analysis section has been re-designed. In addition to the basic facial expressions you can now also analyze Action Units, Custom Expressions, Heart rate, Heart rate variability, Respiration rate, and Expressions in the voice. See Project Analysis for more information. Please note that you need the Action Unit Module to measure Action Units and Custom Expressions, the Vital Signs Module to measure heart rate, heart rate variability, Respiration rate, and the Voice Analysis Module to measure expressions in the voice. Project Analysis is now also available for Baby FaceReader. Improved East Asian Model The East Asian face model has been improved. A validation set of images of East Asian faces has been created and a study has been carried out to validate the enhancements and to further improve the East Asian model. Improved Gaze Direction Measurement Previous versions of FaceReader could track the test participant's gaze in three directions (Left, Right and Forward). In FaceReader the gaze direction can be tracked more accurately, in nine directions (Left, Left-Up, Left_Down, Right, Right-Up, Right-Down, Up, Down and Forward). FaceReader can also determine the gaze angle now (Horizontal gaze angle and Vertical gaze angle). New Custom Expressions FaceReader 10 comes with a number of new custom expressions, including: Attention, Laughing, Smiling, Spontaneous laughter, Talking, Blinking, Frowning, and Raising Eyebrows. See Custom Expressions for more information. More Functionality In Stimulus Presentation Tool A new version of the Stimulus Presentation Tool allows you to display your stimuli full-screen. It is also possible now to define the length of the pause between stimuli and to track the test participant's gaze. See The Stimulus Presentation Tool for more information. Software Activation Code Instead Of Hardware Key FaceReader 10 comes with a software activation code as the license which makes it easier to work with the software. For existing customers it is still possible to upgrade their hardware key. If You Upgraded From FaceReader 8.0 Reporting Display FaceReader now has a fully customizable visualization of its analysis output. You can use it on a second monitor, or to create visuals in a report or presentation. The Reporting Client has been removed, its Valence Monitor and Smiley windows are available in the Reporting Display. See Reporting Display In FaceReader's Output Consumption Behavior Module The Consumption Behavior Module lets you determine whether your test participant shows chewing behavior, takes a bite of the food item you are testing or takes a sip of the drinks you offer. See The Consumption Behavior Module If You Upgraded From FaceReader 7 Baby FaceReader Depending on your FaceReader license you have the regular version of FaceReader, Baby FaceReader or both. With Baby FaceReader you can analyze faces of babies from the age of 6 months and infants up to the age of 2 years. Baby FaceReader can analyze 20 Action Units, Valence and Arousal. You can extend Baby FaceReader with the Vital Signs Module. Custom Expressions FaceReader 10 lets you define your own expressions based on the default facial expressions, Valence, Arousal, Action Units and other parameters. The Affective Attitudes Boredom, Confusion and Interest are now part of the Custom Expressions and a large number of other custom expressions are available in FaceReader's Custom Expression Library. To define Custom Expressions you need the Action Unit Module. For more information see Custom Expressions. Audio Recording If you use FaceReader with a webcam, you can now record audio with your videos. This is important in focus group tests, interviews and usability tests. Left And Right Action Units The Action Unit Module now tells you not only whether Action Units are active in the face but also whether they are active on the left side or right side of the face. 11 out of the 20 Action Units that FaceReader can analyze, are unilateral. This functionality is especially useful if you work with patients that are semi-paralyzed, subjects that have had a stroke or people suffering from Parkinson's disease. For more information see Unilateral Action Units. Infrared Recordings If you want to film your test participants in the (near) dark, for instance, when analyzing people's facial expressions in a cinema, you can use (near) infrared light with a camera that is sensitive for this type of light. FaceReader 10 supports (near) infrared recordings. Please note that it is not possible to measure heart rate, heart rate variability, and breathing rate with infrared recordings. Export Improvements You now have more options to choose from when you export your data. This way it is easier to adjust the format of the export file to the requirements of analysis programs like SPSS. New Camera Besides the Microsoft LifeCam Studio that was already supported in previous versions, FaceReader 10 now also supports the Logitech BRIO webcam. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 10 - Working With Custom Expression Blocks URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-10-working-with-custom-expression-blocks Chapter: FaceReader A Custom Expression Block In Detail - Color — The color on the left side of the block indicated what type of block it is (red for input blocks, orange for processors, purple for Custom Expressions and green for the output block). - Name — The name of the block. - Value Or State — The value of an input block (as defined with the input simulator, shown in a blue field) or the output value or state of a processor block (shown in a green field). - Description/Parameters Button — Click the pencil button to enter the parameters and to view a description of the block. - Connectors — Use the connectors to connect the block to other blocks. Input blocks have one output connector. Processors have one or more input connectors and one output connector. When you hover with your mouse over a connector, you can see what type of input is required and how many inputs are allowed (for an input connector) and what type of output it has and how many output connections are allowed (for an output connector). To make a connection, drag with your mouse from one connector to the other. To delete a connection, hover with your mouse over it until it becomes green and then click. Note A block gets the label 'skipped' (in an orange field) if its value or state is not taken into account when calculating the output value of the Custom Expression. For instance, because one (or more) of its own input or output connections are missing or because a connection further down in the definition is missing. Working With Custom Expression Blocks Copy And Paste A Block Right-click a block, select Copy and then right-click it again and select Paste to duplicate the block. Delete A Block Click the block and then click Delete on your keyboard or right-click the block and select Delete. Multi-Select Blocks Select multiple blocks to move them together in one of the following two ways: - Press the Ctrl key on your keyboard and select multiple blocks. - Drag with your mouse to draw a box around multiple blocks. Source: FaceReader 10 Reference Manual (Help), Noldus Information Technology --- ## FaceReader 9 - API Messages and Data Format URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-9-api-messages-and-data-format Chapter: FaceReader Message Packages The described messages are sent as bytes over TCP. A message is converted to bytes in the following manner: - The first 4 bytes contain the length in bytes (TypeNameLength) of the typename of the message. - Typenames can be: - FaceReaderAPI.Messages.ActionMessage - FaceReaderAPI.Messages.ResponseMessage - FaceReaderAPI.Data.Classification - The next TypeNameLength bytes contain the typename as UTF-8 encoded bytes. - The rest of the bytes are the Message XML as UTF-8 encoded bytes. The total message length is calculated as follows: MessageBytesLength = 4 + TypeNameLength + MessageXmlLength The messages are prefixed with the length of the message to make receiving easier. The actual package sent over TCP consists of the following bytes: - The first 4 bytes contain the total length of the package (MessageBytesLength + 4). - The rest of the bytes contain the MessageBytes. PackageBytes = array of bytes of length MessageBytesLength + 4 Technical Support Technical support on using the Application Programming Interface is available for customers with NoldusCare. Please look on our web site at http://www.noldus.com/support-center/nolduscare for more information about NoldusCare. The use of the Application Programming Interface itself is supported for customers with NoldusCare. However, due to the large number of possible programming languages and operating systems that allow implementation of the API into custom made applications, we are unable to provide active support for the applications you make yourself. If you have any problems, questions, remarks or comments, please let us know. From the Help menu select Noldus Online and then Contact Help Desk, or browse to the MyNoldus section on our website. Under Get Support you will find the contact details of the help desk in your region. Note that if you send us videos showing people's faces, you should have permission from those people that you can use the video for that purpose, and you may need to sign a form granting consent for us to use those videos. Before you contact Technical Support, please have the version number and license number of your copy of FaceReader available. To find these numbers, from the Help menu select About. Please refer to the Contact section on our web site (www.noldus.com) for other contact information. Source: Application Programming Interface - FaceReader 9 Technical Note, Noldus Information Technology --- ## FaceReader 9 - API Overview and Usage URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-9-api-overview-and-usage Chapter: FaceReader What Is an API? An application programming interface (API) is a particular set of rules and specifications that software programs can follow to communicate with each other. It serves as an interface between different software programs and facilitates their interaction, similar to the way the user interface facilitates interaction between humans and computers. This document describes how the FaceReader API can be used to integrate FaceReader into another application or framework. You do NOT need to read this document if you want to use FaceReader as a standalone tool. If you want to use the API, please contact our support department for the possibilities. Our support department can also supply you with an example program that can receive FaceReader data. You can contact our support department via the Help menu of the FaceReader program, or via our website www.noldus.com/support-center. What Can the FaceReader API Be Used For? The FaceReader API allows you to integrate FaceReader with third-party software or your own software. It allows you to: - Start and stop FaceReader analysis. - Score Stimuli and Event Markers (only with the Project Analysis Module). - Receive the classification results from FaceReader (live as they become available). Whenever FaceReader has classified an image, video frame or camera frame, a network package containing the emotional state or detailed values is sent out to connected applications (TCP/IP) that can then use these results. This allows application developers to, for example, adjust the content of a website or application based on the emotions of a user or to log FaceReader values together with input values from other sensors. In early versions of FaceReader (3 or lower) this was already possible by constantly reading the last line from the "live log" that FaceReader can produce. However, the API offers a number of advantages: - Lower I/O overhead; no hard disk operations are necessary anymore and results are only sent once they become available. - Integrating with applications on platforms other than Windows becomes easier as reading large log files from shared network locations is not always feasible. - Integration with applications running on PCs in a completely different network, possibly on the other side of the world. - Packages are sent in XML format which can be parsed consistently, regardless of the settings you choose in FaceReader. How to Use the API To make use of the API there are two options: - Use the supplied FaceReaderAPI.dll. This is a .NET dll containing all functionality needed to receive from and send messages to FaceReader. The way to use this dll is explained by the sample source code of the FaceReaderExternalControlSample application. - Build your own TCP communication application and send the messages defined in the API. This is explained in this document. Receiving FaceReader Data in Microsoft .NET Applications For developers who use Microsoft .NET technology a library (FaceReaderAPI.dll) has been included that allows you to communicate with FaceReader with only a few lines of code. Preparation – Start FaceReader - Install and start FaceReader. - Choose File > Settings > Data Export. - Under External Communication (API and Stimulus Presentation Tool), select Enable External Control. - Use FaceReader as you normally would. You may close all visualization windows to speed up the analysis. Adding FaceReaderAPI.dll to Your Project - Make sure the .NET 4.8 framework is installed on the computer where this dll is used. This framework can be downloaded from the Microsoft Download website, using Automatic Updates (check the Optional components). Alternatively, install FaceReader. This will automatically install the .NET framework if it is missing. - Add FaceReaderAPI.dll as a reference in your project. Build Your Own TCP Communication Application The FaceReader API uses TCP messages to talk to FaceReader and to receive messages from FaceReader. These messages are XML documents describing the information. There are three types of messages: - Action Message – Used to make FaceReader perform an action. Possible actions are: - Start Analyzing – makes FaceReader start the currently open Analysis. - Stop Analyzing – makes FaceReader stop the currently open Analysis. - Start Receiving Detailed Logs – tells FaceReader to start sending detailed logs to this client. - Start Receiving State Logs – tells FaceReader to start sending state logs to this client. - Stop Receiving Detailed Logs – tells FaceReader to stop sending detailed logs to this client. - Stop Receiving State Logs – tells FaceReader to stop sending state logs to this client. - Get Stimuli – makes FaceReader send a Response Message containing a list of the available stimuli in the project. - Get Event Markers – makes FaceReader send a Response Message containing a list of the available event markers in the project. - Score Stimulus – makes FaceReader score a certain stimulus at the current timestamp. - Score Event Marker – makes FaceReader score a certain event marker at the current timestamp. - Response Message – Used by FaceReader to send a response corresponding to a received Action Message. Possible responses are: - Error – the action defined by the Action Message was not possible or another error occurred. - Success – the Action Message was handled correctly. - Sends Stimuli – FaceReader sends the available stimuli in the project as a response to a Get Stimuli Action Message. - Sends Event Markers – FaceReader sends the available event markers in the project as a response to a Get Event Markers Action Message. - Classification Message – Contains the results of a frame/image classified by FaceReader. Can be either: - State Log – contains the dominant expressions only. - Detailed Log – contains all the classifications enabled in the Logging Settings. Action Message An action message contains: - Id – The Id can be any string. Can be used to identify a Response Message. FaceReader will send the Response Message corresponding to this action with the same Id. - Action Type: - FaceReader_Start_Analyzing - FaceReader_Stop_Analyzing - FaceReader_Start_DetailedLogSending - FaceReader_Start_StateLogSending - FaceReader_Stop_DetailedLogSending - FaceReader_Stop_StateLogSending - FaceReader_Get_Stimulus - FaceReader_Get_EventMarker - Information – Can be any amount of strings. Currently only the messages for scoring a stimulus or scoring an event marker should contain the name of this marker in the Information. Example of an Action Message Without Extra Information ID01 FaceReader_Start_Analyzing Example of an Action Message With Extra Information ID02 FaceReader_Score_Stimulus Stimulus 1 Response Message A response message contains: - Id – The Id corresponds to the Action Message this message is responding to. - ResponseType: - FaceReader_Sends_Error - FaceReader_Sends_Success - FaceReader_Sends_Stimuli - FaceReader_Sends_EventMarkers - Information – Can be any amount of strings. Contains for example an error message, a success message, or the Stimuli/Event Markers that the project contains. Example of a Response Message With Information FaceReader_Sends_Error Already analyzing Example of a Response Message With Multiple Information Items FaceReader_Sends_Stimuli Stimulus 1 Stimulus 2 Stimulus 3 Classification Message A classification message contains: - Id – The Id corresponds to the Action Message this message is responding to. - LogType: - DetailedLog - StateLog - AnalysisType: - Video - Camera - FrameNumber - AnalysisStartTime – Start time of the Analysis, when the first result was analyzed. - FrameTimeTicks – Timestamp of the frame in ticks (1 second = 10,000,000 ticks). - In case of video, the FrameTimeTicks is the frame time in the video. - In case of camera, the FrameTimeTicks is the frame time past the AnalysisStartTime. - ClassificationValues – List of ClassificationValue objects: - Classification Value - Type - Value (in case of a numeric value) - State (in case of a string value) - Label – Name of the ClassificationValue. - Value – Only has a value if Type == Value. Can be any amount of floats. - State – Only has a value if Type == State. Can be any amount of strings. Example of a Value-Typed ClassificationValue Value 0.201352075 Example of a State-Typed ClassificationValue State Female Example of a MultiValued-Typed ClassificationValue Value 282.03125 301.93515 290.5138 300.786652 300.093658 302.1726 Example of a Small Detailed Log Note that the ClassificationValues reported by the API are selected with File > Settings > Data Export > Export (Detailed Log, ODX, N-Linx and API). DetailedLog Video 9244 2012-08-01T06:54:24.4580478+02:00 3697600000 Value 0.201352075 Value 0.00125725183 Value 0.151250109 Value 0.2761046 Example of a State Log StateLog Video 9601 2012-08-01T06:54:24.4580478+02:00 3840400000 State Happy Source: Application Programming Interface - FaceReader 9 Technical Note, Noldus Information Technology --- ## FaceReader 9.1 - SBLK Activation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-91-sblk-activation Chapter: FaceReader FaceReader 9.1 – Activating Your Software Based License Software based licenses can be activated as either Fixed or Floating. For more information on the differences between Fixed and Floating, see the License Management section. FaceReader licenses have a variety of modules (Project Analysis, Action Unit, Consumption Behavior, etc.). Some licenses in the lab might not contain any modules while other licenses could have all the modules. When the modules vary from license to license, this results in a new activation key for each module variation. For example, to save costs you might have one license with just the Project Analysis module and another license with all possible FaceReader modules. In this scenario, you will be sent 2 Activation Keys. When you have multiple licenses with the same modules, these can all reside under the same Activation Key, which has multiple Seats. You can fix or float any software based license, regardless of how many Activation Keys or Seats you have. Activation Activating As Fixed – PC With Internet Connection - Download and install FaceReader 9.1 (see Installing FaceReader 9.1 below). - Launch FaceReader 9.1. - Select Activate software license key. - Select Fixed – On this computer only. - Enter the provided Activation Key. - You are now ready to use FaceReader 9.1. The PC can be online or offline during use of FaceReader 9.1. Activating As Fixed – PC Without Internet Connection - Download and install FaceReader 9.1 (see Installing FaceReader 9.1 below). - Launch FaceReader 9.1. - Select Activate software license key. - Select Fixed – On this computer only. - Enter the provided Activation Key. - Scan the QR code using the camera of your smartphone to get a Computer Key. - Under Activate Offline, enter the Computer Key. - You are now ready to use FaceReader 9.1. The PC can be online or offline during use of FaceReader 9.1. Activating As Floating – PC Requires Internet - Download and install FaceReader 9.1 (see Installing FaceReader 9.1 below). - Launch FaceReader 9.1. - Select Activate software license key. - Select Floating – On multiple computers. - Enter the provided Activation Key. - You are now ready to use FaceReader 9.1. The PC must be online during use of FaceReader 9.1. Installing FaceReader 9.1 - Download the FaceReader 9.1 installation file (FaceReader_9.1_Setup.exe) from the Noldus website. - Alternatively, you can download from MyNoldus: - Log in or create a new account. - Go to: Downloads > FaceReader > Versions > Current Version > FaceReader – Setup – 9.1. - Locate and double-click on FaceReader_9.1_Setup.exe to install. License Management Permissions - Fixed license (online): When activated as a Fixed license via the internet, it will check the license server for permission, after which it will lock the license to that specific PC for 90 days. After 90 days, the license checks the server for permission again. - Fixed license (offline): When activated as a Fixed license without an internet connection, it will check the license server for permission, after which it will lock the license to that specific PC for 365 days. After 365 days, the license will require reactivation to confirm permission for another year of use. - Floating license: Permission is shared. Internet access is required each time a PC wants to utilize the full version of the software (i.e., acquire data), as it uses the internet to check for license permission. Access to the Key/Seat is on a first come, first served basis. You can switch between Fixed and Floating activations by deactivating via Help > Deactivate License. When a license is deactivated, it is immediately available to fix or float on another PC. Fixed License A Fixed license is used on a single computer. - An internet connection is required during activation but not during use of FaceReader 9.1. - Once a license is activated as Fixed, it permanently occupies a Seat. - If you receive an error indicating the license is already fixed on another PC, deactivate it on that PC first before activating it on a new one. Floating License A Floating license (with one or more Seats) can be accessed on multiple computers. - A permanent internet connection is required. - You can install FaceReader 9.1 on as many PCs as you would like, but only the number of Seats purchased can be used simultaneously at any given time. - Users must close FaceReader 9.1 after use. This will free up a Seat so another user can use the software on another computer. - You do not need to deactivate after use — simply close FaceReader 9.1 to free up the Seat. Tips For Managing Floating Licenses - Use a shared online calendar, spreadsheet, or schedule to keep track of who is using FaceReader 9.1 and when. This helps you identify who last used it, should you need to ask them to close FaceReader 9.1 to free up a Seat. - Keep a list of all PC names (company and private) that have FaceReader 9.1 installed. - For each Activation Key, note whether it is set to Fixed or Floating. - If you have trouble accessing the license due to a strict local network, ask your IT department to add an exception for: https://qlmlicenses.noldus.com:9999 Support If you run into any issues, please submit a support ticket on the MyNoldus client portal. Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## FaceReader Online - White Paper - Platform and Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-online-white-paper-platform-and-analysis Chapter: FaceReader Online Facial Expression Analysis FaceReader Online is a platform for facial expression analysis via the web. You can send your participants a link that will open a video in their browser. While they watch it on their own computer, anywhere and anytime, the webcam records their facial expressions. The service can easily be incorporated in a web-based survey. While the data is being collected, you can log into the platform and watch the results come in. The analysis is based on FaceReader software, which is used worldwide at more than 600 institutes. The results that FaceReader Online currently gives are six basic emotions and neutral, plus valence and arousal. This can be a valuable addition to your marketing research. FaceReader Online In a Nutshell - Based on widely used validated FaceReader technology. - Get quick results from a diverse population from all over the world. - Get insights into implicit emotional processes. - Run a study in a natural environment. - Do cost-effective pretesting of your video materials. - Integrate it with your survey tool software. Implicit Measures Give Valuable Insights The world is full of messages that we cannot process consciously. However, often in survey research we ask people to comment on something afterwards, while this is not the usual way people process the information. In some cases, implicit processes can predict behavior better. For example, especially when people are uncertain about their decision or when they do impulse shopping, they are more influenced by implicit memory processes. It is therefore useful to also measure automatic responses of people while they experience something, in addition to asking them retrospectively. Emotional Impact Is Important So many processes occur not entirely within conscious awareness. Especially information with emotional value has an impact on memory and decision-making. A structural modelling study argues that it is best to do this by measuring the affective non-verbal response instead of the cognitive response. Furthermore, there is a relation between happy facial expressions and purchase intent and in-market performance. Thus, measuring if people are responding with laughter or frowns is a valuable addition to just asking whether they liked the commercial. Facial Expressions and Online Measures Benefits of Online Testing FaceReader Online allows testing to occur at home or another setting outside the laboratory (restaurant, school, office, etc.). These more natural environments can elicit a more 'real' emotional response. It also makes it possible to reach and compare a very broad audience, for example in different cities or countries. When you do not have to invite participants to your lab or office, it becomes easier to get large numbers of participants. It saves costs, since you can let people do a short study and do not have to pay for travel expenses. Limitations of Online Research There are also some limitations when doing online research. The quality of the recordings could be lower, due to bad lighting or low quality cameras. You do not control the setting, so camera position could also be suboptimal. It is likely that you will have to exclude more participants than in a lab study, but with the lower costs, you can easily compensate by inviting more participants. In addition, if you are interested in small and specific facial movements, you are better off inviting participants to your lab. Still, FaceReader Online can be ideal for testing your material before you run a lab study. Relevant Use Cases and Comparisons Questions You Can Study Whether you are a market research company, a marketing agency, or a university researcher, you can find relevant questions to study with FaceReader Online. It is especially suitable for testing a commercial or other type of video. Some relevant questions include: - What are reasons for high performing or low performing ads? - What message works best for your brand? - Are you reaching the right target audience? - Which part of the video has the strongest emotional impact? With FaceReader Online you can visualize the entire emotional journey that people experience while they watch the video. When you look at the valence (which combines happiness and negative emotions), you see the impact of the video with only one line. This is useful when applying the famous peak-end rule from psychologist Daniel Kahneman, which states that people usually remember the peak and end of an experience the best. Finding the Right Comparisons Since there is a wide range of videos and commercials, make sure you create a good comparison. FaceReader Online has an easy to use comparison insight feature that highlights relevant differences between, for example, a video or audience. You can compare new and old videos to see the improvement over time, and compare the effects of your message within the most suitable population. Remember that, like many other implicit measures, facial expressions can be subtle. People respond differently to certain parts of a video, and results should be interpreted within the appropriate context. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## FaceReader Online - White Paper - Study Design URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/facereader/page/facereader-online-white-paper-study-design Chapter: FaceReader Designing Your Study Some people are very inexpressive in general, which means that average emotional scores can be low. However, when you make the right comparison relevant, differences are easily highlighted. A Good FaceReader Online Study in a Nutshell - Find a suitable research question - Compare your results to a control video or group - Find a good panel - Give people clear instructions Try to Instruct the Participants Well Participating in a FaceReader Online study is very easy: participants do not have to install anything, but just have to give access to their camera. The video recordings are transferred via a secure connection to the FaceReader Online server. The recorder runs on HTML5, so it works with all modern web browsers. It also works on new Android devices; however, this is not optimal (e.g. due to the smaller screen and direction of camera). To make sure you get a good recording, instruct your participants in advance. For example, strong back lighting should be avoided, or lighting from one side. Participants should also try not to move away from the camera, or be eating during the recording. FaceReader Online gives the recording a quality score based on the proportion of frames that could be analyzed. Privacy by Design Make sure you inform people well in advance of the study they will participate in. We include a standard informed consent before the camera is started. Our service is completely compliant with the European General Data Protection Regulation (GDPR). Nevertheless, not all participants may want to participate in a study where they are recorded. We also have a privacy by default design, where recordings are immediately deleted after analysis. In that case, no humans will ever see the recordings. For more information and sample studies, visit www.facereader-online.com. You can also get a free trial account to see if it fits your project by sending an email to info@humaninsightservices.com. References - Loijens, L., & Krips, O. (2018). FaceReader Methodology Note. Noldus Information Technology. https://info.noldus.com/free-white-paper-on-facereader-methodology - Noldus Information Technology. (2016). FaceReader Online - Online expression analysis for market research. Available on request via info@noldus.nl. - Shapiro, S., & Krishnan, H. S. (2001). Memory-Based Measures for Assessing Advertising Effects: A Comparison of Explicit and Implicit Memory Effects. Journal of Advertising, 30(3), 1–13. - Galdi, S., Arcuri, L., & Gawronski, B. (2008). Automatic Mental Associations Predict Future Choices of Undecided Decision-Makers. Science, 321 (August), 1100–1103. - Morris, J. D., Woo, C., Geason, J. A., & Kim, J. (2002). The power of affect: Predicting intention. Journal of Advertising Research, 42(3), 7–17. - Lewinski, P., Fransen, M., & Tan, E. (2014). Predicting Advertising Effectiveness by Facial Expression in Response to Amusing Persuasive Stimuli. Journal of Neuroscience, Psychology, and Economics, 7(1), 1–14. - Rogers, J. & Macbeth, A. (2015). In-Market effectiveness of advertisements: Measured automatically with FaceReader. Noldus Information Technology. Available on request via info@noldus.nl. Contact Information International Headquarters Noldus Information Technology bv Wageningen, The Netherlands Phone: +31-317-473300 Fax: +31-317-424496 Email: info@noldus.nl North American Headquarters Noldus Information Technology Inc. Leesburg, VA, USA Phone: +1-703-771-0440 Toll-free: 1-800-355-9541 Fax: +1-703-771-0441 Email: info@noldus.com Representation Noldus Information Technology is also represented by a worldwide network of distributors and regional offices. Visit the Noldus website for contact information. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## Media Recorder - Camera Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-camera-configuration Chapter: Media Recorder Media Recorder - Camera Configuration IP Cameras and ONVIF Support Control can be done with MediaRecorder and audio from the camera can be recorded. For cameras that do not support ONVIF, pan, tilt, and zoom control must be done with a browser and audio must be recorded with a microphone connected to the sound card of the computer. Power over Ethernet IP cameras can be connected to a PoE (Power over Ethernet) or PoE+ switch to supply them with power. This way no extra power cables are needed. Each device is connected to one channel on the switch. A PoE switch can deliver up to 15 Watt per channel. A PoE+ switch has a higher capacity per channel (up to 30 Watt per channel). Make sure that the maximum total capacity of the switch is high enough for all cameras together. Cameras may also be powered using a 2 or 4-port Network Interface Card (NIC). Example: you connect four cameras that need 30 Watt each to a PoE+ switch. This PoE+ switch must deliver at least 4 x 30 = 120 Watt. - Axis M5525 - requires a regular PoE switch. - Axis M5054 - requires a regular PoE switch. - Axis P1375 - requires a regular PoE switch. The PoE or PoE+ switch must allow a speed of at least 1 Gb per second. Recording Devices - USB Important Notes About USB USB 2 and 3 Ports The supported USB devices are all USB 3 devices and need to be connected to a USB 3 port. You recognize USB 3 ports by a double-S in front of the USB icon. Some USB 3 ports and connectors have blue labeling. The Dell Precision T3640 desktop PC sold by Noldus IT has both USB 2 and USB 3 ports. The Dell Precision 3551 mobile workstation only has USB 3 ports. USB Hub Do not connect your cameras to a USB hub. If you run short of USB connections, connect your license key, keyboard or mouse to a USB hub and connect your USB device directly to the USB port on your computer. Cable Length USB devices can be connected to the computer without an amplifier with a cable of 5 m. For every subsequent 5 m, an amplifier must be used each. In theory, when using a standard resolution, the cables could be extended this way to 30 m. However, not all devices support this. When Do I Need a USB Camera? USB cameras are very easy to use. However, the settings may be limited; for example, many USB cameras have fixed zoom. A USB camera may be perfectly suitable for a usability study in which you film a person sitting behind a computer. A USB camera also works very well to create video files for FaceReader. On the other hand, when you need to create a video file of a person further away from your camera, a USB camera may be less suitable. For videos with accurate time information, needed for EthoVision XT, you need a high-quality USB camera. Supported USB Cameras - Basler acA1920-155um - Basler acA2040-90uc Other USB cameras may also work. However, it could be that you have to change the Color space to MJPG. See Show frame rate, resolution and format. Tested Setups with EthoVision XT The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices, (4) recording time (hours), and (5) whether the test was carried out on a desktop PC (Dell T3640) or a laptop (Dell 3551). Device Resolution Frame Rate No. of Devices Recording Time (hrs) Desktop or Laptop Basler acA1920-155um 1920 x 1200 / 1920 x 1080 60 1 0.5 Desktop Basler acA2040-90uc 2040 x 2046 5, 10, 25, 50 1 8 Desktop Basler acA2040-90uc * 2040 x 2046 25 1 1 Desktop Basler acA2040-90uc ** 2040 x 2046 25 1 48 Desktop Basler acA2040-90uc 1920 x 1200 60 1 10 Laptop - * Tested with output quality settings "EthoVision" and "DanioVision". - ** Tested with output quality setting "EthoVision". Tested Setups for Use in The Observer XT - Portable Set-Up The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices, and (4) recording time (hours). Tests were done on a Dell 3551 notebook. Device Resolution Frame Rate No. of Devices Recording Time (hrs) Logitech Brio (separate videos, Picture-by-picture and Picture-in-picture, camera audio only) 1920 x 1080 30 2 1 Logitech Brio 4096 x 2160 10 1 0.5 Notes - When using the Logitech Brio camera, you have to change the Color space to MJPG. See Show frame rate, resolution and format. - With multiple USB 3 cameras it takes a while before they become visible in MediaRecorder as it takes time for USB 3 cameras to initialize. - Encoding the video stream of USB 3 cameras requires quite some processing capacity, which increases power consumption. If you use the supported devices on the recommended laptop, be aware that after 1 hour of recording the battery level drops from fully charged to 45%. Recording Devices - GigE Vision Cameras GigE Vision cameras are hereinafter referred to as GigE cameras. When Do I Need a GigE Camera? GigE cameras are high-performance industrial cameras. They can have a higher frame rate and resolution than other supported cameras. The images are sent unprocessed to the computer using a standard network cable (UTP). With a high frame rate and resolution this results in a very high transfer of data. You can connect a GigE camera directly to an Ethernet card on your computer. In this way you can obtain very high quality videos. An important advantage of GigE cameras is the possibility to have long cables between the camera and the computer. Network Requirements To use MediaRecorder with GigE cameras, the following network requirements apply: - An Intel Pro/1000 CT or Intel Pro/1000 PT (1 Gb) network adapter needs to be installed in the computer. - The cables must be suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. - We recommend using a dedicated network. Install and Setup If you bought a complete solution from Noldus IT, the network adapter is present in the computer, the GigE cameras are set up and the MediaRecorder settings are made. If you bought your cameras and MediaRecorder separately, you must do the installation and setup yourself. See Set up GigE cameras. Power over Ethernet GigE cameras can be connected to a PoE injector. This is a device that passes power along with data (in this case, video data from the camera) on twisted-pair Ethernet cabling. Cameras may also be powered using a 2 or 4-port Network Interface Card (NIC). This way no separate power supply is needed. Supported GigE Cameras - Basler GigE camera acA1300-60gm mono. Color space: Y800. - Basler GigE camera acA1920-40gc color. Color space: RGB32. Tested Setups with EthoVision XT The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices, and (4) recording time (hours). Tests were done on a Dell T3640 PC. Device Resolution Frame Rate (fps) No. of Devices Recording Time (hrs) Basler acA1300-60gm 640 x 480 / 800 x 600 / 1024 x 768 / 1280 x 1024 60 1 0.5 Basler acA1300-60gm 1284 x 1025 25, 60 1 8 Basler acA1300-60gm 960 x 640 30, 60 4 24 Basler acA1300-60gm 1280 x 1040 40 4 24 Basler acA1300-60gm * 1280 x 960 60 4 1 Basler acA1920-40gc 1920 x 1200 25 1 18 - * Tested with output quality setting "EthoVision" and "DanioVision". IMPORTANT: The file size of an 8, 18, and 24 hour recording is very large (at least 12 GB). When four devices were tested, separate videos were made. Cable Length In theory, a cable length of 150 m is possible. However, the maximum length tested in-house with satisfactory results was 25 m. Recording Devices - Screen Capture Devices When Do I Need a Screen Capture Device? You can easily record what your test participant is doing on his or her computer with a screen capture device. Such a device will provide you with high quality images of the screen at which the test participant is looking. Supported Screen Capture Devices Epiphan Screen Capture Devices Epiphan screen capture devices are hardware devices that will stream the screen captures of the test computer to the computer with MediaRecorder. MediaRecorder supports Epiphan Pearl Nano. See Epiphan screen capture devices. MR Screen Capture Tool The Screen Capture tool is an add-in to your MediaRecorder license. See: Use of the Screen Capture tool. Use of the Screen Capture Tool The Screen Capture tool is an add-in to your MediaRecorder license. It allows you to record the screen of the computer with MediaRecorder. It is a software tool that is built in to MediaRecorder. IMPORTANT: To record the screen of a computer other than the one with MediaRecorder installed, use an Epiphan screen capture device instead. Prerequisites - You record the full screen of the PC with MediaRecorder. - You record one screen only. - You use MediaRecorder on the Dell Precision 3551 mobile workstation. See also System requirements. Drivers For the MR screen capture option, you do not need to install device drivers. Supported Setup (Portable Lab) The table below shows the maximum supported (1) resolution, (2) frame rate (fps), and (3) recording time (hours) on a Dell 3551 notebook. Device Resolution Frame Rate Recording Time (hrs) Logitech Brio + Built-in screen capture 1920 x 1080 30 1 Other USB cameras may also work. However, it could be that you have to change the Color space to MJPG. See Show frame rate, resolution and format. You can also combine built-in screen capture with, for instance, an IP camera. Procedure - In MediaRecorder, choose File > Video Settings. - From the Video device list, select Medialooks Screen Capture. - Click the Advanced Video Settings button to select recording options. - In the Medialooks Screen Capture Properties window that opens, select the frame rate and resolution in the Output field. Although you are allowed to select a high frame rate, the actual frame rate of the recording will depend on the processor speed of your computer. Most likely this will be in the order of magnitude of 10 frames per second. - Although this window has several recording options, the use of the built-in screen capture is designed and supported to record one window on the MediaRecorder computer only. Minimize MediaRecorder after you start recording. To Re-enable Settings As soon as you select the screen capture device, it is used for the video preview and you cannot change its settings. The Output fields are grayed out. To enable these fields again: - Close the Medialooks Screen Capture Properties window. - From the Video device list choose Select video device and click Apply. - Reselect the Medialooks Screen Capture device again and click the video icon to re-open the Medialooks Screen Capture Properties window. You can now change the frame rate and resolution again. Notes - The actual resolution of the recorded file may be lower than the value set in Output. - The use of the built-in screen capture option is supported with a Windows text size of 100% or 125% (Control Panel > Display). - If you change Windows text size to 125%, this may result in MediaRecorder capturing only part of the screen. To solve this, do the following: - Make sure MediaRecorder is not running. - Open the folder C:\Program Files\Noldus\MediaRecorder 6. - Right-click the file MediaRecorder.exe and select Properties. - Open the Compatibility tab. - Select Disable display scaling on high DPI settings and click Apply. Epiphan Screen Capture Devices Supported Devices MediaRecorder supports Epiphan Pearl Nano. This is an encoder device that is able to stream the output of the video card of the test computer to the computer with MediaRecorder. Notes - Audio: To record audio, connect a microphone to the sound card of your computer and select that source in MediaRecorder settings. - Input: Epiphan Pearl Nano only uses HDMI input. - Frame rate: The actual frame rate of the recorded video is limited by the bandwidth of the screen capture device. - Resolution: To record enough screen detail, we recommend using signal resolution as frame size when using the screen capture device. MediaRecorder supports a resolution of 1920 x 1200. However, screen capture devices by default use the resolution of the screen of the test computer. To change the recorded resolution, change the resolution of the monitor of the test computer. Recording Video To Get Started To start working with MediaRecorder, follow these main steps: - Connect all devices and, if applicable, switch them on. - If you have a hardware key, insert it into a USB port of the computer. - Start MediaRecorder. The main window now opens. The first time it opens, the preview window is black. That is because you still have to select the cameras. Proceed with the next steps to do so. - Click Video Settings to select the cameras, microphones and, optionally, the output. See: - Select a video device - Select an audio device - Video file options - Record your videos. Select a Video Device Use this procedure to select the cameras for recording. Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You have opened the Video Settings window. To do so, choose File > Video Settings, or click Video Settings in the main window. If the Video Settings button is not visible, the recording properties may be closed. Click Recording Properties at the bottom of your window. By default the recording properties are open. Procedure In the Video Settings window: - Select your camera from the Video device list. - IMPORTANT: If you have IP cameras, see Set up IP cameras for how to set these up and select them in MediaRecorder. - IMPORTANT: If you use the Screen Capture tool, see Use of the Screen Capture tool on how to select the built-in screen capture device. - Select the preferred frame rate and resolution. The options depend on your type of camera. - For advanced camera settings, click the video symbol next to the name of your camera. The available options depend on your camera. For some cameras you can zoom and adjust settings for brightness and contrast. - Optionally change the names in the Video name column, to, for example, Webcam, or IP camera. - To record audio as well, continue with Select an audio device. - Optionally adjust Video file options. - When satisfied with the settings, click OK to return to the main window and record your videos. See Record your videos. Note: Frame Rate and Resolution By default, the optimal combination of frame rate and resolution for the camera is selected. If you increase the frame rate, the maximum resolution available goes down and vice versa. If you select an impossible combination of frame rate, resolution, and format, MediaRecorder gives a warning. Select an Audio Device Use this procedure to select the audio source. Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You have opened the Video Settings window. To do so, choose File > Video Settings, or click Video Settings in the main window. Procedure - In the Video Settings window, select the microphones under Audio device. Choose between your computer microphone, a separate microphone, or the audio stream of your camera. Choose No audio if you do not wish to record audio. - Optionally record the same audio stream in all videos. To do so, select this checkbox. It means that the device defined as Audio device 1 will supply the audio stream for all your videos. - Check that the green bar is maximal when speech level is normal. Please note that in Picture-in-Picture mode, you may select which audio source to use for all the videos. This may be important if the first video is the screen capture device, which does not record audio directly. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder - Getting Started and Overview URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-getting-started-and-overview Chapter: Media Recorder Welcome to MediaRecorder Introduction MediaRecorder is a software package that makes digital video files with input of many different types of cameras. These video files can be used in the video analysis programs The Observer XT, EthoVision XT and FaceReader. Supported Video Devices MediaRecorder is supported with several types of video devices. In the section on the type of device, you find which specific devices are tested and supported, how many devices you can use simultaneously, at what frame rate and resolution and in which Noldus software. MediaRecorder is supported with the following device types: - Analog cameras - IP cameras - USB devices - GigE Vision cameras - Screen capture devices We recommend creating a test recording with your devices first before you carry out the actual recordings, especially when you have more or other devices than are officially supported. See Record video. Modules MediaRecorder has the following modules: - Base Module - To record up to four video files simultaneously. However this number depends on the type of video device, since multiple cameras are not supported for all devices. See the section on your device for how many devices are supported at what frame rate and resolution. - Additional Camera Module 1-6 camera - For analog or IP cameras only. To extend the number of cameras to 6. - Additional Camera Module 1-8 cameras - For IP cameras only. To extend the number of cameras to 8. Standalone or With Other Software MediaRecorder can be used as a standalone program to create video files. It is also possible to use the Noldus network communication protocol N-Linx to use it in combination with The Observer XT. This way, recording with MediaRecorder starts automatically when starting an observation in The Observer XT and stops when this observation is ended. Furthermore, the videos obtained this way are automatically linked to an observation and synchronized with the manually scored events. It is also possible to control recording with commands from EthoVision XT, for example to start recording when a mouse leaves the shelter. MediaRecorder Help This Help describes how to use MediaRecorder 6.5 with the supported recording devices. Information about devices from companies other than Noldus IT is valid at the moment of release and may change afterwards without our knowledge. If you have any problems, questions, remarks or comments, please let us know. See Support in Troubleshooting for contact information. Tips for Using the Help - To use the Help at its best, set Internet Explorer, Firefox, Google Chrome or a similar browser, not Microsoft Edge, as the default browser. - If you keep getting the message "Internet Explorer restricted this webpage...", do the following: in Internet Explorer, choose Tools > Internet Options > Advanced. Under Security, select Allow active content to run in files on My Computer. Click OK, then close and restart the Help. - If you do not see the Table of Contents on the left, enlarge the Help window or zoom out (Ctrl+mouse wheel, or Ctrl+-). - To search for two or more adjacent words, use quotation marks, for example "Action Unit". - To go back to the search results after visiting one of the result pages, click again on the magnifying glass icon in the Search field. What's New in MediaRecorder 6.5 If you have been using a previous version of MediaRecorder, you should read these topics to get an idea of the improvements in this version. What's New Compared to Version 6.2 Selection of Audio Source for All Videos While previously only Audio device 1 could be used as a common audio source for all the videos, now in Picture-in-Picture mode, you may select which audio source to use for this purpose. Data Transparency Policy When starting recording, a pop-up window will appear, informing you about Noldus's Data Transparency Policy. What's New Compared to Version 6.0 Software Activation Code Instead of Hardware Key MediaRecorder 6.2 comes with a software activation code as the license, which makes it easier to work with the software. For existing customers it is still possible to upgrade their hardware key. What's New Compared to Version 5 Output Quality Selection Instead of using the default output quality you can now select optimized settings for when you are using your recorded video files in (1) a four-camera EthoVision set-up; (2) a DanioVision set-up; or (3) with the Remote Photo Plethysmography module in FaceReader. See Output settings for more information. Recording With a Frame Rate of 1 fps It is now possible to select a frame rate as low as 1 fps when filming slowly-moving subjects. Prevent Black Frames at the Start of Your Videos With the default settings of MediaRecorder there may be black frames at the start of your videos. If that is the case, EthoVision will not automatically start tracking and FaceReader will not start analyzing from the start of your videos. You can now edit the VsSettings file that comes with MediaRecorder to prevent black frames. For more information see Prevent black frames at the start of your videos. Euresys Picolo H264 Boards Not Supported The Picolo U4 and U8 H264 boards are end of life and only have 32-bit drivers. Therefore the latest version of MediaRecorder does not support them anymore. End-User License Agreement Revised: 21 July 2022 IMPORTANT - READ CAREFULLY. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading or using the Software (as defined below). By checking the "accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions of this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions Terms used in this EULA but not otherwise defined shall have the meaning assigned to them below: - 1.1. Authorized Partner: the individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. - 1.2. End-User: the individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3. EULA: this End-User License Agreement. - 1.4. Indirect Losses: any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5. Network License: a licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. - 1.6. Noldus: Noldus Information Technology BV, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries listed in the document https://www.noldus.com/legal/noldus_corporate.pdf. - 1.7. Security System: a system of software protection to limit installation and use of the Software to the authorized End-Users and computers. - 1.8. Security Device: a device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. - 1.9. Software: the software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) provided to the End-User by Noldus or an Authorized Partner together with this EULA, that is not covered by third party terms and conditions and is included in the list under "Noldus software" in the Annex to the General Terms and Conditions (https://www.noldus.com/legal/noldus_gtc.pdf). 2. License - 2.1. Upon payment by the End-User of the license fees for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates or supplements of the Software. If upgrades, updates or supplements of the Software are obtained, the use of such upgrades or updates is governed by this EULA and the amendments that may accompany them and may be subject to additional payments and conditions. - 2.2. The End-User may download, install and use the Software on as many computers as is reasonably necessary, however the Software may not be shared or used concurrently on more computers than for which EULAs are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. - 2.3. End-User is allowed to store or install a copy of the Software for back-up or archival purposes. - 2.4. End-User shall not (i) modify, alter, adapt, merge, decompile or reverse-engineer the Software or any part thereof nor create any derivative works based on all or any part of the Software, or (ii) remove or obscure any copyright, trademark or other ownership notices from the Software, or (iii) sub-license, sell, rent, lease, hire, loan, assign or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. - 2.5. The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices and Network Licensing. End-User is prohibited to (attempt to) remove, alter or circumvent in any way any part of such Security System. - 2.6. End-User is responsible for regular, frequent and effective backups of all files produced or modified while working with the Software. 3. Intellectual Property - 3.1. All title, copyright and other industrial, intellectual or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. - 3.2. The Software may include or make use of third party software, including open source software. Such third party software may be subject to the third party's terms and conditions provided in the documentation accompanying the Software and may contain copyright or other industrial, intellectual or proprietary rights of such third party. End-User hereby agrees to the terms and conditions for such third party software. In the absence of any third party terms and conditions, this EULA will govern the third party software in the Software. - 3.3. End-User may, from time to time, provide Noldus with comments, suggestions, data, information or feedback ("Feedback") on the Software. End-User acknowledges and agrees that such Feedback may be freely used by Noldus, at its sole discretion, for the design, development, improvement, marketing and commercialization of its products and services, without any restrictions based on confidentiality or intellectual property rights. 4. Transfer - 4.1. End-User is entitled to make a one-time, permanent transfer of this EULA and Software only directly to one other End-User. This transfer must include all of the Software (including all component parts, the media and printed materials, any upgrades and this EULA). Such transfer may not be by way of consignment or any other indirect transfer and shall be subject to the following provisions: - End-User will provide to Noldus prior to any such transfer the full name and address details of the new End-User and the expected date of transfer in writing. - The new End-User understands and agrees to all the terms and conditions of this EULA in the same way as if the new End-User had obtained the Software from Noldus or an Authorized Partner. - End-User will destroy all (partial) copies of the Software and all accompanying materials, including but not limited to installed copies and any backup copies on data storage devices, and guarantee to Noldus in writing that this has been done. If the Software is an upgrade, any transfer must include all prior versions of the Software. - Noldus reserves the right to levy an administrative charge upon the End-User and/or the new End-User in relation to transfer of the Software to an End-User. - 4.2. Any attempted transfer without prior written permission from Noldus shall constitute a material breach of this Agreement and shall be deemed null and void. 5. Term; Termination - 5.1. The EULA shall enter into force on the date of acceptance by the End-User and continue until terminated in accordance with this Section 5. - 5.2. If the Software is licensed on a subscription basis, the EULA shall continue until the end of the current subscription period. - 5.3. Noldus is entitled to terminate the EULA immediately upon prior written notice upon: - the breach of any material provision of this Agreement by the End-User if (i) such breach is not curable or (ii) if curable, the End-User has not cured such breach within 30 (thirty) day period following receipt of a written notice by Noldus substantiating such breach ("ingebrekestelling"); - the filing or institution of bankruptcy, liquidation or receivership proceedings of the End-User or in the event a receiver or custodian is appointed for the End-User's business, or if its business is discontinued or if it has a petition presented by a creditor for its winding up or if the End-User enters into any liquidation (other than for purpose of reconstruction or amalgamation). - 5.4. Upon termination of the EULA, the End-User shall immediately discontinue the use of the Software and remove the software from all computers, destroy all (partial) copies of the Software from all storage media and return the documentation and materials relating to the Software to Noldus or its Authorized Partner. - 5.5. Termination of this Agreement does not remove or reduce End-User's obligation to pay any outstanding license fees or other monies, all of which shall be due for payment immediately on termination of the EULA. - 5.6. The following provisions shall survive termination of this EULA: Sections 3, 7, 9, 10 and this Section 5.6. In addition, any other provisions which are required to interpret and enforce the parties' rights and obligations under the EULA shall also survive any termination or expiration of this EULA, but only to the extent required for the full observation and performance of the EULA. 6. Warranty - 6.1. Noldus warrants that the Software, as of the date of delivery to the End-User by Noldus or its Authorized Partner, will, for a period of 90 days ("Warranty Period") materially conform to the specifications set out in the user documentation accompanying the Software ("Specifications"), provided that: - the Software is properly installed on a supported computer platform (as defined in documents that can be accessed on https://my.noldus.com) and used in accordance with the provisions of the accompanying user documentation and/or any Noldus-approved training course; - Noldus is notified in writing within 14 days after any non-conformity of the Software was known or should reasonably have been known to End-User. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder - Installation and Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-installation-and-setup Chapter: Media Recorder Installation and Setup Overview This page covers the steps required to install and configure Media Recorder 6.5, including driver configuration, license activation, and end-user license terms. Main Topics - The steps to install Media Recorder - Turn off automatic updates for device drivers - Install Media Recorder and device drivers - Activate your Media Recorder license - Upgrade to Media Recorder 6.5 The Steps to Install Media Recorder IMPORTANT: If you have an older version of Media Recorder, uninstall Media Recorder 6.0 and older versions before you install Media Recorder 6.5. IMPORTANT: If you have a hardware key, do not insert your key before the installation is complete. If you do so, other drivers are automatically installed, which may lead to incorrect functioning of the license key. Drivers of the license key should be installed using the installation USB stick. - Turn off automatic updates for device drivers - Select correct power options - Install Media Recorder and device drivers Turn Off Automatic Updates for Device Drivers The aim of this procedure is to make sure the devices use the drivers that were tested with Media Recorder. The general recommendation from Microsoft to use automatic updates is good, especially for security updates. However, automatic updates of hardware device drivers can sometimes cause problems. Media Recorder is tested with the device drivers that are available at the moment of release. If device drivers are updated afterwards, correct operation with Media Recorder cannot be guaranteed. Therefore, it is recommended to switch off automatic updates of device drivers. If you ordered a computer with Media Recorder from Noldus IT, the automatic updates for device drivers have already been turned off and you can skip this section. - Open the Start window and type Change Device Installation Settings. - Click the tile that appears. - To the question Do you want Windows to download driver software and realistic icons for your devices?, select No, let me choose what to do. - Select Never install driver software from Windows Update. - Deselect the checkbox in front of Automatically get the device app and info provided by your device manufacturer. - Click Save Changes. Select Correct Power Options The aim of this procedure is to make sure the computer shuts down properly. On computers with Windows 10, by default the computer resumes rather than restarts after shutdown. This can cause problems with Media Recorder and associated software such as The Observer XT. Therefore, it is recommended to make sure that the computer performs a full shutdown. - In the Windows Start window, type Power options and then click the Power options tile. - Choose Choose what the power buttons do. - Click Change settings that are currently unavailable. - Select the following options: - When I press the power button - Shut down - When I close the lid - Shut down - Under Shutdown settings, deselect the checkboxes for Sleep, Hibernate, and Turn on fast startup (recommended) Install Media Recorder and Device Drivers The aim of this procedure is to install Media Recorder and, for some recording devices, their drivers. IMPORTANT: Uninstall Media Recorder 6.0 and older versions before you install Media Recorder 6.5. - Download the installation files from my.noldus.com and extract the contents. - Browse to the file MediaRecorder [Version number] Setup.exe and double-click it. - Choose Standard as the installation type. Choose Custom only to change the location where the program is installed. - In the Drivers and tools field, choose the driver for your video device. - Click Next, accept the License Agreement, and click Install. The following setup prerequisites are installed automatically before Media Recorder is installed: - Sentinel Run time - Needed for correct functioning of your hardware key. - Noldus LeadTools Package 21 - Noldus MediaLooks Proxy Filters 2.1 - Needed for screen capture of the monitor of the computer with Media Recorder. - Medialooks Screen Capture 2.0.3 - Needed for screen capture of the monitor of the computer with Media Recorder. - Microsoft .NET Framework 4.7.1 - Required to run Media Recorder. This program is installed only when not already present on the computer. Activate Your Media Recorder License A license for Media Recorder comes with an activation key. The key determines which license options are available to you. For existing customers it is still possible to upgrade their hardware key and use it as the license. - Start the Media Recorder software and select the option Activate software license key. - Select either Floating or Fixed and click OK. Difference Between Floating and Fixed Activation Floating activation - Choose this option if you want flexibility in which computer you use Media Recorder on. If you purchased a software key with two licenses, you can simultaneously use the software on two computers. You can install and activate Media Recorder on as many computers as you want, but with two licenses you can only use the software on two PCs at a time. If you want to use Media Recorder on a third PC, the software must not be running on one of the other two PCs. A computer must have an internet connection to activate and work with a Floating license. Fixed activation - A Fixed activation is linked to one computer. The advantage is that you do not need an internet connection to work with the software after activation. If you purchased a software key with two licenses, you can activate Media Recorder on two computers. To use Media Recorder on a third computer, you must deactivate one of the existing licenses first. A computer must have an internet connection to activate or deactivate a Fixed license. After activation, Media Recorder can be used without internet. Alternatively, you can activate or deactivate your license using your smartphone. Activate Your Floating License - Enter your Activation key and click OK. The Media Recorder software will open. Activate Your Fixed License - Enter the Activation key that you received with the software. - Select one of the following: - Activate Online if the PC is connected to the internet. Click OK and the Media Recorder software will open. - Activate Offline if the PC does not have an internet connection. Scan the QR code with your smartphone, click WEB, enter the Computer key, and click OK. The Media Recorder software will open. Deactivate Your Media Recorder License Deactivate your fixed license if you have reached your maximum number of activations and want to install and use Media Recorder on another computer. IMPORTANT: If you want to uninstall Media Recorder, first deactivate the license, otherwise you will lose it. Please contact Noldus Technical Support if this has occurred. Deactivate Your Floating License - From the Help menu, select Deactivate License. - You will receive a message that your license key was successfully removed and that Media Recorder will exit. Click OK to close the software. Deactivate Your Fixed License - From the Help menu, select Deactivate License and select one of the following: - Deactivate Online if the computer is connected to the internet. You will receive a message that your license key was successfully removed and that Media Recorder will exit. Click OK to close the software. - Deactivate Offline if the computer does not have an internet connection. Scan the QR code with your smartphone. Click OK to deactivate the license on the PC. You will receive a message that your license key was successfully removed and that Media Recorder will exit. Click OK to close the software. Follow the QR code link on your smartphone within 24 hours to deactivate your license on the Noldus server. You can also first deactivate your license on the Noldus server and then select the checkbox in the window on your PC to deactivate the license on your PC. Using a Hardware Key Media Recorder is no longer sold with a hardware key. Instead, it comes with a software activation code. If you use a version earlier than 6.2, it is possible to upgrade your hardware key or request a software activation key. If you wish to use an upgraded hardware key, follow the steps below: - Plug the key into a USB port on your computer. If the hardware key is correctly connected, a red light is visible inside the key. - Start Media Recorder. Keep the key inserted in your computer while you work with Media Recorder. A hardware key represents the full value of your license and cannot be replaced if lost. You can install Media Recorder on any computer that meets the system requirements. However, to work with the program you must insert the hardware key into one of the computer's USB ports. IMPORTANT: Do not lose the key. You will need to pay for a new license if it is lost. Handle it carefully, as it is sensitive and can be easily damaged. The drivers for the hardware key are installed together with Media Recorder. It is important to install Media Recorder with the hardware key drivers before connecting the license key to the computer. If you connect the hardware key first, drivers are automatically installed which may lead to incorrect functioning of the hardware key. When the hardware key is installed and connected properly, a red light glows inside it. End-User License Agreement Revised: 21 July 2022 IMPORTANT - READ CAREFULLY. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading, or using the Software. By checking the "accept" checkbox, downloading, installing, or otherwise using the Software, End-User agrees to be bound by the terms and conditions of this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install, or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions - 1.1. Authorized Partner: the individual or legal entity that has been granted permission by Noldus to promote, sell, or otherwise distribute the Software on behalf of Noldus. - 1.2. End-User: the individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3. EULA: this End-User License Agreement. - 1.4. Indirect Losses: any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5. Network License: a licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. - 1.6. Noldus: Noldus Information Technology BV, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries listed in the document https://www.noldus.com/legal/noldus_corporate.pdf. - 1.7. Security System: a system of software protection to limit installation and use of the Software to authorized End-Users and computers. - 1.8. Security Device: a device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. - 1.9. Software: the software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) provided to the End-User by Noldus or an Authorized Partner together with this EULA, that is not covered by third party terms and conditions and is included in the list under "Noldus software" in the Annex to the General Terms and Conditions (https://www.noldus.com/legal/noldus_gtc.pdf). 2. License - 2.1. Upon payment by the End-User of the license fees for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install, and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates, or supplements of the Software. If upgrades, updates, or supplements of the Software are obtained, the use of such upgrades or updates is governed by this EULA and any amendments that may accompany them, and may be subject to additional payments and conditions. - 2.2. The End-User may download, install, and use the Software on as many computers as is reasonably necessary; however, the Software may not be shared or used concurrently on more computers than for which EULAs are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. - 2.3. End-User is allowed to store or install a copy of the Software for back-up or archival purposes. - 2.4. End-User shall not: (i) modify, alter, adapt, merge, decompile, or reverse-engineer the Software or any part thereof, nor create any derivative works based on all or any part of the Software; (ii) remove or obscure any copyright, trademark, or other ownership notices from the Software; or (iii) sub-license, sell, rent, lease, hire, loan, assign, or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. - 2.5. The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices, and Network Licensing. End-User is prohibited from attempting to remove, alter, or circumvent in any way any part of such Security System. - 2.6. End-User is responsible for regular, frequent, and effective backups of all files produced or modified while working with the Software. 3. Intellectual Property - 3.1. All title, copyright, and other industrial, intellectual, or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. - 3.2. The Software may include or make use of third party software, including open source software. Such third party software may be subject to the third party's terms and conditions provided in the documentation accompanying the Software and may contain copyright or other industrial, intellectual, or proprietary rights of such third party. End-User hereby agrees to the terms and conditions for such third party software. In the absence of any third party terms and conditions, this EULA will govern the third party software included in the Software. - 3.3. End-User may, from time to time, provide Noldus with comments, suggestions, data, information, or feedback ("Feedback") on the Software. End-User acknowledges and agrees that such Feedback may be freely used by Noldus, at its sole discretion, for the design, development, improvement, marketing, and commercialization of its products and services, without any restrictions based on confidentiality or intellectual property rights. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder - Integration with FaceReader and Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-integration-with-facereader-and-observer-xt Chapter: Media Recorder MediaRecorder with FaceReader Offline video analysis in FaceReader means analyzing prerecorded videos. The videos created by MediaRecorder can be used for offline video analysis in FaceReader 4 or higher. No special settings are needed to use files from MediaRecorder in FaceReader. However, if you record videos to use with the Remote Photo Plethysmography (RPPG) module in FaceReader we advise to use FaceReader-RPPG as the Output Quality setting. With this setting the videos will only be slightly compressed. The file size of the resulting videos is huge, about 260 Mb/minute. For more information see Output settings. You cannot simultaneously analyze live video signals in FaceReader and create video files in MediaRecorder. If you want to analyze and record videos simultaneously, record the videos in FaceReader. Prevent Black Frames at the Start of Your Videos To make sure that MediaRecorder waits for an I-frame before it starts recording, you can edit the VsSettings file that comes with MediaRecorder. If you do not edit this file, your videos may start with black frames and FaceReader will not be able to analyze them from the start. The VsSettings file is installed together with MediaRecorder. You can find the file in C:\ProgramData\Noldus\MediaRecorder\6. By default the ProgramData folder is a hidden folder. In Windows Explorer on the View tab select Hidden items in the Show/hide section to view the folder. - Right-click VsSettings.xml and select Copy. Right-click and select Paste to make a copy of the file. Keep this copy in case you want to go back to the original settings. - Open the VsSettings.xml file in Notepad or a similar text editor. - From the Edit menu select Find and type Wait in the search field. - To make sure that MediaRecorder waits for an I-frame before it starts recording, edit the file and change 0 into 1. - Save the file. Troubleshooting If you are having problems, please first read Specifications or Requirements of a custom computer, to check whether your system is compatible with MediaRecorder. Also check the items below to see if there is a known solution for your problem. No Video Preview If one of your video inputs is black with a warning triangle and the message No signal from Video [n] is shown, the video source was not turned on when MediaRecorder was started. Press the Refresh button in MediaRecorder to show the image from that camera. You also get a black screen with a warning triangle when you have not yet selected this camera in the Video settings window. See also Save the camera settings in Record video. You will also have a black video input if your computer does not have an Nvidia graphics card. By default, MediaRecorder records two cameras on CPU and two on the video card (GPU) if you record from four cameras simultaneously. Only Nvidia GPUs facilitate the use of the GPU as additional processing power for compression of MediaRecorder videos. Other graphics cards are not able to do that. If you ordered a computer with MediaRecorder from Noldus Information Technology, it has an Nvidia card. By default, MediaRecorder checks whether this card is available and if so, uses it. If you purchased a PC elsewhere, it may have a different graphics card and with the default settings, your cameras may give black inputs in MediaRecorder. To prevent this, you can edit the VsSettings file that comes with MediaRecorder. To check the graphics card of your computer, click the Windows button and type Device Manager. In the Device Manager window expand the Display adaptors section. The computer's graphics cards are listed here. The VsSettings file is installed together with MediaRecorder. You can find the file in C:\ProgramData\Noldus\MediaRecorder\6. By default the ProgramData folder is a hidden folder. In Windows Explorer on the View tab select Hidden items in the Show/hide section to view the folder. - Right-click VsSettings.xml and select Copy. Right-click and select Paste to make a copy of the file. Keep this copy in case you want to go back to the original settings. - Open the VsSettings.xml file in Notepad or a similar text editor. - From the Edit menu select Find and type GPU in the search field. - To make sure that MediaRecorder does not use the GPU, edit the file and change -1 into 0. You can also change the value into 1 if your computer has one (Nvidia) graphics card. With this value MediaRecorder will not check what graphics card is available, it will use the card that is installed. Installation Problems If you get an error message during installation of the Picolo card, it is most likely that the card is not correctly inserted into your computer. Turn the computer off and disconnect the power cable. Press the card gently but firmly into place. Sound Problems If you are playing back multiple videos in The Observer XT and you hear an echo on the sound track, turn the sound off on all but one of the video monitors. If you hear no sound on your recording this could be because: - The speakers of your computer are not plugged in, they are turned off or their volume is low. - The Windows volume control is muted or turned low. - You have selected Line-in for your audio device instead of Microphone. - You do not have an audio source connected. Insufficient Disc Space If your output folder is on the C: drive it is possible that you will have insufficient file space. Most computers are configured with more file space on the D: drive, so select your output folder on the D: drive. Missing Frames When Controlling Recording with External Programs When you send commands to MediaRecorder from external programs like EthoVision XT or The Observer XT, there is a small delay in starting the actual recording with MediaRecorder. This results in some missing frames at the start of the video file. Allow enough time at the start of recording to compensate for this delay. When the command Start Recording is given before MediaRecorder is open and has loaded the cameras, recording does not start. To measure this delay, make for example a video of a digital clock and compare the time the command Start Recording is given with the time at the first frame of the video. Problems Loading MediaRecorder MediaRecorder opens using the configuration file Current settings.mrs. When problems occur with these settings, open MediaRecorder with the default settings and recreate camera settings. To do so: - Delete the file Current settings.mrs from the following folder: C:\Users\Public\Documents\Noldus\MediaRecorder - Re-open MediaRecorder. - Re-select the cameras. A new file Current Settings.mrs is created. See also Save the camera settings in Record video. Tools for Troubleshooting VideoInspector This free tool gives basic information about the video files you are trying to play (such as which codecs they were made with) and reports which codecs are installed on your computer. It is reasonably easy to use. It does not report details such as the I-frame rate. http://www.kcsoftwares.com/?vtb GSpot Although GSpot has not been maintained since 2007, it is a powerful tool to get information about both your video file and your computer system. GSpot is a free tool. It is less easy to use than VideoInspector. In addition to providing detailed information about the video file you have opened, GSpot can be used to adjust how Windows uses the codecs installed. This is an advanced function and you should only use it if you understand what you are doing, and carefully write down the changes you make. If several codecs are installed which can be used to play one format, Windows assigns a merit to each codec to determine its preference. You can use GSpot to change the merit of each codec and in that way select which one is used by Windows (and so by other software). This is a way in which you can solve problems of codecs conflicting with each other, for example a piece of software such as The Observer XT works best with a particular codec, but another installation has set the merit of an alternative codec higher. http://gspot.headbands.com MediaInfo MediaInfo provides detailed information about media files. It has less information than GSpot, but at the publication date of this manual, it was maintained. http://www.mediainfo.sourceforge.net/en Windows System Information This can be obtained in Windows with System and Security / System / Advanced System Settings, Dxdiag.exe, and the Device Manager (in the Control Panel). For full system information, SIW is a useful tool. http://www.gtopala.com Support Help Menu MediaRecorder's Help menu contains the following options: - Help topics - Opens the MediaRecorder Help. You can search and find help topics. - Noldus Online - If your computer is connected to the Internet, you can choose this option to go to the MediaRecorder home page on the Noldus website or to the MyNoldus portal. On the MyNoldus portal you can download the latest version of the software and documentation, submit support cases and view your account information. If you encounter a problem with MediaRecorder, you can inform Noldus IT with the Report an Issue option. - Upgrade - If you have purchased an upgrade of MediaRecorder, choose this option to type the new Upgrade Key number that you have received from Noldus. - About MediaRecorder - Choose this option to see details of exactly which version of MediaRecorder you are using. Click User Info to see the registered user and license number of your software. Technical Support For questions about MediaRecorder or any other Noldus product, contact the Support department by opening the Help menu in MediaRecorder, select Noldus Online and subsequently Get Support. The help desk may ask for the MediaRecorder log file. You can find this file in the folder C:\Users\\AppData\Local\Temp. Record at a Predefined Time Use this procedure to schedule video recording. This is especially useful when you want to start recording in the middle of the night, or you do not want to disturb the test subjects by handling the video software. IMPORTANT: The procedure below is an example of the possibilities of Windows Task Scheduler, which is a default program in Windows 10. Since Windows Task Scheduler is a Microsoft program, Noldus IT offers no support for this feature. Procedure - Type Task Scheduler in the Apps window. - Choose Action > Create Task. - In the General tab, type a name in the Name field, for example MediaRecorder with Webcam. - Optionally enter other settings in this tab and open the Triggers tab. - Click the button New. - Select On a schedule from the list next to Begin the task. - Enter the start time of the command in the Start field and choose whether you want to send the command once, daily, weekly or monthly. - Optionally enter Advanced Settings and click OK. - Click the Actions tab and choose New. - Choose Start a program next to Action. - Browse to MRCmd.exe. - Enter the command in the Add arguments (optional) field. For example, to start MediaRecorder and load the configuration file for your webcam, type: /E /C=Configuration_webcam.mrs. If the configuration file is not located in the folder C:\Users\Public\Public documents\Noldus\MediaRecorder, you must type the full path. If the file name or path contains spaces, you must use quotation marks at both ends. - Optionally select or change any settings on the other tabs. - Similarly, you can create tasks to start and stop recording at a predefined time with the commands /R and /S and to close MediaRecorder with the command /X. Create a task for each command. IMPORTANT: Allow enough time between the commands. If a command is sent before the previous one is carried out, the second command is not carried out. For example, if the command Start Recording is sent before MediaRecorder is completely open, recording does not start. By default, the tasks are stored in the folder Task Scheduler Library. To edit or delete a task, click this folder in the tree on the left side and select the task in the window Task Scheduler Library. In the Actions pane, click Properties, or Delete. Integration with The Observer XT Set Up Analog Cameras Choose the situation that applies to you: - You ordered computer, cameras, and MediaRecorder at Noldus IT: The video capture card is already installed in the computer. MediaRecorder has also been set up to use with these cameras. You can connect your cameras and start recording. See Record video. - You bought the computer and cameras somewhere else: Follow the procedure below. Install the Picolo Alert PCIe Card Use this procedure to install the card that digitizes the output of analog cameras. Prerequisites: - You use MediaRecorder with analog cameras. - You did not buy a complete setup from Noldus IT. If you bought a complete setup from Noldus IT, the card has been installed in the computer and you can skip this topic. - Make sure your computer is turned off and the power cable is disconnected. - Open the computer. - Select a free PCIe expansion slot, and remove the corresponding extension cover. See PCIe slot properties for more information on different PCIe slots in a Dell computer. - Unpack the Euresys Picolo Alert PCIe card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. IMPORTANT: When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet, and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Fix the card to the chassis and re-fit the computer's cover. - Close the computer. PCIe Slot Properties Different PCIe slots have different properties, resulting in different performances. When possible, choose the slot that gives maximum performance. Take note of the slot version to estimate performance. Do not use the graphic slots. PCIe slot performance per lane (values should not be multiplied by the number of lanes in a slot, for example x4, since the card has a 1x connector): - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: approximately 1 GB/s - PCIe v4.0: approximately 2 GB/s Install the Drivers for the Picolo Alert Card Use this procedure to install the software that allows communication between the Euresys card and the computer operating system. Prerequisites: - You use MediaRecorder with analog cameras. - You did not buy a complete setup from Noldus IT. - You installed the Euresys Picolo Alert card into the computer. - Insert the MediaRecorder installation USB stick into your computer. - If you have the Picolo Alert card, open the folder Drivers and Tools\Drivers\Euresys\Alert and double-click the file multicam-win10-6.15.1.3573.exe. - Follow the instructions on your screen. - When installation is finished, a message appears that the drivers were successfully installed. Click Close. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder - IP Camera Setup and Network URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-ip-camera-setup-and-network Chapter: Media Recorder Set Up IP Cameras Camera Setup To configure the cameras for use with MediaRecorder, you must carry out the following steps for each camera: - Set camera IP address - Set camera password and select power line frequency - Create camera settings - Create audio settings Prerequisites: - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You followed the procedure in Ethernet card setup. - You connected all cameras. Set Camera IP Address Set the IP address of the camera to the same range as the Ethernet card and the computer. Prerequisites: - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You installed the Ethernet card. See Install the Ethernet card. - You gave the card a fixed IP address. See Set Ethernet card IP address. - You connected all cameras. Procedure: - Insert the MediaRecorder installation USB stick into your computer and copy the file IPUtility.exe from the folder Drivers and Tools\Software\Axis Tools to your computer. Do not copy it to your desktop; the tool will then not work correctly. - Run IPUtility.exe. A window opens in which all the connected devices are listed. - Right-click the device and select Assign IP address. - Enter the IP address and choose Assign. - According to the message that appears, disconnect and reconnect the camera and click Assign. Wait until the IP address is set. - Right-click the camera and select Test IP address. When the details were entered correctly, a message appears that the camera is accessible. - Repeat steps 3 to 6 for all cameras. Make sure you use different IP addresses for all cameras, the computer, and other network devices in the network. Set Camera Password and Select Power Line Frequency Give the camera a password, which is compulsory, and select the power line frequency of your country. Prerequisites: - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You followed the procedure in Ethernet card setup. - You connected all cameras. - You gave the cameras an IP address. See Set camera IP address. Procedure - IP Address: - In the IPUtility tool, click the Home Page button. The camera now opens in a browser. Alternatively, type the IP address in the address field of, for example, Internet Explorer. - The first time you open the camera in a browser, you must set a password. If you obtained cameras from Noldus IT, this password is Noldus. The user name root cannot be changed. Do not use the characters @, space, or colon (:) for the password. These characters cannot be used in MediaRecorder. - As soon as you set the password, you must log in to the camera with the password you just set. Procedure - Power Line Frequency: The first time you log in to the camera, you must select a power line frequency. Look up the correct power line frequency of your country on the Internet. Notes: - IMPORTANT: Close the browser before you start recording. Leaving it open may cause recording problems in MediaRecorder. - If you do not get a view in Internet Explorer, click the Settings wheel in the upper-right corner of your window and choose Compatibility View Settings. Enter the IP address of your camera and click Add. Other browsers may have a comparable setting. Create Camera Settings Configure the camera for optimal recording with MediaRecorder. Prerequisites: - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You installed the Ethernet card. See Install the Ethernet card. - You gave the card a fixed IP address. See Set Ethernet card IP address. - You connected all cameras. - You gave the cameras an IP address. See Set camera IP address. - You gave the camera a password and selected the correct power line frequency. See Set camera password and select power line frequency. Carry out the following steps: - Access camera settings - Create ONVIF User name and Password - Disable replay attack protection - Switch on IR cut filter Note: The procedure below describes camera firmware version 7.20.1. For other firmware versions, search for comparable settings. Access Camera Settings - Open the camera in a browser by clicking the Home page button in the IPUtility tool or typing the IP address in the address field of an Internet browser. Then enter the password. - Click the Settings button in the bottom-right corner of your window. Create ONVIF User Name and Password Configure the camera so that pan, tilt, zoom, and audio recording is possible. Procedure: - Open the camera settings. See Access camera settings. - Open the System tab and click ONVIF. - Click Add and enter the same User name and Password as set in Set camera password and select power line frequency. Do not use the characters @, space, or colon (:) for the user name or password. These characters cannot be used in MediaRecorder. - Select Administrator as User Group and click OK. Notes: - If the camera does not support ONVIF, pan, tilt, and zoom must be done with a browser and audio of the camera cannot be recorded. All IP cameras supported with MediaRecorder support ONVIF. - IMPORTANT: Always close the browser before you start recording with MediaRecorder. Disable Replay Attack Protection Prevent connection to the camera from failing if the time of the MediaRecorder computer differs from the time in the camera. Background: Replay attack protection is a camera security setting. Relevant for video recording with MediaRecorder is that replay attack protection causes the camera connection to fail if the timestamps of MediaRecorder and the camera are not exactly the same. Replay attack protection is necessary for security cameras, but not for IP cameras in a dedicated network. Procedure: - Open the camera settings. See Access camera settings. - Open the System tab and click Plain config. - From the list at the bottom, select WebService and click Select Group. - Under WebService UsernameToken:, make sure the checkbox Enable replay attack protection is not selected. Note: If you do not want to disable this option, make sure that the clock times of the computer and camera are exactly the same. Switch On IR Cut Filter Make sure the camera does not switch to black and white at low light levels. Background: The IR cut filter removes infrared light during daylight. With the default camera settings, the IR cut filter is switched off at low light intensities. The camera then records in near-infrared, which gives a black and white camera image. If you do not want this, set the IR cut filter to On instead of Auto, so that it stays on, independent of the light level. Procedure: - Open the camera settings. See Access camera settings. - Open the Image tab. - Check if there is an option IR cut filter. If so, set it to On. Note: Not all IP cameras supported with MediaRecorder have an IR cut filter. Create Audio Settings Optimize the recording volume. Prerequisites: - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You followed the procedure in Ethernet card setup. - You connected all cameras. - You gave the cameras an IP address. See Set camera IP address. - You gave the camera a password and selected the correct power line frequency. See Set camera password and select power line frequency. - You followed the procedure in Create camera settings. Procedure: - Open the camera settings. See Access camera settings. - Open the Audio tab. - Adjust the Gain slider and check in the Input section that the green field in the Level field is maximal with normal speech. Note: You cannot record the audio of non-ONVIF devices in MediaRecorder. Optionally record audio from a separate microphone that is connected to the microphone input of the computer with MediaRecorder. The Axis cameras supported with MediaRecorder support ONVIF. Select ONVIF Cameras in MediaRecorder Select a camera that supports ONVIF Profile S in MediaRecorder. If your device does not support ONVIF, see Select devices that do not support ONVIF in MediaRecorder instead. Prerequisites: - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You followed the procedure in Ethernet card setup. - You followed the procedure in Camera setup. - You installed MediaRecorder. See Installation. - You connected all cameras to the computer with MediaRecorder. Procedure: - Open MediaRecorder and choose File > Video Settings or click Video Settings. - Select the checkbox in front of the video channel and choose RTSP IP Camera (Noldus RTSP Source Filter). - Click the Advanced Video Settings button. - A list with ONVIF cameras in the network appears. Select the camera. - Enter the ONVIF User name and ONVIF Password for your camera. If you obtained cameras from Noldus IT, the ONVIF user name is root and the ONVIF password is Noldus. - To select another camera, click the Discover button to display the list with ONVIF cameras in the network. - If you have several cameras with the same ONVIF User name and ONVIF Password, choose File > Preferences > IP camera settings. Select Use default IP camera user name and password and enter the credentials. You can then skip steps 5 and 6; the camera is detected automatically. - Click Get device properties. - The Encoding and Quality fields appear with the default video format, frame rate, and resolution of the camera. - Optionally, click Edit and select another frame rate or resolution. Click Update when done. - For low frame rate recordings, it is important to lower the H264 Gov length on the same screen, under Advanced settings. For 5 fps, set the Gov length between 5 and 10. For 1 fps recording, set it between 1 and 2. A lower Gov length will result in larger files but better image. - It is also possible to change the frame rate and resolution in the table with selected video devices. You may still need to adjust the Gov length for optimal results. - Optionally, adjust the video quality, for example to decrease the video file size. We recommend to only do this when problems with video quality or data transfer over the network occur. See Adjust advanced video quality options. - Click Close when done. - Optionally, to reverse the direction the camera moves with Pan and Tilt, select the checkbox Flip pan axis (horizontal movement) or Flip tilt axis (vertical movement) or both. - Click OK. - Select the microphone from the Audio device list. To select the microphone from the camera, or a microphone connected to it, select RTSP IP camera (Noldus RTSP Source Filter) from the Audio device list. - Close the Settings window and tap on the microphone. Check the green bar next to the video device to see whether you selected the correct microphone. - Continue with Record video. Notes: - If you bought cameras yourself, see Create ONVIF User name and Password for the procedure to create an ONVIF user name and ONVIF password. - If the default Port 554 is already in use, ask your system administrator for help to select another one. - See Create audio settings for how to adjust the recording volume. Adjust Advanced Video Quality Options Change video quality, for example to reduce the video file size. Prerequisite: You experience problems with video quality or data transfer over the network. In all other cases, we recommend not to change the default settings. Procedure: - Choose File > Video Settings or click Video settings. - Click the Advanced Video Settings button. - Click Get device Properties. This enables the Edit button. Click Edit. - Select Advanced settings. - Adjust the settings and click Update, then Close. See Advanced video quality options below for a description of the options. Advanced Video Quality Options If an option cannot be edited, your camera does not support other options, or the value is set by the chosen profile. - Encoding interval: This value cannot be edited and is set by the profile. - Bitrate: Sets a limit to the data transfer. The default value 0 means unlimited. If you enter a value, data transfer is limited to that value in Kb per second. - H264 Gov length: The interval in which the I-Frames will be coded in the video file. A value of 1 means that every frame is an I-frame. A value of 2 means that every second frame is an I-frame. Decreasing the number increases the video quality, but also the data transfer. For a description of frame types, see: https://en.wikipedia.org/wiki/Video_compression_picture_types - H264 Profile: The encoding profile from the IP camera. MediaRecorder uses the Baseline profile and this option cannot be edited. - Quality: The quality of the encoded video file. A higher number gives higher encoding quality, but also more data transfer over the network. Select Devices That Do Not Support ONVIF in MediaRecorder Select a device that does not support ONVIF Profile S in MediaRecorder. If your device does support ONVIF, see Select ONVIF cameras in MediaRecorder instead. Prerequisites: - Your device does not support ONVIF Profile S. - You followed the procedure in Ethernet card setup. - You created comparable settings for your device as described in Camera setup. - You installed MediaRecorder. See Installation. - You connected your video device to the computer with MediaRecorder. Procedure: - Open MediaRecorder and choose File > Video settings or click Video settings. - Select the checkbox in front of the video channel and choose RTSP IP Camera (Noldus RTSP Source Filter). - Click the Advanced Video Settings button. - A list with available ONVIF cameras in the network appears. IMPORTANT: If your device does not support ONVIF, it will not be on this list. Click Cancel. - Enter the IP address, User name, and Password of the device. If you bought your device from Noldus IT, the User name is root and the Password is Noldus. If the default Port 554 is already in use, ask your system administrator for help to select another one. - Click Get device properties. - The field Connection string appears. - Look up in the manual of your device where the video files can be accessed via the RTSP communication protocol. Enter the path from the slash after the connection information in the Connection string field. For example, /stream.sdp for an Epiphan Pearl Nano screen capture device. - Click OK. Optionally, select another frame rate or resolution. Make sure you select the same frame rate as is selected in the device itself when you opened the camera in a browser. - Optionally, open the camera in a browser to pan, tilt, or zoom. See Access camera settings. IMPORTANT: Close the browser before starting recording with MediaRecorder. - Click OK and continue with Record video. Set Up GigE Cameras The Steps to Install GigE Cameras Prerequisites: - The network allows data transfer of at least 1 Gb per second. - We recommend using a dedicated network for the cameras. - The cables must be suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. See: https://en.wikipedia.org/wiki/Category_5_cable - You have GigE cameras that are supported with MediaRecorder. See Supported GigE cameras in Recording devices. Which situation applies to you? - You bought the computer, cameras, and MediaRecorder from Noldus IT: The cameras are already installed and MediaRecorder has been set up to use with these cameras. Connect the cameras to the computer and start recording. See Connect the GigE cameras to the PC and Record video. - You bought the cameras from Noldus IT and installed MediaRecorder yourself: Follow the procedures in this section to configure and connect the cameras. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder - Multi-Camera PCIe Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-multi-camera-pcie-setup Chapter: Media Recorder Introduction This document describes how to record from multiple cameras in MediaRecorder using a 4-port PCIe board. MediaRecorder has been tested with two 4-port boards: - Adlink PCIe-GIE74 – This Ethernet board is used with GigE cameras. - Fresco Logic U3X4-PCIE4XE111 rev 1.1 – This board is used in combination with USB 3.0 cameras. Both 4-port PCIe boards are supported on Windows 10 only. Other Manuals - MediaRecorder 6 Reference Manual - Quick Start Guide – MediaRecorder 6 Customer Support For technical support, please contact the Noldus Customer Support Center: https://www.noldus.com/support-center. Browse the customer support database with questions asked by MediaRecorder users and answers from the support department. Install GigE Cameras Together with Basler GigE cameras, you need a 1 Gb Ethernet board installed in your computer. To connect the cameras, you need at least cat-5e cables. Steps to Follow - Install the Ethernet board for GigE cameras. - Install the driver software for the GigE cameras. - Assign IP addresses. - Connect the GigE cameras to the PC. - Configure the GigE cameras. Install the Ethernet Board for GigE Cameras To install the Adlink PCIe-GIE74 network board for GigE cameras to record from multiple GigE cameras in MediaRecorder. If you ordered a computer from Noldus Information Technology when you purchased MediaRecorder and your cameras, the board has already been installed and tested. If you bought your computer somewhere else, you will have to install the board yourself. Follow the instructions in the MediaRecorder 6 Reference Manual (Appendix G – Install the Ethernet Card). Make sure the Ethernet board receives power from the PC. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. Install the Driver Software for the GigE Cameras To install the software that enables you to configure the GigE cameras, for example, to set the video frame rate or the exposure time. If you ordered a computer from Noldus Information Technology when you purchased MediaRecorder and your cameras, the drivers for the cameras have already been installed. If you bought your computer somewhere else, you will have to install the drivers yourself. Follow the instructions in the MediaRecorder 6 Reference Manual (Appendix G – Install MediaRecorder with the Camera Drivers). Assign IP Addresses To make sure that the IP addresses of the GigE cameras match that of the Ethernet board. Assign the IP Address to the Ethernet Board - Open the Control Panel. - Go to Network & Internet and then Network and Sharing Center. - Click Change Adapter Settings on the left side of your window. - Right-click the Local Area Connection and click Properties. If your computer has more than one Local Area Connection, choose Basler GigE Vision Adapter. Write down the number of this connection. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Select Use the Following IP Address and Use the Following DNS Server Addresses and fill in the required details. Also select the option Validate Settings Upon Exit. When done, click OK and then Close. - A Windows Network Diagnostics window appears. Click Close when it is finished. Then close all windows. Assign the IP Addresses to the Cameras Important: Connect the cameras one by one and follow the procedure below for one camera before you connect the next. - Connect the first GigE camera to the PC. - Double-click the Pylon IP Configuration tool icon on the desktop. - Select the camera under Local Area Connection. - Fill in the details in the IP Address and Subnet Mask fields under Static IP Address: - IP Address: 192.168.1.101 - Subnet Mask: 255.255.255.0 - Gateway: 0.0.0.0 - Click Save and then Close. - Repeat steps 1–5 for each additional camera, using the following IP addresses: - Camera 2: 192.168.1.102 - Camera 3: 192.168.1.103 - Camera 4: 192.168.1.104 The subnet mask should be 255.255.255.0 for each camera and the gateway should be 0.0.0.0. Connect the GigE Cameras to the PC To make sure that MediaRecorder receives the video signal from the GigE cameras. Connect each camera to one of the ports on the Ethernet board. It is important that each camera is always connected to the same port on the Ethernet board. Each port is viewed as a network adapter with its own IP address. The information about which port is linked is stored in the driver software of each camera. If you swap cameras, they will not be recognized. Therefore, always label the Ethernet ports and the cameras. To connect GigE cameras to the computer, you need at least cat-5e cables. Note: Your cameras should have the same firmware version. Check this in the Pylon Viewer software. In the Features panel, under Device Information, check Firmware Version. If the cameras do not have the same firmware, an upgrade or downgrade must be performed. End-User Licence Agreement Revised: 4 January 2019 IMPORTANT – READ CAREFULLY. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading or using the Software. By checking the "accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions of this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions - 1.1 Authorized Partner: The individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. - 1.2 End-User: The individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3 EULA: This End-User License Agreement. - 1.4 Indirect Losses: Any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5 Network License: A licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. - 1.6 Noldus: Noldus Information Technology BV, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries listed at https://www.noldus.com/legal/noldus_corporate.pdf. - 1.7 Security System: A system of software protection to limit installation and use of the Software to authorized End-Users and computers. - 1.8 Security Device: A device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. - 1.9 Software: The software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) provided to the End-User by Noldus or an Authorized Partner together with this EULA, that is not covered by third-party terms and conditions and is included in the list under "Noldus software" in the Annex to the General Terms and Conditions (https://www.noldus.com/legal/noldus_gtc.pdf). 2. License - 2.1 Upon payment by the End-User of the license fees for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates or supplements of the Software. If upgrades, updates or supplements of the Software are obtained, the use of such upgrades or updates is governed by this EULA and the amendments that may accompany them, and may be subject to additional payments and conditions. - 2.2 The End-User may download, install and use the Software on as many computers as is reasonably necessary; however, the Software may not be shared or used concurrently on more computers than for which EULAs are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. - 2.3 End-User is allowed to store or install a copy of the Software for back-up or archival purposes. - 2.4 End-User shall not: (i) modify, alter, adapt, merge, decompile or reverse-engineer the Software or any part thereof, nor create any derivative works based on all or any part of the Software; (ii) remove or obscure any copyright, trademark or other ownership notices from the Software; or (iii) sub-license, sell, rent, lease, hire, loan, assign or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. - 2.5 The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices and Network Licensing. End-User is prohibited from attempting to remove, alter or circumvent in any way any part of such Security System. - 2.6 End-User is responsible for regular, frequent and effective backups of all files produced or modified while working with the Software. 3. Intellectual Property - 3.1 All title, copyright and other industrial, intellectual or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. - 3.2 The Software may include or make use of third-party software, including open source software. Such third-party software may be subject to the third party's terms and conditions. Source: MediaRecorder multi-camera, Noldus Information Technology --- ## Media Recorder - Recording Sessions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-recording-sessions Chapter: Media Recorder Recording Sessions Starting and Stopping a Recording - A pop-up window will appear, informing you about Noldus's Data Transparency Policy. Read it carefully before clicking the I will inform the participants button. You can also check the box Don't show me again to prevent further occurrence. - The button changes into the Stop Recording button and the Recording timer starts running. - Press the button again to stop recording. Recording stops automatically when you specified a Maximum recording time. If you have IP cameras, see Pan, Tilt, Zoom control with IP cameras for how to change the camera view before or during recording. Recording Video - Options - Change the video file location - Set video file base name - Select or deselect videos for recording - Mute audio in preview - Change video order in preview - Show frame rate, resolution and format - Refresh the preview - See which preview image comes from which camera - Show or hide recording properties - Enter a default user name and password of IP cameras - Pan, Tilt, Zoom control with IP cameras Mute Audio in Preview To mute audio sources in MediaRecorder. The muted audio is recorded normally in the video files. Prerequisite: You selected microphones in the Video Settings window. See Select an audio device. Procedure Select the audio sources you wish to mute in the Mute column. Change Video Order in Preview To change the order of the video cameras, for example to change the position of the images in a Picture in Picture recording. Prerequisite: You selected the recording devices in the Video Settings window. See Select a video device. Procedure - Drag and drop rows in the table with video devices or drag and drop the preview images. - Click the Refresh button. See Refresh the preview. You cannot drag and drop Picture in Picture, or Picture by Picture preview images. Drag and drop the rows in the table with video devices instead. Show Frame Rate, Resolution and Format To display hidden rows in the table with video devices. Procedure Right-click one of the column headers and select the preferred options. The Format column shows the color space of the video file. The column is hidden by default, because the optimal color space is selected by default. For more information on color space, see: http://www.noldus.com/knowledge-base/what-color-space-format-used-media-recorder. Follow the same procedure to show or hide the Frame rate, Resolution, and Format columns in the Video Settings window. Refresh the Preview To display video images in the preview after a temporary connection loss or if you connected a camera after you opened MediaRecorder. Procedure Click the Refresh button. See Which Preview Image Comes From Which Camera To see which image comes from which camera. Prerequisite: You selected the recording devices in the Video Settings window. See Select a video device. Procedure Press the Identify button. Result: Numbers are superimposed on the camera images. These correspond to the row numbers in the table. Show or Hide Recording Properties To show or hide the table under the preview of the camera images, so that the space for the preview images is increased. Procedure Click Recording properties. Result: The size of preview images is increased. Save the Camera Settings To make a configuration file that can be used to open the correct cameras, microphones and video settings. Prerequisites: - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You selected camera, microphones and video output in the Video Settings window. See Select a video device, Select an audio device and Video file options for the procedures. The settings you create for the different cameras are automatically saved when you close MediaRecorder. They are saved to the file Current settings.mrs that is present in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. These settings are used when you restart MediaRecorder. You can also save your own settings, or save different settings for different setups, for example, a webcam for a test participant's face in a usability test room and three overview IP cameras in an observation room. This way you do not have to select all cameras manually each time. Procedure - Choose File > Save Configuration As. - Give the configuration a name and click Save. To open a saved configuration, choose File > Open configuration. IMPORTANT: Never shut down the computer by pressing the power button or cutting off the electricity. Your settings may become lost, even after you saved the settings. Always use the Windows shut down feature to close your computer. To go back to the default configuration, choose File > Open Configuration. Browse to the file Default Settings.mrs. This file is read-only. When Noldus installed MediaRecorder for you, the file is in the folder D:\Noldus\MediaRecorder. When you installed MediaRecorder yourself, the file is in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder, or the folder you selected when you installed MediaRecorder. If you encounter problems with starting MediaRecorder, for example because you created wrong settings which are loaded when you start MediaRecorder, delete the file Current settings.mrs. MediaRecorder will then start with the default settings and you can create new settings. Pan, Tilt, Zoom Control with IP Cameras To change the camera view in MediaRecorder. Prerequisites: - Your IP camera supports ONVIF Profile S. - Your IP camera can Pan, Tilt and Zoom. - The camera is selected in MediaRecorder. See Select a video device. Hover with your mouse over the camera image. Two buttons appear in the top-right corner of your window: - Enable or disable PTZ control. - Open the PTZ preset menu. PTZ Control - Click the Enable PTZ button in the image you want to adjust. A four-arrow cross appears in the middle of the image and your mouse pointer becomes a small point. - Click the camera image and keep your left mouse button pressed to control the camera. The cross becomes connected to the point and the camera image moves in the direction of the point. The further away from the center cross you click, the faster the camera moves. - Zoom in and out with your mouse wheel. Save Camera Position If you are satisfied with the position of your camera, you can save this as a PTZ preset. Hover over the camera image and click the button that opens the PTZ menu. The following options are available: - Save as first PTZ preset. - Save as second PTZ preset. - Return to first PTZ preset. - Return to second PTZ preset. The Save as buttons appear when you hover over the Return to PTZ preset buttons. PTZ Keyboard Shortcuts The following keyboard shortcuts can be used to control PTZ: - Ctrl + 1 - Enable / disable PTZ in first video - Ctrl + 2 - Enable / disable PTZ in second video - Ctrl + 3 - Enable / disable PTZ in third video - Ctrl + 4 - Enable / disable PTZ in fourth video - Numerical keypad 1 - Move camera left-down - Numerical keypad 2 - Move camera down - Numerical keypad 3 - Move camera right-down - Numerical keypad 4 - Move camera left - Numerical keypad 6 - Move camera right - Numerical keypad 7 - Move camera left-up - Numerical keypad 8 - Move camera up - Numerical keypad 9 - Move camera right-up - Numerical keypad + - Zoom in - Numerical keypad - - Zoom out If you use the CH products RS Desktop joystick for PTZ control, make sure it is connected before you start MediaRecorder. To reverse the camera pan or tilt direction, open the Advanced Video Settings window and select the checkbox Flip Pan axis or Flip Tilt axis. See step 11 in Select ONVIF cameras in MediaRecorder in Set up IP cameras. Change the PTZ Method MediaRecorder has two PTZ methods. The default method is described above. It is also possible to let the camera center its camera view to the point that you click with your mouse. - Open MediaRecorder and select your IP cameras. See Select ONVIF cameras in MediaRecorder. - Close MediaRecorder. This saves settings for the IP cameras in the file Current Settings.mrs. - Create a backup of the file Default Settings.mrs that is present in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. - Open the file Current Settings.mrs from the same folder with Notepad. - Locate the line 1 and change 1 to 0. There is a line for each PTZ camera that you selected in MediaRecorder. Change the line for each PTZ camera. Important: When you selected the same camera multiple times in MediaRecorder, use the same method for pan and tilt in each camera. For each camera, use either 1 or 0. - Save the file as Default Settings.mrs. These settings are used when the file Current Settings.mrs is not found. - Delete the file Current Settings.mrs from the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. - Re-open MediaRecorder. MediaRecorder opens with configuration file Default Settings.mrs and creates a new file Current Settings.mrs with the edited settings. The new PTZ method is now available. To Pan and Tilt the Camera View (Alternative PTZ Method) - Click the Enable PTZ button in the image you want to adjust. - A white cross appears. The camera moves to the point that you click with your mouse. Enter a Default User Name and Password for IP Cameras To enter the ONVIF user name and ONVIF password of IP cameras only once, in case you have several cameras with the same credentials. Procedure - Choose File > Preferences > IP camera settings. - Select Use default IP camera user name and password. - Enter the user name and password. - Follow the procedure in Select ONVIF cameras in MediaRecorder or Select devices that do not support ONVIF in MediaRecorder. When you click the Advanced video settings button, the user name and password are filled in automatically. Use Commands to Control Recording To control video recording with another program that can send commands, for example, EthoVision XT. Prerequisites: - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - You selected cameras, microphones and video output in the Video Settings window of MediaRecorder. See Select a video device, Select an audio device, and Video file options. Procedure In your application, browse to the program MRCmd.exe that is by default located in the folder C:\Program Files\Noldus\MediaRecorder 6 and specify the command. For example, use the following command line to start video recording: "C:\Program Files\Noldus\MediaRecorder 6\MRCmd.exe /R" If you installed MediaRecorder in another folder than the default one, the program MRCmd.exe is present in that folder. Adjust your command lines accordingly. Available Commands - Start MediaRecorder - MRCmd.exe or MRCmd.exe /E - Start recording - MRCmd.exe /R - Stop recording - MRCmd.exe /S - Close MediaRecorder - MRCmd.exe /X - Closes MediaRecorder program. - Load a configuration file - MRCmd.exe /C=[filename.mrs]. See Load a configuration file. - Set the file base name - MRCmd.exe /B=[basename]. See Set file base name. There is a space between MRCmd.exe and the slash. Load a Configuration File The command /C loads a configuration file with the settings for your cameras. This is useful to open MediaRecorder with the correct cameras. Make sure MediaRecorder is not recording at that moment. By default MRCmd.exe loads a file from the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. If the file is located in another folder, you must type the full path. If the file name or the path contains spaces you must type it in between quotation marks. Example 1 - Open MediaRecorder and load Configuration_observation_room.mrs from C:\Users\Public\Public Documents\Noldus\MediaRecorder: MRCmd.exe /E /C=Configuration_observation_room.mrs Example 2 - Opening MediaRecorder and load Configuration Control Room from C:\Configuration files: MRCmd.exe /E /C="C:\Configuration files\Configuration Control Room.mrs" Set File Base Name The command /B sets the File base name. See Set video file base name. Example - Set the File base name to Observation room: MRCmd.exe /B="Observation room" This option cannot be used together with other commands. Command Timing and Delay Allow enough time between commands. If a command is sent before the previous one is carried out, the second command is not carried out. For example, if the command Start Recording is sent before MediaRecorder is completely open, recording does not start. There may be a delay between the command Start Recording and the moment the recording actually starts. This delay depends on the number of cameras, camera settings, the processor speed and programs running in the background. In the most common scenarios with MediaRecorder and The Observer XT, the videos are automatically synchronized with the events, so the delay is not important. See also Synchronize videos with events in MediaRecorder with The Observer XT. Picture by Picture Resolution The highest allowed resolution of a recorded video is 1920 x 1280. The resolution of a Picture by Picture video is a sum of the separate videos. However, if that exceeds a width of 1920 pixels or a height of 1280 pixels, the video resolution is adjusted proportionally. This requires processor capacity and decreases the quality of the output video. It is better to choose a lower resolution of the individual videos, so that the total resolution does not exceed 1920 x 1280. The resolution of the Picture by Picture video is determined in the following way: - Example 1 - The width of the PbP video is the sum of the width of the separate videos. The height of the PbP video is the maximum height of the separate videos. - Example 2 - The total resolution is calculated in the same way as in Example 1. The width of the resulting video exceeds the maximum of 1920 pixels. Therefore both the width and height are reduced proportionally, resulting in a width of 1920 pixels. - Example 3 - The total width is the sum of the width of Video 1 and 2. The height of the resulting video is the maximum height of Video 1 and 2 plus the height of Video 3. Both the width and height of the resulting video will exceed the maximum of 1920 x 1280. Therefore both the width and height are reduced proportionally, resulting in a width of 1920 pixels. The height is now smaller than the maximum of 1280 pixels. If the height was higher than 1280, the width and height would be reduced further, resulting in a height of 1280 pixels. MediaRecorder with The Observer XT How to Record Videos for The Observer XT You can create videos for use in The Observer XT in two ways. You can either first create videos in MediaRecorder and then make your observations offline using The Observer XT, or you can control the recording process with commands from The Observer XT while making a live observation. Offline Observations Using Prerecorded Video Making offline observations in The Observer XT means carrying out an observation using a prerecorded video. The video files created by MediaRecorder can be used to observe offline in The Observer XT. No special settings are needed to use files from MediaRecorder in The Observer XT. Observe Live and Control MediaRecorder You can score live in The Observer XT while simultaneously recording a video using MediaRecorder. You can use The Observer XT to control MediaRecorder. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder - Troubleshooting and Advanced Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-troubleshooting-and-advanced-settings Chapter: Media Recorder Media Recorder - Troubleshooting and Advanced Settings Color Improvements and White Balance - Click Color Improvements Control. - Point the camera at a piece of white paper, so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - Save the settings (see below). To Save the Camera Settings - Click the Stop button. - In the Features panel, open the Configuration Sets item (User Set Control for USB 3 cameras). - From the Configuration Set Selector list (User Set Selector for USB 3 cameras), select User Set 1. - Next to User Set Save, click Execute. The camera settings set in the previous steps are now saved under User Set 1. - From the Default Startup Set list (User Set Default for USB 3 cameras), select User Set 1. - Close Pylon Viewer. These settings will be used each time you start up MediaRecorder. You can also save different settings for the same camera in User Set 2 and User Set 3. Under Default Startup Set (User Set Default), select which you want MediaRecorder to use. Set Up the Epiphan Pearl Nano Screen Capture Device To connect the Epiphan Pearl Nano screen capture device and make the necessary settings. Prerequisites - The network allows data transfer of at least 1 Gb per second. - We recommend using a dedicated network for the cameras. - The cables must be suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. Procedure - Install MediaRecorder with its prerequisites. See Installation. - Using a HDMI cable, connect the output of the video source to the HDMI IN port on the back panel of the Epiphan Pearl Nano device. - Using a HDMI cable, connect the control monitor to the HDMI PASS THROUGH port on the back panel of the Epiphan Pearl Nano device. - Use the control keys on the front panel to configure the system parameters. - Using the right arrow key, navigate to System Status. - Here, you can get the network IP address of your device and you can also check the firmware version. It is recommended to use the latest firmware version. If you need an update, register your device at Epiphan (https://www.epiphan.com/support/product-registration/). - Using the left arrow key, navigate to Menu. Within Menu, navigate to System > Network. - Disable DHCP. Set the IP address manually. Define an IP address range similar to that of the other cameras. - By default, do not change Network mask and Network gateway settings. If uncertain, consult your system administrator. - Open your internet browser. Use the IP address of your Epiphan Pearl Nano device to access the Pearl Admin panel. Include /admin in the address to access the Admin panel. - Using the Pearl Admin panel, configure video encoding. Go to Channel(s), select your channel and click Encoding. In Video settings, make sure Current signal resolution is used as frame size (have the checkbox checked). - Set Key frame interval to 1/2 sec. At Limit frame rate, it is not recommended to change the default value of 30. If you use a higher frame rate, it might jeopardize your recording operation. Do not change the default Bitrate value (auto). - Open MediaRecorder and choose File > Video settings or click Video settings. - In Video Settings, select the option RTSP IP Camera (Noldus RTSP Source Filter). Please note that the Epiphan Pearl Nano device is NOT an ONVIF device. For details, see Select devices that do not support ONVIF in MediaRecorder. The RTSP connection string for this device is /stream.sdp. - Please note that you cannot use the Epiphan Pearl Nano device to make audio recordings. Use another audio device for this purpose. For details, see Select an audio device. Set Up USB 3 Cameras Overview: Steps to Install USB 3 Cameras - Install the USB 3 interface card - Install the USB 3 camera driver - Connect the USB 3 cameras to the PC - Configure the Basler USB 3 camera Prerequisite You have USB 3 cameras that are supported by MediaRecorder. See Supported USB cameras in Recording devices. Which Situation Applies to You? You ordered the computer, cameras and MediaRecorder from Noldus IT. In case of Basler USB 3.0 cameras, your computer has a USB 3 card and its drivers are installed. The cameras are configured. MediaRecorder has also been set up to use these cameras. You can connect your cameras and start recording. See Connect the USB 3 cameras to the PC and Record video. You bought the computer somewhere else. Carry out the entire procedure below. Procedure - In case of Basler USB 3 cameras, install the supported USB 3 interface card, even if your computer already has USB 3 ports. See Install the USB 3 interface card. - Carry out the prerequisite steps before installing MediaRecorder. See The steps to install MediaRecorder in Installation. - Install MediaRecorder with the camera driver. Installing the camera driver is only needed for the Basler USB 3 camera. For the Logitech BRIO no driver installation is needed. See Install the USB 3 camera driver. - Connect the USB 3 cameras to the PC. - Configure the Basler USB 3 camera. Install the USB 3 Interface Card MediaRecorder was tested with the following USB 3 interface cards: - U3-PCIE1XG205-1S - You can connect one USB 3 camera to this card. - Fresco Logic U3X4-PCIE4XE111 rev 1.1 - You can connect up to four USB 3 cameras to this board. To Install the USB 3 Interface Card - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. For details about PCIe slots, see PCIe slot properties in Set up analog cameras. - Unpack the USB 3 interface card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. - Fix the card to the chassis and re-fit the computer's cover. If you have a 4-port Fresco Logic U3X4-PCIE4XE111 rev 1.1 board, make sure the board receives power from the PC. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. Install the USB 3 Camera Driver To install the software that allows communication between your camera and the operating system of the computer with MediaRecorder. Prerequisites - You have the Basler USB 3 camera. - You have installed the USB 3 interface card. See Install the USB 3 interface card. - You carried out the prerequisite steps before installing MediaRecorder. See The steps to install MediaRecorder in Installation. IMPORTANT: If you upgraded from a previous MediaRecorder version and had old drivers for the camera installed, you must uninstall them first. To Uninstall Old Drivers - Open the Control Panel. - Choose Programs and Features. - Select Pylon Camera Software Suite and choose Uninstall. Install the Camera Drivers for the Basler USB 3 Camera If You Have Not Yet Installed MediaRecorder - Download the installation files from my.noldus.com and extract the contents. - Browse to the file MediaRecorder 6 Setup.exe and double-click it. - In the Drivers and tools field, choose Basler USB Camera driver - pylon [version number]. - Click Next, accept the License Agreement and click Install. If You Have Already Installed MediaRecorder Follow the instructions in the section above and choose Modify in the installation window. Alternatively: - Download the necessary files from my.noldus.nl and extract the contents. - Browse to Drivers\Basler\7.1.0.25066. - Double-click the file Basler_pylon_7.1.0.25066.exe. - Agree to the terms in the License Agreement. - In the Profiles window, choose Camera user and click Next. - As camera type, choose USB and click Next. - Optionally, change the location where the camera drivers are stored and choose Next > Install. To Uninstall Old Basler Camera Drivers - Open the Control Panel. - Choose Programs and Features. - Select the Basler camera driver and choose Uninstall. Connect the USB 3 Cameras to the PC Connect the cameras to the USB 3 interface card of the MediaRecorder computer. USB 3 connectors and ports can be recognized by their blue color coding, or by a double-S in front of the USB icon. Important: Using multiple Basler USB 3 cameras with a laptop is not supported. Configure the Basler USB 3 Camera To adjust settings in the USB 3 camera, such as the video frame rate, resolution, and exposure. Note: The camera settings are stored by the camera itself, not on the PC. When you work with multiple cameras, repeat the procedure for each camera. Procedure - Make sure MediaRecorder (and EthoVision XT, when present on the computer) are not running. - Start the Basler Pylon Viewer software that comes with the USB 3 camera. The Basler Pylon Viewer software is installed automatically when you install the camera drivers. - In the Devices panel, under USB, double-click the Basler camera. - Under Features, open the item Basler acA1920-155um and choose the settings you would like to change. For details, see the corresponding settings in Configure the cameras in Set up GigE cameras. - Save the settings under User Set Control. Audio Devices Which Audio Device Should I Use? The appropriate audio device depends on your setup. Take the following rules of thumb into account: - For room settings, use one omnidirectional ceiling microphone. - For meetings around a table, use one boundary layer table microphone. - For usability research behind the computer, use a microphone close to the test participant, for example a wireless microphone or boundary layer table microphone. - For very good audio quality for more than one test participant, use a wireless microphone for each person. - Audio quality strongly depends on the room settings. An expensive audio device does not by itself guarantee good audio. If the devices are not placed correctly, or if the acoustics in the room are bad, audio quality will suffer. - Do not place the microphone cables in the vicinity of 230 V electricity cables. If you route microphone cables in electrical conduits, the electricity can interfere with the audio. - Use sound absorbing material, like curtains, to avoid echoes on audio recordings. Important Concepts in Audio Preamplifiers The signal from a microphone is of low voltage. This signal needs to be amplified prior to further processing, such as mixing or recording. This is done with a preamplifier. The strength of the signal that is amplified this way is called line-level. When you subsequently connect the preamplifier to the sound card of your computer, select Line in when a message pops up that a new device is detected. The unamplified signal is very sensitive to noise. Therefore the preamplifier should be positioned as close to the microphone as possible. When you use a digital video device and connect the audio directly to the sound card of the computer, the sound card of the computer functions as a preamplifier. For recordings with digital devices, you can connect the microphone directly to the computer. When a message pops up that a new device is detected, select Mic-in as input source. Balanced Cables In professional audio, a balanced line or balanced signal pair is a transmission line consisting of two conductors of the same type. Both lines have equal impedances along their lengths and equal impedances to ground and to other circuits. Both lines are twisted together and then wrapped with a third conductor (foil or braid) that acts as a shield. Common balanced cables are cables with XLR connectors. Balanced cables are the opposite of unbalanced cables. A coaxial cable is an example of an unbalanced cable. The main advantage of the use of balanced lines is good rejection of external noise. Because the signal between the microphones and preamplifier is most sensitive to noise, it is most important to use balanced lines there. Phantom Power Phantom power, often indicated with P48, is a method to supply condenser microphones with power through microphone cables. Condenser microphones give better audio quality than other types of microphones, but they are more sensitive to noise. Preamplifiers and mixers can often supply microphones with phantom power. Gain The gain of a preamplifier is the degree to which the amplifier magnifies the low-level input signal compared to its output signal. It is the ratio of the output voltage divided by the input voltage and is expressed in decibels (dB). The formula to calculate gain is 20 x Log (Voltage output / Voltage input). A gain of 6 dB doubles the voltage 2 times and a gain of 20 dB gives a 10-fold increase in the signal. Gain Trim For some amplifiers the gain can be selected in ranges. For example, a LOW gain gives a range from 18 to 38 dB. With the switch Gain trim, you can select the actual gain. High Pass Filter A high-pass filter (HPF) is a device in a preamplifier that passes high frequencies. Therefore it reduces the amplitude of frequencies lower than its cutoff frequency. It is sometimes called a low-cut filter or bass-cut filter. Supported Microphones Ceiling Microphone Ceiling microphones are omnidirectional and are suitable for both speech and other sounds. MediaRecorder supports the following ceiling microphone: - Sennheiser MKE2-60-Gold-C (can also be used as a table microphone). This microphone requires 12-48V phantom power. Table Microphone Table microphones are acoustically optimized for picking up speech. They are designed for use on conference tables, altars and lecterns. MediaRecorder supports the following table microphones: - Sennheiser ME35 - Sennheiser ME36 - Sennheiser MKE2-60-Gold-C (can also be used as a ceiling microphone) - Sennheiser e 912 S BK - Nikon ME-W1 The Sennheiser microphones listed above require 12-48V phantom power. Wireless Microphone MediaRecorder supports the Sennheiser EW 312 G3 B series wireless microphone set. Use this wireless microphone set when there is more than one test participant, and/or the participants are moving. The microphone set comes with a clip-on microphone and a receiver. The wireless microphone receiver continuously switches between antennas, checks which antenna picks up the strongest signal and selects that one. This means that the antennas can be mounted at different places. If reception is poor when the wireless microphone is in the experiment room, you could install one antenna in that room. If the quality of the received signal is bad, for example if the signal has to go through a wall, you can use the special coax cable for extending the antennas (50 ohm). In general, both antennas should use the same cable length. It is recommended to position the two antennas at an angle of 90 degrees. No phantom power is needed for the wireless microphone. The signal that comes from the receiver is preamplified. MediaRecorder also supports the Nikon ME-W1 microphone. This microphone has been tested in a portable lab setup with a Dell 3551 notebook and Axis P1375 cameras. For more information, see Recording devices. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder - User Management and Permissions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-user-management-and-permissions Chapter: Media Recorder Procedure for Domain - Press the Windows key + R. - Type lusrmgr.msc and press OK. - Open the Users folder and double-click Guest. - Deselect Account is disabled and click OK and close the lusrmgr window. - Press the Windows key + R. - Type gpedit.msc and press OK. - Open Computer Configuration\Windows Settings\Security Settings\Local Policies\User Rights Assignment and double-click Deny access to this computer from the network. - Click Guest and then choose Remove > OK. - Close the Local Group Policy Editor window. Map the Shared Folder with MediaRecorder Video Files Carry out this procedure on both computers. - Open File Explorer and then This PC. - Click Computer and then click the Map network drive icon. - Choose a name for the drive and browse to the shared folder. Important: Make sure you select the same drive on both computers. - Click Finish. Note: When you now start the computer with The Observer XT, you need to enter the login details for the computer with MediaRecorder. MediaRecorder with The Observer XT Install N-Linx Agent Aim: To install and set up the tool that starts MediaRecorder when you start an observation in The Observer XT. Important: Install N-Linx Agent on the computer with MediaRecorder. Prerequisite: You installed N-Linx Server on a computer in the network. Procedure - From my.noldus.com, download N-Linx Agent Setup.exe. - In the N-Linx Agent Setup window, select MediaRecorder control in the Drivers and Tools field and click Next. - Accept the terms in the End-User License Agreement and click Install. Connect N-Linx Agent to N-Linx Server - Click the arrow in the bottom-right corner of your window to open the system tray. Then double-click the N-Linx Agent icon. - In the N-Linx Server Address field, enter the computer name of the computer with N-Linx Server. See To find the computer name. You can also enter the IP address, but then the IP address of the computer with N-Linx Server must be fixed. Ask your system administrator for assistance. If MediaRecorder runs on the same computer as N-Linx Server, leave the entry localhost in the N-Linx address field. N-Linx Agent then automatically connects with N-Linx Server. Note: See To change the port if the default port 5672 is already in use. - If the connection with N-Linx Server is established, the text Connected appears in the lower-left corner of the N-Linx Agent window. To Find the Computer Name To find the name of the computer with N-Linx Server, open the Control Panel on that computer and choose System. To Change the Port N-Linx Agent by default uses port 5672 to communicate with N-Linx Server. If this port is in use, type the new port after a colon in the N-Linx Server Address field. Important: Select the same port in all components that communicate with N-Linx Server. Also, disable Windows Firewall for this port. Notes: - N-Linx Agent is installed in the folder C:\Program Files\Noldus\N-Linx Agent 1. - If you did not install N-Linx Server yet, it will not be possible to establish a connection. - The Status of MediaRecorder in the N-Linx Agent window is Online when MediaRecorder is open and connected to N-Linx Server. Create MediaRecorder Settings Aim: To connect MediaRecorder to N-Linx Server and select the video file folder. Prerequisites: - If MediaRecorder, The Observer XT, and N-Linx Server are not all installed on the same computer, you created exceptions for the N-Linx port in Windows Firewall. See Create exceptions for N-Linx port in Windows Firewall. - You installed N-Linx Server on a computer in the network. - N-Linx Agent is installed on the computer with MediaRecorder and connected to N-Linx Server. See Install N-Linx Agent. Procedure - In MediaRecorder, choose File > Preferences > N-Linx settings. - Select Allow communication with N-Linx Server. - In the N-Linx Server address field, leave the default value Localhost if MediaRecorder runs on the same computer as N-Linx Server. If the programs run on different computers, enter the name of the computer with N-Linx Server. See also To find the computer name. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. - When the connection with N-Linx Server is established the Status will be Connected. Click OK. - If MediaRecorder and The Observer XT run on different computers, select the mapped drive as location to store the video files and not the original folder. The original folder is locally on the computer with MediaRecorder and cannot be accessed by The Observer XT. Example: You mapped the default folder C:\Users\Public Documents\Noldus\MediaRecorder\Video files as X:\. Set the default video file location where MediaRecorder stores its video files to X:\ and not to the original folder. Create The Observer XT Settings Aim: To enable communication between The Observer XT and N-Linx Server. Prerequisites: - You installed N-Linx Server on a computer in the network. - If MediaRecorder and The Observer XT, or N-Linx Server run on different computers, you created exceptions for the port that N-Linx uses in Windows Firewall. See Create exceptions for N-Linx port in Windows Firewall. - N-Linx Agent is installed on the computer with MediaRecorder and connected to N-Linx Server. See Install N-Linx Agent. - MediaRecorder is open. Procedure - In The Observer XT, choose File > Preferences > N-Linx Settings. - Select Use N-Linx server to connect with other applications. - In the N-Linx Server address field, enter the computer name of the computer with N-Linx Server. If The Observer XT is installed on the same computer as N-Linx Server, leave the default entry Localhost. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. - Click Test connection. If a connection with N-Linx Server is found, the Status will change to Connected. - Click OK. - Choose Setup > Project Setup. - Under Observation source, select Live Observation. The Devices window now opens. If not, click the Devices button. - Select MediaRecorder [Version number][Computer name] and click Edit Settings. MediaRecorder now opens if it is not already open. - Click Edit Settings again. A window with the available configurations now opens. Select the configuration file you want to use and click OK. If you do not select a configuration, Current Settings.mrs will be used. Optionally enter a unique name in the Identify device as field. This way you can control multiple instances of MediaRecorder with one instance of The Observer XT. - Repeat steps 9 and 10 for each MediaRecorder instance. Note: When you close MediaRecorder, the MediaRecorder line in the Devices window (step 9) will be grayed out and the status will change to Disabled. MediaRecorder will start when you create an observation. Carry Out an Observation in The Observer XT Procedure - In The Observer XT, choose Observe > Observation > New to create an observation. - See Carry out your observation in The Observer XT Help. - Press the Start observation button and score the data. See Start the observation and Score data in The Observer XT Help. - Press the Stop observation button. See Stop the observation in The Observer XT Help. Important: Allow enough time between the actions. If you start an observation before MediaRecorder is completely open, video recording will not start. Troubleshooting: MediaRecorder Control with The Observer XT When MediaRecorder control with The Observer XT does not function properly, check the following: - On the computer with MediaRecorder, check that N-Linx Agent is running. See step 1 in Connect N-Linx Agent to N-Linx Server. If there is no N-Linx Agent icon in the system tray, the program is not running. Then double-click the file NLinxAgent.exe in the folder C:\Program Files\Noldus\N-Linx Agent 1. - On the computer with MediaRecorder, check that the status of N-Linx Agent is Connected. If not, follow steps 2 and 3 in Connect N-Linx Agent to N-Linx Server. - In MediaRecorder, check that the checkbox Allow communication with N-Linx Server is selected (see step 2 in Create MediaRecorder Settings). - In The Observer XT, check that Use N-Linx server to connect with other applications is selected (see step 2 in Create The Observer XT settings) and that the Status in the window is Connected (see step 5 in Create The Observer XT settings). - In The Observer XT, check that MediaRecorder is selected (see step 9 in Create The Observer XT settings). - On all computers with MediaRecorder, The Observer XT, and N-Linx Server, check that an exception is made in Windows Firewall for all inbound and outbound traffic through port 5672 (see Create exceptions for N-Linx port in Windows Firewall). - Check that N-Linx Server is running. To do so, press Ctrl + Shift + Esc and open the Services tab. Locate the line RabbitMQ and check that the Status is Running. If not, right-click the line and select Start. Synchronize Videos with Events Aim: To synchronize the MediaRecorder videos with the event log of The Observer XT. When is Manual Synchronization Not Needed? Videos created by MediaRecorder are automatically synchronized with the events in The Observer XT when you followed the procedure in MediaRecorder with The Observer XT. An automatic offset is applied to the videos. See View the automatic offset of videos imported into The Observer XT to see which offset was applied. When is Manual Synchronization Needed? You need to synchronize videos and events manually in the following situations: - You start video recording manually and import the videos into The Observer XT. - You have an older version of The Observer XT that does not support N-Linx data transfer. See Synchronize manually for the procedure. View the Automatic Offset of Videos Imported into The Observer XT The procedure depends on what you did: - You controlled video recording with The Observer XT. - You manually started video recording within 10 seconds after starting the observation in The Observer XT. You Controlled Video Recording with The Observer XT Right-click the video in The Observer XT and choose Properties. The field Recording details shows the offset. You Manually Started Video Recording Within 10 Seconds After Starting the Observation in The Observer XT When you import the videos into The Observer XT, an offset is automatically set. A message with the calculated offset is shown. If you right-click the video in The Observer XT, the offset is also shown next to Recording details in the Video Properties window that opens. However, there can still be up to 1 second asynchronism between the observation and the video files. If that is a problem for the accuracy of your experiments, Synchronize manually to fine-tune the synchronization. Synchronize Manually Aim: To synchronize imported MediaRecorder videos with events in The Observer XT. Prerequisites: One of the following situations is true: - You have The Observer XT 11 or lower. - You have The Observer XT 12.5 or lower and The Observer XT and MediaRecorder run on different computers. - You manually started video recording more than 10 seconds after starting an observation in The Observer XT and imported those videos manually into The Observer XT. You must carry out the following steps: - Determine the time difference between video and events. - Apply offset to correct for the time difference. Determine the Time Difference Between Video and Events - Make sure an event is recognizable in the videos and the event log. For example, create a dummy behavior with a key code in the coding scheme. - Carry out an observation and simultaneously record a video or the keyboard. - In The Observer XT, press the key of the dummy behavior. The event is recorded in the Event log and is visible in the video. - Import the video into The Observer XT. - Open the observation and scroll to the recognizable event in the video. Note the time difference of the event in the video and the event log. Apply Offset to Correct for the Time Difference - In The Observer XT, open the observation and click the Offset button on the toolbar. - Select Numerical Offset to open the File Synchronization window. - Set the time difference in the Offset cell. For example, if the video started 0.2 seconds before the observation, enter 0.20 seconds in the Offset field of the video. Note: You can also use the SyncBox to assess the delay. See the Technical Note - The SyncBox - The Observer XT for more information. MediaRecorder with EthoVision XT How to Record Videos for EthoVision XT You can create videos for use in EthoVision XT in two ways: - First create videos in MediaRecorder and then track from video file in EthoVision XT. - Control video recording by MediaRecorder with EthoVision XT when you track live. In both cases, if you work with analog cameras, you must adjust the aspect ratio in EthoVision XT. If you work with digital cameras, this is not necessary. See Adjust the video aspect ratio (analog cameras only). Prevent Black Frames at the Start of Your Videos To make sure that MediaRecorder waits for an I-frame before it starts recording you can edit the VsSettings file that comes with MediaRecorder. If you do not edit this file, your video may start with black frames and EthoVision will not be able to track the video from the start. The VsSettings file is installed together with MediaRecorder. You can find the file in C:\ProgramData\Noldus\MediaRecorder\6. By default the ProgramData folder is a hidden folder. In Windows Explorer on the View tab select Hidden items in the Show/hide section to view the folder. - Right-click VsSettings.xml and select Copy. Right-click and select Paste to make a copy of the file. Keep this copy in case you want to go back to the original settings. - Open the VsSettings.xml file in Notepad or a similar text editor. - From the Edit menu select Find and type Wait in the search field. - To make sure that MediaRecorder waits for an I-frame before it starts recording, edit the file and change 0 to 1. - Save the file. First Create Videos in MediaRecorder and Then Track from Video File in EthoVision XT Aim: To create videos that can be used for tracking in EthoVision XT. Prerequisite: You have cameras that are supported for tracking in EthoVision XT. Procedure - Create videos in MediaRecorder. - In EthoVision XT, select Track from video file and select the video. See the EthoVision XT Help for details. Notes: - Important: In theory you can create video files from many different digital cameras with MediaRecorder. However, the quality of the digital camera is essential for accurate tracking. If you use other hardware or cameras than the supported ones, you need to check whether the time information in the video files is correct. See Test an unsupported setup in Specifications. - When you use analog cameras, you must adjust the aspect ratio. For digital cameras that are not supported this may also be necessary. See Adjust the video aspect ratio (analog cameras only). - Choose EthoVision as the Output Quality if you record from four cameras simultaneously. With the default settings two cameras are recorded on CPU and two on the video card (GPU). This results in differences in file size. By selecting EthoVision as the output quality, all four cameras will be recorded using CPU power. For more information see Output settings. - Choose DanioVision as the Output Quality if you film DanioVision larvae. With this setting the compression of the video files is optimized for DanioVision tracking. Source: Media Recorder 6.5 Reference Manual --- ## Media Recorder 6.5 - Quick Start Guide URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-65-quick-start-guide Chapter: Media Recorder Install MediaRecorder IMPORTANT - If you have an older version of MediaRecorder - Uninstall MediaRecorder 6.0 and older versions before you install MediaRecorder 6.5. To Install MediaRecorder 6.5 - Download the installation files from my.noldus.com, and extract the contents. - Double-click the file MediaRecorder [Version number] Setup.exe. - Under Installation type, select Standard. - In the Drivers and tools field, choose the driver of your video device. - Click Next, accept the End-User License Agreement and click Install. Notes - See Specifications for the supported devices. - See Recording Devices for specific information on your device like the maximum number of cameras you can use simultaneously and the maximum supported frame rate and resolution. Up and Running Quickly This Quick Start Guide guides you through the main steps to record video with MediaRecorder. This Quick Start Guide contains basic information on MediaRecorder functionalities. It does not contain information how to connect and setup your cameras. Also, it does not contain information on the prerequisites and restrictions for specific camera types. You can find this additional information in the MediaRecorder Help. Press F1 in the program to open it, or type MediaRecorder Help in the Windows apps screen. Start MediaRecorder - Connect all cameras and microphones to the computer with MediaRecorder. - Depending on your license, do one of the following: - If you have a hardware key - Insert it into a USB port of the computer and start MediaRecorder. - Start MediaRecorder and activate your software license key. You can choose between a Floating or a Fixed activation. - Floating — Choose Floating if you want to be flexible on which computer you use MediaRecorder and your computer is connected to the internet. - Fixed — A Fixed activation is linked to one computer. Your computer must have an internet connection to activate/deactivate a fixed license. After you have activated the license you can use MediaRecorder without internet. The first time MediaRecorder opens, the preview window is black. That is because you still have to select the cameras. Proceed with the next steps to do so. Select Cameras - Choose File > Video Settings, or click Video Settings in the main window. TIP If the Video Settings button is not visible, the recording properties may be closed. Click Recording properties at the bottom of your window. - Select your camera from the Video device list. See Set up IP cameras in the MediaRecorder Help how to select IP cameras. - Select the frame rate and resolution. - For advanced camera settings, click the video symbol next to the name of your camera. The available options depend on your camera. For some cameras you can zoom and adjust settings for brightness and contrast. - Optionally change the names in the Video name column, to, for example, Overview camera, or Close-up participant 1. - To record audio as well, continue with Select Microphones. - Optionally, select some additional settings for your video files. See Options. - When satisfied with the settings, click OK to leave the Video Settings window and start recording. See Record Video. Select Microphones - Select the microphones from the Audio device list. Choose between your computer microphone, a separate microphone, or the audio stream of your camera. Choose No audio to not record audio. - Optionally, record the same audio stream in all videos. To do so, select this checkbox. Please note that in Picture-in-Picture mode, you may select which audio source to use for all the videos. See Select an Audio Device. - Optionally, click the microphone button for advanced audio settings. The available options depend on your microphones. Move the sliders to adjust the recording volume. - Optionally, change the names in the Audio name column. To Check the Recording Volume - Right-click the speaker icon in the bottom-right corner of your window and select Recording devices. - Check that the green bar is maximal when speech level is normal. - Continue with Options, or click OK to close the Video Settings window and start recording. Note Audio is needed and has been tested only for cameras that are supported with The Observer XT. See Recording Devices in the MediaRecorder Help which cameras are. Options For a full overview of the options, see the MediaRecorder Help. Set a Recording Time - Choose File > Video Settings. - Select Use maximum recording time and enter the time. Source: Media Recorder 6.5 Quick Start Guide, Noldus Information Technology --- ## Media Recorder 6.5 - Select Output Settings For Multiple Cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/media-recorder-65-select-output-settings-for-multiple-cameras Chapter: Media Recorder Select Output Settings for Multiple Cameras If you have selected more than one video source, MediaRecorder can create a separate video file for each camera, but also one video of all camera streams. Choose File > Video Settings and select one of the options under Output Settings. The following options are available: - Separate Videos — One video file for each camera. - Picture by Picture — One video file with the images from each camera next or above each other. - Picture in Picture — One video file with a large image of the first camera with the images from the other cameras embedded in it. If you select this option the following settings become available: - PiP Position — The position of the embedded images. - PiP Size — The size of the embedded images. The percentage is based on the width of the first camera image. The aspect ratios of the embedded camera images are maintained. - PiP Margin — The margin of the embedded images. When the percentage is zero, the embedded images are positioned directly on the edge of the main image. The percentage is based on the width of the first camera image. Note: If possible, choose the same frame rate for all the videos for Picture in Picture or Picture by Picture. If you choose different frame rates the videos with the lowest frame rates may flicker. To Select the Video File Location The default location where MediaRecorder stores its video files is: - D:\Noldus\MediaRecorder\Video Files — If Noldus IT installed your system. - C:\Users\Public\Public Documents\Noldus\MediaRecorder\Video Files — In all other cases. To change the default location, click the button next to the File location field of the main MediaRecorder window and select another folder. You must have writing rights in this folder. Also make sure that there is enough disc space. Dependent on the recording device, frame rate, resolution and amount of movement, MediaRecorder videos can be up to 600 Mb per hour. To Select a File Base Name The name of the recorded video file consists of the File base name followed by: - The video input name. - The date and the time the videos were recorded. The format of the date and time depends on the computer's regional settings. - The number of the video camera. Save the Settings The settings you create for the different cameras are automatically saved when you close MediaRecorder. They are saved to the file Current settings.mrs that is present in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. These settings are used when you restart MediaRecorder. But you can also save your own settings, or save different settings for different setups, for example, a webcam for a test participant's face in a usability test room and three overview IP cameras in an observation room. This way you do not have to select all cameras manually each time. Procedure - Choose File > Save Configuration As. - Give the configuration a name and click Save. To Open a Saved Configuration Choose File > Open Configuration and select a .mrs file. - Important: Never shut down the computer by pressing the power button or cutting off the electricity. Always use the Windows shut down feature to close your computer. - To go back to the default configuration, choose File > Open Configuration. Open the file Default Settings.mrs. Record Video When you selected all cameras, you see a preview in the main MediaRecorder window. Tip: If you selected multiple microphones, it can be useful to mute all but one audio channel in the preview. Select the audio source in the Mute column of the table under the preview. Muting audio in the preview does not influence the recording. To start recording, press the Start Recording button. A pop-up window will appear, informing you about Noldus's Data Transparency Policy. Read it carefully before clicking the I will inform the participants button. You can also check the box Don't show me again to prevent further occurrence. The button then changes into the Stop Recording button and the Recording timer starts running. Press the button again to stop recording. Recording stops automatically when you specified a recording time. How to Access the Recorded Videos To quickly access the recorded videos, press the Open target folder button in the main MediaRecorder window. The video files are stored in the default video file location, or the location you specified. See To Select the Video File Location. MediaRecorder Help The MediaRecorder Help opens when you press F1 in the program. It can also be accessed in the Windows apps screen, and can be downloaded from the MyNoldus portal. From the Help menu select Noldus Online and then MyNoldus Portal. Training Courses Noldus offers training courses to help you get the most out of our software/hardware. In addition to on-site courses at your lab and in-house courses at our headquarters in Wageningen (The Netherlands) and Leesburg (VA, USA), we offer remote training courses. Remote trainings are available in the same range of languages as on-site courses. Please contact your sales representative for more information about trainings. Support If you encounter problems, contact Noldus Technical Support. From the Help menu select Noldus Online and then MyNoldus Portal and submit a support case or find a helpdesk in your region. Source: Media Recorder 6.5 Quick Start Guide, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2. License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-2-license-94d Chapter: Media Recorder License 2.1. Upon payment by the End-User of the license fees for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates or supplements of the Software. If upgrades, updates or supplements of the Software are obtained, however, the use of such upgrades or updates is governed by this EULA and the amendments that may accompany them and may be subject to additional payments and conditions. 2.2. The End-User may download, install and use the Software on as many computers as is reasonably necessary, however the Software may not be shared or used concurrently on more computers than for which EULA's are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. 2.3. End-User is allowed to store or install a copy of the Software for back-up or archival purposes. 2.4. End-User shall not (i) modify, alter, adapt, merge, decompile or reverse-engineer the Software or any part thereof nor create any derivative works based on all or any part of the Software, or (ii) remove or obscure any copyright, trademark or other ownership notices from the Software, or (iii) sub-license, sell, rent, lease, hire, loan, assign or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. 2.5. The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices and Network Licensing. End-User is prohibited to (attempt to) remove, alter or circumvent in any way any part of such Security System. 2.6. End-User is responsible for regular, frequent and effective backups of all files produced or modified while working with the Software. Intellectual Property 3.1. All title, copyright and other industrial, intellectual or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. 3.2. The Software may include or make use of third party software, including open source software. Such third party software may be subject to the third party's terms and conditions provided in the documentation accompanying the Software and may contain copyright or other industrial, intellectual or proprietary rights of such third party. End-User hereby agrees to the terms and conditions for such third party software. In the absence of any third party terms and conditions, this EULA will govern the third party software in the Software. 3.3. End-User may, from time to time, provide Noldus with comments, suggestions, data, information or feedback ("Feedback") on the Software. End-User acknowledges and agrees that such Feedback may be freely used by Noldus, at its sole discretion, for the design, development, improvement, marketing and commercialization of its products and services, without any restrictions based on confidentiality or intellectual property rights. Transfer 4.1. End-User is entitled to make a one-time, permanent transfer of this EULA and Software only directly to one other End-User. This transfer must include all of the Software (including all component parts, the media and printed materials, any upgrades and this EULA). Such transfer may not be by way of consignment or any other indirect transfer and shall be subject to the following provisions: - End-User will provide to Noldus prior to any such transfer the full name and address details of the new End-User and the expected date of transfer in writing. - The new End-User understands and agrees to all the terms and conditions of this EULA in the same way as if the new End-User had obtained the Software from Noldus or an Authorized Partner. - End-User will destroy all (partial) copies of the Software and all accompanying materials, including but not limited to installed copies and any backup copies on data storage devices and guarantee to Noldus in writing that this has been done. If the Software is an upgrade, any transfer must include all prior versions of the Software. - Noldus reserves the right to levy an administrative charge upon the End-User and/or the new End-User in relation to transfer of the Software to an End-User. 4.2. Any attempted transfer without prior written permission from Noldus shall constitute a material breach of this Agreement and shall be deemed null and void. Term; Termination 5.1. The EULA shall enter into force on the date of acceptance by the End-User and continue until terminated in accordance with this Section 5. 5.2. If the Software is licensed on a subscription basis, the EULA shall continue until the end of the current subscription period. 5.3. Noldus is entitled to terminate the EULA immediately upon prior written notice upon: - The breach of any material provision of this Agreement by the End-User if (i) such breach is not curable or (ii) if curable, the End-User has not cured such breach within 30 (thirty) day period following receipt of a written notice by Noldus substantiating such breach ("ingebrekestelling"). - The filing or institution of bankruptcy, liquidation or receivership proceedings of the End-User or in the event a receiver or custodian is appointed for the End-User's business, or if its business is discontinued or if it has a petition presented by a creditor for its winding up or if the End-User enters into any liquidation (other than for purpose of reconstruction or amalgamation). 5.4. Upon termination of the EULA, the End-User shall immediately discontinue the use of the Software and remove the software of all computers, destroy all (partial) copies of the Software from all storage media and return the documentation and materials relating to the Software to Noldus or its Authorized Partner. 5.5. Termination of this Agreement does not remove or reduce End-User's obligation to pay any outstanding license fees or other monies, all of which shall be due for payment immediately on termination of the EULA. 5.6. The following provisions shall survive termination of this EULA: Sections 3, 7, 9, 10 and this Section 5.6. In addition, any other provisions which are required to interpret and enforce the Parties' rights and obligations under the EULA shall also survive any termination or expiration of this EULA, but only to the extent required for the full observation and performance of the EULA. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2. License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-2-license Chapter: Media Recorder License 2.1. Upon payment by the End-User of the license fees for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates or supplements of the Software. If upgrades, updates or supplements of the Software are obtained, however, the use of such upgrades or updates is governed by this EULA and the amendments that may accompany them and may be subject to additional payments and conditions. 2.2. The End-User may download, install and use the Software on as many computers as is reasonably necessary, however the Software may not be shared or used concurrently on more computers than for which EULA's are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. 2.3. End-User is allowed to store or install a copy of the Software for back-up or archival purposes. 2.4. End-User shall not (i) modify, alter, adapt, merge, decompile or reverse-engineer the Software or any part thereof nor create any derivative works based on all or any part of the Software, or (ii) remove or obscure any copyright, trademark or other ownership notices from the Software, or (iii) sub-license, sell, rent, lease, hire, loan, assign or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. 2.5. The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices and Network Licensing. End-User is prohibited to (attempt to) remove, alter or circumvent in any way any part of such Security System. 2.6. End-User is responsible for regular, frequent and effective backups of all files produced or modified while working with the Software. Intellectual Property 3.1. All title, copyright and other industrial, intellectual or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. 3.2. The Software may include or make use of third party software, including open source software. Such third party software may be subject to the third party's terms and conditions provided in the documentation accompanying the Software and may contain copyright or other industrial, intellectual or proprietary rights of such third party. End-User hereby agrees to the terms and conditions for such third party software. In the absence of any third party terms and conditions, this EULA will govern the third party software in the Software. 3.3. End-User may, from time to time, provide Noldus with comments, suggestions, data, information or feedback ("Feedback") on the Software. End-User acknowledges and agrees that such Feedback may be freely used by Noldus, at its sole discretion, for the design, development, improvement, marketing and commercialization of its products and services, without any restrictions based on confidentiality or intellectual property rights. Transfer 4.1. End-User is entitled to make a one-time, permanent transfer of this EULA and Software only directly to one other End-User. This transfer must include all of the Software (including all component parts, the media and printed materials, any upgrades and this EULA). Such transfer may not be by way of consignment or any other indirect transfer and shall be subject to the following provisions: - End-User will provide to Noldus prior to any such transfer the full name and address details of the new End-User and the expected date of transfer in writing. - The new End-User understands and agrees to all the terms and conditions of this EULA in the same way as if the new End-User had obtained the Software from Noldus or an Authorized Partner. - End-User will destroy all (partial) copies of the Software and all accompanying materials, including but not limited to installed copies and any backup copies on data storage devices and guarantee to Noldus in writing that this has been done. If the Software is an upgrade, any transfer must include all prior versions of the Software. - Noldus reserves the right to levy an administrative charge upon the End-User and/or the new End-User in relation to transfer of the Software to an End-User. 4.2. Any attempted transfer without prior written permission from Noldus shall constitute a material breach of this Agreement and shall be deemed null and void. Term; Termination 5.1. The EULA shall enter into force on the date of acceptance by the End-User and continue until terminated in accordance with this Section 5. 5.2. If the Software is licensed on a subscription basis, the EULA shall continue until the end of the current subscription period. 5.3. Noldus is entitled to terminate the EULA immediately upon prior written notice upon: - The breach of any material provision of this Agreement by the End-User if (i) such breach is not curable or (ii) if curable, the End-User has not cured such breach within 30 (thirty) day period following receipt of a written notice by Noldus substantiating such breach ("ingebrekestelling"). - The filing or institution of bankruptcy, liquidation or receivership proceedings of the End-User or in the event a receiver or custodian is appointed for the End-User's business, or if its business is discontinued or if it has a petition presented by a creditor for its winding up or if the End-User enters into any liquidation (other than for purpose of reconstruction or amalgamation). 5.4. Upon termination of the EULA, the End-User shall immediately discontinue the use of the Software and remove the software of all computers, destroy all (partial) copies of the Software from all storage media and return the documentation and materials relating to the Software to Noldus or its Authorized Partner. 5.5. Termination of this Agreement does not remove or reduce End-User's obligation to pay any outstanding license fees or other monies, all of which shall be due for payment immediately on termination of the EULA. 5.6. The following provisions shall survive termination of this EULA: Sections 3, 7, 9, 10 and this Section 5.6. In addition, any other provisions which are required to interpret and enforce the Parties' rights and obligations under the EULA shall also survive any termination or expiration of this EULA, but only to the extent required for the full observation and performance of the EULA. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 6. Warranty URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-6-warranty Chapter: Media Recorder Warranty Noldus warrants that the Software as of the date of delivery to the End-User by Noldus or its Authorized Partner, the Software will, for a period of 90 days ("Warranty Period") materially conform to the specifications set out in the user documentation accompanying the Software ("Specifications"), provided that: - The Software is properly installed on a supported computer platform (as defined in documents that can be accessed on https://my.noldus.com) and used in accordance with the provisions of the accompanying user documentation and/or any Noldus-approved training course; - Noldus is notified in writing within 14 days after any non-conformity of the Software was known or should reasonably have been known to End-User and the End-User has made available all the information that might reasonably be required to allow Noldus to investigate, recreate and where possible remedy a non-conformity; - The Software has not been (a) altered, repaired or modified by any party other than Noldus or a third party provider approved by Noldus; or (b) used with software or a computer platform other than set out in the documents that can be accessed on https://my.noldus.com or have been subjected to negligence, or computer or electrical malfunction; or (c) were used, adjusted, or installed other than in accordance with instructions by Noldus. Other than set out above, no warranties are expressed or implied with respect to the Software or any element thereof, including without limitation its quality, performance, accuracy, merchantability or suitability or fitness for any purpose, whether or not that purpose has been communicated by End-User to Noldus. The Software is a general product developed by Noldus for a wide range of solutions, requirements and situations and End-User is responsible for purchasing the Software required for his needs. Noldus explicitly does not warrant that the Software shall be entirely without error or fault nor that it will operate without interruption. End-User agrees that such errors, faults or interruptions shall not be deemed material and cause to terminate this EULA. The warranty set out above applies only to the first installation of the Software and will not apply, resume or renew upon delivery or installation of any subsequent update or upgrade to the Software, alteration in the number of EULAs granted for use of the Software, or any other extensions, upgrades or alterations to the Software where the Software has previously been delivered to or installed by the End-User. The warranty set out above shall further not apply to Software that is licensed or otherwise made available at no cost, or Software that is designated as 'prototype', 'alpha' or 'beta' code, all of which are provided 'as is' and without warranty, representation or liability. Warranty Remedies Upon receipt of an End-User's written notice of the Software not conforming to the Specifications during the Warranty Period, Noldus shall at its option and in its sole discretion: - Assist the Customer in correcting or replacing the non-conforming Software; or - Terminate the EULA immediately and refund the purchase price paid by the End-User. The remedies described above shall be End-User's sole and exclusive remedies. Upon expiration of the Warranty Period, Noldus shall have no obligation to provide such remedies. Support and Maintenance Noldus and Authorized Partners are not responsible for maintaining or supporting use of the Software or obligated to provide any updates, fixes or support to the Software unless otherwise expressly agreed in writing between End-User and Noldus or the Authorized Partners. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 6. Warranty URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-6-warranty-MN4 Chapter: Media Recorder Warranty Noldus warrants that the Software as of the date of delivery to the End-User by Noldus or its Authorized Partner, the Software will, for a period of 90 days (Warranty Period) materially conform to the specifications set out in the user documentation accompanying the Software (Specifications), provided that: - The Software is properly installed on a supported computer platform (as defined in documents that can be accessed on https://my.noldus.com) and used in accordance with the provisions of the accompanying user documentation and/or any Noldus-approved training course; - Noldus is notified in writing within 14 days after any non-conformity of the Software was known or should reasonably have been known to End-User and the End-User has made available all the information that might reasonably be required to allow Noldus to investigate, recreate and where possible remedy a non-conformity; - The Software has not been: - Altered, repaired or modified by any party other than Noldus or a third party provider approved by Noldus; or - Used with software or a computer platform other than set out in the documents that can be accessed on https://my.noldus.com or have been subjected to negligence, or computer or electrical malfunction; or - Used, adjusted, or installed other than in accordance with instructions by Noldus. Limitation of Warranties Other than set out in the warranty provisions above, no warranties are expressed or implied with respect to the Software or any element thereof, including without limitation its quality, performance, accuracy, merchantability or suitability or fitness for any purpose, whether or not that purpose has been communicated by End-User to Noldus. The Software is a general product developed by Noldus for a wide range of solutions, requirements and situations and End-User is responsible for purchasing the Software required for his needs. Noldus explicitly does not warrant that the Software shall be entirely without error or fault nor that it will operate without interruption. End-User agrees that such errors, faults or interruptions shall not be deemed material and cause to terminate this EULA. Scope of Warranty The warranty applies only to the first installation of the Software and will not apply, resume or renew upon delivery or installation of any subsequent update or upgrade to the Software, alteration in the number of EULAs granted for use of the Software, or any other extensions, upgrades or alterations to the Software where the Software has previously been delivered to or installed by the End-User. The warranty shall further not apply to Software that is licensed or otherwise made available at no cost, or Software that is designated as prototype, alpha or beta code, all of which are provided as is and without warranty, representation or liability. Warranty Remedies Upon receipt of an End-User's written notice of the Software not conforming to the Specifications during the Warranty Period, Noldus shall at its option and in its sole discretion: - Assist the Customer in correcting or replacing the non-conforming Software; or - Terminate the EULA immediately and refund the purchase price paid by the End-User. The remedies described above shall be End-User's sole and exclusive remedies. Upon expiration of the Warranty Period, Noldus shall have no obligation to provide such remedies. Support and Maintenance Noldus and Authorized Partners are not responsible for maintaining or supporting use of the Software or obligated to provide any updates, fixes or support to the Software unless otherwise expressly agreed in writing between End-User and Noldus or the Authorized Partners. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 7. Liability; Indemnification URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-7-liability-indemnification Chapter: Media Recorder Liability; Indemnification 7.1. End-User acknowledges that the Software is intended for research or training purposes only and agrees not to use the Software for diagnosis or treatment of disease in human subjects. End-User agrees not to use the Software in any application where the failure, malfunction or inaccuracy of the Software carries the risk of death or bodily injury. 7.2. Noldus Software shall not be used for collection of biometric data from human subjects without prior informed consent from the person whose data is being captured. 7.3. Noldus does not allow the use of its Software for the following applications: - Active defense, i.e. embedding Noldus Software in a weapon system. - Biometric data collection in criminal, security-related or similar investigations or procedures. - Surveillance of people in public spaces for security purposes. - Any other use that may potentially violate fundamental human rights (https://www.un.org/en/about-us/universal-declaration-of-human-rights). 7.4. If Noldus notices that its Software is used for applications that it does not approve, this may lead to discontinuation of customer support and termination of the EULA. 7.5. To the fullest extent permitted by law, and notwithstanding any other provision of this EULA to the contrary: - In no event will Noldus or the Authorized Partners be liable to the End-User for Indirect Losses or for special, incidental, consequential, exemplary, enhanced, or punitive damages, including without limitation, any damages resulting from interruption of business, loss of use, loss of profits or revenue, or loss of business, arising out of or in connection with this EULA, the Software, or the performance of Noldus, the Authorized Partners, or third parties engaged by Noldus in the performance of this EULA, regardless of whether Noldus, the Authorized Partners, End-User, or any other person or entity has been advised of (or could have reasonably foreseen) the possibility of such damages or Indirect Losses. If, despite the provisions in this EULA, liability exists anyway, only direct damage will be eligible for reimbursement. 7.6. Noldus' and Authorized Partners' liability shall also be excluded, and Noldus and the Authorized Partners shall not have any liability under this EULA in the event of: - End-User's use of the Software other than in accordance with Section 7.1; - Direct and indirect consequences of the End-User's failing to adhere strictly to the user documentation provided or made available by Noldus or the Authorized Partner; or - Any loss of or damage to files or data howsoever caused. 7.7. A liability claim will be unenforceable and lapse unless Noldus or the Authorized Partner receives a written notice thereof no later than 6 months after the discovery of an event or circumstance that gives or may give rise to that claim. 7.8. Noldus will hold harmless, defend, and indemnify End-User from and against all losses, damages, claims, liabilities, and expenses incurred by End-User that arise out of, relate to, or are caused by any third party claim that End-User's use of the Software, pursuant to the terms of this EULA, infringes the intellectual property rights of such third party. If such a claim is made or appears likely to be made, Noldus, at its option, will have the right to either (i) procure for the End-User the right to continue to use the Software, (ii) modify or replace the Software so that it is no longer infringing (in a manner that substantially retains its functionality and quality), or (iii) require End-User to terminate the use of and return the Software and refund a pro rata portion, if any, of the amount paid by End-User to Noldus for the infringing Software. Notwithstanding the foregoing, Noldus will have no liability to End-User if the infringement results from use of the Software in combination with software not provided by Noldus or from modifications made by Noldus to conform to specifications provided by End-User. The indemnification obligations in this section are subject to: (i) End-User giving Noldus prompt written notice of any claim (provided that End-User's failure to provide prompt written notice will only relieve Noldus of its obligations under this Section to the extent such failure materially limits or prejudices Noldus' ability to defend or settle such claim); (ii) the transfer of sole control of the defense and any related settlement negotiations to Noldus; and (iii) End-User's cooperation, at Noldus' expense, in the defense of such claim. This section states End-User's sole and exclusive remedies for third party intellectual property infringement claims. 7.9. End-User shall indemnify and hold harmless Noldus, the Authorized Partners, and the third parties engaged by Noldus from and against any and all losses (including Indirect Losses and special, incidental, consequential, exemplary, enhanced, or punitive damages) arising out of or caused by (i) any failure in the performance of the obligations of the End-User under the law, this EULA, or Noldus' General Terms and Conditions, or (ii) any and all third party claims on any grounds whatsoever, directly or indirectly related to the End-User's use of the Software, the contents thereof, or any results or materials generated by the Software. 7.10. The limitation of liability provisions set forth in this Section 7 shall apply even if End-User's remedies under this EULA fail of their essential purpose. 7.11. Noldus and End-User acknowledge and agree that the parties entered into this EULA in reliance upon the limitations of liability set forth in this Section 7, that the same reflect an allocation of risk between the parties (including the risk that a contract remedy may fail of its essential purpose and cause consequential loss), and that the same form an essential basis of the bargain between the parties. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 7. Use Limitation; Liability; Indemnification URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-7-use-limitation-liability-indemnification Chapter: Media Recorder Use Limitation; Liability; Indemnification 7.1. End-User acknowledges that the Software is intended for research or training purposes only and agrees not to use the Software for diagnosis or treatment of disease in human subjects. End-User agrees not to use the Software in any application where the failure, malfunction or inaccuracy of the Software carries the risk of death or bodily injury. 7.2. Noldus Software shall not be used for collection of biometric data from human subjects without prior informed consent from the person whose data is being captured. 7.3. Noldus does not allow the use of its Software for the following applications: - Active defense, i.e. embedding Noldus Software in a weapon system; - Biometric data collection in criminal, security-related or similar investigations or procedures; - Surveillance of people in public spaces for security purposes; - Any other use that may potentially violate fundamental human rights. 7.4. If Noldus notices that its Software is used for applications that it does not approve, this may lead to discontinuation of customer support and termination of the EULA. 7.5. To the fullest extent permitted by law, and notwithstanding any other provision of this EULA to the contrary: - In no event will Noldus or the Authorized Partners be liable to the End-User for Indirect Losses or for special, incidental, consequential, exemplary, enhanced, or punitive damages, including without limitation, any damages resulting from interruption of business, loss of use, loss of profits or revenue, or loss of business, arising out of or in connection with this EULA, the Software, or the performance of Noldus, the Authorized Partners, or third parties engaged by Noldus in the performance of this EULA, regardless of whether Noldus, the Authorized Partners, End-User, or any other person or entity has been advised of (or could have reasonably foreseen) the possibility of such damages or Indirect Losses. If, despite the provisions in this EULA, liability exists anyway, only direct damage will be eligible for reimbursement. 7.6. Noldus' and Authorized Partners' liability shall also be excluded, and Noldus and the Authorized Partners shall not have any liability under this EULA in the event of: - End-User's use of the Software other than in accordance with Section 7.1; - Direct and indirect consequences of the End-User's failing to adhere strictly to the user documentation provided or made available by Noldus or the Authorized Partner; or - Any loss of or damage to files or data howsoever caused. 7.7. A liability claim will be unenforceable and lapse unless Noldus or the Authorized Partner receives a written notice thereof no later than 6 months after the discovery of an event or circumstance that gives or may give rise to that claim. 7.8. Noldus will hold harmless, defend, and indemnify End-User from and against all losses, damages, claims, liabilities, and expenses incurred by End-User that arise out of, relate to, or are caused by any third party claim that End-User's use of the Software, pursuant to the terms of this EULA, infringes the intellectual property rights of such third party. If such a claim is made or appears likely to be made, Noldus, at its option, will have the right to either: - Procure for the End-User the right to continue to use the Software; - Modify or replace the Software so that it is no longer infringing (in a manner that substantially retains its functionality and quality); or - Require End-User to terminate the use of and return the Software and refund a pro rata portion, if any, of the amount paid by End-User to Noldus for the infringing Software. Notwithstanding the foregoing, Noldus will have no liability to End-User if the infringement results from use of the Software in combination with software not provided by Noldus or from modifications made by Noldus to conform to specifications provided by End-User. The indemnification obligations in this section are subject to: - End-User giving Noldus prompt written notice of any claim (provided that End-User's failure to provide prompt written notice will only relieve Noldus of its obligations under this Section to the extent such failure materially limits or prejudices Noldus' ability to defend or settle such claim); - The transfer of sole control of the defense and any related settlement negotiations to Noldus; and - End-User's cooperation, at Noldus' expense, in the defense of such claim. This section states End-User's sole and exclusive remedies for third party intellectual property infringement claims. 7.9. End-User shall indemnify and hold harmless Noldus, the Authorized Partners, and the third parties engaged by Noldus from and against any and all losses (including Indirect Losses and special, incidental, consequential, exemplary, enhanced, or punitive damages) arising out of or caused by: - Any failure in the performance of the obligations of the End-User under the law, this EULA, or Noldus' General Terms and Conditions; or - Any and all third party claims on any grounds whatsoever, directly or indirectly related to the End-User's use of the Software, the contents thereof, or any results or materials generated by the Software. 7.10. The limitation of liability provisions set forth in this Section 7 shall apply even if End-User's remedies under this EULA fail of their essential purpose. 7.11. Noldus and End-User acknowledge and agree that the parties entered into this EULA in reliance upon the limitations of liability set forth in this Section 7, that the same reflect an allocation of risk between the parties (including the risk that a contract remedy may fail of its essential purpose and cause consequential loss), and that the same form an essential basis of the bargain between the parties. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 8.Miscellaneous URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-8miscellaneous-1fm Chapter: Media Recorder Miscellaneous 8.1. Parties may communicate with each other by electronic mail. Parties recognize the risks associated with electronic mail and declare that they shall not hold each other liable for any damage incurred by either of them as a result of the use of electronic mail. If a Party is in doubt as to the content of an electronic message received, the content of the message originating with the sender shall be decisive. 8.2. The invalidity or unenforceability of any provision this EULA shall not affect or limit the validity or enforceability of any other provisions thereof. Any such invalid or unenforceable provision shall be deemed to be substituted by a provision that is considered to be valid and enforceable. The interpretation of the substituting provision shall be as close as possible to the economic, legal and commercial objectives of the severed provision. 8.3. Failure by Noldus or the Authorized Partner to enforce any of its rights under the EULA shall not constitute a waiver of such rights thereunder and shall not relieve End-User of its obligation to comply with such provisions. No waiver or amendment of any provisions therein shall be effective unless signed in writing by a Noldus representative. Any such written waiver shall only be applicable to the specific instance to which it relates and shall not be deemed to be a continuing or future waiver. 8.4. Amendments or changes to this EULA can only be agreed upon in writing between the Parties. 8.5. The EULA shall be binding upon the Parties thereto, their legal representatives, successors and assigns. End-User shall not assign any right or obligation arising out of this EULA without the prior written consent of Noldus. Any attempt by End-User to assign or delegate any obligation hereunder shall be deemed null and void. Governing Law: End-Users USA or Canada 9.1. If End-User is a legal entity and its principal place of business is located in the United States of America or Canada, or if End-User is an individual whose primary residence is located in the United States of America or Canada: - This EULA is exclusively governed by the laws of the Commonwealth of Virginia and the applicable federal laws of the United States of America, without regard to the conflicts of law provisions of any jurisdiction. Without limiting the previous sentence, End-User and Noldus expressly agree: (i) that the Virginia Uniform Computer Information Transactions Act, Virginia Code §§ 59.1-501.1 et seq. ("UCITA"), and the United Nations Convention on Contracts for the International Sale of Goods ("CISG") are expressly excluded from this EULA, (ii) that any and all terms contained in UCITA or CISG will have no force or effect on any portion of this EULA, and (iii) that UCITA and CISG do not apply to this EULA or the Software. - Any and all claims and disputes arising out of or in connection with this EULA, the Software, or the performance or non-performance by either party of any of its obligations under this EULA, which End-User and Noldus cannot resolve amicably within a reasonable period of time, will be commenced and maintained only in a state or federal court of competent subject matter jurisdiction situated or located in the United States of America. Noldus and End-User consent to the exclusive personal jurisdiction of and venue in any such court. - To the extent permitted by law: End-User must commence or file any claim or action arising out of or relating to this EULA or the Software within six months after the cause of action accrues, otherwise, such claim or cause of action is permanently barred. To the extent permitted by law, End-User expressly waives the right to commence or file any such claim or action under any longer statute of limitations. Governing Law: End-Users Other Countries 10.1. If End-User is a legal entity and its principal place of business is located in any country other than the United States of America or Canada, or if End-User is an individual whose primary residence is located in any country other than the United States of America or Canada: - This EULA is exclusively governed by the laws of The Netherlands. The United National Convention for Contracts on the International Sale of Goods is expressly excluded. - Any disputes arising out or in connection with this EULA that cannot be solved amicably within a reasonable period of time will be submitted to the competent court in Arnhem, The Netherlands, for any dispute with End-Users having their principal place of business in the European Union. In the event that an End-User has its principal place of business outside the European Union, the United States of America or Canada, any dispute shall be finally settled in accordance with the Arbitration Rules of the Netherlands Arbitration Institute. Location shall be Arnhem, The Netherlands. The arbitration procedure shall be conducted by one (1) arbiter in the English language. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 8.Miscellaneous URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-8miscellaneous Chapter: Media Recorder Miscellaneous 8.1. Parties may communicate with each other by electronic mail. Parties recognize the risks associated with electronic mail and declare that they shall not hold each other liable for any damage incurred by either of them as a result of the use of electronic mail. If a Party is in doubt as to the content of an electronic message received, the content of the message originating with the sender shall be decisive. 8.2. The invalidity or unenforceability of any provision this EULA shall not affect or limit the validity or enforceability of any other provisions thereof. Any such invalid or unenforceable provision shall be deemed to be substituted by a provision that is considered to be valid and enforceable. The interpretation of the substituting provision shall be as close as possible to the economic, legal and commercial objectives of the severed provision. 8.3. Failure by Noldus or the Authorized Partner to enforce any of its rights under the EULA shall not constitute a waiver of such rights thereunder and shall not relieve End-User of its obligation to comply with such provisions. No waiver or amendment of any provisions therein shall be effective unless signed in writing by a Noldus representative. Any such written waiver shall only be applicable to the specific instance to which it relates and shall not be deemed to be a continuing or future waiver. 8.4. Amendments or changes to this EULA can only be agreed upon in writing between the Parties. 8.5. The EULA shall be binding upon the Parties thereto, their legal representatives, successors and assigns. End-User shall not assign any right or obligation arising out of this EULA without the prior written consent of Noldus. Any attempt by End-User to assign or delegate any obligation hereunder shall be deemed null and void. Governing Law: End-Users USA or Canada 9.1. If End-User is a legal entity and its principal place of business is located in the United States of America or Canada, or if End-User is an individual whose primary residence is located in the United States of America or Canada: - This EULA is exclusively governed by the laws of the Commonwealth of Virginia and the applicable federal laws of the United States of America, without regard to the conflicts of law provisions of any jurisdiction. Without limiting the previous sentence, End-User and Noldus expressly agree: (i) that the Virginia Uniform Computer Information Transactions Act, Virginia Code §§ 59.1-501.1 et seq. ("UCITA"), and the United Nations Convention on Contracts for the International Sale of Goods ("CISG") are expressly excluded from this EULA, (ii) that any and all terms contained in UCITA or CISG will have no force or effect on any portion of this EULA, and (iii) that UCITA and CISG do not apply to this EULA or the Software. - Any and all claims and disputes arising out of or in connection with this EULA, the Software, or the performance or non-performance by either party of any of its obligations under this EULA, which End-User and Noldus cannot resolve amicably within a reasonable period of time, will be commenced and maintained only in a state or federal court of competent subject matter jurisdiction situated or located in the United States of America. Noldus and End-User consent to the exclusive personal jurisdiction of and venue in any such court. - To the extent permitted by law: End-User must commence or file any claim or action arising out of or relating to this EULA or the Software within six months after the cause of action accrues, otherwise, such claim or cause of action is permanently barred. To the extent permitted by law, End-User expressly waives the right to commence or file any such claim or action under any longer statute of limitations. Governing Law: End-Users Other Countries 10.1. If End-User is a legal entity and its principal place of business is located in any country other than the United States of America or Canada, or if End-User is an individual whose primary residence is located in any country other than the United States of America or Canada: - This EULA is exclusively governed by the laws of The Netherlands. The United National Convention for Contracts on the International Sale of Goods is expressly excluded. - Any disputes arising out or in connection with this EULA that cannot be solved amicably within a reasonable period of time will be submitted to the competent court in Arnhem, The Netherlands, for any dispute with End-Users having their principal place of business in the European Union. In the event that an End-User has its principal place of business outside the European Union, the United States of America or Canada, any dispute shall be finally settled in accordance with the Arbitration Rules of the Netherlands Arbitration Institute. Location shall be Arnhem, The Netherlands. The arbitration procedure shall be conducted by one (1) arbiter in the English language. System Requirements Operating System MediaRecorder 6 supports Windows 11 64 bit Professional edition. Language Packs MediaRecorder 6.5 was thoroughly tested with the Windows 11 U.S. English language packs. It is possible that certain local language versions of Windows may affect the performance of the program. Touch Features MediaRecorder is not designed for use with Windows touch features. Desktop Computer MediaRecorder 6.5 has been tested with a Dell Precision™ T3640 and 5820 PC. If you order a complete solution from Noldus Information Technology, you will obtain one of these computers, or a successor, with MediaRecorder installed and ready to use. Laptop MediaRecorder 6.5 has been tested on a Dell Precision™ 3551 mobile workstation with the following devices only: - 2 Axis P1375 cameras (Portable Observation Lab). For more information on the Portable Observation Lab, consult the Reference Manual on the desktop of the notebook. - 1 Axis P1375 camera and 1 Epiphan Pearl Nano (Portable Usability Lab). For more information on the Portable Usability Lab, consult the Reference Manual on the desktop of the notebook. - 1 Basler acA1920-155um USB 3.0 camera. Technical Specifications Test Computers Dell Precision™ T3640 PC - Processor: Intel i7-10700, 4.8 GHz - Internal Memory: 8 GB - Hard Disk: 1 TB - Graphics Card: 5 GB NVIDIA Quadro P2200 Dell Precision™ 5820 - Processor: Intel i9-10900X CPU @ 3.70 GHz - Installed RAM: 8.00 GB - Graphics Card: Nvidia Quadro Pro P2200 Dell Precision™ 3551 Mobile Workstation - Processor: I7-10750H (6-core), 2.2 GHz - Internal Memory: 8 GB - Graphics Card: 4 GB Nvidia Quadro P620 - Hard Disk: 1 TB Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Acknowledgments And Copyright Notices URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-acknowledgments-and-copyright-notices Chapter: Media Recorder Acknowledgments and Copyright Notices MediaRecorder is a product of Noldus bv. However, MediaRecorder would not be what it is without the use of third-party software. This page lists software libraries and other software products used in MediaRecorder and links to license and compliance information and/or acknowledgments thereof. For the complete Terms and Conditions in PDF format, see the PDF files in the folder Documentation\Legal\Acknowledgments, located in your application folder (default: C:\Program Files\Noldus\MediaRecorder 6). - Adobe Acrobat Reader DC Software for viewing PDF files. Adobe | Distribution Agreement - Apache Thrift Combines a software stack with a code generation engine to build services that work efficiently and seamlessly between C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, JavaScript, Node.js, Smalltalk, OCaml and Delphi and other languages. Apache Software Foundation | Apache License 2.0 - Boost Open source (Boost community) software library, C++ templates. Boost Software License - Epiphan Driver A driver for Epiphan screen capture devices. Epiphan | Software License Agreement - Euresys H264 Picolo Driver for the Euresys Picolo video capture cards. Euresys | Terms & Conditions - HASP Library for software protection. Safenet EULA | Sentinel Gemalto - LEADTOOLS DirectShow Filters Video encoder and decoder software. LEADTOOLS - Live555 A set of C++ libraries for multimedia streaming. Live Network Inc. | License Agreement - MediaLooks DirectShow Filters Video mixer and screen capture software. MediaLooks | End User License Agreement - Pylon Camera Software Suite Windows A driver for Basler cameras. Basler | End-User License Agreement - Windows API Code Pack - Core Core library for Windows API Code Pack. Microsoft Software License Terms - Windows API Code Pack - Shell Shell library for Windows API Code Pack. Microsoft Software License Terms - Wix Toolset Tools for software installers. Wix Toolset | .NET Foundation | Microsoft Reciprocal License (MS-RL) Installation Procedure - Upgrade MediaRecorder - Upgrade your MediaRecorder license to continue working with your hardware key - Upgrade recording devices Upgrade MediaRecorder Aim: To upgrade an older version of the MediaRecorder software to version 6.5. Prerequisites: - You have an older MediaRecorder version. - You obtained an activation key for your MediaRecorder license. Procedure: - Download the installation files from my.noldus.com, and extract the contents. - Browse to the file MediaRecorder [Version number] Setup.exe and double-click it. - Follow the steps on your screen to install MediaRecorder 6.5. - Activate your MediaRecorder license. Continue Working with Your Hardware Key Aim: To configure your hardware key so that you can use it with the upgraded version of MediaRecorder. Prerequisites: - You upgraded MediaRecorder, or bought additional modules. - You obtained an upgrade key for your MediaRecorder license. Procedure: - Insert the hardware key into your computer and start the new version of MediaRecorder. - The system automatically detects the old license on the hardware key and the Enter Upgrade Key window appears. Enter the key codes that were supplied to you by Noldus IT. These numbers are normally sent by e-mail or are present in your welcome letter. Notes: - MediaRecorder 6.5 can be installed parallel to MediaRecorder 5, however, we recommend uninstalling older versions. - If you have a previous version of MediaRecorder on a computer with an operating system other than the 64-bit versions of Windows 10, you should either upgrade Windows, or install MediaRecorder on a computer with one of these operating systems. - After upgrading to MediaRecorder 6.5, new settings should be made for the cameras. Drivers and Firmware A device driver is software that allows communication between your operating system and the recording device. Noldus IT tests MediaRecorder with the latest device drivers and does not support older drivers. When you upgrade MediaRecorder, usually you must also upgrade device drivers. Firmware is software that is present in the recording device. Not all recording devices have firmware. Noldus tests MediaRecorder with the latest firmware and does not support older firmware, unless stated otherwise. When you upgrade MediaRecorder, you may also need to upgrade device firmware. Upgrade Device Drivers - Uninstall the old drivers with Windows Programs and Features. To do so, open the Control Panel and select Programs and Features. Locate the driver of your recording device and click Uninstall. See the section on your recording device for details on the driver names. - Install the new camera drivers. See the section on your recording device for details on how to do so. Upgrade Firmware Check the website of the manufacturer of the recording device whether new firmware is available. If this is the case, install the new firmware. Recording Devices Supported Device Types MediaRecorder is supported with the following device types. See the section on the device type for details on which specific devices have been tested. - Analog cameras - IP cameras - USB devices - GigE Vision cameras - Screen capture devices When Do I Need an Analog Camera? Under certain conditions analog cameras will serve you better than digital cameras. If cables longer than 5 m are needed between the camera and recording equipment, for most digital cameras, you need an amplifier. Industrial analog cameras may be more suitable in these cases. Cable lengths of 30–50 meters are generally no problem. An additional advantage of analog cameras is that their signals can easily be split by simply splitting the cable. To split a signal from a digital camera a video splitter or video splitting software is needed. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Apply Offset To Correct For The Time Difference URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-apply-offset-to-correct-for-the-time-difference Chapter: Media Recorder Apply Offset to Correct for the Time Difference - In The Observer XT, open the observation and click the Offset button on the toolbar. - Select Numerical Offset to open the File Synchronization window. - Set the time difference in the Offset cell. For example, if the video started 0.2 seconds before the observation, enter 0.20 seconds in the Offset field of the video. Note: You can also use the SyncBox to assess the delay. See the Technical Note - The SyncBox - The Observer XT for more information. MediaRecorder with EthoVision XT How to Record Videos for EthoVision XT You can create videos for use in EthoVision XT in two ways: - First create videos in MediaRecorder and then track from video file in EthoVision XT. - Control video recording by MediaRecorder with EthoVision XT when you track live. In both cases, if you work with analog cameras, you must adjust the aspect ratio in EthoVision XT. If you work with digital cameras, this is not necessary. See Adjust the Video Aspect Ratio (Analog Cameras Only). Prevent Black Frames at the Start of Your Videos To make sure that MediaRecorder waits for an I-frame before it starts recording, you can edit the VsSettings file that comes with MediaRecorder. If you do not edit this file, your video may start with black frames and EthoVision will not be able to track the video from the start. The VsSettings file is installed together with MediaRecorder. You can find the file in C:\ProgramData\Noldus\MediaRecorder\6. By default the ProgramData folder is a hidden folder. In Windows Explorer, on the View tab, select Hidden items in the Show/hide section to view the folder. - Right-click VsSettings.xml and select Copy. Right-click and select Paste to make a copy of the file. Keep this copy in case you want to go back to the original settings. - Open the VsSettings.xml file in Notepad or a similar text editor. - From the Edit menu select Find and type Wait in the search field. - To make sure that MediaRecorder waits for an I-frame before it starts recording, edit the file and change 0 to 1. - Save the file. Track from Video File in EthoVision XT Aim To create videos that can be used for tracking in EthoVision XT. Prerequisite You have cameras that are supported for tracking in EthoVision XT. Procedure - Create videos in MediaRecorder. - In EthoVision XT, select Track from video file and select the video. See the EthoVision XT Help for details. Notes - IMPORTANT: In theory you can create video files from many different digital cameras with MediaRecorder. However, the quality of the digital camera is essential for accurate tracking. If you use other hardware or cameras than the supported ones, you need to check whether the time information in the video files is correct. See Test an Unsupported Setup in Specifications. - When you use analog cameras, you must adjust the aspect ratio. For digital cameras that are not supported, this may also be necessary. See Adjust the Video Aspect Ratio (Analog Cameras Only). - Choose EthoVision as the Output Quality if you record from four cameras simultaneously. With the default settings, two cameras are recorded on CPU and two on the video card (GPU), resulting in differences in file size. By selecting EthoVision as the output quality, all four cameras will be recorded using CPU power. For more information see Output Settings. - Choose DanioVision as the Output Quality if you film DanioVision larvae. With this setting, the compression of the video files is limited to achieve optimal video quality for detecting small larvae. The file size will be larger than with the default Output Quality setting. Control Video Recording When You Track Live Aim To start video recording automatically when something of interest is detected by EthoVision XT. This is useful, for example, if you have animals that spend a lot of time in a shelter and you want to start video recording when the animal leaves the shelter. Prerequisites - You have cameras that are supported for tracking in EthoVision XT. - MediaRecorder and EthoVision XT run on the same computer. Procedure - In EthoVision XT, open the Trial Control screen by clicking Trial Control Settings in the Experiment Explorer. - In the Components pane, under Actions, click the button next to External command. - Enter a name in the Action Name field, for example, Start Recording. - Under Actions to perform, click the ellipsis button and browse to MRCmd.exe. By default, MRCmd.exe is present in the folder C:\Program Files\Noldus\MediaRecorder 6\MRCmd.exe. - Enter one of the commands available for MediaRecorder (/E, /R, /S, /X, or no command) as a Command line option. See Use Commands in Record Video. Example You carry out live tracking during a 24-hour period and want to make a recording in MediaRecorder only when the animal leaves the shelter. - Create an external command condition with the command /E to start MediaRecorder. - Insert a Condition Out of shelter. Combine this condition box with a Time condition, because opening MediaRecorder takes a few seconds. With a Time condition you make sure that MediaRecorder is open before recording starts. - Insert an External command box with the command /R to start recording. - Similarly, you can stop recording (Command line option: /S) when the animal enters the shelter again. Notes - For an extensive description of how to use Trial Control, see Trial Control in the EthoVision XT Help or the Reference Manual - Trial and Hardware Control in EthoVision XT. - IMPORTANT: Allow enough time between actions. If a command is sent before the previous one is carried out, the second command will not be executed. For example, if the command Start Recording is sent before MediaRecorder is completely open, recording does not start. - There may also be a delay between issuing the Start Recording command and MediaRecorder actually starting to record. This delay results in missed frames at the beginning of the video file. Run a test recording to see how long this delay is. To assess the delay, make a video of a digital clock and check the interval between issuing the Start Recording command and recording the first frame of the video. Adjust the Video Aspect Ratio (Analog Cameras Only) Aim To correct for a distorted video image in EthoVision XT. Prerequisite You created videos with MediaRecorder from analog cameras using the Picolo Alert PCIe Video Capture Board. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Before Purchasing A New Computer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-before-purchasing-a-new-computer Chapter: Media Recorder Before Purchasing a New Computer We recommend that you use the Dell Precision T3640 or T5820 desktop computer. For the devices that are supported on a laptop (See Laptop), we recommend the Dell Precision 3551 mobile workstation. If you are planning to purchase a different computer, please contact us for detailed advice. Computer Requirements For working with MediaRecorder and video (files or cameras), we recommend that you use a professional workstation. It is possible to buy consumer-range computers with a high processor speed and plenty of memory, but in order to remain competitive regarding price, the manufacturers often economize on the underlying system architecture. That means those computers are suitable for home use, but not for running professional scientific software. You should select a computer which is intended for professional use or labeled by the manufacturer as a workstation. If you use an older desktop computer, it should have at least a 2.8 GHz Quad Core processor and at least 4 GB of memory. A laptop should have at least a 2.6 GHz Quad Core processor and at least 4 GB of memory. You need sufficient free disk space to store the video files (MPEG-4 at least 0.5 GB/hr, and H.264 at least 0.6 GB/hr). For working with digital video, a good quality high-end video card designed for workstations is recommended. We recommend to use a separate 1 Gb network adapter for the IP and GigE cameras and the Epiphan Pearl Nano and preferably the Intel Pro/1000 CT or PT. For multiple GigE cameras, you need a separate network adapter for each camera. Test an Unsupported Setup Aim To test the quality of MediaRecorder videos with an unsupported camera or computer. Background When using an unsupported setup, the following problems may occur: - Video frames are dropped, resulting in incorrect video lengths. - The audio and video are not synchronous. - Two or more video streams are not synchronous. Procedure - Set a timer display running on a computer monitor (preferably with both digital and analog display) and play music (not on the same computer as MediaRecorder). Make sure no background programs are running on the computer. - Make a recording in the normal way. Remember to plug in your microphone if you plan to use audio. - After the normal maximum recording time, give an audio and visual cue (e.g. click your fingers) and stop the recording. - Check the recording length in MediaInfo and number of frames in GSpot. Use the frame rate to determine if any frames are dropped. See Tools for troubleshooting. - Go to the moment where you gave the cue and check if the audio and video are in sync, and if multiple videos are in sync. Whether a small error (one that normally tends to occur) is to be considered a problem or not depends entirely on the required level of accuracy of the audio and video recording. Tested Devices The latest version of MediaRecorder has extensively been tested with the following devices: IP Cameras - Axis P1375 - Axis M5525 - Axis M1075-L - Axis P5512 - Axis P5514 - Axis P5515 - Axis P5534 - Axis M1054 - Axis M1065-L - Hikvision IP DS-2PT7D20IW-DE Screen Capture Devices - Epiphan Pearl Nano - Epiphan DVI2USB 3.0 - Epiphan VGADVI Broadcaster - The MR Screen Capture Module Analog Cameras - PhenoTyper Top Unit camera (EIA and CCIR) in combination with the Euresys Picolo Alert PCIe USB Cameras - Basler acA1920-155um USB 3.0 camera - Basler acA2040-90uc - Logitech BRIO USB 3.0 camera FireWire Camera - The Imaging Source DMK 21AF04 for the DanioVision system with FireWire camera GigE Camera - Basler acA1300-60gm monochrome camera Combinations of Devices - Portable Observation Lab version 6 (two Logitech BRIO USB 3.0 cameras) - Portable Observation Lab version 5 (two Axis M1065 IP cameras) - Portable Usability Lab version 5 (one Logitech BRIO USB 3.0 camera and one Epiphan DVI2USB 3.0 screen capture device) - Stationary Usability Lab (three IP cameras and one Epiphan VGADVI broadcaster) Keyboard - CH Products RS Desktop joystick for Pan, Tilt, and Zoom control of IP cameras Formats of Video File Created by MediaRecorder The video format MediaRecorder creates depends on the input: - PhenoTyper Top Unit camera: Video files in H.264 AVC in an MPG container. - IP cameras: Video files in H.264 AVC with audio in AAC in an MP4 container. - Other digital cameras: Video files in MPEG-4 DivX with audio in AAC in an MP4 container. - Picture in Picture, or Picture by Picture; all video formats: Video files in MPEG-4 DivX with audio in AAC in an MP4 container. See Video File Options in Record Video for more information on the options Picture in Picture and Picture by Picture. MPEG-4 DivX MPEG-4 can achieve a high rate of compression with good quality, because it separately codes the background (which does not change much from frame to frame) from the moving parts of the video. MPEG-4 is in fact best seen as a collection of definitions rather than one fixed file format, and there are many different implementations of MPEG-4. MPEG-4 has a higher compression rate than for example MPEG-2 and it can have much higher resolution (with MediaRecorder up to 1920 x 1280 pixels). MediaRecorder creates MPEG-4 DivX video files from several digital recording devices (see above). DivX is an implementation of MPEG-4 which has both high quality and good compression. MPEG-4 DivX decoding software for playing back the video files is installed with MediaRecorder. H.264 AVC H.264 AVC is a type of MPEG-4 and is also known under the names H.264/AVC, AVC/H.264, H.264/MPEG-4 AVC, MPEG-4/H.264 AVC, MPEG-4 Part 10 or x.264. It creates good video quality and uses previously-encoded pictures as references in a much more flexible way than in other standards, allowing the use of up to 16 reference frames. MediaRecorder creates H.264 AVC video files from output of analog and IP cameras (see above). H.264 decoding software for playing back the video files is installed with MediaRecorder. Note: On computers with Windows 10, some Windows Media Player codecs need to be disabled to be able to play back the H.264 video files with an MPG container which MediaRecorder creates from PhenoTyper Top Unit camera. These codecs are disabled by MediaRecorder installation. De-installing MediaRecorder restores the Windows Media Player codecs. Contact Noldus Support if you want to play back the videos from PhenoTyper Top Unit camera on another computer than the one with MediaRecorder. Installation Main Topics - The steps to install MediaRecorder - Turn off automatic updates for device drivers - Install MediaRecorder and device drivers - Activate your MediaRecorder license - Upgrade to MediaRecorder 6.5 Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Connect The Usb 3 Cameras To The Pc URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-connect-the-usb-3-cameras-to-the-pc Chapter: Media Recorder Connect the USB 3 Cameras to the PC Connect the cameras to the USB 3 interface card of the MediaRecorder computer. Tip: USB 3 connectors and ports can be recognized by their blue color coding, or by a double-S in front of the USB icon. Important Note Using multiple Basler USB 3 cameras with a laptop is not supported. Configure the Basler USB 3 Camera Aim: To adjust settings in the USB 3 camera, like the video frame rate, resolution, and exposure. Note: The camera settings are stored by the camera itself, not on the PC. When you work with multiple cameras, repeat the procedure for each camera. Procedure - Make sure MediaRecorder (and EthoVision XT, when present on the computer) are not running. - Start the Basler Pylon Viewer software that comes with the USB 3 camera. Note: The Basler Pylon Viewer software is installed automatically when you install the camera drivers. - In the Devices panel, under USB, double-click the Basler camera. - Under Features, open the item Basler acA1920-155um and choose the settings you would like to change. For details, see the corresponding settings in Configure the Cameras in Set Up GigE Cameras. - Save the settings under User Set Control. See Also Supported USB cameras in Recording Devices Audio Devices Which Audio Device Should I Use? The appropriate audio device depends on your setup. Take the following rules of thumb into account: - For room settings, use one omnidirectional ceiling microphone. - For meetings around a table, use one boundary layer table microphone. - For usability research behind the computer, use a microphone close to the test participant, for example a wireless microphone or boundary layer table microphone. - For very good audio quality for more than one test participant, use a wireless microphone for each person. - Audio quality strongly depends on the room settings. An expensive audio device does not by itself guarantee good audio. If the devices are not placed correctly, or if the acoustics in the room are bad, audio quality will suffer. - Do not place the microphone cables in the vicinity of 230 V electricity cables. If you, for example, route microphone cables in electrical conduits, the electricity can interfere with the audio. - Use sound absorbing material, like curtains, to avoid echoes on audio recordings. Preamplifiers The signal from a microphone is of low voltage. This signal needs to be amplified prior to further processing, like mixing or recording. This is done with a preamplifier. The strength of the signal that is amplified this way is called line-level. When you subsequently connect the preamplifier to the sound card of your computer, select Line in when a message pops up that a new device is detected. The unamplified signal is very sensitive to noise. Therefore the preamplifier should be positioned as close to the microphone as possible. When you use a digital video device and connect the audio directly to the sound card of the computer, the sound card of the computer functions as a preamplifier. So for recordings with digital devices, you can connect the microphone directly to the computer. When a message pops up that a new device is detected, select Mic-in as input source. Balanced Cables In professional audio, a balanced line or balanced signal pair is a transmission line consisting of two conductors of the same type. Both lines have equal impedances along their lengths and equal impedances to ground and to other circuits. Both lines are twisted together and then wrapped with a third conductor (foil or braid) that acts as a shield. Common balanced cables are cables with XLR connectors. Balanced cables are the opposite of unbalanced cables. A coaxial cable is an example of an unbalanced cable. The main advantage of the use of balanced lines is good rejection of external noise. Because the signal between the microphones and preamplifier is most sensitive to noise, it is most important to use balanced lines there. Phantom Power Phantom power, often indicated with P48, is a method to supply condenser microphones with power through microphone cables. Condenser microphones give better audio quality than other types of microphones, but they are more sensitive to noise. Preamplifiers and mixers can often supply microphones with phantom power. Gain The gain of a preamplifier is the degree to which the amplifier magnifies the low-level input signal compared to its output signal. It is the ratio of the output voltage divided by the input voltage and is expressed in decibels (dB). The formula to calculate gain is 20 x Log (Voltage output / Voltage input). A gain of 6 dB doubles the voltage 2 times and a gain of 20 dB gives a 10-fold increase in the signal. Gain Trim For some amplifiers the gain can be selected in ranges. For example, a LOW gain gives a range from 18 to 38 dB. With the switch Gain trim, you can select the actual gain. High Pass Filter A high-pass filter (HPF) is a device in a preamplifier that passes high frequencies. Therefore it reduces the amplitude of frequencies lower than its cutoff frequency. It is sometimes called a low-cut filter or bass-cut filter. Ceiling Microphone Ceiling microphones are omnidirectional and are suitable for both speech and other sounds. MediaRecorder supports the following ceiling microphone: - Sennheiser MKE2-60-Gold-C (can also be used as a table microphone) The microphone needs 12–48V phantom power. Table Microphone Table microphones are acoustically optimized for picking up speech. They are designed for use on conference tables, altars, and lecterns. MediaRecorder supports the following table microphones: - Sennheiser ME35 - Sennheiser ME36 - Sennheiser MKE2-60-Gold-C (can also be used as a ceiling microphone) - Sennheiser e 912 S BK - Nikon ME-W1 The Sennheiser microphones need 12–48V phantom power. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Deactivate Your Mediarecorder License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-deactivate-your-mediarecorder-license Chapter: Media Recorder Deactivate Your MediaRecorder License Deactivate your fixed license if you reached your maximum number of activations and you want to install and use MediaRecorder on another computer. Important: If you want to uninstall MediaRecorder, first deactivate the license otherwise you will lose it. Please contact Noldus Technical Support if this happened. Deactivate Your Floating License - From the Help menu select Deactivate License. - You will get a message that your license key was successfully removed and that MediaRecorder will exit. Click OK to close the software. Deactivate Your Fixed License From the Help menu select Deactivate License and select: - Deactivate Online if the computer is connected to the internet. You will get a message that your license key was successfully removed and that MediaRecorder will exit. Click OK to close the software. - Deactivate Offline if the computer does not have an internet connection. Scan the QR code with your smartphone. Click OK to deactivate the license on the PC. You will get a message that your license key was successfully removed and that MediaRecorder will exit. Click OK to close the software. Follow the QR code link on your smartphone within 24 hours to deactivate your license on the Noldus server. You can also first deactivate your license on the Noldus server and then select the checkbox in the window on your PC to deactivate the license on your PC. If You Have a Hardware Key MediaRecorder is not sold any more with a hardware key; instead, it comes with a software activation code which makes it easier to work with the software. If you use a version earlier than 6.2, it is possible to upgrade your hardware key (see Upgrade your MediaRecorder license to continue working with your hardware key) or request a software activation key. If you wish to use an upgraded hardware key, follow the steps below: - Plug the key into a USB port on your computer. If the hardware key is correctly connected, a red light is visible inside the key. - Now start MediaRecorder. Keep the key inserted in your computer while you work with MediaRecorder. A hardware key is a very important piece of equipment, as it represents the full value of your license and cannot be replaced if lost. You can install MediaRecorder on any computer as long as it meets the System Requirements. However, to work with the program you need to insert the hardware key into one of the computer's USB ports. Important: Please make sure that you do not lose the key! You will need to pay for a new license if so. Also be careful with it, because it is sensitive and can be easily damaged. The drivers for the hardware key are installed together with MediaRecorder. It is important to install MediaRecorder with the drivers for the hardware key before you connect the license key to the computer. If you connect the hardware key first, drivers are automatically installed which may lead to incorrect functioning of the hardware key. When the hardware key is installed and connected properly, a red light glows inside it. End-User Licence Agreement Revised: 21 July 2022 IMPORTANT – READ CAREFULLY. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading or using the Software (as defined below). By checking the "accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions of this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions Terms used in this EULA but not otherwise defined shall have the meaning assigned to them below: - 1.1. Authorized Partner: the individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. - 1.2. End-User: the individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3. EULA: this End-User License Agreement. - 1.4. Indirect Losses: any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5. Network License: a licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. - 1.6. Noldus: Noldus Information Technology BV, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries listed in the document https://www.noldus.com/legal/noldus_corporate.pdf. - 1.7. Security System: a system of software protection to limit installation and use of the Software to the authorized End-Users and computers. - 1.8. Security Device: a device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. - 1.9. Software: the software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) provided to the End-User by Noldus or an Authorized Partner together with this EULA, that is not covered by third party terms and conditions and is included in the list under "Noldus software" in the Annex to the General Terms and Conditions (https://www.noldus.com/legal/noldus_gtc.pdf). Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-files Chapter: Media Recorder Sharing Video Files - Right-click the folder where the video files are going to be stored, which is by default C:\Users\Public\Documents\Noldus\MediaRecorder\Video Files and select Give access to and then Advanced Sharing Settings. - Change the sharing options for all your network profiles ('Private', 'Guest or Public' and 'Domain'): select the option Turn on file and printer sharing for all your profiles. - Under 'All Networks' select the option Turn on sharing so anyone with network access can read and write files in the Public folders. Then click Save Changes. MediaRecorder Computer This procedure is needed to make sure that the folder where MediaRecorder stores its video files can be accessed without a password by the computer with The Observer XT. The procedure differs for Windows workgroups and domains. To see whether the MediaRecorder computer is in a workgroup or a domain, open the Control Panel and choose System. The type of network is listed under Computer name, domain, and workgroup settings. Procedure for Workgroup - Follow the procedure in Share the folder where MediaRecorder stores its video files to open the Advanced sharing settings. - Under Password protected sharing, select the option Turn off password protected sharing. Important: If you do not see this option, most likely your computer is in a domain, not a workgroup. Carry out the Procedure for Domain below. Procedure for Domain - Press the Windows key + R. - Type lusrmgr.msc and press OK. - Open the Users folder and double-click Guest. - Deselect Account is disabled and click OK and close the lusrmgr window. - Press the Windows key + R. - Type gpedit.msc and press OK. - Open Computer Configuration\Windows Settings\Security Settings\Local Policies\User Rights Assignment and double-click Deny access to this computer from the network. - Click Guest and then choose Remove > OK. - Close the Local Group Policy Editor window. Map the Shared Folder with MediaRecorder Video Files Carry out this procedure on both computers. - Open File Explorer and then This PC. - Click Computer and then click the Map network drive icon. - Choose a name for the drive and browse to the shared folder. Important: Make sure you select the same drive on both computers. - Click Finish. Note: When you now start the computer with The Observer XT, you need to enter the login details for the computer with MediaRecorder. Install N-Linx Agent Aim: To install and set up the tool that starts MediaRecorder when you start an observation in The Observer XT. Important: Install N-Linx Agent on the computer with MediaRecorder. Prerequisite You installed N-Linx Server on a computer in the network. Procedure - From my.noldus.com, download N-Linx Agent Setup.exe. - In the N-Linx Agent Setup window, select MediaRecorder control in the Drivers and Tools field and click Next. - Accept the terms in the End-User License Agreement and click Install. Connect N-Linx Agent to N-Linx Server - Click the arrow in the bottom-right corner of your window to open the system tray. Then double-click the N-Linx Agent icon. - In the N-Linx Server Address field, enter the computer name of the computer with N-Linx Server. See To Find the Computer Name. You can also enter the IP address, but then the IP address of the computer with N-Linx Server must be fixed. Ask your system administrator for assistance. If MediaRecorder runs on the same computer as N-Linx Server, leave the entry localhost in the N-Linx address field. N-Linx Agent then automatically connects with N-Linx Server. Note: See To Change the Port if the default port 5672 is already in use. - If the connection with N-Linx Server is established, the text Connected appears in the lower-left corner of the N-Linx Agent window. To Find the Computer Name To find the name of the computer with N-Linx Server, open the Control Panel on that computer and choose System. To Change the Port N-Linx Agent by default uses port 5672 to communicate with N-Linx Server. If this port is in use, type the new port after a colon in the N-Linx Server Address field. Important: Select the same port in all components that communicate with N-Linx Server. Also, disable Windows Firewall for this port. Notes - N-Linx Agent is installed in the folder C:\Program Files\Noldus\N-Linx Agent 1. - If you did not install N-Linx Server yet, it will not be possible to establish a connection. - The Status of MediaRecorder in the N-Linx Agent window is Online when MediaRecorder is open and connected to N-Linx Server. Create MediaRecorder Settings Aim: To connect MediaRecorder to N-Linx Server and select the video file folder. Prerequisites - If MediaRecorder, The Observer XT, and N-Linx Server are not all installed on the same computer, you created exceptions for the N-Linx port in Windows Firewall. See Create Exceptions for N-Linx Port in Windows Firewall. - You installed N-Linx Server on a computer in the network. - N-Linx Agent is installed on the computer with MediaRecorder and connected to N-Linx Server. See Install N-Linx Agent. Procedure - In MediaRecorder, choose File > Preferences > N-Linx settings. - Select Allow communication with N-Linx Server. - In the N-Linx Server address field, leave the default value Localhost if MediaRecorder runs on the same computer as N-Linx Server. If the programs run on different computers, enter the name of the computer with N-Linx Server. See also To Find the Computer Name. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. - When the connection with N-Linx Server is established, the Status will be Connected. Click OK. - If MediaRecorder and The Observer XT run on different computers, select the mapped drive as location to store the video files and not the original folder. The original folder is locally on the computer with MediaRecorder and cannot be accessed by The Observer XT. Example: You mapped the default folder C:\Users\Public Documents\Noldus\MediaRecorder\Video files as X:\. Set the default video file location where MediaRecorder stores its video files to X:\ and not to the original folder. Create The Observer XT Settings Aim: To enable communication between The Observer XT and N-Linx Server. Prerequisites - You installed N-Linx Server on a computer in the network. - If MediaRecorder and The Observer XT, or N-Linx Server run on different computers, you created exceptions for the port that N-Linx uses in Windows Firewall. See Create Exceptions for N-Linx Port in Windows Firewall. - N-Linx Agent is installed on the computer with MediaRecorder and connected to N-Linx Server. See Install N-Linx Agent. - MediaRecorder is open. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Install And Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-install-and-setup Chapter: Media Recorder Install and Setup To convert the output of analog cameras into a digital format, a video capture card is needed. If you bought a complete solution from Noldus IT, the video capture card is present in the computer. If you bought your cameras, video capture card and MediaRecorder separately, you must do the installation and setup yourself. See Set up Analog Cameras Supported Analog Cameras In theory, MediaRecorder works with output of every analog camera that is used with the Euresys Picolo Alert PCIe Video Capture Board. We specifically tested MediaRecorder with output of the following cameras with the Euresys Picolo Alert PCIe Video Capture Board with Multicam driver 6.15.13573: - Ikegami B/W ICD-49 PAL - Panasonic WV-CP504 NTSC - Ikegami Analog PAL/CCIR - Ikegami Analog NTSC/EIA Maximum Supported Number of Cameras Euresys Picolo Alert PCIe Video Capture Board - Four cameras or PhenoTyper Top Units. Tested Setups with EthoVision XT The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) color space, (4) number of devices and (5) recording time (hours). Tests were done on a Dell 3640 PC. Device Resolution Frame Rate Color Space No of Devices Recording Time Ikegami B/W ICD-49 PAL - Analog CCIR, Euresys Picolo Alert PCIe 768 x 576 YUY2, RGB32 0.5 Panasonic WV-CP504 NTSC - Analog EIA, Euresys Picolo Alert PCIe 640 x 480 YUY2 0.5 Analog PAL/CCIR 768 x 576 RGB24 Analog NTSC/EIA 640 x 480 RGB24 Important: The file size of an 18, 24 and 60 hours recording is very large. Note: CCIR is the monochrome version of PAL and EIA is the monochrome version of NTSC. Cable Length In theory, a length of 250 m should be possible, however we did not test that. We know that a length of 100 m can be used without problems. PAL or NTSC MediaRecorder automatically identifies the analog cameras as PAL / CCIR (=monochrome PAL), or NTSC / EIA (=monochrome NTSC). It selects the correct frame rate and resolution automatically. When Do I Need an IP Camera? IP cameras are connected directly to a network. IP cameras are especially useful to film for example at a remote location and receive the video files through an Ethernet network on your computer. Network Requirements To use MediaRecorder with IP cameras, the following network requirements apply: - An Intel Pro/1000 CT or Intel Pro/1000 PT (1 Gb) network adapter is installed in the computer with MediaRecorder. - The cables are suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. See https://en.wikipedia.org/wiki/Category_5_cable - We recommend to use a dedicated network. Install and Setup If you bought a complete solution from Noldus IT, the network adapter is present in the computer, the IP cameras are set up and the MediaRecorder settings are made. If you bought your cameras and MediaRecorder separately, you must do the installation and setup yourself. See Set up IP Cameras Supported IP Cameras - Axis M5525 - Axis M1075 - Axis M1375 Cable Length In theory, for IP devices, a cable length of 150 m should be possible. However, it has not been tested by us. We know that a setup with a cable of 1 m and an extension cable of 50 m with a switch between the cables works well with MediaRecorder. ONVIF Profile S ONVIF is a communication standard for network devices. ONVIF Profile S applies video and audio streaming and PTZ control. Most IP cameras nowadays support ONVIF Profile S. For cameras that do so, pan, tilt, and zoom control can be done with MediaRecorder and audio from the camera can be recorded. For cameras that do not support ONVIF, pan, tilt, and zoom control must be done with a browser and audio must be recorded with a microphone connected to the sound card of the computer. Power over Ethernet IP cameras can be connected to a PoE (Power over Ethernet) or PoE+ switch to supply them with power. This way no extra power cables are needed. Each device is connected to one channel on the switch. A PoE switch can deliver up to 15 Watt per channel. A PoE+ switch has a higher capacity per channel (up to 30 Watt per channel). Make sure that the maximum total capacity of the switch is high enough for all cameras together. Cameras may also be powered using a 2 or 4-port Network Interface Card (NIC). Example: You connect four cameras that need 30 Watt each to a PoE+ switch. This PoE+ switch must deliver at least 4 x 30 = 120 Watt. - Axis M5525 - requires a regular PoE switch. - Axis M5054 - requires a regular PoE switch. - Axis P1375 - requires a regular PoE switch. The PoE or PoE+ switch must allow a speed of at least 1 Gb per second. USB Cameras and Devices USB 2 and 3 Ports The supported USB devices are all USB 3 devices and need to be connected to a USB 3 port. You recognize USB 3 ports by a double-S in front of the USB icon. Some USB 3 ports and connectors have blue labeling. The Dell Precision T3640 desktop PC sold by Noldus IT has both USB 2 and USB 3 ports. The Dell Precision 3551 mobile workstation only has USB 3 ports. USB Hub Do not connect your cameras to a USB hub. If you run short of USB connections, connect your license key, keyboard or mouse to a USB hub and connect your USB device directly to the USB port on your computer. Cable Length USB devices can be connected to the computer without an amplifier with a cable of 5 m. For every subsequent 5 m, an amplifier must be used each. In theory, when using a standard resolution, the cables could be extended this way to 30 m. However we know that not all devices support this. When Do I Need a USB Camera? USB cameras are very easy to use. However, the settings may be limited; for example, many USB cameras have fixed zoom. A USB camera may be perfectly suitable for a usability study in which you film a person sitting behind a computer. A USB camera also works very well to create video files for FaceReader. On the other hand, when you need to create a video file of a person further away from your camera, a USB camera may be less suitable. For videos with accurate time information, needed for EthoVision XT, you need a high-quality USB camera. Supported USB Cameras - Basler acA1920-155um - Basler acA2040-90uc Other USB cameras may also work. However, it could be that you have to change the Color Space to MJPG. See Show Frame Rate, Resolution and Format. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Insufficient Disc Space URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-insufficient-disc-space Chapter: Media Recorder Insufficient Disc Space If your output folder is on the C: drive it is possible that you will have insufficient file space. Most computers are configured with more file space on the D: drive, so select your output folder on the D: drive. External Programs When you sent commands to the MediaRecorder external programs like EthoVision XT or The Observer XT, there is a small delay in starting the actual recording with The MediaRecorder. This results in some missing frames at the start of the video file. Allow enough time at the start of recording to compensate for this delay. When the command Start Recording is given before MediaRecorder is open and has loaded the cameras, recording does not start. To measure this delay, make for example a video of a digital clock and compare the time the command "Start Recording" is given with the time at the first frame of the video. Problems Loading MediaRecorder MediaRecorder opens using the configuration file Current settings.mrs. When problems occur with these settings, open MediaRecorder with the default settings and recreate camera settings. To do so: - Delete the file Current settings.mrs from the following folder: C:\Users\Public\Documents\Noldus\MediaRecorder - Re-open MediaRecorder. - Re-select the cameras. A new file Current Settings.mrs is created. VideoInspector This free tool gives basic information about the video files you are trying to play (such as which codecs they were made with) and reports which codecs are installed on your computer. It is reasonably easy to use. It does not report details such as the I-frame rate. http://www.kcsoftwares.com/?vtb GSpot Although GSpot has not been maintained since 2007, it is a powerful tool to get information about both your video file and your computer system. GSpot is a free tool. It is less easy to use than VideoInspector. In addition to providing detailed information about the video file you have opened, GSpot can be used to adjust how Windows uses the codecs installed. This is an advanced function and you should only use it if you understand what you are doing, and carefully write down the changes you make. If several codecs are installed which can be used to play one format, Windows assigns a 'merit' to each codec to determine its preference. You can use GSpot to change the merit of each codec and in that way select which one is used by Windows (and so by other software). This is a way in which you can solve problems of codecs conflicting with each other, e.g. a piece of software such as The Observer XT works best with a particular codec, but another installation has set the merit of an alternative codec higher. http://gspot.headbands.com MediaInfo MediaInfo provides detailed information about media files. It has less information than GSpot, but at the publication date of this manual, it was maintained. http://www.mediainfo.sourceforge.net/en Windows System Information This can be obtained in Windows with System and Security > System > Advanced System Settings, Dxdiag.exe, and the Device Manager (in the Control Panel). For full system information, SIW is a useful tool. http://www.gtopala.com Help Menu MediaRecorder's Help menu contains the following options: - Help Topics – Opens the MediaRecorder Help. You can search and find help topics. - Noldus Online – If your computer is connected to the Internet, you can choose this option to go to the MediaRecorder home page on the Noldus website or to the MyNoldus portal. On the MyNoldus portal you can download the latest version of the software and documentation, submit support cases and view your account information. If you encounter a problem with MediaRecorder, you can inform Noldus IT with the Report an Issue option. - Upgrade – If you have purchased an upgrade of MediaRecorder, choose this option to type the new Upgrade Key number that you have received from Noldus. - About MediaRecorder – Choose this option to see details of exactly which version of MediaRecorder you are using. Click User Info to see the registered user and license number of your software. Technical Support For questions about MediaRecorder or any other Noldus product, contact the Support department by opening the Help menu in MediaRecorder, select Noldus Online and subsequently Get Support. The help desk may ask for the MediaRecorder log file. You can find this file in the folder C:\Users\\AppData\Local\Temp. Record at a Predefined Time Aim To schedule video recording. This is especially useful when you want to start recording in the middle of the night, or you do not want to disturb the test subjects by handling the video software. Important: The procedure below is an example of the possibilities of Windows Task Scheduler, which is a default program in Windows 10. Since Windows Task Scheduler is a Microsoft program, Noldus IT offers no support for this feature. Procedure - Type Task Scheduler in the Apps window. - Choose Action > Create Task. - In the General tab, type a name in the Name field, for example MediaRecorder with Webcam. - Optionally enter other settings in this tab and open the Triggers tab. - Click the button New. - Select On a schedule from the list next to Begin the task. - Enter the start time of the command in the Start field and choose whether you want to send the command once, daily, weekly or monthly. - Optionally enter Advanced Settings and click OK. - Click the Actions tab and choose New. - Choose Start a program next to Action. - Browse to MRCmd.exe. - Enter the command in the Add arguments (optional) field. For example, to start MediaRecorder and load the configuration file for your webcam, type: /E /C=Configuration_webcam.mrs. If the configuration file is not located in the folder C:\Users\Public\Public documents\Noldus\MediaRecorder, you must type the full path. If the file name or path contains spaces, you must use quotation marks at both ends. - Optionally select or change any settings on the other tabs. - Similarly, you can create tasks to start and stop recording at a predefined time with the commands /R and /S and to close MediaRecorder with the command /X. Create a task for each command. Notes - Important: Allow enough time between the commands. If a command is sent before the previous one is carried out, the second command is not carried out. For example, if the command Start Recording is sent before MediaRecorder is completely open, recording does not start. - By default, the tasks are stored in the folder Task Scheduler Library. To edit or delete a task, click this folder in the tree on the left side and select the task in the Task Scheduler Library window. In the Actions pane, click Properties or Delete. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Ip Address URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-ip-address Chapter: Media Recorder IP Address - In the IPUtility tool, click the Home Page button. The camera now opens in a browser. Alternatively, type the IP address in the address field of, for example, Internet Explorer. - The first time you open the camera in a browser, you must set a password. If you obtained cameras from Noldus IT, this password is Noldus. The user name root cannot be changed. Do not use the characters @, space, or colon (:) for the password. These characters cannot be used in MediaRecorder. - As soon as you set the password, you must log in to the camera with the password you just set. Power Line Frequency The first time you log in to the camera, you must select a power line frequency. Look up the correct power line frequency of your country on the internet. Notes - IMPORTANT Close the browser before you start recording. Leaving it open may cause recording problems in MediaRecorder. - If you do not get a view in Internet Explorer, click the Settings wheel in the upper-right corner of your window and choose Compatibility View Settings. Enter the IP address of your camera and click Add. Other browsers may have a comparable setting. Create Camera Settings Aim To configure the camera for optimal recording with MediaRecorder. Prerequisites - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP Cameras in Recording Devices. - You installed the Ethernet card. See Install the Ethernet Card. - You gave the card a fixed IP address. See Set Ethernet Card IP Address. - You connected all cameras. - You gave the cameras an IP address. See Set Camera IP Address. - You gave the camera a password and selected the correct power line frequency. See Set Camera Password and Select Power Line Frequency. Procedure Carry out the following steps: - Access camera settings - Create ONVIF user name and password - Disable replay attack protection - Switch on IR cut filter Note: The procedure below describes camera firmware version 7.20.1. For other firmware versions, search for comparable settings. Access Camera Settings - Open the camera in a browser by clicking the Home Page button in the IPUtility tool or typing the IP address in the address field of an internet browser. Then enter the password. - Click the Settings button in the bottom-right corner of your window. Create ONVIF User Name and Password Aim To configure the camera so that pan, tilt, zoom, and audio recording is possible. Procedure - Open the camera settings. See Access Camera Settings. - Open the System tab and click ONVIF. - Click Add and enter the same user name and password as set in Set Camera Password and Select Power Line Frequency. Do not use the characters @, space, or colon (:) for the user name or password. These characters cannot be used in MediaRecorder. - Select Administrator as User Group and click OK. Notes - If the camera does not support ONVIF, pan, tilt, and zoom must be done with a browser and audio of the camera cannot be recorded. All IP cameras supported with MediaRecorder support ONVIF. - IMPORTANT Always close the browser before you start recording with MediaRecorder. Disable Replay Attack Protection Aim To prevent that connection to the camera fails if the time of the MediaRecorder computer differs from the time in the camera. Background Replay attack protection is a camera security setting. Relevant for video recording with MediaRecorder is that replay attack protection causes the camera connection to fail if the timestamps of MediaRecorder and the camera are not exactly the same. Replay attack protection is necessary for security cameras, but not for IP cameras in a dedicated network. Procedure - Open the camera settings. See Access Camera Settings. - Open the System tab and click Plain Config. - From the list at the bottom, select WebService and click Select Group. - Under WebService UsernameToken, make sure the checkbox Enable Replay Attack Protection is not selected. Note If you do not want to disable this option, make sure that the clock times of the computer and camera are exactly the same. Switch on IR Cut Filter Aim To make sure the camera does not switch to black and white at low light levels. Background The IR cut filter removes infrared light during daylight. With the default camera settings, the IR cut filter is switched off at low light intensities. The camera then records in near-infrared, which gives a black and white camera image. If you do not want this, set the IR cut filter to On instead of Auto, so that it stays on, independent of the light level. Procedure - Open the camera settings. See Access Camera Settings. - Open the Image tab. - Check if there is an option IR Cut Filter. If so, set it to On. Note Not all IP cameras supported with MediaRecorder have an IR cut filter. Create Audio Settings Aim To optimize the recording volume. Prerequisites - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP Cameras in Recording Devices. - You followed the procedure in Ethernet Card Setup. - You connected all cameras. - You gave the cameras an IP address. See Set Camera IP Address. - You gave the camera a password and selected the correct power line frequency. See Set Camera Password and Select Power Line Frequency. - You followed the procedure in Create Camera Settings. Procedure - Open the camera settings. See Access Camera Settings. - Open the Audio tab. - Adjust the Gain slider and check in the Input section that the green field in the Level field is maximal with normal speech. Note You cannot record the audio of non-ONVIF devices in MediaRecorder. Optionally record audio from a separate microphone that is connected to the microphone input of the computer with MediaRecorder. The Axis cameras supported with MediaRecorder support ONVIF. Select ONVIF Cameras in MediaRecorder Aim To select a camera that supports ONVIF Profile S in MediaRecorder. If your device does not support ONVIF, see Select Devices That Do Not Support ONVIF in MediaRecorder instead. Prerequisites - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP Cameras in Recording Devices. - You followed the procedure in Ethernet Card Setup. - You followed the procedure in Camera Setup. - You installed MediaRecorder. See Installation. - You connected all cameras to the computer with MediaRecorder. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Mute Audio In Preview URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-mute-audio-in-preview Chapter: Media Recorder Mute Audio in Preview Aim To mute audio sources in MediaRecorder. The muted audio is recorded normally in the video files. Prerequisite You selected microphones in the Video Settings window. See Select an Audio Device. Procedure Select the audio sources you wish to mute in the Mute column. Change Video Order in Preview Aim To change the order of the video cameras, for example to change the position of the images in a Picture in Picture recording. Prerequisite You selected the recording devices in the Video Settings window. See Select a Video Device. Procedure - Drag and drop rows in the table with video devices or drag and drop the preview images. - Click the Refresh button. See Refresh the Preview. Note You cannot drag and drop Picture in Picture, or Picture by Picture preview images. Drag and drop the rows in the table with video devices instead. Show Frame Rate, Resolution and Format Aim To display hidden rows in the table with video devices. Procedure Right-click one of the column headers and select the preferred options. Notes - The Format column shows the color space of the video file. The column is hidden by default, because the optimal color space is selected by default. See the following page for more information on color space: http://www.noldus.com/knowledge-base/what-color-space-format-used-media-recorder. - TIP Follow the same procedure to show or hide the Frame Rate, Resolution, and Format columns in the Video Settings window. Refresh the Preview Aim To display video images in the preview after a temporary connection loss or if you connected a camera after you opened MediaRecorder. Procedure Click the Refresh button. See Which Camera Aim To see which image comes from which camera. Prerequisite You selected the recording devices in the Video Settings window. See Select a Video Device. Procedure Press the Identify button. Result — Numbers are superimposed on the camera images. These correspond to the row numbers in the table. Show or Hide Recording Properties Aim To show or hide the table under the preview of the camera images, so that the space for the preview images is increased. Procedure Click Recording Properties. Result The size of preview images is increased. Save the Camera Settings Aim To make a configuration file that can be used to open the correct cameras, microphones and video settings. Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You selected camera, microphones and video output in the Video Settings window. See Select a Video Device, Select an Audio Device and Video File Options for the procedures. Background The settings you create for the different cameras are automatically saved when you close MediaRecorder. They are saved to the file Current settings.mrs that is present in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. These settings are used when you restart MediaRecorder. But you can also save your own settings, or save different settings for different setups, for example, a webcam for a test participant's face in a usability test room and three overview IP cameras in an observation room. This way you do not have to select all cameras manually each time. Procedure - Choose File > Save Configuration As. - Give the configuration a name and click Save. Notes - To open a saved configuration, choose File > Open Configuration. - IMPORTANT Never shut down the computer by pressing the power button or cutting off the electricity. Your settings may become lost, even after you saved the settings. Always use the Windows shut down feature to close your computer. - To go back to the default configuration, choose File > Open Configuration. Browse to the file Default Settings.mrs. This file is read-only. When Noldus installed MediaRecorder for you, the file is in the folder D:\Noldus\MediaRecorder. When you installed MediaRecorder yourself, the file is in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder, or the folder you selected when you installed MediaRecorder. - If you encounter problems with starting MediaRecorder, for example because you created wrong settings which are loaded when you start MediaRecorder, delete the file Current settings.mrs. MediaRecorder now starts with the default settings and you can create new settings. Pan, Tilt, Zoom Control with IP Cameras Aim To change the camera view in MediaRecorder. Prerequisites - Your IP camera supports ONVIF Profile S. - Your IP camera can Pan, Tilt and Zoom. - The camera is selected in MediaRecorder. See Select a Video Device. Procedure Hover with your mouse over the camera image. Two buttons appear in the top-right corner of your window. - Enable or disable PTZ control. - Open the PTZ preset menu. PTZ Control - Click the Enable PTZ button in the image you want to adjust. A four-arrow cross appears in the middle of the image and your mouse pointer becomes a small point. - Click the camera image and keep your left mouse button pressed to control the camera. The cross now becomes connected to the point and the camera image moves in the direction of the point. The further away from the center cross you click, the faster the camera moves. - Zoom in and out with your mouse wheel. Save Camera Position If you are satisfied with the position of your camera, you can save this as a PTZ preset. Hover over the camera image and click the button that opens the PTZ menu. The following buttons now appear. The Save As buttons appear when you hover over the Return to PTZ Preset buttons. - Save as first PTZ preset. - Save as second PTZ preset. - Return to first PTZ preset. - Return to second PTZ preset. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-notes Chapter: Media Recorder Notes The procedures apply to Axis IP cameras. If you bought cameras from a different brand, look for comparable settings in the camera manual. We recommend to use Axis IP cameras since these were tested with MediaRecorder. The Axis cameras sold by Noldus IT support ONVIF. Ethernet Card Setup Aim To insert the 1 Gb Ethernet card into your computer and to configure it to work with MediaRecorder. Prerequisites - You have IP or GigE cameras. - You have an Intel PRO/1000 GT or Intel Pro/1000 PT Ethernet card. - You purchased the computer with MediaRecorder yourself, or you bought the cameras after you received the computer. - If you bought a complete system from Noldus IT, the card has been installed and set up. You can skip this topic. Procedure Carry out the following steps: - Install the Ethernet card - Set Ethernet card IP address Install the Ethernet Card Aim To place the Ethernet card into the computer with MediaRecorder. Prerequisites - You have IP or GigE cameras. - You have an Intel PRO/1000 GT or Intel Pro/1000 PT Ethernet card. - You purchased the computer with MediaRecorder yourself, or you bought the cameras after you received the computer. Procedure - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. See PCIe slot properties in Set up analog cameras for details on the slots in a Dell computer. - Unpack the Ethernet card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. IMPORTANT When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet, and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Fix the card to the chassis and re-fit the computer's cover. Set Ethernet Card IP Address Aim To set the IP address of the Ethernet card to the same range as the cameras and the computer. Prerequisites - You have IP or GigE cameras. - You purchased the computer with MediaRecorder yourself, or you bought the cameras after you received the computer. - You installed the Ethernet card into the computer. See Install the Ethernet Card. Procedure - Open the Control Panel and select Network and Sharing Center. - Click Change adapter settings on the left side of your window. - Right-click Local Area Connection and click Properties. If your computer has more than one Local Area Connection, choose the one used for the cameras. To check which one this is, remove the cable from this IP port on your computer. The LAN connection that has the status Not connected is the correct one. - Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. - Click Use the following IP address and enter the IP address and Subnet mask supplied by your system administrator. Leave the other fields empty. Also select the checkbox Validate settings upon exit. When done, click OK and then Close. - A Windows Network Diagnostics window appears. Click Close when the validation is finished. Then close all windows. PoE Switch Connection Prerequisite You have followed the entire procedure in Ethernet Card Setup. Procedure The procedure applies to a Cisco SG 100D 8 port Gigabit PoE-switch, which is supported with MediaRecorder. Using cross-network cables (cat-5e or newer), connect the Ethernet card on the PC to one of the four right ports of the PoE-switch. - Connect the camera to one of the four left ports of the PoE-switch. Do not use any of the four right ports for this purpose, since they do not supply your cameras with power. - Power up the PoE-switch. Notes The Power over Ethernet (PoE) switch is a device that receives and sends data (in this case, video data from the camera) and passes power along on twisted-pair Ethernet cabling. If you use multiple IP cameras, connect them to separate ports on the PoE-switch. Make sure the capacity of the switch is high enough for the cameras. See Power over Ethernet in Recording devices. Camera Setup Aim To configure the cameras for use with MediaRecorder. Prerequisites - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You followed the procedure in Ethernet Card Setup. - You connected all cameras. Procedure You must carry out the following steps for each camera: - Set camera IP address - Set camera password and select power line frequency - Create camera settings - Create audio settings Set Camera IP Address Aim To set the IP address of the camera to the same range as the Ethernet card and the computer. Prerequisites - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You installed the Ethernet card. See Install the Ethernet Card. - You gave the card a fixed IP address. See Set Ethernet Card IP Address. - You connected all cameras. Procedure - Insert the MediaRecorder installation USB stick into your computer and copy the file IPUtility.exe from the folder Drivers and Tools\Software\Axis Tools to your computer. Do not copy it to your desktop, as the tool will then not work correctly. - Run IPUtility.exe. A window opens in which all the connected devices are listed. - Right-click the device and select Assign IP address. - Enter the IP address and choose Assign. - According to the message that appears, disconnect and reconnect the camera and click Assign. Wait until the IP address is set. - Right-click the camera and select Test IP address. When the details were entered correctly, a message appears that the camera is accessible. - Repeat steps 3 to 6 for all cameras. Make sure you use different IP addresses for all cameras, the computer, and other network devices in the network. Set Camera Password and Power Line Frequency Aim To give the camera a password, which is compulsory, and to select the power line frequency of your country. Prerequisites - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP cameras in Recording devices. - You followed the procedure in Ethernet Card Setup. - You connected all cameras. - You gave the cameras an IP address. See Set Camera IP Address. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Picture By Picture Resolution URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-picture-by-picture-resolution Chapter: Media Recorder Picture by Picture Resolution The highest allowed resolution of a recorded video is 1920 x 1280. The resolution of a Picture by Picture video is a sum of the separate videos. However, if that exceeds a width of 1920 pixels or a height of 1280 pixels, the video resolution is adjusted proportionally. This requires processor capacity and decreases the quality of the output video. It is better to choose a lower resolution of the individual videos, so that the total resolution does not exceed 1920 x 1280. The resolution of the Picture by Picture video is determined in the following way: - Example 1 — The width of the PbP video is the sum of the width of the separate videos. The height of the PbP video is the maximum height of the separate videos. - Example 2 — The total resolution is calculated in the same way as in Example 1. The width of the resulting video exceeds the maximum of 1920 pixels. Therefore both the width and height are reduced proportionally, resulting in a width of 1920 pixels. - Example 3 — The total width is the sum of the width of Video 1 and 2. The height of the resulting video is the maximum height of Video 1 and 2 plus the height of Video 3. Both the width and height of the resulting video will exceed the maximum of 1920 x 1280. Therefore both the width and height are reduced proportionally, resulting in a width of 1920 pixels. The height is now smaller than the maximum of 1280 pixels. If the height was higher than 1280, the width and height would be reduced further, resulting in a height of 1280 pixels. How to Record Videos for The Observer XT You can create videos for use in The Observer XT in two ways. You can either first create videos in MediaRecorder and then make your observations offline using The Observer XT, or you can control the recording process with commands from The Observer XT while making a live observation. Offline Observations Using Prerecorded Video Making offline observations in The Observer XT means carrying out an observation using a prerecorded video. The video files created by MediaRecorder can be used to observe offline in The Observer XT. No special settings are needed to use files from MediaRecorder in The Observer XT. Observe Live and Control MediaRecorder You can score live in The Observer XT while simultaneously recording a video using MediaRecorder. You can use The Observer XT to control MediaRecorder while making an observation. This way you can achieve the following: - When you create an observation in The Observer XT, MediaRecorder opens and the correct configuration file is loaded. - When you start an observation in The Observer XT, video recording with MediaRecorder starts. - When you stop an observation in The Observer XT, video recording with MediaRecorder stops. - The recorded videos are automatically linked to the observation in The Observer XT and synchronized with the events. MediaRecorder with The Observer XT Aim To achieve the following: - When you create a new observation, MediaRecorder starts and loads a configuration. - When you start an observation, MediaRecorder starts recording. - When you stop an observation, MediaRecorder stops recording. - The recorded videos are automatically linked to the observation and synchronized with the events. Background The communication between MediaRecorder and The Observer XT makes use of the Noldus network communication protocol N-Linx. For details on N-Linx, see the Reference Manual - N-Linx. You can find this manual on The Observer XT installation USB stick. You can also download it from the download section of the Noldus website. Prerequisites - N-Linx Server is installed on a computer in the network. - You have The Observer XT 14.1 or higher. Procedure - If MediaRecorder, The Observer XT and N-Linx Server are not all installed on the same computer, make sure that traffic through the N-Linx port is not blocked by Windows Firewall. See Create Exceptions for N-Linx Port in Windows Firewall. - If MediaRecorder and The Observer XT run on different computers, make sure that The Observer XT can access the MediaRecorder videos. See Make Sure The Observer XT Can Access the MediaRecorder Video Files. - Install N-Linx Agent on the computer with MediaRecorder. See Install N-Linx Agent. - Create MediaRecorder settings. - Create The Observer XT settings. - Carry out an observation in The Observer XT. Windows Firewall (2-Computer Setup) Aim To make sure communication between MediaRecorder, The Observer XT and N-Linx Server is not blocked by Windows Firewall. You need to allow inbound and outbound traffic through port 5672 in Windows Firewall on all computers with MediaRecorder, The Observer XT, and N-Linx Server. Prerequisites - MediaRecorder, The Observer XT and N-Linx Server do not all run on the same computer. If they do, skip this topic. - The computers are in the same network. Procedure - Open the Control Panel and select Windows Firewall. - On the left side of the window, click Advanced Settings. - In the left pane, click Inbound Rules and click New Rule in the Actions pane on the right. - In the New Inbound Rule Wizard window that opens, select Port and click Next. - Select TCP and enter 5672 in the Specific local ports field and click Next. - Click Allow the connection and click Next. - Select to which network the rule applies and click Next. - Give the rule a name, for example N-Linx connection, and click Finish. - Check in the Inbound Rules window that this rule is set to Enabled. - In the left pane, click Outbound Rules and click New Rule in the Actions pane on the right. - Repeat steps 4 to 9 for the outbound rule. - Close all Control Panel windows. Accessing the MediaRecorder Video Files (2-Computer Setup) Aim To make sure The Observer XT can access the videos recorded by MediaRecorder. The videos are not copied to The Observer XT. The Observer XT creates a link to the MediaRecorder videos. Procedure - Share the folder where MediaRecorder stores its video files. - Switch off password protected sharing on the MediaRecorder computer. - Map the shared folder with MediaRecorder video files. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Prerequisites URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-prerequisites Chapter: Media Recorder Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You opened the Video Settings window. To do so, choose File > Video Settings, or click Video Settings in the main window. Timer Format Select the options from the lists. The recording timer is present in the lower-left corner of the main window. Maximum Recording Time Select the checkbox and enter the maximum recording time. The maximum is 99:99:59 (hr: min: sec). However, see your camera type in the topic Recording Devices for the supported maximum recording time. Output Settings Output Quality - Videos can be recorded in various qualities depending on the use. Videos with a higher compression rate are usually smaller in size, but they take more processing power to create and play, and their quality may be worse compared to those with lower compression rates. If hardware encoding is used to decrease the CPU usage and redirect load to the video card (GPU), it may result in a larger video file. There are four presets defined, in separate XML files which you can find in C:\ProgramData\Noldus\MediaRecorder\6\EncoderSettings. It is not advised to modify the contents of these files, as they are optimized for the different use cases. For normal use, the default output quality should be used. For EthoVision, DanioVision and the Remote Photo Plethysmography (RPPG) module of FaceReader, special settings are defined. The special setting for EthoVision is only useful if you record the outputs of four cameras simultaneously. With the default settings, two cameras are recorded on CPU and two on the video card (GPU). This results in differences in file size. By selecting EthoVision as the output quality, all four cameras will be recorded using CPU power. Output Mode - If you have selected more than one video source, the following options are available. - Separate Videos — One video file for each camera. - Picture by Picture — One video file with the images from each camera next or above each other. - Picture in Picture — One video file with a large image of the first camera with the images from the other cameras embedded in it. If you select Picture in Picture the following options become available: - PiP Position — The position of the embedded images. - PiP Size — The size of the embedded images. The percentage is based on the width of the first camera image. The aspect ratios of the embedded camera images are maintained. - PiP Margin — The margin of the embedded images. When the percentage is zero, the embedded images are positioned directly on the edge of the main image. The percentage is based on the width of the first camera image. Notes Picture in Picture and Picture by Picture Resolution If possible, choose the same frame rate for all the videos. If you choose different frame rates the videos with the lowest frame rates may flicker and may not be suitable for use in The Observer XT, EthoVision XT, or FaceReader. Picture by Picture Resolution of Input Videos The resolution of the resulting video is a sum of the separate videos, with a maximum of 1920 x 1280. If the resulting video exceeds a width of 1920 pixels or a height of 1280 pixels, the video resolution is adjusted proportionally. This requires processor capacity and decreases the quality of the output video. It is better to choose a lower resolution of the individual videos, so that the total resolution does not exceed 1920 x 1280. See Picture by Picture Resolution for how the resolution of the resulting video is calculated. Picture in Picture with Portrait Format Please note that if you have multiple videos in portrait format, they may overlap when you use Picture in Picture. Change the Video File Location Aim: To save the videos in another location than the default one. The default location where MediaRecorder stores its video files is: - D:\Noldus\MediaRecorder\Video Files — If Noldus IT installed your system. - C:\Users\Public\Public Documents\Noldus\MediaRecorder\Video Files — In all other cases. It is recommended to set this folder to be located on a separate, fast, large capacity drive. Prerequisite You must be able to write in the selected folder and there must be enough file space available (at least 600 MB per video per hour). Procedure Click this button and browse to the new location. Tip: Click this button to open the folder with video files in Windows Explorer and play recorded videos. Set Video File Base Name Aim: To select a word or phrase to start the video file name with. The video file name consists of the File base name followed by: - The video input name. - The date and the time the videos were recorded. - The number of the video camera. Example: The File base name is Video, you changed the name of Video 2 to Webcam in the Video Settings window (File > Video Settings), the date is 11 May 2016, the time 10:54:43 and you create 2 videos simultaneously. The name of the second video will then be: Video Webcam 5_11_2016 10_54_43 AM 2.mp4 Procedure Enter a name in the File base name field. Note The date and time depend on your computer's regional settings. To change these, open the Control Panel and then Region and Language. Select your preferences in one of the tabs. Select or Deselect Videos for Recording Aim: To choose from which video sources to record video files. Prerequisite You selected the recording devices in the Video Settings window. See Select a Video Device. Procedure Select or deselect video sources for recording in the Use column. Record Your Videos Aim: To create video files from the video stream of the connected recording devices. Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You selected the cameras and, optionally, microphones and specified the output of the video files in the Video Settings window (File > Video Settings). Procedure - When you have selected all settings in the Video Settings window, click OK to return to the Main window. You will see a preview of the cameras. - Optionally, adjust options like the video file location, the video file base name or the order of the video files. See Options. - Press the Start Recording button. - A pop-up window will appear, informing you about Noldus's Data Transparency Policy. Read it carefully before clicking the I Will Inform the Participants button. You can also check the box Don't Show Me Again to prevent further occurrence. - The button changes into the Stop Recording button and the Recording timer starts running. - Press the button again to stop recording. Recording stops automatically when you have specified a Maximum Recording Time. Note If you have IP cameras, see Pan, Tilt, Zoom Control with IP Cameras for how to change the camera view before or during recording. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-procedure-xhm Chapter: Media Recorder Procedure - In EthoVision XT choose Setup > Experiment Settings. - Choose From Video File as your Video Source. You find more information on how to make Experiment Settings in Set up an Experiment in the EthoVision XT Help. - Choose Setup > Arena Settings, or click the desired Arena Settings in the Experiment Explorer. - Browse to your video file and grab a background image for your arena. See Arena Settings in the EthoVision XT Help for information on how to do this, and for more information on how to make Arena Settings. - Click the Adjust Aspect Ratio button. - In the Adjust Aspect Ratio window choose Noldus Recorder and click the arrow to open the list. Choose: - Euresys PICOLO U4 H.264 – NTSC — For analog NTSC cameras. NTSC cameras are found in North and Central America, together with parts of Asia. - Euresys PICOLO U4 H.264 – PAL — For analog PAL cameras. PAL cameras are found in Europe and the rest of the world, except for North and Central America, together with parts of Asia. The other options do not apply for video files created with MediaRecorder. Notes For the supported digital cameras, the default option Diligent controlled by EthoVision or video file with aspect ratio is correct. For not supported digital cameras you may need to adjust the aspect ratio. See the section Adjust the video aspect ratio in Arena Settings in the EthoVision XT Help for details. MediaRecorder with FaceReader Offline video analysis in FaceReader means analyzing prerecorded videos. The videos created by MediaRecorder can be used for offline video analysis in FaceReader 4 or higher. No special settings are needed to use files from MediaRecorder in FaceReader. However, if you record videos to use with the Remote Photo Plethysmography (RPPG) module in FaceReader we advise to use FaceReader-RPPG as the Output Quality setting. With this setting the videos will only be slightly compressed. The file size of the resulting videos is huge, about 260 Mb/minute. For more information see Output Settings. You cannot simultaneously analyze live video signals in FaceReader and create video files in MediaRecorder. If you want to analyze and record videos simultaneously, record the videos in FaceReader. Prevent Black Frames at the Start of Your Videos To make sure that MediaRecorder waits for an I-frame before it starts recording, you can edit the VsSettings file that comes with MediaRecorder. If you do not edit this file, your videos may start with black frames and FaceReader will not be able to analyze them from the start. The VsSettings file is installed together with MediaRecorder. You can find the file in C:\ProgramData\Noldus\MediaRecorder\6. By default the ProgramData folder is a hidden folder. In Windows Explorer on the View tab select Hidden Items in the Show/Hide section to view the folder. - Right-click VsSettings.xml and select Copy. Right-click and select Paste to make a copy of the file. Keep this copy in case you want to go back to the original settings. - Open the VsSettings.xml file in Notepad or a similar text editor. - From the Edit menu select Find and type Wait in the search field. - To make sure that MediaRecorder waits for an I-frame before it starts recording, edit the file and change 0 to 1. - Save the file. Troubleshooting If you are having problems, please first read Specifications or Requirements of a Custom Computer, to check whether your system is compatible with MediaRecorder. Also check the items below to see if there is a known solution for your problem. What Problem Do You Have? - No video preview - Installation problems - Sound problems - Insufficient disc space - Missing frames when controlling recording with external programs - Problems loading MediaRecorder No Video Preview If one of your video inputs is black with a warning triangle and the message No signal from Video [n] is shown, the video source was not turned on when MediaRecorder was started. Press the Refresh button in MediaRecorder to show the image from that camera. You also get a black screen with a warning triangle when you have not yet selected this camera in the Video Settings window. See also Save the Camera Settings in Record Video. You will also have a black video input if your computer does not have an Nvidia graphics card. By default, MediaRecorder records two cameras on CPU and two on the video card (GPU) if you record from four cameras simultaneously. Only Nvidia GPUs facilitate the use of the GPU as additional processing power for compression of MediaRecorder videos. Other graphics cards are not able to do that. If you ordered a computer with MediaRecorder from Noldus Information Technology, it has an Nvidia card. By default, MediaRecorder checks whether this card is available and if so, uses it. If you purchased a PC elsewhere, it may have a different graphics card and with the default settings, your cameras may give black inputs in MediaRecorder. To prevent this, you can edit the VsSettings file that comes with MediaRecorder. To check the graphics card of your computer, click the Windows button and type Device Manager. In the Device Manager window expand the Display Adaptors section. The computer's graphics cards are listed here. The VsSettings file is installed together with MediaRecorder. You can find the file in C:\ProgramData\Noldus\MediaRecorder\6. By default the ProgramData folder is a hidden folder. In Windows Explorer on the View tab select Hidden Items in the Show/Hide section to view the folder. - Right-click VsSettings.xml and select Copy. Right-click and select Paste to make a copy of the file. Keep this copy in case you want to go back to the original settings. - Open the VsSettings.xml file in Notepad or a similar text editor. - From the Edit menu select Find and type GPU in the search field. - To make sure that MediaRecorder does not use the GPU, edit the file and change -1 to 0. You can also change the value to 1 if your computer has one Nvidia graphics card. With this value MediaRecorder will not check what graphics card is available; it will use the card that is installed. Installation Problems If you get an error message during installation of the Picolo card, it is most likely that the card is not correctly inserted into your computer. Turn the computer off and disconnect the power cable. Press the card gently but firmly into place. Sound Problems If you are playing back multiple videos in The Observer XT and you hear an echo on the sound track, turn the sound off on all but one of the video monitors. If you hear no sound on your recording this could be because: - The speakers of your computer are not plugged in, they are turned off, or their volume is low. - The Windows volume control is muted or turned low. - You have selected Line-in for your audio device instead of Microphone. - You do not have an audio source connected. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-procedure-ppe Chapter: Media Recorder - Install MediaRecorder with its prerequisites. See Installation - Using a HDMI cable, connect the output of the video source to the HDMI IN port on the back panel of the Epiphan Pearl Nano device. - Using a HDMI cable, connect the control monitor to the HDMI PASS THROUGH port on the back panel of the Epiphan Pearl Nano device. - Use the control keys on the front panel to configure the system parameters. - Using the right arrow key, navigate to System Status. - Here, you can get the network IP address of your device and you can also check the firmware version. It is recommended to use the latest firmware version. If you need an update, register your device at Epiphan. - Using the left arrow key, navigate to Menu. Within Menu, navigate to System > Network. - Disable DHCP. Set IP address manually. Define an IP address range similar to that of the other cameras. - By default, do not change Network mask and Network gateway settings. If uncertain, consult your system administrator. - Open your internet browser. Use the IP address of your Epiphan Pearl Nano device to access the Pearl Admin panel. For this, include /admin to access the Admin panel. - Using the Pearl Admin panel, configure video encoding. Go to Channel(s), select your channel and click Encoding. In Video settings, make sure Current signal resolution is used as frame size (have the checkbox checked). - Set Key frame interval to 1/2 sec. At Limit frame rate, it is not recommended to change the default value 30. If you use a higher frame rate, it might jeopardize your recording operation. Please do not change the default Bitrate value (auto). - Open MediaRecorder and choose File > Video settings or click Video settings. - In Video Settings, select the option RTSP IP Camera (Noldus RTSP Source Filter). Please note that the Epiphan Pearl Nano device is NOT an ONVIF device. For the details, see Select devices that do not support ONVIF in MediaRecorder. Please note that the RTSP connection string for this device is /stream.sdp. - Please note that you cannot use the Epiphan Pearl Nano device to make audio recordings. Use another audio device for the purpose. For the details, see Select an audio device. Set Up USB 3 Cameras Main Topics - The steps to install USB 3 cameras - Install the USB 3 interface card - Install the USB 3 camera driver - Connect the USB 3 cameras to the PC - Configure the Basler USB 3 camera Prerequisite You have USB 3 cameras that are supported with MediaRecorder. See Supported USB cameras in Recording devices. Which Situation Applies to You? You ordered the computer, cameras and MediaRecorder from Noldus IT. In case of Basler USB 3.0 cameras, your computer has a USB 3 card and its drivers are installed. The cameras are configured. Also MediaRecorder has been set up to use with these cameras. You can connect your cameras and start recording. See Connect the USB 3 cameras to the PC and Record video. You bought the computer somewhere else. Carry out the entire Procedure below. Procedure - In case of Basler USB 3 cameras, install the supported USB 3 interface card, even if your computer already has USB 3 ports. See Install the USB 3 interface card. - Carry out the prerequisite steps before installing MediaRecorder. See The steps to install MediaRecorder in Installation. - Install MediaRecorder with the camera driver. Installing the camera driver is only needed for the Basler USB 3 camera. For the Logitech BRIO no driver installation is needed. See Install the USB 3 camera driver. - Connect the USB 3 cameras to the PC. - Configure the Basler USB 3 camera. See Also - Supported USB cameras in Recording devices Install the USB 3 Interface Card MediaRecorder was tested with the following USB 3 interface cards: - U3-PCIE1XG205-1S – You can connect one USB 3 camera to this card. - Fresco Logic U3X4-PCIE4XE111 rev 1.1 – You can connect up to four USB 3 cameras to this board. To Install the USB 3 Interface Card - Turn off your computer and all connected peripherals, such as the monitor and printer. Make sure that the computer is unplugged. - Remove the PC's case according to the instructions provided in the PC's user manual. - Select a free PCIe expansion slot, and remove the corresponding extension cover. For details about PCIe slots, see PCIe slot properties in Set up analog cameras. - Unpack the USB 3 interface card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. - Fix the card to the chassis and re-fit the computer's cover. If you have a 4-port Fresco Logic U3X4-PCIE4XE111 rev 1.1 board, make sure the board receives power from the PC. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. Install the USB 3 Camera Driver Aim: To install the software that allows communication between your camera and the operating system of the computer with MediaRecorder. Prerequisites - You have the Basler USB 3 camera. - You have installed the USB 3 interface card. See Install the USB 3 interface card. - You carried out the prerequisite steps before installing MediaRecorder. See The steps to install MediaRecorder in Installation. - IMPORTANT: If you upgraded from a previous MediaRecorder version and had old drivers for the camera installed, you uninstalled them first. To Uninstall Old Drivers - Open the Control Panel. - Choose Programs and Features. - Select Pylon Camera Software Suite and choose Uninstall. If You Did Not Yet Install MediaRecorder - Download the installation files from my.noldus.com and extract the contents. - Browse to the file MediaRecorder 6 Setup.exe and double-click it. - In the Drivers and tools field, choose Basler USB Camera driver - pylon [version number]. - Click Next, accept the License Agreement and click Install. If You Already Installed MediaRecorder Follow the instructions in If you did not yet install MediaRecorder and choose Modify in the installation window. Alternatively: - Download the necessary files from my.noldus.nl and extract the contents. - Browse to Drivers\Basler\7.1.0.25066. - Double-click the file Basler_pylon_7.1.0.25066.exe. - Agree to the terms in the License Agreement. - In the Profiles window, choose Camera user and click Next. - As camera type, choose USB and click Next. - Optionally, change the location where the camera drivers are stored and choose Next > Install. To Uninstall Old Drivers - Open the Control Panel. - Choose Programs and Features. - Select the Basler camera driver and choose Uninstall. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-procedure Chapter: Media Recorder Procedure - In The Observer XT, choose File > Preferences > N-Linx Settings. - Select Use N-Linx server to connect with other applications. - In the N-Linx Server address field, enter the computer name of the computer with N-Linx Server. If The Observer XT is installed on the same computer as N-Linx Server, leave the default entry Localhost. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. - Click Test connection. If connection with N-Linx Server is found, the Status will change to Connected. - Click OK. - Choose Setup > Project Setup. - Under Observation source, select Live Observation. The Devices window now opens. If not, click the Devices button. - Select MediaRecorder [Version number][Computer name] and click Edit Settings. MediaRecorder now opens if it is not already open. - Click Edit Settings again. A window with the available configurations now opens. Select the configuration file you want to use and click OK. If you do not select a configuration, Current Settings.mrs will be used. Optionally enter a unique name in the Identify device as field. This way you can control multiple instances of MediaRecorder with one instance of The Observer XT. - Repeat steps 9 and 10 for each MediaRecorder instance. Note When you close MediaRecorder, the MediaRecorder line in the Devices window (step 9) will be grayed out and the status will change to Disabled. MediaRecorder will start when you create an observation. Carry Out an Observation in The Observer XT Procedure - In The Observer XT, choose Observe > Observation > New to create an observation. - See Carry out your observation in The Observer XT Help. - Press the Start observation button and score the data. See Start the observation and Score data in The Observer XT Help. - Press the Stop observation button. See Stop the observation in The Observer XT Help. Note IMPORTANT Allow enough time between the actions. If you start an observation before MediaRecorder is completely open, video recording will not start. Troubleshooting When MediaRecorder control with The Observer XT does not function properly, check the following: - On the computer with MediaRecorder, check that N-Linx Agent is running. See step 1 in Connect N-Linx Agent to N-Linx Server. If there is no N-Linx Agent icon in the system tray, the program is not running. Then double-click the file NLinxAgent.exe in the folder C:\Program Files\Noldus\N-Linx Agent 1. - On the computer with MediaRecorder, check that the status of the N-Linx Agent is Connected. If not, follow steps 2 and 3 in Connect N-Linx Agent to N-Linx Server. - In MediaRecorder, check that the checkbox Allow communication with N-Linx Server is selected (see step 2 in Create MediaRecorder Settings). - In The Observer XT, check that Use N-Linx server to connect with other applications is selected (see step 2 in Create The Observer XT Settings) and that the Status in the window is Connected (see step 5 in Create The Observer XT Settings). - In The Observer XT, check that MediaRecorder is selected (see step 9 in Create The Observer XT Settings). - On all computers with MediaRecorder, The Observer XT, and N-Linx Server, check that an exception is made in Windows Firewall for all inbound and outbound traffic through port 5672 (see Create Exceptions for N-Linx Port in Windows Firewall). - Check that N-Linx Server is running. To do so, press Ctrl + Shift + Esc and open the Services tab. Locate the line RabbitMQ and check that the Status is Running. If not, right-click the line and select Start. Synchronize Videos with Events When Is Manual Synchronization Not Needed? Videos created by MediaRecorder are automatically synchronized with the events in The Observer XT when you followed the procedure in MediaRecorder with The Observer XT. An automatic offset is applied to the videos. See View the automatic offset of videos imported into The Observer XT to see which offset was applied. When Is Manual Synchronization Needed? You need to synchronize videos and events manually in the following situations: - You start video recording manually and import the videos into The Observer XT. - You have an older version of The Observer XT that does not support N-Linx data transfer. See Synchronize Manually for the procedure. Procedure The procedure depends on what you did: - You controlled video recording with The Observer XT. - You manually started video recording within 10 seconds after starting the observation in The Observer XT. You Controlled Video Recording with The Observer XT Right-click the video in The Observer XT and choose Properties. The field Recording details shows the offset. You Manually Started Video Recording Within 10 Seconds After Starting the Observation in The Observer XT When you import the videos into The Observer XT, an offset is automatically set. A message with the calculated offset is shown. If you right-click the video in The Observer XT, the offset is also shown next to Recording details in the Video Properties window that opens. However, there can still be up to 1 second of asynchronism between the observation and the video files. If that is a problem for the accuracy of your experiments, see Synchronize Manually to fine-tune the synchronization. Synchronize Manually Prerequisites One of the following situations is true: - You have The Observer XT 11 or lower. - You have The Observer XT 12.5 or lower and The Observer XT and MediaRecorder run on different computers. - You manually started video recording more than 10 seconds after starting an observation in The Observer XT and imported those videos manually into The Observer XT. Procedure You must carry out the following steps: - Determine the time difference between video and events. - Apply offset to correct for the time difference. Determine the Time Difference Between Video and Events - Make sure an event is recognizable in the videos and the event log. For example, create a dummy behavior with a key code in the coding scheme. - Carry out an observation and simultaneously record a video or the keyboard. - In The Observer XT, press the key of the dummy behavior. The event is recorded in the Event log and is visible in the video. - Import the video into The Observer XT. - Open the observation and scroll to the recognizable event in the video. Note the time difference of the event in the video and the event log. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-procedure-J1g Chapter: Media Recorder Procedure - Open MediaRecorder and choose File > Video Settings or click Video Settings. - Select the checkbox in front of the video channel and choose RTSP IP Camera (Noldus RTSP Source Filter). - Click the Advanced Video Settings button. - A list with ONVIF cameras in the network appears. Select the camera. - Enter the ONVIF User name and ONVIF Password for your camera. If you obtained cameras from Noldus IT, the ONVIF user name is root and the ONVIF password is Noldus. - TIP: To select another camera, click the Discover button to display the list with ONVIF cameras in the network. - TIP: If you have several cameras with the same ONVIF User name and ONVIF Password, choose File > Preferences > IP camera settings. Select Use default IP camera user name and password and enter the credentials. You can now skip the relevant steps; the camera is detected automatically. - Click Get Device Properties. - The Encoding and Quality fields appear with the default video format, frame rate, and resolution of the camera. - Optionally, click Edit and select another frame rate or resolution. Click Update when done. For low frame rate recordings, it is important to lower the H264 Gov length on the same screen, under Advanced Settings. For 5 fps, set the Gov length between 5 and 10; for 1 fps recording, between 1 and 2. A lower Gov length will result in larger files but better image. - TIP: It is also possible to change the frame rate and resolution in the table with selected video devices. You may still need to adjust the Gov length for optimal results. - Optionally, adjust the video quality, for example to decrease the video file size, but we recommend doing this only when problems with video quality or data transfer over the network occur. See Adjust Advanced Video Quality Options. - Click Close when done. - You may want to reverse the direction the camera moves with Pan and Tilt. To do so, select the checkbox Flip pan axis (horizontal movement) or Flip tilt axis (vertical movement), or both. - Click OK. - Select the microphone from the Audio Device list. To select the microphone from the camera, or a microphone connected to it, select RTSP IP Camera (Noldus RTSP Source Filter) from the Audio Device list. - Close the Settings window and tap on the microphone. Check the green bar next to the video device to see whether you selected the correct microphone. - Continue with Record Video. Notes - If you bought cameras yourself, see Create ONVIF User Name and Password for the procedure to create an ONVIF user name and ONVIF password. - If the default port 554 is already in use, ask your system administrator for help to select another one. - See Create Audio Settings for how to adjust the recording volume. Adjust Advanced Video Quality Options Aim To change video quality, for example to reduce the video file size. Prerequisite You experience problems with video quality or data transfer over the network. In all other cases, we recommend not changing the default settings. Procedure - Choose File > Video Settings or click Video Settings. - Click the Advanced Video Settings button. - Click Get Device Properties. This enables the Edit button. Click Edit. - Select Advanced Settings. - Adjust the settings and click Update > Close. - See Advanced Video Quality Options for a description of the options. Advanced Video Quality Options If an option cannot be edited, your camera does not support other options, or the value is set by the chosen profile. Encoding Interval This value cannot be edited and is set by the profile. Bitrate To set a limit to the data transfer. The default value 0 means unlimited. If you enter a value, data transfer is limited to this value in Kb per second. H264 Gov Length The interval in which the I-Frames will be coded in the video file. A value of 1 means that every frame is an I-frame. A value of 2 means that every second frame is an I-frame. Decreasing the number increases the video quality, but also the data transfer. For a description of the frame types, see: https://en.wikipedia.org/wiki/Video_compression_picture_types H264 Profile The encoding profile from the IP camera. MediaRecorder uses the Baseline profile and this option cannot be edited. Quality The quality of the encoded video file. A higher number gives higher encoding quality, but also more data transfer over the network. Select Non-ONVIF Devices in MediaRecorder Aim To select a device that does not support ONVIF Profile S in MediaRecorder. If your device does support ONVIF, see Select ONVIF Cameras in MediaRecorder instead. Prerequisites - Your device does not support ONVIF Profile S. - You followed the procedure in Ethernet Card Setup. - You created comparable settings for your device as described in Camera Setup. - You installed MediaRecorder. See Installation. - You connected your video device to the computer with MediaRecorder. Procedure - Open MediaRecorder and choose File > Video Settings or click Video Settings. - Select the checkbox in front of the video channel and choose RTSP IP Camera (Noldus RTSP Source Filter). - Click the Advanced Video Settings button. - A list with available ONVIF cameras in the network appears. - IMPORTANT: If your device does not support ONVIF, it will not be on this list. Click Cancel. - Enter the IP address, User name, and Password of the device. If you bought your device from Noldus IT, the User name is root and the Password is Noldus. If the default port 554 is already in use, ask your system administrator for help to select another one. - Click Get Device Properties. - The Connection string field appears. - Look up in the manual of your device where the video files can be accessed via the RTSP communication protocol. Enter the path from the slash after the connection information in the Connection string field. For example, /stream.sdp for an Epiphan Pearl Nano screen capture device. - Click OK. Optionally, select another frame rate or resolution. However, make sure you select the same frame rate as is selected in the device itself when you opened the camera in a browser. - Optionally, open the camera in a browser to pan, tilt, or zoom. See Access Camera Settings. - IMPORTANT: Close the browser before starting recording with MediaRecorder. - Click OK and continue with Record Video. Set Up GigE Cameras Main Topics - The steps to install GigE cameras - Connect the GigE cameras to the PC - Install MediaRecorder with the camera drivers - Set camera IP address - Configure the cameras Prerequisites - The network allows data transfer of at least 1 Gb per second. We recommend using a dedicated network for the cameras. - The cables must be suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. See https://en.wikipedia.org/wiki/Category_5_cable - You have GigE cameras that are supported with MediaRecorder. See Supported GigE Camera in Recording Devices. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-procedure-DTi Chapter: Media Recorder Procedure - Double-click the Pylon IP Configuration tool icon on the desktop. - Select the camera under Local Area Connection. - Fill in the IP Address and Subnet Mask fields under Static IP Address as supplied by your system administrator. - Click Save and then Close. - If you have multiple cameras, connect the next one and repeat the steps above. Note Your cameras should have the same firmware version. Check this in the Pylon Viewer software. In the Features panel, under Device Information, check Firmware Version. If the cameras do not have the same firmware, an upgrade or downgrade must be done. Configure the Cameras Aim: To adjust settings in a Basler GigE camera or USB 3.0 camera, like the video frame rate, video frame resolution, and exposure time, within the camera software. Note: Settings are stored in the camera software, not on the PC. When you work with multiple cameras, repeat the procedure for each camera. Procedure (General) - Make sure MediaRecorder (and EthoVision XT, when present on the computer) is not running. - Start the Basler Pylon Viewer software that comes with the GigE cameras. Note: The Basler Pylon Viewer software is installed automatically when you install the camera drivers. - In the Devices panel, under GigE, double-click the Basler camera. - To preview the camera image, click the Continuous Shot button on the toolbar. Note: To be able to adjust the settings, click the Stop button first. - Follow the instructions below that apply. To Center the Camera View With this procedure you make sure the camera view is centered. Important: If you center the camera view in MediaRecorder, the settings may not be stored in the camera drivers. Here in Pylon Viewer you make sure that the settings are stored in the drivers, also for future recordings. - In the Features panel, open the Basler camera item and then the AOI Controls item (Image Format Control for USB 3 cameras). - Select both options Center X and Center Y. - Save the settings. See To Save the Camera Settings. To Set the Pixel Format Note: This option applies to black and white digital cameras. - In the Features panel, open the Basler camera item and then double-click Image Format Controls. - Set the Pixel Format to Mono 8. - Save the settings. See To Save the Camera Settings. Important: This corresponds to the option Y800 in MediaRecorder. In Pylon Viewer you make sure that the settings are stored in the drivers, also for future recordings. To Adjust the Camera Exposure Time The exposure time (or shutter time) is the time the camera shutter is kept open to let light in. The exposure time limits the maximum achievable frame rate. If the sum of the exposure time and the time needed for reading the chip (readout time) is greater than the time between consecutive video frames, the next frame may be dropped, resulting in a lower frame rate and missed samples during tracking. To adjust camera exposure that matches a frame rate: - In the Features panel, open the Basler camera item and then double-click Acquisition Controls. - Make sure that Exposure Mode is set to Timed and Exposure Auto is set to Off. - Next to Exposure Time (Abs) [us], enter the exposure time you require, in microseconds. - For zebrafish larvae, enter 4000 or 2000, depending on the video resolution chosen. - In all other cases, you may choose a higher value. For rodents, a value below 20000 is fine. - Faster animals require shorter exposure times. Press Tab or click another field to confirm. - To check that the exposure time is compatible with your frame rate, click the Continuous Shot button on the toolbar. At the bottom of the live video window, locate the frame rate resulting from the new exposure time. This should be the same as the value next to Acquisition Frame Rate (Abs) [Hz]. If the resulting frame rate is lower than Acquisition Frame Rate (Abs) [Hz], then either lower the exposure time (this will make the video image darker; open the lens diaphragm to compensate), or lower the video resolution. Do this until you see the expected frame rate. - Save the settings. See To Save the Camera Settings. To Adjust the Camera Gain This applies to both color and black/white Basler cameras. Important: Increasing gain also increases image noise. Do this only if no other option is available to improve image brightness. For example, make sure that the lens aperture is maximal and increase lighting. - In the Features panel, click Analog Controls. - From the Gain Auto list, select Off. - Next to Gain (Raw) (Gain [dB] for USB 3.0 cameras), select the value you require. A higher gain results in a brighter image, but also more noise and a grainy image. - Save the settings. See To Save the Camera Settings. To Adjust White Balance If you have a color camera, you also need to adjust its white balance. - Click Color Improvements Control. - Point the camera at a piece of white paper so that the camera image is entirely white. Click in the field next to Balance White Auto and select Once from the list. - Save the settings. See To Save the Camera Settings. To Save the Camera Settings - Click the Stop button. - In the Features panel, open the Configuration Sets item (User Set Control for USB 3 cameras). - From the Configuration Set Selector list (User Set Selector for USB 3 cameras), select User Set 1. - Next to User Set Save, click Execute. The camera settings from the previous steps are now saved under User Set 1. - From the Default Startup Set list (User Set Default for USB 3 cameras), select User Set 1. - Close Pylon Viewer. These settings will be used each time you start up MediaRecorder. Tip: You can also save different settings for the same camera in User Set 2 and User Set 3. Under Default Startup Set (User Set Default), select which set you want MediaRecorder to use. Set Up the Epiphan Pearl Nano Screen Capture Device Aim: To connect the Epiphan Pearl Nano screen capture device and make the necessary settings. Prerequisites - The network allows data transfer of at least 1 Gb per second. - We recommend using a dedicated network for the cameras. - The cables must be suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Ptz Keyboard Shortcuts URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-ptz-keyboard-shortcuts Chapter: Media Recorder PTZ Keyboard Shortcuts The following keyboard shortcuts can be used to control PTZ: - Ctrl + 1 — Enable / disable PTZ in first video - Ctrl + 2 — Enable / disable PTZ in second video - Ctrl + 3 — Enable / disable PTZ in third video - Ctrl + 4 — Enable / disable PTZ in fourth video - Numerical keypad 1 — Move camera left-down - Numerical keypad 2 — Move camera down - Numerical keypad 3 — Move camera right-down - Numerical keypad 4 — Move camera left - Numerical keypad 6 — Move camera right - Numerical keypad 7 — Move camera left-up - Numerical keypad 8 — Move camera up - Numerical keypad 9 — Move camera right-up - Numerical keypad + — Zoom in - Numerical keypad - — Zoom out Notes - If you use the CH Products RS Desktop joystick for PTZ control, make sure it is connected before you start MediaRecorder. - To reverse the camera pan or tilt direction, open the Advanced Video Settings window and select the checkbox Flip Pan axis or Flip Tilt axis. - See step 11 in Select ONVIF Cameras in MediaRecorder in Set Up IP Cameras. To Change the PTZ Method MediaRecorder has two PTZ methods. The default method is described above. It is also possible to let the camera center its camera view to the point that you click with your mouse. Procedure - Open MediaRecorder and select your IP cameras. See Select ONVIF Cameras in MediaRecorder. - Close MediaRecorder. This saves settings for the IP cameras in the file Current Settings.mrs. - Create a backup of the file Default Settings.mrs that is present in the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. - Open the file Current Settings.mrs from the same folder with Notepad. - Locate the line 1 and change 1 to 0. There is a line for each PTZ camera that you selected in MediaRecorder. Change the line for each PTZ camera. Important: When you selected the same camera multiple times in MediaRecorder, use the same method for pan and tilt in each camera. For each camera, use either 1 or 0. - Save the file as Default Settings.mrs. These settings are used when the file Current Settings.mrs is not found. - Delete the file Current Settings.mrs from the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. - Re-open MediaRecorder. MediaRecorder opens with configuration file Default Settings.mrs and creates a new file Current Settings.mrs with the edited settings. The new PTZ method is now available. To Pan and Tilt the Camera View - Click the Enable PTZ button in the image you want to adjust. - A white cross appears. The camera moves to the point that you click with your mouse. Recording Video of IP Cameras Aim: To enter the ONVIF user name and ONVIF password of IP cameras only once, in case you have several cameras with the same credentials. Procedure - Choose File > Preferences > IP Camera Settings. - Select Use default IP camera user name and password. - Enter the user name and password. - Follow the procedure in Select ONVIF Cameras in MediaRecorder or Select Devices That Do Not Support ONVIF in MediaRecorder. When you click the Advanced Video Settings button, the user name and password are filled in automatically. Use Commands Aim: To control video recording with another program that can send commands, for example, EthoVision XT. Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - You selected cameras, microphones and video output in the Video Settings window of MediaRecorder. See: - Select a Video Device - Select an Audio Device - Video File Options Procedure In your application, browse to the program MRCmd.exe that is by default located in the folder C:\Program Files\Noldus\MediaRecorder 6 and specify the command. For example, use the following command line to start video recording: "C:\Program Files\Noldus\MediaRecorder 6\MRCmd.exe /R" Note: If you installed MediaRecorder in another folder than the default one, the program MRCmd.exe is present in that folder. Adjust your command lines accordingly. Available Commands - Start MediaRecorder — MRCmd.exe or MRCmd.exe /E - Start recording — MRCmd.exe /R - Stop recording — MRCmd.exe /S - Close MediaRecorder — MRCmd.exe /X — Closes MediaRecorder program. - Load a configuration file — MRCmd.exe /C=[filename.mrs] — See Load a Configuration File. - Set the file base name — MRCmd.exe /B=[basename] — See Set File Base Name. Note: There is a space between MRCmd.exe and the slash. Load a Configuration File The command /C loads a configuration file with the settings for your cameras. This is useful, for example, to open MediaRecorder with the correct cameras. Make sure MediaRecorder is not recording at that moment. By default, MRCmd.exe loads a file from the folder C:\Users\Public\Public Documents\Noldus\MediaRecorder. If the file is located in another folder, you must type the full path. If the file name or the path contains spaces, you must type it in between quotation marks. Example 1 — Open MediaRecorder and load Configuration_observation_room.mrs from C:\Users\Public\Public Documents\Noldus\MediaRecorder: MRCmd.exe /E /C=Configuration_observation_room.mrs Example 2 — Open MediaRecorder and load Configuration Control Room from C:\Configuration files: MRCmd.exe /E /C="C:\Configuration files\Configuration Control Room.mrs" Set File Base Name The command /B sets the file base name. See Set Video File Base Name. Example — Set the file base name to Observation room: MRCmd.exe /B="Observation room" Note: This option cannot be used together with other commands. Delay Allow enough time between commands. If a command is sent before the previous one is carried out, the second command is not carried out. For example, if the command Start Recording is sent before MediaRecorder is completely open, recording does not start. There may be a delay between the command Start Recording and the moment the recording actually starts. This delay depends on the number of cameras, camera settings, the processor speed, and programs running in the background. In the most common scenarios with MediaRecorder and The Observer XT, the videos are automatically synchronized with the events, so the delay is not important. See also Synchronize Videos with Events in MediaRecorder with The Observer XT. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Reference Manual URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-reference-manual Chapter: Media Recorder Welcome to MediaRecorder Main Topics - Introduction - What's New Compared to Version 6.2 - How to Use This Help? Tips - To use the Help at its best, set Internet Explorer, FireFox, Google Chrome or a similar browser, not Microsoft Edge, as the default browser. - If you keep getting the message "Internet Explorer restricted this webpage...", do the following: in Internet Explorer, choose Tools > Internet Options > Advanced. Under Security, select Allow active content to run in files on My Computer. Click OK, then close and restart the Help. - If you do not see the Table of Contents on the left, enlarge the Help window or zoom out (Ctrl+mouse wheel, or Ctrl+-). - To search for two or more adjacent words, use quotation marks, for example "Action Unit". - To go back to the search results after visiting one of the result pages, click again on the magnifying glass icon in the Search field. Introduction MediaRecorder is a software package that makes digital video files with input of many different types of cameras. These video files can be used in the video analysis programs The Observer XT, EthoVision XT and FaceReader. Supported Video Devices MediaRecorder is supported with several types of video devices. In the section on the type of device, you find which specific devices are tested and supported, how many devices you can use simultaneously, at what frame rate and resolution and in which Noldus software. MediaRecorder is supported with the following device types. - Analog cameras - IP cameras - USB devices - GigE Vision cameras - Screen capture devices We recommend to create a test recording with your devices first before you carry out the actual recordings, especially when you have more or other devices than we officially support. See Record Video. Modules MediaRecorder has the following modules. - Base Module – To record up to four video files simultaneously. However this number depends on the type of video device, since multiple cameras are not supported for all devices. See the section on your device for how many devices are supported at what frame rate and resolution. - Additional Camera Module 1-6 Camera – For analog or IP cameras only. To extend the number of cameras to 6. - Additional Camera Module 1-8 Cameras – For IP cameras only. To extend the number of cameras to 8. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Set Up Analog Cameras URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-set-up-analog-cameras Chapter: Media Recorder Which Situation Applies to You? - You ordered computer, cameras, and MediaRecorder at Noldus IT: The video capture card is already installed in the computer. Also MediaRecorder has been set up to use with these cameras. You can connect your cameras and start recording. See Record video. - You bought the computer and cameras somewhere else: Follow the procedure below. Procedure - Install the Picolo Alert PCIe card - Install the drivers for the Picolo Alert card - Connect the analog camera to the computer Install the Picolo Alert PCIe Card Aim: To install the card that digitizes the output of analog cameras. Prerequisites - You use MediaRecorder with analog cameras. - You did not buy a complete setup from Noldus IT. If you bought a complete setup from Noldus IT, the card has been installed in the computer, so you can skip this topic. Procedure - Make sure your computer is turned off and the power cable is disconnected. - Open the computer. - Select a free PCIe expansion slot, and remove the corresponding extension cover. See PCIe slot properties for more information on different PCIe slots in a Dell computer. - Unpack the Euresys Picolo Alert PCIe card, place it into the slot, and press it carefully into position. If the card does not fit into place easily, remove it and repeat the operation. IMPORTANT: When touching the board, its electronic components can be damaged by static electricity. To avoid any such risk, make sure that you are grounded. You can ground yourself by putting on an earthing wristlet, and attaching its clip to the metal frame of the computer. If an earthing wristlet is not available, you can hold the metal frame with one hand while holding the Ethernet card in your other hand. Ensure also that your clothing does not touch any components while handling the card. - Fix the card to the chassis and re-fit the computer's cover. - Close the computer. PCIe Slot Properties Different PCIe slots have different properties, resulting in different performances. When possible, choose the slot that gives maximum performance. To estimate performance, take note of the slot version (2, 3, etc.). Do not use the graphic slots. Compare the slot version with the following table: - PCIe v1.x: 250 MB/s - PCIe v2.x: 500 MB/s - PCIe v3.0: ~1 GB/s - PCIe v4.0: ~2 GB/s Note that values are given per lane; they should not be multiplied by the number of lanes in a slot (e.g. x4) since the card has a 1x connector. Install the Drivers for the Picolo Alert Card Aim: To install the software that allows communication between the Euresys card and the computer operating system. Prerequisites - You use MediaRecorder with analog cameras. - You did not buy a complete setup from Noldus IT. - You installed the Euresys Picolo Alert card into the computer. Procedure - Insert the MediaRecorder installation USB stick into your computer. - If you have the Picolo Alert card, open the folder Drivers and Tools\Drivers\Euresys\Alert and double-click the file multicam-win10-6.15.1.3573.exe. - Follow the instructions on your screen. - When installation is finished, a message appears that the drivers were successfully installed. Click Close. - Installing the Picolo card drivers involves a computer restart. After restart, the installation is finished. Continue with installing MediaRecorder. See Installation. Connect the Analog Camera to the Computer Important: By default, Windows 10 computers have the option Fast Startup enabled. This means that the computer goes into standby instead of shutting down when you switch it off. This can sometimes cause MediaRecorder to stop responding when selecting an input of the H.264 video capture card. Therefore, for analog cameras it is especially important to select the correct power options. See Select Correct Power Options in The Steps to Install MediaRecorder. The Picolo Alert PCIe card has 4 BNC connectors. This card has an effective delivery bandwidth of 180 MB/s. To Connect the Camera - If your camera has a BNC output connector, connect a coaxial cable, with BNC connectors on both sides, between Video Out of the camera and one of the BNC inputs of the breakout cable. - If your camera does not have a BNC connection, use a converter. Change Video Standard Aim: To specify the correct video standard to be used by the Picolo Alert PCIe card. Procedure - Open Video Settings the first time you select the Picolo Alert PCIe card. - Select the correct video standard, depending on your cameras. It is typically PAL for Europe and NTSC for the US. You need to do this four times, selecting all four channels from the Board drop-down box (channels are numbered #0–#3). Press Apply after setting the correct Video Standard for each channel. You should see the preview after setting the Video Standard correctly. Failing this will result in a black preview. You can only modify this setting the first time before the preview is running; after that it will become disabled. To make the setting editable again, deselect the camera from the video inputs and then select it again. Set Up IP Cameras Main Topics - The steps to install IP cameras - Ethernet card setup - Camera setup - Select ONVIF cameras in MediaRecorder - Select devices that do not support ONVIF in MediaRecorder Prerequisites - The network allows data transfer of at least 1 Gb per second. - We recommend using a dedicated network for the cameras. - The cables must be suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. - You have Axis IP cameras that are supported with MediaRecorder. See Supported IP Cameras in Recording Devices. Which Situation Applies to You? - You ordered computer, IP cameras, and MediaRecorder at Noldus IT: The cameras are already installed. Also MediaRecorder has been set up to use with these cameras. You can connect your cameras and start recording. See Record Video. - You bought the cameras from Noldus IT and installed MediaRecorder on your computer: The camera IP address and settings have been created by Noldus IT. Carry out the steps in the procedure below, except for steps 5, 6, 7, and 8. - You bought the computer and cameras somewhere else: Carry out the entire procedure below. Procedure - Install the Ethernet card - Set Ethernet card IP address - Connect IP cameras to the PC - Set camera IP address - Set camera password and select power line frequency - Create camera settings - Create audio settings - Select ONVIF cameras in MediaRecorder, or - Select devices that do not support ONVIF in MediaRecorder Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Standalone Or With Other Software URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-standalone-or-with-other-software Chapter: Media Recorder Standalone or with Other Software MediaRecorder can be used as a standalone program to create video files. It is also possible to use the Noldus network communication protocol N-Linx, to use it in combination with The Observer XT. This way, recording with MediaRecorder starts automatically when starting an observation in The Observer XT and stops when this observation is ended. Furthermore, the videos obtained this way are automatically linked to an observation and synchronized with the manually scored events. It is also possible to control recording with commands from EthoVision XT, for example to start recording when a mouse leaves the shelter. MediaRecorder Help This Help describes how to use MediaRecorder 6.5 with the supported recording devices. Information about devices from companies other than Noldus IT is valid at the moment of the release and may change afterwards without our knowledge. If you have any problems, questions, remarks or comments, please let us know. See Support in Troubleshooting for contact information. What's New in MediaRecorder 6.5 If you have been using a previous version of MediaRecorder, you should read these topics to get an idea of the improvements in this version. - What's new compared to version 6.2 - What's new compared to version 6.0 - What's new compared to version 5 Selection of Audio Source for All the Videos While previously only Audio device 1 could be used as a common audio source for all the videos, now in Picture-in-Picture mode, you may select which audio source to use for this purpose. Data Transparency Policy When starting recording, a pop-up window will appear, informing you about Noldus's Data Transparency Policy. What's New Compared to Version 6.2 Software Activation Code Instead of Hardware Key MediaRecorder 6.2 comes with a software activation code as the license which makes it easier to work with the software. For existing customers it is still possible to upgrade their hardware key. What's New Compared to Version 6.0 Output Quality Selection Instead of using the default output quality you can now select optimized settings for when you are using your recorded video files in: - A four-camera EthoVision set-up - A DanioVision set-up - With the Remote Photo Plethysmography module in FaceReader See Output Settings for more information. Recording with a Frame Rate of 1 fps It is now possible to select a frame rate as low as 1 fps when filming slowly-moving subjects. Prevent Black Frames at the Start of Your Videos With the default settings of MediaRecorder there may be black frames at the start of your videos. If that is the case EthoVision will not automatically start tracking and FaceReader will not start analyzing from the start of your videos. You can now edit the VsSettings file that comes with MediaRecorder to prevent black frames. For more information see Prevent Black Frames at the Start of Your Videos. Euresys Picolo H264 Boards Not Supported The Picolo U4 and U8 H264 boards are end of life and only have 32 bit drivers. Therefore the latest version of MediaRecorder does not support them anymore. End-User Licence Agreement Revised: 21 July 2022 IMPORTANT – READ CAREFULLY. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading or using the Software (as defined below). By checking the "accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions of this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions Terms used in this EULA but not otherwise defined shall have the meaning assigned to them below: - 1.1. Authorized Partner: the individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. - 1.2. End-User: the individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3. EULA: this End-User License Agreement. - 1.4. Indirect Losses: any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5. Network License: a licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. - 1.6. Noldus: Noldus Information Technology BV, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries listed in the document https://www.noldus.com/legal/noldus_corporate.pdf. - 1.7. Security System: a system of software protection to limit installation and use of the Software to the authorized End-Users and computers. - 1.8. Security Device: a device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. - 1.9. Software: the software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) provided to the End-User by Noldus or an Authorized Partner together with this EULA, that is not covered by third party terms and conditions and is included in the list under "Noldus software" in the Annex to the General Terms and Conditions (https://www.noldus.com/legal/noldus_gtc.pdf). Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Tested Setups With Ethovision Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-tested-setups-with-ethovision-xt Chapter: Media Recorder Tested Setups with EthoVision XT The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices and (4) recording time (hours) and (5) whether the test has been carried out on a desktop PC (Dell T3640) or a laptop (Dell 3551). Device Resolution Frame Rate No of Devices Recording Time Desktop or Laptop Basler acA1920-155um 1920 x 1200 1920 x 1080 0.5 D Basler acA2040-90uc 2040 x 2046 D Basler acA2040-90uc* 2040 x 2046 D Basler acA2040-90uc** 2040 x 2046 D Basler acA2040-90uc 1920 x 1200 L - * Tested with output quality settings "EthoVision" and "DanioVision". - ** Tested with output quality setting "EthoVision". Tested Setups for Use in The Observer XT - Portable Set-Up The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices and (4) recording time (hours). Tests were done on a Dell 3551 notebook. Device Resolution Frame Rate No of Devices Recording Time Logitech Brio (separate videos, Picture-by-picture & Picture-in-picture, camera audio only) 1920 x 1080 Logitech Brio 4096 x 2160 0.5 Notes - When using the Logitech Brio camera, you have to change the Color space to MJPG. See Show frame rate, resolution and format. - With multiple USB 3 cameras it takes a while before they become visible in MediaRecorder as it takes time for USB 3 cameras to initialize. - Encoding the video stream of USB 3 cameras requires quite some processing capacity, which increases power consumption. If you use the supported devices on our recommended laptop, be aware that after 1 hour recording the battery level drops from fully charged to 45%. GigE Vision Cameras GigE Vision cameras are hereinafter referred to as GigE cameras. When Do I Need a GigE Camera? GigE cameras are high-performance industrial cameras. They can have a higher frame rate and resolution than the other supported cameras. The images are sent unprocessed to the computer using a standard network cable (UTP). With a high frame rate and resolution this results in a very high transfer of data. You can connect a GigE camera directly to an Ethernet card on your computer. In this way you can obtain very high quality videos. An important advantage of GigE cameras is the possibility to have long cables between the camera and the computer. Network Requirements To use MediaRecorder with GigE cameras, the following network requirements apply: - An Intel Pro/1000 CT or Intel Pro/1000 PT (1 Gb) network adapter needs to be installed in the computer. - The cables must be suitable for Gigabit Ethernet. The minimum cable quality is CAT5e. - We recommend to use a dedicated network. Install and Setup If you bought a complete solution from Noldus IT, the network adapter is present in the computer, the GigE cameras are set up and the MediaRecorder settings are made. If you bought your cameras and MediaRecorder separately, you must do the installation and setup yourself. See Set up GigE cameras Power over Ethernet GigE cameras can be connected to a PoE injector. This is a device that passes power along with data (in this case, video data from the camera) on twisted-pair Ethernet cabling. Cameras may also be powered using a 2 or 4-port Network Interface Card (NIC). This way no separate power supply is needed. Supported GigE Cameras - Basler GigE camera acA1300-60gm mono. Color space: Y800. - Basler GigE camera acA1920-40gc color. Color space: RGB32. Tested Setups with EthoVision XT The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices and (4) recording time (hours). Tests were done on a Dell T3640 PC. Device Resolution Frame Rate (fps) No of Devices Recording Time (hrs) Basler acA1300-60gm 640 x 480 800 x 600 1024 x 768 1280 x 1024 0.5 Basler acA1300-60gm 1284 x 1025 Basler acA1300-60gm 960 x 640 Basler acA1300-60gm 1280 x 1040 Basler acA1300-60gm* 1280 x 960 Basler acA1920-40gc 1920 x 1200 - * Tested with output quality setting "EthoVision" and "DanioVision". Important: The file size of an 8, 18 and 24 hours recording is very large (at least 12 GB). When four devices were tested, separate videos were made. Cable Length In theory, a cable length of 150m is possible. However, the maximum length tested in-house with satisfactory results was 25 m. Screen Capture Devices When Do I Need a Screen Capture Device? You can easily record what your test participant is doing on his or her computer with a screen capture device. Such a device will provide you with high quality images of the screen at which the test participant is looking. Epiphan Screen Capture Devices Epiphan screen capture devices are hardware devices that will stream the screen captures of the test computer to the computer with MediaRecorder. MediaRecorder supports Epiphan Pearl Nano. See Epiphan screen capture devices MR Screen Capture Tool The Screen Capture tool is an add-in to your MediaRecorder license. See: Use of the Screen Capture tool MediaRecorder Screen Capture The Screen Capture tool is an add-in to your MediaRecorder license. It allows you to record the screen of the computer with MediaRecorder. It is a software tool that is built in to MediaRecorder. Important: To record the screen of a computer other than the one with MediaRecorder installed, use an Epiphan screen capture device instead. Prerequisites: - You record the full screen of the PC with MediaRecorder. - You record one screen only. - You use MediaRecorder on the Dell Precision 3551 mobile workstation. See also System requirements. Drivers For the MR screen capture option, you do not need to install device drivers. Supported Setup (Portable Lab) The table below shows the maximum supported (1) resolution, (2) frame rate (fps), and (3) recording time (hours) on a 3551 notebook. Device Resolution Frame Rate Recording Time Logitech Brio + Built-in screen capture 1920 x 1080 Other USB cameras may also work. However, it could be that you have to change the Color space to MJPG. See Show frame rate, resolution and format. You can also combine built-in screen capture with, for instance, an IP camera. Procedure - In MediaRecorder, choose File > Video Settings. - From the Video device list, select Medialooks Screen Capture. - Click the Advanced Video Settings button to select recording options. - In the Medialooks Screen Capture Properties window that opens, select the frame rate and resolution in the Output field. Although you are allowed to select a high frame rate, the actual frame rate of the recording will depend on the processor speed of your computer. Most likely this will be in the order of magnitude of 10 frames per second. - Although this window has several recording options, the use of the built-in screen capture is designed and supported to record one window on the MediaRecorder computer only. Minimize MediaRecorder after you start recording. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - The Steps To Install Mediarecorder URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-the-steps-to-install-mediarecorder Chapter: Media Recorder Important Notes Before Installation Older versions: Uninstall MediaRecorder 6.0 and older versions before you install MediaRecorder 6.5. Hardware key: Do not insert your key before the installation is complete. If you do so, other drivers are automatically installed, which may lead to incorrect functioning of the license key. Drivers of the license key should be installed using the installation USB stick. Installation Procedure Overview - Turn off automatic updates for device drivers - Select correct power options - Install MediaRecorder and device drivers Turn Off Automatic Updates for Device Drivers Aim To make sure the devices use the drivers that were tested with MediaRecorder. Background Information The general recommendation from Microsoft to use automatic updates is good, especially for security updates. However, automatic updates of hardware device drivers can sometimes give problems. MediaRecorder is tested with the device drivers that are available at the moment of the release. If device drivers are updated afterwards, we cannot guarantee that they will work properly with MediaRecorder. Therefore we recommend to switch off automatic updates of device drivers. If you ordered a computer with MediaRecorder from Noldus IT, the automatic updates for device drivers have already been turned off and you can skip this topic. Procedure - Open the Start window and type Change Device Installation Settings. - Click the tile that appears. - To the question Do you want Windows to download driver software and realistic icons for your devices?, select No, let me choose what to do. - Select Never install driver software from Windows Update. - Deselect the checkbox in front of Automatically get the device app and info provided by your device manufacturer. - Click Save Changes. Select Correct Power Options Aim To make sure the computer shuts down properly. Background Information On computers with Windows 10, by default the computer resumes rather than restarts after shutdown. This can cause problems with MediaRecorder and associated software like The Observer XT. Therefore, we recommend making sure that the computer really shuts down. Procedure - In the Windows start window with apps, type Power options and then click the Power options tile. - Choose Choose what the power buttons do. - Click Change settings that are currently unavailable. - Select the following options: - When I press the power button – Shut down. - When I close the lid – Shut down. - Under Shutdown settings, deselect the checkboxes Sleep, Hibernate, and Turn on fast startup (recommended). Install MediaRecorder and Device Drivers Aim To install MediaRecorder and, for some recording devices, their drivers. Procedure Important: Uninstall MediaRecorder 6.0 and older versions before you install MediaRecorder 6.5. - Download the installation files from my.noldus.com and extract the contents. - Browse to the file MediaRecorder [Version number] Setup.exe and double-click it. - We recommend choosing Standard as the installation type. Choose Custom only to change the location where the program is installed. - In the Drivers and tools field, choose the driver of your video device. - Click Next, accept the License Agreement, and click Install. The following setup prerequisites are installed automatically before MediaRecorder is installed: - Sentinel Run time — Needed for correct functioning of your hardware key. - Noldus LeadTools Package 21 - Noldus MediaLooks Proxy Filters 2.1 — Needed for screen capture of the monitor of the computer with MediaRecorder. - Medialooks Screen Capture 2.0.3 — Needed for screen capture of the monitor of the computer with MediaRecorder. - Microsoft .NET Framework 4.7.1 — To run MediaRecorder. This program is installed only when not already present on the computer. Activate Your MediaRecorder License A license for MediaRecorder comes with an activation key. The key determines which license options are available to you. For existing customers it is still possible to upgrade their hardware key and use this key as the license. To activate your MediaRecorder license with your activation key: - Start the MediaRecorder software and select the option Activate software license key. - Select either Floating or Fixed and click OK. What Is the Difference Between a Floating and a Fixed Activation? When you have a software license key you can choose between a Floating and a Fixed activation. - Floating activation — Choose this option if you want to be flexible about which computer you use MediaRecorder on. You can install and activate MediaRecorder on as many computers as you want, but the number of simultaneous users is limited by the number of licenses purchased. If you want to use MediaRecorder on an additional PC, the software must not be running on one of the other licensed PCs. Please note that a computer must have an internet connection to activate and work with a Floating license. - Fixed activation — A Fixed activation is linked to one specific computer. The advantage is that you do not need an internet connection to work with the software after activation. If you want to use MediaRecorder on a different computer, you must first deactivate one of the existing licenses. Please note that a computer must have an internet connection to activate or deactivate a Fixed license. Alternatively, you can activate or deactivate your license using your smartphone. Activate Your Floating License Enter your Activation key and click OK. The MediaRecorder software will now open. Activate Your Fixed License Enter the Activation key that you received with the software and select one of the following options: - Activate Online — Select this option if the PC is connected to the internet. When you click OK, the MediaRecorder software opens. - Activate Offline — Select this option if the PC does not have an internet connection. Scan the QR code with your smartphone, click WEB, enter the Computer key, and click OK. The MediaRecorder software opens. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - To Re-Enable Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-to-re-enable-settings Chapter: Media Recorder To Re-Enable Settings As soon as you select the screen capture device, it is used for the video preview and you cannot change its settings. The Output fields are grayed out. To enable these fields again: - Close the Medialooks Screen Capture Properties window. - From the Video device list choose Select video device and click Apply. Reselect the Medialooks Screen Capture device again and click the video icon to re-open the Medialooks Screen Capture Properties window (see step 3 above). You can now change the frame rate and resolution again. Note The actual resolution of the recorded file may be lower than the value set in Output. The use of built-in screen capture option is supported with a Windows text size of 100% or 125% (Control Panel > Display). If you change Windows text size to 125%, this may result in MediaRecorder capturing only part of the screen. To solve this, do the following: - Make sure MediaRecorder is not running. - Open the folder C:\Program Files\Noldus\MediaRecorder 6. - Right-click the file MediaRecorder.exe and select Properties. - Open the Compatibility tab. - Select Disable display scaling on high DPI settings and click Apply. Supported Devices MediaRecorder supports Epiphan Pearl Nano. This is an encoder device that is able to stream the output of the video card of the test computer to the computer with MediaRecorder. Audio To record audio, connect a microphone to the sound card of your computer and select that source in MediaRecorder settings. Input Epiphan Pearl Nano only uses HDMI input. Frame Rate The actual frame rate of the recorded video is limited by the bandwidth of the screen capture device. Resolution To record enough screen detail, we recommend to use signal resolution as frame size when using the screen capture device. MediaRecorder supports a resolution of 1920 x 1200. However, screen capture devices by default use the resolution of the screen of the test computer. To change the recorded resolution, change the resolution of the monitor of the test computer. Recording Video Main Topics - To get started - Select a video device - Select an audio device - Video file options - Record your videos - Options - Save the camera settings - Use commands to control video recording with other software - Picture by Picture resolution Main Steps To start working with MediaRecorder involves the following steps: - Connect all devices and, if applicable, switch them on. - If you have a hardware key, insert it into a USB port of the computer. - Start MediaRecorder. The main window now opens. The first time it opens, the preview window is black. That is because you still have to select the cameras. Proceed with the next steps to do so. - Click Video Settings to select the cameras, microphones and, optionally, the output. See: - Select a video device - Select an audio device - Video file options - Record your videos. Select a Video Device Aim To select the cameras for recording. Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You opened the Video Settings window. To do so, choose File > Video Settings, or click Video Settings in the main window. Tip: If the Video Settings button is not visible, the recording properties may be closed. Click Recording Properties at the bottom of your window. By default the recording properties are open. Procedure In the Video Settings window: - Select your camera from the Video device list. Important: If you have IP cameras, see Set up IP cameras for how to set these up and select them in MediaRecorder. If you use the Screen Capture tool, see Use of the Screen Capture tool on how to select the built-in screen capture device. - Select the preferred frame rate and resolution. The options depend on your type of camera. - For advanced camera settings, click the video symbol next to the name of your camera. The available options depend on your camera. For some cameras you can zoom and adjust settings for brightness and contrast. - Optionally change the names in the Video name column, to, for example, Webcam or IP camera. - To record audio as well, continue with Select an audio device. - Optionally adjust Video file options. - When satisfied with the settings, click OK to return to the main window and record your videos. Frame Rate and Resolution By default, the optimal combination of frame rate and resolution for the camera is selected. If you increase the frame rate, the maximum resolution available goes down and vice versa. If you select an impossible combination of frame rate and resolution and format, MediaRecorder gives a warning. Select an Audio Device Aim To select the audio source. Prerequisites - Your devices are connected to the computer with MediaRecorder, and, if applicable, switched on. - MediaRecorder is open. - You opened the Video Settings window. To do so, choose File > Video Settings, or click Video Settings in the main window. Procedure - In the Video Settings window, select the microphones under Audio device. Choose between your computer microphone, a separate microphone, or the audio stream of your camera. Choose No audio if you do not wish to record audio. - Optionally record the same audio stream in all videos. To do so, select this checkbox. It means that the device defined as Audio device 1 will supply the audio stream for all your videos. Check that the green bar is maximal when speech level is normal. Please note that in Picture-in-Picture mode, you may select which audio source to use for all the videos. This may be important if the first video is the screencapture device, which does not record audio. - Click the microphone button for Audio settings. The available options depend on your microphones. Move the sliders to adjust the recording volume. To check the recording volume, right-click the speaker icon in the bottom-right corner of your window and select Recording devices. - Optionally, change the names in the Audio name column. - Optionally, adjust the Video file options. - When satisfied with the settings, click OK to return to the main window and record your videos. Note Audio is needed and has been tested only for cameras that are supported in The Observer XT. Video File Options Aim To specify one of the following: - Format of the recording timer. See Timer format. - Maximum recording time. - Video file output: separate videos, or one video with the images from all the cameras. See Output settings. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Which Situation Applies To You? URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-which-situation-applies-to-you Chapter: Media Recorder Which Situation Applies to You? - You bought the computer, cameras and MediaRecorder from Noldus IT. The cameras are already installed. Also MediaRecorder has been set up to use with these cameras. Connect the cameras to the computer and start recording. See Connect the GigE cameras to the PC and Record video - You bought the cameras from Noldus IT and installed MediaRecorder on your own computer. The camera IP address has been set and the cameras are configured. Carry out the Procedure below but skip steps 1 and 2. - You bought the computer and cameras somewhere else. Carry out the Procedure below. Procedure - Install the Ethernet card. This is the same procedure as for IP cameras. See Install the Ethernet card in Set up IP cameras. To record from multiple cameras you can use a 4-port PCIe board. MediaRecorder has been tested with the Adlink PCIe-GIE74 Ethernet board. If you use an Adlink PCIe-GIE74 board make sure the board receives power from the PC. Connect the power connector on the board (Molex/IDE male 4-pin DC) to one of the power supplies inside the PC. Connector types vary between computers. Many computers have a SATA 15-pin power connector. Use an adapter cable with a 4-pin female Molex connector at one end and a SATA 15-pin connector at the other end. - Give the Ethernet card a fixed IP address. This is the same procedure as for IP cameras. See Set Ethernet card IP address in Set up IP cameras. - Connect the camera to the computer with MediaRecorder. See Connect the GigE cameras to the PC. - Carry out the prerequisite steps before installing MediaRecorder. See The Steps to Install MediaRecorder in Installation. - Install MediaRecorder with the camera drivers. - Set camera IP address. - Configure the cameras. MediaRecorder on My Computer You must carry out the following steps: - Install the Ethernet card. This is the same procedure as for IP cameras. See Install the Ethernet card in Set up IP cameras. If you use an Adlink PCIe-GIE74 board make sure the board receives power from the PC. - Give the Ethernet card a fixed IP address. This is the same procedure as for IP cameras. See Set Ethernet card IP address in Set up IP cameras. - Connect the camera to the computer with MediaRecorder. See Connect the GigE cameras to the PC. - Carry out the prerequisite steps before installing MediaRecorder. See The Steps to Install MediaRecorder in Installation. - Install MediaRecorder with the camera drivers. Prerequisite You have followed the entire procedure in Ethernet card setup in Set up IP cameras. - No matter how many cameras you use, you need a 1Gb Ethernet interface board (desktop computers only). - When you use a 4-port Ethernet board, you can power the cameras with Power-over-Ethernet (PoE) injectors, or you can choose to connect the board to the power outlet inside the PC. See Power over Ethernet in GigE Vision cameras. - You must use a 1-Gb Power-over-Ethernet (PoE) injector when the PC does not have a 4-port Ethernet board. Use one PoE injector per camera. - Cables: Use Cat5e or Cat6e crossover cables. - Do not use an Ethernet to USB adapter to connect the camera to the PC. Always connect the camera and the PC directly using an Ethernet crossover cable. Procedure - Using cross-network cables (Cat-5e or newer), connect the Ethernet card on the PC to the IN port of the PoE injector. Connect the camera to the OUT port. Use the short cable between the PoE injector and PC. Use the long cable between the PoE injector and camera. - Power up the PoE injector; make sure that the two CONNECT and ON green LEDs are on. If the green LEDs keep blinking, wait a few more seconds. If you see no change, disconnect the cables, then re-connect them. Notes The Power over Ethernet (PoE) injector is a device that passes power along with data (in this case, video data from the camera) via twisted-pair Ethernet cabling. If you have multiple cameras in combination with a 4-port Adlink PCIe-GIE74 board, make sure to connect the cameras one by one and assign an IP address to the camera before you connect the next camera. It is important that each camera is always connected to the same port on the Ethernet board. Each port is viewed as a network adapter, with its own IP address. The information of the linked port is stored in the driver software of each camera. If you swap cameras, they will not be recognized. Therefore, always label the Ethernet ports and the cameras. Drivers Aim To install the software that allows communication between your camera and the operating system of the computer with MediaRecorder. Prerequisites - You installed the Ethernet card. See Install the Ethernet card in Set up IP cameras. - You gave the Ethernet card a fixed IP address. See Set Ethernet card IP address in Set up IP cameras. - You carried out the prerequisite steps before installing MediaRecorder. See The Steps to Install MediaRecorder in Installation. Procedure Important: If you upgraded from a previous MediaRecorder version and have old drivers for the camera installed, uninstall them first. See To Uninstall Old Drivers. If You Did Not Yet Install MediaRecorder - Download the installation files from my.noldus.com and extract the contents. - Browse to the file MediaRecorder 6 Setup.exe and double-click it. - In the Drivers and tools field, choose Basler GigE Camera driver - pylon [version number]. - Click Next, accept the License Agreement and click Install. If You Already Installed MediaRecorder Follow the instructions in If You Did Not Yet Install MediaRecorder and choose Modify in the installation window. Select Basler GigE Camera driver - pylon [version number] and click Update. Alternatively: - Download the installation files from my.noldus.com. - Browse to Drivers\Basler\5.0.9.10388. - Double-click the file Basler_pylon_5.0.9.10388. - Agree to the terms in the License Agreement. - In the Profiles window, choose Camera user and click Next. - As camera type, choose GigE and click Next. - Optionally, change the location where the camera drivers are stored and choose Next > Install. To Uninstall Old Drivers - Open the Control Panel. - Choose Programs and Features. - Select the Basler camera driver and choose Uninstall. Set Camera IP Address Aim To make sure that the IP address of the GigE camera and the Ethernet interface board physically connected to that camera match. This ensures reliable data transfer to and from the camera. Prerequisites - You followed the procedure in Ethernet card setup. - You connected the camera. This is the same procedure as connecting an IP camera. See Connect IP cameras to the PC in Set up IP cameras. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Wireless Microphone URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/media-recorder/page/phenotyper-xt-18-service-wireless-microphone Chapter: Media Recorder Wireless Microphone MediaRecorder supports the Sennheiser EW 312 G3 B series wireless microphone set. Use this wireless microphone set when there is more than one test participant, and/or the participants are moving. The microphone set comes with a clip-on microphone and a receiver. The wireless microphone receiver continuously switches between antennas, checks which antenna picks up the strongest signal and selects this one. This means that the antennas can be mounted at different places. If for example the reception is poor when the wireless microphone is in the experiment room, you could decide to install one antenna in this room. If the quality of the received signal is bad, for example if the signal has to go through a wall, you can use the special coax cable for extending the antennas (50?). In general you want both antennas to use the same cable length. It is recommended to position the two antennas at an angle of 90º. No phantom power is needed for the wireless microphone. The signal that comes from the receiver is preamplified. MediaRecorder also supports the Nikon ME-W1 microphone. This microphone has been tested in a portable lab set-up with a Dell 3551 notebook and Axis P1375 cameras. For more information see Recording devices. Audio Mixer With an audio mixer you can adjust the audio streams before they go to MediaRecorder. Furthermore, you can combine the audio streams from two or more microphones. MediaRecorder supports the following audio mixers: - Extron DMP 64 - Extron DMP 128 Summary Supported Devices - Supported devices for EthoVision XT - Supported devices for The Observer XT - stationary set-up - Supported devices for The Observer XT - portable set-up - Supported devices for FaceReader - Summary supported devices Supported Devices for EthoVision XT The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) color space, (4) number of devices and (5) recording time (hours). All tests were carried out on a Dell Precision T3640 PC with a Euresys Picolo Alert card, card driver MultiCam 6.15.13573. When four cameras were tested in one recording, separate videos were made. Device Resolution Frame Rate Color Space No of Devices Recording Time Ikegami B/W ICD-49 PAL 768 x 576 YUY2 / RGB32 0.5 Panasonic WV-CP504 NTSC 640 x 480 YUY2 0.5 Analog PAL/CCIR (separate videos) 768 x 576 Analog NTSC/EIA (separate videos) 640 x 480 Basler USB acA1920-155um 1920 x 1200 / 1920 x 1080 / 800 x 600 Y800 0.5 Basler USB acA2040-90uc* 2040 x 2046 Y800 Basler acA2040-90uc* 2040 x 2046 Basler acA2040-90uc** 2040 x 2046 Basler acA2040-90uc (on Dell 3541 notebook) 1920 x 1200 Basler acA1300-60gm mono 1280 x 1024 / 1024 x 768 / 800 x 600 / 640 x 480 Y800 0.5 Basler acA1300-60gm mono 1284 x 1025 Y800 Basler acA1300-60gm mono 1280 x 1040 Y800 Basler acA1300-60gm mono 960 x 640 Y800 Basler acA1300-60gm mono* 1280 x 960 Y800 Basler acA1920-40gc color 1920 x 1200 RGB32 Axis M1075-L 1920 x 1080 - * Tested with output quality settings EthoVision and DanioVision. - ** Tested with output quality setting EthoVision. Important: The file size of an 8, 10, 16, 18, 24 and 60 hours recording is very large. Supported Devices for The Observer XT - Stationary Set-Up The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices and (4) recording time (hours). Tests were done on a Dell Precision T3620 PC. Device Resolution Frame Rate Number of Devices Recording Time Axis M5525 (separate videos, line-in audio and camera audio*) 1920 x 1080 Axis M5525 (Picture-by-picture & Picture-in-picture, line-in audio) 1920 x 1080 Axis M5054 1280 x 720 Axis M1065-L (separate videos, line-in audio and camera audio) 1920 x 1080 Axis M5525 + M1065-L (separate videos, line-in audio and camera audio) 1920 x 1080 2+2 Axis M5525 + Epiphan Pearl Nano (separate videos, line-in audio and camera audio (broadcaster no audio)) 1920 x 1080 3+1 Axis M1065-L + Epiphan Pearl Nano (do NOT use Picture-in-picture or picture-by-picture) 1920 x 1080 3+1 Axis M5525 + M1065-L + Epiphan Pearl Nano (separate videos, line-in audio and camera audio (no audio broadcaster)) 1920 x 1080 1+2+1 * Camera audio = audio over RTSP Supported Devices for The Observer XT - Portable Set-Up The table below shows the maximum supported (1) resolution, (2) frame rate (fps), (3) number of devices and (4) recording time (hours). Tests were done on a Dell 3551 notebook. Device Resolution Frame Rate Number of Devices Recording Time Axis M1075-L (separate videos, line-in audio and camera audio*) 1920 x 1080 Axis M1075-L (Picture-by-picture and Picture-in-picture, line-in audio and camera audio) 1920 x 540 Axis M1075-L + Epiphan Pearl Nano (separate videos, line-in audio and camera audio (no audio broadcaster)) (do NOT use picture-by-picture or picture-in-picture) 1920 x 1080 1+1 Axis P1375 + Nikon ME-W1 microphone (separate videos, picture-by-picture & picture-in-picture, camera audio only) 1920 x 1080 Axis P1375 + Epiphan Pearl Nano + Nikon ME-W1 microphone (separate videos, picture-by-picture & picture-in-picture (broadcaster view in camera view), camera audio only) 1920 x 1080 1+1 Logitech Brio* (separate videos, Picture-by-picture & Picture-in-picture, camera audio only) 1920 x 1080 Logitech Brio* 4096 x 2160 0.5 Logitech Brio* + Epiphan Pearl Nano (separate videos, Picture-by-picture & Picture-in-picture, line-in audio) 1920 x 1080 1+1 Logitech Brio* + Epiphan Pearl Nano (separate videos, Picture-by-picture & Picture-in-picture, Logitech Brio microphone) 1920 x 540 1+1 * When using the Logitech Brio camera you have to change the Color space to MJPG. See Show frame rate, resolution and format. Supported Devices for FaceReader MediaRecorder videos from all the supported devices can be analyzed by FaceReader, but the files from the individual devices have not been tested with this program. It is important to select FaceReader RPPG as the output quality setting if you use the Remote Photo Plethysmography module in FaceReader. The recorded videos are only slightly compressed with this setting for optimal analysis of heart rate and heart rate variability. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## N-Linx - Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/n-linx-installation Chapter: NoldusHub Installation Installation involves the following steps: - If The Observer XT, N-Linx Server and Application 2 are not all installed on the same computer, disable Windows Firewall for the N-Linx port on all computers with N-Linx components. - Install The Observer XT. - Install N-Linx Server. - Install Application 2. - Install N-Linx Agent on the computer with Application 2. Select Application 2 in the N-Linx Agent installation window. - Connect The Observer XT to N-Linx Server. - Connect N-Linx Agent to N-Linx Server. - Connect Application 2 to N-Linx Server. - Select Application 2 in The Observer XT. Disable Windows Firewall for N-Linx Port N-Linx by default makes use of port 5672. Inbound and outbound traffic through this port should not be blocked by Windows Firewall. Therefore, disable Windows Firewall for this port on all computers with N-Linx components, including the computers with The Observer XT and Application 2. If port 5672 is in use by another program, choose another port in all N-Linx components and disable Windows Firewall for that port instead. If all components are installed on the same computer, it is not needed to carry out this procedure. Procedure: - Open the Control Panel and select Windows Firewall. - On the left side of the window, click Advanced Settings. - Click Inbound Rule and click New Rule in the Actions pane. - In the New Inbound Rule Wizard window that opens, select Port and click Next. - Select TCP and enter 5672 in the Specific local ports field and click Next. - Click Allow the connection and click Next. - Select to which network the rule applies and click Next. - Give the rule a name, for example N-Linx connection, and click Finish. - Check in the Inbound Rules window that this rule is set to Enabled. - Click Outbound Rule and click New Rule in the Actions pane. - Repeat steps 4 to 9 for the outbound rule. - Close all Control Panel windows. Install The Observer XT - Double-click the file The Observer XT [version number] Setup.exe on the installation USB stick of The Observer XT. - Choose Standard as installation type, unless you want to change the default program location, and click Next. - Accept the terms in the End-User License Agreement and click Install. - When installation is finished, click Close. Install N-Linx Server N-Linx Server may be installed on any computer in the network. It may also be installed on the same computer as The Observer XT or Application 2. - Double-click the file N-Linx Server Setup.exe. You find this file on The Observer XT installation USB stick in the folder Drivers and Tools/N-Linx Server. - Choose Standard as installation type, unless you want to change the default program location, and click Next. - Accept the terms in the End-User License Agreement and click Install. - When installation is finished, click Close. Install Application 2 Install the application that The Observer XT must control, for example Media Recorder. Consult the documentation of the application for the procedure. Also consult this documentation for extra procedures. For example, for FaceReader the folder with video files must be shared. Install N-Linx Agent N-Linx Agent must be installed on the same computer as Application 2. At present, this is the computer with Media Recorder, BIOPAC AcqKnowledge, or Tobii Pro Studio. Important: To use The Observer XT with FaceReader or Viso, it is not needed to install N-Linx Agent. - Double-click the file N-Linx Agent Setup.exe. You find this file on The Observer XT installation USB stick in the folder Drivers and Tools/N-Linx Agent. - Choose Standard as installation type, unless you want to change the default program location, and click Next. - In the Plugins field, select the application that N-Linx Agent must control and click Next. - Accept the terms in the End-User License Agreement and click Install. - When installation is finished, click Close. Connect The Observer XT to N-Linx Server - In The Observer XT, choose File > Preferences > N-Linx Settings. --- ## N-Linx - Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/n-linx-installation-ABk Chapter: NoldusHub Installation Connect The Observer XT to N-Linx Server - Select Use N-Linx server to connect with other applications. - In the N-Linx Server address field, enter the computer name of the computer with N-Linx Server. If N-Linx Server is on the same computer as The Observer XT, leave the default entry localhost. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. Choose the same port number in all N-Linx components and create exceptions in Windows Firewall for this port. - Click Test connection. If the connection with N-Linx Server is established, the Status will change to Connected. Viso To import Viso sessions, the procedure is slightly different. - Choose File > Preferences > Viso Settings. - Select Use Viso Services to connect with Viso. - Enter the connection details of the computer with Viso Services and click Test connection. - See File Management > Import Viso Sessions in The Observer XT Help for details. To open The Observer XT Help, press F1 in the program. Connect N-Linx Agent to N-Linx Server - Click the arrow in the bottom-right corner of the screen of the computer with Application 2 and N-Linx Agent. This opens the system tray. - Double-click the N-Linx Agent icon. - In the N-Linx Server Address field, enter the computer name of the computer with N-Linx Server. If N-Linx Agent is installed on the same computer as N-Linx Server, enter localhost. It is also possible to enter the IP address, but the IP address of the computer with N-Linx Server must be fixed. Ask your system administrator for assistance. - Click Connect. The status in the bottom-left corner of the window should become Connected. To Find the Computer Name To find the name of the computer with N-Linx Server, open the Control Panel and choose System. The Computer name field lists the name. To Change the Port N-Linx Agent by default uses port 5672 to communicate with N-Linx Server. If this port is in use, type the new port after a colon in the N-Linx Server Address field. Important: Select the same port in all components that communicate with N-Linx Server. Also, disable Windows Firewall for this port. Connect Application 2 to N-Linx Server Consult the documentation of Application 2 for the procedure. See the following documentation: - Media Recorder – Media Recorder with The Observer XT in the Media Recorder Help. - FaceReader – FaceReader with The Observer XT in the FaceReader Help. - Viso – The Viso Setup Manual. - BIOPAC AcqKnowledge – The Technical Note - BIOPAC MP System - The Observer XT. - Tobii Pro Studio – The Technical Note - Tobii Pro Studio - The Observer XT. To Find This Documentation To open an application's Help, press F1 in the program or double-click the Help icon on the desktop of the computer that contains the application. The Technical Notes are present on The Observer XT installation USB stick in the folder Documentation. The Viso Setup Manual is present on the Viso installation USB stick. Select Application 2 in The Observer XT - In The Observer XT, choose Setup > Project Setup. - Under Observation source, select Live Observation. The Devices window will open. If not, click the Devices button. - Select the checkbox in front of [Name Application 2][Computer name] and click Edit Settings. - In the case of Media Recorder, Tobii Pro Studio, and BIOPAC AcqKnowledge, the application will open if it is not already open. Continue with the next step. In the case of FaceReader, a window with settings opens. Select the settings. To run multiple instances of FaceReader, enter a unique name in the Identify device as field. Skip the next step. - Click Edit Settings again. To run multiple instances of Application 2, enter a unique name in the Identify device as field. - Click OK. Consult the documentation of Application 2 for detailed procedures. Control Your Application with The Observer XT Carry out your observation in The Observer XT. See Carry out your observation in The Observer XT Help for the procedure. Press F1 in the program to open the Help. For detailed procedures on using The Observer XT with your application, consult the following documentation: - Media Recorder – Media Recorder with The Observer XT in the Media Recorder Help. - FaceReader – FaceReader with The Observer XT in the FaceReader Help. - BIOPAC AcqKnowledge – The Technical Note - BIOPAC MP System - The Observer XT. - Tobii Pro Studio and Tobii Pro Lab – The Technical Note - Tobii Pro Eye Trackers - The Observer XT. Source: N-Linx Reference Manual, Noldus Information Technology --- ## N-Linx - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/n-linx-introduction Chapter: NoldusHub Introduction What Is N-Linx? N-Linx is a network communication protocol that is developed for Noldus software. At present it is used to control an application with The Observer XT and to transfer data from the application to The Observer XT. As an example, N-Linx is used to start and stop video recording with MediaRecorder by starting and stopping an observation in The Observer XT. Also, N-Linx is used to start and stop FaceReader analysis with an observation in The Observer XT and to transfer FaceReader analysis data and independent variables to The Observer XT. Components N-Linx communication is done by two components: N-Linx Server and N-Linx Agent. N-Linx Server receives information from one application and sends it to another one. N-Linx Agent starts the application when it is not already running and forwards commands from N-Linx Server to the application. Connections The Observer XT and N-Linx Server can be installed on any computer in the network. N-Linx Agent and Application 2 must be installed on the same computer. The following describes the data streams in an N-Linx setup: - The Observer XT sends a command to N-Linx Server. - N-Linx Server forwards the command to N-Linx Agent, or directly to Application 2. - N-Linx Agent starts Application 2, if it is not already open. It also sends commands to Application 2, for example Start Data Acquisition, or Start Video Recording. - Application 2 sends its data to N-Linx Server. - N-Linx Server forwards the data to The Observer XT. Which Applications Work with N-Linx? At present the following setups are supported: - The Observer XT with MediaRecorder - The Observer XT with FaceReader - The Observer XT with Viso - The Observer XT with BIOPAC AcqKnowledge - The Observer XT with Tobii Pro Studio and Tobii Pro Lab The Observer XT with MediaRecorder Version numbers: - The Observer XT 13 or higher - MediaRecorder 4 or higher The following is obtained: - When you create a new Observation, MediaRecorder starts and loads a configuration. - When you start an Observation, MediaRecorder starts recording. - When you stop an Observation, MediaRecorder stops recording. - The recorded videos are automatically linked to the observation in The Observer XT and synchronized with the events. See Media Recorder with The Observer XT in the Media Recorder Help for details. The Observer XT with FaceReader This setup works without N-Linx Agent. Version numbers: - The Observer XT 14.0 or higher - FaceReader 7.0 or higher The following is obtained: - When you create an observation in The Observer XT, FaceReader creates a participant with a camera analysis. - When you start an observation in The Observer XT, FaceReader starts analyzing. - When you stop an observation in The Observer XT, FaceReader analysis stops. - The FaceReader data are imported into the observation of The Observer XT. - The FaceReader data are synchronized with the Event Log. - The FaceReader independent variables are imported into the Independent Variables list of The Observer XT. - FaceReader videos are imported into the observation of The Observer XT and synchronized with the data (with The Observer XT 14.1 or higher and FaceReader 7.1 or higher). See FaceReader with The Observer XT in The FaceReader Help for details. The Observer XT with Viso Version numbers: - The Observer XT 12.5 or higher - Viso 2 or higher The following is obtained: - Viso Sessions can be imported directly from Viso, without exporting them as .odx files first. The Observer XT with BIOPAC AcqKnowledge Version numbers: - The Observer XT 14.1 or higher - BIOPAC AcqKnowledge 5.0.2032 or higher The following is obtained: - When you start an observation, AcqKnowledge starts physiological data acquisition. - When you stop an observation, AcqKnowledge stops physiological data acquisition. - The physiological data are imported into the observation of The Observer XT and synchronized with the events. See the Technical Note - BIOPAC MP System - The Observer XT for details. You can find this technical note on The Observer XT installation USB stick or download it from the Noldus website. The Observer XT with Tobii Pro Studio and Tobii Pro Lab Version numbers: - The Observer XT 14.1 or higher - Tobii Pro Studio 3.4.7 - Tobii Pro Lab 1.98 The following is obtained: - When you start an observation, eye tracking starts. - When you stop an observation, eye tracking stops. See the Technical Note - Tobii Pro Eye Trackers - The Observer XT for details. You can find this technical note on The Observer XT installation USB stick or download it from the Noldus website. Using Your Own Application with N-Linx Noldus IT offers two N-Linx SDKs to build your own setup with a Noldus application, for example to start your application when The Observer XT starts an observation. An SDK is available for application Start and Stop and an SDK for Event and continuous data. Contact your Noldus sales representative for the possibilities. Support If you have any problems, questions, remarks or comments, please contact us through the Noldus website and fill out a Support Request Form (preferred) or phone us during normal working hours. Contact details are available at the support section of the Noldus website. --- ## NoldusHub - Advanced Settings and Reference URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-advanced-settings-and-reference Chapter: NoldusHub Interpretation of Phasic EDA Responses Phasic EDA responses are invoked by the sympathetic branch of the ANS. This part of the ANS regulates adaptive involuntary responses to physiological and psychological stressors in preparation of a fight-or-flight response. Sweating is one such adaptive physiological response. The frequency of phasic EDA responses indicates the magnitude of sympathetic ANS activation. This explains why momentary phasic response frequency is associated with self-reports of momentarily experienced anxiety (Strohmaier et al, 2020). As the rate of involuntary phasic EDA responses is proportional to levels of experienced emotion or anxiety, it has gained popularity in psychological studies of unconscious or unexpressed emotional responses to anxiety triggers. However, it should be noted that EDA does not relay information on the quality of the emotion that is experienced. The phasic EDA peak constitutes an isolated single peak. The number of phasic EDA responses per minute is used as a measure for the magnitude of the ANS activation during the measurement period. In practice, multiple EDA responses are stacked if these are triggered at high frequencies. Stacking of phasic responses may be observed for phasic responses triggered at high frequencies. Subsequent stacked peaks typically have lower amplitudes because of the physiological constraint posed by the maximum achievable diameter of sweat ducts. However, these smaller stacked peaks reflect similar elevations of ANS arousal as any other phasic peak. Signals Present in NoldusHub In NoldusHub, the available EDA signals are: - EDA peak rate - the number of phasic skin conductance responses per minute (unit-free). - EDA tonic - the skin conductance baseline (in µS). NoldusHub EDA Algorithms NoldusHub automatically performs a number of data processing steps to obtain tonic EDA and peak rates: - Short-lived data artefacts in the raw data are removed by median filtering. - The tonic EDA signal is assessed. - To obtain baselined phasic responses, the tonic EDA signal is subtracted from the raw signal. - The theoretical stimulus onset times that invoked phasic EDA responses are identified on the basis of phasic response shapes. To achieve this, the prototypical shape of a human phasic EDA response to known visual stimuli (Bach et al., 2010) is used as the point-spread function in one-dimensional Wiener deconvolution. - For each theoretical stimulus onset time, the subsequent EDA peak-time is obtained at maximum amplitude. - The average phasic peak rate per minute is calculated from the identified peak times. Why Deconvolution as a Peak-Detection Algorithm? Deconvolution allows for the detection of stacked EDA peaks and reveals the point stimulus event times that invoked the phasic EDA responses. These stimulus events may have been external (stimuli) or endogenous (psychological events). Therefore, not every identified phasic response has a stimulus onset time that coincides with an actual external stimulus event. An additional advantage of deconvolution is that it is not sensitive to differences in peak amplitude. This also allows for better detection of trains of stacked EDA peaks. Artefact peaks that do not resemble phasic EDA responses are not identified as peaks by deconvolution, in contrast with algebraic peak-detection algorithms. Keep in Mind To align with common practice in the scientific community, the EDA peak rate calculated in NoldusHub uses peak times, not stimulus onset times. To identify phasic peaks using deconvolution, a peak should be fully revealed in the conductance measure because the peak is recognized on the basis of its entire shape. NoldusHub offers a real-time analysis of phasic EDA responses. However, the 30-second duration of typical phasic EDA responses explains the delay observed for EDA signals in the Live data viewer. The same EDA visualizations in Replay mode are in-sync with all other signals. EDA References - Bach, D.R.; Flandin, G.; Friston, K.J. and Dolan, R.J. (2010). Modelling Event-Related Skin Conductance Responses. International Journal of Psychophysiology, 75: 349–356. - Strohmaier, A.R., Schiepe-Tiska, A. and Reiss, K.M. (2020). A Comparison of Self-Reports and Electrodermal Activity as Indicators of Mathematics State Anxiety. An Application of the Control-Value Theory. Frontline Learning Research, 8: 16–32. Heart Rate Data The availability of different heart rate data signals depends on your version of NoldusHub (v1.4 or v1.6). Two Methods to Measure Heart Rate Data NoldusHub measures heart rate data based on two methods that give similar results but have important differences. The two methods are: - Photoplethysmography (PPG) - Electrocardiography (ECG) ECG ECG determines the heart rate by measuring the electrical signals coming from the heart. It is a reference signal for health assessment and for research. For measurement, several electrodes are placed on the chest. Each electrode has its own signal, which can be found in NoldusHub under the names Lead I, Lead II, and Lead III. PPG PPG determines heart rate by measuring changes in light reflection or transmission through the skin due to blood volume changes. It is generally measured with a single sensor on a finger or an ear lobe. Raw and Derived Signals Due to the fact that blood must travel through the body, the peaks in the PPG signal are later than the peaks in the ECG signal. - Heart rate is the number of peaks per minute. - Interbeat interval (IBI) is the number of milliseconds between two heartbeats. Differences Between ECG and PPG Data - ECG: Direct measurement via electrical current from the heart; reference signal for health; invasive with several sensors on the chest; accurate; sharp peak enabling accurate pulse detection; data obtained accurately using a small time window and real-time signal. - PPG: Indirect measurement via reflection by blood volume; uses ECG as ground truth for research; non-invasive with one sensor on ear lobe or finger; sensitive to noise and movement; broad peak making pulse detection less accurate; requires a time window of several minutes for accurate data. Signals Present in NoldusHub - Heart Rate PPG Signals - Heart rate (BPM): The number of peaks (heartbeats) per minute. - Interbeat interval (ms): The number of milliseconds between two heartbeats. - Raw data: The raw PPG signal. ECG Signals - Heart rate (BPM): The number of peaks (heartbeats) per minute. - Interbeat interval (ms): The number of milliseconds between two heartbeats. - Lead 1 (mV): The ECG vector signal measured from RA to LA. - Lead 2 (mV): The ECG vector signal measured from RA to LL. - Lead 3 (mV): The ECG vector signal measured from LA to LL. This is derived by subtracting Lead 1 from Lead 2. - Vx (mV): The ECG vector signal measured from the average of the RA, LA, and LL to the V electrode. For more details on the Lead and Vx signals, consult the Shimmer ECG user guide. Heart Rate Data Processing Heart rate data are preprocessed in the following way: - High pass filter: Data below 0.5 Hz is not included. - Notch filter: To remove artefacts caused by the power frequency, the 50 Hz (Europe) or 60 Hz (USA) frequency band is not included. Eye Tracking Data The availability of different eye tracking data signals depends on your version of NoldusHub (v1.4, v1.6, or v1.7). Gaze Overlay Gaze data is visualized in NoldusHub through the gaze overlay on the screen video in the Screen Video pane inside the Record and Replay page. Gaze data consists of two parts: fixations and saccades. Fixations are visualized with a pink dot; the line following the dot represents the saccades. What Are Fixations and Saccades? The moments that our eyes focus on something are called fixations. The duration of fixations varies between roughly 50 ms and 1 second. During a fixation, gaze points sampled by an eye tracker are close together. Fixations are alternated with saccades, which are rapid eye movements from one fixation to another. Saccades last much shorter than fixations, roughly 30 to 80 ms. How Does NoldusHub Calculate Fixations? NoldusHub uses the I-DT (Identification by Dispersion-Threshold) fixation algorithm published by LC Technologies, which is a variant of the fixation algorithm described by Salvucci and Goldberg (2000). In NoldusHub, a fixation is recorded if gaze points are within 20 pixels of the fixation center for a minimum duration of 5 samples. For an eye tracker that samples at 60 Hz, this corresponds to 83 ms. The I-DT Fixation Algorithm in NoldusHub The I-DT fixation algorithm makes use of two thresholds: - Dispersion threshold: Determines the maximum distance between a gaze point and the average of all gaze points in a fixation. The default dispersion threshold in NoldusHub is 20 pixels. - Duration threshold: Determines the minimum duration that gaze points should be within the dispersion threshold to become a fixation. The default duration threshold in NoldusHub is 5 samples. For an eye tracker sampling at 60 samples per second, this means 83 ms. The algorithm proceeds as follows: - At t1, five gaze points are recorded. They are all within the dispersion threshold. The duration threshold is exceeded and a fixation is recorded. - At t2, another gaze point is recorded. The average gaze point moves slightly. All gaze points are still within the dispersion threshold and belong to the same fixation. - At t3, another gaze point is recorded. The average gaze point moves. The distance between the new gaze point and the average gaze point exceeds the dispersion threshold. The fixation ends and a saccade is recorded. Gaze Point Validity NoldusHub calculates the gaze point using the average of both eyes and takes into consideration the validity of samples received from the eye tracker. Validity is defined as either Valid or Invalid. NoldusHub discards samples where the X or Y value is NaN: - If samples for both eyes are valid and none of the values are NaN, the average is calculated. - If the validity for one eye is Invalid or there are NaN values, the other eye (valid and without NaN values) is used. - If both eyes have NaN values or are invalid, the gaze point is set to a fixed [NaN, NaN] point. About Gaze Data Coordinates Fixation and gaze points are positioned in a 2D field on the user display area. The user display area can be a computer screen or, for example, an area of a shopping shelf as seen through mobile glasses. NoldusHub uses the Tobii Pro eye tracker reference system. The 2D field is mapped to normalized coordinates for X and Y (floating point values between and including 0.0 and 1.0). Point (0, 0) denotes the upper left corner and point (1, 1) indicates the lower right corner. - Fixation X: The X coordinate of the fixation center, a floating point value from 0.0 to 1.0. - Fixation Y: The Y coordinate of the fixation center, a floating point value from 0.0 to 1.0. - Fixation status: Can be undefined, fixation, or saccade. Indicates whether the eye is moving or not. If the eye is moving, the status is saccade. If the eye is not moving, the status is fixation. Undefined is shown if it is unknown whether the eye is moving or not. - Gaze X: The X coordinate of the gaze point, a floating point value from 0.0 to 1.0. - Gaze Y: The Y coordinate of the gaze point, a floating point value from 0.0 to 1.0. - Validity: Can be valid, invalid, or indeterminate. Indicates the validity of the gaze origin data. Pupil Size Data Besides gaze coordinates, Tobii eye trackers also produce pupil diameter data. Tobii eye trackers calculate pupil diameters (in millimeters) from images of the eyes. NoldusHub uses these pupil diameters, in combination with light intensity measures, to calculate the relative contributions of light and cognitive processes to the pupil diameter. All these measures are available in the Cognitive Load signal group. Eye Tracking References - Salvucci, Dario D., and Joseph H. Goldberg. "Identifying fixations and saccades in eye-tracking protocols." Proceedings of the 2000 Symposium on Eye Tracking Research & Applications. ACM, 2000. - Voßkühler, Adrian, et al. "OGAMA (Open Gaze and Mouse Analyzer): open-source software designed to analyze eye and mouse movements in slideshow study designs." Behavior Research Methods 40.4 (2008): 1150–1162. - Blignaut, Pieter, and Tanya Beelders. "The effect of fixational eye movements on fixation identification with a dispersion-based fixation detection algorithm." Journal of Eye Movement Research 2.5 (2009). - Camilli, M., Nacchia, R., Terenzi, M. and Di Nocera, F. ASTEF: A simple tool for examining fixations. Behavior Research Methods, 40.4 (2008): 373–382. - Shic, F., Chawarska, K. and Scassellati, B. The incomplete fixation measure. Proceedings of the 2008 Symposium on Eye Tracking Research & Applications, ACM, 111–114, 2008. Cognitive Load Cognitive Load in NoldusHub NoldusHub uses pupil sizes and ambient light fluctuations to estimate cognitive load. Ambient light fluctuations are estimated from the light intensities of the participant screen when using a remote eye tracker bar. When using head-mounted eye trackers, the forward-facing camera is used to measure ambient light intensity. Eye trackers are also used to measure pupil sizes. Therefore, cognitive load is only calculated when using an eye tracker and capturing the participant screen or using forward-facing cameras. Cognitive load calculations require heavy usage of system resources. Source: NoldusHub 1.8 Reference Manual --- ## NoldusHub - Guides and Procedures URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-guides-and-procedures Chapter: NoldusHub Set up devices and test stations for a project Aim To set up measurement devices and test stations. Before you begin The devices and test stations functionality depends on your user role: - As an Administrator you can set up devices and test stations for any project. - As a Researcher you can set up devices and test stations for projects you created yourself and for projects shared with you as a member. - As a User you can set up devices and test stations for projects shared with you as a member. Navigate to the project for which you want to set up the devices and test stations. Note: Devices and signals are logically connected A device and its signals are logically connected in NoldusHub. When you switch off a device, all its connected signals are also automatically switched off. And vice versa, when you switch off all signals for a device, the device itself is also switched off. The same applies to switching on: When you switch on a device, all its signals are also switched on. So, for example, when you switch off an Eye tracker device, the Gaze signal is automatically switched off. Or the other way around: When you switch on a Screen video device, the Screen video signal is also switched on. Procedure - If you want to set up a test station other than the first, click on the appropriate test station to collapse its details. - Switch on or switch off the signals and devices toggles to select or unselect them for your project. For example, switch on the Gaze signal and switch off the Screen video signal. What's next? You can calibrate an eye tracker for your project or jump right in to record a session. Connect biosensor to Participant PC Aim To connect a biosensor to a Participant PC. See Supported devices for a list of our currently supported eye trackers, biosensors and webcam. Note If your devices won't connect check out our FAQ for troubleshooting. If your issue or question is not covered, get in contact with Noldus Support through https://my.noldus.com/login. They will be happy to help you. Procedure - Turn on the Participant PC and log in. - Open N-Linx Agent on the Participant PC. - Click Add plugin. Browse to the location of the plugins. - Select Shimmer physiology.nlp and click Open. - Take the biosensor out of its dock and turn it on. - Start the Shimmer ConsensysSytemTray software by clicking the icon in the taskbar. The active Consensys icon now appears in the list of active programs at the bottom-right. - Right-click the Consensys icon, and select the correct Shimmer sensor. See the Device ID at the bottom of the sensor. - Select Start. The selected sensor status will change from Connecting to Streaming. - Check in NoldusHub on the Test leader PC that all devices are connected properly. If not, check out our Frequently Asked Questions section (FAQ). - If your participant arrives, connect the leads/electrodes to the participant. What's next? You can record a session. Calibrate eye tracker Aim To calibrate an eye tracker device to ensure recordings are as accurate as possible. Before you begin The calibrate functionality depends on your application-level user role: - As an Administrator you can calibrate eye trackers for any project. - As a Researcher you can calibrate eye trackers for projects you created yourself and projects shared with you as a member. - As a User you can calibrate eye trackers for projects shared with you as a member. Ask a colleague or co-worker to assist you as a participant because calibration is an interplay between a Test leader PC and the Participant PC. Navigate to the record page of the test station inside your project for which you want to calibrate the eye tracker. Note Calibration starts from the Test leader PC. Each procedure step indicates who, you or the participant, must execute the step. Check the Frequently Asked Questions (FAQ), if you run into trouble. Procedure - You: Ask the participant to take place at the Participant PC and to follow the instructions on the screen. - You: Click Record Session. NoldusHub asks whether you want to calibrate the eye tracker or skip the calibration and start recording. If you skip calibration, the calibration that was stored last will be used. In this case, click Calibrate. You can dismiss the notification for a certain amount of time. To bring back the notification click the notifications icon. A list appears of all dismissed notifications. Find the notification you want to bring back and click Cancel. OR Click the menu icon and select Calibrate in the Screen video pane. NoldusHub shows a Welcome screen for starting the calibration at the test station (Participant PC). - Participant: Follow the instructions that are shown on the screen of the Participant PC. They have to click on Start. - Participant: Once the calibration is finished, click Close. NoldusHub shows the Calibration results pop-up on the test leader PC. - You: If calibration succeeded, click ACCEPT. OR If calibration failed, click Recalibrate and repeat steps starting from step 3. Some tips on how to calibrate your eye tracker successfully can be found in the FAQ section. What's next? You can set up other users as members for your project or jump right in to record a session. Select project members Aim To share your project with co-workers. Background User types NoldusHub distinguishes application and project-level users. See User management for more information about the differences. Project member roles and permissions As the creator of the project, you are immediately assigned the Owner role. You can select users to add them as an Editor. If a user is not an administrator on the application level they will have to be invited as an Editor in order to see the project. The rights of editors are equal to the rights of the owner. - Owner: The project member has all project rights. - Editor: The project member has all project rights. Before you begin The sharing project functionality depends on your application-level user role: - As an Administrator you can select members for any project. - As a Researcher you can select members for projects you created yourself and projects shared with you as a member. - As a User you can select members for projects shared with you as a member. The project member you want to select must already be available as an application-level user. You need to determine what project member role the new project member needs. Navigate to the project for which you want to select members. Procedure Select member(s) for a project - Navigate to the members page by clicking Project members in the Setup section. - Click Share project. - To open the user list, click in the Choose members field. - Optional: To narrow down the list, enter the first characters of the username of the user you want to add. - Select the user you want to add to your project. - Optional: To add other members, repeat steps 3–5. - Click Save. Delete a member from a project - Navigate to the Project members page by clicking Project members in the Setup section. - Scroll to the member you want to delete and click the corresponding delete icon. - Click Yes. What's next? A logical next step would be to record a session. Record a session for a project (v1.6–v1.7) Aim To record a session for your research project. Before you begin The record functionality depends on your application-level user role: - As an Administrator you can record a session for any project. - As a Researcher you can record a session for projects you created yourself and for projects shared with you as a member. - As a User you can record a session for projects shared with you as a member. Navigate to the record page of the test station inside your project for which you want to record a session. Make sure you have connected your devices to the Participant PC. Note: Resizing panes The panes of the Record page can be resized and relocated to your preference. You will have to redo the resizing and relocating every time you visit the page as your preferences are not stored. You have the following options: - Hover with the mouse over the lower right corner of the panes that you want to resize. Click and drag the panes to your preferred size. Note that there should be free space available if you want to make the pane larger, otherwise it will not be resized. - Hover with the mouse over the title bar and click and drag the pane to your preferred location. Note that there should be free space available where you want to place the pane, otherwise it will not be relocated. Procedure - Optional: NoldusHub records all available data signals by default, but you can click the select signals icon if you want to select specific data signals to be visualized or not. - Select or clear the data signal checkboxes you want to select or deselect. - Click Start Recording. NoldusHub asks whether you want to calibrate the eye tracker. Click Start calibration to start calibrating the eye tracker, and tell the participant to follow the instructions on their screen. Click Skip and start recording to start recording straight away; NoldusHub will use the latest stored calibration. - Instruct the participant to perform the requested actions at the recording test station. - When the participant has finished the requested actions, click Stop Recording. Note: Beware that there is no going back once you click Stop Recording. It is not possible to resume your recording. - Enter a name for the recorded session and click Save. What's next? A logical next step would be to replay your recorded session. Record a session for a project (v1.4) Aim To record a session for your research project. Before you begin The record functionality depends on your application-level user role: - As an Administrator you can record a session for any project. - As a Researcher you can record a session for projects you created yourself and for projects shared with you as a member. - As a User you can record a session for projects shared with you as a member. Navigate to the record page of the test station inside your project for which you want to record a session. Make sure you have connected your devices to the Participant PC. Note: Resizing panes The panes of the Record page can be resized and relocated to your preference. You will have to redo the resizing and relocating every time you visit the page as your preferences are not stored. You have the following options: - Hover with the mouse over the lower right corner of the panes that you want to resize. Click and drag the panes to your preferred size. Note that there should be free space available if you want to make the pane larger, otherwise it will not be resized. - Hover with the mouse over the title bar and click and drag the pane to your preferred location. Note that there should be free space available where you want to place the pane, otherwise it will not be relocated. Procedure - Optional: NoldusHub records all available data signals by default, but you can click the Select data icon if you want to select specific data signals to be visualized or not. - Select or clear the data signal checkboxes you want to select or deselect. - Click Save. - Click Start Recording. NoldusHub asks whether you want to calibrate the eye tracker. Click Start calibration to start calibrating the eye tracker, and tell the participant to follow the instructions on their screen. Click Skip and start recording to start recording straight away; NoldusHub will use the latest stored calibration. - Instruct the participant to perform the requested actions at the recording test station. - When the participant has finished the requested actions, click Stop Recording. Note: Beware that there is no going back once you click Stop Recording. It is not possible to resume your recording. - Enter a name for the recorded session and click Save. What's next? A logical next step would be to replay your recorded session. Define, edit or delete a marker Aim To define, edit or delete a marker in your project's markers setup. Before you begin The marker functionality depends on your project-level user (member) role: - As an Owner or Editor, you can define and score markers. - As a Coder, you can only score markers and not define them. Navigate to the project for which you want to define, edit or delete markers. Procedure Define a marker - To open the project's Marker page, click Markers in the Setup section inside your project. - To define your first marker, click Add marker. If there are defined markers already, click Edit list. - Enter the Name of your marker in the Name field. - Optional: To define another marker click Add marker. Repeat step 3. - Click Save. Edit a defined marker - To open the project's Marker page, click Markers in the Setup section. - Click Edit list. - Adjust the Name of your marker in the Name field. NoldusHub shows a warning that the name change will affect all previously scored markers. - Click Save. Delete a defined marker - To open the project's Marker page, click Markers in the Setup section. - Click Edit list. - On the marker that you want to delete, click the delete icon. - Click Save. What's next? With markers defined, you can now score a marker. Score and remove a marker (v1.6–v1.7) Aim To score a marker or remove a scored marker in your project's recording. Before you begin The marker functionality depends on your project-level user (member) role: - As an Owner or Editor, you can define and score markers. - As a Coder, you can only score markers and not define them. Beware that you first have to define markers before you can score them. Navigate to the session inside your project for which you want to define, edit or delete markers. Procedure Score a marker - Start the replay inside the Timeline pane using the play button. - Once you are at the point in time where you want to score, press the corresponding shortcut key. - Your scored markers are visible inside the Scored markers pane. - If necessary, repeat step 2 for the rest of the recording. Remove a scored marker - In the Scored markers pane, click the delete icon on the marker that you want to delete. - If necessary, repeat step 1. What's next? You can define a marker. Score and remove a marker (v1.4) Aim To score a marker or remove a scored marker in your project's recording. Before you begin The marker functionality depends on your project-level user (member) role: - As an Owner or Editor, you can define and score markers. - As a Coder, you can only score markers and not define them. Beware that you first have to define markers before you can score them. Navigate to the session inside your project for which you want to define, edit or delete markers. Procedure Score a marker - Start the replay inside the Timeline pane using the play button. - Once you are at the point in time where you want to score, press the corresponding shortcut key. - Your scored markers are visible inside the Scored markers pane. - If necessary, repeat step 2 for the rest of the recording. Source: NoldusHub 1.8 Reference Manual --- ## NoldusHub - Interface and Visualization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-interface-and-visualization Chapter: NoldusHub Interface and Visualization Pane Controls You have the following options for managing panes in NoldusHub 1.8: - Hover with the mouse between the panes, and drag and drop to rescale. - Hover with the mouse over the panes and click the full screen button to open the panes in full screen. Click again to exit the full screen. - Hover over the panes, click and hold the tab with the data signal that you want to move and drag the panes to the preferred spot, drop the panes at the corresponding location. Replaying a Session - Scroll to the session you want to replay and click the corresponding button or on the name. - Optional: Click + Add signal... inside the Timeline pane to select additional data signals to display in Timeline. - Select or clear the data signal checkboxes you want to select or deselect. - Click the confirm button. - Start the replay by clicking the play button inside the Timeline pane. - Optional: You can add markers to your recording. What's Next? Downloading a session or adding a marker to your recording would be logical next steps. Download, Rename or Delete a Session Aim To download the recorded session data or to rename or delete a recorded session. Background You can download the recorded session data for further processing in other software. For example, you can import the downloaded data into Excel or SPSS as input for (statistical) analysis. Or you can delete a session if the recording went wrong or for another reason. Before You Begin The download and delete a session functionality depends on your application-level user role: - As an Administrator you can download a session for any project. - As a Researcher you can download a session for projects you created yourself and for projects shared with you as a member. - As a User you can download a session for projects shared with you as a member. Navigate to the project from which you want to download a session. Download a Session - Click Sessions. - Scroll to the session you want to download and click the corresponding download button. All data streams (CSV-files) checkbox is automatically selected. - Optional: If you want to download the screen and face video as well, select the All videos checkbox. - Click Download. Chrome downloads the files. The CSV-files are stored in a combined ZIP file. And the screen and webcam footage in separate MP4 files. NoldusHub prefixes the file names with the session name for easy reference. The Zip file contains a separate CSV file for each device, for example eyetracking.csv and facialexpressions.csv. Note: To play the exported MP4 files, in principle, any media player supporting MP4 can be used. However, as of NoldusHub 1.7, the _screencapture.mp4 files have a very limited number of key frames for episodes in which there was no movement in the captured screen. Not all media players can cope equally well with that. In our experience, "Windows Media Player legacy" works best, "PotPlayer", "KM Player" and "GOM Player" work sufficiently well and the Microsoft "Media Player" app and the "VLC Media Player" show many artifacts in navigation and playback and can therefore better be avoided. Rename a Session - To rename your session, click the rename button on the session you want to rename. - Enter the new name for your session in the Name field. - Click Save. Delete a Session - Click Sessions. - Scroll to the session you want to delete and click the corresponding delete button. - Click Yes. Hide or Show Navigation Bar Aim To hide or show the navigation bar that is located on the left side of the application. Hide Navigation - Before you open a project, a limited left navigation will be displayed. - Once you open a project, the full navigation bar is visible on the left. - To collapse the navigation bar, click the arrow button pointing to the left at the bottom of the navigation panel. - To hide the icons of the navigation bar as well, click the button with the arrow pointing to the left again. Show Navigation - To expand the navigation once it is fully hidden, click the button with the arrow pointing to the right. - To expand the navigation from the icon view, click the button with the arrow pointing to the right again. Restart the NoldusHub System In some cases, the NoldusHub server may become unstable, for instance: - Video is not recorded - Facial expression data is missing - Live streaming fails Before You Begin If such problems occur and persist, restarting the system is a last resort solution. For that, you must have the Administrator role to have access to the server. For a bare-metal server system, that requires entering an account name and password. For a system attached to a company network, this requires an IP address, Username and Password to set up a remote desktop connection. Close N-Linx Agent on the Participant Station - Go to the system tray, find N-Linx agent, right click on it, and click Exit. Verify That All Components Are Closed on the Participant Station - Open Windows Task Manager and click the Details tab. - Close all processes called N-Linx Agent or ps.exe by right clicking on each of these and selecting "End task". Execute StopNoldusHub.bat on the Server - Navigate to C:\Program Files\Noldus\NoldusHub\. - Double click StopNoldusHub.bat and wait until all services are stopped. - Once all services are stopped, press Enter or close the window. Execute StartNoldusHub.bat on the Server - In the same folder on the Server, double click StartNoldushub.bat. - When all services are started, press Enter or close the window. Wait 3 Minutes and Then Start the Participant Station(s) - After starting the server, wait for 3 minutes. - On all participant stations, one after the other, search for "N-Linx agent" in the search box in the task bar on the participant station. - Select and start N-Linx agent, and check in the system tray whether the icon has appeared. If this is not the case, repeat the starting of N-Linx agent. - Double click on the N-Linx agent entry and check the statuses of all device plugins. These should now all be online. If any of these steps fails and NoldusHub cannot be restarted, please contact Noldus Support. Supported Devices The following types of devices are supported in NoldusHub 1.8: - Eye trackers - Biosensors - Webcams Eye Trackers The following eye trackers currently on the market are supported in NoldusHub: Tobii Pro (Current Models) - Spark - 60 Hz. - Fusion - 30 Hz, 60 Hz, 120 Hz, 250 Hz. - Spectrum - 60 Hz, 120 Hz, 150 Hz, 300 Hz, 600 Hz or 1200 Hz. NoldusHub supports the 60 Hz setting. The following eye trackers are discontinued by their manufacturer but are still supported in NoldusHub (up to 60 Hz): Tobii Pro (Discontinued Models) - Nano - 60 Hz. - X2-30 - X2-60 - X60 - X120 - T60 - T120 Eyetech - VT3-mini - 40 Hz, 120 Hz. Firmware version 2019.2.3.0_19.11.22.72. NoldusHub supports 40 Hz and 120 Hz settings. Biosensors The following biosensors currently on the market are supported in NoldusHub: Shimmer3 EXG Unit Supported signals: - Raw ECG Lead I (referenced to Lead Neutral) - Raw ECG Lead II (referenced to Lead Neutral) - Raw ECG Lead III (referenced to Lead Neutral) - Raw ECG Lead IV (referenced to Lead Neutral) - Heart rate (calculated from the ECG Lead II signal) - Interbeat intervals (calculated from the ECG Lead II signal) Shimmer3 GSR+ Unit Supported signals: - Raw PPG - Heart rate (calculated from the raw PPG signal) - Interbeat intervals - Tonic skin conductance - Skin conductance peak rate Shimmer biosensors require correct configuration during the installation of the NoldusHub participant stations. Problems with one or all signals from your Shimmer device may be caused by misconfiguration (e.g. sampling frequency settings and signal selections on the device). Your system administrator can check that configuration using the NoldusHub installation documentation for Shimmer devices. Webcams Logitech - Brio webcam, VGA resolution. Frequently Asked Questions (FAQ) Below is a list of Frequently Asked Questions. Is your question not on this list? Reach out to Noldus support via the MyNoldus customer portal for assistance. Timeline Why Are Some Signals Not Displayed in Real Time? Some signals are running behind compared to other signals as they are not raw data but preprocessed data. This is the case for EDA signals, for example. The EDA data comes in later than the other data. This is normal and has to do with the processing that takes place to plot this data. How Many Researchers Can Use NoldusHub Simultaneously? NoldusHub version 1.4–1.7 both allow two researchers to work in parallel. What Is the Maximum Length of the Sessions That I Can Record? The maximum length of the sessions that can be recorded in NoldusHub 1.4–1.6 is 90 minutes or 1.5 hours. Why Do I Not See Any Signals in the Timeline During Replay? In versions 1.4–1.6, this could happen if you did not record EDA data during a session. Click on the + Add signal button and deselect all EDA signals. Go back to your replay and all your signal data should now be visible. Why Do I Not See Any Cognitive Load Data? Make sure to calibrate the eye tracker before each session. Although there is the option to Skip Calibration, please consider always calibrating if cognitive load data is desired. Markers Why Am I Not Seeing Markers That I Defined in the Marker Pane? To define markers it is important to click the Save button to store them. Otherwise, your markers will be lost. Eye Tracking How Should the Participant Be Seated for Eye Tracking? For accurate eye tracking results, take note of the following recommendations: - The participant should be facing straight toward the center of the screen. - For Tobii Pro eye trackers: the height of the eyes should be at one-third from the top of the monitor. The distance between eyes and eye tracker should be approximately 65 cm. Sitting at an arm's length from the monitor is approximately the correct distance. - For Eyetech VT3 Mini: the height of the eyes should be halfway down the monitor. The distance between eyes and eye tracker should be approximately 60 cm. Use the measuring tape supplied by Eyetech. - To optimize the head position towards the eye tracker, use a table or chair that can be adjusted in height. - During the test, let the participant be seated as still as possible. Do not use a chair with wheels. - Make sure that the participant can read items on the screen and, if needed, can easily reach the keyboard and mouse. - Take care that lighting from windows, or other light sources, does not interfere with the eye tracking. - The angle between the eye tracker and the gaze point at the screen is maximally 36° and ideally 20°. In general, when the participant is seated at the correct distance and height in front of the monitor, the angle is correct. Why Am I Not Receiving Eye Tracker Data? - If you have an Eyetech eye tracker, it could be that you did not calibrate the eye tracker. The Eyetech eye tracker does not provide data prior to calibration. Calibrate the Eyetech eye tracker and see if this fixes your issue. If not, reach out to your system administrator or Noldus Support. - If you have a Tobii eye tracker, follow the instructions to install the eye tracker as described by Tobii. If you still run into problems, reach out to your system administrator or Noldus Support. Why Are the Calibration Dots Not Distributed Evenly Across the Participant Screen? When the calibration screen does not look as expected — for example, if the calibration dots are all in one corner — check your Windows display scale. It should be set to 100%. If the display scaling is set to 100% but problems still occur, do the following: - Disconnect the eye tracker from the participant PC. - Reconnect the eye tracker. - Restart the participant PC. - Refresh the browser page on the test leader PC. Why Is the Calibration Failing? If calibration fails, or calibration quality is repeatedly not good enough, this may be due to several reasons: - The participant is not seated correctly in front of the computer. The participant may be sitting at an angle to the monitor or sitting at an incorrect height or distance. Use a table or chair that is easily adjustable in height. Do not use a chair with wheels or a swivel chair, because the participant may change position during either the calibration or test, leading to incorrect eye tracking data. - The participant does not correctly follow the dots during the calibration. This may result in a deviation between the displayed calibration dots and the measured gaze data (low accuracy). Ask the participant to focus on the dots and not anticipate where the dots may appear. - The ambient lighting may not be optimal. Avoid overhead light and bright sunlight in the experiment room. - The eye tracker may not correctly detect the eyes. Make sure the eyes are not (partially) covered by hair. Also, opening the eyes wider may help. Be aware that thick black mascara, bifocal or multifocal glasses, and reflective glasses may cause problems with eye tracking. - The eye tracker may be dirty. This may result in large gaze circles in the calibration results plot (low precision). Clean the eye tracker gently. Please refer to the documentation that came with your eye tracker for cleaning instructions. Disconnect your eye tracker from the power source before cleaning. Do not use strong cleaning agents, and ensure the eye tracker does not become wet. - If you use the Eyetech VT3 Mini, it is essential that both of the green lights on the eye tracker light up during the entire calibration. This means that both eyes are detected during the whole calibration. Why Do I Observe Gaze and Fixation Values Lower Than 0.0 and Higher Than 1.0? Gaze and fixation values outside the range of 0.0 to 1.0 indicate that the gaze point is outside the boundaries of the screen. This can occur when a participant looks away from the screen or when eye tracking accuracy is reduced due to poor calibration or incorrect seating position. Review the participant seating guidelines and recalibrate the eye tracker if necessary. Why Does Screen Sharing Not Work? If screen sharing is not working, verify that the necessary permissions and network settings are correctly configured. Contact your system administrator or Noldus Support if the issue persists. Why Does My Biosensor Not Work? Problems with one or all signals from your biosensor may be caused by misconfiguration, such as incorrect sampling frequency settings or signal selections on the device. Your system administrator can check that configuration using the NoldusHub installation documentation for the respective biosensor. How Can I Back Up My NoldusHub Data? For information on backing up NoldusHub data, contact your system administrator or reach out to Noldus Support via the MyNoldus customer portal. Source: NoldusHub 1.8 Reference Manual --- ## NoldusHub - Introduction and Architecture URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-introduction-and-architecture Chapter: NoldusHub NoldusHub - Introduction and Architecture NoldusHub 1.8 is a data integration platform by Noldus. NoldusHub Basic Concepts Test Station A test station is a space or room in which a participant's physiology and behavior are measured. Each test station consists of one Participant PC. Device A device is an instrument that registers physiological data signals like the heart rate. Raw Signal A signal is the physiological data signal delivered by a device. Examples of signals are: - Electrodermal conductance (EDA conductance) - Photoplethysmography light absorption intensity (PPG) A single device can produce multiple signals. For example, a Shimmer GSR+ device provides an EDA and a PPG signal. Derived Signal A derived signal is a signal calculated on the basis of one or more raw signals using a validated algorithm of some kind. For instance, Electrodermal conductance is a raw signal consisting of conductance values measured over time. The frequency of transient EDA peak patterns present in those EDA conductances calculated by some algorithm would be a derived signal. Derived signals can depend on one raw signal (e.g. EDA peak rate) or on multiple raw signals (e.g. cognitive load, which is calculated using pupil size and ambient light intensity). Session A session records a research observation with the accompanying data from a test station. Project A project is an overall container for your research observations. Projects contain test stations with devices/signals and recorded sessions. NoldusHub continuously monitors system connectivity and data quality during sessions. After recording a session, you can visualize and analyze your results with NoldusHub. NoldusHub Basic Workflow The basic flow for recording an observation with NoldusHub consists of the following steps: - Add a new project or open an existing project. - Select devices. - Optionally: create markers. - Calibrate eye tracker. - Record a session. - Review sessions. - Export session data. How to Get Started with NoldusHub Progressive learning is an excellent way to master NoldusHub: - Start with the Quickstart which covers the essentials you need to record a session, so you get up and running quickly. - In the bottom right, click the help button for help and to leave your suggestions. Quickstart (v1.6–1.7) Aim To master the basic steps for carrying out an observation with NoldusHub. After completing this tutorial, you will know how to: - Log in to NoldusHub. - Create a test station and add devices. - Create a new project. - Optional: Define markers. - Calibrate eye tracker. - Record a session. - Replay a session. - Optional: Score markers. Before You Begin For this tutorial, you must have: - A NoldusHub account. - A test leader PC; this can be your workstation with Google Chrome installed. - A Participant PC which shares its screen and webcam. The setup of these systems is part of the NoldusHub system installation process by the Noldus services department in collaboration with your system administrator. Furthermore, you should be familiar with the concepts of test stations, devices, projects, and sessions as described in the overview. Note: If you have Administrator rights, you have the ability to add test stations and devices. Persons with Researcher rights may create and invite others to projects, but cannot add test stations or devices; therefore, skip step 2 below. What You Will Do You will carry out an observation in which webcam images of a participant are recorded. It is up to you whether to involve an actual participant or act as a participant yourself. Procedure Step 1: Log In to NoldusHub You can only use NoldusHub after you are authorized. A system administrator can prepare an account for you. With the username and password provided by the system administrator, log in on your workstation (which acts as the test leader PC): - Open Google Chrome and navigate to your NoldusHub domain, for example, https://noldushub.mydomain.com. NoldusHub opens with the Login page. - Enter your Username and Password. - Click Log in. If you are a researcher, proceed to step 3. Step 2 only applies to administrators. Step 2: Create a Test Station and Add Devices Add a test station from which to record sessions: - Click Create test station. - Enter the name you want to give your test station in the Full name field, for example, Test room B. - Enter an abbreviated name for your test station in the Nickname field, for example, TRB. - Click Save. - To activate your test station, switch the toggle in front of your test station to the right by clicking on it. Be aware, as long as a test station is inactive, it is not available for researchers. The toggle turns green when activated. Next, add devices to your test station: - Expand the test station settings by clicking the expand icon. - Click Add devices. - Select the devices you want to add using the checkboxes in the Add devices list. Hover over items to see tooltips with the corresponding computer names. - Click Add device. For more information about this page, see Test stations and devices. Step 3: Create a New Project Create a project for gathering your recordings: - Click Projects in the top bar. - Click Create project. - Enter the name you want to give your project in the Enter name field. - Click Save. The Test stations page opens and shows your test stations and devices. For more information about this page, see Project devices and test stations. Optional Step 4: Define Markers It is possible to define markers within your project. Markers allow you to timestamp an event during the replay of your session. In order to be able to score markers later, you first need to define your markers. - To open the project's Marker page, click Markers in the Setup section inside your project. - To define your first marker, click Add marker. - Enter the name of your marker in the Name field. - Optional: To define another marker, click Add marker and repeat step 3. - Click Save. Step 5: Calibrate Eye Tracker Calibrate the eye tracker on the Participant PC to ensure the recording is as accurate as possible. Calibration is an interplay between a test leader PC and the relevant Participant PC and starts from the test leader PC. - You: Ask the participant to take a seat in front of the Participant PC and to follow the instructions on the screen. - You: Click Record Session — NoldusHub asks whether you want to calibrate the eye tracker or skip the calibration and start recording. If you skip calibration, the last stored calibration will be used. Alternatively, click the calibrate option in the Screen video pane — NoldusHub shows a Welcome screen for starting the calibration on the Participant PC. - Participant: Follow the instructions shown on the screen. - Participant: Once the calibration is finished, click Close. NoldusHub shows the Calibration results pop-up on the test leader PC. - You: If the calibration succeeded, click ACCEPT. If calibration failed, click Recalibrate and repeat from step 3. Tips on how to calibrate your eye tracker successfully can be found in the FAQ section. Step 6: Record a Session You are all set for your first recording: - Optional: NoldusHub records all available data signals by default, but you can choose to display or hide specific signals. - Select or clear the data checkboxes you want to display or hide. - Click Save. - Click Start Recording. NoldusHub asks whether you want to calibrate the eye tracker. Click Start calibration to start calibrating the eye tracker and tell the participant to follow the instructions on their screen. Click Skip and start recording to start recording straight away. If you skip the calibration, NoldusHub will use the last stored calibration. - Instruct the participant to perform the requested actions at the recording test station. - When the participant has finished the requested actions, click Stop Recording. - Enter a name for the recorded session and click Save. Step 7: Replay a Session After finishing your recording, you can replay your session to investigate the recorded data signals for your research: - Open the project in which you want to replay a session. - Select Replay in the left navigation bar. In the header bar, select a session in the drop-down list. - Alternatively, open a project, select Sessions in the left navigation bar, and click the name of the session you want to replay. - Optional: Click + Add signal... inside the Timeline pane to select additional data signals to display. - Select or clear the signal checkboxes you want to display or hide. - Click the confirm button. - Start the replay by clicking the play button inside the Timeline pane. Optional Step 8: Score Markers During the replay of your session, it is possible to score markers. - Start the replay inside the Timeline pane using the play button. - Once you are at the point in time where you want to score, press the corresponding shortcut key or click the corresponding button inside the Score a marker pane. - Your scored markers are visible inside the Scored markers pane. - If necessary, repeat step 2 for the rest of the recording. Quickstart (v1.4) Aim To master the basic steps for carrying out an observation with NoldusHub. After completing this tutorial, you will know how to: - Log in to NoldusHub. - Create a test station and add devices. - Create a new project. - Optional: Define markers. - Calibrate eye tracker. - Record a session. - Replay a session. - Optional: Score markers. Before You Begin For this tutorial, you must have: - A NoldusHub account. - A test leader PC; this can be your workstation with Google Chrome installed. - A Participant PC which shares its screen and webcam. The setup of these systems is part of the NoldusHub system installation process by the Noldus services department in collaboration with your system administrator. Furthermore, you should be familiar with the concepts of test stations, devices, projects, and sessions as described in the overview. Note: If you have Administrator rights, you have the ability to add test stations and devices. Persons with Researcher rights may create and invite others to projects, but cannot add test stations or devices; therefore, skip step 2 below. What You Will Do You will carry out an observation in which webcam images of a participant are recorded. It is up to you whether to involve an actual participant or act as a participant yourself. Procedure Step 1: Log In to NoldusHub You can only use NoldusHub after you are authorized, so first, you need to log in on your workstation (which acts as the test leader PC): - Open Google Chrome and navigate to your NoldusHub domain, for example, https://noldushub.mydomain.com. NoldusHub opens with the Login page. - Enter your Username and Password. - Click Log in. If you are a researcher, proceed to step 3. Step 2 can only be done by administrators. Step 2: Create a Test Station and Add Devices Add a test station from which to record sessions: - Click Create test station. - Enter the name you want to give your test station in the Full name field, for example, Test room B. - Enter an abbreviated name for your test station in the Nickname field, for example, TRB. - Click Save. - To activate your test station, switch the toggle in front of your test station to the right by clicking on it. The toggle turns green when activated. Next, add devices to your test station: - Expand the test station settings by clicking the expand icon. - Click Add devices. - Select the devices you want to add using the checkboxes in the Add devices list. Hover over items to see tooltips with the corresponding computer names. - Click Add device. For more information about this page, see Test stations and devices. Step 3: Create a New Project Create a project for gathering your recordings: - Click Projects in the top bar. - Click Create project. - Enter the name you want to give your project in the Enter name field. - Click Save. The Test stations page opens and shows your test stations and devices. For more information about this page, see Project devices and test stations. Optional Step 4: Define Markers It is possible to define markers within your project. Markers allow you to timestamp an event during the replay of your session. In order to be able to score markers later, you first need to define your markers. - To open the project's Marker page, click Markers in the Setup section inside your project. - To define your first marker, click Add marker. - Enter the name of your marker in the Name field. - Optional: To define another marker, click Add marker and repeat step 3. - Click Save. Step 5: Calibrate Eye Tracker Calibrate the eye tracker on the Participant PC to ensure the recording is as accurate as possible. Calibration is an interplay between a test leader PC and the relevant Participant PC and starts from the test leader PC. - You: Ask the participant to take a seat in front of the Participant PC and to follow the instructions on the screen. - You: Click Record Session — NoldusHub asks whether you want to calibrate the eye tracker or skip the calibration and start recording. If you skip calibration, the last stored calibration will be used. Alternatively, click the calibrate option in the Screen video pane — NoldusHub shows a Welcome screen for starting the calibration on the Participant PC. - Participant: Follow the instructions shown on the screen. - Participant: Once the calibration is finished, click Close. NoldusHub shows the Calibration results pop-up on the test leader PC. - You: If the calibration succeeded, click ACCEPT. If calibration failed, click Recalibrate and repeat from step 3. Tips on how to calibrate your eye tracker successfully can be found in the FAQ section. Step 6: Record a Session You are all set for your first recording: - Optional: NoldusHub records all available data signals by default, but you can choose to display or hide specific signals. - Select or clear the data checkboxes you want to display or hide. - Click Save. - Click Start Recording. NoldusHub asks whether you want to calibrate the eye tracker. Click Start calibration to start calibrating the eye tracker and tell the participant to follow the instructions on their screen. Click Skip and start recording to start recording straight away. If you skip the calibration, NoldusHub will use the last stored calibration. - Instruct the participant to perform the requested actions at the recording test station. - When the participant has finished the requested actions, click Stop Recording. - Enter a name for the recorded session and click Save. Step 7: Replay a Session After finishing your recording, you can replay your session to investigate the recorded data signals for your research: - Open the project in which you want to replay a session. - Select Replay in the left navigation bar. In the header bar, select a session in the drop-down list. - Alternatively, open a project, select Sessions in the left navigation bar, and click the name of the session you want to replay. - Optional: Click + Add signal... inside the Timeline pane to select additional data signals to display. - Select or clear the signal checkboxes you want to display or hide. - Click the confirm button. - Start the replay by clicking the play button inside the Timeline pane. Optional Step 8: Score Markers During the replay of your session, it is possible to score markers. - Start the replay inside the Timeline pane using the play button. - Once you are at the point in time where you want to score, press the corresponding shortcut key or click the corresponding button inside the Score a marker pane. - Your scored markers are visible inside the Scored markers pane. - If necessary, repeat step 2 for the rest of the recording. Source: NoldusHub 1.8 Reference Manual --- ## NoldusHub - N-Linx Agent and Connectivity URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-n-linx-agent-and-connectivity Chapter: NoldusHub NoldusHub - N-Linx Agent and Connectivity NoldusHub 1.8 is a data integration platform by Noldus. The following resources document the signals available per device across different versions of NoldusHub. Signals Available in NoldusHub v1.4 (Per Device) Shimmer GSR+ Signal Liveview Recorded Replay Download EDA baseline (µS) 1 Yes Yes Yes Yes EDA average peak rate (min-1) 2 Yes Yes Yes Yes PPG raw signal 3 Yes Yes PPG HR value (min-1) Yes Yes Yes Yes PPG IBI value (msec) 4 Yes Yes Yes Yes - Baseline conductivity is the measured conductivity from which transient peak responses are removed. Conductivity is expressed in microSiemens (µS). - Average peak rate and heart rate are expressed as the (average) number of peaks/beats per minute (min-1). - The raw PPG signal is a normalized, unitless light absorption measure. It reflects the size of expansion/constriction of small blood vessels induced by local blood pressure fluctuation due to the beating of the heart. - Inter-beat intervals, i.e. the interval between two subsequent heart beats, is expressed in milliseconds (msec). Shimmer EXG Signal Liveview Recorded Replay Download Lead_1 (mVolt) Yes Yes Yes Yes Lead_2 (mVolt) Yes Yes Yes Yes Lead_3 (mVolt) Yes Yes Yes Yes Vx (mVolt) Yes Yes Yes Yes ECG HR value (min-1) Yes Yes Yes Yes ECG IBI value (msec) Yes Yes Yes Yes Tobii Pro Remote Eyetrackers Signal Liveview Recorded Replay Download Fixation X (0-1) 1 Yes Yes Yes Yes Fixation Y (0-1) Yes Yes Yes Yes Movement state (Saccade-Fixation) 2 Yes Yes Gaze X (0-1) 3 Yes Yes Yes Yes Gaze Y (0-1) Yes Yes Yes Yes Gaze Left X (0-1) Yes Yes Gaze Left Y (0-1) Yes Yes Gaze Right X (0-1) Yes Yes Gaze Right Y (0-1) Yes Yes Gaze Validity (0-1) Yes Yes - Positions on the screen are normalized values: left (X) = 0, right (X) = 1; top (Y) = 0, bottom (Y) = 1. - Movement state can be "Saccade" (i.e. moving), "Fixation", or "Undefined". - Gaze X and Gaze Y are averaged over both eyes if data from both are available. Otherwise, values are limited to the available data only. Eyetech VT3-mini Signal Liveview Recorded Replay Download Fixation X (0-1) 1 Yes Yes Yes Yes Fixation Y (0-1) Yes Yes Yes Yes Movement state (Saccade-Fixation) 2 Yes Yes Gaze X (0-1) 3 Yes Yes Yes Yes Gaze Y (0-1) Yes Yes Yes Yes Gaze Left X (0-1) Yes Yes Gaze Left Y (0-1) Yes Yes Gaze Right X (0-1) Yes Yes Gaze Right Y (0-1) Yes Yes Gaze Validity (0-1) Yes Yes - Positions on the screen are normalized values: left (X) = 0, right (X) = 1; top (Y) = 0, bottom (Y) = 1. - Movement state can be "Saccade" (i.e. moving), "Fixation", or "Undefined". - Gaze X and Gaze Y are averaged over both eyes if data from both are available. Otherwise, values are limited to the available data only. Insight: Facial Expressions Facial Expressions are "Insights": signals that are derived by applying an algorithm to one or more measured signals. To qualify as an insight, the algorithm used should be validated scientifically to produce a signal that reflects a psychologically meaningful factor. In the case of Facial Expressions, the measured signal is a face video of the participant. The algorithm is a set of video processing routines that quantify facial motor action unit responses and recipes to estimate emotional expressions based on those responses according to the Facial Action Coding System. Facial Expression signals available in NoldusHub: Signal Liveview Recorded Replay Download "Neutral" (0-1) 1 Yes Yes Yes Yes "Happy" (0-1) Yes Yes Yes Yes "Sad" (0-1) Yes Yes Yes Yes "Angry" (0-1) Yes Yes Yes Yes "Surprised" (0-1) Yes Yes Yes Yes "Scared" (0-1) Yes Yes Yes Yes "Disgusted" (0-1) Yes Yes Yes Yes "Confusion" (0-1) Yes Yes Yes Yes "Boredom" (0-1) Yes Yes Yes Yes "Interest" (0-1) Yes Yes Yes Yes - Relative expression intensities are normalized values: minimum = 0, maximum = 1. Insight: Cognitive Workload Cognitive Workload is an "Insight": a psychologically meaningful factor that is estimated from measured physical and physiological signals. The Cognitive Workload insight is obtained from measured pupil sizes and environmental light intensity, using a scientifically validated algorithm. Cognitive Workload signals available in NoldusHub: Signal Liveview Recorded Replay Download Cognitive Load (0-1) 1 Yes Yes Confidence (0-1) Yes Yes Pupil diameter Yes Yes Pupil size by light reflex Yes Yes - Relative Cognitive Load and Cognitive Load Confidence intensities are normalized values: minimum = 0, maximum = 1. Signals Available in NoldusHub v1.6 (Per Device) Shimmer GSR+ Signal Liveview Recorded Replay Download EDA baseline (µS) 1 Yes Yes Yes Yes EDA average peak rate (min-1) 2 Yes Yes Yes Yes PPG raw signal 3 Yes Yes PPG HR value (min-1) Yes Yes Yes Yes PPG IBI value (msec) 4 Yes Yes Yes Yes - Baseline conductivity is the measured conductivity from which transient peak responses are removed. Conductivity is expressed in microSiemens (µS). - Average peak rate and heart rate are expressed as the (average) number of peaks/beats per minute (min-1). - The raw PPG signal is a normalized, unitless light absorption measure. It reflects the size of expansion/constriction of small blood vessels induced by local blood pressure fluctuation due to the beating of the heart. - Inter-beat intervals, i.e. the interval between two subsequent heart beats, is expressed in milliseconds (msec). Shimmer EXG Signal Liveview Recorded Replay Download Lead_1 (mVolt) Yes Yes Yes Yes Lead_2 (mVolt) Yes Yes Yes Yes Lead_3 (mVolt) Yes Yes Yes Yes Vx (mVolt) Yes Yes Yes Yes ECG HR value (min-1) Yes Yes Yes Yes ECG IBI value (msec) Yes Yes Yes Yes Tobii Pro Remote Eyetrackers Signal Liveview Recorded Replay Download Fixation X (0-1) 1 Yes Yes Yes Yes Fixation Y (0-1) Yes Yes Yes Yes Movement state (Saccade-Fixation) 2 Yes Yes Gaze X (0-1) 3 Yes Yes Yes Yes Gaze Y (0-1) Yes Yes Yes Yes Gaze Left X (0-1) Yes Yes Gaze Left Y (0-1) Yes Yes Gaze Right X (0-1) Yes Yes Gaze Right Y (0-1) Yes Yes Gaze Validity (0-1) Yes Yes - Positions on the screen are normalized values: left (X) = 0, right (X) = 1; top (Y) = 0, bottom (Y) = 1. - Movement state can be "Saccade" (i.e. moving), "Fixation", or "Undefined". - Gaze X and Gaze Y are averaged over both eyes if data from both are available. Otherwise, values are limited to the available data only. Eyetech VT3-mini Signal Liveview Recorded Replay Download Fixation X (0-1) 1 Yes Yes Yes Yes Fixation Y (0-1) Yes Yes Yes Yes Movement state (Saccade-Fixation) 2 Yes Yes Gaze X (0-1) 3 Yes Yes Yes Yes Gaze Y (0-1) Yes Yes Yes Yes Gaze Left X (0-1) Yes Yes Gaze Left Y (0-1) Yes Yes Gaze Right X (0-1) Yes Yes Gaze Right Y (0-1) Yes Yes Gaze Validity (0-1) Yes Yes - Positions on the screen are normalized values: left (X) = 0, right (X) = 1; top (Y) = 0, bottom (Y) = 1. - Movement state can be "Saccade" (i.e. moving), "Fixation", or "Undefined". - Gaze X and Gaze Y are averaged over both eyes if data from both are available. Otherwise, values are limited to the available data only. Insight: Facial Expressions Facial Expressions are "Insights": signals that are derived by applying an algorithm to one or more measured signals. To qualify as an insight, the algorithm used should be validated scientifically to produce a signal that reflects a psychologically meaningful factor. In the case of Facial Expressions, the measured signal is a face video of the participant. The algorithm is a set of video processing routines that quantify facial motor action unit responses and recipes to estimate emotional expressions based on those responses according to the Facial Action Coding System. Facial Expression signals available in NoldusHub: Signal Liveview Recorded Replay Download "Neutral" (0-1) 1 Yes Yes Yes Yes "Happy" (0-1) Yes Yes Yes Yes "Sad" (0-1) Yes Yes Yes Yes "Angry" (0-1) Yes Yes Yes Yes "Surprised" (0-1) Yes Yes Yes Yes "Scared" (0-1) Yes Yes Yes Yes "Disgusted" (0-1) Yes Yes Yes Yes "Confusion" (0-1) Yes Yes Yes Yes "B Source: NoldusHub 1.8 Reference Manual --- ## NoldusHub - Pre-Install - Noldushub 1.7 Pre-Installation Guide URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-pre-install-noldushub-17-pre-installation-guide Chapter: NoldusHub Test Leader and Participant PC Outlined below are steps to be performed prior to installing NoldusHub on a PC. Note these steps are specific to installation on the Test Leader and/or Participant PCs and does not include steps for installing NoldusHub on the server. For more information on server installation, contact support@noldus.com. Summary Steps - Hardware meets or exceeds technical requirements - SSL certificate is set up - NoldusHub installation package and related software is downloaded - Participant hardware devices including webcam, Tobii eye tracker, and Shimmer are connected Download Links - Hardware Devices & N-Linx Agent: https://noldus.sharefile.eu/public/share/web-sa14f28a77df841bfbdc7d8ef0f36e3e8 - SSL Certificate Check Tool: https://noldus.sharefile.eu/public/share/web-s6da36bb9b1774141afc4cc99e00c24f8 Detailed Steps Hardware Meets or Exceeds Technical Requirements See supplemental document NoldusHub 1.7 System Specifications for technical requirements of all NoldusHub PCs. SSL Certificate Is Set Up NoldusHub uses a secure connection for communication. This is possible with an SSL certificate. Using such a certificate fulfills two main requirements: - Encrypted communication between user and server computers - Server identification If the certificate used does not comply with the required formats, NoldusHub will not work. The SSL certificate was created when your NoldusHub system was first installed. If your domain has changed, a new SSL certificate may be required. Download and use the Certificate Check Tool to verify the SSL certificate meets NoldusHub requirements. NoldusHub Installation Package and Related Software Is Downloaded Use the link provided above to download all software packages prior to the remote-assisted installation session. Participant Hardware Devices Including Webcam, Tobii Eye Tracker, and Shimmer Are Connected Please follow this procedure for the initial setup of each participant PC and ensure the latest version of Google Chrome is installed. Webcam - Connect the USB webcam to the participant PC. It is also possible to use an internal webcam on a laptop. Tobii Eye Tracker - Connect the eye tracker to the test participant PC and position it at the bottom of the monitor. - In the NoldusHub installation folder, locate and run TobiiProEyeTrackerManager.exe. - Select all checkboxes and accept the firewall popup. - Select Install eye tracker. - Select the corresponding eye tracker type and click Install. - Accept the Windows popup again. - Once the installation complete popup comes up, click Close. - Connect the eye tracker to the PC. - Select the eye tracker and click Calibrate to check the functionality of the eye tracker. This is also possible if you turn on position guide. Shimmer Biosensor Download and configure Consensys, the software for Shimmer biosensors. Consensys has to be installed on at least one PC. It is used to configure the Shimmer devices; this can be done for all Shimmer devices from one PC. - In the NoldusHub installation folder, locate Consensys_v1.6.0_64.zip. - Unzip the file, run it, and follow the steps on your screen. - Choose ConsensysBASIC and enter your details (name, organization, and email). - Connect the Shimmer docking station to the test participant PC, insert the Shimmer device, and turn it on using the slider on the side of the device. - If necessary, first perform a firmware upgrade of the Shimmer device. If not necessary, continue to step 13. - Select the dock you want to configure and click on the Manage button in the bottom left of the application. - Select the Firmware option. - Select LogAndStream_Shimmer3_ and click the Program button. Wait until the software has finished the firmware upgrade. - Click Manage Devices in the Consensys software. - Click on the picture of the Shimmer device on the right side of your screen. The device will appear in the list on the left. - Click Configure. - In the Sampling Rate field, depending on the type of device, enter the value as seen in the table below and click the warning triangle to validate. Device Type Sampling Rate Shimmer3 ECG Shimmer3 GSR+ - Select the Battery Voltage tile (so it is colored and not greyed out), for both Shimmer3 ECG and Shimmer3 GSR+ devices. - Depending on the device, see the corresponding step for the correct configuration: - For Shimmer3 ECG, make sure that the ECG is selected (colored and not greyed out) in the ECG/EMG tile on the Sensors tab. Then click A on the ECG/EMG tile. Set Gain to 4 and Resolution to 24 bit. - For Shimmer3 GSR+, make sure that the GSR and PPG are selected (colored and not greyed out) in the GSR+ tile. - Click on the field with the parameters you want to measure and click Write Config. Wait until the configuration is complete, and then click Finish. - Close the Consensys application. Connect Shimmer Biosensor via Bluetooth The following steps must be done on every participant PC that has a Shimmer biosensor. - Click the Windows icon on the desktop and type settings. - Windows 10: In the Settings screen, click Devices and ensure that the Bluetooth toggle is turned on. Windows 11: In the Settings screen, click Bluetooth & Devices and ensure that the Bluetooth toggle is turned on. - Windows 10: Click the icon in front of Add Bluetooth or Other Devices. Windows 11: Click Devices. The option Bluetooth Devices Discovery is now available. Switch this setting from Default to Advanced. - Click Add Device. - Ensure that your Shimmer device is on. The device will appear in the list with the ID listed on the back of the Shimmer device. - Click on the device name, and in the PIN field, enter 1234 and click Connect. The Your device is ready to go message will appear. Click Done. - Under Bluetooth & Other Devices, locate the Shimmer device and check that it is paired. Install the Consensys System Tray App The following steps must be done on every participant PC that has a Shimmer biosensor. - If the Consensys Tray App v1 is already installed, uninstall it first. The installer for v2 does not upgrade the existing version, so if v1 is already installed, you will have both versions on your PC simultaneously. After uninstalling v1, delete the folder C:\Program Files (x86)\Shimmer\ConsensysSystemTray. - In the NoldusHub installation folder, open Devices - Shimmer and then unzip the zip file. - In the folder that appears, double-click setup.exe and follow the steps on your screen. Select the option to create a desktop shortcut. - Click the Consensys Tray app icon on your desktop. The corresponding icon appears in the system tray. - Right-click the icon, select the appropriate Shimmer device, and click Start. Wait until the Streaming message appears. Source: NoldusHub 1.7 Pre-Installation Guide, Noldus Information Technology --- ## NoldusHub - Projects and Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-projects-and-configuration Chapter: NoldusHub NoldusHub - Projects and Configuration NoldusHub 1.8 is a data integration platform by Noldus. This page provides background information about projects, devices, members, recordings, sessions, and markers, along with step-by-step guides for common tasks. Projects (v1.4) This page provides background information about projects and describes what actions you can take for projects. Background What is a project? A project is a container for arranging your research session recordings. You are free to arrange projects in such a way that they best match how you want to organize your research. We advise you to record all sessions of one research experiment in one project. To go inside a project click the name of the project inside the Projects page. To navigate to the Projects page: - As an Administrator, click Projects. - As a Researcher or User, your home page is the Projects page. The name of the project that you are working in is always displayed at the top of the screen. Actions What do you want to do? - Create a project. - Rename a project. - Delete a project. - Navigate to the sessions list. - Back up all projects. (Ask your administrator.) Learn the basics of NoldusHub - Read the overview to learn the NoldusHub fundamentals. - Follow the quickstart guide / tutorial to learn the basic steps for carrying out an observation in NoldusHub. Project Devices and Test Stations This page provides background information about project test stations and devices and describes what actions you can take for each. Background All the test stations and devices you or your administrator created are available in projects as Test stations for recording sessions. Devices and Test Stations Your project's available devices and test stations appear on the Test stations page. To display this page, open your project. You will automatically land on the Test stations page. If not, navigate to Setup in the left side bar and to Test stations in the header bar. Devices and Signals The Test stations page also shows the signals provided by the devices. Signals are the physiological data signals delivered by devices, for example, Electrodermal activity (EDA). The time-lapse values of the signals you set up in a project are included in your recording sessions. Devices and Signals are Logically Connected A device and its signals are logically connected in NoldusHub. When you switch off a device, all its connected signals are also automatically switched off. And vice versa, when you switch off all signals for a device, the device itself is also switched off. The same applies to switching on: When you switch on a device, all its signals are also switched on. So, for example, when you switch off an Eye tracker device, the Gaze signal is automatically switched off. Or the other way around: When you switch on a Screen video device, the Screen video signal is also switched on. Actions What do you want to do? - Set up devices and test stations for a project. - Connect devices to a Participant PC. Learn the basics of NoldusHub - Read the overview to learn the NoldusHub fundamentals. - Follow the quickstart guide / tutorial to learn the basic steps for carrying out an observation in NoldusHub. Project Members This page provides background information about project members and describes what action you can take for project members. Background What are Project Members? You can share your project with co-workers and lab-mates by inviting them as project members. All administrator users automatically have access to all projects. Other users can be invited in the Members module of the Setup menu. Roles and Permissions You can set the permissions for project members by adding them as an Editor. As the creator of the project, you are immediately assigned the Owner role. - Owner: The project member that created the project and has all project rights. - Editor: The project member can edit a project. Actions What do you want to do? - Select members for a project. - Delete a project member. Learn the basics of NoldusHub - Read the overview to learn the NoldusHub fundamentals. - Follow the quickstart guide / tutorial to learn the basic steps for carrying out an observation in NoldusHub. Project Recording This page provides background information about project recordings and describes what actions you can take for project recordings. Background What is a Project Recording? A project recording is a recording of a participant's behavior and physiological measurements. Project recordings are time-limited because you control how long they last by starting and stopping a recording. As for content, a project recording consists of: - Screen video footage showing the participant's screen content and what actions the participant performs. - Face video footage showing the participant during the recording. - Timeline data showing the recorded data signals. Actions What do you want to do? - Record a session for a project. - Set up devices and test stations for a project. - Calibrate eye trackers. - Set up members for a project. - Score a marker. - Remove a scored marker. Learn the basics of NoldusHub - Read the overview to learn the NoldusHub fundamentals. - Follow the quickstart guide / tutorial to learn the basic steps for carrying out an observation in NoldusHub. Session List This page provides background information about the session list and describes what actions you can take in the session list. Background What is the Session List? The sessions list is a list with the previously saved project sessions. New session recordings are added to the top of the list once you save them. Actions What do you want to do? - Replay a session from a project. - Download a session. - Rename a session. - Delete a session. Learn the basics of NoldusHub - Read the overview to learn the NoldusHub fundamentals. - Follow the quickstart guide / tutorial to learn the basic steps for carrying out an observation in NoldusHub. Project Session This page provides background information about project sessions and describes what actions you can take for project sessions. Background What is a Project Session? A project session is a saved project recording that could, depending on the recorded data, consist of: - Screen video footage of the participant's screen content and actions the participant has performed. - Face video footage of the participant during the recording. - Timeline of the recorded data signals. - Previously scored markers, if you (or someone else) replayed the recording before and scored markers. Actions What do you want to do? - Replay a session from a project. - Score a marker. - Remove a scored marker. Learn the basics of NoldusHub - Read the overview to learn the NoldusHub fundamentals. - Follow the quickstart guide / tutorial to learn the basic steps for carrying out an observation in NoldusHub. Markers This page provides background information about markers and describes what actions you can take. Background What is a Marker? With the use of markers, you can annotate events that are important to your study. Examples of markers may be blinking, to keep track of when the participant blinks, or talking, the moment the participant starts talking. A marker consists of a name, type of marker, shortcut key, and color of marker. You first have to define the markers that you want to use in your project. Afterward, you can use key shortcuts during the replay of your session to place markers, which is called "scoring." During the scoring of markers, a timestamp is added along with the name and color of the marker in the pane Markers. Types of Markers There is one type of marker available: - Point Marker: The marker is a point in time and has no duration. Actions What do you want to do? - Define a marker. - Edit a defined marker. - Delete a defined marker. - Score a marker. - Remove a scored marker. Learn the basics of NoldusHub - Read the overview to learn the NoldusHub fundamentals. - Follow the quickstart guide / tutorial to learn the basic steps for carrying out an observation in NoldusHub. Guides Log in to NoldusHub Aim To get access to NoldusHub. Before You Begin You must have been added as a user in NoldusHub by the system administrator and must have received a username and password. Procedure - Open Google Chrome and navigate to your NoldusHub domain, for example, https://noldushub.mydomain.com. - Enter your Username and Password. - Click Log in. What's Next? It is possible to change your password. Log Out or Change Your Password Aim To log out or to change your password. Before You Begin To log out or to change your password you have to be logged in. Procedure Log Out - Open your account menu. - Click Log out. Change Your Password - Open your account menu and click Change password. - In the Current password field, enter your current password. - In the New password and Repeat password fields, enter your new password. - Click Save. Add, Edit or Delete a User Aim To add, edit or delete a new application user. Background User Types NoldusHub distinguishes application and project-level users. See User management for more information about the differences. Before You Begin - You must have the Administrator role to add an application-level user. - You need to determine what application-level role the new user needs. Procedure Add a User - Open the application settings. - Click User management. - Click Add user. - In the First name, Last name, and Email address fields, enter the corresponding values for the new user. - In the Username field, enter the display name for the user in NoldusHub. Note: The following characters are allowed in the username: a to z (lowercase), A to Z (uppercase), 0 to 9, '@' (at sign), '.' (period), '-' (hyphen) and '_' (underscore). - In the Password and Repeat password fields, enter the password for the user. - Select the role you want to assign to the new user using the Role list. - Click Save. - Provide the username and password to the user. Edit a User - Open the application settings. - Click User management. - Scroll to the user you want to edit and click the edit option for the user. - Edit either the user's First name, Last name, or Email address fields, or change the user's role in the Role list. - Click Save. Delete a User - Open the application settings. - Click User management. - Scroll to the user you want to delete and click the delete option for the user. - Click Yes. What's Next? A logical next step is to create a test station. Reset the Password for a User Aim To reset the password for an existing application user. Before You Begin - You must have the Administrator role to reset the password for a user. - Users can also change their own password. If you forgot your password and are unable to log in, please contact your administrator and ask them to reset your password for you. Procedure - Open the application settings. - Click User management. - Scroll to the user for whom you want to reset the password and click the edit option for the user. - Click Reset password. - In the Password and Repeat password fields, enter the new password for the user. - Click Save. - Provide the new password to the user. What's Next? It is also possible to delete a user. Create, Rename or Delete a Test Station Aim To create, rename or delete a test station. Before You Begin - You must have the Administrator role to create, rename or delete a test station. - You must have installed and connected at least one Participant PC. - Navigate to the Test stations page. Note: Test stations must be created from your Test leader PC. You can create as many test stations as you want but can only have two test stations active simultaneously. Procedure Create a Test Station - Click Create test station. - To give your test station a name, enter the name in the Full name field, for example, Test room B. - To give your test station an abbreviated name, enter an abbreviated name in the Nickname field, for example, TRB. - Click Save. - To activate your test station, switch the toggle in front of your test station to the right by clicking on it. The toggle turns green when activated. Rename a Test Station - Click the options menu on the test station you want to rename and select Rename. - Enter the new name for your test station in the Full name field. - Enter the new abbreviated name for your test station in the Nickname field. - Click Save. Delete a Test Station - Click the options menu on the test station you want to delete and select Delete. - Click Yes. What's Next? Complete your test station by adding devices. Add or Delete a Device Aim To add a device to a test station or to delete a device from a test station. Before You Begin - You must have the Administrator role to add or delete a device from a test station. - The device you want to add must already be installed at the test station (Participant PC). - Navigate to the Test stations page. Note: Devices must be added from your Test leader PC. Procedure Add a Device to a Test Station - Unfold the test station where you want to add a device by clicking the expand option. - Click Add devices. - Select the device(s) you want to add using the checkboxes in the Add devices list. Hover over items to see tooltips with the corresponding computer names. - Click Add device. Delete a Device from a Test Station - Unfold the test station where you want to delete a device by clicking the expand option. - Click the delete option for the device. What's Next? Create a project to record and replay your sessions. Create, Rename or Delete a Project Aim To create, rename or delete a project. Before You Begin - You must have the Administrator or the Researcher role to create or delete a project. - Navigate to the Projects page. Procedure Create a Project - To create a new project, click Create project. - Enter the name you want to give your project in the Enter name field. - Click Save. Rename a Project - Click the options menu on the project you want to rename. - Enter the new name for your project in the Name field. - Click Save. Delete a Project - Scroll to and click the delete option for the corresponding project. - Click Yes. Navigate to the Sessions List There are two ways to get to the sessions list: Option 1: - Navigate to the Projects page. - Click the sessions icon on the line of the corresponding project. Option 2: - Navigate to the Projects page. - Scroll to and click on the name of the project. - Navigate to Sessions in the side menu. What's Next? Set up your project with devices and test stations, and members. Source: NoldusHub 1.8 Reference Manual --- ## NoldusHub - Tips - But Webcam Video Looks Ok URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-tips-but-webcam-video-looks-ok Chapter: NoldusHub But Webcam Video Looks OK Problem: Facial Expressions are calculated from face video streams produced by a webcam. So, when the face video is present in liveview, it appears unlogical when no Facial Expression data is produced in the Timeline graph. Explanation: This is a known issue related to the use of two video processing pipelines: 1) a direct, realtime, processing of video into sequences of images that are sent to the Facial Expressions processor and file storage, and 2) a channel that shows the same live video directly on screen. When only the first process fails, facial expressions cannot be calculated while live video can still be seen. Solution: - Remove and reload Media Plugin in Nlinx-agent on the affected participant stations. - If that does not resolve the issue, then restart the NoldusHub server. Timeline In Liveview mode, selected signals are plotted for the past 45 seconds. Under perfect conditions, signals fill the graph all the way until the now-line, i.e. the vertical red line that intersects the time axis all the way at the right-hand side of the Timeline graph. Problem: This is not always the case. The most recent data shown in the graph may go further back in time than a few seconds. There are several explanations for this behavior, each with their own solution: - Delayed Data Transfer: Delays in data transfer may be caused by slow or interrupted network traffic. This leads to variable short delays, i.e. jumpy signal lines that go back a split second up to a few seconds, and then jump back to the red line. Solution: Improve network connection if any, or just accept the short delays. - Clock Sync Issues: The clock of the Test Leader system is not in sync with the NoldusHub server. The NoldusHub server acts as an NTP server for participant stations, but not for the Test Leader system. If either the NoldusHub server or the Test Leader system is not synced to a reliable external NTP server, the Test Leader system will show data that is out of sync in Liveview mode. Signals on the left-hand side of the graph will be missing if the Test Leader system clock time is earlier than NoldusHub server time, or signals will be missing at the right-hand side of the graph if the Test Leader system clock time is later than NoldusHub server time. Solution: First, make sure that the Test Leader system is synced with a reliable NTP server. If this does not solve the problem, make sure that the NoldusHub server is also synced with a reliable external NTP server. Please note that data quality is not affected by differences between Test Leader and server clock times as long as participant stations are in sync with the NoldusHub server. - Derived Signal Processing Delay: The signal is not a raw live signal, but a derived signal for which signal processing takes time. An example of such a signal is the EDA peak rate signal. EDA peak rates are calculated from raw conductance signals in which EDA peaks are detected. To identify peaks, a full peak needs to be present in the raw signal first. This takes approximately 20 seconds. Therefore, derived EDA signals show delays of 20 seconds. Solution: None. The delay is an inherent signal property. - Signal Out of Range: The signal is out of range. For instance, heart rates of 250 bpm will be plotted out of view. Solution: Check whether the signal is a valid, within-normal-range signal. Plugin Ping-Pong (v1.6) As from version 1.6, NoldusHub features plugin reconnect logic. Device plugins can be loaded with the Nlinx-agent application that resides on each participant station. If a device plugin disconnects for any reason, N-linx will try to reconnect. If that succeeds but the reason to disconnect still exists, the plugin will disconnect again. Generally, this sequence of events will repeat without end. This is called plugin ping-pong. One main reason for the initial disconnect is a stability issue of the used message broker, RabbitMQ. This issue is resolved by assigning dedicated CPUs to RabbitMQ and others to the VideoWebService. A script is run for that during startup (Affinity Settings Script). Reasons for plugin ping-pong to occur: - Script-Wise Affinity Settings Fail Shortly After Server Restart. Solution: Initiate affinity settings again by stopping and restarting the NoldusHub server (on-site or in a remote desktop session): - Go to the DockerDeployment folder and run StopNoldusHub.bat. - Wait until all services are properly stopped. - Run StartNoldusHub.bat. Wait for all services to start, then check the plugins in Nlinx-agent. They should all automatically reconnect and stay connected. After NoldusHub Startup Problem: Data stream recordings and videos may be incomplete when recordings are made shortly after server restart. When the following steps are performed in sequence without pause, recordings may turn out to be incomplete: - Run StopNoldusHub.bat and then StartNoldusHub.bat on the server, then immediately select a location and start recording. - Reboot the NoldusHub server computer, then immediately select a location and start recording. Explanation: Starting up the many containers needed for NoldusHub takes time and a lot of CPU capacity. These initial processes can take up to 5 minutes to complete. Recording sessions also require a lot of CPU capacity. If recordings are started while containers are still starting up, not all data processing during recording (FES images, cognitive load, EDA data processing, HR & IBI calculation) can be completed in time. Hence, data will be lost. Solution: Wait at least 5 minutes after restarting the NoldusHub server before starting recordings. For the Device This is mostly observed for the webcam: in Liveview, the participant can be seen, but the webcam device in the Signals and Devices page shows an error. - This error is not caused by failing video, but by the absence of an audio signal in the composite video-audio output of the camera device. Solution: Check in device setup whether webcam audio is active. Eyetracker Related Problem: When using version 1.6.2, it is possible to start recording without calibration. This should be possible; however, in this version it may cause failing workload recordings. Solution: Always calibrate before starting a recording. Detected Problem: After selecting participant stations and switching to Liveview, the video streams of screen capture and participant webcam may disconnect. As a result, facial expression data will also not be available. This is especially observed when the user starts the system but waits before initialising stimulus presentation. Source: Video disconnects automatically when no video mutations happen on the screen or in the webcam image. Solution: Start up some dynamic video or other dynamic screen content on the participant screen, or have somebody interact with a window (browser or anything else) on the participant system. Knowledge Base Explanations, how-to's, and background information. Source: NoldusHub 1.7 Tips and Tricks, Noldus Information Technology --- ## NoldusHub - Tips - Check Cpu Affinity Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-tips-check-cpu-affinity-settings Chapter: NoldusHub Check CPU Affinity Settings When CPUs are not correctly assigned to important processes like the Video Web Service and the RabbitMQ message service, NoldusHub functionalities will fail. Solution: To resolve issues due to sub-optimal CPU affinity settings, first check whether CPU affinity settings are applied correctly. If the settings are not applied correctly, restart the NoldusHub services with StopNoldusHub.bat and then StartNoldusHub.bat. NoldusHub Services The following file contains the actual CPU affinity settings on the NH server: C:\Program Files\Noldus\NoldusHub\Scripts\Control-NoldusHub.ps1 Look for a section like this: - $Env:AffinityMaskVws = Calculate-AffinityMask 0 62.5 - $Env:AffinityMaskRmq = Calculate-AffinityMask 62.5 100 - $Env:AffinityMaskFes = Calculate-AffinityMask 62.5 100 The settings mean that Vws gets the first 62.5% of the CPU cores. If your server has 32 cores, Vws (Noldus.VWS.Service.exe) will get CPU cores 0–19. RabbitMQ (Rmq: erl.exe) will get CPU cores 20–31 and Fes (Noldus.FacialExpressionService.exe) will also get CPU cores 20–31. All other services should use all CPU cores. Correct Number of CPU Cores - Open Task Manager and locate the NoldusHub service you want to check. - Open the affinity settings via the context menu by selecting Set Affinity. - Check if the service has the correct number of CPU cores assigned. - Verify that really the first or the last CPU cores are selected, as expected. Source: NoldusHub 1.7 Tips and Tricks, Noldus Information Technology --- ## NoldusHub - Tips - Tricks For Support URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-tips-tricks-for-support Chapter: NoldusHub Installation Installation-related tips-n-tricks NoldusHub Starts in Browser, But Does Not Proceed to the Login Window In 9 out-of-10 cases, this problem occurs after installation. The most likely cause is that some or all customer-specific fields in the .ENV file are not updated during installation. Solution: Update the required fields in the ENV file: - IP Address - DNS name - Certificate password (>v1.4) After Installation: No Frontend, Containers Keep Restarting Physical servers are configured at Noldus, and need some reconfiguration at the client. Descriptions are given in the Installation Documentation. It was observed at different occasions that the NoldusHub server was not available after reconfiguration. At closer inspection, some docker containers were observed to be restarting. This was due to errors in .env files. Solution: Inspect docker containers on the server, use PowerShell with the command: docker ps Then, check the up-time column: do some containers show shorter up times that remain short after refresh (type the same command again). The FileStorage service was observed often as one of these. If some containers restart continuously, this is most likely because the configuration file (.env) has incorrect specification of the new (at-premise) computer name, host name, or DNS. When installing at a customer site, this has to be reconfigured. Saved Session Lost Significant Portion of Facial Expression Data This problem is mostly observed in 4-station setups using v1.6, but may also occur in later versions serving more than 4 stations. The main reason that not all facial expression data is saved is that not enough CPU resources are available for the Video Web Service during recording. Solution: Check whether CPU affinity settings are applied correctly, and correct settings if needed. Plugin State Often Jumping Between Online and Unresponding The observation that Nlinx plugins on the participant station appear to be loaded and removed repeatedly is referred to as 'plugin ping-pong'. Solution: Check whether CPU affinity settings are applied correctly, and correct settings if needed. After Installation, Eyetech Eye Tracker Does Not Work, Gaze Fixed at Top Left Corner It was observed upon several occasions that after installation of a newly unboxed Eyetech eye tracker on a cleanly installed system, the eye tracker could not be calibrated, and the gaze overlay was fixed at the (0,0) position (top left side of the screen capture window). In addition, the gaze projection did not respond to the gaze of the person in front of the eye tracker, although the eye tracker did detect both eyes (indicated by both green lights in the eye tracker). This failing gaze detection was the result of missing calibration information. As long as there was no successful calibration made, the gaze position remained at (0,0). To overcome failing calibrations, the eye tracker needed to be positioned exactly below the screen, with the right angle and distance to the subject. Only then would calibration succeed, and calibration info could be used to calculate actual gaze positions. Upgrading Issues observed when upgrading NoldusHub, and their solutions and workarounds. Errors After NoldusHub Upgrade After upgrading NoldusHub to a newer version, the Test Leader PC may produce errors while recording. Still, recordings can be viewed after completion. Solution: This problem is most likely related to conflicting content produced by the previous version in the browser cache. Clear the browser history (empty cache) and try again. After Upgrade, Old Version Still Remains Observed problem: When upgrading v1.4 to v1.6.2 remotely on ChinaHub, upgrading containers took exceptionally long, and when finished, NoldusHub version was still 1.4. Closer inspection of the upgrading steps showed that: - Installation package 1.6.2 was successfully copied to the ProgramFiles folder - The older package was successfully renamed NoldusHub.old - The package for 1.6.2 was renamed to NoldusHub - When running the InstallNoldusHub.bat installation script, the above renaming changes were automatically reversed: NoldusHub.old was automatically renamed to the original name, and the added package was removed. Therefore, effectively v1.4 was re-installed. Most likely, edits to the ProgramFiles folder were undone by the operating system. Solution: Move the older package to another folder before placing the new package in ProgramFiles. Known Issues Known-issue-related tips-n-tricks. Unresponsive Plugins (< v1.6) Problem: Device plugins may disconnect in versions earlier than v1.6, and stay disconnected, causing the absence of signals that the user wishes to record. Explanation: Versions before 1.6 do not have device-plugin reconnect logic. In addition, RabbitMQ configuration and process isolation of RabbitMQ are not optimized. Because of this, services may become unresponsive and plugins may be disconnected. The chances of this happening increase with the number of participant stations connected. Solutions: Depending on the severity of RabbitMQ instability, two solutions may help, a mild solution and a less mild one. - The mild solution: Remove disconnected plugins on affected participant stations and restart them: - On the participant station that has disconnected plugins, open Nlinx Agent and remove disconnected plugins. - Load the plugins again and wait until connected, or repeat up to two times if no reconnect occurs. - If reloading the plugins twice does not resolve the issue, choose the less mild solution. - The less mild solution: Remote-connect to the NoldusHub server and restart it: - On each participant station, one after the other, open Nlinx Agent and remove all plugins. - Go to the DockerDeployment folder and run StopNoldusHub.bat. - Wait until all services are properly stopped. - Run StartNoldusHub.bat and wait for all services to start. - One participant station after the other, open Nlinx Agent on each participant station, connect the Nlinx Agent to the NoldusHub server, and load all plugins. Source: NoldusHub 1.7 Tips and Tricks, Noldus Information Technology --- ## NoldusHub 1.7 - Certificate Check Tool URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-certificate-check-tool Chapter: NoldusHub Certificate Check Tool The certificate verification can be performed using the Certificate Check Tool that is shipped with the NoldusHub installation package. It is an executable that should be run on the Server. This tool is not the same tool as the Installation Readiness test tool. It is a separate executable, available in the installation package, and it should be executed separately. Procedure A flow diagram is shown below, illustrating the Certificate Check procedure (and the Installation Readiness check procedure). - Copy the certificate check tool to the folder on the server that also contains the certificate files (*.pfx, *.cer, *.key). - Run the certificate check tool as an administrator (no parameters needed). - Inspect the results (on screen), and resolve issues if they are reported before testing again. Troubleshooting - Sometimes, the combination of files that constitute the SSL certificate fileset is not complete. Missing files can be created using the OpenSSL toolkit. - Sometimes, the fileset appears complete, but the password protected PFX file is not configured with a password. OpenSSL toolkit can be used to set a password. - The password that protects the PFX file should be RSA-encrypted. If not, the certificate check will fail. Install NoldusHub on the Server Aim To install the necessary software on the server to access NoldusHub on the test leader PC and the observer devices. Before You Begin - Make sure the server meets the computer and network requirements as described in the Specifications. - Ask for the network range used for the server in the customer's network. - Ask for the security certificate details at the customer's site. - Set up a hostname for the server. - Connect the devices in the NoldusHub network. See Connections. - Keep your NoldusHub Software Activation Key within reach. Step 0: Allow PowerShell Script Execution on the Server Before being able to run PowerShell scripts on the server, the execution policy for it needs to be set to "Allowed". For this, PowerShell needs to be opened manually and the following script needs to be run: Set-ExecutionPolicy -ExecutionPolicy Unrestricted -Scope CurrentUser Step 1: Install NoldusHub Docker Components Docker is a service that enables operating system-independent operation and simplifies product updates. To install the Docker components: - Open the DockerDeployment folder in the NoldusHub installation files. Double-click the batch file InstallNoldusHub.bat. If a window opens with the request to click any key to continue, press a key on your keyboard. - Open the folder C:\Program Files\Noldus\NoldusHub and double-click the batch file SetupNoldusHub.bat. A message will appear that you need to restart the server. Press any key to restart the server. During this step the NTP Server is automatically configured. - Open the folder C:\Program Files\Noldus\NoldusHub and double-click the batch file InstallDockerCompose.bat. Follow the instructions on screen. - Open the folder C:\Program Files\Noldus\NoldusHub and double-click the batch file AddDefenderExclusions.bat as administrator. This adds folder exclusions for Defender Antivirus. Step 2: Install NoldusHub - Open Notepad with administrator rights. - Choose File > Open and browse to the folder C:\Program Files\Noldus\NoldusHub to edit the batch file ConfigureNoldusHub.bat. If you do not see the file, select All Files (*.*). The original ConfigureNoldusHub.bat file looks like this: @echo off powershell -command ".\Scripts\Configure-NoldusHub.ps1 -ServerIPAddress \"127.0.0.1\" -CertPassword \"*********\" -ClientHostName \"127.0.0.1\" -APIHostName \"127.0.0.1\" -NumberOfParticipants \"2\" pause Where ********* has to be replaced with the Noldus internally known password. Once logged in, change the password to the license key of the user. If You Have a Subdomain for NoldusHub Note: See the guide Set up a secure connection for your subdomain for more information on subdomains. - Change the field after ClientHostname and APIHostName to the subdomain name you specified in the Set up a secure connection for your subdomain procedure. - For example, if you created the subdomain https://noldushub.mydomain.com: - Change the field after ClientHostname and APIHostName to noldushub.mydomain.com. - Change the field after CertPassword to the password that came with the certificate. Your ConfigureNoldusHub.bat file should now look like this: @echo off powershell -command ".\Scripts\Configure-NoldusHub.ps1 -ServerIPAddress \"YOUR_SERVER_IP_ADDRESS\" -CertPassword \"YOUR_PASSWORD\" -ClientHostName \"noldushub.mydomain.com\" -APIHostName \"noldushub.mydomain.com\" -NumberOfParticipants \"2\" pause If You Do Not Have a Subdomain for NoldusHub - Change the IP address and hostnames in the file to the server's IP address and hostname. Write down the IP address for use in the following steps. See also the IP addresses topic. - Change the -CertPassword field to the password for the server. Your ConfigureNoldusHub.bat file should now look like this: @echo off powershell -command ".\Scripts\Configure-NoldusHub.ps1 -ServerIPAddress \"YOUR_SERVER_IP_ADDRESS\" -CertPassword \"YOUR_PASSWORD\" -ClientHostName \"YOUR_HOSTNAME\" -APIHostName \"YOUR_HOSTNAME\" -NumberOfParticipants \"NUMBER_OF_PARTICIPANTS\" pause - Change the -NumberOfParticipants value to the number of participants you want to run for the server. - Close the file. Choose Yes when prompted to overwrite the existing file. - Double-click the batch file ConfigureNoldusHub.bat. Follow on-screen instructions. - Open the folder C:\Program Files\Noldus\NoldusHub and double-click the batch file UpdateNoldusHub.bat. This will install or update the application. Press a key on your keyboard if you notice the installation process is idle for a while. This resumes the installation process. The first time you carry out this step, it can take some time. Dependent on the speed of the Internet connection, it can take up to one hour. With an upgrade, it will take a few minutes. - Copy the certificate files (*.crt, *.key, *.pfx) to the C:\ProgramData\Noldus\Websites\cert\ folder. For details, see Setup the Certificate. - Open the folder C:\Program Files\Noldus\NoldusHub and double-click the batch file StartNoldusHub.bat. Press a key on your keyboard if you notice the installation process is idle for a while. This resumes the installation process. If the server is restarted, wait two minutes between server restart and starting NoldusHub on any other device to enable all services to start on the server. If an error appears about Docker, wait a few minutes before starting NoldusHub. - To verify that all containers are started and running, open PowerShell and type the command: docker ps -a. Check that the status of all containers are up and running. Step 3: Start and Activate NoldusHub See Start NoldusHub. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Certificate Preparation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-certificate-preparation Chapter: NoldusHub Certificate Preparation If the customer has the PFX format certificate, KEY and CRT format files should be extracted from PFX format. This can be done, using: - DigiCert Certificate Utility for Windows (GUI tool, easy to use) https://www.digicert.com/support/tools/certificate-utility-for-windows - OpenSSL tool (command line tool) openssl pkcs12 -in server_address.pfx -clcerts -nokeys -out server_address.crt openssl pkcs12 -in server_address.pfx -nocerts -out server_address.encrypted-key openssl rsa -in server_address.encrypted-key -out server_address.key If the customer has the certificate and key in KEY and CRT files, the PFX format file should be created. This can be done, using: - OpenSSL tool (command line tool) openssl pkcs12 -export -out server_address.pfx -inkey server_address.key -in server_address.crt A new password will be asked during this process which should be added to the .env file (as CERT_PASSWORD). Docker Container Name Resolution After starting NoldusHub, the docker containers were not able to communicate/ping each other via container name. Example: In the noldus-hub-api container, the ping rabbitmq command failed (request could not find host). Solution: - The Windows Defender profiles were Domain controlled (which overtook some network settings). - Every Windows Defender Firewall Profile on the Local GPO was changed to off: Local Security Policy / Security Settings / Windows Defender Firewall with Advanced Security Set every profile (Domain, Private, Public) to off (from not configured). - Additionally, some security products (e.g. CrowdStrike) can block the network communication. Checking Server Port Access from Participant PC On the customer computer infrastructure, security products like extra firewalls might be applied. These can block the network communication between the server and Participant PC. Example: The Test-NetConnection (PowerShell) command was used from the Participant PC to connect to a server port. The command showed the TcpTestSucceeded result as true, but as soon as the connection was built up, a firewall immediately blocked and refused the communication. This problem was difficult to detect because the connection test passed. Solution: Disable the additional blocking firewall. Video Streams If the webcam image is not available or it appears as black, check the Imaging devices (or USB devices) in Device Manager. Only one webcam must be enabled. Disable all but one and restart the NoldusMedia plugin. If the video streams are still not available with the MediaPlugin, use the Caller page from a Chrome browser as a temporary solution. Possible causes: - One of the security software products might block the WebRTC connection with the NoldusMedia plugin. - The network/firewall settings. Shimmer - If the Participant computer is a PC (not a laptop), the USB Bluetooth dongle must be on site at the installation time. - The dongle driver should be updated before the installation process. - If the EDA data does not appear, check the device frequency settings (GSR+ 128 Hz; ECG 512 Hz). Problems with Connectivity If a Shimmer device has problems with Bluetooth connectivity, it is possible that some security software on the Participant PC is blocking that. This has been observed at the customer with Windows 10 OS and GSR+ device. Symptoms: - It is hard to get the device connected (and streaming) to the Consensys Tray app. This usually works better if the device is placed in the dock. - If the device is removed from the dock while connected and streaming, the connection is lost after a couple of minutes. Consensys Tray app shows "Connection Lost" status. After that, it is very hard to get the device to stream data again. Mitigation: - Test the same Shimmer device with another computer without any security products (except Windows Defender). - Re-flash Shimmer device firmware. Make sure to erase existing configuration. Note: after that, this device will need to be configured properly (see the points above). - Note: When it is not possible to connect to Shimmer via Bluetooth, launch Consensys, select the device and make it stream to PC. - Use internal Bluetooth (PCIe) rather than an external USB Bluetooth device. Tobii Eyetracker The eye tracker position in Tobii Manager software must be set up correctly before using it from the N-Linx Plugin. Without a working setup, the plugin cannot send any eye tracking information, or only very limited information. Eyetech Eyetracker Eyetech eye trackers do not come with setup software. Instead, only a driver needs to be installed, and the correctly versioned Eyetech NLinx plugin needs to be used. It was observed upon several occasions that after installation of a newly unboxed Eyetech eye tracker on a cleanly installed system, the eye tracker could not be calibrated, and the gaze overlay was fixed at the (0,0) position (top left side of the screen capture window). In addition, the gaze projection did not respond to the gaze of the person in front of the eye tracker, although the eye tracker did detect both eyes (indicated by both green lights in the eye tracker). This failing gaze detection was the result of missing calibration information. As long as there was no successful calibration made, the gaze position remained at (0,0). To overcome failing calibrations, the eye tracker needed to be positioned exactly below the screen, with the right angle and distance to the subject. Only then did calibration succeed, and calibration info could be used to calculate actual gaze positions. Verify Installation Requirements NoldusHub versions 1.6 and up require an SSL certificate to be installed on the server. Installation Readiness Tool The Installation Readiness Tool helps verify whether a system is prepared for installation by checking if it meets the required criteria. This tool is a single PowerShell script and is regularly updated with new checks and improvements as part of ongoing development. Distribution The Installation Readiness PowerShell script is distributed together with the NoldusHub installation package (in a separate directory). Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Documentation [Wip] URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-documentation-wip Chapter: NoldusHub Hardware Requirements When you buy computers for NoldusHub, make sure they meet the requirements mentioned below. Also, make sure the network meets the network specifications. In this page, hardware requirements are specified. A tool is available to facilitate the verification of critical hardware requirements: the Installation Readiness Tool. Please use this tool before starting installation. This may save a lot of time. Server Requirements Minimal Recommended 64 GB ECC RAM 64 GB ECC RAM 500 GB NVMe™ or SAS SSD for OS 1 TB NVMe™ or SAS SSD for OS 2 TB NVMe™ or SAS SSD for storage (optional as backup storage, 2 x 1 TB optional) 2 TB NVMe™ or SAS SSD for storage (optional as backup storage, 2 x 1 TB optional) 2 x Xeon 42xx 2.1GHz CPU processor, with at least a total of 12 physical cores, 24 threads (for instance 2 x Xeon 4206) 2 x Xeon 42xx 2.1GHz CPU processor, with at least a total of 16 physical cores, 32 threads (for instance 2 x Xeon 4208) 1 Gbps network bandwidth 1 Gbps network bandwidth Monitor, keyboard, mouse are optional Monitor, keyboard, mouse are optional Microsoft Windows Server 2019 Standard, 16-core, LTS Microsoft Windows Server 2019 Standard, 16-core, LTS The server computer CPU must support Virtualization. Make sure the Virtualization feature is enabled: - On bare metal server (physical server): the Virtualization feature can be enabled in the BIOS. - On virtual computer: the Virtualization feature can be enabled in the Hypervisor software (e.g. Hyper-V, VMware). If the Virtualization feature is not available, NoldusHub cannot be installed and run on the server. In the NoldusHub system, some processes are spread amongst CPU cores (using affinity settings). This method supports only up to 64 CPU cores at the moment, so applying more than 64 CPU cores does not add any benefit for the affinity settings. Participant PC Requirements - Windows 11, 64-bit (Professional or Enterprise); latest update. - 32 GB RAM. - 256 GB SSD (M2). - i7-CPU with hyperthreading. - 1x USB-A 3.0. - 4x USB-A 2.x. - QuadroT1000 GPU graphics card. - 1 Gbps network bandwidth. - Access to Internet (Ethernet or wired). - External Bluetooth Class 2 Bluetooth 2.1 + EDR module: for Shimmer GSR/PPG/EMG. - 1x Monitor, with a maximum resolution of 1920 x 1080. - Reference model: Dell Precision T3660. Supported screen sizes for eye trackers: Vendor Eye Tracker Model Sampling Frequency (Hz) Supported Screen Size EyeTech VT3 mini 40, 120 22" Tobii Pro Nano 19" Tobii Pro Fusion 60, 120, 250 24" Tobii Pro Spark 30, 60 27" Older models in the Tobii Pro series eye trackers are expected to work too. Installed software: - N-Linx Agent: 1.15.2 - Google Chrome, latest update. Remember to frequently check for and install any available updates to your OS and Chrome. Test Leader PC Requirements - Windows 10 or 11, 64-bit (Professional or Enterprise); latest update. - 16 GB RAM. - 256 GB SSD (M2). - i7-CPU processor with hyperthreading. - QuadroT1000 GPU graphics card. - 1 Gbps network bandwidth. - Access to Internet (Ethernet or wireless). - 2x monitor with a resolution of at least 1920 x 1080 is recommended, or 1x 32-inch monitor with a 4K resolution. - Reference model: Dell Precision T3660. Installed software: - Google Chrome, latest update. Remember to frequently check for and install any available updates to your OS and Chrome. Network Specifications The NoldusHub network requires 1 Gbps Ethernet. This means that all cables and network adapters must allow at least 1 Gbps data transfer. Take the following requirements into account: Server - 1 Gbps network adapter for connection to participant PC. - Server hostname: verify that the server has a FQDN name. - Access to the Internet. Participant PC - 1 Gbps network adapter for connection to the server. - Access to the Internet. - Fixed IP address in the same range as the server or hostname. See IP Addresses for the procedure to set up a fixed IP address. Test Leader and Observer Devices - 1 Gbps network adapter for connection to the server. - Access to the Internet. - IP address in the same range as the server or hostname. Network Cables - Cat5 or higher. Network Switch - 1 Gbps uplink speed. - Access to the Internet. - Enough ports for all devices. - Recommended devices: NetGear Switch PoE 24 ports GS728TP or NetGear Switch PoE 8 ports GS310TP. SSL Certificate NoldusHub uses a secure connection for communication. This is possible with an SSL certificate. Using such a certificate fulfills two main requirements: - Encrypted communication between user and server computers. - Server identification. NoldusHub uses SSL certificates in two different formats: *.pfx and *.crt. A decrypted certificate private *.key file is also required. The password of the certificate in the *.pfx format is required too. Please note that this password has to be entered in plain text (unencrypted) in one of the NoldusHub configuration files. If the certificate used does not comply with the required formats, NoldusHub will not work. It is good practice to check whether the used certificate complies. This check can be performed with the Certificate check tool, which is shipped with the installation package. It is possible to convert an SSL certificate into different formats, e.g. from *.pfx to *.crt and to unencrypted *.key. There are different ways to do this, e.g. using the OpenSSL toolkit. To install the SSL certificates on the NoldusHub server, follow the Set Up a Secure Connection for Your Subdomain guide. Install NoldusHub Aim: To install NoldusHub on a server from scratch. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-introduction Chapter: NoldusHub Introduction The Installation documentation describes the steps to install NoldusHub. It contains the following chapters: - Specifications with requirements for the PCs in the network and the network itself. - Connections with an example of a setup with two participant stations. - Guides with the installation procedures. - A Reference section with additional information. Installation Steps Installation of NoldusHub requires the following steps: - Verify whether system configuration is still in line with requirements. For this, the Installation Readiness Tool should be used (see also the installation procedure flow diagram at the bottom of this page). - Set up a secure connection for your subdomain. Create a secure connection within your company domain, so that NoldusHub opens without security warnings. - Install NoldusHub on the server. - Set up NTP Client on the participant PCs. - Set up screen and camera sharing on participant PCs. Carry out this procedure on every participant PC, so that the screen content and camera stream is visible in NoldusHub. - Prepare participant PCs for eye tracking. If you have eye trackers, carry out this procedure on every participant PC that you want to use for eye tracking. - Prepare participant PCs for biosensors. If you have Shimmer devices, carry out this procedure on every participant PC that you want to use for biosensor data collection. - Start and activate NoldusHub. - Perform optional settings: - Change default location of saved videos. - Windows Defender folder exclusions. - Automatic data export after session recording. - NTP syncing of multiple servers. - Modifying Windows update scheduling to prevent performance drops. Upgrade NoldusHub Aim: To upgrade an older NoldusHub version to NoldusHub 1.7. This description presumes an existing and running NoldusHub instance on the server computer. Server - The server should meet the requirements described in the Specifications. - To verify whether system configuration is still in line with requirements, the Installation Readiness Tool should be used first. - Verify whether the SSL certificate is valid for a sufficiently long period, and whether it is still configured correctly. For that, the certificate check tool is made available on MyNoldus. - NoldusHub 1.6 or later versions use only secure N-Linx (RabbitMQ) communication: - Older NoldusHub versions used port 5672. - Since NoldusHub 1.6, port 5671 is used for communication. - Customer IT should open port 5671 for incoming communication before the NoldusHub upgrade process and, at the end of the process, they can close the port. Participant PCs - The participant PCs should meet the requirements described in the Specifications. - NoldusHub 1.6 or later versions use only secure N-Linx (RabbitMQ) communication: - Older NoldusHub versions used port 5672. - Since NoldusHub 1.6, port 5671 is used for communication. - Customer IT should open port 5671 for outgoing communication to the server before the NoldusHub upgrade process and, at the end of the process, they can close port 5672. Step 1: Backup and Upgrade the Server PC - Stop the running NoldusHub instance: - Open the folder C:\Program Files\Noldus\NoldusHub in File Explorer. - Run the batch file StopNoldusHub. - Check if there is a running docker container (with command docker ps -a). - Backup the current NoldusHub files: - The backup script saves the files to D:/NoldusHubBackup/ folder by default. Check if the D: drive exists and has enough free space for the backup. - If the D: drive is not suitable, change this in Backup-NoldusHub.ps1 accordingly (at variable $customer_backup_folder_root). - Run the batch file BackupNoldusHub. - Keep the previous version installation and control files: - Rename the C:\Program Files\Noldus\NoldusHub folder (e.g. to C:\Program Files\Noldus\NoldusHub_1.4). - Install the NoldusHub 1.7 files on the server: - Open the DockerDeployment folder on the NoldusHub 1.7 installation stick and double-click the batch file InstallNoldusHub. - When a window opens with the request to click any key to continue, press a key on your keyboard. - When a question appears about whether you want the software to make changes to your computer, click Yes. - When a question appears about whether you want to run this software, type A. - Replace the .env file with the previous, working one, or update it manually. Overwrite C:\Program Files\Noldus\NoldusHub\.env from the renamed folder (e.g. with C:\Program Files\Noldus\NoldusHub_1.4\.env). - Download the docker images: - Make sure the antivirus software is disabled at this point. - Open the folder C:\Program Files\Noldus\NoldusHub and double-click the batch file UpdateNoldusHub. This will download the docker images. When a window opens with the request to click any key to continue, press a key on your keyboard. - Check the output message. In some cases, the antivirus software blocks the download. Run the UpdateNoldusHub batch file again if required. - Check the downloaded images with the docker image ls command. - Update the number of Video Web Services: - Edit the -vws parameter value in the StartNoldusHub batch file if necessary. - Check the parameter value in the previous version. - Start NoldusHub: - Open the folder C:\Program Files\Noldus\NoldusHub and double-click the batch file StartNoldusHub. When a window opens with the request to click any key to continue, press a key on your keyboard. Step 2: Upgrade Test Participant PCs - On the test participant PC, locate the N-Linx Agent icon in the system tray, right-click and select Exit. Make sure the NLinxAgent.exe is not running (check in Task Manager). - Uninstall N-Linx Agent. - Remove completely the C:\ProgramData\Noldus\N-Linx Agent\ and C:\ProgramData\Noldus\PluginServer\ folders. - Copy the N-Linx Agent folder from the NoldusHub 1.7 installation folders to the test participant PCs (e.g. to Desktop). - Locate N-Linx Agent Setup.exe and double-click this file to run it. - Double-click the N-Linx Agent icon in the system tray. - Add the N-Linx Server Address as the NoldusHub server. - Only a valid DNS name is accepted with a valid certificate. - IP Address cannot be used. - Add suitable plugins (for NoldusHub 1.7) in N-Linx Agent. Devices setup is not affected by plugin updates. However, if devices need to be configured again for any reason, this can be done here. Setup In general, a NoldusHub setup consists of the following hardware: - A server that hosts the NoldusHub software. - One or more participant PCs, each with a USB camera and, optionally, an eye tracker and/or a biosensor device. - A test leader PC. - A switch for connecting the server and PCs. - A router. This schematic depicts a setup with two participant PCs with the supporting hardware. Other setups are an option as well. NoldusHub supports setups with 1–4 participant stations. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-notes Chapter: NoldusHub Notes To remove the folder exclusions on the server, open the folder C:\Program Files\Noldus\NoldusHub and run RemoveDefenderExclusions.bat as administrator. To remove the folder exclusions on the participant PC, open the Scripts folder and run Remove-Participant-Defender-Exclusions.bat as administrator. To check the folder exclusions on a computer, run Get-MpPreference command. Change Location of Saved Video Files Aim: To change the location of where the video files are saved once you download them. Note: Folders that are part of your desired path should be created manually. Procedure - Open the folder C:\Program Files\Noldus\NoldusHub in File Explorer. - Double-click the batch file StopNoldusHub. - Open docker-compose-noldus-hub.yml. - Change the path that can be found under the containers videowebservice and filestorageservice that is located at volumes:, source: to the desired path on the server PC. The paths that have to be changed are highlighted in the following image. Keep in mind, the folders that are part of your desired path have to be created manually. - Save the docker-compose-noldus-hub.yml file. - Double-click the batch file StartNoldusHub. Set Up Automatic Export Aim: To set up automatic export on the Server PC. Before You Begin When automatic export is enabled, your session will be automatically exported, once a session is finalized. Exported files will be in the folder that you specify in the commands run below. Note: - Export can take some minutes if you have a longer recording. - The base folder will contain a subfolder named after your session and that folder contains the exported CSV files and video files plus ready.log file. - The files will not be zipped. - Files will be downloaded to the Server PC. Procedure Automatic export is by default disabled. There are 2 ways to enable it, permanently or temporarily. Permanently Choose this method if you want to always use NoldusHub with automatic export. - Double-click the batch file StopNoldusHub. - Start Command Prompt. - Enter setx /M AUTOMATEDEXPORT_FOLDER "yourfolder". If you would like to disable automatic export, follow the same steps before and after this step, but enter REG delete "HKLM\SYSTEM\CurrentControlSet\Control\Session Manager\Environment" /F /V AUTOMATEDEXPORT_FOLDER instead. - Double-click the batch file StartNoldusHub. - Export is ready when ready.log appears in your folder. Temporarily Choose this method if you want to try out automatic export or if you don't want to modify your environment. - Double-click the batch file StopNoldusHub. - Start Powershell Command Prompt. - Enter .\StartNoldusHub.ps1 -automatedexportfolder "yourfolder". - Export is ready when ready.log appears in your folder. NTP Synchronization of Multiple Servers Aim: To set up the NTP synchronization when there are multiple servers used. Note: This chapter is specific for when multiple servers are used. If you have only one server, you can ignore this chapter. Procedure - Modify Group Policy: - Open Group Policy Editor. - Go to: Local Computer Policy > Computer Configuration > Administrative Templates > System > Windows Time Server > Time Providers. - Double-click Configure Windows NTP Client. - Select Enabled. - NTP Server: IpaddressORNameOfNTPServer,0x08 - Type: NTP - Double-click Enable Windows NTP Client. - Select Enabled. - Restart the Computer: Local Computer Policy changes only take effect after a restart. - Check Status: - w32tm /query /source — To check if the group policy is applied. - w32tm /stripchart /computer:IpaddressORNameOfNTPServer — To track the offset between the client and the NTP server. - w32tm /resync — To force a synchronization if the offset is too high. Windows Update Policy Aim: To keep Windows up to date without the updates interfering with the functioning of NoldusHub. Server Windows Server OS is designed to run services 24/7, so it will not install updates automatically. Therefore, as a system administrator, you will need to take action yourself and plan the OS updates. Participant PC It is recommended to stop the Windows update maintenance and to perform the updates manually. It is possible to set the active hours for the Participant PC so the updates will install after active hours or upon shutdown. However, in this case, the updates will still be downloaded during the active hours. This download can interfere with the N-Linx agent, which can result in difficulties with your measurements or data loss. To stop automatic updates and get notified when an update is available to download, follow these steps: - Open Local Group Policy Editor. To do so, type Edit Group Policy in Start or taskbar search box and press Enter. - Navigate to the following policy: Computer Configuration > Administrative Templates > Windows Components > Windows Update > Manage End User Experience. - Double-click on the policy labeled Configure Automatic Updates on the right side to open its properties. - Select Enabled option. Under Configure Automatic Updating, select the second option labeled Notify for Download and Auto Install. Do not change the rest of the settings. - Click the Apply button. Reference IP Addresses Aim: To find an IP address or to enter a fixed IP address for the server. To Find an IP Address - Open the Windows Start menu and type IP address. - Click on the Change Ethernet Settings tile that appears. Under Ethernet, click the Ethernet connection of your network. Do not use the HyperV Ethernet connection. This is a virtual ethernet connection for the installation files. - In the window that appears, the IP address of the PC is shown in the IPv4 address field. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-procedure Chapter: NoldusHub Procedure - Connect the server to the switch using an Ethernet cable. - Connect the participant PCs to the switch using Ethernet cables. - Connect a USB camera to the participant PCs. It is also possible to use a built-in webcam on a laptop. - Connect the eye trackers to the participant PCs using USB cables. - Connect the biosensor devices to the participant PCs using Bluetooth. - Connect the switch to the Internet. Guides Installation Readiness Tool Aim: To verify whether the NoldusHub server and the network in which it is embedded are configured correctly. What Is the Installation Readiness Tool? The Installation Readiness Tool is a collection of Powershell scripts and executables that can be run on the NoldusHub server to verify whether server and network configurations are in line with NoldusHub requirements. The tool can be executed from command line and it produces results feedback in the user interface (text). The same feedback is also stored in log files for easy communication to Noldus Support. Typical application of the Installation Readiness Tool is after configuring the hardware/virtual server, and prior to installation (see diagram below). What Is Tested with the Installation Readiness Tool? First and foremost, we wish to make clear that the Installation Readiness Tool is a work-in-progress tool. Over time, new tests will be added when needed. At this moment (NoldusHub version 1.7) the Installation Readiness Tool checks whether minimal requirements are met for: - Storage drive type and available storage space (minimally 512 GB PCIe SAS or NVMe™ Class 40 M.2 SSD) - Physical memory availability - Number of CPU Cores - Network speed - Server Operating System - Website availability for NoldusHub installation (tools and images) Results First check for false positives: for instance, some SSD hard drives are not recognized as such. If the test fails to recognize that it is an SSD drive, but you are sure it is, the outcome can be ignored. The same applies to other outcomes. If a test failed and the reason is indeed a misconfiguration (ports not accessible, website not accessible, physical memory too small, etc.), make sure the customer resolves the issue first, and then test again. Distribution of the Installation Readiness Tool The Installation Readiness Tool is maintained and updated by the NoldusHub Developers team. Its release frequency differs from the NoldusHub product releases. However, the most recent version is shipped with the installation package in a separate folder named Ops_InstallationReadinessTool. Subdomain Aim: To set up NoldusHub in your company domain with a secure connection, so NoldusHub starts without security warnings. This step is optional but highly recommended. Before You Begin To open NoldusHub without security warnings, your system administrator should set up NoldusHub in your company domain. Your system administrator should ensure a valid SSL certificate for this domain is available. This information is therefore aimed at the system administrator. NOTE: The steps below are only an example. Your system administrator should have detailed instructions on setting up a secure NoldusHub connection for your particular organization. If you do not want to set up NoldusHub in your company domain, continue with the installation of NoldusHub. Procedure We advise using a secure connection when using NoldusHub. This can be done with a valid SSL certificate, which is necessary to encrypt the connection between the server and the browser. Using SSL certificates fulfills two main requirements: - Encrypted communication between user and server computers - Server identification. By inspecting a certificate that the server presents, it is easier to trust loaded applications from that server. To obtain an SSL certificate: - Buy a certificate from a Certification Authority (e.g. DigiCert). You do not have to install the certificate on the participant PC or the server. Usually it contains the root certificate of the trusted certificate authority and therefore can be validated. This is the recommended solution. - Use a wildcard certificate of your company. Please note that a password for the certificate is required and has to be saved in the plain text configuration file on the NoldusHub server. To set up the certificate: - This step can best be done after installation of NoldusHub. The necessary folders are created during the installation process. - Suppose the company domain name is https://www.mydomain.com. NoldusHub could be set up as a subdomain: https://noldushub.mydomain.com. - Set up a DNS record that points the subdomain to the IP address of the NoldusHub server. - Placement of the certificates in the correct folder is done during the installation of NoldusHub step 2.9. Copy the certificate files (Security Certificate file .cer; Key file .key; Personal Information Exchange file .pfx) to the folder C:\ProgramData\Noldus\Websites\cert on the server. Important: Three certificate files should be copied to the above-mentioned folder: *.cer, *.key, and *.pfx. If you only have a *.pfx file, convert it to *.cer and *.key files and copy all three files to the folder mentioned above. Testing the SSL Certificate After setting the SSL certificate up, its configuration can be tested using the Certificate Checking Tool. This check is good practice before every upgrade. It is essential before a first-time or clean installation. Troubleshooting - Sometimes the combination of files that constitute the SSL certificate fileset is not complete. Missing files can be created using the OpenSSL toolkit. - Sometimes the fileset appears complete, but the password-protected PFX file is not configured with a password. The OpenSSL toolkit can be used to set a password. - Sometimes a certificate will not allow SSL because the PFX file password is not RSA-encrypted. RSA encryption is required. - If you run into problems or get stuck, reach out to Noldus Support. Why Should the SSL Certificate Be Verified? After the SSL certificate is installed on the server, it should be verified whether its configuration is in line with NoldusHub requirements. Important requirements are the combination of different certificate files available and the match between the NoldusHub server domain and the domain for which the certificate was prepared. In addition, one of the certificate files needs to be password-protected (the .pfx file). If any of these requirements is not fulfilled, NoldusHub will not work. Therefore, the SSL certificate should be verified before proceeding to the installation. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-procedure-Y74 Chapter: NoldusHub Procedure - Connect the eye tracker to the test participant PC and position it at the bottom of the monitor. - Optionally, connect a USB camera to the test participant PC. It is also possible to use an internal webcam on a laptop. - Install the eye tracker software and drivers. If you want to install a Tobii eye tracker, see Setup Tobii Eye Tracker for more detailed steps. If you want to install an Eyetech eye tracker, see Setup Eyetech Eye Tracker for more details. See the table Software Components Per Eye Tracker for which software or drivers apply to your eye tracker. - If you already carried out the procedure to Set up screen and camera sharing on Participant PCs, skip to steps 8 and 10 only. If not, continue with the step below. - If you have a previous version of NoldusHub, first uninstall N-Linx Agent and delete all content in the folder C:\ProgramData\Noldus\N-Linx Agent\Plugins. If this is your first time installing NoldusHub, skip this step. - Copy the N-Linx Agent subfolder from the NoldusHub installation USB stick to the desktop of the participant PC. - Open the folder, double-click the file N-Linx Agent Setup and follow the instructions on your screen. Accept the terms in the End-User License Agreement. - N-Linx Agent now opens automatically. If not, open the system tray and double-click the N-Linx Agent icon to open N-Linx Agent. - Enter the hostname of the server in the N-Linx Server Address field and click Connect. At the bottom of the N-Linx Agent window, you now see the text Connected. - Click Add Plugin and browse to the plugin in the N-Linx Agent > Plugins folder on the desktop, select it and click Open. Software Components Per Eye Tracker Eye Tracker Driver/Software Plugin Other Software Tobii Pro Eye Trackers * Tobii Eye Tracker Manager Tobii Pro Eye Tracker N-Linx Agent Eyetech VT-3 Mini EyeTechDriverInstaller16.0 8.16.44 EyeTech Eye Tracker N-Linx Agent * See this overview of the supported eye trackers. Setup Tobii Eye Tracker - Go to the Tobii website. - Download and install the Tobii Eye Tracker Manager. - Select all checkboxes and accept the firewall popup. - Select Install Eye Tracker. - Select the corresponding eye tracker type and click Install. - Accept the Windows popup again. - Once the installation complete popup comes up, click Close. - Connect the eye tracker to the PC. - Select the eye tracker and click Calibrate to check the functionality of the eye tracker. This is also possible if you turn on position guide. Setup Eyetech Eye Tracker - Navigate to: V:\~ Noldus Products\NoldusHub\140 internal only\Devices\EyeTech\EyeTech redistributables installer. - Double-click the file and follow the steps. - Restart PC. - Calibrate the Eyetech eye tracker once server and participant station are set up. In order to work well, the Eyetech eye tracker needs to be calibrated at least once. Prepare Participant PCs for Biosensors Aim To set up your Shimmer biosensor devices and verify whether your sensors are working properly. Before You Begin, Ensure That: - The latest version of Google Chrome is installed. - The NoldusHub computers are connected to the same network switch and are in the same subnet. This means: - The participant PC is connected to the server PC through a 1 Gb Ethernet network. - The IP addresses of both computers fall in the same IP range (the first three blocks of the IP address should be the same). - The Firewall allows inbound and outbound traffic through TCP port 5671. See also Firewall Settings. - The biosensor is supported, and its firmware is updated to the most recent version. See also Supported Biosensors from the reference manual. Procedure You have to carry out this procedure once on every participant PC that you want to use for biosensor data collection. Shimmer Biosensors Consensys has to be installed on at least one PC. It is used to configure the Shimmer devices; this can be done for all Shimmer devices from one PC. - On any PC, open the browser and navigate to shimmersensing.com. - Click Support > Downloads. - Download Consensys V (64-bit). - Open your downloads folder in File Explorer and unzip the zip file. - Locate the file setup.exe in the folder and double-click to run it. Click Yes to continue. - Follow the steps on your screen. - Choose ConsensysBASIC and enter your details (name, organization, and email). - Connect the Shimmer docking station to the test participant PC, insert the Shimmer device, and turn it on using the slider on the side of the device. - If necessary, first do a firmware upgrade of the Shimmer device. If not necessary, you can continue to step 13. - Select the dock you want to configure and click on the Manage button in the bottom left of the application. - Select the firmware option. - Select LogAndStream_Shimmer3_(Version number) and click the Program button. Wait until the software is finished with the firmware upgrade. - Click Manage Devices in the Consensys software. - Click on the picture of the Shimmer device on the right side of your screen. The device will appear in the list on the left. - Click Configure. - In the Sampling Rate field, depending on the type of device, enter the value as seen in the table below and click the warning triangle to validate. Device Type Sampling Rate Shimmer3 ECG Shimmer3 GSR+ - Select the Battery Voltage tile (so it is colored and not greyed out), for both Shimmer3 ECG and Shimmer3 GSR+ devices. - Depending on the device, see the corresponding step for the correct configuration: - For Shimmer3 ECG, make sure that the ECG is selected (colored and not greyed out) in the ECG/EMG tile on the Sensors tab. Then click A on the ECG/EMG tile. Set Gain to 4 and Resolution to 24 bit. - For Shimmer3 GSR+, make sure that the GSR and PPG are selected (colored and not greyed out) in the GSR+ tile. - Click on the field with the parameters you want to measure and click Write Config. Wait until the configuration is complete, and then click Finish. - Close the Consensys application. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Set Up Ntp Client On The Participant Pc'S URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-set-up-ntp-client-on-the-participant-pcs Chapter: NoldusHub Set Up NTP Client on the Participant PCs Aim: To set up the NTP Client on the Participant PCs to achieve synchronization of time between them. Before You Begin To achieve 1ms accuracy on the Participant PC, the following conditions should be met: - The participant PC must have better than 0.1ms of network latency between its time source (NoldusHub server). - The participant PC must be no further than stratum 5 from a highly accurate time source (NoldusHub server). - The participant PC must be within 4 or fewer network hops from the highly accurate time source (NoldusHub server). - The one-day average CPU utilization across each stratum must not exceed 80%. For an explanation on how to verify these conditions, see Procedure below. Note The NTP Server is configured when you run SetupNoldusHub-Server-Docker.bat, which should have been done during the previous step Install NoldusHub on the server. In case the Windows Date & Time settings are changed, rerun Setup-NoldusHub-Participant-NTPClient.bat on the participant PCs and rerun SetupNoldusHub-Server-Docker.bat on the server PC. It is essential to achieve an exact common timebase for all Participant stations and the NoldusHub server. Therefore, all participant stations need to be synced with the NoldusHub server. However, there is no such requirement for the Test leader station. Test leader stations only require a Chrome Browser to operate NoldusHub and are typically synced with a Microsoft time server or a time server in the company network. If NoldusHub time and Company network/Microsoft time are not in sync, the liveview data may be only partially visible, or not visible at all since the Liveview time axis is not aligned with the timeline of the live data sent by the NoldusHub server. Therefore, it is important to verify that the NoldusHub time server is synced with a reliable external time server, while also the Company network time server needs to be synced with a reliable external time server. Small deviations (less than 3 seconds) do merely cause small deviations in the liveview but recorded data will still be in sync. Procedure To configure NTP Client on Participant PC: - Locate the Scripts folder in the installation folder of NoldusHub, under the N-Linx Agent folder. This folder contains two files: Setup-NoldusHub-Participant-NTPClient.bat and Setup-NoldusHub-Participant-NTPClient.ps1. - Copy the folder Scripts to C:\ProgramData\Noldus. - Open Setup-NoldusHub-Participant-NTPClient.bat in the text editor and replace the server IP address (127.0.0.1) with the hostname of the NoldusHub server. - Right-click on PowerShell and click Run as administrator. - Execute the command Set-ExecutionPolicy RemoteSigned. - Run Setup-NoldusHub-Participant-NTPClient.bat. - Restart the Participant PC. To verify the 1ms accuracy conditions on the Participant PC, as mentioned in the Before You Begin section: Measure Network Latency Between NTP Server and NTP Client - Run the following command in Windows PowerShell: w32tm /stripchart /computer:IPAddressOfNtpServer /rdtsc /samples:450 > c:\temp\Target_TsB.csv - Calculate the RoundTripDelay average value from the CSV file; it should be less than 0.1ms. Find the Number of Stratums Between NTP Server and NTP Client - Run the command in Windows PowerShell: w32tm /resync Note: This command should be run after the server and client are already configured in the registry. - Run the command in Windows PowerShell: w32tm /query /status. - Check the value after Stratum; it should be 5 or less. Find the Number of Network Hops Between NTP Server and NTP Client - Run the command in Windows PowerShell: tracert IPAddressOfNtpServer Note: If you receive a timeout error, temporarily disable the firewall on both the client and server PC, then try to run the command again. - Each line starting with a number in the result represents a hop. The last hop number is the number of total hops. - The total hops should be 4 or less. Find the One-Day Average CPU Utilization Across Each Stratum - Run the following command in Windows PowerShell and let it run for 24 hours: Get-Counter -Counter "\Processor(_Total)\% Processor Time" -SampleInterval 10 -MaxSamples 8640 | Select-Object -ExpandProperty countersamples | Select-Object -ExpandProperty CookedValue | Measure-Object -Average > D:\CPUUsage.txt - After 24 hours, results can be found in D:\CPUUsage.txt. Note: The script can be adjusted; for example, the output can be directed to a location other than D:\CPUUsage.txt. The sample interval can be more frequent than 10 seconds, but then MaxSamples should be increased so that SampleInterval x MaxSamples is always 86400 (the number of seconds in 24 hours). Set Up Participant PCs Aim: To display the screen and camera of your participant PCs in NoldusHub. Please follow this procedure for the initial setup of every participant PC. Before You Begin - The latest version of Google Chrome should be installed. - The participant PC must be connected to the server PC through a 1 Gb Ethernet network. - The IP addresses of both computers fall in the same IP range. - The Firewall allows inbound and outbound traffic through TCP port 5671. See also Firewall settings. Procedure - Connect a USB camera to the test participant PC. It is also possible to use an internal webcam on a laptop. - If you have a previous version of NoldusHub, first uninstall N-Linx Agent and delete all content in the folder C:\ProgramData\Noldus\N-Linx Agent\Plugins. If this is the first time NoldusHub is being installed on this computer, skip this step. - Copy the N-Linx Agent subfolder from the NoldusHub installation folder to the desktop of the participant PC. - Open the folder, double-click the file N-Linx Agent Setup and follow the instructions on your screen. Accept the terms in the End-User License Agreement. - N-Linx Agent now opens automatically. If not, open the system tray and double-click the N-Linx Agent icon to open N-Linx Agent. - Enter the hostname of the server in the N-Linx Server Address field and click Connect. At the bottom of the N-Linx Agent window, you will see the text Connected. - Click Add plugin and browse to the Media plugin in the N-Linx Agent > Plugins folder on the desktop. Select it and click Open. - Check that the status of the plugin is Online. Prepare Participant PCs for Eye Tracking Aim: To set up the participant PCs with your specific eye trackers. Follow this procedure once on every participant PC that will use eye tracking. Before You Begin - The latest version of Google Chrome is installed. - The participant PC is connected to the server PC through a 1 Gb Ethernet network. - The IP addresses of both computers fall in the same IP range. - The Firewall allows inbound and outbound traffic through TCP port 5671. See also Firewall settings. - The eye tracker is supported, and its firmware is updated to the most recent version. See also Supported eye trackers from the reference manual. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - System Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-system-specifications Chapter: NoldusHub System Specifications for NoldusHub 1.7 Hardware Requirements When you buy computers for NoldusHub, make sure they meet the requirements mentioned below. Also, make sure the network meets the network specifications. On this page, hardware requirements are specified. A tool is available to facilitate the verification of critical hardware requirements: the Installation Readiness Tool. Please use this tool before starting installation. This may save a lot of time. Server Requirements Component Minimal Recommended RAM 64 GB ECC RAM 64 GB ECC RAM OS Storage 500 GB NVMe™ or SAS SSD 1 TB NVMe™ or SAS SSD Data Storage 2 TB NVMe™ or SAS SSD (optional as backup storage, 2 x 1 TB optional) 2 TB NVMe™ or SAS SSD (optional as backup storage, 2 x 1 TB optional) CPU 2 x Xeon 42xx 2.1GHz, at least 12 physical cores, 24 threads (e.g. 2 x Xeon 4206) 2 x Xeon 42xx 2.1GHz, at least 16 physical cores, 32 threads (e.g. 2 x Xeon 4208) Network 1 Gbps network bandwidth 1 Gbps network bandwidth Peripherals Monitor, keyboard, mouse are optional Monitor, keyboard, mouse are optional Operating System Microsoft Windows Server 2019 Standard, 16-core, LTS Microsoft Windows Server 2019 Standard, 16-core, LTS The server CPU must support virtualization. Make sure this feature is enabled: - On a bare metal server (physical server): The virtualization feature can be enabled in the BIOS. - On a virtual computer: The virtualization feature can be enabled in the hypervisor software (e.g. Hyper-V, VMware). If the virtualization feature is not available, NoldusHub cannot be installed and run on the server. In the NoldusHub system, some processes are spread amongst CPU cores using affinity settings. This method supports only up to 64 CPU cores at the moment, so applying more than 64 CPU cores does not add any benefit for the affinity settings. Participant PC Requirements - Windows 11, 64-bit (Professional or Enterprise); latest update - 32 GB RAM - 256 GB SSD (M.2) - i7 CPU with hyperthreading - 1x USB-A 3.0 - 4x USB-A 2.x - Quadro T1000 GPU graphics card - 1 Gbps network bandwidth - Access to internet (Ethernet or wired) - External Bluetooth Class 2, Bluetooth 2.1 + EDR module: for Shimmer GSR/PPG/EMG - 1x monitor with a maximum resolution of 1920 x 1080 - Reference model: Dell Precision T3660 Supported Eye Trackers Vendor Eye Tracker Model Sampling Frequency (Hz) Supported Screen Size EyeTech VT3 Mini 40, 120 22" Tobii Pro Nano 60 19" Tobii Pro Fusion 60, 120, 250 24" Tobii Pro Spark 30, 60 27" Older models in the Tobii Pro series of eye trackers are expected to work too. Installed Software - N-Linx Agent 1.15.2 - Google Chrome, latest update Remember to frequently check for and install any available updates to your OS and Chrome. Test Leader PC Requirements - Windows 10 or 11, 64-bit (Professional or Enterprise); latest update - 16 GB RAM - 256 GB SSD (M.2) - i7 CPU with hyperthreading - Quadro T1000 GPU graphics card - 1 Gbps network bandwidth - Access to internet (Ethernet or wireless) - 2x monitor with a resolution of at least 1920 x 1080 (recommended), or 1x 32-inch monitor with 4K resolution - Reference model: Dell Precision T3660 Installed Software - Google Chrome, latest update Remember to frequently check for and install any available updates to your OS and Chrome. Network Specifications The NoldusHub network requires 1 Gbps Ethernet. This means that all cables and network adapters must allow at least 1 Gbps data transfer. Take the following requirements into account: Server - 1 Gbps network adapter for connection to the participant PC - Server hostname: verify that the server has an FQDN name - Access to the internet Participant PC - 1 Gbps network adapter for connection to the server - Access to the internet - Fixed IP address in the same range as the server or hostname (see IP Addresses for the procedure to set up a fixed IP address) Test Leader and Observer Devices - 1 Gbps network adapter for connection to the server - Access to the internet - IP address in the same range as the server or hostname Network Cables - Cat5 or higher Network Switch - 1 Gbps uplink speed - Access to the internet - Enough ports for all devices - Recommended devices: NetGear Switch PoE 24 Ports GS728TP or NetGear Switch PoE 8 Ports GS310TP Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## NoldusHub 1.7 - To Enter A Fixed Ip Address For The Server URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-to-enter-a-fixed-ip-address-for-the-server Chapter: NoldusHub To Enter a Fixed IP Address for the Server - Open the Command Prompt as administrator. - Enter ipconfig/all. Your output will contain something like this: Wireless LAN adapter WiFi: Connection-specific DNS Suffix . : home Description . . . . . . . . . . . : Intel(R) Wi-Fi 6 AX201 160MHz Physical Address. . . . . . . . . : 3X-58-X2-XX-04-XX DHCP Enabled. . . . . . . . . . . : Yes Autoconfiguration Enabled . . . . : Yes IPv6 Address. . . . . . . . . . . : 2b02:d454:143b:1:25c3:5386:1c67:ce78(Preferred) Temporary IPv6 Address. . . . . . : 2b02:d454:143b:1:4591:d862:4f1a:8d35(Preferred) Link-local IPv6 Address . . . . . : fa80::25b3:5386:1e67:ce78%16(Preferred) IPv4 Address. . . . . . . . . . . : 192.168.2.12(Preferred) Subnet Mask . . . . . . . . . . . : 255.255.255.0 Default Gateway . . . . . . . . . : fa80::7b96:82bb:ce25:f4cc%16 192.168.2.254 DHCP Server . . . . . . . . . . . : 192.168.2.254 DHCPv6 IAID . . . . . . . . . . . : 138172610 DHCPv6 Client DUID. . . . . . . . : 00-01-00-01-26-61-44-29-X0-5X-XX-36-XX-98 DNS Servers . . . . . . . . . . . : fa80::7d96:82ec:ff25:f4ba%16 192.168.2.254 NetBIOS over Tcpip. . . . . . . . : Enabled - Write down the IPv4 Address, Default Gateway, and DNS server addresses and close the Command Prompt. - Open the Control Panel and choose Network and Sharing Center > Change adapter settings. - Right-click the Ethernet connection and choose Properties. - Click Internet Protocol Version 4 (TCP/IPv4) and choose Properties. - Select Use the following IP address and enter the IP address, Subnet Mask, and Default Gateway. The IP address should be in the same IP range as the Default Gateway. - Select Use the following DNS server address and enter the DNS server address you wrote down in step 3 in the Preferred and Alternate DNS server address fields. If there are more than three DNS server addresses, click Advanced, open the DNS tab and enter the addresses there. Firewall Settings The firewall should allow traffic through the ports described in the table below. These ports are opened in Windows Firewall during the installation of NoldusHub on the server. If you have another firewall, consult its documentation for the procedure to open the ports. - Server PC: Inbound and outbound traffic through TCP (private; public; domain) - Participant PC: Outbound traffic through TCP (private; public; domain) with NLinx Agent version up to 1.9.4; Inbound and outbound traffic through TCP (private; public; domain); Inbound traffic through TCP (private; public; domain) Introduction This page contains the issues encountered during NoldusHub (remote) installation and the possible solutions. Mirantis Container Runtime (MCR) Offline Installation If the Mirantis Container Runtime cannot be installed when the SetupNoldusHub.bat batch file is called, try to use the Install-Mirantis.ps1 PowerShell script with offline installation. Two steps are required: Download the Files for Offline Installation If the download is possible on the server machine, try it from a browser: - For Mirantis Container Runtime 23.0.14: - https://repos.mirantis.com/win/static/stable/x86_64/docker-23.0.14.zip as Docker.zip - https://repos.mirantis.com/win/static/stable/x86_64/containerd-1.6.33.zip as Containerd.zip - Make sure the files are renamed as expected for the installation (Docker.zip and Containerd.zip). If the download is not possible on the server machine, try it on another computer using the PowerShell script: - Run .\Install-Mirantis.ps1 -DownloadOnly in PowerShell. This command downloads Docker.zip and Containerd.zip. Offline Installation Using the Downloaded Files - Copy the Install-Mirantis.ps1, Docker.zip, and Containerd.zip files into the same directory on the server machine. - Run the .\Install-Mirantis.ps1 -Offline command in PowerShell with admin rights. - If the installation is successful, reboot the server machine. Proxy Server This section will be updated based on the proxy server support implementation. If the server is behind a proxy server, the Docker Engine needs a configuration step. Docker Engine Configuration Create a new C:\ProgramData\docker\config\daemon.json file with the following content: { "proxies": { "http-proxy": "http://proxy_server_address:port", "https-proxy": "http://proxy_server_address:port", "no-proxy": "localhost,127.0.0.1" } } - Change the proxy_server_address and port accordingly. In some cases, only the IP address works. - If the proxy server needs additional authentication, use https://username:password@proxy_server_address:port format for http and https protocols accordingly. - Save the file and reboot the server machine. After rebooting, the Docker Engine should use the proxy server. For Docker Engine testing, the docker run hello-world command can be applied. Verifying the proxy server details (no authentication): Invoke-WebRequest https://google.com -ProxyUseDefaultCredentials -Proxy http://proxy_server_address:port Verifying the proxy server details (with authentication): $pass = ConvertTo-SecureString "password" -AsPlainText -Force $cred = New-Object System.Management.Automation.PSCredential -ArgumentList "domain\username", $pass Invoke-WebRequest https://google.com -Proxy http://proxy_server_address:port -ProxyCredential $cred NoldusHub API Container Configuration This section will be updated based on the proxy server support implementation. The NoldusHub API container needs to access the QLM server to check the license (qlmlicenses.noldus.com). This might not be possible directly from the container. At the noldus-hub-api definition in the docker-compose-noldus-hub.yml file, the HTTPS_PROXY environment variable needs to be defined to allow the container proxy access: - Use https://proxy_server_address:port format if no authentication is required. - Use https://username:password@proxy_server_address:port format if authentication is required. - Use domain%5Cusername format for user definition (%5C is for the \ sign) in case of a domain user. Docker Login Fails The docker login command implicitly runs at the beginning of UpdateNoldusHub.bat. It automatically connects to the /v1 endpoint. In some cases, it tries to use the /v2 endpoint for negotiating the image download and gives an authentication required error response. In this case, run these commands one by one, then try to call UpdateNoldusHub.bat: docker login --username noldususers --password %DOCKER_NOLDUSUSERS_PASSWORD% docker login --username noldususers --password %DOCKER_NOLDUSUSERS_PASSWORD% https://index.docker.io/v1/ docker login --username noldususers --password %DOCKER_NOLDUSUSERS_PASSWORD% https://index.docker.io/v2/ Port List For NoldusHub operation, some ports must be open on the server machine. The list is provided for the customer IT department. Earlier versions of NoldusHub do not support secure communication with plugins, so the list of open ports has changed: - NoldusHub 1.4: Port 5672 must be open. - NoldusHub 1.6: Port 5671 must be open. - NoldusHub 1.7: Port 5671 must be open. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## NoldusHub 1.7 - Via Bluetooth URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/noldushub/page/noldushub-17-via-bluetooth Chapter: NoldusHub Via Bluetooth Depending on your version of Windows, some steps can be different. Look at the step that is relevant for you. The following steps have to be done on every Participant PC that has a Shimmer biosensor. - Click the Windows icon on the desktop and type settings. - Windows 10: In the Settings screen, click Devices, ensure that the Bluetooth toggle is turned on. Windows 11: In the Settings screen, click Bluetooth & devices, ensure that the Bluetooth toggle is turned on. - Windows 10: Click the icon in front of Add Bluetooth or other devices. Windows 11: Click Devices. The option Bluetooth devices discovery is now available. Switch this setting from Default to Advanced. - Click Add device. - Ensure that your Shimmer device is on. The device will appear in the list with the ID listed on the back of the Shimmer device. - Click on the device name, and in the PIN field, enter the PIN and click Connect. The Your device is ready to go message will appear. Click Done. - Under Bluetooth & other devices, locate the Shimmer device and check that it is paired. Step 3: Install the Consensys System Tray App The following steps have to be done on every Participant PC that has a Shimmer biosensor. - If the Consensys Tray App v1 is already installed, uninstall this first. (The installer for v2 does not upgrade the existing version, so if v1 is already installed, you will have both versions on your PC simultaneously. Thus we recommend removing the previous version.) After uninstalling v1, delete folder C:\Program Files (x86)\Shimmer\ConsensysSystemTray. - In the NoldusHub installation folder, open Devices - Shimmer and then unzip the zip file. - In the folder that appears, double-click setup.exe and follow the steps on your screen. Select the option to create a desktop shortcut. - Click the Consensys Tray app icon on your desktop. The corresponding icon appears in the system tray. - Right-click the icon, select the appropriate Shimmer device and click Start. Wait until the Streaming message appears. If this does not happen but instead you get the Connection Failed, Disconnected, or Connecting status, check our troubleshooting page. - Open N-Linx Agent and check to make sure the sensors are listed and Online. Set Up Audio Sources on Participant PC Aim To set up the audio sources on the Participant PC so that PC audio is recorded in the screen capture video file and the audio of the microphone is recorded in the face video file. Note NoldusHub participant PCs do have a sound card but no internal speaker. Noldus supplies external speakers that you can plug into the sound card at the back end of the PC. Noldus supplies a webcam that includes a microphone. Before You Begin 2 scenarios are supported: - A headset with microphone that has a single 3.5 mm jack (4 pins). - No headset, external speakers connected. Procedure - Make sure NOT to use the participant PC as a test leader PC, so do not open NoldusHub from the participant PC. On the participant PC: - Either insert the headset into the front of the participant PC or insert the external speakers to the sound card at the back end of the PC. If you don't use a headset, skip to step 4. - Go to Settings → System → Sound. - Select as output: Headphones Realtek® Audio. - Select as input: Jack Mic Realtek® Audio and make sure to give it enough volume (~75). - Unselect the Noldus Media plugin in N-Linx Agent. - Reselect the Noldus Media plugin in N-Linx Agent. On the test leader PC: - Start NoldusHub. - Reselect the devices for the test station of the participant PC. - Open or create a project and have the correct test station selected. - Open the recording module with the correct test station. - On the participant PC, play a video from for example YouTube. Its sound should be hearable on the headset. - On the test leader PC, start a recording. - Comment on the video through the microphone of the headset or, in case of not using a headset, the microphone of the webcam. Make sure the microphone is not muted. - On the test leader PC, stop the recording. - On the test leader PC, replay the recorded session. It should display the screen capture and the face image videos. By muting either video consecutively, verify that: - The screen capture video includes the audio of the participant PC (YouTube video). - The face video includes the audio of the headset or webcam microphone (comments you made on the video). Start and Activate NoldusHub Aim To start and activate your license so you can use NoldusHub. Before You Begin You should have the license key you received from Noldus on hand. This is also referred to as the software activation key. Procedure - On the test leader PC or any other device in the local network, open Google Chrome. - Enter the subdomain value, for instance, https://noldushub.mydomain.com in the address bar of Google Chrome. - A window appears in which you should activate your license. Enter the license key you received from Noldus IT and click Submit. - The first time you start NoldusHub, log in with super-user account name Setup and the provided password, which is identical to the license key. - The default super-user password is unique (the license key). However, it is recommended to have the system administrator change the password during the installation procedure. - Create an official user with the Administrator role according to this procedure. - Use this Admin user account to add users with different roles. - After a test run of NoldusHub, do not forget unlocking used stations and removing test projects before leaving. Notes Get Help – Once logged in, you can get help by clicking the Help Center icon in the bottom right corner of any page. Windows Defender Folder Exclusions Aim The Windows Defender is a Windows antivirus software component that provides real-time protection. It uses some of the available resources (e.g. up to 50% of CPU by default) which could interfere with the NoldusHub recordings. To avoid unwanted high resource usage, some folders can be excluded from real-time checking. Procedure On the server: - Open the folder C:\Program Files\Noldus\NoldusHub. - Double-click the batch file AddDefenderExclusions.bat as administrator. This adds folder exclusions for Defender Antivirus. It will reduce CPU usage as the real-time scanner will not scan some folders. On the participant PC: - Locate the Scripts folder in the installation folder of NoldusHub, under the N-Linx Agent folder. - Double-click the batch file Add-Participant-Defender-Exclusions.bat as administrator. Source: NoldusHub 1.7 Installation Documentation, Noldus Information Technology --- ## PhenoTyper 2 - Acquiring and Analyzing Data - 4.1 Defining an Experiment in EthoVision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-acquiring-and-analyzing-data-41-defining-an-experiment-in-ethovision Chapter: PhenoTyper 4.1 Defining an Experiment in EthoVision - Start EthoVision on your PC. - Create a new workspace or open an existing one (File menu). Next, create a new experiment (from the File menu select New Experiment). What Are Experiments and Workspaces? An EthoVision experiment is the unit of your work. It contains all settings, data files and results related to a particular study or research question. A workspace is the container for one or more experiments. For more information on workspaces and experiments, see Chapter 5 of the EthoVision 3 Reference Manual. - Design your experiment in the Experiment Design module (from the Experiment menu, select Design). What Does the Experiment Design Module Do? In the Experiment Design module, you tell EthoVision how many animals you are tracking in each arena (cage), and which independent variables are important for your study (optional), for example the animal's strain or its age. You can also define the behaviors you will record yourself with keystrokes (optional). Important Note: You must define behaviors in two cases: - When you want to record behaviors that cannot be detected automatically by EthoVision (for example, stretching). - When you want to record the time a stimulus occurred (for example, the buzz or a flash of light), or the working of a device (for example, the turning of a wheel, or the press of a lever). This is especially important when you want to analyze the data in relation to an event that occurred during the recording. For example, assessing the activity levels of the test animal before vs. after PhenoTyper produced a stressful condition. In such cases, you must also connect the cage to the PC through an X-keys Switch Interface that sends the stimulus back to the PC. For more information on the X-keys Switch Interface, see the appropriate technical note that comes with the device. When you define a behavior in EthoVision, it is very important that you set Start Active correctly. The state of the behavior at the beginning of the trial must match the state of your sensors/device at that moment. For more information on designing experiments, see Chapter 6 of the EthoVision 3 Reference Manual. - Define the tracking arena and, if needed, special zones within the arena in the Arena Definition module (from the Experiment menu select Define Arena). What Is an Arena? An arena is the part of the 2D space within the camera image where EthoVision looks for the test animal. If you work with one PhenoTyper, you must draw just one arena. If you work with multiple PhenoTypers at the same time, draw more arenas, one for each cage. For more information on defining arenas, see Section 7.4 of the EthoVision 3 Reference Manual. Note About Using a Shelter: If you put a shelter in the cage, you must define this as a Hidden zone. This way, from the time the animal enters the shelter to the time it is detected again, EthoVision records the animal as being in that zone. To define a hidden zone, draw a zone corresponding to the shelter and specify it as a hidden zone. For more information, see Section 7.4.7 of the EthoVision 3 Reference Manual. Tip About Performing Anxiety Tests: It may be useful to draw an additional zone in the center of the arena. This proves useful when comparing data obtained with PhenoTyper and those obtained with classic Elevated Plus Maze tests. - Calibrate the arena(s). To do so, put an object of known size (for example a piece of paper) in the cage. From the Arena menu, select Calibrate Arena. Why Do I Have to Calibrate Arenas? You must calibrate the arena because EthoVision needs to know the relationship between points in the real world (that is, the cage) and the corresponding points in the monitor image. Without calibration, EthoVision cannot calculate statistics like velocity or distance moved. To perform the best calibration, make sure that the object is placed approximately at the same height as that of the test animal (for mice, 2–3 cm from the cage bottom). For more information on calibrating arenas, see Section 7.7 of the EthoVision 3 Reference Manual. - You are now ready to acquire data. Note About Using an Activity Wheel You can record wheel revolutions in the form of a manually recorded behavior, similarly to other external signals. To do so, you need an X-keys Switch Interface connecting the wheel sensor and the EthoVision PC. - Set a sensor device on the wheel. You can use a simple cycling computer as a substitute for the sensor device. Attach the magnet to the wheel and the sensor to an appropriate location on the cage wall. - If you have not done it yet, install the X-keys Switch Interface on your PC. - Connect the sensor to the PC through the X-keys. - Start the program Macro Maker and program two letters for each cage. - In EthoVision, start the Experiment Design module and in the Behaviors box (Variables menu) define a behavior named for example 'wheel' as Start/Stop. For each PhenoTyper, define the two letters for the Start and Stop codes. Why Two Codes? EthoVision logs behavior in the form of discrete states (e.g. A, B, C, or 0 and 1). When the magnet gets close to the sensor, the sensor sends a signal to the PC through the X-keys Interface. If only one code was defined, the state would not change at the next revolution. With two codes, at each revolution the Wheel state changes from 0 to 1, or from 1 to 0. - In EthoVision, start acquisition. Result: For each arena, one of the two codes is recorded every time the wheel completes a revolution. The codes will be recorded alternately (that is, a, b, a, b, etc.) together with the track. Tip for Analysis: When you calculate frequency of wheel revolutions, take into account that the behavior Wheel consists of two codes per cage. At each revolution, the state of Wheel changes from 0 to 1, or from 1 to 0. Therefore, if the frequency of Wheel is 24, the actual number of revolutions is 48. For information on the X-keys Switch Interface, see the technical note that comes with the device. For information on how to define occurrence of events in the form of manually recorded behaviors, see Section 6.4 of the EthoVision 3 Reference Manual. --- ## PhenoTyper 2 - Acquiring and Analyzing Data - 4.2 Setting Up Data Acquisition in EthoVision URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-acquiring-and-analyzing-data-42-setting-up-data-acquisition-in-ethovision Chapter: PhenoTyper 4.2 Setting Up Data Acquisition in EthoVision Follow the recommendations below if you are about to acquire data with EthoVision: - General data acquisition issues (see below) - Measuring novelty-induced locomotor activity - Measuring anxiety We assume that at this stage you have designed your experiment in EthoVision (see Chapter 6 of the EthoVision 3 Reference Manual), defined and calibrated the arena for each PhenoTyper (see Chapter 7 of the EthoVision 3 Reference Manual), and you have started the Acquisition module. The Data Acquisition Module To acquire your data (tracks and, if planned, manually recorded behavior), from the Experiment menu select Acquire Data or click the Acquire Data button. What Is a Track? In EthoVision, a track is a series of coordinates X,Y of the animal's center of gravity and its body surface area. Coordinates and surface area are recorded from each sample (the video frame that EthoVision processes). Each time you start a trial, EthoVision records a track for each animal. General Data Acquisition Issues - Detection Method: We recommend that you use the Subtraction method when tracking animals in PhenoTyper cages. What Is the Subtraction Detection Method? The subtraction method consists of subtracting a reference image of the arenas with no animals present from the live image (with the animals). Each pixel in the images has a gray scale value. If a pixel in the live image is identical to a pixel in the reference image (that is, it has the same gray scale value), when one is subtracted from the other it gives the value of zero. On the other hand, if an animal is present, the animal's pixels will have a different gray scale value from the same pixels of the reference image, so when they are subtracted they will give a value different from zero. To select the Subtraction method, from the Tracking menu select Processing, then Detection Method. - Remove the sawdust or other bedding material and make sure that there are no animals in the cages. Next, from the Tracking menu select Update Detection Variables, and click the Update Now button. - EthoVision acquires the reference image. Put the bedding material and the animals back into the cages. We recommend that you take the reference image before you put any material on the cage floor. For information on the methods of object detection, see Section 8.3 of the EthoVision 3 Reference Manual. - Test the Detection Method: Detection settings depend greatly on the color of the animal's fur. We recommend that, for each strain and color type, you make a test recording of for example 24 hours. You can then calculate the maximum distance moved and check whether values are suspicious. For example, if you use a sample rate of 12.5 samples/s to track a mouse, it is unlikely if not impossible that you get values of maximum distance moved like 20 cm. Such values are obtained if EthoVision mistakenly identifies other objects as the test animal in one or few samples. - Use Erosion and Dilation: You can improve detection of the animals by using the dilation/erosion function. From the Tracking menu, select Processing, then Image Filtering. We recommend you select First erode, then dilate. - Record the Occurrence of Automatic Events: If you want to record the time a stimulus occurred (for example, the buzz or a flash of yellow light), or the working of a device (for example, the turning of the wheel in the cage, or the press of a lever), you must define these behaviors in the Experiment Design module before you start data acquisition. This is especially important when you want to analyze the data recorded in a time interval within the trial. Using X-Keys Switch Interface With PhenoTyper You can analyze the activity of the test animal after PhenoTyper produced a sound by connecting a X-Keys Switch Interface to the PhenoTyper cages. This allows you to analyze a specific part of a recording session rather than the whole session. What Is a X-Keys Switch Interface? The X-keys Switch Interface is a versatile device that allows input for TTL (Transistor-Transistor Logic) signals and for switch outputs from sensors and control devices such as passive Infrared detectors, beam-break detectors and operant levers. It turns these signals into keystrokes that can be recorded by EthoVision. - If you have not done it yet, install the X-keys Switch Interface on your PC. - Connect the PhenoTyper's switch to the X-keys Interface in such a way that when the switch closes, the signal is sent to the X-keys too. - Connect the X-keys Interface to the PC via one of the PC's USB ports. - Start the program Macro Maker and program one or two letters for the channels of the X-keys Interface linked to the switch. The number of channels depends on the switch, and on whether you define a behavior as Start/Stop or Mutually Exclusive; for more information see Sections 6.4.1 and 6.4.2 of EthoVision 3 Reference Manual. - In EthoVision, start the Experiment Design module and in the Behaviors box (Variables menu) define a behavior and assign the same letter you defined above. You may need to define one or two letter codes depending on whether you define a behavior as Start/Stop or Mutually Exclusive; for more information see Sections 6.4.1 and 6.4.2 of EthoVision 3 Reference Manual. - In EthoVision, start acquisition. The code will be recorded together with the track when the device is activated. For information on the X-keys Switch Interface, see the technical note that comes with the device. For information on how to define occurrence of events in form of manually recorded behaviors, see Section 6.4 of EthoVision 3 Reference Manual. Measuring Novelty-Induced Locomotor Activity Preliminary studies suggest that the early fraction of a long measurement in PhenoTyper provides important data on novelty-induced locomotor activity — for example, the first hour in a 24-hour measurement, or the first day in a multiple-day measurement. - Mobility Detection — If you want to calculate statistics of Mobility, you must enable the Mobility detection function (Tracking menu; see Section 8.10 of EthoVision 3 Reference Manual). - Specify an Aversive Signal and the Condition Activating It — Please see the text under Measuring Anxiety below. --- ## PhenoTyper 2 - Acquiring and Analyzing Data - Acquiring and Analyzing Your Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-acquiring-and-analyzing-data-acquiring-and-analyzing-your-data Chapter: PhenoTyper Acquiring and Analyzing Your Data In this chapter you find information on how to: - Define the experiment and the tracking area (Arena) in EthoVision (see below). - Set up PhenoTyper and EthoVision to perform a certain test. - Calculate statistics in EthoVision for a certain test. Note: If the EthoVision computer is connected to PhenoTyper cages through TTL cables, when you start it all PhenoTyper devices are switched on. This is a normal event, because the PC sends high TTL signals to the printer port at startup. When you start EthoVision, all devices are turned off. --- ## PhenoTyper 2 - Acquiring and Analyzing Data - Analyzing Novelty-Induced Locomotor Activity URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-acquiring-and-analyzing-data-analyzing-novelty-induced-locomotor-activity Chapter: PhenoTyper Analyzing Novelty-Induced Locomotor Activity Choosing Analysis Parameters and Statistics You can assess locomotor activity levels by selecting the following parameters (from the Analysis menu select Add Parameter): - Velocity — The animal's speed for each sample. You can then let EthoVision calculate statistics such as the average, minimum and maximum values. To select statistics, right-click the parameter row (or column) and select Parameter Properties. - Movement — A state parameter whose possible states are discrete. At each sample, Movement has one of two values: Moving or Not Moving. Right-click the Movement row (or column) and select Parameter Properties. Set the Start Velocity and Stop Velocity thresholds to tell EthoVision when to consider the animal moving or not moving. You can then let EthoVision calculate statistics such as the number of times the animal was moving or the total duration of time the animal was not moving. - Mobility — Similar to Movement, however it measures movement of the body independent of spatial displacement. At each sample, Mobility has one of three values: Immobile, Mobile or Strongly Mobile. Right-click the Mobility row (or column) and select Parameter Properties. Set the Immobile Threshold and Strong Mobility Threshold to tell EthoVision when to consider the animal immobile, mobile or strongly mobile. You can then let EthoVision calculate statistics such as the number of times the animal was mobile or the total duration of time the animal was immobile. Note: in order to calculate the Mobility parameter, you must activate the Mobility detection function before acquisition (see Section 8.10 of EthoVision 3 Reference Manual). - Distance Moved — The distance traveled by the animal's center from one sample to the next. You can then let EthoVision calculate statistics such as the total distance moved during the recording or part of it, or the average and standard deviation of distance moved from one sample to the other. To select statistics, right-click the parameter row (or column) and select Parameter Properties. - In Zone — A state parameter that describes whether the animal is in a zone. This is very useful when you define zones such as the shelter. Note: if you use a shelter, before acquisition you must define it as a hidden zone. Analyzing Novelty-Induced Locomotor Activity Choose the Analysis Parameters and Statistics You can assess the test animal's locomotor activity by selecting parameters from the Analysis menu. Use Add Parameter to select the relevant parameters. You can define zones such as the top of the shelter (define it as hidden zone) or the central area of the cage floor. You can then let EthoVision calculate statistics like the number of times the animal entered the shelter, or the average and standard deviation of the time spent in the central area. To select statistics, right-click the parameter row (or column) and select Parameter Properties. Other parameters may be of interest when measuring locomotor activity. See Section 11.3 of the EthoVision 3 Reference Manual. Analyzing Anxiety Choose the Analysis Parameters and Statistics You can assess the test animal's anxiety by selecting the following parameters (from the Analysis menu select Add Parameter): - In Zone — A state parameter that describes whether the animal is within a zone. - If the zone is the top of the shelter, statistics like the time spent in the zone may provide information on the risk-taking behavior of the animal, but only for the early part of a measurement (for example, the first hour). - If the zone is the shelter defined as a hidden zone, you can calculate statistics like the number of times the animal entered the shelter, or the average and standard deviation of the time spent in the shelter. - If the zone is the center of the cage floor, you can calculate statistics like the average and total time in that zone. In preliminary studies, these correlate with parameters calculated for the open arms in Elevated Plus Maze tests. To analyze the time the animal spent on top of the shelter and inside the shelter, make sure that on the In Zone page of the Parameter Properties window, the zone shelter is selected both as a normal zone and as a hidden zone (indicated by [Hidden]). The analysis result spreadsheet shows statistics for the two zones separately. To select statistics, right-click the parameter row (or column) and select Parameter Properties. - Movement, Mobility, Distance Moved — See the corresponding parameters under Analyzing Novelty-Induced Locomotor Activity. Analyzing Activity at the Wheel Choose the Analysis Parameters and Statistics - Wheel Movement — This is defined as a manually recorded behavior (its name depends on what you have specified in EthoVision's Behaviors box). Select the parameter by opening the Add Parameters box, selecting Individual Behaviors, and then selecting Manually Recorded Behaviors in the right-hand pane. You can then let EthoVision calculate statistics like the frequency of revolutions. To select statistics, right-click the parameter row (or column) and select Parameter Properties. When you calculate the frequency of wheel revolutions, take into account that the behavior Wheel consists of two codes per cage. At each revolution, the state of Wheel changes from 0 to 1, or from 1 to 0. Therefore, if the frequency of Wheel is 24, the actual number of revolutions is 48. Source: PhenoTyper 2.0 Reference Manual - Acquiring and Analyzing Data, Noldus Information Technology --- ## PhenoTyper 2 - Acquiring and Analyzing Data - Measuring Anxiety URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-acquiring-and-analyzing-data-measuring-anxiety Chapter: PhenoTyper Measuring Anxiety Specifying an Aversive Signal and the Condition Activating It - From the Tracking menu select Experiment Control. - Click the Action button of the Experiment Control window. - Specify the action, pin number (this refers to the number of the printer port pin that sends the TTL signal) and the characteristics of the signal. Next, click OK. In the example below, we have set the buzzer on line 6. For more information on how to specify an action, see Section 9.4.7 of EthoVision 3 Reference Manual. - In the Experiment Control window, click one of the three Condition buttons to define a condition. In the example below, we have defined a time condition — the buzzer will be activated one minute after the start of the recording. For more information on how to set a condition, see Section 9.4 of EthoVision 3 Reference Manual. - Make sure that the PhenoTyper cages are set with the correct jumpers for the aversive signal. For information on how to activate TTL communication lines, see the relevant section of this manual. Defining the Shelter as a Hidden Zone If the cage contains a shelter, you must define this as a hidden zone. This way, from the time the animal enters the shelter to the time it is detected again, EthoVision records the animal as being in that zone. To define a hidden zone, start the Arena Definition module, draw a zone corresponding to the shelter and specify it as a hidden zone. Next, go back to the Data Acquisition module. For more information on hidden zones, see Sections 7.4.7 and 9.5 of EthoVision 3 Reference Manual. Analyzing Data in EthoVision Follow the instructions below if you have acquired the data with EthoVision and you want to calculate statistics that are important for your test: - General analysis issues - Analyzing novelty-induced locomotor activity - Analyzing anxiety - Analyzing activity at the wheel Please note that this manual does not contain detailed information on how to select data and perform analyses. You will find this information in Chapter 11 of EthoVision 3 Reference Manual (with more information on the analysis parameters given in Chapter 12). What you will find here is information on special issues related to PhenoTyper, what parameters you must select and with which options in order to obtain the results that are most meaningful for your study. The Analysis Module To analyze your data, from the Experiment menu select Analyze Data or click the Analyze Data button. For information on how to analyze data, see Chapter 11 of EthoVision 3 Reference Manual. General Analysis Issues Within-Individual Comparison of Behavior PhenoTyper allows you to acquire behavioral data for extended periods of time. Therefore, comparing behavior of the same individual in two different situations becomes more feasible. Data within a track (that is, within the same recording) can be split into two or more parts with EthoVision's Nesting function (see Section 11.1.3 of EthoVision 3 Reference Manual). Example: Activity of four animals has been recorded in four PhenoTypers (one animal in each cage) for two hours. A buzzing sound was then produced exactly one hour after the start. We want to compare the behavior of the rat between the two hour intervals (before vs. after the stimulus). - Select the tracks you want to analyze (from the Data menu select Select Tracks; see Section 11.1.1 of EthoVision 3 Reference Manual). If you want, you can also group data of more tracks (see Section 11.1.4). - From the Data menu select Nesting, then Time Window. The Time Window function allows you to select part of the track (From time X To time Y), or divide the track into two or more equal intervals using the Intervals option. The original data are not modified or deleted. - Under Interval, select Duration and type the duration of the interval in the field next to it. Since we want to split the data into two equal intervals of one hour, type 01:00:00.000 (hh:mm:ss:ddd). Next, click OK. In the analysis spreadsheet, each track (one per test animal) will show one row (or column) for each interval defined. If you want to only analyze part of the track instead of comparing parts of equal duration, specify the time of start and end of the interval in the From and To boxes. The time interval specified will be analyzed, not the remaining intervals. - Add the parameters and specify their statistics, then click the Calculate button. Analyzing Data in Different Time Intervals for Different Cages The procedure shown above does not work when you want to analyze data in intervals that occur at different times or are of different length in two or more cages. For example, if you have specified the yellow light to switch on when the mouse enters a special zone of the cage, this is likely to occur at different times in different cages, so a single time value (for example, 1 hour after start) will not work. The solution is to log the switching of devices as a state parameter. You can do this by connecting a X-Keys Switch Interface to the PhenoTyper cages and defining the switch as a manually recorded behavior in EthoVision. For information on the X-keys Switch Interface device and how to use it with EthoVision, see the relevant note in this manual and the technical note that comes with the device. --- ## PhenoTyper 2 - Assembling PhenoTyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-assembling-phenotyper Chapter: PhenoTyper Assembling PhenoTyper Important Note Given our policy of continuous improvement of our products, the PhenoTyper system you have purchased may not exactly match the descriptions and pictures in this manual. Parts List Cables - PT-T10.1/P — Top Unit V1.1 PAL/CCIR camera version. Includes camera, circuitry, lights, buzzer. - PT-T10/N — Top Unit V1.1 NTSC/EIA camera version. Includes camera, circuitry, lights, buzzer. - PT-CU-10 — Control Unit. Includes cable to connect to PhenoTyper. - PT-PS1 — Power supply 120V AC–240V AC / 24V DC. - PT-LPT — PC TTL cable 1.8 m. - PT-LPT18 — TTL extension cable 1.8 m. Extends length of PT-LPT. - PT-LPT100 — TTL extension cable 10 m. Extends length of PT-LPT. - PT-TTL18 — TTL feedthrough cable 1.8 m. - PT-PSC — Power supply feed-through cable 1.8 m. - PT-BNC30 — BNC cable 75Ω 3 m. - PT-BNC100 — BNC cable 75Ω 10 m. Bottles, Feeders and Shelters - PT-B-00 — Standard drinking bottle. Model 3000 can have 1 bottle; Model 4500 can have one or two. - PT-F-00 — Feeder, model 3000. Made of stainless steel. - PT-F-01 — Feeder, model 4500. Made of stainless steel. - PT-SH-BL-0 — Shelter, small black. Size 100 x 100 x 50 mm, holes Ø 32 mm. - PT-SH-WH-0 — Shelter, small white. Size 100 x 100 x 50 mm, holes Ø 32 mm. - PT-SH-BL-1 — Shelter, large black. Size 150 x 150 x 120 mm, holes Ø 75 mm. - PT-SH-WH-1 — Shelter, large white. Size 150 x 150 x 120 mm, holes Ø 75 mm. Cage Model 3000 - PT-C-S-A-0 — Wall plain, model 3000. Material: polymethylmethacrylate. - PT-C-S-A-1 — Wall with airgap, model 3000. Material: polymethylmethacrylate. - PT-C-S-A-1s — Airgap shielding, model 3000. Material: polymethylmethacrylate. - PT-C-S-A-2 — Wall prepared for feeder and bottle, model 3000. Material: polymethylmethacrylate. - PT-C-S-A-5 — Wall prepared for shelter, model 3000. Material: polymethylmethacrylate. - PT-C-S-A-10 — Separation plate, model 3000. Material: polymethylmethacrylate. - PT-C-S-A-21 — Cage bottom, model 3000. Material: polymethylmethacrylate, dual satin opaque. Side 31.5 cm. Includes L piece (5 x 3 x 1.5 cm) to keep cage walls firm. - PT-C-S-MNT1 — Set of assembling material and tools for the cage, model 3000. Includes: - 8x hexagon socket screw, cap head, stainless steel, M5 x 12 - 1x hexagon key 3 mm - 1x clamp for drinking bottle - 1x spacer for drinking bottle - 1x stainless steel screw, pan head, M4 x 10 - 1x stainless steel shake-proof external star, M4 - 1x nylon screw CS M4 x 10 - 6x black nylon spacer 5 mm - 6x white nylon screw CS M4 x 16 - 6x white nylon nut/washer Cage Model 4500 - PT-C-L-A-0 — Wall plain, model 4500. Material: polymethylmethacrylate. - PT-C-L-A-1 — Wall with airgap, model 4500. Material: polymethylmethacrylate. - PT-C-L-A-1s — Airgap shielding, model 4500. Material: polymethylmethacrylate. - PT-C-L-A-1sM — Airgap shielding for mice, model 4500. Material: polymethylmethacrylate. - PT-C-L-A-2L — Wall prepared for feeder and bottle, model 4500. Material: polymethylmethacrylate. - PT-C-L-A-5 — Wall prepared for large shelter, model 4500. Material: polymethylmethacrylate. - PT-C-L-A-5M — Wall prepared for small shelter, model 4500. Material: polymethylmethacrylate. - PT-CONV-SL — Separation plate with air holes, model 4500. Material: polymethylmethacrylate. - PT-CONV-SLM — Separation plate with air holes for mice, model 4500. Material: polymethylmethacrylate. - PT-C-L-MNT1 — Set of assembling material and tools for the cage, model 4500. Includes: - 8x hexagon socket screw, cap head, stainless steel, M5 x 12 - 1x hexagon key 3 mm - 2x clamp for drinking bottle - 2x spacer for drinking bottle - 2x stainless steel screw, pan head, M4 x 10 - 2x stainless steel shake-proof external star, M4 - 2x nylon screw CS M4 x 10 - 10x black nylon spacer 5 mm - 10x white nylon screw CS M4 x 16 - 10x white nylon nut/washer Assembly Instructions Despite variation in sizes and wall configurations, assembling PhenoTyper involves the same basic steps. The assembly instructions provided below are based on the home cage version, model 3000. Checking the Wall Elements The following letters are used for reference throughout this chapter: - A — Wall prepared for feeder and bottle (replaced by C in the basic cage) - B — Wall with airgap - C — Wall plain (or prepared for shelter) - D — Cage bottom - E — Separation plate - F — Airgap shield - G — L piece for fixing the walls (model 4500 only) Mounting Set Remove the protecting sheet from the walls. Remove the transparent sheet from the walls (one side) and from the airgap shields (both sides). Assembling the Cage Please note that the following diagrams may not exactly represent the components of your own system. Repeat steps 1 and 2 to mount the shield on the second wall with airgap. Please make sure that for both walls the airgap shield is placed on the inner side. Fixing the Walls in Model 4500 Locate the corner of the cage bottom that does not have the square marks on the inner sides and place the two L pieces as shown. You do not need to do this for Model 3000. Placing the Drinking Bottle (Optional) Place the drinking bottle as shown in the figure. To prevent damage to the cage walls, first insert the end of the drinking tube into the appropriate hole, then gently push the bottle neck towards the cage wall until it is inserted into the clamp. Placing the Shelter (Optional) This is possible if you have items PT-C-S-A-5 and PT-SH-BL(-WH)-0. Before placing the shelter, remove the protecting sheet from the inside. Remove the protecting sheets from both sides of the separation plate (E) and place it on top of the cage. The separation plate prevents the animal from getting out of the cage when you remove the Top Unit. Placing the Feeder (Optional) Place the metal frame and the Top Unit on top of the cage so that the Top Unit's front panel with the red LED and the 15-pin socket is on the same side as the feeder. Cable Connections PhenoTyper cages usually come with the following cables: - A, B — Power cord and transformer (code PT-PS1). - C — Power feed-through cable (code PT-PSC). - D — PC TTL cable (code PT-LPT). - E — TTL feed-through cable (code PT-TTL18). - F — Composite video cable of variable length with BNC connectors (code PT-BNCxx). If you have purchased one PhenoTyper cage, the cable set only includes A, B and D. Connecting the PC to One PhenoTyper If you work with just one PhenoTyper cage, do the following: - Connect the PhenoTyper's Supply In socket to the power outlet using cables A and B. - Connect the PhenoTyper's Video Out socket to the Video In socket of the Picolo board installed on your computer, using a video cable with BNC connectors. - If you want EthoVision to send TTL signals to control the experiment (for example, to switch on a light or produce a sound), connect the PC's printer port to the PhenoTyper's 9-pin TTL In connector next to the video socket, using the PC TTL cable (D). If the computer is running, all PhenoTyper devices (lights and sound) are switched on until you start EthoVision. For more information on using TTL signals, see the TTL signals section of this manual and Section 9.4.7 of the EthoVision 3 Reference Manual. - Connect the Control Unit to the PhenoTyper by attaching the Control Unit cable to the PhenoTyper's 15-pin Sub-D socket. This is located on the front panel, next to the red LED. The function of the Control Unit is (1) to test that all devices in a cage function correctly and (2) to customize each cage (for example, adjust light intensity). Therefore, you do not need to keep the Control Unit connected to any cage once you have adjusted the options you require. Connecting Multiple PhenoTyper Cages to a PC You can connect several cages to the same PC. In order for EthoVision to process the image for all of them, you need one or more Quad Units. A Quad Unit mixes the images coming from four cages into one, just like an ordinary video mixer mixes two images into one. In this setup, the PhenoTyper cages are connected in series, so each cage gets power and TTL signals from the previous one. The video is sent to the four Video In sockets of the Quad Unit, and then to the PC via the Video Out. - Follow the instructions above to connect the first PhenoTyper to the PC and the power supply. Do not connect the PhenoTyper's Video Out to the PC. - Connect the Video Out socket of each PhenoTyper to one of the Quad Unit's Video In sockets, using composite cables with BNC connectors. - Connect the Quad Unit's Video Out socket to the Video In socket of the Picolo board installed on the PC, using a composite cable with BNC connectors. - Connect the TTL Out socket of the first, second and third PhenoTyper to the TTL In socket of the second, third and fourth PhenoTyper respectively, using the TTL feed-through cables (E). - Connect the Supply Out socket of the first cage to the Supply In socket of the second cage, then the Supply Out socket of the second cage to the Supply In socket of the third cage, and finally the Supply Out socket of the third cage to the Supply In socket of the fourth cage, using the power feed-through cables (C). Do not connect the power outlet to more than one PhenoTyper cage — only the first cage must be directly connected to the power. - Switch on all the PhenoTyper cages. The switch is on the back panel of the Top Unit. The red LEDs on the cages' front panels will turn on. Notes: - Some of the lamps may burn less intensely than others when first switched on. Wait a few seconds until all lamps burn equally. - You can also connect TTL cables the other way round (from the TTL In of a PhenoTyper to the TTL Out of the next). This does not affect the direction of data flow. TTL signals always go from the PC to the first PhenoTyper, and then to the others. Source: PhenoTyper 2.0 Reference Manual - Assembling PhenoTyper, Noldus Information Technology --- ## PhenoTyper 2 - Maintenance URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-maintenance Chapter: PhenoTyper Maintenance Your PhenoTyper cage will last longer if you follow these few recommendations. Please always keep the cages clean and dry. Make sure that no liquid penetrates the equipment on top of the cage. Keep this manual in a safe place so that it is available to provide information at any time and so that new employees can familiarize themselves with the equipment. Cleaning the PhenoTyper Cage To clean the cage, please use water and soap only. Do not wash the cage with water at more than 80° C (176° F). Please do not use chemicals to wash the cage. Do not use autoclaves to sterilize the cage or any of its components! It may damage it. Acceptable Cleaning Techniques and Substances - Electronic beam - Gamma radiation - Ethylene oxide gas - Hydrogen peroxide (up to 3% concentration) - UV radiation - High intensity visible light - Alkaline substances (albeit in low concentrations) - Low-temperature hydrogen peroxide gas plasma - Diluted solutions of (isopropyl) alcohol can be used to wipe down acrylic without adverse reaction. - Do not use wet ethylene oxide, steam, strong acids, or hydrocarbons. Important Note: Make sure that the following chemicals do not come in contact with the plastic walls: - Acetaldehyde - Acetone - Allyl alcohol - Aniline - Acetic acid - Benzene - Benzyl alcohol - Butyl acetate - Butyl alcohol - Carbon disulfide - Carbon tetrachloride - Chloroform - Chlorine gas - Chlorobenzene - Dichloroethane - Dioxane - Ethanol - Ethoxyethane - Ethyl acetate - Hydrogen fluoride - Hydrogen peroxide (>10%) - Methanol - Methyl acetate - Methylated spirit - Methylene chloride - Methylethylketone - Nitric acid Cleaning the Top Unit To clean the Top Unit, please use a damp cloth. Please do not use chemicals or soap to wash the Top Unit. Make sure that no liquid penetrates the equipment inside the Top Unit or the connectors. Technical Support If you run into problems of any kind, please let us know. You can contact us via our web site by filling out a Support Request Form. You can also contact Technical Support by e-mail, phone (during working hours), or fax. Please check this reference manual carefully before contacting the Technical Support Department. If you need to send EthoVision data by e-mail, please use the Backup procedure to make a copy of your experiments, and send them as attachments. When you receive it back, use the Restore procedure to retrieve the data. For more information on how to use the Backup and Restore functions, please see Sections 13.1 and 13.2 of the EthoVision 3 Reference Manual respectively. Replacement of Components If any component breaks or wears out, please contact our Technical Support Department to have it sent back to us. Please note that in any case you must send it to our international headquarters (Wageningen, The Netherlands) no matter where you are. Broken components will be fixed or replaced with new ones. Important Note: Plastic components (such as the cage walls) will only be replaced or repaired free of charge if they are broken due to a defect of workmanship and the damage is reported within one month of shipment. Other components are covered by a one year guarantee; to claim under guarantee you must report the damage within one year of shipment. It is possible that you may have a service contract entitling you to free replacement of parts for a longer period; please contact the support department if you are not sure. In any case we can still fix or replace the parts, but it may be necessary to levy a charge. The guarantee is only valid if you treat the PhenoTyper as described in this manual. In any case, shipping broken parts is at your expense, while sending repaired or replacement parts back to you will be at our expense. If you connect the PhenoTyper to any third-party products, such as a video tracking system other than EthoVision, Noldus Information Technology is not responsible for maintenance of that product, or for damage done to the PhenoTyper by that product. Order Spare Parts You can order spare parts for the PhenoTyper. Please see the parts list for available components and contact us to place your order. Source: PhenoTyper 2.0 Reference Manual - Maintenance, Noldus Information Technology --- ## PhenoTyper 2 - Preparing PhenoTyper - 3.4 Copying Light Intensity Values from One PhenoT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-preparing-phenotyper-34-copying-light-intensity-values-from-one-phenot Chapter: PhenoTyper 3.4 Copying Light Intensity Values from One PhenoTyper to Another You can copy the values of light intensity (infrared and visual stimuli) from one cage to other cages. If you want to copy one value only (for example, the intensity of the yellow light), first copy all values from the source cage and then write only the value you require to the other cages. Reading the Values from a Cage - Connect the Control Unit to the PhenoTyper cage you want to copy the values from and switch on that cage. - Press the FUNCTION buttons until READ FROM PT is shown on the Control Unit display. - Press TEST. The Control Unit reads the light intensity values from all sources (IR, yellow, and white). The yellow and white light switch on and the Control Unit display shows 'READING ...' until the reading process is completed. - Follow one of the procedures below to copy the values to other cages. Writing the Values to a Cage - Connect the Control Unit to the PhenoTyper cage you want to copy the values to and switch on that cage. - Press the FUNCTION buttons until WRITE TO PT is shown on the Control Unit display. - Press TEST. The Control Unit writes the light intensity values for all sources (IR, yellow, and white) to the cage. The yellow and white light switch on and the Control Unit display shows 'WRITING ...' until the writing process is completed. If a value copied differs from that currently selected in the cage, the Control Unit display shows Increase ... or Decrease ... while the intensity is increased or reduced to match the value copied. When the display shows WRITE TO PT again, all values are updated. Repeat the procedure to copy the values to other cages. Writing a Single Value to a Cage - Make sure that you have read the light intensity values from a cage. - Connect the Control Unit to the PhenoTyper cage you want to copy the value to and switch on that cage. - Press the FUNCTION buttons until the light device you want to update is selected. - Press TEST. The Control Unit writes the light intensity value to the cage. If you have selected the yellow or the white light, these switch on for a short time. The display shows 'WRITING ...' until the writing process is completed. If the value copied differs from that currently selected in the cage, the Control Unit display shows Increase ... or Decrease ... while the intensity is increased or reduced to match the value copied. When the display shows WRITE TO PT again, the value is updated. Repeat the procedure to copy the values to other cages. Example: Copy the Light Intensity Value of IR Array-1 from Cage 1 to Cage 2 - Connect the Control Unit to cage 1 and read the values. - Connect the Control Unit to cage 2 and press the FUNCTION buttons until you see 4 IR array-1. - Press TEST. - When the display shows 4 IR array-1 again, the value is updated. 3.5 Specifying Communication Lines Between EthoVision and Each PhenoTyper If your testing protocol requires activating light or sound stimuli during data acquisition, you can set up EthoVision and PhenoTyper so that EthoVision activates the PhenoTyper's lights and buzzer when a condition is met during the observation. Eight communication lines are available for this purpose, and EthoVision needs to know which type of signal to send to which PhenoTyper. For example, if you specify in EthoVision that line 3 sends the signal activating the buzzer, you must 'open' line number 3 in those cages in which you want the sound to be produced. You can specify that the same signal is sent simultaneously to the cages, or at different times for each cage, depending on when a specific condition is met. Procedure Repeat the following procedure for each PhenoTyper. - Make sure that the PhenoTyper is turned off. - Remove the Top Unit from the cage, put it upside down, and unscrew the covering. - Lift carefully the covering from the side of the main switch (back panel). Below that, you see the main board. Do not try to remove the covering completely — the lights are connected to the main circuitry board underneath. - Locate the jumpers on the main board. They are just behind the pair of 9-pin connectors for TTL communication, next to the Noldus logo. Jumpers are short lengths of wire that complete a circuit. By placing the jumper over a pair of available pins, you activate that line. In the PhenoTyper board, jumpers can be placed in any of 8 positions (1 to 8, from right to left looking from the 9-pin connectors' side). - Define which pin of the PC's printer port you are going to use for a certain stimulus (available pin numbers from 3 to 9; pin 2 is always used by the white light, while pin 1 is not used). Write this number down because you will need to specify it in EthoVision when you define the Actions on Parallel Port. If you want to send the same signal (for example, yellow light) to different PhenoTyper cages at different times — that is, if the stimulus is independent in each PhenoTyper — you must set a separate line (pin of the printer port) in each cage. For example, connect pins of pair number 3 for yellow light in cage 1, and pins of pair number 4 for yellow light in cage 2. - Choose the pair of pins to be connected, and place the jumpers on it. --- ## PhenoTyper 2 - Preparing PhenoTyper - Example 5 — Set Two Signals in 4 PhenoTyper Cages URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-preparing-phenotyper-example-5-set-two-signals-in-4-phenotyper-cages Chapter: PhenoTyper Example 5 — Set Two Signals in 4 PhenoTyper Cages The buzzer and the yellow light are activated simultaneously in all cages. - Choose one TTL line for the sound: printer port pin 6 (see the table on page 43). Take note of this number because you must specify it in EthoVision (see below). - Choose the TTL line for the yellow light: printer port pin 3 (see the table on page 43). Take note of this number because you must specify it in EthoVision (see below). - For each cage, open the Top Unit and set one jumper in position 4 (which corresponds to line 6 for the sound) and one in position 8 (which corresponds to line 3 for the yellow light). The position numbers are printed on the board next to the jumpers. - In EthoVision, define a condition that activates pin number 6 for the sound and one that activates pin number 3 for the light (see Section 9.4.7 of EthoVision 3 Reference Manual). Next, assign a condition for each action. For example, two Elapsed Time Conditions: the buzzer is activated one hour after the start of the trial, while the light is turned on two hours after the start of the trial. Result — The lines are not separated. When the condition assigned to pin 6 is met, the buzzer is activated in all the cages. When the condition assigned to pin 3 is met, the yellow light is activated in all the cages. In EthoVision, you can also assign the same condition to more lines (pin numbers). 3.6 Adjusting Camera Focus - Connect PhenoTyper to the PC as described on page 31 (TTL connections are not necessary). If you are using multiple PhenoTypers, connect the cages to the PC through the quad unit as described on page 33. - Switch on PhenoTyper(s). - Do one of the following: - Connect the PhenoTyper's video cable to a TV monitor. OR - Connect the PhenoTyper's video cable to the Picolo board of your EthoVision computer. Then start Easy Grab (from the Start menu select All Programs, then Noldus, EthoVision 3, and finally EasyGrab). Next, from the Command menu select Live to view the live video image on your computer screen. - Put the test animal (or an object of approximately the same height) in the cage. - If the object is out of focus, turn off PhenoTyper, then remove the Top Unit from the cage and put it upside down. Next, unscrew the covering. - The camera is in the centre of the Top Unit's board. To adjust focus, turn the lens ring in either direction. Please note that the animal may not be in focus when standing on its hindlimbs; therefore you must make a compromise between sharpness at a specific level from the ground and the range of situations in which the image is in focus. However, image sharpness has little effect on the detection of the animal by the software. - Close the Top Unit and put it back on the cage. Turn PhenoTyper on and check on the monitor that the test animal or object is in focus. If it is not, repeat steps 6 through 7 until you are satisfied with the image focus. Important: See the note on page 44 about closing the Top Unit covering plate. Note — If the EthoVision computer is connected to PhenoTyper cages through TTL cables, when you start it all PhenoTyper devices are switched on. This is a normal event, because the PC sends high TTL signals to the printer port at startup. Source: PhenoTyper 2.0 Reference Manual - Preparing PhenoTyper, Noldus Information Technology --- ## PhenoTyper 2 - Preparing PhenoTyper - Examples of Setting TTL-Out Communication Lines URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-preparing-phenotyper-examples-of-setting-ttl-out-communication-lines Chapter: PhenoTyper Examples of Setting TTL-Out Communication Lines The examples below refer to PhenoTyper hardware settings, not the corresponding settings in EthoVision. These examples assume you have already designed your experiment in EthoVision, defined and calibrated the arena for each PhenoTyper, and started the Acquisition module. Example 1 — Set Two Signals in One PhenoTyper: The Buzzer and the Yellow Light - Choose two separate TTL lines: printer port pin 3 for the yellow light, and pin 6 for the sound. Take note of these numbers because you must specify them in EthoVision. - Open the PhenoTyper's Top Unit and set one jumper in position 8 (which corresponds to line 3 for the yellow light), and the other in position 4 (which corresponds to line 6 for the sound). The position numbers are printed on the board next to the jumpers. - In EthoVision, define a condition for pin numbers 3 and 6. - Assign a condition to each action. For example, the buzzer will be activated 1 minute after the mouse is detected in the arena, and the yellow light will be activated 5 minutes after the mouse is detected in the arena. - You can also assign the same condition to both pin numbers so that the buzzer and the yellow light are activated simultaneously when that condition is met. - If you want to activate the white light, you do not need to specify any jumper position. The only thing you have to do is select pin 2 in EthoVision. If more cages are connected, by definition all of them will be activated at the same time. Example 2 — Set a Sound Signal in 4 PhenoTyper Cages Independently Each cage should activate the buzzer independently of the others. - Choose four separate TTL lines for the sound: printer port pins 6 to 9. Take note of these numbers because you must specify them in EthoVision. - Open the first cage's Top Unit and set one jumper in position 4 (which corresponds to line 6 for the sound). - Open the second cage's Top Unit and set one jumper in position 3 (which corresponds to line 7 for the sound). - Open the third cage's Top Unit and set one jumper in position 2 (which corresponds to line 8 for the sound). - Open the fourth cage's Top Unit and set one jumper in position 1 (which corresponds to line 9 for the sound). - In EthoVision, define a condition for each pin number from 6 to 9. - Assign a condition to each of the four actions. For example, a Location Condition: in each arena the buzzer will be activated when the mouse is detected for at least 1 second in the center zone. - The position numbers are printed on the board next to the jumpers. - In this example, you have placed one jumper per cage. Whatever the position of the second jumper is, that line is not activated unless you select the corresponding printer port pin in EthoVision. - In EthoVision, you can also assign the same condition to more than one line (pin number). Result — The lines are separated. When a condition assigned to pins 6 through 9 is met, the buzzer is activated only in the cage assigned to that line, not the others. Example 3 — Set a Sound Signal in 4 PhenoTyper Cages Simultaneously The buzzer is activated simultaneously in all cages when a condition is met. - Choose one TTL line for the sound: printer port pin 6. Take note of this number because you must specify it in EthoVision. - For each cage, open the Top Unit and set one jumper in position 4 (which corresponds to line 6 for the sound). - In EthoVision, define a condition that activates pin number 6. - Assign a condition for the action valid for all cages. For example, an Elapsed Time Condition: the buzzer is activated 30 minutes after the start of the trial. - The position numbers are printed on the board next to the jumpers. - In this example, you have placed one jumper per cage. Whatever the position of the second jumper is, that line is not activated unless you select the corresponding printer port pin in EthoVision. Result — The lines are not separated. When the condition assigned to pin 6 is met, the buzzer is activated in all cages. Example 4 — Set Two Signals in 4 PhenoTyper Cages: Independent Buzzer, Simultaneous Yellow Light The buzzer is activated independently in each cage, and the yellow light is activated simultaneously in all cages. - Choose four TTL lines for the sound: printer port pins 6 to 9. Take note of these numbers because you must specify them in EthoVision. - Choose the TTL line for the yellow light: printer port pin 3. Take note of this number because you must specify it in EthoVision. - Open the first cage's Top Unit and set one jumper in position 4 (which corresponds to line 6 for the sound) and one in position 8 (which corresponds to line 3 for the yellow light). - Open the second cage's Top Unit and set one jumper in position 3 (which corresponds to line 7 for the sound) and one in position 8 (which corresponds to line 3 for the yellow light). - Open the third cage's Top Unit and set one jumper in position 2 (which corresponds to line 8 for the sound) and one in position 8 (which corresponds to line 3 for the yellow light). - Open the fourth cage's Top Unit and set one jumper in position 1 (which corresponds to line 9 for the sound) and one in position 8 (which corresponds to line 3 for the yellow light). The position numbers are printed on the board next to the jumpers. - In EthoVision, define the conditions that activate the sound for pin numbers 6 to 9, and a condition that activates the light for pin number 3. - Assign a condition for each of the actions. For example, an Elapsed Time Condition for the yellow light (the light is turned on one hour after the start of the trial) and a Location Condition for the sound (the buzzer is activated every time the mouse enters the center zone of its cage). - In EthoVision, you can also assign the same condition to more than one line (pin number). Result — You have established four separate lines for the buzzer and one line for the yellow light. The buzzer will be activated separately in each cage, while the yellow light turns on in all cages simultaneously. --- ## PhenoTyper 2 - Preparing PhenoTyper - Jumper Position Reference Table URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-preparing-phenotyper-jumper-position-reference-table Chapter: PhenoTyper Jumper Position Reference Table Line (Printer Port Pin to Be Selected in EthoVision) Jumpers Signal Type 2 — White light 3 8 Yellow light 4 7 Yellow light 5 6 Yellow light 6 5 or 4 Yellow light (jumper 5) / Sound (jumper 4) 7 3 Sound 8 2 Sound 9 1 Sound Jumper numbers are printed on the board. Notes - As a rule, if you want to activate a signal independently in each cage, you must set a separate line (that is, printer port pin number) for each cage. If you want to activate the signal simultaneously in all cages, you have to set a single line. - Why can no jumper be selected for the white light? — Because the white light is fixed to pin number 2 of the printer port. Therefore, you do not need to open a line for this signal. If you want to activate the white light for this cage, simply select pin number 2 in EthoVision. If you do not want to activate the white light, make sure that pin number 2 is not selected in EthoVision. Important: if more PhenoTyper cages are connected to each other, you cannot activate the white light for some of them individually. Instead, you can activate the white light for either all or none of them. - Why is printer port pin number 6 related to two different jumper positions? — This is due to the number of available pins on the printer port, which limits the number of combinations of signal type when working with multiple PhenoTypers. Because printer port pin number 2 is always fixed to send the TTL signal for the white light, 7 lines are left that can be filled with a combination of cage and signal type. If you work with four PhenoTyper cages and specify a separate line for all cages, you would have in principle 8 different combinations, but only 7 lines are available. Therefore, you must decide which type of signal has to be separate across the 4 cages and which signal fills the other 3 combinations left. For example, if the sound signal is more important than the yellow light in your study and you wish to activate the sound in the 4 cages separately, put the jumper on position 1 in cage 1, position 2 in cage 2, position 3 in cage 3, and position 4 in cage 4. This way, position 5 cannot be used for the yellow light. Positions 6 to 8 can be used for the yellow light, for example to set a separate yellow light signal in three cages. Note that this limitation only applies when you work with 4 cages and you wish to activate a certain signal in all four cages independently of each other. - If you place two jumpers on positions 4 and 5, when EthoVision activates line 6 (which corresponds to those jumper positions) the yellow light and the buzzer are activated simultaneously. Steps to Configure Jumpers - Use the table above to find the correct jumper position based on your chosen printer port pin number and signal type. - If you want to send one more signal to that cage, repeat the jumper placement steps to specify the position of the jumpers for that signal. - Close the Top Unit and put it back on top of the cage. Do not over-tighten the first screws, as doing so may make it difficult to place the remaining ones correctly. Insert the first two or three screws on different sides of the plate and turn them 2–3 times. The separation plate should still be free to move at this stage. Move the plate so that the remaining screws can fit into the corresponding holes in the metal frame underneath. - Repeat all steps above for the other cages, using the examples below to guide setting of separate lines for each cage. Technical Note: Sub-D Connector Wiring The jumpers of the PhenoTyper are connected to the 9-pin sub-D connectors (located next to the Video-out connector) as follows: Sub-D Connector Pin Line (Printer Port Pin to Be Selected in EthoVision) Signal Type 5 2 White light (fixed) 4 3 Yellow light 3 4 Yellow light 2 5 Yellow light 9 6 Yellow light (jumper 5) or Sound (jumper 4) 8 7 Sound 7 8 Sound 6 9 Sound 1 — (ground) --- ## PhenoTyper 2 - Preparing PhenoTyper - Preparing PhenoTyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-preparing-phenotyper-preparing-phenotyper Chapter: PhenoTyper Preparing PhenoTyper This chapter describes how to: - Create optimal lighting conditions around the cages. - Test the functions of PhenoTyper. - Adjust the intensity of light produced by PhenoTyper (infrared and stimuli lights). - Establish TTL-out communication between one or more PhenoTyper cages and the PC. - Adjust the camera focus. 3.1 Lighting Conditions PhenoTyper uses infrared as a light source, and since the camera is infrared sensitive, EthoVision can work independent of the external conditions (day vs. night). However, the light we see also contains variable amounts of infrared, which may compromise detection by EthoVision. For example, direct sunlight or light produced by bulb lamps contain a lot of infrared. This is captured by the PhenoTyper camera, and therefore may compromise object detection by EthoVision. If you need extra visible light in your test room, use tube lamps, especially those producing low infrared light. This minimizes the amount of light that comes outside the PhenoTyper cages. 3.2 Testing PhenoTyper Use the instructions below to check that all functions of PhenoTyper work well (for example, the buzzer device or the lights). When PhenoTyper Is Not Connected to the Computer (Recommended) - Connect the Control Unit to the PhenoTyper. - Switch on PhenoTyper. The switch is on the back panel of the Top Unit. The Control Unit's LCD display switches on. Note: Some of the lamps may burn less intensely than others when they are switched on. Wait a few seconds until all lamps burn equally. - Press one of the Control Unit FUNCTION buttons one or more times to select the device (1 to 6). Each time you press a button, the Control Unit display changes: 1 BUZZER → 2 White LED → 3 Yellow LED → 4 IR array-1 → 5 IR array-2 → 6 IR array-3 → READ FROM PT → WRITE TO PT → 1 BUZZER. The corresponding light turns on when selected. Do not press the TEST button at this point — if you do, light intensity may change because the value read from another cage is copied to the cage. - To test the buzzer, select 1 BUZZER and press the TEST button. Press TEST again to stop the buzzer. Test the Infrared Lights Since humans cannot see infrared light, it is not possible to check directly that the infrared lights work properly. To do so, first connect the video cable of PhenoTyper to a normal TV monitor, or to the Picolo board on your EthoVision computer, with EasyGrab running. There you should see the camera view. Press the Control Unit's FUNCTION buttons to select one of the infrared arrays, then press the LEVEL buttons to change the light intensity. You can check on the TV monitor (or computer screen) the effect of such changes. If the Computer Is Connected to the Cages and Running If the computer is connected to the cages through the TTL cables, when you start it a high TTL signal is sent to all the cages. As a result, all devices (white and yellow light and buzzer) are switched on. Please check that all devices are functioning. To stop all devices, start EthoVision. When you start EthoVision, all TTL signals are set to low, no matter what serial port pins have been defined in EthoVision. Therefore, all devices turn off. 3.3 Adjusting Light Intensity in PhenoTyper Use the instructions below if you want to change the intensity of lights produced by PhenoTyper. If you need to customize light intensity of two or more PhenoTyper cages, repeat the procedure below for each cage. - Connect the Control Unit to PhenoTyper. - Switch on PhenoTyper. The switch is on the back panel of the Top Unit. The Control Unit's LCD display switches on. Note: Some of the lamps may burn less intensely than others when they are switched on. Wait a few seconds until all lamps burn equally. - Press one of the Control Unit's FUNCTION buttons one or more times to select the device. Each time you press the UP button, the display changes in the following way: 1 BUZZER → 2 White LED → 3 Yellow LED → 4 IR array-1 → 5 IR array-2 → 6 IR array-3 → READ FROM PT → WRITE TO PT → 1 BUZZER. - Check whether the intensity of light is satisfactory. - Press the LEVEL buttons on the Control Unit to increase or decrease light intensity. Notes: - The values shown on the Control Unit screen can range from 0 to 200 (indicating current in mA) for the yellow and white lights, and from 0 to 100 for the infrared lights. Even if you set the value to the minimum (0), the lights are still switched on, although at very low intensity. - Intensity values are stored in the non-volatile EEPROM memory of the PhenoTyper's Top Unit. Therefore, once you set the values you want, you do not need to check them the next time you work with PhenoTyper, even if power was turned off. - To change light intensity in other PhenoTyper cages, connect the Control Unit to each cage as explained above. Light intensity values set in one PhenoTyper are not transferred to the other cages connected to it. - Since the human eye cannot detect infrared light, it is not possible to directly adjust the intensity of infrared lights. Therefore, first connect the video cable of PhenoTyper to a normal TV monitor or to the Picolo board on your EthoVision computer, with EasyGrab running. There you should see the camera view. Select one of the infrared arrays and press the LEVEL buttons to change the light intensity. You can check on the TV monitor (or computer screen) the effect of such changes. - You cannot change the intensity of the sound produced by PhenoTyper. - The duration of the signals cannot be set from the Control Unit. You can adjust the duration of the signal in EthoVision by adjusting the Duration (s) value in the Actions on Parallel Port window. --- ## PhenoTyper 2 - Technical Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-technical-specifications Chapter: PhenoTyper Technical Specifications PhenoTyper® Version 2.02 Power Supply 24V DC - 15 W Video Output CCIR black/white, 1 Vpp - 75 W Infrared Image Infrared lighting: 3 integrated IR arrays through diffuser Audio Stimulus (TTL on/off controllable) - Frequency: ±2300 Hz - Amplitude: ±80 dB Yellow Light Stimulus (TTL on/off controllable) - Wavelength: 590 nm White Light Gradient (TTL on/off controllable) - Color temperature: 5500°K - Intensity: 0 – approx. 1000 lux Connections - Supply 24V DC in - Supply 24V DC out (feed-through) - TTL control in/out Sub-D 9 - TTL control in/out Sub-D9 (feed-through) - Video out (BNC) - Control unit Sub-D15 Cage Clear Acrylic (PMMA) Operating Temperature 0 to +40 °C (+32 to +104 °F) Storage Temperature -20 to +70 °C (-4 to +158 °F) Operating Humidity Up to 80%, no condensation Dimensions - Model 3000: 300 x 300 x 435 mm (12 x 12 x 17.1 inches) - Model 4500: 450 x 450 x 660 mm (18.5 x 18.5 x 26 inches) Source: PhenoTyper 2.0 Reference Manual - Technical Specifications, Noldus Information Technology --- ## PhenoTyper 2 - What is PhenoTyper - Using Multiple PhenoTypers URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-what-is-phenotyper-using-multiple-phenotypers Chapter: PhenoTyper Using Multiple PhenoTypers You can connect four PhenoTyper cages to a PC through a quad unit. The EthoVision software allows simultaneous automated tracking of several animals, each in its own cage. A quad unit displays four camera pictures simultaneously on one monitor. When tracking animals, the EthoVision monitor is split into four equal quadrants, allowing EthoVision to acquire data from four animals at the same time. - All PhenoTyper cages are powered by means of feedthrough cables, so you just need to connect one PhenoTyper to the power outlet. - All commands to start and stop acquisition and activate devices are sent from the PC where EthoVision is installed. You cannot activate lights and sound signals manually. - TTL signals are sent from the PC to each cage through separate lines. For example, you can switch on the yellow light in PhenoTyper 1 and produce a sound in PhenoTyper 2 and 3. - You can also assign the same signal to two or more PhenoTyper cages, so the same light or sound is activated at the same time in all the cages as soon as the condition defined in EthoVision is met. Source: PhenoTyper 2.0 Reference Manual - What is PhenoTyper, Noldus Information Technology --- ## PhenoTyper 2 - What is PhenoTyper - What Is PhenoTyper? URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-what-is-phenotyper-what-is-phenotyper Chapter: PhenoTyper What Is PhenoTyper? PhenoTyper combines an open field and video-based monitoring equipment that result in a complete observation system to monitor rodent behavior automatically. The infrared monitoring equipment ensures robust monitoring regardless of ambient light conditions in the lab. Integrated visual and acoustical stimuli can be automatically generated when specific user-defined conditions are met. The walls of PhenoTyper can be configured in different ways, making it suitable for a variety of applications. When PhenoTyper is connected to a computer that runs the EthoVision video-tracking software, the activity and movement of the rodents can be continuously measured, and analyzed afterwards. The video files obtained from PhenoTyper's output can also be used with The Observer software. This allows you to study behavior in details, like aggression and sexual interactions between subjects. How Does PhenoTyper Work? To acquire data, PhenoTyper is connected to a computer on which EthoVision software has been installed. In the basic setup, the camera is connected to the Video Input socket of your PC's Picolo frame grabber board and/or MPEG encoder board. This allows EthoVision to process the video image from the camera and track the test animal's movement and behavior. It is possible to establish communication between the PhenoTyper cage and the PC. EthoVision can send digital signals (TTL-out signals) to devices inside the cage when certain conditions are met, for example a light can be switched on one minute after the start of the trial, or when the animal is detected in a certain zone of the cage. Main Features of PhenoTyper - Camera — PhenoTyper is equipped with a CCD black/white camera that can detect infrared light up to approximately 980 nm. The camera is provided with a high pass infrared filter, so that it does not detect light in the visible range. This means that your recordings are independent of visible light. You can run tests throughout the light-dark cycle without worrying about switching lights on and off. - Do not use lightbulbs as a visible light source, because they produce a lot of infrared light, making it impossible for EthoVision to track the animals. If you need extra visible light in your test room, use tube lamps producing little infrared light. This minimizes the amount of light from outside PhenoTyper that is captured by the camera. - The camera does not detect the heat produced by the animals. - You cannot remove the IR filter from the camera lens. - Infrared Lights — Three arrays of infrared lights are activated as long as PhenoTyper is switched on. You can adjust the intensity of each of these arrays separately. Lights are located in the Top Unit, and arranged in concentric rings of 4 (the innermost), 12, and 20 (the outermost). - Light Stimuli — You can make PhenoTyper switch on a white light (5500 °K color temperature) and a yellow light (wavelength approx. 590 nm). Each of these illuminates approximately a quarter of the cage bottom. You can adjust the intensity of both lights. - Sound Stimulus — You can make PhenoTyper produce a buzzing sound of approximately 2300 Hz, and amplitude of about 80 dB. The only way you can activate light and sound stimuli is through the TTL-out communication system. This means that EthoVision sends the command to the lights or the buzzer when a condition is met. You cannot control the light and sound stimuli outside EthoVision. - TTL Signals — PhenoTyper can receive TTL (Transistor-Transistor Logic) signals from EthoVision through the pins of your PC's printer port. You can set up to 8 different lines to provide different stimuli to different cages, at the same or at different times. TTL signals are used to activate stimuli like a light or a sound when a condition is met. You can also have PhenoTyper send pulses to the PC, so that EthoVision can log the occurrence of specific events. For example, you can attach a sensor to an activity wheel so that it sends a pulse to EthoVision every time the wheel rotates, allowing EthoVision to log data of activity levels of the test animals. Main Advantages of PhenoTyper Relative to Ordinary Test Environments - Robust — The infrared light filter placed in front of the infrared-sensitive video camera blocks out visible light (all wavelengths lower than 850 nm), therefore only infrared light is captured. This makes tracking independent of ambient light conditions in the lab, and even allows studies of circadian rhythms without having to change settings when light conditions change. - Convenient — One no longer has to worry about choosing, mounting, and positioning a camera, nor how to set up the ambient light conditions in the lab. PhenoTyper is also a complete monitoring system: camera, lights, open field, and even visual and acoustical stimuli are all integrated in one system. - Flexible — PhenoTyper can be configured in different ways and extended with a number of accessories. This makes it possible to apply PhenoTyper to different studies and research questions, for example open field studies, home cage testing, circadian rhythm studies, and operant tests. - Minimal Human Interference — Tests can be performed in a series, without moving the test animal. This way handling by the operator is minimized. PhenoTyper Configurations PhenoTyper comes in two main size categories: - Model 3000 — Cage with 300 x 300 mm side length. Suitable for mouse studies. - Model 4500 — Cage with 450 x 450 mm side length. Suitable for both rat and mouse studies. For both size categories, you can make three main cage types depending on the walls and accessories chosen: - Home Cage — Cage provided with feeder, water bottle, and shelter. Two walls have ventilation holes. Suitable for long-term observations. The Model 4500 home cage includes two water bottles instead of one and a bigger feeder. The Model 4500 home cage for rats is provided with a shelter bigger than that of the Model 4500 for mice. - Basic Cage — Cage with two plain walls and two ventilation walls, suitable for short-term studies. - Custom Cage — A custom cage is any combination of walls and accessories that differ from the Basic and Home cage. You can have, for example, a custom cage with feeder and bottle but no shelter, or a cage with three or four ventilation holes if necessary. --- ## PhenoTyper 2 Setup - 16-PhenoTyper Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-setup-16-phenotyper-configuration Chapter: PhenoTyper 16-PhenoTyper Configuration For this configuration you need a high-end workstation (see the Tested Configuration section below). Hardware and Settings - 16 Basler GigE cameras acA1300-60gm. - PCIe Ethernet interface board: FS X550-AT2, 10GBase-T Dual-Port, PCIe 3.0 x4. - Network switch: FS S3100-16TMS-P, 16-Port Gigabit Ethernet L2+ PoE+, 8x PoE+ Ports@125W, 2x 5Gb RJ45, with 2x 10Gb SFP+ Uplinks. - An adapter (SFP+ 10GBASE-T Copper 30m RJ-45 Transceiver module) for the network cable that goes from the PC to the network switch. - We recommend to use CAT6+ network cables. Network Connection Procedure (16-Camera Setup) In this configuration, a single PoE Gigabit Ethernet switch with SFP+ connectors connects all 16 cameras. The PC Ethernet board port assigned 192.168.1.51 connects to the switch. Cameras are grouped into four banks: 192.168.1.101–104, 192.168.1.105–108, 192.168.1.109–112, and 192.168.1.113–116. - Install the Ethernet network interface board on the PC and the network switch. - Connect each PhenoTyper camera to an Ethernet port of the network switch. If you use the network switch FS S3100-16TMS-P, or similar switches with only a fraction of the ports being powered, connect the remaining cameras through a PoE injector. Alternatively, use a network switch with 16 powered ports. - Connect the network switch to one of the ports of the Ethernet board on the PC. Use the 10/1G port on the switch (highlighted port group) and the SFP+ transceiver adapter to connect to the 2-port Ethernet board on the PC. - Assign a unique IP address to the port on the Ethernet board that is connected to the network switch. - Assign a unique IP address to each camera that matches the first three numbers of the IP address of the port on the Ethernet board. See the network diagram described above for an example. Notes - The network switches must be of type PoE (Power over Ethernet), that is, they must provide power to the cameras. If the switch has only a limited number of powered ports, you must use PoE injectors for the remaining ports. - The maximum power provided by a switch, measured in Watt (W), must be greater than the total requirements of the cameras (one Basler camera requires about 2.5 W) and the other devices connected to the switch. - The network switches must be able to handle large packets (known as "jumbo packets" or "jumbo frames"). With jumbo frame-capable devices, the maximum packet size can be up to 16 KB. - For maximum network efficiency, your camera should be configured to use the largest packet size that your network adapters and switches can handle. - For information on how to assign IP addresses, see Install the GigE camera on the EthoVision XT Help. - Refer to the user guide of the network switch for how to set it up. Tested Configuration - Tested PC: Dell Precision 3680, CPU i7-14700K 3.4 GHz, RAM memory 32GB, GPU NVIDIA T1000 8 GB; Windows 11 Pro 23H2. - Experiment Settings in EthoVision XT: Video source: Live tracking; Image binning (in Video settings): 2. Number of subjects per arena: 1; Tracked features: Center-point, nose-point and tail-base detection; Body Point Detection Technique: Contour-based. - Detection Settings: Dynamic Subtraction or Differencing. Acquisition mode: Track + Save video. - Video frame rate: 30 fps. Trial duration: 72 hours. Video Resolution (16-Camera Configuration) Single camera view: 640 x 480. Merged 16-camera video image: 2560 x 1920. The merged view arranges 16 individual camera images into a 4-column by 4-row grid, resulting in a combined resolution of 2560 x 1920 pixels. To set the resolution: - In EthoVision XT, open the Experiment Settings and under Video Source select Live tracking and choose 16 as Number of sources. - Select the first camera. Make sure that the resolution of the single cameras is 1280 x 1024. - Click the camera button and in the General tab set the Binning to 2. This rescales the image without cropping it. - Select the remaining cameras from the first list and make sure that the Binning option is set to 2. - Make sure that the Merged camera view is 2560 x 1920. Tip: Put a sheet with a number in each PhenoTyper cage. That way you easily see which PhenoTyper camera has been selected. Select the first four cameras for group 1, then the fifth to the eighth for group 2, etc. Working With Groups of PhenoTypers See the section on Working With Groups of PhenoTypers for detailed information. Note that with PhenoTyper 2 we recommend to connect up to 16 cages (when recording video only) or 12 cages (when controlling PhenoTyper through TTL) to one EthoVision XT computer. Connect Additional Devices You can have EthoVision XT control PhenoTyper and additional devices. See the section Connect Additional Devices for more information. Lighting Conditions The general recommendations about lighting in the test room for PhenoTyper 1 are also valid for PhenoTyper 2. See the Lighting Conditions section for details. Test the PhenoTyper's Functions Camera Image and the Infrared Light Source - Connect the network cable from the PhenoTyper camera to one of the ports of the Ethernet interface board on the EthoVision XT computer. For information on how to set up the IP addresses of the camera and of the Ethernet interface board, see the EthoVision XT Help. - Start EthoVision XT, create a new experiment, next in the Experiment Settings select Live tracking, select the camera input and click the camera preview button. There you should see the live camera image. - Switch off all the light in the room. If the infrared light source works properly, you should see a clear image of the cage bottom. White Light - Press the White - Test button on the front panel of the TopPlate TTL Interface. The button is labeled "WHITE" on top and "TEST" on the bottom with an indicator light in the center. - Check that the light inside the cage switches on. --- ## PhenoTyper 2 Setup - 8-PhenoTyper Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-setup-8-phenotyper-configuration Chapter: PhenoTyper 8-PhenoTyper Configuration For an 8-PhenoTyper configuration you can also use the solution for 16 PhenoTypers. Hardware and Settings - 1x 4-port AdLink PCIe-GIE74 Ethernet interface board. - 2x Network switches (tested switch: Netgear S350 Series 8-Port Gigabit PoE+). Only use network switches with at least 1Gb Ethernet ports. Also the Ethernet network interface board must have 1Gb ports. See the suggestions in the section Camera Installation in the EthoVision XT Help. - The network switches must have at least n+1 Ethernet ports, where n is the number of PhenoTypers connected to the switch. - The network switches must provide power over Ethernet (PoE) to the cameras. Alternatively, you must connect each camera to the switch through a separate PoE injector with its own power plug. This increases the complexity of cabling. Procedure - Install the Ethernet network interface board on the PC and the network switches. - Connect each PhenoTyper camera to an Ethernet port of the network switch (four cameras per switch). - Connect the network switches to two ports of the Ethernet board on the PC. Network Switch Configuration (8-PhenoTyper Setup) - Assign a unique IP address to each port on the network switch that is connected to a camera. - Assign an IP address to each camera that matches the first three numbers of the IP address of the port on the network switch that camera is connected to. For example, in an 8-camera setup using two PoE Gigabit Ethernet switches, ports on switch 1 are assigned addresses 192.168.1.101 through 192.168.1.104, and cameras connected to those ports also use 192.168.1.x addresses. Ports on switch 2 use 192.168.2.105 through 192.168.2.108, with cameras assigned matching 192.168.2.x addresses. The PC Ethernet board ports are assigned 192.168.1.51 and 192.168.2.52. - Important: Keep the first two numbers 192.168 of the IP address for all ports and cameras. - The network switches must be of type PoE (Power over Ethernet), that is, they must provide power to the cameras. The maximum power provided by a switch, measured in Watt (W), must be greater than the total requirements of the cameras (one Basler camera requires about 2.5 W) and the other devices connected to the switch. - The network switches must be able to handle large packets (known as "jumbo packets" or "jumbo frames"). With jumbo frame-capable devices, the maximum packet size can be up to 16 KB. - For maximum network efficiency, your camera should be configured to use the largest packet size that your network adapters and switches can handle. - For information on how to assign IP addresses, see Install the GigE camera on the EthoVision XT Help. - Refer to the user guide of the network switch for how to set it up. Video Resolution (8-Camera Configuration) Single camera view: 640 x 480. Merged 8-camera image: 2560 x 960. The merged view arranges 8 individual 640 x 480 camera images into a 4-column by 2-row grid, resulting in a combined resolution of 2560 x 960 pixels. To set the resolution, open the Experiment Settings, and under Video Source select Live tracking and choose 8 as Number of sources. Select all the cameras and make sure that the resolution of the single cameras is 640 x 480 and that of the Merged camera view is 2560 x 960. --- ## PhenoTyper 2 Setup - Adjust Light Intensity URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-setup-adjust-light-intensity Chapter: PhenoTyper Adjust Light Intensity PhenoTyper 2 (Digital Camera) For this you need the trimmer adjustment tool that is provided with the PhenoTyper TopPlate TTL Interface, or a small screwdriver. The trimmer adjustment tool is a small yellow tool used to turn the adjustment controls on the TopPlate TTL Interface. To adjust the intensity of the infrared light: - Connect the network cable from the PhenoTyper camera to one of the ports of the Ethernet interface board on the EthoVision XT computer. For information on how to set up the IP addresses of the digital camera and of the Ethernet interface board, see the EthoVision XT Help. - Start EthoVision XT, create a new experiment, and in the Experiment Settings select Live tracking, then select the camera input from the list and click the camera preview button. There you should see the live camera image. - Turn the IR control on the TopPlate TTL Interface, as indicated with the arrows. The IR control dial is labeled "IR" and has + and – indicators showing the direction to increase or decrease intensity. - Check the image in the EthoVision XT screen. To adjust the intensity of the white light: - Turn the WHITE control on the TopPlate TTL Interface, as indicated with the arrows. The WHITE control dial is labeled "WHITE" and has + and – indicators showing the direction to increase or decrease intensity. - Check the intensity of the white light in the cage. Make sure that the white light intensity is equal between cages, and that it does not change with time (unless for reasons related to the experimental treatment). Tip: Measure light intensity with a light meter or a light meter app for smartphones that you can download from the internet. Repeat the procedure for the other cages. The PhenoTyper Camera Lens Focus The camera focus is optimized at production. For more information on the camera and lens, see the PhenoTyper 2 - Service Manual. Advanced Camera Settings The Basler acA1300-60gm is the default camera of PhenoTyper 2. For extensive information on camera settings (resolution, frame rate, and more), see the PhenoTyper 2 - Service Manual. Add a TTL-Controlled Module Aim To control an additional TTL device, like a spotlight. The type of control is currently limited to On/Off. You can have EthoVision XT switch on and off the spotlight, however you cannot adjust the light intensity through the software. Fit the New Module on the Top Plate Remove the cover plate from one of the slots of the Top Plate. Insert the new module and gently press it in such a way the connectors come in contact. Fix the module with the two screws. Current TTL Ports Configuration - TTL 1 is reserved for the PhenoTyper White light. It is not available for use with other modules. - TTL 2 and TTL 3 are set to output by default. Through these ports you can have EthoVision XT send out On/Off commands to the device you have added. That is, the signal always goes from EthoVision XT to the device through the (mini) USB-IO box. In EthoVision XT Trial Control Settings, choose Output Line 1 for that device. - TTL 4 is currently not available. The TTL port panel has the following layout: TTL 1 is used for White Light, TTL 2 and TTL 3 are Output ports, and TTL 4 is Not in use. Note: The name Output line refers to the internal lines that you can set for each port of the interface device — the (Mini) USB-IO box. In general, for each port of those interface devices two output lines (Output Line 1 and Output Line 2) and two input lines (Input Line 1 and Input Line 2) are available. You can specify them in the EthoVision XT Trial Control Settings. For PhenoTyper 2, only Output Line 1 applies currently. For more details, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Advanced Solutions If you need additional configurations, contact your nearest Noldus representative. Set Up an Experiment with PhenoTyper 2 For this section you need: - PhenoTyper 2 and the USB-IO box. Create an Experiment Prerequisites You have followed the section Set up PhenoTyper 2. Procedure - Choose File > New from Template. In the Select a template option window, select Apply a pre-defined template. - Follow the instructions in the guided setup. Under How is the arena configured, choose PhenoTyper (for one cage) or PhenoTyper, quad (four cages). After you have created the new experiment, you must still check/adjust Experiment Settings, Arena Settings and Detection Settings before you can track any animal correctly. Please follow the steps below. --- ## PhenoTyper 2 Setup - Experiment Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-setup-experiment-settings Chapter: PhenoTyper Experiment Settings Select the Cameras - In the Experiment Explorer, click Experiment Settings. - Under Video source, select the number of cameras from the list next to Number of sources. Select your cameras under Sources. For more information, see the EthoVision XT Help. Configure the Devices of PhenoTyper 2 (USB-IO Box) Follow this procedure if you have connected PhenoTyper 2 to EthoVision XT through the USB-IO box. With this setup you can control the white light. - In the Experiment Settings, next to Trial Control Hardware, select Use of Trial Control Hardware and click Settings. - In the window that pops up, select Noldus USB-IO Box and click OK. - In the Device Configuration window, locate the TTL Port of the USB-IO box that is connected to the PhenoTyper Control Unit (TTL 1). Note: The SDI ports do not work with PhenoTyper 2. - Under Device Type select PhenoTyper 2 TTL 1 White Light (PT2I-01_TTL) to control the white light. To control another module, select one of the other options (PhenoTyper 2 TTL 2 Module or PhenoTyper 2 TTL 3 Module). Note that modules other than the White Light are not standard; you have to purchase them separately. - Repeat the steps 3–4 for each PhenoTyper, then click OK. Example with four PhenoTypers: The Device Configuration window shows TTL Port 1 through TTL Port 4 each assigned to PhenoTyper 2 TTL 1 White Light, while TTL Port 5 through TTL Port 7 show no device connected or selected. Analysis Options - Activity analysis. Under Analysis Options select Activity analysis to detect freezing behavior. - Behavior recognition. Under Analysis Options select Behavior recognition. If you work with rodents, you can let EthoVision XT automatically detect behaviors like grooming, drinking, eating and rearing. For this option, you need the Rat/Mouse Behavior Recognition Module. Arena Settings For drawing arenas and zones, refer to the Arena Settings section of the manual. Assign the PhenoTyper Devices to the Arenas For this procedure you must have the Trial and Hardware Control Module. Open the Arena Settings and follow the instructions below. Assign the Devices of PhenoTyper 2 Connected to the USB-IO Box Prerequisite: you have followed the previous step on configuring devices in Experiment Settings. - In the Arena - Hardware Mapping window, click Add device. - Under Device Type, select the type of device. For the standard white light, choose PhenoTyper 2 TTL 1 White Light. - Under Device Name, enter a name (for example, PhenoTyper White Light), or accept the default name (Device A, Device B, etc.). - For each Arena, select the physical device that is associated with that arena. For example, PhenoTyper 2 TTL 1 White Light 1 under Arena 1, PhenoTyper 2 TTL 1 White Light 2 under Arena 2, etc. Which device you should select depends on which TTL port of the USB-IO box is connected to that PhenoTyper (Arena). Tip: Scroll the table to the right to view the remaining arenas. - To add more devices, click Add device. - For the Noldus Lickometer, Pellet Dispenser, and PhenoWheel, under Device Type, repeat the steps from step 2 above. - For a third-party hardware device, under Device Type, select Custom Hardware. Enter a name under Device name and, for each arena, select one of the physical devices from the list. For more information about this step, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Trial Control Settings In the Trial Control Settings you can define the events that take place during the trial and at which condition. For example, have the software switch a light. For more information on Trial Control, see Trial Control Settings in the EthoVision XT Help, and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. See also the chapter Common Tests with PhenoTyper. Detection Settings For more information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Common Tests with PhenoTyper Short-term experiments can be carried out while the subjects are monitored in PhenoTyper. This can be, for example, learning tasks, anxiety tests, or tests on the effects of drugs. For information on how to set up an experiment in EthoVision XT, see Set Up an Experiment in the EthoVision XT Help. - General Behavior Monitoring — see below. - Create Routines - Food Receiving Task - Illuminated Shelter Task - CognitionWall™ Task - Anxiety Tests General Behavior Monitoring Maximum Trial Duration (Tested) With or without simultaneous video recording: 72 hours. For more information on tested configurations, see the EthoVision XT Help. To open the Help, in EthoVision XT choose Help > Help Topics. Prolonged Video Recordings If you need to record video of the same subject for more than 72 hours, we recommend that you make a series of trials. - In the Trial Control Settings, remove the condition immediately before the Start track action box. Source: PhenoTyper 2 Set up Reference Manual, Noldus Information Technology --- ## PhenoTyper 2 Setup - Set Up PhenoTyper 2 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-2-setup-set-up-phenotyper-2 Chapter: PhenoTyper Set Up PhenoTyper 2 Aim This section is about connecting and adjusting the settings of PhenoTyper 2. This is the version with the TopPlate hosting a digital camera. Topics Covered - Cables and Adapters - Connect One PhenoTyper to the PC - Connect Multiple PhenoTypers to the PC - Working with Groups of PhenoTypers - Connect Additional Devices - Lighting Conditions - Test the PhenoTyper's Functions - Adjust Light Intensity - The PhenoTyper Camera - Add a TTL-Controlled Module Cables and Adapters - A, B – Power cord and transformer. For PhenoTyper 2: code MAPS-0014. - C – Power feed-through cable for connecting two PhenoTypers. For PhenoTyper 2: code PT-PSC. - D – Cross network cable with RJ45 connectors for connecting the digital camera to the EthoVision XT PC. If you purchased the USB-IO box, you also have the following cables: - Network cables (as many as PhenoTyper Top Units). - USB cable with connectors of type A and B. - Power cord and DC adapter 24 V 3A for the USB-IO box. Connect One PhenoTyper to the PC Power and Video - Connect the IN socket of the TopPlate TTL Interface to the power outlet using elements A and B (power cord and transformer). - Connect the camera's Ethernet socket to one of the ports of the Ethernet interface board on your computer, using a cross-network cable with RJ-45 connectors (D). - Furthermore, you must set the IP address in the digital camera and the port on the Ethernet interface board. For how to do so, see Configure the digital camera in the EthoVision XT Help or watch the video tutorial Set up your cameras in EthoVision XT. Control of the White Light with the USB-IO Box Follow this section if you have the USB-IO box. - Connect the USB port of the USB-IO box to one of your PC's USB ports using the USB cable that comes with the IO box. - Connect the TTL 1 port (or another one available) of the USB-IO box to the TTL 1 port of the TopPlate TTL Interface. - Make sure that the USB-IO box is connected to the power outlet. Notes - For information about the USB-IO box, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - At the time of release of PhenoTyper 2, control is limited to the PhenoTyper white light. Contact Noldus to discuss possible extensions. - See also Add a TTL-Controlled Module. Connect Multiple PhenoTypers to the PC Power and Video - Connect the first PhenoTyper's 24 VOLT IN socket to the power outlet using elements A (MAPS-0014) and B. Repeat this step for every other PhenoTyper in the group, that is, the first of each pair. Important: Connect a maximum of two PhenoTyper TTL Interfaces to the same power supply. - Using power feed-through cables (C), connect the 24 VOLT OUT socket of the first PhenoTyper to the 24 VOLT IN socket of the second. Connect the 24 VOLT OUT socket of the third PhenoTyper to the 24 VOLT IN socket of the fourth, and so on. - Connect each PhenoTyper's camera to one of the ports of the Ethernet interface board on your computer, using a cross-network cable with RJ-45 connectors (D). Notes - Resolution of each camera image: 1280 x 1024. When using four PhenoTypers, the resolution of the resulting video is 2560 x 2048. - When using more than two PhenoTypers, connect each pair of PhenoTypers to a separate power outlet. Video Resolutions That Work in PhenoTyper 2 Note that the maximal resolution attainable in your system is also depending on the frame rate and the tracking methods. Open the EthoVision XT Help (press F1 in the software) and see the topic GigE cameras for a list of tested configurations. Nr. of Cameras Single Camera Merged View 11280 x 1024– 21280 x 10242560 x 1024 41280 x 10242560 x 2048 8640 x 9602560 x 960 16 (*)640 x 4802560 x 1920 (*) For 16 cameras, set the following in EthoVision XT (Experiment Settings): - Frame rate: 30 fps. Higher frame rates may result in camera connection being lost. You can find the Frame rate option in Experiment Settings > click the camera button > Format tab. - Binning: 2. You can find the Binning option in Experiment Settings > click the camera button > General tab. With Binning set to 2, the resolution of the single camera view is half of the original, while the image is not cropped. Tip: If you want to return to the full resolution, de-select Binning, click OK and in the Experiment Settings click the Refresh button, then click again the camera button. Important: Do not forget to update the background image in the Arena Settings whenever you change the video resolution. Record Video to Separate Files You can use MediaRecorder to save video from each cage to a separate video file, at the maximal resolution. See Record video to separate video files for more information. Control of Devices with the USB-IO Box (Multiple PhenoTypers) - Connect the USB port of the USB-IO box to one of your PC's USB ports using the USB cable that comes with the IO box. - Connect the 24 V IN port of the USB-IO box to the power outlet using its adapter. - Connect a TTL port on the USB-IO box to the TTL 1 port of each PhenoTyper, using network cables with RJ-45 connectors at their ends. This line controls the white light. - If your PhenoTypers have additional modules that can be controlled through TTL, connect the TTL ports of the USB-IO box to TTL ports 2 to 4 of each PhenoTyper. --- ## PhenoTyper 2.0 - Top Plate TTL Interface URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-20-top-plate-ttl-interface Chapter: PhenoTyper PhenoTyper 2.0 TTL Interface General The TTL interface (type PT2I-01_TTL) will enable you to control, using the Noldus USB-IO box, both integrated (IR and white light) and TTL-module functionality on the PT2.0 TopPlate. Using the TTL Interface Connecting the TTL Interface Unit The interface unit can be connected to the PT2.0 TopPlate by positioning both male SUBD connectors to their mating connectors on the TopPlate and gently pressing the box. The box can then be fixed to the TopPlate using 2 screws with the 2.5mm hex key supplied. Supply Connect the unit to the standard 24-volt supply using one of the 2 "24Volt" terminals. The remaining connector can be used to feed through 24-volt power. Whenever 24-volt power is connected and the power switch is in position "ON", the red power LED on both the front and back side will be active. By default, the IR illumination integrated in the TopPlate will be on whenever power is connected. TTL Ports The TTL interface comes with 4 TTL ports. These can be connected to the available TTL control ports on the USB-IO box. For basic use, connect TTL1 to a TTL port on the USB-IO box. This will enable you to control the white light integrated in the PT2 TopPlate to be switched on and off from within EthoVision XT. The actual on/off function will become available by selecting TTL output line 1 from the TTL port involved. The 3 remaining TTL ports are internally connected to the TopPlate modules for future use. White Light Test Button and Adjustment Pressing the button will switch the white light on. This enables you to preset the white light intensity by adjusting the control potentiometer using the yellow adjust tool. Infrared Light Adjustment Infrared light is active by default at all times. The IR intensity can be adjusted to a preset level using the left potentiometer. It is good practice to minimise the amount of IR and use the gain setting in the EthoVision camera menu to obtain an optimal image. However, if the image becomes grainy, the amount of IR should be increased. Whenever the video image needs to be brighter, always start by adjusting the camera settings (gain). Additional Information Additional information on using PhenoTyper and EthoVision can be found in the following documents: - PhenoTyper Reference Manual - PhenoTyper Service Manual Specifications General Specifications - Type Name: PT2I-01_TTL - Power Supply: 24V DC, max 50 watts (with connected TopPlate and maximum IR level) Infrared Lighting - 4 integrated IR arrays through diffuser - Wavelength: 940 nm - Adjustable: 0.1 – 0.35 mW/cm² White Light - 4 integrated white light arrays through diffuser - Color temperature: 4000K - Adjustable (on TTL interface): 0.5 – 2700 lux - Default level: 500 lux Connections - Supply 24V DC in - Supply 24V DC out (feed-through) - 4x TTL port Connections to the TopPlate: - Sub-D9 TopPlate light supply - Sub-D9 module bus Controls - Level adjust for IR and white light - Push button for testing white light Source: PhenoTyper TTL Interface, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2.1 Phenotyper 1 (Analog Camera) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-21-phenotyper-1-analog-camera Chapter: PhenoTyper PhenoTyper 1 (Analog Camera) Camera Focus and Orientation Adjust the Camera Focus If the camera image is out of focus: - The camera is in the center of the Top Unit's covering plate. Remove the ring around the lens, so you can easily access the focus ring on the lens. - Rotate the focus ring in either direction. - Put the test subject, or an object of approximately the same height, in the cage. - Put the Top Unit back on the cage. Turn PhenoTyper on and check in EthoVision XT that the test animal/object is on focus. - Repeat steps 2 to 4 until the image is sharp enough. Note: If you have a NTSC Top Unit with serial number below 01000, you have to remove the Top Unit covering plate. Turn off PhenoTyper, unscrew the covering, and loosen a small screw on the lens, then rotate the focus ring. Important: When closing the Top Unit, do not over-tighten the first screws. Doing so may make it difficult to put the remaining ones in the right place. Instead, insert first two or three screws on different sides of the plate, and turn them 2-3 times. The separation plate should be still free to move at this stage. Move the plate so that the remaining screws can fit in the corresponding holes. Adjust the Camera Orientation If the camera does not point to the center of the cage bottom, and some parts of the cage like the feeder are not visible enough, you can change the orientation of the camera. The information below applies to PhenoTyper top units manufactured after March 2011. In top units from previous batches, it was not possible to adjust the camera orientation. If you want to upgrade an older unit, please contact your sales person for a quote. Required Tools: - A 2.5 mm Allen key (also known as a hex or Inbus key) - A small flat-head screwdriver - A straight edge of approximately 40 cm - Marker pen with washable ink - Post-it stickers Procedure: - Remove the Top Unit from the PhenoTyper cage. - Carefully remove the four black caps next to the camera (if necessary, use the screwdriver). - Remove one wall of the PhenoTyper cage. - On the base of the PhenoTyper cage, draw lines between each corner, so that they intersect precisely in the center of the floor plate. If the base is black, you can tape paper to it and draw on the paper. Alternatively, tape an image to the floor plate to make focusing easier. - Place the Top Unit upside-down and the cage on top of it (so the entire setup is upside down). - Connect the camera connection of the PhenoTyper Top Unit to your computer, so that you can view the image. - Determine the center point of your computer monitor: - Open this document in a PDF viewer (e.g. Adobe Reader). - Maximize the PDF viewer window. - View in Full Screen mode (press Ctrl+L). - Zoom to Fit Width (press Ctrl+2). The image is now centered horizontally. - Scroll until the image is centered vertically. - Mark the center point, for example with two stickers. Do not write on the monitor screen. - If necessary, focus the camera. To do so, remove the ring next to the camera lens and rotate the lens. If you have an NTSC Top Unit camera, you have to remove the plastic plate and loosen a small screw on the lens. - Insert the Allen key into each of the holes and turn until the image from the camera is centered on the cross you have drawn on the cage base. - If necessary, re-focus the camera. - When the image quality is satisfactory, put the caps back in place, remove the lines you have drawn or the test sheet, and reassemble the cage. If you need assistance with this procedure, please contact your nearest Noldus support center at my.noldus.com. Camera Settings When Do I Need to Adjust the Camera Settings? Since the PhenoTyper Top Unit camera is optimized for video tracking with EthoVision XT, it will not be necessary to adjust the camera settings under most conditions. However, there may be exceptions. For example, when you track a white rat on dark bedding material, the animal's body may appear overlit due to automatic gain adjustments. You can change the camera settings based on the instructions below. If you still have questions, contact Noldus Support for guidance at my.noldus.com. A common scenario that may require adjustment of the camera settings is when the image of the animal is too bright. When you carry out video tracking only, it is usually no problem if the animal is overlit. However, if you need to know details of the behavior, for example for manual scoring, you need an image with good contrast and details of the animal's body. When you use the Mouse or Rat Behavior Recognition Module, it is essential that details of the animal's body and fur are visible and sharp. In such situations, do not decrease the infrared light level in the PhenoTyper, since this will only cause the camera to compensate more. Switch off the automatic gain control and adjust the shutter speed. To reset the camera to its default settings, refer to the camera reset instructions. The Camera On-Screen Menu To access the camera on-screen menu for PhenoTypers with serial number 001471 and higher (from 2018 up to now), you need the UTC-100 on-screen device (OSD). Please contact Noldus if you do not have this device. Connect the OSD between PhenoTyper and a monitor (or PC video encoding board). Use video cables with BNC connectors, just like you do when connecting PhenoTyper to the PC. For details, see the PhenoTyper Reference Manual. - Press the central button to enter a menu or confirm a selection. - Press the Down button to navigate the menu, and the Left/Right buttons to switch between options. Note that Move Up does not have any effect. - Remember to select Save and Exit to confirm. To Open the Camera Settings Menu: - Start EthoVision XT, and in the Experiment Settings click the video icon in the row of your camera under Video Source. The live image from the PhenoTyper Top Unit camera appears. - Press the central button of the OSD. The on-screen menu appears. - By default, the first menu item, EXPOSURE, is selected. Important Camera Settings - AGC (Automatic Gain Control): Switch this off when the image of the animal is overlit. - Shutter: Adjust this if the image of the animal is overlit. First switch off Automatic Gain Control before adjusting the shutter. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2.1 Phenotyper 1 (Analog Camera) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-21-phenotyper-1-analog-camera-oCS Chapter: PhenoTyper PhenoTyper 1 (Analog Camera) Camera Focus and Orientation Adjust the Camera Focus If the camera image is out of focus: - The camera is in the center of the Top Unit's covering plate. Remove the ring around the lens, so you can easily access the focus ring on the lens. - Rotate the focus ring in either direction. - Put the test subject, or an object of approximately the same height, in the cage. - Put the Top Unit back on the cage. Turn PhenoTyper on and check in EthoVision XT that the test animal/object is on focus. - Repeat steps 2 to 4 until the image is sharp enough. Note: If you have a NTSC Top Unit with serial number below 01000, you have to remove the Top Unit covering plate. Turn off PhenoTyper, unscrew the covering, and loosen a small screw on the lens, then rotate the focus ring. Important: When closing the Top Unit, do not over-tighten the first screws. Doing so may make it difficult to put the remaining ones in the right place. Instead, insert first two or three screws on different sides of the plate, and turn them 2–3 times. The separation plate should be still free to move at this stage. Move the plate so that the remaining screws can fit in the corresponding holes. Adjust the Camera Orientation If the camera does not point to the center of the cage bottom, and some parts of the cage like the feeder are not visible enough, you can change the orientation of the camera. The information below applies to PhenoTyper top units manufactured after March 2011. In top units from previous batches, it was not possible to adjust the camera orientation. If you want to upgrade an older unit, please contact your sales person for a quote. Required Tools: - A 2.5 mm Allen key (also known as a hex or Inbus key) - A small flat-head screwdriver - A straight edge of approximately 40 cm - Marker pen with washable ink - Post-it stickers Procedure: - Remove the Top Unit from the PhenoTyper cage. - Carefully remove the four black caps next to the camera (if necessary, use the screwdriver). - Remove one wall of the PhenoTyper cage. - On the base of the PhenoTyper cage, draw lines between each corner so that they intersect precisely in the center of the floor plate. If the base is black, you can tape paper to it and draw on the paper. Alternatively, tape an image to the floor plate to make focusing easier. - Place the Top Unit upside-down and the cage on top of it so the entire setup is upside down. - Connect the camera connection of the PhenoTyper Top Unit to your computer so that you can view the image. - Determine the center point of your computer monitor: - Open this document in a PDF viewer (e.g. Adobe Reader). - Maximize the PDF viewer window. - View in Full Screen mode (press Ctrl+L). - Zoom to Fit Width (press Ctrl+2). The image is now centered horizontally. - Scroll until the image is centered vertically. - Mark the center point, for example with two stickers. Do not write on the monitor screen. - If necessary, focus the camera by removing the ring next to the camera lens and rotating the lens. If you have an NTSC Top Unit camera, you have to remove the plastic plate and loosen a small screw on the lens. - Insert the Allen key into each of the holes and turn until the image from the camera is centered on the cross you have drawn on the cage base. - If necessary, re-focus the camera. - When the image quality is satisfactory, put the caps back in place, remove the lines you have drawn or the test sheet, and reassemble the cage. If you need assistance with this procedure, please contact your nearest Noldus support center at my.noldus.com. Camera Settings When Do I Need to Adjust the Camera Settings? Since the PhenoTyper Top Unit camera is optimized for video tracking with EthoVision XT, it will not be necessary to adjust the camera settings under most conditions. However, there may be exceptions. For example, when you track a white rat on dark bedding material, the animal's body may appear overlit due to automatic gain adjustments. You can change the camera settings based on the instructions below. If you still have questions, contact Noldus Support for guidance at my.noldus.com. A common scenario that may require adjustment is when the image of the animal is too bright. When carrying out video tracking only, it is usually no problem if the animal is overlit. However, if you need to know details of the behavior — for example for manual scoring — you need an image with good contrast and details of the animal's body. When using the Mouse or Rat Behavior Recognition Module, it is essential that details of the animal's body and fur are visible and sharp. In such situations, do not decrease the infrared light level in the PhenoTyper, as this will only cause the camera to compensate more. Switch off the automatic gain control and adjust the shutter speed. To reset the camera to its default settings, refer to the relevant section of this manual. The Camera On-Screen Menu To access the camera on-screen menu for PhenoTypers with serial number 001471 and higher (from 2018 up to now), you need the UTC-100 on-screen device (OSD). Please contact Noldus if you do not have this device. Connect the OSD between PhenoTyper and a monitor (or PC video encoding board). Use video cables with BNC connectors, just as when connecting PhenoTyper to the PC. For details, see the PhenoTyper Reference Manual. - Press the central button to enter a menu or confirm a selection. - Press the Down button to navigate the menu, and the Left/Right buttons to switch between options. Note that Move Up does not have any effect. - Remember to select Save and Exit to confirm. To Open the Camera Settings Menu: - Start EthoVision XT, and in the Experiment Settings click the video icon in the row of your camera under Video Source. The live image from the PhenoTyper Top Unit camera appears. - Press the central button of the OSD. The on-screen menu appears. - By default, the first menu item, EXPOSURE, is selected. Important Camera Settings - AGC (Automatic Gain Control): Switch this off when the image of the animal is overlit. - Shutter: Adjust this if the image of the animal is overlit. Switch off Automatic Gain Control before making shutter adjustments. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2.1 Phenotyper 1 (Analog Camera) (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-21-phenotyper-1-analog-camera-continued Chapter: PhenoTyper PhenoTyper 1 (Analog Camera) Flicker. Adjust this depending on whether you have PAL or NTSC Top Unit cameras. Adjust. Only adjust this if switching off Automatic Gain Control and adjusting the Shutter Speed does not result in an image with good contrast. Save & Exit. To save the new settings and exit the menu. AGC (Automatic Gain Control) Using AGC means that weaker video signals receive more gain and stronger signals receive less gain or none at all. For a white animal on a dark background, it is beneficial to turn the AGC off, so that the subject does not appear overlit. For a dark animal on a bright background, the effect of AGC is less evident. Another disadvantage of setting AGC to On is that with a high gain the noise is also increased, and with it the file size of the resulting video. This is because a noisy video contains a lot of unpredictable movement (the noise) that has to be encoded and increases file size. - Select EXPOSURE, then AGC. - To disable AGC, press the Left/Right button to select OFF. - Connect the PhenoTyper Control Unit to increase the infra-red light to maximal (see the PhenoTyper - EthoVision XT 18 - Reference Manual). Then adjust the Shutter time (see below). Shutter The shutter time influences the brightness of the picture. - Select EXPOSURE, then SHUTTER. - Press the Left/Right button until 1/120 is selected. If the subject image is overlit, first switch off the Automatic Gain (see above). Then set the shutter to a value as small as possible. The subject should contrast well with the background and the image should have enough lighting. In most cases, 1/100 or 1/120 will work well. Flicker - Select EXPOSURE, then FLICKER and press the central button to confirm. - Depending on which TV standard your Top Unit camera is, choose 50 for PAL and 60 for NTSC. White Balance White balance is not crucial for a black and white camera like that of PhenoTyper. Adjusting settings will hardly result in a different image. We recommend to leave the settings to the default. Image & Setup Select IMAGE SET then press the central button to confirm. - Contrast. Adjust the image contrast by pressing the Left/Right button. - Sharpness. Adjust the image sharpness by pressing the Left/Right button. Save & Exit - Select SAVE & EXIT then press the central button to confirm. - Select YES, then press the central button to confirm. Select No to exit the menu without saving the settings. Reset This option resets the camera settings back to its default settings that are optimal for the PhenoTyper. - Select RESET then press the central button to confirm. - Under Factory mode, select YES and press the central button to confirm. For more information refer to the documentation that comes with the UTC-100 control device. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2.1 Phenotyper 1 (Analog Camera) (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-21-phenotyper-1-analog-camera-continued-deK Chapter: PhenoTyper PhenoTyper 1 (Analog Camera) Flicker. Adjust this depending on whether you have PAL or NTSC Top Unit cameras. Adjust. Only adjust this if switching off Automatic Gain Control and adjusting the Shutter Speed does not result in an image with good contrast. Save & Exit. To save the new settings and exit the menu. AGC (Automatic Gain Control) Using AGC means that weaker video signals receive more gain and stronger signals receive less gain or none at all. For a white animal on a dark background, it is beneficial to turn the AGC off, so that the subject does not appear overlit. For a dark animal on a bright background, the effect of AGC is less evident. Another disadvantage of setting AGC to On is that with a high gain the noise is also increased, and with it the file size of the resulting video. This is because a noisy video contains a lot of unpredictable movement (the noise) that has to be encoded and increases file size. - Select EXPOSURE, then AGC. - To disable AGC, press the Left/Right button to select OFF. - Connect the PhenoTyper Control Unit to increase the infra-red light to maximal (see the PhenoTyper - EthoVision XT 18 - Reference Manual). Then adjust the Shutter time (see below). Shutter The shutter time influences the brightness of the picture. - Select EXPOSURE, then SHUTTER. - Press the Left/Right button until 1/120 is selected. If the subject image is overlit, first switch off the Automatic Gain (see above). Then set the shutter to a value as small as possible. The subject should contrast well with the background and the image should have enough lighting. In most cases, 1/100 or 1/120 will work well. Flicker - Select EXPOSURE, then FLICKER and press the central button to confirm. - Depending on which TV standard your Top Unit camera is, choose 50 for PAL and 60 for NTSC. White Balance White balance is not crucial for a black and white camera like that of PhenoTyper. Adjusting settings will hardly result in a different image. We recommend to leave the settings to the default. Image & Setup Select IMAGE SET then press the central button to confirm. - Contrast. Adjust the image contrast by pressing the Left/Right button. - Sharpness. Adjust the image sharpness by pressing the Left/Right button. Save & Exit - Select SAVE & EXIT then press the central button to confirm. - Select YES, then press the central button to confirm. Select No to exit the menu without saving the settings. Reset This option resets the camera settings back to its default settings that are optimal for the PhenoTyper. - Select RESET then press the central button to confirm. - Under Factory mode, select YES and press the central button to confirm. For more information refer to the documentation that comes with the UTC-100 control device. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2.2 Phenotyper 2 (Digital Camera) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-22-phenotyper-2-digital-camera Chapter: PhenoTyper PhenoTyper 2 (Digital Camera) The PhenoTyper 2 camera is a Basler acA1300-60gm GigE Vision monochrome camera. To install and configure the camera, see one or more of the following: - The section Camera Installation in the EthoVision XT Help (F1). - The video Set Up your Camera in the EthoVision XT Video Tutorial (Help menu). - The PhenoTyper - EthoVision XT 18 - Reference Manual. Package Contents - Basler acA1300-60 gm. - Evetar 4 mm lens. - IR filter (already mounted on the camera). - CS to S-mount adapter. - Camera bracket. - 4 x M3 4 mm bolts for fixing the camera to its bracket. - 2 x M3 6 mm bolts for fixing the bracket to the PhenoTyper Top Plate. Camera Module You can fit the camera module in the central slot of the Top Plate. To insert or remove the camera module, use the four screws at its corners. The margin of the camera module is made in such a way that there is only one possible orientation — with the bracket facing opposite the Control Unit and the PhenoTyper logo. Power Up the Camera The PhenoTyper 2 camera gets power through the network cable that connects to the PC. You can power up the camera in two ways, depending on whether the Ethernet interface board received power from the PC: - If the Ethernet interface board does not receive power from the PC, you must use Power over Ethernet (PoE) injectors. This usually is the case for one- or two-port boards. - If the Ethernet interface board on the PC can receive power from the PC, like in the case of a 4-port board provided by Noldus, you can connect the camera directly to the board, but you must provide power to that board using an additional power cable connection inside the PC. For details, see the topic Install an Ethernet board for the GigE camera in the EthoVision XT Help. If the board has been installed by Noldus, the board is already powered so you just need to connect the cameras. Camera Focus and Orientation Camera Focus The lens of the PhenoTyper 2 camera is a F1/8 f4 mm fixed focal length, fixed iris lens. The focus of the lens has been optimized for the PhenoTyper cage. Note: The lens is a S-mount type lens. It is therefore provided with a CS-mount to S-mount adapter to fit on the camera. Always make sure that the camera has this adapter attached when, for any reason, you remove the lens from the camera and then put it back. Camera Orientation The orientation of the digital camera has been carefully set at production. There is no need to adjust it. Camera Settings The main camera settings can be adjusted in the Pylon Viewer dedicated software after the camera has been configured and connected to the PC. Alternatively, you can adjust camera settings like Exposure and Frame rate in EthoVision XT. For details, open the EthoVision XT Help (F1) and: - For installing the camera and adjusting its settings, see Camera Installation > Install GigE cameras. - For recommendations about the video resolution, frame rate, number of cameras and test duration, see Camera Installation > Choose your camera > GigE cameras. See also the PhenoTyper - EthoVision XT 18 - Reference Manual. The Top Unit Interface General Information Note: The Top Unit Interface is used in PhenoTyper 1. You can skip this chapter if you work with PhenoTyper 2. Components The Top Unit Interface is needed whenever you want to control multiple PhenoTypers (version 1) with EthoVision XT. You also need the USB-IO Box. You can connect up to four PhenoTypers to a Top Unit Interface. For information about the USB-IO box, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. The Top Unit Interface is meant for use together with PhenoTyper 1, not PhenoTyper 2. The Top Unit Interface comes with: - One 1-m modular cable RJ45 (green) for connecting the Top Unit Interface to the USB-IO box. - Four 2-m modular cables RJ45 (green) with a SubD-9 adapter to connect the Top Unit Interface to the PhenoTypers' Top Unit. - A USB extender cable (20 m), in case you need a longer distance between your computer and the PhenoTyper setup than the 3 m of a standard USB cable. It is possible to order longer cables, but the cable between the Top Unit Interface and the USB IO-Box should not be longer than 2 m. The cable between the Top Unit Interface and the PhenoTyper should not be longer than 5 m. LED Indicators - Busy (yellow LED): Indicates data exchange to/from a PhenoTyper 1 Top Unit. - Power (red LED): Indicates power supply from the USB-IO box through the modular RJ45 cable. Technical Specifications - Noldus type number: PTTI-001x - Power supply: 12V DC supplied by the USB-IO box - Current consumption: 40 mA - Connectors: 1x RJ45 8-pin modular to USB-IO box; 4x RJ45 8-pin modular to PhenoTyper 1 Top Units - Dimensions: 115 x 65 x 32 mm / 4.5 x 2.6 x 1.3 inches (L x W x H) - Weight: 100 gr - Cable to USB-IO box: 1x 1m modular RJ45 (green) - Cable to PhenoTyper Top Unit: 4x 2m modular RJ45 (green) with SubD-9 adapter Connect the Top Unit Interface Connection Scheme - Connect the USB-IO box port on the Top Unit Interface to the SDI Control port on the rear panel of the USB-IO box. - Connect the USB port on the USB-IO box to one of the USB ports of the EthoVision XT computer. - Make sure that the USB-IO box is powered up. - Connect the PhenoTyper Top Unit 1 port on the Top Unit Interface to the TTL in port of the first PhenoTyper, using the network cable with a SubD connector at one end (PhenoTyper Top Unit) and a RJ45 connector at the other end (Top Unit Interface). - Repeat the previous step for the remaining Top Units. Notes - The Top Unit Interface is designed for use with PhenoTyper 1. - For more details on how to connect PhenoTyper to the EthoVision XT computer, see the sections related to PhenoTyper 1 in the PhenoTyper - EthoVision XT 18 - Reference Manual. - If you want to connect multiple Top Unit Interfaces to your EthoVision XT computer, you must alter the position of jumpers inside the USB-IO box. For more information, see The USB-IO Box in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 2.2 Phenotyper 2 (Digital Camera) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-22-phenotyper-2-digital-camera-Buc Chapter: PhenoTyper PhenoTyper 2 (Digital Camera) The PhenoTyper 2 camera is a Basler acA1300-60gm GigE Vision monochrome camera. To install and configure the camera, see one or more of the following: - The section Camera Installation in the EthoVision XT Help (F1). - The video Set Up your Camera in the EthoVision XT Video Tutorial (Help menu). - The PhenoTyper - EthoVision XT 18 - Reference Manual. Package Contents - Basler acA1300-60 gm. - Evetar 4 mm lens. - IR filter (already mounted on the camera). - CS to S-mount adapter. - Camera bracket. - 4 x M3 4 mm bolts for fixing the camera to its bracket. - 2 x M3 6 mm bolts for fixing the bracket to the PhenoTyper Top Plate. Camera Module You can fit the camera module in the central slot of the Top Plate. To insert or remove the camera module, use the four screws at its corners. The margin of the camera module is made in such a way that there is only one possible orientation - with the bracket facing opposite the Control Unit and the PhenoTyper logo. Power Up the Camera The PhenoTyper 2 camera gets power through the network cable that connects to the PC. You can power up the camera in two ways, depending on whether the Ethernet interface board received power from the PC: - If the Ethernet interface board does not receive power from the PC, you must use Power over Ethernet (PoE) injectors. This usually is the case for one- or two-port boards. - If the Ethernet interface board on the PC can receive power from the PC, like in the case of a 4-port board provided by Noldus, you can connect the camera directly to the board, but you must provide power to that board using an additional power cable connection inside the PC. For details, see the topic Install an Ethernet board for the GigE camera in the EthoVision XT Help. If the board has been installed by Noldus, the board is already powered so you just need to connect the cameras. Camera Focus and Orientation Camera Focus The lens of the PhenoTyper 2 camera is a F1/8 f4 mm fixed focal length, fixed iris lens. The focus of the lens has been optimized for the PhenoTyper cage. Note: The lens is a S-mount type lens. It is therefore provided with a CS-mount to S-mount adapter to fit on the camera. Always make sure that the camera has this adapter attached when, for any reason, you remove the lens from the camera and then you put it back. Camera Orientation The orientation of the digital camera has been carefully set at production. There is no need to adjust it. Camera Settings The main camera settings can be adjusted in the Pylon Viewer dedicated software after the camera has been configured and connected to the PC. Alternatively you can adjust camera settings like Exposure and Frame rate in EthoVision XT. For details, open the EthoVision XT Help (F1) and: - For installing the camera and adjusting its settings, see Camera Installation > Install GigE cameras. - For recommendations about the video resolution, frame rate, number of cameras and test duration, see Camera Installation > Choose your camera > GigE cameras. - See also the PhenoTyper - EthoVision XT 18 - Reference Manual. The Top Unit Interface General Information Note: The Top Unit Interface is used in PhenoTyper 1. You can skip this chapter if you work with PhenoTyper 2. Components The Top Unit Interface is needed whenever you want to control multiple PhenoTypers (version 1) with EthoVision XT. You also need the USB-IO Box. You can connect up to four PhenoTypers to a Top Unit Interface. For information about the USB-IO box, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. The Top Unit Interface is meant for use together with PhenoTyper 1, not PhenoTyper 2. The Top Unit Interface comes with: - One 1-m modular cable RJ45 (green) for connecting the Top Unit Interface to the USB-IO box. - Four 2-m modular cables RJ45 (green) with a SubD-9 adapter to connect the Top Unit Interface to the PhenoTypers' Top Unit. - A USB extender cable (20 m), in case you need a longer distance between your computer and the PhenoTyper setup than the 3 m of a standard USB cable. It is possible to order longer cables, but the cable between the Top Unit Interface and the USB IO-Box should not be longer than 2 m. The cable between the Top Unit Interface and the PhenoTyper should not be longer than 5 m. LED Indicators - Busy (yellow LED): Indicates data exchange to/from a PhenoTyper 1 Top Unit. - Power (red LED): Indicates power supply from the USB-IO box through the modular RJ45 cable. Technical Specifications - Noldus Type Number: PTTI-001x - Power Supply: 12V DC supplied by the USB-IO box. - Current Consumption: 40 mA. - Connectors: 1x RJ45 8-pin modular to USB-IO box, 4x RJ45 8-pin modular to PhenoTyper 1 Top Units. - Dimensions: 115 x 65 x 32 mm / 4.5 x 2.6 x 1.3 inches (L x W x H). - Weight: 100 gr. - Cable to USB-IO Box: 1x 1 m modular RJ45 (green). - Cable to PhenoTyper Top Unit: 4x 2 m modular RJ45 (green) with SubD-9 adapter. Connect the Top Unit Interface Connection Scheme - Connect the USB-IO box port on the Top Unit Interface to the SDI Control port on the rear panel of the USB-IO box. - Connect the USB port on the USB-IO box to one of the USB ports of the EthoVision XT computer. - Make sure that the USB-IO box is powered up. - Connect the PhenoTyper Top Unit 1 port on the Top Unit Interface to the TTL in port of the first PhenoTyper, using the network cable with a SubD connector at one end (PhenoTyper Top Unit) and a RJ45 connector at the other end (Top Unit Interface). - Repeat the previous step for the remaining Top Units. Notes - The Top Unit Interface is designed for use with PhenoTyper 1. - For more details on how to connect PhenoTyper to the EthoVision XT computer, see the sections related to PhenoTyper 1 in the PhenoTyper - EthoVision XT 18 - Reference Manual. - If you want to connect multiple Top Unit Interfaces to your EthoVision XT computer, you must alter the position of jumpers inside the USB-IO box. For more information, see The USB-IO Box in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.2 Install The Pellet Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-42-install-the-pellet-dispenser Chapter: PhenoTyper Install the Pellet Dispenser Although the network cables shown in the following schemes are used in networks, the signal from and to the Pellet dispenser is not a network signal. Do not connect the Pellet dispenser via a network hub or similar. Connect the Pellet Dispenser Using the USB-IO Box Connect the Pellet dispenser to a TTL port on your USB-IO box or Mini USB-IO box using the network cable with RJ45 connectors. Connect the Pellet Dispenser Using the Mini USB-IO Box With EthoVision XT 14 and later versions, you can use the Pellet dispenser also when connected to the Mini USB-IO box. Important: Connect maximally two Pellet dispensers to a Mini USB-IO box. Before connecting the devices, do the following: - Browse to my.noldus.com (you need to log in or register first), and choose Downloads > EthoVision XT. Download EthoVision XT - Full installation disc [version number].zip. Unzip the file and locate the folder Drivers and Tools > IoBox MiniIoBox Devices. There you find the file MiniIoBox PelletDispenser. - Open the folder MiniIoBox PelletDispenser and copy one of the files depending on the language set in EthoVision XT: - For Chinese: DeviceTypesNoldusChCh.xml - For English: DeviceTypesNoldusEnUs.xml - Go to the following folder on your EthoVision XT computer: C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface MiniIobox\ - Press Ctrl+V (Edit > Paste). Replace the old file version with the new one. - Delete the file DeviceTypesNoldus.xml in that folder. - Connect the Pellet dispenser to the Mini USB-IO box, and start EthoVision XT. - Create a new experiment and set up EthoVision XT. Attach the Pellet Dispenser to Objects To attach the Pellet dispenser to a stand or any other object, use the four M4 threaded holes located under the foot of the dispenser. For More Information For more information about the interface devices, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. The Pellet Receptacle Purpose Use the Pellet receptacle in two cases: - To collect the pellets dropped by the Pellet dispenser (no measurement). The pellets are kept in the receptacle instead of dropping on the PhenoTyper floor. - To record the number of times that the subject visited the receptacle. This is done with a beam break mechanism that records the nose pokes. How Nose Pokes Are Detected A mechanism based on an infrared beam detects the subject's nose pokes into the opening. When the subject pokes its nose into the opening of the receptacle, the infrared beam is broken. If the beam is broken for at least approximately 50 ms, a TTL signal "Low" is sent to the USB-IO box and therefore to EthoVision XT. When the beam is not broken (or broken for less than 50 ms), the TTL signal stays "High". The TTL signal will stay "Low" for at least 200 ms for a single nose poke. In case of multiple nose pokes shorter than 200 ms, these will be merged into one "Low" TTL signal. Connect the Pellet Receptacle to the USB-IO Box The Pellet receptacle comes attached to its wall. A black network cable with a special connector is included in the package. - Replace one of the PhenoTyper walls with the Pellet receptacle wall. Make sure that the black tube stays at the outer side of PhenoTyper. For how to assemble the PhenoTyper cages, see the PhenoTyper - EthoVision XT 18 - Reference Manual. - Connect the tube of the Pellet dispenser to the black tube of the Pellet receptacle. If necessary, use the transparent tube that comes with the Pellet dispenser to connect the two devices. - Connect the Pellet receptacle to one of the TTL ports of the USB-IO box using the special black cable that comes with the Pellet receptacle wall. Each Pellet dispenser and Pellet receptacle combination needs two TTL ports: one for sending the pellet drop command to the Pellet dispenser, and one to read the nose pokes from the Pellet receptacle. Important: The cage walls equipped with the Pellet receptacle contain an integrated circuit board. They must be cleaned with special care. Always follow the procedure described in the PhenoTyper - EthoVision XT 18 - Reference Manual. Technical Specifications Pellet Dispenser - Noldus Device Number: PTPD-001x - Power Supply: 18–26 V DC - Current Consumption: Standby 30 mA; when dropping pellet 250 mA - Manual Control: Single button - Remote Control: TTL input - Connector: RJ45 8 pin modular - Input: Optical isolated TTL logic 5 Volt - Output: Open collector type - Dimensions: Height: 20 cm (7 7/8"); base diameter: 10 cm (3 15/16"); silo diameter: 7.5 cm (2 61/64") - Weight: 1200 grams (42 oz) - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Pellet Types: 20 mg, 45 mg Pellet Receptacle - Noldus Device Number: PTPR-001x - Power Supply: 7–24 V DC - Current Consumption: Max. 30 mA at 24 V - Output: Open collector type - Connector: 3 pin female KK connector - Dimensions: Height: 7.7 cm (3 1/32"); width: 4.5 cm (1 49/64"); depth: 5.1 cm (2 1/64") - Weight: 62 grams (2.2 oz) - Pellet Types: 20 mg (tested), 45 mg (tested); maximum diameter 10 mm Reliability Noldus has tested the Pellet dispenser thoroughly in order to ensure its reliability and good functioning for long periods of time. Tests have been carried out on 16 Pellet dispensers with more than 20,000 pellets dropped. The pellets tested were from Bio-Serv and TestDiet. The deviation between the number of delivered and expected pellets is always within 5%, and in any case on the positive side. This means that a few more pellets are dropped, not fewer, than expected. For example, one instance of the Drop pellet command in EthoVision XT may result in two pellets being dropped instead of one. There may be some variation between individual Pellet dispensers. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.2 Install The Pellet Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-42-install-the-pellet-dispenser-sEm Chapter: PhenoTyper Install the Pellet Dispenser Although the network cables shown in the following schemes are used in networks, the signal from and to the Pellet dispenser is not a network signal. Do not connect the Pellet dispenser via a network hub or similar. Connect the Pellet Dispenser Using the USB-IO Box Connect the Pellet dispenser to a TTL port on your USB-IO box or Mini USB-IO box using the network cable with RJ45 connectors. Connect the Pellet Dispenser Using the Mini USB-IO Box With EthoVision XT 14 and later versions, you can use the Pellet dispenser also when connected to the Mini USB-IO box. Important: Connect maximally two Pellet dispensers to a Mini USB-IO box. Before connecting the devices, do the following: - Browse to my.noldus.com (you need to log in or register first), and choose Downloads > EthoVision XT. Download EthoVision XT - Full installation disc [version number].zip. Unzip the file and locate the folder Drivers and Tools > IoBox MiniIoBox Devices. There you will find the file MiniIoBox PelletDispenser. - Open the folder MiniIoBox PelletDispenser and copy one of the files depending on the language set in EthoVision XT: - For Chinese: DeviceTypesNoldusChCh.xml - For English: DeviceTypesNoldusEnUs.xml - Go to the following folder on your EthoVision XT computer: C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface MiniIobox\ - Press Ctrl+V (Edit > Paste). Replace the old file version with the new one. - Delete the file DeviceTypesNoldus.xml in that folder. - Connect the Pellet dispenser to the Mini USB-IO box, and start EthoVision XT. - Create a new experiment and set up EthoVision XT. See page 40. Attach the Pellet Dispenser to Objects To attach the Pellet dispenser to a stand or any other object, use the four M4 threaded holes located under the foot of the dispenser. For More Information For more information about the interface devices, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual (see manuals on page 9). The Pellet Receptacle Purpose Use the Pellet receptacle in two cases: - To collect the pellets dropped by the Pellet dispenser (no measurement). The pellets are kept in the receptacle instead of dropping on the PhenoTyper floor. - To record the number of times that the subject visited the receptacle. This is done with a beam break mechanism that records the nose pokes. How Nose Pokes Are Detected A mechanism based on an infrared beam detects the subject's nose pokes into the opening. When the subject pokes its nose into the opening of the receptacle, the infrared beam is broken. If the beam is broken for at least approximately 50 ms, a TTL signal "Low" is sent to the USB-IO box and therefore to EthoVision XT. When the beam is not broken (or broken for less than 50 ms), the TTL signal stays "High". The TTL signal will stay "Low" for at least 200 ms for a single nose poke. In case of multiple nose pokes shorter than 200 ms, these will be merged into one "Low" TTL signal. Connect the Pellet Receptacle to the USB-IO Box The Pellet receptacle comes attached to its wall. A black network cable with a special connector is included in the package. - Replace one of the PhenoTyper walls with the Pellet receptacle wall. Make sure that the black tube stays at the outer side of PhenoTyper. For how to assemble the PhenoTyper cages, see the PhenoTyper - EthoVision XT 18 - Reference Manual. - Connect the tube of the Pellet dispenser to the black tube of the Pellet receptacle. If necessary, use the transparent tube that comes with the Pellet dispenser to connect the two devices. - Connect the Pellet receptacle to one of the TTL ports of the USB-IO box. Use the special black cable that comes with the Pellet receptacle wall. Each Pellet dispenser and Pellet receptacle combination requires two TTL ports: one for sending the pellet drop command to the Pellet dispenser, and one to read the nose pokes from the Pellet receptacle. Important: The cage walls equipped with the Pellet receptacle contain an integrated circuit board. They must be cleaned with special care. Always follow the procedure described in the PhenoTyper - EthoVision XT 18 - Reference Manual. Technical Specifications Pellet Dispenser - Noldus Device Number: PTPD-001x - Power Supply: 18–26 V DC - Current Consumption: Standby 30 mA; when dropping pellet 250 mA - Manual Control: Single button - Remote Control: TTL input - Connector: RJ45 8 pin modular - Input: Optical isolated TTL logic 5 Volt - Output: Open collector type - Dimensions: Height: 20 cm (7 7/8"); base diameter: 10 cm (3 15/16"); silo diameter: 7.5 cm (2 61/64") - Weight: 1200 grams (42 oz) - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Pellet Types: 20 mg, 45 mg Pellet Receptacle - Noldus Device Number: PTPR-001x - Power Supply: 7–24 V DC - Current Consumption: Max. 30 mA at 24 V - Output: Open collector type - Connector: 3 pin female KK connector - Dimensions: Height: 7.7 cm (3 1/32"); width: 4.5 cm (1 49/64"); depth: 5.1 cm (2 1/64") - Weight: 62 grams (2.2 oz) - Pellet Types: 20 mg (tested), 45 mg (tested), maximum diameter 10 mm Reliability Noldus has tested the Pellet dispenser thoroughly in order to ensure its reliability and good functioning for long periods of time. Tests have been carried out on 16 Pellet dispensers with more than 20,000 pellets dropped. The pellets tested were from Bio-Serv and TestDiet. The deviation between the number of delivered and expected pellets is always within 5%, and in any case on the positive side. This means that a few more pellets are dropped, not fewer, than expected. For example, one instance of the Drop pellet command in EthoVision XT may result in two pellets being dropped instead of one. There may be some variation between individual Pellet dispensers. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.3 Work With The Pellet Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-43-work-with-the-pellet-dispenser Chapter: PhenoTyper Work with the Pellet Dispenser EthoVision XT - Prepare the Experiment - If you use the Mini USB-IO box, first follow the instructions under Connect the Pellet Dispenser using the Mini USB-IO box. - Connect the USB-IO box / Mini USB-IO box to the EthoVision XT computer and make sure that all devices are powered up, as described in the previous section. For details about the USB-IO box and the Mini USB-IO box, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Start EthoVision XT and create a new experiment or open an existing one. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control Hardware option, and click Settings next to that option. - In the window that opens, choose the interface device you have: - Noldus USB-IO box - Noldus Mini USB-IO box Next, click OK. The Device Configuration window opens. - For the TTL Control port which you connected the Pellet dispenser to, select Pellet Dispenser (PTPD-001x) as the Device/Device type. Repeat this step for each Pellet dispenser connected to TTL ports. - If your Pellet dispensers are connected to two or more USB-IO boxes, you must repeat the step above for the Pellet dispensers connected to the remaining interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the Port Connections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, in the section covering the USB-IO box and the Mini USB-IO box. EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. - If you have only one arena, you can skip the following steps. The hardware is automatically assigned to the arena. - If you have more than one arena, continue with the steps below. - Click the Arena - Hardware Mapping button in the Arena Settings window. - Under Device type, you should see Pellet Dispenser (PTPD-001x). If that is not the case, click Add Device and under Device type, select Pellet Dispenser (PTPD-001x). - Under Device name, accept the default name or type in a name, for example, Pellet dispenser. - Assign a Pellet dispenser to each arena. To do so, select the physical device Pellet Dispenser (PTPD-001x) [n] under the name of the arena it belongs to. Important: Make sure that each physical device is assigned to only one arena. - To test the Pellet dispenser, see the Check That the Pellet Dispenser Works section below. - Click OK to close the Arena - Hardware Mapping window. For more information on this step, see Assign Devices to Arenas in the EthoVision XT - Trial and Hardware Control - Reference Manual. For more information on the Arena Settings, see Arena Settings in the EthoVision XT Help. EthoVision XT - Trial Control Settings You can control the Pellet dispenser by defining Trial Control Settings in EthoVision XT. As the Pellet dispenser is mostly used in learning tests, you will probably need to define a sub-rule that is repeated a number of times, for a specified duration, or indefinitely in order to teach the animal what the rule is. For instance, drop a pellet every time the mouse is in the trigger zone and repeat this indefinitely. You can define a maximum trial duration to stop the trial or stop it manually. Check That the Pellet Dispenser Works The Pellet Drop Detector An infrared photo beam detector senses whether a pellet is dropped after a "drop pellet" command has been given (either manually by pushing the blue button at the front or with the USB-IO box and EthoVision XT). When no pellet is detected, the stepper motor moves the carousel within the silo one step further. If, even after a full rotation, no falling pellet was detected, the system considers the silo to be empty. The Pellet dispenser goes into error mode and the LED at the front blinks continuously. Fill the silo with pellets and press the blue button at the front of the Pellet dispenser to reset the device. Make sure that there are enough pellets in the silo before you start your experiment. If the silo is almost empty, it may take some time before a pellet is dropped. It is also possible that no pellet is dropped due to an obstruction in the falling path caused by fragments of pellets. Use one of the following options to check whether your Pellet dispenser works and whether your Trial Control Settings behave as expected: Checking Before Running a Trial - Choose Setup > Arena Settings. Open the Arena Settings you defined earlier. - In the Arena Settings window, click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, select the Pellet dispenser and click Test. - A new window appears. The following message should appear: Number of drops: 0; In error state? false. - Click the Test button and check that a pellet is dropped. You can also view the result in the window — the number of drops increases by 1. Note: When you click the Test button for the first time after power-on, the Pellet dispenser delivers one pellet after some delay. This is due to the mechanism that operates to calibrate the drop position. This delay does not occur in subsequent test actions. Checking While the Trial Is Running Check the LED indicator at the front of the Pellet dispenser. The LED blinks two times in a rapid sequence: - Single blink when the Pellet dispenser receives a Drop Pellet command from EthoVision XT. - Single blink when a pellet is dropped. Control the Pellet Dispenser Manually With EthoVision XT You can have the Pellet dispenser drop a pellet every time you press a key on the keyboard. For this, you must use EthoVision XT. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.3 Work With The Pellet Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-43-work-with-the-pellet-dispenser-IGf Chapter: PhenoTyper Work with the Pellet Dispenser EthoVision XT - Prepare the Experiment - If you use the Mini USB-IO box, first follow the instructions under Connect the Pellet Dispenser using the Mini USB-IO box. - Connect the USB-IO box / Mini USB-IO box to the EthoVision XT computer and make sure that all devices are powered up, as described in the previous section. For details about the USB-IO box and the Mini USB-IO box, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Start EthoVision XT and create a new experiment or open an existing one. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device you have: - Noldus USB-IO box - Noldus Mini USB-IO box Next, click OK. The Device Configuration window opens. - For the TTL Control port which you connected the Pellet dispenser to, select Pellet Dispenser (PTPD-001x) as the Device/Device type. Repeat this step for each Pellet dispenser connected to TTL ports. - If your Pellet dispensers are connected to two or more USB-IO boxes, you must repeat the step above for the Pellet dispensers connected to the remaining interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, in the section for the USB-IO box and the Mini USB-IO box. EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. If you have only one arena, you can skip the following steps. The hardware is automatically assigned to the arena. If you have more than one arena, complete the following steps. - Click the Arena - Hardware mapping button in the Arena Settings window. - Under Device type, you should see Pellet dispenser (PTPD-001x). If that is not the case, click Add device and under Device type, select Pellet Dispenser (PTPD-001x). - Under Device name, accept the default name or type in a name, for example, Pellet dispenser. - Assign a Pellet dispenser to each arena. To do so, select the physical device Pellet Dispenser (PTPD-001x) [n] under the name of the arena it belongs to. Important: Make sure that each physical device is assigned to only one arena. - To test the Pellet dispenser, see the section below. - Click OK to close the Arena - Hardware mapping window. For more information on this step, see Assign devices to arenas in the EthoVision XT - Trial and Hardware Control - Reference Manual. For more information on the Arena Settings, see Arena Settings in the EthoVision XT Help. EthoVision XT - Trial Control Settings You can control the Pellet dispenser by defining Trial Control Settings in EthoVision XT. As the Pellet dispenser is mostly used in learning tests, you will probably need to define a sub-rule that is repeated a number of times, for a specified duration, or indefinitely in order to teach the animal what the rule is. For instance, drop a pellet every time the mouse is in the trigger zone and repeat this indefinitely. You can define a maximum trial duration to stop the trial or stop it manually. Check That the Pellet Dispenser Works The Pellet Drop Detector An infrared photo beam detector senses whether a pellet is dropped after a "drop pellet" command has been given (either manually by pushing the blue button at the front or with the USB-IO box and EthoVision XT). When no pellet is detected, the stepper motor moves the carousel within the silo one step further. If, even after a full rotation, no falling pellet was detected, the system considers the silo to be empty. The Pellet dispenser goes into error mode and the LED at the front blinks continuously. Fill the silo with pellets and press the blue button at the front of the Pellet dispenser to reset the device. Make sure that there are enough pellets in the silo before you start your experiment. If the silo is almost empty, it may take some time before a pellet is dropped. It can also be that no pellet is dropped because there is an obstruction in the falling path of the pellet caused by fragments of pellets. Checking Before Running a Trial - Choose Setup > Arena Settings. Open the Arena Settings you defined earlier. - In the Arena Settings window, click the Arena - Hardware mapping button. - In the Arena - Hardware mapping window, select the Pellet dispenser and click Test. - A new window appears. The following message should appear: Number of drops: 0; In error state? false. - Click the Test button and check that a pellet is dropped. You can also view the result in the window; the number of drops increases by 1. Note: When you click the Test button for the first time after power-on, the Pellet dispenser delivers one pellet after some delay. This is due to the mechanism that operates to calibrate the drop position. This delay does not occur in subsequent test actions. Checking While the Trial Is Running Check the LED indicator at the front of the Pellet dispenser. The LED blinks two times in a rapid sequence: - Single blink when the Pellet dispenser receives a Drop pellet command from EthoVision XT. - Single blink when a pellet is dropped. Control the Pellet Dispenser Manually With EthoVision XT You can have the Pellet dispenser drop a pellet every time you press a key on the keyboard. For this, you must use EthoVision XT. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.3 Work With The Pellet Dispenser (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-43-work-with-the-pellet-dispenser-continued-RBB Chapter: PhenoTyper Work with the Pellet Dispenser - In the Manual Scoring Settings, define a fictitious behavior, for example, Pellet of type Point event. Assign a key to this behavior. For more information, see Manual Scoring Settings in the EthoVision XT Help. - In the Trial Control Settings, create a subrule that contains the following conditions and actions: [Rule Begin] > [Condition: Frequency (Pellet)>=1] > [Action: Drop pellet] > [Rule End] Make sure that the Reference box for this Subrule specifies Repeat indefinitely. - During acquisition, in the Manual Scoring tab, to drop a pellet click the button or press the key for the behavior Pellet. - In the Analysis profile, define the variable Pellet to visualize, for example, the total number of pellets dropped. With the Pellet Dispenser Button When using the pellet dispenser as a stand-alone device, you must connect it to a mains socket using the power supply for stand-alone use (PTPD-2010). Push the button at the front to drop a pellet. Note: When you press the blue button for the first time after power-on, the pellet dispenser delivers one pellet after some delay. This is due to the mechanism that operates to calibrate the drop position. This delay does not occur in the following drop actions. Work with the Pellet Receptacle Make sure that the USB-IO box is connected to the EthoVision XT computer, and that the Pellet receptacle is connected to a TTL port of the USB-IO box. Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, select Noldus USB-IO box and click OK. - For the TTL Control port which you connected the Pellet receptacle to, select Pellet Receptacle (PTPR-001x) as the Device/Device type. Repeat this step for each Pellet receptacle connected to TTL ports. - If your Pellet receptacles are connected to two or more USB-IO boxes, you must repeat the step above for the Pellet receptacles connected to the other interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the Port Connections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, in the section for your interface device: The USB-IO Box and the Mini USB-IO Box. Arena Settings If you have only one arena, you can skip the following steps. The hardware is automatically assigned to the arena. If you have more than one arena, do the following: - In the Arena Settings, click the Arena - Hardware Mapping button and click Add device. - Under Device type, select Pellet Receptacle (PTPD-001x). - To assign a Pellet receptacle to a specific arena, select Pellet Dispenser (PTPD-001x) in the corresponding column. When finished, click OK. Trial Control Settings - Choose Setup > Trial Control Settings. - Under Conditions, you find Pellet Receptacle (PTPR-001x). - Click the button next to it to add a condition based on the number of pokes. For example, to stop tracking when the number of nose pokes has reached a certain value. For more details on conditions, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Test the Pellet Receptacle - Choose Setup > Arena Settings. Open the Arena Settings you defined earlier and click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, select the Pellet receptacle and click Test. - A new window appears with the following messages: Number of nose pokes: 0; Is nose poke detected?: false. - Click the Test button and insert a pen tip in the Pellet receptacle. - View the result in the window; the message should say Number of nose pokes: 1 and Is nose poke detected?: true. Note: The green LED at the outer side of the receptacle switches off every time a poke occurs. Troubleshoot the Pellet Receptacle If the Pellet receptacle is not responding, do the following: - Check that the cable is not defective. Replace the cable from the Pellet receptacle to the USB-IO box, and between the USB-IO box and EthoVision XT (if you suspect that it may be defective too). Then repeat the test described above. - Check if the TTL port on the USB-IO box works. - Connect the TTL Port tester to the same port of the USB-IO box that was connected to the Pellet receptacle. As a result, the TTL-power LED of the TTL Port tester should switch on. - Press the IN-1 button; this should be detected by EthoVision XT. If that happens, then the TTL port works to support the Pellet receptacle. Tip: For information about the TTL Port tester, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Connect the Pellet receptacle to the TTL port on the USB-IO box that you have just tested. - During power-up, the green LED on the Pellet receptacle near the cable connector should blink two times and then stay on. - Whenever the infrared beam in the receptacle is interrupted (for example, when inserting the tip of a pen), the green LED should switch off. If that does not happen, the receptacle may be defective (provided that all cables have been checked) and must therefore be replaced. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.3 Work With The Pellet Dispenser (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-43-work-with-the-pellet-dispenser-continued Chapter: PhenoTyper Work with the Pellet Dispenser - In the Manual Scoring Settings, define a fictitious behavior, for example, Pellet of type Point event. Assign a key to this behavior. For more information, see Manual Scoring Settings in the EthoVision XT Help. - In the Trial Control Settings, create a subrule that contains the following conditions and actions: [Rule Begin] > [Condition: Frequency (Pellet)>=1] > [Action: Drop pellet] > [Rule End] Make sure that the Reference box for this Subrule specifies Repeat indefinitely. - During acquisition, in the Manual Scoring tab, to drop a pellet click the button or press the key for the behavior Pellet. - In the Analysis profile, define the variable Pellet to visualize, for example, the total number of pellets dropped. With the Pellet Dispenser Button When using the pellet dispenser as a stand-alone device, you must connect it to a mains socket using the power supply for stand-alone use (PTPD-2010). Push the button at the front to drop a pellet. Note: When you press the blue button for the first time after power-on, the pellet dispenser delivers one pellet after some delay. This is due to the mechanism that operates to calibrate the drop position. This delay does not occur in the following drop actions. Work with the Pellet Receptacle Make sure that the USB-IO box is connected to the EthoVision XT computer, and that the Pellet receptacle is connected to a TTL port of the USB-IO box. Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, select Noldus USB-IO box and click OK. - For the TTL Control port which you connected the Pellet receptacle to, select Pellet Receptacle (PTPR-001x) as the Device/Device type. Repeat this step for each Pellet receptacle connected to TTL ports. - If your Pellet receptacles are connected to two or more USB-IO boxes, you must repeat the step above for the Pellet receptacles connected to the other interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in one of the following sections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, depending on which interface device you use: The USB-IO box and the Mini USB-IO box. Arena Settings If you have only one arena, you can skip the following steps. The hardware is automatically assigned to the arena. If you have more than one arena, do the following: - In the Arena Settings, click the Arena - Hardware mapping button and click Add device. - Under Device type, select Pellet Receptacle (PTPD-001x). - To assign a Pellet receptacle to a specific arena, select Pellet Dispenser (PTPD-001x) in the corresponding column. When finished, click OK. Trial Control Settings - Choose Setup > Trial Control Settings. - Under Conditions, you find Pellet Receptacle (PTPR-001x). - Click the button next to it to add a condition based on the number of pokes. For example, to stop tracking when the number of nose pokes has reached a certain value. For more details on conditions, see also the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Test the Pellet Receptacle - Choose Setup > Arena Settings. Open the Arena Settings you defined earlier and click the Arena - Hardware mapping button. - In the Arena - Hardware Mapping window, select the pellet receptacle and click Test. - A new window appears with the following messages: Number of nose pokes: 0; Is nose poke detected?: false. - Click the Test button and insert a pen tip in the Pellet receptacle. - View the result in the window; the message should say Number of nose pokes: 1 and Is nose poke detected?: true. Note: The green LED at the outer side of the receptacle switches off every time a poke occurs. Troubleshoot the Pellet Receptacle If the pellet receptacle is not responding, do the following: - Check that the cable is not defective. To do so, replace the cable from the Pellet receptacle to the USB-IO box, and between the USB-IO box and EthoVision XT (if you suspect that it may be defective too). Then repeat the test described above. - Check if the TTL port on the USB-IO box works. - Connect the TTL Port tester to the same port of the USB-IO box that was connected to the Pellet receptacle. As a result, the TTL-power LED of the TTL Port tester should switch on. - Press the IN-1 button; this should be detected by EthoVision XT. If that happens, then the TTL port works to support the Pellet receptacle. Tip: For information about the TTL Port tester, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Connect the Pellet receptacle to the TTL port on the USB-IO box that you have just tested. - During power-up, the green LED on the Pellet receptacle near the cable connector should blink two times and then stay on. - Whenever the infrared beam in the receptacle is interrupted (for example, when inserting the tip of a pen), the green LED shall switch off. If that does not happen, the receptacle may be defective (provided that all cables have been checked) and must therefore be replaced. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.5 Maintenance And Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-45-maintenance-and-troubleshooting-ubC Chapter: PhenoTyper Maintenance and Troubleshooting Correct Usage of the Pellet Dispenser How to Fill the Silo Do not (re-)fill the silo while it stands on the Pellet Dispenser. The procedure below prevents a pellet from falling through the hole and being crushed when you push the silo back in place. - Remove the silo and place it on a table. Open its lid and fill it with the pellets. - Close the lid. While holding the lid closed, turn the Pellet Dispenser upside down and attach the silo. - Put the Pellet Dispenser back on the table. Only Use Intact Pellets If you notice dust and broken pellets in the package, carefully remove them. Use for example a sieve to divide the intact pellets from the rest. Clean the Pellet Dispenser Regularly Cleaning the Pellet Dispenser reduces the chance of malfunctioning. Clean at the end of an experiment / after 500 pellets dropped / every two days (whichever comes first). Replace or dry out the silica gel pack, e.g. with an oven, at the same time of cleaning. See also the section below. Keep and Use the Pellets in a Dry Place Make sure that you keep and use the pellets in a climate with relative humidity (RH) less than 40%. Pellets readily absorb moisture from the atmosphere. When kept in a humid climate, they absorb water and become frail. That may result in more broken pellets in the silo. We recommend keeping the silica gel pack attached to the lid of the silo. Replace the Silica Gel From mid 2022 the Pellet Dispenser is provided with 2-gram sachets of RS PRO Indicating Silica Gel that can be easily replaced. This gel changes its color from yellow to green when it has absorbed the maximum moisture. When the gel turns green, remove the sachet and attach a new or regenerated one to the lid of the silo. Regenerate the Silica Gel You can regenerate the silica gel by placing the sachet in an oven at 110°C (230°F) for three to four hours. Do Not Reuse Pellets Pellets that have previously been inside the silo may weaken internally and that increases the risk that they break or produce dust during use. Clean the Pellet Dispenser We recommend thoroughly cleaning the Pellet Dispenser at regular intervals because a clean product ensures reliability and long-term use. - Disassemble the pellet silo to ensure that the pellet dust can be removed easily. If you are going to clean a large number of Pellet Dispensers, consider using an electric screwdriver to disassemble them more quickly. - Clean the tube. Insert a dry cloth (not fraying) in the tube to pull the dust out. - Clean the holes in the carousel. Dust accumulates in holes quite easily, which may cause pellets to get stuck. - Usually cleaning with a dry cloth is sufficient. Do not use any liquids for cleaning purposes. Liquids can stick to the pellets or dust. Whenever liquids are used, make sure to dry all parts completely. - Clean the upper part of the carousel, 8–10 minutes depending on the cleaning substances used. Troubleshooting Issue: The Pellet Dispenser is full of pellets, but it fails to drop a pellet. - Disconnect the Pellet Dispenser from the USB-IO box and remove the silo. - Manually insert a pellet into the acrylic tube and check whether the pellet is dropped. - If the pellet does not come through, there must be some material obstructing the route. Try to remove it by gently poking into the acrylic tube using a 3-mm polyurethane foam swab, a flexible wire, or a tie-wrap. Important: Do not use any object that could cause scratches inside the tube. - If no obstruction is found, do the following: - IR Beam Detector: The IR beam detector could be defective. Connect the dispenser to the USB-IO box in order to get power. After you press the blue button, the Pellet Dispenser attempts to drop the first pellet. Manually drop a pellet into the acrylic tube. When the pellet is detected, the device should stop rotating and the red LED should give a single blink to indicate "pellet dropped". In that case, detection is working fine. If the IR detector is not working correctly, contact Noldus to have the dispenser repaired or replaced. - Mechanical Problem: There may be some mechanical problem. Remove most of the pellets from the silo, leaving only a few (5–8) remaining. Apply power and press the blue button. Look into the silo — the dispenser will search for the first pellet and drop it. If that is the case, press the blue button again and the next pellet should be found and dropped. If that does not work, the aluminum hole cover clip may prevent pellets from falling down. You can adjust the position of the clip by slightly unscrewing it and fastening it gently again afterwards. The optimal position of the clip also depends on the pellet type used. Some experimenting may be needed. If none of the steps above help, the dispenser must be checked and repaired. In case of repair, please always ship the complete unit to Noldus. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 4.5 Maintenance And Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-45-maintenance-and-troubleshooting Chapter: PhenoTyper Maintenance and Troubleshooting Correct Usage of the Pellet Dispenser How to Fill the Silo Do not (re-)fill the silo while it stands on the Pellet dispenser. The procedure below prevents a pellet from falling through the hole and being crushed when you push the silo back in place. - Remove the silo and place it on a table. Open its lid and fill it with the pellets. - Close the lid. While holding the lid closed, turn the Pellet dispenser upside down and attach the silo. - Put the Pellet dispenser back on the table. Only Use Intact Pellets If you notice dust and broken pellets in the package, carefully remove them. Use for example a sieve to divide the intact pellets from the rest. Clean the Pellet Dispenser Regularly Cleaning the Pellet dispenser reduces the chance of malfunctioning. Clean at the end of an experiment / after 500 pellets dropped / every two days (whichever comes first). Replace or dry out the silica gel pack, e.g. with an oven, at the same time of cleaning. Keep and Use the Pellets in a Dry Place Make sure that you keep and use the pellets in a climate with relative humidity (RH) less than 40%. Pellets readily absorb moisture from the atmosphere. When kept in a humid climate, they absorb water and become frail. That may result in more broken pellets in the silo. We recommend keeping the silica gel pack attached to the lid of the silo. Replace the Silica Gel From mid 2022 the Pellet dispenser is provided with 2-gram sachets of RS PRO Indicating Silica Gel that can be easily replaced. This gel changes its color from yellow to green when it has absorbed the maximum moisture. When the gel turns green, remove the sachet and attach a new or regenerated one to the lid of the silo. Regenerate the Silica Gel You can regenerate the silica gel by placing the sachet in an oven at 110°C (230°F) for three to four hours. Do Not Reuse Pellets Pellets that have previously been inside the silo may weaken internally, increasing the risk that they break or produce dust during use. Clean the Pellet Dispenser We recommend thoroughly cleaning the Pellet dispenser at regular intervals because a clean product ensures reliability and long-term use. - Disassemble the pellet silo to ensure that pellet dust can be removed easily. If you are going to clean a large number of Pellet dispensers, consider using an electric screwdriver to disassemble them more quickly. - Clean the tube. Insert a dry cloth (not fraying) into the tube to pull the dust out. - Clean the holes in the carousel. Dust accumulates in holes quite easily, which may cause pellets to get stuck. - Usually cleaning with a dry cloth is sufficient. Do not use any liquids for cleaning purposes. Liquids can stick to the pellets or dust. Whenever liquids are used, make sure to dry all parts completely. - Clean the upper part of the carousel, 8–10 minutes depending on the cleaning substances used. Troubleshooting Problem: The Pellet dispenser is full of pellets, but it fails to drop a pellet. - Disconnect the Pellet dispenser from the USB-IO box and remove the silo. - Manually insert a pellet into the acrylic tube and check whether the pellet is dropped. - If the pellet does not come through, there must be some material obstructing the route. Try to remove it by gently poking into the acrylic tube using a 3-mm Polyurethane foam swab, a flexible wire, or a tie-wrap. Important: Do not use any object that could cause scratches inside the tube. - If no obstruction is found, do the following: - IR Beam Detector: The IR beam detector could be defective. Connect the dispenser to the USB-IO box to get power. After you press the blue button, the Pellet dispenser attempts to drop the first pellet. Manually drop a pellet into the acrylic tube. When the pellet is detected, the device should stop rotating and the red LED should give a single blink to indicate "pellet dropped". If the IR detector is not working correctly, contact Noldus to have the dispenser repaired or replaced. - Mechanical Problem: There may be a mechanical problem. Remove most of the pellets from the silo, leaving only a few (5–8) remaining. Apply power and press the blue button. Look into the silo — the dispenser will search for the first pellet and drop it. Press the blue button again; the next pellet should be found and dropped. If that does not work, the aluminum hole cover clip may be preventing pellets from falling down. Adjust the position of the clip by slightly unscrewing it and fastening it gently again. The optimal position of the clip also depends on the pellet type used. Some experimenting may be needed. If none of the steps above help, the dispenser must be checked and repaired. In case of repair, please always ship the complete unit to Noldus. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.1 General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-51-general-information-ljq Chapter: PhenoTyper General Information The Lickometer The Noldus Lickometer is a device that measures contact between a rat or mouse and its water bottle. It consists of an electronics box with (A) a metal ground plate and (B) a clip attached to it. Whenever a mouse or a rat contacts the spout of the water bottle, the capacitance between the clip attached to the spout and the metal ground plate changes. This change is detected by the Lickometer. The advantage of this system is that there is no current flow through the animal. The Lickometer is designed as an add-on to the PhenoTyper. To be able to receive information from hardware devices you need the Trial and Hardware Control module. You can control multiple lickometers with EthoVision XT (up to six per USB-IO box). For the limitations, see Control Hardware Devices in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Contents of the Lickometer Package A Lickometer package includes: - A Lickometer PTLM-001x - A black network cable with RJ45 connectors, 1 meter long Sample Reference Ho, A.L. et al. 2021. Accumbens coordinated reset stimulation in mice exhibits ameliorating aftereffects on binge alcohol drinking. Brain Stimulation: 330-334. doi: https://doi.org/10.1016/j.brs.2021.01.015 Technical Specifications - Noldus Device Number: PTLM-001x - Power Supply: 12-24 V DC - Current Consumption: Standby 20 mA - Connector: RJ45 8 pin modular - Input/Output: SDI type 1 - Dimensions: 80 x 45 x 21 mm (l x w x h) (electronics box), 80 x 55 mm (ground plate) - Weight: 200 grams - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Interface: Noldus USB-IO box - Applications: The Lickometer is suitable to measure drinking behavior of both rats and mice. You do not need to change any settings when you switch between species. Install the Lickometer Although the network cables shown in the following schemes are used in networks, the signal coming from the Lickometer is not a network signal. Do not connect the Lickometer via a network hub or similar. Also do not connect the Lickometer to the Mini USB-IO box. Connect the Lickometer Using the USB-IO Box - Make sure that the USB-IO box is connected to (A) your EthoVision computer and (B) a power supply. - Connect the Lickometer to one of the SDI Control ports at the backside of your USB-IO box (either one of the ports 1-12, not port 0), using the black RJ45 cable. The power supply also goes via this cable. When you connect the Lickometer, the red LED at the front of the electronics box blinks. - To attach the Lickometer to a PhenoTyper cage, place the metal ground plate underneath the cage. Important: Make sure that the PhenoTyper cage is on a wooden or synthetic table, not a metal one. A metal table interferes with the capacitance. - Connect the clip to the metal spout of the water bottle. - When the animal touches the spout of the water bottle, the red LED at the front of the electronics box turns on. Working with an Older Lickometer Version The previous version of the Lickometer came with an X-keys USB Switch Interface which is no longer used. To use this older version of the Lickometer in combination with a USB-IO box, you must modify the jumper settings inside the Lickometer electronics box. - Unscrew the cover of the Lickometer. - Locate the jumpers on the board, that is, the pins with the blue covers numbered 1-4. - Make sure that jumper position 1 is open (that is, the two pins are visible) and jumper positions 2, 3, and 4 are closed (the two pins are covered with the blue covers). - Close the cover of the Lickometer. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.1 General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-51-general-information Chapter: PhenoTyper General Information The Lickometer The Noldus Lickometer is a device that measures contact between a rat or mouse and its water bottle. It consists of an electronics box with (A) a metal ground plate and (B) a clip attached to it. Whenever a mouse or a rat contacts the spout of the water bottle, the capacitance between the clip attached to the spout and the metal ground plate changes. This change is detected by the Lickometer. The advantage of this system is that there is no current flow through the animal. The Lickometer is designed as an add-on to the PhenoTyper. To be able to receive information from hardware devices you need the Trial and Hardware Control module. You can control multiple lickometers with EthoVision XT (up to six per USB-IO box). For the limitations, see Control Hardware Devices in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Contents of the Lickometer Package A Lickometer package includes: - A Lickometer PTLM-001x - A black network cable with RJ45 connectors, 1 meter long Sample Reference Ho, A.L. et al. 2021. Accumbens coordinated reset stimulation in mice exhibits ameliorating aftereffects on binge alcohol drinking. Brain Stimulation: 330-334. doi: https://doi.org/10.1016/j.brs.2021.01.015 Technical Specifications - Noldus Device Number: PTLM-001x - Power Supply: 12-24 V DC - Current Consumption: Standby 20 mA - Connector: RJ45 8 pin modular - Input/Output: SDI type 1 - Dimensions: 80 x 45 x 21 mm (l x w x h) (electronics box), 80 x 55 mm (ground plate) - Weight: 200 grams - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Interface: Noldus USB-IO box - Applications: The Lickometer is suitable to measure drinking behavior of both rats and mice. You do not need to change any settings when you switch between species. Install the Lickometer Although the network cables shown in the following schemes are used in networks, the signal coming from the Lickometer is not a network signal. Do not connect the Lickometer via a network hub or similar. Also do not connect the Lickometer to the Mini USB-IO box. Connect the Lickometer Using the USB-IO Box - Make sure that the USB-IO box is connected to (A) your EthoVision computer and (B) a power supply. - Connect the Lickometer to one of the SDI Control ports at the backside of your USB-IO box (either one of the ports 1-12, not port 13), using the black RJ45 cable. The power supply also goes via this cable. When you connect the Lickometer, the red LED at the front of the electronics box blinks. - To attach the Lickometer to a PhenoTyper cage, place the metal ground plate underneath the cage. Important: Make sure that the PhenoTyper cage is on a wooden or synthetic table, not a metal one. A metal table interferes with the capacitance. - Connect the clip to the metal spout of the water bottle. - When the animal touches the spout of the water bottle, the red LED at the front of the electronics box turns on. Working with an Older Lickometer Version The previous version of the Lickometer came with an X-keys USB Switch Interface which is no longer used. To use this older version of the Lickometer in combination with a USB-IO box, you must modify the jumper settings inside the Lickometer electronics box. - Unscrew the cover of the Lickometer. - Locate the jumpers on the board, that is, the pins with the blue covers numbered 1-4. - Make sure that jumper position 1 is open (that is, the two pins are visible) and jumper positions 2, 3 and 4 are closed (the two pins are covered with the blue covers). - Close the cover of the Lickometer. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.3 Work With The Lickometer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-53-work-with-the-lickometer-YUl Chapter: PhenoTyper Work with the Lickometer EthoVision XT - Prepare the Experiment - Make sure that you have followed the instructions in the previous section depending on which interface device you have. - Important: If you start EthoVision XT before the Lickometer set-up is fully connected it may not function properly. Also, if you disconnect and reconnect one of the cables of the Lickometer set-up while the experiment is open, the Lickometer may not function properly. - Start EthoVision XT and create a new experiment or open an existing one. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device: - Noldus USB-IO box. Note: The Lickometer does not work in combination with the Mini USB-IO box. Next, click OK. The Device Configuration window opens. - Do the following depending on which interface device you have: - If you have the USB-IO box: For the SDI Control port to which you connected the Lickometer, select Lickometer (PTLM-001x) as the Device type. In the example below, the Lickometer is connected to SDI Port 1. - If the Lickometers are connected to two or more USB-IO boxes, you must repeat the step above for the Lickometers connected to the remaining interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, in the section covering the USB-IO box and the Mini USB-IO box. EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. If you have only one arena, the hardware is automatically assigned to the arena. You can skip this section. If you have more than one arena, continue with the steps below. - Click the Arena - Hardware mapping button in the Arena Settings window. - Under Device type, you should see Lickometer (PTLM-001x). If that is not the case, click Add device, and under Device type select Lickometer (PTLM-001x). - Accept the default name under Device name or type in a name, for example, Lickometer. - Assign a Lickometer to each arena. To do so, select Lickometer (PTLM-001x) under the name of the arena it belongs to. Do this for all lickometers. Important: Make sure that each physical device is assigned to only one arena. - Click OK to close the Arena - Hardware mapping window. For more information on this step, see Assign devices to arenas in the EthoVision XT - Trial and Hardware Control - Reference Manual. For more information on the Arena Settings, see the section Arena Settings in the EthoVision XT Help. Check That the Lickometer Works Important: Before you start EthoVision XT, make sure that the USB-IO box is connected to (A) your EthoVision computer and (B) a power supply, and that the Lickometer is connected to the USB-IO box. If you start EthoVision XT before the Lickometer set-up is fully connected, it may not function properly. Also, if you disconnect and reconnect one of the cables of the Lickometer set-up while the experiment is open, the Lickometer may not function properly. Use one of the following options to check whether your Lickometer works: Before Running a Trial - Open the Arena Settings in which you have mapped the Lickometers. - In the Arena Settings window, click the Arena - Hardware mapping button. - In the Arena - Hardware mapping window, click the Lickometer under Arena and click Test. - The Test Lickometer window appears. Touch the Lickometer's clip and check the result in the window. Every time you touch the clip, the number of licks and the duration of licks should increase. If you notice unusually high numbers of licks during this test, the Lickometer set-up has been connected after you opened the experiment. To solve this, close and re-open the experiment. Test the Lickometer again. It should now work properly. While a Trial Is Running Check the red and yellow LEDs at the front of the Lickometer's electronics box. - The red LED is on when the animal touches the water bottle spout. - The yellow LED blinks periodically. This indicates that EthoVision XT is requesting information from the Lickometer. After the Trial Has Been Acquired - Export your data in a hardware log. The hardware log gives you an overview of the hardware events that occurred during the trial. - Make a Time Event plot. Acquire the Data EthoVision XT and the Lickometer are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information, see the EthoVision XT Help (F1). Lickometer Data Acquired with the USB-IO Box Every two seconds the USB-IO box collects data from the Lickometer and sends it to EthoVision XT. These time points are marked by a blink of the yellow LED on the electronics box. After each reading, the Lickometer is reset. EthoVision XT counts: - The number of touch events since the last reading. - The cumulative touch duration since the last reading (with a 10 msec resolution). When the USB-IO box/EthoVision requests information (reading events), the Lickometer reports the number of touch events since the last reading and the cumulative touch duration. This information is added to EthoVision XT's hardware log. After each reading, the Lickometer is reset and counting starts from zero. Note: The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also includes some time before the trial start (< 2 s). This time is included in the results. - The data between the last reading event and the stop of the trial is not included in the results. This time is again < 2 s depending on when the trial stopped. In most cases the two discrepancies have no effect on your data when the trial lasts at least a few minutes, as in typical PhenoTyper tests. Tip: If you want a device to have a different sample rate, contact Noldus. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.3 Work With The Lickometer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-53-work-with-the-lickometer Chapter: PhenoTyper Work with the Lickometer EthoVision XT - Prepare the Experiment - Make sure that you have followed the instructions in the previous section depending on which interface device you have. - Important: If you start EthoVision XT before the Lickometer set-up is fully connected it may not function properly. Also, if you disconnect and reconnect one of the cables of the Lickometer set-up while the experiment is open, the Lickometer may not function properly. - Start EthoVision XT and create a new experiment or open an existing one. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device: - Noldus USB-IO box. Note: The Lickometer does not work in combination with the Mini USB-IO box. Next, click OK. The Device Configuration window opens. - Do the following depending on which interface device you have: - If you have the USB-IO box: For the SDI Control port to which you connected the Lickometer, select Lickometer (PTLM-001x) as the Device type. In the example below, the Lickometer is connected to SDI Port 1. - If the Lickometers are connected to two or more USB-IO boxes, you must repeat the step above for the Lickometers connected to the remaining interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in one of the following sections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, depending on which interface device you use: The USB-IO box and the Mini USB-IO box. EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. If you have only one arena, the hardware is automatically assigned to the arena. You can skip this section. If you have more than one arena, do the following: - Click the Arena - Hardware mapping button in the Arena Settings window. - Under Device type, you should see Lickometer (PTLM-001x). If that is not the case, click Add device, and under Device type select Lickometer (PTLM-001x). - Accept the default name under Device name or type in a name, for example, Lickometer. - Assign a Lickometer to each arena. To do so, select Lickometer (PTLM-001x) under the name of the arena it belongs to. Do this for all lickometers. Important: Make sure that each physical device is assigned to only one arena. - Click OK to close the Arena - Hardware mapping window. For more information on this step, see Assign devices to arenas in the EthoVision XT - Trial and Hardware Control - Reference Manual. For more information on the Arena Settings, see the section Arena Settings in the EthoVision XT Help. Check That the Lickometer Works Important: Before you start EthoVision XT, make sure that the USB-IO box is connected to (A) your EthoVision computer and (B) a power supply, and that the Lickometer is connected to the USB-IO box. If you start EthoVision XT before the Lickometer set-up is fully connected, it may not function properly. Also, if you disconnect and reconnect one of the cables of the Lickometer set-up while the experiment is open, the Lickometer may not function properly. Use one of the following options to check whether your Lickometer works: Before Running a Trial - Open the Arena Settings in which you have mapped the Lickometers. - In the Arena Settings window, click the Arena - Hardware mapping button. - In the Arena - Hardware mapping window, click the Lickometer under Arena and click Test. - The Test Lickometer window appears. Touch the Lickometer's clip and check the result in the window. Every time you touch the clip, the number of licks and the duration of licks should increase. If you notice unusually high numbers of licks during this test, the Lickometer set-up has been connected after you opened the experiment. To solve this, close and re-open the experiment. Test the Lickometer again. It should now work properly. While a Trial Is Running Check the red and yellow LEDs at the front of the Lickometer's electronics box. - The red LED is on when the animal touches the water bottle spout. - The yellow LED blinks periodically. This indicates that EthoVision XT requests information from the Lickometer. After the Trial Has Been Acquired - Export your data in a hardware log. The hardware log gives you an overview of the hardware events that occurred during the trial. - Make a Time Event plot. Acquire the Data EthoVision XT and the Lickometer are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information, see the EthoVision XT Help (F1). Lickometer Data Acquired with the USB-IO Box Every two seconds the USB-IO box collects data from the Lickometer and sends it to EthoVision XT. These time points are marked by a blink of the yellow LED on the electronics box. After each reading, the Lickometer is reset. EthoVision XT counts: - The number of touch events since the last reading. - The cumulative touch duration since the last reading (with a 10 msec resolution). When the USB-IO box/EthoVision requests information (reading events), the Lickometer reports the number of touch events since the last reading and the cumulative touch duration. This information is added to EthoVision XT's hardware log. After each reading, the Lickometer is reset and counting starts from zero. Note: The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also includes some time before the trial start (< 2 s). This time is included in the results. - The data between the last reading event and the stop of the trial is not included in the results. This time is again < 2 s depending on when the trial stopped. In most cases the two discrepancies have no effect on your data when the trial lasts at least a few minutes, like in typical PhenoTyper tests. Tip: If you want a device to have a different sample rate, contact Noldus. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.3 Work With The Lickometer (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-53-work-with-the-lickometer-continued-pl3 Chapter: PhenoTyper Work with the Lickometer View the Data in the Hardware Log The hardware log lists the hardware events that occurred during the trial. The feedback signal sent by the Lickometer to EthoVision is Number of licks and Duration of licks. To export a hardware log, choose Analysis > Export > Track Data and under Data to Export select the option Hardware log. - The hardware log provides an example of events recorded during a trial. - The feedback signals recorded include the number of licks and the duration of licks. In the next figure you will find an example of a hardware log with Lickometer data. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.3 Work With The Lickometer (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-53-work-with-the-lickometer-continued Chapter: PhenoTyper Work with the Lickometer View the Data in the Hardware Log The hardware log lists the hardware events that occurred during the trial. The feedback signal sent by the Lickometer to EthoVision is Number of licks and Duration of licks. To export a hardware log, choose Analysis > Export > Track Data and under Data to Export select the option Hardware log. - The hardware log provides an example of Lickometer data collected during a trial. - For further details on hardware devices, refer to the EthoVision XT 18 Trial and Hardware Control Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.4 Calculate The Statistics For The Lickometer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-54-calculate-the-statistics-for-the-lickometer-fmT Chapter: PhenoTyper Calculate the Statistics for the Lickometer Analysis Profile You can create an analysis profile to calculate the number of licks or the duration of licks, or visualize and calculate the time that the number or duration of licks exceeded a specific value. Figure 5.4 Hardware log with the number and duration of licks. The sample time is indicated in column A. The type of data (either number of licks or duration of licks) is marked in column D. The value read at the end of the corresponding sampled interval is shown in column E. Procedure - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware choose one or more of the following options: - Hardware continuous if you want to calculate the total number of licks or the total duration of licks, or visualize the raw data on the timeline. - Hardware state if you want to visualize the time when the number of licks or the duration of licks is higher or lower than a specific threshold. - In the window that opens, next to Device type, select Lickometer (PTLM-001x). - Next to Device, select the device you want to analyze. The names reported here were defined in an earlier step. - Next to Signal, select Number of licks or Duration of licks. - If you select Hardware state, and then Duration of licks as Signal, specify the threshold time in microseconds. For example, 1000000 for one second. - In the Trial Statistics tab, select the statistics you want to calculate. For example: - For a Hardware continuous variable: To calculate the total number of licks (Hardware continuous - Number of licks), select Total if you collected the data with the USB-IO box. - For a Hardware state variable: To calculate the time taken before a certain duration of licks has been reached (Hardware state - Duration of licks > ... seconds), select Latency to First. If you want to calculate the time after the threshold has been reached, select Cumulative Duration. - Click Add. Repeat the procedure from step 1 to add another variable. The Cumulative Value Option The Cumulative value option is available when you choose a variable of type Hardware state. How you use this option depends on which interface system you use between EthoVision XT and the Lickometer. - Select Cumulative value if you want to mark the time that the cumulative value of number (or duration) of licking events has reached a specific threshold. For example, Cumulative value of Duration of licks >= 10000000 (10 seconds). At each sample, the value of cumulative number (or duration) taken from all the previous sampled intervals is compared with the threshold value. - Keep Cumulative value deselected if you want to mark the time that the number (or duration) of licking events has reached a threshold within the sampled interval. For example, to mark the time that the duration of licks exceeded 1 second in each sampled interval of the Lickometer, which lasts two seconds. Statistics and Visualization - Choose Analysis > Results > Statistics & Charts. Select a Data profile and an Analysis profile from the lists on the toolbar and click Calculate. - To visualize the number of licks and their durations, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You can now see in the Time Event Plot when licks took place. Lickometer Data Acquired with the USB-IO Box - First plot: Hardware continuous set to Number of licks. The arrows indicate the first five lick events. These are marked with dots when the variable Hardware continuous (Number of licks) has value 1 in each sampled interval. Because the sampled interval is two seconds, the time distance between two subsequent dots is always two seconds. When there are no lick events, the value of the variable is zero. - Second plot: Hardware continuous set to Duration of licks. Each dot represents the duration of licks in each sampled interval. Because this interval lasts two seconds, the values of lick duration range between zero and two seconds. - Third plot: Hardware state set to mark the time that the Number of licks exceeds five. The option Cumulative was selected in the variable settings. For this reason, the variable is active when Hardware continuous (Number of licks) gets the value 1 for the fifth time. - Fourth plot: Hardware state set to mark the time that Duration of licks >= 4000000 (four seconds), with the option Cumulative selected. This variable becomes active for the first time when the sum of the values of the variable Hardware continuous - Duration of licks exceeds four seconds. The Cumulative option allows summing up the values of duration and comparing the sum with the specified threshold. Tip: If the plots of the Hardware continuous variable appear empty, click Show/Hide > Show Graph Data Points and zoom in on the plot to show the dots larger. Notes To determine the time taken for the number or duration of licks to reach the specified value, re-open the variable settings window in the Analysis profile and in the Statistics tab select the statistic Latency to First. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 5.4 Calculate The Statistics For The Lickometer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-54-calculate-the-statistics-for-the-lickometer Chapter: PhenoTyper Calculate the Statistics for the Lickometer Analysis Profile You can create an analysis profile to calculate the number of licks or the duration of licks, or visualize and calculate the time that the number or duration of licks exceeded a specific value. Figure 5.4 Hardware log with the number and duration of licks. The sample time is indicated in column A. The type of data (either number of licks or duration of licks) is marked in column D. The value read at the end of the corresponding sampled interval is shown in column E. Procedure - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware choose one or more of the following options: - Hardware continuous if you want to calculate the total number of licks or the total duration of licks, or visualize the raw data on the timeline. - Hardware state if you want to visualize the time when the number of licks or the duration of licks is higher or lower than a specific threshold. - In the window that opens, next to Device type, select Lickometer (PTLM-001x). - Next to Device, select the device you want to analyze. The names reported here were defined in an earlier step. - Next to Signal, select Number of licks or Duration of licks. If you select Hardware state, and then Duration of licks as Signal, specify the threshold time in microseconds. For example, 1000000 for one second. - In the Trial Statistics tab, select the statistics you want to calculate. For example: - For a Hardware continuous variable: To calculate the total number of licks (Hardware continuous - Number of licks), select Total if you collected the data with the USB-IO box. - For a Hardware state variable: To calculate the time taken before a certain duration of licks has been reached (Hardware state - Duration of licks > ... seconds), select Latency to First. If you want to calculate the time after the threshold has been reached, select Cumulative Duration. - Click Add. Repeat the procedure from step 1 to add another variable. The Cumulative Value Option The Cumulative value option is available when you choose a variable of type Hardware state. How you use this option depends on which interface system you use between EthoVision XT and the Lickometer. - Select Cumulative value if you want to mark the time that the cumulative value of number (or duration) of licking events has reached a specific threshold. For example, Cumulative value of Duration of licks >= 10000000 (10 seconds). At each sample, the value of cumulative number (or duration) taken from all the previous sampled intervals is compared with the threshold value. - Keep Cumulative value de-selected if you want to mark the time that the number (or duration) of licking events has reached a threshold within the sampled interval. For example, to mark the time that the duration of licks exceeded 1 second in each sampled interval of the Lickometer, which lasts two seconds. Statistics and Visualization - Choose Analysis > Results > Statistics & Charts. Select a Data profile and an Analysis profile from the lists on the toolbar and click Calculate. - To visualize the number of licks and their durations, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You can now see in the Time Event Plot when licks took place. Lickometer Data Acquired with the USB-IO Box - First plot: Hardware continuous set to Number of licks. The arrows indicate the first five lick events. These are marked with dots when the variable Hardware continuous (Number of licks) has value 1 in each sampled interval. Because the sampled interval is two seconds, the time distance between two subsequent dots is always two seconds. When there are no lick events, the value of the variable is zero. - Second plot: Hardware continuous set to Duration of licks. Each dot represents the duration of licks in each sampled interval. Because this interval lasts two seconds, the values of lick duration range between zero and two seconds. - Third plot: Hardware state set to mark the time that the Number of licks exceeds five. The option Cumulative was selected in the variable settings. For this reason, the variable is active when Hardware continuous (Number of licks) gets the value 1 for the fifth time. - Fourth plot: Hardware state set to mark the time that Duration of licks >= 4000000 (four seconds), with the option Cumulative selected. This variable becomes active for the first time when the sum of the values of the variable Hardware continuous - Duration of licks exceeds four seconds. The Cumulative option allows summing up the values of duration and comparing the sum with the specified threshold. Tip: If the plots of the Hardware continuous variable appear empty, click Show/Hide > Show Graph Data Points and zoom in on the plot to show the dots larger. Notes To know the time taken for the number or duration of licks to reach the specified value, in the Analysis profile re-open the variable settings window and in the Statistics tab select the statistic Latency to First. PhenoWheel - 6.1 General Information - 6.2 Install PhenoWheel - 6.3 Work with PhenoWheel - 6.4 Calculate the Statistics for PhenoWheel Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 6.1 General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-61-general-information Chapter: PhenoTyper General Information PhenoWheel Overview PhenoWheel is a PhenoTyper add-on for measuring activity in a running wheel in a PhenoTyper cage. PhenoWheel consists of: - A specially prepared cage wall (type PTC3-RW01) for the PhenoTyper 3000 cage. - A running wheel (type PTRW-0150) with a 15-cm diameter. To use PhenoWheel you also need: - EthoVision XT with the Trial and Hardware Control module. - As interface device: the Noldus USB-IO box. - The PTCN-001x PhenoCount module: - PTCN-0010 for use in combination with the USB-IO box (SDI mode only). - The PhenoTyper 3000 cage for mice. Note: The Med Associates Activity Wheel for rats can be used with the USB-IO box. Working Modes Note: The working modes TTL and SDI specify how data are sent out to EthoVision XT. - TTL mode (default factory mode in PTCN-0011): Each wheel turn results in a TTL pulse being sent to EthoVision XT. - SDI mode: Each wheel turn results in an increase of the internal counter by 1. The current number of turns is read by EthoVision XT at regular intervals. Package Contents - Cage wall (type PTC3-RW01) for PhenoTyper 3000 series. - Running wheel (type PTRW-0150) of diameter 15 cm (5 29/32 inches). - PhenoCount module. - A network cable with RJ45 connectors, 1 meter long. Technical Specifications - Noldus Device Number: PTCN-0011 - Power Supply: 12–24 V DC - Current Consumption: Standby 20 mA - Connectors: - To USB-IO box: RJ45 8-pin modular - To magnetic sensor: Molex 2-pin MiniFit Jr. - Input/Output: SDI type 1, TTL (select by jumpers) - Dimensions: Electronics box 80 x 45 x 21 mm; 3 5/32 x 1 49/64 x 53/64 inches (L x W x H); ground plate 80 x 55 mm; 3 5/32 x 2 11/64 inches - Weight: 200 grams - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Interface: Noldus USB-IO box - Applications: PhenoWheel is suitable to measure running wheel activity in mice. Install PhenoWheel Installation Procedure - If not already done, insert the larger bolt (3) in the white plastic holder (1) with the head at the opposite side of the ball bearing, then place the large washer (4) around the bolt. Attach the white holder to the wheel using the bolts with dome nuts and their washers (2); all four washers should be placed at the inner side of the wheel. The dome nuts should face the inner side of the wheel. Before fixing the wheel to the wall, ensure that the washer with the larger diameter (5) is placed between the holder and the PhenoTyper wall so the wheel can rotate freely. - Mount the running wheel to the wall. Place the plain washer (6), the spring washer (7), and fasten using the wing nut (8) on the outside (back of the PhenoTyper wall), while keeping the large bolt firm using a hexagonal key from the inside. Important: Use limited force when fastening the bolt. - Attach the magnetic sensor (1) to the wall with the small bolt. Adjust the position of the magnetic sensor by rotating it so the magnet on the running wheel (2) passes the outside edge of the sensor. - Connect the magnetic sensor to the PTCN-001x counter module. - Verify that the magnetic sensor is in the correct position relative to the magnet on the running wheel. Rotate the wheel; each time the magnet passes the sensor, the Active LED on the counter should blink. - Follow the next section to connect PhenoCount to the interface device. Note: Although network cables are used in the following connection schemes, the signal from and to the PhenoWheel is not a network signal. Do not connect PhenoWheel via a network hub or similar device. Connect PhenoWheel Through the USB-IO Box - If you have PhenoCount version PTCN-0010, the device only works in SDI mode. You can skip this step. If you have PhenoCount version PTCN-0011, you can set the device to work in TTL mode (default factory mode) or SDI mode. Unscrew the cover of the PhenoCount and locate the jumpers on the board. Adjust the jumpers based on the working mode you have chosen, then close the cover of the PhenoCount module. The PhenoCount version number can be found on the back of the device. - Connect the USB-IO box to EthoVision XT through a USB cable. - If the PhenoCount module is set to TTL mode (default in PTCN-0011), connect the PhenoCount to one of the TTL Control ports on the USB-IO box using a network cable. If the PhenoCount module is set to SDI mode, connect the PhenoCount to one of the SDI Control ports on the USB-IO box using a network cable. Notes - The Read yellow LED indicates when EthoVision XT reads the number of rotations since the last reading event. - For more information on the USB-IO box, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 6.1 General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-61-general-information-qwZ Chapter: PhenoTyper General Information PhenoWheel Overview PhenoWheel is a PhenoTyper add-on for measuring activity in a running wheel in a PhenoTyper cage. PhenoWheel consists of: - A specially prepared cage wall (type PTC3-RW01) for the PhenoTyper 3000 cage. - A running wheel (type PTRW-0150) with a 15-cm diameter. To use PhenoWheel you also need: - EthoVision XT with the Trial and Hardware Control module. - As interface device: the Noldus USB-IO box. - The PTCN-001x PhenoCount module: - PTCN-0010 for use in combination with the USB-IO box (SDI mode only). - The PhenoTyper 3000 cage for mice. Note: The Med Associates Activity Wheel for rats can be used with the USB-IO box. Working Modes Note: The working modes TTL and SDI specify how data are sent out to EthoVision XT. - TTL mode (default factory mode in PTCN-0011): Each wheel turn results in a TTL pulse being sent to EthoVision XT. - SDI mode: Each wheel turn results in an increase of the internal counter by 1. The current number of turns is read by EthoVision XT at regular intervals. Package Contents - Cage wall (type PTC3-RW01) for PhenoTyper 3000 series. - Running wheel (type PTRW-0150) of diameter 15 cm (5 29/32 inches). - PhenoCount module. - A network cable with RJ45 connectors, 1 meter long. Technical Specifications - Noldus device number: PTCN-0011 - Power supply: 12–24 V DC - Current consumption: Standby 20 mA - Connectors: - To USB-IO box: RJ45 8 pin modular - To magnetic sensor: Molex 2 pin MiniFit Jr. - Input/output: SDI type 1, TTL (select by jumpers) - Dimensions: Electronics box 80 x 45 x 21 mm; 3 5/32 x 1 49/64 x 53/64 inches (l x w x h), ground plate 80 x 55 mm; 3 5/32 x 2 11/64 inches - Weight: 200 grams - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Interface: Noldus USB-IO box - Applications: PhenoWheel is suitable to measure running wheel activity in mice. Install PhenoWheel Installation Procedure - If not already done, insert the larger bolt (3) in the white plastic holder (1) with the head at the opposite side of the ball bearing, then place the large washer (4) around the bolt. Attach the white holder to the wheel using the bolts with dome nuts and their washers (2); all four washers should be placed at the inner side of the wheel. The dome nuts should face the inner side of the wheel. Before fixing the wheel to the wall, ensure that the washer with the larger diameter (5) is placed between the holder and the PhenoTyper wall so the wheel can rotate freely. - Mount the running wheel to the wall; place the plain washer (6), the spring washer (7), and finally fasten using the wing nut (8) on the outside (back of the PhenoTyper wall), while keeping the large bolt firm using a hexagonal key from the inside. Important: Use limited force when fastening the bolt. - Attach the magnetic sensor (1) to the wall with the small bolt. Adjust the position of the magnetic sensor by rotating it so the magnet on the running wheel (2) passes the outside edge of the sensor. - Connect the magnetic sensor to the PTCN-001x counter module. - Verify that the magnetic sensor is in the correct position relative to the magnet on the running wheel. Rotate the wheel; each time the magnet passes the sensor, the Active LED on the counter should blink. - Follow the next section to connect PhenoCount to the interface device. Note: Although network cables are used in the following connection schemes, the signal from and to the PhenoWheel is not a network signal. Do not connect PhenoWheel via a network hub or similar device. Connect PhenoWheel Through the USB-IO Box - If you have PhenoCount version PTCN-0010, the device only works in SDI mode — you can skip this step. If you have PhenoCount version PTCN-0011, you can set the device to TTL mode (default factory mode) or SDI mode. Unscrew the cover of the PhenoCount and locate the jumpers on the board. Adjust the jumpers based on the working mode you have chosen, then close the cover of the PhenoCount module. The PhenoCount version number can be found on the back of the device. - Connect the USB-IO box to EthoVision XT through a USB cable. - If the PhenoCount module is set to TTL mode (default in PTCN-0011), connect the PhenoCount to one of the TTL Control ports on the USB-IO box using a network cable. If the PhenoCount module is set to SDI mode, connect the PhenoCount to one of the SDI Control ports on the USB-IO box using a network cable. Notes - The Read yellow LED indicates when EthoVision XT reads the number of rotations since the last reading event. - For more information on the USB-IO box, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 6.3 Work With Phenowheel URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-63-work-with-phenowheel Chapter: PhenoTyper Work with PhenoWheel EthoVision XT - Prepare the Experiment - Make sure that you have followed the instructions in the previous section. Also, make sure all devices are powered up. - Start EthoVision XT and create a new experiment or open an existing one. Important: Do not disconnect PhenoWheel while the experiment is open. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose Noldus USB-IO box. Next, click OK. The Device Configuration window opens. - Do the following depending on which interface device you have: - If you have the USB-IO box: For the SDI Control port to which you connected the PhenoCount module, select PhenoWheel as the Device type. In the example below, the PhenoWheel is connected to SDI Port 1. - If the PhenoWheels are connected to two or more USB-IO boxes, you must repeat the step above for the PhenoWheels connected to the remaining interface devices. To do so, from the IO Interface list in the Device Configuration window select a new USB-IO box, then repeat the previous step. - When ready, click OK. For more information, see Setting the port connections in the chapter The USB-IO box and the Mini USB-IO box in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. EthoVision XT - Arena Settings We assume that you have drawn the arenas and the zones in the Arena Settings. If you have only one arena, the hardware is automatically assigned to the arena. You can skip this section. If you have more than one arena, follow the steps below: - Click the Arena - Hardware mapping button in the Arena Settings window. - Under Device type, you should see one row with PhenoWheel/PhenoWheel (60). If that is not the case, click Add device, and under Device type select PhenoWheel/PhenoWheel (60). - Under Device name, accept the default name or type in a name, for example, PhenoWheel. - Assign one PhenoWheel device to each arena. To do so, select the physical device PhenoWheel [n] under the name of the arena it belongs to. For example: - PhenoWheel 1 for Arena 1 - PhenoWheel 2 for Arena 2 Do this for all PhenoWheels. Important: Make sure that each physical device is assigned to only one arena. - To test the counter, click PhenoWheel in one of the Arena columns and then click the Test button. When you rotate that running wheel, the number of cycles is displayed under Value. Note that this number is read out at regular intervals of 60 seconds. - Click OK and repeat the previous step for the remaining wheels. - Click OK to close the Arena - Hardware mapping window. Acquire the Data EthoVision XT and PhenoWheel are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information: - PhenoTyper - EthoVision XT 18 - Reference Manual - EthoVision XT Help (F1) PhenoWheel Data Acquired with the USB-IO Box The way data are collected depends on whether the PhenoCount module is set to work as a SDI device (standard in PTCN-0010) or as a TTL device (optional in PTCN-0011). If the PhenoCount module is set to SDI mode, it sends data to EthoVision XT every 60 seconds. At each sample time, EthoVision XT counts the number of rotations since the last reading event. The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also includes some time before the trial start. This time (< 60 s) is included in the results. - The data between the last reading event and the stop of the trial is not included in the results. This time is again < 60 s depending on when the trial stopped. In most cases the two discrepancies have no effect on your data in long trials, for example a few hours trial. Tip: If you require to work with devices with a different sampling rate, contact Noldus. If the PhenoCount module is set to TTL mode, wheel rotations are detected as TTL pulses in real time, not at regular intervals. Data are treated the same way as in other TTL devices (e.g. the Pellet dispenser). Calculate the Statistics for PhenoWheel Analysis Profile You can create an analysis profile to calculate the number of rotations. - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, click Hardware continuous. - In the Hardware Continuous window, next to Device type, select PhenoWheel (60). - Next to Device, select the correct device name, if you have more than one connected. - Next to Signal, select Number of cycles. - In the Trial Statistics tab, select Total. - Click Add. Statistics and Visualization - To calculate the statistics for wheel data, choose Analysis > Results > Statistics & Charts. - Select the correct Data profile and Analysis profile from the lists on the toolbar and click Calculate. - To visualize the number of rotations, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You will now see in the Time Event Plot when rotations took place. PhenoWheel Data Acquired with the USB-IO Box (SDI Mode) - Hardware continuous set to Number of cycles: A dot appears every time the counter is read out and the height of the dot indicates the number of rotations during the past interval. - Hardware state set to mark the time that the Number of cycles exceeds a specific value. The option Cumulative must be selected in the variable settings. PhenoWheel Data Acquired with the USB-IO Box (TTL Mode) A dot appears every time a rotation event is detected. Because the signal conveys information about a single rotation, the vertical axis shows 1 at every rotation. Note: The TTL mode of the USB-IO box is only possible in PTCN-0011 or later versions. - Hardware continuous set to Number of cycles: The rotations can occur at any sample time, not at regular intervals as is the case for PhenoWheel data collected with the USB-IO box in SDI mode. The moment that the magnet passes the sensor is scored as 1. The rest is scored as zero. - Hardware state set to mark the time that the Number of cycles exceeds a specific threshold. The option Cumulative value is selected in the variable settings. Note: If the plots of the Hardware continuous variable appear empty, that is because the data are shown as small dots. Click Show/Hide > Show Graph Data Points and zoom in the plot to show the dots larger. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 6.3 Work With Phenowheel URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-63-work-with-phenowheel-SIQ Chapter: PhenoTyper Work with PhenoWheel EthoVision XT - Prepare the Experiment - Make sure that you have followed the instructions in the previous section. Also, make sure all devices are powered up. - Start EthoVision XT and create a new experiment or open an existing one. Important: Do not disconnect PhenoWheel while the experiment is open. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose Noldus USB-IO box. Next, click OK. The Device Configuration window opens. - Do the following depending on which interface device you have: - If you have the USB-IO box: For the SDI Control port to which you connected the PhenoCount module, select PhenoWheel as the Device type. In the example below, the PhenoWheel is connected to SDI Port 1. - If the PhenoWheels are connected to two or more USB-IO boxes, you must repeat the step above for the PhenoWheels connected to the remaining interface devices. To do so, from the IO Interface list in the Device Configuration window select a new USB-IO box, then repeat the previous step. - When ready, click OK. For more information, see Setting the port connections in the chapter The USB-IO box and the Mini USB-IO box in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. EthoVision XT - Arena Settings We assume that you have drawn the arenas and the zones in the Arena Settings. If you have only one arena, the hardware is automatically assigned to the arena. You can skip this section. If you have more than one arena, follow the steps below: - Click the Arena - Hardware mapping button in the Arena Settings window. - Under Device type, you should see one row with PhenoWheel/PhenoWheel (60). If that is not the case, click Add device, and under Device type select PhenoWheel/PhenoWheel (60). - Under Device name, accept the default name or type in a name, for example, PhenoWheel. - Assign one PhenoWheel device to each arena. To do so, select the physical device PhenoWheel [n] under the name of the arena it belongs to. For example: - PhenoWheel 1 for Arena 1 - PhenoWheel 2 for Arena 2 Do this for all PhenoWheels. Important: Make sure that each physical device is assigned to only one arena. - To test the counter, click PhenoWheel in one of the Arena columns and then click the Test button. When you rotate that running wheel, the number of cycles is displayed under Value. Note that this number is read out at regular intervals of 60 seconds. - Click OK and repeat the previous step for the remaining wheels. - Click OK to close the Arena - Hardware mapping window. Acquire the Data EthoVision XT and PhenoWheel are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information: - PhenoTyper - EthoVision XT 18 - Reference Manual - EthoVision XT Help (F1) PhenoWheel Data Acquired with the USB-IO Box The way data are collected depends on whether the PhenoCount module is set to work as a SDI device (standard in PTCN-0010) or as a TTL device (optional in PTCN-0011). If the PhenoCount module is set to SDI mode, it sends data to EthoVision XT every 60 seconds. At each sample time, EthoVision XT counts the number of rotations since the last reading event. The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also includes some time before the trial start. This time (< 60 s) is included in the results. - The data between the last reading event and the stop of the trial is not included in the results. This time is again < 60 s depending on when the trial stopped. In most cases the two discrepancies have no effect on your data in long trials, for example a few hours trial. Tip: If you require to work with devices with a different sampling rate, contact Noldus. If the PhenoCount module is set to TTL mode, wheel rotations are detected as TTL pulses in real time, not at regular intervals. Data are treated the same way as in other TTL devices (e.g. the Pellet dispenser). Calculate the Statistics for PhenoWheel Analysis Profile You can create an analysis profile to calculate the number of rotations. - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, click Hardware continuous. - In the Hardware Continuous window, next to Device type, select PhenoWheel (60). - Next to Device, select the correct device name, if you have more than one connected. - Next to Signal, select Number of cycles. - In the Trial Statistics tab, select Total. - Click Add. Statistics and Visualization - To calculate the statistics for wheel data, choose Analysis > Results > Statistics & Charts. - Select the correct Data profile and Analysis profile from the lists on the toolbar and click Calculate. - To visualize the number of rotations, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You now see in the Time Event Plot when rotations took place. PhenoWheel Data Acquired with the USB-IO Box (SDI Mode) - Hardware continuous set to Number of cycles: A dot appears every time the counter is read out and the height of the dot indicates the number of rotations during the past interval. - Hardware state set to mark the time that the Number of cycles exceeds a specific value. The option Cumulative must be selected in the variable settings. PhenoWheel Data Acquired with the USB-IO Box (TTL Mode) A dot appears every time a rotation event is detected. Because the signal conveys information about a single rotation, the vertical axis shows 1 at every rotation. Note: The TTL mode of the USB-IO box is only possible in PTCN-0011 or later versions. - Hardware continuous set to Number of cycles: The rotations can occur at any sample time, not at regular intervals as is the case for PhenoWheel data collected with the USB-IO box in SDI mode. The moment that the magnet passes the sensor is scored as 1. The rest is scored as zero. - Hardware state set to mark the time that the Number of cycles exceeds a specific threshold. The option Cumulative value is selected in the variable settings. Notes If the plots of the Hardware continuous variable appear empty, that is because the data are shown as small dots. Click Show/Hide > Show Graph Data Points and zoom in the plot to show the dots larger. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 7.3 Work With The Feeding Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-73-work-with-the-feeding-monitor Chapter: PhenoTyper Work with the Feeding Monitor EthoVision XT - Prepare the Experiment - Connect the USB-IO box / Mini USB-IO box to the EthoVision XT computer and make sure that all devices are powered up, as described in the previous section. For details about the USB-IO box and the Mini USB-IO box, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Start EthoVision XT and create a new experiment or open an existing one. Important: Do not disconnect the IR Beam Controller while the experiment is open. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device you have: - Noldus USB-IO box - Noldus Mini USB-IO box Next, click OK. The Device Configuration window opens. - For the TTL Control port which you connected the Feeding Monitor to, select Beam Controller (PTBC-001x) as the Device/Device type. If you work with the USB-IO box, the Device ID (third column) changes to Beam Controller (PTBC-001x) 1. Repeat this step for each Feeding Monitor connected. - If you have multiple Feeding Monitors connected to two or more USB-IO boxes, from the IO Interface list select a USB-IO box. Repeat this and the next step for each USB-IO box. - If your Feeding Monitors are connected to two or more USB-IO boxes, you must repeat the step above for those connected to the remaining USB-IO boxes. From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in one of the following chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, depending on which interface you use: The USB-IO box and the Mini USB-IO box. EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. - If you have only one arena, the hardware is automatically assigned to the arena. Skip the following steps. - If you have more than one arena, continue with the steps below. - Click the Arena - Hardware mapping button in the Arena Settings window. Note: The IR Beam Controller box can control two sensors. However, two sensors connected to the same IR Beam Controller box can only be used in the same arena in EthoVision XT. - Under Device type, you should see Beam Controller. If that is not the case, click Add device, and under Device type, select Beam Controller (PTBC-001x). - Under Device name, accept the default name or type in a name, for example, Feeding monitor. - Assign a Beam Controller (PTBC-001x) to each arena. To do so, select the physical device Beam Controller (PTBC-001x) [n] under the name of the arena it belongs to. For example: - Beam Controller 1 for Arena 1 - Beam Controller 2 for Arena 2 Do this for all Feeding Monitors. Important: Make sure that each physical device is assigned to only one arena. - To test the Feeding Monitor: - Click Beam Controller (PTBC-001x) in one of the Arena columns. - Click the Test button. - Locate the corresponding Feeding Monitor and put a finger at the other side of the feeder (that is, the inner side of the cage wall) to interrupt the beam. This simulates a feeding event. - The value next to is beam broken? becomes true and the number of beam breaks is displayed under Value. If you have a LED connected to the IR Food Sensor, you can test it by selecting Cue on from the Command list. - Click OK to close the Arena - Hardware mapping window. Acquire the Data EthoVision XT and the Feeding Monitor are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information, see the PhenoTyper - EthoVision XT 18 - Reference Manual and the EthoVision XT Help (F1). Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 7.3 Work With The Feeding Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-73-work-with-the-feeding-monitor-kXG Chapter: PhenoTyper Work with the Feeding Monitor EthoVision XT - Prepare the Experiment - Connect the USB-IO box / Mini USB-IO box to the EthoVision XT computer and make sure that all devices are powered up, as described in the previous section. For details about the USB-IO box and the Mini USB-IO box, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Start EthoVision XT and create a new experiment or open an existing one. Important: Do not disconnect the IR Beam Controller while the experiment is open. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device you have: - Noldus USB-IO box - Noldus Mini USB-IO box Next, click OK. The Device Configuration window opens. - For the TTL Control port which you connected the Feeding Monitor to, select Beam Controller (PTBC-001x) as the Device/Device type. If you work with the USB-IO box, the Device ID (third column) changes to Beam Controller (PTBC-001x) 1. Repeat this step for each Feeding Monitor connected. - If you have multiple Feeding Monitors connected to two or more USB-IO boxes, from the IO Interface list select a USB-IO box. Repeat this and the next step for each USB-IO box. - If your Feeding Monitors are connected to two or more USB-IO boxes, you must repeat the step above for those connected to the remaining USB-IO boxes. From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in one of the following chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, depending on which interface you use: The USB-IO box and the Mini USB-IO box. EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. - If you have only one arena, the hardware is automatically assigned to the arena. Skip the following steps. - If you have more than one arena, continue with the steps below. - Click the Arena - Hardware mapping button in the Arena Settings window. Note: The IR Beam Controller box can control two sensors. However, two sensors connected to the same IR Beam Controller box can only be used in the same arena in EthoVision XT. - Under Device type, you should see Beam Controller. If that is not the case, click Add device, and under Device type, select Beam Controller (PTBC-001x). - Under Device name, accept the default name or type in a name, for example, Feeding monitor. - Assign a Beam Controller (PTBC-001x) to each arena. To do so, select the physical device Beam Controller (PTBC-001x) [n] under the name of the arena it belongs to. For example: - Beam Controller 1 for Arena 1 - Beam Controller 2 for Arena 2 Do this for all Feeding Monitors. Important: Make sure that each physical device is assigned to only one arena. - To test the Feeding Monitor: - Click Beam Controller (PTBC-001x) in one of the Arena columns. - Click the Test button. - Locate the corresponding Feeding Monitor and put a finger at the other side of the feeder (that is, the inner side of the cage wall) to interrupt the beam. This simulates a feeding event. - The value next to is beam broken? becomes true and the number of beam breaks is displayed under Value. If you have a LED connected to the IR Food Sensor, you can test it by selecting Cue on from the Command list. - Click OK to close the Arena - Hardware mapping window. Acquire the Data EthoVision XT and the Feeding Monitor are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information, see the PhenoTyper - EthoVision XT 18 - Reference Manual and the EthoVision XT Help (F1). Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 8.2 Install The Ttl To 28V Interface URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-82-install-the-ttl-to-28v-interface Chapter: PhenoTyper Install the TTL to 28V Interface Connect the TTL to 28V Interface Using the USB-IO Box / Mini USB-IO Box - Connect a 28-V power supply to the 28V supply-in connection on the TTL to 28V Interface. Either use a 28-V power supply or the Noldus 28-V power supply (Noldus type number: MAPS-0010). - Connect the USB-IO box connection on the TTL to 28V Interface to one of the TTL Control ports on the USB-IO box / Mini USB-IO box, using the supplied network cable. - Connect the Med Associates or third-party device to the output 28V port 1 or 2. Notes: - The green LED light indicates whether a TTL signal is sent from EthoVision XT. - An extension cable (Noldus type number: MACA-0201) is available if you need to increase the distance between the TTL Interface and the device. - USB-IO TTL control and power are fully optically isolated from the 28-Volt Med Associates power and control circuit to prevent any unwanted interaction. Using Multiple TTL to 28V Interfaces You can use multiple TTL to 28V Interfaces with only one 28-V power supply. For this purpose, feed through the power from one of the 28V supply in/out ports on one TTL Interface to one of the 28V supply in/out ports on the next TTL Interface, using the power feed-through cable (Noldus type number: MACA-0101). It does not matter which 28V supply in/out port you use to connect the two boxes; either the one at the top or the one at the bottom is fine. You can also use this solution to connect multiple light sources of the Top Light Unit of DanioVision. For details, see the DanioVision DVOC-0041 Reference Manual. Important: Make sure not to exceed the maximum current output (0.9 A) of the Noldus 28-V power supply. Check the technical specifications of the devices you connect. Inverted Operation If needed, you can invert the output level of the controlled device by changing jumper settings inside the TTL to 28V Interface. This is useful, for example, when you want to change the default position of the doors of the radial arm maze to 'open' instead of 'closed'. - Open the box by pushing the left and right sides a few millimeters in the direction of the red arrow to release the "click system" of the printed cover. Simultaneously, carefully slide the cover in the direction of the white arrow. - Lift the jumper and change the position (A or B) to set the control to inverted/not inverted. JMPR1 does this for device 1, JMPR2 does this for device 2. Technical Specifications - Noldus Type Number: PTMA-001x - Power Requirements: 12 to 20 VDC supplied by USB-IO box; External 28 VDC power supply - Current Consumption: 40 mA without device connected - Weight: ± 100 g (3.5 oz) - Operating Temperature: 10 °C to 35 °C (50 °F to 95 °F) - Storage Temperature: -40 °C to 65 °C (-40 °F to 149 °F) - Relative Humidity (Max.): 20% to 80% (non-condensing) Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - 8.2 Install The Ttl To 28V Interface URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-82-install-the-ttl-to-28v-interface-Oi4 Chapter: PhenoTyper Install the TTL to 28V Interface Connect the TTL to 28V Interface Using the USB-IO Box / Mini USB-IO Box - Connect a 28-V power supply to the 28V supply-in connection on the TTL to 28V Interface. Either use a 28-V power supply or the Noldus 28-V power supply (Noldus type number: MAPS-0010). - Connect the USB-IO box connection on the TTL to 28V Interface to one of the TTL Control ports on the USB-IO box / Mini USB-IO box, using the supplied network cable. - Connect the Med Associates or third-party device to the output 28V port 1 or 2. Notes: - The green LED light indicates whether a TTL signal is sent from EthoVision XT. - An extension cable (Noldus type number: MACA-0201) is available if you need to increase the distance between the TTL Interface and the device. - USB-IO TTL control and power are fully optically isolated from the 28-Volt Med Associates power and control circuit to prevent any unwanted interaction. Using Multiple TTL to 28V Interfaces You can use multiple TTL to 28V Interfaces with only one 28-V power supply. For this purpose, feed through the power from one of the 28V supply in/out ports on one TTL Interface to one of the 28V supply in/out ports on the next TTL Interface, using the power feed-through cable (Noldus type number: MACA-0101). It does not matter which 28V supply in/out port you use to connect the two boxes; either the top or the bottom port is fine. You can also use this solution to connect multiple light sources of the Top Light Unit of DanioVision. For details, see the DanioVision DVOC-0041 - Reference Manual. Important: Make sure not to exceed the maximum current output (0.9 A) of the Noldus 28-V power supply. Check the technical specifications of the devices you connect. Inverted Operation If needed, you can invert the output level of the controlled device by changing jumper settings inside the TTL to 28V Interface. This is useful, for example, when you want to change the default position of the doors of the radial arm maze to 'open' instead of 'closed'. - Open the box by pushing the left and right sides a few millimeters in the direction of the red arrow to release the click system of the printed cover. Simultaneously, carefully slide the cover in the direction of the white arrow. - Lift the jumper and change the position (A or B) to set the control to inverted or not inverted. JMPR1 does this for device 1; JMPR2 does this for device 2. Technical Specifications - Noldus Type Number: PTMA-001x - Power Requirements: 12 to 20 VDC supplied by USB-IO box; external 28 VDC power supply - Current Consumption: 40 mA without device connected - Weight: ±100 g (3.5 oz) - Operating Temperature: 10 °C to 35 °C (50 °F to 95 °F) - Storage Temperature: -40 °C to 65 °C (-40 °F to 149 °F) - Relative Humidity (Max.): 20% to 80% (non-condensing) Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-dispenser Chapter: PhenoTyper Analysis Profile You can create an analysis profile to calculate the number of pellets dropped. Procedure - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, click one or more of the following: - Hardware Continuous or Hardware Command if you want to calculate the total number of pellet drops, or visualize the pellet drops on a timeline. - Hardware State if you want to visualize and calculate when the number of pellets dropped exceeded a certain number. - Whatever option you choose, next to Device Type, select Pellet Dispenser (PTPD-001x). Next to Device, select the correct device if you have more than one pellet dispenser connected. - In the Trial Statistics tab, select the statistic Total. - Click Add. Repeat the steps from step 2 to add more variables. Analysis Profile with the Pellet Receptacle In the Analysis Profile: - To calculate the total number of pellet drops, or visualize the nose pokes on a timeline, under Hardware choose Hardware Continuous. Choose the device you want to extract the data from. - To calculate the total duration of nose pokes, or the time that the number of nose pokes was lower or higher than a certain value, under Hardware choose Hardware State. Choose the device you want to extract the data from. Next to Signal, choose what you want to calculate. Choose Is nose poke detected = true to calculate the total nose poke time. Statistics and Visualization - Choose Analysis > Results > Statistics & Charts. Select the correct Data Profile and Analysis Profile from the lists on the toolbar and click Calculate. - To visualize the pellet drops or nose pokes on a timeline, choose Analysis > Results > Integrated Visualization. Select the correct Analysis Profile from the list on the toolbar. You will now see in the Time Event Plot when pellets were dropped. In the figure below, from top to bottom: Hardware Command, Hardware Continuous (see also the inset when zooming in the timeline), Hardware State which was set to Number of drops >= 5, with Cumulative selected. Tip: For a clearer view of the data points, click Show/Hide > Show Graph Data Points. Pellet Receptacle The example below shows the visualization of a Hardware Continuous and a Hardware State. The first plot shows Hardware Continuous, where the onset of nose pokes are plotted on the timeline. The second plot shows the time that a nose poke occurred. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-dispenser-QYX Chapter: PhenoTyper Analysis Profile You can create an analysis profile to calculate the number of pellets dropped. Procedure - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, click one or more of the following: - Hardware Continuous or Hardware Command if you want to calculate the total number of pellet drops, or visualize the pellet drops on a timeline. - Hardware State if you want to visualize and calculate when the number of pellets dropped exceeded a certain number. - Whatever option you choose, next to Device Type, select Pellet Dispenser (PTPD-001x). Next to Device, select the correct device if you have more than one pellet dispenser connected. - In the Trial Statistics tab, select the statistic Total. - Click Add. Repeat the steps from step 2 to add more variables. Analysis Profile with the Pellet Receptacle In the Analysis profile: - To calculate the total number of pellet drops, or visualize the nose pokes on a timeline, under Hardware choose Hardware Continuous. Choose the device you want to extract the data from. - To calculate the total duration of nose pokes, or the time that the number of nose pokes was lower or higher than a certain value, under Hardware choose Hardware State. Choose the device you want to extract the data from. Next to Signal, choose what you want to calculate. Choose Is nose poke detected = true to calculate the total nose poke time. Statistics and Visualization - Choose Analysis > Results > Statistics & Charts. Select the correct Data Profile and Analysis Profile from the lists on the toolbar and click Calculate. - To visualize the pellet drops or nose pokes on a timeline, choose Analysis > Results > Integrated Visualization. Select the correct Analysis Profile from the list on the toolbar. You will now see in the Time Event Plot when pellets were dropped. In the figure below, from top to bottom: Hardware Command, Hardware Continuous (see also the inset when zooming in the timeline), Hardware State which was set to Number of drops >= 5, with Cumulative selected. Tip: For a clearer view of the data points, click Show/Hide > Show Graph Data Points. Pellet Receptacle The example below shows the visualization of a Hardware Continuous and a Hardware State: - First plot: Hardware Continuous. The onset of nose pokes are plotted on the timeline. - Second plot: Time that a nose poke occurred. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-introduction Chapter: PhenoTyper About This Manual When You Need This Manual This manual is intended for users of PhenoTyper and Noldus trainers and support who need more technical information about the functioning of PhenoTyper and its accessories than is covered in the PhenoTyper - EthoVision XT 18 - Reference Manual. Check regularly the Noldus download page at my.noldus.com for the most recent version of this manual. Using This Manual Some information in this manual may or may not apply to your setup depending on the devices you work with. - For PhenoTyper 1 (analog camera): All chapters apply. - For PhenoTyper 2 (digital camera): All chapters except The Top Unit Interface apply. - For the USB-IO box: All chapters apply. Other Documentation Manuals You can find the following manuals on your computer after you have installed EthoVision XT. From the Windows Start menu, select All Apps > Noldus > EthoVision XT 18 Other Documentation. - The EthoVision XT Help (press F1 to open it in EthoVision XT). This browser-based Help contains extensive information about EthoVision XT. - The PhenoTyper - EthoVision XT 18 - Reference Manual. For how to assemble PhenoTyper, design experiments and analyze data in EthoVision XT. - The EthoVision XT 18 - Quick Start Guide - English. A small manual with a summary on how to use EthoVision XT. This is also available in several different languages. - The EthoVision XT 18 - Application Manual. This manual contains information about different standard tests, including conditioning tests carried out with PhenoTyper. - The EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Open this manual if you are looking for information about the USB-IO box and the TTL tester, or you want to know more about complex Trial Control protocols. You can also find the manuals on the downloads section of the Noldus web site my.noldus.com. Sample Experiments You can find examples of applications with PhenoTypers in the EthoVision XT sample experiments that you can download from my.noldus.com. Note that you have to log in or register first. Next, choose Downloads > EthoVision XT > Sample Experiments. Technical Support Help Desk If you run into problems of any kind, please let us know. You can contact us via our web site my.noldus.com. Please check this manual carefully before contacting Noldus. Send Your Data If you need to send EthoVision XT data by e-mail, please use the Backup procedure (File > Make Backup) to make a copy of your experiments, and send them as attachments. For more information on how to use the Backup and Restore functions, see the EthoVision XT Help. Replacement of Components If any component breaks or wears out, please contact our Technical Support Department to have it sent back to us. Please note that in any case you must send it to our international headquarters (Wageningen, The Netherlands) no matter where you are. Broken components will be fixed or replaced with new ones. Important: Plastic components (such as the cage walls) will only be replaced or repaired free of charge if they are broken due to a defect of workmanship and the damage is reported within one month of shipment. Other components are covered by a one year guarantee; to claim under guarantee you must report the damage within one year of shipment. It is possible that you may have a service contract entitling you to free replacement of parts for a longer period; please contact the support department if you are not sure. In any case we can still fix or replace the parts, but it may be necessary to levy a charge. The guarantee is only valid if you treat the PhenoTyper as described in this manual. In any case, shipping broken parts is at your expenses, while sending repaired or replacing parts back to you will be at our expenses. Important: If you connect the PhenoTyper to any third-party products, such as a video tracking system other than EthoVision XT, Noldus Information Technology is not responsible for maintenance of that product, or for damage done to the PhenoTyper by that product. To order spare parts of PhenoTyper, see Appendix A of the PhenoTyper - EthoVision XT 18 - Reference Manual. There you find a list of the parts available. Please contact your Noldus representative to send your order. The PhenoTyper Camera PhenoTyper 1 (Analog Camera) The camera is integrated in the PhenoTyper 1 Top Unit. PhenoTyper 2 (Digital Camera) The camera is mounted on the TopPlate of PhenoTyper 2. For issues related to the camera image, see Troubleshooting in the EthoVision XT Help. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-introduction-B0s Chapter: PhenoTyper About This Manual When You Need This Manual This manual is intended for users of PhenoTyper and Noldus trainers and support who need more technical information about the functioning of PhenoTyper and its accessories than is covered in the PhenoTyper - EthoVision XT 18 - Reference Manual. Check regularly the Noldus download page at my.noldus.com for the most recent version of this manual. Using This Manual Some information in this manual may or may not apply to your setup depending on the devices you work with. - For PhenoTyper 1 (analog camera): All chapters apply. - For PhenoTyper 2 (digital camera): All chapters except The Top Unit Interface apply. - For the USB-IO box: All chapters apply. Other Documentation Manuals You can find the following manuals on your computer after you have installed EthoVision XT. From the Windows Start menu, select All Apps > Noldus > EthoVision XT 18 Other Documentation. - The EthoVision XT Help (press F1 to open it in EthoVision XT). This browser-based Help contains extensive information about EthoVision XT. - The PhenoTyper - EthoVision XT 18 - Reference Manual. For how to assemble PhenoTyper, design experiments and analyze data in EthoVision XT. - The EthoVision XT 18 - Quick Start Guide - English. A small manual with a summary on how to use EthoVision XT. This is also available in several different languages. - The EthoVision XT 18 - Application Manual. This manual contains information about different standard tests, including conditioning tests carried out with PhenoTyper. - The EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Open this manual if you are looking for information about the USB-IO box and the TTL tester, or you want to know more about complex Trial Control protocols. You can also find the manuals on the downloads section of the Noldus web site my.noldus.com. Sample Experiments You can find examples of applications with PhenoTypers in the EthoVision XT sample experiments that you can download from my.noldus.com. Note that you have to log in or register first. Next, choose Downloads > EthoVision XT > Sample Experiments. Technical Support Help Desk If you run into problems of any kind, please let us know. You can contact us via our web site my.noldus.com. Please check this manual carefully before contacting Noldus. Send Your Data If you need to send EthoVision XT data by e-mail, please use the Backup procedure (File > Make Backup) to make a copy of your experiments, and send them as attachments. For more information on how to use the Backup and Restore functions, see the EthoVision XT Help. Replacement of Components If any component breaks or wears out, please contact our Technical Support Department to have it sent back to us. Please note that in any case you must send it to our international headquarters (Wageningen, The Netherlands) no matter where you are. Broken components will be fixed or replaced with new ones. Important: Plastic components (such as the cage walls) will only be replaced or repaired free of charge if they are broken due to a defect of workmanship and the damage is reported within one month of shipment. Other components are covered by a one year guarantee; to claim under guarantee you must report the damage within one year of shipment. It is possible that you may have a service contract entitling you to free replacement of parts for a longer period, please contact the support department if you are not sure. In any case we can still fix or replace the parts, but it may be necessary to levy a charge. The guarantee is only valid if you treat the PhenoTyper as described in this manual. In any case, shipping broken parts is at your expenses, while sending repaired or replacing parts back to you will be at our expenses. Important: If you connect the PhenoTyper to any third-party products, such as a video tracking system other than EthoVision XT, Noldus Information Technology is not responsible for maintenance of that product, or for damage done to the PhenoTyper by that product. To order spare parts of PhenoTyper, see Appendix A of the PhenoTyper - EthoVision XT 18 - Reference Manual. There you find a list of the parts available. Please contact your Noldus representative to send your order. The PhenoTyper Camera PhenoTyper 1 (Analog Camera) The camera is integrated in the PhenoTyper 1 Top Unit. PhenoTyper 2 (Digital Camera) The camera is mounted on the TopPlate of PhenoTyper 2. For issues related to the camera image, see Troubleshooting in the EthoVision XT Help. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-monitor-3qQ Chapter: PhenoTyper Analysis Profile You can create an analysis profile to calculate the number of beam breaks or select various state variables associated with the beam breaks. - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, choose one of the following: - Hardware continuous if you want to calculate the total number of beam breaks or visualize the raw data on the timeline. - Hardware state if you want to calculate the time when the number of beam breaks was higher or lower than a specific threshold, or the time that a beam was broken, or the time that a cue was on or off. - In the window that opens, next to Device type, select Beam Controller (PTBC-001x). - Next to Device, select the correct device name, if you have more than one connected. - Next to Signal, select the option you require. - For Hardware continuous, select Beam 1 breaks or Beam 2 breaks, depending on which port on the IR Beam Controller the Food Sensor was connected to. - For Hardware state, you have a few options: - Select Beam 1 breaks / Beam 2 breaks and then next to Value select the criterion you are interested in (e.g. to mark the time that the number of Beam 1 breaks >= 100). - To mark the time that a beam was broken, select Is beam 1 broken / Is beam 2 broken, then next to Value select the criterion (e.g. Is beam 1 broken True). - To mark the time that a cue was on or off, select Is cue 1 on / Is cue 2 on, then next to Value select the criterion (e.g. Is cue 1 on False). - Click Add. Note: Beam 1 breaks and Beam 2 breaks correspond to the signals of the two sensors that the IR Beam Controller can control. For each IR Beam Controller, the two sensors can only be used in the same cage (arena). To analyze both beam breaks, add the Hardware continuous twice. Cue Activation With the Hardware command you can calculate statistics of and visualize the events of type "cue on/off", provided that the IR Beam Controller box was connected to an optical cue device (e.g. a LED). - From the Dependent Variables list, under Hardware, click Hardware command. - In the Hardware Command window, next to Device type, select Beam Controller (PTBC-001x). - Next to Device, select the correct device name, if you have more than one connected. - Next to Command, select one of the options: Cue 1 on, Cue 1 off, Cue 2 on, and Cue 2 off. - Click Add. Statistics and Visualization - To calculate the statistics for the variables defined in the previous step, choose Analysis > Results > Statistics & Charts. Select the correct Data profile and Analysis profile from the lists on the toolbar and click Calculate. - To visualize the feeding events, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You will now see in the Time Event Plot when beam breaks took place. Examples - Hardware continuous - Beam 1 breaks: An interruption of the IR beam is scored as one in the timeline. The remaining timeline, with no interruption of the beam, is scored as zero. - Hardware state - Beam 1 breaks >= 10: The state is active after the tenth feeding event occurs. This event is scored in the Hardware continuous plot. - Hardware state - Is beam 1 broken / True: This state is active when the IR beam is interrupted. - Hardware state - Is beam 1 broken / False: This state is active when the IR beam is not interrupted. Note: If the plots of the Hardware continuous variable appear empty, that is because the data are shown as small dots. Click Show/Hide > Show Graph Data Points and zoom in the plot to show the dots larger. Interface 8.1 Why Use the TTL to 28V Interface? The Noldus TTL to 28V Interface (Noldus type number: PTMA-0010) provides a simple plug-and-play connection between the Noldus USB-IO box / Mini USB-IO box and several hardware devices. You need the TTL to 28V Interface when: - You want to control one or more hardware devices, such as doors in a radial arm maze, the Atlantis platform, and sound generators. - You want to control the DanioVision Toplight Unit. In that case, see the DanioVision DVOC-0041 - Reference Manual. Note: The TTL to 28V Interface converts the TTL signals from one of the following devices: USB-IO box / Mini USB-IO box into the Med Associates standard 28-Volt control signal. Furthermore, the TTL to 28V Interface can control two Med Associates devices, so it is a good alternative for the SG-230 or SG-230R TTL-to-28V adapter supplied by Med Associates. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-monitor Chapter: PhenoTyper General Information The Feeding Monitor is a system to monitor the behavior of mice based on sensors. This system can work with any compatible type of sensor. The Feeding Monitor can be used to measure the number of times an animal inserts its nose into the feeder of a PhenoTyper cage model 3000. As such, it can count the number of times the animal is feeding. The Feeding Monitor works by detecting the interruption of an infrared beam between an infrared transmitter and a receiver installed in the IR Food Sensor in the PhenoTyper cage. The IR Food Sensor works in combination with the IR Beam Controller (PTBC-001x) which can also control an optical cue device, for example, a LED. Contents of the Feeding Monitor Package - IR Beam Controller (PTBC-001x) – This box can be used to control any type of sensor in a PhenoTyper cage. Currently, the IR Food Sensor is the only sensor available for the Feeding Monitor. - Network (CAT5 UTP), 2-m purple cable (PTPC-7020) – To connect the IR Beam Controller to the USB IO-Box. - IR Food Sensor (PTFS-0010) – The sensor (see B in the figure below) that is built into the PhenoTyper cage model 3000. - Food Sensor cable (PTFS-0020) – To connect the IR Food Sensor with the IR Beam Controller (see C in the figure below). - Insert for PT3000 feeder (PT-I-00) – To adapt the feeder for use with the IR Food Sensor (see D in the figure below). Without the insert the animal cannot reach the food. Acknowledgements The Feeding Monitor has been developed in close collaboration with Prof. Dr. Martien Kas, University Medical Center, Utrecht. For more information about the application of an early version of the IR Food Sensor see, for example: - Kas et al., (2008). Differential Genetic Regulation of Motor Activity and Anxiety-Related Behaviors in Mice Using an Automated Home Cage Task. Behavioral Neuroscience (4): 769-776. - Kas et al., (2009). High-resolution genetic mapping of mammalian motor activity levels in mice. Genes, Brain and Behavior: 13-22. - De Mooij-Van Malsen et al., (2009). Interspecies Trait Genetics Reveals Association of Adcy8 with Mouse Avoidance Behavior and a Human Mood Disorder. Biological Psychiatry: 1123-1130. Install the Feeding Monitor Note: Although the network cables shown in the following schemes are used in networks, the signal coming from the Feeding Monitor is not a network signal. Do not connect the Feeding Monitor through a network hub or similar. Connect the Feeding Monitor Using the (Mini) USB-IO Box - Remove the feeder from the PhenoTyper cage and replace it with the IR Food Sensor (B in Figure 7.1). - Attach the feeder to the IR Food Sensor as in Figure 7.1 and put the Insert (D) for the PT3000 feeder into the feeder. - Connect the (Mini) USB-IO box to the EthoVision XT PC through a USB cable. - Use the purple network cable to connect the IR Beam Controller box (usb io-box port) to a TTL port of the (Mini) USB IO-Box. - Power up the (Mini) USB-IO box. The power LED indicates 'power on'. The active LEDs on the IR Beam Controller box remain on until the IR Food Sensor (or any other compatible sensor) is connected. If necessary, make sure the IR Beam Controller and its LEDs are out of sight of the animal in the PhenoTyper cage. - Connect the IR Food Sensor to the IR Beam Controller box (Beam-1 or Beam-2 port) with the Food Sensor cable (Figure 7.1, C). - The 'active' LED light turns off. The LED light turns on every time the beam of the IR Food Sensor is interrupted. Notes For details about the USB-IO box and the Mini USB-IO box, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-monitor-CPY Chapter: PhenoTyper Analysis Profile You can create an analysis profile to calculate the number of beam breaks or select various state variables associated with the beam breaks. - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, choose one of the following: - Hardware continuous if you want to calculate the total number of beam breaks or visualize the raw data on the timeline. - Hardware state if you want to calculate the time when the number of beam breaks was higher or lower than a specific threshold, or the time that a beam was broken, or the time that a cue was on or off. - In the window that opens, next to Device type, select Beam Controller (PTBC-001x). - Next to Device, select the correct device name, if you have more than one connected. - Next to Signal, select the option you require. - For Hardware continuous, select Beam 1 breaks or Beam 2 breaks, depending on which port on the IR Beam Controller the Food Sensor was connected to. - For Hardware state, you have a few options: - Select Beam 1 breaks / Beam 2 breaks and then next to Value select the criterion you are interested in (e.g. to mark the time that the number of Beam 1 breaks >= 100). - To mark the time that a beam was broken, select Is beam 1 broken / Is beam 2 broken, then next to Value select the criterion (e.g. Is beam 1 broken True). - To mark the time that a cue was on or off, select Is cue 1 on / Is cue 2 on, then next to Value select the criterion (e.g. Is cue 1 on False). - Click Add. Note: Beam 1 breaks and Beam 2 breaks correspond to the signals of the two sensors that the IR Beam Controller can control. For each IR Beam Controller, the two sensors can only be used in the same cage (arena). To analyze both beam breaks, add the Hardware continuous twice. Cue Activation With the Hardware command you can calculate statistics of and visualize the events of type "cue on/off", provided that the IR Beam Controller box was connected to an optical cue device (e.g. a LED). - From the Dependent Variables list, under Hardware, click Hardware command. - In the Hardware Command window, next to Device type, select Beam Controller (PTBC-001x). - Next to Device, select the correct device name, if you have more than one connected. - Next to Command, select one of the options: Cue 1 on, Cue 1 off, Cue 2 on, and Cue 2 off. - Click Add. Statistics and Visualization - To calculate the statistics for the variables defined in the previous step, choose Analysis > Results > Statistics & Charts. Select the correct Data profile and Analysis profile from the lists on the toolbar and click Calculate. - To visualize the feeding events, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You will now see in the Time Event Plot when beam breaks took place. Examples - Hardware continuous - Beam 1 breaks: An interruption of the IR beam is scored as one in the timeline. The remaining timeline, with no interruption of the beam, is scored as zero. - Hardware state - Beam 1 breaks >= 10: The state is active after the tenth feeding event occurs. This event is scored in the Hardware continuous plot. - Hardware state - Is beam 1 broken / True: This state is active when the IR beam is interrupted. - Hardware state - Is beam 1 broken / False: This state is active when the IR beam is not interrupted. Note: If the plots of the Hardware continuous variable appear empty, that is because the data are shown as small dots. Click Show/Hide > Show Graph Data Points and zoom in the plot to show the dots larger. Interface 8.1 Why Use the TTL to 28V Interface? The Noldus TTL to 28V Interface (Noldus type number: PTMA-0010) provides a simple plug-and-play connection between the Noldus USB-IO box / Mini USB-IO box and several hardware devices. You need the TTL to 28V Interface when: - You want to control one or more hardware devices, such as doors in a radial arm maze, the Atlantis platform, and sound generators. - You want to control the DanioVision Toplight Unit. In that case, see the DanioVision DVOC-0041 - Reference Manual. Note: The TTL to 28V Interface converts the TTL signals from one of the following devices: USB-IO box / Mini USB-IO box into the Med Associates standard 28-Volt control signal. Furthermore, the TTL to 28V Interface can control two Med Associates devices, so it is a good alternative for the SG-230 or SG-230R TTL-to-28V adapter supplied by Med Associates. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-monitor-NQ5 Chapter: PhenoTyper General Information The Feeding Monitor is a system to monitor the behavior of mice based on sensors. This system can work with any compatible type of sensor. The Feeding Monitor you can use to measure the number of times an animal inserts its nose into the feeder of a PhenoTyper cage model 3000. As such, it can count the number of times the animal is feeding. The Feeding Monitor works by detecting the interruption of an infrared beam between an infrared transmitter and a receiver installed in the IR Food Sensor in the PhenoTyper cage. The IR Food Sensor works in combination with the IR Beam Controller (PTBC-001x) which can also control an optical cue device, for example, a LED. Contents of the Feeding Monitor Package - IR Beam Controller (PTBC-001x) – This box can be used to control any type of sensor in a PhenoTyper cage. Currently, the IR Food Sensor is the only sensor available for the Feeding Monitor. - Network (CAT5 UTP), 2-m purple cable (PTPC-7020) – To connect the IR Beam Controller to the USB IO-Box. - IR Food Sensor (PTFS-0010) – The sensor (see B in the figure below) that is built in into the PhenoTyper cage model 3000. - Food Sensor cable (PTFS-0020) – To connect the IR Food Sensor with the IR Beam Controller (see C in the figure below). - Insert for PT3000 feeder (PT-I-00) – To adapt the feeder for use with the IR Food Sensor (see D in the figure below). Without the insert the animal cannot reach the food. Acknowledgements The Feeding Monitor has been developed in close collaboration with Prof. Dr. Martien Kas, University Medical Center, Utrecht. For more information about the application of an early version of the IR Food Sensor see, for example: - Kas et al., (2008). Differential Genetic Regulation of Motor Activity and Anxiety-Related Behaviors in Mice Using an Automated Home Cage Task. Behavioral Neuroscience (4): 769-776. - Kas et al., (2009). High-resolution genetic mapping of mammalian motor activity levels in mice. Genes, Brain and Behavior: 13-22. - De Mooij-Van Malsen et al., (2009). Interspecies Trait Genetics Reveals Association of Adcy8 with Mouse Avoidance Behavior and a Human Mood Disorder. Biological Psychiatry: 1123-1130. Install the Feeding Monitor Although the network cables shown in the following schemes are used in networks, the signal coming from the Feeding Monitor is not a network signal. Do not connect the Feeding Monitor through a network hub or similar. Connect the Feeding Monitor Using the (Mini) USB-IO Box - Remove the feeder from the PhenoTyper cage and replace it with the IR Food Sensor (B in Figure 7.1). - Attach the feeder to the IR Food Sensor as in Figure 7.1 and put the Insert (D) for the PT3000 feeder into the feeder. - Connect the (Mini) USB-IO box to the EthoVision XT PC through a USB cable. - Use the purple network cable to connect the IR Beam Controller box (Figure 7.1, A, usb io-box port) to a TTL port of the (Mini) USB IO-Box. - Power up the (Mini) USB-IO box. The power LED indicates 'power on'. The active LEDs on the IR Beam Controller box remain on until the IR Food Sensor (or any other compatible sensor) is connected. If necessary, make sure the IR Beam Controller and its LEDs are out of sight of the animal in the PhenoTyper cage. - Connect the IR Food Sensor to the IR Beam Controller box (Beam-1 or Beam-2 port) with the Food Sensor cable (Figure 7.1, C). - The 'active' LED light turns off. The LED light turns on every time the beam of the IR Food Sensor is interrupted. Notes For details about the USB-IO box and the Mini USB-IO box, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Phenotyper® URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-phenotyper Chapter: PhenoTyper Contents - Introduction - 1.1 About This Manual - When You Need This Manual - Using This Manual - 1.2 Other Documentation - Manuals - Sample Experiments - 1.3 Technical Support - Help Desk - Replacement of Components - The PhenoTyper Camera - 2.1 PhenoTyper 1 (Analog Camera) - Camera Focus and Orientation - Camera Settings - 2.2 PhenoTyper 2 (Digital Camera) - Package Contents - Camera Module - Camera Focus and Orientation - Camera Settings - The Top Unit Interface - 3.1 General Information - Components - Technical Specifications - 3.2 Connect the Top Unit Interface - Connection Scheme - The Pellet Dispenser and the Pellet Receptacle - 4.1 General Information - The Pellet Dispenser - Contents of the Pellet Dispenser Packages - Pellet Types - 4.2 Install the Pellet Dispenser - The Pellet Receptacle - Technical Specifications - Reliability - 4.3 Work with the Pellet Dispenser - EthoVision XT - Prepare the Experiment - EthoVision XT - Experiment Settings - EthoVision XT - Arena Settings - EthoVision XT - Trial Control Settings - Check That the Pellet Dispenser Works - Control the Pellet Dispenser Manually - Work with the Pellet Receptacle - Test the Pellet Receptacle - 4.4 Calculate the Statistics for the Pellet Dispenser - Analysis Profile - Statistics and Visualization - 4.5 Maintenance and Troubleshooting - Correct Usage of the Pellet Dispenser - Clean the Pellet Dispenser - Troubleshooting - The Lickometer - 5.1 General Information - The Lickometer - Technical Specifications - 5.2 Install the Lickometer - 5.3 Work with the Lickometer - EthoVision XT - Prepare the Experiment - EthoVision XT - Experiment Settings - EthoVision XT - Arena Settings - Check That the Lickometer Works - Acquire the Data - View the Data in the Hardware Log - 5.4 Calculate the Statistics for the Lickometer - Analysis Profile - Statistics and Visualization - PhenoWheel - 6.1 General Information - PhenoWheel - Technical Specifications - 6.2 Install PhenoWheel - Components - Procedure - 6.3 Work with PhenoWheel - EthoVision XT - Prepare the Experiment - EthoVision XT - Experiment Settings - EthoVision XT - Arena Settings - Acquire the Data - 6.4 Calculate the Statistics for PhenoWheel - Analysis Profile - Statistics and Visualization - The Feeding Monitor - 7.1 General Information - 7.2 Install the Feeding Monitor - 7.3 Work with the Feeding Monitor - EthoVision XT - Prepare the Experiment - EthoVision XT - Experiment Settings - EthoVision XT - Arena Settings - Acquire the Data - 7.4 Calculate the Statistics for the Feeding Monitor - Analysis Profile - Statistics and Visualization - The TTL to 28V Interface - 8.1 Why Use the TTL to 28V Interface? - 8.2 Install the TTL to 28V Interface - 8.3 Technical Specifications - Appendix A: Test Sheet for Focusing - Appendix B: Index Legal Information Information in this document is subject to change without notice and does not represent a commitment on the part of Noldus Information Technology BV. The software described in this document is furnished under a license agreement. The software may be used or copied only in accordance with the terms of the agreement. Copyright © 2025 Noldus Information Technology BV. All rights reserved. No part of this publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any other language in whole or in part, in any form or by any means, without the written permission of Noldus Information Technology BV. Trademarks: PhenoTyper and EthoVision are registered trademarks of Noldus Information Technology BV. Other product names are trademarks of their respective companies. Publication Date: March 7, 2025 Compatible With: EthoVision XT version 18 Publisher: Noldus Information Technology BV, International Headquarters, Wageningen, The Netherlands Phone: +31-317-473300 Email: contact@noldus.com For addresses of our other offices and support, please see our web site www.noldus.com. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - Phenotyper® URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-phenotyper-fuQ Chapter: PhenoTyper Contents - Introduction - 1.1 About This Manual - When you need this manual - Using this manual - 1.2 Other Documentation - Manuals - Sample experiments - 1.3 Technical Support - Help desk - Replacement of components - The PhenoTyper Camera - 2.1 PhenoTyper 1 (Analog Camera) - Camera focus and orientation - Camera settings - 2.2 PhenoTyper 2 (Digital Camera) - Package contents - Camera module - Camera focus and orientation - Camera settings - The Top Unit Interface - 3.1 General Information - Components - Technical specifications - 3.2 Connect the Top Unit Interface - Connection scheme - The Pellet Dispenser and the Pellet Receptacle - 4.1 General Information - The pellet dispenser - Contents of the pellet dispenser packages - Pellet types - 4.2 Install the Pellet Dispenser - The pellet receptacle - Technical specifications - Reliability - 4.3 Work with the Pellet Dispenser - EthoVision XT - prepare the experiment - EthoVision XT - experiment settings - EthoVision XT - arena settings - EthoVision XT - trial control settings - Check that the pellet dispenser works - Control the pellet dispenser manually - Work with the pellet receptacle - Test the pellet receptacle - 4.4 Calculate the Statistics for the Pellet Dispenser - Analysis profile - Statistics and visualization - 4.5 Maintenance and Troubleshooting - Correct usage of the pellet dispenser - Clean the pellet dispenser - Troubleshooting - The Lickometer - 5.1 General Information - The lickometer - Technical specifications - 5.2 Install the Lickometer - 5.3 Work with the Lickometer - EthoVision XT - prepare the experiment - EthoVision XT - experiment settings - EthoVision XT - arena settings - Check that the lickometer works - Acquire the data - View the data in the hardware log - 5.4 Calculate the Statistics for the Lickometer - Analysis profile - Statistics and visualization - PhenoWheel - 6.1 General Information - PhenoWheel - Technical specifications - 6.2 Install PhenoWheel - Components - Procedure - 6.3 Work with PhenoWheel - EthoVision XT - prepare the experiment - EthoVision XT - experiment settings - EthoVision XT - arena settings - Acquire the data - 6.4 Calculate the Statistics for PhenoWheel - Analysis profile - Statistics and visualization - The Feeding Monitor - 7.1 General Information - 7.2 Install the Feeding Monitor - 7.3 Work with the Feeding Monitor - EthoVision XT - prepare the experiment - EthoVision XT - experiment settings - EthoVision XT - arena settings - Acquire the data - 7.4 Calculate the Statistics for the Feeding Monitor - Analysis profile - Statistics and visualization - The TTL to 28V Interface - 8.1 Why Use the TTL to 28V Interface? - 8.2 Install the TTL to 28V Interface - 8.3 Technical Specifications - Appendix A: Test Sheet for Focusing - Appendix B: Index Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - The Pellet Receptacle URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-the-pellet-receptacle Chapter: PhenoTyper General Information The Pellet Dispenser The Noldus Pellet dispenser is a device to deliver standard available pellets to mice or rats. It can be used in learning tests to reward the animals when they perform a task well. The Pellet dispenser can be controlled from EthoVision XT to drop pellets automatically when a condition becomes true, for instance, when the animal enters the feeder zone within 30 seconds after a light was switched on. The Pellet dispenser consists of two parts, a pellet silo and the base part with the stepper motor. The Pellet dispenser is often used in combination with the Pellet receptacle. Button and LED Indicator Press the button to drop one pellet. The LED light at the front of the Pellet dispenser indicates the status of the device: - LED off: Waiting for command. - Single blink: Receiving a pellet drop command. Single blink is also given when a pellet is dropped. - Double blink: When connecting the power cable/RJ45 cable or resetting. - Continuous, fast blinking: Error state. - LED constant on: Detector is stuck. Contents of the Pellet Dispenser Packages Pellet Dispenser (Standard) - A Pellet dispenser PTPD-001x. - Additional blue carousel for 45 mg pellets. - A gray RJ45 cable (2 meters long). - Aluminium feed-through and silicon in-between tubing. Optionally available: - Elevated stand (PTPD-1050). - Power supply for stand-alone use (PTPD-2010). - RJ45 modular cable 0.5 - 3 meters, different colors. Note: Beginning 2016, Noldus introduced the Pellet dispenser PTPD-0011, successor of PTPD-0010. The main differences are: - A more accurate drop positioning system. - Two types of carousels, both with 10 holes: - White carousel, for 20 mg pellets, is installed by default. - Blue carousel, for 45 mg pellets. If you have a previous version of the Pellet dispenser PTPD-0010, the carousel has 12 holes. You cannot exchange carousels between Pellet dispenser versions. Pellet Receptacle - The Pellet receptacle PTPR-001x. - PhenoTyper wall specific for a Pellet receptacle. - A black cable with a RJ45 connector at one end and a white 3-pin female connector at the other end (2 m long). Accessories - Aluminium feed-through and silicon in-between tubing. - Silica gel pack to keep the silos dry. - Elevated stand (not included in the standard package). Pellet Types The Noldus Pellet dispenser has been tested with the following pellets: - Bio-Serv 20 mg (3.2 mm x 2.5 mm; product nr. F0071 and F0163). - Bio-Serv 45 mg (3.6 mm diameter; product nr. F0021). - TestDiet 20 mg (3.2 mm x 2.6 mm). See bio-serv.com and testdiet.com. To Switch Between Pellet Types When you receive the Pellet dispenser, it is equipped with the white carousel for 20 mg pellets. Before using pellets of different size, do the following: - Remove the pellet silo from the base of the Pellet dispenser. - Remove the lid of the silo. - Gently press the white plastic insert out of the transparent silo. - Use the hex key to remove the carousel cover plate. - Replace the carousel. - Close the cover plate of the carousel, tighten the bolts and reassemble the silo. - When assembling the Pellet dispenser, make sure that the aluminium hole cover clip inside the silo is aligned with one of the holes. This makes it less likely that multiple pellets are dropped simultaneously. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 18 Service - The Pellet Receptacle URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-18-service-the-pellet-receptacle-IJR Chapter: PhenoTyper General Information The Pellet Dispenser The Noldus Pellet dispenser is a device to deliver standard available pellets to mice or rats. It can be used in learning tests to reward the animals when they perform a task well. The Pellet dispenser can be controlled from EthoVision XT to drop pellets automatically when a condition becomes true, for instance, when the animal enters the feeder zone within 30 seconds after a light was switched on. The Pellet dispenser consists of two parts, a pellet silo and the base part with the stepper motor. The Pellet dispenser is often used in combination with the Pellet receptacle. Button and LED Indicator Press the button to drop one pellet. The LED light at the front of the Pellet dispenser indicates the status of the device: - LED off: Waiting for command. - Single blink: Receiving a pellet drop command. Single blink is also given when a pellet is dropped. - Double blink: When connecting the power cable/RJ45 cable or resetting. - Continuous, fast blinking: Error state. - LED constant on: Detector is stuck. Contents of the Pellet Dispenser Packages Pellet Dispenser (Standard) - A Pellet dispenser PTPD-001x. - Additional blue carousel for 45 mg pellets. - A gray RJ45 cable (2 meters long). - Aluminium feed-through and silicon in-between tubing. Optionally available: - Elevated stand (PTPD-1050). - Power supply for stand-alone use (PTPD-2010). - RJ45 modular cable 0.5 - 3 meters, different colors. Note: Beginning 2016, Noldus introduced the Pellet dispenser PTPD-0011, successor of PTPD-0010. The main differences are: - A more accurate drop positioning system. - Two types of carousels, both with 10 holes: - White carousel, for 20 mg pellets, is installed by default. - Blue carousel, for 45 mg pellets. If you have a previous version of the Pellet dispenser PTPD-0010, the carousel has 12 holes. You cannot exchange carousels between Pellet dispenser versions. Pellet Receptacle - The Pellet receptacle PTPR-001x. - PhenoTyper wall specific for a Pellet receptacle. - A black cable with a RJ45 connector at one end and a white 3-pin female connector at the other end (2 m long). Accessories - Aluminium feed-through and silicon in-between tubing. - Silica gel pack to keep the silos dry. - Elevated stand (not included in the standard package). Pellet Types The Noldus Pellet dispenser has been tested with the following pellets: - Bio-Serv 20 mg (3.2 mm x 2.5 mm; product nr. F0071 and F0163). - Bio-Serv 45 mg (3.6 mm diameter; product nr. F0021). - TestDiet 20 mg (3.2 mm x 2.6 mm). See bio-serv.com and testdiet.com. To Switch Between Pellet Types When you receive the Pellet dispenser, it is equipped with the white carousel for 20 mg pellets. Before using pellets of different size, do the following: - Remove the pellet silo from the base of the Pellet dispenser. - Remove the lid of the silo. - Gently press the white plastic insert out of the transparent silo. - Use the hex key to remove the carousel cover plate. - Replace the carousel. - Close the cover plate of the carousel, tighten the bolts and reassemble the silo. - When assembling the Pellet dispenser, make sure that the aluminium hole cover clip inside the silo is aligned with one of the holes. This makes it less likely that multiple pellets are dropped simultaneously. Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## PhenoTyper XT 19 - A Technical Support URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-a-technical-support Chapter: PhenoTyper Technical Support Help Desk If you run into problems, please contact us at my.noldus.com. Please check this manual carefully and the EthoVision XT Help before contacting the Help Desk. To send experiment data, use the Backup procedure (see the EthoVision XT Help). Replacement of Components If any component breaks or wears out, please contact Noldus to have it sent back to us. Please note that in any case you must send it to our international headquarters (Wageningen, The Netherlands) no matter where you are. Broken components will be fixed or replaced with new ones. To have components replaced, enter a support ticket at my.noldus.com. Important: Plastic components (such as the cage walls) will only be replaced or repaired free of charge if they are broken due to a defect of workmanship and the damage is reported within one month of shipment. Other components are covered by a one year guarantee; to claim under guarantee you must report the damage within one year of shipment. It is possible that you may have a service contract entitling you to free replacement of parts for a longer period, please contact the support department if you are not sure. In any case we can still fix or replace the parts, but it may be necessary to levy a charge. The guarantee is only valid if you treat the PhenoTyper as described in this manual. In any case, shipping broken parts is at your expenses, while sending repaired or replacing parts back to you will be at our expenses. Important: If you connect PhenoTyper to any third-party products, such as a video tracking system other than EthoVision XT, Noldus is not responsible for maintenance of that product, or for damage done to the PhenoTyper by that product. To order spare parts, contact your Noldus representative. Parts List Top Units, Control Unit and Cables The following cables are no longer available as a standard part (only on request): PhenoTyper 1 - PT-T10.5/P — Top Unit V1.5 PAL/CCIR camera version. Includes camera, circuitry, lights, buzzer. - PT-T10.5/N — Top Unit V1.5 NTSC/EIA camera version. Includes camera, circuitry, lights, buzzer. - PT-CU-10 — Control Unit. Includes cable to connect to PhenoTyper. - PT-PS1 — Power supply 120V AC–240V AC / 24V DC. - PTTO-SD01 — Remote On Screen Device (OSD). Available on request. - PT-PSC — Power supply feed-through cable 1.8 m. - PT-BNC30 — Coaxial cable with BNC connectors, 75Ω, 3 m. - PT-BNC100 — Coaxial cable with BNC connectors, 75Ω, 10 m. PhenoTyper 2 - PT2TP-0020 — Top Unit Top Plate. - PT2I-01_TTL — Top Unit TTL Control Unit. - MAPS-0014 — Power supply 120V AC–240V AC / 24V DC. - PT-PSC — Power supply feed-through cable 1.8 m. - *** — Network cable with RJ-45 connectors. - PT-LPT — PC TTL cable 1.8 m. - PT-LPT18 — TTL extension cable 1.8 m (extension of PT-LPT). - PT-LPT100 — TTL extension cable 10 m (extension of PT-LPT). - PT-TTL18 — TTL feed-through cable 1.8 m. Cage Model 3000 (For Mice) Below the standard cage components are listed. For custom solutions, please contact Noldus. - PTC3-W000 — Wall plain, model 3000. Material: polymethylmethacrylate. - PTC3-W001 — Wall with air-gap, model 3000. Material: polymethylmethacrylate. - PTC3-S001 — Airgap shielding, model 3000. Material: polymethylmethacrylate. - PTC3-W002 — Wall prepared for feeder and bottle, model 3000. Material: polymethylmethacrylate. - PTC3-W005 — Wall prepared for shelter, model 3000. Material: polymethylmethacrylate. - PTC3-S010 — Cover plate, model 3000. Material: polymethylmethacrylate. - PTC3-BT01 — Cage bottom, model 3000. Material: polymethylmethacrylate, dual satin opaque. Side 31.5 cm. Includes L piece (5×3×1.5 cm) to keep cage walls firm. - PT-C-S-MNT1 — Set of assembling material and tools for the cage, model 3000. Includes: - 1× hexagon key 3 mm - 1× hexagon key 2.5 mm - 4× silicone tube, 1 cm - 8× hexagon socket screw, cap head, stainless steel, M5×12 - 2× bolts M4×12 - 6× black nylon spacer 5 mm - 6× white nylon screw CS M4×16 - 6× white nylon nut/washer Cage Model 4500 (For Rats) Below the standard cage components are listed. For custom solutions, please contact Noldus. - PTC4-W000 — Wall plain, model 4500. Material: polymethylmethacrylate. - PTC4-W001 — Wall with airgap, model 4500. Material: polymethylmethacrylate. - PTC4-S000 — Airgap shielding, model 4500. Material: polymethylmethacrylate. - PTC4-S001 — Airgap shielding for mice, model 4500. Material: polymethylmethacrylate. - PTC4-W002 — Wall prepared for feeder and bottle, model 4500. Material: polymethylmethacrylate. - PTC4-W005 — Wall prepared for shelter, model 4500. Material: polymethylmethacrylate. - PTC4-F001 — Cover plate with air holes, model 4500. Material: polymethylmethacrylate. - PTC4-F002 — Cover plate with air holes for mice, model 4500. Material: polymethylmethacrylate. - PTC4-BB01 (black) / PTC4-BW01 (white) — Cage bottom. Material: polymethylmethacrylate, matted. - PT-C-L-MNT1 — Set of assembling material and tools for the cage, model 4500. Includes: - 1× hexagon key 3 mm - 1× hexagon key 2.5 mm - 8× silicone tube, 1 cm - 8× hexagon socket screw, cap head, stainless steel, M5×12 - 4× hexagon socket bolts M4×12 - 10× black nylon spacer 5 mm - 10× white nylon screw CS M4×16 - 10× white nylon nut/washer - 4× stainless steel screw, M3×12 - 4× hexagonal nuts Bottles, Feeders and Shelters - PT-B-00 — Standard drinking bottle. Model 3000 can have 1 bottle; model 4500 can have one or two. - PTBM-0001 — Drinking bottle mount. Comes with silicone tubes. - PT-F-00 — Feeder, model 3000. Made of stainless steel. - PT-F-01 — Feeder, model 4500. Made of stainless steel. - PT-SH-BL-0 — Shelter, small black. Size 100×100×50 mm, holes ⌀32 mm. - PT-SH-WH-0 — Shelter, small white. Size 100×100×50 mm, holes ⌀32 mm. - PT-SH-BL-1 — Shelter, large black. Size 150×150×120 mm, holes ⌀75 mm. - PT-SH-WH-1 — Shelter, large white. Size 150×150×120 mm, holes ⌀75 mm. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Assemble Phenotyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-assemble-phenotyper Chapter: PhenoTyper Assemble PhenoTyper Before You Start Assembling PhenoTyper involves the same basic steps no matter what the cage model and configuration is. The instructions below are based on the home cage configuration for PhenoTyper model 3000. Home Cage Components Note: The PhenoTyper components you have purchased may not match exactly the illustrations in this manual. For example, walls may be matte instead of being translucent. - A — Walls with airgap (2x per cage). See page 23. - B — Airgap shields (2x per cage). See page 23. - C — Cage bottom. See page 24. - D — Wall prepared for feeder and bottle (replaced by a plain wall in the basic cage). See page 24. - E — Wall prepared for shelter (replaced by a plain wall in the basic cage). See page 25. - F — L pieces for fixing the walls (2x per cage). See page 27. - G — Cover plate. See page 34. - H — Bottle support. See page 28. - I — Drinking bottle. See page 29. - J — Shelter. See page 30. - K — Feeder. See page 31. The plain wall is part PTC3-W000 for cage model 3000 and PTC4-W000 for cage model 4000. For part serial numbers, see page 116. Remove the Protecting Foil from the Walls All cage elements A–E, G and J are provided with a protecting plastic foil on both sides. Remove the foil before assembling the cage. Mounting Set For cage model 3000: see page 117. For cage model 4500: see page 119. Assemble the Cage Follow the assembly steps for your specific cage model and configuration as outlined in the sections below. Add the Drinking Bottle If you have PhenoTyper walls with one hole only for the bottle support, attach the bottle support with one M4 12 mm screw. Ensure the drinking bottle is placed in the correct position as indicated in the assembly diagram. Add the Shelter Attach the shelter to cage walls PTC3(4)-W005 (cage wall prepared for shelter). See the parts list on page 116. Important: Before placing the shelter, remove the protecting sheet from the inside. Add the Feeder Attach the feeder to the appropriate cage wall as indicated in the assembly diagram. The Top Unit - PhenoTyper 2 For models 4500 and 9000, place the Top Unit on top of the cage according to the assembly diagram for your model. The Top Unit - PhenoTyper 1 Place the metal frame and the Top Unit on top of the cage. The Cover Plate - PhenoTyper 1 When you do not use the Top Unit, place the cover plate (G) on top of the cage. This prevents the animal from escaping. Important: Do not leave the cover plate in between the Top Unit and the cage during experiments. It may decrease image quality. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - B Technical Specifications URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-b-technical-specifications Chapter: PhenoTyper B Technical Specifications PhenoTyper 1 Power Supply 24V DC - 15 W Video Output - CCIR black/white, 1 Vpp - 75 W - Resolution: 720x576 (PAL) or 640x480 (NTSC) Infrared Lighting - 3 integrated IR arrays through diffuser - Wavelength: 940 nm Audio Stimulus (TTL on/off controllable) - Frequency: ±2300 Hz - Amplitude: ±80 dB Yellow Light Stimulus (TTL on/off controllable) - Wavelength: 590 nm White Light Gradient (TTL on/off controllable) - Color temperature: 5500°K - Intensity: 0 - approx. 1000 lux Connections - Supply 24V DC in - Supply 24V DC out (feed-through) - TTL control in/out Sub-D 9 - TTL control in/out Sub-D9 (feed-through) - Video out (BNC) - Control unit Sub-D15 Remote On Screen Device (OSD) For Top Units with serial number 001051 to 1412. For 1471 and higher, OSD on request only. Cage Components Clear or matte Acrylic (PMMA). Environmental Specifications - Operating temperature: 0 to +40 °C (+32 to +104 °F) - Storage temperature: -20 to +70 °C (-4 to +158 °F) - Operating humidity: Up to 80%, no condensation Dimensions (Top Unit Excluded) - Model 3000: 300 x 300 x 435 mm / 11.8 x 11.8 x 17.1 in, Floor area 841 cm² (130.4 in²) - Model 4500: 450 x 450 x 660 mm / 17.7 x 17.7 x 26.0 in, Floor area 1936 cm² (300.1 in²) - Model 9000: 900 x 900 x 1000 mm / 35.4 x 35.4 x 39.4 in, Floor area 7744 cm² (1200.3 in²) Top Unit Versions Top Unit Interface PT-T10.0 Introduced 09-2004; started from serial nr. Features: CMOS type camera PT-T10.1 Introduced 09-2005; started from serial nr. Features: CMOS camera replaced by a CCD-type PT-T10.2 Introduced 03-2011; started from serial nr. 801 Features: Camera mount with alignment method PT-T10.3 Introduced 03-2012; started from serial nr. Features: New LED type for white stimulus/cue light PT-T10.4 Introduced 10-2013; from serial nr. 1053 to 1412. Feature: On Screen Display for camera settings added PT-T10.5 Introduced 4-2018; started from serial nr. 1471 OSD control on request only Noldus Type Number PTTI-001x Power Supply (Top Unit Interface) 12V DC supplied by the USB IO-box Current Consumption 40 mA Connectors - 1x RJ45 8-pin modular to USB IO-box - 4x RJ45 8-pin modular to PhenoTyper Top Units Dimensions (Top Unit Interface) 115 x 65 x 32 mm / 4.5 x 2.6 x 1.3 in (L x W x H) Weight (Top Unit Interface) 100 g Cables - Cable to USB IO-box: 1x 1m modular RJ45 (green) - Cable to PhenoTyper Top Unit: 4x 2m modular RJ45 (green) with SubD-9 adapter PhenoTyper 2 Mains Adapter - Input: 100-240 V AC - Output: 24 V DC 3 A maximum Power Requirements 24 V DC 0.4 A Standard Camera Basler acA1300-60gm - Interface: Gigabit Ethernet (RJ45 connector, CAT5e or higher) - Sensor: 1/1.8" Progressive Scan CMOS, monochrome - Max. resolution: 1280 x 1024 - Max. frame rate: 60 fps Lens Evetar F1.8 4mm, includes IR pass filter Infrared Lighting - Wavelength: 940 nm - Intensity: Adjustable manually, 0.1 to 0.35 mW/cm*; light permanent on White Light - Color temperature: 4000°K - Intensity: Adjustable manually, 0.5 to 2700 lux*. Default 500 lux Connections - 24 V DC input/output feed-through - 4x RJ-45 TTL control port** Cage Components Clear Acrylic (PMMA) Environmental Specifications - Operating temperature: 0 to +40 °C (+32 to +104 °F) - Operating humidity: 20 to 80%, relative, non-condensing - Storage temperature: -20 to +70 °C (-4 to +158 °F) Dimensions Cage (Top Unit Excluded) - Model 3000: 300 x 300 x 435 mm / 11.8 x 11.8 x 17.1 in, Floor area 841 cm² (130.4 in²) - Model 4500: 450 x 450 x 660 mm / 17.7 x 17.7 x 26.0 in, Floor area 1936 cm² (300.1 in²) - Model 9000: 900 x 900 x 1000 mm / 35.4 x 35.4 x 39.4 in, Floor area 7744 cm² (1200.3 in²) Dimensions and Weight - Dimensions Top Plate: 338 x 305 x 22 mm / 13.3 x 12.0 x 0.9 in - Dimensions Control Unit: 305 x 88 x 34 mm / 12.0 x 3.5 x 1.3 in - Weight Top Plate: 2.1 kg (4.6 lbs) (camera module included) - Weight Control Unit: 0.4 kg (0.9 lbs) * Measured at the bottom of a PT3000 cage. ** Ports 3 and 4 for future use. Top Unit Elements PT2TP-0020 — PhenoTyper 2 Top Plate Introduced 01-2024; started from serial nr. PT2I-01_TTL — PhenoTyper 2 Top Plate Control Unit Introduced 01-2024; started from serial nr. PT2MC-BGM-1300 — Digital camera module with Basler acA1300-60gm C Declaration of Conformity PhenoTyper 1 We, Noldus Information Technology b.v. Nieuwe Kanaal 5 NL-6700 AG Wageningen The Netherlands Declare that our product "PhenoTyper" to which this declaration relates is in compliance with the requirements of the EMC Directive (89/336/EEC) because of the following reasons: - It complies with the requirements of NEN-EN50082-1 (Generic immunity standard — Commercial and light industry). - It complies with the requirements of NEN-EN50081-1 (Generic emission standard — Commercial and light industry). The CE marking is affixed on the product according to article 10 of the EC Directive 89/336/EEC. Wageningen, 15 October 2004 EC Declaration of Conformity Manufacturer: Nieuwe Kanaal 5 6709PA Wageningen The Netherlands Declares that the following line of products: PhenoTyper PT-T10 series Fulfills all relevant provisions of the EC EMC directive 89/336/EEC. According to the harmonized standards: - NEN-EN 50081-1 — January 1994: Electromagnetic Compatibility - Generic Emission Standard Part 1: Residential, Commercial and Light Industry - NEN-EN 50082-1 — September 1993: Electromagnetic compatibility - Generic immunity standard - Part 1: Residential, commercial and light industry Fulfills all relevant provisions of the EC RoHS directive 2011/65/EU. According to the harmonized standards: - EN IEC 63000 : 2018 — Technical documentation for the assessment of electrical and electronic products with respect to the restriction of hazardous substances Fulfills all relevant provisions of the EC WEEE Directive 2012/19/EU — Waste Electrical and Electronic Systems (WEEE). Date: September 30, 2020 Name: Jeroen Kemerink Title: Vice President Research & Development PhenoTyper 2 PhenoTyper 2 Digital Camera — EU Declaration of Conformity PhenoTyper 2 Digital Camera — FCC Supplier's Declaration of Conformity Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Common Tests With Phenotyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-common-tests-with-phenotyper Chapter: PhenoTyper Common Tests with PhenoTyper Short-term experiments can be carried out while the subjects are monitored in PhenoTyper. This can be, for example, learning tasks, anxiety tests, or tests on the effects of drugs. For information on how to set up an experiment in EthoVision XT, see Set Up an Experiment in the EthoVision XT Help. - General behavior monitoring - Create routines - Food receiving task - Illuminated shelter task - CognitionWall™ task - Anxiety tests General Behavior Monitoring Maximum trial duration (tested): With or without simultaneous video recording: 72 hours. For more information on tested configurations, see the EthoVision XT Help. To open the Help, in EthoVision XT choose Help > Help Topics. Prolonged Video Recordings If you need to record video of the same subject for more than 72 hours, we recommend that you make a series of trials. - In the Trial Control Settings, remove the condition immediately before the Start track action box. - In the Trial Control Settings, set the Maximum Trial Duration. To make a trial of about 72 hours, set this time to 72 hours minus x minutes. The remaining x minutes are used as inter-trial interval to give the software enough time to save the video and the data. In this example 72 h minus 5 minutes = 4315 minutes. - In the Acquisition screen, select Track all planned trials with an inter-trial interval equal to the time x chosen above. If you want to select a shorter time, test it beforehand. - After data acquisition, and before running analysis, open a Data Profile and group the trials based on the subject. Selected References - Bass, J. S., Tuo, A. H., Ton, L. T., Jankovic, M. J., Kapadia, P. K., Schirmer, C., et al. (2020). On the digital psychopharmacology of valproic acid in mice. Frontiers in Neuroscience 14: 594612. doi: 10.3389/fnins.2020.594612 - de Visser, L., van den Bos, R., Stoker, A. K., Kas, M. J. H., and Spruijt, B. M. (2007). Effects of genetic background and environmental novelty on wheel running as a rewarding behaviour in mice. Behavioral and Brain Research: 290–297. doi: 10.1016/j.bbr.2006.11.019 - Deiana, S., Platt, B., and Riedel, G. (2008). Scopolamine-induced changes in activity measured in a home cage observation system. Proceedings of Measuring Behavior 2008 (Maastricht, The Netherlands, August 26-29, 2008): 312–313. - de Mooij-van Malsen, A. J. G., van Lith, H. A., Oppelaar, H., Hendriks, J., de Wit, M., Kostrzewa, E., et al. (2009). Interspecies trait genetics reveals association of Adcy8 with mouse avoidance behavior and a human mood disorder. Biological Psychiatry: 1123–1130. doi: 10.1016/j.biopsych.2009.06.016 - Jankovic, M. J., Kapadia, P. P., and Krishnan, V. (2019). Home-cage monitoring ascertains signatures of ictal and interictal behavior in mouse models of generalized seizures. PLoS One: e0224856. doi: 10.1371/journal.pone.0224856 - Namdar, I., Feldman, R., Glazer, S., Meningher, I., Shlobin, N. A., Rubovitch, V., et al. (2020). Motor effects of minimal traumatic brain injury in mice. Journal of Molecular Neuroscience: 365–377. doi: 10.1007/s12031-019-01422-9 Create Routines In a conditioning test, drop a food pellet when the animal has been detected on the shelter. Repeat this procedure as soon as the animal eats the food item. The trial must be stopped when the procedure is repeated 25 times. Between two subsequent repeats, an interval of 10 seconds is defined. The corresponding sequence is defined as a Sub-rule in the Trial Control Settings, with the following boxes: - Rule Begin – Start of the sub-rule. - Condition – Specifies that the animal must be in the zone Shelter. - Action – Specifies the command Drop a pellet to the pellet dispenser. You must define this and all other devices in the Port Device Mapping and in the Arena - Hardware Mapping in order to be able to define actions on those devices. - Condition – Specifies that the animal must be in the zone Feeder. - Rule End – Stop of the sub-rule. Define a Reference for this sub-rule and specify that the sub-rule must be repeated 25 times and the Stop to Start interval for subsequent repeats is 10 seconds. Place the Reference box in the Start-Stop trial rule, immediately before the Stop track box. You can create a rule to drop a pellet every time the animal enters a trigger zone, or similarly create a rule to switch on the light in an illuminated shelter when a particular entrance is chosen. For more details about creating routines, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Food Receiving Task In a commonly used learning test, the animal receives a food pellet from the pellet dispenser when it enters a certain zone, for example when it jumps on top of the shelter. The test generally lasts 15 minutes, followed by a period of 1 hour in which no reward can be obtained. If the dark phase in which the animals are active lasts 12 hours, 10 tests can be carried out in this period. To give the test animal a cue that a reward can be obtained, the yellow light of the PhenoTyper is switched on in every 15-minute testing period. This test assesses whether the frequency of moving from the shelter zone to the food pellet zone changes over time. Arena Settings - In the Arena Settings, create a zone for the top of the shelter. Note that this is not the same as the hidden zone used for detecting the animal when it is inside the shelter. - Define a zone for the area where the pellet is dropped. Check that the pellets always drop in this zone. Especially when no bedding material is used, the pellets may roll far from where they are dropped. Trial Control Settings In the Trial Control Settings, create a Trial Control Rule for the Pellet Dispenser. Include conditions for the clock times the tests start and the action "PhenoTyper yellow light on". Create other necessary settings, like detection settings. Next, acquire the data. Data Profile Create a Data Profile with multiple time conditions to filter out the 15-minute periods. Analysis Profile Create an analysis profile and select the dependent variable Zone transition. Under Settings, select from the zone On top of Shelter to the Pellet Dispenser zone. Select Allow intermediate zone visits. Click the Trial Statistics tab and select Frequency. If you run multiple trials, click the Group statistics tab and select the Group mean and Standard Error of the Frequency. Calculate the Statistics Make sure the data profile that filters the 15-minute task periods is active. In the Experiment Explorer click Analysis output under Results. Click Calculate. The frequency of transitions from the top of the shelter to the pellet dispenser zone is now given for each 15-minute task period. If the animal learns, this number increases over time. Illuminated Shelter Task The illuminated shelter has been developed to automate the Discriminative Avoidance Task in mice in the PhenoTyper 3000. The aversive stimulus is generated by two light boxes, each housing a bright white LED and mounted on two cage walls, shining inwards through the Perspex wall into the shelter. The light is switched on briefly or continuously, depending on the presence of the mouse near or inside the shelter. Mice can learn to avoid the "preferred entrance" of the shelter. In a study with 43 different mouse mutants, Maroteaux et al. (2012) showed that mutants differ in their ability to associate a specific shelter entrance with the aversive stimulus. Typical Protocol - Day 1–4: It is assessed over the first four days which of the entrances is preferred by the animal. - Day 5–6: A Trial Control Rule is defined in which a light in the shelter is switched on when the animal uses the preferred entrance. - Day 7: In the probe trial, during a 24-hour period it is checked if the animal learns to use the other entrance of the shelter. Arena Settings In the Arena Settings, create zones for both shelter entrances. These zones are predefined in the PhenoTyper template. Trial Control Settings Make a Trial Control subrule with a condition for when the animal enters the zone "preferred shelter entrance" and an action to switch on the light in the illuminated shelter. Also create a condition and action to switch off the light in the shelter when the animal leaves it. Create other necessary settings, like detection settings. Next, acquire the data. Data Profile In the Data Profile, select the testing trials (days 5–6) or if the testing phase is part of an uninterrupted trial, create a Time filter for the 48-hour testing phase. Click the Settings button on the Result box and select Results per time bin. Use time bins of, for example, 1 hour. Time bins help find trends in cognitive and aversive responses; for instance, an increase in the use of the shelter entry that did not trigger the light. Analysis Profile - To calculate statistics of each entrance, create an Analysis Profile and select the dependent variable In Zone. Select both shelter entrances. Click the Trial Statistics tab and select Frequency. If you run multiple trials, click the Group statistics tab and select the Group mean and Standard Error of the Frequency. - Make sure the data profile that filters the 48-hour testing phase is active. In the Experiment Explorer click Analysis output under Results. Click Calculate. The frequency of visits to both shelter entrances is now shown for every time bin. References - Heer, R.C. de; Schenke, M.; Kuurman, W.W.; Spruijt, B.M. (2008). Learning (in) the PhenoTyper: an integrative approach to conducting cognitive behavioural challenges in a home cage environment. Proceedings of Measuring Behavior 2008, 6th International Conference on Methods and Techniques in Behavioral Research (Maastricht, The Netherlands, 26–29 August 2008), 57. - Maroteaux, G.; Loos, M.; van der Sluis, S.; Koopmans, B.; Aarts, E.; van Gassen, K.; Geurts, A.; Largaespada, D.A.; Spruijt, B.M.; Stiedl, O.; Smit, A.B.; Verhage, M. (2012). High-throughput phenotyping of avoidance learning in mice discriminates different genotypes and identifies a novel gene. Genes, Brain and Behavior: 772–784. doi: 10.1111/j.1601-183X.2012.00820.x CognitionWall™ Task The CognitionWall was designed for the development of operant cognitive tests in PhenoTyper home-cages. The CognitionWall is a wall with three entrances, which is placed in front of the pellet dispenser. Mice are rewarded with a food pellet when they choose to pass through one of the three entrances. The rate at which a mouse gains a relative preference for the rewarded entrance is used as a measure of discrimination learning. After an initial discrimination learning phase, the rewarded entrance is switched to another entrance (reversal). The rate at which a mouse gains a relative preference for the newly rewarded entrance is used as a measure of reversal learning. References - Logan, S., Owen, D., Chen, S. et al. (2018). Simultaneous assessment of cognitive function, circadian rhythm, and spontaneous activity in aging mice. GeroScience: 123–137. doi: 10.1007/s11357-018-0019-x - Remmelink, E., Aartsma-Rus, A., Smit, A. B., Verhage, M., Loos, M. and van Putten, M. (2016). Cognitive flexibility deficits in a mouse model for the absence of full-length dystrophin. Genes, Brain and Behavior: 558–567. doi: 10.1111/gbb.12301 - Remmelink, E., Chau, U., Smit, A. B., Verhage, M., and Loos, M. (2017). A one-week 5-choice serial reaction time task to measure impulsivity and attention in adult and adolescent mice. Scientific Reports: 42519. doi: 10.1038/srep42519 Anxiety Tests In anxiety tests, the exploratory behavior of the animals is tested. The animals are placed under mild stress by projecting a white light beam on the food area during the first three hours of the dark period, in which the animals are active. The animal must choose between feeding and avoiding the bright light. The time it takes before the animal starts feeding could reflect its level of anxiety. Arena Settings Define a zone for the feeding area. Trial Control Settings Create a Trial Control rule with an Action White light on, followed by a Time condition for the first three hours of the dark phase (i.e., "wait three hours"), followed by a second Action White light off which switches off the light after three hours. Create other necessary settings, like detection settings. Next, acquire the data. Data Profile - Create a data profile with a filter for the experiment time. - Create a data profile with a filter for some time after the light on the feeding area has been switched off, for example, one hour. Analysis Profile - Create an analysis profile and select the dependent variable In Zone. Select the zone Feeding area. Click the Trial Statistics tab and select Mean (gives mean duration per visit), Frequency (gives the number of visits), and Cumulative duration (gives the total duration over all visits). If you run multiple trials, click the Group statistics tab and select the Group mean and Standard Error for each statistic. - Create an analysis profile and select the dependent variable In Zone. Select the zone Feeding area. Click the Trial Statistics tab and select Latency to first. Next, select the correct combination of data profile and analysis profile. In the Experiment Explorer click Analysis output under Results. Click Calculate. Selected References - Aarts, E., Maroteaux, G., Loos, M., Koopmans, B., Kovačević, J., Smit, A. B., et al. (2015). The light spot test: measuring anxiety in mice in an automated home-cage environment. Behavioral Brain Research: 123–130. doi: 10.1016/j.bbr.2015.06.011 - de Mooij-van Malsen, A. J. G., van Lith, H. A., Oppelaar, H., Hendriks, J., de Wit, M., Kostrzewa, E., et al. (2009). Interspecies trait genetics reveals association of Adcy8 with mouse avoidance behavior and a human mood disorder. Biological Psychiatry: 1123–1130. doi: 10.1016/j.biopsych.2009.06.016 - Prevot, T. D., Misquitta, K. A., Fee, C., Newton, D. F., Chatterjee, D., Nikolova, Y. S., et al. (2019). Residual avoidance: a new, consistent and repeatable readout of chronic stress-induced conflict anxiety reversible by antidepressant treatment. Neuropharmacology: 98–110. doi: 10.1016/j.neuropharm.2019.05.005 Other References - de Visser, L. (2008). Home Sweet Home: Home Cage Testing for Behavioural Phenotyping of Mice. Dissertation Utrecht University, Faculty Veterinary Medicine. - Grieco, F. et al. (2021). Measuring behavior in the home cage: study design, applications, challenges, and perspectives. Front. Behav. Neurosci.: 735387. doi: 10.3389/fnbeh.2021.735387 - Loos, M., Koopmans, B., Aarts, E., Maroteaux, G., van der Sluis, S., et al. (2014). Sheltering behavior and locomotor activity in 11 genetically diverse common inbred mouse strains using home-cage monitoring. PLoS ONE (9): e108563. doi: 10.1371/journal.pone.0108563 - Maroteaux, G., Loos, M., van der Sluis, S., Koopmans, B., Aarts, E., van Gassen, K., Geurts, A., Largaespada, D. A., Spruijt, B. M., Stiedl, O., Smit, A. B. and Verhage, M. (2012). High-throughput phenotyping of avoidance learning in mice discriminates different genotypes and identifies a novel gene. Genes, Brain and Behavior: 772–784. doi: 10.1111/j.1601-183X.2012.00820.x - Pham, J., Cabrera, S. M., Sanchis-Segura, C., Wood, M. A. (2009). Automated scoring of fear-related behavior using EthoVision software. Journal of Neuroscience Methods (2): 323–326. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Index URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-index Chapter: PhenoTyper Index A - Acetic Acid - Acetone - Acoustical Stimuli - Acrylic - Action - Actions Based on PhenoTyper - Airgap Shield - Alkaline Substances - Analyzing Data - Assembling PhenoTyper - Autoclave - Automatic Gain Control B - Backup - Bedding Material - Behavior Recognition - Benzene - Benzyl Alcohol - Bottle - Bottom of Cage - Buzzer C - Cable Connections - PhenoTyper 1 - Camera - PhenoTyper 1 - PhenoTyper 2 - Charts - Exporting - Cleaning the Cage - CognitionWall - Condition - Conditioning Test - Connect - PhenoTyper 1 - PhenoTyper 2 - Control Unit - PhenoTyper 1 - PhenoTyper 2 - Cover Plate D - Declaration of Conformity - Documentation - Drinking Bottle E - Ethanol - EthoVision XT - General Information - Ethylene Oxide - Experiments (Multiple) - Extension Cables F - Feeder - Focus (Lens) - PhenoTyper 1 - PhenoTyper 2 - Food Receiving Task - Frame Grabber G - Gamma Radiation H - Handling of Subjects - Help - Hexagon Key - Home Cage - Hydrogen Peroxide I - Illuminated Shelter Task - Import Trials - Infrared Light - Copying Settings - PhenoTyper 1 - PhenoTyper 2 - Infrared Lighting - Isopropyl Alcohol J - Jumper Settings L - LED Arrays - Lens Focus - PhenoTyper 1 - PhenoTyper 2 - Lickometer - Light Conditions - Light Intensity - PhenoTyper 1 - PhenoTyper 2 - Light Meter - Light Stimuli - Light-Dark Cycle - L-Shape Element M - Manuals - Maximum Trial Duration - MediaRecorder - Methanol - Mixed Video Images - Model - Multiple Experiments N - Neoprene - Nesting Material - Nortio - With PhenoTyper 1 - With PhenoTyper 2 P - Pellet Dispenser - Pellet Receptacle - Cleaning - Pellets - Peracetic Acid - Perspex/Acrylic Cleaner - PhenoTyper - Assembling - Benefits - Communication with EthoVision - Configurations - Experiment - General Information - Maintenance - Setups - PhenoTyper 1 - Assign Devices to Arenas - Cable Connections - Set Up Experiment - PhenoTyper 2 - Assign Devices to Arenas - Cable Connections - Set Up Experiment - PhenoWheel - Picolo Alert Encoder Board - PMMA - Polycarbonate - Polymethylmethacrylate - Power Cord - Power Supply - Protecting Sheet Q - Quad Unit R - Resolution - PhenoTyper 1 - PhenoTyper 2 - Restore Backup - Rodent S - SDI Control Port - SDI Devices - Separate Video Images - Shelter - Shutter Speed - Sound Intensity - Sound Stimuli - Specifications - Stimuli T - Technical Support - Testing - PhenoTyper 1 - PhenoTyper 2 - Tools - Top Unit - Cleaning - Top Unit Interface - Trial Control - Trial Control Settings - TTL Devices - TTL In - Tube Lamps U - USB-IO Box - With PhenoTyper 1 - With PhenoTyper 2 - USB-IO Box Jumpers - UV Radiation V - Vaporized Hydrogen Peroxide - Ventilation Holes - VHP - Video Cable - PhenoTyper 1 - PhenoTyper 2 - Video Camera - Video Images (Mixing) - Video Processor - Video Resolution - PhenoTyper 1 - PhenoTyper 2 - Video Tracking - Visual Stimuli W - Walls - Protecting Sheets - Water Bottle - Wavelength - White Light (PhenoTyper 2) - White Light Spot (PhenoTyper 1) Y - Yellow Light Spot Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Introduction To Phenotyper URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-introduction-to-phenotyper Chapter: PhenoTyper What Is PhenoTyper? PhenoTyper combines an open field and video-based monitoring equipment in a complete observation system that you can use to monitor rodent behavior automatically. The infrared lighting system ensures robust monitoring regardless of ambient light conditions in the lab. You can also use PhenoTyper to administer visual and acoustical stimuli to your subjects, or to monitor the subjects using specific sensors. To this purpose, PhenoTyper 2 can easily integrate additional devices. The walls of PhenoTyper can be configured in different ways, making it suitable for a variety of applications. PhenoTyper can be fully controlled by the EthoVision XT video tracking software. Activity, movement and specific behaviors (e.g. feeding, grooming) of the subjects can be continuously measured and analyzed afterwards. This and Other Manuals To open the manuals, from the Windows Start menu choose All Apps > Noldus > EthoVision XT > Other Documentation. You can also find all the manuals on the my.noldus portal: my.noldus.com - PhenoTyper - EthoVision XT 18 - Reference Manual.pdf (this manual). Includes information on how to install and configure PhenoTyper and control its devices to automate experiments in EthoVision XT. It also includes examples of PhenoTyper applications. - PhenoTyper - EthoVision XT 18 - Service Manual.pdf — See this manual for specific information on the PhenoTyper camera, and the devices that can be used together with PhenoTyper, for example the Pellet dispenser and PhenoWheel. - EthoVision XT 18 - Trial and Hardware Control - Reference Manual.pdf — This manual contains extensive information on the control of hardware devices through EthoVision XT. Learn how to combine conditions, actions, and subrules to create complex task protocols for your subjects. - EthoVision XT 18 Help — Consult the Help for extensive information about EthoVision XT, for example how to draw arenas and zones, select tracks for analysis and create charts. To open the EthoVision XT Help, press F1 in EthoVision XT. Main Features of PhenoTyper Home Cage Environment Observation and tracking of subjects in a home cage environment has the main advantage that the behavior is more natural and less influenced by human intervention. The cages can be equipped with a shelter, a feeder, a water bottle and a rotating wheel, and can be enriched with bedding material and other objects. Top Unit The Top Unit placed over the cage is the "brain" of PhenoTyper. It holds the camera and additional sensors and actuators and contains all the electronic equipment necessary to exchange information with the tracking software. It also includes infrared and white light arrays. Lighting An array of Infrared (IR) LEDs is activated as long as PhenoTyper is switched on. This allows continuous monitoring and video-tracking independent of the light conditions in the test room. An array of white LEDs (in PhenoTyper 2 only) provides visible white light. You can switch on this light and use it as a visual stimulus or when you need to track color-marked animals. You can adjust the intensity of the IR and white light using the controls on the Top Unit front panel. Video Camera PhenoTyper is equipped with a monochrome analog camera (in PhenoTyper 1) or a monochrome GigE Vision digital camera (in PhenoTyper 2). Both cameras detect infrared light and exclude most of the light in the visible range. For optimal image quality a built-in infrared array ensures illumination; this way your recordings are independent of visible light. You can run tests throughout the light-dark cycle because the image of the subject and the background processed in EthoVision XT won't change. Important: Do not use incandescent light bulbs as visible light source in the test room, because they produce a lot of infrared light which can interfere with video tracking. If you need extra visible light in your test room, use tube lamps, LED lamps or the LED arrays provided with PhenoTyper 2, which produce far less infrared light. The camera can see the subjects at night but does not detect the heat produced by animals. The lens focus and orientation of the camera is optimized by Noldus. If you need to make adjustments, see the PhenoTyper - EthoVision XT 18 - Service Manual. Visible Light and Sound The following stimulus devices are available: - In PhenoTyper 1: the white light spot and the yellow light spot. Each of these illuminate approximately a quarter of the cage bottom. Furthermore, PhenoTyper 1 has a buzzer module that can be used to administer a sound stimulus. - In PhenoTyper 2: the white light (not a light spot) is currently available as a visual stimulus. Contact Noldus if you need additional stimulus devices. The stimuli can be administered automatically using the Trial Control function in EthoVision XT. PhenoTyper - EthoVision XT Communication PhenoTyper is the ideal cage for use in combination with the tracking and analysis software EthoVision XT, no matter how long and complex the trials are. PhenoTyper receives commands from and sends feedback to EthoVision XT. When working with multiple PhenoTypers simultaneously, you can administer stimuli in different cages independently. The course of events during a trial is logged in EthoVision XT. The events are readily available for analysis. For extensive information, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. How Can I Use PhenoTyper? For Monitoring and Video Tracking Connect the PhenoTyper camera to the EthoVision XT computer. The software tracks the subject's position and calculates a wealth of statistics of the subjects' behavior (distance moved, time spent in specific zones, etc.). With Behavior Recognition you can analyze behaviors like grooming and sniffing. This setup does not perform actions on any device. For Recording Video Connect the PhenoTyper camera to a computer with EthoVision XT or MediaRecorder. MediaRecorder is especially useful when you want separate high-resolution video files for each cage. You can use the video later on to carry out offline video-tracking with EthoVision XT. For Video Tracking and Administration of Stimuli This advanced setup is meant for controlling the PhenoTyper devices during a trial, for example in a conditioning experiment where the subject is given a reward when it performs a specific behavior. You can have EthoVision XT carry out actions like switching on a light when a condition is met. PhenoTyper is connected to the EthoVision XT computer through the USB-IO box. In the software you can program the Trial Control with a sequence of conditions (e.g. check that the mouse has reached a zone) and subsequent actions (e.g. switch on the white light) that will be executed during a trial. You can also combine PhenoTyper with other devices like the Noldus Pellet dispenser or the Noldus Lickometer. EthoVision XT also receives feedback from PhenoTyper; for example, you can track in your data how often a stimulus was given, and when a pellet was dropped. For extensive information about how to control hardware devices, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. What's New in PhenoTyper? Digital Video Quality PhenoTyper 2 hosts a Basler acA1300-60gm monochrome digital camera. The main advantage of a digital camera is that its image is less sensitive to noise and allows recording video at a resolution greater than that attainable with PhenoTyper 1. A GigE Vision camera such as that of PhenoTyper can be easily connected to a PC through an Ethernet interface board, so you no longer need an expensive frame-grabber board to record video. - PhenoTyper 2 resolution: 1280 x 1024 - PhenoTyper 1 resolution: PAL video, 768 x 576 Modularity PhenoTyper 2 has a modular structure. Besides the central module that hosts the video camera, additional devices can be attached using the eight slots available. When needed, you can replace them with other devices for a new protocol. With PhenoTyper 1, adding a custom device to the Top Unit was relatively cumbersome by comparison. Improved Lighting PhenoTyper 2 is equipped with an internal white light ring that ensures consistent illumination across your experiments. Better lighting means better detection of the subjects, and more reliable and reproducible results. Backward Compatibility PhenoTyper 2 is backward-compatible with PhenoTyper 1, allowing for an effortless upgrade without changing cables and cage elements. Current Development of PhenoTyper 2 The Top Unit of PhenoTyper 2 is subject to continuous development. Some functions of PhenoTyper 1 are not yet available in that Top Unit. Contact Noldus if you wish to use a specific device with PhenoTyper 2. Advantages of PhenoTyper Compared with Ordinary Test Setups Robustness The video camera blocks out visible light, therefore EthoVision XT works on infrared light only. This makes tracking independent of ambient light conditions in the lab, and even allows studies of circadian rhythms without having to change settings in EthoVision XT when the light conditions change. Ease of Use You no longer have to worry about choosing, mounting and positioning a camera, nor how to set up the ambient light conditions in the lab. PhenoTyper is a complete monitoring system: camera, lights, open field, and even visual and acoustical stimuli are all integrated in one system. Flexibility PhenoTyper can be configured in different ways and extended with a number of accessories. Not only can you combine cage elements, but you can also easily customize the cage walls so that the cage is tailored to your research. This makes it possible to apply PhenoTyper to a wide range of studies and research questions, from a short open field test to multi-day circadian rhythm monitoring, from toxicology trials to operant tests. Scalability and Reproducibility You can easily extend your study by adding cages and replicating experiments with the same settings in EthoVision XT. Furthermore, because the cages can be easily standardized using the same components, you can improve reproducibility by applying the same setup in different studies and across labs. Minimal Human Interference PhenoTyper is a home-cage environment. The subject can live in the cage for days when provided with food and water. Tests can be performed in a series, without moving the subject. This way the subject's behavior is more natural and handling by the operator is minimized. Variable Observation Periods Because PhenoTyper is a home cage and the video image is independent of the external lighting conditions, it can be used in short-term tests as well as in multi-day recordings. For example, it is sometimes necessary to observe animals for long periods in order to detect phenotypic differences between strains or experimental treatments. Applications of PhenoTyper There is a wide range of applications of PhenoTyper as a home-cage monitoring system, and the following list is not exhaustive. Check noldus.com regularly for more examples of use of PhenoTyper with the relevant literature. For an extensive review of studies conducted with PhenoTyper, see the following article: Grieco, F. et al. (2021) Measuring behavior in the home cage: study design, applications, challenges, and perspectives. Front. Behav. Neurosci. :735387. doi: 10.3389/fnbeh.2021.735387 Test Paradigm / Behavior to Be Measured PhenoTyper Add-On or Device Needed EthoVision XT Module Needed Spontaneous Behaviors Activity-related measures — — Activity-related measures (>12 hrs) Drinking bottle, Feeder, Shelter — Circadian rhythm Drinking bottle, Feeder, Shelter — Habituation, novelty response Drinking bottle, Feeder, Shelter — Running wheel activity Running wheel Trial and Hardware Control Feeding behavior Feeding monitor Trial and Hardware Control Drinking behavior Lickometer Trial and Hardware Control Rearing, grooming, sniffing, jumping, twitching (rat) — Rat Behavior Recognition Rearing, grooming, sniffing, hopping, digging (mouse) — Mouse Behavior Recognition Cognition Discrimination learning e.g. CognitionWall Trial and Hardware Control Reversal learning e.g. CognitionWall Trial and Hardware Control Avoidance learning Illuminated shelter Trial and Hardware Control Appetitive operant conditioning Shelter, Pellet dispenser Trial and Hardware Control Anxiety Light avoidance Shelter Trial and Hardware Control Sheltered feeding Open and close feeding platforms — Social Behavior Dyadic interaction — Social Interaction Optogenetics Single or dual channel stimulation Single/Dual channel commutator in top unit, dual channel LED illuminator, pulse train generator Trial and Hardware Control Biotelemetry Physiology (third party product needed) Telemetry receiver placed under PhenoTyper Trial and Hardware Control, External Data PhenoTyper Configurations Cage Size - Model 3000 — Suitable for mouse studies. - Model 4500 — Suitable for both rat and mouse studies. - Model 9000 — Suitable for multi-subject rat studies. Cage Types You can make three main cage types depending on the walls and accessories chosen: - Basic Cage — Cage with one plain wall, one wall with door, and two ventilation walls. Suitable for short-term studies. - Home Cage — Cage provided with door, a feeder, a drinking bottle, and a shelter. Two walls have ventilation holes. Suitable for long-term observations. - The Model 4500 includes two drinking bottles and one feeder larger than that of Model 3000. - The Model 9000 home cage includes two drinking bottles and two large feeders. - The Model 4500 and 9000 are provided with a shelter bigger than that of the Model 3000. - Custom Cage — Any combination of walls and accessories that differs from the Basic and the Home cage. You can build, for example, a custom cage with feeder and bottle but no shelter, or a cage with three or four ventilation walls if necessary. Additional Wall Types Beside the standard walls in clear perspex, several wall types are also available in a matte version. Wall types are available for the following systems: - The PhenoWheel for mice. - The Activity Wheel for rats. - The Pellet dispenser and the Pellet receptacle. - The Mouse Feeding Monitor. - The CognitionWall. For connecting third party hardware to the PhenoTyper cage, contact Noldus to see what the possibilities are for your specific devices. Using Multiple PhenoTypers Maximum Number of PhenoTyper Cameras The following configurations have been tested: - PhenoTyper 1 (analog camera): 16 - PhenoTyper 2 (digital camera): 16 You can also record video using MediaRecorder and then do tracking offline. MediaRecorder is especially useful when you need to record high-resolution video for each cage. Maximum Number of PhenoTypers That Can Be Controlled You can have EthoVision XT control the PhenoTyper devices. The EthoVision XT Trial Control Settings are applied to each PhenoTyper independently, provided that each PhenoTyper is defined as a separate arena. - PhenoTyper 1: You can connect four PhenoTypers to one Top Unit Interface and up to 13 Top Unit interfaces to one EthoVision XT computer through the Noldus USB-IO box. You could in principle control up to 52 PhenoTypers simultaneously. However, the resulting video resolution would be very low. Therefore, we recommend connecting up to 16 PhenoTypers to one computer. - PhenoTyper 2: You can connect PhenoTypers directly to the USB-IO box or the Nortio TTL Terminal Hub. A maximum of eight PhenoTypers connected through TTL ports were tested. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Maintenance URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-maintenance Chapter: PhenoTyper Maintenance Your PhenoTyper cage will last longer if you follow these few recommendations. Please always keep the cages clean and dry. Make sure that no liquid penetrates the equipment on top of the cage. Clean the Cage General Information The cage walls, the bottom plate and the shelter of PhenoTyper are made of Acrylic, also known as Polymethylmethacrylate or PMMA. To clean the cage, please use water and soap only, or wipes for alcohol-sensitive materials (see below). Do not wash the cage with water at more than 80°C (176°F). Important - Read This First - Do not use chemicals to wash the cage except those listed in the next section. - Whatever substance you use to clean PhenoTyper, wipe the surface completely dry. Make sure that droplets do not remain on any component of the cage. - Do not use autoclaves to sterilize the cage or any of its components! It may damage it. Clean the Cage Walls Provided with the Pellet Receptacle Beginning from items with serial number 132, the cage walls with a pellet receptacle can be cleaned without removing the pellet receptacle first. For those items, moisture is expected not to damage the circuits. You can also clean the inside of the receptacle by loosening the screws. However, if you want to clean the pellet receptacle thoroughly, follow this procedure: - Disconnect all cables and remove the wall with the pellet receptacle from the cage. - Unscrew the receptacle unit from the wall. - Remove the label with the serial number, or cut it through on the line between the black enclosure and the transparent support frame. - Gently pull out the two parts from the wall. Each part must be cleaned separately. Clean those parts just like you do for the regular cage walls. - Reassemble the components and attach them back to the cage wall. Acceptable Cleaning Techniques and Substances Important: Noldus takes no responsibility for any damage resulting from improper use of cleaning substances. Always test a substance when in doubt. Always remove remaining liquid after cleaning. Use the following substances and techniques to clean the cage walls, the shelter and the bottom plate. For the drinking bottle and the Top Unit, see the relevant sections below. - Electronic beam. - Gamma radiation. - Ethylene oxide gas. - Hydrogen peroxide (HP), liquid (up to 3% concentration). Only use HP to clean the cage's acrylate/PMMA components. Important: Do not use HP with any metal or electronic components, including the Top Unit! Metals can be severely damaged by HP. If you use (vaporized) hydrogen peroxide, we recommend cleaning the surfaces afterwards using water and mild soap, or a perspex/acrylic cleaner. Always dry all the surfaces. - Vaporized hydrogen peroxide (VHP, up to 30% concentration). This technique requires specific apparatuses and procedures. See https://www.sciencedirect.com/topics/immunology-and-microbiology/vaporized-hydrogen-peroxide. Important: Make sure that the VHP procedure includes the dehumidification process. Dehumidification reduces relative humidity (ideally to less than 30%). If dehumidification is not done, condensation of the gas occurs, resulting in a large number of droplets on the surface of the objects. This means that a much higher concentration of hydrogen peroxide than in the gas phase will be in contact with the objects. This is likely to damage plastic in the long term. When in doubt, always check with the manufacturer of the VHP cleaning equipment about the compatibility of VHP with Acrylate (PMMA) and electronic components. - The risk of damage increases with the number of times that an object is subject to VHP cycles during its lifetime. - Only use VHP to bring material to the safe environment, not to clean the cages on a daily basis. - We recommend cleaning the surfaces afterwards using water and mild soap, or a perspex/acrylic cleaner. Always dry all the surfaces. - Peracetic acid (also known as Peroxyacetic acid, or PAA; up to 2% concentration). This is a good alternative to autoclaving. A trade name for Peracetic acid is Nu-Cidex. - UV radiation. - High intensity visible light. - Alkaline substances (albeit in low concentrations). - Perspex/acrylic cleaner. - Disinfection wipes that are compatible with acrylate. A good option is wipes with Meliseptol® by Carl Roth: https://www.carlroth.com/nl/en/surface-disinfectants/disinfection-wipes-meliseptol-wipes-sensitive/p/xp57.1 - Low-temperature hydrogen peroxide gas plasma. - Diluted solutions of isopropyl alcohol can be used to wipe down acrylic without adverse reaction. Important: Take care with the following cleaning conditions: - Cleaning should take place in a well-ventilated room. - Take the cage apart and clean each component (bottom, walls, etc.) separately. Make sure that there are no parts together. - Use spray or damp cloth to apply the isopropanol. - After wiping down the surfaces, make sure all isopropanol has evaporated; droplets should not remain on the surfaces. Substances That Can Damage PhenoTyper Important: Make sure that the following chemicals do not come in contact with PhenoTyper (cage and Top Unit). Noldus takes no responsibility for any damage resulting from improper use of cleaning substances. Always test a substance when in doubt. - Acetaldehyde - Acetone - Allyl alcohol - Aniline - Acetic acid - Benzene - Benzyl alcohol - Butyl acetate - Butyl alcohol - Carbon disulfide - Carbon tetrachloride - Chloroform - Chlorine gas - Chlorobenzene - Dichloroethane - Dioxane - Ethanol - Ethoxyethane - Ethyl acetate - Ethylene oxide (wet) - Hydrocarbons - Hydrogen fluoride - Hydrogen peroxide liquid (>3%) - Methanol - Methyl acetate - Methylated spirit - Methylene chloride - Methylethylketone - Nitric acid - Steam - Any strong acid Clean the Drinking Bottle The bottle itself is made out of polycarbonate and can be autoclaved at 125°C (257°F). The stopper is made of neoprene and can be cleaned at temperatures up to 90°C (194°F). Clean the Top Unit To clean the Top Unit, please use a damp cloth. Please do not use chemicals or soap to wash the Top Unit. - Make sure that no liquid penetrates the equipment inside the Top Unit or its connectors. Pay particular attention when cleaning the Top Unit of PhenoTyper 2. - Always remove liquid after cleaning, whatever method you use. - Do not use Vaporized Hydrogen Peroxide (VHP) or any of the substances listed in the substances that can damage PhenoTyper section to clean devices or boxes that contain electronics. Recommended Materials For your animals in the PhenoTyper, you may want to use bedding and nesting material. Several suppliers offer different materials. The products described below are known to work well for tracking with EthoVision XT. Bedding Material - For black animals, tracking goes well if you use wood chips, such as 5x5x1 mm wood chips from ABEDD® - LAB & VET Service GmbH (www.abedd.com). Use this bedding material together with a white PhenoTyper floor. - To track white animals you need a black background. In this case, use a black PhenoTyper floor. Tracking white animals goes well when using Paperchip pellets (www.lbs-biotech.com) as bedding material. This material appears black under infrared light. Note: When you try out different types of bedding materials, be aware that many materials that appear black to the human eye appear as white under infrared light. When you track hooded animals, it depends on the proportion of black and white whether you can best track with a white or a black background. Nesting Material A simple white tissue is often used as nesting material and placed inside the shelter. This works well for tracking black animals. To track white animals, nesting material that appears black under infrared light would be most suitable. However, most black tissue-like materials unfortunately appear as white under infrared light. Therefore, a white tissue is often used for these animals as well. When you do so, check that the animals do not drag the tissue out of their shelter. If the tissue is present on the PhenoTyper floor, it will be detected as the animal by EthoVision XT. Pellets for the Pellet Dispenser For the Pellet dispenser you can use 20 mg or 45 mg pellets. For more information, see The Pellet Dispenser and the Pellet Receptacle in the PhenoTyper - EthoVision XT 18 - Service Manual. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Phenotyper 1 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-phenotyper-1 Chapter: PhenoTyper PhenoTyper 1 For this section you need: - PhenoTyper 1 and the USB-IO box, or - PhenoTyper 1, the Nortio Core and the Nortio TTL Terminal Hub. Create an Experiment - Choose File > New from Template. In the Select a template option window, select Apply a pre-defined template. - Follow the instructions in the guided setup. Under How is the arena configured, choose PhenoTyper (for one cage) or PhenoTyper, quad (four cages). After you have created the new experiment, you must still check and adjust Experiment Settings, Arena Settings and Detection Settings before you can track any animal correctly. Experiment Settings Select the Cameras - In the Experiment Explorer, click Experiment Settings. - Under Video source, select the number of cameras from the list next to Number of sources. For PhenoTyper 1 (analog camera): If you use a quad unit to mix four camera images, select the appropriate option. Select your cameras under Sources. For more information, see the EthoVision XT Help. Configure the Devices of PhenoTyper 1 (USB-IO Box) Follow this procedure if you have connected PhenoTyper to EthoVision XT through the USB-IO box. - In the Experiment Settings, next to Trial Control Hardware, select Use of Trial Control Hardware and click Settings. In the window that pops up, select Noldus USB-IO Box and click OK. - In the Device Configuration window, locate the row SDI Port 13 and check that under Device Type, Top Unit Interface PTTI-0010 is selected. Top Unit (Standard) should be selected for each PhenoTyper that you connected to the Top Unit Interface. In the same way, assign a Pellet Dispenser or custom hardware like an Illuminated shelter to a TTL Port. Assign a Noldus Lickometer or a PhenoWheel to an SDI port. For the procedure to test the connected hardware, see Arena Settings. Configure the Devices of PhenoTyper 1 (Nortio Core + Nortio TTL Hub) Follow this procedure if you have connected PhenoTyper to EthoVision XT through the Nortio Core + Nortio TTL Hub. - In the Experiment Settings, next to Trial Control Hardware, select Use of Trial Control Hardware and click Settings. In the window that pops up, select Nortio Core and click OK. - In the Nortio Configuration window, locate the row that corresponds to the TTL port connected to PhenoTyper through the NOCA-TU1x cable. Select one of the two: - Top Unit Light (NOCA-TU1x) for yellow and/or white light. - Top Unit Sound (NOCA-TU1x) for the buzzer. Repeat the step for each PhenoTyper. In the following example, the white light and/or yellow light, and the sound are used for each PhenoTyper. Note that port 1 and 2 of the Nortio Hub are connected to the NOCA-TU10 box of the first PhenoTyper; port 3 and 4 to the second PhenoTyper, etc. See also The Nortio system in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Additional Options - To detect freezing behavior, under Analysis options select Activity analysis. Click the video button next to it and watch the video tutorial to learn about Activity analysis. - If you work with rats, you can let EthoVision XT automatically detect behaviors like grooming, drinking, eating and rearing. Select Behavior recognition under Analysis Options. You need the Rat Behavior Recognition Module for this automatic behavior recognition. Arena Settings Choose Setup > Arena Settings and open Arena Settings 1. For details, see Arena Settings in the EthoVision XT Help. Calibration Click Draw Scale to Calibrate and draw a line between two opposite cage walls or along an object of known length. Do this for both dimensions. Enter this length after drawing the line. For reference, the PhenoTyper cage width is: - 30 cm for model 3000 - 45 cm for model 4500 - 90 cm for model 9000 Arena Click Select Shape and Draw Arena. Move the outline of the arena over the cage floor in the video image. Check that the arena covers the whole area in which you want to track the animal. Include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the pointing tip of the label stays within the arena. Repeat this step for all the cages in the video image. Zones Check that the Spotlight zone, Drinking zone, Feeding zone and Shelter zone with its Entry zones are positioned where the respective zones are on the video image, and that all have the correct shape. If necessary, adjust their size and position. If necessary, remove zones and/or draw additional zone groups/zones. If you want to know how often the animal is on top of the shelter, you have to create an extra shelter zone. If you use a Pellet Dispenser for learning tasks, create a zone where the pellet drops. Check that the pellets always fall within this zone. For testing anxiety-like behaviors, draw an additional zone in the center of each PhenoTyper. This way you can analyze the time that the subject spends in the center relative to the total time. This proves useful when comparing data obtained with PhenoTyper and those obtained with classic Open Field or Elevated Plus Maze tests. Shelters If you put a shelter in PhenoTyper, we advise you to define it as a Hidden zone. This way, from the time the animal enters the shelter to the time it is detected again, EthoVision XT records the animal as being in that zone. To define a hidden zone, draw a zone corresponding to the shelter and specify it as a hidden zone. For more information, see Hidden zones in the EthoVision XT Help. Arena Settings for Rat Behavior or Mouse Behavior Recognition When you selected Behavior recognition (only available when you have the Rat Behavior Recognition Module or Mouse Behavior Recognition Module of EthoVision XT) in the Experiment Settings, defining a few special zones and points significantly increases behavior recognition accuracy. See Zones and points for Behavior recognition in the EthoVision XT Help. Assign the PhenoTyper Devices to the Arenas For this procedure you must have the Trial and Hardware Control Module. Open the Arena Settings and choose the section that applies depending on the interface device (either USB-IO box or Nortio Core + Nortio TTL Hub). Assign the Devices of PhenoTyper 1 (USB-IO Box) - In the Arena - Hardware Mapping window, you should see as many rows as devices added in the Experiment Settings. If not, click Add device for each device you want to add. For example, for four PhenoTypers, click Add device four times. - Under Device Type, select Top Unit (Standard) if it is not selected already. For four PhenoTypers, you should see four rows, each with Top Unit Standard selected. - Under Device Name, enter a name (e.g. PhenoTyper Top Unit) or accept the default name (A, B, C...). - For each Arena, select the corresponding Top Unit (Standard) #. Scroll the table to the right when needed. For multiple PhenoTypers: Make sure that each Top Unit is assigned to only one Arena (PhenoTyper cage), and that each Arena hosts only one Top Unit. - For other devices, click Add device. - Repeat the steps above for the Noldus Lickometer, Pellet Dispenser, and PhenoWheel. - For a third-party hardware device, under Device Type, select Custom Hardware. Enter a name under Device name and select one of the physical devices from the list for each Arena. For more information about this step, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Assign the Devices of PhenoTyper 1 (Nortio Core + Nortio TTL Hub) - In the Arena - Hardware Mapping window, you should see as many rows as devices added in the Experiment Settings. If not, click Add device for each device you want to add. For example, for four PhenoTypers, click Add device four times. - Under Device Type, select Top Unit Light or Top Unit Sound if it is not selected already. For four PhenoTypers, you have four rows for Top Unit Light and four rows for Top Unit Sound, depending on what you selected in the previous step. - Under Device Name, enter a name (e.g. PhenoTyper 1 Light) or accept the default name (A, B, C...). - For each Arena, select the corresponding Top Unit Light # or Top Unit Sound #. Scroll the table to the right when needed. Make sure that each Top Unit device is assigned to only one Arena (PhenoTyper cage), and that each Arena hosts only one Top Unit. Note: The term Top Unit Light indicates both white light and yellow light. You can choose which to activate in the Trial Control Settings. - For other devices, click Add device. - Repeat the steps above for the Noldus Lickometer, Pellet Dispenser, and PhenoWheel. - For a third-party TTL hardware device, under Device Type, select Custom Hardware. Enter a name under Device name and select one of the physical devices from the list for each Arena. For more information about this step, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. To Test a Device Click the name of the device you want to test, and click Test. Select the action you want to test and click Test. For more information on a device, see the PhenoTyper 2 - Service Manual. Trial Control Settings For more information on Trial Control, see Trial Control Settings in the EthoVision XT Help, and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. See also the chapter Common Tests with PhenoTyper. Detection Settings For more information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Phenotyper 2 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-phenotyper-2 Chapter: PhenoTyper Set Up an Experiment with PhenoTyper 2 For this section you need: - PhenoTyper 2 and the USB-IO box, or - PhenoTyper 2, the Nortio Core and the Nortio TTL Terminal Hub. Create an Experiment Prerequisites You have followed the section Set up PhenoTyper 2. Procedure - Choose File > New from Template. In the Select a template option window, select Apply a pre-defined template. - Follow the instructions in the guided setup. Under How is the arena configured, choose PhenoTyper (for one cage) or PhenoTyper, quad (four cages). After you have created the new experiment, you must still check and adjust Experiment Settings, Arena Settings and Detection Settings before you can track any animal correctly. Please follow the steps below. Experiment Settings Select the Cameras - In the Experiment Explorer, click Experiment Settings. - Under Video source, select the number of cameras from the list next to Number of sources. Select your cameras under Sources. For more information, see the EthoVision XT Help. Configure the Devices of PhenoTyper 2 (USB-IO Box) Follow this procedure if you have connected PhenoTyper 2 to EthoVision XT through the USB-IO box. With this setup you can control the white light. - In the Experiment Settings, next to Trial Control Hardware, select Use of Trial Control Hardware and click Settings. - In the window that pops up, select Noldus USB-IO Box and click OK. - In the Device Configuration window, locate the TTL Port of the USB-IO box that is connected to the PhenoTyper Control Unit (TTL 1). Note: The SDI ports do not work with PhenoTyper 2. - Under Device Type, select PhenoTyper 2 TTL 1 White Light (PT2I-01_TTL) to control the white light. To control another module, select one of the other options (PhenoTyper 2 TTL 2 Module or PhenoTyper 2 TTL 3 Module). Note that modules other than the White Light are not standard; you have to purchase them separately. - Repeat steps 3–4 for each PhenoTyper, then click OK. Configure the Devices of PhenoTyper 2 (Nortio Core + Nortio TTL Hub) Follow this procedure if you have connected PhenoTyper 2 to EthoVision XT through the Nortio Core + Nortio TTL Hub. With this setup you can control the white light. - In the Experiment Settings, next to Trial Control Hardware, select Use of Trial Control Hardware and click Settings. - In the window that pops up, select Nortio Core and click OK. - In the Nortio Configuration window, under Nortio Hub, expand the list and locate the TTL Port number connected to the PhenoTyper Control Unit. - Under Device, select Custom Hardware for the white light. Repeat this step for each PhenoTyper. In order to control the white light, you must connect Nortio Hub to the TTL 1 ports of the PhenoTyper Control Unit for all four PhenoTypers. Note: The items PhenoTyper Light and PhenoTyper Sound are for use with PhenoTyper 1. See also the Nortio system section in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Analysis Options - Activity analysis: Under Analysis Options, select Activity analysis to detect freezing behavior. - Behavior recognition: Under Analysis Options, select Behavior recognition. If you work with rodents, you can let EthoVision XT automatically detect behaviors like grooming, drinking, eating and rearing. This option requires the Rat/Mouse Behavior Recognition Module. Arena Settings For drawing arenas and zones, see the Arena Settings documentation. Assign the PhenoTyper Devices to the Arenas For this procedure you must have the Trial and Hardware Control Module. Open the Arena Settings and choose the section that applies depending on the interface device (either USB-IO box or Nortio Core + Nortio TTL Hub). Assign the Devices of PhenoTyper 2 (USB-IO Box) - In the Arena - Hardware Mapping window, you should see as many rows as devices added in the Experiment Settings. If not, click Add device for each device you want to add. For example, for four PhenoTypers, click Add device four times. - Under Device Type, select Top Unit (Standard) if it is not already selected. For four PhenoTypers, you should see four rows, each with Top Unit Standard selected. - Under Device Name, enter a name (e.g. PhenoTyper Light 1) or accept the default name (A, B, C...). - For each Arena, select the corresponding PhenoTyper 2 TTL 1 White Light #. Scroll the table to the right when needed. For multiple PhenoTypers: Make sure that each device is assigned to only one Arena (PhenoTyper cage), and that each Arena hosts only one of such devices. - For other devices, click Add device: - Repeat the steps above for the Noldus Lickometer, Pellet Dispenser, and PhenoWheel. - For a third-party hardware device, under Device Type, select Custom Hardware. Enter a name under Device name and select one of the physical devices from the list for each Arena. For more information about this step, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Assign the Devices of PhenoTyper 2 (Nortio Core + Nortio TTL Hub) - In the Arena - Hardware Mapping window, you should see as many rows as devices added in the Experiment Settings. If not, click Add device for each device you want to add. For example, for four PhenoTypers, click Add device four times. - Under Device Type, select Custom Hardware if it is not already selected. For four PhenoTypers, you should have four rows with Custom Hardware selected. - Under Device Name, enter a name (e.g. PhenoTyper Light 1) or accept the default name (Device A, Device B, etc.). - For each Arena, select the corresponding Custom Hardware #. Scroll the table to the right when needed. Make sure that each Custom Hardware # device is assigned to only one Arena, and that each Arena hosts only one of such devices. - For other devices, click Add device: - Repeat the steps above for the Noldus Lickometer, Pellet Dispenser, and PhenoWheel. - For a third-party TTL hardware device, under Device Type, select Custom Hardware. Enter a name under Device name and select one of the physical devices from the list for each Arena. For more information about this step, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Trial Control Settings For more information on Trial Control, see Trial Control Settings in the EthoVision XT Help, and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. See also the chapter Common Tests with PhenoTyper. Detection Settings For more information on Detection Settings, see Configure Detection Settings in the EthoVision XT Help. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Phenotyper® URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-phenotyper Chapter: PhenoTyper Introduction to PhenoTyper What Is PhenoTyper? Information in this document is subject to change without notice and does not represent a commitment on the part of Noldus Information Technology BV. The software described in this document is furnished under a license agreement. The software may be used or copied only in accordance with the terms of the agreement. Copyright © 2024 Noldus Information Technology BV. All rights reserved. No part of this publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any other language in whole or in part, in any form or by any means, without the written permission of Noldus Information Technology BV. PhenoTyper and EthoVision are registered trademarks of Noldus Information Technology BV. Other product names are trademarks or registered trademarks of their respective companies. April 24, 2024 — For EthoVision XT version 18 Noldus Information Technology BV International Headquarters Wageningen, The Netherlands Phone: +31-317-473300 Email: contact@noldus.com For addresses to our other offices, please see our web site. Contents Introduction to PhenoTyper - What Is PhenoTyper? - This and Other Manuals - Main Features of PhenoTyper - How Can I Use PhenoTyper? - What's New in PhenoTyper? - Advantages of PhenoTyper Compared with Ordinary Test Setups - Applications of PhenoTyper - PhenoTyper Configurations - Using Multiple PhenoTypers Assemble PhenoTyper - Before You Start - Assemble the Cage Set Up PhenoTyper 1 - Aim - Topics - Cables and Adapters - Connect One PhenoTyper to the PC - Connect Multiple PhenoTypers to the PC - Working with Groups of PhenoTypers - Connect Additional Devices - Lighting Conditions - Test the PhenoTyper's Functions - Adjust Light Intensity - Copy Light Intensity Values from One PhenoTyper to Another - The PhenoTyper Camera Set Up an Experiment with PhenoTyper 1 - Create an Experiment - Experiment Settings - Arena Settings - Assign the PhenoTyper Devices to the Arenas - Trial Control Settings - Detection Settings Set Up PhenoTyper 2 - Aim - Topics - Cables and Adapters - Connect One PhenoTyper to the PC - Connect Multiple PhenoTypers to the PC - 8-PhenoTyper Configuration - 16-PhenoTyper Configuration - Working with Groups of PhenoTypers - Connect Additional Devices - Lighting Conditions - Test the PhenoTyper's Functions - Adjust Light Intensity - The PhenoTyper Camera - Add a TTL-Controlled Module Set Up an Experiment with PhenoTyper 2 - Create an Experiment - Experiment Settings - Arena Settings - Assign the PhenoTyper Devices to the Arenas - Trial Control Settings - Detection Settings Common Tests with PhenoTyper - General Behavior Monitoring - Create Routines - Food Receiving Task - Illuminated Shelter Task - CognitionWall™ Task - Anxiety Tests - Other References Maintenance - Clean the Cage - Acceptable Cleaning Techniques and Substances - Substances That Can Damage PhenoTyper - Clean the Drinking Bottle - Clean the Top Unit - Recommended Materials Technical Support - Help Desk - Replacement of Components - Parts List Technical Specifications - PhenoTyper 1 - PhenoTyper 2 Declaration of Conformity - PhenoTyper 1 - PhenoTyper 2 Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Set Up Phenotyper 1 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-set-up-phenotyper-1 Chapter: PhenoTyper Cables and Adapters - A, B – Power cord and transformer. For PhenoTyper 1: code PT-PS1. - C – Power feed-through cable (code PT-PSC) for connecting multiple PhenoTypers. - D – Composite video cable of variable length with BNC connectors (code PT-BNCxx). For the complete list of components and their codes, see the components reference section. If you purchased the USB-IO box and the Top Unit Interface, you also have the following cables: - 1x Network cable, 1 m (green) - 4x Network cable, 2 m (green) - USB cable with connectors of type A and B - Power cord and DC adapter 24 V 3A Connect One PhenoTyper to the PC Power and Video - Connect the PhenoTyper's Supply In socket to the power outlet using elements A and B. - Connect the PhenoTyper's Video Out socket to one of the BNC connectors of the Euresys Picolo Alert encoder board installed on your computer, using a video cable with BNC connectors (D). Connect the video cables directly to the BNC connector on the board. For installing the Picolo Alert encoder board, see the EthoVision XT Help under Camera Installation > Install Analog Cameras. Control of Devices Using the USB-IO Box - Connect the USB port of the USB-IO box (or the Mini USB-IO box) to one of your PC's USB ports using the USB cable that comes with the (Mini) USB-IO box. - Connect the 24 V IN port of the (Mini) USB-IO box to the power outlet using its adapter. - Connect the SDI Control port of the USB-IO box (or the Mini USB-IO box) to the USB IO-box port of the Top Unit Interface, using the 1 m green network cable with RJ-45 connectors at its ends. - Connect the port of the Top Unit Interface to the TTL In port of PhenoTyper, using the 2 m green network cable with one RJ-45 connector and a SubD-9 connector at its ends. Control of Devices Using the Nortio System For this configuration you need: - The Nortio Core - The Nortio T12T TTL Terminal Hub - The interface cable NOCA-TU10. This cable is provided at one side with a Sub-D connector (for PhenoTyper) and at the other side with a box with two RJ-45 network ports. - One or two network cables, depending on how many PhenoTyper devices you want to control. Which PhenoTyper devices you can control depends on which ports on the NOCA-TU10 box you use and which Output line you specify in EthoVision XT. For example, to control the white light: - Connect Port 1 of the NOCA-TU10 box to a TTL port of the Nortio T12T TTL Terminal Hub. - In the EthoVision XT Experiment Settings, locate the TTL port number and from that list select Top Unit Light (NOCA-TU1x). - In the Arena Settings, map the TTL port on the corresponding PhenoTyper and assign a name to the device (e.g. PT 1 Port 1). - In the Trial Control Settings, specify to activate Output line 2 for the device PT1 Port 1. Connect Multiple PhenoTypers to the PC Power and Video - Connect the first PhenoTyper's Power Supply In socket to the power outlet using elements A and B. - Using three power feed-through cables (C), connect the Power Supply Out socket of the first, second, and third PhenoTyper to the Power Supply In socket of the next one respectively (1 out to 2 in, 2 out to 3 in, 3 out to 4 in). - Connect each PhenoTyper's Video Out socket to one of the BNC connectors of the Euresys Picolo Alert encoder board installed on your computer, using a video cable with BNC connectors (D). Connect the video cables directly to the BNC connector on the board. Resolution of each camera image: 768 x 576 (PAL Top Unit camera) or 640 x 480 (NTSC Top Unit camera). The resulting picture-by-picture video file created by EthoVision XT is 1536 x 1152 (PAL) or 1280 x 960 (NTSC). When using more than 4 PhenoTypers, connect each group of 4 PhenoTypers to a separate power outlet. Mix the Camera Images with a Quad Unit This section only applies to PhenoTyper 1 (analog camera). Use a video processor (Quad Unit) to mix video of 4 or 16 PhenoTypers. EthoVision XT will process the mixed image. You can work with this setup when you track live or from previously-recorded video files (offline). Important: If you track the subject's center-point, nose-point, and tail-base, mix maximally four video images. Otherwise the individual images become too small for accurate tracking. To mix four PhenoTyper images, you need one Quad Unit: - Connect the Video Out socket of each PhenoTyper to one of the Quad Unit's Video In sockets, using composite cables with BNC connectors. - Connect the Quad Unit's Video Out socket to one of the BNC connectors of the encoder board installed on the PC. To mix sixteen PhenoTyper images, you need four Quad Units: - Connect the Video Out from each group of 4 PhenoTypers to the video inputs of a Quad Unit. - Connect the four video outputs of the Quad Units to the inputs of the Picolo Alert encoder board on the EthoVision XT computer. Notes on resolution: - In your EthoVision XT experiment, define as many arenas as cages. - When using Quad Unit VM-Q401A and it does not display video, it may be set to the incorrect TV standard. Unplug the device from power. To select PAL mode, hold the Left arrow button on the front while plugging in the power supply. To select NTSC mode, hold the Right arrow button while plugging in the power supply. - Important: When you mix the camera images with a Quad Unit, the resolution of each camera view is one quarter of the original, because both the width and height are reduced to half. When using the Behavior Recognition function, check that the apparent size of the subjects in pixels is still acceptable. - When mixing four PhenoTyper images with a Quad Unit, the video resolution of each camera image is 384 x 288 (PAL) or 320 x 240 (NTSC). The resulting resolution of the picture-by-picture video file is 768 x 576 (PAL) or 640 x 480 (NTSC). - When mixing four camera images with the Picolo Alert encoder board, the original resolution is preserved. The resulting picture-by-picture video file is 1536 x 1152 (PAL) or 1280 x 960 (NTSC). - When mixing 16 PhenoTyper video images with Quad Units, the resolution of each camera image is 384 x 288 (PAL) or 320 x 240 (NTSC). The resulting picture-by-picture video file is 1536 x 1152 (PAL) or 1280 x 960 (NTSC). - Do not mix 16 camera images if you want to track the nose-point and tail-base point of rodents. Mix maximally four images. Record Video to Separate Video Files This section applies to both PhenoTyper 1 and PhenoTyper 2. You can use the MediaRecorder software to record video from each PhenoTyper to a separate video file. This setup is possible only if you track offline and have MediaRecorder. For details, see the MediaRecorder Help. - Once you have recorded video to separate video files, create a new EthoVision XT experiment. Choose Setup > Experiment Settings and under Video Source select From Video File. - Because each video file contains the image of one arena, under Number of Arenas select 1. - Load the video files in EthoVision XT and perform offline tracking. If you choose this setup, note that you cannot control hardware devices during offline tracking. In an alternative setup, you can do live tracking with hardware control and let EthoVision XT trigger video recording with MediaRecorder (see Trial Control in the EthoVision XT Help). Control of Devices Using the USB-IO Box - Connect the USB port of the USB-IO box (or the Mini USB-IO box) to one of your PC's USB ports using the USB cable that comes with the IO box. - Connect the 24 V IN port of the (Mini) USB-IO box to the power outlet using its adapter. - Connect the SDI Control port of the USB-IO box (or the Mini USB-IO box) to the USB IO-box port of the Top Unit Interface, using the 1 m green network cable with RJ-45 connectors at its ends. - Connect the ports of the Top Unit Interface to the TTL In port of the first, second, etc. PhenoTyper, respectively, using 2 m green network cables with one RJ-45 connector and a SubD-9 connector at their ends. By default, the USB IO-box is set to be connected with one Top Unit Interface only (and therefore four PhenoTypers) through SDI Control port 13. If you work with 8 to 16 PhenoTypers, you must use additional SDI Control ports. Connect the USB IO-box port of each Top Unit Interface to one of the SDI Control ports of the USB-IO box. Make sure that the IO-box is set correctly for communicating with multiple Top Unit Interfaces (see Jumper Settings in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, available from Windows Start > All Apps > Noldus > EthoVision XT 18 Other Documentation). Control of Devices with the Nortio System Follow this section if you have the Nortio Core and the Nortio T12T TTL Terminal Hub. You also need: - For each PhenoTyper, one interface cable NOCA-TU10. This cable is provided at one side with a Sub-D connector (for PhenoTyper) and at the other side with a box with two RJ-45 network ports. - For each PhenoTyper, one or two network cables, depending on how many PhenoTyper devices you want to control. Connect the Nortio T12T TTL Terminal Hub to the PhenoTypers as described in the single PhenoTyper connection section. Working with Groups of PhenoTypers You can set one to 16 PhenoTypers controlled by one EthoVision XT computer. When working with more than 4–16 PhenoTypers, it is advisable to use multiple computers. A common configuration includes groups of four PhenoTypers, each controlled by one PC. This optimizes throughput and video resolution, which ultimately affect data quality. Experiments Create one EthoVision XT experiment on each PC controlling a group of PhenoTypers. If you plan to conduct the same test with two or more groups of PhenoTypers, create a template experiment: - Choose File > New from Template. - Select the PhenoTyper configuration, including any zones of interest. - Draw the arenas and zones, and adjust the detection settings. - Choose File > Make Backup. Copy the backup file to the other computers controlling a group of PhenoTypers. - On each computer, choose File > Restore Backup. Save the experiment with a unique name, for example PhenoTyper Group A, B, C, etc. Assign Arenas to the PhenoTypers When you mix the image of 16 PhenoTypers (PhenoTyper 1) or 8 PhenoTypers (PhenoTyper 1 and 2), each group of four cages will be displayed in a quarter of the monitor window. In the mixed video image, group A with PhenoTypers 1 to 4 will be shown in the top-left corner. After creating an EthoVision XT experiment, define the number of arenas in the Experiment Settings (8 or 16). When opening the Arena Settings, arenas are sorted in rows, where the first row contains Arenas 1 to 4. To create a more logical correspondence between PhenoTyper number and Arena number, do one of the following: - Exchange the cables from the Quad Unit so that PhenoTypers of one group are displayed on the same row on the monitor. - Alternatively, in EthoVision XT, re-order the arenas by swapping arena positions: - De-select Arena 9 or other arenas in the Arena Settings panel to create temporary space. - Drag to select a rectangle around the first arena you want to move, including its zones and labels. Ensure you do not select zones of neighboring arenas. Drag the objects to a temporary position. - Move the second arena to its new position. - Move the first arena to its final position. - Repeat for other arenas that need to be swapped. Analyze Data from Multiple Experiments To analyze data from PhenoTypers across multiple groups, open a master experiment and import trials from the original experiments associated with those groups. Note that the settings in all experiments must be identical (for example, zone names) in order to import trials from multiple computers. For more information, see the topic Import Trials from Other Experiments in the EthoVision XT Help. Connect Additional Devices TTL Devices Use the USB-IO box (TTL Control panel) or the Nortio Core and the Nortio T12T TTL Terminal Hub to connect any TTL-compatible device, for example the Noldus Pellet dispenser. SDI Devices Use the USB-IO box (SDI Control panel) to connect SDI devices such as the Lickometer and PhenoWheel. Note: The Nortio system does not work with SDI devices. However, you can connect the Lickometer. See the PhenoTyper - EthoVision XT 18 - Service Manual. For More Information - For devices that work with PhenoTyper: the PhenoTyper - EthoVision XT 18 - Service Manual. - For the USB-IO box and the Nortio system: the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - For defining and mapping devices in your EthoVision XT experiment: the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Lighting Conditions PhenoTyper uses infrared as a light source. Because the camera is infrared sensitive and is provided with an IR-pass filter, EthoVision XT works independently of external light conditions (day vs. night). However, visible light also contains a variable amount of infrared frequencies which may be detected by the camera and compromise detection by EthoVision XT. For example, direct sunlight or light produced by incandescent bulb lamps contains a lot of infrared light. If you need extra visible light in your test room, use tube lamps or LED lamps, which produce little or no infrared light. This minimizes the amount of infrared light entering the PhenoTypers from outside. Test the PhenoTyper's Functions - To test the infrared light source, connect the video cable from PhenoTyper (or the Quad Unit if you work with multiple PhenoTypers) to a monitor or to the encoder board on your EthoVision XT computer. If connecting to the computer, create a new experiment, select Live Tracking in the Experiment Settings, select the camera input, and click the camera preview button to view the live camera image. Otherwise, proceed to step 2. - Connect the Control Unit to the PhenoTyper's Top Unit by attaching the Control Unit cable to the PhenoTyper's 15-pin Sub-D socket located on the front panel, next to the red LED. - Switch on PhenoTyper. The Control Unit's LCD display switches on. Some lamps may burn less intensely than others when first switched on — wait a few seconds until all lamps burn equally. - Press one of the Control Unit FUNCTION buttons one or more times to select the device (1 to 6). Each press changes the display as follows: - BUZZER - White LED - Yellow LED - IR array-1 - IR array-2 - IR array-3 The corresponding light turns on when selected. Do not press the TEST button at this point — doing so may change the light intensity by copying a value from another cage. - To test the buzzer, select 1 BUZZER and press the TEST button. Press TEST again to stop the buzzer. If sound does not work when you connect multiple PhenoTypers, the jumpers inside the Top Units may not be set correctly for EthoVision XT. For information on jumper settings, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Adjust Light Intensity Use the instructions below to change the intensity of light produced by PhenoTyper. If you need to customize the light intensity of two or more PhenoTyper cages, copy the light settings from one cage to the next. - Connect the Control Unit to PhenoTyper. - Switch on PhenoTyper. The Control Unit's LCD display switches on. Wait a few seconds until all lamps burn equally. - Press one of the Control Unit's FUNCTION buttons to select the device. Each press of the UP button cycles through: 1 BUZZER → 2 White LED → 3 Yellow LED → 4 IR array-1 → 5 IR array-2 → 6 IR array-3 → READ FROM PT → WRITE TO PT → 1 BUZZER. Check the light intensity directly (for yellow and white light) or through the camera image in EthoVision XT (for IR light). - Press the LEVEL buttons on the Control Unit to increase or decrease light intensity. Notes: - Values shown on the Control Unit screen range from 0 to 200 (in mA) for yellow and white lights, and from 0 to 100 for infrared lights. Even at a value of 0, the lights remain on at very low intensity. - Intensity values are stored in the non-volatile EEPROM memory of the PhenoTyper's Top Unit. Once set, values are retained even after power is turned off. - Measure light intensity with a light meter or a light meter app to ensure white/yellow light intensity is equal between cages and does not change over time. - You cannot change the intensity of the sound produced by PhenoTyper. - The duration of signals cannot be set from the Control Unit. Set this in EthoVision XT using Time Conditions in the Trial Control Settings. See the EthoVision XT Help and the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Copy Light Intensity Values from One PhenoTyper to Another This section only applies to PhenoTyper 1 (analog camera). You can copy the values of light intensity (infrared LED arrays and visible light spots) from one cage to other cages. If you want to copy only one value (for example, the intensity of the yellow light), first copy all values from the source cage, then write only the required value to the other cages. Read the Values from PhenoTyper - Connect the Control Unit to the PhenoTyper cage you want to copy the values from and switch on that cage. - Press the FUNCTION buttons until READ FROM PT is shown on the Control Unit display. - Press TEST. The Control Unit reads the light intensity values from all sources (IR, yellow, and white). The yellow and white lights switch on and the display shows READING... until the reading process is completed. - Follow one of the procedures below to copy the values to the other cages. Write All Values to PhenoTyper - Connect the Control Unit to the PhenoTyper cage you want to copy the values to and switch on that cage. - Press the FUNCTION buttons until WRITE TO PT is shown on the Control Unit display. - Press TEST. The Control Unit writes the light intensity values for all sources (IR, yellow, and white) to the cage. The display shows WRITING... until the writing process is completed. If a copied value differs from the value currently set in the cage, the Control Unit display shows Increase... or Decrease... while the intensity is adjusted to match. When the display shows WRITE TO PT again, all values are updated. Repeat the procedure to copy values to other cages. Write a Single Value to PhenoTyper - Ensure you have already read the light intensity values from a source cage. - Connect the Control Unit to the PhenoTyper cage you want to copy the value to and switch on that cage. - Press the FUNCTION buttons until the desired light device is selected. - Press TEST. The Control Unit writes the light intensity value to the cage. If you selected yellow or white light, these switch on briefly. The display shows WRITING... until completed. If the copied value differs from the current value in the cage, the display shows Increase... or Decrease... until the adjustment is complete. When the display shows WRITE TO PT again, the value is updated. Repeat for other cages. Example: To copy the light intensity value of IR array-1 from cage 1 to cage 2: - Connect the Control Unit to cage 1 and read the values. - Connect the Control Unit to cage 2 and press the FUNCTION buttons until 4 IR array-1 is displayed. - Press TEST. - When the display shows 4 IR array-1 again, the value is updated. The PhenoTyper Camera Camera Orientation If the camera does not point to the center of the cage bottom and some parts of the cage (such as the feeder) are not sufficiently visible, you can change the orientation of the camera. For more information, see the PhenoTyper - EthoVision XT 18 - Service Manual. Lens Focus If the camera image is out of focus: - The camera is in the center of the Top Unit's covering plate. Remove the ring around the lens and rotate the lens ring. - Place the test animal (or an object of approximately the same height) in the cage. - Place the Top Unit back on the cage. Check in EthoVision XT that the test animal or object is in focus. If you have an NTSC Top Unit with serial number 01000 or below, you must remove the covering plate. Turn off PhenoTyper, unscrew the covering plate, loosen the small screw on the lens, and then rotate the focus ring. When closing the Top Unit, do not over-tighten the first screws, as this may make it difficult to place the remaining ones correctly. Instead, insert two or three screws on different sides of the plate and turn them 2–3 times, keeping the plate free to move. Adjust the plate so the remaining screws align with their holes before tightening. Additional Settings for PhenoTyper 1 Although the PhenoTyper camera is optimized for video tracking, there may be cases when you need to adjust camera settings. For example, when the image of the animal is too bright, you can switch off the Automatic Gain Control and adjust the shutter speed. - PhenoTyper Top Units with a serial number between 01051 and 01412 are equipped with OSD functionality. For details, see the PhenoTyper - EthoVision XT 18 - Service Manual, under The PhenoTyper Top Unit Camera > Camera Settings. - For Top Units with a serial number above 1470, contact Noldus to order an OSD controller. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 - Set Up Phenotyper 2 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-set-up-phenotyper-2 Chapter: PhenoTyper Cables and Adapters - A, B – Power cord and transformer: For PhenoTyper 2: code MAPS-0014. - C – Power feed-through cable: For connecting two PhenoTypers. For PhenoTyper 2: code PT-PSC. - D – Cross network cable with RJ45 connectors for connecting the digital camera to the EthoVision XT PC. If you purchased the USB-IO box, you also have the following cables: - Network cables (as many as PhenoTyper Top Units). - USB cable with connectors of type A and B. - Power cord and DC adapter 24 V 3A for the USB-IO box. Connect One PhenoTyper to the PC Power and Video - Connect the PhenoTyper's IN socket to the power outlet using elements A and B. - Connect the camera's Ethernet socket to one of the ports of the Ethernet interface board on your computer, using a cross-network cable with RJ-45 connectors. - Set the IP address in the digital camera and the port on the Ethernet interface board. See Configure the Digital Camera in the EthoVision XT Help or watch the video tutorial Set Up Your Cameras in EthoVision XT. Control of the White Light with the USB-IO Box Follow this section if you have the USB-IO box. - Connect the USB port of the USB-IO box to one of your PC's USB ports using the USB cable that comes with the IO box. - Connect the TTL 1 port (or another one available) of the USB-IO box to the TTL 1 port of the Control Unit of the PhenoTyper Top Unit. - Make sure that the USB-IO box is connected to the power outlet. Control of the White Light with the Nortio System Follow this section if you have the Nortio Core and the Nortio TTL Terminal Hub. - Connect the Nortio Core Ethernet port to the Ethernet port of your PC using a network cable. The IP address of the Ethernet port on your PC must be configured in order to communicate with the Nortio Core. See the chapter The Nortio System in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Connect the 24 V IN port of the NortIO Core to the power outlet using its adapter. - Connect the NortIO Core to the Nortio T12T TTL Terminal Hub using the matching Backbone input cable. - Connect a TTL port on the Nortio T12T TTL Terminal Hub to the TTL 1 port of the PhenoTyper Control Unit, using a network cable. The TTL port is configured to control the white light. - If you have additional devices like pellet dispensers, connect those devices to available TTL ports of the Nortio T12T TTL Terminal Hub. Notes: - For information about the USB-IO box, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - At the time of release of PhenoTyper 2, control is limited to the PhenoTyper white light. Contact Noldus to discuss possible extensions. Connect Multiple PhenoTypers to the PC Power and Video - Connect the first PhenoTyper's 24 VOLT IN socket to the power outlet using elements A (MAPS-0014) and B. Repeat this step for every other PhenoTyper in the group, that is, the first of each pair. - Important: Connect a maximum of two PhenoTyper Top Units to the same power supply. - Using power feed-through cables (C), connect the 24 VOLT OUT socket of the first PhenoTyper to the 24 VOLT IN socket of the second. Connect the 24 VOLT OUT socket of the third PhenoTyper to the 24 VOLT IN socket of the fourth, and so on. - Connect each PhenoTyper's camera to one of the ports of the Ethernet interface board on your computer, using a cross-network cable with RJ-45 connectors (D). Notes: - Resolution of each camera image: 1280 x 1024. When using four PhenoTypers, the resolution of the resulting video is 2560 x 2048. - When using more than two PhenoTypers, connect each pair of PhenoTypers to a separate power outlet. - The maximum resolution attainable in your system also depends on the frame rate and the tracking methods. Open the EthoVision XT Help (press F1 in the software) and see the topic GigE Cameras for a list of tested configurations. Video Resolutions That Work in PhenoTyper 2 - 1 camera: Single camera 1280 x 1024 - 2 cameras: Single camera 1280 x 1024, merged view 2560 x 1024 - 4 cameras: Single camera 1280 x 1024, merged view 2560 x 2048 - 8 cameras: Single camera 640 x 480, merged view 2560 x 960 - 16 cameras *: Single camera 640 x 480, merged view 2560 x 1920 * Set frame rate to 25. Higher frame rates may result in camera connection being lost. Control of Devices with the USB-IO Box - Connect the USB port of the USB-IO box to one of your PC's USB ports using the USB cable that comes with the IO box. - Connect the 24 V IN port of the USB-IO box to the power outlet using its adapter. - Connect a TTL port on the USB-IO box to the TTL 1 port of each PhenoTyper, using the network cables with RJ-45 connectors. This line controls the white light. - If your PhenoTypers have additional modules that can be controlled through TTL, connect the TTL ports of the USB-IO box to the TTL ports of each PhenoTyper. Control of Devices with the Nortio System - Connect the Nortio Core's Ethernet port to the Ethernet port of your PC using a network cable. The IP address of the Ethernet port on your PC must be configured in order to communicate with the Nortio Core. See the chapter The NortIO System in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Connect the 24 V IN port of the NortIO Core to the power outlet using its adapter. - Connect the Nortio Core to the Nortio T12T TTL Terminal Hub using the matching Backbone input cable. - Connect a TTL port on the Nortio T12T TTL Terminal Hub to the TTL 1 port of each PhenoTyper, using network cables. The TTL 1 port is configured to control the white light. - If your PhenoTypers have additional devices like pellet dispensers, connect those devices to the available TTL ports of the Nortio T12T TTL Terminal Hub. 8-PhenoTyper Configuration To connect your EthoVision XT computer to eight PhenoTyper cameras, make the video connections in one of the following ways: - Video connections with two 4-port Ethernet boards - Video connections with one 4-port Ethernet board and two network switches Video Connections with Two 4-Port Ethernet Boards Prerequisites: - Only use Ethernet network interface boards with at least 1Gb Ethernet ports. See the suggestions in the section Camera Installation in the EthoVision XT Help. - The Ethernet network interface boards must provide Power over Ethernet (PoE) to the cameras. Alternatively, you must connect each camera to the board through a separate PoE injector with its own power plug. Procedure: - Install the two boards on the PC and assign a unique IP address to each port. For example, use 192.168.x.x with subnet mask 255.255.255.0 for all ports. - Connect one group of four PhenoTypers to one board, and the other group to the second board. - Assign IP addresses to the cameras that match the IP address of the ports of the Ethernet board, with subnet mask 255.255.255.0 for all ports. Important: Keep the first two numbers 192.168 of the IP address for all ports and cameras. The third number of the IP address must be unique for each camera–Ethernet port combination. Video Connections with One 4-Port Ethernet Board and Two Network Switches Prerequisites: - Only use network switches with at least 1Gb Ethernet ports. The Ethernet network interface board must also have 1Gb ports. See the suggestions in the section Camera Installation in the EthoVision XT Help. - The network switches must have at least n+1 Ethernet ports, where n is the number of PhenoTypers connected to the switch. For example, use 2x 5-port switches. - The network switches must provide Power over Ethernet (PoE) to the cameras. Alternatively, connect each camera through a separate PoE injector. - The network switches must be able to handle large packets (jumbo packets or jumbo frames), with a maximum packet size of up to 16 kB. - For maximum network efficiency, configure your camera to use the largest packet size that your network adapters and switches can handle. Procedure: - Install the Ethernet network interface board on the PC and the network switches. - Connect each PhenoTyper camera to an Ethernet port of the network switch (four cameras per switch). - Connect the network switches to two ports of the Ethernet board. - Assign a unique IP address to each port on the network switch that is connected to a camera. - Assign an IP address to each camera that matches the first three numbers of the IP address of the port on the network switch to which that camera is connected. Important: Keep the first two numbers 192.168 of the IP address for all ports and cameras. Notes: - The maximum power provided by a switch (in Watts) must be greater than the total requirements of the cameras (one Basler camera requires about 2.5 W) and the other devices connected to the switch. - For information on how to assign IP addresses, see Install the GigE Camera in the EthoVision XT Help. - Refer to the user guide of the network switch for setup instructions. Video Resolution for 8-PhenoTyper Configuration - Single camera view: 640 x 480 - Merged 8-camera image: 2560 x 960 To set the resolution, open the Experiment Settings, under Video Source select Live Tracking and choose 8 as the number of sources. Select all cameras and make sure the resolution of single cameras is 640 x 480 and the merged camera view is 2560 x 960. 16-PhenoTyper Configuration Prerequisites: - You have four network switches with at least 5 network ports, and one 4-port Ethernet interface board installed on the EthoVision XT computer. - See the prerequisites for network switches described in the 8-PhenoTyper configuration section. Procedure: - Connect the PhenoTyper cameras to the network switches and the switches to the PC. See also the procedure for the 8-PhenoTyper configuration. - When assigning IP addresses, make sure that the third number of the IP address of the cameras and the network switch is the same within each group of four PhenoTypers, and unique across groups. Video Resolution for 16-PhenoTyper Configuration - Single camera view: 640 x 480 - Merged 16-camera image: 2560 x 1920 To set the resolution, open the Experiment Settings, under Video Source select Live Tracking and choose 16 as the number of sources. Select all cameras and make sure the resolution of single cameras is 640 x 480 and the merged camera view is 2560 x 1920. Tip: Put a sheet with a number in each PhenoTyper cage so you can easily identify which camera has been selected. Select the first four cameras for group 1, then the fifth to eighth for group 2, and so on. Tested Configuration - System: Dell Precision 3660 with 12th Gen Intel Core i7-12700K, 3.6 GHz, 12 cores, 20 logical processors, 8 GB RAM, Windows 11 Pro - Video resolution: As specified above - Camera frame rate: 25 fps - Trial duration: 48 hours This configuration resulted in no missing samples. Increasing the resolution may lead to a high percentage of missing samples and/or loss of camera connection during the trial. Working with Groups of PhenoTypers With PhenoTyper 2 you can have up to eight cages (and cameras) connected to one PC. See the section on working with groups of PhenoTypers for further details. Connect Additional Devices You can have EthoVision XT control PhenoTyper and additional devices. See the section Connect Additional Devices for further details. Lighting Conditions The general recommendations about lighting in the test room for PhenoTyper 1 are also valid for PhenoTyper 2. See the Lighting Conditions section for further details. Test the PhenoTyper's Functions Camera Image and the Infrared Light Source - Connect the network cable from the PhenoTyper camera to one of the ports of the Ethernet interface board on the EthoVision XT computer. For information on how to set up IP addresses, see the EthoVision XT Help. - Start EthoVision XT, create a new experiment, then in the Experiment Settings select Live Tracking, select the camera input, and click the camera preview button. You should see the live camera image. - Switch off all the light in the room. If the infrared light source works properly, you should see a clear image of the cage bottom. White Light - Press the White - Test button on the front panel of the Control box. - Check that the light inside the cage switches on. Adjust Light Intensity Adjusting Infrared Light Intensity You need the trimmer adjustment tool provided with the PhenoTyper Top Unit, or a small screwdriver. - Connect the network cable from the PhenoTyper camera to one of the ports of the Ethernet interface board on the EthoVision XT computer. For information on how to set up IP addresses, see the EthoVision XT Help. - Start EthoVision XT, create a new experiment, and in the Experiment Settings select Live Tracking, then select the camera input from the list and click the camera preview button. You should see the live camera image. - Turn the IR control on the Control box. - Check the image in the EthoVision XT screen. Adjusting White Light Intensity - Turn the White control on the Control box. - Check the intensity of the white light in the cage. Make sure that the white light intensity is equal between cages and does not change over time (unless for reasons related to the experimental treatment). Tip: Measure light intensity with a light meter or a light meter app for smartphones. Repeat the procedure for each cage. The PhenoTyper Camera Lens Focus The camera focus is optimized at production. For more information on the camera and lens, see the PhenoTyper 2 - Service Manual. Advanced Camera Settings The Basler acA1300-60gm is the default camera of PhenoTyper 2. For extensive information on camera settings (resolution, frame rate, exposure, gain, etc.) and for how to install and configure the camera in EthoVision XT, see Install GigE Cameras in the EthoVision XT Help. Add a TTL-Controlled Module Overview To control an additional TTL device, such as a spotlight. The type of control is currently limited to On/Off. You can have EthoVision XT switch the spotlight on and off; however, you cannot adjust the light intensity through the software. Fit the New Module on the Top Plate - Remove the cover plate from one of the slots of the Top Plate. - Insert the module and gently press it so that the connectors come into contact. - Fix the module with the two screws. Current TTL Ports Configuration - TTL 1 is reserved for the PhenoTyper white light. It is not available for use with other modules. - TTL 2 and TTL 3 are set to output by default. Through these ports you can have EthoVision XT send On/Off commands to the device you have added. The signal goes from EthoVision XT to the device through the (mini) USB-IO box or the Nortio TTL Hub. In EthoVision XT Trial Control Settings, choose Output Line 1 for that device. - TTL 4 is currently not available. Note: The name Output Line refers to the internal lines that you can set for each port of the interface device (the Mini USB-IO box or the Nortio TTL Hub). In general, for each port two output lines (Output Line 1 and Output Line 2) and two input lines (Input Line 1 and Input Line 2) are available. These can be specified in the EthoVision XT Trial Control Settings. For PhenoTyper 2, only Output Line applies currently. For more details, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Advanced Solutions If you need additional configurations, contact your nearest Noldus representative. Source: PhenoTyper - EthoVision XT 19 Reference Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 2.1 Phenotyper 1 (Analog Camera) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-21-phenotyper-1-analog-camera Chapter: PhenoTyper Camera Focus and Orientation Adjust the Camera Focus If the camera image is out of focus: - The camera is in the center of the Top Unit's covering plate. Remove the ring around the lens, so you can easily access the focus ring on the lens. - Rotate the focus ring in either direction. - Put the test subject, or an object of approximately the same height, in the cage. - Put the Top Unit back on the cage. Turn PhenoTyper on and check in EthoVision XT that the test animal/object is on focus. - Repeat steps 2 to 4 until the image is sharp enough. Note: If you have a NTSC Top Unit with serial number below 01000, you have to remove the Top Unit covering plate. Turn off PhenoTyper, unscrew the covering, and loosen a small screw on the lens, then rotate the focus ring. Important: When closing the Top Unit, do not over-tighten the first screws. Doing so may make it difficult to put the remaining ones in the right place. Instead, insert first two or three screws on different sides of the plate, and turn them 2–3 times. The separation plate should be still free to move at this stage. Move the plate so that the remaining screws can fit in the corresponding holes. Adjust the Camera Orientation If the camera does not point to the center of the cage bottom, and some parts of the cage like the feeder are not visible enough, you can change the orientation of the camera. The information below applies to PhenoTyper top units manufactured after March 2011. In top units from previous batches, it was not possible to adjust the camera orientation. If you want to upgrade an older unit, please contact your sales person for a quote. Required Tools: - A 2.5 mm Allen key (also known as a hex or Inbus key) - A small flat-head screwdriver - A straight edge of approximately 40 cm - Marker pen with washable ink - Post-it stickers Procedure: - Remove the top unit from the PhenoTyper cage. - Carefully remove the four black caps next to the camera (if necessary, use the screwdriver). - Remove one wall of the PhenoTyper cage. - On the base of the PhenoTyper cage, draw lines between each corner so that they intersect precisely in the center of the floor plate. If the base is black, you can tape paper to it and draw on the paper. Alternatively, tape an image to the floor plate to make focusing easier. - Place the top unit upside-down and the cage on top of it, so the entire setup is upside down. - Connect the camera connection of the PhenoTyper Top Unit to your computer so that you can view the image. - Determine the center point of your computer monitor: - Open this document in a PDF viewer (e.g. Adobe Reader). - Maximize the PDF viewer window. - View in Full Screen mode (press Ctrl+L). - Zoom to Fit Width (press Ctrl+2). The image is now centered horizontally. - Scroll until the image is centered vertically. - Mark the center point, for example with two stickers. Do not write on the monitor screen. - If necessary, focus the camera. To do so, remove the ring next to the camera lens and rotate the lens. If you have an NTSC Top Unit camera, you have to remove the plastic plate and loosen a small screw on the lens. - Insert the Allen key into each of the holes and turn until the image from the camera is centered on the cross you have drawn on the cage base. - If necessary, re-focus the camera. - When the image quality is satisfactory, put the caps back in place, remove the lines you have drawn or the test sheet, and reassemble the cage. If you need assistance with this procedure, please contact your nearest Noldus support center at my.noldus.com. Camera Settings When to Adjust the Camera Settings Since the PhenoTyper Top Unit camera is optimized for video tracking with EthoVision XT, it will not be necessary to adjust the camera settings under most conditions. However, there may be exceptions. For example, when you track a white rat on dark bedding material, the animal's body may appear overlit due to automatic gain adjustments. You can change the camera settings based on the instructions below. If you still have questions, contact Noldus Support for guidance at my.noldus.com. A common scenario that may require adjustment of the camera settings is when the image of the animal is too bright. When you carry out video tracking only, it is usually no problem if the animal is overlit. However, if you need to know details of the behavior — for example for manual scoring — you need an image with good contrast and details of the animal's body. When using the Mouse or Rat Behavior Recognition Module, it is essential that details of the animal's body and fur are visible and sharp. In such situations, do not decrease the infrared light level in the PhenoTyper, since this will only cause the camera to compensate more. Switch off the automatic gain control and adjust the shutter speed. To reset the camera to its default settings, refer to the camera reset instructions. The Camera On-Screen Menu To access the camera on-screen menu for PhenoTypers with serial number 001471 and higher (from 2018 onwards), you need the UTC-100 on-screen device (OSD). Please contact Noldus if you do not have this device. Connect the OSD between PhenoTyper and a monitor (or PC video encoding board). Use video cables with BNC connectors, just like you do when connecting PhenoTyper to the PC. For details, see the PhenoTyper Reference Manual. - Press the central button to enter a menu or confirm a selection. - Press the Down button to navigate the menu, and the Left/Right buttons to switch between options. Note that Move Up does not have any effect. - Remember to select Save and Exit to confirm. To open the camera settings menu: - Start EthoVision XT, and in the Experiment Settings click the video icon in the row of your camera under Video Source. The live image from the PhenoTyper Top Unit camera appears. - Press the central button of the OSD. The on-screen menu appears. - By default, the first menu item, EXPOSURE, is selected. Important Camera Settings - AGC (Automatic Gain Control): Switch this off when the image of the animal is overlit. - Shutter: Adjust this if the image of the animal is overlit. Switch off Automatic Gain Control before adjusting the shutter. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 2.1 Phenotyper 1 (Analog Camera) (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-21-phenotyper-1-analog-camera-continued Chapter: PhenoTyper PhenoTyper 1 (Analog Camera) AGC (Automatic Gain Control) Using AGC means that weaker video signals receive more gain and stronger signals receive less gain or none at all. For a white animal on a dark background, it is beneficial to turn the AGC off, so that the subject does not appear overlit. For a dark animal on a bright background, the effect of AGC is less evident. Another disadvantage of setting AGC to On is that with a high gain the noise is also increased, and with it the file size of the resulting video. This is because a noisy video contains a lot of unpredictable movement (the noise) that has to be encoded and increases file size. - Select EXPOSURE, then AGC. - To disable AGC, press the Left/Right button to select OFF. - Connect the PhenoTyper Control Unit to increase the infra-red light to maximal (see the PhenoTyper - EthoVision XT 18 - Reference Manual). Then adjust the Shutter time (see below). Shutter The shutter time influences the brightness of the picture. - Select EXPOSURE, then SHUTTER. - Press the Left/Right button until 1/120 is selected. If the subject image is overlit, first switch off the Automatic Gain (see above). Then set the shutter to a value as small as possible. The subject should contrast well with the background and the image should have enough lighting. In most cases, 1/100 or 1/120 will work well. Flicker - Select EXPOSURE, then FLICKER and press the central button to confirm. - Depending on which TV standard your Top Unit camera is, choose 50 for PAL and 60 for NTSC. White Balance White balance is not crucial for a black and white camera like that of PhenoTyper. Adjusting settings will hardly result in a different image. We recommend leaving the settings at the default. Image & Setup Select IMAGE SET then press the central button to confirm. - Contrast: Adjust the image contrast by pressing the Left/Right button. - Sharpness: Adjust the image sharpness by pressing the Left/Right button. Save & Exit - Select SAVE & EXIT then press the central button to confirm. - Select YES, then press the central button to confirm. Select No to exit the menu without saving the settings. Reset This option resets the camera settings back to its default settings that are optimal for the PhenoTyper. - Select RESET then press the central button to confirm. - Under Factory mode, select YES and press the central button to confirm. For more information refer to the documentation that comes with the UTC-100 control device. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 2.2 Phenotyper 2 (Digital Camera) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-22-phenotyper-2-digital-camera Chapter: PhenoTyper PhenoTyper 2 (Digital Camera) The PhenoTyper 2 camera is a Basler acA1300-60gm GigE Vision monochrome camera. To install and configure the camera, see one or more of the following: - The section Camera Installation in the EthoVision XT Help (F1). - The video Set Up your Camera in the EthoVision XT Video Tutorial (Help menu). - The PhenoTyper - EthoVision XT 18 - Reference Manual. Package Contents - Basler acA1300-60 gm. - Evetar 4 mm lens. - IR filter (already mounted on the camera). - CS to S-mount adapter. - Camera bracket. - 4 x M3 4 mm bolts for fixing the camera to its bracket. - 2 x M3 6 mm bolts for fixing the bracket to the PhenoTyper Top Plate. Camera Module You can fit the camera module in the central slot of the Top Plate. To insert or remove the camera module, use the four screws at its corners. The margin of the camera module is made in such a way that there is only one possible orientation - with the bracket facing opposite the Control Unit and the PhenoTyper logo. Power Up the Camera The PhenoTyper 2 camera gets power through the network cable that connects to the PC. You can power up the camera in two ways, depending on whether the Ethernet interface board received power from the PC: - If the Ethernet interface board does not receive power from the PC, you must use Power over Ethernet (PoE) injectors. This usually is the case for one- or two-port boards. - If the Ethernet interface board on the PC can receive power from the PC, like in the case of a 4-port board provided by Noldus, you can connect the camera directly to the board, but you must provide power to that board using an additional power cable connection inside the PC. For details, see the topic Install an Ethernet Board for the GigE Camera in the EthoVision XT Help. If the board has been installed by Noldus, the board is already powered so you just need to connect the cameras. Camera Focus and Orientation Camera Focus The lens of the PhenoTyper 2 camera is a F1/8 f4 mm fixed focal length, fixed iris lens. The focus of the lens has been optimized for the PhenoTyper cage. Note: The lens is a S-mount type lens. It is therefore provided with a CS-mount to S-mount adapter to fit on the camera. Always make sure that the camera has this adapter attached when, for any reason, you remove the lens from the camera and then put it back. Camera Orientation The orientation of the digital camera has been carefully set at production. There is no need to adjust it. Camera Settings The main camera settings can be adjusted in the Pylon Viewer dedicated software after the camera has been configured and connected to the PC. Alternatively you can adjust camera settings like Exposure and Frame Rate in EthoVision XT. For details, see the section Configure the Digital Camera in the EthoVision XT Help (F1). General Information Note: The Top Unit Interface is used in PhenoTyper 1. You can skip this chapter if you work with PhenoTyper 2. Components The Top Unit Interface is needed whenever you want to control multiple PhenoTypers with EthoVision XT. You also need the USB-IO Box. You can connect up to four PhenoTypers to a Top Unit Interface. For information about the USB-IO box, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. The Top Unit Interface is meant for use together with PhenoTyper 1, not PhenoTyper 2. The Top Unit Interface comes with: - One 1-m modular cable RJ45 (green) for connecting the Top Unit Interface to the USB-IO box. - Four 2-m modular cables RJ45 (green) with a SubD-9 adapter to connect the Top Unit Interface to the PhenoTypers' Top Unit. - A USB extender cable (20 m), in case you need a longer distance between your computer and the PhenoTyper setup than the 3 m of a standard USB cable. It is possible to order longer cables, but the cable between the Top Unit Interface and the USB IO-Box should not be longer than 2 m. The cable between the Top Unit Interface and the PhenoTyper should not be longer than 5 m. LED Indicators - Busy (yellow LED): Indicates data exchange to/from a PhenoTyper Top Unit. - Power (red LED): Indicates power supply from the USB-IO box through the modular RJ45 cable. Technical Specifications - Noldus Type Number: PTTI-001x - Power Supply: 12V DC supplied by the USB-IO box - Current Consumption: 40 mA - Connectors: 1x RJ45 8-pin modular to USB-IO box, 4x RJ45 8-pin modular to PhenoTyper Top Units - Dimensions: 115 x 65 x 32 mm / 4.5 x 2.6 x 1.3 inches (L x W x H) - Weight: 100 gr - Cable to USB-IO Box: 1x 1m modular RJ45 (green) - Cable to PhenoTyper Top Unit: 4x 2m modular RJ45 (green) with SubD-9 adapter Connect the Top Unit Interface Connection Scheme - Connect the USB-IO box port on the Top Unit Interface to the SDI Control port on the rear panel of the USB-IO box. - Connect the USB port on the USB-IO box to one of the USB ports of the EthoVision XT computer. - Make sure that the USB-IO box is powered up. - Connect the PhenoTyper Top Unit 1 port on the Top Unit Interface to the TTL in port of the first PhenoTyper, using the network cable with a SubD connector at one end (PhenoTyper Top Unit) and a RJ45 connector at the other end (Top Unit Interface). - Repeat the previous step for the remaining Top Units. Notes - The Top Unit Interface is designed for use with PhenoTyper 1. - For more details on how to connect PhenoTyper to the EthoVision XT computer, see the PhenoTyper - EthoVision XT 18 - Reference Manual. - If you want to connect multiple Top Unit Interfaces to your EthoVision XT computer, you must alter the position of jumpers inside the USB-IO box. For more information, see The USB-IO Box in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 4.1 General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-41-general-information Chapter: PhenoTyper General Information The Pellet Dispenser The Noldus Pellet dispenser is a device to deliver standard available pellets to mice or rats. It can be used in learning tests to reward the animals when they perform a task well. The Pellet dispenser can be controlled from EthoVision XT to drop pellets automatically when a condition becomes true, for instance, when the animal enters the feeder zone within 30 seconds after a light was switched on. The Pellet dispenser consists of two parts, a pellet silo and the base part with the stepper motor. The Pellet dispenser is often used in combination with the Pellet receptacle. Button and LED Indicator Press the button to drop one pellet. For controlling the Pellet dispenser with EthoVision XT, see Work with the Pellet Dispenser. The LED light at the front of the pellet dispenser indicates the status of the device: - LED off: Waiting for command. - Single blink: Receiving a pellet drop command. Single blink is also given when a pellet is dropped. - Double blink: When connecting the power cable/RJ45 cable or resetting. - Continuous, fast blinking: Error state. - LED constant on: Detector is stuck. Contents of the Pellet Dispenser Packages Pellet Dispenser (Standard) - A Pellet dispenser PTPD-001x. - Additional blue carousel for 45 mg pellets. - A gray RJ45 cable (2 meters long). - Aluminium feed-through and silicon in-between tubing. Optionally available: - Elevated stand (PTPD-1050). - Power supply for stand-alone use (PTPD-2010). - RJ45 modular cable 0.5 - 3 meters, different colors. Note: Beginning in 2016, Noldus introduced the Pellet dispenser PTPD-0011, successor of PTPD-0010. The main differences are: - A more accurate drop positioning system. - Two types of carousels, both with 10 holes: - White carousel, for 20 mg pellets, is installed by default. - Blue carousel, for 45 mg pellets. If you have a previous version of the Pellet dispenser PTPD-0010, the carousel has 12 holes. You cannot exchange carousels between Pellet dispenser versions. Pellet Receptacle - The Pellet receptacle PTPR-001x. - PhenoTyper wall specific for a Pellet receptacle. - A black cable with a RJ45 connector at one end and a white 3-pin female connector at the other end (2 m long). Accessories - Aluminium feed-through and silicon in-between tubing. - Silica gel pack to keep the silos dry. - Elevated stand (not included in the standard package). Pellet Types The Noldus Pellet dispenser has been tested with the following pellets: - Bio-Serv 20 mg (3.2 mm x 2.5 mm; product nr. F0071 and F0163). - Bio-Serv 45 mg (3.6 mm diameter; product nr. F0021). - TestDiet 20 mg (3.2 mm x 2.6 mm). See bio-serv.com and testdiet.com. To Switch Between Pellet Types When you receive the Pellet dispenser, it is equipped with the white carousel for 20 mg pellets. Before using pellets of different size, do the following: - Remove the pellet silo from the base of the Pellet dispenser. - Remove the lid of the silo. - Gently press the white plastic insert out of the transparent silo. - Use the hex key to remove the carousel cover plate. - Replace the carousel. - Close the cover plate of the carousel, tighten the bolts and reassemble the silo. - When assembling the Pellet dispenser, make sure that the aluminium hole cover clip inside the silo is aligned with one of the holes. This makes it less likely that multiple pellets are dropped simultaneously. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 4.2 Install The Pellet Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-42-install-the-pellet-dispenser Chapter: PhenoTyper Install the Pellet Dispenser Although the network cables shown in the following schemes are used in networks, the signal from and to the Pellet dispenser is not a network signal. Do not connect the Pellet dispenser via a network hub or similar. Connect the Pellet Dispenser Using the USB-IO Box Connect the Pellet dispenser to a TTL port on your USB-IO box or Mini USB-IO box using the network cable with RJ45 connectors. Connect the Pellet Dispenser Using the Nortio System - Connect the Nortio Core to the EthoVision XT through a network cable. - Connect the Nortio T12T TTL Terminal Hub to the Nortio Core using the backbone input cable. - Connect the Pellet dispenser to one of the TTL control ports of the Nortio T12T TTL Terminal Hub. For how to install the Nortio system and configure the Ethernet board on your PC, see the section The Nortio System in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Connect the Pellet Dispenser Using the Mini USB-IO Box With EthoVision XT 14 and later versions, you can use the Pellet dispenser also when connected to the Mini USB-IO box. Important: Connect maximally two Pellet dispensers to a Mini USB-IO box. Before connecting the devices, do the following: - Browse to my.noldus.com (you need to log in or register first), and choose Downloads > EthoVision XT. Download EthoVision XT - Full installation disc [version number].zip. Unzip the file and locate the folder Drivers and Tools > IoBox MiniIoBox Devices. There you will find the file MiniIoBox PelletDispenser. - Open the folder MiniIoBox PelletDispenser and copy one of the files depending on the language set in EthoVision XT: - For Chinese: DeviceTypesNoldusChCh.xml - For English: DeviceTypesNoldusEnUs.xml - Go to the following folder on your EthoVision XT computer: C:\ProgramData\Noldus\Components\Ethovision\Noldus HardwareInterface MiniIobox\ - Press Ctrl+V (Edit > Paste). Replace the old file version with the new one. - Delete the file DeviceTypesNoldus.xml in that folder. - Connect the Pellet dispenser to the Mini USB-IO box, and start EthoVision XT. - Create a new experiment and set up EthoVision XT. Attach the Pellet Dispenser to Objects To attach the Pellet dispenser to a stand or any other object, use the four M4 threaded holes located under the foot of the dispenser. For More Information For more information about the interface devices, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. The Pellet Receptacle Purpose Use the Pellet receptacle in two cases: - To collect the pellets dropped by the Pellet dispenser (no measurement). The pellets are kept in the receptacle instead of dropping on the PhenoTyper floor. - To record the number of times that the subject visited the receptacle. This is done with a beam break mechanism that records the nose pokes. How Nose Pokes Are Detected A mechanism based on an infrared beam detects the subject's nose pokes into the opening. When the subject pokes its nose into the opening of the receptacle, the infrared beam is broken. If the beam is broken for at least approximately 50 ms, a TTL signal "Low" is sent to the USB-IO box and therefore to EthoVision XT. When the beam is not broken (or broken for less than 50 ms), the TTL signal stays "High". The TTL signal will stay "Low" for at least 200 ms for a single nose poke. In case of multiple nose pokes shorter than 200 ms, these will be merged into one "Low" TTL signal. Connect the Pellet Receptacle to the USB-IO Box The Pellet receptacle comes attached to its wall. A black network cable with a special connector is included in the package. - Replace one of the PhenoTyper walls with the Pellet receptacle wall. Make sure that the black tube stays at the outer side of the PhenoTyper. For how to assemble the PhenoTyper cages, see the PhenoTyper - EthoVision XT 18 - Reference Manual. - Connect the tube of the Pellet dispenser to the black tube of the Pellet receptacle. If necessary, use the transparent tube that comes with the Pellet dispenser to connect the two devices. - Connect the Pellet receptacle to one of the TTL ports of the USB-IO box using the special black cable that comes with the Pellet receptacle wall. Each Pellet dispenser and Pellet receptacle combination needs two TTL ports: one for sending the pellet drop command to the Pellet dispenser, and one to read the nose pokes from the Pellet receptacle. Connect the Pellet Receptacle to the Nortio System Important: The cage walls equipped with the pellet receptacle contain an integrated circuit board. They must be cleaned with special care. Always follow the procedure described in the PhenoTyper - EthoVision XT 18 - Reference Manual. Technical Specifications Pellet Dispenser - Noldus Device Number: PTPD-001x - Power Supply: 18–26 V DC - Current Consumption: Standby 30 mA; when dropping pellet 250 mA - Manual Control: Single button - Remote Control: TTL input - Connector: RJ45 8 pin modular - Input: Optical isolated TTL logic 5 Volt - Output: Open collector type - Dimensions: Height: 20 cm (7 7/8"); base diameter: 10 cm (3 15/16"); silo diameter: 7.5 cm (2 61/64") - Weight: 1200 grams (42 oz) - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Pellet Types: 20 mg, 45 mg Pellet Receptacle - Noldus Device Number: PTPR-001x - Power Supply: 7–24 V DC - Current Consumption: Max. 30 mA at 24 V - Output: Open collector type - Connector: 3 pin female KK connector - Dimensions: Height: 7.7 cm (3 1/32"); width: 4.5 cm (1 49/64"); depth: 5.1 cm (2 1/64") - Weight: 62 grams (2.2 oz) - Pellet Types: 20 mg (tested), 45 mg (tested); maximum diameter 10 mm Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 4.2 Install The Pellet Dispenser (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-42-install-the-pellet-dispenser-continued Chapter: PhenoTyper Install the Pellet Dispenser (Continued) functioning for long periods of time. Tests have been carried out on 16 Pellet dispensers with more than 20000 pellets dropped. The pellets tested were from Bio-Serv and TestDiet. The deviation between the number of delivered and expected pellets is always within 5%, and in any case on the positive side. This means that a few more pellets are dropped, not fewer, than expected. For example, one instance of the Drop pellet command in EthoVision XT results in two pellets being dropped instead of one. There may be some variation between individual Pellet dispensers. The Pellet Dispenser and the Pellet Receptacle Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 4.3 Work With The Pellet Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-43-work-with-the-pellet-dispenser Chapter: PhenoTyper Work with the Pellet Dispenser EthoVision XT - Prepare the Experiment - If you use the Mini USB-IO box, first follow the instructions under Connect the Pellet Dispenser using the Mini USB-IO box. - Connect the USB-IO box / Nortio Core / Mini USB-IO box to the EthoVision XT computer and make sure that all devices are powered up, as described in the previous section. For details about the USB-IO box, the Mini USB-IO box and the Nortio Core, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Start EthoVision XT and create a new experiment or open an existing one. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device you have: - Noldus USB-IO box - Noldus Mini USB-IO box - Noldus Nortio Core Next, click OK. The Device Configuration/Nortio Configuration window opens. - For the TTL Control port which you connected the Pellet dispenser to, select Pellet Dispenser (PTPD-001x) as the Device/Device type. Repeat this step for each Pellet dispenser connected to TTL ports. Example for when using the Nortio system (four Pellet dispensers connected to TTL ports 1-4 of the Nortio T12T TTL Terminal Hub): - Under Nortio Hub, expand the item that applies. A list appears with the TTL ports available. - Under Device, select the Pellet dispensers connected to each port. - If your Pellet dispensers are connected to two or more USB-IO boxes, you must repeat the step above for the Pellet dispensers connected to the remaining interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in one of the following sections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, depending on which interface device you use: - The USB-IO box and the Mini USB-IO box - The Nortio system EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. If you have only one arena, you can skip the following steps. The hardware is automatically assigned to the arena. If you have more than one arena, do the following: - Click the Arena - Hardware mapping button in the Arena Settings window. - Under Device type, you should see Pellet dispenser (PTPD-001x). If that is not the case, click Add device and under Device type, select Pellet Dispenser (PTPD-001x). - Under Device name, accept the default name or type in a name, for example, Pellet dispenser. - Assign a Pellet dispenser to each arena. To do so, select the physical device Pellet Dispenser (PTPD-001x) [n] under the name of the arena it belongs to. Important: Make sure that each physical device is assigned to only one arena. - To test the Pellet dispenser, see the checking procedure below. - Click OK to close the Arena - Hardware mapping window. For more information on this step, see Assign devices to arenas in the EthoVision XT - Trial and Hardware Control - Reference Manual. For more information on the Arena Settings, see the section Arena Settings in the EthoVision XT Help. EthoVision XT - Trial Control Settings You can control the pellet dispenser by defining Trial Control Settings in EthoVision XT. As the pellet dispenser is mostly used in learning tests, you will probably need to define a sub-rule that is repeated a number of times, for a specified duration or indefinitely in order to teach the animal what the rule is. For instance, drop a pellet every time the mouse is in the trigger zone and repeat this indefinitely. You can define a maximum trial duration to stop the trial or stop it manually. Check That the Pellet Dispenser Works The Pellet Drop Detector An infrared photo beam detector senses whether a pellet is dropped after a "drop pellet" command has been given (either manually by pushing the blue button at the front or with the USB-IO box and EthoVision XT). When no pellet is detected, the stepper motor moves the carousel within the silo one step further. If, even after a full rotation, no falling pellet was detected, the system considers the silo to be empty. The pellet dispenser goes into error mode and the LED at the front of the pellet dispenser blinks continuously. Fill the silo with pellets and press the blue button at the front of the pellet dispenser to reset the device. It is then ready to be used again. Make sure that there are enough pellets in the silo before you start your experiment. If the silo is almost empty, it may take some time before a pellet is dropped. It can also be that no pellet is dropped because there is an obstruction in the falling path of the pellet caused by fragments of pellets. Use one of the following options to check whether your pellet dispenser works and whether your Trial Control Settings do what you want them to do: Checking Before Running a Trial - Choose Setup > Arena Settings. Open the Arena Settings you defined earlier. - In the Arena Settings window, click the Arena - Hardware mapping button. - In the Arena - Hardware mapping window, select the pellet dispenser and click Test. - A new window appears. The following message should appear: Number of drops: 0; In error state? false. - Click the Test button and check that a pellet is dropped. You can also view the result in the window; the number of drops increases by 1. Note: When you click the Test button for the first time after power-on, the pellet dispenser delivers one pellet after some delay. This is due to the mechanism that operates to calibrate the drop position. This delay does not occur in the following test actions. Checking While the Trial Is Running Check the LED indicator at the front of the Pellet dispenser. The LED blinks two times in a row to indicate a successful pellet drop. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 4.3 Work With The Pellet Dispenser (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-43-work-with-the-pellet-dispenser-continued Chapter: PhenoTyper Work with the Pellet Dispenser LED Blink Sequence The LED blinks in the following rapid sequence: - Single blink when the Pellet dispenser receives a Drop pellet command from EthoVision XT. - Single blink when a pellet is dropped. Control the Pellet Dispenser Manually With EthoVision XT You can have the Pellet dispenser drop a pellet every time you press a key on the keyboard. For this, you must use EthoVision XT. - In the Manual Scoring Settings, define a fictitious behavior, for example, Pellet of type Point event. Assign a key to this behavior. For more information, see Manual Scoring Settings in the EthoVision XT Help. - In the Trial Control Settings, create a subrule that contains the following conditions and actions: [Rule Begin] > [Condition: Frequency (Pellet)>=1] > [Action: Drop pellet] > [Rule End] Make sure that the Reference box for this subrule specifies Repeat indefinitely. - During acquisition, in the Manual Scoring tab, to drop a pellet click the button or press the key for the behavior Pellet. - In the Analysis profile, define the variable Pellet to visualize, for example, the total number of pellets dropped. With the Pellet Dispenser Button When using the pellet dispenser as a stand-alone device, you must connect it to a mains socket using the power supply for stand-alone use (PTPD-2010). Push the button at the front to drop a pellet. Note: When you press the blue button for the first time after power-on, the pellet dispenser delivers one pellet after some delay. This is due to the mechanism that operates to calibrate the drop position. This delay does not occur in the following drop actions. Work with the Pellet Receptacle Make sure that the USB-IO box is connected to the EthoVision XT computer, and that the Pellet receptacle is connected to a TTL port of the USB-IO box (page 38). Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, select Noldus USB-IO box or Noldus Nortio Core and click OK. - For the TTL Control port to which you connected the Pellet receptacle, select Pellet Receptacle (PTPR-001x) as the Device/Device type. Repeat this step for each Pellet receptacle connected to TTL ports. - When using the Nortio system: Under Nortio Hub, expand the item that applies. A list appears with the TTL ports available. Under Device, select the Pellet receptacle connected to each port. - If your Pellet receptacles are connected to two or more USB-IO boxes or Nortio Hubs, repeat the step above for the Pellet receptacles connected to the other interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - If you use the Nortio system: Under Nortio Hub, expand a new Hub item, then repeat the step above. - When ready, click OK. For more information, see Setting the Port Connections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, in the following sections depending on which interface device you use: - The USB-IO box and the Mini USB-IO box. - The Nortio system. Arena Settings If you have only one arena, you can skip the following steps. The hardware is automatically assigned to the arena. If you have more than one arena, do the following: - In the Arena Settings, click the Arena - Hardware Mapping button and click Add device. - Under Device type, select Pellet Receptacle (PTPD-001x). - To assign a Pellet receptacle to a specific arena, select Pellet Dispenser (PTPD-001x) in the corresponding column. When finished, click OK. Trial Control Settings - Choose Setup > Trial Control Settings. - Under Conditions, locate Pellet Receptacle (PTPR-001x). - Click the button next to it to add a condition based on the number of pokes. For example, to stop tracking when the number of nose pokes has reached a certain value. For more details on conditions, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Test the Pellet Receptacle - Choose Setup > Arena Settings. Open the Arena Settings you defined earlier and click the Arena - Hardware Mapping button. - In the Arena - Hardware Mapping window, select the Pellet receptacle and click Test. - A new window appears with the following messages: Number of nose pokes: 0; Is nose poke detected?: false. - Click the Test button and insert a pen tip in the Pellet receptacle. - View the result in the window; the message should say Number of nose pokes: 1 and Is nose poke detected?: true. Note: The green LED at the outer side of the receptacle switches off every time a poke occurs. Troubleshoot the Pellet Receptacle If the Pellet receptacle is not responding, do the following: - Check that the cable is not defective. Replace the cable from the Pellet receptacle to the USB-IO box, and between the USB-IO box and EthoVision XT if you suspect it may also be defective. Then repeat the test described above. - Check if the TTL port on the USB-IO box or Nortio TTL Terminal Hub works. - Connect the TTL Port tester to the same port of the USB-IO box that was connected to the Pellet receptacle. The TTL-power LED of the TTL Port tester should switch on. - Press the IN-1 button; this should be detected by EthoVision XT. If that happens, the TTL port works to support the Pellet receptacle. Tip: For information about the TTL Port tester, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Connect the Pellet receptacle to the TTL port on the USB-IO box or Nortio TTL Terminal Hub that you have just tested. - During power-up, the green LED on the Pellet receptacle near the cable connector should blink two times and then stay on. - Whenever the infrared beam in the receptacle is interrupted (for example, when inserting the tip of a pen), the green LED should switch off. If that does not happen, the receptacle may be defective (provided that all cables have been checked) and must be replaced. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 4.5 Maintenance And Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-45-maintenance-and-troubleshooting Chapter: PhenoTyper Maintenance and Troubleshooting Correct Usage of the Pellet Dispenser How to Fill the Silo Do not (re-)fill the silo while it stands on the Pellet Dispenser. The procedure below prevents a pellet from falling through the hole and being crushed when you push the silo back in place. - Remove the silo and place it on a table. Open its lid and fill it with the pellets. - Close the lid. While holding the lid closed, turn the Pellet Dispenser upside down and attach the silo. - Put the Pellet Dispenser back on the table. Only Use Intact Pellets If you notice dust and broken pellets in the package, carefully remove them. Use for example a sieve to divide the intact pellets from the rest. Clean the Pellet Dispenser Regularly Cleaning the Pellet Dispenser reduces the chance of malfunctioning. Clean at the end of an experiment / after 500 pellets dropped / every two days (whichever comes first). Replace or dry out the silica gel pack, e.g. with an oven, at the same time of cleaning. Keep and Use the Pellets in a Dry Place Make sure that you keep and use the pellets in a climate with relative humidity (RH) less than 40%. Pellets readily absorb moisture from the atmosphere. When kept in a humid climate, they absorb water and become frail. That may result in more broken pellets in the silo. We recommend keeping the silica gel pack attached to the lid of the silo. Replace the Silica Gel From mid 2022 the Pellet Dispenser is provided with 2-gram sachets of RS PRO Indicating Silica Gel that can be easily replaced. This gel changes its color from yellow to green when it has absorbed the maximum moisture. When the gel turns green, remove the sachet and attach a new or regenerated one to the lid of the silo. Regenerate the Silica Gel You can regenerate the silica gel by placing the sachet in an oven at 110°C (230°F) for three to four hours. Do Not Reuse Pellets Pellets that have previously been inside the silo may weaken internally and that increases the risk that they break or produce dust during use. Clean the Pellet Dispenser We recommend thoroughly cleaning the Pellet Dispenser at regular intervals because a clean product ensures reliability and long-term use. - Disassemble the pellet silo to ensure that the pellet dust can be removed easily. If you are going to clean a large number of Pellet Dispensers, consider using an electric screwdriver to disassemble them more quickly. - Clean the tube. Insert a dry cloth (not fraying) in the tube to pull the dust out. - Clean the holes in the carousel. Dust accumulates in holes quite easily, which may cause pellets to get stuck. - Usually cleaning with a dry cloth is sufficient. Do not use any liquids for cleaning purposes. Liquids can stick to the pellets or dust. Whenever liquids are used, make sure to dry all parts completely. - Clean the upper part of the carousel, 8–10 minutes depending on the cleaning substances used. Troubleshooting Problem: The Pellet Dispenser is full of pellets, but it fails to drop a pellet. - Disconnect the Pellet Dispenser from the USB-IO box and remove the silo. - Manually insert a pellet into the acrylic tube and check whether the pellet is dropped. - If the pellet does not come through, there must be some material obstructing the route. Try to remove it by gently poking into the acrylic tube using a 3-mm Polyurethane foam swab, a flexible wire, or a tie-wrap. Important: Do not use any object that could cause scratches inside the tube. - If no obstruction is found, do the following: - IR Beam Detector: The IR beam detector could be defective. Connect the dispenser to the USB-IO box in order to get power. After you press the blue button, the Pellet Dispenser attempts to drop the first pellet. Manually drop a pellet into the acrylic tube. When the pellet is detected, the device should stop rotating and the red LED should give a single blink to indicate "pellet dropped". If the IR detector is not working correctly, contact Noldus to have the dispenser repaired or replaced. - Mechanical Problem: There may be a mechanical problem. Remove most of the pellets from the silo, leaving only a few (5–8) remaining. Apply power and press the blue button. Look into the silo — the dispenser will search for the first pellet and drop it. Press the blue button again; the next pellet should be found and dropped. If that does not work, the aluminum hole cover clip may prevent pellets from falling down. You can adjust the position of the clip by slightly unscrewing it and fastening it gently again afterwards. The optimal position of the clip also depends on the pellet type used. Some experimenting may be needed. If none of the steps above help, the dispenser must be checked and repaired. In case of repair, please always ship the complete unit to Noldus. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 5.1 General Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-51-general-information Chapter: PhenoTyper General Information The Lickometer The Noldus Lickometer is a device that measures contact between a rat or mouse and its water bottle. It consists of an electronics box with (A) a metal ground plate and (B) a clip attached to it. Whenever a mouse or a rat contacts the spout of the water bottle, the capacitance between the clip attached to the spout and the metal ground plate changes. This change is detected by the Lickometer. The advantage of this system is that there is no current flow through the animal. The Lickometer is designed as an add-on to the PhenoTyper. To be able to receive information from hardware devices you need the Trial and Hardware Control module. You can control multiple lickometers with EthoVision XT (up to six per USB-IO box). For the limitations, see Control Hardware Devices in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Contents of the Lickometer Package A Lickometer package includes: - A Lickometer PTLM-001x. - A black network cable with RJ45 connectors, 1 meter long. Sample Reference Ho, A.L. et al. 2021. Accumbens coordinated reset stimulation in mice exhibits ameliorating aftereffects on binge alcohol drinking. Brain Stimulation: 330-334. doi: https://doi.org/10.1016/j.brs.2021.01.015. Technical Specifications - Noldus Device Number: PTLM-001x - Power Supply: 12-24 V DC - Current Consumption: Standby 20 mA - Connector: RJ45 8 pin modular - Input/Output: SDI type 1 - Dimensions: 80 x 45 x 21 mm (l x w x h) (electronics box), 80 x 55 mm (ground plate) - Weight: 200 grams - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Interface: Noldus USB-IO box and Nortio T12T TTL Terminal Hub - Applications: The Lickometer is suitable to measure drinking behavior of both rats and mice. You do not need to change any settings when you switch between species. Install the Lickometer Although the network cables shown in the following schemes are used in networks, the signal coming from the Lickometer is not a network signal. Do not connect the Lickometer via a network hub or similar. Also do not connect the Lickometer to the Mini USB-IO box. Connect the Lickometer Using the USB-IO Box - Make sure that the USB-IO box is connected to (A) your EthoVision computer and (B) a power supply. - Connect the Lickometer to one of the SDI Control ports at the backside of your USB-IO box (either one of the ports 1-12, not port 0), using the black RJ45 cable. The power supply also goes via this cable. When you connect the Lickometer, the red LED at the front of the electronics box blinks. - To attach the Lickometer to a PhenoTyper cage, place the metal ground plate underneath the cage. Important: Make sure that the PhenoTyper cage is on a wooden or synthetic table, not a metal one. A metal table interferes with the capacitance. - Connect the clip to the metal spout of the water bottle. - When the animal touches the spout of the water bottle, the red LED at the front of the electronics box turns on. Connect the Lickometer with the Nortio System Important: In order to use the Lickometer in combination with the Nortio system, you must modify the jumper settings inside the Lickometer electronics box. - Unscrew the cover of the Lickometer. - Locate the jumpers on the board, that is, the pins with the blue covers numbered 1-4. - Make sure that jumper position 1 is closed (that is, the two pins are covered with a blue cover) and the other jumper positions 2, 3, and 4 are open (the pairs of pins are visible). This way the Lickometer is set to work as a TTL device. - Close the cover of the Lickometer. You can now connect the Lickometer to the Nortio system: - Connect the Nortio Core to the EthoVision XT computer using a network cable. - Connect the Nortio T12T TTL Terminal Hub to the Nortio Core using the backbone input cable. - Connect the Lickometer to one of the TTL control ports of the Nortio T12T TTL Terminal Hub using a network cable. - Make sure that the Nortio Core is connected to a power supply. - To attach the Lickometer to a PhenoTyper cage, place the metal ground plate underneath the cage. Important: Make sure that the PhenoTyper cage is on a wooden or synthetic table, not a metal one. A metal table interferes with the capacitance. - Connect the clip to the metal spout of the water bottle. - When the animal touches the spout of the water bottle, the red LED at the front of the electronics box turns on. For how to install the Nortio system and configure the Ethernet board on your PC, see the section The Nortio System in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Working with an Older Lickometer Version The previous version of the Lickometer came with an X-keys USB Switch Interface which is no longer used. To use this older version of the Lickometer in combination with a USB-IO box, you must modify the jumper settings inside the Lickometer electronics box. - Unscrew the cover of the Lickometer. - Locate the jumpers on the board, that is, the pins with the blue covers numbered 1-4. - Make sure that jumper position 1 is open (that is, the two pins are visible) and jumper positions 2, 3, and 4 are closed (the two pins are covered with the blue covers). - Close the cover of the Lickometer. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 5.3 Work With The Lickometer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-53-work-with-the-lickometer Chapter: PhenoTyper Work with the Lickometer EthoVision XT - Prepare the Experiment - Make sure that you have followed the instructions in the previous section depending on which interface device you have. - Important: If you start EthoVision XT before the Lickometer set-up is fully connected it may not function properly. Also, if you disconnect and reconnect one of the cables of the Lickometer set-up while the experiment is open, the Lickometer may not function properly. - Start EthoVision XT and create a new experiment or open an existing one. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device: - Noldus USB-IO box. - Noldus Nortio Core. Note: The Lickometer does not work in combination with the Mini USB-IO box. Next, click OK. The Device Configuration/Nortio Configuration window opens. - Do the following depending on which interface device you have: - If you have the USB-IO box: For the SDI Control port to which you connected the Lickometer, select Lickometer (PTLM-001x) as the Device type. In the example below, the Lickometer is connected to SDI Port 1. - If you have the Nortio system: Under Nortio Hub, expand the item that applies. A list appears with the TTL ports available. Under Device, select the Lickometers connected to each port. - If the Lickometers are connected to two or more USB-IO boxes, you must repeat the step above for the Lickometers connected to the remaining interface devices. - If you use the USB-IO box: From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in one of the following sections in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, depending on which interface device you use: - The USB-IO box and the Mini USB-IO box. - The Nortio system. EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. If you have only one arena, the hardware is automatically assigned to the arena. You can skip this section. If you have more than one arena, complete the following steps. - Click the Arena - Hardware mapping button in the Arena Settings window. - Under Device type, you should see Lickometer (PTLM-001x). If that is not the case, click Add device, and under Device type select Lickometer (PTLM-001x). - Accept the default name under Device name or type in a name, for example, Lickometer. - Assign a Lickometer to each arena. To do so, select Lickometer (PTLM-001x) under the name of the arena it belongs to. Do this for all lickometers. Important: Make sure that each physical device is assigned to only one arena. - Click OK to close the Arena - Hardware mapping window. For more information on this step, see Assign devices to arenas in the EthoVision XT - Trial and Hardware Control - Reference Manual. For more information on the Arena Settings, see the section Arena Settings in the EthoVision XT Help. Check That the Lickometer Works Important: Before you start EthoVision XT, make sure that the USB-IO box is connected to (A) your EthoVision computer and (B) a power supply, and that the Lickometer is connected to the USB-IO box/Nortio T12T TTL Terminal Hub. If you start EthoVision XT before the Lickometer set-up is fully connected, it may not function properly. Also, if you disconnect and reconnect one of the cables of the Lickometer set-up while the experiment is open, the Lickometer may not function properly. Use one of the following options to check whether your Lickometer works: Before Running a Trial - Open the Arena Settings in which you have mapped the Lickometers. - In the Arena Settings window, click the Arena - Hardware mapping button. - In the Arena - Hardware mapping window, click the Lickometer under Arena and click Test. - The Test Lickometer window appears. Touch the Lickometer's clip and check the result in the window. Every time you touch the clip, the number of licks and the duration of licks should increase. If you notice unusually high numbers of licks during this test, the Lickometer set-up has been connected after you opened the experiment. To solve this, close and re-open the experiment. Test the Lickometer again. It should now work properly. While a Trial Is Running Check the red and yellow LEDs at the front of the Lickometer's electronics box. - The red LED is on when the animal touches the water bottle spout. - The yellow LED blinks periodically. This indicates that EthoVision XT requests information from the Lickometer. After the Trial Has Been Acquired - Export your data in a hardware log. The hardware log gives you an overview of the hardware events that occurred during the trial. - Make a Time Event plot. Acquire the Data EthoVision XT and the Lickometer are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information, see the EthoVision XT Help (F1). Lickometer Data Acquired with the USB-IO Box Every two seconds the USB-IO box collects data from the Lickometer and sends it to EthoVision XT. These time points are marked by a blink of the yellow LED on the electronics box. After each reading, the Lickometer is reset. EthoVision XT counts: - The number of touch events since the last reading. - The cumulative touch duration since the last reading (with a 10 msec resolution). When the USB-IO box/EthoVision requests information (reading events), the Lickometer reports the number of touch events since the last reading and the cumulative touch duration. This information is added to EthoVision XT's hardware log. After each reading, the Lickometer is reset and counting starts from zero. Note: The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also includes some time before the trial start (less than 2 seconds). This time is included in the results. - The data between the last reading event and the stop of the trial is not included in the results. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 5.3 Work With The Lickometer (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-53-work-with-the-lickometer-continued Chapter: PhenoTyper Work with the Lickometer (Continued) Results. This time is again less than 2 seconds depending on when the trial stopped. In most cases the two discrepancies have no effect on your data when the trial lasts at least a few minutes, like in typical PhenoTyper tests. Tip: If you want a device to have a different sample rate, contact Noldus. See User-defined Hardware Devices in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Lickometer Data Acquired with the Nortio System The Lickometer data are of the same type whether you use the USB-IO box or the Nortio system. However, an important difference is that with the Nortio system the lick events are recorded real-time, not at regular intervals. While the USB-IO box reads the Lickometer data every two seconds, in such a way that Lickometer data are stored at two-second time resolution, the Nortio system makes it possible to record the Lickometer data as true TTL signals associated with a specific sample time. The latter ensures higher timing accuracy. The sequence of events is as follows: - The Lickometer sends the sensor signal to the Nortio T12T TTL Terminal Hub. - The Nortio T12T TTL Terminal Hub sends the signal to the Nortio Core. - The Nortio Core evaluates the signal every 5 ms and counts the number of licks and the cumulative duration of the licks. - EthoVision XT receives the data from the Nortio Core. Data are assigned to a specific sample time. Note that this differs from what occurred when using the USB-IO box, where data were associated with a 2-second interval. View the Data in the Hardware Log The hardware log lists the hardware events that occurred during the trial. The feedback signal sent by the Lickometer to EthoVision is Number of Licks and Duration of Licks. To export a hardware log, choose Analysis > Export > Track Data and under Data to Export select the option Hardware Log. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 5.4 Calculate The Statistics For The Lickometer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-54-calculate-the-statistics-for-the-lickometer Chapter: PhenoTyper Calculate the Statistics for the Lickometer Analysis Profile You can create an analysis profile to calculate the number of licks or the duration of licks, or visualize and calculate the time that the number or duration of licks exceeded a specific value. Procedure - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware choose one or more of the following options: - Hardware continuous if you want to calculate the total number of licks or the total duration of licks, or visualize the raw data on the timeline. - Hardware state if you want to visualize the time when the number of licks or the duration of licks is higher or lower than a specific threshold. - In the window that opens, next to Device type, select Lickometer (PTLM-001x). - Next to Device, select the device you want to analyze. The names reported here were defined in an earlier step (see page 66). - Next to Signal, select Number of licks or Duration of licks. If you select Hardware state, and then Duration of licks as Signal, specify the threshold time in microseconds. For example, 1000000 for one second. - In the Trial Statistics tab, select the statistics you want to calculate. For example: - For a Hardware continuous variable: To calculate the total number of licks (Hardware continuous - Number of licks), select Total if you collected the data with the USB-IO box. However, if you collected the Lickometer data with the Nortio system, select Maximum. - For a Hardware state variable: To calculate the time taken before a certain duration of licks has been reached (Hardware state - Duration of licks > ... seconds), select Latency to First. If you want to calculate the time after the threshold has been reached, select Cumulative Duration. - Click Add. Repeat the procedure from step 1 to add another variable. The Cumulative Value Option The Cumulative value option is available when you choose a variable of type Hardware state. How you use this option depends on which interface system you use between EthoVision XT and the Lickometer. - Select Cumulative value if you want to mark the time that the cumulative value of number (or duration) of licking events has reached a specific threshold. For example, Cumulative value of Duration of licks >= 10000000 (10 seconds). At each sample, the value of cumulative number (or duration) taken from all the previous sampled intervals is compared with the threshold value. - Keep Cumulative value de-selected if you want to mark the time that the number (or duration) of licking events has reached a threshold within the sampled interval. For example, to mark the time that the duration of licks exceeded 1 second in each sampled interval of the Lickometer, which lasts two seconds. If you work with the Nortio system: - For Number of licks, keep Cumulative value selected. - For Duration of licks, keep Cumulative value de-selected. Statistics and Visualization - Choose Analysis > Results > Statistics & Charts. Select a Data profile and an Analysis profile from the lists on the toolbar and click Calculate. - To visualize the number of licks and their durations, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You can now see in the Time Event Plot when licks took place. Lickometer Data Acquired with the USB-IO Box - First plot: Hardware continuous set to Number of licks. The arrows indicate the first five lick events. These are marked with dots when the variable Hardware continuous (Number of licks) has value 1 in each sampled interval. Because the sampled interval is two seconds, the time distance between two subsequent dots is always two seconds. When there are no lick events, the value of the variable is zero. - Second plot: Hardware continuous set to Duration of licks. Each dot represents the duration of licks in each sampled interval. Because this interval lasts two seconds, the values of lick duration range between zero and two seconds. - Third plot: Hardware state set to mark the time that the Number of licks exceeds five. The option Cumulative was selected in the variable settings. For this reason, the variable is active when Hardware continuous (Number of licks) gets the value 1 for the fifth time. - Fourth plot: Hardware state set to mark the time that Duration of licks >= 4000000 (four seconds), with the option Cumulative selected. This variable becomes active for the first time when the sum of the values of the variable Hardware continuous - Duration of licks exceeds four seconds. The Cumulative option allows the values of duration to be summed and compared with the specified threshold. Tip: If the plots of the Hardware continuous variable appear empty, click Show/Hide > Show Graph Data Points and zoom in on the plot to show the dots larger. Lickometer Data Acquired with the Nortio System Hardware Continuous Variables - First plot: Hardware continuous set to Number of licks. The lick events can occur at any sample time, not at regular intervals as is the case for Lickometer data collected with the USB-IO box. The start of a lick event is scored as 1. The rest is scored as zero. - Second plot: Hardware continuous set to Duration of licks. The color line is made of dots that represent the duration of licks at the current time. In the beginning, the duration is always zero. The first lick event occurs just before 10:00 and lasts about two seconds. The duration of the lick event is shown in this plot at the end of the lick event. Note that each spike of Duration of licks comes after a spike of Number of licks. The distance between the two spikes is the duration of that lick event. The total duration of the lick events is the sum of the height of the spikes in the second plot. Hardware State Variables - First plot: Number of licks displayed with the variable Hardware continuous. - Second plot: Hardware state set to mark the time that the Number of licks exceeds 4. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 5.4 Calculate The Statistics For The Lickometer (Continued) URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-54-calculate-the-statistics-for-the-lickometer-continued Chapter: PhenoTyper Calculate the Statistics for the Lickometer (Continued) The option Cumulative value was selected in the variable settings. The variable Hardware state is active when the cumulated number of lick events reaches 4. First plot: Duration of licks displayed with the variable Hardware continuous. A previous event of about 10 seconds is not shown. The current event lasts more than 20 seconds, so the cumulative duration of licks at the current time exceeds 30 seconds. Second plot: Hardware state set to mark the time that Duration of licks >= 30000000 microseconds (30 seconds). The option Cumulative was selected in the variable settings. The variable Hardware state is active when the cumulated duration of licks reaches 30 seconds. Notes To know the time taken for the number or duration of licks to reach the specified value, in the Analysis profile re-open the variable settings window and in the Statistics tab select the statistic Latency to First. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 6.3 Work With Phenowheel URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-63-work-with-phenowheel Chapter: PhenoTyper Work with PhenoWheel EthoVision XT - Prepare the Experiment - Make sure that you have followed the instructions in the previous section. Also, make sure all devices are powered up. - Start EthoVision XT and create a new experiment or open an existing one. Important: Do not disconnect PhenoWheel while the experiment is open. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control Hardware option, and click Settings next to that option. - In the window that opens, choose Noldus USB-IO box or Nortio Core depending on the interface device you have. Note: PhenoWheel only works in combination with the Nortio system when its version number is PTCN-0011 or later. Click OK. The Device Configuration window opens. - Do the following depending on which interface device you have: - If you have the USB-IO box: For the SDI Control port to which you connected the PhenoCount module, select PhenoWheel as the Device type. - If you have the Nortio system: Under Nortio Hub, click the arrow button to show the list of TTL ports available. Under Device, select PhenoWheel for each port connected to a PhenoCount box. - If the PhenoWheels are connected to two or more USB-IO boxes, you must repeat the step above for the PhenoWheels connected to the remaining interface devices. To do so, from the IO Interface list in the Device Configuration window select a new USB-IO box, then repeat the previous step. - When ready, click OK. For more information, see Setting the Port Connections in the chapter The USB-IO Box and the Mini USB-IO Box in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. EthoVision XT - Arena Settings We assume that you have drawn the arenas and the zones in the Arena Settings. If you have only one arena, the hardware is automatically assigned to the arena. You can skip this section. If you have more than one arena, follow the steps below: - Click the Arena - Hardware Mapping button in the Arena Settings window. - Under Device type, you should see one row with PhenoWheel/PhenoWheel (60). If that is not the case, click Add Device, and under Device type select PhenoWheel/PhenoWheel (60). - Under Device name, accept the default name or type in a name, for example, PhenoWheel. - Assign one PhenoWheel device to each arena. To do so, select the physical device PhenoWheel [n] under the name of the arena it belongs to. For example: - PhenoWheel 1 for Arena 1 - PhenoWheel 2 for Arena 2 Do this for all PhenoWheels. Important: Make sure that each physical device is assigned to only one arena. - To test the counter, click PhenoWheel in one of the Arena columns and then click the Test button. When you rotate that running wheel, the number of cycles is displayed under Value. Note that this number is read out at regular intervals of 60 seconds. - Click OK and repeat the previous step for the remaining wheels. - Click OK to close the Arena - Hardware Mapping window. Acquire the Data EthoVision XT and PhenoWheel are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information: - PhenoTyper - EthoVision XT 18 - Reference Manual - EthoVision XT Help (F1) PhenoWheel Data Acquired with the USB-IO Box The way data are collected depends on whether the PhenoCount module is set to work as a SDI device (standard in PTCN-0010) or as a TTL device (optional in PTCN-0011). If the PhenoCount module is set to SDI mode, it sends data to EthoVision XT every 60 seconds. At each sample time, EthoVision XT counts the number of rotations since the last reading event. The reading events are not in sync with the trial start and stop. This means that: - The data of the first reading event after the trial start also includes some time before the trial start. This time (< 60 s) is included in the results. - The data between the last reading event and the stop of the trial is not included in the results. This time is again < 60 s depending on when the trial stopped. In most cases the two discrepancies have no effect on your data in long trials, for example a few hours trial. Tip: If you require working with devices with a different sampling rate, contact Noldus. If the PhenoCount module is set to TTL mode, wheel rotations are detected as TTL pulses in real time, not at regular intervals. Data are treated the same way as in other TTL devices (e.g. the Pellet dispenser). PhenoWheel Data Acquired with the Nortio System With the Nortio system, PhenoWheel works as a TTL device. The wheel rotations are recorded as TTL events associated with a specific time stamp, not counts read out at regular time intervals. The Nortio system therefore ensures higher timing accuracy. The sequence of events is as follows: - The PhenoCount module sends the sensor signal to the Nortio T12T TTL Terminal Hub. - The Nortio T12T TTL Terminal Hub sends the signal to the Nortio Core. - The Nortio Core evaluates the signal every 5 ms and counts the number of rotations. - EthoVision XT receives the data from the Nortio Core. The rotation event is assigned to a specific sample time. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 6.4 Calculate The Statistics For Phenowheel URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-64-calculate-the-statistics-for-phenowheel Chapter: PhenoTyper Calculate the Statistics for PhenoWheel Analysis Profile You can create an analysis profile to calculate the number of rotations. - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, click Hardware continuous. - In the Hardware Continuous window, next to Device type, select PhenoWheel (60). - Next to Device, select the correct device name, if you have more than one connected. - Next to Signal, select Number of cycles. - In the Trial Statistics tab, select Total. - Click Add. Statistics and Visualization - To calculate the statistics for wheel data, choose Analysis > Results > Statistics & Charts. - Select the correct Data profile and Analysis profile from the lists on the toolbar and click Calculate. - To visualize the number of rotations, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You will now see in the Time Event Plot when rotations took place. PhenoWheel Data Acquired with the USB-IO Box (SDI Mode) - Hardware continuous set to Number of cycles. A dot appears every time the counter is read out and the height of the dot indicates the number of rotations during the past interval. - Hardware state set to mark the time that the Number of cycles exceeds a specific value. The option Cumulative must be selected in the variable settings. PhenoWheel Data Acquired with the USB-IO Box (TTL Mode) or the Nortio System A dot appears every time a rotation event is detected. Because the signal conveys information about a single rotation, the vertical axis shows 1 at every rotation. Note: The TTL mode of the USB-IO box is only possible in PTCN-0011 or later versions. - Hardware continuous set to Number of cycles. The rotations can occur at any sample time, not at regular intervals as is the case for PhenoWheel data collected with the USB-IO box in SDI mode. The moment that the magnet passes the sensor is scored as 1. The rest is scored as zero. - Hardware state set to mark the time that the Number of cycles exceeds a specific threshold. The option Cumulative value is selected in the variable settings. Note: If the plots of the Hardware continuous variable appear empty, that is because the data are shown as small dots. Click Show/Hide > Show Graph Data Points and zoom in the plot to show the dots larger. General Information The Feeding Monitor is a system to monitor the behavior of mice based on sensors. This system can work with any compatible type of sensor. The Feeding Monitor can be used to measure the number of times an animal inserts its nose into the feeder of a PhenoTyper cage model 3000. As such, it can count the number of times the animal is feeding. The Feeding Monitor works by detecting the interruption of an infrared beam between an infrared transmitter and a receiver installed in the IR Food Sensor in the PhenoTyper cage. The IR Food Sensor works in combination with the IR Beam Controller (PTBC-001x) which can also control an optical cue device, for example, a LED. Contents of the Feeding Monitor Package - IR Beam Controller (PTBC-001x) – This box can be used to control any type of sensor in a PhenoTyper cage. Currently, the IR Food Sensor is the only sensor available for the Feeding Monitor. - Network (CAT5 UTP), 2-m purple cable (PTPC-7020) – To connect the IR Beam Controller to the USB IO-Box. - IR Food Sensor (PTFS-0010) – The sensor that is built into the PhenoTyper cage model 3000. - Food Sensor cable (PTFS-0020) – To connect the IR Food Sensor with the IR Beam Controller. - Insert for PT3000 feeder (PT-I-00) – To adapt the feeder for use with the IR Food Sensor. Without the insert the animal cannot reach the food. Acknowledgements The Feeding Monitor has been developed in close collaboration with Prof. Dr. Martien Kas, University Medical Center, Utrecht. For more information about the application of an early version of the IR Food Sensor see, for example: - Kas et al., (2008). Differential Genetic Regulation of Motor Activity and Anxiety-Related Behaviors in Mice Using an Automated Home Cage Task. Behavioral Neuroscience (4): 769–776. - Kas et al., (2009). High-resolution genetic mapping of mammalian motor activity levels in mice. Genes, Brain and Behavior: 13–22. - De Mooij-Van Malsen et al., (2009). Interspecies Trait Genetics Reveals Association of Adcy8 with Mouse Avoidance Behavior and a Human Mood Disorder. Biological Psychiatry: 1123–1130. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 7.2 Install The Feeding Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-72-install-the-feeding-monitor Chapter: PhenoTyper Install the Feeding Monitor Although the network cables shown in the following schemes are used in networks, the signal coming from the Feeding Monitor is not a network signal. Do not connect the Feeding Monitor through a network hub or similar. Connect the Feeding Monitor Using the (Mini) USB-IO Box - Remove the feeder from the PhenoTyper cage and replace it with the IR Food Sensor (B in Figure 7.1). - Attach the feeder to the IR Food Sensor as in Figure 7.1 and put the Insert (D) for the PT3000 feeder into the feeder. - Connect the (Mini) USB-IO box to the EthoVision XT PC through a USB cable. - Use the purple network cable to connect the IR Beam Controller box (Figure 7.1, A, usb io-box port) to a TTL port of the (Mini) USB IO-Box. - Power up the (Mini) USB-IO box. The power LED indicates 'power on'. The active LEDs on the IR Beam Controller box remain on until the IR Food Sensor (or any other compatible sensor) is connected. If necessary, make sure the IR Beam Controller and its LEDs are out of sight of the animal in the PhenoTyper cage. - Connect the IR Food Sensor to the IR Beam Controller box (Beam-1 or Beam-2 port) with the Food Sensor cable (Figure 7.1, C). - The 'active' LED light turns off. The LED light turns on every time the beam of the IR Food Sensor is interrupted. Connect the Feeding Monitor Using the Nortio System - Connect the Nortio Core to the EthoVision XT through a network cable. - Connect the Nortio T12T TTL Terminal Hub to the Nortio Core using the backbone input cable. - Use the purple network cable to connect the usb io-box port of the IR Beam Controller box (Figure 7.1, A) to a TTL port of the Nortio T12T TTL Terminal Hub. - Power up the Nortio Core. The power LED indicates 'power on'. The active LEDs on the IR Beam Controller box remain on until the IR Food Sensor (or any other compatible sensor) is connected. If necessary, make sure the IR Beam Controller and its LEDs are out of sight of the animal in the PhenoTyper cage. - Connect the IR Food Sensor to the IR Beam Controller box (Beam-1 or Beam-2 port) with the Food Sensor cable (Figure 7.1, C). - The 'active' LED light turns off. The LED light turns on every time the beam of the IR Food Sensor is interrupted. Notes For details about the USB-IO box, the Mini USB-IO box and the Nortio system, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Work with the Feeding Monitor EthoVision XT - Prepare the Experiment - Connect the USB-IO box / Nortio Core / Mini USB-IO box to the EthoVision XT computer and make sure that all devices are powered up, as described in the previous section. For details about the USB-IO box and the Mini USB-IO box and the Nortio system, see the relevant chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. - Start EthoVision XT and create a new experiment or open an existing one. Important: Do not disconnect the IR Beam Controller while the experiment is open. EthoVision XT - Experiment Settings - In the Experiment Settings, select the Use of Trial Control hardware option, and click Settings next to that option. - In the window that opens, choose the interface device you have: - Noldus USB-IO box - Noldus Mini USB-IO box - Nortio Core Next, click OK. The Device Configuration/Nortio Configuration window opens. - For the TTL Control port which you connected the Feeding Monitor to, select Beam Controller (PTBC-001x) as the Device/Device type. If you work with the USB-IO box, the Device ID (third column) changes to Beam Controller (PTBC-001x) 1. Repeat this step for each Feeding Monitor connected. - If you have multiple Feeding Monitors connected to two or more USB-IO boxes, from the IO Interface list select a USB-IO box. Repeat this and the next step for each USB-IO box. When using the Nortio system (for example, four Feeding Monitors connected to TTL Ports 1–4 of the Nortio T12T TTL Terminal Hub): - Under Nortio Hub, click the arrow button to open the list of the TTL ports available. - Under Device, select Beam Controller for each port. - If your Feeding Monitors are connected to two or more USB-IO boxes, you must repeat the step above for those connected to the remaining USB-IO boxes. From the IO Interface list select a new USB-IO box, then repeat the step above. - When ready, click OK. For more information, see Setting the port connections in one of the following chapters in the EthoVision XT 18 - Trial and Hardware Control - Reference Manual, depending on which interface you use: - The USB-IO box and the Mini USB-IO box - The Nortio interface system EthoVision XT - Arena Settings - In the Arena Settings, define the arenas. For more information on this step, see Arena Settings in the EthoVision XT Help. If you have only one arena, the hardware is automatically assigned to the arena. Skip the following steps and proceed to the hardware mapping step. If you have more than one arena, continue with the following steps. - Click the Arena - Hardware mapping button in the Arena Settings window. Note: The IR Beam Controller box can control two sensors. However, two sensors connected to the same IR Beam Controller box can only be used in the same arena in EthoVision XT. - Under Device type, you should see Beam Controller. If that is not the case, click Add device, and under Device type, select Beam Controller (PTBC-001x). - Under Device name, accept the default name or type in a name, for example, Feeding monitor. - Assign a Beam Controller (PTBC-001x) to each arena. To do so, select the physical device Beam Controller (PTBC-001x) [n] under the name of the arena it belongs to. For example: - Beam Controller 1 for Arena 1 - Beam Controller 2 for Arena 2 Do this for all Feeding Monitors. Important: Make sure that each physical device is assigned to only one arena. - To test the Feeding Monitor: - Click Beam Controller (PTBC-001x) in one of the Arena columns. - Click the Test button. - Locate the corresponding Feeding Monitor and put a finger at the other side of the feeder (that is, the inner side of the cage wall) to interrupt the beam. That simulates a feeding event. - The value next to is beam broken? becomes true and the number of beam breaks is displayed under Value. If you have a LED connected to the IR Food Sensor, you can test it by selecting Cue on from the Command list. - Click OK to close the Arena - Hardware mapping window. Acquire the Data EthoVision XT and the Feeding Monitor are now configured. Follow the usual steps to define the detection settings and acquire the data. For more information, see the PhenoTyper - EthoVision XT 18 - Reference Manual and the EthoVision XT Help (F1). Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - 8.2 Install The Ttl To 28V Interface URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-82-install-the-ttl-to-28v-interface Chapter: PhenoTyper Install the TTL to 28V Interface Connect the TTL to 28V Interface Using the USB-IO Box / Mini USB-IO Box - Connect a 28-V power supply to the 28V supply-in connection on the TTL to 28V Interface. Either use a 28-V power supply or the Noldus 28-V power supply (Noldus type number: MAPS-0010). - Connect the USB-IO box connection on the TTL to 28V Interface to one of the TTL Control ports on the USB-IO box / Mini USB-IO box, using the supplied network cable. - Connect the Med Associates or third-party device to the output 28V port 1 or 2. Connect the TTL to 28V Interface Using the Nortio System - Connect a 28-V power supply to the 28V supply-in connection on the TTL to 28V Interface. Either use a 28-V power supply or the Noldus 28-V power supply (Noldus type number: MAPS-0010). - Connect the Nortio Core to the EthoVision XT through a network cable. - Connect the Nortio T12T TTL Terminal Hub to the Nortio Core using the backbone input cable. - Connect the USB-IO box port on the TTL to 28V Interface to one of the TTL Control ports on the Nortio T12T TTL Terminal Hub, using the supplied network cable. Notes - The green LED light indicates whether a TTL signal is sent from EthoVision XT. - An extension cable (Noldus type number: MACA-0201) is available if you need to increase the distance between the TTL Interface and the device. - USB-IO TTL control and power are fully optically isolated from the 28-Volt Med Associates power and control circuit to prevent any unwanted interaction. Using Multiple TTL to 28V Interfaces You can use multiple TTL to 28V Interfaces with only one 28-V power supply. For this purpose, feed through the power from one of the 28V supply in/out ports on one TTL Interface to one of the 28V supply in/out ports on the next TTL Interface, using the power feed-through cable (Noldus type number: MACA-0101). It does not matter which 28V supply in/out port you use to connect the two boxes; either the one at the top or the one at the bottom is fine. You can also use this solution to connect multiple light sources of the Top Light Unit of DanioVision. For details, see the DanioVision DVOC-0041 Reference Manual. Important: Make sure not to exceed the maximum current output (0.9 A) of the Noldus 28-V power supply. Check the technical specifications of the devices you connect. Inverted Operation If needed, you can invert the output level of the controlled device by changing jumper settings inside the TTL to 28V Interface. This is useful, for example, when you want to change the default position of the doors of the radial arm maze to open instead of closed. - Open the box by pushing the left and right sides a few millimeters in the direction of the red arrow to release the click system of the printed cover. Simultaneously, carefully slide the cover in the direction of the white arrow. - Lift the jumper and change the position (A or B) to set the control to inverted or not inverted. JMPR1 does this for device 1; JMPR2 does this for device 2. Technical Specifications - Noldus Type Number: PTMA-001x - Power Requirements: 12 to 20 VDC supplied by USB-IO box; external 28 VDC power supply - Current Consumption: 40 mA without device connected - Weight: ± 100 g (3.5 oz) - Operating Temperature: 10 °C to 35 °C (50 °F to 95 °F) - Storage Temperature: -40 °C to 65 °C (-40 °F to 149 °F) - Relative Humidity (Max.): 20% to 80% (non-condensing) Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - Dispenser URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-dispenser Chapter: PhenoTyper Analysis Profile You can create an analysis profile to calculate the number of pellets dropped. Procedure - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, click one or more of the following: - Hardware Continuous or Hardware Command if you want to calculate the total number of pellet drops, or visualize the pellet drops on a timeline. - Hardware State if you want to visualize and calculate when the number of pellets dropped exceeded a certain number. - Whatever option you choose, next to Device Type, select Pellet Dispenser (PTPD-001x). Next to Device, select the correct device if you have more than one pellet dispenser connected. - In the Trial Statistics tab, select the statistic Total. - Click Add. Repeat the steps from step 2 to add more variables. Analysis Profile with the Pellet Receptacle In the Analysis Profile: - To calculate the total number of pellet drops, or visualize the nose pokes on a timeline, under Hardware choose Hardware Continuous. Choose the device you want to extract the data from. - To calculate the total duration of nose pokes, or the time that the number of nose pokes was lower or higher than a certain value, under Hardware choose Hardware State. Choose the device you want to extract the data from. Next to Signal, choose what you want to calculate. Choose Is nose poke detected = true to calculate the total nose poke time. Statistics and Visualization - Choose Analysis > Results > Statistics & Charts. Select the correct Data Profile and Analysis Profile from the lists on the toolbar and click Calculate. - To visualize the pellet drops or nose pokes on a timeline, choose Analysis > Results > Integrated Visualization. Select the correct Analysis Profile from the list on the toolbar. You will now see in the Time Event Plot when pellets were dropped. In the figure below, from top to bottom: Hardware Command, Hardware Continuous (see also the inset when zooming in the timeline), Hardware State which was set to Number of drops >= 5, with Cumulative selected. Tip: For a clearer view of the data points, click Show/Hide > Show Graph Data Points. Pellet Receptacle The example below shows the visualization of a Hardware Continuous and a Hardware State: - First plot: Hardware Continuous. The onset of nose pokes are plotted on the timeline. - Second plot: Time that a nose poke occurred. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - Index URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-index Chapter: PhenoTyper Index A - Adding - Lickometer in EthoVision - AGC - Arena - Hardware Mapping - Feeding monitor - Lickometer - Arena Settings - Adding feeding monitor - Adding lickometer - Automatic Gain Control C - Calculating - Number and duration of licks - Number of pellets dropped - Camera (PhenoTyper 1) - Camera (PhenoTyper 2) - Camera Settings (PhenoTyper 1) - Camera Settings (PhenoTyper 2) - Camera Test Sheet - Checking - Lickometer - Pellet dispenser - Phenowheel - Contrast - Controlling - Pellet dispenser D - DanioVision Toplight Unit - Declaration of Conformity - Documentation Folder F - Feeding Monitor - Adding in EthoVision - Flicker - Focus - Focus of the Lens H - Help Desk I - Installing - Phenowheel - Interface TTL to 28V - IR Beam Controller - IR Food Sensor J - Jumper Settings - Of the lickometer - Of the USB-IO box L - LEDs - Pellet dispenser - Top unit interface - Lick Duration Cumulative - Lickometer - Adding in EthoVision - And X-keys switch interface - Calculating number of licks - Checking - Collecting data - Lick duration cumulative - Number of licks - Setting up - Technical specifications M - Manuals - Menu (Camera On-Screen) - Mouse Interaction Monitor - Testing N - Number Of - Beam breaks - Licks - Pellets dropped - Rotations - Number of Licks - Export to hardware log O - On-Screen Menu - Orientation of the Camera P - Pellet Dispenser - Calculating statistics - Checking - Cleaning - Controlling - Detecting dropped pellets - LED indicator - Setting up - Stand-alone - Technical specifications - Troubleshooting - With EthoVision XT - Pellet Receptacle - Cleaning - In analysis profile - In arena settings - In data visualization - In experiment settings - In trial control settings - Setting up - Testing - Troubleshooting - Pellets - Phenocount Module - PhenoWheel - Adding in EthoVision - Calculating statistics - Installation - Testing - Using with EthoVision R - Replacement of Components - Reset Camera - Running Wheel - See PhenoWheel S - SDI Control Port - Setting Up - Feeding monitor - Lickometer - Pellet dispenser - Phenowheel - Sharpness - Shutter - Spare Parts T - Technical Specifications - Feeding monitor - Lickometer - Pellet dispenser - Top unit interface - Technical Support - Test Sheet - Testing - Feeding monitor - Lickometer - Pellet dispenser - Phenowheel - Top Unit Interface - Cables - Technical specifications - Trial and Hardware Control - TTL Control Port - TTL Tester - TTL to 28V Interface U - USB-IO Box V - Visualization - Number of beam breaks - Number of licks - Number of pellets dropped - Number of rotations W - White Balance X - X-Keys Switch Interface Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-introduction Chapter: PhenoTyper About This Manual When You Need This Manual This manual is intended for users of PhenoTyper and Noldus trainers and support who need more technical information about the functioning of PhenoTyper and its accessories than is covered in the PhenoTyper - EthoVision XT 18 - Reference Manual. Check regularly the Noldus download page at my.noldus.com for the most recent version of this manual. Using This Manual Some information in this manual may or may not apply to your setup depending on the devices you work with. - For PhenoTyper 1 (analog camera): All chapters apply. - For PhenoTyper 2 (digital camera): All chapters except The Top Unit Interface apply. - For the USB-IO box: All chapters apply. - For the Nortio system: All chapters except The Top Unit Interface. Lickometer and PhenoWheel can only work if they are of recent versions and configured based on the instructions. Other Documentation Manuals You can find the following manuals on your computer after you have installed EthoVision XT. From the Windows Start menu, select All Apps > Noldus > EthoVision XT 18 Other Documentation. - The EthoVision XT Help (press F1 to open it in EthoVision XT). This browser-based Help contains extensive information about EthoVision XT. - The PhenoTyper - EthoVision XT 18 - Reference Manual. For how to assemble PhenoTyper, design experiments and analyze data in EthoVision XT. - The EthoVision XT 18 - Quick Start Guide - English. A small manual with a summary on how to use EthoVision XT. This is also available in several different languages. - The EthoVision XT 18 - Application Manual. This manual contains information about different standard tests, including conditioning tests carried out with PhenoTyper. - The EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Open this manual if you are looking for information about the USB-IO box and the TTL tester, or you want to know more about complex Trial Control protocols. You can also find the manuals on the downloads section of the Noldus web site my.noldus.com. Sample Experiments You can find examples of applications with PhenoTypers in the EthoVision XT sample experiments that you can download from my.noldus.com. Note that you have to log in or register first. Next, choose Downloads > EthoVision XT > Sample Experiments. Technical Support Help Desk If you run into problems of any kind, please let us know. You can contact us via our web site my.noldus.com. Please check this manual carefully before contacting Noldus. Send Your Data If you need to send EthoVision XT data by e-mail, please use the Backup procedure (File > Make Backup) to make a copy of your experiments, and send them as attachments. For more information on how to use the Backup and Restore functions, see the EthoVision XT Help. Replacement of Components If any component breaks or wears out, please contact our Technical Support Department to have it sent back to us. Please note that in any case you must send it to our international headquarters (Wageningen, The Netherlands) no matter where you are. Broken components will be fixed or replaced with new ones. Important: Plastic components (such as the cage walls) will only be replaced or repaired free of charge if they are broken due to a defect of workmanship and the damage is reported within one month of shipment. Other components are covered by a one year guarantee; to claim under guarantee you must report the damage within one year of shipment. It is possible that you may have a service contract entitling you to free replacement of parts for a longer period, please contact the support department if you are not sure. In any case we can still fix or replace the parts, but it may be necessary to levy a charge. The guarantee is only valid if you treat the PhenoTyper as described in this manual. In any case, shipping broken parts is at your expenses, while sending repaired or replacing parts back to you will be at our expenses. Important: If you connect the PhenoTyper to any third-party products, such as a video tracking system other than EthoVision XT, Noldus Information Technology is not responsible for maintenance of that product, or for damage done to the PhenoTyper by that product. To order spare parts for PhenoTyper, see Appendix A of the PhenoTyper - EthoVision XT 18 - Reference Manual. There you will find a list of the parts available. Please contact your Noldus representative to send your order. The PhenoTyper Camera PhenoTyper 1 (Analog Camera) The camera is integrated in the PhenoTyper 1 Top Unit. PhenoTyper 2 (Digital Camera) The camera is mounted on the Top Plate of the PhenoTyper 2 Top Unit. For issues related to the camera image, see Troubleshooting in the EthoVision XT Help. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - Monitor URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-monitor Chapter: PhenoTyper Analysis Profile You can create an analysis profile to calculate the number of beam breaks or select various state variables associated with the beam breaks. - Choose Analysis > Analysis Profile > New. - From the Dependent Variables list, under Hardware, choose one of the following: - Hardware continuous if you want to calculate the total number of beam breaks or visualize the raw data on the timeline. - Hardware state if you want to calculate the time when the number of beam breaks was higher or lower than a specific threshold, or the time that a beam was broken, or the time that a cue was on or off. - In the window that opens, next to Device type, select Beam Controller (PTBC-001x). - Next to Device, select the correct device name, if you have more than one connected. - Next to Signal, select the option you require. - For Hardware continuous, select Beam 1 breaks or Beam 2 breaks, depending on which port on the IR Beam Controller the Food Sensor was connected to. - For Hardware state, you have a few options: - Select Beam 1 breaks / Beam 2 breaks and then next to Value select the criterion you are interested in (e.g. to mark the time that the number of Beam 1 breaks >= 100). - To mark the time that a beam was broken, select Is beam 1 broken / Is beam 2 broken, then next to Value select the criterion (e.g. Is beam 1 broken True). - To mark the time that a cue was on or off, select Is cue 1 on / Is cue 2 on, then next to Value select the criterion (e.g. Is cue 1 on False). - Click Add. Note: Beam 1 breaks and Beam 2 breaks correspond to the signals of the two sensors that the IR Beam Controller can control. For each IR Beam Controller, the two sensors can only be used in the same cage (arena). To analyze both beam breaks, add the Hardware continuous twice. Cue Activation With the Hardware command you can calculate statistics of and visualize the events of type "cue on/off", provided that the IR Beam Controller box was connected to an optical cue device (e.g. a LED). - From the Dependent Variables list, under Hardware, click Hardware command. - In the Hardware Command window, next to Device type, select Beam Controller (PTBC-001x). - Next to Device, select the correct device name, if you have more than one connected. - Next to Command, select one of the options: Cue 1 on, Cue 1 off, Cue 2 on, and Cue 2 off. - Click Add. Statistics and Visualization - To calculate the statistics for the variables defined in the previous step, choose Analysis > Results > Statistics & Charts. Select the correct Data profile and Analysis profile from the lists on the toolbar and click Calculate. - To visualize the feeding events, choose Analysis > Results > Integrated Visualization. Select the correct Analysis profile from the list on the toolbar. You will now see in the Time Event Plot when beam breaks took place. Examples - Hardware continuous - Beam 1 breaks: An interruption of the IR beam is scored as one in the timeline. The remaining timeline, with no interruption of the beam, is scored as zero. - Hardware state - Beam 1 breaks >= 10: The state is active after the tenth feeding event occurs. This event is scored in the Hardware continuous plot. - Hardware state - Is beam 1 broken / True: This state is active when the IR beam is interrupted. - Hardware state - Is beam 1 broken / False: This state is active when the IR beam is not interrupted. Note: If the plots of the Hardware continuous variable appear empty, that is because the data are shown as small dots. Click Show/Hide > Show Graph Data Points and zoom in the plot to show the dots larger. Why Use the TTL to 28V Interface? The Noldus TTL to 28V Interface (Noldus type number: PTMA-0010) provides a simple plug-and-play connection between the Noldus USB-IO box / Mini USB-IO box / Nortio T12T TTL Terminal Hub and several hardware devices. You need the TTL to 28V Interface when: - You want to control one or more hardware devices, such as doors in a radial arm maze, the Atlantis platform, and sound generators. - You want to control the DanioVision Toplight Unit. In that case, see the DanioVision DVOC-0041 - Reference Manual. Note: The TTL to 28V Interface converts the TTL signals from one of the following devices: USB-IO box / Mini USB-IO box / Nortio T12T TTL Terminal Hub into the Med Associates standard 28-Volt control signal. Furthermore, the TTL to 28V Interface can control two Med Associates devices, so it is a good alternative for the SG-230 or SG-230R TTL-to-28V adapter supplied by Med Associates. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - Phenotyper® URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-phenotyper Chapter: PhenoTyper Contents - Introduction - The PhenoTyper Camera - The Top Unit Interface - The Pellet Dispenser and the Pellet Receptacle - The Lickometer - PhenoWheel - The Feeding Monitor - The TTL to 28V Interface - Appendix A: Test Sheet for Focusing - Appendix B: Index Introduction About This Manual - When You Need This Manual: Refer to this manual for guidance on setup, configuration, and use of PhenoTyper hardware and associated EthoVision XT software settings. - Using This Manual: This manual is organized by hardware component, with each chapter covering installation, operation, and statistics calculation. Other Documentation - Manuals: Additional manuals are available for related Noldus products and software. - Sample Experiments: Sample experiments are provided to help you get started with EthoVision XT. Technical Support - Help Desk: Contact Noldus Information Technology BV for technical assistance. Phone: +31-317-473300, Email: info@noldus.nl, Web: www.noldus.com. - Replacement of Components: For replacement parts, contact Noldus technical support through the channels listed above. The PhenoTyper Camera PhenoTyper 1 (Analog Camera) - Camera Focus and Orientation: Instructions for adjusting the focus and physical orientation of the analog camera module. - Camera Settings: Configuration settings specific to the analog camera. PhenoTyper 2 (Digital Camera) - Package Contents: Lists all items included with the digital camera package. - Camera Module: Description and overview of the digital camera module components. - Camera Focus and Orientation: Instructions for adjusting the focus and physical orientation of the digital camera module. - Camera Settings: Configuration settings specific to the digital camera. The Top Unit Interface General Information - Components: Overview of the components that make up the Top Unit Interface. - Technical Specifications: Detailed technical specifications for the Top Unit Interface. Connect the Top Unit Interface - Connection Scheme: Diagram and instructions for connecting the Top Unit Interface to the system. The Pellet Dispenser and the Pellet Receptacle General Information - The Pellet Dispenser: Overview of the pellet dispenser hardware and its function. - Contents of the Pellet Dispenser Packages: Lists all items included in the pellet dispenser package. - Pellet Types: Description of compatible pellet types for use with the dispenser. Install the Pellet Dispenser - The Pellet Receptacle: Instructions for installing the pellet receptacle. - Technical Specifications: Detailed technical specifications for the pellet dispenser. - Reliability: Notes on the reliability and performance of the pellet dispenser. Work with the Pellet Dispenser - EthoVision XT - Prepare the Experiment: Steps for preparing an experiment in EthoVision XT. - EthoVision XT - Experiment Settings: Configuration of experiment-level settings in EthoVision XT. - EthoVision XT - Arena Settings: Configuration of arena settings in EthoVision XT. - EthoVision XT - Trial Control Settings: Configuration of trial control settings in EthoVision XT. - Check That the Pellet Dispenser Works: Procedure for verifying correct operation of the dispenser. - Control the Pellet Dispenser Manually: Instructions for manual operation of the pellet dispenser. - Work with the Pellet Receptacle: Instructions for using the pellet receptacle during experiments. - Test the Pellet Receptacle: Procedure for testing the pellet receptacle functionality. Calculate the Statistics for the Pellet Dispenser - Analysis Profile: Setting up the analysis profile for pellet dispenser data. - Statistics and Visualization: Available statistics and visualization options for pellet dispenser data. Maintenance and Troubleshooting - Correct Usage of the Pellet Dispenser: Guidelines for proper use to ensure longevity and accuracy. - Clean the Pellet Dispenser: Cleaning procedures for the pellet dispenser. - Troubleshooting: Common issues and their solutions for the pellet dispenser. The Lickometer General Information - The Lickometer: Overview of the lickometer hardware and its function. - Technical Specifications: Detailed technical specifications for the lickometer. Install the Lickometer Step-by-step instructions for physically installing the lickometer in the PhenoTyper setup. Work with the Lickometer - EthoVision XT - Prepare the Experiment: Steps for preparing an experiment in EthoVision XT. - EthoVision XT - Experiment Settings: Configuration of experiment-level settings in EthoVision XT. - EthoVision XT - Arena Settings: Configuration of arena settings in EthoVision XT. - Check That the Lickometer Works: Procedure for verifying correct operation of the lickometer. - Acquire the Data: Instructions for acquiring lickometer data during an experiment. - View the Data in the Hardware Log: How to access and review lickometer data in the hardware log. Calculate the Statistics for the Lickometer - Analysis Profile: Setting up the analysis profile for lickometer data. - Statistics and Visualization: Available statistics and visualization options for lickometer data. PhenoWheel General Information - PhenoWheel: Overview of the PhenoWheel hardware and its function. - Technical Specifications: Detailed technical specifications for PhenoWheel. Install PhenoWheel - Components: Lists the components included with PhenoWheel. - Procedure: Step-by-step installation instructions for PhenoWheel. Work with PhenoWheel - EthoVision XT - Prepare the Experiment: Steps for preparing an experiment in EthoVision XT. - EthoVision XT - Experiment Settings: Configuration of experiment-level settings in EthoVision XT. - EthoVision XT - Arena Settings: Configuration of arena settings in EthoVision XT. - Acquire the Data: Instructions for acquiring PhenoWheel data during an experiment. Calculate the Statistics for PhenoWheel - Analysis Profile: Setting up the analysis profile for PhenoWheel data. - Statistics and Visualization: Available statistics and visualization options for PhenoWheel data. The Feeding Monitor General Information Overview of the Feeding Monitor hardware, its purpose, and how it integrates with the PhenoTyper system. Install the Feeding Monitor Step-by-step instructions for physically installing the Feeding Monitor in the PhenoTyper setup. Work with the Feeding Monitor - EthoVision XT - Prepare the Experiment: Steps for preparing an experiment in EthoVision XT. - EthoVision XT - Experiment Settings: Configuration of experiment-level settings in EthoVision XT. - EthoVision XT - Arena Settings: Configuration of arena settings in EthoVision XT. - Acquire the Data: Instructions for acquiring Feeding Monitor data during an experiment. Calculate the Statistics for the Feeding Monitor - Analysis Profile: Setting up the analysis profile for Feeding Monitor data. - Statistics and Visualization: Available statistics and visualization options for Feeding Monitor data. The TTL to 28V Interface Why Use the TTL to 28V Interface? Explanation of the purpose and benefits of using the TTL to 28V Interface with PhenoTyper hardware. Install the TTL to 28V Interface Step-by-step instructions for installing the TTL to 28V Interface. Technical Specifications Detailed technical specifications for the TTL to 28V Interface. Appendix A: Test Sheet for Focusing A reference test sheet used to assist with focusing the PhenoTyper camera during setup. Appendix B: Index An alphabetical index of key terms, components, and topics covered in this manual. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## PhenoTyper XT 19 Service - Phenowheel URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/phenotyper/page/phenotyper-xt-19-service-phenowheel Chapter: PhenoTyper General Information PhenoWheel is a PhenoTyper add-on for measuring activity in a running wheel in a PhenoTyper cage. PhenoWheel consists of: - A specially prepared cage wall (type PTC3-RW01) for the PhenoTyper 3000 cage. - A running wheel (type PTRW-0150) with a 15-cm diameter. To use PhenoWheel you also need: - EthoVision XT with the Trial and Hardware Control module. - As interface device: the Noldus USB-IO box or the Noldus Nortio system. - The PTCN-001x Phenocount module: - PTCN-0010 for use in combination with the USB-IO box (SDI mode only). - PTCN-0011 for use in combination with the USB-IO box (SDI mode, or TTL mode) or with the Nortio system (TTL mode only). Note: The Med Associates Activity Wheel for rats can be used with the USB-IO box. Note: The working modes TTL and SDI specify how data are sent out to EthoVision XT. - In TTL mode (default factory mode in PTCN-0011), each wheel turn results in a TTL pulse being sent to EthoVision XT. - In SDI mode, each wheel turn results in an increase of the internal counter by 1. The current number of turns is read by EthoVision XT at regular intervals. Package Contents - Cage wall (type PTC3-RW01) for PhenoTyper 3000 series. - Running wheel (type PTRW-0150) of diameter 15 cm (5 29/32 inches). - PhenoCount module. - A network cable with RJ45 connectors, 1 meter long. Technical Specifications - Noldus Device Number: PTCN-0011 - Power Supply: 12–24 V DC - Current Consumption: Standby 20 mA - Connectors: - To USB-IO box, Nortio: RJ45 8 pin modular - To magnetic sensor: Molex 2 pin MiniFit Jr. - Input/Output: SDI type 1, TTL (select by jumpers) - Dimensions: Electronics box 80 x 45 x 21 mm; 3 5/32 x 1 49/64 x 53/64 inches (l x w x h); ground plate 80 x 55 mm; 3 5/32 x 2 11/64 inches - Weight: 200 grams - Compliance: CE compliant in accordance with EMC directive 2004/108/EC - Interface: Noldus USB-IO box and Nortio T12T TTL Terminal Hub - Applications: PhenoWheel is suitable to measure running wheel activity in mice Install PhenoWheel Installation Procedure - If not already done, insert the larger bolt (3) in the white plastic holder (1) with the head at the opposite side of the ball bearing, then place the large washer (4) around the bolt. Attach the white holder to the wheel using the bolts with dome nuts and their washers (2); all four washers should be placed at the inner side of the wheel. The dome nuts should face the inner side of the wheel. Before fixing the wheel to the wall, make sure that the washer with the larger diameter (5) is placed between the holder and the PhenoTyper wall so the wheel can rotate freely. - Mount the running wheel to the wall; place the plain washer (6), the spring washer (7), and finally fasten using the wing nut (8) on the outside (back of the PhenoTyper wall), while keeping the large bolt firm using a hexagonal key from the inside. Important: Use limited force when fastening the bolt. - Attach the magnetic sensor (1) to the wall with the small bolt. Adjust the position of the magnetic sensor by rotating it so the magnet on the running wheel (2) passes the outside edge of the sensor. - Connect the magnetic sensor to the PTCN-001x counter module. - Check whether the magnetic sensor is in the correct position relative to the magnet on the running wheel. Rotate the wheel; each time the magnet passes the sensor, the Active LED on the counter blinks. - Follow the appropriate section below to connect PhenoCount to your interface device. Note: Although network cables are used in the following connection schemes, the signal from and to the PhenoWheel is not a network signal. Do not connect PhenoWheel via a network hub or similar device. Connect PhenoWheel Through the USB-IO Box - If you have PhenoCount version PTCN-0010, the device only works in SDI mode; you can skip this step. If you have PhenoCount version PTCN-0011, you can set the device to work in TTL mode (default factory mode) or SDI mode. Unscrew the cover of the PhenoCount module, locate the jumpers on the board, and adjust them based on your chosen working mode. Then close the cover of the PhenoCount module. - Connect the USB-IO box to the EthoVision XT computer through a USB cable. - If the PhenoCount module is set to TTL mode (default in PTCN-0011), connect the PhenoCount to one of the TTL Control ports on the USB-IO box using a network cable. If the PhenoCount module is set to SDI mode, connect the PhenoCount to one of the SDI Control ports on the USB-IO box using a network cable. Connect PhenoWheel Through the Nortio System Important: In order to use PhenoWheel in combination with the Nortio system, the PhenoCount module version must be PTCN-0011 and the jumper settings inside the PhenoCount module must be configured to make PhenoCount work as a TTL device. - Unscrew the cover of the PhenoCount module. - Locate the jumpers on the board. These are pins with blue or red covers numbered 1–4. - Place the red jumper in the correct position for use with the Nortio system. - Close the cover of the PhenoCount module. You can now connect the PhenoCount module to the Nortio system: - Connect the Nortio Core to the EthoVision XT computer using a network cable. - Connect the Nortio T12T TTL Terminal Hub to the Nortio Core using the backbone input cable. - Connect the PhenoCount module (version PTCN-0011) to one of the TTL control ports of the Nortio T12T TTL Terminal Hub using a network cable. - Make sure that the Nortio Core is connected to a power supply. For information on how to install the Nortio system, see the section The Nortio System in the EthoVision XT Trial and Hardware Control Reference Manual. Notes - The Read yellow LED indicates when EthoVision XT reads the number of rotations since the last reading event. - For more information on the USB-IO box and the Nortio system, see the EthoVision XT Trial and Hardware Control Reference Manual. Source: PhenoTyper - EthoVision XT 19 Service Manual, Noldus Information Technology --- ## The Observer XT - Back up your data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-back-up-your-data Chapter: The Observer XT Back Up Your Data Use the backup functionality in The Observer XT to: Make a safe copy of your project. Transfer your project to another computer. It is also possible to group events and to select events or intervals with a minimum duration. Also, you can make time intervals based on a combination of behaviors and time, with manual interval selection. And you can analyze your data in regular time intervals. For more information on data selection, see Select Data for Analysis in The Observer XT Help. For more information on analyzing and visualizing data, see Calculate statistics and Visualize data in The Observer XT Help. Back up your data Copying files with Windows Explorer does not backup everything. Therefore, always use the backup functionality in The Observer XT. Choose File > Make Backup. This makes a backup of your entire project in a file with the name of your project and the extension*.vpb. Make sure you create a backup at least once a day. Do not forget to create backups of your videos as well. Store the backups at a safe location, which is in a different building from the computer with The Observer XT. To open a backup of your project, choose File > Restore Backup. Open the *.vpb file. Source: The Observer XT 17 - Quick Start Guide --- ## The Observer XT - BIOPAC MP System Integration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-biopac-mp-system-integration Chapter: The Observer XT Introduction This document describes how to achieve automatic synchronization between observational data in The Observer XT and the physiological data acquired with and exported from the BIOPAC MP160 system using BIOPAC's AcqKnowledge 5.0 software. A large part of this note also applies to AcqKnowledge 4.x. The versions 4.4 and 5.0 of AcqKnowledge support the import and export of event markers in The Observer XT data format. This means that you can: - Import AcqKnowledge markers into an observation in The Observer XT. - Export the events scored in The Observer XT to an AcqKnowledge data file. Systems Used The Observer XT - Processing unit: Dell Precision T5810 - Processor: E5-1620 v3 (Xeon 3.50 GHz 4-core) - RAM Memory: 8 GB - Operating system: Windows 10 Professional Edition - Software: The Observer XT 16, N-Linx Server 1.3 The N-Linx Server can also be installed on a third computer connected to The Observer PC and the BIOPAC PC. BIOPAC MP160 and AcqKnowledge Software - Processing unit: Dell Precision T5810 - Processor: E5-1620 v3 (Xeon 3.50 GHz 4-core) - RAM Memory: 8 GB - Operating system: Windows 10 Professional Edition - Software: AcqKnowledge 5.0.2032 with Network Data Transfer Module, N-Linx Agent 1.1.1.0 Notes: - When you install the N-Linx Agent on the AcqKnowledge computer, you also install a second piece of software, called AcqKnowledge Control. - You can also install N-Linx Server on a third computer, connected to The Observer XT computer and the AcqKnowledge computer through a local network. Use this configuration when you want to use N-Linx Server to communicate with other applications, independent of The Observer XT. For Further Information and Help Other manuals: - The Observer XT Help - Quick Start Guide - The Observer XT - Reference Manual - The N-Linx - The BIOPAC MP hardware and AcqKnowledge software manuals - Manuals and user guides on www.biopac.com For technical support, please contact the Noldus Customer Support Center: https://www.noldus.com/support-center. Browse the customer support database with questions asked by The Observer XT users and answers from the support department. Automatic Synchronization After the software is properly installed and configured, automatic synchronization of observational and physiological data is obtained with the following basic steps: - Set The Observer XT and AcqKnowledge for DAQ co-acquisition. On the AcqKnowledge computer, install the N-Linx Agent communication software, which ensures the files are correctly transferred between computers. In AcqKnowledge, define the channels for data acquisition and one channel for the synchronization signal. In The Observer XT, specify which synchronization signal you want to use (On-Off or Time Code (TCAP)) and the sample rate of the BIOPAC system. Connect the Observer XT computer and the BIOPAC system with a synchronization cable. - Carry out a Live Observation while The Observer XT sends out the synchronization signal to the BIOPAC system. Simultaneously, the BIOPAC AcqKnowledge software acquires data through its modules (e.g., PPG, ECG, GSR). - When you stop the observation in The Observer XT, the AcqKnowledge data files are imported automatically into The Observer XT through the local network. The data files contain both the physiological data and the time information from the synchronization signal. The observational and physiological data are automatically synchronized. Notes: - If you do not have N-Linx installed on the AcqKnowledge computer, you must export the AcqKnowledge data file to an ASCII export file. Make sure to also include header information in this export file. - Optionally, in The Observer XT you can make a data selection, visualize your data, carry out further data analysis and export the synchronized observational and physiological data. For details, see The Observer XT Help. Synchronization Cable Your Observer XT system comes with a synchronization cable. This has the following connectors: For The Observer XT computer: A 9-pin serial connector. Most modern computers do not have a 9-pin COM port; instead, connect this end to a USB-to-serial adapter, then the USB end to the computer. For the BIOPAC MP160 system: A mono mini-jack. Connect this end to the input of the INSO isolation adapter. Connect the INISO adapter to analog channel 16 (or any other available channel) on the HLT100C module with the RJ11 cable. Software Setup Install N-Linx Server Important: Install N-Linx Server on the The Observer XT computer, or on a computer connected to both the AcqKnowledge computer and the The Observer XT computer through a local network. - Insert The Observer XT installation USB stick in one of the PC's USB ports. Browse to Drivers and Tools\N-Linx Server. - Double-click N-Linx Server Setup.exe. - Next to Installation type choose Standard, unless you want to specify an installation folder other than the default one (C:\Program Files\Noldus\N-Linx Server). - Follow the instructions on your screen. Install and Connect N-Linx Agent Important: Install this piece of software on the AcqKnowledge computer. - Insert The Observer XT installation USB stick in one of the BIOPAC PC's USB ports. Browse to Drivers and Tools\N-Linx Agent. - Double-click N-Linx Agent Setup.exe. - Next to Installation type choose Standard, unless you want to specify an installation folder other than the default one (C:\Program Files\Noldus\N-Linx Agent 1). - Select Biopac AcqKnowledge control, and click Next. - Accept the license agreement, click Install and follow the instructions on your screen. - If the N-Linx Agent window does not open after installation, at the bottom-left corner of the screen, on the system tray, click the arrow icon and double-click the N-Linx Agent icon. - Next to N-Linx Server Address, enter the IP address of the computer where N-Linx Server is installed. This IP address must be fixed. If The Observer XT and N-Linx Server are installed on the same computer, enter localhost. You can also enter the Computer name instead of the IP address. To find the Computer name of the computer where N-Linx Server is installed, on that computer open the Control Panel and choose System. Locate Computer name. - Click Connect. If connection is established, the message at the bottom of the N-Linx window says Connected. When properly connected, N-Linx Agent shows the connected icon in the system tray. Set AcqKnowledge for DAQ Co-Acquisition The aim of this procedure is: - To allow The Observer XT to gain access to AcqKnowledge. This is done in Networking Preferences in AcqKnowledge. - To specify the sample rate, the recording channels, and the triggering event (optional) in AcqKnowledge. Prerequisites: - AcqKnowledge is running, the experiment is open and the MP160 system is powered up. - AcqKnowledge must have the licensed Network Data Transfer (NDT) module. If that is not the case, automatic import of AcqKnowledge data into The Observer XT will not work. Configure Networking Preferences in AcqKnowledge - In AcqKnowledge, choose Display > Preferences. - Click Networking and select Enable network data transfer. - Next to Control TCP port, leave the number as it is. Next, click OK. Set the Sample Rate in AcqKnowledge - Choose MP160 > Set Up Data Acquisition. - In the Data Acquisition Settings window, select the Length/Rate tab. - Choose the Sample Rate. Define the Channels for Data Acquisition - Click the Channels tab. - Select the channels you want to use. You can set up channels automatically by using the Add New Module button to add the modules currently connected to the BIOPAC system. For details, see the AcqKnowledge documentation. - Click the View by Modules button. For each module, de-select the option below the green symbol. Important: If the calibration option is selected, The Observer XT will not be able to start recording using N-Linx, because AcqKnowledge is set to start calibration automatically every time you start acquisition. If you require auto calibration before acquisition, create a separate graph template with the option selected. Name the template for example "PPG EDA for Calibration". Use that template to do calibration and a short test recording. Then, load the graph template with the option de-selected (named for example "PPG EDA for Acquisition") before starting acquisition from within The Observer XT. Define the Channel for the Synchronization Signal - Click the Channels tab. - Select the channel to which you connected the synchronization cable. Click the Analog tab and select the channel to which you connected the synchronization cable. Optionally, rename the Label for this channel to a logical name (for example, Sync signal or Time code signal). - For this channel and all channels defined for data acquisition, select the Acquire and Plot check box. Set The Observer XT for DAQ Co-Acquisition Connect The Observer XT to N-Linx Server Follow this procedure just once. The settings are also valid for any new The Observer XT project that you create. - In The Observer XT, choose File > Preferences. - Click N-Linx Settings on the left. - Select Use N-Linx Server to connect with other applications. - Next to N-Linx Server address, enter the IP address of the computer with N-Linx Server. Leave the default entry localhost if The Observer XT and N-Linx Server are installed on the same computer. You can also enter the Computer name of the computer where N-Linx Server is installed, instead of its IP address. On the computer where N-Linx Server is installed, open the Control Panel and choose System. Locate Computer name (not Full Computer name). - Make sure the N-Linx Server port is 5672. Ask your system administrator for assistance if this port is used by another program. - Click Test connection, and check that the message appears Connected. If connection fails, it means that N-Linx Server is not installed properly. Reinstall N-Linx Server, or check that the Windows Firewall is not blocking traffic through port 5672. Project Setup Follow these steps for each new The Observer XT project you create to work together with the BIOPAC acquisition system. - Open the project and choose Setup > Project Setup. - Under Observation Source, select Live Observation. - In the Devices window, select DAQ Settings and click the Edit settings button at the bottom-right. - In the DAQ Hardware Settings window, select the COM1 port as the Output Device. If there is no COM port available on the The Observer XT computer, use a USB-to-COM converter. The COM port number is randomly assigned by the USB-to-serial converter driver, so make sure to select the active COM port, that is, the one that is Online. For more information, see the documentation of the USB-to-COM device to see which COM port the device uses. - Under Signal Type, select Time Code (TCAP), and next to DAQ sample rate, enter the same value as the acquisition sample rate specified in AcqKnowledge. Note that there may be other programs that use COM ports. In that case one or more COM ports in the list are not available. De-install those programs if necessary to free a COM port that can be used by The Observer XT. - In the Devices window, check that Biopac AcqKnowledge is selected. If you do not see this item, it is likely that N-Linx Agent is not installed, or Biopac AcqKnowledge Control was not selected when you installed N-Linx Agent. - Optional: If more persons are being observed during a single test session, and the BIOPAC system collects data of one of those persons, not the others, it is a good idea to label the data with the subject name. In the Devices window, double-click the item Biopac AcqKnowledge Control and next to Identify device as enter the role of that subject. When imported to The Observer XT, the physiological data sets will be marked with the subject's role. - Click OK. Notes: - Also use the option Identify device as to specify the subject's role in case you connect multiple BIOPAC systems. Always give unique names. The physiological data streams will be imported with those names. - You can also specify a template for recording physiological data directly in The Observer XT. In the Devices window, double-click the item Biopac AcqKnowledge Control and under Identify device as select the template you want to use. Make sure that the template corresponds to the channels currently connected to the MP160 system. Data Acquisition Carry Out Data Acquisition - In The Observer XT, create a new observation (Alt+F6). - To start data acquisition, click the Start Observation button. - To stop data acquisition, click the Stop Observation button. - At the end of acquisition, the physiological data sets are imported automatically. Check that the data sets are listed in the Project Explorer, under External Data Files for the current observation. Monitoring AcqKnowledge During Acquisition In the AcqKnowledge program, you can visualize your channels during acquisition. This is useful when you want to check whether the synchronization signal is actually received by the BIOPAC system. Select the Plot check box in the Channels tab of the Data Acquisition Settings window. Checking N-Linx Agent Status On the AcqKnowledge computer, you can check the status of N-Linx Agent. Click the arrow icon on the system tray, then double-click the N-Linx Agent icon. The N-Linx Agent window shows the status of Biopac AcqKnowledge Control and The Observer XT: - The Observer XT is visible and Online when the program is open. - Biopac AcqKnowledge Control is Offline when it is installed, but not active. This is the case immediately after installation of N-Linx Agent and after the computer is restarted. - After creating an observation in The Observer XT, the status of Biopac AcqKnowledge Control becomes Online. - Online means that Biopac AcqKnowledge Control is started and therefore available for communication. Once Biopac AcqKnowledge Control is started, it remains running until the PC is shut down. Source: The Observer XT 17 - Technical Note - BIOPAC MP System --- ## The Observer XT - E-Prime: Data Import and Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-e-prime-data-import-and-analysis Chapter: The Observer XT Analyze Data Click the + symbol next to the behaviors to expand the chart and view the modifiers. Notes - All the system events are states of Start-stop type (see Set up your Project in The Observer XT Help for information on this event type). - There is usually an empty area in the chart from the observation start time (Relative time 0) to the start of the first event (Instructions in the example above). This is the time from when the E-Run starts to when the first instructions are shown on the screen. This time may vary between observations, depending on how long it takes to fill in the information in the dialog boxes that appear at the start of the experiment (Subject ID, Session Number etc.) The E-Prime Events in the Coding Scheme Subjects Behaviors The name of a behavior depends on the name of the corresponding E-object set in E-Prime (see Prepare the experiment in E-Studio). System events and user responses are stored in separate Start-Stop behavior groups, System Behaviors and User Behaviors. - System Behaviors contains events named Show followed by the E-object name. The Show Stimulus behavior has a modifier group attached, named Media. This group contains the names specified in the Trial List under Stimulus. - User Behaviors contains a behavior named Answer. The Answer behavior has two modifiers attached, Response and Correct. Nominal Modifiers In this example, the following modifier groups have been imported, with their elements: - Response (nominal). Contains Response: followed by the character(s) entered by the test participant. - Media (nominal). Contains the filenames of the stimuli, or other attributes you may want to import. - Correct (nominal). Contains Correct: followed by the correct response for the corresponding stimulus (that is set in E-Prime's Trial List). Numerical Modifiers If you specified in E-Prime that the answer was numerical, they are added as a numerical modifier group to the Coding Scheme. See Example 3: To import responses as numerical modifiers. Note: You can modify the names of coding scheme elements at any time, however we advise you not to do so. If you import new data, these will have the names set in E-Prime, and added to the coding scheme. The same event type could therefore be represented by two or more different subjects, behaviors and modifiers, leading to wrong analysis results. Analysis The analyses in The Observer XT allow you to calculate most statistics on the stimuli and the user responses. Nominal (Default) Responses Nominal responses are analyzed with a Behavior Analysis. Choose Analyze > Behavior Analysis > New and click Calculate. Example 1: Correct vs. Incorrect Responses In the default Behavior Analysis result, each cell contains the statistics of a specific combination of behavior and modifiers. For example, the table lists the statistic Total Number for the events of type Answer and a specific combination of the modifiers Correct and Response. In this example, the test participant gave three times a correct response: one time when Correct= 1 and Response= 1, and two times when Correct =2 and Response =2 (first two lines). In one case the test participant gave an incorrect response, when choosing 2 when the Correct response was 1 (third line). Therefore, the percentage of correct responses is 3/(3+1)= 75%. In the table, the response "SPACE" was given by the user to start the procedure and should be ignored. "Any Modifier" is the number of events with any combination of modifiers. Example 2: Response Time (RT) There are two main cases: - If the stimulus ends exactly when the user gives a response, the response time is equal to the stimulus presentation time. In this case the response time is the duration of the state event Show Stimulus. - If the stimulus duration is independent of the user's response, follow the steps below. - In the Data profile, choose Select Intervals - By manual selection and define an interval from the start of the event Show Stimulus to the start of the event User Answer. - Choose Analyze > Behavior Analysis > New. - Click the Statistics button and under Intervals select Analyzed interval duration. - In the results table, look for the column named Analyzed interval duration. Example 3: Response Time Grouped per Response In this example, Response time (RT) is calculated for when subjects gave a particular response. For simplicity, the solution shown here calculates RT only when subject responses were correct. For example: - Correct response was "1" - User Response was "1" - RT was ... - Correct response was "2" - User Response was "2" - RT was ... - Define an interval that captures the response time, as in Example 2. Choose Intervals - By manual selection and select From System Show Stimulus to User Answer. This is the least selective interval, because it captures all instances of response times, even those for incorrect responses. The following steps add more interval criteria, to select only the instances of response time when Correct =1 and Response =1, OR Correct =2 and Response =2. - Create two branches that point to two result containers (to create a new result container, click Result Containers - Result). One branch will select Correct = 1, Response = 1, the other Correct = 2, Response = 2. Name the result boxes R1 C1 and R2 C2, respectively. - In each branch, define intervals (Select intervals - By manual selection) that include a correct answer. Intervals are defined From 2.00 s before start of User Answer to 0.00 seconds after end of User Answer. However, intervals can only be defined with one modifier (either Correct or Response). Therefore, define two intervals in each branch. For the branch ending with R 1, C 1 (Correct response 1 when Response was 1), the first interval is based on Correct = 1, the second is based on Response = 1. By placing the two Interval boxes one after the other, define an interval that meets both criteria, that is, an interval for when Response 1 was Correct. Create a similar selection in the other branch, for Correct =2 and Response =2. Note: Choose "2 seconds before User Answer" to make sure that the time around the answer is included in the selection. Choosing 0 seconds for a point event like User Answer would make the selection invalid. The intervals defined in this step reduce the total number of instances of response time, because they are set after the first, less selective Interval box made in step 1. Only the time segments corresponding to the most selective criterion will be in the Result Container. - Use a Filter to choose which data to analyze. This removes all events in the selected intervals that are not of interest. This box should be placed at the end of the branch. - The Data profile is now configured. For details about selecting events and intervals for analysis, see Select Data for Analysis in The Observer XT Help. - Select Analyze > Visualize Data. The two charts at the top show the intervals (response times) selected for R 1, C 1. The other charts show the same for R 2, C 2. You can see that the first instance of response time is not selected because of the incorrect response given (Response = 1, Correct = 2). - Run Behavior Analysis and look at the statistics that refer to a specific response (this is indicated with the Result Container column header). - To group results, select Layout > de-select Intervals. Look at the Mean duration statistic for the mean response time. Notes: - This data profile is also valid when the response does not terminate the stimulus presentation. - You can create more complex data profiles by adding branches that select instances of incorrect responses (for example: Response was "1", Correct was "2"). Numerical Responses If you specified in E-Prime that the answer was numerical, for example to rate the stimulus, you may want to calculate numerical statistics such as the mean value or median. See Example 3: To import responses as numerical modifiers for how to specify the response as numerical. In The Observer XT, carry out a numerical analysis. Choose Analyze > Numerical Analysis > New and click the Calculate button. By default the minimum value, maximum value and mean value of the numerical modifiers are calculated. To select other statistics, click the Statistics button on the toolbar and select the statistic under Numerical Modifiers. For more information, see Calculate Statistics in The Observer XT Help. Lag Sequential Analysis With Lag Sequential Analysis you can quickly calculate how often a stimulus triggers a specific response. Choose Analyze > Lag Sequential Analysis > New. Example: How Often a Stimulus Produces a Correct Response In this example, a stimulus picture is presented for a few seconds, and the test participant must enter a response. The response ends the presentation of the stimulus. For this reason a State lag sequential analysis can be carried out (a Time lag analysis is also possible). The stimulus presentation is recorded as the behavior Show Stimulus and its modifier Media. The test participant's response and the correct response are stored as modifiers Response and Correct of the behavior Answer, respectively. - Click Settings and under Lag Type choose State lag. - Because the stimulus and the response events are events scored for different subjects (System and User), de-select Restrict lag to Subject-Behavior group combination. - Run analysis. In the Lag Sequential Analysis result, locate the part of the table that contains the transitions from the behavior Show Stimulus (on the rows) to the behavior Answer (on the columns). In this example, the stimulus BlueCar.bmp was followed two times by a correct response (Response= 2 and Correct= 2). The stimulus RedCar.bmp was followed by one correct (Response= 1 and Correct= 1) and one incorrect response (Response= 2 when Correct= 1). For more information, see Lag Sequential Analysis in The Observer XT Help. Advanced Settings Use Advanced Settings to change basic settings like the port number for communication between The Observer XT PC and the E-Prime PC, and the location of the E-Prime software and experiments. If some events are not imported correctly to The Observer XT, see Prepare the experiment in E-Studio. Procedure - On the E-Prime computer, start Noldus E-Prime Server (Apps > Noldus > Noldus E-Prime Server). - Click Advanced Settings. IP Address This is the IP address of the E-Prime computer. It is shown for information purposes only, and cannot be changed. This number must be entered in the Noldus E-Prime Client software. Port The port number should always be the same as that set in The Observer XT. The default is 155. E-Run Location This is the location on the E-Prime PC where the E-Run.exe software is installed. If it has been installed on another location, specify that location here. The default is C:\Program Files (x86)\PST\E-Prime 3.0\Program. For E-Prime 2.0, the default location is C:\Program Files (x86)\PST\E-Prime 2.0\Program. Experiment Text Output This is the folder where the E-Prime output text file is stored. By default, this is the same folder as where the experiment file (*.ebs3 / *.ebs2) you are using is stored. Notes: - If you change the Port number after clicking Start, this has no effect on the software. Click Restart to activate communication on the new port. - If you set the Experiment text output location in E-Prime different from that of the experiment file (*.ebs3 / *.ebs2), you must specify this new location also in Noldus E-Prime Server. - When clicked, the Start button of Noldus E-Prime Server does not start the E-Prime experiment; it activates the E-Prime Controller to accept messages from The Observer XT. Troubleshooting E-Prime Error Messages Runtime Error: "Unable to obtain a valid refresh rate" This occurs on Windows 10 computers with Windows version 1703 or later (Windows Creators). Please see the workaround on the following web page: https://support.pstnet.com/hc/en-us/articles/115011182147 Source: The Observer XT 17 - Technical Note - E-Prime --- ## The Observer XT - E-Prime: Introduction and Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-e-prime-introduction-and-setup Chapter: The Observer XT Introduction About This Technical Note In this Technical Note you find all information you need to establish communication between The Observer XT and the E-Prime software for stimulus presentation, run a test and analyze the data of E-Prime and The Observer XT as one data set. Throughout this note we assume that you are familiar with the basic use of The Observer XT and E-Prime Professional 3.0, and that you have created an E-Prime experiment in E-Studio. After reading this note you will be able to: - Set up The Observer XT and E-Prime to communicate with each other. - Start recording in E-Run through The Observer XT. - Automatically import the E-Prime data into The Observer XT. - Analyze the E-Prime data in The Observer XT. You can find this technical note in PDF format in the folder C:\Program Files (x86)\Noldus\EPrime Server. Note: The Observer XT 14.1 and later versions combined with E-Prime Client/Server 1.5 and later were not tested with E-Prime 2.x. If you have E-Prime 2.0, make sure that this combination works before running an experiment. For more information on The Observer XT, see The Observer XT Help. To open the Help, press F1 in the program. For E-Prime, see the E-Prime Reference Manual. The Observer XT and E-Prime: Workflow The workflow is generally as follows: - Make sure that the Observer XT and the E-Prime computers are connected to the local network. - In The Observer XT, open the project you require. - In E-Studio, open the E-Studio experiment that you require. - Prepare the test subject in front of the test monitor. - In The Observer XT, start an observation. This will send a start command to E-Run. - Let the E-Prime experiment run as usual. - When the E-Studio experiment has terminated, in The Observer XT stop the observation. The E-Prime experiment events are imported automatically into The Observer XT. Prerequisites Tools You Need In order for The Observer XT and E-Prime to communicate, you need additional software installed on your computers: - Noldus E-Prime Client 1.6. Installed on the computer where The Observer XT is installed. - Noldus E-Prime Server 1.5. Installed on the computer where E-Studio is installed. Noldus E-Prime Server also includes this technical note as documentation. You can find this technical note in PDF format in the folder C:\Program Files (x86)\Noldus\EPrime Server. Note: If you have E-Prime 3.0 and The Observer XT 14.0, update The Observer XT to 14.1 or later version. The Observer XT 14.0 only works with older versions of E-Prime Server and E-Prime Client made for E-Prime 2.x. Computer Connection The Observer XT and E-Prime must be installed on two separate computers, connected through a Local Area Network (LAN). Make sure that your connection is stable. If connection is lost once during an observation, it cannot be restored and most likely the data of that observation will be incomplete or invalid. The Noldus E-Prime plug-in 1.5 was developed with The Observer XT 14.1, E-Prime 3.0.3.31 and E-Studio Professional version 3.0.3.18. E-Prime Add-on License Your copy of The Observer XT can only work together with E-Prime if your Observer XT license includes the E-Prime Tool. Operating System The Noldus E-Prime Client and E-Prime Server software supports the 64 bit Professional editions of Microsoft Windows 10. In Case of Complex Setups When The Observer XT and E-Prime are part of a more complex observational setup, including for example a physiological data acquisition system which uses a dedicated board on the E-Prime PC, or IP cameras, make sure that The Observer XT communicates directly with the E-Prime PC, using either a crossover cable or a dedicated network switch. If you use a network switch to connect The Observer XT and the E-Prime computers, it must have a fixed IP address with a range different from that of other switches, in order to prevent communication conflicts. For example: 192.168.0.101 for switch 1 and 192.168.1.xxx for switch 2. Install the Software The E-Prime integration solution consists of two pieces of software: - The E-Prime Client software, to be installed on the computer where The Observer XT is installed. - The E-Prime Server software, to be installed on the E-Prime computer. On the Observer XT PC - Copy the file E-Prime Client 1.6 Setup.exe to The Observer XT computer. - Double-click this file and follow the instructions on your screen to install the E-Prime Client. Accept the terms in the License Agreement. The software is installed on C:\Program Files\Common Files\Noldus\The Observer\EPrime Client 1. Proceed with the next section. On the E-Prime PC - Copy the file E-PrimeServer 1.5 Setup.exe to the E-Prime computer. - Double-click this file and follow the instructions on your screen to install the E-Prime Server. Accept the terms in the License Agreement. The software is installed on C:\Program Files (x86)\Noldus\EPrime Server. Proceed with the next section. Set Up Communication The Observer XT PC - In The Observer XT, create a new project or open an existing one. - Click Setup Project in the main window. Under Observation Source, select Live Observation. - If the Devices window does not open, click Devices under Live Observation. - In the Devices window, select the option E-Prime, and double-click the cell under Status. - In the new window that appears, next to E-Prime computer enter the IP address of the E-Prime computer. Leave the Port value as 155. To obtain the IP address of the E-Prime computer: On the E-Prime computer, start the Noldus E-Prime Server, then click the Advanced settings tab. The window that appears contains the E-Prime Controller IP address. - Click OK, then OK in the Devices window. - Proceed with the settings on the E-Prime PC (next section). Notes: - You can also use a port number other than the default 155, but you must set it in both The Observer XT and in E-Prime Controller. - If the E-Prime item does not appear in the Devices window, check that the E-Prime Client software is installed and that your license includes the E-Prime add-on. - Some firewalls can block communication ports. If port 155 is blocked, ask your system administrator to find a free port that is not blocked. Select this new port number in step 5 above and in the Advanced settings of the E-Prime Server. Alternatively, let your system administrator create an exception in Windows Firewall for port 155. The E-Prime PC - On the E-Prime PC, start Noldus EPrime Server. - On the Experiment Settings tab, browse to the experiment file you want to use (*.ebs3). - Click Start to activate Noldus E-Prime Server. From this moment on, it will accept messages from The Observer XT. Notes: - For E-Prime 2.0, the file extension is ebs2. Note: E-Prime 2.0 was not tested with The Observer XT 14.1 and later versions. - Notice the difference between the file extensions: .es3 is the extension of E-Studio files, which specify the experimental procedure. The extension .ebs3 is of the E-Basic script file generated for that experiment. In order to have an ebs3 file in your experiment folder, generate it in E-Studio: choose E-Run > Generate. The experiment folder now also contains the ebs3 file. - E-Prime Server can only be started once. If you start it multiple times, the Noldus E-Prime Server window comes on top of your screen. - Do not click Exit until you are done with data recording. Instead, click the Minimize button or the Close (X) button. Prepare the Experiment in E-Studio Specify the Events to Import A typical E-Prime experiment consists of a number of E-objects (instructions, stimuli, feedbacks) organized in nested sequences called procedures. Follow this section to specify the E-objects that you want to import in The Observer XT, and their properties. - Start E-Studio and open your experiment. - In the Experiment Explorer window, double-click one of the E-objects in your procedure. - In the window that appears, click the Properties button (this is located just under the window's title bar). - Click the Logging tab. Follow all steps below. Default parameters - Make sure that OnsetTime and Duration are selected. System events like the presentation of a stimulus will be imported in The Observer XT as state events for the subject System using these properties. Properties for User responses - For experiments in which a response is given by the test participant after presentation of a stimulus, make sure that the following items are selected: - CRESP (Correct Response) - RESP (Actual Response) - RTTime (Subject response timestamp) The participant responses will be imported in The Observer XT as point events for the subject "User". - Click OK. Repeat steps 2 to 7 for all the other objects you are interested in. Display Settings: E-Prime Experiments in Windows 10 Windows 10 only supports 32 bit color depth. However, when an E-Prime experiment that was created in a prior version of E-Prime and with a bit depth lower than 32 is loaded into E-Prime 3.0, E-Prime keeps the originally-specified color depth setting. This may affect the correct functioning of E-Prime. To check that the Color bit depth is correct: - In E-Studio, choose Edit > Experiment (Ctrl+E). - Click the Devices tab, then double-click Display. - Next to Color Bit Depth, select 32 if not selected already. Important: You must follow this procedure for any experiment that you open on that computer. For a more general solution for Windows 8 and 10 computers, see the web page: https://support.pstnet.com/hc/en-us/articles/115001493487-INFO-Windows-8-DirectX-11-or-greater-detected-23888- Specify the Event Properties to Import For some events you may want to import additional information to The Observer XT, like the name of the picture used as a stimulus. This information can be imported as modifiers. General rule: The Observer XT imports the object property that, in the Trial List, has the same name as the object. The values in the column cells are imported as modifiers. In the example below, the object in the procedure is named Stimulus. Of this object, The Observer XT imports the values in the column Stimulus of the Trial List, RedCar.bmp and BlueCar.bmp. They are imported as modifiers of the behavior Show Stimulus. Example 1: To Import Stimulus File Names An image E-object has been inserted in a procedure, and named Prime. The trial list specifies that for Prime an image will be chosen randomly between the available image files, and displayed on the test participant monitor. The researcher requires that, for each instance of image presentation, the image file name is imported in The Observer XT as a modifier of the event "Show Prime". For example, "Show Prime - Flower_12.bmp". - Open the experiment in E-Studio. - In the Experiment Explorer window, double-click the list in which the object is located. - In the list properties window, click the Add attribute button. Enter the name as the object (in this example, Prime). - Fill in the cells in the new column with the names you want to import (in this example, the name of the image files for Prime). - In the Experiment Explorer window, click the E-object again. - Important: If the attribute value is a file (image, video, etc): - In the Properties window locate the Filename item. In the field next to it, click the Browse button and select the folder that contains the stimulus files, then click OK. - In the field next to Filename, type in the object name in brackets [ ]. In this example: [Prime]. - Run the experiment in E-Studio (E-Run > Run or F7). - The experiment is ready to work with The Observer XT. The value of the attribute in a specific trial will be imported as a behavior modifier in the group Media. Notes: - For correct import into The Observer XT, the name of the attribute must be the same as the name of the object, including the case. - It is not possible to import two or more attributes to the same object. For example, a stimulus object has two attributes, File (with the image file names as values) and CorrectAnswer (with values 1 or 2). For this object, you can import either the image file name or the correct response as a modifier, not both. In the first case you rename File as the object name, in the second you rename CorrectAnswer as the object name. - It is not possible to change the name of the modifier group Media in The Observer XT. Example 2: To Import Non-Filenames A stimulus has an attribute named PictureType with possible values Positive and Negative defined in the Trial List. For each stimulus event, the corresponding value must be imported in The Observer XT as a modifier of the behavior Show Stimulus. - In E-Studio, open the experiment. - In the Experiment Explorer window, double-click the list in which the object is located. - In the list properties window, take note of the attribute that contains the values to import (in this example, PictureType). - Rename the object to match the attribute name that contains the values to import. Source: The Observer XT 17 - Technical Note - E-Prime --- ## The Observer XT - E-Prime: Recording and Synchronization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-e-prime-recording-and-synchronization Chapter: The Observer XT Prepare the Experiment in E-Studio Response Option Types - numericalpredefined for response options with predefined values. - numericalrange for response options within a range. - Click the Logging tab and select Tag. - Run the experiment in E-Studio. - After that, the experiment is ready to work with The Observer XT. The values of the attribute in a specific trial will be imported as numerical modifiers. Notes - The tag you specified in the procedure above is present in the log file of the E-Run experiment, which is the text file present in the same folder as your experiment. - You can specify one response for each stimulus for import into The Observer XT. Multiple answers per stimulus is not supported. - Warning: If you want to use numbers as responses, do not use an existing project created in The Observer XT 13 or earlier. Since this option did not exist in a previous version, it will result in errors in the Event log. Create a new project instead. Ensure High Synchronicity Between The Observer XT and E-Prime In order to ensure synchronicity with E-Run, The Observer XT needs to acquire the time information with the highest accuracy. To do so, it uses a package that runs in the E-Prime experiment. You must specify this package in all your experiments that work together with The Observer XT. Note: A package is a re-usable block of E-Basic script that you can add to E-Prime experiments via the PackageCall objects. Procedure - With the File Explorer, make sure that the file TheObserverXT.epk3 is present in the following two locations: - C:\Users\[user name]\Documents\My Experiments\3.0\Packages This is the default E-Prime search folder for packages. Note: If you use E-Prime 2, the correct folder for this package is C:\Users\[user name]\Documents\My Experiments\Packages. The package file extension is epk2. - C:\Program Files (x86)\Noldus\EPrime Server This is the installation folder of Noldus E-Prime Server. This package must be in that folder only if you installed Noldus E-Prime Server with a user account different from that you use when working with E-Prime. If the package file is not present, repeat installation of Noldus E-Prime Server. Note: If you use E-Prime 2, the correct folder for this package is C:\Program Files (x86)\Noldus\EPrime Server. The package file extension is epk2. - Specify the Packages Search Folders in E-Studio. - In E-Studio, choose Tools > Options > Packages. Under User Search Folder you should see the default folder C:\Users\[user name]\Documents\My Experiments\3.0\Packages. Note: For E-Prime 2.0, the folder is C:\Users\[user name]\Documents\My Experiments\Packages. - Under User Search Folder you should see a second location (C:\Program Files (x86)\Noldus\EPrime Server). If that is not the case, click the New button. Browse to C:\Program Files (x86)\Noldus\EPrime Server, then click OK. - Now the Packages tab in the Options window should display both locations. - Specify the TheObserverXT package file in the E-Studio experiment. - In E-Studio, open the experiment, and in the Experiment Explorer window double-click the experiment name. - Click the Packages tab, then click the Add button. - Select TheObserverXT, click OK. If this package is not visible, restart E-Studio. - Click Apply, then OK. The package can now be inserted in the experiment. - Insert the PackageCall in the E-Studio experiment. - In the Toolbox window, locate PackageCall, and drag it to the beginning of the first procedure. - Result: An object named PackageCall1 is inserted. - Double-click PackageCall1, click the General tab, and from the Package list select TheObserverXT. From the Routine list select SyncTime. - Click the Common tab. Ignore the warning and click OK. - Next to Name, rename PackageCall1 to SyncTime, and click OK. - Result: In the Structure window, the PackageCall object is now named SyncTime. - Run the experiment once (E-Run > Run, or press F7) then save the experiment. Notes - The SyncTime routine of the TheObserverXT package reads the timestamps with high accuracy from E-Run, and writes it down in a text file named NoldusSync.txt. This time will be read by Noldus E-Prime Server when sending the E-Prime data to The Observer XT PC. - The file NoldusSync.txt is stored in the same location as that of the experiment file. - If the TheObserverXT package is not added to your E-Prime experiment, when importing the data from E-Prime, The Observer XT shows a message in the Comment column of the first line of the E-Prime event log, that accurate synchronization is not possible for that E-Prime data set. The E-Prime event log is still added to the observation, but aligned with the Observer XT data with a 1-second accuracy. - If you use E-Prime 2.0, see the Technical Note - E-Prime - The Observer 12.5, which you can also find on the Observer XT 12.5 download web page. Acquire Data Things to Check First - On the E-Prime PC, make sure to close the E-Run window. - On the E-Prime PC, make sure that Noldus E-Prime Server is running in the background. To do so, check that its icon is visible in the taskbar. If Noldus E-Prime Server is not running, in the Apps screen choose Noldus > E-Prime Server (in Windows 7, choose Start > All Programs > Noldus > E-Prime Server > E-Prime Server). - On the E-Prime PC, in the Noldus E-Prime Server window, click Start. Result: Noldus E-Prime Server says "Server is running". Important: Do not click Exit until your test sessions are finished! The Start button is not available when the server is already running. Procedure - On the Observer XT PC, open your project in The Observer XT. Optionally, create a coding scheme which you can use to annotate the test participant's behavior manually. See The Observer XT Help for instructions. - Create a new observation (Alt+F6) and give it a name, then click OK. Result: The E-Prime Status window opens. The status is Ready to start. - Ask your test participant to sit in front of the test PC, and give him/her the necessary instructions. - On the Observer XT PC, when ready, click the Start observation button. Result: The E-Prime Status window says: Connection: Connected. Status: Waiting for E-Prime. - On the E-Prime PC, the experiment starts. Insert the subject and session data, then let the test participant carry out the assigned tasks. The Noldus E-Prime Server window says Client connected. - On the Observer XT PC, optionally manually code the test participant's behavior. When the experiment in E-Prime is finished, the E-Prime Status window says Finished. The Noldus E-Prime Server says Client disconnected. - On the Observer XT PC, stop the observation by clicking the Stop observation button. - The E-Prime events are imported as a new event log named E-Prime in the current observation. Notes - In order for the Noldus E-Prime Server to start correctly, the experiment script file (ebs3/ebs2 file) must be selected under E-Prime Experiment. See the Set up communication - the E-Prime PC section for details. - If you create an observation before starting Noldus E-Prime Server, the E-Prime Status window on the Observer XT PC says Connection: Not connected. To solve this problem, do the following: - In The Observer XT, click another item in the Project Explorer, for example the coding scheme. This action closes the observation. - On the E-Prime PC, in Noldus E-Prime Server, click the Start button. - In The Observer XT, in the Project Explorer, click the name of that observation. This re-opens the observation. Note that the observation name is labeled with a yellow triangle icon. This indicates that the observation has yet to be started. - The E-Prime Status window now says Connection: Connected. You are ready to start the observation. - Warning: Make sure that you stop the observation in The Observer XT only when the E-Prime Status window says Connection: Connected and Status: Finished. If you stop before this, The Observer XT will not import the E-Prime data for that observation. - If you cancel the run on the E-Prime PC after starting the observation, for example when clicking Cancel in one of the dialogs that appear at the start of the run, connection is lost for that observation. On the Observer XT PC, stop the observation, delete it, and create a new one. - There may be a significant delay (30 seconds or more) between the start of the observation and the start of E-Run. This could be due to a number of factors, such as: - The driver software of the E-Prime hardware key is not up-to-date. Go to http://sentinelcustomer.safenet-inc.com/sentineldownloads/ and download Sentinel HASP/LDK Windows GUI Run-time Installer. Next, remove the E-Prime hardware key from the E-Prime PC and launch installation of the driver. After installation is complete, insert the hardware key in the E-Prime PC and start E-Studio. - The E-Prime PC has other hardware installed that conflicts with E-Prime, for example an additional network card. See the In case of complex setups section for details. - When E-Prime data are imported into The Observer XT, it adds two subjects to the Coding Scheme: User and System. When you manually score events, The Observer XT expects that for each event you first score a subject and then a behavior. Define a subject in the Coding Scheme. Then choose Setup > Project Settings > Scoring Options and select Auto-record subject. You then only need to score the subject once at the start of the test. Scoring Data Offline Once you finish an observation, the E-Prime data are sent to The Observer XT. It may happen that you want to review the observation, possibly with external video, and score events manually. However, after data import, the coding scheme has two additional subjects: User and System. This means that every time you want to score an event manually, you must score the subject in The Observer XT's Codes window before you can score the event (behavior). To prevent this from happening, and to reduce the number of key presses, you can use the Auto-record subject function. With this option, The Observer XT assumes you will be scoring events for the first subject you score in an observation session. - In The Observer XT, choose Setup > Project Settings > Scoring Options. - Select Auto-record Subject. - If they are not already present, define one or more subjects (roles) in the coding scheme, which can be used to score events manually. - Open and start the observation as usual. - Position the observation (or video) at the time where you want to enter the event. - Score the event as usual, including the subject: [Subject] - [Behavior] - [Modifiers]. - The next time you score an event, that subject is scored automatically. Complete the event with the Behavior and Modifiers. For more information, see Auto-record Subject in The Observer XT Help. Note: The subjects User and System added after E-Prime data import are not shown in the Codes window. Analyze Data How E-Prime Events Are Stored in The Observer XT Event Files The data of E-Prime are stored in a separate event file named E-Prime. You can see this in the tree view of the Project Explorer. Click the observation name, and open Event Files. - E-Prime contains all events imported from the E-Prime computer. - Event log is the event file that The Observer XT creates by default when you create an observation. If you code events manually during the observation, the events are written to this file. If you do not code events, Event log only contains two lines that mark the start and the end time of the observation. Click E-Prime to open the E-Prime event log. Two Subjects: System and User In the E-Prime event log, the column named Subject specifies the subject of the event in each row. - System: for all events determined by E-Prime (for example, a stimulus presentation). - User: for all responses by the test participant. System Events A state event like the presentation of a stimulus is indicated by two rows: - The start row (with a green symbol in the Behavior column). The start time is the value of OnsetTime of the E-object in E-Prime. - The stop row (with a red symbol in the Behavior column). The stop time is the value of OnsetTime + Duration of the E-object in E-Prime. Note that the times in the event log may differ from the times in the E-Prime output file (a text file generated by E-Run). This is normal, since the time stamps are corrected to ensure millisecond-accurate synchrony between E-Prime and The Observer XT. For system events, the name shown in the Behavior column is always Show followed by the name of the E-object. User Responses A point event like the user response is indicated by one row, with a blue circle in the Behavior column. The time of the event is the value of OnsetTime of the E-object in E-Prime. The Modifier column shows two modifiers: - Response: followed by the character(s) entered by the test participant. - Correct: followed by the correct response for the corresponding stimulus (that is set in the E-Prime Trial List). Numerical Responses Modifiers are by default nominal, unless you specified in E-Prime that they should be imported as numerical. Numerical responses are then imported into the Event log as numerical modifiers. Notes - If events are missing or incomplete, it could be due to wrong settings in E-Prime. For example, if RTTime is not selected in E-Prime logging settings, user answers will not be imported in The Observer XT. If CRESP or RESP are not selected, an event line is imported but does not contain the corresponding modifier (correct response or actual response, respectively). If neither of the two is selected, the event is not imported at all. - If the Subject, Behavior, or Modifier columns are not shown in the E-Prime event log, right-click one of the column headers and select them. - It is not possible to remove Show from the name of system events. It is also not possible to customize the behavior Answer and the part of its modifiers Correct: and Response:. You can only customize the responses; to do so, edit the values in the Trial List. - See the Prepare the Experiment in E-Studio section for how to customize the information in the E-Prime events sent to The Observer XT. - If the first event line of the E-Prime event log contains the message The E-Prime data could not be synchronized automatically in the Comment column, it means that E-Prime could not use the TheObserverXT package correctly, or the package was not installed. In such cases the E-Prime event log is added to the observation and aligned with other data with a 1-second accuracy. - Note that the times in the event log may differ from the times in the E-Prime output file (a text file generated by E-Run). This is normal, since the time stamps are corrected to ensure millisecond-accurate synchrony between E-Prime and The Observer XT. Synchronicity Between E-Prime and The Observer XT Data We advise connecting the Observer XT PC and the E-Prime PC to a local area network (LAN). In most cases the network speed is high enough to have a negligible delay between the start of the observation in The Observer XT and the start of the E-Run experiment. Source: The Observer XT 17 - Technical Note - E-Prime --- ## The Observer XT - Step 1 - Create all settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-step-1-create-all-settings Chapter: The Observer XT Step 1 - Create All Settings Create A New Project To create a new project, choose File > New Project. Then: - Create settings for your project (see below). - Make your Coding Scheme with relevant codes for your research question (page 8). - Define Independent Variables, which are factors that remain constant throughout one observation, like temperature, or gender and age of your test participants (page 12). Create Settings To specify how to observe and code your videos, choose Setup > Project Setup. Observation source Under Observation source, choose whether you want to observe offline from a video file, or carry out the observation live while the behaviors occur. If you carry out a live observation, you can use MediaRecorder to simultaneously create a video file. Step 1 - Create all settings Observation method Under Observation method, choose Continuous sampling. You get a full record of the absolute durations and frequencies of behaviors. Select one of the other options if you want to score at regular time intervals. You will then get frequencies of behaviors, not durations. Step 1 - Create all settings Create A Coding Scheme Create your Coding Scheme in such a way that you can answer your research questions with the annotations. Coding can be a time-consuming process. Therefore, it is important to only define the factors that are really needed for your research. Subjects If you study only one person or animal in each observation, do not define subjects in the Coding Scheme. Enter their identity in the Independent Variables list (see page 12). If you study multiple persons or animals in one observation, enter their roles as subjects. Enter their identity in the Independent Variables list (see page 12). Step 1 - Create all settings Behaviors Define the behaviors that are relevant for your research question and the key codes with which you want to score their occurrence during the observations. Create behavior groups, like in the example below Locomotion, Pecking and Ingestion, and define the individual behaviors within the groups. Behaviors with and without duration Behaviors can have a duration or not. Examples of behaviors that have a duration, are Walking or Playing. Examples of behaviors that do not have a duration, or of which duration is not important are Answer Yes, or User error. Behaviors with a duration are called State events and behaviors with no duration Point events. Step 1 - Create all settings Overlapping or non-overlapping behaviors There are two types of groups with behaviors. A group in which the behaviors cannot overlap is called a Mutually exclusive behavior group and is the easiest to work with. In such a group the start of a new behavior automatically stops the previous behavior. You only need a key code for the start of each behavior. This makes scoring effort less. During an observation, behaviors may occur that you did not define in your Coding Scheme and are not relevant for your study. To be prepared for this, define a behavior like Other behavior. This way you can stop an active behavior when something occurs that you did not think of when you created the Coding Scheme. Also, all behaviors in the group now add up in time to 100%. If the new behavior is relevant for your study, click the Add new element button at the bottom of the Codes window to add it to the Coding Scheme. If it is not possible to define a group with non overlapping behaviors, create a group in which behaviors can overlap. Such a group is called a Start-Stop behavior group. In such a group scoring effort is higher because you need to press a key when the behavior starts and when it stops. In such a group there may also be time periods in which no behavior occurs. Step 1 - Create all settings Modifiers Optionally define Modifiers. Modifiers specify the behaviors more precisely. They can consist of text (nominal modifiers), or numbers (numerical modifiers). If behaviors have a duration, the attached modifiers have a duration as well, independent on whether they are nominal or numerical. For both types of modifiers you can calculate statistics like the frequency or duration. For numerical modifiers, you can calculate additional statistics, like the minimum, maximum and mean values. Scoring modifiers requires pressing extra keys, which makes scoring slower. Therefore, only define them when it is really necessary. This is, for example, the case when you want to know mean values. To specify for which behaviors you want to score the modifiers, double-click the modifier group name and select to which behavior the modifier must be linked. Step 1 - Create all settings If the Modifiers column is not shown in your Coding Scheme, choose View Settings > Modifiers. Independent Variables Independent Variables are factors that can potentially influence the observation, and are assumed to remain constant for a certain subject (like a test person's ID or an animals age) or an observation session (like temperature). Define the variables that are important for your study (in the example below, Brood size, Hatching date and Age of adult). To do so, choose Setup > Independent Variables. Click Add Variable to enter your Independent Variables. For more information on how to create a Coding Scheme, see Coding Scheme in The Observer XT Help. For more information on Independent Variables, see Independent Variables in The Observer XT Help. Step 2 - Acquire your data Source: The Observer XT 17 - Quick Start Guide --- ## The Observer XT - Step 2 - Acquire your data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-step-2-acquire-your-data Chapter: The Observer XT Step 2 - Acquire Your Data Create Observation To create a new observation, choose Observe > Observation > New. Give the observation a name and select your videos. Position the video to where you want to start your observation. Observe Press the Start observation button to start observing. Step 2 - Acquire your data Score the observation by pressing the keys of your keyboard. In the Codes window you can see which of the elements you should score next, Subject, Behavior or Modifier. Once you scored the Subject, the tab Behaviors opens. Similarly, once you scored behaviors that have modifiers attached to it, the tab Modifiers opens. You can view your scored data in a Time-Event plot similar to the plot in the Visualization part of the software. The plot "grows" while you are scoring, giving you a good overview of the scored data. To stop the observation, click the Stop observation button. Options Free text For each event line you can enter a comment of up to 1024 characters. For example, to transcribe speech from an audio file. Choose View Settings > Comment. Type or paste the text in the Comment cell in the event log or in the Comment window. Note that free text is not analyzed, however it can be visualized. Step 2 - Acquire your data Control video playback To play the video at lower or higher speed, click the Speed down or Speed up button. Press the space bar on your keyboard to pause and play the video. If you missed an event in the video, click the Quick Review button. The video then jumps back a few seconds and plays the event you missed at a lower speed. Click the Quick Review button multiple times to jump back more in time To review a video fragment multiple times, click the Loop button and set the flags that appear to the start and end of the fragment. Code in runs If you have a large Coding Scheme, you will probably not be able to code everything at once. It is common that you play the video once for every subject-behavior group combination. For example, score the behavior group Playing for the subject Child in run 1, Verbal behavior for Child in run 2 and Verbal behavior for Parent in run 3. After you finished with one run, do not stop the observation, but go back to the start of your observation. To do so, click the first row, You can also use keyboard shortcuts to control video playback. See Keyboard shortcuts in The Observer XT Help for the options. Step 2 - Acquire your data that has time 0.00, and click the play button on the Playback Control window. You can now score the next subject - behavior group combination. If you stopped the observation after a run, you have to click the Start-observation button again to continue with the next run. Code in runs with multiple subjects If you defined multiple subjects in the Coding Scheme, use the Auto-record Subject feature. With this feature the subject scored in the last event is automatically scored in the next event. Run through the video one or more times for one subject. Then run through the video for the next subject. Once you pressed the key code for that subject, it is automatically scored for the next events. To switch on Auto-record Subject, choose Setup > Project Settings > Scoring Options. Select Auto-record Subject. Step 3 - Analyze your data Source: The Observer XT 17 - Quick Start Guide --- ## The Observer XT - Step 3 - Analyze your data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-step-3-analyze-your-data Chapter: The Observer XT Step 3 - Analyze Your Data First determine what you want to analyze. For example: Analyze the duration and frequency of behaviors in an observation or all observations. Carry out Behavior analysis (below) or, for numerical modifiers, Numerical analysis (page 19). Analyze a selection of behaviors, subjects or observations. Use Data selection (page 19) to filter the behaviors, subjects, or observations (page 20) and then carry out the analysis (below). Analyze a behavior while another one occurs. Use Data selection (page 19) to create intervals based on a behavior (page 22) and then carry out the analysis (below). Behavior Analysis Choose Analyze > Behavior analysis > New. Click Statistics to choose which statistics you want in your analysis result. Next, click Calculate. You obtain a table with the calculated statistics. Step 3 - Analyze your data To change the table layout, click the Layout button. You can move categories with the arrow keys, for example from On Rows to On Columns, or On Sheets. Alternatively, drag the item from a box and drop it in another one. Choose how you want to organize the layout of the analysis result. The effect of selecting and deselecting a category If you select the checkbox in front of a category, you get separate analysis results for each item in that category. For example, if you have two observations and select the checkbox in front of Observations, you get separate analysis results for each observation. Step 3 - Analyze your data If you deselect the checkbox, all observations are grouped and you get one analysis result for all observations together. It is not possible to deselect the category Behaviors. Numerical Analysis A numerical analysis can only be carried out if you have numerical modifiers in your Coding Scheme. A numerical analysis gives additional statistics above the ones obtained in the behavior analysis. For example if you defined Sound level as numerical modifier, you can calculate the minimum, mean and maximum sound level. The procedure is the same as for the Behavior Analysis. Analyze A Selection Of The Data To analyze a selection of your data, do the following: 1. Choose Analyze > Select Data > New Data Profile to create a data profile. You can create multiple data profiles, for example, one to analyze gaze behavior and one to analyze play behavior. 2. Specify the selection. - Use Filter to select some observations, subjects or behaviors (page 20). - Use Select Intervals to create time intervals during which a certain behavior occurred (page 22). Step 3 - Analyze your data 3. Check the result of your selection. To do so click Visualize button on the toolbar and select the observations to visualize. 4. Click the correct data profile in the Project Explorer to activate it. This profile is used for analysis and visualization. 5. Analyze your data (see page 17). Analyze a selection of behaviors, subjects or observations Use the filter option to analyze only some observations, subjects, or behaviors. For example, to analyze only the behavior Gazing at patient. 1. Click the box next to Filter Events > By Behaviors. 2. Make your selection. Step 3 - Analyze your data 3. Click OK and drag the box between the Start and the Result box. 4. Visualize the selected data. Check whether your selection criteria are correct. Filtering gives you only those data you defined in your filter. In the example below the behavior Gazing at patient was filtered. Only this behavior is shown in the Visualization. 5. If the selection is correct, carry out Behavior analysis (page 17) or Numerical analysis (page 19) on the selected data. Step 3 - Analyze your data Analyze a behavior while another one occurs As an example, you want to know what a female bird did when the male bird was at the nest. Define a time interval based on the behavior (or behavior and its modifiers). To do so: 1. Click the box next to Select Intervals > By Behaviors. 2. Select the behavior in the window that opens. If you have multiple subjects in your Coding Scheme, choose from the The selected Behaviors occur in list which subject performed the behavior. 3. Then position the selection box in the data selection sequence (see 3 in the picture on page 21). 4. Visualize the data to check your selection. The time fragments when the male bird was in the nest are selected. All events that took place in these intervals, not only Male > In, are shown in the white areas in the visualization. These data Back up your data will be analyzed. Compare the figure below with the bottom one on page 21 for the difference between analyzing a subset of the data and analyzing intervals. 5. If the selection is correct, carry out Behavior analysis (page 17) or Numerical analysis (page 19) on the selected data. Source: The Observer XT 17 - Quick Start Guide --- ## The Observer XT - Tobii Pro: 1 Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-1-introduction Chapter: The Observer XT Introduction 1 Introduction Aim Of This Technical Note This document describes how to start and stop Tobii Pro eye trackers in The Observer XT and how to import the eye tracking data into the observation. This document describes the use of the Tobii Pro X2 Eye Trackers. These are stationary eye trackers that are positioned below a computer monitor. They are controlled with the analysis software Tobii Pro Lab or Tobii Pro Studio. This technical note describes both Tobii Pro Lab and Tobii Pro Studio. When instructions are identical, both applications are referred to as Tobii Pro software. Where needed, separate instructions for the two applications are given. System Used Computer All software was tested on our standard test platform, which is a Dell Precision T5810 desktop computer. Processor: Intel Xeon E5-1620 v3, at 3.50 GHz. RAM Memory: 8 GB. Operating system: Windows 10 64 bit. The Observer XT and the Tobii Pro software were installed on two separate computers. Software On the The Observer XT computer The Observer XT 14.2. Introduction N-Linx Server version 1.0, for communication between The Observer XT and other applications. note The N-Linx Server can also be installed on a third computer, connected with The Observer XT computer and the computer with Tobii Pro software. On the computer with Tobii Pro software We tested: - Tobii Pro X2-30 Eye tracker with Tobii Pro Lab 1.98.15089. - Tobii Pro X2-60 Eye tracker with Tobii Pro Studio 3.4.7. note If you have another eye tracker than the ones tested by Noldus IT, check thoroughly that the solution described in this note works. N-Linx Agent version 1.2, for communication between The Observer XT and Tobii Pro Studio or Tobii Pro Lab. Tobii Pro Studio and Lab plugin installed on the computer with Tobii Pro Studio or Tobii Pro Lab. note You can install this component when you install N-Linx Agent. Noldus Tobii Studio File Converter 3, to convert Areas of Interest (AOI) data from the Tobii Pro software. For other data types you do not need a file converter. Introduction Notes The communication system N-Linx Server + N-Linx Agent + Tobii Pro Studio and Lab plugin takes care of automatic start and stop of data co-acquisition with Tobii Pro software when you operate The Observer XT. It does not transfer the data from Tobii Pro software to The Observer XT, or synchronize the data with the event log. For this, you must export the data files from the Tobii Pro software, import them into The Observer XT, and synchronize manually with the event log. The N-Linx Server adds the possibility to extend the solution with other N-Linx enabled software and custom development (N-Linx SDK). Contact Noldus for details. Import Profiles Import profiles for data from Tobii Pro Lab To import data from Tobii Pro Lab into The Observer XT, import profiles are available. These can be downloaded from https:// Download the zip-file and extract it to a temporary folder. Copy the profile to C:\ProgramData\Noldus\Common\Profiles on your computer with The Observer XT. Copy both the folder and the file. Import profiles for data from Tobii Pro Studio To import Tobii Pro Studio data, a number of import profiles are available. These are installed automatically when you install The Observer XT. For the import procedures, see page 26 and page 37 for non-AOI data and AOI data, respectively. For More Information About The Observer XT The Observer XT Help. Introduction - For visualizing data: see Visualize Data. - For calculating statistics: see Calculate Statistics. Quick Start Guide - The Observer XT. The Observer XT sample project, which you can find on the installation USB stick, in the folder Sample Projects/Human sample project. Other sample projects can be downloaded from https:// register and login first. support-center. The web page of the Noldus Customer support center also contains the customer support database with questions asked by The Observer XT users and answers from the help desk. About N-Linx The Reference Manual - N-Linx, which you can find on The Observer XT installation USB stick. About Tobii Pro Software The Tobii Pro Lab or Tobii Pro Studio User Manual. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 10 Synchronization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-10-synchronization Chapter: The Observer XT Synchronization 10 Synchronization How To Determine The Delay Between The Observer Xt And Tobii Pro Software Data synchronization The system described in this note makes it possible to start recording in Tobii Pro software the moment you start an observation in The Observer XT. The eye tracking data are aligned with the observational data scored manually. However, there may be a delay between the start of the observation and the start of recording in the Tobii Pro software. The delay may be caused, among other things, by delays in the network communication. As a result, there may be a mismatch between eye tracking data and observational data. To measure the delay - Define in your coding scheme a Point event labeled, for example, sync. - Start an observation as usual. - Ask the test participant to perform an action that could be seen on the screen (for example, typing in a letter in a web field or the Windows Notepad). - The very moment he/she performs that action, score the sync event. - Import the video made by the Tobii Pro software into The Observer XT, and look when the letter appears on the screen. The difference in timing between that time and the time that you scored sync gives you the value of the delay. This method is less precise than the previous as it relies on the coder's reaction time. To compensate for a delay - Take note of the value you measured with one of the two methods above. Synchronization - Open the observation and click the Offset button. - Click Numerical offset. - Next to the name of the event log containing the eye tracking data, enter this delay. For example, if the delay was 0.5 s, then enter 00:00.500. For more information, in The Observer XT Help see External Data > Import External Data > Manual Synchronization. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 11 Firewall Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-11-firewall-settings Chapter: The Observer XT Firewall settings 11 Firewall settings Aim When N-Linx Agent is installed, it enables the necessary communication ports. Follow this section in case communication is for some reason blocked by Windows Firewall. Prerequisites The Tobii Pro software and The Observer XT run on different computers, or N-Linx Server runs on a third computer other than The Observer XT computer and the computer with Tobii Pro software. If that is not the case, skip this section. The computers must be in the same network. Procedure important Do the following in all computers: the computer with Tobii Pro Studio software, the Observer XT computer, and the computer where N-Linx Server is installed (if this is different from the computers where The Observer XT and the Tobii Pro software are installed). 1. Open the Windows Control Panel and choose Windows Firewall. 2. On the left side of the window, click Advanced Settings. 3. In the pane on the left, click Inbound Rules and then in the Actions pane on the right click New Rule. 4. In the window that opens, select Port and click Next. 5. Select TCP and Specific local ports. Next to that option enter 5672, then click Next. 6. Select Allow the connection and click Next. 7. Select to which network the rule applies and click Next. Firewall settings 8. Give the rule a name, for example N-Linx connection and click Finish. 9. Check in the Inbound Rules list that this rule is set to Enabled. 10.Click Outbound Rules and click New Rule in the Actions pane. Repeat steps 4 to 9 for the outbound rule. 11. Close all Control panel windows. Check Connection In N-linx Agent - At the bottom-right corner of the screen of the computer with Tobii Pro software, click the arrow icon and in the system tray double- click the N-Linx Agent icon. - Next to N-Linx Server Address make sure that the IP address of the Observer XT computer is specified. This IP address must be fixed. note If The Observer XT and N-Linx Server are installed on the same computer, enter localhost. tip You can also enter the Computer name of the computer where N-Linx Server is installed, instead of its IP address. On the computer where N-Linx Server is installed, open the Control Panel and choose System. Locate Computer name (not Full Computer name). 3. Click Connect. If connection is established, the message at the bottom of the N-Linx Agent window says Connected. 4. Click the Close button to close the N-Linx Agent window. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 12 General Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-12-general-notes Chapter: The Observer XT General notes 12 General notes The Observer Xt Independent Variables If the Independent Variables list appears when you press the Start Observation button, the actual observation (and therefore eye tracking by Tobii Pro Studio) starts when you click OK in the Enter Independent Variables window. You can choose when the Enter Independent Variables window appears. For details, see Set up your Project > Project Settings in The Observer XT Help. For more information on recording data in The Observer XT, see Carry out an Observation in The Observer XT Help. N-linx Agent On the Tobii Pro Studio computer, you can check the status of N-Linx Agent. Click the arrow icon on the system tray, then double-click the N- Linx Agent icon. The N-Linx Agent window shows the status of Tobii Pro and The Observer XT. General notes The Observer XT is visible and Online when the program is open. Tobii Pro is Offline when it is installed, but not active. This is the case immediately after installation of N-Linx Agent and after the computer is restarted. After creating an observation in The Observer XT, the status of Tobii Pro becomes Online. Online means that the Tobii Pro plugin is started and therefore available for communication. Once the Tobii Pro plugin is started, it remains running until the PC is shut down. Eye Tracking To carry out a new recording with the same participant Tobii Pro Studio: Start a new recording on the Tobii Pro Studio computer. Open the tab Use Existing Participant. Select the participant and click Continue. Then repeat the procedure from step 13 on page 24. Tobii Pro Lab: Open the Record tab and select the participant in the Participant pane at the bottom. Then repeat the procedure from step 9 on page 21. To repeat calibration Select the points to recalibrate and click Recalibrate (n. points). General notes If the calibration continues to be unsatisfactory, Tobii Pro Studio has the option to look into the calibration in more detail. To do so, click Check Calibration. Nine points appear on the screen of the test participant, with the gaze represented as a circle. Move the chair up and down or backwards and forwards until the circle is around the dot the participant looks at. Make sure the gaze is detected in the correct position for each calibration point. When done, let the participant press the Esc key. Tobii Pro Lab does not have this functionality. To view the fixations live Do one of the following: Connect the Tobii Pro system to two monitors. Place one of the two monitors in the observation room. In Tobii Pro Studio, click the Setup icon and choose Show Live Viewer, and select that monitor. If you have the Enterprise version of Tobii Pro Studio, this version includes a remote viewer application. Install this on the Observer computer to view the fixations live. You can also use this program to control Tobii Pro Studio, for example start a new recording, and do the calibration. Test Leader Display Windows font size To make sure that the gaze points are correctly positioned when reviewing the test, set the Windows font size on the stimulus monitor to 100%. In the Search field of the start screen, type "display" and click Change display settings. Under Scale and layout, choose 100% from the list Make text and other items larger or smaller. General notes Multiple monitors When using a dual screen setup, set the same resolution on both screens. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 2 Computer Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-2-computer-configuration Chapter: The Observer XT Computer configuration 2 Computer configuration Main Steps The Observer XT computer and the computer with Tobii Pro software must be connected to a local network, and both must have a fixed IP address that fall in the same range. For example 191.168.0.50 and 191.168.0.51. See set ip address below. Install N-Linx Server on computer with The Observer XT, or on a third computer that is connected to both The Observer XT and the Tobii Pro computer. See page 12. Install N-Linx Agent together with the plugin Tobii Pro Studio and Lab on the computer with Tobii Pro software. See page 13. It can be useful to create a shared folder on the Tobii Pro software computer where gaze replay videos and exported data are stored. This way you have always quick access to the eye tracking video and data from The Observer XT computer. See page 14. Set Ip Address Connect both computers with an Ethernet cable. Then give both computers a fixed IP address that falls in the same range. To do so, follow the procedure below for both computers: 1. Open the Control Panel and select Network and Sharing Center. 2. Click Change adapter settings on the left side of your window. Computer configuration 3. Right-click the Local Area Connection and click Properties. If your computer has more than one Local Area Connection, choose the one with which the computer is connected to the other one. To check which one this is, remove the cable. The LAN connection that gets the disconnected symbol is the correct one. 4. Select Internet Protocol Version 4 (TCP/IPv4) and click Properties. 5. Click Use the following IP address. 6. In the IP address field, enter the same first three numbers for both computers and a fourth number that is differs on both computers. 7. Enter the number 255.255.255.0 in the Subnet mask field on both computers. Leave the other fields empty. Computer configuration 8. Click OK and close the Control Panel. Install N-linx Server important Install this piece of software on the The Observer XT computer, or on a computer connected with both the computer with The Observer XT and the one with Tobii pro Software. 1. Insert The Observer XT installation USB stick in one of the PC's USB ports. 2. Browse to Drivers and Tools\N-Linx Server. 3. Double-click N-Linx Server Setup.exe. 4. Next to Installation type choose Standard, unless you want to change the program location. 5. Follow the instructions on your screen. Computer configuration Install N-linx Agent important Install this piece of software on the computer with Tobii Pro software. 1. Insert The Observer XT installation USB stick in one of the USB ports of the computer on which the Tobii Pro software is installed. Browse to Drivers and Tools\N-Linx Agent. 2. Double-click N-Linx Agent Setup.exe. 3. Next to Installation type choose Standard, unless you want to change the program location (C:\Program Files\Noldus\N-Linx Agent 1). 4. In the Plugins field, select Tobii Pro Studio and Lab, and click Next. 5. Accept the End-User License Agreement, click Install and follow the instructions on your screen. 6. If the N-Linx Agent user interface does not open after installation, at the bottom-left corner of the screen, on the system tray, click the arrow icon and double-click the N-Linx Agent icon. 7. In the N-Linx Agent user interface, next to N-Linx Server Address, enter the IP address of the computer where N-Linx Server is installed. This IP address must be fixed. Computer configuration If The Observer XT and N-Linx Server are installed on the same computer, enter localhost. tip You can also enter the Computer name instead of the IP address. To find the Computer name of the computer where N-Linx Server is installed, on that computer open the Control Panel and choose System. Locate Computer name. 8. Click Connect. If connection is established, the message at the bottom of the N-Linx window says Connected. Notes If N-Linx Agent is already connected, the icon in the taskbar looks like this: Create A Shared Folder Share the folder with eye tracking data and videos, so that it can be accessed from the computer with The Observer XT. This is useful when you import eye tracking data and videos into The Observer XT. On the computer with Tobii Pro software - Right-click the folder where the Tobii Pro exported data and videos are going to be stored, and select Share with and then Specific People. 2. Click the arrow next to Add and select Everyone and then click Add. Computer configuration 3. Select Read/Write as Permission level and click Share. On both computers - Open File Explorer and then This PC. - Click the Map network drive icon. - Choose a name for the drive and browse to the shared folder. Choose the same name on both computers. Then click Finish. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 3 Workflow URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-3-workflow Chapter: The Observer XT Workflow 3 Workflow Main Steps - Prepare The Observer XT (page 17) to make sure that the data collected can be started and stopped with The Observer XT. - Record data with Tobii Pro Lab (page 20) or Tobii Pro Studio (page 23). - Export eye tracking data like fixations and saccades from Tobii Pro Lab (page 26) or Tobii Pro Studio (page 27). - Import Tobii Pro data in The Observer XT (page 29). - Import the Gaze replay video in The Observer XT (page 36). - Optionally, export Area of Interest data (AOI) from Tobii Pro Lab (page 37) or Tobii Pro Studio (page 38). Next, use the Noldus Tobii Studio File Converter 3.0 to make the data files compatible with The Observer XT (page 39) and import those files into The Observer XT (page 43). Important Terms You define a project both in The Observer XT and the Tobii Pro software, however this term represents different things in the two programs. In Tobii Pro Lab, a project can contain one or more recordings. In Tobii Pro Studio, a project can contain different tests, each of them containing one or more recordings. In The Observer XT, a project contains observations, which are the equivalent of the recordings in the Tobii Pro software. However, you can import data from one test/study, or multiple tests/ studies into one project of The Observer XT. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 4 Prepare The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-4-prepare-the-observer-xt Chapter: The Observer XT Prepare The Observer XT 4 Prepare The Observer XT Aim To set The Observer XT to start and stop eye tracking with the Tobii Pro software. If you ordered a set-up from Noldus IT, these settings have already been made. Then, continue with: Record with Tobii Pro Lab on page 20 or Record with Tobii Pro Studio on page 23. Prerequisites N-Linx Agent and the plugin Tobii Pro Studio and Lab are installed on the computer with Tobii Pro software. N-Linx Server is installed on the The Observer XT computer or on a third computer connected to the The Observer XT computer and the computer with Tobii Pro software computer. The Observer XT is opened and you have created a project. Procedure Connect The Observer XT to N-Linx Server Follow this procedure just once. The settings are also valid for any new The Observer XT project that you create. 1. In The Observer XT, choose File > Preferences. 2. Click N-Linx Settings on the left. 3. Select Use N-Linx Server to connect with other applications. Prepare The Observer XT 4. Next to N-Linx Server address, enter the computer name of the computer with N-Linx Server. Leave the default entry localhost if The Observer XT and N-Linx Server are installed on the same computer. tip To find the Computer name of the computer with N-Linx Server, open the Control Panel and choose System. Locate Computer name (not Full Computer name). 5. Make sure the N-Linx Server port is 5672. Ask your system administrator for assistance with choosing another port if port 5672 is used by another program. 6. Click Test connection, and check that the Status changes to Connected. If connection fails, review all the settings under Computer configuration (page 10). Project Setup Follow these steps for each new The Observer XT project you create to work together with the Tobii Pro system. 1. Choose Setup > Project Setup. 2. Under Observation Source select Live Observation. In the next steps you specify that The Observer XT communicates with the Tobii Pro Studio and Lab plugin, which should be installed together with N-Linx Agent on the computer with Tobii Pro software. 3. In the Devices window, check that Tobii Pro [computer name] is selected. Prepare The Observer XT If you do not see this item, it is likely that N-Linx Agent is not installed, or that the plugin Tobii Pro Studio and Lab was not selected when you installed N-Linx Agent. Re-run the N-Linx Agent installer file, and select Modify and choose Tobii Pro Studio and Lab. See page 13. 4. Click OK. Coding Scheme To annotate your test participant's behavior, create a Coding Scheme. See The Observer XT Help for more information. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 5 Record With Tobii Pro Lab URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-5-record-with-tobii-pro-lab Chapter: The Observer XT Record with Tobii Pro Lab 5 Record with Tobii Pro Lab Aim To design a test in Tobii Pro Lab and start and stop eye tracking acquisition with The Observer XT. Prerequisite You set up The Observer XT, following the procedure on page 17. Procedure In Tobii Pro Lab - Create a new Tobii Pro Lab project, or open an existing one. In case of a new project, choose Screen as Project type. - Open the Design tab. - Press the Add stimulus button on toolbar on the top and browse to the stimulus to display. Set its properties, for example the display duration, in the Properties pane on the right. Add more stimuli, if needed. 4. You are now ready to start your observation in The Observer XT. In The Observer XT - Create a new observation. To do so, click Observations in the Project Explorer, then Create a new observation. - Name the observation, then click OK. In Tobii Pro Lab - Let the participant take place behind the monitor with the eye tracker. Record with Tobii Pro Lab - Open the Record tab. important Do not click the Start Recording button. Start the recording by starting an observation in The Observer XT (see below). In The Observer XT - To start the test, click the Start observation button. If the Enter Independent Variable Values window opens on the screen of The Observer XT, enter the independent variable values for that observation and click OK. In Tobii Pro Lab 10.The calibration starts. Check that the test participant's eyes are visible as two white circles in the center box of the drawing that appears on your screen. If not, change his/her position relative to the monitor (lower or raise the chair or let the test participant sit closer or further away from the monitor). 11. Click Start calibration to start the calibration and let the test participant follow the symbol moving on the screen. When the calibration is ready, a plot with the calibration results appears on the test leader monitor. 12. Check whether the calibration is good, that is, whether the distance between the gaze points and the positions of the calibration symbol is acceptable. If so, click Accept. 13. The stimuli are now presented. Let the participant carry out the tasks assigned. In The Observer XT 14.Optionally, score the behaviors with keys on your keyboard. 15. To stop the test, click the Stop observation button in The Observer XT. Record with Tobii Pro Lab Eye tracking now stops automatically. Notes Eye tracking also stops when the test you designed in Tobii Pro Studio ends before you pressed the Stop observation button in The Observer XT. If the computer with the Tobii Pro software is restarted, you must restart The Observer XT as well. Otherwise starting acquisition with the Tobii Pro software will not work. If the computers with The Observer XT and the Tobii Pro software are restarted, it may take some time before the Tobii Pro plugin starts when you create the first observation. If you start an observation in The Observer XT before the plugin is fully running, acquisition with the Tobii Pro software does not start. If you notice this, create and start a second observation. Acquisition with the Tobii Pro software will now start. More Information For more information on how to design a test in Tobii Pro Lab, see the Tobii Pro Lab user manual. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 6 Record With Tobii Pro Studio URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-6-record-with-tobii-pro-studio Chapter: The Observer XT Record with Tobii Pro Studio 6 Record with Tobii Pro Studio Aim To design a test in Tobii Pro Studio and control recording with The Observer XT. Prerequisite You set up The Observer XT, following the procedure on page 17. Procedure In Tobii Pro Studio - Create a new project, or open an existing one. - Create a new test. - From the toolbar on the top, choose the stimulus to test and set its properties, for example how long it should be displayed on the test screen. Add more stimuli, if needed. - You are now ready to start your observation in The Observer XT. In The Observer XT - Create a new observation. To do so, click Observations in the Project Explorer, then Create a new observation. - Name the observation, then click OK. In Tobii Pro Studio - Let the participant take place behind the monitor with the eye tracker. - Click Start Recording. Record with Tobii Pro Studio - optional Enter the name of the test participant, and click Continue. 10.The Calibration screen opens. Check that the test participant's eyes are visible as two white oval shapes in the Calibration screen. If not, change his/her position relative to the monitor (lower or raise the chair or let the test participant sit closer or further away from the monitor). 11. Click Start to start the calibration and let the test participant follow the symbol moving on the screen. When the calibration is ready, the Calibration window appears. This window shows at what points on the screen the test participant looked and the positions of the calibration symbol. 12. Check whether the calibration is good, that is, whether the distance between the gaze points and the positions of the calibration symbol is acceptable. If so, click Accept. A new screen appears. Fill in the name of the recording. important At this stage, do not click the Start Recording button in Tobii Pro Studio. The system is configured to start recording automatically from The Observer XT. In The Observer XT - To start the test, click the Start observation button in The Observer XT. If the Enter Independent Variable Values window opens on the screen of The Observer XT, enter the independent variable values for that observation and click OK. Eye tracking now starts automatically. 14.Let the participant carry out the tasks assigned. 15. Optionally, score the behaviors with keys on your keyboard. 16.To stop the test, click the Stop observation button in The Observer XT. Record with Tobii Pro Studio Eye tracking now stops automatically. Notes Eye tracking also stops when the test you designed in Tobii Pro Studio ends before you pressed the Stop observation button in The Observer XT. If the computer with the Tobii Pro software is restarted, you must restart The Observer XT as well. Otherwise starting acquisition with the Tobii Pro software will not work. If the computers with The Observer XT and the Tobii Pro software are restarted, it may take some time before the Tobii Pro plugin starts when you create the first observation. If you start an observation in The Observer XT before the plugin is fully running, acquisition with the Tobii Pro software does not start. If you notice this, create and start a second observation. Acquisition with the Tobii Pro software will now start. More Information For more information on how to design a test in Tobii Pro Studio, see the Tobii Pro Studio user manual. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 7 Import Non-AOI Data Into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-7-import-non-aoi-data-into-the-observer-xt Chapter: The Observer XT Import Non-AOI data into The Observer XT 7 Import Non-AOI data into The Observer XT Aim To import the following data into The Observer XT: Fixation data. Stimulus data. Mouse click data. Key press data. Recording type data (for Tobii Pro Lab only). Prerequisite You carried out an observation in The Observer XT and simultaneously acquired eye tracking data with the Tobii Pro software. Procedure - Export the data from Tobii Pro Lab (page 26) or Tobii Pro Studio (page 27). - Import the data into The Observer XT (page 29). Export The Data From Tobii Pro Lab - Open the project and click on Data export on the toolbar. Import Non-AOI data into The Observer XT - In the Settings pane on the right, select the recording to export. important Select a single recording. Export each recording individually. Give each file a different name so that it does not overwrite the previously exported one. 3. Under Select columns for the data export, select all columns. important Always select all columns. Otherwise the import profile won't recognize the columns to import. 4. Click on Export. Export Data From Tobii Pro Studio - In Tobii Pro Studio, click the Data Export tab. - Click Select Data Set and choose the recordings to export. - From the Output list on the toolbar select Individual files. Import Non-AOI data into The Observer XT - Click the Column Order button and then the Reset Defaults button. Next, click OK. This ensures that the import profile matches the columns of the exported data file. 5. In the Data Export tab, select all columns for the data export, from General data to Eye tracking data and validity codes. important Always select all columns, except [Variable Name] Value. Otherwise the import profile won't recognize the columns to import. 6. Click the Export data button and choose where to save the export files. 7. Proceed with importing the data into The Observer XT (next page). Import Non-AOI data into The Observer XT Import Non-aoi Data Into The Observer Xt You must use a specific import profile. You do not need to convert the non-AOI export data before import in The Observer XT. 1. Copy the export files from the Tobii Pro software to The Observer XT computer. 2. In The Observer XT, open the observation in which you want to import the eye tracking data. Click the Import data button on the toolbar. Select Import observational data. The Import Observational Data window opens. 3. From the Files of type list, select the import profile you require. - For Tobii Pro Lab fixation data: Tobii Pro Lab 1.98 Fixation Data (.tsv). - For Tobii Pro Lab stimulus data: Tobii Pro Lab 1.98 Stimulus Data (.tsv). - For Tobii Pro Lab key presses and mouse clicks: Tobii Pro Lab 1.98 Keyboard and Mouse event Data (.tsv). - To exclude calibration from the observation (Tobii Pro Lab only): Tobii Pro Lab 1.98 Recording type (.tsv). See To exclude the calibration from Tobii Pro Lab data on page 30 for more information. - For Tobii Pro Studio fixation data: Tobii Studio 3.3-3.4 Fixation Data (.tsv). - For Tobii Pro Studio stimulus data: Tobii Studio 3.3-3.4 Stimulus Data (.tsv). - For Tobii Pro Studio mouse clicks: Tobii Studio 3.3-3.4 Mouse Click Data (.tsv). - For Tobii Pro Studio key presses: Tobii Studio 3.3-3.4 Key Press Data (.tsv). 4. Under Treat new Behaviors as, select Point events. 5. Browse to the location on your computer where you stored the data file. Select the appropriate file and click Open. Import Non-AOI data into The Observer XT 6. If this is the first file you import into the project, you will be asked whether you want to import new coding scheme elements. Click Yes. 7. The data are imported into The Observer XT as a new event log in the current observation. To exclude the calibration from Tobii Pro Lab data Tobii Pro Lab, by default, adds a calibration to the Timeline. This calibration is included in the export file. For further analysis of the eye tracking data, you may want to exclude the calibration. To do so: 1. Import the Tobii data, following the procedure above. In step 3 choose Tobii Pro Lab Recording Events (*.tsv) from the Files of type list. 2. Choose Analyze > Select Data > New Data Profile. Give the profile a name and click OK. 3. Under Select intervals click on the box next to By Manual Selection. 4. Under Interval Start Criteria choose Observational Data. 5. From the Behaviors list, choose Eye tracker calibration end. Leave the rest of the fields at their default values. The window now looks like this: Import Non-AOI data into The Observer XT You now created an interval from the end of the calibration till the end of the recording. When you select this data profile, the data during calibration are excluded from visualization and analysis. Import Non-AOI data into The Observer XT Notes For the first file you import into the project, you will be asked whether you want to import new coding scheme elements. Click Yes. Data from each import profile are imported as point events in a separate behavior group of type "Start-Stop". Note that fixations and saccades are imported as point events, that is, events with no duration. If you are interested in calculating fixation duration, follow the same procedure as in Import AOI data into The Observer XT on page 37. If you want to analyze the behavior of the subject while a specific stimulus was presented, in the Data profile choose Select interval - By manual selection. For both Interval Start Criteria and Interval Stop Criteria, choose Observational data and then select the same stimulus element from the behavior list. Next, insert the Intervals box in the Data profile. Import Non-AOI data into The Observer XT Check in the Visualization that the interval is selected for analysis that corresponds to the time between the start of the stimulus and the end of the stimulus (white area): When you have two or more instances of the same stimulus, under Interval Stop Criteria select the following: Various intervals will be defined: - From start of first stimulus to end of first stimulus. - From end of first stimulus to start of second stimulus. Ignore this result in the statistics table. - From start of second stimulus to end of second stimulus. - etc. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 8 Import Gaze Replay Video Into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-8-import-gaze-replay-video-into-the-observer-xt Chapter: The Observer XT Import gaze replay video into The Observer XT 8 Import gaze replay video into The Observer XT Aim To import the video with the gaze overlay into The Observer XT. tip If you have MediaRecorder and Tobii Pro Studio, you can record the screen of the Tobii Pro Studio computer (set Tobii Pro Studio to Remote Live Viewing) and import it automatically in the observation. This way you do not need to import video manually. In the Observer PC, add an exception to Windows Firewall to the application Tobii Studio Remote Viewer. Prerequisite You carried out an observation in The Observer XT and simultaneously acquired eye tracking data with Tobii Pro software. Procedure Carry out the following steps: 1. Export the gaze replay video from Tobii Pro Lab (page 34) or Tobii Pro Studio (page 36). 2. Import the gaze replay video into The Observer XT, see page 36. Export Gaze Replay Video From Tobii Pro Lab - Open the project and click on the Recordings button on the toolbar on the left. Import gaze replay video into The Observer XT - Double-click the recording from which you want to export the gaze replay video. - On the left-hand side of the timeline you find two small yellow markers. Click-and -hold the right-hand one and drag it to the end of the video. This way the entire gaze replay video is selected for export. - Right-click the yellow bar and choose Export video clip. - Browse to the location to store the video file, name the file and click Save. Import gaze replay video into The Observer XT Export Gaze Replay Video From Tobii Pro Studio - Click the Replay tab, then click the Export Movie button. - In the window that appears, choose the options you require. optional As Output folder, choose the folder shared with The Observer XT computer. 3. Click OK. Import The Gaze Replay Video Into The Observer Xt - In the Observer XT, open the observation you want to import the video to. - Choose Observe > Video > Open in Current Observation, or click the import video button on the toolbar. - Choose the video file exported from the Tobii Pro software and click Open. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Tobii Pro: 9 Import AOI Data Into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-tobii-pro-9-import-aoi-data-into-the-observer-xt Chapter: The Observer XT Import AOI data into The Observer XT 9 Import AOI data into The Observer XT Aim To import Area of Interest data into The Observer XT. Prerequisites You defined Areas of Interest in the Tobii Pro software. You have Tobii Pro Lab 1.98 or Tobii Pro Studio 3.4. Contact the Noldus help desk if you have another version of Tobii Pro software. You have the file Tobii Studio File Converter 3.0 Setup.exe provided by Noldus Information Technology. Procedure Carry out the following steps. 1. Export the eye tracking data from Tobii Pro Lab (page 26) or Tobii Pro Studio (page 36). For AOI data, it is not needed to export all columns, as long as all columns described in variables to export - tobii pro studio on page 38 are exported. 2. Convert the export file, see page 39. 3. Import the converted file into The Observer XT, see page 43. Variables To Export - Tobii Pro Lab Under General Project name: The name of the project in Tobii Pro Lab. Recording name: The ID of the recording. Import AOI data into The Observer XT Recording Date: The start date of the recording. Recording Start time. The start time of the recording. Recording Timestamp: The time stamp of a sample point from the start of the recording (set to zero). Under Gaze events: Gaze Event Duration: The duration of a fixation. AOI hit: The name of the Area of Interest. Variables To Export - Tobii Pro Studio Under General data: StudioProjectName: The name of the project in Tobii Pro Studio. RecordingName: The ID of the recording. RecordingDate: The start date of the recording. Under Timestamp data: RecordingTimestamp: The time stamp of a sample point from the start of the recording (set to zero). LocalTimeStamp: The local time stamp of a sample point. Under Gaze event data and AOI activity information: GazeEventDuration: The duration of a fixation. AOI[Name of AOI]Hit: The name of the Area of Interest. Tips In Tobii Pro Studio, it is possible to save the current selection of variables as "AOI data", so you can quickly open the same selection when necessary (Load Settings). To do so, click the Save Settings button. Import AOI data into The Observer XT To use the same data file also to import non-AOI data, for Tobii Pro Lab select all variables, or for Tobii Pro Studio select all variables except [Variable Name]Value. You can use that file in the procedures on page 26. Structure of the export file In the export file, each area of interest is represented by a column (see the last column in the example below). For each sample point, the cell contains 1 (fixation in that AOI) or 0 (no fixation). Convert The Aoi Data Why convert AOI data? To be able to import the AIO data into The Observer XT, the export file must be converted into a format that can be read by The Observer XT. note To import non-AOI data, such as fixations, mouse clicks, key presses and stimulus data, see page 26. Import AOI data into The Observer XT Install Noldus Tobii Studio File Converter - Close Tobii Pro Lab or Tobii Pro Studio. - Copy the file Tobii Studio File Converter 3.0 Setup.exe to the PC where you have stored the Tobii Pro export files. - Double-click Tobii Studio File Converter 3.0 Setup.exe and follow the instructions on the screen. - When installation is completed, click Close. By default, the Tobii Studio File Converter is installed on C:\Program Files (x86)\Noldus\Noldus Tobii Studio File Converter. Convert AOI data into The Observer XT format - In the Apps screen, under Noldus click Noldus Tobii Studio File Converter. - Next to Tobii Studio source file, click Browse, select one or more files exported from the Tobii Pro software and click Open. To select multiple TSV files, click Browse, click the TSV file names while holding the Ctrl key down, and click Open. A message confirms that multiple files are selected. 3. Next to The Observer XT destination folder, click Browse and select the folder where you want to store your converted files. Import AOI data into The Observer XT 4. Click Convert. 5. A message appears in the window "Conversion is ready". Click Exit to close the window. The converted export file To check the contents of the converted export file (*.txt), right-click it and select Open with Notepad. Do not open it in a word processor such as Microsoft Word. The file should look like this. The first line contains the value of the variable RecordingDate and the first value of Recording Start time (Tobii Pro Lab) or LocalTimeStamp (Tobii Pro Studio) in the recording. If the variables are not in the original export file, they do not appear in this line. The second line contains 0 (zero). This line is added automatically by Noldus Tobii Studio File Converter. The columns contain the following information: Time from the recording start time (in ms). Import AOI data into The Observer XT Name of the area of interest. Event type (start/stop). File name of the stimulus (optional). To import the file into The Observer XT, see page 43. Notes The name of the converted file is Observer-[StudioProjectName] [RecordingDate] [RecordingName].txt. If Studio Project Name and Recording Date are not exported from the Tobii Pro software, the converted file name is Observer- [Recording Name].txt. If the Tobii Pro export file contains more recordings, each recording is converted to a separate text file. If the Tobii export file does not contain one of the required columns, when trying to convert this file the message appears: Click Yes to continue converting (if you have selected multiple files), otherwise click No. Re-export the file with the correct columns and convert it again. The Tobii export files may also contain other columns like ParticipantName or GazeEventType, but they will not be converted. The converted file ends when the last AOI hit ends. The length of the converted file may therefore be shorter than the original recording. Import AOI data into The Observer XT Import Aoi Data Into The Observer Xt IMPORTANT Make sure that you have converted the export files with Noldus Tobii Studio File Converter (page 39). To import the data into The Observer XT - In The Observer XT, in the Project Explorer, open the observation in which you want to import the eye tracking data. Click the Import data button on the toolbar. 2. Select Import observational data. 3. In the Import Observational Data window, from the Files of type list, select Tobii 3.x AOI Data (*.txt). 4. Browse to the location where you stored the converted files. Select the appropriate file and click Open. Notes To import multiple recording files in the same observation, click each converted file name while holding the Ctrl key down. Import AOI data into The Observer XT The files are imported as separate event logs in the same observation. When visualizing multiple recordings, they appear in separate charts, one for each recording. If this is the first file you import into the project, you will be asked whether you want to import new coding scheme elements. Click Yes. Source: The Observer XT 17 - Technical Note - Tobii Pro Eye trackers --- ## The Observer XT - Up and running quickly URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-up-and-running-quickly Chapter: The Observer XT Up And Running Quickly Working with The Observer XT consists of three main steps. These three steps are visible in the main window of The Observer XT that opens once you have created a project (page 6). In step 1 you create all the necessary settings for your observations (page 6). In step 2 you collect your data (page 13). And in step 3 you analyze your data (page 17). This Quick Start Guide guides you through these main steps. Only the most basic features of The Observer XT are addressed. Inevitably, some features that may be vital to your application are not discussed. You find additional information in The Observer XT Help. Press F1 in The Observer XT to open it. Video tutorial To get you going, you can also watch the video tutorial. You can open this tutorial within The Observer XT. Choose Help > Video Tutorial. Up and running quickly Support If you encounter problems, from the Help menu select Noldus Online > Get Support. You will be directed to MyNoldus. Log in with your MyNoldus username and password. Select Support. Install and start The Observer XT Install And Start The Observer XT To install The Observer XT - Download the Observer installation zip file via your MyNoldus account: click on Downloads and then Versions. Browse to my.noldus.com if you do not have a MyNoldus account yet. - Unzip the zip file and double-click the file The Observer XT 17 Setup.exe. - Under Installation type, select Standard. - Follow the rest of the instructions on your screen to install The Observer XT. - Dependent on your license, do one of the following: If you have a software activation code, start The Observer XT and activate your license. You can choose between a Floating or a Fixed activation. - Floating - Choose Floating if you want to be flexible on which computer you use The Observer XT and your computer is connected to the internet. - Fixed - A Fixed activation is linked to one computer. You can activate your license online (if the computer has an internet connection) or offline by scanning a QR code with your smartphone. After you have activated the license you can use The Observer XT without internet. If you have a hardware key, insert it into the computer and open The Observer XT. Step 1 - Create all settings Source: The Observer XT 17 - Quick Start Guide --- ## The Observer XT 17 - BitBrain EEG - Bitbrain Diadem EEG and The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-bitbrain-eeg-bitbrain-diadem-eeg-and-the-observer-xt Chapter: The Observer XT Bitbrain Diadem EEG and The Observer XT Introduction The BitBrain Diadem is a 12-channel wearable and portable, dry EEG device designed for real-world applications that require easy set-up and high signal quality. The Diadem system is designed to address the pre-frontal, frontal, parietal and occipital brain areas to measure emotional and cognitive states such as cognitive workload. The Diadem has been designed for adults. It can be used for children from the age of 10. The sample frequency is 256 Hz and battery life is more than 8 hours. Sensor Layout The headband includes 12 EEG sensors, plus ground (GND) and reference (REF). The sensors are placed at positions AF7, Fp1, Fp2, AF8, F3, F4, P3, P4, PO7, O1, O2 and PO8, according to the EEG 10/10 international standard. REF is located on the ear clip. The correspondence between channel numbers and sensors is as follows: - Channel 1: AF7 - Channel 2: Fp1 - Channel 3: Fp2 - Channel 4: AF8 - Channel 5: F3 - Channel 6: F4 - Channel 7: P3 - Channel 8: P4 - Channel 9: PO7 - Channel 10: O1 - Channel 11: O2 - Channel 12: PO8 About This Technical Note This document describes how to achieve automatic synchronization between observational data in The Observer XT and EEG data acquired with and exported from a Bitbrain system. You can: - Start and stop data acquisition in the Bitbrain Acquisition software from The Observer XT. - Manually import Bitbrain EEG data into The Observer XT after the observation is ready. System Tested Processing Unit: Dell Precision T3660 - Processor: Intel Core i7 12700K (12 Core), 3.6 GHz or better - Internal memory: 16 GB - Operating system: Windows 10 and Windows 11 Professional Edition Software: - The Observer XT 16 or higher - N-Linx Server 1.4 or higher - N-Linx Agent 1.4 or higher - BitBrainControl 1.0 software to control the EEG device - Bitbrain Acquisition 0.3 software — the acquisition software for the Bitbrain device Note: Tests were carried out with all the software on one PC. You can also use two PCs and set up a local network. In that case The Observer XT and N-Linx Server are installed on PC 1, and the BitBrain Acquisition software, the Bitbrain Control software and N-Linx Agent are installed on PC 2. For Further Information and Help Other Manuals: - User Guide - Diadem - Bitbrain - The Observer XT Help - The Observer XT Quick Start Guide - N-Linx - Reference Manual Customer Support: For technical support, please visit the MyNoldus portal (my.noldus.com). Log into your account or create a new one and submit a support case. --- ## The Observer XT 17 - BitBrain EEG - Carry Out Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-bitbrain-eeg-carry-out-data-acquisition Chapter: The Observer XT Carry Out Data Acquisition - Place the headset on the test participant's head following the instructions in the User Guide - Diadem - Bitbrain. - Browse to the folder in which you installed the BitBrain Acquisition software and open the bin subfolder, for instance D:\BitBrain\bitbrain-acquisition-0.3\bitbrain-acquisition-0.3\bin. - Double-click the file named Bitbrain Acquisition.exe. A Console window will open. - In The Observer XT, create a new observation (Alt+F6). - To start data acquisition, click the Start Observation button. The Bitbrain window shows the channels in green (good connection), yellow (unstable connection) or red (bad or no connection). - If necessary, adjust the Diadem, wait a few seconds (more than 10) and then check whether the status of the channels has changed to green. - To stop data acquisition, click the Stop Observation button. The data are saved in the output folder that you defined during configuration. Both raw data (*_eeg.csv) and derived data (alpha, beta, delta and theta rhythms) are saved. The derived data are saved in the eeg_power subfolder. - Browse to the output folder and copy the data files from the BitBrain PC to The Observer PC in a 2-PC set-up. Import the Bitbrain Data into The Observer XT The Observer XT 17 has a built-in import profile for Bitbrain data. In The Observer XT 16 this is not present yet. If you work with The Observer XT 16, follow steps 1–3 below. If you use The Observer XT 17, you can skip these steps. - Make sure that The Observer XT is not running. - Download the zip file with the Bitbrain import profile (Profiles.zip) via your MyNoldus account (my.noldus.com) and copy it to The Observer PC. - Unzip the zip file and copy the import profile (BitBrain EEG.eip) and the folder with the data file (BitBrain EEG) to C:\ProgramData\Noldus\Common\Profiles. - Note: The ProgramData folder is a hidden folder. To view this folder, browse to C:\ and on the View tab select Hidden items. - Start The Observer XT and from the File menu select Import and then External Data. The Import External Data window opens. - Select the Bitbrain EEG (*.csv) import profile from the Files of type drop-down list. - Select the observation that corresponds with the data file. - Browse to the output folder and select the appropriate data file, either a data file with the raw EEG data or a data file with pre-processed data (alpha, beta, theta and delta activity). You can use the import profile for both types of data files. Click Open. The EEG data for each channel are now imported. The data stream names will appear in the Project Explorer and in the Independent Variable list. Optionally, in The Observer XT you can select data, visualize them, carry out further data analysis and export the synchronized observational and EEG data. For details, see The Observer XT Help. You can also further process your data in EEGLab, Matlab or Python. How to Interpret the Data By measuring when and in what brain regions activity occurs, you can get important insights into brain functions. It is key to take the context into account when trying to interpret EEG data. The Bitbrain system allows you to measure alpha, beta, theta and delta activity. - Alpha — In healthy awake adults, alpha waves occur while resting with the eyes closed. They disappear when people concentrate on a specific task. Relative asymmetry in alpha activity in the frontal cortex indicates positive affect and approach motivation (Paul et al., 2022). - Beta — Beta waves are involved in conscious thought and logical thinking. - Theta — Theta waves are relevant for cognition studies including learning, memory and spatial navigation. Recent research has shown that theta activity in the frontal cortex is an index for cognitive workload (Chikhi et al., 2022). - Delta — Delta waves are the slowest brain waves in human subjects. They are related to sleep depth. Source: The Observer XT 17 - BitBrain EEG, Noldus Information Technology --- ## The Observer XT 17 - BitBrain EEG - Software Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-bitbrain-eeg-software-setup Chapter: The Observer XT Software Setup If you purchased your PC from Noldus Information Technology, all the software is already installed and tested. If you purchased your own PC, please follow the instructions below. Install The Observer XT - Download the Observer XT installation file (The Observer XT Setup.exe) via your MyNoldus account (my.noldus.com, under Downloads > The Observer XT > Versions). - Double-click the installation file to run it and follow the instructions on the screen. - Activate or insert your license key: - If you have a software license — activate your license. - If you have a hardware key — insert the key into your computer. Install N-Linx Server Important: If your set-up includes more than one PC, install N-Linx Server on the Observer XT computer. - Download the N-Linx Server installation file (N-Linx Server Setup.exe) via your MyNoldus account (my.noldus.com, under Downloads > The Observer XT > Drivers & Tools). - Double-click the installation file to run it. - Next to Installation type, choose Standard, unless you want to specify an installation folder other than the default one (C:\Program Files\Noldus\N-Linx Server 1). - Follow the instructions on your screen. Install and Connect N-Linx Agent Important: If you use a 2-PC set-up, install N-Linx Agent on the Bitbrain computer. - Download the N-Linx Agent installation file (N-Linx Agent Setup.exe) via your MyNoldus account (my.noldus.com, under Downloads > The Observer XT > Drivers & Tools). - Double-click the installation file to run it. - Next to Installation type, choose Standard, unless you want to specify an installation folder other than the default one (C:\Program Files\Noldus\N-Linx Agent 1). - Agree with the license agreement, click Install and follow the instructions on your screen. - If the N-Linx Agent window does not open after installation, at the bottom-left corner of the screen, on the system tray, click the Show hidden icons icon and double-click the N-Linx Agent icon. - Next to N-Linx Server Address, enter the IP address of the computer where N-Linx Server is installed. This IP address must be fixed. If N-Linx Server and N-Linx Agent are installed on the same PC, enter localhost as the N-Linx Server Address. - Tip: You can also enter the Computer name instead of the IP address. To find the Computer name of the computer where N-Linx Server is installed, on that computer open the Control Panel and choose System. Locate Device name. - Click Connect. If connection is established, the message at the bottom of the N-Linx window says Connected. Install Bitbrain Control Software - Download the BitBrainControl installation file (BitBrainControl.Installer.exe) via your MyNoldus account (my.noldus.com, under Downloads > Versions). - Double-click the installation file to run it and follow the instructions on your screen. - Browse to C:\ProgramData\Noldus\BitBrain Control\1, copy the file named Noldus.Proxy.BitBrain.config and rename it to Noldus.Proxy.BitBrain.config_old to make sure that you have an original version of the file. - Note: The ProgramData folder is a hidden folder. To view this folder, browse to C:\ and on the View tab select Hidden items. - Open Notepad or another text editor and open the file named Noldus.Proxy.BitBrain.config. - Edit the file as follows: - — IP address of the PC on which N-Linx Server is installed - — IP address of the PC on which Bitbrain software/N-Linx Agent is running - — shown on the amplifier device - — folder in which the data will be saved - Always use a forward slash (/) in the pathname, not a backward slash (\). - The RabbitMQAddress is localhost if N-Linx Server is installed on the same PC as the BitBrainControl software. - The BitBrainAddress is localhost if you have a 1-PC set-up. - Save the config file with the same name. - Create the folder that you defined as the output folder in step 5. To Find an IP Address: - Click the Windows button, type cmd and press Enter. A Command Prompt window will open. - Type ipconfig and press Enter. - The IP address you need is the IPv4 address. Install Bitbrain Acquisition Software and Prepare Data Acquisition - Download the Bitbrain acquisition software (bitbrain-acquisition-0.3.zip) via your MyNoldus account (my.noldus.com). - Unzip the zip file. - Turn on the Bitbrain amplifier by pressing the power button. The LED on the amplifier will flash until a connection with the software is established, at which point the light will be steady. - Connect the Bitbrain Diadem via Bluetooth: - Click the Windows button, type Settings and press Enter. - Click Devices and then click the plus (Add Bluetooth or other device) icon at the top of the screen. - Click Bluetooth and wait until the Bitbrain device with the ID that you entered in the configuration step appears. - Click the device name. The device will then start making a connection with the PC. When the connection is established you will see a message that your device is ready to go. Click Done. The device ID will appear in the list with Other devices and will have the status Paired. Prepare The Observer XT Connect The Observer XT to N-Linx Server Follow this procedure just once. The settings are also valid for any new Observer XT project that you create. - In The Observer XT, choose File > Preferences. - Click N-Linx settings on the left. - Select Use N-Linx Server to connect with other applications. - Next to N-Linx Server address, leave the default entry localhost. - Make sure the N-Linx Server port is 5672. Ask your system administrator for assistance if this port is used by another program. - Click Test connection, and check that the message Connected appears. If connection fails, it means that N-Linx Server is not installed properly. Reinstall N-Linx Server. Project Setup Follow these steps for each new Observer XT project you create to work together with the Bitbrain system. - Open the project and choose Setup > Project Setup. - Under Observation Source, select Live Observation. - In the Devices window, select BitBrain Control. If you do not see this item, it is likely that N-Linx Agent is not installed. - Double-click the Status cell next to BitBrain Control and check that the status is Enabled, Running. --- ## The Observer XT 17 - Calculate Statistics - Analyzing Observations Containing Multiple Event L URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-calculate-statistics-analyzing-observations-containing-multiple-event-l Chapter: The Observer XT Analyzing Observations Containing Multiple Event Logs An observation can have multiple event logs if you imported observational data into it, for example FaceReader states. Choose how to analyze the event logs: - Event logs as separate data sets, so each event log produces one result. - Event logs as one data set, so all event logs within an observation are collapsed into one result. Event Logs as Separate Data Sets - Click the Layout button on the Analysis toolbar. - Make sure that both Observations and Event Logs are selected. The statistics are calculated as follows: If you have not defined intervals and time bins in your data profile: - Analyzed Duration – The duration of each event log. If the imported event log has an offset compared to the Observer XT event log, it will be shorter, since the stop of the observation determines the end of both event logs. - Total Number and Duration Statistics – These are calculated per event log. - Rate Per Minute (Observation Duration), Percentage (Observation Duration) – These are based on the duration of the corresponding event log. - Rate Per Minute (Analyzed Observation Duration), Percentage (Analyzed Observation Duration) – These are based on the event log duration, excluding the suspend time. If you have defined intervals or time bins in your data profile: - Total Number and Duration Statistics – They are calculated per interval and event log. - Rate Per Minute (Interval Duration), Percentage (Interval Duration) – These are based on the duration of the interval. - Rate Per Minute (Analyzed Observation Duration), Percentage (Analyzed Observation Duration) – These are based on the duration of the event log, excluding the time that the observation was suspended. - Rate Per Minute (Analyzed Interval Duration), Percentage (Analyzed Interval Duration) – These are based on the time line set by data selection, excluding the time that the observation was suspended. The duration of the interval is not necessarily the same as the analyzed duration, for example when two or more separate intervals split the event log into different sections. To analyze each interval separately, select the check box in front of Intervals in the Layout window. - Percentage (Interval Duration) – This is calculated over the entire duration of the interval, not the part of the event log falling within the interval. This may give unexpected results when the event log does not cover the entire interval duration. If you want to calculate the percentage relative to the event log only, select a different type of interval (for example by selecting intervals by behavior) or use Percentage (observation duration). Event Logs as One Data Set - Click the Layout button on the Analysis toolbar. - Make sure that Observations is selected and Event Logs is not selected. If you have not defined intervals and time bins in your data profile: - Analyzed Duration – The duration of the Observer XT event log. - Total Number and Duration Statistics – They are calculated per event log, then summed up. - Rate Per Minute (Observation Duration), Percentage (Observation Duration) – These are based on the time from the earliest start of any event log to the latest stop of any event log. - Rate Per Minute (Analyzed Observation Duration), Percentage (Analyzed Observation Duration) – These are based on the time from the earliest start of any event log to the latest stop of any event log, excluding the time the observation was suspended. If you have defined intervals or time bins in your data profile: - Total Number and Duration Statistics – They are calculated per interval and event log, then summed up. - Rate Per Minute (Interval Duration), Percentage (Interval Duration) – These are based on the summed duration of the intervals. To analyze each interval separately, keep Intervals selected in the Layout page of your Analysis settings. - Percentage (Interval Duration) – This is calculated over the entire duration of the interval, not the part of the event log falling within the interval. This may give unexpected results when the event log does not cover the entire interval duration. If you want to calculate the percentage relative to the event log only, define an interval that only includes the event log. - Rate Per Minute (Analyzed Observation Duration), Percentage (Analyzed Observation Duration) – These are based on the time from the earliest start of any event log to the latest stop of any event log, excluding the time the observation was suspended. - Rate Per Minute (Analyzed Interval Duration), Percentage (Analyzed Interval Duration) – These are based on the time from the earliest start of any event log to the latest stop of any event log, excluding the time the observation was suspended and the time excluded by data selection. If overlapping event logs generate overlapping intervals, these are merged along the time line to calculate the analyzed duration. To analyze each interval separately, select the check box in front of Intervals in the Layout page of your Analysis settings. Source: The Observer XT 17 Help - Calculate Statistics, Noldus Information Technology --- ## The Observer XT 17 - Calculate Statistics - Calculate Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-calculate-statistics-calculate-statistics Chapter: The Observer XT Calculate Statistics Introduction The Observer XT has a large number of descriptive statistics that give a full numerical overview of your data. For any analysis, you can restrict the data to analyze in a data profile (see Select Data for Analysis). If you use the default data profile with all data, The Observer XT calculates statistics on all observations in your project. It is therefore important to select the correct data profile before you carry out any analysis. The Observer XT has the following descriptive analysis types: Behavior Analysis To calculate statistics for events scored in the observations, like the duration or number of occurrences of an event. See Statistics for Behavior Analysis in Detail for a detailed description. - Example 1 – The average duration and standard deviation of the behavior Play for the subject Child. - Example 2 – The number of times the subject Test Participant 1 requested help. Numerical Analysis To calculate statistics for numerical modifiers and external data in the observation, like the average value. See Statistics for Numerical Analysis in Detail for a detailed description. - Example 1 – Calculate the average value of the numerical modifier Speed. - Example 2 – Calculate the average heart rate of the test participant. To analyze numerical modifiers as events, for example to calculate their duration or frequency, carry out a Behavior Analysis instead of a Numerical Analysis. See To Analyze Numerical Modifiers. See also Analyze Modifiers. General Procedure To calculate descriptive statistics for your observations. Prerequisite: You carried out at least one observation. - Select the data profile specifying the data you want to analyze. To do so, click it in the Project Explorer. - Choose Analyze > Behavior Analysis or Numerical Analysis > New. A table appears with question marks. - Click the Statistics button on the toolbar and select the statistics. - Click the Calculate button on the toolbar. The Statistics Result table appears. The Statistics Result In the statistic result table, you can distinguish the following groups of cells. The exact position depends on the choices you made in the Layout window. See Customize the Results. - A – Statistics: Cells containing a statistic for a combination of Results Container, Observation, Event Log, Subject, Behavior, and Modifier. - B – Independent Variables (optional): Cells containing the value of an independent variable linked to a certain observation, event log, or subject. Shown if you have selected Independent Variables on the Layout page. - C – Main Headers (dark gray area): The names of the main categories: Data Selection Result Containers, Intervals, Observations, Event Logs, Subjects, Behaviors and their Modifiers, and Variables. - D – Secondary Headers (light gray area): Show the single element values, for example the name of the behaviors or independent variables. Modifiers A behavior may be associated with several modifier values. Statistics are shown for the modifiers attached to a number of communication types. Result Containers The Result Containers column or row shows the name of the Results boxes specified in the currently active data profile (see Select Data for Analysis). If you have specified more than one Results box, their names are shown in the Result Containers row or column. Statistics are calculated for each Results box separately, if you selected Result Containers in the Layout window. See Group Elements. Intervals The Intervals row or column shows the start and end time of the time segments analyzed if you have specified intervals or time bins in your data profile. To display intervals, make sure that Result Containers and Intervals are selected in the Layout window. See Group Elements. The format of the intervals depends on what you chose as time format. See Time Formats. What Happens at the Interval Borders? The border of two connecting time intervals can only be used for analysis in one of the two time intervals. Otherwise the data for this data point would be duplicated. The Observer XT uses the left borders (start) of the time intervals for analysis, while the right borders (end) are used in the analysis of the next interval. In the example below the exact data point 0.0 is used in the first interval, 10.0 in the second, 20.0 in the third, and 30.0 is not used in any interval. If your project contains external data, the sample at the exact end of an interval is also not included in the analysis. Events Scored at the Observation Stop Time Events scored at the exact stop of the observation are not included in the analysis. Instantaneous samples cannot be scored at the exact stop of the observation. and The and rows/columns show the statistics for records you have scored with no subject or no behavior. For example, when you score a behavior with no subject, or when you scored comments only. You can only calculate the frequency, rate per minute, and latency of Missing Behaviors and no durations. Durations are only calculated for State behaviors that are defined in the Coding Scheme. To hide or , choose View Settings > Subjects or Behaviors and deselect . Group Elements To group all elements in one category and obtain average or total values for that category. For example, obtain the mean value of the duration of a behavior for all subjects, or for all observations. Prerequisite: You carried out at least one observation. - Follow the General Procedure to obtain a statistics results table. - Click the Layout button on the toolbar. - Deselect the element you want to group. For example, deselect Observations to calculate the total number of times an event was scored across all observations. Examples - Example 1 – Grouping Observations: When Observations is selected in the Layout window, statistics are displayed per observation. When Observations is deselected, the statistics are given for all observations grouped. - Example 2 – Grouping Modifiers: Deselect Modifiers to calculate statistics for the behaviors, independent of which modifiers were scored. Notes on Grouping - Important: Do not group categories if you want to calculate statistics for external data. Doing so may give unexpected results. - You cannot group Result Containers and Behaviors. To analyze behaviors as a group, merge them first in the data profile. See Merge Data. - If you want to group some elements in one category and others not, use Merging (see Merge Data) in a data profile and carry out an analysis while this profile is active. Statistics with Merged or Grouped Data Merged Data: If you have merged data in the data profile (see Merge Data), the analysis results show the merged results. Consider the following example: Behaviors A and B both have a duration of 5 seconds and they overlap for 1 second. After merging, the frequency of the merged behavior is 1 and its duration is 9 seconds. The percentage of time the merged behavior occurs is 100%. Grouped Data: If you have grouped data by deselecting a category in the Layout window (see Group Elements), the Number and Duration used to calculate the statistics are summed across all elements in that category. Example: In two observations of 10 minutes each, behavior A is scored for 5 minutes in the first and 5 minutes in the second. When deselecting Observations in the Layout window, the frequency of behavior A is 2. The total duration is 10 + 10 = 20 minutes. The percentage of time behavior A occurred is ((5+5) / (10+10)) * 100 = 50%. Analyze Modifiers To Analyze Numerical Modifiers Numerical modifiers can be analyzed in two ways: - Numerical Analysis: This gives numerical statistics on numerical modifiers, like the mean value, minimum or maximum value, or the median. - Behavior Analysis: This analyzes numerical modifiers as events. Do this, for example, to analyze the number of times that the modifier 0.1 was scored, or the average duration of the numerical modifier 0.5. Do not carry out behavior analysis if you defined a modifier range instead of predefined values and scored many values. Also do not carry out behavior analysis on external data values. To Analyze Merged Numerical Modifiers Merging numerical modifiers in a data profile makes a nominal group, which means you cannot carry out a numerical analysis on the group to calculate mean, maximum, and minimum values. You can analyze the group as an event, for example to calculate the frequency or duration. You get separate results for the group and for the modifiers outside the group. For example, if you have a numerical modifier Speed with predefined values 1, 2, 3, 4, 5, 6, 7, 8 and you created a group Slow containing the modifiers 1, 2, 3, a Behavior Analysis gives results for the group Slow and the modifiers 4, 5, 6, 7, 8. To Analyze Nominal Modifiers Nominal modifiers are analyzed in the same way as behaviors. To Analyze Multiple Nominal Modifiers If you have attached more than one modifier to a specific behavior, there are two options to analyze them in behavior analysis: - In specific combinations as they were scored: For example, calculate the number of times this combination occurred: Play (behavior), Duet (modifier 1), Constructive (modifier 2), etc. To do so, select Show Combined Modifiers. - Independently of other modifiers scored in the same event: For example, calculate the number of times that Duet occurred independent of other modifiers. To do so, clear the Show Combined Modifiers option. Example: In a study of interactions among children, the type of play is coded with two modifier groups: Play 1 to specify whether the subjects play as a Duet or In Parallel, and Play 2 to specify whether play is Manipulative, With Rules, etc. A typical event scored is, for example, Play – Duet – With Rules. - If you select Show Combined Modifiers, the statistics are calculated for each combination of modifiers scored. For example: Play–Duet–With Rules Frequency = 4. - If you do not select Show Combined Modifiers, the statistics are calculated for each modifier separately, regardless of which other modifiers were scored with it. For example: Play–Duet Frequency = 3; Play–With Rules Frequency = 2. Notes on Show Combined Modifiers - The results obtained with Show Combined Modifiers are not necessarily the sum of the separate results. In the example above, Play–With Rules may also refer to an event where With Rules was scored with a modifier other than Duet of the Play 1 group. - The Show Combined Modifiers option is only available in Behavior Analysis. Customize the Results - Customize the table layout - Show missing values as - Show/hide elements not scored - Choose number of decimals - Sort the table - Select elements - Set default analysis settings - Edit statistics - Save statistics - Hide rows and columns Customize the Table Layout - Follow the General Procedure to obtain a statistics results table. - Click the Layout button on the toolbar. - Select the element you want to view on rows, columns, and separate sheets. - Clear the selection for the elements you do not want to include in the table. See also Group Elements. --- ## The Observer XT 17 - Calculate Statistics - Moving Categories Between Boxes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-calculate-statistics-moving-categories-between-boxes Chapter: The Observer XT Moving Categories Between Boxes To move a category to a different box, click its name and then click the appropriate arrow button, or drag it to the destination box. You cannot move Behaviors without the attached Modifiers. Example: If you select Statistics under On Sheets, each statistic will be shown in its own sheet. To place each statistic on columns of the same table, move Statistics to the On Columns box. Show Missing Values As Aim To choose how to display missing values. Missing values are given for: - Events that did not occur in the selected data. - Events that have no duration (see Behavior Types) while the statistic describes a duration, like Mean Duration or Total Duration. Procedure - Click the Settings button on the toolbar of the statistics results table. - Choose the character you want to have displayed for missing values in the statistics result. Show/Hide Elements Not Scored Aim To display elements, for example behaviors, that were not scored in the project in the statistics results table. Procedure - Click the Layout button on the toolbar. - Select the option Show Elements Not Scored. - The elements will then be displayed in the table, with the symbol that you chose to display for Show Missing Values As. Choose Number of Decimals Aim To choose the number of decimals of non-time values in the statistics results table. Procedure - Click the Settings button on the toolbar of the statistics results table. - Choose the number of decimals. Note: - To change the decimals of time values, see Time Formats. - To change the decimal symbol, from for example point to comma, do so in the Windows Regional Settings. In the Control Panel, choose Region > Formats. Select a language or click Customize and change the decimal symbol. Changing your regional settings takes effect after restarting The Observer XT. Sort the Table To sort the table by the main categories, change their position within each box (top = highest hierarchical level) with the arrows at the bottom of the box. Select Elements To select the elements to view in the table, click the category name and click the Settings button, then select the elements. For example, to show two observations out of three, select Observations, click the Settings button and then select the observations. See also Group Elements. Set Default Analysis Settings To save the settings specified in the steps above, click the Set Default button in the Analysis Settings window. The new settings are applied in future analyses. To return to these settings after you made new changes, click the Reset to Default button in the Analysis Settings window. Edit Statistics You cannot edit the content of the statistics result. If you want to make any changes to the result, export it to another program like Excel and then edit it in that program. See Export Analysis Results. Save Statistics To save a result, click the Archive button on the toolbar of the Analysis Result window. To re-open a saved result, click its name under the analysis item in the Project Explorer. For more information on saving, opening and exporting results, see Manage Analysis Results. Hide Rows and Columns To hide rows and columns of your statistics result, right-click a header and choose Hide Row or Hide Column. When you hide rows or columns, the row or column deleted is always the one at the lowest level selected, independent of which cell you right-click. For example, right-clicking the cell Play under Behaviors results in hiding the row corresponding to the modifier Manipulative, not the group of rows corresponding to Play, because the mouse pointed to the row of the modifier Manipulative. To show hidden rows and columns, right-click the header of one of the remaining rows or columns and select Show Hidden Rows or Show Hidden Columns. Statistics in Detail Behavior Analysis The following statistics are available for Behavior Analysis. See also Statistics for Behavior Analysis in Detail. For continuous sampling: - Minimum duration - Maximum duration - Mean duration - Total duration - Standard deviation - Standard error - Rate per minute - Total number - Percentage - Latency - 25th percentile - Median - 75th percentile For instantaneous sampling: - Proportion - Scored samples - Total number For intervals: - Minimum interval - Maximum interval - Number of intervals - Interval duration - Total interval duration - Analyzed interval duration - Analyzed duration Numerical Analysis The following statistics are available for Numerical Analysis. See also Statistics for Numerical Analysis in Detail. For numerical modifiers only: - Total duration - Total value - Mean (per minute) For numerical modifiers and external data: - Minimum value - Maximum value - Mean value - 25th percentile - Median - 75th percentile For external data only: - Number of samples - Number of valid samples Note: To calculate the frequency with which each value of numerical modifiers was scored, or the duration of the corresponding event scored, carry out Behavior Analysis instead. Normal Distribution Statistics like the mean and the standard deviation are meaningful when your data are normally distributed. However, behavioral data are often not normally distributed. We therefore recommend checking whether your data are normally distributed with a statistical package. If the data are not normally distributed, you should first transform your data before analysis, or use statistics suited for non-normally distributed data, like the median. If you have defined intervals in your data selection, this can result in only a small number of samples (both in observational and external data), which often are not normally distributed. For instance, a mean of values 1, 10 and 10 is not meaningful. Statistics in Detail For an extensive description of the statistics, see for example: Zar, J.H., Biostatistical Analysis, Pearson Education, 2007. The statistics available in The Observer XT depend on the type of analysis and the type of events. --- ## The Observer XT 17 - Calculate Statistics - Statistics for Behavior Analysis in Detail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-calculate-statistics-statistics-for-behavior-analysis-in-detail Chapter: The Observer XT Statistics for Behavior Analysis in Detail For Continuous Sampling For behaviors with duration only: - Minimum duration – The shortest duration of a behavior. - Maximum duration – The longest duration of a behavior. - Mean duration – The total duration divided by the number of times the event occurred: D is the duration of the individual behavior, and N is the number of times the behavior occurs. - Total duration – The sum of the duration of all events of a specific behavior. - Standard deviation – The sample standard deviation of the duration of a behavior, where D is the duration of the individual behavior, the mean duration, and N the number of occurrences of the behavior. - Standard error – The standard error of the mean (s.e.m.), where s is the standard deviation of a sample and N is the number of occurrences (sample size). - Percentage – The general formula of Percentage is: Percentage = Duration of event * 100 / Duration in seconds. For Duration, you can choose between: - Observation duration – The total duration of the observation. - Interval duration – The duration of the interval specified in the data profile. - Analyzed observation duration – The total duration of the intervals specified in the data profile, excluding the time the observation was suspended. - Analyzed interval duration – The duration of the interval specified in the data profile, excluding the time the observation was suspended. - 25th percentile – Twenty-five percent of the events of this type has this duration or lower. The 25th percentile is also called the first quartile. See Percentiles in Detail. - Median – Fifty percent of the events of this type have this duration or lower. The Median is the same as the 50th percentile or 2nd quartile. See Percentiles in Detail. - 75th percentile – Seventy-five percent of the events of this type have this duration or lower. The 75th percentile is also called the 3rd quartile. See Percentiles in Detail. For all behaviors: - Rate per minute (RPM) – The general formula of Rate per minute is: Rate per minute = (Total number of occurrences / Duration in seconds) * 60. For Duration, you can choose between: - Observation duration – The total duration of the observation. - Interval duration – The duration of the interval specified in the data profile. - Analyzed observation duration – The total duration of the intervals specified in the data profile, excluding the time the observation was suspended. - Analyzed interval duration – The duration of the interval specified in the data profile, excluding the time the observation was suspended. - Total number – The number of times the selected event occurs in the observation or event log. - Latency – The time from the start of the observation to the first occurrence of a behavior. When you have created intervals based on data selection, the latency is only calculated for the behavior within one of the intervals. Note: To calculate the time between a behavior and the moment another behavior starts, do not use Latency. Latency is always calculated from the start of the observation. Instead, select Intervals by Manual Selection and calculate the interval duration. For example, to find the time between the moment the mother leaves the room and the baby first starts crying, create an interval by manual selection with the start and stop criteria both based on observational data. Carry out a behavior analysis and from the statistics select Analyzed Interval Duration. In the Layout window, select the checkbox in front of Intervals. See Group Elements. Percentiles in Detail In this example, 25% of the events scored has a duration of 2 s or lower. 50% of the events has a duration of 3 s or lower. The 50th percentile is the Median. 75% of the events has a duration of 4 s or lower. The event Play was scored eight times. When the duration of the events is sorted, the Median (50th percentile) divides the scored events equally. In this example it lies halfway between 4 and 5 s, which is 4.5. Fifty percent of the events, which is four events, has a duration of 4.5 s or lower. Statistics for Instantaneous Sampling - Proportion (All Samples) – The number of times a behavior has been scored divided by the total number of samples in the observation. - Proportion (Scored Samples) – The number of times a behavior has been scored divided by the number of scored samples. - Scored Samples – The number of times a behavior has been scored in an observation. - Total Number (All Samples) – The total number of samples in an observation. - Total Number (Scored Samples) – The total number of scored samples. Example: A group of 10 animals is observed during an hour with a sample interval length of 5 minutes. The Total number (all samples) is 12. For a specific animal, 4 samples are missing. Total number (scored samples) for this animal is 8. For this animal behavior 'Sit' has been scored '4' times. Scored samples for Sit is 4. Proportion (all samples) = 4/12 = 0.33. Proportion (scored samples) = 4/8 = 0.50. Statistics for Intervals - Minimum Interval – The shortest interval duration. - Maximum Interval – The longest interval duration. - Number of Intervals – The total number of intervals. - Interval Duration – The duration of each interval. - Total Interval Duration – The duration of all intervals together. - Analyzed Interval Duration – The interval duration minus the time that the observation was suspended within this interval. Make sure Intervals is selected in the layout window. - Analyzed Duration – The sum of the intervals minus the time that the observation was suspended within the intervals. Notes on Intervals or Time Bins When one event overlaps two or more intervals, it is counted one time in each interval. The Total number statistic is the number of times an event occurs within an interval or time bin. This means that when you define intervals or time bins, the Total number statistic may be larger than the true number of occurrences of that event. --- ## The Observer XT 17 - Calculate Statistics - Statistics for Numerical Analysis in Detail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-calculate-statistics-statistics-for-numerical-analysis-in-detail Chapter: The Observer XT Statistics for Numerical Analysis in Detail For Numerical Modifiers Only - Total Duration – The sum of the durations of a scored modifier. - Total Value – The sum of the values of a scored modifier. - Mean (Per Minute) – The mean value of a scored modifier weighted for the duration it lasted. For example, modifier 3 lasted 5 seconds and modifier 2 lasted 2 seconds. The Mean (per minute) is ((3 x 5) + (2 x 2)) / (5 + 2) = 19 / 7 = 2.71. The Mean (per minute) is calculated for events with duration only, not for events without duration. If a numerical modifier is associated with an event without duration, the Mean (per minute) is zero. For Numerical Modifiers and External Data - Minimum Value – The lowest value of a scored numerical modifier or external data. - Maximum Value – The highest value of a scored numerical modifier or external data. - Mean Value – The arithmetic mean of a scored numerical modifier or external data. - 25th Percentile – Twenty-five percent of the modifiers or external data samples of this type has this value or lower. The 25th percentile is also called the first quartile. - Median – Fifty percent of the modifiers or external data samples of this type has this value or lower. The Median is the same as the 50th percentile or 2nd quartile. - 75th Percentile – Seventy-five percent of the modifiers or external data samples of this type has this value or lower. The 75th percentile is also called the 3rd quartile. For External Data Only - Number of Samples – The number of external data samples that are included in an interval. This number includes the samples that have a NaN value (missing samples). - Number of Valid Samples – The number of external data samples that are included in an interval and have a valid value. The number of valid samples is the Number of samples minus the number of samples with a NaN value (missing samples). Notes - For external data, all statistics, except for the Number of samples, are based on the Number of valid samples. Hence, missing samples do not influence them. - Do not group categories if you want to calculate statistics for the external data. Doing so may give unexpected results. Examples of Calculation of External Data Statistics The calculation of statistics for external data is based on the actual sample points; the external data is not interpolated. Example 1: You have an observation with external data. In a data profile, you created intervals based on observation time/event log data. For this interval, the numerical statistics values of the external data are: Minimum = '98', Maximum = '100', Mean = '98.77' (the mean of 98, 100, and 98.3), Number of samples = '3'. Example 2: You have the same observation with external data as in the previous example. In a data profile, you created an interval by manual selection with external data values higher or equal to 92. For this interval, the numerical statistics values for the external data are: Minimum = '92', Maximum = '100', Mean = '97.07' (the mean of 92, 98, 100, and 98.3), Number of samples = '4'. --- ## The Observer XT 17 - Carry Out an Observation - Advanced Observations URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-advanced-observations Chapter: The Observer XT Advanced Observations Import Data into an Observation Import Event Data You can import event data in the form of: - Observational data files from The Observer 4/5, The Observer XT, and Pocket Observer. - External observational data files: any data files in which events are organized in rows. For transferring files between The Observer XT and Pocket Observer, see the Pocket Observer Reference Manual. Import External (Physiological) Data For the detailed procedure, see the External Data section. Import Video or Audio Files - If you still have to create the observation in which to import the media files: Choose File > Import > Video in New Observation or Audio in New Observation. Name the observation and click OK. Then select the media file. - If you have created an observation and you want to add media files to it: Make sure the observation is open on your screen. Choose Observe > Video (or Audio) > Open in Current Observation. Alternatively, click the Import Video or Import Audio button on the toolbar. Browse to the video/audio files and click Open. Export Observational Data You can export observations to The Observer XT files (*.odx format), to Microsoft Excel format (*.xlsx format), or to text files. Choose File > Export > Observational Data. Choose the observations to export. If you want to export only one observation, open the observation and click the Export Current Observation button on the toolbar. Carry Out Observations with External Programs What Is an External Program? In The Observer XT, an external program is software that you can use in combination with The Observer XT to record additional data. For example, MediaRecorder controlled with The Observer XT to automatically start and stop video recording together with an observation and import the videos into the observation. How to Carry Out Observations with External Programs Carry out an observation in the usual way. The external program starts and stops together with the observation, according to the settings you specified for the external program. Score Data after Importing External Data - Create a new observation. - Import the external data. - If necessary, synchronize the external data files with the (still empty) Event Log file by adjusting the Offset. - Start the observation and score data. Find Events Aim To find events, or free text entered in the Event Log's Comment column. You can export these events or copy and paste them to another program. Prerequisites - You carried out at least one observation. - One of your observations is open. Procedure - Press Ctrl+F or click the Find Events in the Selected Observations button. - Specify the criteria by choosing options from the lists and click Find. For subjects and behaviors, you can either choose Any, or a specific one. Notes on Comments - To search for an event containing specific text in the Event Log's Comment column, enter this text in the Comments field. - To search for a specific sequence of words, type the words between quotes, for example "Where is the puppet?". - To search for a word OR another, type those words without quotes, for example: chalk shoe. Modifiers If you select modifiers in two or multiple groups, the program searches for events which contain any of these modifiers. For example, if you select Play Alone for the modifier group Play Mode and Play Imaginary for the group Play Type, all events containing either Play Alone or Play Imaginary are found. Numerical Modifiers - To search for events with a specific value of the modifier, unfold the Modifier group item, choose Exact Value and enter that value. - To search for events with multiple values, unfold the Modifier group item, select Range and enter the limits. Customize the Found Events - Click a column header to sort the events. - To show or hide columns, right-click a column header, choose Show Column and make your selection. - If you have start-stop groups in your coding scheme, you can hide stop events in the Find window by selecting Hide Stop Events. This is useful if you want to export the list of events and use those data in a statistical package. - To reset the search criteria, click Reset. Export the Found Events - To export all events, click the Export All Events button in the bottom-right corner of the Find window. - To export a selection of events, make your selection and click the Export Selected Events button. - You can also copy events and paste them into another program like Excel. Notes - You cannot use Find in another part of the program other than the observation, for example when an Event Plot or Analysis Result is open. - You cannot make a selection of some subjects or behaviors and not others. If this is what you want, create a Data Profile instead. See Select Data for Analysis. - You cannot use wildcards like * or ?. The Observer XT will search for events containing those characters. The Observation Screen - Choose the windows to view - Position and resize the windows on the screen - The Timers window - The Codes window - The Event Log window - The Data and Audio Visualization window - The Playback Control window - The Videos window --- ## The Observer XT 17 - Carry Out an Observation - Carry Out an Observation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-carry-out-an-observation Chapter: The Observer XT Carry Out an Observation Overview Carrying out an observation involves the following steps: - Create an observation and (for offline observations only) load the videos. - Position the video (offline observations only). - Choose the active states at observation start (mutually exclusive and exhaustive behavior groups only). - Start the observation. - Score data. - Stop the observation. Create an Observation Aim To create an empty worksheet for event logging, called an Event Log. Prerequisite You followed the procedure in Set Up Your Project. Procedure - Choose Observe > Observation > New. - Optionally, enter an observation name and add a description. - Live observation – Optionally, select devices in the Devices tab (see Control External Devices or Programs during a Live Observation in Set Up Your Project). Click OK. Offline observation – The Devices tab is grayed out. Click OK. - Offline observation only – Select your video. To visualize the audio of a video file as a waveform, select Visualize Audio. See Visualize Audio Waveforms from a Video File. To code from audio files without video, close the Select Videos window and click the Import Audio button on the toolbar. Select the audio file and click OK. Modifying Observation or Event Log Name and Description - For observations – In the Project Explorer, open the Observations folder, right-click the observation and select Properties. For event logs – In the Project Explorer, open the Observations folder, unfold the observation and then the Event Files item. Right-click the event log and select Properties. - Edit the name of the observation or event log and description, then click OK. Position the Video Aim To choose the moment in the videos where you want to start scoring. This is needed for offline observations only. Prerequisites - You chose Offline Observation as the observation source. - You created an observation and selected the videos. Procedure Move the playback slider to where you want to start scoring. Use the playback buttons for fine positioning. See The Playback Control Window. If you do not see the Playback Control window, choose View Settings > Show Window > Playback Control. Choose the Active States at Observation Start Aim To make sure the correct events are scored at the start of the observation. This is only needed if you have mutually exclusive and exhaustive behavior groups. Prerequisites - You defined a mutually exclusive and exhaustive behavior group in your coding scheme. - You created an observation. Procedure - If you defined a mutually exclusive and exhaustive behavior group in your coding scheme, Initial State events appear in your event log and Data and Audio Visualization window when you create an observation. Check that the states are correct. The Initial State events run from time 0 until the end of the video. When you work live, the Initial State events have a duration of 15 minutes. The duration will be corrected as soon as you start coding. - If an Initial State event is not correct, select the cell and score the correct event behavior by pressing the key code. This behavior is now recorded at time 0. For example, if the initial state event in the mutually exclusive and exhaustive group Playing is Not Playing, and you notice the child is playing with a toy, code the behavior Play Toy before you start the observation. - If the initial state events are linked to one or more modifiers that must be scored, score the modifiers as well. See Define Modifier (Group) Properties in Set Up Your Project. - Repeat the steps above for all initial state events. Start the Observation Procedure - Click the Start Observation button. - If you have defined independent variables in your project setup and chose to edit them before the observation, enter the values in the window that appears. You can skip values that are not compulsory. See Value Update in Set Up Your Project. - Score your data. For the general procedure, see Score Data. For detailed procedures, see Continuous Sampling, Instantaneous Sampling, and Continuous and Instantaneous Sampling. To pause a live observation, see Suspend an Observation. Score Data Aim To carry out an observation. Prerequisites You created and started an observation. Procedure Score the subjects, behaviors, and their modifiers by typing the predefined key code or by clicking the key code in the Codes window. Typing key codes is generally faster. What you have scored appears in the Event Log window and is visualized in the Data and Audio Visualization window. Each row in the event log corresponds to one event. You can also type free text in the Comment column and press Enter. See Enter Events as Free Text. Scoring Order For each event line, score the subject first, then the behavior, and then the modifiers linked to that behavior. Score subjects and modifiers only if they are defined in your coding scheme. The Codes window displays which element should be scored next. Event Log Symbols - The start of an event with duration (state event). - The stop of an event with duration (state event). - The start of an event in a mutually exclusive and exhaustive group. The state is active from that moment and the previous state is no longer active. - An event without duration (point event). - An instantaneous sample event. Notes - When you save the project, the Event Log file is saved in the Event Data subfolder within your regular project folder. - Make sure that the time before your computer goes into standby mode or hibernation is set to longer than the longest likely interval between scored events. To specify the interval, in the Control Panel choose Power Options, click Change When the Computer Goes to Sleep, and make your selection. --- ## The Observer XT 17 - Carry Out an Observation - Change the Observation's Start Time and Duration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-change-the-observations-start-time-and-duration Chapter: The Observer XT Change the Observation's Start Time and Duration By default, the Start time and Stop time of an observation are the earliest Start time and the latest Stop time of any data set in that observation. You find those times in the Independent Variable List (choose Setup > Independent Variables). If you want to exclude a section at the beginning of the observation, or if you stopped the observation too early, you need to change the start or stop time. You can change the start time and duration. The stop time is determined automatically from the start time and the duration. Changing the Start Time and/or Duration of an observation does not move Event Logs, Video, Audio and External Data files. If, for example, you reduce the Start time (that is, you move the Start to the left), the files belonging to that observation are not moved accordingly. This results in a larger gap between the Start time and the start of the files. Procedure - Choose Setup > Independent Variables. - Choose View Settings > Show Independent Variables and select Start Time, Stop Time and Duration. - Edit the Start Time or Duration cell. Notes: - Changing the observation start time or duration does not affect synchronization between individual files, meaning the start time of one file relative to others. To change the synchronization between files, see Synchronize Data Sets. - The observation Stop time is changed automatically according to the changes in the observation start time and duration, and cannot be edited. Events that are recorded before the start time or after the stop time of the observation are shown in gray in the Event Log. Edit the Coding Scheme Add an Element to the Coding Scheme It may happen that you observe something that does not comply with any element in your coding scheme. You can add new elements (Subjects, Behaviors, Modifiers) or element groups (Behavior and Modifier groups) in two ways: - Method 1 (best for offline observations, and for extensive changes to the coding scheme): Stop the observation, re-open the coding scheme (Setup > Open Coding Scheme) and add the new element, then re-open and start the observation. - Method 2 (for both live and offline observations, and for limited changes to the coding scheme): Add the new element while you are observing and score that element immediately. See Add a Coding Scheme Element While Observing. Add a Coding Scheme Element While Observing - If you are carrying out an observation from video or audio, pause the video or audio file first. - In the Codes window, click the tab you want to add an element to. For example, if you want to add a behavior, choose Behaviors. - Choose one of the options at the bottom of the Codes window. Add a Subject - Enter the name of the new subject and its keycode, or accept the suggested code. - Click Add. Add a Behavior - From the Add to Group list, select the behavior group that you want the new behavior to be part of. - Enter the name and the keycodes for the new behavior, or accept the suggested ones. - From the Type list, select whether the new behavior is a Point Event, a State Event or an Initial State Event. See Behavior Types in Set Up Your Project. - In the Link To box, select the modifier groups you want to associate with the behavior. - Click Add. Add a Behavior Group When your observation method is Instantaneous Sampling, you cannot add a behavior group. To add a behavior group for continuous sampling: - Enter a name in the Group Name field. - Choose whether the behaviors in the group can or cannot occur at the same time. See Behavior Group Types in Set Up Your Project. - Enter the behaviors and, for each behavior, choose whether it has duration or not. See Behavior Types in Set Up Your Project. Add a Modifier - Select the group to which the new modifier belongs. If the modifier does not belong to any existing group, create a new group first (see below). - Enter a Value and Keycode. - Click Add. Add a Modifier Group - In the Add Modifier Group window, choose a Nominal or Numerical group. See Modifier Group Types in Set Up Your Project for the difference. - Enter a name and all modifiers. - In the Link to Behaviors box, select the behaviors that you want to associate with the modifier group, then click Create Group. Notes: - Remember to also define connections between subjects and behaviors and between behaviors and modifiers. - If the configuration is locked (see Lock the Project Setup in Set Up Your Project), it is not possible to add new elements to the coding scheme. - In the Codes window, you can add new elements to your coding scheme, but not modify or delete existing ones. To modify or delete existing elements, open the coding scheme. Edit a Coding Scheme Element After Observing - Stop the observation. - Open the coding scheme (choose Setup > Open Coding Scheme). - Click the element. - To change the element, choose Properties at the bottom of the screen to open the Properties pane. Modify the element properties (see Create Coding Scheme in Set Up Your Project for details). To delete the element, press Ctrl+Delete. - Re-open the observation and resume scoring. If at least one of the observations contains the element you want to delete, the program inactivates it instead. The element is still present in your data, so you can analyze it. --- ## The Observer XT 17 - Carry Out an Observation - Check the Event Log for Errors URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-check-the-event-log-for-errors Chapter: The Observer XT Check the Event Log for Errors Aim To check you scored your observation correctly so that you can analyze it. Background Errors in an event log may occur when, for example, you edited the event log and accidentally removed start codes but not the associated stop codes, or when you did not score all compulsory modifiers. Event logs with errors cannot be visualized or analyzed. Procedure - Click the Check Event Log button on the Observation toolbar. - The Check Observation window opens with a list of the errors. - Do one of the following: - Correct event log errors automatically - Correct event log errors manually How Event Log Errors Are Indicated - An observation that contains an event log with errors has a warning sign next to its name in the Project Explorer. - The event rows with errors are highlighted in red. Hover with the mouse over a row for details of the error. Correct Event Log Errors Automatically Aim To let The Observer XT automatically correct event log errors. Errors That Can Be Corrected Automatically - Missing stop codes – These will be added. - Stop codes without a corresponding start code – These will be deleted. - Gaps in a mutually exclusive and exhaustive behavior group – These will be corrected. If no initial state event was scored, it will be added. If there is a gap further on in the event log, it will be corrected by extending the behavior that was active before the gap. - Missing combinations – If you removed combinations between subjects and behaviors or behaviors and modifiers in your coding scheme while these have been scored in an observation, the events with these combinations will be deleted. Procedure - Click the Check Event Log button on the Observation toolbar. - The Check Observation window opens with a list of the errors. Click the Fix Errors Automatically button. Notes - If you have multiple event logs within one observation, the event log checker checks for errors between all event logs, for example whether there are overlapping events. Such errors cannot be fixed automatically. - If you find many errors in the event log, this could be caused by an accidental change in the coding scheme, such as the removal of a subject-behavior combination. See Define Subject Properties. Correct Event Log Errors Manually Important: Always make a backup of your project before editing data. See Create a Backup of a Project. Replace an Element in the Event Log - Click its cell in the Event Log and then score the correct element. Delete an Element in the Event Log - Click its cell in the Event Log and press Delete. Add an Element to a Scored Event Example: Add one more Modifier Value to the Behavior 'Initiate Play'. - Click the cell where you want to add the element. The Codes window displays the elements that you can add in that cell. - Either type in the keycode for the new element or click the code in the Codes window. The new modifier is added in a new cell that was inserted under the cell you wanted to edit. Add a New Event Row in the Event Log Example: To add an event between the event scored at 1.72 and the event scored at 4.36. - Click the row immediately above where you want the new row (in this example, the header of the row with 1.72). - Click the Insert Event button on the toolbar. Alternatively, right-click in the event row and select Insert Event Above or Insert Event Below. A new empty event is added below the selected row with the same timestamp as the selected row. - Score the data as usual. If necessary, change the timestamp (see Change the Time of a Scored Event). If you score events from a video file, you can also insert a line as follows: - Position the video to the moment where the event occurs. - Score the event as usual. The new event line is inserted between two existing lines. Remove Event Rows from the Event Log - Click the left-most cell of the row or rows you want to delete. The entire row is highlighted in black. - Click the Delete Event button on the toolbar. Change the Time of a Scored Event Example: You scored an event slightly later or earlier than the actual time. Instead of deleting and re-scoring the event, change the time of the existing record. - Locate the event line you want to change and double-click the cell in the Event Time column. The time cell is highlighted in blue. - Click the number you want to change and type the new time, or use the two arrow buttons to adjust its value. - Press Enter. - Tip: Alternatively, use the Update Time option. Click the left cell of the event line to select it, move the video or audio to the correct time, and press Ctrl+T to update the timestamp in the Event Log. You can also right-click the row and select Update Time. - The new timestamp cannot be earlier or later than the timestamp of the previous or next event from the same Behavior group. --- ## The Observer XT 17 - Carry Out an Observation - Choose the Windows to View URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-choose-the-windows-to-view Chapter: The Observer XT Choose the Windows to View Procedure - Click View Settings in the upper-right corner of your toolbar. - Select the objects you want to view during the observation. Event Log Options - To view Subjects, Behaviors, Modifiers or Comments in your Event Log. Video Files Options - To select which video files to view. External Data and Audio Options - Visualization Window — To view the Data and Audio Visualization window plotting external data, events and audio. - Show External Data — Select which External Data streams you want to view. - Show Audio — To visualize audio files or the audio of your video files. - Data Points — To display data points in external data or audio graphs. Event Visualization Options - Visualization Window — To view the Data and Audio Visualization window showing your scored events and audio on the timeline. - Show Time-Event Plot — Select which subjects to view in the Data and Audio Visualization window. - Show Comments — To view the comments that you entered during scoring on the timeline in the Data and Audio Visualization window. Show Window Options - Codes — To view the Codes window, which you can use to score data with mouse clicks. - Playback Control — To view the Playback Control window. - Comment — To view the Comment window. See Enter Events as Free Text. - Timers — To view the Timers window with the absolute and relative time while scoring. See The Timers Window. - N-Linx Data Transfer — To view feedback information about ongoing co-acquisition of external data. This window is available if you score data live and co-acquire FaceReader data or Biopac data. Each row in the table represents one channel. The Data column shows the channel name. The Messages column shows the number of samples recorded up to that time. - Time Formats — To change the format of your time stamps in the Event Log. To undock the View Settings window, click the dots under the header View Settings, then drag the window to a new location. Position and Resize the Windows on the Screen Move a Window - Click the title bar and drag it to the new position. Docking icons appear to show you where you can position the undocked window. - Hover with your window over one of the docking icons. The new position of the window is shown in blue. - Release the window. The window is positioned at the chosen location. Resize a Window - Hover with the mouse on one of its margins until the cursor changes to the resize symbol. - Drag the margin to adjust the window size. The Timers Window The Timers window can display the following information: - Observation - Current Time: The current, absolute time during an observation. When you stop the observation, this timer shows the Event Log - Stop Time and no longer runs. - Observation - Elapsed Time: The elapsed, relative time during an observation. - Observation - Observed Time: The observed, relative time during an observation. This counter pauses when you suspend an observation and starts again when you resume. - Observation - Remaining Time: The remaining, relative time in the observation. If you have defined a Maximum Duration for the observation, this is the time left. Note that Observation - Remaining Time + Observation Elapsed Time in the event log may not exactly equal the Event Log - Stop Time due to rounding of decimals. - Observation - Start Time: The minimum start time of all data sets in the current observation. If you score data from one media file, this is usually 00:00:00.000. If two or more media files are opened and not all synchronized on the first frame, this shows the time of the earliest media file when the latest media file is positioned on zero. - Observation - Stop Time: The maximum end time of all data sets in the current observation. If two or more media files are opened, it shows the end time of the longest media file. - Event Log - Start Time: The minimum start time of the current event log in the observation. - Event Log - Stop Time: The maximum end time of the current event log in the observation. - Interval - Elapsed Time (hidden by default): For instantaneous sampling; shows the elapsed time since the previous interval. To show this timer, right-click the Timers window and select Interval - Elapsed Time. - Interval - Remaining Time (hidden by default): For instantaneous sampling; shows the time until the next interval. To show this timer, right-click the Timers window and select Interval - Remaining Time. Customize the Timers Window - To change the time formats, choose Setup > Project Settings > Time Formats. - To hide or show a timer, right-click in the Timers window and deselect or select the timer. The Codes Window The Codes window displays the elements of the coding scheme and their properties. The Codes window contains three tabs: - Subjects: Lists the subjects and their code under Start. If one or more state events are active for a certain subject, these are shown under Status, separated by a comma. - Behaviors: Lists the behaviors and their start and stop code under Start and Stop. Behaviors in a mutually exclusive and exhaustive behavior group only have a code under Start. If a state behavior is active for one or more subjects, the Status column shows those subjects separated by a comma. - Modifier: Lists the modifiers and their code under Start. If state behaviors are active for a certain subject, these are shown under Status, separated by a comma. --- ## The Observer XT 17 - Carry Out an Observation - Continuous and Instantaneous Sampling URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-continuous-and-instantaneous-sampling Chapter: The Observer XT Continuous and Instantaneous Sampling Aim To code your observation with a combination of Continuous and Instantaneous sampling. Prerequisites - You created and started an observation. - You chose Combine Continuous and Instantaneous Sampling as the Observation method. Procedure - As soon as the observation is started, the first cell in the Instantaneous sample block is selected. Score this sample according to the general procedure for Instantaneous Sampling. - As soon as you finish scoring the Instantaneous sample, Continuous sampling starts and you can score data for the subjects you follow continuously. Follow the procedure described in Continuous Sampling. Notes on Continuous and Instantaneous Sampling - What do I do when I score live and my focal subject changes behavior while I am scoring the Instantaneous sample? – Click the row under Instantaneous Sample (#) End and score the behavior for the focal subject. Next, click a row in the Instantaneous sample block to continue Instantaneous Sampling. - When your observation duration is a multiple of the sample interval (see Specify the Duration of the Observation), no sample is scored at the end of the observation. If you do want to score this sample, make the observation for example 1 second longer. Also an event scored with continuous sampling at the exact moment the observation stops is not included in the analysis. - When a new sample starts before you have finished scoring a continuous event, you are asked whether you want to finish or discard the event before scoring the sample. This is, for example, the case when you have not yet scored a required modifier. How To… Edit the Observation - Check the event log for errors - Correct Event Log errors automatically - Correct Event Log errors manually - Synchronize data sets - Change the observation's start time and duration Edit the Coding Scheme - Add an element to the coding scheme - Edit a coding scheme element after observing Miscellaneous Coding Actions - Undo coding actions - Enter events as free text - Submit an incomplete event - Score action-reaction data (triggering behavior) - Score reciprocal behavior - Suspend an observation Advanced Observations - Carry out observations with external programs - Import data into an observation - Score data after importing external data - Export observational data - Find Events Check the Event Log for Errors Aim To check you scored your observation correctly so that you can analyze it. Background Errors in an event log may occur when, for example, you edited the Event Log and accidentally removed start codes but not the associated stop codes, or when you did not score all compulsory modifiers. Event logs with errors cannot be visualized or analyzed. Procedure - Click the Check Event Log button on the Observation toolbar. - The Check Observation window opens with a list of the errors. - Now do one of the following: - Correct Event Log errors automatically - Correct Event Log errors manually How Event Log Errors Are Indicated An observation that contains an event log with errors has a warning sign next to its name in the Project Explorer. The event rows with errors are highlighted in red. Hover with the mouse over a row for details of the error. See Correct Event Log Errors Manually. Correct Event Log Errors Automatically Aim To let The Observer XT automatically correct the following errors: - Missing stop codes – These will be added. - Stop codes without corresponding start code – These will be deleted. - Gaps in a mutually exclusive and exhaustive behavior group – These will be corrected. If no Initial State event (see Behavior Types) was scored, it will be added. If there is a gap further on in the event log, it will be corrected by extending the behavior that was active before the gap. - Missing combinations – You may have removed combinations between subjects and behaviors or behaviors and modifiers in your Coding Scheme, while these have been scored in an observation. The events with these combinations will be deleted. Procedure - Click the Check Event Log button on the Observation toolbar. - The Check Observation window opens with a list of the errors. Click the Fix Errors Automatically button. Notes - If you have multiple event logs within one observation, the event log checker checks for errors between all event logs, for example whether there are overlapping events in the event logs. Such errors cannot be fixed automatically. - If you find many errors in the event log, that could be caused by some accidental change in the coding scheme, for example the removal of a subject-behavior combination. See Define Subject Properties. --- ## The Observer XT 17 - Carry Out an Observation - Correct Event Log Errors Manually URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-correct-event-log-errors-manually Chapter: The Observer XT Correct Event Log Errors Manually IMPORTANT: Always make a backup of your project before editing data. See Create a Backup of a Project. What do you want to do? - Replace an element in the Event Log - Delete an element in the Event Log - Add an element to a scored event - Add a new event row in the Event Log - Remove event rows from the Event Log - Change the time of a scored event Replace an Element in the Event Log Click its cell in the Event Log and then score the correct element. Delete an Element in the Event Log Click its cell in the Event Log and press Delete. Add an Element to a Scored Event Example: Add one more Modifier Value to the Behavior 'Initiate Play'. - Click the cell where you want to add the element. The Codes window displays the elements that you can add in that cell. - Either type in the keycode for the new element or click the code in the Codes window. Result: The new modifier is added in a new cell that was inserted under the cell you wanted to edit. Add a New Event Row in the Event Log Example: To add an event between the event scored at 1.72 and the event scored at 4.36. - Click the row immediately above where you want the new row (in the example above, the header of the row with 1.72). - Click the Insert Event button on the toolbar. Alternatively, right-click in the event row and select Insert Event Above or Insert Event Below. Result: A new empty event is added below the selected row. The time stamp is the same as that of the selected row. - Score the data as usual. If necessary, change the time stamp (see below). If you score events from a video file, it is also possible to insert a line in the following way: - Position the video to the moment where the event occurs. - Score the event as usual. The new event line is inserted between two existing lines. Remove Event Rows from the Event Log - Click the left-most cell of the row or rows you want to delete. Result: The entire row is highlighted in black. - Click the Delete Event button on the toolbar. Change the Time of a Scored Event Example: You have scored an event slightly later (or earlier) than the real time. Instead of deleting the event and re-scoring it at the right time, change the time of the existing record. - Locate the event line you want to change and double-click the cell in the Event Time column. Result: The time cell is highlighted in blue. - Click the number you want to change and type the new time, or use the two arrow buttons to adjust its value. - Press Enter. Tip: Alternatively, use the option Update Time. Click the left cell of the event line to select the line, move the video or audio to the correct time, and press Ctrl+T to update the time in the Event Log to the correct timestamp. Alternatively, right-click the row and select Update Time. The new timestamp cannot be earlier or later than the timestamp of the previous or next event from the same Behavior group. Synchronize Data Sets Aim To change the Start time of a data set (Event Log, Video, Audio, External Data) relative to others. Example 1: You started video recording with one camera 30 seconds earlier than with the other camera. Before you start observing, you want to synchronize the video files. Example 2: After the observation, you imported associated physiological data. You want to synchronize the physiological data with the events. Prerequisite An event can be recognized in all streams to synchronize. For example, you type a key that is assigned to a behavior in the Coding Scheme and record that on video. The key press will appear in the Event Log and will be visible in the video as well. When you record external data and you cannot use automatic synchronization (see External Data), the event can be recognized in the external data as well. For example, you counted down aloud until you pressed the start button on the external data system and you recorded this on video. Procedure - Open an existing observation, and make sure that the video, audio and external data linked to the observation are visible on your screen. If a data set is not shown on your screen, click View Settings on the far-right side of the toolbar and select that option. - You can synchronize data sets in two ways: numerically, by typing in the offset value, or manually, by moving the slider of the video file or dragging the visual presentation of the data set. See Numerical Offset and Manual Offset below. Numerical Offset - Click the Offset button on the Component toolbar, then choose Numerical Offset. Result: The File Synchronization window appears. This window lists the event log currently open, the video and audio files, and the external data linked to it. - Locate the data set (event, video, audio or external data) of which you want to change the start time relative to others, and click the Offset cell. - Enter the offset value. Example: If your event log starts 20 seconds after the video file, locate the row of the video file and enter -20 in the seconds group of the Offset column. - Click Apply. Manual Offset - Click the Offset button on the Component toolbar, then choose Manual Offset. Result: The Synchronize window appears explaining the next three steps. Click Start Synchronization. - Click the window with the data you want to synchronize. Result: A red border appears around the window. You can now alter the time in this window while the time in the other windows remains fixed. - For video or audio, use the Playback Control buttons to play the media file to the new position. For external data, click the window and move the data stream with the cursor to the new position. The aim is to position the video, audio, or external data to the matching event in the Event Log. - Click the Offset button again. Result: The red border disappears. The files are now synchronized as you have specified. Notes: - If you use MediaRecorder 4 or higher to record video, the video files are automatically synchronized with your observation. - You can use the File Synchronization window (see Numerical Offset) to check that the time difference between video, audio, event log and other data streams is correct. You can change this difference at any time. --- ## The Observer XT 17 - Carry Out an Observation - Edit the Coding Scheme URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-edit-the-coding-scheme Chapter: The Observer XT Edit the Coding Scheme Add an Element to the Coding Scheme If you observe something that does not match any element in your coding scheme, you can add new elements (Subjects, Behaviors, Modifiers) or element groups (Behavior and Modifier groups) in two ways: - Method 1 (best for offline observations and extensive changes): Stop the observation, re-open the coding scheme via Setup > Open Coding Scheme, add the new element, then re-open and start the observation. - Method 2 (for both live and offline observations with limited changes): Add the new element while observing and score it immediately. See Add a Coding Scheme Element While Observing. Add a Coding Scheme Element While Observing - If carrying out an observation from video or audio, pause the file first. - In the Codes window, click the tab you want to add an element to. For example, to add a behavior, choose Behaviors. - Choose one of the options at the bottom of the Codes window. Add a Subject - Enter the name of the new subject and its keycode, or accept the suggested code. - Click Add. Add a Behavior - From the Add to Group list, select the behavior group that the new behavior should belong to. - Enter the name and keycodes for the new behavior, or accept the suggested ones. - From the Type list, select whether the new behavior is a Point Event, a State Event, or an Initial State Event. See Behavior Types in Set Up Your Project. - In the Link To box, select the modifier groups you want to associate with the behavior. - Click Add. Add a Behavior Group When your observation method is Instantaneous Sampling, you cannot add a behavior group. To add a behavior group for continuous sampling: - Enter a name in the Group Name field. - Choose whether the behaviors in the group can or cannot occur at the same time. See Behavior Group Types in Set Up Your Project. - Enter the behaviors and, for each behavior, choose whether it has duration or not. See Behavior Types in Set Up Your Project. Add a Modifier - Select the group to which the new modifier belongs. If the modifier does not belong to any existing group, create a new group first. - Enter a Value and Keycode. - Click Add. Add a Modifier Group - In the Add Modifier Group window, choose a Nominal or Numerical group. See Modifier Group Types in Set Up Your Project for the difference. - Enter a name and all modifiers. - In the Link to Behaviors box, select the behaviors you want to associate with the modifier group, then click Create Group. Notes - Remember to also define connections between subjects and behaviors, and between behaviors and modifiers. - If the configuration is locked (see Lock the Project Setup in Set Up Your Project), it is not possible to add new elements to the coding scheme. - In the Codes window, you can add new elements to your coding scheme but cannot modify or delete existing ones. To modify or delete existing elements, open the coding scheme. Edit a Coding Scheme Element After Observing - Stop the observation. - Open the coding scheme by choosing Setup > Open Coding Scheme. - Click the element. - To change the element, choose Properties at the bottom of the screen to open the Properties pane and modify the element properties. See Create Coding Scheme in Set Up Your Project for details. To delete the element, press Ctrl+Delete. - Re-open the observation and resume scoring. - If at least one observation contains the element you want to delete, the program inactivates it instead. The element remains present in your data so it can still be analyzed. --- ## The Observer XT 17 - Carry Out an Observation - Instantaneous Sampling URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-instantaneous-sampling Chapter: The Observer XT Instantaneous Sampling Aim To code your observation with instantaneous sampling. Prerequisites - You created and started an observation. - You chose Instantaneous Sampling as the observation method. Procedure - A sound signal is given at the observation start. The Event Log shows all subjects from the Instantaneous Sampling subject group at time 0. It also shows the behavior groups that are linked to the subjects and must be scored in gray. When you carry out an offline observation, the video file pauses until you have scored all subjects, irrespective of whether you selected the option Pause Playback When Scoring an Event in the Project Settings. The Codes window shows the current subject-behavior combination in the Status column and the behavior group that needs to be scored. - Score a behavior for each subject. As soon as the behavior is scored it appears in the event log. - If the behavior was linked to one or more modifiers, the modifier cell will be selected. The Codes window now shows all the modifiers that can be attached to the scored behavior. Score the modifier. The modifier appears in the event log. - If you have selected Add Comment in the Properties pane of the subject or the behavior you have just scored, the Comment cell will be selected with the word Comment in gray. Enter a comment and press Enter. If you do not want to add a comment, just press Enter. The event is now complete. - Add new events by repeating the steps above to finish scoring the complete sample. - Live – Wait until the sample interval has elapsed to score the next sample, indicated by a sound signal. - Offline – Click the Next Sample button to position the video at the time of the next sample. What's Next - To stop the observation, see Stop the Observation. - To correct scoring errors, see Correct Event Log Errors Manually. - For more information, see the Notes on Instantaneous Sampling and How To procedures. Notes on Instantaneous Sampling Timers - The Timers window displays the Remaining Interval Time. - Live – The timer counts down until the next instantaneous sample. - Offline – The timer displays the sample interval length. - If no Timers window is visible, choose View Settings > Show Window > Timers. You can drag the Timers window to below or next to the Event Log so you can easily see how much time is left until the next sample. To hide specific timers, right-click in the Timers window and deselect the timer. Subjects - Subjects in an instantaneous sample block appear in the order they are placed in the coding scheme. Click the behavior cell of another subject to score in a different order. Modifiers - If modifiers are not required, you can skip them and go to the Comment column or start a new event line by pressing Enter. Comments - If you do not want the Comment cell to be selected every time you score an event, make sure that for all behaviors and subjects the Add Comment option is not selected. See Define Subject Properties and Define Modifier (Group) Properties in Set Up Your Project. Samples - When the next sample begins before you finished scoring the previous sample, which only occurs in a live observation, the non-scored events are set to missing. - When your observation duration is a multiple of the sample interval, no sample is scored at the end of the observation. If you do want to score this sample, make the observation for example one second longer. Continuous and Instantaneous Sampling Aim To code your observation with a combination of continuous and instantaneous sampling. Prerequisites - You created and started an observation. - You chose Combine Continuous and Instantaneous Sampling as the observation method. Procedure - As soon as the observation is started, the first cell in the instantaneous sample block is selected. Score this sample according to the general procedure for Instantaneous Sampling. - As soon as you finish scoring the instantaneous sample, continuous sampling starts and you can score data for the subjects you follow continuously. Follow the procedure described in Continuous Sampling. Notes on Continuous and Instantaneous Sampling - If you score live and your focal subject changes behavior while you are scoring the instantaneous sample, click the row under Instantaneous Sample End and score the behavior for the focal subject. Next, click a row in the instantaneous sample block to continue instantaneous sampling. - When your observation duration is a multiple of the sample interval, no sample is scored at the end of the observation. If you do want to score this sample, make the observation for example one second longer. An event scored with continuous sampling at the exact moment the observation stops is also not included in the analysis. - When a new sample starts before you have finished scoring a continuous event, you are asked whether you want to finish or discard the event before scoring the sample. This occurs, for example, when you have not yet scored a required modifier. How To Edit and Correct Observations Available Procedures - Check the event log for errors - Correct event log errors automatically - Correct event log errors manually - Synchronize data sets - Change the observation's start time and duration - Add an element to the coding scheme - Edit a coding scheme element after observing - Undo coding actions - Enter events as free text - Submit an incomplete event - Score action-reaction data (triggering behavior) - Score reciprocal behavior - Suspend an observation - Carry out observations with external programs - Import data into an observation - Score data after importing external data - Export observational data - Find events --- ## The Observer XT 17 - Carry Out an Observation - Miscellaneous Coding Actions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-miscellaneous-coding-actions Chapter: The Observer XT Miscellaneous Coding Actions Undo Coding Actions Example: You have coded the first element of an event. You realize that the event should not be scored, so you want to cancel that action. - When recording: Click the Undo button on the toolbar. To make a correction undone, press the Redo button. - When you inserted an incorrect event between two existing events: Select the event line and click the Delete Event button on the toolbar. Alternatively, right-click in the first column of the event you want to remove and select Delete event(s). Enter Events as Free Text Log free text in the Comment column or choose View Settings > Show Window > Comment and type the text in the window that appears. You can also paste text that was copied from another source. You can enter maximally 1024 characters per event. Enter Text Associated with a Scored Event Score the event as usual, then click the Comment cell in that row and type the text. Enter Text Only - To enter a new line of text only, press Ctrl+I or click the Insert Event button on the toolbar. - Click the Comment cell for the new line and enter the text. The time stamp of an event line that only includes a comment is the time when you type the first character in the Comment column. Notes on Comments - Comments are not visualized in the time-event plot if they are not associated with an event. To visualize comment-only events, create a dummy behavior in the coding scheme and score that behavior in the row of the comment. - To annotate only free text, hide the Subject, Behavior, and Modifier columns in the event log. - You cannot analyze free text, but you can use the Find function to find text across all observations, including the number of events that contain a certain word or phrase. - To type text while listening to audio to transcribe speech, choose Setup > Project Settings > Scoring Options and de-select Pause Playback of Video When Scoring an Event. - If you want to be reminded to add comments, open the properties for that element and select the option Add a Comment. - Pressing Enter does not separate text lines within the same comment; it enters the comment in the event log. To keep two or more lines of text separated, create multiple event lines. Submit an Incomplete Event If an event is made of several elements (for example, Subject, Behavior, and three Modifiers), The Observer XT checks that all the required elements are scored. You can allow incomplete events, for example if you score instantaneous samples and some subjects are not visible. Choose Setup > Project Settings > Scoring Options > Always Press Enter to Confirm Event Line. To submit an incomplete event, press Enter. Score Action-Reaction Data (Triggering Behavior) Aim To score data in a sequence like the following: Subject 1 - Behavior A - Subject 2 - Behavior B, where Subject 2 performs Behavior B as a response to Behavior A by Subject 1. Procedure - Define a group of modifiers containing all subjects reacting (like Subject 2 in the example). - Define a group of modifiers containing all response behaviors (like Behavior B). - Score the data in sequence: Subject - Behavior - Modifier of first group - Modifier of second group. Score Reciprocal Behavior Aim To score behavior that has no specific direction, for example Mark Plays with James. Procedure - Define both Mark and James as both subjects and modifiers. - Define Play as Behavior. - Score two event lines: Mark - Plays - James and James - Plays - Mark. - If necessary, pause the video or edit the time in the event log afterwards to ensure the events get the same time stamp. Suspend an Observation Aim To temporarily stop observing, for example when a subject is out of view. The currently active states for all subjects are stopped. The Observer XT is put in standby awaiting that you resume the observation. Prerequisite You chose Live Observation as Observation Source. You cannot suspend when you score offline from prerecorded video. Procedure - Choose Observe > Suspend Observation. Alternatively, click the Suspend Observation button. - In the Timers window, the Observation - Observed Time timer stops and the Observation - Elapsed Time timer continues. - In the Event Log, two lines are added: Suspend (marked by the time when the observation was suspended) and Resume (with no time yet). For each state that was active at the time the observation was suspended, the program adds a row below the Resume row. The program assumes that those states are active when you resume the observation. You can change these states immediately before or after you resume the observation if the subjects have changed state in the meantime, or confirm them and resume the observation. - Example for mutually exclusive behaviors: In a chimpanzee study, the observation was suspended at 17:07 when the subject went out of sight. At that time, the states Walk and No Consumption of two different mutually exclusive behavior groups were active. After the line Resume, the start events for those states are added automatically. - Example for Start-Stop behaviors: The observation was suspended at 17.79. Before the line Suspend, stop codes are added for the active behaviors. Below the line Resume, two start codes are added for the behaviors that were active at the moment the observation was suspended. - When your subject comes back into view or when you are ready to resume, update the behaviors in the lines below the Resume line. If the states do not need to be updated, go to the next step. To update the behaviors, click the cell you want to update and score the new state. - To resume the observation, choose Observe > Resume Observation or click the Resume Observation button. - Continue scoring data as usual. Notes - The time period between suspending and resuming an observation is not considered for analysis. - You cannot suspend Instantaneous Sampling. If you use both Continuous and Instantaneous Sampling, when you suspend the observation, only Continuous Sampling is suspended. - Start codes cannot be changed into stop codes since this would lead to errors in the Event Log. --- ## The Observer XT 17 - Carry Out an Observation - Observations with Multiple Event Logs URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-observations-with-multiple-event-logs Chapter: The Observer XT Observations with Multiple Event Logs Observations and Event Logs While you carry out an observation, events and comments are logged in what is called an Event Log. The data from your whole observation are stored in one event log. If you import event data from an external program, like FaceReader emotional expressions, or event data from an eye tracker, these are imported as separate event logs. Furthermore, Pocket Observer files and files from certain Plug-ins, such as the questionnaire tool Noldus uASQ, are also stored as separate event logs within your observation. So one observation can contain more than one event log (see the figure below). But you cannot add events in The Observer XT to the imported event logs. Video files are also part of an observation. Similarly, if you import external data (see Import External Data as Text Files in File Management), those are part of an observation as well, although they are stored in separate files. Manage Observations with Multiple Event Logs Import Event Logs into an Observation - Export the event logs as ODX files. See Export Observational Data in File Management. - Open the observation, and click the Import Data button, then choose Import Observational Data. - Select The Observer XT Data File (*.odx) from the Files of Type list, and open your file. Note: If the ODX file contains more than one observation, only the event logs from the first observation are imported. To make sure that each ODX file contains one observation, select Create Separate File Per Observation when exporting the event logs. Check That Data Are Imported Correctly - Choose Analyze > Visualize Data and select your observation. - Check that the event logs are properly aligned, and that the data you want to analyze fall within the white area. The left margin of the white area is Observation Start Time. The right margin is Observation Stop Time. Make sure that all your data fall in this interval. - If the alignment is not correct, re-open the observation and click the Offset button to adjust the time between event logs. See Synchronize Data Sets. - If some data fall outside the white area, change the observation's start time and duration. Note: If you cannot select your observation, you may have a data profile active that does not contain your observation. Also make sure that no intervals are defined in your data profile. See Select Data for Analysis. Source: The Observer XT 17 Help - Carry Out an Observation, Noldus Information Technology --- ## The Observer XT 17 - Carry Out an Observation - Score Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-score-data Chapter: The Observer XT Score Data Aim To carry out an observation. Prerequisites You created and started an observation. Procedure Score the subjects, behaviors and their modifiers by typing the predefined key code or by clicking the key code in the Codes window. Typing key codes is generally faster. What you have scored appears in the Event Log window and is visualized in the Data and Audio Visualization window. Each row in the event log corresponds to one event. You can also type free text in the Comment column and press Enter. See Enter Events as Free Text. Scoring Order For each event line, score the subject first, then the behavior, and then the modifiers that are linked to that behavior. Of course, you score subjects and modifiers only if these are defined in your coding scheme. The Codes window displays which element should be scored next. The following symbols appear in your Event Log: - The start of an event with duration (state event). - The stop of an event with duration (state event). - The start of an event in a mutually exclusive and exhaustive group. The state is active from that moment and the previous state is no longer active. - An event without duration (point event). - An instantaneous sample event. For detailed scoring procedures, see the following topics: - Continuous Sampling - Instantaneous Sampling - Continuous and Instantaneous Sampling Notes When you save the project, the Event Log file is saved in the Event Data subfolder within your regular project folder. Make sure that the time before your computer goes into standby mode or hibernation is set to longer than the longest likely interval between scored events. To specify the interval for system standby and hibernation, in the Control Panel choose Power Options, click Change When the Computer Goes to Sleep, and make your selection. Stop the Observation Procedure An observation is ended when either the maximum recording time has elapsed, the video ends, or you manually end the observation. To stop the observation manually: - Click the Stop Observation button in the Playback Control window. - Depending on your Project Settings (see Value Update and Edit Independent Variables in Set Up Your Project), the Independent Variables window may appear. If so, enter the values. Note A confirmation window pops up when you stop the observation, unless you deselected this option in the Observation settings. The event log ends at the time point that you clicked the Stop Observation button. This is the Stop Time that you see in the Event Log. The observation stops at the time that you click Yes to confirm that you want to end the observation. This means that if you co-acquire external data, they extend beyond the end of the event log and are therefore grayed out. What's Next? - To play back the data, use the Play button in the Playback Control window (not the Start Observation button). - To visualize data without the Event Log and Codes window, choose Analyze > Visualize Data, or click the Visualize button on the toolbar. - To analyze data, select data for analysis and then choose an option from the Analyze menu. See Calculate Statistics. - When closing an observation, the program checks if the event log currently open contains errors, for example a start code without a matching stop code. Event logs with errors are not analyzed or visualized. See Check the Event Log for Errors. Notes An event scored at the exact moment the observation stops is not included in the analysis. If the maximum time is reached while you are in the middle of scoring elements in an event line, that line is saved but is not complete. You can either delete or edit the incomplete line. See Correct Event Log Errors Manually. Score Data: Detailed Procedure What Is Your Observation Method? - Continuous Sampling - Instantaneous Sampling - Continuous and Instantaneous Sampling Continuous Sampling Aim To code your observation with continuous sampling. Prerequisites - You created and started an observation. - You chose Continuous Sampling as Observation method. Procedure The procedure described below is very general and may not apply to your own coding scheme. If you did not define subjects or modifiers, ignore the instructions referring to them. You can also change the usual order of scoring, for example to score the behavior before the subject. - The first cell in the Subject column is selected. The Codes window shows all subjects. When a subject performs a behavior you are interested in, score the subject. The row is time-stamped and the time appears under Time. - The Behavior cell in the event line is now selected. The Codes window now shows all possible behaviors for this subject. Score the behavior. The name of the behavior appears in the row in the Event Log and the event is visualized in the Data and Audio Visualization window. The event runs until the end of the video. The duration will be corrected as soon as you code the next event. - If the behavior was linked to one or more modifiers, the Modifier cell in the event line is now selected. The Codes window now shows all the modifiers that can be attached to the scored behavior. Score the modifiers. The name of the modifier appears in the row in the Event Log. For numerical modifiers with a predefined range, first score the numerical modifier group and then type the value. - Score the other modifiers that are linked to that behavior. If scoring modifiers is compulsory, the name of the modifier group which contains required modifiers is displayed in the event log before you actually score it. This helps you to see which modifiers (from which modifier group) need to be scored. --- ## The Observer XT 17 - Carry Out an Observation - Scoring Events URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-scoring-events Chapter: The Observer XT Scoring Events You can score required modifiers in any order you want, but they will appear in the event log in the same order as in the coding scheme. In this example, the behavior 'Walk' has two modifier groups: 'Speed of walking' and the associated 'Breathing rate' of the subject. - A - The Event Log before the Modifiers of behavior Walk are scored; the Modifier column indicates in gray the required Modifier groups. - B - The Codes window with required Modifiers groups and their Modifiers. - C - The Event Log after the modifiers of 'Walk' have been scored. - If you have selected Add Comment in the Properties pane of the subject or the behavior you have just scored (see Define Subject Properties), you must add a comment. The Comment cell in the event line will be activated, with the word Comment in gray. Enter the comment, and press Enter. You can also copy and paste comments. If the Comment column is not present in your event log, right-click a column header and select Comment. If you do not want to add any comment, just press Enter. - The event is now complete. - The Subject cell in the next row is selected, and the Codes window now shows the subjects again. Add new events by repeating the steps above. - To stop a behavior or modifier, first score the subject, then: - Start-stop behavior – score the stop of the behavior/modifier. You cannot do this before the subject was scored. - Mutually exclusive behavior – score another element in the same group and its modifier. Score the stop of the behavior if no other behavior is active. - Mutually exclusive modifier – score a behavior and then another modifier. Notes - The time is assigned to an event when the first element of the coding scheme is entered, no matter whether it is a subject or a behavior. In the case you enter only free text, the time is assigned when you enter the first character under Comment. - If scoring modifiers is not compulsory (see Define Modifier (Group) Properties), you can skip them by placing the cursor in the Comment column, or pressing Enter. - If you do not want the Comment cell to be selected every time you score an event, make sure that for all behaviors and subjects the Add Comment option is not selected. See Define Subject Properties and Define Behavior (Group) Properties in Set Up Your Project. - Press the Undo button on the toolbar to correct a mistake. To make a correction undone, press the Redo button. For information on how to correct scoring errors after you finished the observation, see Correct Event Log Errors Manually. Instantaneous Sampling Aim To code your observation with instantaneous sampling. Prerequisites - You created and started an observation. - You chose Instantaneous Sampling as the Observation method. Procedure - A sound signal is given at the observation start. The Event Log shows all subjects from the Instantaneous Sampling subject group at time 0. It also shows the behavior groups that are linked to the subjects and must be scored in gray (see Define Subject Properties). When you carry out an Offline observation, the video file pauses until you scored all subjects, irrespective of whether you selected the option Pause Playback When Scoring an Event in the Project settings. The Codes window shows the current Subject-Behavior combination in the Status column and the behavior group that needs to be scored. - Score a behavior for each subject. As soon as the behavior is scored it appears in the event log. - If the behavior was linked to one or more modifiers, the modifier cell will be selected. The Codes window now shows all the modifiers that can be attached to the scored behavior. Score the modifier. The modifier appears in the event log. - If you have selected Add Comment in the Properties pane of the subject or the behavior you have just scored (see Define Subject Properties or Define Behavior (Group) Properties), the Comment cell will be selected with the word 'Comment' in gray. Enter a comment, and press Enter. If you do not want to add a comment, just press Enter. The event is now complete. - Add new events by repeating the steps above to finish scoring the complete sample. - Live – Wait until the sample interval has elapsed to score the next sample (indicated by a sound signal). - Offline – Click the Next Sample button to position the video at the time of the next sample. Use the Quick Review button to play back the video/audio file a few seconds before the sample time. This is useful to determine what behavior each subject is performing. What's Next? - To stop the observation, see Stop the Observation. - To correct scoring errors, see Correct Event Log Errors Manually. - For more information, see the Notes on Instantaneous Sampling and How To… procedures. Notes on Instantaneous Sampling Timers The Timers window displays the Remaining Interval Time. - Live – the timer counts down until the next Instantaneous sample. - Offline – the timer displays the sample interval length. If no Timers window is visible, choose View Settings > Show Window > Timers. You can drag the Timers window to below or next to the Event Log so you can easily see how much time is left until the next sample. To hide specific timers, right-click in the Timers window and deselect the timer. Subjects Subjects in an instantaneous sample block appear in the order they are placed in the coding scheme. Click the behavior cell of another subject to score in a different order. Modifiers If modifiers are not required (see Define Modifier (Group) Properties), you can skip them and go to the Comment column or start a new event line by pressing Enter. Comments If you do not want the Comment cell to be selected every time you score an event, make sure that for all behaviors and subjects the Add Comment option is not selected. See Define Subject Properties and Define Modifier (Group) Properties in Set Up Your Project. Samples - When the next sample begins before you finished scoring the previous sample (this only occurs in a Live observation), the non-scored events are set to "missing". - When your observation duration is a multiple of the sample interval (see More Options), no sample is scored at the end of the observation. If you do want to score this sample, make the observation for example 1 second longer. --- ## The Observer XT 17 - Carry Out an Observation - Stop the Observation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-stop-the-observation Chapter: The Observer XT Stop the Observation Procedure An observation ends when the maximum recording time has elapsed, the video ends, or you manually end the observation. To stop the observation manually: - Click the Stop Observation button in the Playback Control window. - Depending on your project settings, the Independent Variables window may appear. If so, enter the values. See Value Update and Edit Independent Variables in Set Up Your Project. A confirmation window appears when you stop the observation, unless you have deselected this option in the Observation settings. The event log ends at the time point that you clicked the Stop Observation button. If you co-acquire external data, it extends beyond the end of the event log and is therefore grayed out. What's Next - To play back the data, use the Play button in the Playback Control window (not the Start Observation button). - To visualize data without the Event Log and Codes window, choose Analyze > Visualize Data, or click the Visualize button on the toolbar. - To analyze data, select data for analysis, then choose an option from the Analyze menu. See Calculate Statistics. - When closing an observation, the program checks if the event log contains errors, for example a start code without a matching stop code. Event logs with errors are not analyzed nor visualized. See Check the Event Log for Errors. Notes on Stop Time - An event scored at the exact moment the observation stops is not included in the analysis. - If the maximum time is reached while you are in the middle of scoring elements in an event line, that line is saved but is not complete. You can either delete or edit the incomplete line. See Correct Event Log Errors Manually. Score Data: Detailed Procedure Continuous Sampling Aim To code your observation with continuous sampling. Prerequisites - You created and started an observation. - You chose Continuous Sampling as the observation method. Procedure The procedure below is general and may not apply to your own coding scheme. If you did not define subjects or modifiers, ignore the instructions referring to them. You can also change the usual order of scoring, for example to score the behavior before the subject. - The first cell in the Subject column is selected. The Codes window shows all subjects. When a subject performs a behavior you are interested in, score the subject. The row is time-stamped and the time appears under Time. - The Behavior cell in the event line is now selected. The Codes window shows all possible behaviors for this subject. Score the behavior. The name of the behavior appears in the row in the Event Log and the event is visualized in the Data and Audio Visualization window. The event runs until the end of the video and the duration will be corrected as soon as you code the next event. - If the behavior was linked to one or more modifiers, the Modifier cell in the event line is now selected. The Codes window shows all modifiers that can be attached to the scored behavior. Score the modifiers. The name of the modifier appears in the row in the Event Log. For numerical modifiers with a predefined range, first score the numerical modifier group and then type the value. - Score the other modifiers linked to that behavior. If scoring modifiers is compulsory, the name of the modifier group containing required modifiers is displayed in the event log before you actually score it, helping you to see which modifiers from which modifier group are required. Scoring Events Completing Required Modifiers and Comments You can score required modifiers in any order you want, but they will appear in the event log in the same order as in the coding scheme. - If the behavior has modifier groups, the Modifier column indicates in gray the required modifier groups. Score each required modifier. The modifier appears in the event log after scoring. - If you have selected Add Comment in the Properties pane of the subject or the behavior you have just scored, you must add a comment. The Comment cell in the event line will be activated with the word Comment in gray. Enter the comment and press Enter. You can also copy and paste comments. If the Comment column is not present in your event log, right-click a column header and select Comment. If you do not want to add any comment, just press Enter. - The event is now complete. - The Subject cell in the next row is selected and the Codes window shows the subjects again. Add new events by repeating the steps above. - To stop a behavior or modifier, first score the subject, then: - Start-stop behavior – Score the stop of the behavior or modifier. You cannot do this before the subject was scored. - Mutually exclusive behavior – Score another element in the same group and its modifier. Score the stop of the behavior if no other behavior is active. - Mutually exclusive modifier – Score a behavior and then another modifier. Notes on Scoring Events - The time is assigned to an event when the first element of the coding scheme is entered, no matter whether it is a subject or a behavior. If you enter only free text, the time is assigned when you enter the first character under Comment. - If scoring modifiers is not compulsory, you can skip them by placing the cursor in the Comment column or pressing Enter. - If you do not want the Comment cell to be selected every time you score an event, make sure that for all behaviors and subjects the Add Comment option is not selected. See Define Subject Properties and Define Behavior (Group) Properties in Set Up Your Project. - Press the Undo button on the toolbar to correct a mistake. To make a correction undone, press the Redo button. For information on how to correct scoring errors after you finished the observation, see Correct Event Log Errors Manually. --- ## The Observer XT 17 - Carry Out an Observation - Synchronize Data Sets URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-synchronize-data-sets Chapter: The Observer XT Synchronize Data Sets Aim To change the Start Time of a data set (Event Log, Video, Audio, External Data) relative to others. - Example 1: You started video recording with one camera 30 seconds earlier than with the other. Before observing, you want to synchronize the video files. - Example 2: After the observation, you imported associated physiological data and want to synchronize it with the events. Prerequisite An event must be recognizable in all streams to synchronize. For example, you press a key assigned to a behavior in the Coding Scheme and record that on video. The key press will appear in the Event Log and be visible in the video. When recording external data without automatic synchronization, the event should also be recognizable in the external data. Procedure - Open an existing observation and make sure that the video, audio, and external data linked to the observation are visible on your screen. If a data set is not shown, click View Settings on the far-right side of the toolbar and select that option. - Synchronize data sets in one of two ways: numerically by typing an offset value, or manually by moving the slider of the video file or dragging the visual presentation of the data set. Numerical Offset - Click the Offset button on the Component toolbar, then choose Numerical Offset. The File Synchronization window appears, listing the open Event Log, video and audio files, and linked external data. - Locate the data set (event, video, audio, or external data) whose start time you want to change relative to others, and click its Offset cell. - Enter the offset value. Example: If your Event Log starts 20 seconds after the video file, locate the row of the video file and enter -20 in the seconds group of the Offset column. - Click Apply. Manual Offset - Click the Offset button on the Component toolbar, then choose Manual Offset. The Synchronize window appears explaining the next steps. Click Start Synchronization. - Click the window with the data you want to synchronize. A red border appears around the window. You can now alter the time in this window while the time in other windows remains fixed. - Position the video, audio, or external data to the matching event in the Event Log: - Video or audio: Use the Playback Control buttons to play the media file to the new position. - External data: Click the window and move the data stream with the cursor to the new position. - Click the Offset button again. The red border disappears and the files are synchronized as specified. Notes - If you use MediaRecorder 4 or higher to record video, the video files are automatically synchronized with your observation. - You can use the File Synchronization window to check that the time difference between video, audio, Event Log, and other data streams is correct. You can change this difference at any time. Change the Observation's Start Time and Duration By default, the Start Time and Stop Time of an observation are the earliest Start Time and the latest Stop Time of any data set in that observation. These times are found in the Independent Variable List (Setup > Independent Variables). If you want to exclude a section at the beginning of the observation, or if you stopped the observation too early, you can change the Start Time and Duration. The Stop Time is determined automatically from the Start Time and Duration. Changing the Start Time and/or Duration does not move Event Logs, Video, Audio, or External Data files. For example, reducing the Start Time moves the Start point earlier but does not shift the associated files, resulting in a larger gap between the Start Time and the beginning of the files. Procedure - Choose Setup > Independent Variables. - Choose View Settings > Show Independent Variables and select Start Time, Stop Time, and Duration. - Edit the Start Time or Duration cell. Notes - Changing the observation Start Time or Duration does not affect synchronization between individual files. To change synchronization between files, see Synchronize Data Sets. - The observation Stop Time is updated automatically based on changes to the Start Time and Duration, and cannot be edited directly. - Events recorded before the Start Time or after the Stop Time of the observation are shown in gray in the Event Log. --- ## The Observer XT 17 - Carry Out an Observation - The Event Log Window URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-the-event-log-window Chapter: The Observer XT The Event Log Window The Event Log is the window in which you score and edit your data. The Event Log is your data file. Toolbar Buttons - Undo (Ctrl+Z): To undo your latest entry. - Redo (Ctrl+Y): To undo your latest correction to your Event Log. - Check Event Log: To check for errors in the data. See Check the Event Log for Errors. - Insert Event: To insert an event between two existing events. See Check the Event Log for Errors. - Delete Event (Ctrl+DEL): To delete the selected event from the event log (not from the coding scheme). - Delete Element (DEL): To delete the selected element from the event log (not from the coding scheme). - Finish Sample (Ctrl+Enter): To finish scoring the current sample without scoring all subject-behavior combinations. - Find (Ctrl+F): To find events. See Find Events. - Import Video: To import video files in the current observation. Use this button also to show audio from video in the form of waveforms by selecting the Visualize Audio checkbox in the Select Video window. - Import Audio: To import audio files in the current observation. - Import Data: To import observational data, external data, and other types of data in the current observation. See Import Observational Data in File Management and Import External Data as Text Files in External Data. - Settings: To open the Project Settings. See Define Project Settings in Set Up Your Project. - Independent Variables (Alt+F3): To open the Independent Variables list. - Offset (Ctrl+Shift+=): To synchronize video, audio, and external data files. See Manual Synchronization in External Data. - Visualize (Alt+F8): To visualize your current observation. When you select an event line before visualizing, the video will be positioned at that moment in the visualization. See Visualize Data. - Mouse Pointer: To deselect the zoom in or zoom out button. Available when the observation contains External Data. - Zoom In (Ctrl+.): To zoom in the external data plot. Available when an observation contains External Data. - Zoom Out (Ctrl+,): To zoom out the external data plot. Available when an observation contains External Data. - Export Current Observation: To export the observation to another project in The Observer XT, Microsoft Excel, or a text file. - Quick Help: For more information on carrying out an observation. - View Settings: To choose which windows to display. Customize the Event Log Window Choose the Time Format - Choose View Settings > Show Window > Time Formats. Hovering over the Time column displays a tooltip showing the time format. Show or Hide Columns By default, all elements defined in the coding scheme appear in the event log, along with a Comment column. - Right-click one of the column headers of the event log. - Select or deselect the category you want to show or hide. If you hide a column in the Event Log, you cannot score those elements anymore. If you click the tab of that element in the Codes window, the column reappears in the event log and you can score the element again. The Data and Audio Visualization Window The Data and Audio Visualization window shows the data that you have scored in a Time-Event Plot. The window displays event plots for each subject with colored bars for state events, narrow vertical bars for point events, and colored dots for Instantaneous Sampling data. If you co-acquire data such as FaceReader or Biopac data, a plot for each data stream is added to the window after you stop the observation. Data selection does not affect your plot. If you do not want to see the data of all subjects, go to View Settings > Event Visualization > Show Time-Event Plot and select the subjects of your choice. See the Visualize Data chapter to: - Change the time format - Show and hide events - Sort plots within a visualization - Change the colors - Customize the audio plot --- ## The Observer XT 17 - Carry Out an Observation - The Playback Control Window URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-the-playback-control-window Chapter: The Observer XT The Playback Control Window With the Playback Control window you can: - Start, pause and stop an observation. - Control playback of video files, audio files and other data sets (event log, external data). - Review segments of video, audio and other data sets. Some playback control buttons are hidden by default. Others can be hidden. Playback Control Buttons - Start Observation – Starts the observation. - Stop Observation – Stops the observation. - Pause/Still – Pauses the video/audio. Pressing the space bar toggles between Pause and Play forward at speed 1. - Play Forward at Speed 1 – Plays the video at the normal play speed. Pressing the space bar toggles between Pause and Play forward at speed 1. - Increase Speed – Increases the forward or backward playback speed by one step. - Decrease Speed – Decreases the forward or backward playback speed by one step. - Quick Review – Reviews the latest segment of video/audio, for example to check that an event was scored at the correct time or to add/edit events. Press the button multiple times to let the video jump back more. The video segment plays back at lower speed. Set the review length and speed in the Project Settings. Quick Review is also useful when carrying out Instantaneous Sampling during an offline observation. After clicking the Next and Previous Sample button, use the Quick Review button to get more information about which behavior the subjects are performing. To pause the video before quick review, set the quick review playback speed to 0. To pause the video after quick review, select the checkbox in front of Pause Playback After Quick Review. These settings are found in the Playback Control Options tab of the Project Settings. - Loop – Activates a loop to replay a fragment a number of times. The procedure depends on whether you chose User Defined or Fixed Interval for Loop Options in the Playback Control Options tab of the Project Settings window. - User Defined – Replays the entire observation or a segment. Two flags appear when you click the Loop button, one at the start and one at the end of the slider. Move these flags to select a segment. Click the Loop button again to stop the loop. - Fixed Interval – A fixed interval can be useful to score whether an event occurs in fixed time fragments (1-0 sampling). The flags show an interval with the length specified in the Playback Control Options tab of the Project Settings window. Move the flags to the episode you want to replay. You can move the flags in increments equal to the interval length defined in the Playback Control Options tab. For example, if the interval length is 10 seconds, you can position the start of the loop at 0 s, 10 s, 20 s, etc. If the interval length is 30 seconds, you can position the start at 0 s, 30 s, 60 s, etc. Use the shortcut key Ctrl+K (next interval) and Ctrl+J (previous interval) to jump to another interval. - Step Forward – Moves the video one frame forward. Moves audio files 1 second forward. When clicked during video playback, the video is paused and moves one frame forward. - Step Backward – Moves the video one frame backward with each click. Moves audio files 1 second backward. When clicked during video playback, the video is paused and moves one frame backward. - Time – Shows the time elapsed from the start time of the observation. If you select to display Remaining Time, it is possible that the remaining time plus elapsed time in the event log is not exactly the total duration due to rounding of decimals. - Playback Speed Indicator – Indicates the current playback speed. Playback Speed Notes - The available playback speeds depend on the video frame rate and video format. In general, speed ranges from 1/25 or 1/30 to +16 playing forward, and from -1/25 or -1/30 to -16 playing backward. - If the audio is spoken language, you will not be able to hear what subjects say when playing audio slower or faster. In most cases no sound is heard when playing forward at 2x or faster, or backward at any speed. - Occasionally during scoring, playback of the audio file may appear to jolt slightly. This is purely a cosmetic effect; the data being scored still have accurate time stamps. - If you have multiple video files and one has fewer available speeds than others, only those speeds are available for all videos. - If you select to display Remaining Time, it is possible that the remaining time plus elapsed time in the event log is not exactly the total duration due to rounding of decimals. Optional Playback Control Buttons The following buttons are hidden by default. To show them, choose Setup > Project Settings > Playback Control Options and select the desired buttons. - Play Backward at Speed 1 – Plays the video/audio/event log backward at normal play speed. - Jump to Begin – Moves the video/audio/event log to the start. - Jump to End – Advances the video/audio/event log to the end. - Volume Control – Move the slider to increase or decrease the volume of the audio file. The volume control works independently from the Windows volume control. Click the speaker icon to mute or unmute the sound. If an offset exists between video/audio/data streams, clicking Jump to Begin or Jump to End positions playback at the start of the earliest or latest stream. For example, if the event log starts one minute after the first video frame, clicking Jump to Begin positions at the start of the earliest stream, which is the video. Playback Control Buttons for Live Scoring The following buttons are only available when Live Observation is selected under Observation Source in the Project Setup. - Suspend Observation – Suspends the current observation. - Resume Observation – Resumes the current observation. Playback Control Buttons for Instantaneous Sampling The following buttons are only available when Instantaneous Sampling or Combine Continuous and Instantaneous Sampling is selected under Observation Method in the Project Setup. - Previous Sample – Moves the video/audio to the previous instantaneous sample. - Next Sample (Ctrl+Shift+Up Arrow) – Moves the video/audio to the next instantaneous sample. Customizing the Playback Control Window - To show and hide buttons, see Optional Playback Control Buttons. - To resize and move the Playback Control window, see Position and Resize the Windows on the Screen. - To customize the time interval represented by the slider, see Slider Range. --- ## The Observer XT 17 - Carry Out an Observation - The Videos Window URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-carry-out-an-observation-the-videos-window Chapter: The Observer XT The Videos Window The Videos window is present when scoring offline from video files. If scoring data from more than one video file, additional Video windows appear on screen. Video Properties Right-click the video image and choose Properties. The properties panel shows details about the video file such as frame rate, resolution, and file size. Video Codec and Audio Codec show the file formats read from the video file. Filter Details shows the filters and codecs used to play back the video file. Customizing the Videos Window - Dock/Undock Videos – Right-click the video and choose Undock. This option is not available if you have only one video; in that case double-click the title bar instead. The video is then displayed at 100% size and can be moved to a second monitor for a better view. To dock a window back, right-click and choose Dock. - Turn Audio On/Off – Click the speaker symbol on the top right corner of the Videos window for a specific video file. If your observation has audio files, you can mute their sound by clicking the speaker symbol in the External Data and Audio window. Switch Between Video Files One video file is positioned on the right part of the window, and the remaining files on the left part. Click one of the video files on the left to display it as the main video on the right. Drag the margins of the separation bar between the videos to adjust the size. You cannot deselect your main video in the Videos window; you can only deselect the smaller ones on the left side. To deselect the main video, first click a smaller one on the left to make it the main video. Manage Media Files Visualize Audio Waveforms from a Video File - Open an observation. - Click the Import Video button on the toolbar. - Select the video file and select Visualize Audio. - Click Open. The audio from the video file is converted and the audio waveforms are displayed in the External Data and Audio window. Up to two channels (Left and Right) are visualized. If the video contains more channels, only the first two are visualized. Replace a Media File - Open the Independent Variables List (Setup > Independent Variables). - In the Video or Audio column, click the ellipsis button in the cell corresponding to the observation for which you want to replace the media file. - Select the new media file and click Open. Remove a Media File - Open the Independent Variables List (Setup > Independent Variables). - In the Video or Audio column, right-click the cell corresponding to the observation for which you want to delete the media file. - Select Delete and click OK to remove the file from the observation. The media file is not deleted from the hard disk. Media File Notes - If the video was already in the observation, open the Independent Variables List, click the button next to the video file, select the Visualize Audio option, and click Open. Then re-open the observation. - The title of the audio waveforms plot from video is Video File (dB). Contrary to audio files, the audio waveforms from a video are not an independent variable. - Audio waveforms from a video file are shown when the corresponding video is also shown. To select or deselect a video file, choose View Settings > Video Files > Show Video and select the file. - To mute audio from a video, click the speaker icon in the External Data and Audio window or in the Videos window. - To remove the audio waveforms from your observation, remove the video file. - The number of media files you can use per observation depends on your The Observer XT license. - The number of videos you can play back smoothly simultaneously depends on your computer. Observations with Multiple Event Logs Observations and Event Logs While you carry out an observation, events and comments are logged in what is called an Event Log. The data from your whole observation are stored in one event log. If you import event data from an external program, like FaceReader emotional expressions, or event data from an eye tracker, these are imported as separate event logs. Furthermore, Pocket Observer files and files from certain plug-ins, such as the questionnaire tool Noldus uASQ, are also stored as separate event logs within your observation. So one observation can contain more than one event log. But you cannot add events in The Observer XT to the imported event logs. Video files are also part of an observation. Similarly, if you import external data, those are part of an observation as well, although they are stored in separate files. Manage Observations with Multiple Event Logs Import Event Logs into an Observation - Export the event logs as ODX files. See Export Observational Data in File Management. - Open the observation, and click the Import Data button, then choose Import Observational Data. - Select The Observer XT Data File (*.odx) from the Files of Type list, and open your file. Note: If the ODX file contains more than one observation, only the event logs from the first observation are imported. To make sure that each ODX file contains one observation, select Create Separate File Per Observation when exporting the event logs. Check That Data Are Imported Correctly - Choose Analyze > Visualize Data and select your observation. - Check that the event logs are properly aligned, and that the data you want to analyze fall within the white area. The left margin of the white area is Observation Start Time. The right margin is Observation Stop Time. Make sure that all your data fall in this interval. - If the alignment is not correct, re-open the observation and click the Offset button to adjust the time between event logs. See Synchronize Data Sets. - If some data fall outside the white area, change the observation's start time and duration. Note: If you cannot select your observation, you may have a data profile active that does not contain your observation. Also make sure that no intervals are defined in your data profile. See Select Data for Analysis. Source: The Observer XT 17 Help - Carry Out an Observation, Noldus Information Technology --- ## The Observer XT 17 - Coder License - Coder License and The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-coder-license-coder-license-and-the-observer-xt Chapter: The Observer XT Coder License and The Observer XT Introduction What Is a Coder License? The Coder License is a license that restricts the use of The Observer XT software to coding only. This means that the functionality regarding the setup and the analysis of a project are not available or locked. It is designed for use with Coding Stations, in combination with one or more full licenses. Both the full and the Coder Licenses use the same The Observer XT software. A Coder License can come in the form of a USB hardware key that needs to be inserted into a USB port of a coding station. A Coder License can also be a Site License that is assigned to coders. When you start up The Observer XT, choose Start with Site License and enter the login details supplied to you by your Site License administrator. Why Use a Coder License? When working with large projects, a lot of coding (scoring of the behaviors) can be involved. Sometimes it is worthwhile to split up the work between several observers. An efficient way to do this is to create multiple Coding Stations. Using Coder Licenses in a Multiple Coding Station setup has the advantage that you do not need full licenses for the computers that are only used for coding. Possibilities and Restrictions License Options The Observer XT Coder License restricts the functionality of the program to coding and visualization only. An add-on module is available for the use of digital media files and for the use of external (physiological) data. Both media files and external data can only be imported with a Coder License; you cannot acquire them. Observation Method The Observation method in the main project (Offline or Live) determines what Observation method you can use on the Coding Station. You cannot score Live and control external devices simultaneously. This means that you cannot control MediaRecorder or other software to acquire data. Coding The Coder License allows you to: - Score subjects, behaviors, and modifiers during an observation. - Edit your Event log, for example, when you scored the wrong behavior or missed one. You cannot edit the Coding Scheme or the Coding Scheme Settings. Independent Variables You can enter independent variable values. You cannot add or edit independent variables. Data Selection and Analysis Data selection and statistical analysis are not available with a Coder License. You can visualize data, but visualization is based on the Data Profile that was active when the project was saved with the full license. Therefore, it may not show all data within an observation. File Management With the Coder License, you cannot create a project. You can open and save a project, open a project template, make a backup of the project, restore a project, and export data as odx files or text files. Furthermore: - You can import external data if you have the External Data Module. - Importing observational data is not possible. - Importing media files is possible with the Media Module. --- ## The Observer XT 17 - Coder License - Technical Support URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-coder-license-technical-support Chapter: The Observer XT Technical Support If you have any problems, questions, remarks, or comments, please contact Noldus through the support website and fill out a Support Request Form (preferred) or phone during normal working hours. If you encounter a problem using The Observer XT, you can search through hundreds of entries in a database of questions submitted by customers to the Noldus support department, along with answers from the support staff. Source: The Observer XT 17 - Coder License, Noldus Information Technology --- ## The Observer XT 17 - Coder License - Using a Coder License in a Multiple Coding Station Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-coder-license-using-a-coder-license-in-a-multiple-coding-station-configuration Chapter: The Observer XT Using a Coder License in a Multiple Coding Station Configuration A multiple coding station configuration is a way to collect and manage data from a number of coding stations. You define a project on a computer with a full license. Each coding station with a Coder License receives the Project Setup, Coding Scheme, and Independent Variable List and scores the behaviors. After coding is completed, all data is transferred back into the main project for analysis. File Formats Used - *.vop – Project file: used for opening and saving a project. - *.otb – Project Template: template to export Project Setup to Coding Stations. - *.odx – Observational data: file containing one or more observations to import into the main project on the full license computer. Creating a Multiple Coding Station Project On the Full License Computer - On the computer with a full license, create a project and define a Coding Scheme and the other setup options (Project Setup, Independent Variables, etc.). - Choose File > Save Project as Template. - Type in the name of the template project or use the current name. - Click the Save Options button to open the Save Template Options window: - Include Independent Variables – When you select this option, the Independent Variables are included in the template project. - Include Hardware and Software Devices – When you select this option, external commands in the Devices list are contained in the template project. - Template Information – Optionally, you can type in additional information about the template project. - Click OK twice to save the template project. The template has the extension *.otb. In the template, Project Setup, Coding Scheme, and Independent Variable List are locked. If you need to make changes to your project setup: - On the computer with a full license, either change the original project, or create a new project with the template and then unlock it (Setup > Unlock Configuration). - Make the required changes. - Repeat the steps above and make sure that the Coding Stations receive the right copy. On the Coding Stations - Copy the *.otb file, or *.otx file for templates made with The Observer XT, to the Coding Station computers. It is recommended to copy it to the folder: C:\Users\Public\Public Documents\Noldus\The Observer XT\Templates. The Observer XT will then automatically open the correct folder. - If you use video or audio files in your project, make sure that these files are also accessible from the Coding Stations. - On a coding station, start The Observer XT and choose File > New Project From Template. If the *.otb or *.otx file is stored in the default templates folder, the correct location is selected automatically. Otherwise, browse to the correct location. - Click the Select button and open the template project (*.otb, or *.otx if you made the template with a previous version of The Observer XT): - If you open a template project in the Coder License version of The Observer XT, the suggested name for the new project is the name of the template project followed by "sub". - If you open the template project in a Full License version of The Observer XT, you can type in a name for the new project. - Click OK. The new project opens. Repeat steps 1–4 for all coding stations. - You can now create a new observation and score the behaviors. Retrieving Data for Analysis On the Coding Stations - After coding is completed, export the observations from the coding stations as *.odx files: choose File > Export Observational Data > The Observer XT. By default, all observations are selected. If you only want to export some of the observations, adjust the selection. Click Next. - A new window appears. By default, all selected observations will be exported into one *.odx file. If you do not want this, select Create Separate File Per Observation. Choose a name and location for the export file, and click Export. - Copy the *.odx files to the computer with the full license. Repeat steps 1–3 for every Coding Station. Note: Because the *.odx file contains a link to the video or audio file used, it is useful to either work with a media file located on a shared server, or to work with a media file that is in the exact same location on both local computers (for example, the default folders C:\Users\Public\Public Documents\Noldus\The Observer XT\Video Files or C:\Users\Public\Public Documents\Noldus\The Observer XT\Audio Files). This way, The Observer XT automatically opens the right media file. If the locations are different, a window will open when importing the *.odx file so you can browse to the correct location. On the Full License Computer - On the computer with a full license, open the main project (the *.vop file). - Import the observational data as new observations: choose File > Import Observational Data. The Select Observational Data Files window appears. In the Look In box, browse to the folder in which the *.odx files are located, select the file you want to import, and click Open. You can only import one *.odx file at a time; however, this file can contain multiple observations. If the name of an imported observation matches an existing observation or event log in the project, the file name automatically changes to [filename]_imported. If that name is also taken, the program will automatically number the file by adding [1], [2], etc. - Perform your data selection and analysis. Visualizing Data with a Coder License Choose Analyze > Visualize Data to visualize the observations on the coding station. The data are visualized according to the data profile that was active on the full license computer when exporting the project (*.otb). If this data profile filtered some events out, these will not be shown on the Coder License computer. Data is shown together with the video files, audio data, and external data, if the corresponding add-on modules are present. --- ## The Observer XT 17 - Dongle Deactivation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-dongle-deactivation Chapter: The Observer XT The Observer XT 17: Switching from Dongle to Software Based Licensing Deactivating Your Dongles Thanks for letting us know which dongles you would like to convert to a software-based license. The next step is to deactivate the dongle key(s) and confirm the deactivation by sending the requested screenshots. Please Read This First - Deactivation of the dongle(s) cannot be reversed. - Once deactivated, dongles have a 5-day grace period before expiring and becoming inactive. - Once you upgrade to a software-based license you will not be able to work in projects in any earlier version of The Observer XT. - If you are upgrading from an earlier version, please open that version and make backups of your projects via File > Make Backup. Backups (*.VPB files) can be opened in The Observer XT 17 via File > Restore Backup. - Complete this process (emailing information back and forth with Noldus) within 5 days to avoid losing access to your Observer license(s). - If you run into any issues, please submit a support ticket on the MyNoldus client portal. Step 1: Install The Observer XT 17 If you are upgrading from an earlier version of The Observer XT, download and install The Observer XT 17 first. Download the installation file: The Observer XT - Setup - 17.0.1300.exe Alternatively, you can download from MyNoldus: - Log in or create a new account. - Go to: Downloads > The Observer > Versions > Current Version > The Observer XT - Setup - 17.0.1300. Locate and double-click on The Observer XT - Setup - 17.0.1300.exe to install. Step 2: Deactivate Dongle(s) Repeat the following procedure with each dongle: - Insert the dongle into a USB port. - Launch The Observer XT 17. - If you are upgrading to version 17, the Enter Upgrade Key box will open. If it does not, go to Help > Upgrade. - Enter the provided upgrade keys for the inserted dongle. - Enter Key 1 and Key 2 (if needed) and click OK to close. - Only fill in the first field for Key 2 despite all fields being active. Step 3: Send Screenshot(s) of Dongle Expiration - Insert the dongle into a USB port. - Launch The Observer XT 17. - Go to Help > About The Observer XT > License Info. - Make a screenshot of the License Information box using Snipping Tool, Snip & Sketch, or Fn-PrintScreen + Ctrl-V. - Email the screenshot(s) to support@noldus.com. You will receive the activation key(s) for your software-based Observer XT license within 5 business days. If you run into any issues, please submit a support ticket on the MyNoldus client portal. Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## The Observer XT 17 - Episode Selection - Edit the Episode Selection URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-episode-selection-edit-the-episode-selection Chapter: The Observer XT Edit the Episode Selection What Do You Want to Edit? - Events within Episode - Episode Selection - Episodes - Transitions Events Within Episode Add Events to an Episode - In the Event Log pane of the Episode Selection window, select an observation from the first list and an event log from the second (if the selected observation contains more than one event log). - Drag events to the Episode Selection pane. For state events with start and stop lines, you do not need to drag and drop the stop line. Just drag the start line (with the green triangle next to the behavior name). The information about the duration of that state is copied anyway. Move an Event to Another Episode To move an event to another episode, select it and drag it to the required position. You cannot move an event to a new position within the same episode, because events in an episode are ordered chronologically. Remove Events from an Episode To remove events, select them and click the Delete event button on the toolbar. Removing events from the Episode Selection does not affect events in the Event Log pane. Edit the Cell Contents - Double-click the cell you want to edit. - Enter text, or, for time/duration cells, click one of the numbers (s.dd) and use the arrow keys to change the value. Note: Only columns that are not grayed out can be edited. Episode Selection Sort Episode Selection Columns To sort the columns of the Episode Selection, click a column header and drag the column to another position. Episodes Rename an Episode To rename the Episode title row, double-click the name and enter the new text. Split Episodes To split an episode, insert a transition. See Transitions. Move an Episode To move an entire episode, select the transition title and drag it to the required position. To move an episode to the beginning of the Episode Selection, drag its title row to the header row of the Episode Selection. To move an episode to the end of the Episode Selection, drag its title row to the last transition title row in the Episode Selection. Transitions Delete a Transition To delete a transition, select the transition row and click the Delete transition button on the toolbar. The events in the episode are moved to the previous episode. Delete an Episode To delete an entire episode, select the transition row and click the Delete episode button on the toolbar. Customize the Episode Selection Window Optionally, customize the Episode Selection window by choosing the panes or columns to display. To do so: - Choose View Settings at the far-right side of your screen. - Select what to display: - Event Log – The Event Log pane. - Videos – The Videos window. If your Episode Selection contains multiple videos, click Videos and select one of the following options: - Show All Videos per Episode – To display all videos that are associated with the events in the episode. The video that is selected in the Video column for that episode is shown in the middle of the Videos window. The other videos are shown on the left side of the Videos window. - Show Videos Selected for Episode Video Only – Only the video that is selected in the Video column for that episode is shown in the Videos window. - External Data – This option is only available if you have the External Data Module. To display the External Data window, choose External Data > External Data Window. To choose some external data streams, choose External Data > Show External Data and select which streams to display. The areas in the External Data window with a white background show the data which are included in the Episode Selection. The blue areas show the data which are excluded. You cannot display different external data sets in separate windows. - Playback Control – To display the Playback Control window. - Show Column – Select which columns you want to show in the Event Log or Episode Selection. Alternatively, right-click a column header and select Show Column. The Episode Selection Columns The Episode Selection contains the following columns. Dependent on your license, some columns may not be available. - Observation – The name of the observation the event was scored in. - Event Log – The name of the event log data file in which the event was stored. - Episode Selection Time – The start time of the event relative to the start of the Episode Selection. This includes the duration of the first transition at the start of the Episode Selection (see the time in the subtitle duration column in the transition row). - Start Time – The start time of the event. - Stop Time – The stop time of the event. - Relative Event Time – The start time of the event relative to the start of the Event Log. - Event Duration – The duration of the event. For point events and events scored with Instantaneous Sampling, the duration is zero. - Subject – The Subject in the event line. - Behavior – The Behavior in the event line. - Modifier – The Modifier in the event line. - Comment – The comment in the event line. - Video (editable) – The name of the video file associated with the observation. If the episode is associated with more videos, the Video cell in the episode title row contains a list with the available videos. You can only select one video per episode. - Roll-On Time (editable) – The time that playback starts before the actual start of the event. - Roll-Off Time (editable) – The time that playback continues after the stop of the event. - Subtitle Text (editable) – The text that will be used as subtitle. You can specify a text for each event or transition. By default, it shows the name of the Behavior. - Subtitle Duration (editable) – The duration of the subtitle text of events and transitions. Source: The Observer XT 17 Help - Episode Selection, Noldus Information Technology --- ## The Observer XT 17 - Episode Selection - Episode Selection URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-episode-selection-episode-selection Chapter: The Observer XT Episode Selection Four Ways to Select Episodes To select events or video fragments, select episodes in one of the following ways: - Method 1 – Select Events Manually. Create an empty Episode Selection and then select events manually by dragging and dropping them from the Event Log to the Episode Selection. - Method 2 – Select the Entire Event Log. - Method 3 – Select All Events from a Data Profile in an Episode Selection. - Method 4 – Select Events in the Visualization. Notes: - If the observation contains video files, these open when you select events or episodes. - Audio files associated with an observation are not visualized. - If you do not see the videos, choose View Settings > Videos > Video Window. - If this does not solve the problem, it may be that The Observer XT does not find the videos. To solve this: - Click the observation name in the Project Explorer. - Select the video file and click Open. - Re-open the Episode Selection (click the Episode Selection in the Project Explorer). - Events within one episode must be from the same observation. Method 1 – Select Events Manually To select events manually in the Event Log, follow these steps: - Choose Analyze > Episode Selection > New. The Event Log pane appears with the empty Episode Selection at the bottom. - The Event Log pane has two lists from which you can select an observation and an event log within an observation. Select the correct observation and event log. - Select events by dragging and dropping them from the Event Log to the Episode Selection. Method 2 – Select the Entire Event Log To select all events from an event log, in the Project Explorer right-click the Event Log file you want to create an Episode Selection from, and select Create Episode Selection. You must right-click an event log, not an observation. To find an event log, first open the Observations folder in the Project Explorer, then the Observation containing the event log, and finally the Event Files folder. The Episode Selection contains all events in the event log, grouped in an episode. The light blue line is the title of the episode, and is named after the event log. Method 3 – Select All Events from a Data Profile in an Episode Selection To select events with a Data Profile, follow these steps: - Click the Data Profile you want to use in the Project Explorer. For more information on data profiles, see Select Data for Analysis. - Choose Analyze > Episode Selection > New From Current Data Profile. Notes: - The events that took place during the Roll-on and Roll-off Time are also included in the Episode Selection. - Data from different observations are placed in separate episodes (indicated by light-blue title rows). Data from different intervals (see Select Intervals) are also placed in separate episodes. If the same event is included in two or more intervals, the event is repeated in each episode. Method 4 – Select Events in the Visualization To select episodes in the videos or Time-Event plots. Each episode selected with this method represents one video segment from one observation. Episodes defined with this method cannot overlap. - In the visualization (Analyze > Visualize Data), scroll the video to the start of the episode. Then click the Start Episode button on the toolbar. - Move the slider, or click and drag the Event plot. The selected area is shown in orange in the Event plot. - When you have made your selection, click the Stop Episode button on the toolbar. - Optionally select more areas of interest. When done, click the Create Episode Selection button on the toolbar. The Episode Selection window now contains the events or event fragments in the selected time intervals. Partial Events A key difference between this method and the three other methods is that with this method you do not necessarily select entire events. You can also select episodes that start or stop halfway through an event. With the other three methods it is only possible to select entire events. Selecting Episodes Outside Data Selection Criteria If you created a data profile, the data that fall outside the selection criteria are displayed in gray in the visualization. If you select episodes that fall (partly) within the area in gray and create an Episode Selection, the video of the entire interval is selected. However, the events that do not meet the selection criteria are not included in the Episode Selection. Removing Episodes in the Visualization To remove the latest selected episode, click the Remove Episode button on the toolbar. To remove all selected episodes, click the Remove All Episodes button on the toolbar. All selected episodes are removed when you exit the Visualization. Subtitles To change the default subtitles for the episode. By default, each event is shown as a subtitle. You must have created an Episode Selection before proceeding. - Choose Analyze > Episode Selection > Settings, or click the Settings button on the toolbar. - Select what to display as subtitles on the Subtitles tab: - Behavior Name – The content of the Behavior column. - Behavior Name and Comment – The content of both the Behavior and Comment columns. - Comment – The text in the Comment column for each event. - None – To not display subtitles. - Include Time – To display the time of the event or transition. Either select Absolute Time, or Relative Time, which is the time from the start of the event log. To change the time format, do so in the Project Settings (see Time Formats). - Click Apply to All to apply the changes to all events in the Episode Selection. If you do not click Apply to All, the changes will only apply to events you later add to the Episode Selection. Subtitle Duration To change the subtitle duration. Subtitles are by default shown for 5 seconds, or less if the event is shorter, with a 3-second Roll-on time and 2-second Roll-off time. - Choose Analyze > Episode Selection > Settings, or click the Settings button on the toolbar. - Open the Duration tab. - Set the duration in the Subtitles field. The default value is 5.0 seconds. Note that the duration of a subtitle cannot exceed the duration of the event plus Roll-off time. See Roll-on and Roll-off Time. - Example 1 – A state event has a duration of 5 seconds and a Roll-off time of 2 seconds. The subtitle will be shown for a maximum of 7 seconds. - Example 2 – A state event has a duration of 20 seconds. If you set the subtitle duration to 10 seconds, it will be shown for 10 seconds, independent of the Roll-off time. - Example 3 – A point event has a Roll-off time of 2 seconds. The subtitle will be shown for 2 seconds. Increase the Roll-off time to increase the subtitle duration. - Click Apply to All to apply the changes to all events in the Episode Selection. If you do not click Apply to All, the changes will only apply to events you later add to the Episode Selection. Transitions Transitions separate episodes. Transitions are shown as a blue row in the Episode Selection. There is also a transition at the start of the Episode Selection. You must have created an Episode Selection before proceeding. - Click the first event line in the Episode Selection that you want to have in the episode. - Click the Insert Transition button on the toolbar. A light-blue transition row is added immediately before the selected event. Transition Duration To change the default transition duration of 4 seconds, follow these steps: - Click the Settings button on the toolbar, or choose Analyze > Episode Selection > Settings. - Open the Duration tab. - Change the time in the Transitions field. - Optionally, change the Roll-on and Roll-off Time. - Click Apply to All to apply the changes to all events in the Episode Selection. If you do not click Apply to All, the changes will only apply to events you later add to the Episode Selection. Roll-on and Roll-off Time Roll-on and Roll-off times add some time before and after the events in an Episode Selection. You must have created an Episode Selection before proceeding. Procedure for a Single Event You can set the times for each event individually in the Roll-on and Roll-off columns in the Episode Selection. Procedure for All Events - Click the Settings button on the toolbar, or choose Analyze > Episode Selection > Settings. - Click the Duration tab. - Change the time in the Roll-on or Roll-off field. - Click Apply to All to apply the changes to all events in the Episode Selection. If you do not click Apply to All, the changes will only apply to events you later add to the Episode Selection. Episode Selection Options Select the Video If the observation is associated with a video file, this video is shown in the Videos window of the Episode Selection view. If the observation contains multiple video files, the ones that are associated with the selected episodes are all shown in the Videos window. Play the Episodes - Make sure that with View Settings on the Component toolbar, the option Videos > Video Window is selected. Also select Playback Control and, if applicable, External Data. - Right-click the line of the event where you want to start, and select Play. Segments of video and external data are played, synchronized with the events highlighted in the Episode Selection. - Optionally, jump to the next or previous event in the Episode Selection with the step forward and backward buttons. For information about other Playback Control buttons, see The Playback Control Window. Play a Point Event By definition, events scored with Instantaneous Sampling have no duration. By default, each event has a Roll-on Time of 3.0 seconds and a Roll-off Time of 2.0 seconds. This means that three seconds of video are played before the event and two seconds after it. When you want to play a point event, make sure that its Roll-on Time or Roll-off Time is greater than zero (if both are zero, they are shown in red). See Roll-on and Roll-off Time. Save an Episode Selection The Episode Selection is saved as soon as it is created. It is named Episode Selection N, where N is an incremental number. Episode Selections are shown in the Episode Selections folder in the Project Explorer. To rename an Episode Selection, right-click it and select Rename. To delete an Episode Selection, right-click the Episode Selections folder and select Delete, then select the episode selection and click OK. When you save your project, each Episode Selection is saved to a file with the extension *.esr, within your project's Episode Selections folder. Export the Episode Selection You can export Episode Selections to text files. If your observation includes external data, these are exported together with the Episode Selection in separate files. To export the currently active Episode Selection, click the Export Selected Data button on the toolbar. To export all Episode Selections, choose Analyze > Episode Selection > Export. Enter a file base name, choose where to save the file, the file type, and list separator, then click Export. Episode Selections are saved as - Episode Selection 1.txt, - Episode Selection 2.txt, and so on. Associated physiological data are saved as - Episode Selection 1 - physiological data 001.txt, and so on. If you have set Roll-on and Roll-off Times, the external data samples within these intervals are also exported. Edit the Episode Selection The Episode Selection Columns --- ## The Observer XT 17 - External Data - External Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-external-data-external-data Chapter: The Observer XT External Data What Is External Data and How Do I Work with It? External Data External data can be data that have been acquired with a separate Data AcQuisition (DAQ) system, such as a MindWare or BIOPAC system. This can be, for example, physiological data (e.g., ECG, EEG, blood pressure, skin temperature), environmental data (e.g., temperature, humidity) or eye-tracking data. To be able to work with external data in The Observer XT, your license must include the External Data Module. N-Linx BIOPAC AcqKnowledge 5, Tobii Pro Lab, Tobii Pro Studio 3.4.7 and Tobii Glasses software and the Bitbrain EEG acquisition software can be integrated with The Observer XT using the Noldus network communication protocol N-Linx. This simplifies the setup and ensures synchronization. For these systems, separate technical notes are available. - Technical Note - BIOPAC MP System - The Observer XT - Technical Note - Tobii Pro Eye Trackers - The Observer XT - Technical Note - Tobii Glasses - The Observer XT - Technical Note - Bitbrain EEG - The Observer XT In addition to this, technical notes are available for integration between The Observer XT and Mindware Biolab and SMI eye-trackers. You can download these technical notes from the MyNoldus section of the Noldus website. What Can I Do with External Data? You can import external data into The Observer XT and synchronize them with logged events. You can then visualize, select and analyze the external data based on events. Or, the other way around, you can analyze events when external data have a certain value. This topic focuses on the import of external data and the synchronization with logged events. - For selecting external data, see Select Data for Analysis. - For visualizing external data, see Visualize Data. - For analyzing external data, see Calculate Statistics. How Do I Work with External Data? The procedure to work with external data in The Observer XT depends on the way these data are going to be synchronized with logged events. The Observer XT can send a synchronization signal to the DAQ system. The external data are then automatically synchronized with the events. See External Data Acquisition with Synchronization Signal. You can also record external data stand-alone and import these data afterwards in The Observer XT. In this case you need to synchronize the data manually. See Stand-Alone External Data Acquisition. Workflow External Data Acquisition with Synchronization Signal - Set up The Observer XT for live observation and to send a synchronization signal to the DAQ system. The synchronization signal is an analog signal which is fed into a free analog input of the DAQ system. In the DAQ device this signal is configured equally as a standard physiological signal (e.g. ECG, EEG, EMG). The time information in this synchronization signal is stored in the external data file. See Set Up Your Experiment with Synchronization Signal. - Carry out a live observation and simultaneously collect the external data. See step 8 in Set Up Your Experiment with Synchronization Signal. - Import the external data set together with the synchronization signal into The Observer XT and link it to an observation. The Observer XT uses the synchronization signal to synchronize the external data with the events. See Import External Data as Text Files. Stand-Alone External Data Acquisition - Record the external data. Optionally, record a video of your test subjects with MediaRecorder as well, or carry out a live observation in The Observer XT. - Export the external data as a text or EDF file. - Import the external data into The Observer XT. See Import External Data as Text Files or Import European Data Format Files. - Synchronize the external data manually with the events in The Observer XT. See Manual Synchronization. - Optionally, score your observation in more detail with the recorded video. See Carry Out an Observation. What's Next? - Optionally, make a selection of external data or events in a data profile. See Select Data for Analysis. - Visualize the data. See Visualize Data. - Calculate statistics on behaviors/modifiers and/or external data. See Calculate Statistics. Set Up and Acquire External Data What do you want to do? - Set Up Your Experiment with Synchronization Signal - Set Up Your Experiment with Stand-Alone External Data Acquisition - Read About the Synchronization Signal Set Up Your Experiment with Synchronization Signal Aim To have The Observer XT send a synchronization signal to your DAQ system. The synchronization signal is imported into The Observer XT with the external data and is used to synchronize the external data with the Event log. Prerequisites - Your license for The Observer XT includes the External Data Module. - You have a synchronization cable. Procedure - Connect your DAQ system to its dedicated computer (that is, the computer that records such data). Also connect it with the synchronization cable to the computer with The Observer XT. Use one of the computer's COM ports of the computer with The Observer XT. If the computer has no COM port, use a USB-RS232 adapter. - In The Observer XT, choose Setup > Project Setup > Live Observations. The Devices window opens. If not, click the Devices button. - Choose DAQ Settings (or any other name indicating the external data acquisition device) and click Edit Settings. - Under Predefined Settings, select the item corresponding to your Data Acquisition device, or create a new one. - Under Output Device, select how the PC with The Observer XT is connected to the DAQ system. Select the correct COM port, or Noldus Mini-IObox sync if you use a Noldus mini USB-IO box. - Click the Check Status button to check whether the selected port is Online. If it is Offline, check that other programs (also those not running) are not using that port. Change the port settings in those programs or uninstall them when not necessary. When you use a USB-RS232 adapter, search for the COM port from the list that is Online. - Under Signal Type select: - On-Off if your DAQ system uses a low sample rate (< 10 Hz) or samples continuously (without regular intervals). Also select this option if you use the Noldus mini USB-IO box for synchronization. - Time Code (TCAP) in all other cases. Enter the Sample Rate of your DAQ device. The program calculates the Minimal Sampling Time in seconds. This is the time The Observer XT needs to send the complete synchronization signal to the DAQ device at that sample rate. See The Time Code (TCAP) Synchronization Signal. - Start the observation as usual (see Start the Observation in Carry Out an Observation). The Observer XT now asks you to start data acquisition on your DAQ device. - Start the DAQ acquisition. - In The Observer XT, click OK. - After you finish the observation, export the data from the DAQ system as a text file. Name your synchronization data as 'sync' or use 'sync' as the type of Unit. The Observer XT then automatically recognizes your synchronization data upon import. - Continue with Import External Data as Text Files. Notes - It is also possible to connect the computer with The Observer XT with a USB cable to a Noldus mini USB-IO box. The synchronization cable connects your DAQ system to one of the TTL ports of the Noldus mini USB-IO box. Select Noldus Mini IObox Sync in the Output Device list in step 5. Select On-Off in step 7. Contact your Noldus sales representative if you are interested in this option. - If you click Cancel after you clicked the Start Observation button in step 8, the observation starts anyway, but the synchronization signal is not sent to the DAQ device. - If the DAQ system uses a filter for incoming external data, it might also affect the synchronization signal from The Observer XT. Watch the sync signal on your DAQ system; it should display square pulses. - Automatic synchronization with the synchronization signal was tested with text export from the DAQ system only. You can also import EDF files into The Observer XT (see Import European Data Format Files), but then we recommend synchronizing manually (see Manual Synchronization). Set Up Your Experiment with Stand-Alone External Data Acquisition Aim To manually start and stop acquisition with a DAQ system and import the external data into The Observer XT. The imported data must be synchronized manually with the Event log. Prerequisites Your license for The Observer XT includes the External Data Module. Procedure - Make sure an event is recognizable in the Event log, the videos and the external data file, so that you can use it to synchronize the streams. Do so in, for example, one of the following ways: - Count down until you press the button to start the DAQ acquisition, and make sure you can hear this on the video file. - Define a dummy behavior in the Coding Scheme and score that behavior at the same moment as you start the DAQ acquisition. - Synchronize the clock times of both computers with a time server to make sure the time stamps of the external data files match those of the Event logs. - If the DAQ system does not require many computer resources, install the DAQ software on the same computer as The Observer XT. The time stamps in the external data file then automatically match the ones in the Event log. - In The Observer XT, choose Setup > Project Setup and then: - Live Observation – if you score events simultaneously with recording the external data. Optionally, record video with MediaRecorder as well. See Observe Live and Record Video with MediaRecorder in Set Up Your Project. - Offline Observation – if you recorded videos together with recording the external data and annotate them at a later stage. See Observation Method in Set Up Your Project. - Carry out the observation as usual. See Score Data in Carry Out an Observation. - Export the data from your DAQ system as a text or EDF file. - Import the external data. See Import External Data as Text Files or Import European Data Format Files. - Synchronize the data manually with the observation. See Manual Synchronization. The Synchronization Signal What Is the Synchronization Signal? If you score events and simultaneously acquire external data, you can synchronize external and event log data with The Observer XT. This is done by sending a synchronization signal from the Observer XT PC to the external DAQ system. This synchronization signal contains time information from The Observer XT PC. This time information is used to synchronize the event log data and the associated external data after import of the external data file. There are two types of synchronization signals: - The On-Off synchronization signal - The Time Code (TCAP) synchronization signal The preferred Signal Type depends on how the external data are sampled by the DAQ system. The On-Off Synchronization Signal Use the On-Off signal in the following situations: - The sample rate of the DAQ system is lower than 10 Hz. - The collection of external data is uninterrupted. - You use the Noldus mini USB-IO box for the synchronization signal. --- ## The Observer XT 17 - External Data - Import External Data Files with Missing Samples URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-external-data-import-external-data-files-with-missing-samples Chapter: The Observer XT Import External Data Files with Missing Samples Aim To import external data files that contain gaps. Prerequisites - Your license for The Observer XT includes the External Data Module. - The time series has a resolution of at least one decimal more than the resolution of the sample rate. So with a sample rate of 1 Hz, the time stamps are in seconds with at least one decimal. - The file contains no entire empty rows. - The file contains a column with time stamps. - The file is exported as a text file. Create an Import Profile for a Data Set with Missing Samples - Follow the general procedure in Create an Import Profile. - In the Import profile definition window, drop the column with the time information in the Time series cell. Do not use the Sample rate or Sample interval option. - If your data set contains missing samples indicated by non-numeric symbols, specify this symbol and select the Treat as number checkbox. Alternatively, click the button next to the Treat as number field to select one or more predefined symbols. To select a specific text, click , click OK and enter this text after a comma (,). If text is identified by a character, select this from the Text qualifier list. Import a Data Set with Missing Samples - Follow the procedure in Import External Data as Text Files to import the dataset. - Choose the import profile you created for the dataset with missing samples. The following warning appears. - Choose Import and ignore and click OK. Notes - Missing samples may indicate that something is wrong with the setup of your DAQ system. - The missing samples are converted into a NaN value, which are not present in the visualization and are ignored in the analysis. Import Heartbeat Intervals Introduction Heartrate interval data by definition have a variable sample rate and do not meet the specification to import them as a text file. Heartbeat interval data can be imported as numerical modifiers. You can follow this procedure to import other data as well that do not meet the requirements to import them as external data. Procedure - Open the heartbeat file in Excel. - Depending on the format of your Interbeat interval data file, either merge the time and millisecond columns, or create a time column and calculate the time stamps from the interbeat intervals. If not present already, add a column with the behavior IBI. Add a column with a sequence 1-2-1-2-1-2-1-2 etc. - Save the new file as a text file. - Close the text file before you proceed with the next steps. - In The Observer XT, open the observation in which you want to import the IBI file. - Click the Import data button on the toolbar, then select Import Observational Data. - Click Custom Import Profiles > Create New. - Click Browse and open the file with interbeat intervals that you have edited in Excel. The file appears in the Import Profile Definition window. Select Tab and Space under Select Data Delimiters and drag-and-drop the correct columns under Data Sets to the Time, Behavior, and Behavior Modifier columns. Do not drag the column with the actual interbeat interval data. - Click Save As, give the import profile a name and click OK and then Close. - In the Import Observational Data window, select the IBI file (*.txt) that you have edited in Excel. - Select State Events under Treat new Behaviors as, and make sure that the correct import profile is selected under Files of type. Click Open. - The new event log opens. Click the Offset button on the toolbar and choose Numerical offset. - Change the offset of the imported event log to 0:00:00.000 or the same time as the others. Click OK. - Open the visualization and check that all files are displayed (manual events, IBI and HRA). - If necessary, synchronize the imported data relative to the video. To do so, look at the video and find out when the physiological data recording device started recording. Adjust the time in the File Synchronization window. Notes - If HR recording started before starting video capture, the time shift for the IBI data is negative (e.g. if it started 10 seconds earlier, -0:00:10.000). - If part of the data are not shown (for example, the first part of the IBI data that have been shifted before the start of the video), data were collected before you started video capture and may not be critical. However, if you want to show them from the very start, change the Start of the Observation in the Independent Variables window. How IBI Data Are Shown In the Coding Scheme When you import the first IBI data file, the coding scheme shows a behavior IBI under a group named Behavior 1. The modifiers 1 and 2 are shown in the Modifiers view. They refer to the right-most column in the imported file. These modifiers are not used in analysis. In the Visualization The IBI are state events. The vertical bars inside the colored bar represent starts of the states (heart beats). The bar is single colored as the behavior is just one (IBI). In the Statistics To calculate statistics on the duration of IBIs: - Choose Analyze > Behavior Analysis > New > Calculate. - Click Layout and de-select Modifiers. - Double-click Behaviors and de-select the behaviors you are not interested in. - Click OK. Under the behavior IBI you find the corresponding statistics. Source: The Observer XT 17 Help - External Data, Noldus Information Technology --- ## The Observer XT 17 - External Data - Importing External Data Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-external-data-importing-external-data-files Chapter: The Observer XT Importing External Data Files Time Information - Sample Rate - If the header contains a cell with the sample rate, select the Sample rate button in the Profile definition section. Drag the cell with the sample rate to the Sample rate box and select the appropriate unit (Hz or kHz) from the list. - Sample Interval - If the header contains a cell with the sample interval, select the Sample interval button in the Profile definition section. Drag the cell with the sample interval to the Sample interval box. Select the unit of time from the list. - Time Series - If the header does not contain information on sample rate, select the Time series button under Timing based on. Under Data sets in the File content section, select the column with time stamps and drag this to the Time series box. The column with time stamps now appears grayed. The Select Time Format window opens. If the time matches one of the predefined formats, The Observer automatically selects one. Converted time shows the conversion of the text to time and Conversion is OK. You can also define your own format by typing an H for each number representing 'hour', an m for 'minute', an s for second and a f for each decimal of a second. Under Import Time, select one of the options: - Relative to Time Zero - Suppose the first row in the imported external data set has time 00:00:05. When the option Relative to time zero is selected, the time stamp of the first row of the imported data set will remain 00:00:05. - Relative to the Time of the First Data Line - Suppose the data set you want to import starts at 14:28:00 and has samples every 5 seconds. With this option, the first row of the imported data will get the time stamp 00:00:00. The second row will have time stamp 00:00:05. The options under Import Time are grayed out when your time stamps contain the date the file was created. In this case the option Relative to time zero is used. Select the option Allow timestamps to be non equidistant when the time stamps do not represent regular intervals. For example, 0, 490, 572, etc. Data Under Data definition in the Profile definition section there are two parts. The lilac part is labeled Header Data where you drag cells from the lilac Header section. The green part is labeled Raw data where you drag Data sets from the green cells in the Data sets section. - Drag the first column under Data Sets to the first empty cell in the Raw data - Data Set column. As a result, the letter of the original column appears in the cell and the column in the Data Sets section is grayed. - Locate the data set name, the unit and, optionally, other information in the header and drag those cells to the Header data cells in the same row. If you drag and drop the Start Date and/or Start Time, a window opens in which you can define the format. Accept the default format, or see the Time Information section for the procedure to change it. Multiple Data Sets - Follow the procedure above to define the next dataset. Once two datasets are defined, the Validity Check button becomes active. - Click this button. The Observer XT now automatically fills the other rows in the Data definition field. - Check that the correct columns are selected. How the Validity Check Is Applied The Observer XT assumes that your header and data set info are ordered in a regular way in your external data file (e.g., left-right, with or without empty cells in between). Example - your external data file contains four Data Sets in columns A, C, E and G. Columns B, D, F are empty. When you drag columns A and C to the first two rows in the Raw Data column and then click the Validity Check button, The Observer XT automatically assigns columns E and G to rows 3 and 4, taking into account the empty columns between Data Sets. The distance between the columns should be the same. For example, dropping columns A and C and clicking Validity Check works — columns E, G, I, K etc. are automatically added to the other rows. Dropping columns A and B and clicking Validity Check also works. However, dropping A, B, and D and clicking Validity Check does not work, because there is an empty column between B and D, but not between A and B. Save the Import Profile When all the information is in the Import Profile Definition sheet, click the Save As button and give the profile a name. Import a Text File with the New Import Profile The newly created import profile is now in the Files of Type list. - Locate the external data file and select the filename. - Click Open. Edit an Import Profile - Choose File > Import > External Data. - Click the Custom Import Profiles button, choose the profile and click the Edit button. - Browse to the external data file you want to base the profile on. Change the profile as needed. To change cells that were dragged and dropped, click the cell you dropped information into and press the Delete key on your keyboard. - When done, save the profile. --- ## The Observer XT 17 - External Data - Manual Synchronization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-external-data-manual-synchronization Chapter: The Observer XT Manual Synchronization Aim To synchronize the external dataset manually with the event log and the videos. Prerequisites - Your license for The Observer XT includes the External Data Module. - You did not use automatic synchronization with a synchronization signal to acquire your external data. See Set Up Your Experiment with Synchronization Signal. Procedure There are three methods for manual synchronization: - Numerical offset – If you know how many seconds the observational and external data are out of sync. - Manual offset – For visual synchronization. Use this method when you score from a media file and the start of the observation or external data acquisition is signaled by a visual or auditory cue. For example, you counted down until you pressed the Start button in the DAQ system and you can hear this on the recorded video. See also Set Up Your Experiment with Stand-Alone External Data Acquisition. - Change the start or stop time with manual import. Numerical Offset - Open the observation in which you imported the external data. - On the component toolbar, click the Offset button. - Select Numerical Offset to open the File Synchronization window. - Synchronize the files by entering the offset values. For example, if you started your observation 3 seconds before you started acquisition of external heart rate data, enter 3.00 for the heart rate. The external data stream now starts 3 seconds after the event log. Manual Offset - Open the observation in which you imported the external data. The current position in the event log is highlighted in blue and a red vertical line in the External Data window indicates the current position. - Click the Offset button on the toolbar and choose Manual offset. A window appears with instructions on how to set the offset in a video, audio file, or external data window. - Click Start Synchronization. - Click the External Data window; the border of this window turns red and the cursor becomes an offset icon. - Keep the left mouse button pressed to drag the graph window to the left or the right to the point where the external data match the event or the video frame. - Click the Offset button on the toolbar once more to finish synchronization. Change the Start or Stop Time with Manual Import When you import external data and choose Manual import (see To Import a Specific Data Set), a window with data sets appears together with the Independent Variables list. In the window with data sets, edit the Start time or Stop time cell. By changing the start time you set the offset of a file. By changing the end time and/or start time you set the gain by stretching or shrinking your file. Import External Data, Special Cases What do you want to do? - Create an Import Profile - Import External Data Files with Missing Samples - Import Heartbeat Intervals Create an Import Profile Aim To import external data as text files when The Observer XT does not have a predefined import profile (see step 2 in Import External Data as Text Files). With an import profile you create a template based on the structure of the external data file. Prerequisites - Your license for The Observer XT includes the External Data Module. - You exported your external data as text files. Procedure - Choose File > Import > External Data. - Click the Custom Import Profiles button and then the New button. - Browse to the external data file. - Build the import profile by specifying the structure of the data file. This is done by dragging and dropping cells. To undo a selection, select the cell to which content was dropped and press Delete. Follow the procedure in these sections: - Header - Delimiters - Time Information - Data - Import a text file with the new import profile. 1 - Header The Observer XT usually automatically detects header and data information in the file. If not, specify which part of the data file contains the header. Choose an option from the Header detection list: - Automatic (default) – The Observer XT is set to automatically detect the header and data sections in the data file. Choose one of the other options if automatic header detection does not work. - Specify tag – Select this option if the data file has a variable number of header lines and the header always ends with the same word. Specify the phrase (with either nominal or numerical information) that indicates the end of the header part of the file. If necessary, also specify the number of rows between the header line that contains this phrase and the data. For example, if the header always ends with a line containing the text [Data] and after that line there is always an empty line before the data starts, enter [Data] in the End tag field and 1 in the Extra rows field. - Specify row number – If the data file always has the same number of rows in the header, select this option and specify the number of header rows. 2 - Delimiters The Observer XT uses the comma as the default delimiter to separate text in the header and data sets. However, the data file may have other delimiters. If this is the case, select the correct ones from the Select header delimiters and Select data delimiters lists. You can also select multiple delimiters. Some DAQ software enables you to select the type of delimiter when saving the DAQ data to an ASCII export file. In that case, select the same delimiter in the File content section of the Profile Definition window. A comma or semicolon are advised as delimiters. 3 - Time Information Specify which cell or column contains the time information. This can be a column with time stamps, a cell with the sample rate, or a cell with the sample interval, which is the time between samples. Drag and drop the cell or column with time information to the appropriate field in the Profile definition section. - Sample rate – If the header contains a cell with the sample rate, select the Sample rate button under Timing based on in the Profile definition section. --- ## The Observer XT 17 - External Data - The On-Off Signal URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-external-data-the-on-off-signal Chapter: The Observer XT The On-Off Signal The On-Off signal coincides with the start and stop of an observation. The Observer XT sends a 'one' at the start and a 'zero' at the stop of an observation. When you use the On-Off signal you need to start the DAQ system before you start an observation and switch it off after the end of your observation. The Time Code (TCAP) Synchronization Signal Use the TCAP signal in the following situations: - When the DAQ system uses scheduled sampling, i.e., when sampling is carried out at set intervals (for example, 5 minutes every hour). - When the sample rate of the DAQ system is higher than 10 Hz. With the Time Code signal, The Observer XT continuously sends encoded pulses of zeros and ones to the DAQ system during an observation. Each pulse (consisting of 60 bits) contains time and date information in the initial bits. Pulses and the empty spaces between pulses are evenly divided over time. When you use the Time Code signal during an observation, you can start acquisition of physiological data any time during that observation, because the DAQ system can 'catch up' with The Observer XT based on the time and date information in each pulse. The external data are saved in the computer dedicated to the DAQ device, not in the PC with The Observer XT. The Observer XT PC only records the manually coded data (events). During the observations, you do not see the external data on your Observer screen. It is possible to import data sets from more than one DAQ system, each with its own TCAP signal. Import External Data What do you want to do? - Import External Data as Text Files - Import European Data Format Files - Manual Synchronization Import External Data as Text Files Aim To import external data that were exported from your DAQ system as text files. Prerequisites - Your license for The Observer XT includes the External Data Module. - You acquired the data with your DAQ system. - You exported the data from your DAQ system as a text file. Procedure - Choose File > Import > External Data, or in the observation, click the Import Data button on the toolbar and choose Import External Data. - The Import External Data window opens. The Observer XT contains import profiles for text files from several DAQ systems. Select your system from the Files of type list. Next, select the external data file. If your type of file is not in the list of predefined files of type, you can create an import profile, or contact Noldus Support to make one for you. - Next to Import to, select an existing observation from the list or choose New observation. - To import the complete file including all data sets, click Open. To import specific data sets from the external data file, continue with the steps below. To Import a Specific Data Set If your external data file contains more data sets than you want to import: - Follow the instructions above until step 3, then click the Manual import button. A new Import External Data window opens showing the data sets. The Independent Variable List also appears. - Select one or more data sets and drag-and-drop them to the observation in the Independent Variable List window. If The Observer XT sent a synchronization signal to the DAQ system, make sure you import this data set as well. The row containing this signal has a clock icon on the left side. If not, right-click the first cell in this row and select Sync Data Set. - Click Import. - If you used the DAQ system stand-alone, and therefore did not let The Observer XT send a synchronization signal, continue with Manual Synchronization. Import European Data Format Files Aim To import European Data Format (EDF) and BioSemi Data Format (BDF) files. Background European Data Format (EDF) and BioSemi Data Format (BDF) are standard binary formats to store and exchange physiological data. BDF is the 24-bit version of EDF, which is 16-bit. Many systems to collect physiological data can export to EDF or BDF. Prerequisites - Your license for The Observer XT includes the External Data Module. - You exported your external data as EDF or BDF files. Procedure - Open the observation that you want to import the data into. - Click the Import data button on the toolbar and select Import European Data Format Files. Alternatively, choose File > Import > European Data Format Files. - Locate the file and click Open. You can now: - If necessary, synchronize the imported data with the event log. See Manual Synchronization. - Select data based on the value of the imported data. See Select Intervals by External Data in Select Data for Analysis. - Visualize the imported data. See Visualize External Data in Visualize Data. - Analyze the imported data with Numerical Analysis. See Calculate Statistics. Notes - Importing European Data Format files with a synchronization signal from The Observer XT was not tested. Therefore, we recommend exporting text files instead and importing these if you want to synchronize with a synchronization signal. See Import External Data as Text Files. - If you do not have an observation open, a new observation will be created. - Importing EDF+ or BDF+ files that contain annotations is not supported. --- ## The Observer XT 17 - File Management - Create a Multiple Coding Station Configuration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-create-a-multiple-coding-station-configuration Chapter: The Observer XT Create a Multiple Coding Station Configuration Aim To create a main project on a computer with a full license of The Observer XT and collect data from a number of coding stations with a coder license. You export the data from the coding stations and import them into the main project. Prerequisites - You have one full license of The Observer XT. - You have at least one coder license for The Observer XT. - You created a project with a coding scheme on the main Observer XT computer. - You installed The Observer XT on the coding stations. Procedure To Copy the Project to the Coding Stations - On the main Observer XT computer, choose File > Save Project as Template. See Save a Project as a Template. - Copy the template project to each coding station. If you copy the template project to the Templates folder of The Observer XT, the program automatically locates the template. By default the location of this folder is: C:\Users\Public\Public Documents\Noldus\The Observer XT\Templates. - On a coding station, start The Observer XT and choose File > New Project From Template. - If the project is stored in the Templates folder, the correct location is selected automatically. Otherwise browse to the correct location. - Click the Select button and open the template project (*.otb). - Repeat steps 2–5 for all coding stations. To Code on the Coding Stations Create observations, enter independent variables, and code, like in a project with a full license. See Carry Out an Observation. To Copy the Observations to the Main Project - On each coding station, choose File > Export > Observational Data. Choose the observations to export and specify whether you want to export external data and media files. Make sure that ODX files from different coding stations have unique names (for example: Coding Station 1 File 0001.odx). - Copy the ODX file from each coding station to the main PC. - In the main project, choose File > Import > Observational Data. The observations are imported in the main project, including the observational data, the independent variable values and the coding scheme. See Import Observational Data. Notes - If you open a template project in the Coder License version of The Observer XT, the name of the project is [name of template project] - sub. - The Project Setup, Coding Scheme and Independent Variables in the new project are locked on the coding stations (indicated by a lock icon in the Project Explorer). - We recommend also locking the settings of the main project, to make sure the settings stay the same. To do so, choose Setup > Lock Configuration. Import External Data Supported Formats External data can be imported as .txt files and as European Data Format (EDF) and BioSemi Data Format (BDF) files. Your license must include the External Data Module to be able to import external data. - Text files – See Import External Data as Text Files. - EDF and BDF files – See Import European Data Format Files. Import Viso Sessions Aim To import sessions made in the Noldus video recording program Viso into The Observer XT. Prerequisites - You have a license for Viso that includes the Annotation Module. - If your Viso license includes User Management, your user role allows import of Viso sessions. - You recorded sessions in Viso. - The computer with The Observer XT is in the same network as the Viso computers. Procedure - Choose File > Preferences > Viso Settings. - Enter the IP address of the computer with Viso Services in the Services address field. Do not change the Services port 5672, unless this was also changed in Viso. - Click the Test connection button. If the two computers are connected properly, the Status Connected appears. - Choose File > Import > Viso Sessions. - Enter the login details for your Viso account. - Select the sessions and import them. Notes - The Viso subjects, markers and remarks are imported into the coding scheme and event log. Viso subjects are imported as subjects, markers are imported as behaviors without duration (point events) and remarks as comments in the event log. - If the computers are in different networks, export the sessions in Viso to The Observer XT and import the sessions (*.odx) as observational data into The Observer XT. See Import Observational Data. - For more information on Viso sessions in The Observer XT, consult the Viso Help. --- ## The Observer XT 17 - File Management - Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-data Chapter: The Observer XT Data Assign Data Set information to the corresponding columns in the Data definition part. - Missing Samples – If your data set contains missing samples indicated by non-numeric symbols, you need to specify this symbol first. If you do not do this, The Observer XT will interpret the symbols as indicating that all the file up to that point is the header. Select the Treat as number check box. Type in the non-numeric symbol in the Treat as number field or click the button next to it to select one or more predefined symbols. To select a specific text, click > OK and enter this text after a comma (,). If text is identified by a character, select this from the Text qualifier list. - Time – Drag-and-drop one of the cells containing time stamps to the Time column. The Select Time Format window opens. Under Select Format, select a Numeric Value or a Date/time format. Click OK if the Converted time shows the right format and Conversion is OK. Under Import Time, select one of the options: - Relative to time zero – Suppose the first row in the imported event data set has time 00:00:05. When the option Relative to time zero is selected, the time stamp of the first row of the imported data set will remain 00:00:05. - Relative to the time of the first data line – Suppose the event data set you want to import starts at 14:28:00 and samples every 5 seconds. With the option Relative to the time of the first data line, the first row of the imported event data will get the time stamp 00:00:00. The second row will have time stamp 00:00:05. - Subject, Behavior, Modifier, Comment – Drag-and-drop cells containing information on Subject, Behavior, Modifier and Comment from the Data Sets sheet to the corresponding column in the Data definition sheet. To import multiple modifiers, select multiple modifier columns in the Data Sets group and drag them to the Modifier column in the Data definition group. The modifiers placed in different columns in the import file will be automatically organized in separate groups in the coding scheme. Event Type – If the import file contains a column that specifies whether the event line is a start/stop of an event, drag this column to the Event Type column in the Data definition group. In the Define Event Keywords window that appears, under Keyword enter the text that identifies the start of a state event (with duration), the stop of a state event and the point event (without duration) in the import file. Click OK to confirm. Save the Import Profile When all the information is in the Import Profile Definition sheet, click the Save As button and give the profile a name. Import a Text File with the New Import Profile The newly created import profile is now in the Files of Type list. - Locate the data file and select the filename. - Click Open. Edit an Import Profile - Choose File > Import > External Data. - Click the Custom Import Profiles button. - Select the Import Profile from the list and click Edit. In the Select Sample File group, you see the original sample file next to Profile based on. - Browse to the original, or a new observational data file and click Open. - Follow the general instructions in Procedure to create an import profile. - When done, click Save Profile As. - Enter a name and choose OK > Close. - Select the new import profile from the Files of Type list. - Select the observational data file and click Open to import the data. Notes - If the import file contains data collected with Instantaneous Sampling, the Define Event Keywords window does not recognize the samples. We advise you to import sample data as ODX files. See Import ODX Files. - If you add datasets to the Event Type columns, the Treat new behaviors as option (see Import Observational Data) is disabled because the program recognizes events automatically. - To import data with Chinese, Japanese, or Cyrillic characters or characters like "ü" or "ç", make sure that the import file is Unicode UTF-16 encoded. - To import data recorded with Instantaneous Sampling, see Import ODX Files. - You cannot specify the type of modifier which is imported. If you import multiple modifiers of different types, all modifiers are imported as Numerical 'range' Modifiers. --- ## The Observer XT 17 - File Management - Export External Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-export-external-data Chapter: The Observer XT Export External Data Aim To export external data to an Excel file (*.xlsx) or a text file (*.txt). Export of external data can be done either with or without the associated event data. Prerequisites Your license must include the External Data Module. Procedure - Select one of the following options: - To export external data from multiple observations at once, choose File > Export > Observational Data. In the window that opens, choose Excel or Other software. Then select the observations to export. - To export a specific observation, open the observation. Then click the Export current observation button on the toolbar and choose Excel or Other software. - To export external data selected in a Data Profile, open that Data Profile and choose Analyze > Select Data > Export Selected Data. - If you also want to export event data, select your observations in the Observations tab. - If you want to exclude event data from the export, make sure you select the option Export external data only and exclude event data described in step 5 below. - In the External Data tab, select the external data signals you want to export. - Under Export options, you can select the following: - Export external data only and exclude event data – If you select this option, no event data are exported. - Point events with the same time-stamp are exported in: - One column – If you select this option, point events and instantaneous samples that have the same time-stamp after resampling are exported to one column and separated by commas. Select this option if you have used point events as markers. - Separate columns – If you select this option, point events and instantaneous samples that overlap in time after resampling are exported each to a separate column. Select this option if you have used point events to score behaviors and want to analyze point events. - Missing value symbol – If the external data file contains missing values, you can select "Blank", "NaN", "–", or "." to replace the missing values. Missing values are ignored in the external data statistics. - Resample options: - External data sample rate – Here you can select one of the available sample rates (Hz) based on the selected external data signals. By default, the lowest available sample rate is selected. - User defined sample rate – Here you can enter a user-defined sample rate (possible range between 0.001 and 2000 Hz). Notes - If you export external data and event data combined, the time basis (that is, time-stamps at regular intervals) of the external data is used in the export file. - The option Point events with the same time-stamp are exported in is not available if you have selected the option Export external data only and exclude event data. - Columns are separated by the list separator that you can select under Export options in the Observation tab. How Combined External Data and Event Data Are Exported - Event data and external data are resampled based on the sample rate you select. This makes time-stamps equidistant for both external and event data. - For an event with duration, the value at a sample is exported. - For a point event (without duration) and an instantaneous sample, the value at the next sample after the event time of the point event or instantaneous sample is exported. If a point event was scored more than once between two samples, only the last value is exported at the next sample. - Each Subject–mutually-exclusive Behavior group combination is exported to a separate column, including modifiers. Each Subject–start-stop Behavior group combination is exported to a separate column. - Observations are written as contiguous blocks above each other without empty rows in between. - Each independent variable is exported to a separate column. Independent variables with event log or subject scope are exported to separate columns. For example, when you have an observation with two event logs and an independent variable "Task", this results in two separate independent variable columns with headings "Task/Event Log 1" and "Task/Event Log 2". - The same columns are exported as when you export event data, except for the columns Durations (s), Event Log, Event type, and Comments. --- ## The Observer XT 17 - File Management - Export Observational Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-export-observational-data Chapter: The Observer XT Export Observational Data The aim is to export logged events and related data. You have the following options: - Export data to The Observer XT data files (*.odx) – To transfer event data from one project to another with The Observer XT data files (*.odx). - Export data to Excel files (*.xlsx) – To export event data including external data to a Microsoft Excel workbook (*.xlsx) for further analysis. - Export data to text files (*.txt) – To export event data including external data to other software for further analysis. Also use this option to export part of your event data selected in a data profile. Export Data to The Observer XT Data Files (*.odx) - To export event data to Observer XT ODX files, choose one of the following options: - Export multiple observations at once – Choose File > Export > Observational Data. In the window that opens, choose The Observer XT, then select the observations to export. - Export a specific observation – Open the observation, click the Export current observation button on the toolbar, and choose The Observer XT. - Under Export options, choose one of the following as needed: - Include media files – To include a copy of each media file associated with the observations in the same folder as the ODX file. - Include external data – To include a copy of the external data files (*.pbi) associated with the observations. This option is only available if your license includes the External Data Module. - Create separate file per observation – To export each observation to a separate ODX file. Otherwise, all observations are exported to a single ODX file. - Click OK. - Enter a name and file location and click Export. What an ODX File Contains Observations All selected observations are included in one ODX file. If an observation contains multiple event logs, these are all included in the ODX file. You cannot choose to export some of the event logs from an observation. ODX files also contain the coding scheme, the coding scheme settings, the values of independent variables for the exported observations, event logs and subjects, and the current Project Settings for those observations. Media Files The ODX file contains the path to the media files associated with the observations. Even if you choose not to include those media files in the ODX file, when you import the observations to another project, the program can find your media files and re-link them to the observations provided that the media files are on the same computer or a network server. See Import Media Files. External Data The ODX file contains a link to the location of the external data files associated with the observations, not the external data itself. When you next import the observations into another project, make sure that the external data folder contains those files otherwise the program cannot open them. To do so, locate the file with the extension *.pbi in the folder to which you exported the observation. Create a new project and save it. Then close the new project and copy the *.pbi file to the folder /External of the new project. Do not rename this file. Now re-open the new project and import the ODX file. The external data are now imported together with the observational data. Export Data to Excel Files (*.xlsx) - To export event data to an Excel file, you have the following options: - Export multiple observations at once - Choose File > Export > Observational Data. In the window that opens, choose Microsoft Excel. - Export a specific observation - Open the observation. Then click the Export current observation button on the toolbar and choose Microsoft Excel. - Export event data selected in the currently active Data Profile (indicated in blue and bold in the Experiment Explorer) - Choose Analyze > Select Data > Export Selected Data and then Microsoft Excel. - In the Export Observational Data window, in the Observations tab, select the observations you want to export. - If your project contains external data, the Export Observational Data window also contains an External Data tab. See Export External Data. - Under Export options, select the following: - Create a single sheet with all observations – all observations are exported to a single Excel sheet. - Create separate sheets per observation – each observation is exported to a separate Excel sheet. - Create separate files per observation – each observation is exported to a separate Excel file. - Include user-defined Independent Variables – the user-defined Independent Variables are added to the export file. - Click OK. - Enter a name and click Export. Export Data to Text Files (*.txt) - To export event data to a text file, you have the following options: - Export multiple observations at once - Choose File > Export > Observational Data. In the window that opens, choose Other software > OK. - Export a specific observation - Open the observation. Then click the Export current observation button on the toolbar and choose Other software. - Export event data selected in the currently active Data Profile (indicated in blue and bold in the Experiment Explorer) - Choose Analyze > Select Data > Export Selected Data. - In the Export Observational Data window, in the Observations tab, select the observations you want to export. - If your project contains external data, the Export Observational Data window also contains an External Data tab. See Export External Data. - Under Export options, select the following: - List separator – the selected list separator (comma, semicolon, tab or space, or the default Windows list separator) is used in the text file to separate columns. You can find and change the default Windows list separator in the Control Panel. Go to Region and Language and click Additional Settings. - Include user-defined Independent Variables – user-defined Independent Variables are added to the export file. - Create separate file per observation – each observation is exported to a separate text file. Otherwise, all observations are exported to a single text file. - Click OK. - From the Save as type list, select Unicode Text (in case your data file contains Chinese/Japanese/Cyrillic characters, or characters like "ä", "õ" etc.) or ANSI Text (in all other cases). Choose ANSI if you want to import your data into SPSS. - Optionally, change the file name and file location and click Export. --- ## The Observer XT 17 - File Management - File Locations URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-file-locations Chapter: The Observer XT File Locations General Folders The default application folder of The Observer is: C:\Program Files\Noldus\The Observer XT 17 You can change the application folder during installation. Your The Observer XT files are stored, by default, in: - C:\Users\Public\Public Documents\Noldus\The Observer XT\Projects - C:\Users\Public\Public Documents\Noldus\The Observer XT\Video files - C:\Users\Public\Public Documents\Noldus\The Observer XT\Audio files - C:\Users\Public\Public Documents\Noldus\The Observer XT\Templates Project-Level Folders Each project you make has its own folder. It is named as the project and contains the following subfolders: - Analysis Results — with the analysis results files (*.arx). - Episode Selections — with the episode selection files (*.esr). - Event Data — with the binary observational data files. - Export — with the exported files (*.odx, *.txt, *.xls). - External — with the imported binary external data, or imported European Data Format Files (*.pbi). - Intermediate — with files created by the external data analysis. - Plug-ins — with settings of installed external plugins. Other Folders Import Profiles The profiles for import of observational (*.oip) and physiological data (*.eip) are stored in: C:\ProgramData\Noldus\Common\Profiles Log and Dump Files The Observer continually records computer events to a log file. If you encounter problems using the software, the Technical Support Department may ask you to send two files: the log file Observer.log and the dump file The Observer XT 17.dmp. These are stored at: - Log file — C:\ProgramData\Noldus\The Observer\XT 17\Log - Dump file — C:\Users\\AppData\Local\Temp\ Recover Data Temporary Project When you open a project, The Observer XT creates a temporary copy of the entire project folder in: C:\ProgramData\Noldus\The Observer\XT 17\Temp The ProgramData folder is usually hidden. To show it, open Windows Explorer and select Hidden files from the View menu. The name of the temporary copy is the same as the project folder, but with a tilde (~) at the front. This folder contains the file ~[project name].vop and ~[project name].bkp. When you save a project, all files from the temporary copy are copied to the original project folder. When you score observational data, data are saved every new event line to the temporary copy. When you save the project, the new data are saved in the original project folder. The temporary copy only contains files created by The Observer XT. Other files, such as video files, are not copied to the temporary folder. The temporary copy can be used to restore a damaged project. Contact Noldus support if this is needed. Autosave The Observer XT by default automatically creates a temporary backup every five minutes. To change this, choose File > Preferences > Auto Recovery and specify the settings. Backup in Windows 10 and Windows 11 Besides the Backup function in The Observer XT (to back up single projects), you can use the File History function of Windows 10 and 11 to back up multiple projects automatically. - Include your project folders in a Library. To do so, open Windows File Explorer, right-click the folder you want to back up, for example the entire Noldus\The Observer XT folder. Select a library, or choose Create New Library to make a new one. - Connect your computer to a network drive or an external hard disk. - In the Apps window, type File History. - Click the File History tile that appears. - Choose a drive for the backup. - Choose Advanced Settings, then choose how often the changed files are backed up and how long the files are kept. - Choose Exclude Folders and select the folders to leave out of the backup. - Click Turn On. Notes: - To restore the backed-up library, click Restore Personal Files. Use the arrow keys at the bottom to select the correct version and click the Restore button. - To create a backup of an individual project, choose File > Backup in The Observer XT. Source: The Observer XT 17 Help - File Management, Noldus Information Technology --- ## The Observer XT 17 - File Management - File Management URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-file-management Chapter: The Observer XT File Management What Is File Management File management involves the handling of different types of files that you can open, save, rename, import or export. File management also involves the settings for file locations. Important Notes - To store your project at a secure location, create a backup of a project and store the *.vpb file. Copying files from the Project folder, for example only the *.vop file, does not copy the entire project. Create a backup of your videos as well. - Carry out all your file management in The Observer XT Project Explorer. If you delete, move or rename files using the Windows Explorer, The Observer XT may not be able to find the files again (because The Observer XT files contain references to other files). - Never shut down the computer by pressing the power button or cutting off the electricity. Your project data may become lost, even after you saved your project. Always use the Windows shut down feature to close your computer. File Types File types that can be managed in The Observer XT are: - Project files (*.vop) – See Open a Project - Project backup files (*.vpb) – See Create a Backup of a Project - Template projects (*.otb) – See Save a Project as a Template - Observational Data (*.odx from The Observer XT, or other observational data in text format) – See Export Data to The Observer XT Data Files (*.odx) and Import Observational Data - External data – See External Data and Import External Data - European Data Format files (*.edf; *.bdf) – See Import European Data Format Files - Media files (*.avi, *.mpg, *.mpeg) – See Import Media Files - Analysis Results (*.arx, or *.arm from previous versions) – See Manage Analysis Results - Episode Selections (*.esr) – See Export Episode Selections - Independent Variables – See Export Independent Variables Main Topics - Manage Projects - Export Observational Data - Export Independent Variables - Export Episode Selections - Export External Data - Export Data to Text Files with the Find Function - Import Observational Data - Create a Multiple Coding Station Configuration - Import External Data - Import Viso Sessions - Import Media Files - Manage Analysis Results - Export Independent Variables - File Locations - Recover Data --- ## The Observer XT 17 - File Management - How Event Data Are Exported URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-how-event-data-are-exported Chapter: The Observer XT How Event Data Are Exported Each event is exported with its original time stamp. All start and stops are exported, also for mutually exclusive behavior groups. For each behavior, the event type is indicated in a separate column. Coding scheme elements (Subject, Behavior, Modifier) that were not scored for any of the exported observations are not included in the text file. Modifiers of the same group are put in the same column. All observations contain the same number of modifier columns. Event logs of the same observation are merged. Observations are written as contiguous blocks above each other without empty rows in between. The following columns are exported to both the Excel and text file: Date/Time Columns - Date_Time_Absolute_dmy_hmsf – the day, month, year, hour, minutes, seconds with three decimals. - Date_dmy – the date (day - month - year) belonging to the absolute time. - Time_Absolute_hms – the hours, minutes and seconds belonging to the absolute time. - Time_Absolute_f – the decimals belonging to the seconds of the absolute time. - Time_Relative_hmsf – the time since the start of the observation in hours, minutes, and seconds with decimals. - Time_Relative_hms – the hours, minutes, and seconds belonging to the relative time. - Time_Relative_f – the decimals of the seconds belonging to the relative time. - Time_Relative_sf – the seconds with decimals belonging to the relative time. Other Columns - Duration_sf – the duration of the current state in seconds with decimals. - Result Container – this column is only present if you exported the data selected with a Data Profile (Analyze > Select Data > Export Selected Data). It contains the name of the result container in the Data Profile. - Observation – the observation name. - Event_Log – the event log name. - Coding scheme element columns (if scored) – behaviors, subjects or modifiers. - Event_Type – State start, State stop, Point, Sample, Suspend, Resume. - Comment – only present when comments were scored. - Independent Variable. Notes on Export of Event Data - To export media files and external data together with observational data, choose ODX as export format. See Export Data to The Observer XT Data Files (*.odx). - Default name – the suggested name of an exported text file with multiple observations consists of the [Project name] - [first selected observation name] - [last selected observation name] - "Event Logs". Export Independent Variables Two Export Files Independent variables are exported in two files. One file contains the header with variable names and their properties. The other file contains the actual values of the variables for each combination of observation, event log and subject. - Choose File > Export > Independent Variables. - Browse to the folder where you want to store the variable list. - In the File base name field, enter a name. The file name will start with this name. - Select Unicode or ANSI from the Encoding list. - From the List separator list, select the column separator you require. By default, Windows default list separator is selected. - Click Save. Structure of the Export File The values file contains the values of all independent variables, including those you chose not to display in the Independent Variables List. See Show/Hide Variables in Set Up Your Project. Each combination of observation, event log and subject is written in a row. Values of variables with Subject scope are written in those rows. If a variable has Event log or Observation scope, it gets an additional row. Values of such variables are written in those rows. All other cells are filled in with missing values (""). See also Variable Scope in Set Up Your Project. Example: The project contains six observations, each with one event log. The independent variables include the user-defined variable Patients file and Observer with Observation scope. For Observation 1, the export file opened with Notepad contains the following: - A – First line containing the variable names. - B – A line specifying the event log. In this file there are no variables with Event Log scope, thus all values for this line are "". This line does not contain the subject names. - C – A line specifying the observation. This line contains the values of the system variables, since those have Observation scope. It also contains the variable values of the user-defined values with Observation scope. If the coding scheme also contained subjects, the export file would contain extra lines for each subject. Export Episode Selections Aim To export the data selected in an Episode Selection. Prerequisite You created an Episode Selection. Procedure - Choose what to export: - To export all episode selections at once, choose Analyze > Episode Selection > Export. - To export a single episode selection, click the Export Selected Data button on the toolbar. - Browse to the folder where you want to store the episode selections. - In the File base name field, enter a name. The export file name will start with this name. - Select whether you want the files to be exported as Unicode (UTF-16) (choose this if your export file contains Chinese, Japanese, or Cyrillic characters, or characters like "ä", "õ" etc.) or ANSI text files from the Encoding list. - Select the column separator you require from the List separator list. By default, Windows default list separator is selected. - Click Export. Notes - Default folder – by default, The Observer opens the Export folder of your project. - If you have set roll-on and roll-off times, the samples within these intervals are also exported. - Exporting multiple episode selections – the name of each text export file is: [Base filename]-[Episode Selection name] (#).txt. --- ## The Observer XT 17 - File Management - Import Media Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-import-media-files Chapter: The Observer XT Import Media Files Supported Formats See Media Files for an overview of the supported media formats. Aim To select a video or audio file if you did not already do so when you created an observation. Prerequisites You carried out at least one observation. Your license for The Observer XT includes the Single Media Module or the Media Module. Procedure To Add a Video File - Open the observation. - Click the Import Video button on the Component toolbar. - Select a video file. - Optionally select Visualize Audio to display the audio of the video as waveforms. See Visualize Audio in Visualize Data. - Click OK. To Add an Audio File - Open the observation. - Click the Import Audio button in the Component toolbar. - Select an audio file and click OK. To Replace a Media File - Open the Independent Variable List window by doing one of the following: - Choose Setup > Independent Variables. - In the Project Explorer, click Independent Variables. - Click the ellipsis button next to the video you want to replace. - Select another media file and click Open. To Remove a Media File from an Observation To remove a single media file from an observation, open the Independent Variables list (see To Replace a Media File) and click the corresponding cell in the Video or Audio column. Then press Delete > OK. The media file is only removed from your project, not deleted from disk. Remove a Media File Variable The instructions below remove a Video or Audio column in your Independent Variable List. This means that all the links between the video/audio files in that column and the observations are removed. To remove a specific media file from your project, see To Remove a Media File from an Observation. - Open the Independent Variable List. See Independent Variables in Set Up Your Project. - Right-click in a Video or Audio column and select Delete independent variable. - Click OK. Notes - You can add one video and/or audio file to an existing observation in The Observer XT with the Single Media Module. With the Media Module you can add a maximum of 20 media files. - Media files are always added with Scope Observation. See Variable Scope in Set Up Your Project. Manage Analysis Results Save Analysis Results - Make sure that the analysis result is open on the screen. - Click the Archive button on the toolbar. - Enter a name and click Save. The analysis result now appears in the Project Explorer in the appropriate folder under Analyses. Notes: - The destination folder is named as the type of analysis you have run, and is located under Analysis Results in the current Project folder. You cannot save your analysis results outside that folder. - The default name for the Analysis Results file is: .arx. The prefix varies according to the type of result (Behavior Analysis, Reliability Analysis etc.). The number is augmented by 1 every time you save the result with the default name. Open Analysis Results Do one of the following: - Choose Analyze, select the analysis type and then Open Archive. Select the result file and click Open. - Click the Analysis result in the Project Explorer. - Right-click the Analysis result in the Project Explorer and select Open. Remove Analysis Results To remove an archived analysis result, right-click it in the Project Explorer and select Remove. Removing an analysis result does not delete the file (*.arx) from the Analysis Results folder of your project. To open it again, click the Open Archive button on the Component toolbar. Export Analysis Results You can export analysis results to Excel or ASCII (text). - Make sure that the analysis result you want to export is open on the screen. - Choose Analyze > Export Analysis Results, or click the Export button on the Component toolbar. - Browse to the folder where you want to store the exported file. By default, this is the Export folder within your project folder. - From the Save as type list, select either Excel Workbook (*.xlsx) or Text File (*.txt). - If you choose Text File, select a column separator from the List separator list next to Encoding. - Optionally, select the option Merge header rows. Do so if you want to open the analysis results in SPSS. - Select whether you want to export as Unicode (UTF-16) — if your export file contains Chinese, Japanese, or Cyrillic characters, or characters like "ä", "õ" etc. — or ANSI, if you want to open the analysis results in SPSS. - Enter a name and click Export. Notes: - You can only export the current analysis result or those saved previously. If you plan to export many results, first save each of them, or export each of them before creating the next one. - Exporting to text files: results in separate sheets are exported to separate text files. The name of such a file is: [File name]_[name of sheet].txt. - Exporting to Excel: results in separate sheets are exported as separate worksheets within the Excel file. --- ## The Observer XT 17 - File Management - Import ODX Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-import-odx-files Chapter: The Observer XT Import ODX Files Import ODX Files As Separate Observations - Choose File > Import > Observational Data. Alternatively, in the Project Explorer, click the Observations item, then in the overview window, click Import Observations. - Make sure that The Observer XT (*.odx) is selected in the Files of Type list. - Browse to the file and click Open. Import ODX Files to an Existing Observation - Open the observation you want the data to be imported to. - Click the Import Data button on the toolbar, then choose Import Observational Data. - Make sure that The Observer XT (*.odx) is selected under Files of Type. - Browse to the file and click Open. Notes - If the ODX file contains multiple observations and you import it into an existing observation, data are imported only for the first observation. - The imported event logs retain their original names. If the observation already contains event logs with that name, a suffix _imported [#] is added to the imported file names. - If your coding scheme or data contain special characters like ü or ç, or Chinese, Japanese, or Cyrillic language characters, make sure that your Windows Regional Options support those characters before importing *.odx files. Open the Control Panel, choose Language, select your preferred language, then close and restart The Observer. - Export files from FaceReader can be very large when you choose the option to save all analyses to a single odx-file. Such large files take very long to import into The Observer XT, or it may not be possible to import them at all. We recommend transferring FaceReader data to The Observer XT with the Noldus network communication protocol N-Linx. See Observe Live and Analyze with FaceReader in Set Up Your Project. Alternatively, export results of single participants or analyses and import them one by one into The Observer XT. What Happens to the Coding Scheme? An ODX file contains information on the coding scheme of the project it was exported from. All elements of the coding scheme are imported, regardless of whether they were scored in those observations. When you import an observation to a project, The Observer XT checks that the elements in that observation have exactly the same characteristics as the elements in the coding scheme of the destination project — for example, that a behavior has the same name, properties (with or without duration, belonging to the same group type, etc.), and modifiers. If the element is exactly the same, the existing element is used. Differences in Description, Sound File, Plot Color, and the Always Add Comment option are ignored. If there is any other difference, a new element is added to the coding scheme. Possible conflicts between imported data and existing data: if your imported data contain restrictions between subject and behavior, or connections between a subject/behavior and a modifier that are not specified in your coding scheme, the data already present in your project may be invalidated. The Observer XT performs a check when you import observational data. If errors are found, a window appears listing the errors. You can choose to let The Observer XT fix the errors automatically, or you can correct the errors yourself. See Check the Event Log for Errors. - Example 1 — You import an observation where the behavior Play can be scored for subject Child, but not the subject Parent. If the project contains data like Parent-Play, these are marked as errors. - Example 2 — You import an observation where the behavior Play is attached to the required group of modifiers Play Type. If the project contains events like Play without modifiers, these are marked as errors. Event logs with errors cannot be analyzed or visualized. Open those observations and edit the data to correct the errors. See Correct Event Log Errors Manually in Carry Out an Observation. What Happens to the Independent Variables? If a variable is already present in the Independent Variable List of the destination project, it is updated with the values from the imported observations. If it is a new variable, it is added to the Independent Variable List. Import Media Files and External Data If you have chosen to include media files or external data files in the exported observations, the program looks for those files in the folder where the ODX file was stored. - Media files — The original path to the file written in the ODX file is stored in the Independent Variables List under Video or Audio if the file was not found in the folder where the ODX is stored. When opening the observation, the program asks you to locate that media file. - External data — The ODX file contains a link to the location of the external data files associated with the observations, not the external data itself. When you next import the observations into another project, make sure that the external data folder contains those files; otherwise the program cannot open them. If the external data cannot be opened, locate the file with the extension *.pbi in the folder to which you exported the observation. Create a new project and save it, then close the new project and copy the *.pbi file to the folder /External of the new project. Do not rename this file. Reopen the new project and import the ODX file. The external data are now imported together with the observational data. How Are the Imported Data Synchronized? When you import observational data that are collected offline from video, the absolute time stamps differ from the time stamps of the observation. Therefore, the time stamps of the imported data are not aligned with the time stamps of the Event Log. This is also the case when you import data from FaceReader that were collected offline. The Observer XT will align the time stamps of the imported data with the time stamps of the Event Log depending on the circumstances described in the synchronization table. --- ## The Observer XT 17 - File Management - Import Other Observational Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-import-other-observational-data Chapter: The Observer XT Import Other Observational Data To import event data stored as text files: - Choose File > Import > Observational Data. Alternatively, in the Project Explorer, click the Observations item, then in the overview window, click Import Observations. - If you already have an Import Profile for the observational data file, select the name of this profile from the Files of Type list. If not, create a Custom Import Profile. - If the data file does not have a column that specifies whether events have duration or not, choose how to import the behaviors by selecting Point Events (No Duration) or State Events (Mutually Exclusive) in the Treat New Behaviors As group. - Select the external data file and click Open. Create a Custom Import Profile Aim To make a template for import of observational data stored in text files. Prerequisites - The observational data file contains a column with time stamps. - Subjects, Behaviors, and Modifiers are in different columns. - Each time stamp contains a value that indicates the start or stop of a behavior. Procedure - Choose File > Import > Observational Data. Alternatively, in the Project Explorer, click the Observations item, then in the overview window, click Import Observations. - Choose Custom Import Profiles > New. - Browse to a representative file for defining your import profile and click Open. Build the import profile by specifying the position of the header in the data file and the cells or columns containing the time information and the data. This is done by dragging and dropping cells. To undo a selection, select the cell to which content was dropped and press Delete. Follow the procedure in these sections: - Header - Delimiters - Time Information - Data 1 - Header The Observer XT usually automatically detects header and data information in the file. If not, specify which part of the data file contains the header by choosing an option from the Header Detection list: - Automatic (default) — The Observer XT is set to automatically detect the header and data sections in the data file. Choose one of the other options if automatic header detection does not work. - Specify Tag — Select this option if the data file has a variable number of header lines and the header always ends with the same word. Specify the phrase (with either nominal or numerical information) that indicates the end of the header part of the file. If necessary, also specify the number of rows between the header line that contains this phrase and the data. For example, if the header always ends with a line containing the text [Data] and there is always an empty line before the data starts, enter [Data] in the End Tag field and 1 in the Extra Rows field. - Specify Row Number — If the data file always has the same number of rows in the header, select this option and specify the number of header rows. 2 - Delimiters The Observer XT uses the comma as the default delimiter to separate text in the header and data sets. However, the data file may use other delimiters. If this is the case, select the correct ones from the Select Header Delimiters and Select Data Delimiters lists. You can also select multiple delimiters. 3 - Time Information Drag and drop content from the File Content section to the corresponding cells in the Profile Definition section. If the header contains date and time information, drag and drop this to the Start Date box and the Start Time box in the Profile Definition section. When you drop the date in the Start Date box, the Select Date Format window opens. If the date matches one of the predefined formats, The Observer XT automatically selects one, and Converted Date shows the date with a Conversion is OK message. If not, define your own format by typing a d for each number representing day, an M for month, and a y for each number representing year. If the proper date is shown after Converted Date, click OK. When you drop the time in the Start Time box, the Select Time Format window opens. If the time matches one of the predefined formats, The Observer automatically selects one, and Converted Time shows the time with a Conversion is OK message. If not, define your own format by typing an H for each number representing hour, an m for minute, an s for second, and an f for each number representing millisecond. If the time is correct, click OK. --- ## The Observer XT 17 - File Management - Manage Projects URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-manage-projects Chapter: The Observer XT Manage Projects Projects A project contains the elements Project Setup, Coding Scheme, Independent Variables, Observations, Data Profiles, Episode Selections, and Analyses. These are visible in the Project Explorer and can be opened either from the menu or by clicking an element or item in the Project Explorer. What Do You Want to Do? - Create a new project - Save a Project - Rename a Project - Save a Project as a template - Open a Project - Create a backup of a Project - Restore a backup of a project Create a New Project You can create a project in two ways: - A new blank project – This empty project contains no settings. - A project from a template – This template project contains settings like a coding scheme and independent variables. Create a New Blank Project - To open a new project, do one of the following: - In The Observer XT startup window, under Create a new project, click New blank project. - Choose File > New Project. - Press Ctrl+N. - Enter a name and click OK. Create a New Project from a Template See Save a Project as a Template for information about a project template. - Do one of the following: - In The Observer XT startup window, under Create a new project, click New project from template. - Choose File > New Experiment From Template. - Click the Select button to select a template project (*.otb) from the Template folder. See also Save a Project as a Template. - Enter a name and click OK. Notes: - The project is saved in a Project directory with the same name. - A project file name cannot contain any of the following characters: \ / : ; * ? " < > | Save a Project Choose File > Save or press Ctrl+S. Auto-Save Use auto-save to temporarily save a project at regular intervals. Choose File > Preferences > Auto recovery. Select Save auto recovery and set the interval. Auto Recovery saves data to a temporary file. Your data are only saved in the Project file when you actually choose File > Save Project. Media files or external data files are not saved to this temporary folder. When the program crashes, you get the choice to open the auto-saved project or to open The Observer XT. When you choose the latter option, you can open the manually saved project. Rename a Project Choose File > Save Project As and enter the new name. Save a Project as a Template A template is a copy of an existing project, but without the observations and analyses. Use it to create a similar project without having to create the Coding Scheme, Independent Variables and other settings again. A template contains project settings, coding scheme and independent variables but no data. You can use a template project to exchange coding schemes or to re-use devices in the project setup. The templates (*.otb) replace the templates and read-only projects (*.otx and *.vpx) from previous versions of The Observer XT. - Choose File > Save Project as Template. - Enter a name. - Click the Save options button and, optionally, select: - Include Independent Variables – To include Independent Variables in the template. - Include hardware and software devices – To include the hardware and software from the Devices list in the template (see Control External Devices or Programs during a Live Observation in Set up your Project). This is useful, for example, if you use The Observer XT in an observation lab and want to create a new project but use the standard hardware and software setup of your lab. - Template information – To enter additional information about the template project. - Click OK twice to save the template project. Open a Project - Choose File > Open Project or press Ctrl+O. - Browse to the folder where the project is stored. - Open the folder with the same name as the project. - Select the *.vop file and click Open. Notes: - See Restore a Backup of a Project to open a backup file (*.vpb). - If you open a project created in a previous version of The Observer XT, it is automatically updated to an Observer 17 project. This then can no longer be read in the previous version. The Observer XT 17 automatically creates a backup (*.vpb) copy of the project in the Projects folder which can be opened in the previous version of The Observer XT. - If your project includes Chinese, Japanese, or Cyrillic language characters: you can view these characters on a computer with an English language Windows system only when the correct language pack has been installed. If the project was created on an English language Windows system with the appropriate language pack installed, you can view it on a Chinese, Japanese, or Cyrillic language Windows computer. In all other cases the project opens but you cannot view these characters. - Use Latin characters in the path names and file names, as otherwise The Observer XT cannot find the data. Create a Backup of a Project The aim is to create a copy of your project that can be stored as a backup, sent to a colleague, or to Technical Support in case of problems. - Choose File > Make Backup, or press Ctrl+B. - Select the following options as needed: - External data (selected by default) – To include the external (physiological) data files (*.pbi) in the backup file. If you do not select this option, the backup still contains the names of the files (*.pbi). You can copy those files manually to the project's External folder. If your project contains no physiological data, selecting or deselecting this option has no effect. - Import profiles – Select this option if you want to include the import profiles used to import the physiological data (*.eip) in the backup file. - Optionally, change the file name and file location. - Click Save. Notes: - The backup file contains a zipped copy of the entire Project folder and of the log file. It also contains Preferences, references to media files and external (physiological) data outside the Project folder. - Media files are not stored in the backup file. Store a copy of the videos at a safe location as well. - If you want to quickly copy observations, including references to media files and external data, export them as ODX. See Export Data to The Observer XT Data Files (*.odx). - Store the backup file on a secure medium (CD, DVD, external hard disk or network drive), in a separate location. - The Observer XT creates a backup automatically every tenth time you save a project. Restore a Backup of a Project To open a project from a backup file: - Choose File > Restore Backup, or press Ctrl+R. - Locate and select the backup file (*.vpb) and click Open. The Project directory and all associated files in the project are now restored. Notes: - If your backup file includes external data and import profiles (see the options in Create a Backup of a Project), these are copied to the External project folder and the Profiles folder respectively. - If you chose not to include the external data, you can still recover them. Open the Independent Variables List and point the mouse to the cells in the External data columns. A tooltip informs you about the name of the imported file (*.pbi). Copy this file to the External project folder. See Project-level Folders for its location. --- ## The Observer XT 17 - File Management - Resampling URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-file-management-resampling Chapter: The Observer XT Resampling Why Resampling? Event data and external data are not likely to have the same sample rate. Also, for the event log, it is unlikely that the timestamps are equidistant. Therefore, if you export the event log together with external data, exporting them at the sample rate of the external dataset means that the event log must be resampled. If you have different external datasets, these may differ in sample rate. If you export all external datasets linked to an observation and these differ in sample rate, some external datasets will be resampled. How Point Events Are Resampled When you export event data and external data and choose to export point events to separate columns, Subject–Behavior group combinations that have the same time-stamp after resampling are each written to their own column. When you export to one column, the same Subject–Behavior group combinations that have the same time-stamp after resampling are exported to the same column. - If you have mainly defined point events (events without duration) in your coding scheme to score and analyze your data, you should export point events to separate columns. As a result, point events that have the same time-stamp after resampling are written to separate columns. - Different Subject–Behavior group combinations are always exported to separate columns. How External Data Are Resampled When exporting event data and external data at a chosen sample rate, any external data recorded at a different sample rate must be resampled. This is done by linearly interpolating the data at the sample time points for which data is missing. For example, if you have heart rate data sampled at 2 Hz and FaceReader data sampled at 29.981 Hz and you export at 29.981 Hz, the heart rate data is linearly interpolated to fill in the missing sample points. How Event Data And External Data Are Resampled When both event data and external data are exported together, all data are resampled to the selected sample rate before export. The column with relative time in the export file contains the time-stamps based on the chosen sample rate. Point events without duration are resampled at the first sample following the original time the event occurred. If the One column option was selected, events that occur at the same time are exported to the same column, separated by a comma. How Missing Values Are Resampled If your dataset contains missing samples, the missing sample is converted to the symbol NaN. When such external data are exported, the resampled samples will get a NaN value in the export file when at least one of the samples used for interpolation has a NaN value. Export Data To Text Files With The Find Function Aim To quickly export your data by copying and pasting them into another program, or to export a specific selection of your events. Use this method for a quick view of your events or a selection of events. Procedure - Open an observation. - Do one of the following: - Click the Find button on the toolbar. - Choose Edit > Find. - Press Ctrl+F. - Specify the selection in the upper part of the screen. - Click Find. - Optionally, hide columns that are not of interest. To select which columns to show or hide, right-click a header and specify your selection. - If you scored start-stop events and do not want to export the stop events, select Hide Stop events. - To export all events, click the Export all events button. Otherwise, select the events you want to export and click the Export selected events button. You can export the events as a text file or to Excel. Notes - The Find function does not create a subset of data ready to be analyzed (for example, to calculate statistics). For this purpose, select data in the Data Profile. - You can also copy the events and paste them into another program. To do so, right-click one of the cells and select Copy all. - To use the exported data in a statistical package you may need the event start time together with the event durations. Make sure the Duration column is visible. If it is hidden, right-click a column header, select Show column, and select Duration. Import Observational Data Aim To import observational data into an existing project. Observational data can be: - Exported The Observer XT data files (*.odx) - Observer log files from FaceReader (*.odx) - Exported Viso sessions (*.odx) — see Import ODX Files - Other data in text format containing a header, a column with time stamps, and one or more columns with codes — see Import Other Observational Data --- ## The Observer XT 17 - Installation - Deactivate Your Observer XT License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-deactivate-your-observer-xt-license Chapter: The Observer XT Deactivate Your Observer XT License Aim - To use your Fixed license for The Observer XT on another computer. - To change a Fixed license for The Observer XT into a Floating license or the other way around. - To make sure that The Observer XT cannot be used on a certain computer. Procedure - From the Help menu select License and then Deactivate. A message appears informing you that deactivation has been successful and that The Observer XT will exit. You can now use the license to activate The Observer XT on another computer. --- ## The Observer XT 17 - Installation - End-User License Agreement URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-end-user-license-agreement Chapter: The Observer XT End-User License Agreement IMPORTANT – READ CAREFULLY. Please read this End-User License Agreement ("EULA" or "Agreement") carefully before checking the "accept" checkbox, downloading or using the Software (as defined below). By checking the "accept" checkbox, downloading, installing or otherwise using the Software, End-User agrees to be bound by the terms and conditions of this EULA. If you do not agree to the terms and conditions of this EULA, do not check the "accept" checkbox and do not download, install or use the Software. The Software is protected by copyright laws and international copyright treaties, as well as other intellectual property laws and treaties. The Software is licensed, not sold. 1. Definitions - 1.1. Authorized Partner: The individual or legal entity that has been granted permission by Noldus to promote, sell or otherwise distribute the Software on behalf of Noldus. - 1.2. End-User: The individual or legal entity that has acquired or uses the Software under the terms and conditions of this EULA. - 1.3. EULA: This End-User License Agreement. - 1.4. Indirect Losses: Any indirect loss, claim, damage, liability, or expenses (including reasonable attorney's fees), including lost profits, and damage due to the stagnation of business operations. - 1.5. Network License: A licensing mechanism comprising a license file and accompanying software managing the number of concurrent users of the Software. - 1.6. Noldus: Noldus Information Technology bv, with registered office at Nieuwe Kanaal 5, 6709 PA Wageningen, The Netherlands, listed in the Trade Register under Chamber of Commerce number 09094422, or its subsidiaries. - 1.7. Security System: A system of software protection to limit installation and use of the Software to the authorized End-Users and computers. - 1.8. Security Device: A device that forms part of or is attached to the computer, and is used as part of the Security System to control access to the Software. - 1.9. Software: The software (including, but not limited to, any updates, upgrades and associated media, printed or electronic documentation and online services) provided to the End-User by Noldus or an Authorized Partner together with this EULA, that is not covered by third party terms and conditions. 2. License - 2.1. Upon payment by the End-User of the license fees for the Software, Noldus grants End-User a revocable, non-exclusive license to download, install and use the Software in accordance with the terms and conditions of this EULA. This EULA does not grant any rights to obtaining future upgrades, updates or supplements of the Software. If upgrades, updates or supplements of the Software are obtained, the use of such upgrades or updates is governed by this EULA and the amendments that may accompany them and may be subject to additional payments and conditions. - 2.2. The End-User may download, install and use the Software on as many computers as is reasonably necessary, however the Software may not be shared or used concurrently on more computers than for which EULAs are granted. End-User shall take all reasonably required steps to ensure that this number is not exceeded. - 2.3. End-User is allowed to store or install a copy of the Software for back-up or archival purposes. - 2.4. End-User shall not (i) modify, alter, adapt, merge, decompile or reverse-engineer the Software or any part thereof nor create any derivative works based on all or any part of the Software, or (ii) remove or obscure any copyright, trademark or other ownership notices from the Software, or (iii) sub-license, sell, rent, lease, hire, loan, assign or otherwise transfer the Software or your rights in the Software or any part thereof, except as provided for in this EULA. - 2.5. The Software may be protected by a Security System, including but not limited to the use of expiry dates, time-limited or feature-limited licenses, authorization codes, Security Devices and Network Licensing. End-User is prohibited to (attempt to) remove, alter or circumvent in any way any part of such Security System. - 2.6. End-User is responsible for regular, frequent and effective backups of all files produced or modified while working with the Software. 3. Intellectual Property - 3.1. All title, copyright and other industrial, intellectual or proprietary rights in and to the Software (including but not limited to any images, photographs, animations, video, audio, music, and text incorporated into the Software), the accompanying printed materials, and any copies of the Software are owned by Noldus or its Authorized Partners. All rights not expressly granted are reserved by Noldus. - 3.2. The Software may include or make use of third party software, including open source software. Such third party software may be subject to the third party's terms and conditions provided in the documentation accompanying the Software and may contain copyright or other industrial, intellectual or proprietary rights of such third party. End-User hereby agrees to the terms and conditions for such third party software. In the absence of any third party terms and conditions, this EULA will govern the third party software in the Software. - 3.3. End-User may, from time to time, provide Noldus with comments, suggestions, data, information or feedback ("Feedback") on the Software. End-User acknowledges and agrees that such Feedback may be freely used by Noldus, at its sole discretion, for the design, development, improvement, marketing and commercialization of its products and services, without any restrictions based on confidentiality or intellectual property rights. 4. Transfer - 4.1. End-User is entitled to make a one-time, permanent transfer of this EULA and Software only directly to one other End-User. This transfer must include all of the Software (including all component parts, the media and printed materials, any upgrades and this EULA). Such transfer may not be by way of consignment or any other indirect transfer and shall be subject to the following provisions: - a. End-User will provide to Noldus prior to any such transfer the full name and address details of the new End-User and the expected date of transfer in writing. - b. The new End-User understands and agrees to all the terms and conditions of this EULA in the same way as if the new End-User had obtained the Software from Noldus or an Authorized Partner. - c. End-User will destroy all (partial) copies of the Software and all accompanying materials, including but not limited to installed copies and any backup copies on data storage devices, and guarantee to Noldus in writing that this has been done. If the Software is an upgrade, any transfer must include all prior versions of the Software. - d. Noldus reserves the right to levy an administrative charge upon the End-User and/or the new End-User in relation to transfer of the Software to an End-User. - 4.2. Any attempted transfer without prior written permission from Noldus shall constitute a material breach of this Agreement and shall be deemed null and void. 5. Term and Termination - 5.1. This EULA shall enter into force on the date of acceptance by the End-User and continue until terminated in accordance with this Section 5. - 5.2. If the Software is licensed on a subscription basis, the EULA shall continue until the end of the current subscription period. - 5.3. Noldus is entitled to terminate the EULA immediately upon prior written notice upon: - a. The breach of any material provision of this Agreement by the End-User if (i) such breach is not curable or (ii) if curable, the End-User has not cured such breach within a 30 (thirty) day period following receipt of a written notice by Noldus substantiating such breach. - b. The filing or institution of bankruptcy, liquidation or receivership proceedings of the End-User or in the event a receiver or custodian is appointed for the End-User's business, or if its business is discontinued or if it has a petition presented by a creditor for its winding up or if the End-User enters into any liquidation (other than for purpose of reconstruction or amalgamation). - 5.4. Upon termination of the EULA, the End-User shall immediately discontinue the use of the Software and remove the software from all computers, destroy all (partial) copies of the Software from all storage media and return the documentation and materials relating to the Software to Noldus or its Authorized Partner. - 5.5. Termination of this Agreement does not remove or reduce End-User's obligation to pay any outstanding license fees or other monies, all of which shall be due for payment immediately on termination of the EULA. - 5.6. The following provisions shall survive termination of this EULA: Sections 3, 7, 9, 10 and this Section 5.6. In addition, any other provisions which are required to interpret and enforce the Parties' rights and obligations under the EULA shall also survive any termination or expiration of this EULA, but only to the extent required for the full observation and performance of the EULA. 6. Warranty - 6.1. Noldus warrants that as of the date of delivery to the End-User by Noldus or its Authorized Partner, the Software will, for a period of 90 days ("Warranty Period"), materially conform to the specifications set out in the user documentation accompanying the Software ("Specifications"), provided that: - a. The Software is properly installed on a supported computer platform and used in accordance with the provisions of the accompanying user documentation and/or any Noldus-approved training course. --- ## The Observer XT 17 - Installation - Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-installation Chapter: The Observer XT Installation System Requirements Operating System The Observer XT 17 has been thoroughly tested using a US English version of Windows 10 and Windows 11 (64-bit Professional edition). Minimal version number 20H2 (October 2020). To check which version you have, type Windows version in the App window and click See if you have a 32-bit or 64-bit version of Windows. Note the information in the Edition, Version, and System type fields. The Observer XT is not designed for use with the touch features of Windows. Languages The Observer XT was tested with the US English language packs of Windows. The Observer XT has also been tested with Cyrillic, Japanese and simplified Chinese language packs. It is possible that certain local language versions of Windows may affect how well the program runs. For more information about using non-Latin characters in specific parts of the program, see File Management. Computer The type of computer you need to run The Observer XT depends on how you will use the program. If you are carrying out a few live observations, then a simple netbook will suffice. If you are working with video or have a large number of observations in your project, then a professional workstation is necessary. If you purchase a complete setup from Noldus, then we will make sure your computer suits your purposes. System Requirements for Live Observations For using The Observer XT for live observation (no video files, cameras or physiological data), with a maximum of 200 short observations, or a small number of observations with up to 5000 event lines, a simple netbook is sufficient. Coding schemes with non mutually-exclusive modifiers should not be used with such a computer, as this type of modifier has a severe impact on performance. Noldus recommends in this case an ultrabook or laptop with at least 2 GHz processor and 2 GB of memory. System Requirements for Observations with Video For working with The Observer XT and video, we recommend that you use a professional workstation. It is possible to buy consumer-range computers with a high processor speed and plenty of memory, but in order to remain competitive regarding price, the manufacturers often economize on the underlying system architecture. That means those computers are suitable for home use, but not for running professional scientific software. You should select a computer which is intended for professional use or labeled by the manufacturer as a workstation. If you use other software which installs codec packages on your computer, this can interfere with the codecs installed by The Observer XT. We recommend to uninstall DVD burner software, video editing packages and similar. See Codecs Installed by Other Programs in Media Files. Recommended Computer The Observer XT has been tested with the Dell Precision™ T3650 desktop PC and the M3551 mobile workstation. If you order a complete solution from Noldus Information Technology, you will obtain a Dell Precision™ T3650 workstation (or its successor), or a M3551 mobile workstation (or its successor) with The Observer XT software installed and ready to use. These computers are the standard test platforms for The Observer XT, and we recommend that you use those computers. Technical specifications Dell Precision™ T3650 PC: - Processor: Intel Core i7-11700, 8 Core, 16 MB Cache, 2.5 GHz - Internal memory: 8 GB DDR4 - Primary hard disk: M.2 256 GB PCIe NVMe Class 40 SSD - Secondary hard disk: 3.5 inch 1 TB SATA (7200 rpm) - Graphics card: NVIDIA Quadro P2200, 5 GB Technical specifications Dell Precision™ M3551 mobile workstation: - Processor: Intel i7-10750H (6-core), 2.2 GHz - Internal memory: 8 GB - Hard disk: 1 TB - Graphics card: 4 GB NVIDIA Quadro P620 If you are planning to purchase a different computer than the ones mentioned above, please contact us for detailed advice. Older Computers If you are upgrading from an older version of The Observer XT, you can still install the latest version on an older workstation. To use The Observer XT with video, the computer should have at least a 2.6 GHz dual core processor and at least 4 GB of memory, as well as a video card supporting DirectDraw acceleration. We recommend a 2.8 GHz quad core processor with 8 GB of memory. Video Card To be able to play back videos in The Observer XT, your video card should have Direct3D Acceleration. All newer cards support this feature, but older cards (in older PCs) do not. For Windows 10 and Windows 11, Direct3D Acceleration is enabled by default. Note: If you have video files on CD, DVD or mobile devices, copy these to your hard disk before scoring with The Observer XT. See also Supported Formats in Media Files. Supported Hardware Drivers of the supported hardware must be installed separately. These drivers are available on the MyNoldus portal. The following hardware works with The Observer XT 17 running on 64-bit Windows 10 or Windows 11: Video Controlling Device - Contour ShuttlePRO v2 Jog/shuttle device Mobile Scoring Device for Pocket Observer - Android devices for Pocket Observer 3.4 Pocket Observer 3.4 was tested with Android version 10 on a Samsung S9 phone and with Android version 11 on a Samsung S10 phone. We cannot guarantee that Pocket Observer will work well with future versions of Google Android. Please contact our Support center if you use a newer version and run into issues. Before You Install The Observer XT If you ordered a new computer from Noldus Information Technology when you purchased The Observer XT, all your software and any internal hardware is already installed and tested. If you install The Observer XT yourself, please follow the instructions below in the order they are presented. Please note that it is not possible to install The Observer XT on one computer and access it from another across a network. The program must be installed on the computer where it will be used. Prior to installation, please check the packing list to make sure all the components are present. If any of the components listed is missing or damaged, please report this to us immediately. Before you install The Observer XT, carry out the following steps: - Turn off automatic updates for device drivers - Select correct power options Turn Off Automatic Updates for Device Drivers The general recommendation from Microsoft to use automatic updates is good, especially for security updates. However, automatic updates of hardware device drivers can sometimes cause problems. The Observer XT is tested with the device drivers that are available at the moment of release. If device drivers are updated afterwards, we cannot guarantee that they work properly with The Observer XT. Therefore we recommend switching off automatic updates of device drivers. If you ordered a computer with The Observer XT from Noldus IT, the automatic updates for device drivers have already been turned off and you can skip this section. - Click the Windows icon on your desktop and type Change device. - Click Change Device Installation Settings. - Select No (your devices might not work as expected). - Click Save Changes. Select Correct Power Options On computers with Windows 10 and Windows 11, by default the computer resumes rather than restarts after shutdown. This can cause problems with The Observer XT and associated software like N-Linx and MediaRecorder. Therefore, with installation of The Observer XT, the option that makes the computer resume is disabled, so the computer is really restarted after shutdown. With Windows updates, these options can become enabled again. Therefore, check whether the computer shutdown settings are correct. - In the Windows start window, type Power options and then click the Power options tile. - Choose Choose what the power buttons do. - Click Change settings that are currently unavailable. - Select the following options: - When I press the power button – Shut down - When I close the lid – Shut down - Under Shutdown settings, deselect the checkboxes: Sleep, Hibernate, and Turn on fast startup (recommended) Note: The option Turn on fast startup (recommended) under Shutdown settings is disabled automatically when you install The Observer XT. Install The Observer XT Prerequisite: You have Windows administrator rights. This means you either are the system administrator or a member of the Windows group Administrators and have been assigned administrator rights. Important: If your license comes with a hardware key, first install The Observer XT and then connect the key to your computer, not the other way around. - Download the Observer installation zip file via your MyNoldus account: click on Downloads and then Versions. - Unzip the zip file and double-click the file The Observer XT 17 Setup.exe. - In the window that appears, select Standard. Select Custom only if you want to change the default location where the program is stored and the default project folders. - Optionally, select Adobe Acrobat Reader DC in the Drivers and Tools field. Adobe Reader is needed to display the documentation. If you have the Shuttle Pro keyboard to control video playback, select Shuttle Pro 2 Keyboard in the Drivers and Tools field. See the Technical Note - ShuttlePro2 - The Observer XT on the MyNoldus website for further installation instructions. - Click Next and follow the instructions on your screen to install. Notes: - The Observer XT is installed in C:\Program Files\Noldus\The Observer XT 17. Project files are saved in the following folders: - Projects: C:\Users\Public\Public Documents\Noldus\The Observer XT\Projects - Templates: C:\Users\Public\Public Documents\Noldus\The Observer XT\Templates - Video: C:\Users\Public\Public Documents\Noldus\The Observer XT\Video files - Audio: C:\Users\Public\Public Documents\Noldus\The Observer XT\Audio files - If the installation software finds a previous version of Sentinel Runtime installed on your computer, it informs you that clicking Yes will uninstall the previous version and install the new one. - You can download The Observer XT installation file with or without codecs from the MyNoldus website. The version without codecs is for scoring live only. The video tutorial can be downloaded separately. To Install uASQ uASQ is not shown in the Setup window. Install uASQ from the MyNoldus website. You will find the installation file under Installation instructions. If you upgrade from a previous version of The Observer XT, first uninstall uASQ using the Programs and Features item in the Control Panel, then re-install uASQ from the MyNoldus website. See the Reference Manual - uASQ for details. To Install uLog Install uLog from the MyNoldus website. You will find the installation files under Installation instructions. --- ## The Observer XT 17 - Installation - Miscellaneous URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-miscellaneous Chapter: The Observer XT Miscellaneous Electronic Communications Parties may communicate with each other by electronic mail. Parties recognize the risks associated with electronic mail and declare that they shall not hold each other liable for any damage incurred as a result of the use of electronic mail. If a Party is in doubt as to the content of an electronic message received, the content of the message originating with the sender shall be decisive. Severability The invalidity or unenforceability of any provision of this EULA shall not affect or limit the validity or enforceability of any other provisions thereof. Any such invalid or unenforceable provision shall be deemed to be substituted by a provision that is considered valid and enforceable, interpreted as close as possible to the economic, legal, and commercial objectives of the severed provision. Waiver Failure by Noldus or the Authorized Partner to enforce any of its rights under the EULA shall not constitute a waiver of such rights and shall not relieve End-User of its obligation to comply with such provisions. No waiver or amendment of any provisions shall be effective unless signed in writing by a Noldus representative. Any such written waiver shall only be applicable to the specific instance to which it relates and shall not be deemed a continuing or future waiver. Amendments Amendments or changes to this EULA can only be agreed upon in writing between the Parties. Binding Effect and Assignment The EULA shall be binding upon the Parties thereto, their legal representatives, successors, and assigns. End-User shall not assign any right or obligation arising out of this EULA without prior written consent from Noldus. End-User License Agreement Assignment - End-User may not assign or delegate any obligation under this EULA without the prior written consent of Noldus. Any attempt to do so shall be deemed null and void. Governing Law: End-Users in the USA or Canada - If End-User is a legal entity with its principal place of business in the United States of America or Canada, or an individual whose primary residence is in the United States of America or Canada: - This EULA is exclusively governed by the laws of the Commonwealth of Virginia and applicable federal laws of the United States of America, without regard to conflicts of law provisions of any jurisdiction. - The Virginia Uniform Computer Information Transactions Act (UCITA), Virginia Code §§ 59.1-501.1 et seq., and the United Nations Convention on Contracts for the International Sale of Goods (CISG) are expressly excluded from this EULA. - Any and all terms contained in UCITA or CISG will have no force or effect on any portion of this EULA. - Any claims and disputes arising out of or in connection with this EULA that cannot be resolved amicably within a reasonable period of time will be commenced and maintained only in a state or federal court of competent subject matter jurisdiction situated in the United States of America. - Noldus and End-User consent to the exclusive personal jurisdiction of and venue in any such court. - End-User must commence or file any claim or action arising out of or relating to this EULA within six months after the cause of action accrues; otherwise, such claim or cause of action is permanently barred. - To the extent permitted by law, End-User expressly waives the right to commence or file any such claim or action under any longer statute of limitations. Governing Law: End-Users in Other Countries - If End-User is a legal entity with its principal place of business in any country other than the United States of America or Canada, or an individual whose primary residence is in any such country: - This EULA is exclusively governed by the laws of The Netherlands. The United Nations Convention for Contracts on the International Sale of Goods is expressly excluded. - Disputes arising out of or in connection with this EULA that cannot be solved amicably within a reasonable period of time will be submitted to the competent court in Arnhem, The Netherlands, for End-Users with their principal place of business in the European Union. - If an End-User has its principal place of business outside the European Union, the United States of America, or Canada, any dispute shall be finally settled in accordance with the Arbitration Rules of The Netherlands Arbitration Institute, with the location being Arnhem, The Netherlands. - The arbitration procedure shall be conducted by one arbiter in the English language. Acknowledgments and Copyright Notices The Observer XT makes use of the following third-party software libraries and products. For complete terms and conditions, see the PDF files in the folder Documentation\Legal\Acknowledgments located in your application folder (default: C:\Program Files\Noldus\The Observer XT 17). Third-Party Software Components - Boost – Open source C++ templates software library (Boost community). Licensed under the Boost Software License. - HASP – Library for software protection. Licensed under the Safenet EULA (Sentinel Gemalto). - LEADTOOLS DirectShow Filters – Video encoder and decoder software. Licensed under the LEADTOOLS license. - Wix Toolset – Tools to author software installers. Licensed under the Microsoft Reciprocal License (MS-RL) via the .NET Foundation. - Adobe Acrobat Reader DC – Software for viewing PDF files. Licensed under the Adobe Distribution Agreement. - RabbitMQ – Robust messaging for applications (Pivotal). Licensed under the Mozilla Public License 1.1. - Erlang OTP 18 – A programming language used by RabbitMQ. Licensed under the Apache License 2.0. - Apache Thrift – Combines a software stack with a code generation engine to build services that work efficiently and seamlessly between C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, JavaScript, Node.js, Smalltalk, OCaml, Delphi, and other languages. Licensed under the Apache License 2.0. - Telerik UI for WPF – WPF controls. Licensed under the Telerik EULA for UI for WPF. - SimpleAmqpClient – C++ client for RabbitMQ by Alan Antonuk. Licensed under the MIT License. --- ## The Observer XT 17 - Installation - N-Linx Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-n-linx-settings Chapter: The Observer XT N-Linx Settings Choose File > Preferences > N-Linx Settings. The Noldus network communication protocol N-Linx is used for communication between The Observer XT and other Noldus IT software programs like MediaRecorder and external programs like BIOPAC AcqKnowledge, Tobii Pro Studio, Tobii Pro Lab, Tobii Glasses software, and Bitbrain EEG acquisition software. All programs communicate with The Observer XT using N-Linx Server. For details on using N-Linx for communication between The Observer XT and other software, see the Reference Manual - N-Linx, or the technical note of the program to control. Connecting The Observer XT with N-Linx Server - Select Use N-Linx Server to connect with other applications. - In the N-Linx Server address field, enter the name of the computer with N-Linx Server. You can also enter the IP address, but the IP address of the computer with N-Linx Server must then be fixed. - In the N-Linx Server port field, leave the default port number 5672 unless this port is in use by other programs. You must enter the same port number for all N-Linx components. Related Documentation - Observe Live and Record Video with MediaRecorder - Observe Live and Analyze with FaceReader - Reference Manual - N-Linx - Technical Note - BIOPAC MP System - The Observer XT - Technical Note - Tobii Pro Eye Trackers - The Observer XT - Technical Note - Tobii Glasses - The Observer XT - Technical Note - Bitbrain EEG - The Observer XT These documents are available for download from the MyNoldus section of the Noldus website. Using N-Linx with Your Own Software N-Linx can also be used to control your own software. For example, to start and stop your own application with The Observer XT, or to import data from your own software in real time into an observation. Consult Noldus support for options and documentation on how to work with the N-Linx Software Development Kit. Viso Settings Choose File > Preferences > Viso Settings. Viso settings are needed if you want to import sessions created in the observation recording program Viso into The Observer XT. Viso settings establish the connection between the computer running The Observer XT and the computer running Viso Services. - Enter the IP address of the computer with Viso Services in the Services address field. - Do not change the Services port value of 5672. - Click the Test Connection button. If the two computers are connected properly, the status Connected appears. See also: Import Viso Sessions in File Management. Source: The Observer XT 17 Help - Installation, Noldus Information Technology --- ## The Observer XT 17 - Installation - Upgrade to The Observer XT 17 URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-upgrade-to-the-observer-xt-17 Chapter: The Observer XT Upgrade to The Observer XT 17 Overview Use this procedure to start working with a newer version of The Observer XT. Prerequisites - You have an older version of The Observer XT and have purchased an upgrade to version 17. - Your computer meets the system requirements for the new version. Upgrade Steps - Install The Observer XT 17. - Upgrade the license (see below). Upgrading the License Upgrading the license is required if you purchased a newer version of The Observer XT, or if you purchased extra modules or tools for the current version. The procedure differs for software licenses and hardware keys. If You Have a Software License Key - Start The Observer XT and deactivate your current license. The software will close. - Restart The Observer XT and activate your license with your new software license key. - If this is the first time you are using a software license key, you can skip step 1. If You Use a Hardware Key - Insert the hardware key into a USB port of the computer running The Observer XT. - Start The Observer XT 17. The program automatically detects the old license on the hardware key and the Enter Upgrade Key window appears. - Enter the numbers supplied to you by Noldus IT, normally sent by e-mail or included in your welcome letter. If You Already Upgraded to The Observer XT 17 and Purchased an Extra Module - In The Observer XT 17, choose Help > Upgrade. - Enter the upgrade key supplied to you by Noldus IT. Notes - Installing The Observer XT 17 installs it alongside previous versions of The Observer XT. - You cannot record video directly in The Observer XT 17. If you previously recorded videos in a Live Observation project with The Observer XT 12.5 or an older version, recording devices such as webcams will be removed from the project. It is recommended to use MediaRecorder to record video and control the start and stop of recording with commands from The Observer XT by selecting MediaRecorder as an external device. The Observer XT Trial Version Overview Use the trial version to try out The Observer XT for free for a limited period. Restrictions - Valid for 14 days from the day of activation. Prerequisites - Your computer meets the system requirements. Procedure - Go to the Noldus website and navigate to The Observer XT product page for animal behavior research or human behavior research. - Click Free Trial to receive a free trial license number by e-mail. - Install The Observer XT 17 and start it. - In the window that opens, choose Activate software license key and click OK. - Select either Floating or Fixed and click OK. - Enter your activation key in the window that appears and click OK. Notes - To see how many days remain in your trial, choose Help > About The Observer XT > License Info. Preferences Overview Use Preferences to configure the following settings: - Terminology used in the program. - Warning messages to display. - File locations. - The time interval at which The Observer XT saves your project. - Connection settings with other software, such as MediaRecorder. - Connection settings with Viso. Accessing Preferences Choose File > Preferences and select one of the options described below. Restart The Observer XT after editing these preferences. Restore Defaults - To return to the default settings, click the Reset to Default button. This resets preferences in all tabs, not only the current tab. - Important: If you have entered settings for N-Linx or Viso, you must re-enter them after clicking Reset to Default. Write down your settings before resetting. Terminology Choose File > Preferences > Terminology. - Enter custom singular and plural terms for subjects. For example, if the subjects of your study are children, you can enter "child" and "children". - Be aware that changing the terminology means the terms in the Help documentation and other materials will no longer match the terms displayed in the program. Warnings Choose File > Preferences > Warnings. - Select the situations for which you want to receive warnings. All warnings are selected by default. - Select the Never Show Warnings check box to suppress all warnings. File Locations Choose File > Preferences > File Locations. Default file locations are set during installation. You can change file locations for the following: - Projects – The default project location when creating a new project. - Video Files – The default video file location in the Video Selection window when starting a new observation. - Audio Files – The location for audio files used for coding. - Templates – The default location in which templates are stored. Auto Recovery Choose File > Preferences > Auto Recovery. - Auto Recovery saves all data from The Observer XT to a temporary file located in the folder with the same name as your project, prefixed with a tilde (~), under C:\ProgramData\Noldus\The Observer\XT 17\Temp. - Media files and external data files are not saved to this temporary folder. Saving and Recovery Settings - Your data are only saved in the project file when you manually save them (choose File > Save Project). - By default, auto recovery is enabled and your data are saved to a temporary file every five minutes. - Optionally change the interval. Noldus recommends leaving auto recovery enabled. --- ## The Observer XT 17 - Installation - Use Limitation, Liability, and Indemnification URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-use-limitation-liability-and-indemnification Chapter: The Observer XT Use Limitation, Liability, and Indemnification Permitted and Prohibited Uses - The Software is intended for research or training purposes only. - End-User agrees not to use the Software for diagnosis or treatment of disease in human subjects. - End-User agrees not to use the Software in any application where the failure, malfunction, or inaccuracy of the Software carries the risk of death or bodily injury. - Noldus Software shall not be used for collection of biometric data from human subjects without prior informed consent from the person whose data is being captured. Prohibited Applications - Active defense, meaning embedding Noldus Software in a weapon system. - Biometric data collection in a judicial context with the aim to use such data as evidence in court. Noldus Software cannot and shall not be used as a lie detector. - Surveillance of people in public spaces for security purposes. - Any other use that may potentially violate fundamental human rights. If Noldus notices that its Software is used for applications that it does not approve, this may lead to discontinuation of customer support and termination of the EULA. Exclusion of Indirect Losses - In no event will Noldus or the Authorized Partners be liable to the End-User for indirect losses or for special, incidental, consequential, exemplary, enhanced, or punitive damages. - This exclusion includes without limitation any damages resulting from interruption of business, loss of use, loss of profits or revenue, or loss of business, arising out of or in connection with this EULA or the Software. - This exclusion applies regardless of whether Noldus, the Authorized Partners, End-User, or any other person or entity has been advised of or could have reasonably foreseen the possibility of such damages. - If liability exists despite the provisions of this EULA, only direct damage will be eligible for reimbursement. Additional Liability Exclusions Noldus and Authorized Partners shall not have any liability under this EULA in the event of: - End-User's use of the Software other than in accordance with the permitted use provisions. - Direct and indirect consequences of the End-User's failing to adhere strictly to the user documentation provided or made available by Noldus or the Authorized Partner. - Any loss of or damage to files howsoever caused. Liability Cap Save for gross negligence or willful misconduct of Noldus or its officers, the Authorized Partner, or third parties engaged by Noldus, any and all liability of Noldus or the Authorized Partner arising out of or relating to this EULA or the Software is limited to an amount equal to the purchase price or license fees paid by the End-User for the specific Software from which the liability arises. A claim will be unenforceable and lapse unless Noldus or the Authorized Partner receives written notice no later than 6 months after the discovery of an event or circumstance that gives or may give rise to that claim. Noldus Indemnification of End-User Noldus will hold harmless, defend, and indemnify End-User from and against all losses, damages, claims, liabilities, and expenses arising out of any third party claim that End-User's use of the Software infringes the intellectual property rights of such third party. If such a claim is made or appears likely to be made, Noldus at its option will: - Procure for the End-User the right to continue to use the Software, or - Modify or replace the Software so that it is no longer infringing in a manner that substantially retains its functionality and quality, or - Require End-User to terminate the use of and return the Software and refund a pro rata portion of the amount paid by End-User for the infringing Software. Noldus will have no liability to End-User if the infringement results from use of the Software in combination with software not provided by Noldus, or from modifications made by Noldus to conform to specifications provided by End-User. The indemnification obligations are subject to: - End-User giving Noldus prompt written notice of any claim. - Transfer of sole control of the defense and any related settlement negotiations to Noldus. - End-User's cooperation, at Noldus' expense, in the defense of such claim. This section states End-User's sole and exclusive remedies for third party intellectual property infringement claims. End-User Indemnification of Noldus End-User shall indemnify and hold harmless Noldus, the Authorized Partners, and third parties engaged by Noldus from and against any and all losses arising out of or caused by: - Any failure in the performance of the obligations of the End-User under the law, this EULA, or Noldus' General Terms and Conditions. - Any and all third party claims on any grounds whatsoever, directly or indirectly related to the End-User's use of the Software, the contents thereof, or any results or materials generated by the Software. Acknowledgment of Liability Limitations The limitation of liability provisions shall apply even if End-User's remedies under this EULA fail of their essential purpose. Noldus and End-User acknowledge and agree that the parties entered into this EULA in reliance upon the limitations of liability set forth in this section, that the same reflect an allocation of risk between the parties, and that the same form an essential basis of the bargain between the parties. --- ## The Observer XT 17 - Installation - Warranty Conditions and Limitations URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-installation-warranty-conditions-and-limitations Chapter: The Observer XT Warranty Conditions and Limitations Conditions for Warranty Coverage - Noldus is notified in writing within 14 days after any non-conformity of the Software was known or should reasonably have been known to End-User, and the End-User has made available all the information that might reasonably be required to allow Noldus to investigate, recreate, and where possible remedy a non-conformity. - The Software has not been altered, repaired, or modified by any party other than Noldus or a third party provider approved by Noldus. - The Software has not been used with software or a computer platform other than set out in the applicable documents, subjected to negligence, or computer or electrical malfunction. - The Software was not used, adjusted, or installed other than in accordance with instructions by Noldus. Disclaimer of Implied Warranties Other than set out in the warranty conditions, no warranties are expressed or implied with respect to Software or any element thereof, including without limitation its quality, performance, accuracy, merchantability, or suitability or fitness for any purpose, whether or not that purpose has been communicated by End-User to Noldus. The Software is a general product developed by Noldus for a wide range of solutions, requirements, and situations, and End-User is responsible for purchasing the Software required for their needs. Noldus explicitly does not warrant that the Software shall be entirely without error or fault nor that it will operate without interruption. End-User agrees that such errors, faults, or interruptions shall not be deemed material cause to terminate this EULA. Scope of Warranty Coverage - The warranty applies only to the first installation of the Software. - The warranty will not apply, resume, or renew upon delivery or installation of any subsequent update or upgrade to the Software. - The warranty will not apply upon any alteration in the number of EULAs granted for use of the Software. - The warranty will not apply to any other extensions, upgrades, or alterations to the Software where the Software has previously been delivered to or installed by the End-User. Exclusions from Warranty - Software that is licensed or otherwise made available at no cost. - Software designated as prototype, alpha, or beta code. - All such excluded Software is provided as-is and without warranty, representation, or liability. Warranty Remedies Upon receipt of an End-User's written notice of the Software not conforming to the Specifications during the Warranty Period, Noldus shall at its option and in its sole discretion: - Assist the Customer in correcting or replacing the non-conforming Software, or - Terminate the EULA immediately and refund the purchase price paid by the End-User. The remedies described above shall be End-User's sole and exclusive remedies. Upon expiration of the Warranty Period, Noldus shall have no obligation to provide such remedies. Support and Maintenance Noldus and Authorized Partners are not responsible for maintaining or supporting use of the Software, nor obligated to provide any updates, fixes, or support to the Software, unless otherwise expressly agreed in writing between End-User and Noldus or the Authorized Partners. --- ## The Observer XT 17 - Lag Sequential Analysis - Lag Sequential Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-lag-sequential-analysis-lag-sequential-analysis Chapter: The Observer XT Lag Sequential Analysis What Is Lag Sequential Analysis? Transitions Between Events In The Observer XT, Lag Sequential Analysis calculates the frequency of transitions between pairs of events within a certain lag. Lag Sequential Analysis allows you to answer questions like: - How many times is the event Mother Smiles followed by the event Baby Smiles? - How likely is the dog's behavior Ignores Trainer preceded by each type of command by the trainer? - How often is Courtship Song by a fruit fly male followed by Mating? Important Terms in Lag Sequential Analysis Criterion – Of a pair of behaviors, the first one is called Criterion. Target – Of a pair of behaviors, the second one is called Target. State Lag – State lags are transitions between events that directly follow each other or are separated by a specific number (lag order) of other events. For example, from an event to the next one (lag order +1), or to the second next (lag order +2), the third next, etc. You can calculate transitions with a lag order from -9 to +9. The time between the Criterion and the Target does not influence your results. Time Lag – Time lags are transitions between events within a specific time window, independent of how many events are between them. You can calculate transitions, for example, from an event to those events occurring in the next 1 minute. Since there may be more than one Target event in that 1 minute window, Time Lag analysis generates multiple transitions from the same Criterion. General Procedure Aim: To analyze how often or how likely an event is followed or preceded by other events. Prerequisites: - Your license for The Observer XT includes the Advanced Analysis Module. - You carried out at least one observation. Procedure: - Make sure that the data profile specifying the data you want to analyze is active, that is, highlighted in blue in the Project Explorer. - Do one of the following: - Choose Analyze > Lag Sequential Analysis > New. - In the Project Explorer, click the Analyses folder. In the window that appears, choose Analyze Data > Lag Sequential Analysis. - In the Project Explorer under Analyses, click Lag Sequential Analyses and then New Lag Sequential Analysis. - A table with question marks appears. Click the Calculate button on the toolbar to perform the analysis. Note: By default, the table contains a State Lag - Order 1 analysis with frequencies. Lag Sequential Analysis Options Aim: To choose the type of lag sequential analysis and other settings. Prerequisites: - Your license for The Observer XT includes the Advanced Analysis Module. - You carried out at least one observation. - You opened the Lag Sequential Analysis window (Analyze > Lag Sequential Analysis). Procedure: Click the Settings button on the toolbar and select the following options: - Lag Type - Restrict Lag to Subject-Behavior Group - Frequency or Probability - Missing values and number of decimals Lag Type Select one of the following: - State Lag – Enter the lag order you want analysis to be based on. For example, to analyze transitions from each event to the next one, enter 1. If you want to calculate transitions from each event to the second next, enter 2. If you want to calculate transitions from each event to the previous third event, enter -3. By default, 1 is selected. - Time Lag – Enter the limits of the time window. This time window will be applied to each Criterion event. By default, From 0 to 1 sec is selected, that is, transitions are counted from each event to any event occurring up to 1 second later. You have the following additional options: - Ignore Recurring Criteria – Select this option if you want to exclude instances of a criterion event that occur in the same time lag. - Ignore Recurring Targets – Select this option if you want to exclude second, third, etc. instances of a target event that occur within the same time lag. Restrict Lag to Subject-Behavior Group Select this option to calculate the transitions within subject and behavior groups. For example, select this option to calculate transitions within the behavior groups Locomotion and Social Behavior, that is, from an event of Locomotion to another event of Locomotion, and from an event of Social Behavior to another event of Social Behavior, not from an event of Locomotion to an event of Social Behavior (or vice versa). If you leave this option cleared, transitions are calculated regardless of which group events belong to. Leave the option deselected to calculate transitions between the behavior of one subject (for example Mother) and another subject (for example Child). Frequency or Probability - Frequency – To calculate the number of transitions from the criterion to the target. - Probability – To calculate the number of transitions for a particular combination of criterion and target divided by the total number of transitions from that criterion. The sum of the transition probabilities for each criterion event equals 1. Select the Only Show When Greater Than option if you want to display only the transition probabilities that are greater than a specific threshold. Missing Values and Number of Decimals - Show Missing Values As – Choose the character you want to have displayed for missing values, that is, cells in which transitions are not calculated. For example, transitions between behaviors of different groups when you have selected the Restrict Lag to Subject-Behavior Group option. - Number of Decimals – Choose the number of decimals in the matrix cells. This option is only available if you have chosen to display lag probabilities. Note: If you defined a range of numerical modifiers instead of predefined values, many different values may have been scored. If you subsequently carry out a Lag Sequential Analysis, this may result in many cells in the analysis result. This may especially happen if you have numerical modifiers with several decimals, or if you have imported external data as numerical modifiers. Deselect Modifiers in the Layout window, or create a Data Selection to reduce the data to analyze. The Lag Sequential Analysis Result Results Table The Lag Sequential Analysis results table contains the following: - A – Cells containing the values of independent variables. - B – Cells containing counts or probabilities of transition. Each row represents a criterion event and each column a target event. Each cell contains, depending on what you have chosen in your analysis settings: - If you have chosen Frequency, the number of transitions from the criterion (on the row) to the target event (on the column). - If you have chosen Probability, the probability of transition from the criterion event to the target event. - C – Main headers for categories (for example, Observations, Subjects, Behaviors, etc.). - D – Secondary headers for the elements within a category. Dependent on your choices for the layout, some of the options may not be shown. Understanding X0 and Y0 Transitions are also counted when no criterion can be found for a target or vice versa. Such transitions can be found in the cells of the matrix indicated by X0 (last row) or Y0 (last column). X0 refers to transitions where a target has been identified but the criterion is not found. This happens in the following cases: - If the lag is positive – At the start of an observation (or interval defined within an observation). If the first event is 2.00 Sit, this event is considered to be the target of no event. A transition is counted from X0 to 2.00 Sit. - If the lag is negative – At the end of an observation or interval, where the last event is considered to be the target of no event. - Special case – In Time Lag analysis, when an event is preceded by a gap longer than the time lag of the previous event. For example, the event Answer occurs after a gap. If the time lag is shorter than the time between Answer and any preceding event, then Answer is considered to be the target of no event. A transition is counted from X0 to Answer. Y0 refers to transitions where no target is found. This happens in the following cases: - If the lag is positive – At the end of an observation or interval, where the last event is considered to be the criterion of no event. - If the lag is negative – At the start of an observation or interval, where the first event is considered to be the criterion of no event. - Special case – In Time Lag analysis, when there is no event within a time lag. For example, the event Play Music is not followed by any other event in the next 10 seconds. With a time lag of 5 seconds, the time lag of Play Music does not cover any target event. A transition is counted from Play Music to Y0. Note: when at least one event is found within a time lag, the gap is not considered, so the transition from Play Music to Y0 is not counted. Instead, the transition from Play Music to that event is counted. Notes: - X0 and Y0 transitions are included in the probability calculations to quantify the probability that an event is not preceded nor followed by any events. - For instantaneous sampling – X0 and Y0 do not indicate transitions from/to samples not scored. In lag sequential analysis, samples not scored are ignored. Save a Result To save a lag sequential analysis result, click the Archive button on the toolbar of the result window. To re-open a saved result, choose Analyze > Lag Sequential Analysis > Open Archive. Notes: - You cannot edit the content of the statistics result. - To print a result table, choose File > Print. We advise you to select Landscape mode prior to printing. Customize the Analysis Results Aim: To change the layout of the analysis results table. Prerequisites: - Your license for The Observer XT includes the Advanced Analysis Module. - You carried out at least one observation. - You opened the Lag Sequential Analysis window (Analyze > Lag Sequential Analysis). Procedure: Click the Layout button on the toolbar. Specify what the resulting transition matrix will look like. Select the type of elements you want to view on rows, columns, and separate sheets. Clear the selection for any element type you do not want included in the matrix. - Criteria – Are displayed on rows. Select the element types to include. - Targets – Are displayed on columns. Select the element types to include. - On Sheets – Select the element types you want to view in separate sheets. Show Elements Not Scored Select this option if you want to have all elements of your coding scheme shown in the matrix, including those you have not scored in any observation. For not scored elements, cells will contain zeros or the missing value symbol. If you keep this option cleared, the matrix lists the elements scored in at least one observation. --- ## The Observer XT 17 - Lag Sequential Analysis - Lag Sequential Analysis in Detail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-lag-sequential-analysis-lag-sequential-analysis-in-detail Chapter: The Observer XT Lag Sequential Analysis in Detail State Lag in Detail A positive value of lag order N means that the program counts N events forward in time from the criterion event. The transition is established from the criterion to the Nth event. A negative value for N means that the program counts events back in time. A state lag with order +1 results in the following transitions: - X0 > Stand - Stand > Sit - Sit > Stand (2nd) - Stand (2nd) > Walk - Walk > Other locomotion - Other locomotion > Y0 There are also transitions when a criterion is found but no target, or the other way round. In the example above, from no event (X0) to 0.0 Stand, and from Other locomotion to no event (Y0). See Understanding X0 and Y0. A state lag with order -3 results in the following transitions: - Stand (2nd) > X0 - Walk > Stand (1st) - Other locomotion > Sit - Y0 > Stand (2nd) Gaps between events are not taken into account, so there is no transition from or to a gap. Time Lag in Detail The time lag can be negative, positive, or partly negative and partly positive (for example, from -2s to +2s around each event). Transitions are counted from an event to another event starting within the time lag. Entering From 0 sec to 1 minute next to Time Lag results in the following transitions: - X0 > Stand - X0 > Sit - X0 > Stand (2nd) - Stand > Sit - Stand > Stand (2nd) - Sit > Stand (2nd) - Sit > Y0 - Stand (2nd) > Y0 - Walk > Other locomotion - Walk > Y0 - Other locomotion > Y0 Time Lag and Gaps Transitions are also counted when no event is found in the time lag, for example at the start and end of the observation. See Understanding X0 and Y0. If there is a gap between events, the program does not count transitions from an event to the gap that falls in its time lag, unless there is no event at all in that lag. When the time lag is partly negative and partly positive, transitions are calculated from the focal event to the events that precede or follow it. To Ignore Recurring Criteria If you select the Ignore Recurring Criteria option, all events of the same type as the criterion that occur within the time lag are ignored as criterion events. Select this option when events of the same type occur next to each other, and you want to make sure that transitions from those events are not counted twice. If the time lag is at least partly negative, the recurring criteria are ignored within a time interval around the focal criterion whose length is twice as long as the longest side of the time lag. For example, if the time lag is set to from -10s to +5s, selecting Ignore Recurring Criteria removes the recurring criteria from -10s to +10s for each focal criterion. If the time lag is set to from -3s to +5s, recurring criteria are removed from -5s to +5s around each focal criterion. To Ignore Recurring Targets If you select the Ignore Recurring Targets option, the second, third, and subsequent instances of the same target within the time lag are ignored. Select this option when events of the same type occur next to each other, and you want to make sure that multiple transitions to those events are not counted. If the time lag is at least partly negative, the recurring targets are also removed in the negative part of the lag. Transitions with Events with Duration Transitions indicate a change from one event (criterion) to another (target) in a temporal sequence. In the case of state behaviors, which have a start and a stop event, transitions are always counted using start events only, even if you have coded the end event manually. Transitions and Instantaneous Sampling If you have collected data with Instantaneous sampling, samples not scored are not taken into account when calculating transitions. For example, the sequence of samples (sample interval = 10s): - 0.0 A - 10.0 - (not scored) - 20.0 B Results in a transition from 0.0 A to 20.0 B. This is the same result as if A and B were scored with Continuous sampling. Transitions and Multiple Event Logs Lag sequential analysis is performed on each event log separately. If an observation contains multiple event logs and you de-select Event Logs in the Layout page of the Lag Sequential Analysis window, transitions are counted within each event log and then summed up in the transition matrix. Transitions across event logs are not calculated. To calculate transitions from an event in one event log to an event in another event log, follow the procedure below: - In your data profile, select Intervals by Manual Selection. - Under Begin Interval, specify the event you want to use as a criterion (for example, Game starts). - Under End Interval, specify the end of the same event (if you want to analyze transitions as long as the event occurs) or a time value (if you want to apply a time lag; do this if Game starts is an event without duration). - Calculate statistics with this data profile. Make sure that you include the Total Number as a statistic. See Statistics in Detail in Calculate Statistics. The Total Number column shows the number of times that a behavior occurs in the specified intervals. The Happy column/row displays the number of Happy occurrences in the specified time after Game starts took place. This provides results similar to time lag sequential analysis. Source: The Observer XT 17 Help - Lag Sequential Analysis, Noldus Information Technology --- ## The Observer XT 17 - Lag Sequential Analysis - Time Formats URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-lag-sequential-analysis-time-formats Chapter: The Observer XT Time Formats When you have selected to show Intervals or Independent Variables, some of the cells contain time values. To specify the format of time, choose Setup > Project Settings > Time Formats. See Time Formats in Set Up Your Project. Decimal Symbol Change your decimal symbol in Windows regional settings. Then restart The Observer and re-run the analysis. Save Your Analysis Settings To save the settings specified in your analysis, click the Set to Default button in the Lag Sequential Analysis Settings window. If this window is gone, click Settings on top of the result window and click Set as Default in the window that appears. Apply Settings to a New Analysis If you are about to run a new Lag Sequential Analysis and want to recall default settings specified earlier, click the Reset to Default button in the Lag Sequential Analysis Settings window. Notes - If you select Observations under On Sheets and keep Intervals selected, each sheet includes the layout for all observations, but only the results for the corresponding observation (you have to scroll down the result to find them). To reduce the size of the sheets, de-select Intervals. - It is not possible to de-select behaviors or move subjects, behaviors, modifiers, or Independent Variables to On Sheets. --- ## The Observer XT 17 - Media Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-media-files Chapter: The Observer XT Media Files Formats, Containers and Codecs The term "video format" can often be confusing, because it involves two distinct and very different technology concepts: containers (created by software called a multiplexer) and codecs (short for coder/decoder). The container describes the structure of the file where the video and audio streams are stored, how they are interleaved, and which codecs are used by which stream. It is used to package the video and its components (audio/metadata) and is usually identified by a file extension such as .AVI or .MPG. Codecs are used inside of a container. A codec is a way of encoding audio or video into a stream of bytes. It is the method used to encode the video and is the chief determiner of quality. The important thing to realize is that most good container formats can hold many codecs. Even .AVI files can hold a wide variety of codecs as their contents. The container does not decide the quality or features of the video itself; that is up to the codec. The proper way to describe video is to indicate both: for example, an .AVI file containing DivX video and MP2 audio. How Do I Know the Format of My Video File? There are free tools available to see what format your video file has and which codec, container, and audio format is used. Examples are MediaInfo and GSpot. GSpot gives a lot of information on your video files, but has not been maintained since 2007. - https://mediaarea.net/nl/MediaInfo - http://www.headbands.com/gspot/ Play Media in The Observer XT Decoders Installed with The Observer XT Decoders are needed to play back media files. When you install The Observer XT, it installs the LeadTools Package 20.0 to play back video. Important: Codecs from, for example, DVD burning software may conflict with the ones used by The Observer XT. See Codecs Installed by Other Programs. The LeadTools Codec Package 20.0 contains the following: - MP4 Demultiplexer - MPEG Demultiplexer - H.264/AVC Video Decoder - MPEG-2 Video Decoder - MPEG-4 Video Decoder - AAC Audio Decoder Supported Formats Supported Video Formats See "How Do I Know the Format of My Video File?" to determine video formats. The Observer XT supports playback of the following digital video formats: - MPEG-1 (*.mpg, *.mpeg) - MPEG-2 (*.mpg, *.mpeg, *.vob) - MPEG-4 (*.avi) including DivX, Xvid, and H.264 * - Uncompressed AVI (*.avi) - DV-AVI (*.avi) - MPEG-4 QuickTime (*.mov) Note that not all playback speeds may be available in The Observer XT, even for supported formats. * These video formats are not supported for creating an Episode Selection. Important: We recommend not opening a video file directly from a mobile device (a smartphone, tablet, etc.). First copy the files to the PC with The Observer XT, then open that copy in the observation. Supported Audio Formats - MP3 (*.mp3) - WAV (*.wav) - WMA (*.wma) AAC (*.aac) audio files are not supported, but video files with .aac audio are. The maximum number of audio files that can be opened is determined by your license. With the Single Media Module you can import one audio file. With the Media Module, you can import up to twenty audio files in a single observation. Supported Audio Formats for Visualization You can visualize the following audio formats: - MPEG Audio Stream, Layer 1 (*.mp1) - MPEG Audio Stream, Layer 2 (*.mp2) - MPEG Audio Stream, Layer 3 (*.mp3) - MPEG-2 Advanced Audio Coding file (*.aac) - AC3 Audio file format (*.ac3) - PCM – Pulse-Code Modulation (*.wav) - ADPCM – Adaptive Differential Pulse-Code Modulation (*.wav) - Adaptive Multi-Rate ACELP Codec (*.amr) - Windows Media Audio (*.wma) When you play your video at a higher or lower speed, .wma audio files are still played at normal speed. Other formats may be displayed depending on the audio decoders installed on your computer. Troubleshooting Invalid Video/Audio When you try to open a video/audio file, you may get a message stating that the file is of invalid type. This can occur for different reasons, for example the appropriate codec is not installed, the codec cannot play that format, the file does not contain a video stream, or the appropriate demultiplexer is not installed. The warning message shows details of the format The Observer XT tries to play. Check in the list above whether it corresponds to the supported formats and that the necessary codecs are installed. If necessary, contact the Noldus Help Desk to solve this issue. When a media file is opened and the audio codec is not found, an error message appears; however, the video plays correctly in The Observer XT. Record Video Record Video with MediaRecorder We recommend recording video with MediaRecorder and using these videos in The Observer XT for offline scoring. See the MediaRecorder documentation for an overview of the supported cameras. Codecs Installed by Other Programs Codecs Can Give Problems Codecs for media players and DVD burning software already installed on your PC may conflict with the codecs that are installed with The Observer XT. It may happen that The Observer XT uses the wrong codec to play back the videos. This may lead to wrong time stamps in the event log, or videos that cannot be played back. Therefore we strongly recommend not installing such programs on the computer with The Observer XT. Check Which Codecs The Observer XT Uses - Open the observation containing video. - Right-click the video window and select Properties. The video and audio codecs that are used by The Observer XT are shown next to Video Codec and Audio Codec. Additional information is shown under Filter Details. The Observer XT provides some audio codecs (see Play Media in The Observer XT). To play back other audio files you must have the right codecs installed. If the required codecs are not available, The Observer XT cannot play it back properly. Please note that The Observer XT plays audio files with a maximum of two audio channels. Source: The Observer XT 17 Help - Media Files, Noldus Information Technology --- ## The Observer XT 17 - Reliability Analysis - Choose the Observations to Compare URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-choose-the-observations-to-compare Chapter: The Observer XT Choose the Observations to Compare Aim To select which pairs of observations to use for the Reliability Analysis. Prerequisites - You carried out at least one pair of observations. - The Settings tab of the Reliability Analysis Settings window is open (Choose Analyze > Reliability Analysis > New > Settings). Procedure Select an observation in the list with observations and click the Add>> button. Add as many pairs as you want. Tip: If you have many observations, type part of the name in the Filter Observations field. For example, if you have a large number of observations with the type of patients file (on paper or on tablet) in the observation name, type the name of the patients file type in the Filter Observations field. As a result, the list of observations only shows the observations with that type in the name. To reset the filter, click the 'x' icon at the right of the Filter Observations field. Notes - If your observations contain two or more event logs, you must select single event logs for comparison. To do so, create a data profile with a filter on the event logs. See Filter Observations. - If the list does not include an observation, it could be due to that observation containing errors. Open the observation and check for errors. See Check the Event Log for Errors. - Reliability analysis is meant to be applied to whole observations. It is recommended not to apply a data profile where data are merged or split in intervals or time bins. - If your data profile contains more than one result container (see Create Groups of Data), you need to specify one of them for each observation. The lists show all the combinations of observations and result containers. - You can also add an observation pair in the Statistics view of the reliability analysis results by clicking the empty row at the bottom (indicated by Click to Add Observation). - Always select the observation that is the 'gold standard' as the first observation in a pair. When you view the paired events in the comparison list, you see the video image associated with the first observation, not the second. Edit the Selection To Replace Observations To replace observations in a pair in the Observation Pairs list, click on the observation you want to replace. The observation name becomes highlighted in blue. Now add the new observation; this will replace the old one. To Remove Pairs To remove a specific observation pair, click on one of the observations of that pair and click the Remove pair button. To remove the whole list of observation pairs, click the Remove all pairs button. Choose the Comparison Settings Aim To choose the way The Observer XT compares the observation pairs. Prerequisites - You carried out at least one pair of observations. - The Settings tab of the Reliability Analysis Settings window is open (Choose Analyze > Reliability Analysis > New > Settings). Tip: Click on one of the Quick Help buttons to read more about an option or setting. Settings - Comparison method - Tolerance window - Analyze gaps between events - Comparison scope - Synchronization - Show extra Kappa statistics - Combine multiple pairs of observations - Modifiers Comparison Method Select a comparison method from the list. See Reliability Analysis - Four Methods. Tolerance Window The Tolerance window setting is only available if you have selected the Frequency/Sequence comparison method. The tolerance window defines how accurate the timing of an event must be (in the comparison between two observations in Reliability Analysis) to be considered an agreement or not. For example, if in Observation 1 the event 'Gaze at screen' occurs at 4.0 s and stops at 6.0 s while in Observation 2 it starts at 6.5 s, that is counted as an agreement when the tolerance window is set to 3 s. However, if the tolerance window is set to 1 s, the two events are counted as a disagreement as the mismatch between their start times (2.5 s) is greater than the tolerance window. Analyze Gaps Between Events Analyze gaps between events is only available if you select Frequency/Sequence or Duration/Sequence as a comparison method. With this option, The Observer XT also takes gaps between events into account when comparing two observations. A gap is a time-interval in an observation in which no event was scored for a specific behavior group. Important: Analyzing gaps between events may give unexpected results. We advise you to only select it if the stop of events are important for your analysis. The example in the figure below shows the effect of including gaps in a reliability analysis with the Frequency/Sequence method. The figure shows two observations scored with two events, A and B. Observation 1 contains gaps, Observation 2 does not. The way gaps are compared differs between the comparison methods and also between behavior group types. See Reliability Analysis and Gaps. Comparison Scope With comparison scope, you define what section of the observations is compared for analysis. Select one of the following: - Compare all events (default) – To compare all the events no matter whether one observation is longer than the other. - Compare time based intersection – To compare two observations that differ in length, comparing only the events in the time period shared by both observations. For example, two observers score data from a video file. One observer starts scoring later and stops earlier in the video than the other observer. The result is that the second observation will be longer than the other. If you select Compare time based intersection, The Observer compares the video segments that both observers scored. Synchronization To select the way two observations in a pair are aligned: - Use absolute start times (clock times) – Select this option if your observations were scored live, and you want to align them according to their 'true' start time (for example, 14h 23min 56s). - Align the start of observations – Select this option if you coded from video and started your observations at the same moment in the video. Do not use this option when you score live and observers do not start scoring at the exact same time. --- ## The Observer XT 17 - Reliability Analysis - Comparison List URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-comparison-list Chapter: The Observer XT Comparison List How to Display the Comparison List The Comparison List is available when you used the Frequency/Sequence comparison method. To display it: - Choose Analyze > Reliability Analysis > New. - Select the Frequency/Sequence method, specify the other settings and click OK. See Reliability Analysis General Procedure. - Click the Comparison List button on the toolbar of the Reliability Analysis Results. - Select the pair from the list next to the Comparison List button. The Comparison List Window The Comparison List lists all agreements and disagreements of the observations compared with the Frequency/Sequence method. It contains, from left to right: - The Run number of the reliability analysis algorithm. If you hover over this number with the mouse pointer, a tooltip is displayed with a short explanation. By default, the Run column is hidden. To show it, choose View Settings > Run. - The events with duration (with their start and stop time) and events without duration (with their start time) of the first observation of each pair selected in the analysis settings window. - The Result of the comparison between the records of the two observations. - The events with duration (with their start and stop time) and events without duration (with their start time) of the second observation. The Comparison List in Detail Symbols - Marks starts of events with duration (mutually exclusive and start-stop), including the . - Marks events without duration. - Marks an agreement between an event in the two observations. - Marks a disagreement between an event in the two observations. Observation Start Observation start marks the observation start time relative to the point where the program starts comparing the data files. See Synchronization. Please note: - If you have selected Use the Start of Observations from the Synchronization list and you are comparing live observations, Observation Start shows the time difference between the two start times. - If you have selected Align First Scored Events from the Synchronization list and there are no events starting at 0:00, the comparison starts at the first scored event, which gets time 0.0. Therefore, Observation Start is negative (for example, -50.4 if the first event occurs at 50.4 s). - If you have started observing from a point in a media file later than 0:00, and you select Align Video Start Time from the Synchronization list, Observation Start shows the start of the observation relative to the video start time (for example, 60.0 if you start observing at 1 minute in the video file). Synchronization Point The point in time where the program starts comparing the two files. It is always the same for both observations. Events in one observation are paired to when there is no data from the same subject and behavior group in the other observation. This results in a disagreement. Gaps in the observations are only analyzed when the option Analyze gaps between events has been selected. Events in one observation are paired to when the closest event in the other observation is the stop of an event with duration that is not followed by the start of a new one. For example, when you score the stop of a behavior by using the Stop code. These instances usually result in disagreements. When the gaps overlap in two observations, you get an agreement between a pair of . See also Reliability Analysis and Gaps. Disagreements Caused by Modifiers Events with the same subject and behavior result in disagreements if they have different modifiers. If the modifiers are numerical, they result in a disagreement only if they differ by more than the margin value set. See Modifiers. Edit the Comparison List To Change the Time Format By default, the Comparison List shows the event times as time elapsed from the point where the two observations are aligned. To change the format, do so in the Project Settings. To Change the Decimal Symbol Change the decimal symbol in Windows Regional Settings. Then restart The Observer XT and re-run the analysis. If you select Include all results combined for multiple comparisons (see Combine multiple pairs of observations), the comparison list of the combined results sums up all agreements and disagreements from all pairs of observations. Effect of the Coding Scheme on Reliability Analysis How Behaviors Are Organized Matters Reliability analysis works differently for behaviors that exclude each other in a mutually exclusive behavior group and behaviors that may overlap in a Start-Stop group. - Behaviors in a Mutually Exclusive group are compared with each other within the group. - Behaviors in a Start-Stop group are compared with the same behavior in the other observation. This may result in more disagreements in a Start-Stop group than in a Mutually Exclusive group. See: - Effect of Behavior Group - Frequency/Sequence Method - Effect of Behavior Group - Duration/Sequence Method See also: - Behavior Group Types in Select Data for Analysis --- ## The Observer XT 17 - Reliability Analysis - Confusion Matrix URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-confusion-matrix Chapter: The Observer XT Confusion Matrix How to Display the Confusion Matrix - Choose Analyze > Reliability Analysis > New. - Select the settings and click OK. See Reliability Analysis General Procedure. - Click the Confusion Matrix button on the toolbar of the Reliability Analysis Results. The Confusion Matrix The Confusion Matrix displays agreements and disagreements of the observation pairs in a matrix. This matrix has one row and one column for each combination of Subject, Behavior, and Modifiers scored in those observations. If you have multiple observation pairs, you can select the pairs from the list on the toolbar. If you selected the option Include All Results Combined in the Comparison Settings (see Combine Multiple Pairs of Observations), there is an additional pair in the list on the toolbar: Observations A Combined - Observations B Combined. Cell Values The values of the confusion matrix can be understood as follows: - Dark blue cells are agreements. - White cells including Window Error, Modifier Error and No Records are disagreements. - Light blue cells along the diagonals are displayed when your coding scheme contains numerical modifiers and you set a margin to the modifiers in the Reliability Analysis Settings. You can select a margin if you choose Frequency/Sequence or Duration/Sequence as the comparison method. The light blue cells contain agreements of events with modifier values that are not exactly the same in both observations but differ less than the margin. - Additional rows and columns indicate special cases, including , No Records, Error, and Window Error. can appear in the table when you chose Frequency/Sequence or Duration/Sequence as the comparison method and you chose to analyze gaps. It appears in the following cases: - When no behavior is scored at the start of the observation. A state is added at the start of the observation for each behavior of a Start-Stop group, ending with the start of the first behavior of that group. - When a behavior with duration ends, that is, when you press the stop code for a behavior. A state is added that starts at the end of the event and ends at the start of the next occurrence of that behavior. - When the behavior group type is set to Behaviors Cannot Occur at the Same Time, it contains both events with and without duration, and you have only scored events without duration. A state is added at the start of the observation, ending at the end of the observation. No Records Rows and columns named No Records can appear in the table when you chose Frequency/Sequence or Duration/Sequence as the comparison method. It shows the occurrences of events in one observation that cannot be paired with any event in the second observation. No Records appear in the following cases: - There is no data from the same behavior group in the other observation. - When you have selected Compare All Events from the Comparison Scope list and one or both of the following is true: - One observation is longer than the other. - You have aligned the two observations in such a way that one starts earlier than the other. For example, two live observations started at different times, and you have selected Use the Start of Observations as the Synchronization method. Error Rows and columns named Error appear in the table when you chose Frequency or Duration as the comparison method. It shows the number of occurrences (frequency method) or seconds (duration method) that events differ in both observations. - Numbers in the Error row indicate that events occurred more often, or longer, in the first observation of a pair. - Numbers in the Error column indicate that events occurred more often, or longer, in the second observation of a pair. Window Error Rows and columns named Window Error can appear in the Reliability Analysis table when you chose Frequency/Sequence as the comparison method. Rows and columns named Window Error show the disagreements between the events of the same type whose onset times differ by more than the Tolerance window. - The Window Error row shows the disagreements between the same event types where the event in observation 1 (left of the diagonal) occurs earlier than that in observation 2. - The Window Error column shows the disagreements between the same event types where the event in observation 1 occurs later than that in observation 2. Notes - If you have defined two or more observation pairs for comparison, the size of the matrix is constant across pairs of observations, because it includes the combinations of events in all pairs regardless of whether a specific event was scored in a specific pair of observations. This means that if event A was scored in an observation of Pair 1 and in neither observation of Pair 2, the matrix of Pair 2 still contains the row and column for event A. - If you have selected Show Elements Not Scored, the matrix also includes those combinations of Subject, Behavior and their Modifiers that were not scored in those observations. Therefore, the matrix can be much larger. - If you select Include All Results Combined for multiple comparisons (see Combine Multiple Pairs of Observations), the confusion matrix of the combined results page sums up all agreements and disagreements from all pairs of observations. --- ## The Observer XT 17 - Reliability Analysis - Effect of Behavior Group - Frequency/Sequence Meth URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-effect-of-behavior-group-frequencysequence-meth Chapter: The Observer XT Effect of Behavior Group - Frequency/Sequence Method Mutually Exclusive Groups In a Mutually Exclusive group, the behaviors are compared within the group. In the example below, events A, B, and C are part of the same Mutually Exclusive group. Two observations differ in that event B was scored at time 16 in Observation 1 while event C was scored in Observation 2 at that moment. When you do not select Analyze gaps between events and run a Reliability Analysis with the Frequency/Sequence method, one disagreement is found at time 16. See Frequency/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups for what happens when you include gaps between events in the analysis. Start-Stop Groups In a Start-Stop group, each behavior is analyzed independent from the others. The frequency/sequence method searches for matches between event A and event A, between event B and event B, and event C and event C. This means that there will be no disagreements like Event B (Obs 1) - Event C (Obs 2), that you do find with Mutually Exclusive groups. Instead you will find disagreements like Event B (Obs 1) - No event (Obs 2), and disagreements in the time events of the same type were scored in both observations. In the example below, with similar observations as in the example above, Reliability Analysis finds two disagreements. The first disagreement (1 in picture below) is found at time 16.00, because the time of event B in Observation 1 does not match the time of event B in Observation 2. The nearest event B in Observation 2 is from 8.00 to 12.00. This is outside the tolerance window and therefore it is a disagreement. The second disagreement (2 in picture below) is found because event C was scored at time 16.00 in Observation 2, while no event C was scored at that moment in Observation 1. See Frequency/Sequence and Gaps; Start-Stop Behavior Groups for what happens when you include gaps between events in the analysis. Effect of Behavior Group - Duration/Sequence Method One Mutually Exclusive Group In a Mutually Exclusive group, instances of the behaviors within the group are compared. Within the group these behaviors will never overlap. Therefore, within the behavior group, the agreements and disagreements will exclude each other and the total agreement and disagreement will never exceed the observation length. Multiple Mutually Exclusive Groups When you have multiple Mutually Exclusive groups, behaviors from different groups may overlap. This means that also the agreements and disagreements may overlap and the total agreement and disagreement is likely to be larger than the observation length. In the picture below events A and B form one Mutually Exclusive behavior group and events C and D another. Note that the sum of the Agreement and Disagreement is almost twice the observation length. This is because the Agreements and Disagreements in the two groups overlap. See Duration/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups for what happens when you include gaps in your analysis. Start-Stop Groups In a Start-Stop group, behaviors may overlap within the group. Therefore agreements and disagreements may also overlap within the group. See the double disagreement at time 5.5 s in the example below. See Duration/Sequence and Gaps; Start-Stop Behavior Groups for what happens when you include gaps in the analysis. Reliability Analysis and Gaps Definition of a Gap A gap in an observation is the time interval in which no event was scored for a specific behavior group. In the following example, a gap occurs after the end of Event A and before the start of Event B. The two events form the behavior group 'Group AB'. When Do Gaps Occur and How Are They Analyzed? Gaps can occur: - When suspending a live observation. See Reliability Analysis and Gaps when Suspending an Observation. - In behavior groups in which behaviors exclude each other. Gaps in this group type can only occur if the behaviors in the group are not exhaustive, so they do not add up to 100%. The way gaps are treated differs between comparison methods. See: - Frequency/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups - Duration/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups - In behavior groups in which behaviors can overlap. The way gaps are treated differs between comparison methods. See: - Frequency/Sequence and Gaps; Start-Stop Behavior Groups - Duration/Sequence and Gaps; Start-Stop Behavior Groups Reliability Analysis and Gaps When Suspending an Observation Definition of a Gap The interval during which the observation was suspended is treated as a gap. When you score, for example, behavior A and then suspend-resume the observation, you have one occurrence of behavior A with a gap. The reliability analysis then counts two occurrences of behavior A: one before suspend, and one after resume. Example Consider the figure below. It shows part of the visualization of an observation which was suspended and resumed; behavior A was active before and after suspend-resume. In the reliability analysis, this is counted as two occurrences of behavior A as if A was scored again after resuming the observation. How Is the Suspended Time Analyzed? The suspended time is analyzed just like any other gap. This depends on the group type and the comparison method. See: - Frequency/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups - Duration/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups - Frequency/Sequence and Gaps; Start-Stop Behavior Groups - Duration/Sequence and Gaps; Start-Stop Behavior Groups --- ## The Observer XT 17 - Reliability Analysis - Frequency/Sequence and Gaps; Mutually Exclusive, N URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-frequencysequence-and-gaps-mutually-exclusive-n Chapter: The Observer XT Frequency/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups Example The figure below shows the visualization of two observations, Obs 1 and Obs 2, with events (A, B) from a group in which behaviors exclude each other. The behaviors in the group are non-exhaustive, which means that gaps between events may occur. Obs 1 contains two gaps: - From 1.3 to 3.2 s. - From 12.3 s till the end of the observation. Without Analyzing Gaps When you de-select Analyze gaps between events, two agreements and one disagreement are found. - Agreement: 0.0 A (Obs 1) - 0.0 A (Obs 2). - Disagreement: 3.2 A (Obs 1) - 0.0 B (Obs 2). - Agreement: 7.9 A (Obs 1) - 7.9 B (Obs 2). With Analyzing Gaps When you select Analyze gaps between events, the comparison of observations 1 and 2 gives two extra disagreements between a gap in observation 1 and an event in observation 2. This results in the following: - Agreement: 0.0 A (Obs 1) - 0.0 A (Obs 2). - Disagreement: 1.3 (Obs 1) - 0.0 A (Obs 2). - Disagreement: 3.2 A (Obs 1) - 0.0 A (Obs 2) (this is a disagreement because 0.0 A in Obs 2 was already in agreement with event A in Obs 2). - Agreement: 7.9 B (Obs 1) - 7.9 B (Obs 2). - Disagreement: 12.3 (Obs 1) - 7.9 B (Obs 2). If during an observation no behaviors from a mutually exclusive non-exhaustive group are scored, Reliability Analysis will consider a gap for that group from the start to the end of the observation. Duration/Sequence and Gaps; Mutually Exclusive, Non-Exhaustive Behavior Groups Example The figure below shows the visualization of two observations, Obs 1 and Obs 2, with events (A, B) from a group in which behaviors exclude each other. The behaviors in the group are non-exhaustive, which means that gaps between events may occur. Obs 1 contains two gaps: - From 1.3 to 3.2 s. - From 12.3 s till the end of the observation (16.0 s). Obs 2 contains one gap: - From 14.9 s till the end of the observation (16.0 s). Without Analyzing Gaps When you de-select Analyze gaps between events, the comparison of Obs 1 and Obs 2 results in the following three agreements and two disagreements: - Agreement: from 0.0 till 1.3 s; Event A overlaps; duration 1.3 s. - Disagreement: from 1.3 till 3.2 s; gap in Obs 1 and Event A in Obs 2; duration 1.9 s. - Agreement: from 3.2 till 7.9 s; Event A overlaps in both observations; duration 4.7 s. - Agreement: from 7.9 till 12.3 s; Event B overlaps in both observations; duration 4.4 s. - Disagreement: from 12.3 till 14.9 s; gap in Obs 1 and Event B in Obs 2; duration 2.6 s. With Analyzing Gaps When you select Analyze gaps between events, this example contains an extra agreement, because there is an overlapping gap of 1.1 s at the end of both observations. Frequency/Sequence and Gaps: Start-Stop Behavior Groups Gaps in Start-Stop Groups In a behavior group in which behaviors may overlap, each behavior is analyzed independent from the others. The frequency/sequence method searches for matches between event A and event A, and between event B and event B (see Start-Stop groups for a detailed explanation). When you analyze gaps between events, the same is true for the gaps in such groups. For each individual behavior is recorded whether there is a gap or no gap. So the program compares Gap A with Gap A, and Gap B with Gap B. Note: If during an observation a start-stop behavior is not scored, Reliability Analysis will consider a gap for that behavior from the start to the end of the observation. Example Without Analyzing Gaps When you do not analyze gaps between events, the Reliability Analysis gives the following two run 1 agreements, because the events partially overlap in both observations: - Agreement: 0.0 A (Obs 1) - 3.2 A (Obs 2) - Agreement: 9.5 B (Obs 1) - 5.5 B (Obs 2) With Analyzing Gaps When you select Analyze gaps between events, two agreements and one disagreement are added, so you obtain four agreements and one disagreement: - Agreement: 0.0 Gap B (Obs 1) - 0.0 Gap B (Obs 2) - Agreement: 0.0 A (Obs 1) - 3.2 A (Obs 2) - Disagreement: 0.0 A (Obs 1) - 0.0 Gap A (Obs 2) - Agreement: 5.5 Gap A (Obs 1) - 6.1 Gap A (Obs 2) - Agreement: 9.5 B (Obs 1) - 5.5 B (Obs 2) Duration/Sequence and Gaps: Start-Stop Behavior Groups Gaps in Start-Stop Groups In a behavior group in which behaviors may overlap, each behavior is analyzed independent from the others. The duration/sequence method searches for overlaps between event A and event A, and between event B and event B (see Start-Stop groups for an explanation). When you select Analyze gaps between events, the same is true for the gaps in such groups. For each individual behavior is recorded whether there is a gap or no gap. So the program compares overlaps of Gap A with Gap A, and Gap B with Gap B. Example Without Analyzing Gaps When you deselect Analyze gaps between events, comparison of observations 1 and 2 results in the following agreements and disagreements: - Disagreement: from 0.0 till 3.7 s; Event A in Obs 1 and Gap A in Obs 2; duration 3.7 s. - Agreement: from 3.7 till 5.5 s; Event A overlaps; duration 1.8 s. - Disagreement: from 5.5 till 6.1 s; Gap A in Obs 1 and Event A in Obs 2; duration 0.6 s. - Disagreement: from 5.5 till 9.5 s; Gap B in Obs 1 and Event B in Obs 2; duration 4.0 s. - Agreement: from 9.5 till 16 s; Event B overlaps; duration 6.5 s. With Analyzing Gaps When you select Analyze gaps between events, extra agreements are found for Gap B from 0.0 till 5.5 s and for Gap A from 6.1 till 16 s = 9.9 s. --- ## The Observer XT 17 - Reliability Analysis - Frequently Asked Questions About Reliability Analy URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-frequently-asked-questions-about-reliability-analy Chapter: The Observer XT Frequently Asked Questions About Reliability Analysis Why Do I Get Different Kappa Values with Different Comparison Methods? Different comparison methods have different ways to calculate the number of agreements (A) and disagreements (D). A and D are used to calculate Kappa. See: - The Frequency/Sequence Method in Detail - The Duration/Sequence Method in Detail - The Frequency Method in Detail - The Duration Method in Detail - Statistics Why Are the Combined Kappa and Average Kappa Not the Same? - The Combined kappa is the kappa of the sum of all agreements and disagreements in the observation pairs. - Average kappa is the average of all kappas of the observation pairs. These values differ in the same way as the average of all values in a number of samples differs from the mean of the averages of the individual samples. When there is a bias in one observation pair, this has a larger effect on the Average kappa than on the Combined kappa. Why Is Rho High While Kappa Is Low? Cohen's Kappa and Pearson's Rho do not measure the same thing. Rho measures correlation between observations while Kappa measures agreement between observations. A high Rho could result even when agreement measured by Kappa is low. Example: Events are coded by means of predefined numerical modifiers (10, 20, 30...). If one coder consistently codes 10 points higher than the other coder, the correlation between observations is high, while the agreement is low. So Rho is high, but Kappa is low (and will even be negative). Why Does the Frequency Method Give Different Statistics Compared to the Frequency/Sequence Method When I Have Only Point Events? With the frequency method, the total number of each event in both observations is compared. With the frequency/sequence method you investigate event pairs instead of the number of events. Consider the example of two observations with the only difference that at the same time behavior B was scored in observation 1 and behavior A was scored in observation 2. The behaviors A and B are point events in the same start-stop group. Frequency/Sequence Method With the frequency/sequence method, the behaviors A and B are compared with each other, which leads to 1 disagreement. Frequency Method With the frequency method, the total number of occurrences of behavior A is different between the two observations, and the total number of occurrences of behavior B is different as well. This results in two disagreements. It also adds an extra count to the total number, which is the sum of all agreements and disagreements. See: - The Frequency/Sequence Method in Detail - The Frequency Method in Detail Why Is the Total Agreement Duration Longer Than My Observation Duration? The total agreement duration can be longer than the observation duration in the following cases: - Your observations contain overlapping behaviors. You defined a behavior group in which behaviors can overlap, or you have multiple behavior groups. - You used the Duration/Sequence or the Duration comparison method. Consider the example below with a behavior group in which behaviors A, B, and C may overlap. The three behaviors each overlap for 10 seconds in both observations. Both observations have a duration of 15 s. The Duration/Sequence method calculates three agreements of 10 seconds, which is a total of 30 seconds. This is longer than the observation duration. Similarly, the Duration method calculates a total duration of 10 seconds for all three behaviors in both observations, also resulting in a total agreement of 30 seconds. See also: - The Duration/Sequence Method in Detail - The Duration Method in Detail - Effect of Behavior Group - Duration/Sequence Method Why Is the Agreement Much Higher Than I Expect? If you have many gaps between the events and select the option Analyze gaps between events, you may get an unrealistically high agreement. This is because gaps are treated as events, so the gaps in the observation pairs are compared with each other and counted as agreements. Therefore, if there are many gaps, they bias the statistics towards agreements. In this example the Duration/Sequence method was used. To solve this, deselect Analyze gaps between events. The Reliability Analysis would then result in only the two disagreements. Why Does Rho Change for Old Pairs When I Add New Pairs? If you add more observation pairs to the list of pairs and run the analysis again, it could happen that the Rho value for the pre-existing pairs differs slightly from those obtained in the previous analysis. This happens because the confusion matrix, which is used to calculate the statistics, always contains all event types in the observations selected, regardless of which event types were scored in a specific observation. When you add more observations to the list of pairs, this could result in adding event types to the confusion matrix that were not scored in the pre-existing observations. Additional event types means extra rows and columns. Because of the way Rho is computed (see Pearson's Rho), this changes the values of Rho in the Statistics page. If you want to keep the confusion matrix fixed, select the Show Not Scored Elements option (see Choose Table Layout Options). Why Is an Event Paired with Multiple Events in the Comparison List? The comparison list is shown if you use the Frequency/Sequence comparison method. In some cases, an event is associated with two or more events (not necessarily of the same type) in the other observation. For example, 4.24 Walk in observation 1 is associated with 6.00 Walk (agreement) and 0.00 Walk in observation 2 (disagreement). This is an inevitable consequence of the fact that one observation contains more events than the other. In such cases only one agreement is counted (usually the one found in run 1 of the algorithm; see The Frequency/Sequence Method in Detail). All other associations are scored as disagreements, no matter if the event type is the same. Source: The Observer XT 17 Help - Reliability Analysis, Noldus Information Technology --- ## The Observer XT 17 - Reliability Analysis - Reliability Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-reliability-analysis Chapter: The Observer XT Reliability Analysis Main Topics - What is Reliability Analysis? - Reliability Analysis - Four Methods - Reliability Analysis General Procedure - Reliability Analysis Settings - Reliability Analysis Methods in Detail - The Reliability Analysis Result - Effect of the Coding Scheme on Reliability Analysis - Reliability Analysis and Gaps - Frequently Asked Questions about Reliability Analysis What Is Reliability Analysis? Consistency In The Observer XT, Reliability Analysis assesses the extent to which two observations are in agreement with each other. This indicates how free the observations are from random errors and to which extent repeated measurements of the same event produce the same results. Reliability Analysis always works with pairs of observations. If you want to compare three or more observations with each other, you have to specify each combination of observations as the pairs for comparison. Intra-Observer Reliability Check your own consistency. At the beginning of a study, make a video of your study subjects, and code it with The Observer XT. You keep both the video and the observational data file as a reference. Periodically, for example once every six months, you score the same video again and measure the agreement between the new data set and the reference data set. Inter-Observer Reliability Train observers. If a new student joins your research group, he/she has to adopt the coding scheme used in your research. After, for example, one month of practice, test the trainee's data with a reference data file. Reliability analysis helps determining when the trainee is ready for the real work. Reliability Analysis - Four Methods Available Methods Frequency/Sequence This method compares all event types. It compares the frequency of events and timing and overlap between the two observations. Duration/Sequence This method compares events with duration. It compares whether events overlap in two observations. It does not take into account events without duration and instantaneous sampling events. Frequency This method compares all event types. It compares the total number of occurrences of each event in the two observations. The duration or timing of events is not taken into account. Duration This method compares events with duration. It compares the total duration of each event between two observations. The frequency or timing of events is not taken into account. It does not take into account events without duration and instantaneous sampling events. Which Method Should I Choose? - Frequency/Sequence – A detailed indicator of the correspondence between two observations when timing of the events is important. - Duration/Sequence – When you want to know to what extent two observers scored the same events with the same durations. - Frequency – When timing and duration of events are not important in your study. This method is suited for observations with a relatively high rate of transitions between events. - Duration – When you want to compare the duration of events but the timing is not important in your study. Note: Just like in any other analysis, only the events selected in your active data profile will be used. If you run reliability analysis with the default data profile, all events in your observations will be used for comparison. Reliability Analysis General Procedure Aim To determine the reliability of annotations, either between coders or between observations of the same coder. Prerequisites - Your license for The Observer XT includes the Advanced Analysis Module. - You have at least two observations, scored from the same video or live scene. Procedure - Make sure that the data profile specifying the data you want to analyze is active, that is, highlighted in blue in the Project Explorer. - Do one of the following: - Choose Analyze > Reliability Analysis > New. - In the Project Explorer, click the Analyses folder. Then choose Analyze data > Reliability Analysis. - In the Project Explorer, expand the Analyses item. Click Reliability Analysis > New Reliability Analysis. The Reliability Analysis Settings window appears. - In the Pairs tab, add the pairs of observations you want to compare. See Choose the Observations to Compare. - In the Settings tab, select the Comparison method and additional settings. See Choose the Comparison Settings. - Click OK to calculate the reliability statistics. - Optionally, edit the table layout. See Choose Table Layout Options. The results of the selected comparison method are shown in the Reliability Analysis Result. The Statistics and Confusion Matrix are displayed. If you selected the Frequency/Sequence method, the Results also contains the Comparison List. Save Your Analysis Settings To save the settings specified in your analysis, click the Set default button. If this window is gone, click Settings on top of the result window. The settings for the Settings and Layout tab are saved. Apply Settings to a New Analysis If you are about to run reliability analysis and want to recall the settings you have specified earlier, click the Reset to default button. The settings for the Settings and Layout tab are restored. Reliability Analysis Settings What Do You Want to Do? - Choose the Observations to Compare - Choose the Comparison Settings - Choose Table Layout Options --- ## The Observer XT 17 - Reliability Analysis - Reliability Analysis Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-reliability-analysis-settings Chapter: The Observer XT Reliability Analysis Settings Synchronization Options Align first scored events – Select this option if you want to take the first event you scored in each observation as a synchronization point. For example, if a classroom carried out live scoring of a projected video, previously scored by an expert. Align video start time – Select this option if you score from video, but observer 1 started coding at another moment in the video than observer 2. For example, observer 1 started to code the video at t=0:00:00 and coded an event at t=0:01:00 and observer 2 started at t=0:00:50 and coded the same event about 10 seconds after that start. Show Extra Kappa Statistics Select this option to calculate the minimum, maximum and average Kappa of all the combined observation pairs. This enables you to easily see how much Kappa varies between your observation pairs. Note that the average Kappa is not the same as the Kappa of the combined results of two or more pairs of observations. See Why are the Combined Kappa and Average Kappa Not the Same? Combine Multiple Pairs of Observations Select Include all results combined to get an additional row in the Reliability Analysis results sheet that sums up all agreements and disagreements from all pairs of observations. When you select Include all results combined, each observation should occur in only one pair in the list. An overall Kappa or Rho value obtained with many pairs of observations is likely to be affected by bias and prevalence due to the large numbers in some cells of the matrix, not in others. Furthermore, an overall Kappa means losing information on single pairs of observations. In addition, it is always a good idea to export the Kappa values for each pair of observations, and then make a histogram of those values to see how they are distributed. Some observations or observers may be more associated with a lower Kappa than others. There may be observations in which some behaviors which are difficult to observe are prevalent, so they result in low Kappa values. Modifiers If you select Include Modifiers, these are included in the events to compare. If some of the modifiers are numerical and you use the Frequency/Sequence comparison method, you can enter a Margin on numericals as a tolerance value. Modifiers in two events of the same type that differ by less than the margin result in an agreement. See also the example in Confusion Matrix. Choose Table Layout Options Aim To select the number of decimals in the results table and specify how to display elements that are in the coding scheme, but are not scored in any of the observations. Prerequisite You carried out at least one pair of observations. Number of Decimals - Open the Settings tab of the Reliability Analysis Settings window (choose Analyze > Reliability Analysis > New > Settings). - Choose a number from the Number of decimals list. Show Elements Not Scored - Open the Layout tab of the Reliability Analysis Settings window (choose Analyze > Reliability Analysis > New > Layout). - Select Show not scored elements if you want the result to include the event types that were not scored in any observation. If you do so, the matrix of agreements and disagreements will be larger. The cells corresponding to not scored events will contain the missing value symbol. See Show Missing Values As. If the option is not selected (default), only the event types that were scored in at least one observation are included in the result. Show Missing Values As - Open the Settings tab of the Reliability Analysis Settings window (choose Analyze > Reliability Analysis > New > Settings). - Choose the character you want to have displayed for missing values in the confusion matrix. Reliability Analysis Methods in Detail - The Frequency/Sequence Method in Detail - The Duration/Sequence Method in Detail - The Frequency Method in Detail - The Duration Method in Detail --- ## The Observer XT 17 - Reliability Analysis - Reliability Analysis Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-reliability-analysis-statistics Chapter: The Observer XT Reliability Analysis Statistics Significance of Rho To test the significance of ρ, a standard score t is calculated. A one-tailed test is carried out, and the probability is shown next to ρ. The test of significance of r is based on the assumption that the distribution of the residual values (that is, the deviations of the column totals from the regression over the row totals) follows the normal distribution, and that the variability of the residual values is the same for all values of the independent variable. However, Monte Carlo simulations suggest that meeting those assumptions closely is not absolutely crucial if your sample size is not very small and when the departure from normality is not very large. If the number of rows and columns of your confusion matrix is 50 or more then serious biases are unlikely, and if it is over 100 then you do not need to be concerned with the normality assumptions. Prevalence Index Prevalence index is the degree to which a particular event occurs more in a group of subjects than another event. For example, when the number of agreements in Reliability Analysis in one behavior group is higher than in another group, the Prevalence index is high but the Kappa is low. The Prevalence index is therefore useful to explain odd Kappa values. Please note that special columns in the Confusion Matrix, such as No Records, Window Error and Total are not taken into account in the calculation of the Prevalence index. Confidence Interval The 95% confidence interval low and high values are given in the Confusion Matrix. First, the standard error of Kappa is calculated, where Ao is the observed proportion of agreements, Ae is the proportion of agreements expected by chance, and n is the sum of the column totals and the number of columns. The confidence interval is then calculated from this standard error. Extra Kappa Statistics Three extra statistics are available if you selected the option Show Extra Kappa Statistics in the Reliability Analysis Settings. These are Minimum Kappa, Maximum Kappa and Average Kappa, and represent the summarization of Cohen's Kappa for all pairs. Note that the Average Kappa is not the same as the Kappa obtained by summing up the agreements and disagreements from two or more pairs of observations (see Combine Multiple Pairs of Observations), although those two values are often correlated. --- ## The Observer XT 17 - Reliability Analysis - Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-statistics Chapter: The Observer XT Statistics How to Display the Statistics - Choose Analyze > Reliability Analysis > New. - Select the settings and click OK. - Click the Statistics button on the toolbar of the Reliability Analysis Results. Available Statistics - Agreements - Disagreements - Index of concordance - Percentage of agreements - Cohen's Kappa (k) - Significance of Kappa - Kappa max - Pearson's Rho (ρ) - Significance of Rho - Prevalence index - Confidence interval - Extra Kappa statistics Agreements The duration of agreement (Duration, or Duration/Sequence method) or the number of agreements (Frequency, or Frequency/Sequence method) in the observation pair. It is the sum of the values in the diagonal of the confusion matrix of the Reliability Analysis. The way the Agreements are calculated depends on the comparison method. Disagreements The duration of disagreement (Duration, or Duration/Sequence method) or the number of disagreements (Frequency, or Frequency/Sequence method) in the observation pair. It is the total of the values in the off-diagonal cells, including Window Error, Modifier Error and No Records in the Confusion Matrix of the Reliability Analysis. The way the Disagreements are calculated depends on the comparison method. Index of Concordance The proportion of agreements between events in Reliability Analysis, calculated as Agreements / (Agreements + Disagreements). The values range between 0 (no agreements) and 1 (full agreement). Percentage of Agreements The percentage of agreements between events in Reliability Analysis, calculated as (Agreements / (Agreements + Disagreements)) * 100%. The values range between 0 (no agreements) and 100 (full agreement). Cohen's Kappa (k) An overall measure of agreement in Reliability Analysis, from Cohen J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20(1), 37-46. The formula is: κ = (po - pc) / (1 - pc) Where po is the observed proportion of agreements and pc is the proportion of agreements expected by chance. The term aij is the value of the matrix cell at row i and column j. The terms ain and anj are the values of the cells of row i and column j (n ranges from 1 to the last item of the row/column). The term wij is the weight of the value at row i and column j, with two possible values: 0 for agreements (in the diagonal and in the light blue cells) and 1 for disagreements (the remaining cells). When the events do not include numerical modifiers or the margin set for comparison is zero, the proportion of expected agreement is calculated from the row and column marginal totals. The values of k range between -1 (non-random full disagreement) and +1 (non-random full agreement), but for practical purposes the range from 0 to 1.00 is of interest. A k of zero means that there is no agreement beyond chance, and a k of 1.00 means that there is perfect agreement. Interpretations of intermediate values are subjective. Kappa is scored as Invalid if it is based on one comparison, such as one event in each observation, in which case agreement is 100%. Significance of Kappa To test the significance of κ, a standard score z is calculated and a one-tailed test on this score is carried out. The probability is shown next to k. A one-tailed test is considered appropriate when the null hypothesis states a value of zero for kappa, because a negative value of kappa does not normally have a meaningful interpretation. The common statement that kappa is a "chance-corrected measure of agreement" may be misleading. As a test statistic, kappa can verify that agreement exceeds chance levels. But as a measure of the level of agreement, kappa is not "chance-corrected"; indeed, in the absence of some explicit model of rater decision making, one cannot know whether or not a specific agreement was achieved by chance. Kappa Max Kappa max is the maximum Kappa that can be obtained with your data. It is based on the maximum number of agreements possible in your observation pair. For example, if you have event B that is scored by two observers, and Observer 1 scores B three times while Observer 2 scores it nine times, then the maximum number of agreements in your observation pair is 3. Kappa max is calculated as: κmax = (Amax - Ae) / (1 - Ae) Where Amax is the maximum possible proportion of agreements and Ae is the proportion of agreements expected by chance, both derived from the row and column marginal totals of the confusion matrix. Pearson's Rho (ρ) A measure of the strength and direction of the linear relationship between the row totals and the column totals in the confusion matrix of a Reliability Analysis. If there are no disagreements in the confusion matrix, then the total for row 1 is equal to the total for column 1, the total for row 2 is equal to the total for column 2, and so on, meaning there is perfect correlation between the two observations. Rho values range between -1.0 and +1.0, where -1.0 is the perfect negative (inverse) correlation, 0.0 means no correlation at all, and +1.0 is the perfect positive correlation. --- ## The Observer XT 17 - Reliability Analysis - The Duration/Sequence Method in Detail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-the-durationsequence-method-in-detail Chapter: The Observer XT The Duration/Sequence Method in Detail Calculation In the Duration/Sequence method, only events with duration are taken into account. For each observation pair, The Observer XT compares the total duration that the events of the same type overlap in both observations. Gaps between events are only included in the calculation if you select Analyze gaps between events. Suppose you observe Event B and Event C in two observations, i and j. The agreements (A) are calculated as the sum of the duration that Event B overlaps in observations i and j, plus the duration that Event C overlaps in observations i and j. A is the total of all overlapping durations. The disagreements (D) represent the total duration that events of the same type do not overlap. If the observations are compared entirely, the events within the observation do not overlap, and both observations have the same duration, then D equals the observation duration minus A. Agreements and Disagreements The values A and D are used in calculation of the reliability statistics. Effect of Behavior Group - Duration/Sequence Method Reliability Analysis and Gaps Example Four behaviors have the following overlapping duration in two observations. Agreements (A) = 28.8 + 14.1 + 12.3 + 12.5 = 67.7 s You also find these numbers in the diagonal of the Confusion matrix. BehaviorTotal Duration Same Event Overlaps in Both Observations (s) Gazing at patient28.8 Gazing at nurse14.1 Gazing at patients file12.3 Other gazing behavior12.5 The observation duration is 74.0 s. The Disagreements (D) is 74.0 - 67.7 = 6.3 s. You also find these numbers by adding up the numbers outside the diagonal of the Confusion matrix, including the No Records. The sum of these values is 6.4. The small difference with the calculated D is because of a rounding effect. Gaps If you select Analyze gaps between events, a gap is treated as an event, so the time nothing is scored in both observations is treated as agreement. Mind that this may lead to a high agreement between observations if the gaps are large compared to the scored events. The Frequency Method in Detail Calculation For each observation pair, The Observer XT compares the total number of occurrences of each event. Gaps between events are not included in the calculation. Suppose you observe Event B and Event C in two observations i and j. The agreements (A) are calculated as follows: A = min[Bi, Bj] + min[Ci, Cj] Where Bi and Bj are the total number of occurrences of Event B in observation i and observation j. Ci and Cj are the total number of occurrences of Event C in observation i and observation j. A (Agreements) is the sum of the minimum occurrences of events B and C. The disagreements (D) are calculated as follows: D = (max[Bi, Bj] + max[Ci, Cj]) - A The values A and D are used in calculation of the reliability statistics. Example You observe the following total numbers of occurrences of four behaviors in two observations. Agreements (A) = 10 + 7 + 5 + 5 = 27 You also find these numbers in the diagonal of the confusion matrix. BehaviorObservation 1 Total NumberObservation 2 Total Number Gazing at patient1012 Gazing at nurse77 Gazing at patients file55 Other gazing behavior56 Disagreements (D) = (12 + 7 + 5 + 6) - 27 = 3 You also find these numbers when you add up the Total Error cells of the confusion matrix. The Duration Method in Detail Calculation In the Duration method only events with duration are taken into account. For each observation pair, The Observer XT compares the total duration of each event type, which is the sum of the durations of the individual events. Gaps between events are not included in the calculation. Suppose you observe Event B and Event C in two observations. The agreements (A) are calculated as follows: A = min[Bi, Bj] + min[Ci, Cj] Where Bi and Bj are the total durations of Event B in observation i and observation j. Ci and Cj are the total durations of Event C in observation i and observation j. A (Agreements) is the sum of the minimum durations of events B and C. The disagreements (D) are calculated as follows: D = (max[Bi, Bj] + max[Ci, Cj]) - A The values A and D are used in calculation of the percentage and proportion of agreements, Kappa, Rho, and other statistics. Example You observe the following total durations of four behaviors in two observations. Agreements (A) = 29.7 + 14.8 + 13.1 + 14.3 = 71.9 s You also find these numbers in the diagonal of the Confusion matrix. BehaviorObservation 1 Total Duration (s)Observation 2 Total Duration (s) Gazing at patient29.730.4 Gazing at nurse14.816.1 Gazing at patients file13.113.1 Other gazing behavior15.214.3 Disagreements (D) = (30.4 + 16.1 + 13.1 + 15.2) - 71.9 = 2.9 s. You also find these numbers when you add up the Total Error cells of the confusion matrix. The value 3.0 instead of 2.9 is due to a rounding effect. The Reliability Analysis Result How to Display the Results - Choose Analyze > Reliability Analysis > New. - Select the settings and click OK. The Results Windows The Reliability Analysis results consists of the following windows: - Statistics - Confusion Matrix - If you selected the Frequency/Sequence comparison method, the Reliability Analysis Result also contains the Comparison List. To Save a Result To save a result, click the Archive button on the toolbar of the result window, or from the Analyze menu, select Archive Analysis Results. To re-open a saved result, click the Open Archive button on the toolbar or choose Analyze > Reliability Analysis > Open Archive. For more information on saving, opening and exporting results, see Manage Analysis Results in File Management. To Print a Result To print a result, choose File > Print. Note: You cannot edit the content of the Reliability Analysis Results sheet. --- ## The Observer XT 17 - Reliability Analysis - The Frequency/Sequence Method in Detail URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-reliability-analysis-the-frequencysequence-method-in-detail Chapter: The Observer XT The Frequency/Sequence Method in Detail Calculation For each pair of observations selected in the Pairs tab of the Reliability Analysis Settings window, The Observer XT analyzes the two observations in five runs. The Observer XT searches for matches between state events and matches between point events. State events are never matched to point events. Gaps between events are only included in the calculation if you select the option Analyze gaps between events. See also Effect of Behavior Group – Frequency/Sequence Method and Reliability Analysis and Gaps. Example See the example below of two observations. B, C, and E are events with duration. F and G are events without duration. A tolerance window of 1 s was used and gaps between events were not analyzed. Run 1 – Find Overlapping Events The program searches for events of the same type in the two observations that overlap in time at least partially. The onset and offset times of the events need not be the same. The following agreements are scored: - 1.6 Event E (Obs 1) – 0.8 Event E (Obs 2) - 4.5 Event C (Obs 1) – 4.1 Event C (Obs 2) - 12.3 Event E (Obs 1) – 10.7 Event E (Obs 2) Run 2 – Find Overlapping Events Within the Tolerance Window The program searches for events of the same type among all those that have not been considered in the previous run, and scores agreements between those which do not overlap, but whose onset time differs less than the tolerance window (dotted lines). The onset times of Event B differ by less than the tolerance window. The following agreement is scored: - 0.9 Event B (Obs 1) – 0.2 Event B (Obs 2) Run 3 – Find Disagreements: First Event Within Tolerance Window The program considers the events left out in the previous runs, and searches for any event in the other observation within the tolerance window (dotted lines) that overlaps the event in the first observation. If multiple events are available in the other observation, then the first event is considered. Pairing in run 3 always results in disagreements, because if the events are of the same type they would have been considered as an agreement in run 1 or 2. The following disagreement is scored: - 11.0 Event G (Obs 1) – 11.2 Event F (Obs 2) Run 4 – Find Disagreements: Any Event Within Tolerance Window The program considers the events left out in the previous runs; however, it searches for any event in the other observation within the tolerance window (dotted lines), even if that has been scored as agreement or disagreement in a previous run. If multiple events are available in the other observation, then the last event is considered. Pairing results in disagreements. The following disagreements are scored: - 11.0 Event B (Obs 1) – 10.7 Event E (Obs 2) - 11.0 Event G (Obs 1) – 11.9 Event F (Obs 2) Please note that 10.7 Event E (Obs 2) was also paired as an agreement in run 1. This is one of the frequent cases in which an event produces one agreement and one or more disagreements. 11.0 Event G (Obs 1) was also paired as a disagreement in run 3. Run 5 – Find Disagreements: Events Outside the Tolerance Window The program considers the events that have not been considered in the previous runs, and searches for the most nearby event in the other observation that has yet to be scored as agreement or disagreement. If two events are equally far in time from the focal event, the first of the two is considered. Pairing results in disagreements. If the paired events are of the same type, which is the case in the example below, they are scored as Window Error. The following disagreement is scored: - 8.0 Event F (Obs 1) – 11.7 Event F (Obs 2) Please note that 11.2 Event F (Obs 2) was also paired as a disagreement in run 3. References For more information, please see the following paper: Jansen, R. G., Wiertz, L. F., Meyer, E. S., & Noldus, L. P. (2003). Reliability analysis of observational data: Problems, solutions, and software implementation. Behavior Research Methods, Instruments, & Computers, 35(3), 391–399. For general information about reliability analysis see Haccou, P., & Meelis, E. (1992). Statistical analysis of behavioural data: An approach based on time-structured models. Oxford University Press. Agreements and Disagreements The number of Agreements (A) and Disagreements (D) are used in calculation of the reliability statistics. Each count represents an event pair. See Statistics. You find these values by adding up the cells in the Confusion Matrix. The number of Agreements is the sum of the cells in the diagonal. The number of Disagreements is the sum of off-diagonal cells, including Window Error, Modifier Error, and No Records. Stop Times The stop times are not compared directly; however, they are compared indirectly. When you score the stop of a behavior without starting a new one, there are gaps between events. If you selected Analyze gaps between events, The Observer XT treats such gaps as and finds matches between them just like events. For more information, see and Reliability Analysis and Gaps. Analyze Modifiers - If behavioral modifiers are not defined in your coding scheme, the Behavior Modifiers options in the settings window are not available. - If you select the Include Modifiers option, comparison of events is more discriminating, as two events with the same subject or behavior but different modifiers will result in a disagreement. De-selecting this option makes the comparison of events less selective. Choose Specific Event Logs for Comparison In the Reliability Analysis Settings window, you choose observations for comparison. If your observations include two or more event logs, this window does not distinguish between them. To select a specific event log, open your data profile (or create a new one) and create a Result container for each event log. Next, filter event logs in such a way that the event logs you want to compare end up in different Results boxes. Then, in the Reliability Analysis Settings window, choose the combination Observation * Result container to specify an event log for comparison. Comments If you have scored comments without associated behaviors, these rows in the event log result in in the analysis, which are treated as events without duration in the reliability analysis. This affects the outcome of the reliability analysis. To avoid this, create a data profile (see Select Data for Analysis) and use a filter box in which you select all behaviors. This filter box removes the lines in your event log that contain only comments. Then carry out the reliability analysis. --- ## The Observer XT 17 - SBLK Activation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-sblk-activation Chapter: The Observer XT The Observer XT 17 – Activating Your Software Based License Software based licenses can be activated as either Fixed or Floating. For more information on the differences between Fixed and Floating, see the License Management section. The Observer XT licenses can have a variety of modules (Video Analysis, Advanced Analysis, Coder Only, etc.). Some licenses in the lab might only contain the Advanced Analysis module while other licenses could have all the modules. When the modules vary from license to license, this results in a new activation key for each module variation. For example, to save costs you might have one full license and one Coder Only license. In this scenario, you will be sent two Activation Keys. When you have multiple licenses with the same modules, these can all reside under the same Activation Key, which has multiple Seats. You can fix or float any software based license, regardless of how many Activation Keys or Seats you have. Activation Activating as Fixed – PC Requires Internet - Download and install The Observer XT 17. - Launch The Observer XT 17. - Select Activate Software License Key. - Select Fixed – On This Computer Only. - Choose the Activate Online option. - Enter the Activation Key. - You are now ready to use The Observer XT 17. The PC can be online or offline during use of The Observer XT 17. Activating as Fixed – PC Does Not Require Internet - Download and install The Observer XT 17. - Launch The Observer XT 17. - Select Activate Software License Key. - Select Fixed – On This Computer Only. - Choose the Activate Offline option and enter the Activation Key. - Scan the QR code using the camera of your smartphone to get a Computer Key. - Under Activate Offline, enter the Computer Key. - You are now ready to use The Observer XT 17. The PC can be online or offline during use of The Observer XT 17. Activating as Floating – PC Requires Internet - Download and install The Observer XT 17. - Launch The Observer XT 17. - Select Activate Software License Key. - Select Floating – On Multiple Computers. - Enter the Activation Key. - You are now ready to use The Observer XT 17. The PC must be online during use of The Observer XT 17. License Management Permissions - When activated as a Fixed license via the internet (online), it will check the license server for permission, after which it will lock the license to that specific PC for 90 days. After 90 days, the license checks the server for permission again. - When activated as a Fixed license without an internet connection (offline), it will check the license server for permission, after which it will lock the license to that specific PC for 365 days. After 365 days, the license will require reactivation to confirm permission for another year of use. - When activated as a Floating license, permission is shared. Internet access is required each time a PC wants to utilize the full version of the software (i.e., acquire data), as it uses the internet to check for license permission. Access to the Key/Seat is on a first come, first served basis. You can switch between Fixed and Floating activations by deactivating via Help > Deactivate License. When a license is deactivated, it is immediately available to fix or float on another PC. Fixed License A Fixed license is used on a single computer. An internet connection is required during activation but not during use of The Observer XT 17. - Once a license is activated as Fixed, it permanently occupies a Seat. - If you receive an error indicating the license is already fixed on another PC, deactivate it on that PC first before activating it on this one. Floating License A Floating license (with one or more Seats) can be accessed on multiple computers. A permanent internet connection is required. - You can install The Observer XT 17 on as many PCs as you would like, but only the number of Seats purchased can be used simultaneously at any given time. - Users must close The Observer XT 17 after use. This frees up a Seat so another user can use the software on another computer. - You do not need to deactivate after use — simply closing The Observer XT 17 is sufficient to free up a Seat. Tips for Managing Floating Licenses - Use a shared online calendar, spreadsheet, or schedule to keep track of who is using The Observer XT 17 and when. This helps identify who last used it, should you need to ask them to close the software to free up a Seat. - Keep a list of all PC names (company and personal) that have The Observer XT 17 installed. - For each Activation Key, note whether it is set to Fixed or Floating. - If you have trouble accessing the license due to a strict local network, ask your IT department to add an exception for: https://qlmlicenses.noldus.com:9999 Support If you run into any issues, please submit a support ticket on the MyNoldus client portal. Source: DanioVision Temperature Control Unit in a Nutshell, Noldus Information Technology --- ## The Observer XT 17 - Select Data for Analysis - Data Selection: Filters and Intervals URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-select-data-for-analysis-data-selection-filters-and-intervals Chapter: The Observer XT Data Selection: Filters and Intervals Instead, select both behavior groups in one filter box. If Your Sequence Contains Interval Boxes Only The order in which you place the boxes does not matter. If Your Sequence Contains Interval and Filter Boxes Together Example: One Filter (Subjects) box to filter the subject Doctor, one Filter (Behaviors) box to filter the behavior Instruction, and one Interval box to select the time that the behavior Gazing at Patient occurred. The selection may not work if the Filter boxes are placed before the Interval box. This is because a Filter box may filter out the subjects and behaviors specified in the Interval box. As a general rule, insert the Filter boxes after the Interval boxes. Create Groups of Data Aim To split your data into groups for analysis. Example: To analyze the behavior of male subjects and compare that with the behavior of the females. Solution: Create an independent variable Gender. In the Data Selection, create two sequences. Insert an extra Results box to do so. Select female subjects in one sequence and male subjects in the other. Prerequisite You carried out your observations. Procedure - Create an independent variable and enter a value for all subjects (see Create User-Defined Variables). In this example, create an independent variable Gender with the values female and male. - In the data selection sequence, click the Settings button on the existing Results box and name it Males. - Click Results to create an extra Results box. - Name the extra Results box Females. - Connect the Results box with an arrow to the Start box. - Click By Gender under Filter Events and make your selection. Insert a selection box in both sequences. - Analyze the data with the data profile you just created active. The data for males and females are now calculated separately. Note: If the scope of the independent variable Gender is Observation instead of Subject (see Variable Scope), By Gender is present under Filter Observations instead of under Filter Events. Create Groups of Data Based on a Behavior Following the procedure above, you can also divide the data into time intervals during which a behavior takes place. Example: To analyze the behavior of a driver when it was either watching the left mirror or the right mirror. - Add an extra Results box and click the Settings button on each box to give them a logical name. - Click By Behaviors under Select Intervals and define your selection. Then insert the box in the correct branch of the data selection sequence. - Repeat the procedure for each branch. Manage Data Profiles View and Open Data Profiles All data profiles are listed in the Project Explorer in the Data Profiles folder in the Analyses folder. Click a data profile to activate it. It is then highlighted in blue and used in the Visualization and all analyses. Edit a Data Profile Delete a Selection Box To delete selection boxes, select them and press Delete. You cannot delete the Start box. You can delete a Results box if there are more than one. If you delete a box within a sequence, the arrows connecting the adjacent boxes are lost. You must then re-connect the adjacent boxes (see step 4 in Data Selection: General Procedure). Delete a Connecting Arrow To delete an arrow, click it and press Delete. Edit Selection Criteria in a Selection Box To edit selection criteria in a box, click the Settings button in the bottom-right corner of the box and select the new criteria. Create a New Results Box Create multiple Results boxes if you want to split your data for analysis, for example to analyze male and female participants separately. See Create Groups of Data for an example. Click the box next to Results and change the name of the Results box, for example to Males or Females. This name is shown in the analysis results. Arrange Data Selection Boxes Choose View Settings > Snap to Grid to automatically align the boxes to a grid. Choose Show Grid to display the grid in the Data Selection window. Reset a Data Profile If you reset a data profile, all your selection criteria in that profile are deleted. As a result, the data profile contains all observations of your project and all data within them. To do so, choose Analyze > Select Data > Reset Current Data Profile. Important: You cannot undo a data profile reset. Rename a Data Profile To rename a data profile, right-click the name of the data profile in the Project Explorer and select Rename. Then enter the new name. Create a Copy of a Data Profile To copy an existing data profile, right-click a data profile and select Duplicate, or click the Duplicate button on the toolbar. Delete a Data Profile To delete a data profile, right-click it in the Project Explorer under Data Profiles and select Delete. Deleting a data profile does not delete your data; it removes the data selection settings. Important: You cannot restore a deleted data profile. Zoom In and Out Use the Zoom In, Zoom Out, Zoom to Fit, and Reset Zoom icons on the toolbar to customize your Data Selection window. You can also use Ctrl+scroll wheel to zoom in and out. Create a Screenshot of the Data Selection Click the camera icon at the right-hand side of the toolbar to save the data selection to an image file (*.png, *.emf, *.jpg, *.bmp, *.gif). Source: The Observer XT 17 Help - Select Data for Analysis, Noldus Information Technology --- ## The Observer XT 17 - Select Data for Analysis - Filtering and Selecting Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-select-data-for-analysis-filtering-and-selecting-data Chapter: The Observer XT Filtering and Selecting Data Filter by Independent Variable The scope of the variable determines what is filtered: - Example 1 – The scope of the variable Temperature is Observation. Filtering by Temperature results in selecting observations with the chosen Temperature values. - Example 2 – The scope of the variable Subject Experience is Subject. Filtering by Subject Experience results in selecting events for subjects with the chosen Subject Experience values. Procedure - Click By [Independent Variable name]. - Choose one of the following: - To filter specific variable values, select Select by Value and select the values. - To filter a range of variable values, select Select by Definition and specify the range by entering the To and From values. - Insert the box in the sequence between the Start box and the Results box. Important: To filter data by User-defined Variable values, make sure that you enter a value for that variable for each Subject/Event Log/Observation in the Independent Variable List. If you do not do this, your selection may be wrong. You can also use the Independent Variables to split your data. For example, to analyze Male and Female subjects separately. See Create Groups of Data to do so. Filter Subjects Use this filter to analyze events scored for some subjects and not others. Prerequisites - You defined Subjects in your Coding Scheme. - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Subjects. - Select the subjects you want to analyze. - Insert the box in the sequence between the Start box and the Results box. Filter Behaviors Use this filter to analyze some behaviors and not others. Prerequisites - You carried out your observations. - You defined Behaviors in your Coding Scheme. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Behaviors. - Select the behaviors you want to analyze. By default, all behaviors are selected. - Insert the box in the sequence between the Start box and the Results box. Note: If you filter behaviors, you only analyze those events. All others are excluded. This is different from analyzing what events take place when another event occurs. If that is what you want, use Select Intervals by Behaviors instead. Filter Modifiers Use this filter to choose some modifiers and not others. Prerequisites - You defined Modifiers in your Coding Scheme. - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Modifiers. - Select a Modifier group from the Modifier list. - Select the Modifiers. For numerical modifiers, you can also specify a range of values. - Insert the box in the sequence between the Start box and the Results box. Note: If the selected modifiers are linked to more than one behavior, all these behaviors with the selected modifiers will be analyzed. If you want to analyze only a selection of these behaviors, position a By Behavior box with the selected behaviors in the data selection sequence as well. See Advanced Data Selections for how to combine selection boxes. Filter by Duration Use this filter to select events that are longer or shorter than a given duration. For example, if you observe aphids, you can select only the feeding events that are longer than 10 seconds to distinguish events during which the aphid tests the leaf content from events during which the aphid is actually eating. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Insert a By Behaviors (Filter Behaviors) or By Modifiers (Filter Modifiers) box with the event of interest in the sequence between the Start box and the Results box. - Choose By Duration. - Specify a duration and choose Higher than, Higher or equal to, Lower than, or Lower or equal to. In the example of the aphids, select Higher than 10 s. - Insert the box after the other filter boxes in the sequence between the Start box and the Results box. Note: If you do not combine the By Duration filter with a Filter by Behaviors or Modifiers box, you apply the minimum or maximum duration to all events. See Advanced Data Selections for more information on combining selection boxes. --- ## The Observer XT 17 - Select Data for Analysis - Select Data for Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-select-data-for-analysis-select-data-for-analysis Chapter: The Observer XT Select Data for Analysis Why Select Data? In many cases you may want to visualize or analyze your entire dataset and obtain complete descriptive statistics for all your events in all your observations. If this is the case, do not select data, but continue with Visualize Data, or Calculate Statistics. If you want to analyze only a subset of your data, or analyze a number of behaviors together, carry out data selection first. To open the Data Selection window, choose Analyze > Select Data > New Data Profile. There are four ways to analyze a selection of data: - Analyze several events as if they are one - Analyze some observations, subjects or events, not others - Analyze events that occurred in specific time intervals - Analyze data in regular time intervals What Do You Want to Do? Analyze several events as if they are one - Example 1 – Visualize behaviors of the group Play type as one behavior. - Example 2 – Analyze the behaviors Left hand moving and Right hand moving together as Any hand moving. Merge the data, then visualize and run the analysis. See Merge Data. Analyze some observations, subjects or events, not others - Example 1 – Calculate the average duration of speech of the subject Child, not of the subject Mother. - Example 2 – Visualize data in observations of female subjects, not of males. - Example 3 – Calculate the rate of occurrence of events of the group User Error, not of others. Filter the data, then run the analysis. See Filter Data. Analyze events that occurred in specific time intervals - Example 1 – Calculate the number of times the child smiled when the mother was present. - Example 2 – Visualize the data from the moment the mother entered the room until ten minutes later. - Example 3 – Analyze events when the subject's heart rate was higher than 100 beats per minute. This is possible when your license includes the External Data Module. Select intervals, then run the analysis. See Select Intervals. Analyze data in regular time intervals - Example 1 – Split your observations in 10-minute intervals and calculate statistics for each of them. - Example 2 – Split your observations in three equal intervals and calculate statistics for each of them. Define Time bins, then run the analysis. See Select Regular Intervals. The Data Selection Screen Explained To open the data selection window choose Analyze > Select Data > New Data Profile and name the data profile. Alternatively, right-click the Data Profiles folder under Analyses in the Project Explorer and choose New. The window that appears contains the Components pane on the left and a window on the right with the data selection sequence. The Data Selection sequence in the window on the right contains two boxes connected by an arrow. - The Start box (left) contains all the data in all the observations currently stored in your project. - The Results box (right) contains the data used for analysis. The Start box is connected with a direct arrow to the Results box. This means that all data are used for analysis. Add boxes in the sequence to define which data to analyze. See Data Selection: General Procedure. The Results Box Explained The Results box shows the result of the data selection. When your project contains two observations and you defined three subjects and seven behaviors in the Coding Scheme, both the Start box and the Results box show three subjects and seven behaviors. The Results box also shows two intervals, one for every observation. Filtering When you filter by subjects, behaviors, modifiers, or duration (see Filter Data), the numbers in the Results box match the numbers you have selected in the filter box. Filtering has no effect on the analyzed observation time and no intervals are created. So the number of intervals in the Results box remains the same as in the Start box and represents the number of observations. When your data selection contains no data, this is shown in red on the Results box. Intervals When you select intervals by subjects, behaviors, modifiers, or duration (see Select Intervals), you create time intervals based on the selected data. No subjects, behaviors, or modifiers are filtered out, so these numbers remain unchanged in the Results box. The number of intervals changes; it shows the total number of intervals over all observations. If the data selection contains no data because the selected subject, behavior, or modifier has not been scored, the Results box shows 0 intervals in red. Data Selection: General Procedure Make space between the Start and Results box by moving the Results box to the right. To do so, click the header of the Results box so that the pointer becomes a four-arrow cross. Drag the box to the right. Then do the following: - Click one of the buttons in the Components pane to select the criteria to add to the data selection sequence. For example, to analyze only a selection of observations, click the button next to By Observation name. - Choose the values that specify your selection. - Click OK. A new box appears in the Data Selection window. Drag the box over the arrow between the Start and Results box. When the arrow turns white, release the mouse button. - If necessary, draw extra arrows to connect selection boxes. To do so, point to the center of the first box, press and hold the left mouse button and drag toward the center of the other box. Release the mouse button when the cursor has reached the center of the other box. - Click the Visualize button on the toolbar to check whether your data selection works as expected. The selected data are displayed in the white fields of the Time-Event Plot. Tip: Click the Settings button on the Results box to change its name. This name is shown in the visualization and analysis results, so you always know which data selection the results come from. Note: You cannot create connections from the Results box to any other box, or from a box to the Start box. Merge Data To treat two or more coding scheme elements (behaviors or modifiers) as one. For example, treat the behaviors Grab antennae, Grab mandibles, Grab head as one behavior Grabbing and calculate the total frequency or duration. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click the Merging button on the Start box. - Click the tab for the elements you want to merge. - To create a merged group: - Behaviors – Click the Add button at the bottom. The merged group appears at the bottom of the list. - Modifiers – Select the Modifier group name in which you want to merge Modifiers (see Notes about Merging). Then click Add. The merged group appears in the Modifier group. - Name the group and press Enter. - Drag and drop elements into the group. How Merged Data Are Analyzed Merged Behaviors Behaviors A and B both have a duration of 5 seconds and they overlap for 1 second. After merging, the frequency of the merged behavior is 1 and its duration is 9 seconds. Merged Modifiers The top part in the picture below shows three occurrences of Behavior Walk, each with a duration of 3 seconds, scored with associated modifiers Slow, Normal and Fast. Merging the modifiers into one modifier Speed results in one occurrence of Behavior Walk with a duration of 9 seconds (bottom picture). Notes about Merging Behaviors - Modifiers are not visualized and analyzed when you merge Behaviors. Modifiers - You can only merge Modifiers from the same Modifier group. - If you create a Merged group of numerical modifiers, this group is considered as nominal. This means you cannot calculate average modifier values, but can calculate statistics like frequency and duration. To Remove a Merged Group To remove a merged group, select the group name and click the Remove button at the bottom. To remove all Merged groups in one of the tabs at once, click the Reset to default button. What Happens with Merged Groups If I Change the Coding Scheme? - If you add a new element to the coding scheme – If you want to include this element in the merged group, add it manually. - If you delete an element in the coding scheme – The element is deleted from the merged group as well. Filter Data To choose a subset of data and exclude others from visualization or analysis. You can filter observations and filter events. Observations and subjects can be filtered directly, for example by choosing only the first five observations. You can also choose observations or subjects indirectly, by the value of independent variables. For example, to analyze only those observations in which the subject's age was below 10. See Filter by Independent Variable Values. Filter Observations - By observation name – to analyze some observations, not others. See Filter Observations. - By Independent variable with scope observation – to analyze observations with specific independent variable values. See Filter by Independent Variable Values. Filter Events - By Independent variable with scope subject – to analyze events of subjects with a specific independent variable value. See Filter by Independent Variable Values. - By Subjects – to analyze events for some subjects, not others. See Filter Subjects. - By Behaviors – to analyze some behaviors, not others. See Filter Behaviors. - By Modifiers – to analyze some modifiers, not others. See Filter Modifiers. - By Duration – to analyze events with a minimum or maximum duration. See Filter by Duration. Filter Observations To choose some observations for analysis and exclude others. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Observation name. - Select the observations and event logs to analyze. If your observations contain multiple event logs and you want to analyze only a few, unfold the observation item and select the event logs. - Insert the box in the sequence between the Start box and the Results box. Filter by Independent Variable Values To choose observations, event logs or subjects according to the value of an independent variable. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Independent Variables and Scope Each independent variable has a variable scope. System variables, like Start time, always have scope Observation and therefore filters for these variables appear under Filter Observations. User-defined variables can have scope Observation, Event Log, or Subject. Depending on the scope you can filter observations, event logs or subjects according to the variable values. For example, the user-defined independent variable Patients file has the scope Observation, while Gender has the scope Subject. Therefore, By Patients file appears under Filter Observations and By Gender under Filter Events. --- ## The Observer XT 17 - Select Data for Analysis - Select Intervals URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-select-data-for-analysis-select-intervals Chapter: The Observer XT Select Intervals Use interval selection to analyze events that occur in time periods defined by an event or a combination of events (interval conditions). - Example 1 – You want to analyze the events that occurred when the user was performing Task 3. You select intervals based on behavior Task 3. This way analysis is done on all events scored when the state Task 3 was active. - Example 2 – You want to analyze co-occurrence of two behaviors, for example how often a child was playing at a table. Select intervals based on the behavior Child Play and analyze the behavior At Table. You can select intervals in the following ways: - Select Intervals by Manual Selection – To define the start and stop of the intervals manually. - Select Intervals by Subjects – To analyze the time intervals during which behaviors by certain subjects took place. - Select Intervals by Behaviors – To analyze time intervals during which certain behaviors took place. - Select Intervals by Modifiers – To analyze time intervals during which certain modifiers took place. - Select Intervals by Duration – To analyze time intervals with a minimum or maximum duration. - Select Intervals by External Data – If your license includes the External Data Module. To analyze time intervals during which your external data had a certain value. Select Intervals by Manual Selection Use this option to set the start and end of the intervals manually. Both the start and end of the interval can be determined by: - Observation time – For example, one minute after the start of the observation. - Observational data – For example, the start of Task 1. - External data – If your license includes the External Data Module. For example, when the heart rate becomes higher than 100 bpm. You can also combine time, events, or external data to define the interval. For example: From 1 minute after the event Start Test to the event User Error. See also How Manual Intervals Are Generated. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Manual Selection. - In the window that opens, specify the criteria for the start and the stop of the interval: - Observation time – Enter the time in the appropriate field and select after start of or before end of from the list. - Observational data – Select the event from the lists. Depending on your Coding Scheme, subjects or modifiers may not be available. Optionally enter a time in the Start interval at / Stop interval at field and select after end of, after start of, before end of, or before start of from the list. - External data – This option is available if your license includes the External Data Module. Specify the criteria for the external data. The options are Becomes higher than/or equal to and Becomes lower than/or equal to. Optionally, set a time in the Start/Stop interval at field and select after or before from the list. See also The Difference Between Select Intervals by External Data and Select Intervals by Manual Selection with External Data. - Insert the Interval box in the selection sequence between the Start box and the Results box. Select Intervals by Behaviors Use this option to analyze all time segments when a state event occurred. Prerequisites - You carried out your observations. - You defined Behaviors in your Coding Scheme. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Behaviors. - Select the behaviors you want to use as interval criteria. - If your Coding Scheme contains Subjects, specify which ones should perform the behavior. You have the following choices: - – To specify the time intervals as long as the behaviors occurred, independent of which subject performed those behaviors. Example: When either the male or the female bird was in the nest. - – To specify the time intervals as long as the behaviors occurred for all subjects simultaneously. Example: When both the male and female bird were simultaneously in the nest. - – To specify the time intervals during which a behavior was scored but no subject was recorded. - – To specify the time intervals as long as the behaviors occurred for that subject. Example: When the specified bird, either the male or the female, was in the nest. - Insert the Interval box in the sequence between the Start box and the Results box. Notes: - To select intervals based on the behaviors performed by a subset of subjects, not just one or all, create multiple selection conditions. See Advanced Data Selections. - Selecting a certain combination of subject and behavior in the Select Intervals (Behaviors) window is equal to selecting the same combination when you Select Intervals by Subjects. Select Intervals by Subjects Use this option to analyze all time segments when one or more subjects were scored. Prerequisites - You defined Subjects in your Coding Scheme. - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Subjects. - Select the subjects you want to use as interval criteria. - Specify what behaviors the selected subjects performed: - – To specify the time intervals when the selected subjects were scored, independent of their behavior. - – To specify the time intervals when the selected subjects were scored but no behavior was recorded. Example: All intervals in which Tijmen and Martijn were scored independent of their behavior. - – To specify the time intervals when the selected subjects performed the selected behavior. Example: All intervals in which Tijmen and Martijn were interacting with a colleague. - Insert the Interval box in the sequence between the Start box and the Results box. Notes: - To select intervals by two or more subjects when performing a subset of behaviors, not just one, you need to create multiple interval conditions. See Advanced Data Selections. - Selecting a certain combination of subject and behavior in the Select Intervals (Subjects) window is equal to selecting the same combination in the Select Intervals (Behaviors) window. See Select Intervals by Behaviors. Select Intervals by Modifiers Use this option to analyze all time intervals when a modifier has a certain value. Prerequisites - You defined Modifiers in your Coding Scheme. - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click By Modifiers. - Select a Modifier group from the Modifier list. - Select the Modifiers. For numerical modifiers, you can also specify a range of values. - Insert the box in the sequence between the Start box and the Results box. Note: If the selected modifiers are linked to more than one behavior, all intervals in which these behaviors with the selected modifiers were scored will be analyzed. If you want to analyze only time intervals in which a selection of these behaviors took place, position a By Behavior box with the selected behaviors in the data selection sequence as well. See Advanced Data Selections for how to combine selection boxes. --- ## The Observer XT 17 - Select Data for Analysis - Select Intervals by Duration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-select-data-for-analysis-select-intervals-by-duration Chapter: The Observer XT Select Intervals by Duration Aim To select intervals that are longer or shorter than a given duration. For example, if you observe a child, to select its behavior when the mother was present for longer than 1 minute. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Insert a By Behaviors (see Select Intervals by Behaviors) or By Modifiers (see Select Intervals By Modifiers) interval box with the event of interest in the sequence between the Start box and the Results box. - Choose Select Intervals By Duration. - Specify a duration and choose Higher than, Higher or equal to, Lower than, or Lower or equal to. In the example of the child above, select Higher than 60 s. - Insert the box after the other interval boxes in the sequence between the Start box and the Results box. Important: Always place the By Duration interval box after the interval boxes with the other selection criteria. Note: If you do not combine the By Duration interval box with a By Behavior or Modifier box, you select entire observations that have that minimum or maximum duration. See Advanced Data Selections for more information on combining selection boxes. Select Intervals by External Data Aim To analyze data when external data values are above or below a specific value. Prerequisites - Your license includes the External Data Module. - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click the button next to the appropriate By . - Specify the criteria for the external data. You can set a higher than (or equal to), or lower than (or equal to) limit. It is also possible to define a range. - To avoid creating intervals for external data spikes that were the result of noise, specify a Minimum interval length. - Insert the Interval box in the sequence between the Start box and the Results box. Result The upper and lower limits of the interval are fixed and based on the external data values. In the picture below, the intervals are based on a heart rate between 80 and 100 bpm. The selected intervals are shown in the white areas. See also: The difference between Select Intervals by External Data and Select Intervals by Manual Selection with external data. Notes on Intervals The following notes apply to all intervals, including time bins. Intervals and Suspending a Live Observation If you carried out a live observation and suspended it (see Suspend an Observation), defining intervals may lead to incorrect selections. This is because suspend/resume creates extra stop and start events for that behavior. For example, if you suspended the observation when Play was active and then select an interval by Play, the resulting interval will be from the start of Play to the suspend time, not the time that you actually score the stop of Play. If this behavior is still active after you resume scoring, you will obtain a second interval from the moment the observation is resumed until the stop of Play. Intervals and Behaviors Without Duration It is not possible to select intervals by behaviors without duration (Point events), but you can define intervals starting or ending a defined time before or after them. See Select Intervals by Manual Selection. Intervals and Multiple Event Logs If an observation includes two or more event logs, an interval defined in one event log is also applied to other event logs within that observation. Example: An interval is defined from the start of the observation to the event End of Task. FaceReader states were imported as a second event log. The interval is also applied to the FaceReader states. If the start and stop criteria are present in more than one event log within one observation, intervals may give unexpected results. We recommend you do not use intervals in this case. Interval Borders See What Happens at the Interval Borders? How Manual Intervals Are Generated Manual Intervals in Detail Consider the following example for selection of manual intervals. From 3 seconds after a blue tit female enters the nest until 2 seconds after the bird starts removing faeces. Set the criteria for the intervals in the following way: Manual intervals are generated as follows: - The first point that matches the selection criteria for the interval start is determined. - The offset (before or after) specified in the Start interval at field is applied. This sets the start point of the interval. - The first point after the point that matches the selection criteria for the interval stop is determined. - The offset (before or after) specified in the Stop interval before field is applied. This sets the end point of the first interval. - Steps 1 to 4 are repeated until the end of the observation. The start of the next interval is always after the stop of the previous one. Note that the four instances of In after the one at approximately 40 s are not considered for the second interval. An interval is determined by: - The first instance of the start criteria following the previous interval. - The first instance of the stop criteria following the start criteria. What Happens if a Start or Stop Criterion Is Missing? If either a start criterion is missing in the observation, or no stop criterion follows the start criterion, no interval is selected. --- ## The Observer XT 17 - Select Data for Analysis - The Difference Between Select Intervals by Externa URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-select-data-for-analysis-the-difference-between-select-intervals-by-externa Chapter: The Observer XT The Difference Between Select Intervals by External Data and Select Intervals by Manual Selection with External Data With selecting intervals by external data, the upper and lower limits of the interval are fixed and based on the external data only. In the picture below, the intervals are based on a heart rate between 80 and 100 bpm. The selected intervals are shown in the white areas. With selecting intervals by manual selection, you can include time in the interval start and end criteria, for example 1 minute after the heart rate becomes higher than 100 bpm. Furthermore, there need not be an upper and lower limit; you can use higher than or lower than for both the start and the end of the interval. In the figure below, the interval starts when the heart rate becomes higher than 100 bpm and stops when the heart rate becomes higher than 80 bpm. Note: Depending on the sample rate of the external data, in the event plot it can sometimes seem as if the interval does not include external data values that should have been included. This is because in the event plot samples are connected by a line as if the external data is continuous, while in fact it consists of discrete samples. See also Visualize External Data. Select Regular Intervals Aim To divide your data sets in time intervals of equal length. The results of your analyses will be shown for each interval in separate tables or cells. You can specify intervals of a specific length (for example, to split your observations in 10-minute units) or a fixed number of intervals. In the latter case, the duration of each interval depends on the observation length and the number of intervals. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Procedure - Click the Settings button on the Results box. - Choose either: - Use time bins of duration – To specify a fixed interval length. The number of time bins depends on the observation length. If the duration of the observation or event log is not an exact multiple of the interval length, the last time bin will be incomplete. Select the Ignore Last Time Bin if Incomplete option if you do not want to analyze this last interval. - Use number of time bins – To specify a fixed number of intervals to analyze. The duration of the time bins depends on the observation length. - If your data profile contains two or more result containers (see examples in Create Groups of Data), optionally click Apply to All to set the time bins in all Results boxes. Notes - Time bins and the Results box: The Results box shows whether you selected time bins and their duration. - If an event falls in two or more time bins: If a behavior occurs across two time bins (marked by dotted lines), it is counted in both time bins. For example, its duration may be four minutes in the first time bin and two minutes in the second time bin. - Maximum number of time bins: In theory you can create as many time bins as you want, but time bins increase calculation time. Make sure you do not have very small, and therefore very many, time bins. - Time bins and multiple event logs: Time bins start at the observation start time, which is the start of the earliest event log. For event logs that start later, the time bins at the beginning of the observation contain no data. - The borders of time bins: See What Happens at the Interval Borders? - Combine intervals with time bins: You can use intervals and time bins simultaneously. The time bins are then generated per interval. The data outside the intervals are not analyzed. For example, if you have two intervals from 0–9 sec and from 20–32 sec, and you define Number of Time Bins = 3, you get three 3-second time bins for the first interval (0–9 sec) and three 4-second time bins for the second interval (20–32 sec). - The difference between time bins and other intervals: With time bins, you analyze data in regular time segments. Intervals are based on values of events or external data and therefore vary in time. The only exception is by manual selection based on observation time; however, this creates one interval per observation, whereas with time bins you create a number of intervals of the same length within one observation. Advanced Data Selections What Do You Want to Do? - Combine Selection Criteria - Create Groups of Data Combine Selection Criteria Aim To select data based on a combination of selection criteria. Prerequisites - You carried out your observations. - The Data Selection window is open (Choose Analyze > Select Data > New/Open Data Profile). Basic Rules To create advanced data selections, combine selection boxes. Below you find the basic rules to do so. And Logic To obtain an And logic, position the boxes after each other in the sequence. Example: To select intervals by the behavior Playing And filter the behavior Talk to Parent. This way you analyze only the behavior Talking to Parent during the intervals that the subject was playing. Or Logic To obtain an Or logic, split the data selection sequence into two branches and place the boxes in parallel. Example: To analyze those intervals during which a bird either brought a caterpillar or spider into the nest, or a prey smaller than 1 cm. Do not use this Or logic if you use multiple selection boxes in each branch. The data selection may give unexpected results. Create a separate Results box for each branch instead. Order of Selection Boxes The order in which you place boxes in a selection sequence is very important. Please read this section carefully. If your sequence contains Filter boxes only: - If each Filter box refers to a different type of element (for example, one Filter box for an independent variable, one for subjects, one for behaviors), then the order you place the boxes does not matter. - If Filter boxes refer to the same type of element (for example, one Filter (Behaviors) box filtering the behavior group Area of Interest Behaviors, and another Filter (Behaviors) box for Facial Expression Behaviors), then the selection does not work, because the first filter has removed the behaviors in the second filter. --- ## The Observer XT 17 - Set Up Your Project - Access the Video Files on Another Computer URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-access-the-video-files-on-another-computer Chapter: The Observer XT Access the Video Files on Another Computer Aim In a two-computer setup, this procedure ensures that The Observer XT can access videos from FaceReader or MediaRecorder on another computer. The videos are not copied to The Observer XT; instead, The Observer XT creates a link to the videos. Overview of Steps - Share the folder where the video files are stored. - Turn off password protected sharing on the computer with the video files. - Create a mapped drive from the shared folder on both computers. Share the Folder Where the Video Files Are Stored - Right-click the folder where the video files are going to be stored, select Give Access To, and then select Advanced Sharing Settings. - Change the sharing options for all your network profiles (Private, Guest or Public, and Domain): select the option Turn On File and Printer Sharing for all your profiles. - Under All Networks, select the option Turn On Sharing So Anyone with Network Access Can Read and Write Files in the Public Folders. Then click Save Changes. Switch Off Password Protected Sharing on the Computer with the Video Files This procedure ensures that the folder where the video files are stored can be accessed without a password by the computer running The Observer XT. The procedure differs depending on whether the computer is in a Windows workgroup or a domain. To check, open the Control Panel, choose System, and look under Computer Name, Domain, and Workgroup Settings. Procedure for Workgroup - Follow the procedure in Share the Folder Where the Video Files Are Stored to open the Advanced Sharing Settings. - Under Password Protected Sharing, select the option Turn Off Password Protected Sharing. Important: If you do not see this option, most likely your computer is in a domain, not a workgroup. Carry out the procedure for domain below. Procedure for Domain - Press the Windows key + R. - Type lusrmgr.msc and press OK. - Open the Users folder and double-click Guest. - Deselect Account Is Disabled and click OK and close the lusrmgr window. - Press the Windows key + R. - Type gpedit.msc and press OK. - Open Computer Configuration\Windows Settings\Security Settings\Local Policies\User Rights Assignment and double-click Deny Access to This Computer from the Network. - Click Guest and then choose Remove > OK. - Close the Local Group Policy Editor window. Map the Shared Video File Folder Carry out this procedure on both computers. - Open File Explorer and then This PC. - Click Computer and then click the Map Network Drive icon. - Choose a name for the drive and browse to the shared folder. Important: Make sure you select the same drive letter on both computers. - Click Finish. - When you start the computer with The Observer XT you will need to enter the login details for the computer with the video files. - Make sure the computer with the video files is switched on when you open your project in The Observer XT. Otherwise The Observer XT will not be able to open the videos. --- ## The Observer XT 17 - Set Up Your Project - Add a Custom External Device URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-add-a-custom-external-device Chapter: The Observer XT Add a Custom External Device Aim To control a device that cannot communicate with The Observer XT using the Noldus communication protocol N-Linx. Examples of such devices are older versions of MediaRecorder and FaceReader, some physiological data acquisition systems, and some eye trackers. Note: BIOPAC AcqKnowledge 5, Tobii Pro Studio, Tobii Pro Lab, Tobii Glasses software, and the Bitbrain EEG acquisition software can be controlled using N-Linx, which simplifies data acquisition and ensures synchronization with events with the acquired data. See the following technical notes available for download from the MyNoldus section of the Noldus website: - Technical Note - BIOPAC MP System - The Observer XT - Technical Note - Tobii Pro Eye Trackers - The Observer XT - Technical Note - Tobii Glasses - The Observer XT - Technical Note - Bitbrain EEG - The Observer XT Prerequisite The external device can be controlled with a command line. General Procedure - Choose Setup > Project Setup. Under Observation Source, select Live Observation. - The Devices window opens. If not, click the Devices button. Click the Add External Program button at the bottom of the table. - Enter a name for the action, for example, Control MediaRecorder 3. - Under At:, select when you want the program to run. The action will be defined in step 5. - In each of the three rows, click the button next to the Program field and browse to the program to control. - In the Command Line Options field, enter the command to be carried out, for example /R in the Start Observation row for MediaRecorder 3. You can also enter the following commands in the Command Line Options field: - %ON% – Enters the current observation name in the command line. - %SN% – Enters all available subject names in the command line, separated by spaces. Use these options to, for example, run a batch file and enter the current observation name or the subject names in the file name it produces. It is not possible to combine these options with other commands in the command line. - There may be a delay between the observations and the commands being carried out in the external program. Enter this delay in the ms. before fields. The Observer XT will then send the commands the specified time before the observation starts or ends. See also: How Do I Determine the Delay? - Click OK. The Devices window shows the newly added action of the external program. Select the checkbox in front of it. Click Edit Settings to change this action. To rename or delete an action, right-click the corresponding row and select the option. - To add more actions, repeat steps 2 through 9 for each external program. - Optionally, set up Automatic Linking of Digital Media Files to automatically import videos created by the external program into the observation. - For detailed procedures for older versions of MediaRecorder or FaceReader, consult the Reference Manual of that version. - Videos created by MediaRecorder 2.5 or higher are automatically synchronized with the Event Log when you import them in The Observer XT. How Do I Determine the Delay? - Carry out a test observation and make sure that with The Observer XT you score some conspicuous event that is also visible in the imported video or data file. For example, you record pressing a key on video. - Manually synchronize the event log and the imported file using the logged event. See Manual Offset. - Open the File Synchronization window (see Numerical Offset); the offset of the data file relative to the event log is displayed here. - Enter this value in the ms. before fields in step 7 of Add a Custom External Device. Note: For complex lab setups with various external applications, you can use the Noldus SyncBox to facilitate determining this delay. See the SyncBox - The Observer XT Technical Note, available for download from the Noldus website. --- ## The Observer XT 17 - Set Up Your Project - Automatic Linking of Digital Media Files URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-automatic-linking-of-digital-media-files Chapter: The Observer XT Automatic Linking of Digital Media Files Aim To automatically import videos into the observation and synchronize them with the Event Log. Prerequisite You have an external video recording device that can be controlled with command lines, for example MediaRecorder 3 or lower. Current versions of Noldus software support data transfer and video linking with N-Linx, which is the recommended method. See, for example, Observe Live and Record Video with MediaRecorder or Observe Live and Analyze with FaceReader. Procedure - First, follow the procedure Add a Custom External Device to start and stop the video recording software with commands from The Observer XT. - Then select Automatic Linking of Video Files in the Devices window. The Automatic Linking of Video Files window opens. If not, click Edit Settings. - Video Linking Folder – Browse to the folder with the video files. Important: If the video files are stored in a shared folder, for example in a two-computer setup, select the shared folder, not the original folder. The original folder is a local folder on the computer with the video files and cannot be accessed by The Observer XT. Also make sure the application stores videos in the shared folder and not in the original folder. Example: You shared the default folder C:\Users\Public Documents\Noldus\MediaRecorder\Videos as MediaRecorder 3 Videos. Then select MediaRecorder 3 Videos as the default location where MediaRecorder stores its video files, and also browse to MediaRecorder 3 Videos in the Video Linking Folder field. - Link Video Extensions – Make sure the video file format is present in this list. To specify multiple extensions, enter a semicolon (;). - Link Video Based On – Choose one of the following: - Observation Name Found in Media File Name – To let The Observer XT look for video files that contain the name of or have the same name as the current observation. - Video Start Time (Later Than Observation Start Time) – To let The Observer XT search for video files that are saved after the observation start time. - Search For – Specify the number of videos per observation The Observer XT should look for. - Stop Searching After – Specify the time The Observer XT should look for video files. Maximum time is 600 seconds. - Visualize Audio of Video Files – To view the audio stream of the video files as waveforms. - Make sure the Automatic Linking of Video Files option and the External Command option are selected in the Devices window. - Carry out an observation. After you have stopped the observation, the videos are imported into the observation. Troubleshooting No Media Files Are Detected This can be because: - You have set the wrong folder in the Video Linking Folder box. - You have set the time in Stop Searching After too short to detect any media files. - You have selected Observation Name Found in Media File Name but the current observation name and media file name do not match. - The video file extension is not present in the Link Video Extensions box. - In a two-computer setup, you shared the video file folder but selected the original folder name as the linking folder instead of the shared folder. The original folder is a local folder on the computer with the video files and cannot be accessed by The Observer XT. Example: You shared the default folder C:\Users\[your username]\Documents\Noldus\FaceReader 9\Projects\[project name]\Recorded Videos as FaceReader Videos. Then browse to FaceReader Videos and not to the original folder. - In a two-computer setup, you shared the video file folder but the application saves its videos to the original folder. Choose the shared folder as the location where the application stores its video files. Not All Media Files Are Detected This can be because: - You have set the time in Stop Searching After too short to detect all media files. - The number of video files set next to Search For is smaller than the number of video files actually created in one observation. All Media Files Have Been Detected but Monitoring Continues This can be because the number of media files set next to Search For is larger than the number of video files actually created. Click Stop Search. Source: The Observer XT 17 Help - Set Up Your Project, Noldus Information Technology --- ## The Observer XT 17 - Set Up Your Project - Behaviors URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-behaviors Chapter: The Observer XT Behaviors What Are Behaviors? Behaviors are actions, tasks, movements, situations, and locations of the subjects under study that are relevant for your research question. Behaviors must be organized in groups. Examples of Behaviors - Mother-infant interaction study – Gaze Mother, Baby Smile, Vocal Imitation, etc. - Research on monkeys – Walk, Forage, Groom, Chase Away, etc. - Usability study – Task 1, Task 2, Usability Hit, User Error, etc. Behavior Groups Behaviors are organized in groups. Behavior groups contain behaviors that are closely related. Behaviors cannot be part of groups within larger groups. Examples of behavior groups include: - Mother-infant interaction study – A Gaze group including Gaze Mother and Gaze Elsewhere; an Emotion group including Baby Smile, Baby Neutral, etc. - Research on monkeys – A Locomotory group including Walk and Climb; a Social group including Bite and Groom. - Usability study – A Tasks group including Task 1 and Task 2; a User Experience group including Usability Hit and User Error. Behavior Group Types The Observer XT has the following group types: - Mutually Exclusive – Behaviors in this group cannot occur at the same time. When one behavior is active, the other behaviors within the same group cannot be active. During coding, you only score the start of behaviors. When you code the start of a new behavior, the previously coded behavior of the same group automatically stops. - Mutually Exclusive and Exhaustive – A special case of the mutually exclusive group where always one behavior is active, with no gaps between behaviors. To make a group exhaustive, select the group name in the Behaviors panel of the Coding Scheme, click the Properties button, and select the Exhaustive checkbox. Fill any gaps between events with a behavior such as Other Locomotion or No Locomotion. If you use a mutually exclusive and exhaustive behavior group, a behavior must be scored at the start of the observation using an Initial State Event. Note: In The Observer XT version 12.0 or lower, a mutually exclusive group was exhaustive by default. This is no longer the case, so it is no longer necessary to define and score Initial State Events. - Start-Stop – Behaviors in this group can overlap and there can be gaps between behaviors. You must code both the start and the stop of each behavior. This group type requires more key presses than a mutually exclusive group. It is recommended to use mutually exclusive behavior groups where possible to reduce scoring effort. - Sample Group – Used when instantaneous sampling is the observation method. Behaviors in sample groups do not have a duration. You score which behaviors are occurring at regular intervals and obtain frequencies rather than durations. Behaviors in a sample group always exclude each other, meaning only one behavior from the group can be scored in each sample. If behaviors can occur at the same time, define them in different sample groups. Behavior Types There are three types of behaviors: - Point Events – Behaviors without measurable or relevant duration. Either their duration is immeasurably short (for example, hitting) or you are not interested in the duration but only in its frequency (for example, talking). - State Events – Behaviors with a distinct start and end. Both the frequency of occurrence and the duration are recorded. Examples include walking, playing, and grooming. - Initial State Events – This behavior type is only needed in a mutually exclusive and exhaustive behavior group. In such a group, one behavior is always active, including at the start of the observation. An Initial State Event is automatically scored at time 0. If another behavior is occurring at the start of the observation, press the key for the correct behavior before you start the observation. Define Behaviors in a Behavior Group for Continuous Sampling Aim To specify the behaviors for continuous sampling observations. Prerequisite Your Coding Scheme is open. If this is not the case, choose Setup > Open Coding Scheme. Procedure - Click the Add Behavior Group button. - In the window that appears, enter the Behavior Group name. - Choose whether the behaviors in the group type cannot occur at the same time or can overlap. See Behavior Group Types. - Add the behaviors and select whether they have duration or not. Take notice of the example of the data you can obtain with this behavior type under Behavior Analysis. See Behavior Types. - When done, click OK. The new group appears in the Behaviors panel. - Repeat the procedure for the other behavior groups. Define Behaviors in a Sample Group for Instantaneous Sampling Aim To specify the behaviors for instantaneous sampling observations. Prerequisite Your Coding Scheme is open. If this is not the case, choose Setup > Open Coding Scheme. Procedure - Click the Add Sample Group button. - In the window that appears, enter the Group name. - Add the behaviors. - When done, click OK. The new group appears in the Behaviors panel. - Repeat the procedure for the other sample groups. Notes - By default, each behavior/sample group is connected to each subject in a Subject-Behavior Combination, which means that you score every behavior/sample group for each subject. To change that, see Define Subject Properties. - To re-open the behavior/sample group, double-click the name in the Behavior Name column. --- ## The Observer XT 17 - Set Up Your Project - Define Behavior (Group) Properties URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-define-behavior-group-properties Chapter: The Observer XT Define Behavior (Group) Properties Aim To specify details for the behavior or behavior group. Behavior Group Properties Open the Behavior Group Properties pane by selecting the group name and clicking the Properties button at the bottom of the screen. Enter the following details: - Description – Optionally add a description to your behavior in the Description field (maximum 1024 ASCII characters). This is particularly useful if two or more people are using the same coding scheme and need to know how the behaviors are defined. - Mutually Exclusive – To change a group in which behaviors can overlap (start-stop) into a group in which behaviors cannot occur at the same time (mutually exclusive), or vice versa. - Exhaustive – By default, gaps can occur in a group in which behaviors cannot occur at the same time. If you do not want that, select the Exhaustive checkbox. If you do so, also define one of the behaviors in this group as an Initial State Event. See Behavior Types. - Inactive – To make the behavior group inactive when you do not want to use it anymore. See Delete a Coding Scheme Element or Group. Behavior Properties Open the Behavior Properties pane by selecting the behavior name and clicking the Properties button at the bottom of the screen. Enter the following details: - Description – Optionally add a description to your behavior in the Description field (maximum 1024 ASCII characters). This is particularly useful if two or more people are using the same coding scheme and need to know how the behaviors are defined. - Start Code – The code to score the behavior. With the option Generate Keycodes Automatically, the key code is automatically assigned to the behavior. Optionally, change it. - Color – This color and pattern are shown in the Data and Audio Visualization window and in the Visualization. Click the Color cell to change it and to add a pattern (optionally). - Sound – Optionally browse to a sound (*.wav file) you want to hear when you score that behavior. To play the sounds, you must select the Use Coding Scheme Sounds (for elements only) checkbox in the Sound Feedback tab of the Project Settings. - Event Type – Optionally, change the behavior type. See Behavior Types. - Add Comment – Select this checkbox if you want to add a comment every time you score that behavior. Selecting Add Comment is especially useful if you score from audio files and want to transcribe spoken text into comments; select the Add Comment checkbox for each behavior separately. - Inactive – Select this checkbox if you want to make the behavior inactive when you do not want to use it anymore. See Edit a Coding Scheme Element After Observing in Carry Out an Observation. - Modifiers – Choose the modifier groups you want to link to that behavior. See Modifiers for information about modifiers, how to define them, and how to assign modifier groups to behaviors. Note: Many of the properties can be shown as columns in the Behaviors pane but are hidden by default. To show these columns, right-click one of the headers and select Show All Columns. To hide a column, right-click that column's header and select Hide Column. To choose a subset of columns, right-click a header, select Show Column, and make your selection. Frequently Asked Questions About Behaviors When to Use Behaviors With or Without Duration? Define behaviors with duration (State events) if you need to know the duration of activities. Behaviors without duration (Point events) are recommended for behaviors of negligible duration, like eye blinks. The behavior "look at screen" can be defined as a state, and each blink as a point event. However, if you want to know the durations of the time between blinks, you need to define them as states, recording with every "blink" event the start of an interval between two blinks. Point events can be placed anywhere in the coding scheme and do not stop mutually exclusive states. When to Use a Group Type in Which Behaviors Cannot Occur at the Same Time? Use behavior groups in which behaviors cannot overlap (Mutually Exclusive) when you want to calculate time budgets or when you are interested in the durations of the events. Use this kind of group also when you plan to analyze the time when a specific event occurred during a certain episode. For example, if you want to calculate the number of user errors during each task performed, define the tasks in a mutually exclusive group. When to Use Mutually Exclusive Exhaustive Behavior Groups? Make the behavior group in which behaviors cannot overlap Exhaustive if you want the durations within the group to add up to 100%. This way you can compare figures from different calculations. Mutually exclusive groups were exhaustive by default in The Observer XT 12.0 and earlier versions; this is no longer the case. When to Use Behavior Groups in Which Behaviors Can Overlap? Use a group in which behaviors can overlap (Start-Stop) when the behaviors in the group do not exclude each other. Scoring effort is higher in such a group because you have to press a key for both the start and the stop of each behavior. If possible, divide the behaviors over multiple behavior groups in which behaviors cannot occur at the same time. When to Use Sample Groups? Use sample groups when the observation method is instantaneous sampling. See Observation Method. Can I Use Point Events in a Behavior Group for Instantaneous Sampling? You cannot define point events when you use instantaneous sampling. You can use them if you use Combine Continuous and Instantaneous Sampling. See Observation Method. --- ## The Observer XT 17 - Set Up Your Project - Define Project Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-define-project-setup Chapter: The Observer XT Define Project Setup Aim To define whether you want to observe live or from prerecorded video, whether you want to score continuously or with intervals, and how long you want to score. Procedure - Choose Setup > Project Setup. - Choose the Observation Source. - Choose the Observation Method. - Choose the Observation Duration and, optionally, enter Project Information. Observation Source Choose one of the following options: - Offline Observation — To score data from previously recorded video or audio files. - Live Observation — If you want to score data from a live scene. If you select this option, the Devices window opens. Choose this option also: - To record video with MediaRecorder while you observe simultaneously. - To record data other than events, for example physiological data. Note: You can change the observation source for different observations, for example if you want to analyze video you created during a live observation. Select the observation source before you create a new observation. Observation Method Choose one of the following options: - Continuous Sampling — With this method you record all occurrences of the behaviors of interest of one or more subjects as they occur. You obtain full descriptive statistics of the behaviors, including duration per instance, total duration, and frequency. Choose Continuous Sampling to calculate absolute frequencies and durations of the behaviors of interest. - Example: You want to record the interaction between a parent and child and calculate the duration and frequency of the child smiling in the presence and absence of the parent. - Instantaneous Sampling — With this method you record the behavior of one or more subjects at preselected moments in time. You obtain frequencies of the behaviors, not their durations. This method is also referred to as scan sampling, interval sampling, intermittent sampling, or point sampling. It is not the same as one-zero sampling, where it is recorded whether a behavior occurred or not during the previous sample period. Choose Instantaneous Sampling when your observations are too long or your number of subjects is too large to score every behavior of every subject as it occurs. Instantaneous sampling is commonly used to calculate time budgets, general activity, behavioral synchronization, and spatial relations in groups. Instantaneous sampling is not suitable for behaviors with very short duration, and should not be used if you plan to create episode selections with your data. - Example: You observe a group of children and want to know the spatial distribution of the group over different tables. - Combine Continuous and Instantaneous Sampling — This method combines Continuous Sampling and Instantaneous Sampling. Use it when you want to record the behavior of one or more subjects in detail while recording the behavior of other subjects in less detail. - Example: You observe a group of chickens and want to record the behavior of one chicken in detail and the behavior of the rest of the group at regular time intervals. Sample Interval Length If you select Instantaneous Sampling or Combine Continuous and Instantaneous Sampling, the Sample Interval Length field appears under Observation Duration. It is important to choose an appropriate interval between samples to yield meaningful data. If the sample interval is too long, collecting a decent amount of data is time-consuming. If the sample interval is too short, data from successive samples are not independent. More Options See Other Project Setup Options. Define Project Settings Aim To define the way you record data, for example how many characters keycodes have, the time format, and which playback control buttons to use. Procedure Choose Setup > Project Settings. See Project Settings for a full description of the options. Note: You can change project settings at any time, even after you have already carried out observations. To return to the default options, click the Reset to Default button. Note that this resets the options of all tabs to their default settings, not only the ones on the current tab. Create Coding Scheme Aim To create the set of elements that describe the events to be recorded. The Coding Scheme may consist of the following elements: - Subjects (optional) — The individuals (persons, animals) that are observed. - Behaviors — The behaviors or actions that are relevant for your research hypothesis. - Modifiers (optional) — Factors that describe the behaviors in more detail. Each element in the coding scheme is linked to a keycode. Procedure - Choose Setup > Open Coding Scheme. - Create Subjects (optional), Behaviors, and Modifiers (optional). - Check your Coding Scheme for errors. Notes - The coding scheme can contain a maximum of 250 subjects, 250 behaviors, and 250 modifiers in up to 100 modifier groups. The maximum number of subject-behavior combinations is 5000. - All coding scheme names must be unique and may consist of a maximum of 64 characters. - Different limits apply if you use Pocket Observer. See the Pocket Observer Reference Manual for details. - It is not mandatory to score subjects, behaviors, or modifiers. It is possible to record only free text in the comments column. However, you can only visualize and analyze an observation that contains scored behaviors. --- ## The Observer XT 17 - Set Up Your Project - Enter Modifier Details URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-enter-modifier-details Chapter: The Observer XT Enter Modifier Details - Description – Optionally add a description to your modifier in the Description field (maximally 1024 ASCII characters). This is particularly useful if two or more people are using the same coding scheme and need to know how the modifiers are defined. - Start Code – The code to score the modifier. With the option Generate Keycodes Automatically, the key code is automatically assigned to the modifier. Optionally, change it. - Color – This color and pattern are shown in the Data and Audio Visualization window and in the Visualization. Click the Color cell to change it and to add a pattern (optionally). - Sound – Optionally browse to a sound (*.wav file) you want to hear when you score that behavior. To play the sounds, you must select the Use Coding Scheme Sounds (for elements only) check box in the Sound Feedback tab of the Project Settings. - Inactive – Select this check box if you want to make the behavior inactive when you do not want to use it anymore. Notes On Modifier Properties - Many of the properties can be shown as columns in the Modifiers pane, but are hidden by default. To show these columns, right-click one of the headers and select Show All Columns. To hide a column, right-click that column's header and select Hide Column. To choose a subset of columns, right-click a header, select Show Column and make your selection. - To score an action of A directed to B, B must be defined as a modifier. You can therefore create a modifier group containing the names of your subjects that can be the receivers of an action. You can copy your list of subjects and paste them into a modifier group. The header Subject Name is also pasted. Right-click it and select Delete. - You can create a coding scheme by importing a data file, for instance an ODX file from The Observer XT. In the coding scheme which you create in this way, all the subjects, behaviors and modifiers are ungrouped. This means that you may need to reorganize your coding scheme. Note that there are limits to the number of subjects, behaviors, and modifiers that you can import. You can only import files that comply with these restrictions. Check Your Coding Scheme Aim To check whether the coding scheme is free of errors. Background You cannot carry out an observation when your coding scheme contains errors. When you have the Check Coding Scheme While Editing option selected in the Coding Scheme Settings window, a warning triangle appears in front of the coding scheme element as soon as you enter an element with an error. When you point with the mouse at an icon with a warning triangle, a description of the coding error pops up. Procedure For a detailed overview of the coding scheme errors, click the Check button. The window that opens lists all the errors in your coding scheme. To Correct Coding Scheme Errors - Select an error to view a description of the problem. - Click the element to jump to it in the coding scheme, then correct it. - Click the Check Again button to check whether the errors were corrected successfully. - Click Close when all the errors are corrected. Common Errors In The Coding Scheme - Two or more subjects, behaviors or modifiers are given the same keycode, or the same name. - A behavior or modifier group does not contain any elements. - A mutually exclusive and exhaustive behavior group does not contain an Initial State event. - You have selected the Use Pocket Observer With option in the Coding Scheme Settings and you have created a behavior group with only one behavior. - You have selected the Use Pocket Observer With option in the Coding Scheme Settings and the element name exceeds 16 characters. Edit The Coding Scheme Add A Coding Scheme Element - To add a subject, click the Add Subject button in the Subjects panel. - To add a behavior or modifier, click first the group of behaviors or modifiers you want to add the element to, then click the Add button on top of the panel that applies. - To add a behavior group or modifier group, click the Add Behavior Group or Add Modifier Group button. Sort Coding Scheme Elements You can change the order of the elements of your coding scheme for visualization purposes. For example, when creating a plot of the events, you may want to view the Verbal behaviors at the top and the Play behaviors at the bottom of the event plot. To change the order of elements or groups, click an element or group and drag it below the name of other elements or groups. Edit A Coding Scheme Element You can change the name and the properties of a coding scheme element at any time. Do this either in the coding scheme, or in its properties window. To open the properties window, select the element and click the Properties button at the bottom of your window. To move an element from one group to another, drag it to the name of the group where you want to place it. Delete A Coding Scheme Element Or Group You can only delete a coding scheme element or group when it has not been scored yet. Select the element and press Ctrl+Del. If you delete a group, you also delete the individual elements within that group. When the element was scored in at least one observation, a question appears whether you want to inactivate it. If you want to delete the element anyway, you must first delete all the observations in which it was scored. When a coding scheme element is set to inactive, it is not used anymore although it is still present in the coding scheme. An inactive element is grayed out in the coding scheme. If the element was already scored, it will remain present in the event log. However, it is not shown in the Codes window of new observations, so you cannot score it. In event plots and analysis results, the element is displayed as [Element Name] (Inactive). You can use the keycode of an inactive element for new elements. To reactivate an inactive element, right-click it and select Activate. --- ## The Observer XT 17 - Set Up Your Project - Independent Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-independent-variables Chapter: The Observer XT Independent Variables What Are Independent Variables Independent variables are assumed to remain constant within observations but may differ between observations. To open the Independent Variables list, choose Setup > Independent Variables, or click Independent Variables in the Project Explorer. Types Of Independent Variables - User-Defined Variables – Variables that describe the subjects, observation sessions and environmental conditions. Examples include the name of the subject, the name of the observer, and the weather during the observation. - Video Files – Name and location of the video files used in the observation. They are added automatically to the independent variable list when you create an observation. The scope of a video file is always observation. If you already have observations, click Add Video to add video files to your observation. - Audio Files – Name and location of the audio files used in the observation. The scope of an audio file is always observation. If you already have observations, click Add Audio to add audio files to your observation. - External Data Files – This column is only present when you have the External Data Module. It shows the name of the external (physiological) data files imported into an observation. The scope of an external data file is always observation. - System Variables – Three variables are automatically created by the system: the start time, stop time and the duration of an observation. To change the format of these variables, click the arrow in the Format field and make your selection in the window that appears. Create User-Defined Variables Aim - To define variables that potentially influence the value of a dependent variable. - To list the names or numbers of the subjects in your observations. Prerequisite The Independent Variables list is open. If this is not the case, choose Setup > Independent Variables. Procedure - Click Add Variable. - Enter the following options: variable type, variable format, predefined variable values (optional), variable scope, and value update. Notes - You can add maximally 40 user-defined variables. - The independent variable name may have maximally 64 characters. The description may have maximally 255 characters. Variable Type Click the arrow in the Type field and choose one of the following options: - Text – A text variable is denoted by alphanumeric characters, composed of letters, numbers or both. For example, the name of the observer. - Numerical – A variable represented by numbers only, for example, the age of the subject. - Timestamp – A variable represented by a time stamp, for example the starting date and time of the experiment. - Duration – A variable represented by a duration, for example, the duration of the treatment. - Boolean – A variable that is either False or True. For example, the presence of the observer during the test. Variable Format - Text And Boolean Variables – For Text and Boolean variables you cannot specify a format. - Numerical Variables – Choose the number of decimals (maximum 9). Deselecting No. of Decimals will result in using integers. Select Scientific Notation to display numbers as, for example, 1.485e+0.03 instead of 1485.236. In the Unit field, enter the unit of your variable, for instance, years for the age of the subject. - Timestamp Variables – Specify the format. The format f represents the decimals you specified in the Time Formats tab of the Project Settings window. - Duration Variables – Specify the format. The format f represents the decimals you specified in the Time Formats tab of the Project Settings window. Note On Regional Settings The program uses the decimal separator specified in your computer's regional settings (Control Panel > Region). If you change regional settings, close and restart The Observer XT. Predefined Variable Values Optionally predefine values so you can select from them when entering user-defined variables. For Timestamp and Duration variables you cannot specify predefined values. - Text Variables – Enter the text you want to choose from. Select Allow Other Values if you are not sure whether the values you have defined are exhaustive. This allows you to add new values as they are needed. - Numerical Variables – Choose whether your variable can have any value, a value in a range, or predefine values. Select Allow Other Values if you are not sure whether the predefined values are exhaustive, so you can add new values when needed. - Boolean Variables – Enter the names to display. For instance, if your variable is Parent Present, you may define the values No (False) and Yes (True). --- ## The Observer XT 17 - Set Up Your Project - Keycodes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-keycodes Chapter: The Observer XT Keycodes Aim To explain the concept of keycodes, what the restrictions are, and how they are generated. Background Each element in the coding scheme can be linked to a keycode, which is a key or combination of keys on the keyboard that you press to code events. If you code without keycodes, you have to click on the screen with your left mouse button, which is generally slower and requires you to take your eyes off the observed scene to look at the computer monitor. The assignment of keycodes is crucial because it determines the efficiency and convenience of your recording. Your code definitions should be logical, easy to memorize, and ergonomic. Procedure The Observer XT can generate keycodes automatically while you build your Coding Scheme. The automatically generated keycode is based on the name of the element, for instance "w", "wa", or "wal" for "walk" using a default keycode length of 1, 2, or 3 respectively. If the keycode is already in use, the next character in the name is used. If the resulting keycodes are also in use, the next suitable character in the alphabet is used. To choose a different keycode, click the cell next to the element in the coding scheme and type another code. Make sure the code is not already in use. Keycodes Conditions - Maximum keycode length is 3 characters. - Within a category (subjects, behaviors, or modifiers), all keycodes must be unique. - For keycodes of more than one character, you can use code 'ab' for subject 1 and 'ac' for subject 2, but you cannot use 'a' and 'ab'. - The keycode length may be different for subjects, behaviors, and modifiers and may also differ within the categories. - The characters must be ASCII characters in the range between 32d and 127d. - You cannot use the space bar as a keycode. Notes - To regenerate a keycode because it is conflicting with another one, right-click the code in the coding scheme and select Regenerate Selected Keycodes. To regenerate all codes, right-click any code and select Regenerate All Keycodes. - If you have keycodes with the Shift key, you may press the right Shift key for a long time while scoring. Pressing the right Shift key for 8 seconds enables the Filter Keys option in Windows. With Filter Keys, rapid keystrokes are ignored. To disable Filter Keys, press the Windows key + U, click Make the Keyboard Easier to Use, deselect Turn on Filter Keys, and click Set Up Filter Keys. Deselect the check boxes in front of Turn on Filter Keys and Turn on Filter Keys When Right Shift Is Pressed for 8 Seconds. Click OK twice. --- ## The Observer XT 17 - Set Up Your Project - Modifiers URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-modifiers Chapter: The Observer XT Modifiers What Are Modifiers? Modifiers can be attached to behaviors and are used to limit the scope of a behavior. Like behaviors, modifiers are defined in groups. You assign a modifier group to one or more behaviors. Scoring modifiers involves making extra keystrokes. If you have a simple coding scheme without numerical data, it can be better to define more behaviors and not use modifiers. For example, use two behaviors — Play Alone and Play in a Group — instead of one behavior "Play" with two modifiers (Alone and In a Group) attached. Examples of Modifiers - Child Behavior Study – To describe the object being played with, a modifier group "Object" is defined that includes the elements Cards, Ball, and Castle for the behavior Play. - Usability Study – To describe the type of error by the test participant, a modifier group "Error Type" is defined that includes Wrong Value and Wrong Weblink for the behavior User Error. - Aggression in Lobsters – To describe the level of aggressiveness in territorial interactions, a modifier group "Level" is defined that includes the values 0 to 5. Modifier Group Types Modifier groups can be nominal (text) or numerical (numbers). - For nominal modifiers you can calculate the same descriptive statistics as for behaviors, such as mean duration and frequency. - For numerical modifiers you can calculate additional statistics such as average and other numerical statistics of the numbers scored. For example, the numbers 1, 2, 3, and 2 scored in an observation result in Total Number = 8, Average = 2, Minimum = 1, and Maximum = 3. Define Modifiers Aim To specify the modifiers attached to a behavior. Prerequisites - Your Coding Scheme is open. If this is not the case, choose Setup > Open Coding Scheme. - The Modifiers pane is shown. If this is not the case, choose View Settings > Modifiers. Procedure for Nominal Modifiers - Click the Add Modifier Group button. - Choose Add Nominal Modifier Group. - Give the modifier group a name and, optionally, select the following: - Mutually Exclusive – Select this for a mutually exclusive group. If you select this option, you can only score one modifier at a time for that group; you cannot score two or more modifiers from the same group for a specific event. - Modifier Group Must Be Scored – Selecting this option makes scoring a modifier compulsory when you score the associated behavior. - Enter the modifiers in the Value fields. - Define to which behavior the modifier group should be attached in the Link to Behaviors field. Procedure for Numerical Modifiers - Click the Add Modifier Group button. - Choose Add Numerical Modifier Group. - Give the modifier group a name and define the keycode to activate this modifier group. From the Values list, select one of the following: - Predefined Values – Make a list of predefined options from which to choose. For example, for the modifier group Aggression Level, you want the observer to choose between 0, 1, 2, and 3. - Range of Values – Score the modifier by entering a value between a minimum and a maximum value. For example, for the modifier group Speed, you want the observer to score a value between a minimum of 0 and a maximum of 150 with a precision of 1 decimal. - Define to which behavior the modifier group should be attached in the Link to Behaviors field. Define Modifier (Group) Properties Aim To specify details for the modifier group or modifier. Modifier Group Properties Open the Modifier Group Properties pane by selecting the group name and clicking the Properties button at the bottom of the screen. Enter the following details: - Description – Optionally add a description to your modifier group in the Description field (maximum 1024 ASCII characters). This is particularly useful if two or more people are using the same coding scheme and need to know how the modifiers are defined. - Inactive – Select this checkbox if you want to make the modifier group inactive when you do not want to use it anymore. See Edit a Coding Scheme Element After Observing in Carry Out an Observation. - Modifiers – Select to which behaviors the modifier group should be attached. Modifier Properties Open the Modifier Properties pane by selecting the modifier name and clicking the Properties button at the bottom of the screen. --- ## The Observer XT 17 - Set Up Your Project - Observe Live and Analyze with FaceReader URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-observe-live-and-analyze-with-facereader Chapter: The Observer XT Observe Live and Analyze with FaceReader Aim Integrating FaceReader with The Observer XT achieves the following: - When you start an observation, FaceReader starts analyzing with the selected settings and records a video of the test participant's face. - When you stop an observation, FaceReader stops analyzing. - The FaceReader analysis results are automatically imported into The Observer XT and synchronized with the events. - The recorded video is automatically linked to the observation and synchronized with the events and FaceReader analysis results. Prerequisites - You have FaceReader 8 or higher. For earlier versions, the procedure may be different; consult the documentation of that version. - The Observer XT, FaceReader, and N-Linx Server are installed on computers that are in the same network. - Your license for The Observer XT includes the External Data Module. - FaceReader is open. - You created a project with at least one participant in FaceReader. - You selected a default camera in FaceReader and selected to record video. - In the FaceReader Data Export Settings, you selected Enable N-Linx and entered the IP address or computer name of the computer with N-Linx Server. - If FaceReader, N-Linx Server, and The Observer XT do not all run on the same computer, you created exceptions in Windows Firewall for the default port 5672 on all computers. If you chose another port, you created exceptions in Windows Firewall for that port. - If FaceReader and The Observer XT run on different computers, you made sure that the computer with The Observer XT can access the FaceReader video files. See Access the Video Files on Another Computer. Procedure in Short The detailed procedure to set up FaceReader with The Observer XT is present in the topic FaceReader with The Observer XT in the FaceReader Help. Press F1 in FaceReader to open it. In The Observer XT - Choose File > Preferences > N-Linx Settings. - Select Use N-Linx Server to connect with other applications. - In the N-Linx Server address field, enter the IP address of the computer with N-Linx Server. Leave the default entry Localhost if N-Linx Server is on the same computer as The Observer XT. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. - Click Test Connection. If connection with N-Linx is found, the Status will change to Connected. If not, enter the correct settings and click Test Connection again. - Click OK. - Choose Setup > Project Setup. - Select Live Observation. The Devices window now opens. If not, click the Devices button. - Select the checkbox in front of FaceReader - [computer name] and click Edit Settings. - Select the FaceReader settings for your experiment. Optionally, enter a name in the Identify Device As field. This name will be added to the Coding Scheme as Subject and allows you to control multiple instances of FaceReader running on different computers with The Observer XT. - Click OK and select the checkbox in front of the line FaceReader - [computer name]. In FaceReader - Choose File > Set Default Camera, choose your camera, and select the option Record. - Choose File > Settings > Data Export. - Under External Communication (N-Linx), select Enable N-Linx. - If FaceReader and N-Linx Server run on the same computer, leave the default address Localhost in the N-Linx Server Address field. If the programs run on different computers, enter the IP address or computer name of the computer with N-Linx Server. To find that name, open the Control Panel and choose System. - In the N-Linx Server Port field, leave the default port 5672. Ask your system administrator for assistance if this port is in use by another program. - Under Export (Detailed Log, ODX, N-Linx and API), choose which data to send to The Observer XT. Carry Out Observation When you carry out an observation, FaceReader analysis starts. You can follow the data transfer in the N-Linx Data Transfer window. When you stop the observation, the FaceReader data are imported into the observation. The name entered in the Identify Device As field is imported as Subject in the Coding Scheme. The video is also imported into The Observer XT automatically. The N-Linx Data Transfer Window Each row in the window represents a data stream with the following columns: - Stream: The name given in the Identify Device As field combined with the name of the data stream. - Messages: The number of times information was sent from FaceReader to The Observer XT. - Error: An error can occur when a package contains data that The Observer XT cannot handle, for example when time information in the package is incorrect. Check the setup if many errors occur. - Last Error: The last time an error occurred. Notes - See the FaceReader documentation for details on how FaceReader data are imported into The Observer XT. - Consider entering the name of the test participants in the Independent Variables list instead of defining it as Subject. See Independent Variables. - When you enter a name in the Identify Device As field, this name is added as a subject to the Coding Scheme. When manually scoring events, The Observer XT expects that for each event you first score a subject and then a behavior. Define a subject in the Coding Scheme, then choose Setup > Project Settings > Scoring Options and select Auto-Record Subject. You then only need to score the subject once at the start of the test. --- ## The Observer XT 17 - Set Up Your Project - Observe Live with MediaRecorder URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-observe-live-with-mediarecorder Chapter: The Observer XT Observe Live with MediaRecorder Procedure in Short The detailed procedure is present in the chapter MediaRecorder with The Observer XT in the MediaRecorder Reference Manual. Press F1 in MediaRecorder to open the Reference Manual. In The Observer XT - Choose File > Preferences > N-Linx Settings. - Select Use N-Linx Server to connect with other applications. - In the N-Linx Server address field, enter the computer name of the computer with N-Linx Server. If N-Linx Server is on the same computer as The Observer XT, leave the default entry Localhost. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. If you change the port number, enter the same number in the N-Linx connection settings in MediaRecorder. Also, create exceptions in Windows Firewall for this port on all computers with MediaRecorder, The Observer XT, and N-Linx Server. See the MediaRecorder Help for details. - Click Test Connection. If connection with N-Linx is found, the Status will change to Connected. If not, enter the correct settings and click Test Connection again. - Click OK. - Choose Setup > Project Setup. - Under Observation Source, select Live Observation. The Devices window now opens. If not, click the Devices button. - Select the checkbox in front of MediaRecorder [version number - computer name] and click Edit Settings. This opens MediaRecorder when it is not already open. - Click Edit Settings again. A window with the available MediaRecorder configuration files now opens. Select the configuration file you want to use and click OK. If you do not select a configuration, Current Settings.mrs will be used. - Enter a name in the Identify Device As field. This allows you to control multiple MediaRecorders on different computers with The Observer XT. In MediaRecorder - Choose File > Preferences > N-Linx Settings. - Select Allow Communication with N-Linx Server. - In the N-Linx Server address field, leave the default value Localhost if MediaRecorder runs on the same computer as N-Linx Server. If both programs are on different computers, enter the IP address or computer name of the computer with N-Linx Server. - In the N-Linx Server port field, leave the default port 5672. Ask your system administrator for assistance if this port is used by another program. - When the connection with N-Linx Server is established, the Status will be Connected. Click OK. - If MediaRecorder and The Observer XT run on different computers, select the mapped drive as the location to store the video files. For example, if you mapped the default folder C:\Users\Public Documents\Noldus\MediaRecorder\Video files as X:\, set the default video file location to X:\ and not to the original folder. The original folder is locally on the computer with MediaRecorder and cannot be accessed by The Observer XT. Carry Out Observation When you create a new observation, MediaRecorder opens if it is not already open. When you carry out an observation, MediaRecorder starts video recording. When you stop an observation, video recording stops. The videos are automatically linked to the observation and synchronized with the events. Note: If MediaRecorder is not open, the MediaRecorder line in the Devices window is grayed out and the status is Disabled. MediaRecorder will be started when you create an observation. --- ## The Observer XT 17 - Set Up Your Project - Project Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-project-settings Chapter: The Observer XT Project Settings Choose Setup > Project Settings. The following settings are available: - Coding Scheme Settings - Observation Settings - Time Formats - Scoring Options - Sound Feedback - Playback Control Options Coding Scheme Settings Choose Setup > Project Settings > Coding Scheme Settings. Specify the following options: - Keycodes Are Required – Select this option to code your observations by pressing keys on the keyboard and not with mouse clicks on the screen. - Case-Sensitive Codes Are Allowed – Select this option to distinguish between upper-case (capital letters) and lower-case (small letters) codes. Selecting this option gives the possibility to define more elements, but using capitals will slow down your scoring. - Generate Keycodes Automatically – Select this option if you want the keycodes for your subjects, behaviors, and modifiers to be generated automatically while building your coding scheme. If your project contains Start-Stop behaviors, choose from the Generate Stop Codes list how to generate these automatically: - Same As Start Code – For instance, 'w' for start and stop walking. - Switch Case of Start Code – For instance, 'w' for start walking and 'W' for stop walking. Note that it is only possible to have case-sensitive keycodes if you have the option Case-Sensitive Keycodes Are Allowed selected. - Default Keycode Length – The keycode length for keycodes that are automatically generated. - Check Coding Scheme While Editing – When this option is selected, you get visual feedback when you make a mistake while editing the coding scheme. A warning triangle in the icon in front of the coding element warns you when the element contains an error. When you point with the mouse at an icon with a warning triangle, a description of the coding error pops up. Click the Check Coding Scheme button at the top of the coding scheme screen for more detailed information on the errors. See Check Your Coding Scheme. - Use Pocket Observer With... – When you want to send your coding scheme to Pocket Observer and score data on a Pocket PC, your coding scheme must be compatible with Pocket Observer. See the Pocket Observer Reference Manual for more information. Observation Settings Choose Setup > Project Settings. The Project Settings window appears with the Observation Settings tab open. The following options are available: - Observation Base Name – Type a common name for your observations. The default base name is Observation. The observations will be named 1, 2, etc., unless you give them another name when you start an observation. - Prompt for Confirmation to End Observation – Keep this option selected if you want The Observer XT to ask you whether you really want to end the observation when you stop it. - Edit Independent Variables – Specify whether to enter the values of independent variables before, after, or both before and after the observation. Select Hide 'Manual' Variables if you want The Observer XT not to show variables that are specified as Manual in the Value Update field of the independent variables list. If you select this option and all user-defined variables are defined as Manual, the Independent Variables List is not shown at the start or end of the observation. If at least one of the variables is defined as Optional or Compulsory, the variable list is shown at the start or end of the observation, but the Manual variables are hidden. Time Formats Choose Setup > Project Settings > Time Formats to change the time format. The time format is used in the Event Log window, File Synchronization window, Timers window, Playback Control window, Visualization, and the Analysis Results. - Time Formats – Select the preferred format and decimals. - Project Time Format – Select either Absolute (the actual time during observing) or Relative (the time from the start of the observation). If you select a format with AM or PM notation, it may happen that you do not see this in the event log. This is caused by the settings of Windows for your clock time. To change these settings, click the clock in the lower-right corner of your screen, then click Change Date and Time Settings > Change Date and Time > Change Calendar Settings > Time. After AM Symbol choose AM and after PM Symbol choose PM. - Show Date with Absolute Times – Select this option to include the date in the time stamps. - Show Frame Numbers While Observing from Video – Select this option to display frame numbers in the event log instead of times. Scoring Options Choose Setup > Project Settings > Scoring Options. The following options are available: - Auto Record Subject – Select this to score the same subject for consecutive events. Use this option when you score from video, have multiple subjects, and go through the video for every subject. As soon as you want to enter the event for a different subject, click the cell where the subject was entered automatically, and score the new subject, the behavior, and so on. The new subject is then scored for all subsequent events. - Pause Playback When Scoring an Event – With this option the video pauses when you score the first element of an event. Playback resumes after scoring the last element of the event or pressing Enter to confirm the event line. When you carry out an offline observation with the Instantaneous Sampling method, the media file automatically stops at the moment of sampling. This option is also very useful if you score from audio files and you want to transcribe spoken text into comments. - Always Press Enter to Confirm Event Line – An event can consist of more than one element (Subject, Behavior, Modifier). By default, The Observer XT automatically ends the coding of the event and moves to the next line in the event log when no further elements can be scored for that event. By selecting Press Enter to Confirm Event Line, you can press Enter once you have scored all the elements you require. This way, you can end an event when not all elements have been scored. For example, an event type where the Behavior is linked to a Modifier could be ended by scoring the Behavior and then pressing Enter; the Modifier is then not scored. - Repeated Scoring of Active Behaviors – Suppose an event started at the start of the observation and you score it again at ten seconds without having scored intermediate events. Select one of the options below to specify how both states are recorded: - Allow Repeated Scoring of Active Behaviors – The Observer XT records the end of the first event at T=10s and starts the same behavior at this point, meaning two different states are recorded: one from T=0 to T=10 and one from T=10 to the stop of this event. The frequency of this event would be 2. If the second event is stopped at T=15, the average duration will be 7.5 s. - Ignore Repeated Scoring of Active Behaviors – The Observer XT ignores the second start of the event at T=10s and gives an error message. With the example above, the frequency of the event will be 1 and the average duration 15 s. - Ask Me for Repeated Scoring of Active Behaviors – Select this option if you want The Observer XT to ask you what you want to do, whether to allow or to ignore the recurring start. --- ## The Observer XT 17 - Set Up Your Project - Set Up Your Project URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-set-up-your-project Chapter: The Observer XT Set Up Your Project Main Topics - Get Started - Create Coding Scheme - Independent Variables - Project Settings - Other Project Setup Options - External Programs Get Started - Start The Observer XT - Create a New Project - Define Project Setup - Define Project Settings - Create Coding Scheme - Create Independent Variables Start The Observer XT Aim To start working with The Observer XT. Procedure The procedure depends on your license type. You may either have: - A software license key - One or more hardware keys Activate The Observer XT With a Software License Key - Start The Observer XT and select Activate Software License Key and click OK. - Select either Floating or Fixed and click OK. - Enter the Activation key that you received with the software. If you selected Fixed you can choose between: - Activate Online if the PC is connected to the internet. When you click OK the Observer software opens. - Activate Offline if the PC does not have an internet connection. Scan the QR code with your smartphone and click WEB. Copy the Computer key shown on your smartphone to the Computer key field on the Observer PC and click OK. The Observer software opens. What Is the Difference Between a Floating and a Fixed Activation? When you have a software license key you can choose between a Floating and a Fixed activation. - Floating Activation — Choose this option if you want to be flexible on which computer you use The Observer XT. If you bought, for instance, a software key with two licenses, you can simultaneously use the software on the Observer XT computer in your lab and on the computer in your office. You can install and activate The Observer XT on as many computers as you want, but with two licenses you can use the software only on two PCs at a time. If you want to use The Observer XT on a third PC, the software should not be running on one of the other two PCs. Please note that a computer must have an internet connection to activate and work with a floating license. - Fixed Activation — A Fixed activation is linked to one computer. The advantage of a Fixed activation is that you do not need an internet connection to work with the software. If you bought a software key with two activations, you can activate The Observer on two computers. If you want to use The Observer XT on a third computer, you have to deactivate one of the licenses and activate it on the third computer. Please note that a computer must have an internet connection to activate or deactivate a Fixed license. After you have activated the license you can use The Observer XT without internet. Instead of activating both licenses as Fixed licenses, you can also choose to activate one as Fixed and the other as Floating. Hardware Key - Insert the hardware key into a USB port of the computer with The Observer XT. If it is correctly connected, a red light glows inside it. - Start The Observer XT. Keep the key inserted in your computer while you work with The Observer XT. If you forgot to connect the hardware key, a window opens stating that no hardware key was found. Insert the key and choose Check Hardware Key Again. - Continue with Create a New Project. Create a New Project A project is a container with all your observations, video files, and analyses. Choose File > New Project. Give the project a name, select where to store the project, and click OK. Continue with Define Project Setup. Note: You cannot use the characters \ / : ; * ? " < > | in a filename. --- ## The Observer XT 17 - Set Up Your Project - Sound Feedback URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-sound-feedback Chapter: The Observer XT Sound Feedback Choose Setup > Project Settings > Sound Feedback. Select one of the options for Sound Feedback: - None – No sound feedback. - After Each Key Press – A sound at each key press. - After Each Input Element (default) – A sound after each element (Subject, Behavior, etc.) was entered. - After Each Input Event – A sound after the event has been completely coded. Sound Selection If you selected to play sounds, select what to play under Sound Selection. Select Use Coding Scheme Sounds (for Elements Only) to play the sounds specified in the coding scheme (Subjects, Behaviors, or Modifiers). This option only applies when you have selected a sound feedback After Each Input Event. Playback Control Options Choose Setup > Project Settings > Playback Control Options. Slider Range Choose the segment of time you want to have displayed by the playback slider: - All Streams – The segment between A and B represents the time between the start of the earliest event/external/media file and the end of the latest event/external/media file. - Observation – The segment between A and B represents the time interval that data was scored in, no matter how long the other data/media file streams are. Note: The selection above affects the behavior of the Jump to Begin or Jump to End buttons. For example, if the event log starts 60 seconds later than the first video frame, and you select Observation as Slider Range, clicking Jump to Begin will position the slider cursor to the start of the observation (at 60 seconds in the video), not at the start of the video. If you select All Streams, the same action positions the slider cursor to the start of the earliest of all streams, that is the start of the video. Select Playback Control Buttons By default some buttons are hidden in the Playback Control window. You can select or deselect buttons that you do not need while scoring. See The Playback Control Window for more information on the buttons and Playback Control Options for the buttons that can be hidden. Loop Options To replay a video fragment for accurate scoring or demonstration purposes: - Loop Interval – By default the option User Defined is selected. With this option selected, you either loop the entire video or set an interval manually. If you select Fixed Interval, a loop of a fixed length is created. See The Playback Control Window. - Interval Length – This option is enabled if you select Fixed Interval in the Loop Interval list. Set the length of the loop. Quick Review With the Quick Review function (see The Playback Control Window) you can automatically rewind to a certain point and play the media file at a certain speed. Customize your Quick Review function with the following options: - Pause Playback After Quick Review – Select this checkbox if you want the video to pause after the video fragment is played back. - Quick Review Interval – Enter the number of seconds you want the video to be rewound before reviewing. - Quick Review Speed – Select the speed at which the media file is played back. Note that not all speeds are available with certain video formats. Other Project Setup Options Apart from the options described in Define Project Setup, the following options are available: - Control External Devices or Programs During a Live Observation - Specify the Duration of the Observation - Enter Project Information - Lock the Project Setup Control External Devices or Programs During a Live Observation You can control external devices or programs when you carry out a live observation with The Observer XT. For example, start a Data Acquisition System (DAQ) system or video recording with MediaRecorder when you start an observation. This ensures synchronization of data streams. To Select External Devices - Choose Setup > Project Setup > Live Observation under Observation Source. The Devices window opens. If not, click the Devices button under Live Observation. You have the following options: - DAQ Settings (available with the External Data Module) – Select this option to co-acquire external (physiological) data during your observations. See External Data for details. - Automatic Linking of Video Files – To associate videos that were recorded with, for example, an eye tracker, to an observation. Instruct the program how to locate the video files (see Automatic Linking of Digital Media Files). If you control MediaRecorder 4 or higher with The Observer XT, the videos are automatically linked to the observation, so do not select this option. - Other Options – Depending on what devices or programs are connected, more options may be available, such as MediaRecorder, FaceReader, uASQ, or E-Prime. You can also create settings to control a program with command lines. See External Programs and the manual of those programs for details. If you change the Observation method from live to offline between observations, you can no longer see the devices set for the live observations. To view them, right-click the observation in the Project Explorer, select Properties, and go to the Devices tab. --- ## The Observer XT 17 - Set Up Your Project - Specify the Duration of the Observation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-specify-the-duration-of-the-observation Chapter: The Observer XT Specify the Duration of the Observation Select one of the following options: - Open Ended Observation – The observation ends when you stop it manually, or when the end of the video file has been reached. Select one of the other options if you want the observation to stop automatically after a predefined time. - Duration Based on Elapsed Time – The observation stops after a predefined time. Enter the time in the Observation Duration field that appears. - Duration Based on Observed Time – The observation stops after a predefined time, excluding the time the observation was suspended (see Suspend an Observation). Enter the time in the Observation Duration field that appears. If you observe from pre-recorded video, there is no difference between the elapsed and observed time. There is only a difference when you observe live and at some point you suspend the observation. - Duration Based on Sample Intervals – This option is only available when you chose Instantaneous Sampling, or Combine Continuous and Instantaneous Sampling as observation method. Enter the Sample Interval Length and the Number of Sample Intervals in the fields that appear. The Observation Duration is calculated automatically based on the combination of Number of Sample Intervals and Sample Interval Length. The first sample is taken at 0 seconds, and there is no sample at the stop of the observation. Therefore, the duration of the observation is actually one sample interval shorter than the displayed Observation Duration. For example, if you set the Sample Interval Length to 60 seconds and the Number of Sample Intervals to 10, the Observation Duration is automatically set to 600 seconds. However, since the first sample is at 0 seconds, the last sample is at 540 seconds. There is no sample at the exact stop time of the observation. Enter Project Information Under Project Information, you can enter important information about your project. The following project information is available: - Date Created – The date and time when the project was created. This field cannot be edited. - Location – The location where your project is stored on your computer. For the default location, see File Locations in File Management. To change the default location of future projects, see File Locations in Installation. - Description – Enter information about your project such as location, date or time of year of the study, observers, the scientific research question that you aim to answer with this study, etc. You can edit the description at any time. You can enter a maximum of 2047 ASCII characters. Template Information If your project is based on a template, the Project Setup window also contains Template Information with the Name, Date Created, and additional information. The template information cannot be edited. See also: Create a New Project from a Template in File Management. Lock the Project Setup To prevent changes to the setup, lock your setup. Choose Setup > Lock Configuration. In a locked configuration the following items cannot be edited: - Observation Source – You cannot change the observation source from Offline Observation to Live Observation or vice versa. However, if the observation source is live, you can select new devices, deselect devices, edit settings for the devices, or add new external programs. See External Programs for more information about selecting devices for live observation. - Observation Method - Observation Duration – See Specify the Duration of the Observation. - Sample Interval Length - Project Information – See Enter Project Information. - Coding Scheme – See Create Coding Scheme. - Independent Variables – You cannot define new independent variables or change the properties of existing variables. Entering and editing independent variable values is possible. If you observe offline, you can add new video files. When you save your project as a template project, the project setup in the new project created with the template is locked. To Unlock the Project Setup To unlock the project setup, choose Setup > Unlock Configuration. External Programs Use External Programs to control external programs with The Observer XT. Examples - Example 1 – Start video recording with MediaRecorder when you start an observation and stop recording when the observation ends. See Observe Live and Record Video with MediaRecorder. - Example 2 – Start and stop facial expression analysis with FaceReader together with an observation. See Observe Live and Analyze with FaceReader. - Example 3 – Start and stop an eye tracker that cannot be controlled with N-Linx together with an observation. See Add a Custom External Device. Observe Live and Record Video with MediaRecorder Configuring this integration provides the following behavior: - When you create a new observation, MediaRecorder starts and loads a camera configuration. - When you start an observation, MediaRecorder starts recording. - When you stop an observation, MediaRecorder stops recording. - The recorded videos are automatically linked to the observation. - The recorded videos are automatically synchronized with the events. Prerequisites - You have MediaRecorder 4 or higher. For earlier versions of MediaRecorder, the procedure may be different; consult the documentation of that version. - The Observer XT, MediaRecorder, and N-Linx Server are installed on computers that are in the same network. - On the computer with MediaRecorder, you installed N-Linx Agent and selected Noldus MediaRecorder in the installation window. - In N-Linx Agent, you entered the computer name or IP address of the computer with N-Linx Server. - In MediaRecorder, you selected Allow Communication with N-Linx as N-Linx Settings and entered the computer name or IP address and the port of the computer with N-Linx Server. - If MediaRecorder, N-Linx Server, and The Observer XT do not all run on the same computer, you created exceptions in Windows Firewall for the default port 5672 on all computers. If you chose another port, you created exceptions in Windows Firewall for that port. - If MediaRecorder and The Observer XT run on different computers, you made sure that the computer with The Observer XT can access the MediaRecorder video files. --- ## The Observer XT 17 - Set Up Your Project - Subjects URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-subjects Chapter: The Observer XT Subjects What Are Subjects? When you are observing more than one individual at a time, you normally not only want to record what somebody is doing, but also who that somebody is. These individuals are referred to as subjects. Subjects are usually the roles of the individuals, like child and mother, a doctor and a patient, or alpha male and subdominant male. Subjects can be individual animals or humans, but also, for instance, hands (on a keyboard), muscles in the face, or shoals of fish. It is not compulsory to specify subjects. If you observe only one person or animal in each observation, do not define subjects. Examples of Subjects - Mother-child interaction – Mother and Child. - Social interaction in a short-term study of a group of animals – Alpha Male, Sub-dominant Male, Female. - Imitation in twins – Twin A, Twin B, Parent. - School environment – Teacher, Pupil 1, Pupil 2. - Test participant, where one person is observed in each test session – No subject needed. Notes - If you want to specify the name or other properties of each subject, create Independent Variables with scope Subject and enter the properties as values. - If you observe only one subject in each observation, do not define subjects. Specify the actual names or identities of the subjects as Independent Variables. Define Subjects Define the roles in your study. Prerequisites - Your Coding Scheme is open. If not, choose Setup > Open Coding Scheme. - The Subjects pane is visible. If not, choose View Settings > Subjects. - Your study includes more than one person or animal in each observation. Procedure - Click the Add Subject button. - Enter the subject name. Notes - A Subject group is created for each Observation method you have selected. The Subjects pane displays a subject group for continuous sampling and instantaneous sampling. By default, the continuous sampling subject group contains no subject, whereas the instantaneous sampling subject group contains one subject. - The instantaneous sampling group also initially contains an error: "Missing Combinations." When you first open the coding scheme window, no behavior groups have yet been defined. However, a subject should be linked to a behavior group to score for that subject. Define Subject Properties Specify details for the subject by opening the Subject Properties pane. Click the subject name and then the Properties button at the bottom of the Subjects pane. Enter the following details: - Description – Optionally add a description to your subject in the Description field (maximum 1024 ASCII characters). This is particularly useful if two or more people are using the same coding scheme and need to know who the various subjects are. - Start Code – The code to score the subject. With the option Generate Keycodes Automatically, the key code is automatically assigned to the subject. Optionally, change it. - Sound – Optionally browse to a sound (*.wav file) you want to hear when you score that subject. To play the sounds, you must select the Use Coding Scheme Sounds (for elements only) check box in the Sound Feedback tab of the Project Settings. - Observation Method – Shows which subject group (Continuous Sampling or Instantaneous Sampling) a subject is assigned to. If you use both continuous and instantaneous sampling, you can change the group a subject is assigned to. The instantaneous subject group must contain at least one subject. - Add Comment – To enter a comment every time you score that subject. - Inactive – To make the subject inactive when you do not want to use it anymore. - Subject-Behavior Combinations – To specify which behavior to score for which subject. Examples include: - Mother-child interaction study – You are observing a mother and her two-year-old child and decide to score Play behavior of the child only. You define a Play behavior group and assign it to the subject Child, not Mother. - Primate study – You are observing a group of primates and decide to follow two of them as focal subjects (a mother and her baby). You have defined four behavior groups: Individual Behavior, Social Behavior, Location, and Distance to Mother. For the focal subject Baby, you record behaviors of all four groups. For the subject Mother, you only record Individual Behavior and Social Behavior, resulting in a total of 6 combinations. Notes - Many properties can be shown as columns in the Subjects pane but are hidden by default. To show these columns, right-click one of the headers and select Show All Columns. To hide a column, right-click that column's header and select Hide Column. To choose a subset of columns, right-click a header, select Show Column, and make your selection. - If you delete a Subject-Behavior Combination and you have already scored data for that combination, the observation will contain errors. Restore the combination, remove the events with errors, or re-score them using valid combinations. --- ## The Observer XT 17 - Set Up Your Project - Variable Scope URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-set-up-your-project-variable-scope Chapter: The Observer XT Variable Scope The scope of a variable is the portion of the observation for which the variable has a specific value. Choose between the following: - Observation – A variable has scope Observation if it has the same value during the entire observation. Typical examples of variables with scope Observation are the name of the observer, or the temperature in the observation room. Also, if you observe only one subject per observation, and therefore did not define subjects in your Coding Scheme, variables like Age or Gender of the subject will have scope Observation. The scope of a video or audio file and of external data files is always Observation. - Event Log – In general there will be no difference between scope Observation and scope Event Log, because each observation contains only one event log. An observation can only have multiple event logs if you imported data as event logs into an observation. This happens, for example, if you import FaceReader facial states into an observation. In this case you can set the scope of a user-defined variable to Event Log if it has different values per event log. - Subject – This option is only available if you defined Subjects in your coding scheme. If your observation contains multiple subjects and the user-defined variable has different values per subject, select scope Subject. Typical examples of user-defined variables with scope Subject are Age, Gender, and Identity of your subjects. Notes - If you plan to create groups of observations for analysis, set the scope to either Observation or Subject, not Event Log. See Create Groups of Data in Select Data for Analysis. - You can change the scope of a variable at any time. If you do, the variable column shows the first values previously stored for each observation. Enter the variable values according to the new scope. Value Update Dependent on your preferences, you are asked to enter Independent Variables before, after, or before and after you carried out an observation. Choose in the Value Update field whether entering variable values is: - Compulsory – You must enter a value to proceed. - Manual – If you specified to Hide manual variables in the Project Settings (see Edit Independent Variables), Manual variables are not shown when you are asked to enter the independent variables. Open the independent variable list to update the values. - Optional – You do not need to enter a value. To Enter Variable Values - Define in the Observation settings (Setup > Project Settings) whether to enter the independent variables before the start of an observation, after the end of an observation, or both. - Enter the user-defined variable values in the window that opens when you start or end an observation. It is also possible to enter the values in the independent variables list. You can also copy and paste values from, for example, Excel. However, if you predefined a range, the values should fall within that range. Manage Independent Variables Show/Hide Variables You can select which columns to display in the Independent Variables list. - To show columns, right-click a column header and select Show Independent Variables. - To hide one column, right-click in one of the variable fields and choose Hide Independent Variable. Export Independent Variables To export the independent variables and their values, choose File > Export > Independent Variables. See Export Independent Variables in File Management. Edit Predefined Values To replace or delete predefined values, delete first all the values from the variable column, then delete the values. To remove variables, right-click the column header and choose Delete Independent Variable. Print the Independent Variables List In the current version of The Observer XT, printing is not fully supported. To print the independent variable list, copy and paste the columns into another program such as Excel. If you copy the columns to Microsoft Word, you can use the Convert Text to Table function. --- ## The Observer XT 17 - Software Development Kits URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-software-development-kits Chapter: The Observer XT Software Development Kits What Is a Software Development Kit? A Software Development Kit (SDK) is a set of development tools that allows software engineers to create applications for use in combination with The Observer XT. The Observer XT has the following SDKs: - The Observer XT SDK - N-Linx SDK To obtain an SDK, please contact support@noldus.nl. Please note that support on the SDK, including help with making them, is only available to customers with a service contract. The Observer XT SDK The Observer XT SDK is a set of development tools that allows software engineers to create applications for use in combination with The Observer XT. The Observer XT SDK includes a debugging aid, an example tool plus C++ sample source code and supporting technical documentation. The Observer XT has a default folder for plug-ins: C:\Program Files (x86)\Common Files\Noldus\Plugins. However it depends on the requirements of the plug-in where they must be stored. Plug-ins can only work with The Observer XT if they have been written with specific methods. These methods are described in The Observer XT Software Development Kit (SDK). The SDK includes the following applications: - External Application Control - Observational Data XML (ODX) - Automatic Synchronization - Plug-in Viewer COM-Object - Event Data Plug-in - External Data Plug-in External Application Control The Observer XT can execute other (external) applications during the user actions New Observation, Start Observation, Stop Observation, and Close Observation. The Observer XT can execute a command with optional parameters, a batch file or Visual Basic scripting. The SDK contains documentation with background information, examples of how to execute applications and a summary of batch file processing. The SDK also contains three pre-programmed command files. Observational Data XML (ODX) The SDK explains how to create an ODX file that can be imported into The Observer XT. An ODX file is an Observational Data file in XML format. With the SDK you can create your own ODX file to exchange information between your own application and The Observer XT. The SDK contains documentation describing the contents and format of an ODX file. The SDK also contains an ODX file from The Observer XT, XSD schema definition files for an ODX file and a C++ header file with all tag names used in ODX files. Automatic Synchronization The Observer XT uses a serial binary data exchange mechanism for automatic synchronization of observational and external data. Two types of Sync Out signals are available to achieve this automatic synchronization. The SDK describes in detail the mechanism for automatic synchronization and the Sync Out signals. It enables you to decode the Sync Out signal and to use it with your own application. The SDK contains a document describing the synchronization method, the Sync Out signals and a sample synchronization data file. Plug-in Viewer COM-Object With the SDK you can create a custom viewer in The Observer XT. To create a custom Observer XT viewer plug-in it must be a COM (Component Object Model) object according to the specifications described in the SDK document. Such a viewer can be used, for instance, to visualize the movement of a shoulder prosthesis, while simultaneously viewing a video of the patient and physiological data. For this plug-in your The Observer XT license must include the Media Module. The SDK contains documentation describing how the Plug-in Viewer COM-Object works and how to work with plug-ins in The Observer XT. To open viewer plug-in data while observing: - Create an observation or open an existing one. - Choose File > Import > Plug-in Data. - Select a plug-in from the list, choose an observation and click OK. - If the plug-in requires a file to be opened, a new window opens: select a file and click Open. - Start the observation and score or review the data as you usually do. To open plug-in data while visualizing data: - Choose Analyze > Visualize Data. - Choose File > Import > Viewer Plug-in Data. - Select a plug-in from the list, choose an observation and click OK. - If the plug-in requires a file to be opened, a window opens: select a file and click Open. Similarly you can open plug-in data in an Episode Selection. See Episode Selection for more information. Event Data Plug-in This plug-in offers the possibility to obtain event data from an external program while you carry out a live observation in The Observer XT. The external events are imported during your observation in The Observer XT. In The Observer XT, these event data are stored in a separate Event Log. You can visualize and analyze the event data like any other event data in The Observer XT. External Data Plug-in This plug-in offers the possibility to obtain external data while you carry out a live observation in The Observer XT. The external data are imported during your observation in The Observer XT. In The Observer XT, these external data are stored in the External Data Files folder of the observation. You can visualize and analyze the external data together with event data in The Observer XT. N-Linx SDK The N-Linx SDK allows you to control external applications with The Observer XT and import their data into the observation. The SDK makes use of the Noldus network communication protocol N-Linx. The SDK contains a protocol to start and stop an external application when you start and stop an observation in The Observer XT, and it contains a protocol for real-time import of data obtained by the external application into The Observer XT. N-Linx Start Stop Protocol This protocol offers the possibility to start and stop an external program while you carry out an observation in The Observer XT. This enables synchronization of external and event data. The SDK contains documentation with background information and examples to set up communication. N-Linx Event and Continuous Data Import Protocol This protocol offers the possibility to obtain events and continuous data from an external program while you carry out a live observation in The Observer XT. The external events are imported during your observation in The Observer XT. In The Observer XT, these event data are stored in a separate Event Log. You can visualize and analyze the event data like any other event data in The Observer XT. The SDK contains documentation with background information and examples to set up communication. Source: The Observer XT 17 Help - Software Development Kits, Noldus Information Technology --- ## The Observer XT 17 - Software License Key (SBLK) Activation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-software-license-key-sblk-activation Chapter: The Observer XT Software Based License Overview Software based licenses can be activated as either Fixed or Floating. The Observer XT licenses can have a variety of modules (Video Analysis, Advanced Analysis, Coder Only, etc.). Some licenses in the lab might only contain the Advanced Analysis module while other licenses could have all the modules. When the modules vary from license to license this results in a new activation key for each module variation. For example, to save costs you might have 1 full license and 1 coder only license. In this scenario, you will be sent 2 Activation Keys. When you have multiple licenses with the same modules, these can all reside under the same Activation Key, which has multiple Seats. You can fix or float any Software Based License, regardless of how many Activation Keys or Seats you have. Activation Activating as Fixed PC Has Internet - Download and install The Observer XT 17. - Launch The Observer XT 17. - Select Activate software license key. - Select Fixed - On this computer only. - Choose the Activate online option. - Enter the Activation Key. - You are now ready to use The Observer XT 17. The PC can be online or offline during use of The Observer XT 17. PC Has No Internet - Download and install The Observer XT 17. - Launch The Observer XT 17. - Select Activate software license key. - Select Fixed - On this computer only. - Choose the Activate offline option and enter the Activation Key. - Scan the QR code using the camera of your smartphone to get a Computer Key. - Under Activate Offline, enter the Computer Key. - You are now ready to use The Observer XT 17. The PC can be online or offline during use of The Observer XT 17. Activating as Floating PC Requires Internet - Download and install The Observer XT 17. - Launch The Observer XT 17. - Select Activate software license key. - Select Floating - On multiple computers. - Enter the Activation Key. - You are now ready to use The Observer XT 17. The PC must be online during use of The Observer XT 17. License Management Permissions When activated as a Fixed license via the internet (online), it will check the license server for permission, after which it will lock the license to that specific PC for use for 90 days. After 90 days, the license checks the server for permission again. When activated as a Fixed license without an internet connection (offline), it will check the license server for permission, after which it will lock the license to that specific PC for use for 365 days. After 365 days, the license will require a reactivation to confirm permission for another year of use. When activated as a Floating license, permission is shared. Internet access is required each time a PC wants to utilize the full version of the software (i.e., acquire data), as it uses the internet to check for license permission. Access to the Key/Seat will be on a first come, first served basis. You can switch between Fixed and Floating activations by deactivating via Help > Deactivate License. When a license is deactivated, it is immediately available to fix or float on another PC. Fixed License A Fixed license is used on a single computer. An internet connection is required during activation but not during use of The Observer XT 17. Once a license is activated as Fixed it takes up a Seat permanently. If you receive an error indicating the license is already fixed on another PC, you must deactivate it on that PC first before activating it here. Floating License A Floating license (with 1 or more Seats) can be accessed on multiple computers. A permanent internet connection is required. You can install The Observer XT 17 on as many PCs as you would like, but only the number of Seats purchased can be used simultaneously at any given time. Users must close The Observer XT 17 after use. This will free up a Seat so another user can use the software on another computer. You do not need to deactivate after use; simply closing The Observer XT 17 will free up the Seat. The following practices are recommended for managing a Floating license: - Use a shared online calendar, spreadsheet, or schedule to keep track of who is using The Observer XT 17 and when. This way you know who last used it, should you need to ask them to close The Observer XT 17 to free up the Seat. - Keep a list of all PC names (company and private) which have The Observer XT 17 installed. - For each Activation Key, note whether it is set to Fixed or Floating. If you have trouble accessing the license due to a strict local network, ask your IT department to add an exception for: https://qlmlicenses.noldus.com:9999 Support If you run into any issues, please submit a support ticket on the MyNoldus client portal. Source: The Observer XT 17 - Software License Key (SBLK) Activation --- ## The Observer XT 17 - SyncBox - Determining The Difference In Offset URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-syncbox-determining-the-difference-in-offset Chapter: The Observer XT Determining The Difference In Offset After you have imported all data (such as physiological data or a video file) into the corresponding observation in The Observer XT, you can determine the difference in offset by carrying out manual synchronization. When You Used One Trigger Pulse Through manual synchronization you make sure that the time-stamped trigger comment logged in the event log file in The Observer XT coincides with the corresponding signal recorded in a video file, an audio file, or a physiological data file. After you have carried out manual synchronization, you can see the difference in offset in the File Synchronization window in The Observer XT. Next time you carry out an observation, you need to enter this difference in offset as the delay for starting up an observation for this specific application in the Add External Programs window in The Observer XT. As a result, the start of the observation and the start of the external application are now synchronous. When You Used A Series Of Trigger Pulses When you used a series of trigger pulses in the case of a long observation, you first determine the delay in starting up the external application by using a pulse at the start of the observation. Next, you use the pulse at the end of the observation to determine how far the observational and external data have started running out of sync. Upon re-import of the external data you can stretch the external data to match the duration of the observation by changing the end time of the external data file. Determining The Difference In Offset Between An Event Log File And A Video File The procedure below assumes that the video file has already been imported into the corresponding observation. - Open the observation. - In the Event log, click on the row with a trigger comment. - Click the Offset button on the toolbar. - Select Manual offset, read the instructions in the Synchronize window, and click the Start Synchronization button. - Click in the Video window. The video window turns red. - Use the Playback Control to go forward or backward to find the onset of the corresponding visual or auditory signal in the video, or the keycode signal recorded in the screen capture. Note: If you have The Observer XT 11.5 or higher and MediaRecorder 2.5 or higher and you start video recording with commands from The Observer XT, you do not have to determine the offset between the observation and the video. The Observer XT does that for you and synchronizes event log data and video automatically. - Click the Offset button again to confirm the offset. - To view the offset, click the Offset button again and select Numerical Offset. The File Synchronization window displays the offset for the video file relative to the event log file. - In the Project Setup, click Devices, then locate the video recording program item. Enter the offset value (converted to ms) in the fields ms before Start Observation and ms before Stop Observation in the Add External Program window. Determining The Difference In Offset Between An Event Log File And A Physiological Data File - Open the observation containing the physiological data. - In the Event log, click on the row with the trigger comment. - Click the Offset button on the tool bar. - Select Manual offset, read the instructions in the Synchronize window, and click the Start Synchronization button. - Click in the External Data and Audio window that displays the physiological data. The border of the External Data and Audio window turns red. - In the External Data and Audio window, click on the graph and drag the graph so the peak created by the TTL pulse coincides with the vertical hairline, which indicates the corresponding position of the trigger comment in the Event Log file. - Click the Offset button again to confirm the offset. The event log and the external data file are now synchronized. - To view the offset, click the Offset button again and select Numerical Offset. The File Synchronization window displays the difference in offset for the file. - Do one of the following: - When you used one trigger pulse — This is the value you need to enter in the fields ms before Start Observation and ms before Stop Observation in the Add External Program window next time you carry out an observation. - When you used a series of trigger pulses — After you have determined the offset difference at the start and end of the observation, you need to re-import the physiological data file and, upon import, change the Start and Stop time of the physiological data set. In the Import External Data window you can change the Start and Stop time by double-clicking the corresponding cell. Source: The Observer XT 17 - SyncBox Technical Note, Noldus Information Technology --- ## The Observer XT 17 - SyncBox - SyncBox and The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-syncbox-syncbox-and-the-observer-xt Chapter: The Observer XT SyncBox and The Observer XT --- ## The Observer XT 17 - SyncBox - The SyncBox URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-syncbox-the-syncbox Chapter: The Observer XT The SyncBox Introduction When you use The Observer XT as part of a complex lab setup, it is necessary that the observational data from The Observer XT and external data from other applications/devices play back as synchronized as possible. Such a complex setup might consist of (depending on your type of research): - The Observer XT — to record a participant's behavior. - One or more cameras and the MediaRecorder software — to create one or more digital video files. - An eye tracking system — to monitor the point of gaze of a test subject when testing a website or software. - One or more data acquisition systems — to measure, for example, heart rate or galvanic skin response. Synchronize the Data Sets One way to achieve simultaneous playback of observational and external data is to start external applications from within The Observer XT as External Programs at the start of an observation. However, most applications take some time to start which results in a delay between the start of the observation in The Observer XT and the start of the external application. Use the SyncBox to Determine the Delay The SyncBox is a device that has been developed to determine this delay. Once you know the delay for a specific external application, you can set this in The Observer XT, so the start of the observation and the start of the external application are synchronous. In general, you can determine the difference in offset between The Observer XT and external applications/devices by using one of the following methods: - At the start of an observation in The Observer XT, record one signal in all applications/devices and a synchronous time stamped trigger comment in The Observer XT — for example, record a visual and/or auditory cue for video or a pulse in the physiological data signal. Afterwards, the difference in offset between The Observer XT and other applications/devices can be determined and set in The Observer XT. - Record a series of signals in all applications/devices at fixed intervals during an observation and a synchronous time stamped trigger comment in The Observer XT — this might be necessary for long observations when you expect the different computer clocks to start running asynchronously. Afterwards, you can determine the difference in offset between The Observer XT and the other applications/devices at the start and end of the observation and correspondingly stretch the external data. You can only stretch external ASCII data, not video data. Note: If you have MediaRecorder 2.5 or higher, and start video recording together with a live observation in The Observer XT, you do not need to measure the delay between The Observer XT and MediaRecorder video. In this case The Observer XT takes care of correcting for this delay when importing the video files. For more information, see The Observer XT Help and the MediaRecorder Help. How the SyncBox Works The SyncBox is triggered by The Observer XT to send out different types of signals at exactly the same time to one or more external applications, based on the clock of The Observer XT computer. Simultaneously, a time stamped trigger comment is recorded in The Observer XT. After import of the different data streams into The Observer XT, you can use the trigger comment and the recorded signals to manually synchronize the observational and external data. By doing this, you can determine the difference in offset and set this in The Observer XT as a delay. Subsequently, an observation and external applications will start synchronously. Furthermore, when you trigger the SyncBox to send out a series of signals during a longer period of time, you can use these multiple trigger events to correct for your (long) observation and the external applications/devices running out of sync. Note: Use the SyncBox before you actually start acquiring data. Create a SyncBox project in The Observer XT, carry out a test observation while The Observer XT triggers the SyncBox to send out its signals and determine the difference in offset between the trigger comment(s) in the observation and the external applications/devices. These differences in offset can then be used in the real observation to correct these offset differences. Components of the SyncBox The SyncBox system consists of the following components: - SyncBox — Contains a Power in, a COM in, X-keys out (2x), LED out (4x), Sound out (4x), TTL direct out (6x), TTL opto-isolated out (2x), a Trigger button, an Auto off/on switch, and a Speaker off/on switch. - Power supply (2x) — You can either use the 5V VDC medical power supply or the USB-to-5V supply cable to get power from a PC. - COM cable — To connect the COM port of the SyncBox to the COM port of the The Observer XT PC (or the USB-to-COM converter). - LED box — A box with a red and infrared light connected to a cable (length: 5 m) with a white RCA plug at the end. - Sound box — A box with a small speaker connected to a cable (length: 5 m) with a red RCA plug at the end. - Line-in cable — A cable with an RCA plug on one end and a stereo 3.5 mm phone plug on the other end. This cable connects a Sound output of the SyncBox with the line-in of a PC or amplifier. - TTL cable — A cable (length: 5 m) with a 3.5 mm phone plug on one end. The white minus wire and brown plus wire can be connected to a plug suitable for your data acquisition system (for example, a phone plug or RJ-11 jack). - X-keys USB cable — A USB-A-B cable that connects the X-keys outputs to a USB port on a test PC. How to Install the SyncBox The SyncBox gets its power (5 VDC) from the provided power supply or from the USB port of a computer via the supplied USB-to-5V cable. All signals are functional once you plug in the power supply. Using the SyncBox Signals The SyncBox can send out the signals described below. Which signal you use depends on the application or device you send the signal to. The LED Signal A LED signal is a light signal. There are 4 LED signal outputs and one LED light on the SyncBox itself. The LED signal is sent via an RCA connector to a LED box with a red and infrared LED light. Connect the RCA connector of the LED box to one of the LED signal outputs. Use the LED signal when you use a camera; record the LED signal as a visual cue in a video recording. The Sound Signal The Sound signal is an audio signal (audio frequency: 2.3 KHz). There are 4 Sound signal outputs. The Sound signal is sent via an RCA connector to a Sound box with a speaker. Alternatively, the sound signal can be sent to the Line-in of a PC or other equipment. You can also hear the Sound signal through the internal loudspeaker on the SyncBox when the Speaker switch is set to On. Connect the RCA connector of the Sound box to one of the Sound signal outputs, or connect the RCA connector of the Line-in cable to one of the Sound outputs. Use the Sound signal when you use audio equipment; record the Sound signal as an auditory signal in an audio file. Note: When you use a microphone to record the Sound signal, make sure you place the Sound box as close to the microphone as possible so the sound travels the shortest distance possible. The TTL Direct Pulse The TTL direct pulse is an electrical signal (Max. DC levels: less than +1 Volt and greater than +3 Volts). There are 6 TTL direct pulse outputs. The TTL direct pulse is sent via a TRS connector (or phone plug/jack plug) to a DC input on a data acquisition system. Connect the 3.5 mm phone plug of the TTL cable to one of the TTL direct pulse outputs. The type of connector that you need to attach to the other end of the cable depends on the type of input on your data acquisition system. Use the TTL direct pulse signal when you use a data acquisition system; record the signal as a marker in the data file. Note: We recommend using the synchronization signal when acquiring physiological data, rather than the TTL pulse. The synchronization signal enables you to automatically synchronize your observational and physiological data. See The Observer XT Help for information on how to use this signal. Use the TTL direct pulse in case the sensors on your subject are wirelessly connected to the data acquisition system. The TTL Opto-Isolated Pulse The TTL opto-isolated pulse is an electrical signal. There are 2 TTL opto-isolated outputs. This TTL pulse signal is optically isolated from the SyncBox electronics and all connected devices. Connect the 3.5 mm phone plug of the TTL cable to one of the TTL opto-isolated pulse outputs. The type of connector that you need to attach to the other end of the cable depends on the type of input on your data acquisition system. Use the TTL opto-isolated pulse signal when you use a DAQ system; record the signal as a marker in the physiological data file. Note: We recommend using the synchronization signal when acquiring physiological data, rather than the TTL pulse. The synchronization signal enables you to automatically synchronize your observational and physiological data. See The Observer XT Help for information on how to use this signal. Use the TTL opto-isolated pulse in case the sensors on your subject are connected through wires to the DAQ system. The opto-isolated pulse prevents a high voltage from being applied to a subject attached to the data acquisition system, in the unlikely case that the SyncBox might malfunction. The Keycode Signal The keycode signal sends out a pre-programmed keyboard key. There are 2 keycode signal outputs (via the X-keys device). The X-keys device is a keyboard simulator that can send out any keystroke. The X-keys device in the SyncBox sends out a "t". Please contact support@noldus.nl when you want the SyncBox to send out a character other than "t". Connect the X-keys USB cable between one of the X-keys outputs and a USB port on the PC you want to send the signal to. A green light above the output indicates that the port is active. Use the Keycode signal when you use an application that records keystrokes or captures the screen of the test computer: - Screen capture software — Use the Keycode signal to record a "t" in Notepad. While the software captures the screen, simply open Notepad and the character "t" appears in the screen capture when the SyncBox sends the Keycode signal. - Eye tracking system — Use the Keycode signal to record a "t" in Notepad. While the eye tracking system captures the screen, simply open Notepad and the character "t" appears in the screen capture when the SyncBox sends the Keycode signal. --- ## The Observer XT 17 - SyncBox - Working With The SyncBox URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-syncbox-working-with-the-syncbox-KDa Chapter: The Observer XT Working With The SyncBox Setting Up Synchronization - Set up all the necessary connections and make sure you are able to record the signals. For example, the LED box should be visible in the camera view, you should have started a test observation in The Observer XT, etc. Set up The Observer XT for triggering the SyncBox. - Start an observation and, simultaneously, all external applications as External Programs in The Observer XT. During the observation The Observer XT triggers the SyncBox to send out one or more signals. - Stop the observation and the external applications, and import all data into The Observer XT. - Manually synchronize the observational and external data in order to be able to determine the difference in offset. - Once you know this difference in offset for a specific application, simply set this delay in The Observer XT next time you start this application from within The Observer XT simultaneously with the start of an observation. As a result, the start of the observation and the external application are now synchronous. Triggering The SyncBox You use The Observer XT to trigger the SyncBox to send out signals. You can set the interval between consecutive trigger pulses in The Observer XT. Make sure the SyncBox is connected to The Observer XT PC via the COM port and the Auto on/off switch on the SyncBox is set to off. Before You Start Triggering The SyncBox - Make all the necessary connections and make sure the signal(s) can be recorded by the appropriate applications and devices. - After you have made all connections you can check whether signals are sent out properly by pressing the blue Trigger button on the SyncBox. - In The Observer XT, before you start an observation, make sure you have added all external applications as External Programs in the Observation source. This way the external applications are started when you start an observation. Steps To Start Triggering The SyncBox - Make sure to close all unused programs; variable processor load may cause the delay to vary in the start-up of some applications. - In The Observer XT, open a SyncBox project. - Under Observation source, make sure you select Live Observation. You should not select DAQ settings when you want to use the SyncBox. If you do so, the SyncBox settings are grayed out. - Create a new observation. - Click View Settings on the far-right of the tool bar of the observation, then select SyncBox. - In the SyncBox Settings window, select the Enable SyncBox pulse box. Next, set the following: - Output port — Select the COM port that connects The Observer XT PC to the SyncBox. Usually this is the default COM1. However, if you use a Noldus USB-to-COM converter because you run The Observer XT on a laptop without a COM port, you should select another COM port. Selecting the correct COM port causes the SyncBox internal speaker to play back a sound (if switched on). - Pulse interval — Enter a value between 1 and 3600 seconds. - Press OK. If you carry out another action in The Observer XT after making the SyncBox settings, you need to return to step 5 to redo these settings. - Start the observation. As soon as the observation starts, all external applications are also started and the first trigger pulse is sent to the SyncBox. Synchronously, a trigger comment is logged in the event log in The Observer XT with the format: Pulse - . - Stop the observation after the required number of pulses have been sent. You can now determine the difference in offsets by manually synchronizing the observational and external data. How Many Pulses Should I Use? Send two trigger pulses at the start of an observation in the following case: - You carry out a short observation (less than 60 minutes) — In this case it is unlikely that The Observer XT computer and the external computer will start running out of sync during an observation, so you only need to determine the difference in offset at the start of the observation. You should always send at least two trigger pulses because The Observer XT sends the first trigger pulse at the start of the observation when the external application might not be ready yet to record the SyncBox signal. Using A Series Of Trigger Pulses Send a series of pulses in the following case: - You carry out a long observation (more than 60 minutes) and you are not sure that the clocks on all systems are accurate — In this case you should send out a series of pulses during the observation. The pulse interval depends on a) the total duration of the observation and b) the inaccuracy of the clocks. By determining the difference in offset at the start and the end of the observation you know how much you should stretch the external data. Example 1 — You carry out an observation of 8 hours while simultaneously acquiring physiological data. You know that the clock of one of the systems is not completely accurate but not dramatically so; you send a trigger pulse every 30 minutes. After you have imported the external data you determine the difference in offset at the start and end of the observation. The start is synchronous but at the end of the observation the external data lags behind 30 seconds; you should then re-import the data and shift the end time of the external data 30 seconds ahead. Example 2 — You carry out an observation of 1 hour while simultaneously acquiring physiological data. You know that the clock of one of the systems is very inaccurate; you send a trigger pulse every 5 minutes. After you have imported the external data you determine the difference in offset at the start and end of the observation. The start is synchronous but at the end of the observation the external data lags behind 15 seconds; you should then re-import the data and shift the end time of the external data 15 seconds ahead. Troubleshooting No time-stamped trigger comments appear in my test observation. - You did not select Enable SyncBox pulse in the SyncBox Settings window. See step 6 in the steps above. No signals are sent out by the SyncBox. - You made incorrect connections — redo the connections and test the signals by pressing the blue Trigger button on the SyncBox. - You did not connect The Observer XT computer to the SyncBox — use the COM cable to make the connection. - You selected the wrong COM port in the SyncBox Settings window — see step 6 in the steps above. - One of the jumpers inside the SyncBox is in the wrong position — Open the SyncBox by unscrewing the two Philips screws sunk into the bottom of the SyncBox. Carefully remove the top part of the SyncBox. The two red jumpers are located between the COM port and the X-keys USB outputs. The RTS/DTR jumper should be set to DTR; the 1/2 jumper should be set to 2. To change the position of a jumper, lift the jumper using the small crevice just below the top and slide it back over two pins, moving one position. When I start up my computer with the SyncBox connected, it almost continuously sends out signals. - This happens when the default voltage of the RTS/DTR pin of your computer is +11 Volt. Only when you open an observation in The Observer XT and select the SyncBox is the base voltage on the RTS/DTR pin set to -11 Volt. During an observation, the SyncBox is triggered by +11 Volt pulses. The only solution is to turn off the internal speaker and to disconnect the external speakers until you open the SyncBox settings in an observation. What do I use the Auto on/off switch for? - When the Auto on/off switch is set to on, the SyncBox sends out a signal every approximately 30 seconds. You should preferably not use the Auto on/off switch for triggering the SyncBox but use The Observer XT instead, because its time base is more accurate. --- ## The Observer XT 17 - SyncBox - Working with the SyncBox URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-syncbox-working-with-the-syncbox Chapter: The Observer XT Working with the SyncBox Workflow Working with the SyncBox involves the following basic steps: - Determine what type of signals you want to send out with the SyncBox. Note: Use the SyncBox before you actually start acquiring data. Create a SyncBox project in The Observer XT, carry out a test observation while The Observer XT triggers the SyncBox to send out its signals, and determine the difference in offset between the trigger comment(s) in the observation and the external applications/devices. --- ## The Observer XT 17 - Tobii Glasses - 2. Automatic Import into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-tobii-glasses-2-automatic-import-into-the-observer-xt Chapter: The Observer XT 2. Automatic Import into The Observer XT Software Installation - The Observer XT 17 - MediaRecorder 6.5 - N-Linx Server 2.0, for communication between The Observer XT and other applications. - N-Linx Agent 1.5.1.0 - Noldus Tobii Glasses 3 Control — N-Linx plug-in 1.0.1.0. - Tobii Pro Glasses 3 controller application — You can download this software from the Tobii website (www.tobii.com). The solution was tested with one pair of Tobii Glasses 3. The solution does not work with the Tobii Glasses 2. The solution was tested with all software on one computer. If you ordered a new computer from Noldus Information Technology when you purchased the solution, all the software is already installed and tested. If you bought your own computer, please follow the instructions below. You can download the installation files via your MyNoldus account. Browse to my.noldus.com and log in or create an account. Install The Observer XT - Download the Observer XT installation file via your MyNoldus account (my.noldus.com, Downloads > The Observer XT > Versions > Current version). - Double-click the installation file to run it. Install MediaRecorder - Download the MediaRecorder installation file via your MyNoldus account (my.noldus.com, Downloads > MediaRecorder > Versions > Current version). - Double-click the installation file to run it. Install N-Linx Server - Download the N-Linx Server installation file (N-Linx_Server_Setup.exe) via your MyNoldus account (my.noldus.com, Downloads > The Observer XT > Drivers & Tools > Drivers for current version > N-Linx Server Setup 2.0 > Download). - Double-click the installation file to run it. Install N-Linx Agent - Download the N-Linx Agent installation file (N-Linx_Agent_Setup.exe) via your MyNoldus account (my.noldus.com, Downloads > The Observer XT > Drivers & Tools > Drivers for current version > N-Linx Agent Setup 1.5.1 > Download). - Double-click the installation file to run it. Install Noldus Tobii Glasses 3 Control - Download the Tobii Glasses 3 Control installation file (TobiiGlasses3Control.Installer.exe) via your MyNoldus account (my.noldus.com, Downloads > The Observer XT > Drivers & Tools > Drivers for current version > Tobii Glasses 3 Control Installer > Download). - Double-click the installation file to run it. Enable N-Linx in MediaRecorder and The Observer XT Settings in MediaRecorder - From the File menu select Preferences > N-Linx Settings. - Select Allow communication with N-Linx Server. - The Client name field is filled in automatically and cannot be changed. - The Computer name field is filled in automatically and cannot be changed. - In the N-Linx Server address field, leave the default value localhost. - In the N-Linx Server port field, leave the default port 5672. Ask your administrator if this port is used by another program. - When the connection with N-Linx Server is established the Status will be Connected. Click OK. Settings in The Observer XT - From the File menu select Preferences and then N-Linx Settings. - Select Use N-Linx Server to connect with other applications. - In the N-Linx Server address field, leave the default value localhost. - In the N-Linx Server port field, leave the default port 5672. Ask your administrator if this port is used by another program. - Click Test Connection and check that the Status is Connected. Then click OK. Edit Config Files Edit the Noldus.Proxy.TobiiGlasses3.Config File - Run N-Linx Agent to create the config file: in the Windows search field, type N-Linx Agent and click on the name of the app in the list that appears to run it. - Stop N-Linx Agent: click the Show Hidden Icons icon in the lower-right corner of your screen, right-click on the N-Linx Agent icon and select Exit. - Open Notepad and from the File menu select Open and browse to C:\ProgramData\Noldus\TobiiGlasses3 Control\1. Note: The ProgramData folder is a hidden folder. To view this folder, browse to C:\ and on the View tab select Show and then Hidden Items. - In the lower-right corner of the window that opens, select All Files (*.*) and open the file Noldus.Proxy.TobiiGlasses3.config. - RabbitMQAddress — Do not change the line localhost. - RabbitMQPort — Do not change the line 5672. - IsFirstTimeConfig — Enter false instead of true in the line true. - TobiiGlasses3Address — Do not change the line 192.168.75.51. - TobiiGlasses3DeviceId — Replace the ID in the line tg03b-080200044301 with 9fbb7a3f-5c0b-485f-b531-70384f925222. - TobiiGlasses3HostId — Add the following line to the config file: 9fbb7a3f-5c0b-485f-b531-70384f925222. - TobiiGlasses3DisplayName — Replace the ID in the line tg03b-080200044301 with the ID of your Tobii Glasses that you can find on the sticker at the back of the recording unit. - TobiiGlasses3AutoDetect — Enter false instead of true in the line true. - Save the config file. - Restart N-Linx Agent: click the Windows button and type N-Linx Agent in the search field. Click on N-Linx Agent in the list that appears. Edit the MediaRecorder Config File - Open Notepad and from the File menu select Open and browse to C:\ProgramData\Noldus\MediaRecorder\6. Note: The ProgramData folder is a hidden folder. To view this folder, browse to C:\ and on the View tab select Hidden Items. - In the lower-right corner of the window that opens, select All Files (*.*) and open the file Noldus.MediaRecorder.config. - Edit the second-to-last line and change false into true. - Save the config file. Edit the Noldus.UMR.GazeOverlay.Config File - Log into your MyNoldus account (my.noldus.com) and download the Noldus.UMR.GazeOverlay.config.xml file (my.noldus.com, Downloads > The Observer XT > Drivers & Tools > Drivers for current version > Noldus.UMR.GazeOverlay.config > Download). - Enter the GazeOverlayChannel name. This should match the TobiiGlasses3DeviceID of the Noldus.Proxy.TobiiGlasses3.config file (9fbb7a3f-5c0b-485f-b531-70384f925222). - Save the file in C:\ProgramData\Noldus\MediaRecorder\6. Make sure that you save the file with the extension *.xml. Prepare the Tobii Glasses - Connect the glasses with the recording unit, insert a battery and SD card in the recording unit and switch the recording unit on by pressing the button. - Check that the button is green. If the button is orange or red the battery is low or empty. In that case, insert a new battery. - Connect the Tobii Glasses with the PC via Wi-Fi: click the Wi-Fi icon in the lower-right corner of your screen and click the Tobii Glasses name (starting with TG). - If this is the first time you connect the glasses, fill in TobiiGlasses as the password. - Start the Tobii Pro Glasses 3 controller application. The live view of the glasses should be visible on your screen now. Prepare MediaRecorder - Start MediaRecorder and click the Video Settings button. - Under Video name change Video 1 into Tobii Glasses 3. Note: The settings for the Tobii Glasses must be made for Video 1 (the first line in the Video Settings). If you choose Video 2, Video 3, or Video 4, the gaze data will not be imported into The Observer XT. - Under Video device select RTSP IP Camera (Noldus RTSP Source Filter). - Click the Advanced Video Settings icon and enter: - IP address: 192.168.75.51 - Port: 8554 - User name: root - Password: Noldus - Click Get Device Properties and in the Connection string field enter: /live/all?gaze-overlay=true - Click OK twice. You should now see the live view of the Tobii Glasses in MediaRecorder. Prepare The Observer XT - Start The Observer XT, create a new project, give it a name and click OK. - Read the text in the Data Transparency window and the End-User License Agreement and click OK. - Click Set Up Project and under Observation source select Live Observation. The Devices window opens. - Select MediaRecorder 6- and TobiiGlasses3 Control 1.0- and check that the status of both is Enabled, Running. Run a Test Prepare the Test Participant - Brief the participant and ask him/her to sign the consent form. - Help the participant to wear the eye tracker glasses. --- ## The Observer XT 17 - Tobii Glasses - Manual Import into The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-tobii-glasses-manual-import-into-the-observer-xt Chapter: The Observer XT Manual Import into The Observer XT Software Requirements We recommend installing The Observer XT and the Tobii Pro software on two separate computers. On the Observer XT Computer: - The Observer XT 17 - Noldus Tobii Pro Lab File Converter 4.0, to convert Areas of Interest (AOI) data from the Tobii Pro Lab software On the Tobii Computer: - Tobii Pro Lab - Tobii Pro Glasses 3 controller application If you ordered a new computer from Noldus Information Technology when you purchased the solution, all the software is already installed and tested. If you bought your own computer, you can download the installation files via your MyNoldus account. You can download the Tobii software from the Tobii website. Workflow - Prepare the Tobii Glasses. - Run a test and record data with the Tobii Pro Glasses 3 controller application. - Import your recordings into Tobii Pro Lab. - Export a gaze overlay video from Tobii Pro Lab. - Collect AOI data by running assisted mapping. - Export AOI data from Tobii Pro Lab. - Convert AOI data with the Noldus Tobii Pro Lab File Converter Tool. - Export pupil diameter data from Tobii Pro Lab. - Import a gaze overlay video into The Observer XT. - Import AOI data into The Observer XT. - Import pupil diameter data into The Observer XT. Run a Test - Prepare the Tobii Glasses. - Brief the participant and ask him/her to sign the consent form. - Help the participant to wear the eye tracker glasses. - Ask the participant to (1) hold the calibration card at arm's length and (2) look at the center of the circle. Click the Calibrate button in the Tobii Pro Glasses 3 controller application. A message will appear if the calibration is successful. - Click the Record button to start the recording and at the end of the test click the Stop button to stop the recording. - Remove the SD card from the recording unit and insert it in the Tobii Pro Lab PC. Import Your Recordings into Tobii Pro Lab - Start the Tobii Pro Lab software. The Create New Project tab opens. - Click Glasses, enter a name for the project and click Create. The Project Overview window opens. - At the top of the screen click Import > Glasses 3 Recordings. - Browse to the SD card, open the appropriate data folder and click Select Folder (do not open the meta folder). Check the Date Modified column to see which folder has the data you need. The Glasses Data Import window opens with the list of recordings made in the project. - Select the recordings that you want to import and click Import. Click OK when the import is ready. The recordings will be listed in the Project Overview. - Check that the percentage of gaze samples is at least 70–80%. - Double-click a recording in the Project Overview to open it. You will now see a timeline with the scene video with the participant's gaze overlay. Export a Gaze Overlay Video from Tobii Pro Lab - Open the appropriate project and click on the Recordings button on the toolbar on the left. - Double-click the recording from which you want to export the gaze replay video. - On the left-hand side of the timeline you will find two small yellow markers. Click and hold the right-hand marker and drag it to the end of the video to select the entire gaze replay video for export. Select the interval that you want to export. - Click the circle in the middle of the yellow bar and choose Export Video Clip. - Select the location where you want to save the video. - Enter a name for the video and select an appropriate video resolution. Then click Export. - The Activities icon at the top right of your screen shows the progress. - Copy the gaze overlay video to the computer with The Observer XT to import it. Collect AOI Data - Run Assisted Mapping Areas of Interest (AOIs) are useful in tests where participants look at a stationary set-up, for instance, at a shelf in a supermarket. You can give test participants the assignment to search for a certain product in a supermarket or a book in a bookshop. - Use your mobile phone to make a photo of the shelf containing the product that you want your participants to search for, and transfer the photo to the Tobii computer. - In Tobii Pro Lab, open your project and your recording. - In the Gaze Data field on the right side of your screen, open the Snapshots tab and click the plus icon to add a snapshot. - Browse to the photo of the shelf, select it and click Open. The photo will appear as a thumbnail in the Gaze Data field. - Enable the Show Snapshot switch in the Gaze Data field. You will see the photo next to the recording. - From the Analyze menu select AOI Tool and use one of the Draw icons at the top of your screen to draw your areas of interest. Make sure to give them logical names such as left-upper, left-middle, left-bottom, right-upper, right-middle, and right-bottom in the case of a bookshelf with compartments. - Move the yellow sliders on the timeline to indicate the portion of the recording for which you want to run assisted mapping. - Click the circle in the middle of the yellow bar and select Run Assisted Mapping. - The Activities icon at the top right of your screen shows the progress. When the mapping is ready, you can play the recording and view the mapping on the photo. Export AOI Data from Tobii Pro Lab - In Tobii Pro Lab, from the Analyze menu select Data Export. - Select all parameters to export. The list includes: - AOI Hit: fixations in an AOI. - AOI Visit: all data between the start of the first fixation inside an AOI and the end of the last fixation in the same AOI. - AOI Glance: the data from the first saccade leading into an AOI until the last fixation inside the AOI, including all data such as saccades, blinks, and invalid gaze data. You can select AOI Hit, AOI Visit, and AOI Glance, or make a selection of one or two of these parameters. - In the Settings field on the right side of your screen, from the Format drop-down list select Tobii Pro Lab Output (.plof). - From the Timestamp Precision drop-down list select milliseconds. - In the Data Selection field: - Recordings: select from which recordings you want to export the data. - Times of Interest: select Snapshot Gaze Data. - Snapshots: select the appropriate snapshot name. - Areas of Interest: select all areas of interest that you have drawn, or make a selection. - Click the Export Files button at the top of your screen, browse to the folder in which you want to save the data and click Select Folder. - A subfolder will be created with the name Data Export - . Click OK. - Copy the AOI data (*.plof) to the Observer XT PC. Convert AOI Data To be able to import the AOI data into The Observer XT, the export file must be converted into a format that can be read by The Observer XT. - Open the Noldus Tobii Pro Lab File Converter Tool. - Browse to the folder with your export files (*.plof), select one or more files and click Open. To select multiple files, click the file names while holding the Ctrl or Shift key, then click Open. A message confirms that multiple files are selected. - Select the destination folder in which you want to save the converted files. - Click Convert. A Conversion Is Ready message will appear when the data have been converted to text format. - Copy the data files to the computer with The Observer XT to import them. Export Pupil Diameter Data from Tobii Pro Lab - In Tobii Pro Lab, from the Analyze menu select Data Export. - Unselect all parameters and under Eye Tracking Data select Pupil Diameter. - In the Settings panel on the right: - From the Format drop-down list, select Multiple Standard Files (.tsv). - From the Timestamp Precision drop-down list, select milliseconds. - In the Data Selection field: - Recordings: select from which recordings you want to export the data. - Times of Interest: select Snapshot Gaze Data. - Snapshots: select the appropriate snapshot name. - Areas of Interest: this selection is not relevant for pupil diameter export. - Click the Export Files button at the top of your screen, browse to the folder in which you want to save the data and click Select Folder. - A subfolder will be created with the name Data Export - . Click OK. - Copy the data files to the computer with The Observer XT to import them. Import a Gaze Overlay Video into The Observer XT - Start The Observer XT, open the project and then the observation in which you want to import the video. - From the Observe menu select Video > Open in Current Observation, or click the Import Video button on the toolbar. - Select the video that you exported from the Tobii Pro Lab software and click Open. Import AOI Data into The Observer XT Important: Make sure that you have converted the export files with the Noldus Tobii Pro Lab File Converter Tool before proceeding. - Start The Observer XT and open the project and then the observation in which you want to import the AOI data. - Click the Import Data button on the toolbar and select Import Observational Data. - In the Import Observational Data window, from the Files of Type list, select Tobii Pro Lab 1.x AOI and Fixation Data (*.txt). - Browse to the location in which you stored the converted files. Select the appropriate file and click Open. - Click Yes to import new coding scheme elements. The data are then imported and visualized in the Data and Audio Visualization window. Note: The Areas of Interest and fixations are imported as State Events in a behavior group of type Start-Stop. Import Pupil Diameter Data into The Observer XT To be able to import pupil diameter data you need an import profile. You can download this profile via your MyNoldus account under Downloads > The Observer XT > Drivers & Tools > Drivers for Current Version. - Make sure The Observer XT is not running, then copy the import profile (*.eip) to the following folder: C:\ProgramData\Noldus\Common\Profiles. Note that the ProgramData folder is a hidden folder. To view it, browse to C:\ and on the View tab select Show and then Hidden Items. - Start The Observer XT, open the project and the observation in which you want to import the pupil diameter data. - Click the Import Data button on the toolbar and select Import External Data. - Browse to the folder where you stored the pupil diameter data and select the appropriate *.tsv file. - In the Files of Type drop-down list select Tobii Glasses 3 Pupil Diameter (*.tsv) and click Open. - Select Import and Ignore if you receive any warning messages. The data are then imported and visualized in the Data and Audio Visualization window. Tobii Pro Lab exports three parameters: Pupil Diameter Left, Pupil Diameter Right, and Pupil Diameter Filtered. The Pupil Diameter Filtered data are calculated by applying the selected gaze filter and pupil diameter filter. --- ## The Observer XT 17 - Tobii Glasses - Running a Test and Calibrating URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-tobii-glasses-running-a-test-and-calibrating Chapter: The Observer XT Running a Test and Calibrating - Prepare the Tobii Glasses as described in the preparation section. - Brief the participant and ask him/her to sign the consent form. - Help the participant to wear the eye tracker glasses. - Ask the participant to (1) hold the calibration card at arm's length and (2) look at the center of the circle. Click the Calibrate button in the Tobii Pro Glasses 3 controller application. A message will appear if the calibration is successful. Recording an Observation in The Observer XT - From the Observe menu select Observation and then New. Enter a name for the observation and click OK. - Click the Start Observation button. The Observer XT starts the gaze video recording in MediaRecorder and subsequently the acquisition of eye tracker data. - At the end of the test, click the Stop Observation button. The gaze video from MediaRecorder with the gaze overlay of the participant is now automatically imported into The Observer XT. Manual Import of Pupil Diameter Data Pupil diameter is the distance between the center and the outer edge of the pupil. Pupil size can vary depending on factors such as age and light conditions. The pupil diameter data measured with the Tobii Glasses are not corrected for variations in light. Pupils tend to become bigger (dilate) in low-light situations, allowing more light into the eyes. When there is a lot of bright light, pupils will become smaller (constrict). Pupil size has been associated with cognitive processes underlying perception, attention, and action for external stimuli. Pupil dilation was shown to indicate interest in the content of presented visual stimuli, revealing sex-specific differences. It is also known to indicate general mental activity and correlate with task difficulty. More recent studies have shown that high-resolution tracking of pupil size can be used to predict perception of specific stimuli and even voluntary decisions about attending to stimuli, suggesting a link between pupil responses and the higher-order brain systems supporting cognition, decision-making, and execution of actions. References - Hess, E. H. & Polt, J. M. Pupil Size as Related to Interest Value of Visual Stimuli. Science 132, 349–350 (1960). - Hess, E. H. & Polt, J. M. Pupil Size in Relation to Mental Activity during Simple Problem-Solving. Science 143, 1190–1192 (1964). - Kahneman, D. & Beatty, J. Pupil Diameter and Load on Memory. Science 154, 1583–1585 (1966). - Einhäuser, W., Stout, J., Koch, C. & Carter, O. Pupil dilation reflects perceptual selection and predicts subsequent stability in perceptual rivalry. Proc. Natl. Acad. Sci. 105, 1704–1709 (2008). - Einhäuser, W., Koch, C. & Carter, O. L. Pupil dilation betrays the timing of decisions. Front. Hum. Neurosci. 4, 18 (2010). Procedure - Open the observation in which you want to import the pupil diameter data. - Click the Import Data button on the toolbar and select Import External Data. - Browse to the folder where MediaRecorder stored the gaze overlay video and the pupil diameter data (by default, C:\Users\Public\Public Documents\Noldus\MediaRecorder\Video Files) and select the appropriate text file. - In the Files of Type drop-down list select Tobii Glasses 3 Pupil Diameter (*.txt) and click Open. The data are imported and visualized in the Data and Audio Visualization window. --- ## The Observer XT 17 - Tobii Glasses - Synchronization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-tobii-glasses-synchronization Chapter: The Observer XT Synchronization Collecting eye tracker data in The Observer XT allows you to combine it with other data modalities such as facial expressions and physiological data. It is crucial that all data are in sync. Use the procedure below to synchronize your data. Procedure - In your coding scheme, define a Point event labeled, for example, sync. - Start an observation as usual in The Observer XT and start recording with the Tobii Glasses. - Use a light signal or another visual marker and ask the participant to look at it so that it is visible in the gaze overlay video. Alternatively, you can use an audio marker. - The very moment the marker is visible or audible, score the sync event. - Import the gaze overlay video made by the Tobii Pro software into The Observer XT, and check when the marker is visible or audible in the video. You can then calculate the difference in timing between that time (the Tobii video and data) and the time that you scored sync (the event log in The Observer XT). Note that this method relies on the coder's reaction time. To Synchronize the Tobii Video and Data with the Event Log - Take note of the time difference value measured with the method above. - Open the observation and click the Offset button. - Click Numerical Offset. - Next to the name of the event log containing the eye tracking video and data, enter the time difference. For example, if the difference was 0.5 seconds, enter 00:00.500. For more information, see External Data > Import External Data > Manual Synchronization in The Observer XT Help. Source: The Observer XT 17 - Tobii Glasses Technical Note, Noldus Information Technology --- ## The Observer XT 17 - Tobii Glasses - Tobii Glasses 3 - Integration with The Observer XT URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-tobii-glasses-tobii-glasses-3-integration-with-the-observer-xt Chapter: The Observer XT Tobii Glasses 3 - Integration with The Observer XT 1. Introduction Aim of This Technical Note This document describes how to use the Tobii Glasses 3 in combination with The Observer XT. Collecting eye tracker data in The Observer XT allows you to combine them with other data modalities, like facial expressions and physiological data. You can either let MediaRecorder collect data from the Tobii Glasses and automatically import the gaze overlay video and eye tracker data into The Observer XT, or use the Tobii Pro Glasses 3 controller application and manually import the gaze overlay video and eye tracker data: - Automatic Import into The Observer XT — The Observer XT starts and stops MediaRecorder. MediaRecorder collects data from the Tobii Glasses, it receives the video signal and the gaze overlay data. When you stop the observation, the gaze overlay video and gaze data are automatically imported into The Observer XT. If you like, you can manually import pupil diameter data. Please note that with this method you cannot collect Area of Interest data. However, you can manually code the gaze overlay video in The Observer XT. - Manual Import into The Observer XT — Use the Tobii Pro Glasses 3 controller application to make a recording with the Tobii Glasses. Open the recording in the Tobii Pro Lab software. Export the gaze overlay video and the eye tracker data from Tobii Pro Lab in a *.plof format and convert the data file to a *.csv format with the Noldus Tobii Pro Lab File Converter tool. Manually import the gaze overlay video and the converted data into The Observer XT. Systems Used The solutions were tested on our standard test platforms, which are a Dell Precision T3660 PC and a Dell Mobile Precision 3581. Desktop Computer - Processor: Intel Core i7-12700, 25 MB Cache, 12 Core. - RAM Memory: 16 GB. - Operating System: Windows 11, 64 bit. Mobile Workstation - Processor: i7-12700H, 14 Core. - RAM Memory: 16 GB. - Operating System: Windows 11, 64 bit. For More Information About The Observer XT - The Observer XT 17 - Help. - For visualizing data: see Visualize Data. - For calculating statistics: see Calculate Statistics. - The Observer XT 17 - Quick Start Guide. About N-Linx - N-Linx - Reference Manual, which you can find on the MyNoldus portal of the Noldus website (Downloads > The Observer XT > Documentation). About Tobii Pro Software - Tobii Pro Glasses 3 User Manual. - Tobii Pro Lab User Manual. You can download both manuals from the Tobii website (www.tobii.com). --- ## The Observer XT 17 - Visualize Data - Customize and Manage the Visualization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-visualize-data-customize-and-manage-the-visualization Chapter: The Observer XT Customize and Manage the Visualization Edit the Event Data To edit the event data, for example to add events or correct a scoring error, do the following: - If you have only one observation visualized, click the Open Current Observation button on the toolbar. If you visualized more observations, choose Observe > Observation > Open. - Edit the data as explained in Correct Event Log Errors Manually in Carry Out an Observation. You can only edit observational data, not external data or audio. - To return to the visualization, click the Visualize Current Observation button on the toolbar. Alternatively choose Analyze > Visualize. Zoom In/Out To zoom the plots relative to time, click the Zoom In or Zoom Out button on the toolbar. Click the plot multiple times to reach the desired time zoom level. Every time you click, the plot is enlarged or reduced by a factor of 2. To zoom in or out relative to amplitude (only for external data and audio), click the Y-axis with one of the zoom buttons. To return to the normal mouse pointer, click the mouse pointer on the toolbar. To set a specific time span, choose View Settings > Time Span and set the desired length of the X-axis. Change the Time Format To change the time format, for example from absolute to relative, or to change the number of decimals, do the following: - Choose Setup > Project Settings > Time Formats in the left pane. - Select the preferred options. See Time Formats. Show and Hide Events Events are shown according to the hierarchical structure in the coding scheme. Behavior groups are listed in the left-most column of a plot. By default, all events are shown. To collapse a behavior group, a behavior, or modifiers attached to a behavior, click the – sign in front of the behavior group name, behavior name, or modifier name. To expand again, click the + sign. To remove behaviors from a plot, create a data profile (see Select Data for Analysis) and re-create an event plot. Sort Plots To change the order in which plots are displayed, move them up and down in the visualization. - Click the header (left-most cell) of the plot you want to move. The border of the plot is highlighted in blue. - Drag the plot to the desired position. Release the mouse button to confirm the position. Show and Hide Plots, Video, Audio, and Comments Choose which plots to display with View Settings on the far-right side of the toolbar. - Event Plots — Choose View Settings > Events or double-click the header (the left-most cell of the plot). Choose which event logs to display. - Video — Choose View Settings and select or deselect Videos. - Audio — Choose View Settings and select or deselect Show Audio. - Comments — Choose View Settings and select or deselect Show Comments. Change the Colors To change the color of events or imported data, click the colored square in front of the appropriate event or data stream and choose a new color. Customize the Audio Plot To show or hide specific audio streams, choose View Settings > Show Audio and choose the audio streams. To display data points in the plot, choose View Settings > Data Points. To change the color of the audio plot, click the colored square in front of the file name or the audio waveform and choose another color. Export Visualization as Picture To create a screenshot of the visualization: - Make sure the part of the visualization you want to export is visible on your screen. - Click the camera button on the component toolbar. - Choose the location and picture format. - Accept the default file name or enter another one and click OK. You can also copy the visualization and paste it into another program. Export the Visualization as Table - Click the Export Visualization Data button on the component toolbar. - Choose the file format (Excel or text). - Choose the observations to export. - Select the destination folder and enter the export file name, and click OK. Notes: - If you selected data before creating the visualization, only the time intervals specified in the Data Profiles are exported. See Export Observational Data. - It is not possible to export the event plot of multiple observations with the Export Visualization Data option if the observations contain external data. Instead, choose File > Export > Observational Data. See Export Observational Data. - It is not possible to edit an event plot if the project is read-only, for example if the project is stored on a CD/DVD, or if the project is already open in another Observer XT window (that is, two or more instances of The Observer XT are active at the same time and one shows the same event plot). Source: The Observer XT 17 Help - Visualize Data, Noldus Information Technology --- ## The Observer XT 17 - Visualize Data - Visualize Audio URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-visualize-data-visualize-audio Chapter: The Observer XT Visualize Audio How Audio Files Are Displayed Audio files are visualized as waveforms. By default, the waveforms are shown as a line plot. To view the audio data points, choose View Settings > Data Points. Audio Level With the volume control in the Playback Control window you can adjust the volume for all media files, and mute/unmute all audio streams. This volume control works independent from the Windows volume control. By default, the volume control is hidden. To show it, choose Setup > Project Settings > Playback Control Options and select Show Volume Control. Audio Channels The audio plot shows two channels (left and right) for stereo signals, and one channel for mono signals. If an audio/video file contains more channels, only the first two are visualized. The first audio signal you add to an observation is not muted; additional audio files are muted. This is indicated by the red line through the speaker icon. Click the speaker icon to unmute it. Audio Values You can see the value of a data point in the audio plot in one of the following ways: - Drag the audio plot to the point you require (also using the Playback Control) and check the value next to the video/audio file name. This is the value corresponding to the red hairline. - With the mouse, hover on a data point. This point becomes bigger and its value appears in a tool tip. Values are shown in dB (deciBel). These are dBFS, Decibel Full Scale, which is commonly used for digital signals. The average loudness generally determines its overall perceived volume. In the waveform, the level of average loudness appears as the densest, darkest part around the middle. dBFS is calculated as follows: dBFS = 20 * Log10 (Acur/Amax) Where: - Acur = the absolute value at the current time point - Amax = the maximum possible absolute value. For instance, for 16-bit audio: 215 - 1 = 32767 - dBFSmin = 20 * Log10 (0/32767) = -∞ dB (infinite) - dBFSmax = 20 * Log10 (32767/32767) = 0 dB 0 dB represents the highest possible value. All values below the maximum are negative numbers. For instance, for 16-bit audio the lowest possible value is -96 dBFS. Notes - Synchronization between audio from video files and the corresponding video images is within 2 frames (80 ms for PAL, 67 ms for NTSC). - See Supported Audio Formats for Visualization for the audio formats that can be visualized. - Audio data are plotted once, even if your Data Profile contains more than one Result container. Visualize External Data Prerequisite Your license includes the External Data Module. The External Data Plot External data imported into The Observer XT are shown in line or waveform-like plots. The imported data consist of discrete samples. In the visualization in The Observer XT, the samples are connected by a line, but this does not mean that the data are interpolated and become continuous. To show the individual data points, choose View Settings > Data Points. External Data Labels Dependent on the device that collects data, the dataset may not display units or other details on the external data stream. To edit these labels in the visualization, click the label in the external data plot and enter the details in the window that opens. The fields are also entered in the Independent Variables list. The other way around, if you fill out fields in the Independent Variables list for external data, these are shown in the External Data and Audio plot. External Data Plots and Data Selection In the example below, the heart rate of the child was acquired using Polar equipment (sample rate: 0.2 Hz). In a data profile, you select intervals by Polar heart rate higher or equal to 100 bpm. The sample at time stamp 76.16 s is the first one that is below 100 bpm and therefore the first interval ends at that time. Similarly, the sample at time 87 s is the first one above 100 bpm and therefore the second interval starts at that time. A sample at the exact end of an interval is not included in any statistical analysis. External Data Plots with Missing Samples If your imported data contain missing values, these appear as gaps in the visualization. Notes - External data streams are plotted once, even if your Data Profile contains more than one Result container. Visualize Comments By default, comments are not shown in the event plot. To visualize them, choose View Settings > Show Comments. The comments are now shown in the bars of state events, or next to the point events. If a comment is longer than the bar of the state event, or the space between two point events, only part of the comment is shown. Zoom in to show the full comment. You can visualize observations when it either contains events (or when the active data profile contains events) or when the observation contains external or audio data. So, when your observation only contains comments but also external data, the observation can be visualized. However, the comments themselves are only visualized when they are scored together with an event. --- ## The Observer XT 17 - Visualize Data - Visualize Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/the-observer-xt/page/the-observer-xt-17-visualize-data-visualize-data Chapter: The Observer XT Visualize Data When you visualize data, The Observer XT produces plots in which events are displayed against time. Video files and, optionally, visualized audio from video, and imported external data, are also displayed and synchronized with the observational data. To open the visualization choose Analyze > Visualize Data. You can play the videos together with the plots. The red hairline represents the current position in the video files. Make a Visualization Aim To visually inspect your observation and play back the video with the annotations. Prerequisites - You carried out at least one observation. - Your observations contain scored behaviors. Procedure - If you created data profiles (see Select Data for Analysis), make sure the correct one is highlighted in the Project Explorer. - Choose Analyze > Visualize Data. Alternatively, when you want to visualize only the observation that is open, click the Visualize Current Observation icon in the toolbar. The video in the visualization then opens at the timestamp that was selected in the Event Log. Result The Visualization window opens. See The Visualization Explained in Detail. Notes - If your coding scheme contains no behaviors, you cannot make an event plot. In that case you can only visualize video, audio and external data. - If you cannot visualize an observation, possibly the observation contains errors. Your observation is marked with an error symbol in the Project Explorer. See Correct Event Log Errors Manually in Carry Out an Observation. Alternatively, the active data profile does not contain data for that observation. Check the Results box in your data profile whether your selection contains data. - If you see you need to synchronize the different data files, click the Open Current Observation button to re-open the observation and change the offset. See Synchronize Data Sets. The Visualization Explained in Detail Aim To explain what is shown in each visualization window. Prerequisite You opened a visualization (Analyze > Visualize Data). The Visualization Windows The visualization has the following windows: - Event plots - Videos - External data and audio plots - Playback control window Event Plots The visualization displays event plots for each event log, subject and observation. These plots contain colored bars for state events, narrow vertical bars for point events and colored dots for Instantaneous Sampling data. See also: - Visualize Events - Visualize Comments Videos Videos are shown if you observed offline from video, or if you imported videos into your observation. See also: - Observation Source in Set Up Your Project - Import Media Files in File Management The number of videos you can display simultaneously in the Visualization is limited to eight, unless your license allows more than four videos per observation. To select other videos than shown by default, choose View Settings > Videos > Show Video and specify which videos to display. External Data and Audio Plots Each audio stream and external data file is displayed in a line plot. An observation can only contain external data if your license includes the External Data Module. If you do not see such a plot type, choose View Settings > Show Audio or Show External Data. See also: - Visualize Audio - Visualize External Data Playback Control Window See The Playback Control Window for an explanation of all playback control buttons. If you do not see the Playback Control window, choose View Settings > Playback Control. When you play the video, the hairline in the event plot moves synchronous with it. Also imported external data or audio streams play back synchronous. General Notes on Visualization - The visualization shows the data selected in the active data profile. - The hairline in the plot corresponds to the current position of the event log. The hairline is fixed in the middle of the plot area. - When you select intervals, these are shown on a white background. The non-selected intervals are shown semi-transparent, enabling you to see the excluded data in these intervals. - Transparent gray areas indicate the time that is not part of the observation. This is also the case for the time that a live observation was suspended. - When there is an offset between the start of an observation and, for instance, external data, the excluded data are shown in the transparent area. Visualize Events General The visualization displays event plots for each event log, subject and observation. These plots contain colored bars for state events, narrow vertical bars for point events and colored dots for Instantaneous Sampling data. When you hover with your cursor over a colored bar, a tool tip shows the behavior name, the modifiers scored (if applicable), the comment (if free text was entered for that event line) and the duration (for state events). Merged Events Merged behaviors are visualized under a new group Merged Behaviors. The modifiers of merged behaviors are not visualized. Merged modifiers are visualized under the behavior, with the name of the merged group. See also Merge Data. Time Bins If you defined intervals and time bins, then time bins are visualized per interval. See also Select Regular Intervals. Numerical Modifiers Numerical modifiers are shown as one colored bar with the name of the modifier group. The height of this bar is 20 pixels. The numerical modifier values are indicated by the height of the darker-colored area within the bar. By moving the hairline over a bar you can see the exact value of a numerical modifier after the modifier name on the Y axis. The values that are scored are categorized. For instance, you defined a range from -50 to 50 and coded the following 10 values: -50, -35, -20, -15, -5, 5, 10, 15, 25, 40. Each category gets a height of 2 pixels. So, for the value of -35, a bar height of 4 pixels is used. If you have more than 20 categories, some categories will get the same bar height. See also Modifiers. Multiple Result Containers If your Data Profile contains more than one Result container, intervals and time bins are shown in the corresponding plot. See also Create Groups of Data. --- ## Track3D - 1 Introduction URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-1-introduction Chapter: Track3D 1 Introduction 1 Introduction What Is Track3d? Track3D 2.0 is an add-on to the EthoVision XT software for automated tracking of animals in a 3D space. It allows you to visualize the trajectory of the animal in a three-dimensional picture, and calculate a wide range of movement variables such as velocity and turn angles in the 3D space. How Does Track3d Work? As you may already know, the EthoVision XT software records the position and movement of an animal in a 2D space by analyzing the images coming from a video camera or a pre-recorded video. In order to analyze the movement of animals in 3D space, two video cameras are needed. EthoVision XT tracks the animal's body center from both Figure 1 Example of 3D flight trajectory of a mosquito. Circles represent the odour plume. 1 Introduction camera views. This results in two sets of coordinates, each in a 2D space. The Track3D software combines the EthoVision track data from the two camera views. This software includes CentroidFinder, to calibrate the video image and obtain an accurate representation of the 3D world projected on two dimensions, and Track3D, which does the job of transforming the two sets of 2D coordinates into one set of 3D coordinates (X,Y,Z). Track3D also visualizes the trajectory of the animal in a 3D space, and quantifies the animal's movement by calculating a number of variables. Step 1 - Recording video Aim - To provide video footage that EthoVision uses to track the animal and record the 2D coordinates. Video is recorded from the two cameras simultaneously and is saved to full resolution video files. How? - With EthoVision XT or MediaRecorder. See page 44 Figure 2 Main steps in the Track3D workflow. 1 Introduction Step 2 - Acquiring the tracks Aim - To provide sets of coordinates of the animal's body center in a 2D space. How? - With EthoVision XT. See page 48, page 54, page 58 Step 3 - Visualizing and analyzing 3D tracks Aim - To obtain a 3D representation of the animal's trajectory and calculate 3D movement variables (e.g. speed, heading). How? - With Track3D. See page 59 Calibration Aim - To determine the relationship between the 3D coordinates in the real world and their projection on the 2D space of the video image that is used by EthoVision to track the animal. You can obtain reliable 3D data only if you carry out an accurate calibration. How? See page 26. You do not need to calibrate every time you acquire data. A new calibration is needed when the camera position changes relative to the tracking chamber. If the cameras and the tracking chamber are fixed, you can always work with the same calibration. Track3d Software Components MediaRecorder It includes an encoder board to be installed on your PC and special software that records video from multiple cameras to high-quality video files. Recording starts at the same time for all cameras, so the images recorded are synchronized. 1 Introduction EthoVision XT Software for video-tracking. In EthoVision XT, you track the subject from the video files recorded with MediaRecorder. First, you define in which area of each camera view the subject is going to be (arena). Next, you instruct EthoVision on how to distinguish the subject from the background, and start data acquisition. Calibration software: CentroidFinder In order to calculate movement variables in 3D units (e.g. 3D flight path) one needs to transform the original tracking data (obtained from 2D images) to 3D coordinates. This transformation is only possible if the relationship between the position of specific points (called calibration markers) in the real world and their projection on the video image is known. The calibration software helps you assessing this relationship from a static picture of the calibration markers. Visualization and Analysis software: Track3D The program for visualizing the tracking data. This program has two inputs (1) the calibration file obtained from the calibration software and (2) the input data file with the 2D data that you create from the two tracking data sets (one per video camera). In order to use CentroidFinder and Track3D, you need to install a Matlab Component Runtime library. If this is not installed on your PC, you can find it on the installation disk. Copy the file MCRInstaller.exe to the folder C:\MCR, and double-click it. Follow the instructions on the screen and make sure that you install the library on C:\MCR. What's New In Track3d 2.0 Software license key In order to run Track3D and CentroidFinder, you must have your EthoVision XT hardware key plugged in your computer. Note that you do not have to install EthoVision XT and Track3D on the same computer. You can have them on two different computers. However, make sure that the computer on which Track3D is installed 1 Introduction has the drivers for the hardware key correctly installed. You can find these drivers on the EthoVision XT installation DVD. Importing EthoVision XT track files You no longer have to combine the track files for camera 1 and camera 2. Track3D does that for you. Definition of 3D zones You can split your tracking chamber in several three-dimensional zones, cuboids or cylinders. Track3D marks each data point in the results file based on the point's position in one of those zones. You can then filter the data of the results file with Excel to analyze data points in a zone or a combination of zones. See page 67 for definition and page 116 for analysis. Creating a video of your 3D track After opening the 3D track chart, you can let Track3D capture part of your computer screen while the track is being played back. Track3D saves this video as an AVI file. For more information, see page 82. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 11 Data Visualization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-11-data-visualization Chapter: Track3D 11 Data Visualization 11 Data Visualization Visualize The 3d Track We assume at this point that you have completed the 3D analysis procedure (page 60). A 3D track chart opens on the screen. Default views By default, the track is viewed from above (X-Y view). To revert to this view, right-click anywhere in the middle of the chart and select Reset to Original View. Additional default views are: X-Z view and Y-Z view. To activate a view, right-click within the chart and select the option you require. Figure 20 Default view of the 3D track. 11 Data Visualization Data points Each point of the track is a sample originated by a pair of valid 2D EthoVision samples. The first point is marked by a green triangle, the last by a magenta circle. The color and style of the samples varies according to their position: Green star - For samples within the cone (1 in Figure 21) Magenta triangle - For samples in the buffer zone (2) Red dot - For samples outside the cone and buffer zone (3) Different blocks of valid samples are separated by a number of missing samples depending on what you have specified under interpolation (see page 71). Thus the time between the end of a red track and the start of the next is not fixed. Odour plume cone The cone represents the diffusion pattern of the odour plume throughout the test chamber. It is indicated by blue circles. The cone's top position is indicated by a blue cross. To change the shape and size of the cone, enter the appropriate values in Track3D (page 65), select Old calibration and click Start calculations. Figure 21 The sample points differ in style and color depending on their position. See the text for an explanation. 11 Data Visualization Panning options - To move the chart, click the Pan button on the tool bar. - Click anywhere within the chart and drag to the position you require. If you have selected one of the default 2D views (X-Y, X-Z, Y-Z; see above), you can also pan the chart in fixed directions: right-click the chart and select Pan Options, then Horizontal Pan or Vertical Pan. Next, drag the chart as usual. To revert to normal pan mode, right-click, select Pan Options then Unconstrained Pan. Rotating the 3D chart - Click the Rotate 3D button on the tool bar of the chart window. - To rotate the chart, drag the mouse over the chart. - To rotate the chart around the z axis, drag the mouse horizontally. To rotate the chart around the x axis, drag the mouse vertically. - To rotate the chart while viewing the previous orientation, right- click within the chart, select Rotate Options and then Plot Box Rotate. To rotate the chart continuously, right-click within the chart, select Rotate Options and then Continuous Rotate. Zooming in and out - To zoom in and out the chart, click the corresponding magnifying glass button on the tool bar. 11 Data Visualization - Click within the chart one or more times, or move the mouse wheel to get the zoom level you require. Visualizing specific data points - Click the Data Cursor button on the tool bar. The mouse pointer changes to a cross symbol. - Point to a specific sample, then click. A datatip opens showing the 3D coordinates of the sample and the time stamp. If you click the line connecting two samples, the coordinates of the nearest sample point are displayed. To display the coordinates of two or more data points, right-click the chart, select Create New Datatip, then click the sample you want to visualize, or press Alt and click the sample you want to visualize. To remove datatips, press Delete. Visualizing the track in multiple colors You can visualize the 3D chart with points in different colors, based for example on speed. We advise you to open the raw data file (page 85) in RapidMiner. You can download RapidMiner for free from the web site https://rapidminer.com. Editing the 3D chart There are a few options to edit your chart before exporting it. 11 Data Visualization From the File menu of the 3D chart window, select Export Setup. Make the necessary changes, then click OK. To test a change, click Apply to Figure. To return to the default chart, click Restore Figure. Size (for printing) - Select the units you require, and enter the Width and Height of the chart. This includes the title text and the axis labels). To return to the original size, select Auto for both options. Rendering - Select the Colorspace you require. To change the background color, select Custom color and there type in a letter for the color you require (w= white, y= yellow, m= magenta, r= red, c= cyan, g= green, b= blue, or k= black). Choose the resolution of the picture. De-select the Keep axis limits option if you want to stretch the chart depending on the window size. Fonts - To change font size, select Use fixed font size and enter the size in points. Select Custom name and select the font you want to use. Lines - To change the width of the lines (including the track), select Use fixed line width and enter the width you require. For more information, see the MATLAB documentation. Export And Print The 3d Track Chart Saving and exporting the 3D chart You can export the chart as a picture file. To save the chart, from the File menu select Save, or click the Save Figure button on the tool bar. In the File name field enter the name you require for the file, then from the Save as type list choose the format, and click Save. tip You can save the 3D chart as MatLab figure (*.fig), which you can re-open, rotate and play back using Track3D. From the File menu select Save As, keep the option MATLAB Figure (*.fig) 11 Data Visualization selected, type in a name for this file and click Save. To re-open the figure, make sure that a Figure window is open, and from the File menu select Open. Printing the 3D chart To print the chart, from the File menu select Print, or click the Print Figure button on the tool bar. You can also add titles and change the text style by selecting Print Preview from the File menu. Play Back The 3d Track You can play back the track in the Track3D chart. In this animation the subject is represented by a red circle which moves along the 3D trajectory at a user-defined speed. 1. Specify the playback speed: under Speed, click Normal for 1x, or select the second option and move the slider to the speed you require. 2. To play back the track, click the Start animate button. 11 Data Visualization 3. To pause playback, click Pause. To resume playback, click Resume. 4. To stop playback, click Stop animate. To replay the track, you must first click Stop animate. Create A Video Of The 3d Track With the Record function you can create a video of your 3D track that you can play on a computer without Track3D. 1. Make sure that the 3D chart is open on your screen. Rotate and zoom in/out if necessary. 2. Under Record, click Preferences. The Preferences record box appears. 3. Under Resolution, choose the size of the video image in pixels. 4. Under Compression, choose one of the options: - None - Video is saved as a RGB raw bitmap AVI file. It gives the best image quality but also larger file size. Choose this option especially with high density of points in your 3D track. In the field below, enter the Maximum file size (in MB) you want to accept. 11 Data Visualization - Cinepak - Video is encoded using a Cinepak codec. In the field below, enter the Quality (1-100). The higher the value, the better the picture quality and larger the size of the resulting video file. 5. Click Start record. The chart window comes on top at the bottom-left corner of your screen, and track animation starts. The screen is captured according to the options selected. 6. When the screen recording ends, the Start record button becomes available again, and a text appears at the bottom of the Track3D window: 11 Data Visualization 7. The file is saved in the MCR folder. The file name is "AVI"+ date + time_n. The value n increases 1, 2,... if multiple videos are saved in the same minute. Notes The animation shows the odour plume cone, not the other user- defined zones. In most cases the screen capture only includes the chart (white area), not the title text. If you choose None and the video file size exceeds the Maximum file size entered in step 4, video capture will stop at that size. Therefore, the track will not be played back for its entire length. You cannot make a video from a 3D chart that was saved previously and opened via File, Open. You must repeat the analysis procedure in order to visualize the track in a new 3D chart. Next, make a video from that track chart. After starting recording, check that the Start record button is greyed out. If not, click it once more. In the table below you can see how much disk space a video requires. Frame rates: For Cinepak 8-12 frames/s, depending on quality; For Uncompressed 10 frames/s. Resolution Compression Quality Space 402 x 378 Cinepak 100* 6 MB/min None 320 MB/min 838 x 790 Cinepak 100* 17 MB/min None 1300 MB/min Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 12 Analysis Variables URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-12-analysis-variables Chapter: Track3D 12 Analysis variables 12 Analysis Variables The Track3D results file is an Excel file containing the 3D coordinates of the samples collected by EthoVision, and a number of position and movement variables calculated from those coordinates. Raw Data Block # Indicates the block number the sample belongs to. A block is a set of successive valid samples. Within a block there may be samples interpolated using adjacent samples. Interpolation can be done for missing samples (see page 71). Whether a missing sample was replaced by interpolated values is indicated by the interpolation code (see below). Different blocks are separated by a number of missing samples. This is why there is a time gap between the end of a block and the start of the next one (Figure 22). Those missing samples were not interpolated as 12 Analysis variables they formed a sequence longer than the limits specified at interpolation (see page 71). Analysis variables are calculated for each sample using the coordinate values of that sample and at least one preceding sample. Because the samples immediately preceding the first sample of a block are missing by definition, the variables are not calculated for that sample. Line # Indicates the line number of the original sample. In a boundary between blocks the line numbers differ by more than one since a number of missing, non-interpolated samples have been removed. Time Indicates the time the sample was collected relative to the start of the EthoVision trial. If you started a trial from a specific time or frame number of the video file, the time is still the time since the start of the trial, not from the begin of the video file! It can happen that the first lines of the recording are not included in the file. This depends on your interpolation settings which may exclude those points. Figure 22 Boundary between two successive blocks 1 and 2. The end time of block 1 is 21.32 s, while the start time of block 2 is 21.56 s. This means that an interval of 0.24 s has been excluded from analysis. 12 Analysis variables x, y, z columns Indicate the 3D coordinates in mm of the supposed center of the tracked animal. The axis origin (0,0,0) and the axis orientation depend on the calibration used to obtain the 3D data. Inters. err. Indicates the intersection error, in pixels, for that sample. Intersection error is the distance between two lines in the 3D space connecting each camera with the object found. If the two cameras provide two values of distance, the smallest value is taken. This value is always lower than the maximum intersection error, because If this distance is greater than the sample is removed from the results file. Plume code Indicates where the subject is located relative to the supposed plume cone (see Figure Figure 24): Figure 23 Example of x coordinate of a sample. Figure 24 Examples of plume codes for three data points. 12 Analysis variables Interp. code Indicates whether the current 3D coordinates were obtained from measured 2D coordinates (that is, values exported by EthoVision) or interpolated 2D coordinates. 1 - 2D coordinates Interpolated for both cameras 2 - 2D coordinates measured for one camera and interpolated for the other 12 Analysis variables Path Shape Path 3d The distance moved from the starting point of the present block up to the current sample. It measured as the sum of the segments joining adjacent samples and is expressed in mm. Figure 25 Example of Path 3d. Dots are sample points in the 3D space. The sample s0 is the start of the block. Path 3d equals: d1 for sample s1, d1+d2 for sample s2, d1+d2+d3 for sample s3, etc. 12 Analysis variables Path xy The distance moved (in mm) up to the current sample projected on the x-y plane. Figure 26 Example of Path xy. Dark dots are the projection of the samples on the x-y plane. Path xy equals: d1 for sample s1, d1+d2 for sample s2. d1+d2+d3 for sample s3, etc. 12 Analysis variables Path xz The distance moved (in mm) up to the current sample projected on the x-z plane. Figure 27 Example of Path xz. Dark dots are the projection of the samples on the x-z plane. Path xz equals: d1 for sample s1, d1+d2 for sample s2, d1+d2+d3 for sample s3, etc. 12 Analysis variables Tortuosity 3d Equals the value of Path 3d divided by the length of the straight line connecting the starting sample of the block and the current sample. Tortuosity 3d is a dimensionless number. It can only be equal to or larger than 1. When the samples in a block form a perfectly straight line, tortuosity is 1. Figure 28 Example of Tortuosity 3d. l3 is the straight line connecting the starting sample of the block and sample s3. See also Figure 25. Tortuosity 3d for sample s3= (d1+d2+d3)/ l3 12 Analysis variables Tortuosity xy Equals the value of Path xy divided by the length of the straight line connecting the projection of the starting sample of the block and the current sample on the x-y plane. Tortuosity xy is a dimensionless number. It can only be >= 1. Figure 29 Example of Tortuosity xy. l3 is the straight line connecting the projection of the starting sample of the block and the sample s3 on the x-y plane. See also Figure 26. Tortuosity xy for sample s3= (d1+d2+d3)/ l3. 12 Analysis variables Tortuosity xz Equals the value of Path xz divided by the length of the straight line connecting the projection of the starting sample of the block and the current sample on the x-z plane. Tortuosity xz is a dimensionless number. It can only be >= 1. Figure 30 Example of Tortuosity xz. l3 is the straight line connecting the projection of the starting sample of the block and the sample s3 on the x-z plane. See also Figure 27. Tortuosity xz for sample s3= (d1+d2+d3)/ l3. 12 Analysis variables Speed Velocity x The component on the x axis of the velocity vector calculated for the current sample. This vector is calculated from a number of samples around the current one using a cubic spline function (see page 98). Velocity x is expressed in mm/s and can be negative or positive: Positive values when the animal is moving in the positive direction of the x axis (the x coordinate is increasing), negative in the other case. Figure 31 Example of Velocity x. For each sample sk a velocity vector vk is computed. Velocity x is the component of vk on the x axis. 12 Analysis variables Velocity y The component on the y axis of the velocity vector calculated for the current sample (see Speed on page 98). Velocity y is expressed in mm/s and can be negative or positive: Positive values when the animal is moving in the positive direction of the y axis (the y coordinate is increasing), negative in the other case. Figure 32 Example of Velocity y. For each sample sk a velocity vector vk is computed. Velocity y is the component of vk on the y axis. 12 Analysis variables Velocity z The component on the z axis of the velocity vector calculated for the current sample (see Speed on page 98). Velocity z is expressed in mm/s and can be negative or positive: Positive values when the animal is moving in the positive direction of the z axis (the z coordinate is increasing), negative in the other case. Figure 33 Example of Velocity z. For each sample sk a velocity vector vk is computed. Velocity z is the component of vk on the z axis. 12 Analysis variables Speed The scalar, absolute value of the velocity vector in the 3D space. The velocity vector is calculated for each sample sk with one of the following formulas, according to how many samples are present around it. When only 1 sample sk-1 occurs before sk: Velocity vk = (pk - pk-1)/ (tk - tk-1). When 1 sample sk-1 occurs before and another sk+1 occurs after sk: Velocity vk = (pk+1 - pk-1)/ (tk+1 - tk-1) When more samples are available around sk (as in most cases): Velocity is the value of the derivative of a cubic spline function through all samples of that block, at sample sk. Figure 34 Example of Speed. vk is the velocity vector calculated for each sample sk. See the text for details. 12 Analysis variables Where p is the X,Y,Z coordinates and t is the time of the sample. Speed is expressed in mm/s, and can only have positive values. Speed xy The scalar, absolute value in mm/s of the component of velocity on the x-y plane. It is calculated with the formula of the Pythagorean theorem from Velocity x and Velocity y. Speed xy is expressed in mm/s. Because of the way it is defined, Speed xy can only have positive values. Figure 35 Example of Speed xy. Speed xy is the absolute value of the vector obtained from the components of vk on the x-y plane. 12 Analysis variables Heading Angles Track xv The angle in the 3D space formed by the velocity vector vk (see Speed above) and the x axis. Track xv is expressed in degrees and can only be positive, no matter wether the animal is moving to higher or lower y or z values. Frequent angles being around 90 degrees may indicate cross-wind flight. Because Track3D assumes the wind is going in the direction of the x axis defined in calibration, it follows that: When the animal is pointing exactly against the wind (less positive x values), then Track xv =0. When the animal is pointing in the same direction as the wind, Track xy = 180. Contrary to Course xv (see page 102), Track xv does not consider any effect of the air flow inside the test chamber. Figure 36 Example of Track xv. Note that the angle formed by the velocity vector and the x direction can lay on any plane passing by x, depending on the orientation of the vector. 12 Analysis variables Track xy The angle in the x-y plane formed by the component of the velocity vector vk on the x-y plane and the x direction. Track xy is expressed in degrees and can be positive or negative: Positive when the y component of the velocity vector is positive (like in the figure above, where the animal is moving to the right, that is, to higher values of the y coordinate), negative in the opposite cases. Note: When the animal points exactly against the wind (less positive x values), then Track xy =0. When the animal points exactly to the same direction as the wind, Track xy = 180. When the animal moves along the x axis, Track xy may have very different values for adjacent samples, for example -170 at time k and + 170 at time k+1. The change in Track xy (= Angular change xy) is not 170-(-170) = +340, but 20 like in circular statistics. Figure 37 Example of Track xy. 12 Analysis variables Track xz The angle in the x-z plane formed by the component of the velocity vector vk on the x-z plane and the x direction. Track xz is expressed in degrees and can be positive or negative: Positive when the z component of the velocity vector is positive (like in the figure above, where the animal is moving to higher values of the z coordinate), negative in the other cases. Course xv It is calculated as Track xv, but considering the effect of air speed and direction. It is essentially the heading direction from the point of view of an observer who would move with the air. First consider the vector 'Heading relative to air', which is the 'intended' velocity and direction of movement in absence of wind. The actual heading is the resultant of this vector and the wind velocity vector. Figure 38 Example of Track xz. 12 Analysis variables Course xv is the angle in the 3D space formed by the vector 'Heading relative to air' and the x direction (see Figure 36 for an example - the vector 'Heading relative to air should replace vk). Course xv is expressed in degrees and can only be positive. Course values are calculated assuming that the wind direction is the same as the x axis. If you have made a calibration with the origin closer to the downwind screen, the wind direction is opposite to the x axis Figure 39 Course is synonymous of Heading relative to air. Track is the Actual heading. Figure 40 Example of Course xv. 12 Analysis variables direction. To obtain correct values of course, enter a negative value of wind speed (see page 64). Course xy It is calculated as Track xy, but considering the effect of air speed and direction. Course xy is expressed in degrees and can be positive or negative: Positive when the y component of the velocity vector is positive (like in the figure above, where the animal is moving to higher values of the y coordinate), negative in the other cases. Course values are calculated assuming that the wind direction is the same as the x axis. If you use a calibration with the origin closer to the downwind screen than to the upwind screen, the wind direction is opposite to the x axis direction. To obtain correct values of course, enter a negative value of air speed (see page 64). Figure 41 Example of Course xy. 12 Analysis variables Course xz It is calculated as Track xz, but considering the effect of air speed and direction. Course xz is expressed in degrees and can be positive or negative: Positive when the z component of the velocity vector is positive (like in the figure above, where the animal is moving to higher values of the z coordinate), negative in the other case. Course values are calculated assuming that the wind direction is the same as the x axis. If you have made a calibration with the origin closer to the downwind screen, the wind direction is opposite to the x axis direction. To obtain correct values of course, enter a negative value of air speed (see page 64). Drift xv It is calculated as the difference Track xv - Course xv. It is the change in the heading angle in the 3D space, due to the wind. Drift xv is expressed in degrees and can only be positive. Drift values are calculated assuming that the wind direction is the same as the x axis. If you have made a calibration with the origin closer to the downwind screen, the wind direction is opposite to the x axis Figure 42 Example of Course xz. 12 Analysis variables direction. To obtain correct values of drift, enter a negative value of air speed (see page 64). Drift xy It is calculated as the difference Track xy - Course xy. It is the change in the heading angle in the x-y plane, due to the wind. Drift xy is expressed in degrees and can be positive or negative, with the same sign as Track xy and Course xy for the same sample. This is because the wind direction coincides with the x direction, so Track xy Figure 43 Example of Drift xv. Figure 44 Example of Drift xy. 12 Analysis variables cannot be on the other side of the x axis relative to Course xy and vice versa. Drift values are calculated assuming that the wind direction is the same as the x axis. If you have made a calibration with the origin closer to the downwind screen, the wind direction is opposite to the x axis direction. To obtain correct values of drift, enter a negative value of air speed (see page 64). Drift xz It is calculated as the difference Track xz - Course xz. It is the change in the heading angle in the x-z plane, due to the wind. Figure 45 Example of Drift xz. 12 Analysis variables Drift xz is expressed in degrees and can be positive or negative, and has the same sign as Track xz and Course xz. Drift values are calculated assuming that the wind direction is the same as the x axis. If you have made a calibration with the origin closer to the downwind screen, the wind direction is opposite to the x axis direction. To obtain correct values of drift, enter a negative value of air speed (see page 64). Angular Changes (turns) General information Contrary to heading variables, which are calculated from velocity vectors, angular changes are calculated from the coordinates of the samples. In Track3D, any turn to the right of the segment joining sk to sk-1 results in a positive angular change for the sk sample point. Any turn to the left results in a negative value. This is independent of the direction of movement (e.g. towards lower/higher values of x). Figure 46 Please take this picture into account when interpreting angular change values. 12 Analysis variables Ang. ch. xv Stands for Angular change xv. It is calculated as the difference between the angles in the 3D space formed by the segments joining sk to sk-1 and sk to sk+1, and the x direction (see the figure below). Angular change xv can also be seen as: Figure 47 Example of Angular change xv. Figure 48 Example of Angular change xv calculated by translating the vector sk - sk+1 in such a way that it starts from sk-1. (the translated point s'k+1 is shown in grey). Angular change xv is the difference between the two highlighted angles. 12 Analysis variables Angular change xv is expressed in degrees and can be positive or negative. Its sign depends on which heading value is bigger between the two, and therefore does not contain information about the direction of movement, it gives an indication on how strongly the animal make turns (see also Track xv). Ang. ch. xy Stands for Angular change xy. It is calculated as the difference between the angles in the x-y plane formed by the projection of the segments joining sk to sk-1 and sk to sk+1 on the x-y plane, and the x direction. Angular change xy is expressed in degrees and can be positive or negative: Positive for a right turn, negative for a left turn. See also the notes on page 113. Figure 49 Left: Example of Angular change xy. Right: The angles formed by the segments sk-sk-1 and sk-sk+1 with the x direction are both positive (right turns). The difference is positive. 12 Analysis variables Ang. ch. xz Stands for Angular change xz. It is calculated as the difference between the angles in the x-z plane formed by the projection of the segments joining sk to sk-1 and sk+1 on the x-z plane, and the x direction. Angular change xz is expressed in degrees and can be positive or negative: Positive when the turn is towards more positive values of the z coordinate (right turn), negative in the other cases. See also the notes on page 113. Figure 50 Left: Example of Angular change xz. Right: The angles formed by the segments sk-sk-1 and sk-sk+1 with the x direction are positive and negative, respectively. Tip: rotate mentally the x-z plane in such a way that the x axis points to your right (see the picture at the bottom). You see that the first angle is positive (right turn) and the second negative (left turn). The difference is more negative (seen from the x-z plane, the overall turn is to the left). 12 Analysis variables Ang. ch. 3d Stands for Angular change 3d. It is calculated as the angle in the 3D space formed by the segment joining sk and sk+1 and the prolongation of the segment joining sk and sk-1. Angular change 3d can also be seen as: Angular change 3d is expressed in degrees and can only be positive. Figure 51 Example of Angular change 3d. Angular change 3d is the angle in the 3D space formed by the velocity vector and the prolongation of the previous velocity vector. Figure 52 Example of Angular change 3d, calculated by translating the vector sk - sk+1 in such a way that it starts from sk-1. (the translated point s'k+1 is shown in grey). Angular change 3d is the highlighted angle. 12 Analysis variables Questions About Angular Changes How are track and angular changes related? In general, angular change is the change in heading (track) between that sample and the previous, for the corresponding plane. For example, angular change xy at sample k corresponds to track xy at sample k minus track xy at sample k-1. However, when the track value changes sign from one sample to the next, Angular change follows the rule of circular statistics. For example, when the animal moves along the x axis, Track xy may have very different values for adjacent samples, for example -170 at time k and + 170 at time k+1. The change in Track xy (= Angular change xy) is not 170- (-170) = +340, but 20 like in circular statistics. In many cases there is a slight difference between angular change and the change in track. This is due to the fact that track is based on the velocity vector (see for example Track xy on page 101), while angular Figure 53 In this example, a fish is making a turn to the left. The scatterplot shows the x-y position of the fish (the arrow shows the direction of movement). For a specific sample, the value of angular change xy (leftmost column) is equal to the difference in track xy between that sample and the previous: -142 - (-126) = -16. 12 Analysis variables change is based on the actual point's coordinates. Because of the way the vector is calculated, this may not exactly overlap with the segments joining the data points. What is the difference between Angular change xv and Angular change 3d? Consider Angular change xv: Now consider, for the same data points, Angular change 3d: If we overlap the two pictures, the three highlighted angles can be seen as: 12 Analysis variables Where A = Angular change 3d, and B-C = Angular change xv. For the same reason why, in a triangle the following inequality is valid: Then Angular change 3D is always greater than or equal to the absolute value of Angular change xv. Angular Velocities Ang. vel. xv Stands for Angular velocity xv. It is the Angular change xv per time unit. It is expressed in degrees/s. Ang. vel. xy Stands for Angular velocity xy. It is the Angular change xy per time unit. It is expressed in degrees/s. Ang. vel. xz Stands for Angular velocity xz. It is the Angular change xz per time unit. It is expressed in degrees/s. Ang. vel. 3d Stands for Angular velocity xv. It is the Angular change 3d per time unit. It is expressed in degrees/s. 12 Analysis variables 3d Zones The columns Zone x ind. through Zone cyl. mark each data point with numeric codes, based on the coordinates relative to the defined three- dimensional zones. With Excel, you can easily filter those codes to analyze the data points that occur in a specific zone, or in a combination of zones. The ranges of coordinates that are assigned to a zone are open to the lower limit (low limit, high limit]. For example: If the values entered as limits of zones parallel to the z axis are 100 and 200 mm, then a data point with z=100 mm gets the code 1 for the zone (-, 100], a data point with z=200 gets the code 2 for the zone (100-200]. For a cylinder zone, if a data point falls exactly on a cylinder (boundary between two zones), it is assigned to the inner zone. For the odour plume cone, see page 65. Figure 54 The four columns in the results file mark each sample with a code indicating the presence of the data point in a 3D zone. The sixth row in the column zone z ind. marks the transition from one zone (1) to another (2). 12 Analysis variables Zone x ind. Indicates where the animal is located relative to the zones perpendicular to the x axis (see page 67). 1 - In the first zone (x ordinates below the first limit entered; 2 - In the second zone (x ordinates falling between the first and the second limit entered) 3 - In the third zone (x ordinates between the second and the third limit entered) The highest number - Last zone, with the x ordinates exceeding the highest limit entered. Zone y ind. Indicates where the animal is located relative to the zones perpendicular to the y axis (see page 69). 1 - In the first zone (y ordinates below the first limit entered; 2 - In the second zone (y ordinates falling between the first and the second limit entered) 3 = In the third zone (y ordinates between the second and the third limit entered); The highest number - Last zone, with the y ordinates exceeding the highest limit entered. Zone z ind. Indicates where the animal is located relative to the zones perpendicular to the z axis (see page 69). 1 - In the first zone (z ordinates below the first limit entered; 2 - In the second zone (z ordinates falling between the first and the second limit entered); 3 - In the third zone (z ordinates between the second and the third limit entered); The highest number - Last zone, with the z ordinates exceeding the highest limit entered. 12 Analysis variables Zone cyl. Indicates where the animal is located relative to the concentric cylinders (see page 70). 1 - In the inner cylinder (indicated by the first diameter entered); 2 - In the zone between the first and the second cylinder; 3 - In the zone between the second and the third cylinder; The highest number - Last zone, outside the outer cylinder. Example of data selection based on a cylindric zone The following picture shows the data points for a zone defined by two cylinders of 200 mm and 400 mm diameter, respectively. Figure 55 In this example, the data of a Track3D results file have been filtered in Excel (Data menu). The chart shows the y and z coordinates (like in a cross section of the wind tunnel). Data points are selected that have code =2 for zone defined by two cylinders. The cylinders have center at y=200 and z=300. The inner cylinder has a 200 mm diameter, the outer cylinder a 400 mm diameter. Because of the selection, only data points in the zone defined between the two cylinders are displayed. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 2 System Setup URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-2-system-setup Chapter: Track3D 2 System setup 2 System Setup Test Environment Track3D can be used with wind tunnels or any other test chamber with at least one transparent wall. Wind tunnel For studies of insect orientation and flight in relation to visual and odor stimuli, a wind tunnel is the optimal set up. Wind tunnels with glass walls and metal frames are not optimal for video tracking as they cause reflections. Noldus offers a complete solution with a high-quality and flexible wind tunnel, optimized for video tracking with Track3D. Our wind tunnel consists of a tracking chamber and an air flow production system. The tracking chamber is made of polycarbonate with a transparent top wall. The black infrared-absorbing walls combined with the infrared LED arrays make it ideal for tracking insects in the dark (provided that the insect body or wings reflect infrared). However, you can also track insects in daylight. Figure 3 Standard wind tunnel. Left: Air flow production system and chamber for the stimulus source. Right: tracking chamber. 2 System setup In our standard wind tunnel, the tracking chamber measures 160 x 60 x 60 cm (L x W x H), but other sizes are possible. Please contact us for more information. The air supply system consists of a fan and an air lamination diaphragm. You can set different air speeds, up to approx. 40 cm/s (with an air flow of approx. 450 m3/h. The multi-layer air lamination diaphragm ensures that air speed and direction are uniform throughout the tracking chamber. Below you find an example of the relationship between flow (in m3/h) and air speed: Note that these figures may vary slightly between wind tunnels. See the documentation that comes with your wind tunnel. For details, see Spitzen, J.; Spoor, C.W.; Grieco, F.; ter Braak, C.; Beeuwkes, J. et al. (2013). A 3D analysis of flight behavior of anopheles Figure 4 The fan with air speed control box. 2 System setup gambiae sensu stricto malaria mosquitoes in response to human odor and heat. PLoS one, 8(5), e62995, doi:10.1371/journal.pone.0062995. tip Watch the video: www.youtube.com/watch?feature=player_embedded&v=AEfK2IInWi0 Fish tanks You can use a wide range of fish tanks to reliably track fish in 3D. The fish tank you use in your experiments determines the shape and size of the calibration object. Contact Noldus if you plan to use a new type of tank. Useful web sites: www.aquaticsolutions.it/index.php www.aquatichabitats.com Large enclosures Large enclosures require custom-made calibration frames. Contact Noldus for information. Figure 5 Tracking a bat (red dots) and a moth (blue dots) in a large enclosure. 2 System setup Lighting Infrared LED arrays Use Infrared LED arrays for tracking insects in dim light or in the dark. For tracking mosquitoes in a Noldus standard wind tunnel, we recommend to use at least four LED arrays. Place the LED arrays on a frame, and point them to the downwind mesh screen. Check on the video image that shadows inside the tracking chamber are minimized. Also try to minimize the amount of light hitting the Plexiglas wall. Good lighting is crucial for a good tracking result. A good image of a wind tunnel under infrared lighting may look like the following: Figure 6 Four infrared LED arrays placed at the downwind side a wind tunnel. Figure 7 Camera view of the tracking chamber. 2 System setup Infrared backlight units For tracking fish we recommend to use backlight units. This has the advantage that it dramatically reduces reflections and thereby improves tracking. Place the fish tank directly on one unit. Place another backlight unit behind the fish tank. Video Equipment Digital cameras If you have digital cameras connected though Gigabit Ethernet (GigE), connect each camera to the labeled Ethernet port on the computer. Each camera is dedicated to a specific Ethernet port. If you switch cameras, EthoVision XT no longer detect them. Take note of which camera (serial number) is associated with which Ethernet port. For how to install and connect digital GigE Vision cameras, watch the EthoVision XT video tutorial Set Up the Cameras. To open the tutorial, in EthoVision XT choose Help > Video Tutorial. Figure 8 Sketch of a setup for zebrafish tracking. The two white boxes represent Infrared backlight units. 2 System setup Analog video cameras If you have analog video cameras, connect them via gen-lock. That is, the Video output of one camera (master) is split into two signals using a T-connector. One video signal goes to the Gen-lock In input of the other camera (slave). The other signal goes to one of the inputs of the encoder board. Camera position - wind tunnel Place the cameras in such a way that the image of the tracking chamber in your video is maximized. Make sure that the cameras are firmly attached to the walls/ceiling. To achieve good accuracy in 3D positioning of the subject, make sure that the angle formed by the camera axes is no less than 40 degrees. An angle of 90 degrees is optimal, but often cannot be obtained, for example when the markers of the calibration frame cannot be seen from one camera. If the angle is less than 30 degrees, inaccuracy in the direction of the cameras is about 4-5 times greater than it would be if Figure 9 Gen-lock camera connections. Left: master camera (video output split in two). Right: slave camera. 2 System setup the cameras are perpendicular to each other, keeping the distance between cameras equal. note There has to be enough space between the cameras and the test chamber in order to obtain a proper image on the screen. Camera position - fish tank The optimal position is: one camera at the top of the water tank (pointing below) and one at the front (see Figure 8 on page 15). Always keep the cameras perpendicular to the water tank walls. This minimizes distortions due to the water refractive index. Figure 10 The angle formed by the camera long axes should be greater than 40 degrees. 2 System setup The Calibration Object Standard calibration frame For wind tunnels, the calibration object is a black frame provided with white round markers on two planes. The frame must be placed inside the tracking chamber in such a way that all or most of the markers are fully visible to both cameras. The standard calibration frame can be of two sizes, depending on the size of the tracking chamber: 40x40x40 cm (15.75x15.75x15.75 inches). This is suitable for chambers wider than 42 cm (16.5 inches). 60x60x60 cm (23.6x23.6x23.6 inches). This is suitable for larger chambers. Figure 11 A standard calibration frame for wind tunnels. 2 System setup Two or more objects can be connected and combined to create a larger calibration object. Custom calibration frames Calibration objects for water tanks and for tracking chambers other then wind tunnels can be made upon request. Notes The X,Y,Z coordinates of the center of each marker in the real world must be known in order to have a reliable calibration. When projected on the video monitor, the markers should not be very close to each other or to bright objects in the image (minimum distance 10 pixels). When doing calibration, It is handy to have a sketch of the calibration object with markers numbered. An example is stored in the Calibration Coordinates.xls excel file on your installation disk under Documentation. Figure 12 You can connect two calibration frames to calibrate large tracking chambers. You can click all markers or some of them when doing calibration. 2 System setup Typical Setups General recommendations We advise to place the EthoVision XT/Track3D computer in a room separate from the test room. Alternatively, hang curtains around the test apparatus and the cameras. This prevents that lights in the test room, like that of the computer screen, interfere with the software detection, and ensure that the behavior of the animals is not influenced by movement and light changes outside the test environment. Using an infrared-pass filter mounted on the camera lens is not always necessary. However, in some situations external light sources interfere with subject detection and tracking by the software. If those light sources cannot be switched off, use this kind of filter to block visible light. As a result, the cameras only see the infrared light coming from the IR arrays or backlight units. Track3D setup for wind tunnels Figure 13 A typical setup for recording insects in a wind tunnel. 1 - PC with EthoVision XT, MediaRecorder (optional) and Track3D add-on. 2 - Two cameras fixed to the ceiling of the test room, connected to the PC. 3 - A number of infrared LED arrays for illuminating the tracking chamber. 4 - wind tunnel with ventilation unit and tracking chamber with transparent top plate. 5 - Calibration frame for the wind tunnel. 6 - Curtains hanging between computer and wind tunnel. 2 System setup When using infrared lights, it is important that infrared light is absorbed by the materials of the tracking chamber and of the objects around it. This will reduce reflections that can interfere with tracking. Contact Noldus for information on infrared-absorbing materials that you can use to optimize the background. Track3D setup for fish tanks Avoid placing the fish tank under reflecting objects or light sources other than the backlight units. Figure 14 Typical setup for fish in small tanks. 1 - PC with EthoVision XT and Track3D add-on. 2 - Two digital cameras connected to the PC via Gigabit Ethernet. 3 - Two infrared backlight units. 4 - Calibration frame for fish tanks. 5 - Fish tank. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 3 Software Installation URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-3-software-installation Chapter: Track3D 3 Software installation 3 Software Installation If you have ordered a complete Track3D system, the software has already been installed. You can skip this section. System Requirements For the requirements of EthoVision XT, see the EthoVision XT Help. Windows Track3D and CentroidFinder have been tested on Windows 10 Professional and Windows 11 Pro. Microsoft Excel Track3D can import EthoVision track files in the format of Microsoft Excel 2007 and later (*.xlsx). We recommend to install Excel on the computer where Track3D is installed. This makes it easier to edit the calibration files and visualize the results. EthoVision XT and MediaRecorder Track3D 2.0 makes use of the Noldus software EthoVision XT 12 or newer for video tracking, and MediaRecorder 4 or newer for saving video to high quality, synchronized digital video files. Install Track3d Follow the procedure below if you want to install Track3D on a computer other than the one you purchased from Noldus. 1. Browse to my.noldus.com, log in or register first. Under Downloads, search for Track3D. Download Track3D- Setup - 2.0.zip. 2. Create a folder on your PC's C: drive and name it MCR. 3 Software installation 3. Unzip the file and save the contents to C:\MCR. 4. Double-click MCRInstaller.exe. important During installation, change the installation destination folder is C:\MCR. When installation is finished, you find a folder named C:\MCR\v715, containing subfolders and files. 5. Right-click CentroidFinder.exe and select Send to Desktop (create shortcut). Rename the shortcut. Repeat this step with Track3D.exe so you will have two shortcuts on your desktop. Optional: Right-click each shortcut, choose Properties and click Change Icons. Select the appropriate icons on C:\MCR. 6. Run the file ebussdk3.1.14.3284.exe located on the installation drive under Utilities. Accept the default installation location and complete installation. You can download the installation files on the my.noldus web portal. 7. Plug your EthoVision XT license key in your PC. important Track3D only works with an EthoVision XT license stored on the hardware key, not a software license key! Contact Noldus if you only received a software license key. 8. Double-click the CentroidFinder and Track3D shortcuts to test the applications. You should see a black (DOS) window appearing, followed by the CentroidFinder/Track3D user interface window. 9. If the CentroidFinder and the Track3D windows do not appear or close shortly after start, make sure that the hardware key is inserted in the PC and its red LED is on, and that your EthoVision XT license includes Track3D. See also page 127. Notes To uninstall Track3D, see page 25. 3 Software installation Other Software EthoVision XT and MediaRecorder To install EthoVision XT and MediaRecorder, see the corresponding documentation. Microsoft Excel To use Track3D and CentroidFinder at best, install Excel on the computer where Track3D is installed. Paint.net We advise you to install a paint application like Paint.net, which you can download for free from the internet. Use this app to edit the calibration images in the case the markers are not detected correctly. Enable Pixel Calibration In Ethovision Xt Before using EthoVision XT for the first time, you must enable pixel calibration. With pixel calibration, the 2D coordinates of the subjects recorded in EthoVision XT will be exported in pixels rather than typical measurements units like cm. Track3D only works with pixel coordinates as input. To set pixel calibration: 1. Close EthoVision XT. 2. Browse to your Track3D installation disk, under Utilities. 3. Copy the registry entry file pixelcalibration[n].reg (n= the version number of your EthoVision XT) to a temporary location on your computer. 4. Run this file and follow the instructions on the screen. 3 Software installation Enabling pixel calibration manually You can also enable pixel calibration manually. Please do this only if you are an advanced Windows user. 1. From the Windows Start menu, select Run, type in regedit and press Enter. 2. In the Registry Editor window that appears, browse to the following location: HKEYCURRENTUSER\Software\Noldus Information Technology\EthoVision\9\Settings App. 3. If "Pixel Calibration" is not in the list of entries, from the Edit menu select New DWORD Value. Name this as PixelCalibration (mind the capital letters), then double-click it and set the value to 1. Next, close the Registry Editor window. Uninstall Track3d To uninstall Track3D, do the following: 1. Open the Windows Control Panel, and choose Programs > Uninstall a program. 2. On the list that appears, click MATLAB Compiler Runtime 7.15. 3. Click Uninstall and follow the instructions. 4. In Windows, open the folder C:\MCR and delete all its contents. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 4 Calibration URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-4-calibration Chapter: Track3D 4 Calibration 4 Calibration Why Calibration? The aim of Calibration is to provide Track3D with a system of reference parameters (Dynamic Linear Transformation parameters) that it uses to reconstruct the 3D position of the subject from the two sets of 2D coordinates obtained from the EthoVision XT video-tracking software. DLT parameters are calculated by the software CentroidFinder, using a number of calibration markers in each camera view. The output of calibration is the Calibration file, which you load in Track3D (see Figure 18 on page 59). Note - You do calibration once, provided that the cameras do not move relative to the tracking chamber. Overview Of The Procedure important Before you carry out calibration, make sure you mark the cameras "Camera 1" and "Camera 2". Always be consistent with this labeling when doing calibration and when recording the subjects. The procedure differs depending on whether you use MediaRecorder or EthoVision XT to record video. If you use MediaRecorder, see below. If you use EthoVision XT, go to step 2. 5. With EthoVision XT, create the calibration images. - If you make video with EthoVision XT, you create one image from the mixed camera view. See page 28. - If you make video with MediaRecorder, you create two images, one for each camera view. 6. Open CentroidFinder, load the calibration images and carry out calibration. See page 31. 4 Calibration Object With Mediarecorder Skip this section if you use EthoVision XT to make video. 1. Place the calibration object in the middle of the test chamber, and make sure that the cameras are switched on and connected to the PC. 2. Start MediaRecorder. 3. Click the folder button next to File location and specify where to save the video files. If your hard disk is partitioned, save the video on the D: drive. 4. In the File base name field, type the base name you want to give to the files (for example, Calibration; see the note below). 5. Make sure that Video 1 and Video 2 are selected. 6. Click the Start Recording button. 7. A couple of seconds later, click Stop Recording. Result - Two short calibration video files are created, one for camera 1 and one for camera 2. Proceed with page 29. 4 Calibration Notes The origin of the 3D coordinates in your results depends on the coordinates of the markers in your calibration reference file. The location of the origin does not influence statistics of speed and heading. However, if you want the coordinates to originate from a specific point, for example the odour release point, then you must edit the calibration reference file to adjust the coordinates of the markers relative to this point. The name of the video file consists of the File base name followed by the video input name (you can change this in the Settings window), the date and the time the videos were recorded, and the number of the video camera. For instance, if your File base name is Calibration, the date is 11 May 2011, the time 10:54:43 and you create 2 videos simultaneously, the video from the second camera is named: Calibration Video 2 11-5-2011 105443 2.avi. If you make video with EthoVision XT If you use MediaRecorder to make video, see page 29. 1. Place the calibration object in the test chamber, and make sure that the cameras are switched on and connected to the PC. For calibration in water tanks - Remove the infrared filter from the camera lens. Increase the lens aperture to obtain a bright image. 2. Start EthoVision XT and open your experiment. Make sure that in the Experiment Settings, Video source is set to Live tracking with Number of sources = 2. 3. Choose Setup > Arena Settings > New and rename it to Calibration. 4. Click Grab. If you do not see this button click the Grab background image button, then click Grab. Note - When you click Grab, EthoVision XT saves the background to a file, background.bmp (see the next step). 4 Calibration 5. With Windows Explorer, browse to the Bitmap Files folder in your EthoVision experiment folder and copy the newest background.bmp file to the location of your choice (e.g. D:\calibrations). 6. Rename this file, for example Calibration image.bmp. 7. important If you work with fish tanks and backlight units, the calibration image will be predominantly white with black markers. You must invert the colors of the image to get white markers on a black background. The final image should be like this: To do so, see edit the calibration images on page 119. 8. Load this image two times in CentroidFinder. See 3 - carry out calibration on page 31. If you make video with MediaRecorder We assume that you have made two video file with MediaRecorder. Do the following: 1. Start EthoVision XT. If you have not yet done so, create an experiment (File menu). Make sure that in the Experiment Settings, the Video Source is From video file. 2. Choose Setup > Arena Settings > New and rename it to CalibrationCamera1. 3. Click Browse and select the video file for that camera. 4. Click the Grab button. The image from the video file of that camera is pasted on the EthoVision screen. tip If you do not see this button click the Grab background image button, then click Grab. Before clicking Grab, make sure that the camera view displayed in the video file corresponds to the name of the Arena Settings profile that you have just created. If you realize that you have grabbed the 4 Calibration image from the wrong file, click the Grab Background Image button in the Arena Settings window, select the correct video file, and click Grab. note When you click Grab, EthoVision XT saves the background to a file, background.bmp (see the next step). 5. Using the File Explorer, browse to the Bitmap Files folder in your EthoVision experiment folder and copy the newest background.bmp file to the location of your choice (e.g. D:\calibrations). 6. Rename this file, for example CalibrationCamera1.bmp. 7. Repeat the steps from 2 to 4, this time choose the other video and name the bitmap CalibrationCamera2.bmp. 8. If you work with water tanks, you must invert the colors of the images to get white markers on a black background. See edit the calibration images page 119. Notes For obtaining calibration images, you do not need to draw an arena and set pixel calibration in the Arena Settings. For more information on how to make an experiment and an arena profile, see the EthoVision XT Help. Check that the markers in both calibration images are well defined, with sharp margins and well contrasting with the background. To edit the images, see edit the calibration images page 119. 4 Calibration At this point you should have two calibration bitmap files. See the previous section for how to obtain such files. 1. Insert the EthoVision XT hardware key in your computer. 2. Start CentroidFinder. The CentroidFinder window appears on the screen. 3. Click Select Images. In the window that appears, select the Calibration image file(s). - If you make video with EthoVision, load the same image two times. - If you make video with MediaRecorder, load first CalibrationCamera1.bmp, then CalibrationCamera1.bmp. 4. Click Indicate Markers below the first image. As a result, that button turns green. 4 Calibration tip To get a larger image of the calibration object, click the Zoom in button, then click and drag the mouse to select a box around the calibration object. For details see page 37. 5. Click the markers in the order pre-defined in your calibration reference file. The reference file is an Excel file containing the markers' real world coordinates, listed in a specific order. Follow that order when clicking markers in both images. When the mouse pointer hovers on the image, it turns into a black circle. Click inside the white marker. Note: - If a marker is not fully visible in that image, and visible in the other, do not click it. Rather, enter the value of the next visible marker before clicking the next visible marker. This way you tell the program that one or more markers in the sequence must be skipped for that image. See page 34 for details. 4 Calibration - If a marker is visible in that image, not in the other, click that marker as usual. - Do not click markers that are partly hidden by the calibration object, or that are too close (less than 10 pixels) to white objects in the image. When clicked, the marker is labeled with a progressive number. If you click a marker twice, take note of the number of that marker. Type this number in the field under next marker in the middle of the screen, and click that marker again. If you want to restart clicking markers on an image, click the Indicate markers button below that image. 6. After clicking a marker, the Label for next marker increases by 1. 7. Click now the following marker according to the predefined order. 8. Once you have clicked the last marker for the first calibration image, click the Indicate markers button below the other image. Repeat the procedure described at step 4. Make sure that you click the markers exactly in the same order as for the first image (see the example below). 9. After you have clicked the very last marker, click the Calculate and save button. 4 Calibration 10.A message appears: 11. An Excel Calibration file has been created in the folder where the calibration images are stored. The file is named as [name of the first image]+[Date]+[Time]. See below for information about this file. 12. Open the Calibration reference file containing the real-world 3D coordinates of the markers. This file has been provided by Noldus. Copy the values of the columns B, C, D. 13. In Excel, open the Calibration file saved in step 9 and paste the values to the columns F, G, H. This will replace the zeros with the 3D coordinates. If Excel is not installed on that PC, see also complete the calibration without excel on page 40. 14. Save the Calibration file. You will load this file in Track3D (page 60). Hidden Markers: What To Do? Marker hidden in one image If a marker is not visible in one image, and is visible in the other, enter the number of the next visible marker before clicking it. example Consider the following calibration images: 4 Calibration Each image is the top view of the calibration object from two cameras. The object is made of two horizontal frames one on top of the other (markers of the upper frame look bigger than those on the lower frame). Four markers in the left image (indicated by the arrows) are hidden by the upper frame when viewed from the other camera (right image, indicated by the brackets). Note that the image on the right is upside down - The marker number 1 has been marked with a circle). 1. If a marker is visible in one image, not the other, click it as usual. In this example, 27 and 28 are visible in image 1, not in image 2. 2. When the next marker to click is hidden, look at Label for next marker. For example, marker number 27 in the other image is hidden (see the bracket in the figure below). 4 Calibration 3. Click the number under Label for next marker and enter the number of the next visible marker. In this example, enter 29 (this is the next visible marker after 27 and 28). 4. Click the markers as usual (29, 30, 31...). Markers hidden in both images If a marker is hidden in both images, skip that marker in both images. Simply type the number of the next visible marker in the Label for next marker field. tip For easy identification of markers, make a printout of the calibration images, and write down the marker numbers. 4 Calibration Zoom In/out The Calibration Image To make the markers more visible and calibration more accurate, you can zoom in the calibration image. We recommend that you do this only before you click the Indicate markers button. 1. Click the zoom in button. 2. The mouse cursor turns into a cross. Drag the mouse to draw a rectangle around the calibration object. Pay attention to include all markers. 3. Release the mouse button. CentroidFinder only shows the portion of the image selected. 4 Calibration 4. You can now begin with clicking the markers. 5. To return to the original image, click the Zoom out button. Use Multiple Calibration Objects When using multiple calibration objects (see Figure 12 on page 19), the calibration procedure does not change. The only difference is that you have more markers to click. You can choose to click them all, or some of them (for instance, click one every two). In any case, it is handy to make a scheme of the marker numbers, like in this example: If you click a subset of markers, make sure that your calibration reference file only contains the coordinates of those markers, so you can copy those values directly to your calibration file. 4 Calibration The Calibration File The calibration file is an Excel sheet with eight columns: Note that the calibration file does not have headers. The Calibration Reference File Noldus Information Technology provides you with a Calibration reference file that matches your calibration object. Column Value Marker number B,C X and Y coordinates of the marker in the first image (in pixels) D,E X and Y coordinates of the marker in the second image (in pixels) F,G,H X, Y, Z coordinates of the marker in the real world relative to an arbitrary origin, respectively. 4 Calibration A Calibration reference file is an Excel file that contains the real-world coordinates of the markers of your calibration frame. Markers are listed in a certain order, which must match the order of clicking in CentroidFinder. Make your own calibration reference file If you like, you can create your own Calibration reference file with the markers listed in a different order. If you use two or more calibration objects combined, you can create a reference file with a sub-sample of markers to reduce the number of markers to click. To make a Calibration reference file, create an Excel file with the following columns: Column A - Marker number. Column B, C, D - Values (in mm) of the X, Y, Z coordinates of the markers, respectively. Each line corresponds to a marker. The markers must be listed in the same order as they are clicked. Do not insert headers. Complete The Calibration Without Excel If the computer where Track3D is installed does not have Microsoft Excel, CentroidFinder exports the calibration file to text (tab- delimited). You can now add the 3D real-world coordinates of the calibration markers in the following way: 4 Calibration Using Excel on another computer - Copy the calibration file to the computer with Excel. - Open the file in Excel. - Copy the 3D real-world coordinates from the calibration reference file to the last three columns of the calibration file. Those values must replace the zeroes. - Save the file as Tab-delimited text (.txt). - Load this file in Track3D. Using only text files - Open the calibration file in Windows Notepad. - Copy the values of the 3D real-world coordinates from the calibration reference file, one row at a time. - Paste them in the calibration file to the left of the first "0.000". - Remove the remaining zeroes. - Repeat the steps 2-4 above for each row. - In Notepad, choose Edit > Replace and in the Find field enter a space (press the spacebar) and leave the Replace field empty. Next, click Replace all. This will remove all the spaces. 4 Calibration 7. Save the calibration file. You can now load it in Track3D. Do Calibration Manually If for any reason CentroidFinder fails to detect the markers, you can still enter the 2D coordinates of the calibration marker. tip You can also try editing the calibration images to remove objects that interfere with marker detection. Open the images in Paint.net, and after editing save them to bitmap (with bit depth 24). 1. Open a calibration file or create one like that on page 39. Alternatively, create a new calibration file with 8 columns and as may rows as markers. 2. Enter the marker numbers in the first column and the the markers' 3D coordinates in the last three columns. 3. Open the first calibration image in an image editor that shows the pixel coordinates of images. For example, Microsoft Paint or Paint.NET. 4. Move the mouse over the center of a marker. 4 Calibration 5. Take note of the coordinates. In most cases these are reported on the status bar at the bottom of the screen. 6. Enter the X and Y coordinates in the second and third column (for the calibration image 1) or the 4th and fifth column (for the calibration image 2) of the calibration file, respectively. Fill in the row that corresponds to that marker number! 7. Repeat the steps 4 to 6 for all markers and both the calibration images. 8. Save the file (Excel or text). Next, load this file in Track3D as the calibration file (see page 60). Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 5 Recording Video URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-5-recording-video Chapter: Track3D 5 Recording Video 5 Recording Video Video Quality Is Important Track3D works at its best with high quality digital media files. The video tracking software EthoVision XT must be able to distinguish the image of the animal from the background to calculate its position and measure its behavior. Several factors influence the ability of EthoVision to find and track a moving object, among which the lighting conditions are the most important. In order to optimize detection of the animal, before you carry out your experiments it is wise to record a few trial videos where the animal moves in different parts of the test chamber, and use those videos in EthoVision to see where and when detection is not optimal. Next, adjust lighting and background characteristics to improve detection. Always use the same software to record video for calibration and for video-tracking. Record Video With Ethovision Xt With EthoVision XT you can record video from the two cameras to a single video file of resolution 1280 x 480. (640x480 per camera image). Preparing the experiment for video recording - Start EthoVision XT and open your experiment. We advise you to create an EthoVision XT experiment for recording video only. Name this experiment for example Video recording. In this experiment you do not need to adjust settings like Arena Settings, Detection Settings etc., since you use this experiment only for video recording. For video tracking, create a separate experiment (for details see page 48). - Make sure that in the Experiment Settings, Video source is set to Live tracking with Number of sources = 2. 5 Recording Video - Choose Setup > Arena Settings > New. - Right-click the Arena Settings window, just below the Validate Setup button, and select Set pixel calibration on. - Click OK. You are ready to record video. Recording video - Choose Acquisition > Open Acquisition. - In the Acquisition Settings window, select Save video only, track later. Click OK on the message that appears. - Click the Start trial button (Ctrl+F5). Result The video is saved in the Media Files folder of the Video recording experiment. The default file name is Trial 1, Trial 2, etc. Always keep a copy of your videos in a safe place. 5 Recording Video Record Video With Mediarecorder With MediaRecorder you can record video from the two cameras to separate video files of resolution 1280 x 960. Recording video - Make sure that the cameras are powered, and that the Video output of each video camera is connected to your PC. - Start MediaRecorder. - Make sure that Video 1 and Video 2 are selected. - Click the folder button next to File location and specify where to save the video files. Make sure that you have enough disk space to save video. On average, one video file takes about 10 MB per minute of recording. - Under File base name, type a generic (prefix) name for the two files. For example, CO2 test. The program will use this prefix to name the two video files. 5 Recording Video - Start recording by clicking the Start Recording button. Release the animal into the test chamber. - To stop recording, click the Stop Recording button. The two files, one per video input, are created. Result The name of the video file consists of the File base name followed by the video input name (you can change this in the Settings window), the date and the time the videos were recorded, and the number of the video camera. For instance, if your File base name is CO2 test, the date is 11 May 2011, and the time 10:54:43, the video files are named: CO2 test Video 1 11-5-2011 105443 1.avi (for Camera 1) and CO2 test Video 2 11-5-2011 105443 2.avi (for Camera 2). 6 The EthoVision XT experiment for Track3D 6 The EthoVision XT Experiment For Track3D In this chapter you find how to create an EthoVision XT experiment for video-tracking. For creating an EthoVision XT experiment for video- recording, see page 44. Make sure that Pixel calibration has been enabled (see page 24). This section contains only the very basic settings that you must adjust in EthoVision. You can customize your experiment in various ways, for example adding trials and independent variables. For more information, see the EthoVision XT Help. Experiment Settings - In EthoVision Xt, create a new default experiment (File > New). Give this experiment a name. - Click Experiment Settings. - Select: - Under Video Source, From video file. - Under Arenas, next to Number of Arenas select 1. - Under Subjects, next to Number of Subjects per Arena select 1. - Under Units, next to Unit of distance select mm. - Continue with the next section. Note The settings described above make it possible to track from one camera view (= Arena) at a time. If you have the Multiple Arena module, you could in principle select 2 under Arenas, so you can track from both camera views at the same time. However, this has the limitation that when you do the tracking, you must use the same Detection Settings for both camera views. In some cases the lighting conditions differ between camera views, so that the same Detection Settings may not 6 The EthoVision XT experiment for Track3D be optimal for each camera. For example, when the contrast between animal and background is lower in one camera. In all those situations we advise to select Number of Arenas =1, and define separate Detection Settings for the two camera views. Then, do the tracking for one camera view at a time. Arena Settings Drawing the arenas - Choose Setup > Arena Settings > New. Enter a name (for example Camera 1 or Camera 2, depending on which camera you use to draw this arena). - Click Browse to select the video file(s) depending on your setup: - If you make video with EthoVision XT, you have one video file for both camera views. Choose this file. - If you make video with MediaRecorder, you have one file per camera view. Select the file that applies. Click Grab. - Right-click the Arena Settings window, just below the Validate Setup button, and in the message window Set pixel calibration on, click OK. Note - If the message says Set pixel calibration off, it means that calibration is already set to pixel. Click Cancel. 6 The EthoVision XT experiment for Track3D 4. Click 2. Select Shape and Draw the Arena. Draw the arena and make sure that the label points to inside the arena. 5. Repeat the steps 1-4 for the second camera. Result You should have two arena settings in your experiment explorer (and two more for calibration that you created earlier, see page 28). Notes If you work with the Multiple arena module, you can draw two arenas in the same Arena Settings. With pixel calibration: The origin of the 2D space is the upper left corner of the video. The x-axis points to the right, and the y-axis points downward. The X,Y coordinates of the tracked subjects will be exported in pixels (with decimals). This is an important prerequisite of Track3D. For more information See Arena Settings in the EthoVision XT Help. Trial Control Settings Adjust the Trial Control Settings to start tracking immediately when you press the Start Trial button, for both camera 1 and camera 2. This ensures that the resulting tracks are synchronized. 6 The EthoVision XT experiment for Track3D Removing the start track condition - Choose Setup > Trial Control Settings > Open (or see 1 in Figure 15). - Click the second box in the sequence, named Condition In Zone (1), then press Delete. - Point the mouse pointer to the center of the first box (Rule Begin - Start-stop trial), click and drag to the center of the next box (Action - Start track). The two boxes are connected again. For more information See Trial Control in the EthoVision XT Help. Figure 15 Adjust the Trial Control rule to ensure synchronization between the tracks of camera 1 and camera 2. 6 The EthoVision XT experiment for Track3D Detection Settings Premise In most cases you need two Detection Settings, one for camera 1 and one for camera 2. The reason is that the light conditions might differ slightly between camera views, requiring slightly different detection settings. Creating Detection Settings for one camera view - Make sure that the arena settings for the camera you want to use is highlighted in blue in the Experiment Explorer. - Choose Setup > Detection Settings > New. Enter a name (for example, the name of the camera that you are going to use) and click OK. - In the Detection Settings window, under Video, click Select Video and choose the video file for that camera view (if it is not already selected). If you make video with EthoVision XT, you have one video file for both camera views. Select this video file. - Choose the sample rate. For the best results choose the maximum value attainable. (25 (for PAL) and 29.97 (for NTSC) for analog cameras, 30+ for digital cameras). - In the Detection Settings window, click Automated Setup and follow the instructions. - If detection is not good, in the Detection Settings window, click Advanced, then: - Choose the Detection method (Dynamic Subtraction is recommended; for difficult tracing choose Differencing). - Adjust the contrast if needed. For example, for mosquitoes filmed under IR light conditions, the subject is white on a dark 6 The EthoVision XT experiment for Track3D background. Therefore, choose Brighter. When the animal is detected, it is marked with a red dot. - Under Subject Size, enter the Minimum and Maximum subject size. Specify the values in such a way that all groups of pixels smaller than the subject's apparent size (such as system noise) or larger (for instance, reflections) are not confused with the animal. 7. When the subject is well detected, click Save. Repeat the procedure to create Detection settings for the other camera view. Result You should have two Detection Settings: Notes Make sure that when the animal is not in the arena, EthoVision does not detect any object as the subject. You can see this at the beginning of the video: if the red track jumps from one point to another in the image, it means that it considers pixels of the arena as the subject. Reduce the contrast range, until the red track disappears. For more information See Configuring Detection Settings of the EthoVision XT Help. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 7 Video-tracking URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-7-video-tracking Chapter: Track3D 7 Video-tracking 7 Video-tracking Important Things To Know Prepare the experiment Before you acquire data, make sure that the EthoVision experiment you use for video tracking is optimized for Track3D: The measurement unit is mm (see page 48). The arena is set to pixel calibration (page 49). Trial Control does not have the start track condition (page 50). Trials vs. tracks In EthoVision XT, each data acquisition session is called a Trial. You start a trial when you click the Start trial button. The set of 2D x,y coordinates of the animal's center point in each arena during one trial is called a track. How many trials per subject? It depends on how many Arena Settings you defined. Here we assume that one subject is tracked at a time. If you defined two Arena Settings, one for each camera view (where each Arena settings containing one arena; recommended), then you acquire two trials per subject. - One trial for camera 1, using the Arena Settings for camera 1. - One trial for camera 2, using the Arena Settings for camera 2. Each trial contains one track for that camera view. In most cases you also use different detection settings for different camera views. 7 Video-tracking If you defined one Arena Settings profile with two arenas, then you acquire data from both camera views simultaneously, in one trial per subject. The trial contains two tracks, one for Arena 1 (camera 1) and one for Arena 2 (camera 2). Figure 16 Typical scenario when using two arena settings profiles. Figure 17 Example of using one arena settings profile. 7 Video-tracking Tracking multiple subjects in the same chamber If you have two subjects in the same chamber (for example, bat and moth), then you have two tracks per trial. Video-tracking Procedure - Choose Acquisition > Open Acquisition. - Make sure that the correct Arena Settings, Trial Control Settings and Detection Settings are selected in the Acquisition Settings window (for example, Arena Settings Camera 1 if you are about to track from the video of camera 1). To activate a settings profile, right-click it in the Experiment Explorer and select Set as Current. 3. If necessary, add a trial. 4. In the Acquisition Settings window, click the button next to Video to select the video file you want to use (if that video file not yet shown in the Video window). 5. Position the video to the time or frame where you want to start. You can do this by using the Step forward/backward buttons to play the video frame-by-frame. Take note of the time/frame number when the subject becomes visible in both videos, and use this as starting point. After tracking from the video of camera 1, when you open the video for camera 2, make sure that you position that video exactly on the same time or frame number, otherwise the two tracks will be out of sync when you combine them. - You can check the time/frame number in the lower right corner of the Video window. - To show frame numbers, right-click the Video window and select Position in frames. 6. Make sure that the option DDS is selected in the Playback Control window. 7 Video-tracking 7. Click the Start trial button or press Ctrl+F5 to start acquisition. 8. To stop acquisition, click the Stop trial button or press Ctrl+F6. The trial stops automatically at the end of the video file. 9. Repeat the procedure from step 2 for the video of the other camera. Notes After you have acquired data, the Arena Settings, the Trial Control Settings and the Detection Settings used for that trial become read-only to prevent accidental changes to the settings that would invalidate your data. If you want to edit the settings, make a copy of them. Right-click the settings profile in the Experiment Explorer, select Duplicate, and rename the new settings profile. Next, make the necessary changes to the settings. To visualize the tracks in 2D, from the Analysis menu select Results, Plot integrated data. To delete a track, delete its trial. In the Experiment Explorer, under Acquisition, Acquired Trials right-click that trial and select Delete. Visualize The 2d Tracks To visualize the 2D tracks, choose Analyze > Results > Plot Tracks. For more information on how to analyze tracks in 2D, see the EthoVision XT Help. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 8 Export The 2D Tracks URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-8-export-the-2d-tracks Chapter: Track3D 8 Export the 2D tracks 8 Export The 2D Tracks Export Procedure You must export the 2D tracks from EthoVision XT before using Track3D. 1. Optional - To export part of your tracks, choose Analysis > Data Profile, and filter the trials you want to export to Track3D. For more information, see Filter tracks in the EthoVision XT Help. 2. Choose Analysis > Export > Raw Data. 3. Make sure that Track and dependent variables is selected. 4. Under Export Settings, click Browse and specify the folder where you want to save the export files. 5. Select one of the two File type options: - Excel if your computer has Microfoft Excel installed. - ANSI text in all the other cases. 6. Click Start Export. Notes The export data files are named as follows: Raw data + [name of experiment] + [trial number].xlsx EthoVision exports all the tracks contained in the Data Profile currently active. If you want to export some tracks, not others, click the Data Profile in the Experiment Explorer and filter the tracks you want to export. You can for example select all tracks corresponding to a treatment, or those acquired on a particular day. For more information, see the EthoVision XT Help. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - 9 Running 3D Analysis URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-9-running-3d-analysis Chapter: Track3D 9 Running 3D analysis 9 Running 3D Analysis Overview In this chapter you find the procedure for importing the 2D data in the Track3D software and obtaining the results, both graphical and numerical. What you need now is: The input data files (*.xls, *.xlsx, .txt) - Containing the X,Y (2D) coordinates from the two camera views. The calibration file (.xls, .xlsx) - Containing the calibration data (see page 39). Make sure that the EthoVision XT hardware key is plugged in one of the USB ports of your computer. At the end of this procedure, for each pair of input data files you obtain: An output file (.xls). A 3D chart (that you can export as a picture file). Figure 18 Track3D receives the input files from EthoVision XT and the Calibration file from CentroidFinder. 9 Running 3D analysis Analysis Procedure - Start Track3D. The Track3D window opens. Together with the Track3D window, another (DOS command) window appears. Do not close this window. 2. Make sure that the settings in Track3D correspond to what you require (see Settings in Track3D on page 64). 3. Under Analysis, select: - New calibration if you want to use a calibration file different from that used the last time you ran analysis. 9 Running 3D analysis - Old calibration to retain the last used calibration. To be able to use the Old calibration option, make sure that the old calibration file is stored where Track3D is installed (C:\MCR). Next, click Start calculations. 4. If you have selected New calibration, the Select calibration file window opens. Select the calibration file (this is the file created with the procedure on page 31) and click Open. Result - Three windows appear one on top, named with progressive numbers (Figure 1, Figure 2, etc.). Those images illustrate the quality of calibration (see page 124 for details). If you have selected Old calibration, go to the next step. 5. The One or two input files window appears. - Click One combined file if you combined the track files from the two cameras into one. - Click Two separate files if you use the original track files exported from EthoVision XT. 6. The Select input from camera 1 window opens. Select the file you require (available formats: *.xls, *.xlsx, *.txt) and click Open. Next, the Select input from camera 2 window opens. Select the file you require and click Open. Make sure that the camera view of the first file corresponds to that of the first calibration image, and that the camera view of the second file corresponds to that of the second calibration image. 9 Running 3D analysis If you selected One combined file in the previous step, you are asked to select the combined input file (available formats: *.xls, *.xlsx, *.txt). 7. The Save file window opens. In this window you can specify where to save the results data file (see page 85). Browse to destination folder and enter a name for the file, then click Save. By default, the file name is out_3d.xls and is saved in the same folder as that of the Track3D software. 8. The Statistics window appears. This lists the percentage of missing samples found in the input data for camera 1 and camera 2 and in total (camera 1 OR camera 2). 9. Click OK. A new window "Figure n" appears showing the subject's trajectory in 3D. Notes If you encounter issues and error messages, see the Troubleshooting section for Track3D on page 127. The Track3D output file is saved in Excel format (*.xls) or text format if Excel is not installed on the PC. If the results file with that name already exists in the destination folder, the program asks whether you want to replace it with the new version. The name of the chart window is "Figure n" where n is an increasing number. In the Statistics window the total percentage of missing samples may be higher than the sum of the values for camera 1 and 2. This 9 Running 3D analysis can be due to the clean up input settings. A low Maximum intersection error (page 74) results in excluding several (non- missing) data points. What next? Look at the 3D chart and animate the track (see page 76). Create a video of the track (see page 82). Open the results file (see page 85). 10 Settings in Track3D 10 Settings In Track3D Lenses Additional lenses correction (optional) Under Lenses, select Perform lens correction if you want to correct for lens distortion (see page 120). If you do not want to perform lens correction, clear this option. Lens correction is necessary if the lenses you use have a significant barrel distortion ("fish-eye" effect). If you use rectilinear lenses, keep this option de-selected. Air Speed Click the Air speed button. Under Air speed, enter the estimated speed (in mm/s) of the air flow in the test chamber (if known), otherwise enter 0. 10 Settings in Track3D Odour Plume Click the Odour plume button. If the test is performed with an odour plume, and you want to analyze the data of the subject relative to the odour plume, select Include odour plume. Under Cone top position, enter the X, Y and Z coordinates of the vertex of the cone (the release point of the odour; see Figure 19). Under Axis point position, enter the X, Y, and Z coordinates of the point that, together with the top position (vertex), defines the axis (and therefore the orientation) of the cone. Next to Cone angle (degrees), enter the angle in degrees that determines the aperture of the cone. Enter the Number of circles you want to visualize in the 3D chart (see Figure 19). Next to Buffer zone width, enter the width in mm of the buffer area. This generates a second cone external to the main one. 10 Settings in Track3D Selecting this option results in the test chamber being divided in three spaces: (a) a cone representing the odour plume in the test chamber, (b) a buffer zone around the cone, and (c) the remaining space. The coordinates' origin and axis orientation are those indicated by your calibration (see Calibration on page 26). Figure 19 Representation of the odour plume in 3D. To draw the cone, enter the coordinates of the Cone top position and the Axis position points. Those points define the cone axis. You can also define a buffer zone around the cone by entering the zone width. The points of the 3D track will be displayed in different colors depending on in which zone they are: within the cone, in the buffer zone or outside the buffer zone. In this example the cone's main axis is placed horizontally. If you want the cone's axis to be oblique, for example when the odour plume points upward, then follow the note on page 122. 10 Settings in Track3D 3d Zones Use this option to analyze the data in relation to the position of the subject in one or more three-dimensional zones of the tracking chamber. Click the Zone indication button. In the Zone indication box, select one or more of the following: Note that the axes and the position of the origin point are those defined by your calibration. Zones separated by planes perpendicular to x axis Choose this option to divide the tracking chamber in two or more regions, separated by planes perpendicular to the x axis (wind direction). 10 Settings in Track3D Enter the values of distance D from the x axis, separated by blank spaces. For example, entering 100 and 200 will define three zones: A - Within 100 mm from the vertical plane passing through the origin. B - Between 100 mm and 200 mm from the same vertical plane. C - Between 200 mm from the same vertical plane and the other end of the tracking chamber. 10 Settings in Track3D Zones separated by planes perpendicular to y axis Choose this option to divide the tracking chamber in two or more regions, separated by horizontal planes. Enter the values of distance D along the y axis, separated by blank spaces. For example, entering 200 and 400 will define three zones: A - Within 200 mm from the vertical plane passing through the origin. B - Between 200 mm and 400 mm from the same vertical plane. C - Between 400 mm from the same vertical plane and the other end of the tracking chamber. Zones separated by planes perpendicular to z axis Choose this option to divide the tracking chamber in two or more regions, separated by planes perpendicular to the z axis. Enter the values of distance D from the x axis, separated by blank spaces. For example, entering 200 and 400 mm will define three zones: A - Within 200 mm from the horizontal plane passing through the origin *(this is usually the bottom of the wind tunnel). B - Between 200 mm and 400 cm from the same plane. 10 Settings in Track3D C - Between 400 cm from the same plane and the other end of the tracking chamber. Note - Track 3D marks each 3D data point depending on in which zone it is located. It does not analyze or visualize those points based on the 3D zones. To analyze the data points in this way, filter the results file with Excel using the zone codes (see page 116). Cylindric zones Choose this option to divide the tracking chamber in concentric cylinders.Enter the coordinates of the center of the cylinder (Point on axis), the Slope relative to the x axis (in degrees; default = 0, which means that the cylinders are parallel the x axis), and the values of diameter of each cylinder, separated by blank spaces (Diameters, in mm). For example, entering 200 and 400 mm will define three zones: A - A cylinder with diameter 200 mm. B - A zone between two cylinders of 200 mm and 400 mm diameter. C - A zone including all space out of zone B. 10 Settings in Track3D Interpolation Click the Interpolation button. Select Perform interpolation if you want to replace missing samples in the input file (with 2D data) with values obtained by interpolation using adjacent valid samples. Enter the maximum number of successive missing samples acceptable within a block. 10 Settings in Track3D Notes Interpolation is applied after clean up input (page 74). Missing samples are missing X,Y coordinate values in the input data files. They occur when EthoVision cannot detect an object using the current detection settings. For example, when the animal is out of the camera view. Here you can choose whether to replace missing samples with interpolated data. If you decide not to perform interpolation, the missing bits of the track are visualized as blue dashed lines. If missing samples occur in trains, with one missing sample immediately following another, performing interpolation makes little sense as the longer time between adjacent valid samples reduces the predictive power. You can prevent this from happening by entering the maximum number of successive samples to be interpolated. Example - An input data file contains three consecutive missing samples for camera 1. To interpolate those samples, enter 3 or a higher value. If you enter a value smaller then 3, the missing samples will not be interpolated. The data before and after those samples will be considered in two different blocks. Missing samples that are not interpolated are not included in the output file. 10 Settings in Track3D Filtering (track Smoothing) Click the Filtering button. Select Perform filtering if you want to replace the raw coordinates with values obtained with a lowpass Butterworth filter (see page 123). Note that Filtering does not reduce the number of samples in your input data set Select 2D if you want to smooth the 2D data, that is, the X and Y coordinate values obtained from EthoVision. Select 3D if you want to smooth the 3D data, that is, the calculated X, Y, Z coordinates values (that is, the values you find in the output file). If you select this option, the output file always contains the smoothed data, not the original 3D data. For both options specify: - Filter order - Enter the order of the spline interpolation function. - Cut off - Enter the cut off frequency (in Hz). Apparent movements with frequency higher then the value you enter are 10 Settings in Track3D smoother out. The lower the cutoff value, the smoother the resulting line. By default, 2D and 3D are selected with filter options: Filter order = 2, and Cut off = 8. Next to Frame rate (fps), enter the sample rate you used for tracking with EthoVision. More details on page 123. Clean Up Input Choose this option to remove artifacts and less reliable data points. Click the Clean up input button. Enter the following: Maximum change of any coordinate in successive frames is - Enter the maximum distance (in pixels) between two successive samples that you want to consider as valid. Use this function for example to exclude samples that are so far from each that they likely result from bad detection (see an example below). Maximum intersection error is - The program checks whether Ethovision tracked the same object at every sample. This is done by comparing the ideal lines that join each camera lens and the tracked object. If the EthoVision tracked different objects from the two cameras (for example, the actual animal from Camera 1 and a 10 Settings in Track3D reflection from Camera 2), the two lines do not intersect. You can remove such instances entering a maximum distance (in pixels) between the two lines. Notes Clean up input removes samples from your input data set. Because interpolation (see page 71) is applied after removing those samples, a different clean up setting (for example a lower Maximum intersection error) results in different values of x,y,z coordinates and output parameters. If you enter a small Maximum intersection error value, you take the risk of excluding good samples. A high value makes it more likely to include false detections in the 3D tracks. Run analysis a few times, each with a different maximum intersection error and compare the charts. If you need to enter a large maximum intersection error to obtain good results, it could be due to the fact that the calibration is not valid anymore, for example a camera may have been moved in the meantime. Make a new calibration and specify this in analysis (page 60). Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - A Special Features And Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-a-special-features-and-notes Chapter: Track3D A Special features and notes A Special Features And Notes Edit The Calibration Images Make a white marker well detectable When one or more markers is not detected properly during calibration. For example, when a marker is too close to a bright object, the blue cross symbol is placed far from the center of the associated marker. This means that CentroidFinder also includes at least part of the bright object in the detected marker. Do the following: 1. Open the calibration image in a program like Paint or Paint.net and remove the bright regions around the markers. 2. Save the image with a new name. Choose BMP (bitmap) as file type and choose 24 as Bit Depth. 3. Repeat the steps above for the second calibration image. 4. Re-do calibration using the new images. For water tanks: invert the colors When filming the calibration frame in water tanks, the calibration markers appear black over a white background. You must convert the image to one where the markers appear white over a black background. 1. In Paint.net, open the calibration image and choose Adjustments > Invert colors. 2. Select Adjustments > Brightness/ Contrast. 3. Adjust the values to increase the white/black contrast. A Special features and notes If necessary, remove the white spots that are too close to the markers. The image should look like this: 4. Save the image with a new name. Choose BMP (bitmap) as file type and choose 24 as Bit Depth. 5. Re-do calibration using this new image. Additional Lens Correction Distortion is a divergence from rectilinear projection of an object on a video image. In a rectilinear projection, straight lines in a scene remain straight in a video image. If the level of barrel distortion (fish eye effect) in your video image is not acceptable, you can enter values of focal length, principal point and radial corrections in Track3D. To obtain such values for your cameras, follow the procedure: 1. Download the programs named DLR CalDe and DLR CalLab from the web page: A Special features and notes https://www.dlr.de/rm-neu/desktopdefault.aspx/tabid-3925/ 6084_read-9197/ and follow the instructions to install the program on your PC. 2. Make a checkerboard pattern. 3. Browse to the following web page and follow the instructions on own_calib.html to create a number of pictures of the checkerboard in various orientations and for both cameras: https://data.caltech.edu/records/jx9cx-fdh55 Note: Each individual camera lens is unique, resulting in calibration parameters different from that of lenses of the same model. Make sure that each lens is mounted on the corresponding camera. 4. Run the programs and import the calibration pictures for camera 1. Follow the steps on the page example.html located in https://data.caltech.edu/records/jx9cx-fdh55 Repeat the procedure for the other camera. See also the documentation coming with the programs. 5. You get the following parameters: - Focal length (x and y) - The x and y values should be equal if the pixels are perfectly square. Copy the first two values given by the program to the corresponding fields under focal length in Track3D. - Principal points - The program calculates the coordinates of the projection point of the focus. This point does not necessarily coincide with the center of the screen, an can differ between A Special features and notes camera 1 and camera 2. Copy the first two values to the corresponding fields under principal point in Track3D. - Distortion kc - The program calculates distortion coefficients of order 2, 4 to correct for radial distortion. Copy the first two values to the radial corrections fields in Track3D. More information on the calibration parameters can be found in the file parameters.html located in https://data.caltech.edu/records/jx9cx-fdh55 Draw An Oblique Cone If you want the cone's main axis to be oblique, you have to set the coordinates of the axis point position in such a way that the cone axis forms the required angle with the x axis. For example if you want the cone pointing upward: 1. Choose the Xtop, Ytop, Ztop coordinates of the cone top position. 2. For the axis point position: - Xaxis= Xtop + cos() A Special features and notes - Yaxis= Ytop - Zaxis= Ztop + sin() Notes On Filtering Filtering replaces the coordinates in the 2D track files with values using a smoothing polynomial function. It helps smoothing your data and removing artifacts due to noise. The coordinates exported from EthoVision XT are in fractions of pixels, thus the effect of filtering is very small. The effect is negligible when you smooth the tracks in EthoVision XT before exporting them. In the case of tracking of mosquitoes, when applying filtering about 90% of your data differ by less than 0.5 mm from the original, non- filtered data. However, if the animal is large (e.g. a moth), its center point may move at a high rate due to random noise. We recommend to use filtering when you have not smoothed the tracks in EthoVision XT. If you use data exported from EthoVision 3.1, the coordinates are rounded off to whole pixels, increasing the likelihood of high-frequency movements with no biological significance. In this case, always enable filtering. Cut off frequency - A low cut off frequency means that a smoother line will be calculated. A high cut off frequency means that high frequency movements of the animal's center are kept in the data. Be careful not to exclude frequencies that can be important in your study by setting too low a cut off frequency. Cut off frequency and sample rate - If you set a low sample rate, for example 5 samples per second, setting a cut off frequency higher than the sample rate is not meaningful. Butterworth filter - In contrast with other frequency filters, a Butterworth filter preserves a uniform sensitivity for the passband frequencies (the magnitude response is maximally flat in the passband zone). A second-order filter decreases the signal at 16 dB A Special features and notes per halving of a frequency. The transfer function (magnitude ratio of output to input) of a Butterworth filter is: Where n is the filter order and the c the cutoff frequency. For more information, see: https://en.wikipedia.org/wiki/Butterworth_filter. Calibration Check After selecting a calibration file in Track3D, you can check the quality of calibration by looking at the three images opening on the screen: Calibration check of camera 1 Calibration check of camera 2 Calibration check 3D The first two images refer to the markers found in the calibration images for camera 1 and 2, respectively. The third image combines the two data sets. H i - 2n A Special features and notes Each red dot is the center of a marker that the calibration program estimated by analyzing the degree of white of the pixels in the calibration images around the clicked point. A line, if visible, connects this dot with the expected position (that is, the position of that marker when taking into account the position of the other markers; the software builds a "model" of the calibration frame assuming that the markers are on straight lines). For most markers the line is not visible as the error is rather small. A black triangle marks the largest error among the markers of each calibration image. Calibration Error Statistics of calibration quality (Residual Mean Square (RSM) error and Maximum error) are given on top of the pictures. The measurement unit of the error is: pixels for Calibration check of camera 1 and Calibration check of camera 2 and mm for the Calibration check 3D. Notes You can move the calibration check windows after clicking OK in the Statistics window. The pictures displayed in Calibration check of camera 1 and Calibration check of camera 2 are 2D images of the calibration markers. If you close the calibration check windows, you can re-open them by running analysis again (select New calibration). A Special features and notes Settings For Mediarecorder MediaRecorder is set to ensure that EthoVision XT works with video of the best quality. This is usually done by Noldus when installing your system. The settings for the MediaRecorder are stored in a file called Track3D.mrs which is located in the following folder: C:\Users\Public\Public Documents\Noldus\MediaRecorder Make sure you do not edit this file. If you wish to change any settings, save them under a different name: choose File > Save Configuration As. To go back to the default configuration, choose File > Open Configuration, and select the file Track3D.mrs. Optimize the settings file If for any reason the file Track3D.mrs is missing, do the following: 1. Browse to C:\Users\Public\Public Documents\Noldus\ MediaRecorder, right click the file Default.mrs, and select Open with the Notepad. 2. The content of the file displays. Change the following values: - GOPsize= 2 - Quality= 100 3. Choose File > Save As... and save the file as Track3D.mrs. 4. Before making the next recordings, start MediaRecorder and choose File > Open Configuration, and select the file Track3D.mrs. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - B Troubleshooting URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-b-troubleshooting Chapter: Track3D B Troubleshooting B Troubleshooting Installation Error message: The wizard was interrupted before MATLAB component Runtime 7.x could be completely installed. You system has not been modified. To complete installation at another time, please run setup again. 1. Download the Microsoft Visual C++ Redistributable Package. For 32-bit systems, download vcredistx86.exe. For 64-bit systems, download vcredistx64.exe. 2. Install the package on the Track3D computer. 3. Run MCRInstaller.exe. At some point you see a pop-up message indicating that .Net Framework is not installed. Click the option to continue without installing .NET Framework. Track3d Track3D closes immediately after start This may occur in a few cases. When the EthoVision XT hardware key is not inserted, or not recognized by Windows. Check that the hardware key is inserted in one of the USB ports of your computer and the red LED is on. If the hardware key is inserted and functioning, it might be that it does not contain the license of Track3D, or the license was not correctly updated. Start EthoVision XT and choose Help > About EthoVision XT > License Info. Check that Track3D is selected. If that is not the case, contact the Noldus office nearest to you. You may have just installed Track3D on a Windows 10 or 11 computer. Run the file ebussdk3.1.14.3284.exe located on the B Troubleshooting installation drive. You can download the installation files on the my.noldus web portal. The hard disk may be full. Check that there is enough space on the hard disk. Remove unnecessary programs and files. Then restart Track3D. If the steps above do not solve the issue, contact my.noldus.com. tip Some error messages appear for a very short time before the DOS window closes. Make a screen recording that captures the computer screen while you try to start the software. There you can see error messages that help troubleshooting. Error message Can't find mclmcrrt7_15.dll However the file is present in the folder C:\MCR\v715\runtime\win32. Right-click the Track3D.exe or CentroidFinder exe, select Properties, Compatibility, then select Run this program as an administrator. Error message in the DOS command window: Attempted to access Linesrelevant(1): index out of bounds because numel(Linesrelevant)=0 This message appears after you choose the file name for the output file. Track3D cannot calculate any 3D data. This happens in two cases: When the coordinates in the input files have not been exported in pixels. When the tracks obtained from camera 1 and camera 2 do not start at the same video time. Check in EthoVision XT that: The measurement unit for distance is mm. All Arena Settings are set to pixel calibration. The Trial Control Settings does not have the Time condition box inserted before the Start track action box. After that: B Troubleshooting 1. Clear the trials already acquired. 2. Make the necessary changes in Experiment Settings, Arena Settings and Trial Control Settings. - In the Experiment Settings, select mm as units of distance. - In the Arena Settings, right-click the panel on the right and select Set pixel calibration on. - In the Trial Control Settings, remove the condition box and restore the connecting arrow between the Start trial box and the Start track box. These two boxes must be connected directly. 3. Re-do the tracking. Remember to start the trials from the same video time in both camera views. 4. Export the new tracks to Track3D. Error message in the DOS command window: Track3D>pushanimate_Callback at 2293 The 3D chart window was closed before stopping an animation. First stop the animation, then close the window. Error message in the DOS command window: Error using --> loaddefinedlibrary The specified module cannot be found This can happen for both Track3D and CentroidFinder. Make sure that the C:\MCR folder and all subfolders are not read-only. Error message in the DOS command window: Too few calibration points are visible for camera 1 This error may appear when you load a calibration file in TXT format, and the file contains one or more extra tabs between the 8 numbers in each row. Track3D gives an error message because it always expects a total of eight values in each row. If it finds another tab (which contains no value) it considers this value undefined and stops looking in the next lines. So it's like Track3D sees a calibration file with only one marker. Make sure to remove the extra tabs between the marker values. B Troubleshooting If you obtained the TXT file from an excel file, check that the format of the cells is Number, not others, then export to TXT again. If you obtained a Calibration file in TXT, for example when you run CentroidFinder and Excel is not installed on that computer, then check that only tab spaces, not blank spaces, are present between the values. Error message in the DOS command window: DLT3dcalc at 22 In Track3D, select New calibration and click Start calculations. Make sure to select the correct calibration file. Error message in the DOS command window: "ÿ_Number of header lines" was read This happens when you import text files of wrong format. Open each text file, select File > Save as, choose Encoding: ANSI. Save with a different name, then import those files in Track3D. Error message in the DOS command window: Cannot access the MCR component cache The DOS command window closes after a very short time. Go to the following folder: C:\Users[user name]\AppData\Local\Temp[user name] and delete the folder mcrCache7.15., then restart Track3D. Error message in the DOS command window: Error using ==> xlswrite at 211 Object returned error code: 0x800A03EC Track3D attempts to write in an Excel file with extension *.xls, where the row limitation is about 65000, but the number of rows in the output file is probably greater than that. The solution is to re-run the analysis. In the Save As window, type the extension "*.xlsx" in the File name field, just before clicking Save. B Troubleshooting Do this whenever you analyze long recordings (e.g. longer than an hour or so). Error message in the DOS command window: Values must be increasing and non-NaN This occurs when: You have loaded a calibration file which contains zeroes in the last three columns. Copy the real-world x,y,z coordinates of the calibration markers to the three columns of the calibration file and click again the Start calculations button. At least one of the Arena Settings in EthoVision XT is not pixel- calibrated. See page 134. Error message in the DOS command window: Error in ==> @(hObject, eventdata)Track3D... The software (either Track3D and CentroidFinder) are installed on a folder other than C:\MCR. If that is the case, remove Track3D and the MCR runtime library. Then, re-install Track3D in the correct folder (C:\MCR). The calibration check shows a "star"pattern B Troubleshooting The pattern shown in the figure above appears in the figures Calibration check camera 1 and Calibration check camera 2 after you open the calibration file in Track3D. The reason for this pattern is that the calibration file does not contain the real world coordinates of the calibration markers. To solve this issue, open the calibration file and replace the zeros with the x,y,z coordinates copied from the calibration reference file. See step 12 on page 34. The position of the subject in the chart does not match what I see in the video Most probably the calibration is not valid anymore for those tracks. This happens for example when you move the cameras (or the tracking chamber) after calibration. Check carefully the video and the calibration images, to see if they overlap perfectly. The x,y,z coordinates in my output file change after using another cleanup input setting clean up input (page 74) is likely to remove several samples from the input data set. After applying this filter, Track3D performs interpolation according to the settings specified (see interpolation on page 71). Because interpolation is applied on an input data set that slightly differ from the previous one, the x,y,z coordinates and output variables may change. Values of Track xv are much higher than expected Example: when an insect flies upwind, Track xv should be around 0 degrees. Actual values exceed 100 degrees. Check the axis orientation. If the x axis is reversed, that is, it points to upwind instead of downwind, you might obtain values of Track xv opposite to those expected (e.g. 180 instead of 0). Values of Course xv are very high, even if air speed is low Example: when an insect flies upwind, Course shows values corrected by 40 degrees or more when air speed is 200 mm/s. B Troubleshooting Check the axis orientation. Probably the x axis is reversed, that is, it points to upwind instead of downwind. Track3D always assumes that the air flow is in the x direction. I get very high error values in the Calibration check charts Most probably the calibration file has X, Y or Z values in the wrong columns. For example, values of X and Y may have accidentally been swapped. Another reason could be that the same markers have been clicked multiple times during calibration. If that is the case, repeat the calibration procedure. Trajectories look as if the 3D space was distorted B Troubleshooting This is likely due to the fact that the two input track files (*.txt or *.xlsx) were obtained from the same video file. To check this, open the original input files and check the name of the video file next to the header Video file. Next, in EthoVision XT, re-do tracking from the correct video file and export the raw data. Then, import the correct track files in Track3D. The 3D tracks look tilted and far from the origin of the axes This occurs in two situations: The calibration images and the video used for acquisition do not match, for example when the cameras were accidentally moved between calibration and data acquisition. In most cases you need to re-do calibration using the current camera images. When at least one of the arena settings was not pixel-calibrated. To check this, make a duplicate of the arena settings, then right-click one of the buttons on the right-hand panel of the Arena Settings. The message that pops should be Set pixel calibration off. If you see Set pixel calibration on, click OK and re-do tracking using that Arena Settings profile. Do the same for other Arena Settings. See Calibration on page 26. Another way to check that the coordinates are in pixels is to look at the values of X center and Y center in the EthoVision XT export files. Those values should match the position (in pixels) where the subject is supposed to be when looking at the calibration images. For example if the fish was swimming in an area of the calibration images ranging between 200 and 300 pixels on the horizontal axis, then the X center coordinates exported from EthoVision XT should only be within that range. B Troubleshooting After loading the track files, Track3D does not give any message and nothing seems to happen This may occur when the track files are very large, for example when tracking a subject for hours. Track3D may take long especially when it has to interpolate many pissing points. For 2-hours track files it may take more than 20 minutes. Please wait until the Save as window appears. Centroidfinder CentroidFinder closes immediately after start See Track3D closes immediately after start on page 127. tip Some error messages appear for a very short time before the DOS window closes. Make a screen recording that captures the computer screen while you try to start the software. There you can see error messages that help troubleshooting. The calibration images look grainy in CentroidFinder This is most probably caused by the fact that the images were edited and then saved with a low bit depth. Re-open the original calibration image in Paint.net, edit it when necessary (see page 119), then select Save as, choose BMP as image type, and under Bit Depth choose 24. B Troubleshooting Re-do calibration using this new image. Blue cross symbols do not appear on both calibration images This issue occurs often when you work with calibration frames with black markers. Most likely you have seen this error message: Attempted to access handles.im(NaN,NaN); index must be a positive integer or logical First, create an inverse version of both calibration frames (see 2 - save the calibration images on page 28). Make sure tha the markers look bright and clearly visible. Then save the new images, re-load them in CentroidFinder and repeat calibration. Error message in the DOS command window: Error using --> loaddefinedlibrary The specified module cannot be found This can happen for both Track3D and CentroidFinder. Make sure that the C:\MCR folder and all subfolders are not read-only. B Troubleshooting Error message in the DOS command window: Attempted to access handles.im(x,y); index must be a positive integer or logical This can happen when CentroidFinder looks for the boundaries of a marker until it reaches the margin of the calibration image because it does not find enough contrast, like in the example below. Try to reduce light around the calibration frame and make sure that the markers are far enough from the image margins. If this cannot be done, open the calibration image file in a paint program, and make the bright objects around the markers black. Next, save the image as bitmap (*.bmp) with bit depth set to 24 bits. Use this new bitmap file in your calibration. Error message in the DOS command window: ??? Error using ==> xlswrite at 211. Errors occurred in servers. To solve this issue, disable one or more add-ins in Excel, especially those which are not present by default. We know that, for example, the FoxitReader PDF Creator COM Add-in may cause this issue. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - C Wind Tunnel Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-c-wind-tunnel-settings Chapter: Track3D C Wind tunnel settings C Wind Tunnel Settings Set The Air Speed In The Wind Tunnel Prerequisite See the document Wind tunnel characteristics which comes with the wind tunnel. There you find reference points for air speed and flow. Procedure - Open the lid of the Control Unit at the back of the ventilation unit. - Power up the fan, and switch it on using the switch located on the lower side of the Control Unit. - The LCD display shows: FAN 1 with the current set parameters, e.g. 0018 Pa, 00.19 m/s, 0149 m3h. - Press and hold the SETUP button located immediately under the LCD display, until you see SETUP on the display. - Release the SETUP button. The display shows now LANGUAGE GB. Press the ENTER button. - When the display shows DISPLAY m3h? Y, press the ENTER button. - When the display shows DISPLAY Pa? Y, press the ENTER button. - When the display shows DISPLAY m/s? Y, press the ENTER button. - When the display shows AREA? 0.2200 m2, press the ENTER button until the last number is highlighted, then press ENTER once more. C Wind tunnel settings 10.When the display shows FAN TYPE 720124, press the ENTER button. - When the display shows #FANS F1, press the ENTER button. - When the display shows WORKING MODE CA, press the ENTER button. - The display shows m3h K1? followed by a value, e.g. 0150. This corresponds to the current flow set. See the Wind tunnel characteristics chart for reference. 14. The first number (o) is highlighted. Press ENTER. 15. When the second number is highlighted, change this with the arrow buttons and or accept it by pressing ENTER. Do this for all the numbers. - For example, if the value set is 0150 (= 150 cubic meters per hour) and 1 is highlighted, to select 250 press the arrow keys to select 2 instead of 1, then press three times ENTER. 16. The display shows m3h K2?. Press ENTER four times. 17. The display shows m3h K3?. Press ENTER four times. 18. When the display shows CONFIG TIME? N, press the ENTER button. 19. When the display shows TIME SEGMENT? N, press the ENTER button. 20.When the display shows PRESSURE ALARM? N, press the ENTER button. 21. The display now shows END SETUP. You do not have to press any key. 22.Place the lid back in its position and tighten the screws. Notes If you do not see WORKING MODE CA, press the arrow buttons one or more times. If WORKING MODE CA is not available, see the TAC 5 Ventilator Regulation user manual to carry out a hard reset, or contact Noldus Support. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - D Wind Tunnel Maintenance URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-d-wind-tunnel-maintenance Chapter: Track3D D Wind tunnel maintenance D Wind Tunnel Maintenance Replace The Charcoal Filter Remove the old filter Hold the cylinder with both hands and exert mild pressure toward the fan (1). At the same time, turn the cylinder counter-clockwise (2). D Wind tunnel maintenance Where to get a new charcoal filter Camcarb GM 2600 Galva CEX003 2600 CCGAS CEX003 (CEX 003 is the code of the activated carbon medium). https://www.camfil.com/products/molecular-filters/cylinders/ camcarb/camcarb-cm-_-54678 Clean the new filter When you get a new charcoal filter, it is good to dedust it. Use compressed air for this purpose. Attach the new charcoal filter Position the filter so that the three bolts at one end coincide with the large holes at the side of the motor. Gently push the filter toward the fan (1), then turn the cylinder clockwise (2). This will fix the filter. D Wind tunnel maintenance Clean Or Replace The Filter In The Lamination Unit The filter inside the lamination unit may show sigh of wear and accumulated dust. Extract the filter For this you need an Allen (hexagonal) key. 1. Separate the lamination unit from the wind tunnel. 2. Remove the four tie-wraps (see the picture below). D Wind tunnel maintenance 3. Remove the two L-shape profiles that are attached at the top edges of the lamination unit. 4. At the top of the Lamination Unit you find bolts in the middle of the panel. Remove these bolts and extract the filter holder. Filter material You can replace the existing filter with 20-mm universal polyester HVAC air filter. For example: https://nl.rs-online.com/web/p/hvac-air-filters/1221774 Make sure to put enough filter material in order to avoid air leakage around the edges. Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D - E Copyright And Acknowledgments URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-e-copyright-and-acknowledgments Chapter: Track3D E Copyright and acknowledgments E Copyright And Acknowledgments EthoVision XT Copyright 1993-2023 Noldus Information Technology BV. See the License Agreement in the EthoVision XT Help. CentroidFinder and Track3D software Copyright 2007-2023 Wageningen University. Documentation: Copyright 2007-2023 Noldus Information Technology BV. MATLAB runtime library Copyright 1984-2017 The MathWorks, Inc. Deployment rights are governed by the license agreement between Wageningen University and The MathWorks, Inc. Acknowledgments Track3D is the result of a joint effort of researchers at Wageningen University and Noldus Information Technology. The Track3D and CentroidFinder software was written by Johan van Leeuwen, Kees Spoor and Sander Kranenbarg at the Experimental Zoology Group, Wageningen University. The requirements were specified by Willem Takken, Jeroen Spitzen and Jacob Beeuwkes at the Laboratory of Entomology, Wageningen University. Most of the practical testing took place in the wind tunnel setup at the Laboratory of Entomology. We thank Johan, Kees, Sander, Willem, Jeroen and Jacob for their cooperation and patience. Index Numbers Air filter Index Camera Cone EthoVision XT 6, 8, 9, 22, 24, 29, 123 Index Matlab component runtime library .9 MediaRecorder 8, 22, 24, 27, 46, 126 Index Samples Time stamp Index Zooming in/out calibration image . 37 Source: Track3D 2 - Reference Manual (March 2025) --- ## Track3D 2 - Video Recording with EthoVision XT - Experiment Settings URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-2-video-recording-with-ethovision-xt-experiment-settings Chapter: Track3D Experiment Settings Video Source: Live tracking For Merged camera view, select 1280 x 1024. Number of Arenas: Arena Settings Put the tracking chamber on the backlight unit. Draw the two arenas. Important: Right-click in the Arena Settings window and Trial Control Settings Remove the condition box between the Start-stop trial and Start track. Detection Settings Main Settings: - Method: Dynamic Subtraction - Subject: Darker than background - Track Noise Reduction: Off Acquisition Select Save Video. Release the animal in the test arena, and click Start Trial. To stop recording, click Stop Trial. Analysis > Export Raw Data Export Raw Data (Track and dependent variables, File type = Excel). - For each trial, one file is exported (…….Trial [n].xlsx). - Each file contains data for both cameras (Arena 1 and 2). For each Excel file: - Rename it by adding Cam1 (this file has Arena 1 in the first sheet). - Make a copy and rename this copy by adding Cam2. In this copy, put the sheet of Arena 2 in front. Track3D - Adjust the settings (interpolation, filters, 3D zones etc.). - Select New Calibration, then click Start Calculations; select the calibration file calibration_edited… (see the next page). - Select the first file from Camera 1, then the file for Camera 2. - Give a name to the results file (*.xlsx). The 3D track chart appears. For the next trial, select Old Calibration. For more information, see: - The EthoVision XT Help - The Track3D Reference Manual Calibration Do calibration only once, or whenever you change the position of the cameras relative to the test arena. The test arena must be exactly in the same position as when you record the animals. 1. EthoVision XT - Put the calibration frame in the test arena. - Make a new Arena Settings and rename it to Calibration. - Click Grab Background Image, then Grab. - Go to the Bitmap Files folder in your EthoVision experiment folder and copy the newest background.bmp file to the location of your choice (e.g. D:\calibrations). - Rename this file, for example Calibration image.bmp. 2. Paint.NET Optional: Open the Calibration image. Choose Adjustments > Brightness/Contrast. Adjust the values to increase the white/black contrast. Save the picture as Calibration_edited.bmp. 3. CentroidFinder - Import the Calibration_edited.bmp image twice. - Click the markers, first for Camera 1, then Camera 2. Follow the same order as in your calibration reference file. - The calibration file is saved (default name is Calibration_edited_date_time.xls). - Copy the coordinates from your Calibration reference file to this Calibration file. For details, see the Track3D Reference Manual. Source: Track3D 2 - Video Recording with EthoVision XT, Noldus Information Technology --- ## Track3D 2 - Video Recording with MediaRecorder - 3. When Done, Click Stop Recording. URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-2-video-recording-with-mediarecorder-3-when-done-click-stop-recording Chapter: Track3D 3D Calibration Do 3D calibration only once, or whenever you change the position of the cameras relative to the tracking chamber. Calibration Video Files Record the calibration object in the wind tunnel. Result: You obtain two calibration video files. Preparing Calibration Images - Rename the calibration image (e.g. CalCam1.bmp, CalCam2.bmp). - Repeat the steps for CalCam2.bmp. Note: If you work with backlight, reverse the picture in a paint application so that the markers become white. Applying the Calibration File Link the file to the Calibration file. If calibration is not good, edit the calibration images with a paint application and repeat the process. Video Recording and Track Acquisition - When done, click Stop Recording. Result: Two video files are saved (e.g. Video_1.avi and Video_2.avi). Arena Settings - Open the Arena Settings for Video 1 (or Video 2). - If this is the first time, draw the arenas and set Pixel Calibration to On. See the manual for details. Track Acquisition - Do track acquisition. - Repeat steps 2–4 for Video 2. Start tracking from the beginning. - Give a name to the results file (.xls). Result: The 3D track chart appears. Open the results file for the analysis variables. - Rotate and zoom the chart in and out. - Create a video of the animated track. Source: Track3D 2 - Video Recording with MediaRecorder, Noldus Information Technology --- ## Track3D 2 - Zebrafish Solution Assembly - Assembly Instructions URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/track3d-2-zebrafish-solution-assembly-assembly-instructions Chapter: Track3D Assembly Instructions Try to center the cameras as much as possible. Make sure that the camera view is like this. All Markers (or most of them) should be visible. - Front - Top Source: Track3D 2 - Zebrafish Solution Assembly, Noldus Information Technology --- ## TrackLab 2 - Quick Start Installation Guide URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/track3d/page/tracklab-2-quick-start-installation-guide Chapter: Track3D First Time Installing TrackLab Demo Projects - Request a user license from operations. - Go to \\nit-srv3\Applications\Noldus Products\TrackLab - Open the latest version. - Copy the folder to your computer. - Open the Recorder Setup and select the standard option for installation. - Open the Server Setup and choose the custom installation type and select the demo projects. (See screenshots below.) Note: If you already have TrackLab data on your PC, the demo projects will overwrite all previous TrackLab data. - Open the TrackLab Setup and install the standard version. Select in the options field if you want to install both the human and animal skin. - Open the TrackLab program. - Activate your license following the instructions. - Login with the following credentials: - Username: Admin - Password: admin - Open one of the demo projects: - Animal GPS for the outdoor cattle project - Animal UWB for the indoor cattle project - Human UWB for the supermarket project Re-Installing a New Version of TrackLab Demo Projects - Go to your application settings and remove N-Linx Server. - Open your TrackLab Server Setup and select uninstall. - Open your TrackLab Recorder Setup and select uninstall. - Remove your TrackLab Setup. - Go to \\nit-srv3\Applications\Noldus Products\TrackLab - Open the latest version. - Copy the folder to your computer. - Open the Recorder Setup and select the standard option for installation. - Open the Server Setup and choose the custom installation type and select the demo projects. (See screenshots below.) - Open the TrackLab Setup and install the standard version. Select in the options field if you want to install both the human and animal skin. - Open the TrackLab program. - Re-activate your license following the instructions. - Login with the following credentials: - Username: Admin - Password: admin - Open one of the demo projects: - Animal GPS for the outdoor cattle project - Animal UWB for the indoor cattle project - Human UWB for the supermarket project Source: EthoVision XT 18 - THC - Trial and Hardware Control, Noldus Information Technology --- ## UltraVox XT - Acquire Data URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-acquire-data Chapter: UltraVox XT Acquire data Acquire Data To record sound - Choose Acquisition > Open Acquisition. - Release the animals in their test environments. - To start recording manually, click the Start recording button when ready. - To stop recording manually, click the Stop recording button. See also page 8 for how to start/stop recording automatically. Notes You can also import audio files in UltraVox XT, provided that it is stored in a WAV file, 16 bit mono. For more information, see Record sound in the UltraVox XT Help. Choose Acquisition > Recording List for an overview of your recordings. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT - Activate Your License URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-activate-your-license Chapter: UltraVox XT Activate your license Activate Your License You need to have a license activation code to be able to run the full version of UltraVox XT. 1. To start UltraVox XT, in the Apps screen, under Noldus, double-click the UltraVox XT icon. 2. Click Import License File. Select the UltraVox XT 4 license file (*.json) that you received from Noldus. 3. A message informs you that the license has been activated. You can start using UltraVox XT. Notes Click Evaluate UltraVox XT to open the free evaluation version. With a free evaluation version, you can only work with the sample experiment that is stored on C:\Users\Public\Documents\Noldus\UltraVox XT\Experiments. Click Request a License to purchase a new UltraVox XT license. Your first UltraVox XT experiment Your First UltraVox XT Experiment - Make sure that the microphones are connected (see page 3). - Start UltraVox XT. - Under New experiment, click New, or choose File > New. - In the New experiment window, enter the name for your experiment and click OK. - The Experiment Settings page opens. - To add a microphone, click Notes The new experiment is saved in a folder with the same name as the experiment. This folder is by default located in C:\Users\Public\Documents\Noldus\UltraVox XT\Experiments If you want to change the default experiment locations for your next experiments, choose File > Settings and select the new location under Experiment location. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT - Call Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-call-statistics Chapter: UltraVox XT Call statistics Call Statistics In the Call Statistics screen you can view and export statistics of individual calls. 1. Choose Analysis > Call Statistics. 2. Choose a recording from the Recording list to view the list of calls and their statistics. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT - Detect The Calls URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-detect-the-calls Chapter: UltraVox XT Detect the calls Detect The Calls Detect The Calls In the Call Detection screen, specify the parameters that define the basic unit of vocalization (call). 1. Choose Analysis > Call Detection. 2. In the window that appears, select a recording. 3. tip Under View, click Filter and apply a high-pass filter to remove low-frequency noise. 4. Under Step through all data, click the buttons to visualize part of the recording and locate vocalizations in the spectrogram. Detect the calls tip Use the mouse wheel to zoom in and out the timeline in the spectrogram. 5. Locate the spectrogram of a representative vocalization. 6. Draw a rectangle around the spectrogram, as indicated in the figure below. 7. Click OK in the window that opens, or first adjust the values of the detection parameters, and click OK. 8. Click Detect calls in this recording to let UltraVox XT detect the calls. Detect the calls 9. Click Edit and fine-tune the frequency, amplitude and temporal parameters of the call definition to detect more calls of that type. When ready, click Detect calls in this recording to apply the new parameter values. Notes Click Edit and then Save to save a call definition as a template, which you can copy to another experiment. You can also add calls that were not detected by UltraVox XT, or delete unwanted detected calls. See Call labeling in the UltraVox XT Help. For tips on how to detect more calls, see Call detection in the UltraVox XT Help. When you are confident that a call definition detects most of the calls, click Detect calls across all recordings. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT - For More Information URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-for-more-information Chapter: UltraVox XT For more information For More Information UltraVox XT Help For more details, in UltraVox XT, choose Help > Help Topics to open the Help. Sample experiment The UltraVox XT installation package contains the sample experiment UltraVox XT 4 - Sample experiment - Mouse vocalizations (in the Extras folder). Copy the entire folder UltraVox XT 4 - Sample experiment - Mouse vocalizations to your experiment folder (default: C:\Users\Public\Documents\Noldus\UltraVox XT\Experiments). You can then open the experiment in UltraVox XT (File > Open). The experiment contains two copies of the same recording. In the first copy, a number of calls have been detected. Open the second recording and define the calls, then let UltraVox XT search for calls. Noldus Support If you encounter problems, see my.noldus.com to search the support knowledgebase or contact Noldus Support. About Noldus then Contact. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT - Label The Detected Calls URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-label-the-detected-calls Chapter: UltraVox XT Label the detected calls Label The Detected Calls In the Call Labeling screen, categorize the detected calls based on their pattern or any other criterion you are interested in. For example, "Flat", "Chevron", "Distress" or "Social". 1. Choose Analysis > Call Labeling. 2. Select a recording from the list at the top. 3. Click one of the calls in the spectrogram or in the Detected calls list. 4. To label that call, double-click the label you require in the Labels list. Notes To label multiple calls, or reassign labels, see Labeling calls in the UltraVox XT Help. Label the detected calls To add a new label to the list, right-click a label in the Pattern labels list and select Add label. To remove a label, double-click the label in the Label column for that call and press Delete. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT - Prepare Data Acquisition URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-prepare-data-acquisition Chapter: UltraVox XT Prepare data acquisition Prepare Data Acquisition Microphone Settings - Make sure that the microphones you want to use are connected. If you work with a laptop, ensure that the microphones are powered through the USB hub (see page 3). - Position the microphones at 20-30 cm from the sound source. For tips about how to elicit vocalizations in rodents, see the UltraVox XT Help. - For each microphone in the Experiment Settings (see page 6): - Click the Settings button. - In the Microphone Settings window, click the Start monitoring button. - Wait that the animals produce vocalizations. Check the waveform plot and the spectrogram. - Adjust the Gain until the waveforms of the vocalizations are well visible, but only rarely enter the upper and lower areas highlighted in red. This prevents that the signal is clipped during the actual tests, resulting in distortion of acoustic frequencies. - Try to keep the gain as low as possible. Remember that gain also increases the amplitude of the background noise picked by the microphone, not only the amplitude of the actual signal. Prepare data acquisition Control The Start/stop Of Data Acquisition You can start and stop acquisition manually, or automatically using an external triggering software. 1. Choose Setup > Trial Control Settings. 2. Choose one of the options available under Start acquisition and Stop acquisition. Note Choose External program trigger to start and stop acquisition from another program, like EthoVision XT, or The Observer XT. For details, see Control UltraVox XT from other software in the UltraVox XT Help. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT - Recording Statistics URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-recording-statistics Chapter: UltraVox XT Recording statistics Recording Statistics In the Recording statistics screen you can view and export per- recording statistics, for example the number of calls and the average dominant frequency. You can group the calls according to their name, pattern label, or a combination name*pattern label. 1. Click Recording Statistics. 2. Under Call grouping, choose how to group results. Under Statistics, select the statistics that you want to calculate. 3. Select the recordings that you want to include in the table. Source: UltraVox XT 4 - Quick Start Guide --- ## UltraVox XT 4 - Calls - How Detected Calls Are Sorted URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-calls-how-detected-calls-are-sorted Chapter: UltraVox XT How Detected Calls Are Sorted In the Detected Calls List, calls are sorted first by the time interval chosen to visualize the signal, then by the call definition they originate from. Example: The Time interval is 2 seconds. Within each 2-s interval, the calls obtained with the first call definition are listed first, then those obtained with the second call definition, etc. The orange rectangles below represent the time intervals. To View Information on a Detected Call - Click within the rectangle around the call in the Spectrogram. - In the Detected Calls list, the row for the selected call is highlighted. To View the Spectrogram of a Detected Call - Click a detected call in the Spectrogram or click a row in the Detected Calls list. The corresponding rectangle in the Spectrogram is highlighted. If the call is located in a time interval other than the current one, all plots are updated with the new interval. - A detailed spectrogram of that call appears at the bottom-right corner of the screen. - To view details of the call, move the mouse over the plot and check the values at the bottom: t (time), f (frequency) and a (amplitude). TIP: To navigate through calls, you can also use the arrow keys or the Page Up/Page Down keys. Definition A pattern label is a label that you can assign to multiple calls in order to analyze them as a group. A pattern label is often labeled according to the shape of the call spectrogram. Procedure - Choose Analysis > Call Labeling, or click Call Labeling on the left pane. - Select one of the calls in the call list. - Observe the spectrogram of the call that is highlighted. - In the Labels list at the bottom-left corner of the screen, double-click the name of the pattern that you want to assign. - The pattern name appears in the corresponding cell. - The cursor moves automatically to the next call. You can now label the following calls. See Label Multiple Calls. The Labels List The Labels list shows the names of the call pattern labels currently available. NOTE: The Labels list is used for all your experiments. You cannot create different lists for different experiments. Add a New Pattern Label - Right-click within the Labels list, and select Add label. - A new row is appended to the list. - Enter the label you require, then press Enter. Edit a Pattern Label - Select a pattern label in the Labels list, right-click and select Edit label. - The label name becomes editable. Make the necessary changes and press Enter. Delete a Pattern Label In the Labels list, right-click the label and select Delete label. NOTE: When you delete a label, the labels of the same type assigned to calls are not deleted. If you want to delete those labels, see Remove Labels. Enter a Pattern Label That Is Not in the Labels List You can label one or more calls with a pattern name that is not (yet) included in the Patterns list. - In the Call Labeling screen, click the row of the call you are interested in. - Type in a new pattern name in the Label cell for that call. The label is not included automatically in the Pattern labels list. You can also add a pattern label to the list. See Add a New Pattern Label. Label Multiple Calls Aim: To quickly label a number of vocalizations of a specific pattern. Procedure - Open the Call Labeling screen and select one recording. - For each call that you want to label with a specific pattern label, click the cell in the first column, so that it is marked with a check symbol. - In the Labels list, double-click the label that you want to assign. - Click Yes on the message that appears. - Select the label you require and click OK. - The labels appear in the corresponding cells. Replace a Pattern Label for Multiple Calls Aim: To re-assign a pattern label to multiple calls. This is especially handy in two situations: - When you want to assign the same pattern label to all unlabeled calls. - When you want to replace a specific label with another one. To Re-Assign a Pattern Label to Multiple Calls - Click the button next to the Pattern Label column header. - In the Multi Pattern Label Editing window, under Rename pattern label, click the first button and in the Select pattern label window select the pattern label that you want to replace. Leave this empty if you want to assign a label to unlabeled calls. - Click the second button and select the label you want to assign. - Click Apply. - The Pattern Label column is updated with the new pattern label. A message shows how many calls have been labeled. Remove Labels Aim: To remove the labels from the calls in your recordings. Procedure (Single Call) - Double-click the Pattern Label cell so that its content is highlighted in blue. - Press Delete, or right-click the label name and select Delete. Procedure (Multiple Calls) To remove the labels of a specific type, do the following: - Right-click anywhere in the call list and select Select by label. - In the second menu, select the label you want to delete. NOTE: The second menu includes the labels that are scored in the current recording. - As a result, all the rows that include that label are selected with a check mark. - Right-click again somewhere in the call list and select Remove label of [n] selected calls. The number [n] indicates how many calls in that recording are labeled with the label chosen. - The labels are removed. Select Multiple Calls for Editing Aim: To select multiple calls for deletion or call labeling. Prerequisites: Open the Call Labeling screen. Procedure - Simple manual selection: Click the check box next to each call that you want to select. - Select by call name: Right-click anywhere in the call list and select Select by call name, then select one of the names available in the second menu. - Select by label: Right-click anywhere in the call list and select Select by label, then select one of the labels available in the second menu. Once selected, a call can be: - Labeled - See Label Multiple Calls - Deleted - See Delete Calls - Renamed - See Rename Calls - Assigned to a different pattern - See Replace a Pattern Label for Multiple Calls Source: UltraVox XT 4 - Calls, Noldus Information Technology --- ## UltraVox XT 4 - Calls - Main Topics And Tasks URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-calls-main-topics-and-tasks Chapter: UltraVox XT Background Call definitions are used to detect calls in your recordings. See how to Add a call definition. The signal is detected as "call" when it fulfills the conditions set by the call definition parameters. - Call Name: The name of the call definition. The same name will be given automatically to all calls detected based on that definition. - Call Color: The color for this call definition (and the detected calls). Parameters - Frequency Low (Hz): The lower frequency limit. Signals with frequency below that value are ignored. - Frequency High (Hz): The higher frequency limit. Signals with frequency above that value are ignored. - Min Amplitude: The value of amplitude below which the signal is not included in the call. - Min Duration (ms): The minimum duration of the call. - Max Duration (ms): The maximum duration of the call. - Min Gap (ms): The shortest time allowed between the stop of one call and the start of the next one. If two events matching the other parameters are found at less than the minimum gap, they are considered as one call. Add a Call Definition There are three ways to define a call: - Select a call in the spectrogram and define a call. - In the Call Detection screen, click the Add button and enter the call parameters. See Adjust a Call Definition. - In the Call Detection screen, click Edit, then load a call template that was saved previously. See Load a Call Template. Adjust a Call Definition At least in some cases, selecting a rectangle around a call in the spectrogram does not lead to detection of similar calls as expected. For example, calls in the spectrogram that are a bit shorter than the minimum duration estimated when drawing the rectangle around a call will not be detected. To Adjust a Call Definition For all parameters: - Click on a call definition in the Call Definition list, then click the Edit button. Make the necessary changes and click OK. - Click Detect calls in this recording to detect the calls with the new definition. Note that clicking this button also updates the calls detected with other call definitions. For the call definition name: - Double-click the cell under Call Definition and rename the frequency range if necessary (that is important especially if you change the frequency limits). For the frequency range: - Drag the top or bottom side of the rectangle to select a higher or lower high frequency limit. Note: Changing the frequency limits by dragging the rectangle top/bottom sides does not result in changing the call definition name (frequency label on the spectrogram). You have to do that manually. For duration: - Drag the left/right sides of the rectangle to change the minimum duration of the call definition. Notes - Editing the frequency limits does not result in changing the call definition name (frequency label on the spectrogram). You have to do that manually. - You can save the call definition as a template to use it to search for calls in other experiments. In the Save as template field, enter a name for your template and click Save. Load a Call Template To apply a call definition to the current recording that was saved previously as a template, also in experiments other than that currently open. Procedure - Under Recording, select the recording in which you want to detect calls based on an existing definition. - Click the Add button. - In the Edit Call Definition window, click the Load Call Template button. - Select a call template and click OK. - The Add Call Definition window is updated with the values stored in the imported template. - Edit the call definition (optional), then click OK. - The new call definition is appended to the Call Definition list. - Click Detect calls for this recording to detect the calls based on the call definition. Call Templates You can use a call template to detect calls in one or multiple recordings based on information that you obtained from other recordings (or experiments). Definition A call template is a container of one call definition. A call template includes the following information: - Template Name - Call Name - Color - Frequency lower and higher limits - Minimum Amplitude - Minimum Duration (ms) - Maximum Duration (ms) - Minimum Gap (ms) Save a Call Definition as a Template To save a call definition that can be used to detect calls in multiple experiments. Procedure - Define a call. - When necessary, adjust a call definition. - Click the call definition name in the Call Definition List, and click the Edit button. - In the Edit Call Definition window, next to Save as template, enter a name for that call template. - Click Save. - Click OK. Note The call templates are saved in the call_defs.txt file located in C:\ProgramData\Noldus\UltraVox. Do not edit this file. Detected Calls List Contents - Detected Calls: The name of the call definition used to detect that call. See Call Definitions. - Color: The color of the call definition the call belongs to. - Duration (ms): Duration of the detected call. This equals Stop time – Start time. - Start Time (s): The start time is back-calculated when a number of samples above the Min amplitude (set in the call definition) have been found that exceed the Min duration (set in the call definition). From this time (tm) the Min duration is then subtracted to obtain the Start time. - Stop Time (s): The stop time is back-calculated when a number of samples with low amplitude values (that is, below the Min amplitude in the call definition) have been found that exceed the Min gap time set in the call definition. From this time (tg), the Min gap time is subtracted to obtain the Stop time. - Freq at Max Amp (Hz): The frequency at which the amplitude is the highest in that call. - Mean Amplitude: The mean amplitude of a call is calculated as the sum of the amplitude of all points inside the call rectangle with an amplitude above the specified Min amplitude limit (in the call definition), divided by the number of points found. White background points in the spectrogram are generally not included as they would reduce the mean amplitude to a meaningless low value. This means also that mean amplitude is always higher than (or equal to) the Min amplitude limit. Source: UltraVox XT 4 - Calls, Noldus Information Technology --- ## UltraVox XT 4 - Calls - Notes URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-calls-notes Chapter: UltraVox XT Notes To select or de-select all the calls in the Call Labeling screen, do one of the following: - Click the first check box of the list, near Call Name, to select all calls. To de-select all calls, click that check box once again. - Right-click somewhere in the call list and select Select All or Select None. Add a Call Manually Aim: To add a call that was not detected automatically. The call will be analyzed just as the calls detected automatically. If you want to have the new call analyzed in the same group as the other, automatically-detected calls, rename the new call with the name of those calls. See Rename Calls. Procedure - In the Call Labeling screen, draw a box around the call spectrogram. - A new row is inserted. Under Call Name, the text Manual is entered automatically. - Optional: Double-click Manual under Call Name and enter the name you require. - Optional: Assign a Pattern Label. See Pattern Labels. Note If you rename a call with an existing call name (e.g. 45-69k), the cell under Color is updated with the corresponding color. Rename Calls Aim: To provide meaningful names of the calls for a publication or to facilitate analysis of groups of calls across recordings and experiments. What Do You Want to Do? - Rename a Single Call - Rename Multiple Calls - Rename the Calls with a Specific Name - Rename the Calls with a Specific Label - Rename All Calls in a Recording Rename a Single Call - In the Call Labeling screen, double-click the Call Name cell for the call you want to rename. - Enter the new name for the call. - To confirm and stop editing, click anywhere in the call list. If you want to edit the next call name, press Enter. Rename Multiple Calls - In the Call Labeling screen, for each call you want to rename, select the check box in the first column. Make sure that the calls selected have the same name. Tip: If you only have one call name and you want to select all the calls, select the uppermost check box, at the left of Call Name. - Enter the new name under Call Name for one of the calls selected, then press Enter. - In the message dialog that opens, click Yes to confirm. Rename the Calls with a Specific Name - In the Call Labeling screen, right-click anywhere in the call list and select Select Call by Name, then choose the name that you want to modify. - The rows with the chosen name are selected. Double-click the Call Name for one of those rows and enter the new call name. - In the message dialog that opens, click Yes to confirm. Rename the Calls with a Specific Label - In the Call Labeling screen, right-click anywhere in the call list and select Select Call by Label, then choose a label. - As a result, calls with the specified label are selected. - Double-click one of those rows and enter the new name. - In the message dialog that opens, click Yes to confirm. Rename All Calls in a Recording - Select the uppermost check box, at the left of Call Name. - Enter the new name under Call Name for one of the calls selected, then press Enter. - In the message dialog that opens, click Yes to confirm. Edit a Call Aim: To edit the frequency and time boundaries of a call if they do not match the call spectrogram. Do this for example when the red rectangle around a detected call does not include some weak signal that you believe is part of that call. Procedure Adjust the Frequency Boundaries - In the Spectrogram, hover the mouse cursor over the upper side (to adjust the High Frequency boundary) or the lower side (to adjust the Low Frequency boundary) of the rectangle around the call. - When the mouse cursor turns to a double-headed arrow, drag the boundary up or down to the new position. - To save the changes, select File > Save or press Ctrl+S. Adjust the Time Boundaries - In the Spectrogram, hover the mouse cursor over one of the lateral sides of the rectangle around the call, depending on whether you want to adjust the start boundary or the end boundary. - When the mouse cursor turns to a double-headed arrow, drag the boundary up or down to the new position. - To save the changes, select File > Save or press Ctrl+S. Notes - When you edit the frequency or time boundaries of a call, the values reported in the call list for the corresponding call are updated. - If you adjust the frequency boundaries, the values Freq at Max Amp and/or Mean Amplitude will change. - If you adjust the time boundaries, one or more of the following values may change: Duration, Start Time (or Stop Time), Freq at Max Amp, and Mean Amplitude. See also: Adjust a Call Definition. Delete Calls Aim: To remove calls that represent noise or calls that should not be analyzed. What Do You Want to Do? - Delete a Single Call - Delete a Selection of Calls - Delete the Calls with a Specific Name - Delete the Calls with a Specific Label (or No Label) - Delete All Calls in a Recording - Restore a Deleted Call Delete a Single Call In the Call Labeling screen, right-click the corresponding row in the call list and select Delete Call. The call is removed from the call list and the corresponding spectrogram is no longer highlighted with a rectangle. Delete a Selection of Calls - For each call you want to delete, select the check box in the first column. - Right-click anywhere in the list and select Delete [n] Selected Calls, where [n] is the number of calls currently selected for deletion. - The calls are removed from the call list. The corresponding spectrograms are no longer highlighted with a rectangle. To reset a selection of calls, select and then de-select the check box at the top of the list, at the left side of Call Name. Delete the Calls with a Specific Name - Right-click anywhere in the list and select Select by Call Name, then select the name of the calls you want to delete. - As a result, the calls with that name are selected. - Right-click anywhere in the call list and select Delete [n] Selected Calls, where [n] is the number of calls currently selected for deletion. - The calls are removed from the call list. The corresponding spectrograms are no longer highlighted with a rectangle. Delete the Calls with a Specific Label (or No Label) - Click the button next to the Pattern Label column header. - In the Multi Pattern Label Editing window, under Delete by Label, click the button and select the label of the calls you want to delete. Leave the field empty to delete all calls that currently have no label. - Click Apply. - The calls are deleted and a message informs you about how many calls have been removed. Delete All Calls in a Recording - Click the button at the top of the first column and select Tag All. - Click the same button once again and select Delete. Click Yes to confirm. Source: UltraVox XT 4 - Calls, Noldus Information Technology --- ## UltraVox XT 4 - Calls - Restore A Deleted Call URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-calls-restore-a-deleted-call Chapter: UltraVox XT Restore a Deleted Call If you deleted a call unintentionally, do the following: - In the Spectrogram, drag a rectangle around the call spectrogram. - The call list shows a new row, with the text Manual in the Call Name cell. Double-click Manual and enter the name you require. - Optional: Label the call. See Labeling Calls. If you want to restore all the deleted calls, open the Call Detection screen and click the Detect calls in this recording button to restore the deleted calls according to the current definitions. This will not restore changes that you may have applied manually, nor will it restore the calls added manually. Problem After creating a call definition and clicking Detect calls in this recording, UltraVox XT does not detect the calls that look like the one selected to create the call definition. Solution In the Call Detection screen, select the call definition and click Edit. Try the following: - Reduce the frequency range (Freq Low - Freq High). See Keep the Frequency Range as Narrow as Possible. - Increase Min Amplitude. Hover the mouse over the calls and take note of the amplitude values you see. Min Amplitude should stay below those values. - If calls that are not detected show weaker signal (lower amplitude), reduce Min Amplitude by steps of for example 30 or 50, and see if this improves detection. See Increase the Min Amplitude Parameter and Get a Feel of the Amplitude in a Call. - Reduce the Min Duration value. Tip: Draw a rectangle around a few calls, then in the resulting call definitions look at the Min Duration parameter and take note of the average value. When you define the true call definition, click Edit and enter half of the average value as a Min Duration. Do not forget to delete the call definitions made before. See Reduce Min Duration. - Increase the Max Duration value. See Increase Max Duration. - Reduce Min Gap. Sometimes two calls are detected as one when Min Gap is too high. - When calls have different frequency ranges, define two call definitions instead of one. See also: Call Definitions I See No Vocalizations in the Spectrogram One simple explanation is that the subject did not make vocalizations. However, it may be that the recording is so noisy that the calls do not emerge in the spectrogram. The colors displayed in the spectrogram for one event also depend on the amplitude of the signal in the surrounding interval. The same call may appear or not (or appear less evident) if another, unwanted signal like strong noise (for example, a door being closed) or constant noise from electrical appliances occurs in the interval displayed. To Find Out Whether There Is Constant Noise in the Signal - Under View, select Spectrum. - Look at peaks in the spectrum. If necessary, zoom in the spectrum. See Zoom In/Out. Examples: - With strong noise at 60 Hz, zoom in the left part of the spectrum. - In another example, after filtering at 20000 Hz, two peaks are visible at 32 kHz and 47 kHz. See also: The Spectrogram, Factors Affecting Ultrasound Recording Increasing Min Amplitude in a Call Definition Results in Fewer Calls Detected This result may sound counterintuitive. One may expect to detect fewer calls after increasing the Min Amplitude parameter, that is, after applying more restrictive criteria. In fact, more calls are often detected after increasing Min Amplitude. The reason is that when Min Amplitude is low, UltraVox XT captures large regions of the spectrogram that have amplitude higher than that value. But such large regions may not correspond to the other criteria in the call definition. For example, some regions may exceed Max Duration, and would not be considered as calls. When you increase Min Amplitude, it is more likely that smaller regions of the spectrogram will be found which correspond to all criteria in the call definition. This explains why when you increase Min Amplitude you begin to see more detected calls. For example, suppose 50 is used for Min Amplitude. Amplitudes just above 50 are found in large regions of the spectrogram. However, such a region may not satisfy the other criteria set in the call definition — for example, it could be longer than 100 milliseconds, which conflicts with the Max Duration setting. Therefore, the call within that region is not found. After setting a higher value of Min Amplitude and clicking Detect calls in this recording, the software finds smaller regions of the spectrogram that are above that value. This time two regions are found that match the other settings of the call definition, and therefore two calls are detected. The third, slightly longer call is not yet found because it conflicts with the Max Duration setting. It is detected after increasing Max Duration to for example 200 ms and clicking Detect calls in this recording. See also: The Spectrogram Problem In the Spectrogram, vocalizations are visible that were not detected. Further optimization of the call definition did not help. Solution You can add a call manually. - Open the Call Labeling screen (Analysis > Call Labeling). - Draw a rectangle around the spectrogram of the call that was missed. - In the detected calls list, a new row appears. Double-click the Call Name cell for that row, and change its name from Manual to the one you require. See also: Add a Call Manually Problem You applied a call definition and detected most calls. However, some calls that look very prominent are not detected. Solution In some cases, noise at the end of a call increases the time that the signal is above the Min Amplitude threshold, pushing it above the Max Duration threshold. In such cases UltraVox XT does not detect the call because the signal appears too long to match the criteria of the call definition. You can solve this issue in two ways: - Increase the Min Amplitude threshold, but check that the other calls are still detected. - Increase the Max Duration threshold. If necessary, reduce the call duration in the Call Labeling screen. See Adjust Frequency and Time Boundaries in a Call. Problem The spectrogram shows constant, narrow-band noise (for example, at about 70 kHz). Constant noise could be due to an electronic device near the microphone, or to the microphone being defective. Note: Cables and electric/electronic devices produce ultrasound. Voltage changes may occur, resulting in a change in noise levels during recording, which is also difficult to deal with. Isolate all cables and devices as much as possible. Source: UltraVox XT 4 - Calls, Noldus Information Technology --- ## UltraVox XT 4 - Calls - Solution URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-calls-solution Chapter: UltraVox XT Solution - First, try to know what amplitude is the noise signal. Draw a rectangle around the horizontal line, without including any call. - A call definition is defined. Look at the spectrogram that appears at the bottom-right corner. Hover the mouse over the horizontal line and get a feel of the amplitude of that signal. Take note of the maximum values you see. - Select the call definition and click the Remove button. - Draw a rectangle around a call. - Select the new call definition and click the Edit button. Set the Min-Amplitude parameter to a value well above the values of the noise. - Click Detect the calls in this recording. Problem After clicking Detect the calls in this recording in the Call Detection screen, processing goes very slowly. Solution Right-click the spectrogram area and reduce the Overlap, for example to 50% or lower. See Also - Spectrogram Settings - Overlap Problem When examining the Call Statistics table, the value of Duration is not the same as one would obtain by calculating the difference between Stop Time and Start Time. Solution The value of Duration is obtained with the difference between Stop Time and Start Time using six decimals, that is, more than those you see in the table (three for both Start Time and Stop Time). After that, the value is rounded to the milliseconds. This is the reason why you see a discrepancy between Duration and the value expected from Start Time and Stop Time in the table. The result is, however, very accurate. Source: UltraVox XT 4 - Calls, Noldus Information Technology --- ## UltraVox XT 4 - EthoVision and Observer Integration - In The Observer Xt URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-ethovision-and-observer-integration-in-the-observer-xt Chapter: UltraVox XT In The Observer XT - Under Observation Source select Live. - In the Devices window that appears, click Add external program. - In the Add External Program window, under Name, enter a title (for example Control UltraVox XT). - Select Start Observation. Next, click and select the batch file StartUV - 2 PCs.bat. - Select Stop Observation. Next, click and select the batch file StopUV - 2 PCs.bat. For how to edit the batch files, see Edit the StartUV/StopUV Batch Files. - Click OK. In UltraVox XT - Choose Setup > Trial Control Settings. - Under Start acquisition and Stop acquisition, select External program trigger. See also - Trigger Start/Stop Recording - Edit the StartUV/StopUV Batch Files Co-Acquisition of Data Aim: To acquire UltraVox XT data together with EthoVision XT or The Observer XT data. Procedure Follow the instructions that apply to your software (EthoVision XT or The Observer XT). - In UltraVox XT, open the acquisition screen. In EthoVision XT, open the acquisition screen. In The Observer XT, create a new observation. - In EthoVision XT, start the trial and release the animal in the arena. In The Observer XT, start the observation. - On the EthoVision XT/The Observer XT computer, the software activates the batch file. The file start.txt is sent to the Sync folder on the UltraVox XT computer. When this occurs, UltraVox XT detects the file and starts recording. - In EthoVision XT, after a fixed time, the trial stops automatically depending on the Time condition specified in the Trial Control rule (Trigger settings for EthoVision XT). In The Observer XT, stop the observation. In both cases, this stops recording in UltraVox XT. - In UltraVox XT, detect and label the calls. - In UltraVox XT, export the call data to EthoVision XT or The Observer XT. See Export Call Statistics. - In EthoVision XT or The Observer XT, import the call data. See also - Export Call Statistics - Import Call Data in The Observer XT - Import Call Data in EthoVision XT - Import Profiles EthoVision XT To import UltraVox XT data into EthoVision XT, you must have the import profile UltraVox 3/4. The import profile is installed on C:\ProgramData\Noldus\Common\Profiles. Note: If you do not see the C:\ProgramData folder, it may be hidden. To view hidden folders: - In the Windows Control Panel, choose Appearance and Personalization, then under Folder Options click Show Hidden Files and Folders. - In the window that appears, under Hidden files and folders, select Show hidden files, folders and drives. For information on how to import UltraVox XT data, see the EthoVision XT Help. The Observer XT To import UltraVox XT data into The Observer XT, you do not need an import profile. Just export the call statistics in UltraVox XT in The Observer XT format (*.odx), and import the export file into The Observer XT. To Access the Trial Control Settings - Choose Setup > Trial Control Settings. - Choose one of the options below for Start acquisition and Stop acquisition. Start Acquisition - Manually — To start acquisition when you click the Start recording button in the Acquisition screen. - External program trigger — Choose this option to start acquisition when a file is detected in a specific location (default: C:\ProgramData\Noldus\UltraVox\XT 4\Synch). To test the external program trigger option, see the note below. Choose this option to control UltraVox XT recording from EthoVision XT or The Observer XT. Stop Acquisition - Manually — To stop acquisition when you click the Stop recording button in the Acquisition screen. - External program trigger — To stop acquisition when a file is detected in a specific location (default: C:\ProgramData\Noldus\UltraVox\XT 4\Synch). To test the external program trigger option, see the note below. Choose this option to control UltraVox XT recording from EthoVision XT or The Observer XT. - After ... minutes — To stop acquisition after a fixed time has elapsed. Maximum recording time is 99 minutes. Note To test the external program trigger, do the following: Copy a text file named start.txt or stop.txt to the destination folder (default: C:\ProgramData\Noldus\UltraVox\XT 4\Synch). If you want to change this folder, click the [...] button and select the new folder path. When the file is copied, a message appears: - In the case you copied the start.txt file, a start message appears. - When you copy the stop.txt file, a stop message appears. Tip: To retrieve the current destination folder for the start/stop files, click the Copy button to copy the folder path to the clipboard. See also - Control UltraVox XT from Other Software - Trigger Settings for EthoVision XT - Trigger Settings for The Observer XT To Import the Data In The Observer XT, do one of the following: - To import a recording as a separate observation: Choose File > Import > Observational Data. - To import a recording into an existing observation: Open that observation and click the Import data button. Next, follow the instructions on the screen. Coding Scheme In The Observer XT coding scheme, calls are imported as discrete events, each consisting of a state event (call name) and a modifier (pattern label). State events are listed in one Start-stop group named Calls. Call events with different names can be overlapping. - If a call was labeled in UltraVox XT before exporting, the corresponding state event is attached to the modifier with the same name as the label. - Modifiers are listed in a group named Pattern. Data in the Event Log In the event log, calls are represented with two rows, one marking the call start time and one marking the stop time. Data Visualization When visualizing the observation, calls are shown as colored segments on the timeline. Click the + sign next to the headers to view the calls with their pattern labels. The audio data is displayed as a waveform. For more information, see the EthoVision XT Help. To Import Call Data - In EthoVision XT, open the Trial List. - Click the Import External Data button. - Under Files of type, select UltraVox XT [version number]. If you do not see this profile, install it from the UltraVox XT installation USB stick. - Select the *.etx files and click Open. - Drag the data lines from the Import External Data window to the trial you require. - When ready, click Import. Data for each call name (or call name * pattern label) is imported and resampled as a separate dependent variable. For more information on importing and analyzing external data, see the EthoVision XT Help. Analysis Profile For each call type imported, the analysis profile shows two dependent variables: the continuous (resampled) and the state variable. The state variable has discrete values 0 and 1 derived from the resampled variable. For example, you exported calls of type 52-65 kHz (call name) labeled with Chevron (label name). To analyze those calls you have two options: - Click the button next to the variable you want to analyze, and choose the type of upsampling/downsampling you require. Source: UltraVox XT 4 - EthoVision and Observer Integration, Noldus Information Technology --- ## UltraVox XT 4 - EthoVision and Observer Integration - Integrated Visualization URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-ethovision-and-observer-integration-integrated-visualization Chapter: UltraVox XT Integrated Visualization To visualize the original UltraVox call data, choose Show/Hide > Dependent Variables and select the [call name*pattern label] (original signal). When plotted against time, the data look like this: - Where 1 on the y-axis represents the onset of the call. - The transition 1-0 represents the call end. When visualized, the resampled variable looks like this (second and third plot): Source: UltraVox XT 4 - EthoVision and Observer Integration, Noldus Information Technology --- ## UltraVox XT 4 - EthoVision and Observer Integration - Other Software URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-ethovision-and-observer-integration-other-software Chapter: UltraVox XT Other Software To start and stop recording in UltraVox XT from EthoVision XT or The Observer XT. Example: You plan to video-track animals with EthoVision XT or record their behavior with The Observer XT and, at the same time, record ultrasound with UltraVox XT. For ease of use you want to start and stop recording with one click, in such a way the UltraVox data and the EthoVision XT/The Observer XT data are synchronized. How It Works - When proper communication is set between the two applications, you can start and stop recording in UltraVox XT by clicking the Start trial/Stop trial button in EthoVision XT. - You can then import call data into EthoVision XT for combined analysis of tracks and vocalizations. See Import call data in The Observer XT and Import call data in EthoVision XT. Main Topics and Tasks - Computer setup - Trigger settings for EthoVision XT - Trigger settings for The Observer XT - Co-acquisition of data - Import profiles See also: Start and stop recording at specific times Computers We advise to run UltraVox XT and EthoVision XT/The Observer XT on separate computers. On both computers, disable the firewall. Important: Running EthoVision XT/The Observer XT and UltraVox XT on the same computer is not recommended. The large data transfer may cause malfunctioning in either application. Test this solution thoroughly if you want to use it. For example, check that EthoVision XT does not miss samples, or that data streams from the two applications are in sync. Network The two computers should be connected to a dedicated network using a network switch. To avoid the risk of network communication delays, we recommend not to connect the computers to a larger network. UltraVox XT computer (right) connected to an EthoVision XT or The Observer XT computer (left) through a network switch. Procedure Overview - Specify the IP address of the UltraVox XT PC - Share the UltraVox XT synchronization folder - Make a virtual drive for the EthoVision XT / The Observer XT - Copy the UltraVox XT Control folder to the EthoVision XT/The Observer XT PC - Edit the StartUV/StopUV batch files - Make UltraVox XT data import easier Specify the IP Address of the UltraVox XT PC On the UltraVox XT computer, do the following: - In the Control Panel, choose Network and Internet > Network and Sharing Center. - Choose Change adapter settings. - Right-click the local network and choose Properties. - Select Internet Protocol Version 4 and click the Properties button. - Select Use the following IP address. - Enter the IP address that is in the batch file (suggested: 192.168.0.202; this address must also be specified in the batch file). Leave the Subnet mask and Default gateway unchanged. Note We recommend using one PC for EthoVision XT and one PC for UltraVox XT. Connect the two computers through a network switch and assign the IP addresses to enable communication. For example: - Network switch: 192.168.0.239 (Netgear GS310TP) - EthoVision XT PC: 192.168.0.201 - UltraVox XT PC: 192.168.0.202 You can assign an IP address other than specified here. However, you must enter the same address in the batch file. This address must be different from that of the EthoVision XT/The Observer XT computer. See Edit the StartUV/StopUV batch files. Share the UltraVox XT Synchronization Folder - With Windows Explorer, browse to C:\ProgramData\Noldus\UltraVox\XT 4\Synch. - If you do not see this folder, it may be hidden. See the note below. - Right-click and select Properties, then click the Sharing tab. - Click Share and select Everyone. In the context menu choose Read/Write. - Click Share, then Done. The Synch folder can now be seen by the EthoVision XT/The Observer XT computer. Note: To View Hidden Folders - In the Windows Control Panel, choose Appearance and Personalization, then under Folder Options click Show Hidden Files and Folders. - In the window that appears, under Hidden files and folders, select Show hidden files, folders and drives. Make a Virtual Drive for EthoVision XT / The Observer XT To make data transfer from UltraVox XT and EthoVision XT easier. Once the procedure is completed, you can easily access the UltraVox XT data and import them in EthoVision XT/The Observer XT. - On the EthoVision XT PC, with Windows Explorer, right-click This Computer and choose Map network drive. - Choose a drive letter. - Select the shared Synch folder from the UltraVox XT PC. - Click Finish. Copy the UltraVox XT Control Folder to the EthoVision XT/The Observer XT PC To provide EthoVision XT or The Observer XT with the files necessary to communicate with UltraVox XT. Note: The UltraVox XT Control folder is installed automatically with EthoVision XT. Therefore, if you have EthoVision XT you do not have to follow the procedure below. Skip this topic and go to Edit the StartUV/StopUV batch files. - Open the UltraVox XT 4 installation package and browse to Extras. - Select the folder UltraVox XT 4 Control, and press Ctrl+C. - Open the following folder: C:\Program Data\Noldus\Common\Tools. If the Tools folder is not present, create it. - Open the Tools folder and press Ctrl+V. - Open the folder just copied, and check that the two files SUV.bat and start.txt are present. Edit the StartUV/StopUV Batch Files To make sure that the batch file triggers UltraVox XT when activated by Noldus software. Background Information Once activated by Noldus software, a batch file StartUV*.bat or StopUV*.bat does the following: - It connects with the UltraVox XT computer, and deletes any file named start.txt from the folder C:\Program Data\Noldus\UltraVox\XT 4\Synch (if present). - It copies the file start.txt (or stop.txt) to the folder C:\Program Data\Noldus\UltraVox\XT 4\Synch on the UltraVox XT computer. The files start.txt and stop.txt are empty text files. Their function is to trigger UltraVox XT, provided that this is set to external program trigger in the Trial Control Settings. See Trigger start/stop recording. Source: UltraVox XT 4 - EthoVision and Observer Integration, Noldus Information Technology --- ## UltraVox XT 4 - EthoVision and Observer Integration - Procedure URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-ethovision-and-observer-integration-procedure Chapter: UltraVox XT Procedure - Browse to C:\ProgramData\Noldus\Common\Tools\UltraVox XT 4 Control. If this folder does not exist, see Copy the UltraVox XT Control folder to the EthoVision XT/The Observer XT PC. - Locate one of the *.bat batch files: - For EthoVision XT with one arena, or The Observer XT: choose StartUV - 2 PCs.bat or StopUV - 2 PCs.bat depending on which you want to use. - For EthoVision XT with two or more arenas, choose StartUV - 2 PCs multiple arenas.bat or StopUV - 2 PCs multiple arenas.bat. - Right-click the batch file and select Edit with Notepad. - Insert the IP address that you assigned in step Specify the IP address of the UltraVox XT PC. See the instructions below depending on what file you are editing. - In all cases, make sure that the path of the file start.txt / stop.txt is C:\ProgramData\Noldus\Common\Tools\UltraVox XT 4 Control. - Save and close the file. StartUV - 2 PCs.bat Use this file in the external command for starting recording in UltraVox XT. @if exist "\\IP address of UltraVox XT PC\Synch\start.txt" del "\\IP address of UltraVox XT PC\Synch\start.txt" @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 4 Control\start.txt" "\\IP address of UltraVox XT PC\Synch" > nul Replace "IP address..." with the actual IP address of the UltraVox XT PC. Alternatively, enter the name of the PC that you find in Windows (e.g. DESKTOP-123ABC) instead of the IP address. The batch file copies the file start.txt to the trigger folder of UltraVox XT. This starts recording in UltraVox XT. StopUV - 2 PCs.bat Use this file in the external command for stopping recording in UltraVox XT. @if exist "\\IP address of UltraVox XT PC\Synch\stop.txt" del "\\IP address of UltraVox XT PC\Synch\stop.txt" @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 4 Control\stop.txt" "\\IP address of UltraVox XT PC\Synch" > nul Replace "IP address..." with the actual IP address of the UltraVox XT PC. Alternatively, enter the name of the PC that you find in Windows (e.g. DESKTOP-123ABC) instead of the IP address. The batch file copies the file stop.txt to the trigger folder of UltraVox XT. This stops recording in UltraVox XT. StartUV - 2 PCs Multiple Arenas.bat If you work with multiple arenas, use the batch file StartUV - 2 PC multiple arenas.bat to start recording in UltraVox XT. This way the file start.txt is sent out just one time, for Arena 1. If the arena has a different name, open the file with Notepad and edit the name between the quotes. @if exist "\\IP address of UltraVox XT PC\Synch\start.txt" del "\\IP address of UltraVox XT PC\Synch\start.txt" @echo off echo %1 IF %1=="Arena 1" ( @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 4 Control\start.txt" "\\IP address of UltraVox XT PC\Synch" > nul ) Replace "IP address..." with the actual IP address of the UltraVox XT PC. Alternatively, enter the name of the PC that you find in Windows (e.g. DESKTOP-123ABC) instead of the IP address. StopUV - 2 PCs Multiple Arenas.bat If you work with multiple arenas, use the batch file StopUV - 2 PC multiple arenas.bat to stop recording in UltraVox XT. This way the file stop.txt is sent out just one time, for Arena 1. If the arena has a different name, open the file with Notepad and edit the name between the quotes. @if exist "\\IP address of UltraVox XT PC\Synch\stop.txt" del "\\IP address of UltraVox XT PC\Synch\stop.txt" @echo off echo %1 IF %1=="Arena 1" ( @copy "C:\ProgramData\Noldus\Common\Tools\UltraVox XT 4 Control\stop.txt" "\\IP address of UltraVox XT PC\Synch" > nul ) Replace "IP address..." with the actual IP address of the UltraVox XT PC. Alternatively, enter the name of the PC that you find in Windows (e.g. DESKTOP-123ABC) instead of the IP address. Command Line Options An important point when working with multiple arenas: in the Action boxes in the Trial Control Settings of EthoVision XT, specify the Command line options: "%an%", quotes included. For more information, see the EthoVision XT 18 - Trial and Hardware Control - Reference Manual. Working with One PC It is also possible to run EthoVision XT and UltraVox XT on the same PC. In this case use the batch files StartUV - 1 PC.bat and StopUV - 1 PC.bat. However, this solution is not supported as it may cause high workload on the memory and the processor. If you opt for this solution, test it thoroughly and make sure that the proportion of missing samples in your tracks is acceptable. Make UltraVox XT Data Import Easier When importing the call statistics files from UltraVox XT to EthoVision XT/The Observer XT, a shared folder may be handy that allows you to import the files directly through the network. Procedure - On the UltraVox XT computer, make a general folder where you are going to place all export (*.etx) files. - Share this folder (see a similar procedure in Share the UltraVox XT Synchronization Folder). - On the EthoVision XT/The Observer XT computer, create a virtual drive for this shared folder (see a similar procedure in Make a Virtual Drive for the EthoVision XT / The Observer XT). In EthoVision XT - Choose Setup > Trial Control Setting > New. - Make a Trial Control Settings rule with the following components: - External command that runs one of the batch files StartUV*.bat. This copies the start.txt file to the trigger folder of UltraVox XT. - Time condition for waiting a fixed time (for example, 10 minutes). This determines the length of the EthoVision XT tracks and UltraVox XT recordings. - External command that runs one of the batch files StopUV*.bat. This copies the file stop.txt to the trigger folder of UltraVox XT. External Command Box - In the Components pane, under Actions, choose External command. - In the External Command Action window that appears, under Action to perform, click the button. - In the Open window, choose to view Batch Files (*.bat, *.cmd). - Select the file with extension .bat that you require. - Important: When you work with multiple arenas, enter "%an%" under Command line options in both External command boxes. See Command Line Options. - Optional: Under Name, give a name to this action box (e.g. Start UltraVox recording or Stop UltraVox recording). Time Condition Box - Click the Settings button. - Enter the time required, i.e., the duration of the recording. In UltraVox XT - Choose Setup > Trial Control Settings. - Under Start acquisition and Stop acquisition, select External program trigger. Prerequisites In The Observer XT, you have created a new project (File > New). Next, choose Setup > Project Setup. Source: UltraVox XT 4 - EthoVision and Observer Integration, Noldus Information Technology --- ## UltraVox XT 4 - MICS - Main Topics/Tasks URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-mics-main-topicstasks Chapter: UltraVox XT General Information UltraVox XT has been thoroughly tested with the full-spectrum microphone Pettersson M500-384, specifically designed for recording ultrasonic vocalizations. This microphone has a sample rate 384 kHz and can record ultrasound up to 160 kHz. Connect the Microphone To connect multiple microphones to the PC, use a multi-port USB 3.0 interface card. See Install the USB 3.0 Interface Card. Alternatively, use a powered USB 3.0 hub. USB hubs that are not powered do not work with those microphones. IMPORTANT When using 384-kHz microphones, we recommend to use a Windows 11 computer. These microphones are not recognized in Windows 8. Notes The Dodotronic Ultramic 250 is not officially supported. However, short tests carried out with UltraVox XT 4 on Dell 3680 desktop with Windows 11 version 24H2 did not reveal significant issues. See also: Connect Multiple Microphones with a USB Hub Connect Microphones to the PC When using 384-kHz microphones, we recommend to use a multi-port USB 3.0 interface card. See Install the USB 3.0 Interface Card. Connect the microphones using the USB cables that come with the microphones. - Type A plug goes to the USB 3 (recommended) port of your PC. USB 3.0 connectors and ports can be recognized by their symbols, and often also by their blue color coding. - Type Mini-B plug goes to the microphone. IMPORTANT Always connect the same microphone to the same USB port. If you purchased a PC together with UltraVox XT, microphones and USB ports are labeled. Always make sure that microphones are plugged into the USB ports with the matching labels. See also: Microphone Position Connect Multiple Microphones with a USB Hub When you work with UltraVox XT installed on a laptop, use a powered USB 3 hub. NOTE A powered, or active, USB hub is powered through a wall outlet to bring each hub port to the same energy level as an on-system port. Non-powered, or passive, USB hubs do not have an external power source and only pull power from the computer's USB port. Maximum Number of Microphones The number of microphones that you can use simultaneously depends on your UltraVox XT license. This is specified in the UltraVox XT license. - Choose Help > About UltraVox XT. - Click License Info. - Next to Number of microphones you see how many microphones you can use simultaneously. See: Activate Your License Microphone Position Position the microphone in such a way that it receives sound optimally to minimize the effect of the position of the animal in the test environment. Here we report basic examples from the literature. Test Setups - Home cage observation: Microphones are positioned suspended 2 to 20 cm above the cage, pointing downward. Testing cages are generally placed in a sound-attenuating chamber. - Separation test for rodent pups: Pups are placed into an empty container located inside a sound-attenuating chamber. The microphone is placed through a hole in the middle of the cover of the chamber, about 20 cm above the pup. - Self-administration chamber: Position the microphone outside the chamber behind a mesh screen, if possible between the response levers at approximately head-level of the animal. - Male-female interaction (rats): The test cage is divided in two compartments, the lower one for the male, and the upper one for the female. The microphone is attached to the divider, pointing to the lower compartment. Holes are drilled into the dividing panel to allow odor to pass to the male chamber. The diameter of the holes is smaller than the 50-kHz vocalization wavelength to sufficiently attenuate female vocalizations (Ciucci et al., Behav Brain Res. : 284–289, 2007). - Male-male interaction (rats): In this setup, a male rat is paired with another male and housed throughout the experiment period. Each pair is housed in a polycarbonate cage (26 cm width x 43 cm depth x 20 cm height) in an environmentally controlled rearing system where temperature and humidity are kept constant and external sound and light sources are shut out. The microphones were suspended close to the lid of the cage (Takahashi et al., PLoS ONE (11): e14115, 2010. doi:10.1371/journal.pone.00141152010). Eliciting Vocalizations for Test Purposes For optimal gain adjustment, it is important that animals produce vocalizations. To trigger vocalizations: - For mother-pup interaction: Separate the pups. - For male-male interactions (mice): Add bedding contaminated with urine of another male in the cage. - For male-female interactions (mice): Wild-derived male mice increase the number and diversity of courtship vocalizations if they previously interacted with a female (Zala et al 2020). The exposure to a female partner or to the urine induces a clear USV response in adult male mice with previous reproductive experience (Holy and Guo 2005, Maggio et al. 1983; Nyby 2001, Whitney and Nyby 1979). - For prairie voles: Put two individuals in the cage (e.g. same-sex siblings). The frequency of vocalizations is reduced when the animals are placed in separate, side-by-side cages. For single-individual recordings, optimal distance is about 15 cm (6 in) (Stewart A.M. PhD thesis, University of Illinois at Chicago, 2012). Relevant Literature Browse to http://www.noldus.com/search-publications, then under Products click UltraVox. Animal Care Guidelines http://www.animalethics.org.au/policies-and-guidelines/animal-care Adjust the Microphone Gain in UltraVox XT Aim: With the Gain function you can adjust the amplification of the signal from the microphone. NOTE If adjusting the microphone gain in the software does not give the expected results, you can also Adjust the Microphone Internal Gain. Procedure - Place the microphones at the top of the cage, pointing down to the middle. - Click the name of the microphone you want to adjust, and then click the Settings icon. - In the Microphone settings window, click the Start monitoring button. - The Amplitude plot (top) and the Spectrogram plot (bottom) show the real-time values. - Move the Gain slider in such a way that the peak of the waveforms (almost) never cross the red shaded area of the Amplitude plot. - In the spectrogram, the calls should be clearly visible, provided that the subject emits vocalizations. See Eliciting Vocalizations for Test Purposes. - When ready, click the Stop monitoring button, then click OK. - The current value of gain is shown in the Gain column. Repeat the steps above for the next microphone. Source: UltraVox XT 4 - MICS, Noldus Information Technology --- ## UltraVox XT 4 - MICS - Note URL: https://noldus.com/shared/resources/book/noldus-product-documentation/chapter/ultravox-xt/page/ultravox-xt-4-mics-note Chapter: UltraVox XT Note: Microphones of the 384 kHz type are not given a unique ID. Because of that, UltraVox XT stores the gain settings based on the USB port the microphone is attached to, not the microphone itself. If you plug a microphone into a different USB port, UltraVox XT will assign the gain that was last saved for that USB port, and will show no error message. To prevent confusion, always label microphones and USB ports, so you always know which microphone goes to which port. Gain and Signal Offset When the gain is high, an offset may appear in the Amplitude plot, that is, the average signal is higher than zero, and the maximum values are higher than unsigned minimum values. The offset is caused by the electronics of the microphone. Therefore, increasing the gain usually results in a higher offset. However this has generally no effect on your measurements. You can reduce the offset by lowering the gain. When the offset is significantly high, it can reduce the dynamic range, that is, the range of amplitudes that can be described by a digital system. In the case of UltraVox XT where audio is sampled with a 16 bit resolution, the signal can range from -32767 to +32768. If the offset is, for example, 2500, then the positive side of the signal can be from 2500 to +32768, that is, leaving an actual range of 30268. This limitation increases the probability that loud sound exceeds the maximum possible value, generating artifacts (see below). Gain and Frequency Artifacts A high gain also produces additional high frequencies, which do not correspond to vocalizations. This occurs when the signal exceeds a lower or upper limit. The result is that the waveforms are cut off flat, or "clipped". When sound is loud, clipping produces extra frequencies that you can see in the spectrogram. When setting the microphone gain, create conditions similar to those of the actual recordings. For example, put the mouse pups at the same distance from the microphone as when you carry out the real tests. Microphone Internal Gain If the vocalizations do not appear in the spectrogram, it may be that they are covered by overall noise. To further reduce noise, for 250-kHz microphones, you can then adjust the microphone internal gain. Adjust the Microphone Internal Gain Aim To adjust the gain of the 250-kHz microphone. Do this only when adjusting the gain in UltraVox XT does not give the expected results. - For rough gain adjustments, adjust the microphone internal gain (see below). - For fine-tuning the output, adjust the microphone gain in UltraVox XT. See also Experimental Setup and Microphone Position. Procedure (250-kHz Microphone) - Unscrew the microphone lid (connector side) and pull out the circuit board out of the aluminium cylinder. - Place the microphone at the top of the cage, pointing down to the middle of the cage. - Connect the microphone to the PC. - Start UltraVox XT, and choose Setup > Experiment Settings. - Click Settings for that microphone, then click the Start Monitoring button. - In the software, set the Gain to a low value like 20. A low value is recommended because a high software gain increases noise more than the microphone's internal gain. - Place the microphone over the subjects. Check the waveforms on the Amplitude plot and in the spectrogram. The vocalizations should be visualized in the spectrogram. See Eliciting Vocalizations for Test Purposes. - Locate the trimmer on the board. This is a small box with a tiny screw on one side. - Gently turn the trimmer screw: counterclockwise if the waveforms are out of scale; clockwise if the call waveforms are too narrow. - Test the microphone with the actual sound source. There should always be a gap between signal peaks and the minimum and maximum values of the plot. - When finished, click the Stop Monitoring button and then click OK. - Put the board back in place and close the microphone. - For fine tuning, adjust the Gain value in UltraVox XT. Repeat the procedure for the other microphones. Notes - The Dodotronic Ultramic 250 is not officially supported. However, short tests carried out with UltraVox XT 4 on Dell 3680 desktop with Windows 11 version 24H2 did not reveal significant issues. - For 384-kHz microphones, we recommend not to adjust the internal gain. The trimmer inside the microphone only allows changes in sensitivity significantly larger than microphone-to-microphone sensitivity variation. - To produce ultrasound, move a key chain in front of the microphone, at a fixed distance. However, with this method you do not calibrate the microphone to the real animal's vocalizations. See Eliciting Vocalizations for Test Purposes. - Multiple microphones need not have exactly the same optimal gain. For each microphone, try to find the gain that results in a clear spectrogram of calls. Microphone with Sampling Frequency 384 kHz - Type: Advanced electret - ADC Resolution: 16 bits - Max Sampling Frequency: 384 kHz - Frequency Range: 10 - 160 kHz - Interface: USB 2.0, full speed, OTG/host - Connection: Mini-B USB - Anti-Aliasing Filter: 8th order, 160 kHz - Dimensions: 43 mm (1 11/16") x 114 mm (4 31/64") x 13 mm (33/64") - Weight: 60 g Microphone with Sampling Frequency 250 kHz - ADC Resolution: 16 bits - Sensor: MEMS high-sensitivity Surface Mount Wide-band Ultrasonic Acoustic Sensor - Processor: 32 bit 80 MHz integrated microcontroller - Digital Signal Processing: 8th order anti-aliasing low-pass filter - Connection: Mini-B USB - Max Sampling Frequency: 250 kHz - Frequency Range: 0 - 125 kHz - Dimensions: Length 130 mm (5 1/8") x Diam 20 mm (25/32") - Weight: 50 g Select the Microphones Aim To choose the microphones for recording data in the current experiment. Important: Always plug the same microphone into the same USB port. If you purchased a PC together with UltraVox XT, microphones and USB ports are labeled. Always make sure that microphones are plugged into the USB ports with the matching labels. Prerequisites You have created or opened an experiment. See Create a New Experiment. Procedure - Connect the microphones you want to use. Important: When using multiple microphones, always connect each microphone to the same USB port. Label the microphones in such a way that you always know which microphone is connected to which port. - Choose Setup > Experiment Settings. - Click Refresh. - In the Microphone column, click